spatstat/0000755000176200001440000000000014155350602012116 5ustar liggesusersspatstat/NAMESPACE0000644000176200001440000000264414155341545013351 0ustar liggesusers# spatstat NAMESPACE file importFrom(utils, RShowDoc, news, page, read.table) import(spatstat.utils) import(spatstat.data) import(spatstat.geom) import(spatstat.core) import(spatstat.linnet) # no dynamic library # Do not edit the following. # It is generated automatically. # .................................................. # load dynamic library # (native routines are now registered in init.c) # .................................................. # There is no dynamic library # useDynLib(spatstat, .registration=TRUE) # .................................................. # Automatically-generated list of documented objects # .................................................. export("beginner") export("bugfixes") export("foo") export("latest.news") export("plot.foo") export("print.autoexec") export("print.bugtable") export("spatstat.family") # ....... Special cases ........... # ....... End of special cases ... # ......................................... # Automatically generated list of S3 methods # ......................................... S3method("plot", "foo") S3method("print", "autoexec") S3method("print", "bugtable") # ......................................... # Assignment methods # ......................................... # ......................................... # End of methods # ......................................... spatstat/demo/0000755000176200001440000000000014141377564013055 5ustar liggesusersspatstat/demo/spatstat.R0000644000176200001440000005456614141377564015063 0ustar liggesusersif(dev.cur() <= 1) { dd <- getOption("device") if(is.character(dd)) dd <- get(dd) dd() } oldpar <- par(ask = interactive() && dev.interactive(orNone=TRUE)) oldoptions <- options(warn=-1) fanfare <- function(stuff) { plot(c(0,1),c(0,1),type="n",axes=FALSE, xlab="", ylab="") text(0.5,0.5, stuff, cex=2.5) } par(mar=c(1,1,2,1)+0.1) fanfare("Spatstat demonstration") fanfare("I. Types of data") plot(swedishpines, main="Point pattern") plot(demopat, cols=c("green", "blue"), main="Multitype point pattern") plot(longleaf, fg="blue", main="Marked point pattern") plot(finpines, main="Point pattern with multivariate marks") a <- psp(runif(20),runif(20),runif(20),runif(20), window=owin()) plot(a, main="Line segment pattern") marks(a) <- sample(letters[1:4], 20, replace=TRUE) plot(a, main="Multitype line segment pattern") marks(a) <- runif(20) plot(a, main="Marked line segment pattern", style="width") plot(owin(), main="Rectangular window") plot(letterR, main="Polygonal window") plot(as.mask(letterR), main="Binary mask window") Z <- as.im(function(x,y){ sqrt((x - 1)^2 + (y-1)^2)}, square(2)) plot(Z, main="Pixel image") X <- runifpoint(42) plot(dirichlet(X), main="Tessellation") plot(rpoispp3(100), main="Three-dimensional point pattern") plot(simplenet, main="Linear network (linnet)") X <- rpoislpp(20, simplenet) plot(X, main="Point pattern on linear network (lpp)", show.window=FALSE) V <- as.linim(function(x,y,seg,tp){x^2-y^2}, L=simplenet) plot(V, main="Pixel image on a linear network") fanfare("II. Graphics") plot(letterR, col="green", border="red", lwd=2, main="Polygonal window with colour fill") plot(letterR, hatch=TRUE, spacing=0.15, angle=30, main="Polygonal window with line shading") plot(letterR, hatch=TRUE, hatchargs=list(texture=8, spacing=0.12), main="Polygonal window with texture fill") plot(amacrine, chars=c(1,16), main="plot(X, chars = c(1,16))") plot(amacrine, cols=c("red","blue"), chars=16, main="plot(X, cols=c(\"red\", \"blue\"))") opa <- par(mfrow=c(1,2)) plot(longleaf, markscale=0.03, main="markscale=0.03") plot(longleaf, markscale=0.09, main="markscale=0.09") par(opa) plot(longleaf, pch=21, cex=1, bg=colourmap(terrain.colors(128), range=c(0,80)), main="colourmap for numeric mark values") Z <- as.im(function(x,y) { r <- sqrt(x^2+y^2); r * exp(-r) }, owin(c(-5,5),c(-5,5))) plot(Z, main="pixel image: image plot") plot(Z, main="pixel image: image plot (heat colours)", col=heat.colors(256)) plot(Z, main="pixel image: logarithmic colour map", log=TRUE, col=rainbow(128, end=5/6)) contour(Z, main="pixel image: contour plot", axes=FALSE) plot(Z, main="pixel image: image + contour plot") contour(Z, add=TRUE) persp(Z, colmap=terrain.colors(128), shade=0.3, phi=30,theta=100, main="pixel image: perspective plot") ct <- colourmap(rainbow(20), breaks=seq(-1,1,length=21)) plot(ct, main="Colour map for real numbers") ca <- colourmap(rainbow(8), inputs=letters[1:8]) plot(ca, main="Colour map for discrete values") Z <- as.im(nnfun(runifpoint(8))) plot(Z, main="colour image for discrete values") textureplot(Z, main="texture plot for discrete values") W <- owin(c(1,5),c(0,4.5)) Lout <- scaletointerval(distmap(rebound.owin(letterR, W))) Lin <- scaletointerval(distmap(complement.owin(letterR, W))) L <- scaletointerval(eval.im(Lin-Lout)) D <- scaletointerval(density(runifpoint(30, W), adjust=0.3)) X <- scaletointerval(as.im(function(x,y){ x }, W=W)) plot(listof(L=L, D=D, X=X), main="Multiple images") pairs(L, D, X, main="Multiple images: pairs plot") persp(L, colin=D, theta=-24, phi=35, box=FALSE, apron=TRUE, main="Two images:\nperspective + colours", shade=0.4, ltheta=225, lphi=10) plot(rgbim(D,X,L,maxColorValue=1), valuesAreColours=TRUE, main="Three images: RGB display") plot(hsvim(D,L,X), valuesAreColours=TRUE, main="Three images: HSV display") V <- as.linim(function(x,y,seg,tp){(y/1000)^2-(x/1000)^3}, L=domain(chicago)) plot(V, main="Pixel image on a linear network (colour plot)") plot(V, style="w", main="Pixel image on a linear network (width plot)") fanfare("III. Conversion between types") W <- as.owin(chorley) plot(W, "window W") plot(as.mask(W)) plot(as.mask(W, dimyx=1000)) plot(as.im(W, value=3)) plot(as.im(W, value=3, na.replace=0), ribbon=TRUE) plot(as.im(function(x,y) {x^2 + y}, W=square(1)), main="as.im(function(x,y){x^2+y})") V <- delaunay(runifpoint(12)) plot(V, main="Tessellation V") plot(as.im(V, dimyx=256), main="as.im(V)") plot(as.owin(V)) X <- swedishpines plot(X, "point pattern X") plot(as.im(X), col=c("white","red"), ribbon=FALSE, xlab="", ylab="") plot(as.owin(X), add=TRUE) fanfare("IV. Subsetting and splitting data") plot(X, "point pattern X") subset <- 1:20 plot(X[subset], main="subset operation: X[subset]") subwindow <- owin(poly=list(x=c(0,96,96,40,40),y=c(0,0,100,100,50))) plot(X[subwindow], main="subset operation: X[subwindow]") plot(lansing, "Lansing Woods data") plot(split(lansing), main="split operation: split(X)", mar.panel=c(0,0,2,0), hsep=1, pch=3) plot(longleaf, main="Longleaf Pines data") plot(cut(longleaf, breaks=3), main=c("cut operation", "cut(longleaf, breaks=3)")) Z <- dirichlet(runifpoint(16)) X <- runifpoint(100) plot(cut(X,Z), main="points cut by tessellation", leg.side="left") plot(Z, add=TRUE) plot(split(X, Z), main="points split by tessellation", mar.panel=c(0,0,2,2), hsep=1) W <- square(1) X <- as.im(function(x,y){sqrt(x^2+y^2)}, W) Y <- dirichlet(runifpoint(12, W)) plot(split(X,Y), main="image split by tessellation") fanfare("V. Tessellations") plot(quadrats(square(1), nx=5, ny=3)) plot(hextess(square(1), 0.07)) plot(quantess(letterR, "x", 7)) plot(polartess(letterR, nangular=6, radii=(0:4)/2, origin=c(2.8, 1.5)), do.col=TRUE) plot(delaunay(cells)) plot(cells, add=TRUE) plot(dirichlet(cells)) plot(cells, add=TRUE) plot(rpoislinetess(2.5), do.col=TRUE) fanfare("VI. Exploratory data analysis") par(mar=c(3,3,3,2)+0.1) plot(swedishpines, main="Quadrat counts", pch="+") tab <- quadratcount(swedishpines, 4) plot(tab, add=TRUE, lty=2, cex=2, col="blue") par(mar=c(5,3,3,2)+0.1) plot(swedishpines, main="", pch="+") title(main=expression(chi^2 * " test"), cex.main=2) tes <- quadrat.test(swedishpines, 3) tes plot(tes, add=TRUE, col="red", cex=1.5, lty=2, lwd=3) title(sub=paste("p-value =", signif(tes$p.value,3)), cex.sub=1.4) par(mar=c(4,4,3,2)+0.1) tesk <- cdf.test(nztrees, "x") tesk plot(tesk) mur <- lapply(murchison, rescale, s=1000) mur <- lapply(mur, "unitname<-", value="km") X <- mur$gold D <- distfun(mur$faults) plot(X, main="Murchison gold deposits", cols="blue") plot(mur$faults, add=TRUE, col="red") rh <- rhohat(X,D) plot(rh, main="Smoothed rate estimate", xlab="Distance to nearest fault (km)", legend=FALSE) plot(predict(rh), main="predict(rhohat(X,D))") Z <- density(cells, 0.07) plot(Z, main="Kernel smoothed intensity of point pattern") plot(cells, add=TRUE) plot(redwood, main="Redwood data") te <- scan.test(redwood, 0.1, method="poisson") plot(te, main=c("Scan Statistic for redwood data", paste("p-value =", signif(te$p.value,3)))) plot(redwood, add=TRUE) te X <- unique(unmark(shapley)) plot(X, "Shapley galaxy concentration", pch=".") coco <-colourmap(rev(rainbow(128, end=2/3)), range=c(0,1)) pa <- function(i, ...) { if(i == 1) list(chars=c(".", "+"), cols=1:2) else list(size=0.5, pch=16, col=coco) } plot(nnclean(X, k=17), panel.args=pa, mar.panel=c(0,1,1,0), nrows=2, main="Byers-Raftery nearest neighbour cleaning", cex.title=1.2) Y <- sharpen(X, sigma=0.5, edgecorrect=TRUE) plot(Y, main="Choi-Hall data sharpening", pch=".") owpa <- par(mfrow=c(1,2)) W <- grow.rectangle(as.rectangle(letterR), 1) X <- superimpose(runifpoint(300, letterR), runifpoint(50, W), W=W) plot(W, main="clusterset(X, 'm')") plot(clusterset(X, 'marks', fast=TRUE), add=TRUE, chars=c("o", "+"), cols=1:2) plot(letterR, add=TRUE) plot(W, main="clusterset(X, 'd')") plot(clusterset(X, 'domain', exact=FALSE), add=TRUE) plot(letterR, add=TRUE) par(owpa) D <- density(a, sigma=0.05) plot(D, main="Kernel smoothed intensity of line segment pattern") plot(a, add=TRUE) X <- runifpoint(42) plot(dirichlet(X)) plot(X, add=TRUE) plot(delaunay(X)) plot(X, add=TRUE) parsave <- par(mfrow=c(1,1), mar=0.2+c(0,1,3,1)) plot(listof("Longleaf Pines data"=longleaf, "Nearest mark"=nnmark(longleaf), "Kernel smoothing of marks"=Smooth(longleaf,10), "Inverse distance weighted\nsmoothing of marks"=idw(longleaf)), equal.scales=TRUE, halign=TRUE, valign=TRUE, main="", mar.panel=0.2+c(0,0,2,2)) par(parsave) fryplot(cells, main=c("Fry plot","cells data"), pch="+") miplot(longleaf, main="Morishita Index plot", pch=16, col="blue") plot(swedishpines, main="Swedish Pines data") K <- Kest(swedishpines) plot(K, main="K function for Swedish Pines", legendmath=TRUE) en <- envelope(swedishpines, fun=Kest, nsim=10, correction="translate") plot(en, main="Envelopes of K function based on CSR", shade=c("hi", "lo")) pc <- pcf(swedishpines) plot(pc, main="Pair correlation function") plot(swedishpines, main="nearest neighbours") m <- nnwhich(swedishpines) b <- swedishpines[m] arrows(swedishpines$x, swedishpines$y, b$x, b$y, angle=12, length=0.1, col="red") plot(swedishpines %mark% nndist(swedishpines), markscale=1, main="Stienen diagram", legend=FALSE, fg="blue") plot(Gest(swedishpines), main=c("Nearest neighbour distance function G", "Gest(swedishpines)"), legendmath=TRUE) Z <- distmap(swedishpines, dimyx=512) plot(swedishpines$window, main="Distance map") plot(Z, add=TRUE) points(swedishpines) plot(Fest(swedishpines), main=c("Empty space function F", "Fest(swedishpines)"), legendmath=TRUE) W <- rebound.owin(letterR, square(5)) plot(distmap(W), main="Distance map") plot(W, add=TRUE) a <- psp(runif(20),runif(20),runif(20),runif(20), window=owin()) contour(distmap(a), main="Distance map") plot(a, add=TRUE,col="red") plot(Jest(swedishpines), main=c("J-function", "J(r)=(1-G(r))/(1-F(r))")) X <- swedishpines X <- X[sample(1:npoints(X))] Z <- nnfun(X) plot(as.owin(X), main="Nearest neighbour map") plot(Z, add=TRUE) points(X) plot(allstats(swedishpines)) Fig4b <- residualspaper$Fig4b plot(Fig4b, main="Inhomogeneous point pattern") plot(Kinhom(Fig4b), main="Inhomogeneous K-function") plot(pcfinhom(Fig4b, stoyan=0.1), main="Inhomogeneous pair correlation") plot(Ginhom(Fig4b, sigma=0.06), main="Inhomogeneous G-function") plot(Jinhom(Fig4b, sigma=0.06), main="Inhomogeneous J-function") X <- unmark(bronzefilter) plot(X, "Bronze filter data") lam <- predict(ppm(X ~x)) plot(Kscaled(X, lam), xlim=c(0, 1.5), main="Locally-scaled K function") plot(urkiola) plot(split(urkiola), cex=0.5) plot(density(split(urkiola))) contour(density(split(urkiola)), panel.begin=as.owin(urkiola)) plot(relrisk(urkiola), main="Relative risk (cross-validated)") plot(bramblecanes) br <- rescale(bramblecanes) plot(alltypes(br, "K"), mar.panel=c(4,5,2,2)+0.1) ama <- rescale(amacrine) plot(alltypes(ama, Lcross, envelope=TRUE, nsim=9), . - r ~ r, ylim=c(-25, 5)) ponderosa.extra$plotit(main="Ponderosa Pines") L <- localL(ponderosa) pL <- plot(L, lty=1, col=1, legend=FALSE, main=c("neighbourhood density functions", "for Ponderosa Pines"), cex.main=0.8) parsave <- par(mfrow=c(1,2)) ponderosa.extra$plotit() par(pty="s") plot(L, iso007 ~ r, main="point B") par(mar=0.2+c(1,1,3,1)) ponderosa.extra$plotit() L12 <- localL(ponderosa, rvalue=12) P12 <- ponderosa %mark% L12 Z12 <- Smooth(P12, sigma=5, dimyx=128) plot(Z12, col=topo.colors(128), main=c("smoothed", "neighbourhood density"), cex.main=0.8) contour(Z12, add=TRUE) points(ponderosa, pch=16, cex=0.5) plot(amacrine, main="Amacrine cells data", cex.main=0.8) par(pty="s") mkc <- markcorr(amacrine, correction="translate", method="density", kernel="epanechnikov") plot(mkc, main="Mark correlation function", legend=FALSE, cex.main=0.8) par(parsave) par(mar=0.2+c(4,4,3,1)) plot(alltypes(amacrine, markconnect), title="Mark connection functions for amacrine cells") parsave <- par(mfrow=c(1,2)) parspruce2 <- par(mar=0.2+c(0,2,2,0)) plot(spruces, cex.main=0.8, markscale=10) par(pty="s", mar=0.2+c(2,3,2,0)) plot(markcorr(spruces), main="Mark correlation", legendpos="bottomright") par(parspruce2) plot(spruces, cex.main=0.8, markscale=10) par(pty="s", mar=0.2+c(2,3,2,0)) plot(markvario(spruces), main="Mark variogram", legendpos="topright") par(parsave) plot(listof("Emark(spruces)"=Emark(spruces), "Vmark(spruces)"=Vmark(spruces)), main="Independence diagnostics", ylim.covers=0, legendpos="bottom") par3 <- par(mfrow=c(1,2)) X <- rpoispp3(100) plot(X, main="3D point pattern X") plot(K3est(X), main="K-function in 3D") plot(X, main="3D point pattern X") plot(G3est(X), main="G-function in 3D", legendpos="bottomright") par(par3) par(mfrow=c(1,3)) X <- unmark(chicago) plot(X, col="green", cols="red", pch=16, main="Chicago Street Crimes", cex.main=0.75, show.window=FALSE) plot(density(X, 100, distance="e"), main="Kernel density estimate (Euclidean)") plot(density(X, 100, distance="p"), main="Kernel density estimate (shortest path)") plot(X, col="green", cols="red", pch=16, main="Chicago Street Crimes", cex.main=0.75, show.window=FALSE) plot(linearK(X, correction="none"), main="Network K-function", cex.main=0.75) plot(linearK(X, correction="Ang"), main="Corrected K-function", cex.main=0.75) par(mfrow=c(1,1)) fanfare("VII. Model-fitting") parsave <- par(mar=0.2+c(1,1,3,2)) plot(japanesepines) fit <- ppm(japanesepines ~1) print(fit) fit <- ppm(japanesepines ~polynom(x,y,2)) print(fit) plot(fit, how="image", se=FALSE, main=c("Inhomogeneous Poisson model", "fit by maximum likelihood", "Fitted intensity")) plot(fit, how="image", trend=FALSE, main=c("Standard error", "of fitted intensity")) plot(leverage(fit)) plot(influence(fit)) plot(mur$gold, main="Murchison gold deposits", cols="blue") plot(mur$faults, add=TRUE, col="red") fit <- ppm(mur$gold ~D, covariates=list(D=distfun(mur$faults))) par(mar=0.2+c(4,4,4,2)) plot(parres(fit, "D"), main="Partial residuals from loglinear Poisson model", xlab="Distance to nearest fault (km)", ylab="log intensity of gold", legend=FALSE) legend("bottomleft", legend=c("partial residual", "loglinear fit"), col=c(1,4), lty=c(1,4)) par(mar=rep(0.2, 4), mfrow=c(1,1)) fitT <- kppm(redwood ~1, clusters="Thomas") simT <- simulate(fitT)[[1]] plot(listof(redwood, simT), main.panel=c("Redwood", "simulation from\nfitted Thomas model"), main="", mar.panel=0.2, equal.scales=TRUE) mop <- par(mfrow=c(1,2), pty="s", mar=rep(4.4, 4)) plot(fitT, xname=c("Thomas model", "minimum contrast fit"), pause=FALSE) par(mop) oop <- par(pty="s", mar=0.2+c(4,4,4,2)) os <- objsurf(fitT) plot(os, main="Minimum contrast objective function", col=terrain.colors(128)) contour(os, add=TRUE) par(oop) parra <- par(mfrow=c(1,2), mar=0.2+c(3,3,4,2)) plot(swedishpines) fit <- ppm(swedishpines ~1, Strauss(r=7)) print(fit) plot(fit, how="image", main=c("Strauss model", "fit by maximum pseudolikelihood", "Conditional intensity plot")) # fitted interaction plot(swedishpines) fit <- ppm(swedishpines ~1, PairPiece(c(3,5,7,9,11,13))) plot(fitin(fit), legend=FALSE, main=c("Pairwise interaction model", "fit by maximum pseudolikelihood")) # simulation par(mfrow=c(1,1), mar=0.5+c(0,0,2,0)) Xsim <- rmh(model=fit, start=list(n.start=80), control=list(nrep=100)) plot(listof(swedishpines, Xsim), main="", main.panel=c("Swedish Pines", "Simulation from\nfitted Strauss model"), mar.panel=c(0,0,3,0),hsep=1,equal.scales=TRUE) # model compensator par(parra) par(mar=0.2+c(4,4,3,1)) plot(swedishpines) fit <- ppm(swedishpines ~1, Strauss(r=7)) plot(Kcom(fit), cbind(iso, icom, pois) ~ r, legend=FALSE, main="model compensators") legend("topleft", legend=c("empirical K function", "Strauss model compensator of K", "Poisson theoretical K"), lty=1:3, col=1:3, inset=0.05) par(parsave) # Multitype data dpat <- rescale(demopat, 8) unitname(dpat) <- c("mile", "miles") dpat plot(dpat, cols=c("red", "blue")) fit <- ppm(dpat ~marks + polynom(x,y,2), Poisson()) plot(fit, trend=TRUE, se=TRUE) # Linear network data plot(spiders) fit <- lppm(spiders ~ polynom(x,y,2)) anova(fit, test="Chi") (fit <- step(fit)) lam <- predict(fit) plot(lam, main="Point process model on linear network", ribscale=1000) plot(spiders, add=TRUE, pch=16, show.network=FALSE) fanfare("VIII. Simulation") plot(letterR, main="Poisson random points") lambda <- 10/area.owin(letterR) points(rpoispp(lambda, win=letterR)) points(rpoispp(9 * lambda, win=letterR)) points(rpoispp(90 * lambda, win=letterR)) plot(rpoispp(100)) plot(rpoispp(function(x,y){1000 * exp(-3*x)}, 1000), main="rpoispp(function)") plot(rMaternII(200, 0.05)) plot(rSSI(0.05, 200)) plot(rThomas(10, 0.2, 5)) plot(rMatClust(10, 0.05, 4)) plot(rCauchy(30, 0.01, 5)) plot(rVarGamma(30, 2, 0.02, 5)) plot(rGaussPoisson(30, 0.05, 0.5)) if(require(RandomFields) && RandomFieldsSafe()) { X <- rLGCP("exp", 4, var=0.2, scale=0.1) plot(attr(X, "Lambda"), main="log-Gaussian Cox process") plot(X, add=TRUE, pch=16) } plot(rStrauss(200, 0.3, 0.07)) plot(rDiggleGratton(200,0.03,0.08)) plot(rDGS(300, 0.05)) plot(redwood, main="random thinning - rthin()") points(rthin(redwood, 0.5), col="green", cex=1.4) plot(rcell(nx=15)) plot(rsyst(nx=5)) abline(h=(1:4)/5, lty=2) abline(v=(1:4)/5, lty=2) plot(rstrat(nx=5)) abline(h=(1:4)/5, lty=2) abline(v=(1:4)/5, lty=2) X <- rsyst(nx=10) plot(rjitter(X, 0.02)) Xg <- rmh(list(cif="geyer", par=list(beta=1.25, gamma=1.6, r=0.2, sat=4.5), w=c(0,10,0,10)), control=list(nrep=1e4), start=list(n.start=200)) plot(Xg, main=paste("Geyer saturation process\n", "rmh() with cif=\"geyer\"")) L <- as.psp(matrix(runif(20), 5, 4), window=square(1)) plot(L, main="runifpointOnLines(30, L)") plot(runifpointOnLines(30, L), add=TRUE, pch="+") plot(L, main="rpoisppOnLines(3, L)") plot(rpoisppOnLines(3, L), add=TRUE, pch="+") plot(runiflpp(20, simplenet)) plot(rpoislpp(5, simplenet)) plot(rpoisline(10)) plot(rlinegrid(30, 0.1)) spatstat.options(npixel=256) X <- dirichlet(runifpoint(30)) plot(rMosaicSet(X, 0.4), col="green", border=NA) plot(X, add=TRUE) plot(rMosaicField(X, runif)) plot(rMosaicSet(rpoislinetess(3), 0.5), col="green", border=NA, main="Switzer's random set") spatstat.options(npixel=100) plot(Halton(512, c(2,3)), main="quasirandom pattern") plot(Halton(16384, c(2,3)), main="quasirandom pattern", pch=".") fanfare("IX. Geometry") A <- letterR B <- shift(letterR, c(0.2,0.1)) plot(boundingbox(A,B), main="shift", type="n") plot(A, add=TRUE) plot(B, add=TRUE, border="red") B <- rotate(letterR, 0.2) plot(boundingbox(A,B), main="rotate", type="n") plot(A, add=TRUE) plot(B, add=TRUE, border="red") mat <- matrix(c(1.1, 0, 0.3, 1), 2, 2) B <- affine(letterR, mat=mat, vec=c(0.2,-0.1)) plot(boundingbox(A,B), main="affine", type="n") plot(A, add=TRUE) plot(B, add=TRUE, border="red") par1x2 <- par(mfrow=c(1,2)) L <- rpoisline(10, owin(c(1.5,4.5),c(0.2,3.6))) plot(L, main="Line segment pattern") plot(L$window, main="L[window]", type="n") plot(L[letterR], add=TRUE) plot(letterR, add=TRUE, border="red") par(par1x2) a <- psp(runif(20),runif(20),runif(20),runif(20), window=owin()) plot(a, main="Self-crossing points") plot(selfcrossing.psp(a), add=TRUE, col="red") a <- as.psp(matrix(runif(20), 5, 4), window=square(1)) b <- rstrat(square(1), 5) plot(a, lwd=3, col="green", main="project points to segments") plot(b, add=TRUE, col="red", pch=16) v <- project2segment(b, a) Xproj <- v$Xproj plot(Xproj, add=TRUE, pch=16) arrows(b$x, b$y, Xproj$x, Xproj$y, angle=10, length=0.15, col="red") plot(a, main="pointsOnLines(L)") plot(pointsOnLines(a, np=100), add=TRUE, pch="+") parry <- par(mfrow=c(1,3), mar=0.3+c(1,1,3,1)) X <- tess(xgrid=seq(2, 4, length=10), ygrid=seq(0, 3.5, length=8)) plot(X, cex.main=0.75) plot(letterR, cex.main=0.75) plot(intersect.tess(X, letterR), cex.main=0.75) X <- dirichlet(runifpoint(10)) plot(X) L <- infline(0.3,0.5) plot(owin(), main="L", cex.main=0.75) plot(L, col="red", lwd=2, cex.main=0.75) plot(chop.tess(X,L), cex.main=0.75) par(parry) W <- chorley$window plot(W, main="simplify.owin") WS <- simplify.owin(W, 2) plot(WS, add=TRUE, border="green") nopa <- par(mfrow=c(2,2)) Rbox <- grow.rectangle(as.rectangle(letterR), 0.3) v <- erosion.owin(letterR, 0.25) plot(Rbox, type="n", main="erode.owin", cex.main=0.75) plot(letterR, add=TRUE, col="red", cex.main=0.75) plot(v, add=TRUE, col="blue") v <- dilation.owin(letterR, 0.25) plot(Rbox, type="n", main="dilate.owin", cex.main=0.75) plot(v, add=TRUE, col="blue") plot(letterR, add=TRUE, col="red") v <- closing.owin(letterR, 0.3) plot(Rbox, type="n", main="closing.owin", cex.main=0.75) plot(v, add=TRUE, col="blue") plot(letterR, add=TRUE, col="red") v <- opening.owin(letterR, 0.3) plot(Rbox, type="n", main="opening.owin", cex.main=0.75) plot(letterR, add=TRUE, col="red") plot(v, add=TRUE, col="blue") par(nopa) laslett(heather$fine, main="Laslett's Transform") fanfare("X. Operations on pixel images") Z <- distmap(swedishpines, dimyx=512) plot(Z, main="An image Z") plot(levelset(Z, 4)) plot(cut(Z, 5)) plot(eval.im(sqrt(Z) - 3)) plot(solutionset(abs(Z - 6) <= 1)) nopa <- par(mfrow=c(1,2)) plot(Z) segments(0,0,96,100,lwd=2) plot(transect.im(Z)) par(nopa) d <- distmap(cells, dimyx=256) W <- levelset(d, 0.06) nopa <- par(mfrow=c(1,2)) plot(W) plot(connected(W)) par(nopa) Z <- as.im(function(x,y) { 4 * x^2 + 3 * y }, letterR) plot(Z) plot(letterR, add=TRUE) plot(blur(Z, 0.3, bleed=TRUE)) plot(letterR, add=TRUE) plot(blur(Z, 0.3, bleed=FALSE)) plot(letterR, add=TRUE) plot(blur(Z, 0.3, bleed=FALSE)) plot(letterR, add=TRUE) fanfare("XI. Programming tools") showoffK <- function(Y, current, ..., fullpicture,rad) { plot(fullpicture, main=c("Animation using `applynbd'", "explaining the K function")) points(Y, cex=2) u <- current points(u[1],u[2],pch="+",cex=3) theta <- seq(0,2*pi,length=100) polygon(u[1]+ rad * cos(theta),u[2]+rad*sin(theta)) text(u[1]+rad/3,u[2]+rad/2,Y$n,cex=3) if(runif(1) < 0.2) Sys.sleep(runif(1, max=0.4)) return(npoints(Y)) } par(ask=FALSE) applynbd(redwood, R=0.2, showoffK, fullpicture=redwood, rad=0.2, exclude=TRUE) par(oldpar) options(oldoptions) spatstat/demo/data.R0000644000176200001440000000614014141377564014112 0ustar liggesusersif(dev.cur() <= 1) { dd <- getOption("device") if(is.character(dd)) dd <- get(dd) dd() } oldpar <- par(ask = interactive() && dev.interactive(orNone=TRUE)) oldoptions <- options(warn=-1) plot(amacrine) plot(anemones, markscale=1) ants.extra$plotit() plot(austates) plot(bei.extra$elev, main="Beilschmiedia") plot(bei, add=TRUE, pch=16, cex=0.3) plot(betacells) plot(bramblecanes, cols=1:3) plot(split(bramblecanes)) plot(bronzefilter,markscale=2) plot(cells) plot(chicago, main="Chicago Street Crimes", col="grey", cols=c("red", "blue", "black", "blue", "red", "blue", "blue"), chars=c(16,2,22,17,24,15,6), leg.side="left", show.window=FALSE) chorley.extra$plotit() plot(clmfires, which.marks="cause", cols=2:5, cex=0.25, main="Castilla-La Mancha forest fires") plot(clmfires.extra$clmcov200, main="Covariates for forest fires") plot(copper$Points, main="Copper") plot(copper$Lines, add=TRUE) plot(demohyper, quote({ plot(Image, main=""); plot(Points, add=TRUE) }), parargs=list(mar=rep(1,4))) plot(dendrite, leg.side="bottom", main="", cex=0.75, cols=2:4) plot(demopat) plot(finpines, main="Finnish pines") wildM1 <- with(flu, virustype == "wt" & stain == "M2-M1") plot(flu[wildM1, 1, drop=TRUE], main=c("flu data", "wild type virus, M2-M1 stain"), chars=c(16,3), cex=0.4, cols=2:3) plot(gordon, main="People in Gordon Square", pch=16) plot(gorillas, which.marks=1, chars=c(1,3), cols=2:3, main="Gorilla nest sites") plot(hamster, cols=c(2,4)) plot(heather) plot(humberside) plot(hyytiala, cols=2:5) plot(japanesepines) plot(lansing) plot(split(lansing)) plot(longleaf) plot(mucosa, chars=c(1,3), cols=c("red", "green")) plot(mucosa.subwin, add=TRUE, lty=3) plot(murchison, main="Murchison data") plot(murchison$greenstone, main="Murchison data", col="lightgreen") plot(murchison$gold, add=TRUE, pch=3, col="blue") plot(murchison$faults, add=TRUE, col="red") plot(nbfires, use.marks=FALSE, pch=".") plot(split(nbfires), use.marks=FALSE, chars=".") plot(split(nbfires)$"2000", which.marks="fire.type", main=c("New Brunswick fires 2000", "by fire type"), cols=c("blue", "green", "red", "cyan"), leg.side="left") plot(nztrees) plot(trim.rectangle(as.owin(nztrees), c(0,5), 0), add=TRUE, lty=3) plot(osteo[1:10,], tick.marks=FALSE, xlab="", ylab="", zlab="") plot(paracou, cols=2:3, chars=c(16,3)) ponderosa.extra$plotit() pyr <- pyramidal pyr$grp <- abbreviate(pyramidal$group, minlength=7) plot(pyr, quote(plot(Neurons, pch=16, main=grp)), main="Pyramidal Neurons") rm(pyr) plot(redwood) plot(redwood3, add=TRUE, pch=20) redwoodfull.extra$plotit() plot(residualspaper$Fig1) plot(residualspaper$Fig4a) plot(residualspaper$Fig4b) plot(residualspaper$Fig4c) shapley.extra$plotit(main="Shapley") plot(simdat) plot(spiders, pch=16, show.window=FALSE) plot(sporophores, chars=c(16,1,2), cex=0.6) points(0,0,pch=16, cex=2) text(15,8,"Tree", cex=0.75) plot(spruces, maxsize=min(nndist(spruces))) plot(swedishpines) plot(urkiola, cex=0.5, cols=2:3) plot(waka, markscale=0.04, main=c("Waka national park", "tree diameters")) plot(waterstriders) par(oldpar) options(oldoptions) spatstat/demo/sumfun.R0000644000176200001440000000775214141377564014530 0ustar liggesusers## demonstration of all summary functions opa <- par(mfrow=c(1,1), mar=c(0,0,1,0)+0.2) ## Ripley's K-function plot(swedishpines) par(mar=c(4,4,2,1)+0.2) plot(Kest(swedishpines)) ## Besag's transformation plot(Lest(swedishpines)) ## pair correlation function plot(pcf(swedishpines)) par(mfrow=c(2,3), mar=c(0,0,1,0)+0.2) ## Showing the utility of the K-function plot(cells) plot(nztrees) plot(redwood) par(mar=c(4,4,2,1)+0.2) plot(Kest(cells)) plot(Kest(nztrees)) plot(Kest(redwood)) ## Showing the utility of the pair correlation function par(mar=c(0,0,1,0)+0.2) plot(cells) plot(nztrees) plot(redwood) par(mar=c(4,4,2,1)+0.2) plot(pcf(cells)) plot(pcf(nztrees)) plot(pcf(redwood)) ## par(mfrow=c(1,1)) ## Analogues for inhomogeneous patterns ## Reweighted K-function plot(japanesepines) fit <- ppm(japanesepines, ~polynom(x,y,2)) plot(predict(fit)) plot(Kinhom(japanesepines, fit)) plot(pcfinhom(japanesepines, fit)) plot(Linhom(japanesepines)) ## Rescaled K-function plot(unmark(bronzefilter)) plot(Kscaled(bronzefilter)) fit <- ppm(unmark(bronzefilter), ~x) plot(predict(fit)) plot(unmark(bronzefilter), add=TRUE) plot(Kscaled(bronzefilter, fit)) plot(Lscaled(bronzefilter, fit)) ## Local indicators of spatial association plot(localL(swedishpines)) plot(localK(swedishpines)) ## anisotropic plot(Ksector(redwood, 0, 90)) plot(Rf <- pairorient(redwood, 0.05, 0.15)) rose(Rf, main="Rose diagram of pair orientation distribution") plot(deriv(Rf, spar=0.6, Dperiodic=TRUE)) rose(nnorient(redwood)) ## par(mfrow=c(2,3), mar=rep(0.2, 4)) ## Empty space function F plot(cells) plot(nztrees) plot(redwood) par(mar=c(4,4,2,1)+0.2) plot(Fest(cells)) plot(Fest(nztrees)) plot(Fest(redwood)) ## Nearest neighbour distance function G par(mar=rep(0.2, 4)) plot(cells) plot(nztrees) plot(redwood) par(mar=c(4,4,2,1)+0.2) plot(Gest(cells)) plot(Gest(nztrees)) plot(Gest(redwood)) ## J-function par(mar=rep(0.2, 4)) plot(cells) plot(nztrees) plot(redwood) par(mar=c(4,4,2,1)+0.2) plot(Jest(cells)) plot(Jest(nztrees)) plot(Jest(redwood)) par(mfrow=c(1,1), mar=c(4,4,2,1)+0.2) ## versions for inhomogeneous patterns plot(Finhom(japanesepines)) plot(Ginhom(japanesepines)) plot(Jinhom(japanesepines)) ## Display F,G,J,K plot(allstats(swedishpines)) ## Multitype patterns plot(amacrine) plot(Kcross(amacrine)) plot(Kdot(amacrine)) I <- (marks(amacrine) == "on") J <- (marks(amacrine) == "off") plot(Kmulti(amacrine, I, J)) plot(alltypes(amacrine, "K")) plot(Lcross(amacrine)) plot(Ldot(amacrine)) plot(pcfcross(amacrine)) plot(pcfdot(amacrine)) plot(pcfmulti(amacrine, I, J)) plot(Gcross(amacrine)) plot(Gdot(amacrine)) plot(Gmulti(amacrine, I, J)) plot(alltypes(amacrine, "G")) plot(Jcross(amacrine)) plot(Jdot(amacrine)) plot(Jmulti(amacrine,I,J)) plot(alltypes(amacrine, "J")) plot(alltypes(amacrine, "F")) plot(Iest(amacrine)) plot(markconnect(amacrine)) ## Multitype, inhomogeneous plot(Kcross.inhom(amacrine)) plot(Kdot.inhom(amacrine)) plot(Kmulti.inhom(amacrine, I, J)) plot(Lcross.inhom(amacrine)) plot(Ldot.inhom(amacrine)) plot(pcfcross.inhom(amacrine)) plot(pcfdot.inhom(amacrine)) plot(pcfmulti.inhom(amacrine, I, J)) ## Numerical marks plot(markcorr(longleaf)) plot(markvario(longleaf)) plot(Emark(longleaf)) plot(Vmark(longleaf)) ## Linear networks plot(chicago) plot(linearK(chicago)) plot(linearKcross(chicago)) plot(linearKdot(chicago)) plot(linearpcf(chicago)) plot(linearpcfcross(chicago)) plot(linearpcfdot(chicago)) lam <- rep(intensity(unmark(chicago)), npoints(chicago)) A <- split(chicago)$assault B <- split(chicago)$burglary lamA <- rep(intensity(A), npoints(A)) lamB <- rep(intensity(B), npoints(B)) plot(linearKinhom(chicago, lam)) plot(linearKcross.inhom(chicago, "assault", "burglary", lamA, lamB)) plot(linearKdot.inhom(chicago, "assault", lamA, lam)) plot(linearpcfinhom(chicago, lam)) plot(linearpcfcross.inhom(chicago, "assault", "burglary", lamA, lamB)) plot(linearpcfdot.inhom(chicago, "assault", lamA, lam)) plot(linearmarkconnect(chicago)) plot(linearmarkequal(chicago)) rm(I,J,fit) par(opa) spatstat/demo/00Index0000755000176200001440000000032414141377564014211 0ustar liggesusersspatstat Demonstration of spatstat library diagnose Demonstration of diagnostic capabilities for models in spatstat data Datasets in spatstat sumfun Demonstration of nonparametric summary functions in spatstat spatstat/demo/diagnose.R0000644000176200001440000001230014141377564014765 0ustar liggesusersif(dev.cur() <= 1) { dd <- getOption("device") if(is.character(dd)) dd <- get(dd) dd() } oldpar <- par(ask = interactive() && (.Device %in% c("X11", "GTK", "windows", "Macintosh"))) par(mfrow=c(1,1)) oldoptions <- options(warn = -1) # ####################################################### # X <- rpoispp(function(x,y) { 1000 * exp(- 4 * x)}, 1000) plot(X, main="Inhomogeneous Poisson pattern") fit.hom <- ppm(X ~1, Poisson()) fit.inhom <- ppm(X ~x, Poisson()) diagnose.ppm(fit.inhom, which="marks", type="Pearson", main=c("Mark plot", "Circles for positive residual mass", "Colour for negative residual density")) par(mfrow=c(1,2)) diagnose.ppm(fit.hom, which="marks", main=c("Wrong model", "(homogeneous Poisson)", "raw residuals")) diagnose.ppm(fit.inhom, which="marks", main=c("Right model", "(inhomogeneous Poisson)", "raw residuals")) par(mfrow=c(1,1)) diagnose.ppm(fit.inhom, which="smooth", main="Smoothed residual field") par(mfrow=c(1,2)) diagnose.ppm(fit.hom, which="smooth", main=c("Wrong model", "(homogeneous Poisson)", "Smoothed residual field")) diagnose.ppm(fit.inhom, which="smooth", main=c("Right model", "(inhomogeneous Poisson)", "Smoothed residual field")) par(mfrow=c(1,1)) diagnose.ppm(fit.inhom, which="x") par(mfrow=c(1,2)) diagnose.ppm(fit.hom, which="x", main=c("Wrong model", "(homogeneous Poisson)", "lurking variable plot for x")) diagnose.ppm(fit.inhom, which="x", main=c("Right model", "(inhomogeneous Poisson)", "lurking variable plot for x")) par(mfrow=c(1,1)) diagnose.ppm(fit.hom, type="Pearson",main="standard diagnostic plots") par(mfrow=c(1,2)) diagnose.ppm(fit.hom, main=c("Wrong model", "(homogeneous Poisson)")) diagnose.ppm(fit.inhom, main=c("Right model", "(inhomogeneous Poisson)")) par(mfrow=c(1,1)) # ####################################################### # LEVERAGE/INFLUENCE plot(leverage(fit.inhom)) plot(influence(fit.inhom)) plot(dfbetas(fit.inhom)) # ####################################################### # COMPENSATORS ## Takes a long time... CF <- compareFit(listof(hom=fit.hom, inhom=fit.inhom), Kcom, same="iso", different="icom") plot(CF, main="model compensators", legend=FALSE) legend("topleft", legend=c("empirical K function", "compensator of CSR", "compensator of inhomogeneous Poisson"), lty=1:3, col=1:3) # ####################################################### # Q - Q PLOTS # qqplot.ppm(fit.hom, 40) #conclusion: homogeneous Poisson model is not correct title(main="Q-Q plot of smoothed residuals") qqplot.ppm(fit.inhom, 40) # TAKES A WHILE... title(main=c("Right model", "(inhomogeneous Poisson)", "Q-Q plot of smoothed residuals")) # conclusion: fitted inhomogeneous Poisson model looks OK # ####################################################### # plot(cells) fitPoisson <- ppm(cells ~1, Poisson()) diagnose.ppm(fitPoisson, main=c("CSR fitted to cells data", "Raw residuals", "No suggestion of departure from CSR")) diagnose.ppm(fitPoisson, type="pearson", main=c("CSR fitted to cells data", "Pearson residuals", "No suggestion of departure from CSR")) # These diagnostic plots do NOT show evidence of departure from uniform Poisson plot(Kcom(fitPoisson), cbind(iso, icom) ~ r) plot(Gcom(fitPoisson), cbind(han, hcom) ~ r) # K compensator DOES show strong evidence of departure from uniform Poisson qqplot.ppm(fitPoisson, 40) title(main=c("CSR fitted to cells data", "Q-Q plot of smoothed raw residuals", "Strong suggestion of departure from CSR")) # Q-Q plot DOES show strong evidence of departure from uniform Poisson. # fitStrauss <- ppm(cells ~1, Strauss(r=0.1)) diagnose.ppm(fitStrauss, main=c("Strauss model fitted to cells data", "Raw residuals")) diagnose.ppm(fitStrauss, type="pearson", main=c("Strauss model fitted to cells data", "Pearson residuals")) plot(Kcom(fitStrauss), cbind(iso, icom) ~ r) plot(Gcom(fitStrauss), cbind(han, hcom) ~ r) # next line takes a LOOONG time ... qqplot.ppm(fitStrauss, 40, type="pearson") title(main=c("Strauss model fitted to cells data", "Q-Q plot of smoothed Pearson residuals", "Suggests adequate fit")) # Conclusion: Strauss model seems OK # ####################################################### # plot(nztrees) fit <- ppm(nztrees ~1, Poisson()) diagnose.ppm(fit, type="pearson") title(main=c("CSR fitted to NZ trees", "Pearson residuals")) diagnose.ppm(fit, type="pearson", cumulative=FALSE) title(main=c("CSR fitted to NZ trees", "Pearson residuals (non-cumulative)")) lurking(fit, expression(x), type="pearson", cumulative=FALSE, splineargs=list(spar=0.3)) # Sharp peak at right is suspicious qqplot.ppm(fit, 40, type="pearson") title(main=c("CSR fitted to NZ trees", "Q-Q plot of smoothed Pearson residuals")) # Slight suggestion of departure from Poisson at top right of pattern. par(oldpar) options(oldoptions) spatstat/man/0000755000176200001440000000000014141460522012667 5ustar liggesusersspatstat/man/foo.Rd0000644000176200001440000000237314141460522013746 0ustar liggesusers\name{foo} \alias{foo} \alias{plot.foo} \title{ Foo is Not a Real Name } \description{ The name \code{foo} is not a real name: it is a place holder, used to represent the name of any desired thing. The functions defined here simply print an explanation of the placeholder name \code{foo}. } \usage{ foo() \method{plot}{foo}(x, \dots) } \arguments{ \item{x}{Ignored.} \item{\dots}{Ignored.} } \details{ The name \code{foo} is used by computer scientists as a \emph{place holder}, to represent the name of any desired object or function. It is not the name of an actual object or function; it serves only as an example, to explain a concept. However, many users misinterpret this convention, and actually type the command \code{foo} or \code{foo()}. Then they email the package author to inform them that \code{foo} is not defined. To avoid this correspondence, we have now defined an object called \code{foo}. The function \code{foo()} prints a message explaining that \code{foo} is not really the name of a variable. The function can be executed simply by typing \code{foo} without parentheses. } \value{ Null. } \author{ \spatstatAuthors. } \seealso{ \code{\link{beginner}} } \examples{ foo } \keyword{documentation} spatstat/man/spatstat.family.Rd0000644000176200001440000000264414141460522016307 0ustar liggesusers\name{spatstat.family} \alias{spatstat.family} \title{Names of All Packages in the Spatstat Family} \description{ Provides the names of all the packages belonging to the \pkg{spatstat} family of packages. } \usage{ spatstat.family(subpackages=TRUE, extensions=FALSE) } \arguments{ \item{subpackages}{ Logical value specifying whether to include sub-packages. } \item{extensions}{ Logical value specifying whether to include extension packages. } } \value{ Character vector of package names. } \details{ This function returns a character vector containing the names of the packages that belong to the \pkg{spatstat} family. By default, only the sub-packages are listed, and not the extension packages. A \dQuote{sub-package} is a package which is implicitly loaded or imported when the command \code{library(spatstat)} is issued. Currently the sub-packages are: \itemize{ \item \code{spatstat.utils} \item \code{spatstat.data} \item \code{spatstat.sparse} \item \code{spatstat.geom} \item \code{spatstat.core} \item \code{spatstat.linnet} \item \code{spatstat} } An \dQuote{extension package} is a package which must be loaded explicitly. The extension packages are: \itemize{ \item \code{spatstat.gui} \item \code{spatstat.local} \item \code{spatstat.Knet} } } \seealso{ \code{\link{latest.news}} } \author{ \spatstatAuthors. } \keyword{spatial} spatstat/man/bugfixes.Rd0000644000176200001440000000530114155341545015001 0ustar liggesusers\name{bugfixes} \alias{bugfixes} \title{ List Recent Bug Fixes } \description{ List all bug fixes in a package, starting from a certain date or version of the package. Fixes are sorted alphabetically by the name of the affected function. The default is to list bug fixes in the latest version of the \pkg{spatstat} family of packages. } \usage{ bugfixes(sinceversion = NULL, sincedate = NULL, package = spatstat.family(), show = TRUE) } \arguments{ \item{sinceversion}{ Earliest version of \code{package} for which bugs should be listed. The default is the current installed version. } \item{sincedate}{ Earliest release date of \code{package} for which bugs should be listed. A character string or a date-time object. } \item{package}{ The name of the package (or packages) for which bugs are to be listed. A character string or character vector. } \item{show}{ Logical value indicating whether to display the bug table on the terminal. } } \details{ Bug reports are extracted from the NEWS file of the specified \code{package}. Only those after a specified date, or after a specified version of the package, are retained. The bug reports are then sorted alphabetically, so that all bugs affecting a particular function are listed consecutively. Finally the table of bug reports is displayed (if \code{show=TRUE}) and returned invisibly. The argument \code{sinceversion} should be a character string like \code{"1.2-3"}. The default is the current installed version of the package. The argument \code{sincedate} should be a character string like \code{"2015-05-27"}, or a date-time object. If \code{sinceversion="all"} or \code{sincedate="all"} then all recorded bugs will be listed. The special options \code{sinceversion="book"} and \code{sincedate="book"} are interpreted to mean \code{sincedate="2015-06-05"}, which gives all bugs reported after publication of the book by Baddeley, Rubak and Turner (2015). Typing \code{bugfixes} without parentheses will display a table of all bugs that were fixed in the current installed version of \pkg{spatstat} and its sub-packages. } \value{ (Invisibly) a data frame, belonging to the class \code{"bugtable"}, which has a \code{print} method. } \author{ \adrian. } \seealso{ \code{\link{latest.news}}, \code{\link[utils]{news}}. } \references{ Baddeley, A., Rubak, E. and Turner, R. (2015) \emph{Spatial Point Patterns: Methodology and Applications with R}. Chapman and Hall/CRC Press. } \examples{ bugfixes ## show all bugs reported after publication of the spatstat book if(interactive()) bugfixes(sinceversion="book") } \keyword{documentation} spatstat/man/macros/0000755000176200001440000000000014141377564014170 5ustar liggesusersspatstat/man/macros/defns.Rd0000755000176200001440000000432014141377564015560 0ustar liggesusers%% macro definitions for spatstat man pages \newcommand{\adrian}{Adrian Baddeley \email{Adrian.Baddeley@curtin.edu.au}} \newcommand{\rolf}{Rolf Turner \email{r.turner@auckland.ac.nz}} \newcommand{\ege}{Ege Rubak \email{rubak@math.aau.dk}} \newcommand{\spatstatAuthors}{\adrian, \rolf and \ege} % Names with accents \newcommand{\Bogsted}{\ifelse{latex}{\out{B\o gsted}}{Bogsted}} \newcommand{\Cramer}{\ifelse{latex}{\out{Cram\'er}}{Cramer}} \newcommand{\Hogmander}{\ifelse{latex}{\out{H{\"o}gmander}}{Hogmander}} \newcommand{\Jyvaskyla}{\ifelse{latex}{\out{Jyv\"askyl\"a}}{Jyvaskyla}} \newcommand{\Matern}{\ifelse{latex}{\out{Mat\'ern}}{Matern}} \newcommand{\Moller}{\ifelse{latex}{\out{M\o ller}}{Moller}} \newcommand{\Oehlschlaegel}{\ifelse{latex}{\out{Oehlschl\"{a}gel}}{Oehlschlaegel}} \newcommand{\Prokesova}{\ifelse{latex}{\out{Proke\u{s}ov{\'{a}}}}{Prokesova}} \newcommand{\Sarkka}{\ifelse{latex}{\out{S\"{a}rkk\"{a}}}{Sarkka}} %% List of all Gibbs interactions \newcommand{\GibbsInteractionsList}{\code{\link{AreaInter}}, \code{\link{BadGey}}, \code{\link{Concom}}, \code{\link{DiggleGatesStibbard}}, \code{\link{DiggleGratton}}, \code{\link{Fiksel}}, \code{\link{Geyer}}, \code{\link{Hardcore}}, \code{\link{HierHard}}, \code{\link{HierStrauss}}, \code{\link{HierStraussHard}}, \code{\link{Hybrid}}, \code{\link{LennardJones}}, \code{\link{MultiHard}}, \code{\link{MultiStrauss}}, \code{\link{MultiStraussHard}}, \code{\link{OrdThresh}}, \code{\link{Ord}}, \code{\link{Pairwise}}, \code{\link{PairPiece}}, \code{\link{Penttinen}}, \code{\link{Poisson}}, \code{\link{Saturated}}, \code{\link{SatPiece}}, \code{\link{Softcore}}, \code{\link{Strauss}}, \code{\link{StraussHard}} and \code{\link{Triplets}}} %% List of interactions recognised by RMH code \newcommand{\rmhInteractionsList}{\code{\link{AreaInter}}, \code{\link{BadGey}}, \code{\link{DiggleGatesStibbard}}, \code{\link{DiggleGratton}}, \code{\link{Fiksel}}, \code{\link{Geyer}}, \code{\link{Hardcore}}, \code{\link{Hybrid}}, \code{\link{LennardJones}}, \code{\link{MultiStrauss}}, \code{\link{MultiStraussHard}}, \code{\link{PairPiece}}, \code{\link{Penttinen}}, \code{\link{Poisson}}, \code{\link{Softcore}}, \code{\link{Strauss}}, \code{\link{StraussHard}} and \code{\link{Triplets}}} spatstat/man/spatstat-internal.Rd0000644000176200001440000000107714144335731016646 0ustar liggesusers\name{spatstat-internal} \title{Internal spatstat functions} \alias{print.autoexec} \alias{print.bugtable} %%%%%%% \description{ Internal spatstat functions. } \usage{ \method{print}{autoexec}(x, \dots) \method{print}{bugtable}(x, \dots) } \details{ These internal \pkg{spatstat} functions should not be called directly by the user. Their names and capabilities may change without warning from one version of \pkg{spatstat} to the next. } \value{ The return values of these functions are not documented, and may change without warning. } \keyword{internal} spatstat/man/latest.news.Rd0000644000176200001440000000417514141460522015434 0ustar liggesusers\name{latest.news} \alias{latest.news} \title{ Print News About Latest Version of Package } \description{ Prints the news documentation for the current version of \code{spatstat} or another specified package. } \usage{ latest.news(package = spatstat.family(), doBrowse=FALSE, major=TRUE) } \arguments{ \item{package}{ Name of package for which the latest news should be printed. A character string, or vector of character strings. } \item{doBrowse}{ Logical value indicating whether to display the results in a browser window instead of printing them. } \item{major}{ Logical value. If \code{TRUE} (the default), print all information for the current major version \code{"x.y"}. If \code{FALSE}, print only the information for the current minor version \code{"x.y-z"}. } } \details{ This function prints the news documentation about changes in the current installed version of a package. By default, it prints the latest news about all the sub-packages in the \pkg{spatstat} family. The function can be called simply by typing its name without parentheses (see the Examples). If \code{major=FALSE}, only information for the current minor version \code{"x.y-z"} will be printed. If \code{major=TRUE} (the default), all information for the current major version \code{"x.y"} will be printed, encompassing versions \code{"x.y-0"}, \code{"x.y-1"}, up to \code{"x.y-z"}. If \code{package} is given, then the function reads the news for the specified package from its \code{NEWS} file (if it has one) and prints only the entries that refer to the current version of the package. To see the news for all previous versions as well as the current version, use the \R utility \code{\link[utils]{news}}. See the Examples. } \value{ Null. } \author{ \spatstatAuthors. } \seealso{ \code{\link{spatstat.family}} lists the packages in the \pkg{spatstat} family. \code{\link{bugfixes}} lists bug fixes. \code{\link[utils]{news}} } \examples{ if(interactive()) { # current news latest.news # all news # news(package="spatstat") } } \keyword{documentation} spatstat/man/beginner.Rd0000644000176200001440000000142414141460522014750 0ustar liggesusers\name{beginner} \alias{beginner} \title{ Print Introduction For Beginners } \description{ Prints an introduction for beginners to the \code{spatstat} package, or another specified package. } \usage{ beginner(package = "spatstat") } \arguments{ \item{package}{ Name of package. } } \details{ This function prints an introduction for beginners to the \pkg{spatstat} package. The function can be executed simply by typing \code{beginner} without parentheses. If the argument \code{package} is given, then the function prints the beginner's help file \code{BEGINNER.txt} from the specified package (if it has one). } \value{ Null. } \author{\adrian and \rolf } \seealso{ \code{\link{latest.news}} } \examples{ beginner } \keyword{documentation} spatstat/man/spatstat-package.Rd0000644000176200001440000027505014144335731016431 0ustar liggesusers\name{spatstat-package} \alias{spatstat-package} \alias{spatstat} \docType{package} \title{The Spatstat Package} \description{ This is a summary of the features of \pkg{spatstat}, a family of \R packages for the statistical analysis of spatial point patterns. } \details{ \pkg{spatstat} is a family of \R packages for the statistical analysis of spatial data. Its main focus is the analysis of spatial patterns of points in two-dimensional space. \pkg{spatstat} is designed to support a complete statistical analysis of spatial data. It supports \itemize{ \item creation, manipulation and plotting of point patterns; \item exploratory data analysis; \item spatial random sampling; \item simulation of point process models; \item parametric model-fitting; \item non-parametric smoothing and regression; \item formal inference (hypothesis tests, confidence intervals); \item model diagnostics. } Apart from two-dimensional point patterns and point processes, \pkg{spatstat} also supports point patterns in three dimensions, point patterns in multidimensional space-time, point patterns on a linear network, patterns of line segments in two dimensions, and spatial tessellations and random sets in two dimensions. The package can fit several types of point process models to a point pattern dataset: \itemize{ \item Poisson point process models (by Berman-Turner approximate maximum likelihood or by spatial logistic regression) \item Gibbs/Markov point process models (by Baddeley-Turner approximate maximum pseudolikelihood, Coeurjolly-Rubak logistic likelihood, or Huang-Ogata approximate maximum likelihood) \item Cox/cluster point process models (by Waagepetersen's two-step fitting procedure and minimum contrast, composite likelihood, or Palm likelihood) \item determinantal point process models (by Waagepetersen's two-step fitting procedure and minimum contrast, composite likelihood, or Palm likelihood) } The models may include spatial trend, dependence on covariates, and complicated interpoint interactions. Models are specified by a \code{formula} in the \R language, and are fitted using a function analogous to \code{\link[stats]{lm}} and \code{\link[stats]{glm}}. Fitted models can be printed, plotted, predicted, simulated and so on. } \section{Getting Started}{ For a quick introduction to \pkg{spatstat}, read the package vignette \emph{Getting started with spatstat} installed with \pkg{spatstat}. To read that document, you can either \itemize{ \item visit \url{https://cran.r-project.org/package=spatstat} and click on \code{Getting Started with Spatstat} \item start \R, type \code{library(spatstat)} and \code{vignette('getstart')} \item start \R, type \code{help.start()} to open the help browser, and navigate to \code{Packages > spatstat > Vignettes}. } Once you have installed \pkg{spatstat}, start \R and type \code{library(spatstat)}. Then type \code{beginner} for a beginner's introduction, or \code{demo(spatstat)} for a demonstration of the package's capabilities. For a complete course on \pkg{spatstat}, and on statistical analysis of spatial point patterns, read the book by Baddeley, Rubak and Turner (2015). Other recommended books on spatial point process methods are Diggle (2014), Gelfand et al (2010) and Illian et al (2008). The \pkg{spatstat} package includes over 50 datasets, which can be useful when learning the package. Type \code{demo(data)} to see plots of all datasets available in the package. Type \code{vignette('datasets')} for detailed background information on these datasets, and plots of each dataset. For information on converting your data into \pkg{spatstat} format, read Chapter 3 of Baddeley, Rubak and Turner (2015). This chapter is available free online, as one of the sample chapters at the book companion website, \url{https://book.spatstat.org/}. For information about handling data in \bold{shapefiles}, see Chapter 3, or the Vignette \emph{Handling shapefiles in the spatstat package}, installed with \pkg{spatstat}, accessible as \code{vignette('shapefiles')}. } \section{Structure of the spatstat family}{ The original \pkg{spatstat} package grew to be very large. It has now been divided into several \bold{sub-packages}: \itemize{ \item \pkg{spatstat.utils} containing basic utilities \item \pkg{spatstat.sparse} containing linear algebra utilities \item \pkg{spatstat.data} containing datasets \item \pkg{spatstat.geom} containing functionality for geometrical operations, and defining the main classes of spatial objects \item \pkg{spatstat.core} containing the main functions for statistical analysis and modelling of spatial data \item \pkg{spatstat.linnet} containing functions for spatial data on a linear network \item \pkg{spatstat}, which simply loads the other sub-packages listed above, and provides documentation. } The breakup has been done in such a way that the user should not notice any difference. Source code that worked with the old \pkg{spatstat} package should work with the new \pkg{spatstat} family. Code that is documented in our books, journal articles and vignettes should still work. When you install \pkg{spatstat}, the sub-packages listed above are also installed. Then if you load the \pkg{spatstat} package by typing \code{library(spatstat)}, the other sub-packages listed above will automatically be loaded or imported. This help file covers all the functionality and datasets that are provided in the sub-packages listed above. } \section{Extension packages}{ Additionally there are several \bold{extension packages:} \itemize{ \item \pkg{spatstat.gui} for interactive graphics \item \pkg{spatstat.local} for local likelihood (including geographically weighted regression) \item \pkg{spatstat.Knet} for additional, computationally efficient code for linear networks \item \pkg{spatstat.sphere} (under development) for spatial data on a sphere, including spatial data on the earth's surface } The extension packages must be installed separately and loaded explicitly if needed. They also have separate documentation. } \section{Updates}{ New versions of \pkg{spatstat} are released every 8 weeks. Users are advised to update their installation of \pkg{spatstat} regularly. Type \code{latest.news} to read the news documentation about changes to the current installed version of \pkg{spatstat}. See the Vignette \emph{Summary of recent updates}, installed with \pkg{spatstat}, which describes the main changes to \pkg{spatstat} since the book (Baddeley, Rubak and Turner, 2015) was published. It is accessible as \code{vignette('updates')}. Type \code{news(package="spatstat")} to read news documentation about all previous versions of the package. } \section{FUNCTIONS AND DATASETS}{ Following is a summary of the main functions and datasets in the \pkg{spatstat} package. Alternatively an alphabetical list of all functions and datasets is available by typing \code{library(help=spatstat)}. For further information on any of these, type \code{help(name)} or \code{?name} where \code{name} is the name of the function or dataset. } \section{CONTENTS:}{ \tabular{ll}{ I. \tab Creating and manipulating data \cr II. \tab Exploratory Data Analysis \cr III. \tab Model fitting (Cox and cluster models) \cr IV. \tab Model fitting (Poisson and Gibbs models) \cr V. \tab Model fitting (determinantal point processes)\cr VI. \tab Model fitting (spatial logistic regression)\cr VII. \tab Simulation \cr VIII. \tab Tests and diagnostics\cr IX. \tab Documentation } } \section{I. CREATING AND MANIPULATING DATA}{ \bold{Types of spatial data:} The main types of spatial data supported by \pkg{spatstat} are: \tabular{ll}{ \code{\link[spatstat.geom]{ppp}} \tab point pattern \cr \code{\link[spatstat.geom]{owin}} \tab window (spatial region) \cr \code{\link[spatstat.geom]{im}} \tab pixel image \cr \code{\link[spatstat.geom]{psp}} \tab line segment pattern \cr \code{\link[spatstat.geom]{tess}} \tab tessellation \cr \code{\link[spatstat.geom]{pp3}} \tab three-dimensional point pattern \cr \code{\link[spatstat.geom]{ppx}} \tab point pattern in any number of dimensions \cr \code{\link[spatstat.linnet]{lpp}} \tab point pattern on a linear network } \bold{To create a point pattern:} \tabular{ll}{ \code{\link[spatstat.geom]{ppp}} \tab create a point pattern from \eqn{(x,y)} and window information \cr \tab \code{ppp(x, y, xlim, ylim)} for rectangular window\cr \tab \code{ppp(x, y, poly)} for polygonal window \cr \tab \code{ppp(x, y, mask)} for binary image window \cr \code{\link[spatstat.geom]{as.ppp}} \tab convert other types of data to a \code{ppp} object \cr \code{\link[spatstat.geom]{clickppp}} \tab interactively add points to a plot \cr \code{\link[spatstat.geom]{marks<-}}, \code{\%mark\%} \tab attach/reassign marks to a point pattern } \bold{To simulate a random point pattern:} \tabular{ll}{ \code{\link[spatstat.core]{runifpoint}} \tab generate \eqn{n} independent uniform random points \cr \code{\link[spatstat.core]{rpoint}} \tab generate \eqn{n} independent random points \cr \code{\link[spatstat.core]{rmpoint}} \tab generate \eqn{n} independent multitype random points \cr \code{\link[spatstat.core]{rpoispp}} \tab simulate the (in)homogeneous Poisson point process \cr \code{\link[spatstat.core]{rmpoispp}} \tab simulate the (in)homogeneous multitype Poisson point process \cr \code{\link[spatstat.core]{runifdisc}} \tab generate \eqn{n} independent uniform random points in disc\cr \code{\link[spatstat.core]{rstrat}} \tab stratified random sample of points \cr \code{\link[spatstat.geom]{rsyst}} \tab systematic random sample of points \cr \code{\link[spatstat.geom]{rjitter}} \tab apply random displacements to points in a pattern\cr \code{\link[spatstat.core]{rMaternI}} \tab simulate the \Matern Model I inhibition process\cr \code{\link[spatstat.core]{rMaternII}} \tab simulate the \Matern Model II inhibition process\cr \code{\link[spatstat.core]{rSSI}} \tab simulate Simple Sequential Inhibition process\cr \code{\link[spatstat.core]{rStrauss}} \tab simulate Strauss process (perfect simulation)\cr \code{\link[spatstat.core]{rHardcore}} \tab simulate Hard Core process (perfect simulation)\cr \code{\link[spatstat.core]{rStraussHard}} \tab simulate Strauss-hard core process (perfect simulation)\cr \code{\link[spatstat.core]{rDiggleGratton}} \tab simulate Diggle-Gratton process (perfect simulation)\cr \code{\link[spatstat.core]{rDGS}} \tab simulate Diggle-Gates-Stibbard process (perfect simulation)\cr \code{\link[spatstat.core]{rPenttinen}} \tab simulate Penttinen process (perfect simulation)\cr \code{\link[spatstat.core]{rNeymanScott}} \tab simulate a general Neyman-Scott process\cr \code{\link[spatstat.core]{rPoissonCluster}} \tab simulate a general Poisson cluster process\cr \code{\link[spatstat.core]{rMatClust}} \tab simulate the \Matern Cluster process\cr \code{\link[spatstat.core]{rThomas}} \tab simulate the Thomas process \cr \code{\link[spatstat.core]{rGaussPoisson}} \tab simulate the Gauss-Poisson cluster process\cr \code{\link[spatstat.core]{rCauchy}} \tab simulate Neyman-Scott Cauchy cluster process \cr \code{\link[spatstat.core]{rVarGamma}} \tab simulate Neyman-Scott Variance Gamma cluster process \cr \code{\link[spatstat.core]{rthin}} \tab random thinning \cr \code{\link[spatstat.core]{rcell}} \tab simulate the Baddeley-Silverman cell process \cr \code{\link[spatstat.core]{rmh}} \tab simulate Gibbs point process using Metropolis-Hastings \cr \code{\link[spatstat.core]{simulate.ppm}} \tab simulate Gibbs point process using Metropolis-Hastings \cr \code{\link[spatstat.core]{runifpointOnLines}} \tab generate \eqn{n} random points along specified line segments \cr \code{\link[spatstat.core]{rpoisppOnLines}} \tab generate Poisson random points along specified line segments } \bold{To randomly change an existing point pattern:} \tabular{ll}{ \code{\link[spatstat.core]{rshift}} \tab random shifting of points \cr \code{\link[spatstat.geom]{rjitter}} \tab apply random displacements to points in a pattern\cr \code{\link[spatstat.core]{rthin}} \tab random thinning \cr \code{\link[spatstat.core]{rlabel}} \tab random (re)labelling of a multitype point pattern \cr \code{\link[spatstat.core]{quadratresample}} \tab block resampling } \bold{Standard point pattern datasets:} Datasets in \pkg{spatstat} are lazy-loaded, so you can simply type the name of the dataset to use it; there is no need to type \code{\link[utils]{data}(amacrine)} etc. Type \code{demo(data)} to see a display of all the datasets installed with the package. Type \code{vignette('datasets')} for a document giving an overview of all datasets, including background information, and plots. \tabular{ll}{ \code{\link[spatstat.data]{amacrine}} \tab Austin Hughes' rabbit amacrine cells \cr \code{\link[spatstat.data]{anemones}} \tab Upton-Fingleton sea anemones data\cr \code{\link[spatstat.data]{ants}} \tab Harkness-Isham ant nests data\cr \code{\link[spatstat.data]{bdspots}} \tab Breakdown spots in microelectrodes \cr \code{\link[spatstat.data]{bei}} \tab Tropical rainforest trees \cr \code{\link[spatstat.data]{betacells}} \tab Waessle et al. cat retinal ganglia data \cr \code{\link[spatstat.data]{bramblecanes}} \tab Bramble Canes data \cr \code{\link[spatstat.data]{bronzefilter}} \tab Bronze Filter Section data \cr \code{\link[spatstat.data]{cells}} \tab Crick-Ripley biological cells data \cr \code{\link[spatstat.data]{chicago}} \tab Chicago crimes \cr \code{\link[spatstat.data]{chorley}} \tab Chorley-Ribble cancer data \cr \code{\link[spatstat.data]{clmfires}} \tab Castilla-La Mancha forest fires \cr \code{\link[spatstat.data]{copper}} \tab Berman-Huntington copper deposits data \cr \code{\link[spatstat.data]{dendrite}} \tab Dendritic spines \cr \code{\link[spatstat.data]{demohyper}} \tab Synthetic point patterns\cr \code{\link[spatstat.data]{demopat}} \tab Synthetic point pattern \cr \code{\link[spatstat.data]{finpines}} \tab Finnish Pines data \cr \code{\link[spatstat.data]{flu}} \tab Influenza virus proteins \cr \code{\link[spatstat.data]{gordon}} \tab People in Gordon Square, London \cr \code{\link[spatstat.data]{gorillas}} \tab Gorilla nest sites \cr \code{\link[spatstat.data]{hamster}} \tab Aherne's hamster tumour data \cr \code{\link[spatstat.data]{humberside}} \tab North Humberside childhood leukaemia data \cr \code{\link[spatstat.data]{hyytiala}} \tab {Mixed forest in \ifelse{latex}{\out{Hyyti{\"a}l{\"a}}}{Hyytiala}, Finland}\cr \code{\link[spatstat.data]{japanesepines}} \tab Japanese Pines data \cr \code{\link[spatstat.data]{lansing}} \tab Lansing Woods data \cr \code{\link[spatstat.data]{longleaf}} \tab Longleaf Pines data \cr \code{\link[spatstat.data]{mucosa}} \tab Cells in gastric mucosa \cr \code{\link[spatstat.data]{murchison}} \tab Murchison gold deposits \cr \code{\link[spatstat.data]{nbfires}} \tab New Brunswick fires data \cr \code{\link[spatstat.data]{nztrees}} \tab Mark-Esler-Ripley trees data \cr \code{\link[spatstat.data]{osteo}} \tab Osteocyte lacunae (3D, replicated) \cr \code{\link[spatstat.data]{paracou}} \tab Kimboto trees in Paracou, French Guiana \cr \code{\link[spatstat.data]{ponderosa}} \tab Getis-Franklin ponderosa pine trees data \cr \code{\link[spatstat.data]{pyramidal}} \tab Pyramidal neurons from 31 brains \cr \code{\link[spatstat.data]{redwood}} \tab Strauss-Ripley redwood saplings data \cr \code{\link[spatstat.data]{redwoodfull}} \tab Strauss redwood saplings data (full set) \cr \code{\link[spatstat.data]{residualspaper}} \tab Data from Baddeley et al (2005) \cr \code{\link[spatstat.data]{shapley}} \tab Galaxies in an astronomical survey \cr \code{\link[spatstat.data]{simdat}} \tab Simulated point pattern (inhomogeneous, with interaction) \cr \code{\link[spatstat.data]{spiders}} \tab Spider webs on mortar lines of brick wall \cr \code{\link[spatstat.data]{sporophores}} \tab Mycorrhizal fungi around a tree \cr \code{\link[spatstat.data]{spruces}} \tab Spruce trees in Saxonia \cr \code{\link[spatstat.data]{swedishpines}} \tab Strand-Ripley Swedish pines data \cr \code{\link[spatstat.data]{urkiola}} \tab Urkiola Woods data \cr \code{\link[spatstat.data]{waka}} \tab Trees in Waka national park \cr \code{\link[spatstat.data]{waterstriders}} \tab Insects on water surface } \bold{To manipulate a point pattern:} \tabular{ll}{ \code{\link[spatstat.geom]{plot.ppp}} \tab plot a point pattern (e.g. \code{plot(X)}) \cr \code{spatstat.gui::iplot} \tab plot a point pattern interactively \cr \code{\link[spatstat.geom]{edit.ppp}} \tab interactive text editor \cr \code{\link[spatstat.geom]{[.ppp}} \tab extract or replace a subset of a point pattern \cr \tab \code{pp[subset]} or \code{pp[subwindow]} \cr \code{\link[spatstat.geom]{subset.ppp}} \tab extract subset of point pattern satisfying a condition \cr \code{\link[spatstat.geom]{superimpose}} \tab combine several point patterns \cr \code{\link[spatstat.geom]{by.ppp}} \tab apply a function to sub-patterns of a point pattern \cr \code{\link[spatstat.geom]{cut.ppp}} \tab classify the points in a point pattern \cr \code{\link[spatstat.geom]{split.ppp}} \tab divide pattern into sub-patterns \cr \code{\link[spatstat.geom]{unmark}} \tab remove marks \cr \code{\link[spatstat.geom]{npoints}} \tab count the number of points \cr \code{\link[spatstat.geom]{coords}} \tab extract coordinates, change coordinates \cr \code{\link[spatstat.geom]{marks}} \tab extract marks, change marks or attach marks \cr \code{\link[spatstat.geom]{rotate}} \tab rotate pattern \cr \code{\link[spatstat.geom]{shift} } \tab translate pattern \cr \code{\link[spatstat.geom]{flipxy} } \tab swap \eqn{x} and \eqn{y} coordinates \cr \code{\link[spatstat.geom]{reflect} } \tab reflect in the origin \cr \code{\link[spatstat.geom]{periodify} } \tab make several translated copies \cr \code{\link[spatstat.geom]{affine}} \tab apply affine transformation\cr \code{\link[spatstat.geom]{scalardilate}} \tab apply scalar dilation\cr \code{\link[spatstat.core]{density.ppp}} \tab kernel estimation of point pattern intensity\cr \code{\link[spatstat.core]{densityHeat.ppp}} \tab diffusion kernel estimation of point pattern intensity\cr \code{\link[spatstat.core]{Smooth.ppp}} \tab kernel smoothing of marks of point pattern\cr \code{\link[spatstat.geom]{nnmark}} \tab mark value of nearest data point\cr \code{\link[spatstat.core]{sharpen.ppp}} \tab data sharpening\cr \code{\link[spatstat.geom]{identify.ppp}} \tab interactively identify points \cr \code{\link[spatstat.geom]{unique.ppp}} \tab remove duplicate points \cr \code{\link[spatstat.geom]{duplicated.ppp}} \tab determine which points are duplicates \cr \code{\link[spatstat.geom]{uniquemap.ppp}} \tab map duplicated points to unique points \cr \code{\link[spatstat.geom]{connected.ppp}} \tab find clumps of points \cr \code{\link[spatstat.geom]{dirichlet}} \tab compute Dirichlet-Voronoi tessellation \cr \code{\link[spatstat.geom]{delaunay}} \tab compute Delaunay triangulation \cr \code{\link[spatstat.geom]{delaunayDistance}} \tab graph distance in Delaunay triangulation \cr \code{\link[spatstat.geom]{convexhull}} \tab compute convex hull \cr \code{\link[spatstat.geom]{discretise}} \tab discretise coordinates \cr \code{\link[spatstat.geom]{pixellate.ppp}} \tab approximate point pattern by pixel image \cr \code{\link[spatstat.geom]{as.im.ppp}} \tab approximate point pattern by pixel image } See \code{\link[spatstat.geom]{spatstat.options}} to control plotting behaviour. \bold{To create a window:} An object of class \code{"owin"} describes a spatial region (a window of observation). \tabular{ll}{ \code{\link[spatstat.geom]{owin}} \tab Create a window object \cr \tab \code{owin(xlim, ylim)} for rectangular window \cr \tab \code{owin(poly)} for polygonal window \cr \tab \code{owin(mask)} for binary image window \cr \code{\link[spatstat.geom]{Window}} \tab Extract window of another object \cr \code{\link[spatstat.geom]{Frame}} \tab Extract the containing rectangle ('frame') of another object \cr \code{\link[spatstat.geom]{as.owin}} \tab Convert other data to a window object \cr \code{\link[spatstat.geom]{square}} \tab make a square window \cr \code{\link[spatstat.geom]{disc}} \tab make a circular window \cr \code{\link[spatstat.geom]{ellipse}} \tab make an elliptical window \cr \code{\link[spatstat.geom]{ripras}} \tab Ripley-Rasson estimator of window, given only the points \cr \code{\link[spatstat.geom]{convexhull}} \tab compute convex hull of something \cr \code{\link[spatstat.data]{letterR}} \tab polygonal window in the shape of the \R logo \cr \code{\link[spatstat.geom]{clickpoly}} \tab interactively draw a polygonal window \cr \code{\link[spatstat.geom]{clickbox}} \tab interactively draw a rectangle } \bold{To manipulate a window:} \tabular{ll}{ \code{\link[spatstat.geom]{plot.owin}} \tab plot a window. \cr \tab \code{plot(W)}\cr \code{\link[spatstat.geom]{boundingbox}} \tab Find a tight bounding box for the window \cr \code{\link[spatstat.geom]{erosion}} \tab erode window by a distance r\cr \code{\link[spatstat.geom]{dilation}} \tab dilate window by a distance r\cr \code{\link[spatstat.geom]{closing}} \tab close window by a distance r\cr \code{\link[spatstat.geom]{opening}} \tab open window by a distance r\cr \code{\link[spatstat.geom]{border}} \tab difference between window and its erosion/dilation \cr \code{\link[spatstat.geom]{complement.owin}} \tab invert (swap inside and outside)\cr \code{\link[spatstat.geom]{simplify.owin}} \tab approximate a window by a simple polygon \cr \code{\link[spatstat.geom]{rotate}} \tab rotate window \cr \code{\link[spatstat.geom]{flipxy}} \tab swap \eqn{x} and \eqn{y} coordinates \cr \code{\link[spatstat.geom]{shift} } \tab translate window \cr \code{\link[spatstat.geom]{periodify} } \tab make several translated copies \cr \code{\link[spatstat.geom]{affine}} \tab apply affine transformation \cr \code{\link[spatstat.geom]{as.data.frame.owin}} \tab convert window to data frame } \bold{Digital approximations:} \tabular{ll}{ \code{\link[spatstat.geom]{as.mask}} \tab Make a discrete pixel approximation of a given window \cr \code{\link[spatstat.geom]{as.im.owin}} \tab convert window to pixel image \cr \code{\link[spatstat.geom]{pixellate.owin}} \tab convert window to pixel image \cr \code{\link[spatstat.geom]{commonGrid}} \tab find common pixel grid for windows \cr \code{\link[spatstat.geom]{nearest.raster.point}} \tab map continuous coordinates to raster locations\cr \code{\link[spatstat.geom]{raster.x}} \tab raster x coordinates \cr \code{\link[spatstat.geom]{raster.y}} \tab raster y coordinates \cr \code{\link[spatstat.geom]{raster.xy}} \tab raster x and y coordinates \cr \code{\link[spatstat.geom]{as.polygonal}} \tab convert pixel mask to polygonal window } See \code{\link[spatstat.geom]{spatstat.options}} to control the approximation \bold{Geometrical computations with windows:} \tabular{ll}{ \code{\link[spatstat.geom]{edges}} \tab extract boundary edges \cr \code{\link[spatstat.geom]{intersect.owin}} \tab intersection of two windows\cr \code{\link[spatstat.geom]{union.owin}} \tab union of two windows\cr \code{\link[spatstat.geom]{setminus.owin}} \tab set subtraction of two windows\cr \code{\link[spatstat.geom]{inside.owin}} \tab determine whether a point is inside a window\cr \code{\link[spatstat.geom]{area.owin}} \tab compute area \cr \code{\link[spatstat.geom]{perimeter}} \tab compute perimeter length \cr \code{\link[spatstat.geom]{diameter.owin}} \tab compute diameter\cr \code{\link[spatstat.geom]{incircle}} \tab find largest circle inside a window \cr \code{\link[spatstat.geom]{inradius}} \tab radius of incircle \cr \code{\link[spatstat.geom]{connected.owin}} \tab find connected components of window \cr \code{\link[spatstat.geom]{eroded.areas}} \tab compute areas of eroded windows\cr \code{\link[spatstat.geom]{dilated.areas}} \tab compute areas of dilated windows\cr \code{\link[spatstat.geom]{bdist.points}} \tab compute distances from data points to window boundary \cr \code{\link[spatstat.geom]{bdist.pixels}} \tab compute distances from all pixels to window boundary \cr \code{\link[spatstat.geom]{bdist.tiles}} \tab boundary distance for each tile in tessellation \cr \code{\link[spatstat.geom]{distmap.owin}} \tab distance transform image \cr \code{\link[spatstat.geom]{distfun.owin}} \tab distance transform \cr \code{\link[spatstat.geom]{centroid.owin}} \tab compute centroid (centre of mass) of window\cr \code{\link[spatstat.geom]{is.subset.owin}} \tab determine whether one window contains another \cr \code{\link[spatstat.geom]{is.convex}} \tab determine whether a window is convex \cr \code{\link[spatstat.geom]{convexhull}} \tab compute convex hull \cr \code{\link[spatstat.geom]{triangulate.owin}} \tab decompose into triangles \cr \code{\link[spatstat.geom]{as.mask}} \tab pixel approximation of window \cr \code{\link[spatstat.geom]{as.polygonal}} \tab polygonal approximation of window \cr \code{\link[spatstat.geom]{is.rectangle}} \tab test whether window is a rectangle \cr \code{\link[spatstat.geom]{is.polygonal}} \tab test whether window is polygonal \cr \code{\link[spatstat.geom]{is.mask}} \tab test whether window is a mask \cr \code{\link[spatstat.geom]{setcov}} \tab spatial covariance function of window \cr \code{\link[spatstat.geom]{pixelcentres}} \tab extract centres of pixels in mask \cr \code{\link[spatstat.geom]{clickdist}} \tab measure distance between two points clicked by user } \bold{Pixel images:} An object of class \code{"im"} represents a pixel image. Such objects are returned by some of the functions in \pkg{spatstat} including \code{\link[spatstat.core]{Kmeasure}}, \code{\link[spatstat.geom]{setcov}} and \code{\link[spatstat.core]{density.ppp}}. \tabular{ll}{ \code{\link[spatstat.geom]{im}} \tab create a pixel image\cr \code{\link[spatstat.geom]{as.im}} \tab convert other data to a pixel image\cr \code{\link[spatstat.geom]{pixellate}} \tab convert other data to a pixel image\cr \code{\link[spatstat.geom]{as.matrix.im}} \tab convert pixel image to matrix\cr \code{\link[spatstat.geom]{as.data.frame.im}} \tab convert pixel image to data frame\cr \code{\link[spatstat.geom]{as.function.im}} \tab convert pixel image to function\cr \code{\link[spatstat.geom]{plot.im}} \tab plot a pixel image on screen as a digital image\cr \code{\link[spatstat.geom]{contour.im}} \tab draw contours of a pixel image \cr \code{\link[spatstat.geom]{persp.im}} \tab draw perspective plot of a pixel image \cr \code{\link[spatstat.geom]{rgbim}} \tab create colour-valued pixel image \cr \code{\link[spatstat.geom]{hsvim}} \tab create colour-valued pixel image \cr \code{\link[spatstat.geom]{[.im}} \tab extract a subset of a pixel image\cr \code{\link[spatstat.geom]{[<-.im}} \tab replace a subset of a pixel image\cr \code{\link[spatstat.geom]{rotate.im}} \tab rotate pixel image \cr \code{\link[spatstat.geom]{shift.im}} \tab apply vector shift to pixel image \cr \code{\link[spatstat.geom]{affine.im}} \tab apply affine transformation to image \cr \code{X} \tab print very basic information about image \code{X}\cr \code{\link[spatstat.geom:summary.im]{summary}(X)} \tab summary of image \code{X} \cr \code{\link[spatstat.geom]{hist.im}} \tab histogram of image \cr \code{\link[spatstat.geom]{mean.im}} \tab mean pixel value of image \cr \code{\link[spatstat.geom]{integral.im}} \tab integral of pixel values \cr \code{\link[spatstat.geom]{quantile.im}} \tab quantiles of image \cr \code{\link[spatstat.geom]{cut.im}} \tab convert numeric image to factor image \cr \code{\link[spatstat.geom]{is.im}} \tab test whether an object is a pixel image\cr \code{\link[spatstat.geom]{interp.im}} \tab interpolate a pixel image\cr \code{\link[spatstat.core]{blur}} \tab apply Gaussian blur to image\cr \code{\link[spatstat.core]{Smooth.im}} \tab apply Gaussian blur to image\cr \code{\link[spatstat.geom]{connected.im}} \tab find connected components \cr \code{\link[spatstat.geom]{compatible.im}} \tab test whether two images have compatible dimensions \cr \code{\link[spatstat.geom]{harmonise.im}} \tab make images compatible \cr \code{\link[spatstat.geom]{commonGrid}} \tab find a common pixel grid for images \cr \code{\link[spatstat.geom]{eval.im}} \tab evaluate any expression involving images\cr \code{\link[spatstat.geom]{im.apply}} \tab evaluate a function of several images \cr \code{\link[spatstat.geom]{scaletointerval}} \tab rescale pixel values \cr \code{\link[spatstat.geom]{zapsmall.im}} \tab set very small pixel values to zero \cr \code{\link[spatstat.geom]{levelset}} \tab level set of an image\cr \code{\link[spatstat.geom]{solutionset}} \tab region where an expression is true \cr \code{\link[spatstat.geom]{imcov}} \tab spatial covariance function of image \cr \code{\link[spatstat.geom]{convolve.im}} \tab spatial convolution of images \cr \code{\link[spatstat.core]{transect.im}} \tab line transect of image \cr \code{\link[spatstat.geom]{pixelcentres}} \tab extract centres of pixels \cr \code{\link[spatstat.geom]{transmat}} \tab convert matrix of pixel values \cr \tab to a different indexing convention \cr \code{\link[spatstat.core]{rnoise}} \tab random pixel noise } \bold{Line segment patterns} An object of class \code{"psp"} represents a pattern of straight line segments. \tabular{ll}{ \code{\link[spatstat.geom]{psp}} \tab create a line segment pattern \cr \code{\link[spatstat.geom]{as.psp}} \tab convert other data into a line segment pattern \cr \code{\link[spatstat.geom]{edges}} \tab extract edges of a window \cr \code{\link[spatstat.geom]{is.psp}} \tab determine whether a dataset has class \code{"psp"} \cr \code{\link[spatstat.geom]{plot.psp}} \tab plot a line segment pattern \cr \code{\link[spatstat.geom]{print.psp}} \tab print basic information \cr \code{\link[spatstat.geom]{summary.psp}} \tab print summary information \cr \code{\link[spatstat.geom]{[.psp}} \tab extract a subset of a line segment pattern \cr \code{\link[spatstat.geom]{subset.psp}} \tab extract subset of line segment pattern \cr \code{\link[spatstat.geom]{as.data.frame.psp}} \tab convert line segment pattern to data frame \cr \code{\link[spatstat.geom]{marks.psp}} \tab extract marks of line segments \cr \code{\link[spatstat.geom]{marks<-.psp}} \tab assign new marks to line segments \cr \code{\link[spatstat.geom]{unmark.psp}} \tab delete marks from line segments \cr \code{\link[spatstat.geom]{midpoints.psp}} \tab compute the midpoints of line segments \cr \code{\link[spatstat.geom]{endpoints.psp}} \tab extract the endpoints of line segments \cr \code{\link[spatstat.geom]{lengths_psp}} \tab compute the lengths of line segments \cr \code{\link[spatstat.geom]{angles.psp}} \tab compute the orientation angles of line segments \cr \code{\link[spatstat.geom]{superimpose}} \tab combine several line segment patterns \cr \code{\link[spatstat.geom]{flipxy}} \tab swap \eqn{x} and \eqn{y} coordinates \cr \code{\link[spatstat.geom]{rotate.psp}} \tab rotate a line segment pattern \cr \code{\link[spatstat.geom]{shift.psp}} \tab shift a line segment pattern \cr \code{\link[spatstat.geom]{periodify}} \tab make several shifted copies \cr \code{\link[spatstat.geom]{affine.psp}} \tab apply an affine transformation \cr \code{\link[spatstat.geom]{pixellate.psp}} \tab approximate line segment pattern by pixel image \cr \code{\link[spatstat.geom]{as.mask.psp}} \tab approximate line segment pattern by binary mask \cr \code{\link[spatstat.geom]{distmap.psp}} \tab compute the distance map of a line segment pattern \cr \code{\link[spatstat.geom]{distfun.psp}} \tab compute the distance map of a line segment pattern \cr \code{\link[spatstat.core]{density.psp}} \tab kernel smoothing of line segments\cr \code{\link[spatstat.geom]{selfcrossing.psp}} \tab find crossing points between line segments \cr \code{\link[spatstat.geom]{selfcut.psp}} \tab cut segments where they cross \cr \code{\link[spatstat.geom]{crossing.psp}} \tab find crossing points between two line segment patterns \cr \code{\link[spatstat.geom]{extrapolate.psp}} \tab extrapolate line segments to infinite lines \cr \code{\link[spatstat.geom]{nncross}} \tab find distance to nearest line segment from a given point\cr \code{\link[spatstat.geom]{nearestsegment}} \tab find line segment closest to a given point \cr \code{\link[spatstat.geom]{project2segment}} \tab find location along a line segment closest to a given point \cr \code{\link[spatstat.geom]{pointsOnLines}} \tab generate points evenly spaced along line segment \cr \code{\link[spatstat.core]{rpoisline}} \tab generate a realisation of the Poisson line process inside a window\cr \code{\link[spatstat.geom]{rlinegrid}} \tab generate a random array of parallel lines through a window } \bold{Tessellations} An object of class \code{"tess"} represents a tessellation. \tabular{ll}{ \code{\link[spatstat.geom]{tess}} \tab create a tessellation \cr \code{\link[spatstat.geom]{quadrats}} \tab create a tessellation of rectangles\cr \code{\link[spatstat.geom]{hextess}} \tab create a tessellation of hexagons \cr \code{\link[spatstat.geom]{polartess}} \tab tessellation using polar coordinates \cr \code{\link[spatstat.geom]{quantess}} \tab quantile tessellation \cr \code{\link[spatstat.geom]{venn.tess}} \tab Venn diagram tessellation \cr \code{\link[spatstat.geom]{dirichlet}} \tab compute Dirichlet-Voronoi tessellation of points\cr \code{\link[spatstat.geom]{delaunay}} \tab compute Delaunay triangulation of points\cr \code{\link[spatstat.geom]{as.tess}} \tab convert other data to a tessellation \cr \code{\link[spatstat.geom]{plot.tess}} \tab plot a tessellation \cr \code{\link[spatstat.geom]{tiles}} \tab extract all the tiles of a tessellation \cr \code{\link[spatstat.geom]{[.tess}} \tab extract some tiles of a tessellation \cr \code{\link[spatstat.geom]{[<-.tess}} \tab change some tiles of a tessellation \cr \code{\link[spatstat.geom]{intersect.tess}} \tab intersect two tessellations \cr \tab or restrict a tessellation to a window \cr \code{\link[spatstat.geom]{chop.tess}} \tab subdivide a tessellation by a line \cr \code{\link[spatstat.core]{rpoislinetess}} \tab generate tessellation using Poisson line process \cr \code{\link[spatstat.geom]{tile.areas}} \tab area of each tile in tessellation \cr \code{\link[spatstat.geom]{bdist.tiles}} \tab boundary distance for each tile in tessellation \cr \code{\link[spatstat.geom]{connected.tess}} \tab find connected components of tiles \cr \code{\link[spatstat.geom]{shift.tess}} \tab shift a tessellation \cr \code{\link[spatstat.geom]{rotate.tess}} \tab rotate a tessellation \cr \code{\link[spatstat.geom]{reflect.tess}} \tab reflect about the origin \cr \code{\link[spatstat.geom]{flipxy.tess}} \tab reflect about the diagonal \cr \code{\link[spatstat.geom]{affine.tess}} \tab apply affine transformation } \bold{Three-dimensional point patterns} An object of class \code{"pp3"} represents a three-dimensional point pattern in a rectangular box. The box is represented by an object of class \code{"box3"}. \tabular{ll}{ \code{\link[spatstat.geom]{pp3}} \tab create a 3-D point pattern \cr \code{\link[spatstat.geom]{plot.pp3}} \tab plot a 3-D point pattern \cr \code{\link[spatstat.geom]{coords}} \tab extract coordinates \cr \code{\link[spatstat.geom]{as.hyperframe}} \tab extract coordinates \cr \code{\link[spatstat.geom]{subset.pp3}} \tab extract subset of 3-D point pattern \cr \code{\link[spatstat.geom]{unitname.pp3}} \tab name of unit of length \cr \code{\link[spatstat.geom]{npoints}} \tab count the number of points \cr \code{\link[spatstat.core]{runifpoint3}} \tab generate uniform random points in 3-D \cr \code{\link[spatstat.core]{rpoispp3}} \tab generate Poisson random points in 3-D \cr \code{\link[spatstat.core]{envelope.pp3}} \tab generate simulation envelopes for 3-D pattern \cr \code{\link[spatstat.geom]{box3}} \tab create a 3-D rectangular box \cr \code{\link[spatstat.geom]{as.box3}} \tab convert data to 3-D rectangular box \cr \code{\link[spatstat.geom]{unitname.box3}} \tab name of unit of length \cr \code{\link[spatstat.geom]{diameter.box3}} \tab diameter of box \cr \code{\link[spatstat.geom]{volume.box3}} \tab volume of box \cr \code{\link[spatstat.geom]{shortside.box3}} \tab shortest side of box \cr \code{\link[spatstat.geom]{eroded.volumes}} \tab volumes of erosions of box } \bold{Multi-dimensional space-time point patterns} An object of class \code{"ppx"} represents a point pattern in multi-dimensional space and/or time. \tabular{ll}{ \code{\link[spatstat.geom]{ppx}} \tab create a multidimensional space-time point pattern \cr \code{\link[spatstat.geom]{coords}} \tab extract coordinates \cr \code{\link[spatstat.geom]{as.hyperframe}} \tab extract coordinates \cr \code{\link[spatstat.geom]{subset.ppx}} \tab extract subset \cr \code{\link[spatstat.geom]{unitname.ppx}} \tab name of unit of length \cr \code{\link[spatstat.geom]{npoints}} \tab count the number of points \cr \code{\link[spatstat.core]{runifpointx}} \tab generate uniform random points \cr \code{\link[spatstat.core]{rpoisppx}} \tab generate Poisson random points \cr \code{\link[spatstat.geom]{boxx}} \tab define multidimensional box \cr \code{\link[spatstat.geom]{diameter.boxx}} \tab diameter of box \cr \code{\link[spatstat.geom]{volume.boxx}} \tab volume of box \cr \code{\link[spatstat.geom]{shortside.boxx}} \tab shortest side of box \cr \code{\link[spatstat.geom]{eroded.volumes.boxx}} \tab volumes of erosions of box } \bold{Point patterns on a linear network} An object of class \code{"linnet"} represents a linear network (for example, a road network). \tabular{ll}{ \code{\link[spatstat.linnet]{linnet}} \tab create a linear network \cr \code{\link[spatstat.linnet]{clickjoin}} \tab interactively join vertices in network \cr \code{spatstat.gui::iplot.linnet} \tab interactively plot network \cr \code{\link[spatstat.data]{simplenet}} \tab simple example of network \cr \code{\link[spatstat.linnet]{lineardisc}} \tab disc in a linear network \cr \code{\link[spatstat.linnet]{delaunayNetwork}} \tab network of Delaunay triangulation \cr \code{\link[spatstat.linnet]{dirichletNetwork}} \tab network of Dirichlet edges \cr \code{\link[spatstat.linnet]{methods.linnet}} \tab methods for \code{linnet} objects\cr \code{\link[spatstat.linnet]{vertices.linnet}} \tab nodes of network \cr \code{\link[spatstat.linnet]{joinVertices}} \tab join existing vertices in a network \cr \code{\link[spatstat.linnet]{insertVertices}} \tab insert new vertices at positions along a network \cr \code{\link[spatstat.linnet]{addVertices}} \tab add new vertices, extending a network \cr \code{\link[spatstat.linnet]{thinNetwork}} \tab remove vertices or lines from a network \cr \code{\link[spatstat.linnet]{repairNetwork}} \tab repair internal format \cr \code{\link[spatstat.linnet]{pixellate.linnet}} \tab approximate by pixel image } An object of class \code{"lpp"} represents a point pattern on a linear network (for example, road accidents on a road network). \tabular{ll}{ \code{\link[spatstat.linnet]{lpp}} \tab create a point pattern on a linear network \cr \code{\link[spatstat.linnet]{methods.lpp}} \tab methods for \code{lpp} objects \cr \code{\link[spatstat.linnet]{subset.lpp}} \tab method for \code{subset} \cr \code{\link[spatstat.linnet]{rpoislpp}} \tab simulate Poisson points on linear network \cr \code{\link[spatstat.linnet]{runiflpp}} \tab simulate random points on a linear network \cr \code{\link[spatstat.data]{chicago}} \tab Chicago crime data \cr \code{\link[spatstat.data]{dendrite}} \tab Dendritic spines data \cr \code{\link[spatstat.data]{spiders}} \tab Spider webs on mortar lines of brick wall } \bold{Hyperframes} A hyperframe is like a data frame, except that the entries may be objects of any kind. \tabular{ll}{ \code{\link[spatstat.geom]{hyperframe}} \tab create a hyperframe \cr \code{\link[spatstat.geom]{as.hyperframe}} \tab convert data to hyperframe \cr \code{\link[spatstat.geom]{plot.hyperframe}} \tab plot hyperframe \cr \code{\link[spatstat.geom]{with.hyperframe}} \tab evaluate expression using each row of hyperframe \cr \code{\link[spatstat.geom]{cbind.hyperframe}} \tab combine hyperframes by columns\cr \code{\link[spatstat.geom]{rbind.hyperframe}} \tab combine hyperframes by rows\cr \code{\link[spatstat.geom]{as.data.frame.hyperframe}} \tab convert hyperframe to data frame \cr \code{\link[spatstat.geom]{subset.hyperframe}} \tab method for \code{subset} \cr \code{\link[spatstat.geom]{head.hyperframe}} \tab first few rows of hyperframe \cr \code{\link[spatstat.geom]{tail.hyperframe}} \tab last few rows of hyperframe } \bold{Layered objects} A layered object represents data that should be plotted in successive layers, for example, a background and a foreground. \tabular{ll}{ \code{\link[spatstat.geom]{layered}} \tab create layered object \cr \code{\link[spatstat.geom]{plot.layered}} \tab plot layered object\cr \code{\link[spatstat.geom]{[.layered}} \tab extract subset of layered object } \bold{Colour maps} A colour map is a mechanism for associating colours with data. It can be regarded as a function, mapping data to colours. Using a \code{colourmap} object in a plot command ensures that the mapping from numbers to colours is the same in different plots. \tabular{ll}{ \code{\link[spatstat.geom]{colourmap}} \tab create a colour map \cr \code{\link[spatstat.geom]{plot.colourmap}} \tab plot the colour map only\cr \code{\link[spatstat.geom]{tweak.colourmap}} \tab alter individual colour values \cr \code{\link[spatstat.geom]{interp.colourmap}} \tab make a smooth transition between colours \cr \code{\link[spatstat.geom]{beachcolourmap}} \tab one special colour map } } \section{II. EXPLORATORY DATA ANALYSIS}{ \bold{Inspection of data:} \tabular{ll}{ \code{\link[spatstat.geom:summary.ppp]{summary}(X)} \tab print useful summary of point pattern \code{X}\cr \code{X} \tab print basic description of point pattern \code{X} \cr \code{any(duplicated(X))} \tab check for duplicated points in pattern \code{X} \cr \code{spatstat.gui::istat(X)} \tab Interactive exploratory analysis \cr \code{spatstat.gui::View.ppp(X)} \tab spreadsheet-style viewer } \bold{Classical exploratory tools:} \tabular{ll}{ \code{\link[spatstat.core]{clarkevans}} \tab Clark and Evans aggregation index \cr \code{\link[spatstat.core]{fryplot}} \tab Fry plot \cr \code{\link[spatstat.core]{miplot}} \tab Morisita Index plot } \bold{Smoothing:} \tabular{ll}{ \code{\link[spatstat.core]{density.ppp}} \tab kernel smoothed density/intensity\cr \code{\link[spatstat.core]{relrisk}} \tab kernel estimate of relative risk\cr \code{\link[spatstat.core]{Smooth.ppp}} \tab spatial interpolation of marks \cr \code{\link[spatstat.core]{bw.diggle}} \tab cross-validated bandwidth selection for \code{\link[spatstat.core]{density.ppp}}\cr \code{\link[spatstat.core]{bw.ppl}} \tab likelihood cross-validated bandwidth selection for \code{\link[spatstat.core]{density.ppp}}\cr \code{\link[spatstat.core]{bw.CvL}} \tab Cronie-Van Lieshout bandwidth selection for density estimation\cr \code{\link[spatstat.core]{bw.scott}} \tab Scott's rule of thumb for density estimation\cr \code{\link[spatstat.core]{bw.abram}} \tab Abramson's rule for adaptive bandwidths\cr \code{\link[spatstat.core]{bw.relrisk}} \tab cross-validated bandwidth selection for \code{\link[spatstat.core]{relrisk}} \cr \code{\link[spatstat.core]{bw.smoothppp}} \tab cross-validated bandwidth selection for \code{\link[spatstat.core]{Smooth.ppp}} \cr \code{\link[spatstat.core]{bw.frac}} \tab bandwidth selection using window geometry\cr \code{\link[spatstat.core]{bw.stoyan}} \tab Stoyan's rule of thumb for bandwidth for \code{\link[spatstat.core]{pcf}} } \bold{Modern exploratory tools:} \tabular{ll}{ \code{\link[spatstat.core]{clusterset}} \tab Allard-Fraley feature detection \cr \code{\link[spatstat.core]{nnclean}} \tab Byers-Raftery feature detection \cr \code{\link[spatstat.core]{sharpen.ppp}} \tab Choi-Hall data sharpening \cr \code{\link[spatstat.core]{rhohat}} \tab Kernel estimate of covariate effect\cr \code{\link[spatstat.core]{rho2hat}} \tab Kernel estimate of effect of two covariates\cr \code{\link[spatstat.core]{spatialcdf}} \tab Spatial cumulative distribution function\cr \code{\link[spatstat.core]{roc}} \tab Receiver operating characteristic curve } \bold{Summary statistics for a point pattern:} Type \code{demo(sumfun)} for a demonstration of many of the summary statistics. \tabular{ll}{ \code{\link[spatstat.geom]{intensity}} \tab Mean intensity \cr \code{\link[spatstat.geom]{quadratcount}} \tab Quadrat counts \cr \code{\link[spatstat.geom]{intensity.quadratcount}} \tab Mean intensity in quadrats \cr \code{\link[spatstat.core]{Fest}} \tab empty space function \eqn{F} \cr \code{\link[spatstat.core]{Gest}} \tab nearest neighbour distribution function \eqn{G} \cr \code{\link[spatstat.core]{Jest}} \tab \eqn{J}-function \eqn{J = (1-G)/(1-F)} \cr \code{\link[spatstat.core]{Kest}} \tab Ripley's \eqn{K}-function\cr \code{\link[spatstat.core]{Lest}} \tab Besag \eqn{L}-function\cr \code{\link[spatstat.core]{Tstat}} \tab Third order \eqn{T}-function \cr \code{\link[spatstat.core]{allstats}} \tab all four functions \eqn{F}, \eqn{G}, \eqn{J}, \eqn{K} \cr \code{\link[spatstat.core]{pcf}} \tab pair correlation function \cr \code{\link[spatstat.core]{Kinhom}} \tab \eqn{K} for inhomogeneous point patterns \cr \code{\link[spatstat.core]{Linhom}} \tab \eqn{L} for inhomogeneous point patterns \cr \code{\link[spatstat.core]{pcfinhom}} \tab pair correlation for inhomogeneous patterns\cr \code{\link[spatstat.core]{Finhom}} \tab \eqn{F} for inhomogeneous point patterns \cr \code{\link[spatstat.core]{Ginhom}} \tab \eqn{G} for inhomogeneous point patterns \cr \code{\link[spatstat.core]{Jinhom}} \tab \eqn{J} for inhomogeneous point patterns \cr \code{\link[spatstat.core]{localL}} \tab Getis-Franklin neighbourhood density function\cr \code{\link[spatstat.core]{localK}} \tab neighbourhood K-function\cr \code{\link[spatstat.core]{localpcf}} \tab local pair correlation function\cr \code{\link[spatstat.core]{localKinhom}} \tab local \eqn{K} for inhomogeneous point patterns \cr \code{\link[spatstat.core]{localLinhom}} \tab local \eqn{L} for inhomogeneous point patterns \cr \code{\link[spatstat.core]{localpcfinhom}} \tab local pair correlation for inhomogeneous patterns\cr \code{\link[spatstat.core]{Ksector}} \tab Directional \eqn{K}-function\cr \code{\link[spatstat.core]{Kscaled}} \tab locally scaled \eqn{K}-function \cr \code{\link[spatstat.core]{Kest.fft}} \tab fast \eqn{K}-function using FFT for large datasets \cr \code{\link[spatstat.core]{Kmeasure}} \tab reduced second moment measure \cr \code{\link[spatstat.core]{envelope}} \tab simulation envelopes for a summary function \cr \code{\link[spatstat.core]{varblock}} \tab variances and confidence intervals\cr \tab for a summary function \cr \code{\link[spatstat.core]{lohboot}} \tab bootstrap for a summary function } Related facilities: \tabular{ll}{ \code{\link[spatstat.core]{plot.fv}} \tab plot a summary function\cr \code{\link[spatstat.core]{eval.fv}} \tab evaluate any expression involving summary functions\cr \code{\link[spatstat.core]{harmonise.fv}} \tab make functions compatible \cr \code{\link[spatstat.core]{eval.fasp}} \tab evaluate any expression involving an array of functions\cr \code{\link[spatstat.core]{with.fv}} \tab evaluate an expression for a summary function\cr \code{\link[spatstat.core]{Smooth.fv}} \tab apply smoothing to a summary function\cr \code{\link[spatstat.core]{deriv.fv}} \tab calculate derivative of a summary function\cr \code{\link[spatstat.core]{pool.fv}} \tab pool several estimates of a summary function\cr \code{\link[spatstat.geom]{nndist}} \tab nearest neighbour distances \cr \code{\link[spatstat.geom]{nnwhich}} \tab find nearest neighbours \cr \code{\link[spatstat.geom]{pairdist}} \tab distances between all pairs of points\cr \code{\link[spatstat.geom]{crossdist}} \tab distances between points in two patterns\cr \code{\link[spatstat.geom]{nncross}} \tab nearest neighbours between two point patterns \cr \code{\link[spatstat.geom]{exactdt}} \tab distance from any location to nearest data point\cr \code{\link[spatstat.geom]{distmap}} \tab distance map image\cr \code{\link[spatstat.geom]{distfun}} \tab distance map function\cr \code{\link[spatstat.geom]{nnmap}} \tab nearest point image \cr \code{\link[spatstat.geom]{nnfun}} \tab nearest point function \cr \code{\link[spatstat.core]{density.ppp}} \tab kernel smoothed density\cr \code{\link[spatstat.core]{densityHeat.ppp}} \tab diffusion kernel smoothed density\cr \code{\link[spatstat.core]{Smooth.ppp}} \tab spatial interpolation of marks \cr \code{\link[spatstat.core]{relrisk}} \tab kernel estimate of relative risk\cr \code{\link[spatstat.core]{sharpen.ppp}} \tab data sharpening \cr \code{\link[spatstat.core]{rknn}} \tab theoretical distribution of nearest neighbour distance } \bold{Summary statistics for a multitype point pattern:} A multitype point pattern is represented by an object \code{X} of class \code{"ppp"} such that \code{marks(X)} is a factor. \tabular{ll}{ \code{\link[spatstat.core]{relrisk}} \tab kernel estimation of relative risk \cr \code{\link[spatstat.core]{scan.test}} \tab spatial scan test of elevated risk \cr \code{\link[spatstat.core]{Gcross},\link[spatstat.core]{Gdot},\link[spatstat.core]{Gmulti}} \tab multitype nearest neighbour distributions \eqn{G_{ij}, G_{i\bullet}}{G[i,j], G[i.]} \cr \code{\link[spatstat.core]{Kcross},\link[spatstat.core]{Kdot}, \link[spatstat.core]{Kmulti}} \tab multitype \eqn{K}-functions \eqn{K_{ij}, K_{i\bullet}}{K[i,j], K[i.]} \cr \code{\link[spatstat.core]{Lcross},\link[spatstat.core]{Ldot}} \tab multitype \eqn{L}-functions \eqn{L_{ij}, L_{i\bullet}}{L[i,j], L[i.]} \cr \code{\link[spatstat.core]{Jcross},\link[spatstat.core]{Jdot},\link[spatstat.core]{Jmulti}} \tab multitype \eqn{J}-functions \eqn{J_{ij}, J_{i\bullet}}{J[i,j],J[i.]} \cr \code{\link[spatstat.core]{pcfcross}} \tab multitype pair correlation function \eqn{g_{ij}}{g[i,j]} \cr \code{\link[spatstat.core]{pcfdot}} \tab multitype pair correlation function \eqn{g_{i\bullet}}{g[i.]} \cr \code{\link[spatstat.core]{pcfmulti}} \tab general pair correlation function \cr \code{\link[spatstat.core]{markconnect}} \tab marked connection function \eqn{p_{ij}}{p[i,j]} \cr \code{\link[spatstat.core]{alltypes}} \tab estimates of the above for all \eqn{i,j} pairs \cr \code{\link[spatstat.core]{Iest}} \tab multitype \eqn{I}-function\cr \code{\link[spatstat.core]{Kcross.inhom},\link[spatstat.core]{Kdot.inhom}} \tab inhomogeneous counterparts of \code{Kcross}, \code{Kdot} \cr \code{\link[spatstat.core]{Lcross.inhom},\link[spatstat.core]{Ldot.inhom}} \tab inhomogeneous counterparts of \code{Lcross}, \code{Ldot} \cr \code{\link[spatstat.core]{pcfcross.inhom},\link[spatstat.core]{pcfdot.inhom}} \tab inhomogeneous counterparts of \code{pcfcross}, \code{pcfdot} \cr \code{\link[spatstat.core]{localKcross},\link[spatstat.core]{localKdot}} \tab local counterparts of \code{Kcross}, \code{Kdot} \cr \code{\link[spatstat.core]{localLcross},\link[spatstat.core]{localLdot}} \tab local counterparts of \code{Lcross}, \code{Ldot} \cr \code{\link[spatstat.core]{localKcross.inhom},\link[spatstat.core]{localLcross.inhom}} \tab local counterparts of \code{Kcross.inhom}, \code{Lcross.inhom} } \bold{Summary statistics for a marked point pattern:} A marked point pattern is represented by an object \code{X} of class \code{"ppp"} with a component \code{X$marks}. The entries in the vector \code{X$marks} may be numeric, complex, string or any other atomic type. For numeric marks, there are the following functions: \tabular{ll}{ \code{\link[spatstat.core]{markmean}} \tab smoothed local average of marks \cr \code{\link[spatstat.core]{markvar}} \tab smoothed local variance of marks \cr \code{\link[spatstat.core]{markcorr}} \tab mark correlation function \cr \code{\link[spatstat.core]{markcrosscorr}} \tab mark cross-correlation function \cr \code{\link[spatstat.core]{markvario}} \tab mark variogram \cr \code{\link[spatstat.core]{markmarkscatter}} \tab mark-mark scatterplot \cr \code{\link[spatstat.core]{Kmark}} \tab mark-weighted \eqn{K} function \cr \code{\link[spatstat.core]{Emark}} \tab mark independence diagnostic \eqn{E(r)} \cr \code{\link[spatstat.core]{Vmark}} \tab mark independence diagnostic \eqn{V(r)} \cr \code{\link[spatstat.core]{nnmean}} \tab nearest neighbour mean index \cr \code{\link[spatstat.core]{nnvario}} \tab nearest neighbour mark variance index } For marks of any type, there are the following: \tabular{ll}{ \code{\link[spatstat.core]{Gmulti}} \tab multitype nearest neighbour distribution \cr \code{\link[spatstat.core]{Kmulti}} \tab multitype \eqn{K}-function \cr \code{\link[spatstat.core]{Jmulti}} \tab multitype \eqn{J}-function } Alternatively use \code{\link[spatstat.geom]{cut.ppp}} to convert a marked point pattern to a multitype point pattern. \bold{Programming tools:} \tabular{ll}{ \code{\link[spatstat.geom]{applynbd}} \tab apply function to every neighbourhood in a point pattern \cr \code{\link[spatstat.geom]{markstat}} \tab apply function to the marks of neighbours in a point pattern \cr \code{\link[spatstat.core]{marktable}} \tab tabulate the marks of neighbours in a point pattern \cr \code{\link[spatstat.geom]{pppdist}} \tab find the optimal match between two point patterns } \bold{Summary statistics for a point pattern on a linear network:} These are for point patterns on a linear network (class \code{lpp}). For unmarked patterns: \tabular{ll}{ \code{\link[spatstat.linnet]{linearK}} \tab \eqn{K} function on linear network \cr \code{\link[spatstat.linnet]{linearKinhom}} \tab inhomogeneous \eqn{K} function on linear network \cr \code{\link[spatstat.linnet]{linearpcf}} \tab pair correlation function on linear network \cr \code{\link[spatstat.linnet]{linearpcfinhom}} \tab inhomogeneous pair correlation on linear network } For multitype patterns: \tabular{ll}{ \code{\link[spatstat.linnet]{linearKcross}} \tab \eqn{K} function between two types of points \cr \code{\link[spatstat.linnet]{linearKdot}} \tab \eqn{K} function from one type to any type \cr \code{\link[spatstat.linnet]{linearKcross.inhom}} \tab Inhomogeneous version of \code{\link[spatstat.linnet]{linearKcross}} \cr \code{\link[spatstat.linnet]{linearKdot.inhom}} \tab Inhomogeneous version of \code{\link[spatstat.linnet]{linearKdot}} \cr \code{\link[spatstat.linnet]{linearmarkconnect}} \tab Mark connection function on linear network \cr \code{\link[spatstat.linnet]{linearmarkequal}} \tab Mark equality function on linear network \cr \code{\link[spatstat.linnet]{linearpcfcross}} \tab Pair correlation between two types of points \cr \code{\link[spatstat.linnet]{linearpcfdot}} \tab Pair correlation from one type to any type \cr \code{\link[spatstat.linnet]{linearpcfcross.inhom}} \tab Inhomogeneous version of \code{\link[spatstat.linnet]{linearpcfcross}} \cr \code{\link[spatstat.linnet]{linearpcfdot.inhom}} \tab Inhomogeneous version of \code{\link[spatstat.linnet]{linearpcfdot}} } Related facilities: \tabular{ll}{ \code{\link[spatstat.linnet]{pairdist.lpp}} \tab distances between pairs \cr \code{\link[spatstat.linnet]{crossdist.lpp}} \tab distances between pairs \cr \code{\link[spatstat.linnet]{nndist.lpp}} \tab nearest neighbour distances \cr \code{\link[spatstat.linnet]{nncross.lpp}} \tab nearest neighbour distances \cr \code{\link[spatstat.linnet]{nnwhich.lpp}} \tab find nearest neighbours \cr \code{\link[spatstat.linnet]{nnfun.lpp}} \tab find nearest data point \cr \code{\link[spatstat.linnet]{density.lpp}} \tab kernel smoothing estimator of intensity \cr \code{\link[spatstat.linnet]{densityHeat.lpp}} \tab diffusion kernel estimate \cr \code{\link[spatstat.linnet]{distfun.lpp}} \tab distance transform \cr \code{\link[spatstat.linnet]{envelope.lpp}} \tab simulation envelopes \cr \code{\link[spatstat.linnet]{rpoislpp}} \tab simulate Poisson points on linear network \cr \code{\link[spatstat.linnet]{runiflpp}} \tab simulate random points on a linear network } It is also possible to fit point process models to \code{lpp} objects. See Section IV. \bold{Summary statistics for a three-dimensional point pattern:} These are for 3-dimensional point pattern objects (class \code{pp3}). \tabular{ll}{ \code{\link[spatstat.core]{F3est}} \tab empty space function \eqn{F} \cr \code{\link[spatstat.core]{G3est}} \tab nearest neighbour function \eqn{G} \cr \code{\link[spatstat.core]{K3est}} \tab \eqn{K}-function \cr \code{\link[spatstat.core]{pcf3est}} \tab pair correlation function } Related facilities: \tabular{ll}{ \code{\link[spatstat.core]{envelope.pp3}} \tab simulation envelopes \cr \code{\link[spatstat.geom]{pairdist.pp3}} \tab distances between all pairs of points \cr \code{\link[spatstat.geom]{crossdist.pp3}} \tab distances between points in two patterns \cr \code{\link[spatstat.geom]{nndist.pp3}} \tab nearest neighbour distances \cr \code{\link[spatstat.geom]{nnwhich.pp3}} \tab find nearest neighbours \cr \code{\link[spatstat.geom]{nncross.pp3}} \tab find nearest neighbours in another pattern } \bold{Computations for multi-dimensional point pattern:} These are for multi-dimensional space-time point pattern objects (class \code{ppx}). \tabular{ll}{ \code{\link[spatstat.geom]{pairdist.ppx}} \tab distances between all pairs of points \cr \code{\link[spatstat.geom]{crossdist.ppx}} \tab distances between points in two patterns \cr \code{\link[spatstat.geom]{nndist.ppx}} \tab nearest neighbour distances \cr \code{\link[spatstat.geom]{nnwhich.ppx}} \tab find nearest neighbours } \bold{Summary statistics for random sets:} These work for point patterns (class \code{ppp}), line segment patterns (class \code{psp}) or windows (class \code{owin}). \tabular{ll}{ \code{\link[spatstat.core]{Hest}} \tab spherical contact distribution \eqn{H} \cr \code{\link[spatstat.core]{Gfox}} \tab Foxall \eqn{G}-function \cr \code{\link[spatstat.core]{Jfox}} \tab Foxall \eqn{J}-function } } \section{III. MODEL FITTING (COX AND CLUSTER MODELS)}{ Cluster process models (with homogeneous or inhomogeneous intensity) and Cox processes can be fitted by the function \code{\link[spatstat.core]{kppm}}. Its result is an object of class \code{"kppm"}. The fitted model can be printed, plotted, predicted, simulated and updated. \tabular{ll}{ \code{\link[spatstat.core]{kppm}} \tab Fit model\cr \code{\link[spatstat.core]{plot.kppm}} \tab Plot the fitted model\cr \code{\link[spatstat.core]{summary.kppm}} \tab Summarise the fitted model\cr \code{\link[spatstat.core]{fitted.kppm}} \tab Compute fitted intensity \cr \code{\link[spatstat.core]{predict.kppm}} \tab Compute fitted intensity \cr \code{\link[spatstat.core]{update.kppm}} \tab Update the model \cr \code{\link[spatstat.core]{improve.kppm}} \tab Refine the estimate of trend \cr \code{\link[spatstat.core]{simulate.kppm}} \tab Generate simulated realisations \cr \code{\link[spatstat.core]{vcov.kppm}} \tab Variance-covariance matrix of coefficients \cr \code{\link[spatstat.core:methods.kppm]{coef.kppm}} \tab Extract trend coefficients \cr \code{\link[spatstat.core:methods.kppm]{formula.kppm}} \tab Extract trend formula \cr \code{\link[spatstat.core]{parameters}} \tab Extract all model parameters \cr \code{\link[spatstat.core]{clusterfield}} \tab Compute offspring density \cr \code{\link[spatstat.core]{clusterradius}} \tab Radius of support of offspring density \cr \code{\link[spatstat.core]{Kmodel.kppm}} \tab \eqn{K} function of fitted model \cr \code{\link[spatstat.core]{pcfmodel.kppm}} \tab Pair correlation of fitted model } For model selection, you can also use the generic functions \code{\link[stats]{step}}, \code{\link[stats]{drop1}} and \code{\link[stats]{AIC}} on fitted point process models. For variable selection, see \code{\link[spatstat.core]{sdr}}. The theoretical models can also be simulated, for any choice of parameter values, using \code{\link[spatstat.core]{rThomas}}, \code{\link[spatstat.core]{rMatClust}}, \code{\link[spatstat.core]{rCauchy}}, \code{\link[spatstat.core]{rVarGamma}}, and \code{\link[spatstat.core]{rLGCP}}. Lower-level fitting functions include: \tabular{ll}{ \code{\link[spatstat.core]{lgcp.estK}} \tab fit a log-Gaussian Cox process model\cr \code{\link[spatstat.core]{lgcp.estpcf}} \tab fit a log-Gaussian Cox process model\cr \code{\link[spatstat.core]{thomas.estK}} \tab fit the Thomas process model \cr \code{\link[spatstat.core]{thomas.estpcf}} \tab fit the Thomas process model \cr \code{\link[spatstat.core]{matclust.estK}} \tab fit the \Matern Cluster process model \cr \code{\link[spatstat.core]{matclust.estpcf}} \tab fit the \Matern Cluster process model \cr \code{\link[spatstat.core]{cauchy.estK}} \tab fit a Neyman-Scott Cauchy cluster process \cr \code{\link[spatstat.core]{cauchy.estpcf}} \tab fit a Neyman-Scott Cauchy cluster process\cr \code{\link[spatstat.core]{vargamma.estK}} \tab fit a Neyman-Scott Variance Gamma process\cr \code{\link[spatstat.core]{vargamma.estpcf}} \tab fit a Neyman-Scott Variance Gamma process\cr \code{\link[spatstat.core]{mincontrast}} \tab low-level algorithm for fitting models \cr \tab by the method of minimum contrast } } \section{IV. MODEL FITTING (POISSON AND GIBBS MODELS)}{ \bold{Types of models} Poisson point processes are the simplest models for point patterns. A Poisson model assumes that the points are stochastically independent. It may allow the points to have a non-uniform spatial density. The special case of a Poisson process with a uniform spatial density is often called Complete Spatial Randomness. Poisson point processes are included in the more general class of Gibbs point process models. In a Gibbs model, there is \emph{interaction} or dependence between points. Many different types of interaction can be specified. For a detailed explanation of how to fit Poisson or Gibbs point process models to point pattern data using \pkg{spatstat}, see Baddeley and Turner (2005b) or Baddeley (2008). \bold{To fit a Poisson or Gibbs point process model:} Model fitting in \pkg{spatstat} is performed mainly by the function \code{\link[spatstat.core]{ppm}}. Its result is an object of class \code{"ppm"}. Here are some examples, where \code{X} is a point pattern (class \code{"ppp"}): \tabular{ll}{ \emph{command} \tab \emph{model} \cr \code{ppm(X)} \tab Complete Spatial Randomness \cr \code{ppm(X ~ 1)} \tab Complete Spatial Randomness \cr \code{ppm(X ~ x)} \tab Poisson process with \cr \tab intensity loglinear in \eqn{x} coordinate \cr \code{ppm(X ~ 1, Strauss(0.1))} \tab Stationary Strauss process \cr \code{ppm(X ~ x, Strauss(0.1))} \tab Strauss process with \cr \tab conditional intensity loglinear in \eqn{x} } It is also possible to fit models that depend on other covariates. \bold{Manipulating the fitted model:} \tabular{ll}{ \code{\link[spatstat.core]{plot.ppm}} \tab Plot the fitted model\cr \code{\link[spatstat.core]{predict.ppm}} \tab Compute the spatial trend and conditional intensity\cr \tab of the fitted point process model \cr \code{\link[spatstat.core]{coef.ppm}} \tab Extract the fitted model coefficients\cr \code{\link[spatstat.core]{parameters}} \tab Extract all model parameters\cr \code{\link[spatstat.core]{formula.ppm}} \tab Extract the trend formula\cr \code{\link[spatstat.core]{intensity.ppm}} \tab Compute fitted intensity \cr \code{\link[spatstat.core]{Kmodel.ppm}} \tab \eqn{K} function of fitted model \cr \code{\link[spatstat.core]{pcfmodel.ppm}} \tab pair correlation of fitted model \cr \code{\link[spatstat.core]{fitted.ppm}} \tab Compute fitted conditional intensity at quadrature points \cr \code{\link[spatstat.core]{residuals.ppm}} \tab Compute point process residuals at quadrature points \cr \code{\link[spatstat.core]{update.ppm}} \tab Update the fit \cr \code{\link[spatstat.core]{vcov.ppm}} \tab Variance-covariance matrix of estimates\cr \code{\link[spatstat.core]{rmh.ppm}} \tab Simulate from fitted model \cr \code{\link[spatstat.core]{simulate.ppm}} \tab Simulate from fitted model \cr \code{\link[spatstat.core]{print.ppm}} \tab Print basic information about a fitted model\cr \code{\link[spatstat.core]{summary.ppm}} \tab Summarise a fitted model\cr \code{\link[spatstat.core]{effectfun}} \tab Compute the fitted effect of one covariate\cr \code{\link[spatstat.core]{logLik.ppm}} \tab log-likelihood or log-pseudolikelihood\cr \code{\link[spatstat.core]{anova.ppm}} \tab Analysis of deviance \cr \code{\link[spatstat.core]{model.frame.ppm}} \tab Extract data frame used to fit model \cr \code{\link[spatstat.core]{model.images}} \tab Extract spatial data used to fit model \cr \code{\link[spatstat.core]{model.depends}} \tab Identify variables in the model \cr \code{\link[spatstat.core]{as.interact}} \tab Interpoint interaction component of model \cr \code{\link[spatstat.core]{fitin}} \tab Extract fitted interpoint interaction \cr \code{\link[spatstat.core]{is.hybrid}} \tab Determine whether the model is a hybrid \cr \code{\link[spatstat.core]{valid.ppm}} \tab Check the model is a valid point process \cr \code{\link[spatstat.core]{project.ppm}} \tab Ensure the model is a valid point process } For model selection, you can also use the generic functions \code{\link[stats]{step}}, \code{\link[stats]{drop1}} and \code{\link[stats]{AIC}} on fitted point process models. For variable selection, see \code{\link[spatstat.core]{sdr}}. See \code{\link[spatstat.geom]{spatstat.options}} to control plotting of fitted model. \bold{To specify a point process model:} The first order ``trend'' of the model is determined by an \R language formula. The formula specifies the form of the \emph{logarithm} of the trend. \tabular{ll}{ \code{X ~ 1} \tab No trend (stationary) \cr \code{X ~ x} \tab Loglinear trend \eqn{\lambda(x,y) = \exp(\alpha + \beta x)}{lambda(x,y) = exp(alpha + beta * x)} \cr \tab where \eqn{x,y} are Cartesian coordinates \cr \code{X ~ polynom(x,y,3)} \tab Log-cubic polynomial trend \cr \code{X ~ harmonic(x,y,2)} \tab Log-harmonic polynomial trend \cr \code{X ~ Z} \tab Loglinear function of covariate \code{Z} \cr \tab \eqn{\lambda(x,y) = \exp(\alpha + \beta Z(x,y))}{lambda(x,y) = exp(alpha + beta * Z(x,y))} } The higher order (``interaction'') components are described by an object of class \code{"interact"}. Such objects are created by: \tabular{ll}{ \code{\link[spatstat.core]{Poisson}()} \tab the Poisson point process\cr \code{\link[spatstat.core]{AreaInter}()} \tab Area-interaction process\cr \code{\link[spatstat.core]{BadGey}()} \tab multiscale Geyer process\cr \code{\link[spatstat.core]{Concom}()} \tab connected component interaction\cr \code{\link[spatstat.core]{DiggleGratton}() } \tab Diggle-Gratton potential \cr \code{\link[spatstat.core]{DiggleGatesStibbard}() } \tab Diggle-Gates-Stibbard potential \cr \code{\link[spatstat.core]{Fiksel}()} \tab Fiksel pairwise interaction process\cr \code{\link[spatstat.core]{Geyer}()} \tab Geyer's saturation process\cr \code{\link[spatstat.core]{Hardcore}()} \tab Hard core process\cr \code{\link[spatstat.core]{HierHard}()} \tab Hierarchical multiype hard core process\cr \code{\link[spatstat.core]{HierStrauss}()} \tab Hierarchical multiype Strauss process\cr \code{\link[spatstat.core]{HierStraussHard}()} \tab Hierarchical multiype Strauss-hard core process\cr \code{\link[spatstat.core]{Hybrid}()} \tab Hybrid of several interactions\cr \code{\link[spatstat.core]{LennardJones}() } \tab Lennard-Jones potential \cr \code{\link[spatstat.core]{MultiHard}()} \tab multitype hard core process \cr \code{\link[spatstat.core]{MultiStrauss}()} \tab multitype Strauss process \cr \code{\link[spatstat.core]{MultiStraussHard}()} \tab multitype Strauss/hard core process \cr \code{\link[spatstat.core]{OrdThresh}()} \tab Ord process, threshold potential\cr \code{\link[spatstat.core]{Ord}()} \tab Ord model, user-supplied potential \cr \code{\link[spatstat.core]{PairPiece}()} \tab pairwise interaction, piecewise constant \cr \code{\link[spatstat.core]{Pairwise}()} \tab pairwise interaction, user-supplied potential\cr \code{\link[spatstat.core]{Penttinen}()} \tab Penttinen pairwise interaction\cr \code{\link[spatstat.core]{SatPiece}()} \tab Saturated pair model, piecewise constant potential\cr \code{\link[spatstat.core]{Saturated}()} \tab Saturated pair model, user-supplied potential\cr \code{\link[spatstat.core]{Softcore}()} \tab pairwise interaction, soft core potential\cr \code{\link[spatstat.core]{Strauss}()} \tab Strauss process \cr \code{\link[spatstat.core]{StraussHard}()} \tab Strauss/hard core point process \cr \code{\link[spatstat.core]{Triplets}()} \tab Geyer triplets process } Note that it is also possible to combine several such interactions using \code{\link[spatstat.core]{Hybrid}}. \bold{Finer control over model fitting:} A quadrature scheme is represented by an object of class \code{"quad"}. To create a quadrature scheme, typically use \code{\link[spatstat.geom]{quadscheme}}. \tabular{ll}{ \code{\link[spatstat.geom]{quadscheme}} \tab default quadrature scheme \cr \tab using rectangular cells or Dirichlet cells\cr \code{\link[spatstat.geom]{pixelquad}} \tab quadrature scheme based on image pixels \cr \code{\link[spatstat.geom]{quad}} \tab create an object of class \code{"quad"} } To inspect a quadrature scheme: \tabular{ll}{ \code{plot(Q)} \tab plot quadrature scheme \code{Q}\cr \code{print(Q)} \tab print basic information about quadrature scheme \code{Q}\cr \code{\link[spatstat.geom:summary.quad]{summary}(Q)} \tab summary of quadrature scheme \code{Q} } A quadrature scheme consists of data points, dummy points, and weights. To generate dummy points: \tabular{ll}{ \code{\link[spatstat.geom]{default.dummy}} \tab default pattern of dummy points \cr \code{\link[spatstat.geom]{gridcentres}} \tab dummy points in a rectangular grid \cr \code{\link[spatstat.core]{rstrat}} \tab stratified random dummy pattern \cr \code{\link[spatstat.geom]{spokes}} \tab radial pattern of dummy points \cr \code{\link[spatstat.geom]{corners}} \tab dummy points at corners of the window } To compute weights: \tabular{ll}{ \code{\link[spatstat.geom]{gridweights}} \tab quadrature weights by the grid-counting rule \cr \code{\link[spatstat.geom]{dirichletWeights}} \tab quadrature weights are Dirichlet tile areas } \bold{Simulation and goodness-of-fit for fitted models:} \tabular{ll}{ \code{\link[spatstat.core]{rmh.ppm}} \tab simulate realisations of a fitted model \cr \code{\link[spatstat.core]{simulate.ppm}} \tab simulate realisations of a fitted model \cr \code{\link[spatstat.core]{envelope}} \tab compute simulation envelopes for a fitted model } \bold{Point process models on a linear network:} An object of class \code{"lpp"} represents a pattern of points on a linear network. Point process models can also be fitted to these objects. Currently only Poisson models can be fitted. \tabular{ll}{ \code{\link[spatstat.linnet]{lppm}} \tab point process model on linear network \cr \code{\link[spatstat.linnet]{anova.lppm}} \tab analysis of deviance for \cr \tab point process model on linear network \cr \code{\link[spatstat.linnet]{envelope.lppm}} \tab simulation envelopes for \cr \tab point process model on linear network \cr \code{\link[spatstat.linnet]{fitted.lppm}} \tab fitted intensity values \cr \code{\link[spatstat.linnet]{predict.lppm}} \tab model prediction on linear network \cr \code{\link[spatstat.linnet]{linim}} \tab pixel image on linear network \cr \code{\link[spatstat.linnet]{plot.linim}} \tab plot a pixel image on linear network \cr \code{\link[spatstat.linnet]{eval.linim}} \tab evaluate expression involving images \cr \code{\link[spatstat.linnet]{linfun}} \tab function defined on linear network \cr \code{\link[spatstat.linnet]{methods.linfun}} \tab conversion facilities } } \section{V. MODEL FITTING (DETERMINANTAL POINT PROCESS MODELS)}{ Code for fitting \emph{determinantal point process models} has recently been added to \pkg{spatstat}. For information, see the help file for \code{\link[spatstat.core]{dppm}}. } \section{VI. MODEL FITTING (SPATIAL LOGISTIC REGRESSION)}{ \bold{Logistic regression} Pixel-based spatial logistic regression is an alternative technique for analysing spatial point patterns that is widely used in Geographical Information Systems. It is approximately equivalent to fitting a Poisson point process model. In pixel-based logistic regression, the spatial domain is divided into small pixels, the presence or absence of a data point in each pixel is recorded, and logistic regression is used to model the presence/absence indicators as a function of any covariates. Facilities for performing spatial logistic regression are provided in \pkg{spatstat} for comparison purposes. \bold{Fitting a spatial logistic regression} Spatial logistic regression is performed by the function \code{\link[spatstat.core]{slrm}}. Its result is an object of class \code{"slrm"}. There are many methods for this class, including methods for \code{print}, \code{fitted}, \code{predict}, \code{simulate}, \code{anova}, \code{coef}, \code{logLik}, \code{terms}, \code{update}, \code{formula} and \code{vcov}. For example, if \code{X} is a point pattern (class \code{"ppp"}): \tabular{ll}{ \emph{command} \tab \emph{model} \cr \code{slrm(X ~ 1)} \tab Complete Spatial Randomness \cr \code{slrm(X ~ x)} \tab Poisson process with \cr \tab intensity loglinear in \eqn{x} coordinate \cr \code{slrm(X ~ Z)} \tab Poisson process with \cr \tab intensity loglinear in covariate \code{Z} } \bold{Manipulating a fitted spatial logistic regression} \tabular{ll}{ \code{\link[spatstat.core]{anova.slrm}} \tab Analysis of deviance \cr \code{\link[spatstat.core]{coef.slrm}} \tab Extract fitted coefficients \cr \code{\link[spatstat.core]{vcov.slrm}} \tab Variance-covariance matrix of fitted coefficients \cr \code{\link[spatstat.core]{fitted.slrm}} \tab Compute fitted probabilities or intensity \cr \code{\link[spatstat.core]{logLik.slrm}} \tab Evaluate loglikelihood of fitted model \cr \code{\link[spatstat.core]{plot.slrm}} \tab Plot fitted probabilities or intensity \cr \code{\link[spatstat.core]{predict.slrm}} \tab Compute predicted probabilities or intensity with new data \cr \code{\link[spatstat.core]{simulate.slrm}} \tab Simulate model } There are many other undocumented methods for this class, including methods for \code{print}, \code{update}, \code{formula} and \code{terms}. Stepwise model selection is possible using \code{step} or \code{stepAIC}. For variable selection, see \code{\link[spatstat.core]{sdr}}. } \section{VII. SIMULATION}{ There are many ways to generate a random point pattern, line segment pattern, pixel image or tessellation in \pkg{spatstat}. \bold{Random point patterns:} \tabular{ll}{ \code{\link[spatstat.core]{runifpoint}} \tab generate \eqn{n} independent uniform random points \cr \code{\link[spatstat.core]{rpoint}} \tab generate \eqn{n} independent random points \cr \code{\link[spatstat.core]{rmpoint}} \tab generate \eqn{n} independent multitype random points \cr \code{\link[spatstat.core]{rpoispp}} \tab simulate the (in)homogeneous Poisson point process \cr \code{\link[spatstat.core]{rmpoispp}} \tab simulate the (in)homogeneous multitype Poisson point process \cr \code{\link[spatstat.core]{runifdisc}} \tab generate \eqn{n} independent uniform random points in disc\cr \code{\link[spatstat.core]{rstrat}} \tab stratified random sample of points \cr \code{\link[spatstat.geom]{rsyst}} \tab systematic random sample (grid) of points \cr \code{\link[spatstat.core]{rMaternI}} \tab simulate the \Matern Model I inhibition process\cr \code{\link[spatstat.core]{rMaternII}} \tab simulate the \Matern Model II inhibition process\cr \code{\link[spatstat.core]{rSSI}} \tab simulate Simple Sequential Inhibition process\cr \code{\link[spatstat.core]{rHardcore}} \tab simulate hard core process (perfect simulation)\cr \code{\link[spatstat.core]{rStrauss}} \tab simulate Strauss process (perfect simulation)\cr \code{\link[spatstat.core]{rStraussHard}} \tab simulate Strauss-hard core process (perfect simulation)\cr \code{\link[spatstat.core]{rDiggleGratton}} \tab simulate Diggle-Gratton process (perfect simulation)\cr \code{\link[spatstat.core]{rDGS}} \tab simulate Diggle-Gates-Stibbard process (perfect simulation)\cr \code{\link[spatstat.core]{rPenttinen}} \tab simulate Penttinen process (perfect simulation)\cr \code{\link[spatstat.core]{rNeymanScott}} \tab simulate a general Neyman-Scott process\cr \code{\link[spatstat.core]{rMatClust}} \tab simulate the \Matern Cluster process\cr \code{\link[spatstat.core]{rThomas}} \tab simulate the Thomas process \cr \code{\link[spatstat.core]{rLGCP}} \tab simulate the log-Gaussian Cox process \cr \code{\link[spatstat.core]{rGaussPoisson}} \tab simulate the Gauss-Poisson cluster process\cr \code{\link[spatstat.core]{rCauchy}} \tab simulate Neyman-Scott process with Cauchy clusters \cr \code{\link[spatstat.core]{rVarGamma}} \tab simulate Neyman-Scott process with Variance Gamma clusters \cr \code{\link[spatstat.core]{rcell}} \tab simulate the Baddeley-Silverman cell process \cr \code{\link[spatstat.core]{runifpointOnLines}} \tab generate \eqn{n} random points along specified line segments \cr \code{\link[spatstat.core]{rpoisppOnLines}} \tab generate Poisson random points along specified line segments } \bold{Resampling a point pattern:} \tabular{ll}{ \code{\link[spatstat.core]{quadratresample}} \tab block resampling \cr \code{\link[spatstat.geom]{rjitter}} \tab apply random displacements to points in a pattern\cr \code{\link[spatstat.core]{rshift}} \tab random shifting of (subsets of) points\cr \code{\link[spatstat.core]{rthin}} \tab random thinning } See also \code{\link[spatstat.core]{varblock}} for estimating the variance of a summary statistic by block resampling, and \code{\link[spatstat.core]{lohboot}} for another bootstrap technique. \bold{Fitted point process models:} If you have fitted a point process model to a point pattern dataset, the fitted model can be simulated. Cluster process models are fitted by the function \code{\link[spatstat.core]{kppm}} yielding an object of class \code{"kppm"}. To generate one or more simulated realisations of this fitted model, use \code{\link[spatstat.core]{simulate.kppm}}. Gibbs point process models are fitted by the function \code{\link[spatstat.core]{ppm}} yielding an object of class \code{"ppm"}. To generate a simulated realisation of this fitted model, use \code{\link[spatstat.core]{rmh}}. To generate one or more simulated realisations of the fitted model, use \code{\link[spatstat.core]{simulate.ppm}}. \bold{Other random patterns:} \tabular{ll}{ \code{\link[spatstat.geom]{rlinegrid}} \tab generate a random array of parallel lines through a window \cr \code{\link[spatstat.core]{rpoisline}} \tab simulate the Poisson line process within a window \cr \code{\link[spatstat.core]{rpoislinetess}} \tab generate random tessellation using Poisson line process \cr \code{\link[spatstat.core]{rMosaicSet}} \tab generate random set by selecting some tiles of a tessellation \cr \code{\link[spatstat.core]{rMosaicField}} \tab generate random pixel image by assigning random values in each tile of a tessellation } \bold{Simulation-based inference} \tabular{ll}{ \code{\link[spatstat.core]{envelope}} \tab critical envelope for Monte Carlo test of goodness-of-fit \cr \code{\link[spatstat.core]{bits.envelope}} \tab critical envelope for balanced two-stage Monte Carlo test \cr \code{\link[spatstat.core]{qqplot.ppm}} \tab diagnostic plot for interpoint interaction \cr \code{\link[spatstat.core]{scan.test}} \tab spatial scan statistic/test \cr \code{\link[spatstat.core]{studpermu.test}} \tab studentised permutation test\cr \code{\link[spatstat.core]{segregation.test}} \tab test of segregation of types } } \section{VIII. TESTS AND DIAGNOSTICS}{ \bold{Hypothesis tests:} \tabular{ll}{ \code{\link[spatstat.core]{quadrat.test}} \tab \eqn{\chi^2}{chi^2} goodness-of-fit test on quadrat counts \cr \code{\link[spatstat.core]{clarkevans.test}} \tab Clark and Evans test \cr \code{\link[spatstat.core]{cdf.test}} \tab Spatial distribution goodness-of-fit test\cr \code{\link[spatstat.core]{berman.test}} \tab Berman's goodness-of-fit tests\cr \code{\link[spatstat.core]{envelope}} \tab critical envelope for Monte Carlo test of goodness-of-fit \cr \code{\link[spatstat.core]{scan.test}} \tab spatial scan statistic/test \cr \code{\link[spatstat.core]{dclf.test}} \tab Diggle-Cressie-Loosmore-Ford test \cr \code{\link[spatstat.core]{mad.test}} \tab Mean Absolute Deviation test \cr \code{\link[spatstat.core]{anova.ppm}} \tab Analysis of Deviance for point process models } More recently-developed tests: \tabular{ll}{ \code{\link[spatstat.core]{dg.test}} \tab Dao-Genton test \cr \code{\link[spatstat.core]{bits.test}} \tab Balanced independent two-stage test \cr \code{\link[spatstat.core]{dclf.progress}} \tab Progress plot for DCLF test \cr \code{\link[spatstat.core]{mad.progress}} \tab Progress plot for MAD test \cr } \bold{Sensitivity diagnostics:} Classical measures of model sensitivity such as leverage and influence have been adapted to point process models. \tabular{ll}{ \code{\link[spatstat.core]{leverage.ppm}} \tab Leverage for point process model\cr \code{\link[spatstat.core]{influence.ppm}} \tab Influence for point process model\cr \code{\link[spatstat.core]{dfbetas.ppm}} \tab Parameter influence\cr \code{\link[spatstat.core]{dffit.ppm}} \tab Effect change diagnostic } \bold{Diagnostics for covariate effect:} Classical diagnostics for covariate effects have been adapted to point process models. \tabular{ll}{ \code{\link[spatstat.core]{parres}} \tab Partial residual plot\cr \code{\link[spatstat.core]{addvar}} \tab Added variable plot \cr \code{\link[spatstat.core]{rhohat}} \tab Kernel estimate of covariate effect\cr \code{\link[spatstat.core]{rho2hat}} \tab Kernel estimate of covariate effect (bivariate) } \bold{Residual diagnostics:} Residuals for a fitted point process model, and diagnostic plots based on the residuals, were introduced in Baddeley et al (2005) and Baddeley, Rubak and \Moller (2011). Type \code{demo(diagnose)} for a demonstration of the diagnostics features. \tabular{ll}{ \code{\link[spatstat.core]{diagnose.ppm}} \tab diagnostic plots for spatial trend\cr \code{\link[spatstat.core]{qqplot.ppm}} \tab diagnostic Q-Q plot for interpoint interaction\cr \code{\link[spatstat.data]{residualspaper}} \tab examples from Baddeley et al (2005) \cr \code{\link[spatstat.core]{Kcom}} \tab model compensator of \eqn{K} function \cr \code{\link[spatstat.core]{Gcom}} \tab model compensator of \eqn{G} function \cr \code{\link[spatstat.core]{Kres}} \tab score residual of \eqn{K} function \cr \code{\link[spatstat.core]{Gres}} \tab score residual of \eqn{G} function \cr \code{\link[spatstat.core]{psst}} \tab pseudoscore residual of summary function \cr \code{\link[spatstat.core]{psstA}} \tab pseudoscore residual of empty space function \cr \code{\link[spatstat.core]{psstG}} \tab pseudoscore residual of \eqn{G} function \cr \code{\link[spatstat.core]{compareFit}} \tab compare compensators of several fitted models } \bold{Resampling and randomisation procedures} You can build your own tests based on randomisation and resampling using the following capabilities: \tabular{ll}{ \code{\link[spatstat.core]{quadratresample}} \tab block resampling \cr \code{\link[spatstat.geom]{rjitter}} \tab apply random displacements to points in a pattern\cr \code{\link[spatstat.core]{rshift}} \tab random shifting of (subsets of) points\cr \code{\link[spatstat.core]{rthin}} \tab random thinning } } \section{IX. DOCUMENTATION}{ The online manual entries are quite detailed and should be consulted first for information about a particular function. The book Baddeley, Rubak and Turner (2015) is a complete course on analysing spatial point patterns, with full details about \pkg{spatstat}. Older material (which is now out-of-date but is freely available) includes Baddeley and Turner (2005a), a brief overview of the package in its early development; Baddeley and Turner (2005b), a more detailed explanation of how to fit point process models to data; and Baddeley (2010), a complete set of notes from a 2-day workshop on the use of \pkg{spatstat}. Type \code{citation("spatstat")} to get a list of these references. } \references{ Baddeley, A. (2010) \emph{Analysing spatial point patterns in R}. Workshop notes, Version 4.1. Online technical publication, CSIRO. \url{https://research.csiro.au/software/wp-content/uploads/sites/6/2015/02/Rspatialcourse_CMIS_PDF-Standard.pdf} Baddeley, A., Rubak, E. and Turner, R. (2015) \emph{Spatial Point Patterns: Methodology and Applications with R}. Chapman and Hall/CRC Press. Baddeley, A. and Turner, R. (2005a) Spatstat: an R package for analyzing spatial point patterns. \emph{Journal of Statistical Software} \bold{12}:6, 1--42. \code{DOI: 10.18637/jss.v012.i06}. Baddeley, A. and Turner, R. (2005b) Modelling spatial point patterns in R. In: A. Baddeley, P. Gregori, J. Mateu, R. Stoica, and D. Stoyan, editors, \emph{Case Studies in Spatial Point Pattern Modelling}, Lecture Notes in Statistics number 185. Pages 23--74. Springer-Verlag, New York, 2006. ISBN: 0-387-28311-0. Baddeley, A., Turner, R., \Moller, J. and Hazelton, M. (2005) Residual analysis for spatial point processes. \emph{Journal of the Royal Statistical Society, Series B} \bold{67}, 617--666. Baddeley, A., Rubak, E. and \Moller, J. (2011) Score, pseudo-score and residual diagnostics for spatial point process models. \emph{Statistical Science} \bold{26}, 613--646. Baddeley, A., Turner, R., Mateu, J. and Bevan, A. (2013) Hybrids of Gibbs point process models and their implementation. \emph{Journal of Statistical Software} \bold{55}:11, 1--43. \url{https://www.jstatsoft.org/v55/i11/} Diggle, P.J. (2003) \emph{Statistical analysis of spatial point patterns}, Second edition. Arnold. Diggle, P.J. (2014) \emph{Statistical Analysis of Spatial and Spatio-Temporal Point Patterns}, Third edition. {Chapman and Hall/CRC}. Gelfand, A.E., Diggle, P.J., Fuentes, M. and Guttorp, P., editors (2010) \emph{Handbook of Spatial Statistics}. CRC Press. Huang, F. and Ogata, Y. (1999) Improvements of the maximum pseudo-likelihood estimators in various spatial statistical models. \emph{Journal of Computational and Graphical Statistics} \bold{8}, 510--530. Illian, J., Penttinen, A., Stoyan, H. and Stoyan, D. (2008) \emph{Statistical Analysis and Modelling of Spatial Point Patterns.} Wiley. Waagepetersen, R. An estimating function approach to inference for inhomogeneous Neyman-Scott processes. \emph{Biometrics} \bold{63} (2007) 252--258. } \section{Licence}{ This library and its documentation are usable under the terms of the "GNU General Public License", a copy of which is distributed with the package. } \author{ \spatstatAuthors. } \section{Acknowledgements}{ Kasper Klitgaard Berthelsen, Ottmar Cronie, Tilman Davies, Yongtao Guan, Ute Hahn, Abdollah Jalilian, Marie-Colette van Lieshout, Greg McSwiggan, Tuomas Rajala, Suman Rakshit, Dominic Schuhmacher, Rasmus Waagepetersen and Hangsheng Wang made substantial contributions of code. Additional contributions and suggestions from Monsuru Adepeju, Corey Anderson, Ang Qi Wei, Ryan Arellano, Jens \ifelse{latex}{\out{{\AA}str{\" o}m}}{Astrom}, Robert Aue, Marcel Austenfeld, Sandro Azaele, Malissa Baddeley, Guy Bayegnak, Colin Beale, Melanie Bell, Thomas Bendtsen, Ricardo Bernhardt, Andrew Bevan, Brad Biggerstaff, Anders Bilgrau, Leanne Bischof, Christophe Biscio, Roger Bivand, Jose M. Blanco Moreno, Florent Bonneu, Jordan Brown, Ian Buller, Julian Burgos, Simon Byers, Ya-Mei Chang, Jianbao Chen, Igor Chernayavsky, Y.C. Chin, Bjarke Christensen, \ifelse{latex}{\out{Luc\'{\i{}}a}}{Lucia} Cobo Sanchez, Jean-Francois Coeurjolly, Kim Colyvas, Hadrien Commenges, Rochelle Constantine, Robin Corria Ainslie, Richard Cotton, Marcelino de la Cruz, Peter Dalgaard, Mario D'Antuono, Sourav Das, Peter Diggle, Patrick Donnelly, Ian Dryden, Stephen Eglen, Ahmed El-Gabbas, Belarmain Fandohan, Olivier Flores, David Ford, Peter Forbes, Shane Frank, Janet Franklin, Funwi-Gabga Neba, Oscar Garcia, Agnes Gault, Jonas Geldmann, Marc Genton, Shaaban Ghalandarayeshi, Julian Gilbey, Jason Goldstick, Pavel Grabarnik, C. Graf, Ute Hahn, Andrew Hardegen, Martin \Bogsted Hansen, Martin Hazelton, Juha Heikkinen, Mandy Hering, Markus Herrmann, Maximilian Hesselbarth, Paul Hewson, Hamidreza Heydarian, Kassel Hingee, Kurt Hornik, Philipp Hunziker, Jack Hywood, Ross Ihaka, \ifelse{latex}{\out{\u{C}enk I\c{c}\"{o}s}}{Cenk Icos}, Aruna Jammalamadaka, Robert John-Chandran, Devin Johnson, Mahdieh Khanmohammadi, Bob Klaver, Lily Kozmian-Ledward, Peter Kovesi, Mike Kuhn, Jeff Laake, Robert Lamb, \ifelse{latex}{\out{Fr\'{e}d\'{e}ric}}{Frederic} Lavancier, Tom Lawrence, Tomas Lazauskas, Jonathan Lee, George Leser, Angela Li, Li Haitao, George Limitsios, Andrew Lister, Nestor Luambua, Ben Madin, Martin Maechler, Kiran Marchikanti, Jeff Marcus, Robert Mark, Peter McCullagh, Monia Mahling, Jorge Mateu Mahiques, Ulf Mehlig, Frederico Mestre, Sebastian Wastl Meyer, Mi Xiangcheng, Lore De Middeleer, Robin Milne, Enrique Miranda, Jesper \Moller, Annie \ifelse{latex}{\out{Molli{\'e}}}{Mollie}, Ines Moncada, Mehdi Moradi, Virginia Morera Pujol, Erika Mudrak, Gopalan Nair, Nader Najari, Nicoletta Nava, Linda Stougaard Nielsen, Felipe Nunes, Jens Randel Nyengaard, Jens \Oehlschlaegel, Thierry Onkelinx, Sean O'Riordan, Evgeni Parilov, Jeff Picka, Nicolas Picard, Tim Pollington, Mike Porter, Sergiy Protsiv, Adrian Raftery, Suman Rakshit, Ben Ramage, Pablo Ramon, Xavier Raynaud, Nicholas Read, Matt Reiter, Ian Renner, Tom Richardson, Brian Ripley, Yonatan Rosen, Ted Rosenbaum, Barry Rowlingson, Jason Rudokas, Tyler Rudolph, John Rudge, Christopher Ryan, Farzaneh Safavimanesh, Aila \Sarkka, Cody Schank, Katja Schladitz, Sebastian Schutte, Bryan Scott, Olivia Semboli, \ifelse{latex}{\out{Fran\c{c}ois S\'{e}m\'{e}curbe}}{Francois Semecurbe}, Vadim Shcherbakov, Shen Guochun, Shi Peijian, Harold-Jeffrey Ship, Tammy L Silva, Ida-Maria Sintorn, Yong Song, Malte Spiess, Mark Stevenson, Kaspar Stucki, Jan Sulavik, Michael Sumner, P. Surovy, Ben Taylor, Thordis Linda Thorarinsdottir, Leigh Torres, Berwin Turlach, Torben Tvedebrink, Kevin Ummer, Medha Uppala, Andrew van Burgel, Tobias Verbeke, Mikko Vihtakari, Alexendre Villers, Fabrice Vinatier, Maximilian Vogtland, Sasha Voss, Sven Wagner, Hao Wang, H. Wendrock, Jan Wild, Carl G. Witthoft, Selene Wong, Maxime Woringer, Luke Yates, Mike Zamboni and Achim Zeileis. } \keyword{spatial} \keyword{package} spatstat/DESCRIPTION0000644000176200001440000000707314155350602013633 0ustar liggesusersPackage: spatstat Version: 2.3-0 Date: 2021-12-12 Title: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests Authors@R: c(person("Adrian", "Baddeley", role = c("aut", "cre"), email = "Adrian.Baddeley@curtin.edu.au"), person("Rolf", "Turner", role = "aut", email="r.turner@auckland.ac.nz"), person("Ege", "Rubak", role = "aut", email = "rubak@math.aau.dk")) Maintainer: Adrian Baddeley Depends: R (>= 3.5.0), spatstat.data (>= 2.1-0), spatstat.geom (>= 2.3-0), spatstat.core (>= 2.3-0), spatstat.linnet (>= 2.3-0), utils Imports: spatstat.utils (>= 2.2-0) Suggests: Description: Comprehensive open-source toolbox for analysing Spatial Point Patterns. Focused mainly on two-dimensional point patterns, including multitype/marked points, in any spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, point patterns on a linear network, and patterns of other geometrical objects. Supports spatial covariate data such as pixel images. Contains over 2000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks. Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the functions ppm(), kppm(), slrm(), dppm() similar to glm(). Types of models include Poisson, Gibbs and Cox point processes, Neyman-Scott cluster processes, and determinantal point processes. Models may involve dependence on covariates, inter-point interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods. A model can be fitted to a list of point patterns (replicated point pattern data) using the function mppm(). The model can include random effects and fixed effects depending on the experimental design, in addition to all the features listed above. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots. License: GPL (>= 2) URL: http://spatstat.org/ NeedsCompilation: yes ByteCompile: true BugReports: https://github.com/spatstat/spatstat/issues Packaged: 2021-12-12 09:58:04 UTC; adrian Author: Adrian Baddeley [aut, cre], Rolf Turner [aut], Ege Rubak [aut] Repository: CRAN Date/Publication: 2021-12-12 10:40:02 UTC spatstat/build/0000755000176200001440000000000014155343651013223 5ustar liggesusersspatstat/build/vignette.rds0000644000176200001440000000061314155343651015562 0ustar liggesusersRN0uҰ,BB3H_UKԂ$Nj8r9N8xYx!?mXGgp?Y^yc("`؊`V9%hAνR83C `"2g3CG|a 8jI;OdDPBfڋ+NVjyJu:6緄'ntE]DLTL_`UI UImBM 93&!I/H/Kȕ\qlI W?6⤠r ឩE\=ΌV'ҘwmJX;^794spatstat/vignettes/0000755000176200001440000000000014155343651014134 5ustar liggesusersspatstat/vignettes/updates.Rnw0000644000176200001440000035275114155343622016304 0ustar liggesusers\documentclass[11pt]{article} \usepackage{graphicx} \usepackage{Sweave} \usepackage{bm} \usepackage{anysize} \marginsize{2cm}{2cm}{2cm}{2cm} % \VignetteIndexEntry{Summary of Recent Updates to the Spatstat Family} % $Revision: 1.53 $ $Date: 2021/11/21 02:03:40 $ \newcommand{\pkg}[1]{\texttt{#1}} \newcommand{\code}[1]{\texttt{#1}} \newcommand{\R}{{\sf R}} \newcommand{\spst}{\pkg{spatstat}} \newcommand{\Spst}{\pkg{Spatstat}} \begin{document} \bibliographystyle{plain} <>= library(spatstat) x <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = c("Version", "Date")) sversion <- as.character(x[,"Version"]) sdate <- as.character(x[,"Date"]) options(useFancyQuotes=FALSE) @ \title{Summary of recent updates to \spst} \author{Adrian Baddeley, Rolf Turner and Ege Rubak} \date{\today} \maketitle \thispagestyle{empty} <>= readSizeTable <- function(fname) { if(is.null(fname) || !file.exists(fname)) return(NULL) a <- read.table(fname, header=TRUE) a$date <- as.Date(a$date) return(a) } getSizeTable <- function(packagename="spatstat", tablename="packagesizes.txt") { fname <- system.file("doc", tablename, package=packagename) readSizeTable(fname) } RemoveDevel <- function(sizetable) { ## remove entries with fractional version numbers if(is.null(sizetable)) return(NULL) ver <- sizetable$version isdevel <- sapply(ver, function(x) { length(unlist(package_version(x))) > 3 }) st <- if(all(isdevel)) NULL else sizetable[!isdevel, , drop=FALSE] return(st) } counts <- c("nhelpfiles", "nobjects", "ndatasets", "Rlines", "srclines") mergeSizeTables <- function(a, b, breakupdate, allow.devel=FALSE) { #' a is the running total for spatstat; b is a sub-package. #' breakupdate is the date when the code in b was removed from spatstat #' so that the size of 'b' must be added to 'a' for all dates >= breakupdate if(!allow.devel) b <- RemoveDevel(b) if(is.null(b)) return(a) adates <- a$date bdates <- b$date alldates <- sort(unique(c(adates,bdates))) if(missing(breakupdate)) breakupdate <- min(bdates) #' functions to determine, for any given date, #' the relevant (latest) row of the table aok <- rev(!duplicated(rev(adates))) arowfun <- approxfun(adates[aok], seq_along(adates)[aok], method="constant", f=0, rule=2, yleft=0) bok <- rev(!duplicated(rev(bdates))) browfun <- approxfun(bdates[bok], seq_along(bdates)[bok], method="constant", f=0, rule=2, yleft=0) result <- NULL for(k in seq_along(alldates)) { thedate <- alldates[k] i <- arowfun(thedate) j <- browfun(thedate) #' i > 0 because spatstat's founding date is earlier than any sub-package nextrow <- a[i, ] if(j > 0 && thedate >= breakupdate) { #' add contribution from 'b' nextrow[, counts] <- nextrow[, counts] + b[j, counts] } result <- rbind(result, nextrow) } return(result) } ## start collating size tables for the spatstat family z <- getSizeTable() ## sub-packages- access via the sub-package zgeom <- getSizeTable("spatstat.geom") zcore <- getSizeTable("spatstat.core") zlin <- getSizeTable("spatstat.linnet") zutils <- getSizeTable("spatstat.utils") zdata <- getSizeTable("spatstat.data") zsparse <- getSizeTable("spatstat.sparse") ## merge history of geom, core, linnet after the big split Bday <- "2020-12-14" z <- mergeSizeTables(z, zgeom, Bday) z <- mergeSizeTables(z, zcore, Bday) z <- mergeSizeTables(z, zlin, Bday) ## merge history of other packages after their split dates z <- mergeSizeTables(z, zutils, "2017-03-22") z <- mergeSizeTables(z, zdata, "2017-09-23") z <- mergeSizeTables(z, zsparse, "2020-11-04") ## extension packages - use copy of package size file stored in spatstat zlocal <- getSizeTable("spatstat", "spatstatlocalsize.txt") zgui <- getSizeTable("spatstat", "spatstatguisize.txt") zKnet <- getSizeTable("spatstat", "spatstatKnetsize.txt") z <- mergeSizeTables(z, zlocal) z <- mergeSizeTables(z, zgui) z <- mergeSizeTables(z, zKnet) # currentcount <- z[nrow(z), counts] bookcount <- z[z$version == "1.42-0", counts] changes <- currentcount - bookcount newobj <- changes[["nobjects"]] newdat <- changes[["ndatasets"]] + 1 # counting rule doesn't detect redwood3 newcode <- changes[["Rlines"]] + changes[["srclines"]] bookcode <- bookcount[["Rlines"]] + bookcount[["srclines"]] currentcode <- currentcount[["Rlines"]] + currentcount[["srclines"]] growth <- signif((100 * newcode)/bookcode, digits=2) @ %$ This is a summary of changes to the \spst\ package that have occurred since the publication of the book \cite{baddrubaturn15} in 2015. Since then, the \spst\ family has grown by \Sexpr{growth}\%, including \Sexpr{newobj} new functions and \Sexpr{newdat} new datasets, and now contains more than \Sexpr{10 * floor(currentcode/10000)},000 lines of code. This document summarises the most important changes. <>= options(SweaveHooks=list(fig=function() par(mar=0.2+c(2,4,2,0)))) Plot <- function(fmla, ..., dat=z) { yvals <- eval(as.expression(fmla[[2]]), envir=dat) plot(fmla, ..., data=dat, type="l", xlab="", lwd=2, ylim=c(0, max(yvals))) } @ \SweaveOpts{eps=TRUE} \setkeys{Gin}{width=0.55\textwidth} \centerline{ <>= Plot((Rlines + srclines)/1000 ~ date, ylab="Lines of code (x 1000)", main="Spatstat growth") lines(srclines/1000 ~ date, data=z) text(as.Date("2015-01-01"), 9.5, "C code") text(as.Date("2015-01-01"), 60, "R code") @ } \setcounter{tocdepth}{1} \tableofcontents \newpage \newpage \section{Version information} The book \cite{baddrubaturn15}, published in December 2015, covered \spst\ version \texttt{1.42-0}, released in May 2015. <>= ## Tabulate latest version numbers of packages vtable <- data.frame(package="spatstat", version=sversion, date=as.Date(sdate)) AppendVersion <- function(pkg, sizetable, v, allow.devel=FALSE) { if(!allow.devel) sizetable <- RemoveDevel(sizetable) if(is.null(sizetable)) return(v) lastrow <- sizetable[nrow(sizetable), , drop=FALSE] if(is.null(lastrow)) return(v) rbind(v, data.frame(package=pkg, version=lastrow[,"version"], date=as.Date(lastrow[,"date"]))) } vtable <- AppendVersion("spatstat.geom", zgeom, vtable) vtable <- AppendVersion("spatstat.core", zcore, vtable) vtable <- AppendVersion("spatstat.linnet", zlin, vtable) vtable <- AppendVersion("spatstat.sparse", zsparse, vtable) vtable <- AppendVersion("spatstat.data", zdata, vtable) vtable <- AppendVersion("spatstat.utils", zutils, vtable) vtable <- AppendVersion("spatstat.local", zlocal, vtable) vtable <- AppendVersion("spatstat.Knet", zKnet, vtable) vtable <- AppendVersion("spatstat.gui", zgui, vtable) @ The current versions of the \spst\ family of packages (used to produce this document) are: <>= print(vtable[,c(3,1,2)], row.names=FALSE) @ \section{Package structure} The original \pkg{spatstat} package grew to be very large. It has now been split into a family of packages, to satisfy the requirements of CRAN. This should not affect the user: existing code will continue to work in the same way. Typing \code{library(spatstat)} will load the familiar \pkg{spatstat} package which can be used as before. \subsection{Sub-packages} Currently there are seven sub-packages, called \pkg{spatstat.utils}, \pkg{spatstat.data}, \pkg{spatstat.sparse}, \pkg{spatstat.geom}, \pkg{spatstat.core}, \pkg{spatstat.linnet}, and \pkg{spatstat}. \begin{itemize} \item The \code{spatstat} package now contains only documentation and introductory material. It provides beginner's introductions, vignettes, interactive demonstration scripts, and a few help files summarising the package. \item The \pkg{spatstat.data} package now contains all the datasets for \pkg{spatstat}. \item The \pkg{spatstat.utils} package contains utility functions for \pkg{spatstat}. \item The \pkg{spatstat.sparse} package contains functions for manipulating sparse arrays and performing linear algebra. \item The \pkg{spatstat.geom} package contains definitions of spatial objects (such as point patterns, windows and pixel images) and code which performs geometrical operations. \item The \pkg{spatstat.core} package contains the main code for statistical analysis of spatial point patterns and other spatial data. \item The \pkg{spatstat.linnet} package defines spatial data on a linear network, and performs geometrical operations and statistical analysis on such data. \end{itemize} \noindent\textbf{Installing:} If you install \pkg{spatstat}, then the system will install all the other sub-packages listed above. \noindent\textbf{Running:} If you type \code{library(spatstat)} in an \textsf{R} session, the system will automatically load \pkg{spatstat.data}, \pkg{spatstat.geom}, \pkg{spatstat.core} and \pkg{spatstat.linnet}. It will also silently \textbf{``import''} \pkg{spatstat.utils} and \pkg{spatstat.sparse}. To access the functions in \pkg{spatstat.utils} directly, you would need to type \code{library(spatstat.utils)}. Similarly for \pkg{spatstat.sparse}. \subsection{Extension packages} There are also extension packages which provide additional capabilities and must be loaded explicitly when you need them. Currently there are three extension packages, with a fourth in development: \begin{itemize} \item \pkg{spatstat.local} for local model-fitting, \item \pkg{spatstat.Knet} provides additional code for analysing point patterns on a network. \item \pkg{spatstat.gui} containing interactive graphics functions, \item \pkg{spatstat.sphere} for analysing point patterns on a sphere (under development!) \end{itemize} %\pagebreak \section{Precis of all changes} Here is the text from the `overview' sections of the News and Release Notes for each update. \begin{itemize} \item the original \spst\ package has now been split into 7 sub-packages (\pkg{spatstat.utils}, \pkg{spatstat.data}, \pkg{spatstat.sparse}, \pkg{spatstat.geom}, \pkg{spatstat.core}, \pkg{spatstat.linnet} and \pkg{spatstat}). \item The interactive graphics functions \texttt{iplot} and \texttt{istat} have been removed from \spst\ into a new extension package \pkg{spatstat.gui}. \item The packages \pkg{tcltk} and \pkg{rpanel} are no longer Suggested by \spst. \item \spst\ now Imports the package \pkg{spatstat.sparse}. \item \spst\ now Imports the package \pkg{spatstat.utils}. \item \spst\ now requires the package \pkg{spatstat.data} which contains the datasets. \item \spst\ now suggests the package \pkg{fftwtools}. \item Conditional simulation in \texttt{kppm}. \item More diagnostics for spatial logistic regression models. \item Increased numerical stability in \texttt{kppm}. \item Simulation of the product shot noise Cox process. \item Information criteria for model selection in \texttt{kppm}. \item Estimation of the spatial covariance function of a pixel image \item Modified handling of covariates in \texttt{slrm} \item New options for \texttt{weighted.quantile} \item Buffer tessellation \item New function for jittering point patterns on a network. \item Extensions to \texttt{rhohat} \item \texttt{densityfun.ppp} handles query points outside original window \item Extension to \texttt{discretise}. \item Improvement to \texttt{densityEqualSplit}. \item summary method for spatial logistic regression models \item New options for \texttt{distmap.psp} \item Improved output in \texttt{summary.mppm} \item Increased speed for large datasets. \item Variance calculations handle larger datasets. \item Relative risk estimation on a network. \item Leave-one-out density estimation on a network. \item Add new vertices to a linear network. \item More support for multi-dimensional patterns. \item \texttt{predict.mppm} now works for multitype point process models. \item Improved handling of \texttt{newdata} in \texttt{predict.mppm} \item New datasets \texttt{concrete} and \texttt{btb}. \item Changed default value of \texttt{stringsAsFactors}. \item Function \texttt{lengths.psp} has been renamed \verb!lengths_psp!. \item Tessellations on a linear network can now have marks. \item More functions for manipulating tessellations on a linear network. \item New functions for simulating point processes on a linear network. \item Nearest Neighbour Index function can now return mark values. \item Index of repulsion strength for determinantal point process models. \item Nearest neighbours between two point patterns in any number of dimensions. \item More options for handling bad simulation outcomes in \texttt{envelope}. \item \texttt{mppm} accepts case weights. \item Bandwidth selectors warn about extreme values of bandwidth. \item Fast kernel estimation on a linear network using 2D kernels. \item Extension of Scott's rule for bandwidth selection. \item Cross-validated bandwidth selection on a linear network. \item Random thinning and random labelling of spatial patterns extended to different types of pattern. \item Confidence intervals for multitype $K$ function. \item Envelopes for balanced two-stage test \item Extensions to adaptive intensity estimators \item `Dartboard' tessellation using polar coordinates. \item Standard error calculation for inverse-distance weighting. \item Kernel estimate of intensity as a \texttt{function(x,y)}. \item Extract discrete and continuous components of a measure. \item Improvements and extensions to leverage and influence code. \item Plot a line segment pattern using line widths. \item Find connected components of each tile in a tessellation. \item Geometrical operations on \texttt{distfun} objects. \item Join vertices in a linear network. \item Distance map and contact distribution for rectangular structuring element. \item Lurking variable plot for models fitted to several point patterns. \item New dataset \code{cetaceans}. \item Gamma correction for colour maps and image plots. \item Class \code{units} has been renamed \code{unitname} to avoid package collision. \item More support for tessellations. \item Fixed longstanding bug in leverage and influence diagnostics. \item Improvements and bug fixes for leverage and influence diagnostics. \item Tighter bounding box for \code{psp}, \code{lpp}, \code{linnet} objects. \item Improved layout in \code{plot.solist} \item Tools to increase colour saturation. \item Connected components of a 3D point pattern. \item Accelerated computations on linear networks. \item Accelerated simulation of determinantal point processes. \item Improved printing of 3D point patterns. \item Minor corrections to handling of unitnames. \item Improvements to \texttt{ppm} and \texttt{update.ppm}. \item Correction to \texttt{lohboot} \item Numerous bug fixes for linear networks code. \item Now handles disconnected linear networks. \item Effect function is now available for all types of fitted model. \item Geometric-mean smoothing. \item A model can be fitted or re-fitted to a sub-region of data. \item New fast algorithm for kernel smoothing on a linear network. \item Leverage and influence diagnostics extended to Poisson/Gibbs models fitted by logistic composite likelihood. \item Two-stage Monte Carlo test. \item Dirichlet/Voronoi tessellation on a linear network. \item Thinning of point patterns on a linear network. \item More support for functions and tessellations on a linear network. \item Bandwidth selection for pair correlation function. \item Pooling operations improved. \item Operations on signed measures. \item Operations on lists of pixel images. \item Improved pixellation of point patterns. \item Stieltjes integral extended. \item Subset operators extended. \item Greatly accelerated \texttt{rmh} when using \texttt{nsave} \item Sufficient Dimension Reduction for point processes. \item Alternating Gibbs Sampler for point process simulation. \item New class of spatially sampled functions. \item ROC and AUC extended to other types of point patterns and models. \item More support for linear networks. \item More support for infinite straight lines. \item \spst\ now depends on the packages \pkg{nlme} and \pkg{rpart}. \item Important bug fix in \code{linearK}, \code{linearpcf} \item Changed internal format of \code{linnet} and \code{lpp} objects. \item Faster computation in linear networks. \item Bias correction techniques. \item Bounding circle of a spatial object. \item Option to plot marked points as arrows. \item Kernel smoothing accelerated. \item Workaround for bug in some graphics drivers affecting image orientation. \item Non-Gaussian smoothing kernels. \item Improvements to inhomogeneous multitype $K$ and $L$ functions. \item Variance approximation for pair correlation function. \item Leverage and influence for multitype point process models. \item Functions for extracting components of vector-valued objects. \item Recursive-partition point process models. \item Minkowski sum, morphological dilation and erosion with any shape. \item Minkowski sum also applicable to point patterns and line segment patterns. \item Important bug fix in Smooth.ppp \item Important bug fix in spatial CDF tests. \item More bug fixes for replicated patterns. \item Simulate a model fitted to replicated point patterns. \item Inhomogeneous multitype $F$ and $G$ functions. \item Summary functions recognise \texttt{correction="all"} \item Leverage and influence code handles bigger datasets. \item More support for pixel images. \item Improved progress reports. \item New dataset \texttt{redwood3} \item Fixed namespace problems arising when spatstat is not loaded. \item Important bug fix in leverage/influence diagnostics for Gibbs models. \item Surgery with linear networks. \item Tessellations on a linear network. \item Laslett's Transform. \item Colour maps for point patterns with continuous marks are easier to define. \item Pair correlation function estimates can be pooled. \item Stipulate a particular version of a package. \item More support for replicated point patterns. \item More support for tessellations. \item More support for multidimensional point patterns and point processes. \item More options for one-sided envelopes. \item More support for model comparison. \item Convexifying operation. \item Subdivide a linear network. \item Penttinen process can be simulated (by Metropolis-Hastings or CFTP). \item Calculate the predicted variance of number of points. \item Accelerated algorithms for linear networks. \item Quadrat counting accelerated, in some cases. \item Simulation algorithms have been accelerated; simulation outcomes are \emph{not} identical to those obtained from previous versions of \spst. \item Determinantal point process models. \item Random-effects and mixed-effects models for replicated patterns. \item Dao-Genton test, and corresponding simulation envelopes. \item Simulated annealing and simulated tempering. \item spatstat colour tools now handle transparent colours. \item Improvements to \verb![! and \texttt{subset} methods \item Extensions to kernel smoothing on a linear network. \item Support for one-dimensional smoothing kernels. \item Mark correlation function may include weights. \item Cross-correlation version of the mark correlation function. \item Penttinen pairwise interaction model. \item Improvements to simulation of Neyman-Scott processes. \item Improvements to fitting of Neyman-Scott models. \item Extended functionality for pixel images. \item Fitted intensity on linear network \item Triangulation of windows. \item Corrected an edge correction. \end{itemize} \section{New datasets} The following new datasets have been added. These are now provided in the sub-package \pkg{spatstat.data}. \begin{itemize} \item \texttt{austates}: The states and large mainland territories of Australia represented as polygonal regions forming a tessellation. \item \texttt{redwood3}: a more accurate version of the \texttt{redwood} data. \item \texttt{cetaceans}: point patterns of whale and dolphin sightings. \item \texttt{concrete}: air bubbles in concrete. \item \texttt{btb}: bovine tuberculosis occurrences. \end{itemize} \section{New classes} The following new classes of objects may be of use. \begin{itemize} \item \texttt{metric}: Class of distance metrics. An object of class \texttt{metric} represents a distance metric between points in two-dimensional space. See \texttt{help(metric.object)}. \item \texttt{ssf}: Class of spatially sampled functions. An object of class \texttt{"ssf"} represents a spatial function which has been evaluated or sampled at an irregular set of points. See \texttt{help(ssf)}. \end{itemize} \section{New Functions} Following is a list of all the functions that have been added, starting with the most recent additions. \begin{itemize} \item \texttt{lurking.slrm}: Lurking variable plot for spatial logistic regression models. \item \texttt{eem.slrm}: Exponential energy marks for spatial logistic regression models. \item \texttt{eem.ppm}: Exponential energy marks for Gibbs and Poisson point process models (this function was previously called \texttt{eem}). \item \texttt{transformquantiles}: Transform the quantiles of a vector, matrix, array or pixel image. \item \texttt{convexmetric}: Distance metric based on a convex set. \texttt{invoke.metric}: Low level function to perform a desired operation using a given metric. \item \texttt{mean.ecdf, mean.ewcdf} Calculate the mean of an empirical cumulative distribution function. \item \texttt{rjitter.ppp} This function was previously called \texttt{rjitter}. It is now a method for the new generic function \texttt{rjitter}. \item \texttt{bufftess}: Distance buffer tessellation \item \texttt{ic}: Information criteria for model selection in ppm and kppm. Kindly contributed by Achmad Choiruddin, Jean-Francois Coeurjolly and Rasmus Waagepetersen. \item \texttt{rPSNCP}: Generate simulated realisations of the product shot noise Cox process. Contributed by Abdollah Jalilian, Yongtao Guan and Rasmus Waagepetersen. \item \texttt{spatcov}: Estimate the spatial covariance function of a pixel image. \item \texttt{summary.slrm}, \texttt{print.summary.slrm} Summary method for spatial logistic regression models \item \texttt{coef.summary.slrm}: Print the fitted coefficients, confidence interval and p-values for a spatial logistic regression model. \item \texttt{pairMean}: Compute the mean of a specified function of interpoint distance between random points in a window. \item \texttt{rjitterlpp}: Apply random displacements to the points on a linear network. \item \texttt{intersect.boxx}: Compute intersection of boxes in multi-dimensional space \item \texttt{scale.boxx}, \texttt{scale.ppx}: Methods for \texttt{scale} for boxes and patterns in multi-dimensional space \item \texttt{shift.boxx}, \texttt{shift.ppx}: Methods for \texttt{shift} for boxes and patterns in multi-dimensional space \item \texttt{is.boxx}: Determine whether an object is a multidimensional box \item \texttt{relrisk.lpp}: nonparametric estimation of relative risk on a network. \item \texttt{bw.relrisklpp}: Bandwidth selection for relative risk estimation on a network. \item \texttt{bw.lppl}: Bandwidth selection for kernel density estimation of point patterns on a linear network, using likelihood cross-validation. \item \texttt{densityfun.lpp}: a method for \texttt{densityfun} for point patterns on a linear network. \item \texttt{addVertices}: Add new vertices to a network, at locations outside the existing network. \item \verb!lengths_psp!: this is the new name of the function \texttt{lengths.psp}, which had to be changed because of a conflict with the generic \texttt{lengths}. \item \texttt{densityEqualSplit}: The equal-split algorithm for kernel density estimation on a network is now visible as a separate function. \item \texttt{densityHeat}: The heat-equation algorithm for kernel density estimation on a network is now visible as a separate function. It has also been extended to computing leave-one-out density estimates at the data points. \item \texttt{hotrod}: Compute the heat kernel $\kappa(u,v)$ on a one-dimensional line segment. \item \texttt{heatkernelapprox}: Calculate an approximation to the value of the heat kernel on a network evaluated at the source point, $\kappa(u,u)$. \item \texttt{is.linim}: test whether an object is a pixel image on a linear network (class \verb!"linim"!). \item \texttt{rcelllpp}: Simulate the cell point process on a linear network. \item \texttt{rSwitzerlpp}: Simulate the Switzer-type point process on a linear network. \item \texttt{intersect.lintess}: Form the intersection of two tessellations on a linear network. \item \texttt{chop.linnet}: Divide a linear network into tiles using infinite lines. \item \texttt{repairNetwork}: Detect and repair inconsistencies in internal data in a \texttt{linnet} or \texttt{lpp} object. \item \verb!marks<-.lintess!, \texttt{unmark.lintess}: Assign marks to the tiles of a tessellation on a linear network. \item \texttt{marks.lintess}: Extract the marks of the tiles of a tessellation on a linear network. \item \texttt{tilenames.lintess}: Extract the names of the tiles in a tessellation on a linear network \item \verb!tilenames<-.lintess!: Change the names of the tiles in a tessellation on a linear network \item \texttt{nobjects.lintess}: Count the number of tiles in a tessellation on a linear network \item \texttt{as.data.frame.lintess}: Convert a tessellation on a linear network into a data frame. \item \texttt{repul}: Repulsiveness index for a determinantal point process model. \item \texttt{reach.kppm}: Reach (interaction distance) for a Cox or cluster point process model. \item \texttt{summary.dppm}, \texttt{print.summary.dppm}: Summary method for determinantal point process models. \item \texttt{nncross.ppx}: Nearest neighbours between two point patterns in any number of dimensions. \item \texttt{rthinclumps}: Divide a spatial region into clumps and randomly delete some of them. \item \texttt{densityQuick.lpp}: Fast kernel estimator of point process intensity on a network using 2D smoothing kernel. \item \texttt{data.lppm}: Extract the original point pattern dataset (on a linear network) to which the model was fitted. \item \texttt{bw.scott.iso}: Isotropic version of Scott's rule (for point patterns in any dimension). \item \texttt{bits.envelope}: Global simulation envelope corresponding to \texttt{bits.test}, the balanced independent two-stage Monte Carlo test. \item \texttt{extrapolate.psp}: Extrapolate line segments to obtain infinite lines. \item \texttt{uniquemap}: Map duplicate points to unique representatives. Generic with methods for \texttt{ppp}, \texttt{lpp}, \texttt{ppx} \item \texttt{uniquemap.data.frame}, \texttt{uniquemap.matrix}: Map duplicate rows to unique representatives \item \texttt{localKcross}, \texttt{localLcross}, \texttt{localKdot}, \texttt{localLdot}, \texttt{localKcross.inhom}, \texttt{localLcross.inhom}: Multitype local $K$ functions. \item \texttt{polartess}: tessellation using polar coordinates. \item \texttt{densityVoronoi}: adaptive estimate of point process intensity using tessellation methods. \item \texttt{densityAdaptiveKernel}: adaptive estimate of point process intensity using variable kernel methods. \item \texttt{bw.abram}: compute adaptive smoothing bandwidths using Abramson's rule. \item \texttt{coords.quad}: method for \texttt{coords}, to extract the coordinates of the points in a quadrature scheme. \item \texttt{lineartileindex}: low-level function to classify points on a linear network according to which tile of a tessellation they fall inside. \item \texttt{markmarkscatter}: Mark--mark scatterplot. \item \texttt{bw.CvL}: Cronie-van Lieshout bandwidth selection for density estimation. \item \texttt{subset.psp}: subset method for line segment patterns. \item \texttt{densityfun}, \texttt{densityfun.ppp}: Compute a kernel estimate of intensity of a point pattern and return it as a function of spatial location. \item \texttt{as.im.densityfun}: Convert \texttt{function(x,y)} to a pixel image. \item \texttt{measureDiscrete}, \texttt{measureContinuous}: Extract the discrete and continuous components of a measure. \item \texttt{connected.tess}: Find connected components of each tile in a tessellation and make a new tessellation composed of these pieces. \item \texttt{dffit.ppm}: Effect change diagnostic \texttt{DFFIT} for spatial point process models. \item \texttt{shift.distfun}, \texttt{rotate.distfun}, \texttt{reflect.distfun}, \texttt{flipxy.distfun}, \texttt{affine.distfun}, \texttt{scalardilate.distfun}: Methods for geometrical operations on \texttt{distfun} objects. \item \texttt{rescale.distfun}: Change the unit of length in a \texttt{distfun} object. \item \texttt{plot.indicfun}: Plot method for indicator functions created by \texttt{as.function.owin}. \item \texttt{Smooth.leverage.ppm}, \texttt{Smooth.influence.ppm}: Smooth a leverage function or an influence measure. \item \texttt{integral.leverage.ppm}, \texttt{integral.influence.ppm}: Compute the integral of a leverage function or an influence measure. \item \texttt{mean.leverage.ppm}: Compute the mean value of a leverage function. \item \texttt{rectdistmap}: Distance map using rectangular metric. \item \texttt{rectcontact}: Contact distribution function using rectangular structuring element. \item \texttt{joinVertices}: Join specified vertices in a linear network. \item \code{summary.ssf}: Summary method for a spatially sampled function (class \code{ssf}). \item \code{unstack.tess}: Given a tessellation with multiple columns of marks, take the columns one at a time, and return a list of tessellations, each carrying only one of the original columns of marks. \item \code{contour.leverage.ppm}: Method for \code{contour} for leverage functions of class \code{leverage.ppm} \item \code{lurking}: New generic function for lurking variable plots. \item \code{lurking.ppp}, \code{lurking.ppm}: These are equivalent to the original function \code{lurking}. They are now methods for the new generic \code{lurking}. \item \code{lurking.mppm}: New method for class \code{mppm}. Lurking variable plot for models fitted to several point patterns. \item \code{print.lurk}: Prints information about the object returned by the function \code{lurking} representing a lurking variable plot. \item \code{model.matrix.mppm}: Method for \code{model.matrix} for models of class \code{mppm}. \item \code{test.crossing.psp}, \code{test.selfcrossing.psp}: Previously undocumented functions for testing whether segments cross. \item \code{to.saturated}: Convert a colour value to the corresponding fully-saturated colour. \item \code{intensity.psp}: Compute the average total length of segments per unit area. \item \code{boundingbox.psp}: Bounding box for line segment patterns. This produces a tighter bounding box than the previous default behaviour. \item \code{boundingbox.lpp}: Bounding box for point patterns on a linear network. This produces a tighter bounding box than the previous default behaviour. \item \code{boundingbox.linnet}: Bounding box for a linear network. This produces a tighter bounding box than the previous default behaviour. \item \verb!"Frame<-.default"!: New default method for assigning bounding frame to a spatial object. \item \code{connected.pp3}: Connected components of a 3D point pattern. \item \code{colouroutputs}, \verb!"colouroutputs<-"!: Extract or assign colour values in a colour map. (Documented a previously-existing function) \item \texttt{fitin.profilepl}: Extract the fitted interaction from a model fitted by profile likelihood. \item \verb![<-.linim!: Subset assignment method for pixel images on a linear network. \item \texttt{nnfromvertex}: Given a point pattern on a linear network, find the nearest data point from each vertex of the network. \item \texttt{tile.lengths}: Calculate the length of each tile in a tessellation on a network. \item \texttt{text.ppp}, \texttt{text.lpp}, \texttt{text.psp}: Methods for \texttt{text} for spatial patterns. \item \texttt{as.data.frame.envelope}: Extract function data from an envelope object, including the functions for the simulated data ('simfuns') if they were saved. \item \texttt{is.connected}, \texttt{is.connected.default}, \texttt{is.connected.linnet}: Determines whether a spatial object consists of one topologically connected piece, or several pieces. \item \texttt{is.connected.ppp}: Determines whether a point pattern is connected after all pairs of points closer than distance R are joined. \item \texttt{hist.funxy}: Histogram of values of a spatial function. \item \texttt{model.matrix.ippm}: Method for \texttt{model.matrix} which allows computation of regular and irregular score components. \item \texttt{harmonise.msr}: Convert several measures (objects of class \texttt{msr}) to a common quadrature scheme. \item \texttt{bits.test}: Balanced Independent Two-Stage Monte Carlo test, an improvement on the Dao-Genton test. \item \texttt{lineardirichlet}: Computes the Dirichlet-Voronoi tessellation associated with a point pattern on a linear network. \item \texttt{domain.lintess}, \texttt{domain.linfun}: Extract the linear network from a \texttt{lintess} or \texttt{linfun} object. \item \texttt{summary.lintess}: Summary of a tessellation on a linear network. \item \texttt{clicklpp}: Interactively add points on a linear network. \item \texttt{envelopeArray}: Generate an array of envelopes using a function that returns \texttt{fasp} objects. \item \texttt{bw.pcf}: Bandwidth selection for pair correlation function. \item \texttt{grow.box3}: Expand a three-dimensional box. \item \texttt{hexagon}, \texttt{regularpolygon}: Create regular polygons. \item \texttt{Ops.msr}: Arithmetic operations for measures. \item \texttt{Math.imlist}, \texttt{Ops.imlist}, \texttt{Summary.imlist}, \texttt{Complex.imlist}: Arithmetic operations for lists of pixel images. \item \texttt{measurePositive}, \texttt{measureNegative}, \texttt{measureVariation}, \texttt{totalVariation}: Positive and negative parts of a measure, and variation of a measure. \item \texttt{as.function.owin}: Convert a spatial window to a \texttt{function(x,y)}, the indicator function. \item \texttt{as.function.ssf}: Convert an object of class \texttt{ssf} to a \texttt{function(x,y)} \item \texttt{as.function.leverage.ppm} Convert an object of class \texttt{leverage.ppm} to a \texttt{function(x,y)} \item \texttt{sdr}, \texttt{dimhat}: Sufficient Dimension Reduction for point processes. \item \texttt{simulate.rhohat}: Simulate a Poisson point process with the intensity estimated by \texttt{rhohat}. \item \texttt{rlpp}: Random points on a linear network with a specified probability density. \item \texttt{cut.lpp}: Method for \texttt{cut} for point patterns on a linear network. \item \texttt{has.close}: Faster way to check whether a point has a close neighbour. \item \texttt{psib}: Sibling probability (index of clustering strength in a cluster process). \item \texttt{rags}, \texttt{ragsAreaInter}, \texttt{ragsMultiHard}: Alternating Gibbs Sampler for point processes. \item \texttt{bugfixes}: List all bug fixes in recent versions of a package. \item \texttt{ssf}: Create a spatially sampled function \item \texttt{print.ssf}, \texttt{plot.ssf}, \texttt{contour.ssf}, \texttt{image.ssf}: Display a spatially sampled function \item \texttt{as.im.ssf}, \texttt{as.ppp.ssf}, \texttt{marks.ssf}, \verb!marks<-.ssf!, \texttt{unmark.ssf}, \verb![.ssf!, \texttt{with.ssf}: Manipulate data in a spatially sampled function \item \texttt{Smooth.ssf}: Smooth a spatially sampled function \item \texttt{integral.ssf}: Approximate integral of spatially sampled function \item \texttt{roc.kppm}, \texttt{roc.lppm}, \texttt{roc.lpp}: Methods for \texttt{roc} for fitted models of class \texttt{"kppm"} and \texttt{"lppm"} and point patterns of class \texttt{"lpp"} \item \texttt{auc.kppm}, \texttt{auc.lppm}, \texttt{auc.lpp}: Methods for \texttt{auc} for fitted models of class \texttt{"kppm"} and \texttt{"lppm"} and point patterns of class \texttt{"lpp"} \item \texttt{timeTaken}: Extract the timing data from a \texttt{"timed"} object or objects. \item \texttt{rotate.infline}, \texttt{shift.infline}, \texttt{reflect.infline}, \texttt{flipxy.infline}: Geometrical transformations for infinite straight lines. \item \texttt{whichhalfplane}: Determine which side of an infinite line a point lies on. \item \texttt{matrixpower}, \texttt{matrixsqrt}, \texttt{matrixinvsqrt}: Raise a matrix to any power. \item \texttt{points.lpp}: Method for \texttt{points} for point patterns on a linear network. \item \texttt{pairs.linim}: Pairs plot for images on a linear network. \item \texttt{closetriples}: Find close triples of points. \item \texttt{anyNA.im}: Method for \texttt{anyNA} for pixel images. \item \texttt{bc}: Bias correction (Newton-Raphson) for fitted model parameters. \item \texttt{rex}: Richardson extrapolation for numerical integrals and statistical model parameter estimates. \item \texttt{boundingcircle}, \texttt{boundingcentre}: Find the smallest circle enclosing a window or point pattern. \item \verb![.linim! : Subset operator for pixel images on a linear network. \item \texttt{mean.linim}, \texttt{median.linim}, \texttt{quantile.linim}: The mean, median, or quantiles of pixel values in a pixel image on a linear network. \item \texttt{weighted.median}, \texttt{weighted.quantile}: Median or quantile of numerical data with associated weights. \item \verb!"[.linim"!: Subset operator for pixel images on a linear network. \item \texttt{mean.linim}, \texttt{median.linim}, \texttt{quantile.linim}: The mean, median, or quantiles of pixel values in a pixel image on a linear network. \item \texttt{boundingcircle}, \texttt{boundingcentre}: Smallest circle enclosing a spatial object. \item \texttt{split.msr}: Decompose a measure into parts. \item \texttt{unstack.msr}: Decompose a vector-valued measure into its component measures. \item \texttt{unstack.ppp}, \texttt{unstack.psp}, \texttt{unstack.lpp}: Given a spatial pattern with several columns of marks, separate the columns and return a list of spatial patterns, each having only one column of marks. \item \texttt{kernel.squint}: Integral of squared kernel, for the kernels used in density estimation. \item \texttt{as.im.data.frame}: Build a pixel image from a data frame of coordinates and pixel values. \item \texttt{covering}: Cover a window using discs of a given radius. \item \texttt{dilationAny}, \texttt{erosionAny}, \verb!%(-)%! : Morphological dilation and erosion by any shape. \item \texttt{FmultiInhom}, \texttt{GmultiInhom} Inhomogeneous multitype/marked versions of the summary functions \texttt{Fest}, \texttt{Gest}. \item \texttt{kernel.moment} Moment or incomplete moment of smoothing kernel. \item \texttt{MinkowskiSum}, \verb!%(+)%!: Minkowski sum of two windows: \verb!A %(+)% B!, or \texttt{MinkowskiSum(A,B)} \item \texttt{nobjects}: New generic function for counting the number of 'things' in a dataset. There are methods for \texttt{ppp}, \texttt{ppx}, \texttt{psp}, \texttt{tess}. \item \texttt{parameters.interact}, \texttt{parameters.fii}: Extract parameters from interpoint interactions. (These existing functions are now documented.) \item \texttt{ppmInfluence}: Calculate \texttt{leverage.ppm}, \texttt{influence.ppm} and \texttt{dfbetas.ppm} efficiently. \item \texttt{rppm}, \texttt{plot.rppm}, \texttt{predict.rppm}, \texttt{prune.rppm}: Recursive-partition point process models. \item \texttt{simulate.mppm} Simulate a point process model fitted to replicated point patterns. \item \texttt{update.interact}: Update the parameters of an interpoint interaction. [This existing function is now documented.] \item \texttt{where.max}, \texttt{where.min} Find the spatial location(s) where a pixel image achieves its maximum or minimum value. \item \texttt{compileK}, \texttt{compilepcf}: make a $K$ function or pair correlation function given the pairwise distances and their weights. [These existing internal functions are now documented.] \item \texttt{laslett}: Laslett's Transform. \item \texttt{lintess}: Tessellation on a linear network. \item \texttt{divide.linnet}: Divide a linear network into pieces demarcated by a point pattern. \item \texttt{insertVertices}: Insert new vertices in a linear network. \item \texttt{thinNetwork}: Remove vertices and/or segments from a linear network etc. \item \texttt{connected.linnet}: Find connected components of a linear network. \item \texttt{nvertices}, \texttt{nvertices.linnet}, \texttt{nvertices.owin}: Count the number of vertices in a linear network or vertices of the boundary of a window. \item \texttt{as.data.frame.linim}, \texttt{as.data.frame.linfun}: Extract a data frame of spatial locations and function values from an object of class \texttt{linim} or \texttt{linfun}. \item \texttt{as.linfun}, \texttt{as.linfun.linim}, \texttt{as.linfun.lintess}: Convert other kinds of data to a \texttt{linfun} object. \item \texttt{requireversion}: Require a particular version of a package (for use in stand-alone R scripts). \item \texttt{as.function.tess}: Convert a tessellation to a \texttt{function(x,y)}. The function value indicates which tile of the tessellation contains the point $(x,y)$. \item \texttt{tileindex}: Determine which tile of a tessellation contains a given point $(x,y)$. \item \texttt{persp.leverage.ppm}: Method for persp plots for objects of class \texttt{leverage.ppm} \item \texttt{AIC.mppm}, \texttt{extractAIC.mppm}: AIC for point process models fitted to replicated point patterns. \item \texttt{nobs.mppm}, \texttt{terms.mppm}, \texttt{getCall.mppm}: Methods for point process models fitted to replicated point patterns. \item \texttt{rPenttinen}: Simulate the Penttinen process using perfect simulation. \item \texttt{varcount}: Given a point process model, compute the predicted variance of the number of points falling in a window. \item \texttt{inside.boxx}: Test whether multidimensional points lie inside a specified multidimensional box. \item \texttt{lixellate}: Divide each segment of a linear network into smaller segments. \item \texttt{nsegments.linnet}, \texttt{nsegments.lpp}: Count the number of line segments in a linear network. \item \texttt{grow.boxx}: Expand a multidimensional box. \item \texttt{deviance.ppm}, \texttt{deviance.lppm}: Deviance for a fitted point process model. \item \texttt{pseudoR2}: Pseudo-R-squared for a fitted point process model. \item \texttt{tiles.empty} Checks whether each tile of a tessellation is empty or nonempty. \item \texttt{summary.linim}: Summary for a pixel image on a linear network. \item Determinantal Point Process models: \begin{itemize} \item \texttt{dppm}: Fit a determinantal point process model. \item \texttt{fitted.dppm}, \texttt{predict.dppm}, \texttt{intensity.dppm}: prediction for a fitted determinantal point process model. \item \texttt{Kmodel.dppm}, \texttt{pcfmodel.dppm}: Second moments of a determinantal point process model. \item \texttt{rdpp}, \texttt{simulate.dppm}: Simulation of a determinantal point process model. \item \texttt{logLik.dppm}, \texttt{AIC.dppm}, \texttt{extractAIC.dppm}, \texttt{nobs.dppm}: Likelihood and AIC for a fitted determinantal point process model. \item \texttt{print.dppm}, \texttt{reach.dppm}, \texttt{valid.dppm}: Basic information about a \texttt{dpp} model. \item \texttt{coef.dppm}, \texttt{formula.dppm}, \texttt{print.dppm}, \texttt{terms.dppm}, \texttt{labels.dppm}, \texttt{model.frame.dppm}, \texttt{model.matrix.dppm}, \texttt{model.images.dppm}, \texttt{is.stationary.dppm}, \texttt{reach.dppm}, \texttt{unitname.dppm}, \verb!unitname<-.dppm!, \texttt{Window.dppm}: Various methods for \texttt{dppm} objects. \item \texttt{parameters.dppm}: Extract meaningful list of model parameters. \item \texttt{objsurf.dppm}: Objective function surface of a \texttt{dppm} object. \item \texttt{residuals.dppm}: Residual measure for a \texttt{dppm} object. \end{itemize} \item Determinantal Point Process model families: \begin{itemize} \item \texttt{dppBessel}, \texttt{dppCauchy}, \texttt{dppGauss}, \texttt{dppMatern}, \texttt{dppPowerExp}: Determinantal Point Process family functions. \item \texttt{detpointprocfamilyfun}: Create a family function. \item \texttt{update.detpointprocfamily}: Set parameter values in a determinantal point process model family. \item \texttt{simulate.dppm}: Simulation. \item \texttt{is.stationary.detpointprocfamily}, \texttt{intensity.detpointprocfamily}, \texttt{Kmodel.detpointprocfamily}, \texttt{pcfmodel.detpointprocfamily}: Moments. \item \texttt{dim.detpointprocfamily}, \texttt{dppapproxkernel}, \texttt{dppapproxpcf}, \texttt{dppeigen}, \texttt{dppkernel}, \texttt{dppparbounds}, \texttt{dppspecdenrange}, \texttt{dppspecden}: Helper functions. \end{itemize} \item \texttt{dg.envelope}: Simulation envelopes corresponding to Dao-Genton test. \item \texttt{dg.progress}: Progress plot (envelope representation) for the Dao-Genton test. \item \texttt{dg.sigtrace}: significance trace for the Dao-Genton test. \item \texttt{markcrosscorr}: Mark cross-correlation function for point patterns with several columns of marks. \item \texttt{rtemper}: Simulated annealing or simulated tempering. \item \texttt{rgb2hsva}: Convert RGB to HSV data, like \texttt{rgb2hsv}, but preserving transparency. \item \texttt{superimpose.ppplist}, \texttt{superimpose.splitppp}: New methods for 'superimpose' for lists of point patterns. \item \texttt{dkernel}, \texttt{pkernel}, \texttt{qkernel}, \texttt{rkernel}: Probability density, cumulative probability, quantiles and random generation from distributions used in basic one-dimensional kernel smoothing. \item \texttt{kernel.factor}: Auxiliary calculations for one-dimensional kernel smoothing. \item \texttt{spatdim}: Spatial dimension of any object in the \spst\ package. \item \texttt{as.boxx}: Convert data to a multi-dimensional box. \item \texttt{intensity.ppx}: Method for \texttt{intensity} for multi-dimensional space-time point patterns. \item \texttt{fourierbasis}: Evaluate Fourier basis functions in any number of dimensions. \item \texttt{valid}: New generic function, with methods \texttt{valid.ppm}, \texttt{valid.lppm}, \texttt{valid.dppm}. \item \texttt{emend}, \texttt{emend.ppm}, \texttt{emend.lppm}: New generic function with methods for \texttt{ppm} and \texttt{lppm}. \texttt{emend.ppm} is equivalent to \texttt{project.ppm}. \item \texttt{Penttinen}: New pairwise interaction model. \item \texttt{quantile.density}: Calculates quantiles from kernel density estimates. \item \texttt{CDF.density}: Calculates cumulative distribution function from kernel density estimates. \item \texttt{triangulate.owin}: decompose a spatial window into triangles. \item \texttt{fitted.lppm}: fitted intensity values for a point process on a linear network. \item \texttt{parameters}: Extract all parameters from a fitted model. \end{itemize} \section{Alphabetical list of changes} Here is a list of all changes made to existing functions, listed alphabetically. \begin{itemize} %%A \item \texttt{adaptive.density}: This function can now perform adaptive estimation by two methods: either tessellation-based methods or variable-bandwidth kernel estimation. The calculations are performed by either \texttt{densityVoronoi} or \texttt{densityAdaptiveKernel}. \item \texttt{affine.owin}: Allows transformation matrix to be singular, if the window is polygonal. \item \texttt{alltypes}: If \texttt{envelope=TRUE} and the envelope computation reaches the maximum permitted number of errors (\texttt{maxnerr}) in evaluating the summary function for the simulated patterns, then instead of triggering a fatal error, the envelope limits will be set to \texttt{NA}. \item \texttt{anova.mppm}: \begin{itemize} \item Now handles Gibbs models, and performs the adjusted composite likelihood ratio test. \item New argument \texttt{fine}. \item Issues a warning when applied to random-effects models (models fitted using the argument \texttt{random}). \end{itemize} \item \texttt{anyDuplicated.ppp}: Accelerated. \item \texttt{append.psp}: arguments may be \texttt{NULL}. \item \texttt{as.function.tess}: New argument \texttt{values} specifies the function values. \item \texttt{as.im.distfun}: New argument \texttt{approx} specifies the choice of algorithm. \item \texttt{as.im.function}: \begin{itemize} \item New argument \texttt{strict}. \item New argument \texttt{stringsAsFactors}. \item The formal default value of \texttt{stringsAsFactors} has been changed to \texttt{NULL} to conform to changes in R. (The actual default value is \texttt{TRUE} for \texttt{R < 4.1.0} and \texttt{FALSE} for \texttt{R >= 4.1.0}). \end{itemize} \item \texttt{as.im.leverage.ppm}: New argument \texttt{what}. \item \texttt{as.im.nnfun}: New argument \texttt{approx} chooses between a fast, approximate algorithm and a slow, exact algorithm. \item \texttt{as.im.smoothfun}: New argument \texttt{approx} chooses between a fast, approximate algorithm and a slow, exact algorithm. \item \texttt{as.layered}: Default method now handles a (vanilla) list of spatial objects. \item \texttt{as.linfun.lintess}: \begin{itemize} \item New argument \texttt{values} specifies the function value for each tile. \item The default \texttt{values} are the marks, if present. \item New argument \texttt{navalue}. \item Computation accelerated. \end{itemize} \item \texttt{as.linim.default}: New arguments \texttt{delta} and \texttt{nd} control spacing of sample points in internal data. \item \texttt{as.linnet.linnet}: New argument \texttt{maxsize}. \item \texttt{as.linnet.psp}: \begin{itemize} \item If the line segment pattern has marks, then the resulting linear network also carries these marks in the \verb!$lines! component. \item Computation accelerated. \item The resulting network has attribute \texttt{"camefrom"} indicating the provenance of each line segment in the network. \end{itemize} \item \texttt{as.lpp}: accepts more data formats: \begin{itemize} \item Now handles the case where coordinates \texttt{seg} and \texttt{tp} are given but \texttt{x} and \texttt{y} are missing. \item Now handles the case where \texttt{x} is a data frame with columns named \texttt{x,y,seg,tp} or \texttt{x,y} or \texttt{seg,tp}. \end{itemize} \item \texttt{as.owin.default}: \begin{itemize} \item Now refuses to convert a \code{box3} to a two-dimensional window. \item Now accepts a structure with entries named \code{xmin},\code{xmax}, \code{ymin}, \code{ymax} in any order. This handles objects of class \code{bbox} in the \pkg{sf} package. \item Now detects objects of class \code{SpatialPolygons} and issues a more helpful error message. \end{itemize} \item \texttt{as.owin.data.frame}: New argument \texttt{step} \item \texttt{as.polygonal}: \begin{itemize} \item Can now repair errors in polygon data, if \texttt{repair=TRUE}. \item Accelerated when \texttt{w} is a pixel mask. \end{itemize} \item \texttt{as.psp}: now permits a data frame of marks to have only one column, instead of coercing it to a vector. \item \texttt{as.solist}: The argument \texttt{x} can now be a spatial object; \texttt{as.solist(cells)} is the same as \texttt{solist(cells)}. %%B \item \texttt{bdist.pixels}: Accelerated for polygonal windows. New argument \texttt{method}. \item \texttt{bdist.points}: Accelerated for polygonal windows. \item \texttt{beachcolours}: \begin{itemize} \item Improved positioning of the yellow colour band. \item If \texttt{sealevel} lies outside \texttt{srange}, then \texttt{srange} will be extended to include it (without a warning). \end{itemize} \item \texttt{beachcolourmap}: Improved positioning of the yellow colour band. \item \texttt{bilinearform}: This function has been moved to the sub-package \texttt{spatstat.sparse}. \item \texttt{bind.fv}: New argument \texttt{clip}. \item \texttt{blur}: New argument \texttt{kernel}. \item \texttt{bw.abram}: \begin{itemize} \item New argument \texttt{smoother} determines how the pilot estimate is computed. \item Formal arguments rearranged. \end{itemize} \item \texttt{bw.diggle}, \texttt{bw.ppl}, \texttt{bw.relrisk}, \texttt{bw.smoothppp}: \begin{itemize} \item These functions now extract and store the name of the unit of length from the point pattern dataset. When the bandwidth selection criterion is plotted, the name of the unit of length is shown on the x-axis. \item A warning is issued if the optimal value of the cross-validation criterion occurs at an endpoint of the search interval. New argument \texttt{warn}. \end{itemize} \item \texttt{bw.ppl}: \begin{itemize} \item New arguments \texttt{weights} and \texttt{sigma}. \item New argument \texttt{shortcut} allows faster computation. \item Additional arguments \verb!...! are now passed to \texttt{density.ppp}. \end{itemize} \item \texttt{bw.scott}: \begin{itemize} \item the two bandwidth values in the result now have names \texttt{sigma.x} and \texttt{sigma.y}. \item Now handles point patterns of any dimension. \item New arguments \texttt{isotropic} and \texttt{d}. \end{itemize} \item \texttt{bw.stoyan}: The rule has been modified so that, if the pattern is empty, it is now treated as if it contained 1 point, so that a finite bandwidth value is returned. %%C \item \texttt{cbind.hyperframe}: \begin{itemize} \item The result now retains the \texttt{row.names} of the original arguments. \item \end{itemize} \item \texttt{cdf.test}: \begin{itemize} \item Calculations are more robust against numerical rounding effects. \item The methods for classes \texttt{ppp}, \texttt{ppm}, \texttt{lpp}, \texttt{lppm}, \texttt{slrm} have a new argument \texttt{interpolate}. \item Monte Carlo test runs much faster. \item More jittering is applied when \texttt{jitter=TRUE}. Warnings about tied values should not occur any more. \end{itemize} \item \texttt{cdf.test.mppm}: \begin{itemize} \item Now handles Gibbs models. \item Now recognises \texttt{covariate="x"} or \texttt{"y"}. \end{itemize} \item \texttt{clarkevans}: The argument \texttt{correction="all"} is now recognised: it selects all the available options. [This is also the default.] \item \texttt{clickpoly}: The polygon is now drawn progressively as the user clicks new vertices. \item \texttt{closepairs.ppp}: New argument \code{periodic}. \item \texttt{closepairs.ppp}, \texttt{closepairs.pp3}: \begin{itemize} \item New arguments \texttt{distinct} and \texttt{neat} allow more options. \item Argument \texttt{ordered} has been replaced by \texttt{twice} (but \texttt{ordered} is still accepted, with a warning). \item Performance improved (computation time and memory requirements reduced.) This should improve the performance of many functions in \texttt{spatstat}. \end{itemize} \item \texttt{closepairs.pp3}: Argument \texttt{what} can take the value \texttt{"ijd"} \item \texttt{clusterset}: Improved behaviour. \item \texttt{clusterfit}: \begin{itemize} \item New argument \texttt{algorithm} specifies the choice of optimisation algorithm. \item Changed precedence rule for handling the algorithm parameters in the minimum contrast algorithm. Individually-named arguments \texttt{q,p,rmax,rmin} now take precedence over entries with the same names in the list \texttt{ctrl}. \item New argument \texttt{verbose}. \end{itemize} \item \texttt{colourmap}: argument \texttt{col} have have length 1, representing a trivial colour map in which all data values are mapped to the same colour. \item \texttt{collapse.fv}: \begin{itemize} \item This is now treated as a method for the \texttt{nlme} generic \texttt{collapse}. Its syntax has been adjusted slightly. \item Recognises the abbreviations used by \texttt{fvnames()}. \end{itemize} \item \texttt{connected.im}: Now handles a logical-valued image properly. Arguments \texttt{...} now determine pixel resolution. \item \texttt{connected.owin}: Arguments \texttt{...} now determine pixel resolution. \item \texttt{contour.im}: New argument \texttt{col} specifies the colour of the contour lines. If \texttt{col} is a colour map, then the contours are drawn in different colours. \item \texttt{convolve.im}: the name of the unit of length is preserved. \item \texttt{crossdist.lpp}: \begin{itemize} \item Now handles much larger networks, using the sparse representation of the network. \item New argument \texttt{check}. \end{itemize} \item \texttt{crossing.psp}: New argument \texttt{details} gives more information about the intersections between the segments. \item \texttt{crosspairs.pp3}: Argument \texttt{what} can take the value \texttt{"ijd"} \item \texttt{cut.ppp}: Argument \texttt{z} can be \texttt{"x"} or \texttt{"y"} indicating one of the spatial coordinates. %%D \item \texttt{dclf.test, mad.test, dclf.progress, mad.progress,} \texttt{dclf.sigtrace, mad.sigtrace}, \texttt{dg.progress, dg.sigtrace}: \begin{itemize} \item New argument \texttt{clamp} determines the test statistic for one-sided tests. \item New argument \texttt{rmin} determines the left endpoint of the test interval. \item New argument \texttt{leaveout} specifies how to calculate discrepancy between observed and simulated function values. \item New argument \texttt{scale} allows summary function values to be rescaled before the comparison is performed. \item New argument \texttt{interpolate} supports interpolation of $p$-value. \item Function values which are infinite, \texttt{NaN} or \texttt{NA} are now ignored in the calculation (with a warning) instead of causing an error. Warning messages are more detailed. \end{itemize} \item \texttt{default.rmhcontrol, default.rmhexpand}: New argument \texttt{w}. \item \texttt{densityfun.ppp}: The resulting function can now handle query points which lie outside the window of the original data, and has argument \texttt{drop=TRUE} which specifies how to handle them. \item \texttt{densityEqualSplit}: New arguments \texttt{at} and \texttt{leaveoneout} for consistency with other functions. \item \texttt{densityHeat}: \begin{itemize} \item default behaviour has changed slightly. \item new argument \texttt{finespacing}. \end{itemize} \item \texttt{density.lpp}: \begin{itemize} \item New fast algorithm (up to 1000 times faster) for the default case where \texttt{kernel="gaussian"} and \texttt{continuous=TRUE}. Generously contributed by Greg McSwiggan. \item Fast algorithm has been further accelerated. \item Further accelerated when the point pattern contains duplicated points. \item New argument \texttt{kernel} specifies the smoothing kernel. Any of the standard one-dimensional smoothing kernels can be used. \item Now supports both the `equal-split continuous' and `equal-split discontinuous' smoothers. New argument \texttt{continuous} determines the choice of smoother. \item New arguments \texttt{weights} and \texttt{old}. \item New argument \texttt{distance} offers a choice of different kernel methods. \item Infinite bandwidth (\texttt{sigma=Inf}) is now permitted, and results in a density estimate that is constant over all locations. \end{itemize} \item \texttt{density.ppp}: \begin{itemize} \item A non-Gaussian kernel can now be specified using the argument \texttt{kernel}. \item Argument \texttt{weights} can now be a pixel image. \item Infinite bandwidth \texttt{sigma=Inf} is supported. \item Accelerated by about 30\% when \texttt{at="pixels"}. \item Accelerated by about 15\% in the case where \texttt{at="points"} and \texttt{kernel="gaussian"}. \item Accelerated in the cases where weights are given or \texttt{diggle=TRUE}. \item New argument \texttt{verbose}. \end{itemize} \item \texttt{density.psp}: \begin{itemize} \item New argument \texttt{method}. \item Accelerated by 1 to 2 orders of magnitude. \end{itemize} \item \texttt{density.splitppp}: New argument \texttt{weights}. \item \texttt{dfbetas.ppm}: \begin{itemize} \item For Gibbs models, memory usage has been dramatically reduced, so the code can handle larger datasets and finer quadrature schemes. \item Increased the default resolution of the pixel images. Spatial resolution can now be controlled by the arguments \code{dimyx}, \code{eps}. \end{itemize} \item \texttt{diagnose.ppm}: \begin{itemize} \item Infinite values of \texttt{rbord} are now ignored and treated as zero. This ensures that \texttt{diagnose.ppm} has a sensible default when the fitted model has infinite reach. \item Accelerated, when \texttt{type="inverse"}, for models without a hard core. \end{itemize} \item \texttt{diagnose.ppm, plot.diagppm}: \begin{itemize} \item New arguments \texttt{col.neg, col.smooth} control the colour maps. \item Accelerated, when \texttt{type="inverse"}, for models without a hard core. \end{itemize} \item \texttt{dilation.ppp}: Improved geometrical accuracy. Now accepts arguments to control resolution of polygonal approximation. \item \texttt{dirichletEdges}: New argument \texttt{clip}. \item \texttt{discretise}: New argument \texttt{move.points} determines whether the point coordinates are also discretised. \item \texttt{discs}: \begin{itemize} \item Now accepts a single numeric value for \texttt{radii}. \item New argument \texttt{npoly}. \item Accelerated in some cases. \end{itemize} \item \texttt{distcdf}: \begin{itemize} \item Arguments which are \texttt{NULL} will be treated as missing. \item New argument \texttt{savedenom}. \end{itemize} \item \texttt{distfun}: When the user calls a distance function that was created by \texttt{distfun}, the user may now give a \texttt{ppp} or \texttt{lpp} object for the argument \texttt{x}, instead of giving two coordinate vectors \texttt{x} and \texttt{y}. \item \texttt{distfun.lpp}: \begin{itemize} \item New argument \texttt{k} allows computation of $k$-th nearest point. \item Computation accelerated. \end{itemize} \item \texttt{distmap.psp}: New arguments \texttt{extras} and \texttt{clip}. \item \texttt{dppm}: Changed precedence rule for handling the algorithm parameters in the minimum contrast algorithm. Individually-named arguments \texttt{q,p,rmax,rmin} now take precedence over entries with the same names in the list \texttt{ctrl}. \item \texttt{duplicated.ppp}: accelerated. %%E \item \texttt{edge.Trans}: New argument \texttt{gW} for efficiency. \item \texttt{eem}: The function \texttt{eem} is now generic, with methods for \texttt{ppm} and \texttt{slrm}. The function previously named \texttt{eem} is now called \texttt{eem.ppm}. \item \texttt{effectfun}: \begin{itemize} \item Now works for \texttt{ppm}, \texttt{kppm}, \texttt{lppm}, \texttt{dppm}, \texttt{rppm} and \texttt{profilepl} objects. \item New argument \texttt{nvalues}. \end{itemize} \item \texttt{envelope}: \begin{itemize} \item New argument \texttt{clamp} gives greater control over one-sided envelopes. \item New argument \texttt{funargs} \item New argument \texttt{scale} allows global envelopes to have width proportional to a specified function of $r$, rather than constant width. \item New argument \texttt{funYargs} contains arguments to the summary function when applied to the data pattern only. \item The argument \texttt{simulate} can now be a function (such as \texttt{rlabel}). The function will be applied repeatedly to the original data pattern. \item \texttt{rejectNA} and \texttt{silent}. \end{itemize} \item \texttt{envelope.lpp}, \texttt{envelope.lppm}: \begin{itemize} \item New arguments \texttt{fix.n} and \texttt{fix.marks} allow envelopes to be computed using simulations conditional on the observed number of points. \item New arguments \texttt{maxnerr}, \texttt{rejectNA} and \texttt{silent}. \end{itemize} \item \texttt{eval.im}: New argument \texttt{warn}. \item \texttt{eval.linim}: New argument \texttt{warn}. \item \texttt{ewcdf}: \begin{itemize} \item Argument \texttt{weights} can now be \texttt{NULL}. \item New arguments \texttt{normalise} and \texttt{adjust}. \item Computation accelerated. \item The result does not inherit class \texttt{"ecdf"} if \texttt{normalise=FALSE}. \end{itemize} %%F \item \texttt{Fest}: Additional checks for errors in input data. \item \texttt{Finhom}: \begin{itemize} \item A warning is issued if bias is likely to occur because of undersmoothing. \item New arguments \texttt{warn.bias} and \texttt{savelambda}. \end{itemize} \item \texttt{fitted.lppm}: New argument \texttt{leaveoneout} allows leave-one-out computation of fitted value. \item \texttt{fitted.ppm}: \begin{itemize} \item New option, \texttt{type="link"}. \item New argument \code{ignore.hardcore}. \end{itemize} \item \texttt{funxy}: \begin{itemize} \item When the user calls a function that was created by \texttt{funxy}, the user may now give a \texttt{ppp} or \texttt{lpp} object for the argument \texttt{x}, instead of giving two coordinate vectors \texttt{x} and \texttt{y}. \item Functions of class \texttt{"funxy"} can now be applied to quadrature schemes. \end{itemize} %%G \item \texttt{Gcross}: Function labels (shown on the plot legend) have been improved when \texttt{i = j}. \item \texttt{Geyer}: The saturation parameter \texttt{sat} can now be less than 1. \item \texttt{Ginhom}: \begin{itemize} \item A warning is issued if bias is likely to occur because of undersmoothing. \item New arguments \texttt{warn.bias} and \texttt{savelambda}. \end{itemize} \item \texttt{grow.rectangle}: New argument \texttt{fraction}. %%H \item \texttt{harmonise.im}: The result belongs to classes \texttt{solist} and \texttt{imlist} so that it can be plotted. \item \texttt{Hest}: \begin{itemize} \item Argument \texttt{X} can now be a pixel image with logical values. \item New argument \texttt{W}. [Based on code by Kassel Hingee.] \item Additional checks for errors in input data. \end{itemize} \item \texttt{hist.im}: New argument \texttt{xname}. \item \texttt{hyperframe}: \begin{itemize} \item The formal default value of \texttt{stringsAsFactors} has been changed to \texttt{NULL} to conform to changes in R. (The actual default value is \texttt{TRUE} for \texttt{R < 4.1.0} and \texttt{FALSE} for \texttt{R >= 4.1.0}). \end{itemize} %%I \item \texttt{identify.psp}: Improved placement of labels. Arguments can be passed to \texttt{text.default} to control the plotting of labels. \item \texttt{idw}: Standard errors can now be calculated by setting \texttt{se=TRUE}. \item \texttt{imcov}: the name of the unit of length is preserved. \item \texttt{im.apply}: \begin{itemize} \item Computation accelerated \item New argument \texttt{fun.handles.na} \item New argument \texttt{check} \end{itemize} \item \texttt{influence.ppm}: For Gibbs models, memory usage has been dramatically reduced, so the code can handle larger datasets and finer quadrature schemes. \item \texttt{integral.im}: Accelerated in the case where \texttt{domain} is a tessellation. \item \texttt{integral.linfun}: \begin{itemize} \item New argument \texttt{delta} controls step length of approximation to integral. \item New argument \texttt{nd} controls approximate number of sample points used to calculate integral. \item Argument \code{domain} can be a tessellation. \item Now handles complex-valued functions. \end{itemize} \item \texttt{integral.linim}: \begin{itemize} \item Argument \code{domain} can be a tessellation. \item Now handles complex-valued functions. \end{itemize} \item \texttt{integral.ssf}: Argument \code{domain} can be a tessellation. \item \texttt{intensity.ppm}: Intensity approximation is now implemented for area-interaction model, and Geyer saturation model. \item \texttt{interp.im}: New argument \texttt{bilinear}. \item \texttt{iplot}, \texttt{iplot.ppp}, \texttt{iplot.layered}, \texttt{iplot.linnet}, \texttt{iplot.default}: These interactive plotting functions have been removed from \pkg{spatstat} into a new package \pkg{spatstat.gui}. \item \texttt{ippm}: \begin{itemize} \item Accelerated. \item The internal format of the result has been extended slightly. \item Improved defaults for numerical algorithm parameters. \end{itemize} \item \texttt{istat}: This interactive analysis function has been removed from \pkg{spatstat} into a new package \pkg{spatstat.gui}. %%J \item \texttt{Jcross}: Function labels (shown on the plot legend) have been improved when \texttt{i = j}. \item \texttt{Jfox}: new argument \texttt{warn.trim}. \item \texttt{Jinhom}: \begin{itemize} \item A warning is issued if bias is likely to occur because of undersmoothing. \item New arguments \texttt{warn.bias} and \texttt{savelambda}. \end{itemize} %%K \item \texttt{Kcross}: Function labels (shown on the plot legend) have been improved when \texttt{i = j}. \item \texttt{Kcross.inhom}, \texttt{Kdot.inhom}, \texttt{Kmulti.inhom}: \begin{itemize} \item These functions now allow intensity values to be given by a fitted point process model. \item New arguments \texttt{update}, \texttt{leaveoneout}, \texttt{lambdaX}. \item Leave-one-out calculation is now implemented when \texttt{lambbdaX} is a fitted model of class \texttt{"dppm"}. \end{itemize} \item \texttt{Kest} \begin{itemize} \item Accelerated computation (for translation and rigid corrections) when window is an irregular shape. \item Calculation of isotropic edge correction for polygonal windows has changed slightly. Results are believed to be more accurate. Computation has been accelerated by about 20 percent in typical cases. \end{itemize} \item \texttt{Kest.fft}: Now has \verb!...! arguments allowing control of spatial resolution. \item \texttt{Kinhom}: \begin{itemize} \item New argument \texttt{ratio}. \item Stops gracefully if \texttt{lambda} contains any zero values. \item Leave-one-out calculation is implemented when \texttt{lambda} is a fitted model of class \texttt{"dppm"}. \end{itemize} \item \texttt{kppm}: \begin{itemize} \item New default settings ensure greater numerical stability of the optimization algorithm against the effects of the scale of the spatial coordinates. New argument \texttt{stabilize} specifies whether the optimization algorithm should be numerically stabilized. \item Fitting a model with \texttt{clusters="LGCP"} no longer requires the package \pkg{RandomFields} to be loaded explicitly. \item New argument \texttt{algorithm} specifies the choice of optimisation algorithm. \item Left hand side of formula can now involve entries in the list \texttt{data}. \item refuses to fit a log-Gaussian Cox model with anisotropic covariance. \item A warning about infinite values of the summary function no longer occurs when the default settings are used. Also affects \texttt{mincontrast}, \texttt{cauchy.estpcf}, \texttt{lgcp.estpcf}, \texttt{matclust.estpcf}, \texttt{thomas.estpcf}, \texttt{vargamma.estpcf}. \item Changed precedence rule for handling the algorithm parameters in the minimum contrast algorithm. Individually-named arguments \texttt{q,p,rmax,rmin} now take precedence over entries with the same names in the list \texttt{ctrl}. \item Improved printed output. \item Improved numerical robustness. \end{itemize} %%L \item \texttt{latest.news}: Now prints news documentation for the current major version, by default. New argument \texttt{major}. \item \texttt{Lcross.inhom}, \texttt{Ldot.inhom}: These functions now allow intensity values to be given by a fitted point process model. New arguments \texttt{update}, \texttt{leaveoneout}, \texttt{lambdaX}. \item \texttt{lengths.psp}: \begin{itemize} \item New argument \texttt{squared}. \item This function will soon be Deprecated in favour of the new name \verb!lengths_psp!. \end{itemize} \item \texttt{Lest}, \texttt{Linhom}, \texttt{Ldot}, \texttt{Lcross}, \texttt{Ldot.inhom}, \texttt{Lcross.inhom}: These summary functions now have explicit argument \texttt{"correction"}. \item \texttt{leverage.ppm}: \begin{itemize} \item For Gibbs models, memory usage has been dramatically reduced, so the code can handle larger datasets and finer quadrature schemes. \item Increased the default resolution of the pixel images. Spatial resolution can now be controlled by the arguments \code{dimyx}, \code{eps}. \end{itemize} \item \texttt{leverage.ppm}, \texttt{influence.ppm}, \texttt{dfbetas.ppm}: \begin{itemize} \item These methods now work for models that were fitted by logistic composite likelihood (\texttt{method='logi'}). \item Computation has been vastly accelerated for models with Geyer interaction fitted using isotropic or translation edge corrections. \item Faster computation in many cases. \item Virtually all models and edge corrections are now supported, using a ``brute force'' algorithm. This can be slow in some cases. \end{itemize} \item \texttt{lineardisc}: \begin{itemize} \item New argument \texttt{add}. \item Default plotting behaviour has changed. \end{itemize} \item \texttt{linearK}, \texttt{linearpcf} and relatives: \\ \begin{itemize} \item substantially accelerated. \item ratio calculations are now supported. \item new argument \texttt{ratio}. \end{itemize} \item \texttt{linearKinhom}: new argument \texttt{normpower}. \item \texttt{linearKinhom}, \texttt{linearpcfinhom}: \begin{itemize} \item Changed behaviour when \texttt{lambda} is a fitted model. \item New arguments \texttt{update} and \texttt{leaveoneout}. \end{itemize} \item \texttt{linearpcf}: new argument \texttt{normpower}. \item \texttt{linim}: \begin{itemize} \item The image \texttt{Z} is now automatically restricted to the network. \item New argument \texttt{restrict}. \end{itemize} \item \texttt{linnet}: \begin{itemize} \item The internal format of a \texttt{linnet} (linear network) object has been changed. Existing datasets of class \texttt{linnet} are still supported. However, computation will be faster if they are converted to the new format. To convert a linnet object \texttt{L} to the new format, use \verb!L <- as.linnet(L)!. \item If the argument \texttt{edges} is given, then this argument now determines the ordering of the sequence of line segments. For example, the \texttt{i}-th row of \texttt{edges} specifies the \texttt{i}-th line segment in \texttt{as.psp(L)}. \item New argument \texttt{warn}. \item When argument \texttt{edges} is specified, the code now checks whether any edges are duplicated. \end{itemize} \item \texttt{lintess}: \begin{itemize} \item Argument \texttt{df} can be missing or \texttt{NULL}, resulting in a tesellation with only one tile. \item Tessellations can now have marks. New argument \texttt{marks}. \end{itemize} \item \texttt{localpcf}: New argument \texttt{rvalue}. \item \texttt{localpcfinhom}: \begin{itemize} \item New arguments \texttt{update}, \texttt{leaveoneout}, \texttt{rvalue}. \end{itemize} \item \texttt{logLik.ppm}: \begin{itemize} \item New argument \texttt{absolute}. \item The warning about pseudolikelihood (`log likelihood not available') is given only once, and is not repeated in subsequent calls, within a spatstat session. \end{itemize} \item \texttt{logLik.mppm}: new argument \texttt{warn}. \item \texttt{lohboot}: \begin{itemize} \item Algorithm has been corrected and extended thanks to Christophe Biscio and Rasmus Waagepetersen. \item New arguments \texttt{block}, \texttt{basicboot}, \texttt{Vcorrection}. \item Accelerated when the window is a rectangle. \item Now works for multitype $K$ functions \texttt{Kcross}, \texttt{Kdot}, \texttt{Lcross}, \texttt{Ldot}, \texttt{Kcross.inhom}, \texttt{Lcross.inhom} \item Confidence bands for \texttt{Lest}, \texttt{Linhom}, \texttt{Lcross}, \texttt{Ldot}, \texttt{Lcross.inhom} are now computed differently. First a confidence band is computed for the corresponding $K$ function \texttt{Kest}, \texttt{Kinhom}, \texttt{Kcross}, \texttt{Kdot}, \texttt{Kcross.inhom} respectively. Then this is transformed to a confidence band for the $L$ function by applying the square root transformation. \end{itemize} \item \texttt{lpp}: \begin{itemize} \item The internal format of an \texttt{lpp} object has been changed. Existing datasets of class \texttt{lpp} are still supported. However, computation will be faster if they are converted to the new format. To convert an \texttt{lpp} object \texttt{X} to the new format, use \verb!X <- as.lpp(X)!. \item \texttt{X} can be missing or \texttt{NULL}, resulting in an empty point pattern. \item Now handles the case where coordinates \texttt{seg} and \texttt{tp} are given but \texttt{x} and \texttt{y} are missing. \end{itemize} \item \texttt{lppm}: \begin{itemize} \item New argument \texttt{random} controls placement of dummy points. \item Computation accelerated. \end{itemize} \item \texttt{lurking.ppm}: accelerated. \item \texttt{lut}: argument \texttt{outputs} may have length 1, representing a lookup table in which all data values are mapped to the same output value. %%M \item \texttt{markconnect}: Accepts the argument \texttt{weights} which is passed to \texttt{markcorr}. \item \texttt{markcorr}: New argument \texttt{weights} allows computation of the weighted version of the mark correlation function. Weights can be an expression to be evaluated, or a function, or a pixel image, or a numeric vector. \item \texttt{markvario}: Accepts the argument \texttt{weights} which is passed to \texttt{markcorr}. \item \texttt{mincontrast}: New argument \texttt{action.bad.values} specifies what action is taken when the summary function produces \texttt{NA} or \texttt{NaN} or infinite values. \item \texttt{minnndist}, \texttt{maxnndist}: New argument \texttt{by} makes it possible to find the minimum or maximum nearest neighbour distance between each pair of possible types in a multitype pattern. \item \texttt{mppm}: \begin{itemize} \item Now handles models with a random effect component. (This is covered in \cite[Chap.\ 16]{baddrubaturn15}.) \item New argument \texttt{random} is a formula specifying the random effect. (This is covered in \cite[Chap.\ 16]{baddrubaturn15}.) \item Performs more checks for consistency of the input data. \item New arguments \texttt{gcontrol} and \texttt{reltol.pql} control the fitting algorithm. \item New argument \texttt{weights} specifies case weights for each row of data. \end{itemize} \item \texttt{msr}: Infinite and \texttt{NA} values are now detected (if \texttt{check=TRUE}) and are reset to zero, with a warning. %%N \item \texttt{nbfires}: \begin{itemize} \item the unit of length for the coordinates is now specified in this dataset. \item This dataset now includes information about the different land and sea borders of New Brunswick. \end{itemize} \item \texttt{nncorr,nnmean,nnvario}: New argument \texttt{na.action}. \item \texttt{nncross.lpp}: \begin{itemize} \item New argument \texttt{k} allows computation of $k$-th nearest point. \item Computation accelerated. \end{itemize} \item \texttt{nndist.pp3}: New argument \texttt{by} allows computation of the nearest distance to each group of points. \item \texttt{nndist.ppx}: New argument \texttt{by} allows computation of the nearest distance to each group of points. \item \texttt{nndist.lpp}: \begin{itemize} \item New argument \texttt{k} allows computation of $k$-th nearest point. \item new argument \texttt{by} allows computation of the nearest distance to each group of points. \item Computation accelerated. \end{itemize} \item \texttt{nnwhich.lpp}: \begin{itemize} \item New argument \texttt{k} allows computation of $k$-th nearest point. \item new argument \texttt{by} allows computation of the nearest distance to each group of points. \item Computation accelerated. \end{itemize} \texttt{nnfun.lpp}: \begin{itemize} \item New argument \texttt{k}. \item New argument \texttt{value} specifies whether to return the index of the nearest neighbour or the mark value of the nearest neighbour. \end{itemize} \texttt{nnfun.ppp}: \begin{itemize} \item New argument \texttt{value} specifies whether to return the index of the nearest neighbour or the mark value of the nearest neighbour. \end{itemize} \texttt{nnfun.psp}: \begin{itemize} \item New argument \texttt{value} specifies whether to return the index of the nearest neighbour or the mark value of the nearest neighbour. \end{itemize} %%O \item \texttt{owin}: If argument \texttt{mask} is a logical matrix, \texttt{NA} entries will be accepted, and converted to \texttt{FALSE}. %%P \item \texttt{padimage}: New argument \texttt{W} allows an image to be padded out to fill any window. \item \texttt{pairdist.lpp}: Now handles much larger networks, using the sparse representation of the network. \item \texttt{pairorient}: Default edge corrections now include \texttt{"bord.modif"}. \item \texttt{pairs.im}: new argument \texttt{drop}. \item \texttt{parres}: the argument \texttt{covariate} is allowed to be missing if the model only depends on one covariate. \item \texttt{pcf.ppp}: \begin{itemize} \item New argument \code{close} for advanced use. \item New argument \texttt{ratio} allows several estimates of pcf to be pooled. \item Now calculates an analytic approximation to the variance of the estimate of the pair correlation function (when \texttt{var.approx=TRUE}). \item Now returns the smoothing bandwidth used, as an attribute of the result. \item New argument \texttt{close} for advanced use. \item Now accepts \texttt{correction="none"}. \end{itemize} \item \texttt{pcfinhom}: \begin{itemize} \item New argument \code{close} for advanced use. \item Default behaviour is changed when \texttt{lambda} is a fitted model. The default is now to re-fit the model to the data before computing pcf. New arguments \texttt{update} and \texttt{leaveoneout} control this. \item New argument \texttt{close} for advanced use. \item Now handles \texttt{correction="good"} \item Leave-one-out calculation is implemented when \texttt{lambda} is a fitted model of class \texttt{"dppm"}. \end{itemize} \item \code{persp.funxy}: Improved $z$-axis label. \item \texttt{pixellate.ppp}: \begin{itemize} \item If the pattern is empty, the result is an integer-valued image (by default) for consistency with the results for non-empty patterns. \item Accelerated in the case where weights are given. \item New arguments \texttt{fractional} and \texttt{preserve} for more accurate discretisation. \item New argument \texttt{savemap}. \end{itemize} \item \texttt{plot.anylist}: \begin{itemize} \item If a list entry \verb!x[[i]]! belongs to class \texttt{"anylist"}, it will be expanded so that each entry \verb!x[[i]][[j]]! will be plotted as a separate panel. \item New arguments \texttt{panel.begin.args}, \texttt{panel.end.args} \item Result is now an (invisible) list containing the result from executing the plot of each panel. \end{itemize} \item \texttt{plot.colourmap}: \begin{itemize} \item Now handles a colour map for a zero-length interval [a,a] \item New argument \texttt{increasing} specifies whether the colours are displayed in order left-to-right/bottom-to-top. \item Changed default behaviour for discrete colour maps when \texttt{vertical=FALSE}. \end{itemize} \item \texttt{plot.im}: \begin{itemize} \item Now handles complex-valued images. \item New argument \texttt{workaround} to avoid a bug in some MacOS device drivers that causes the image to be displayed in the wrong spatial orientation. \item The number of tick marks in the colour ribbon can now be controlled using the argument \texttt{nint} in \texttt{ribargs}. \item Improved behaviour when all pixel values are \texttt{NA}. \item Improved handling of tickmarks on colour ribbon. \item Improved behaviour when the image values are almost constant. \item New argument \texttt{riblab}. \item Axes are prevented from extending outside the image rectangle. \item New argument \texttt{zap}. \item Some warnings are suppressed when \texttt{do.plot=FALSE}. \end{itemize} \item \texttt{plot.imlist}: Result is now an (invisible) list containing the result from executing the plot of each panel. \item \texttt{plot.influence.ppm}: New argument \texttt{multiplot}. \item \texttt{plot.kppm}: \begin{itemize} \item New arguments \texttt{pause} and \texttt{xname}. \item The argument \texttt{what="all"} is now recognised: it selects all the available options. [This is also the default.] \end{itemize} \item \texttt{plot.leverage.ppm}: \begin{itemize} \item New arguments \texttt{multiplot} and \code{what}. \item A contour line showing the average value of leverage is now drawn on the colour ribbon, as well as on the main image. New argument \texttt{args.contour}. \end{itemize} \item \texttt{plot.linfun}: \begin{itemize} \item Now passes arguments to the function being plotted. \item A scale bar is now plotted when \texttt{style="width"}. \item New argument \texttt{legend}. \item The return value has a different format. \end{itemize} \item \texttt{plot.linim}: \begin{itemize} \item The return value has a different format. \item New argument \texttt{fatten} improves visual appearance when \texttt{style="colour"}. \item A scale bar is now plotted when \texttt{style="width"}. \item When \texttt{style="width"}, negative values are plotted in red (by default). New argument \texttt{negative.args} controls this. \item New argument \texttt{zlim} specifies the range of values to be mapped. \item New explicit argument \texttt{box} determines whether to plot a bounding box; default is \texttt{FALSE} in all cases. \end{itemize} \item \texttt{plot.lintess}: \begin{itemize} \item Improved plot method, with more options. \item Modified to display the marks attached to the tiles. \item Options: \verb!style=c("colour", "width", "image")!. \end{itemize} \item \texttt{plot.lpp}: \begin{itemize} \item New argument \texttt{show.network}. \item For a point pattern with continuous marks (``real numbers'') the colour arguments \texttt{cols}, \texttt{fg}, \texttt{bg} can now be vectors of colour values, and will be used to determine the default colour map for the marks. \end{itemize} \item \texttt{plot.mppm}: New argument \texttt{se}. \item \texttt{plot.msr}: \begin{itemize} \item Now handles multitype measures. \item New argument \texttt{multiplot}. \item New argument \texttt{massthresh}. \item New arguments \texttt{equal.markscale} and \texttt{equal.ribbon}. \end{itemize} \item \texttt{plot.onearrow:} Graphical parameters, specified when the object was created, are now taken as the defaults for graphical parameters to the plot. \item \texttt{plot.owin:} New argument \texttt{use.polypath} controls how to plot a filled polygon when it has holes. \item \texttt{plot.profilepl}: This function has now been documented, and the graphics improved. \item \texttt{plot.psp}: \begin{itemize} \item Segments can be plotted with widths proportional to their mark values. \item New argument \texttt{style}. \item New argument \texttt{col} gives control over the colour map representing the values of marks attached to the segments. \item The code for \texttt{style="width"} has been completely rewritten, so that it no longer depends on \texttt{plot.linim}, and is much more efficient. \item The formal argument list has been extended. \end{itemize} \item \texttt{plot.pp3}: New arguments \texttt{box.front}, \texttt{box.back} control plotting of the box. \item \texttt{plot.ppp}: \begin{itemize} \item The default colour for the points is now a transparent grey, if this is supported by the plot device. \item For a point pattern with continuous marks (``real numbers'') the colour arguments \texttt{cols}, \texttt{fg}, \texttt{bg} can now be vectors of colour values, and will be used to determine the default colour map for the marks. \item Now recognises graphics parameters for text, such as \texttt{family} and \texttt{srt} \item When \texttt{clipwin} is given, any parts of the boundary of the window of \texttt{x} that lie inside \texttt{clipwin} will also be plotted. \item Improved placement of symbol map legend when argument \texttt{symap} is given. \end{itemize} \item \code{plot.tess}: \begin{itemize} \item This plot method can now fill each tile with a different colour. \item New arguments \code{do.col}, \code{values}, \code{col} and \code{ribargs}. Old argument \code{col} has been renamed \code{border} for consistency. \item Now generates a separate plot panel for each column of marks, if \texttt{do.col=TRUE}. \item New argument \texttt{multiplot}. \end{itemize} \item \texttt{plot.profilepl} ,\texttt{plot.quadratcount}, \texttt{plot.quadrattest}, \texttt{plot.tess}: Now recognise graphics parameters for text, such as \texttt{family} and \texttt{srt} \item \texttt{plot.solist}: \begin{itemize} \item New arguments \texttt{panel.begin.args}, \texttt{panel.end.args} \item Result is now an (invisible) list containing the result from executing the plot of each panel. \end{itemize} \item \texttt{plot.studpermutest}: This existing function now has a help file. \item \texttt{plot.symbolmap}: New argument \texttt{nsymbols} controls the number of symbols plotted. \item \code{ponderosa}: In this installed dataset, the function \code{ponderosa.extra\$plotit} has changed slightly (to accommodate the dependence on the package \pkg{spatstat.utils}). \item \texttt{polynom}: This function now has a help file. \item \texttt{pool.fv}: \begin{itemize} \item The default plot of the pooled function no longer includes the variance curves. \item New arguments \texttt{relabel} and \texttt{variance}. \end{itemize} \item \texttt{pool.rat}: New arguments \texttt{weights}, \texttt{relabel} and \texttt{variance}. \item \texttt{ppm}: \begin{itemize} \item Argument \code{interaction} can now be a function that makes an interaction, such as \code{Poisson}, \code{Hardcore}, \code{MultiHard}. \item Argument \texttt{subset} can now be a window (class \texttt{"owin"}) specifying the sub-region of data to which the model should be fitted. \end{itemize} \item \texttt{ppm.ppp, ppm.quad}: \begin{itemize} \item New argument \texttt{emend}, equivalent to \texttt{project}. \item New arguments \texttt{subset} and \texttt{clipwin}. \end{itemize} \item \code{ppmInfluence}: The result now belongs to class \code{ppmInfluence}, for which there are methods for \code{leverage}, \code{influence}, \code{dfbetas} which extract the desired component. \item \texttt{ppp}: \begin{itemize} \item New argument \texttt{checkdup}. \item If the coordinate vectors \code{x} and \code{y} contain \code{NA}, \code{NaN} or infinite values, these points are deleted with a warning, instead of causing a fatal error. \end{itemize} \item \texttt{pp3}: New argument \texttt{marks}. \item \texttt{predict.kppm, residuals.kppm} Now issues a warning when the calculation ignores the cluster/Cox component and treats the model as if it were Poisson. (This currently happens in predict.kppm when se=TRUE or interval != "none", and in residuals.kppm when type != "raw"). \item \texttt{predict.lppm}: Argument \texttt{locations} can now be an \texttt{lpp} object. \item \texttt{predict.mppm}: \begin{itemize} \item The argument \texttt{type="all"} is now recognised: it selects all the available options. [This is also the default.] \item Now supports multitype point process models. \item Improved handling of argument \texttt{newdata}. \end{itemize} \item \texttt{predict.ppm}: \begin{itemize} \item Now recognises the arguments \code{dimyx} and \code{eps} for specifying the resolution of the grid of prediction points. \item New argument \code{ignore.hardcore}. \item Accelerated for models fitted with \texttt{method="VBlogi"} \end{itemize} \item \texttt{predict.rhohat}: New argument \texttt{what} determines which value should be calculated: the function estimate, the upper/lower confidence limits, or the standard error. \item \texttt{print.linim}: More information is printed. \item \texttt{print.lintess}: Output includes information about marks. \item \texttt{print.quad}: More information is printed. \item \texttt{print.rmhmodel}: More information is printed. \item \texttt{progressreport} \begin{itemize} \item Behaviour improved. \item New arguments \texttt{state}, \texttt{tick}, \texttt{showtime}. \item New option: \verb!style="tk"! \end{itemize} \item \code{pseudoR2.ppm}, \code{pseudoR2.lppm}: \begin{itemize} \item The null model now includes any offset terms, by default. \item New argument \code{keepoffset}. \end{itemize} %%Q \item \texttt{quadform}: This function has been moved to the sub-package \texttt{spatstat.sparse}. \item \texttt{quadratcount.ppp}: Computation accelerated in some cases. \item \texttt{quadrat.test.ppm}: Computation accelerated in some cases. \item \texttt{quantess}: \begin{itemize} \item The covariate \texttt{Z} can now be \texttt{"rad"} or \texttt{"ang"} representing polar coordinates. \item New argument \texttt{origin} specifies the origin of polar coordinates. \item New argument \texttt{eps} controls the accuracy of the calculation. \end{itemize} \item \texttt{quantile.ewcdf}: The function is now normalised to the range \verb![0,1]! before the quantiles are computed. This can be suppressed by setting \texttt{normalise=FALSE}. \item \texttt{qqplot.ppm} Argument \texttt{expr} can now be a list of point patterns, or an envelope object containing a list of point patterns. %%R \item \texttt{rbind.hyperframe}: The result now retains the \texttt{row.names} of the original arguments. \item \texttt{rcellnumber}: New argument \texttt{mu}. \item \texttt{rebound.owin}: Now preserves unitnames of the objects. \item \texttt{rescale.owin}, \texttt{rescale.ppp}, \texttt{rescale.psp}: The geometrical type of the window is now preserved in all cases. (Previously if the window was polygonal but was equivalent to a rectangle, the rescaled window was a rectangle.) \item \texttt{rgbim, hsvim}: New argument \texttt{A} controls the alpha (transparency) channel. \item \texttt{rgb2hex, col2hex, paletteindex, is.colour, samecolour,} \texttt{complementarycolour, is.grey, to.grey} These colour tools now handle transparent colours. \item \texttt{rgb2hex}: New argument \texttt{maxColorValue} \item \texttt{relrisk.ppp}: \begin{itemize} \item If \texttt{se=TRUE} and \texttt{at="pixels"}, the result belongs to class \texttt{solist}. \item The arguments \texttt{adjust}, \texttt{edge}, \texttt{diggle} are now explicit formal arguments. \item New argument \texttt{weights}. \end{itemize} \texttt{rhohat}: \begin{itemize} \item The result now includes the ``average'' intensity $\overline\rho$. \item New options \texttt{smoother="piecewise"} computes a piecewise-constant estimate of $\rho(z)$. \item Nonparametric maximum likelihood estimation is now supported, assuming the intensity is a monotone function of the covariate. \item New options \texttt{smoother="increasing"} and \texttt{smoother="decreasing"}. \item New argument \texttt{subset} allows computation for a subset of the data. \item New argument \texttt{positiveCI} specifies whether confidence limits should always be positive. \end{itemize} \texttt{rhohat.lpp}: New argument \texttt{random} controls placement of dummy points. \item \texttt{rlabel}: \begin{itemize} \item New argument \texttt{group} specifies that the points are divided into several groups, and that relabelling is applied within each group. \item New arguments \texttt{nsim} and \texttt{drop}. \item \texttt{X} can now be a point pattern of any type (\texttt{ppp}, \texttt{lpp}, \texttt{pp3}, \texttt{ppx}) or a line segment pattern (\texttt{psp}). \end{itemize} \item \texttt{rlabel.ppp}: New argument \texttt{group} specifies that the points are divided into several groups, and that relabelling is applied within each group. \item \texttt{rLGCP}: \begin{itemize} \item Accelerated. \item This function no longer requires the package \pkg{RandomFields} to be loaded explicitly. \end{itemize} \item \texttt{rMaternI, rMaternII}: These functions can now generate random patterns in three dimensions and higher dimensions, when the argument \texttt{win} is of class \texttt{box3} or \texttt{boxx}. \item \texttt{rmh}: \begin{itemize} \item Accelerated, in the case where multiple patterns are saved using \texttt{nsave}. \item The printed output of the debugger (invoked by \texttt{snoop=TRUE}) has been improved. \end{itemize} \item \texttt{rmh.ppm, rmhmodel.ppm, simulate.ppm}: A model fitted using the \texttt{Penttinen} interaction can now be simulated. \item \texttt{rmh.default, rmhmodel.default}: \begin{itemize} \item These functions now recognise \verb!cif='penttinen'! for the Penttinen interaction. \item New arguments \texttt{nsim}, \texttt{saveinfo}. \item The printed output of the debugger (invoked by \texttt{snoop=TRUE}) has been improved. \end{itemize} \item \texttt{rmhcontrol}: \begin{itemize} \item New parameter \texttt{pstage} determines when to generate random proposal points. \item The parameter \texttt{nsave} can now be a vector of integers. \end{itemize} \item \texttt{rose.default} New argument \texttt{weights}. \item \texttt{rose} New arguments \texttt{start} and \texttt{clockwise} specify the convention for measuring and plotting angles. \item \texttt{rotmean}: \begin{itemize} \item New argument \texttt{padzero}. \item Default behaviour has changed. \item Improved algorithm stability. \item The result now has the same \texttt{unitname} as the input object. \item New argument \texttt{adjust} controls the smoothing bandwidth. \end{itemize} \item \texttt{rpoint}: New argument \texttt{forcewin} forces the code to use the window \texttt{win} when \texttt{f} is a pixel image. \item \texttt{rpoispp}: Accelerated, when \texttt{lambda} is a pixel image. \item \texttt{rpoisppx}: New argument \code{drop}. \item \texttt{rpoisline}: Also returns information about the original infinite random lines. \item \texttt{rpoislpp}: If \texttt{lambda} is a list of \texttt{"linim"} or \texttt{"linfun"} objects, then the argument \texttt{L} can be omitted. \item \texttt{rshift.ppp}, \texttt{rshift.splitppp}: new argument \texttt{nsim}. \item \texttt{rSSI}: Accelerated. \item \texttt{rStrauss, rHardcore, rStraussHard, rDiggleGratton, rDGS, rPenttinen:} New argument \texttt{drop}. \item \texttt{rtemper:} new argument \texttt{track}. \item \texttt{rthin} \begin{itemize} \item Accelerated, when \texttt{P} is a single number. \item \texttt{X} can now be a point pattern of any type (\texttt{ppp}, \texttt{lpp}, \texttt{pp3}, \texttt{ppx}) or a line segment pattern (\texttt{psp}). \end{itemize} \item \texttt{rThomas, rMatClust, rCauchy, rVarGamma}: \begin{itemize} \item When the model is approximately Poisson, it is simulated using rpoispp. This avoids computations which would require huge amounts of memory. New argument \texttt{poisthresh} controls this behaviour. \item New argument \texttt{saveparents}. \end{itemize} \item \texttt{runifpointOnLines}, \texttt{rpoisppOnLines}: New argument \code{drop}. \item \texttt{runifpointx}: New argument \code{drop}. %%S \item \texttt{selfcut.psp}: \begin{itemize} \item Computation accelerated. \item The result now has an attribute \texttt{"camefrom"} indicating the provenance of each segment in the result. \item No longer checks for validity of the resulting segments. \end{itemize} \item \texttt{sessionInfo}: Output now includes a list of packages that are imported but not loaded. \item \texttt{sessionLibs}: Package names are now sorted alphabetically \item \texttt{setcov}: the name of the unit of length is preserved. \item \code{shapley}: In this installed dataset, the function \code{shapley.extra\$plotit} has changed slightly (to accommodate the dependence on the package \pkg{spatstat.utils}). \item \texttt{shift.im}, \texttt{shift.owin}, \texttt{shift.ppp}, \texttt{shift.psp}: More options for the argument \texttt{origin}. \item Simulation: Several basic simulation algorithms have been accelerated. Consequently, simulation outcomes are not identical to those obtained with previous versions of \spst, even when the same random seed is used. To ensure compatibility with previous versions of spatstat, revert to the slower code by setting \texttt{spatstat.options(fastthin=FALSE, fastpois=FALSE)}. \item \texttt{simulate.kppm}: \begin{itemize} \item Conditional simulation of the model, given a fixed number of points, is now supported using the new arguments \texttt{n.cond} and \texttt{w.cond}. \item Accelerated for LGCP models. \item Additional arguments \verb!...! are now passed to the function that performs the simulation. \end{itemize} \item \texttt{simulate.ppm}: \begin{itemize} \item New argument \texttt{w} controls the window of the simulated patterns. \item New argument \texttt{verbose}. \item Now recognises the argument \texttt{window} as an alternative to \texttt{w}. \end{itemize} \item \texttt{slrm}: \begin{itemize} \item In the default case (where \texttt{dataAtPoints} is not given) all spatial covariates, including the spatial coordinates \texttt{x} and \texttt{y}, are now evaluated at the centre of each pixel. This improves consistency with other implementations of spatial logistic regression. \item Silently ignores any arguments \verb!'...'! that are not recognised by \texttt{as.mask} \end{itemize} \item \texttt{Smooth.ppp}: \begin{itemize} \item A non-Gaussian kernel can now be specified using the argument \texttt{kernel}. \item Argument \texttt{weights} can now be a pixel image, a function, a numeric vector or an expression to be evaluated. \item Infinite bandwidth \texttt{sigma=Inf} is supported. \item Accelerated by about 30\% in the case where \texttt{at="pixels"}. \item Accelerated by about 15\% in the case where \texttt{at="points"} and \texttt{kernel="gaussian"}. \item Now exits gracefully if any mark values are \texttt{NA}, \texttt{NaN} or \texttt{Inf}. \item New argument \texttt{geometric} supports geometric-mean smoothing. \item The arguments \texttt{adjust}, \texttt{edge}, \texttt{diggle} and \texttt{kernel} are now explicit formal arguments. \end{itemize} \item \texttt{solist}: New argument \verb!.NameBase! \item \texttt{spatialcdf}: \begin{itemize} \item Computation accelerated. \item The result does not inherit class \texttt{"ecdf"} if \texttt{normalise=FALSE}. \end{itemize} \item \texttt{spatstat.options} New options \texttt{fastthin} and \texttt{fastpois} enable fast simulation algorithms. Set these options to \texttt{FALSE} to reproduce results obtained with previous versions of \spst. \item \texttt{split.ppp}, \texttt{split.ppx}: The splitting variable \texttt{f} can now be a logical vector. \item \verb!split<-.ppp!: The default for argument \texttt{un} in \verb!split<-.ppp! now agrees with the default for the same argument in \texttt{split.ppp}. \item \texttt{square}: Handles a common error in the format of the arguments. \item \texttt{step}: now works for models of class \texttt{"mppm"}. \item \texttt{stieltjes}: Argument \texttt{M} can be a stepfun object (such as an empirical CDF). \item \texttt{subset.ppp}, \texttt{subset.lpp}, \texttt{subset.pp3}, \texttt{subset.ppx}: The argument \texttt{subset} can now be any argument acceptable to the \verb!"["! method. \item \texttt{Summary.linim} (methods for the operations \texttt{range}, \texttt{max}, \texttt{min} etc): Recognises the argument \texttt{finite} so that \texttt{range(x, finite=TRUE)} works for a linim object \texttt{x}. \item summary functions: The argument \texttt{correction="all"} is now recognised: it selects all the available options. \begin{quote} This applies to \texttt{Fest}, \texttt{F3est}, \texttt{Gest}, \texttt{Gcross}, \texttt{Gdot}, \texttt{Gmulti}, \texttt{G3est}, \texttt{Gfox}, \texttt{Gcom}, \texttt{Gres}, \texttt{Hest}, \texttt{Jest}, \texttt{Jmulti}, \texttt{Jcross}, \texttt{Jdot}, \texttt{Jfox}, \texttt{Kest}, \texttt{Kinhom}, \texttt{Kmulti}, \texttt{Kcross}, \texttt{Kdot}, \texttt{Kcom}, \texttt{Kres}, \texttt{Kmulti.inhom}, \texttt{Kcross.inhom}, \texttt{Kdot.inhom}, \texttt{Kscaled}, \texttt{Ksector}, \texttt{Kmark}, \texttt{K3est}, \texttt{Lscaled}, \texttt{markcorr}, \texttt{markcrosscorr}, \texttt{nnorient}, \texttt{pairorient}, \texttt{pcfinhom}, \texttt{pcfcross.inhom}, \texttt{pcfcross}, \texttt{pcf}, \texttt{Tstat}. \end{quote} \item \texttt{summary.distfun}, \texttt{summary.funxy}: \begin{itemize} \item More information is printed. \item Pixel resolution can now be controlled. \end{itemize} \item \texttt{summary.im}: Output improved when the image is empty (i.e. when all pixel values are undefined). \item \texttt{summary.kppm}: prints more information about algorithm convergence. \item \texttt{summary.lintess}: prints information about marks. \item \texttt{summary.mppm}: Improved summary of the dependence of the interpoint interaction on the covariates. \item \texttt{summary.ppm}: New argument \texttt{fine} selects the algorithm for variance estimation. \item \texttt{summary.owin}, \texttt{summary.im}: The fraction of frame area that is occupied by the window/image is now reported. \item \texttt{sumouter}: \begin{itemize} \item New argument \texttt{y} allows computation of asymmetric outer products. \item This function has now been moved to the sub-package \texttt{spatstat.sparse} \end{itemize} \item \texttt{symbolmap}: \begin{itemize} \item Now accepts a vector of colour values for the arguments \texttt{col}, \texttt{cols}, \texttt{fg}, \texttt{bg} if the argument \texttt{range} is given. \item New option: \texttt{shape="arrows"}. \end{itemize} %%T \item \texttt{tess}: Argument \texttt{window} is ignored when xgrid, ygrid are given. \item \texttt{texturemap}: Argument \texttt{textures} can be missing or NULL. \item \texttt{textureplot}: Argument \texttt{x} can now be something acceptable to \texttt{as.im}. \item \texttt{tilenames}, \verb!tilenames<-!: These functions are now generic, with methods for \texttt{tess} and \texttt{lintess}. \item \texttt{to.grey} New argument \texttt{transparent}. \item \texttt{transect.im}: new argument \texttt{nsample}. %%U \item \texttt{union.owin}: Improved behaviour when there are more than 2 windows. \item \texttt{unstack.lintess}: now handles marks. \item \texttt{update}: now works for models of class \texttt{"mppm"}. \item \texttt{update.kppm}: \begin{itemize} \item New argument \texttt{evaluate}. \item Now handles additional arguments in any order, with or without names. \item Changed arguments. \item Improved behaviour. \end{itemize} \item \texttt{update.ppm}: For the case \texttt{update(model, X)} where \texttt{X} is a point pattern, if the window of \texttt{X} is different from the original window, then the model is re-fitted from scratch (i.e. \texttt{use.internal=FALSE}). %%V \item \texttt{valid.ppm} This is now a method for the generic function \texttt{valid}. \item \texttt{vcov.mppm}: \begin{itemize} \item Now handles models with Gibbs interactions. \item New argument \texttt{nacoef.action} specifies what to do if some of the fitted coefficients are \texttt{NA}, \texttt{NaN} or \texttt{Inf}. \end{itemize} \item \texttt{vcov.ppm}: \begin{itemize} \item Performance slightly improved, for Gibbs models. \item Variance calculations now handle larger datasets because they use sparse arrays, by default. \item New argument \texttt{nacoef.action} specifies what to do if some of the fitted model coefficients are \texttt{NA}, \texttt{NaN} or infinite. \end{itemize} %%W %%X %%Y %%Z \item \verb![<-.im! \begin{itemize} \item Accepts an array for \texttt{value}. \item The subset index \texttt{i} can now be a linear network. Then the result of \verb!x[i, drop=FALSE]! is a pixel image of class \texttt{linim}. \item New argument \texttt{drop} controls behaviour when indices are missing as in \verb!x[] <- value! \end{itemize} \item \verb![.layered!: \begin{itemize} \item Subset index \texttt{i} can now be an \texttt{owin} object. \item Additional arguments \verb!...! are now passed to other methods. \end{itemize} \item \verb![.leverage.ppm!: New argument \texttt{update}. \item \verb![.linnet!: \begin{itemize} \item New argument \texttt{snip} determines what to do with segments of the network that cross the boundary of the window. Default behaviour has changed. \item More robust against artefacts when the subset index is a pixel mask. \end{itemize} \item \verb![.linim!: \begin{itemize} \item More robust against artefacts. \item Accelerated. \end{itemize} \item \verb![.lpp!: New argument \texttt{snip} determines what to do with segments of the network that cross the boundary of the window. Default behaviour has changed. \item \verb![.ppx!: \begin{itemize} \item The subset index \texttt{i} may now be a spatial domain of class \texttt{boxx} or \texttt{box3}. \item New argument \texttt{clip}. \end{itemize} \item \verb![.ppp! New argument \texttt{clip} determines whether the window is clipped. \item \verb![.ppp! The previously-unused argument \texttt{drop} now determines whether to remove unused levels of a factor. \item \verb![.pp3!, \verb![.lpp!, \verb![.ppx!, \texttt{subset.ppp, subset.pp3, subset.lpp, subset.ppx}: These methods now have an argument \texttt{drop} which determines whether to remove unused levels of a factor. \item \verb![.psp!: \begin{itemize} \item accelerated. \item New argument \texttt{fragments} specifies whether to keep fragments of line segments that are cut by the new window, or only to retain segments that lie entirely inside the window. \end{itemize} \item \verb![.solist!: Subset index \texttt{i} can now be an \texttt{owin} object. \end{itemize} \begin{thebibliography}{1} \bibitem{badd10wshop} A.~Baddeley. \newblock Analysing spatial point patterns in {{R}}. \newblock Technical report, CSIRO, 2010. \newblock Version 4. \newblock URL \texttt{https://research.csiro.au/software/r-workshop-notes/} \bibitem{baddrubaturn15} A. Baddeley, E. Rubak, and R. Turner. \newblock {\em Spatial Point Patterns: Methodology and Applications with {{R}}}. \newblock Chapman \& Hall/CRC Press, 2015. \end{thebibliography} \end{document} spatstat/vignettes/mask.eps0000644000176200001440000001077314141460522015600 0ustar liggesusers%!PS-Adobe-3.0 %%DocumentNeededResources: font Helvetica %%+ font Helvetica-Bold %%+ font Helvetica-Oblique %%+ font Helvetica-BoldOblique %%+ font Symbol %%DocumentMedia: a4 595 841 0 () () %%Title: R Graphics Output %%Creator: R Software %%Pages: (atend) %%Orientation: Landscape %%BoundingBox: 46 61 550 781 %%EndComments %%BeginProlog /bp { gs sRGB 595.00 0 translate 90 rotate gs } def % begin .ps.prolog /gs { gsave } bind def /gr { grestore } bind def /ep { showpage gr gr } bind def /m { moveto } bind def /l { rlineto } bind def /np { newpath } bind def /cp { closepath } bind def /f { fill } bind def /o { stroke } bind def /c { newpath 0 360 arc } bind def /r { 4 2 roll moveto 1 copy 3 -1 roll exch 0 exch rlineto 0 rlineto -1 mul 0 exch rlineto closepath } bind def /p1 { stroke } bind def /p2 { gsave bg fill grestore newpath } bind def /p3 { gsave bg fill grestore stroke } bind def /p6 { gsave bg eofill grestore newpath } bind def /p7 { gsave bg eofill grestore stroke } bind def /t { 5 -2 roll moveto gsave rotate 1 index stringwidth pop mul neg 0 rmoveto show grestore } bind def /ta { 4 -2 roll moveto gsave rotate show } bind def /tb { 2 -1 roll 0 rmoveto show } bind def /cl { grestore gsave newpath 3 index 3 index moveto 1 index 4 -1 roll lineto exch 1 index lineto lineto closepath clip newpath } bind def /rgb { setrgbcolor } bind def /s { scalefont setfont } bind def % end .ps.prolog /sRGB { [ /CIEBasedABC << /DecodeLMN [ { dup 0.03928 le {12.92321 div} {0.055 add 1.055 div 2.4 exp } ifelse } bind dup dup ] /MatrixLMN [0.412457 0.212673 0.019334 0.357576 0.715152 0.119192 0.180437 0.072175 0.950301] /WhitePoint [0.9505 1.0 1.0890] >> ] setcolorspace } bind def /srgb { setcolor } bind def %%IncludeResource: font Helvetica /Helvetica findfont dup length dict begin {1 index /FID ne {def} {pop pop} ifelse} forall /Encoding ISOLatin1Encoding def currentdict end /Font1 exch definefont pop %%IncludeResource: font Helvetica-Bold /Helvetica-Bold findfont dup length dict begin {1 index /FID ne {def} {pop pop} ifelse} forall /Encoding ISOLatin1Encoding def currentdict end /Font2 exch definefont pop %%IncludeResource: font Helvetica-Oblique /Helvetica-Oblique findfont dup length dict begin {1 index /FID ne {def} {pop pop} ifelse} forall /Encoding ISOLatin1Encoding def currentdict end /Font3 exch definefont pop %%IncludeResource: font Helvetica-BoldOblique /Helvetica-BoldOblique findfont dup length dict begin {1 index /FID ne {def} {pop pop} ifelse} forall /Encoding ISOLatin1Encoding def currentdict end /Font4 exch definefont pop %%IncludeResource: font Symbol /Symbol findfont dup length dict begin {1 index /FID ne {def} {pop pop} ifelse} forall currentdict end /Font5 exch definefont pop %%EndProlog %%Page: 1 1 bp 62.38 47.08 779.50 548.20 cl 0 0 0 srgb 0.75 setlinewidth [] 0 setdash 1 setlinecap 1 setlinejoin 10.00 setmiterlimit np 88.94 77.13 m 664.00 0 l o np 752.94 77.13 m 0 441.02 l o np 752.94 518.15 m -664.00 0 l o np 88.94 518.15 m 0 -441.02 l o /bg { 0 0 0 srgb } def 88.94 77.13 66.40 88.20 r p2 88.94 165.33 66.40 88.20 r p2 88.94 341.74 66.40 88.20 r p2 155.34 77.13 66.40 88.20 r p2 155.34 165.33 66.40 88.20 r p2 155.34 253.54 66.40 88.20 r p2 155.34 341.74 66.40 88.20 r p2 155.34 429.94 66.40 88.20 r p2 221.74 77.13 66.40 88.20 r p2 221.74 165.33 66.40 88.20 r p2 221.74 253.54 66.40 88.20 r p2 221.74 341.74 66.40 88.20 r p2 221.74 429.94 66.40 88.20 r p2 288.14 165.33 66.40 88.20 r p2 288.14 253.54 66.40 88.20 r p2 288.14 341.74 66.40 88.20 r p2 288.14 429.94 66.40 88.20 r p2 354.54 165.33 66.40 88.20 r p2 354.54 429.94 66.40 88.20 r p2 420.94 77.13 66.40 88.20 r p2 420.94 165.33 66.40 88.20 r p2 420.94 429.94 66.40 88.20 r p2 487.34 77.13 66.40 88.20 r p2 487.34 165.33 66.40 88.20 r p2 487.34 253.54 66.40 88.20 r p2 487.34 341.74 66.40 88.20 r p2 487.34 429.94 66.40 88.20 r p2 553.74 77.13 66.40 88.20 r p2 553.74 165.33 66.40 88.20 r p2 553.74 253.54 66.40 88.20 r p2 553.74 341.74 66.40 88.20 r p2 553.74 429.94 66.40 88.20 r p2 620.14 77.13 66.40 88.20 r p2 620.14 165.33 66.40 88.20 r p2 620.14 253.54 66.40 88.20 r p2 620.14 341.74 66.40 88.20 r p2 620.14 429.94 66.40 88.20 r p2 686.54 165.33 66.40 88.20 r p2 686.54 253.54 66.40 88.20 r p2 686.54 341.74 66.40 88.20 r p2 ep %%Trailer %%Pages: 1 %%EOF spatstat/vignettes/mask.pdf0000644000176200001440000001003314141460522015547 0ustar liggesusers%PDF-1.4 %ρ\r 1 0 obj << /CreationDate (D:20201125103512) /ModDate (D:20201125103512) /Title (R Graphics Output) /Producer (R 4.0.3) /Creator (R) >> endobj 2 0 obj << /Type /Catalog /Pages 3 0 R >> endobj 7 0 obj << /Type /Page /Parent 3 0 R /Contents 8 0 R /Resources 4 0 R >> endobj 8 0 obj << /Length 313 /Filter /FlateDecode >> stream x}N0E{|q[@Z %ZX+-)}b> endobj 4 0 obj << /ProcSet [/PDF /Text] /Font <<>> /ExtGState << >> /ColorSpace << /sRGB 5 0 R >> >> endobj 5 0 obj [/ICCBased 6 0 R] endobj 6 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~endstream endobj 9 0 obj << /Type /Encoding /BaseEncoding /WinAnsiEncoding /Differences [ 45/minus 96/quoteleft 144/dotlessi /grave /acute /circumflex /tilde /macron /breve /dotaccent /dieresis /.notdef /ring /cedilla /.notdef /hungarumlaut /ogonek /caron /space] >> endobj xref 0 10 0000000000 65535 f 0000000021 00000 n 0000000163 00000 n 0000000676 00000 n 0000000759 00000 n 0000000860 00000 n 0000000893 00000 n 0000000212 00000 n 0000000292 00000 n 0000003588 00000 n trailer << /Size 10 /Info 1 0 R /Root 2 0 R >> startxref 3845 %%EOF spatstat/vignettes/bugfixes.Rnw0000644000176200001440000010334714155341545016450 0ustar liggesusers\documentclass[11pt]{article} \usepackage{graphicx} \usepackage{Sweave} \usepackage{bm} \usepackage{anysize} \marginsize{2cm}{2cm}{2cm}{2cm} % \VignetteIndexEntry{Bugs Fixed in Spatstat} \newcommand{\pkg}[1]{\texttt{#1}} \newcommand{\code}[1]{\texttt{#1}} \newcommand{\R}{{\sf R}} \newcommand{\spst}{\pkg{spatstat}} \newcommand{\Spst}{\pkg{Spatstat}} \begin{document} \bibliographystyle{plain} <>= library(spatstat) sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") options(useFancyQuotes=FALSE) @ \title{Bugs fixed in \spst} \author{Adrian Baddeley, Rolf Turner and Ege Rubak} \date{For \spst\ version \texttt{\Sexpr{sversion}}} \maketitle \thispagestyle{empty} This vignette lists all \emph{important} bugs detected and fixed in the \spst\ package since 2010. It also explains how to search the list of all recorded bugs in the \spst\ famil of packages. <>= nbugs <- nrow(news(grepl("^BUG", Category), package="spatstat")) nbugssince <- nrow(news(Version > "1.42-0" & grepl("^BUG", Category), package="spatstat")) @ \tableofcontents \pagebreak \section{Bug history} Thousands of bugs have been detected and fixed in \spst\ since it was first released in 2001. We started recording the bug history in 2010. Bugs that may have affected the user are listed in the package \texttt{NEWS} file, and can be searched using the \R\ command \texttt{news} or the \spst\ command \texttt{bugfixes}. To see the bugs which have just been fixed in the latest version of \spst, type <>= bugfixes @ To see all bugs which were fixed after a particular version of \spst, for example, bugs that were fixed in version \texttt{1.50-0} or later, type <>= bugfixes(sinceversion="1.50-0") @ To see all bugs in \spst\ that were fixed after a particular date, for example 30 June 2017, type <>= bugfixes(sincedate="2017-06-30") @ To see all bugs fixed after the book \cite{baddrubaturn15} was written, type <>= bugfixes("book") @ To see all bugs in the entire recorded history of \spst, type <>= bugfixes("all") @ which currently produces a list of \Sexpr{nbugs} bugs, of which \Sexpr{nbugssince} were detected after publication of the book \cite{baddrubaturn15}. Recently \spst\ was divided into a family of sub-packages. The command \texttt{bugfixes} now covers the bug history in all of these sub-packages. See the help for \texttt{bugfixes} for further details. \pagebreak \section{Serious bugs} Following is a list of the {\bf most serious bugs}, in decreasing order of potential impact. A bug is classified as ``serious'' if it produced incorrect results without the user's knowledge. Bugs which cause an error exit are not listed here, because ' the presence of a bug is obvious, and the bug would not have misled the user. \newcommand\bugger[4]{% \\ {} % {\small (Bug introduced in \texttt{spatstat {#1}}, {#2}; % fixed in \texttt{spatstat {#3}}, {#4})}% } \newcommand\bugin[4]{% \\ {} % {\small (Bug introduced in \texttt{{#1}}, {#2}; % fixed in \texttt{{#3}}, {#4})}% } \newcommand\bugbefore[4]{% \\ {} % {\small (Bug introduced before \texttt{{#1}}, {#2}; % fixed in \texttt{{#3}}, {#4})}% } %%% LEVEL 1 \subsection{Serious Bugs, Always Wrong, Broad Impact} \begin{itemize} \item \texttt{nncross.ppp}: Results were completely incorrect if $k > 1$. \bugger{1.31-2}{april 2013}{1.35-0}{december 2013} \item \texttt{nncross.pp3}: Results were completely incorrect in some cases. \bugger{1.32-0}{august 2013}{1.34-0}{october 2013} \item \texttt{cdf.test.ppm}: Calculation of $p$-values was incorrect for Gibbs models: $1-p$ was computed instead of $p$. \bugger{1.40-0}{december 2014}{1.45-2}{may 2016} \item \texttt{Smooth.ppp}: Results of \verb!Smooth(X, at="points", leaveoneout=FALSE)! were completely incorrect. \bugger{1.20-5}{august 2010}{1.46-0}{july 2016} \item \texttt{rmh}: \begin{itemize} \item Simulation was completely incorrect in the case of a multitype point process with an interaction that does not depend on the marks, such as \verb!ppm(betacells, ~marks, Strauss(60))! due to a coding error in the \texttt{C} interface. \bugger{1.22-3}{march 2010}{1.22-3}{june 2011} \item Simulation of the Area-Interaction model was completely incorrect. \bugger{1.23-6}{october 2011}{1.31-0}{january 2013} \item Simulation of the Geyer saturation process was completely incorrect. \bugger{1.31-0}{january 2013}{1.31-1}{march 2013} \item Simulation of the Strauss-Hard Core process was partially incorrect, giving point patterns with a slightly lower intensity. \bugger{1.31-0}{january 2013}{1.37-0}{may 2014} \item Simulation of the \emph{multitype} hard core model was completely incorrect (the interaction was effectively removed, changing the model into a Poisson process). \bugger{1.31-0}{january 2013}{1.63-0}{january 2020} \item The result of simulating a model with a hard core did not necessarily respect the hard core constraint, and simulation of a model with strong inhibition did not necessarily converge. This only happened if the first order trend was large, the starting state (\texttt{n.start} or \texttt{x.start}) was not given, and the number of iterations \texttt{nrep} was not very large. It occurred because of a poor choice for the default starting state. {\small (Bug was present since about 2010. Fixed in \texttt{spatstat 1.40-0}, december 2014)} \item Simulation was incorrect in the case of an inhomogeneous multitype model with \texttt{fixall=TRUE} (i.e.\ with a fixed number of points of each type) if the model was segregated (i.e.\ if different types of points had different first order trend). The effect of the error was that all types of points had the same first order trend. {\small (Bug was present since about 2010. Fixed in \texttt{spatstat 1.43-0}, september 2015)} \item Simulation of the Geyer saturation process was incorrectly initialised, so that the results of a short run (i.e. small value of \texttt{nrep}) were incorrect, while long runs were correct. \bugger{1.17-0}{october 2009}{1.31-1}{march 2013} \end{itemize} \item \texttt{nnmark, as.im.ssf}: If \code{marks(X)} was a matrix rather than a data frame, the results were completely incorrect. \bugger{1.32-0}{august 2013}{1.55-1}{april 2018} \item \texttt{rVarGamma}: Simulations were incorrect; they were generated using the wrong value of the parameter \texttt{nu.ker}. \bugger{1.25-0}{december 2011}{1.35-0}{december 2013} \item \texttt{rCauchy}: Simulations were incorrect; they were generated using the wrong value of the parameter \texttt{omega}. \bugger{1.25-0}{december 2011}{1.25-2}{january 2012} \item \texttt{lppm}: For multitype patterns, the fitted model was completely incorrect due to an error in constructing the quadrature scheme. \bugger{1.23-0}{july 2011}{1.30-0}{december 2012} \item \verb![.lpp!: The local coordinate \texttt{seg} was completely incorrect, when \texttt{i} was a window. \bugger{1.31-2}{april 2013}{1.45-0}{march 2016} \item \texttt{lohboot}: Implementation was completely incorrect. \bugger{1.26-1}{april 2012}{1.53-2}{october 2017} \item \texttt{leverage.ppm}, \texttt{influence.ppm}, \texttt{dfbetas.ppm}: Results were incorrect for non-Poisson processes due to a mathematical error. \bugger{1.25-0}{december 2011}{1.51-0}{may 2017} \end{itemize} %%% LEVEL 2 \subsection{Serious Bugs, Often Completely Wrong, Moderate Impact} \begin{itemize} \item \texttt{rLGCP}, \texttt{simulate.kppm}: Simulation results for log-Gaussian Cox processes were incorrect unless the pixel dimensions and pixel spacings were identical on the horizontal and vertical axes. (If pixel dimensions were not specified, then the results were incorrect whenever the Frame of the simulation window was not a square.) \bugger{1.22-2}{june 2011}{1.65-0}{december 2020} \item \texttt{deviance.lppm}, \texttt{pseudoR2.lppm}: Results were completely incorrect, due to a coding error. \bugger{1.44-0}{december 2015}{1.64-2}{november 2020} \item \texttt{kppm}: Results were sometimes incorrect for method='clik2' and method='palm' because the log composite likelihood was erroneously truncated to positive values. Any fitted model for which \verb!logLik(model) = 2.2e-16! should be suspected of being incorrect. \bugin{spatstat.core 2.0-0}{march 2021}{spatstat.core 2.3-2}{november 2021} \item \texttt{bw.pcf}: Results were totally incorrect due to a typo. \bugger{1.51-0}{may 2017}{1.52-0}{august 2017} \item \texttt{density.ppp}: edge correction factors were calculated incorrectly when the window was not a rectangle, causing a negative bias in the estimated intensity. \bugger{1.57-0}{oct 2018}{1.64-0}{april 2020}. \item \texttt{density.ppp}: The standard error (calculated when \texttt{se=TRUE}) was incorrect when \texttt{sigma} was a single numeric value. The output was equal to \texttt{sqrt(sigma)} times the correct answer. \bugger{1.41-1}{february 2015}{1.57-0}{october 2018} \item \texttt{rthin}: If \texttt{P} was close to 1, the result was sometimes an empty point pattern when it should have been identical to \texttt{X}. \bugger{1.43-0}{october 2015}{1.57-0}{october 2018} \item \texttt{predict.mppm}: If the model included random effects, and if the library \pkg{MASS} was not loaded, the predictions were on the log scale (i.e.\ they were logarithms of the correct values). \bugger{1.43-0}{october 2015}{1.55-1}{april 2018} \item \texttt{nnmap}, \texttt{nnmark}: Values were incorrect if the resulting pixel image had unequal numbers of rows and columns. \bugger{1.35-0}{december 2013}{1.55-0}{january 2018} \item \texttt{vcov.mppm}: Format was incorrect (rows/columns were omitted) in some cases. \bugger{1.45-1}{may 2016}{1.55-0}{january 2018} \item \texttt{model.matrix.ppm}, \texttt{model.frame.ppm}: Values were sometimes incorrect when applied to the result of \texttt{subfits}. To be precise, if \texttt{fit} was an \texttt{mppm} object fitted to a hyperframe that included ``design covariates'' (covariates that take a constant value in each row of the hyperframe), and if \verb!futs <- subfits(fit)!, then \verb!model.matrix(futs[[i]])! gave incorrect values in the columns corresponding to the design covariates. \bugger{1.45-1}{may 2016}{1.55-0}{january 2018} \item \texttt{predict.rhohat}, \texttt{simulate.rhohat}: Results were incorrect for a \texttt{rhohat} object computed from linear network data (class \texttt{"lpp"} or \texttt{"lppm"}). \bugger{1.31-0}{march 2013}{1.63-1}{february 2020} \item \texttt{predict.rho2hat}: Results were incorrect for a \texttt{rho2hat} object computed from a point pattern. \bugger{1.42-0}{may 2015}{1.52-0}{august 2017} \item \texttt{density.ppp}: Result was incorrect for non-Gaussian kernels when \texttt{at="points"} and \texttt{leaveoneout=FALSE}. \bugger{1.47-0}{october 2016}{1.57-0}{october 2018} \item \texttt{envelope.ppm}: If the model was an inhomogeneous Poisson process, the resulting envelope object was incorrect (the simulations were correct, but the envelopes were calculated assuming the model was CSR). \bugger{1.23-5}{september 2011}{1.23-6}{october 2011} \item \texttt{linearK}, \texttt{linearpcf}, \texttt{linearKinhom}, \texttt{linearpcfinhom} and multitype versions: These functions were sometimes greatly underestimated when the network had segments shorter than 10 coordinate units. \bugger{1.44-0}{december 2015}{1.46-2}{july 2016} \item \texttt{nncross}, \texttt{distfun}, \texttt{AreaInter}: Results of \texttt{nncross} were possibly incorrect when \code{X} and \code{Y} did not have the same window. This bug affected values of \texttt{distfun} and may also have affected ppm objects with interaction \texttt{AreaInter}. \bugger{1.9-4}{june 2006}{1.25-2}{january 2012} \item \texttt{update.kppm}: \begin{itemize} \item Did not function correctly when several additional arguments were given. \bugger{1.42-2}{june 2015}{1.54-0}{november 2017} \item If the call to \texttt{update} did not include a formula argument or a point pattern argument, then all arguments were ignored. Example: \texttt{update(fit, improve.type="quasi")} was identical to \texttt{fit}. \bugger{1.42-2}{june 2015}{1.45-0}{march 2016} \end{itemize} \item \texttt{markcorrint}: Results were completely incorrect. \bugger{1.39-0}{october 2014}{1.40-0}{december 2014} \item \texttt{leverage.ppm}, \texttt{influence.ppm}, \texttt{dfbetas.ppm}: Results were slightly incorrect for models with a hard core, due to a mathematical error. \bugger{1.51-0}{may 2017}{1.55-1}{april 2018} \item \texttt{Ops.msr}: If the input data contained a pixel image of the smoothed density, this image was not updated; it was copied to the output unchanged. Plots of the resulting measure were incorrect. \bugger{1.52-0}{august 2017}{1.55-1}{april 2018} \item \verb![.linnet!: in calculating \verb!L[W]! where \texttt{W} is a window, the code ignored segments of \code{L} that crossed \code{W} without having a vertex in \code{W}. \bugger{1.53-0}{september 2017}{1.55-1}{april 2015} \item \verb!as.im.function!: if the function domain was not a rectangle and the function values were categorical (factor) values, the result was an empty image. \bugger{1.42-0}{may 2015}{1.57-0}{october 2018} \end{itemize} %%% LEVEL 3 \subsection{Bugs, Substantially Incorrect, Moderate Impact} \begin{itemize} \item \texttt{nncross.ppp}: If the argument \texttt{by} was given, some of the results were incorrect. [Spotted by Hank Stevens.] \bugger{1.32-0}{august 2013}{2.2-0}{june 2021} \item \texttt{nncross.ppp}, \texttt{nncross.pp3}: If \texttt{iX} and \texttt{iY} were given, some of the results were incorrect. \bugger{1.32-0}{august 2013}{2.2-0}{june 2021} \item \texttt{vcov.ppm}: Result was sometimes incorrect for Gibbs models. The Fisher information was slightly underestimated. \bugger{1.31-1}{march 2013}{1.64-1}{may 2020} \item \texttt{as.linnet.psp}: Sometimes produced a network with duplicated segments. [Such objects can be repaired using \texttt{repairNetwork}.] \bugger{1.41-1}{february 2015}{1.62-0}{december 2019} \item \texttt{rlpp}: The resulting pattern was unmarked even when it should have been multitype. \bugger{1.48-0}{december 2016}{1.63-0}{january 2020} \item \texttt{spatialcdf}: Argument \texttt{weights} was ignored, unless it was a fitted model. {\small (Bug was present since about 2010. Fixed in \texttt{spatstat 1.59-0}, march 2019)} \item \texttt{ppp}: Points inside the window were erroneously rejected as lying outside the window, if the window was a polygon equivalent to a rectangle with sides longer than $10^6$ units. {\small (Bug was present since the beginning. Fixed in \texttt{spatstat 1.59-0}, march 2019)} \item \texttt{inside.owin}: All results were \texttt{FALSE} if the window was a polygon equivalent to a rectangle with sides longer than $10^6$ units. {\small (Bug was present since the beginning. Fixed in \texttt{spatstat 1.59-0}, march 2019)} \item \texttt{sumouter}: result was incorrect (all entries were zero) if \texttt{w} was missing and \texttt{y} was given. \bugger{1.47-0}{october 2016}{1.59-0}{march 2019} \item \texttt{simulate.dppm}, \texttt{simulate.detpointprocfamily}: In dimensions higher than 2, the result was shifted so that it was centred at the origin. \bugger{1.54-0}{december 2017}{1.55-0}{january 2018} \item \texttt{integral.msr}: If the result was a matrix, it was the transpose of the correct answer. \bugger{1.35-0}{december 2012}{1.55-1}{april 2018} \item \texttt{density.ppp}: Values of \verb!density(X, at="points")! and \verb!Smooth(X, at="points")! were sometimes incorrect, due to omission of the contribution from the data point with the smallest $x$ coordinate. \bugger{1.26-0}{april 2012}{1.46-1}{july 2016} \item \texttt{multiplicity.default}: The first occurrence of any value in the input was incorrectly assigned a multiplicity of 1. \bugger{1.32-0}{december 2013}{1.57-1}{november 2018} \item \texttt{update.ppm}: If the argument \texttt{Q} was given, the results were usually incorrect, or an error was generated. \bugger{1.38-0}{august 2014}{1.38-1}{august 2014} \item \texttt{subfits}: The interaction coefficients of the submodels were incorrect for Gibbs models with a multitype interaction (\texttt{MultiStrauss}, etc). \bugger{1.35-0}{december 2013}{1.45-2}{may 2016} \item \texttt{F3est}: Estimates of $F(r)$ for the largest value of $r$ were wildly incorrect. {\small (Bug was present since about 2010. Fixed in \texttt{spatstat 1.48-0}, december 2016)} \item \texttt{kppm}, \texttt{matclust.estpcf}, \texttt{pcfmodel}: The pair correlation function of the M\'atern Cluster Process was evaluated incorrectly at distances close to 0. This could have affected the fitted parameters in \texttt{matclust.estpcf()} or \texttt{kppm(clusters="MatClust")}. \bugger{1.20-2}{august 2010}{1.33-0}{september 2013} \item \texttt{ppm}: Results were incorrect for the Geyer saturation model with a non-integer value of the saturation parameter \texttt{sat}. \bugger{1.20-0}{july 2010}{1.31-2}{april 2013} \item \texttt{clip.infline}: Results were incorrect unless the midpoint of the window was the coordinate origin. \bugger{1.15-1}{april 2009}{1.48-0}{december 2016} \item \texttt{intensity.ppm}: Result was incorrect for Gibbs models if the model was exactly equivalent to a Poisson process (i.e. if all interaction coefficients were exactly zero). \bugger{1.28-1}{june 2012}{1.47-0}{october 2016} \item \texttt{idw}: Results were incorrect if \texttt{se=TRUE} and \verb!at="pixels"! and \texttt{power} was not equal to 2. The pixel values of \verb!$estimate! were all equal to zero. \bugger{1.58-0}{january 2019}{1.63-0}{january 2020} \item \texttt{funxy}: Did not correctly handle one-line functions. The resulting objects evaluated the wrong function in some cases. \bugger{1.45-0}{march 2016}{1.46-0}{july 2016} \item \texttt{kernel.moment}: Result was incorrect for \texttt{kernel="cosine"} and \texttt{kernel="optcosine"}. \bugger{1.45-2}{may 2016}{1.56-0}{june 2018} \item \verb![.msr!: Format was mangled if the subset contained exactly one quadrature point. \bugger{1.21-3}{january 2011}{1.56-0}{june 2018} \item \texttt{hyperframe}: Did not correctly handle date-time values (columns of class \texttt{"Date"}, etc). \bugger{1.19-1}{may 2010}{1.63-0}{january 2020} \item \texttt{tess}: If a list of tiles was given, and the tiles were pixel images or masks, their pixel resolutions were ignored, and reset to the default $128 \times 128$. {\small (Bug fixed in \texttt{spatstat 1.56-0}, june 2018)} \item \texttt{nnorient}: crashed if the point pattern was empty. \bugger{1.40-0}{december 2015}{1.57-0}{october 2018} \item \verb!as.im.data.frame!: Results were incorrect for factor-valued data. \bugger{1.45-2}{may 2016}{1.63-0}{january 2020} \end{itemize} %% LEVEL 4: \subsection{Partially Incorrect} \begin{itemize} \item \texttt{density.lpp}: The result had the wrong length if \texttt{x} contained duplicated points when \texttt{weights} were given and \texttt{at="points"}. [Spotted by Andrea Gilardi] \bugger{1.55-1}{april 2018}{2.2-0}{june 2021} \item \texttt{crossdist.pp3}: Results with \texttt{periodic=TRUE} were partially incorrect. \bugger{1.34-1}{dec 2013}{1.65-0}{dec 2020} \item \texttt{mppm}: Internal data were malformed if the interaction was \texttt{Hardcore} or \texttt{MultiHard} or a hybrid involving these interactions. This caused various errors when the fitted model was used. \bugger{1.61-0}{september 2019}{1.64-0}{april 2020}. \item \texttt{mppm}: Ignored the arguments \texttt{nd} and \texttt{eps} controlling the quadrature scheme. \bugger{1.35-0}{december 2013}{1.64-0}{april 2020}. \item \texttt{edge.Ripley}: Results were incorrect for data points lying exactly at the corners of a rectangle. \bugbefore{spatstat 1.21-0}{november 2010}{spatstat.core 2.3-2}{november 2021} \item \texttt{kppm}, \texttt{AIC}: For kppm models fitted with \verb!method='clik2'!, the resulting value of \texttt{logLik()} was equal to $1/2$ of the correct value. This would have affected model comparison using AIC, and model selection using \texttt{step}. \bugger{1.42-0}{may 2015}{1.63-0}{january 2020}. \item \texttt{edge.Ripley}, \texttt{Kest}, \texttt{Kinhom}: Isotropic correction weights for polygonal windows were sometimes incorrect for small radius \texttt{r} if the polygon contained many small segments or if the polygon was very long and thin. \bugger{1.60-0}{june 2019}{1.62-0}{december 2019}. \item \texttt{beachcolours}, \texttt{beachcolourmap}: The number of colours was not always equal to \texttt{ncolours}. \bugger{1.32-0}{august 2013}{1.59-0}{march 2019} \item \texttt{extractbranch.lpp}: Point pattern coordinates were sometimes erroneously set to \texttt{NA}. \bugger{1.42-0}{may 2015}{1.59-0}{march 2019} \item \texttt{rotmean}: When \texttt{result="im"} the resulting image did not have the same dimensions as the input. \bugger{1.42-2}{june 2015}{1.58-0}{january 2019} \item \texttt{quadratcount.ppp}: Sometimes issued an incorrect warning that data points were outside the tessellation, when \texttt{tess} was a tessellation represented by a pixel image. {\small (Bug fixed in \texttt{spatstat 1.59-0}, march 2019)} \item \texttt{quadrat.test}: the $p$-value was \texttt{NA} if one of the observed counts was zero, for the Cressie-Read tests with \texttt{CR} not equal to $1$ or $-1$. \bugger{1.38-0}{august 2014}{1.59-0}{march 2019} \item \texttt{quadrat.test}: argument \texttt{CR} was ignored if \texttt{method="MonteCarlo"}. \bugger{1.38-0}{august 2014}{1.61-0}{september 2019} \item \texttt{rotmean}: If argument \texttt{origin} was given, and if \texttt{result="im"} was specified, the resulting image was wrongly displaced. \bugger{1.42-2}{june 2015}{1.58-0}{january 2019} \item \texttt{runifpointx}: Result was mangled when \texttt{n=0} or \texttt{n=1}. \bugger{1.50-0}{march 2017}{1.58-0}{january 2019} \item \texttt{model.matrix.ppm}: The attribute \texttt{assign} was omitted in some cases. \bugger{1.45-1}{may 2016}{1.55-0}{january 2018} \item \texttt{model.matrix.mppm}: Sometimes returned a matrix with the wrong number of rows. \bugger{1.55-0}{january 2018}{1.63-0}{january 2020} \item \texttt{density.ppp}: If the smoothing bandwidth \texttt{sigma} was very small (e.g.\ less than the width of a pixel), results were inaccurate if the default resolution was used, and completely incorrect if a user-specified resolution was given. \bugger{1.26-0}{april 2012}{1.52-0}{august 2017} \item \texttt{selfcrossing.psp}: $y$ coordinate values were incorrect. \bugger{1.23-2}{august 2011}{1.25-3}{february 2012} \item \texttt{Geyer}: For point process models with the \texttt{Geyer} interaction, \texttt{vcov.ppm} and \texttt{suffstat} sometimes gave incorrect answers. \bugger{1.27-0}{may 2012}{1.30-0}{december 2012} \item \texttt{leverage.ppm}, \texttt{influence.ppm}, \texttt{dfbetas.ppm}: Calculations were incorrect for a Geyer model fitted using an edge correction other than \texttt{"border"} or \texttt{"none"}. \bugger{1.25-0}{december 2011}{1.51-0}{may 2017} \item \texttt{leverage.ppm}, \texttt{influence.ppm}, \texttt{dfbetas.ppm}: Results were slightly incorrect for models fitted using the border correction. \bugger{1.25-0}{december 2011}{1.54-0}{november 2017} \item \texttt{leverage.ppm}: The mean leverage value (shown as a contour level in \texttt{plot.leverage.ppm}) was slightly incorrect for Gibbs models. \bugger{1.25-0}{december 2011}{1.54-0}{november 2017} \item \texttt{vcov.ppm}, \texttt{suffstat}: These functions sometimes gave incorrect values for marked point process models. \bugger{1.27-0}{may 2012}{1.29-0}{october 2012} \item \texttt{diagnose.ppm}: When applied to a model obtained from \texttt{subfits()}, in the default case (\texttt{oldstyle=FALSE}) the variance calculations were incorrect. Consequently the dotted lines representing significance bands were incorrect. An error or warning about negative variances occurred sometimes. However, calculations with \texttt{oldstyle=TRUE} were correct. The default has now been changed to \texttt{oldstyle=TRUE} for such models. \bugger{1.35-0}{december 2013}{1.45-0}{march 2016} \item \texttt{Smooth.ppp}: Results for \verb!at="points"! were garbled, for some values of \texttt{sigma}, if \texttt{X} had more than one column of marks. \bugger{1.38-0}{october 2014}{1.46-0}{july 2016} \item \texttt{linearK}, \texttt{linearKinhom}: If any data points were located exactly at a vertex of the linear network, the weights for Ang's correction were incorrect, due to numerical error. This sometimes produced infinite or NA values of the linear $K$ function. \bugger{1.23-0}{july 2011}{1.27-0}{may 2012} \item \texttt{Kinhom}, \texttt{Linhom}: the results were not renormalised (even if \texttt{renormalise=TRUE}) in some cases. \bugger{1.21-0}{december 2010}{1.37-0}{may 2014} \item \texttt{Kinhom}, \texttt{Linhom}: Ignored argument \texttt{reciplambda2} in some cases. \bugger{1.39-0}{october 2014}{1.40-0}{december 2014} \item \texttt{Kinhom}, \texttt{Linhom}: Calculations were incorrect if \texttt{lambda} was a fitted point process model. \bugger{1.38-0}{august 2014}{1.38-1}{august 2014} \item \texttt{integral.linim}, \texttt{integral.linfun}: \begin{itemize} \item results were inaccurate because of a bias in the distribution of sample points. \bugger{1.41-0}{february 2015}{1.47-0}{october 2016} \item results were inaccurate if many of the segment lengths were shorter than the width of a pixel. \bugger{1.41-0}{february 2015}{1.48-0}{december 2016} \item results were wildly inaccurate in some extreme cases where many segments were very short. \bugger{1.41-0}{february 2015}{1.54-0}{november 2017} \end{itemize} \item \texttt{predict.ppm}: Calculation of the conditional intensity omitted the edge correction if \texttt{correction='translate'} or \texttt{correction='periodic'}. \bugger{1.17-0}{october 2009}{1.31-3}{may 2013} \item \texttt{varblock}: Calculations were incorrect if more than one column of edge corrections was computed. \bugger{1.21-1}{november 2010}{1.39-0}{october 2014} \item \texttt{scan.test} Results were sometimes incorrect due to numerical instability (a 'Gibbs phenomenon'). \bugger{1.24-1}{october 2011}{1.26-1}{april 2012} \item \texttt{relrisk}: When \verb!at="pixels"!, a small fraction of pixel values were sometimes wildly inaccurate, due to numerical errors. This affected the range of values in the result, and therefore the appearance of plots. {\small (Bug fixed in \texttt{spatstat 1.40-0}, december 2014)} \item \texttt{predict.slrm}: Results of \texttt{predict(object, newdata)} were incorrect if the spatial domain of \texttt{newdata} was larger than the original domain. \bugger{1.21-0}{november 2010}{1.25-3}{february 2012} \item \texttt{Lest}: The variance approximations (Lotwick-Silverman and Ripley) obtained with \texttt{var.approx=TRUE} were incorrect for \texttt{Lest} (although they were correct for \texttt{Kest}) due to a coding error. \bugger{1.24-1}{october 2011}{1.24-2}{november 2011} \item \texttt{bw.diggle}: Bandwidth was too large by a factor of 2. \bugger{1.23-4}{september 2011}{1.23-5}{september 2011} \item pair correlation functions (\texttt{pcf.ppp}, \texttt{pcfdot}, \texttt{pcfcross} etc:) The result had a negative bias at the maximum $r$ value, because contributions to the pcf estimate from interpoint distances greater than \texttt{max(r)} were mistakenly omitted. {\small (Bugs fixed in \texttt{spatstat 1.35-0}, december 2013)} \item \texttt{Kest}, \texttt{Lest}: Gave incorrect values in very large datasets, due to numerical overflow. `Very large' typically means about 1 million points in a random pattern, or 100,000 points in a tightly clustered pattern. [Overflow cannot occur unless there are at least 46,341 points.] \item \texttt{bw.relrisk}: Implementation of \texttt{method="weightedleastsquares"} was incorrect and was equivalent to \texttt{method="leastsquares"}. \bugger{1.21-0}{november 2010}{1.23-4}{september 2011} \item \texttt{triangulate.owin}: Results were incorrect in some special cases. \bugger{1.42-2}{june 2015}{1.44-0}{december 2015} \item \texttt{crosspairs}: If \texttt{X} and \texttt{Y} were identical point patterns, the result was not necessarily symmetric (on some machines) due to numerical artifacts. \bugger{1.35-0}{december 2013}{1.44-0}{december 2015} \item \texttt{bdist.tiles}: Values were incorrect in some cases due to numerical error. {\small (Bug fixed in \texttt{spatstat 1.29-0}, october 2012)} \item \texttt{Kest.fft}: Result was incorrectly normalised. \bugger{1.21-2}{january 2011}{1.44-0}{december 2015} \item \texttt{crossdist.ppp}: Ignored argument \texttt{squared} if \texttt{periodic=FALSE}. {\small (Bug fixed in \texttt{spatstat 1.38-0}, july 2014)} \item polygon geometry: The point-in-polygon test gave the wrong answer in some boundary cases. {\small (Bug fixed in \texttt{spatstat 1.23-2}, august 2011)} \item \texttt{MultiStraussHard}: If a fitted model with \texttt{MultiStraussHard} interaction was invalid, \texttt{project.ppm} sometimes yielded a model that was still invalid. {\small (Bug fixed in \texttt{spatstat 1.42-0}, may 2015)} \item \texttt{pool.envelope}: Did not always respect the value of \texttt{use.theory}. \bugger{1.23-5}{september 2011}{1.43-0}{september 2015} \item \texttt{nncross.lpp}, \texttt{nnwhich.lpp}, \texttt{distfun.lpp}: Sometimes caused a segmentation fault. \bugger{1.44-0}{december 2015}{1.44-1}{december 2015} \item \texttt{anova.ppm}: If a single \texttt{object} was given, and it was a Gibbs model, then \texttt{adjust} was effectively set to \texttt{FALSE}. \bugger{1.39-0}{october 2014}{1.44-1}{december 2015} \item \verb![.linim!: the result sometimes had the wrong class. \bugger{1.53-0}{september 2017}{1.55-1}{april 2015} \item \verb![.linim!: factor values were erroneously converted to integers, in some cases. \bugger{1.53-0}{september 2017}{1.61-0}{september 2019} \item \verb!is.subset.owin!: sometimes gave the wrong result for polygonal windows due to numerical rounding error. {\small (Bug was always present. Fixed in \texttt{spatstat 1.59-0}, march 2019)} \item \texttt{plot.tess}: the legend showed the tile names in lexicographical order, rather than their original order. \bugger{1.55-1}{april 2018}{1.59-0}{march 2019} \item \texttt{rThomas}, \texttt{rMatClust}, \texttt{rCauchy}, \texttt{rVarGamma}: If the simulation window was not a rectangle, the attribute \texttt{Lambda} was a numeric vector, rather than a pixel image as intended. \bugger{1.43-0}{october 2015}{1.59-0}{march 2019} \item \texttt{effectfun}: In a multitype point process model, \texttt{effectfun} ignored any user-specified value of \texttt{marks}. \bugger{1.52-0}{august 2017}{1.61-0}{september 2019} \item \verb!"[<-.hyperframe"!: Some classes of objects were not handled correctly. \bugger{1.37-0}{may 2014}{1.61-0}{september 2019} \item \texttt{relrisk.ppp}: Crashed if there were more than 2 types of points and \texttt{method = "leastsquares"} or \texttt{method = "weightedleastsquares"}. \bugger{1.23-4}{september 2011}{1.63-0}{january 2020} \item \texttt{nncross.ppp}: Format of output was incorrect if \texttt{X} was an empty pattern. \bugger{1.56-0}{june 2018}{1.63-0}{january 2020} \item \texttt{rmh}, \texttt{rmh.default}: For a marked point process, the debugger did not display the marks. (The \texttt{rmh} debugger is invoked by calling \texttt{rmh} with \texttt{snoop=TRUE}). \bugger{1.31-1}{march 2013}{1.63-0}{january 2020} \item \texttt{model.matrix.mppm}: If the model was fitted using \texttt{gam}, the resulting matrix did not have an \texttt{"assign"} attribute. \bugger{1.55-0}{march 2018}{2.2-0}{june 2021} \item \texttt{update.slrm}: Failed to find covariates that were provided in \texttt{env}. \bugger{1.33-0}{september 2013}{2.2-0}{june 2021} \end{itemize} \begin{thebibliography}{1} \bibitem{baddrubaturn15} A. Baddeley, E. Rubak, and R. Turner. \newblock {\em Spatial Point Patterns: Methodology and Applications with {{R}}}. \newblock Chapman \& Hall/CRC Press, 2015. \end{thebibliography} \end{document} spatstat/vignettes/hexagon.pdf0000644000176200001440000000473214141377564016273 0ustar liggesusers%PDF-1.4 %쏢 5 0 obj <> stream x-1As^1/@`X^` 2E0T YA=qNOc?4M 9,T;SvzI!ŕehV)OkbJ#S|8xh+] bendstream endobj 6 0 obj 118 endobj 4 0 obj <> /Contents 5 0 R >> endobj 3 0 obj << /Type /Pages /Kids [ 4 0 R ] /Count 1 >> endobj 1 0 obj <> endobj 7 0 obj <>endobj 8 0 obj <> endobj 9 0 obj <>stream 2013-12-23T19:49:36+08:00 2013-12-23T19:49:36+08:00 fig2dev Version 3.2 Patchlevel 5d hexagon.fig endstream endobj 2 0 obj <>endobj xref 0 10 0000000000 65535 f 0000000410 00000 n 0000001982 00000 n 0000000351 00000 n 0000000222 00000 n 0000000015 00000 n 0000000203 00000 n 0000000474 00000 n 0000000515 00000 n 0000000544 00000 n trailer << /Size 10 /Root 1 0 R /Info 2 0 R /ID [<7169BA68125AE1AEC0984268ECC4E10A><7169BA68125AE1AEC0984268ECC4E10A>] >> startxref 2169 %%EOF spatstat/vignettes/datasets.Rnw0000644000176200001440000007007514141377564016452 0ustar liggesusers\documentclass[11pt]{article} % \VignetteIndexEntry{Datasets Provided for the Spatstat Package} <>= options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) @ \usepackage{graphicx} \usepackage{anysize} \marginsize{2cm}{2cm}{2cm}{2cm} \newcommand{\pkg}[1]{\texttt{#1}} \newcommand{\bold}[1]{{\textbf {#1}}} \newcommand{\R}{{\sf R}} \newcommand{\spst}{\pkg{spatstat}} \newcommand{\Spst}{\pkg{Spatstat}} \newcommand{\sdat}{\pkg{spatstat.data}} \newcommand{\Sdat}{\pkg{Spatstat.data}} \begin{document} \bibliographystyle{plain} \thispagestyle{empty} \SweaveOpts{eps=TRUE} \setkeys{Gin}{width=0.6\textwidth} <>= library(spatstat) sdate <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Date") sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") spatstat.options(transparent=FALSE) options(useFancyQuotes=FALSE) @ \title{Datasets provided for \spst} \author{Adrian Baddeley, Rolf Turner and Ege Rubak} \date{For \spst\ version \texttt{\Sexpr{sversion}}} \maketitle This document is an overview of the spatial datasets that are provided for the \spst\ package. To flick through a nice display of all the data sets that come with \spst\ type \texttt{demo(data)}. To see information about a given data set, type \texttt{help({\em name})} where \emph{name} is the name of the data set. To plot a given data set, type \texttt{plot({\em name})}. Datasets in \spst\ are ``lazy-loaded'', which means that they can be accessed simply by typing their name. Not all packages do this; in some packages you have to type \texttt{data({\em name})} in order to access a data set. To list all the datasets in \spst, you need to type \texttt{data(package="spatstat.data")}. This is because, for efficiency, the datasets are actually installed in a sub-package \sdat. This is the only time you should ever need to mention \sdat\ explicitly. When the \spst\ package is loaded by the command \texttt{library(spatstat)}, the sub-package \sdat\ is automatically loaded. \section{List of datasets} \subsection{Point patterns in 2D} Here is a list of the standard point pattern data sets that are supplied with the current installation of \sdat: \newcommand{\recto}{\framebox{\hphantom{re}\vphantom{re}}} \newcommand{\irregpoly}{\includegraphics*[width=6mm]{irregpoly}} \newcommand{\masque}{\includegraphics*[width=6mm]{mask}} \newcommand{\convpoly}{\includegraphics*[width=4mm]{hexagon}} \newcommand{\disc}{$\bigcirc$} \newcommand{\nomarks}{$\cdot$} \newcommand{\nocov}{$\cdot$} \begin{tabular}{l|l|ccc} {\sf name} & {\sf description} & {\sf marks} & {\sf covariates} & {\sf window} \\ \hline {\tt amacrine} & rabbit amacrine cells & cell type & \nocov & \recto \\ {\tt anemones} & sea anemones & diameter & \nocov & \recto \\ {\tt ants} & ant nests& species & zones & \convpoly \\ {\tt bdspots} & breakdown spots & \nomarks & \nocov & \disc \\ {\tt bei} & rainforest trees & \nomarks & topography & \recto \\ {\tt betacells} & cat retinal ganglia & cell type, area & \nocov & \recto \\ {\tt bramblecanes} & bramble canes & age & \nocov & \recto \\ {\tt bronzefilter} & bronze particles & diameter & \nocov & \recto \\ {\tt btb} & bovine tuberculosis & type, year & \nocov & \irregpoly \\ {\tt cells} & biological cells & \nomarks &\nocov & \recto \\ {\tt chorley} & cancers & case/control &\nocov & \irregpoly \\ {\tt clmfires} & forest fires & cause, size, date & \shortstack[c]{elevation, orientation,\\ slope, land use} & \irregpoly \\ {\tt concrete} & air bubbles in concrete & \nomarks & \nocov & \masque \\ {\tt copper} & copper deposits & \nomarks & fault lines & \recto \\ {\tt demopat} & artificial data & type & \nocov & \irregpoly \\ {\tt finpines} & trees & diam, height & \nocov & \recto \\ {\tt gordon} & people in a park & \nomarks & \nocov & \irregpoly \\ {\tt gorillas} & gorilla nest sites & group, season & \shortstack[c]{terrain, vegetation,\\ heat, water} & \irregpoly \\ {\tt hamster} & hamster tumour cells & cell type &\nocov & \recto \\ {\tt humberside} & child leukaemia & case/control & \nocov & \irregpoly\\ {\tt hyytiala} & mixed forest & species &\nocov & \recto \\ {\tt japanesepines} & Japanese pines & \nomarks &\nocov & \recto \\ {\tt lansing} & mixed forest & species & \nocov & \recto \\ {\tt longleaf} & trees & diameter & \nocov & \recto \\ {\tt mucosa} & gastric mucosa cells & cell type & \nocov & \recto \\ {\tt murchison} & gold deposits & \nomarks & faults, rock type & \irregpoly \\ {\tt nbfires} & wildfires & several & \nocov & \irregpoly \\ {\tt nztrees} & trees & \nomarks & \nocov & \recto \\ {\tt paracou} & trees & adult/juvenile & \nocov & \recto \\ {\tt ponderosa} & trees & \nomarks & \nocov & \recto \\ {\tt redwood} & saplings & \nomarks & \nocov & \recto \\ {\tt redwood3} & saplings & \nomarks & \nocov & \recto \\ {\tt redwoodfull} & saplings & \nomarks & zones & \recto \\ {\tt shapley} & galaxies & magnitude, recession, SE & \nocov & \convpoly \\ {\tt simdat} & simulated pattern & \nomarks & \nocov & \recto \\ {\tt sporophores} & fungi & species & \nocov & \disc \\ {\tt spruces} & trees & diameter & \nocov & \recto \\ {\tt swedishpines} & trees & \nomarks & \nocov & \recto \\ {\tt urkiola} & mixed forest & species & \nocov & \irregpoly \\ {\tt vesicles} & synaptic vesicles & \nomarks & zones & \irregpoly \\ {\tt waka} & trees & diameter & \nocov & \recto \\ \hline \end{tabular} \bigskip \noindent The shape of the window containing the point pattern is indicated by the symbols \recto\ (rectangle), \disc\ (disc), \convpoly\ (convex polygon), \irregpoly\ (irregular polygon) and \masque (binary mask). Additional information about the data set \texttt{\em name} may be stored in a separate list \texttt{{\em name}.extra}. Currently these are the available options: \begin{tabular}[!h]{ll} {\sc Name} & {\sc Contents} \\ \hline {\tt ants.extra} & field and scrub subregions; \\ & additional map elements; plotting function \\ {\tt bei.extra} & covariate images \\ {\tt chorley.extra} & incinerator location; plotting function \\ {\tt gorillas.extra} & covariate images\\ {\tt nbfires.extra} & inscribed rectangle; border type labels \\ {\tt ponderosa.extra} & data points of interest; plotting function\\ {\tt redwoodfull.extra} & subregions; plotting function \\ {\tt shapley.extra} & individual survey fields; plotting function \\ {\tt vesicles.extra} & anatomical regions \\ \hline \end{tabular} For demonstration and instruction purposes, raw data files are available for the datasets \texttt{vesicles}, \texttt{gorillas} and \texttt{osteo}. \subsection{Other Data Types} There are also the following spatial data sets which are not 2D point patterns: \begin{tabular}[c]{l|l|l} {\sf name} & {\sf description} & {\sf format} \\ \hline {\tt austates} & Australian states & tessellation \\ {\tt cetaceans} & marine survey & replicated 2D point patterns \\ {\tt chicago} & crimes & point pattern on linear network \\ {\tt demohyper} & simulated data & replicated 2D point patterns with covariates\\ {\tt dendrite} & dendritic spines & point pattern on linear network \\ {\tt flu} & virus proteins & replicated 2D point patterns \\ {\tt heather} & heather mosaic & binary image (three versions) \\ {\tt osteo} & osteocyte lacunae & replicated 3D point patterns with covariates\\ {\tt pyramidal} & pyramidal neurons & replicated 2D point patterns in 3 groups\\ {\tt residualspaper} & data \& code from Baddeley et al (2005) & 2D point patterns, \R\ function \\ {\tt simba} & simulated data & replicated 2D point patterns in 2 groups\\ {\tt spiders} & spider webs & point pattern on linear network \\ {\tt waterstriders} & insects on water & replicated 2D point patterns\\ \hline \end{tabular} Additionally there is a dataset \texttt{Kovesi} containing several colour maps with perceptually uniform contrast. \section{Information on each dataset} Here we give basic information about each dataset. For further information, consult the help file for the particular dataset. <>= opa <- par() ## How to set all margins to zero and eliminate all outer spaces zeromargins <- function() { par( mar=rep(0,4), omd=c(0,1,0,1), xaxs="i", yaxs="i" ) invisible(NULL) } ## Set 'mar' setmargins <- function(...) { x <- c(...) x <- rep(x, 4)[1:4] par(mar=x) invisible(NULL) } @ \subsubsection*{\texttt{amacrine}: Amacrine cells} Locations of displaced amacrine cells in the retina of a rabbit. There are two types of points, ``on'' and ``off''. \SweaveOpts{width=5.5,height=3}\setkeys{Gin}{width=0.8\textwidth} <>= plot(amacrine) @ <>= setmargins(0,1,2,0) plot(amacrine) @ \subsubsection*{\texttt{anemones}: Sea Anemones} These data give the spatial locations and diameters of sea anemones on a boulder near sea level. \SweaveOpts{width=7,height=4.5}\setkeys{Gin}{width=0.8\textwidth} <>= plot(anemones, markscale=1) @ <>= setmargins(0,0,2,0) plot(anemones, markscale=1) @ \subsubsection*{\texttt{ants}: Ants' nests} Spatial locations of nests of two species of ants at a site in Greece. The full dataset (supplied here) has an irregular polygonal boundary, while most analyses have been confined to two rectangular subsets of the pattern (also supplied here). % Parameters for Ants data with key at right \SweaveOpts{width=6.3,height=4}\setkeys{Gin}{width=0.7\textwidth} <>= ants.extra$plotit() @ %$ <>= setmargins(0,0,1,0) ants.extra$plotit() @ %$ \subsubsection*{\texttt{austates}: Australian states} The states and large mainland territories of Australia are represented as polygonal regions forming a tessellation. <>= plot(austates) @ \subsubsection*{\texttt{bdspots}: Breakdown spots} A list of three point patterns, each giving the locations of electrical breakdown spots on a circular electrode in a microelectronic capacitor. \SweaveOpts{width=12,height=6}\setkeys{Gin}{width=\textwidth} <>= plot(bdspots, equal.scales=TRUE, pch="+", panel.args=function(i)list(cex=c(0.15, 0.2, 0.7)[i])) @ <>= zeromargins() plot(bdspots, equal.scales=TRUE, pch="+", main="", mar.panel=0, hsep=1, panel.args=function(i)list(cex=c(0.15, 0.2, 0.7)[i])) @ \subsubsection*{\texttt{bei}: Beilschmiedia data} Locations of 3605 trees in a tropical rain forest. Accompanied by covariate data giving the elevation (altitude) and slope of elevation in the study region. \SweaveOpts{width=12,height=6}\setkeys{Gin}{width=0.8\textwidth} <>= plot(bei.extra$elev, main="Beilschmiedia") plot(bei, add=TRUE, pch=16, cex=0.3) @ <>= setmargins(0,0,2,0) plot(bei.extra$elev, main="Beilschmiedia") plot(bei, add=TRUE, pch=16, cex=0.3) @ The following command gives a perspective display similar to the front cover of Baddeley, Rubak and Turner (2015): <>= M <- persp(bei.extra$elev, theta=-45, phi=18, expand=7, border=NA, apron=TRUE, shade=0.3, box=FALSE, visible=TRUE, main="") perspPoints(bei, Z=bei.extra$elev, M=M, pch=16, cex=0.3) @ \subsubsection*{\texttt{betacells}: Beta ganglion cells} Locations of beta ganglion cells in cat retina, each cell classified as `on' or `off' and also labelled with the cell profile area. <>= plot(betacells) @ \subsubsection*{\texttt{bramblecanes}: Bramble canes} <>= plot(bramblecanes, cols=1:3) @ Try the following <>= plot(split(bramblecanes)) @ \subsubsection*{\texttt{bronzefilter}: Bronze filter section profiles} Spatially inhomogeneous pattern of circular section profiles of particles, observed in a longitudinal plane section through a gradient sinter filter made from bronze powder. <>= plot(bronzefilter,markscale=2) @ \subsubsection*{\texttt{btb}: bovine tuberculosis} Locations of farms where bovine tuberculosis was detected, marked by year of detection and spoligotype of tuberculosis. <>= plot(btb, which.marks="spoligotype", cols=2:5, chars=1:4) @ \subsubsection*{\texttt{cells}: Biological cells} Locations of the centres of 42 biological cells observed under optical microscopy in a histological section. Often used as a demonstration example. <>= plot(cells) @ \subsubsection*{\texttt{cetaceans}: Survey of marine species} Recorded sightings of whales, dolphins and other marine species in a series of surveys. Replicated 2D marked point patterns. <>= plot(cetaceans.extra$patterns, main="Cetaceans data", cols=1:5, hsep=1) @ \subsubsection*{\texttt{chicago}: Chicago crimes} Locations (street addresses) of crimes reported in a two-week period in an area close to the University of Chicago. A multitype point pattern on a linear network. <>= plot(chicago, main="Chicago Crimes", col="grey", cols=c("red", "blue", "black", "blue", "red", "blue", "blue"), chars=c(16,2,22,17,24,15,6), leg.side="left", show.window=FALSE) @ \subsubsection*{\texttt{chorley}: Chorley-Ribble cancer data} Spatial locations of cases of cancer of the larynx and cancer of the lung, and the location of a disused industrial incinerator. A marked point pattern, with an irregular window and a simple covariate. <>= chorley.extra$plotit() @ %$ \subsubsection*{\texttt{clmfires}: Castilla-La Mancha Fires} Forest fires in the Castilla-La Mancha region of Spain between 1998 and 2007. A point pattern with 4 columns of marks: \begin{tabular}{ll} \texttt{cause} & cause of fire\\ \texttt{burnt.area} & total area burned, in hectares \\ \texttt{date} & date of fire \\ \texttt{julian.date} & date of fire in days since 1.1.1998 \end{tabular} <>= plot(clmfires, which.marks="cause", cols=2:5, cex=0.25, main="Castilla-La Mancha forest fires") @ The accompanying dataset \texttt{clmfires.extra} is a list of two items \texttt{clmcov100} and \texttt{clmcov200} containing covariate information for the entire Castilla-La Mancha region. Each of these two elements is a list of four pixel images named \texttt{elevation}, \texttt{orientation}, \texttt{slope} and \texttt{landuse}. <>= plot(clmfires.extra$clmcov100$elevation, main="Elevation") @ %$ \subsubsection*{\texttt{concrete}: Air bubbles in concrete} Prof.\ Shin-ichi Igarashi's data: a point pattern of the locations of centroids of air bubbles seen in a cross-section of concrete. Air bubbles are present in the matrix of cement paste which surrounds the particles of aggregate. The outline of the aggregate, and the locations of the centroids of the bubble profiles, are recorded. <>= plot(concrete,chars="+",cols="blue",col="yellow") @ \subsubsection*{\texttt{copper}: Queensland copper data} These data come from an intensive geological survey in central Queensland, Australia. They consist of 67 points representing copper ore deposits, and 146 line segments representing geological `lineaments', mostly faults. <>= plot(copper$Points, main="Copper") plot(copper$Lines, add=TRUE) @ \subsubsection*{\texttt{demohyper}} A synthetic example of a \texttt{hyperframe} for demonstration purposes. <>= plot(demohyper, quote({ plot(Image, main=""); plot(Points, add=TRUE) }), parargs=list(mar=rep(1,4))) @ \subsubsection*{\texttt{demopat}} A synthetic example of a point pattern for demonstration purposes. <>= plot(demopat) @ \subsubsection*{\texttt{dendrite}} Dendrites are branching filaments which extend from the main body of a neuron (nerve cell) to propagate electrochemical signals. Spines are small protrusions on the dendrites. This dataset gives the locations of 566 spines observed on one branch of the dendritic tree of a rat neuron. The spines are classified according to their shape into three types: mushroom, stubby or thin. <>= plot(dendrite, leg.side="bottom", main="", cex=0.75, cols=2:4) @ \subsubsection*{\texttt{finpines}: Finnish pine saplings} Locations of 126 pine saplings in a Finnish forest, their heights and their diameters. <>= plot(finpines, main="Finnish pines") @ \subsubsection*{\texttt{flu}: Influenza virus proteins} The \texttt{flu} dataset contains replicated spatial point patterns giving the locations of two different virus proteins on the membranes of cells infected with influenza virus. It is a \texttt{hyperframe} containing point patterns and explanatory variables. <>= wildM1 <- with(flu, virustype == "wt" & stain == "M2-M1") plot(flu[wildM1, 1, drop=TRUE], main=c("flu data", "wild type virus, M2-M1 stain"), chars=c(16,3), cex=0.4, cols=2:3) @ \subsubsection*{\texttt{gordon}: People in Gordon Square} Locations of people sitting on a grass patch on a sunny afternoon. <>= plot(gordon, main="People in Gordon Square", pch=16) @ \subsubsection*{\texttt{gorillas}: Gorilla nesting sites} Locations of nesting sites of gorillas, and associated covariates, in a National Park in Cameroon. \texttt{gorillas} is a marked point pattern (object of class \texttt{"ppp"}) representing nest site locations. \texttt{gorillas.extra} is a named list of 7 pixel images (objects of class \texttt{"im"}) containing spatial covariates. It also belongs to the class \texttt{"listof"}. <>= plot(gorillas, which.marks=1, chars=c(1,3), cols=2:3, main="Gorilla nest sites") @ The \texttt{vegetation} covariate is also available as a raw ASCII format file, <>= system.file("rawdata/gorillas/vegetation.asc", package="spatstat") @ \subsubsection*{\texttt{hamster}: Hamster kidney cells} Cell nuclei in hamster kidney, each nucleus classified as either `dividing' or `pyknotic'. A multitype point pattern. <>= plot(hamster, cols=c(2,4)) @ \subsubsection*{\texttt{heather}: Heather mosaic} The spatial mosaic of vegetation of the heather plant, recorded in a 10 by 20 metre sampling plot in Sweden. A list with three entries, representing the same data at different spatial resolutions. <>= plot(heather$coarse) @ Type the following to see all three images: <>= plot(heather) @ \subsubsection*{\texttt{humberside}: Childhood Leukemia and Lymphoma} Spatial locations of cases of childhood leukaemia and lymphoma, and randomly-selected controls, in North Humberside. A marked point pattern. <>= plot(humberside) @ The dataset \texttt{humberside.convex} is an object of the same format, representing the same point pattern data, but contained in a larger, 5-sided convex polygon. \subsubsection*{\texttt{hyytiala}: Mixed forest} Spatial locations and species classification for trees in a Finnish forest. <>= plot(hyytiala, cols=2:5) @ \subsubsection*{\texttt{japanesepines}: Japanese black pine saplings} Locations of Japanese black pine saplings in a square sampling region in a natural forest. Often used as a standard example. <>= plot(japanesepines) @ \subsubsection*{\texttt{lansing}: Lansing Woods} Locations and botanical classification of trees in a forest. A multitype point pattern with 6 different types of points. Includes duplicated points. <>= plot(lansing) @ Type the following to see 6 plots, each showing the location of one of the types of points: <>= plot(split(lansing)) @ \subsubsection*{\texttt{longleaf}: Longleaf Pines} Locations and diameters of Longleaf pine trees. <>= plot(longleaf) @ \subsubsection*{\texttt{mucosa}: Gastric Mucosa Cells} A bivariate inhomogeneous point pattern, giving the locations of the centres of two types of cells in a cross-section of the gastric mucosa of a rat. <>= plot(mucosa, chars=c(1,3), cols=c("red", "green")) plot(mucosa.subwin, add=TRUE, lty=3) @ \subsubsection*{\texttt{murchison}: Murchison Gold Deposits} Spatial locations of gold deposits and associated geological features in the Murchison area of Western Australia. A list of three elements: \begin{itemize} \item \texttt{gold}, the point pattern of gold deposits; \item \texttt{faults}, the line segment pattern of geological faults; \item \texttt{greenstone}, the subregion of greenstone outcrop. \end{itemize} Type the following to see the full Murchison dataset: <>= plot(murchison$greenstone, main="Murchison data", col="lightgreen") plot(murchison$gold, add=TRUE, pch=3, col="blue") plot(murchison$faults, add=TRUE, col="red") @ Some analysis of the data uses a rectangle close to the abandoned town of Reedy: <<>>= reedy <- owin(c(580, 650), c(6986, 7026)) @ Here are the data in that area: <>= plot(murchison$greenstone[reedy], main="Murchison data", col="lightgreen") plot(murchison$gold[reedy], add=TRUE, pch=3, col="blue") plot(murchison$faults[reedy], add=TRUE, col="red") @ \subsubsection*{\texttt{nbfires}: New Brunswick Fires} Fires in New Brunswick (Canada) with marks giving information about each fire. <>= plot(nbfires, use.marks=FALSE, pch=".") @ The following command would show the data for each year in a separate panel: <>= plot(split(nbfires), use.marks=FALSE, chars=".") @ <>= par(mar=c(0,0,2,0)) plot(split(nbfires)$"2000", which.marks="fire.type", main=c("New Brunswick fires 2000", "by fire type"), cols=c("blue", "green", "red", "cyan"), leg.side="left") @ \subsubsection*{\texttt{nztrees}: New Zealand Trees} Locations of trees in a forest plot in New Zealand. Often used as a demonstration example. <>= plot(nztrees) plot(trim.rectangle(as.owin(nztrees), c(0,5), 0), add=TRUE, lty=3) @ \subsubsection*{\texttt{osteo}: Osteocyte Lacunae} Replicated three-dimensional point patterns: the three-dimensional locations of osteocyte lacunae observed in rectangular volumes of solid bone using a confocal microscope. A \texttt{hyperframe} containing 3D point patterns and explanatory variables. <>= plot(osteo[1:4,], main.panel="", pch=21, bg='white') @ For demonstration and instruction purposes, the raw data from the 36th point pattern are available in a plain ascii file in the \texttt{spatstat} installation, <>= system.file("rawdata/osteo/osteo36.txt", package="spatstat") @ \subsubsection*{\texttt{paracou}: Kimboto trees} Point pattern of adult and juvenile Kimboto trees recorded at Paracou in French Guiana. A bivariate point pattern. <>= plot(paracou, cols=2:3, chars=c(16,3)) @ \subsubsection*{\texttt{ponderosa}: Ponderosa Pines} Locations of Ponderosa Pine trees in a forest. Several special points are identified. <>= ponderosa.extra$plotit() @ %$ \subsubsection*{\texttt{pyramidal}: Pyramidal Neurons in Brain} Locations of pyramidal neurons in sections of human brain. There is one point pattern from each of 31 human subjects. The subjects are divided into three groups: controls (12 subjects), schizoaffective (9 subjects) and schizophrenic (10 subjects). To reduce space, we show only the odd-numbered patterns: <<>>= pyr <- pyramidal[c(FALSE,TRUE), ] @ <>= pyr$grp <- abbreviate(pyr$group, minlength=7) plot(pyr, quote(plot(Neurons, pch=16, main=grp)), main="Pyramidal Neurons") @ \subsubsection*{\texttt{redwood}, \texttt{redwood3}, \texttt{redwoodfull}: Redwood seedlings and saplings} California Redwood seedlings and saplings in a forest. There are two versions of this dataset: \texttt{redwood} and \texttt{redwoodfull}. The \texttt{redwoodfull} dataset is the full data. It is spatially inhomogeneous in density and spacing of points. The \texttt{redwood} dataset is a subset of the full data, selected because it is apparently homogeneous, and has often been used as a demonstration example. This comes in two versions commonly used in the literature: \texttt{redwood} (coordinates given to 2 decimal places) and \texttt{redwood3} (coordinates given to 3 decimal places). <>= plot(redwood) plot(redwood3, add=TRUE, pch=20) @ <>= redwoodfull.extra$plotit() @ %$ \subsubsection*{\texttt{residualspaper}: Data from residuals paper} Contains the point patterns used as examples in \begin{quote} A. Baddeley, R. Turner, J. M{\o}ller and M. Hazelton (2005) Residual analysis for spatial point processes. \emph{Journal of the Royal Statistical Society, Series B} \textbf{67}, 617--666 \end{quote} along with {\sf R} code. <>= plot(as.solist(residualspaper[c("Fig1", "Fig4a", "Fig4b", "Fig4c")]), main="") @ \subsubsection*{\texttt{shapley}: Shapley Galaxy Concentration} Sky positions of 4215 galaxies in the Shapley Supercluster (mapped by radioastronomy). <>= shapley.extra$plotit(main="Shapley") @ %$ \subsubsection*{\texttt{simdat}: Simulated data} Another simulated dataset used for demonstration purposes. <>= plot(simdat) @ \subsubsection*{\texttt{spiders}: Spider webs} Spider webs across the mortar lines of a brick wall. A point pattern on a linear network. <>= plot(spiders, pch=16, show.window=FALSE) @ \subsubsection*{\texttt{sporophores}: Sporophores} Sporophores of three species of fungi around a tree. <>= plot(sporophores, chars=c(16,1,2), cex=0.6) points(0,0,pch=16, cex=2) text(15,8,"Tree", cex=0.75) @ \subsubsection*{\texttt{spruces}: Spruces in Saxony} Locations of Norwegian spruce trees in a natural forest stand in Saxonia, Germany. Each tree is marked with its diameter at breast height. <>= plot(spruces, maxsize=min(nndist(spruces))) @ \subsubsection*{\texttt{swedishpines}: Swedish Pines} Locations of pine saplings in a Swedish forest. Often used as a demonstration example. <>= plot(swedishpines) @ \subsubsection*{\texttt{urkiola}: trees in a wood} Locations of birch and oak trees in a secondary wood in Urkiola Natural Park (Basque country, northern Spain). Irregular window, bivariate point pattern. <>= plot(urkiola, cex=0.5, cols=2:3) @ \subsubsection*{\texttt{waka}: trees in Waka National Park} Spatial coordinates of each tree, marked by the tree diameter at breast height. <>= par(mar=c(0,0,2,0)) plot(waka, markscale=0.04, main=c("Waka national park", "tree diameters")) @ \subsubsection*{\texttt{vesicles}: synaptic vesicles} Point pattern of synaptic vesicles observed in rat brain tissue. <>= v <- rotate(vesicles, pi/2) ve <- lapply(vesicles.extra, rotate, pi/2) plot(v, main="Vesicles") plot(ve$activezone, add=TRUE, lwd=3) @ The auxiliary dataset \texttt{vesicles.extra} is a list with entries\\ \begin{tabular}{ll} \texttt{presynapse} & outer polygonal boundary of presynapse \\ \texttt{mitochondria} & polygonal boundary of mitochondria \\ \texttt{mask} & binary mask representation of vesicles window \\ \texttt{activezone} & line segment pattern representing the active zone. \end{tabular} For demonstration and training purposes, the raw data files for this dataset are also provided in the \pkg{spatstat} package installation:\\ \begin{tabular}{ll} \texttt{vesicles.txt} & spatial locations of vesicles \\ \texttt{presynapse.txt} & vertices of \texttt{presynapse} \\ \texttt{mitochondria.txt} & vertices of \texttt{mitochondria} \\ \texttt{vesiclesimage.tif} & greyscale microscope image \\ \texttt{vesiclesmask.tif} & binary image of \texttt{mask} \\ \texttt{activezone.txt} & coordinates of \texttt{activezone} \end{tabular} The files are in the folder \texttt{rawdata/vesicles} in the \texttt{spatstat} installation directory. The precise location of the files can be obtained using \texttt{system.file}, for example <>= system.file("rawdata/vesicles/mitochondria.txt", package="spatstat") @ \subsubsection*{\texttt{waterstriders}: Insects on a pond} Three independent replications of a point pattern formed by insects on the surface of a pond. <>= plot(waterstriders) @ \end{document} spatstat/vignettes/irregpoly.pdf0000644000176200001440000000524114141377564016652 0ustar liggesusers%PDF-1.4 %쏢 5 0 obj <> stream xm=n1 =O0?}n #EJH6@ob%^EsMo? 'P*fvjqp}]",D <qe]X/pRiuS\ *qX2B*XkӜ\lDU1J卼PX]rrZ0CP$!7D,(ƃ[Q5C2)RHQ5A70=x"EuZ1m=@4)YJ9VL,6}9f,q^ѕ:'1V8'3&R[UXߑX |endstream endobj 6 0 obj 311 endobj 4 0 obj <> /Contents 5 0 R >> endobj 3 0 obj << /Type /Pages /Kids [ 4 0 R ] /Count 1 >> endobj 1 0 obj <> endobj 7 0 obj <>endobj 8 0 obj <> endobj 9 0 obj <>stream 2013-12-23T19:50:47+08:00 2013-12-23T19:50:47+08:00 fig2dev Version 3.2 Patchlevel 5d irregpoly.fig endstream endobj 2 0 obj <>endobj xref 0 10 0000000000 65535 f 0000000605 00000 n 0000002179 00000 n 0000000546 00000 n 0000000415 00000 n 0000000015 00000 n 0000000396 00000 n 0000000669 00000 n 0000000710 00000 n 0000000739 00000 n trailer << /Size 10 /Root 1 0 R /Info 2 0 R /ID [] >> startxref 2368 %%EOF spatstat/vignettes/getstart.Rnw0000644000176200001440000003126414141377564016474 0ustar liggesusers\documentclass[11pt]{article} % \VignetteIndexEntry{Getting Started with Spatstat} <>= options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) @ \usepackage{graphicx} \usepackage{anysize} \marginsize{2cm}{2cm}{2cm}{2cm} \newcommand{\pkg}[1]{\texttt{#1}} \newcommand{\bold}[1]{{\textbf {#1}}} \newcommand{\R}{{\sf R}} \newcommand{\spst}{\pkg{spatstat}} \newcommand{\Spst}{\pkg{Spatstat}} \begin{document} \bibliographystyle{plain} \thispagestyle{empty} \SweaveOpts{eps=TRUE} \setkeys{Gin}{width=0.6\textwidth} <>= library(spatstat) spatstat.options(image.colfun=function(n) { grey(seq(0,1,length=n)) }) sdate <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Date") sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") options(useFancyQuotes=FALSE) @ \title{Getting started with \texttt{spatstat}} \author{Adrian Baddeley, Rolf Turner and Ege Rubak} \date{For \spst\ version \texttt{\Sexpr{sversion}}} \maketitle Welcome to \spst, a package in the \R\ language for analysing spatial point patterns. This document will help you to get started with \spst. It gives you a quick overview of \spst, and some cookbook recipes for doing basic calculations. \section*{What kind of data does \spst\ handle?} \Spst\ is mainly designed for analysing \emph{spatial point patterns}. For example, suppose you are an ecologist studying plant seedlings. You have pegged out a $10 \times 10$ metre rectangle for your survey. Inside the rectangle you identify all the seedlings of the species you want, and record their $(x,y)$ locations. You can plot the $(x,y)$ locations: <>= data(redwood) plot(redwood, pch=16, main="") @ This is a \emph{spatial point pattern} dataset. Methods for analysing this kind of data are summarised in the highly recommended book by Diggle \cite{digg03}, or our own book \cite{baddrubaturn15}, or other references in the bibliography below. \nocite{handbook10,bivapebegome08} Alternatively the points could be locations in one dimension (such as road accidents recorded on a road network) or in three dimensions (such as cells observed in 3D microscopy). You might also have recorded additional information about each seedling, such as its height, or the number of fronds. Such information, attached to each point in the point pattern, is called a \emph{mark} variable. For example, here is a stand of pine trees, with each tree marked by its diameter at breast height (dbh). The circle radii represent the dbh values (not to scale). <>= data(longleaf) plot(longleaf, main="") @ You might also have recorded supplementary data, such as the terrain elevation, which might serve as explanatory variables. These data can be in any format. \Spst\ does not usually provide capabilities for analysing such data in their own right, but \spst\ does allow such explanatory data to be taken into account in the analysis of a spatial point pattern. \Spst\ is \underline{\bf not} designed to handle point data where the $(x,y)$ locations are fixed (e.g.\ temperature records from the state capital cities in Australia) or where the different $(x,y)$ points represent the same object at different times (e.g.\ hourly locations of a tiger shark with a GPS tag). These are different statistical problems, for which you need different methodology. \section*{What can \spst\ do?} \Spst\ supports a very wide range of popular techniques for statistical analysis for spatial point patterns, for example \begin{itemize} \item kernel estimation of density/intensity \item quadrat counting and clustering indices \item detection of clustering using Ripley's $K$-function \item spatial logistic regression \item model-fitting \item Monte Carlo tests \end{itemize} as well as some advanced statistical techniques. \Spst\ is one of the largest packages available for \R, containing over 1000 commands. It is the product of 25 years of software development by leading researchers in spatial statistics. \section*{How do I start using \spst?} \begin{enumerate} \item Install \R\ on your computer \begin{quote} Go to \texttt{r-project.org} and follow the installation instructions. \end{quote} \item Install the \spst\ package in your \R\ system \begin{quote} Start \R\ and type \verb!install.packages("spatstat")!. If that doesn't work, go to \texttt{r-project.org} to learn how to install Contributed Packages. \end{quote} \item Start \R\ \item Type \texttt{library(spatstat)} to load the package. \item Type \texttt{help(spatstat)} for information. \end{enumerate} \section*{How do I get my data into \spst?} <>= data(finpines) mypattern <- unmark(finpines) mydata <- round(as.data.frame(finpines), 2) @ Here is a cookbook example. Suppose you've recorded the $(x,y)$ locations of seedlings, in an Excel spreadsheet. You should also have recorded the dimensions of the survey area in which the seedlings were mapped. \begin{enumerate} \item In Excel, save the spreadsheet into a comma-separated values (CSV) file. \item Start \R\ \item Read your data into \R\ using \texttt{read.csv}. \begin{quote} If your CSV file is called \texttt{myfile.csv} then you could type something like <>= mydata <- read.csv("myfile.csv") @ to read the data from the file and save them in an object called \texttt{mydata} (or whatever you want to call it). You may need to set various options inside the \texttt{read.csv()} command to get this to work for your file format: type \texttt{help(read.csv)} for information. \end{quote} \item Check that \texttt{mydata} contains the data you expect. \begin{quote} For example, to see the first few rows of data from the spreadsheet, type <<>>= head(mydata) @ To select a particular column of data, you can type \texttt{mydata[,3]} to extract the third column, or \verb!mydata$x! to extract the column labelled \texttt{x}. \end{quote} \item Type \texttt{library(spatstat)} to load the \spst\ package \item Now convert the data to a point pattern object using the \spst\ command \texttt{ppp}. \begin{quote} Suppose that the \texttt{x} and \texttt{y} coordinates were stored in columns 3 and 7 of the spreadsheet. Suppose that the sampling plot was a rectangle, with the $x$ coordinates ranging from 100 to 200, and the $y$ coordinates ranging from 10 to 90. Then you would type <>= mypattern <- ppp(mydata[,3], mydata[,7], c(100,200), c(10,90)) @ The general form is <>= ppp(x.coordinates, y.coordinates, x.range, y.range) @ Note that this only stores the seedling locations. If you have additional columns of data (such as seedling height, seedling sex, etc) these can be added as \emph{marks}, later. \end{quote} \item Check that the point pattern looks right by plotting it: <>= plot(mypattern) @ \item Now you are ready to do some statistical analysis. Try the following: \begin{itemize} \item Basic summary of data: type <>= summary(mypattern) @ \item Ripley's $K$-function: <>= options(SweaveHooks=list(fig=function() par(mar=rep(4,4)+0.1))) @ <>= plot(Kest(mypattern)) @ For more information, type \texttt{help(Kest)} \item Envelopes of $K$-function: <>= plot(envelope(mypattern,Kest)) @ <>= env <- envelope(mypattern,Kest, nsim=39) @ <>= plot(env, main="envelope(mypattern, Kest)") @ <>= options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) @ For more information, type \texttt{help(envelope)} \item kernel smoother of point density: <>= plot(density(mypattern)) @ For more information, type \texttt{help(density.ppp)} \end{itemize} \item Next if you have additional columns of data recording (for example) the seedling height and seedling sex, you can add these data as \emph{marks}. Suppose that columns 5 and 9 of the spreadsheet contained such values. Then do something like <>= marks(mypattern) <- mydata[, c(5,9)] @ <>= mypattern <-finpines @ Now you can try things like the kernel smoother of mark values: <>= plot(Smooth(mypattern)) @ \setkeys{Gin}{width=0.8\textwidth} <>= plot(Smooth(mypattern, sigma=1.2), main="Smooth(mypattern)") @ \setkeys{Gin}{width=0.4\textwidth} \item You are airborne! Now look at the book \cite{baddrubaturn15} for more hints. \end{enumerate} \section*{How do I find out which command to use?} Information sources for \spst\ include: \begin{itemize} \item the Quick Reference guide: a list of the most useful commands. \begin{quote} To view the quick reference guide, start \R, then type \texttt{library(spatstat)} and then \texttt{help(spatstat)}. Alternatively you can download a pdf of the Quick Reference guide from the website \texttt{www.spatstat.org} \end{quote} \item online help: \begin{quote} The online help files are useful --- they give detailed information and advice about each command. They are available when you are running \spst. To get help about a particular command \texttt{blah}, type \texttt{help(blah)}. There is a graphical help interface, which you can start by typing \texttt{help.start()}. Alternatively you can download a pdf of the entire manual (1000 pages!) from the website \texttt{www.spatstat.org}. \end{quote} \item vignettes: \begin{quote} \Spst\ comes installed with several `vignettes' (introductory documents with examples) which can be accessed using the graphical help interface. They include a document about \texttt{Handling shapefiles}. \end{quote} \item book: \begin{quote} Our book \cite{baddrubaturn15} contains a complete course on \texttt{spatstat}. \end{quote} \item website: \begin{quote} Visit the \spst\ package website \texttt{www.spatstat.org} \end{quote} \item forums: \begin{quote} Join the forum \texttt{R-sig-geo} by visiting \texttt{r-project.org}. Then email your questions to the forum. Alternatively you can ask the authors of the \spst\ package (their email addresses are given in the package documentation). \end{quote} \end{itemize} \begin{thebibliography}{10} % \bibitem{badd10wshop} % A. Baddeley. % \newblock Analysing spatial point patterns in {{R}}. % \newblock Technical report, CSIRO, 2010. % \newblock Version 4. % \newblock URL \texttt{https://research.csiro.au/software/r-workshop-notes/} % \bibitem{baddrubaturn15} A. Baddeley, E. Rubak, and R. Turner. \newblock {\em Spatial Point Patterns: Methodology and Applications with {{R}}}. \newblock Chapman \& Hall/CRC Press, 2015. \bibitem{bivapebegome08} R. Bivand, E.J. Pebesma, and V. G{\'{o}}mez-Rubio. \newblock {\em Applied spatial data analysis with {R}}. \newblock Springer, 2008. \bibitem{cres93} N.A.C. Cressie. \newblock {\em Statistics for Spatial Data}. \newblock {John Wiley and Sons}, {New York}, second edition, 1993. \bibitem{digg03} P.J. Diggle. \newblock {\em Statistical Analysis of Spatial Point Patterns}. \newblock Hodder Arnold, London, second edition, 2003. \bibitem{fortdale05} M.J. Fortin and M.R.T. Dale. \newblock {\em Spatial analysis: a guide for ecologists}. \newblock Cambridge University Press, Cambridge, UK, 2005. \bibitem{fothroge09handbook} A.S. Fotheringham and P.A. Rogers, editors. \newblock {\em The {SAGE} {H}andbook on {S}patial {A}nalysis}. \newblock SAGE Publications, London, 2009. \bibitem{gaetguyo09} C. Gaetan and X. Guyon. \newblock {\em Spatial statistics and modeling}. \newblock Springer, 2009. \newblock Translated by Kevin Bleakley. \bibitem{handbook10} A.E. Gelfand, P.J. Diggle, M. Fuentes, and P. Guttorp, editors. \newblock {\em Handbook of Spatial Statistics}. \newblock CRC Press, 2010. \bibitem{illietal08} J. Illian, A. Penttinen, H. Stoyan, and D. Stoyan. \newblock {\em Statistical Analysis and Modelling of Spatial Point Patterns}. \newblock John Wiley and Sons, Chichester, 2008. \bibitem{mollwaag04} J. M{\o}ller and R.P. Waagepetersen. \newblock {\em Statistical Inference and Simulation for Spatial Point Processes}. \newblock Chapman and Hall/CRC, Boca Raton, 2004. \bibitem{pfeietal08} D.U. Pfeiffer, T. Robinson, M. Stevenson, K. Stevens, D. Rogers, and A. Clements. \newblock {\em Spatial analysis in epidemiology}. \newblock Oxford University Press, Oxford, UK, 2008. \bibitem{wallgotw04} L.A. Waller and C.A. Gotway. \newblock {\em Applied spatial statistics for public health data}. \newblock Wiley, 2004. \end{thebibliography} \end{document} spatstat/vignettes/replicated.Rnw0000644000176200001440000014174114141377564016755 0ustar liggesusers\documentclass[11pt]{article} % \VignetteIndexEntry{Analysing Replicated Point Patterns in Spatstat} \usepackage{graphicx} \usepackage{Sweave} \usepackage{bm} \usepackage{anysize} \marginsize{2cm}{2cm}{2cm}{2cm} \newcommand{\pkg}[1]{\texttt{#1}} \newcommand{\code}[1]{\texttt{#1}} \newcommand{\R}{{\sf R}} \newcommand{\spst}{\pkg{spatstat}} \newcommand{\Spst}{\pkg{Spatstat}} \newcommand{\bold}[1]{{\textbf {#1}}} \newcommand{\indicate}[1]{\boldmaths{1}\{ {#1} \}} \newcommand{\dee}[1]{\, {\rm d}{#1}} \newcommand{\boldmaths}[1]{{\ensuremath\boldsymbol{#1}}} \newcommand{\xx}{\boldmaths{x}} \begin{document} \bibliographystyle{plain} \thispagestyle{empty} <>= options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) @ \SweaveOpts{eps=TRUE} \setkeys{Gin}{width=0.6\textwidth} <>= library(spatstat) spatstat.options(image.colfun=function(n) { grey(seq(0,1,length=n)) }) sdate <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Date") sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") options(useFancyQuotes=FALSE) @ \title{Analysing replicated point patterns in \texttt{spatstat}} \author{Adrian Baddeley} \date{For \spst\ version \texttt{\Sexpr{sversion}}} \maketitle \begin{abstract} This document describes \spst's capabilities for fitting models to replicated point patterns. More generally it applies to data from a designed experiment in which the response from each unit is a spatial point pattern. \end{abstract} \tableofcontents \newpage %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Introduction} `Replicated point patterns' are datasets consisting of several point patterns which can be regarded as independent repetitions of the same experiment. For example, three point patterns taken from micrographs of three pipette samples of the same jug of milk, could be assumed to be replicated observations. More generally we could have several experimental groups, with replicated point pattern data in each group. For example there may be two jugs of milk that were treated differently, and we take three pipette samples from each jug. Even more generally our point patterns could be the result of a designed experiment involving control and treatment groups, covariates such as temperature, and even spatial covariates (such as image data). This document describes some capabilities available in the \spst\ package for analysing such data. \textbf{For further detail, see Chapter 16 of the spatstat book \cite{TheBook}.} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Overview of software} The main components needed are: \begin{itemize} \item the model-fitting function \texttt{mppm}, an extension of the \texttt{spatstat} function \texttt{ppm}, that will fit Gibbs point process models to multiple point pattern datasets; \item support for the class \texttt{"mppm"} of point process models fitted by \texttt{mppm} (e.g. functions to print and plot the fitted model, analysis of deviance for Poisson models) \item some tools for exploratory data analysis; \item basic support for the data from such experiments by storing the data in a \emph{``hyperframe''}. A hyperframe is like a data frame, except that each entry in a column can be a point pattern or a pixel image, as well as a single number or categorical value. \item four example datasets. \end{itemize} \section{Formulating the problem} We view the experiment as involving a series of {\em `units'\/}. Each unit is subjected to a known set of experimental conditions (described by the values of the {\em covariates\/}), and each unit yields a {\em response\/} which is a spatial point pattern. The value of a particular covariate for each unit can be either a single value (numerical, logical or factor), or a pixel image. Three important cases are: \begin{description} \item[independent replicates:] We observe $n$ different point patterns that can be regarded as independent replicates, i.e.\ independent realisations of the same point process. The `responses' are the point patterns; there are no covariates. \item[replication in groups:] there are $K$ different experimental groups (e.g. control, aspirin, nurofen). In group $k$ ($k=1,\ldots,K$) we observe $n_k$ point patterns which can be regarded as independent replicates within this group. We regard this as an experiment with $n = \sum_k n_k$ units. The responses are the point patterns; there is one covariate which is a factor (categorical variable) identifying which group each point pattern belongs to. \item[general case:] there are covariates other than factors that influence the response. The point patterns are assumed to be independent, but no two patterns have the same distribution. \end{description} Examples of these three cases are given in the datasets \texttt{waterstriders}, \texttt{pyramidal} and \texttt{demohyper} respectively, which are installed in \spst. \section{Installed datasets} The following datasets are currently installed in \spst. \begin{itemize} \item \texttt{waterstriders}: Penttinen's \cite{pent84} waterstriders data recording the locations of insect larvae on a pond in 3 independent experiments. \item \texttt{pyramidal}: data from Diggle, Lange and Benes \cite{digglangbene91} on the locations of pyramidal neurons in human brain, 31 human subjects grouped into 3 groups (controls, schizoaffective and schizophrenic). \item \texttt{flu}: data from Chen et al \cite{chenetal08} giving the locations of two different virus proteins on the membranes of cells infected with influenza virus; 41 multitype point patterns divided into two virus types (wild and mutant) and two stain types. \item \texttt{simba}: simulated data from an experiment with two groups and 5 replicate point patterns per group. \item \texttt{demohyper}: simulated data from an experiment with two groups in which each experimental unit has a point pattern response and a pixel image covariate. \end{itemize} \section{Lists of point patterns} First we need a convenient way to store the \emph{responses} from all the units in an experiment. An individual point pattern is stored as an object of class \verb!"ppp"!. The easiest way to store all the responses is to form a list of \verb!"ppp"! objects. \subsection{Waterstriders data} The \texttt{waterstriders} data are an example of this type. The data consist of 3 independent point patterns representing the locations of insect larvae on a pond. See \texttt{help(waterstriders)}. <<>>= waterstriders @ The \texttt{waterstriders} dataset is a list of point patterns. It is a list, each of whose entries is a point pattern (object of class \verb!"ppp"!). Note that the observation windows of the three point patterns are {\tt not\/} identical. \subsection{The class \texttt{listof}} For convenience, the \texttt{waterstriders} dataset also belongs to the class \verb!"listof"!. This is a simple mechanism to allow us to handle the list neatly --- for example, we can provide special methods for printing, plotting and summarising the list. \SweaveOpts{width=6,height=2} \setkeys{Gin}{width=0.9\textwidth} <>= plot(waterstriders, main="") @ Notice that the plot method displays each entry of the list in a separate panel. There's also the summary method: <<>>= summary(waterstriders) @ \subsection{Creating a \texttt{listof} object} For example, here is a simulated dataset containing three independent realisations of the Poisson process with intensity 100. <<>>= X <- listof(rpoispp(100), rpoispp(100), rpoispp(100)) @ Then it can be printed and plotted. <>= plot(X) X @ To convert an existing list to the class \code{listof}, use \code{as.listof}. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Hyperframes} A \emph{hyperframe} is like a data frame, except that its entries can be objects of any kind. A hyperframe is effectively a two-dimensional array in which each column consists of values of one type (as in a data frame) or consists of objects of one class. The entries in a hyperframe can be point patterns, pixel images, windows, or any other objects. To analyse an experiment, we will store {\bf all} the data from the experiment in a single hyperframe. The rows of the hyperframe will correspond to different experimental units, while the columns represent different variables (response variables or covariates). \subsection{Creating hyperframes} The function \texttt{hyperframe} will create a hyperframe. <>= hyperframe(...) @ The arguments \verb!...! are any number of arguments of the form \texttt{tag=value}. Each \texttt{value} will become a column of the array. The \texttt{tag} determines the name of the column. Each \texttt{value} can be either \begin{itemize} \item an atomic vector or factor (i.e. numeric vector, integer vector, character vector, logical vector, complex vector or factor) \item a list of objects which are all of the same class \item one atomic value, which will be replicated to make an atomic vector or factor \item one object, which will be replicated to make a list of identical objects. \end{itemize} All columns (vectors, factors and lists) must be of the same length, if their length is greater than 1. For example, here is a hyperframe containing a column of numbers and a column of \emph{functions}: <<>>= H <- hyperframe(X=1:3, Y=list(sin,cos,tan)) H @ Note that a column of character strings will be converted to a factor, unless you set \texttt{stringsAsFactors=FALSE} in the call to \code{hyperframe}. This is the same behaviour as for the function \code{data.frame}. <<>>= G <- hyperframe(X=1:3, Y=letters[1:3], Z=factor(letters[1:3]), W=list(rpoispp(100),rpoispp(100), rpoispp(100)), U=42, V=rpoispp(100), stringsAsFactors=FALSE) G @ This hyperframe has 3 rows and 6 columns. The columns named \texttt{U} and \texttt{V} are constant (all entries in a column are the same). The column named \texttt{Y} is a character vector while \texttt{Z} is a factor. \subsection{Hyperframes of data} To analyse an experiment, we will store {\bf all} the data from the experiment in a single hyperframe. The rows of the hyperframe will correspond to different experimental units, while the columns represent different variables (response variables or covariates). Several examples of hyperframes are provided with the package, including \texttt{demohyper}, \texttt{flu}, \texttt{simba} and \texttt{pyramidal}, described above. The \texttt{simba} dataset contains simulated data from an experiment with a `control' group and a `treatment' group, each group containing 5 experimental units. The responses in the control group are independent Poisson point patterns with intensity 80. The responses in the treatment group are independent realisations of a Strauss process (see \texttt{help(simba)} for details). The \texttt{simba} dataset is a hyperframe with 10 rows and 2 columns: \texttt{Points} (the point patterns) and \texttt{group} (a factor with levels \texttt{control} and \texttt{treatment}). <<>>= simba @ The \texttt{pyramidal} dataset contains data from Diggle, Lange and Benes \cite{digglangbene91} on the locations of pyramidal neurons in human brain. One point pattern was observed in each of 31 human subjects. The subjects were classified into 3 groups (controls, schizoaffective and schizophrenic). The \texttt{pyramidal} dataset is a hyperframe with 31 rows and 2 columns: \code{Neurons} (the point patterns) and \code{group} (a factor with levels \texttt{control}, \texttt{schizoaffective} and \texttt{schizophrenic}). <<>>= pyramidal @ The \texttt{waterstriders} dataset is not a hyperframe; it's just a list of point patterns. It can easily be converted into a hyperframe: <<>>= ws <- hyperframe(Striders=waterstriders) @ \subsection{Columns of a hyperframe} Individual columns of a hyperframe can be extracted using \verb!$!: <<>>= H$X H$Y @ The result of \verb!$! is a vector or factor if the column contains atomic values; otherwise it is a list of objects (with class \texttt{"listof"} to make it easier to print and plot). Individual columns can also be assigned (overwritten or created) using \verb!$<-!: <<>>= H$U <- letters[1:3] H @ This can be used to build up a hyperframe column-by-column: <<>>= G <- hyperframe() G$X <- waterstriders G$Y <- 1:3 G @ \subsection{Subsets of a hyperframe} Other subsets of a hyperframe can be extracted with \verb![!: <<>>= H[,1] H[2,] H[2:3, ] H[1,1] @ The result of \verb![! is a hyperframe, unless you set \verb!drop=TRUE! and the subset consists of only one element or one column: <<>>= H[,1,drop=TRUE] H[1,1,drop=TRUE] H[1,2,drop=TRUE] @ There is also a method for \verb![<-! that allows you to assign values to a subset of a hyperframe. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Plotting} \subsection{Plotting a \code{listof} object} The plot method for \code{listof} objects has formal arguments <>= plot.listof(x, ..., main, arrange = TRUE, nrows = NULL, ncols = NULL) @ where \code{main} is a title for the entire page. If \code{arrange=TRUE} then the entries of the list are displayed in separate panels on the same page (with \code{nrows} rows and \code{ncols} columns of panels), while if \code{arrange=FALSE} then the entries are just plotted as a series of plot frames. The extra arguments \verb!...! control the individual plot panels. These arguments will be passed to the plot method that displays each entry of the list. Suitable arguments depend on the type of entries. <>= plot(waterstriders, pch=16, nrows=1) @ \subsection{Plotting a hyperframe} \subsubsection{Plotting one column} If \code{h} is a hyperframe, then the default action of \code{plot(h)} is to extract the first column of \code{h} and plot each of the entries in a separate panel on one page (actually using the plot method for class \verb!"listof"!). \SweaveOpts{width=7,height=5} \setkeys{Gin}{width=0.9\textwidth} <>= plot(simba) @ This only works if the entries in the first column are objects for which a plot method is defined (for example, point patterns, images, windows). To select a different column, use \verb!$! or \verb![!: \SweaveOpts{width=6,height=2} \setkeys{Gin}{width=0.9\textwidth} <>= H <- hyperframe(X=1:3, Y=list(sin,cos,tan)) plot(H$Y) @ The plot can be controlled using the arguments for \code{plot.listof} (and, in this case, \code{plot.function}, since \verb!H$Y! consists of functions). \subsubsection{Complex plots} More generally, we can display any kind of higher-order plot involving one or more columns of a hyperframe: <>= plot(h, e) @ where \code{h} is a hyperframe and \code{e} is an \R\ language call or expression that must be evaluated in each row to generate each plot panel. \SweaveOpts{width=9,height=5} \setkeys{Gin}{width=0.9\textwidth} <>= plot(demohyper, quote({ plot(Image, main=""); plot(Points, add=TRUE) })) @ Note the use of \code{quote}, which prevents the code inside the braces from being evaluated immediately. To plot the $K$-functions of each of the patterns in the \code{waterstriders} dataset, \SweaveOpts{width=6,height=2} \setkeys{Gin}{width=0.9\textwidth} <>= H <- hyperframe(Bugs=waterstriders) plot(H, quote(plot(Kest(Bugs))), marsize=1) @ %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Data analysis} \subsection{Computing with hyperframes} Often we want to perform some computation on each row of a hyperframe. In a data frame, this can be done using the command \code{with}: <<>>= df <- data.frame(A=1:10, B=10:1) with(df, A-B) @ In this example, the expression \code{A-B} is evaluated in each row of the data frame, and the result is a vector containing the computed values for each row. The function \code{with} is generic, and has a method for data frames, \code{with.data.frame}. The computation above was executed by \code{with.data.frame}. The same syntax is available for hyperframes using the method \code{with.hyperframe}: <>= with(h,e) @ Here \code{h} is a hyperframe, and \code{e} is an {\sf R} language construct involving the names of columns in \code{h}. For each row of \code{h}, the expression \code{e} will be evaluated in such a way that each entry in the row is identified by its column name. <<>>= H <- hyperframe(Bugs=waterstriders) with(H, npoints(Bugs)) with(H, distmap(Bugs)) @ The result of \code{with.hyperframe} is a list of objects (of class \verb!"listof"!), or a vector or factor if appropriate. Notice that (unlike the situation for data frames) the operations in the expression \code{e} do not have to be vectorised. For example, \code{distmap} expects a single point pattern, and is not vectorised to deal with a list of point patterns. Instead, the expression \code{distmap(Bugs)} is evaluated separately in each row of the hyperframe. \subsection{Summary statistics} One application of \code{with.hyperframe} is to calculate summary statistics for each row of a hyperframe. For example, the number of points in a point pattern \code{X} is returned by \code{npoints(X)}. To calculate this for each of the responses in the \code{simba} dataset, <<>>= with(simba, npoints(Points)) @ The summary statistic can be any kind of object. For example, to compute the empirical $K$-functions for each of the patterns in the \code{waterstriders} dataset, <<>>= H <- hyperframe(Bugs=waterstriders) K <- with(H, Kest(Bugs)) @ To plot these $K$-functions you can then just type \SweaveOpts{width=6,height=2} \setkeys{Gin}{width=0.9\textwidth} <>= plot(K) @ The summary statistic for each row could be a numeric vector: <<>>= H <- hyperframe(Bugs=waterstriders) with(H, nndist(Bugs)) @ The result is a list, each entry being a vector of nearest neighbour distances. To find the minimum interpoint distance in each pattern: <<>>= with(H, min(nndist(Bugs))) @ \subsection{Generating new columns} New columns of a hyperframe can be created by computation from the existing columns. For example, I can add a new column to the \code{simba} dataset that contains pixel images of the distance maps for each of the point pattern responses. <>= simba$Dist <- with(simba, distmap(Points)) @ \subsection{Simulation} This can be useful for simulation. For example, to generate Poisson point patterns with different intensities, where the intensities are given by a numeric vector \code{lambda}: \SweaveOpts{width=6,height=6} \setkeys{Gin}{width=0.7\textwidth} <>= lambda <- rexp(6, rate=1/50) H <- hyperframe(lambda=lambda) H$Points <- with(H, rpoispp(lambda)) plot(H, quote(plot(Points, main=paste("lambda=", signif(lambda, 4))))) @ It's even simpler to generate 10 independent Poisson point patterns with the \emph{same} intensity 50, say: <>= H$X <- with(H, rpoispp(50)) @ \noindent The expression \code{rpoispp(50)} is evaluated once in each row, yielding a different point pattern in each row because of the randomness. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Exploratory data analysis} Before fitting models to the data, it is prudent to explore the data to detect unusual features and to suggest appropriate models. \subsection{Exploring spatial trend and covariate effects} Points may be distributed non-uniformly either because they are intrinsically non-uniform (``spatial trend'') or because their abundance depends on a spatial covariate (``covariate effects''). Non-uniformity of a point pattern can be investigated using the kernel smoothed intensity. This is the convolution of the point pattern with a smooth density called the kernel. Effectively each point in the pattern is replaced by a copy of the kernel, and the sum of all copies of the kernel is the kernel-smoothed intensity function. It is computed by \texttt{density.ppp} separately for each point pattern. <>= plot(simba, quote(plot(density(Points), main="")), nrows=2) @ Covariate effects due to a real-valued spatial covariate (a real-valued pixel image) can be investigated using the command \code{rhohat}. This uses a kernel smoothing technique to fit a model of the form \[ \lambda(u) = \rho(Z(u)) \] where $\lambda(u)$ is the point process intensity at a location $u$, and $Z(u)$ is the value of the spatial covariate at that location. Here $\rho$ is an unknown, smooth function which is to be estimated. The function $\rho$ expresses the effect of the spatial covariate on the point process intensity. If $\rho$ turns out to be constant, then the covariate has no effect on point process intensity (and the constant value of $\rho$ is the constant intensity of the point process). <>= rhos <- with(demohyper, rhohat(Points, Image)) plot(rhos) @ \SweaveOpts{width=6,height=4} \setkeys{Gin}{width=0.9\textwidth} \subsection{Exploring interpoint interaction} Still to be written. See Chapter 16 of \cite{baddrubaturn15}. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Fitting models of spatial trend} The command \code{mppm} fits models to multiple point patterns. Its syntax is very similar to that of \code{lm} and \code{glm}: <>= mppm(formula, data, interaction, ...) @ where \code{formula} is a formula describing the systematic trend part of the model, \code{data} is a hyperframe containing all the data (responses and covariates), and \code{interaction} determines the stochastic interpoint interaction part of the model. For example: <>= mppm(Points ~ group, simba, Poisson()) @ Note that the formula has a left hand side, which identifies the response. This should be the name of a column of \code{data}. \subsection{Trend formula} The right side of \code{formula} is an expression for the linear predictor (effectively the {\bf logarithm} of the spatial trend). The variables appearing in the right hand side of \code{formula} should be either \begin{itemize} \item names of columns in \code{data} \item objects in the {\sf R} global environment (such as \code{pi} and \code{log}) \item the reserved names \code{x}, \code{y} (representing Cartesian coordinates), \code{marks} (representing mark values attached to points) or \code{id} (a factor representing the row number in the hyperframe). \end{itemize} \subsubsection{Design covariates} The variables in the trend could be `design covariates'. For example, to fit a model to the \code{simba} dataset in which all patterns are independent replicates of the same uniform Poisson process, with the same constant intensity: <<>>= mppm(Points ~ 1, simba) @ To fit a model in which the two groups of patterns (control and treatment groups) each consist of independent replicates of a uniform Poisson process, but with possibly different intensity in each group: <<>>= mppm(Points ~ group, simba) @ To fit a uniform Poisson process to each pattern, with different intensity for each pattern: <<>>= mppm(Points ~ id, simba) @ \subsubsection{Spatial covariates} The variables in the trend could be `spatial covariates'. For example, the \code{demohyper} dataset has a column \code{Image} containing pixel images. <<>>= mppm(Points ~ Image, data=demohyper) @ This model postulates that each pattern is a Poisson process with intensity of the form \[ \lambda(u) = \exp(\beta_0 + \beta_1 Z(u)) \] at location $u$, where $\beta_0, \beta_1$ are coefficients to be estimated, and $Z(u)$ is the value of the pixel image \code{Image} at location $u$. It may or may not be appropriate to assume that the intensity of the points is an exponential function of the image pixel value $Z$. If instead we wanted the intensity $\lambda(u)$ to be \emph{proportional} to $Z(u)$, the appropriate model is <>= mppm(Points ~ offset(log(Image)), data=demohyper) @ which corresponds to an intensity proportional to \code{Image}, \[ \lambda(u) = \exp(\beta_0 + \log Z(u)) = e^{\beta_0} \; Z(u). \] The \code{offset} indicates that there is no coefficient in front of $\log Z(u)$. Alternatively we could allow a coefficient: <>= mppm(Points ~ log(Image), data=demop) @ which corresponds to a gamma transformation of \code{Image}, \[ \lambda(u) = \exp(\beta_0 + \beta_1 \log Z(u)) = e^{\beta_0} \; Z(u)^{\beta_1}. \] %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Interpoint interaction} The stochastic interpoint interaction in a point process model is specified by the arguments \code{interaction} and (optionally) \code{iformula} in <>= mppm(formula, data, interaction, ..., iformula=NULL) @ \subsection{Same interaction for all patterns} In the simplest case, the argument \texttt{interaction} is one of the familiar objects that describe the point process interaction structure. It is an object of class \texttt{"interact"} created by calling one of the functions \begin{center} \begin{tabular}{rl} \texttt{Poisson()} & the Poisson point process\\ \texttt{Hardcore()} & the hard core process \\ \texttt{Strauss()} & the Strauss process \\ \texttt{StraussHard()} & the Strauss/hard core point process\\ \texttt{Softcore()} & pairwise interaction, soft core potential\\ \texttt{PairPiece()} & pairwise interaction, piecewise constant \\ \texttt{DiggleGatesStibbard() } & Diggle-Gates-Stibbard pair potential \\ \texttt{DiggleGratton() } & Diggle-Gratton pair potential \\ \texttt{Fiksel() } & Fiksel pair potential \\ \texttt{LennardJones() } & Lennard-Jones pair potential \\ \texttt{Pairwise()} & pairwise interaction, user-supplied potential\\ \texttt{AreaInter()} & area-interaction potential\\ \texttt{Geyer()} & Geyer's saturation process\\ \texttt{BadGey()} & multiscale Geyer saturation process\\ \texttt{Saturated()} & Saturated pair model, user-supplied potential\\ \texttt{OrdThresh()} & Ord process, threshold potential\\ \texttt{Ord()} & Ord model, user-supplied potential \\ \texttt{MultiStrauss()} & multitype Strauss process \\ \texttt{MultiStraussHard()} & multitype Strauss/hard core process \\ \texttt{Concom()} & connected component interaction \\ \texttt{Hybrid()} & hybrid of several interactions \\ \end{tabular} \end{center} In this `simple' usage of \texttt{mppm}, the point process model assumes that all point patterns have exactly the same interpoint interaction, (with the same interaction parameters), and only differ in their spatial trend. \subsection{Hyperframe of interactions} More generally the argument \code{interaction} can be a hyperframe containing objects of class \texttt{"interact"}. For example, we might want to fit a Strauss process to each point pattern, but with a different Strauss interaction radius for each pattern. <>= radii <- with(simba, mean(nndist(Points))) @ Then \code{radii} is a vector of numbers which we could use as the values of the interaction radius for each case. First we need to make the interaction objects: <<>>= Rad <- hyperframe(R=radii) Str <- with(Rad, Strauss(R)) @ Then we put them into a hyperframe and fit the model: <<>>= Int <- hyperframe(str=Str) mppm(Points ~ 1, simba, interaction=Int) @ An important constraint is that all of the interaction objects in one column must be \emph{instances of the same process} (e.g. Strauss) albeit possibly having different parameter values. For example, you cannot put Poisson and Strauss processes in the same column. \subsection{Interaction formula} If \code{interaction} is a hyperframe, then the additional argument \code{iformula} may be used to fully specify the interaction. (An \code{iformula} is also required if \code{interaction} has more than one column.) The \code{iformula} should be a formula without a left hand side. Variables on the right hand side are typically the names of columns in \code{interaction}. \subsubsection{Selecting one column} If the right hand side of \code{iformula} is a single name, then this identifies the column in \code{interaction} to be used as the interpoint interaction structure. <<>>= h <- hyperframe(Y=waterstriders) g <- hyperframe(po=Poisson(), str4 = Strauss(4), str7= Strauss(7)) mppm(Y ~ 1, data=h, interaction=g, iformula=~str4) @ \subsubsection{Interaction depending on design} The \code{iformula} can also involve columns of \code{data}, but only those columns that are vectors or factors. This allows us to specify an interaction that depends on the experimental design. [This feature is {\bf experimental}.] For example <<>>= fit <- mppm(Points ~ 1, simba, Strauss(0.07), iformula = ~Interaction*group) @ Since \code{Strauss(0.1)} is not a hyperframe, it is first converted to a hyperframe with a single column named \code{Interaction}. The \code{iformula = ~Interaction*group} specifies (since \code{group} is a factor) that the interpoint interaction shall have a different coefficient in each experimental group. That is, we fit a model which has two different values for the Strauss interaction parameter $\gamma$, one for the control group and one for the treatment group. When you print the result of such a fit, the package tries to do `automatic interpretation' of the fitted model (translating the fitted interaction coefficients into meaningful numbers like $\gamma$). This will be successful in \emph{most} cases: <<>>= fit @ <>= co <- coef(fit) si <- function(x) { signif(x, 4) } @ Thus we see that the estimate of the Strauss parameter $\gamma$ for the control group is \Sexpr{si(exp(co[2]))}, and for the treatment group \Sexpr{si(exp(sum(co[c(2,4)])))} (the correct values in this simulated dataset were $1$ and $0.5$). The fitted model can also be interpreted directly from the fitted canonical coefficients: <<>>= coef(fit) @ The last output shows all the coefficients $\beta_j$ in the linear predictor for the (log) conditional intensity. The interpretation of the model coefficients, for any fitted model in \R, depends on the \emph{contrasts} which were applicable when the model was fitted. This is part of the core {\sf R} system: see \code{help(contrasts)} or \code{options(contrasts)}. If you did not specify otherwise, the default is to use \emph{treatment contrasts}. This means that, for an explanatory variable which is a \texttt{factor} with $N$ levels, the first level of the factor is used as a baseline, and the fitted model coefficients represent the factor levels $2, 3, \ldots, N$ relative to this baseline. In the output above, there is a coefficient for \code{(Intercept)} and one for \code{grouptreatment}. These are coefficients related to the \code{group} factor. According to the ``treatment contrasts'' rule, the \code{(Intercept)} coefficient is the estimated effect for the control group, and the \code{grouptreatment} coefficient is the estimated difference between the treatment and control groups. Thus the fitted first order trend is $\exp(\Sexpr{si(co[1])}) = \Sexpr{si(exp(co[1]))}$ for the control group and $\exp(\Sexpr{si(co[1])} + \Sexpr{si(co[3])}) = \Sexpr{si(exp(sum(co[c(1,3)])))}$ for the treatment group. The correct values in this simulated dataset were $80$ and $100$. The remaining coefficients in the output are \code{Interaction} and \code{Interaction:grouptreatment}. Recall that the Strauss process interaction term is $\gamma^{t(u,\xx)} = \exp(t(u,\xx) \log\gamma)$ at a spatial location $u$, for a point pattern $\xx$. Since we're using treatment contrasts, the coefficient \code{Interaction} is the estimate of $\log\gamma$ for the control group. The coefficient \code{Interaction:grouptreatment} is the estimate of the difference in $\log\gamma$ between the treatment and control groups. Thus the estimated Strauss interaction parameter $\gamma$ is $\exp(\Sexpr{si(co[2])}) = \Sexpr{si(exp(co[2]))}$ for the control group and $\exp(\Sexpr{si(co[2])} + (\Sexpr{si(co[4])})) = \Sexpr{si(exp(co[2]+co[4]))}$ for the treatment group. The correct values were $1$ and $0.5$. \subsubsection{Completely different interactions for different cases} In the previous example, when we fitted a Strauss model to all point patterns in the \code{simba} dataset, the fitted model for the patterns in the control group was close to Poisson ($\gamma \approx 1$). Suppose we now want to fit a model which {\it is} Poisson in the control group, and Strauss in the treatment group. The Poisson and Strauss interactions must be given as separate columns in a hyperframe of interactions: <>= interaction=hyperframe(po=Poisson(), str=Strauss(0.07)) @ What do we write for the \code{iformula}? The following \emph{will not} work: <>= iformula=~ifelse(group=="control", po, str) @ This does not work because the Poisson and Strauss models are `incompatible' inside such expressions. The canonical sufficient statistics for the Poisson and Strauss processes do not have the same dimension. Internally in \code{mppm} we translate the symbols \code{po} and \code{str} into matrices; the dimensions of these matrices are different, so the \code{ifelse} expression cannot be evaluated. Instead we need something like the following: <>= iformula=~I((group=="control")*po) + I((group=="treatment") * str) @ The letter \code{I} here is a standard R function that prevents its argument from being interpreted as a formula (thus the \code{*} is interpreted as multiplication instead of a model interaction). The expression \code{(group=="control")} is logical, and when multiplied by the matrix \code{po}, yields a matrix. So the following does work: <<>>= g <- hyperframe(po=Poisson(), str=Strauss(0.07)) fit2 <- mppm(Points ~ 1, simba, g, iformula=~I((group=="control")*po) + I((group=="treatment") * str)) fit2 @ %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %#%^!ifdef RANDOMEFFECTS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Random effects} \subsection{Mixed effects models} It is also possible to fit models that include `random effects'. Effectively, some of the coefficients in the model are assumed to be Normally-distributed random variables instead of constants. \subsubsection{Mixed Poisson model} Consider the simplest model of a uniform Poisson process which we fitted to the 3 point patterns of waterstriders. It might be sensible to assume that each pattern is a realisation of a Poisson process, but with {\em random intensity\/}. In each realisation the intensity $\lambda$ is constant across different locations, but it is a different, random value in different realisations. This example is called a `mixed Poisson process' and belongs to the class of `Cox processes' (Poisson processes with random intensity functions). Let's assume further that the log-intensity is a Normal random variable. Then the model is a (very degenerate) special case of a `log-Gaussian Cox process'. To fit such a model we use the standard techniques of mixed effects models \cite{lairware82,davigilt95,pinhbate00}. The mixed Poisson process which we discussed above would be written in standard form \begin{equation} \label{mixPois} \lambda_i(u) = \exp(\mu + Z_i) \end{equation} for the $i$th point pattern, where $\mu$ is a parameter to be estimated (the `fixed effect') and $Z_i \sim N(0, \sigma^2)$ is a zero-mean Normal random variable (the `random effect' for point pattern $i$). In the simplest case we would assume that $Z_1, \ldots, Z_n$ are independent. The variance $\sigma^2$ of the random effects would be estimated. One can also estimate the individual realised values $z_i$ of the random effects for each point pattern, although these are usually not of such great interest. Since the model includes both fixed and random effects, it is called a ``mixed-effects'' model. \subsubsection{Dependence structure} When we formulate a random-effects or mixed-effects model, we must specify the dependence structure of the random effects. In the model above we assumed that the $Z_i$ are independent for all point patterns $i$. If the experiment consists of two groups, we could alternatively assume that $Z_i = Z_j$ whenever $i$ and $j$ belong to the same group. In other words all the patterns in one group have the same value of the random effect. So the random effect is associated with the group rather than with individual patterns. This could be appropriate if, for example, the groups represent different batches of a chemical. Each batch is prepared under slightly different conditions so we believe that there are random variations between batches, but within a batch we believe that the chemical is well-mixed. \subsubsection{Random effects are coefficients} In the mixed Poisson model (\ref{mixPois}), the random effect is an additive constant (with a random value) in the log-intensity. In general, a random effect is a \emph{coefficient} of one of the covariates. For example if $v$ is a real-valued design covariate (e.g. `temperature'), with value $v_i$ for the $i$th point pattern, then we could assume \begin{equation} \label{ranef2} \lambda_i(u) = \exp(\mu + Z_i v_i) \end{equation} where $Z_i \sim N(0, \sigma^2)$ are independent for different $i$. This model has a random effect in the dependence on $v$. We could also have a random effect for a spatial covariate $V$. Suppose $V_i$ is a real-valued image for the $i$th pattern (so that $V_i(u)$ is the value of some covariate at the location $u$ for the $i$th case). Then we could assume \begin{equation} \label{ranef3} \lambda_i(u) = \exp(\mu + Z_i V_i(u)) \end{equation} where $Z_i \sim N(0, \sigma^2)$ are independent for different $i$. This kind of random effect would be appropriate if, for example, the images $V_i$ are not `normalised' or `standardised' relative to each other (e.g.\ they are images taken under different illumination). Then the coefficients $Z_i$ effectively include the rescaling necessary to standardise the images. \subsection{Fitting a mixed-effects model} The call to \texttt{mppm} can also include the argument \texttt{random}. This should be a formula (with no left-hand side) describing the structure of random effects. The formula for random effects must be recognisable to \texttt{lme}. It is typically of the form \begin{verbatim} ~x1 + ... + xn | g \end{verbatim} or \begin{verbatim} ~x1 + ... + xn | g1/.../gm \end{verbatim} where \verb!x1 + ... + xn! specifies the covariates for the random effects and \texttt{g} or \verb!g1/.../gm! determines the grouping (dependence) structure. Here \code{g} or \code{g1, \ldots, gm} should be factors. To fit the mixed Poisson model (\ref{mixPois}) to the waterstriders, we want to have a random intercept coefficient (so \texttt{x} is \texttt{1}) that varies for different point patterns (so \texttt{g} is \texttt{id}). The reserved name \code{id} is a factor referring to the individual point pattern. Thus <<>>= H <- hyperframe(P=waterstriders) mppm(P ~ 1, H, random=~1|id) @ To fit the mixed effects model (\ref{ranef2}) to the coculture data with the \code{AstroIm} covariate, with a random effect associated with each well, <>= mppm(Neurons ~ AstroIm, random=~AstroIm|WellNumber) @ %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %#%^!endif %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Studying the fitted model} Fitted models produced by \code{mppm} can be examined and validated in many ways. \subsection{Fits for each pattern} \subsubsection{Subfits} The command \code{subfits} takes an \code{mppm} object and extracts, for each individual point pattern, the fitted point process model for that pattern \emph{that is implied by the overall fit}. It returns a list of objects of class \code{ppm}. <<>>= H <- hyperframe(W=waterstriders) fit <- mppm(W ~ 1, H) subfits(fit) @ In this example the result is a list of three \code{ppm} objects representing the implied fits for each of the three point patterns in the \code{waterstriders} dataset. Notice that {\bf the fitted coefficients are the same} in all three models. Note that there are some unresolved difficulties with the implementation of \code{subfits}. Two completely different implementations are supplied in the package; they are called \code{subfits.old} %(used in versions 0.1--1 and earlier) and \code{subfits.new}.% (introduced in 0.1--2). The old version would occasionally crash. Unfortunately the newer version \code{subfits.new} is quite memory-hungry and sometimes causes R to hang. We're still working on this problem. So for the time being, \code{subfits} is the same as \code{subfits.old}. You can change this simply by reassigning, e.g. <>= subfits <- subfits.new @ \subsubsection{Fitting separately to each pattern} For comparison, we could fit a point process model separately to each point pattern dataset using \code{ppm}. The easy way to do this is with \code{with.hyperframe}. To fit a \emph{separate} uniform Poisson point process to each of the three waterstriders patterns, <<>>= H <- hyperframe(W=waterstriders) with(H, ppm(W)) @ The result is again a list of three fitted point process models (objects of class \code{ppm}), but now the fitted coefficients are different. \subsection{Residuals} One standard way to check a fitted model is to examine the residuals. \subsubsection{Point process residuals} Some recent papers \cite{baddetal05,baddmollpake08} have defined residuals for a fitted point process model (fitted to a \emph{single} point pattern). These residuals are implemented in \code{spatstat} as \code{residuals.ppm} and apply to an object of class \code{ppm}, that is, a model fitted to a \emph{single} point pattern. The command \code{residuals.mppm} computes the point process residuals for an \code{mppm} object. <<>>= fit <- mppm(P ~ x, hyperframe(P=waterstriders)) res <- residuals(fit) @ The result is a list, with one entry for each of the point pattern datasets. Each list entry contains the point process residuals for the corresponding point pattern dataset. Each entry in the list is a signed measure (object of class \code{"msr"}) as explained in the help for \code{residuals.ppm}). It can be plotted: <>= plot(res) @ You probably want the smoothed residual field: <>= smor <- with(hyperframe(res=res), Smooth(res, sigma=4)) plot(smor) @ \subsubsection{Sums of residuals} It would be useful to have a residual that is a single value for each point pattern (representing how much that point pattern departs from the model fitted to all the point patterns). That can be computed by \emph{integrating} the residual measures using the function \code{integral.msr}: <<>>= fit <- mppm(P ~ x, hyperframe(P=waterstriders)) res <- residuals(fit) totres <- sapply(res, integral.msr) @ In designed experiments we can plot these total residuals against the design covariates: <>= fit <- mppm(Points~Image, data=demohyper) resids <- residuals(fit, type="Pearson") totres <- sapply(resids, integral.msr) areas <- with(demohyper, area.owin(as.owin(Points))) df <- as.data.frame(demohyper[, "Group"]) df$resids <- totres/areas plot(resids~Group, df) @ \subsubsection{Four-panel diagnostic plots} Sometimes a more useful tool is the function \code{diagnose.ppm} which produces a four-panel diagnostic plot based on the point process residuals. However, it is only available for \code{ppm} objects. To obtain a four-panel diagnostic plot for each of the point patterns, do the following: \begin{enumerate} \item fit a model to multiple point patterns using \code{mppm}. \item extract the individual fits using \code{subfits}. \item plot the residuals of the individual fits. \end{enumerate} For example: <>= fit <- mppm(P ~ 1, hyperframe(P=waterstriders)) sub <- hyperframe(Model=subfits(fit)) plot(sub, quote(diagnose.ppm(Model))) @ (One could also do this for models fitted separately to the individual point patterns.) \subsubsection{Residuals of the parameter estimates} We can also compare the parameter estimates obtained by fitting the model simultaneously to all patterns (using \code{mppm}) with those obtained by fitting the model separately to each pattern (using \code{ppm}). <<>>= H <- hyperframe(P = waterstriders) fitall <- mppm(P ~ 1, H) together <- subfits(fitall) separate <- with(H, ppm(P)) Fits <- hyperframe(Together=together, Separate=separate) dr <- with(Fits, unlist(coef(Separate)) - unlist(coef(Together))) dr exp(dr) @ One could also try deletion residuals, etc. \subsection{Goodness-of-fit tests} \subsubsection{Quadrat count test} The $\chi^2$ goodness-of-fit test based on quadrat counts is implemented for objects of class \code{ppm} (in \code{quadrat.test.ppm}) and also for objects of class \code{mppm} (in \code{quadrat.test.mppm}). This is a goodness-of-fit test for a fitted {\bf Poisson} point process model only. The model could be uniform or non-uniform and the intensity might depend on covariates. <<>>= H <- hyperframe(X=waterstriders) # Poisson with constant intensity for all patterns fit1 <- mppm(X~1, H) quadrat.test(fit1, nx=2) # uniform Poisson with different intensity for each pattern fit2 <- mppm(X ~ id, H) quadrat.test(fit2, nx=2) @ See the help for \code{quadrat.test.ppm} and \code{quadrat.test.mppm} for further details. \subsubsection{Kolmogorov-Smirnov test} The Kolmogorov-Smirnov test of goodness-of-fit of a Poisson point process model compares the observed and predicted distributions of the values of a spatial covariate. We want to test the null hypothesis $H_0$ that the observed point pattern ${\mathbf x}$ is a realisation from the Poisson process with intensity function $\lambda(u)$ (for locations $u$ in the window $W$). Let $Z(u)$ be a given, real-valued covariate defined at each spatial location $u$. Under $H_0$, the \emph{observed} values of $Z$ at the data points, $Z(x_i)$ for each $x_i \in {\mathbf x}$, are independent random variables with common probability distribution function \[ F_0(z) = \frac{\int_W \lambda(u) \indicate{Z(u) \le z} \dee u} {\int_W \lambda(u) \dee u}. \] We can therefore apply the Kolmogorov-Smirnov test of goodness-of-fit. This compares the empirical cumulative distribution of the observed values $Z(x_i)$ to the predicted c.d.f. $F_0$. The test is implemented as \code{kstest.ppm}. The syntax is <>= kstest.mppm(model, covariate) @ where \code{model} is a fitted model (of class \texttt{"mppm"}) and \code{covariate} is either \begin{itemize} \item a \code{function(x,y)} making it possible to compute the value of the covariate at any location \code{(x,y)} \item a pixel image containing the covariate values \item a list of functions, one for each row of the hyperframe of original data \item a list of pixel images, one for each row of the hyperframe of original data \item a hyperframe with one column containing either functions or pixel images. \end{itemize} See Chapter 16 of \cite{baddrubaturn15} for further information. \newpage \addcontentsline{toc}{section}{Bibliography} %\bibliography{% %extra,% %extra2,% %biblio/badd,% %biblio/bioscience,% %biblio/censoring,% %biblio/mcmc,% %biblio/spatstat,% %biblio/stat,% %biblio/stochgeom% %} \begin{thebibliography}{1} \bibitem{baddmollpake08} A. Baddeley, J. M{\o}ller, and A.G. Pakes. \newblock Properties of residuals for spatial point processes. \newblock {\em Annals of the Institute of Statistical Mathematics}, 60:627--649, 2008. \bibitem{TheBook} A. Baddeley, E. Rubak, and R. Turner. \newblock {\em Spatial Point Patterns: Methodology and Applications with R}. \newblock Chapman \& Hall/CRC Press, 2015. \bibitem{statpaper} A. Baddeley, I. Sintorn, L. Bischof, R. Turner, and S. Heggarty. \newblock Analysing designed experiments where the response is a spatial point pattern. \newblock In preparation. \bibitem{baddetal05} A. Baddeley, R. Turner, J. M{\o}ller, and M. Hazelton. \newblock Residual analysis for spatial point processes (with discussion). \newblock {\em Journal of the Royal Statistical Society, series B}, 67(5):617--666, 2005. \bibitem{chenetal08} B.J. Chen, G.P. Leser, D. Jackson, and R.A. Lamb. \newblock The influenza virus {M2} protein cytoplasmic tail interacts with the {M1} protein and influences virus assembly at the site of virus budding. \newblock {\em Journal of Virology}, 82:10059--10070, 2008. %#%^!ifdef RANDOMEFFECTS \bibitem{davigilt95} M. Davidian and D.M. Giltinan. \newblock {\em Nonlinear Mixed Effects Models for Repeated Measurement Data}. \newblock Chapman and Hall, 1995. %#%^!endif \bibitem{digglangbene91} P.J. Diggle, N. Lange, and F. M. Benes. \newblock Analysis of variance for replicated spatial point patterns in clinical neuroanatomy. \newblock {\em Journal of the {A}merican {S}tatistical {A}ssociation}, 86:618--625, 1991. %#%^!ifdef RANDOMEFFECTS \bibitem{lairware82} N.M. Laird and J.H. Ware. \newblock Random-effects models for longitudinal data. \newblock {\em Biometrics}, 38:963--974, 1982. %#%^!endif \bibitem{pent84} A. Penttinen. \newblock {\em Modelling Interaction in Spatial Point Patterns: Parameter Estimation by the Maximum Likelihood Method}. \newblock Number 7 in {Jyv\"askyl\"a} Studies in Computer Science, Economics and Statistics. University of {Jyv\"askyl\"a}, 1984. %#%^!ifdef RANDOMEFFECTS \bibitem{pinhbate00} J.C. Pinheiro and D.M. Bates. \newblock {\em Mixed-Effects Models in {S} and {S-PLUS}}. \newblock Springer, 2000. %#%^!endif \end{thebibliography} %\addcontentsline{toc}{section}{Index} %\printindex \end{document} spatstat/vignettes/hexagon.eps0000644000176200001440000000577014141377564016314 0ustar liggesusers%!PS-Adobe-2.0 EPSF-2.0 %%Title: hexagon.fig %%Creator: fig2dev Version 3.2 Patchlevel 5a %%CreationDate: Tue Nov 23 11:04:35 2010 %%BoundingBox: 0 0 98 98 %Magnification: 1.0000 %%EndComments %%BeginProlog /$F2psDict 200 dict def $F2psDict begin $F2psDict /mtrx matrix put /col-1 {0 setgray} bind def /col0 {0.000 0.000 0.000 srgb} bind def /col1 {0.000 0.000 1.000 srgb} bind def /col2 {0.000 1.000 0.000 srgb} bind def /col3 {0.000 1.000 1.000 srgb} bind def /col4 {1.000 0.000 0.000 srgb} bind def /col5 {1.000 0.000 1.000 srgb} bind def /col6 {1.000 1.000 0.000 srgb} bind def /col7 {1.000 1.000 1.000 srgb} bind def /col8 {0.000 0.000 0.560 srgb} bind def /col9 {0.000 0.000 0.690 srgb} bind def /col10 {0.000 0.000 0.820 srgb} bind def /col11 {0.530 0.810 1.000 srgb} bind def /col12 {0.000 0.560 0.000 srgb} bind def /col13 {0.000 0.690 0.000 srgb} bind def /col14 {0.000 0.820 0.000 srgb} bind def /col15 {0.000 0.560 0.560 srgb} bind def /col16 {0.000 0.690 0.690 srgb} bind def /col17 {0.000 0.820 0.820 srgb} bind def /col18 {0.560 0.000 0.000 srgb} bind def /col19 {0.690 0.000 0.000 srgb} bind def /col20 {0.820 0.000 0.000 srgb} bind def /col21 {0.560 0.000 0.560 srgb} bind def /col22 {0.690 0.000 0.690 srgb} bind def /col23 {0.820 0.000 0.820 srgb} bind def /col24 {0.500 0.190 0.000 srgb} bind def /col25 {0.630 0.250 0.000 srgb} bind def /col26 {0.750 0.380 0.000 srgb} bind def /col27 {1.000 0.500 0.500 srgb} bind def /col28 {1.000 0.630 0.630 srgb} bind def /col29 {1.000 0.750 0.750 srgb} bind def /col30 {1.000 0.880 0.880 srgb} bind def /col31 {1.000 0.840 0.000 srgb} bind def end /cp {closepath} bind def /ef {eofill} bind def /gr {grestore} bind def /gs {gsave} bind def /sa {save} bind def /rs {restore} bind def /l {lineto} bind def /m {moveto} bind def /rm {rmoveto} bind def /n {newpath} bind def /s {stroke} bind def /sh {show} bind def /slc {setlinecap} bind def /slj {setlinejoin} bind def /slw {setlinewidth} bind def /srgb {setrgbcolor} bind def /rot {rotate} bind def /sc {scale} bind def /sd {setdash} bind def /ff {findfont} bind def /sf {setfont} bind def /scf {scalefont} bind def /sw {stringwidth} bind def /tr {translate} bind def /tnt {dup dup currentrgbcolor 4 -2 roll dup 1 exch sub 3 -1 roll mul add 4 -2 roll dup 1 exch sub 3 -1 roll mul add 4 -2 roll dup 1 exch sub 3 -1 roll mul add srgb} bind def /shd {dup dup currentrgbcolor 4 -2 roll mul 4 -2 roll mul 4 -2 roll mul srgb} bind def /$F2psBegin {$F2psDict begin /$F2psEnteredState save def} def /$F2psEnd {$F2psEnteredState restore end} def /pageheader { save newpath 0 98 moveto 0 0 lineto 98 0 lineto 98 98 lineto closepath clip newpath -11.0 102.4 translate 1 -1 scale $F2psBegin 10 setmiterlimit 0 slj 0 slc 0.06299 0.06299 sc } bind def /pagefooter { $F2psEnd restore } bind def %%EndProlog pageheader % % Fig objects follow % % % here starts figure with depth 50 % Polyline 0 slj 0 slc 30.000 slw n 1485 1395 m 1683 657 l 1143 117 l 405 315 l 207 1053 l 747 1593 l cp gs col0 s gr % here ends figure; pagefooter showpage %%Trailer %EOF spatstat/vignettes/irregpoly.eps0000644000176200001440000000646114141377564016675 0ustar liggesusers%!PS-Adobe-2.0 EPSF-2.0 %%Title: irregpoly.fig %%Creator: fig2dev Version 3.2 Patchlevel 5a %%CreationDate: Tue Nov 23 11:04:01 2010 %%BoundingBox: 0 0 226 144 %Magnification: 1.0000 %%EndComments %%BeginProlog /$F2psDict 200 dict def $F2psDict begin $F2psDict /mtrx matrix put /col-1 {0 setgray} bind def /col0 {0.000 0.000 0.000 srgb} bind def /col1 {0.000 0.000 1.000 srgb} bind def /col2 {0.000 1.000 0.000 srgb} bind def /col3 {0.000 1.000 1.000 srgb} bind def /col4 {1.000 0.000 0.000 srgb} bind def /col5 {1.000 0.000 1.000 srgb} bind def /col6 {1.000 1.000 0.000 srgb} bind def /col7 {1.000 1.000 1.000 srgb} bind def /col8 {0.000 0.000 0.560 srgb} bind def /col9 {0.000 0.000 0.690 srgb} bind def /col10 {0.000 0.000 0.820 srgb} bind def /col11 {0.530 0.810 1.000 srgb} bind def /col12 {0.000 0.560 0.000 srgb} bind def /col13 {0.000 0.690 0.000 srgb} bind def /col14 {0.000 0.820 0.000 srgb} bind def /col15 {0.000 0.560 0.560 srgb} bind def /col16 {0.000 0.690 0.690 srgb} bind def /col17 {0.000 0.820 0.820 srgb} bind def /col18 {0.560 0.000 0.000 srgb} bind def /col19 {0.690 0.000 0.000 srgb} bind def /col20 {0.820 0.000 0.000 srgb} bind def /col21 {0.560 0.000 0.560 srgb} bind def /col22 {0.690 0.000 0.690 srgb} bind def /col23 {0.820 0.000 0.820 srgb} bind def /col24 {0.500 0.190 0.000 srgb} bind def /col25 {0.630 0.250 0.000 srgb} bind def /col26 {0.750 0.380 0.000 srgb} bind def /col27 {1.000 0.500 0.500 srgb} bind def /col28 {1.000 0.630 0.630 srgb} bind def /col29 {1.000 0.750 0.750 srgb} bind def /col30 {1.000 0.880 0.880 srgb} bind def /col31 {1.000 0.840 0.000 srgb} bind def end /cp {closepath} bind def /ef {eofill} bind def /gr {grestore} bind def /gs {gsave} bind def /sa {save} bind def /rs {restore} bind def /l {lineto} bind def /m {moveto} bind def /rm {rmoveto} bind def /n {newpath} bind def /s {stroke} bind def /sh {show} bind def /slc {setlinecap} bind def /slj {setlinejoin} bind def /slw {setlinewidth} bind def /srgb {setrgbcolor} bind def /rot {rotate} bind def /sc {scale} bind def /sd {setdash} bind def /ff {findfont} bind def /sf {setfont} bind def /scf {scalefont} bind def /sw {stringwidth} bind def /tr {translate} bind def /tnt {dup dup currentrgbcolor 4 -2 roll dup 1 exch sub 3 -1 roll mul add 4 -2 roll dup 1 exch sub 3 -1 roll mul add 4 -2 roll dup 1 exch sub 3 -1 roll mul add srgb} bind def /shd {dup dup currentrgbcolor 4 -2 roll mul 4 -2 roll mul 4 -2 roll mul srgb} bind def /$F2psBegin {$F2psDict begin /$F2psEnteredState save def} def /$F2psEnd {$F2psEnteredState restore end} def /pageheader { save newpath 0 144 moveto 0 0 lineto 226 0 lineto 226 144 lineto closepath clip newpath -3.6 146.6 translate 1 -1 scale $F2psBegin 10 setmiterlimit 0 slj 0 slc 0.06299 0.06299 sc } bind def /pagefooter { $F2psEnd restore } bind def %%EndProlog pageheader % % Fig objects follow % % % here starts figure with depth 50 % Polyline 0 slj 0 slc 30.000 slw n 945 180 m 1170 1035 l 225 315 l 135 405 l 90 1215 l 675 1350 l 675 1665 l 135 1755 l 180 2205 l 990 2295 l 1260 1350 l 1530 1440 l 1440 2205 l 2250 2115 l 1890 1350 l 2520 1305 l 2250 1530 l 2475 2250 l 3330 2250 l 3330 1575 l 2790 1530 l 3600 1260 l 3465 720 l 2790 810 l 2475 765 l 3465 585 l 3510 360 l 2430 90 l 2115 225 l 2070 630 l 1800 945 l 1935 135 l 990 225 l gs col0 s gr % here ends figure; pagefooter showpage %%Trailer %EOF spatstat/vignettes/shapefiles.Rnw0000644000176200001440000005064714141377564016770 0ustar liggesusers\documentclass[twoside,11pt]{article} % \VignetteIndexEntry{Handling shapefiles in the spatstat package} \SweaveOpts{eps=TRUE} <>= options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) @ \usepackage{graphicx} \usepackage[colorlinks=true,urlcolor=blue]{hyperref} \usepackage{color} \usepackage{anysize} \marginsize{2cm}{2cm}{2cm}{2cm} \newcommand{\pkg}[1]{\texttt{#1}} \newcommand{\bold}[1]{{\textbf {#1}}} \newcommand{\R}{{\sf R}} \begin{document} %\bibliographystyle{plain} \thispagestyle{empty} <>= library(spatstat) options(useFancyQuotes=FALSE) sdate <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Date") sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") @ \title{Handling shapefiles in the \texttt{spatstat} package} \author{Adrian Baddeley, Rolf Turner and Ege Rubak} \date{ \Sexpr{sdate} \\ \pkg{spatstat} version \texttt{\Sexpr{sversion}} } \maketitle This vignette explains how to read data into the \pkg{spatstat} package from files in the popular `shapefile' format. This vignette is part of the documentation included in \pkg{spatstat} version \texttt{\Sexpr{sversion}}. The information applies to \pkg{spatstat} versions \texttt{1.36-0} and above. \section{Shapefiles} A shapefile represents a list of spatial objects --- a list of points, a list of lines, or a list of polygonal regions --- and each object in the list may have additional variables attached to it. A dataset stored in shapefile format is actually stored in a collection of text files, for example \begin{verbatim} mydata.shp mydata.prj mydata.sbn mydata.dbf \end{verbatim} which all have the same base name \texttt{mydata} but different file extensions. To refer to this collection you will always use the filename with the extension \texttt{shp}, for example \texttt{mydata.shp}. \section{Helper packages} \label{S:helpers} We'll use two other packages to handle shapefile data. The \pkg{maptools} package is designed specifically for handling file formats for spatial data. It contains facilities for reading and writing files in shapefile format.% \footnote{ Some code in \pkg{maptools} is no longer maintained, and may give you a message recommending that you use the packages \pkg{rgdal} and \pkg{sf}. However these packages are more difficult to install than \pkg{maptools} because of their software requirements. So we recommend that you try \pkg{maptools} first. } The \pkg{sp} package supports a standard set of spatial data types in \R. These standard data types can be handled by many other packages, so it is useful to convert your spatial data into one of the data types supported by \pkg{sp}. \section{Caveat about longitude-latitude coordinates} The shapefile format supports geographical coordinates, usually longitude-latitude coordinates, which specify locations on the curved surface of the Earth. However, \texttt{spatstat} deals only with spatial data on a flat two-dimensional plane. When shapefile data are converted into \texttt{spatstat} objects, longitude and latitude coordinates are (currently) treated as $x$ and $y$ coordinates, so that the Earth's surface is effectively mapped to a rectangle. This mapping distorts distances and areas. If your study region is a \emph{small} region of the Earth's surface (about 3 degrees, 180 nautical miles, 200 statute miles, 320 km across) then a reasonable approach is to use the latitude and longitude as $x$ and $y$ coordinates, after multiplying the longitude coordinates by the cosine of the latitude of the centre of the region. This will approximately preserve areas and distances. This calculation is a simple example of a \emph{geographical projection} and there are some much better projections available. It may be wise to use another package to perform the appropriate projection for you, and then to convert the projected data into \texttt{spatstat} objects. If your study region is a large part of the sphere, then your data may not be amenable to the techniques provided by \texttt{spatstat} because the geometry is fundamentally different. Please consider the extension package \texttt{spatstat.sphere}. \section{How to read shapefiles into \pkg{spatstat}} To read shapefile data into \pkg{spatstat}, you follow two steps: \begin{enumerate} \item using the facilities of \pkg{maptools}, read the shapefiles and store the data in one of the standard formats supported by \pkg{sp}. \item convert the \pkg{sp} data type into one of the data types supported by \pkg{spatstat}. \end{enumerate} \subsection{Read shapefiles using \pkg{maptools}} Here's how to read shapefile data. \begin{enumerate} \item ensure that the package \pkg{maptools} is installed. You will need version \texttt{0.7-16} or later. \item start R and load the package: <>= library(maptools) @ \item read the shapefile into an object in the \pkg{sp} package using \texttt{readShapeSpatial}, for example <>= x <- readShapeSpatial("mydata.shp") @ In recent versions of \pkg{maptools} you may get a warning, saying that this code is no longer supported, and recommending the packages \pkg{rgdal} and \pkg{sf}. As far as we know, this warning is premature, as the code still works fine! \item To find out what kind of spatial objects are represented by the dataset, inspect its class: <>= class(x) @ The class may be either \texttt{SpatialPoints} indicating a point pattern, \texttt{SpatialLines} indicating a list of polygonal lines, or \texttt{SpatialPolygons} indicating a list of polygons. It may also be \texttt{SpatialPointsDataFrame}, \texttt{SpatialLinesDataFrame} or \texttt{SpatialPolygonsDataFrame} indicating that, in addition to the spatial objects, there is a data frame of additional variables. The classes \texttt{SpatialPixelsDataFrame} and \texttt{SpatialGridDataFrame} represent pixel image data. \end{enumerate} Here are some examples, using the example shapefiles supplied in the \pkg{maptools} package itself. % fake data because we don't want spatstat to depend on maptools <>= baltim <- columbus <- fylk <- list() class(baltim) <- "SpatialPointsDataFrame" class(columbus) <- "SpatialPolygonsDataFrame" class(fylk) <- "SpatialLinesDataFrame" @ <>= setwd(system.file("shapes", package="maptools")) baltim <- readShapeSpatial("baltim.shp") columbus <- readShapeSpatial("columbus.shp") fylk <- readShapeSpatial("fylk-val.shp") @ <<>>= class(baltim) class(columbus) class(fylk) @ \subsection{Convert data to \pkg{spatstat} format} To convert the dataset to an object in the \pkg{spatstat} package, the procedure depends on the type of data, as explained below. Both packages \pkg{maptools} and \pkg{spatstat} must be \textbf{loaded} in order to convert the data. \subsubsection{Objects of class \texttt{SpatialPoints}} An object \texttt{x} of class \texttt{SpatialPoints} represents a spatial point pattern. Use \verb!as(x, "ppp")! or \texttt{as.ppp(x)} to convert it to a spatial point pattern in \pkg{spatstat}. (The conversion is performed by \texttt{as.ppp.SpatialPoints}, a function in \pkg{maptools}.) The window for the point pattern will be taken from the bounding box of the points. You will probably wish to change this window, usually by taking another dataset to provide the window information. Use \verb![.ppp! to change the window: if \texttt{X} is a point pattern object of class \verb!"ppp"! and \texttt{W} is a window object of class \verb!"owin"!, type <>= X <- X[W] @ \subsubsection{Objects of class \texttt{SpatialPointsDataFrame }} An object \texttt{x} of class \texttt{SpatialPointsDataFrame} represents a pattern of points with additional variables (`marks') attached to each point. It includes an object of class \texttt{SpatialPoints} giving the point locations, and a data frame containing the additional variables attached to the points. Use \verb!as(x, "ppp")! or \texttt{as.ppp(x)} to convert an object \texttt{x} of class \texttt{SpatialPointsDataFrame} to a spatial point pattern in \pkg{spatstat}. In this conversion, the data frame of additional variables in \texttt{x} will become the \texttt{marks} of the point pattern \texttt{z}. <>= y <- as(x, "ppp") @ (The conversion is performed by \texttt{as.ppp.SpatialPointsDataFrame}, a function in \pkg{maptools}. So the \pkg{maptools} and \pkg{spatstat} packages must be loaded in order for this to work.) Before the conversion you can extract the data frame of auxiliary data by \verb!df <- x@data! or \verb!df <- slot(x, "data")!. After the conversion you can extract these data by \verb!df <- marks(y)!. For example: <>= balt <- as(baltim, "ppp") bdata <- slot(baltim, "data") @ \subsubsection{Objects of class \texttt{SpatialLines}} \label{spatiallines.2.psp} A ``line segment'' is the straight line between two points in the plane. In the \pkg{spatstat} package, an object of class \texttt{psp} (``planar segment pattern'') represents a pattern of line segments, which may or may not be connected to each other (like matches which have fallen at random on the ground). In the \pkg{sp} package, an object of class \texttt{SpatialLines} represents a \textbf{list of lists} of \textbf{connected curves}, each curve consisting of a sequence of straight line segments that are joined together (like several pieces of a broken bicycle chain.) So these two data types do not correspond exactly. The list-of-lists hierarchy in a \texttt{SpatialLines} object is useful when representing internal divisions in a country. For example, if \texttt{USA} is an object of class \texttt{SpatialLines} representing the borders of the United States of America, then \verb!USA@lines! might be a list of length 52, with \verb!USA@lines[[i]]! representing the borders of the \texttt{i}-th State. The borders of each State consist of several different curved lines. Thus \verb!USA@lines[[i]]@Lines[[j]]! would represent the \texttt{j}th piece of the boundary of the \texttt{i}-th State. If \texttt{x} is an object of class \texttt{SpatialLines}, there are several things that you might want to do: \begin{enumerate} \item collect together all the line segments (all the segments that make up all the connected curves) and store them as a single object of class \texttt{psp}. \begin{quote} To do this, use \verb!as(x, "psp")! or \texttt{as.psp(x)} to convert it to a spatial line segment pattern. \end{quote} \item convert each connected curve to an object of class \texttt{psp}, keeping different connected curves separate. To do this, type something like the following: <>= out <- lapply(x@lines, function(z) { lapply(z@Lines, as.psp) }) @ (The conversion is performed by \texttt{as.psp.SpatialLines}, a function in \pkg{maptools}. So the \pkg{maptools} and \pkg{spatstat} packages must be loaded in order for this to work.) The result will be a \textbf{list of lists} of objects of class \texttt{psp}. Each one of these objects represents a connected curve, although the \pkg{spatstat} package does not know that. The list structure will reflect the list structure of the original \texttt{SpatialLines} object \texttt{x}. If that's not what you want, then use \verb!curvelist <- do.call("c", out)! or <>= curvegroup <- lapply(out, function(z) { do.call("superimpose", z)}) @ to collapse the list-of-lists-of-\texttt{psp}'s into a list-of-\texttt{psp}'s. In the first case, \texttt{curvelist[[i]]} is a \texttt{psp} object representing the \texttt{i}-th connected curve. In the second case, \texttt{curvegroup[[i]]} is a \texttt{psp} object containing all the line segments in the \texttt{i}-th group of connected curves (for example the \texttt{i}-th State in the \texttt{USA} example). \end{enumerate} The window for the spatial line segment pattern can be specified as an argument \texttt{window} to the function \texttt{as.psp}. (The conversion is performed by \texttt{as.psp.SpatialLines} or \texttt{as.psp.Lines}, which are functions in \pkg{maptools}.) \subsubsection{Objects of class \texttt{SpatialLinesDataFrame}} An object \texttt{x} of class \texttt{SpatialLinesDataFrame} is a \texttt{SpatialLines} object with additional data. The additional data is stored as a data frame \verb!x@data! with one row for each entry in \verb!x@lines!, that is, one row for each group of connected curves. In the \pkg{spatstat} package, an object of class \texttt{psp} (representing a collection of line segments) may have a data frame of marks. Note that each \emph{line segment} in a \texttt{psp} object may have different mark values. If \texttt{x} is an object of class \texttt{SpatialLinesDataFrame}, there are two things that you might want to do: \begin{enumerate} \item collect together all the line segments that make up all the connected lines, and store them as a single object of class \texttt{psp}. \begin{quote} To do this, use \verb!as(x, "psp")! or \texttt{as.psp(x)} to convert it to a marked spatial line segment pattern. \end{quote} \item keep each connected curve separate, and convert each connected curve to an object of class \texttt{psp}. To do this, type something like the following: <>= out <- lapply(x@lines, function(z) { lapply(z@Lines, as.psp) }) dat <- x@data for(i in seq(nrow(dat))) out[[i]] <- lapply(out[[i]], "marks<-", value=dat[i, , drop=FALSE]) @ The result is a list-of-lists-of-\texttt{psp}'s. See the previous subsection for explanation on how to change this using \texttt{c()} or \texttt{superimposePSP}. \end{enumerate} (The conversion is performed by \texttt{as.psp.SpatialLines}, a function in \pkg{maptools}. So the \pkg{maptools} and \pkg{spatstat} packages must be loaded in order for this to work.) In either case, the mark variables attached to a particular \emph{group of connected lines} in the \texttt{SpatialLinesDataFrame} object, will be duplicated and attached to each \emph{line segment} in the resulting \texttt{psp} object. \subsubsection{Objects of class \texttt{SpatialPolygons}} First, so that we don't go completely crazy, let's introduce some terminology. A \emph{polygon} is a closed curve that is composed of straight line segments. You can draw a polygon without lifting your pen from the paper. \setkeys{Gin}{width=0.4\textwidth} \begin{center} <>= data(chorley) plot(as.owin(chorley), lwd=3, main="polygon") @ \end{center} A \emph{polygonal region} is a region in space whose boundary is composed of straight line segments. A polygonal region may consist of several unconnected pieces, and each piece may have holes. The boundary of a polygonal region consists of one or more polygons. To draw the boundary of a polygonal region, you may need to lift and drop the pen several times. \setkeys{Gin}{width=0.4\textwidth} \begin{center} <>= data(demopat) plot(as.owin(demopat), col="blue", main="polygonal region") @ \end{center} An object of class \texttt{owin} in \pkg{spatstat} represents a polygonal region. It is a region of space that is delimited by boundaries made of lines. An object \texttt{x} of class \texttt{SpatialPolygons} represents a \textbf{list of polygonal regions}. For example, a single object of class \texttt{SpatialPolygons} could store information about every State in the United States of America (or the United States of Malaysia). Each State would be a separate polygonal region (and it might contain holes such as lakes). There are two things that you might want to do with an object of class \texttt{SpatialPolygons}: \begin{enumerate} \item combine all the polygonal regions together into a single polygonal region, and convert this to a single object of class \texttt{owin}. \begin{quote} For example, you could combine all the States of the USA together and obtain a single object that represents the territory of the USA. To do this, use \verb!as(x, "owin")! or \texttt{as.owin(x)}. The result is a single window (object of class \texttt{"owin"}) in the \pkg{spatstat} package. \end{quote} \item keep the different polygonal regions separate; convert each one of the polygonal regions to an object of class \texttt{owin}. \begin{quote} For example, you could keep the States of the USA separate, and convert each State to an object of class \texttt{owin}. \end{quote} To do this, type the following: <>= regions <- slot(x, "polygons") regions <- lapply(regions, function(x) { SpatialPolygons(list(x)) }) windows <- lapply(regions, as.owin) @ The result is a list of objects of class \texttt{owin}. Often it would make sense to convert this to a tessellation object, by typing <>= te <- tess(tiles=windows) @ \end{enumerate} (The conversion is performed by \texttt{as.owin.SpatialPolygons}, a function in \pkg{maptools}. So the \pkg{maptools} and \pkg{spatstat} packages must be loaded in order for this to work.) {\bf The following is different from what happened in previous versions of \pkg{spatstat}} (prior to version \texttt{1.36-0}.) During the conversion process, the geometry of the polygons will be automatically ``repaired'' if needed. Polygon data from shapefiles often contain geometrical inconsistencies such as self-intersecting boundaries and overlapping pieces. For example, these can arise from small errors in curve-tracing. Geometrical inconsistencies are tolerated in an object of class \texttt{SpatialPolygons} which is a list of lists of polygonal curves. However, they are not tolerated in an object of class \texttt{owin}, because an \texttt{owin} must specify a well-defined region of space. These data inconsistencies must be repaired to prevent technical problems. \pkg{Spatstat} uses polygon-clipping code to automatically convert polygonal lines into valid polygon boundaries. The repair process changes the number of vertices in each polygon, and the number of polygons (if you chose option 1). To disable the repair process, set \texttt{spatstat.options(fixpolygons=FALSE)}. \subsubsection{Objects of class \texttt{SpatialPolygonsDataFrame}} What a mouthful! An object \texttt{x} of class \texttt{SpatialPolygonsDataFrame} represents a list of polygonal regions, with additional variables attached to each region. It includes an object of class \texttt{SpatialPolygons} giving the spatial regions, and a data frame containing the additional variables attached to the regions. The regions are extracted by <>= y <- as(x, "SpatialPolygons") @ and you then proceed as above to convert the curves to \pkg{spatstat} format. The data frame of auxiliary data is extracted by \verb!df <- x@data! or \verb!df <- slot(x, "data")!. For example: <>= cp <- as(columbus, "SpatialPolygons") cregions <- slot(cp, "polygons") cregions <- lapply(cregions, function(x) { SpatialPolygons(list(x)) }) cwindows <- lapply(cregions, as.owin) @ There is currently no facility in \pkg{spatstat} for attaching marks to an \texttt{owin} object directly. However, \pkg{spatstat} supports objects called \textbf{hyperframes}, which are like data frames except that the entries can be any type of object. Thus we can represent the \texttt{columbus} data in \pkg{spatstat} as follows: <>= ch <- hyperframe(window=cwindows) ch <- cbind.hyperframe(ch, columbus@data) @ Then \texttt{ch} is a hyperframe containing a column of \texttt{owin} objects followed by the columns of auxiliary data. \subsubsection{Objects of class \texttt{SpatialGridDataFrame} and \texttt{SpatialPixelsDataFrame}} An object \texttt{x} of class \texttt{SpatialGridDataFrame} represents a pixel image on a rectangular grid. It includes a \texttt{SpatialGrid} object \texttt{slot(x, "grid")} defining the full rectangular grid of pixels, and a data frame \texttt{slot(x, "data")} containing the pixel values (which may include \texttt{NA} values). The command \texttt{as(x, "im")} converts \texttt{x} to a pixel image of class \texttt{"im"}, taking the pixel values from the \emph{first column} of the data frame. If the data frame has multiple columns, these have to be converted to separate pixel images in \pkg{spatstat}. For example <>= y <- as(x, "im") ylist <- lapply(slot(x, "data"), function(z, y) { y[,] <- z; y }, y=y) @ An object \texttt{x} of class \texttt{SpatialPixelsDataFrame} represents a \emph{subset} of a pixel image. To convert this to a \pkg{spatstat} object, it should first be converted to a \texttt{SpatialGridDataFrame} by \texttt{as(x, "SpatialGridDataFrame")}, then handled as described above. \end{document} spatstat/NEWS0000755000176200001440000134106714155341545012642 0ustar liggesusers CHANGES IN spatstat VERSION 2.3-0 OVERVIEW o Minor tweaks to package information and documentation o The NEWS file for package='spatstat' now contains only the news for the sub-package 'spatstat'. Other changes in the spatstat family of packages are reported in the NEWS file for the relevant sub-package. o 'latest.news' now collects news from all packages in the spatstat family o 'bugfixes' now collects bug fixes from all packages in the spatstat family o New function 'spatstat.family' NEW FUNCTIONS o spatstat.family Return the names of all packages in the spatstat family. SIGNIFICANT USER-VISIBLE CHANGES o latest.news Now gives the latest news for all packages in the spatstat family. o bugfixes Now lists bugs reported for all packages in the spatstat family. CHANGES IN spatstat VERSION 2.2-0 OVERVIEW o Minor tweaks to package information CHANGES IN spatstat VERSION 2.1-0 OVERVIEW o Minor changes to package structure. CHANGES IN spatstat VERSION 2.0-1 OVERVIEW o Minor changes to satisfy CRAN checks. CHANGES IN spatstat VERSION 2.0-0 OVERVIEW o We thank Corey Anderson, Michael Chirico, Andy Craig, Marcelino de la Cruz, Tilman Davies, Pavel Fibich, Kurt Hornik, Gopalan Nair, Yonatan Rosen and Rasmus Waagepetersen for contributions. o spatstat has been divided into 7 sub-packages (spatstat.utils, spatstat.data, spatstat.sparse, spatstat.geom, spatstat.core, spatstat.linnet and spatstat). o spatstat now depends on R version 3.5.0 or later. o Version nickname: "Caution: contains small parts" SIGNIFICANT USER-VISIBLE CHANGES o package structure The original 'spatstat' package has been divided into 7 sub-packages (spatstat.utils, spatstat.data, spatstat.sparse, spatstat.geom, spatstat.core, spatstat.linnet and spatstat). The remaining 'spatstat' package requires all the other sub-packages. Your existing code scripts should still work with minimal changes. o sessionInfo Output now lists packages that are imported but not loaded. o sessionLibs Package names are now sorted alphabetically. CHANGES IN spatstat VERSION 1.64-1 OVERVIEW o Important bug fix in vcov.ppm o Relative risk estimation may include case weights. o We thank Ian Buller, Brian Ripley, Maximilian Vogtland and Maximilian Hesselbarth for contributions. o Nickname: 'Help you I can, yes!' SIGNIFICANT USER-VISIBLE CHANGES o rshift.ppp, rshift.splitppp New argument 'nsim'. o relrisk.ppp New argument 'weights'. o density.splitppp New argument 'weights'. BUG FIXES o vcov.ppm Variances were sometimes overestimated for Gibbs models. That is, entries of the Fisher information matrix were underestimated, because some contributions due to interaction were omitted (due to a coding error). Fixed. o density.ppp Crashed when se=TRUE if there were multiple columns of 'weights'. Fixed. o rbind.hyperframe Crashed unless all arguments had the same number of rows. (Spotted by Maximilian Vogtland). Fixed. CHANGES IN spatstat VERSION 1.64-0 OVERVIEW o We thank Robert Aue, Tilman Davies, Greg McSwiggan, Tyler Rudolph and Rasmus Plenge Waagepetersen for contributions. o Interactive graphics functions have been removed to a separate package. o spatstat no longer needs the packages 'tcltk' and 'rpanel'. o The suggested package 'maptools' should be version 0.9-9 or later. o Important bug fix in density.ppp. o Add new vertices to a linear network. o Relative risk estimation on a network. o Leave-one-out density estimation on a network. o Improvements and extensions to linear networks code. o Improvements to 'nndist' methods. o Function lengths.psp has been renamed lengths_psp. o Bug fixes related to mppm. o Stability improvements. o Version nickname: 'Susana Distancia' NEW FUNCTIONS o relrisk.lpp Method for 'relrisk' for point patterns on a linear network. o bw.relrisklpp Bandwidth selection for relative risk on a network. o densityfun.lpp Method for 'densityfun' for point patterns on a linear network. o addVertices Add new vertices to a network, at locations outside the existing network. o lengths_psp This is the new name of the function 'lengths.psp', which had to be changed because of a conflict with the generic 'lengths'. o densityEqualSplit The equal-split algorithm for kernel density estimation on a network is now visible as a separate function. o densityHeat The heat-equation algorithm for kernel density estimation on a network is now visible as a separate function. It has also been extended to computing leave-one-out density estimates at the data points. o hotrod Compute the heat kernel kappa(u,v) on a one-dimensional line segment. o heatkernelapprox Calculate an approximation to the value of the heat kernel on a network evaluated at the source point, kappa(u,u). SIGNIFICANT USER-VISIBLE CHANGES o nndist.pp3, nndist.ppx, nndist.lpp These functions now recognise the argument 'by' allowing computation of the nearest distance to each group of points. o pairdist.lpp, crossdist.lpp These functions can now handle large networks, using the sparse representation. o density.lpp, densityQuick.lpp Infinite bandwidth (sigma=Inf) is now permitted, and results in a density estimate that is constant over all locations. o as.linnet.psp The resulting network now has an attribute 'camefrom' indicating the provenance of each line segment in the network. o as.linnet.linnet New argument 'maxsize'. o repairNetwork Increased capability of detecting and repairing inconsistencies. o joinVertices New argument 'marks'. o insertVertices Marks attached to the lines of the network are now retained. o as.lpp Accepts more data formats. o iplot, iplot.ppp, iplot.layered, iplot.linnet, iplot.default These interactive plotting functions have been removed from spatstat into a new package 'spatstat.gui' o istat This interactive analysis function has been removed from spatstat into a new package 'spatstat.gui' o crossdist.lpp New argument 'check'. o lengths.psp This function will soon be Deprecated, in favour of the new name 'lengths_psp' o density.lpp Formal arguments changed. No effect on usage. o integral.linim Now handles complex-valued functions. o transect.im New argument 'nsample'. o bw.lppl Accelerated when distance="path". o collapse.fv Recognises the abbreviations used by fvnames() BUG FIXES o density.ppp Edge correction factors were calculated incorrectly when the window was not a rectangle, causing a negative bias in the estimated intensity. [Spotted by Tilman Davies.] Bug introduced in spatstat 1.57-0, october 2018. Fixed. o mppm Internal data were malformed if the interaction was Hardcore() or MultiHard() or a hybrid involving these interactions. This caused various errors when the fitted model was used. Fixed. o mppm Ignored the arguments 'nd' and 'eps' controlling the quadrature scheme. Fixed. o "[.linnet", "[.lpp" In X[W] where W is a window, if a vertex of the network lay exactly on the boundary of W, an edge of length zero was created. Fixed. o valid.ppm Crashed sometimes when applied to the result of subfits(). Fixed. o as.im.densityfun Crashed if argument W was missing. Fixed. o as.linnet.linnet This code could crash the R session, when sparse=FALSE, if there was insufficient memory available to create the matrix of distances between all pairs of network vertices. Fixed. o Summary.linim A spurious warning was generated when the operation any() or all() was applied to a logical-valued image on a network. Fixed. o "[<-.linim" Crashed if the assignment would have replaced some existing NA values. Fixed. CHANGES IN spatstat VERSION 1.63-3 OVERVIEW o Minor changes for compatibility with future versions of R o Minor improvements o Version nickname: "Wet paint" SIGNIFICANT USER-VISIBLE CHANGES o plot.ppp The coordinate axes will be plotted if axes=TRUE. Axis labels xlab, ylab will be plotted if ann=TRUE. CHANGES IN spatstat VERSION 1.63-2 OVERVIEW o Minor changes to satisfy the package checker. o Version nickname: "I'm sorry Dave, I'm afraid I can't do that" CHANGES IN spatstat VERSION 1.63-1 OVERVIEW o Enhancement to plot.linim o Fill missing pixel values by taking the nearest defined pixel value. o Minor improvements and bug fixes. o spatstat now requires spatstat.utils version 1.17-0. o Version nickname: 'Made from recycled electrons' NEW FUNCTIONS o is.linim Tests whether an object belongs to class 'linim'. o nearestValue Given a pixel image on a subset of a rectangle, extend the image to the entire rectangle, using the nearest well-defined pixel value. SIGNIFICANT USER-VISIBLE CHANGES o markconnect Runs faster and handles much larger datasets. o markvario Runs faster and handles much larger datasets. o markcorr, markconnect, markvario The 'weights' can now be an expression to be evaluated, or a function, or a pixel image, as well as a numeric vector. o Smooth.ppp The 'weights' can now be an expression to be evaluated, or a function, or a pixel image, as well as a numeric vector. o rpoislpp If 'lambda' is a list of 'linim' or 'linfun' objects, then the argument L can be omitted. o plot.linim New argument 'fatten' improves visual appearance when style="colour". o plot.im, plot.owin The coordinate axes will be plotted if axes=TRUE. Axis labels xlab, ylab will be plotted if ann=TRUE. o bugfixes If sincedate="all" or sinceversion="all", then all bugs will be listed. o Jfox New argument 'warn.trim' makes it possible to suppress repeated warnings. o requireversion New argument 'fatal' BUG FIXES o predict.rhohat, simulate.rhohat When applied to a 'rhohat' object computed from linear network data (lpp or lppm), there was a warning about the lengths of vectors, and the results were incorrect. Fixed. o predict.rhohat, simulate.rhohat Crashed when applied to a 'rhohat' object computed from *multitype* linear network data (multitype lpp or lppm). Fixed. o Jfox envelope() commands using the summary function 'Jfox' crashed sometimes with a message about illegal spacing of 'r' values. Fixed. o leverage, influence, dfbetas Crashed when applied to an 'ippm' object in which the irregular components of the score, but not the Hessian, were provided by symbolic differentiation. Fixed. o parres Crashed in rare circumstances, when the data did not contain enough useable values to perform smoothing. Fixed. CHANGES IN spatstat VERSION 1.63-0 OVERVIEW o Compute minimum or maximum nearest-neighbour distance between each pair of types in a multitype point pattern. o Important bug fix in simulations of the multitype hard core process. o Numerous improvements and bug fixes. o Deprecated functions have been removed. o Version nickname: "Trees in space" SIGNIFICANT USER-VISIBLE CHANGES o minnndist, maxnndist New argument 'by' makes it possible to find the minimum or maximum nearest neighbour distance between each pair of possible types in a multitype pattern. o beachcolours If 'sealevel' lies outside 'srange', then 'srange' will be extended to include it (without a warning). o split<-.ppp The default for argument 'un' in 'split<-.ppp' now agrees with the default for the same argument in 'split.ppp'. o lineardisc New argument 'add'. Default plotting behaviour has changed. o rmh, rmh.default The printed output of the debugger (invoked by snoop=TRUE) has been improved. o plot.owin New argument 'use.polypath' controls how to plot a filled polygon when it has holes. o plot.profilepl This function has now been documented, and the graphics improved. o erode.owin, dilate.owin These deprecated functions have now been deleted (replaced by erosion.owin and dilation.owin) o delaunay.distance, delaunay.network These deprecated functions have now been deleted (replaced by delaunayDistance, delaunayNetwork) o dirichlet.edges, dirichlet.network, dirichlet.vertices, dirichlet.weights These deprecated functions have now been deleted (replaced by dirichletEdges, dirichletNetwork, dirichletVertices, dirichletWeights) BUG FIXES o rmh, simulate.ppm, MultiHard Simulated realisations of the multitype hard core model were completely incorrect (the interaction was effectively removed, changing the model into a Poisson process). Fixed. o kppm, AIC For kppm models fitted with method='clik2', the resulting value of logLik() was equal to 1/2 of the correct value. This would have affected model comparison using AIC, and model selection using step(). Fixed. o hyperframe Did not correctly handle date-time values (columns of class 'Date', etc). Fixed o rlpp The resulting pattern was unmarked even when it should have been multitype. Fixed. o idw Estimates were zero if 'se=TRUE' and 'power != 2' and 'at="pixels"'. Fixed. o model.matrix.mppm Sometimes returned a matrix with the wrong number of rows. Fixed. o nncross.ppp Format of output was incorrect if X was an empty pattern. Fixed. o rmh, rmh.default For a marked point process, the debugger did not display the marks. (The rmh debugger is invoked by calling rmh with snoop=TRUE). Fixed. o pairs.im, pairs.linim The argument 'labels' was sometimes ignored. Fixed. o as.im.data.frame Results were incorrect for factor-valued data. Fixed. o relrisk.ppp Crashed if there were more than 2 types of points and method = "leastsquares" or "weightedleastsquares". Fixed. o as.im.nnfun Crashed when applied to a function generated by nnfun.psp. Fixed. o diagnose.ppm Crashed for some models with an error message from 'beachcolours'. Fixed. o predict.rho2hat Crashed if one of the original covariates was a function rather than an image. Fixed. o lineardisc Crashed in some graphics environments. Fixed. o lineardisc Crashed if the network segments had marks. Fixed. o rmh Crashed for multitype models if 'nsave' was specified. Fixed. o vcov.mppm, simulate.mppm Crashed for multitype models with a hardcore interaction component. Fixed. o effectfun Crashed if 'covname' was not the name of a covariate appearing in the model and was not one of the reserved names 'x', 'y', 'marks'. Fixed. CHANGES IN spatstat VERSION 1.62-2 OVERVIEW o Urgent bug fixes and workarounds. o Version nickname: "Shape-shifting lizard" SIGNIFICANT USER-VISIBLE CHANGES o colourmap Argument 'col' is now permitted to have length 1, representing a colour map in which all values are mapped to the same colour. o lut Argument 'outputs' is now permitted to have length 1, representing a lookup table in which all inputs are mapped to the same output value. BUG FIXES o envelope Crashed sometimes, with a message about unrecognised arguments, when applied to a summary function created by the user. Fixed. CHANGES IN spatstat VERSION 1.62-1 OVERVIEW o We thank Mohammad Ghorbani, Ute Hahn, Abdollah Jalilian, Nestor Luambua, Greg McSwiggan, Annie Mollie and Jakob Gulddahl Rasmussen for contributions. o spatstat now requires spatstat.utils version 1.15-0 and goftest version 1.2-2. o Nearest Neighbour Index function can now return mark values. o Important fix in Ripley isotropic correction. o Index of repulsion strength for determinantal point process models. o Nearest neighbours between two point patterns in any number of dimensions. o More options for handling bad simulation outcomes in envelope(). o Bandwidth selectors warn about extreme values of bandwidth. o Tessellations on a linear network can now have marks. o New functions for simulating point processes on a linear network. o More functions for manipulating tessellations on a linear network. o mppm accepts case weights. o Bug fixes and minor improvements. o Nickname: 'An update which will live in infamy' NEW FUNCTIONS o repul Repulsiveness index for a determinantal point process model. o reach.kppm Reach (interaction distance) for a Cox or cluster point process model. o summary.dppm, print.summary.dppm Summary method for determinantal point process models. o nncross.ppx Nearest neighbours between two point patterns in any number of dimensions. o uniquemap.matrix Method for uniquemap for matrices. o repairNetwork Detect and repair inconsistencies in internal data in a linnet or lpp object. o marks<-.lintess, unmark.lintess Assign marks to the tiles of a tessellation on a linear network. o marks.lintess Extract the marks of the tiles of a tessellation on a linear network. o tilenames.lintess Extract the names of the tiles in a tessellation on a linear network o tilenames<-.lintess Change the names of the tiles in a tessellation on a linear network o nobjects.lintess Count the number of tiles in a tessellation on a linear network o as.data.frame.lintess Convert a tessellation on a linear network into a data frame. o rcelllpp Simulate the cell point process on a linear network o rSwitzerlpp Simulate the Switzer-type point process on a linear network o intersect.lintess Form the intersection of two tessellations on a linear network o chop.linnet Divide a linear network into tiles using infinite lines SIGNIFICANT USER-VISIBLE CHANGES o lintess New argument 'marks' Tessellations can now have marks. o tilenames, tilenames<- These functions are now generic, with methods for 'tess' and 'lintess' o mppm New argument 'weights' specifies case weights for each row of data. o unstack.lintess Now handles marks. o plot.lintess Modified to display the marks attached to the tiles. Changed options: style=c("colour", "width", "image"). o as.linfun.lintess The default function values are the marks. o print.lintess, summary.lintess, print.summary.lintess Output now includes information about marks. o nnfun.ppp, nnfun.psp, nnfun.lpp New argument 'value' specifies whether to return the index of the nearest neighbour or the mark value of the nearest neighbour. o envelope.ppp, envelope.ppm, envelope.kppm, envelope.pp3 New arguments 'rejectNA' and 'silent'. o envelope.lpp, envelope.lppm New arguments 'maxnerr', 'rejectNA' and 'silent'. o plot.psp New argument 'col' gives control over the colour map representing the values of marks attached to the segments. o plot.im Some warnings are suppressed when do.plot=FALSE. o plot.linim New explicit argument 'box' determines whether to plot a bounding box. Default is now FALSE in all cases. o Kest, Kinhom, pcf, pcfinhom, edge.Ripley Calculation of isotropic edge correction for polygonal windows has changed slightly. Results are believed to be more accurate. Computation has been accelerated by about 20 percent in typical cases. o bw.diggle, bw.ppl, bw.lppl, bw.pcf, bw.CvL, bw.voronoi A warning is issued if the optimal value of the cross-validation criterion occurs at an endpoint of the search interval. New argument 'warn'. o mad.test, dclf.test, dg.test, bits.test Function values which are infinite, NA or NaN are now ignored in the calculation (with a warning) instead of causing an error. Warning messages are more detailed. o rmhcontrol, rmh The parameter 'nsave' can now be a vector of integers. o diagnose.ppm Accelerated, when type="inverse", for models without a hard core. o uniquemap.data.frame Accelerated for some cases. o vcov.ppm, vcov.mppm New argument 'nacoef.action' specifies what to do if some of the fitted coefficients are NA, NaN or Inf. o Lest, Linhom, Ldot, Lcross, Ldot.inhom, Lcross.inhom These summary functions now have an explicit argument 'correction'. Behaviour is unchanged. o bugfixes Arguments sinceversion="book" or sincedate="book" are interpreted to give all bugs reported after publication of the spatstat book. o cbind.hyperframe, rbind.hyperframe The result now retains the row.names of the original arguments. o print.summary.owin More information is printed. o append.psp Arguments may be NULL. o as.psp Now permits a data frame of marks to have only one column, instead of coercing it to a vector. BUG FIXES o as.linnet.psp Sometimes produced a network with duplicated segments. [Such objects can be repaired using 'repairNetwork'.] Fixed. o edge.Ripley, Kest, Kinhom Isotropic correction weights for polygonal windows were sometimes incorrect for small radius 'r' if the polygon contained many small segments [spotted by Annie Mollie] or if the polygon was very long and thin [spotted by Nestor Luambua]. Problem arose in spatstat 1.60-0. Fixed. o lppm Did not correctly handle the case where the left-hand side of the formula is the name of an entry in the 'data' argument. Fixed. o plot.lpp Did not correctly handle the argument 'which.marks'. Fixed. o plot.im Did not correctly handle the argument 'ribargs$at'. Fixed. o density.lpp Sometimes requested a larger value of 'iterMax' but ignored it. Fixed. o [.linnet, [.lpp Crashed if x contained inconsistent internal data (when index 'j' was a window, and snip=TRUE). Fixed. o plot.linim Crashed if the pixel values were complex numbers. Fixed. o plot.linfun Crashed if the function values were complex numbers. Fixed. o integral.linim, mean.linim Crashed if the image had logical values. Fixed. o Re, Im, Arg, Mod, Conj For pixel images on a linear network (class 'linim') these operations crashed if the pixel values were complex numbers. o studpermu.test Crashed if the hyperframe was very large. Fixed. o studpermu.test Crashed in some cases when the simulated functions were incompatible with each other, due to the use of different edge corrections. Fixed. o vcov.ppm, print.ppm, summary.ppm Crashed in some cases if the fitted coefficients were NA. Fixed. o quantess.owin, quantess.ppp, quantess.im Crashed in some cases because the tile labels were not unique. Fixed. o plot.pp3 Did not correctly handle graphical arguments ('col', 'pch', 'cex') if they were vectors [Spotted by Abdollah Jalilian]. Fixed. o shift.linnet Generated a spurious warning. Fixed. o density.lpp, lixellate Crashed in some cases when a data point was exactly at a vertex. [Spotted by Jakob Gulddahl Rasmussen.] Fixed. o plot.linim Crashed (when style="width") if any pixel values were NaN. Fixed. o Fest, Jest, Jdot, Jcross, Hest, Iest, rectcontact envelope() commands using one of these summary functions crashed sometimes with a message about illegal spacing of 'r' values. Fixed. o plot.linnet, plot.psp Ignored argument 'col' when style="width". Fixed. o rshift.psp Crashed if X had a data frame of marks. [Spotted by Ute Hahn.] Fixed. o Kscaled Crashed if Ripley's isotropic edge correction was selected but the translation edge correction was not. Fixed. CHANGES IN spatstat VERSION 1.61-0 OVERVIEW o We thank Jordan Brown, Tilman Davies and Greg McSwiggan for contributions. o Fast kernel estimation on a linear network using 2D kernels. o Nonparametric maximum likelihood estimation of 'rho'. o Extension of Scott's rule for bandwidth selection. o Cross-validated bandwidth selection on a linear network. o More support for character-valued images. o Random thinning of clumps. o Bug fixes and minor improvements. o Nickname: 'Puppy zoomies' NEW FUNCTIONS o densityQuick.lpp Fast kernel estimator of point process intensity on a network using 2D smoothing kernel. o bw.scott.iso Isotropic version of Scott's rule (for point patterns in any dimension). o data.lppm Extract the original data point pattern from a fitted model of class 'lppm'. o rthinclumps Divide a spatial region into clumps and randomly delete some of them. o dimnames.hyperframe, dimnames<-.hyperframe Methods for extracting and changing the 'dimnames' of a hyperframe. SIGNIFICANT USER-VISIBLE CHANGES o rhohat Estimation by nonparametric maximum likelihood is now supported, assuming the intensity is a monotone function of the covariate. New options: smoother="increasing" and smoother="decreasing". o density.lpp New argument 'distance' offers a choice of different kernel methods. o bw.scott Now handles point patterns of any dimension. New arguments 'isotropic' and 'd'. o bw.ppl New argument 'shortcut' allows faster computation. Additional arguments '...' are now passed to density.ppp. o [<-.im New argument 'drop' controls behaviour when indices are missing as in 'x[] <- value' o mppm Now supports 'self-starting' interactions. o as.im New argument 'stringsAsFactors' is recognised by many methods. It enables the creation of character-string-valued images. o plot.im Axes are now prevented from extending outside the image rectangle. o plot.im New argument 'zap'. o blur New argument 'kernel'. o Smooth.im New argument 'kernel'. o quadrat.test New argument 'df.est'. o edge.Ripley Numerical stability has been improved on some platforms. Results may have changed in marginal cases (e.g. where the circle of radius r centred at X is tangent to an edge of the polygonal window). o rownames, rownames<-, colnames, colnames<- These operations now work for hyperframes. o quadrat.test Improved labelling of test when argument 'CR' is given. o plot.pppmatching This existing function now has a help file. New argument 'adjust'. o solist, is.sob, lintess Objects of class 'lintess' are now recognised as 2D spatial objects for the purposes of solist() and is.sob(). o as.linfun.lintess Functions created by as.linfun.lintess() now generate better output when the function is printed. BUG FIXES o densityVoronoi.lpp Did not correctly handle patterns containing duplicated points. Fixed. o quadrat.test Argument 'CR' was ignored when method="MonteCarlo". Fixed. o localKcross.inhom, localLcross.inhom Argument lambdaX was ignored. Fixed. o "[.linim" Factor values were erroneously converted to integers, in some cases. Fixed. o "[<-.hyperframe" Did not handle some classes of objects correctly. Fixed. o effectfun In a multitype point process model, effectfun() ignored any user-specified value of 'marks'. Fixed. o as.linim.linfun Additional arguments (other than spatial coordinates) were ignored. Fixed. o plot.solist Display output was mangled if one entry in the list was an object that would normally generate multiple panels of graphics, such as an 'lpp' or 'tess' object with multiple columns of marks, or a marked 'msr', 'leverage.ppm' or 'influence.ppm' object. Fixed. o plot.lpp Return value was mangled when x had multiple columns of marks. Fixed. o colourtable Crashed in some cases when 'breaks' was given. Fixed. o rLGCP Crashed if 'win' was not a rectangle and 'mu' was not a constant. Fixed. o intersect.tess Crashed if 'Y' was a window object and 'keepmarks=TRUE'. Fixed. o envelope.lppm Crashed if argument 'simulate' was given. Fixed. o unstack.solist Did not correctly handle objects of class 'lintess'. o unstack.solist Did not correctly handle objects of class 'tess' if they had multiple columns of marks. o plot.pppmatching Issued spurious warnings about unrecognised plot arguments. Fixed. o plot.lintess Issued spurious warnings about unrecognised plot arguments. Fixed. o shift.lpp, rotate.lpp Issued spurious warnings if argument 'origin' was given. Fixed. CHANGES IN spatstat VERSION 1.60-1 OVERVIEW o Version number incremented for administrative reasons. CHANGES IN spatstat VERSION 1.60-0 OVERVIEW o We thank Ottmar Cronie, Tilman Davies, Andrew Hardegen, Tom Lawrence, Robin Milne, Mehdi Moradi, Gopalan Nair, Tim Pollington and Suman Rakshit for contributions. o Random thinning and random labelling of spatial patterns extended to different types of pattern. o Confidence intervals for multitype K functions. o Envelopes for balanced two-stage test o Accelerated some code. o Minor bug fixes and improvements. o Package built under R 3.6.0. o Version nickname: 'Swinging Sixties' NEW FUNCTIONS o bits.envelope Global simulation envelope corresponding to bits.test, the balanced independent two-stage Monte Carlo test. o extrapolate.psp Extrapolate line segments to obtain infinite lines. o uniquemap Map duplicate points to unique representatives. Generic with methods for ppp, lpp, ppx o uniquemap.data.frame Map duplicate rows to unique representatives o localKcross, localLcross, localKdot, localLdot, localKcross.inhom, localLcross.inhom Multitype local K functions. SIGNIFICANT USER-VISIBLE CHANGES o lohboot Now works for multitype K functions Kcross, Kdot, Lcross, Ldot, Kcross.inhom, Lcross.inhom. o Kinhom, pcfinhom Leave-one-out calculation is implemented when 'lambda' is a fitted model of class 'dppm'. o Kcross.inhom, Kdot.inhom, Lcross.inhom, Ldot.inhom Leave-one-out calculation is implemented when 'lambdaX' is a fitted model of class 'dppm'. o rthin, rlabel These functions now work on point patterns of all classes (ppp, lpp, pp3, ppx) and line segment patterns (psp). o bw.abram New argument 'smoother' determines how the pilot estimate is computed. Formal arguments rearranged. o plot.im New argument 'riblab'. o rlabel New arguments 'nsim' and 'drop'. o localK, localKinhom New argument 'rmax'. o rLGCP Accelerated. o anyDuplicated.ppp Accelerated. o duplicated.ppp Accelerated, in most cases. o simulate.kppm Accelerated, for LGCP models. o predict.ppm Accelerated, for models fitted with method="VBlogi" o print.rmhmodel Output improved. BUG FIXES o plot.linim, plot.linfun Not all the entries of 'leg.args' were passed to text.default. Fixed. o densityVoronoi.ppp Did not correctly handle patterns containing duplicated points. Fixed. o markcorr The argument 'correction="none"' did not generate any results. [Spotted by Tim Pollington.] Fixed. o names<-.fv Did not adjust the plotting formula, so that a subsequent call to plot.fv would complain about missing variables. Fixed. o im.apply Crashed if 'FUN' returned factor values. Fixed. o stienenSet Crashed if the data contained duplicated points. Fixed. o predict.ppm, effectfun Crashed in some cases, with the message 'ncol(x)=nrow(v) is not TRUE'. Fixed. o parres Crashed in some cases, with the message 'logical subscript too long'. Fixed. o dclf.test, mad.test, dg.test, bits.test Crashed in some cases if the summary function values were infinite or NA. Fixed. CHANGES IN spatstat VERSION 1.59-0 OVERVIEW o We thank Lucia Cobo Sanchez, Tilman Davies, Maximilian Hesselbarth, Kassel Hingee, Mehdi Moradi, Suman Rakshit, Jan Sulavik and Luke Yates for contributions. o Extensions to adaptive intensity estimators. o 'Dartboard' tessellation using polar coordinates. o Performance improvements. o Minor improvements and bug fixes. o Version nickname: "J'ai omis les oeufs de caille" NEW FUNCTIONS o polartess Tessellation using polar coordinates. o bw.abram Variable bandwidths for adaptive smoothing, using Abramson's Rule. o densityAdaptiveKernel Calculates adaptive estimate of point process intensity using variable-bandwidth kernel estimation. o densityVoronoi, densityVoronoi.ppp Calculates adaptive estimate of point process intensity using tessellation methods. This is an extension of the old function adaptive.density. o densityVoronoi.lpp Voronoi or smoothed Voronoi estimator of intensity for point pattern on a linear network. o coords.quad New method for 'coords', to extract the coordinates of the points in a quadrature scheme. o lineartileindex Low-level function to classify points on a linear network according to which tile of a tessellation they fall inside. SIGNIFICANT USER-VISIBLE CHANGES o latest.news Now prints news documentation for the current major version, by default. New argument 'major'. o quantess The covariate Z can now be "rad" or "ang" representing polar coordinates. New argument 'origin' specifies the origin of polar coordinates. New argument 'eps' controls accuracy of calculation. o envelope The argument 'simulate' can now be a function (such as 'rlabel'). The function will be applied repeatedly to the original data Y, and should yield point patterns of the same kind. o adaptive.density This function can now perform adaptive estimation by two methods: either tessellation-based methods or variable-bandwidth kernel estimation. The calculations are performed by either 'densityVoronoi' or 'densityAdaptiveKernel'. o densityVoronoi This performs the calculations of the old function 'adaptive.density'. New argument 'fixed' specifies the subsampling. New argument 'method' allows a choice between the original algorithm and the recently described 'smoothed Voronoi' estimator. Default value of 'f' changed to 'f=1'. o pcf.ppp Now accepts correction="none". o pairorient Default edge corrections now include 'bord.modif'. o funxy Functions of class 'funxy' can now be applied to quadrature schemes. o lohboot Computation accelerated when the window is a rectangle. o nncorr, nnmean, nnvario New argument 'na.action'. o pp3 New argument 'marks'. o clusterfit New argument 'verbose'. o beachcolours, beachcolourmap Improved positioning of the yellow colour band. o linearK, linearpcf, linearKdot, linearKcross, linearpcfcross, linearpcfdot Computation accelerated for networks which are not connected. o as.linnet.psp Computation accelerated. o as.linfun.lintess Computation accelerated. o selfcut.psp Computation accelerated. The result now has an attribute "camefrom" indicating the provenance of each segment in the result. o bw.stoyan The rule has been modified so that, if the pattern is empty, it is now treated as if it contained 1 point, so that a finite bandwidth value is returned. o rebound.owin Now preserves unitnames of the objects. o rescale.owin, rescale.ppp, rescale.psp The geometrical type of the window is now preserved in all cases (previously if the window was polygonal but was equivalent to a rectangle, the rescaled window was a rectangle). o shift.im, shift.owin, shift.ppp, shift.psp More options for the argument 'origin'. o nnwhich.ppp, nnwhich.default Accelerated, in the case k > 1. o is.subset.owin Improved robustness against numerical error. o plot.im Improved behaviour when the pixel values are almost constant. o Finhom, Ginhom, Jinhom A warning is issued if bias is likely to occur because of undersmoothing. New arguments 'warn.bias' and 'savelambda'. o plot.colourmap Now handles a colourmap defined on an interval of length zero. o ewcdf Computation accelerated. New arguments 'normalise' and 'adjust'. The result does not inherit class 'ecdf' if normalise=FALSE. o spatialcdf Computation accelerated. The result does not inherit class 'ecdf' if normalise=FALSE. o effectfun New argument 'nvalues'. o parres The argument 'covariate' may be omitted if the model involves only one covariate. o alltypes If 'envelope=TRUE' and the envelope computation reaches the maximum permitted number of errors (maxnerr) in evaluating the summary function for the simulated patterns, then instead of triggering a fatal error, the envelope limits will be set to NA. o simulate.kppm Additional arguments '...' are now passed to the function that performs the simulation. BUG FIXES o spatialcdf The argument 'weights' was ignored in some cases. Fixed. o ppp Points inside the window were erroneously rejected as lying outside the window, if the window was a polygon equivalent to a rectangle with sides longer than 10^6 units. Fixed. o inside.owin All results were FALSE if the window was a polygon equivalent to a rectangle with sides longer than 10^6 units. Fixed. o sumouter Result was incorrect (all entries were zero) if 'w' was missing and 'y' was given. Fixed. o extractbranch.lpp Point pattern coordinates were sometimes erroneously set to NA. Fixed. o beachcolours, beachcolourmap The number of colours was not always equal to 'ncolours'. [Spotted by Tilman Davies.] Fixed. o is.subset.owin Sometimes gave the wrong answer for polygonal windows due to numerical rounding error. Fixed. o update.kppm Crashed if the updating information was a point pattern and the original model call did not include a formula. Spotted by Luke Yates. Fixed. o incircle, inpoint Crashed if the window was extremely thin. Fixed. o effectfun Crashed in some obscure cases. Fixed. o closepairs.pp3 Crashed if distinct=FALSE and what="all". Fixed. o update.ippm Crashed if the model was fitted using method="logi". Fixed. o plot.msr Crashed sometimes if x was multitype and multiplot=FALSE. Fixed. o anova.mppm Crashed if applied to a single model, unless the current environment was the global environment. Fixed. o lurking.mppm If 'covariate' was a list of images, the code crashed sometimes with message 'Fisher information is singular'. Fixed. o im Crashed if 'mat' was a 1-dimensional table (class 'table'). Fixed. o dirichlet Crashed if the pattern was empty or contained only 1 point. Fixed. o rjitter Crashed if the pattern contained 0 or 1 points and the argument 'radius' was not specified. Fixed. o quantess.owin Crashed if Z was a function(x,y). Fixed. o quadrat.test The p-value was NA if one of the observed counts was zero, for the Cressie-Read tests with CR not equal to 1 or -1. Fixed. o quadratcount.ppp Sometimes issued an incorrect warning that data points were outside the tessellation, when 'tess' was a tessellation represented by a pixel image. Fixed. o as.linim.linfun Factor-valued functions were converted to integer-valued images. Spotted by Suman Rakshit. Fixed. o plot.linfun Did not display factor-valued functions correctly. Spotted by Suman Rakshit. Fixed. o dclf.test, mad.test Crashed, in rare cases, when applied to an 'envelope' object. Spotted by Jan Sulavik. Fixed. o plot.spatialcdf, plot.ewcdf A horizontal line was plotted at height 1, even if the CDF was unnormalised. Fixed. o plot.tess The names of the tiles were sometimes re-ordered in the legend. Fixed. o rThomas, rMatClust, rCauchy, rVarGamma If the simulation window was not a rectangle, the attribute 'Lambda' was a numeric vector, rather than a pixel image. Fixed. CHANGES IN spatstat VERSION 1.58-2 OVERVIEW o Venn diagram tessellation o Internal bug fixes. NEW FUNCTIONS o venn.tess Venn diagram tessellation. CHANGES IN spatstat VERSION 1.58-1 OVERVIEW o Bug fixes. o Version nickname: "Compliment Sandwich" BUG FIXES o lpp Did not correctly detect some situations where the input data are invalid. Fixed. o lurking.ppp, lurking.ppm Did not correctly detect some situations where the input data are invalid. Fixed. CHANGES IN spatstat VERSION 1.58-0 OVERVIEW o We thank Andrew Bevan, Hamidreza Heydarian and Andrew P Webster for contributions. o Mark-mark scatter plot. o Standard error calculation for inverse-distance weighting o Minor improvements and extensions. o Version nickname: 'Drop Bear' NEW FUNCTIONS o markmarkscatter Mark-mark scatterplot SIGNIFICANT USER-VISIBLE CHANGES o idw Standard errors can now be calculated by setting 'se=TRUE'. o im.apply Computation accelerated, especially when NA's are absent. New arguments 'fun.handles.na' and 'check'. o kppm, dppm, clusterfit Changed precedence rule for handling the algorithm parameters in the minimum contrast algorithm. Individually-named arguments 'q,p,rmax,rmin' now take precedence over entries with the same names in the list 'ctrl'. o rotmean Improved algorithm stability o summary.kppm Prints more information about algorithm convergence. o closepairs.pp3, crosspairs.pp3 Argument 'what' can take the value "ijd" o plot.onearrow Graphical parameters, specified when the object was created, are now taken as the defaults for graphical parameters to the plot. BUG FIXES o rotmean When result="im" the resulting image did not have the same dimensions as the input. [Spotted by Hamidreza Heydarian.] Fixed. o rotmean If argument 'origin' was given, and if result="im" was specified, the resulting image was wrongly displaced. Fixed. o runifpointx Result was mangled when n=0 or n=1. Fixed. CHANGES IN spatstat VERSION 1.57-1 OVERVIEW o Bug fixes. o Version nickname: 'Cartoon Physics' BUG FIXES o multiplicity.default Some entries of the result were incorrectly set to 1. Fixed. o anova.ppm Crashed if adjust=TRUE and the models were fitted with use.gam=TRUE. Fixed. CHANGES IN spatstat VERSION 1.57-0 OVERVIEW o We thank Corey Anderson, Ryan Arellano, Hadrien Commenges, Ottmar Cronie, Tilman Davies, Maximilian Hesselbarth, Kassel Hingee, Tomas Lazauskas, Marie-Colette van Lieshout, Rasmus Waagepetersen and 'daitakahashi' for contributions. o Cronie-van Lieshout bandwidth selection. o Smoothing functions handle non-Gaussian kernels. o Infinite smoothing bandwidths permitted. o Positive confidence limits for rhohat. o Improved bivariate interpolation. o subset() method for line segment patterns. o Important bug fixes in rthin and density.ppp o Minor bug fixes and improvements. o Version nickname: 'Zombie apocalypse' NEW FUNCTIONS o bw.CvL Cronie-Van Lieshout bandwidth selection for density estimation. [Contributed by Ottmar Cronie and Marie-Colette van Lieshout.] o subset.psp Method for 'subset' for line segment patterns. SIGNIFICANT USER-VISIBLE CHANGES o densityfun.ppp, Smoothfun.ppp, Smooth.ppp These commands now handle non-Gaussian kernels. o density.ppp, relrisk.ppp, Smooth.ppp, densityfun.ppp, Smoothfun.ppp Argument 'sigma' can be infinite. o interp.im New argument 'bilinear' specifies the choice of interpolation rule. o rhohat Methods for rhohat have a new argument 'positiveCI' specifying whether confidence limits should be positive. o plot.colourmap New argument 'increasing' specifies whether the colours are displayed in order left-to-right/bottom-to-top. Changed default behaviour for discrete colour maps when vertical=FALSE. o split.ppx Argument 'f' can be a logical vector. o relrisk.ppp If se=TRUE and at="pixels", the result belongs to class 'solist'. o imcov, setcov, convolve.im The name of the unit of length is preserved. o density.ppp Slightly accelerated for non-Gaussian kernels. o bw.scott The two bandwidth values in the result now have names ('sigma.x' and 'sigma.y'). o pairdist.default Now checks whether the data are valid 2-dimensional coordinates. o pixellate.ppp New argument 'savemap' o rtemper New argument 'track'. Code runs slightly faster. o eval.im, eval.linim New argument 'warn'. o Kres, Kcom, Gcom, psstG If any of the calculated weights for the summary function are infinite or NA, they are reset to zero, with a warning, instead of a fatal error. BUG FIXES o rthin If P was close to 1, the result was sometimes an empty point pattern when it should have been identical to X. [Spotted by Maximilian Hesselbarth.] Fixed. o density.ppp Standard error calculations were incorrect when sigma was a single numeric value. The output was equal to 'sqrt(sigma)' times the correct answer. Fixed. o density.ppp Result was incorrect for non-Gaussian kernels when at="points" and leaveoneout=FALSE. Fixed. o density.ppp Did not pass additional arguments "..." to a user-supplied kernel function, in some cases. Fixed. o as.im.function, as.im.funxy If the function values were factor values and the window was not a rectangle, the result was an image with all pixel values NA. [Spotted by Corey Anderson.] Fixed. o plot.funxy If the function values were factor values and the window was not a rectangle, the plot was empty. [Spotted by Corey Anderson.] Fixed. o nnorient Crashed if the border correction did not retain any data points. [Spotted by Tomas Lazauskas.] Fixed. o linim Crashed in some cases with a message about unitnames. Fixed. o density.lpp Default value of 'dx' was sometimes incorrect. Fixed. o rMatClust, rThomas, rCauchy, rVarGamma Issued a spurious warning about bandwidth selection when saveLambda=TRUE. Fixed. o density.ppp Issued a spurious warning about bandwidth selection when 'kernel' was a user-supplied function. Fixed. o clusterfield.function Issued a spurious warning about bandwidth selection. Fixed. o relrisk.ppp Issued a spurious warning if the argument 'case' or 'control' was given, for a bivariate point pattern. Fixed. o superimpose.ppp If 'W' was a character string or function, the behaviour was not exactly as described in the help file. Fixed. o plot.psp If the marks were factor values, the colour map was displayed upside down. Fixed. o eval.fv If one of the 'fv' objects included ratio information (class 'rat') then this was erroneously retained, in some cases. Fixed. o linearKcross Crashed (with a message about a missing value of 'correction') if there were no pairs of points to count. Fixed. o envelope.lpp Crashed (randomly) when fix.n=TRUE and fix.marks=TRUE. Fixed. CHANGES IN spatstat VERSION 1.56-1 OVERVIEW o We thank Agustin Lobo for contributions. o Improvements to infrastructure. o Bug fixes. o Version nickname: "Invisible Friend" NEW FUNCTIONS o as.im.expression New method for 'as.im' for expressions. o flipxy.tess Method for 'flipxy' for tessellations. SIGNIFICANT USER-VISIBLE CHANGES o sdr This is now a generic function, with a method for class 'ppp'. o pointsOnLines The result now has an attribute named "map" which maps each point to its parent line segment. o summary.lpp Improved output. o intersect.owin Argument 'fatal' now defaults to FALSE. o quadrature schemes (class "quad" and "logiquad") Improved print and summary methods. BUG FIXES o cut.lpp Crashed if the marks were a data frame or hyperframe. Fixed. o summary.lpp, print.summary.lpp Output was garbled if the marks were a data frame or hyperframe. Fixed. o integral.linim Crashed if the function had NA values. Fixed. o Tstat Crashed if ratio=TRUE. Fixed. o intersect.owin Ignored argument 'fatal' in some cases. [Spotted by Agustin Lobo.] Fixed. o plot.tess Crashed if do.col=TRUE and 'values' was a factor. Fixed. o pcf.ppp Crashed if 'domain' was given and ratio=TRUE. Fixed. o "[<-.sparse3Darray" Crashed if 'value' was one-dimensional and the indices i, j, k specified a two-dimensional subset of x. Fixed. o plot.quad Crashed if tiles=TRUE for a quadrature scheme created by quadscheme(method="dirichlet", exact=TRUE). Fixed. o bugtable Crashed if there were no bugs! Fixed. o sparse array code An array bounds violation (segmentation fault) could occur. Fixed. o internal code Numerous internal bugs have been fixed. CHANGES IN spatstat VERSION 1.56-0 OVERVIEW o We thank Sebastian Meyer and Suman Rakshit for contributions. o Kernel estimate of intensity as a function(x,y) o Extract discrete and continuous components of a measure. o Improvements and extensions to leverage and influence code. o Plot a line segment pattern using line widths. o Find connected components of each tile in a tessellation. o Geometrical operations on 'distfun' objects. o Join vertices in a linear network. o Distance map and contact distribution for rectangular structuring element. o An infinite number of infinitesimal bugs has been detected and fixed. o Version nickname: "Bondi Tram" NEW FUNCTIONS o densityfun, densityfun.ppp Compute a kernel estimate of intensity of a point pattern and return it as a function of spatial location. o as.im.densityfun Convert function(x,y) to a pixel image. o measureDiscrete, measureContinuous Extract the discrete and continuous components of a measure. o connected.tess Find connected components of each tile in a tessellation and make a new tessellation composed of these pieces. o dffit.ppm Effect change diagnostic DFFIT for spatial point process models. o shift.distfun, rotate.distfun, reflect.distfun, flipxy.distfun, affine.distfun, scalardilate.distfun Methods for geometrical operations on 'distfun' objects. o rescale.distfun Change the unit of length in a 'distfun' object. o plot.indicfun Plot method for indicator functions created by as.function.owin. o Smooth.leverage.ppm, Smooth.influence.ppm Smooth a leverage function or an influence measure. o integral.leverage.ppm, integral.influence.ppm Compute the integral of a leverage function or an influence measure. o mean.leverage.ppm Compute the mean value of a leverage function. o rectdistmap Distance map using rectangular metric. o rectcontact Contact distribution function using rectangular structuring element. o joinVertices Join specified vertices in a linear network. SIGNIFICANT USER-VISIBLE CHANGES o plot.psp Segments can be plotted with widths proportional to their mark values. New argument 'style'. o msr Infinite and NA values are now detected (if check=TRUE) and are reset to zero, with a warning. o leverage.ppm, influence.ppm, dfbetas.ppm Faster computation in some cases. o as.im.nnfun, as.im.smoothfun New argument 'approx' chooses between a fast, approximate algorithm and a slow, exact algorithm. o cdf.test More jittering is applied when jitter=TRUE. Warnings about tied values should not occur any more. o plot.im Improved behaviour when all pixel values are NA. o plot.tess Now generates a separate plot panel for each column of marks, if do.col=TRUE. New argument 'multiplot'. o pcfinhom Now handles correction='good' o solist New argument '.NameBase' o runifpointOnLines, rpoisppOnLines New argument 'drop' o plot.studpermutest This existing function now has a help file. o bdist.points Accelerated, for polygonal windows (thanks to Sebastian Meyer). o linnet When argument 'edges' is specified, the code now checks whether any edges are duplicated. BUG FIXES o kernel.moment Result was incorrect for kernel="cosine" and kernel="optcosine". Fixed. o "[.msr" Format was mangled if the subset contained exactly one quadrature point. Fixed. o tess If a list of tiles was given, and the tiles were pixel images or masks, their pixel resolutions were ignored, and reset to the default 128x128. Fixed. o plot.linim Ignored argument 'legend' when style="colour". [Spotted by Suman Rakshit.] Fixed. o leverage.ppm, influence.ppm, dfbetas.ppm Crashed sometimes if the model was fitted by method="logi". Fixed. o Smooth.ppp Crashed with some combinations of the arguments varcov and weights when X had several columns of marks. Fixed. o plot.tess Crashed sometimes when do.col=TRUE and values=NULL. Fixed. o dilation.ppp Crashed if polygonal=FALSE. o plot.tess Ignored the marks of a tessellation defined by a pixel image. Fixed. o predict.ppm Crashed when computing a confidence interval or prediction interval if 'window' was a tessellation. Fixed. o tiles names(tiles(x)) was not always identical to tilenames(x). Fixed. o model.images.lppm Crashed in many cases. Fixed. o model.images.lppm Names or dimnames were missing in some cases. Fixed. o nncross.ppp Result had the wrong format if npoints(X) = 0 and length(what) = 1. (Spotted by Sebastian Meyer). Fixed. o plot.colourmap Crashed if the colourmap was defined on an interval of dates or times. Fixed. o StraussHard, leverage.ppm, influence.ppm, dfbetas.ppm Leverage and influence calculations generated an error when applied to models fitted with the StraussHard interaction. Fixed. o "[.ppp" Crashed if there were several columns of marks, some of which were factors, and drop=TRUE. Fixed. CHANGES IN spatstat VERSION 1.55-1 OVERVIEW o We thank Jens Astrom, Ines Moncada, Mehdi Moradi and Nicholas Read for contributions. o More support for tessellations. o Improved support for linear networks. o Fixed longstanding bug in leverage and influence diagnostics. o Minor improvements and bug fixes. o Version nickname: "Gamble Responsibly" NEW FUNCTIONS o summary.ssf Summary method for a spatially sampled function (class 'ssf'). o unstack.tess Given a tessellation with multiple columns of marks, take the columns one at a time, and return a list of tessellations, each carrying only one of the original columns of marks. SIGNIFICANT USER-VISIBLE CHANGES o plot.tess This plot method can now fill each tile with a different colour. New arguments 'do.col', 'values', 'col' and 'ribargs'. Old argument 'col' has been renamed 'border' for consistency. o integral.linim, integral.linfun Argument 'domain' can now be a tessellation. o integral.ssf Argument 'domain' can now be a tessellation. o as.owin.default Now accepts a structure with entries named 'xmin,ymin,xmax,ymax' in any order. This handles objects of class 'bbox' in the 'sf' package. o as.owin.default Now detects objects of class "SpatialPolygons" and issues a more helpful error message. o pseudoR2.ppm, pseudoR2.lppm The null model now includes any offset terms, by default. [Suggested by Jens Astrom.] New argument 'keepoffset'. o closepairs.ppp New argument 'periodic' o fitted.ppm New argument 'ignore.hardcore'. o predict.ppm New argument 'ignore.hardcore'. o leverage.ppm, influence.ppm, dfbetas.ppm Computation has been vastly accelerated for models with Geyer interaction fitted using isotropic or translation edge corrections. o leverage.ppm, influence.ppm, dfbetas.ppm Virtually all models and edge corrections are now supported, using a "brute force" algorithm. This can be slow in some cases. o cdf.test Monte Carlo test runs faster. o summary.distfun, summary.funxy Pixel resolution can now be controlled. o persp.funxy Improved z-axis label. o plot.ppp Improved placement of symbol legend when argument 'symap' is given. o plot.msr Changed the default rule for bandwidth for smoothing the density. BUG FIXES o nnmark, as.im.ssf if marks(X) was a matrix rather than a data frame, the results were completely incorrect (and had completely wrong format). Fixed. o predict.mppm If the model included random effects, and if the library 'MASS' was not loaded, the predictions were on the log scale (i.e. they were logarithms of the correct values). [Spotted by Nicholas Read.] Fixed. o leverage.ppm, influence.ppm, dfbetas.ppm Calculations were slightly incorrect for models with a hard core. Fixed. o leverage.ppm The mean leverage value (shown as a contour line in plot.leverage.ppm) was slightly incorrect for Gibbs models. Fixed. o Ops.msr If the input data contained an auxiliary pixel image of the density component of the measure (attribute "smoothdensity") this image was not updated; it was copied to the output unchanged. Plots of the resulting measure were incorrect, but calculations with the measure were correct. Fixed. o integral.msr If the result was a matrix, it was the transpose of the correct answer. Fixed. o "[.linim" The result sometimes had the wrong class. Fixed. o "[.linnet" In calculating L[W] where W is a window, the code ignored segments of L that crossed W without having a vertex in W. Fixed. o nnmap Crashed if W = NULL. Fixed. o density.lpp, nncross.lpp Crashed sometimes with an obscure message about "z$which". [Spotted by Ines Moncada.] Fixed. o as.im.distfun Crashed, for the distfun of a point pattern, if approx=FALSE. Fixed. o as.solist Crashed when x was a 'layered' object. Fixed. o linnet Crashed in some trivial cases where there were no points or lines. Fixed. CHANGES IN spatstat VERSION 1.55-0 OVERVIEW o We thank 'AdriMaz' and Nicholas Read for contributions. o Lurking variable plot for models fitted to several point patterns. o Improvements to code for class 'mppm'. o Improvements to leverage and influence diagnostics. o Improved summary information for funxy and distfun objects. o Bug fixes and improvements. o Removed old warnings and deprecated functions. o Nickname: "Stunned Mullet" NEW FUNCTIONS o contour.leverage.ppm Method for 'contour' for leverage functions of class 'leverage.ppm' o lurking New generic function for lurking variable plots. o lurking.ppp, lurking.ppm These are equivalent to the original function 'lurking'. They are now methods for the new generic 'lurking'. o lurking.mppm New method for class 'mppm' Lurking variable plot for models fitted to several point patterns. o print.lurk Prints information about the object returned by the function 'lurking' representing a lurking variable plot. o model.matrix.mppm Method for 'model.matrix' for models of class 'mppm'. o test.crossing.psp, test.selfcrossing.psp Previously undocumented functions for testing whether segments cross. SIGNIFICANT USER-VISIBLE CHANGES o predict.ppm Now recognises the arguments 'dimyx' and 'eps' for specifying the resolution of the grid of prediction points. o leverage.ppm, dfbetas.ppm Increased the default resolution of the pixel images. Spatial resolution can now be controlled by the arguments 'dimyx', 'eps'. o ppmInfluence The result now belongs to class 'ppmInfluence', for which there are methods for 'leverage', 'influence', 'dfbetas' which extract the desired component. o plot.leverage.ppm New argument 'what'. o persp.leverage.ppm New arguments 'zlab' and 'what'. o as.im.leverage.ppm New argument 'what'. o summary.funxy, summary.distfun Printed information now includes a summary of the function values. o lurking.ppm Accelerated. o "[.psp" Accelerated. o clf.test, conspire, bounding.box, ksmooth.ppp, mpl, superimposePSP, eval.hyper, smooth.fv, smooth.ppp, smooth.msr, rtoro, plot.kstest These deprecated functions have now been removed. o bermantest This deprecated function has now been removed. Use berman.test instead. o kstest This deprecated function has now been removed. Use cdf.test instead. o plot.ppp A very old warning, about the interpretation of the mark scale as the circle diameter, is no longer printed. BUG FIXES o nnmap, nnmark Values were incorrect if the resulting pixel image had unequal numbers of rows and columns. Fixed. o vcov.mppm Format was incorrect (rows/columns were omitted) in some cases. Fixed. o model.matrix.ppm, model.frame.ppm Values were sometimes incorrect when applied to the result of subfits(). To be precise, if 'fit' was an mppm object fitted to a hyperframe that included 'design covariates' (covariates that take a constant value in each row of the hyperframe), and if 'futs <- subfits(fit)', then model.matrix(futs[[i]]) gave incorrect values in the columns corresponding to the design covariates. Fixed. o model.matrix.ppm The attribute 'assign' was omitted, in some cases. Fixed. o simulate.dppm, simulate.detpointprocfamily In dimensions higher than 2, the result was shifted so that it was centred at the origin. Fixed. o Smooth.ppp Crashed if geometric=TRUE and there were several columns of marks. Fixed. o simulate.dppm, simulate.detpointprocfamily Crashed if nsim > 1 and the spatial dimension was not equal to 2. Fixed. o plot.leverage.ppm Contour line was annotated, which was not intended. Fixed. o leverage.ppm The leverage function was oversmoothed, when the model was fitted with method="logi". Fixed. CHANGES IN spatstat VERSION 1.54-0 OVERVIEW o We thank Rochelle Constantine, Lily Kozmian-Ledward, Ian Renner and Leigh Torres for contributions. o New dataset 'cetaceans'. o Gamma correction for colour maps and image plots. o Class 'units' has been renamed 'unitname' to avoid package collision. o Bug fix in leverage code o Tighter bounding box for psp, lpp, linnet objects. o Improved layout in plot.solist o Tools to increase colour saturation. o Connected components of a 3D point pattern. o Accelerated computations on linear networks. o Accelerated simulation of determinantal point processes. o Improved printing of 3D point patterns. o Minor corrections to handling of unitnames. o Nickname: 'Vacuous Mission Statement' NEW DATASETS o cetaceans Nine replicates of a marine survey in New Zealand, consisting of recorded sightings of dolphins, whales and other species. Generously contributed by Lily Kozmian-Ledward, Rochelle Constantine and Leigh Torres. NEW FUNCTIONS o to.saturated Convert a colour value to the corresponding fully-saturated colour. o intensity.psp Compute the average total length of segments per unit area. o boundingbox.psp Bounding box for line segment patterns. This produces a tighter bounding box than the previous default behaviour. o boundingbox.lpp Bounding box for point patterns on a linear network. This produces a tighter bounding box than the previous default behaviour. o boundingbox.linnet Bounding box for a linear network. This produces a tighter bounding box than the previous default behaviour. o "Frame<-.default" New default method for assigning bounding frame to a spatial object. o connected.pp3 Connected components of a 3D point pattern. o colouroutputs, "colouroutputs<-" Extract or assign colour values in a colour map. (Documented a previously-existing function) SIGNIFICANT USER-VISIBLE CHANGES o plot.im New argument 'gamma' supports gamma correction of colour maps. New argument 'ncolours' specifies the default number of colours. o colourmap, lut New argument 'gamma' supports gamma correction of colour maps. o plot.solist, plot.anylist New argument 'panel.vpad' controls vertical space for panel title when equal.scales=FALSE. o class 'units' The class 'units' has been renamed 'unitname' to avoid a clash with other packages. o unitname The generic function 'unitname' now returns an object of class 'unitname'. o print.units, summary.units, print.summary.units, as.character.units, compatible.units These methods are now called print.unitname, summary.unitname, print.summary.unitname, as.character.unitname and compatible.unitname. o as.units This function has been renamed 'as.unitname' and now returns an object of class 'unitname'. o rescale.units This method has been renamed 'rescale.unitname' and now returns an object of class 'unitname'. o profilepl New argument 'fast' controls the use of shorcuts. o reload.or.compute New argument 'force'. o pixellate.ppp, pixellate.owin, pixellate.psp New argument 'DivideByPixelArea'. o density.psp New argument 'at' determines locations where the density is evaluated. o as.solist as.solist(x) always returns an object of class 'solist', removing any additional classes. o lineardirichlet Accelerated. o integral.linim Accelerated. o "[.ppp", "[.lpp", "[.psp" In the expression X[W] where W is a window, if X has a unitname but W does not, the result now inherits the unitname of X. o distfun.ppp New argument 'undef'. o print.pp3 More informative output when x is marked. BUG FIXES o leverage.ppm, influence.ppm, dfbetas.ppm Calculations were slightly incorrect for models fitted using the border correction. Fixed. o integral.linim Gave incorrect value in some extreme cases (where many network segments were shorter than one pixel width). Fixed. o update.kppm Did not function correctly when several additional arguments were given. Fixed. o plot.solist Panel titles were cut off, when equal.scales=FALSE (the default). Fixed. o intersection.owin, union.owin, setminus.owin The result sometimes did not inherit the correct 'unitname'. Fixed. CHANGES IN spatstat VERSION 1.53-2 OVERVIEW o We thank Christophe Biscio and Rasmus Waagepetersen for contributions. o Correction to 'lohboot' o Improvements to ppm and update.ppm o Bug fixes and minor improvements. o Nickname: "Quantum Entanglement" NEW FUNCTIONS o fitin.profilepl Extract the fitted interaction from a model fitted by profile likelihood. SIGNIFICANT USER-VISIBLE CHANGES o lohboot Algorithm has been corrected and extended thanks to Christophe Biscio and Rasmus Waagepetersen. New arguments 'block', 'basicboot', 'Vcorrection'. o ppm.ppp, ppm.quad New argument 'clipwin' o update.ppm For the case 'update(model, X)' where X is a point pattern, if the window of X is different from the original window, then the model is re-fitted from scratch (i.e. use.internal=FALSE). o plot.leverage.ppm A contour line showing the average value of leverage is now drawn on the colour ribbon, as well as on the main image. New argument 'args.contour'. BUG FIXES o lohboot Implementation was completely incorrect. [Spotted and fixed by Christophe Biscio and Rasmus Waagepetersen.] Fixed. o update.ppm Did not always work correctly with formulae that included 'polynom()' terms. Fixed. CHANGES IN spatstat VERSION 1.53-1 OVERVIEW o We thank Suman Rakshit for contributions. o Bug fix in plot.linim o Nickname: "Drongo" BUG FIXES o plot.linim Colour map was mangled if log=TRUE. Fixed. CHANGES IN spatstat VERSION 1.53-0 OVERVIEW o We thank Tilman Davies and Mehdi Moradi for contributions. o Numerous bug fixes for linear networks code. o spatstat now requires the sub-package 'spatstat.data' which contains the datasets. o Minor enhancements and bug fixes. o Nickname: "Tinfoil Hat" NEW FUNCTIONS o "[<-.linim" Subset assignment method for pixel images on a linear network. o nnfromvertex Given a point pattern on a linear network, find the nearest data point from each vertex of the network. o tile.lengths Calculate the length of each tile in a tessellation on a network. o text.ppp, text.lpp, text.psp Methods for 'text' for spatial patterns. SIGNIFICANT USER-VISIBLE CHANGES o datasets All datasets installed in 'spatstat' have now been moved into the sub-package 'spatstat.data'. This should not have any effect on normal use. The 'spatstat.data' package is automatically loaded when spatstat is loaded, and the datasets are lazy-loaded so that they are available in the usual way. To list all datasets you now need to type 'data(package="spatstat.data")' o nbfires This dataset now includes information about the different land and sea borders of New Brunswick. o rhohat New argument 'subset' allows computation for a subset of the data. o predict.lppm Argument 'locations' can now be an 'lpp' object. o ewcdf Argument 'weights' can now be NULL. o plot.msr New arguments 'equal.markscale' and 'equal.ribbon'. o plot.im The number of tick marks in the colour ribbon can now be controlled using the argument 'nint' in 'ribargs'. o plot.symbolmap New argument 'nsymbols' controls the number of symbols plotted. o square Handles a common error in the format of the arguments. o [.linim More robust against artefacts. o [.linnet More robust against artefacts when the subset index is a pixel mask. o linim The image Z is now automatically restricted to the network. New argument 'restrict'. o plot.linim When style="width", negative values are plotted in red (by default). New argument 'negative.args' controls this. o plot.linim New argument 'zlim' specifies the range of values to be mapped. o Summary.linim Recognises the argument 'finite' so that range(x, finite=TRUE) works for a linim object x. o identify.psp Improved placement of labels. Arguments can be passed to text.default to control the plotting of labels. o as.polygonal Accelerated when w is a pixel mask. o density.lpp Accelerated in the default case. o Kinhom Stops gracefully if 'lambda' contains any zero values. o print.linim Prints more information. BUG FIXES o with.msr The value of 'atommass' was incorrect, due to a coding error. Fixed. o [.linim Internal data was sometimes corrupted. Fixed. o as.linim The result had incorrect internal format when Window(X) was a mask and one of the arguments 'eps', 'dimyx', 'xy' was present. Fixed. o as.im.im If W was a rectangle or polygonal window, the pixel resolution of the result was determined by the spatstat defaults, rather than being determined by the image argument X. This was contrary to the rule advertised in help(as.im). Fixed. o density.lpp In the 'slow' case (kernel not Gaussian, or continuous=FALSE), occasionally a pixel could incorrectly be assigned the value 1. [Spotted by Mehdi Moradi.] Fixed. o "[.solist" Ignored the "..." arguments in some cases. Fixed. o density.lpp Ignored the resolution arguments 'eps', 'dimyx' in the default case. Fixed. o plot.msr Plotted the panel titles on top of each other, if how="contour". Fixed. o contour.im Plotted the title text at the wrong place when add=TRUE and show.all=TRUE. Fixed. o predict.lppm Crashed if 'locations' was an 'lpp' object. Fixed. o plot.ppp Crashed if the window had height 0 and width 0 and the pattern had several columns of marks. Fixed. o plot.solist Crashed if all panels had windows of height 0 and width 0. Fixed. o linearK, linearKinhom, linearpcf, linearpcfinhom Crashed if the linear network was disconnected and one component of the network contained fewer than 2 points. Fixed. o integral.linim Crashed in some cases. Fixed. o "[.linim" Crashed in some cases. Fixed. CHANGES IN spatstat VERSION 1.52-1 OVERVIEW o Bug fix to satisfy the development version of R. o Nickname: "Apophenia" SIGNIFICANT USER-VISIBLE CHANGES o Ops.imlist Improved the 'names' of the result. BUG FIXES o bw.smoothppp Crashes in R-devel. Fixed. CHANGES IN spatstat VERSION 1.52-0 OVERVIEW o We thank Nicholas Read, Abdollah Jalilian, Suman Rakshit, Dominic Schuhmacher and Rasmus Waagepetersen for contributions. o Important bug fixes. o Now handles disconnected linear networks. o Effect function is now available for all types of fitted model. o A model can be fitted or re-fitted to a sub-region of data. o More support for measures. o 'Pool' operations improved. o Geometric-mean smoothing. o Changed algorithm defaults in ippm. o Version nickname: "Rudimentary Lathe" NEW FUNCTIONS o as.data.frame.envelope Extract function data from an envelope object, including the functions for the simulated data ('simfuns') if they were saved. o is.connected, is.connected.default, is.connected.linnet Determines whether a spatial object consists of one topologically connected piece, or several pieces. o is.connected.ppp Determines whether a point pattern is connected after all pairs of points closer than distance R are joined. o hist.funxy Histogram of values of a spatial function. o model.matrix.ippm Method for 'model.matrix' which allows computation of regular and irregular score components. o harmonise.msr Convert several measures (objects of class 'msr') to a common quadrature scheme. SIGNIFICANT USER-VISIBLE CHANGES o Smooth.ppp New argument 'geometric' supports geometric-mean smoothing. o Kinhom New argument 'ratio'. o linearKinhom, linearpcfinhom Changed default behaviour when 'lambda' is a fitted model. New arguments 'update' and 'leaveoneout'. o linearK, linearKinhom, linearpcf, linearpcfinhom, compilepcf Ratio calculations are now supported. New argument 'ratio'. o effectfun Now works for 'ppm', 'kppm', 'lppm', 'dppm', 'rppm' and 'profilepl' objects. o ppm, kppm The argument 'subset' can now be a window (class 'owin') specifying the subset of data to which the model should be fitted. o fitted.lppm New argument 'leaveoneout' allows leave-one-out computation of fitted value. o pool.rat New arguments 'relabel' and 'variance'. o density.lpp The return value is a pixel image of class 'linim' in all cases. o plot.linim, plot.linfun A scale bar is now plotted when style="width". New argument 'legend'. o ippm Default values for the parameters of the optimisation algorithm (nlm.args) have changed. o ippm The internal format of the result has been extended slightly. o bind.fv New argument 'clip'. o as.im.distfun New argument 'approx' specifies the choice of algorithm. o "[.psp" New argument 'fragments' specifies whether to keep fragments of line segments that are cut by the new window, or only to retain segments that lie entirely inside the window. o predict.rhohat New argument 'what' determines which value should be calculated: the function estimate, the upper/lower confidence limits, or the standard error. o pool.fv New arguments 'relabel' and 'variance' o pool.rat New argument 'weights'. o plot.msr New argument 'massthresh'. o Ops.msr Calculations like A+B can now be performed even when the measures A and B are not defined on the same quadrature scheme. o density.ppp New argument 'verbose'. o bw.pcf New argument 'verbose'. o hist.im New argument 'xname'. o [.leverage.ppm New argument 'update'. o [.layered Additional arguments '...' are now passed to other methods. o logLik.ppm The warning about pseudolikelihood ('log likelihood not available') is given only once, and is not repeated in subsequent calls, within a spatstat session. o kppm Refuses to fit a log-Gaussian Cox model with anisotropic covariance. o plot.linim, plot.linfun The return value has a different format. Arguments have been renamed and reorganised. o density.lpp New argument 'old'. o ippm Accelerated. o Smooth.ppp Now exits gracefully if any mark values are NA, NaN or Inf. o timeTaken Now exits gracefully if there is no timing information. o nbfires The unit of length for the coordinates is now specified in this dataset. BUG FIXES o bw.pcf Results were totally incorrect due to a typo. [Spotted by Abdollah Jalilian and Rasmus Waagepetersen.] Fixed. o predict.rho2hat Results were incorrect for a rho2hat object computed from a point pattern. Fixed. o density.ppp If the smoothing bandwidth was very small (e.g.\ smaller than pixel width), results were inaccurate if the default resolution was used, and completely wrong if another resolution was specified. [Spotted by Dominic Schuhmacher.] Fixed. o linearK, linearKinhom, linearpcf, linearpcfinhom, linearKcross, linearKdot, linearpcfcross, linearpcfdot, linearKcross.inhom, linearKdot.inhom, linearpcfcross.inhom, linearpcfdot.inhom Crashed if the network was disconnected. Fixed. o crossdist.lpp Crashed if the network was disconnected. Fixed. o countends Crashed if the network was disconnected. Fixed. o model.images.ppm Crashed for models fitted using 'covfunargs'. Fixed. o model.matrix.ppm Crashed for models fitted using 'covfunargs', if argument 'Q' was given. Fixed. o polynom Expansion of some polynomials caused an error message about 'invalid model formula'. Fixed. o plot.ppp The argument 'type="n"' did not suppress plotting of the legend, for marked point patterns. Fixed. o plot.psp Ignored 'show.all' when 'add=TRUE'. Fixed. o intensity.ppm Result had incorrect 'names' attribute in some cases. Fixed. o marks<-.ppx The assignment marks(X) <- a, where 'a' is a single atomic value, caused an error if 'X' contained zero points. Fixed o model.depends Crashed when applied to regression models fitted by 'gam', or point process models fitted by 'ppm' with 'use.gam=TRUE'. Fixed. o pool.fv Crashed sometimes, if the arguments did not have the same set of column names. Fixed. o pool.rat Crashed with an error message from 'fmt' if there were more than 20 objects to be pooled. Fixed. o linearK The 'theo' column was missing if npoints(X) < 2 and correction="Ang". Fixed. o model.matrix.ppm Result was malformed if the model was fitted with 'use.gam=TRUE'. Fixed. o effectfun Crashed if 'covname' was omitted, if the model was fitted with 'use.gam=TRUE'. Fixed. o nncross.lpp Result had incorrect format if Y was empty, in some cases. Fixed. o linearKinhom Plot label for y axis was incorrect. [Spotted by Suman Rakshit.] Fixed. o plot.solist If the entries were 'linim' objects, they were plotted using image() so arguments like 'style="w"' were ignored. Fixed. o as.ppp.data.frame Crashed if X was an object of class 'tbl_df' from the dplyr package. Fixed. o plot.lpp Crashed if there were multiple columns of marks. Fixed. CHANGES IN spatstat VERSION 1.51-0 OVERVIEW o We thank Greg McSwiggan, Mehdi Moradi and Tammy L Silva for contributions. o New fast algorithm for kernel smoothing on a linear network. o Leverage and influence diagnostics extended to Poisson/Gibbs models fitted by logistic composite likelihood. o Two-stage Monte Carlo test. o Dirichlet/Voronoi tessellation on a linear network. o Thinning of point patterns on a linear network. o More support for functions and tessellations on a linear network. o Improvements and bug fixes. o Version nickname: 'Poetic Licence' NEW FUNCTIONS o bits.test: Balanced Independent Two-Stage Monte Carlo test, an improvement on the Dao-Genton test. o lineardirichlet Computes the Dirichlet-Voronoi tessellation associated with a point pattern on a linear network. o domain.lintess, domain.linfun Extract the linear network from a 'lintess' or 'linfun' object. o summary.lintess Summary of a tessellation on a linear network. o clicklpp Interactively add points on a linear network. o envelopeArray Generate an array of envelopes using a function that returns 'fasp' objects. SIGNIFICANT USER-VISIBLE CHANGES o density.lpp New fast algorithm (up to 1000 times faster) for the default case where kernel="gaussian" and continuous=TRUE. Generously contributed by Greg McSwiggan. o leverage.ppm, influence.ppm, dfbetas.ppm These methods now work for models that were fitted by logistic composite likelihood (method='logi'). o rthin Argument X can now be a point pattern on a linear network (class 'lpp'). o fitted.ppm New option: type = "link" o update.kppm New argument 'evaluate'. o integral.linfun New argument 'delta' controls step length of approximation to integral. o as.linim.default New argument 'delta' controls spacing of sample points in internal data. o as.linfun.lintess New argument 'values' specifies the function value for each tile. New argument 'navalue'. BUG FIXES o leverage.ppm, influence.ppm, dfbetas.ppm Results for Gibbs models were incorrect due to a mathematical error. (Results for Poisson models were correct). Fixed. o leverage.ppm, influence.ppm, dfbetas.ppm, ppmInfluence Calculations were incorrect for a Geyer model fitted using an edge correction other than "border" or "none". Fixed. o step, kppm, update.kppm 'step' did not work for kppm objects in some cases due to a scoping problem in update.kppm. Fixed. o improve.kppm Crashed if the window was not a rectangle. Fixed. o pcf.ppp, pcfinhom Crashed if kernel="epa" rather than "epanechnikov". Fixed. o alltypes Crashed if envelope=TRUE and reuse=FALSE. Fixed. o pairdist.lpp, nndist.lpp, nnwhich.lpp, nncross.lpp Crashed if the network was disconnected. Fixed. o as.im.linim, as.linim.linim Additional arguments such as 'eps' and 'dimyx' were ignored. Fixed. o as.im.default Arguments 'eps and 'xy' were ignored if X was a single numeric value. Fixed. o 'timed' class Printing of these objects did not work in some locales. Fixed. o runifpoint Ignored 'drop' argument if the window was a rectangle. Fixed. CHANGES IN spatstat VERSION 1.50-0 OVERVIEW o We thank Richard Cotton, Adrian Heyner, Abdollah Jalilian, Dominic Schuhmacher and Rasmus Waagepetersen for contributions. o spatstat now 'Imports' the package 'spatstat.utils'. o Bandwidth selection for pair correlation function. o Improvements and bug fixes. o Version nickname: 'Bunyip Aristocracy' NEW PACKAGE STRUCTURE o spatstat is being split into several sub-packages, to satisfy the requirements of CRAN. This should not affect the user: existing code will continue to work in the same way. Currently there are two sub-packages, called 'spatstat.utils' and 'spatstat'. Typing 'library(spatstat)' will load the familiar 'spatstat' package which can be used as before, and will silently import the 'spatstat.utils' package. The 'spatstat.utils' package contains utility functions that were originally written for 'spatstat': they were undocumented internal functions in 'spatstat', but are now documented and accessible in a separate package because they may be useful for other purposes. To access these functions, you need to type 'library(spatstat.utils)'. NEW FUNCTIONS o bw.pcf Bandwidth selection for pair correlation function. Original code contributed by Abdollah Jalilian and Rasmus Waagepetersen. o grow.box3 Expand a three-dimensional box. SIGNIFICANT USER-VISIBLE CHANGES o as.owin Now refuses to convert a 'box3' to a two-dimensional window. o pixellate.ppp If the pattern is empty, the result is an integer-valued image (by default) for consistency with the results for non-empty patterns. o ppp If the coordinate vectors x and y contain NA, NaN or infinite values, these points are deleted with a warning, instead of causing a fatal error. o ppm Argument 'interaction' can now be a function that makes an interaction, such as Poisson, Hardcore, MultiHard. o pcf, pcfinhom New argument 'close' for advanced use. o runifpointx, rpoisppx New argument 'drop'. o shapley, ponderosa In these installed datasets, the functions shapley.extra$plotit and ponderosa.extra$plotit have changed slightly (to accommodate the dependence on the package spatstat.utils). o kppm Improved printed output. BUG FIXES o rMaternI, rMaternII If 'win' was a three-dimensional box of class 'box3', the result was a two-dimensional point pattern. [Spotted by Adrian Heyner.] Fixed. o rmhmodel.ppm, simulate.ppm Crashed when applied to a fitted Lennard-Jones model. [Spotted by Dominic Schuhmacher.] Fixed. o leverage.ppm, influence.ppm, dfbetas.ppm Crashed when applied to some hard-core models. Fixed. o "[.ppx" The format of the result was slightly malformed if exactly one point was selected. Fixed. o unmark.lpp, marks<-.lpp The result had class c("lpp", "lpp", "ppx") instead of c("lpp", "ppx"). Fixed. CHANGES IN spatstat VERSION 1.49-0 OVERVIEW o We thank Tilman Davies, Kassel Hingee, Abdollah Jalilian, Brian Ripley and Dominic Schuhmacher for contributions. o spatstat now 'Suggests' the package 'fftwtools'. o Operations on signed measures. o Operations on lists of pixel images. o Improved pixellation of point patterns. o Stieltjes integral extended. o Subset operators extended. o Greatly accelerated 'rmh' when using 'nsave' o Some computations accelerated. o Size of namespace reduced, for efficiency. o Bug fixes. o Version nickname: 'So-Called Software' NEW DEPENDENCIES o fftwtools spatstat now 'Suggests' the package 'fftwtools'. This package provides a very fast implementation of the Fast Fourier Transform, leading to much faster computation in the spatstat functions 'density.ppp', 'relrisk.ppp', 'convolve.im', 'blur', 'scan.test' and many other functions. The 'fftwtools' package requires the external software library 'fftw'. We strongly recommend installing this library if possible. NEW FUNCTIONS o hexagon, regularpolygon Create regular polygons. o Ops.msr Arithmetic operations for measures. o Math.imlist, Ops.imlist, Summary.imlist, Complex.imlist Arithmetic operations for lists of pixel images. o measurePositive, measureNegative, measureVariation, totalVariation Positive and negative parts of a measure, and variation of a measure. o as.function.owin Convert a spatial window to a function (x,y), the indicator function. o as.function.ssf Convert an object of class 'ssf' to a function(x,y) o as.function.leverage.ppm Convert an object of class 'leverage.ppm' to a function(x,y) SIGNIFICANT USER-VISIBLE CHANGES o stieltjes Argument 'M' can be a stepfun object (such as an empirical CDF). o quantile.ewcdf The function is now normalised to the range [0,1] before the quantiles are computed. This can be suppressed by setting normalise=FALSE. o pixellate.ppp New arguments 'fractional' and 'preserve' for more accurate discretisation. o "[.layered" Subset index i can now be an 'owin' object. o "[.solist" Subset index i can now be an 'owin' object. o plot.solist, plot.imlist, plot.anylist Result is now an (invisible) list containing the result from executing the plot of each panel. o ppp New argument 'checkdup'. o Summary.im Argument 'na.rm' is no longer ignored. o cdf.test The methods for classes ppp, ppm, lpp, lppm, slrm have a new argument 'interpolate'. o as.solist The argument x can now be a spatial object; as.solist(cells) is the same as solist(cells). o bw.diggle, bw.ppl, bw.relrisk, bw.smoothppp These functions now extract and store the name of the unit of length from the point pattern dataset. When the bandwidth selection criterion is plotted, the name of the unit of length is shown on the x-axis. o polynom This function now has a help file. o rmhcontrol New parameter 'pstage' determines when to generate random proposal points. o rmh Accelerated, in the case where multiple patterns are saved using 'nsave'. o bdist.pixels Accelerated for polygonal windows. New argument 'method'. o spatstat namespace The namespace of the spatstat package has been shortened (by internally registering the native routines) which should make the package run faster. o sum.im, range.im, max.im, min.im These functions have been removed, as they are now subsumed in Summary.im. BUG FIXES o plot.msr If one of 'nrows' or 'ncols' was specified, but not both, an obscure error occurred. Fixed. o plot.solist, plot.imlist, plot.anylist Crashed if 'nrows' and 'ncols' were given values implying that some rows or columns would not contain any plots. Fixed. o as.ppp.lpp Crashed if there was more than one column of marks. Fixed. o has.close.pp3 Results were incorrect, or a crash occurred, when argument 'Y' was given. Fixed. o rmpoispp If 'lambda' was a list of images, 'names(lambda)' was ignored, rather than serving as the default value of 'types'. Fixed. o bugfixes Output was garbled, in rare cases. Fixed. o kppm Result was malformed when clusters="VarGamma" and method="clik2". Spotted by Abdollah Jalilian. Fixed. o QQversion Plotting labels were malformed. Fixed. CHANGES IN spatstat VERSION 1.48-0 OVERVIEW o We thank Kim Colyvas, Yongtao Guan, Gopalan Nair, Nader Najari, Suman Rakshit, Ian Renner and Hangsheng Wang for contributions. o Sufficient Dimension Reduction for point processes. o Alternating Gibbs Sampler for point process simulation. o Intensity approximation for area-interaction and Geyer models. o New class of spatially sampled functions. o ROC and AUC extended to other types of point patterns and models. o More support for linear networks. o More support for infinite straight lines. o Simulation of 'rhohat' objects. o Kernel smoothing accelerated. o Methods for 'head' and 'tail' for spatial patterns. o More low-level functionality. o Improvements and bug fixes. o spatstat now has more than 1000 help files. o Nickname: 'Model Prisoner' NEW CLASSES o ssf Class of spatially sampled functions. NEW FUNCTIONS o sdr, dimhat Sufficient Dimension Reduction for point processes. Matlab code contributed by Yongtao Guan, translated by Suman Rakshit. o rags, ragsAreaInter, ragsMultiHard Alternating Gibbs Sampler for point processes. o psib Sibling probability (index of clustering strength in a cluster process). o bugfixes List all bug fixes in recent versions of a package. o roc.kppm, roc.lppm, roc.lpp Methods for 'roc' (receiver operating characteristic curve) for fitted models of class 'kppm' and 'lppm' and point patterns of class 'lpp' o auc.kppm, auc.lppm, auc.lpp Methods for 'auc' (area under the ROC curve) for fitted models of class 'kppm' and 'lppm' and point patterns of class 'lpp' o rlpp Random points on a linear network with a specified probability density. o cut.lpp Method for 'cut' for point patterns on a linear network. o crossing.linnet Find crossing points between a linear network and another set of lines. o ssf Create a spatially sampled function o print.ssf, plot.ssf, contour.ssf, image.ssf Display a spatially sampled function o as.im.ssf, as.ppp.ssf, marks.ssf, marks<-.ssf, unmark.ssf, [.ssf, with.ssf Manipulate data in a spatially sampled function o Smooth.ssf Smooth a spatially sampled function o integral.ssf Approximate integral of spatially sampled function o simulate.rhohat Generate a Poisson random point pattern with intensity that is a function of a covariate, given by a 'rhohat' object. o head.ppp, head.ppx, head.psp, head.tess, tail.ppp, tail.ppx, tail.psp, tail.tess Methods for 'head' and 'tail' for spatial patterns. o as.data.frame.tess Convert a tessellation to a data frame. o timeTaken Extract the timing data from a 'timed' object or objects. o rotate.infline, shift.infline, reflect.infline, flipxy.infline Geometrical transformations for infinite straight lines. o whichhalfplane Determine which side of an infinite line a point lies on. o points.lpp Method for 'points' for point patterns on a linear network. o pairs.linim Pairs plot for images on a linear network. o has.close Faster way to check whether a point has a close neighbour. o closetriples Low-level function to find all close triples of points. o matrixpower, matrixsqrt, matrixinvsqrt Raise a matrix to any power. SIGNIFICANT USER-VISIBLE CHANGES o intensity.ppm Intensity approximation is now available for the Geyer saturation process and the area-interaction process (results of research with Gopalan Nair). o envelope.lpp, envelope.lppm New arguments 'fix.n' and 'fix.marks' allow envelopes to be computed using simulations conditional on the observed number of points. o "[.im" The subset index "i" can now be a linear network (object of class 'linnet'). The result of "x[i, drop=FALSE]" is then a pixel image of class 'linim'. o cut.ppp Argument z can be "x" or "y" indicating one of the spatial coordinates. o rThomas, rMatClust, rCauchy, rVarGamma, rPoissonCluster, rNeymanScott New argument 'saveparents'. o lintess Argument 'df' can be missing or NULL, resulting in a tesellation with only one tile. o lpp X can be missing or NULL, resulting in an empty point pattern. o plot.lintess Improved plot method, with more options. o rpoisline Also returns information about the original infinite random lines. o density.ppp, Smooth.ppp Accelerated. o density.psp New argument 'method' controls the method of computation. New faster option 'method="FFT"' o nndist.lpp Accelerated. BUG FIXES o F3est Estimates of F(r) for the largest value of r were wildly incorrect. Fixed. o clip.infline Results were incorrect unless the midpoint of the window was the coordinate origin. Fixed. o integral.linim Results were inaccurate if many of the segment lengths were shorter than the width of a pixel. Fixed. o predict.lppm Bizarre error messages about 'class too long' or 'names too long' occurred if the model was multitype. Fixed. o superimpose Point patterns containing 0 points were ignored when determining the list of possible marks. Fixed. o chop.tess Vertical lines were not handled correctly with pixellated tessellations. Fixed. o timed Argument 'timetaken' was ignored. Fixed. o ppm Crashed if method="logi" and the 'covariates' were a data frame. [Spotted by Kim Colyvas and Ian Renner.] Fixed. o rpoislpp, runiflpp Crashed if nsim > 1. Fixed. o rpoisline Crashed if zero lines were generated. Fixed. o model.frame.ppm Crashed if the original model was fitted to a data frame of covariates and there were NA's amongst the covariate values. [Spotted by Kim Colyvas.] Fixed. o any, all When applied to pixel images (objects of class 'im') the result was sometimes NA when a finite value should have been returned. Fixed. o predict.rhohat When the original data were on a linear network, the result of predict.rhohat did not belong to the correct class 'linim'. Fixed. CHANGES IN spatstat VERSION 1.47-0 OVERVIEW o We thank Marcel Austenfeld, Guy Bayegnak, Tilman Davies, Cenk Icos, Jorge Mateu, Frederico Mestre, Mehdi Moradi, Virginia Morera Pujol, Suman Rakshit and Sven Wagner for contributions. o Non-Gaussian smoothing kernels. o Important bug fix in linearK, linearpcf o Changed internal format of linnet and lpp objects. o Faster computation in linear networks. o Bias correction techniques. o Bounding circle of a spatial object. o Minkowski sum also applicable to point patterns and line segment patterns. o Option to plot marked points as arrows. o Kernel smoothing accelerated. o Workaround for bug in some graphics drivers affecting image orientation. o Bug fixes and improvements. o Version nickname: 'Responsible Gambler' NEW FUNCTIONS o anyNA.im Method for 'anyNA' for pixel images. o bc Bias correction (Newton-Raphson) for fitted model parameters. See also 'rex'. o boundingcircle, boundingcentre Find the smallest circle enclosing a window or point pattern. o "[.linim" Subset operator for pixel images on a linear network. o mean.linim, median.linim, quantile.linim The mean, median, or quantiles of pixel values in a pixel image on a linear network. o rex Richardson extrapolation for numerical integrals and statistical model parameter estimates. o weighted.median, weighted.quantile Median or quantile of numerical data with associated weights. SIGNIFICANT USER-VISIBLE CHANGES o linear networks The internal format of a 'linnet' (linear network) object has been changed. Existing datasets of class 'linnet' and 'lpp' are still supported. However, computation will be faster if they are converted to the new format. To convert a linnet object L to the new format, use L <- as.linnet(L). To convert an lpp object X to the new format, use X <- as.lpp(X). o density.ppp, Smooth.ppp New argument 'kernel' allows the user to specify the smoothing kernel. o density.ppp, Smooth.ppp Argument 'weights' can now be a pixel image. o MinkowskiSum, %(+)% Now accepts arguments which are point patterns or line segment patterns as well as windows. o plot.im New argument 'workaround' to avoid a bug in some device drivers that causes the image to be displayed in the wrong spatial orientation. [Thanks to Marcel Austenfeld for drawing attention to this.] o sumouter New argument 'y' allows computation of asymmetric outer products. o linearKinhom, linearpcfinhom New argument 'normpower'. o rmh.default, rmh.ppm New arguments 'nsim', 'saveinfo'. o symbolmap, plot.ppp, plot.lpp New option: shape="arrows" o rcellnumber New argument 'mu'. o lengths.psp New argument 'squared'. o plot.linfun Now passes arguments to the function being plotted. o as.linnet.psp If the line segment pattern has marks, then the resulting linear network also carries these marks in the $lines component. o summary.owin, summary.im The fraction of frame area that is occupied by the window/image is now reported. o density.ppp, Smooth.ppp Computation accelerated by about 15% in the case where at='points' and kernel='gaussian'. o linearK, linearpcf Accelerated by about 40%. o pixellate.ppp Accelerated in the case where weights are given o density.ppp Accelerated in the cases where weights are given or 'diggle=TRUE' o dilation.ppp Improved geometrical accuracy. Now accepts arguments to control resolution of polygonal approximation. o discs New argument 'npoly'. Accelerated in some cases. o plot.pp3 New arguments 'box.front', 'box.back' control plotting of the box. o grow.rectangle New argument 'fraction'. o nnfun.lpp New argument 'k'. o bw.ppl New argument 'sigma'. o lppm New argument 'random' controls placement of dummy points. o rhohat.lpp New argument 'random' controls placement of dummy points. o quadrat.test.ppm Accelerated in the case where the original window is a rectangle. o kppm, mincontrast, cauchy.estpcf, lgcp.estpcf, matclust.estpcf, thomas.estpcf, vargamma.estpcf A warning about infinite values of the summary function no longer occurs when the default settings are used. o circumradius This function is now deprecated, in favour of 'boundingradius' o print.quad More information is printed. BUG FIXES o linearK, linearpcf, and relatives: These functions were sometimes greatly underestimated when the network had segments shorter than 10 coordinate units. [Bug introduced in spatstat 1.44-0, december 2015.] Fixed. o integral.linim, integral.linfun Results were slightly inaccurate because of a bias in the distribution of sample points. [Bug introduced in spatstat 1.41-0, february 2015.] Fixed. o intensity.ppm Result was incorrect for Gibbs models if the model was *exactly* equivalent to a Poisson process (i.e. if all interaction coefficients were exactly zero). [Bug introduced in spatstat 1.28-1, june 2012.] Fixed. o rSSI Sometimes terminated prematurely. [Spotted by Frederico Mestre.] Fixed. o perspPoints Crashed if the image Z contained NA (i.e. if Z was only defined on a subset of the bounding frame). Spotted by Guy Bayegnak. Fixed. o plot.ppp, plot.lpp Crashed if the argument 'shape' was given. Fixed. o plot.kppm Crashed if the model was not fitted by minimum contrast. Fixed. o superimpose Crashed if the argument was a 'solist' containing line segment patterns. Fixed. o Jest Crashed sometimes, depending on the shape of the observation window. [Spotted by Cenk Icos.] Fixed. o plot.studpermutest Crashed when the summary statistic was a multitype pair correlation function or multitype K function. [Spotted by Sven Wagner.] Fixed. o pool.anylist Crashed with a message about buffer size, if the list was longer than about 100 items. Fixed. o diagnose.ppm, plot.diagppm Crashed in some cases when cumulative=FALSE. Fixed. o leverage.ppm, influence.ppm, dfbetas.ppm Crashed sometimes with a message about wrong replacement length. [Spotted by Virginia Morera Pujol.] Fixed. o as.linnet.psp Crashed with marked segment patterns, if any segments were very short. [Spotted by Suman Rakshit.] Fixed. o stieltjes Returned NA if some values of f were not finite. Fixed. o plot.symbolmap If a new plot window was initialised, it was sometimes too small to contain the geometric figures (circles, squares etc) in the symbol map. Fixed. o plot.ppp, plot.im Ignored xlim, ylim. Fixed. o rhohat.lpp Ignored nd, eps. Fixed. o nnfun.lpp Print method gave incorrect information about the point pattern. Fixed. o "[.fv" The default plot formula was not updated. Fixed. o fitted.ppm The result was sometimes a 1-dimensional array rather than a numeric vector. Fixed. CHANGES IN spatstat VERSION 1.46-1 OVERVIEW o Important bug fix. o Version nickname: 'Spoiler Alert' BUG FIXES o density.ppp, Smooth.ppp The results of density(X, at="points") and Smooth(X, at="points") were incorrect in some cases. The contribution from the left-most data point (the point with the smallest x coordinate) was omitted. [Bug introduced in spatstat 1.26-0, April 2012.] Fixed. CHANGES IN spatstat VERSION 1.46-0 OVERVIEW o We thank Corey Anderson and Sebastian Meyer for contributions. o spatstat now depends on R 3.3.0 or later. o Improvements to inhomogeneous multitype K and L functions. o Variance approximation for pair correlation function. o Leverage and influence for multitype point process models. o Functions for extracting components of vector-valued objects. o Important bug fix in Smooth.ppp o Minor improvements and bug fixes. o Version nickname: 'Multidimensional Toothbrush' NEW FUNCTIONS o split.msr Decompose a measure into parts. o unstack.msr Decompose a vector-valued measure into its component measures. o unstack.ppp, unstack.psp, unstack.lpp Given a spatial pattern with several columns of marks, separate the columns and return a list of spatial patterns, each having only one column of marks. o kernel.squint Integral of squared kernel, for the kernels used in density estimation. SIGNIFICANT USER-VISIBLE CHANGES o Kcross.inhom, Kdot.inhom, Kmulti.inhom, Ldot.inhom, Lcross.inhom These functions now allow intensity values to be given by a fitted point process model. New arguments 'update', 'leaveoneout', 'lambdaX'. o diagnose.ppm Infinite values of 'rbord' are now ignored and treated as zero. This ensures that diagnose.ppm has a sensible default when the fitted model has infinite reach. o pcf.ppp Now calculates an analytic approximation to the variance of the estimate of the pair correlation function (when var.approx=TRUE). Now returns the smoothing bandwidth used, as an attribute of the result. o plot.ppp When 'clipwin' is given, any parts of the boundary of the window of x that lie inside 'clipwin' will also be plotted. o plot.msr Now handles multitype measures. New argument 'multiplot'. o plot.anylist If a list entry x[[i]] belongs to class 'anylist', it will be expanded so that each entry x[[i]][[j]] will be plotted as a separate panel. o influence.ppm, leverage.ppm These can now be applied to multitype point process models and the results can be plotted. o plot.influence.ppm, plot.leverage.ppm New argument 'multiplot'. o plot.anylist, plot.solist, plot.listof New arguments panel.begin.args, panel.end.args o influence.ppm, leverage.ppm, dfbetas.ppm For Gibbs models, memory usage has been dramatically reduced, so the code can handle larger datasets and finer quadrature schemes. BUG FIXES o Smooth.ppp Results were incorrect when at='points' and leaveoneout=FALSE. [Bug introduced in spatstat 1.20-5, October 2010.] Fixed. o funxy Did not correctly handle one-line functions: the resulting objects evaluated the wrong function in some cases. [Spotted by Sebastian Meyer. Bug introduced in spatstat 1.45-0] Fixed. o mppm Did not recognise the variable 'marks' in a formula. Fixed. o Smooth.ppp, bw.smoothppp Crashed if X had two columns of marks and one column was constant. [Bug introduced in spatstat 1.38-0, October 2014] Fixed. o Smooth.ppp Results for 'at="points"' were garbled, for some values of 'sigma', if X had more than one column of marks. [Bug introduced in spatstat 1.38-0, October 2014] Fixed. o plot.layered Crashed if one layer was a point pattern with several columns of marks. Fixed. o plot.ppm Sometimes gave a spurious warning about a singular matrix. Fixed. o setminus.owin Gave wrong or strange answer if the correct answer was empty. Fixed. o parameters.dppm Crashed, due to a typo. Fixed. o progressreport Crashed if n = 1. Fixed. CHANGES IN spatstat VERSION 1.45-2 OVERVIEW o We thank Ottmar Cronie, Virginia Morera Pujol, Sven Wagner and Marie-Colette van Lieshout for contributions. o Recursive-partition point process models. o Minkowski sum, morphological dilation and erosion with any shape. o Important bug fix in spatial CDF tests. o More bug fixes for replicated patterns. o Simulate a model fitted to replicated point patterns. o Inhomogeneous multitype F and G functions. o Summary functions recognise correction="all" o Leverage and influence code handles bigger datasets. o More support for pixel images. o Improved progress reports. o New dataset 'redwood3' o spatstat now Depends on the package 'rpart' o Version nickname: 'Caretaker Mode' NEW DATASETS o redwood3 A more accurate version of the 'redwood' data. NEW FUNCTIONS o as.im.data.frame Build a pixel image from a data frame of coordinates and pixel values. o covering Cover a window using discs of a given radius. o dilationAny, erosionAny, %(-)% Morphological dilation and erosion by any shape. o FmultiInhom, GmultiInhom Inhomogeneous multitype/marked versions of the summary functions Fest, Gest. o kernel.moment Moment or incomplete moment of smoothing kernel. o MinkowskiSum, %(+)% Minkowski sum of two windows: A %(+)% B, or MinkowskiSum(A,B) o nobjects New generic function for counting the number of 'things' in a dataset. There are methods for ppp, ppx, psp, tess. o parameters.interact, parameters.fii Extract parameters from interpoint interactions. [These existing functions are now documented.] o ppmInfluence Calculate leverage.ppm, influence.ppm and dfbetas.ppm efficiently. o rppm, plot.rppm, predict.rppm, prune.rppm Recursive-partition point process models o simulate.mppm Simulate a point process model fitted to replicated point patterns. o update.interact Update the parameters of an interpoint interaction. [This existing function is now documented.] o where.max, where.min Find the spatial location(s) where a pixel image achieves its maximum or minimum value. SIGNIFICANT USER-VISIBLE CHANGES o cdf.test.mppm Now handles Gibbs models. Now recognises covariate="x" or "y". o leverage.ppm, influence.ppm, dfbetas.ppm For Gibbs models, memory usage has been dramatically reduced, so the code can handle larger datasets and finer quadrature schemes. o plot.im Now handles complex-valued images. o connected.im Now handles a logical-valued image properly. o qqplot.ppm Argument 'expr' can now be a list of point patterns, or an envelope object containing a list of point patterns. o as.layered Default method now handles a (vanilla) list of spatial objects. o summary functions The argument 'correction="all"' is now recognised: it selects all the available options. This applies to Fest, F3est, Gest, Gcross, Gdot, Gmulti, G3est, Gfox, Gcom, Gres, Hest, Jest, Jmulti, Jcross, Jdot, Jfox, Kest, Kinhom, Kmulti, Kcross, Kdot, Kcom, Kres, Kmulti.inhom, Kcross.inhom, Kdot.inhom, Kscaled, Ksector, Kmark, K3est, Lscaled, markcorr, markcrosscorr, nnorient, pairorient, pcfinhom, pcfcross.inhom, pcfcross, pcf, Tstat. o clarkevans The argument 'correction="all"' is now recognised: it selects all the available options. [This is also the default.] o predict.mppm The argument 'type="all"' is now recognised: it selects all the available options. [This is also the default.] o plot.kppm The argument 'what="all"' is now recognised: it selects all the available options. [This is also the default.] o connected.im, connected.owin Arguments '...' now determine pixel resolution. o anova.mppm New argument 'fine' o as.owin.data.frame New argument 'step' o discs Now accepts a single numeric value for 'radii'. o plot.ppp, plot.profilepl, plot.quadratcount, plot.quadrattest, plot.tess Now recognise graphics parameters for text, such as 'family' and 'srt' o as.function.tess New argument 'values' specifies the function values. o cdf.test Calculations are more robust against numerical rounding effects. o progressreport Behaviour improved. New arguments 'tick', 'showtime'. o simulate.ppm New argument 'verbose' o compileK, compilepcf These internal functions are now documented. BUG FIXES o cdf.test.ppm Calculation of p-values was incorrect for Gibbs models: 1-p was computed instead of p. [Spotted by Sven Wagner.] Fixed. o subfits The interaction coefficients of the submodels were incorrect for Gibbs models with a multitype interaction (MultiStrauss, etc). [Spotted by Sven Wagner.] Fixed. o subfits Crashed when a Gibbs model included factor-valued spatial covariates and not all levels of the factor were present in each row of the data. [Spotted by Sven Wagner.] Fixed. o subfits For Gibbs models with a multitype interaction (MultiStrauss, etc), computation of the conditional intensity caused an error. [Spotted by Sven Wagner.] Fixed. o diagnose.ppm Crashed if what="smooth", when the original window was a rectangle. [Spotted by Virginia Morera Pujol.] Fixed. o mppm The x and y coordinates were not permitted in the random-effects formula 'random'. [Spotted by Sven Wagner.] Fixed. o vcov.ppm The result had no 'dimnames', if the model was fitted using method="ho". Fixed. CHANGES IN spatstat VERSION 1.45-1 OVERVIEW o This version was never released. CHANGES IN spatstat VERSION 1.45-0 OVERVIEW o We thank Monsuru Adepeju, Mario D'Antuono, Markus Herrmann, Paul Hewson, Kassel Hingee, Greg McSwiggan, Suman Rakshit and Sven Wagner for contributions. o Important bug fix in leverage/influence diagnostics for Gibbs models. o Numerous bug fixes in code for replicated point patterns. o Surgery on linear networks. o Tessellations on a linear network. o Laslett's Transform. o Colour maps for point patterns with continuous marks are easier to define. o Pair correlation function estimates can be pooled. o Stipulate a particular version of a package. o Fixed namespace problems arising when spatstat is not loaded. o Bug fixes and performance improvements. o spatstat now contains 100,000 lines of R code. o Version nickname: 'One Lakh' NEW FUNCTIONS o laslett Laslett's Transform. [Thanks to Kassel Hingee] o lintess Tessellation on a linear network. o divide.linnet Divide a linear network into pieces demarcated by a point pattern. o insertVertices Insert new vertices in a linear network. o thinNetwork Remove vertices and/or segments from a linear network etc o connected.linnet Find connected components of a linear network. o nvertices, nvertices.linnet, nvertices.owin Count the number of vertices in a linear network or vertices of the boundary of a window. o as.data.frame.linim, as.data.frame.linfun Extract a data frame of spatial locations and function values from an object of class 'linim' or 'linfun'. o as.linfun, as.linfun.linim, as.linfun.lintess Convert other kinds of data to a 'linfun' object. o requireversion Require a particular version of a package (for use in stand-alone R scripts). SIGNIFICANT USER-VISIBLE CHANGES o [.linnet, [.lpp New argument 'snip' determines what to do with segments of the network that cross the boundary of the window. Default behaviour has changed. o pcfinhom Default behaviour is changed when 'lambda' is a fitted model. The default is now to re-fit the model to the data before computing pcf. New arguments 'update' and 'leaveoneout' control this. o envelope methods New argument 'funYargs' contains arguments to the summary function when applied to the data pattern only. o plot.ppp, plot.lpp For a point pattern with continuous marks ('real numbers') the colour arguments 'cols', 'fg', 'bg' can now be vectors of colour values, and will be used to determine the default colour map for the marks. o symbolmap Now accepts a vector of colour values for the arguments 'col', 'cols', 'fg', 'bg' if argument 'range' is given. o closepairs.ppp, closepairs.pp3 New arguments 'distinct' and 'neat' allow more options. o closepairs.ppp, closepairs.pp3 Argument 'ordered' has been replaced by 'twice' (but 'ordered' is still accepted, with a warning). o closepairs.ppp, closepairs.pp3 Performance improved (computation time and memory requirements reduced.) This should improve the performance of many functions in spatstat. o Geyer The saturation parameter 'sat' can now be less than 1. o lpp, as.lpp These functions now handle the case where 'seg' and 'tp' are given but 'x' and 'y' are missing. o linnet If the argument 'edges' is given, then this argument now determines the ordering of the sequence of line segments. For example, the i-th row of 'edges' specifies the i-th line segment in as.psp(L). o funxy, distfun The functions created by funxy and distfun have arguments (x,y). The user may now give a ppp or lpp object for the argument 'x', instead of giving two coordinate vectors 'x' and 'y'. o crossing.psp New argument 'details' gives more information about the intersections between the segments. o subset.ppp, subset.lpp, subset.pp3, subset.ppx The argument 'subset' can now be any argument acceptable to the "[" method. o density.lpp New argument 'weights'. o pcf.ppp New argument 'ratio' allows several estimates of pcf to be pooled. o summary.ppm New argument 'fine' selects the algorithm for variance estimation. o texturemap Argument 'textures' can be missing or NULL. o plot.lpp New argument 'show.network' o linnet New argument 'warn' o mppm Performs more checks for consistency of the input data. o mppm New arguments 'gcontrol' and 'reltol.pql' control the fitting algorithm. o edge.Trans New argument 'gW' for efficiency. o pool.fv The default plot of the pooled function no longer includes the variance curves. o clickpoly The polygon is now drawn progressively as the user clicks new vertices. o Kest Accelerated computation (for translation and rigid corrections) when window is an irregular shape. o vcov.ppm, leverage.ppm, influence.ppm, dfbetas.ppm Performance slightly improved, for Gibbs models. o Internal code Performance slightly improved. o Fest, Hest Additional checks for errors in input data. BUGS o leverage.ppm, influence.ppm, parres.ppm, addvar.ppm Calculations were completely incorrect for Gibbs models, due to a coding error. Fixed. o update.kppm If the call to 'update' did not include a formula argument or a point pattern argument, then all arguments were ignored. Example: update(fit, improve.type="quasi") was identical to 'fit'. Fixed. o diagnose.ppm When applied to a model obtained from subfits(), in the default case (oldstyle=FALSE) the variance calculations were incorrect. Consequently the dotted lines representing significance bands were incorrect. An error or warning about negative variances occurred sometimes. However, calculations with oldstyle=TRUE were correct. The default has now been changed to oldstyle=TRUE for such models. o [.lpp The local coordinate 'seg' was completely incorrect, when 'i' was a window. Fixed. o leverage.ppm, influence.ppm, parres.ppm, addvar.ppm Crashed for Gibbs models in which the coefficient vector had length 1, such as the stationary Hardcore model. Fixed. o subfits Crashed if the model included factor-valued spatial covariates. [Spotted by Sven Wagner] Fixed. o subfits If the model included factor-valued spatial covariates, and if not all levels of the factor were present in each row of the data, the resulting objects were malformed and caused errors in other code. [Spotted by Sven Wagner] Fixed. o subfits Crashed with some random-effects formulas. [Spotted by Sven Wagner] Fixed. o improve.kppm An error message about a missing object 'gminus1' occurred when vcov=TRUE, fast.vcov=FALSE and type="clik1" or "wclik1". Fixed. o plot.profilepl Failed with a message about a missing object 'finite'. Fixed. o selfcut.psp Gave an error if marks(A) was a vector rather than a data frame. [Spotted by Paul Hewson.] Fixed. o suffstat Gave an error for point process models with Geyer interaction. Fixed. o nncross.lpp, distfun.lpp Crashed with obscure errors if Y consisted of a single point. Fixed. o scan.test, scanmeasure Crashed sometimes with an error message from 'grow.mask'. Fixed. o dppm Crashed sometimes with a message that the point pattern could not be found. [Scoping bug.] Fixed. o mppm, profilepl Crashed, with a message about 'SpatstatVersion', if the 'spatstat' package was neither loaded nor attached. [Spotted by Markus Herrmann.] Fixed. o qqplot.ppm Crashed sometimes when applied to a model obtained from subfits(). Fixed. o anova.mppm Crashed sometimes with a message about mismatched coefficients. [Spotted by Sven Wagner.] Fixed. o anova.mppm Crashed sometimes with a message about unrecognised option 'type="score"'. [Spotted by Sven Wagner.] Fixed. o split.ppx Crashed if 'f' was not a factor. Fixed. o idw The result was a pixel image defined in the rectangle Frame(X) instead of Window(X). Fixed. o ppm Parameter estimates were slightly inaccurate when the model included the Geyer() interaction and the "isotropic" edge correction was used. Fixed. o [.ppx Crashed if the number of points selected was less than 2. Fixed. o linnet Crashed if there were no line segments at all. Fixed. o kppm, improve.kppm Crashed if the model was stationary and improve.type != "none". Fixed. o as.linim.default Did not correctly handle factor-valued data. Fixed. o texturemap Crashed if no graphical arguments were specified. Fixed. o vcov.mppm Ignored "..." arguments. Fixed. o Kest If ratio=TRUE and correction=c('border', 'none') the result did not contain ratio information. Fixed. o plot.ppp, plot.lpp Arguments 'chars' and 'cols' were ignored in some cases. Fixed. o ppm Ignored argument 'emend'. Fixed. o plot.dppm Gave warnings about unrecognised argument 'objectname'. Fixed. o overlap.owin Sometimes returned a very small negative value, when the correct answer was 0. Fixed. CHANGES IN spatstat VERSION 1.44-1 OVERVIEW o We thank Brian Ripley for contributions. o Urgent bug fix. o More support for replicated point patterns. o More support for tessellations. o Version nickname: 'Gift Horse' NEW FUNCTIONS o as.function.tess Convert a tessellation to a function(x,y). The function value indicates which tile of the tessellation contains the point (x,y). o tileindex Determine which tile of a tessellation contains a given point (x,y). o persp.leverage.ppm Method for persp plots for objects of class leverage.ppm o AIC.mppm, extractAIC.mppm AIC for point process models fitted to replicated point patterns. o nobs.mppm, terms.mppm, getCall.mppm Methods for point process models fitted to replicated point patterns. SIGNIFICANT USER-VISIBLE CHANGES o anova.mppm Now handles Gibbs models, and performs the adjusted composite likelihood ratio test. o update, step These functions now work for models of class 'mppm'. o textureplot Argument x can now be something acceptable to as.im o logLik.mppm New argument 'warn'. BUGS o nncross.lpp, nnwhich.lpp, distfun.lpp Caused a segmentation fault. [Spotted by Brian Ripley.] Fixed. o anova.ppm If a single 'object' was given, and the object was a Gibbs model, then 'adjust' was effectively set to FALSE. Fixed. CHANGES IN spatstat VERSION 1.44-0 OVERVIEW o We thank Jonas Geldmann, Andrew Hardegen, Kassel Hingee, Tom Lawrence, Robin Milne, Gopalan Nair, Suman Rakshit, Peijian Shi and Rasmus Waagepetersen for contributions. o More support for multidimensional point patterns and point processes. o More options for envelopes and related Monte Carlo tests. o More support for model comparison. o k-th nearest neighbours on a linear network. o Penttinen process can be simulated (by Metropolis-Hastings or CFTP). o Calculate the predicted variance of number of points. o Convexifying operation for sets. o Subdivide a linear network. o Accelerated algorithms for linear networks. o Quadrat counting accelerated, in some cases. o Version nickname: 'The Sound of One Hand Typing' NEW FUNCTIONS o rPenttinen Simulate the Penttinen process using perfect simulation. o varcount Given a point process model, compute the predicted variance of the number of points falling in a window. o inside.boxx Test whether multidimensional points lie inside a specified multidimensional box. o lixellate Divide each segment of a linear network into smaller segments. o nsegments.linnet, nsegments.lpp Count the number of line segments in a linear network. o grow.boxx Expand a multidimensional box. o deviance.ppm, deviance.lppm Deviance for a fitted point process model. o pseudoR2 Pseudo-R-squared for a fitted point process model. o tiles.empty Checks whether each tile of a tessellation is empty or nonempty. o summary.linim Summary for a pixel image on a linear network. SIGNIFICANT USER-VISIBLE CHANGES o rMaternI, rMaternII These functions can now generate random patterns in three dimensions and higher dimensions, when the argument 'win' is of class 'box3' or 'boxx'. o "[.ppx" The subset index 'i' may now be a spatial domain of class 'boxx' or 'box3'. o rmh.ppm, rmhmodel.ppm, simulate.ppm A model fitted using the 'Penttinen' interaction can now be simulated. o rmh.default, rmhmodel.default These functions now recognise cif='penttinen' for the Penttinen interaction. o envelope New argument 'clamp' gives greater control over one-sided envelopes. o dclf.test, mad.test, dclf.progress, mad.progress, dclf.sigtrace, mad.sigtrace New argument 'clamp' determines the test statistic for one-sided tests. o dclf.progress, mad.progress, dclf.sigtrace, mad.sigtrace, mctest.progress, mctest.sigtrace, dg.progress, dg.sigtrace New argument 'rmin' determines the left endpoint of the test interval. o dclf.test, mad.test, dg.test, dg.progress, dg.sigtrace, dg.envelope (also accepted by dclf.progress, mad.progress, dclf.sigtrace, mad.sigtrace) New argument 'leaveout' specifies how to calculate the deviation between the observed summary function and nominal reference value. o envelope New argument 'funargs' o Hest Argument X can now be a pixel image with logical values. New argument 'W'. [Based on code by Kassel Hingee.] o nncross.lpp, distfun.lpp New argument 'k' allows calculation of k-th nearest neighbour. Computation accelerated. o logLik.ppm New argument 'absolute'. o plot.kppm New arguments 'pause' and 'xname'. o tess Argument 'window' is ignored when xgrid, ygrid are given. o as.polygonal Can now repair errors in polygon data, if repair=TRUE. o rStrauss, rHardcore, rStraussHard, rDiggleGratton, rDGS, rPenttinen New argument 'drop'. o Kest.fft Now has '...' arguments allowing control of spatial resolution. o lppm Computation accelerated. o quadratcount.ppp Computation accelerated in some cases. o dg.test Computation accelerated. BUGS o runifpointx, rpoisppx Crashed if nsim > 1. Fixed. o triangulate.owin Results were incorrect in some special cases. Fixed. o quadrat.test, clarkevans.test In rare cases, the computed Monte Carlo p-value could have been greater than 1. This could have occurred only when nsim was an even number and when the correct p-value was equal to 1. Fixed. o linearmarkequal Result was a data frame instead of an 'fv' object. Fixed. o point-in-polygon test The function inside.owin could take a very long time to check whether points are inside a polygonal window, if the coordinates were very large numbers. This was due to numerical overflow. (Fixed??) o as.fv.kppm Crashed if the model was not fitted by minimum contrast. Fixed. o plot.fv Crashed in some obscure cases. Fixed. o collapse.fv Did not allow 'same=NULL'. Fixed. o dclf.progress, mad.progress, dg.progress, dclf.sigtrace, mad.sigtrace, dg.sigtrace The results could not be re-plotted using a plot formula, because the internal data were slightly corrupted. Fixed. o Kest.fft Result was incorrectly normalised. Fixed. o crosspairs If X and Y were identical point patterns, the result was not necessarily symmetric (on some machines) due to numerical artifacts. Fixed. o plot.fv Lines were not correctly clipped to the plot region when 'ylim' was given. Fixed. o pool.envelope The 'scale' argument was not handled correctly. Fixed. CHANGES IN spatstat VERSION 1.43-0 OVERVIEW o We thank Leanne Bischof, Christophe Biscio, Belarmain Fandohan, Andrew Hardegen, Frederic Lavancier, Tom Lawrence, Martin Maechler, Greg McSwiggan, Robin Milne, Gopalan Nair, Tuomas Rajala, Suman Rakshit, Ben Ramage, Francois Semecurbe and Ida-Maria Sintorn for contributions. o spatstat now depends on the package 'nlme'. o spatstat now depends on R 3.2.2 or later. o Simulation algorithms have been accelerated; simulation outcomes are *not* identical to those obtained from previous versions of spatstat. o Determinantal point process models. o Random-effects and mixed-effects models for replicated patterns. o Dao-Genton test, and corresponding simulation envelopes. o Simulated annealing and simulated tempering. o spatstat colour tools now handle transparent colours. o Improvements to "[" and subset() methods o Extensions to kernel smoothing on a linear network. o Support for one-dimensional smoothing kernels. o Bug fix in Metropolis-Hastings simulation. o Mark correlation function may include weights. o Cross-correlation version of the mark correlation function. o Variance calculations for replicated patterns. o Penttinen pairwise interaction model. o Contour plots with colours determined by a colour map. o New dataset: Australian states and territories. o More support for multi-dimensional point patterns. o Minor improvements and bug fixes. o Version nickname: "Mixed Effects" NEW DATASET o austates The states and large mainland territories of Australia represented as polygonal regions forming a tessellation. NEW FUNCTIONS o dppm Fit a determinantal point process model to point pattern data. o fitted.dppm, predict.dppm, intensity.dppm Predict a fitted dppm object. o logLik.dppm, AIC.dppm, extractAIC.dppm, nobs.dppm Likelihood and AIC for determinantal point process models (enabling the use of 'step') o coef.dppm, formula.dppm, print.dppm, terms.dppm, labels.dppm, model.frame.dppm, model.matrix.dppm, model.images.dppm, is.stationary.dppm, reach.dppm, unitname.dppm, unitname<-.dppm, Window.dppm Various methods for dppm objects. o parameters.dppm Extract meaningful list of model parameters o objsurf.dppm Objective function surface of a dppm object o residuals.dppm Residual measure for a dppm object. o dppBessel, dppCauchy, dppGauss, dppMatern, dppPowerExp Determinantal Point Process models. o update.dppmodel Set parameter values in a dpp model. o is.stationary.dppmodel, print.dppmodel, reach.dppmodel, valid.dppmodel Basic information about a dpp model o rdpp, simulate.dppmodel Simulation of a dpp model. o intensity.dppmodel, Kmodel.dppmodel, pcfmodel.dppmodel Moments of a dpp model o dim.dppmodel, dppapproxkernel, dppapproxpcf, dppeigen, dppfamily, dppkernel, dppparbounds, dppspecdenrange, dppspecden Helper functions for dpp models. o dclf.sigtrace, mad.sigtrace, mctest.sigtrace Significance trace of Monte Carlo test o dg.test Dao-Genton adjusted Monte Carlo goodness-of-fit test. o dg.envelope Simulation envelopes corresponding to Dao-Genton test. o dg.sigtrace Significance trace for Dao-Genton test o dg.progress Progress plot for Dao-Genton test o markcrosscorr Mark cross-correlation function for point patterns with several columns of marks o fixef.mppm, ranef.mppm Extract fixed effects and random effects from a point process model fitted to replicated point patterns. o rtemper Simulated annealing or simulated tempering. o to.opaque, to.transparent Change transparency value in colours o rgb2hsva Convert RGB to HSV data, like rgb2hsv, but preserving transparency. o superimpose.ppplist, superimpose.splitppp New methods for 'superimpose' for lists of point patterns. o dkernel, pkernel, qkernel, rkernel Probability density, cumulative probability, quantiles and random generation from distributions used in basic one-dimensional kernel smoothing. o kernel.factor Auxiliary calculations for one-dimensional kernel smoothing. o PPversion, QQversion Transformation of a summary function to its P-P or Q-Q counterpart. o spatdim Spatial dimension of any object in the spatstat package. o as.boxx Convert data to a multi-dimensional box. o intensity.ppx Method for 'intensity' for multi-dimensional space-time point patterns. o fourierbasis Evaluate Fourier basis functions in any number of dimensions. o valid New generic function, with methods valid.ppm, valid.lppm, valid.dppmodel o emend, emend.ppm, emend.lppm New generic function with methods for ppm and lppm. emend.ppm is equivalent to project.ppm o Penttinen New pairwise interaction model. o quantile.density Calculates quantiles from kernel density estimates. o CDF.density Calculates cumulative distribution function from kernel density estimates. SIGNIFICANT USER-VISIBLE CHANGES o simulation Several basic simulation algorithms have been accelerated. Consequently, simulation outcomes are not identical to those obtained with previous versions of spatstat, even when the same random seed is used. To ensure compatibility with previous versions of spatstat, revert to the slower code by setting spatstat.options(fastthin=FALSE, fastpois=FALSE). o mppm Now handles models with a random effect component. New argument 'random' is a formula specifying the random effect. o vcov.mppm Now handles models with Gibbs interactions. o [.ppp New argument 'clip' determines whether the window is clipped. o [.ppp The previously-unused argument 'drop' now determines whether to remove unused levels of a factor. o [.pp3, [.lpp, [.ppx, subset.ppp, subset.pp3, subset.lpp, subset.ppx These methods now have an argument 'drop' which determines whether to remove unused levels of a factor. o density.lpp Now supports both the 'equal-split continuous' and 'equal-split discontinuous' smoothers. New argument 'continuous' determines the choice of smoother. o envelope New argument 'scale' allows global envelopes to have width proportional to a specified function of r, rather than constant width. o dclf.test, mad.test, dclf.progress, mad.progress, mctest.progress New argument 'scale' allows summary function values to be rescaled before the comparison is performed. o dclf.test, mad.test New argument 'interpolate' supports interpolation of p-value. o dclf.progress, mad.progress, mctest.progress New argument 'interpolate' supports interpolation of critical value of test. o simulate.ppm New argument 'w' controls the window of the simulated patterns. o default.rmhcontrol, default.rmhexpand New argument 'w'. o markcorr New argument 'weights' allows computation of the weighted version of the mark correlation function. o density.lpp New argument 'kernel' specifies the smoothing kernel. Any of the standard one-dimensional smoothing kernels can be used. o contour.im New argument 'col' specifies the colour of the contour lines. If 'col' is a colour map, then the contours are drawn in different colours. o plot.ppp The default colour for the points is now a transparent grey, if this is supported by the plot device. o rgbim, hsvim New argument 'A' controls the alpha (transparency) channel. o rgb2hex, col2hex, paletteindex, is.colour, samecolour, complementarycolour, is.grey, to.grey These colour tools now handle transparent colours. o rgb2hex New argument 'maxColorValue' o to.grey New argument 'transparent'. o progressreport New argument 'state' New option: style="tk" o rLGCP This function no longer requires the package 'RandomFields' to be loaded explicitly. o kppm Fitting a model with clusters="LGCP" no longer requires the package 'RandomFields' to be loaded explicitly. o rpoispp Accelerated, when 'lambda' is a pixel image. o rthin Accelerated, when 'P' is a single number. o spatstat.options New options 'fastthin' and 'fastpois' enable fast simulation algorithms. Set these options to FALSE to reproduce results obtained with previous versions of spatstat. o split.ppp The splitting variable 'f' can now be a logical vector. o collapse.fv This is now treated as a method for the 'nlme' generic 'collapse'. Its syntax has been adjusted slightly. o diagnose.ppm, plot.diagppm New arguments col.neg, col.smooth control the colour maps. o valid.ppm This is now a method for the generic function 'valid'. o ppm.ppp, ppm.quad New argument 'emend', equivalent to 'project'. o "[<-.im" Accepts an array for 'value'. o as.im.function New argument 'strict'. o bw.ppl New argument 'weights'. o plot.mppm New argument 'se'. o dclf.test, mad.test Formal arguments 'use.theo' and 'internal' have been removed. o predict.kppm, residuals.kppm Now issues a warning when the calculation ignores the cluster/Cox component and treats the model as if it were Poisson. (This currently happens in predict.kppm when se=TRUE or interval != "none", and in residuals.kppm when type != "raw"). BUG FIXES o lpp Crashed if X was a 4-column matrix. Fixed. o plot.fv Crashed with some graphics devices, if legend=TRUE. Fixed. o effectfun Crashed if 'covname' was missing. Fixed. o rVarGamma, rMatClust, rThomas, rCauchy, rNeymanScott Crashed if 'kappa' was a function or image instead of a single number. [Spotted by Ben Ramage.] Fixed. o plot.mppm Crashed with a message about "figure margins too large" unless the argument se=FALSE was given explicitly. Fixed. o opening.owin, closing.owin Crashed sometimes, with a message about a rectangle not containing a window. Fixed. o persp.im Crashed if all pixel values were equal to zero (unless zlim was given). Fixed. o predict.ppm Crashed sometimes if the model was fitted with use.gam=TRUE. o as.linim.linfun Generated an error ('L must be a linear network') if extra arguments were given. o as.function.fv Generated an error when executed in the 'covr' package. Fixed. o rmh, simulate.ppm Results were incorrect for inhomogeneous multitype models simulated with fixall=TRUE (i.e. prescribing a fixed number of points of each type) if the model was segregated (i.e. if different types of points had different first order trend). Fixed. o dclf.progress, mad.progress Ignored the argument 'alternative'. Fixed. o $<-.hyperframe, [<-.hyperframe Result was garbled if 'value' was a hyperframe with one column. o rmh.ppm Argument 'w' was ignored in some cases. Fixed. o Hest There was an artefact at r=0 when conditional=TRUE. Fixed. o [.msr The result of M[W] where W is a window was a measure with window W, instead of intersect.owin(W, Window(M)). Fixed. o pool.envelope Did not always respect the value of 'use.theory'. Fixed. o envelope, pool.envelope If 'ginterval' was given, the results were in a slightly incorrect format. Fixed. o pool.envelope Did not check for compatible values of 'ginterval'. Fixed. CHANGES IN spatstat VERSION 1.42-2 OVERVIEW o We thank Bob Klaver and Harold-Jeffrey Ship for contributions. o Improvements to simulation of Neyman-Scott processes. o Improvements to fitting of Neyman-Scott models. o Extended functionality for pixel images. o Fitted intensity on linear network o Triangulation of windows. o Corrected an edge correction. o Bug fixes and performance improvements. o Nickname: 'Barking at Balloons' NEW FUNCTIONS o triangulate.owin Decompose a spatial window into triangles. o fitted.lppm Fitted intensity values for a point process on a linear network. SIGNIFICANT USER-VISIBLE CHANGES o rThomas, rMatClust, rCauchy, rVarGamma When the model is approximately Poisson, it is simulated using rpoispp. This avoids computations which would require huge amounts of memory. New argument 'poisthresh' controls this behaviour. o update.kppm Now handles additional arguments in any order, with or without names. Changed arguments. Improved behaviour. o kppm, clusterfit New argument 'algorithm' specifies the choice of optimisation algorithm. o kppm Left hand side of formula can now involve entries in the list 'data'. o rotmean New argument 'padzero'. Default behaviour has changed. o rose.default New argument 'weights'. o rose New arguments 'start' and 'clockwise' specify the convention for measuring and plotting angles. o padimage New argument 'W' allows an image to be padded out to fill any window. o union.owin Improved behaviour when there are more than 2 windows. o clusterset Improved behaviour. o affine.owin Allows transformation matrix to be singular, if the window is polygonal. BUG FIXES o spatstat spatstat could not be installed on some 64-bit VM systems because of an apparent bug in R. Fixed. o rThomas, rMatClust, rCauchy, rVarGamma Large values of the scale parameter could cause the algorithm to freeze or require huge amounts of memory. Fixed. o pcf, pcfinhom Crashed if the point pattern was empty. Fixed. o plot.fv Gave an error message if all 'y' values were equal, when legend=TRUE. Fixed. o rose.default Display was incorrect when unit="radian". Fixed. o Kest Ohser-Stoyan rigid motion correction (correction='rigid') was calculated incorrectly at large distances. Fixed. o summary.im Issued a warning about numerical overflow in some cases. [Spotted by Bob Klaver.] Fixed. o plot.im Sometimes warned that 'box' is not a graphical parameter. Fixed. CHANGES IN spatstat VERSION 1.42-1 OVERVIEW o We thank Andrew Hardegen, Tom Lawrence, Robin Milne, Suman Rakshit, and Brian Ripley for contributions. o Urgent bug fix. o More robust simulation of cluster processes. o Slightly accelerated. o Version nickname: 'Vogon Poetry' NEW FUNCTIONS o boundingbox.solist Method for boundingbox for lists of spatial objects. SIGNIFICANT USER-VISIBLE CHANGES o rThomas, rMatClust, rCauchy, rVarGamma, rNeymanScott New faster algorithm which is more robust against extreme values of the parameters. o rNeymanScott New argument 'nonempty' controls choice of algorithm. o solist, as.solist Accelerated. o as.list.hyperframe Accelerated. BUG FIXES o residuals.mppm Brought some computers to a grinding halt, due to the bug in solist(). Fixed. o solist, as.solist In rare cases, the format was corrupted, or the algorithm never terminated. Fixed. CHANGES IN spatstat VERSION 1.42-0 OVERVIEW o We thank Anders Bilgrau, Ute Hahn, Jack Hywood, Tuomas Rajala, Cody Schank, Olivia Semboli and Ben Taylor for contributions. o Version nickname: 'Life, The Universe and Everything' o Permutation test for difference between groups of point patterns. o Variational Bayes estimation for point process models. o Score test in anova.ppm o ROC curve, and discrimination index AUC, for fitted models. o Interactive text editor for spatial datasets. o Tools for analysing data on a tree. o Kernel density/intensity estimation on a linear network. o Random pixel noise. o Improved behaviour of polygon geometry operations. o Improved support for cluster and Cox models. o Improved basic support for owin objects. o Improved support for tessellations. o More hierarchical Gibbs interactions. o Modifications to Kest. o summary method for Cox and cluster models. o class 'listof' is almost completely replaced by 'anylist' and 'solist'. o Improvements and bug fixes. o spatstat now depends on R version 3.2.0 or later. NEW FUNCTIONS o studpermu.test Studentised permutation test for difference between groups of point patterns. Generously contributed by Ute Hahn. o AIC.kppm, extractAIC.kppm, logLik.kppm, nobs.kppm Methods for computing AIC for fitted Cox and cluster models. o transmat Convert pixel arrays between different display conventions. o roc Receiver Operating Characteristic curve. o auc Discrimination index AUC (area under the ROC curve) o edit.ppp, edit.psp, edit.im Interactive text editor works for spatial datasets. o edit.hyperframe Interactive text editor works for hyperframes. o parameters Extract all parameters from a fitted model. o density.lpp Kernel estimation of point process intensity on a linear network. o extractbranch, deletebranch, treeprune, treebranchlabels, begins Tools for analysing data on a tree. o rnoise Random pixel noise. o as.data.frame.owin Convert a window to a data frame. o harmonise.owin Convert several binary mask windows to a common pixel grid. o copyExampleFiles Copy the raw data files from an installed dataset to a chosen folder, for use in a practice exercise. o density.ppplist Method for 'density' for lists of point patterns. o inradius Radius of largest circle inside a window. o mergeLevels Merge different levels of a factor. o relevel.im, relevel.ppp, relevel.ppx Change the reference level of a factor. o simulate.profilepl simulation method for models fitted by profile maximum pseudolikelihood. o predict.rho2hat Prediction method for class rho2hat o with.msr Evaluate (an expression involving) components of a measure. o summary.kppm, print.summary.kppm, coef.summary.kppm Methods for 'summary' and 'coef(summary(..))' for Cox and cluster models. o as.im.funxy Method for as.im for class funxy. o shift.linim, scalardilate.linim, affine.linim Geometrical transformations for 'linim' objects. o Smooth.solist Smooth method for a list of spatial objects. o unitname.tess, unitname<-.tess Tessellations now keep track of the name of the unit of length. o dirichletAreas Faster algorithm for tile.areas(dirichlet(X)). o identify.lpp Method for 'identify' for point patterns on a linear network. o HierStraussHard, HierHard Hierarchical interactions for Gibbs models. o delaunayDistance, delaunayNetwork, dirichletEdges, dirichletNetwork, dirichletVertices, dirichletWeights These functions will replace delaunay.distance, delaunay.network, dirichlet.edges, dirichlet.network, dirichlet.vertices and dirichlet.weights respectively. The latter are now 'deprecated'. SIGNIFICANT USER-VISIBLE CHANGES o ppm Now supports Variational Bayes fitting method. o kppm 'AIC' and 'step' now work for kppm objects fitted using maximum Palm likelihood. o kppm The default for the weight function 'weightfun' has been changed, for better performance. o envelope envelope methods now have argument 'use.theory' specifying whether to use the 'theoretical' value of the summary function when constructing simultaneous envelopes. o anova.ppm Now performs the Score Test, for Poisson models only, if argument test="Rao" or test="score". o Kest New argument 'rmax' controls maximum value of argument 'r' o diagnose.ppm Now computes and prints the null standard deviation of the smoothed Pearson residual field, when appropriate. o nncorr, nnmean, nnvario New argument 'k' specifies k-th nearest neighbour. o quadrat.test.ppp, quadrat.test.quadratcount New argument 'lambda' supports a test of the Poisson process with given intensity 'lambda'. o clickpoly, clickbox These functions now handle graphical arguments to polygon() when drawing the resulting polygon or rectangle. o owin, as.owin, as.mask owin(mask=D) or as.owin(D) or as.mask(D) will produce a binary mask window if D is a data frame with two columns of (x,y) coordinates or a data frame with three columns containing (x,y,logical). o as.owin.data.frame W can now be a data frame with only two columns, giving the spatial coordinates of the pixels that are inside the window. o rose Tick marks now have labels showing the angle (in degrees or radians). o distcdf New argument 'regularise' determines whether values at short distances will be smoothed to avoid discretisation artefacts. o rpoislinetess Return value now has an attribute 'lines' giving the realisation of the Poisson line process. o intersect.owin, union.owin, setminus.owin New argument 'p' controls resolution of polygon clipping algorithm. o intersect.owin, union.owin Arguments may be lists of windows, of class 'solist'. Formal arguments A and B have been removed. o superimpose Now handles lists of point patterns (objects of class 'ppplist' or 'splitppp') o density.ppp New argument 'positive' allows the user to stipulate that density values must be positive (avoiding numerical errors which occasionally produce small negative values). o adaptive.density Now accepts f = 0 (uniform intensity estimate) and f = 1 (Voronoi intensity estimate) as well as 0 < f < 1. Algorithm accelerated. o rSSI Can now generate inhomogeneous patterns. o effectfun Now works for 'kppm' and 'lppm' objects as well. o integral.im, integral.msr Argument 'domain' can now be a tessellation; the integral over each tile of the tessellation is returned. o allstats, compareFit, markcorr, split.ppx, by.ppp Result is now of class 'anylist'. o by.im, density.splitppp, idw, model.images, nnmark, pixellate.ppp, predict.lppm, predict.ppm, quadratcount.splitppp, quadratresample, relrisk, Smooth.msr, split.im, tiles Result is now of class 'solist'. o split.ppp New argument 'reduce'. Result now inherits class 'ppplist' and 'solist', as well as 'splitppp' o rLGCP New argument 'nsim' allows multiple patterns to be generated. o alltypes New argument 'reuse' determines whether all simulation envelopes are based on the same set of simulated patterns, or on independent sets. o rpoispp, runifpoint New argument 'ex' makes it possible to generate a random pattern similar to an example point pattern. o effectfun Argument 'covname' is not needed if the model has only one covariate. o quadratcount Argument 'tess' can now be anything acceptable to as.tess. o tess New argument 'unitname' specifies the name of the unit of length. If it is missing, unitname information will be extracted from the other data. o intersect.tess, chop.tess, quadrats Results of these functions now have the same 'unitname' as their input. o persp.im, nnclean, plot.qqppm, plot.bw.optim These plotting functions now obey spatstat.options('monochrome') o lurking Now returns an object of class 'lurk' which has a plot method. Two-standard-deviation limits are now plotted using grey shading. o marktable New argument 'N' for studying the N nearest neighbours. New argument 'collapse' for manipulating the contingency table. o harmonise.fv Now discards columns with names which do not match. o eval.fv New argument 'equiv' can be used to declare that two columns with different names in different objects are equivalent. o quantile.ewcdf New argument 'type' controls the type of quantile. o plot.imlist New argument 'plotcommand' specifies how to plot each image. o persp.im The lower extent of the apron can now be controlled by 'zlim'. o quadscheme Argument 'method' is partially matched. o Kdot, Ldot New argument 'from' is an alternative to 'i'. o Kcross, Lcross New arguments 'from' and 'to' are alternatives to 'i' and 'j' respectively. o varblock Changed the ordering (and therefore default colours/styles) of curves in the plot, to match other functions like lohboot. o bw.diggle New argument 'nr' controls accuracy. o textureplot Now accepts a pixel image, a tessellation, or anything acceptable to as.tess. o textureplot Line spacing in legend now matches line spacing in main display. o [.tess Subset index can now be a window. o plot.tess Can now plot a text label in each tile. o plot.tess New argument 'do.plot'. o MultiHard, MultiStrauss, MultiStraussHard, HierStrauss Printed output of fitted model now respects spatstat.options('terse'). o print.ppm Reduced redundancy in output in some cases. o print.msr Responds better to spatstat.options('terse'). o print.ppm, print.fii, print.interact Irregular parameters are now printed to the number of significant figures specified by options("digits"). o square New argument 'unitname'. o plot.fv Return value is now invisible. o delaunay.distance, delaunay.network, dirichlet.edges, dirichlet.network, dirichlet.vertices These functions are now 'deprecated', and will be replaced by delaunayDistance, delaunayNetwork, dirichletEdges, dirichletNetwork and dirichletVertices respectively. o data(residualspaper) In the real datasets (Fig1 and Fig11), the name of the unit of length has now been recorded. o rLGCP This function now requires the package 'RandomFields' to be loaded explicitly by library(RandomFields) or require(RandomFields), unless model="exp". o iplot, istat These functions now require the package 'rpanel' to be loaded explicitly by library(rpanel) or require(rpanel). o ppm, quadscheme Improved calculation of Dirichlet weights. o countends New argument 'toler' controls numerical errors o diagnose.ppm Improved handling of additional graphics arguments. o pcf3est Mathematical labels changed. o plot.hyperframe Default margin spacing has been increased. BUG FIXES o Kinhom, Linhom The value of 'theo' was erroneously rescaled by a small amount, when renormalise=TRUE (the default). Fixed. o Kmark Values were erroneously rescaled. Fixed. o union.owin Strange results were sometimes obtained when taking the union of more than two windows. Fixed. o rpoispp3 Implementation was incorrect for nsim > 1. (Results may have been incorrect.) Spotted by Jack Hywood. Fixed. o as.owin.data.frame Crashed if the window was not connected. Fixed. o Frame<- Crashed when applied to a binary mask. Fixed. o rho2hat Crashed if cov1="x" and cov2="y". Fixed. o as.mask Crashed sometimes when only the argument 'xy' was given. Fixed. o ppm Crashed (rarely) when method='ho' if the simulated pattern was empty. Fixed. o istat, iplot Crashed in recent versions of rpanel. Fixed. o convexhull Crashed if applied to a 'psp' object. Fixed. o plot.ppm Crashed with message about 'variable lengths differ'. Fixed. o plot.solist Crashed when applied to a list of point patterns if some patterns had more than one column of marks. Fixed. o Smooth.ppp Crashed if applied to a point pattern with several columns of marks if some of the columns were factors. Fixed. o runifpoint3, rpoispp3 Crashed if nsim > 1. Spotted by Jack Hywood. Fixed. o hist.im Crashed if argument 'freq' was given. Fixed. o MultiStraussHard Generated misleading error messages (e.g. 'model is invalid') when arguments 'iradii' and 'hradii' did not have the same pattern of NA's. Fixed. o plot.solist Figures were sometimes aligned incorrectly when the argument 'panel.args' was given. Fixed. o scaletointerval Results sometimes fell slightly outside the desired interval due to numerical error. Fixed. o plot.solist Behaved incorrectly when plotcommand='persp'. Fixed. o "[.hyperframe" Sometimes returned an 'anylist' when it should have returned a 'solist'. Fixed. o plot.im Did not plot surrounding frame box when ribbon=FALSE. Fixed. o envelope The functions stored when savefuns=TRUE did not inherit the correct name for the unit of length. Fixed. o print.ppm, print.fii, print.interact Layout was misaligned. Fixed. o plot.plotppm Paused for input when it was not appropriate. Fixed. o plot.fv On png devices, the legend box was drawn with a white background, obscuring the main plot. Fixed. o plot.owin, plot.ppp, plot.im There was unnecessary extra space above the main title. Fixed. o plot.rho2hat Colour map ribbon was drawn but not annotated. Fixed. o density.splitppp, density.ppplist Format was out of order if se=TRUE. Fixed. o MultiStraussHard project.ppm sometimes yielded a model that was still invalid. Fixed. CHANGES IN spatstat VERSION 1.41-1 OVERVIEW o This is identical to the major release 1.41-0 except for minor bug fixes. The change log for 1.41-0 is repeated here with minor modifications. o Version nickname: 'Ides of March' o We thank Ahmed El-Gabbas, Ute Hahn, Aruna Jammalamadaka, Ian Renner, Brian Ripley, Torben Tvedebrink and Sasha Voss for contributions. o Fixed a bug causing a segmentation fault. o Standard errors for kernel estimates of intensity. o Test for segregation. o Tessellations may now have marks. o Nested splitting. o More support for cluster models. Reorganised parametrisation. o Sparse data representation of linear networks. o More support for data on a linear network. o New datasets: 'spiders' and 'dendrite'. o Improvements and bug fixes. o spatstat no longer uses Fortran. o spatstat no longer depends on the package 'scatterplot3d'. o spatstat now imports (rather than 'suggests') the Matrix package. NEW DATASETS o dendrite Dendritic spines on the dendrite network of a neuron. A point pattern on a linear network. Generously contributed by Aruna Jammalamadaka. o spiders Spider webs on the mortar lines of a brick wall. A point pattern on a linear network. Generously contributed by Sasha Voss. NEW FUNCTIONS o segregation.test Test of spatial segregation of types in a multitype point pattern. o clusterfield, clusterkernel Compute the cluster kernel (offspring density) of a cluster process model, or compute the cluster field generated by superimposing copies of the cluster kernel at specified locations. o clusterradius Compute the radius of the support of the offspring density of a cluster process model. o as.linnet.psp Convert a line segment pattern to a linear network by guessing the connectivity using a distance threshold. o iplot.linnet, iplot.lpp Methods for interactive plotting 'iplot' for objects of class lpp and linnet. o Mathematical operations are now supported for pixel images on a linear network. See help(Math.linim) o dirichlet.network, delaunay.network The linear networks formed by the Dirichlet tessellation and Delaunay triangulation. o dirichlet.edges The edges of the Dirichlet tessellation. o selfcut.psp Cut line segments where they cross each other. o vertices.linnet Extract the vertices (nodes) of the linear network. o vertexdegree Compute the degree of each vertex in a linear network. o pixellate.linnet Pixellate a linear network. o subset.hyperframe 'subset' method for class 'hyperframe'. o head.hyperframe, tail.hyperframe 'head' and 'tail' methods for hyperframes. o clickdist Measures the distance between two spatial locations clicked by the user. o solapply, anylapply wrappers for 'lapply' which return a list of class 'solist' or 'anylist'. o Kmark Weighted K-function. Identical to 'markcorrint' and will eventually replace it. o marks.tess, marks<-.tess, unmark.tess: Extract or change the marks associated with the tiles of a tessellation. o quantess Quantile tessellation: divide space into pieces which contain equal amounts of 'stuff'. o nestsplit Nested split o integral New generic function for integrating functions, with methods for 'im', 'msr', 'linim' and 'linfun'. o selfcut.psp Cut line segments where they cross each other o as.function.im Convert a pixel image to a function(x,y). o as.linnet.linim Extract the linear network from a 'linim' object. o pool.fv, pool.anylist New methods for 'pool' o Window.linnet Extract the two-dimensional window containing a linear network. SIGNIFICANT USER-VISIBLE CHANGES o linnet, lpp A linear network can now be built in 'sparse matrix' form which requires much less memory. o chicago The Chicago street crimes data are now stored in 'sparse matrix' form. To convert them to non-sparse form, use as.lpp(chicago, sparse=FALSE) o kppm The parametrisation of cluster models has been reorganised. The scale parameter is now always called 'scale'. Results should be backward-compatible. o cauchy.estK, cauchy.estpcf, matclust.estK, matclust.estpcf, thomas.estK, thomas.estpcf, vargamma.estK, vargamma.estpcf The parametrisation of cluster models has been reorganised. The scale parameter is now always called 'scale'. o plot.kppm Also plots the cluster kernel. o density.ppp New argument 'se' allows calculation of standard errors as well. o plot.pp3 Now produces a genuine perspective view. New arguments control the eye position for the perspective view. o Emark, Vmark These functions can now work with multiple columns of marks. o pixellate.psp Can now count the number of segments that intersect each pixel, instead of the total length of intersection. o linfun If g = linfun(f, L), the function f will always be called as f(x,y,seg,tp, ...) It is no longer expected to handle the case where 'seg' and 'tp' are absent. The resulting function g can now be called as g(X) where X is an lpp object, or as g(x,y) or g(x,y,seg,tp) where x,y,seg,tp are coordinates. o tess New argument 'marks' allows marks to be associated with tiles. o anova.lppm Outdated argument 'override' has been removed. o split<-.ppp Preserves the original ordering of the data, if possible. o MultiHard, MultiStrauss, MultiStraussHard, HierStrauss Zero values in the interaction radii are now treated as NA. Improved handling of missing arguments. Printed output now respects options('width') o linearKinhom, linearKcross.inhom, linearKdot.inhom, linearpcfinhom, linearpcfcross.inhom, linearpcfdot.inhom If the intensity argument lambda, lambdaI, lambdaJ, lambdadot is a fitted point process model, the model is first updated by re-fitting it to the data, before computing the fitted intensity. o solutionset The expression will be evaluated using pixel arithmetic (Math.im) if it cannot be evaluated using eval.im. o to.grey Now uses better weights for the R, G, B channels. o rVarGamma Accelerated. o summary.mppm, print.mppm These functions now respect options('width') and spatstat.options('terse'). o print.quadrattest Now respects options('width') and spatstat.options('terse'). o print.pp3 Now respects options('width') o print.lpp Now respects options('width') and options('digits'). o print.owin, print.im, print.summary.owin, print.summary.im Now respect options('width'). o nnmean Now yields a vector, instead of a 1-column matrix, when there is only a single column of marks. o pairdist.psp, crossdist.psp, nndist.psp The option 'method="Fortran"' is no longer supported. The default is 'method="C"'. o [.hyperframe: When a row of data is extracted with drop=TRUE, the result belongs to class 'anylist'. o installation of spatstat A Fortran compiler is no longer needed to compile spatstat from source. o hyperframe class The internal structure of hyperframes has changed slightly: columns of objects are now stored and returned as lists of class 'anylist' or 'solist'. There should be no change in behaviour. o datasets Internal format of the datasets bdspots, bei, clmfires, demohyper, flu, gorillas, heather, Kovesi, murchison, osteo, pyramidal, waterstriders has changed slightly to use the classes 'anylist' and 'solist'. There should be no change in behaviour. o K3est New argument 'ratio'. o spatstat.options New option 'par.points3d' sets default arguments for plot.pp3. o diagnose.ppm New arguments 'xlab', 'ylab', 'rlab' determine the labels in the 4-panel plot, and new argument 'outer' controls their position. The confusing default value for 'compute.sd' has been changed. o iplot.layered New argument 'visible' controls which layers are initially visible. o plot.lpp New argument 'show.window' controls whether to plot the containing window. o textstring Any number of spatial locations (x,y) can be specified, with a corresponding vector of text strings. o plot.hyperframe New argument 'mar' o plot.linnet New argument 'do.plot' o summary.hyperframe Improved output. o eval.linim Improved scoping rules. o pixellate.owin Accelerated. o summary.linnet Now prints more information, and respects options('digits'). o rmpoispp, rmpoint The vector of possible types of points will default to the 'names' vector of the argument 'lambda', 'n', or 'f' where appropriate. o rpoislpp Argument 'L' can be omitted when lambda is a 'linim' or 'linfun' o simulate.ppm, simulate.kppm, simulate.lppm, simulate.slrm New argument 'drop': if nsim = 1 and drop=TRUE, the result is a point pattern rather than a list containing one point pattern. o runifdisc, runifpoint, rpoint, rpoispp, rmpoint, rmpoispp, rMaternI, rMaternII, rSSI, rPoissonCluster, rGaussPoisson, rstrat, rsyst, rcell, rthin, rNeymanScott, rMatClust, rThomas, rCauchy, rVarGamma, rpoispp3, runifpoint3 New argument 'drop': if nsim = 1 and drop=TRUE, the result is a point pattern rather than a list containing one point pattern. o spatstat.options New option 'units.paren' controls the type of parenthesis enclosing the explanatory text about the unit of length, in print.ppm, plot.fv, etc. o closepairs, crosspairs New option: what="ijd" returns only the indices i, j and the distance d o rCauchy, rMatClust, rNeymanScott, rPoissonCluster, rThomas, rVarGamma Argument names have changed. BUG FIXES o sumouter A segmentation fault could occur if any data were NA. Fixed. o simulate.kppm Simulation failed for log-Gaussian Cox processes (in simulate.kppm only) with an error message from the RandomFields package. Fixed. o ppm, predict.ppm, profilepl Crashed sometimes with message "interaction evaluator did not return a matrix". Fixed. o lppm step() did not work correctly on 'lppm' objects. Fixed. o quadscheme If quadscheme() was called explicitly, with the stipulated number of tiles exceeding the number of dummy points given, then the quadrature weights were sometimes vastly inflated - total quadrature weight was much larger than window area. Spotted by Ian Renner. Fixed. o predict.rhohat Result was incorrect for data on a non-rectangular window (and a warning was issued about incorrect vector length). Fixed. o Math.im Unary operators did not work (e.g."-x") Fixed. o density.ppp Crashed when at="points" if the dataset had exactly 1 point. Fixed. o rSSI Crashed if nsim > 1. Fixed. o influence.ppm, leverage.ppm, dfbetas.ppm Crashed or issued a warning if any quadrature points had conditional intensity zero under the model (negative infinite values of the sufficient statistic). Fixed. o clickppp, clickpoly Did not work correctly in the RStudio display device. Fixed. o Iest Ignored the arguments 'r' and 'eps'. Fixed. o markvario Result was garbled, when X had more than one column of marks. Fixed. o rMatClust, rVarGamma, rCauchy, rNeymanScott Result was a list, but not a 'solist', when nsim > 1. Fixed. o print.mppm, summary.mppm, subfits Crashed if a Poisson interaction was implied but not given explicitly. Fixed. o Kest Crashed if ratio=TRUE and the window was a rectangle. Fixed. o anova.ppm Crashed sometimes with message 'models were not all fitted to the same size of dataset'. (This occurred if there were quadrature points with conditional intensity equal to zero in some models but not in all models.) Fixed. o vcov.kppm Occasionally ran out of memory. Fixed. o as.linim.linfun Erroneously converted the pixel values to numeric values. Fixed. o as.owin.layered Ignored layers with zero area. Fixed. o plot.ppm Paused the plot between frames even when there was only one frame. Fixed. o plot.layered Did not allocate space for legends of 'lpp' objects. Fixed. o plot.lpp Ignored symbolmap arguments like 'cex' and confused the arguments 'col' and 'cols'. Fixed. o plot.diagppm Ignored add=TRUE in some cases. Fixed. o iplot.layered Did not handle 'diagramobj' objects correctly. Fixed. o plot.yardstick Changed arguments. CHANGES IN spatstat VERSION 1.41-0 OVERVIEW o We thank Ahmed El-Gabbas, Ute Hahn, Aruna Jammalamadaka, Ian Renner, Brian Ripley, Torben Tvedebrink and Sasha Voss for contributions. o Fixed a bug causing a segmentation fault. o Standard errors for kernel estimates of intensity. o Test for segregation. o Tessellations may now have marks. o Nested splitting. o More support for cluster models. Reorganised parametrisation. o Sparse data representation of linear networks. o More support for data on a linear network. o New datasets: 'spiders' and 'dendrite'. o Improvements and bug fixes. o spatstat no longer uses Fortran. o spatstat no longer depends on the package 'scatterplot3d'. o spatstat now imports (rather than 'suggests') the Matrix package. o Nickname: 'Team Australia' NEW DATASETS o dendrite Dendritic spines on the dendrite network of a neuron. A point pattern on a linear network. Generously contributed by Aruna Jammalamadaka. o spiders Spider webs on the mortar lines of a brick wall. A point pattern on a linear network. Generously contributed by Sasha Voss. NEW FUNCTIONS o segregation.test Test of spatial segregation of types in a multitype point pattern. o clusterfield, clusterkernel Compute the cluster kernel (offspring density) of a cluster process model, or compute the cluster field generated by superimposing copies of the cluster kernel at specified locations. o clusterradius Compute the radius of the support of the offspring density of a cluster process model. o as.linnet.psp Convert a line segment pattern to a linear network by guessing the connectivity using a distance threshold. o iplot.linnet, iplot.lpp Methods for interactive plotting 'iplot' for objects of class lpp and linnet. o Mathematical operations are now supported for pixel images on a linear network. See help(Math.linim) o dirichlet.network, delaunay.network The linear networks formed by the Dirichlet tessellation and Delaunay triangulation. o dirichlet.edges The edges of the Dirichlet tessellation. o selfcut.psp Cut line segments where they cross each other. o vertices.linnet Extract the vertices (nodes) of the linear network. o vertexdegree Compute the degree of each vertex in a linear network. o pixellate.linnet Pixellate a linear network. o subset.hyperframe 'subset' method for class 'hyperframe'. o head.hyperframe, tail.hyperframe 'head' and 'tail' methods for hyperframes. o clickdist Measures the distance between two spatial locations clicked by the user. o solapply, anylapply wrappers for 'lapply' which return a list of class 'solist' or 'anylist'. o Kmark Weighted K-function. Identical to 'markcorrint' and will eventually replace it. o marks.tess, marks<-.tess, unmark.tess: Extract or change the marks associated with the tiles of a tessellation. o quantess Quantile tessellation: divide space into pieces which contain equal amounts of 'stuff'. o nestsplit Nested split o integral New generic function for integrating functions, with methods for 'im', 'msr', 'linim' and 'linfun'. o selfcut.psp Cut line segments where they cross each other o as.function.im Convert a pixel image to a function(x,y). o as.linnet.linim Extract the linear network from a 'linim' object. o pool.fv, pool.anylist New methods for 'pool' o Window.linnet Extract the two-dimensional window containing a linear network. SIGNIFICANT USER-VISIBLE CHANGES o linnet, lpp A linear network can now be built in 'sparse matrix' form which requires much less memory. o chicago The Chicago street crimes data are now stored in 'sparse matrix' form. To convert them to non-sparse form, use as.lpp(chicago, sparse=FALSE) o kppm The parametrisation of cluster models has been reorganised. The scale parameter is now always called 'scale'. Results should be backward-compatible. o cauchy.estK, cauchy.estpcf, matclust.estK, matclust.estpcf, thomas.estK, thomas.estpcf, vargamma.estK, vargamma.estpcf The parametrisation of cluster models has been reorganised. The scale parameter is now always called 'scale'. o plot.kppm Also plots the cluster kernel. o density.ppp New argument 'se' allows calculation of standard errors as well. o plot.pp3 Now produces a genuine perspective view. New arguments control the eye position for the perspective view. o Emark, Vmark These functions can now work with multiple columns of marks. o pixellate.psp Can now count the number of segments that intersect each pixel, instead of the total length of intersection. o linfun If g = linfun(f, L), the function f will always be called as f(x,y,seg,tp, ...) It is no longer expected to handle the case where 'seg' and 'tp' are absent. The resulting function g can now be called as g(X) where X is an lpp object, or as g(x,y) or g(x,y,seg,tp) where x,y,seg,tp are coordinates. o tess New argument 'marks' allows marks to be associated with tiles. o anova.lppm Outdated argument 'override' has been removed. o split<-.ppp Preserves the original ordering of the data, if possible. o MultiHard, MultiStrauss, MultiStraussHard, HierStrauss Zero values in the interaction radii are now treated as NA. Improved handling of missing arguments. Printed output now respects options('width') o linearKinhom, linearKcross.inhom, linearKdot.inhom, linearpcfinhom, linearpcfcross.inhom, linearpcfdot.inhom If the intensity argument lambda, lambdaI, lambdaJ, lambdadot is a fitted point process model, the model is first updated by re-fitting it to the data, before computing the fitted intensity. o solutionset The expression will be evaluated using pixel arithmetic (Math.im) if it cannot be evaluated using eval.im. o to.grey Now uses better weights for the R, G, B channels. o rVarGamma Accelerated. o summary.mppm, print.mppm These functions now respect options('width') and spatstat.options('terse'). o print.quadrattest Now respects options('width') and spatstat.options('terse'). o print.pp3 Now respects options('width') o print.lpp Now respects options('width') and options('digits'). o print.owin, print.im, print.summary.owin, print.summary.im Now respect options('width'). o nnmean Now yields a vector, instead of a 1-column matrix, when there is only a single column of marks. o pairdist.psp, crossdist.psp, nndist.psp The option 'method="Fortran"' is no longer supported. The default is 'method="C"'. o [.hyperframe: When a row of data is extracted with drop=TRUE, the result belongs to class 'anylist'. o installation of spatstat A Fortran compiler is no longer needed to compile spatstat from source. o hyperframe class The internal structure of hyperframes has changed slightly: columns of objects are now stored and returned as lists of class 'anylist' or 'solist'. There should be no change in behaviour. o datasets Internal format of the datasets bdspots, bei, clmfires, demohyper, flu, gorillas, heather, Kovesi, murchison, osteo, pyramidal, waterstriders has changed slightly to use the classes 'anylist' and 'solist'. There should be no change in behaviour. o K3est New argument 'ratio'. o spatstat.options New option 'par.points3d' sets default arguments for plot.pp3. o diagnose.ppm New arguments 'xlab', 'ylab', 'rlab' determine the labels in the 4-panel plot, and new argument 'outer' controls their position. The confusing default value for 'compute.sd' has been changed. o iplot.layered New argument 'visible' controls which layers are initially visible. o plot.lpp New argument 'show.window' controls whether to plot the containing window. o textstring Any number of spatial locations (x,y) can be specified, with a corresponding vector of text strings. o plot.hyperframe New argument 'mar' o plot.linnet New argument 'do.plot' o summary.hyperframe Improved output. o eval.linim Improved scoping rules. o pixellate.owin Accelerated. o summary.linnet Now prints more information, and respects options('digits'). o rmpoispp, rmpoint The vector of possible types of points will default to the 'names' vector of the argument 'lambda', 'n', or 'f' where appropriate. o rpoislpp Argument 'L' can be omitted when lambda is a 'linim' or 'linfun' o simulate.ppm, simulate.kppm, simulate.lppm, simulate.slrm New argument 'drop': if nsim = 1 and drop=TRUE, the result is a point pattern rather than a list containing one point pattern. o runifdisc, runifpoint, rpoint, rpoispp, rmpoint, rmpoispp, rMaternI, rMaternII, rSSI, rPoissonCluster, rGaussPoisson, rstrat, rsyst, rcell, rthin, rNeymanScott, rMatClust, rThomas, rCauchy, rVarGamma New argument 'drop' o spatstat.options New option 'units.paren' controls the type of parenthesis enclosing the explanatory text about the unit of length, in print.ppm, plot.fv, etc. o closepairs, crosspairs New option: what="ijd" returns only the indices i, j and the distance d o rCauchy, rMatClust, rNeymanScott, rPoissonCluster, rThomas, rVarGamma Argument names have changed. BUG FIXES o sumouter A segmentation fault could occur if any data were NA. Fixed. o simulate.kppm Simulation failed for log-Gaussian Cox processes (in simulate.kppm only) with an error message from the RandomFields package. Fixed. o ppm, predict.ppm, profilepl Crashed sometimes with message "interaction evaluator did not return a matrix". Fixed. o lppm step() did not work correctly on 'lppm' objects. Fixed. o quadscheme If quadscheme() was called explicitly, with the stipulated number of tiles exceeding the number of dummy points given, then the quadrature weights were sometimes vastly inflated - total quadrature weight was much larger than window area. Spotted by Ian Renner. Fixed. o predict.rhohat Result was incorrect for data on a non-rectangular window (and a warning was issued about incorrect vector length). Fixed. o Math.im Unary operators did not work (e.g."-x") Fixed. o density.ppp Crashed when at="points" if the dataset had exactly 1 point. Fixed. o rSSI Crashed if nsim > 1. Fixed. o influence.ppm, leverage.ppm, dfbetas.ppm Crashed or issued a warning if any quadrature points had conditional intensity zero under the model (negative infinite values of the sufficient statistic). Fixed. o clickppp, clickpoly Did not work correctly in the RStudio display device. Fixed. o Iest Ignored the arguments 'r' and 'eps'. Fixed. o markvario Result was garbled, when X had more than one column of marks. Fixed. o rMatClust, rVarGamma, rCauchy, rNeymanScott Result was a list, but not a 'solist', when nsim > 1. Fixed. o print.mppm, summary.mppm, subfits Crashed if a Poisson interaction was implied but not given explicitly. Fixed. o Kest Crashed if ratio=TRUE and the window was a rectangle. Fixed. o anova.ppm Crashed sometimes with message 'models were not all fitted to the same size of dataset'. (This occurred if there were quadrature points with conditional intensity equal to zero in some models but not in all models.) Fixed. o vcov.kppm Occasionally ran out of memory. Fixed. o as.linim.linfun Erroneously converted the pixel values to numeric values. Fixed. o as.owin.layered Ignored layers with zero area. Fixed. o plot.ppm Paused the plot between frames even when there was only one frame. Fixed. o plot.layered Did not allocate space for legends of 'lpp' objects. Fixed. o plot.lpp Ignored symbolmap arguments like 'cex' and confused the arguments 'col' and 'cols'. Fixed. o plot.diagppm Ignored add=TRUE in some cases. Fixed. o iplot.layered Did not handle 'diagramobj' objects correctly. Fixed. o plot.yardstick Changed arguments. CHANGES IN spatstat VERSION 1.40-0 OVERVIEW o We thank Markus Herrmann, Peter Kovesi, Andrew Lister, Enrique Miranda, Tuomas Rajala, Brian Ripley, Dominic Schuhmacher and Maxime Woringer for contributions. o Important bug fixes. o Mathematical operators now apply to images. o Parametric estimates of relative risk from fitted point process models. o Standard errors for relative risk (parametric and non-parametric). o Kernel smoothing and rose diagrams for angular data. o Perceptually uniform colour maps. o Hierarchical interactions for multitype patterns. o Hard core parameters in all interactions no longer need to be specified and will be estimated from data. o Improvements to analysis of deviance and model selection. o New datasets. o New vignette, summarising all datasets installed with spatstat. o Tests and diagnostics now include a Monte Carlo option. o Faster checking of large datasets. o Faster simulations. o Code for drawing diagrams (arrows, scale bars). o Version nickname: 'Do The Maths' NEW DATASETS o bdspots Breakdown spots on microelectronic capacitor electrodes. Generously contributed by Prof Enrique Miranda. o Kovesi Colour maps with perceptually uniform contrast. Generously contributed by Peter Kovesi. NEW FUNCTIONS o Mathematical operations are now supported for images. For example: alpha <- atan(bei.extra$grad) * 180/pi See help(Math.im) o relrisk.ppm Spatially-varying probabilities of different types of points predicted by a fitted point process model. o circdensity Kernel density estimate for angular data o rose Rose diagram (rose of directions) for angular data o nnorient Nearest neighbour orientation distribution. o AIC.ppm Calculate AIC of a Gibbs model using Takeuchi's rule. o interp.colours Interpolate a sequence of colour values. o anyDuplicated.ppp, anyDuplicated.ppx Fast replacements for any(duplicated(x)) for point patterns. o textstring, onearrow, yardstick Objects representing a text string, an arrow, or a scale bar, for use in drawing spatial diagrams. o plot.imlist, image.imlist, contour.imlist Methods for the new class 'imlist' o [<-.layered, [[<-.layered More support for class 'layered' SIGNIFICANT USER-VISIBLE CHANGES o (vignettes) New vignette 'datasets' summarises all the datasets installed with the spatstat package. o relrisk The function relrisk is now generic, with methods for ppp and ppm. New argument 'relative' specifies whether to calculate the relative risk or the absolute probability of each type of point. New argument 'se' specifies whether to calculate standard errors. o plot.im The default colour map for plotting images, specified by spatstat.options('image.colfun'), has been changed to a perceptually uniform map. o DiggleGratton, Fiksel, MultiHard, MultiStraussHard The hard core distance parameters in these models can now be omitted by the user, and will be estimated automatically from data (by the 'self-starting' feature of interactions). This was already true of Hardcore and StraussHard. o Hybrid Hybrid models now apply the 'self-starting' feature to each component model. o anova.ppm Can now reconcile models fitted using different dummy points, different values of 'rbord', different values of 'use.gam', etc. o profilepl New argument 'aic' makes it possible to optimise the parameters by minimising AIC. o profilepl No longer requires values for parameters which are 'optional' (such as the hard core distance). o rmh, simulate.ppm, rmh.ppm, rmh.default The Metropolis-Hastings algorithm now starts by deleting any points in the initial state that are 'illegal' (i.e. whose conditional intensity is equal to zero). This ensures that the result of rmh never contains illegal points. o runifpoint, rpoispp, rStrauss, rHardcore, rStraussHard, rDiggleGratton, rDGS, runifdisc, rpoint, rMaternI, rMaternII, rSSI, rPoissonCluster, rGaussPoisson, rstrat, rsyst, rcell, rthin, rjitter, rNeymanScott, rMatClust, rThomas, rCauchy, rVarGamma, rmpoint, rmpoispp, runifpointOnLines, rpoisppOnLines, runiflpp, rpoislpp, runifpointx, rpoisppx, runifpoint3, rpoispp3 These random point pattern generators now have an argument 'nsim' specifying the number of simulated realisations to be generated. o pairorient New argument 'cumulative'. New algorithm to compute kernel estimate of probability density. Default behaviour changed. Argument 'units' has been renamed 'unit' for consistency. Labels and descriptions of columns have been corrected. o predict.ppm New syntax (backward-compatible). New argument 'se' replaces option 'type="se"'. Old argument 'total' is deprecated: use 'window' and set 'type="count"'. o cdf.test The methods for class 'ppm' and 'lppm' now handle Gibbs models and perform a Monte Carlo test in this case. o lurking, diagnose.ppm Lurking variable plot can now include simulation envelopes. o rmh.ppm New argument 'w' determines the window in which the simulated pattern is generated. o ppp Accelerated. o Gcom, Gres When conditional=TRUE and restrict=TRUE, the Hanisch estimate was not calculated exactly as described in Appendix E.1 of Baddeley, Rubak and Moller (2011). The intensity was estimated on the full window rather than the eroded window. Fixed. o step, drop1, add1, extractAIC The AIC of a Gibbs model is now calculated using Takeuchi's rule for the degrees of freedom. o model.matrix.ppm, model.matrix.kppm New argument 'Q' allows prediction at any desired locations. o vcov.ppm New argument 'fine' gives more control over computation. o predict.ppm For multitype models, when the result is a list of images, the names of list entries are now identical to the mark levels (e.g. "hickory" instead of "markhickory") o print.slrm Output now respects options('width') o image.listof New argument 'ribmar' controls margin space around the ribbon when equal.ribbon=TRUE. o integral.im New argument 'domain' specifies the domain of integration. o plot.fasp New argument 'transpose' allows rows and columns to be exchanged. o plot.im The list 'ribargs' can now include the parameter 'labels'. o rmh, rpoint, rpoispp, rmpoint, rmpoispp Accelerated, for inhomogeneous processes. o stienen Now recognises the parameter 'lwd'. o suffstat Accelerated (also affects ppm with method='ho'). o Poisson, AreaInter, BadGey, Concom, DiggleGatesStibbard, DiggleGratton, Fiksel, Geyer, Hardcore, Hybrid, LennardJones, MultiHard, MultiStrauss, MultiStraussHard, OrdThresh, Ord, PairPiece, Pairwise, SatPiece, Saturated, Softcore, Strauss, StraussHard, Triplets These functions can now be printed (by typing the function name) to give a sensible description of the required syntax. o fitin A plot of the fitted interpoint interaction of a point process model e.g. plot(fitin(ppm(swedishpines ~ 1, Strauss(9)))) now shows the unit of length on the x-axis. o fitin Plots of the fitted interpoint interaction are now possible for some higher-order interactions such as Geyer and AreaInter. o anova.ppm New argument 'warn' to suppress warnings. o rmhmodel.ppm Argument 'win' renamed 'w' for consistency with other functions. o print.ppm Printed output for the fitted regular parameters now respects options('digits'). o print.ppm, print.summary.ppm Output now respects options('width') and spatstat.options('terse') o print.ppm By default, standard errors are not printed for a model fitted with method="logi" (due to computational load) o plot.profilepl Now recognises 'lty', 'lwd', 'col' etc o vesicles, gorillas Some of the raw data files for these datasets are also installed in spatstat for demonstration and training purposes. BUG FIXES o rmh, rmh.ppm, rmh.default, simulate.ppm The result of simulating a model with a hard core did not necessarily respect the hard core constraint, and simulation of a model with strong inhibition did not necessarily converge. This only happened if the first order trend was large, the starting state (n.start or x.start) was not given, and the number of iterations (nrep) was not very large. It occurred because of a poor choice for the default starting state. Bug was present since about 2010. Fixed. o markcorrint Results were completely incorrect. Bug introduced in spatstat 1.39-0, october 2014. Fixed. o Kinhom Ignored argument 'reciplambda2' in some cases. Bug introduced in spatstat 1.39-0, october 2014. Fixed. o relrisk When at="pixels", a small fraction of pixel values were sometimes wildly inaccurate, due to numerical errors. This affected the range of values in the result, and therefore the appearance of plots. Fixed. o model.images Crashed if the model was multitype. Fixed. o profilepl Crashed in some cases when the interaction was multitype. [Spotted by Andrew Lister.] Fixed. o profilepl Crashed if the model involved covariates that were not given in a 'data' argument. Fixed. o envelope.ppm Crashed if global=TRUE and savefuns=TRUE. Fixed. o setminus.owin Crashed if the result was empty and the input was polygonal. Fixed. o predict.ppm Crashed sometimes when type="cif" and ngrid was very large. Fixed. o pixelquad If X was a multitype point pattern, the result was mangled. Fixed. o relrisk Did not accept a character string value for the argument 'case'. Fixed. o intensity.ppm Format of result was incorrect for ppm(Y ~ 1) where Y is multitype. Fixed. o $<-.hyperframe Columns containing character values were converted to factors. Fixed. o clickppp Sometimes filled the window in solid black colour.. Fixed. o plot.psp Ignored 'show.all' in some cases. Fixed. o plot.ppp Warned about NA values amongst the marks, even if there were no NA's in the column(s) of marks selected by the argument 'which.marks'. Fixed. o stienen Did not suppress the border circles when border=FALSE. Fixed. CHANGES IN spatstat VERSION 1.39-1 OVERVIEW o Urgent bug fix. o We thank Suman Rakshit and Brian Ripley for contributions. BUG FIXES o bdry.mask, convexhull In R-devel only, these functions could return an empty window, causing errors in other packages. [Spotted by Brian Ripley.] Fixed. o project2segment An error occurred if any line segments had length zero. [Spotted by Suman Rakshit.] Fixed. CHANGES IN spatstat VERSION 1.39-0 OVERVIEW o We thank Shane Frank, Shaaban Ghalandarayeshi, Ute Hahn, Mahdieh Khanmohammadi, Nicoletta Nava, Jens Randel Nyengaard, Sebastian Schutte, Rasmus Waagepetersen and Carl G. Witthoft for contributions. o ANOVA extended to Gibbs models. o Improved algorithm for locally-scaled K-function. o Leave-one-out calculation of fitted values in ppm objects. o New dataset: presynaptic vesicles. o Geometrical operations with windows and images. o More edge corrections for K-function. o Improved handling and plotting of 'fv' objects. o Utilities for perspective views of surfaces. o New classes 'anylist', 'solist' will ultimately replace 'listof'. o Bug fixes. o Version nickname: 'Smoke and Mirrors' NEW DATASETS o vesicles Synaptic vesicles (includes raw data files for training purposes) NEW CLASSES o anylist List of objects. (A replacement for 'listof') o solist List of two-dimensional spatial objects. (A replacement for some uses of 'listof') NEW FUNCTIONS o perspPoints, perspLines, perspSegments, perspContour Draw points and lines on a surface, as seen in perspective view. o hopskel.test Hopkins-Skellam test of CSR o project2set For each data point in a point pattern X, find the nearest spatial location in a given window W. o stienen, stienenset Stienen diagrams o dirichlet.vertices Vertices of the Dirichlet tessellation o discs Union of discs. Given a point pattern dataset recording the locations and diameters of objects, find the region covered by the objects. o increment.fv Increments of a summary function: g(x) = f(x+h)-f(x-h). o rotmean Rotational average of pixel values in an image o fardist Distance from each pixel/data point to farthest part of window boundary o circumradius.owin Circumradius of a window o rmax.Trans, rmax.Ripley Compute the maximum distance 'r' for which the translation edge correction and isotropic edge correction are valid. o is.grey Determines whether a colour value is a shade of grey. o harmonise Convert several objects of the same class to a common format. (New generic function with existing methods harmonise.im and harmonise.fv) o area New generic function, with methods for 'owin' and 'default'. o Fhazard Hazard rate of empty space function o anylist, as.anylist, [.anylist, [<-.anylist, print.anylist, summary.anylist Support for new class 'anylist' o solist, as.solist, [.solist, [<-.solist, print.solist, summary.solist Support for new class 'solist' o plot.anylist, plot.solist Plot methods for the classes 'anylist' and 'solist' (Currently identical to 'plot.listof') SIGNIFICANT USER-VISIBLE CHANGES o anova.ppm Now applies to Gibbs models as well as Poisson models, using adjusted composite likelihood ratio test statistic. o persp.im If visible=TRUE, the algorithm will also calculate which pixels of x are visible in the perspective view. This is useful for drawing points or lines on a perspective surface. o Kscaled Improved algorithm [thanks to Ute Hahn.] New arguments 'renormalise' and 'normpower' allow renormalisation of intensity, similar to Kinhom. o Kest New option: correction="rigid" computes the rigid motion correction. o pairwise interactions Fitted parameters and other calculations for pairwise interaction models DiggleGatesStibbard, DiggleGratton, Fiksel, Geyer, Strauss may change slightly due to a change in handling numerical rounding effects. o eval.fv Functions no longer need to have exactly the same sequence of 'r' values. They will now be made compatible using 'harmonise.fv'. o fitted.ppm New argument 'leaveoneout' allows leave-one-out calculation of fitted intensity at original data points. o Kinhom, Linhom New argument 'leaveoneout' specifies whether the leave-one-out rule should be applied when calculating the fitted intensities. o crosspaircounts Results may change slightly due to a change in handling numerical rounding effects. o Fest, Gest New argument 'domain' supports bootstrap methods. o plot.fv New argument 'mathfont' determines the font (e.g. plain, italic, bold) for mathematical expressions on the axes and in the legend. Defaults to italic. o scanpp Upgraded to handle multiple columns of mark data. o circumradius The function 'circumradius' is now generic, with methods for the classes 'owin' and 'linnet'. o edge.Trans New argument 'give.rmax' o fvnames, plot.fv The symbol '.a' is now recognised. It stands for 'all function values'. o as.function.fv Argument 'extrapolate' can have length 1 or 2. o varblock New argument 'confidence' determines the confidence level. o $<-.fv This can now be used to add an extra column to an 'fv' object (previously it refused). o minnndist, maxnndist New argument 'positive'. If TRUE, coincident points are ignored: the nearest-neighbour distance of a point is the distance to the nearest point that does not coincide with the current point. o plot.fv Improved handling of 'shade' argument. o Kmeasure Now passes '...' arguments to as.mask() o Ksector Now allows start < 0. New arguments 'units' and 'domain'. o pairorient New arguments 'units' and 'domain'. o eroded.areas New argument 'subset' o disc New argument 'delta' o plot.plotppm New argument 'pppargs' o harmonise.fv, harmonise.im These are now methods for the new generic 'harmonise' o Fest, Gest These functions now also compute the theoretical value of hazard for a Poisson process, if correction = "km". o with.fv Improved mathematical labels. o Gfox, Jfox Improved mathematical labels. o area.owin This function is now a method for the new generic 'area' o edges Default for argument 'check' changed to FALSE. BUG FIXES o varblock Calculations were incorrect if more than one column of edge corrections was computed. [Bug introduced in spatstat 1.21-1, november 2010.] Fixed. o varblock Crashed if one of the quadrats contained no data points. Fixed. o lohboot Interval was calculated wrongly when global=TRUE and fun="Lest" or "Linhom". Fixed. o nnmark Crashed when at="points" if there was only a single column of marks. [Spotted by Shane Frank.] Fixed. o plot.msr Some elements of the plot were omitted or cut off. Fixed. o plot.msr Did not work with 'equal.scales=TRUE'. Fixed. o plot.msr, augment.msr Crashed if every data point was duplicated. Fixed. o as.im.owin Crashed if X was a 1 x 1 pixel array. Fixed. o owin Coordinates of polygon data were altered slightly when fix=TRUE. [Spotted by Carl Witthoft.] Fixed. o objects of class 'fv' Assigning a new value to names(x) or colnames(x) or dimnames(x) would cause the internal data format to become corrupted. Fixed. o to.grey, complementarycolour Did not work properly on 'colourmap' objects. Fixed. o Kest Ignored argument 'var.approx' if the window was a rectangle. Fixed. o rmh.ppm, rmhmodel.ppm Ignored the argument 'new.coef'. [Spotted by Sebastian Schutte] Fixed. o as.function.fv The meanings of 'extrapolate=TRUE' and 'extrapolate=FALSE' were swapped. Fixed. o varblock Handled the case 'fun=Lest' incorrectly. Fixed. o [.fv Sometimes garbled the internal data format, causing plot.fv to crash. Fixed. o range.fv Sometimes returned NA even when na.rm=TRUE. Fixed. o Fest Argument 'eps' was not interpreted correctly. Fixed. o plot.fv Argument 'lwd' was not passed to legend() o flipxy.owin Sometimes deleted the name of the unit of length. Fixed. CHANGES IN spatstat VERSION 1.38-1 OVERVIEW o We thank Ute Hahn and Xavier Raynaud for contributions. o Urgent Bug Fixes. o Nickname: 'Le Hardi' NEW FUNCTIONS o "[<-.fv", "$<-.fv" Subset replacement methods for 'fv' objects. SIGNIFICANT USER-VISIBLE CHANGES o clarkevans.test Simulations are now performed with a fixed number of points. o plot.owin, plot.ppp, plot.psp, plot.im The default size of the outer margin of white space has been reduced. o dclf.test Improved information in printed output. BUG FIXES o update.ppm Results were incorrect in several cases. [Spotted by Xavier Raynaud.] Bug introduced in spatstat 1.38-0. Fixed. o Kinhom, Linhom Calculations were incorrect if 'lambda' was a fitted point process model. [Spotted by Xavier Raynaud.] Bug introduced in spatstat 1.38-0. Fixed. o envelope.envelope Ignored the arguments 'global' and 'VARIANCE'. Fixed. o fv objects If 'f' was an object of class 'fv', then an assignment like f$name <- NULL mangled the internal format of the object 'f', leading to errors in print.fv and plot.fv. [Spotted by Ute Hahn.] Fixed. o split.ppp split(X, A) where A is a rectangular tessellation, produced errors if the window of 'A' did not include the window of 'X'. [Spotted by Ute Hahn.] Fixed. o names<-.hyperframe Mangled the internal format. [Spotted by Ute Hahn.] Fixed. o plot.fv y axis label was incorrect in some cases when the 'fv' object had only a single column of function values. [Spotted by Ute Hahn.] Fixed. CHANGES IN spatstat VERSION 1.38-0 OVERVIEW o We thank Malissa Baddeley, Colin Beale, Oscar Garcia, Daniel Esser, David Ford, Eric Gilleland, Andrew Hardegen, Philipp Hunziker, Abdollah Jalilian, Tom Lawrence, Lore De Middeleer, Robin Milne, Mike Porter, Suman Rakshit, Pablo Ramon, Jason Rudokas, Christopher Ryan, Dominic Schuhmacher, Medha Uppala and Rasmus Waagepetersen for contributions. o spatstat now Requires the package 'goftest' and Suggests the package 'Matrix'. o New dataset: 'sporophores' o Palm likelihood method for fitting cluster processes and Cox processes. o Quasi-likelihood and weighted composite likelihood methods for estimating trend in cluster processes and Cox processes. o Further extensions to model formulas in ppm and kppm. o Faster variance calculations for ppm objects. o One-sided tests and one-sided envelopes of summary functions. o Cramer-Von Mises and Anderson-Darling tests of spatial distribution. o Cressie-Read test statistic in quadrat counting tests. o Spatial cumulative distribution functions. o Faster algorithm for point pattern matching. o Improvements to plots. o Increased support for envelopes. o New generic functions 'Window', 'Frame' and 'domain'. o Directional K-function and directional distribution. o Raster calculations accelerated. o Summary functions accelerated. o Many improvements and bug fixes. o Version nickname: 'Wicked Plot' NEW DATASETS o sporophores Spatial pattern of three species of mycorrhizal fungi around a tree. [Contributed by E. David Ford.] NEW FUNCTIONS o improve.kppm Re-estimate the trend in a kppm (cluster or Cox) model using quasi-likelihood or weighted first-order composite likelihood. [Contributed by Abdollah Jalilian and Rasmus Waagepetersen.] o Window, Window<- Generic functions to extract and change the window of a spatial object in two dimensions. Methods for ppp, psp, im, and many others. o Frame, Frame<- Generic functions to extract and change the containing rectangle ('frame') of a spatial object in two dimensions. o domain Generic function to extract the spatial domain of a spatial object in any number of dimensions. o Ksector Directional version of the K-function. o pairorient Point pair orientation distribution. o spatialcdf Compute the spatial cumulative distribution of a spatial covariate, optionally using spatially-varying weights. o cdf.test [Supersedes 'kstest'.] Test of goodness-of-fit of a Poisson point process model. The observed and predicted distributions of the values of a spatial covariate are compared using either the Kolmogorov-Smirnov, Cramer-Von Mises or Anderson-Darling test. o berman.test Replaces 'bermantest'. o harmonise.fv Make several functions compatible. o simulate.lppm Simulate a fitted point process model on a linear network. o subset.ppp, subset.lpp, subset.pp3, subset.ppx Methods for 'subset', for point patterns. o closepairs.pp3, crosspairs.pp3 Low-level functions to find all close pairs of points in three dimensions o volume.linnet Method for the generic 'volume'. Returns the length of the linear network. o padimage Pad the border of a pixel image. o as.layered Convert spatial data to a layered object. o panel.contour, panel.image, panel.histogram Panel functions for 'pairs' plots. o range.fv, min.fv, max.fv Range, minimum and maximum of function values. SIGNIFICANT USER-VISIBLE CHANGES o ppm.formula The left hand side of the formula can now be the name of an object in the list 'data', or an expression involving such objects. o ppm The right hand side of the formula can now include the symbol '.' representing all covariates in the list 'data'. o ppm New argument 'subset' makes it possible to fit the model in a subset of the spatial domain defined by an expression. o kppm New option: method="palm", will fit the model by maximising Palm likelihood. o pppdist Substantially accelerated. New argument 'auction' controls choice of algorithm. o rhohat New arguments 'weights' and 'horvitz' for weighted calculations. o persp.im Surface heights and colours can now be controlled by different images. Option to draw a grey apron around the sides of the perspective plot. Return value has a new attribute 'expand'. o plot.listof New arguments 'halign' and 'valign' give improved control over the alignment of panels. o plot.listof If all components of the list are objects of class 'fv' representing functions, then if equal.scales=TRUE, these functions will all be plotted with the same axes (i.e. the same xlim and the same ylim). o envelope The argument 'transform' is now processed by 'with.fv' giving more options, such as 'transform=expression(. - r)' o envelope, dclf.test, mad.test One-sided tests and one-sided envelopes can now be produced, by specifying the argument 'alternative'. o dclf.test, mad.test A pointwise test at fixed distance 'r' can now be performed by setting rinterval = c(r,r). o envelope New arguments 'fix.n' and 'fix.marks' for envelope.ppp and envelope.ppm make it easy to generate simulated patterns conditional on the total number of points, or on the number of points of each type. o quadrat.test Can now calculate the Cressie-Read test statistic instead of the Pearson X2 statistic. o Kres, Gres, Kcom, Gcom, psst, psstA, psstG New argument 'model' makes it easier to generate simulation envelopes of the residual summary functions. o layered, plot.layered The layer plot arguments can include the argument '.plot' specifying a function to perform the plotting instead of the generic 'plot'. o deriv.fv New arguments make it possible to differentiate a periodic function. o ppm Argument 'data' or 'covariates' can now include entries which are not spatial covariates, provided they do not appear in the model formula. o closepairs, crosspairs These functions are now generic, with methods for 'ppp' and 'pp3' o rLGCP Updated to conform to new usage of RandomFields package. Argument syntax has changed. Now allows control over pixel resolution. o bw.diggle New arguments 'correction' and 'hmax' for controlling the calculation. o predict.lppm New argument 'new.coef' for computing predictions with a different vector of model coefficients. o predict.ppm If 'locations' is a pixel image, its pixels determine the spatial locations for prediction. o cut.ppp Argument 'z' can now be a window. o split.ppp Argument 'f' can now be a window. o print.ppm, summary.ppm, coef.summary.ppm The table of parameter estimates, standard errors and confidence intervals now also includes the value of the (signed square root) Wald test statistic. o plot.im Now automatically detects problems in some Windows graphics displays and tries to avoid them. o plot.im The position of axis tick marks alongside the colour ribbon can now be controlled using the parameter 'at' in the argument 'ribargs'. o plot.ppp Can now plot numeric marks using characters chosen by 'pch' or 'chars' with size determined by mark value. o plot.ppp New argument 'meansize' for controlling mark scale. o hsvim, rgbim New argument 'autoscale' causes automatic scaling of colour channel values. o plot.ppp If type='n', a legend is now displayed when x is a marked point pattern. o whist Accelerated by a factor of 5. o Fest, Jest Accelerated by a factor of 2 to 3. o fryplot Accelerated. Now displays a legend if the point pattern is marked. Now handles numerical marks nicely. New argument 'axes'. o frypoints Accelerated. New arguments 'to', 'from' and 'dmax'. o duplicated.ppp New option: rule = 'unmark' o rjitter Argument 'radius' now has a default. o Smooth.msr New argument 'drop' o LambertW Now handles NA and infinite values. o update.ppm Now handles formulae with a left-hand side. o raster.x, raster.y, raster.xy These functions can now handle images, as well as masks. o Smooth.ppp If the mark values are exactly constant, the resulting smoothed values are now exactly constant. o eval.im, eval.fv, eval.fasp Argument 'envir' can now be a list, instead of an environment. o plot.ppp The printout (of the resulting symbol map object) now displays the numerical value of the mark scale. o with.fv Improved mathematical labels. o plot.fv Improved mathematical labels on x axis. o ppm Improved error messages. o vcov.ppm Computations greatly accelerated for Hybrid interactions and for Area-interaction models. o vcov.kppm Computations greatly accelerated (when fast=TRUE) o interp.im Argument 'x' can now be a point pattern. o pool.envelope Improved handling of text information. o miplot Improved layout. o print.summary.ppp Improved layout. Now respects spatstat.options('terse') o print.profilepl Improved layout. Now respects spatstat.options('terse') o anova.ppm Now respects spatstat.options('terse') o print.fv, print.envelope Now respect spatstat.options('terse') and options('width') o summary.envelope Now respects options('width') o kstest, bermantest These functions will soon be Deprecated. They are retained only for backward compatibility. BUG FIXES o vcov.ppm Sometimes gave wrong answers for Poisson models fitted by method='logi'. Fixed. o unnormdensity If weights were missing, the density was normalised, contrary to the documentation. Fixed. o logLik.ppm, anova.ppm, AIC For models fitted by 'ippm', the number of degrees of freedom was incorrect. Fixed. o im.apply Pixels outside the window were not assigned the value NA as they should. Fixed. o pixellate.owin Crashed, unpredictably, if the pixel raster had unequal numbers of rows and columns. [Spotted by Rasmus Waagepetersen.] Fixed. o vcov.ppm Crashed for pairwise interaction models fitted by method="logi". Fixed. o predict.ppm Crashed for models fitted by method="logi" if the model included external covariates. Fixed. o predict.ppm Crashed if the argument 'covariates' or 'data' in the original call to 'ppm' included entries that were not spatial covariates. [These entries were ignored by ppm but caused predict.ppm to crash.] Fixed. o simulate.kppm, rNeymanScott, rThomas, rMatClust Crashed randomly when simulating an inhomogeneous model. [Spotted by Philipp Hunziker.] Fixed. o bw.diggle In some extreme cases, generated an error message about `NaN values in Foreign function call.' [Spotted by Colin Beale.] Fixed. o textureplot Crashed if 'spacing' was too large. Fixed. o superimpose.psp Crashed if the result was empty. Fixed. o istat Crashed with an error message about 'vars'. Fixed. o dirichlet, delaunay, delaunay.distance Crashed in rare cases due to a problem in package 'deldir'. [Spotted by Pierre Legendre.] Fixed. o rgbim, hsvim Crashed if any argument was constant. Fixed. o scaletointerval Crashed if x was constant. Fixed. o linnet, [.linnet Crashed if the result contained only a single vertex. [Spotted by Daniel Esser.] Fixed. o plot.fv If some of the function values were NA, they were replaced by fictitious values (by linearly interpolating). Fixed. o crossdist.ppp Ignored argument 'squared' if periodic=FALSE. [Spotted by Mike Porter.] Fixed. o marks<-.ppp Ignored argument 'drop'. [Spotted by Oscar Garcia.] Fixed. o update.ppm Sometimes did not respect the argument 'use.internal'. Fixed. o plot.rhohat Did not respect the argument 'limitsonly'. Fixed. o contour.im Argument 'axes' defaulted to TRUE, but FALSE was intended. Fixed. o print.hyperframe, as.data.frame.hyperframe Column names were mangled if the hyperframe had a single row. Fixed. o as.psp.data.frame Generated a warning about partially-matched names in a data frame. [Spotted by Eric Gilleland.] Fixed. o plot.leverage.ppm Generated a warning from 'contour.default' if the leverage function was constant. Fixed. o plot.diagppm Issued warnings about unrecognised graphics parameters. Fixed. o update.symbolmap Discarded information about the range of input values. Fixed. o plot.fv Label for y axis was garbled, if argument 'shade' was given. Fixed. o plot.ppp The legend was sometimes plotted when it should not have been (e.g. when add=TRUE). Fixed. o plot.listof, plot.im In an array of plots, containing both images and other spatial objects, the titles of the panels were not correctly aligned. Fixed. o plot.tess, plot.quadratcount Ignored arguments like 'cex.main'. Fixed. o iplot Navigation buttons (Left, Right, Up, Down, Zoom In, Zoom Out) did not immediately refresh the plot. Fixed. o iplot.layered Reported an error 'invalid argument type' if all layers were deselected. Fixed. CHANGES IN spatstat VERSION 1.37-0 OVERVIEW o Ege Rubak is now a joint author of spatstat. o We thank Peter Forbes, Tom Lawrence and Mikko Vihtakari for contributions. o Spatstat now exceeds 100,000 lines of code. o New syntax for point process models (ppm, kppm, lppm) equivalent to syntax of lm, glm, ... o Covariates in ppm and kppm can now be tessellations. o Confidence intervals and prediction intervals for fitted models. o Quasirandom point patterns and sequences. o Plots using texture fill. o Support for mappings from data to graphical symbols and textures. o Automatic re-fitting of model in Ginhom, Kinhom, Finhom, Jinhom. o Support for Mixed Poisson distribution. o Interpretation of mark scale parameters has changed in plot.ppp o Syntax of multitype interactions (eg MultiStrauss) has changed. o Bug fix in Metropolis-Hastings simulation of 'StraussHard' models o Changed default behaviour of perfect simulation algorithms. o Improvements to layout of text output. o Version nickname: 'Model Prisoner' NEW CLASSES o symbolmap An object of class 'symbolmap' represents a mapping from data to graphical symbols o texturemap An object of class 'texturemap' represents a mapping from data to graphical textures. NEW FUNCTIONS o split.hyperframe, split<-.hyperframe methods for split and split<- for hyperframes. o dmixpois, pmixpois, qmixpois, rmixpois (log-)normal mixture of Poisson distributions. o vdCorput, Halton, Hammersley, rQuasi quasirandom sequences and quasirandom point patterns. o Smoothfun create a function(x,y) equivalent to the result of Smooth.ppp o minnndist, maxnndist Faster ways to compute min(nndist(X)), max(nndist(X)) o add.texture Draw a simple texture inside a specified region. o textureplot Display a factor-valued pixel image using texture fill. o texturemap Create a texture map o plot.texturemap Plot a texture map in the style of a legend o symbolmap Create a symbol map o update.symbolmap Modify a symbol map o invoke.symbolmap Apply symbol map to data values, and plot them o plot.symbolmap Plot the symbol map in the style of a legend o as.owin.boxx Converts a 'boxx' to an 'owin' if possible. o ellipse Create an elliptical window. o clickbox Interactively specify a rectangle, by point-and-click on a graphics device. o complementarycolour Compute the complementary colour value of a given colour value, or the complementary colour map of a given colour map. o gauss.hermite Gauss-Hermite quadrature approximation to the expectation of any function of a normally-distributed random variable. o boundingbox Generic function, replaces bounding.box o edges Extract boundary edges of a window. Replaces and extends 'as.psp.owin' o pixelcentres Extract centres of pixels as a point pattern. SIGNIFICANT USER-VISIBLE CHANGES o ppm, kppm, lppm NEW SYNTAX FOR POINT PROCESS MODELS The model-fitting functions 'ppm', 'kppm' and 'lppm' now accept a syntax similar to 'lm' or 'glm', for example ppm(X ~ Z), but still accept the older syntax ppm(X, ~Z). To support both kinds of syntax, the functions 'ppm' and 'kppm' are now generic, with methods for the classes 'formula', 'ppp' and 'quad'. The 'formula' method handles a syntax like ppm(X ~ Z) while the 'ppp' method handles the old syntax ppm(X, ~Z). Similarly 'lppm' is generic with methods for 'formula' and 'lpp'. o ppm, kppm, lppm Covariates appearing in the model formula can be objects which exist in the R session, instead of always having to be elements of the list `covariates'. o ppm.formula, kppm.formula, lppm.formula Formulae involving polynom() are now expanded, symbolically, so that polynom(x, 3) becomes x + I(x^2) + I(x^3) and polynom(x,y,2) becomes x + y + I(x^2) + I(x*y) + I(y^2). This neatens the model output, and also makes it possible for anova() and step() to add or delete single terms in the polynomial. o predict.ppm New argument 'interval' allows confidence intervals or prediction intervals to be calculated. o predict.ppm New argument 'total' allows for prediction of the total number of points in a specified region. o plot.ppp, plot.lpp For marked point patterns, a legend is automatically added to the plot, by default. Arguments have changed: new arguments include parameters of the legend, and an optional symbol map. Result has changed: it is now an object of class 'symbolmap'. o plot.ppp, plot.lpp Interpretation of the parameters 'markscale' and 'maxsize' has changed. The size of a circle in the plot is now defined as the circle's diameter instead of its radius. (Size of a square is measured, as before, by its side length). o parres Now handles the case where the fitted model is not separable but its restriction to the given 'subregion' is separable. o envelope Now issues a warning if the usage of envelope() appears to be `invalid' in the sense that the simulated patterns and the data pattern have not been treated equally. o Kinhom, Finhom, Ginhom, Jinhom New argument 'update'. If 'lambda' is a fitted model (class ppm or kppm) and update=TRUE, the model is re-fitted to the data pattern, before the intensities are computed. o rDiggleGratton, rDGS, rHardcore, rStrauss, rStraussHard By default the point pattern is now generated on a larger window, and trimmed to the original window. New argument expand=TRUE. o MultiStrauss, MultiHard, MultiStraussHard The syntax of these functions has changed. The new code should still accept the old syntax. o rhohat rhohat.ppp and rhohat.quad have new argument 'baseline' o ippm Algorithm improved. Argument syntax changed. o default.dummy, quadscheme Dummy points can now be generated by a quasirandom sequence. o plot.owin The window can now be filled with one of 8 different textures. Arguments changed. o ppm, kppm Covariates in the model can now be tessellations. o [.im New argument 'tight' allows the resulting image to be trimmed to the smallest possible rectangle. o [.psp, rlinegrid, rpoisline These functions now handle binary mask windows. o rotate The user can specify the centre of rotation. o rescale rescale() and all its methods now have argument 'unitname' which can be used to change the name of the unit of length. o anova.ppm Output format has been improved. Number of columns of result has changed. o print.ppp, print.summary.ppp, print.owin, print.summary.owin, print.im, print.summary.im, print.fv, print.msr, print.profilepl These functions now avoid over-running the text margin (i.e. they respect options('width') where possible). o layerplotargs<- Now handles any spatial object, converting it to a 'layered' object. o effectfun Improved display in case se.fit=TRUE. o scaletointerval New argument 'xrange' o contour.im New argument 'show.all'. Default value of 'axes' changed to FALSE. o identify.ppp Now handles multivariate marks. o plot.listof Improved layout. New arguments 'hsep', 'vsep'. Argument 'mar.panel' may have length 1, 2 or 4. o plot.splitppp This function is no longer identical to plot.listof. Instead it is a much simpler function which just calls plot.listof with equal.scales=TRUE. o anova.ppm Output is neater. o plot.layered New argument 'do.plot' o plot.psp New argument 'do.plot' o as.psp.owin New argument 'window' o plot.im, contour.im, textureplot New argument 'clipwin' o plot.ppp New argument 'clipwin' o plot.msr New argument 'how' allows density to be plotted as image and/or contour o diagnose.ppm, plot.diagppm More options for 'plot.neg' o plot.leverage.ppm, plot.influence.ppm, plot.msr Argument 'clipwin' can now be used to restrict the display to a subset of the full data. o [.hyperframe, [<-.hyperframe, $.hyperframe, $<-.hyperframe These functions are now documented. o leverage.ppm, influence.ppm, dfbetas.ppm Resulting objects are now smaller (in memory size). o print.ppm Now indicates whether the irregular parameters 'covfunargs' were optimised (by profilepl or ippm) or whether they were simply provided by the user. o plot.ppp A point pattern with numerical marks can now be plotted as filled dots with colours determined by the marks, by setting pch=21 and bg= o colourmap Now handles dates and date-time values (of class 'Date' or 'POSIXt'). o plot.ppp, print.ppp, summary.ppp Improved handling of dates and date-time values (of class 'Date' or 'POSIXt') in the marks of a point pattern. o cut.im Now refuses to handle images whose pixel values are factor, logical or character. o centroid.owin New argument 'as.ppp' o superimpose Improved default names for columns of marks. o Softcore() Improved printout. o kppm, lgcp.estpcf, lgcp.estK Adjusted to new structure of RandomFields package. No change in syntax. o data(murchison) This dataset now belongs to class 'listof' so that it can be plotted directly. o data(clmfires) The format of the covariate data has changed. The objects 'clmcov100' and 'clmcov200' are now elements of a list 'clmfires.extra'. o bounding.box This function is now Deprecated; it has been replaced by the generic boundingbox(). o as.psp.owin This function is now Deprecated; it has been replaced and extended by the function edges(). o plot.kstest Changed defaults so that the two curves are distinguishable. o with.fv Improved mathematical labels. BUG FIXES o intensity.quadratcount Values were incorrect for a rectangular tessellation (the matrix of intensities was transposed). Fixed. o rmh, simulate.ppm Simulation of the Strauss-hard core model (StraussHard) was incorrect (intensity of the simulated process was about 15% too low). Bug introduced in spatstat 1.31-0 (January 2013). o intensity.quadratcount Crashed for a rectangular tessellation with only a single row or column. Fixed. o model.images.ppm Crashed sometimes if the argument W was given. Fixed. o eval.im Crashed when applied to images with only a single row or column. Fixed. o ppp, marks<-.ppp If the marks were a vector of dates, they were erroneously converted to numbers. Fixed. o ippm Crashed if the model formula included an offset term that was not a function. Fixed. o leverage.ppm Crashed sometimes when the model had irregular parameters ('covfunargs'). Fixed. o residuals.ppm Crashed sometimes when type='score'. Fixed. o scaletointerval Did not handle dates and date-time values correctly. Fixed. o rbind.hyperframe, as.list.hyperframe Gave incorrect results for hyperframes with 1 row. Fixed. o Kinhom Did not renormalise the result (even when renormalise=TRUE), in some cases. Spotted by Peter Forbes. Fixed. o disc If mask=TRUE the disc was erroneously clipped to the square [-1,1] x [-1,1]. Fixed. o plot.fv Sometimes shaded the wrong half of the graph when the 'shade' coordinates were infinite. Fixed. o print.ppm Gave an error message if the coefficient vector had length zero. Fixed. o vcov.ppm Gave an error message if the coefficient vector had length zero. Fixed. o plot.distfun, as.im.distfun These functions effectively ignored the argument 'invert' in the original call to distfun. Fixed. o plot.msr Ignored certain additional arguments such as 'pch'. Fixed. o cut.im Crashed if the image had 1 row or 1 column of pixels. Fixed. o iplot.ppp Crashed with message about missing object 'vals'. Fixed. o effectfun Demanded a value for every covariate supplied in the original call to ppm, even for covariates which were not used in the model. Fixed. o plot.listof, plot.hyperframe When plotting 3D point patterns (class pp3), these functions issued warnings about 'add' being an unrecognised graphics argument. Fixed. CHANGES IN spatstat VERSION 1.36-0 OVERVIEW o We thank Sebastian Meyer, Kevin Ummer, Jean-Francois Coeurjolly, Ege Rubak, Rasmus Waagepetersen, Oscar Garcia and Sourav Das for contributions. o Important change to package dependencies. o Geometrical inconsistencies in polygons are now repaired automatically. o Improved quadrature schemes and reduced bias in ppm. o New vignette 'Summary of Recent Changes to Spatstat'. o Approximation to K function and pcf for Gibbs models. o Counterpart of 'apply' for lists of images. o Hexagonal grids and tessellations. o Extensions to scan test and Allard-Fraley cluster set estimator. o Change the parameters of a fitted model before simulating it. o Accelerated Kest, Kinhom for rectangular windows. o Extensions and improvements to plotting functions. o Improvements to labelling of 'fv' objects. o New demo of summary functions. o More methods for 'intensity'. o Version nickname: 'Intense Scrutiny' NEW FUNCTIONS o Kmodel.ppm, pcfmodel.ppm Compute approximation to K-function or pair correlation function of a Gibbs point process model. o im.apply Apply a function to corresponding pixel values in several images. o hexgrid, hextess Create a hexagonal grid of points, or a tessellation of hexagonal tiles o shift.tess, rotate.tess, reflect.tess, scalardilate.tess, affine.tess Apply a geometrical transformation to a tessellation. o quantile.ewcdf Extract quantiles from a weighted cumulative distribution function. o scanLRTS Evaluate the spatially-varying test statistic for the scan test. o pcfmulti General multitype pair correlation function o intensity.splitppp Estimate intensity in each component of a split point pattern. o intensity.quadratcount Use quadrat counts to estimate intensity in each quadrat. o as.owin.quadratcount, as.owin.quadrattest Extract the spatial window in which quadrat counts were performed. o reload.or.compute Utility function for R scripts: either reload results from file, or compute them. o to.grey Convert colour to greyscale. o Smooth.im Method for Smooth() for pixel images. Currently identical to blur(). o demo(sumfun) Demonstration of nonparametric summary functions in spatstat. SIGNIFICANT USER-VISIBLE CHANGES o Package Dependencies spatstat now "Imports" (rather than "Depends" on) the libraries mgcv, deldir, abind, tensor, polyclip. This means that these libraries are not accessible to the user unless the user explicitly loads them by typing 'library(mgcv)' and so on. o owin, as.owin Polygon data are no longer subjected to strict checks on geometrical validity (self-crossing points, overlaps etc.) Instead, polygon geometry is automatically repaired. o ppm The default quadrature scheme for a point pattern has been improved (in the case of a non-rectangular window) to remove a possible source of bias. o Performance various parts of spatstat now run slightly faster. o scan.test Now handles multiple values of circle radius 'r'. o plot.scan.test, as.im.scan.test These functions can now give the optimal value of circle radius 'r'. o pcfcross, pcfdot Algorithms have been reimplemented using a single-pass kernel smoother and now run much faster. Bandwidth selection rule improved. o plot.listof, plot.splitppp Default behaviour has changed: panels are now plotted on different scales. o plot.listof, plot.splitppp When 'equal.scales=TRUE' the panels are plotted on exactly equal scales and are exactly aligned (under certain conditions). o ppp, marks.ppp, marks<-.ppp New argument 'drop' determines whether a data frame with a single column will be converted to a vector. o simulate.ppm, rmh.ppm, rmhmodel.ppm New argument 'new.coef' allows the user to change the parameters of a fitted model, before it is simulated. o logLik.ppm New argument 'new.coef' allows the user to evaluate the loglikelihood for a different value of the parameter. o clusterset The argument 'result' has been renamed 'what'. It is now possible to give multiple values to 'what' so that both types of result can be computed together. o residuals.ppm Argument 'coefs' has been renamed 'new.coef' for consistency with fitted.ppm etc. o residuals.ppm If drop=TRUE the window associated with the residuals is now taken to be the domain of integration of the composite likelihood. o intensity.ppp Now has argument 'weights' o density.ppp, Smooth.ppp, markmean, markvar, intensity.ppp Argument 'weights' can now be an 'expression'. o pcf New argument 'domain' causes the computation to be restricted to a subset of the window. o nnclean The result now has attributes which give the fitted parameter values, information about the fitting procedure, and the histogram bar heights. o nnclean Extra arguments are now passed to hist.default. o plot.tess For a tessellation represented by a pixel image, plot.tess no longer treats the pixel labels as palette colours. o relrisk New argument 'case' allows the user to specify which mark value corresponds to the cases in a case-control dataset. o Kinhom Now accepts correction="good" o spatstat.options New option ('monochrome') controls whether plots generated by spatstat will be displayed in colour or in greyscale. This will eventually be applied to all plot commands in spatstat. o plot.im, persp.im, contour.im, plot.owin, plot.psp, plot.fv, plot.fasp These functions now obey spatstat.options('monochrome') o plot.ppp, plot.owin, plot.im, plot.psp, plot.tess, plot.layered New universal argument 'show.all' determines what happens when a plot is added to an existing plot. If show.all = TRUE then everything is plotted, including the main title and colour ribbon. o plot.ppp New argument 'show.window' o plot.im New arguments 'add' and 'do.plot'. More arguments recognised by 'ribargs' o plot.layered New arguments 'add', 'main' Better argument handling. o plot.fv Improved handling of argument 'shade' o layered, layerplotargs, plot.layered The plotting argument can now be a list of length 1, which will be replicated to the correct length. o varblock Ugly legends have been repaired. o quad.ppm New argument 'clip' o edge.Trans New arguments 'dx', 'dy' o disc Argument 'centre' can be in various formats. o affine, shift Argument 'vec' can be in various formats. o Geyer, BadGey A warning is no longer issued when the parameter 'sat' is fractional. o adaptive.density Now has argument 'verbose' o Smooth.ppp 'sigma' is now a formal argument of Smooth.ppp o plot.quadratcount, plot.quadrattest These functions have now been documented. o Summary functions and envelopes Improved mathematical labels in plots. o Kest Accelerated, in the case of a rectangular window. o Kscaled Argument 'lambda' can now be a fitted model (class ppm) o print.fv Improved layout. o plot.bermantest Improved graphics. o which.max.im This function is now deprecated. which.max.im(x) is superseded by im.apply(x, which.max) o smooth.ppp, smooth.fv, smooth.msr These functions are now deprecated, in favour of 'Smooth' with a capital 'S' BUG FIXES o bw.ppl Crashed if the point pattern had multiple points at the same location. Fixed. o quantile Crashed when applied to the result of 'ewcdf'. Fixed. o marks<-.ppp Crashed with a message about 'unrecognised format' if the current or replacement values of marks were date/time values (belonging to class 'Date' or 'POSIXt'). Fixed. o plot.im Crashed in case log=TRUE if the window was not a rectangle. Fixed. o vcov.ppm Crashed sometimes for models with a hard core term (Hardcore, StraussHard, MultiHard or MultiStrauss interactions). Spotted by Rasmus Waagepetersen. Fixed. o multiplicity.data.frame Results were incorrect and included NA's (spotted by Sebastian Meyer). Fixed. o markvar Values were incorrect. Fixed. o Smooth.ppp Ignored argument 'diggle'. Fixed. o rotate.im, affine.im Factor-valued images were not handled correctly. Fixed. o shift.layered If argument 'origin' was used, different layers were shifted by different amounts. Fixed. o tile.areas Sometimes returned a list instead of a numeric vector. Fixed. o print.ppp If the marks were date/time values (belonging to class 'Date' or 'POSIXt'), print.ppp reported that they were double precision numbers. Fixed. o plot.layered Graphics were mangled if the argument 'add=FALSE' was given explicitly. Fixed. o Smooth.ppp The argument 'sigma' was only recognised if it was explicitly named. For example in 'Smooth(X, 5)' the '5' was ignored. Fixed. o clusterset The bounding frame of the result was smaller than the original bounding frame of the point pattern dataset, when result="domain" and exact=TRUE. Fixed. o plot.im Ignored argument 'col' if it was a 'function(n)'. Fixed. o Kinhom Ignored argument 'correction' if there were more than 1000 points. Fixed. o [.fv Mangled the plot label for the y axis. Fixed. o cbind.fv Mangled the plot label for the y axis. Fixed. o plot.envelope Main title was always 'x'. Fixed. o print.ppp Ran over the right margin. Fixed. o union.owin, intersect.owin, setminus.owin Sometimes deleted the name of the unit of length. Fixed. CHANGES IN spatstat VERSION 1.35-0 OVERVIEW o We thank Melanie Bell, Leanne Bischof, Ida-Maria Sintorn, Ege Rubak, Martin Hazelton, Oscar Garcia, Rasmus Waagepetersen, Abdollah Jalilian and Jens Oehlschlaegel for contributions. o Support for analysing replicated spatial point patterns. o New vignette on analysing replicated spatial point patterns. o Objective function surface plots. o Estimator of point process intensity using nearest neighbour distances. o Improved estimator of pair correlation function. o Four new datasets. o Simple point-and-click interface functions for general use. o More support for fv objects. o More support for ppx objects. o Extensions to nearest neighbour functions. o Morphological operations accelerated. o Bug fix to pair correlation functions. o Bug fix to k-th nearest neighbour distances o Version nickname: 'Multiple Personality' NEW CLASSES o mppm An object of class 'mppm' represents a Gibbs point process model fitted to several point pattern datasets. The point patterns may be treated as independent replicates of the same point process, or as the responses in an experimental design, so that the model may depend on covariates associated with the design. Methods for this class include print, plot, predict, anova and so on. o objsurf An object of class 'objsurf' contains values of the likelihood or objective function in a neighbourhood of the maximum. o simplepanel An object of class 'simplepanel' represents a spatial arrangement of buttons that respond to mouse clicks, supporting a simple, robust graphical interface. NEW FUNCTIONS o mppm Fit a Gibbs model to several point patterns. The point pattern data may be organised as a designed experiment and the model may depend on covariates associated with the design. o anova.mppm Analysis of Deviance for models of class mppm o coef.mppm Extract fitted coefficients from a model of class mppm o fitted.mppm Fitted intensity or conditional intensity for a model of class mppm o kstest.mppm Kolmogorov-Smirnov test of goodness-of-fit for a model of class mppm o logLik.mppm log likelihood or log pseudolikelihood for a model of class mppm o plot.mppm Plot the fitted intensity or conditional intensity of a model of class mppm o predict.mppm Compute the fitted intensity or conditional intensity of a model of class mppm o quadrat.test Quadrat counting test of goodness-of-fit for a model of class mppm o residuals.mppm Point process residuals for a model of class mppm o subfits Extract point process models for each individual point pattern dataset, from a model of class mppm o vcov.mppm Variance-covariance matrix for a model of class mppm o integral.msr Integral of a measure. o objsurf For a model fitted by optimising an objective function, this command computes the objective function in a neighbourhood of the optimal value. o contour.objsurf, image.objsurf, persp.objsurf, plot.objsurf Plot an 'objsurf' object. o fvnames Define groups of columns in a function value table, for use in plot.fv, etc o multiplicity New generic function for which multiplicity.ppp is a method. o unique.ppx, duplicated.ppx, multiplicity.ppx Methods for unique(), duplicated() and multiplicity() for 'ppx' objects. These also work for 'pp3' and 'lpp' objects. o closepairs, crosspairs, closepaircounts, crosspaircounts Low-level functions for finding all close pairs of points o nndensity Estimate point process intensity using k-th nearest neighbour distances o simplepanel, run.simplepanel Support for a simple point-and-click interface for general use. NEW DATASETS o pyramidal Diggle-Lange-Benes data on pyramidal neurons in cingulate cortex. 31 point patterns divided into 3 groups. o waterstriders Nummelin-Penttinen waterstriders data. Three independent replicates of a point pattern formed by insects. o simba Simulated data example for mppm. Two groups of point patterns with different interpoint interactions. o demohyper Simulated data example for mppm. Point patterns and pixel image covariates, in two groups with different regression coefficients. SIGNIFICANT USER-VISIBLE CHANGES o plot.hyperframe The argument 'e' now has a different format. Instead of plot(h, plot(XYZ)) one must now type plot(h, quote(plot(XYZ))) This is necessary in order to avoid problems with 'S4 method dispatch'. o pcf.ppp, pcfinhom New argument 'divisor' enables better performance of the estimator of pair correlation function for distances close to zero. o applynbd The arguments N, R and criterion may now be specified together. o markstat The arguments N and R may now be specified together. o ppx New argument 'simplify' allows the result to be converted to an object of class 'ppp' or 'pp3' if appropriate. o as.function.fv Now allows multiple columns to be interpolated o multiplicity.ppp This function is now a method for the generic 'multiplicity'. It has also been accelerated. o nnfun.ppp, distfun.ppp New argument 'k' allows these functions to compute k-th nearest neighbours. o rVarGamma, kppm, vargamma.estK, vargamma.estpcf New argument 'nu.pcf' provides an alternative way to specify the kernel shape in the VarGamma model, instead of the existing argument 'nu.ker'. Function calls that use the ambiguous argument name 'nu' will no longer be accepted. o nnmap Image is now clipped to the original window. o dilation, erosion, opening, closing Polygonal computations greatly accelerated. o plot.colourmap Improved appearance and increased options, for discrete colourmaps. o plot.msr Improved appearance o plot.ppp, plot.owin An `empty' plot can now be generated by setting type="n" o nndist.ppp, nnwhich.ppp, nncross.ppp Column names of the result are now more informative. BUG FIXES o nncross.ppp Results were completely incorrect when k > 1. Spotted by Jens Oehschlaegel. Bug was introduced in spatstat 1.34-1. Fixed. o rVarGamma Simulations were incorrect; they were generated using the wrong value of the parameter 'nu.ker'. Spotted by Rasmus Waagepetersen and Abdollah Jalilian. Bug was always present. Fixed. o pair correlation functions (pcf.ppp, pcfdot, pcfcross, pcfinhom, ...) The result had a negative bias at the maximum 'r' value, because contributions to the pcf estimate from interpoint distances greater than max(r) were mistakenly omitted. Spotted by Rasmus Waagepetersen and Abdollah Jalilian. Bug was always present. Fixed. o demo(spatstat) This demonstration script had some unwanted side-effects, such as rescaling the coordinates of standard datasets 'bramblecanes', 'amacrine' and 'demopat', which caused the demonstration to crash when it was repeated several times, and caused errors in demo(data). Fixed. o rmh Visual debugger crashed sometimes with message 'XI not found'. Fixed. o predict.ppm Crashed if the model was fitted using 'covfunargs'. Fixed. o bounding.box Crashed if one of the arguments was NULL. Fixed. o multiplicity.ppp Did not handle data frames of marks. Fixed. CHANGES IN spatstat VERSION 1.34-1 OVERVIEW o We thank Kurt Hornik, Ted Rosenbaum, Ege Rubak and Achim Zeileis for contributions. o Important bug fix. SIGNIFICANT USER-VISIBLE CHANGES o as.box3 Now accepts objects of class 'ppx' or 'boxx'. o crossdist.ppp, crossdist.pp3, crossdist.default New argument 'squared' allows the squared distances to be computed (saving computation time in some applications) BUG FIXES o union.owin, is.subset.owin, dilation.owin Results were sometimes completely wrong for polygons with holes. Spotted by Ted Rosenbaum. Fixed. o psstA, areaLoss Crashed in some cases, with error message 'Number of items to replace is not a multiple of replacement length'. Spotted by Achim Zeileis. Fixed. CHANGES IN spatstat VERSION 1.34-0 OVERVIEW o We thank Andrew Bevan, Ege Rubak, Aruna Jammalamadaka, Greg McSwiggan, Jeff Marcus, Jose M Blanco Moreno, and Brian Ripley for contributions. o spatstat and all its dependencies are now Free Open Source. o spatstat does not require the package 'gpclib' any more. o spatstat now depends on the packages 'tensor', 'abind' and 'polyclip' o polygon clipping is now enabled always. o Substantially more support for point patterns on linear networks. o Faster computations for pairwise interaction models. o Bug fixes in nearest neighbour calculations. o Bug fix in leverage and influence diagnostics. o Version nickname: "Window Cleaner" o spatstat now requires R version 3.0.2 or later NEW FUNCTIONS o as.lpp Convert data to a point pattern on a linear network. o distfun.lpp Distance function for point pattern on a linear network. o eval.linim Evaluate expression involving pixel images on a linear network. o linearKcross, linearKdot, linearKcross.inhom, linearKdot.inhom Multitype K functions for point patterns on a linear network o linearmarkconnect, linearmarkequal Mark connection function and mark equality function for multitype point patterns on a linear network o linearpcfcross, linearpcfdot, linearpcfcross.inhom, linearpcfdot.inhom Multitype pair correlation functions for point patterns on a linear network o linfun New class of functions defined on a linear network o nndist.lpp, nnwhich.lpp, nncross.lpp Methods for nndist, nnwhich, nncross for point patterns on a linear network o nnfun.lpp Method for nnfun for point patterns on a linear network o vcov.lppm Variance-covariance matrix for parameter estimates of a fitted point process model on a linear network. o bilinearform Computes a bilinear form o tilenames, tilenames<- Extract or change the names of tiles in a tessellation. SIGNIFICANT USER-VISIBLE CHANGES o package dependencies Previous versions of spatstat used the package 'gpclib' to perform geometrical calculations on polygons. Spatstat now uses the package 'polyclip' for polygon calculations instead. o free open-source licence The restrictive licence conditions of 'gpclib' no longer apply to users of spatstat. Spatstat and all its dependencies are now covered by a free open-source licence. o polygon clipping In previous versions of spatstat, geometrical calculations on polygons could be performed 'exactly' using gpclib or 'approximately' using pixel discretisation. Polygon calculations are now always performed 'exactly'. o intersect.owin, union.owin, setminus.owin If A and B are polygons, the result is a polygon. o erosion, dilation, opening, closing If the original set is a polygon, the result is a polygon. o intersect.tess, dirichlet The tiles of the resulting tessellation are polygons if the input was polygonal. o plot.owin Polygons with holes can now be plotted with filled colours on any device. o lppm New arguments 'eps' and 'nd' control the quadrature scheme. o pairwise interaction Gibbs models Many calculations for these models have been accelerated. BUG FIXES o nncross.pp3 Values were completely incorrect in some cases. Usually accompanied by a warning about NA values. (Spotted by Andrew Bevan.) Fixed. o nnmap, nnmark A small proportion of pixels had incorrect values. [These were the pixels lying on the boundary of a Dirichlet cell.] Fixed. o leverage.ppm, influence.ppm, dfbetas.ppm Results were incorrect for non-Poisson processes. Fixed. o distcdf Results were incorrect in some cases when W was a window and V was a point pattern. Fixed. o Kcross, Kdot, pcfcross, pcfdot Results were incorrect in some rare cases. Fixed. o as.fv.kppm Erroneously returned a NULL value. Fixed. o vcov.ppm For point process models fitted with method = 'logi', sometimes crashed with error "object 'fit' not found". (Spotted by Ege Rubak). Fixed. o vcov.ppm For multitype point process models, sometimes crashed with error "argument 'par' is missing". Fixed. o plot.im Crashed if some of the pixel values were infinite. Fixed. o owin owin(poly=..) crashed if there were NA's in the polygon coordinates. Spotted by Jeff Marcus. Fixed. o plot.fv Crashed, giving an incomprehensible error, if the plot formula contained a number with a decimal point. Fixed. o alltypes Crashed if envelopes=TRUE and global=TRUE, with error message 'csr.theo not found'. Spotted by Jose M Blanco Moreno. Fixed. o chop.tess, rMosaicField Format of result was garbled in some cases. Fixed. o vcov.ppm Sometimes gave an irrelevant warning "parallel option not available". Fixed. CHANGES IN spatstat VERSION 1.33-0 OVERVIEW o We thank Kurt Hornik and Brian Ripley for advice. o The package namespace has been modified. o Numerous internal changes. o Likelihood cross-validation for smoothing bandwidth. o More flexible models of intensity in cluster/Cox processes. o New generic function for smoothing. o Version nickname: 'Titanic Deckchair' NEW FUNCTIONS o bw.ppl Likelihood cross-validation technique for bandwidth selection in kernel smoothing. o is.lppm, is.kppm, is.slrm Tests whether an object is of class 'lppm', 'kppm' or 'slrm' o Smooth New generic function for spatial smoothing. o Smooth.ppp, Smooth.fv, Smooth.msr Methods for Smooth (identical to smooth.ppp, smooth.fv, smooth.msr respectively) o fitted.kppm Method for 'fitted' for cluster/Cox models SIGNIFICANT USER-VISIBLE CHANGES o namespace The namespace of the spatstat package has been changed. o internal functions Some undocumented internal functions are no longer visible, as they are no longer exported in the namespace. These functions can still be accessed using the form spatstat:::functionname. Functions that are not visible are not guaranteed to exist or to remain the same in future. o methods For some generic functions defined in the spatstat package, it is possible that R may fail to find one of the methods for the generic. This is a temporary problem due to a restriction on the size of the namespace in R 3.0.1. It will be fixed in future versions of R and spatstat. It only applies to methods for a generic which is a spatstat function (such as nndist) and does not apply to methods for generics defined elsewhere (such as density). In the meantime, if this problem should occur, it can be avoided by calling the method explicitly, in the form spatstat:::genericname.classname. o speed The package should run slightly faster overall, due to the improvement of the namespace, and changes to internal code. o envelope New argument 'envir.simul' determines the environment in which to evaluate the expression 'simulate'. o kppm More flexible models of the intensity, and greater control over the intensity fitting procedure, are now possible using the arguments 'covfunargs', 'use.gam', 'nd', 'eps' passed to ppm. Also the argument 'X' may now be a quadrature scheme. o distcdf Arguments W and V can now be point patterns. o Kest New option: correction = "good" selects the best edge correction that can be computed in reasonable time. o bw.diggle Accelerated. o predict.ppm Calculation of standard error has been accelerated. o smooth.ppp, smooth.fv, smooth.msr These functions will soon be 'Deprecated' in favour of the methods Smooth.ppp, Smooth.fv, Smooth.msr respectively. o stratrand, overlap.owin, update.slrm, edge.Trans, edge.Ripley These already-existing functions are now documented. BUG FIXES o kppm, matclust.estpcf, pcfmodel The pair correlation function of the Matern Cluster Process was evaluated incorrectly at distances close to 0. This could have affected the fitted parameters in matclust.estpcf() or kppm(clusters="MatClust"). Fixed. o anova.ppm Would cause an error in future versions of R when 'anova.glm' is removed from the namespace. Fixed. CHANGES IN spatstat VERSION 1.32-0 OVERVIEW o We thank Ege Rubak for major contributions. o Thanks also to Patrick Donnelly, Andrew Hardegen, Tom Lawrence, Robin Milne, Gopalan Nair and Sean O'Riordan. o New 'logistic likelihood' method for fitting Gibbs models. o Substantial acceleration of several functions including profile maximum pseudolikelihood and variance calculations for Gibbs models. o Nearest neighbours for point patterns in 3D o Nearest-neighbour interpolation in 2D o New 'progress plots' o Hard core thresholds can be estimated automatically. o More support for colour maps o More support for 'fv' objects o Spatstat now has version nicknames. The current version is "Logistical Nightmare". o Minor improvements and bug fixes. NEW FUNCTIONS o nncross.pp3 Method for 'nncross' for point patterns in 3D o nnmark Mark of nearest neighbour - can be used for interpolation o dclf.progress, mad.progress Progress plots (envelope representations) for the DCLF and MAD tests. o deriv.fv Numerical differentiation for 'fv' objects. o interp.colourmap Smooth interpolation of colour map objects - makes it easy to build colour maps with gradual changes in colour o tweak.colourmap Change individual colour values in a colour map object o beachcolourmap Colour scheme appropriate for `altitudes' (signed numerical values) o as.fv Convert various kinds of data to an 'fv' object o quadscheme.logi Generates quadrature schemes for the logistic method of ppm. o beginner Introduction for beginners. SIGNIFICANT USER-VISIBLE CHANGES o ppm New option: method = "logi" Fits a Gibbs model by the newly developed 'logistic likelihood' method which is often faster and more accurate than maximum pseudolikelihood. Code contributed by Ege Rubak. o profilepl Greatly accelerated, especially for area-interaction models. o vcov.ppm Greatly accelerated for higher-order interaction models. o smooth.ppp Now handles bandwidths equal to zero (by invoking 'nnmark') o Hardcore, StraussHard The hard core distance 'hc' can now be omitted; it will be estimated from data. o plot.ppp Now behaves differently if there are multiple columns of marks. Each column of marks is plotted, in a series of separate plots arranged side-by-side. o plot.im Argument 'col' can now be a function o lohboot Now computes confidence intervals for L-functions as well (fun="Lest" or fun="Linhom") o dclf.test, mad.test The argument X can now be an object produced by a previous call to dclf.test or mad. o plot.fv Labelling of plots has been improved in some cases. o smooth.fv Further options added. o density.ppp The argument 'weights' can now be a matrix. o smooth.ppp Accelerated, when there are several columns of marks. o density.ppp Accelerated slightly. o simulate.ppm, simulate.kppm The total computation time is also returned. o simulate.kppm Now catches errors (such as 'insufficient memory'). o latest.news, licence.polygons Can now be executed by typing the name of the function without parentheses. o latest.news The text is now displayed one page at a time. BUG FIXES o Hest, Gfox, Jfox The 'raw' estimate was not computed correctly (or at least it was not the raw estimate described in the help files). Spotted by Tom Lawrence. Fixed. o edges2vees Format of result was incorrect if there were fewer than 3 edges. Fixed. o Jfox The theoretical value (corresponding to independence between X and Y) was erroneously given as 0 instead of 1. Spotted by Patrick Donnelly. Fixed. o ppm, quadscheme, default.dummy If the grid spacing parameter 'eps' was specified, the quadrature scheme was sometimes slightly incorrect (missing a few dummy points near the window boundary). Fixed. o print.timed Matrices were printed incorrectly. Fixed. CHANGES IN spatstat VERSION 1.31-3 OVERVIEW o spatstat now 'Suggests' the package 'tensor' o Code slightly accelerated. o More support for pooling of envelopes. o Bug fixes. NEW FUNCTIONS o nnmap Given a point pattern, finds the k-th nearest point in the pattern from each pixel in a raster. o coef.fii, coef.summary.fii Extract the interaction coefficients of a fitted interpoint interaction o edges2vees Low-level function for finding triples in a graph. SIGNIFICANT USER-VISIBLE CHANGES o predict.ppm New argument 'correction' allows choice of edge correction when calculating the conditional intensity. o pool.envelope New arguments 'savefuns' and 'savepatterns'. o pool.envelope Envelopes generated with VARIANCE=TRUE can now be pooled. o pool.envelope The plot settings of the input data are now respected. o Numerous functions have been slightly accelerated. BUG FIXES o predict.ppm Calculation of the conditional intensity omitted the edge correction if correction='translate' or correction='periodic'. Fixed. o shift.lpp, rotate.lpp, scalardilate.lpp, affine.lpp, shift.linnet, rotate.linnet, scalardilate.linnet, affine.linnet The enclosing window was not correctly transformed. Fixed. o rHardcore, rStraussHard, rDiggleGratton, rDGS The return value was invisible. Fixed. o ppm In rare cases the results obtained with forcefit=FALSE and forcefit=TRUE were different, due to numerical rounding effects. Fixed. CHANGES IN spatstat VERSION 1.31-2 OVERVIEW o We thank Robin Corria Anslie, Julian Gilbey, Kiran Marchikanti, Ege Rubak and Thordis Linda Thorarinsdottir for contributions. o spatstat now depends on R 3.0.0 o More support for linear networks o More functionality for nearest neighbours o Bug fix in fitting Geyer model o Performance improvements and bug fixes NEW FUNCTIONS o affine.lpp, shift.lpp, rotate.lpp, rescale.lpp, scalardilate.lpp Geometrical transformations for point patterns on a linear network o affine.linnet, shift.linnet, rotate.linnet, rescale.linnet, scalardilate.linnet Geometrical transformations for linear networks o [.linnet Subset operator for linear networks o timed Records the computation time taken SIGNIFICANT USER-VISIBLE CHANGES o nncross nncross.ppp can now find the k-th nearest neighbours, for any k. o nndist, nnwhich New argument 'by' makes it possible to find nearest neighbours belonging to specified subsets in a point pattern, for example, the nearest neighbour of each type in a multitype point pattern. o [.fv Now handles the argument 'drop'. o with.fv Argument 'drop' replaced by new argument 'fun' (with different interpretation). o [.lpp Subset index may now be a window (class 'owin') o Kest Options correction='border' and correction='none' now run about 4 times faster, thanks to Julian Gilbey. o density.ppp Numerical underflow no longer occurs when sigma is very small and 'at="points"'. A warning is no longer issued. Thanks to Robin Corria Anslie. o crossing.psp New argument 'fatal' allows the user to handle empty intersections o union.owin It is now guaranteed that if A is a subset of B, then union.owin(A,B)=B. o plot.colourmap Now passes arguments to axis() to control the plot. Appearance of plot improved. o image.listof Now passes arguments to plot.colourmap() if equal.ribbon=TRUE. o kppm Accelerated (especially for large datasets). o plot.envelope plot.envelope is now equivalent to plot.fv and is essentially redundant. o rThomas, rMatClust, rNeymanScott Improved explanations in help files. o All functions Many functions have been slightly accelerated. BUG FIXES o ppm Results were incorrect for the Geyer saturation model with a non-integer value of the saturation parameter 'sat'. Spotted by Thordis Linda Thorarinsdottir. Bug introduced in spatstat 1.20-0, July 2010. Fixed. o ppm Fitting a stationary Poisson process using a nonzero value of 'rbord', as in "ppm(X, rbord=R)" with R > 0, gave incorrect results. Fixed. o predict.slrm Crashed with message 'longer object length is not a multiple of shorter object length' if the original data window was not a rectangle. Fixed. o iplot Main title was sometimes incorrect. Fixed. o plot.layered Ignored argument 'main' in some cases. Fixed. o plot.listof, image.listof Crashed sometimes with a message 'figure margins too large' when equal.ribbon=TRUE. Fixed. o print.ppx Crashed if the object contained local coordinates. Fixed. o transect.im Crashed if the transect lay partially outside the image domain. Fixed. o rthin Crashed if X was empty. Fixed. o max.im, min.im, range.im Ignored additional arguments after the first argument. Fixed. o update.lppm Updated object did not remember the name of the original dataset. Fixed. o envelope Grey shading disappeared from plots of envelope objects when the envelopes were transformed using eval.fv or eval.fasp. Fixed. CHANGES IN spatstat VERSION 1.31-1 OVERVIEW o We thank Marcelino de la Cruz, Daniel Esser, Jason Goldstick, Abdollah Jalilian, Ege Rubak and Fabrice Vinatier for contributions. o Nonparametric estimation and tests for point patterns in a linear network. o More support for 'layered' objects. o Find clumps in a point pattern. o Connected component interaction model. o Improvements to interactive plots. o Visual debugger for Metropolis-Hastings algorithm. o Bug fix in Metropolis-Hastings simulation of Geyer process. o Faster Metropolis-Hastings simulation. o Faster computation of 'envelope', 'fv' and 'fasp' objects. o Improvements and bug fixes. NEW FUNCTIONS o connected.ppp Find clumps in a point pattern. o kstest.lpp, kstest.lppm The spatial Kolmogorov-Smirnov test can now be applied to point patterns on a linear network (class 'lpp') and point processes on a linear network (class 'lppm'). o bermantest.lpp, bermantest.lppm Berman's Z1 and Z2 tests can now be applied to point patterns on a linear network (class 'lpp') and point processes on a linear network (class 'lppm'). o rhohat.lpp, rhohat.lppm Nonparametric estimation of the dependence of a point pattern on a spatial covariate: 'rhohat' now applies to objects of class 'lpp' and 'lppm'. o intensity.lpp Empirical intensity of a point pattern on a linear network. o as.function.rhohat Converts a 'rhohat' object to a function, with extrapolation beyond the endpoints. o [.layered Subset operator for layered objects. o shift, rotate, affine, rescale, reflect, flipxy, scalardilate These geometrical transformations now work for 'layered' objects. o iplot.layered Interactive plotting for 'layered' objects. o as.owin.layered Method for as.owin for layered objects. o [.owin Subset operator for windows, equivalent to intersect.owin. o rcellnumber Generates random integers for the Baddeley-Silverman counterexample. o is.lpp Tests whether an object is a point pattern on a linear network. o is.stationary.lppm, is.poisson.lppm New methods for is.stationary and is.poisson for class 'lppm' o sessionLibs Print library names and version numbers (for use in Sweave scripts) SIGNIFICANT USER-VISIBLE CHANGES o iplot iplot is now generic, with methods for 'ppp', 'layered' and 'default'. iplot methods now support zoom and pan navigation. o rmh.default New argument 'snoop' allows the user to activate a visual debugger for the Metropolis-Hastings algorithm. o connected connected() is now generic, with methods for 'im', 'owin' and 'ppp'. o alltypes Now works for lpp objects o rlabel Now works for lpp, pp3, ppx objects o plot.kstest Can now perform P-P and Q-Q plots as well. o plot.fasp New argument 'samey' controls whether all panels have the same y limits. o plot.fasp Changed default value of 'samex'. o Objects of class 'envelope', 'fv' and 'fasp' Reduced computation time and storage required for these objects. o pcfmodel.kppm Improved calculation. o plot.fv Improved collision-avoidance algorithm (for avoiding overlaps between curves and legend) o ppm Improved error handling o envelope All methods for 'envelope' now handle fun=NULL o setminus.owin Better handling of the case where both arguments are rectangles. o rmh Simulation has been further accelerated. o lppm Accelerated. o vcov.ppm Accelerated. o marktable Accelerated. o Triplets() interaction Accelerated. o alltypes Accelerated when envelope=TRUE. BUG FIXES o rmh Simulation of the Geyer saturation process was incorrect. [Bug introduced in previous version, spatstat 1.31-0.] Fixed. o rmh Simulation of the Geyer saturation process was incorrectly initialised, so that the results of a short run (i.e. small value of 'nrep') were incorrect, while long runs were correct. [Bug introduced in spatstat 1.17-0, october 2009.] Fixed. o ppm Objects fitted with use.gam=TRUE caused fatal errors in various functions including print, summary, vcov and model.frame. Spotted by Jason Goldstick. Fixed. o lpp, runiflpp, rpoislpp Empty point patterns caused an error. Fixed. o rmh.default Crashed for hybrid models, with message 'Attempt to apply non-function'. Spotted by Ege Rubak. Fixed. o relrisk Crashed when 'at="points"' for a multitype pattern with more than 2 types. Spotted by Marcelino de la Cruz. Fixed. o erosion.owin, dilation.psp, border Ignored the arguments "..." in some cases (namely when the window was polygonal and 'gpclib' was disabled). Fixed. o rsyst, rcell Did not correctly handle the argument 'dx'. Spotted by Fabrice Vinatier. Fixed. o correction="trans" Various functions such as Kest no longer recognised 'correction = "trans"'. Fixed. o istat Crashed with an error message about envelopes. Fixed. o summary.ppm, print.ppm p-values which were exactly equal to zero were reported as NA. Fixed. o [.im Crashed if the intersection consisted of a single row or column of pixels. Fixed. o plot.im Sometimes incorrectly displayed an image consisting of a single row or column of pixels. Fixed. o plot.layered The plot region was determined by the first layer, so that objects in subsequent layers could sometimes fall outside the plot region. Fixed. o transect.im If the arguments 'from' and 'to' were numeric vectors of length 2, the result was garbled. Fixed. o Inhomogeneous K functions and pair correlation functions [Kinhom, pcfinhom, Kcross.inhom, Kdot.inhom, pcfcross.inhom, etc.] These functions reported an error 'lambda is not a vector' if the intensity argument lambda was computed using density(, at="points"). Fixed. o rlabel Did not accept a point pattern with a hyperframe of marks. Fixed. o alltypes Crashed when envelope=TRUE if the summary function 'fun' did not have default values for the marks i and j. Fixed. o Kres, Gres, psst, psstA Ignored the unit of length. Fixed. CHANGES IN spatstat VERSION 1.31-0 OVERVIEW o We thank Frederic Lavancier and Ege Rubak for contributions. o Major bug fix in simulation of area-interaction process. o Metropolis-Hastings simulations accelerated. o Rounding of spatial coordinates o clmfires dataset corrected. o Bug fixes and minor improvements. NEW FUNCTIONS o round.ppp Round the spatial coordinates of a point pattern to a specified number of decimal places. o rounding Determine whether a dataset has been rounded. SIGNIFICANT USER-VISIBLE CHANGES o rmh Simulation of the following models has been accelerated: areaint, dgs, diggra, fiksel, geyer, hardcore, lennard, multihard, strauss, straush, straussm, strausshm. o rmh The transition history of the simulation (which is saved if 'track=TRUE') now also contains the value of the Hastings ratio for each proposal. o clmfires The clmfires dataset has been modified to remove errors and inconsistencies. o plot.linim Appearance of the plot has been improved, when style='width'. o summary.ppm Now reports whether the spatial coordinates have been rounded. o dclf.test, mad.test The range of distance values ('rinterval') used in the test is now printed in the test output, and is saved as an attribute. BUG FIXES o rmh Simulation of the Area-Interaction model was completely incorrect. Spotted by Frederic Lavancier. The bug was introduced in spatstat version 1.23-6 or later. Fixed. o dclf.test The test statistic was incorrectly scaled (by a few percent). This did not affect the p-value of the test. Fixed. o ppx If argument 'coord.type' was missing, various errors occurred: a crash may have occurred, or the results may have depended on the storage type of the data. Spotted by Ege Rubak. Fixed. o plot.ppx Crashed for 1-dimensional point patterns. Spotted by Ege Rubak. Fixed. CHANGES IN spatstat VERSION 1.30-0 OVERVIEW o We thank Jorge Mateu, Andrew Bevan, Olivier Flores, Marie-Colette van Lieshout, Nicolas Picard and Ege Rubak for contributions. o The spatstat manual now exceeds 1000 pages. o Hybrids of point process models. o Five new datasets o Second order composite likelihood method for kppm. o Inhomogeneous F, G and J functions. o Delaunay graph distance o Fixed serious bug in 'lppm' for marked patterns. o bug fix in some calculations for Geyer model o Improvements to linear networks code o Pixel images can now be displayed with a logarithmic colour map. o spatstat now formally 'Depends' on the R core package 'grDevices' o miscellaneous improvements and bug fixes NEW DATASETS o clmfires Forest fires in Castilla-La Mancha o gordon People sitting on the grass in Gordon Square, London o hyytiala Mixed forest in Hyytiala, Finland (marked by species) o paracou Kimboto trees in Paracou, French Guiana (marked as adult/juvenile) o waka Trees in Waka national park (marked with diameters) NEW FUNCTIONS o Hybrid The hybrid of several point process interactions [Joint research with Jorge Mateu and Andrew Bevan] o is.hybrid Recognise a hybrid interaction or hybrid point process model. o Finhom, Ginhom, Jinhom Inhomogeneous versions of the F, G and J functions [Thanks to Marie-Colette van Lieshout] o delaunay.distance Graph distance in the Delaunay triangulation. o distcdf Cumulative distribution function of the distance between two independent random points in a given window. o bw.frac Bandwidth selection based on window geometry o shortside.owin, sidelengths.owin Side lengths of (enclosing rectangle of) a window SIGNIFICANT USER-VISIBLE CHANGES o ppm Can now fit models with 'hybrid' interactions [Joint research with Jorge Mateu and Andrew Bevan] o kppm Now has the option of fitting models using Guan's (2006) second order composite likelihood. o envelope.lpp Now handles multitype point patterns. o envelope.envelope New argument 'transform' allows the user to apply a transformation to previously-computed summary functions. o runifpointOnLines, rpoisppOnLines, runiflpp, rpoislpp Can now generate multitype point patterns. o rmhmodel, rmh, simulate.ppm Now handle point process models with 'hybrid' interactions. o kppm Accelerated, and more reliable, due to better choice of starting values in the optimisation procedure. o kppm The internal format of kppm objects has changed. o minimum contrast estimation Error messages from the optimising function 'optim' are now trapped and handled. o rhohat This command is now generic, with methods for ppp, quad, and ppm. o raster.x, raster.y, raster.xy These functions have a new argument 'drop' o summary.ppm Improved behaviour when the model covariates are a data frame. o progressreport Output improved. o second order summary functions (Kest, Lest, Kinhom, pcf.ppp, Kdot, Kcross, Ldot etc etc) These functions now accept correction="translation" as an alternative to correction = "translate", for consistency. o plot.im New argument 'log' allows colour map to be equally spaced on a log scale. o as.owin.ppm, as.owin.kppm New argument 'from' allows the user to extract the spatial window of the point data (from="points") or the covariate images (from="covariates") o dclf.test, mad.test The rule for handling tied values of the test statistic has been changed. The tied values are now randomly ordered to obtain a randomised integer rank. o with.fv New argument 'enclos' allows evaluation in other environments BUG FIXES o lppm For multitype patterns, the fitted model was completely incorrect due to an error in constructing the quadrature scheme. Fixed. o Geyer For point process models with the 'Geyer' interaction, vcov.ppm() and suffstat() sometimes gave incorrect answers. [Spotted by Ege Rubak.] Fixed. o as.im.im Did not correctly handle factor-valued images if one of the arguments 'dimyx', 'eps', 'xy' was given. Fixed. o envelope.lppm Crashed if the model was multitype. Fixed. o lpp Did not handle empty patterns. Fixed. o density.ppp If 'sigma' was a bandwidth selection function such as bw.scott() which returned a numeric vector of length 2, a warning message was issued, and the smoothing bandwidth was erroneously taken to be the first element of the vector. Fixed. o Fest, Jcross, Jdot, Jmulti If these functions were computed using correction = 'rs', plotting them would sometimes give an error, with the message "no finite x/y limits". Fixed. o pcfmodel.kppm For models with clusters="VarGamma" the value of the pcf at distance r=0 was given as NaN. Fixed. o vcov.ppm Result was incorrect in rare cases, due to numerical rounding effects. Fixed. o rLGCP, simulate.kppm For models fitted to point patterns in an irregular window, simulation sometimes failed, with a message that the image 'mu' did not cover the simulation window. (Spotted by George Limitsios.) Fixed. o rLGCP, simulate.kppm Crashed sometimes with an error about unequal x and y steps (from 'GaussRF'). Fixed. CHANGES IN spatstat VERSION 1.29-0 OVERVIEW o We thank Colin Beale, Li Haitao, Frederic Lavancier, Erika Mudrak and Ege Rubak for contributions. o random sequential packing o Allard-Fraley estimator o method for pooling several quadrat tests o better control over dummy points in ppm o more support for data on a linear network o nearest neighbour map o changes to subsetting of images o improvements and bug fixes NEW FUNCTIONS o clusterset Allard-Fraley estimator of high-density features in a point pattern o pool.quadrattest Pool several quadrat tests o nnfun Nearest-neighbour map of a point pattern or a line segment pattern o as.ppm Converts various kinds of objects to ppm o crossdist.lpp Shortest-path distances between pairs of points in a linear network o nobs.lppm Method for 'nobs' for lppm objects. o as.linim Converts various kinds of objects to 'linim' o model.images.slrm Method for model.images for slrm objects o rotate.im Rotate a pixel image SIGNIFICANT USER-VISIBLE CHANGES o "[.im" and "[<-.im" New argument 'j' allows any type of matrix indexing to be used. o "[.im" Default behaviour changed in the case of a rectangular subset. New argument 'rescue' can be set to TRUE to reinstate previous behaviour. o rSSI Performs 'Random Sequential Packing' if n=Inf. o ppm New argument 'eps' determines the spacing between dummy points. (also works for related functions quadscheme, default.dummy, ...) o fitted.ppm, predict.ppm Argument 'new.coef' specifies a vector of parameter values to replace the fitted coefficients of the model. o lppm Stepwise model selection using step() now works for lppm objects. o vcov.slrm Can now calculate correlation matrix or Fisher information matrix as well as variance-covariance matrix. o eval.fv Improved behaviour when plotted. o "[.fv" Improved behaviour when plotted. o lohboot When the result is plotted, the confidence limits are now shaded. o lohboot New argument 'global' allows global (simultaneous) confidence bands instead of pointwise confidence intervals. o vcov.ppm Accelerated by 30% in some cases. o quadrat.test.splitppp The result is now a single object of class 'quadrattest' o progressreport Improved output (also affects many functions which print progress reports) o Full redwood data (redwoodfull) Plot function redwoodfull.extra$plotit has been slightly improved. o nncross This function is now generic, with methods for 'ppp' and 'default'. o distfun The internal format of objects of class 'distfun' has been changed. o duplicated.ppp, unique.ppp New argument 'rule' allows behaviour to be consistent with package 'deldir' BUG FIXES o bdist.tiles Values were incorrect in some cases due to numerical error. (Spotted by Erika Mudrak.) Fixed. o vcov.ppm, suffstat These functions sometimes gave incorrect values for marked point process models. Fixed. o simulate.ppm, predict.ppm Did not correctly handle the 'window' argument. (Spotted by Li Haitao). Fixed. o smooth.ppp, markmean If sigma was very small, strange values were produced, due to numerical underflow. (Spotted by Colin Beale). Fixed. o MultiHard, MultiStrauss, MultiStraussHard Crashed if the data point pattern was empty. (Spotted by Ege Rubak). Fixed. o vcov.ppm Crashed sporadically, with multitype interactions. (Spotted by Ege Rubak). Fixed. o rStrauss, rHardcore, rStraussHard, rDiggleGratton, rDGS If the simulated pattern was empty, these functions would either crash, or return a pattern containing 1 point. (Spotted by Frederic Lavancier). Fixed. o model.matrix.slrm Crashed if the model was fitted using split pixels. Fixed. o residuals.ppm, diagnose.ppm Did not always correctly handle models that included offset terms. Fixed. o project.ppm When a model was projected by project.ppm or by ppm(project=TRUE), the edge corrections used the projected models were sometimes different from the edge corrections in the original model, so that the projected and unprojected models were not comparable. Fixed. o plot.listof, plot.splitppp Crashed sometimes due to a scoping problem. Fixed. o dclf.test, mad.test Crashed if any of the function values were infinite or NaN. Fixed. o psstA Default plot did not show the horizontal line at y=0 corresponding to a perfect fit. Fixed. o vcov.ppm names attribute was spelt incorrectly in some cases. Fixed. CHANGES IN spatstat VERSION 1.28-2 OVERVIEW o We thank Thomas Bendtsen, Ya-Mei Chang, Daniel Esser, Robert John-Chandran, Ege Rubak and Yong Song for contributions. o New code for Partial Residual Plots and Added Variable Plots. o maximum profile pseudolikelihood computations vastly accelerated. o New dataset: cells in gastric mucosa o now possible to capture every k-th state of Metropolis-Hastings algorithm. o size of 'ppm' objects reduced. o scope of 'intensity.ppm' extended. o quadrat.test can now perform Monte Carlo tests and one/two-sided tests o improvements to 'plot.fv' o improvement to 'rescale' o some datasets reorganised. o numerous bug fixes NEW DATASET o mucosa Cells in gastric mucosa Kindly contributed by Dr Thomas Bendtsen NEW FUNCTIONS o parres Partial residual plots for spatial point process models. A diagnostic for the form of a covariate effect. o addvar Added variable plots for spatial point process models. A diagnostic for the existence of a covariate effect. SIGNIFICANT USER-VISIBLE CHANGES o profilepl Accelerated (typically by a factor of 5). o rmh, rmhcontrol It is now possible to save every k-th iteration of the Metropolis-Hastings algorithm. The arguments 'nsave' and 'nburn' may be given to rmh or to rmhcontrol. They specify that the point pattern will be saved every 'nsave' iterations, after an initial burn-in of 'nburn' iterations. o simulate.ppm New argument 'singlerun' determines whether the simulated patterns are generated using independent runs of the Metropolis-Hastings algorithm or are obtained by performing one long run of the algorithm and saving every k-th iteration. o exactMPLEstrauss New argument 'project' determines whether the parameter gamma is constrained to lie in [0,1]. o intensity.ppm Now works for stationary point process models with the interactions DiggleGratton, DiggleGatesStibbard, Fiksel, PairPiece and Softcore. o plot.fv Improved algorithm for avoiding collisions between graphics and legend. o plot.fv New argument 'log' allows plotting on logarithmic axes. o envelope Can now calculate an estimate of the true significance level of the "wrong" test (which declares the observed summary function to be significant if it lies outside the pointwise critical boundary anywhere). Controlled by new argument 'do.pwrong'. o quadrat.test New argument 'alternative' allows choice of alternative hypothesis and returns one-sided or two-sided p-values as appropriate. o quadrat.test Can now perform Monte Carlo test as well (for use in small samples where the chi^2 approximation is inaccurate) o Softcore Improved numerical stability. New argument 'sigma0' for manual control over rescaling. o rescale If scale argument 's' is missing, then the data are rescaled to native units. For example if the current unit is 0.1 metres, coordinates will be re-expressed in metres. o psst Extra argument 'verbose=TRUE' o is.subset.owin Accelerated for polygonal windows o rmh.default 'track' is no longer a formal argument of rmh.default; it is now a parameter of rmhcontrol. However there is no change in usage: the argument 'track' can still be given to rmh.default. o clf.test Has been renamed 'dclf.test' to give proper attribution to Peter Diggle. o betacells This dataset has been restructured. The vector of cell profile areas, formerly given by betacells.extra$area, has now been included as a column of marks in the point pattern 'betacells'. o ants The function ants.extra$plot() has been renamed plotit() for conformity with other datasets. o redwoodfull The function redwoodfull.extra$plot() has been renamed plotit() for conformity with other datasets. o nbfires For conformity with other datasets, there is now an object nbfires.extra BUG FIXES o ripras Expansion factor was incorrect in the rectangular case. Fixed. o Triplets Crashed sometimes with error "dim(X) must have positive length". Fixed. o affine.im Crashed in the case of a diagonal transformation matrix! Spotted by Ege Rubak. Fixed. o envelope.envelope Ignored the argument 'global'. Fixed. o MultiStraussHard The printed output showed the hardcore radii as NULL. Spotted by Ege Rubak. Fixed. o "[.psp" Crashed if the data were generated by rpoisline(). Spotted by Marcelino de la Cruz. Fixed. o plot.linim If style="colour", the main title was always "x". Fixed. o plot.ppx Setting add=TRUE did not prevent the domain being plotted. Fixed. o rmh Crashed if x.start was an empty point pattern. Spotted by Ege Rubak. Fixed. o as.ppp.data.frame Crashed if any points lay outside the window. Spotted by Ege Rubak. Fixed. o Ripley isotropic edge correction Divide-by-zero error in rare cases. Spotted by Daniel Esser. Fixed. o summary functions For many of the summary functions (e.g. Kest, pcf), the result of saving the object to disc was an enormous file. Spotted by Robert John-Chandran. Fixed. o pcf.fv Default plot was wrongly coloured. Fixed. CHANGES IN spatstat VERSION 1.28-1 OVERVIEW o We thank Ege Rubak, Gopal Nair, Jens Oehlschlaegel and Mike Zamboni for contributions. o New approximation to the intensity of a fitted Gibbs model. o Minor improvements and bug fixes o spatstat now 'Suggests' the package 'gsl' NEW FUNCTIONS o intensity, intensity.ppp, intensity.ppm Calculate the intensity of a dataset or fitted model. Includes new approximation to the intensity of a fitted Gibbs model o LambertW Lambert's W-function SIGNIFICANT USER-VISIBLE CHANGES o envelope Improved plot labels for envelopes that were generated using the 'transform' argument. o plot.fv Improved algorithm for collision detection. o plot.im Now returns the colour map used. o plot.listof, plot.splitppp Slight change to handling of plot.begin and plot.end o square Now accepts vectors of length 2 o plot.fii Increased resolution of the plot obtained from plot(fitin(ppm(...))) o image.listof If equal.ribbon=TRUE, the colour ribbon will no longer be displayed repeatedly for each panel, but will now be plotted only once, at the right hand side of the plot array. BUG FIXES o vcov.ppm Results were sometimes incorrect for a Gibbs model with non-trivial trend. Spotted by Ege Rubak. Fixed. o nncross In rare cases the results could be slightly incorrect. Spotted by Jens Oehlschlaegel. Fixed. o plot.fv When add=TRUE, the x limits were sometimes truncated. Spotted by Mike Zamboni. Fixed. o plot.im Labels for the tick marks on the colour ribbon were sometimes ridiculous, e.g. "2.00000001". Fixed. CHANGES IN spatstat VERSION 1.28-0 OVERVIEW o We thank Farzaneh Safavimanesh, Andrew Hardegen and Tom Lawrence for contributions. o Improvements to 3D summary functions. o A multidimensional point pattern (ppx) can now have 'local' coordinates as well as spatial and temporal coordinates and marks. o Changed format for point patterns on a linear network (lpp). Changes are backward compatible. Many computations run faster. o More support for fitted cluster models (kppm). o split method for multidimensional point patterns (ppx) and point patterns on a linear network (lpp). o Fixed bug causing errors in plot.im o Miscellaneous improvements and bug fixes NEW FUNCTIONS o exactMPLEstrauss Fits the stationary Strauss point process model using an exact maximum pseudolikelihood technique. This is mainly intended for technical investigation of algorithms. o split.ppx Method for 'split' for multidimensional point patterns (class 'ppx'). This also works for point patterns on a linear network (class 'lpp'). o model.images This function is now generic, with methods for classes ppm, kppm, lppm o model.frame, model.matrix These generic functions now have methods for classes kppm, lppm o as.owin.kppm, as.owin.lppm New methods for 'as.owin' for objects of class kppm, lppm o as.linnet.lppm Extracts the linear network in which a point process model was fitted. SIGNIFICANT USER-VISIBLE CHANGES o class 'ppx' An object of class 'ppx' may now include 'local' coordinates as well as 'spatial' and 'temporal' coordinates, and marks. o ppx Arguments have changed. o class 'lpp' The internal format of lpp objects has been extended (but is backward-compatible). Many computations run faster. To convert an object to the new format: X <- lpp(as.ppp(X), as.linnet(X)). o F3est Calculation of theoretical Poisson curve ('theo') has changed, and is now controlled by the argument 'sphere'. o rmh, rmhstart The initial state ('start') can now be missing or null. o im, as.im The pixel coordinates in an image object are now generated more accurately. This avoids a numerical error in plot.im. o eval.fv, eval.fasp Evaluation is now applied only to columns that contain values of the function itself (rather than values of the derivative, hazard rate, etc). This is controlled by the new argument 'dotonly'. o spatstat.options New option 'nvoxel' o quad.ppm Now accepts kppm objects. o str This generic function (for inspecting the internal structure of an object) now produces sensible output for objects of class 'hyperframe', 'ppx', 'lpp' o ppx, coords.ppx, coords<-.ppx The arguments to these functions have changed. o lgcp.estK, Kmodel Computation can be greatly accelerated by setting spatstat.options(fastK.lgcp=TRUE). o G3est Computation accelerated. o envelope Computation slightly accelerated. o spatstat.options New option 'fastK.lgcp' BUG FIXES o nndist.psp Caused an error if length(k) > 1. Fixed. o plot.im Sometimes reported an error "useRaster=TRUE can only be used with a regular grid." This was due to numerical rounding effects on the coordinates of a pixel image. Fixed. o plot.fv If a formula was used to specify the plot, the names of variables in the formula were sometimes incorrectly matched to *functions*. Spotted by Farzaneh Safavimanesh. Fixed. o F3est Took a very long time if the containing box was very flat, due to the default value of 'vside'. Fixed. o rmh, rmhmodel An erroneous warning about 'outdated format of rmhmodel object' sometimes occurred. Fixed. o marks<-.ppx Names of result were incorrect. Fixed. o hyperframe class Various minor bug fixes. CHANGES IN spatstat VERSION 1.27-0 OVERVIEW o Variance estimates are now available for all Gibbs point process models. o Cressie-Loosmore-Ford test implemented o plot.fv now avoids collisions between the legend and the graphics. o Extension to predict.ppm o Improvements to envelopes and multitype summary functions. o Line transects of a pixel image. o Changes to defaults in Metropolis-Hastings simulations. o More geometrical operations o Bug fixes. o We thank Aruna Jammalamadaka for contributions. NEW FUNCTIONS o clf.test Perform the Cressie (1991)/ Loosmore and Ford (2006) test of CSR (or another model) o mad.test Perform the Maximum Absolute Deviation test of CSR (or another model). o convolve.im Compute convolution of pixel images. o Kmulti.inhom Counterpart of 'Kmulti' for spatially-varying intensity. o rmhexpand Specify a simulation window, or a rule for expanding the simulation window, in Metropolis-Hastings simulation (rmh) o transect.im Extract pixel values along a line transect. o affine.im Apply an affine transformation to a pixel image. o scalardilate Perform scalar dilation of a geometrical object relative to a specified origin. o reflect Reflect a geometrical object through the origin. o "[.lpp", "[.ppx" Subset operators for the classes "lpp" (point pattern on linear network) and "ppx" (multidimensional space-time point pattern). o is.rectangle, is.polygonal, is.mask Determine whether a window w is a rectangle, a domain with polygonal boundaries, or a binary pixel mask. o has.offset Determines whether a fitted model object (of any kind) has an offset. SIGNIFICANT USER-VISIBLE CHANGES o predict.ppm This function can now calculate the conditional intensity of a model relative to any point pattern X (not just the original data pattern). o vcov.ppm This function now handles all Gibbs point process models. o plot.fv Collisions between the legend box and the graphics are now detected and avoided. o rmh.ppm, rmh.default, simulate.ppm, qqplot.ppm, envelope.ppm These functions now have slightly different default behaviour because of changes to the handling of arguments to 'rmhcontrol'. o rmhcontrol The default value of the parameters 'periodic' and 'expand' has changed. o rmhcontrol The parameter 'expand' can now be in any format acceptable to rmhexpand(). o rmh.ppm, rmh.default, simulate.ppm Any 'rmhcontrol' parameter can now be given directly as an argument to rmh.ppm, rmh.default or simulate.ppm. o Kmulti, Gmulti, Jmulti The arguments I, J can now be any kind of subset index or can be functions that yield a subset index. o envelope.envelope In envelope(E, fun=NULL) if E does not contain simulated summary functions, but does contain simulated point patterns, then 'fun' now defaults to Kest, instead of flagging an error. o print.ppp, summary.ppp If the point pattern x was generated by Metropolis-Hastings simulation using 'rmh', then print(x) and summary(x) show information about the simulation parameters. o print.ppm Standard errors for the parameter estimates, and confidence intervals for the parameters, can now be printed for all Gibbs models (but are printed only for Poisson models by default). o eval.im Images with incompatible dimensions are now resampled to make them compatible (if harmonize=TRUE). o spatstat.options New option 'print.ppm.SE' controls whether standard errors and confidence intervals are printed for all Gibbs models, for Poisson models only, or are never printed. o inside.owin Now accepts the form list(x,y) for the first argument. o image.listof New argument 'equal.ribbon' allows several images to be plotted with the same colour map. o is.subset.owin Improved accuracy in marginal cases. o expand.owin Functionality extended to handle all types of expansion rule. o default.rmhcontrol, default.expand These functions now work with models of class 'rmhmodel' as well as 'ppm' o print.rmhcontrol Output improved. BUG FIXES o linearK, linearKinhom If any data points were located exactly at a vertex of the linear network, the weights for Ang's correction were incorrect, due to numerical error. This sometimes produced infinite or NA values of the linear K function. Fixed. o predict.ppm In some cases, predict.ppm(type="cif") generated a spurious warning that "number of rows of result is not a multiple of vector length." Fixed. o crossing.psp Results were sometimes incorrect due to numerical rounding error associated with GCC bug #323. Fixed. o MultiHard, MultiStrauss, MultiStraussHard If the mark values contained non-alphanumeric characters, the names of the interaction coefficients in coef(ppm(...)) were sometimes garbled. Fixed. o profilepl For edge corrections other than the border correction, an error message about 'rbord' would sometimes occur. Fixed. o is.marked, is.multitype These functions gave the wrong answer for 'lpp' objects. Fixed. o marks<-.lpp, marks<-.ppx Format of result was garbled if new columns of marks were added. Fixed. o reach.rmhmodel Gave the wrong answer for Geyer and BadGey models. Fixed. o envelope.envelope Ignored the argument 'savefuns'. Fixed. o BadGey Sometimes wrongly asserted that the parameter 'sat' was invalid. Occurred only in ppm(project=TRUE). Fixed. CHANGES IN spatstat VERSION 1.26-1 OVERVIEW o Variance-covariance matrix for Gibbs point process models. o Bootstrap confidence bands for pair correlation function and K function. o Bug fix in scan test. o Area-interaction model accelerated. o we thank Jean-Francois Coeurjolly and Ege Rubak for contributions. NEW FUNCTIONS o lohboot Computes bootstrap confidence bands for pair correlation function and K function using Loh's (2008) mark bootstrap. SIGNIFICANT USER-VISIBLE CHANGES o vcov.ppm Now works for all Gibbs point process models, thanks to new code (and theory) from Jean-Francois Coeurjolly and Ege Rubak o AreaInter Computations related to the area-interaction point process (ppm, predict.ppm, residuals.ppm, diagnose.ppm, qqplot.ppm) have been accelerated. BUG FIXES o scan.test Results were sometimes incorrect due to numerical instability (a 'Gibbs phenomenon'). Fixed. CHANGES IN spatstat VERSION 1.26-0 OVERVIEW o We thank Jens Oehlschlaegel for contributions. o Further substantial acceleration of spatstat functions. o Workaround for bug in RandomFields package. o Numerous modifications to internal code. NEW FUNCTIONS o RandomFieldsSafe There is a bug in the package 'RandomFields' (version <= 2.0.54) which causes a crash to occur, in the development version of R but not in R 2.15.0. To avoid crashing spatstat, we have written the temporary, undocumented function RandomFieldsSafe() which returns TRUE if it is safe to use the RandomFields package. Examples in the spatstat help files for kppm, lgcp.estK, lgcp.estpcf and rLGCP are only executed if RandomFieldsSafe() returns TRUE. SIGNIFICANT USER-VISIBLE CHANGES o Many functions Many spatstat functions now run faster, and will handle larger datasets, thanks to improvements in the internal code, following suggestions from Jens Oehlschlaegel. o Many functions The response to an 'Interrupt' signal is slightly slower. CHANGES IN spatstat VERSION 1.25-5 OVERVIEW o We thank Ya-Mei Chang, Jens Oehlschlaegel and Yong Song for contributions. o Extended functionality of 'rhohat' to local likelihood smoothing and bivariate smoothing. o Nearest neighbour distance computations accelerated. o spatstat now 'Suggests:' the package 'locfit' NEW FUNCTIONS o rho2hat Bivariate extension of 'rhohat' for estimating spatial residual risk, or intensity as a function of two covariates. SIGNIFICANT USER-VISIBLE CHANGES o rhohat Estimation can now be performed using local likelihood fitting with the 'locfit' package, or using kernel smoothing. o nncross Substantially accelerated. New arguments added to control the return value and the sorting of data. BUG FIXES o plot.msr Crashed if the argument 'box' was given. Fixed. CHANGES IN spatstat VERSION 1.25-4 OVERVIEW o We thank Jonathan Lee and Sergiy Protsiv for contributions. o Improvements and bug fixes to K function for very large datasets NEW FUNCTIONS o rStraussHard Perfect simulation for Strauss-hardcore process (with gamma <= 1) SIGNIFICANT USER-VISIBLE CHANGES o plot.im The colour ribbon can now be placed left, right, top or bottom using new argument 'ribside' o profilepl Does not generate warnings when some of the candidate models have zero likelihood - for example when fitting model with a hard core. o Kest Now includes fast algorithm for 'correction="none"' which will handle patterns containing millions of points. BUG FIXES o Kest, Lest Gave incorrect values in very large datasets, due to numerical overflow. `Very large' typically means about 1 million points in a random pattern, or 100,000 points in a tightly clustered pattern. [Overflow cannot occur unless there are at least 46,341 points.] [Spotted by Sergiy Protsiv.] Fixed. o Kest, Lest Ignored 'ratio=TRUE' if the argument 'domain' was given. [Spotted by Jonathan Lee.] Fixed. o rjitter Output was sometimes incorrect. [Spotted by Sergiy Protsiv.] Fixed. CHANGES IN spatstat VERSION 1.25-3 OVERVIEW o We thank Daniel Esser for contributions. o Improved support for fitted point process models. o Bug fixes. NEW FUNCTIONS o simulate.slrm Method for 'simulate' for spatial logistic regression models. o labels.ppm, labels.kppm, labels.slrm Methods for 'labels' for fitted point process models. o commonGrid Determine a common spatial domain and pixel resolution for several pixel images and/or binary masks SIGNIFICANT USER-VISIBLE CHANGES o effectfun Now has argument 'se.fit' allowing calculation of standard errors and confidence intervals. o [.msr Now handles character-valued indices. o print.summary.ppm Output gives a more precise description of the fitting method. o ppm, kppm, slrm Confidence intervals for the fitted trend parameters can now be obtained using 'confint' o predict.slrm New argument 'window' o union.owin Now handles a single argument: union.owin(A) returns A. BUG FIXES o selfcrossing.psp y coordinate values were incorrect. [Spotted by Daniel Esser.] Fixed. o as.im.owin Did not handle a binary mask with a 1 x 1 pixel array. Fixed. o predict.slrm Results of predict(object, newdata) were incorrect if the spatial domain of 'newdata' was larger than the original domain. Fixed. o ppm If the model was the uniform Poisson process, the argument 'rbord' was ignored. Fixed. o image subset assignment "[<-.im" Generated an error if the indexing argument 'i' was a point pattern containing zero points. Fixed. o hyperframe subset assignment "[<-.hyperframe" Did not correctly handle the case where a single column of the hyperframe was to be changed. Fixed. o help(bw.relrisk), help(rmh.ppm), help(plot.plotppm) These help files had the side-effect of changing some options in spatstat.options. Fixed. CHANGES IN spatstat VERSION 1.25-2 OVERVIEW o We thank Abdollah Jalilian and Thierry Onkelinx for contributions. o Very Important Bug fixes. o Improved mechanism for handling 'invalid' point processes NEW FUNCTIONS o as.matrix.owin Converts a window to a logical matrix. SIGNIFICANT USER-VISIBLE CHANGES o project.ppm Improved algorithm. Now handles terms in the trend formula as well as the interaction. The projected point process is now obtained by re-fitting the model, and is guaranteed to be the maximum pseudolikelihood fit. o plot.im Now handles many arguments recognised by plot.default such as 'cex.main'. Also handles argument 'box'. New argument 'ribargs' contains parameters controlling the ribbon plot only. o spatstat.options New option 'project.fast' allows a faster shortcut for project.ppm o spatstat.options New options 'rmh.p', 'rmh.q', 'rmh.nrep' determine the default values of the parameters p, q and nrep of the Metropolis-Hastings algorithm. See rmhcontrol o ppm Slightly accelerated. BUG FIXES o nncross, distfun, AreaInter Results of nncross were possibly incorrect when X and Y did not have the same window. This bug affected values of 'distfun' and may also have affected ppm objects with interaction 'AreaInter'. [Spotted by Thierry Onkelinx] Bug introduced in spatstat 1.9-4 (June 2006). Fixed. o rCauchy Simulations were incorrect in the sense that the value of 'omega' was inadvertently doubled (i.e. omega was incorrectly replaced by 2 * omega). Bug introduced in spatstat 1.25-0. Fixed. o plot.im White lines were present in the image display, on some graphics devices, due to changes in R 2.14. Fixed. o update.ppm The result of 'update(object, formula)' sometimes contained errors in the internal format. Bug introduced in spatstat 1.25-0. Fixed. o example(AreaInter), example(bw.smoothppp), example(Kest.fft), example(plot.owin), example(predict.ppm), example(simulate.ppm) Executing these examples had the side-effect of changing some of the parameters in spatstat.options. Fixed. CHANGES IN spatstat VERSION 1.25-1 OVERVIEW o We thank Neba Funwi-Gabga and Jorge Mateu for contributions. o New dataset of gorilla nest sites o New functions for perfect simulation o Bug fix for rare crashes in rStrauss o Code for ensuring a fitted point process model is a valid point process NEW DATASET o gorillas Gorilla nest sites in a National Park in Cameroon. Generously contributed by Neba Funwi-Gabga NEW FUNCTIONS o rDiggleGratton, rDGS, rHardcore Perfect simulation for the Diggle-Gratton process, Diggle-Gates-Stibbard process, and Hardcore process. o bw.scott Scott's rule of thumb for bandwidth selection in multidimensional smoothing o valid.ppm Checks whether a fitted point process model is a valid point process o project.ppm Forces a fitted point process model to be a valid point process SIGNIFICANT USER-VISIBLE CHANGES o ppm New argument 'project' determines whether the fitted model is forced to be a valid point process o linnet Substantially accelerated. o rStrauss Slightly accelerated. o summary.lpp Now prints the units of length. BUG FIXES o rStrauss Crashed rarely (once every 10 000 realisations) with a memory segmentation fault. Fixed. CHANGES IN spatstat VERSION 1.25-0 OVERVIEW o Leverage and influence for point process models o New cluster models (support for model-fitting and simulation). o Fit irregular parameters in trend of point process model o Third order summary statistic. o Improvements to speed and robustness of code. o spatstat now depends on R 2.14 o We thank Abdollah Jalilian and Rasmus Waagepetersen for contributions. NEW FUNCTIONS o leverage.ppm, influence.ppm, dfbetas.ppm Leverage and influence for point process models o ippm Experimental extension to 'ppm' which fits irregular parameters in trend by Fisher scoring algorithm. o Tstat Third order summary statistic for point patterns based on counting triangles. o rCauchy, rVarGamma simulation of a Neyman-Scott process with Cauchy clusters or Variance Gamma (Bessel) clusters. Contributed by Abdollah Jalilian. o rPoissonCluster simulation of a general Poisson cluster process o model.covariates Identify the covariates involved in a model (lm, glm, ppm etc) o as.im.distfun Converts a 'distfun' to a pixel image. o cauchy.estK, cauchy.estpcf, vargamma.estK, vargamma.estpcf Low-level model-fitting functions for the Neyman-Scott process with Cauchy or Variance-Gamma cluster kernel. Contributed by Abdollah Jalilian. SIGNIFICANT USER-VISIBLE CHANGES o kppm Now accepts clusters="Cauchy" or clusters="VarGamma" for the Neyman-Scott process with Cauchy or Variance-Gamma cluster kernel. Code contributed by Abdollah Jalilian. o rNeymanScott Argument 'rcluster' may now take a different format. o psst Argument 'funcorrection' changed to 'funargs' allowing greater flexibility. o plot.fv, plot.envelope New argument 'limitsonly' allows calculation of a common x,y scale for several plots. o overall speed spatstat is now byte-compiled and runs slightly faster. o user interrupt Long calculations in spatstat now respond to the Interrupt/Stop signal. o update.ppm Now runs faster and uses much less memory, when the update only affects the model formula (trend formula). o rNeymanScott, rThomas, rMatClust Accelerated thanks to Rasmus Waagepetersen. o multitype data and models Second order multitype statistics (such as Kcross, pcfcross) and multitype interaction models (such as MultiStrauss) now run faster, by a further 5%. BUG FIXES o distfun Some manipulations involving 'distfun' objects failed if the original data X in distfun(X) did not have a rectangular window. Fixed. CHANGES IN spatstat VERSION 1.24-2 OVERVIEW o Geyer's triplet interaction o more functionality for replicated point patterns o changed default for simulation window in point process simulation o changed default for edge correction in Kcom, Gcom o data in spatstat is now lazy-loaded o bug fixes NEW FUNCTIONS o Triplets Geyer's triplet interaction, for point process models o coef.summary.ppm New method coef.summary.ppm You can now type 'coef(summary(fit))' to extract a table of the fitted coefficients of the point process model 'fit' SIGNIFICANT USER-VISIBLE CHANGES o data in spatstat are now lazy-loaded so you don't have to type data(amacrine), etc. o rmh.default, rmh.ppm, simulate.ppm These now handle the 'triplets' interaction o fryplot Now has arguments 'to' and 'from', allowing selection of a subset of points. o fryplot, frypoints These functions now handle marked point patterns properly. o Kcross, Kdot, Kmulti New argument 'ratio' determines whether the numerator and denominator of the estimate of the multitype K-function will be stored. This enables analysis of replicated point patterns, using 'pool.rat()' to pool the K function estimates. o rmh.ppm, simulate.ppm, default.expand For point process models which have a trend depending only on x and y, the simulation window is now taken to be the same as the original window containing the data (by default). That is, `expansion' does not take place, by default. (In previous versions of spatstat the simulation window was larger than the original data window.) o rmh.ppm, simulate.ppm The argument sequence for these functions has changed. New argument 'expand' allows more explicit control over simulation domain. o Kcom, Gcom New argument 'conditional' gives more explicit control over choice of edge correction in compensator. Simplified defaults for edge correction. o Kinhom Improved plot labels. o profilepl Printed output improved. BUG FIXES o Lest The variance approximations (Lotwick-Silverman and Ripley) obtained with var.approx=TRUE, were incorrect for Lest (although they were correct for Kest) due to a coding error. Fixed. o simulate.ppm Ignored the argument 'control' in some cases. Fixed. o pcf and its relatives (pcfinhom, pcfcross.inhom, pcfdot.inhom) Sometimes gave a warning about 'extra arguments ignored'. Fixed. CHANGES IN spatstat VERSION 1.24-1 OVERVIEW o Spatial Scan Test o Functionality for replicated point patterns o Bug fixes NEW FUNCTIONS o scan.test Spatial scan test of clustering o rat New class of 'ratio objects' o pool.rat New method for 'pool'. Combines K function estimates for replicated point patterns (etc) by computing ratio-of-sums o unnormdensity Weighted kernel density with weights that do not sum to 1 and may be negative. o compatible New generic function with methods for 'fv', 'im', 'fasp' and 'units' SIGNIFICANT USER-VISIBLE CHANGES o Kest New argument 'ratio' determines whether the numerator and denominator of the estimate of the K-function will be stored. This enables analysis of replicated point patterns, using 'pool.rat()' to pool the K function estimates. o Lest Now handles theoretical variance estimates (using delta method) if var.approx=TRUE o as.mask Argument 'eps' can now be a 2-vector, specifying x and y resolutions. o default.expand Behaviour changed slightly. o plot.listof, plot.splitppp, contour.listof, image.listof The arguments 'panel.begin' and 'panel.end' can now be objects such as windows. BUG FIXES o rgbim, hsvim Did not work on images with non-rectangular domains. Fixed. o scaletointerval Did not handle NA's. Fixed. CHANGES IN spatstat VERSION 1.24-0 OVERVIEW o This version was not released publicly. CHANGES IN spatstat VERSION 1.23-6 OVERVIEW o Spatial covariance functions of windows and pixel images. o Area-interaction models can now be fitted in non-rectangular windows o Bug fix for envelope of inhomogeneous Poisson process o Bug fix for raster conversion o New vignette on 'Getting Started with Spatstat' o Code accelerated. NEW FUNCTIONS o imcov Spatial covariance function of pixel image or spatial cross-covariance function of two pixel images o harmonise.im Make several pixel images compatible by converting them to the same pixel grid o contour.listof, image.listof Methods for contour() and image() for lists of objects o dummify Convert data to numeric values by constructing dummy variables. SIGNIFICANT USER-VISIBLE CHANGES o setcov Can now compute the `cross-covariance' between two regions o AreaInter Point process models with the AreaInter() interaction can now be fitted to point pattern data X in any window. o areaGain, areaLoss These now handle arbitrary windows W. They are now more accurate when r is very small. o Kcom Computation vastly accelerated, for non-rectangular windows. o vignettes New vignette 'Getting Started with the Spatstat Package' o nncorr, nnmean, nnvario These functions now handle data frames of marks. BUG FIXES o envelope.ppm If the model was an inhomogeneous Poisson process, the resulting envelope object was incorrect (the simulations were correct, but the envelopes were calculated assuming the model was CSR). Bug was introduced in spatstat 1.23-5. Fixed. o envelope.ppm If the model was an inhomogeneous Poisson process with intensity a function of x and y only, overflow errors sometimes occurred ('insufficient storage' or 'attempting to generate a large number of random points'). Fixed. o as.im.im The result of as.im(X, W) was incorrect if 'W' did not cover 'X'. Fixed. o as.mask The result of as.mask(w, xy) was incorrect if 'xy' did not cover 'w'. Fixed. o plot.fv Legend was incorrectly labelled if 'shade' variables were not included in the plot formula. Fixed. o areaGain, areaLoss Crashed if the radius r was close to zero. Fixed. CHANGES IN spatstat VERSION 1.23-5 OVERVIEW o Bug fix to bandwidth selection. o Functions to pool data from several objects of the same class. o Improvements and bug fixes. o We thank Michael Sumner for contributions. NEW FUNCTIONS o pool Pool data from several objects of the same class o pool.envelope Pool simulated data from several envelope objects and create a new envelope o pool.fasp Pool simulated data from several function arrays and create a new array o envelope.envelope Recalculate an envelope from simulated data using different parameters SIGNIFICANT USER-VISIBLE CHANGES o bw.diggle, bw.relrisk, bw.smoothppp, bw.optim Plot method modified. o model.depends Now also recognises 'offset' terms. BUG FIXES o bw.diggle Bandwidth was too large by a factor of 2. Fixed. o plot.psp Crashed if any marks were NA. Fixed. o pointsOnLines Crashed if any segments had zero length. Ignored argument 'np' in some cases. Fixed. o stieltjes Crashed if M had only a single column of function values. Fixed. CHANGES IN spatstat VERSION 1.23-4 OVERVIEW o Bandwidth selection for density.ppp and smooth.ppp o Layered plots. o Model-handling facilities. o Improvements and bug fixes. NEW FUNCTIONS o bw.diggle Bandwidth selection for density.ppp by mean square error cross-validation. o bw.smoothppp Bandwidth selection for smooth.ppp by least-squares cross-validation. o layered, plot.layered A simple mechanism for controlling plots that consist of several successive layers of data. o model.depends Given a fitted model (of any kind), identify which of the covariates is involved in each term of the model. o model.is.additive Determine whether a fitted model (of any kind) is additive, in the sense that each term in the model involves at most one covariate. SIGNIFICANT USER-VISIBLE CHANGES o smooth.ppp Bandwidth 'sigma' is now selected by least-squares cross-validation o bw.relrisk Computation in large datasets accelerated. New arguments 'hmin', 'hmax' control the range of trial values of bandwidth. o Hest, Gfox, Jfox Improved algebraic labels for plot o spatstat.options New parameter 'n.bandwidth' o density.ppp, smooth.ppp Slightly accelerated. o point-in-polygon test Accelerated. BUG FIXES o with.fv Mathematical labels were incorrect in some cases. Fixed. o bw.relrisk Implementation of method="weightedleastsquares" was incorrect and was equivalent to method="leastsquares". Fixed. o smooth.ppp NaN values occurred if the bandwidth was very small. Fixed. CHANGES IN spatstat VERSION 1.23-3 OVERVIEW o Urgent bug fix. BUG FIXES o crossing.psp Crashed occasionally with a message about NA or NaN values. Fixed. o affine.ppp Crashed if the point pattern was empty. Fixed. CHANGES IN spatstat VERSION 1.23-2 OVERVIEW o Bug fixes. o Several functions have been accelerated. o We thank Marcelino de la Cruz and Ben Madin for contributions. NEW FUNCTIONS o sumouter, quadform Evaluate certain quadratic forms. o flipxy Exchange x and y coordinates. SIGNIFICANT USER-VISIBLE CHANGES o vcov.ppm Accelerated. o owin, as.owin Checking the validity of polygons has been accelerated. o crossing.psp, selfcrossing.psp Accelerated. BUG FIXES o split.ppp If drop=TRUE then some of the point patterns had the wrong windows. Spotted by Marcelino de la Cruz. Fixed. o split.ppp Crashed if the tessellation did not cover the point pattern. Fixed. o predict.ppm Crashed when type="se" if NA's were present. Spotted by Ben Madin. Fixed. o plot.ppp Incorrectly handled the case where both 'col' and 'cols' were present. Fixed. o polygon geometry The point-in-polygon test gave the wrong answer in some boundary cases. Fixed. CHANGES IN spatstat VERSION 1.23-1 OVERVIEW o Important bug fix to 'localpcf'. o Inverse-distance weighted smoothing. o Inhomogeneous versions of neighbourhood density functions. o Internal repairs and bug fixes. o We thank Mike Kuhn and Ben Madin for contributions. NEW FUNCTIONS o idw Inverse-distance weighted smoothing. o localKinhom, localLinhom, localpcfinhom Inhomogeneous versions of localK, localL, localpcf BUG FIXES o localpcf The columns of the result were in the wrong order. [i.e. pair correlation functions were associated with the wrong points.] Fixed. o delaunay If the union of several Delaunay triangles formed a triangle, this was erroneously included in the result of delaunay(). Fixed. o predict.ppm, plot.ppm Sometimes crashed with a warning about 'subscript out of bounds'. Fixed. o point-in-polygon test Vertices of a polygon were sometimes incorrectly classified as lying outside the polygon. Fixed. o Internal code Numerous tweaks and repairs to satisfy the package checker for the future R version 2.14. CHANGES IN spatstat VERSION 1.23-0 OVERVIEW o point patterns on a linear network: new tools including geometrically-corrected linear K function, pair correlation function, point process models, envelopes o changes to renormalisation of estimates in Kinhom and pcfinhom o new dataset: Chicago street crime o spatstat now 'Suggests:' the package RandomFields o spatstat now has a Namespace o we thank Mike Kuhn, Monia Mahling, Brian Ripley for contributions. NEW DATASET o chicago Street crimes in the University district of Chicago. A point pattern on a linear network. NEW FUNCTIONS o envelope.lpp Simulation envelopes for point patterns on a linear network o lineardisc Compute the 'disc' of radius r in a linear network o linearpcf Pair correlation for point pattern on a linear network o linearKinhom, linearpcfinhom Inhomogeneous versions of the K function and pair correlation function for point patterns on a linear network o lppm Fit point process models on a linear network. o anova.lppm Analysis of deviance for point process models on a linear network. o predict.lppm Prediction for point process models on a linear network. o envelope.lppm Simulation envelopes for point process models on a linear network. o linim Pixel image on a linear network o plot.linim Plot a pixel image on a linear network SIGNIFICANT USER-VISIBLE CHANGES o linearK New argument 'correction'. Geometrically-corrected estimation is performed by default (based on forthcoming paper by Ang, Baddeley and Nair) o Kinhom New argument 'normpower' allows different types of renormalisation. o pcfinhom Now performs renormalisation of estimate. Default behaviour changed - estimates are now renormalised by default. BUG FIXES o density.ppp Crashed if argument 'varcov' was given. Fixed. CHANGES IN spatstat VERSION 1.22-4 OVERVIEW o new diagnostics based on score residuals o new dataset o improvements to plotting summary functions o We thank Ege Rubak, Jesper Moller, George Leser, Robert Lamb and Ulf Mehlig for contributions. NEW FUNCTIONS o Gcom, Gres, Kcom, Kres New diagnostics for fitted Gibbs or Poisson point process models based on score residuals. Gcom is the compensator of the G function Gres is the residual of the G function Kcom is the compensator of the K function Kres is the residual of the K function o psst, psstA, psstG New diagnostics for fitted Gibbs or Poisson point process models based on pseudoscore residuals. psst is the pseudoscore diagnostic for a general alternative psstA is the pseudoscore diagnostic for an Area-interaction alternative psstG is the pseudoscore diagnostic for a Geyer saturation alternative o compareFit Computes and compares several point process models fitted to the same dataset, using a chosen diagnostic. o as.interact Extracts the interpoint interaction structure (without parameters) from a fitted point process model or similar object. NEW DATASET o flu Spatial point patterns giving the locations of influenza virus proteins on cell membranes. Kindly released by Dr George Leser and Dr Robert Lamb. SIGNIFICANT USER-VISIBLE CHANGES o pixel images and grids The default size of a pixel grid, given by spatstat.options("npixel"), has been changed from 100 to 128. A power of 2 gives faster and more accurate results in many cases. o residuals.ppm New arguments 'coefs' and 'quad' for advanced use (make it possible to compute residuals from a modified version of the fitted model.) o relrisk New argument 'casecontrol' determines whether a bivariate point pattern should be treated as case-control data. o plot.fv Further improvements in mathematical labels. o plot.fv The formula can now include the symbols .x and .y as abbreviation for the function argument and the recommended function value, respectively. o plot.fv New argument 'add' BUG FIXES o multitype summary functions (Kcross, Kdot, Gcross, Gdot, .....) Plotting these functions generated an error if the name of one of the types of points contained spaces, e.g. "Escherichia coli". Fixed. CHANGES IN spatstat VERSION 1.22-3 OVERVIEW o Important bug fix to simulation code o Miscellaneous improvements o spatstat now depends on R 2.13.0 or later o We thank Ege Rubak, Kaspar Stucki, Vadim Shcherbakov, Jesper Moller and Ben Taylor for contributions. NEW FUNCTIONS o is.stationary, is.poisson New generic functions for testing whether a point process model is stationary and/or Poisson. Methods for ppm, kppm, slrm etc o raster.xy raster coordinates of a pixel mask o zapsmall.im 'zapsmall' for pixel images SIGNIFICANT USER-VISIBLE CHANGES o density.ppp New argument 'diggle' allows choice of edge correction o rotate.owin, affine.owin These functions now handle binary pixel masks. New argument 'rescue' determines whether rectangles will be preserved BUG FIXES o rmh, simulate.ppm Serious bug - simulation was completely incorrect in the case of a multitype point process with an interaction that does not depend on the marks, such as ppm(betacells, ~marks, Strauss(60)) The calling parameters were garbled. Fixed. o effectfun Crashed if the covariate was a function(x,y). Fixed. o lurking Gave erroneous error messages about 'damaged' models. Fixed. o envelope.ppm Did not recognise when the fitted model was equivalent to CSR. Fixed. o plot.ppx Crashed in some cases. Fixed. CHANGES IN spatstat VERSION 1.22-2 OVERVIEW o Fitting and simulation of log-Gaussian Cox processes with any covariance function o More support for 'kppm' and 'rhohat' objects o K-function for point patterns on a linear network o Metropolis-Hastings algorithm now saves its transition history o Easier control of dummy points in ppm o Convert an 'fv' object to an R function o spatstat now depends on the package 'RandomFields' o We thank Abdollah Jalilian, Shen Guochun, Rasmus Waagepetersen, Ege Rubak and Ang Qi Wei for contributions. NEW FUNCTIONS o linearK Computes the Okabe-Yamada network K-function for a point pattern on a linear network. o pairdist.lpp Shortest-path distances between each pair of points on a linear network. o vcov.kppm Asymptotic variance-covariance matrix for regression parameters in kppm object. [Contributed by Abdollah Jalilian and Rasmus Waagepetersen] o rLGCP Simulation of log-Gaussian Cox processes [Contributed by Abdollah Jalilian and Rasmus Waagepetersen] o predict.rhohat Method for 'predict' for objects of class 'rhohat' Computes a pixel image of the predicted intensity. o Kmodel, pcfmodel Generic functions that compute the K-function or pair correlation function of a point process *model*. So far the only methods are for the class 'kppm'. o as.function.fv Converts a function value table (class 'fv') to a function in R o coef.kppm Method for 'coef' for objects of class 'kppm' o unitname, unitname<- These generic functions now have methods for fitted model objects (classes ppm, slrm, kppm, minconfit) and quadrature schemes (quad). o nobs.ppm Method for 'nobs' for class 'ppm'. Returns the number of points in the original data. SIGNIFICANT USER-VISIBLE CHANGES o kppm Can now fit a log-Gaussian Cox process o simulate.kppm Can now simulate a fitted log-Gaussian Cox process o lgcp.estK, lgcp.estpcf These functions previously fitted a log-Gaussian Cox process with exponential covariance. They can now fit a log-Gaussian Cox process with any covariance function implemented by the RandomFields package. o rmh If track=TRUE, the history of transitions of the Metropolis-Hastings algorithm is saved and returned. o ppm New argument 'nd' controls the number of dummy points. o as.fv Now handles objects of class kppm or minconfit. o rhohat If covariate = "x" or "y", the resulting object has the same 'unitname' as the original point pattern data. o rhohat Now has arguments 'eps, 'dimyx' to control pixel resolution. o MultiStrauss, MultiHard, MultiStraussHard Default value of 'types' has been changed to NULL. o data(ants) The auxiliary data 'ants.extra' now includes a function called 'side' determining whether a given location is in the scrub or field region. Can be used as a covariate in ppm, kppm, slrm. o print.ppm Now has argument 'what' to allow only selected information to be printed. BUG FIXES o profilepl Crashed in some cases involving multitype interactions. Fixed. o plot.splitppp Behaved incorrectly if 'main' was an expression. Fixed. o effectfun Crashed in trivial cases. Fixed. o kppm, thomas.estpcf, matclust.estpcf, lgcp.estpcf Gave a spurious warning message. Fixed. o step When applied to ppm objects this gave a spurious warning. Fixed. CHANGES IN spatstat VERSION 1.22-1 OVERVIEW o marked line segment patterns can now be plotted o multitype point process models are now 'self-starting' o new functions to manipulate colour images NEW FUNCTIONS o rgbim, hsvim Specify three colour channels. These functions convert three pixel images with numeric values into a single image whose pixel values are strings representing colours. o scaletointerval Generic utility function to rescale data (including spatial data) to a specified interval SIGNIFICANT USER-VISIBLE CHANGES o plot.im Can now plot images whose pixel values are strings representing colours. New argument 'valuesAreColours' o plot.psp Now handles marked line segment patterns and plots the marks as colours. o MultiHard, MultiStrauss, MultiStraussHard The argument 'types' can now be omitted; it will be inferred from the point pattern data. o rhohat Improved mathematical labels (when the result of rhohat is plotted) o plot.fv Minor improvements in graphics BUG FIXES o several minor bug fixes and improvements to satisfy R-devel CHANGES IN spatstat VERSION 1.22-0 OVERVIEW o support for point patterns on a linear network o 'superimpose' is now generic o improved mathematical labels when plotting functions NEW CLASSES o linnet An object of class 'linnet' represents a linear network, i.e. a connected network of line segments, such as a road network. Methods for this class include plot, print, summary etc. o lpp An object of class 'lpp' represents a point pattern on a linear network, such as a record of the locations of road accidents on a road network. Methods for this class include plot, print, summary etc. NEW FUNCTIONS o runiflpp Uniformly distributed random points on a linear network o rpoislpp Poisson point process on a linear network o clickjoin Interactive graphics to create a linear network o superimpose The function 'superimpose' is now generic, with methods for ppp, psp and a default method. o as.ppp.psp New method for as.ppp extracts the endpoints and marks from a line segment pattern NEW DATASETS o simplenet Simple example of a linear network SIGNIFICANT USER-VISIBLE CHANGES o superimposePSP This function is now deprecated in favour of 'superimpose' o superimpose Now handles data frames of marks. o plot.fv Argument 'legendmath' now defaults to TRUE. New argument 'legendargs' gives more control over appearance of legend. Increased default spacing between lines in legend. o eval.fv, with.fv Functions computed using eval.fv or with.fv now have better labels when plotted. o summary functions (Kest, Kest.fft, Kcross, Kdot, Kmulti, Kinhom, Kcross.inhom, Kdot.inhom, Kmulti.inhom, Lest, Lcross, Ldot, pcf, pcfcross, pcfdot, pcfinhom, pcfcross.inhom, pcfdot.inhom, Fest, Gest, Gcross, Gdot, Gmulti, Jest, Jcross, Jdot, Jmulti, Iest, localL, localK, markcorr, markvario, markconnect, Emark, Vmark, allstats, alltypes) Improved plot labels. BUG FIXES o superimpose If the marks components of patterns consisted of character vectors (rather than factors or non-factor numeric vectors) an error was triggered. Fixed. o plot.fv The y axis limits did not always cover the range of values if the argument 'shade' was used. Fixed. o plot.rhohat The y axis label was sometimes incorrect. Fixed. o plot.rhohat If argument 'xlim' was used, a warning was generated from 'rug'. Fixed. CHANGES IN spatstat VERSION 1.21-6 OVERVIEW o A line segment pattern can now have a data frame of marks. o Various minor extensions and alterations in behaviour NEW FUNCTIONS o nsegments Number of segments in a line segment pattern SIGNIFICANT USER-VISIBLE CHANGES o psp class A line segment pattern (object of class 'psp') can now have a data frame of marks. o density.ppp New argument 'adjust' makes it easy to adjust the smoothing bandwidth o plot.envelope If the upper envelope is NA but the lower envelope is finite, the upper limit is now treated as +Infinity o msr Argument 'continuous' renamed 'density' BUG FIXES o [.psp In X[W] if X is a line segment pattern and W is a polygonal window, marks were sometimes discarded, leading to an error. Fixed. o [.psp In X[W] if X is a line segment pattern and W is a rectangular window, if the marks of X were factor values, they were converted to integers. Fixed. o superimposePSP If the marks were a factor, they were mistakenly converted to integers. Fixed. o is.marked.ppp Did not generate a fatal error when na.action="fatal" as described in the help file. Fixed. CHANGES IN spatstat VERSION 1.21-5 OVERVIEW o Increased numerical stability. o New 'self-starting' feature of interpoint interactions. SIGNIFICANT USER-VISIBLE CHANGES o ppm Interaction objects may now be 'self-starting' i.e. initial parameter estimates can be computed from the point pattern dataset. So far, only the LennardJones() interaction has a self-starting feature. o LennardJones Increased numerical stability. New (optional) scaling argument 'sigma0'. Interpoint distances are automatically rescaled using 'self-starting' feature. o vcov.ppm New argument 'matrix.action' controls what happens when the matrix is ill-conditioned. Changed name of argument 'gamaction' to 'gam.action' o rmhmodel.ppm Default resolution of trend image has been increased. o is.poisson.ppm Accelerated. o ppm, kppm, qqplot.ppm Improved robustness to numerical error CHANGES IN spatstat VERSION 1.21-4 OVERVIEW o Urgent bug fix BUG FIXES o print.summary.ppm exited with an error message, if the model had external covariates. Fixed. CHANGES IN spatstat VERSION 1.21-3 OVERVIEW o Point process model covariates may now depend on additional parameters. o New class of signed measures, for residual analysis. o Miscellaneous improvements and bug fixes. NEW FUNCTIONS o clarkevans.test Classical Clark-Evans test of randomness o msr New class 'msr' of signed measures and vector-valued measures supporting residual analysis. o quadrat.test.quadratcount Method for 'quadrat.test' for objects of class 'quadratcount' (allows a chi-squared test to be performed on quadrat counts rather than recomputing from the original data) o tile.areas Computes areas of tiles in a tessellation (efficiently) SIGNIFICANT USER-VISIBLE CHANGES o ppm The spatial trend can now depend on additional parameters. This is done by allowing spatial covariate functions to have additional parameters: function(x, y, ...) where ... is controlled by the new argument 'covfunargs' to ppm o profilepl Can now maximise over trend parameters as well as interaction parameters o residuals.ppm The value returned by residuals.ppm is now an object of class 'msr'. It can be plotted directly. o eval.im When the argument 'envir' is used, eval.im() now recognises functions as well as variables in 'envir' o colourmap The argument 'col' can now be any kind of colour data o persp.im The 'colmap' argument can now be a 'colourmap' object o ppm The print and summary methods for 'ppm' objects now show standard errors for parameter estimates if the model is Poisson. o quadrat.test The print method for 'quadrattest' objects now displays information about the quadrats o lurking Improved format of x axis label o distmap.ppp Internal code is more robust. BUG FIXES o im Did not correctly handle 1 x 1 arrays. Fixed. o as.mask, pixellate.ppp Weird things happened if the argument 'eps' was set to a value greater than the size of the window. Fixed. CHANGES IN spatstat VERSION 1.21-2 OVERVIEW o New multitype hardcore interaction. o Nonparametric estimation of covariate effects on point patterns. o Output of 'Kmeasure' has been rescaled. o Numerous improvements and bug fixes. NEW FUNCTIONS o MultiHard multitype hard core interaction for use in ppm() o coords<- Assign new coordinates to the points in a point pattern o rhohat Kernel estimate for the effect of a spatial covariate on point process intensity SIGNIFICANT USER-VISIBLE CHANGES o as.ppp.matrix, as.ppp.data.frame These methods for 'as.ppp' now accept a matrix or data frame with any number of columns (>= 2) and interpret the additional columns as marks. o Kmeasure The interpretation of the output has changed: the pixel values are now density estimates. o rmh.ppm, rmhmodel.ppm These functions now accept a point process model fitted with the 'MultiHard' interaction o rmh.default, rmhmodel.default These functions now accept the option: cif='multihard' defining a multitype hard core interaction. o markcorr Now handles a data frame of marks o varblock Improved estimate in the case of the K function o colourmap, lut New argument 'range' makes it easier to specify a colour map or lookup table o [<-.hyperframe Now handles multiple columns o plot.fv Improved y axis labels o spatstat.options New option 'par.fv' controls default parameters for line plotting o rmhmodel More safety checks on parameter values. o quadratresample New argument 'verbose' o smooth.fv Default value of 'which' has been changed. BUG FIXES o Kest If the argument 'domain' was used, the resulting estimate was not correctly normalised. Fixed. o Kest The Lotwick-Silverman variance approximation was incorrectly calculated. (Spotted by Ian Dryden and Igor Chernayavsky). Fixed. o plot.owin, plot.ppp Display of binary masks was garbled if the window was empty or if it was equivalent to a rectangle. Fixed. o plot.bermantest One of the vertical lines for the Z1 test was in the wrong place. Fixed. o marks<-.ppx Crashed in some cases. Fixed. o is.convex An irrelevant warning was issued (for non-convex polygons). Fixed. CHANGES IN spatstat VERSION 1.21-1 OVERVIEW o Confidence intervals for K-function and other statistics o Bug fixes for smoothing and relative risk estimation NEW FUNCTIONS o varblock Variance estimation (and confidence intervals) for summary statistics such as Kest, using subdivision technique o bw.stoyan Bandwidth selection by Stoyan's rule of thumb. o which.max.im Applied to a list of images, this determines which image has the largest value at each pixel. o as.array.im Convert image to array SIGNIFICANT USER-VISIBLE CHANGES o smooth.ppp, markmean, sharpen.ppp, relrisk, bw.relrisk Further acceleration achieved. o Kest Argument 'correction' now explicitly overrides automatic defaults o plot.fv More robust handling of 'shade' BUG FIXES o relrisk Format of relrisk(at="points") was incorrect. Fixed. o bw.relrisk Result was incorrect in the default case method="likelihood" because of previous bug. Fixed. o Jdot, Jcross, Jmulti Return value did not include the hazard function, when correction="km" Fixed. o Jdot, Jcross, Jmulti Format of output was incompatible with format of Jest. Fixed. CHANGES IN spatstat VERSION 1.21-0 OVERVIEW o Implemented Spatial Logistic Regression o Implemented nonparametric estimation of relative risk with bandwidth selection by cross-validation. o Smoothing functions can handle a data frame of marks. o New options in Kinhom; default behaviour has changed. NEW FUNCTIONS o slrm Fit a spatial logistic regression model o anova.slrm, coef.slrm, fitted.slrm, logLik.slrm, plot.slrm, predict.slrm Methods for spatial logistic regression models o relrisk Nonparametric estimation of relative risk o bw.relrisk Automatic bandwidth selection by cross-validation o default.rmhcontrol Sets default values of Metropolis-Hastings parameters SIGNIFICANT USER-VISIBLE CHANGES o smooth.ppp, markmean These functions now accept a data frame of marks. o Kinhom Default behaviour has changed. New argument 'renormalise=TRUE' determines scaling of estimator and affects bias and variance in small samples. o residuals.ppm Now also computes the score residuals. o plot.im New argument 'ribscale' o plot.listof, plot.splitppp New arguments panel.begin, panel.end and panel.args o ppp Now checks for NA/NaN/Inf values in the coordinates o envelope.ppm Changed default value of 'control' New argument 'nrep' o qqplot.ppm Changed default value of 'control' BUG FIXES o marks<-.ppp, setmarks, %mark% A matrix of marks was accepted by ppp() but not by these assignment functions. Fixed. o density.ppp, smooth.ppp, sharpen.ppp, markmean Crashed if the bandwidth was extremely small. Fixed. CHANGES IN spatstat VERSION 1.20-5 OVERVIEW o Accelerated computations of kernel smoothing. o Implemented Choi-Hall data sharpening. NEW FUNCTIONS o sharpen.ppp Performs Choi-Hall data sharpening of a point pattern SIGNIFICANT USER-VISIBLE CHANGES o density.ppp, smooth.ppp Computation has been vastly accelerated for density(X, at="points") and smooth.ppp(X, at="points") o Kinhom Accelerated in case where lambda=NULL o Vignette 'shapefiles' updated CHANGES IN spatstat VERSION 1.20-4 OVERVIEW o New functions for inhomogeneous point patterns and local analysis. o Pair correlation function for 3D point patterns o Minor improvements and bug fixes to simulation code and image functions NEW FUNCTIONS o pcf3est Pair correlation function for 3D point patterns. o Kscaled, Lscaled Estimator of the template K function (and L-function) for a locally-scaled point process. o localpcf Local version of pair correlation function o identify.psp Method for 'identify' for line segment patterns. o as.im.matrix Converts a matrix to a pixel image SIGNIFICANT USER-VISIBLE CHANGES o rMaternI, rMaternII New argument 'stationary=TRUE' controls whether the simulated process is stationary (inside the simulation window). Default simulation behaviour has changed. o im New arguments 'xrange', 'yrange' o envelope Improvements to robustness of code. BUG FIXES o quadratcount If V was a tessellation created using a factor-valued image, quadratcount(X, tess=V) crashed with the error "Tessellation does not contain all the points of X". Fixed. o [.im If Z was a factor valued image and X was a point pattern then Z[X] was not a factor. Fixed. CHANGES IN spatstat VERSION 1.20-3 OVERVIEW o minor improvements (mostly internal). NEW FUNCTIONS o unmark.ppx Method for 'unmark' for general space-time point patterns SIGNIFICANT USER-VISIBLE CHANGES o plot.ppx Now handles marked patterns, in two-dimensional case o as.psp.psp Default value of argument 'check' set to FALSE CHANGES IN spatstat VERSION 1.20-2 OVERVIEW o Extensions to minimum contrast estimation. o Bug fix in simulation of Lennard-Jones model. o More support for distance functions. o Changes to point process simulations. NEW FUNCTIONS o thomas.estpcf Fit Thomas process model by minimum contrast using the pair correlation function (instead of the K-function). o matclust.estpcf Fit Matern Cluster model by minimum contrast using the pair correlation function (instead of the K-function). o lgcp.estpcf Fit log-Gaussian Cox process model by minimum contrast using the pair correlation function (instead of the K-function). o contour.distfun, persp.distfun Methods for 'contour' and 'persp' for distance functions o default.expand Computes default window for simulation of a fitted point process model. SIGNIFICANT USER-VISIBLE CHANGES o kppm Models can now be fitted using either the K-function or the pair correlation function. o ppm The list of covariates can now include windows (objects of class 'owin'). A window will be treated as a logical covariate that equals TRUE inside the window and FALSE outside it. o plot.distfun Pixel resolution can now be controlled. o envelope.ppm, qqplot.ppm The default value of 'control' has changed; simulation results may be slightly different. o rmh Slightly accelerated. BUG FIXES o rmh Simulation of the Lennard-Jones model (cif = 'lennard') was incorrect due to an obscure bug, introduced in spatstat 1.20-1. Fixed. o thomas.estK, matclust.estK, lgcp.estK The value of 'lambda' (if given) was ignored if X was a point pattern. Fixed. CHANGES IN spatstat VERSION 1.20-1 OVERVIEW o Further increases in speed and efficiency of ppm and rmh o New pairwise interaction model NEW FUNCTIONS o DiggleGatesStibbard Diggle-Gates-Stibbard pairwise interaction for use in ppm() SIGNIFICANT USER-VISIBLE CHANGES o ppm has been accelerated by a factor of 10 for the BadGey interaction. o rmh simulation of the Lennard-Jones model (cif='lennard') has been greatly accelerated. o rmh, rmhmodel.ppm Point process models fitted by ppm() using the DiggleGatesStibbard interaction can be simulated automatically using rmh. BUG FIXES o fitin The plot of a fitted Hardcore interaction was incorrect. Fixed. CHANGES IN spatstat VERSION 1.20-0 OVERVIEW o spatstat now contains over 1000 functions. o Substantial increase in speed and efficiency of model-fitting code. o Changes to factor-valued images. SIGNIFICANT USER-VISIBLE CHANGES o ppm has been accelerated by a factor of 10, and can handle datasets with 20,000 points, for the following interactions: DiggleGratton, Fiksel, Geyer, Hardcore, Strauss, StraussHard o predict.ppm accelerated by a factor of 3 (when type = "cif") with vastly reduced memory requirements for the following interactions: DiggleGratton, Fiksel, Geyer, Hardcore, Strauss, StraussHard o pixel images (class "im") The internal representation of factor-valued images has changed. Existing objects in the old format should still work. o im The syntax for creating a factor-valued image has changed. Argument 'lev' has been deleted. o ppm Some warnings have been reworded for greater clarity. BUG FIXES o [.im Mishandled some factor-valued images. Fixed. o hist.im Produced slightly erroneous output for some factor-valued images. Fixed. o plot.owin Filled polygons appeared to contain criss-cross lines on some graphics drivers. Fixed. o deltametric Did not handle windows with different enclosing frames (error message: 'dA and dB are incompatible') Fixed. o quadratcount Crashed if the pattern was empty and the window was a rectangle. (Noticed by Sandro Azaele) Fixed. o rNeymanScott Crashed if the parent process realisation was empty. (Noticed by Sandro Azaele) Fixed. CHANGES IN spatstat VERSION 1.19-3 ACKNOWLEDGEMENTS o We thank David Dereudre for contributions. OVERVIEW o Urgent bug fix to Metropolis-Hastings for Lennard-Jones model. o Miscellaneous additions to plotting and colour management. NEW FUNCTIONS o col2hex, rgb2hex, paletteindex, samecolour Functions for converting and comparing colours. o plot.envelope New method for plotting envelopes. By default the area between the upper and lower envelopes is shaded in grey. SIGNIFICANT USER-VISIBLE CHANGES o plot.fasp If the entries in the array are envelopes, they are plotted using plot.envelope (hence the envelope region is shaded grey). o plot.fv Now displays mathematical notation for each curve, if legendmath=TRUE. o print.fv Now prints the available range of 'r' values as well as the recommended range of 'r' values. BUG FIXES o rmh Simulation of Lennard-Jones model was incorrect; the simulations were effectively Poisson patterns. (Spotted by David Dereudre.) Fixed. o plot.fv Did not correctly handle formulas that included I( ) Fixed. CHANGES IN spatstat VERSION 1.19-2 ACKNOWLEDGEMENTS o We thank Jorge Mateu, Michael Sumner and Sebastian Luque for contributions. OVERVIEW o More support for fitted point process models and pixel images. o Improved plotting of pixel images and envelopes. o Simulation algorithm for Lennard-Jones process. o Improvements and bug fixes to envelopes. o Bug fixes to Metropolis-Hastings simulation. NEW FUNCTIONS o pairs.im Creates a scatterplot matrix for several pixel images. o model.frame.ppm Method for 'model.frame' for point process models. o sort.im Method for 'sort' for pixel images. SIGNIFICANT USER-VISIBLE CHANGES o plot.fv, plot.fasp New argument 'shade' enables confidence intervals or significance bands to be displayed as filled grey shading. o LennardJones The parametrisation of this interaction function has been changed. o rmh, rmhmodel These functions will now simulate a point process model that was fitted using the LennardJones() interaction. o rmh.default, rmhmodel.default These functions will now simulate a point process model with the Lennard-Jones interaction (cif='lennard'). o ecdf This function now works for pixel images. o dim, row, col These functions now work for pixel images. o order This function now works for pixel images. o [.im and [<-.im The subset index can now be any valid subset index for a matrix. o density.ppp, smooth.ppp The return value now has attributes 'sigma' and 'varcov' reporting the smoothing bandwidth. o plot.im The argument 'col' can now be a 'colourmap' object. This makes it possible to specify a fixed mapping between numbers and colours (e.g. so that it is consistent between plots of several different images). o rmh, spatstat.options spatstat.options now recognises the parameter 'expand' which determines the default window expansion factor in rmh. o rmh Improved handling of ppm objects with covariates. o kstest The 'covariate' can now be one of the characters "x" or "y" indicating the Cartesian coordinates. BUG FIXES o model.matrix.ppm For a fitted model that used a large number of quadrature points, model.matrix.ppm sometimes reported an internal error about mismatch between the model matrix and the quadrature scheme. Fixed. o plot.ppx Minor bugs fixed. o rmh In rare cases, the simulated point pattern included multiple points at the origin (0,0). (Bug introduced in spatstat 1.17-0.) Fixed. o rmh, rmhmodel.ppm Crashed when applied to a fitted multitype point process model if the model involved more than one covariate image. (Spotted by Jorge Mateu) Fixed. o density.psp If any segment had zero length, the result contained NaN values. (Spotted by Michael Sumner and Sebastian Luque.) Fixed. o envelope Crashed with fun=Lest or fun=Linhom if the number of points in a simulated pattern exceeded 3000. Fixed. o plot.kstest Main title was corrupted if the covariate was a function. Fixed. CHANGES IN spatstat VERSION 1.19-1 OVERVIEW o New dataset: replicated 3D point patterns. o Improvements to Metropolis-Hastings simulation code. o More support for hyperframes. o Bug fixes. NEW DATASETS o osteo: Osteocyte Lacunae data: replicated 3D point patterns NEW FUNCTIONS o rbind.hyperframe: Method for rbind for hyperframes. o as.data.frame.hyperframe: Converts a hyperframe to a data frame. SIGNIFICANT USER-VISIBLE CHANGES o Fiksel: Fitted point process models (class ppm) with the Fiksel() double exponential interaction can now be simulated by rmh. o rmh.default: Point processes with the Fiksel interaction can now be simulated by specifying parameters in rmh.default. o logLik.ppm: New argument 'warn' controls warnings. o profilepl: No longer issues spurious warnings. BUG FIXES o Hardcore, rmh: Simulation of the 'Hardcore' process was incorrect. The hard core radius was erroneously set to zero so that the simulated patterns were Poisson. Fixed. o fitin: A plot of the pairwise interaction function of a fitted model, generated by plot(fitin(model)) where model <- ppm(...), was sometimes incorrect when the model included a hard core. Fixed. CHANGES IN spatstat VERSION 1.19-0 OVERVIEW o Numerous bugs fixed in the implementation of the Huang-Ogata approximate maximum likelihood method. o New interpoint interaction model. NEW FUNCTIONS o Fiksel: new interpoint interaction: Fiksel's double exponential model. SIGNIFICANT USER-VISIBLE CHANGES o runifpoint, rpoispp, envelope These functions now issue a warning if the number of random points to be generated is very large. This traps a common error in simulation experiments. BUG FIXES o predict.ppm, fitted.ppm: Predictions and fitted values were incorrect for objects fitted using ppm(..., method="ho"). Fixed. o logLik, AIC: Values of logLik() and AIC() were incorrect for objects fitted using ppm(..., method="ho"). Fixed. o profilepl: Results were incorrect if the argument 'method="ho"' was used. Fixed. o fitin The result of fitin() was incorrect for objects fitted using ppm(..., method="ho"). Fixed. o rmhcontrol: rmhcontrol(NULL) generated an error. Fixed. CHANGES IN spatstat VERSION 1.18-4 ACKNOWLEDGEMENTS o We thank Michael Sumner for contributions. BUG FIXES o pixellate.psp: segments shorter than one pixel width were measured incorrectly if the 'weights' argument was present. Fixed. NEW FUNCTIONS o pairdist.ppx, crossdist.ppx, nndist.ppx, nnwhich.ppx: Methods for pairdist, crossdist, nndist, nnwhich for multidimensional point patterns (class 'ppx') o runifpointx, rpoisppx: Random point patterns in any number of dimensions o boxx: Multidimensional box in any number of dimensions o diameter.boxx, volume.boxx, shortside.boxx, eroded.volumes.boxx: Geometrical computations for multidimensional boxes o sum.im, max.im, min.im: Methods for sum(), min(), max() for pixel images. o as.matrix.ppx: Convert a multidimensional point pattern to a matrix SIGNIFICANT USER-VISIBLE CHANGES o plot.ppp: New argument 'zap' o diameter: This function is now generic, with methods for "owin", "box3" and "boxx" o eroded.volumes: This function is now generic, with methods for "box3" and "boxx" CHANGES IN spatstat VERSION 1.18-3 ACKNOWLEDGEMENTS o We thank Michael Sumner for contributions. BUG FIXES o pixellate.psp: segments shorter than one pixel width were measured incorrectly. Fixed. o fv: 'alim' not handled correctly. Fixed. NEW FUNCTIONS o smooth.fv: Applies spline smoothing to the columns of an fv object. CHANGES IN spatstat VERSION 1.18-2 ACKNOWLEDGEMENTS o We thank Michael Sumner for contributions. NEW FUNCTIONS o Gfox, Jfox: Foxall's G and J functions o as.owin.distfun: New method for as.owin extracts the domain of a distfun object. SIGNIFICANT USER-VISIBLE CHANGES o distfun: objects of class 'distfun', when called as functions, will now accept either two vectors (x,y) or a point pattern x. o Hest: this function can now compute the Hanisch estimator. It now has arguments 'r', 'breaks' and 'correction', like other summary functions. o Hest: new argument 'conditional'. BUG FIXES o pixellate.psp: Values were sometimes incorrect due to coding error. (Spotted by Michael Sumner) Fixed. o kstest: Crashed if the covariate contained NA's. Fixed. o kstest: Crashed if X was a multitype point pattern in which some mark values were unrepresented. Fixed. o lurking: Minor bug in handling of NA values. Fixed. o Hest: labels of columns were incorrect. Fixed. CHANGES IN spatstat VERSION 1.18-1 ACKNOWLEDGEMENTS o we thank Andrew Bevan and Ege Rubak for suggestions. NEW FUNCTIONS o Hardcore: Hard core interaction (for use in ppm) o envelope.pp3: simulation envelopes for 3D point patterns o npoints: number of points in a point pattern of any kind SIGNIFICANT USER-VISIBLE CHANGES o rmh.ppm, rmhmodel.ppm: It is now possible to simulate Gibbs point process models that are fitted to multitype point patterns using a non-multitype interaction, e.g. data(amacrine) fit <- ppm(amacrine, ~marks, Strauss(0.1)) rmh(fit, ...) o rmh.ppm, rmhmodel.ppm, rmh.default, rmhmodel.default: Hard core models can be simulated. o rmh.default, rmhmodel.default: The argument 'par' is now required to be a list, in all cases (previously it was sometimes a list and sometimes a vector). o Fest: Calculation has been accelerated in some cases. o summary.pp3 now returns an object of class 'summary.pp3' containing useful summary information. It is plotted by 'plot.summary.pp3'. o F3est, G3est, K3est: these functions now accept 'correction="best"' o union.owin, intersect.owin: these functions now handle any number of windows. o envelope.ppp, envelope.ppm, envelope.kppm: argument lists have changed slightly BUG FIXES o Fest: The result of Fest(X, correction="rs") had a slightly corrupted format, so that envelope(X, Fest, correction="rs") in fact computed the envelopes based on the "km" correction. (Spotted by Ege Rubak). Fixed. o rmh (rmh.ppm, rmhmodel.ppm): rmh sometimes failed for non-stationary point process models, with a message about "missing value where TRUE/FALSE needed". (Spotted by Andrew Bevan). Fixed. o diagnose.ppm, lurking: Calculations were not always correct if the model had conditional intensity equal to zero at some locations. Fixed. o ppm, profilepl: If data points are illegal under the model (i.e. if any data points have conditional intensity equal to zero) the log pseudolikelihood should be -Inf but was sometimes returned as a finite value. Thus profilepl did not always work correctly for models with a hard core. Fixed. o F3est, G3est: Debug messages were printed unnecessarily. Fixed. CHANGES IN spatstat VERSION 1.18-0 ACKNOWLEDGEMENTS o we thank Ege Rubak and Tyler Dean Rudolph for suggestions. HEADLINES o A point pattern is now allowed to have a data frame of marks (previously the marks had to be a vector). o Extended capabilities for 'envelope' and 'kstest'. NEW FUNCTIONS o pixellate.psp, as.mask.psp Convert a line segment pattern to a pixel image or binary mask o as.data.frame.im Convert a pixel image to a data frame SIGNIFICANT USER-VISIBLE CHANGES o A point pattern is now allowed to have a data frame of marks (previously the marks had to be a vector). o Many functions in spatstat now handle point patterns with a data frame of marks. These include print.ppp, summary.ppp, plot.ppp, split.ppp. o finpines, nbfires, shapley: The format of these datasets has changed. They are now point patterns with a data frame of marks. o envelope() is now generic, with methods for "ppp", "ppm" and "kppm". o kstest() now handles multitype point patterns and multitype point process models. o nnclean() now returns a point pattern with a data frame of marks. o plot.ppp() has new argument 'which.marks' to select one column from a data frame of marks to be plotted. o plot.ppp() now handles marks that are POSIX times. o complement.owin now handles any object acceptable to as.owin. BUG FIXES o erosion(w) and opening(w) crashed if w was not a window. Fixed. o diameter() and eroded.areas() refused to work if w was not a window. Fixed. CHANGES IN spatstat VERSION 1.17-6 ACKNOWLEDGEMENTS o We thank Simon Byers and Adrian Raftery for generous contributions. OVERVIEW o Nearest neighbour clutter removal algorithm o New documentation for the 'fv' class. o Minor improvements and bug fixes. NEW FUNCTIONS o nnclean: Nearest neighbour clutter removal for recognising features in spatial point patterns. Technique of Byers and Raftery (1998) [From original code by Simon Byers and Adrian Raftery, adapted for spatstat.] o marks.ppx, marks<-.ppx: Methods for extracting and changing marks in a multidimensional point pattern o latest.news: print news about the current version of the package SIGNIFICANT USER-VISIBLE CHANGES o news: spatstat now has a NEWS file which can be printed by typing news(package="spatstat"). o areaGain, areaLoss: New algorithms in case exact=TRUE. Syntax slightly modified. o with.hyperframe: - The result now inherits 'names' from the row names of the hyperframe. - New argument 'enclos' controls the environment in which the expression is evaluated. - The algorithm is now smarter at simplifying the result when simplify=TRUE. o update.ppm: Tweaked to improve the ability of ppm objects to be re-fitted in different contexts. ADVANCED USERS ONLY o Documentation for the class 'fv' of function value tables - fv: Creates an object of class 'fv' - cbind.fv, collapse.fv: Combine objects of class 'fv' - bind.fv: Add additional columns of data to an 'fv' object BUG FIXES o "$<-.hyperframe" destroyed the row names of the hyperframe. Fixed. o model.matrix.ppm had minor inconsistencies. Fixed. o ppm: The fitted coefficient vector had incorrect format in the default case of a uniform Poisson process. Fixed. o plot.ppx: Crashed if the argument 'main' was given. Fixed. o envelope.ppp: Crashed if the object returned by 'fun' did not include a column called "theo". Fixed. spatstat/R/0000755000176200001440000000000014141460522012315 5ustar liggesusersspatstat/R/news.R0000644000176200001440000000252014144335731013421 0ustar liggesusers# # news.R # # News and warnings # latest.news <- function(package=spatstat.family(), doBrowse=FALSE, major=TRUE) { stopifnot(is.character(package)) n <- length(package) result <- vector(mode="list", length=n) names(result) <- package for(i in seq_len(n)) { pack <- package[i] ## get version number v <- read.dcf(file=system.file("DESCRIPTION", package=pack), fields="Version") if(major) { ## the current major version vp <- package_version(v) vv <- unlist(vp) v <- paste0(vv[1], ".", vv[2]) } ne <- eval(substitute(news(Version >= v0, package=pack), list(v0=v))) if(n > 1 && !doBrowse) { hdr <- paste0("Package ", sQuote(pack), ":") if(interactive()) readline(hdr) else cat(paste(hdr, "\n")) } page(ne, method="print", doBrowse=doBrowse) result[[i]] <- ne } if(n == 1) result <- result[[1]] return(invisible(result)) } class(latest.news) <- "autoexec" spatstat.family <- function(subpackages=TRUE, extensions=FALSE) { sub <- c("spatstat.utils", "spatstat.data", "spatstat.sparse", "spatstat.geom", "spatstat.core", "spatstat.linnet", "spatstat") ext <- c("spatstat.gui", "spatstat.local", "spatstat.Knet") result <- c(if(subpackages) sub else NULL, if(extensions) ext else NULL) as.character(result) } spatstat/R/bugtable.R0000644000176200001440000000723014144335731014235 0ustar liggesusers#' #' bugtable.R #' #' $Revision: 1.10 $ $Date: 2021/09/06 05:28:59 $ bugfixes <- function(sinceversion=NULL, sincedate=NULL, package=spatstat.family(), show=TRUE) { package <- as.character(package) is.spat <- package %in% spatstat.family(TRUE, TRUE) if("book" %in% list(sinceversion, sincedate)) { ## special usage sinceversion <- NULL sincedate <- "2015-06-05" } n <- length(package) z <- NULL for(i in seq_len(n)) { packi <- package[i] if("all" %in% list(sinceversion, sincedate)) { ## no date constraint - show all news a <- eval(substitute(news(grepl("^BUG", Category), package=packi))) } else if(!is.null(sincedate) && !is.spat[i]) { #' news items after specified date #' non-spatstat package ne <- news(package=packi) if(is.null(ne) || is.null(ne$Date) || anyNA(ne$Date)) stop(paste(if(is.null(ne)) "News" else "Date", "information is not available for package", sQuote(packi)), call.=FALSE) a <- eval(substitute(news(Date >= SD & grepl("^BUG", Category), package=packi), list(SD=sincedate))) } else { #' determine a corresponding version number if(is.null(sinceversion) && is.null(sincedate)) { #' default is latest version dfile <- system.file("DESCRIPTION", package=packi) sinceversion <- read.dcf(file=dfile, fields="Version") } else if(!is.null(sincedate) && is.spat[i]) { #' read release history table fname <- system.file("doc", "packagesizes.txt", package=packi) p <- read.table(fname, header=TRUE, stringsAsFactors=FALSE) #' find earliest package version on or after the given date imin <- with(p, min(which(as.Date(date) >= sincedate))) sinceversion <- p[imin, "version"] } a <- eval(substitute(news(Version >= sv & grepl("^BUG", Category), package=packi), list(sv=sinceversion))) } #' convert format if(is.data.frame(a) && nrow(a) > 0) { #' split each entry into lines alines <- strsplit(a$Text, "\n") #' extract first line f <- unname(sapply(alines, "[", i=1L)) #' extract body b <- unname(lapply(alines, "[", i=-1L)) b <- unname(sapply(b, paste, collapse="\n")) #' extract header from first line h <- unname(sapply(strsplit(f, ":"), "[", i=1L)) h <- unname(sapply(strsplit(h, ","), "[", i=1L)) h <- unname(sapply(strsplit(h, " "), "[", i=1L)) #' rebuild zi <- data.frame(Header=h, Firstline=f, Body=b, Version=a$Version, stringsAsFactors=FALSE) if(n > 1) zi$Package <- packi z <- if(i == 1) zi else rbind(z, zi) } } if(is.null(z)) return(NULL) #' sort by header oo <- with(z, order(Header, Firstline)) z <- z[oo, ] #' wrap up class(z) <- c("bugtable", class(z)) if(show) page(z, method="print") return(invisible(z)) } class(bugfixes) <- "autoexec" print.bugtable <- function(x, ...) { hprev <- "" haspack <- "Package" %in% colnames(x) for(i in seq_len(nrow(x))) { h <- x$Header[i] f <- x$Firstline[i] v <- x$Version[i] p <- if(haspack) x$Package[i] else NULL b <- x$Body[i] if(h != hprev) { # new main header cat("\n***", h, "***\n", fill=TRUE) } if(haspack) cat(p, v, ":", f, fill=TRUE) else cat(v, ":", f, fill=TRUE) cat(b, "\n", fill=TRUE) hprev <- h } return(invisible(NULL)) } spatstat/R/First.R0000644000176200001440000000155614141460522013536 0ustar liggesusers## spatstat/R/First.R .onLoad <- function(...) { reset.spatstat.options() umf <- system.file("doc", "umbrella.txt", package="spatstat") isum <- !is.null(umf) && file.exists(umf) putSpatstatVariable("Spatstat.Is.Umbrella", isum) invisible(NULL) } .onAttach <- function(libname, pkgname) { vs <- read.dcf(file=system.file("DESCRIPTION", package="spatstat"), fields="Version") vs <- as.character(vs) putSpatstatVariable("SpatstatVersion", vs) nickfile <- system.file("doc", "Nickname.txt", package="spatstat") ni <- scan(file=nickfile, what=character(), n=1, quiet=TRUE) msg <- paste("\nspatstat", vs, " ", paren(paste("nickname:", sQuote(ni))), "\nFor an introduction to spatstat, type", sQuote("beginner"), "\n") packageStartupMessage(msg) return(invisible(NULL)) } spatstat/R/beginner.R0000644000176200001440000000174114144335731014242 0ustar liggesusers# # beginner.R # # Helpful information for beginners # # $Revision: 1.3 $ $Date: 2015/10/21 09:06:57 $ # print.autoexec <- function(x, ...) { x() } beginner <- function(package="spatstat") { package <- as.character(substitute(package)) RShowDoc("BEGINNER.txt", type="txt", package=package) return(invisible(NULL)) } class(beginner) <- "autoexec" foo <- local({ fooText <- paste0("Error: object 'foo' not found.\n\n", "'foo' is not a defined variable or function.\n", "It is a placeholder name, which serves only to ", "demonstrate a concept. It represents the name of ", "any desired object or function. ", "Other placeholder names popular with computer scientists ", "are 'bar', 'foobar', 'qux' and 'mork'.") foo <- function() { splat(fooText) return(invisible(NULL)) } class(foo) <- "autoexec" foo }) plot.foo <- function(x, ...) foo() spatstat/MD50000644000176200001440000000615614155350602012436 0ustar liggesuserse06d04f080d29fb5d4ec29102ddf0e9b *DESCRIPTION 5574ba0f7f8c73d792d81ecc28bacaf0 *NAMESPACE 40188b052235e111fc569557c82ea9b5 *NEWS 49905919b82868975d4ebda0b60e9552 *R/First.R 789f24a9b671b204cca2bea93c57a49e *R/beginner.R e1f7a0377fb27735eeefab4efa62b71c *R/bugtable.R f8e2b275811c50b1b137dfc282be49e1 *R/news.R 4c8e0a77fd6de537e03de77c7f8a18d2 *build/vignette.rds 864845ec756c9bdd720c4399e3aff644 *demo/00Index 68d9e760c09449956b5a218bf1c91fbd *demo/data.R 69fec98d1b46c8c3205c44b677e6da15 *demo/diagnose.R fcf9060eb6ef637cbecdbb7614dc62a2 *demo/spatstat.R 0382b9ed5e27f7c537787d3d2c654ea2 *demo/sumfun.R 152bbf4b15996c2c583ad5578f14d45b *inst/CITATION 40b7c225a16a40129627f60b05dcbe32 *inst/doc/BEGINNER.txt 9e197a3a019e6a4cfde5eea3664bbcf0 *inst/doc/Nickname.txt 0692d176362b7733c3eae77f82bb0611 *inst/doc/bugfixes.R 0d6ae172b3341f7bec10ebdeba253c9d *inst/doc/bugfixes.Rnw 36dc60eb2bf1b847982579ab4dda4e20 *inst/doc/bugfixes.pdf 58ba77a7058b2a65bed152577baf73b6 *inst/doc/datasets.R c155ddffd6d0d352273a5d7720108072 *inst/doc/datasets.Rnw 373d817e2502e43d8fab915cd9c7633f *inst/doc/datasets.pdf f10eb74b6eb784867cb8e1e28b1d31c7 *inst/doc/getstart.R 23c7cff7980144d2d528097174bf7114 *inst/doc/getstart.Rnw 30180e290dd799df47f08f0d18877921 *inst/doc/getstart.pdf 915cac05e679985ba01ee56a8cc937c6 *inst/doc/packagesizes.txt 52355a471d94901f23144944391cd5f4 *inst/doc/replicated.R 471ba4e0d3f21bfb11da447894ed47d4 *inst/doc/replicated.Rnw a1f3bb1c0b247a00029714136b4067a8 *inst/doc/replicated.pdf 4fe0175127f4df355434ef95e954db03 *inst/doc/shapefiles.R 0bd1c5d601f8b5a1f966bc5d746dbdb7 *inst/doc/shapefiles.Rnw 61b9ef9fbd8fd4c20a86b8dc9b2d48f0 *inst/doc/shapefiles.pdf 898374b07a47ea71311df5e834d379f8 *inst/doc/spatstatKnetsize.txt 39b63203d98bbdec141a0a9e4d69187f *inst/doc/spatstatguisize.txt ae9c750aa338ceb790513a358fb42af7 *inst/doc/spatstatlocalsize.txt eb4585ad9fe0426781ed7c49252f8225 *inst/doc/umbrella.txt 3a4ea5fc62d915a5120e39e5af569f1c *inst/doc/updates.R 0b580929324c88035ac9e92910185e14 *inst/doc/updates.Rnw b0e18e2edfb2d30da36acb9ce139ec0e *inst/doc/updates.pdf a843cd73ef1835fe4ea1a0ae21377f01 *man/beginner.Rd 640564db9b663cbf748d8ced982b6681 *man/bugfixes.Rd a80e59ebd95db6eb22126f9c9db42621 *man/foo.Rd f3ad2abca6bb193bf551edac8b7a61bc *man/latest.news.Rd 390c43841b92ba3277f25852a55d2cc9 *man/macros/defns.Rd 65fcc10944432c768f8368b2562587e7 *man/spatstat-internal.Rd ea33c262bf6e5fdc118344ed887075c5 *man/spatstat-package.Rd cc96e89175e335db3d8ead88f8658b69 *man/spatstat.family.Rd 0d6ae172b3341f7bec10ebdeba253c9d *vignettes/bugfixes.Rnw c155ddffd6d0d352273a5d7720108072 *vignettes/datasets.Rnw 23c7cff7980144d2d528097174bf7114 *vignettes/getstart.Rnw 8cda84badf5153c61e2b6b2e7bf14322 *vignettes/hexagon.eps 28c409e6cfde065a32cdc922787086ec *vignettes/hexagon.pdf 5d818e3b6c4cc36b55b35289c3282394 *vignettes/irregpoly.eps 1dd34a3acaa93d24bf0388fa83caf892 *vignettes/irregpoly.pdf 17601cddcf7c30437a7657106ed958d7 *vignettes/mask.eps f3867232ba6adc3951f2c73f827df4b3 *vignettes/mask.pdf 471ba4e0d3f21bfb11da447894ed47d4 *vignettes/replicated.Rnw 0bd1c5d601f8b5a1f966bc5d746dbdb7 *vignettes/shapefiles.Rnw 0b580929324c88035ac9e92910185e14 *vignettes/updates.Rnw spatstat/inst/0000755000176200001440000000000014141377564013106 5ustar liggesusersspatstat/inst/doc/0000755000176200001440000000000014155343651013646 5ustar liggesusersspatstat/inst/doc/updates.Rnw0000644000176200001440000035275114155343622016016 0ustar liggesusers\documentclass[11pt]{article} \usepackage{graphicx} \usepackage{Sweave} \usepackage{bm} \usepackage{anysize} \marginsize{2cm}{2cm}{2cm}{2cm} % \VignetteIndexEntry{Summary of Recent Updates to the Spatstat Family} % $Revision: 1.53 $ $Date: 2021/11/21 02:03:40 $ \newcommand{\pkg}[1]{\texttt{#1}} \newcommand{\code}[1]{\texttt{#1}} \newcommand{\R}{{\sf R}} \newcommand{\spst}{\pkg{spatstat}} \newcommand{\Spst}{\pkg{Spatstat}} \begin{document} \bibliographystyle{plain} <>= library(spatstat) x <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = c("Version", "Date")) sversion <- as.character(x[,"Version"]) sdate <- as.character(x[,"Date"]) options(useFancyQuotes=FALSE) @ \title{Summary of recent updates to \spst} \author{Adrian Baddeley, Rolf Turner and Ege Rubak} \date{\today} \maketitle \thispagestyle{empty} <>= readSizeTable <- function(fname) { if(is.null(fname) || !file.exists(fname)) return(NULL) a <- read.table(fname, header=TRUE) a$date <- as.Date(a$date) return(a) } getSizeTable <- function(packagename="spatstat", tablename="packagesizes.txt") { fname <- system.file("doc", tablename, package=packagename) readSizeTable(fname) } RemoveDevel <- function(sizetable) { ## remove entries with fractional version numbers if(is.null(sizetable)) return(NULL) ver <- sizetable$version isdevel <- sapply(ver, function(x) { length(unlist(package_version(x))) > 3 }) st <- if(all(isdevel)) NULL else sizetable[!isdevel, , drop=FALSE] return(st) } counts <- c("nhelpfiles", "nobjects", "ndatasets", "Rlines", "srclines") mergeSizeTables <- function(a, b, breakupdate, allow.devel=FALSE) { #' a is the running total for spatstat; b is a sub-package. #' breakupdate is the date when the code in b was removed from spatstat #' so that the size of 'b' must be added to 'a' for all dates >= breakupdate if(!allow.devel) b <- RemoveDevel(b) if(is.null(b)) return(a) adates <- a$date bdates <- b$date alldates <- sort(unique(c(adates,bdates))) if(missing(breakupdate)) breakupdate <- min(bdates) #' functions to determine, for any given date, #' the relevant (latest) row of the table aok <- rev(!duplicated(rev(adates))) arowfun <- approxfun(adates[aok], seq_along(adates)[aok], method="constant", f=0, rule=2, yleft=0) bok <- rev(!duplicated(rev(bdates))) browfun <- approxfun(bdates[bok], seq_along(bdates)[bok], method="constant", f=0, rule=2, yleft=0) result <- NULL for(k in seq_along(alldates)) { thedate <- alldates[k] i <- arowfun(thedate) j <- browfun(thedate) #' i > 0 because spatstat's founding date is earlier than any sub-package nextrow <- a[i, ] if(j > 0 && thedate >= breakupdate) { #' add contribution from 'b' nextrow[, counts] <- nextrow[, counts] + b[j, counts] } result <- rbind(result, nextrow) } return(result) } ## start collating size tables for the spatstat family z <- getSizeTable() ## sub-packages- access via the sub-package zgeom <- getSizeTable("spatstat.geom") zcore <- getSizeTable("spatstat.core") zlin <- getSizeTable("spatstat.linnet") zutils <- getSizeTable("spatstat.utils") zdata <- getSizeTable("spatstat.data") zsparse <- getSizeTable("spatstat.sparse") ## merge history of geom, core, linnet after the big split Bday <- "2020-12-14" z <- mergeSizeTables(z, zgeom, Bday) z <- mergeSizeTables(z, zcore, Bday) z <- mergeSizeTables(z, zlin, Bday) ## merge history of other packages after their split dates z <- mergeSizeTables(z, zutils, "2017-03-22") z <- mergeSizeTables(z, zdata, "2017-09-23") z <- mergeSizeTables(z, zsparse, "2020-11-04") ## extension packages - use copy of package size file stored in spatstat zlocal <- getSizeTable("spatstat", "spatstatlocalsize.txt") zgui <- getSizeTable("spatstat", "spatstatguisize.txt") zKnet <- getSizeTable("spatstat", "spatstatKnetsize.txt") z <- mergeSizeTables(z, zlocal) z <- mergeSizeTables(z, zgui) z <- mergeSizeTables(z, zKnet) # currentcount <- z[nrow(z), counts] bookcount <- z[z$version == "1.42-0", counts] changes <- currentcount - bookcount newobj <- changes[["nobjects"]] newdat <- changes[["ndatasets"]] + 1 # counting rule doesn't detect redwood3 newcode <- changes[["Rlines"]] + changes[["srclines"]] bookcode <- bookcount[["Rlines"]] + bookcount[["srclines"]] currentcode <- currentcount[["Rlines"]] + currentcount[["srclines"]] growth <- signif((100 * newcode)/bookcode, digits=2) @ %$ This is a summary of changes to the \spst\ package that have occurred since the publication of the book \cite{baddrubaturn15} in 2015. Since then, the \spst\ family has grown by \Sexpr{growth}\%, including \Sexpr{newobj} new functions and \Sexpr{newdat} new datasets, and now contains more than \Sexpr{10 * floor(currentcode/10000)},000 lines of code. This document summarises the most important changes. <>= options(SweaveHooks=list(fig=function() par(mar=0.2+c(2,4,2,0)))) Plot <- function(fmla, ..., dat=z) { yvals <- eval(as.expression(fmla[[2]]), envir=dat) plot(fmla, ..., data=dat, type="l", xlab="", lwd=2, ylim=c(0, max(yvals))) } @ \SweaveOpts{eps=TRUE} \setkeys{Gin}{width=0.55\textwidth} \centerline{ <>= Plot((Rlines + srclines)/1000 ~ date, ylab="Lines of code (x 1000)", main="Spatstat growth") lines(srclines/1000 ~ date, data=z) text(as.Date("2015-01-01"), 9.5, "C code") text(as.Date("2015-01-01"), 60, "R code") @ } \setcounter{tocdepth}{1} \tableofcontents \newpage \newpage \section{Version information} The book \cite{baddrubaturn15}, published in December 2015, covered \spst\ version \texttt{1.42-0}, released in May 2015. <>= ## Tabulate latest version numbers of packages vtable <- data.frame(package="spatstat", version=sversion, date=as.Date(sdate)) AppendVersion <- function(pkg, sizetable, v, allow.devel=FALSE) { if(!allow.devel) sizetable <- RemoveDevel(sizetable) if(is.null(sizetable)) return(v) lastrow <- sizetable[nrow(sizetable), , drop=FALSE] if(is.null(lastrow)) return(v) rbind(v, data.frame(package=pkg, version=lastrow[,"version"], date=as.Date(lastrow[,"date"]))) } vtable <- AppendVersion("spatstat.geom", zgeom, vtable) vtable <- AppendVersion("spatstat.core", zcore, vtable) vtable <- AppendVersion("spatstat.linnet", zlin, vtable) vtable <- AppendVersion("spatstat.sparse", zsparse, vtable) vtable <- AppendVersion("spatstat.data", zdata, vtable) vtable <- AppendVersion("spatstat.utils", zutils, vtable) vtable <- AppendVersion("spatstat.local", zlocal, vtable) vtable <- AppendVersion("spatstat.Knet", zKnet, vtable) vtable <- AppendVersion("spatstat.gui", zgui, vtable) @ The current versions of the \spst\ family of packages (used to produce this document) are: <>= print(vtable[,c(3,1,2)], row.names=FALSE) @ \section{Package structure} The original \pkg{spatstat} package grew to be very large. It has now been split into a family of packages, to satisfy the requirements of CRAN. This should not affect the user: existing code will continue to work in the same way. Typing \code{library(spatstat)} will load the familiar \pkg{spatstat} package which can be used as before. \subsection{Sub-packages} Currently there are seven sub-packages, called \pkg{spatstat.utils}, \pkg{spatstat.data}, \pkg{spatstat.sparse}, \pkg{spatstat.geom}, \pkg{spatstat.core}, \pkg{spatstat.linnet}, and \pkg{spatstat}. \begin{itemize} \item The \code{spatstat} package now contains only documentation and introductory material. It provides beginner's introductions, vignettes, interactive demonstration scripts, and a few help files summarising the package. \item The \pkg{spatstat.data} package now contains all the datasets for \pkg{spatstat}. \item The \pkg{spatstat.utils} package contains utility functions for \pkg{spatstat}. \item The \pkg{spatstat.sparse} package contains functions for manipulating sparse arrays and performing linear algebra. \item The \pkg{spatstat.geom} package contains definitions of spatial objects (such as point patterns, windows and pixel images) and code which performs geometrical operations. \item The \pkg{spatstat.core} package contains the main code for statistical analysis of spatial point patterns and other spatial data. \item The \pkg{spatstat.linnet} package defines spatial data on a linear network, and performs geometrical operations and statistical analysis on such data. \end{itemize} \noindent\textbf{Installing:} If you install \pkg{spatstat}, then the system will install all the other sub-packages listed above. \noindent\textbf{Running:} If you type \code{library(spatstat)} in an \textsf{R} session, the system will automatically load \pkg{spatstat.data}, \pkg{spatstat.geom}, \pkg{spatstat.core} and \pkg{spatstat.linnet}. It will also silently \textbf{``import''} \pkg{spatstat.utils} and \pkg{spatstat.sparse}. To access the functions in \pkg{spatstat.utils} directly, you would need to type \code{library(spatstat.utils)}. Similarly for \pkg{spatstat.sparse}. \subsection{Extension packages} There are also extension packages which provide additional capabilities and must be loaded explicitly when you need them. Currently there are three extension packages, with a fourth in development: \begin{itemize} \item \pkg{spatstat.local} for local model-fitting, \item \pkg{spatstat.Knet} provides additional code for analysing point patterns on a network. \item \pkg{spatstat.gui} containing interactive graphics functions, \item \pkg{spatstat.sphere} for analysing point patterns on a sphere (under development!) \end{itemize} %\pagebreak \section{Precis of all changes} Here is the text from the `overview' sections of the News and Release Notes for each update. \begin{itemize} \item the original \spst\ package has now been split into 7 sub-packages (\pkg{spatstat.utils}, \pkg{spatstat.data}, \pkg{spatstat.sparse}, \pkg{spatstat.geom}, \pkg{spatstat.core}, \pkg{spatstat.linnet} and \pkg{spatstat}). \item The interactive graphics functions \texttt{iplot} and \texttt{istat} have been removed from \spst\ into a new extension package \pkg{spatstat.gui}. \item The packages \pkg{tcltk} and \pkg{rpanel} are no longer Suggested by \spst. \item \spst\ now Imports the package \pkg{spatstat.sparse}. \item \spst\ now Imports the package \pkg{spatstat.utils}. \item \spst\ now requires the package \pkg{spatstat.data} which contains the datasets. \item \spst\ now suggests the package \pkg{fftwtools}. \item Conditional simulation in \texttt{kppm}. \item More diagnostics for spatial logistic regression models. \item Increased numerical stability in \texttt{kppm}. \item Simulation of the product shot noise Cox process. \item Information criteria for model selection in \texttt{kppm}. \item Estimation of the spatial covariance function of a pixel image \item Modified handling of covariates in \texttt{slrm} \item New options for \texttt{weighted.quantile} \item Buffer tessellation \item New function for jittering point patterns on a network. \item Extensions to \texttt{rhohat} \item \texttt{densityfun.ppp} handles query points outside original window \item Extension to \texttt{discretise}. \item Improvement to \texttt{densityEqualSplit}. \item summary method for spatial logistic regression models \item New options for \texttt{distmap.psp} \item Improved output in \texttt{summary.mppm} \item Increased speed for large datasets. \item Variance calculations handle larger datasets. \item Relative risk estimation on a network. \item Leave-one-out density estimation on a network. \item Add new vertices to a linear network. \item More support for multi-dimensional patterns. \item \texttt{predict.mppm} now works for multitype point process models. \item Improved handling of \texttt{newdata} in \texttt{predict.mppm} \item New datasets \texttt{concrete} and \texttt{btb}. \item Changed default value of \texttt{stringsAsFactors}. \item Function \texttt{lengths.psp} has been renamed \verb!lengths_psp!. \item Tessellations on a linear network can now have marks. \item More functions for manipulating tessellations on a linear network. \item New functions for simulating point processes on a linear network. \item Nearest Neighbour Index function can now return mark values. \item Index of repulsion strength for determinantal point process models. \item Nearest neighbours between two point patterns in any number of dimensions. \item More options for handling bad simulation outcomes in \texttt{envelope}. \item \texttt{mppm} accepts case weights. \item Bandwidth selectors warn about extreme values of bandwidth. \item Fast kernel estimation on a linear network using 2D kernels. \item Extension of Scott's rule for bandwidth selection. \item Cross-validated bandwidth selection on a linear network. \item Random thinning and random labelling of spatial patterns extended to different types of pattern. \item Confidence intervals for multitype $K$ function. \item Envelopes for balanced two-stage test \item Extensions to adaptive intensity estimators \item `Dartboard' tessellation using polar coordinates. \item Standard error calculation for inverse-distance weighting. \item Kernel estimate of intensity as a \texttt{function(x,y)}. \item Extract discrete and continuous components of a measure. \item Improvements and extensions to leverage and influence code. \item Plot a line segment pattern using line widths. \item Find connected components of each tile in a tessellation. \item Geometrical operations on \texttt{distfun} objects. \item Join vertices in a linear network. \item Distance map and contact distribution for rectangular structuring element. \item Lurking variable plot for models fitted to several point patterns. \item New dataset \code{cetaceans}. \item Gamma correction for colour maps and image plots. \item Class \code{units} has been renamed \code{unitname} to avoid package collision. \item More support for tessellations. \item Fixed longstanding bug in leverage and influence diagnostics. \item Improvements and bug fixes for leverage and influence diagnostics. \item Tighter bounding box for \code{psp}, \code{lpp}, \code{linnet} objects. \item Improved layout in \code{plot.solist} \item Tools to increase colour saturation. \item Connected components of a 3D point pattern. \item Accelerated computations on linear networks. \item Accelerated simulation of determinantal point processes. \item Improved printing of 3D point patterns. \item Minor corrections to handling of unitnames. \item Improvements to \texttt{ppm} and \texttt{update.ppm}. \item Correction to \texttt{lohboot} \item Numerous bug fixes for linear networks code. \item Now handles disconnected linear networks. \item Effect function is now available for all types of fitted model. \item Geometric-mean smoothing. \item A model can be fitted or re-fitted to a sub-region of data. \item New fast algorithm for kernel smoothing on a linear network. \item Leverage and influence diagnostics extended to Poisson/Gibbs models fitted by logistic composite likelihood. \item Two-stage Monte Carlo test. \item Dirichlet/Voronoi tessellation on a linear network. \item Thinning of point patterns on a linear network. \item More support for functions and tessellations on a linear network. \item Bandwidth selection for pair correlation function. \item Pooling operations improved. \item Operations on signed measures. \item Operations on lists of pixel images. \item Improved pixellation of point patterns. \item Stieltjes integral extended. \item Subset operators extended. \item Greatly accelerated \texttt{rmh} when using \texttt{nsave} \item Sufficient Dimension Reduction for point processes. \item Alternating Gibbs Sampler for point process simulation. \item New class of spatially sampled functions. \item ROC and AUC extended to other types of point patterns and models. \item More support for linear networks. \item More support for infinite straight lines. \item \spst\ now depends on the packages \pkg{nlme} and \pkg{rpart}. \item Important bug fix in \code{linearK}, \code{linearpcf} \item Changed internal format of \code{linnet} and \code{lpp} objects. \item Faster computation in linear networks. \item Bias correction techniques. \item Bounding circle of a spatial object. \item Option to plot marked points as arrows. \item Kernel smoothing accelerated. \item Workaround for bug in some graphics drivers affecting image orientation. \item Non-Gaussian smoothing kernels. \item Improvements to inhomogeneous multitype $K$ and $L$ functions. \item Variance approximation for pair correlation function. \item Leverage and influence for multitype point process models. \item Functions for extracting components of vector-valued objects. \item Recursive-partition point process models. \item Minkowski sum, morphological dilation and erosion with any shape. \item Minkowski sum also applicable to point patterns and line segment patterns. \item Important bug fix in Smooth.ppp \item Important bug fix in spatial CDF tests. \item More bug fixes for replicated patterns. \item Simulate a model fitted to replicated point patterns. \item Inhomogeneous multitype $F$ and $G$ functions. \item Summary functions recognise \texttt{correction="all"} \item Leverage and influence code handles bigger datasets. \item More support for pixel images. \item Improved progress reports. \item New dataset \texttt{redwood3} \item Fixed namespace problems arising when spatstat is not loaded. \item Important bug fix in leverage/influence diagnostics for Gibbs models. \item Surgery with linear networks. \item Tessellations on a linear network. \item Laslett's Transform. \item Colour maps for point patterns with continuous marks are easier to define. \item Pair correlation function estimates can be pooled. \item Stipulate a particular version of a package. \item More support for replicated point patterns. \item More support for tessellations. \item More support for multidimensional point patterns and point processes. \item More options for one-sided envelopes. \item More support for model comparison. \item Convexifying operation. \item Subdivide a linear network. \item Penttinen process can be simulated (by Metropolis-Hastings or CFTP). \item Calculate the predicted variance of number of points. \item Accelerated algorithms for linear networks. \item Quadrat counting accelerated, in some cases. \item Simulation algorithms have been accelerated; simulation outcomes are \emph{not} identical to those obtained from previous versions of \spst. \item Determinantal point process models. \item Random-effects and mixed-effects models for replicated patterns. \item Dao-Genton test, and corresponding simulation envelopes. \item Simulated annealing and simulated tempering. \item spatstat colour tools now handle transparent colours. \item Improvements to \verb![! and \texttt{subset} methods \item Extensions to kernel smoothing on a linear network. \item Support for one-dimensional smoothing kernels. \item Mark correlation function may include weights. \item Cross-correlation version of the mark correlation function. \item Penttinen pairwise interaction model. \item Improvements to simulation of Neyman-Scott processes. \item Improvements to fitting of Neyman-Scott models. \item Extended functionality for pixel images. \item Fitted intensity on linear network \item Triangulation of windows. \item Corrected an edge correction. \end{itemize} \section{New datasets} The following new datasets have been added. These are now provided in the sub-package \pkg{spatstat.data}. \begin{itemize} \item \texttt{austates}: The states and large mainland territories of Australia represented as polygonal regions forming a tessellation. \item \texttt{redwood3}: a more accurate version of the \texttt{redwood} data. \item \texttt{cetaceans}: point patterns of whale and dolphin sightings. \item \texttt{concrete}: air bubbles in concrete. \item \texttt{btb}: bovine tuberculosis occurrences. \end{itemize} \section{New classes} The following new classes of objects may be of use. \begin{itemize} \item \texttt{metric}: Class of distance metrics. An object of class \texttt{metric} represents a distance metric between points in two-dimensional space. See \texttt{help(metric.object)}. \item \texttt{ssf}: Class of spatially sampled functions. An object of class \texttt{"ssf"} represents a spatial function which has been evaluated or sampled at an irregular set of points. See \texttt{help(ssf)}. \end{itemize} \section{New Functions} Following is a list of all the functions that have been added, starting with the most recent additions. \begin{itemize} \item \texttt{lurking.slrm}: Lurking variable plot for spatial logistic regression models. \item \texttt{eem.slrm}: Exponential energy marks for spatial logistic regression models. \item \texttt{eem.ppm}: Exponential energy marks for Gibbs and Poisson point process models (this function was previously called \texttt{eem}). \item \texttt{transformquantiles}: Transform the quantiles of a vector, matrix, array or pixel image. \item \texttt{convexmetric}: Distance metric based on a convex set. \texttt{invoke.metric}: Low level function to perform a desired operation using a given metric. \item \texttt{mean.ecdf, mean.ewcdf} Calculate the mean of an empirical cumulative distribution function. \item \texttt{rjitter.ppp} This function was previously called \texttt{rjitter}. It is now a method for the new generic function \texttt{rjitter}. \item \texttt{bufftess}: Distance buffer tessellation \item \texttt{ic}: Information criteria for model selection in ppm and kppm. Kindly contributed by Achmad Choiruddin, Jean-Francois Coeurjolly and Rasmus Waagepetersen. \item \texttt{rPSNCP}: Generate simulated realisations of the product shot noise Cox process. Contributed by Abdollah Jalilian, Yongtao Guan and Rasmus Waagepetersen. \item \texttt{spatcov}: Estimate the spatial covariance function of a pixel image. \item \texttt{summary.slrm}, \texttt{print.summary.slrm} Summary method for spatial logistic regression models \item \texttt{coef.summary.slrm}: Print the fitted coefficients, confidence interval and p-values for a spatial logistic regression model. \item \texttt{pairMean}: Compute the mean of a specified function of interpoint distance between random points in a window. \item \texttt{rjitterlpp}: Apply random displacements to the points on a linear network. \item \texttt{intersect.boxx}: Compute intersection of boxes in multi-dimensional space \item \texttt{scale.boxx}, \texttt{scale.ppx}: Methods for \texttt{scale} for boxes and patterns in multi-dimensional space \item \texttt{shift.boxx}, \texttt{shift.ppx}: Methods for \texttt{shift} for boxes and patterns in multi-dimensional space \item \texttt{is.boxx}: Determine whether an object is a multidimensional box \item \texttt{relrisk.lpp}: nonparametric estimation of relative risk on a network. \item \texttt{bw.relrisklpp}: Bandwidth selection for relative risk estimation on a network. \item \texttt{bw.lppl}: Bandwidth selection for kernel density estimation of point patterns on a linear network, using likelihood cross-validation. \item \texttt{densityfun.lpp}: a method for \texttt{densityfun} for point patterns on a linear network. \item \texttt{addVertices}: Add new vertices to a network, at locations outside the existing network. \item \verb!lengths_psp!: this is the new name of the function \texttt{lengths.psp}, which had to be changed because of a conflict with the generic \texttt{lengths}. \item \texttt{densityEqualSplit}: The equal-split algorithm for kernel density estimation on a network is now visible as a separate function. \item \texttt{densityHeat}: The heat-equation algorithm for kernel density estimation on a network is now visible as a separate function. It has also been extended to computing leave-one-out density estimates at the data points. \item \texttt{hotrod}: Compute the heat kernel $\kappa(u,v)$ on a one-dimensional line segment. \item \texttt{heatkernelapprox}: Calculate an approximation to the value of the heat kernel on a network evaluated at the source point, $\kappa(u,u)$. \item \texttt{is.linim}: test whether an object is a pixel image on a linear network (class \verb!"linim"!). \item \texttt{rcelllpp}: Simulate the cell point process on a linear network. \item \texttt{rSwitzerlpp}: Simulate the Switzer-type point process on a linear network. \item \texttt{intersect.lintess}: Form the intersection of two tessellations on a linear network. \item \texttt{chop.linnet}: Divide a linear network into tiles using infinite lines. \item \texttt{repairNetwork}: Detect and repair inconsistencies in internal data in a \texttt{linnet} or \texttt{lpp} object. \item \verb!marks<-.lintess!, \texttt{unmark.lintess}: Assign marks to the tiles of a tessellation on a linear network. \item \texttt{marks.lintess}: Extract the marks of the tiles of a tessellation on a linear network. \item \texttt{tilenames.lintess}: Extract the names of the tiles in a tessellation on a linear network \item \verb!tilenames<-.lintess!: Change the names of the tiles in a tessellation on a linear network \item \texttt{nobjects.lintess}: Count the number of tiles in a tessellation on a linear network \item \texttt{as.data.frame.lintess}: Convert a tessellation on a linear network into a data frame. \item \texttt{repul}: Repulsiveness index for a determinantal point process model. \item \texttt{reach.kppm}: Reach (interaction distance) for a Cox or cluster point process model. \item \texttt{summary.dppm}, \texttt{print.summary.dppm}: Summary method for determinantal point process models. \item \texttt{nncross.ppx}: Nearest neighbours between two point patterns in any number of dimensions. \item \texttt{rthinclumps}: Divide a spatial region into clumps and randomly delete some of them. \item \texttt{densityQuick.lpp}: Fast kernel estimator of point process intensity on a network using 2D smoothing kernel. \item \texttt{data.lppm}: Extract the original point pattern dataset (on a linear network) to which the model was fitted. \item \texttt{bw.scott.iso}: Isotropic version of Scott's rule (for point patterns in any dimension). \item \texttt{bits.envelope}: Global simulation envelope corresponding to \texttt{bits.test}, the balanced independent two-stage Monte Carlo test. \item \texttt{extrapolate.psp}: Extrapolate line segments to obtain infinite lines. \item \texttt{uniquemap}: Map duplicate points to unique representatives. Generic with methods for \texttt{ppp}, \texttt{lpp}, \texttt{ppx} \item \texttt{uniquemap.data.frame}, \texttt{uniquemap.matrix}: Map duplicate rows to unique representatives \item \texttt{localKcross}, \texttt{localLcross}, \texttt{localKdot}, \texttt{localLdot}, \texttt{localKcross.inhom}, \texttt{localLcross.inhom}: Multitype local $K$ functions. \item \texttt{polartess}: tessellation using polar coordinates. \item \texttt{densityVoronoi}: adaptive estimate of point process intensity using tessellation methods. \item \texttt{densityAdaptiveKernel}: adaptive estimate of point process intensity using variable kernel methods. \item \texttt{bw.abram}: compute adaptive smoothing bandwidths using Abramson's rule. \item \texttt{coords.quad}: method for \texttt{coords}, to extract the coordinates of the points in a quadrature scheme. \item \texttt{lineartileindex}: low-level function to classify points on a linear network according to which tile of a tessellation they fall inside. \item \texttt{markmarkscatter}: Mark--mark scatterplot. \item \texttt{bw.CvL}: Cronie-van Lieshout bandwidth selection for density estimation. \item \texttt{subset.psp}: subset method for line segment patterns. \item \texttt{densityfun}, \texttt{densityfun.ppp}: Compute a kernel estimate of intensity of a point pattern and return it as a function of spatial location. \item \texttt{as.im.densityfun}: Convert \texttt{function(x,y)} to a pixel image. \item \texttt{measureDiscrete}, \texttt{measureContinuous}: Extract the discrete and continuous components of a measure. \item \texttt{connected.tess}: Find connected components of each tile in a tessellation and make a new tessellation composed of these pieces. \item \texttt{dffit.ppm}: Effect change diagnostic \texttt{DFFIT} for spatial point process models. \item \texttt{shift.distfun}, \texttt{rotate.distfun}, \texttt{reflect.distfun}, \texttt{flipxy.distfun}, \texttt{affine.distfun}, \texttt{scalardilate.distfun}: Methods for geometrical operations on \texttt{distfun} objects. \item \texttt{rescale.distfun}: Change the unit of length in a \texttt{distfun} object. \item \texttt{plot.indicfun}: Plot method for indicator functions created by \texttt{as.function.owin}. \item \texttt{Smooth.leverage.ppm}, \texttt{Smooth.influence.ppm}: Smooth a leverage function or an influence measure. \item \texttt{integral.leverage.ppm}, \texttt{integral.influence.ppm}: Compute the integral of a leverage function or an influence measure. \item \texttt{mean.leverage.ppm}: Compute the mean value of a leverage function. \item \texttt{rectdistmap}: Distance map using rectangular metric. \item \texttt{rectcontact}: Contact distribution function using rectangular structuring element. \item \texttt{joinVertices}: Join specified vertices in a linear network. \item \code{summary.ssf}: Summary method for a spatially sampled function (class \code{ssf}). \item \code{unstack.tess}: Given a tessellation with multiple columns of marks, take the columns one at a time, and return a list of tessellations, each carrying only one of the original columns of marks. \item \code{contour.leverage.ppm}: Method for \code{contour} for leverage functions of class \code{leverage.ppm} \item \code{lurking}: New generic function for lurking variable plots. \item \code{lurking.ppp}, \code{lurking.ppm}: These are equivalent to the original function \code{lurking}. They are now methods for the new generic \code{lurking}. \item \code{lurking.mppm}: New method for class \code{mppm}. Lurking variable plot for models fitted to several point patterns. \item \code{print.lurk}: Prints information about the object returned by the function \code{lurking} representing a lurking variable plot. \item \code{model.matrix.mppm}: Method for \code{model.matrix} for models of class \code{mppm}. \item \code{test.crossing.psp}, \code{test.selfcrossing.psp}: Previously undocumented functions for testing whether segments cross. \item \code{to.saturated}: Convert a colour value to the corresponding fully-saturated colour. \item \code{intensity.psp}: Compute the average total length of segments per unit area. \item \code{boundingbox.psp}: Bounding box for line segment patterns. This produces a tighter bounding box than the previous default behaviour. \item \code{boundingbox.lpp}: Bounding box for point patterns on a linear network. This produces a tighter bounding box than the previous default behaviour. \item \code{boundingbox.linnet}: Bounding box for a linear network. This produces a tighter bounding box than the previous default behaviour. \item \verb!"Frame<-.default"!: New default method for assigning bounding frame to a spatial object. \item \code{connected.pp3}: Connected components of a 3D point pattern. \item \code{colouroutputs}, \verb!"colouroutputs<-"!: Extract or assign colour values in a colour map. (Documented a previously-existing function) \item \texttt{fitin.profilepl}: Extract the fitted interaction from a model fitted by profile likelihood. \item \verb![<-.linim!: Subset assignment method for pixel images on a linear network. \item \texttt{nnfromvertex}: Given a point pattern on a linear network, find the nearest data point from each vertex of the network. \item \texttt{tile.lengths}: Calculate the length of each tile in a tessellation on a network. \item \texttt{text.ppp}, \texttt{text.lpp}, \texttt{text.psp}: Methods for \texttt{text} for spatial patterns. \item \texttt{as.data.frame.envelope}: Extract function data from an envelope object, including the functions for the simulated data ('simfuns') if they were saved. \item \texttt{is.connected}, \texttt{is.connected.default}, \texttt{is.connected.linnet}: Determines whether a spatial object consists of one topologically connected piece, or several pieces. \item \texttt{is.connected.ppp}: Determines whether a point pattern is connected after all pairs of points closer than distance R are joined. \item \texttt{hist.funxy}: Histogram of values of a spatial function. \item \texttt{model.matrix.ippm}: Method for \texttt{model.matrix} which allows computation of regular and irregular score components. \item \texttt{harmonise.msr}: Convert several measures (objects of class \texttt{msr}) to a common quadrature scheme. \item \texttt{bits.test}: Balanced Independent Two-Stage Monte Carlo test, an improvement on the Dao-Genton test. \item \texttt{lineardirichlet}: Computes the Dirichlet-Voronoi tessellation associated with a point pattern on a linear network. \item \texttt{domain.lintess}, \texttt{domain.linfun}: Extract the linear network from a \texttt{lintess} or \texttt{linfun} object. \item \texttt{summary.lintess}: Summary of a tessellation on a linear network. \item \texttt{clicklpp}: Interactively add points on a linear network. \item \texttt{envelopeArray}: Generate an array of envelopes using a function that returns \texttt{fasp} objects. \item \texttt{bw.pcf}: Bandwidth selection for pair correlation function. \item \texttt{grow.box3}: Expand a three-dimensional box. \item \texttt{hexagon}, \texttt{regularpolygon}: Create regular polygons. \item \texttt{Ops.msr}: Arithmetic operations for measures. \item \texttt{Math.imlist}, \texttt{Ops.imlist}, \texttt{Summary.imlist}, \texttt{Complex.imlist}: Arithmetic operations for lists of pixel images. \item \texttt{measurePositive}, \texttt{measureNegative}, \texttt{measureVariation}, \texttt{totalVariation}: Positive and negative parts of a measure, and variation of a measure. \item \texttt{as.function.owin}: Convert a spatial window to a \texttt{function(x,y)}, the indicator function. \item \texttt{as.function.ssf}: Convert an object of class \texttt{ssf} to a \texttt{function(x,y)} \item \texttt{as.function.leverage.ppm} Convert an object of class \texttt{leverage.ppm} to a \texttt{function(x,y)} \item \texttt{sdr}, \texttt{dimhat}: Sufficient Dimension Reduction for point processes. \item \texttt{simulate.rhohat}: Simulate a Poisson point process with the intensity estimated by \texttt{rhohat}. \item \texttt{rlpp}: Random points on a linear network with a specified probability density. \item \texttt{cut.lpp}: Method for \texttt{cut} for point patterns on a linear network. \item \texttt{has.close}: Faster way to check whether a point has a close neighbour. \item \texttt{psib}: Sibling probability (index of clustering strength in a cluster process). \item \texttt{rags}, \texttt{ragsAreaInter}, \texttt{ragsMultiHard}: Alternating Gibbs Sampler for point processes. \item \texttt{bugfixes}: List all bug fixes in recent versions of a package. \item \texttt{ssf}: Create a spatially sampled function \item \texttt{print.ssf}, \texttt{plot.ssf}, \texttt{contour.ssf}, \texttt{image.ssf}: Display a spatially sampled function \item \texttt{as.im.ssf}, \texttt{as.ppp.ssf}, \texttt{marks.ssf}, \verb!marks<-.ssf!, \texttt{unmark.ssf}, \verb![.ssf!, \texttt{with.ssf}: Manipulate data in a spatially sampled function \item \texttt{Smooth.ssf}: Smooth a spatially sampled function \item \texttt{integral.ssf}: Approximate integral of spatially sampled function \item \texttt{roc.kppm}, \texttt{roc.lppm}, \texttt{roc.lpp}: Methods for \texttt{roc} for fitted models of class \texttt{"kppm"} and \texttt{"lppm"} and point patterns of class \texttt{"lpp"} \item \texttt{auc.kppm}, \texttt{auc.lppm}, \texttt{auc.lpp}: Methods for \texttt{auc} for fitted models of class \texttt{"kppm"} and \texttt{"lppm"} and point patterns of class \texttt{"lpp"} \item \texttt{timeTaken}: Extract the timing data from a \texttt{"timed"} object or objects. \item \texttt{rotate.infline}, \texttt{shift.infline}, \texttt{reflect.infline}, \texttt{flipxy.infline}: Geometrical transformations for infinite straight lines. \item \texttt{whichhalfplane}: Determine which side of an infinite line a point lies on. \item \texttt{matrixpower}, \texttt{matrixsqrt}, \texttt{matrixinvsqrt}: Raise a matrix to any power. \item \texttt{points.lpp}: Method for \texttt{points} for point patterns on a linear network. \item \texttt{pairs.linim}: Pairs plot for images on a linear network. \item \texttt{closetriples}: Find close triples of points. \item \texttt{anyNA.im}: Method for \texttt{anyNA} for pixel images. \item \texttt{bc}: Bias correction (Newton-Raphson) for fitted model parameters. \item \texttt{rex}: Richardson extrapolation for numerical integrals and statistical model parameter estimates. \item \texttt{boundingcircle}, \texttt{boundingcentre}: Find the smallest circle enclosing a window or point pattern. \item \verb![.linim! : Subset operator for pixel images on a linear network. \item \texttt{mean.linim}, \texttt{median.linim}, \texttt{quantile.linim}: The mean, median, or quantiles of pixel values in a pixel image on a linear network. \item \texttt{weighted.median}, \texttt{weighted.quantile}: Median or quantile of numerical data with associated weights. \item \verb!"[.linim"!: Subset operator for pixel images on a linear network. \item \texttt{mean.linim}, \texttt{median.linim}, \texttt{quantile.linim}: The mean, median, or quantiles of pixel values in a pixel image on a linear network. \item \texttt{boundingcircle}, \texttt{boundingcentre}: Smallest circle enclosing a spatial object. \item \texttt{split.msr}: Decompose a measure into parts. \item \texttt{unstack.msr}: Decompose a vector-valued measure into its component measures. \item \texttt{unstack.ppp}, \texttt{unstack.psp}, \texttt{unstack.lpp}: Given a spatial pattern with several columns of marks, separate the columns and return a list of spatial patterns, each having only one column of marks. \item \texttt{kernel.squint}: Integral of squared kernel, for the kernels used in density estimation. \item \texttt{as.im.data.frame}: Build a pixel image from a data frame of coordinates and pixel values. \item \texttt{covering}: Cover a window using discs of a given radius. \item \texttt{dilationAny}, \texttt{erosionAny}, \verb!%(-)%! : Morphological dilation and erosion by any shape. \item \texttt{FmultiInhom}, \texttt{GmultiInhom} Inhomogeneous multitype/marked versions of the summary functions \texttt{Fest}, \texttt{Gest}. \item \texttt{kernel.moment} Moment or incomplete moment of smoothing kernel. \item \texttt{MinkowskiSum}, \verb!%(+)%!: Minkowski sum of two windows: \verb!A %(+)% B!, or \texttt{MinkowskiSum(A,B)} \item \texttt{nobjects}: New generic function for counting the number of 'things' in a dataset. There are methods for \texttt{ppp}, \texttt{ppx}, \texttt{psp}, \texttt{tess}. \item \texttt{parameters.interact}, \texttt{parameters.fii}: Extract parameters from interpoint interactions. (These existing functions are now documented.) \item \texttt{ppmInfluence}: Calculate \texttt{leverage.ppm}, \texttt{influence.ppm} and \texttt{dfbetas.ppm} efficiently. \item \texttt{rppm}, \texttt{plot.rppm}, \texttt{predict.rppm}, \texttt{prune.rppm}: Recursive-partition point process models. \item \texttt{simulate.mppm} Simulate a point process model fitted to replicated point patterns. \item \texttt{update.interact}: Update the parameters of an interpoint interaction. [This existing function is now documented.] \item \texttt{where.max}, \texttt{where.min} Find the spatial location(s) where a pixel image achieves its maximum or minimum value. \item \texttt{compileK}, \texttt{compilepcf}: make a $K$ function or pair correlation function given the pairwise distances and their weights. [These existing internal functions are now documented.] \item \texttt{laslett}: Laslett's Transform. \item \texttt{lintess}: Tessellation on a linear network. \item \texttt{divide.linnet}: Divide a linear network into pieces demarcated by a point pattern. \item \texttt{insertVertices}: Insert new vertices in a linear network. \item \texttt{thinNetwork}: Remove vertices and/or segments from a linear network etc. \item \texttt{connected.linnet}: Find connected components of a linear network. \item \texttt{nvertices}, \texttt{nvertices.linnet}, \texttt{nvertices.owin}: Count the number of vertices in a linear network or vertices of the boundary of a window. \item \texttt{as.data.frame.linim}, \texttt{as.data.frame.linfun}: Extract a data frame of spatial locations and function values from an object of class \texttt{linim} or \texttt{linfun}. \item \texttt{as.linfun}, \texttt{as.linfun.linim}, \texttt{as.linfun.lintess}: Convert other kinds of data to a \texttt{linfun} object. \item \texttt{requireversion}: Require a particular version of a package (for use in stand-alone R scripts). \item \texttt{as.function.tess}: Convert a tessellation to a \texttt{function(x,y)}. The function value indicates which tile of the tessellation contains the point $(x,y)$. \item \texttt{tileindex}: Determine which tile of a tessellation contains a given point $(x,y)$. \item \texttt{persp.leverage.ppm}: Method for persp plots for objects of class \texttt{leverage.ppm} \item \texttt{AIC.mppm}, \texttt{extractAIC.mppm}: AIC for point process models fitted to replicated point patterns. \item \texttt{nobs.mppm}, \texttt{terms.mppm}, \texttt{getCall.mppm}: Methods for point process models fitted to replicated point patterns. \item \texttt{rPenttinen}: Simulate the Penttinen process using perfect simulation. \item \texttt{varcount}: Given a point process model, compute the predicted variance of the number of points falling in a window. \item \texttt{inside.boxx}: Test whether multidimensional points lie inside a specified multidimensional box. \item \texttt{lixellate}: Divide each segment of a linear network into smaller segments. \item \texttt{nsegments.linnet}, \texttt{nsegments.lpp}: Count the number of line segments in a linear network. \item \texttt{grow.boxx}: Expand a multidimensional box. \item \texttt{deviance.ppm}, \texttt{deviance.lppm}: Deviance for a fitted point process model. \item \texttt{pseudoR2}: Pseudo-R-squared for a fitted point process model. \item \texttt{tiles.empty} Checks whether each tile of a tessellation is empty or nonempty. \item \texttt{summary.linim}: Summary for a pixel image on a linear network. \item Determinantal Point Process models: \begin{itemize} \item \texttt{dppm}: Fit a determinantal point process model. \item \texttt{fitted.dppm}, \texttt{predict.dppm}, \texttt{intensity.dppm}: prediction for a fitted determinantal point process model. \item \texttt{Kmodel.dppm}, \texttt{pcfmodel.dppm}: Second moments of a determinantal point process model. \item \texttt{rdpp}, \texttt{simulate.dppm}: Simulation of a determinantal point process model. \item \texttt{logLik.dppm}, \texttt{AIC.dppm}, \texttt{extractAIC.dppm}, \texttt{nobs.dppm}: Likelihood and AIC for a fitted determinantal point process model. \item \texttt{print.dppm}, \texttt{reach.dppm}, \texttt{valid.dppm}: Basic information about a \texttt{dpp} model. \item \texttt{coef.dppm}, \texttt{formula.dppm}, \texttt{print.dppm}, \texttt{terms.dppm}, \texttt{labels.dppm}, \texttt{model.frame.dppm}, \texttt{model.matrix.dppm}, \texttt{model.images.dppm}, \texttt{is.stationary.dppm}, \texttt{reach.dppm}, \texttt{unitname.dppm}, \verb!unitname<-.dppm!, \texttt{Window.dppm}: Various methods for \texttt{dppm} objects. \item \texttt{parameters.dppm}: Extract meaningful list of model parameters. \item \texttt{objsurf.dppm}: Objective function surface of a \texttt{dppm} object. \item \texttt{residuals.dppm}: Residual measure for a \texttt{dppm} object. \end{itemize} \item Determinantal Point Process model families: \begin{itemize} \item \texttt{dppBessel}, \texttt{dppCauchy}, \texttt{dppGauss}, \texttt{dppMatern}, \texttt{dppPowerExp}: Determinantal Point Process family functions. \item \texttt{detpointprocfamilyfun}: Create a family function. \item \texttt{update.detpointprocfamily}: Set parameter values in a determinantal point process model family. \item \texttt{simulate.dppm}: Simulation. \item \texttt{is.stationary.detpointprocfamily}, \texttt{intensity.detpointprocfamily}, \texttt{Kmodel.detpointprocfamily}, \texttt{pcfmodel.detpointprocfamily}: Moments. \item \texttt{dim.detpointprocfamily}, \texttt{dppapproxkernel}, \texttt{dppapproxpcf}, \texttt{dppeigen}, \texttt{dppkernel}, \texttt{dppparbounds}, \texttt{dppspecdenrange}, \texttt{dppspecden}: Helper functions. \end{itemize} \item \texttt{dg.envelope}: Simulation envelopes corresponding to Dao-Genton test. \item \texttt{dg.progress}: Progress plot (envelope representation) for the Dao-Genton test. \item \texttt{dg.sigtrace}: significance trace for the Dao-Genton test. \item \texttt{markcrosscorr}: Mark cross-correlation function for point patterns with several columns of marks. \item \texttt{rtemper}: Simulated annealing or simulated tempering. \item \texttt{rgb2hsva}: Convert RGB to HSV data, like \texttt{rgb2hsv}, but preserving transparency. \item \texttt{superimpose.ppplist}, \texttt{superimpose.splitppp}: New methods for 'superimpose' for lists of point patterns. \item \texttt{dkernel}, \texttt{pkernel}, \texttt{qkernel}, \texttt{rkernel}: Probability density, cumulative probability, quantiles and random generation from distributions used in basic one-dimensional kernel smoothing. \item \texttt{kernel.factor}: Auxiliary calculations for one-dimensional kernel smoothing. \item \texttt{spatdim}: Spatial dimension of any object in the \spst\ package. \item \texttt{as.boxx}: Convert data to a multi-dimensional box. \item \texttt{intensity.ppx}: Method for \texttt{intensity} for multi-dimensional space-time point patterns. \item \texttt{fourierbasis}: Evaluate Fourier basis functions in any number of dimensions. \item \texttt{valid}: New generic function, with methods \texttt{valid.ppm}, \texttt{valid.lppm}, \texttt{valid.dppm}. \item \texttt{emend}, \texttt{emend.ppm}, \texttt{emend.lppm}: New generic function with methods for \texttt{ppm} and \texttt{lppm}. \texttt{emend.ppm} is equivalent to \texttt{project.ppm}. \item \texttt{Penttinen}: New pairwise interaction model. \item \texttt{quantile.density}: Calculates quantiles from kernel density estimates. \item \texttt{CDF.density}: Calculates cumulative distribution function from kernel density estimates. \item \texttt{triangulate.owin}: decompose a spatial window into triangles. \item \texttt{fitted.lppm}: fitted intensity values for a point process on a linear network. \item \texttt{parameters}: Extract all parameters from a fitted model. \end{itemize} \section{Alphabetical list of changes} Here is a list of all changes made to existing functions, listed alphabetically. \begin{itemize} %%A \item \texttt{adaptive.density}: This function can now perform adaptive estimation by two methods: either tessellation-based methods or variable-bandwidth kernel estimation. The calculations are performed by either \texttt{densityVoronoi} or \texttt{densityAdaptiveKernel}. \item \texttt{affine.owin}: Allows transformation matrix to be singular, if the window is polygonal. \item \texttt{alltypes}: If \texttt{envelope=TRUE} and the envelope computation reaches the maximum permitted number of errors (\texttt{maxnerr}) in evaluating the summary function for the simulated patterns, then instead of triggering a fatal error, the envelope limits will be set to \texttt{NA}. \item \texttt{anova.mppm}: \begin{itemize} \item Now handles Gibbs models, and performs the adjusted composite likelihood ratio test. \item New argument \texttt{fine}. \item Issues a warning when applied to random-effects models (models fitted using the argument \texttt{random}). \end{itemize} \item \texttt{anyDuplicated.ppp}: Accelerated. \item \texttt{append.psp}: arguments may be \texttt{NULL}. \item \texttt{as.function.tess}: New argument \texttt{values} specifies the function values. \item \texttt{as.im.distfun}: New argument \texttt{approx} specifies the choice of algorithm. \item \texttt{as.im.function}: \begin{itemize} \item New argument \texttt{strict}. \item New argument \texttt{stringsAsFactors}. \item The formal default value of \texttt{stringsAsFactors} has been changed to \texttt{NULL} to conform to changes in R. (The actual default value is \texttt{TRUE} for \texttt{R < 4.1.0} and \texttt{FALSE} for \texttt{R >= 4.1.0}). \end{itemize} \item \texttt{as.im.leverage.ppm}: New argument \texttt{what}. \item \texttt{as.im.nnfun}: New argument \texttt{approx} chooses between a fast, approximate algorithm and a slow, exact algorithm. \item \texttt{as.im.smoothfun}: New argument \texttt{approx} chooses between a fast, approximate algorithm and a slow, exact algorithm. \item \texttt{as.layered}: Default method now handles a (vanilla) list of spatial objects. \item \texttt{as.linfun.lintess}: \begin{itemize} \item New argument \texttt{values} specifies the function value for each tile. \item The default \texttt{values} are the marks, if present. \item New argument \texttt{navalue}. \item Computation accelerated. \end{itemize} \item \texttt{as.linim.default}: New arguments \texttt{delta} and \texttt{nd} control spacing of sample points in internal data. \item \texttt{as.linnet.linnet}: New argument \texttt{maxsize}. \item \texttt{as.linnet.psp}: \begin{itemize} \item If the line segment pattern has marks, then the resulting linear network also carries these marks in the \verb!$lines! component. \item Computation accelerated. \item The resulting network has attribute \texttt{"camefrom"} indicating the provenance of each line segment in the network. \end{itemize} \item \texttt{as.lpp}: accepts more data formats: \begin{itemize} \item Now handles the case where coordinates \texttt{seg} and \texttt{tp} are given but \texttt{x} and \texttt{y} are missing. \item Now handles the case where \texttt{x} is a data frame with columns named \texttt{x,y,seg,tp} or \texttt{x,y} or \texttt{seg,tp}. \end{itemize} \item \texttt{as.owin.default}: \begin{itemize} \item Now refuses to convert a \code{box3} to a two-dimensional window. \item Now accepts a structure with entries named \code{xmin},\code{xmax}, \code{ymin}, \code{ymax} in any order. This handles objects of class \code{bbox} in the \pkg{sf} package. \item Now detects objects of class \code{SpatialPolygons} and issues a more helpful error message. \end{itemize} \item \texttt{as.owin.data.frame}: New argument \texttt{step} \item \texttt{as.polygonal}: \begin{itemize} \item Can now repair errors in polygon data, if \texttt{repair=TRUE}. \item Accelerated when \texttt{w} is a pixel mask. \end{itemize} \item \texttt{as.psp}: now permits a data frame of marks to have only one column, instead of coercing it to a vector. \item \texttt{as.solist}: The argument \texttt{x} can now be a spatial object; \texttt{as.solist(cells)} is the same as \texttt{solist(cells)}. %%B \item \texttt{bdist.pixels}: Accelerated for polygonal windows. New argument \texttt{method}. \item \texttt{bdist.points}: Accelerated for polygonal windows. \item \texttt{beachcolours}: \begin{itemize} \item Improved positioning of the yellow colour band. \item If \texttt{sealevel} lies outside \texttt{srange}, then \texttt{srange} will be extended to include it (without a warning). \end{itemize} \item \texttt{beachcolourmap}: Improved positioning of the yellow colour band. \item \texttt{bilinearform}: This function has been moved to the sub-package \texttt{spatstat.sparse}. \item \texttt{bind.fv}: New argument \texttt{clip}. \item \texttt{blur}: New argument \texttt{kernel}. \item \texttt{bw.abram}: \begin{itemize} \item New argument \texttt{smoother} determines how the pilot estimate is computed. \item Formal arguments rearranged. \end{itemize} \item \texttt{bw.diggle}, \texttt{bw.ppl}, \texttt{bw.relrisk}, \texttt{bw.smoothppp}: \begin{itemize} \item These functions now extract and store the name of the unit of length from the point pattern dataset. When the bandwidth selection criterion is plotted, the name of the unit of length is shown on the x-axis. \item A warning is issued if the optimal value of the cross-validation criterion occurs at an endpoint of the search interval. New argument \texttt{warn}. \end{itemize} \item \texttt{bw.ppl}: \begin{itemize} \item New arguments \texttt{weights} and \texttt{sigma}. \item New argument \texttt{shortcut} allows faster computation. \item Additional arguments \verb!...! are now passed to \texttt{density.ppp}. \end{itemize} \item \texttt{bw.scott}: \begin{itemize} \item the two bandwidth values in the result now have names \texttt{sigma.x} and \texttt{sigma.y}. \item Now handles point patterns of any dimension. \item New arguments \texttt{isotropic} and \texttt{d}. \end{itemize} \item \texttt{bw.stoyan}: The rule has been modified so that, if the pattern is empty, it is now treated as if it contained 1 point, so that a finite bandwidth value is returned. %%C \item \texttt{cbind.hyperframe}: \begin{itemize} \item The result now retains the \texttt{row.names} of the original arguments. \item \end{itemize} \item \texttt{cdf.test}: \begin{itemize} \item Calculations are more robust against numerical rounding effects. \item The methods for classes \texttt{ppp}, \texttt{ppm}, \texttt{lpp}, \texttt{lppm}, \texttt{slrm} have a new argument \texttt{interpolate}. \item Monte Carlo test runs much faster. \item More jittering is applied when \texttt{jitter=TRUE}. Warnings about tied values should not occur any more. \end{itemize} \item \texttt{cdf.test.mppm}: \begin{itemize} \item Now handles Gibbs models. \item Now recognises \texttt{covariate="x"} or \texttt{"y"}. \end{itemize} \item \texttt{clarkevans}: The argument \texttt{correction="all"} is now recognised: it selects all the available options. [This is also the default.] \item \texttt{clickpoly}: The polygon is now drawn progressively as the user clicks new vertices. \item \texttt{closepairs.ppp}: New argument \code{periodic}. \item \texttt{closepairs.ppp}, \texttt{closepairs.pp3}: \begin{itemize} \item New arguments \texttt{distinct} and \texttt{neat} allow more options. \item Argument \texttt{ordered} has been replaced by \texttt{twice} (but \texttt{ordered} is still accepted, with a warning). \item Performance improved (computation time and memory requirements reduced.) This should improve the performance of many functions in \texttt{spatstat}. \end{itemize} \item \texttt{closepairs.pp3}: Argument \texttt{what} can take the value \texttt{"ijd"} \item \texttt{clusterset}: Improved behaviour. \item \texttt{clusterfit}: \begin{itemize} \item New argument \texttt{algorithm} specifies the choice of optimisation algorithm. \item Changed precedence rule for handling the algorithm parameters in the minimum contrast algorithm. Individually-named arguments \texttt{q,p,rmax,rmin} now take precedence over entries with the same names in the list \texttt{ctrl}. \item New argument \texttt{verbose}. \end{itemize} \item \texttt{colourmap}: argument \texttt{col} have have length 1, representing a trivial colour map in which all data values are mapped to the same colour. \item \texttt{collapse.fv}: \begin{itemize} \item This is now treated as a method for the \texttt{nlme} generic \texttt{collapse}. Its syntax has been adjusted slightly. \item Recognises the abbreviations used by \texttt{fvnames()}. \end{itemize} \item \texttt{connected.im}: Now handles a logical-valued image properly. Arguments \texttt{...} now determine pixel resolution. \item \texttt{connected.owin}: Arguments \texttt{...} now determine pixel resolution. \item \texttt{contour.im}: New argument \texttt{col} specifies the colour of the contour lines. If \texttt{col} is a colour map, then the contours are drawn in different colours. \item \texttt{convolve.im}: the name of the unit of length is preserved. \item \texttt{crossdist.lpp}: \begin{itemize} \item Now handles much larger networks, using the sparse representation of the network. \item New argument \texttt{check}. \end{itemize} \item \texttt{crossing.psp}: New argument \texttt{details} gives more information about the intersections between the segments. \item \texttt{crosspairs.pp3}: Argument \texttt{what} can take the value \texttt{"ijd"} \item \texttt{cut.ppp}: Argument \texttt{z} can be \texttt{"x"} or \texttt{"y"} indicating one of the spatial coordinates. %%D \item \texttt{dclf.test, mad.test, dclf.progress, mad.progress,} \texttt{dclf.sigtrace, mad.sigtrace}, \texttt{dg.progress, dg.sigtrace}: \begin{itemize} \item New argument \texttt{clamp} determines the test statistic for one-sided tests. \item New argument \texttt{rmin} determines the left endpoint of the test interval. \item New argument \texttt{leaveout} specifies how to calculate discrepancy between observed and simulated function values. \item New argument \texttt{scale} allows summary function values to be rescaled before the comparison is performed. \item New argument \texttt{interpolate} supports interpolation of $p$-value. \item Function values which are infinite, \texttt{NaN} or \texttt{NA} are now ignored in the calculation (with a warning) instead of causing an error. Warning messages are more detailed. \end{itemize} \item \texttt{default.rmhcontrol, default.rmhexpand}: New argument \texttt{w}. \item \texttt{densityfun.ppp}: The resulting function can now handle query points which lie outside the window of the original data, and has argument \texttt{drop=TRUE} which specifies how to handle them. \item \texttt{densityEqualSplit}: New arguments \texttt{at} and \texttt{leaveoneout} for consistency with other functions. \item \texttt{densityHeat}: \begin{itemize} \item default behaviour has changed slightly. \item new argument \texttt{finespacing}. \end{itemize} \item \texttt{density.lpp}: \begin{itemize} \item New fast algorithm (up to 1000 times faster) for the default case where \texttt{kernel="gaussian"} and \texttt{continuous=TRUE}. Generously contributed by Greg McSwiggan. \item Fast algorithm has been further accelerated. \item Further accelerated when the point pattern contains duplicated points. \item New argument \texttt{kernel} specifies the smoothing kernel. Any of the standard one-dimensional smoothing kernels can be used. \item Now supports both the `equal-split continuous' and `equal-split discontinuous' smoothers. New argument \texttt{continuous} determines the choice of smoother. \item New arguments \texttt{weights} and \texttt{old}. \item New argument \texttt{distance} offers a choice of different kernel methods. \item Infinite bandwidth (\texttt{sigma=Inf}) is now permitted, and results in a density estimate that is constant over all locations. \end{itemize} \item \texttt{density.ppp}: \begin{itemize} \item A non-Gaussian kernel can now be specified using the argument \texttt{kernel}. \item Argument \texttt{weights} can now be a pixel image. \item Infinite bandwidth \texttt{sigma=Inf} is supported. \item Accelerated by about 30\% when \texttt{at="pixels"}. \item Accelerated by about 15\% in the case where \texttt{at="points"} and \texttt{kernel="gaussian"}. \item Accelerated in the cases where weights are given or \texttt{diggle=TRUE}. \item New argument \texttt{verbose}. \end{itemize} \item \texttt{density.psp}: \begin{itemize} \item New argument \texttt{method}. \item Accelerated by 1 to 2 orders of magnitude. \end{itemize} \item \texttt{density.splitppp}: New argument \texttt{weights}. \item \texttt{dfbetas.ppm}: \begin{itemize} \item For Gibbs models, memory usage has been dramatically reduced, so the code can handle larger datasets and finer quadrature schemes. \item Increased the default resolution of the pixel images. Spatial resolution can now be controlled by the arguments \code{dimyx}, \code{eps}. \end{itemize} \item \texttt{diagnose.ppm}: \begin{itemize} \item Infinite values of \texttt{rbord} are now ignored and treated as zero. This ensures that \texttt{diagnose.ppm} has a sensible default when the fitted model has infinite reach. \item Accelerated, when \texttt{type="inverse"}, for models without a hard core. \end{itemize} \item \texttt{diagnose.ppm, plot.diagppm}: \begin{itemize} \item New arguments \texttt{col.neg, col.smooth} control the colour maps. \item Accelerated, when \texttt{type="inverse"}, for models without a hard core. \end{itemize} \item \texttt{dilation.ppp}: Improved geometrical accuracy. Now accepts arguments to control resolution of polygonal approximation. \item \texttt{dirichletEdges}: New argument \texttt{clip}. \item \texttt{discretise}: New argument \texttt{move.points} determines whether the point coordinates are also discretised. \item \texttt{discs}: \begin{itemize} \item Now accepts a single numeric value for \texttt{radii}. \item New argument \texttt{npoly}. \item Accelerated in some cases. \end{itemize} \item \texttt{distcdf}: \begin{itemize} \item Arguments which are \texttt{NULL} will be treated as missing. \item New argument \texttt{savedenom}. \end{itemize} \item \texttt{distfun}: When the user calls a distance function that was created by \texttt{distfun}, the user may now give a \texttt{ppp} or \texttt{lpp} object for the argument \texttt{x}, instead of giving two coordinate vectors \texttt{x} and \texttt{y}. \item \texttt{distfun.lpp}: \begin{itemize} \item New argument \texttt{k} allows computation of $k$-th nearest point. \item Computation accelerated. \end{itemize} \item \texttt{distmap.psp}: New arguments \texttt{extras} and \texttt{clip}. \item \texttt{dppm}: Changed precedence rule for handling the algorithm parameters in the minimum contrast algorithm. Individually-named arguments \texttt{q,p,rmax,rmin} now take precedence over entries with the same names in the list \texttt{ctrl}. \item \texttt{duplicated.ppp}: accelerated. %%E \item \texttt{edge.Trans}: New argument \texttt{gW} for efficiency. \item \texttt{eem}: The function \texttt{eem} is now generic, with methods for \texttt{ppm} and \texttt{slrm}. The function previously named \texttt{eem} is now called \texttt{eem.ppm}. \item \texttt{effectfun}: \begin{itemize} \item Now works for \texttt{ppm}, \texttt{kppm}, \texttt{lppm}, \texttt{dppm}, \texttt{rppm} and \texttt{profilepl} objects. \item New argument \texttt{nvalues}. \end{itemize} \item \texttt{envelope}: \begin{itemize} \item New argument \texttt{clamp} gives greater control over one-sided envelopes. \item New argument \texttt{funargs} \item New argument \texttt{scale} allows global envelopes to have width proportional to a specified function of $r$, rather than constant width. \item New argument \texttt{funYargs} contains arguments to the summary function when applied to the data pattern only. \item The argument \texttt{simulate} can now be a function (such as \texttt{rlabel}). The function will be applied repeatedly to the original data pattern. \item \texttt{rejectNA} and \texttt{silent}. \end{itemize} \item \texttt{envelope.lpp}, \texttt{envelope.lppm}: \begin{itemize} \item New arguments \texttt{fix.n} and \texttt{fix.marks} allow envelopes to be computed using simulations conditional on the observed number of points. \item New arguments \texttt{maxnerr}, \texttt{rejectNA} and \texttt{silent}. \end{itemize} \item \texttt{eval.im}: New argument \texttt{warn}. \item \texttt{eval.linim}: New argument \texttt{warn}. \item \texttt{ewcdf}: \begin{itemize} \item Argument \texttt{weights} can now be \texttt{NULL}. \item New arguments \texttt{normalise} and \texttt{adjust}. \item Computation accelerated. \item The result does not inherit class \texttt{"ecdf"} if \texttt{normalise=FALSE}. \end{itemize} %%F \item \texttt{Fest}: Additional checks for errors in input data. \item \texttt{Finhom}: \begin{itemize} \item A warning is issued if bias is likely to occur because of undersmoothing. \item New arguments \texttt{warn.bias} and \texttt{savelambda}. \end{itemize} \item \texttt{fitted.lppm}: New argument \texttt{leaveoneout} allows leave-one-out computation of fitted value. \item \texttt{fitted.ppm}: \begin{itemize} \item New option, \texttt{type="link"}. \item New argument \code{ignore.hardcore}. \end{itemize} \item \texttt{funxy}: \begin{itemize} \item When the user calls a function that was created by \texttt{funxy}, the user may now give a \texttt{ppp} or \texttt{lpp} object for the argument \texttt{x}, instead of giving two coordinate vectors \texttt{x} and \texttt{y}. \item Functions of class \texttt{"funxy"} can now be applied to quadrature schemes. \end{itemize} %%G \item \texttt{Gcross}: Function labels (shown on the plot legend) have been improved when \texttt{i = j}. \item \texttt{Geyer}: The saturation parameter \texttt{sat} can now be less than 1. \item \texttt{Ginhom}: \begin{itemize} \item A warning is issued if bias is likely to occur because of undersmoothing. \item New arguments \texttt{warn.bias} and \texttt{savelambda}. \end{itemize} \item \texttt{grow.rectangle}: New argument \texttt{fraction}. %%H \item \texttt{harmonise.im}: The result belongs to classes \texttt{solist} and \texttt{imlist} so that it can be plotted. \item \texttt{Hest}: \begin{itemize} \item Argument \texttt{X} can now be a pixel image with logical values. \item New argument \texttt{W}. [Based on code by Kassel Hingee.] \item Additional checks for errors in input data. \end{itemize} \item \texttt{hist.im}: New argument \texttt{xname}. \item \texttt{hyperframe}: \begin{itemize} \item The formal default value of \texttt{stringsAsFactors} has been changed to \texttt{NULL} to conform to changes in R. (The actual default value is \texttt{TRUE} for \texttt{R < 4.1.0} and \texttt{FALSE} for \texttt{R >= 4.1.0}). \end{itemize} %%I \item \texttt{identify.psp}: Improved placement of labels. Arguments can be passed to \texttt{text.default} to control the plotting of labels. \item \texttt{idw}: Standard errors can now be calculated by setting \texttt{se=TRUE}. \item \texttt{imcov}: the name of the unit of length is preserved. \item \texttt{im.apply}: \begin{itemize} \item Computation accelerated \item New argument \texttt{fun.handles.na} \item New argument \texttt{check} \end{itemize} \item \texttt{influence.ppm}: For Gibbs models, memory usage has been dramatically reduced, so the code can handle larger datasets and finer quadrature schemes. \item \texttt{integral.im}: Accelerated in the case where \texttt{domain} is a tessellation. \item \texttt{integral.linfun}: \begin{itemize} \item New argument \texttt{delta} controls step length of approximation to integral. \item New argument \texttt{nd} controls approximate number of sample points used to calculate integral. \item Argument \code{domain} can be a tessellation. \item Now handles complex-valued functions. \end{itemize} \item \texttt{integral.linim}: \begin{itemize} \item Argument \code{domain} can be a tessellation. \item Now handles complex-valued functions. \end{itemize} \item \texttt{integral.ssf}: Argument \code{domain} can be a tessellation. \item \texttt{intensity.ppm}: Intensity approximation is now implemented for area-interaction model, and Geyer saturation model. \item \texttt{interp.im}: New argument \texttt{bilinear}. \item \texttt{iplot}, \texttt{iplot.ppp}, \texttt{iplot.layered}, \texttt{iplot.linnet}, \texttt{iplot.default}: These interactive plotting functions have been removed from \pkg{spatstat} into a new package \pkg{spatstat.gui}. \item \texttt{ippm}: \begin{itemize} \item Accelerated. \item The internal format of the result has been extended slightly. \item Improved defaults for numerical algorithm parameters. \end{itemize} \item \texttt{istat}: This interactive analysis function has been removed from \pkg{spatstat} into a new package \pkg{spatstat.gui}. %%J \item \texttt{Jcross}: Function labels (shown on the plot legend) have been improved when \texttt{i = j}. \item \texttt{Jfox}: new argument \texttt{warn.trim}. \item \texttt{Jinhom}: \begin{itemize} \item A warning is issued if bias is likely to occur because of undersmoothing. \item New arguments \texttt{warn.bias} and \texttt{savelambda}. \end{itemize} %%K \item \texttt{Kcross}: Function labels (shown on the plot legend) have been improved when \texttt{i = j}. \item \texttt{Kcross.inhom}, \texttt{Kdot.inhom}, \texttt{Kmulti.inhom}: \begin{itemize} \item These functions now allow intensity values to be given by a fitted point process model. \item New arguments \texttt{update}, \texttt{leaveoneout}, \texttt{lambdaX}. \item Leave-one-out calculation is now implemented when \texttt{lambbdaX} is a fitted model of class \texttt{"dppm"}. \end{itemize} \item \texttt{Kest} \begin{itemize} \item Accelerated computation (for translation and rigid corrections) when window is an irregular shape. \item Calculation of isotropic edge correction for polygonal windows has changed slightly. Results are believed to be more accurate. Computation has been accelerated by about 20 percent in typical cases. \end{itemize} \item \texttt{Kest.fft}: Now has \verb!...! arguments allowing control of spatial resolution. \item \texttt{Kinhom}: \begin{itemize} \item New argument \texttt{ratio}. \item Stops gracefully if \texttt{lambda} contains any zero values. \item Leave-one-out calculation is implemented when \texttt{lambda} is a fitted model of class \texttt{"dppm"}. \end{itemize} \item \texttt{kppm}: \begin{itemize} \item New default settings ensure greater numerical stability of the optimization algorithm against the effects of the scale of the spatial coordinates. New argument \texttt{stabilize} specifies whether the optimization algorithm should be numerically stabilized. \item Fitting a model with \texttt{clusters="LGCP"} no longer requires the package \pkg{RandomFields} to be loaded explicitly. \item New argument \texttt{algorithm} specifies the choice of optimisation algorithm. \item Left hand side of formula can now involve entries in the list \texttt{data}. \item refuses to fit a log-Gaussian Cox model with anisotropic covariance. \item A warning about infinite values of the summary function no longer occurs when the default settings are used. Also affects \texttt{mincontrast}, \texttt{cauchy.estpcf}, \texttt{lgcp.estpcf}, \texttt{matclust.estpcf}, \texttt{thomas.estpcf}, \texttt{vargamma.estpcf}. \item Changed precedence rule for handling the algorithm parameters in the minimum contrast algorithm. Individually-named arguments \texttt{q,p,rmax,rmin} now take precedence over entries with the same names in the list \texttt{ctrl}. \item Improved printed output. \item Improved numerical robustness. \end{itemize} %%L \item \texttt{latest.news}: Now prints news documentation for the current major version, by default. New argument \texttt{major}. \item \texttt{Lcross.inhom}, \texttt{Ldot.inhom}: These functions now allow intensity values to be given by a fitted point process model. New arguments \texttt{update}, \texttt{leaveoneout}, \texttt{lambdaX}. \item \texttt{lengths.psp}: \begin{itemize} \item New argument \texttt{squared}. \item This function will soon be Deprecated in favour of the new name \verb!lengths_psp!. \end{itemize} \item \texttt{Lest}, \texttt{Linhom}, \texttt{Ldot}, \texttt{Lcross}, \texttt{Ldot.inhom}, \texttt{Lcross.inhom}: These summary functions now have explicit argument \texttt{"correction"}. \item \texttt{leverage.ppm}: \begin{itemize} \item For Gibbs models, memory usage has been dramatically reduced, so the code can handle larger datasets and finer quadrature schemes. \item Increased the default resolution of the pixel images. Spatial resolution can now be controlled by the arguments \code{dimyx}, \code{eps}. \end{itemize} \item \texttt{leverage.ppm}, \texttt{influence.ppm}, \texttt{dfbetas.ppm}: \begin{itemize} \item These methods now work for models that were fitted by logistic composite likelihood (\texttt{method='logi'}). \item Computation has been vastly accelerated for models with Geyer interaction fitted using isotropic or translation edge corrections. \item Faster computation in many cases. \item Virtually all models and edge corrections are now supported, using a ``brute force'' algorithm. This can be slow in some cases. \end{itemize} \item \texttt{lineardisc}: \begin{itemize} \item New argument \texttt{add}. \item Default plotting behaviour has changed. \end{itemize} \item \texttt{linearK}, \texttt{linearpcf} and relatives: \\ \begin{itemize} \item substantially accelerated. \item ratio calculations are now supported. \item new argument \texttt{ratio}. \end{itemize} \item \texttt{linearKinhom}: new argument \texttt{normpower}. \item \texttt{linearKinhom}, \texttt{linearpcfinhom}: \begin{itemize} \item Changed behaviour when \texttt{lambda} is a fitted model. \item New arguments \texttt{update} and \texttt{leaveoneout}. \end{itemize} \item \texttt{linearpcf}: new argument \texttt{normpower}. \item \texttt{linim}: \begin{itemize} \item The image \texttt{Z} is now automatically restricted to the network. \item New argument \texttt{restrict}. \end{itemize} \item \texttt{linnet}: \begin{itemize} \item The internal format of a \texttt{linnet} (linear network) object has been changed. Existing datasets of class \texttt{linnet} are still supported. However, computation will be faster if they are converted to the new format. To convert a linnet object \texttt{L} to the new format, use \verb!L <- as.linnet(L)!. \item If the argument \texttt{edges} is given, then this argument now determines the ordering of the sequence of line segments. For example, the \texttt{i}-th row of \texttt{edges} specifies the \texttt{i}-th line segment in \texttt{as.psp(L)}. \item New argument \texttt{warn}. \item When argument \texttt{edges} is specified, the code now checks whether any edges are duplicated. \end{itemize} \item \texttt{lintess}: \begin{itemize} \item Argument \texttt{df} can be missing or \texttt{NULL}, resulting in a tesellation with only one tile. \item Tessellations can now have marks. New argument \texttt{marks}. \end{itemize} \item \texttt{localpcf}: New argument \texttt{rvalue}. \item \texttt{localpcfinhom}: \begin{itemize} \item New arguments \texttt{update}, \texttt{leaveoneout}, \texttt{rvalue}. \end{itemize} \item \texttt{logLik.ppm}: \begin{itemize} \item New argument \texttt{absolute}. \item The warning about pseudolikelihood (`log likelihood not available') is given only once, and is not repeated in subsequent calls, within a spatstat session. \end{itemize} \item \texttt{logLik.mppm}: new argument \texttt{warn}. \item \texttt{lohboot}: \begin{itemize} \item Algorithm has been corrected and extended thanks to Christophe Biscio and Rasmus Waagepetersen. \item New arguments \texttt{block}, \texttt{basicboot}, \texttt{Vcorrection}. \item Accelerated when the window is a rectangle. \item Now works for multitype $K$ functions \texttt{Kcross}, \texttt{Kdot}, \texttt{Lcross}, \texttt{Ldot}, \texttt{Kcross.inhom}, \texttt{Lcross.inhom} \item Confidence bands for \texttt{Lest}, \texttt{Linhom}, \texttt{Lcross}, \texttt{Ldot}, \texttt{Lcross.inhom} are now computed differently. First a confidence band is computed for the corresponding $K$ function \texttt{Kest}, \texttt{Kinhom}, \texttt{Kcross}, \texttt{Kdot}, \texttt{Kcross.inhom} respectively. Then this is transformed to a confidence band for the $L$ function by applying the square root transformation. \end{itemize} \item \texttt{lpp}: \begin{itemize} \item The internal format of an \texttt{lpp} object has been changed. Existing datasets of class \texttt{lpp} are still supported. However, computation will be faster if they are converted to the new format. To convert an \texttt{lpp} object \texttt{X} to the new format, use \verb!X <- as.lpp(X)!. \item \texttt{X} can be missing or \texttt{NULL}, resulting in an empty point pattern. \item Now handles the case where coordinates \texttt{seg} and \texttt{tp} are given but \texttt{x} and \texttt{y} are missing. \end{itemize} \item \texttt{lppm}: \begin{itemize} \item New argument \texttt{random} controls placement of dummy points. \item Computation accelerated. \end{itemize} \item \texttt{lurking.ppm}: accelerated. \item \texttt{lut}: argument \texttt{outputs} may have length 1, representing a lookup table in which all data values are mapped to the same output value. %%M \item \texttt{markconnect}: Accepts the argument \texttt{weights} which is passed to \texttt{markcorr}. \item \texttt{markcorr}: New argument \texttt{weights} allows computation of the weighted version of the mark correlation function. Weights can be an expression to be evaluated, or a function, or a pixel image, or a numeric vector. \item \texttt{markvario}: Accepts the argument \texttt{weights} which is passed to \texttt{markcorr}. \item \texttt{mincontrast}: New argument \texttt{action.bad.values} specifies what action is taken when the summary function produces \texttt{NA} or \texttt{NaN} or infinite values. \item \texttt{minnndist}, \texttt{maxnndist}: New argument \texttt{by} makes it possible to find the minimum or maximum nearest neighbour distance between each pair of possible types in a multitype pattern. \item \texttt{mppm}: \begin{itemize} \item Now handles models with a random effect component. (This is covered in \cite[Chap.\ 16]{baddrubaturn15}.) \item New argument \texttt{random} is a formula specifying the random effect. (This is covered in \cite[Chap.\ 16]{baddrubaturn15}.) \item Performs more checks for consistency of the input data. \item New arguments \texttt{gcontrol} and \texttt{reltol.pql} control the fitting algorithm. \item New argument \texttt{weights} specifies case weights for each row of data. \end{itemize} \item \texttt{msr}: Infinite and \texttt{NA} values are now detected (if \texttt{check=TRUE}) and are reset to zero, with a warning. %%N \item \texttt{nbfires}: \begin{itemize} \item the unit of length for the coordinates is now specified in this dataset. \item This dataset now includes information about the different land and sea borders of New Brunswick. \end{itemize} \item \texttt{nncorr,nnmean,nnvario}: New argument \texttt{na.action}. \item \texttt{nncross.lpp}: \begin{itemize} \item New argument \texttt{k} allows computation of $k$-th nearest point. \item Computation accelerated. \end{itemize} \item \texttt{nndist.pp3}: New argument \texttt{by} allows computation of the nearest distance to each group of points. \item \texttt{nndist.ppx}: New argument \texttt{by} allows computation of the nearest distance to each group of points. \item \texttt{nndist.lpp}: \begin{itemize} \item New argument \texttt{k} allows computation of $k$-th nearest point. \item new argument \texttt{by} allows computation of the nearest distance to each group of points. \item Computation accelerated. \end{itemize} \item \texttt{nnwhich.lpp}: \begin{itemize} \item New argument \texttt{k} allows computation of $k$-th nearest point. \item new argument \texttt{by} allows computation of the nearest distance to each group of points. \item Computation accelerated. \end{itemize} \texttt{nnfun.lpp}: \begin{itemize} \item New argument \texttt{k}. \item New argument \texttt{value} specifies whether to return the index of the nearest neighbour or the mark value of the nearest neighbour. \end{itemize} \texttt{nnfun.ppp}: \begin{itemize} \item New argument \texttt{value} specifies whether to return the index of the nearest neighbour or the mark value of the nearest neighbour. \end{itemize} \texttt{nnfun.psp}: \begin{itemize} \item New argument \texttt{value} specifies whether to return the index of the nearest neighbour or the mark value of the nearest neighbour. \end{itemize} %%O \item \texttt{owin}: If argument \texttt{mask} is a logical matrix, \texttt{NA} entries will be accepted, and converted to \texttt{FALSE}. %%P \item \texttt{padimage}: New argument \texttt{W} allows an image to be padded out to fill any window. \item \texttt{pairdist.lpp}: Now handles much larger networks, using the sparse representation of the network. \item \texttt{pairorient}: Default edge corrections now include \texttt{"bord.modif"}. \item \texttt{pairs.im}: new argument \texttt{drop}. \item \texttt{parres}: the argument \texttt{covariate} is allowed to be missing if the model only depends on one covariate. \item \texttt{pcf.ppp}: \begin{itemize} \item New argument \code{close} for advanced use. \item New argument \texttt{ratio} allows several estimates of pcf to be pooled. \item Now calculates an analytic approximation to the variance of the estimate of the pair correlation function (when \texttt{var.approx=TRUE}). \item Now returns the smoothing bandwidth used, as an attribute of the result. \item New argument \texttt{close} for advanced use. \item Now accepts \texttt{correction="none"}. \end{itemize} \item \texttt{pcfinhom}: \begin{itemize} \item New argument \code{close} for advanced use. \item Default behaviour is changed when \texttt{lambda} is a fitted model. The default is now to re-fit the model to the data before computing pcf. New arguments \texttt{update} and \texttt{leaveoneout} control this. \item New argument \texttt{close} for advanced use. \item Now handles \texttt{correction="good"} \item Leave-one-out calculation is implemented when \texttt{lambda} is a fitted model of class \texttt{"dppm"}. \end{itemize} \item \code{persp.funxy}: Improved $z$-axis label. \item \texttt{pixellate.ppp}: \begin{itemize} \item If the pattern is empty, the result is an integer-valued image (by default) for consistency with the results for non-empty patterns. \item Accelerated in the case where weights are given. \item New arguments \texttt{fractional} and \texttt{preserve} for more accurate discretisation. \item New argument \texttt{savemap}. \end{itemize} \item \texttt{plot.anylist}: \begin{itemize} \item If a list entry \verb!x[[i]]! belongs to class \texttt{"anylist"}, it will be expanded so that each entry \verb!x[[i]][[j]]! will be plotted as a separate panel. \item New arguments \texttt{panel.begin.args}, \texttt{panel.end.args} \item Result is now an (invisible) list containing the result from executing the plot of each panel. \end{itemize} \item \texttt{plot.colourmap}: \begin{itemize} \item Now handles a colour map for a zero-length interval [a,a] \item New argument \texttt{increasing} specifies whether the colours are displayed in order left-to-right/bottom-to-top. \item Changed default behaviour for discrete colour maps when \texttt{vertical=FALSE}. \end{itemize} \item \texttt{plot.im}: \begin{itemize} \item Now handles complex-valued images. \item New argument \texttt{workaround} to avoid a bug in some MacOS device drivers that causes the image to be displayed in the wrong spatial orientation. \item The number of tick marks in the colour ribbon can now be controlled using the argument \texttt{nint} in \texttt{ribargs}. \item Improved behaviour when all pixel values are \texttt{NA}. \item Improved handling of tickmarks on colour ribbon. \item Improved behaviour when the image values are almost constant. \item New argument \texttt{riblab}. \item Axes are prevented from extending outside the image rectangle. \item New argument \texttt{zap}. \item Some warnings are suppressed when \texttt{do.plot=FALSE}. \end{itemize} \item \texttt{plot.imlist}: Result is now an (invisible) list containing the result from executing the plot of each panel. \item \texttt{plot.influence.ppm}: New argument \texttt{multiplot}. \item \texttt{plot.kppm}: \begin{itemize} \item New arguments \texttt{pause} and \texttt{xname}. \item The argument \texttt{what="all"} is now recognised: it selects all the available options. [This is also the default.] \end{itemize} \item \texttt{plot.leverage.ppm}: \begin{itemize} \item New arguments \texttt{multiplot} and \code{what}. \item A contour line showing the average value of leverage is now drawn on the colour ribbon, as well as on the main image. New argument \texttt{args.contour}. \end{itemize} \item \texttt{plot.linfun}: \begin{itemize} \item Now passes arguments to the function being plotted. \item A scale bar is now plotted when \texttt{style="width"}. \item New argument \texttt{legend}. \item The return value has a different format. \end{itemize} \item \texttt{plot.linim}: \begin{itemize} \item The return value has a different format. \item New argument \texttt{fatten} improves visual appearance when \texttt{style="colour"}. \item A scale bar is now plotted when \texttt{style="width"}. \item When \texttt{style="width"}, negative values are plotted in red (by default). New argument \texttt{negative.args} controls this. \item New argument \texttt{zlim} specifies the range of values to be mapped. \item New explicit argument \texttt{box} determines whether to plot a bounding box; default is \texttt{FALSE} in all cases. \end{itemize} \item \texttt{plot.lintess}: \begin{itemize} \item Improved plot method, with more options. \item Modified to display the marks attached to the tiles. \item Options: \verb!style=c("colour", "width", "image")!. \end{itemize} \item \texttt{plot.lpp}: \begin{itemize} \item New argument \texttt{show.network}. \item For a point pattern with continuous marks (``real numbers'') the colour arguments \texttt{cols}, \texttt{fg}, \texttt{bg} can now be vectors of colour values, and will be used to determine the default colour map for the marks. \end{itemize} \item \texttt{plot.mppm}: New argument \texttt{se}. \item \texttt{plot.msr}: \begin{itemize} \item Now handles multitype measures. \item New argument \texttt{multiplot}. \item New argument \texttt{massthresh}. \item New arguments \texttt{equal.markscale} and \texttt{equal.ribbon}. \end{itemize} \item \texttt{plot.onearrow:} Graphical parameters, specified when the object was created, are now taken as the defaults for graphical parameters to the plot. \item \texttt{plot.owin:} New argument \texttt{use.polypath} controls how to plot a filled polygon when it has holes. \item \texttt{plot.profilepl}: This function has now been documented, and the graphics improved. \item \texttt{plot.psp}: \begin{itemize} \item Segments can be plotted with widths proportional to their mark values. \item New argument \texttt{style}. \item New argument \texttt{col} gives control over the colour map representing the values of marks attached to the segments. \item The code for \texttt{style="width"} has been completely rewritten, so that it no longer depends on \texttt{plot.linim}, and is much more efficient. \item The formal argument list has been extended. \end{itemize} \item \texttt{plot.pp3}: New arguments \texttt{box.front}, \texttt{box.back} control plotting of the box. \item \texttt{plot.ppp}: \begin{itemize} \item The default colour for the points is now a transparent grey, if this is supported by the plot device. \item For a point pattern with continuous marks (``real numbers'') the colour arguments \texttt{cols}, \texttt{fg}, \texttt{bg} can now be vectors of colour values, and will be used to determine the default colour map for the marks. \item Now recognises graphics parameters for text, such as \texttt{family} and \texttt{srt} \item When \texttt{clipwin} is given, any parts of the boundary of the window of \texttt{x} that lie inside \texttt{clipwin} will also be plotted. \item Improved placement of symbol map legend when argument \texttt{symap} is given. \end{itemize} \item \code{plot.tess}: \begin{itemize} \item This plot method can now fill each tile with a different colour. \item New arguments \code{do.col}, \code{values}, \code{col} and \code{ribargs}. Old argument \code{col} has been renamed \code{border} for consistency. \item Now generates a separate plot panel for each column of marks, if \texttt{do.col=TRUE}. \item New argument \texttt{multiplot}. \end{itemize} \item \texttt{plot.profilepl} ,\texttt{plot.quadratcount}, \texttt{plot.quadrattest}, \texttt{plot.tess}: Now recognise graphics parameters for text, such as \texttt{family} and \texttt{srt} \item \texttt{plot.solist}: \begin{itemize} \item New arguments \texttt{panel.begin.args}, \texttt{panel.end.args} \item Result is now an (invisible) list containing the result from executing the plot of each panel. \end{itemize} \item \texttt{plot.studpermutest}: This existing function now has a help file. \item \texttt{plot.symbolmap}: New argument \texttt{nsymbols} controls the number of symbols plotted. \item \code{ponderosa}: In this installed dataset, the function \code{ponderosa.extra\$plotit} has changed slightly (to accommodate the dependence on the package \pkg{spatstat.utils}). \item \texttt{polynom}: This function now has a help file. \item \texttt{pool.fv}: \begin{itemize} \item The default plot of the pooled function no longer includes the variance curves. \item New arguments \texttt{relabel} and \texttt{variance}. \end{itemize} \item \texttt{pool.rat}: New arguments \texttt{weights}, \texttt{relabel} and \texttt{variance}. \item \texttt{ppm}: \begin{itemize} \item Argument \code{interaction} can now be a function that makes an interaction, such as \code{Poisson}, \code{Hardcore}, \code{MultiHard}. \item Argument \texttt{subset} can now be a window (class \texttt{"owin"}) specifying the sub-region of data to which the model should be fitted. \end{itemize} \item \texttt{ppm.ppp, ppm.quad}: \begin{itemize} \item New argument \texttt{emend}, equivalent to \texttt{project}. \item New arguments \texttt{subset} and \texttt{clipwin}. \end{itemize} \item \code{ppmInfluence}: The result now belongs to class \code{ppmInfluence}, for which there are methods for \code{leverage}, \code{influence}, \code{dfbetas} which extract the desired component. \item \texttt{ppp}: \begin{itemize} \item New argument \texttt{checkdup}. \item If the coordinate vectors \code{x} and \code{y} contain \code{NA}, \code{NaN} or infinite values, these points are deleted with a warning, instead of causing a fatal error. \end{itemize} \item \texttt{pp3}: New argument \texttt{marks}. \item \texttt{predict.kppm, residuals.kppm} Now issues a warning when the calculation ignores the cluster/Cox component and treats the model as if it were Poisson. (This currently happens in predict.kppm when se=TRUE or interval != "none", and in residuals.kppm when type != "raw"). \item \texttt{predict.lppm}: Argument \texttt{locations} can now be an \texttt{lpp} object. \item \texttt{predict.mppm}: \begin{itemize} \item The argument \texttt{type="all"} is now recognised: it selects all the available options. [This is also the default.] \item Now supports multitype point process models. \item Improved handling of argument \texttt{newdata}. \end{itemize} \item \texttt{predict.ppm}: \begin{itemize} \item Now recognises the arguments \code{dimyx} and \code{eps} for specifying the resolution of the grid of prediction points. \item New argument \code{ignore.hardcore}. \item Accelerated for models fitted with \texttt{method="VBlogi"} \end{itemize} \item \texttt{predict.rhohat}: New argument \texttt{what} determines which value should be calculated: the function estimate, the upper/lower confidence limits, or the standard error. \item \texttt{print.linim}: More information is printed. \item \texttt{print.lintess}: Output includes information about marks. \item \texttt{print.quad}: More information is printed. \item \texttt{print.rmhmodel}: More information is printed. \item \texttt{progressreport} \begin{itemize} \item Behaviour improved. \item New arguments \texttt{state}, \texttt{tick}, \texttt{showtime}. \item New option: \verb!style="tk"! \end{itemize} \item \code{pseudoR2.ppm}, \code{pseudoR2.lppm}: \begin{itemize} \item The null model now includes any offset terms, by default. \item New argument \code{keepoffset}. \end{itemize} %%Q \item \texttt{quadform}: This function has been moved to the sub-package \texttt{spatstat.sparse}. \item \texttt{quadratcount.ppp}: Computation accelerated in some cases. \item \texttt{quadrat.test.ppm}: Computation accelerated in some cases. \item \texttt{quantess}: \begin{itemize} \item The covariate \texttt{Z} can now be \texttt{"rad"} or \texttt{"ang"} representing polar coordinates. \item New argument \texttt{origin} specifies the origin of polar coordinates. \item New argument \texttt{eps} controls the accuracy of the calculation. \end{itemize} \item \texttt{quantile.ewcdf}: The function is now normalised to the range \verb![0,1]! before the quantiles are computed. This can be suppressed by setting \texttt{normalise=FALSE}. \item \texttt{qqplot.ppm} Argument \texttt{expr} can now be a list of point patterns, or an envelope object containing a list of point patterns. %%R \item \texttt{rbind.hyperframe}: The result now retains the \texttt{row.names} of the original arguments. \item \texttt{rcellnumber}: New argument \texttt{mu}. \item \texttt{rebound.owin}: Now preserves unitnames of the objects. \item \texttt{rescale.owin}, \texttt{rescale.ppp}, \texttt{rescale.psp}: The geometrical type of the window is now preserved in all cases. (Previously if the window was polygonal but was equivalent to a rectangle, the rescaled window was a rectangle.) \item \texttt{rgbim, hsvim}: New argument \texttt{A} controls the alpha (transparency) channel. \item \texttt{rgb2hex, col2hex, paletteindex, is.colour, samecolour,} \texttt{complementarycolour, is.grey, to.grey} These colour tools now handle transparent colours. \item \texttt{rgb2hex}: New argument \texttt{maxColorValue} \item \texttt{relrisk.ppp}: \begin{itemize} \item If \texttt{se=TRUE} and \texttt{at="pixels"}, the result belongs to class \texttt{solist}. \item The arguments \texttt{adjust}, \texttt{edge}, \texttt{diggle} are now explicit formal arguments. \item New argument \texttt{weights}. \end{itemize} \texttt{rhohat}: \begin{itemize} \item The result now includes the ``average'' intensity $\overline\rho$. \item New options \texttt{smoother="piecewise"} computes a piecewise-constant estimate of $\rho(z)$. \item Nonparametric maximum likelihood estimation is now supported, assuming the intensity is a monotone function of the covariate. \item New options \texttt{smoother="increasing"} and \texttt{smoother="decreasing"}. \item New argument \texttt{subset} allows computation for a subset of the data. \item New argument \texttt{positiveCI} specifies whether confidence limits should always be positive. \end{itemize} \texttt{rhohat.lpp}: New argument \texttt{random} controls placement of dummy points. \item \texttt{rlabel}: \begin{itemize} \item New argument \texttt{group} specifies that the points are divided into several groups, and that relabelling is applied within each group. \item New arguments \texttt{nsim} and \texttt{drop}. \item \texttt{X} can now be a point pattern of any type (\texttt{ppp}, \texttt{lpp}, \texttt{pp3}, \texttt{ppx}) or a line segment pattern (\texttt{psp}). \end{itemize} \item \texttt{rlabel.ppp}: New argument \texttt{group} specifies that the points are divided into several groups, and that relabelling is applied within each group. \item \texttt{rLGCP}: \begin{itemize} \item Accelerated. \item This function no longer requires the package \pkg{RandomFields} to be loaded explicitly. \end{itemize} \item \texttt{rMaternI, rMaternII}: These functions can now generate random patterns in three dimensions and higher dimensions, when the argument \texttt{win} is of class \texttt{box3} or \texttt{boxx}. \item \texttt{rmh}: \begin{itemize} \item Accelerated, in the case where multiple patterns are saved using \texttt{nsave}. \item The printed output of the debugger (invoked by \texttt{snoop=TRUE}) has been improved. \end{itemize} \item \texttt{rmh.ppm, rmhmodel.ppm, simulate.ppm}: A model fitted using the \texttt{Penttinen} interaction can now be simulated. \item \texttt{rmh.default, rmhmodel.default}: \begin{itemize} \item These functions now recognise \verb!cif='penttinen'! for the Penttinen interaction. \item New arguments \texttt{nsim}, \texttt{saveinfo}. \item The printed output of the debugger (invoked by \texttt{snoop=TRUE}) has been improved. \end{itemize} \item \texttt{rmhcontrol}: \begin{itemize} \item New parameter \texttt{pstage} determines when to generate random proposal points. \item The parameter \texttt{nsave} can now be a vector of integers. \end{itemize} \item \texttt{rose.default} New argument \texttt{weights}. \item \texttt{rose} New arguments \texttt{start} and \texttt{clockwise} specify the convention for measuring and plotting angles. \item \texttt{rotmean}: \begin{itemize} \item New argument \texttt{padzero}. \item Default behaviour has changed. \item Improved algorithm stability. \item The result now has the same \texttt{unitname} as the input object. \item New argument \texttt{adjust} controls the smoothing bandwidth. \end{itemize} \item \texttt{rpoint}: New argument \texttt{forcewin} forces the code to use the window \texttt{win} when \texttt{f} is a pixel image. \item \texttt{rpoispp}: Accelerated, when \texttt{lambda} is a pixel image. \item \texttt{rpoisppx}: New argument \code{drop}. \item \texttt{rpoisline}: Also returns information about the original infinite random lines. \item \texttt{rpoislpp}: If \texttt{lambda} is a list of \texttt{"linim"} or \texttt{"linfun"} objects, then the argument \texttt{L} can be omitted. \item \texttt{rshift.ppp}, \texttt{rshift.splitppp}: new argument \texttt{nsim}. \item \texttt{rSSI}: Accelerated. \item \texttt{rStrauss, rHardcore, rStraussHard, rDiggleGratton, rDGS, rPenttinen:} New argument \texttt{drop}. \item \texttt{rtemper:} new argument \texttt{track}. \item \texttt{rthin} \begin{itemize} \item Accelerated, when \texttt{P} is a single number. \item \texttt{X} can now be a point pattern of any type (\texttt{ppp}, \texttt{lpp}, \texttt{pp3}, \texttt{ppx}) or a line segment pattern (\texttt{psp}). \end{itemize} \item \texttt{rThomas, rMatClust, rCauchy, rVarGamma}: \begin{itemize} \item When the model is approximately Poisson, it is simulated using rpoispp. This avoids computations which would require huge amounts of memory. New argument \texttt{poisthresh} controls this behaviour. \item New argument \texttt{saveparents}. \end{itemize} \item \texttt{runifpointOnLines}, \texttt{rpoisppOnLines}: New argument \code{drop}. \item \texttt{runifpointx}: New argument \code{drop}. %%S \item \texttt{selfcut.psp}: \begin{itemize} \item Computation accelerated. \item The result now has an attribute \texttt{"camefrom"} indicating the provenance of each segment in the result. \item No longer checks for validity of the resulting segments. \end{itemize} \item \texttt{sessionInfo}: Output now includes a list of packages that are imported but not loaded. \item \texttt{sessionLibs}: Package names are now sorted alphabetically \item \texttt{setcov}: the name of the unit of length is preserved. \item \code{shapley}: In this installed dataset, the function \code{shapley.extra\$plotit} has changed slightly (to accommodate the dependence on the package \pkg{spatstat.utils}). \item \texttt{shift.im}, \texttt{shift.owin}, \texttt{shift.ppp}, \texttt{shift.psp}: More options for the argument \texttt{origin}. \item Simulation: Several basic simulation algorithms have been accelerated. Consequently, simulation outcomes are not identical to those obtained with previous versions of \spst, even when the same random seed is used. To ensure compatibility with previous versions of spatstat, revert to the slower code by setting \texttt{spatstat.options(fastthin=FALSE, fastpois=FALSE)}. \item \texttt{simulate.kppm}: \begin{itemize} \item Conditional simulation of the model, given a fixed number of points, is now supported using the new arguments \texttt{n.cond} and \texttt{w.cond}. \item Accelerated for LGCP models. \item Additional arguments \verb!...! are now passed to the function that performs the simulation. \end{itemize} \item \texttt{simulate.ppm}: \begin{itemize} \item New argument \texttt{w} controls the window of the simulated patterns. \item New argument \texttt{verbose}. \item Now recognises the argument \texttt{window} as an alternative to \texttt{w}. \end{itemize} \item \texttt{slrm}: \begin{itemize} \item In the default case (where \texttt{dataAtPoints} is not given) all spatial covariates, including the spatial coordinates \texttt{x} and \texttt{y}, are now evaluated at the centre of each pixel. This improves consistency with other implementations of spatial logistic regression. \item Silently ignores any arguments \verb!'...'! that are not recognised by \texttt{as.mask} \end{itemize} \item \texttt{Smooth.ppp}: \begin{itemize} \item A non-Gaussian kernel can now be specified using the argument \texttt{kernel}. \item Argument \texttt{weights} can now be a pixel image, a function, a numeric vector or an expression to be evaluated. \item Infinite bandwidth \texttt{sigma=Inf} is supported. \item Accelerated by about 30\% in the case where \texttt{at="pixels"}. \item Accelerated by about 15\% in the case where \texttt{at="points"} and \texttt{kernel="gaussian"}. \item Now exits gracefully if any mark values are \texttt{NA}, \texttt{NaN} or \texttt{Inf}. \item New argument \texttt{geometric} supports geometric-mean smoothing. \item The arguments \texttt{adjust}, \texttt{edge}, \texttt{diggle} and \texttt{kernel} are now explicit formal arguments. \end{itemize} \item \texttt{solist}: New argument \verb!.NameBase! \item \texttt{spatialcdf}: \begin{itemize} \item Computation accelerated. \item The result does not inherit class \texttt{"ecdf"} if \texttt{normalise=FALSE}. \end{itemize} \item \texttt{spatstat.options} New options \texttt{fastthin} and \texttt{fastpois} enable fast simulation algorithms. Set these options to \texttt{FALSE} to reproduce results obtained with previous versions of \spst. \item \texttt{split.ppp}, \texttt{split.ppx}: The splitting variable \texttt{f} can now be a logical vector. \item \verb!split<-.ppp!: The default for argument \texttt{un} in \verb!split<-.ppp! now agrees with the default for the same argument in \texttt{split.ppp}. \item \texttt{square}: Handles a common error in the format of the arguments. \item \texttt{step}: now works for models of class \texttt{"mppm"}. \item \texttt{stieltjes}: Argument \texttt{M} can be a stepfun object (such as an empirical CDF). \item \texttt{subset.ppp}, \texttt{subset.lpp}, \texttt{subset.pp3}, \texttt{subset.ppx}: The argument \texttt{subset} can now be any argument acceptable to the \verb!"["! method. \item \texttt{Summary.linim} (methods for the operations \texttt{range}, \texttt{max}, \texttt{min} etc): Recognises the argument \texttt{finite} so that \texttt{range(x, finite=TRUE)} works for a linim object \texttt{x}. \item summary functions: The argument \texttt{correction="all"} is now recognised: it selects all the available options. \begin{quote} This applies to \texttt{Fest}, \texttt{F3est}, \texttt{Gest}, \texttt{Gcross}, \texttt{Gdot}, \texttt{Gmulti}, \texttt{G3est}, \texttt{Gfox}, \texttt{Gcom}, \texttt{Gres}, \texttt{Hest}, \texttt{Jest}, \texttt{Jmulti}, \texttt{Jcross}, \texttt{Jdot}, \texttt{Jfox}, \texttt{Kest}, \texttt{Kinhom}, \texttt{Kmulti}, \texttt{Kcross}, \texttt{Kdot}, \texttt{Kcom}, \texttt{Kres}, \texttt{Kmulti.inhom}, \texttt{Kcross.inhom}, \texttt{Kdot.inhom}, \texttt{Kscaled}, \texttt{Ksector}, \texttt{Kmark}, \texttt{K3est}, \texttt{Lscaled}, \texttt{markcorr}, \texttt{markcrosscorr}, \texttt{nnorient}, \texttt{pairorient}, \texttt{pcfinhom}, \texttt{pcfcross.inhom}, \texttt{pcfcross}, \texttt{pcf}, \texttt{Tstat}. \end{quote} \item \texttt{summary.distfun}, \texttt{summary.funxy}: \begin{itemize} \item More information is printed. \item Pixel resolution can now be controlled. \end{itemize} \item \texttt{summary.im}: Output improved when the image is empty (i.e. when all pixel values are undefined). \item \texttt{summary.kppm}: prints more information about algorithm convergence. \item \texttt{summary.lintess}: prints information about marks. \item \texttt{summary.mppm}: Improved summary of the dependence of the interpoint interaction on the covariates. \item \texttt{summary.ppm}: New argument \texttt{fine} selects the algorithm for variance estimation. \item \texttt{summary.owin}, \texttt{summary.im}: The fraction of frame area that is occupied by the window/image is now reported. \item \texttt{sumouter}: \begin{itemize} \item New argument \texttt{y} allows computation of asymmetric outer products. \item This function has now been moved to the sub-package \texttt{spatstat.sparse} \end{itemize} \item \texttt{symbolmap}: \begin{itemize} \item Now accepts a vector of colour values for the arguments \texttt{col}, \texttt{cols}, \texttt{fg}, \texttt{bg} if the argument \texttt{range} is given. \item New option: \texttt{shape="arrows"}. \end{itemize} %%T \item \texttt{tess}: Argument \texttt{window} is ignored when xgrid, ygrid are given. \item \texttt{texturemap}: Argument \texttt{textures} can be missing or NULL. \item \texttt{textureplot}: Argument \texttt{x} can now be something acceptable to \texttt{as.im}. \item \texttt{tilenames}, \verb!tilenames<-!: These functions are now generic, with methods for \texttt{tess} and \texttt{lintess}. \item \texttt{to.grey} New argument \texttt{transparent}. \item \texttt{transect.im}: new argument \texttt{nsample}. %%U \item \texttt{union.owin}: Improved behaviour when there are more than 2 windows. \item \texttt{unstack.lintess}: now handles marks. \item \texttt{update}: now works for models of class \texttt{"mppm"}. \item \texttt{update.kppm}: \begin{itemize} \item New argument \texttt{evaluate}. \item Now handles additional arguments in any order, with or without names. \item Changed arguments. \item Improved behaviour. \end{itemize} \item \texttt{update.ppm}: For the case \texttt{update(model, X)} where \texttt{X} is a point pattern, if the window of \texttt{X} is different from the original window, then the model is re-fitted from scratch (i.e. \texttt{use.internal=FALSE}). %%V \item \texttt{valid.ppm} This is now a method for the generic function \texttt{valid}. \item \texttt{vcov.mppm}: \begin{itemize} \item Now handles models with Gibbs interactions. \item New argument \texttt{nacoef.action} specifies what to do if some of the fitted coefficients are \texttt{NA}, \texttt{NaN} or \texttt{Inf}. \end{itemize} \item \texttt{vcov.ppm}: \begin{itemize} \item Performance slightly improved, for Gibbs models. \item Variance calculations now handle larger datasets because they use sparse arrays, by default. \item New argument \texttt{nacoef.action} specifies what to do if some of the fitted model coefficients are \texttt{NA}, \texttt{NaN} or infinite. \end{itemize} %%W %%X %%Y %%Z \item \verb![<-.im! \begin{itemize} \item Accepts an array for \texttt{value}. \item The subset index \texttt{i} can now be a linear network. Then the result of \verb!x[i, drop=FALSE]! is a pixel image of class \texttt{linim}. \item New argument \texttt{drop} controls behaviour when indices are missing as in \verb!x[] <- value! \end{itemize} \item \verb![.layered!: \begin{itemize} \item Subset index \texttt{i} can now be an \texttt{owin} object. \item Additional arguments \verb!...! are now passed to other methods. \end{itemize} \item \verb![.leverage.ppm!: New argument \texttt{update}. \item \verb![.linnet!: \begin{itemize} \item New argument \texttt{snip} determines what to do with segments of the network that cross the boundary of the window. Default behaviour has changed. \item More robust against artefacts when the subset index is a pixel mask. \end{itemize} \item \verb![.linim!: \begin{itemize} \item More robust against artefacts. \item Accelerated. \end{itemize} \item \verb![.lpp!: New argument \texttt{snip} determines what to do with segments of the network that cross the boundary of the window. Default behaviour has changed. \item \verb![.ppx!: \begin{itemize} \item The subset index \texttt{i} may now be a spatial domain of class \texttt{boxx} or \texttt{box3}. \item New argument \texttt{clip}. \end{itemize} \item \verb![.ppp! New argument \texttt{clip} determines whether the window is clipped. \item \verb![.ppp! The previously-unused argument \texttt{drop} now determines whether to remove unused levels of a factor. \item \verb![.pp3!, \verb![.lpp!, \verb![.ppx!, \texttt{subset.ppp, subset.pp3, subset.lpp, subset.ppx}: These methods now have an argument \texttt{drop} which determines whether to remove unused levels of a factor. \item \verb![.psp!: \begin{itemize} \item accelerated. \item New argument \texttt{fragments} specifies whether to keep fragments of line segments that are cut by the new window, or only to retain segments that lie entirely inside the window. \end{itemize} \item \verb![.solist!: Subset index \texttt{i} can now be an \texttt{owin} object. \end{itemize} \begin{thebibliography}{1} \bibitem{badd10wshop} A.~Baddeley. \newblock Analysing spatial point patterns in {{R}}. \newblock Technical report, CSIRO, 2010. \newblock Version 4. \newblock URL \texttt{https://research.csiro.au/software/r-workshop-notes/} \bibitem{baddrubaturn15} A. Baddeley, E. Rubak, and R. Turner. \newblock {\em Spatial Point Patterns: Methodology and Applications with {{R}}}. \newblock Chapman \& Hall/CRC Press, 2015. \end{thebibliography} \end{document} spatstat/inst/doc/updates.pdf0000644000176200001440000067150714155343650016025 0ustar liggesusers%PDF-1.5 % 4 0 obj << /Length 979 /Filter /FlateDecode >> stream xڝUKFWR;fen+Mn,?t `7y vR+J" ss׫'_&T"Yo&v*&Lz.YIGHtZ̖鉹()˭O7@5':O:Pf3ꣻR'AjHQVL+g kF<T/yDt}*bwb\6HԀ 6Ϸ;H:P]!>m _17v}f+A#?diXVmj]*_q{ 2nJ:@E'0g*)ojK0iOR1Sue%'2%pJ.DuR%8/ip({C42m1ϓ0o>HZ&B4¡{I@u/jFu<τь/_G&Ym-<-&i "EtP+˨E 0 n1ퟯ<#,/x 7ҡÎu*o>3.Z0Kaʯ2đ,4ૼZe5s b*܈?Feڃpt#`$M-ي,01s@ 8GߖΥ}6=ch'TPQʀ)[K~J| XQO~Mf\ʣ#^Ya(]>t*+i_GQΥ|Lv^6YndYUA2Tv,l]Aܨԑ^Dh e0TII8.:k.@'ԀTs&fKxtX?#zs)Fo1y%6'un\׈S\ |t.],a7YƎr B endstream endobj 1 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/updates-004.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 13 0 R /BBox [0 0 432 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 14 0 R/F3 15 0 R>> /ExtGState << >>/ColorSpace << /sRGB 16 0 R >>>> /Length 2910 /Filter /FlateDecode >> stream xKSx,:-JH] ($]<hH*Mσ_^<> 1|~|8ھrmck ?' |a}}=a_>Col12ˇѷ}o澍jFBM[¼坈}M1m{a*n ۖ ǖP-}rJT[Hhjڷ:Sl~oCͥs#Ҝ4.*sO,[h! 6ƊI`GS8v=< 1r&EX[l`HkqǁVL{1SZzâ{~#ox8oIu&Bά|ylv 0}Cm;& =Z84@ ET7fCTTfiW*j$:Ne-0!seB!"hSSvmpfLu%탻%UodbHcΉ 6νBnjiV0'sw'*f(ɥ-n&#D {650Y;$59 ȕl^a~83cZb~._W"#1:zA"M@LbV>'+ɉϗ+%t/d4DV*J}fLHȘ/f9tQݬdX_xGN(>}>ZD|` 0 x^p >N2Mh}}*'G;l\bO-w+k}goVS#|2 2ܸ0o ?fà|0qpZwD|SG)}̋)$d8!O?HTHY #~ϼEgF;d#G2WȈ_vkw38x@au#.C;˧UE3Ҥ)*x:^sVŜwg~:2S#Wo2Vx9G3'2W'Y*cd3m?*W3WixDrc||m^+VXMOKF|y~cxGF<;/PDBd_ Ώ<3_?f/={۟se^v.)y:0.\ruz,> m+GJ-Me}k+q:[җh:1߅go/>-.g.YV)D,ƫ _<_{W*<:K%/&ixßu~=tpkǻ{onxybdtUOq/y@9^uG0񰱋ֺ\߿vɁ#q:x7eC,(7%:.WԔ7ƗA) ~ٿx?zO~x;rxo~CG,r¡_*ux×_Ϟ_NgO=۳ג^9^Cz- ](uׅiku׉^t0ZPBM慒^v{]K;{1^Ck>pJs^b%u>PDK %.P=PBw췖-o-[z]("j&-P Ub~Wmk&-Xj%U/oKz]^}ZAK;b)/lB'[^. 0-PҫGB %hm{8׉^Jzq^uJLҫSzݑXxpޤׅ^'ZzNyl%Gׅ^w.lCr)IR/pm ѥ^DK+I/ƞy/JD /jJYwo.^ioe hݔLׅZwl\Tkk/fuGUOq](uGlU`ڏo]([`ŏ (-nЪje*l(zܔqb7y('R8օZ*]1aC!Zꇟ":B,)ic5duLE"O.TVP/Ӆ ҅ck 8)*.b29p(+> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 21 0 obj << /Length 2433 /Filter /FlateDecode >> stream xZ[s۸~ϯe[mw&I=}-юtM)n} $Ovf\agW7PEʬTYYֳ̮_f4Z 32|/ k󷫿fFZW׳C[\%_/x_o0G~5H^ B̟mv XWjj?/l=Y3ɥITN㹑~{>'jG ~q ~~~KNS49% 6CY'ҁ_XϖYnTϖ&S'_g\x:n'#xMfU_娗n#ls2R ȋys t1=OCjeT 6;'t6_dy}$9[Nm5Gjʳ9ȳZsHKګ/ f+ڻ8cXBk }!Vپ@:A1Z4y\S1'! EUEmh{n??r2Pn7T) [kB:2!Ie)eЈp*!VAɊ;DF?6h-XC҉ip罠engG &R~0j.7ˢoÍ!;TxGc`f UgEmY{Ԟ@6ׄ1B#_q #6.2C p%a#h:f&͚FL8E0V>˦{ʨQG&wt 5x[ 9dFiT?3]w{/gt: RxM@%Fwm|Q谭N}L%90m3t6 .ϔch"JCYc*:S~S<ش`enFC4v!TUT~y'/N>M3Ӧ vsJ^*v;e'ʹ[K5:UUգ JRgLwuNPs A0p{߉—u+tST<\piE)+9M/{j7EMP P_2^e4.Xge nqG\;dM\r\Q {v`F4aYkϰ%}K$mXK˝W4I<4ۊe )<3L_aXsTl 嫩fMD~i2KYUN/CJUf$AHRk"zķq3`ؒB_uMZ,/$"y(#SEa4A=F(QP`oh GDT֪(_WBΪ̕/lJF̼2@;2!w" 9ǃx. &QDAllC &yNN!sl=tmlFi@FRk Wr,iYbWIZz)aHATRp ark12>>y6$jXB47{.9$GrԏľAG@>VnnΝ$mEN$!BPttn۞>lVuxv'45S .f& aUy`N:y¤-0*8RdCToZaoMbx2S tx}x ]1袌Y:b>9Q@gDk 5uu#:8:bBU:6BP I޺B ,Y - 䲣> ;}Fd?Bb8LKE("ܢ/u~f3m2Lؐ0~e=ҖTr/Pu1" KdAG7*lgeLĪ6imS kg3cLF]}7y\rX],:E@-%:HTW^^a'kd6M&Rc>юߤP2>$\BoqRGr|؂r3 &](ӥ*ͣ(Q`3#OMvI+OV1w_>]xsI’x0RXVV*i = s,I8!VL6- F"oi w18_H endstream endobj 26 0 obj << /Length 2102 /Filter /FlateDecode >> stream xZ[o6~5'EqEuÊa6`Zm+:9<(r.;W߼Y|qyHS\d2c2Sרэwk~u6-ooEެ[uc&`RI )˒m.J -b$qT%|&hlp?ipr":n,T%} ~^UjE5wbΔV%,MrǁVoWK)e"Vp[7Rh-ȳʩ},}X9&$ -N=OW~CZ⒳$SݓDFlm. ݴ!i,"łs%K%㩱Ȉ%8z}O+&H%{}HUT buRM[_"[gVSU=75P7/Tt2k3,mX6Yy$W+z8xa* r꯲2xzDp+QI,,/'δV@bƳf= 3I `f.blSx}kI34DCu_Zr  xP@cԁ|Ld$@q0C8$rB,>䌒)Շl(l]tmxr̾~x',ؤT[xfˇ3~EQQIZ+6ctگ 4EDo\X#,tZi[k8?5%:iPulabe}W%ںU_"q+a Bj3Ҋ8Vܚd6 !; xL!wi ㅰI#&eILd,BJ?ؼ&6H:MJrCYjK!Uyi{J7I`(lQ!j_*T)"Uد/4`# R2ѝʡbflI19½ajAеbԄZyb` əH'99Ahtzؘ7WN(E P.3r#>h-+HmJI|j꤉z:xh^H+fstR,x ?4(?hC|M`Jg&pq^%HT>J4yjQhdғAi|X0 Z^j*) (f+c,! :A֭͆tYv$TX(Eڵ\>LtQMxg2'$'۝!eIOCRִ|zs5b\gc!^n=bHjf j2籩g!=(`"%?@I$Aӝ K~UBY1%ouEu_=}muVĕ dh5J7L2r}-7s]ȸ )Rϑ'1PbFnJF& Rn6mΩ0>F][V\ӹr7[ϐ-H܁k#֝zE7G#,e 2c`8q"A[n|UZwe 웺O+È?bkL>!i]Lk"ys7]y_tgk<~ vN5{wc9C9 D!`_Rܸ|qx V595[\8&~"KMUoCNL²;#W{JңЖj]XtYcwQsD9Yuި^u܅\1j~6YE>'d}wgM&^~-ܔٟ=^qG?]|bcv:ƣM ;o1^|7B endstream endobj 29 0 obj << /Length 1627 /Filter /FlateDecode >> stream xڵYKFWp h;ުbʗ$$-Kg{fdY8e~|b-XHql$O8,ɟӿO{$N& }7<ȣϧJVRLoimOp+׏ )a8s΂;FҜ٩!Gytxcg$>"^ nKO <X'8^whL~Vo4LN.`Ҁ~:k2-Ohq{bȖ0f^kؠoϙǯj@^TJBZ T AU{M>MZePU)eEyy>JB PQ:[!FZH.vEm)Rzv{]Sipr/zO9 Z8ix3bJn+wTM ΤKdX94T|HȥUge޴iKX`Pؖ]ϫ,m%gD.J<.lf]@ëTO#%YX%WKؕdwM;(hBwz^.0-!י%cqRo>vJ>}-a̓nl tr$+w(L5^F*eHU 'aP/QaI4A~spH,sƹQ[ A}VG::f ?g3:zP?)~Ɩ4 eVՠ7RI,W瓞֎eF`h ]my`gAgѳ}@,jT "~>$R2EȐYL;ȹ BZ7Kg YG4k߂H{S- u6Q ̣U1DB0MQ\40PRUZ{ԞQR GBxH4A%2omPy6cDԡlV1|abçғ2'8שMh] jA|T CP7i/f_ݪ.9v Ձ#J ;vŎ&/hZW*9utPٰCP-i6eN0!!8c((r =m͐'vRy5#ݕXn9]P+3^qVWθ8liԊ_0%Jݨ*`ߓ-_xĂ.>pG0T-vg"~l1 ǺBECXb^UӮ̯ +M6m ɬ[3(RA n{J)t/qյ$`#fܡ&_aZ#.z+NbگO0ϷʡmMI5b7ynU(e) һws endstream endobj 32 0 obj << /Length 1693 /Filter /FlateDecode >> stream xXKs6WVi&F&ul4i:ַ3)Zf͇4c@rlEn{D o_zW0`./y,P?lqYEV]yd ]EiQjw;تYKKz٨kye.nwTvFoQ܇C׋6ק alPuVsAe5A<6gd(I>үN lpᲬVgqX*0h8蠗t gځQ,I"2WXdVb8sB9Taց˼e?h[7ƗƋ$a4uP[FVnɴhQu봾|; XgZ2;ZG.H/jZ~F5RMKw@@ \3栳]HrZII+6 7:~'ID 9lȢe6RUb"X)o1gA99J5&(WF`^qʝCC=&$3qôQp$(`)HHy>V-ODFVQ$)o`R19CE Y)uP5i)EvB0-FW-q$q[m}Ac;o8: ^J1ԽMuBfdifVBR m] JOl=okbGHgP+B.Cp%Cq!iQCW5cBkPB43$Š9?i}9:9!E7`0X ky-Z$5c#B,^U4YmpX16x*6mHC0*_?.fEoخ^:Hej:NYv]pڧ%3"b]XYug &Io u'xkM%2.L:*B|%ei4Ѐ{`h1}0Qkћ0i6{FKuKՓY$T$DHQѵi afLtyHr7W_ R!Q<1OJsETTd~X;#)r]jޤ:';aZ; i/3Cqݎΰ3[Kq02j4"c# UUcWga+w4|V]L)z gnI{m0'/x­~494U`c簳+32o? c0ݬy\"@o-abP⥷,5F߶YnfV18|*njPDA|²AG,^fNhh0)LO-\ScbnU("\g.K:-0qY2kQ.xZ I O^=:J endstream endobj 36 0 obj << /Length 1487 /Filter /FlateDecode >> stream xXrF+x$QVlW69e39 H@-鞞02XT `0uwb,Xj; ="/d^LV?ӯ(& m̜)\Y9j6ۅ>LvV׋P^Z2V<3)ԅI2^!">`x?5L"_SO S[^F<{85T&Ӻ$Ex.C;[.[9J#7#_eݥY ];ʼ?Dbp:)~6iȸZ'X_:U~&HHB+YbrzE!͒Bq2|LaWZ w+,Ή,15t|FNC岅| g6KmBW%WR\,3HlslX K`FTWKV77"|pL*=֑=;ʥ*dI% ^v٩OqE5R_mϩXia+j2,Gboigv e~a)1G-}5ԷP$ZHE2b$q'EmL-Հb!#ػцc7M&YIArRS-[8`(KTF#_}܋f9rZYqĊ d=0Ϣ`y6e[ \X{R6D&U>USL )aHM!s * SCQ $AVRNhJQ˘:WKqv 'D+\g(+g] uKAwT kYq!$+r3kYW=GNoOoSL8c7ĤYp& oGZܩygʷyFq ޠcR1+%ԁ"'ގjcT2ku +')-uĽ'hNFleÍ s8#Mh|;,#^m _`|9')?:ڣw37Q[q$3ѐ6U^S53ߵ9%Fs]ANvYʒz=/7;r0{̋8~'G=& endstream endobj 39 0 obj << /Length 1460 /Filter /FlateDecode >> stream xYM60z ZS%K"mhK+,U_pl.Ez|͐yK#1Ӆ-FqODa/s 㿗>Ld45Oݍ'~,L$ CopGŸ-\ۙpW.}<ߏ;ث}EouO$L<@"4dEx{ `6n JXu@n 'nȳFS kxz009Ue]NO3xg74mpl0ڛ4!RsO f:̫ 48~ϙ¯@NCtgD*HCv 2_0b OhUcV,TUzl3ZiC<);ɱs˜d6 OGur YM^01OxQ4"t~y^h?Y?q+u08*3 u P<:[\vƨNb|jX"[2f׆F+dX)ҫ%}J:_HѠWRZA QuհcT=|`SΩS;0|{Z1LPMͮ9PeshbCc]/(k:ؑъeK (.`5[cQX`څpInOaTꄠ#oh4OcE$нǷ@6yնViȅ\;Lpww*0w˘UɐPͻЧ mcƧ^;?铻6ڙړ^ G!lv%bڸfm6َ->fǾ(:҉ڵ^c ^xGpEa/X/;e#G$6&f'lDxǦ>d17uJѦ~wJ t&n;ٝeݾZ;\z*=<@V*D>upϟt2^:@3T{PȾ5]8/l UANN[{@ Vot6m&kuf=;&~lxK.vIp\#kW݃+!)QkHn}gy ?I3n  endstream endobj 43 0 obj << /Length 1481 /Filter /FlateDecode >> stream xXKsHW航dP)J*-FX̫ɏ/X.`fqu2'-e0YNBQdBOz͹/g=Fa4i,r⬙J͜d8UӘkK5 Jz3%72-s *ռbsn,43ƇHܾj.o6J$I4!?q#/izC> ]m" ̻.N/ev.3,)k0D==X*Y"L=%͟8ihJ}r$#H12Fs15vȠ`kMOЊ'~( Ef4U {SxF :C;(:~9 #ĢFBE4j{j^TMخ|SnȸGĹְoSg.a<4y@Cߏ`3L\)%EC{AÄ(Es0oo`3 }&=Zp%Ѯ9p..Y:qKgmSh`(4Ě?`JkX$?>ء3iO5qH)[f?4Qp>9U1P1sSRj~OyGgu]ÓXKZ=8W?;QvWP#I rɅ (L4'j6u?HBF,2FhFJ,!+Tkʁ@-q+O\? /igjHѡTQ ^a6ʄ=瑷026`LL,a1 /T!6-@b bQYR'S6K3Gr=/KBM@*V0\U IH0?MZGԽ]Ž}WOJvkLR*'%(b2),:$~(}mSKMG,&M4-z]ԵlnjX7G:6e6;R/pp6i,p6a0O'(z͚lC|)oڷC.=eȜgdd6$ eGE*ɵ#}dSWPD.h~*, 3kU( Eڌ8_cMc*"ԕDZ嗃j߷f>n_ug1i[ Xi9)a<x&)wgV1I>[5(&v|~7Xnj,0^GNr:x\B^!]Jbnήz_R }=[ԫ}_ڏ!zyP< JěQKܦ]U;HKlrO*sZWH9ݱfwx'F!ڎ\ĺ-Yh$ؤv.9dFS똍 #ҋ٧`5 endstream endobj 47 0 obj << /Length 2436 /Filter /FlateDecode >> stream xڵYYo~_!"6ugE%:xsve5}.|g_?|P8 4WYẙ"ݯf"(|$Iҗ gU(*ŢB饓ֹ"͋A_[~\SkzOp6pǛf}R\*@vOcŸp(ӌe Q`O(}/PR6<}8뛥-ur6ϴ 떰)"4K$*5F Ht5\BF-$ʎ=9cC[9-8LB iH鉴H0hJ|}YFz%k/yFE"]R=Tr"[zZ5L}\u{zσd#رcz!pT@?Ec 5x!tr=Xrt~߭{Iopǃp@ftBn5; HfiJqǰ #~p\c45z5T>c\@IV '`N^(Oߖ~J$mzRwJLJEk*_zJG7Okz >m398$cj>lصxz#Ozu ݊Ph4s'k nT} j42"F=4AQL{Q3(M_)-B/WXMbXZ,$p3VU@8Gm \@J׃$ c!Uо tO uaȲ&44![xqBXI:֫솺sWP3FXUc";u`S(jZfUI"ٵVdEF Fib5'~:NRfy~0 /)9R`vZ0Q{&D)Jl$').-GiI{vn, v(`J/TyXi6Il/+Xm-3/QN(o>y=5L0Qq L#Mn{}` p]vӈz.QTF 5r ӏ8x!!G/{ܿP\eʒ±r8,JjW}!E=InHQ66_&M=$C+>DY o8rep@|;{1/OX4/uG go=bM2zCFWj?{)]wrxµ9z'V0JeEHo-Z&ox{҅il +jA|pmB5(e8o?,AP?1L ~L_22|!b13aϴWL+u%WurqdhJ)Ύzd1jjIXY"g& ‚tkh DLȢm)PM9AmZ.TXV(N%J= e{""fj}gcn>'-G>ry^4vPk+"uP$xs%Wö %$ٞCb-+5pgyuױWO iIV6dnӴ<<$0VZX5 Ѯ;\O梯Yx[Gq7 ypšc#SšOWI0'6ݟ}=Al)ʸܖ&~(EpNr9avjZ~B'Խݠ%^87d0 lRgۘtk# ֶsY79>UxeFND c*xc'cƯ-q(R+}e_o/ͷ=o!kL4L~8;9WyLYShTaYrWW>B1 endstream endobj 50 0 obj << /Length 2551 /Filter /FlateDecode >> stream xZIo0r⚜f2H \AʒڒRίOR%(m{^?|4NJ'U,ߣ/"M&x^[}[]BI렯Z}}fI4d+}mS.O1-5<ѬROQwQ_GjO'K5=T vMs E-By_ ۑ0|W}pl.pC3q[w<؊8xI4x8XC @q؜<ƒ=CE:҅<gFW klE1SkDHzi-4B9"7Zx+$2N`U M=EEgNgk[ H6>BÂny9i;s{ӆhyNBAIASFQuNVn@LSYMpFf̲B[1,0D by\ԓq%[ЗOK^GÌ?se2 3AdZYP{Z-_m({RvCB:4瞟5Zy /ǰo #C.$\j!!ݎ. X6Dp¨ЬA{(:zh@a"CjnnVYSTi,:Xc~ŠM_ \i jvrO]Nsnh6Q/?a8pwG)r!_j= Yȁᾼώqkx=j,~}%=GdD;“q=!Ÿ-'FSBkcbKun8RaXm̒_ՃnՄӄ@4'5_֒,Bqqs?^bGAhn샹φn76Lp]Ԅ"qQMYg @>F&^{|8 W-%olsTes܍ѱP.7+ߑO+PG[^U왡z 7a,XbOdF?黚yQ؀g( SͩH~ U5ûzE˺=BQa pZ<"Jo^nSªW9K;ZB'I'4ޝG9!9XGOi旫SL/EJ4/R9ۚ 0 +CSzׅq{y{8:k'"|j9rE'>Bdq]׸Ɇyُ+]гnlq<[K*}$GBp#Pn)TtɄ뵰FlvA9 Xĕ`MdC4s#Vl/Xr4hB[5=F-hoZ2ׄSKeI+[6sܖnr Pc 5'+]tí~Όv+/0*)GBiex ƲNo?_;M{oi;\=D~pd_S[uv-h i%G*a]UMOze.omиHuSrY'P6rY96R?y%'I`pUGMM{tbs*pxeC!qr4#p +y+_8&+UB+'bTO K=5JݖΓquʣ?h,ՎL-`WupNbjp@o3gYP}m9覸$5G^Q v}0sPӧfpkXr=$-bdk~X*8wpM&:|ID4E͈s(OBcfwde<-Ⲕxi07mqᢴ- c3.qQDeρ˳a+!4^լPtKBKMpv (ZRp{>^n_sݷZFM)LWWP/S5/)n}.eؽ4ަa+,_R־0UgR^~7չ[p5s?"[Pfb~4)Mw=`m]SݠR+MBX/S 9Μ9ǒu,3qM{ڻ>򻧝h̔!צ!OT>w3T'Y %=\S~υFC=;T)M8QFzCyLe'YuT Wp.0q#կpw O*NNEglK;pXٜ" \eBW$ѤP6ml=kUtas3W#?=gOsC83x\4HZKn;T!rsƹ>: #2^mjI".kn's|$.+K\ zLڈÇFg endstream endobj 53 0 obj << /Length 2303 /Filter /FlateDecode >> stream xZIFW-4;\oLS90R{F$fׯkh`;#{;͓goJ~UAOGYzu{`OdpgU{mf+õk.I}z0?kCpy{|‚}>g^`w5v6 XIZoq=H]}m% z8q8j.On"? {u`{Wωyb/>#'.lE(b.pb|6d{DaR?6#h1mgH |y ԓKP\ ȩ,/%.aȽn4X=ưf5BRuаgA , n IH9L6j_qRZnPķJ` Ѓ.N%p/ ?)*E+[&84~<1&pF͡D]>(*H~iA$oW҆5 oG>AZhb6U[84 N ׷E z0lÍ!S:腹}4cDrK5~SՃJް$r;@-RZhGU5 |ɩKn#0 7XŸ'HPl& hjPG{$sBB* v3V#/+!m %=kU++k' gq$z^2$Gч"=Sԃ̶8>Y/ڈ9ۖ iOc -elYמ %S`~'I9 My9ŮyKU[>J 垭=x+Dn5B"'1'M:Cж5Z+v(RcvʨCV7riewn !ϒ|c[Y|-ߍ^c7t܁fgmCV,Fc ~mpG{uIiTU5*)^r~@l.&\ۜER~v ّn#f"+I㴀(d…<(_1I04eAωmHq-I8pNw_iD'GD B׏v=&L7cv}2Fę;OGN&(V,[V@8x \I7,-JTԣ?!i6dC{0t~I&d:.)I"6'Z~ZJ(`AUC2?+R8FQwj/]j%Â}N9NP`;ϴ՘#BǠ Яz9_;|>LFGޒa1&A%{zMҸJE6A)!E+aгi @ ?s1y &mQG-NgV>r^VF_~]c_9r+07)9_4(3mzu]hA|)1v,* MɾozFH1۲AȻ%iah;-biJ띈ի9$/'jH+-ڝD"qJQ;޳`T0FTS~#mPS0z)TrVg 4!ޚF=NJ_xNٓ2Ӣku"E\H\Ebzp2TN՜iP:f'Kmqh`/ij3uK<;t,<A+q9WZ9w@6NxAkg.*otVd?\IJ:N=7_H=mNMs8R>Vahˑ{6-Lf2Ӭx4?f*:kWsG7"`VL}7kOι(Q)!84 CE08VaaaρCR.˝%AdRj~һ:RFQ-wǿbٙkV2"kW^Xn sGV ei2FP\#6ڥ^[V| GbHb#jYx%-N tҎ5ȯS(y{9HG ˴nR\`ݚ#9ߏ*iߵYV}ર> stream xڵZK۸WQSea $=NeIjrs9Ҍ]i=f|D`v&ȣ\?dߋJF٠5V.U٫Wk=o<7$LH$" vDHUe Ğoeţ=8% >4ةtLcR'gp_t ( ,ZSW0ϋib{R6N szyr4K͒_X$:G) x<}t=Vmc!1Xw|~,6$>hǐjȒ}Qrlj=]?GEw_޺e4ݛ~<M} _,+wzק)b-TnTzM/otQԸŸsEɴOy*S6<6-ހ)lƤ UZ9DHWȬ#BjPR9m7%$2Gj)C2'ksBHe;0h᭶V6V$Di5"HjD5XkwZ t~j$i~@JVD"R6',8el+Z$ok,۪1|oYta+%] 3ZBj =`Z$[T-N[JJRt@ GGcˢaC_:#k@n*LLN.` }iufԴL`ۯӆ7bzm b5 Ej _Km!6%&V٫$>g@~obO<{"_B',Шlg!*2];!:~ @v^CS= 2<X& pψ@(A@ݜl@ҩӏVVb:8Z AW[zjN\$ROFA:vmq(tIֺ  Q, ~Ûx"- Bf*~}r.u;-l>G2eEkm| WNU"K#]d:iٔvmHo0b@_)H^s>$%yweZRwa{ ϩx'݌I]#WN&4U6沛 AnZdjnM;<ȍA SNWxҊ= lA#-\O'.Gc|qyϊXƨk |oՆ2R=A!K 6Ӛ+@S|%y~ͬg8n$w\)i1.b?snC{64Ϋ~Acf0ߧb-RSYةG,l`#32&X'˳/3a###OZL}!Hk˳'$n0"â&5d+Ś*T8{hڕný}QqiBסb W$0:H +Z6ɷY}eq +FKf6j# &ty9p}ZNIq=PeZ'Ō[`rN9֚(8J.h\,2J"2ExaAݪ$k#Έ(I_3rI,̦ʆB#!=p ;?[ٶn ZmCڲÞC,Jb(G¿;S w}M +Sn7$lMȱ],cw:b Ȃm_:C)ٟ$M_U+JM;>R"5BJ4~_V}5z~;־1ciqFbЙ~ͮvɩmGPRCbKtbA6Ǧ*LUuڛ"(B"X#E"PJԾ'T#:bC[s˪%xBPQպ"#ܖ[dŒ:Pw;Ѣl8FCoPZ2R]E!*Ȋ>sm0y`[Q7Y=C}D>V(zޔl:3eC@XC\MT~f`W:膳O vf&>cKC!LE߉>=0*D2T0^+MbX.Le"650 VOB} r ;uN{X Dđ?t܃t9;= l'mG7iukJ&۝`hhZK!)߬ _z ^[*UבU^Z†*i5XOo`R~UNV6q֎=l$`.3889W%XM tC/>M"Hh$&fMLu<`߸> stream xZKϯhs%46䠶nؒcHtALRb=*]2,](O<|Q8_֚"/BZD\Ks5ڙKke=}'2pɤXa2M(Pk&@Zd'haz]x˶<o{d`SMNW3TmLP{=&™ÁGHTj4֣O2Ve? (e`IM\ Mciw(ViRd1q0&'iT0 ܷQsh4S*567#ku", _kJcQv $~P-h숧^[Y0QSVZBE4X)w$vA3ت:ebK`~,~]i"ae(sDz\ZJk6<9̏^M<|Q=tdRZ3|EfͼW >sZ Ǒ_uJ= /O͖ CɣIGvRjQ>;(GW gB~Y@q!fW#A;e$t1Zt(XS+ [T|(dp< y,Sۇޒ0x ihd^(eÆi&F±ێ-@cރ–,Y^ /y0O}b^#wFb/6&6g{N%՞:SOli=]k>5_da|B{DHolڨmn80 j#[h1JPWLtahnF 䰺! L&Y!AX ֤GdBIǦdaIh%4LA5k=ي~aۊ0,/7[ }lL)4s=rsUv!AJkVqqH5<i$c]8)zt*J]lFhi$uTX颵Pa3Dfj\ "w a!<҉?#'  椔\"նe#y(t=\p ƺVRddI;F\O#N!ˌ?e$64g[W)PqU o=~MF, A|wiP}j؋9.ZFR8Z֬~Grp:l7Q\gMZMJX@@vCe!u$jyCPǷD_F)'S-4RI=Ý}qHC|F9Hsń10p{@(k e#QqN!F 8CAE)f䔨>2iq,|- 'Yp. [2$4OY2nDŷA?mo4_.K- .oa V룾 n15H!W Thbzޑr.eNxV,GgH&omn}-BuXwՈ{^;d*) ߫{NsiŢbIZ-<ryвk#7^@T5̌bS߸ac\pdn)( ~+[ʶ#]|/?gnG(\lޯMyh[ih^٠ba^?5Ak=/9/6<0td 3(O8U,D2>Kd vdZ^TsɣDoT:Zȧ`ov}9Hm#OZ2譏Ȭd; њ}v{T/c$.9Rwuk D\Yn#5tTkFAez%) t_7Xޓ5^%م4BWK&A?8F L F'~ock7JrZZ?tbtmkilЮ/ x= AGYxNr q.p1R(K.jEpɌt4ĝMUIbȯ lTÇ5 HtU ]SZGzNVGxH|t>Vwl#w~Èl(0#-_3WX_'Rt.T\D> stream xZKϯQhBv2oc;;ABtϿ߬,H44-PdV~һ7| mȊf8 C'g7i[t}$dIxpb93V #\$i>&jq!CEWm~%>.B1ՍH?+iwp/`zp?J?ДqaN/(|@-Iύ$85g!ljlIjXJ)\DeHLb/_(Te*]ךWNc %H%=M04'|Ԛ%|~[6X&zDc}[81ӓT |$ړHU უ}T>1 * ti5]$3JeO` w'2- ۙ\(#lw "%gX92г~i[{$σCU #ǝlH^0 P{:bIm puT /(۞ KarnO)"9E⯤NcaL%L6 5@Xۇh>^ l~JxD`'֮=(b NVU,ߞ$Y4k2e[5ߠaٔcBZN'!Rh(prt`pRodHe waO 0񾵁ޘAV T{&bgbMe|mSs7gg.aKw3ke|>KLEUddwMn9~fԭ] fQ?uy^1~!c[ca2ҹQ`[!ajG^&X<Qn W>/Yq(n-{c~Z()]7uP[Z8Ag貤ft~G=Vik,v<6{+J-Bi71dAgʤw<OYWv´ 5dXjE:4SZmO^@ Y?M;#"Ϟ:HK*{M7\>j5ݮJcp}lMduo_q~%U{;x41PDA4ko! .{hj=ltEoiz 0OI jF1_-LiO zkqU9Gմ! 8CST mEc*V~]5PodžeՐ}CR)~jj۹@JHbs&Wo 0cksj'G]CikN1\! vK6fjWN^/ie^S:t"t!pVn76<~No*fZԄJ(BXYIQEݩ7WΘn=<^}5:Jid[lϬIMx(.%D~`he!DC} R_)`1Ie}8rqߚ`}d&_ZŘLZT6k@b9۬tgco+ I1N2澍#~?7"{u su5rQ)&JƸ~͊V:=n&bxjMo}l,{O$!)C5MtUw6d05#B3a w7'G1hڰYg&f6LAxf{v&@Fb:}}FS5}BFv8 1' gIO?ΘT.&ƍp$6\ol}@L{ 3ľvOZYhݽ\Ӧd>TG~qHTA0,OvaٛoV endstream endobj 66 0 obj << /Length 2269 /Filter /FlateDecode >> stream xZ͏۶0z1+|m^EŖwݕlf}gCR$hуZ g~A}<\Pa!ED }!o?~6ͅ<\\wp*p|m4(wɥHԐ2Ut7Q<ͶAR)ŜaԲ>5E~ۃy'5.O*ޡwךnQyiӋk"2D"k\_OAq"2e~c c/C?LG;!DfOs=Z[Zѻ d+p $* @ ,fY6|Tc2!x ŬKmP͋ ̳L DLCI%_O!P(Y,R$q!C?iw| ik]RZ8C"}o$c2Ix$Au;_؝|-wd>0Op[U܄-SO"Eg3Mbceg҈;|MJ+|7@!-= XvTq{sUGű$)E+;He95o(f`|Qqj2Y ~.2M]i+xP8yYe]Mϔ~8/7LdEIj]H2`KQ/z7j\ew<ɗqO8pwT_4m3ɱ;U†wg5P1!lm G5c{N v\l^Gz?ّX s׻;n$g5IܛDdmE"d_/Dѥ.B]%;HֵK;-l mzaڛXA-ފ_peG)Y-x z!QɔȒ|fLgTg=8qyo: V8QK탸13,m~(~;'kPv5/猑dwOoigrD"e+NJL jٵ]?dm0 Q 8D[wv#y"{7_V0_j*)wj*bW)>=ǽ'LwNjCu%iP0Pj/jf=3vxZz{Vۓ˫=9Y6vEGZg5![#;NU/bܼ*,ySWN>NΔUi`ŷqs-ǣX#xSV!EV$i'&ͥEX|zwzƓY$$ _OLDg2KE's5`p#%I`ℷ,XݕU#+4ȹa/i<'Hdn=Q9dMaFWbWS&3~YG!u1SɸD`!y[y,mֲu6G^ԆnsG=:QB+<]>}>is^!PNA3yTy| YDv٫ ˴5R%1YK㏍IQP045`ٶ:V*H} ݚpM־[O͉7;#m]oOoP3a_'35^*MX EnUXQ 4jgpܝt9_؏XGQyp~4W[u\'HlpZvr[%jݏxsmkјB_ț"'>q}9Gv͑^j\꽝LZz՗rkx+ʪ,XKR:ұZ`th%3VM?86pb[7nD3@bD9ߕfNd'#.<J7 C4"&<Eiؖ(c"/O=i4bWb7" )dffM}{Xg2_S\;xπ?NϮ;omutqռ~L|`pOd[sjl͙Y :~ܯv(d!焇919̡t@@е- Zã7flfkyyş9`1T>^<:*R4RIQe^p/}C endstream endobj 69 0 obj << /Length 2792 /Filter /FlateDecode >> stream xZIwϯopN$aL2G$(TWW/"HU>}$+"*lq I <ͯLUM"^ [$>j>D!yeOHK˽gq72{M-9+ETuԐ=^"?P`+un-Hg[%5 glL-sJD#q +di$`%vJ0Vr1ʥ]_wiwڡ3jQum¾S 2qn4cЗp0jF,cp}4 IHcD6W$ /3O~ڬ5"c1ӢKKx6Y(SXD[ϒz׵"wvEE&j5ݙSԺk& &]w̵KP@0ԦejD`bnj;w9R3`L/-!;߷a֫Gd)dvfeha &.<RN~FгJi0BKXb\f;jĹېBF٤MWV>pAJ L4,I ŋ8ƷN@ϝU4ESrJ/ M+IC rTƲMYntO2&"+o'O> stream xZKs6ϯQ HrxgRM*+9dr%VF+>x4Z$Gm"Ѝۛ7_ϣ Htrs7\rcLٟ7}+n,DÌNWZs$I27y \jP53Ʀ[l xw$M#Y&28أW)fn6V'~:)#J3UQٜ9$(+ TsIBRrn&H%\12`$4sp,!+a5zWm k#iRb# +rrE;QQqҰvxvx2996#5]>۔r+alPh% d6O! $p3MA^*\?X?g&F[\7 ejcD!\ %WըaPM[7G4px: iēFRSrD|LdJE Cfc0j늦+kݹI.j^QL,W?qd6ii͚::IIcG*c0Iit:hj{N/fu0UT@‚ b$!!_xrFXQ̓(8+h#@faWנu8/ȉWğny_Xm`W棝M\#BG?EU)q^N!i$AJ *_%drPs9{.{]@<(  VaQq#)yf\_)N[.A'bk@(@A*r~ sDiMKyϰqjJκrQrmy5\&ĶՋꇘjY3U)˺qqĄ\e]9EuXRmU6E\Eר;i\w?}wбEO+S[^~W_"7I ID+;?+h},إj#'"+V^uv@|p(.Jcs,ER 4Й )pTQ QbtmL`x-~חʣv /̣>vij} eLV"DT`iEjAzEF* ׋*WʐٯRבֿ5Yc?>]Ό2::Z::g cΎΎ ,, {&͂LR6ȌLKNw?Ҟ\$ޣ &O}1 kzDU!YR:Y^-PkOä GtRA!w,6 JCݙ9 Z0Kϲ [tcΥrKk!u4{qBF\(j.vEzHУ,v :.NjQ%ޏ!eqp8V{s)&R\-yڴ[{>rW=9yM:mv@O4wwwJxw3;f~-8}NPP¶!4m5=2Rp޿Eܜ~͢69ؔ/u4|xb|U~{-=q65 <|PiCDxo@GݸP RE:\[v>,j}$PD8iR6s`q&UW޷G6;[BֿVv#*1ꪴr ,&/-Eqqh]+#iE8ilr1AKAnNtP;?y뷋$DEZCd^Rw_9?a,^[~\Dub}`& Җ٠3)JJy8bguPN3YB!k4?yw-P endstream endobj 75 0 obj << /Length 2308 /Filter /FlateDecode >> stream xZKsWT5xػ\*8)&HI@=_{|:z,Wų8 f+ۙKn\\G ^+xM?Sk'õf%?wbO:,>',$oO3M;+ AoT44m{Q*f2Niv7~@ZJEܰ@rܨ-laYx”B4$PI-X! /vT\(À|6MġxPD/D8!#T$`X5ZMfFkfe!|kL@~`{oA9Q;%sE#?j%z"G]ڋ|F|&U(@>O}z%|mED*ə$7?ujdFݼˆQ4ah۰`,7[6A&hؔa#0]x{#Un.+alMvdxVWZ|³(H|'f-Qu~mHA˼z!VԆv :v`)ds,&7SQ8M("[!ENXǣS/Vh-eMkqy2e]BN+ӻT/jŒb~b`WەÀOPA V%Pk{YȮsU{ 4M`}jU`^jk `(0Y쭺9Ԝ]ES2U ~u:|7ݬ {Z0S|eR"0Sh<=nzFsjá][uf 5QY\LtM"6k23ucACD?qO_'0$5kG251LdRNK~Ä>o:MIc;(kzpz[]@t# m_M\'-9?L'?<̖&1wlp:)I[mMKLuʚbzdԬ82&/MM/(|m{DWCay;8:ީoĴ`r9g?Tej+}S;HwZ25/uU6[eM6vӳ4Ia=Ś梭oIS끄Kf#%^Bad l,4_䎴Yp[AE/Y'`-r6%=YR(i_&PQ'f16@;m%ؠ[6cNksLe'%}1z`m^B+a}/uTܴPZqV%QI"ճ. #,5qޱط$^丁o8pzՀZ/N)Q(ţ{4&-X2OqIټo\ڦ&1jLBѨ(0Q$f|lX @7'6A:L/EmH@wpz 0bO@Uk|%İ+iF3)ʼnv8;KЖX;׳ Nb> stream xZIQIN2L2CK:7Xv-ȟHI6U{9$S}|?\|sa&:S6jrWvRB"\,&JLi|d?7pԗә).K3DZtfIV8mSS&75\7ȿ/gSNt(A:ǖ_=<˖5Ϸ;˰ xCd5 xYB=-78'v5߹#ӂps3E{ܢ' ,'x.baZfbci:Wr`\ETE jAy%VSr7⮥<KUk?o3WōW{:*:tsk(=rǣ;6 j<^Nho5׆|=As_|}wp\\NƿawÝ%4 5Dיekagiq˚.l5 ʔS'~s6K8gwit߰(4SӏuO.:[rbHO4h͒AuD83e ݪTڅKy#e,dKr5v]4nªbF8#f'ֹ̩%?]a2 bU฀ E"L")fiK]zw!CmZ?b]rǎ]tA^diʕf$q;jJ!x&"ٷ<5uQ#̴Os/8\YsǾ t)2h,8Irc6#ޟ4B80P-zy')r74ҿDSԋ!/ @xOV-ɞ>vÀhXl!G)xm62/ C{)2U"73$:"+{+\ V CtlAtFh|d62XjM8UrP8ŨD =FMmW-Ja I.*|vڥ+t}9j*Kr0CY |[I| ^DْPӂr<͙DY F?Nf-[ Y5WRV; *~^pWg2GG|-=sY3Er/nV)Sr2aJiغKIJR 1c.}#L'zա1tZeû?ڜގ ~ $x$_MbJei?1TY9{8; S=cQv LR+]}]4iSBU6,Jh ϸrњv4J՝{mz/,|MM{(3@~'r߿aK Dy}o7~ HfAgDTӪ<c/Uo>=,?<]iF.3ɜj@q'9q2OhZ8W/&>>L*Fp[}UCFG0*ޱZf, @eM[9HG[ fUƖ/|X|W6 T{ ~7_`уbWŃGf*<ٰ1ҙvf ltM~˧L0M9L8 ŚR]c:X DFRSkz`d"̙+{^lNX:'=kr7!4=)FG m>.^mL{[@+_f0ZfMMܡ6|iD [ -ц0a>JwI>w qa^2'#cִrG#{w04@iNq#/  h\ .D\л:-8k80~pG`+|6]%z> Y7^A/&_nj$Xv-Ҟ~~} l]~B|,v/).0N?J˓j{._X6 i]8M]{fݢ'6[ӽo~k7W<яt˼|9TƹU>'v6_#O>ثN4`: LɿX }S endstream endobj 82 0 obj << /Length 2339 /Filter /FlateDecode >> stream xڵZKϯ09+>$,va$Բm=ϧ*Lu=zW_={xe63᳇,+Ka5}g=xNK]2|Zyc = Op eL/bJ9b)s9pkB!!iY0_K_$.SmO,@H.{kxDo[w+KF%'zZ$sO(-/4i^{)=nxRΖB=[rre}*g !$/`"Ȟ!L9y"t0AZ4֋~8MPLL:Qrhtz 몣O>Hͅh_12Y.4ѻ"cWFӔs0BTk+8b0E+d/dU/I$;d40cn!mk"䠎.bo~|66T6W(^+2Ip]2YAJ[pp I"aASx(srKe22jQ~+yuUH57leδ_.6`E!H.fȖX{7 V z<1eS'ч+2cY6!TԄ!U(i7%r婣[Ϲ&,8|u3`7A 0y)r#hKYġ>dYH\~A޶`B֛OBA HNrHY9TRzf; tJWKr>.GުJH؁K%ʁ+V*:ML9`ΑѫNS,?,b^2%+k1֊ꨢٷ&+3pdʭQVQwSAvRR\~e,zTjڨ&hBĶsU0nvp&>sto\Oց &QJXՏ^_]ZFsECzf3q4 bRQPwBߜ߇Cq@AK{.Lx:~JOZűdC_ P op4ѭl jFnubn{$44q=U|zu\U7ݽs`f +{0 B3np}{I){6I*PP#(dZFU5|9,H@nɭǛc6G#/~t5SطW[VyugT.ʘ m6SRV'?]M59e Ş@&LvKP%2.j1@x2ta3~$p^Qʡ'\E=ÊvarӲ۔Z s[liL]#jc&j۠("mqD}Gj.bqd8cb>=~"Mn wCә֭#mӍMfOnXecdFV\Aahp Cdn*N3ǔݠߜ?>-xZ3ԡi.'wR endstream endobj 85 0 obj << /Length 2222 /Filter /FlateDecode >> stream xڽZo6"x'hX(i=} ,{XdCۃb+[Y2$9yp8CQIڃb}Pp>~Q~/E|#cQƥ"%_|6N[5ppUÕx_n4]?%IU=1/VZBnatɨ&t U:I2LK9Uy֟pTpQ% @ɜ̘_X[JHb>jQh8J;@?p7[\վ#ǗX8Ӑڍ՝8|1Dn hcy`z YZN@êD\%8y,&9ͣ^v#s1NcɃIfAcQv٘S-4DJЫ R[ @Nk띑nXH`8&P-i,95KG6ўڃ0TGOx8s NМ.v/iC5|O;W;f|6RVtw!Kqz$mt6|VF[p~rAѦ͈m4ͫpt{&nJ^YWV'hL7&>S1yQ 11ƌP8̟z#vJCx2X5}7|ז\"LXRdBoCC5^qzτeC5찝ǹB8f/ #1Q|0zwB*|Q*2z:8'Yz1e*@Ϊ%3MkPJ"] Xn흽 W3(ӡHѹLxXK̭.7ӯtEV؆ !늧'yo !wȍ]$HL UNjmKIujE=7VѩomϬͯ5\,gm…M ׯdܴ!؅R c348VaVm4.0pt/+p;6(y.¥qQID˷zŚ,.x|FV͜+<=MN>8]~/e6;n.0Ojn~}xw={vizBƒi! rK0T-Rlj>@d a@_>ujNRhkDS&OI2D2~v(٥eЉ*E}e9-6^0DQ=71Do;Wy?VnA筵a|)pZx[{װ o|R(%z9񰇁9XIةش\jH^J_mn<֝?cn~CjE9Q2d[gb_O `Y YwVnkKp9 6ƹR;ev6{}$۠"%f9f3\c]+(&+R%/Y#r4=]4Nz`kX/9t.v-ЭBWt#…نzY=~u/eE?~O X6&:6qi}d6W~ڸ ;BOk+0CPwHOܸImWiqKxݹ٧?_ endstream endobj 88 0 obj << /Length 2295 /Filter /FlateDecode >> stream xZrWf%WY 0$T]ns)E{|H-?&dADuts~~gS\E/o.d1fRWM> ^\?~\m. 7kv'+pjkKw.+L)X!²]NRN~i/RIcYOLθQ~ gKGGx;BܿܔTQS53B@0?/{۹b*_|zhc(+*IAKVsCZLx!f~oZ+ɞ={o92wdmxU]y=)[VTћUP>Bܭ Xo{gfbʔ0Ll~b[A5]Sn R40({3aXP;wC'Hq3]X9xAas*JV\9iNY(; ]Ǡ:g``K0 }w*6w`JH{7y~Q+T>CmvL|䑢?D& D ٝZ9a;БlaEZ,rXG%GVyx!( .+ dPn,07?le\ufeF]'>/z%mIx%Xo n9)HJ%Kn &-i9~[4cT_:? ͜6n&ㄣ"Ha\O>=ӽ[|kjEm:RPZ00~=0b>B)âې̎cx9n7Zkx@G)ZQHyw?J^ u]9W\$Qv>4Ӷzft "ǀ .^8flV! UsǙ.Z(J?mH{g/<;fa/D. `tDž㴍g{^QMfvr%WYa/P\ Ij}"fz] #~ӔSQ$A#*@q+^ݨ6#׷a4,HM1Ć^hܼ0FS,^p2gT:Sc݃ (;ihQi46~Czܻ D %+ȇ]ݚτވ'1 &},Xsc8uZ't+ _?l<^2zrcP Ci>%j}8QuyӤztiKD֟+">`!I̲ EJjnt"9 ++zʷv먹ؿ+1bJJLY]ˬ @ys&on]1khOYڣavڌVU=uZ햧jgv)a V,xK rm0|gXL_ r8uCNO8E,h'!rGZ6p]f}۟TRsҳOC᷃^Edo<#d . zLC)I?fH]R:l렺|}L7PiblBo}?M8FVK!㌸>a&B÷`|5vKVr _UŊxEFc_kf@;R;՛RWf.~ʈ'bZo]7ݘ{4R3@+t}YG (th-!wn;qA}YJ@joHhwDlN 5I0x- Aa/ܷceߚMQx`3n6J6|O#Jq İJrYO˥;M+ /6+O`+NP`P4 xmv>yqۼ endstream endobj 91 0 obj << /Length 2589 /Filter /FlateDecode >> stream xڽZKW XDX;@`o6@|"8@8"%rV<;ȟOUu)7ei<#~}Uգw~zWD7:ReT꛻M('Wq7}0:z"/n"U}g p-Rpj<5l\B#>kҵn& ψvLxi  Q&p!H}WF'Q9 5ױJq^uf@JYҟyd*R:`V{<̪pCael@sc=t)wP`(φTwlUքNa:0x!ԨuMG!}9 Zg $7Jg- ,,̶%#HKIPsXXg;btF3۰tfjK5Rɞ jh/GĨ@rաv~{4#]Je#H٬Y\>D:+*A: G1]jQ]rc=T(g{JCˣa l' N726Zi:f"ZY%cX2.9iӵVNXYהMJz̊Rg}lvuGkx -Ǒ _h@MIߓIՖNYZ&EGtJ+"Zh(S k%ȑuvϮarNd't5&IW{8r_&=we4<~c2ф Ɇtq)尽g18mx@6׻wEDSWRB75ދ Z E:תԃ)gI+t0TKhbGM.+Fjlǵ؄JxG/زˠ$b!\&y3K?.U+Pkn034*dx9>ұ/v׈~Yux*/"5LٽU.C&@G"ɿ`  VQJ&r=pp곗K)l]͛N0Sm^89vY fՇ 4T(+^ ieBbuY藑QDȞ d7R{Aye0G?6IBL* ^EV*\±VAA?! ɋ+ 4"?Vć`e _Z&U_jHe*bfbl|* endstream endobj 94 0 obj << /Length 2037 /Filter /FlateDecode >> stream xZIW>q^/䐗H $RcBIKa1񸆢EzD%qr̞"ۻ%`@Đ,%iTz(=F !N_5LUnzٍc|i4K=yz-A^ ^6EU+I?.*'CNvN2w1d.GlC 4:>:O6<$λь_y,@ fLǁVeT.2 X@ӌ@Jt7RbY#j7E UNczJSDbܷݔ*lƘXQFp"4q\2zv"&g++¥+$YMۄ`=kA(T3@%Gr!( UeFn&}WUN':&U=;[qÐեiП;#lȷ:xy?)Ѩ*Mn#L#m}wC-ǽ=!ZJgSq)/_lHRf3E;I h٢J ?nw- O,.JٳE&9 ./Jqr 6O mTdAzQKd}-{Lq@Y S@>x'k9yI"Uڣ+MI"<8ptǽgqSsɖ]1g Lf`}\tHr)PS\@~v2z _72H ѓMP>T*&,w Y_ɉ lěIc^{[|1q̖"?c{/ŋw7*}6ITk9? [!$_lFϔSpA>}sd-1E|ZO碽_!"joO*VehRԹoԽeH+p7E lObY2+BwM% (u{^_ʢUp#6)u)7f(Gy1q~r-9,rعHkQggHrv@4pX'.1W/M\ FrG%%_̔$:U:6MT2s{ EhN}b 1~wh;WLXEv{]@Q8lk㥠jsNjj9)=ߙ48=f%7p((Wo_奬 endstream endobj 97 0 obj << /Length 2210 /Filter /FlateDecode >> stream xڽZIFW4rZ 0a \҃ ΁-%#JVyKU.j%X˫|o)͏s Q&|x|~(sCsq?QaG}H˯a|ÇopMبRVM:^Z)T;󨍹t} cU_fJI)AA-_|t6GҫY:8&39Slu9Zw-c58t JWhN[R"l{+PG tg7 @e>y z-[I!4Ms!3}ǀ2BH:Qz`eO̦Ne Ѿ =(q# .a #aD,0PbQ~ͥSzȀsLm6$ufG=ƦsU>8ɍZ#^u9z<{z J->!!u _*³h酇wF5AN5Hs"sIAl>|\*ygHZY.OB𞂂/u<ǥE*އQ.$.pu A'=g'̄)kCun-x?S8p.~xځE;ŕBquRdWWֆ!L}.1PRjێ:JO*.k}כ* R/K76΋T;vDNlVXOZ~p<惛@,BC̬!:srk6Jb!r^GɌP4a1 l'T כLSod 8΋(P616YAو[O†k.n] !.6NvRx 2B,cp <̂jq!fU*+UzpY9+=(Jt^lbc*߸`!J325%a1ѾwB63jiˆBÂKZZ0,Z4sj|_qpd]!b\+G[B0J/_2BtXZ+raɋtHg^`1/%ՈG>a.o*|>,r}زs[+ƒ.K9[*ʾ n|%?@,lʖ0wf_֟(:խ ȇ4, /4 :.7\Uf*yz 0-ݣ2~l#54w۾? <Ŋ܇'Ϩ]xTOݫͩ ˕k=K,Hj"Ajq:c0pBj঳hcv|Q-)^ uUUWA1R}91}B}>r'f-/n̔"vH4Vw?>mfK? ~P<R+Hl~C6sDG_`Pן<]$0G(]^|saU xBhC @߽L endstream endobj 101 0 obj << /Length 2146 /Filter /FlateDecode >> stream xYY6~ϯX Čx`HlyHH$Zk;Zep8]Wd9>|HxtY.YRʙ̳;=;cȋĎ8< xiIńn}O+pPp&ނ %bOr=\133=&lg3o6bpe &fi}k<7~ +h6𳲭WК Ʀܘ465C#nonzP(׈C3̴ݼ\M7c6]#s-53ZȒm#<ߑܜmdzȔ< "%V$q)< mLj}vph\|>D&\1@)R\3y>XSyMЯ/nOOI!I$p[$*  }HIsL)6QhahX!NaRu f5]5dCqx4鹯Q^LE;87v _tuJ>-sP*~ψ;G.]^}v;!b #})o'$޳E :>"XùؤpRRֿ+!cA ں:ԗjLoLV5sз9 ¢&(U6čSn[۴[^0xQ^iu|A!c4 gG$|,l^Q.BA/mmG:=fВc {|?O{wQz|*Y²Trº>b XZ91hu0d^kq1O,ITtYBLSz_Cnl;ƞB {LܵQI&dK'<#k 76cYJX3Œj$+fߔ}L`cPh L%n̄,3 +o%{ExeEƸ;AȖha+|`_w rg m(_Ar3G`@{뙹\krI&+>@i ~CƥRVVQc3oa h+kMN{X$-eѹO*r1srt*+k٭ h5۱ar}zCj\u?G|v jW{qS9֗镻od@~Mp{׭uI6␒v,ww{ppm,'m#͢\_m>"_dZy, yob>,]@ɺ8*eǧi?/fOߦ7 /@cg e-(dģ լ( G/ Ma endstream endobj 104 0 obj << /Length 1989 /Filter /FlateDecode >> stream xZK6ϯQbFHQZ ,2 ԇ=mmJ4ϧX(d3`z'z{{#gI,HfwYaD̤F&ݭfGez/TFe9͓h_a.MtMN6H?y c9x,8Iaf )NQ&Ml$ZõL\|6 xn0yFu"'LER»,|ZX!NS:C-{yb-ڭ W f{/0wCDodi㎹W]YkY,ll+^BcMU=ڮppPbٚGP\[A#| -k v{ٙ& doKمƼ8Lz4]ЭgH 8ܫƥ*'fkY*H[(y=kTpLgF~]zliCu mLXIqiM#oʽ,+SW۽3GPSX0 :;@_Avm"p?h /-KF1P:l܂P|@ \,+/B"Ҥ|pX],Aw8H{dWw..bO]{nIԡ\3dnG4"K9Gtg9_Zۿ Z%m-)8) tz=!FWw{ otQ@mvumv]UHp5("{%td@Mjxv@kH72(\"Z=hWݺPz[@j}ˇw( Sr;cĹ*ȏ˰6>HuѪyS9_cD6Z"Nq0&Cw?߽ř endstream endobj 107 0 obj << /Length 2681 /Filter /FlateDecode >> stream xڭZKW ^64ċM`3qp)ĵD*4cԫM5# ~UWW}U|YxU)2$Me*қͿo s#?.olxV/] 8JU CyG -pd=;68 g?-6x|Yq ,kI(68~J˷$PqᎨ%ɿZ$F ꪦMNnH&ȼBH,uൿQ%*,r#.t3^JP>q1|c>1#xb3z_U83j:#+8GOA<{|gКްK]i=6CEsj[4w{ [$cvX0~E'# أ@Ь=Jz):\L%GT_3 5̞ttR4]N'YڴbÁ[6`6ҀOpc|c0e`z0N7WvDRfl[ac@3tc "kT5GCFIlA 0:m:qj< ,_m/ C& ;Q47~G4%1Cc4#È9S^w8Zd7a,J'Z~e@e],f}9$_ȿ֎Ikn:Q'zmue}ǯ}p/W?&um^4j .@'vٯ@HDt`U09W\  OYuO\!Ts̅YP2UPu4K:S$]۱>& n4~8cz^ .c ٌ6De0ݓjGW uQCr~㡆(Nx!Wf.T[0NkD0Q,&p|MQRt:8@ЮnDx)>&+9 ba-IcLj&&Q)#mJ`!r]&[T笖11+ˀ; wyN{#Qb&"2d,әaː=Cg✍ %q*b¨+~Z[ZP`:Uk~kTB>$M!ĕoq ҭ@~!8c;,lH'!xAp9tF?c@m 8оƍ{!%Q# <:$^|A^}?Qfj.1[v6%@ӗ&I(|%h?߂MڻD㰮Jkk00I"` 70SEm\գyDmc+9U'{v])bEkcsa"Z@ rm8SN؉Fݳ<*aꇑ0Q 1$.HiuxϥUM>(x
    fOwNpBIXi@KŽ&hp4ӽ$&8_G\Uf;8d Gqd/`a׍54(O6#8tjdrSX[Gӈz|1]A֒F^Nu4<(t5/`PII=?w6uUdK3&T0!O׸w+ qŽ%֓̓Pp*N596DH endstream endobj 110 0 obj << /Length 2135 /Filter /FlateDecode >> stream xZMsϯp%T K K6;Ne]9$MH#JʟO$eҒ'Jp<-Nz{O<[C*' ^,DHk1MlwVŵnųv@AvMAo62ʩ}7赝0`= < , SXXW.< Ӌ]>xc^DK,$M#{jyya3x}$U=\ԏ/=~85fPHaB euindx<е_>0RU"M{s&B*bRIzAM!̘ !HhHzn]Luկ1 ,t OpNWT"񋊱ΝNDt`%ϤɆ!j,iA'x 8:E[I[[[5E/ĽM_q om#vۗW^]O't_xqTK 5ªكf|JSеgkly~\򫋫'!UW+`ĺ;q ~(A ~QoIܭ ~x+='AIYRu3Pơs %2*ܣQj:"cfCsBxәlWe}@TI#EGv#IƄ)5Guh*҅m}u9{09@dּ&UVY >AQclWo_ʄx1A/ Ms'`ZuDT@9˯N31V:o]AZ{Zn,>%PI_4 }K^2 7QBwSN;nrvi Ti[*-f*`թpIg2qb '4;Ax[瑓}jp˯h\ݰط53!]w@gdOFJ|U>S2q|rh|@*ko6RqƎNl8(wi+AYv Ho|8S/Ӹ"@ ႝcuҩ7XmK-^uCInHSgϡm|?,s=+d >z3>#z7AϣۅKfvQU20~6rZE*3ɚʸ|eBv:-V=I@nKk0}ɷïӘ>T JQJn\L/|?L^ endstream endobj 113 0 obj << /Length 2593 /Filter /FlateDecode >> stream xڽZ[o~?b*^F$%Q*9h{we{^cwf8)ڋɃDq.B}wᛏFd*QeDFhS%߿pR;o7Ld?Ic[?߲Yݨ2uLSJQTڭ)Fd#PqiQ|W$er wsdeBlGފIVeg; jv Hk- Ƀm9BFc)3QUEUV8XMXen)do5؊≛qYUx LѬ7xR#\Q*#[ # 7clW#zVFP+XI3aʬ-G+2 6MU&% CU}iz/LĐ=DSl2ʶY:`Z3BI=يQowx3!:WAR)`@|*Rk/-D T*dv!NF!!KE;!NtGyLaiԶ('O^x͞mKb!}|Gfe7PnZ~v-IMda}`|dokpEsur (׾r8FfoX8m! 'fOQSadj`Ol[&0Br.<=frԂ/N?_ӸNm=x*Q$jy ϗdgد:lŤJ(^RCYus*d+O*xM1_brsedm]M~b5 Eȹؤl3Af9Z (@.>`0ޥE8ޟk+~eS% B,:-Ea8ccoNK~XOWq YMvi~Ͱj9 6ͮS{Po݅G3E+LL}͂%U+@6dvvXrz U)fZT{C=\Aeb‰Ɲھ]nWHnn} d-AƎE x5ZJ^ <0Ĭ:!5bf&]/rF v$5 oGSRTݹGcO@4agJ}LECN]QScgϧ 6PJy $E/ςo l]Iab˽{8?wV9i:ԋ}90j:_u -t̔VF腧V-=k[vL+O}Ybg50E|- Ľ;vnTkl72&/0lǭ/G(SD#^IkC6GKWie]X^vD\X稸}UO؛ށfNw+\j,+~etbP?Xo.ݮrV;x8g ˯`|i Vp"ˉ Q ~;irz㾹T3`)s<1{P>*HU.W^/()}Yfx<,=6gò#(GgX蜦]2\SIzA!P×gN>Y.F^!*WM~ endstream endobj 116 0 obj << /Length 2264 /Filter /FlateDecode >> stream xZKoϯQ^6l ; 䰳Dۂ%Q!'W?(Q{=⣻Y*?Z&W:QUR髛۫¨,PW7&SLpZU£VS=ycCr0P:̘I;n6ӴtSRrL'M]Ӵ|Ό֓{C_Qp7Sz l 7۠T:y(mZO4Zt疟 !q|o [[qiAZgtu[x7NW3-~Au'@z˛IY=Sˏk9kw|'k+6Лf"4Ui"wZkjR;*pN;D-ȽQw),5pL~f=u! Ӎ:$d#d3KrSi3ljzvϛXz\zڎJTR41\F4R9Z~"|j6FUUJ倀^ Mu >Wn7ߝHj hh 70mp%Yf]9ԋTsyۉr =Gyx3[eLlŞj0 wypK3bk&$y5t8ql4HFn3<( >]w(ꚃ S%A#l'l#{z"謹VY@(`K +6\:WNTN$26eZh@>`@"_Le=|,霈7"Zȵs8ҏV'ʂ^\d|Ntֈ5n>^fNs݅pk1 iE#q~m2L8na4Xޟ`O bsXѥ2B[.MT+j|qP5f*,B~;C: (m"S]{%,Ry9;TDž.Lk1ꥬoRDy`)j\u~ 6n„& %Uy%\t>oXF6 ~et hˆ=x*xpܵ@#'%^.5iU N硜WD Ks'pus۱֐ʜm Sأ^z謁U|@թ Pi~R `t-NfҀ]j<^i WOnqrmDn BkFq6; ӸTAQ ֳhgMF7+&Q0a$7ݾJe5xz$~i]}))vw a7-nCwBHB_Gr__0'm-AZjt5ڭ+geRW&Wu$] 6wAP] Z[$MM2f`B:ݩ X@Ȕ&tQb~-/~ZY+Ͷғ?;¼񼀑0/Nxj;ߪL{O<˲.DkB52/BQ2Ρ'n8e8ά$_TV:= p}/J-vhb(hEN&fjG8w5-vj,$h)6͋90=B."F JEG"աswf/lbnh)<~d3 jy7 ƅ_IOIy͍1,'\,#E@N}ɕSLDtBQH: A|ZLH[+4װ 󵸘::H^+S le1;@Wejv_VJr(=\3E0^^/~/y[`H_Qj)}A bRA9)ܪ$4pjRyBXyŋcK}!s~~a<9O NeYrig:WMԬJM~iԁ7<'w>`?SwY_driW*Cv> =H9>a=LJI1K"S`G%EiJ+=E͕6D>k1G^jeXRl _n>1 endstream endobj 120 0 obj << /Length 1972 /Filter /FlateDecode >> stream xYKoFW=@> C ТȡuCӃLҲIDN?y풔IIv-|Z~W/^ˢ [T e#JƯσ*J/V2a'(xx+ E%kk^D-tQ7GA7ZSDV 5B TKʪmUvx7*k\z|mla74XpP _LܹG_ j"o y` wxY=ub$*,Am\wղsS*󹍠2 pp_wJ= 0Q\ʉw$ jO0rPϹ=y8ȭ|M8Y5*?X$ 'gs1N`-U  ZB{5݅5op)e! %tɓ=n^8'w6#d?(dR}׺sr0ffpt5;Q%qCCzal~lQhnA/4|kEs:reS=V `vY~U|<̩zPF YߥV} RW]wd)y+DF;‘ hJ2%ؓ뽨w`(౮JN٦t,^ ־y[y8 xND9XY19-T>=X~!u]q T^4i_ B|/TxyZeyQ sGPl6Þz^maWEYPv4 u|$U?KقIiƎy!E) I.38CujBACGn<PYe{b^S8E6Z+ P/ur&K S>ʒH%x]!_nUא]ЩN\| Q5iAZ{ra5N~_IUK;t$\\ A˶ucfCu3ܛZ@a|Ջ& endstream endobj 123 0 obj << /Length 2299 /Filter /FlateDecode >> stream xڽYK6ϯhd1G$JZ d$Y [fjYNd{foqrPDd_}Uw#UFe|s{S*SV/Ȧ/v摆{!X=we V P2-HL4Yhn *r`s g {'>d3r|짍]oG>&gF%_B;d*˜'v#,b5#ډЎ1Yx؞ǔg.t<҃Bhbu<6"CY D𾫜h@b[|[.KZτoMU*oal ]ڹr^XQa4e}cVL?#t Ja覠0Ғw(brLp!AB^|K^pŽN.߾5L?8n/뚠w|0Zy'G9gl;^= y֘mn:u*I J2qg0+ `E*/T&I%V^eݝO8GZ960ؕY ղ~;Sm[DC)Wv'wA4L#|6|&p\[|D*LFkHYh!(@A|EA? 1,T;߲Or шBCrf]H= EO<~p,*ٞ@Dwȸzh>q%H;[rX婴Nx}P (<'qt:t6A3SD TA?ME[ahM-X$QTXE1*]ؑ;ď`=v~:Gpwn% 3,'JXl W;IPXd%ofe'< V< Tŋe>0!E;iϠ_+G~Cuݻ5),HD/CXx5qc`gÕi;ujf{"s(qd z} _KIzՇXXߙ۶gix'1ӽrixu $B8^6o)Sh7*67yJ:\ pr?F+;^kUأ `TNJ*B<JdYyȻXj{~~< GЫLTi_&;Ftw@TnDZL~Z1qpRNS^O[ b 5t6E5!XwN&u!6nzpJn~(/# 5F㮙d*1x Vhȓ@\7G;14_h Ӟv-,q}@r߹ʒEDg11>ř$E^+i 1,m10cy5?x/<ZCJKUZ3/K>cz6X1Cz}Qkw!.eЗ_ܬ ;fpC\+:3I3to J(4\ sR0P %bt髪ZgJ$_C&bAEOn%LS{/A~_>Й&ysˆ뻞m+@.`gBeڼɯ&[kr\9 Ug5xsֽdգ4tuJ}9U qZXCEX?o2jjIlAt߾Cx5FṳϐxՒnF<^yb[]Ѯ[٘~Eބ V Ʌ̮ҥpqaY=U?ۻWt$}%FC_xDq endstream endobj 126 0 obj << /Length 1928 /Filter /FlateDecode >> stream xYK6W9@͈)R)zH,ТC!Fli!qCrh{udS|3ߌ}$#HM!L8LJxK45,Uh*\&sM?/~2MS1.ή_O5kcҚe\*aw>.ckV(Ǧ<@QcS Ô~)nl4}rn4 DOL7%:/iVtq]㞭i-z="y1l6D%H8'_ܣ ;LIݪ&5 Ե BV$1l(c.50ձhgQeA|1@<Ԍ? ZP@\f*{F-<Ҳ' gDqbѣ=DCFe5a77]F:l}q/ҠHsg<bJ[䉯%8XE@(ä hCʳ d*VءrVLfd%a=5ٗRL%bcfYH>݆F%Q1^?;xgsqCXMu0i._gN}lWje1N*&=s.9KHODAU kZ^*d5DS&=>CL^z6u%A=C}r4`F\n&FFiqpURzgm9Ža!u=âw> stream xZKsϯp$WUj'S9dr%ZRF"Qە?ݍƃ$K{M htuCx×2Z=>եLyWR{s=/ywwA|l{9Yn;@(d ?nZ%p ~iԧMV |n:7KK!=p%\O|ĴE%LN.hƇ( Hc~en ˄X6+$ٝ׏IQ+?_BI+JN6 f->e&!/&5%M÷9;V@;ѓc˔_d-&ٶ/{5߰u[t}JV7H$xg-`e ڛ9c%OIQЎk kf 2Z ޝBO[qd ̡c8Cc~:yL^}y+gڰuoRFJFAc# 2?iٛ'Rw!QZ_̩}-[`w.DZޢmf~7~v;ǁZxF0PHk{;*rU~$ o^R joS)sr/ƺ gސ,ZQKh#_L^m`{4Fl` ~dy=M u%@#m7S|YRBAۚC"F~9 -H,[!"?)k;'Y^Cn2'p\-x6?tMB*r!kB=:+ `y54\Lіh]ilZ:`T s76Cmz^y缍t Ԥv2ezoAOühlQѝFLļUp*6տGWxnz<^+t-q6*x_B6;*\c Վy-&(W_d endstream endobj 132 0 obj << /Length 2419 /Filter /FlateDecode >> stream xZo6~߿· ";=A؍l,;)ʡl'-p%"Ùo毋wΣDrdZDy?Y:Y,'NS2ǟA_ͳ|^6pppu|k õ~g4*ND^vg8 \k5r-\wب8˶⩰ݚ-y!ܗ!HƼZi KE\)kum ?$W@ey$"Uhs,QwMM BR)~{F.$E\+кi]8UmI onfsNikoo4lo2R`{j$7v޲-={nY=eH Lgކ<~3Aؚ׺N4v)تhΒZ>k];Hmzݢwg/$w޾G]Z`Ykpgp4:neO:ds$.x;$bAZ6 QlqMB|$ Fj#ЂweV~?KiyWT[SNJ+YV=9V/ko1`ϛ H,rp>ׁ"p> ,x50qOY] 'C785O<6d ||fƬႥ5mD4`jl{Hぼb] ??З"3V\f":㰧`g1ypLҡaqϡ"큾4HEj={j MLKX.oqr.sQ~ l~(@KB"M-YHk,+Q~4fלEGDJ֜'0{"qW%2ڀrey(G S1` ) :íIZ?V(G" +:*D:?WfН[0`+"R{ֺd]|^~o^$#A"勣ÕIS.: *,XOMyhDi+ X]n.zBˊ%*ܑ&4Y.1nNRly䈪9NmFwiCU = 950#3Ao'bs^W$DWʂP(ذ1O(BًM Q$-t׼% H+7vkC]r%=mTlea@Q*I*|y=@c﵄ǚmjH)R'6[(YJ!taHIP>GzXV= !Zg[yM#- ៣ Iu{GS3̭/傁C@dQwVN(עkHF'qf nsUtY0ՃRXux^2)GU4|XFz\Rz{fDZuS J ^韐DSxb2&F$!P @!sĿ =Ol<]ɫǗ^ V3t1.pA/]s'DN%{O_P끪:X3GŎ&ۚ #fBCd TPF>-3eE+/[kwv,1U].'Uy8_񐷆23[V} ZyƓ):Urh1&x("e~-@)E~QMOçUC ,\IV VMi~XXDnez:؂RfT<%{[l#͍cX}j F#! ltoi]ڗ,>zg8ucF/'e-OHxGef *$DQM4rO:nGLN;vwӥ3lp}+%ya!1ugOi7eO#w2E\hj2-=+.=;8͓o0E|XxHH9x tm~Ze endstream endobj 135 0 obj << /Length 2307 /Filter /FlateDecode >> stream xZK6WrTE0IU{S!Jr$(D+Shć=PH^"D~Qh)R z7]"2C$zyY"_7apϲ k#8EOCi=MSP* aν?B2DIf)0n;Tq(qc:% M iޣQVNPp,%aŹVh1?iyڍA$D*BiQ5>N2!et 4{{kFOf~R=%5Y-^ `֬8& WNzFɬero*\F(@Fs"RR6"kTd)] Oi1-e")R{mw8g8 vKh|2*b1D\%~M((IDy1}Z`Y#"%pW&AL`sK&JQ_v+Æ% NN;郹FlqґѶUw]Snp#X 8OE$\Ƚ oMhP M#橪9`)8ήe;^iEkse;F}16-EL(<9LtDuʝwd@xds/ T.I;U̞[(ZݎIᐷ^* _l[y:XNδMWGs2jIƅ☋4H&e r ^tajEOFQ"JԴe6ct ͋hn];}D [Dh}uܖ؏2(&5z.6ùY쒡M$ÌPt;64k&2'Ͳ'wz􈀊HtTptӘ*bX3uMH;ؔ t$PN {B-I2HN]=+Rkzω_kib4bbn qr=U1`B7!ーC wBSTicS{)l|9z}₯"?2/"_Ezr80Gw-bf-w=*+͞]Tk{X[8#%f }J 7QN)ӝ:ssapAo ŪN3wv  ~Ez$OIb-|%iKhZ"ޮ9M1RhzZkgn6& G 8BѢc>Lŏ`+:7[aB}cトb O7#BR\GR)v N'8.ag[QPŐl~'΀\R+8F:#3 lg~g'0a#Mfgޥբζ0k|yi<۰ʂBICyoCjW> endstream endobj 139 0 obj << /Length 2586 /Filter /FlateDecode >> stream xZo_a6<Q{mE{^؊e,{m eS>(-rDo~3w7|(LDrr0ɵHBn1eId_mĎt =\knvp}H*BiY!L9iݦ~_?nӊqrbzB>Rt#-˒v}};Be)1 |IÇ(ƏI;>S9i oe$'J #[p&z#qpmƇ>xH[<= ׿8f |dЎаg_3 sӷ}}ybPѠ[aXsZdirG*hyμEyGkay{~X-6Ns;brdz>fRa-+q267ߟOL~ |HKV"]j~md)Q:`ii)Z1Y ]/x\߽cP`+H|Xk6ZG^λs(ޣb{ "u.-8꺨yC-9r=ĖSJ^HDpF_nNa$7On9.ǻLdƇq͂}x YvkzfL0RK}-OAX2-l oH=e"Qlb{2ؒ`Q%Cn5^y @`ٳWKTrt˞ OLqaX`Q'j2``ޚR&2 |)|ww z(r`&V|2on~5,!A94QLyoog@^mqULW,Qi*RS=݁42Ppٰ۴옎#>@l=$O0QS6sCMI-Qm"[QFq[nC~-'ԡT_zRT/DDAI?q)7:EzwU~MU< tFO2?S@O+waeD4E3_@i~ٔLD^';G ߥmiDa?5ĖYÑ+yvef2jpcîP-GXkk[AqBLcvnuTԆ "0t"̐9rFH4﫷K!֎EH",ՎA~ry\YŰKw8ve4jzEzz Wk?ޮnMg !8%湒Bf%_MXː\^ގ*?@W^ 4&>tm4`6{_!_rEY [A#%f눹F[CV RUzx@U{un^؂V !]; A޸."a.om9V m" GtE氡fx\oe XىR}0WA߱C.2}co4|U&ީ/v/wFt[RdєtR~)ʃ׼B+ٰRaeshfT:= ¹[ sYɢj+/9N6SZ)rA1%E{89'+;]œMYipHV1ƲtzUxhZ LbHZ.S+~,I tR^/G]>':T!J.uE"Rc^pV d]1 *$;g4|h~68g-e5Y n30On,pq<7]0`oVm/(:ƤQArDփx7(CVِV|u|o;\V[Η/o*NC~ÉkWFw,|3Şg4jc~o946,ځΕPo58T-G SȂlHGMSOߊnURyO_1nr2@Ca%]H tntBv]KF>%5),A 9!Hkm3|W|{Ig糕6@2QI)tnC b1"G ]E80-Dٟs<>YD 6*&i➞QPdoL"9)#AN:mã?rht;(gۥI'lS7'K:TѩH|6҆LKm9'ޖLkܦZ }3S\?䇔~1%wvZGV닾 0$/6 ixH9mon\X1on4ΐJ7äㆸb7XpZZIK=jfT>v)݉lL5ZySpàt}5$9v5灶H+HOyń.* d"rL]# endstream endobj 142 0 obj << /Length 2101 /Filter /FlateDecode >> stream xڵY[o6~02Y)a{PEI+KewHRBŗdJl";9a4шdQFg˫YI/!<F?={ 4IgY5\p.*ຂ+kW n%b@")HV(5,`D|`*v< ιiWßF)uZ+Ē|WqmWm'$Ψ+\άO3=JaREs +yq2:dh0@ l[t/KEѵ(`-ʣ{%A8ۄ~K-|SZ]ȚIB$u֡]4$R0̿7ڦbxNaP!-4O|bϵخQ۶[yjiY"9ea/OY9W}TwoC&d` ߈5≺Z=t7~UH}FAY)L ?b8:ٵZft^  9v4VaPc-#<=\gN `@Ǣ׫/u΄b1c8$k.Q[.ڈd`jg"i.PAft*"Jq֪=1$((#:Y㚥b== dwi )T&>SA=sB@ޜp{H]bzzcT(ƖҬAV >`W\JBbN,RV=bb(Y 9 ֢*ha38@XLXOp /[ 0ui~ҧc̡Jv:8"-FU|r?kG/lG0KOX|ݧwϙ tq8#\ oF]?R" ]}.`%BTtܲbRPSD@Av}hM ""Uwf`/t QF)̤ 5sY6 ğ\ 1SʍͿΨvb"vv.C1%>~2b+cW[~+%",Qy%ёT}ǠghM'Gӄ0#z)T ۸? oRB7?8}0cP5H`fCI=5^}"^obDUӯ5^iPb;[=bj RI%#Ǵtb \9{ȹ(%]/21UUo IX"Qܠ UI7m&L}WK"BCg:X&=59*)L>?O uRmK]LrKCh~3P&G☃,V$#ԩx{DwLExvN\SfmPd(s3?$,d"DЦ2ynBn=ȪC}0xL}:l{5.A/0ywugTUώk2ᯝ&&R 6wLgXؔ>Jr=JZk*gu"ޚ/8 UaoBd k:M( },Э{ͬdzx/|Ǩ8jG[z]ż}gMx-My)&_˵GJ?U7=EQA0_ {-}|;\W9xz/`` (Xyl( 'Z>'M% endstream endobj 146 0 obj << /Length 2653 /Filter /FlateDecode >> stream xڽZ[o8~ PZ`t1L }Pl6jKIn̟s#E)>((ߐEQ{lIm,ȰbHJ[y>8K y6Y#SAdMy8^P뫅R e~VQ nsmD"Bw+m~N{uJd`hO,bjB5qiŠ:&=10dyDmelL Yv^?S?O94w$:\ӎgpSMCR:ceK\qHd?A3c?E #CK ^+pW+L]S&1b:F.b"C(.[xJ!C6} L| <@كß a2!Rg;ڇX ;3r ălUlDn]1̆$I!F^ Fh `Wc0Ȣ#fԨ \9gbOET:Z(iy='~*/,j8ڭ P;='Yi,f#/NƱ&tQdK%QޘDQJ48 >(.O~NM̹8`CD)dYY$ D$ecqaxvdk7_ڌF%cM3DCMp5+Yg'l>GϦnpE `TL|o#''1ҐKq'?pV>1c׿w( ?,y?|Z;9t_I'AO/(! _n`a{X%}q<7@#uؔER8,DQUZQ3Ph{G#WY:DжwZ|\)DzyĬO)9`^ jiEG>7!ėGD$A#l?ybKgǬK$LdwPdZ~* ON-_?A5wǦvo2 á-6aAgjĴ]gM'uw Nlg;[vW96dTi=4ǙqBPO) $~I|8MQuߒ$&q[&OEvfn5>Wqzh!8|GR؉'ONx'c]#E-pCtI f9iOjԭ҉'!LGnu,NMi d R!!Jg'_i$"Ud A͑ZL>\:%NҴ栩%$ExϹYqQ̔ƶppjh7߸EdCj81;ޑ; j *I,ͽ9zvmђ(םjo@G$X\}p=0"B;)zӽZxwkfEY^^C!~Jg;Q.v]7{W;y2/Cpi%}`(s2!ѿ'ܱbm B'2ʉaaҞrg8̀_S~ PesQ ׀r L1z,> stream xڽ[YoF~_! D#Hry8,SfhK#JcouwA)Q2WUu_͗WфIAG7QDfggnQbv2圏7:7Sߦ?rÄj s\ۛz²9L2'#j}HPߙ{R\v^=`NKoZW%ά&K "rtdc} F\ b4\ ש|K.gyBaB&NpBA|UہMԛB,͵GuP+{rWlr՛噕n񩙹Q QoU/"WJGeJ{5Ur>'Rf[Z8\)(whe^ưraV Pn*IQ?v1p,&Rc 7phI<Խ@+4nc$u@3mZDZL[O5k:m<.z0'j}I-Wb+z3VHxᣠ㐀i:]hQP@^׎z[)Q3WrhkZ+/JN0K*H %Ÿhi@M F h&S! ̡} Υwxx[vJYJxJqk}D 4 Wgm)kf#iM0 b("5FSc\Qck&>t;^Ucĝχ[`0NytS` y}EAyV+W:pǏ1rI2!;y|4gc裍u Z%\)K[ɸnDmR'N 4wxܻ2Ba] ؄l-RlJպt\!Ot;VG'(wءh[e5TBD3,)Dձ` i7ԯ kb;rFu)1hu >DYJ&o Ŷ4O^%}Ԉ#=M_v4Z4yO8+*W#2Tb^&ݜy%QaM_BH(A ᾎN'b[/tEd6ᨉ NRVBK\zt|^Zٙs &)}Ԃqr_X!ZbTaa4 / pZmfD,R>j`7 hvr fSD5?R Q(ά3PaOf~rSqzƼg ۭO[E'SsrP}฿l'm(4]ρsO*ȑs?[*r)wxӺčmdtqB(lvW}EVQvW4FBZ8Z趍3U MC"3X6_m7Y/Z7 )N$;72n^dzhP鷣1Z}.FvEs1zO,`Bbhry&pO[.p9N]hT%+\9C \ap0|hwRp;ZuyZUeUzW+#R11%bkbf6vyssrl]-]!oOʽՓ7l㕮3=Y)n43퐟Z;ח;̰gXBҖ Ft"C=S@D3FOTQ~@dk򤮠.tB_!K: †C& IFQ7XNc҆2LOc{s\]pJkVS? lSpv !zt_/lI<Ӷj7Gw&c L3A8eÙn`ZEV5]g@`4:(G rpk 833O9I= Z{n Vo?33iV,Wju[AiVmm9^͡LmByF7?޼?jI endstream endobj 152 0 obj << /Length 2258 /Filter /FlateDecode >> stream xڽZK6W,r5#Rԫhm)-Akiږ q%S [~{}aon҈Y)殼3KpݯާpM{mg<õ.W8i$2|7DZ~S7(K42YP]~gqyJ<Ϻ0XEtf$L;uW_UϾ,Nt}e4?ŧMFGnă9X,sb{ȥ(.4!2 BОHyO(@0N1 O[<`шf;9QIqtt56t&mJZ!ԄJM&YLX&VvL/Y*؇ E>Ec p؅uO y} YXq8 >LxW 67<@j%/ko!OӪX^b E昤ECN(jj{ZXeHK?UR<48[;I3I3̓c'oQ0Wd[2ò13`!zTmi\f3sa7R~ i:X5[ߊ d:YrOEpgX.c2^5^]ʨ&(J4fF'r={zaء6A}ᝍhx<, ӡUA;P?wi:c巌 ݛ:H$"+9jo.}k"{;.1f},&drn ; jIQjG[nodC")/q#ҍ,{$2h7JVp quLG@KhY>r{=*=[4C5 ܲLս`yf:.c; Zc:9d|LBa))+ͯgөBPtYKŗ5B;a߼!}nU$25y阽7Mx*029yR!eɘmw}uuXrW9EhCDT+WS}9P)k\1ٚfsi)t?`BMUԄBA(.j&-hxx|t+ltvzYyS=ީ{{IBɯѬQ&]䝤]򸟕I Tbh݃J&ub{z{g^.BͪN<zGtaHo(*1.=o4B[_ǔN*Ű`8Y/}rᢶxQҟ,.+'Ywu#s>+ eK?jH;|i2k:>v|=_[>ek'(Eye)dƣS4bq:7Ҟܣ>" >^ܛ8IþHhTKP,}F7qf"<:T!zh ^kaðA_b'\s]E|$m ALp}&< w D`QND 7wueot3Ӻ?6Tz9}|a\zT0_8 T? :V3,-@pwr ^O~I"S΢jsnPIzs8+teӘrKMl{S9B-_V0BJw+)Ի7ܽ8g endstream endobj 155 0 obj << /Length 2141 /Filter /FlateDecode >> stream xZo6_5eDR"}mp@yWݕM\ᐔz%"Cͫo]v%3QfZdښ%7~¥*>]Z 5Gnk?r) )܆)UT\; s5WJBMM/dkegZPmjtثfzc?gck ڶZ[vfXƹB>2;085Exz~oVAqf,?27́Awo M:].IS׮r=JJcqv]Q~?x 0A( 鬙ғ2*Z;f0Jþj++բ4#Ԭ*0kۏ+N7%2'7!B>TO[ KF 6xw-]WEڭ?)dظZE>/E~XsZcM 6E*yK%6NfZ}h5[RƼu )c i(AIdro8jb<`Ảe"SeTOwऐ.z=/W(C!ɩʌЮZvaftz_^vB}?ƯH>1iRYbr|zd,LB>ɯql]r$ _نkI٭0Sp$ \%e$G[BAqYa M J{ ^y.EKv2`i| I;o^C9yWϛ3@HŰoDs ۠+[/]PR >k]X&4RG]ApL5^}Z#È/)0ba2+SBrUR8fr٫n^j endstream endobj 159 0 obj << /Length 961 /Filter /FlateDecode >> stream xڕVKoFW,pE\ I Y%Ɂ(KC" HQ fj1$4ERn[\<[IB!FҰZX=Iń ڇtPy'VT$Nv"6FԳ?sx;*7pZ=~w[ j kinT(6xTSG&W\rM;`ݣ2H)m3>ܵ>S="U*S=D[{NŊ ns@>vhٱ &PStTr/9:l$Lj&dws[k_ Fu%Der'K 7kMP\;(Ե,bQpR신&̪ib[d18u5,Kd%0aL+j~c Xًft3Ϣ(!؛[Zr &t0`;hĵ/L\Ά?W͕e#F?uru,l#eMs};CGib宑Y+2s$Yddg* LJgo oy&ܔ0UJD֨bz02$J66myفXb$6"GeSsQ%~ߠ!) KBlT>~fEۆ H A'I~ɰ\s5D#Ѩ,_⧻QPZo3a""&:WW; endstream endobj 160 0 obj << /Length 97 /Filter /FlateDecode >> stream x31ӳP0P0T06P0P05WH1* ̡2ɹ\N\ \@a.}O_T.}gC.}hCX.OȠl\=% endstream endobj 11 0 obj << /Type /ObjStm /N 100 /First 830 /Length 1913 /Filter /FlateDecode >> stream xZ]o6}ׯ0Kn֭ t@VRmrK9XN }yyyP )HdN:jA^RB PRx[f1JY~gm0W0T8)e`0y?y&8]5u.O=AI*[o#]>y%~^ߵӵ}ӽtzZ6fŽR=εdӣ!cKHE[}}Nu>hvZOr..x$?Yg=v6N3]1GWoŏu~ڞ7 ˴l5^Yvͼ9Xl R붺Xn||v>kzZ.>RO(n5k1ź]Wb͚j)1wE\MW-/jZszLL =~ ʠi˙ mܶMlj񪉭@6"VfG|~5xLh:R| j>vbiIo,E7W×.%MX6nNil1Qf1Hnơcݏ}m8V7j^=62ә0^0ޘ6&tC_zzn Ϡ1! z7ĝv C*p]u0}p318-"ϞC<6O懤a4i o7qۍttSZLLI1L>^(Ex<|x(qdG=\~o>}~oR(ߙ~;Or{Y> 4[n!P^ݪ Js՚')C>!!ɐ&`DLgjݝWBc_7{Nz#n+yvtq%~v!:Vx3-]_-QIkoFZx(r{Xe1:`ST"AA<3#Zdהͨ9d}{w*(yd)b_شNjs8f0z>!ᗪDJ>8<+{<'-3fש4q/[ ;#͋O|XoXaײZr9{У.|ͳU rq9փOF Z e5s³2i/nl2.Gl4fˈS^U: ;V %`CU#"*f%H1~mz?'7yfRr[9,ZC撚|edǤV3C7@?CQb endstream endobj 167 0 obj << /Length 155 /Filter /FlateDecode >> stream x313R0P0U0S01CB.cI$r9yr\`W4K)YKE!P E ?0? J!DH" @ l%r38 H.WO@.E endstream endobj 178 0 obj << /Length1 2061 /Length2 13429 /Length3 0 /Length 14687 /Filter /FlateDecode >> stream xڍT[ Cq@q NqAACqwww-R+Vw+}qLs%&WQg&6fV~+ZGLtv;@h yIB^9W `geC3?@ ;]6V֐43`a jt17u(BMAu B ZC ,,̦.`g+w5@ tvZ" P2Ìam\l q7u^ s˫.Pv:c#?17 d𷳩9 `i!F_ 𫿩 MRWblqavE0]t .'a 4m'?'kvwq#+PV?&"?2+ :,t[|%~ {gW!,l!3b?m<`';<},22bb 0NL ff0sX_>0*6)_`?վ*vg9w,%t܀o6 )Wo5 ?C y]E8_Sm?K+Y_,u D@mBbnϬ#k@6@_ ^pyȿU׽)%-;7_u-0 yuX:On._EHX  `Q/}T,jЫ `/{n4^k1/zՙAM_cd@״3ukaBZXڸK vuëտ 'O8FZ{:Z]ӫ_ݿ+ п+C?uYzuux_ du/kԯ}v|]58!@ 3h U~sS_/\.w2{ X 3/Wڮ,uD_+az= `s`ۆλ:Q"ws;\RpM\ݒY!{>j֞d6Ӂ4;HqICdG+ [:ɕ]}@ڣqDŽ'nyYhyo&Dzs9/dr Ⱦ1%z?cyUkP\cMx-zFo|X剈Y H&E@Q9CB76UOy3H;\2r8D=QڂT^JtZ 3e^OÿWdU07ayV`vŸ,akB6Ž̈́ϣtv)(['4zn!AKbwQBzaGpq!-QVi*Fm] K I什Hد/nAlVٵPWFtfDC} V^:1fUv|@M/Z?c^߲(70ZmNC$Q (rTapC6.ꁈ10wbn/9fz; Y`x3W!`M5t㘜dyЎ'DnniԚk+ċ?>䧿3Qy2{:\49y&o/PQ븡<`bOcf-w8lz*OƈAl;rc ~) *,BJ;Q~ҜڿHu*f,/Www`Un[=_'+'1FunהA ,;ƙ:u݂J쑷Q5DU-ုL3a9I~Gt+e!?SiQ{N;hr+U#}mՍE&)#2^%SN/4ۥu=_4evE BΩaXҊ$G(Uj 9pd dbbVe} йqnw*U<\dbp4B/}M7&}dΥmϤX$Cnį `ʻY7J؂9&wd襇Kp'e(mz!P3Y>7Wd|4ao#{ii[6jξqKPt}\3}؂1>]nGP.R%&x$#ϪmNU?}%rc7u$a` <;^J!lhG۹櫅mI~A .'ӀI3hL+pR֤[( 39T(iz̡|gI5L#iޠ=$ZZ+If+l"r eHRuN+VJ}8a¨PJ'bD4ipP5\& >^Yz5XGS \IL}%~N'gL| ^'k*}Zm ͔wθ?>e)PwL]5mi{Km*]B[k'Q-Tk;GNX.yQqQsڂDFV̤B[K+GZ}4S/vv]lwZorao)ZLW" JACL=md_W'-4D}PI9¥ZMB6}x@̈0y2" S̨^ˍ1<عYњkܐOʮx)ȽJx> ֞Ķ b k,Om Ľ_gDb jG H [SI8)ẰwZ}5gݮDm|S;Ao,PgTdgB5PYKfTt ش΋R X__~+&!bpBۜ;njiv tX5]Ȗ5o>%T.]i!?4ELϙʌ~vL&3i;ŽX3\Œ`V^%2~mɞ&'  d$>tlyӗۑ16bp83v~눘o40Stצ$4MmDz 'Wlnմ!?/f1?&K_ lfWI3Os&S!ձ\6efjm uŚ*o=nĭ)o5%M$=ZomkdQKF=6yNh> s=V9R@}̡K# F/" fgpS8ʆ6aMT -*r  |з@&\钹9Gzbr(t<|e) L[ A²2?L7MnHŃIgx<{F )ɼM$nHy +`EЅC=`_f+s Y-O'(ܦh8jbl]Xh٠ բ\nᢈ c;_qo'rh׷;Ku/I"ӿ;jx0h Ż"zFDOٽB}FHriAb*ٔ=Q95DGЯe'Bpz+i$(,hKvN";ztW0LHY^ŨcHթ^j1urbEZcq ֠9|wXɔZ&iJXV*K16{g_Cw.0U;l7udL ըҞ^o ”> `G+wRtBl{/DiGϫDfY8^c3Ag**gU3h:|u"~dj$BJ69; c F5EGjePs5$̀=*9449) &X%eB[}uTPMUQG^}haw)a i瘺;|Nd SeGx=nc>SLz WB,b/k(;y6LL |Mw :2~=muNfDٹ["KMˋŋ Ft"9ZNv-'BuD7#4qm>$N2|ZՀQtM?~Qy;^+6oF}Z$/.Xc=}wfV%5[<`W)?_m~T7_v7LVrsbIPꈒMrI s ꥖xs.I'"{¬̂ىoiݩb$2o9V9Ukágu%[uW݈2u$[SDY"C~3HUJ/ٛS 4Io3_ջn֣R`%AVV{&tƽӺ0+ FC,L)*[ۺȨ{[[U‡[}mK tdN-[4ROp3^v{Aѡ^ݵp8*p1ҸZ󓐅q5C_MJEzX<"1B٧1˄$^K7HR#&V^kOj0 S]:wf))-Bl5t8t|3Tx8$0N_m&#kQe 8B3i)^BػF(Ƹ'zSnIbM"zŠx: =p#VRcZ(9  I'~ZM,3DWΰeיNK@ANH/'Լ䰃GVIiicjz~aja?otx;x=H9sw֣̓vv6TApm&b6U3E1X1o{aల1 9Z̥4р>[[¨s)ͣen]} be{1n{҃{24U2 L2ҥϺ˿6mO +@τ. ~gԾ-z ڞ..,1U7ؗm ,A+ 8HY!2$=`&Sd|bں¿N_=DӒ|kݴB2 }?.ހۤ ,w46/@wOEPRNCKio>!%]YQܽ-py &e(l Q*m"CW|8 mQ <5JjSp !ZU=ԩ cTQx 9N2Y^6 E˩G.iYu/6\?3_a{Q[=+tSܶAOdy3x(fP?EH"³n~>hb8DRv tH|Su,pA;~{~^NgIb 7%Qh]Gh5#"sHF^xs yog-vCAs!(gg#"ކUњDmb`-c #Df*?̊^3)Jdsɛ6^ޕP\QdVtF4,za}m^F5F,䪣8I#MdSGQS!̂RZ|A]Ʒ(DvddL{r9JJmZ) wk^^D TxHJ}S/4dBk`~\n2hvF^la`I;=XMkY3[TCy(8CpmIK UVcY [@|NvB1TL*~jK8a;v^  `FxA[y._hݟ1`e9!nRS|ȸ:Zh=e? @BG\BLu'-Pu {=c9mu2Iβ%r{Ӟh؜K_I_^וҮYIXW%l-햁rqUЎdDpC%WIK[m-oR27t r}Zku2 ?6xGC;2A{gE[P}4 ʌ{;p/+1;XQ.S~G5ItitFEm$z ى;r;(9{ZpbU.^ 2'f.g:&LƪE¢*bSD:HVנ/"e6C*ؐN)Vߦ`@2 n<uH0\@U[ڗPxJ~ы%]M?]DK2t]Ɯjxk{UR?/V-PM6b\ay%Uzy 9EfҝeA? ~)EqE pf f,-ɰKl CvizonQd92úr\Wu-1 2D6Sq!OVMFR3߸{俠ShICgګXԛ?y; U'K^!- ^#cQa%aS+цόISO1=2py[?IQK]1tݢ&=$gy}nfF@kP/I祉 @`~>|% 2~IRNY)==Cg3Qts|O|AYYҸ<:vf.v€#܈Gqn-M͕^''J`n Ai^ߡԸ^ӡnX3 #vڂ*Z}aO1AĚT2hLd,#\M!NNHC{U-3+ĚT)V lp_%Vz\Jւ֌=5̚(ϞY8R끾ridY^p- sg{*_\MY%#3Q֏u(% ^A-\+1Ɠ_[=, ['-UMթ;?``|K{Wca"+q qC]xpP\P зK8[_b,xUK8tNN-Ěs(Lc,pt u󉨄 bO:A VR?{T:Qau>ҽĴS=[]7ώp9I\j/Ǭh &Fr,Y熸`3^Ngvrr`4A-BƆ}.q.YDO!%!>W>^/cb& Uؠgoν7"P?}-?j"D\K_hM'\8GCj([DZ% }j /?O t@KDSo 2Huœ'\WTGv3 +iI(E:\8 q{U B:Qq*S5k]}kqHվILVCØۚc>EaJ}DLow4*!l讑zHMF&ꜢNL+673,%F!=H ]| sNEi-y({ JY np`R@ndwtA@EδJt2 ^o!yW5l(/1hk״Hƻmjd.;i*T'\e8mfҡٳt*Dt!"Ϙ":bTCb'W͢h}Ci\nlRU/,'>zתZqxP6$ƽDFG}X2̿uyL'M,D:dQ`mw0^V xoP "͹2w9׋aTa,4cu:mBГƒCs&\Aў^rP]MܝpU `S 7`֥la@|'tOױ[R yi"IcCꡡfZ^IcVJ R*S$Ya)N+u=i٤VXfsnb749'궕:-:ka4ϩ7.r(zy ۶uPF,S>ruːZߣ/:1ew 2bJ 16 vP-EʚqcS&`x(GDx|Kuwn8T)%u۝d9\ucD'\7%8F=3gy6=7抎9ObgvqĴMoZAy2ݷňWg\з`Ѵ CbJՁ wY%O>%Mʥ/1AeNsطމ:GG3VLl!ѩݪ~Fba@_ldTa^?%ffqee[" ʣ @04V$MIwc_OAxU y7\^ vӒf%jW=ْF>.+%NX+-¯|^ <~w "Ϟ1ch!U:8p,mzQ.1;[p5,Fm fttBi-=jpKVx  v%}$oNkφA OĨ {\cK7ơ冢d!Rl)7ߟa"#Z$M${6@:lKV we 0 %lo^x#mm4Lm<\[&=?ȕo66,[yr;PU }lg!&?[!Xf,K7d5 "V!S{aUc ?Kw6υ6&ᩗǯ~N \XI68g!δMlx?n1+X@/A1" ސߘ8gTA!שĹ3) T9ti%ҴS,oly *x_ZkW*\xS)q/_Bv.ēڗ}w6Sja"HonWXㅸ NMwv8ʡ_t>'VډC16_1Nelz}L\Pc?U:Y0YX)cU&آݭG̝ .]ܚ2At}GYX.{:ͧ/r #ce /t(~a"NΟ@=M4_T u޾ۚH.Nҧ} 0=oJ_%4.l}N@V('X<` y?׀CC6,ߍ#h* #y)=|֮tKF |z-Yr ?d=Uuc^o tm!@3UW0Ʈ4`?'@rtc]/Z.EbP&}zߘ6rrP0v.׆7-2( JPnGB.$vFMFHU1>8# c,FZi^B@:%+oa4]ΣDnBAz(:( Y2 P=ԡabp2q5pB~=žvntW9][]X:; c3r˄gذ\x:>]Q>ӰG7ϗC3U%$b9g i~i\nh@U2u(T@觅CJgkiiZA? MZd]_E\sl8-K6b31??ݎ /:|[d)Jt&_ϱGqw/& hO5Ox2"OjjPbvӋ K>Os=6y "061Wxs57־$w&xt_vD:c?[PTjQ%zĊOFec]1[mm4"@srWAfzJvu n-`64ͿLV9*z:u#uSfb4OdGaIYxN-wpD탒Jθq+^ٺ9&asS/HٸV5}q+-Eءz MGKUEnsd\Ϯ(q*FLEgS{^ ߐMxF~S: !ʛx,V'!f]1I|k*SA2bY$z%ΧY[qǟ%O74:'3XA#hU-dm?N;97_~LRq?|S`Ǡ|˹Qf7o@/zq *b0wkdRH!Mv q!!?co=$-XʪD__E*:ۜYO䖷 Ϊ T㫷z|9?g[M&JGGk9K¸n/`رdb *w_ڇxM-P8GvSأkFՇj rV&x[aFBQ0ni}&?Xsv1΢тX?2(J@@ >f'À+0P~e:<p˃$+)4Pvfd̜&ZpF|h@Mϕb/+7hXGiɩ>Oގ +GM+"-枃 ;j.O͙^S]z;$M-b]G *#ES`.qG}Z4Sdu0S"Qarvk]4\Jebh[>d0-w':!ꯤvQ@n~nމY}|ar; z>}*E9 ;=8\ːt|!ihM*qQT&&;gAn!ٻ;4M[B%;vxD8rxᔧ!b-Sڴ| ^yyX> stream xڍTm6NKH ͒ݠ,.HHH7H))  !)HO9ww\3H!e ܜ@a7r 9 !6Ys(y/@(7Ȃ\5N2({ 6s~0YBB/H9@P0B@O:00̢6H$\͍ CXܠH6pX~ P9@jkuӡB 8:߇8ZB:J 8Ov_psr'_ѿA08h CHw$;hwǃ\AP{=Ay)-ÿs#p33w\܏YRqD:O9FVPGKmXN.%ٿ8&l$(Wq@6\Cpr6Vm@|V/\/g+D@|o 5f՟Pw^~Lf ssIHI0w/ ^?wM:hNA]_"`kCXLv/]?z#O濳_ɻg1낼_528/A,.UBA^|@?Pgy;R)?zф9Cbo5|?] Cq1~9G0 @?~M-!Cއ{X/%'p)\* ~@p_yہy\A>}z _t..{ ޟa]iIxoA 04 ,l[~Q#EƱ1*y~a1Zd쓛0[MɞS)7Rv]9Zm;㠕߲;CL:~܂ UFчIEЍ#aiݧy]$7&R!5٪TB{ߴ'd9EGgҫv^&U .R Pv 8dEʉ R=_(x+u7BXrײ2KEѮ sr dh=KjBt:"p3r>7y@VA 9 g!џ(Ce)ޖ mne%d+ m['"\ l%kH> g}H5.rҚrrT,S{ 5%q#ZN3;;ٓCi*MGhM9YV@G۰W ,Er>^6HV׳yz&@9FXb2CubyM-3=[Ax!|fXk;ĘD Wls_P4 aٲo#;Ňf믌hMtfjFr]㭯2 = u'yY9t MtM"|ŏg׮\IUXE<Ǟ<0&|hxZe٭Oo!t:B" )x$QS77G; qɮF l8>W.@Ur}M3pr>N_4=.l\G381C(+^afAї ^w`}%tf3E2?h\}7 ߉PBds1e}2[m|eq#n!/;kco+gyЛ5yGۙ>e<>*Af5̏ptGo%.~S|SӏJA.EeABi'mxm[қcN~W2d~V5z"Lwz2pO"=2(Bm&y#(܂_!o$Fb(mf'U!'4 >敺\bO?N^6N} XV}b0h2bK*.7iW_Gg׭tz A/,k fH58q " 6TdoRz,W1P$+LqK6rr +{&3ʥn?c%O[SUx5obTesmՏ4:ttcFǧm[M4Xlv|#RυZ+%E#+r145"R/,?˪ʫ419^E**P! t,T}GŴ 4n_ F)2^gF)80T]jSGl z0pN<ayO^g=9;[Q G_r#F"[n)TDp-RR{^2%#uv">/T6"K&@bO}+PU_7޻2*vL 8 liɾe{5U1|Zx{[8o$'XIuIZъ 49RG?Q܆o=)bc{| B,gq=[z3a?qv=ׄ|Pd+m/V9;׭;۾iTx;k~ wDgq~'~ɁH̙߮\+#n]4g׆K:Nmƒ*x B HX̿IfU2*O0*K*=O gmlj~U&,sjc~tv+><V5}kuŮ:#h%B酻gB(]2WQ?lIt??dgQh\9[%7}5vqj6F61YDT90*fOc :>~v &!,%&dF`ՖM`C' Fi gMg-ěTOi/}:)5䗋 d /t"qRh6%gpsLOIvQ# r6L[OB+U)9kBQt0cI$n6ogWs z"r!Iw׫~u$wSqw)^h,ڎ=n0,۔KnK<1]A 1S+W@4G'EϿ̼q0٨*5ll={"Ib΅&X#Q4QK6 g f楣AS=^j̆ӃcLw]Q-(1yW R_79K;M(EyB:$$D('t$wW.  Дk edXh>qpܧ~bAFhf_Ro>0uw)sۀ)$CR|eq<{}pwAgS#f-sX(q;@$${bRu^L ˏ/ńN%cbmH8A<> ¡Tl ?0,=Wʥ-Ir7ǸCk"˝FZ&WLÿ[y,Og/889Ztu&uzHڝ!D``nwr@PIxI R~"yճa;}F85iS`V=_$Co?t{jNw1o{.8xv#YF~f Pd3jG(DvKY9;|Ԍ%%MuRyUjᣲ>zۼ3IH|˅yC[} k>Ppn_hy:OՔQS1nZ<ڔ{Sq<~gbIN2݉1%{򄫞(pIQMяwߖ>ODieRR;[B$Riz'f.@я|H<*h7D-LkE]# g{0)HBg c;]$&= !)ɳ:uE7 <|jx-0m({N ˲ $NFZ{]q[fïo6nҪ'46B|F^z>fs7~V]\k 0[5AbPbO &ں7 mc,6XIżє$ Qоᓳ~JDkZV8y4ҞKB?O`z t9!X%E~E9s|N"Qb<8Y׼4Q508pgpOtN3°{ʡ,^:z3Q7nӾu\K|:gY@6|Id)%AK$jհpjl~VsOjWzoFbwVsh(܏-+ZUzwTq=Zpz$ l_=iWj=`V}s;5# U1mݼ䚐3/Yn@Ql0NV%% l-K=fpL5J%p4;^JSÕ:yB4DU+xzѤ2,)䘃ۺ!"~ؗ\ k,U8c:t#r' D]Vz0rV_es4{a)nsgUuⰧŻ9gX:_DaS:OnޚjSQOd(@YL3uaԽv8r9Z8aTs8Tj"?l5[aqQ?q̿yS6<#9@=sX = 8g_( IƚT[702H$ˎŹ_E>(qZED=?_ۍZK6]x4:\B3JŧZ;bcKcsjU-Giΐȉ=ap@"EPeω각Nn\ +pxص>hѿ׳ ]]wxqcx kb8DiS`e7ű"DOH%YL̂X5-~ C bJe=DT.#&[P,w cޢb[p~BRj(P,5ux3 R y;Z\a-'U!g,Þf1 تi)R u^&Jt!'@O78EAds,d0t=q:eFȅ¤5k7r Im6pF՝JȻsG$Jk5#y u,ĬH.q%O`syWC p.Aa'1uQ ;QfX3NV ?:jLKl?y(ɚ=SU牸WLnʘr6OKU8դj>6uW!y1\ rt*^Qk% ׏?3{dnU9dP_GULUa:O;@8D}ѬZSj3r6#FC76*7?b_v2FRGAmrri@1-a I?K}y_TKt,5sl)f2]jI\{lӺ(O~E۪|QlTr /E>z6o<@Z:n>4͋\:3yYhUG<ڨϩ8Ēz8pm;X03+w;F0$i]|oյ4ƪ[+c͑_E5e(T7mn 4)5z S+U_ ƻO7qГd)}_/hGb_l&G}ZGfvESO*BP>jy}˄7+u2T&9nf#Ι.KӞO PcOQNL]- ^9 *),1dtUp /1oYE{Cgp)WVLG8 n:FJÎb|z> 7nV}P 5ͰT{680Cz/)VNm?'T5& }Nckv$9y B-uuWom\+I5k{)!+nQO(Ꜵ_ل4sK*{5scQh`It_qZ`ˊ5PGcZr,,T=T QJDT1bslP\xlqpMP;iSqc?"(wT#? ?bLswDcml`o)1hfEReB|Uaީb (zԭcgs!hvߞ3ا*--iC!|QK|c%"F%xV/m ܎7l*>6՘s%ӾOa%#8?ZM)Zy6kN^OT*lGr1lF ;zܓ*72FӲ2o#3v9Ff`.W瑎4}9V}|81ٜp:ܟ~J܄r+ %`2#tO%?%tG8 >%S+[u{( d?7^G"Vp-qIA7^Ex *yʝ--elUr ,UX2+U|3A~WfxgbXH76Yd0WRn.y VTط:L!.˖UIGQP_Dҩ"ɿeRyH=7K!FS1Rc!XQ.Au>PPeD'qf.w`ЮU?=іٙ[!{c|TvxdT!=a@T16نS$2N"-Hɏzlkٷk ؊sbY|#2? F J,yq;dc㉽J?)?/u lP78UҹA, .PpBI6zY)qe\\7hfv= {]\@䳢7oD (Q ˘?!gȚWzHJv.'HFVA &Md Rlqe /S;ÂFzb*/uMDk+bWK4eoh0xv$9K4gNo4*b|H+#W?A\;'L:/JxkQRS]Y3t+/K5PΑL󔶥1%[$q#&Tpס)0߆ư%5Fzy0Nc~)I[i=<T~\Fc>"G{ioIxh>>B@UC]-_?LلVO&[9R{AUڿ`k?.Bz">B#ShLm߅)[I)j] NwxdM8j S`MrQ^z<^@}rҬgn~3o]Æ9DxXPݻ IXg'@t9I"~m3*zዊ!N}5.Ko\Y6!*@tTiS֏2s;}w,l i k '8\M^z*уlL=e MD~5p+!Ԓ~nǍ-1 endstream endobj 182 0 obj << /Length1 2706 /Length2 23482 /Length3 0 /Length 24993 /Filter /FlateDecode >> stream xڌt  GMc۶m7ęnhn8ضچ}{wYYk2 PPRgcr0#PQiڸ#Pi]\mAHM2IS7# n`qYYg4(1A@W* G'o+k7p}Кxr9]lMA%S7k8=@nnN,,̦̎.VtO7k:*l2f*r GK7OS ,1\ !Pq6VۀOollW _ΦN oPVdvrc,~ڻ:M=LmM17HLS+Y~wY d!"'i4ݛځ=AK",ܝX@6@9L"2+ṱY~vd%W!zn.@?Ell s7;:X bg߿ em|YT4_ `d1mqZڸ[-˵~] j`en~tW/|9M)2wub\SSo E _K `a9].&`%qX#o `,R"Vo`,E7F`. o(F`.*"^0E7sQ\4~#0E7s\t~#pvXg/4up˯G޿6`ofhbjn,~9}C* E\`7_b. lU3u=_>_F^D77X9A?Ҁo z&K;/sGw? s'hd a\<;? @pe zp펿ɀ[ ~lH;p.J߷r%qcʿ{k ݀f[טt ծvr:wS~=8+o]Z]C660io7k @X=`f$779p$ߩT6ww&zBmBo?z2 P1.tߣNvZ,ymuGJtGK$G6IbDL~O~v-_ryQT1o=dWFk˧b Kf̲aݘ1μPgg0r&^Hb8|6c|*5])0F}Sq|KVZHsSWИ3klԣ@MKlɀPݤڲ&,cr6(LZ; aZvm*2t `YGPsCMxjpNNH'~ &qr1.G2+0A߷lۅzz!GNrcϔ;7g=1 C^B_̾[sH| ˔~G&Pl )g9۬a,&ULZ<,┓[4xm{W|]UF{4v<$wmq}]Q!nQp&OhN.Wt(⛝^x3cMq28TMGOr9I*%~o~KEDq_5uB }D[Ma1ܤ}L NyO ѻ0=Cuj׾ʠ m@Mq!Dlټ)ְLT9;8x%<~$ (,XĀ2m%zO,TjPu%V!dХ I!)N;#wrδLh0#צjC6";n~vNQ Ye؛pQp;s4XCuq)ꘪRydL4ϓb(5̯$!!{}y`k('{'~&]DH/XyKs}e 㛈\A4}y*6G|!6q+ ,!CKMN[UԌ7s9 iAk> ~\kG}( ⊟JwJ9qx n{P.9B74uWu3ʌ(@ !^ET eWaNSv_̔߅c86u;H0@Ne'F~?1@g=1=7b>bxH_s:7[gV9nU"e;} XI픹͙*E:^d;?vٴYąDk/Xu}(&oL c{no:nD䬿;H7-X ys߼Z^K#)4~zR1T-s[Oh&qv]ZawWa>ʦz\Ch\x^aêR+{6X,z;TI4YqN0% 6n}v!R.yM$HU_tLDĥ592{TsTB4ƜIAx&J@U:|ȭ51u&Uaǒ!}N37 E9¤LӚ>CKDt ,<}]yp5fQ[X@vCc_k Sր^ }` FMàSPZ(|pΡb^ػdjfMv^ފy0!MQr{[J9Eg$E+-=7d<|JOAc*bbx#I{ 4K:˓{!] g| xiwxl >1٢Ho^-knlbUYHNbfne'@ STm5^Cio1tؤ&NfS7V 1^WSY>x%N?үK]Sbu%$-D)nJy!&#f>At}ME\V,*xy8LB{ܠo(K ,v*lC2 o1G4.]ѷ=HYA>~ʷwIcSE|䲬sǯhujC(eG#b0jvNO2{}YvS:ϵ#>=ȓ1^zi 5bhZw Ԓ{Wm4qcJ&!Tʭ :%g!n9YYP2M\׌fR+ :}hFDk l=gK`9>]Be\'S=~.1 j! i/\BJk[=ix]Qo À;{GoI)YdwM"mܟIm{ky$c <.&9%햬L>-[x9-_0;|E+ Ig+2/l5F7amޱ$`~RuJ>Cn,wt6l{uJōM7]R*?Y:|VHXb[ٿGn$QPڛJXٍQ7ªv9%]sEvK h5SqML"2(%*U:q؊Vbc@6@@ ɧR3n`UҚf_Ԝ *g?g5dxOdrſ#_k+˫>DUfD`{E*l&MY6@`3!hq=^Q-Mk 9ay(Xd7j҇MB@78 >Q!<lO{>H G VcqpRRyF,FʦTmph;,L}MM>qG6 )7W:@uh^$U|D)$4*gHviEFW W.e{mPRՕ) ჉!2)Յ  J\ۘ%@ 4,)kk5aGxyr&o.zپO:B`9O`<ԮOI`H9,u˫38K-vm9Giw V9Y٫fJX,96R2|-!)KA:Trz=KFG񺱩Y11hvvlL4JEnx,saDmf<`U ʥ+4"\邡xOm_?u&UegV61aGwԁlPTBb0 ]1 6i} ܬ%kx̻Q9+Uv*4dzhhC$$s{gE;s/WwӚ\=mcd[.ݾ NjcJ7bigIXJ>&w[}>!azTqZ]$ȓ>;Fx_c5?sU)%x4zCl +l9d׬#Ƀ&hЁfLcGmt' 'Ij^[w.c׷Kln,ѳϛ1gk٪@$`-˭)K! EOL[d*` =ʹ8rXEq Y1uz4X?.fقz I Sy<#viypl B"~(zB]O*!P^Q΃!0r)/h\%r]~$] >ۘZ=m1 Oz}پl\vBߊBTbϯ;l0Z&h{~jm>n4 ϺrD?ț@cT.)4UV);;v9I%,(}{ZMk`%][j~k_52+釃]D{VaGF'a)T S㺤 YI G`@r|:Q~,X aMHcO5jZ\&o~rzT}qRVXwWgNzCJ)a0cHv%9;Zv>ηѣO˃NS66I\ƴ|A>_5 /Twq7j4ԊK"oT tT˙-DRŌqW%VGX^k04t#7c ٍˊSͰ"!J Ė (NKcw]Z8YK.zCJ4rFvGQq$?@=?_5md~ERn|^<|[R!qJ4%iI5r/l a推ms!Z*bXA4(zюbO'@>YzmϗK:ԞoEW P䛮;EA\_rW}f 97w1eckNg1?Z(#'kNd}Mi6pO_@ǚ2b#j M*ACH0Yf~s=Iyξ"] [Spdt¸w 5KntQ/޲%ft$@[yz0kC;{^*jCjw"Rv_#z~tvtC&=c5Ez Vx.)Ns-V3tZq]vUX8MS)"k@]c|mi&ɰJ xRvO7-j/&c4Tn+غ b.p"|bfHDY=N˧Sȫ:R8rL'̣@w<3yޏ嬫" YX6З{L1l[I:U&&^adž\e ҹƣG| =Jfԯo`|o.&$3ł$!$=r*d[ClҩPfo~Bo:8Ý /7 wL~z ϏG3\_Gxl޳.G~`#!`)?P}]|w0(K)P5qЫt!Nsi*C \k&A;wvp?/l: 3m(N&^|!ړTO)O7Dl, kz<\qƄZ~Y@#%0<hwGrѽ|2{'r\{&1gc폕_KԞO>ÄIɫYlnZ?iXh/;_Af^} T,g=U5t$\QtJ2\z On{f=:ўdq+O L0檥D5Dƾnbk-1uub҈*3(zr}jw9Mt䉒0mU/$s.f;$7#wQC_R~5]JUxؕcH [Lyj cg+ͥ7o,ʕh,/' ԹʶgqrfKqB[#Jd2:x4O I!j鱠9cݎXdӷ xċ sDBrlɟYτQLpqַi53BAZu3#Z»hukJ0a;/]BmeF#C$S X4d55c g3$o?e~9l@ b5ۍ!u,.ZGaǖ ÊE)̼4>-fX֛dz<.Zj˻ "WyUQ}Vq53iVnrҗk &(k1SMCiYN~u悟0J b5jϝӑϻps^(,y3.[ A[] *"uL h-*M!UC{);i8 0_ʞ7+"}FD9ۣRtX`Bܞ_!.a\] 1kuDއF^V& dfA3|m~o=m'BBTBlǐ*B 88`[|݃~,9#6/VC  sj8cS -s 99lT҈4Run] m v.J #BE-wB՘tO6 _)^Z~R[1 [ m%G%oYOCC&P+nxxYJZ 8%Y|9̛$L;'8ޮwqx&bF@h@r XCV$ѕDKnWI 5cfiRVYgV3,Ӹ=e?7u`ɸo?Q8jVY"r4,!op+DM 8֯jh]tU"\~\_oƩtzc&ILSI|B!ޥl{\6*'bŨl[4ьArz)cʚ}/Φ,xhp4&` ذ@%6䣒un4>vxOTׄWHҪEl(VPв[P ?푇*s;WLAw0uCuʹ*!WJBTp?}8 ?>́9KHCfK)+ʷh-ezM6v e iCGS}E<(8 KBjaܤ3*QC.sq#bRM?bj,Pl/5(ǔs*BVND\,XcW{|ŠuX?uLbԍ\a&':lNi ĹuGî=*A~F̹x8 6CWDo2 sN#C_u} {b"VzJ5b^F8Dž:!J$-~(S'LŢqQe;i78V545gvET LD߇|SX.\v 7=oAh :4. e? +OKaF;.ug|ּ M@*윌R_Łeu?=opC~?'5|QNN77x3hE3=2G/젹, ڐ`WݛsID'yע_8[3q=vY*HX d=!l=y靨Q*l'RLOF*5h+ ƚiC[3Ѓ`X蜥zef 0g7ޱi4(/(85x_;|?~Yx@=z}}j{}c>OEt-Ko]lyZS;&C! MgnkC{4sC΄LЃ콎QHI[%왗b?jnBzPHjUS6?75򣤸V]f)4zx Ə1Th)5w_杓NRn_"u9Sq|pK$m<_:6SM: zP{tԖJ=N"Jdc$wqŦFI;5LHEZ,OU{)PguɋwV#džIya`кs yŜzFC" h9U_J7ܧf5䤺ʱ$}lJ 'SV1̧ecmq??a$7=蚗nJr&}ߠ- 벍/?clV/#U5gW PU}-l RN9Q m@rf֗~} ^u$+bO3 J'yxþOQz[ALԖ>km̀x^Ni%XTm>}1bNӞ  ˧j#Oj߬Jg,s*lK nB 2+қǩ֝j#gCvΖu6n-x6vBۦ#fpD21mJp R"u2K(q2")cu]5E֦=4sO6Ӫ+N^mNR=?~gL3z0T~w(R|D _]{*P.HL!rZY!^Xgɘ4uitѸDZ#-86#VW~"W9:MYˎv#M>UF"bOZ~CZrrWX$uH 0W)G I/(>q"z;@C/4[+%yl!)LM7g'/KFk \f w y ²Fa+ʇ*ߴ,e"کOmBbgތ^G.$KyaC`̔nDcxsU6`-zHv >>7rg℥]L-Q\`.u@(2hGw]XIc~ ޸w?Mw?u?7!(--Ial7P`Ȕ>;'Ձ(( "'fi`hGB5QW@KtfQOL.yؐ_0ã!U4¥H8e>vE4㋮WO{W&q'2ǛxzךΏ}Lh@!p`F<1Fh2 đM ]d?vJ9xɃ,u/Oejwߧx=J1!"ofGSu@ʎ[*1/wYG;ճViL7dWD{ﺐU'?l=J30ֳO0y+3f~G:;p|D-(t2TC( "vA*}IsSox Fa&q1./ $d IQ,}ԹdM%D$0YK_UQDw$lɴ4v{9 bF"h>̒MB']4dXˢf6Sw!:̦.>/~uT]WDsY7^}es2ŒgWBp9Z_/ŝ2!@/H'1{ԖB.PYc |2gv_,).R]|pL9Q`$fPt F6pn.%.DrƉr)tzH1WW +!IPD&[R<5a,^kp,,|h"9O"C:V^e#[$8NAJKF'*~? }&63& ]iyA>RZ"뫪aZz=tdh'?[Kw}K$7{,.'W=F7ֵYM@)k F}һyxT# F!}NzJz2zz{*18(hUl2誥l4$0O.$PK ͩ3-!76bTd/f N[!F|.y1]oDYR_o8gHh/0=b=ЮH!EfflAvf e4Rvki6|lMy^4f2\c%H/Z7`*ҺyTK)v7\V㋩)<+H\/lCZP*5U9uLhİHwb2o2.DZōS VpL- y[5ЩGº;6*']qvmڗĘr̫hH:q.өt˾d 1(%*.TnFlOG, 4Et+u3x3, j_Q6Yf' SwϏ'}ҩ?KIW-9h&:zg}L WzsZ9vyE( #&X1`5 [W+eLٯ ˻78?rg#J F6ްg<5L|V 丹lU.}iE>*`{lo" g3z+&8^HT4%y/-l{ZS;Sr\XTd"y?qD*2:$2O &L}ċKD({>{ ݑ^=BtԓG;BR_c΢!i΀tI]=!/~w#W(iQЉ}>_ɿq +?5crP1Z솝} ˈ>ւ^ш-cҘA6h .vזny)IA`UjlZ>bq-xlYPeU)s2g&# I =@tESxʚT FbDl@APC@XNW=Yx =q@P53i|գ!ɥOg[(1,o"csb1K|E 70\hIa,oťT L5AW{AE75RI2ǣ:!LSpwU8Hc@m9D*,GBR \YY Z~(f"VLU)ZQM8)['=5 bUB XhМ;*9sRtl{D- ( V(\vl.؝;9YCM{B9q:4(6>/qLYR3Շ>vz3ӦCrg-;#jaJХ-B<C*\._b7P0Hd!],6MY S F oߔxuA_2Rosӯ}sc!FEa JFrA8ֳVKYq,3kٗ⟾0Q<.)]&.BfcErikOcsS}5li9 NPWG"Yq=T w;oO}cT+UAg!oEM֗H=#6`\.WM@ݑS #3(Qo, Ƌ7{l`gM 'm~F#|Qs2HTs-nF_]#QGT[5| QX$E b\ˉ&rvm%LGM·Fmx9vrA MޟrGy> 9zZUt!K0KP-yihw xV)Ojyuљ KWs/E[ OnQ7cَ޶XK-(~#oFtu7ݪrNDZ(褎I#/ |oD~Xc{hk7jz eQz){SPf:>Yjx%P9dx7;Lulz8dal~V'Y1J2ĺJUs @0U,$v '}5GK\pgW1Pb6iM[*ЙjD#Yv5T#/K; 9۟jSz?>O3q"68ݚ%4gyt{? _ ЖAVm a1x@O^Lt~L+??'}TD ApCG^wjit)/7 .ijP 8EH|0۠7+a+0w蟦j #GsIM>;:;fe0<^Cmt|7ӨJ)x(ÿ/R08wMl?o`t!3'>{|9)B9t$oXY=8ݴj%}@d0ۘf>D&ДNccې!,ġҰᐁh6Mz&tL֡qfbу[҄i[pb̓zn?y3n3ϻq#Af7a{~)FL# -G)ԣ%vjd\-AuZ[l܌%J n^P( ME( Q`tK[DoRQ9#7baY)]_JÜ XT&|>)WEw\3->H (OQ:7KTY,w|ō:[(J/pc}ߚ_gVжhY"5>jyg.>s;FWirb:Y Rs(0o s4XQKLn9RV/%r /O$)PQXhAi "^T-|L#Y;e7X2z -`CkF‚I#>i--IٝwB]4޶*m aT*CڿRƙn|t͝D:MMBzQ퍩2m{jv|CKm[}8 C#_d9`?ٟ>}8c{GZO Gߘ+~j)J_Wl/jVq,EY*ê+ztgqA=gsK0 "۶D{sCy=ПJ Kί՝ лN'aƢ&;WԤQvm"|(4pW(дWێV$uzsZ/@0rh0*ba ,DMF rTDM\/4t;twu]{KGxJq*zI zU'G{OV)G>:P?T+=)yO&%=ydտXD9=`rz\3)WVvFF_jGFLj S5bDL.]7OLׅ# Wr[kC2|2.yLuX*--g2'A/٭d!]5Yߒ Ϭ "<$|v̲`MoUi9@mV22]_E #v!X |>$A`*V1=S7Rژ1ekP4pe|HK{޸DVEj3k2)`B]3Pk1rk~7xTmn/q:0R;"$>4hfcɪD^݊+$mAK9 +cqpT6c]h"pn>A_$5=)'DP! J' 2O8ziӛ}zO 8ZVMN>4<_`*͝? =w҄#e530`~Lv 9Ƽf1Cnd-:I'M5A| ((Fqw*ǯw k^֖{?md $4i%6@3eYֹHO<렴v xyCۇƋ!ه-IUc*:k{bt38/M2dyA Lu¾Bqy&sgqЫdD3"[_xOH`6Iy_o5qUZ-ASOv#BgyTd-|_j7D_(94^p]OJ 3Z̳biYdz7Sh%Px ^N(`@~ԌEW-3|N|g O _ć!d]ڶzV=}qsQIo1]n؅Q˙$i]~m6J7Bw@:@>c@RLxZَP:ٳas4~S^gz[fۍrD$iz shġͿ@C=ÆaÆ!1x]蒄t!^iЛ1/k6$6TIeYZ02 Eh2Bj4r哃bFZ F 1?u*G%⑙1N^UF6>ܲ?fD?6'4)#reL\tVH*&(xpdOh՛Wl"_ ~+is VqjI]"E1ͱ7C}]mIK!yI 7.w2B48Eu&)ΥXGdwXti fkAY2 \h"wo<{uT~UZ%= 5xڭD;.XU"s5.ZɝBK;S x'd!1O*0=fC~!Mn/tΔ >m\Ǟ7r̭BMKx 5,Mb' cBE0;RT&>mrhezoIr+3:By2Fu[n $akQM B[S$;"$ftv'\ 3' 5 04-PcJK9qepm:|, wUޥ) <*uӂ9w:KVr]>P\dA^ܪZqggŚmfDegLJ+8漨s3^EI'~dFiM4+oXC8I =}e[jI#bjl_C'`_ktyynf<R~h)"ėt_GՎaBpX$-/MTp6!S'0cV9~,B޸ߑ߁]jgj2<[0SihW VM[h56>~\yh%ʍp̃YN٦6C#Z>N*"g䰃HMg)qEHXO4-f@YnrD,^,NSJQB36 ,'pRDxTnϒ;>{G}<5D7yUkYj%cycg}$ 1<[`;sVMZYR;kZ\rv dni$F>rƞiDd} ͏N%0/,PdC)L腘2Վݛ#Ŷ.hD$W>jPMސȄ?lVZjYRqL| @dZZ X[SPWbGϖוWkF}2T(t[Rci@oL*Zz+VRs]$2T mN~Bf9mgݡŃe&ƕ 槠ڍt~Doj^Kxݘ9ˆMv"h1GЕX If gRRV[?Rw aJ}} PWsma.O];X; 4degAMj?}_ <.=4qʣb'*`xy6ƒk?7,̬%u\ ;yNlj3 /e0t&# @9[Jru@QIC-<4GTӍ`:WxddS 6u乸ezSo7UR(=zL7lɷvSP-ǽF?Jz2x0>NBvkm(}ЄYtXy1S vUmjk\ h'4Xgԑa.2hIՃ{ͱYь䕾c2qg(g%+NejJAtcDtM#HJT _DiWLVH1B~|:lw ԕ nUPY f}Nl ɰ(`_ Q\X%navU :͙u;+$ֳH9fwY|:U85w=v8YKӍEq|WR3+]ٳK$+c# c<5SNk.R(o Z)dc^QePd 51ꆰ\:П,yA:~rf5i֠ڶl`TJH̑a 3?LQ[ V]A9k^rR0@P̓El9?/fWS]x߽IRH3ER|=jsM.0ť*BRlqMqȋ'6=tQTv%Դ OIِ-Gg DU^j">Nd3;0סxqHxXj>;TI؉]|fMbb| Rf86#Do o;X fs4x"q`^f9 +,W_fFe;W}`8b hXP@VfQh43ؖxi¾[pGuDƬQPFG<U}ƒhx~^4$NP]>{{t Y,AӄtP넄M_\j@hQ8mNq--ݱk,yńoT:>ȥz \ARЎy 盋GF `\~]̓z'^ԗ\75I3L Vj(Ésx5\DG2s~!Kiy";BkrKHMmCgBF;NAUCfbWL |}ݯsF^.+@7"Q1Hԭd,z endstream endobj 184 0 obj << /Length1 1736 /Length2 10325 /Length3 0 /Length 11434 /Filter /FlateDecode >> stream xڍT- Ŋ[(n]$@E(Rw(NV\P ̝{VJǾ#4:Ζ;7@VMŃFO 9냠n`gȿP$žxj#- -(*zjeg ^ =_3[XXs Bj@)l "trpJ0<0;6 Y~ P:kvSlBA'# q{pX%U 'YO௷psp/ߎ?VVN.@7b ;/U9`^06btts~z@'/* vq+Ce@Pӳ{sY'/`X.݅Svu)Ey#\\\|+ee۽ %oS.."@`AAV7BX`K-'1O|( `4{ߟ>3TД3xegdd|v~n@ ^4࿲T b 3٧WO`/u秡q.~./Io{&5v4Ws~R @Z%i!?#% d Y9,~/#tv*vn.=mp{?T+g/B@o4Ar?5pr@aO&6PpJ2 !?H)7pj#aA'odt$a~NAn'_)Ϳ /_SO8 >e~ |OOܧ /SпSs8aR?Ev<9S> j;tXNq;A /✳hirOqi쾋[,TwkKO8_.ԣ&kݛ'jO-|!(S[,'VY]cnNf {5rDuٔ-Hd2Zx4M?3gU{]Gl=JWW -DUDiz1NeCDn/|C9"),̠Xٱi;G 6c QF8~r3^bV$/тC}{#Keslk9wψ%:ҽ>j?0&%6ּ5#n?#x];HG?~PCj̚ˮo7 @ yhnm[iCph7! v1'0L`* 7GJ}EOfK̓;-L]Σ1&B_GatGNt95sزpS_vbJ;n+m}C/lkzY/îޟa:i3{1n3ZaG_MĂT+0iSG8IU+Y2E5eaE0ѓ.[,g}F}3dNZ} J@Fw&_Priμa=^1O#”L-z7K8iTf!LϱNe TF):q_ۄ/}G[B2Sp$ ڵ_$SB@R.!RTƥDrNLt.sp>T LJ^_HDZ$.)'ڹzWͧ \% iYS'aJ^,t4_mHu(E{I8~U[[ x'Lr9,قP$|-/Mߒ@l!+BY M; s1VC_VL/U^XZpLF]1*Z×*juMvM?zff,lJ<߁vSǥwq,!rƜ>g [toŖ<%ujʺИ%rE>ҫRC0ON]cB6PuK>LMGޟ͔.\cq7x*Fr/6J%3^a!NK(p# Qo1BX,^y,}nUA0)wHG!빙Z&SŲ|$Xu.=u3r:mߝA^Ynd 5r`GvE:J55"7 n}1U4}pdO Sb\3Ug-2g=Ϩ½:+tpn0zփ~=-uˠ$le4d؞<+'(Y_Dn9]N4 ~1B٣!N.]!.Ll/kl +q)G>g &D㯞{>'76<&(d*R SƗ]݉!tduV%7zz#Kq%BȞ``R۶v ;;{eŭ{E#GW.D,~9Ru4iu⦷-nB\S?9_ EA IHEJi1\Z6=QwԤkY9 M?_Dc " W̯R3G%d)ZoMìUeܛ<3fYg:ubd1*RRoc ^Tm܄~A N"S{EM F=46|(CGˋrQ5҈:&j9<׉&:x㗿^uWgšPx`q*Sۊ%sِ.$ݽDM Tr}G=<敔ɕ_C JG8-amѣN/G&TC~M-`[91K ,`KhSW0T]KMs 6Q`\n1]㗥;ZUmòV*e[ՒX;m1v*54`p`e7yه}iЙnGd?x1F uErKY]-]feműL{ Ƭw^DŽIh~擄3{F)Vܲ{ŏ@5ėe,5]M}n,VR l+wso5n &IJpyA kNj[y](&]=_FO]d+ TeZ..q/_8= Uzhn2+Tohc1׀ķl8ڴK;lǓ}@(a>q̀[ 3|`Mf{b]yFL^`dLkh=KMCՎ9WK{yd峸3V}R"]39`1c?4nsi\5cf0&ٗ(4yBcu+-Սq}2V3)5&vjRQ][^קWeƵL틏3AdGM=s1.Kur9 -Tܳ DZÂ֝fAs( "g>½cL.i!7N5H$MgryNƢ5I*K< ^"͈U 4W|8?_L \֏G~QO:%FF:1KߢG?}ZbBBK$MڳVX ZTrXG25уu L7Zm_o?CJyMJ|+HG$@N^ۣAjvrdͳmncKz'IHW7]b&xcmem°m[Ă{8a]bo6՗./v0mRgaZV<CɃz$>Iq|}w"g*9|MJ|x409gwSvL`cV˪IT< 1>Y"vIqYY:v ѯ]&s957s$Ѻ8i,_!99y{*-×ʩ|V{<,K&* '5?qj:sl̨8,߹̮Uͦq ^wJXΈƶ^ !eO06Q񶮦} [yLJH&hT5 Ǩwo{uKNwOs:&V4wH)]( Fǽ8ޫop'>pKGwi^/ w;=pٕ7 b-[p*C]#GO+{Ux |WsZDƜ-mj;zJ+ B)n3ļypIgkFw#H})Ə41F"컁?[cB ]SV&/7^̸$KٻioH\WI8ɒu*gJ< bEc?@uȰq#^숔 0}hCWNpsV*/AF0wm-{^ѹ-H^k'/[y_FOqP!e6C8 W;9e܀!A^_iSG?PiI8^%m0y" Xퟁ 0.PAZ;8ՂqiTXJ®UhK}=SN))fv2JGPnQk- [̆3BӃ!/WzBGɥoah M/ݗFU2'D]Ixzz8z-n}C/3ޕSyIgٜiQ7(MpJo}c,08-rq|q;|Agg}IN9sPk&hVƁ?PėMb_L#!}[j&\{Ah xnvYߴªVT ˯4.^e@E-sjt]OEE^dJhrh+x.PC>񫣥Hbb+OvڄmpXwϤ =L@AK ؋iw`p֔ ,aekg=wwW|XENL\2ݭJpf¹vr^a~I:1[Ҋ"TXy~}yBfH٧S6iA[}3K/՝tɦasW$܂lc>=:B ?y6<5A款AEh`[YiJh SC@W,GxX{z sn-虝t!ѣԧ߬a#𼟠v$@T57.O @B\ꤕVU}-j}z8?b)L@d'Ƴg>!B*WNO90{}JBŁVɫ$z:^]Ls6A@[m&e71l5fv1.' _mvEQ5*f?̏JQhA\Z _NS3+2Zjlᦏ:e) !"rT QV$`Ҭ]}^ 7kpZ3SLS;{2&$vĿ9?9 yp<볩UڊZp>amu55Y1//@pAΪ&P.NXNfln6ѻAELoFÊyZ?{Fpt 6}r;rAN63=ܬV\Dryd E oV$5{L9iȧvznU{bёQ)-#q;$!iK3.sFT}YVB[4ܙ߄$ endstream endobj 186 0 obj << /Length1 1570 /Length2 8430 /Length3 0 /Length 9460 /Filter /FlateDecode >> stream xڍP-ː $;`5Kpw \[p . nᑜs={5U3_wջ:9$:1yll,lljj -o3Z A 2qzI8=) @9g[ ;' ?;?_0~ AAjq5zҙxЁ T4qAhfb TANNɎՕsgj G a Wg,j/:|2؂@P'3|z9P]VlWYoD` bguC-`[PYJ͉ h5hb{⛸mMLTnU<5w{f`;'GGYy$\NI@fOcwgdm0W 5݄&l ;fcc 73+5@OxyOM  h6s,P?AwٞdaP[9_Vy Q9ƿ:OL d2sp<\|@΢b Pe0 _>M_}t=s)D Gظ̞'Yo߂mm?n':;=_  s3N&O{ R`7 /ed`(H}Yf6O7"@O߯o;IH@OU40 szZOȪYMfFc5d9O\ ą>q@V7@V925&3g⏐f/V@f9@jQRWqizfEv[LD 5Kġ-I %O!-wb&wZ _' Eɘ5Dg S:ޙS%[]_oUo1K?hF+5͜%Dqb&Gc=qÚ͞xex|,[爺X)p"~MGDx;:I)$G8Y1e#A. pǷz\Ur= > CM-v[` D 0bwzPn(l|cSx d|^ViBAwljed_C/o..ޚʴpR^6WToBFh?Zq?ń \GIi(nMh+ lPmOI'FҨH򲴱˔%8ҹ_Ld]Wٖ&KjG'iLz:,#Q8T>*I0;I˃SGӇTEXTe-IG&wy彶]L4HĤۓn3-U3YɊvvDDpA ĕY۳w҃W7X.BCqqEQ#̰S HֈFѹ9 2ϋ.8CL.$-C"2g%V'= U[ dX1Ҙ>w3I _\Hyɺ /X}[H֮j78#y31j"AWOqx&E /oCޢ( je>&TGLÓ~L&b;ȧ$Ȱד7لzHhS9_mϡB6yQu raF+ǯPډ17}Gbq8>UhL?y$L2Eߦ[S$+ǂ$?Vi 8d_\]TJYL֠h-idiOm٦|wD쬴h&Vl~PkbkFjӫgƭQ&tܹ|8 qIWyݦC.S4C:{UUhtd5 %v#þL/"eɏzl>R#[)}>tzG;Ð&?"ZQ(elYc68ygw9._ b5,ue%7\QY`un\t*_.ה_M-`;d[-uyѽdZR0@ kȢ4QtlD+\":f?[WxkGwl({-rZ\=ڙ"3Įiunr\pFӷ(OXa0Mm櫁ovsн_y 20_|ƅW":BW,O:j"龎Z7$ƯX<Myh0v&z:XG9 E+i4˶-1 Jҗ2Ы$/[ 3̩ e٪jϸ33o~8־ f`*!+R"K\Z5>(h!oggnwkyOnV< Qآ*IYEd6*rN$SܘW;M[&['s(ǽ b(p i9ܳOi">C8vڬ}֟RՈRS器O[ۍ/SL~WRTNIÖml52U crVk9!&hoaE f$ҐJ1Qc_I%xT9̕sR#gCsCigdP;n@bŲq[4[T7Fڄ4>en[,=P9⠟_Y!3n7u duzC{ep҄pl_D$HuQOe3lE/R%<ԝY~e'a?KmǿVx(ौ9K$ =*3Wn3ҌR6JTSphH5$#`M?!=?˻,plDꔡ>W1X/JpB̐*+QD>&^yG*vմ\| \EFO V6h3 yn*OViLTIB,+P宱O"i|y(<;3? x 2$}!%^WvFYf.:LcasxL#Sυ*%\"~\71Y\ͽ} f`{t콋^2"JKؐ,,g:|6 R:saU2f_ڳgC Ε2'Qą>+y?$h0Wؽx߆(`˲px;aכV5n}XE4mK,Tow FTaZn,y5f ؃^ׇtj̇O!yhTvȥ^nѬۧ(u׮}ɒJu70mR7>PF|ԪП|{Q}S~8&T;Jgy:T" T68WrP7o:[(3 tkL򬔛`$ SOƹ M;E4>v,;&VPVuA#VŸL mG",Xw&DQzHOI/ a_?_W%*pKx Rl)vReqZkAgS(wLYoMi/"ky;#&[{T*ˋeXdN}mYGVVCc̤orĒ@ŏ?u$3 ^5q%Lflۡ}/ΉsӼ_W I۫Z%K~m) BGH+SG?eVKuX}- GV4d騢3p:O­%fIsO?ք1\cFs 2*4 WEH'ln)/)~BS2D&by!g4zŽ{G9T͒X(W cSjEdD&:?_vRt q~{#9|!;ran|/qx\Fp+H`Oyܹ¨)Ve/pi8܋5Vz}V&B&0f*H:|~.ٓXXO2Q؄c~JAX FJ4G?_%+ B-_ (4OޣYH;BV4}K' KVϐY }Sz7:Cק^wH-q5xI3d t!^ZO oZs޺lg x!J74d34qUQO9k d b5acB, ϼ{ %۵OlҙS?uHQh+5*cU~R#KѸJ76QX/0^OyƏn+&b1k'LwQR)]2V|ͰY+DE[t~1b{+-RIr;]9I_t(|=psQ)"$iV03SѦ RϳT^u1yIgL+|y)GT嫕%ؒh7^ (4d\ ew+t|xsEe!8%_%91SI;y65[xcf2x3*+yX^g5|L'sFGkY U8Aum A3Ջ5ΉР#LoW|E F5WG8.Ln%nGi.I:>RV3)Up^E (ړ,&܀K67=?q3T)&\1_,DP?7s6/~R5QvJslSRʖh+`% ֏ W׈x=M0)y /@A 9ZM85GZũI d΅Kv^E<\!b6Ӿk%y*tK=vM>MCJKn-9抣`$)Jz-y@_׃|Tn.u'b~>fɪC\RGVTvcJ8n#-]ӹ\{iv5̌lQ37'ÙkaSWS |wyfz^Le€#P̏lʎ~F1Bq]rlޅv~xE=ja'+:4:،\-W XH' 0܍s4TV֗=Rah7㍢~&P˻)Јڈ%M֢w`Wq2 PR$i (3 5i}QPJts:ןXiP5? UשOd s[OUe+le;nScAƄh>y!A'fc'Z1ܴc!w t-| uiDu82oװC(K5%fWvcF֥emY皳;!ðSP^S_gHoHJ’1'M -ŌYWeev5YQް$";NY@σ3 dͱҽ\τL}K. KX؎/98q{Dn3g9jP|2L@21tF?VzdJEEMYSBW} ho'C= b!M輽|tA ,EzN=9J2|Ak煡omݐo/D %wD*cV{pe-ڸo2ao$W5?yf;Œj&>.=+ϽlȔ4na =':R$FwCcE98"ez3Qy9hr-z~䩊cAL? eR2^xK٤N(2\ha"Y^nt`sع29Tq.kDž͸ Qϊ4vݩIiBz2: q.il9o w1ފ؃xyz]$vh@]x"*J7| <4r?,;I3 t=Қ70%@q$tpJ1cSe"8 `E#rS+˟s?I}`iPO97YBحQ6+n^Mj%9U!eꎗ/ b``<ŚӜOh(vN%9D'V+ iWt˱shlvoR(| 㷮Rǂ=hɠ[=o=FEn3$3Pկq=DDvDQ/(o yzd}FaƗT;S"6@[ʿz$a V>B:5mX o^[`1I13E1ZGhHo_V_֗A؛ūDPtZ!k%R%~aCx$@8l5L=EuJc|oӿ?ҷ~d9wCXΎ#а&SۑQx@W8? ?,2of?5郆 ⱓ7w.4{K?(ϘE&T[0Oc< NF6+ iIy~9 "67U 5~ m`{+ 5w^lS|(.aGO o6kǩ0FHD}&Q;\]f`20*D,{_ +Ӛ,CzDTU_~ ie< E*eN"Y5\Qa3d ؋`֥ok;I+R;?˺=spsT@ N>E.dĠLV!FpΎ)FQxnU/i}NCrDGH](ZK4r5,xq{>mS>l&A•"Dʚ7J#F8v=V$ c0}~٤$wTsk[?*;4lpv* ET"5ffa0ܱ΀U endstream endobj 188 0 obj << /Length1 1370 /Length2 5960 /Length3 0 /Length 6892 /Filter /FlateDecode >> stream xڍwT6R HK7 tw03 ] !-4()%!ݍ}[us]ZD%m(aH.^n @ ~nItma҇!p d `Ma @$7&ȁ=67 A8Lpo7=ߏ5+**;vA0@ 8V;:pk(H'7 wd؀R AC$w񃝡NuGފ@ ~+C )W buwo|+iӿ E(@ 6P_|ˮKiNPDz\ nex@ܒ rYm~ɌOPq@\|yohMcGކp7_w*h2#ۭ~_mͿϿ xAq&ա-gUT\˟0[z"_s}U?q)'Hќ, b92 KVA,qvAhlvS&hQ[$L\ wV\"VE7g脀. +ݺmDǸhdJGfꮫ5w*Cqd۷ޞ|Jp" be(H2(2'c](1G[iuiexE}gmF_CE)"W`|d}hF/jN~0(.5IҪSPbE,f촗oC!vv5!}Yw_,a!o.oqهW؁G[U,JLقdOhBS+B>1| 3^iAK c݇'EB/=${&Q%:(wDq"F4g]L21~by*WH 4:t8|-0B ja)-9'Vuj:0 @{<=- mE ݖJ6rJeCޖ7FcsC;۫MAU-gi@1 ELCӳВe # '%EIP?I{pC2bo7j9>B ]MbeFtsWc ?mO9uJКoD^):4$Fչݣ 9x)&UTǾi1 טmJrHƑH)z!%_B 2~Xrz]Z^|.̣8*oX!YI:4DF:ɢ85鵣v]E+ %r$s۱s(e3C$vol6 Gkч AI9*4Gv;?+$GvoK-$Y-^ayr+!@Yg)ǡ%,gAt\ZM~™ԴzgvQI0l72ʎ_9 LQ`gYS7޴Fwt~n0#7W&DX%/KRTH#P71v,3V\hj$\ۺd`8 XdM:$w*@^EWk'銳#], jL|1܋3iwcݹ7^݈n/Hn>}0Xy'A `?->P*t.WtPD:xX-dL.Z{|J Dr^x@ݻ@Pg ]h9sēSIa/ Id?A9[IP >=~fMk0#(3uVHw BGfo`3ZHڼ)͝۝R*c9kG{?LFOokw-qaKP_з fVd=џoK#3df½̭ eԜC ۂ.pjRUpY˻LXkP~+h;+ӱð<wE&\ǫ8{X͍pNX]ꛃW .s Ke6@FqO 5YH aQCs;N)v x8aN˕SdCЭuop,a2jL@GR+=_v7e2t=3h18P .Q̛dݲ:#cAN([ߦVV=>EN]ZyZL.dk*ƭٗ d:ep9xBr;֋p3V? O&-& |ga0$_/cY##Loz#< a~ɠ?IUD|GֱrwE "Y[7@f|,Lz2͜ߪP dΞ^hBOhggs$t8@6\AubTWj<,Ue_޴ͻ#p_ɂjͥ־3N*C&F:9Տދ:D-XW`/q.R.+DWzJR̾i}.zv:~P/F !-rMN *,P~ ߞ jV_ Yçb4%7h|}Z^O/=+ʊ٫O9XӕnegM^Э2KYTruÛ`T;e U"o6o)cSh4&l&"7%"a wã:mL*yloIkew͚XU@fù))o,].` gmc;uM) _0v! KҜ%G Z\ݯ7GJL|pu+!y]>KR,IyCUrUMӐm3[˲cV-CRJ V>Ԋ Dy>mtU >CH:\wX}s-#5{(^c+)RE;}two$P$$Zڶ膔E0Zq? 2⦓L8uRI1mg21oL)˴R|îrC+`2?,KDIlK-9.hq,ܩ}fjs˨{sS<*{۟:#AZ؏DrZ+nt$% 0Pe+4M+?qbdJѦhi#IXԹ> &CP8vI!Cu3\CVݷ.У&%B]ϓ'>‚^ &sFt':z\͵srKO̺o(J|m=I!Jt.e6 n"V'Gq*OR{8O`̚AYrVD0EW1lL'KVT,IJDlεQNx3etr 8z ;I9kyW++mC\+iy63b6 = ]졯{xlPǽ l+Kz|,G^c ԟ2.j8$hF$\8! d)/de[ o r! mp Ű\2PfŸ4,*8F|Y_WmdL|;+fVll]Wcb$*F/jdZ%̄j,*eHFoTl֙.6ƃ<@;zB~tPV A>/zMY@i.[>wW/ҳ+QȾ: 3𨟿$r bj`Dz0Tq_~0=T$r ޳7 }?@Li eb % :{&22JG{j:&_Q:>/` 5uP]̰q>`}ì֊*Hm#PjV;?M2/&~N6fXHJctFCMʻ,n(ZRD^H3_hI(NY3sa^=nq0FphOLZIL&5Rpv]3S+7a/~Mg%S?Q]);"J^(SJȺT0V HH}<ϗ4Mg@Z/:.{,n5ܘU ?4\0Pb{2# G::6 >[dbAN;zv#&]zU>ص> '^ HDJ~F`7 Ҫ!gC?ʏ׺B7ǭFLZ Go`2*NZ[*&O4J_3֢pؖp]cF+ ajƼcuXameđMAl]5v]2I?T6WTa!+kY7lH "|~1-fv֫̀.b9(&#> stream xڍP[-wqn-h @.!;Ip 23w+om;{Td77C,Ie-yv;;+;;'*-j V #B ؤЗ@e{@x'+dgW@ 6(! gTZI{'}@N`3  Z^N44 `BXvάN"70 r9P@ScEhYrh[@݀N l8@ANJU`_g2C,`[@UFe!m_@-%ցqu͜PgVg(rsI{;;GR`'˽{=\_ 16;ń% agg w3+?p`BCrP'?P98`3(d d~E~?e0s{1̘o;|w5 >+=e׿50rA݀Y*WoG2. v`[#^}e]o.U]+l8E,ܬ2`wjfjko`H ?%3yyE_ C}4ey:9=P_fx^/[irS6V=%`a`0xylF|6 NM߈%`37{A/e'?  Rf0qƱPp|R B?ǟa67/!Af?kn߸lqrcE\ nJH ݞsF.wlGޮp=7N Q׆`a=+|w¹ބ bnIpܤ1v!6Hx5'+DTq]nuDn,* .]<נy51i2 fh'ɈB5^ Vk}ǒCĊ8'?#~7~4"Ogkgkc;>"n~e?qף;i,3Q DwUrk%X4@Zļ'/MQrq&ӏáABpaDտϩ'Id#h>َQFfbe ^a}F(hv֔Ժ^|Rќ֨~BI+z sVZ%hx7 f|#7s{5p)@_+,4zA͏3Top2K@dڷ'YKo_ r b%f@37JVsԁګ +'mA|^ ^/r\ZV¥uA?a=Z ꬒUyE< 4cY\K䷊_ymcbgW;BݝLS/_ZcPUhǣE`,^}VQ2L {*0qNd6 ,7h t Do.h3=rdi>dEOQOÕfX| /2e|"Ony:X#lI;2tvJϳ#HvN,htlNSRj$<+|MA˨A;dú8+R1~j#:$ƨsb̳za .A;sJV0ı6Yڵ Xn'e8[]b@eRKtB<ŀ̺Uwqޜ]cUhrmEAm th, \_]yM{hYjzd%Le}PzZ0+/}ڻb1&!DXaDՊ %ʻHyc6͓͙$6bBV{\68\iu;_5%Mjˌ4φ'f9E>SPe r=]=sjk#*)ޛe9#1,Us/>>Zõ_CpÞÓh)w-yKi@}ph`]=tdTlN [Uߟ0dEހ|gف1(Un |׷+dkk(TOEApQ~ 7֫5;pSrS*NAȴ$mѿMzr%"]^Rvr,\(j/y6eش]q!/NqK `]Nȍ]w»L%q靡[vhs :f7w٬3%;iq|l-5V$^ Q[⶿-0> M.,r:z}^:kiFC4>ڷIƽ PcLi#T#ϰI(\g9N&$Gc9K*̡):4w<{]#1tE%Cx8OOrm*};`9"=55%SdOMtYja*dּ=[D[r[]/p52̄/XGČut ;@˧0: zn4ŜK:I,f!jGu̞_o{=#': *i9(`jCt\_.NE6$CЌ1 kF!PcN,K{_R7#Q7N:Q>D|-ʼnrv%K)UC$`;!F:ll C-s"]똙Fxzhglg?<_РauǑS6fcWkG^y(ޅ-pJh}]%ŭvix=E8o0Jó5T]EE#djhձqu59 7]3ݠݘdVΓT ? SN]-u˴3G3 v){P02cGI\54-˻n9=Qlern͖t>E(zjf% "sbD=3,,Vt]>N=쌹5G"PYYlN:{"}W/Ǚ?3KE& d@PTEqihyy`K _~mSCYM̏j%M n៌}| Dc9u&eB%mhs!1c¡5 A嬟c<'8ezpSBBw5,89r|3qe [eZqdxC?c\t59LSZ=H#Mےu'ѪBjg*o0Φ`,oCNVk9:;f !pFQ|NJ_y4o=h5f3?:;TעoWCg2ےGA;Ee6V)SxQ5a|WAJx?Z$K0نXqs7rn~6&'Vj;鬱 prۨyl-g]鯚w28Do *7!orKw6/uaOk_C809[.sˑ;V7FXhك۷90ٿ&B>Y"uS(ht@A?̒Fd ;@F"Sq'KV4~LygVͮ#NRï{`ԹvH]%>p/PQI} uchxX$mίc-0{Z? `zi!PS1>CY(Sn_ɼ=$/V%M#':Ѱ[7xlLV<8k\r2n.U'wf`gL yt)Ui6XqLX/l&0Lv?77Ƴվ|DbtL_:oV(qA>bMx:5~ʏNda[]`B7\7FM2"b$o(犷\.M"p 1ѷeԐ+=^kgR]~dеֺ::Wt1WTjt:o$[ڄJctqԯİBYU~40%@O(u-UF.6O*-]{(3vsYKW L;x%|@ 芍$XA!IaVkI?MȗũsۣXWU(:λ}ډrJ#i~ %J~u|^"|T+!A`JUOpQl,e.\?ϔ/q'2U 3%h21?7%Afzv洅w9st9vIWQϣ! ޼=d]2oTEjI@{[~t 4QL .6Υ0gFF#WWği qľ~Ҙئ] Knn[ozLA^Vca< ̩|䕒Ȳm:ToU4&Y~֤Na3RzZH$dPk9Ҭ"v1= T4 IKŽdeoEUTTVB*eex I V%2H*t;kæIcE8Ԩ;l6P,V~?[743Mx?NtJmԴHr%䒉깤Zrt?c3#Hy,V$2ޗ0YT—<9s<jH |'Voe2f6[I6]٠thm5IY"iDO%noL EMHSFewdgҽ6='ڄbfNڛ8|jXZǷVA41]w {~gxʥݥA^I: 4sЀˤ^w# phh~DPv>҃MgɅKBQu('AæyI5\bQQ4[QMe:o~ľ[L>ɳȈ)y㿩lK*gԝ~_ɗu\' # +~n3Nԃqkgݴ-B!Fi`2$bFW,i=R UY^8LYJʼC^ngK49T 0H!l+ct+-E*!3{P`NRoUDžeciR_;Թ<* ]L=P3:ˉp0/~Ͳ(!S%6ݟY檴 ̃`ֈ3`\A~jHY՞h{"3J.1hmey5GBiy $l4W!_6$~S=2롹v7LFG3Ţ?1Gv޳0~y[25o#@"/=~#(TXbтA4~/~ё]ɧ^;qKwi!]KI'uM3P)M&c r)j3?'Ss1f~(IeMh ȭ43(qy-llI bkxɏ z;'.aNv$,WR 17 5|B<To76)\Wb1%GR=ʤ+y'4MQ-; d84.'Ngz/'Թ׌5p,jPu@2Y:# 8!'nK }ayzlKX~Opٜ4lJBhi}y'S߽r1Ŕ{YxGgR))u]rѲIO9vXZc0A2J: jo &ѣ ;-a%0bTq8*U7ٻEdB$kԔk {^xӧo2Dq SAP p G[ -wjo%Ę~f[]}C]5'֚Գ_,Z&YAĻ-ME_e4\#So|83DB]/Z};\w|;59>R2=:<TZ+gPVŒз#V , ,Hd Ba+6v DTeR ~8'4|Y>KL(k-Tف9V>ݓu,("-EbL]ۂ4/[~)i/1;B_= ȓEuTL$C<UijR.hƫat7G%*F1 ʎP_Ź]T`d["KJ\w6:O;'₝{wUS+BVS pay1ޯ%Ojulňsھ "=cfzے:1̡Jq82nƁƱ^YKP#GZYmpn̤SvZ EU3Dg!|muzE_d2z9Qy/AL՜_~N&wnd׍uSw7bJisHGd" ft: {(?ϗ\ȽrF!!,mr(^}㆟H@?/at/WoE*]\W&7Nb/|z\U2&dƒG^ H.5̖6u}GZ7ͩGȃUwUmuI p^fiG' qvT]F S#6)z:R!RxnMHa4!o5Ӯ8Wdb-0Vu:b;mV2~{*E~s orcg8)}*]n닮``ٲc oq"ջr@݇3`yIHs ⡷  X?P8l XYb!/Ut|kþ6V]Y`CNLb}izwc!ʉ>G)j-CË߱Ω&s&}vtXK Ltl 2XĈf T2yތK[Ek*qhA5ȭ++ڋ3[*cح=CYPuȂәV>oX55krf,ߡ|kY" #<+1ޙƘr#"xCى}mh|0 w0"yȂlT?Px"0@"Gͻ+B-x;ԃ׈S=$B.bn{m?#mz$F Bcgw p[ R|$c}ڥ:zo$s]xbgp_Y X -s`U]~Y"MmrO9tOn&o0{Iڢ#q^>?,'~oKگb$?f~ZދȊ e&Ú",.D"\YҔc&A#@~iTҪ -J"üLiB @/nx;DGB ~g@aPe78PYr|=6Yq?\7>:7v;}{f]ͦm>Tӟjv ֍WMr Pu2oh8zoOLK12`.Zz(Y"b1แ´)#|يDGu)`ͨݙ7ݘSgo2j|{:$zml}vEho8eEU7*ւ~~fϡsfr?0CDI:ؗ{^,ƫipkJ ugSN h 2n\pˠ4D$hTj~, a^t˿u!e ]bNs\c<+r?~쾁9t(Kq?};łp^Ki8f`F4̞+{˛C]@TQ41*U !oIEGd !z} fӌ(lEueL&=0fׁ{)ODUy X^5=f;׆g0?c\G'y~b2Ff VjpbC61 U7i _K#i=FW1tC;g+'ix^m:Zh9(; H*nx-?Xb?8[DNǸk b&M,9!؞BE8"}"|uUE_rw8[I+øIX9~F䓾$73sȧqJ$v˨9-tX;1=\0Ax΄^Q=jMٰ7`˫r[ &4V!w"o2_l hWkWysOc_BDcfR+G"3 Ǖ zx~>}o (AyV(UDS^r섻Z-ݍzۆ(6mbD0<^͙ L.1YY sTuw?%< qD?<=#eI j =< > _YιR)mR,wti#'g?gk]u.B*c5vBţXr&wvbm[0HW3=Wv>?6'ۍ\Ϙ"eX`%{ <  ˋR!cQ a+XGpNv]Iw9)#?o6Y&ڤL)$+%փO&_<Q\2IfASގ[׃4{cS[Y* 1\H<9Bwk渉]^|p:7Y &K8͗ƴTtWf׌ UQ{|?vZOiw]c%[V,ϩ۝ᷩ"_ l;~$a~ÜOc 5M4aH%v:k~?48/ Ų%G͟~<Ry 8KXz &3ePm%uy4 ]/mO} ,Fq>!={8{?3Yk)GO4YwE+?voM1^ ,r](Ke|#oJ/]I E'5St ˇph CY}O6+v׍gtgz+>@ L#:H=7\кhvrJ@TEk"Y]A@j-o) X۵b6ߟxv\CI? |bj3 /~ɋ3i]Yrbz37FCE["H|=" O"_;YP˭NE;ɐ:HZl'e"Wfo`[2 T?!\?mKX#S8r%'o)SL`(ܖ_$[ɉ 4W~쐄ԓaJYr}4vü;>@K%0TbDN^wچeܪoKJģ/Sq9ky|*ywߞ/?EɅD x" "^S5` CM'ĺl,l2nòDS$em&;/ )0q~Xh$O*FjɚKMQ3[Cm;rdæub%fw.iu#.pH.E|ƏNQo T#z%ȰJ8(Lf5r &zHh5=cZF^XZ'3F:*7k(߫H"Ѱ;X6'3.ܚZU SFUa!+ Vۖզ=ܦut4~զ k/)&А?i\ endstream endobj 192 0 obj << /Length1 2586 /Length2 18554 /Length3 0 /Length 20039 /Filter /FlateDecode >> stream xڌP }pw``pw'8݃{pw N7\+`V{bf&@i{;fv6&;Zb#do' ' X&i6TȻ9<ll66; $@f%Z da:Sz;??/1[db g45h؛.NAݝ֙==b P:܀fJ(] 5@/؀Lv`W;3!PqX_L7p+ogcSS{[c;OdH+x024qlMS7H>gS'33Y n-/~ ')>\k;{w; s_e:~9$m!,.n666>N0d+o%_bp sp@_9 pqrzS`2u-@vHob0@=6'}x}ĬZ: .Jqq{73 oUcпYS/.ۿ'AX7)aߌu/#iWt2ۂlZCBvS:cݹx.W( ?0|XG/wwFO"9nf2+_8PiL 9 #e wfUҧJa=eyfu'͇O"atŒ[S##euXWvt   q ~L!rޠDKF÷t6oW̤֫POS(׏ҘU j~E(.#KX֯Kӝ]  Ԣԋ=Ƞlk'nQ6^b1|]!Kָncp|7;2m3NZO7WWWlMQE5Ez\(#(T6[з]6ՀԢk9Y7v8qH Si..6SHٴy WSw}{Yz.S3#+ߢ2E,Edn0,@Q ERTCޅdDS^)0}>Xzmw_%Xr>g[+\=ß̊$5AO9Cb1ڔQm\+{dLz(t~;A߷:iud欤"GP y\E9-];jxVى#Y.~FIyж sK Yur|[0>sgt7v`#R'e'B^qTec)uCޣLֻ4v{ƾ0O4N=D/te|lL[/,3ݢ8WڤPTHiԈ> ǻIAU[a܏^߾f⒅qh"娺!WߪgIJTs?S(2$~Bu6D,NNv : E|@1ͼФy\P gq&,tr) eRF tIpi$ h ;(s02T#58e8QEy>l0_j^K8Z\=-+W}p/6_ [bĝ|'XsL"Dd7IЈ#?h0Ͻ=>vhf\lgS>W_nr0ovSn%ᛨt0:7+JXOU`5hN?+ H$TbGIŁ_~a' ',~Fbm<ԥ 4QS%vP}, dwFGzj,C5ϧiOv\u_k۝z>K,Tms2'pg *;BI4'[־dq01zbq| IgF+WVh7Gxb9) GU6f6GuAFéx_|9m3v]2T{tA` |ǵwʮp+h\Q2htӽ/(%(ݑ^;*>/^ͺbd[߀{D&"q)&p _GuC2"4,l`c?~w U'k<~J{ΕCTJNX$r.UE_vg LR ng83JyEv\,a, 1TVsB6~1): {'fH[Ak8ǬW;mQc]-~'>E-r$M%WwmdLzxy29{}#{ߜ^8}۠UKCHMzbX8kjj7ĖWwW4E+7[IE3%Jj45Pt'F*>mI m)WJ?S(LhG)9˯kMh3þĔhhηPIY<*GR,&~rԏ(bIp /QQQJCShth>UD5S?Q+*8z/[ލBIh 4hqNJ_Yl w:&s8=L*v|8#OeUxRs$/!츀QZƺي{ d 5Dw yKmzA)"G4I=2ȟ|qDdf)6ޤ C7*qp9Aeiy5ӿg?p\YHacS: +3uފZn4! PN]&T¿یhz3|bD'_U}W'˖@E!Qee^2Xnq Sb¼(YgYJO[57v=q[&7_\TX\G>7ek*(UYxܯ)S[S *APwP>Vfsz]Gt -{,8" @Ѵ@O[4N )2ɘ)j{.2dtId[@,;5 ^ɍ//RePQg@v` o)j$@14>1&>gam04ᦿzW?;Hr0;"#XVeiH_Ng0IwKyhd%l`}x0S ];4 mЕ[7U{(llTקJbXoFx$т_ M.>{Ŧ,6PQwl&B 8_%s E,P/G4; k:&'f#wW#n^1ߐ4BE9GVtZ(#ɹP ] %m8|rT2LIcJF2Ex"_`7~'n+ ~b9²tq5 I8PIǕAy"v1Poh9sKV-ӂ}q)QѯO w#rsnW<2Dvk7*J)w$5i']47˃ `%WQ6M#m^q\ġCj<,-|Zд3m4< %]P]B玦N (%9Je;WpRzwR -{~B]Q h]acN@T5e:zG^Ԫ(ȜIkD ?pp\YaoM74vYE\9ƶY CLK\n؏Y|Gf{L eޮly- z@L?HiҔ6Jy4U߻03.t6Ƶ?jf-]HcyX6=ϵI̾As= x-rUíb?Td R1yvɰ;bAܛ&ʷud(({LuVIGZnJ&n4LUM2zA!qhJU=Zh0^O bAth?Rr|T`lܪ~w:S!ezAKĘK~Ӗ&JQkLmeW7&90twx|Kxwǫ9 ]*a Oi&Hڊ6#]y#mL6gv?g9YD.]ܺAsۈ@AwT@341ЊI*"W^}?Iei/Ï֯cԳl g+=?I5il5*Gѓ ɘ&cMK۱0De!:G*DapJ޺L+"'%^2~ƶiy[q gq;-9}Q!РH;݌?N9f+6DZ37}*p7ETDA&C̅@@쬂,1W֍^§κI̴ۀk"Q6m'\dT0NBPӇYSF懿"Mxzśs`KR&YJ§ڌa8܈[24ϒX6L*gA9h̏յ"ĹI sEt njc99pzUԌixl+nt%ޘca1"&%#2-;2:ʞ!m=HMO0weLLF[y+SP7=|x/ޮ%67:֟ <鷛٬N|W"<7|P^۝Y"<ލߡ˯Ώ1{Z%<D:k+.`y[ʒa٢/7j5D]0b51vQ}j_k֪p8"[eo XBgojhhtȡ-CZj͉nm魇 <V^_0Ae_L-Yv=$R!/ŻrrV_Y +q!)@wc?3Cv}b_IHB7(mD.,aϕ[q(J`4lTltĠ@DNl ITD0Ku~ iwD{!2UW9mT LbzQq @G~EBi2.m\s{-F'#ЖB1biMOcS=l' QwX?|Җ ;>Q"&l.;'I,e Ps oħ~G|DҾ`G eD [[rL7X _ 3S*6R*Eۂ do0 K{fB. E}sݚ{X#˓f '?/\U7ȜT.ReqdVCr%+m%:wG$k>Vq`tN9{q K rBRsj¶F l4LX6EODN2]nČW[6 jI{b_#kḟ3Do *'Mťx#9K/%n)f%VLؘ+U Y䝵Z 6)mKuS8|Gu3mN7A|VHsvV0ДSKНeI%6/V׽5\tҠCXsQoׯw~k&dž2]92IlDCTxW ©a#`~$Փ:<5ͰEm,a?>0Gݾ{vP_9· /wL|<[QUhKD?;Ø9F XDD52Nը)ҙsq"iƄ~%V^\We [!sѝtSRvP$ͯVdt Jw|,>$;;KUJ{R/+&%Nӹ ZcHդ&= P R)}^Q t4LSSmcy^T։=W%9$;mJܡ_ N$8&)ނrZeM%'hn<6C#yֺ츐4 l(]ck~mƾq#ta.3VOj@?鲱f݇x`XLĿkA-IU?gQxh D~&<ҦcIX 6wض g.gj=AنPѮo;lj$hz9M -3 %m{>IZcMYqsk]v;\PF'#ҹ8-VoC 2?H VbԜPfYm'˗ߕss&MBPGZP2*&\UH{0&7!&AzH ˛<@/~^JjaY>vk$oJ ǷQ8!G~`SR?m euͱ`1vG37/wLT.:n08NWv?/B$kq iF|TSssodP @RCws'/5}1s wަD@Ѽ|u5pQp:vt;mYSCca+y}%zlvGwn'c|0"ƣV (T@3,ݷ2_KNce ~]GOiQt-̖ch`&Cw"hGeER4*Vu3 ̱1*I,MTemS,S*H&Hh;y2d<=Ww=oi{*>13y|{**GrwVYr.JdH޻ *Bcr_)W.QOa] ]jf6?нJ޷T'QBfo&de?ШuwȰ8㒒Q0bA)&=|]"+ ޝnp 87lj(:981|^NgbP6ȽB줠ly-d%aiE 9hs(kG}eNsxAnkǗ:`92Wu v#R#e8[r`/LE$U wʞ:SR όTTBZ!"'jqb; ?<ޣ9|ta!5': thILU[o;,/q:et ݞi6acct`W?U߸~?^qȗbKL<`B'$ / 2UF})D"vf"/`QKjDmPVg~V,^OvZhR&gj$'עpUW+%FqWYFm8^16U$#V~yۖ浮>(i4m xa*ψ4E22]]#5+'q> 5܆J~ѩb(IVH=FN )xXgD42)yOjיG$}A@ Lp!ĴaHxםkCQч ԉ@1RYbek:q"T"sU?bᣎ¬RŔ{ NKz頜/KC:5ux~08IRVL m7 Sut],+I9[X 'euZF21tˑ_-^МXyO!jQ] 5~xwOc5$ wwɭYI1DuqZaA dܸdSҢ'yf*h 'p-0Gqm,ڳGLB~!6G:7in_rG~r5Q7ٴdS+Z/g1r-#ǁWNj7mr̠B&%X&3f:o&cc`1s\M`|>""p ˜_ 3TOCaIx8R=Sk t&m&vtDvQʑ?M'J@u:j/9Sx;2s*R \Ó8 ],uf׉lNEwƦ*jN{k;Mb8rUwF${@'jƗ3tZV3a#f+8`ȔA} P4lNM=U̱+\馪a斄40˞ܘ)1)#G+v.o{v\tFwI rqv& ɫNB4L:{C oN}6.eE'/H}:ӽIl5No%/1qIW~lpA)PDP=Br' UwtUJ{-fIeS|v|˶_=ΐmGXֈ2,z*~βɯulXtA6q*B89n"&5ٓ8#Ha?в[ 1&::FȪ ڟ_4Q-oМOC^:sz5f ^ +]Α#8.5(7=V .aP\ai )%F\Ө%=ЀjMٲ]`#^Dz63z;Pk^k *3T$G3?CY{EAm+$6:w2yTx_l$::7-;֥\+䎕ryunQqjcne_tZ!zxWf4.mIqܾJe%.`-X0sKɔ0nU(N|xnjv"^*0b%\Q AXLcpgX)m7G~bE mW~ɐE`V%W ;-<8.ZX=T)cä́J0靖@!z=ʼniNZŒH}leZ1*wڱ'摄<׮} &\#lFjw1 r^|XN>̓'>ɹ 9C(^;lEqWS,btw݆v3`G bcBw2B{ Gk҄)~uωx:MuIN+c>RZPkizoM3Pw(ٱ˓VS7tMWd-j׾_OǑt%d}z9g}5IݿMb+B1ZfՈu{-SHi>Ca? vQ-.pKE3Mp' J̔=qׁWDi{ګk^ SXc^B[tB΂?{r92D{@Dd}8!ˋx ְ;ptYՕOl-Z%?_ ɾy|)f+928Q| !8+mM0Q-\uah,4fe+JLP"u])Osj$bhNu0/opq#N{VX#Ҧ6xTL^Us:y7{MW\rUƘ'J7?D\#?ܰ1Ju*NG'D 7AiDVvl8$.E8X^Xķ#2;rCГ)ovumyQQgU_{ 5m*lBA؉||-C0VVN  91e,0/qB[6"[̉Y bV)}A{Υ1a'ۓgw+̘^vϊy3٣m+/so|K哵WYbORdЃP2LZճ^տGb7,Kk0^WmaہF;K%33/;돎b@ܤC0ΰ=zsֹ![֞S7~1 fK#[%;xȠZMj"Oҗո?0]n5 7YAMRa*{j"e_.UC$:p<5Wkzwv)྇4ϳ-2ew }mM}Ʌgx땡?qC.v.?+:M4äZqZHxlA; I*=‘5uÄP__#Sƚ`g1d{I= I1Э⥳ojrcL*}['1N{%I?G1=d>]vھ[ea_O/B$͍ajQ|+̓mGQ=cjX'={cvXË4j^V@ ;s/BEls, ٶPxe" kG$s7|tߤw~Ѷ)RET*a &O;&x4F^zYM 3p.C؈"2%}QíXIDϸU'l&csI#x[ ˛b':C/Shraxq][ǹmqHzCi1A΋|zrt, r!e? -wLIv% ?snOSL0b HRv!ׂ/~.vXzխMQ*j;|eIJw$fo6 xQn0H!=9fhn8ϴ'ihi"QWa}.J}fN]N[)~ SPF7ro4`˨5=+1(S[%.ˏp~86LNit!rbeBL`#:5ғw壒nKImrׁ7I(|3gR֪0Ok,<]2AGi'nH4lj(tb*`y0 7qΠ%~ IWR֧Vb~푞i{(BYlϒmf* I-V!#F@q6Q1m+NY` A% ;eL Cv:APSrJ{]\9S3}ՙ|r%Gc9m Q-UNpA#k=g=Y(|I3la%#tPq5=Z3wmuI1BVn!Rju6"-|z~UY>x*_GH55!-2p"VL"mmzu&@PßkZ0t2e[nwi lS@ NSʥB+^ SnYUƪ 6\Ғ䊜TkNٗ`E}f؊X/Lh-)ʦ 1}I_4i `\,wY(Xw%KFsMP2,4*|7MQ{sHےO:E҉: ݅'iUkO3{HH(^9BPs ~)eK<0[`X:5N*|զ0?/^9RryJ岁,w~>LJD;s,dh{J X¶@IdVdB- dծjF$*VE\gN*&q0n>EU$5!ZߔI?4NT!Tٗ2yLڿê#~@)L/'So@ׯFm`*ɫ/l K^hKѓC$V*f 1ү)q4&#\yװ"-Z Uy=xQIΛ|$\ťY\yImD􍅺 [7K|jyVBc %,/3E~B3@K@ Eee&WZRl.٨:6̆41^1ƓkG{Jtus5{NL_sUl u* E3H۽A_` Y0 5v};~1[ ?-?(8a(q`MoXȐ]d .5}ݵ7 -.wL{xsG.ݧfIlF*i IP3 W<8ۥ[FX\xG +~%ϯ"Og>-L4`..2Ζ[o  x h mɮ$4T^PI?ww~,jr?&K;r3 ۸zŁf됫ꥂ5VȖj 3`_qiBެ/+Ɂ!4I'瀞 U,j[|E"rWsdtjI.xlN$1;R#낔6Xj`A1G3FCgGE.b>ӝJ6+~e'ouNw`{*Q\9T2n/#.e0g τQdvM!7`^QчeHŘ?2X*$(TybSo1:̆ĩ-@^fb&M_R6ɖro@Z$Тx **14+&< |38:!`=J;ŭcXaj63ꌩ^V+2^w:nI7SFyr]HX/穆ar0Bz=OPӶ(x!R . Nn`ΊeIn$kaq rUT2Gd UFZ-ͻp5PE LbrOu674Y㭞8zxlAm S' #k|5:b?fy2Ya1`ۚ}u3 ^ ' @ޒ+EP~GLz<ͮ)\xoG O"`35wgWh]w DYw4H$S;C}r2DS: xb{f=.m<^zpX@I?Z (^VPE ˯O-qaF#V|u.DeyYN/O֪ƕ5*q6H!0_W iyCMH9`sϱ`-"G(vbf玈sL 0Rx4v!F<1a/<d^@ >霏xO0 S;x[cfw2mSN󾑼&SXd+ ;qn&vPbG¶ժD|Us c<q;\!% Pt&[g>w%+`kgMAIX2)ܑe.i|^U|dbrph[[2Rwfh&3ʥBWL(T.':ZXcqKz3/+7OAVu|SZT=s%]a6HI"?\B yC&<@B3CZy4I|0gihy>K}ٻ`J,E-f|H?Ap:қ>)/acQ. "<>F^D,ߧةgi O> u0!jEtx"ӝpkEdЗ9{W|6/3"XHb'5 ݹ}Xeٙ,9I#HXw`" 7,F, /l5&anh}p\4mj>ЄKF^hVl b|QlSS=DkOic B!aRɉxLg7>2hw`-6O`i#rk{ `$~?cJF'm uY|~|V1QU@  }?Rb*#[W?_4Dp284[S9!>.&M82-="#ܢDaRgA+#<Gܖ] }d;&WM^j A݄^Lp#[!tϴԽì_ M'_3Hj.eDC3Q>YN>)Y6Z4G"@ee}RslXDV{Uy?6,a+;;lӡ;rH-9)޸)ُzP鑟o 448TswyC e<%5SR\rذ#m!:QV̂IA]TWaJǯP6.CG\־D&tA79rEw?/,w쉼Yώ"I֏GlOb-'|s]FɥCluէN*V;CϺf] endstream endobj 194 0 obj << /Length1 1413 /Length2 1877 /Length3 0 /Length 2784 /Filter /FlateDecode >> stream xڍT 8T{O勉m,bV,f-R1sƜ93f1"F.E*BJFJ4))}g}}<ϙ,22y#qK`M$#HoXā1 !? ]"Cd@4$.$@ ,==fwp!c``Fhad$PfN!.ڑA/D!?ZE"%/Hpt42X4H &P йj8fр%@!B4E0!@/g7Q( ʍe+ H2qt$F @ ' :T!ͧaNԵn8!"!Ns;ecv@v<.BDBr>{X1s]v'ABZ,ak0|!g1 |@"@!d(+x QFwy|B׀0 B0BzD1$ 1!f?#Q7`ooQ1y';|4[/KVPS"0%d-(@sO:<6{3aS:pc0?ZCy w( dIoWV4u"G13ǎ#Nœ1[Հ;U+t=4*\w FEtT T$ a# 1=a=QRg25r%j+~W8V"Qڪϙώ*W&0qW8:PFc=2ay<%Ѝ i_}71l1o[Z-*wzN boL$zmx8 k|<(i{:YŒOi'zHVj76x}7k޶k:XࣾL֖- .hx+*}nrbENYRKbꕘ ݦ|Li!{s>ԌT\;qx29{fi<ŠiwQ&ѰuBpʋzT}WmT$XdFFLW -Kä3SOfw]q8NqXA-bSX:dL[KMu ge x$m'VM֕֒'n*;_]Mt,]f@Q | E+zaYJչަW֗negiEĽL=s;Bvf?hژW ;@>$#lWőUWcUW- =8}QRrN]=>a 3o]՟xC]u%c`N &WUU@28[>O."sE3%^D;vHqñ-j9!jsnmJ%wDXGW̨>ܮ3xaׅ`Ftp\ ifWKjTs[QM:#{xL5#|S'rIIm@oEv %j|l_mͮU9n1DR^%MnڲWOwәK$(`\FGYq~Fk6>K(+u͢n,m M̻ӕ.[6&^!uz?꼛 sϕ2<as^ܜ8М߅)K^~njlv9y &tO˧LlՄCLz#oGwm&]#2$/ ._8ɰ",d #.yM[%}?FH pb~=V?An} Tø/zmc|ܴ?.|LG8Mg U๳â5ަn\=QZk&Ԧ<N7Rr5/Vn7;'I~Qy[Jj*@U[X2Dg)۞_MB}FġOgoojU=Ӕy0D׊&ˮVDKϰ<~u2%˷5rf5q3  endstream endobj 200 0 obj << /Producer (pdfTeX-1.40.21) /Creator (TeX) /CreationDate (D:20211212175800+08'00') /ModDate (D:20211212175800+08'00') /Trapped /False /PTEX.Fullbanner (This is pdfTeX, Version 3.14159265-2.6-1.40.21 (TeX Live 2020/Debian) kpathsea version 6.3.2) >> endobj 168 0 obj << /Type /ObjStm /N 40 /First 332 /Length 2093 /Filter /FlateDecode >> stream xR]_1IٹTR  "ZZ@]a|}GjN)3=wO"%˘IpB/zTb.58 <ˤ98Ɏp(@I^1%l)8c* !BA1m3fT:J1ac%sX03^h LӚZELY%9ɬ֎ktֱ[A&f<^) R0 @ A=s(s:;`|w:wx<qRu|։y9egY7 vzSX-??.M9(*9Gt/氉m2_=v~Pj*/QGqLhr ^_E)@zMW+Y;|{tqQ;"<On9dj,Aιg2nH-X[ Ƶ>#3]j'A0jiƙ*DW㼵]8oe-zE{=4c^0Y9r&>Cjـm)XM FPC !:Jpdču%’Lbw[V![#uD5k֋- ]si/,d YU/xGR4g\FhOY 6SӂŶYpNgv ߐ:[@q Tp7##X 8XH9 r-bY<Jvjiumqihkp+0]p%#'e7"&g\'|t2hFȪ ܸ ev90 Fda x"m؋tv.5bb 6R07Zb! :g3X5X:Yۓ|fqlgܣC-޿WI"c{ިjPfiIey{{;o{_^|b^=* >H PmUb2ǂ|W.``C*L<[q}^\DߧCTa}/ ?Ǽ>>/&übPgK~ůή O|̯OFOh:Lx\\̗9%xU|, >27 ;Q1:lvO@LJmJVK%k}J~&BNִD]˻%?A9S>堤W(g~˿D&"v1|&1'$=/ʆVyxj;zK*^i'wS<.|c>2 &Y8%1fOZuyq;CulqW"u`U|;Vu+ׯz|@t1&h1dK(ht /+,0XfKeohAoWQ E #hUDxLk!k$,%]n"w dz$%~0HGڵ,lN_$' ܤt&A {0]Ոd.[7◆F>zIk&R&kp)!|8y%eY;qQU,|=T}'1$.,a|}7ʯ&uդfk oMI]^Ԩ?Aڤ1PwSo^zMwy_ݜzjPw6 ߼,AWީ7X N^ྡ UMo0u`\bDa"b.N? 9!Ғ:K])=!Qށ*$vFI)>F2pdT0r'aM^~1OJ$0 G%e|2 ;?[t‘piDCy J$dp:~ IrARnU=߷Wn>oth[_PL/;tzIڲ endstream endobj 201 0 obj << /Type /XRef /Index [0 202] /Size 202 /W [1 3 1] /Root 199 0 R /Info 200 0 R /ID [<0D1430BFE3729E4AC2B69C9707BA2B66> <0D1430BFE3729E4AC2B69C9707BA2B66>] /Length 557 /Filter /FlateDecode >> stream x%KlLa=3әћmըPA.6ԭUuhB$Mc!$.i"̿!;VʆlOgfV1,"(k"IHH3\Q|O*H%,Q9bՐ,=0 `?kIO;c$ ^W\ >RIQuu\E F>h_i^ XዢnV\@ROUnvXbtJ3]ڷ0nsd` JOu5d5#kaKI 6 @&24)Aڷ1n!η*FI&wP,. _䁑Oj> stream x[r۸}_;HܚJ8xTy#K$g9 7Ɍ#uK @>}0 0*f9fg Ka)*ԩ@IPW2%T*TTaZP1udŒQ }0d3q$rl \3'H(HYJ"%8;OYaFx%HHY%\kjtBe54H&x{ 1MSzkϼ49 Fn4.0z-ԟqP𚡭ʣ%)P;4I%5 ѯ~%MJXRF/֢@#,iEJdB% РT s4v,Qt0$Ţ@9..X s$$CNB'"A/ ,PA&' zBOTl= c]<UFɓdkhݛfPJPPQ*o"E_~٣m-ލG M{͞]&82ؚF)'/xWwfKx\S 0xƛ.JX~ȼ4N',M~`ԃ1\$51@ZQP^6]O!@9dTxtM!A<)fooo\Q?ԝ|P `Gffeg/cP >>8A_9p/n,OwxCjm~C\'*G-7wy1:jR,Z5R ŷlȯU6G}hʧ,ӿGl<`JSHuPQ&Qf:z7W1Fw"ƐznŘhblϝ!f}HYB :o,&!X& QXCQ,$1YɬD5C]#fu񪊵x9"Sp./{1F|BWx,:KBU:@nR|j2t&JPK wXLnL bɪ ߴH^qK(?Om NpL5j&+Jɷ^".t23=`K6& ^]ŅQHz!u708wqQq?]8XR[P9מ&(G3$#ZGeGvg9_|o;x>|zӌ.'ai;Mٴ(~ W% }uo;9q>yQd/%t3x4uC)7$_4 EMIvNzɠ7%Q6)M"v vićW_TĪ\JιH W"FPX%i64oUBGȐWEMs gm0zPv!󙐿lKqՌ޴; |P<#i" #_QΝ$n'8-YgdnVeTb\s,^Ӝ^J;sq4WrK1ZݾE>DG)1|X7jU)9(CN9'W&y>추I4͜2ɒ42&f(ĒИ©ZvN+>eݧk^tCƩz8ݙy8m*4uo4&DŽV8x$T󼥓i? m]XH*>B(*l Wrs|q'Ik3|q/io;s2 ֜-df?M[,0y֢Iۢw|ci>9$ 'v'i([&K$!銲XcJ{R?㫥Zsrt©OӶ9`g:$m![5'Z m!SSBץCՕ>?}r=]:BzT@-P/bw84)D_WS/ 5". ˬᜟӎN6^Іbi(U4 *VжA>C;($rkQ4L{L=C$`P('1~62)bLWmnڃ)m oX>ebl@K X÷G/,?qe@-mn_\DyͭҤ?5?fU,Ho6PUj];asEZ|x-K?R'׬֕ Q|sxI#9hBD ҕ#$5غ- -l/綸̇ט][m7;ILM ZSDz4|7KP2J[1)zޅ{v1Gv–Kle H:VIsL"}@;0'6h?"[Мty\*L]΋ey%=UQMł"MT41I$L,;YW/>q'rղbS [=G;MKd+.[]joCKۂ2W+/#ǽPMuHԪYPc<x e%}Ć~"ƄK^b.gn~3R|9.^}$VuP'_e9_buMw+m=o~ZD0WYEfC JWJӀ,ߡMVx]|&PܰH)@ܖ^D Gc@^z1lU> [sְJK:l*_=endstream endobj 81 0 obj << /Subtype /XML /Type /Metadata /Length 1167 >> stream 2021-12-12T17:58:01+08:00 2021-12-12T17:58:01+08:00 TeX Untitled endstream endobj 82 0 obj << /Filter /FlateDecode /Length 1784 >> stream xXnE}8ءoDA߰w;&s23ڹ)Pu$_P];)dvʼ\pTNZ,qNM4N%lQԝ]y5pnz\ݿIP^rz|E_\لŔ5In?jDgh吱>3 ;u/w.U,:{$yw>oO-$»9DuN4XBfҥYxGHzVc:j>y鿖6"VIY&")K>4yig˓?+j84" +G} -z֒dR))A`y͐ RwtSM!a}5RϏ}AAZhgs&X΋\uydHc@u˥e22^R@}+mM9j "͘ߣ&˒`}9_;\,h1MCclB޷c^βn*Q.sǣwRU*u+9cIbwR;ss?_ϟuo"jl8食q9{>.Q|n89;[@ (Owlht21f "sFͮblGC>f2snw)xjfl3[TM5vlb Ee'oߩCI5Xs^tmFԉesCy!M;>,VR~ѡl)A-gVK>j}${JS.۫;{ §.@8X1 lp!Η QK+Zم:Keȅc&7lӆe+Ʋ`5kJBdd*Ǚ?z9VGF曹";/1K2B,ZcDe) c*d`_K#lOjR}{SU (]۞B=aBZ\j3'8YDBSk81'T0 ieG.݆c]27*>>WUMD΃2r|+L (^,l7s]8mFDzb $GMU&<@K|. ss|ۡ'Oo~/d򔍗^;5ƽ{IѪOD<5˱?S5o/.|:yR.n!ت qb7r.Lb7ՇX8vuLR:u%w+#t _3P~}"GD;|噯C~&Mt_se{HϫI40EFލpL[nfꁸ64"A1^GGݏ'"f+LarhTncED9wZGy,/$kk?uzkn_6. 7Xry 3\:=&H Iq\>0 ~XOendstream endobj 83 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 1471 >> stream x}{LSW{AĹ 3/ j4D"ι16ҖJ[i)G)Xb9S9Ȳ$o}?ߏ$$q wsH~?S8m,1E3CedҧIfc2CKD/.RsliB^!WCtZҰ ^4"`0t꜌H JB(s;ltCJ.}1N9NyN6AAٱ e0Al$fID2XMku$dH(i';+eD://uA> dhu;XEMU-nWX'|&xZo9ʢ$k_t/2xM:%QetJRgGg' M^mi-cCp% _J4Mȷ,a冕`{â^@z&2661l.~I#qKRU,bTVZmIvE͛d/yL Ş\Ƞt[#g]12Ս]nX<2r6^nwjz~4xMgQ=RԦ9W7g?2 We4 3NLXN]SYݡq( ITC{B > I/~EO>_@%9>OP#G\>R, 4zJK5PҒUoF!l/X6qΜ 9$r'$ԮBj5*L%)[?0i,jz97PB{GC%!dz<P`un-r!u=\"tbÊ(-}h)s"q(~X M)TFޠT)ΞՄ]=٧hc<ƒoQnzEv ]bIM==O<| =W[ IRnTHm"&I-}P?\9/49*I<}nQo7 .87bƱ1hl?bMu܋f^?" D,~DgYUoXh`1 ?xÔfB*nugvMXRi#U¨wyqGG,}͐.>.1NA :8 lLs\endstream endobj 84 0 obj << /Filter /FlateDecode /Length 215 >> stream x]=0 "7#"* ,@@H4Jہ㸅=kߋlW80G{Y]i\Egn vވݾLdPRgZC˟dGS2O=_ %Y䄨YH;E䄍f6["l wf^QOqW*aias~'*#忻Jq !iL%Imlendstream endobj 85 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 1100 >> stream xE[PWw mf͎(TDnX*xLr1$QGM{2~ݯm 0ZkKǧkc!0<βu;R(Վeܗy(yJѝSЕr\iPŨ1EQ2 Mw ǽ{{p<^ b@zovǀ[:nn57g @< 2>=-;GGfS7 v C?tS^2иI ]!pvy˙c){VbQv|r:>C,r5-+?bFLL  sԃC.4au;BN-Zlq:fW<[렖 گ&&vl2l|\h+rܗ W"cendstream endobj 86 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 2693 >> stream xVyTSW1T8hmQnZ]lUAM(HB PE`R[=-ZXӪ]}s8ۙ䝼sw~]0D5f7IxF$&<+,K1$CF'1qJ,)Rr"*&1>AЙϛ:kƌK2Mn"tT K%9trwL }aaVZ0}zzz4ZjѸ{Xmd3mY`͠z,iO;tbS7q$X0%BeXx X-E0d/3?I@}V1ٰ$&)|pVe1Eҿ\9{BHgϵ[@ML! ׇnw_c.87Dp !H_ݻYu\17Osx)EV(FK~hbX̿fwȇz-Z$0%jCM}baJbfpx4~)HFpa Zѣ:V.v8|hu+t]Cls48H5m2 `}pzѨM)W$CyʒT*<%ChJм Od<5J R$C?$4iCogw޹jBA!kڗ*Fͮv*T;_RL X_zh=M?P:n.kc^B#>7gQZdV=syoK gHzJ}B&oc%O O\KcHwL r3RssuE{WlȆEyh3ůTP2;5fC*grb.4A>0`xcbqpbVUo? 5kZrJfUъryQx%4FiVΒ[ )L#3~)'Nq/4?ud@|SR+$k L>zYnq:X0g|" Sl ! 2!JHVG69dChzj,o5M$C!gT&࿇Vc9C8&.Y{.яѮ}O!Kq玎_R{kkjj!9nG61 9ΓNp{s|70s_gSRr28Uŭa“vnvEmVn.I}D,.7{eAƼoخ&(`-m;,aAϧ'NQкOn(x'dDBm ZB!K\ &sŨ.سel}+jVP 9vcE2 c 9o}:q47.tg#| 7ޫ*s9C~8]%^d:C"K1tnPY A}tgUY`>]%3Ƶ ÉSyu{M-2uÆ*rXQP.,4 ISl_Q-ӉЂ l}WNMSk3js8RI}?~_Ѓ t!z?޿/r5DJ,b `7-Ye}t"øx3 OA!^Pg-.[}AI|%58*I J*1:,X.ۯwt䠆͠2Ǥ 8<G(&9 \~/lЏidinBR.ff`NjK3_2`FI"\b^HUdUԦb[w f7R͛ `b6SDsin! )Kn ѾGr#湂J.W;> stream x]=n@D{7~l@i\$\?KC)A>3(E0h7kvuݺ-qέi n9ͷMx__/z1\?/}\ƹ]}_Zwm[{ycZ_Nx u TڪZPR pU{|fYOUAS 03+Tf 0u *L*4*dPiT_PhT*4*^TgMQQ )2*4*)2*4*cUPGVLΠN+,4𚘍^kb62xMFfl51 &f#ld6𚘍^p C1lbƁx(1P:8l\FN#iq9.ߥTpZҹ!.H'dS69@ RBTAQ*H8sp`2 A!v]l9s`6!Q&4{(`2 afΞpM͞=M&\SI߄k7pM&})ߤo5M| הo7M&\S%x_{\tyQoݠouLendstream endobj 88 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 7626 >> stream xYt׶!P XLL -@BcMM.%Iʖ r0@x Kc_$o_^˖s>g}G@E ѢN15&ckygB ǎ BUЦP  K\'vx۩s̞h;mʔ9v;]mWxmwzGَFDDLv ;}l{y]n5ִɦߋឡ<R*7  ~-/ X/NV?0 o y>}=~ od,spgZ= a! ֱ6lrm]9t0:>qI/< %ml/5ȍ#aw1Lj :UlJ23A!O]YGmq٨b ~MCY:oҪs!4N!&9I{~8jSD)gan"K ETgz]@^ i',#7jTTCyvdpPV?]:qlnPPa w[[KjF|%G,iY$[HV>F,|6ḌPTt&CEOgmZm6J&OJ/+̽wo7^kV>"d͹yTO&/[yh%):Am綐C,<M<?@9Yp.>z>&+Tj/o_ZRaYN/s ޯ1T?Dh֠? br 3NG`- D#@>ES2N `@[.A t1dRS!>jմ;`#~L<;&mBV.CO{ƣ)w)jCSpT{̥趍_bxS["~2\#(=z(0?-pf۹{KbA e$i`ˋ ;tO {*K"Ckz< M%x?lYSfh<}G_=F{o^n I;_}DUmTD5?S/' 8 M<Đ<]ZFY< iX\_#0 G4{m36t%>c@ 4>ڦGz!~ ZBx0ئe'~$zT*)ME"sK"4 7a !Eי>4_CoXԋcM}'>[SkjڡEa.N$AI*S* PECT+׺pk {Y - ݀ܠGBF\ЯYSZQ:iVxM!QTwsz7etO&ޡs$`KYVЏQ>!mbua}lDr|UZ0q%nHMWKK94%\ CXEAR~]HXԐXB ۦ)0Oq ,/mq& %h!/-s@{6(fdȿ~yIVvVm( [p*oǂ_4] <c.ͪӤWez4 {e.vh2QhUH5'v|*#xK5q'C7Dx-Ŝ>3 |'m^* "|LQu7=(~ ?W텫hO Ud t6 _$?;Fs- GII{ D㱿 ^Bؾt}uPL <&rp3{ /DRc\1$.Y}CB6 1>ѽz´JY9? (c tͮ(^pe*`fxOYLMqoT''T2]1-9 i|4#XMJ>CZvZAETw w7W>Aw:l/S\Gޞ XgK_x5W"k`tk%OtVz)&!VQϖ17ÒNHsXM*]_ʔ)8zKSi ݦzg( {j"eN\<7 3r&NRzV G O燬$c4?&9Mf&(d䧫z0!U۵ Cwbܫ]ہ)kɉPz]\z0C4>f}[3gU5%eUy);Ԓùu>1MEۢH*`̼$,Gr3=v,=qNmnG>idp1F0xxv޽+ M(T!$]4q+NKg= (,.3P-WF.pTuԪvn_V l*A]Ц43T˯ZgIc:wFGxjI!J^˘ڔcyȖ"[bn1fc=VgT3m[ 'bq1:"P ܢ}'>ɪRY]nॴt2-mA{ϙ7FjClHv,I͌; VL! _ 1Dd(;4!?4@٣"Q#5Ǡ*MuJ?RsiUPʙ }1MX Đ"*(!Ǽ; }9Ho˃HXIITʓ詐[}OxspH%ҪUÜ_;=#w[Ixv#i249q--*@yhQq6.o~WbN-q'K'@?'DE,bo? Ԩ8e‹"k *7}4ksokƯ"6U>G/(]`<ꇨ0[)=@,0۩"4FlsӍUT 鈸^mp>5D  xVQ+K*jZcÃU~1 w$ƃ4(.Ԫ( ךC+$M M%A ٝ_SYQ_,ws\]R`&/YSK >|OCn?pg=݀,Q^o=T֐yj] m2_`,9zZi]fn\u|(bjKY QlۓA/~疝R10X{Tb陼_pEy4T@N2`ީ%aqgqu{,ro&%$mzsi?.iܹaVVO{^|&rdD6H:8uԹmJc+>:?D}įa1ϳdzT>$㨱'MSI?{ٺ ipH.P/#!5tN:Qr}qnIef`BpOt= N-ynQC;LN(YO|ԺN#NH8{-,M=q7#~\'ƫ<$L(fEĭ;8jR$F:ldZɁZ?fy>7nzIė[HJN/3eQ2e1/ײƖvJ2%C´fʂ"B6:ys vN]VXV[[YYK<rd,hң(K/9BH,%,Uf֣w2GY 2g&vBH_Ԫ} h5a  Fv$+(I%.rBihn0hc$ 0*"޳hvBYܕN6{Xn;_x /F{tHRH6LpZ) [Έ>~拯`uW5mnZ~ur0?9uCdӂ&NtNv.B7R(+XIH(B t]cM|.'=v'*8$8 '^ZF~ɋV`SsoaW#PGD~WAzށ] s*JF iu_LgtZ&3%-E|ǾicIu6,䭱C)!Y2w4 dh^ @o'L]k-W<~-wW͔vkM݆,\=0`䩩r(K$?;< /U9iԌ_ i(ꕇpȲXzbi,e[&K rh##A87 *1ZeLJa=ٞ2M)hƷ*h mvq-Xa??~FhT9fL9sa=*4 Z2hD.'J5) Ds=2)^o^L]r שRj H2#aF ,%yա+ՐX%F'@De_Z;Y_&NpGo,]dJJٳp:cb+!ptO4X'!B~E#o--MMHPp,L#rEi#N-Hri/ ǣ aÑ]Hu:(붐wAYrʎ=, q$e| Ҧp*?]݅p2kQ#8 |RjQr`>T2f'k)x+B9M8ztƟ.#b OqT-pSF˗?DͦS|}MAܙĖiG@[ܘZU哤x)`[nX-x f#~Ӣ"T5q#ϏPY"ڏ^O]$5;cEtG!3>L'ҩu!Β;$U2T*H`]2Y&sD×:,(>#iL1`/\ȣ֪ FC +p5a4atv.Z . unza,>#:Qa|t$I(DHaa ҡ!H= S0_,I9Q>~u<̝v@U]w;6@1m.ۼhv{N~|GNN(S#'źㆎx%Mm\dytf+̫l56v 6ϙۧ}nNӣ;hcW?\ jNEVF=\ZHh"3=Ip= ݚ먌!<R`{WE1Q\xkV`&7i fyyvoƔjC ͋.Ia,:~Q1 Љ[ms/ק~oP֯?E7}3Gendstream endobj 89 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 3122 >> stream xW{Tw㣬ҝ⮥նۺ#Đ!$$%!HB@ oŊuEîվݳnbO9əɜ&{;x6&|i횙˕L y`c>7+#` =82 ߋ Rc|O^(WsrqYb׮[G׬YA**geb2"i$eq*~9!w与:u*MJ:TZGy[SsXK̟%7՝<] -oYA\49ZAE=-Cq `^UPỦ4}, A:h 6Ѩ0;_Nޑ2YJ;W@{w$Z;gu^3`Gj\]),ˤiV}r8Ne [jIWqnS~aBMoc=Pټ} 7{9@oJERT+1pwJ];'d,Fz9] j\MtoeY) .IACKcaMX,P*+zl˷I$3%RG~j3@ ni16\W|BсD/#FI gٕO.^/mO#'ݮ$ }Љ0AK>Ϯs4]#7<]#c_SO7}x%y C\ݞLDP&ЖͲ$f0C!Y@5ӛ.;f-:II5 uZarR!豅gwnj[49> e䭯 v̟qoՉ `K7ب>i? fz(: 8k}7*Ϝ^K1':MgiZJzh8nWL@ʊ#{h u9ڨmm܀N Oz6 wHW tHEMq.8Nd7=ė-K# >xP!~]8Yϥ :M .B1Em>(v_sk G?Q cxuB7 .b(N)MN:E p62vM14k1IMX.f˂ fE> G<B[_ObuO꾯gv?wcLWYz6ׅsv^ً bn48Tǔ!^g|> N?vQRYr3+(Qeީms{I0sΣ O6M$JϨR|ä 쨬k4&> stream x]=nP{7?6`n\$\" Z.ř)"}__^.ӯvNesZwloe7<]M}\wo:n?O2u6.omtCUOT fYUA۩*\ԙU 2}'PԁDETTTxUP5gPE E E E @@d2RLTF*He 2Q D&*#De2Tv &H#iČMs6NUA?ēc䮱;q9#w9vK)s :r.AC%tȹ9S!t :\NAi A!! d0 d2 BCA`2 A!c s9RK B XHh)ZJp)\J5M| הo7M&\SI߄k7pM&})ߤo5M)*O_稛>-W1)ަݹ%R5endstream endobj 91 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 6240 >> stream xYXT>٣F#`b/D5Q(t-C[@:қ"ƮX,k,7&$X$?<8;3|}oQ(H$YT,uSz߶2bӎUw~{:_g.;[&M2uwg|o֛ߞKQoRGmj 5ZKQc(gj,GP)WjHmSMj2zZFM>R˩i5rޥVP3LʉzZE͢8S j5B ))5rXj8eCRvAYRPT(Jt߸~b+Ve-QDb/QK`f3o9' LقJ'/|%(,+wQ4-GU_Gσі*(7NZTW`C. B5_ۄ \`KES$sjb Y: XD~ 9g n?n\q2iB"N6H8j钚ãzP7q40]Jy- cEKB. v q:!O':kBp-E5)I)\Z*Jol fF`G_̷ Aq ' 1Sfa:/2ϊ̌jDL j rk= & r@{™˷.,zwRǥx?8='4#D) E iŞ/SWNt7\/$۳R}#F x,: $`N!Xlv[ݮ"qr T"=mk,FMRߵcUZm2hlk7͞w뿼}tg,Pw;FT8:6d{rNт0% k$.6ղUVpzq!ͅG{ nJwp]Mh^0IHV?\ q!eTjJ4fmXҙ~׸gŻciŦS| zI(PH_zCMӥ5d]Jbu:38y"[% }67Uq@pԓz:BRUIi΋ȇ*^-;wNټK)O-F!"xI7frm^gIjOk/}~Ŭ/.G#PKj=xv@ѱbf̙I_rSe|f:dmKxƯcWljHi=thDO# 4 L>ij}6]#BEOuÝHɥ;W f:]c6ӁNt_j6c vl$t8LNl^ ? ?-*GM* ݹw:'o.A+ 4 :y $1Pf5Tt@u0e6o2XznDBXXDh XocܶiEiG>Ev 1ؙzDBXb8AK"!Z)t:6X˻ Q<]I1diW8ef u-j/lEVdwejdgU2tk+XY Q+*ͮdz5UTg}NH„~l?D%uZ.oP^F&8#x.a#xG= Fa;""P"bVmv14,Lg}'nQ`/\a ^:c l P7}kB~gYzo i٩L@]\כ.{Bpg*7yx,~ ϰn& NR&ϖǿFV04NqPf K?Fn> hqSY`*$I--#nv癦oR4^$ OKF82YbpW':|b39".NH&UL$ۚWWW o?QJCi1@gtryPdDmOmA6'o!S,[ӔI\rL慈'Ak?A |w1ڲo!7`59[0 sYྥFz;Ԑ=,X^ ɁFO4u|x_-jTM?^ΐlcE9I¤BT߀ L*I'nOU%Uכ@dgƂh<5n+:M[ߍQ;:TW:YW_i[lʣGF|V Ḃfc`of"2hXٵȻ45fuo<%K#/0 ͅug<0F ǿ1>"qWxa} -@ NF}d\bo^ ߮:7\`PX=vNaA0> 'XYY8 ӑ\{2ΡtXŦ{6jI(q.LNZВqæ>VڠOQ#ESUZ}-r.cLmFm&jݣW`NDP$H# =ZXa&OTfXf2&X<,<ldp!@\XsF{` G>{hZwwW~7_ц7ot6&4D uPUnĔU6T7۔*؂IKZ[K10ycQ3*^t|qrCQ91KD3Q2-+NנLY2;f#4DL'X nFx9>ْ2TV"&)/oɿ>>Eǘ&HQ3(1gdR֏gNk,jG>QtRu ZTB?oPDL@)Rz ErK,̇c{_n9X P󀱵WXkD7G>xۚ)bؿVA/L_ZzYVBrD~eQ{sILo@:3RVUW[wZeľG!`-ԛfb; ?aJ7i3!͢>R& *C++^l>}Jz^5lul}WJ.Mu9Ce~= nW*܁]Ү07t^:[o;A9#}6ܣг;v3P2_e$kz[c˔mkY_FK` !-SvcE.#NtM+^}F DHOtZ ͌"5+Fa>I ;FՃl{+ZiD_~o u\͚c!s ~Xfb3DKxap|rKw8gX=3n0QkP_BѾn!m8wX-j1.WKjYBxζ/+t*Y]@}欳> G'0MkT;$^a=p0Çi[#9b%)D|=-`[WV]? e}_bAFQЫl!펿M\.#I6(`JOZxsw('"鬫`oSu~=3]jl# ڭ= 1H+vGdkQ.F9-XplҲ3{*_?X_2Ja6 :vF*B2m!AEcnNQBrs))((SWkCfU,8gQIRvD!~-`=< 70y)@|<ԖܙE\M#i.n!'+ rv0 J cvb>%:>1E3jeMl[76K[(Ĵ bM @&%\!W&m0(CְFbpOK9*65~WD R2%eB?ݎOܷ+<{Թf]FOI:A'!4E0?oC>cIZHd CEĶbyw67ijI=|BhУF -t zmX<@jśha'n^౎x=`sr+=ɱ)L׸4$c)%p]sHL|mr`oC^6!19CC#j{eN/ۏ]A_2`56̝=sg}\0(!+9vb}eMky[^%pY\ A b϶?2}%j|kTfɻweqMM)r  i^ikS dZfպS+8䪑~!|cG1lEFC `x>b#FpFF%$'q(˜"!Y"R"u:k--F)-фEuLSP{ 5 o]lB 酕o~R9r2UMAri$p2:(~Â[n' f颇tߡQc{ҶPB/Õh.ٝ5,@{G9d{ydģyģ Ұ耄^ 0w 椿?3(vlB/_Uo({夐dremxR # I_xXD? V@O8\#ݶ1`hGRNWҳG[ieDt\:g/vqYZU':?Ojp!AcTȷˁVt5噙1x_ɥG/{H9 :BRZlc(.v'sc׵N//뎶̽w@l9km" lG F4o;^\fvC^wϯ\aݬnT Eb.Q?Q/ο( u'/,"nVjPNyF![ efw@+޵bmek@+#4;'GʘM\Wo&:HbD,=Ē~0 HFˎdOoz-@:4RP~n^ ᰾peE7' O-1m8fD8ZV}J;U1!e-.&iM/EQ UH I=*@,0D5i [?wZe?Gq/f|1skwCЉ:v\ٮ5FHb rPS^+=A{x{BrL" C1yq[i[Np|`98@X h+ XDȬ묬V(e[endstream endobj 92 0 obj << /Filter /FlateDecode /Length 392 >> stream x]AN0D9EnP'6,@@8(Q.=3S`b,6c̗zryr>]ԇ9/U<\~Hpjܯ_kAni;Li,/ڇӔ8L?CB ,Y`d)6Ke cFz#|QHo/Y,G% ZQ!`bפwN5iĝg @C"S*c*5z >51526%`"ZF!Le xGD9SAcAÕx톮ƾ0 M]]]]]y]]!!64wj8W߁붕1֘r:MzZ骡 endstream endobj 93 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 3689 >> stream xW TךTT5>7\bI0AQA,"w .@l-XnѸ`b$ID$9\FM̛9gΜ9uNӷ1L]mLznȎGINM4N=)F.iYڸ]td}n؋bŋ_q_Eh}C Q}6,ZmHqjrѢ!Z]/wO6D֫upwo1$V>p >=q Wiyaf3N7$Nݱ-Xt`613?f¼3[yLd3o2 /ƛY̬c<e62/3Όqef&3SM!ct6٩qKuYykiS+E;6̝x݄y*'v\|/.9׍RH>([eґe|Vc9R InyMA#1胳i"f\ٍrG*D*kn[}K,9/'UdE: $WB.%~H1{nlG{•䊷m1_t/[ƎF5ӇyKbm擖nF%H -pU TL򎑵49׆y&pH}+pM^UV dJ%OqVhzUm Y{oB\P"Hmz&"bP3_@f=X훻.xG.xv; B'pmױc];@23# QM} # F<(O2s[wԽ HYDD?Wū}~;d%k2[6U6]J6Z֒97z);u~3 ,'GgB!-{Nq3=+q߶uG&ӣW?꘻E9c"?t)% 4\h[ґ#m=5ѿ U:E|ԖXIȵI϶o 9ޓ^3;)#g_[sn}ʶY=ك JԈ M!נ$26K-PY-,/.! kK[Pj, -S{-9ݒoiD\m}oD9Hyt3nQ)L+D1;4"gG>,WiQ Z#Ph6O@g=6`{_Xs>>l:v u *qYVJ Em:cd:PX72QTD,Pz-Bt* C/?|.ʈZ)Q6"MK[J/'zƤ [fl5B]f~ 9^&b!k9V&LY&?Y2f: i3--lh6 %E 0}I+aa_XVO75׆;[q}:-\$Tֶھ*Y-*rS:e$Kf0{A`o@[JhfZ2JU!Z(}4.nMdM hƘ}x=){4`:s,0<=.ZYwlW+w =]Kc礪6M(jK^xR eB1ò3ϔ&KD eO@ThL덱,c ptzvg_4m`dv*dќo>TRw:v}CV :kb5؏k$dz|>+;# ?^*q[WeϵC=oڗ/$%_.;4'+Oݯ0\~yܬSޗ*ddʪ+JvpY `$$BpI*1h18iIPIf wiV(:P\On[ T/umM긿^6h[c:C sVdQ}C?_Y}"#A]MޮDޯ< `KoVS#lhǕ;45|ce8S=R_.:Ry{8Nlw0)DpiPde(z즄w6L:5-$IIYd"E|F@nA~_}t nRqj~B\d˺ ^5xo: ^q6|O1J}q \QX"!3gO*sMGj{< % afEo #kOxG7t'lWE%!r v|k6W)6.[YÆaCCjr9z-u*9K,\.L\gf`*>34= Z-W8y\vĠVA[w  ^ÅdN(+k^lVAfQ8q8T)5{}`{30,@+o5=AM'b [ŧ)a,.:9]JU26y] _c}le'JaРƀ|a&YL e*|礙;tZr.dXP{TMN mPǯ/,{Jxri,g2%UBMZJjw6Rڲ%ugO%Tu+$NG=G0UCq“(3Ez93qeȅjeE4]4l0sdX(L/8ث?*y1%;m~ZO;~g&E{XXmqBU1 MS_oٵ# Q2it, o1d71f耖 2ct#y;ޱ'Ҷ K:Clyj&#:88JKY=Δ^uÙh&ɢJʋSa;JZJ[u 4C.UQva|Ә w kVi_VFm2R>H^g?3Iwvoǭ2jAɈo˃h3 DIޯF+*?Y#k'ieqMM\GRsK~ LT }`9{Zstg8qL_n􆶞ӽQ%BѮbqbvd5d ٞfi)،65]J[~٥:oּ~S-ii7:[_˥;ĵE8c:r_Ќ4w]ohl;Vn]D7:MUF1\~~#DɋaH%.?WK(Mڴ> stream xZnG <}~,]&$ 'ŖF$GTb{$ 8l>UuNZr-_՟+IzrO2qjXOںEڻzm!v/7[ G=lDo Zvֺ1+U(E@tB {bRwwЮQ v_j;\QDSRzjͫnG9E*t<&ᆵQ"jد\$نнmBǻK3w6ʁjoE)ݝcO`- 3hDž!|w.4#q')=aUL=t{ ZN+G$HM^^VOTI]Bq, X <q(}Uߖ;%th!2pD7E{<|5GSKgM%k4] (R7{AJӰMOclfk= &hؼ.P[۰J[ӛBh.h`Sj4*ؤƖҴB1>.mlfO6^z4;B^x:o.o|wluiN<4Z#1H>x  L'h AۘUCp9oJ1,qPﳊR2Y%?ha0X> 魓9<g5:bXK 0aj.ӼK))^21ӑO|zpfv**:Q{Kd{ihM~(a"Rğ&qLQ0 KF—'f'ic*ARaY,XE;l_B|gыE:6A*)SYLzTSr_!\lD{Y<\Üro˶O& rIwKa(>y9 Q|kUhNF4ѕueH,-IAjxYċ"^|k94A`*M]v8B >'-̫ɭYm5HpKba#u5r^CcE ̈_@/;;3ftX/xQī">6B]77ZW&QjG= o "/ (sNWH:أ~4a2+̌G:%CtႲG &@ܐlRփG sl fXbHPf"SߴW疘yl C!Sϟ; 预MBs<Y9 B:@ om}ɦy:?&nOy _YvTDǚ< T7r좒,-T]Jςԩ+^7vYN.؈@*AN7 OHQ|R~fsIv>2Qɥ-.bEO CL}V5&V!al´R`Ic\?+r_~SB t S"InJ o^0"M_c鲫q*q&_5g0QrٗfwgIb)- V`rM/]: O[ eX[ Ln@ɀ$y}owZ0%r3->&PLS7zG"[6-ɛQ ЮBKBymrʫ^[tCP"^񪈏E> stream xcd`ab`dddw 641U~H3a!O/nn7 }=\19(3=DA#YS\GR17(391O7$#57QOL-Tа())///K-/JQ(,PJ-N-*KMQp+QKMUMB9)槤1000103012)ٽgf|;?̿ܥ;~3>,}} |g|Waq6;7<_s/wt\7Xp9yendstream endobj 96 0 obj << /Filter /FlateDecode /Length 353 >> stream x]An0D9En@ !oETY}g袋[dr\ϗnmN> stream xWiTS1zQ^+^匈ZZgZREjb&c$aH0)8V]U-Tjkv^z+keX}ooD@ o躍k7m1{UC8 5f~8e E@*)╁cΜ?^Pଐ$bEBL4p]2^,V?n$i+3fGKq$(7U22h8_BeyR\'+AJeʤcbŻvYx!3g͞3w8#%6b+'BJb&XC%  b1'#(eb4!$"| qU0WpyA&>"R% |y`*nNMD>{]~4sF]n-|t$JRTh:iMfchg"c[#e0Byv0I>5>܆/iVHhvQnJs 2 t,EF݂{=KșP)|_YLX=h<58^[7pӊd.h[PA\!%--LVBaL (Wunh^V s fx@ȿP"7t \Z*E1=yDQxO/eM0do1djVA.nTU0ƞPhI'4HjNe5tC)j#vU!S{ Zh-j3חU[TT\I-v>x6Y P_[bP33D!}t0&`E'v[uvirNgKW3Z lE`4U/ WMv>oTiU.C#v Pk .hn4Z/'DžS~cEMG vF@Oy9ky此4JAb_O jI<_ۄ=-<WC-@ [(/y_܂kGC"Sq}2]P͆L|WQs߰i#x#ٗDys#)ڍ_t'-L6戼쯺>F^|[ן3bVl8edy^/!?"WB6D$&{tVk+Uhců? Gbb欹}YrH@WdW(lF)J Ԃ=?b͐_ J#]7LHه?nU^j`9Q) xGxsmS-lA^A>dS2J<|+o&$9YoӉFwQ ! mm/4&u!B$B.uKbߞ Ժ?:麞sW ^߫CA_J䉢us%nK WjF҈~ &1kƣ zmB ;[OPsfxDܹ!|ƃtaQTE-9=W3*EIJP J[jr63So.}|^#!k"iD|C=Zrq ;tgLg[#]/w/}¨[TڼP*OVBˊڡKIޜ c'|qusjI鳍gTaZʕbK۲=dg3T~..싧m^-%ɚW L[kO #XirXK w>7 ZhS I]M.> {SRud*-eN`ieiӗDۏٲ2;ة*ut;l͚}k4 F>\s}> stream x][o\Grγ?ؗ I/ 6wao6؇flB'ƍٟWf}sW߬i[XMT$:'55}T~{m~u>nJxVopsquqD:?-,yUָ@kɞy:ٍQfCvK")B^&lrz5~!XX\pMKɹ.=-heCla۩Q;}aSJyX=wNKnڨ=|~Ua2¶]eYn[봱&ٜQ\aoKa"TVcCSd&@qK f T9!脒)3-s/(g"Ήy"-&X4KV 't'Ut3ޖ"Kc٥h2Bk1J:fr6[gnI.6̳$: RbjQvu/&`8Sȶ<{ J&}טz0gmF@BKOoezڮ-+pѲ OqGT:XG'*t7FɬbGpVhɖrfNvNcq臒iKK/=),ԼlY: ֣{FM&?{ը! N}_״&)x ̀34 #>y*xa?'^~KD l rh0Avbb\pp'9Z` p>GHBhNO0Dd ^"Ϣ5I 4[KY5̾cuTGH̫@GJs3阢ZX@TZsw+b{8 7r L)nBuZ).&"jI?m 6.gikvâJGVILV{#򰤸j A 'pvBIuHF6 '4vrr-H[l#40wQyi}Kms2Mf9{OvI@'3lh!/)B>YվX!bj%m++d!`@7Dw_Ls| LՏl+t_'"r2[˵v[Y ,kS;iI?|^{=ua !@Gxd &&`:8eykR`U\m ּYhL`pIիs qINǞڥYU[^dyʛfs(;Nz ر$Zo3$z? px{KdiC\7 ~uc< \-L' SN&l$EM@L(EϪ( 8 _tUB`4Mf@z=sMU0HZ[G[_̻}m q?: CQP57 /سq։22~)gap9/8 xϼ3`ރCQ^yklMbã5J-~`^m/[@ħ0+c2[_ydZMqGu*۵4?/=*5>[8RK=7~/0NAnbbnF}%DܞM^]Q|'96G'99zv`сBSvo4>=ˠޟiorVy!1J e,(5v` f6Ӝ@^=LĆ pr,ZN(cV7Λg9LHgbR*ndb*4ʏP0aÑg'h5߀U쀨i5w\ͿɁ>[tD}9yf  ^Oι' 5 J?Zs)Gh߶[f8ּv7L}}њbeovÉ<ͯH}m5i/[aMu5m-,CKDgHuӾGF\Hy9Ty.4O7Oی}gfrWʺbeekrB3HX*q:vb񠂮|I1?U1?F1 =×`SFuǫkۡ}56 E)˽X" ø cUV4o)5_+4I(.78s¯ ~?*&zbPhot4s ,\K_k 8y)Rr^gקܵiDZz((O#Nw!Jz.7"K{C&}B]_w4[vx%[N&wHj)eM|. M DIr]NC,SżTQ 2eh.n I pH!ٻצ0&!tCH1)nY,<%IBΊESlEf~C's&2MKW #l8 b#cY nh TXχ}/ͻfV#ۯ}jmk޶9Lĸof Ck~>NIl)Ϻ$7xZe.`{We]!wa p=(SU# 2 PRӶ k' 8S^apbc8J3џ1f1ˈ#6~6jQk6xOEtRY3kJ-l#5-邽C"1?3טrAВWX׸= e~!]iluBSk3)]|sAiUz.$ 3s&Xau`'k"8|H?.:̙ѦoŏNd>b~ a=F#QF2[cCd^Q)P~8ŝ3 1xb6f5lŅDq!:{P:g°:u>-vp~(~WM" *y9> :Xڽ({(QK; ف;?5#@H -.|p}\ tw}+sp pKt$& h*1p{IĎ}#D vk^SDIv/i|G)sm-OדeƇky8=n: oߣw žA\Yoxc9Y,x]XM/43iE}LzQUAGn}7.ā> '_l473NAh_ u,O% U<)>sD Z "+qx!IWGq]^dzgO ҵ~> oRmZW(}ӼN]Zoa ެ=ڬ//trqտkr,Sv$}%c_~cT*_\?{\%ӛiPhatt#d3U!CLZ[ e|QK^.=VnVLM;/rrNTʝGLnuϹJUȌO`f, t(hOaw.5%촏}Q A  ޗGd'ϟ}XQƠ7d_s[>؅ԯÏf=(*"!uz?nXzReZѪNEӱ߭G y+; W4ԭ XdC\" ^?蜰 J{?gEb#M |XT"4KOU%>-V 8 xPѰH;FD)ַ)ұǯKA>n gv刔_~,} &ѝquTqſ)T/owւ77{DcWIrG2T(YSt/W hM&8|.ltsrfq`)l+M[ZY KgB\/A Ni$+vfΒD/6V/Anz E^ &eIMWTv7#HG+ QJ6[NڭJ]ge/뤈,R&S:U&s#{!Gor}vٽ3R^F~JC̔-DDSFQcM7cHp91+Ӡ<9gÁYs ݿ[=$Jͼ+~+Gmg.JЧE_`pK T5s""TvW4Y!H _wEdK:־Y>7|ʶD/5ߵ)-P ԛR rmk׭oCjo 95G(E ;VuJv,͙ X᠇UNcYlŀśGw*zDTߥܥL)3f@}Yj=h?R$GS]lEiv1 JźJ@~օKM"@T_mhelXw3[ﴶmRiHe?!97(\YRZJqcv]`[jW5T0wA51A0OR7K > cqRETq7QCO+[|r.vފ %smhx[^hGPg#˱1>VҖh8MϣCඬ-mLf7A-zQpn74LC H wCp0ۡ <Θ㮮Gޙ󢝬(閟Q#?-$J~Z_5o 0;͔E/˳g /d{endstream endobj 99 0 obj << /Filter /FlateDecode /Length 159 >> stream x313R0P0U0S01C.=Cɹ\ &`A RN\ %E\@i.}0`ȥ 43KM V8qy(-> stream x]O10 . 2D! }I.|D/J`H_#490Lu@vw=|ZC -A#EN?p6MWP_.Xyp8I.~r 6/ASuendstream endobj 101 0 obj << /Filter /FlateDecode /Length 214 >> stream x] @|n钥xa> stream xklvsB6#5mKHMzd\$]d[vtL[/u'(Q7[LǶl9xfMdkڦi^ ci0 pF;~y@>/UX:LRojnUu]/{V U3j}#?Z*d:mJu]v6jo۶K`3fa0(esZ{j4PN:(^[u[-Z7l} Bg2hd1Y{)Mllf x2`cX v{#' JXvE:z^UFP9XBcI%B}RYI48|Pig{2PHy`bzOs Gsor]Iz?5:F/=I$ e}C-Z*J g:wHG;+piN>DH*o>0 3N8EhS48#LE3wHawLR\៟F\G&> +z<@{r|[-"%h@5+ɺUDyQ@SAAÊ;-"8bA'Y_YKЯNONWb]쪉bF"$a^P<"Ou@iYURɂYC !Ϧ =]3|"@2q 6AϷ10)bi*0!BAqM3޼vإVepah]yj\;?HVHUJh@>.H0 )mUh0 {iZ`8b%qsx-eFUO_u09~ ,A z֨f Wf:RnvWI3hl8%xNnO;V[EK4wNB@/3ƠO&Mٗnx"6 !D YSfOٲ$H%%$NZoJTFM4Cg 0%ؠt[C^azܥG{o)(ε4U>J7#,(-$retd돜c˹bpri=m4+Ϗ(eI1Qdz΁#-Km=|7T]$-ߤ%ԶB>j&I&|a: N\d2ʗ5WBP iQ0Qf2{úY7ޅ֫3S#$bb)u8|uph!Q?ÕEǣ#d4QH'LHg._t @p09(Ճ{i uMѠo5 *rAuWFȡI1HCc+WPW8X 'eYQ֐?o-zSb_FSǾ;PPݐTo/(F!"3A v0sQ+MT.vjjk1?:AoRendstream endobj 103 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 407 >> stream xcd`ab`dddw 441U~H3a!G=k7s7BG``fd/mq/,L(QHT04Q020TpM-LNSM,HM,rr3SK*4l2JJ s4u3K2RSRSJsS nӃP%E )Ey L@ȰaQ,tj3ߙ3{*?٪*vϑ*|?ʙH~_%;{tnƦi c~ↆɆMS'N.='vMj-9}iz7ĄfL=cZ9?ƾk3XZ=<<@Pendstream endobj 104 0 obj << /Filter /FlateDecode /Length 5547 >> stream x]r$7r}gGmm/ЃWU!Z]?3I$#lg"Q@g4`AP U$yN^t*VT?'~=:>?~'#"ӳ'<~%?گwg'.~韚_,Hx( /bcv^(B1z++C{hU +%va,Zh|bؼƶzhCް:q!L_C0R=C Xu[OߥN-/ 9&8pn,0!8p Nj 󾣗順ʭ <רoK\tus8h‹ T^>ab>&:wt_}/'Zڕ1f"> o5}c0 F"jQewxEێ)ӋrƎqqK *mٮ e 4BjE@7mUNnLoC'LIVI:F ju C[ RseP(P5#na-l*:@oOhDFJBkqB [*=j3>Wyoi,RL(16j6Lc̋@Kc khyޔ΍`LkN:ҕたoKڪQ7r%ZVt;:~KجrUi|i-KK,:kCq/n\Zyu1:Kj0Ł2.o; +aYK/LVڑvU:R!Rv$Ry/oR[RdvF 봻v7 I›}`L59C1K$Þ.]Ya%~qdk=Ú׵NM0NkM{W6]+LXz&ߠ20fDԅ$eȅ&|]t6j3/;p MOxFI4[|NP:M#c#vG$6Jo"ΐI.#%Pv0m]Q1m_V|̺P$Z9i%8peBɲ&R>QD<L=6sx^$'o`A Q}wѲ{{vFZ>ْ Y:P 5Zg>0bvYͧW;Vpۓ BuW#Rkذ,ru_Zw!(@~z$j̸2jgbl0H&98U?=XZU NLYl;Gc:oVQ+Au|V`U"  {AIw0$SNM_&ns# . EE/[.K2]׉ BAZ튙{N"RbrY@/V{r3h9[j~6g._1:3O6l&ȗ깶:et0YHA}([lèI,J8yYm.YpH&Q:`YmD@9=h@ms^]Bˈ+Τ{[Q'.:z'$/П2}=.tv<0aVdLJ%hiu!S}G:yZ/rp 8?бUWr}/zN7,}ˤNYh" {RC.3r^oj}מBΠv+~"p/(CqJ ȴ[ljuEeŮ:[B;_r:U{ǃ=TȧvBer jeo󴯥3Q7_7" 0@6!iME+9}[%RZ6Cf X3,jḋY2^*wl,jTA37̌%`;k ~@ÀLc^"b}d^}e_H,q60)/ c-xVW6j3-0j~9LWZ?WWgmHb0No\ixnJE H&VnnY<a kv5>8ܫNwzFP\*\/yi^y- XӢydT[AÒqʪx,6_VtF xO61ƎNզH{\džGu<܆3q ɞ[o9kxwq\ C M5μV N3'-Auꕻ?cVMײb~`}YmُM:pI5"TچaŻum^CwijʛzԬ._ˮr_:`{@w#kLs(ҁ%=xCVzqM]- P80P,2jϨmyKG.t=XyW]f!\`\Le9fMS,Rm }sקg )"vyjWKT¾:ǯԐVbvhlTGf' qC0$ĤH,k4ax*T ~]cxX?Vi|Nb^=ѫJԂWtHsDH,Z4fOJ4~Xe[ϗ#]>oFa_0}C#5C%Ge8砭N\qy)xi_P4ggqUxKb&?-7H-IWez9eGCcuWt*ݙMdSu^YHs$j63?yhD' t́7:^XޡR1KmM l|+LB>mue1=1ߑa.*@w%.(a?b;kE u\d%Ej3ǰ[M^2'r)4P]16P/zY&#_nce <5cR04YB> ] g|$lNsؿ)*nΎu~t˥4A98u8XM-5M$75YՔ4* ]y5;#h 8DGȱ{S'ɞ1E 8~\= _ZٜvMf7slL .qeṊbƘ<ޞemgo[֦B``D.EM:/30{\^7P=s6g2XL/mn|#=kG?z\turX.̮Na<7mڽ祵)ry1`@} 8ˁ *E1I ]eQE.꣇߹CyE)V弈 :%䞧njamuoO*sIW-Ǎ czn=͸,/N@7~! |ߥLMi ^ ^ 'T$Y;Oc&6R6uPd-0WPۻ:'V[eL+vy&wӅHq; Rt=t oܘ{n~7WkEF =R1rOupQWwd9tSMj=. p/OI5G-k |ǿI&Xm(\׫, YwDf"1apN8͈:ń4/LF 'AӵcpPTGxzeІ\p^?ZY V~FI{'6%_XJ.3|va3endstream endobj 105 0 obj << /Filter /FlateDecode /Length 161 >> stream x]O10 . 2D! }I.|D/J`H_#490Lu@vw=|JC -A#EN?p6MWP_.Xyp8I.~r 6/@Ssendstream endobj 106 0 obj << /Filter /FlateDecode /Length 5784 >> stream x][s\~WG49Y?$[I*lUbsv+Ø(Z$)ӍgpBbA ht}'b']'/޾ӓoO_+!(ON_|;9~w/!_;=1qo. qqYucux;34_S8.ߖ+Z.WbPBaLTV6FX[`W1DXF-)-i<:e#*giJhC9 :=:p7K"TA>հJtшd$BС9#Upt -01 ,u杷{&mp%VaO(?DNVR|\b\&4t/YbZ#0PB VR֎Xߡ .}XZ nd}T\ 3+xYl$N+D,^MrO_ qtai^i:@V:Px#eȡK}(c::\)}i+UY;t7C+ <}+8Ta*hE9g:h}$B8Da&,i[Fm& * OkD1AAL4Ctbr(iZWչ@2=8IKHIΫ nڪxr"-uݗ]3zt9U |8)s$*I;.1Sn_|[?%=Q0xrvVUURle_ M5x n;£>iɍ-#Nqt`r2rYr۸Eo͹3 ނ PܖKy'*p52HZ@6WA)yYp!wP:d+@5`#e% pVFK^xn_g)b2 UF_ Qp~*&r,.L*:D%_=.o MB lD9)߇)|# z ymt;p0HƀW?-zg\|Mb:*G**VʏJ(~ x&V`'N,c1pb-Xj} r:zzoO%d:>)hfL{]2k8`0SC9zE rqzSu7xigf>QW15aK/F 6~Zfƕy$D*Mm}t4"QhQeM>(_˵M~͇] jUwI sp8\/se&/ @ &8 S0e۹2hb#jh9= =Y%л;z쇑eq] OouU0hr{ZӯyK+oHdoWoF;LLh $I}ӣGm҄ ,\1Vݰ/t Qna0X^y 0F0~J@/Lw;t?$xmam)nZ_ΝrN_J6˾!Z*ejkRrp,MEz2V7y]iKҘUE%!׀߫bZO?+\pf24 qI5@r4Ʀϻ x >`C^@lo!{߻9.Ud_dk6 F PH}&̡ %{R`_c4KbMD|&Q/M]4DD15Eb٦ZfL ֑g$:i6OgLfs/hHDhW'x9)\b˳G rOʼ`puA CT88B+Vfӯf1fִǵŐ.`6X0ߗQk~YSE`l#vOՋx<{܎Ti1NB l-FnyN+Euاat̲X,)^$/XR_'Lg+!/hOM)VPuR՗uxGw$l9(&8: }rfԳ[WAN%9(c5 ,4~E}sJV" irR"ng4^Q +M{-D %(%eZ=&%bӦy@S=&d5nHA{sJ`u|z B@beLT9 H{ ]wv.H +AQ#mj򪢛2>98#izxc4E dޘ~9g CJ,xDN ƶq[*).;|_ͽq9c C< O[Ai= & OHKY6zZbd02 ?l x,w9LI;Ʃ ö/Ɔ M!DJ.UR{}^ W]-a<pN}wUCr/ XQ`ƺdTŒb.ga*kq 4f~~Y_m2vӝO6X,Qk`@uȶ*wfXjKwtc َ!Z$[)Rv&%`)hXCf` [a/+рʭxj`l7?myla]H(#@_|ִ^"$$E#'[jt3~lH괐-5{ {kmjKV xl8+R!C-+N21cp0;RhE1)0HEdo'v6&Mgz@xBP!6¢t yvGJUS<>3LD}ЪʆUdXy-BsYdޏÝ] #s/A1fzGzz,ܖ1nLn lu"([s0Xr HPq{t H \HYKISp _V:UŲ]Pk=ǟ)'O0!{Đ43/uX6t`",:dl~e}pxs2D-dVXYKmA*qEiPΑ s1ep+nv\zrZv/i~qf7}BZĘK2ogw& 6Uiv@JbB=]H#ގjk#&;bWZgI? QSdOTPV>ퟛssbZntLpV>p$œYg|ϼtګ&"m0gUւtjnc昿WÙ&^/{ķBUW(nˀ*E\yyCndM` Ϥ^:wFTA0)L=/%?fn>'z$B%6է*MӸ6nՙC?P.J{{7?iǜx;i<]uΊX5²OI8ꗾ磫ݹ2҅o<[7nbW._4U걚%`juA8HЫ}rlkh?DVXV_9.ot4W& f5 2~w? endstream endobj 107 0 obj << /Filter /FlateDecode /Length 162 >> stream x]O10  ]ZUm?eB:gׁm_Xց$i, x`ES{endstream endobj 108 0 obj << /Filter /FlateDecode /Length 5738 >> stream x]o9rX~lra\n $>-y]KH5NUM{3#^LdX/s1s/3IO/,#<<~֟{GVϿOMxٷ?(p څrum <5 13Z] PA+%1o;R7ޤ8ag}]5rxx!LVAL:hN֑? 3e:Z n՚aNGޯ1|l4PRa6Pa}Yqm+Z >@Bx䘦W.D-a #5vWtͼnpFhϿKV.e߆! ::{| `L`PX-u6|A=/7/$PD@5ᷴ!dJ41XrĢ01TfA8lW@!EҰ:jj'#s̀T(_TY( H[5Qe#`ZS+:Z3*Xw,2J=@^?YZ)1Hܠc1aT!g~SEh3)Ү nZq^.> !mbNQRO| E$JxB0#m paa]78`zTΗ68SpP 16%,}Kx@Yģ1=뷴tަBޮ^8?;4/ks]wyU($S0?: S/j!b1&o\D \&1Bd9j(kz[5Ha^qy>S6a>i`ȷ$8m߫XM$k`AS4ڑ,1l]j=%{wcxj )@ L/h务.<=~jT,+d)Ь̕Ki\wUk0>0 闭J?=3ϚO-9ށVDdhO4HDS6׵yWWI _{PkԶ|A*Odmmͫk6?mͿk6׵7@ $h_dֻ}t@  T: 6uo' .k nXg>LmFd}wɀGW9k6ӛQFxBOW>M~4zԕy 81<1aJ[L VU >ȕ3f|W?6dR昀peJ_!4A^EPW49(}&'YJ&x @Mg6=ֺUsԙ@w:Mժ ى\XTհ{D,JkyvdХ$:"x΄x;٠bڠ泊_`Y0FD(.|H&={@tYT[u~[Um?Kbfo=^cmv}i$$o Tk/ȊV kWSJ VЋ "f^=ͯYi)",y3f~jz POneTƵdF2 J7ՏgDӛ;{-6Y&.&4D&)eؒ_0IN?`8m\^o"'ptA $1f>Y@E_Gw1UۀgQFޯ%!Z $_|LR:MLJCtIT"mS% d,{O (CϞQSm! ܱ&FyNT[f%a_*3+-C6K36(Kog8 V L<{E%M:ksLOD4#ʶY|DKKơ5pp ewFO"Lh ECHJ"/Mw]UrFC/?ύŭ[ ff{ҔR0ö.ElY0'AppWe^]" |,}0 xS% 0>,; aqw\K,T;F+39%wxO'y C|K9d2R7BH3m <>.}%y(:7 VF y f]5:F{e[S-weJy\S H)vۤ[TS<?<~G8W>qi)s\ OPPG?pHs֭1@O(y7 uR)J{)9NGY|  @r'#C#b0c~ײq T#$ #hɅh&Յ`Y}L7xPwl | 2m?Y&YR~ƟP&AA/YzKi4 g$c bqUxR=?0a/ޯݴ`vܟ@LI93)Rf;RBr"-)"&[=A!m2.~IX<Žկ%]Z~[d.lG JZ59ETa!h\Ѹ٣`O9 _0r9Oʩ=9:T'x,EDҧ(J847H [.Ko(V ]f{e}Knfڞ&=^ya] C 9u2pq #GZp#lVo605*V IÂX9F9|`Y8P$gC*c3w~pq2i+WI0ObxY{`>m 띌׌z8ـ=TI!Yys*5_&KbomM=1I ^0[0D4aFD:3sWܰk[Sra-]LɞUmk~_`,Tdr/a|ydGF2Iw\yhXϋKQ^|8}7,U Py P[r|S++u;^vȉHEam(B:TX3/a!OLȻ&r:[Ww՛QVOdxY5 擣-!dx@{^\?p#)y<3)?A+TrA5y~P2*Bu$"7%>Oגfk]-c.vK%ہy΋q-ʱ00 |̺ '9 'sZsɩLGyҌd(5X|ҝOsOwůj~ eHt *J_aN8*M΁d֝":%=\N<#[r2c5mg]ѝHK_M?JBE5h.I.d837%Oo)@<' IeQٕ:7" fp!W8/Em^Ho'b)Ϗu*P"1.z }=5樶Ҧ2`(YHeWJ;,݄qFo)/O1>x2X?<(_ p>XPllu,}\ְذ (q۶gϗڣ$Z:[J!w ##9"zz*W]g=;MT4t>]4 O{{+[8,뮉;53TPt7)iiϫRc?M~&dnviJS)':u@YX v`Gu<77Huu5 Y̤i &JLImVn3IS G8|v#j8ў:$[g_V4FNq$ʟ? (E!PnU0f0KܟaN$#nht2QSssDn #RiΥOyj! ApiF"mo>)ZYڶ3+a&m ]Ѥld{$}I-!]u}H+‚n29ªyI6zښ6 :qnkx HÐLHvP+Ƶ몒X\LCZ-a#*%UR,Mb~k`([:y}Vl^Oש駱-ڲ*_*RHgÚ?mLxPۄw\4Ò>9l;2OU䧅&kag<t70D %5[B,."]O0IMXsGQeq 7=iyi1S[ݸF}I;To-0сgP#A!^(bS٩L'von˫J=!ـCꨚ"7C/$K=B 4m'}ayU2m+ȏIl7!~YW̖z8T3B!tW̜endstream endobj 109 0 obj << /Filter /FlateDecode /Length 162 >> stream x]O10 0 0~ 8@0%!tpw'0^Gk"GpXhu[@fcA剋7OH.Oqy%:EHAڙXWU}uȪ?&]mgM*)J747I3 BSvendstream endobj 110 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 398 >> stream x|CMR8$vz-  WTQmqCopyright (c) 1997, 2009 American Mathematical Society (), with Reserved Font Name CMR8.CMR8Computer Modern6v糥ޒԯȩʋh^imz^1!lH컿(C`]ZtVj|tϋؽqhf^XX_wgq]hy_vCoa  7 כ hendstream endobj 111 0 obj << /Filter /FlateDecode /Length 5771 >> stream x][u~Wyy +_b6v6` @h4zifA~v΅UYٯ>~2dO+,A8Ξ~tl~'zusy6okJڼ͡6Cmޜ!Y9`pHyҿCy Y[Wkܐ_O V.zsǏ=3VquMO8A)#5^[he@BJv4[%k8}+d!^𨃲4TTiRK[euLTUv:YE)"~ lFa+>ՖW)d/zھѾ=u_ wVs=y]+}rڠxSdSV7s8^MXԌ䂺&!+~z,Y4H%DbEp0x{v.^[|)nt 蔁m,c-O+{ǜ2^?amӴ&0J;Uڇd9~7=lojٺ}}h|+hbz[r0sa2W)?qu3V:Ύ v?[)1I'-t~L&q?S2E-mXU.A" ˟PgtJZእpߣe(na@+sEƲ# @ 9p5mI[%3 v яԺZsko̐A zpZ~j婵Z꼳ZUU׼:1kYKVR+چha-a xGC4r"@{?Y)С<#TlƯkum ͻ.낔C&1!ށK@6yRu6'Hn^WhÃca Ac'aMU'Bm pMOj_9H'bnvTE DUfbSj̀p/⽗[E<0 yсW[Y0:O褣S 0fjmԺ|vvS+Txօ@0<Uij@]8sgZ}U=s789#d8Oݑ8n> _](`3<+Pumn0v5|mgB-WtbOEP:vVsu͊jy|sk=\ۮkCWڃD_+Ȍh E8}*4V1\dz`360_=gh[*HVRCVA${w<[w_$ߚ|_2}F%'fR.,Lؑ t;w)ȕ{p/H`.0y];e( -"(4]gZjI/z&sqШ#(g"ݐ~ЮWhb;K]X 'Z#p6Εᆎ5V e xgV얶r8úE /Sϭ;6XMhC4$9$z(όDӐhsS}e&kt|4.Mxpj}y%1f9o/.-uܡh#֕®횢PJ?kk^ϻqE͟=vk1qSPדrqo}y`o5Q?͛|ْLưٮy/X|ɛ lI ADu%:fR@9ř Ec\MlI= #paW N%/&d0p:6v[Z 4- Σ:+c$'{\17:IP%P{FBvMZpIhϊLr_ERyќq8&}eҁoFhj Y[=|WGzf~xzߚF<\4j ײ 4PgiR((# ,$xS4v6]Z,Mv,$<0bܶ!G.M:QLT<+&)]ϩ+;zvIa0'K9cS:ϋ/ ؓVRiNDoYƓA ojSNI8%AkeAB a1Yy5츒H S8ZeD S:zva)u1R`\ u& Qd(ic|0%FrZBLRq28Ap"~y[DJ5'd&év3{*tk զNmNvM'EQǡ *h)[84X?tkjQ!FpD ڸv 䛢5G4ilyfA(ieB8Ę)UMױ> gE.qD(Z`?)V)&MOS Ym:o6ȉ":esM#ZL%IAIL-;Qy9z$ԟPRGH^)@=ѯ^;_vh""XUkV6Hwu52dž5p!{ZLj3ȏk`Jdi_\  doN qϞ '?j2o+)`DK͎1$K \ Է*}ҦK)emRF`Zm; U5cW>>ΐISݢ__Orx,.f  %9 o\ ^4Z17"`:/@ C*ey:!ޏGQn4bW5+4TߕH j SmƎXT\H&V[^J(_lλ!yf{SP&kڸ{Fyd착͏G>%2DWx:MwHS>e?SŽEtZ~M/={}ۋ\{ă*"~UZn#J63.Xzf?FI@þ,*Tک,l4v<+5x,曻//ukaW_WZo+f̊&Yv)@v cBqheۙE5&m3bwP+5W3=H4<4E R q"*dEFZ!O4bS0orx-00N)R޼>au[V:ݝUiwωԔH, (h'v8/ W5USWd|Np3*aqvK%Z~ 75K:Iݕ(W_#um *(_lhwٯuÆsD)3aS΄ 4Oc'ߪB=Fa'YR:έdoۘLsi=)V)0pS{WU_X4ɛD]@awKb籔K~.[ά׬_gƎ7 gU# cavoڗx8*F2k4h_c3}-#5KQeK.vSlNʭdJ}^1?styϸ(%@.++ y=‹s5*t.\- zpaZ׮R`FdqΖh-˔KLn"6'E ['нdv6ƯC@qD@𓸸'E㾯S(BoC3$"J`|8/*nzqQ&޳9#/:񘏤,A L's8)aGw>JNSR 9 )DԾOhϝL8:TxB^1ןc5Ysς7aPnv!Tx%igQ a^-RoeBSYYu\@٣/ 9UJF y_Qb'vL)gO)rtIK<:O#LGMP#Ptmqi.TڹDlSPނML>cՕ8Wk?TI6ũήnڗ%ؔO6i:,H[>~2_7 ?m% 0|^xi97vsEKGj~WQF*)F,\,t1j}0NM&qM/7om:6n%/`nrX 6P _'‹eQjreXj.js!F,NF0G_@s~I,*7^WayzŬ~LV]j‹Z{NG,8%F70w: yM塷w{Ҧ)s/CEMrBP-Q.Ñ%^>"@ӢTQ%O5D,3^t}jB) Жh$oo=?jkiSnC+DEt++܃'Sп3V%~3bwq6r=2# TXAZH]e5pRM v! fDЮ &sYHBJܾ5S&]հ:u釥 ~POA#vvYV::;`8|Kg={s7c=eip'ܩק}4G\aog݅-)eL/\23}I [endstream endobj 112 0 obj << /Filter /FlateDecode /Length 161 >> stream x]O10 . 2D! }I.|D/J`H_#490Lu@vw=|*J!􆖠D[U]km'͟tF{8+/,S\ HJ$pLg9AAStendstream endobj 113 0 obj << /Filter /FlateDecode /Length 5669 >> stream x]Y7rX?bB/vlqЃ򮽎v3 CJ?vf$Q}%Qb_ S1S7'퉤ߝ7“!(O^O׃>~ޝݜ,oy| }ɷWK茉".>.~X0 X.W&!|*pk(+) J;1(jyGK|Ջ;2ס+&,^S'T^:F=5irq].XkXNb31D ЇFd-VXV1r VMI"s 'R!d!B>U,MX*7gX(}c5@j}CCJ@k8: rBxځ֗/b:d?Q'i񜖖nv\Ii.88/|G[ai zE -,5U0J7Y|]Y-~LZKӈ Qn/dz [i`+x\f~jai$Y&Q^ ɷԚn7N=#C 'go Z F] 6<JL}]BAaLaIƼSb\)?)pw&IgZ!Z$<sI#ࢤI^%y!TeyB%yP *AjwxRZR/k/kqSϻ}}K,3oH :c62#GiP(\؄S}PZd.e;pI=oTX(˰ t$s@P7xW!ݡ)AԟAYoGkvVD!`-KdLck+xR]#Y8wf4|Y=8r PV8P78r4絫⹎{Q[^ζ!zz&ͮlBԥ6.sE ˻|AO](-Z\w6hNbZe 'b;M*\2ѬsY|V0bGcCsd*Vudvo^m %kxsfr ` -(Ƹ~Xthvp}TG.0MHښ" UT<@5Ra_7Aqq<<|&AL?zum8T7q[fM6QQ?CeuTg]5_HwI#:@z-0#;zQԶ liWq_n1Z(n~nҢ24vv4L8Pg@sZBa_1j5ssلS,YɮRQ(k5úa!94?+8ۉ4vLLcӱ9աs|k3@Un!_?t,V J@-"Q`%DÒ A`HZ~.\5z·ʀvDzKXqSE{CS^cָyOyA;;AB;Q,VM'G5oLfr+'"ӛq])gޒGgV)MaAD<);V? 5&L'l`, ` ߠ=+<]M ONh2z, _?iLW qJ}{3Y_i_;;8Ywma qd,}pF.Nl>Ӥ/1R_ E-9 ;X Р?^3 lZlٻRw`Xg#\ ?k43ZZdL/üw@‹ UȄNd\D7It췶`lQsG.lf\1 w";q(NZH$xoZOǹmz@(fpe/@.kY\]` H(ߟLB!t?16WIV}9 `T|U_v?Keʹig?ZWkof@[r/ B_Li jϾGlo˒iӏ. @O"0N(p<.b:TxJԬ{U\@b' 5&Vd L2c[uؠ|Wȍv؀%\X=۪X?N#gM-o-/O?[ J1uڏ2f]Go"'Lj>BB)r+x <>y02%64U3X&~&6'`Iaf+nf>~OnI,F}O] tc գ/e$=z%N?X!6m&FtB)7%k^Xet W \U5KdIi}M-Q3#M0z<]dX?PLVoXImcY]N1ߖEN]ӈ-&&?qvibfſQ瞧Ӥ I{ʡ7mS*h=&f/q4 wbA=Yj6t 9ӆfHbQ [mu!y3^v@u %ilgn0E]iU+w|-l0ϲ+WI)&'h$GHirfa Nv5K{Σ N?蘱p8%9&`4G["OmJ9Fd|;j=3Ï joOHv?ՂI=`=1A|C̞%ZZk)vgoNؚ]ot9=Rfxh2?R$.^,M;&_ƃ k|F}Pj8.Z_Tqp$4(*T6yql`N0&Gv+`| 2|εxlr8缇mOxE^:h2 ^/B`) ,Yn4׿EF3e3Q\2z)h蝡uIϫL<'3k5ͶSFu>9QӲNOn 5K%@ԅl?UW}6prVK]@/P̛xI۬< m.HSFȕ0,3GN$4*vDU['8,AK"`,[ 2/kX |)ʜ;7nrct%NQ@85qΰ[Β-e0S1xZ K5!9ERx4n6^m#٥`r"m5E)YST}N;(qeP<P̮;ڷ444 (ʯ+4w M>6)簽:0r).(I #7b]jNE JV LHL-C0˳4ZwM3Y[OvBduuKJ@gnt4M[*"~A`NĎL .}L|2},Kth@Y]2Z,}-0'va4P% */L 6t5j@t/1QQ)`xgn s`vW0U$ 6ƖjLˉn1M'yr'6(1.<`'*lX}1YݰNeUvJou, lžikEw?.axXjéSVp#R~L%vgzo̮jGF=$VdEߚ{jkHs92#n㱋h󫁩 q,bں,YT5ZA\4't$V)S{rm;$w~-W)rKrUbsr&]74`Y~xZ+uX/i0a)ߕh5GO!?m$Syz{ si*h*k.euߺ0wnwID&Holm`9YKϨ>oz+98{]z&=SL$*]zYslf2.ZM*]MPu!Quӕtwta}邉[ ϛ$;ƂC&biO.v̄{]t{kU|jQ*;=l4;x}^8"XZI؋LEv."{ʎ^w~EvwM?!m65Ԓ^w|H&Zdig9}!e_KYP`{`/(LhFKJ)yfhZ 6h9ǧ~c7#&wRe< SyFVz1zӥ@o WgnQ>9 K7K,(֟Oi?z٥eMUl]n '_ u6GiQ0>$9O#ļ?7Miendstream endobj 114 0 obj << /Filter /FlateDecode /Length 162 >> stream x]O10  ]ZUm?eB:gׁm_Xց$i, x`FS}endstream endobj 115 0 obj << /Filter /FlateDecode /Length 151 >> stream x31ӳP0P0T06P0P05WH1230!U`aS027i`9'O.}O_T.p .}*.}gC.}h\nn@n.P9?47XΎEAmGTa?ߠ pS! B)endstream endobj 116 0 obj << /Filter /FlateDecode /Length 159 >> stream x]O10 ‚XЪ@p' aKB,N>al#gpƲ= LeQ7-Uy!'8 dNP+ɩڼ:MWHAB3O*g fh*qC in X3 >1Sfendstream endobj 117 0 obj << /Filter /FlateDecode /Length 5023 >> stream x]Is$9G8TEL%9L@#80[uO.i ټ'),e-{CiM~{:~_/8wv}_ty~|ry_VvYNZs|r}4x9O.+ox_why)})bf K+ūR'%餼8o3d& )d1yΤЌgЋ9Ή3f"Uqa@Ak , J6t0n!97&a]X9 R8&*#GcVN$\(|UyEt~ɐ)1]Oqr72,q^Y6S^._o$Q؍cu X]]܂;eavr\ۉNI֛;kCFaK*D.rM:}qM;o{\6fmZTqX0&(^j8q& |coտZ?I.m~8\җVg;%rD mŧB>|KK)§L*qYZ{,B숂'bg|[xM#Bten%vTҀU jT?kQ:!+Y8^5^o*LӜ64HM,fGԶJ PztgPGc쬠^fjD/b>Q?5@N:4fyi `ו|?Jޛ^]%7I9Ljn ߙ) };KW쇫D`/0' sEly`E(h9(\_,H aį%a".W#D\J1, ǐVeVuȝ*c=K+{Y$!vn֩ᎣJ.^nN1>tPey_@[X]x z3R˶ĺuIG pǮΈĂ㼊 p =e{0wXH.Lr@5zvsg6˥&KI@lO^lUz(#MW|bO⾭>"JW6*p(]96'1}kh 5wSsEbPb| @2%`uzf;n9}dPTE1O/e<Ρ5b݊`'*Ci98JjT-<`L,0i 7F <)ŦbH,3KTU5?xܞXE H%Ϡd- ]\@r_mUVM9dSwNUXy%WIbjˤ; :&aP /Hk#+o3Xh<,^`!gu?"JlpJш-Lz1, OFÅ3"|0Ϥ* ї$G *j>9)au-E*6x\+Ucתv0q] &4Kl%NR/ץ,Rn]2K!=<.n D@+л%yۦ- }!P2ğ!+bH 1l)uNt }y} nYU$?urX'AfTWqWJb n %Wѝ-y'1,P7`e)5QRFu%c )2ou#ґjA%b6[ pPS:v!0Cటظg;𲓊'@"_D)3]^i_cXHm'>,b zT~>bDړJo6=)ގ=mQZg_DtIX/CiHck}T=y*H~NbꖺgHAc4M2"ob LuMc* N9.7RGE Y50ݖG1pz/l3Z\8jF\N1lஅ p=6Gd7t3^2JY9jKỌO##D SWgd. x$U9΃| Co,MzZŧh!M$d :rf%We)M>OR ]`u n dU~_"qDfb!U.t kAY{tӠ, :W~,ҷt'-/ѹTC6'cJJO2)Sؘۚ \. = }&1BO٢~?X^V,z!gd}8ik2Aɫ/>TwM8||3o .n&: lC2:kae`fp +Qm1-Tsf>UϲN2^8P'耊,L/Jd ])fGvJbZ&{_$U/ERXK*#$mUルbSzP_$.@_e{'8D8-ct[뤵{tT/ g5KdC`߄{Қɹ}ҬH*e)6G2{mON{&O%4,)ʡLSb'΋\pGjEXр{<^R@j4hp- wlH=F6c')7g > FT\b&nظA>ŵl$1$%9DEaXE I3PS4V}\n( FwF'S<1X5aK3K7%(!j6]Dٔ>^[4.^p xI RGX29,ͅ/F4QnkxuK胎F"cB%L2!.N]\12ݻ F.f+)~(?OQȕ9?/}ʛ=铟7 wpt$|&//]Oi>݇*:Raz4*O:Vq cg2Xlh3.B<<17Dc6Apz)]lr3R[5~oO|yHJ]E)k>+EZ4.nŝRkSx_M(_*|!d<^|, &mF.9w >HG:?-m(=mB+>>Qǝ8*N뷪:endstream endobj 118 0 obj << /Filter /FlateDecode /Length 161 >> stream x]O10 b C+qP(/ СY:ߝ|pFcpƲ- DeQV-Ɠ剋BwOϲ> stream x][sq~W#X~agŮ}X٭TESea(RWfW?n4h h7`~8</}8z3?/ߞ? QDyr"ODA{wrO /1𵳋g^)1q7Hq5m {ԼGcEWk1͕A(T6c-YZũ_ 0@:Ñ*!TЌ&:m]IZΥQ锍|XJvRHcBxVo iV|QDkhYA3[3퐰= ڃK]M j;?J\fܷ *aL5d>j$na5uj!1C6N">F:Qkbkd|\ .JZ(IG$!MmH:Dª#aXJtyF@$"#9r%áT)RZ8އA|L U6m7sZ)!oWH.ljhZJ$e]㠥-q 3:@x5X2Dyڜ4{(Wy1/[$ 60#s mpE78UZtQPdXCSb(M@9FJIx[[&o*I(~0(RbjCsP%Dt)Ş@EP4w"@E~ C8'6eL=FF3o[Ɔ06x^jM-"k!|][+c\dD bq#/#Y#y' X>^UEi Ζ:"KPQE:L ={dnPUDRc.^]-kU-s-~]kݥ@YUɖ:õI$R#$݂Z\bzXjBYmW#=ܤETY YY1qKj[t7'D nXXR:/wމ܏vlcЈv Jw:uN㘋 )GCMi-)IBM2FD7Zi,05bmêL8&TW5h3-W*H(ؘ[uSBҥN)W4{Zie@"vVAI%2|k)BZ{"V-7r]xCi\.p4AwC]S|w'v5Ħ6Jwbo^}}C]">/l9*Ք)\5 ls2`WS/^ {5[ ZS5eL*̸~9l4ETLY.ha2 dA㴙 ѵ(<Öe_j 3#2$?{{ vA]XhDx Ig5O/+x4䱡ګiSvh8DžVHZu-^tU0vY_Y-jBxPD:8H$7,E Xخn]3MK%8 %IuCn=뒚HxKki`st$gbs V΋CzpYm@ xW#.N@2ۜjZ?(-0u-2c|_׵̾j_wWac1O&Aq}/Q&8)6#_sZ36{_OnՓ>,]J>ꖢm(@UџLLHyu'L`J3o⛃_eJ+IR;I9 Cx]Yz\Vcmokq3/ZѺ{=@IqGw,Hn$ j H=C؁kSHB]CG42#o7ea] )Zd stu~B+w6rb+k{+t2rm  W8 [ m{UJCdžZAs̃kZO]缩ūZ|[c*Lۡ8uƾ1EP'Ygsz焫5 <鍽a˹! j 5ޣ޶nKzjR269'/ %ZUȴ z>ps΀Sh( <'q W/RgUDlvs G>I#\lN!ne.Veu"2Cd~Y-jŋr0<n1i&*>nP!;1379`0* 3b'>2~~ t@9,Jg wEc-TnʮXӞ ڄY܏YJ,[WCԠTu#,d46h % #)]O ΣOs7Aq.bBLw g$ eѨ؇ZdIT0KB` ,a>{G9:[{dɞw}OdGjSgO5i6v_YHҋnCymYȈRY4!nuÔ)+%6Xd*u]46)% ͲK<JtNq2;y|e_3:B奿n5h/xvcH&p@ E#[ vZ+(|W3O-yi΋[q@ɭEfBUX/1~&k8笍mC&\9C0hi#]>f.:(ź ܦħx *& <%tdk-} @,w<9<ͱtǖQBPl9ʉUC۰3w0)aRĪ6f88F@1- 94AkÖfs~yJϜEa 2ɀC<}@v do|$iIMДRg9A%1i(7K=ҬYM:֝$R;3)UvW .@4Y0hk8P[I~uО^"i -t< Dj?3))#K&ZJ!) yٿ>Ec3-g X <=I5Op_ p7 A1”-a~n.$ vPJ}WHae-2_C~ < md5` m,Ro]Dj ܰKuh#.|mf:-u 7Y tk z0[ݐF4^<`*r?/(!:KY <ԘdA x/Wx0 NO:+u,u&[O;1g (X]![y@~v&`*ߒub,{ؽ,RYbo]EKEvQ݇{ tS6٣=*Lď|a}l2ݡztHXYaKk w(cL}_@qǧip%ywA]~8/*yw QKz\:io\b/6 89*C|xчWjZ'ʑx ` ;lAanV47Roƛ4}f9먇fC&:e~9kL}#8`4Dގ%<64&1ڧ,墍k#XaҴ67o쌑w|T7ʎJ"g]ZO{g?*Z ~dǤaI*Ϟ?x_^endstream endobj 120 0 obj << /Filter /FlateDecode /Length 162 >> stream x]O10 *XЪj8(Nߗ,N>~l#GpƲ5 HeQV-ƃ剳B7OfϲUiZB 'mQt1 l.kSIT @s$Lg)B|Svendstream endobj 121 0 obj << /Filter /FlateDecode /Length 5861 >> stream x]rGr}}ӮEz ] ÎF )q@Rf5z.XjtWWgeeIoOwN3ON_>+欇 99}d7lpcO^ŸQ/<M˘_ͳڼ͡67yYjI::M˕frp\.[. ˊ14/0>Όdfi \_ 8)v.Bh|]gyS/j{]kMޞL>sc/.q)  1jA,3ipr/~{y,5 S6nFzЮ_U Y;eP/9_ogKzހBIz^[ 0[q )߈kJX;Yq"J?v]cw2~{G\WgĩúZ\IvFû%LJ+3[Wdt2p(:ηd6/΄Zߙ s&υ04؆aTdĹp. )X*bmzv".$" ^I V +Iሗ0Vw1rC`@ѼIm&( "Q>:)V?ΙK-oHҺ)MZݎ/x8(UieguyOT'a(7+L3_|X$)xsf3╒QwS,uC~ hͣERsc:|5ڼZExgCptnp%..m^+!ZFC)qv㖷yxO:,ĊQUaP-t}IcFU6|WCn<͟j Wuͮφ:<2Y7B |]isHZUUP.aB\jl:K6qEM\4DyVf^9 Ur *&j8#}ޏFAIPeʡ(?/іp)xB;+Q6![R%`lKQŖ) P!*Lz\>\` t+@a˥o¼n9 Kf 56i/Ug:_FsNzn&; '",Gĭ3Yoٖ3uޚ46^GQWĀ&[5l*֋!j_;ETrTI $ wqx5 "9Пj3ڧ3mi/lrr5JQ3=Q&h4W%ZL0FESm3jP%&͖.]SGaj(9 Qg%ԓ5HaK,au$uv6T܋a\>"UȢWʃjݗWWVʂ<P4Sg dX4wJ48Oc~ۃ8@`4C8ދU;8\7H|c,AԪaC6=&¹*-_^][Pޠ ~umR^5C\&fPvl Wj&X kr;mK4` Q`:zL|u FpD>&4!,$C&mgO 3![DL&Ifg4;#fj{-mV!rŁr:Ǐ%@QUħd*ͫ ">֑p~$Bŧ`9%)\92mT(8G$XeR័Û+OV1O:Wa2,OxmݎciTDH~_vChAdI.|?eCPNgI!cnJE[xh4VctႵ{tOAW%9!h/+#y$#19Ɉrϭ۾N{§ƴ|zƮņ鳜S3ieM oPJ0"5 x`,mWIՔ#- òy}B+ lVZ<\)I FЌP,q~iZr̈́i*"hZQ'+J&#~9Uc) ׵IUm:]CBوFl.p/EoKL F,ئYʖZ3 J˭ TϗkN$%kξO Xd9M}*nXs>Q(HQōэ];dFT7$XJG5Mŏ>rRAuZwtȟ80 g]wMJIkG;,Up }ɖni2ݫ*`d9n᧾gN6V@Nywrۼq$.cϘb[s}PJ[B!6[q)(|ⲿqam<Z♌G k^qk;M \Pvr,ݛKuɖmwp5!WƆRuB( nc [`V4Iյy$S1} 4=kFu;="+2GC0G(ň p'!B&CJn* J{r $̡1ٴlYuzY1pRnk?Q>1s)C-;vkbo ]bLYJxWdI \lX:nB|cfn"B~qkf2]Ld-QZUiuMu1_|)![Z#UN`VJa7P<ֳL/~՗҃΅&IOy"'z #8 DV6TQE5Me~yيhcoq#F+tCqQJ7GPS>ޑRo5 g=mՀYD7QaQZkALPi.jL8ސQai 9u5sGYWk~|_tGBU/3 IAk7mm>/XTRYHwd(avDi%Fc%쑷㬙! F|9iMś 0'T0d3p K&uû7F2>lE%25٣E %%㡢 4E{+1ۻ8z V\ڡEgnEG|wHxw(PCU8XضH1v?E@R+ٰv#_^m[uF5;iggSڙ3&5<l]);o ʲk{vl˥Ҭ<矿"(8BSנl$8%&Es!ȭݵ0߼eEi*Bπ(Aae-09x+z_g]xE$I^Hg}#%ﶋ_\:]b0UGmh{'璑9 }M`m'mHU.)%Ynn ̤n#\1&-ΕwޛqEggO,g;arrÎ <͛$#ODG9ȭC .C~̜I6V0OAyn|uDvÔcwIc%f&jfv?73BCƪmJY(Ɠ(lL lqFzGcNzu]F0[D\^D'@ &@M"LrH{ 8 iP%P&XUb7H\)9sWM,Ydc9}ޕ p6 r/ES &cS>peã7Pٗ>‘D#j8w!?A[D_8⒈KOj0v]K?d#Z^ag}{F31۟l3i B x򆧊~4'<תXxEOJ%Zs&[ˍHT7L `IMh1ljc~2lm*lskq'aԏRKJY4 ~IEG l$ # BaXwJw2ymJ}mnjs SHO˲9 ڧ׸Ag՞жNdoSR@ Qt~7I#~p`a1:O>x D Cxڻ~= p88Lr*\A@܍> stream x]O10 ЅUqP(/ Ct;̇:Z?Eƪ@L4D `,,O\g|Ix@w q+q)ZD ĺ;{FVI%0l>nSIT @6榹I*`,Χ`_CSxendstream endobj 123 0 obj << /Filter /FlateDecode /Length 4626 >> stream x\Yo~'#?9p.8@"3A+R$e\JKJ?NUut)Y=5GUu}u/={$=.9Y"ÓG{^/_}_;܊}2F!-.J4o!h6q^7_"E5ڧMBFf>:3*䧎l$pL$T"Tx;,( G r\p庌[RH-fÄBuǙYVG%8xlzlNĒ `G,yzm9jlZ6~ (KV!#d'LJزcK%f  wnXi> lpÊ\ٚ Hũ;g\ _%! 6t @P ߈~MzT;ጟB>lv#R u^&' yԦd4"iTR)54>%AF[$3h챝 Hmb",$)K\ %u2E{PPl-Q&D)CFZshY8 "(#H=G˼`/\ (Ff0s޻=Rی,!A[I](*Mp t|uwE"Hh" ;K"f%8)g:29{k7k\O"A30a'*jN @> v(Dګ !$SKD'>%B" FTAGT9R9dʯQ \8XKXq+wY9*-i<:{pr57HL-*pChj ˢVN*`'ݟt Jw?GwC} pvc\$0L1D[ᇌ}0~5~\5Ei=eX1@`@DEU&?/й^iRW& Z M&~WX5{ \/ҁ^>*xk$oSg@[+qT:,NY _8U"{apqf4z$1]b/ $3'$F`6Jp/g {z9 (@TA 0~4u'Q< ǕJFn7 kS4yS [X,(>#J_xb{` ԬQ@b˚]E0Fлy6M7}1=՚Q3CKT{!ݍˀpaх1̓.kxVF=gS$Z'YfN4N|c>eض%/(8{Z8ˏ4hXGKFCe.#;7Zc\z WZ]°lޮ`]HsE1 OMJ9jv'MktoZ=-d` C艱yjy@vE1yFqۜCD"͠Gr<֛U#ipj\(YaJBJ 8-h6@z{RCj2OMց;^^j W`y`hv5# h0$f暊GWl͟Daof`mCPv62pKvm6O,r&_7z*a?dm` }{i*l4-+Ε$nOg}'η7P݂Uwϋ ``,̓X4oK4Ii+d#|HωsijW CO+Q CvS*h`lZiSʮGŕ M(ޏ@*ZHhQ4JsQxxv_ysyi.J9lr{;f bl j|M5%>cleMk ٸL6hϰX~b4NQҼn>}U7^7`#!=v~'#偌0W ƚS}.?J,,_2ݤ'%sZ N#ćtY,+wcc|G}?x;JŽ{`ow}އ6Ȱ /z)~vQ4UČfA/-d;En`mg֖x*O;5׵;v\Sq)^c39OUhQ O&.$lg&c[W @iZV)4ܡ"2FwE4qr=E9).dDH.?zAV̅{Wc U-5vw*ߧQi?/V igY:`C0_s蛈U7@- =v9xgd63,*~07}-92~rp?I2 \P?e>rn 1T4Ej`ك*x!i0kU3ͬ0>}S6z RH<$8\&pȸ/Mx;:gdዊpdlknFX252ΪQq3 _t)d3VuV|3$}we]@vӆ,Dz`1}W 7~B.e6|?8")q!>0`HFxX[MW3 ]'4s:_l@nI 3DkQ^֋!F,Hk%zVBk8^ksdYЍ]C_5$P:TsDiSJ!D3Ӆfe;u#q: t;_i\)s4v| JJX$y)k t]EjYJMdneIguEYb vewC0Lv?#k 8)ǀ85[D'mUse6L#!a.Z endstream endobj 124 0 obj << /Filter /FlateDecode /Length 162 >> stream x]O10 *,tahU@p$ aKtpw'y?\gG:ikD&똨A[L+go*?`3]ğB\J!rdgdtFs8VM*9K7ɥҴ43 F1S|endstream endobj 125 0 obj << /Type /XRef /Length 161 /Filter /FlateDecode /DecodeParms << /Columns 5 /Predictor 12 >> /W [ 1 3 1 ] /Info 3 0 R /Root 2 0 R /Size 126 /ID [<32548dcff22d782aecd3fd1b5402e742><8e49d686e7b5c193bc04c9a6b36c7874>] >> stream xcb&F~0 $8J+?& !(~A$$d@$}tDʫH<DJ^"W<?HYG`k (f`z NY`F%i;jl(\#} endstream endobj startxref 104168 %%EOF spatstat/inst/doc/bugfixes.Rnw0000644000176200001440000010334714155341545016162 0ustar liggesusers\documentclass[11pt]{article} \usepackage{graphicx} \usepackage{Sweave} \usepackage{bm} \usepackage{anysize} \marginsize{2cm}{2cm}{2cm}{2cm} % \VignetteIndexEntry{Bugs Fixed in Spatstat} \newcommand{\pkg}[1]{\texttt{#1}} \newcommand{\code}[1]{\texttt{#1}} \newcommand{\R}{{\sf R}} \newcommand{\spst}{\pkg{spatstat}} \newcommand{\Spst}{\pkg{Spatstat}} \begin{document} \bibliographystyle{plain} <>= library(spatstat) sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") options(useFancyQuotes=FALSE) @ \title{Bugs fixed in \spst} \author{Adrian Baddeley, Rolf Turner and Ege Rubak} \date{For \spst\ version \texttt{\Sexpr{sversion}}} \maketitle \thispagestyle{empty} This vignette lists all \emph{important} bugs detected and fixed in the \spst\ package since 2010. It also explains how to search the list of all recorded bugs in the \spst\ famil of packages. <>= nbugs <- nrow(news(grepl("^BUG", Category), package="spatstat")) nbugssince <- nrow(news(Version > "1.42-0" & grepl("^BUG", Category), package="spatstat")) @ \tableofcontents \pagebreak \section{Bug history} Thousands of bugs have been detected and fixed in \spst\ since it was first released in 2001. We started recording the bug history in 2010. Bugs that may have affected the user are listed in the package \texttt{NEWS} file, and can be searched using the \R\ command \texttt{news} or the \spst\ command \texttt{bugfixes}. To see the bugs which have just been fixed in the latest version of \spst, type <>= bugfixes @ To see all bugs which were fixed after a particular version of \spst, for example, bugs that were fixed in version \texttt{1.50-0} or later, type <>= bugfixes(sinceversion="1.50-0") @ To see all bugs in \spst\ that were fixed after a particular date, for example 30 June 2017, type <>= bugfixes(sincedate="2017-06-30") @ To see all bugs fixed after the book \cite{baddrubaturn15} was written, type <>= bugfixes("book") @ To see all bugs in the entire recorded history of \spst, type <>= bugfixes("all") @ which currently produces a list of \Sexpr{nbugs} bugs, of which \Sexpr{nbugssince} were detected after publication of the book \cite{baddrubaturn15}. Recently \spst\ was divided into a family of sub-packages. The command \texttt{bugfixes} now covers the bug history in all of these sub-packages. See the help for \texttt{bugfixes} for further details. \pagebreak \section{Serious bugs} Following is a list of the {\bf most serious bugs}, in decreasing order of potential impact. A bug is classified as ``serious'' if it produced incorrect results without the user's knowledge. Bugs which cause an error exit are not listed here, because ' the presence of a bug is obvious, and the bug would not have misled the user. \newcommand\bugger[4]{% \\ {} % {\small (Bug introduced in \texttt{spatstat {#1}}, {#2}; % fixed in \texttt{spatstat {#3}}, {#4})}% } \newcommand\bugin[4]{% \\ {} % {\small (Bug introduced in \texttt{{#1}}, {#2}; % fixed in \texttt{{#3}}, {#4})}% } \newcommand\bugbefore[4]{% \\ {} % {\small (Bug introduced before \texttt{{#1}}, {#2}; % fixed in \texttt{{#3}}, {#4})}% } %%% LEVEL 1 \subsection{Serious Bugs, Always Wrong, Broad Impact} \begin{itemize} \item \texttt{nncross.ppp}: Results were completely incorrect if $k > 1$. \bugger{1.31-2}{april 2013}{1.35-0}{december 2013} \item \texttt{nncross.pp3}: Results were completely incorrect in some cases. \bugger{1.32-0}{august 2013}{1.34-0}{october 2013} \item \texttt{cdf.test.ppm}: Calculation of $p$-values was incorrect for Gibbs models: $1-p$ was computed instead of $p$. \bugger{1.40-0}{december 2014}{1.45-2}{may 2016} \item \texttt{Smooth.ppp}: Results of \verb!Smooth(X, at="points", leaveoneout=FALSE)! were completely incorrect. \bugger{1.20-5}{august 2010}{1.46-0}{july 2016} \item \texttt{rmh}: \begin{itemize} \item Simulation was completely incorrect in the case of a multitype point process with an interaction that does not depend on the marks, such as \verb!ppm(betacells, ~marks, Strauss(60))! due to a coding error in the \texttt{C} interface. \bugger{1.22-3}{march 2010}{1.22-3}{june 2011} \item Simulation of the Area-Interaction model was completely incorrect. \bugger{1.23-6}{october 2011}{1.31-0}{january 2013} \item Simulation of the Geyer saturation process was completely incorrect. \bugger{1.31-0}{january 2013}{1.31-1}{march 2013} \item Simulation of the Strauss-Hard Core process was partially incorrect, giving point patterns with a slightly lower intensity. \bugger{1.31-0}{january 2013}{1.37-0}{may 2014} \item Simulation of the \emph{multitype} hard core model was completely incorrect (the interaction was effectively removed, changing the model into a Poisson process). \bugger{1.31-0}{january 2013}{1.63-0}{january 2020} \item The result of simulating a model with a hard core did not necessarily respect the hard core constraint, and simulation of a model with strong inhibition did not necessarily converge. This only happened if the first order trend was large, the starting state (\texttt{n.start} or \texttt{x.start}) was not given, and the number of iterations \texttt{nrep} was not very large. It occurred because of a poor choice for the default starting state. {\small (Bug was present since about 2010. Fixed in \texttt{spatstat 1.40-0}, december 2014)} \item Simulation was incorrect in the case of an inhomogeneous multitype model with \texttt{fixall=TRUE} (i.e.\ with a fixed number of points of each type) if the model was segregated (i.e.\ if different types of points had different first order trend). The effect of the error was that all types of points had the same first order trend. {\small (Bug was present since about 2010. Fixed in \texttt{spatstat 1.43-0}, september 2015)} \item Simulation of the Geyer saturation process was incorrectly initialised, so that the results of a short run (i.e. small value of \texttt{nrep}) were incorrect, while long runs were correct. \bugger{1.17-0}{october 2009}{1.31-1}{march 2013} \end{itemize} \item \texttt{nnmark, as.im.ssf}: If \code{marks(X)} was a matrix rather than a data frame, the results were completely incorrect. \bugger{1.32-0}{august 2013}{1.55-1}{april 2018} \item \texttt{rVarGamma}: Simulations were incorrect; they were generated using the wrong value of the parameter \texttt{nu.ker}. \bugger{1.25-0}{december 2011}{1.35-0}{december 2013} \item \texttt{rCauchy}: Simulations were incorrect; they were generated using the wrong value of the parameter \texttt{omega}. \bugger{1.25-0}{december 2011}{1.25-2}{january 2012} \item \texttt{lppm}: For multitype patterns, the fitted model was completely incorrect due to an error in constructing the quadrature scheme. \bugger{1.23-0}{july 2011}{1.30-0}{december 2012} \item \verb![.lpp!: The local coordinate \texttt{seg} was completely incorrect, when \texttt{i} was a window. \bugger{1.31-2}{april 2013}{1.45-0}{march 2016} \item \texttt{lohboot}: Implementation was completely incorrect. \bugger{1.26-1}{april 2012}{1.53-2}{october 2017} \item \texttt{leverage.ppm}, \texttt{influence.ppm}, \texttt{dfbetas.ppm}: Results were incorrect for non-Poisson processes due to a mathematical error. \bugger{1.25-0}{december 2011}{1.51-0}{may 2017} \end{itemize} %%% LEVEL 2 \subsection{Serious Bugs, Often Completely Wrong, Moderate Impact} \begin{itemize} \item \texttt{rLGCP}, \texttt{simulate.kppm}: Simulation results for log-Gaussian Cox processes were incorrect unless the pixel dimensions and pixel spacings were identical on the horizontal and vertical axes. (If pixel dimensions were not specified, then the results were incorrect whenever the Frame of the simulation window was not a square.) \bugger{1.22-2}{june 2011}{1.65-0}{december 2020} \item \texttt{deviance.lppm}, \texttt{pseudoR2.lppm}: Results were completely incorrect, due to a coding error. \bugger{1.44-0}{december 2015}{1.64-2}{november 2020} \item \texttt{kppm}: Results were sometimes incorrect for method='clik2' and method='palm' because the log composite likelihood was erroneously truncated to positive values. Any fitted model for which \verb!logLik(model) = 2.2e-16! should be suspected of being incorrect. \bugin{spatstat.core 2.0-0}{march 2021}{spatstat.core 2.3-2}{november 2021} \item \texttt{bw.pcf}: Results were totally incorrect due to a typo. \bugger{1.51-0}{may 2017}{1.52-0}{august 2017} \item \texttt{density.ppp}: edge correction factors were calculated incorrectly when the window was not a rectangle, causing a negative bias in the estimated intensity. \bugger{1.57-0}{oct 2018}{1.64-0}{april 2020}. \item \texttt{density.ppp}: The standard error (calculated when \texttt{se=TRUE}) was incorrect when \texttt{sigma} was a single numeric value. The output was equal to \texttt{sqrt(sigma)} times the correct answer. \bugger{1.41-1}{february 2015}{1.57-0}{october 2018} \item \texttt{rthin}: If \texttt{P} was close to 1, the result was sometimes an empty point pattern when it should have been identical to \texttt{X}. \bugger{1.43-0}{october 2015}{1.57-0}{october 2018} \item \texttt{predict.mppm}: If the model included random effects, and if the library \pkg{MASS} was not loaded, the predictions were on the log scale (i.e.\ they were logarithms of the correct values). \bugger{1.43-0}{october 2015}{1.55-1}{april 2018} \item \texttt{nnmap}, \texttt{nnmark}: Values were incorrect if the resulting pixel image had unequal numbers of rows and columns. \bugger{1.35-0}{december 2013}{1.55-0}{january 2018} \item \texttt{vcov.mppm}: Format was incorrect (rows/columns were omitted) in some cases. \bugger{1.45-1}{may 2016}{1.55-0}{january 2018} \item \texttt{model.matrix.ppm}, \texttt{model.frame.ppm}: Values were sometimes incorrect when applied to the result of \texttt{subfits}. To be precise, if \texttt{fit} was an \texttt{mppm} object fitted to a hyperframe that included ``design covariates'' (covariates that take a constant value in each row of the hyperframe), and if \verb!futs <- subfits(fit)!, then \verb!model.matrix(futs[[i]])! gave incorrect values in the columns corresponding to the design covariates. \bugger{1.45-1}{may 2016}{1.55-0}{january 2018} \item \texttt{predict.rhohat}, \texttt{simulate.rhohat}: Results were incorrect for a \texttt{rhohat} object computed from linear network data (class \texttt{"lpp"} or \texttt{"lppm"}). \bugger{1.31-0}{march 2013}{1.63-1}{february 2020} \item \texttt{predict.rho2hat}: Results were incorrect for a \texttt{rho2hat} object computed from a point pattern. \bugger{1.42-0}{may 2015}{1.52-0}{august 2017} \item \texttt{density.ppp}: Result was incorrect for non-Gaussian kernels when \texttt{at="points"} and \texttt{leaveoneout=FALSE}. \bugger{1.47-0}{october 2016}{1.57-0}{october 2018} \item \texttt{envelope.ppm}: If the model was an inhomogeneous Poisson process, the resulting envelope object was incorrect (the simulations were correct, but the envelopes were calculated assuming the model was CSR). \bugger{1.23-5}{september 2011}{1.23-6}{october 2011} \item \texttt{linearK}, \texttt{linearpcf}, \texttt{linearKinhom}, \texttt{linearpcfinhom} and multitype versions: These functions were sometimes greatly underestimated when the network had segments shorter than 10 coordinate units. \bugger{1.44-0}{december 2015}{1.46-2}{july 2016} \item \texttt{nncross}, \texttt{distfun}, \texttt{AreaInter}: Results of \texttt{nncross} were possibly incorrect when \code{X} and \code{Y} did not have the same window. This bug affected values of \texttt{distfun} and may also have affected ppm objects with interaction \texttt{AreaInter}. \bugger{1.9-4}{june 2006}{1.25-2}{january 2012} \item \texttt{update.kppm}: \begin{itemize} \item Did not function correctly when several additional arguments were given. \bugger{1.42-2}{june 2015}{1.54-0}{november 2017} \item If the call to \texttt{update} did not include a formula argument or a point pattern argument, then all arguments were ignored. Example: \texttt{update(fit, improve.type="quasi")} was identical to \texttt{fit}. \bugger{1.42-2}{june 2015}{1.45-0}{march 2016} \end{itemize} \item \texttt{markcorrint}: Results were completely incorrect. \bugger{1.39-0}{october 2014}{1.40-0}{december 2014} \item \texttt{leverage.ppm}, \texttt{influence.ppm}, \texttt{dfbetas.ppm}: Results were slightly incorrect for models with a hard core, due to a mathematical error. \bugger{1.51-0}{may 2017}{1.55-1}{april 2018} \item \texttt{Ops.msr}: If the input data contained a pixel image of the smoothed density, this image was not updated; it was copied to the output unchanged. Plots of the resulting measure were incorrect. \bugger{1.52-0}{august 2017}{1.55-1}{april 2018} \item \verb![.linnet!: in calculating \verb!L[W]! where \texttt{W} is a window, the code ignored segments of \code{L} that crossed \code{W} without having a vertex in \code{W}. \bugger{1.53-0}{september 2017}{1.55-1}{april 2015} \item \verb!as.im.function!: if the function domain was not a rectangle and the function values were categorical (factor) values, the result was an empty image. \bugger{1.42-0}{may 2015}{1.57-0}{october 2018} \end{itemize} %%% LEVEL 3 \subsection{Bugs, Substantially Incorrect, Moderate Impact} \begin{itemize} \item \texttt{nncross.ppp}: If the argument \texttt{by} was given, some of the results were incorrect. [Spotted by Hank Stevens.] \bugger{1.32-0}{august 2013}{2.2-0}{june 2021} \item \texttt{nncross.ppp}, \texttt{nncross.pp3}: If \texttt{iX} and \texttt{iY} were given, some of the results were incorrect. \bugger{1.32-0}{august 2013}{2.2-0}{june 2021} \item \texttt{vcov.ppm}: Result was sometimes incorrect for Gibbs models. The Fisher information was slightly underestimated. \bugger{1.31-1}{march 2013}{1.64-1}{may 2020} \item \texttt{as.linnet.psp}: Sometimes produced a network with duplicated segments. [Such objects can be repaired using \texttt{repairNetwork}.] \bugger{1.41-1}{february 2015}{1.62-0}{december 2019} \item \texttt{rlpp}: The resulting pattern was unmarked even when it should have been multitype. \bugger{1.48-0}{december 2016}{1.63-0}{january 2020} \item \texttt{spatialcdf}: Argument \texttt{weights} was ignored, unless it was a fitted model. {\small (Bug was present since about 2010. Fixed in \texttt{spatstat 1.59-0}, march 2019)} \item \texttt{ppp}: Points inside the window were erroneously rejected as lying outside the window, if the window was a polygon equivalent to a rectangle with sides longer than $10^6$ units. {\small (Bug was present since the beginning. Fixed in \texttt{spatstat 1.59-0}, march 2019)} \item \texttt{inside.owin}: All results were \texttt{FALSE} if the window was a polygon equivalent to a rectangle with sides longer than $10^6$ units. {\small (Bug was present since the beginning. Fixed in \texttt{spatstat 1.59-0}, march 2019)} \item \texttt{sumouter}: result was incorrect (all entries were zero) if \texttt{w} was missing and \texttt{y} was given. \bugger{1.47-0}{october 2016}{1.59-0}{march 2019} \item \texttt{simulate.dppm}, \texttt{simulate.detpointprocfamily}: In dimensions higher than 2, the result was shifted so that it was centred at the origin. \bugger{1.54-0}{december 2017}{1.55-0}{january 2018} \item \texttt{integral.msr}: If the result was a matrix, it was the transpose of the correct answer. \bugger{1.35-0}{december 2012}{1.55-1}{april 2018} \item \texttt{density.ppp}: Values of \verb!density(X, at="points")! and \verb!Smooth(X, at="points")! were sometimes incorrect, due to omission of the contribution from the data point with the smallest $x$ coordinate. \bugger{1.26-0}{april 2012}{1.46-1}{july 2016} \item \texttt{multiplicity.default}: The first occurrence of any value in the input was incorrectly assigned a multiplicity of 1. \bugger{1.32-0}{december 2013}{1.57-1}{november 2018} \item \texttt{update.ppm}: If the argument \texttt{Q} was given, the results were usually incorrect, or an error was generated. \bugger{1.38-0}{august 2014}{1.38-1}{august 2014} \item \texttt{subfits}: The interaction coefficients of the submodels were incorrect for Gibbs models with a multitype interaction (\texttt{MultiStrauss}, etc). \bugger{1.35-0}{december 2013}{1.45-2}{may 2016} \item \texttt{F3est}: Estimates of $F(r)$ for the largest value of $r$ were wildly incorrect. {\small (Bug was present since about 2010. Fixed in \texttt{spatstat 1.48-0}, december 2016)} \item \texttt{kppm}, \texttt{matclust.estpcf}, \texttt{pcfmodel}: The pair correlation function of the M\'atern Cluster Process was evaluated incorrectly at distances close to 0. This could have affected the fitted parameters in \texttt{matclust.estpcf()} or \texttt{kppm(clusters="MatClust")}. \bugger{1.20-2}{august 2010}{1.33-0}{september 2013} \item \texttt{ppm}: Results were incorrect for the Geyer saturation model with a non-integer value of the saturation parameter \texttt{sat}. \bugger{1.20-0}{july 2010}{1.31-2}{april 2013} \item \texttt{clip.infline}: Results were incorrect unless the midpoint of the window was the coordinate origin. \bugger{1.15-1}{april 2009}{1.48-0}{december 2016} \item \texttt{intensity.ppm}: Result was incorrect for Gibbs models if the model was exactly equivalent to a Poisson process (i.e. if all interaction coefficients were exactly zero). \bugger{1.28-1}{june 2012}{1.47-0}{october 2016} \item \texttt{idw}: Results were incorrect if \texttt{se=TRUE} and \verb!at="pixels"! and \texttt{power} was not equal to 2. The pixel values of \verb!$estimate! were all equal to zero. \bugger{1.58-0}{january 2019}{1.63-0}{january 2020} \item \texttt{funxy}: Did not correctly handle one-line functions. The resulting objects evaluated the wrong function in some cases. \bugger{1.45-0}{march 2016}{1.46-0}{july 2016} \item \texttt{kernel.moment}: Result was incorrect for \texttt{kernel="cosine"} and \texttt{kernel="optcosine"}. \bugger{1.45-2}{may 2016}{1.56-0}{june 2018} \item \verb![.msr!: Format was mangled if the subset contained exactly one quadrature point. \bugger{1.21-3}{january 2011}{1.56-0}{june 2018} \item \texttt{hyperframe}: Did not correctly handle date-time values (columns of class \texttt{"Date"}, etc). \bugger{1.19-1}{may 2010}{1.63-0}{january 2020} \item \texttt{tess}: If a list of tiles was given, and the tiles were pixel images or masks, their pixel resolutions were ignored, and reset to the default $128 \times 128$. {\small (Bug fixed in \texttt{spatstat 1.56-0}, june 2018)} \item \texttt{nnorient}: crashed if the point pattern was empty. \bugger{1.40-0}{december 2015}{1.57-0}{october 2018} \item \verb!as.im.data.frame!: Results were incorrect for factor-valued data. \bugger{1.45-2}{may 2016}{1.63-0}{january 2020} \end{itemize} %% LEVEL 4: \subsection{Partially Incorrect} \begin{itemize} \item \texttt{density.lpp}: The result had the wrong length if \texttt{x} contained duplicated points when \texttt{weights} were given and \texttt{at="points"}. [Spotted by Andrea Gilardi] \bugger{1.55-1}{april 2018}{2.2-0}{june 2021} \item \texttt{crossdist.pp3}: Results with \texttt{periodic=TRUE} were partially incorrect. \bugger{1.34-1}{dec 2013}{1.65-0}{dec 2020} \item \texttt{mppm}: Internal data were malformed if the interaction was \texttt{Hardcore} or \texttt{MultiHard} or a hybrid involving these interactions. This caused various errors when the fitted model was used. \bugger{1.61-0}{september 2019}{1.64-0}{april 2020}. \item \texttt{mppm}: Ignored the arguments \texttt{nd} and \texttt{eps} controlling the quadrature scheme. \bugger{1.35-0}{december 2013}{1.64-0}{april 2020}. \item \texttt{edge.Ripley}: Results were incorrect for data points lying exactly at the corners of a rectangle. \bugbefore{spatstat 1.21-0}{november 2010}{spatstat.core 2.3-2}{november 2021} \item \texttt{kppm}, \texttt{AIC}: For kppm models fitted with \verb!method='clik2'!, the resulting value of \texttt{logLik()} was equal to $1/2$ of the correct value. This would have affected model comparison using AIC, and model selection using \texttt{step}. \bugger{1.42-0}{may 2015}{1.63-0}{january 2020}. \item \texttt{edge.Ripley}, \texttt{Kest}, \texttt{Kinhom}: Isotropic correction weights for polygonal windows were sometimes incorrect for small radius \texttt{r} if the polygon contained many small segments or if the polygon was very long and thin. \bugger{1.60-0}{june 2019}{1.62-0}{december 2019}. \item \texttt{beachcolours}, \texttt{beachcolourmap}: The number of colours was not always equal to \texttt{ncolours}. \bugger{1.32-0}{august 2013}{1.59-0}{march 2019} \item \texttt{extractbranch.lpp}: Point pattern coordinates were sometimes erroneously set to \texttt{NA}. \bugger{1.42-0}{may 2015}{1.59-0}{march 2019} \item \texttt{rotmean}: When \texttt{result="im"} the resulting image did not have the same dimensions as the input. \bugger{1.42-2}{june 2015}{1.58-0}{january 2019} \item \texttt{quadratcount.ppp}: Sometimes issued an incorrect warning that data points were outside the tessellation, when \texttt{tess} was a tessellation represented by a pixel image. {\small (Bug fixed in \texttt{spatstat 1.59-0}, march 2019)} \item \texttt{quadrat.test}: the $p$-value was \texttt{NA} if one of the observed counts was zero, for the Cressie-Read tests with \texttt{CR} not equal to $1$ or $-1$. \bugger{1.38-0}{august 2014}{1.59-0}{march 2019} \item \texttt{quadrat.test}: argument \texttt{CR} was ignored if \texttt{method="MonteCarlo"}. \bugger{1.38-0}{august 2014}{1.61-0}{september 2019} \item \texttt{rotmean}: If argument \texttt{origin} was given, and if \texttt{result="im"} was specified, the resulting image was wrongly displaced. \bugger{1.42-2}{june 2015}{1.58-0}{january 2019} \item \texttt{runifpointx}: Result was mangled when \texttt{n=0} or \texttt{n=1}. \bugger{1.50-0}{march 2017}{1.58-0}{january 2019} \item \texttt{model.matrix.ppm}: The attribute \texttt{assign} was omitted in some cases. \bugger{1.45-1}{may 2016}{1.55-0}{january 2018} \item \texttt{model.matrix.mppm}: Sometimes returned a matrix with the wrong number of rows. \bugger{1.55-0}{january 2018}{1.63-0}{january 2020} \item \texttt{density.ppp}: If the smoothing bandwidth \texttt{sigma} was very small (e.g.\ less than the width of a pixel), results were inaccurate if the default resolution was used, and completely incorrect if a user-specified resolution was given. \bugger{1.26-0}{april 2012}{1.52-0}{august 2017} \item \texttt{selfcrossing.psp}: $y$ coordinate values were incorrect. \bugger{1.23-2}{august 2011}{1.25-3}{february 2012} \item \texttt{Geyer}: For point process models with the \texttt{Geyer} interaction, \texttt{vcov.ppm} and \texttt{suffstat} sometimes gave incorrect answers. \bugger{1.27-0}{may 2012}{1.30-0}{december 2012} \item \texttt{leverage.ppm}, \texttt{influence.ppm}, \texttt{dfbetas.ppm}: Calculations were incorrect for a Geyer model fitted using an edge correction other than \texttt{"border"} or \texttt{"none"}. \bugger{1.25-0}{december 2011}{1.51-0}{may 2017} \item \texttt{leverage.ppm}, \texttt{influence.ppm}, \texttt{dfbetas.ppm}: Results were slightly incorrect for models fitted using the border correction. \bugger{1.25-0}{december 2011}{1.54-0}{november 2017} \item \texttt{leverage.ppm}: The mean leverage value (shown as a contour level in \texttt{plot.leverage.ppm}) was slightly incorrect for Gibbs models. \bugger{1.25-0}{december 2011}{1.54-0}{november 2017} \item \texttt{vcov.ppm}, \texttt{suffstat}: These functions sometimes gave incorrect values for marked point process models. \bugger{1.27-0}{may 2012}{1.29-0}{october 2012} \item \texttt{diagnose.ppm}: When applied to a model obtained from \texttt{subfits()}, in the default case (\texttt{oldstyle=FALSE}) the variance calculations were incorrect. Consequently the dotted lines representing significance bands were incorrect. An error or warning about negative variances occurred sometimes. However, calculations with \texttt{oldstyle=TRUE} were correct. The default has now been changed to \texttt{oldstyle=TRUE} for such models. \bugger{1.35-0}{december 2013}{1.45-0}{march 2016} \item \texttt{Smooth.ppp}: Results for \verb!at="points"! were garbled, for some values of \texttt{sigma}, if \texttt{X} had more than one column of marks. \bugger{1.38-0}{october 2014}{1.46-0}{july 2016} \item \texttt{linearK}, \texttt{linearKinhom}: If any data points were located exactly at a vertex of the linear network, the weights for Ang's correction were incorrect, due to numerical error. This sometimes produced infinite or NA values of the linear $K$ function. \bugger{1.23-0}{july 2011}{1.27-0}{may 2012} \item \texttt{Kinhom}, \texttt{Linhom}: the results were not renormalised (even if \texttt{renormalise=TRUE}) in some cases. \bugger{1.21-0}{december 2010}{1.37-0}{may 2014} \item \texttt{Kinhom}, \texttt{Linhom}: Ignored argument \texttt{reciplambda2} in some cases. \bugger{1.39-0}{october 2014}{1.40-0}{december 2014} \item \texttt{Kinhom}, \texttt{Linhom}: Calculations were incorrect if \texttt{lambda} was a fitted point process model. \bugger{1.38-0}{august 2014}{1.38-1}{august 2014} \item \texttt{integral.linim}, \texttt{integral.linfun}: \begin{itemize} \item results were inaccurate because of a bias in the distribution of sample points. \bugger{1.41-0}{february 2015}{1.47-0}{october 2016} \item results were inaccurate if many of the segment lengths were shorter than the width of a pixel. \bugger{1.41-0}{february 2015}{1.48-0}{december 2016} \item results were wildly inaccurate in some extreme cases where many segments were very short. \bugger{1.41-0}{february 2015}{1.54-0}{november 2017} \end{itemize} \item \texttt{predict.ppm}: Calculation of the conditional intensity omitted the edge correction if \texttt{correction='translate'} or \texttt{correction='periodic'}. \bugger{1.17-0}{october 2009}{1.31-3}{may 2013} \item \texttt{varblock}: Calculations were incorrect if more than one column of edge corrections was computed. \bugger{1.21-1}{november 2010}{1.39-0}{october 2014} \item \texttt{scan.test} Results were sometimes incorrect due to numerical instability (a 'Gibbs phenomenon'). \bugger{1.24-1}{october 2011}{1.26-1}{april 2012} \item \texttt{relrisk}: When \verb!at="pixels"!, a small fraction of pixel values were sometimes wildly inaccurate, due to numerical errors. This affected the range of values in the result, and therefore the appearance of plots. {\small (Bug fixed in \texttt{spatstat 1.40-0}, december 2014)} \item \texttt{predict.slrm}: Results of \texttt{predict(object, newdata)} were incorrect if the spatial domain of \texttt{newdata} was larger than the original domain. \bugger{1.21-0}{november 2010}{1.25-3}{february 2012} \item \texttt{Lest}: The variance approximations (Lotwick-Silverman and Ripley) obtained with \texttt{var.approx=TRUE} were incorrect for \texttt{Lest} (although they were correct for \texttt{Kest}) due to a coding error. \bugger{1.24-1}{october 2011}{1.24-2}{november 2011} \item \texttt{bw.diggle}: Bandwidth was too large by a factor of 2. \bugger{1.23-4}{september 2011}{1.23-5}{september 2011} \item pair correlation functions (\texttt{pcf.ppp}, \texttt{pcfdot}, \texttt{pcfcross} etc:) The result had a negative bias at the maximum $r$ value, because contributions to the pcf estimate from interpoint distances greater than \texttt{max(r)} were mistakenly omitted. {\small (Bugs fixed in \texttt{spatstat 1.35-0}, december 2013)} \item \texttt{Kest}, \texttt{Lest}: Gave incorrect values in very large datasets, due to numerical overflow. `Very large' typically means about 1 million points in a random pattern, or 100,000 points in a tightly clustered pattern. [Overflow cannot occur unless there are at least 46,341 points.] \item \texttt{bw.relrisk}: Implementation of \texttt{method="weightedleastsquares"} was incorrect and was equivalent to \texttt{method="leastsquares"}. \bugger{1.21-0}{november 2010}{1.23-4}{september 2011} \item \texttt{triangulate.owin}: Results were incorrect in some special cases. \bugger{1.42-2}{june 2015}{1.44-0}{december 2015} \item \texttt{crosspairs}: If \texttt{X} and \texttt{Y} were identical point patterns, the result was not necessarily symmetric (on some machines) due to numerical artifacts. \bugger{1.35-0}{december 2013}{1.44-0}{december 2015} \item \texttt{bdist.tiles}: Values were incorrect in some cases due to numerical error. {\small (Bug fixed in \texttt{spatstat 1.29-0}, october 2012)} \item \texttt{Kest.fft}: Result was incorrectly normalised. \bugger{1.21-2}{january 2011}{1.44-0}{december 2015} \item \texttt{crossdist.ppp}: Ignored argument \texttt{squared} if \texttt{periodic=FALSE}. {\small (Bug fixed in \texttt{spatstat 1.38-0}, july 2014)} \item polygon geometry: The point-in-polygon test gave the wrong answer in some boundary cases. {\small (Bug fixed in \texttt{spatstat 1.23-2}, august 2011)} \item \texttt{MultiStraussHard}: If a fitted model with \texttt{MultiStraussHard} interaction was invalid, \texttt{project.ppm} sometimes yielded a model that was still invalid. {\small (Bug fixed in \texttt{spatstat 1.42-0}, may 2015)} \item \texttt{pool.envelope}: Did not always respect the value of \texttt{use.theory}. \bugger{1.23-5}{september 2011}{1.43-0}{september 2015} \item \texttt{nncross.lpp}, \texttt{nnwhich.lpp}, \texttt{distfun.lpp}: Sometimes caused a segmentation fault. \bugger{1.44-0}{december 2015}{1.44-1}{december 2015} \item \texttt{anova.ppm}: If a single \texttt{object} was given, and it was a Gibbs model, then \texttt{adjust} was effectively set to \texttt{FALSE}. \bugger{1.39-0}{october 2014}{1.44-1}{december 2015} \item \verb![.linim!: the result sometimes had the wrong class. \bugger{1.53-0}{september 2017}{1.55-1}{april 2015} \item \verb![.linim!: factor values were erroneously converted to integers, in some cases. \bugger{1.53-0}{september 2017}{1.61-0}{september 2019} \item \verb!is.subset.owin!: sometimes gave the wrong result for polygonal windows due to numerical rounding error. {\small (Bug was always present. Fixed in \texttt{spatstat 1.59-0}, march 2019)} \item \texttt{plot.tess}: the legend showed the tile names in lexicographical order, rather than their original order. \bugger{1.55-1}{april 2018}{1.59-0}{march 2019} \item \texttt{rThomas}, \texttt{rMatClust}, \texttt{rCauchy}, \texttt{rVarGamma}: If the simulation window was not a rectangle, the attribute \texttt{Lambda} was a numeric vector, rather than a pixel image as intended. \bugger{1.43-0}{october 2015}{1.59-0}{march 2019} \item \texttt{effectfun}: In a multitype point process model, \texttt{effectfun} ignored any user-specified value of \texttt{marks}. \bugger{1.52-0}{august 2017}{1.61-0}{september 2019} \item \verb!"[<-.hyperframe"!: Some classes of objects were not handled correctly. \bugger{1.37-0}{may 2014}{1.61-0}{september 2019} \item \texttt{relrisk.ppp}: Crashed if there were more than 2 types of points and \texttt{method = "leastsquares"} or \texttt{method = "weightedleastsquares"}. \bugger{1.23-4}{september 2011}{1.63-0}{january 2020} \item \texttt{nncross.ppp}: Format of output was incorrect if \texttt{X} was an empty pattern. \bugger{1.56-0}{june 2018}{1.63-0}{january 2020} \item \texttt{rmh}, \texttt{rmh.default}: For a marked point process, the debugger did not display the marks. (The \texttt{rmh} debugger is invoked by calling \texttt{rmh} with \texttt{snoop=TRUE}). \bugger{1.31-1}{march 2013}{1.63-0}{january 2020} \item \texttt{model.matrix.mppm}: If the model was fitted using \texttt{gam}, the resulting matrix did not have an \texttt{"assign"} attribute. \bugger{1.55-0}{march 2018}{2.2-0}{june 2021} \item \texttt{update.slrm}: Failed to find covariates that were provided in \texttt{env}. \bugger{1.33-0}{september 2013}{2.2-0}{june 2021} \end{itemize} \begin{thebibliography}{1} \bibitem{baddrubaturn15} A. Baddeley, E. Rubak, and R. Turner. \newblock {\em Spatial Point Patterns: Methodology and Applications with {{R}}}. \newblock Chapman \& Hall/CRC Press, 2015. \end{thebibliography} \end{document} spatstat/inst/doc/packagesizes.txt0000644000176200001440000002363014155343627017067 0ustar liggesusersdate version nhelpfiles nobjects ndatasets Rlines srclines "2001-08-08" "1.0-1" 109 196 0 706 1370 "2002-05-17" "1.1-3" 116 220 0 1140 1370 "2002-08-06" "1.2-1" 129 237 0 1786 1474 "2003-03-12" "1.3-1" 134 242 0 1955 1474 "2003-05-05" "1.3-2" 148 257 0 2024 1474 "2003-07-28" "1.3-3" 148 266 0 2034 1474 "2003-11-12" "1.3-4" 148 261 0 2033 1474 "2004-01-27" "1.4-3" 166 296 0 3641 1437 "2004-02-11" "1.4-4" 166 296 0 3641 1437 "2004-03-25" "1.4-5" 166 296 0 3646 1439 "2004-05-23" "1.4-6" 166 296 0 3689 1514 "2004-06-17" "1.5-1" 166 300 0 4255 1514 "2004-09-01" "1.5-3" 171 311 0 4636 1514 "2004-09-24" "1.5-4" 174 315 0 4642 1514 "2004-10-21" "1.5-5" 180 319 0 4686 1514 "2004-11-15" "1.5-6" 180 319 0 4686 1512 "2004-11-27" "1.5-7" 180 319 0 4687 1512 "2005-01-25" "1.5-8" 182 320 0 4770 1512 "2005-01-27" "1.5-9" 182 321 0 4805 1512 "2005-02-16" "1.5-10" 182 321 0 4805 1512 "2005-03-14" "1.6-1" 188 345 0 5597 1517 "2005-03-30" "1.6-2" 188 345 0 5600 1450 "2005-04-08" "1.6-3" 189 352 0 5715 1474 "2005-04-14" "1.6-4" 194 358 0 6056 1544 "2005-04-21" "1.6-5" 194 358 0 6056 1544 "2005-05-09" "1.6-6" 195 373 0 6385 1592 "2005-05-25" "1.6-7" 201 392 0 7727 1644 "2005-06-07" "1.6-8" 206 400 0 8003 1644 "2005-07-01" "1.6-9" 207 402 0 8025 1644 "2005-07-26" "1.7-11" 212 406 0 8213 1643 "2005-08-10" "1.7-12" 213 407 0 8279 1643 "2005-10-27" "1.7-13" 215 410 0 8531 1643 "2005-11-24" "1.8-1" 215 418 0 8539 1643 "2005-12-05" "1.8-2" 229 440 0 9031 1643 "2005-12-21" "1.8-3" 237 446 0 9175 1643 "2006-01-09" "1.8-4" 237 446 0 9207 1643 "2006-01-18" "1.8-5" 237 446 0 9225 1643 "2006-02-23" "1.8-6" 241 449 0 9315 1643 "2006-03-02" "1.8-7" 247 457 0 9627 1643 "2006-03-30" "1.8-8" 248 459 0 9662 1643 "2006-04-18" "1.8-9" 259 446 21 10144 1832 "2006-05-03" "1.9-0" 259 447 21 10396 1817 "2006-05-26" "1.9-1" 266 466 21 10861 3069 "2006-06-05" "1.9-2" 268 473 21 11409 3487 "2006-06-20" "1.9-3" 268 479 21 11941 4140 "2006-08-03" "1.9-4" 273 490 22 12435 5619 "2006-08-22" "1.9-5" 274 490 22 12493 5560 "2006-09-27" "1.9-6" 277 494 22 12573 5601 "2006-10-19" "1.10-1" 283 529 22 13124 5601 "2006-10-19" "1.10-1" 283 529 22 13124 5171 "2006-11-06" "1.10-2" 283 529 22 13194 5601 "2006-11-20" "1.10-3" 287 540 22 13425 5684 "2007-01-08" "1.10-4" 291 554 22 13591 5684 "2007-01-08" "1.10-4" 291 554 22 13591 5684 "2007-01-12" "1.11-0" 291 562 22 13728 5684 "2007-02-01" "1.11-1" 294 564 23 13614 5684 "2007-03-10" "1.11-2" 301 574 24 13860 5684 "2007-03-16" "1.11-3" 305 580 24 14106 5819 "2007-03-19" "1.11-4" 307 589 24 14316 5868 "2007-05-08" "1.11-5" 307 591 24 14373 5940 "2007-05-18" "1.11-6" 308 592 24 14390 5940 "2007-06-09" "1.11-7" 311 595 24 14506 5940 "2007-07-26" "1.11-8" 312 596 24 14552 6055 "2007-08-20" "1.12-0" 319 619 25 15246 6055 "2007-09-22" "1.12-1" 319 619 25 15250 6055 "2007-10-26" "1.12-2" 322 623 25 15684 6188 "2007-11-02" "1.12-3" 322 626 25 15767 6188 "2007-12-18" "1.12-4" 322 626 25 15814 6188 "2008-01-07" "1.12-5" 322 630 25 15891 6238 "2008-02-04" "1.12-6" 328 638 25 16334 6446 "2008-02-26" "1.12-8" 328 639 25 16405 6718 "2008-03-18" "1.12-9" 331 644 25 16606 6718 "2008-04-02" "1.12-10" 331 644 25 16649 6771 "2008-04-11" "1.13-0" 332 645 25 16753 6771 "2008-04-23" "1.13-1" 333 647 25 16812 6840 "2008-05-14" "1.13-2" 339 654 25 17057 6840 "2008-06-24" "1.13-3" 340 657 25 17182 6840 "2008-07-18" "1.13-4" 348 672 26 17527 6840 "2008-07-22" "1.14-0" 354 681 26 17923 7131 "2008-07-22" "1.14-1" 356 684 26 18052 7131 "2008-09-08" "1.14-2" 360 688 27 18087 7185 "2008-09-26" "1.14-3" 362 693 27 18194 7185 "2008-10-16" "1.14-4" 366 707 27 18427 7185 "2008-10-23" "1.14-5" 368 715 27 18493 7185 "2008-11-07" "1.14-6" 372 726 27 18657 7185 "2008-11-17" "1.14-7" 374 730 27 18671 7185 "2008-12-10" "1.14-8" 377 734 27 18766 7185 "2008-12-16" "1.14-9" 377 734 27 18772 7185 "2009-01-30" "1.14-10" 381 741 27 18949 7186 "2009-03-02" "1.15-0" 384 750 27 19212 7362 "2009-03-31" "1.15-1" 386 752 28 19292 7439 "2009-04-14" "1.15-2" 396 772 28 19880 7436 "2009-05-13" "1.15-3" 398 777 29 20141 7524 "2009-06-11" "1.15-4" 399 776 29 20176 7524 "2009-07-01" "1.16-0" 405 787 29 20774 7524 "2009-07-27" "1.16-1" 411 814 29 21433 7524 "2009-08-22" "1.16-2" 417 821 29 21863 7937 "2009-08-28" "1.16-3" 419 831 29 22060 7941 "2009-10-22" "1.17-0" 420 833 30 21881 8705 "2009-11-04" "1.17-1" 437 875 30 22900 10614 "2009-11-10" "1.17-2" 439 880 30 22943 10606 "2009-12-15" "1.17-3" 442 885 30 23193 10606 "2009-12-15" "1.17-4" 445 890 30 23640 10606 "2010-01-06" "1.17-5" 451 906 30 24283 12003 "2010-02-08" "1.17-6" 456 921 30 24795 12003 "2010-03-10" "1.18-0" 459 931 30 25073 12333 "2010-03-19" "1.18-1" 462 945 30 25464 12439 "2010-04-09" "1.18-2" 463 950 30 25631 12475 "2010-04-19" "1.18-3" 464 953 30 25720 12475 "2010-05-02" "1.18-4" 475 980 30 26093 13417 "2010-05-07" "1.18-5" 475 981 30 26117 13417 "2010-05-14" "1.19-0" 476 982 30 26205 13417 "2010-05-22" "1.19-1" 479 984 31 26286 13556 "2010-06-09" "1.19-2" 481 996 31 26653 13667 "2010-06-16" "1.19-3" 483 1003 31 26733 13667 "2010-07-15" "1.20-0" 483 1017 31 26926 14009 "2010-07-26" "1.20-1" 484 1020 31 27107 14263 "2010-08-10" "1.20-2" 489 1028 31 27728 14466 "2010-08-23" "1.20-3" 489 1033 31 27869 14564 "2010-10-21" "1.20-4" 493 1040 31 28237 14805 "2010-10-25" "1.20-5" 494 1043 31 28377 15160 "2010-11-05" "1.21-0" 504 1067 31 41301 15160 "2010-11-11" "1.21-1" 507 1075 31 41714 15554 "2011-01-17" "1.21-3" 515 1103 31 42975 15747 "2011-01-20" "1.21-4" 515 1103 31 42985 15747 "2011-02-10" "1.21-5" 515 1103 31 43037 15747 "2011-04-25" "1.21-6" 517 1107 31 43211 15747 "2011-04-28" "1.22-0" 526 1148 32 44006 15831 "2011-05-19" "1.22-1" 528 1154 32 44235 15820 "2011-06-13" "1.22-2" 537 1188 32 45006 16282 "2011-06-17" "1.22-3" 539 1197 32 45153 16269 "2011-07-07" "1.22-4" 550 1218 33 46696 16269 "2011-07-24" "1.23-0" 562 1244 34 47694 16496 "2011-08-01" "1.23-1" 564 1252 34 48014 16658 "2011-08-11" "1.23-2" 566 1260 34 48313 17035 "2011-08-12" "1.23-3" 566 1260 34 48319 17035 "2011-09-09" "1.23-4" 571 1269 34 48747 17243 "2011-09-23" "1.23-5" 575 1274 34 49128 17141 "2011-10-11" "1.23-6" 579 1286 34 49508 17141 "2011-10-22" "1.24-1" 585 1308 34 50154 17141 "2011-11-11" "1.24-2" 588 1312 34 50604 17839 "2011-12-06" "1.25-0" 602 1334 34 52015 18351 "2011-12-21" "1.25-1" 609 1339 35 52235 19088 "2012-01-19" "1.25-2" 610 1338 35 52774 19120 "2012-02-05" "1.25-3" 613 1345 35 53004 19120 "2012-02-29" "1.25-4" 614 1347 35 53302 19423 "2012-03-14" "1.25-5" 616 1351 35 53720 19506 "2012-04-08" "1.26-0" 616 1356 35 53816 19169 "2012-04-19" "1.26-1" 617 1358 35 54498 19261 "2012-05-16" "1.27-0" 630 1393 35 55787 19363 "2012-06-11" "1.28-0" 632 1417 35 56384 19363 "2012-08-23" "1.28-2" 640 1438 36 58566 19372 "2012-10-14" "1.29-0" 651 1470 36 59711 19457 "2012-12-23" "1.30-0" 666 1499 41 61344 19806 "2013-01-17" "1.31-0" 668 1507 41 61446 20094 "2013-03-01" "1.31-1" 678 1562 41 63783 20536 "2013-04-25" "1.31-2" 682 1581 41 64501 21117 "2013-05-27" "1.31-3" 685 1600 41 65545 21773 "2013-08-13" "1.32-0" 695 1625 41 67120 22151 "2013-09-05" "1.33-0" 701 1630 43 67397 22218 "2013-10-24" "1.34-0" 720 1666 43 69219 22867 "2013-11-03" "1.34-1" 720 1666 43 69180 23340 "2013-12-12" "1.35-0" 745 1717 47 72110 23491 "2014-02-18" "1.36-0" 757 1753 47 73946 24042 "2014-05-09" "1.37-0" 781 1841 47 77585 24633 "2014-08-15" "1.38-0" 803 1963 48 80709 25191 "2014-08-27" "1.38-1" 803 1965 48 80833 25191 "2014-10-23" "1.39-0" 824 2015 49 82274 25554 "2014-10-24" "1.39-1" 824 2015 49 81990 25554 "2014-12-31" "1.40-0" 839 2071 51 85832 25637 "2015-02-26" "1.41-0" 861 2135 53 88407 25650 "2015-02-27" "1.41-1" 861 2135 53 88407 25650 "2015-05-27" "1.42-0" 888 2222 53 91600 25650 "2015-06-05" "1.42-1" 888 2225 53 91658 25650 "2015-06-28" "1.42-2" 890 2232 53 91985 25650 "2015-10-07" "1.43-0" 939 2342 54 95950 25802 "2015-12-22" "1.44-0" 949 2378 54 97522 27569 "2015-12-29" "1.44-1" 951 2385 54 97745 27569 "2016-03-10" "1.45-0" 961 2456 54 100964 28122 "2016-05-08" "1.45-1" 977 2478 54 101981 28124 "2016-05-09" "1.45-2" 977 2478 54 101981 28124 "2016-07-06" "1.46-0" 981 2490 54 102484 28310 "2016-07-08" "1.46-1" 981 2491 54 102573 28310 "2016-10-12" "1.47-0" 988 2533 54 103848 28679 "2016-12-22" "1.48-0" 1017 2611 54 105733 29466 "2017-02-08" "1.49-0" 1024 2629 54 106522 31029 "2017-02-08" "1.49-0" 1024 2629 54 106522 31029 "2017-03-22" "1.50-0" 1025 2476 54 104021 29413 "2017-05-04" "1.51-0" 1029 2501 54 105229 29430 "2017-08-10" "1.52-0" 1035 2518 54 106162 29416 "2017-08-16" "1.52-1" 1035 2518 54 106170 29416 "2017-09-23" "1.53-0" 984 2525 0 106672 29418 "2017-09-28" "1.53-1" 984 2525 0 106675 29418 "2017-10-08" "1.53-2" 984 2526 0 106797 29418 "2017-11-21" "1.54-0" 986 2544 0 107420 29488 "2018-01-29" "1.55-0" 988 2536 0 108015 29488 "2018-04-05" "1.55-1" 990 2545 0 109017 29769 "2018-06-15" "1.56-0" 999 2574 0 109767 30024 "2018-07-27" "1.56-1" 999 2577 0 109857 30024 "2018-10-30" "1.57-0" 1001 2584 0 110444 29954 "2018-11-03" "1.57-1" 1001 2584 0 110459 29954 "2019-01-09" "1.58-0" 1002 2585 0 110702 30470 "2019-01-10" "1.58-1" 1002 2585 0 110702 30470 "2019-01-10" "1.58-2" 1003 2586 0 110732 30470 "2019-03-22" "1.59-0" 1010 2609 0 112044 30729 "2019-06-23" "1.60-0" 1017 2628 0 113056 31026 "2019-09-12" "1.61-0" 1022 2638 0 113652 31027 "2019-12-08" "1.62-0" 1032 2668 0 114943 31548 "2019-12-08" "1.62-1" 1032 2668 0 114943 31548 "2019-12-10" "1.62-2" 1032 2668 0 114956 31548 "2020-01-23" "1.63-0" 1033 2666 0 115171 31549 "2020-02-21" "1.63-1" 1035 2670 0 115401 31553 "2020-02-22" "1.63-2" 1035 2670 0 115401 31553 "2020-03-01" "1.63-3" 1035 2670 0 115401 31553 "2020-04-27" "1.64-0" 1041 2676 0 116305 32031 "2020-05-10" "1.64-1" 1041 2678 0 116541 32104 "2020-11-04" "1.64-2" 1041 2647 0 115286 31429 "2020-11-05" "1.64-3" 1041 2647 0 115286 31429 "2020-12-14" "1.65-0" 5 7 0 181 0 "2021-02-12" "2.0-0" 6 9 0 175 0 "2021-02-22" "2.0-0" 6 9 0 175 0 "2021-02-22" "2.0-0" 6 9 0 175 0 "2021-02-23" "2.0-1" 6 9 0 175 0 "2021-03-29" "2.1-0" 6 9 0 175 0 "2021-04-02" "2.1-0" 6 9 0 175 0 "2021-06-23" "2.2-0" 6 9 0 175 0 "2021-12-12" "2.3-0" 7 10 0 212 0 "2021-12-12" "2.3-0" 7 10 0 212 0 spatstat/inst/doc/datasets.Rnw0000644000176200001440000007007514141377564016164 0ustar liggesusers\documentclass[11pt]{article} % \VignetteIndexEntry{Datasets Provided for the Spatstat Package} <>= options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) @ \usepackage{graphicx} \usepackage{anysize} \marginsize{2cm}{2cm}{2cm}{2cm} \newcommand{\pkg}[1]{\texttt{#1}} \newcommand{\bold}[1]{{\textbf {#1}}} \newcommand{\R}{{\sf R}} \newcommand{\spst}{\pkg{spatstat}} \newcommand{\Spst}{\pkg{Spatstat}} \newcommand{\sdat}{\pkg{spatstat.data}} \newcommand{\Sdat}{\pkg{Spatstat.data}} \begin{document} \bibliographystyle{plain} \thispagestyle{empty} \SweaveOpts{eps=TRUE} \setkeys{Gin}{width=0.6\textwidth} <>= library(spatstat) sdate <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Date") sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") spatstat.options(transparent=FALSE) options(useFancyQuotes=FALSE) @ \title{Datasets provided for \spst} \author{Adrian Baddeley, Rolf Turner and Ege Rubak} \date{For \spst\ version \texttt{\Sexpr{sversion}}} \maketitle This document is an overview of the spatial datasets that are provided for the \spst\ package. To flick through a nice display of all the data sets that come with \spst\ type \texttt{demo(data)}. To see information about a given data set, type \texttt{help({\em name})} where \emph{name} is the name of the data set. To plot a given data set, type \texttt{plot({\em name})}. Datasets in \spst\ are ``lazy-loaded'', which means that they can be accessed simply by typing their name. Not all packages do this; in some packages you have to type \texttt{data({\em name})} in order to access a data set. To list all the datasets in \spst, you need to type \texttt{data(package="spatstat.data")}. This is because, for efficiency, the datasets are actually installed in a sub-package \sdat. This is the only time you should ever need to mention \sdat\ explicitly. When the \spst\ package is loaded by the command \texttt{library(spatstat)}, the sub-package \sdat\ is automatically loaded. \section{List of datasets} \subsection{Point patterns in 2D} Here is a list of the standard point pattern data sets that are supplied with the current installation of \sdat: \newcommand{\recto}{\framebox{\hphantom{re}\vphantom{re}}} \newcommand{\irregpoly}{\includegraphics*[width=6mm]{irregpoly}} \newcommand{\masque}{\includegraphics*[width=6mm]{mask}} \newcommand{\convpoly}{\includegraphics*[width=4mm]{hexagon}} \newcommand{\disc}{$\bigcirc$} \newcommand{\nomarks}{$\cdot$} \newcommand{\nocov}{$\cdot$} \begin{tabular}{l|l|ccc} {\sf name} & {\sf description} & {\sf marks} & {\sf covariates} & {\sf window} \\ \hline {\tt amacrine} & rabbit amacrine cells & cell type & \nocov & \recto \\ {\tt anemones} & sea anemones & diameter & \nocov & \recto \\ {\tt ants} & ant nests& species & zones & \convpoly \\ {\tt bdspots} & breakdown spots & \nomarks & \nocov & \disc \\ {\tt bei} & rainforest trees & \nomarks & topography & \recto \\ {\tt betacells} & cat retinal ganglia & cell type, area & \nocov & \recto \\ {\tt bramblecanes} & bramble canes & age & \nocov & \recto \\ {\tt bronzefilter} & bronze particles & diameter & \nocov & \recto \\ {\tt btb} & bovine tuberculosis & type, year & \nocov & \irregpoly \\ {\tt cells} & biological cells & \nomarks &\nocov & \recto \\ {\tt chorley} & cancers & case/control &\nocov & \irregpoly \\ {\tt clmfires} & forest fires & cause, size, date & \shortstack[c]{elevation, orientation,\\ slope, land use} & \irregpoly \\ {\tt concrete} & air bubbles in concrete & \nomarks & \nocov & \masque \\ {\tt copper} & copper deposits & \nomarks & fault lines & \recto \\ {\tt demopat} & artificial data & type & \nocov & \irregpoly \\ {\tt finpines} & trees & diam, height & \nocov & \recto \\ {\tt gordon} & people in a park & \nomarks & \nocov & \irregpoly \\ {\tt gorillas} & gorilla nest sites & group, season & \shortstack[c]{terrain, vegetation,\\ heat, water} & \irregpoly \\ {\tt hamster} & hamster tumour cells & cell type &\nocov & \recto \\ {\tt humberside} & child leukaemia & case/control & \nocov & \irregpoly\\ {\tt hyytiala} & mixed forest & species &\nocov & \recto \\ {\tt japanesepines} & Japanese pines & \nomarks &\nocov & \recto \\ {\tt lansing} & mixed forest & species & \nocov & \recto \\ {\tt longleaf} & trees & diameter & \nocov & \recto \\ {\tt mucosa} & gastric mucosa cells & cell type & \nocov & \recto \\ {\tt murchison} & gold deposits & \nomarks & faults, rock type & \irregpoly \\ {\tt nbfires} & wildfires & several & \nocov & \irregpoly \\ {\tt nztrees} & trees & \nomarks & \nocov & \recto \\ {\tt paracou} & trees & adult/juvenile & \nocov & \recto \\ {\tt ponderosa} & trees & \nomarks & \nocov & \recto \\ {\tt redwood} & saplings & \nomarks & \nocov & \recto \\ {\tt redwood3} & saplings & \nomarks & \nocov & \recto \\ {\tt redwoodfull} & saplings & \nomarks & zones & \recto \\ {\tt shapley} & galaxies & magnitude, recession, SE & \nocov & \convpoly \\ {\tt simdat} & simulated pattern & \nomarks & \nocov & \recto \\ {\tt sporophores} & fungi & species & \nocov & \disc \\ {\tt spruces} & trees & diameter & \nocov & \recto \\ {\tt swedishpines} & trees & \nomarks & \nocov & \recto \\ {\tt urkiola} & mixed forest & species & \nocov & \irregpoly \\ {\tt vesicles} & synaptic vesicles & \nomarks & zones & \irregpoly \\ {\tt waka} & trees & diameter & \nocov & \recto \\ \hline \end{tabular} \bigskip \noindent The shape of the window containing the point pattern is indicated by the symbols \recto\ (rectangle), \disc\ (disc), \convpoly\ (convex polygon), \irregpoly\ (irregular polygon) and \masque (binary mask). Additional information about the data set \texttt{\em name} may be stored in a separate list \texttt{{\em name}.extra}. Currently these are the available options: \begin{tabular}[!h]{ll} {\sc Name} & {\sc Contents} \\ \hline {\tt ants.extra} & field and scrub subregions; \\ & additional map elements; plotting function \\ {\tt bei.extra} & covariate images \\ {\tt chorley.extra} & incinerator location; plotting function \\ {\tt gorillas.extra} & covariate images\\ {\tt nbfires.extra} & inscribed rectangle; border type labels \\ {\tt ponderosa.extra} & data points of interest; plotting function\\ {\tt redwoodfull.extra} & subregions; plotting function \\ {\tt shapley.extra} & individual survey fields; plotting function \\ {\tt vesicles.extra} & anatomical regions \\ \hline \end{tabular} For demonstration and instruction purposes, raw data files are available for the datasets \texttt{vesicles}, \texttt{gorillas} and \texttt{osteo}. \subsection{Other Data Types} There are also the following spatial data sets which are not 2D point patterns: \begin{tabular}[c]{l|l|l} {\sf name} & {\sf description} & {\sf format} \\ \hline {\tt austates} & Australian states & tessellation \\ {\tt cetaceans} & marine survey & replicated 2D point patterns \\ {\tt chicago} & crimes & point pattern on linear network \\ {\tt demohyper} & simulated data & replicated 2D point patterns with covariates\\ {\tt dendrite} & dendritic spines & point pattern on linear network \\ {\tt flu} & virus proteins & replicated 2D point patterns \\ {\tt heather} & heather mosaic & binary image (three versions) \\ {\tt osteo} & osteocyte lacunae & replicated 3D point patterns with covariates\\ {\tt pyramidal} & pyramidal neurons & replicated 2D point patterns in 3 groups\\ {\tt residualspaper} & data \& code from Baddeley et al (2005) & 2D point patterns, \R\ function \\ {\tt simba} & simulated data & replicated 2D point patterns in 2 groups\\ {\tt spiders} & spider webs & point pattern on linear network \\ {\tt waterstriders} & insects on water & replicated 2D point patterns\\ \hline \end{tabular} Additionally there is a dataset \texttt{Kovesi} containing several colour maps with perceptually uniform contrast. \section{Information on each dataset} Here we give basic information about each dataset. For further information, consult the help file for the particular dataset. <>= opa <- par() ## How to set all margins to zero and eliminate all outer spaces zeromargins <- function() { par( mar=rep(0,4), omd=c(0,1,0,1), xaxs="i", yaxs="i" ) invisible(NULL) } ## Set 'mar' setmargins <- function(...) { x <- c(...) x <- rep(x, 4)[1:4] par(mar=x) invisible(NULL) } @ \subsubsection*{\texttt{amacrine}: Amacrine cells} Locations of displaced amacrine cells in the retina of a rabbit. There are two types of points, ``on'' and ``off''. \SweaveOpts{width=5.5,height=3}\setkeys{Gin}{width=0.8\textwidth} <>= plot(amacrine) @ <>= setmargins(0,1,2,0) plot(amacrine) @ \subsubsection*{\texttt{anemones}: Sea Anemones} These data give the spatial locations and diameters of sea anemones on a boulder near sea level. \SweaveOpts{width=7,height=4.5}\setkeys{Gin}{width=0.8\textwidth} <>= plot(anemones, markscale=1) @ <>= setmargins(0,0,2,0) plot(anemones, markscale=1) @ \subsubsection*{\texttt{ants}: Ants' nests} Spatial locations of nests of two species of ants at a site in Greece. The full dataset (supplied here) has an irregular polygonal boundary, while most analyses have been confined to two rectangular subsets of the pattern (also supplied here). % Parameters for Ants data with key at right \SweaveOpts{width=6.3,height=4}\setkeys{Gin}{width=0.7\textwidth} <>= ants.extra$plotit() @ %$ <>= setmargins(0,0,1,0) ants.extra$plotit() @ %$ \subsubsection*{\texttt{austates}: Australian states} The states and large mainland territories of Australia are represented as polygonal regions forming a tessellation. <>= plot(austates) @ \subsubsection*{\texttt{bdspots}: Breakdown spots} A list of three point patterns, each giving the locations of electrical breakdown spots on a circular electrode in a microelectronic capacitor. \SweaveOpts{width=12,height=6}\setkeys{Gin}{width=\textwidth} <>= plot(bdspots, equal.scales=TRUE, pch="+", panel.args=function(i)list(cex=c(0.15, 0.2, 0.7)[i])) @ <>= zeromargins() plot(bdspots, equal.scales=TRUE, pch="+", main="", mar.panel=0, hsep=1, panel.args=function(i)list(cex=c(0.15, 0.2, 0.7)[i])) @ \subsubsection*{\texttt{bei}: Beilschmiedia data} Locations of 3605 trees in a tropical rain forest. Accompanied by covariate data giving the elevation (altitude) and slope of elevation in the study region. \SweaveOpts{width=12,height=6}\setkeys{Gin}{width=0.8\textwidth} <>= plot(bei.extra$elev, main="Beilschmiedia") plot(bei, add=TRUE, pch=16, cex=0.3) @ <>= setmargins(0,0,2,0) plot(bei.extra$elev, main="Beilschmiedia") plot(bei, add=TRUE, pch=16, cex=0.3) @ The following command gives a perspective display similar to the front cover of Baddeley, Rubak and Turner (2015): <>= M <- persp(bei.extra$elev, theta=-45, phi=18, expand=7, border=NA, apron=TRUE, shade=0.3, box=FALSE, visible=TRUE, main="") perspPoints(bei, Z=bei.extra$elev, M=M, pch=16, cex=0.3) @ \subsubsection*{\texttt{betacells}: Beta ganglion cells} Locations of beta ganglion cells in cat retina, each cell classified as `on' or `off' and also labelled with the cell profile area. <>= plot(betacells) @ \subsubsection*{\texttt{bramblecanes}: Bramble canes} <>= plot(bramblecanes, cols=1:3) @ Try the following <>= plot(split(bramblecanes)) @ \subsubsection*{\texttt{bronzefilter}: Bronze filter section profiles} Spatially inhomogeneous pattern of circular section profiles of particles, observed in a longitudinal plane section through a gradient sinter filter made from bronze powder. <>= plot(bronzefilter,markscale=2) @ \subsubsection*{\texttt{btb}: bovine tuberculosis} Locations of farms where bovine tuberculosis was detected, marked by year of detection and spoligotype of tuberculosis. <>= plot(btb, which.marks="spoligotype", cols=2:5, chars=1:4) @ \subsubsection*{\texttt{cells}: Biological cells} Locations of the centres of 42 biological cells observed under optical microscopy in a histological section. Often used as a demonstration example. <>= plot(cells) @ \subsubsection*{\texttt{cetaceans}: Survey of marine species} Recorded sightings of whales, dolphins and other marine species in a series of surveys. Replicated 2D marked point patterns. <>= plot(cetaceans.extra$patterns, main="Cetaceans data", cols=1:5, hsep=1) @ \subsubsection*{\texttt{chicago}: Chicago crimes} Locations (street addresses) of crimes reported in a two-week period in an area close to the University of Chicago. A multitype point pattern on a linear network. <>= plot(chicago, main="Chicago Crimes", col="grey", cols=c("red", "blue", "black", "blue", "red", "blue", "blue"), chars=c(16,2,22,17,24,15,6), leg.side="left", show.window=FALSE) @ \subsubsection*{\texttt{chorley}: Chorley-Ribble cancer data} Spatial locations of cases of cancer of the larynx and cancer of the lung, and the location of a disused industrial incinerator. A marked point pattern, with an irregular window and a simple covariate. <>= chorley.extra$plotit() @ %$ \subsubsection*{\texttt{clmfires}: Castilla-La Mancha Fires} Forest fires in the Castilla-La Mancha region of Spain between 1998 and 2007. A point pattern with 4 columns of marks: \begin{tabular}{ll} \texttt{cause} & cause of fire\\ \texttt{burnt.area} & total area burned, in hectares \\ \texttt{date} & date of fire \\ \texttt{julian.date} & date of fire in days since 1.1.1998 \end{tabular} <>= plot(clmfires, which.marks="cause", cols=2:5, cex=0.25, main="Castilla-La Mancha forest fires") @ The accompanying dataset \texttt{clmfires.extra} is a list of two items \texttt{clmcov100} and \texttt{clmcov200} containing covariate information for the entire Castilla-La Mancha region. Each of these two elements is a list of four pixel images named \texttt{elevation}, \texttt{orientation}, \texttt{slope} and \texttt{landuse}. <>= plot(clmfires.extra$clmcov100$elevation, main="Elevation") @ %$ \subsubsection*{\texttt{concrete}: Air bubbles in concrete} Prof.\ Shin-ichi Igarashi's data: a point pattern of the locations of centroids of air bubbles seen in a cross-section of concrete. Air bubbles are present in the matrix of cement paste which surrounds the particles of aggregate. The outline of the aggregate, and the locations of the centroids of the bubble profiles, are recorded. <>= plot(concrete,chars="+",cols="blue",col="yellow") @ \subsubsection*{\texttt{copper}: Queensland copper data} These data come from an intensive geological survey in central Queensland, Australia. They consist of 67 points representing copper ore deposits, and 146 line segments representing geological `lineaments', mostly faults. <>= plot(copper$Points, main="Copper") plot(copper$Lines, add=TRUE) @ \subsubsection*{\texttt{demohyper}} A synthetic example of a \texttt{hyperframe} for demonstration purposes. <>= plot(demohyper, quote({ plot(Image, main=""); plot(Points, add=TRUE) }), parargs=list(mar=rep(1,4))) @ \subsubsection*{\texttt{demopat}} A synthetic example of a point pattern for demonstration purposes. <>= plot(demopat) @ \subsubsection*{\texttt{dendrite}} Dendrites are branching filaments which extend from the main body of a neuron (nerve cell) to propagate electrochemical signals. Spines are small protrusions on the dendrites. This dataset gives the locations of 566 spines observed on one branch of the dendritic tree of a rat neuron. The spines are classified according to their shape into three types: mushroom, stubby or thin. <>= plot(dendrite, leg.side="bottom", main="", cex=0.75, cols=2:4) @ \subsubsection*{\texttt{finpines}: Finnish pine saplings} Locations of 126 pine saplings in a Finnish forest, their heights and their diameters. <>= plot(finpines, main="Finnish pines") @ \subsubsection*{\texttt{flu}: Influenza virus proteins} The \texttt{flu} dataset contains replicated spatial point patterns giving the locations of two different virus proteins on the membranes of cells infected with influenza virus. It is a \texttt{hyperframe} containing point patterns and explanatory variables. <>= wildM1 <- with(flu, virustype == "wt" & stain == "M2-M1") plot(flu[wildM1, 1, drop=TRUE], main=c("flu data", "wild type virus, M2-M1 stain"), chars=c(16,3), cex=0.4, cols=2:3) @ \subsubsection*{\texttt{gordon}: People in Gordon Square} Locations of people sitting on a grass patch on a sunny afternoon. <>= plot(gordon, main="People in Gordon Square", pch=16) @ \subsubsection*{\texttt{gorillas}: Gorilla nesting sites} Locations of nesting sites of gorillas, and associated covariates, in a National Park in Cameroon. \texttt{gorillas} is a marked point pattern (object of class \texttt{"ppp"}) representing nest site locations. \texttt{gorillas.extra} is a named list of 7 pixel images (objects of class \texttt{"im"}) containing spatial covariates. It also belongs to the class \texttt{"listof"}. <>= plot(gorillas, which.marks=1, chars=c(1,3), cols=2:3, main="Gorilla nest sites") @ The \texttt{vegetation} covariate is also available as a raw ASCII format file, <>= system.file("rawdata/gorillas/vegetation.asc", package="spatstat") @ \subsubsection*{\texttt{hamster}: Hamster kidney cells} Cell nuclei in hamster kidney, each nucleus classified as either `dividing' or `pyknotic'. A multitype point pattern. <>= plot(hamster, cols=c(2,4)) @ \subsubsection*{\texttt{heather}: Heather mosaic} The spatial mosaic of vegetation of the heather plant, recorded in a 10 by 20 metre sampling plot in Sweden. A list with three entries, representing the same data at different spatial resolutions. <>= plot(heather$coarse) @ Type the following to see all three images: <>= plot(heather) @ \subsubsection*{\texttt{humberside}: Childhood Leukemia and Lymphoma} Spatial locations of cases of childhood leukaemia and lymphoma, and randomly-selected controls, in North Humberside. A marked point pattern. <>= plot(humberside) @ The dataset \texttt{humberside.convex} is an object of the same format, representing the same point pattern data, but contained in a larger, 5-sided convex polygon. \subsubsection*{\texttt{hyytiala}: Mixed forest} Spatial locations and species classification for trees in a Finnish forest. <>= plot(hyytiala, cols=2:5) @ \subsubsection*{\texttt{japanesepines}: Japanese black pine saplings} Locations of Japanese black pine saplings in a square sampling region in a natural forest. Often used as a standard example. <>= plot(japanesepines) @ \subsubsection*{\texttt{lansing}: Lansing Woods} Locations and botanical classification of trees in a forest. A multitype point pattern with 6 different types of points. Includes duplicated points. <>= plot(lansing) @ Type the following to see 6 plots, each showing the location of one of the types of points: <>= plot(split(lansing)) @ \subsubsection*{\texttt{longleaf}: Longleaf Pines} Locations and diameters of Longleaf pine trees. <>= plot(longleaf) @ \subsubsection*{\texttt{mucosa}: Gastric Mucosa Cells} A bivariate inhomogeneous point pattern, giving the locations of the centres of two types of cells in a cross-section of the gastric mucosa of a rat. <>= plot(mucosa, chars=c(1,3), cols=c("red", "green")) plot(mucosa.subwin, add=TRUE, lty=3) @ \subsubsection*{\texttt{murchison}: Murchison Gold Deposits} Spatial locations of gold deposits and associated geological features in the Murchison area of Western Australia. A list of three elements: \begin{itemize} \item \texttt{gold}, the point pattern of gold deposits; \item \texttt{faults}, the line segment pattern of geological faults; \item \texttt{greenstone}, the subregion of greenstone outcrop. \end{itemize} Type the following to see the full Murchison dataset: <>= plot(murchison$greenstone, main="Murchison data", col="lightgreen") plot(murchison$gold, add=TRUE, pch=3, col="blue") plot(murchison$faults, add=TRUE, col="red") @ Some analysis of the data uses a rectangle close to the abandoned town of Reedy: <<>>= reedy <- owin(c(580, 650), c(6986, 7026)) @ Here are the data in that area: <>= plot(murchison$greenstone[reedy], main="Murchison data", col="lightgreen") plot(murchison$gold[reedy], add=TRUE, pch=3, col="blue") plot(murchison$faults[reedy], add=TRUE, col="red") @ \subsubsection*{\texttt{nbfires}: New Brunswick Fires} Fires in New Brunswick (Canada) with marks giving information about each fire. <>= plot(nbfires, use.marks=FALSE, pch=".") @ The following command would show the data for each year in a separate panel: <>= plot(split(nbfires), use.marks=FALSE, chars=".") @ <>= par(mar=c(0,0,2,0)) plot(split(nbfires)$"2000", which.marks="fire.type", main=c("New Brunswick fires 2000", "by fire type"), cols=c("blue", "green", "red", "cyan"), leg.side="left") @ \subsubsection*{\texttt{nztrees}: New Zealand Trees} Locations of trees in a forest plot in New Zealand. Often used as a demonstration example. <>= plot(nztrees) plot(trim.rectangle(as.owin(nztrees), c(0,5), 0), add=TRUE, lty=3) @ \subsubsection*{\texttt{osteo}: Osteocyte Lacunae} Replicated three-dimensional point patterns: the three-dimensional locations of osteocyte lacunae observed in rectangular volumes of solid bone using a confocal microscope. A \texttt{hyperframe} containing 3D point patterns and explanatory variables. <>= plot(osteo[1:4,], main.panel="", pch=21, bg='white') @ For demonstration and instruction purposes, the raw data from the 36th point pattern are available in a plain ascii file in the \texttt{spatstat} installation, <>= system.file("rawdata/osteo/osteo36.txt", package="spatstat") @ \subsubsection*{\texttt{paracou}: Kimboto trees} Point pattern of adult and juvenile Kimboto trees recorded at Paracou in French Guiana. A bivariate point pattern. <>= plot(paracou, cols=2:3, chars=c(16,3)) @ \subsubsection*{\texttt{ponderosa}: Ponderosa Pines} Locations of Ponderosa Pine trees in a forest. Several special points are identified. <>= ponderosa.extra$plotit() @ %$ \subsubsection*{\texttt{pyramidal}: Pyramidal Neurons in Brain} Locations of pyramidal neurons in sections of human brain. There is one point pattern from each of 31 human subjects. The subjects are divided into three groups: controls (12 subjects), schizoaffective (9 subjects) and schizophrenic (10 subjects). To reduce space, we show only the odd-numbered patterns: <<>>= pyr <- pyramidal[c(FALSE,TRUE), ] @ <>= pyr$grp <- abbreviate(pyr$group, minlength=7) plot(pyr, quote(plot(Neurons, pch=16, main=grp)), main="Pyramidal Neurons") @ \subsubsection*{\texttt{redwood}, \texttt{redwood3}, \texttt{redwoodfull}: Redwood seedlings and saplings} California Redwood seedlings and saplings in a forest. There are two versions of this dataset: \texttt{redwood} and \texttt{redwoodfull}. The \texttt{redwoodfull} dataset is the full data. It is spatially inhomogeneous in density and spacing of points. The \texttt{redwood} dataset is a subset of the full data, selected because it is apparently homogeneous, and has often been used as a demonstration example. This comes in two versions commonly used in the literature: \texttt{redwood} (coordinates given to 2 decimal places) and \texttt{redwood3} (coordinates given to 3 decimal places). <>= plot(redwood) plot(redwood3, add=TRUE, pch=20) @ <>= redwoodfull.extra$plotit() @ %$ \subsubsection*{\texttt{residualspaper}: Data from residuals paper} Contains the point patterns used as examples in \begin{quote} A. Baddeley, R. Turner, J. M{\o}ller and M. Hazelton (2005) Residual analysis for spatial point processes. \emph{Journal of the Royal Statistical Society, Series B} \textbf{67}, 617--666 \end{quote} along with {\sf R} code. <>= plot(as.solist(residualspaper[c("Fig1", "Fig4a", "Fig4b", "Fig4c")]), main="") @ \subsubsection*{\texttt{shapley}: Shapley Galaxy Concentration} Sky positions of 4215 galaxies in the Shapley Supercluster (mapped by radioastronomy). <>= shapley.extra$plotit(main="Shapley") @ %$ \subsubsection*{\texttt{simdat}: Simulated data} Another simulated dataset used for demonstration purposes. <>= plot(simdat) @ \subsubsection*{\texttt{spiders}: Spider webs} Spider webs across the mortar lines of a brick wall. A point pattern on a linear network. <>= plot(spiders, pch=16, show.window=FALSE) @ \subsubsection*{\texttt{sporophores}: Sporophores} Sporophores of three species of fungi around a tree. <>= plot(sporophores, chars=c(16,1,2), cex=0.6) points(0,0,pch=16, cex=2) text(15,8,"Tree", cex=0.75) @ \subsubsection*{\texttt{spruces}: Spruces in Saxony} Locations of Norwegian spruce trees in a natural forest stand in Saxonia, Germany. Each tree is marked with its diameter at breast height. <>= plot(spruces, maxsize=min(nndist(spruces))) @ \subsubsection*{\texttt{swedishpines}: Swedish Pines} Locations of pine saplings in a Swedish forest. Often used as a demonstration example. <>= plot(swedishpines) @ \subsubsection*{\texttt{urkiola}: trees in a wood} Locations of birch and oak trees in a secondary wood in Urkiola Natural Park (Basque country, northern Spain). Irregular window, bivariate point pattern. <>= plot(urkiola, cex=0.5, cols=2:3) @ \subsubsection*{\texttt{waka}: trees in Waka National Park} Spatial coordinates of each tree, marked by the tree diameter at breast height. <>= par(mar=c(0,0,2,0)) plot(waka, markscale=0.04, main=c("Waka national park", "tree diameters")) @ \subsubsection*{\texttt{vesicles}: synaptic vesicles} Point pattern of synaptic vesicles observed in rat brain tissue. <>= v <- rotate(vesicles, pi/2) ve <- lapply(vesicles.extra, rotate, pi/2) plot(v, main="Vesicles") plot(ve$activezone, add=TRUE, lwd=3) @ The auxiliary dataset \texttt{vesicles.extra} is a list with entries\\ \begin{tabular}{ll} \texttt{presynapse} & outer polygonal boundary of presynapse \\ \texttt{mitochondria} & polygonal boundary of mitochondria \\ \texttt{mask} & binary mask representation of vesicles window \\ \texttt{activezone} & line segment pattern representing the active zone. \end{tabular} For demonstration and training purposes, the raw data files for this dataset are also provided in the \pkg{spatstat} package installation:\\ \begin{tabular}{ll} \texttt{vesicles.txt} & spatial locations of vesicles \\ \texttt{presynapse.txt} & vertices of \texttt{presynapse} \\ \texttt{mitochondria.txt} & vertices of \texttt{mitochondria} \\ \texttt{vesiclesimage.tif} & greyscale microscope image \\ \texttt{vesiclesmask.tif} & binary image of \texttt{mask} \\ \texttt{activezone.txt} & coordinates of \texttt{activezone} \end{tabular} The files are in the folder \texttt{rawdata/vesicles} in the \texttt{spatstat} installation directory. The precise location of the files can be obtained using \texttt{system.file}, for example <>= system.file("rawdata/vesicles/mitochondria.txt", package="spatstat") @ \subsubsection*{\texttt{waterstriders}: Insects on a pond} Three independent replications of a point pattern formed by insects on the surface of a pond. <>= plot(waterstriders) @ \end{document} spatstat/inst/doc/shapefiles.pdf0000644000176200001440000025175314155343653016503 0ustar liggesusers%PDF-1.5 % 1 0 obj << /Type /ObjStm /Length 3425 /Filter /FlateDecode /N 69 /First 554 >> stream x[YS~fbWuߚJa0YT[ME,An-e#2zS/|g`$&TL$D ITh"$JKB)DL(I0D0H(OKhԄ(TXL%&m2Sb* 3᱆kB0&<2CD,t9'0T`;gD#4I qA.pVΡ_)%i5Ct h %4W'Z!P'M I IʼnQp0@Xj*(H"ՠ f)e0*\JSna*x 2Xv@833 ffN,wgP,h92Q ]`f.qpLʑ o$:̪tV)I(DyJPr*#S;uuQ,Ͽ@2KX //*'"f$(!OgxW KEbÚa%qc/Q磧#bQT8+`W,l0FHt p.agIV ,(ZqV<춂 >mn}lS˲"A eJ^AYVV+2E>Gx%,s=jP_W,g/wY2Z'7}/zl"W3@ ҳn-IȼX4{2|.   'lEZ Zlr'k8PH*LT}0% $_@cyVeV]vlIp52îVv tV.9LE<[%YӀl E6d/I,_<3|śEeD{G R']G}6މ])P΍ h@Ft_d eT Hʋ)"*.YU_ٲh10[{B]/K ibw16F8āuqq;;ޱ 8ip`λ}c v p^J Vg_L1g679#q̶iUJjpP+(D$:P~&e*;RXdQ 輎no!Fc( $L4!-@-HA)Y'{GvJu< VF wb Hfkm:YoGu+K1Θ(z Y+Z3?;V I@;am*qc(8\+v{3Ek 3檁 +~qN l)*g ,/ut 3yΜ͋ECtQv9Mˋ(l6Cb߀ͣXIV.Wfy6\iimǗuQeOs;W[[F2nV-ۖ B)ݢsxb[eW8T% }3x@{N#S:*>u֔q_vf;bݙۿa[_{ߜ!@]$e=fZx~ZYe.;y4%u:wF+,Ke-[ +iKXӶltmÖw|=/vaݶu{j]GgYڞeI]B.vb*qTmSԽL%`%J elKaܶq6E|][BgٴqC [̐bW-#AP+0+>Z9=41Dtcm3(#!j Ԫj+R[]1x +)&[D6q`DHcɭH<~q9:`ClƗY Ad NXAz" M!D><=<:D99QDZMqűu"@'r(wgqv4:0= ԭ&vΰg-7g80~]nh{)#]ٴkw{`Iף|/Y%wQMlgǫp]Y(;3xl-fe-=`Ep coNO|3>&L5?dL n @ޝgw7Z&< 6XNe)C[}%|'#oQ3§4 ]G&(< aʌ= V~.tpHw]2>e}]NźlEWwu t}پG{rjBY@Ktn8 s\t]uۮYs)47Nulj&CmyPy黝1 Fok aNw0:$8RB쇯c CM{:&PH4H-r"*/zw$zK j4ځ R# swg|_2R~mMlHFnJ Pژؼ]')׳|_"Ӑ6I@fcgV_ΖlJ'7=/y5. :fRr`>Ů[Ѹ'H --ӡj2v=m9Kl*v%e-ߙbK&!( {l {g^_~al~o3xZ;0Pq1E",D9z|o1q c6{ -ُe4[wG6|\n_[=$wiqO;qendstream endobj 71 0 obj << /Subtype /XML /Type /Metadata /Length 1387 >> stream GPL Ghostscript 9.54.0 2021-12-12T17:58:03+08:00 2021-12-12T17:58:03+08:00 LaTeX with hyperref endstream endobj 72 0 obj << /Filter /FlateDecode /Length 5204 >> stream x\YǑ~%=^.bi} ɞi<a~ƑGduՐ#2/"FMzO݇ 9^pWčmn.NO&Mv2)n>\eNM&lv&}~{MTHy{;sN1moSə$;/wV)}A9m}C<\Rq{ =<޾z$0ǰPahf]t x;MTfW T$dci]@6O}}Y<~ۋr;(mr,u)4D.Ad>lq S$@lηjA78XK<q(V) Zdzl $iXlj>ez(ga(Pht&>֋kJg2I_HSHnxo.L}qyFaPk*2TW/΁n?xnc2|\wWbêhjxg{˽w^c\HУf#tɺ 4 nvNޥ #ejIZ-1tI ZיP/*gD'gUՒH~ 6o`=i \`|1 &VfOq<9ceXT|Z|:]U%SKxRXNfJ< f_dN|Ӈ',_NN JխLZ ]\hN(#3(@:$hy~0 ~ g0~HRߜMd[;"~q{"H΀%}(L*!Ƒ `cL U0!EgsDR cIG@6 C C9iρvБiO`hqe')w$h=VNuuI>BzG\x-cK?ǑU^y7p:2v >II : b{/aF%_ X"3 ڡ#Z3g4*PDzЛ|ͧŧCU.3* ">Y!$[d达Л\V*PlU{:MFBr(Ya>d]`F#N]KuO;`ؼٵjX(PXu! Z Qao0T=Z &OWOzⓏ/ x_ݴw2Aa7E-- 14W_CN<8 f3ND ;or.l¦0e7w~AmяI)qtuVH6tY Rѵm/;Y9-Ic/A>wM>.9ǧ.ޠ` {;*r,O P4> `5/T\ɆXEr0Jclģ%+lP0ѐAdS%D8Υ@ObJaX% h@ۮX#O ' d$^-H=:J~S}܇uDW [{Uj xܞQ*ͩMux#{,#wdEg%kXQB9ndA,:/c)&޼8"ߕ`rgM|?ma)q 86xV;~? ? )+O=q$%XQ Ȗ09 =~tHj|`O}Co.g*ko;:H8}=eE 2YJa$ M,g!?/ۭB7a&PEJh`t2al2+wyt^Z3lW3`=Mz.-PVܬl}$w&F !3buL<1 @&;|ߛ1V^h8z2%cXȿU$2XD(7%A""6gI&еI{_L $,fe(i#o"ec s2X9YPhe"3E1ʖ% ȓyFexCi`nxjhq#>@e~gt81ם,uiWm"U⊁Ncfr5ء\$mvi/t[9@nC\as\D=Eq.  vxZlIVNS"Fs^z"QZӣ q^5ۮ"n2.Z#ex s3!Q*E9#νX_K'5$u Y)H uH0(S'0wRO}qiLlC2bd"v *G)gDKLth :0raFt&90x'Zۀx3Ƌ` E +}c$=XOp̧4}繌RM@_N04W9@lA6НEo*=O1ֹUJ BnS^5/6xi J{rDŃ!6!h:Ċ/?P`K/ {5C2 Q׮)[SI?q$ joѭ Y%ڳĖjU S5rvVS#0(1&?dzO5+hڭ"~'1e>㑤@G uv\:29a \2皝[Wx0yyƥ$$:&TKs۹tw<&~h>9G__ѷ7>KZt8HFbV|*oJ<+&f8ىY\rnt CAc,k=%NB>/VKFM饀%3iRZ0!]YJl 2̖ $MUhkY:0ޯJ =M\: aHqЛ " 0 0+%yH&̍׿Dkz j E8MQۈԠb^#f_]X`Vo.Zq72"Ixڬxd`9FVmME4+T3O/Z^ g@Q)D6v/ )Icaj [ 6#7О]|qve1|N "Եm߀op,.fQP<1?Gc<~wFT*V,؃2E" OT ܛ]oA6cqcP׍UPhjET?f!@ 9=-ZaE b }CHMv6 X*t0u Co.J|bG&bsRazx/UT.n0gՏFQ!.4>1He!Rrb>tSz"fAA Kg(}W.wT+q!؍|2I@ca0 bƬӱ%@A܂mC'e16 ׊{hwKŪ75ap D{Y[2F>)8oH@4J-RM('TSK"-!/a.L({y gNMF&tW ca% :Z:T5֘Xja Lhw3KBrsсL 7$]_b0mXfxe6ЛϽyZl#s5zs})vr&.8FA7Edm`@GǪgTT|؎1k(=V)ܣ\٘a%IL}i3oڎ rhox7M5d[NC 8e2\x7ӯ/r&OݢJh~<ǹ`;;yd;LQL|EIendstream endobj 73 0 obj << /Filter /FlateDecode /Length 5929 >> stream x\[\7r~W#&y@}"l?8A硥Ƒǚ-Ty"ie/a<Յ wͳIzzzwd"ʋ+ũ_w濶0f>͛N,6F;eN[8a6b1 v<{6g9-zp:"x ?=m5q6^nwv؝ F :mM$଴H!2 onWS6")tȺcϯsϓ ǎ 1:D0ɜCsp+hJn.eTzQx n/$9FHL ؼiG.˱331nnp "w (ydڿ ǸF6]=\Vő2Bn|E#b߁H4أͽ*98AVR%T%Q%9HLL 'cv-ԛ%7h؆\P $tTZ19Ssdb#zGÁ Xthߗ8#J8< ->`F0`tʫj*m:QLg=q(F]!yL[I;;u:>YэG bC+! |EDLPtCEmM^߄D lC$9k %A' Z- [mթKvWހ2ΰ (43wz@J%_:d1ī/39|Co[$\eW$MgL+a1 724=@*p5X۪Q7WTHՑW]NwpCUDLש#mw[IҊ]+J8_]zP^U),~,esԉq)04 vHЦ#F\UeڻBQ)y_W9.A'EA|щ#+OM Eu ?4;Aus=,VX`|Ȼk2tDf=-ac & h'DgbzE7H8ObyM|Nˋhg=h@Pd؝>'0fc?LhIN!#> IpZyٳ|E<ʍM,Fm6/346.I-lGEuиQIT]yid<&OwxZ7՟3s̃}\.e’uECu=e`y[,:K(>H^nsJC` s<i-ÒUpu@RDŠ혬(g/ÜU[?S86hp֨9 0k<䋯bѽa0*'4j^uA:YMn 7^b8ђV uyU9֪!' $ѕn8_ c>LirG#D.h5I-(04U(e170L  cTx5ﷀ"If+-:1_|\0$ )7iQ|DQeuWuis(wq4,-L(`eNpO] L;}lmN?81 HJDpl M$)o!GѺ,A{n8p،3,`xea$b䉌l+Ol9 EO29넛}u)cbt`?!Vwx/&fY ؒ1hP Lc]l+L"N@:i8K'5iLNpAC`0B7Q)>0@ϔ:Ɣi3_Șe ETx.5 VھFӟNL>JF6 ̳f?|>mNҗI.}p XX1QؐbzoxHܘ.cN6&7ĄcI08…%dT 챉 )ʛˠ (4#7i2c}CV 4 `=f zNx-NOD  ښ&l>d*Ō.V;@J,EAs\&r[⻭U^1׃# s!d1r͏rJ)B|g) :OVz΀yݧl7׃m5Si!\mH C/Ϋ.M'SB]51E;xstρ^[S#Hk4p&ID9EЍX4@SLN2)ZK@j+*6`` Zo2c #z(xYl5b 6)&-)<txTmVԊ xB˫EPj1v(¸8Mm^{t$1 n_H%~.vKfݘt f:LHlEtJMA[L!B8tyT`R%ef0ڷݮ\8!b3vqQI6RU2F.ԁD _2W.x++TSHưX87cYQ(GG d.ȏx 0w;OU\nZ4vVZE7.훪`Nۘs$ISwC`w0Z/Ubk‹{ ܄Nc-adJ!*-PP@~_{~m#*sxPr0 *m3Xɇn@p9hO!7х>A9G fA?N&\ E^P0lu|,(WU"'`ZgM٥->.oࠩ%"ʣ(Lp.<) M S\_[ruiF S0u,pBԵv흴:vIt X$Ęփcr0ʐ}01]L GCE1̙WPa;nI5uSc(5J*E8{N99'FM="HX&-ާk1Ed Aӝ%TjIZWٖ|Ja)I0kZڜ+w~z\D=5ka;E58\&hM&3 t %h8&Anw@ =KV#_JĴTV5}W,'\A&C90d`LBE'uɥ@-L d8Cu`6VqqݤCyzej{;]ᠸ&CU+}].P v8Uuiᚮ4W^9AULTǣ`4lgVc`]n$$JZ&Zz_kޅטv-/ 1 9sb*MNIC:,x< 5ۊiWNTxD&'%G>rEKmզM7<,A#ˢ(;/n:\Ja  7aд˰BxZzKۨ$eV2ԳKt`;[qzel,>>3&a2{Y.{6>Ov}0lM g4f|Fɓ9Ǎ-f&'ϲS 2n:) ;OoR+oP&׊@h5Іt8bku4jB/F Tu.Q50-j 9*A#QL4: ?(o%qˑ$4JY4zR] 789̎:u 1s.f)9T5l~J`SkDͿ<İ=7X'8&!U Pr,u˅.X`( SҦ90s~w'G:ɽYgiI$t_5PgziaGѱIlMP񝇎c Gb"Uz$t%:XlLJaG5>ǧ'@/&Ij_nq8ew@/: GTijlkgu0_OYN|i~;D쵻c,09rwxxz#i?@_v㐔#VԳUшrQq>^r҇xVf6ksrTT5cGk~y;W7á2I<:/(cľŊp q{B/DZO}@ /\zxBr5VQrY&e=ft9gFx+CJ,A>DF>rзItwxf-nM$~y)7800o~_}mkT[kw9.j8Ÿ'Ji ~_eJ{q>zJH4Ѡ%)KB/!I`zp}ǖy¦s5|Oe:e2d4q#"͹ZϜ"C3n1/sc (Ց5!]IH~#oC^cQِJDCGEɩZ~{LyjeYdtE&?Gyུr:݋G :B8sG ɯr+ߋzF/8y(v󁊧X?G9^3]U0:aKWT/N>y_P c6v'޻/ S2R&ZY0P 0\w6Y2œy74\pfQ֑Tc|ky^I57j?> endstream endobj 74 0 obj << /Filter /FlateDecode /Length 4706 >> stream x\[o~ׯU~)ҢIS-4$E+)Z+R}!9!qC 9|v>֊yWDZYzU׳k%m zMUgE<emuHF;@t^5{Yu싓0_ں,s$/ͮ-!ne'~$"tvI$Ik_IMn&/ |T>)Û]l/p};/Iw^}\7&9$Xe_H]n7뮴fl61k 7\{ud#m8F޿a\vADb?e___rxS~YoKQrs1ޏrS+3֘[d`'iiGLXDxӆޗRABz+=c.a.(ü^u;q{ .w,<1jʿ 6anʃ cҙ ŅqtuCVrsOXZ\z7}[Z ~˕UzuܒRA; 'NJ,HХ 3ZfuHAAö 0bb%XX&+3hhGQ^Y疃 ̓ӊj0\-g ' ,7fImjqjM'4n1N{cjgAFhOgF RS ݦ{^W)[] œR= c 'ӥE:QnWy7rpG@e$,%n4Nav"B `{6057`a2ъu TEgr8w.ky'˲2d)1p."EcGW^ŠDˇ@,n]Ri*wn` \;qj0x:Q~S/*F[j6Ee?wH L}[~t_Sz!%Q\J1SL <-$~Eݺ;$Yv3cpWlQ$pP6zp79obqNmrPS|phijFcb8|ҁ$b*d ^qk@vrʎ1ɎI'24DNtRr'Jm@‹(f޷bv+ƚJƍFlM^\"dwAv6Q / ZpsgI `b8VAtpgq8UbZ" ƀb!y{o܁mlQ+ SweO}t՛]CroeAr`M*v@_a8`3;٥uiq5MB)lI֔j(,% 9!Si9o˥p,0 ]3RѐN`>2@e0 Hcș-Xoj n))'n{У ؊!і223-/kJpJ -!59 }Cph>NHH@0!R$JUʝ2Q#]eQQ,B"j;c&G[Nnv ɽO0-z $E~x^3"f `N@1^]t0H+ehX-^|+o$pas- [pL#U{qiZW1Nh1'eUM|\蜰 ?B ًP ~z bOlBԸ0P\o*qhc.zAgdŌQuZ(?/<%h)f.#|6xc\:]T$īcx @5ڑ4&8dnyIڅ v њhJ= 9NX Qv'X Y* A&.R*T8ZJ+H$`A(<}Dr/91e}#"7'w9ިqZwdsx ۥTPd}lYK5nK5q"̄Y՞/Z*SyHTelӡgO!C=Mof]M J8^Ǻ쯀6Mkeeb(6u@V-, Y*f]u*<ӐrPATO˷=ޣ7 WA,2u%߄\idUZ~-ǣ- ?5,i*Rz8 r>CW<|Tw}dO제8t/n9xuX,BAu| NldRq'Jw\luũʫW<y:\?>а$E(?6$prR{e(W^2ԆTA *0NJ厔F/A>RMxtH8LTPQƤ|[?%<1Ͼ6MQ`44M{l3e:W|rǶ0)D:}/?94Ŏ/( Xq`ׯŅpAquxJ?PCz My)\u=ܥU,9 'չ^;|fA$ ωȏj|1L~.!0]?`zG,9wo(r=c pϡ_>s0sWM-ԥ};% {r!Sj qjp_׾b:uEYS#p׶J&`f&>4vԠGJ :T:{_!640ib;$㡬u;o·f\n)қ5Ea2dr5`[PR@xYn"b޴. l}lYq6wW_5A| wQbe~ruY/\d9aUÙmێICO HO5Q!#sxF'uFj m釞Bx|Hxhf{P LJԬ5l> Qۋ }:f a6S7]}EN!:\1)x;Q~ɪ<Î*I^4N n'z"'ki,vnAmZKM܍"?eږ2{EW&lqETh ZAFD!ȗ@endstream endobj 75 0 obj << /Filter /FlateDecode /Length 6155 >> stream x]K9rkGP&ߤa#k FsZ=z%FdIVԚ`AL>A/Ia-lYj{&y1 *Длқ<A;ymvs=SJ/KlɄoFm`bVovfL,!W K;|9lnKsWJjOy]74ivlޙFY>۞M@o2q9U0JĘ/X-|jZx7[&-u8װyi.7H}ux)m/c]Ӫ]&>M #$2ۇ`2GV/ r.rfr' x`/τ"ISiL )ez2^?COw{rLX-3]V`-(% $8?:X"d\Qih::4]>j.ŻڱdDnvJ;{'բ𕮺Rbre]H1 V_Y-,9IZXUh`wqnV4Vi] (c5l*<_dQwwQ&Q1xjBky]6e>8p^gLdį$UA.j(@]lnnvbρdR9y " @{w8iF&\T/,0zܯdjWZ-49W("3B]̳ :HӢb3/=ޑ>l><.h ]쐓@J._9lVntwip ˦pua˫vj3 ({Eh!Jm^(n?^rQJ_P,bdT+8rP/N7&>ϛ.z$xo:Ye?`KWmK3hnxdM`G#Z(-[ZzSB2y#qThbe$d㚫;|޹{X1h-m̲)0a*׷<*qo{C$rjqy2Ud5(_^#. BDEc5-]i"{W q~l۲ƙOHhMP+ͨra+(+I=*eD%l6"Q6>ՕC : z El.84؞ ZG3%lGD4kD~NH"Ld_3edS\vK1 zQi+L;Bwg9e" BUQwoZHPsf Tن| :ey$9NE+ aL65lO=3 CxP׎'6QUsA,pN;/xo1-4K%t ƋF扐!GuKTg_z7yIF縎  ,Cb$3Y]{^<,Jc=i}-:ii!ܢͶuh_zt?lNnVh(w ea%<\_T@2;MSMw s}b.6dOfTKpD /Ad.L-h0m@{MIPE7gzr8fk9+E ^PVXa&l Tr|$i,?Jw?1aY0gRɁY:əu0Ũ ^EAٹ%GqJ8?C]p=ڏb((Atoc_0s Vtz wej7"EL|#UMzopeGwV/9a:rg5 )P'F ~pww.22W;?>\='Uc]9w 7vƏ͌U"Rx3 MJ|;]'El8?& WcpKrSD,ܕ2<JafAff 4PL5i;$伂(NO5T7P/Z# aZ_Qgʵf^J,ro@ەxrwJR4`p KKT= |ufJpnQKuUC)H.bC;MC$V^JCo r8Vĺь@8 bzFvi0ʋ^SH·i@z`yr)sV5i5gVef2M,'Ha`nSs-Hڤ TnE#ġ2:ߏxĠ@/iT}E]sB^ǎ,E _!^q]p_LU}¸_ .QցTW>U^-OSde0d~:s0j#^K<.JJw?ojCOi L&{{fZa9JMkJ4^eO !T}o N}?CpqS4XOkV_3fJXVJf<ɿ)TAu:-GoELx%4"MmaqMU:` Ώܺ.;+ Jsm~ LN b*6KA5߭EТ* JwζF4 ]3ni@H3 Ќ]<ʖxTbwct" x52 f0]F<̣ĵt1#l(}YW.%>!3I֌32\y3V=14 (GGFXz[wϴ pWnX1,0Z.'w< R˸B;Li*pH̍|/[Eq33>LYuBvÂ,݄!\,%fl\R9(],(~RAxURx끺P%W` w1cG ˀnSAڨWq(X9<C7VV4|v}Z2Ɗ(eT1 dhAҲ:#Qn'WbNr aijR&5֙Ir$JSԷٜ.,s291['̓oړz`sAqm.' kBQYIH1v"$ioY/͖ ̪D?3*~`٣O(W,g(s[UtVQ*tQ'mޠ?Uv>kn`m\8 iUıL=~>ܢ.~aQQx~1 ݕdŒx\"^~d5u8ɃbO],FfAA&w0IH5L3IuwMڋ^6׊Duebc# %}}w팡 87kNvж-Y"nGuq Yvr>bŀbLJ>UISdD,*ڝT\9Vcwԋv`(thQA4W,/ByL5݃5P!&ϸZ߮JJ<,m7u\`-1swCO29PX^L>Y BDgprx!LȔ^noAVs5Kʞl.8@oXZe &C>]I_A >%0 .x`7N\vAɯ3CЛt)* !;i7`c[OTh> stream x\Yo~g&q߇av H zX䊖KMꙮ!%q z`y:wb/wG2==^9'_kO(<>9?Wuk?jO≠9fP4B {Z[;:a- g@*]j c47HCpj_9z1hzxsH]6Em<; Vǒ~UpS80F/D. )M!/^'҆Dž(䮐g. )MB^ueh΀ācA#ca4sk&z$ΊIN zjTADۃ=)ԓPa/vQL\us <۱FKeabEa5Hx@Sjx|l,y5F#gKP5MM`p :TZ=%Hc10"㇗YtV)[ߓc1Vwl5-`4t t} H͸Z;Fp6:|Z+ [4 ėccegƥ #SӎacFϲweP240;2CRa`gOEU2w<وƕ!v8gCJټaA쁀0~(ZE!OCL̦Q(}TNI>^NL(Y2$R rKJEN|/B\0|56`Ri:)SƏqT_u!/ +Y!vea5 ;!,,Z;rd`Ed'5MTdI9[Ti`iZZx%X$dd5G$*x 8H#*@N0*`[#z=xi ~$pEÍ> q:-ST+R_1EHTG \`Z ] :0D1)W# |]G{jlW'ӊeLVްrfy > :H5`'}5$a/aCv-5=?!EZ?P\e,ĄJc0eyĦy̹G6ɨ3|  ѳ $iQ0l yxߔ,53zQGtm |Z*'cN*{ӻT p?1C.-R|wuFHC>hHiN#Dqb#2G؁٤w^%mM3rUF= :RspWLG G[s's5 N3VRwԄ +XP$'S8f0P 0@bRYyc:ষbY-R~VE؟AkuPmŔ {>CԐQ]q7QVXWiLm䞰Ts0 wvsk#yM(Pmu_ R"CmqA`OE&L `%$WWes8bU"b/j \ U:~Rp-)(@M+ d0m?XY3**%$Jq@-t>SEFۗ8iEͮ{~C'd^fC81N`Q^[2xzA Pz])Z S1N `ۊ?_5N Fg/4l.Ngh٨'BCNVk$`E4y@]|bav[3|tL2,n8cљdc!9֧+KWϪ{l/6?+O)`KwD~}5/ /0t^^_w_x K edc\~`%'1K`-,ÿ9{)iQiWUk\v v`"e7U_/v*2 V]|̭(hdr^X-*vYK2<ӷ .+vIfEϺd?bEFxV|յ .Gvx=& `Gl>AC\w=|T/ O U!iS9XIABE*.(aF0aqZX? =0 M!qk*]dfluxKG ϟ|6饺~;QY}ℷ-ڎj on l4'n,KLgTم[A3=޹QUno ?juazR,pa}XtJ\tEڛU^T=5:UvXYQ]Q@YSi3h@u QAꜤ"^.ucM<_^UED8E?.%]+dzԶך+ s )0+;YcVɂ ?/RVk0㽱onm^=~7PDݿ#Յw)h̓&=ԉ:cxJ#0mТtFM%|:)TfHItx/&M6G:`ʤcWf)WU՘>{@7yB-t< ާ[Q7Vl mZ;:7赐̐Lđ 53oˢ+XSv95 2A벐B+W׮8:TTr'>UP~sZ0 jE))]I/o&o.FMeul?P_uLe?vĺ2 Rzt ؘ6B't mVYdᥬ󹾚ZD|nۄf`+ZU6ϋI-Rn){]BQ\ticޞFl@%*hstrU^N MQ޾P8 x[fÍGr:2孁݅GP<1hJ]4}ѕORki)"m)j؈Л~ F_nF(6^?Ie?s]cwdy?-xG]xR Yt˽m({g.NjZ,c%-nxbiNn ~#)L dɼZp3O7nf64zI=NxaaHUbfW!mo@5Jifꄲ{Y[u]ݶnwKX-HxS|c*3B9R̷ESzjԱˆ1瞜>z#0Vqvئ۬<1xiq U6n,7e-˲VVyHL ذ |I# /}KM)#ʾ\\ =/JR1*smn#x~A1X+YiI_䁻=O* %S:jrՋ . }~F% _UnTR.J 6.|\52lfAQR&N}fƻƣi8?۬%SRN+q)cy%KnuD<~sժa&cV hS:ڧ5OT[TC2:ᥰM5v?Wu7y ]y̏;*GsAqYP|&:g3Ϩd`('Jخ ؖ/!k:t·^3/+Qt4žIf c WA}vcꯈY#\q@!"ID_U*nendstream endobj 77 0 obj << /Filter /FlateDecode /Length 5560 >> stream x\[s$u~_G0zIi:7ة(eIUV"`avɥh]V*=0CJ$W*bh\sALL+uv/4?on3&W>Ԩ7gF;W̸ٺƨLQRʺ}dƠR1 _4m.`8\CheC~cMJ1٦&?<6%9 {WqM)*xwNiwN)h}iɠÁ7k&Luy6OJ8:Z;mEe!6vވIK}{wAG^Qwfc,|pZ<8m9h1 ÍtcgJ!9+;18u~|tEo192a3c:3ŝbm{Yř 6ql]2;|3Va&>qRԚ1iÔCnӁ҇, tcp= w^[,mm^&H>̳d)&z6Ƴqc217Š50z I7rȟqݭI|D7Uh哟`fnݿ˯-qPKwAD@ *&xW90A[ x{|ǗN$gK(LUКjvYYA~]}8V ؤGGGvAJK]dvS@(dɤCk(LEtUVj <7K J.uR9tڤVp}R6O Y\h^p7RVyiHV/՘ưuU'8@ x[h/Mn慓p@mQ8LE|W9W8FSCN:ë(`JAJS %bMuPwy' ïkjdPj:'ukSMm~ͫűwyM6Ğ$1<DbSLՇڼ\$wT9H {->6ک9/cԫ>_E0~>+3_f7GڼM1q{Ӵ3U?M72vJb:?ػdk&'Gnc_ T*e6 p6-ppAY4@4.:86ʩvlf@CXN!( b˜A q T Ճ0#8x/J31.'0Kx7o+HfJ)1j/pHOk W+5ϛy&w#!B޸Y.{.`htʲB<dv0Lwݗ_/IF^RNk :6P&$ ,2ר.wSRqo+*"/6d]6* q2,đbZleo}m =_lhCup{q$F[ uzXmƮ.Օ7r蝂"5ݕ6L햢]h|eوEls2OXHA: Gq|YS`vVvQe-z G3q;@`NTo X'Cl~_>E8\FӪfրjλLh9p F~ iC4+|ӾK~H89( xYU?3 6N]dyIKJ徲vmb OfHsǐ^<@iv~S"R _Pfxhp"i]g(ܠIr)O_\Tq!N!0>,)kZF^EM 7(2 kf2E .;G ~g[OSucm MHP$D>V![=ѭ-B `*zxsU&z~!d)EZvI=I Vj>m0\ӾEmrUX fp/.&+W}:( >^,Ė)/ X@{m  "ސN:5![32w@JI@B@u d++hwWjI4mL|oRh.Bf+s " 㽮 Kߊ+rQX5i|cYCTKh(Qmm Һ]/ʟdJVɂq@Fcқ@!Բ]jxM4~ "]a%-kb2ErW: {wqd*F*u rON( {8@S-hWc)5.ւ01"+Ai(3(Pgf 65Vŋi!qB1ͼr.8eH=/&đCLTuzmB6%&/DԹU0Y; #"'v",zFVzT ]A\Xcm,*2wʕѓL=rwkQ4PCxY±Ïy8n#\%)%-) l%tI'D;ns"'*Oȁ ݖ i+n&L&Ӭ  0X2=i`,0KT^haeVl RQP9[:|WbO[y[([T?rzA)'X Yʁơ>MSAP,x[8Wч$fAn10? qokZ qqxw a=*Y>آuj7$]C&>*)duŶdMi M7G!R7JHrYtg#2B\~كi=HY4Xg.ұlD:,6ct+ h%C'-&Wnj-H`j}UsuMG)(@Qh7:#GQZF˷Q3/dZ }-z"Yxޟo9(mY?!S2\ "S`#p[qM_X*aARDR? +Vb!$\` c>$!zqUᵑ^&`ρ';E=^`hRLiCݩ?s/I'Ԙ Dv =ۦ| !\eO o<Ջ}#w,c#-SVNXt{&M|z \Cm<f@} 5NhPqv3Y M"+SEׂn}EGpabT>9 {>8pq3ݽ"U5qHVRutORjN9ԾF1Z¨Wͮyݭ9TILB*Q=uX=KgMqk@T=-W])MY|vq/_1Ǟ56??Ԧ6(`i:Q%IH.QӉ~=FrzڂG蚮0\ksN䈺n\je^P%sɮqoY+7R"=;y(zݗP.^C79 &.<{fڛ- 6"'kgRfvWoDA:^2Mi9.46K˽|](Fq|qr2E5JY|/gs;gOh$~2"|< '(s ?J&Lտԋiendstream endobj 78 0 obj << /Filter /FlateDecode /Length 3507 >> stream x[Ys~gG4NpSR7KryH.MRT{tcZ h4PP@p aqr}ǣKk飈 " ~^{wxt};EPw3` BVFֺ7Rv0.tw8Sߝw:FmfP {!LȫI)˛ɫaц]A W:3$^:-8ȨcϔM~k+Z@G ;o\yO]s[v.^;׷Y^n pHK!( | x^7lγ@"LN _D{6hI,oMk,(PB6%lx5C"T>1ZUS:pc}<[{λelpژAg|YiS%B0Ւ}xEZB;]O!s ]Υ-_k%?#>3%23{1^KKNX,|8l"DynYM;fb~"7I:V%W,T S7 ⷌ7$u2 j* eW<*YR3"7 gt!#XΘ&HiYøU%yGl.Ât+:ۓjsDJ4P.r_xjzNrsx~*Tp)o.+.8e^A%1[+n 4W3nwr{`v|2c.5k $_uYgsZ'SV!-BnXiHzÞX% *?K[8wy5+tƀwdN< ʈ3]DP-q4$ FAN;kF] cφ-d6B+/Y <pdT@`n= n^Wqx47&=2ZR\e%*]C#*^F/7ZlWDwM1l][|fL #hH>Bl#Kbh5wq 77^\s^ f bU> NP P5jbw 7>̗Rzp7ݗ` /W Ă }IsDyeAw$rE)g_2@%+"O>cYR~O=/ÅD^yܜn͋k;l\F m<s !k[n r)ub]-G \4VΓU;&5A`f}M't#2d[;ŌcO<k|zU^lwJ֔nlI$hÓR:#E ;]Q~ ο*eHVB}dP ].e@\,8JzHQqEh#ERLu8N7d2â:)CQ~63DV1Se{C!"&aAȘ "%SQrH=bK.Ԡ6};lN`5M+a=lsY;1"CWɡ9PŐ]iղ&4>C>i&`zK$ /nm,p ^W^P* &k.o&X6C($6ȗ p KR짙m&W=IF3-UvZcc5F.J!uˊZ8CWy #EU>_9[g>k:dPJ 2F*\C;"9,+ <}:0IkS% I%QY`2im F@^RNO;[] jH "lNxe\%#f'2 (owEQfy<9:{NyG$emNB1Q8lyնIE*`{G'`=AVWTN¹v+#/ hyف͞romzi| -nmoҒ:4XЃq^َ ZrrF\Ԥh7VZnnQD? Ϲ> (l"tg06ؒbfņRG)|Q]C׸ff;q Jq1 аp{=`*KWa1s#r)UR7r]_13cStOэuB{AĪLq{FEZE[9kMmٝ酗R2R2 2O!HyAף&Fbd۸ģt)5\K' ؓ j7JG$sU(7V5\ςлc̯GrNzb%Sc"9 ?oWzMQ!{C* zG H۾H8 /򃮶,eCƮm!-=IWa4g—+tSuByV!؉'AtJDA*@XRrYWn7U87qؿ!0%+gmkawjLP"UFt S. <'񔗫85B=.n\Y/.%(;hZlR<3>X-YH>3 6椲(cyΔ7`0O; j\톱WwdЂa^e/#*,L[)mW\e-O4F}H'7 K #@K6W1)^eSe7+@0n1{0/s}9K @HWH]Zⲕ6Fl%]M|ds?Oii!}ui>-몟4`h)?5wX69 _b$/itN?e~%-OG n4uC ۷.oG;aԆ^ RXooSOSh|R^E`e{IDaY L;,uyDlt9vz\ԡ{*z !i_|i&l SCG_C9kHrX#|3_?J!oN/I0kKjj[2xyv og ߷S]pF{Y? HC3?ol1J)ZNZ"_yU~̮+"yx R&+ZxFc,w3{IەԠR%H[g,5?i-?{v;I3Ӑ\ejiJ? XHi ~'Ab?]؞endstream endobj 79 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 1757 >> stream xT{PTW%ltBvb^ɴ΄93goyH"4 IR=%5vy*DX-5̥ACWѺ'y%]W,,ڮrU:Yb,6.nFً11qWq3Z{AG/7uKJ,cЀJijy-{ٿ̢}:]ל:hk> q6aH-컸j/zfp!gD.ͽ|}Y.VO%?&mzV9p¿)FN3.\ӂ!y(k*+ã=)WJgK<^Klx[-ݙw K(qx0h p9َCE Պ|ڊ47NtdʰI.a~p4Μ} Y-| UM-.wS[y{Be(Ұ\w8)/u*3e+p~?IQȃߠU8t`7ueg`?/g6"E7= E2}>#)D%Å=q*Y! SC_6VLΊ-3>c`ԕz 6o'}ΌS ]6t>J R*B0n @L،ZavB 8~~BN)qg4ȵj&8N0&TPJ[&oPhJ/ ؟Éu~H|?{YR`1VO yDDX#$3%+fARDz.||Px*۽^w#C)8$pxODhuU(Gֈ4fg5PeP&|l   endstream endobj 80 0 obj << /Filter /FlateDecode /Length 235 >> stream x]1n0 EwB7l \%C > stream x[PWwYHV`wƪdڎ@ш8j*>X6` A$fJ/CG:zs|F3go I$IJՙ cϹlR$|Lc/2 dG愴a`4HlJ6[V}SFE)&&S$*WV}ƤTk8֨`k92r,K,p8*De,t9rDkk(WM2Mc*'ܩ&dbVڼEk5!3[J88_G:"H$j"ӈ0b!*ėLvE) MR`ip"ZyO~姄ld`PXSL`"&ѯ^=|YdG/\r~*Z"Y! `+byt'QB9x{P78?4i7;w)5]+)/C615>ia5VeʣVLtKz6Ϸ@x[>g*U 8jV|_u2|N9txk[@BC l=0ʞԞӻq?xCNu;k=@B{b NEQo0h-?^|W sIxDu^]X6;[~'2M/_݉EǙ[oٚac[w=.W8C0h=f32V;6mM)5 s4Y8Z7 7n,W|u칥P tƷ#B SZd)>2 v^hQ?:.vj fDFY8=3'hJaq0KSQ(BQ~r‘Xt > stream x]n0 w??)$KEe:po%|:8*yXe[>Sm.Uuޏi{kKVg 6J(lo4 ͘*,>YD)8Fqp) 18("E*(2UT"SEO!2_/<զ???Ny[9endstream endobj 83 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 2936 >> stream xV TSg~1TX{8Z+j]ֺuAB %$D¾f!ld\ݶZ댶:t9g̙9srw{w}WD9 D"gq"a0M1࠾GpfF Kh˔X$ŦzȣaJ)\g/\`Y.*w\aҨ %yt .U&NYTF?sfBBŒrEb 0WiT/ v]!)]GE) W/yT!(e2wGظIҐPp߈"PQʗHm)j+ZIRqF|>>:guQT{ cG"QΌHO˅Dl%ikSƕKj_hOiΫεK/#y nW?L`(,lwSs2] "wEn?kSG+d@8bR"55ӛ$m._I~ ]Ueԏn ;F %W|QX2w~}*GedgAMEx37yhZr}8NnG9D-Y*Lfhѣmy".3K 2FYVYVVy(ԾE~oqx+$*dE~n[*:߃%4kUgsw 8mAy*G٧:;“8|⹤?; K;zCA)Qb:KV;OQC:׬EG?hVwe6Dէ2DJ%`"kv,D55U.0h.V1qQ s؛R~}տ~$_g $ s&QE賛 }%I8ֱBR79Dj!OgApPq2IGb-4 3v`ʐ_g CKD7H; UbtXЧ_9סhv. 6rHʳRa/xOp#P }#̕禀jlJOV: ڇF109a?H-h)鐇E6e[eq1渺\cT@Yn?A&1jW9h}Q%Zvb?qxKQ[/#[/3 47C{w a,=Z` 7-oY{@ k'p*D$J9dHeg?Rgy>+a,IN&Ց޵;{ĨemObL~ME$5dW>fHzhPl 1QXXUL'W7=Շ4^KՕh:r=}ۚu)6w~kuiCmY,-ge`zb[qwDsU(E<Gr#X[.9hendstream endobj 84 0 obj << /Filter /FlateDecode /Length 592 >> stream x]=n@{7ޏ8A PPa"0Jb ~3xǗ/og7ulM9׷rrNz8|_:^?n?4.c[=> stream xyXTW9'T@`I1vc.vQm SЋa`p@@ hbFhhb$7>sZ]}=VTnp5Ǚ!?Њԍkzu;hh-?*VVasBwx;8~ڴc'7qvg@n>nG Q#cz>rcĎp5a;=;. w\h9XϹApPA=C)?;pNЦy!C- _$Y3-=cy+Vyo#FN8i)Sg=)jJ>VSPk)'j8AFRQj#5Dͥ6Sj>1G-SDj 5ZJMQS vPQ=7HP}T?ʖRR"?RSeOu R;`oG7t{|_݄}B.`V3K1GK^ֽ{ӽ]{i3M߶~ 3lsED]&̮sf9(|820``@4(oЫqc&`qj*^aӖ&/YUCږ)yʌ,%{h#vK5`feX&zSUg5#H-@?] Q5(K!ff5e%BLuDo]FDQ7%6),"/Qה콷cER8,F߮x!gnPPa _W[ s5h9#ƃb$+dљs^ډxwcd4ry͔K7ODypy=>ͿLxS#ѢJ\??Hǣi7 Wfq?2Zhay  ~ȗE޸(la=!ؙu#B=,;T~d?V'x:dK&`,o2YܗUh*a&DMO(21Kbt494PbH=̙honU1/(LiA? tgZUrz sYb&Mhwh5ض^FD,{Ź!stUyYcr8y,:-awX$w7 , +7Uڹ?u@8Ԡ#IԴd订vMGV5x gq::Rx.K;*k2,\9"xIG"t{|s,^GʟОE+/|63CFq" 8dȟŃi ;3gE Q+i}:Yk4ڠ5Р[lWׅ (:Tdž=MPQp7% ;z|m3aXj ~`WǷ^j}h'>C߳j[QtW7j*`?4~ xvҳ9b4MwPi8*"BX}!ʿҕݜދ\IEI&t#̵4 oMgۏגh"X=O:K1R= x.dp/!̑mxNVB(CQ;Q ڎֳzl1"O xHc{:sbNMQ!êgߞؓ+ڞIFS΢3jni5:1&i_BȐ(!!Sw%Kgɧ \"TTȾ#1HL:j?0ٞzOi/y9dAf͡SӾ"}Z ZsWяR/RZԈcQbGhSߟu&)mO.$nlu'G^ Ix"Z#^;ƽ_^p 2OtV]FJgX4ԄeBմǑrF=qg W+^NrZO ;oB{M46WVs+3 }ɬYcqNOB٬ƒԄR•pJSC$$*r8wGU<\TNpuT *G0OӤAffzul[d0ELy5m%d[ 6MdǶ*}]ʔq8~TV^:kj2  k:(Pfǧr2"'1HKΙڵrXXq r~nM2STk+K?r&7>޶斧hk;Q ;6գܭsO:ѫCeR_49u7lfhcEΘRU-.i!tz-:xbbbYylr /nd'pz6>Α*W ~ٷh=hNp2@Bҵ^ߑef<1Sdg%Ѭ ??KgYZHPWGի;6jLj#TB$<}eon)͋!eLL 6 =S=!zʤA&AP=jDVfѕN]aigZ]Ȉ6]%FB2fsL,r9,PRit׮wR ܶwlﲰ:'Pdy7}^B぀Hpjp\]o# 54TDR)S>*{,@zy2X\GmH}Шv+8_YdmЂϊLz(`m .8}TxO fi,tC,zDw 箐@<RQaffǘ}9kĠUWv.P)K'D6oFtN Fz9g%_ ,IS %xAcUHniiV9LA®ZƢ2w'*_5 a*9 '_o`@f;K(_Jdk0:ԍP{'JA )q辰$(Taw`S}`hC]$b:ո!#1E?@f^{ U *h4:`6gư}!ZӜ<\bW}j!ִ-'3?V!@m\:l0t|UBHo*QHU2~Ls*ݐQ,rh|Eڬ_ج+pϤ;0PmIj]wƦ {ynĝ,Pbsb{~bGks 4)JY6v&^p.A-Hblj"r啠=e+%x!ODgF6`G?(}Gho8y `nޫHx)$&IJy>Q=cuqsb"Xj{u%;34_bGs_e wJ}RSFQMWŢ_R}lUhI$8$Xb0TFjU؞2\D\\Or ۳iypsgzɶtN-YNA[-"YJH|T@ `s+X#?p%=+Oޓ\UM&3oܩ3ӚsO*.jUIrc7dpjOv\n!<ޝQ7\|o a0KV<6^r\L/s^Ƙr3,5mC^ 1JT/>!6{eXY``XX``YXeeYY%.^$J:ZlAAضil;Fb ahr~5 E9H!!qC8p{,fv$]C] dЀ(mTU {`jFyE_'rG*_jJTUv<EY͊L%߶}WUouBcѺwM͛hvζ7wޘ6uMm0`ooآ6@"~ v&~'S$)exT=ǫRą9F˅BK\5kNC zcql׷4 Vœ~ Rfg0+u?'ỒC?V]N썯a!'Yx _Eye RTl' 1,.&`n^A*Sg:D`|]e /~:f#ӞOFPx,=u o?z" XDA m~M/&c˓$ɶBw$t@w c-=`2$)AJ:Yw'?٦kZ+50kV9ĕ$MNZL*qJQ_lP)Ϟ|e':^\!i7g髏4ǜ!35]ʫ !.-;$U2T*ňڥ ( --tqU&Ť}Lm.0/eܳ v̓:o8wKXօ{̽dyg࢐(_}:V ٠MS2x_LD > IBCoN已[B!s.nf>>.1O'7c4P10VNv1`^#^+=Ed/ wcQa &=L9KL(sx6_ աY$jѳvKDѷwS xiP u&3TN@^=k_&BیhῼWS9330?e?W1lŭj5f"S' i[sBKz\>U=}V^uzSpendstream endobj 86 0 obj << /Filter /FlateDecode /Length 496 >> stream x]=n@{7}?`lc7.I.@KC)>3#;EY`$3þruun|Y_?uzYvc7]ۧ9 nmXY[|߇y r3^cۆ>sݵe/J}J*h*S`'V%[P{*hY[[J` mT 6hJI E5 kT(QXÐi52M\*W ii52M\C)טk`5y\gE$rAc䮱;*ithBDAC N2 XCA@P`k7hjlhjl 1T vEP`B *P?BB .*>&dr `0L&RI\ 0 K&p)$`.L  Np_؍֖XK,ߞוou/a>endstream endobj 87 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 4705 >> stream xX XSWھ!ps!ֹ֊VZk\ZWUACBvrE=lF@)q%T6*:uV[=?I$}ܜ~D"dkL6!*F*A9mHdg'(tQb(J jJ,wY>uYH9yw_(W,=iR=1J4y@YL6QrM4YC!((jg䆨 G/+b[ⶭ aPpȚаu>}s7O8yԷgzE}HFSj KS>j>@mRSIbj 5ZJyQ4jAVR3)D ^PCPʑr))5r\)14eKE36lĴ8\|6mg$%|f nP>ilvh1$mġcw9v vrqY|ttT.=?ix;ձ|e+ BPpWOA˦R焣HR^QFvrFF Jd"Q%GMJ=t( % GUS5ܓTg)PbAװҦEKVk ./a0mA|:^F52UG{ +}3^x4wӦ[؍ǒvVP?]'VaG,tPt  &r?K<=jTbb\#\$[Q|AT[=at,RlE[Ҝ'dIc5a"=2Xt! r+ Wtteky͡,f[̒o,[%=5HrF1:F/Hɂȁ^uy9C>\"}g`7+W "󗔢OƖ柿.ؙ5#ƸoT]lObI+4y܏j^##oiMYd'bߒ#YSqEN[)t.[G7S zYmX4@#a:d5fQ: nܴ1 ~S|n\aRcߖ79&39$ n ('{vxg /mHiF jDƤO%ɐ 4 3-͚f/Bq_uߺ{ iC51qf9b梳 )Z#[,iQbQռ/ܣMYS !m줰9@ uQL3Dws#Ȟ6]g^T/ A1Ȃ"|ඝO3X 4i[5C%Li^T!$HEVEe5Ai]'>* F)@ɊR2uCb>EMܓ/K8*}Z&.iÃJP)jCyL?S [z`A:FiakOi!FWkn)yi!Sd{'WˌH㶶+%I~{):r'hi,8Į\O๙ޖ~ѫheέƻW&/9"zƞM4YJ?^>>$$fJc&=~ݏh%>3&޾ҫ&,+Ws`o|o"a4ݤD*ĄWעOx% c}9c5H=GڏԕysX-/_dEzjmQ\PHuH4-ۿL/*4b!YoXy2GE=&ب)LTb((MxS b(Q:n-sIfoMAp=nD4XǪ"Y#*"ոG~萰V,lں&Iz; >Jyxdzemd$%:)4HYjIⵎER<=><(H̚x v֏so!6fUO;eOY2-$ XT#o4f;R2QVl[ͦ/:aQXxCPYL=aou<< x$1.x)^Ceo.E,&AEhÛO;_o䅣'=wyf_"lp>x10ًMO L^r/+1$n6*6Dz.RZ؄vd2I(lyzl> G(,-, ^Wk^Va?GV^fjEuQ0Y,̂z>ؘtR0I}+!ID$;]l[DcX,<|{ΖC  _t" +G cW>.`a2 ƻa0ïx{fAvd\^I͎d(FVY^}qwd@A}_Nw67?Ħed"5ހ*8 Dc匍p*}y*x(l,;({"oƴq'_,]rsKwE1352"!lUDH\Nt٫.E@c0kk?ݻLTLt#[$q#I+~~pRneaѶ>PS] G'4EٕD!sK={^`Vh#jH3tL쉗0jZYY+6krsQc)3*TƻjR}׊j]hJB|g;l^{DrgLۋ\sbtTT2$nV1ʇB<[Rw7fbKS4ji( %Nޓ@ײ< jEui]5yLJnhr/Hl۪ C(qendstream endobj 88 0 obj << /Filter /FlateDecode /Length 410 >> stream x]n@D{~@'k6N"F`aQ"x=_˭=دWN{~c}[xj}ؚaί{=> stream xW PTךmC߫"H6. ƨĘDUfG١nwF My1ꋉщd^̫9Lޜh{ɛUTS9[H$ۊys-^_/_6Zl:_79f)v},#H4gUD|THPa߫zk,s<< *G B43k4bcc稢}uCl&as: *&U8 p:ܜΪhM@? J0 9"Jy/:&7?`C`P-{̞3oh4l`62әMf+y`v2+gƝYɸ0\fYa^g2 u gl;9f333Q̫;Ɗ.Y-9;GG"^eoj!{SVڳa-n!HZ=ꯣG7,ьS2m۱v60GRQk+~(5KE.BTË+DwEF[{M ]=&cty]4XNUe-Il3vB/\U ڊ.qY҄qߒD4L?\pH& @_aõZ{`ؑ v 0ES|+0>MH7mݵf5L";Ob_#p7.z~0$K"Ln!| O\Y×nc ʁk0D])fql.r]dok8g2P PEJ-C,7{]^y}s[}/p';cWCqt]6(Eox>>oK-]nlصG^4 #^1u~NgZ$ Oد*yAdEKhGdp6z&y:++ |}Npj( +y9]n(u\q>yobOkɷcpf6UA^--yrfUaK$wPv_Nqd nl.id y~r?㱍ݖ˕@)` #9pt`8CA~9daCݛofSrC}C~H~@yF9<-?69xuS<~ϒiqi7Ke@BduXA"Gr(Rek5էAxļ9gRV2E Y+I[_fa(tβ%xW@5Ԥf'M\DR oө  F7]XЁ^m#NTnAoi@FbX08*?!7nJ`;d_zle?2Ռ-2[dl!?Z~!t[[:x V)X2]K&삩ܛCoic`[VU uU#J#k#8'7v73q0z7j]0 9:7dRD"@+ᐺ8xl ܓB!B";iu,$JEqTn4]N6$$R@xDn@Ia NIVI3dJkJkUׅqg>;qUoRn%iR@%OKOI + 2Ѫ^HM'gkCww{8ۊ"@Bc+d#v| _#%Mm _FD6X TyR:R<5.8U^Z@ ʲjSLTMop$ c!Nɽ?VWAV.koB~S=yEd{dFa;= 8~iqrL%/GdI$8_PÓ_v<vM> }rg8 V53DJnjxJ#̒7o?pmCQN.sԌ y5j>4ݗW6y#O/hn35G$ ԱyJqHcd ڂ"$*7OF) r굺,H+j}!_* ߘ.xW();C3j`3~]ty_9d*7,w'NBիNX%^= {vNs 8vQ(W< :}Yo=߳9 @9Jf36 IzqqIb 3:d]|5l!g̎; A]@U( A)bRp/xXTK Wd{Fh8~I[٧%rwdZ .%-C3\#d"hPwpw{pO(OgJϒBḱxL LoӛD 2*Äaz"G0I`5p:Wggh33uzfA0)[~+Ndͭ%Ȝٗut&;u5CB0I+&HxY6iq3>)x8`;"{o焂3Un. ;C0DX*ĭr= M yꪬJ>6K~Hs{sM "#r?*KOwTu {5%EX!óBTd-`ӑǹR qL)P-ŏ,W y u,"VlGl:gH;.<̂NQ0J!Ӫ3ܓߠ0pFXѥƺVU?Q-IG̻Ml,^hc_R]KW͉#|㡎Kbğqpg3mG[r:{k>ڙK-$&*=պ@].C \~%Bqlx?o&Ub$k%3- #p:\JYNzpm$nc$OTphei oUIWAVbwt_X^eL֨. %*6]NFS5;]Nڑ~I\?h2:G оK@]Ek9Amo@_Q "R47v6s>YrP:8O|46W{wpa|N$ +wmxV`&Fzj1)F:͔bH^XFMoCdW@[yȂ i^[^gIY^-8@q,suf{ȎI+πLȻŸbF>.8~ng%I 4q%7eF~@UL_/Bi;^;r*}z%IH0T$sSX۔"qc!zV/&Vh~բ*]&dlll'@endstream endobj 90 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 321 >> stream xcd`ab`dddu 1T~H3a!#.k7s7鉶 ~(Ș[_PYQ`hii`d``ZXX('gT*hdX뗗%i(gd(((%*\"s JKR|SR YtX޽53~OAe=rIa:Y˺v]g*{ZG\Fۖ;Q> stream xcd`ab`dddw 641U~H3a!O/nn7 }=\19(3=DA#YS\GR17(391O7$#57QOL-Tа())///K-/JQ(,PJ-N-*KMQp+QKMUMB9)槤1000103012)ٽgf|;?̿ܥ;~3>,}} |g|Waq6;7<_s/wt\7Xp9yendstream endobj 92 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 321 >> stream xcd`ab`dddu 21T~H3a!.k7s7鉶 ~(Ș[_PYQ`hii`d``ZXX('gT*hdX뗗%i(gd(((%*\"s JKR|SR Yt޽M3~_+ۻsO/{Vw\B ۡ݇f<ʛUg+[yNƾ|Փxxe` Kq'endstream endobj 93 0 obj << /Filter /FlateDecode /Length 337 >> stream x]1n@E{N X%4ӸH%,Ea@}|)HEv8_Ӹ:ϴ8k5Kq*ǸkKV^{I9Ұ[{MGO)}-mLk;]Rք`0XRuwtã53t4`2 0Ƅ51!ԾWJcBT+G4 c`(Q# <1h a#47`9 qZ=!!TT)rJAuARP]P!TT)rJAuAz>)}]Ӵq8.>%&nߕ#eJendstream endobj 94 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 3146 >> stream xW TSW>19*BπsۓQZkjN-(>+ !I  ֩uvYG:YvYcgf$++Y#<<3dˎ` ?xؗNMDx7=\/ \~H_ <\ Qd$Rpa"k+ W,_,\'D-"T,0\ Vg!USVFY&.S$k-jRqXuH|P^nBwl_! yJZnQ x)YT7҈b3%҄${2Fl'#vN"XD"vDECK'B F"/b3JȉY/o&`\ݟ'zlx߳K@Fٔ910szyJuj5X{36y>Џj1\05Y5 ysB;I]6qXg+(=[WF F- |*mk(Fr=\|ȗ4\$D6)eaں;Y(t'5% xxO_v9R3gfcv>v?ԍKq+U&hB=JWG@hP[nFĞX2-ty\t@DSyz66jczRo M w#{QEFs4d@Q.my"ڧ7Wħ@ktӼeeH!+RkfqLM$ڢf<>$_æZVh4ۺEZB9C|t]Mb=0z}~~QYfN&TlId' 3 l ^/2*9l(psLȯ1 L'_g^ڧq:%o(ukDTRc.U8yXpNh ni'mVu I5VDu2WSOOuec{VW>#%nAB-&! DvMwi8-(t*/IW zfRXZ+s'hYo ~'y@6)$d24r8h:J8b8^DC]5]FIu1Ȍ vàQWF)l4NPڊNvaΔA7{2{  >n(6 K +a/:ԮA%行t%ZU}%CilC-y?9p N(CHo6f;c)|KCB߈ )؄z##2+.Qq|4<ޝ~& zbIS9݁/TRߕ+~:*49,m@}jX[KC;ƼhH}GSڤ,xSG&g #qnDIexA' oD̾uXwfv+wr3Yg+spYa%JٓtGj\V%'nIsN,o^AzM ^/ cJӍ5*@d-4r ݙMϽ5?}o-/o(F3+ F+SQo-_ .` 0LAjh`jr:f v,[>=t&Cp`$:̂-«){x$%Y%1ٌ= 6C3< \ԧɅy\$dSЎ>Y"%g_w5)j 1bʥ,Bܵҳr I&x=I? Q೓Ľg/'p>.4|y Am hK> stream x{LSWKɒ{P=kFSa&Rhy@ Td(㥔נڢu(j2PsLi@#!3M|$IR [BIa~.Z \zf~_P\R I,%FSY 5ʥ11+"#cqyZ^6(ԜN W٨k"/tg]f-VYY+BÕ6=SnZmr)yZxsxcicl bdp̬ a.84r]( 4yh֧tؠc30+=FFWo$jzG"˓hXC}uʔ0H.:AW7z3zg*ShgGV 8VĦ/aMjA:!~sp 7RIއ}[u[Q {._WRs(tK@ ?󔸊;ֺʆQdgS{՝ʥ2d&}8Utf}N-ȇ|P+שlwzgZ7َd=^oOO__OzJJzVV i֤.\;ʎS""tQ8pwTc 쬸?0$Bh$:fʏFdN۠tp^:Izd"t,Z-{|bsJ j_GfOU.3}"|/ĿG&endstream endobj 96 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 621 >> stream x%mHq `T`>#ul7797.9rTE)IoI}H U%'5OL(W2*HʢR hʯ2+7/ ApsxykE\ZQQ^JJ*Fڎ `aXZ8!g2߲fq)YWǷ.(`;\M >=WtzuvPFԈTF[]Q~I>ICJ-F^<܃1XnÃKSKK񻏢v צ| DXO9&XUiNc`@?I ~wښ?xRk{jҼf賬G0 } Ho5)E$1QzҴ%)7$BFmҥjG / R!ghIW^?[d}_jNr_7vTymМ cc 3ԩ3^BYI$ǽ:7C7tmLC &̑+рklHwș *-)zQɬt&MY+?QyxDA?u endstream endobj 97 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 2613 >> stream xWkXS>1J>9Z uZ2W( 0C@HH$!!rp  Um;d*>>z#i>ڮO>}oX `߲̊nw..`93N^:˜CcPH34c2]XR$d"2#Ĭ\DL(2+ 2L_VLs. 󗉥ٯF/,r"r>/rX$#-Ċ_/" "D/+feY9ܝ0 K6afl ۆbo8l {[6`FL=J`0Ɖa9R>sXfKB_=3;q9aA}x\c1?D(mz->Q05w4_x9UF)$U}9PŦ %UV"N\nt6m3r(~m/9 :! eJ"S K R+*%5b0VxuDxzK3X[.HͥԓE⯣DOT-a "d`6,K E[v&NJm %S'a~D=yF :Ke0 Z[m]kMم310-e ԉ2u٫'﷽ǕPsD2iz5jSJc^t}Tݏ 4GσJ\Uhu[o]T$#+z"Kqmn NUi%յ-ͭ Qn'"WϗWhV'b=4g\Ğ`5鱔\FQ5` [lH5rZ<3Wՠ(&rK4VU)7?ޓtD[ MuTNSCǘA[p\k@5n: :@NW\QE4Sz-Ƈsri͍55vkp]+_#)呻v#:;[ 7t zFiBDfoƯu7aЯG|ymOާ\@8 *DD")oŤfSK+.tA~ձSDm^[=9@äl`%\PA#L"efY&:9}W4j^c4(mQmGmAN׫HD!zM9+}P zy gKsw Yf`ϾUx:G|Eog1_V6Y[=Tg"6h½J{QbC_|g~oATkyPGfF|*e&lZj6Z|?s: C Ƞ +wzһ7|Q=rN֮25Zb*i:Hvv783vjDS*b%R :H~!:k[M-t o\oI .Mi*C=j$>uU0)ٝN8u@ց OR SqWn^֫=ck#k}^6b G)=T?z} tN:mrh|j>EJaei>.Mߛ;#ZJ=*rju, i2YwB5rVڞ PT"R*-Iwqeu]4>}GnH.̏>aW%UNfJ& v6xww,evݸ}Wb8iLٿLU:J% jE=ZB؉BGH~z_%!f|*·F u}hW5=ѺRe2xS7rr; zӨ99y 8G$y>G[jjkuuto_:rsNYKTt}m9eJYZS—TeSʯZ2}=SCD2(c rIX6zĴǃ)\97PΙ#=њ&hď{7GmM=LM ;^NZ =`(}WOxc12i~~Vi$P'ه|B(lDƷz :iq+L__7mlC`nv ^|vHt"C9r|UD/NM?^87=)qIiiBB{q; 9W𻟢OgSgxT<3BN;(Rsn?$NMm.3ǮbҲ\7=:Ρp_V<0NJ_25G=!!\Xe&5dnj[6 T >bT;^ QǢYCVzB}a?Qu&endstream endobj 98 0 obj << /Filter /FlateDecode /Length 466 >> stream x]1n@D{7aq#Hr\,L\)R 8ye5u]o4/V߯PK}،pro??:KV-c}_nZw-i*՝uXXbўd/ŢŢdbюX61M&撳I\r6)K&e;Hm+X\,,Ţ YNe>&QYʩXIŢ,'=idFB9sQUUp<$|PEɲ~!F!OQ`dd= wws9b9sg !@A8`@!@A8`@!@Ţe B  ȫK.h>.7WK5/vU}xendstream endobj 99 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 4444 >> stream xX XS׶>1xP{*T9T^:TlmJj*Z'!@@ȰƐ!̃V}ġulmjz{; }䜳Z׿@D"ߥk6޸qt1"a/ )J ϧi蒑T2 NELRiR,6:&5pbċ3͛3%p_MF' OJO%nFFfN\4ڴ`,zS3bScGDң"_&8ǿ,&$FH#dEx5q4)yԴpՙYQߊhlTH"*nyP$ђ542#g>oA 2vj̡ s o~g=#CGG>5{T樚Q̂g>f'9YnP.aHH!|t(`t@Q {-P?mͰ54. I 6rZR Y[Pi3c!2XMEH$|\NqMd 4v4-AGЎb mНL%`awpMog%[ifѬc'9\*O,04|o,R e=%GÛ<~/il$I!Mjp^$I{6AMMdY_yӓPq.˨X02,:~x81eh lN׵~O߸l,̅yPqI^; ?䋞G>KM_=Y7-zB{CA(y*d=S3f/O]kh#1 rKv^uZ ~ž$=W]=~^h&/ha4^DX~% !%ꭍ!x(B;]"uYP˄BFVX*k\կr)LWWpY K+-RSho3UqK$t3i|4)%1^ <FKqS23V#1A-+T%gIhs\2yvg~PhЁq3 -vݎcבᄍV"][W[3Ic{3.ѭK6mvұ A;cɷ ={VS/ƺ¬<>yVy80ka._>} {07%'H]t~K9Eŝ-E۬]'_;#rU<1*4&ȋ{^C%'.#Փ_gp|~9c.y)(ͫ"V]<K꩏zKH{F\l>&F]wڲӭo6h|\iȜV`Ϊ܎ dglY0/4sZ#ޤ=dc'wj[V̝;| @${%so[4hci}mE_ heڼ- 8Jc7!Je2D.}~Kv2r,g%g)eWg4(ѦffcNt@qìq _C$١_]]ł Vt@ggn?ъiwKyB [!:!3)WO3jV;XgiU'Fn :K.3;e4*Ceظ}ŇL Ymah{k9xk?1ru(_7wwM'Zt-6MƸO+c4h!m RV'&9,\7):ʣt GlYLgF N4h37*4\LnE}Iw%GE7hM{ 'Ri,WO8!4``68tO2u[<[ٶ؄w="$4#E%!T4ITIe|KWotj!^`iu9&FP*s"4K.lPbl&^e5'Uk/}dc~{"2 Q$-bpaNgR5*9smb^6MVgl]v.nQ)T4GUS1|{qgهu󷴖&zskK1;'td*.D8SLZjG1 XT*!!L2pRFQġTw1&(0ZǢahi,Ua^>5R^݆hБilήj=略Aʡˬ r8U*P@fڢEq=V[WR@ZЊVI*e ƙ%]. dJ|)׈endstream endobj 100 0 obj << /Filter /FlateDecode /Length 4908 >> stream x[KǑϯhTة7k9l| Iie~/"2{(K Ɋvg߮nNvߜVXewWfwV>ߵ^?..y}Ε8G_w9亻yno\Kӗ74əل͵Φ7V,~k}^o7~6ysLsW᳀ZjwwXo]+,]!r&ձ;̙h@N1|-&qIyp^jCgv("d xʄBF1]L<7gvɦ8gly|B'XB%-Y)NT|45^Ì3$29AF6O)c[& dWRuMLFk307 &!\\{`0!3`̥qʘPUEGe :Y}RS5t9cyH0_=7c.lM"IRV 6G8,[he {3eheڀI^]s -br!Q˙I`@r`ʃKԑK 8ORFg6%D >x!Ft8Mӭ 0S,1 gPD5`x/IG]2G]yXFՀR"C I30ހ5PiQN'ONh7>I9٪KPx9qcb5p>1 "gk+%j2c?C11~ 1Ͻ  cFuJ*t:I#s[Jv3S0~#!U9bPQ}N7y_Ş"U4QYV3?7 cͺ7q*b Ed7@%#ðJ2\!AK!EIqɊP6IG&bɒ(dtdb9\=G&TetŽZ3gM7u'pݼd>:?tVbPJnl,ݕ N\q5OF jXn-(Ԓ/[~IX0HIɡ $i9[sTLc2 qXk8I <\t583$!L*Yx ˂[H]7gF6 pfM_7s+ީ_ʞ ig S!D~p|/Bp^Av4.2EP"v\|ni@ɸ(E nW,p5Fچp.qW=YAZ–q1֖BӺRA5"la:VRC{w뱾k0q㽨w uOb 4#K>fO/"cSبVKJ:"uK* a#sw[sa"pF?}U6+.!eWGIFDlXqKaG\m8Xr(u>lDPxp\;BNhTYҏO/&L6{d-::On@?}dUvZ1M,>:wV)DZKR m*NH+\ leK꼪(~!K@($LjlPBNA!bJi_5R9:GAz'؇ 92b;h/^*J'G]m^@JOO(NUX`R<.NR.DGkl,zƮS#0!S+EF [C)#9a2ZƮg0(kf7dg8WQ+\( 9wZW69i>vXb֎@Iv%J,T[(;٬&0ux<gʘjoYuj2<ٷ|Y>t8"GX.Q:@ =ϦIET%mj DPҾKNͬ}`6']Sp7Q* =1R"3HX[ [K"f?rA1f]Sa3Ȥ=ٓV ]*Wz/W4x/K)%GeԬ#})#)E0K;I=ɻ56gIM/֡J+J~Ãd1><>|8;Y{S-Y[TZ ޴,)B3I l )؃*WiSZOIrx1m7nXT;:͖Jj`ᔕ}T$jV"m*ioY$7T"tX:/ڈr-P4[]E侵lcQ&mXK puVRݳ>nAiӌ6FRfXUW.=u:VkŔdN[+)aީRV!$mp8ƜΡ 뚓N?h; Ȁ^7VֶDxg߇><᧳H9,mpXoϮ1l S!Wk呣Mn|JlJC !)\Y{<ozbcO ^ ד/7`ڶN*զ9z76G0eВ>A=*mrjw' oCs놊j> w_!em.҇g~!+tmjA;/L6=Wo .T'!A Ԛbnw!iwa@F5XCiQMQ;y2䋒&=rhq!Nn{n|f 1& ;Nc[AA:<%i'is.tzɽ꒩J݉y{{X5 .$A:G 7_mvvęFVcJӘķ;M+Weu( D2SmDҽv(GNHT?V͚v${-]˥ɐ7E{9XP%9jLg9Kxbχpjs7̎O,qs;k/*yy|Sr7m(V'% ԰͓E }ߞ]pׇ/}x{v}^(\CXӼ_B_\Ih.sTv՚;3B]៊SzF]_+nq@هƮ  Nn"DLG KK, m=X<4n7)T? RA;C/H|QXˣg*A7+{qC6OENWyv)Mz[ݎ:<؅XNB``ɍ}~ Ge`7Ka|ל;\~nv!X^J⃝ gUxF^hMvW~*KؘWyZ3q xcK]Mn_./lFN w  VqWwnL0l(^Qs?K}>w}_{anC 3ҿb ۳ƚ?*[nPjkJQr5$9`o:mƤڍ. \Vy{rQXb6_܏W wϻ+?;ɰlͿq܋a셌`H0N^MsF x؏SlS][C/?׮6J-}ʕsLW#l88{rkڄ wDq:&%Zf=zJ- \GFkoO !|jPh:2%Ej!ie}E_Njֵ$yʂWHn%еte3 _{H67gwyִ>uy,-S)08"^Q]]{Q7endstream endobj 101 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 992 >> stream xRmPTU>w?ugCZ{%@WÆ6>V@(esw/+8|L qlrJf5PK$44MSdPYt{s}^)da0VkvY+ʷE[e iLc"JsR5kXe$x#> H0Ody$lbxZvX-U.IA#VCA&VW~S/w8X]S6[6\= dBYhbn)P&:~e L0*I ዜ!xRkW4]Ps S^;b6OԠɚ&襜 KZM!\۠d9IhɎ8tq HK$UJڅqv޽;:;@NX?JfBկ"ʆʠL%q -#zpb:k.-ZQ;w1;Kg(|40KRs{o 8|XuSk3~ g}6#%AE^"$PFOB &uwiM+jJH=$sY̎-#G4`Q߰^pÛ׳n_t x,TI vmJEiZo\o_j{j|;R!op#(VbH$TP2̯27YǪ-]C<;QgWOu pj!&-3R7j[8౦g-I,y@d7yF gWՕU |G}(vSx -g/TS%)hOM\v dᷟ' "35g#-il|4ĔS6t~nR fD0X=۪]AAթ@H3FW{CkAw4{5endstream endobj 102 0 obj << /Type /XRef /Length 141 /Filter /FlateDecode /DecodeParms << /Columns 5 /Predictor 12 >> /W [ 1 3 1 ] /Info 3 0 R /Root 2 0 R /Size 103 /ID [<3982bb151ca95f63aa5687bdd92c0554>] >> stream xcb&F~0 $8J:?=@6^PE Rx5A#"A$1dML =D`v?`f`q{&؄% D2\`Y)) DH+%o endstream endobj startxref 86604 %%EOF spatstat/inst/doc/spatstatlocalsize.txt0000644000176200001440000000042314146324064020154 0ustar liggesusersdate version nhelpfiles nobjects ndatasets Rlines srclines "2017-03-30" "3.5-6" 21 85 0 4677 0 "2018-01-30" "3.5-7" 21 85 0 4677 0 "2019-04-13" "3.6-0" 21 84 0 4663 0 "2021-01-10" "4.0-0" 21 84 0 4663 0 "2021-03-31" "4.1-0" 21 84 0 4663 0 "2021-04-20" "4.1-1" 21 84 0 4663 0 spatstat/inst/doc/spatstatguisize.txt0000644000176200001440000000051414146324064017647 0ustar liggesusersdate version nhelpfiles nobjects ndatasets Rlines srclines "2020-03-03" "1.0-0" 4 10 0 865 0 "2020-03-03" "1.0-1" 4 10 0 865 0 "2020-03-13" "1.0-2" 4 10 0 868 0 "2021-01-04" "1.1-0" 4 10 0 868 0 "2021-01-10" "1.1-1" 4 10 0 868 0 "2021-02-15" "1.65-0" 4 10 0 868 0 "2021-02-15" "1.2-0" 4 10 0 868 0 "2021-03-31" "2.0-0" 4 10 0 868 0 spatstat/inst/doc/replicated.R0000644000176200001440000004062614155343645016120 0ustar liggesusers### R code from vignette source 'replicated.Rnw' ################################################### ### code chunk number 1: replicated.Rnw:29-30 ################################################### options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) ################################################### ### code chunk number 2: replicated.Rnw:35-42 ################################################### library(spatstat) spatstat.options(image.colfun=function(n) { grey(seq(0,1,length=n)) }) sdate <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Date") sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") options(useFancyQuotes=FALSE) ################################################### ### code chunk number 3: replicated.Rnw:180-181 ################################################### waterstriders ################################################### ### code chunk number 4: replicated.Rnw:199-200 ################################################### getOption("SweaveHooks")[["fig"]]() plot(waterstriders, main="") ################################################### ### code chunk number 5: replicated.Rnw:207-208 ################################################### summary(waterstriders) ################################################### ### code chunk number 6: replicated.Rnw:216-217 ################################################### X <- listof(rpoispp(100), rpoispp(100), rpoispp(100)) ################################################### ### code chunk number 7: replicated.Rnw:222-224 ################################################### getOption("SweaveHooks")[["fig"]]() plot(X) X ################################################### ### code chunk number 8: replicated.Rnw:253-254 (eval = FALSE) ################################################### ## hyperframe(...) ################################################### ### code chunk number 9: replicated.Rnw:279-281 ################################################### H <- hyperframe(X=1:3, Y=list(sin,cos,tan)) H ################################################### ### code chunk number 10: replicated.Rnw:289-294 ################################################### G <- hyperframe(X=1:3, Y=letters[1:3], Z=factor(letters[1:3]), W=list(rpoispp(100),rpoispp(100), rpoispp(100)), U=42, V=rpoispp(100), stringsAsFactors=FALSE) G ################################################### ### code chunk number 11: replicated.Rnw:324-325 ################################################### simba ################################################### ### code chunk number 12: replicated.Rnw:338-339 ################################################### pyramidal ################################################### ### code chunk number 13: replicated.Rnw:345-346 ################################################### ws <- hyperframe(Striders=waterstriders) ################################################### ### code chunk number 14: replicated.Rnw:353-355 ################################################### H$X H$Y ################################################### ### code chunk number 15: replicated.Rnw:365-367 ################################################### H$U <- letters[1:3] H ################################################### ### code chunk number 16: replicated.Rnw:372-376 ################################################### G <- hyperframe() G$X <- waterstriders G$Y <- 1:3 G ################################################### ### code chunk number 17: replicated.Rnw:384-388 ################################################### H[,1] H[2,] H[2:3, ] H[1,1] ################################################### ### code chunk number 18: replicated.Rnw:394-397 ################################################### H[,1,drop=TRUE] H[1,1,drop=TRUE] H[1,2,drop=TRUE] ################################################### ### code chunk number 19: replicated.Rnw:410-411 (eval = FALSE) ################################################### ## plot.listof(x, ..., main, arrange = TRUE, nrows = NULL, ncols = NULL) ################################################### ### code chunk number 20: replicated.Rnw:426-427 ################################################### getOption("SweaveHooks")[["fig"]]() plot(waterstriders, pch=16, nrows=1) ################################################### ### code chunk number 21: replicated.Rnw:442-443 ################################################### getOption("SweaveHooks")[["fig"]]() plot(simba) ################################################### ### code chunk number 22: replicated.Rnw:455-457 ################################################### getOption("SweaveHooks")[["fig"]]() H <- hyperframe(X=1:3, Y=list(sin,cos,tan)) plot(H$Y) ################################################### ### code chunk number 23: replicated.Rnw:469-470 (eval = FALSE) ################################################### ## plot(h, e) ################################################### ### code chunk number 24: replicated.Rnw:479-480 ################################################### getOption("SweaveHooks")[["fig"]]() plot(demohyper, quote({ plot(Image, main=""); plot(Points, add=TRUE) })) ################################################### ### code chunk number 25: replicated.Rnw:492-494 ################################################### getOption("SweaveHooks")[["fig"]]() H <- hyperframe(Bugs=waterstriders) plot(H, quote(plot(Kest(Bugs))), marsize=1) ################################################### ### code chunk number 26: replicated.Rnw:507-509 ################################################### df <- data.frame(A=1:10, B=10:1) with(df, A-B) ################################################### ### code chunk number 27: replicated.Rnw:522-523 (eval = FALSE) ################################################### ## with(h,e) ################################################### ### code chunk number 28: replicated.Rnw:533-536 ################################################### H <- hyperframe(Bugs=waterstriders) with(H, npoints(Bugs)) with(H, distmap(Bugs)) ################################################### ### code chunk number 29: replicated.Rnw:559-560 ################################################### with(simba, npoints(Points)) ################################################### ### code chunk number 30: replicated.Rnw:567-569 ################################################### H <- hyperframe(Bugs=waterstriders) K <- with(H, Kest(Bugs)) ################################################### ### code chunk number 31: replicated.Rnw:577-578 ################################################### getOption("SweaveHooks")[["fig"]]() plot(K) ################################################### ### code chunk number 32: replicated.Rnw:583-585 ################################################### H <- hyperframe(Bugs=waterstriders) with(H, nndist(Bugs)) ################################################### ### code chunk number 33: replicated.Rnw:591-592 ################################################### with(H, min(nndist(Bugs))) ################################################### ### code chunk number 34: replicated.Rnw:604-605 ################################################### simba$Dist <- with(simba, distmap(Points)) ################################################### ### code chunk number 35: replicated.Rnw:618-622 ################################################### getOption("SweaveHooks")[["fig"]]() lambda <- rexp(6, rate=1/50) H <- hyperframe(lambda=lambda) H$Points <- with(H, rpoispp(lambda)) plot(H, quote(plot(Points, main=paste("lambda=", signif(lambda, 4))))) ################################################### ### code chunk number 36: replicated.Rnw:628-629 ################################################### H$X <- with(H, rpoispp(50)) ################################################### ### code chunk number 37: replicated.Rnw:658-659 ################################################### getOption("SweaveHooks")[["fig"]]() plot(simba, quote(plot(density(Points), main="")), nrows=2) ################################################### ### code chunk number 38: replicated.Rnw:678-680 ################################################### getOption("SweaveHooks")[["fig"]]() rhos <- with(demohyper, rhohat(Points, Image)) plot(rhos) ################################################### ### code chunk number 39: replicated.Rnw:698-699 (eval = FALSE) ################################################### ## mppm(formula, data, interaction, ...) ################################################### ### code chunk number 40: replicated.Rnw:709-710 (eval = FALSE) ################################################### ## mppm(Points ~ group, simba, Poisson()) ################################################### ### code chunk number 41: replicated.Rnw:743-744 ################################################### mppm(Points ~ 1, simba) ################################################### ### code chunk number 42: replicated.Rnw:751-752 ################################################### mppm(Points ~ group, simba) ################################################### ### code chunk number 43: replicated.Rnw:758-759 ################################################### mppm(Points ~ id, simba) ################################################### ### code chunk number 44: replicated.Rnw:769-770 ################################################### mppm(Points ~ Image, data=demohyper) ################################################### ### code chunk number 45: replicated.Rnw:788-789 (eval = FALSE) ################################################### ## mppm(Points ~ offset(log(Image)), data=demohyper) ################################################### ### code chunk number 46: replicated.Rnw:801-802 (eval = FALSE) ################################################### ## mppm(Points ~ log(Image), data=demop) ################################################### ### code chunk number 47: replicated.Rnw:819-820 (eval = FALSE) ################################################### ## mppm(formula, data, interaction, ..., iformula=NULL) ################################################### ### code chunk number 48: replicated.Rnw:870-871 ################################################### radii <- with(simba, mean(nndist(Points))) ################################################### ### code chunk number 49: replicated.Rnw:878-880 ################################################### Rad <- hyperframe(R=radii) Str <- with(Rad, Strauss(R)) ################################################### ### code chunk number 50: replicated.Rnw:885-887 ################################################### Int <- hyperframe(str=Str) mppm(Points ~ 1, simba, interaction=Int) ################################################### ### code chunk number 51: replicated.Rnw:914-917 ################################################### h <- hyperframe(Y=waterstriders) g <- hyperframe(po=Poisson(), str4 = Strauss(4), str7= Strauss(7)) mppm(Y ~ 1, data=h, interaction=g, iformula=~str4) ################################################### ### code chunk number 52: replicated.Rnw:928-929 ################################################### fit <- mppm(Points ~ 1, simba, Strauss(0.07), iformula = ~Interaction*group) ################################################### ### code chunk number 53: replicated.Rnw:947-948 ################################################### fit ################################################### ### code chunk number 54: replicated.Rnw:951-953 ################################################### co <- coef(fit) si <- function(x) { signif(x, 4) } ################################################### ### code chunk number 55: replicated.Rnw:964-965 ################################################### coef(fit) ################################################### ### code chunk number 56: replicated.Rnw:1022-1023 (eval = FALSE) ################################################### ## interaction=hyperframe(po=Poisson(), str=Strauss(0.07)) ################################################### ### code chunk number 57: replicated.Rnw:1028-1029 (eval = FALSE) ################################################### ## iformula=~ifelse(group=="control", po, str) ################################################### ### code chunk number 58: replicated.Rnw:1039-1040 (eval = FALSE) ################################################### ## iformula=~I((group=="control")*po) + I((group=="treatment") * str) ################################################### ### code chunk number 59: replicated.Rnw:1050-1055 ################################################### g <- hyperframe(po=Poisson(), str=Strauss(0.07)) fit2 <- mppm(Points ~ 1, simba, g, iformula=~I((group=="control")*po) + I((group=="treatment") * str)) fit2 ################################################### ### code chunk number 60: replicated.Rnw:1178-1180 ################################################### H <- hyperframe(P=waterstriders) mppm(P ~ 1, H, random=~1|id) ################################################### ### code chunk number 61: replicated.Rnw:1187-1188 (eval = FALSE) ################################################### ## mppm(Neurons ~ AstroIm, random=~AstroIm|WellNumber) ################################################### ### code chunk number 62: replicated.Rnw:1211-1214 ################################################### H <- hyperframe(W=waterstriders) fit <- mppm(W ~ 1, H) subfits(fit) ################################################### ### code chunk number 63: replicated.Rnw:1235-1236 (eval = FALSE) ################################################### ## subfits <- subfits.new ################################################### ### code chunk number 64: replicated.Rnw:1248-1250 ################################################### H <- hyperframe(W=waterstriders) with(H, ppm(W)) ################################################### ### code chunk number 65: replicated.Rnw:1273-1275 ################################################### fit <- mppm(P ~ x, hyperframe(P=waterstriders)) res <- residuals(fit) ################################################### ### code chunk number 66: replicated.Rnw:1285-1286 ################################################### getOption("SweaveHooks")[["fig"]]() plot(res) ################################################### ### code chunk number 67: replicated.Rnw:1291-1293 ################################################### getOption("SweaveHooks")[["fig"]]() smor <- with(hyperframe(res=res), Smooth(res, sigma=4)) plot(smor) ################################################### ### code chunk number 68: replicated.Rnw:1305-1308 ################################################### fit <- mppm(P ~ x, hyperframe(P=waterstriders)) res <- residuals(fit) totres <- sapply(res, integral.msr) ################################################### ### code chunk number 69: replicated.Rnw:1314-1321 ################################################### getOption("SweaveHooks")[["fig"]]() fit <- mppm(Points~Image, data=demohyper) resids <- residuals(fit, type="Pearson") totres <- sapply(resids, integral.msr) areas <- with(demohyper, area.owin(as.owin(Points))) df <- as.data.frame(demohyper[, "Group"]) df$resids <- totres/areas plot(resids~Group, df) ################################################### ### code chunk number 70: replicated.Rnw:1342-1345 ################################################### getOption("SweaveHooks")[["fig"]]() fit <- mppm(P ~ 1, hyperframe(P=waterstriders)) sub <- hyperframe(Model=subfits(fit)) plot(sub, quote(diagnose.ppm(Model))) ################################################### ### code chunk number 71: replicated.Rnw:1358-1366 ################################################### H <- hyperframe(P = waterstriders) fitall <- mppm(P ~ 1, H) together <- subfits(fitall) separate <- with(H, ppm(P)) Fits <- hyperframe(Together=together, Separate=separate) dr <- with(Fits, unlist(coef(Separate)) - unlist(coef(Together))) dr exp(dr) ################################################### ### code chunk number 72: replicated.Rnw:1383-1392 ################################################### H <- hyperframe(X=waterstriders) # Poisson with constant intensity for all patterns fit1 <- mppm(X~1, H) quadrat.test(fit1, nx=2) # uniform Poisson with different intensity for each pattern fit2 <- mppm(X ~ id, H) quadrat.test(fit2, nx=2) ################################################### ### code chunk number 73: replicated.Rnw:1421-1422 (eval = FALSE) ################################################### ## kstest.mppm(model, covariate) spatstat/inst/doc/updates.R0000644000176200001440000001427614155343650015447 0ustar liggesusers### R code from vignette source 'updates.Rnw' ################################################### ### code chunk number 1: updates.Rnw:22-28 ################################################### library(spatstat) x <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = c("Version", "Date")) sversion <- as.character(x[,"Version"]) sdate <- as.character(x[,"Date"]) options(useFancyQuotes=FALSE) ################################################### ### code chunk number 2: updates.Rnw:38-125 ################################################### readSizeTable <- function(fname) { if(is.null(fname) || !file.exists(fname)) return(NULL) a <- read.table(fname, header=TRUE) a$date <- as.Date(a$date) return(a) } getSizeTable <- function(packagename="spatstat", tablename="packagesizes.txt") { fname <- system.file("doc", tablename, package=packagename) readSizeTable(fname) } RemoveDevel <- function(sizetable) { ## remove entries with fractional version numbers if(is.null(sizetable)) return(NULL) ver <- sizetable$version isdevel <- sapply(ver, function(x) { length(unlist(package_version(x))) > 3 }) st <- if(all(isdevel)) NULL else sizetable[!isdevel, , drop=FALSE] return(st) } counts <- c("nhelpfiles", "nobjects", "ndatasets", "Rlines", "srclines") mergeSizeTables <- function(a, b, breakupdate, allow.devel=FALSE) { #' a is the running total for spatstat; b is a sub-package. #' breakupdate is the date when the code in b was removed from spatstat #' so that the size of 'b' must be added to 'a' for all dates >= breakupdate if(!allow.devel) b <- RemoveDevel(b) if(is.null(b)) return(a) adates <- a$date bdates <- b$date alldates <- sort(unique(c(adates,bdates))) if(missing(breakupdate)) breakupdate <- min(bdates) #' functions to determine, for any given date, #' the relevant (latest) row of the table aok <- rev(!duplicated(rev(adates))) arowfun <- approxfun(adates[aok], seq_along(adates)[aok], method="constant", f=0, rule=2, yleft=0) bok <- rev(!duplicated(rev(bdates))) browfun <- approxfun(bdates[bok], seq_along(bdates)[bok], method="constant", f=0, rule=2, yleft=0) result <- NULL for(k in seq_along(alldates)) { thedate <- alldates[k] i <- arowfun(thedate) j <- browfun(thedate) #' i > 0 because spatstat's founding date is earlier than any sub-package nextrow <- a[i, ] if(j > 0 && thedate >= breakupdate) { #' add contribution from 'b' nextrow[, counts] <- nextrow[, counts] + b[j, counts] } result <- rbind(result, nextrow) } return(result) } ## start collating size tables for the spatstat family z <- getSizeTable() ## sub-packages- access via the sub-package zgeom <- getSizeTable("spatstat.geom") zcore <- getSizeTable("spatstat.core") zlin <- getSizeTable("spatstat.linnet") zutils <- getSizeTable("spatstat.utils") zdata <- getSizeTable("spatstat.data") zsparse <- getSizeTable("spatstat.sparse") ## merge history of geom, core, linnet after the big split Bday <- "2020-12-14" z <- mergeSizeTables(z, zgeom, Bday) z <- mergeSizeTables(z, zcore, Bday) z <- mergeSizeTables(z, zlin, Bday) ## merge history of other packages after their split dates z <- mergeSizeTables(z, zutils, "2017-03-22") z <- mergeSizeTables(z, zdata, "2017-09-23") z <- mergeSizeTables(z, zsparse, "2020-11-04") ## extension packages - use copy of package size file stored in spatstat zlocal <- getSizeTable("spatstat", "spatstatlocalsize.txt") zgui <- getSizeTable("spatstat", "spatstatguisize.txt") zKnet <- getSizeTable("spatstat", "spatstatKnetsize.txt") z <- mergeSizeTables(z, zlocal) z <- mergeSizeTables(z, zgui) z <- mergeSizeTables(z, zKnet) # currentcount <- z[nrow(z), counts] bookcount <- z[z$version == "1.42-0", counts] changes <- currentcount - bookcount newobj <- changes[["nobjects"]] newdat <- changes[["ndatasets"]] + 1 # counting rule doesn't detect redwood3 newcode <- changes[["Rlines"]] + changes[["srclines"]] bookcode <- bookcount[["Rlines"]] + bookcount[["srclines"]] currentcode <- currentcount[["Rlines"]] + currentcount[["srclines"]] growth <- signif((100 * newcode)/bookcode, digits=2) ################################################### ### code chunk number 3: updates.Rnw:137-142 ################################################### options(SweaveHooks=list(fig=function() par(mar=0.2+c(2,4,2,0)))) Plot <- function(fmla, ..., dat=z) { yvals <- eval(as.expression(fmla[[2]]), envir=dat) plot(fmla, ..., data=dat, type="l", xlab="", lwd=2, ylim=c(0, max(yvals))) } ################################################### ### code chunk number 4: updates.Rnw:148-153 ################################################### getOption("SweaveHooks")[["fig"]]() Plot((Rlines + srclines)/1000 ~ date, ylab="Lines of code (x 1000)", main="Spatstat growth") lines(srclines/1000 ~ date, data=z) text(as.Date("2015-01-01"), 9.5, "C code") text(as.Date("2015-01-01"), 60, "R code") ################################################### ### code chunk number 5: updates.Rnw:170-188 ################################################### ## Tabulate latest version numbers of packages vtable <- data.frame(package="spatstat", version=sversion, date=as.Date(sdate)) AppendVersion <- function(pkg, sizetable, v, allow.devel=FALSE) { if(!allow.devel) sizetable <- RemoveDevel(sizetable) if(is.null(sizetable)) return(v) lastrow <- sizetable[nrow(sizetable), , drop=FALSE] if(is.null(lastrow)) return(v) rbind(v, data.frame(package=pkg, version=lastrow[,"version"], date=as.Date(lastrow[,"date"]))) } vtable <- AppendVersion("spatstat.geom", zgeom, vtable) vtable <- AppendVersion("spatstat.core", zcore, vtable) vtable <- AppendVersion("spatstat.linnet", zlin, vtable) vtable <- AppendVersion("spatstat.sparse", zsparse, vtable) vtable <- AppendVersion("spatstat.data", zdata, vtable) vtable <- AppendVersion("spatstat.utils", zutils, vtable) vtable <- AppendVersion("spatstat.local", zlocal, vtable) vtable <- AppendVersion("spatstat.Knet", zKnet, vtable) vtable <- AppendVersion("spatstat.gui", zgui, vtable) ################################################### ### code chunk number 6: updates.Rnw:194-195 ################################################### print(vtable[,c(3,1,2)], row.names=FALSE) spatstat/inst/doc/getstart.pdf0000644000176200001440000047635714155343653016226 0ustar liggesusers%PDF-1.5 % 1 0 obj << /Type /ObjStm /Length 3111 /Filter /FlateDecode /N 64 /First 519 >> stream xZYSܸ~BoT"Y[Sb LtLMMBHvnLcYsȒ f^(a20g,`~ERyZ(w$*y)/ˆ)% C4̋ю*じ# +5=%Z UIbn>#Ɉ2A $ Q,< ³aahh,b*`BZm/bQ`$&ϢB*P F'JƲD(P?XO_zJAxP#vz&mϡ(K!#P0 Rh@X}Pv.4|?a8b1GU2`؇ hM؛74t2ތ Ņ]&S49dt2$stv'l6^Z>nAJ~: 4]ݰ]7׆-7/ ݢY2f6Džd{ DMd^CC#qO~d6@mIt28I2G<@͛D+kICt`^ڷbWFYq!H1q{-Mdh)& ϾOtR*)RRE@hT.UU|_|UȨ Y1єOX-b1e F- L&*zS"褥F-O~"[+9I^7B7qy-#wTe=em-͏)&77.d)e fwQ3  UWpZ4Dhv0Q5_泚 4bj^b\b!6Θ*h)`!Jv;+ӵ mA yڶ)xzܠ96#Cϡph}q4aC1l1|+ TҳtcbN*Ӗ)EM#4ti( UVXQ if=~@>OPxp%<*v1$(̊Fhh2.頝On'Q|_oPRz-F*{;Q=!_юlKn|_&Yb[mɵϒo >K#TF =mZ&]WZVBd\Uu@D>m8'zZ bL/ JSIxoS\ocVtuٟJvJJR>vhOw M[bVËQM4Wu8yk55&^XT{yj/l>Z'',M%ǒN//T*qiX>b^Muטʢحϻg^o kߴpvϺWOJEM';0 J>ۀ7_6DaZ_~F$哗o8XP_A= j0.P`('5ok7µ` 6 hUljK޸iJ޻m҆ӽސВ\Δr2P ܰN"PWMg7 z7Ej16Xw}meve]Ѡ_upɹu!Zڸ0MȰdz-]"@ GPT LoX7?W eLe=Xk(xFLS78߷Qގ~:PN^XUNGuNP龆aU}Q等hz>Waݕye(kԌ ;vu^yeYOTEYPtMcJXY^+.d1OB6%WSWIWC2;d6{rΪ}`JN.v&Ǿ`_p/]͢[|#,ӿN,ʅp kc&eߧO{[7ϕ31}wݤς7RRʀU^^&`4q/75˔sLcQXtSS ?=:L%HA6*@ҧ_‹oܷ[gd?Z,endstream endobj 66 0 obj << /Subtype /XML /Type /Metadata /Length 1167 >> stream 2021-12-12T17:58:02+08:00 2021-12-12T17:58:02+08:00 TeX Untitled endstream endobj 67 0 obj << /Filter /FlateDecode /Length 7323 >> stream x<ێdm@+TR 퇚޵gwm߇wQI`EHJ~Nvx. <<~b(v#*|l8H~;R;mض[I;ßaǧ7iN|Ep0`*b:g1zwضJ[lW7`cJl|cY\O#EX+ h CKL[l>]04JM(z;FBb)~ȅѶZHm 攙vݶ+.r|?ɹ-43n9QjKz?~X |r)tO&8/ha)W"r|{ŸCW`S̶*n+6nc="On!<'4`.F>Kl_K%יw|2. I~b H}uP y]I4eegRM+oyJ)D,%\2SmݴSܓ7>otP"A(<mX)`){m"k.&`?83PXKR1xQ'4ų.vW??柯W 5eZp"l`Vkx~@5`1qKMO(k@22 fRcSQS4/]oփvY}k{9ȿHrLhx|,2b~S-Ys@Ǵ|ҥ, {L[[ ,IhB`>u S .-[(Idr^ү#Nd+4?oG+R8ug7%[8kl XbkIG`|VPp)x%SŻGDO.< h\0k2jXQLy FZφgG -zJs+8"V-fz]317m3w3y*tg6Pf(Pߥ0CJ=};}N3IrQS)i`zӜ=w~$rYv*`b&!`˽ md Í%6vBdˇo(0e`{;aJ;џ׫+ Ksb65nu=\-JU-?l+]+~ejPx|G=6_9n>sA/;3A?: /q%QBRm]Cᔡ|0P K)@R3s% l 6~#l1H+m+N?0XoՂ~oH2#\v$TX́'&&N}Jĩi((@Z a8nY`~`xvZ asMV2璇*]ѻ-Ie".QkJVw)MR[W8)@G8.JQ@`:і{#dzLHY]}N@>RHdvܹha^!ߜvZvYQE+wr|a)L} м}C*Y>\zOp0艎,k E̮1cE_,j7}8q~|\Ү4G+px)??stjgo,n!u /g#Lo*>Q|)_^'션vƆkՆDIr 1Tph@[|wJ:Yca 0TTPBKIs6*ߘg>nlt!:ՀH[}m#lm=*Ϧ- e؜ pdȾ?SIZ=c]ꏌEˏ3 ?ct/Nwj.9)ՙ(&Ӈ Su@˖C\ pֻʼnHe K>P[h(FϷmKQUᛖ~yL!Ry'^1=?/zIV|w$׬zrB0ws#kI'HM&xΒB/oz[R%'9d*2Ms_XӰ[7^i_V]򔜮ml*Zool lXewCl5 ; X!b mu@zx<:nBx@b-^B/|8s_ g؉'b\'9~~POqC#U#oBmp*"8_ V(1ڽWpm^/Iwe/3NJ5-Er%,Bx)4'@L9!;p9E.z~S3 +rlWr~QbRưx_+}q_wねTO-ۿ~wP׻pOwWwN{!`; ?-=H L3^wpxv(r?>B1fn8``a`FHuP(y KF!py1) C4 w`["MH,P 8n$yܐo>:maI; :.wB~2I>ydmJ*RX ɝFsv^X%eg78dGGAǺU7 bav3) C4 nxj+dՕjhW'_; C$7 :fN n*%8ԧ*{*?LzQ RyTcc4<7ߖE-Ȕ&U W(dxdͤP R)zP>1Gnu;gi))|0xc9C: `l<`A c#QW WIYzx U@^%șJδJAS%dF6T8U` γ4S0'|D8x41XIAcǪR&O&J6yn\ug.3\R*>D沱 *R \ʟ~;sKsi4!TX X`)e x\)̱d06⤏Wo*[_ ՝BmPP;BeQ(dPȋBVVag+~Gϓ!Qx'K,dLg3.cw1 O;WuN?i;u^SG xUݒ.^;} CTN~VHl1Q!*Z(2!dLIEI ΋"R = *y^TäYUc{TQHc\9F)y l,1ʆ$8z*aJOQ'E3~OG߈Ya9F~5w$( ut[xB8 O d@aT8t%|MvB" $`LTBx>2 yel6]l,Pc/kbJaՃtKR,u+uC3wJ/c63 " nƀ-J'-Rf[BnPeDh.|h!*F1l˺3eDl`"*U R KմXͫbbe)f"(FX-SVz@#¨7H I3NG˸cST#C@Ƃ8CP Q)Z^fB;*:5V'je< B,jM CT {9LQ-7 oJIjbԤc1">*6)񼹚*RX@~}Qs+T]c"_iP¯iD]1; jSO#'d=b-2gkkǚ lU*ܘ$^e[FgԨJn#uu p6ܫuqW?̏ 5a>Z0dl'w'} 6m!:2ogU+~oJ_^@8~>=}s60__tc/}.qN87M$ڇېm'$&~`#ugʱz[_usjSp_{/*\5ؽRXsPGvqO(af/TP/]eETGߐ« Du{b~щ;T.gyLydQɑoU$S ]w=X]#Ϩh߉DϹnxI{"]K0= RjM_N5p痢H󩾥U7).ܧ?udrԲKq\x7w_zDbju&=ViȐݻ덱\۵aSv)[,Ŝ=3:l5Yp~F13FN,s_eZK{q}l؅"9>f޽YVK7t;\tIt VkL-Q8l>#l#"(cqUK k裇r+8<2=t, -}:c(#rjz]I<521 5KPkL:y;ƀCuŧ}T`wXzFQFܖ9-;mi}e t~lg%rN2}EO {%wzi x+c0oxpU`0-9:Iݬlmw&szoGXklK _SRowݴW#uq=\8# +fhޛ߸~d["%+QNNnw<ڟ^ ܴ؛w+s]K鎅nSXWV`'L*;j7vDÛm1M1ܿ7&eFendstream endobj 68 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 1615 >> stream xTmL[ۄu[zjڐ& ISR YԂm\7Ɓe}}lll d#,*s!AQS 5U,딭Q}/{KYk:J>9! i A,pkYIRX"<%\{`*I M:b~yF%? $$Ymi5f]֪ToPlޤxa˖+zYVV+ VF*EAXZո=+noV- 抝6):VQh5rEڪ8kkmVYQ`(ט H6[YrMVG"$oD*OX%$;ėdS = V+9[: RZΤHp`x".^&. 4'l<ޓ.qZݮʱ'[Ԝ>~Ԑp;" TJˑnv0n:vz(۫1Ė rI$h)G +PCƭn1GQ)sQDTVb“W 3\Gd 42T{ꄫq};ӥl)u,ҿu -9=5z5JG@'G!ulP/'AG/N$e OĒE(:%Av o-8?笯 )*SZ:?Owv^V t=.~bԀ"s=Qr:jQ(.Ge?~Ə N|< \kt1}ź '`~A{{Ag&LbRqY/zsN/2̑tlʸIЫs'Ɓ9׏#g.p<-.:["=p>^֚ ~"\)f_K*ͬ^ *hSX3VzJ Gܻ%HRM}LiU ԌyD_^ m.m,!_=CaQ } `sq^z.&?xDSvd juXmځD_l̄?!K0!+Ȩ BQ.ɕ ÐH4"gendstream endobj 69 0 obj << /Filter /FlateDecode /Length 214 >> stream x]A E4l Q/0uk'3Ӎ~Jqݩfw|G~VTG|Ͷn> stream xE[PWw mf͎(TDnX*xLr1$QGM{2~ݯm 0ZkKǧkc!0<βu;R(Վeܗy(yJѝSЕr\iPŨ1EQ2 Mw ǽ{{p<^ b@zovǀ[:nn57g @< 2>=-;GGfS7 v C?tS^2иI ]!pvy˙c){VbQv|r:>C,r5-+?bFLL  sԃC.4au;BN-Zlq:fW<[렖 گ&&vl2l|\h+rܗ W"cendstream endobj 71 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 2693 >> stream xVyTSW1T8hmQnZ]lUAM(HB PE`R[=-ZXӪ]}s8ۙ䝼sw~]0D5f7IxF$&<+,K1$CF'1qJ,)Rr"*&1>AЙϛ:kƌK2Mn"tT K%9trwL }aaVZ0}zzz4ZjѸ{Xmd3mY`͠z,iO;tbS7q$X0%BeXx X-E0d/3?I@}V1ٰ$&)|pVe1Eҿ\9{BHgϵ[@ML! ׇnw_c.87Dp !H_ݻYu\17Osx)EV(FK~hbX̿fwȇz-Z$0%jCM}baJbfpx4~)HFpa Zѣ:V.v8|hu+t]Cls48H5m2 `}pzѨM)W$CyʒT*<%ChJм Od<5J R$C?$4iCogw޹jBA!kڗ*Fͮv*T;_RL X_zh=M?P:n.kc^B#>7gQZdV=syoK gHzJ}B&oc%O O\KcHwL r3RssuE{WlȆEyh3ůTP2;5fC*grb.4A>0`xcbqpbVUo? 5kZrJfUъryQx%4FiVΒ[ )L#3~)'Nq/4?ud@|SR+$k L>zYnq:X0g|" Sl ! 2!JHVG69dChzj,o5M$C!gT&࿇Vc9C8&.Y{.яѮ}O!Kq玎_R{kkjj!9nG61 9ΓNp{s|70s_gSRr28Uŭa“vnvEmVn.I}D,.7{eAƼoخ&(`-m;,aAϧ'NQкOn(x'dDBm ZB!K\ &sŨ.سel}+jVP 9vcE2 c 9o}:q47.tg#| 7ޫ*s9C~8]%^d:C"K1tnPY A}tgUY`>]%3Ƶ ÉSyu{M-2uÆ*rXQP.,4 ISl_Q-ӉЂ l}WNMSk3js8RI}?~_Ѓ t!z?޿/r5DJ,b `7-Ye}t"øx3 OA!^Pg-.[}AI|%58*I J*1:,X.ۯwt䠆͠2Ǥ 8<G(&9 \~/lЏidinBR.ff`NjK3_2`FI"\b^HUdUԦb[w f7R͛ `b6SDsin! )Kn ѾGr#湂J.W;> stream x]=n@D{7В؀ӸH$E- Y.ř)Z=//6_~vuá8 r\nu}>{6iZ~~׾{*=k߫|8=4e=uM)`xÔ>NcSJ))#CSVgIߌ')Gκ6OL) DUTTuj *#> stream xygXT9'TrK5{6zGz0Y3Cu`(H{5nbb4}ps `ͽ~skw}1zLLLKm>X~ ??B5od Oz>9|&&! K#wyzZw`5}޼9fL6j{.WguΡ^~Ρ_C# x԰)~!S=?0*lW&nVC;[77sI_$=j]{?EQ֋/ر$piв!+BWJV^&emH<7zmڵ{VmcǍ`oS:M=c9wE})jeMͣFS1Fj5LP)jHm&Q۩djI-P2j*FS+*j&EfSkuj=5)zCͧԧ5H-Q攂Q)zBYP(Kj(5ʤbLPHޔd^^|{W﫦[L ?Ѷߙ%VWG'Ծ_K꿬ef8>pA3 zank~N2vH|C[3͇ ?;шߌxs\xX"ViUffdOFqt,sf̯f G;RڎE~TZ69OQ %`-"F(_\_zhW*w*5lZ| 1E TYi7"\\5tR+PW(XX`(4əj ڢ*FO{;:pW }JJZsqrLX$)SN@ܸ{{UdC&5#BhNThR@n qH'Cm5I[&:;m1Nj|IH|~^,Ru6 >h뚝s@8}Vr"||?.~[!z;+h+OS.ė.Dy7 Wf "N*)+n7Fl˥:~֤sO o ǃ&b<MBDv8 >xŁCmepK**`#I'H%;y[1t6;Z $ We FuX0,6E&p^>O5YRrzړ ^l,T1}2Ah 4ޚZwBOMbdCuxHO}uCDOOY>z4g$FL6dJAhyx^tT,m{!RN|` AS&FtdHSR .۱ȣaI`)zl<;tz4Y[__A~%1ZQ,0{UJwk>EE| ψEbѳ&a4E!t5G~n&6Y^()v{ ;tzK#G&< M x߭X#}]@}.<W$Gߐ5[{ ܴq,_D]X{~9$4SѳX ̨}鵳zT v$F'@o=q~-lE9`<%t1 l6g9>u8X8[;] чP0IL;t?<__z`&}Ǣ^4m4?Iզfhf#rwӋ9 b44o2ԠTsreX1eb]nmo''[LFɹdc=wt!<8\dH$NO5XRGyʍ\#mOi[o>As\'z ZLٹ;2w4D5y65(frU~ťu*qUVr!Em/lW6pd>~|#\C%mLˎ'/ӥȉ{h^:i?@ȏh%Zyf x&գYC!%nr WXs0 7z-Ni؝w0 Ko˫ű{;\Qoh)h3"H "EުE"3xdٺ ~M0tK((*5ޡ\` *UP)۬Ň ]֫*Z]:@IʃԝqҼ(@ޣ:Ф@:1 h-h[Dlgne$Χ:Z̯jcDC Zw|=GRM 3/'" YBC r NȬT^.ࡰwmYHT1%\Zs]\a 6X( w]:C:S><ҍ(PiXhU}?m兣BxF`tG,$f+^HX)يT҅Pu(]6Ě&vX$xb%[db‹Z(d* C$~G.:U{Ҩ3(mObtSgќDz.(=9bҢ=6}Mȉ^'pZegǃ0LOY:s?-6{3;$&hds ^V@cy=r UdFjo&Fe*3a2)t ?XkҪCIY9c!ׅR1C#왘FPwh~ v13 qK78U1jfȀppAe3MF:H "?Eal2(Z9dxj&*UdO}kP,PUJg:KEtZJ*'w>ȊS)3ɇ1^ʝ oj.P@qB s~eh֜لKFFil:p_x'fQP_lcsC_M$ d'D5f:p9\ucN Q/ $b!WC< Y7OCj4 DNC@(|{4z)xĜb3tHhL }_"h K`&0ѣn벏0=6W.]0+,Z Du#; 1Z䨈E]&̈́;4Lv)GN/GPn^v-Qxzw) Fyy@'-n{'ƅ 1n,ByQiS@Wlj .7mH+6F)MIBW]Q^W(sq5`,_][ ^B7 YR:H!;Oq8T1aANqc":  !ڃd}^ZhҠCQN1cۉXBk>]P&A1e,L삘QEbĄ+= :X~qjt i4(dz]$xQhV6+h7GnȔpr]ꌺeMu cXVX(D0^;yh @:uL+QfK!b=,!]JCoPQ,5vmA&x$b0y=E"NS Y̠t4 bObxAll$Kc5.&Z:2a:F)a+0U5U']YDt^\5-f^-7ZS3/'قS0Yw"#dX`Mٛͥ&8%D,ƒC@hg8Y0)YXێ{aЂ6=1̈#?="2x ,E  }4ćr. YD1ޕ%{li]4ݎM8,K!c%H%몤SlN6U1k;ډe2csoF4N>|H`g<I*d͞ Kkh1' ];;ش<0,iLJ|X2Ҭla'K%) %vWϰ+K(HxHt$g5\Na;:̈B`Doqq'3vӱ32ሜ+UTDcg_zE#OH$6nU~q3#d!Nd41VvihWpj:\<,R,}?'p=̖A} v-DPܪ}s[gmOD;e7MN~|"lq"fK)a؅cMaօ܌[G*F&x7$ol( '4'2?8pw^)K^"w3 , :mUѪ\MiH^4%Bj5눙yCGX xAV.,*{M33ΙETzEm7{{k/~ֵ'1B~p'@XǎiȬ)҇HVwȌeRG[vF88q.0D ){!˫'>nWCOZg83&tOo1]3JMꯠW ]'bNOWwTR|Ieԧ<1,Qߟ?|^-ƻs֣5Vɪ{ڏ5GG1lz17XF+#E>m0A.hя́\88"Z*p(t]*MK\{Ɠ֓i~vOn螒7nN f2faJ8ڑ_Z)nA)HETU Ğ%@iL!t>Wr}z)6_+SP endstream endobj 74 0 obj << /Filter /FlateDecode /Length 443 >> stream x]An0D>n`ǀMɢADZDggftxEO|k?ޚi^ƭ_?6:/ñE^~럿kmNw~ש:/uwnr߫/.8m˕ C|C< X(!Vbb'm!\#FJ!&!%JjrqY!C I :R⅘(UVF٭ZenޜY, GAGGAGr $ ( B, aH!A!B;C&և`N 4AL!:hhA`H0( ‚!M(d 6aQ&lUϫ[Z4ǶˢK2/}[j'pendstream endobj 75 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 4361 >> stream xX XS׶>!prD!:wu8UUqV C@AFa3 c a"VkTũ;a ~ޛ/v{_7<ԄxS ӿӏ6? +7nfȒ,MF/l5C >'H^ UHE2 m:9}bg;Y' >2nlJ'SN#BgO"}܉vv_4obIv϶t= $COB}$T.[)qڪ_2`U`Pxčv';L6}Y8~A,' VOb51XK#\;b=@,$ω%+1p#fRƒXF "̉9`b.aE ! BH #h=b81IQ10%vOedR͏16U3k&G Lp2b )Ֆ-Ӄneeo`m퐥Cuzz6clvۼT_eBZzjmt. &T˸1R,E%1mt54JQ H7:S"Y`6A:ü)ɗa (;E s:LslM'`k,|j&`WaI;{zʕk/9{wf%T Smoy\wa6ΟtˌI}&zxLIlB𺞂L{F/Ep+O/{'ේ/`rh0Y ),+ f25Rթ;sW,d Sv0؄TJ8wqlJR&aHb>u-kÅ/вy47$btmj|C8,ɌΊnDT3RX Ոbo7BT?uXV-5otش莔IH+ CEُ1HPXR̴IppMk+|}M3?M,΁*$45}wq fDF3+w5a{Ԃ@"VfFj׻Oc{7y+58K ‘|j?4| ]À-!1;rX\[}e,rcK5- *TedF/ډ4j%W0u6R \|"@2M텒uZ`lNZ^g;lPN'a2qTV Jjt8KP?'FO`lؾzPE;N fɒZCc{iVۋRC$OCL3_04( t!f>2#j-+4H;GQd^am>8{BFzJFi{# )dje:G}14!~(]' OWfQTHCa>{}^E9LN~;hMJّ.OfR69#jւNh@D6ST[juy1 _GOǖ`>+gm7$b27Ȳ.aϼy?¶e[ǼIvXpuz L Vy9]ZW\ܶʳ7awV՜́U -&Cq@È֟k q*vF%V'J|4dOTEƅWi!-`R]>j@Z;ߠ&p[jO(ӹg0k%S,V8"8;{6_?e0 ί>\{BzOsG5+ײSEtv~Y߸ِXa93B$BT=Q6dlfcD5yY[KX!&b#ģDZ>G ` {c:&.ߧj*I(%e)Q /I(P,U |?ъ¦&[SVn L[6n2}_?UX7%/,` &hk!᚝G\˻N>> ^+$x_Tj!y9g}.$D!qePXQ+`ҷGK3PA&^-g]εX̝ tG=v|1xp&?—tSMDD!TEh4UU}(wŰxњhvs$r|AN*Uy%MA62gU;/n=Y%|9§دy=s* Xb8^E'ܘ(i9u,6.U+Iٵ3ilfpߞ+ElP4?}eJ!mq%+Z;5C*:J%E(uh0.tm׆AhT mtbgT`ar#Уq&L.`$d8J͈sW׷ݯ_W\\ .ߡA?!dU=+ $kU58ϕ}p'.Ԃ|.zYYR"0?r3N}kuJ {^TʽR ֨(<{1x<޳` Nlkhw#9Dmmrmz^F^zPF^^u'q癮+tKoq1/ P(Ʌ . ,TBbdJp @Q EmFS{tuA)]> stream xcd`ab`dddw 641U~H3a!O/nn7 }=\19(3=DA#YS\GR17(391O7$#57QOL-Tа())///K-/JQ(,PJ-N-*KMQp+QKMUMB9)槤1000103012)ٽgf|;?̿ܥ;~3>,}} |g|Waq6;7<_s/wt\7Xp9yendstream endobj 77 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 2628 >> stream xV PSW1p">Dm+mUDkmֵTlUWH OQy? "oE<ju:kVUuwz.=tvO⣳}윙L2#܆P2|oۋҳ2i99? <'xԍFPf$%tl}|ZbZcTD{9S3gxCPJ)#6H~lQUӔ>oj)))#D[/MU5U**1Y ZUtק^dT%*ѪDEQ:}n{)iQѪfUl ާVSKej6zZDPwYjH-^Oȗ˲WdC< R%t>~~1:v4)C?~؟ L Jr6D˥TtbE4S{(s |. 9h9cmv8m>(, W{gPa9jm8cztLy Vr)94qm<s3 ;su:R8r1<g"-mv0tC4t3FYY1F5҂Gh#:`]@7yAH :69TPCûI-'@ m18L_%yfYexYnHPOߥ/Q?+q ;qm99gw@ ?I  Ϩ2&+mV(䋋v軠X4+4mۭܢE سY(^l-ւ*`렸V)@#PTɮ!(G뤉.PZ<>`/hx fjtapa?9P"jQ(# $1֘ ,?>BrovoN#ނn4Ԏqf? sOk/]&|ȣ ^K3S>k8 xb-.2Ю(ЉD7 1!04"ɚjWoކNn?n9SP-e0n^X1utn5Xg*j 2,_T~ZBYZZV^f_- s0zew^Xi66Xu3hఝEYu]E+^Cy/x]%Dy MsNP49ч݅xf<ɞz9i`᫋J=Xf&<.&߉rS'Úo.ꪲEh!j'Kt64y7XyO:~Q1ri4;I$$BlnD3APV ߜZS"k4}pbNaɎdo}:'l)T쬩VPץF}qXI"^2CB: \vNV0OM5{Vb{ȱ Mȭl6(v)IKԤ =p=h2i/Hche-kx20{dX̔yO;wlUD2h/j'{Qool:r{EGK}'4#《t7 4OޕK/#WoFC/fD/}6P] m Q7@N+Z,' sػ' C;d!"-G%n>?h藖"mS5Wwviz}4~ф7:.;S@Gr9K&a-)Xv:N|D=LQ^RVH0!Mܗаo]m=2CmUQ Aj4*Db 26*vC[h%4O8wt ׯڝy)3G`I9{'$j /z;LGIM;iѴqc2d7^}>|+~d]~H1Ǿԩ lIs<{NY-xZAVAQ)%QO2ڼB!;&#lcM-njFga;?GDrh.(V;nh.G/dN?&1k)(M!{}4c-2FTeO좲 הgXǺK_~"ZDLG&y1i826Yk\:Ĥ9B\un=Bi` 4uFi>'HD". XIx>Ƽ8u_ʜZ4ʪ+N3l s,b@+ēy)R_qIHhW^ao-ή=Pn-E7y$IpƶY5@-)4R$W>$6./\;X Xa_ʥBoonlI-]=^5Ɋ3f6I:Yǟ\Dv{7i"u D՜ fv#׫wSF7&8M5=bELc.Ȕ'~EH_}3L *Eaջhƈ ?mNZ=[<<)0endstream endobj 78 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 4289 >> stream xX teN ?ZF_AP@QGuYR"v/mhfiMI%I-mi,Rp\Aq\n/9~i 9|}yc2&Ob0)nXD\fI`?JIa0'?8{  )(TKxQ SE-[QO>U9yd~TtrAfzNr~'HF-|!@Nj&/eab^AfԖWM9Qwti GXX-HK3yᚵy n(NN)MNK߳9#s /nkVvΒKfF,w8VB6"vƣkKk011360bld<=5F4c#10.c2njcOJt;y/NQL#L枆iaӮOwN{ 'ofPD9:khge@{{Yh+ $t2}l6c3Cǧ?lrACr=g6VGq?*a;a$JN0=g}Э -6;%YK%:( ȦYZ |%>&A#,TVsL>s}m[u{qȐPHOR֌_vE&ЖIP("lm

    4q<Ii'mǛ3r}?Z7'ϊ[w&_Gǯőg5i:WYaRYܢV.ʸE liKYSI"&Es,fWROIyws%jc:w4-YBzUJv'7F`ƒj~fp',B$øA βQ,CG]V%$ F 4d,Mfnce{"*tr>Z4fPWEFжuJA-M,YSRvnf)gP+S:2tTU dZklVBp2eP*g:P)Ή2qL|z`̋._uc,BS0A+xę2M_FW2 El0~oDvj^,y -=x xs;s"D9**`%|~~a鄈ցZ "yvZXU 0qe",]iSaϰktNߙzN R9Yz-@5VjBQy.gEak: !EbL N)Gnat ,RN,RzXߝv~~~"Kh((8*0TUSPSjao=b,Un*8`~8/Qhȡ8,=C% .Ue#h: @/p] Ys»S?&-&]#~rA<+9C0#i{OpG0Hy¬ sYXS敥JyxQq:^0}vBa;ףE (zidNacWOѾ(jpY JGF,ɪɚK{g}ygE ~44rx?#M;:V4^eMy /Й2 !lJ\SiȅrNG F:rT@:AT(z$4yEY`i>AwF;} BCrKa:W-PGK>y9H]kW=n|^KC1QXWQw0!eQ= IaB(tS/MFW(rdGT@Qn7U7Eyyř zG{q<6γBez"o.L%)q7u[OWNZ\(=L/9$\&_>,ׅs"@=+W xݩPcuzpUfR{J[דXJ[59_MF~&&ͥ'SCYp$.jNQE۴;#TөC8)=+)ouK/L6]˕뽮Zrwٖ։i:<_wd9ٸ9>A:gJsV`v`ci,@\+,QnF pzZF1bG?w/]gt]!s8\D5a>pRZQj1F_oihN%Րeq9Y@hZ:f`:^8y`gq?@9Q%1\%XtPK6ܵz=Kx"alr|b e|E d?t5֘rNhgUTl yy BV&z}%_Ly"dU:6 qi英G3ߔCBʬ)cO[52'^|ɕ+o0$ 9G%(wZNҤ6[t8;쮞mOYB6Enm*]WVBR'Dƒ=̠8c9V@| BIfJ+-P) :#َpdB9fg,L_% ƪ*0IA7Az.v m%78vUfVV}uͥ] ۓSy "QffV 󫳿r;3TC9w{&Y­U)A!yekK=eÃCO6?=0;!.r6Үb'p+X9]{yoNPŜa~,&c\هY=ozRU:B^6 7f CLyN7(<' ͭ+kw#9 "]PSᅾj7tci=LM`[/endstream endobj 79 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 368 >> stream xcd`ab`dddw 441U~H3a!G=k7s7O ~.Ș__PYQ`hii`d``ZXX('gT*hdX뗗%i(gd(((%*@ܦs JKR|SRV001249wʂ(g!};{%Zz;5:;[$6M;}h L5mbSvwLm0rw&Κ1abOo$iS_[zfr\,bi> stream x%RoLufΤ̲dl_ܢ.ψA h\+)׾kKBGO c aa32 웛}%Y~n,Û}☶ q|hNyX9+/U)/k@5=޻F54?>Cϡ cg&踽T.F;-΋7@|6*Jrծ;[[YsE#5tIoKn/˸fKL !Sd$MxdŘI!?r,G{|F{6aendstream endobj 81 0 obj << /Filter /FlateDecode /Length 42254 >> stream xlɮ-Ms6Oqʮۀfx`ye%[;c5Y‡ؑTMD:#ӿ??*~oki9q9uOί2Ɵz_/ǟ/s8I\wx'Koq&K_7m$s{~QgןKmTSQAs]uҦ8:v_fz,k95S}nҦhwӛ/_&mg{9x^Ɓy2RH_]O]XK~{ݏR[\VޥyӎNOHȘg^~ _h~_?G/c??!tb7oȿǸR)o~fwۣxAy~g GQ==Zi(oX+<{2_ӈoR.[~tk79|~#.a̫/M$x1)7nX`a=u>^ϒ l)S%L{0bqnKxߎgg(aG e^i#9(SOP{/ x+0AM0CZ>矍2y1=lT|~稕Skx^m+ވP~pC,H.ЭR0F-SF?[xG .NC:ï-4|sIHLpMvc)uY~Ql=y|KC稼ǙXx,E-LU=!X*Y &t~;@tx}3avOΞsTy뎅C|!N =`L h!ʼ%%̞'AF# j\Đn};蔎+qRWoH^xJ֏2/-`~1G$S,eq$@u1lDrH x{̩́D (1=_5>yœsE"/L”9nq-R - "WI;|g'°rv1>& 1T/PZK W:qh F l~'̘}?p\ѧ$6UT+Ebc^>t.aj' wx9g9WzxKCk'9p!)%zMA:r氕Kw=taIR5q ,9 ōksџM1uD1[ͼǦ:dErnKxAjoIy1Izy}=g9Cek8K讀O[ݤC's7},gR)sԁLo=O}㘯r -)1^R2^~<lna >/|[[o>c/COJ0_M| o~svlϢGۘ1)1C]°3% 0!)Qq) L4Aa- xvŊ4`(U8O,z  9( `7=ZIᒔ'͕n cbQN?%;.J'4c*$$İZ AkJ'8l$|t!Nk9K @Sn}2|& 4. Jgjt?e>9D|VJۉa~?PT L]^j-l9DIp"+L?04s[~uVb`_`q(I T-LiOtsKMq搑r~;vg_\_zL$$h!OJNsV$?x _G%eqp gk059b l#Zr=n}ԲT릅!#-<73ܢgK]­ ^xE_c ~`,a)s9\"9l%]{br>=w5e~<_yEЮ9f{k/H$%~kMA!-0 t>8 FܔP 0,ԁǦԣ$$h`)]Mp8&#̑FJ [a(79{bxMr8FbKs>6OLRFR B#-xKLlQ|ϻ|0wyꇬk$ZI^ݤqӕE9Sb6iy'^x}|vӛ#ZR >ߖk%RAAj1jtg|Xa"[DžҴ7Zm(%$haFǣj fF:,+VJ‡9[R:Sʉ?F CZi÷ W->|&a hBr>Kx{@f7k-)Ǹ%>{pd>>G|?baL_XG{! C_sP )a>xxCWZaR>а(sytNoo,N;ҎM1n잧cC%a~c:GZ) ~p1~-)s@TĚSCrW6yLAy|p?IF;%f7D̛ !aqtXT`1Ay[J +C++ZNh\g ~ ]b9,cNzK Ѣ& 4%Vv%RK㩖8|3|nD]11Y2G9;yjć#óBniB(J >cAƨV$bH%vD\m1yX,]Vv*fö 0>rmp05u`-ւ?E*`Y ۺ ^ؤP +1\{+*:7JHLpMF, *cA09[,lOEn85l ԁEQT-.oXZ!R>VY3b~6ʅ9+q1!@XKccnJ 0 4ST \I K:i9lCwq>3EŢՉ}$ǔs<[sc0Eٙ=[}kDh*sZ/nງ(噏9߱1S0\fRR MV9 Q72L?L;E2a<(?2cttVVJ‡m^x6FO˸C1:!"#,CjеmI7`'˜҄䰉vŦ|ׁ1Fd叩|,_<K xϸ™GI +aI@,RAAD7pB3&xLy_܈hŶMCo#9b >>C`,X#x$R=o6W ?̧KE+aI+&__ Sc/bTk l9F CV?6$m/Ӭ'lcBQ'šukqĦ]lH@Bj@/'J8|e{a8F&R W#и&̦AnܿHlC%$ ג8t sH x9ACbƒGHgZsĎ^k- 14hfoʼR!֌&Z{CSȇ\2j؃mr̾6 kQAKZ:1a-g AvGgQb^+ ۅ Ľe6 kQKQM+!u[V$pAQ*Ǚ!WR dcIȱI_IXW :+zFIB!c,[i ~h\0D:x9_xݯ%~=7Y @ V#vV5ۢ|By1ݚ؟WL"lJ2=jhQ3@|Mbd ^0}nA9DIxCq0~Qfݍ)f03.ȶ:0%ve/ 7 q}U;hyJ ʈqƈ9#76pM'4ViM21>Tm[/s/fJ?V2k-F{os):4oH ƻh s)~6J%_ DžJKoZQo ha#a#-$Z cQ#r7sdkQH{CjA!i& q,?Q<"B)Y*ClH٘^0dpéE] ϻ!(c1Go9>EXEXZvXe9l%-lU㎙p6\SZ"ҰBaiDTH~:s_ĦR@ l9f x'12FJNNLG I.D"a(}\dK1UD S, ZbU 2^NЯ@_9THʉ=]XNQ5yDܭ3G$"0ISbAQƔTfަiaI^ab-Q-J̢븹HYV/e{УR ~(yngW^J*DA $!%L0OBڍCiZg@W <$bT  d9l=z:jJy0S0zT9q\{e7K:V2Z g/>R41o)G' 3m1ք"FɁ0U"}i“!8uqb{e']-6ϗb H%k~(8l02gF~% %Ù~J0(f޼$ětJ+VZsc7|l,B;[aub!9& F|b@DVłvo6<}27&ϊa &rJRTDXN=RG%!1u XQJh9sZ~oةǮڹ-{B܀#)V- 141YAbeh_4!db xg PQßmG1qhͪ11‰ ($1xMbt`T 0xx#Jp+ݤr8i9`Zoӗ5 {i&b3 !.H;$ m?$xƔ LA}lߢ$ܓW`)r>S*k)5FAN3F$- kސ PkCB_n`wr) V P>|țklr󅌥mc_GO#W7Y$1b/`4ZN1E|BAq||5}Ϊ8Ɂb4K 51Jv5ñSCqDKx;bLDgoaʉm:xo'sNqRb]bբoDԡ9#;do9큔`Lh!J! @氕d J-sI#)1|"5!$祰ob)!1u)ۦ9S:!2%Ј") /a釜a?`5̓su:%vQ*:K{[aZ*߉bb !GƋaGhٟGPUSJOI0`ELr5}ݱaԚjmÌh,nI vФ}3A"ac CGT/cI0haʸYV⭸ B FmQ,W(jb5A 5r(ٴ&:(1z%Ĭ## sJK qgQƁ5bꦲqzmk ,”Ṑ̜!-hj BΞ?x+ȴ/=N7L (ӷ։kBc?-*gН L7Ƹ )7URq#n`{ǟoUsĔk JTCr~"M! OۧoN) K>Ua9.%$,21cÊH+%*TBC "VKgQXEҦVc S@b@ QXNkI*UT2l0m\56ܵ0FsTwzk$] N# c`\=MJ,űa Ӗh!+VZ7tRlTTA/BZߙ3W !+ OTa-h⠍K l:bQF )jB܂ɠE`CEOpGW**`-Py4eR73T[y& 1v s*v%Sv;,iucR|}kr.UOJņ|zU_4Tܫ*9Ր QS^NPbE8c}6{=8g[wCF82a9] -G1^KBj?_arzMX6Q>ȭk;20$h4nI /[b,tJ0g%%DYh!+ygST(IL{X#՟gxq3Jytqt a$ʅ*)!qC8Z sݒ]OQFI8Q~>,2ԇ#97H/̰N ݲ0Aot܋&x{A>?R".^'Ἐ1duc8"Z;;nσ eӧY1;)jW1 )<5-(E X;9n$KG0"%yMh!+DYvS§$64 }Ɖ]5r֏†`h= s1n) a׽4ñ,) tGYxMu}A5YT|Z諘ǚQa% 1UD Q"0v-!Dzu.Èd;ˍ.JDPg~zm8/U/cHbK 1CV$HXezLvjaȟ>1lg<K~%ί%!ۦ7ZVVZ7lXD#7KX/>ĸ 7N|LښPzDg(ӖdB9-s8, ".Wi-@E-"? PcJ0.r=<3T(|eb69AX5Qr,)xZ}X&óCm C1`<]\U&Ij 9ʫ7t`"tѵm,Sm0[w3w:X"eTn{jpJWwEV*([‰MBV$m<8 %\:-^ġV-wEݰ$ Kk#<H#%J?}_ !YM(Z(}d0]pŠ.w& Ǫ,C6%_KmLU\EǓSRE8z,D.tH+%fU~:5Q"/BrD[W"+9Ĩ#sÁ| ߔ+ :l{TV2taTߤq6_YYG-J8dZ_ܶyHcN-![?p0_7uM+a+%UL=͒0%q^@1md(_FmI` A&+̑vK+ó~v W#H ќD;`fIMe *z#LqWEc TeKM_*&Q 7s}Ԝ2v2j"Qj7$z%8],ј .RFXJ1j(#5 6Z>TEGP)C=LgxXNAdck1\xćޓ2ߖ(Kz#`ho/tzߝUgcXGos2YX}/Y#l\c'(mRԖp"n8ZHY-/'`>P|uJ 6μ\m+/6ON ^H4-`4QNh\g_Yp!'/fͳ쮍!v>M@;ƳC, +KCOC6Z zUB8Fad"+Ev <+2"QcIH|)eQ8_O ,.wmP,saDwJ"L]SsGXNvrã?h_K88I0?(ڑQGD@# GYg9CRB➇R*${xM14R>o c\)Q2, ,Ȣ#3KI,C9UtRuBJS4K@(W*192N8-@y‰5?*43>kQ8/SE<0%ܭF!m/X5eQb xǃҢ$n)N80^^ZK¼ostG aho/2gP!jQZX9PiX=J+(A~GP4MjM̧KU>P8? Ӛ>㝎8o[0EG/ T L}Zw]d5.ؽ~ %cI0sD`*X!Hc Ź$KG0e`?%Dɼ-m sݒ} { ܳIg0 i%.sec6tƃ_lՖ%0DKn\y rњ6ט{ RZb|8N, ց172ց+Ua)_I)u|\3,8cbe\4Z*F^ah o/k]8Z#3?YA:fHOUI@D0Q ha#a#-ݺ('΄XQUU=ģ%bվ` EM:ۥyYa[i o?[1)(6 Ί fJU(': Q ҭadֺMH@$C6xvRysM5#S%,uؤDZ2ZH©ٛu9!+%ʤLJcE>V1f#C$$LJSƃ0: CVZ‡M;Ѯ(G8d{Qubvsܾ(vReJ # ouxTsXN25C\bL}码? 0u S>?[8L>Nt+%CV;(V4"b^@RnF'T#Ba*γn;ǣ%!qŔb`) rriZa[i o?r#ܳ!Ul( 01܉qd9% 1`xC~JHLr\Jܡ-eVGZ) ~(~6r3U<:BXmcʳ 0 $Ŋ+l[䰍E%2ĭHk媅#ɸ<].%gHZ**^*0lT ]q!h$K|vjשMu 3f98܎%!qQmpI_.Sq氕Cu9TsQvhcgM21xBg%A:PC09L=u:Km o?t8y.Tl[n~N#ySf\ YD`['|%ʉxl{xoֹ~Bɼ( x.:8YġajqAԳ$SG00 5%'uG [a[i o?,`ro`l1QrހRd9#T;t5NL]۷JoߚkIlۿDƂ‰;ryJ 3YS_,aGeD(7 Y@AQ&,T znn6Er|EhN \X^TAr扩D9Xb-AM0G( NбbeFD<ʂX'< ڵ/. (߿6 +Hˆ)aWvKV Qm^1扩qnۣCm)_w "vfF){+UC30/%!1u?%_0.HR>г8nh(F.oі׆9c@ Qj5, t]6ĺɰ~Yd]gml};~myz6)TW#̔%acA&+a+%޷b"Ҋg!$#"ds*"KXG39"$S:qQT:ySGwpoZ~D+:nž(N=R>kxþUr`Vhx&e9nIxdp#dƇQ: #a$V|y]UOJA#N@dgJHLT8yo %tܫZl~-lErJIՂD:;q.n噣cl )WWpķX6< iPiěu0yQ"_+#ku#<(b 0_I([6+Ɛ&$Mzɚ<)QxC8P`).U GlXl 5yY@+*Y90^г: =$\,wx|zt Mg3^dtZJ,Zc^Q,~š>k WVXʥ B HY) ~. :J(' sݱvrd15{|qmMih*f#1S0"\ Ks`IPXU4> dX6vnyyxLN7+47 0q6$[02ңsؚ&]՞6q2_ V"WN)I>DtUWa}U!ɠ`t}R lX@啷w`[h/? EK;8uq+$aw,),巗^V$ /1^ΔrJǡc5KV5un uG8DIx;Ab߭EAluGQd՚z "mkXS9l%gw!a"1k8Ҷp Kwost["KC2BW6^^̰;>[ǿ(bxqh}-7 R}zC6&BSa&씨a4çVͼ*MYrt-xJ庐IA&-ηf3Bi$gyX s!s~܉Xߕh,!&K5u~ s-J>JE8d#Ӓ!.LcmA,!JMqH%T^'Q4?¨a73[Q769N!{K@õi氕C7?; =N:o~R6ch%|nz/ q5tES.9hP)DȚn9eĜl^T%&FV@&k|Q2ȗdm: Ya[i /?tfr=kPՉ2/n=C g;l 0][-!"RA~?@~@xh.nYR B  ujn\~R9Ws^]y{Gڧor+ԁ$%N8n-:GKȰHJrV?%NOFlZcs&fzUqtTg$sG[:)zG0ֵͣ) 6!9l$c#ԒELX6@0Bjf#M@qRxŒp A 4"dc xyA\x;6JC~ף5q8Ԟ|7#Z{Q8n0,\/6J$ЌJ2mt)9zn^Z ]T/XT -,#a-:x뮳rHǼp@ *xǥrg`G/Jd[~^ONBXQXGM^aʤ1DgQNv]l82d~^$h ͍btCK67 ږL0Mr_xq2P*' Mؐ;*,}x0ݡGrt覄GV%Km^:QɏV$?2r bEa\E+!-[8"ȡl0}Jc,ºZ>1y3>=fe0KQvn7ϙ8^qd-Q3sSB~ȷ+$)sx;Gx%N+C8b6 (4- X8iU÷Z@vk \ >okV-r wf$eJ0t"k<PoZ1d9d.hE䆟]ILQ[1 Zj/`Lha &:a-F9nIxg0®CKy aUdEYFeao9םjyύ %831,JZlT]eiLJ編>|#vB1Z [6?&Tmu(U_őI= )f5`}GL0 s$@O$ L/ MJJ_=7+c8I0>|L).xM1Z sJKxOum+V+vJct1Oi`%,LOr0I[0=a]Ɗ%氕Cs،9TAB7Fͽ{c%'̎ȱ1 3Jᠴ!>i^z!HM1UZ q^ԕ C# .Эn1ag-ʥ6(8{F5Ԭ$nmqAT:txTU% M>[a[) ~7.Sunާz)XXw],>l0u_͵ڔ r=*M0G- o't*?KWhqQb<7zj=mqv 0 ʉ͟%d S8F6Z z;sEaC:A*}6^`@<(K2Dxxh`}@GkX(bVTɊ݉xXc~1xc\,mj R~зѹr<@LkUZdVnNԀ{l rn}#R10GZ- o/b]EP'LJErOU\G I #< ﹌m t^r+%=H Σ_\E߽($LR:0mLTm<]m`ȔJW$ɛaȋ%c|Qi.kT\:6mH/y><@NY{u<%xbt`]]"fb,qB` ᖟ3\\楐%4MP.^ՏE\fb<#mIHїLK f4|;uBMIaIh3GeI* gć48Z*,`Q ^3null)Mq1n,B7o $n:2)!pR^E`Y/x$B'%'SSB&uklG- o?[(, iz /t.+hcξ$$^mp$]A97SľT28as`8[(? R´&,> k$%jk_n_ s9ӄ䰅@vqR*E_At`4Q{(#q\9b]6y(83>3Jm\^гr0/ц?I9mRg[5=] q谘@lpMi)4Jqa `ݖCoڅ T(= ȍ7CƩa`9x"Zr"Fأcgw^NЯ~ca\\|_ -ɗ.sF7f7 T-91{{ Ol xVJ0./ʡK8Fb΋^VFsn5gØAt$`ˆ눰 .xd* Ԛr:׺tJ+̑VJ‡m>  5%,@Ŭ5z8vSln|eYۤ \ h9hIp#PkDC! k_YT)_|RO"X*0"#a#-o)FƵZȅ=p|(:BDD9vQ*͟05Bt=8h+R4?ۜƺx2]nrq2UY!+)xSRnl @t˦r2!4^гGpΧ_pٰSs%~s}q)[&*FlaNhK_Qp^U'F6ooPig~X>8'VT,.5Re}n@U(u<͛;%)x.J ʳs<ڇdzQ`݆ sݒC|O>`SUW_ynw(f$K0h+n%8c i$oiLʈ+Qbmܣ޶Ke7-!q>NȒPQr Ր᱋$obQg*QL等%l V23HDZ%\Pg~$} smZ 6 ^KC@0$_9xأ!9y?["2n#/DTef9eS +!҆ j KbB>rN]]IMwL( t \! @*ϝXi4 ؅AT̖6q[MXz"h>vMQ:8ᕜ@i `!{s`WtVM r9ZVuڢiW)qQlh:U0a6DDx50 RN狂qfYp~% mRt/JN+zȜv2܂0ƙa\Wғs:xc8˱`ǚ=neڡ!h` sv&|s4m"$p#/)/-8I/0^zI6  Q>hY` sGX„H {x1(.͵gݺH-ΌUjrGӈ44- PTk2!::s.=9Fc5 ]zu\ykˋy!ъ32YC#( П:͖e/BN[Ƥi0PX=RnFJmd  A hkF[ Ia h7C~t-Z=}Ov{:qzR!gcHsg \TeS'Vʰ̗gX ւDhHZ683'P=75gEJG>b:q8vpdי>Y޵$H' A0#вAD50!Ppq\eEk d!N m3pT8h|p UfuÌ'Փ- ߽WD8ثP%b`l/^׮w`g`f0XxrHe%~Baoxap AI 2<;"(@2>$az] Une%CC{X "Q |1ܣ;=@+ t+RbNf q/a |dhݞa#n /B"{MwqCx9[p%hni;ʓai& AKx>Cqz 5IpCGuZF^+i[v!fw)qF`6X"8ᴋ߃``H[#29R^缃d`V8Z-)7C^t!C ڝuk2vlډͽ{t8WU S+Fm)|\8N准e%OI 1 (a/BN{Z/<;R#<]8zr3F:M{YH IY9{^:<ȒSgGpmmr;>)ѸU5-\kkb)XPÄi"C.j~w gQ8x+Ǵ|nU`BA2/ l01^deJ1/4m/o1;[jȊ"0͑2sc]梯65*Q7&=$pAWʵ˙7ltN&cZXI4uHl3J IoR S{ aB42v5ܣn v`T9*Yh;xUdEW'%hM,FOMns4J^$@Tmyu\JdlAiF%B64-܄4 x?a!!ً/C={K#cʶj68j@ۘF5M{ےȐ(? I{Qspi(1͇a',NJC(A;%zuh߸3$Dzl=h-ʳx! P/Ͱo MoxmF)CC}ʍI3,פZ6^ 8(.n48\BJEGK r꫾ɹx`*Fn&4hi$.{kH`,ҐlDpw>ZɆh^Dxi q(]b>}:stal8b `ݖ4./)Ԑ| 1RC^Q:24PlY3Yr D3 ׮=Kˡ,֐tf 6v{T}IÔ4q$w_R3N&0M 95ܣ¥pkor2mt8ZO G4KCMCyB0ɆiF'B (\V}8FڬvZpIQ!ĵ5-4z)4rQ>q(-޷ʋxawS^֔}6iHPsRNHB<\CCA^W{)MeniU' @*KTaC4KȉH#i}4mLM~k 7URA%Ϊ3FDHVp Qon]NK@U'P:?}tԢ$64%xN G |x"$pCm[^'Я9OOեދ-z3^!2iPrp 4=lF"$p`Z۰jN?9FҖ V(3"(%t|hz @44het؈EHmOiu1!0&4nr&M L|JS"aC4K؋Gn8lVfaZCһ5&a' :8l9EHUtƛ3$xdJdCnmRA5ߚ9ۑ.THc2!ىC= @6{^gN18 8&M8(eg\kBtYq $H {nqU׉S@{V&? 2x!P q ^;85DI"i>@x nQzuuVSNk@»_2RS6RCв1|':C>&Oxehǡ[h'QLs}RNMcX"jH[' Io#=8L84476Q!^Z=7k4 r[l%?і#i3N ]U LW Fɥ,^! L`R WDU0H*^|RLà@$GCit!%Ek"0#uP% c:%B6Mp,Ic.4-/oɃЖN%M2l~y^Dxq;{vzܘM 'Fބ9-KX$qliYCҲDx@TJPC0͞F^DxSra n!pR &oﷷԀg6LH {i qck}1yO3#Jͩ& O[ӖBJ) <'Q"24ȫvo[ 8`!I.cTK*L0 Wx-DƂeqP"ӁZxj'9zmiq`<&foJY bZ6!0SR+!y[N ( hźMx#Ɨ~.4,<&A>)dBa$>Kܣ0@Φ2-^. #$k)$mh} 99  B"={9PK`o9A4U'uJ(Hz=9;4lv=&1ܣpdŬwl@#s hC5zGt.t9(8Q( >fx50:SreHs!bIZQL>s#xn#m0%ĤA P/B" 8dyȑsٽ28 JjQpy+4{\@疜;Аt3oÄHF&pZP` 7U/-8oWT, 4 ' }tJTCwrw ͦdۜM 7tV̩LOAd*t-VTIԜ8-(`N; `(r!$P#cZNY ed#cGQX({. CkhHZ6z, H MY҆iذ)^{ BmIT`zK3 ؕĥ-P,9``Lfdr"%J{u: ;8:s%$ CPCA2Yqÿ4!1| PKY =o 5 4P.Fމɑ|ͨSy.˯L{6 N6\ ;o0&,u1 '+i삹Ie M `u*{Sѧ}@>o= lFDxn!(EEyovbŠU섘Uh)Vm퇆}ogh?lF"%Kkظz~+KqW61O^L]+PxY 8CA244̤&D B |(YNU, |a&m/4 ڇeVb /r/C=v*a((xtU-A˖C+,{`CAЇC) ӄH!>Z= GMG_'yزGe O2,( ٴ<d$\ߓܺE(~4ζ1Mum %]!iJ'R61lI" 8[-|UWaTLx\6 Ӭ%CH>7ZIC^'NB8l^Dm 8\ЎßUӰ_ 8ן$+Lc-E !sމ+wO !޺{Eދj09:r).Iҩڂ;݈/#I/pGM󡝾j ; !hXe!&?;AuԾBGfАt Q 6NyD:i (tAig+EnnpG a_y"h.ܪxR+ɼ:%?yIk&r7Sa7$ޘ L˛9ݿ+T Ӭr"%p·93s׉H@4!tf>%v#/N2̦. Ѭv"$pBM ʂw)౵nv5"h \`}m ka4!PD ס.Shg=xwhi%BEBe\3p Iޞt?PIAЧ .=Xtܭ !/@9w{KubT^qLzĶnW$0}#+H黃,4$ ϡᷬ<ʫF1 V4FNSctd:T>;i-4҇=\ S+׉SwrlPͶ&jpe`#Ly1igjol6H {qdAʲ(pd W\q %L~睌kOZw jZ=؉b wȅC=ָ@O<6hߜľ{35,\i6Db؋/!Vun\)UPL\VwAF=FIb_gImYf LIAc(Gᦶ+WRuX`ptQ)sp kႋgf ] RCв)E,ր\r) ӁrL25pOd)=Kr.01 T_y+$UiI!Ȟ28a6F"$Kkxd Ɍ(PyЙ{$_bI,oRY`QZYDS}C ՝I Vv>+ 5Z3S\\)"mxbtYڏTnSYOSQŜA,g/;3fÙ4gu,& mc{sbdn 8Fdd0MTy5 v6ZLݣdHbQ -H| *8xR2UU AA5ZOa#Ny /B" 8e(َ1.&rnY5Nʹ?e뻏A lOQC}{3& ; B^tuz1>N<"L%M?u:$pHMS삎\.L6L)^ZCFލ`/R(R#`8Vs {g]B909\H y n.|"^5 mЅhT>y$ء!h02ݪ,~!Q&9#o;ѫ4cQm A2g!Jjذ ӆ ӌK^Dzi qK&NLZraA(I'QmSbɴ4-@0*9Eqptp*6Vh(΁(0wL3GSXZCqspdaaP^Dxq(zy4]r2SgrΛf+t7$`N >Ɇi>>:c(Gȴ q}dOe)e!I#ZO7xҋ&PYdMطi˛t!%bj.@*t3@lu_tBޙ$\‛ơCA1 wSnMY0+R.{ I(aTr*NJT,Ws/IYt.&и i@ s0 cNkL)&YC! 6Zo5c7'5=BP4i8L d5[2Ve—(0g'R"\ XQj/幔38l7a^Z_k|qjLJ/˧⃖_]!p;esI % ).Jc X}62BX(E+iy@-GNeDCo] Ѽf/I'!̚ܪ;o)3y%koÌӸ` 6l`µNHF[}NSI(u{l!K.ͿsXtlrhö85ixt^W.`IU" j pC)gIn[!pf2M(}weD=s/i-QVwK|)L84<3l!a'C-\U`2k%WtRC!D=&5`!dIZXtTK=aG3p]r_mpiHeF٠PmBA3LXhGCwݦ_! u iT]лQE)|J\`6 i-HXC}ajwh!`gKE0 v= 4]!2K,%g]e b6Ln@^Dxi qC Gǩ rv#pCIGkpc*6`Wg"0';_!Y+Ǖ:]*ZYSŧű Pa4BJpBv)FQە-02 ݷ}[u8}.4)&>ߩaiM5{50sv?xzu`DC4q׊dRCвBj e`=! &z8y l&[ 8υ9S'J!<9+CÊIt?s.1Jyetkop R}҆' Jm8+^G+[LpB 4LW><6=70`9MET50Lp f :%H Ao$g75lfN[7)~[=705XrZ{"6h5OwnKAPPykX%B ]{l-Vrxp~rOnA6GHu-5$= (^Dxi 8`U\@nQ hĢD ^H_QpS`!!Pd S%CHW2 l~gKpBu N $kQ; r̹4[,%8@eYQu7ʯmjpJpՃUǜ R=|8'M!EXŜBDYC2(p(m^1?fG~x-uٙN9 Y 讓*0%mpXŋ|L dp@Q!$XyuD8V|V Hd Bbk^ e]8 [3&LI'B"| Qx¬V18e8X4IFvK O >k .Р{BÆ\@k$F;!rBT?|T]Ax :6,BHp•m*E3D]nLNfM!@ON?ey|uX0&}Q 1(]D/-1@{J"M[gFum t(Z&P"88M4-,$>\cpB@w3yXV}Ty-e9' |@x.~]I*( %!&É'3ƿNJDjdjm,dN /Ya4KȋH[Qh|79~ }/ޠ5U-;.T8λeoŀDhXֻ%ҋ/C=ִiXd:qCX%1ݿLa,f6[Y;upw2T,JDEDU$,M 8w:]uѴ"UHl<74$YQ|ݔk+ vQo\7| ))m(-IeeOZYB X /oBl}GTti_$bpx{; 4+UEӑk]BRCҫGioЯɆhڰ)a/S-ŶkfNIA^14wPqnI8}hZ6X"86~"$ok؊h/If]qiatNEWL\ÅHa!m#uC6*4jT8]>0+^D%DJVpŸSPY1%ͮ|7MTDBJUCGovҁ6IV;nEl ;ƵJ|axJHdZ7$ oƦLF`!g+Ǡ"9ѕm>4;|8gf^B&CyRC lv? 5LFp"$I+GȰIo\ ,n^%a=iZeEJ7ME a`BJ`p8x_=.ȗ9",V+O mSdI&RA['M p- ޝg@g-MZMNv^t zn2¥vOZxrmJHC"ՁC[JFȱ 8X :sJ4NMġ iZfrzf$€^ \t 1e-C?eqO N-48"а`8r!$Ekx) >c"fLZ6XdcKv Br&lK0gtjB^Dzi q焕9aXkiԔBՆ-" GqJ&E{ H^Z;0Y9!~vZ+z]9.33.Au@y3xr/L; fth!A';yK{p,ڮ ύFM-2:%E'R8^8ؤ1Ѧqx`Ѹp@Ѱ h:Kj!H+98 %16Ds2a/B"{>){.@fLgc}lQX<+[!hxy3qϤ; <1l/,18x9`zjp(28"4e6~%0 |(z8apyB&(Ӵic(GV#Z)/% + [fMl[ )ŃdTtP^A0["s AJ<4 NfM3 =Pf!h@଼a׈Æi!^ZCoDO[qV-~wO߽Y?}@{oV< G"^l~՛m]ewo>k`,3L8BޞǷ_`e|_׷ڗe{/0;ͯ\ߣ`]8||~w}{tzג.Y}Fv痷0 V| Zm)}ֶw6=ۗ{3??6Q`|-.r-u?o^w&'r֫Z,҃E]&ys)ˠFGù<7jgۿFysoxϥ^>ĹܷoM%6ZuWȿ -_{Fږ?_g)@>ޘ|c`,쿜ϳSz˱͏.[wJf*QUUG8_`܎f[Z3 ֕>_[A.k+GZD\lGۭ> ={n ulGcmss ץ Qɶrs}roHj?KH3[~<u~ZKJzwW,Nm<6cޓY{2Gy%<^onC<?gP~=_oSoU޿&>?߽6:7̯6mfpZOؚ}{\޿ ﭭ}YzMTe]X4ݙ{u;g%k֛ G +x|4 С^5{SqyZ,og"ݺҴܻnbsc~M:&[4YMO69ɸ?`^. g| Ѳ/9deejMڽ mES2jQ ׿o,yx=M4=2be'7ϟ4z>:G;?>ԻQ?`^I}ۢƟ?rޏ??nRNOkj]9מ}?٫ r*U>7+Ky8 '0R96"886/f^_ݪٺo4^fg f,`Uw2uk]orvhw|?{!T+um߄?澷A~Fn^5"yPv;; 'Fg>#K1}@0Do? y'<:pëDz"'XݺWc2'Q[i:IޖAbvZ}&pi籯G㋤~;Á3^ޠQ ۾ A'~=_S4o`N&0##[,;[xkc"hS&cs%Зg$r>df?,[ !qn)CG~`۞ !8 Sz7}3?[?FT)bFRrn a:7ոe˞Eލ֌f>a21?;ùooƫUj`纝oߺujNކR\:?Zz۱_?_ڠ Gzw嗟^`u}{s_[CR*y[ -|N~ѧKG6>*`a;4-hHl!`v]Vwܺ#VM?ッF㎃NȽ'Gۻ}?o+ } w.fn@Ǵ.yϺqqI>Ybefp1/6spZbqpW=T~fg$`yi?>S/Vd\9N[_a6g{{~X,_Lô? &ѥ#{>[k8?]P[6Mo,>Ǭm 1ox\mG]Eo?ͥy<.?vH/v  IVΟ^~/"]S=GÕGbnL,=Jܜ^Ttgm/ޝY_km,/os~FM_TFؾ^[o6z'$vO~w~(N\kT*&O9?G6rv0ۊmpR\^u^>Ϭ=&4F;xM_Sgz_e5As?L'׻oSy)Wyެ|;f?%>'Xӓ6FK R>S>Gy'vW:u51۫g>O,}f2z_4|?{}[0|uɏڧJGDpqK/~]8 MɼNh8Fg7r?Y No1Sy'wp D7m#wRgtl'&\9t9mgճqZ\bt0ӣ\97/`K]?}:^^Z:rX<`Ö4{r,\gJ;=iM|Ev=M>j:_;[?kMPO)̟!<.IϚ@އœ]^V,ӡ]endstream endobj 82 0 obj << /Filter /FlateDecode /Length 298 >> stream x]Mn@ bn_I7Y^ &bl.x>)M[?9~) 520A^_/?qgryG]tѬ+ Q2MÿWU;h"@*.k|TR\Ұ2  qC |{.!"K%O, h<YĀ:FDlG`h 6G`Pmϡmux_WM/ٗh˛˼+@/cendstream endobj 83 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 1927 >> stream xTyPwfcI;8=+pá"$* C\À0?Ѝ9L\]2(2k!H # 2#+V4zGjS[V}# s3$i eB8Y9ssHތ 24i, KZ{fB5$ $bǨN..s4ijS#Ue 2;'KRgd%I#UymF1KN(#=<,%"#"H"XEk@“&#L† 1b^ œ% $"E4{#hg3aamk񌲧6SيFU\*A88,}=U3#.K70מ$B\@"y hWrd 8͵0c~FpGo3/>g,^>"]g'9g=$K V1#POuDi F |fYg E>1/3eC` WV03R6?\,qRa P(.5' %eyӢЧ<)n(689g;<jE|WX[RbbX8ZS ):Vڃ:\H+ƋYS'T5N{Ud w8~}RQ-ޚen w<i[YovpgL}h/Uێ׳pC8߅4I^ήBv /<)/ӶkeoRn@k_ȯ}ݵWIW_A'ё4^ ޽5WLha(PQW >"9[?gsMf~R)LGvhGr_ :9Qx͉v(4Yپ5 ɕC||ƨe'^ +#XU~LħhPݱOM.en ~*r``5̛} WI4(1gX 4 LWzr`#8Wc۾IYځyh˰{gij\.p;RWlP;ΕHiэ]kFA 自^t E9ku HG.+ۜG,:>Fs mdy%%p D]vK,(uuPA]!3*}a7oaK,{(p<xhwm`3/A| #ӑ;h =x& qpxMM8ch01($+5vZ ³i\2p@1HIRBm68- qI0 _Dє&Tb^Cr;AH~XQW3݈ELP8 ;.nn)3pؚ16lQJ=)9kVlώO0qz&V]wfÌ?9S/DbJ;>RSux5ʔlޮ}a=xCͽy\\X$KA.h)@r^9fŒeqR懮s??T+ϮCF~Dy[U\\zSy vnO/rS-݋W&|̏ߋy" \lcoX+u-W}+2Q?hi9\n9 dSendstream endobj 84 0 obj << /Filter /FlateDecode /Length 159 >> stream x313R0P0U0S01C.=Cɹ\ &`A RN\ %E\@i.}0`ȥ 43KM V8qy(-> stream x]O10 PXҡUqP(/ СY:ߝ|reA>E0u- -m1,O)x@fw5|OySntfD[]kL';˨PR4u8N.!\4I,|J  ?SPendstream endobj 86 0 obj << /Filter /FlateDecode /Length 4132 >> stream xneGGX)C +Jpؓ}۳=UVef@yNOuuvxv?agã~hl𯝥5GM6pt]K]mkgn~IW~N G'pK8.8j^L͖X1}aE\&{tK!.E+tvcګÌr0vBM6ZMK#<{'ro~ezZke(rzAH _2aK4pD3b/Hz7^S$Y[*^gt3%ziG",PEHxh&LMp +#X@j3.Oa)iĴ B ~lr~'wfn;o"?{m/nç)VX q[.g48gG(ru]'bRE#OR/Ai}GMgDQTztU#!t.Cx>ŕ7N#8ԭF?\r97_"޻@ &ƃb JT Zq #\06Nm 夊a-(g!{P@\)`5Vq΀D' GPz8\$!A/\DC)KuN3 e;2HeD)>Df;C xI=M 7ԨHrPem~ŧ 22/Y$YuIb0 h(`J\ yBh,P3xs{ \IV%km-mk7`}\yWw_vg:,ʲNF'S`׃.#y5)kuۗe(yGFJq6>H:,FV{se -w֊ {d`:$bP P<.t@c0!^@ FD/ex,2E+}-I8c^jn..纼~v\tS]jxb|w7Pт/A{>0l  7A,ȱ3Ŝ%^+6lS) 'tKX;c׊6KVDžIz ب9W /mrmA54D%eBK5]U|Nys)e *w'z 9.[ '%='bDj+$w33Ga 瀙jCz{"X%T[ۑB'{/1Gt!X.m@`& ɻm.o S@-MNR9ۖ,b/uWN $WO2?JXUZ*1ZiXBǒ"ȯ6Gc.2V2RŠ wt"kKmHw- BzHiC VZ&Y&IT)`n&.l*Vf!B1C\A^I[A: e!jyNkۊmp. 6WS!kݤ^**hhx1*RsŦx'/poFFķ9KͽzsTD6]3ibn.^mbFEku Rހ +8Z~k `[m 9P޳TsN%oJ}"]ːF r۔+] T 5Z"WŃozt01h~G[&8Z Hqd1dmKʶE^ȳKmҨPFuMQ*SJʡ'uI K o==[HH 4"[8}Yu?漐r[ y3, xse|Q/bȯQgeyL$u!Lf: b wmUx>'Nn(l ":|`rV }.uBC]R<#We.GK3M]JgLRK?԰]uԡӴ4zbS53S0{<8#jP?CzHc|>Mԥ(H] @ 464lZA[/{4>-vXZb(Jۖ@UF#ik"g1|&wK.YFR}:tar\ &b(k\emNt<0N ۋB(z\ Wڏ9m/WLMV<Imɐ94>k2x y,Jp$^iŇnR!69b, AE< b%XHA?+SROڇ"guJW+^3+ГJYѓT!"hn1nA丮O0UgI:3𾢋hg=3;5jdlб# > stream x]AN0D9EnP6,@@8(Q( nXKya/y;ziyqJm}^nߎsrfw8o_kmB4 ~ꮛyP6,9Ӕ8g%oYKV8f8kVQ + #̨s#ύ1+HLY&gD4j*QTVjDY ksH8$ă$=Mz $D#C_Sgcg>^^kllQߤ`T0ܱ鞍l1 L r&A$\MF___qkw^e4rظFa2r9 .r-Vf^3QX+wH Oұendstream endobj 88 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 3629 >> stream xW TSgھ1zQ\ׁދrKuԺם", $, 6)nuZDvjut8_?99ɗ{y}/ X뷬ۺuVK5g0Td APkz LYB P! 2-tւ#BgGG/]Mf$B'2Ҹ"Kv~Jf0t H0* 2/Z)ݜ&OK ]B7$sB|a+ CSӄ< æa(/?y0%5mozF斬l#fFFϚ3w0l# {ۂmŶa۱r,VbX,c0 F`Ql46M16*:6)"/Y]`DZ"8s8 8|F |-#SF VU}: 5cԺQ6:i1cN4a}s `{d".Y<p&no:rNU1}oH鹿NW vPG;9{C"TZZN:W)(h Yw.îKlIL4Fķw8a26}7ű+g. nKj.?A:]` `kћr9t+zvza&ӁQ^/qV6>>4 ڱafϣ}e=fnr7|͊\ϢM]oo>ڔe \י@6#vTJ묆EQ+8 KlOg$@\pbHŅRDPxB\9tm\jPAYd MԱԳޟPm|bKy#ۏB6[4eG@YZMǁh w[ .e$\t5@ t!fUcW],QQQh?H*j Yx+_Xv^~BKW*KU~~% ⌎eq7DD(%RbQ_m:fpvCr5×s"L{ڻTu<'P0`џɼ< QC_fG_m_q;#مA2A3iMEIϐ. d7,8S$4v a$Q 4Jz KN=GAA Zh| 1-T)Ď8NGT$\r.`p3L(l W_T|ϾwFzN<)Lav |=ttT~ME3\n?#c8fd?o@/8o%t:r"=nVmP~aHT]j:E{68/?¿CP/g ʤe=4j [Y(Sƹ~Nh#,Zf)e(-)o7 \> A T5VUkQ2ٻj^9(b+[ 9,nq5x}$@svl!;( |މ^ZSQ2[Ew任O| Ywy|e%<.Xv,x&7b0$-d N^4yZ9pۮUEtΞxq2 /'[._>s ?7se@x2Yד@zn`r2P(1E&("_'$i5T}i?LgYʳluy8kiSrܾE,kmN}(t[pԷ˺7+G9 o̙n)iH>c kM-yĪk (N=wֿqC?7hnpUH^Ax7X)OA t<,3_N=b{xΓ-b'?[8]TGC"S3^⛮|K11:EyZ[@U(j)OVs*3uG̙ߔO \oğ9Aa㊘~錠j%e )eB4'pA#u8#f3zJhA*6fW+tٖVKp:hA~wku*p${h"5g87gw}8ڈf|Z5Rr%oI΢w295_ab`x^_AcB!M?4Ia'ic/@X5eykuW-ת*`'wYeO̪!,mym*^=ÓfXACIMi9!X,Zʫ+iXAѺR5ԛzKǓ\F<n#Jf~c:F\8`VRnKAu-t0s6jO9UM&>j'GAзPQP.5),e%hX GqPU)Qn,pB\ {a~p3(FT2觱x.(Tf#_kULJ8C HGq,NfZ!^ZPh P@j `7>NIJwwt@r}ԓPR[52XY0X l;r`e?=lO6l!-='û]e #X}p<޾Dv223i\@ww xp~ W-/,x0j>.K(ضrgFWEmsKchݗ6@x^Wޤj "rù|0 t$T \dEF \,mf3u9c' .wm:c8Q)]S]cgA̋;JcyNW&HT2Lc.T^^F*zbS}0p5 'ԘmNo0g2 fUjYE U6VڬNp\p*wCÆ> stream x}]f.=CA.6;@.vbܒen,ɱg>h8骷X<T}f yi s럯AL"OݦHW<乭NvigXpyȰ2H2Fϸ]F׷#ެn2M&g9>Tǟ'&3O%_qx )WMn¢^jA,&zAt閯A/bŲp-pఖ(b>Cb([Cd#bźc$G>|s~;L˳oj.=]i<_JW]hrIi_R,Af+UH7𽶫dHEs!F ;tM>W:f:/s*cȨ B-/ *SOS^9^_sWh5\pk d=;FsH຦#˹CI!Kc}Z$>BR}xYG>U?)g9Ux,xh~=39f|(JegD/QH'I_v4G mE?Dx5\ X j=>\+sX$Ƒ@DVy]jg`{z5lBAZw iY ~Z~\~sϲ3?iy&#$`<)9pVF0Wb9?+;dUq49'~s]d֋'r0\Vq|}آ):xȷg<1-Ȼ-xmIv/g^|\>6XnŘo~bNs|ҵmLn3F~zg5뫚}*MW|?11V~KO=zøGb2SlE55tapөN/g4,ӑZ2.Vfj. EX0}>sӺ^}@пGF1[I2|n1m.Z. t٣ 6hsf^.85G,#&ֹcގ [iseyb؋r'ZdO7ez^BtJ,f.M{}YFN>᭟l}鄩CfZVM?>deǰ?RDB_y5,^y-Gt^ܷѶn߶ſ]i_߿7z#D[.uާ;fqm|޾ɝn=;97q!\Tn0Y-*|?|7K'h5QU)*$sk5!/"ߋMEeYU/([=OYiÌ]Kv?ʳGi1e(dsYV"084y y0dNZ:bx|O D.*2Stpb8U..Y#m2FZ8ki^aA}HP\6d] (\ mER!`A sTNFPW% iXqxa(!g$iOipȲ7Rh>zQ8hqpXeXMLѠ!8HoMAлͯF0FDS DY7Sg?Y-pmy0Sˬ(D2PZ F S!(LYPBU2N8t<3c&dK Oaظ(dc` t<~n2F )\KpC ,y m4pPLSTŒUS8E<Ø.'#E!TJ?o^. s,POsePqJn#0be*9]F\`(&*Ub#AsyT[UtEPj Z '$Va96*b1E^૷d#Zk+Lc 8+ &YCF-#Mj! @ hB3`n~#} _k]VlaK:q(QjByHCa$ea+y'<03B M}&)Y)Br[fOA ()hD@`0 Aa*6:D 4A!K xtx$:ܜìHUh(4ZVH28d(̊isAP='׶c:ehKb Za \.\|0-6/PdKf@H8)!Z>2(%%88ܬ0`S9d(Sbĥ.P.N{]*!.%5#.U6 :UVB)~q!2RAZ:Z鐿šH2Qe=%\@܋oJmO&s}qpXec$IsUY ´ 9\P?"R^Jdrx yLʈyDZ`s.A֣a`CP=gy0SS(BIpB c0=$F;fZ#%XUJ fVQ~QsnVcsR2xo*o{'RR!)%6H9 VI$(J0wè_M*􆀪f9pUp W9\P%p=_,FA uc$܋BSa<%sd]T (Tj=z7!\9s66xu9`>0uArqpXE1bnDGՂ)+܍X=!è#97 ˃* SW.&BaNa*: Z) <䪛@[IJfl$49,[6.YA+F{\&Ca /Ás4OYcPC=^}*882`m1k! ]5W4/dK9TH,;J;EY^ 6la<8ty,Λ ´p8CC8!~02:#ĉSJaE` dI|Jy0OFZvXPA܉sbEz` p< n mH9K P Hh.]>bn0#yqx< s37oơ8ݏ04ϖF!XO/k$8puZ"CUW#԰J|%6Vd^vdlYGI-g݋Vz ւqrG~ȜVk=R7kV.)\9o~U&\6q\32{QYICLkg,Mck찲Gt&_ $Mm P LyfTa4P;mjavA1Ve4,v38*5 o.fM´Tp W9\0&4iFV G͇/lI;,Hd*v)flG#&`0T W#tf>>-&2e [8Dyx`q⍢C0X%aReT43Y2U%TWԪ r<`NW%W'9镎a_zbqpXF;9oM(TEkï8:B)% S'FPLΛ``J "p69|Z(Sjvp8'FO3 pG C̈bv[PÇ_DrLlQ}fPPn*Fjrأ6n:!kD\0vmЅqqp8Ņ >ۑ6 W9\0xEg{`@p@"JZIA?tš;h婢/<MyfO_J teYERլkP_Kέ*`q1W.hLp[=h) & `pc a۩A'U=_b$E*)BoNaJ:jWz y]9n6ix_2л<0\cz98| JbO(^WKCP%]*O|T0I}"I\z%:nmeqR(UV"Ҭt[6 > w/_-/ s>BˮGpSuatUxbp-- h>:ﮢ7!$ qe 3`+%8ǰ`.oC*-ynq@.o2fWFZvжև~AAAT`8N6: E'àc1XEHtX,N::D(pp *_z+F9yxqG`:!e/Ԏ}4v6nz:4+ .)\=gp5@Bn .uP9`9eaJؾ4oJ@ ~-%@B^v4i$zeU90"Rdh䠺U䂡b77up ւCѰ(d(SjVyb0a[e7/ee77 l3Lf6fZmevCm<Qi/ZϪ}ȍi?1SSޝ[:UZ8F;|[h.`0-µtW;ԶDgO E{h,w=k0䞚E,+88216qZ [Q p-VI_) mAo{j-%SHӻAz00$1zM]U W80ȭfHM\XVi1*Gy}k 3LmZ1sDζIPOTp W9\PPOUC/ '9VR'<2NzN0J7!ju)+lC*n}8a0;O S\H0n DOwmA-hwv ~ěC6Eq` Ü1$&AA kh&,\T%Å9\\k?YM\85 B|˃/Iwp6&)\/gBs|էZe0XpgQagQLyfq0daX %ې Ǟ࿻jFmG+z`yawBzX0{sA1882;fJhU>7W^ÙXֿq .xs-\=`#J3p@}M@!&`0UttLp)d-84z~1BH  6FDZqp"Xe0-Lp% ťmʇ麋xpE6 2j㍐E쫵ʞa*gjBMLL ԫ#MǥLI#nf`ƬWLfc u uCE64p N:* 4 ug j L_bmKcca. imq"@0ڧ1ڠfթ:!ug4=C=Ԫ$=yaH=w(Tʠ9𢁲D(zwkwi}4;CgL, V L} Ss@vun2F S LEo1Acaɇ/L9493yLC?q7gd^ItGNE(pu0,cb*Ӣ~Ei@gJa8*Gs &`*8Eh^T^/V7 OWA@N }O#7, ܘ L7햌oNZ:j_HNQ`dyh[E`LwB)>9821HC_2Sjrzf+n C/7+0; O9CAF*z=xK;0ø7ȃ'5!ĸU(p_xs;a "FؖTp]f[Lf$= hyπf"` /س3Iy0kjsxaSpaR[C_à!7qtQ}qٳ߂CZtc6-µt/bw&h|_n= A>eaaq 3WµvW+tEzy``?\Zx}D= E )N^] 6hu<2 F "(\opC|vzI{akMW[ ;9@P`^W T1x |/ أZiv,UM϶9i1 oE'0GqHi0=!(:// =|tp=7w]Eo~5BȡaBu#95cr6S\wE奭`fa^, e" il1ZLi=u?mo[weV0˵ @pXeXDLҽgg $||T]CmD4=^J?X%ǩS-P+h-9t 30+S(BE[&;:^xbaEU/$ F/֍hVhaw"%`0-´ W;ݷǪd ;i+_ N3r& Q |h1p!i\cKDK p +v'}iWKFr+8XC4!k((p#o>,8ڛfWKNZ:6xHhVPq6=>5? v<)0Wͱ_C_ J[ָ M;zɷT%z1E^+ѸAsճY996 =882h91šp. MµtW;4`,%6 A-\N 96L p-;KcH<t>y65#@d`8| _CTwLh~WWvpkѩf *qYD;HkZ0]|"s#Hvho-]{+.Aa;4fh6=ģ{$۞'Ģ`z n//q˃v ) &t\+#ש1ː؈gI2>ZSU[*) q҂`ɸ" F S"(\IpB/m6ߴH xVJm6w-ݘ}-ppZ+SjlO~\-;,98kszGepu{} >!W˗uyUW|o}-.>Ȗ?u[v(Hߓ W{7|_H._9o/?lHHoԕuW~"9mWܿ\|^b d㛑_^;G xqD$M#vxc#W~}Mvh/ۿS?6&]hb8K.Տ ^?)k_,+COANEl'ޟ_fW÷}oٿ2޾__*wlsAk.''~VdfC_A=p+ɒ- [KMI6>/I\o;|#.>D_{'>Qoc6ڔU]q#>-Bendstream endobj 90 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 1628 >> stream xU}TT?wf (uwD D+-V69P2||3`FBXKQq S!%@.h4-eyzgƞu>;2HA LI)4W:J lfF0jFbb]YXUF8Xu#p8x 8"<>fʬ'V\Z\?੅No;eb>.* Ͷ2KՑ^jXng[z?ؿ!j+lwT9M%fKLl zeUh5B##JB)h9JE+P: BPb4Z C}g4!&W-^etg_fa1GUlu^t&<Լ7|:2pdSLnQxNY\ O!`NzZW?sф!Ft XH'J-aIK_X;/}# d h2(+ 5 cz^E\Wr<5"g[K3LIWN6.{{*I>CE#]ʷN}Ú}2V8 7qJ4p4LTTgF,EID[`W{|֌NW L[Rl49ʆ ;i=2tXGW]G%g'ƾmqp}} sa}I0ɜWn}Hy5.,U5(oyJ ]$#̄BTſW' w#Wҟ{06\%SɳOd)bϕMW"g:L&! *XBcȝ=#_:12ΨBmzܿŷ^$ ŞOtd9yY0Bnw(D6-Grs`gP7&u y >gtRbb^נ)}eD6^c/2δ%x,@й9nXz%'Vtŭ[() !Hr076'Ř}AH%d4X"6'ʥg;\rsW%.\^gOQІp^Wf͇BG@CBA`-hG*p/Gh0:0,n/˓DsDODPR=3_~ou{ a.ؒ)xi|LLk<1dHL0C"O6n- sn"P#Đa~6Dj sqLv_ g2%L.!o]/aM쁔r0u(m18U|~endstream endobj 91 0 obj << /Filter /FlateDecode /Length 160 >> stream x]O10 b C+qP(/ СY:ߝ|pFcpƲ- DeQV-Ɠ剋BwOϲ8VBi )(IEѵtXIg`2i1/%ES&qMsT2Χ_A@Stendstream endobj 92 0 obj << /Filter /FlateDecode /Length 26512 >> stream xսͮ%q;ϧ8Ó(==w @9U@H5&RfUj5ml-sS)T.)϶;~[f9ˁ_}1[/5=^m^_˷y'p[_y|C?ʕ G-K+gy}?*-vQ˲5|s?*-VvӲ{\G/+7/ՇY+//_C򏟮rMkB\vb rߧuz ebWVzeq7ZzR X;~7[o/GU-~;Ӿ|^oqiqv%8wv_/?r_yˁfZ^_:g{kgxwy;5//?o.r],q20"n#I"J{;q8F xa暈sqei|HRkXzٺO{P{%a@~[vÅVGr\wK\m9~W1,^[i92_rWwݟkWio'F7>l]<Ўƫ»?0qjkX75Xf>eꍠXΰRp]n_a/kxi}a?f/zZ.f'r~r6xv\`=b@6KY.kZhqeĉņry-[\ۋ`b-{,m858-?6G+5*4b9װϹYܛ1˅kۆq42!{BWvO 6uom{s+W35c'ݚ72->muzone7m#7ң-]qe9;џmݸa#-Wo-3ugۛM|LpqyDs[3ZmM= w4clJolGc`Z?Ydg-~ņ^ol6&X2ms.mYl6oഡ۲XƶYNomW8eW S6vVfoފk38L|{yZN4icoX{hifzDi/Yd/Y>2WWgf9U5vVQ_[ [z~|spc ˈZ/qt̪=߲A7VoWs8?}[=_7ؠV{ ZÙF?fU<s*z-E ~0 6  %~>xe9YGK- n[]4j GKv[k׎^yw[aК0ب֬մ;,foì=,Zp\8M mX=,N{iqhA8+,W{~Gdfd7fD4`󵼩BojZ!˳M/>f%NfFk <0yeQ1b-c.u<h}A.f_*cy}tؚM̄Vlwoctc&[ok+,ۚJ -^"qA}̊3|W?ehH>`^bB}i0=b660loaDpvq6N\\z1ю{R/;~| !ieax溡/{)ܽme3&7wLJ`v@4 yl1z{gܺxxhnۈch4nnN\^v\\#n7p{evhm`+GCe4w__"l#;(//areu88 u}s=[E@S8F^4 K8#p0+v{E"f=%aKk^eܸl?cC =14BK¯kGKa+7ڀsІuGw尷c@_0 bvva.K.ZܿDdėJ7zwMF$ˌkh[X#Os/D)/DObؠvWDЂ=?}yN9/o{1 wKڰqm!\_āhmƨ6zGF,S_73,w t6a'a.ۍPR\W46b2FmyO56Z=0{=ċKx=89Rxhm^t]D"Rw sZmasKƾIr9cf8MxHxط D+\ rz^Ňk/#R6Gcsm Dx/.=7Rw?zw/mX:ݷ=8Dv}KWw.r!PtE6Z#X<6^8= N.^݇CX_Y:if/mƉ1);X#VTqMhA;`E w#ގm\3읙/[8p,^ͼ+pG,*V죸[m/ya ѕӝ^v4\8cvlh ~1ozǶ)x'Yeu!sKRu߲>bh[P}iw-͉XsN"EZsLojbZ.q7 J~e&ߌ#0`;kn+/1#xtljo+;35B44,)K|v\|V~y%ܯ'ncj1j͂0֮54]4bJNoh)ЂI)e44F} Dy3mo\+vhhXy !TE[-Mk~\ݬ?j_~K?1.J/!@6eֈ3O\؀Sipˌ!ocu[@+;{գTW; oggDRmE;'%"hggܸNF,D81v壓"|_aVf"^߼ىʭWٱ[WD;ê%A/V̮3a׽.X%B;zo]U*4'= f-.6NDlZ[pc91o_P|C piE8qG[!w_%ؽaMSv[/֔mlfWV Q"kVgA$V o6 .hgX w';VŸ-j؈PN%<;oS9'Q x9Kތ7/7J?/bƱc!0r- caa,a0#0XbxP,#(Y2iY -"ˢXd2cDO}eQ,ba1,?BX;"`CX*wҸe’DXEˈ!,3ư/%-ɰ01,"%-ɰ,er1,6rK%-ɰ 7eYDL8Ip7eYD0:,"Zɲ,"Y&$Y.d,"YXn$F,H$F, IlK"edY,$u͠r&F\|I/'I+dѻr IeỸT,:a,E, cF"^n,"eD zCKeĆf!т +-Dn2Di)˃gI$ye ;ӊgmgA{ DZ@uXKeda-Ib-g!X]1Z6MeY\CL.*N9Z0% k]*Xf "LKn`/e NP'P Ö ɓ$"P O j)j)j `G4 6i µbZI9ƘbZNm'hLG-1-%닁%b2Zp^PKPK"Zn ii i9 &rkKN#eIeiil!3BZHE Z߳&b$v-td--.Z&-e.ENx-u-U@K$ТR@KZKO- ,eT]r-_-iIY*WgalY*gų,xJ< +YOx}y,l8 ΢ŽLo,xg3x[W<Z.&!D'iZh/%n:Z+-t*ϒW< ,ϢA},r YH˲iz*&,n!-iIg!-J]XDB-He9H>I;-es<ˤl,rM 2,CK haq-qr$2,El-:;Z w"Zx)#yYr6ǕYbgs$G氱zAx7EX)`<; Qyc"g e LBl@vxDp:l8C@HMt(v񒳑Ƭ/S)gAArZgga&l?i {lvCp6gc{ g5})?l{ gS2$hsYM):rǔSBc0ŷH@78iA&H,M&H^iSKyIHT%2Kƕqzں + mY6%H 쐴ĈH:2A@M9n f+ Y#65XcIڴ쐵}$Kmlk6@۴ ۴`gL!lB x6!faBئe~6ۑ!l`+ 6p(CSYxLmZ' B iX ~{|&l"3A$|$i]A(m^n a7 Qc7c7\$y60I6 nsK` ramm6|%pHÿ́k9SB'puYqNA6Ƚ0 i4a6L4A8xmι;iO C?:A |7m\1@mbn6xALͲA0r$_㴍%c!ps7P' bej"Aāp yq{0y1D$͕xbo08p( ^\pY`/En  >^7=A7q` X X1rd!86ɽ Km\2d ,xXFy.n/N~\o8Qӹw,NVtHroΥ@IPJe[NgZ``' (uK:پN߳:X Ng~:ǖk:GN [(%Zg%qf:Ro/Zgpi:C2+h:F 81uI`&:dyc_6^8U Og ,ϲNH懬NKqW$:]7qqNVg.:IxbubB:+yXJeCV۾(FJ$VPduOV7_6T9,H΁MȗaABR[NNABRWӐ ZEq0@e\JN0jޅVb:\s Etί Ӊ+"FNvJF0btʩ F\J#F b]Q'㧔 Zw2NfdT8HBOLS/Q*JS~wN*Ը[ŝNȱ;5u!:Ei) f!e@wĂTt)`NF(G2:ED2:N\$SX"$p̻CD9P$uC8D)]>:7P:Ew:NBSFB)t\Y:=8J@K Az:X7Z:˓?tyt +)&Q UTcjs2UrdS4%9,cCGxN gy'D^pU x~s)Bs|EN^gX(OxNUsJY;+!MNg%Ix UwBV=DELMs4MwT1sj&EAp k7ㄛYnwD &k):fЬGE:'SE&QJq^Cpa/榪:. :QhsPLNlS|Mxb-sm'ByX)vQj :WT>fT*tt{w# D1i4>f+@Qtbe9mPs"x8%E@g$#2Dq 'RʞT$t< 0P%:g#Y:gf1x":gf(sDl77謚fBt ?IJ%9$gTBt_%9|̍mjT(ן9%8(tfz<:(HN@atp,$ULΙMi9p fF8f @JWĦp耉',@LGdN&i89rlUϹVs\L>|tseX"/Gs<{2d\'\ĉƫ#s R85s,?'>ž$s[ 8LxΡa$EГtN),$8 M8's%/G_I:]I/B8ǿ|9| 9=o A& 6 a*tNOZt* : .Af%B&sV5098 :8TaHtAsΤsr:g~SK&!Sw:pay !:M9A 9U3Ka\%:ʽt-FkXk 4Hbt-6PȜXЉAh03t',1:Iс;ԉ8fDF')dt2U2:f'2:^4s&tT\j1:dt.fXNgrDt@tT% >JDZM}+HUO$t]  )B#m@":U^c2:zdt|bt dt[Q"FԓѹTaЅܜHs3&D'ADt@ )t8-ĉ np@DzbtEKFGbtجXΙT!:t%*{V#D'Dt9RDtVɧ t6xdā ,pGF$! .B`Z8EjΙ3S5EYJ] $sg*1:+ ,E"!J:d'!%qJ"(^!)&'( ")凈`@t䟄xfBl<,g Í ѹ>"CH#Z)|`T ^ n^NO(Hi q^":X Dǥ*vс@?`=>R с5A`[YrqBGh  V"3c񬧧:2gN : x :ZAWs@2@r1-  B tG*:pYrDB?@:غ[\o?1r8/%P4^QrھP̪ .5Q<׵~ kOuҬxnsܴ?rW߼Wghظ_͇i谈6~͇ן~BcGfwk/_3!i  ؟Sf?|s2^O_'8_یbÑ=풭ix1Th<tO^ 'ؿ;Fb W?$N'ǀznO=2KӏZF2 =^8.{y|"cKݗ#Vf;}"8wCc;/؛<"/k&o:=?m&XeaO?R;{s @i|-};? s]^!X{s1Qp Nuȟ~^9ZE-fȒ^1?{Ns}7Zӷ޲l9Z_0/h^q:??y%Ы?[d+^~/jHb_l߯?]]o>a22-ހ~/~jـ ڦ;)9QR!GiێJ:bufu,Qp-J:1OvԻ;qt9Ё/@rY@^՞kR/,Ne7wKHJ?Kaq`>dJ\15v&24%2 n [9C8ovKeoaaq2x洄aqC5W:[iKMd9lP9X֡TP9xC#dKxB21&K M7`CP]PPbC@` <LDaBTP;LQڡ 5v((G?Sk|: ܈j3CArW;<VҖeFCܒp}Ϻ[(1QPf))x(J_sJCl\%<λ oࡠo*>!wŃCP#GC`&-H2x!wI79;얐;ؤ[L CLT3 Pc kޱ#9KnPpxKICABʤTj3Y (wٞqC`m[2|a_sK:; meOHj!x(Nŏ]!w-!wxXǜ3+aa3'.`tf*QaP<[)_C`e ("G,B`^> GV/ ?B q&fT78M#q5!xpGYKC"+w+5ӄ⡂ T<얁k]xCJ3Vvq!xS5w_b}8ijɒ;TH)CCP*X;vLd)x%*SKTKZpH|ڔ#©DDQCS!u%tO&Yҡ,{2ҊxEtkS"j3\!)t-5/BDx:ؔ4:TW(CE`p*%С")t؉1x,Gs& bM#w4*r\O zV%$ss CR4C|Xӄ̡l'E!soH͒2:X\2%<ٙ29ԙ̩sPsp:y;2S:v(Mt6p)M/u>]s!GPP`cRPa!tAPBCsEBcM9:u>D;Ρ!sB]CBCBu%tBS{.YtVR~4l:QP: 띸OkH/:뜗sh^ pOE ~@CPOZܟl2h4,fB:3SjˌshXĨMZ|fisʡ- UfQc Cby>CАצ*Trh9ʡ5Q lrh^- dKGҐ94,ZYbR2/ۡrh+!3U޺XU CsI (݈/!/y7 3>.=D)%> mOP]JuKyUꐪ^|g[9on:d#:3pLƈK3[+eL->5Ik[9W'a:?zWR{EL=z137GЈz> ˰{whۑ'G7'ٗ1ѽn:5ܢWr}U h{$\hE\k*T\Ǫc˅2p2h}3 @]@B|+XCͬJu,Ctnտb {kXa1Z!F̮Zb2i:r}K4 $Jw3׺34/j|'\W#\{߹V :p +YDe(NAa`ܙU(ꀈ+J‘ p;Dtc\*1#H2BqOqY &1X35aAH͏A̸к9cG@n<>_eB?a)D, vaw`00Zn"d3r,)^VlO3|v0b dQ@l1PW F{ S`"#=**dWԞYNQg K#T Rb/3V-:b<i\bS—.#J9+S7yڷ%#IoFx4r)j-Ըko{uV%=6~gM/F 836qL~h3 9p[2!OI ƆwaKsk;5gnΙsf Z a+sgzϦ{T͏6VS9ntϫ _еֲʫ6 Znjk~VUF!pqG5XjȖ嗹cOsi 3}ϖ\{)Rjbpc+A%vjc_ihژ _'\3`.k#Y0\{5s_k W}u^b[IsSt΍ylQphv@qmώX s@A͌dEM€XB]/.?{:GJ{r&#tKbfvJaSPrEoHqY J$2qg9>XR2*7 A, ANgݠ A5~K4#i S2) ^ L, o[«,,[j6At~nnqr3iijVUQS@ppC1 sv!3|>jQ[ tGt,\=qA9urdwUAĉcs|lz$MY.)8ר{be`#Xړ ^1@`i-=EllT2mLv"ґ}fqv g 5kLg9GG2Iά.r4K$@$9x)/vps}:Wl)dj-J^BXtˌ~X<򙗩9E 05&%cp0{ѳ>je=s=Zh@"s|# & ^%q,-nhd~%>oݒ(1;I'N>-I̫tт7 {B4QP3y*BfL7HLЕ6HD!QB@o@G/taR/H+í'qĝi%n ?K݄I@;ۢT!wgKxAFU(W~_͕T KY,&^kee`FԒgցq`Yߙ6 t_]6 )tN+Biee,Љ\ :1%bYIb0faF ܠVchUc0غYtDԇ2CrO f{HK<HnzRBֆ- g4CTbvDZxmQlRi s&8Q}XN&Ѡ<nkn(-EzYҢ6әvmoU,lˢv./tQ ʱV^7T}1;faW_ f`rsɰxU(Vfv7&r*TkD)7 eѸY8[n9;fh,<_j 9-vǨ%fOx21jE N7 gjg>וG~\CawKn /g;wOfΑGD؄Fig,|}'mЉ[9zZY/gpalSYx.BJ"'a):t/t;P#LNw?'1Gt7 |5(ZhY`&,\fJsfiYʱ'Zˢf 0pUwSmf r^âU嫕/fmUfxy a.o̅}H]TG}̛ gG.22x|قwcُ ``+> rܧA @@X"r_*2MfVv n^`xzIM"I`fa@*Tdj05A/|;ΣظUX!4h=a;Àĩz&NЛGS,b2L]/Ag_ g-$. vbD`QdԳG1rOSqY#vhoa b%0CTU&gHS}l-7O," TROvTL~'H=gw"m+)\mPu0r s(7 2PnRFF֣͎ɺ#kC$3p$XH;|lL)3Hы8vy<[+NYȽj7澟[b4xKyJ{O,(_60w* ľ'!j0[,b3J֠9CPcd 9$N%'̡bᩩ~m}Imf4;7WQ{[n<8ȝ{z'VAӢ-e@,ಙ%3 hջ>r;&ʻI,mP?vҠiÿ4Ն΢?BsܵKQb WA:\ɕ0D/&D9*6 lEpƭʀ p@cy, 83YlBN0ܒ!R$nlB2bрmb6l q<b -`j&R>C%U$0:.)&pbmtB ~ *ޯx{\K~bY29L[X򐀻DC!v&l!$.ڔ@2]'F ·i- Ak-S l-aDÈNP`Bg0\Zk»x>ּq2ˑ l :A2 !Pf!K2.XǤLV$ɬ~\-\e>op .fb/9# ,Zg)A= cv`JC}62akٱ|yh|Ii%)hrGh]9P$8K־6$K<;u!tѩQeΥ&IYE*Nx ChR&ZYC /#8n!2 .MlAT@xO ^=^~Tz .BS<ԹB0 c| udL BI$-Լr[SRugɮ<k'Y.¯k./B,j0=c +¨$Ch6[7)ҮSߒjs;y)VrF,L|%@2Yb&\J{CD'dQHdXʸufia jDd %!%R:v¶K Z&hr }E1ߥS9JeĥlZ6!d(HќCd4bbWN=Kzb-,6"C+um&HPAhtA>>TSld+ Ub$aZ KHqrUqWJ2r cXZ\=$YR K'Iq 7]o [SNJDKE3% '6$tf f&SIJsp(PB(PWLɔ dVօv+]3+wCVt2M|[* U5W ,5b))Ei+_=dj)NWAD6eQ s"CFd☪|`Lqꇔ3d "HT3J>RVU~8kqSy'4}lPҒRZ΄*'[ҕLyYNQ. xww8+Lc,17)_|CysX$x؞7ʇٍ o#jި#m%KJ$cy s"HH@s@%_ySbHW-o'j&xhbX*+ɷJ6vqՑ?޾0t.&8Yt0|b:W1ta:I뭊NtnRYωʭE==EtL/JY ggy&T,hɋKRDKITEMT-|U qUvf],E8 x,vrG%twpV_xo"Grޢ1`"xoH&iZDY}f|~^DHߍ=+: NsBt"Fn&JZ|sRUIV='L[4k,V='߰zN9M YijzNbA9]L_D8A%H.lR@HXB:Jؽ )tSؓ)":pT/FV)&btwTTFK`QܕJQR4Tʷꕥΐ¥e-`,Lz7Ӝ*SٞSs.ݎwMK@b dPRR"vVTH$M7R$hm )t S_յ;a5'ᱫ꿬%]J1/NzNV='gFU xyH :DE'T,4)QII/ntSr> Ɓ0n<,D-d4)7<\Rs,G񥌬X%'ȀXSM0S :ͪl{6eHMGR6}%)KOm 9 칄rRʃ[tYIЪ%@ϒNYu *:a)*: eETfE&"FnWE'ÊNJլ40J|ˏ奘ުX4Y+uT VDB|^xN/ėZܫ Vj:43Rߔ>)?ςNXӄήZHES9]D%#zzNם9uLzNtsP)6PsJLzNwՉUω*tߙ%"9͢ZM4&5c+DD>o)*V!#f-19 XI2 4'H,-q,G9;r ̼*gr4U M^ G9NY$ :ea,gX͂N]Mt$tL*:%A0؉NC|-#+:bOͤ|Yir- :Mme~ڕ&yssF±@{*&:IdޝZt}S5yg$3O9Z޸' jS,!&ZIx(Y,ᢠӥSY)_vVtZgYѩ*:C4D*t ̂NwfvRA[< :MQY)3d^)twB;=u0Se_UDgۙ*Jz#OFXejri=fS}`R'DDq#ARH圐lQLY),4s /YSvʬ ʢTLA&{;[$!c4șr3\mJ tY VuS"t5z:-{:9-.RU|BI0\T>=Aӭ :AD :ML>'%shfN>40S1VUctUUG3cJخ|Ι`̮958s^*AQٚJY%S9Q8m.8ԙ|UtUt*ްMnUt*iHxC p$]8E} <69lN[y`RA4348 gI-qZUtBꌸ|9AaV9!9pɜ3KAmқdIO-c;1#S_z_~}yT 1ӡy;-W^֗ s-ׅ:j:Ht( ~}of/eì߾|%AT!x6O}͇ן~QC~NOpxbw!eC ~C%7.|CS!I<tOHhwYEy~OtcXoۺҎЦp;zyq~mʰe>:ӿ}֕?y&AlLr0\xw3ߪ -~ /%’ņ?U\s61[Wmww9r^xt.k7ؿ?^lSȶxb\/vz_GlU*?~BjOv65 Jwkr؜-o3`~qU'f/ss?wi2/KXNGl^>~NV=^ r/'$}Oby/_}ody\'wJyHwq{amLj_&(?܏#>j'CgCgw'?/QƁ~_slo;|$E+ȉ#1^<^ϭ%YZƼFOA> stream xTkPSg>'md3҅pkvmbJ XWE"!&1@.7Bn ^ TPZ[eȥauh۝:;v;̡3=83߼wy}`8gHZFv4X.++,GpY'.0+ Na/bp<5so_]fJLZnXKBqaFUI؃V"/)UH,B\W|"K1 {JYRRkHd&val/{[cob۰Ll;KXMv?89#w6Fs8B 8K AzdQ0߇2] 1Oo Nx{I#}EzKUE^ph(wQw 47~I5zm5^{^0[䠠n$ ȧ~~/):Y)iU`.Ů G!s|D]S(!hP3}!* 5Qen,.F&#s]Ķ6k;LgW-(˘#{Jsī$+;;W8ڢqA yoWReK5P[BUD[a;U"X2z uu'~2pNvnLʆ[)5DǏ}/G9;>͟tao/5yy,m8H !rt"_\KwX{W zDPn賺l.pABm 5ЁRބ.\p(~=9V|fcgJZAOI)ȟ9lg C-02G FIJLkpiK~كVYEl%Mri5jG4j n::PlB5T@9p؝Yp\~I<ǥGF,jW˟@ E>SP#] #O|>_g ZUNqb3L r}zݟyf~*?XvCUϢ}pU.=֖Kye(mZams6B5[z݁{#}vS fGZt\h@4J0E@#/@h}͎jo3쥗(dx_x^6  =RIiP77SMqbGt`76UG=V8NWGO0L|-$+MywIsnkub*j,pc7+|h,h]TU9z):9ףmciz^#&I}tAnXMݞw|'>90Wendstream endobj 94 0 obj << /Filter /FlateDecode /Length 160 >> stream x]O10  ]ZUm?eB:gׁm_Xց$i, x> stream xX;oTGND\)USލy?"Da^EJ@z׬׀ON_"M|3s\& tgΜw5a6߽㊑u#4c3FOz9WRo Ri Wꛃ2fx˘\fruerLj;W||QB;3#9亗erE&:θz#k=Eb MNV3,̂#̈2 By#Vpj}J!eNp}KF7>?׳բ/ZȭLFaVm`NP-ͅ[Ta5.ޑG*QUarXƕOZ8)ᾝɽjHx5ytjtwtw^n?qch5+5-gNj\yfu6y?_|u_>w'՝q%e4-W"egq s\#BC R:\!r:RN)D)pJ)#R-#L-Wb'KroBZ%2!R3Cqjl#YE &py *p2Ypw$z DQp2*XgZ D$UG@I+,+}awPz%<(HJ-Rj^E, X8 &1*ڄyq>+C#pe/D{AAHO{xz^D.^O6w1CD9 MrPyO7~㬽iPI>] EdHYfcu>hOlDgIR!i,C"2;DOJ8w>qQV"2I4Jb'ucR*D, N8d?Ei5VhcC\|4A2b3BHgØ 婸rOJOmz6֭`(d>Uj}N@Bu!ͺm.gg?wꍺlPI*:?IV2o! *V^$O1l ;:gDHnj$ Ej־HR,%8w:s * %} Z "rQGr `K8h)N$P"..C]n=wPWoϽP,K5Hv+4%>K 44cvq&zyHFn+TsÔLTJ]PJHv)Mk !jMΥmtFze ߓ!/A`Q ;9 (6oZ `sYBz5dlqL%c'@:X=#t42qӝ,cmH&P%vij YAݏ?Gi˛Mu?O9kףQ}'Ƈ*G/+,Ʌu/9뽹x)>od0s{bguqxސw+KhspWWpx*[0ua a~i8$~gW*֎v=@mg&QѥU(j~9S֦U6ON/,qg\ztV-J&Y9njl}{tVsMٝ&Οբ'E?7N-[¯.5MKFs<̞ ƯWHendstream endobj 96 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 128 /Predictor 15 >> /Filter /FlateDecode /Height 128 /Subtype /Image /Width 128 /Length 5293 >> stream xuO7܍+AE%(.5j\!QUt}79[=мr>f];:gXћљQl6c>nlmmE;ݰ/w_OG矃XPv [s^+ '4}jQY jXl5+zԌB)cT_0$ZB &4_=oU/] Οd,":82.t!:)6__50̝*` W-FD {FB/Reu ʂ۩&,pƪb5?uZǩ duj?;0k$zH}'7)hO?-``)4k© Y Ѵ|d *^20`+U @ h9q%9/!4 CĀv`j~&EXT:G\Q{@;8r @]VZ ֠bX&& BIIz}9wDmI;1yUz`4D_o@4^7zA dꀎyVP5>"~pfFS5/Z L)&bMB0\PWKgOBS}DNbt7#z2ER+P>sQk. bP D}@WիW49;.=@P')Ͱ 42UVrTߑEb&GG P?*4'E|MEIbAD`c# ?conQ.]B@ "(Z[nS 7 w}F@ŋ]g3 >0T~ mpH( *; D *(Z fO?|DXGӸ[ ]"GeEP2% USR>cEKi.Ǫo1w'@B4 ;}FPǵ_\WX&ByS I\6>݂qy :"Gy"%pGsYxMSF P~p)QsRbSO]xwARiz-&*@D3p!$htB:sCgjYۿB@ox4CnȀJ}K|ЍÔj6Ό(Vdžӟ+w#:6( >%Q`kalO't 0J3U}`kIڊN"\!~;R?ՀMCO6@K$+oVaMhƍ6OP!$&Tx_/~P /P& IJ(5K{nV0/O*mcd"}\ia !ˀ MwqV[uR||`7c`7 nDc`Dc`S ko$׭P f"Ł{jc7B_Oُ_KGPPP}hD {l|oY7^{ ρMТgԍN 4Kb!v#^y\o5wI =fgI V1{Ic9uT 'P> 6zv.aFcZh}"e_ Pbk8 t:"TH.pjx(/Rm=Àzra^}BqyT28T~I1QQNO1D+9Fg[Uǵ` nD0@Qz ~RzqE߃?xǪJ!CG 'y߽3:;z.ⲿYG0PQ}T\U5.D?ꞿl&tDa ʽ+H!@a#tL6wє^nI NV)'_؄4G"!D$6~i-?] zy7xPq 2hz?+k!K1\Y`8 (ztU2]mAQe`4E0h@#-kFW^` +z4 ZUmZD9Jo* Q`,dY *HtEց Yi2GnKPPF(ëj&: ##z?wn D+v VWNP'I_'xHGӑ_9[#v'xvm'}<m.mwCQC?4>u#P-fST8z= &,|S(_ ؕk]wE`c#kFjxwV;zFg@3R>LL?~G*l ufD>Vׯ EDp1wT}aH}:/,#>`轇@TW=pgO 0l`9,xPwb6|k׬O?m(J ?~@F}0gY;{ @珵 ?<a|0qH}͟ᣯ{KڿK^$Sܑw,1|v.>۬&ny=o1h#AS}t}g\.?;~`%O<ңVwɣ?Xw._u{\u?~< ;qХۯ?RǦ}0F x7K{k9G[qɣ3G{oRU@s } ,N↏P ԩSBzǠi)  k;ac̩VW_r'?@KhGo_6=`_ӵf7RW>Z' >:d9}4+7>ń ܏qתY ދW鑁qͅ_K4|O8ۿN\^ڿGc^LR%˙3g"#ݩt@U\ % i÷jS3;N}lWԓDDG 9{Ӕ]L@b^6ܢ^G@3V}=5s(k®K܁7/W\siM3G"7p  4{oW[ Ο?b[Tz `!nB+~mHF|ť"6P.&u`6%6~k}.\б{v8P(l]uvn͟_ŏKDӋ/D׋YtAˉ55U_7OmV m;l|D\K.aF ̀:fnrWtZUvG'ΑM/_=d* ]i\FDԁ) 0EPlx$DWwLu5Tz*Ea~E^DDנ@{>nM\ > stream xZKovKpNrfpY~=ÊHK.E.r) 9_C.n8_uLwΒR !lozaoσً31NF:;_ysy|ќXs YnYsoRtH?ťy#<1c4g퓳zse{6cr9/nϿϿ|~ݔ`^FH.;Z)2/KݸS1u9ҭm׳UBv3Y{x<;"-!{pX|\09csQư;¾{51R67Psj:?1>/fOk@u Sўqv>z{/P>ۻ>d5ۻ^l֗ xh>;J~8{p͟?~vw?/}y4JN g "^F8H>W'YYhaF[v3 l%fJ)2ZRL%%L%B*TRR*|~\Hd ܁V@(E 0,¸( !h޶8j"aęjUWQ-,(a-sS!hY >9:=>j(Lx#H+%07V`̊x+8ȶ!,jRJ !;$,TRZA*TRIB͡ A <$4!" 8 CyE_Cm%A3Kh1@~.ec{l=wNv}=_Hİa]^W̷0}KQ&kᖷ Zp9$Vրd.6WH`_8D&n.09Ƶk .7QmܤS2מ.cE {^Ovk<;mx,7&+Hc3LovD)`326G Rh'i;_9r; Q@Յʼn-*:{~FO m2I/$sپCBٓ|F}4phMz кjt:q0 6dW)<rvuK,iJXsk[AM:éT{-6: jϓ֜6#`Yl=%#O!9HWhϒR R<ʍ*D@?*@'#;[CTQ ÛG]`{tM"  оenjq0 sCЭpAAK]cFh5 ~ʖqg[«qA~n]±f4"'ì-T,T "d&RXO ˀri* _:& #2}Uz8vrW,b O9.Rjv8tLb:rӣ>Ã!Jt^8lG6LDyyoM|b+*jT#Jا~/YU iMoBR*{"WaHWSfb)4$ζm_E.p3)K6]lS& Z4+XSL8)Bl2#J(m0HѨqp5ϒY3-;lpxS-ѵ*d&)q<\, 2xIA*ЦUk*e^)asa/~&y`y.P&AC 4"x(4`aP.Y!A"iXy/bB [ߒO{۲pS7)Zq.YQt4J%'8'rdY8agxcGK u )BmwݐlRLDZr)e|7[a]^ŎrJvW:zGU#WEqPiANbf\KYxD.*1NB2úZ%UU7YVO[U./0UdMF L\9dLG AoЧP$aWQ(ǧThwU:.F˼¶a2iҭMf79ңK&z &!ݫ8րHD6^W'^:FNQe4ԧe{rD% :V-m7$)5Ѝ8dsC nbPu,[=2u0 PcmէGP1Ycր4ʒгu>y2AgŚ߅6]}sq{TT7_FHڛ4e+rL}K<-1^YUOi[mB^T\ -"Нilli'y,ۊ[ kҴ?VN:t3h`Pg-;jMY`MծC+x4o + ())#R2jF h//rq}2d̼\]zx"H?`D,:}r,1 Lp @i:C@T0u1*6^{8B'A@\Adӌ9otUs2Vl^I)f͝ :7e3V(pȨFTU3C4L_2GwJ:3YN2vHƋ588v.O<}LўNMk;2h_$Z\O0JEB< >&IUW
  1. > stream x]O10 TXЪj8(Nߗ,N>~l#GpƲ5 HeQV-ƃ剳B7OfϲUiZB 'mQt1 l.kSIT @s$Lg)CSwendstream endobj 99 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 128 /Predictor 15 >> /Filter /FlateDecode /Height 128 /Subtype /Image /Width 128 /Length 4764 >> stream xEŻ71泈""QxW  jB4Wfͬ9uzvcXzggί.l믥Zk1M:O<ߚqی_ ~z1-O30`}2 *ATHyJPmҭ?4e$q mKPhX7~8W'h]^e@ 72o*c@+<0tLy :h'VIV@8=3(=1 ` uvh7a 4?]8Ge"ңdbPS2 `74.W4RjO :x8&L rNm( A7L úJP|֭[4D9-X++6@[ "e oܸ{[' P8]ö6s 7B ^$A ! ic `6@y8HD^~] ͨu`Nh*S )p5gDV2(H}S_m%(J%2Zwo hs[" Nn.XW6tQ>@2%`_D#d[W (qr\;y+u?b?Av^(€*bɡO+DyȀv(֜ h .{UdP=YFE'~L@c`s.[qTU_ ￟` k;ؚeK 0;w! (?+AMu 2{"k *+o6^"a M̥I n2IPE]O2_  tl%N;eE>/Bd0 [ևIBB *S ]/_[һǠ,}H4H<4||V҃=- CEi ;wţ@6W%hk|!:&#wޡPtt vS3O"O^0~.#&cPXr!l%^݊Q2"׷z{" b{UYbq~A Cpo+iy@&D* U~V?o+8 M]{ak+GUb0Aa$@J&0 I1^u\7" [v#Gf]Qĸq\_{5QX %(AM8Hpr$0 ` ? :#e8 AbTzneST2wZm1 CS&YfE tc W=lji7+yѺ@PFzeufԏ׼>5 }B0dp jGGI*vP1%0QNaɫ?wm/Z#CSG$(3MB/#Yh λyzE\2Ec+0%AڍZDB뿫 VH2*b?fڙ)8'W/A@@lGQ#1/HfDg˗ōs;Bid+togn?$=*%ɿ Ωm?C.EfP0S Ou?ruB#eЭBcj~;9" ttwB Y6n TT?B$ߺj" *ZidM̀Jn:`/6 &>(6-Lk>^v\ L -ꨟu yU{Z8%hEmXԫ?=7"ѓ0{ G= ˕ DNGa՗ΤbGY;O 𧩰:#[[SJA[I2G bH>PeیΒI+rkY7I 0c'] Oe\,~rChm Ż=vnjw`uS%d݅t·%jI Plq(wxA<*jH6 A3~q֍wnV}!=bꎧEDN1,.o?΍"$R_3#0i028((9vİڣ?АBD>~:tUo=B4&R_`(A@"۰o)R_dyJGp6*{f(ȃI?`ƚuG䭊¿;hξQh$GdU$d`Juʠ 8ap# |%Όa:#6TYz + k~a ܰȀ.TJ0  1F\%aXdچmJ&tcyԽ7QIDY> j*H^U!)ja#tCw1|6 h,oyLLрvҫ?mь.p੧aP)[). 2 q{cߪ?n'6;3u'.ip p q 5͑v47>g_3΂'x@(k7ۤ8!ϴ$A^}ZQ6 'vG+H}#Ǣr $S|h 1tir1}4"n/Tبo[T8d< ?1g4t!v.pg6G5 CB{hvA*z;cxgX X(+S܎D]:I&%oSO,>6݃}Ey>endstream endobj 100 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 128 /Predictor 15 >> /Filter /FlateDecode /Height 128 /Subtype /Image /Width 128 /Length 5049 >> stream xŜ=E_1`Yʲ, aHH,@l{=uw`T3S]u{zjZ)ezmȴ>x`zǴYkNO#lθpQ{tm:x8}ܭ+Z]}ڎmfO:M.}wvP&1ocZSj$]R9&k[>G&c_mn I٦>eژyȠS9EƁ 6LSfk݋b՟:S""g@4i +2f!"[~ cN?2XaS k P!]SPu?u- ̋3e`9yI5TSKH"+)f(t>KwAu8:ր*SPԺ2+Ӯ}O&Ym ՘ +R՗3AW`\t3H?vրn ]1(2?2Ov(эYȮpw@?Qqw%WʼXT._5ߕ_w[FuAtk{*=Htg6@^}`MU`jHA]p@~Wt8up&pN.h4bs+aէG@@@N"] r(f#$`@ayEt#PM+E۱w8JA7$dM+2 a&+vD8g*@c2?GD*XQ<a"8AmV_&.Z^&p Z w/F/tQڕ0f]|%k@Ġ᩵ܕ) 1 D#o.Gv(ԅ@ D ~DO_(xxBNz k`|8@ߧGZFKA (>Q ?(.ǜ!X44{ˆ QݑA$kCtw,L'-Y3e@a-DJ(yg[l" -lD *`spETjoF}|J/sݻM;"|)h{(#g6?QopY( E) BQ=JT?o25 "8$0}B]ݻGgݺZ_@p'+eLj@A4Z_$jْFqrh(w8Qr;,4|GO^RQ_Zu[i:Bȥ ] fUPmE_8/U(DN}Jh&~4:pnyϭQZ jX7p-VJ"*4EgOAV>3zPᒘ./YՀ L9)zIA~hZX)D[U1ި؏[]'#q&)Tw'|&|"y*f)*G;2>q޺&Z6u @J܏R Gd>hQ.Ha@͕:1A?D G@#'z ʲMG`ԠS+`Rԩ|AE[?b5eR >e۠ӉH0@`ލ`ؕ7]82Ha5dPܹcuG+ (rvWhZ{dg!aw;9&"!,MDIoOGV[otN>9)#aZ @1XWXA7o:SD ֥#:OA&ȸ!c޸q6 f!P0ĕ  .+u~}5cEUaj3Cb畠^v _E JG.!d`Y*huYP2>W^3ZP<@]%`Q,ˑQ @.,%$D@P." I{W\[A3ґv@Uc]y+\|9:B2X/X"4!ҥK(coOnr&hqsmu&8#IkeE%A2mL _}PM)^,v+he} 2M1)2d$Š@%zER7tDd2gV3Cp 2&W \?zhvȤ'z饗]cnw. fm40ui t(%mz[҈AT4|`n_! gݠM086B~e^q / `VR]D[ ZT8?'CAWW<*JO? RR=z1Q'`[Dw1>q>;> i} @Eq!OP)+.&J"];gs %NGJ 0~RLPRQkU~( kS* ];yRuHu_ `f맞zj%)}긜.0X7'Yv z @O[NRZ \c)$,H_ f'x'ŌmgVe@wڀvUF&(8Ae8@7jdEwpɻ%`t+"2 l ՉȽk JgNXH">e^tG1! HY+wyeb r'b|:\xj!!py{&HzHnԁqHVXJ9… G+UE ٓ"L4|f=/:T-_EE}: ;IA=ꫯ wٳLU $Utӕ["4].$1hQwc.;;!:6D@ilE/p^0Bwa !Z=)ep|| y`dĩ_HEHP ]yQCZ\3h5H4nX$ m Dwe]=R k7,.N@_ݙRГ| ~:^P!S;6T? J*N!! HqF>+H1 p(h]v_GqU4m?vZza @~{|;OA7o\tI鑁IDRAs|M;]ݜpT?€Mc>{i@էx?@& _tq\nBEwPq"D K"1 }v$=u,VnS)`e* xκ؏t8|w$#(dfD3xwo2t 0T~& B}T)_5y~-pCDwG}jJS͒(sDB5g?u-LwQ#自 5lR}f{G:x_,AYu^2&IણG  0J^S pѢGAu ˸ 6ׁ !eM;]ϲ/P0z2J|@e`X`WdgNc[Vmǧb`*A$]87AOcELu&1=Yȭ_,ALT}4;UlP;"M"nIn1(ึ QF.31Ӆ~.̕ KAv4 ZB"n> Uyh4*w´u1OAb$?ԏ>;,7b@S9 [92@vJ2OfJuJ6D5`1C5ȭ'ƎP? ;P}s`rU̝KDt͇N}P>eP/)mS3:$WC4"]CI9իW;i gqu~;h`'#DgnE 6hI]>pş8>>dk} %qZ#: #: (7߈" +S9R@yZ*>5I]*/_tדg-)"и Gs/žS`cNP. P+Uր >wͼ@沐=2/!0߂,6B~v1Q'x1)h_~QD rոۙDy9N1 &[?fMendstream endobj 101 0 obj << /Filter /FlateDecode /Length 5220 >> stream x\Ks$qӪ÷%%Q2%;(Exb!b1 GuWVMa; /}xN.^BӓgN>;}7Ó1ON߽W4m78{u8slUE??Q{eVZ)K[۰)l)Y' Ps&+3H+lAskasنa/mFxc MJzt֛iw\6ӧiUyY`X@T=}_ϛmnqŶw!Q+9"pdۭ1nƞX6YvL1NXu=U?o0n6_fDwAc"syD=;x@^;Žu̒o

    Yp]pTr'.En0%ri Rt\f(P ?-m =-D|&ًg +2<. ]58?[$'6hH^1LD-vhXciK{ӜbMsͭfy2 0b$]=bS{I~=}2GFȉaoAׂ-Po[ >Se8[!Hכ9gl,1.eQΦMGsֶ&*i$"휙5'n Ff[.&n<Әe9km hyV0 9s艵'CD߬B MդIS.3%wlӘTS91)9o&Njwtޫ&k}GHǜ(cs9S" i3RM7|&6!ddi-d1% ^ӑ& _++4vh?Tޙhnf0&dQpRVnX7#7BxlsR')1B4@K# wGg\`?n5q8\/biQo5 x-rGn!L&?l9Ɖ"a7B"bMŒ3(MgƉ7ħfιVvn} Ƈ|IKV~ `M{R\_]+~masGKr L+-`HE-Z4mVKٍ3D?_wR9AAh'G_IhŪ B&cpPĀ]]8arƥ9/4@~io!;@Fs'(p`3ZsA 2TT$NLX?:y@`OemC;XbF8< AN+A{!Y?拒HOo=@cVe[:syAq)c2`{o) !L9I*73Z~+*%+h!ֆ< G+Uk;Swq/Nߑ_S;=<SH*v9Kk*וe:W28g7ܸVN!v }:_~84ѱ6(G AXw%| Sl"]χNetqCUy !)>}5i9 Z^}[((3^*7b;lLEIKI" ~H|:xd؛Ǒ^L* 2}7 HWV $YǶ+'7@Bpp `4F +-# -)Ј~{AEP#jz_MUB"o@=]XxT89N2 T_̻P} ^@X`Q +|P%V{hƺv[NNXE80w#%ՌN_&4%<4yc( S7sќJR 9>! _J:1RR хt=Ł#ģv?@`ͥYÌe+ v2~^cӹM[m7!8# `ߊ~X9neVA=;gy r_2a6/l A2vP.}!Ijp÷6/E4u 9 pnL,2)QՑp[nZ* h4-C^$m/XF~HP VK8'"B^ױU30qPVWň0^IQDhU W 7cQ: T/8v&D3oKjy_rt޷:y9L鵻:5c`;)g*eZ m dҥJ2{^v4YK947H (8G쭠.oRvf ӵR}`ams-Y sWdR.DB֢c#!d$ ( ׼TcdACfK%1ُX\.,&,,q3/,N#y#Zi$%'e8E,xve`@46-qpq*(t쇼d paMAD#3hq9by r|&C  ~&kԋ {y,J[,O\+De =mFrOAYіOq}n;=ݸ[~l}a3M`Äa!VXPP-|#y*^SVE+7nŨeXҾ2lnTo۹[O|o3*ͼ\1,x91-{qbg&+%gĊT!"ґ;b`L*%Z"·hfWp80u"E[nb_hyD3"%%w4OJ.p }aQ_|q|,lm~7M[fp2XV3O_ZQW7p($E&t1N-2i,fE6Kˮ1o( `%/sZCO^qbSr3r]BuwyUsmDO߬NH BG_d8:\UR;s Ps9 ȘU"YYe٨,Fxe5sXjhb8.2 !ɉ HT~G!Zͨv_X ByNdu̮f>Ed긼6 ^ʞ*t>mC2g-_u7&k AKw?넘S,5iHTO,֏8Oа^iÃ۬U¹fZ?bQOV&)j#J&Ζobq.=YM]]Yu=tcu{yf;=oaX9$B!O_+߻9[endstream endobj 102 0 obj << /Filter /FlateDecode /Length 161 >> stream x]O10 b C+qP(/ СY:ߝ|pFcpƲ- DeQV-Ɠ剋BwOϲ> /W [ 1 3 1 ] /Info 3 0 R /Root 2 0 R /Size 104 /ID [] >> stream xcb&F~0 $8JgA !(dH QD,A$D21Hd0{>X<4XI^. ɸ,,R"90>@@.؄ D꤂ݰ Ȅ[`{tlm<Dd/XvT endstream endobj startxref 162623 %%EOF spatstat/inst/doc/umbrella.txt0000644000176200001440000000000414141460522016174 0ustar liggesusersyes spatstat/inst/doc/getstart.Rnw0000644000176200001440000003126414141377564016206 0ustar liggesusers\documentclass[11pt]{article} % \VignetteIndexEntry{Getting Started with Spatstat} <>= options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) @ \usepackage{graphicx} \usepackage{anysize} \marginsize{2cm}{2cm}{2cm}{2cm} \newcommand{\pkg}[1]{\texttt{#1}} \newcommand{\bold}[1]{{\textbf {#1}}} \newcommand{\R}{{\sf R}} \newcommand{\spst}{\pkg{spatstat}} \newcommand{\Spst}{\pkg{Spatstat}} \begin{document} \bibliographystyle{plain} \thispagestyle{empty} \SweaveOpts{eps=TRUE} \setkeys{Gin}{width=0.6\textwidth} <>= library(spatstat) spatstat.options(image.colfun=function(n) { grey(seq(0,1,length=n)) }) sdate <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Date") sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") options(useFancyQuotes=FALSE) @ \title{Getting started with \texttt{spatstat}} \author{Adrian Baddeley, Rolf Turner and Ege Rubak} \date{For \spst\ version \texttt{\Sexpr{sversion}}} \maketitle Welcome to \spst, a package in the \R\ language for analysing spatial point patterns. This document will help you to get started with \spst. It gives you a quick overview of \spst, and some cookbook recipes for doing basic calculations. \section*{What kind of data does \spst\ handle?} \Spst\ is mainly designed for analysing \emph{spatial point patterns}. For example, suppose you are an ecologist studying plant seedlings. You have pegged out a $10 \times 10$ metre rectangle for your survey. Inside the rectangle you identify all the seedlings of the species you want, and record their $(x,y)$ locations. You can plot the $(x,y)$ locations: <>= data(redwood) plot(redwood, pch=16, main="") @ This is a \emph{spatial point pattern} dataset. Methods for analysing this kind of data are summarised in the highly recommended book by Diggle \cite{digg03}, or our own book \cite{baddrubaturn15}, or other references in the bibliography below. \nocite{handbook10,bivapebegome08} Alternatively the points could be locations in one dimension (such as road accidents recorded on a road network) or in three dimensions (such as cells observed in 3D microscopy). You might also have recorded additional information about each seedling, such as its height, or the number of fronds. Such information, attached to each point in the point pattern, is called a \emph{mark} variable. For example, here is a stand of pine trees, with each tree marked by its diameter at breast height (dbh). The circle radii represent the dbh values (not to scale). <>= data(longleaf) plot(longleaf, main="") @ You might also have recorded supplementary data, such as the terrain elevation, which might serve as explanatory variables. These data can be in any format. \Spst\ does not usually provide capabilities for analysing such data in their own right, but \spst\ does allow such explanatory data to be taken into account in the analysis of a spatial point pattern. \Spst\ is \underline{\bf not} designed to handle point data where the $(x,y)$ locations are fixed (e.g.\ temperature records from the state capital cities in Australia) or where the different $(x,y)$ points represent the same object at different times (e.g.\ hourly locations of a tiger shark with a GPS tag). These are different statistical problems, for which you need different methodology. \section*{What can \spst\ do?} \Spst\ supports a very wide range of popular techniques for statistical analysis for spatial point patterns, for example \begin{itemize} \item kernel estimation of density/intensity \item quadrat counting and clustering indices \item detection of clustering using Ripley's $K$-function \item spatial logistic regression \item model-fitting \item Monte Carlo tests \end{itemize} as well as some advanced statistical techniques. \Spst\ is one of the largest packages available for \R, containing over 1000 commands. It is the product of 25 years of software development by leading researchers in spatial statistics. \section*{How do I start using \spst?} \begin{enumerate} \item Install \R\ on your computer \begin{quote} Go to \texttt{r-project.org} and follow the installation instructions. \end{quote} \item Install the \spst\ package in your \R\ system \begin{quote} Start \R\ and type \verb!install.packages("spatstat")!. If that doesn't work, go to \texttt{r-project.org} to learn how to install Contributed Packages. \end{quote} \item Start \R\ \item Type \texttt{library(spatstat)} to load the package. \item Type \texttt{help(spatstat)} for information. \end{enumerate} \section*{How do I get my data into \spst?} <>= data(finpines) mypattern <- unmark(finpines) mydata <- round(as.data.frame(finpines), 2) @ Here is a cookbook example. Suppose you've recorded the $(x,y)$ locations of seedlings, in an Excel spreadsheet. You should also have recorded the dimensions of the survey area in which the seedlings were mapped. \begin{enumerate} \item In Excel, save the spreadsheet into a comma-separated values (CSV) file. \item Start \R\ \item Read your data into \R\ using \texttt{read.csv}. \begin{quote} If your CSV file is called \texttt{myfile.csv} then you could type something like <>= mydata <- read.csv("myfile.csv") @ to read the data from the file and save them in an object called \texttt{mydata} (or whatever you want to call it). You may need to set various options inside the \texttt{read.csv()} command to get this to work for your file format: type \texttt{help(read.csv)} for information. \end{quote} \item Check that \texttt{mydata} contains the data you expect. \begin{quote} For example, to see the first few rows of data from the spreadsheet, type <<>>= head(mydata) @ To select a particular column of data, you can type \texttt{mydata[,3]} to extract the third column, or \verb!mydata$x! to extract the column labelled \texttt{x}. \end{quote} \item Type \texttt{library(spatstat)} to load the \spst\ package \item Now convert the data to a point pattern object using the \spst\ command \texttt{ppp}. \begin{quote} Suppose that the \texttt{x} and \texttt{y} coordinates were stored in columns 3 and 7 of the spreadsheet. Suppose that the sampling plot was a rectangle, with the $x$ coordinates ranging from 100 to 200, and the $y$ coordinates ranging from 10 to 90. Then you would type <>= mypattern <- ppp(mydata[,3], mydata[,7], c(100,200), c(10,90)) @ The general form is <>= ppp(x.coordinates, y.coordinates, x.range, y.range) @ Note that this only stores the seedling locations. If you have additional columns of data (such as seedling height, seedling sex, etc) these can be added as \emph{marks}, later. \end{quote} \item Check that the point pattern looks right by plotting it: <>= plot(mypattern) @ \item Now you are ready to do some statistical analysis. Try the following: \begin{itemize} \item Basic summary of data: type <>= summary(mypattern) @ \item Ripley's $K$-function: <>= options(SweaveHooks=list(fig=function() par(mar=rep(4,4)+0.1))) @ <>= plot(Kest(mypattern)) @ For more information, type \texttt{help(Kest)} \item Envelopes of $K$-function: <>= plot(envelope(mypattern,Kest)) @ <>= env <- envelope(mypattern,Kest, nsim=39) @ <>= plot(env, main="envelope(mypattern, Kest)") @ <>= options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) @ For more information, type \texttt{help(envelope)} \item kernel smoother of point density: <>= plot(density(mypattern)) @ For more information, type \texttt{help(density.ppp)} \end{itemize} \item Next if you have additional columns of data recording (for example) the seedling height and seedling sex, you can add these data as \emph{marks}. Suppose that columns 5 and 9 of the spreadsheet contained such values. Then do something like <>= marks(mypattern) <- mydata[, c(5,9)] @ <>= mypattern <-finpines @ Now you can try things like the kernel smoother of mark values: <>= plot(Smooth(mypattern)) @ \setkeys{Gin}{width=0.8\textwidth} <>= plot(Smooth(mypattern, sigma=1.2), main="Smooth(mypattern)") @ \setkeys{Gin}{width=0.4\textwidth} \item You are airborne! Now look at the book \cite{baddrubaturn15} for more hints. \end{enumerate} \section*{How do I find out which command to use?} Information sources for \spst\ include: \begin{itemize} \item the Quick Reference guide: a list of the most useful commands. \begin{quote} To view the quick reference guide, start \R, then type \texttt{library(spatstat)} and then \texttt{help(spatstat)}. Alternatively you can download a pdf of the Quick Reference guide from the website \texttt{www.spatstat.org} \end{quote} \item online help: \begin{quote} The online help files are useful --- they give detailed information and advice about each command. They are available when you are running \spst. To get help about a particular command \texttt{blah}, type \texttt{help(blah)}. There is a graphical help interface, which you can start by typing \texttt{help.start()}. Alternatively you can download a pdf of the entire manual (1000 pages!) from the website \texttt{www.spatstat.org}. \end{quote} \item vignettes: \begin{quote} \Spst\ comes installed with several `vignettes' (introductory documents with examples) which can be accessed using the graphical help interface. They include a document about \texttt{Handling shapefiles}. \end{quote} \item book: \begin{quote} Our book \cite{baddrubaturn15} contains a complete course on \texttt{spatstat}. \end{quote} \item website: \begin{quote} Visit the \spst\ package website \texttt{www.spatstat.org} \end{quote} \item forums: \begin{quote} Join the forum \texttt{R-sig-geo} by visiting \texttt{r-project.org}. Then email your questions to the forum. Alternatively you can ask the authors of the \spst\ package (their email addresses are given in the package documentation). \end{quote} \end{itemize} \begin{thebibliography}{10} % \bibitem{badd10wshop} % A. Baddeley. % \newblock Analysing spatial point patterns in {{R}}. % \newblock Technical report, CSIRO, 2010. % \newblock Version 4. % \newblock URL \texttt{https://research.csiro.au/software/r-workshop-notes/} % \bibitem{baddrubaturn15} A. Baddeley, E. Rubak, and R. Turner. \newblock {\em Spatial Point Patterns: Methodology and Applications with {{R}}}. \newblock Chapman \& Hall/CRC Press, 2015. \bibitem{bivapebegome08} R. Bivand, E.J. Pebesma, and V. G{\'{o}}mez-Rubio. \newblock {\em Applied spatial data analysis with {R}}. \newblock Springer, 2008. \bibitem{cres93} N.A.C. Cressie. \newblock {\em Statistics for Spatial Data}. \newblock {John Wiley and Sons}, {New York}, second edition, 1993. \bibitem{digg03} P.J. Diggle. \newblock {\em Statistical Analysis of Spatial Point Patterns}. \newblock Hodder Arnold, London, second edition, 2003. \bibitem{fortdale05} M.J. Fortin and M.R.T. Dale. \newblock {\em Spatial analysis: a guide for ecologists}. \newblock Cambridge University Press, Cambridge, UK, 2005. \bibitem{fothroge09handbook} A.S. Fotheringham and P.A. Rogers, editors. \newblock {\em The {SAGE} {H}andbook on {S}patial {A}nalysis}. \newblock SAGE Publications, London, 2009. \bibitem{gaetguyo09} C. Gaetan and X. Guyon. \newblock {\em Spatial statistics and modeling}. \newblock Springer, 2009. \newblock Translated by Kevin Bleakley. \bibitem{handbook10} A.E. Gelfand, P.J. Diggle, M. Fuentes, and P. Guttorp, editors. \newblock {\em Handbook of Spatial Statistics}. \newblock CRC Press, 2010. \bibitem{illietal08} J. Illian, A. Penttinen, H. Stoyan, and D. Stoyan. \newblock {\em Statistical Analysis and Modelling of Spatial Point Patterns}. \newblock John Wiley and Sons, Chichester, 2008. \bibitem{mollwaag04} J. M{\o}ller and R.P. Waagepetersen. \newblock {\em Statistical Inference and Simulation for Spatial Point Processes}. \newblock Chapman and Hall/CRC, Boca Raton, 2004. \bibitem{pfeietal08} D.U. Pfeiffer, T. Robinson, M. Stevenson, K. Stevens, D. Rogers, and A. Clements. \newblock {\em Spatial analysis in epidemiology}. \newblock Oxford University Press, Oxford, UK, 2008. \bibitem{wallgotw04} L.A. Waller and C.A. Gotway. \newblock {\em Applied spatial statistics for public health data}. \newblock Wiley, 2004. \end{thebibliography} \end{document} spatstat/inst/doc/getstart.R0000644000176200001440000001154514155343640015632 0ustar liggesusers### R code from vignette source 'getstart.Rnw' ################################################### ### code chunk number 1: getstart.Rnw:5-6 ################################################### options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) ################################################### ### code chunk number 2: getstart.Rnw:25-32 ################################################### library(spatstat) spatstat.options(image.colfun=function(n) { grey(seq(0,1,length=n)) }) sdate <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Date") sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") options(useFancyQuotes=FALSE) ################################################### ### code chunk number 3: getstart.Rnw:56-58 ################################################### getOption("SweaveHooks")[["fig"]]() data(redwood) plot(redwood, pch=16, main="") ################################################### ### code chunk number 4: getstart.Rnw:80-82 ################################################### getOption("SweaveHooks")[["fig"]]() data(longleaf) plot(longleaf, main="") ################################################### ### code chunk number 5: getstart.Rnw:139-142 ################################################### data(finpines) mypattern <- unmark(finpines) mydata <- round(as.data.frame(finpines), 2) ################################################### ### code chunk number 6: getstart.Rnw:157-158 (eval = FALSE) ################################################### ## mydata <- read.csv("myfile.csv") ################################################### ### code chunk number 7: getstart.Rnw:169-170 ################################################### head(mydata) ################################################### ### code chunk number 8: getstart.Rnw:185-186 (eval = FALSE) ################################################### ## mypattern <- ppp(mydata[,3], mydata[,7], c(100,200), c(10,90)) ################################################### ### code chunk number 9: getstart.Rnw:189-190 (eval = FALSE) ################################################### ## ppp(x.coordinates, y.coordinates, x.range, y.range) ################################################### ### code chunk number 10: getstart.Rnw:199-200 ################################################### getOption("SweaveHooks")[["fig"]]() plot(mypattern) ################################################### ### code chunk number 11: getstart.Rnw:207-208 (eval = FALSE) ################################################### ## summary(mypattern) ################################################### ### code chunk number 12: getstart.Rnw:212-213 ################################################### options(SweaveHooks=list(fig=function() par(mar=rep(4,4)+0.1))) ################################################### ### code chunk number 13: getstart.Rnw:215-216 ################################################### getOption("SweaveHooks")[["fig"]]() plot(Kest(mypattern)) ################################################### ### code chunk number 14: getstart.Rnw:222-223 (eval = FALSE) ################################################### ## plot(envelope(mypattern,Kest)) ################################################### ### code chunk number 15: getstart.Rnw:225-226 ################################################### env <- envelope(mypattern,Kest, nsim=39) ################################################### ### code chunk number 16: getstart.Rnw:228-229 ################################################### getOption("SweaveHooks")[["fig"]]() plot(env, main="envelope(mypattern, Kest)") ################################################### ### code chunk number 17: getstart.Rnw:231-232 ################################################### options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) ################################################### ### code chunk number 18: getstart.Rnw:238-239 ################################################### getOption("SweaveHooks")[["fig"]]() plot(density(mypattern)) ################################################### ### code chunk number 19: getstart.Rnw:249-250 (eval = FALSE) ################################################### ## marks(mypattern) <- mydata[, c(5,9)] ################################################### ### code chunk number 20: getstart.Rnw:252-253 ################################################### mypattern <-finpines ################################################### ### code chunk number 21: getstart.Rnw:256-257 (eval = FALSE) ################################################### ## plot(Smooth(mypattern)) ################################################### ### code chunk number 22: getstart.Rnw:260-261 ################################################### getOption("SweaveHooks")[["fig"]]() plot(Smooth(mypattern, sigma=1.2), main="Smooth(mypattern)") spatstat/inst/doc/Nickname.txt0000644000176200001440000000004114141460522016117 0ustar liggesusers"That's not important right now" spatstat/inst/doc/BEGINNER.txt0000644000176200001440000000202314141377564015602 0ustar liggesusers -== Welcome to the 'spatstat' package! ==- For a friendly introduction to spatstat, type the command vignette('getstart') which displays the document "Getting Started with Spatstat". For an overview of all capabilities, type help(spatstat) View the documentation for any command/function 'foo' by typing help(foo) Activate the graphical help interface by typing help.start() To handle spatial data in the 'shapefile' format, see the document "Handling shapefiles in the spatstat package", by typing vignette('shapefiles') For a complete course on spatstat, see the book "Spatial Point Patterns: Methodology and Applications with R" by Baddeley, Rubak and Turner, Chapman and Hall/CRC Press, December 2015. For a summary of changes to spatstat since the book was finished, type vignette('updates') Visit the website www.spatstat.org for updates and free chapters. For news about the very latest version of spatstat, type latest.news [[[Press 'Q' to exit, on some computers]]] spatstat/inst/doc/replicated.Rnw0000644000176200001440000014174114141377564016467 0ustar liggesusers\documentclass[11pt]{article} % \VignetteIndexEntry{Analysing Replicated Point Patterns in Spatstat} \usepackage{graphicx} \usepackage{Sweave} \usepackage{bm} \usepackage{anysize} \marginsize{2cm}{2cm}{2cm}{2cm} \newcommand{\pkg}[1]{\texttt{#1}} \newcommand{\code}[1]{\texttt{#1}} \newcommand{\R}{{\sf R}} \newcommand{\spst}{\pkg{spatstat}} \newcommand{\Spst}{\pkg{Spatstat}} \newcommand{\bold}[1]{{\textbf {#1}}} \newcommand{\indicate}[1]{\boldmaths{1}\{ {#1} \}} \newcommand{\dee}[1]{\, {\rm d}{#1}} \newcommand{\boldmaths}[1]{{\ensuremath\boldsymbol{#1}}} \newcommand{\xx}{\boldmaths{x}} \begin{document} \bibliographystyle{plain} \thispagestyle{empty} <>= options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) @ \SweaveOpts{eps=TRUE} \setkeys{Gin}{width=0.6\textwidth} <>= library(spatstat) spatstat.options(image.colfun=function(n) { grey(seq(0,1,length=n)) }) sdate <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Date") sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") options(useFancyQuotes=FALSE) @ \title{Analysing replicated point patterns in \texttt{spatstat}} \author{Adrian Baddeley} \date{For \spst\ version \texttt{\Sexpr{sversion}}} \maketitle \begin{abstract} This document describes \spst's capabilities for fitting models to replicated point patterns. More generally it applies to data from a designed experiment in which the response from each unit is a spatial point pattern. \end{abstract} \tableofcontents \newpage %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Introduction} `Replicated point patterns' are datasets consisting of several point patterns which can be regarded as independent repetitions of the same experiment. For example, three point patterns taken from micrographs of three pipette samples of the same jug of milk, could be assumed to be replicated observations. More generally we could have several experimental groups, with replicated point pattern data in each group. For example there may be two jugs of milk that were treated differently, and we take three pipette samples from each jug. Even more generally our point patterns could be the result of a designed experiment involving control and treatment groups, covariates such as temperature, and even spatial covariates (such as image data). This document describes some capabilities available in the \spst\ package for analysing such data. \textbf{For further detail, see Chapter 16 of the spatstat book \cite{TheBook}.} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Overview of software} The main components needed are: \begin{itemize} \item the model-fitting function \texttt{mppm}, an extension of the \texttt{spatstat} function \texttt{ppm}, that will fit Gibbs point process models to multiple point pattern datasets; \item support for the class \texttt{"mppm"} of point process models fitted by \texttt{mppm} (e.g. functions to print and plot the fitted model, analysis of deviance for Poisson models) \item some tools for exploratory data analysis; \item basic support for the data from such experiments by storing the data in a \emph{``hyperframe''}. A hyperframe is like a data frame, except that each entry in a column can be a point pattern or a pixel image, as well as a single number or categorical value. \item four example datasets. \end{itemize} \section{Formulating the problem} We view the experiment as involving a series of {\em `units'\/}. Each unit is subjected to a known set of experimental conditions (described by the values of the {\em covariates\/}), and each unit yields a {\em response\/} which is a spatial point pattern. The value of a particular covariate for each unit can be either a single value (numerical, logical or factor), or a pixel image. Three important cases are: \begin{description} \item[independent replicates:] We observe $n$ different point patterns that can be regarded as independent replicates, i.e.\ independent realisations of the same point process. The `responses' are the point patterns; there are no covariates. \item[replication in groups:] there are $K$ different experimental groups (e.g. control, aspirin, nurofen). In group $k$ ($k=1,\ldots,K$) we observe $n_k$ point patterns which can be regarded as independent replicates within this group. We regard this as an experiment with $n = \sum_k n_k$ units. The responses are the point patterns; there is one covariate which is a factor (categorical variable) identifying which group each point pattern belongs to. \item[general case:] there are covariates other than factors that influence the response. The point patterns are assumed to be independent, but no two patterns have the same distribution. \end{description} Examples of these three cases are given in the datasets \texttt{waterstriders}, \texttt{pyramidal} and \texttt{demohyper} respectively, which are installed in \spst. \section{Installed datasets} The following datasets are currently installed in \spst. \begin{itemize} \item \texttt{waterstriders}: Penttinen's \cite{pent84} waterstriders data recording the locations of insect larvae on a pond in 3 independent experiments. \item \texttt{pyramidal}: data from Diggle, Lange and Benes \cite{digglangbene91} on the locations of pyramidal neurons in human brain, 31 human subjects grouped into 3 groups (controls, schizoaffective and schizophrenic). \item \texttt{flu}: data from Chen et al \cite{chenetal08} giving the locations of two different virus proteins on the membranes of cells infected with influenza virus; 41 multitype point patterns divided into two virus types (wild and mutant) and two stain types. \item \texttt{simba}: simulated data from an experiment with two groups and 5 replicate point patterns per group. \item \texttt{demohyper}: simulated data from an experiment with two groups in which each experimental unit has a point pattern response and a pixel image covariate. \end{itemize} \section{Lists of point patterns} First we need a convenient way to store the \emph{responses} from all the units in an experiment. An individual point pattern is stored as an object of class \verb!"ppp"!. The easiest way to store all the responses is to form a list of \verb!"ppp"! objects. \subsection{Waterstriders data} The \texttt{waterstriders} data are an example of this type. The data consist of 3 independent point patterns representing the locations of insect larvae on a pond. See \texttt{help(waterstriders)}. <<>>= waterstriders @ The \texttt{waterstriders} dataset is a list of point patterns. It is a list, each of whose entries is a point pattern (object of class \verb!"ppp"!). Note that the observation windows of the three point patterns are {\tt not\/} identical. \subsection{The class \texttt{listof}} For convenience, the \texttt{waterstriders} dataset also belongs to the class \verb!"listof"!. This is a simple mechanism to allow us to handle the list neatly --- for example, we can provide special methods for printing, plotting and summarising the list. \SweaveOpts{width=6,height=2} \setkeys{Gin}{width=0.9\textwidth} <>= plot(waterstriders, main="") @ Notice that the plot method displays each entry of the list in a separate panel. There's also the summary method: <<>>= summary(waterstriders) @ \subsection{Creating a \texttt{listof} object} For example, here is a simulated dataset containing three independent realisations of the Poisson process with intensity 100. <<>>= X <- listof(rpoispp(100), rpoispp(100), rpoispp(100)) @ Then it can be printed and plotted. <>= plot(X) X @ To convert an existing list to the class \code{listof}, use \code{as.listof}. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Hyperframes} A \emph{hyperframe} is like a data frame, except that its entries can be objects of any kind. A hyperframe is effectively a two-dimensional array in which each column consists of values of one type (as in a data frame) or consists of objects of one class. The entries in a hyperframe can be point patterns, pixel images, windows, or any other objects. To analyse an experiment, we will store {\bf all} the data from the experiment in a single hyperframe. The rows of the hyperframe will correspond to different experimental units, while the columns represent different variables (response variables or covariates). \subsection{Creating hyperframes} The function \texttt{hyperframe} will create a hyperframe. <>= hyperframe(...) @ The arguments \verb!...! are any number of arguments of the form \texttt{tag=value}. Each \texttt{value} will become a column of the array. The \texttt{tag} determines the name of the column. Each \texttt{value} can be either \begin{itemize} \item an atomic vector or factor (i.e. numeric vector, integer vector, character vector, logical vector, complex vector or factor) \item a list of objects which are all of the same class \item one atomic value, which will be replicated to make an atomic vector or factor \item one object, which will be replicated to make a list of identical objects. \end{itemize} All columns (vectors, factors and lists) must be of the same length, if their length is greater than 1. For example, here is a hyperframe containing a column of numbers and a column of \emph{functions}: <<>>= H <- hyperframe(X=1:3, Y=list(sin,cos,tan)) H @ Note that a column of character strings will be converted to a factor, unless you set \texttt{stringsAsFactors=FALSE} in the call to \code{hyperframe}. This is the same behaviour as for the function \code{data.frame}. <<>>= G <- hyperframe(X=1:3, Y=letters[1:3], Z=factor(letters[1:3]), W=list(rpoispp(100),rpoispp(100), rpoispp(100)), U=42, V=rpoispp(100), stringsAsFactors=FALSE) G @ This hyperframe has 3 rows and 6 columns. The columns named \texttt{U} and \texttt{V} are constant (all entries in a column are the same). The column named \texttt{Y} is a character vector while \texttt{Z} is a factor. \subsection{Hyperframes of data} To analyse an experiment, we will store {\bf all} the data from the experiment in a single hyperframe. The rows of the hyperframe will correspond to different experimental units, while the columns represent different variables (response variables or covariates). Several examples of hyperframes are provided with the package, including \texttt{demohyper}, \texttt{flu}, \texttt{simba} and \texttt{pyramidal}, described above. The \texttt{simba} dataset contains simulated data from an experiment with a `control' group and a `treatment' group, each group containing 5 experimental units. The responses in the control group are independent Poisson point patterns with intensity 80. The responses in the treatment group are independent realisations of a Strauss process (see \texttt{help(simba)} for details). The \texttt{simba} dataset is a hyperframe with 10 rows and 2 columns: \texttt{Points} (the point patterns) and \texttt{group} (a factor with levels \texttt{control} and \texttt{treatment}). <<>>= simba @ The \texttt{pyramidal} dataset contains data from Diggle, Lange and Benes \cite{digglangbene91} on the locations of pyramidal neurons in human brain. One point pattern was observed in each of 31 human subjects. The subjects were classified into 3 groups (controls, schizoaffective and schizophrenic). The \texttt{pyramidal} dataset is a hyperframe with 31 rows and 2 columns: \code{Neurons} (the point patterns) and \code{group} (a factor with levels \texttt{control}, \texttt{schizoaffective} and \texttt{schizophrenic}). <<>>= pyramidal @ The \texttt{waterstriders} dataset is not a hyperframe; it's just a list of point patterns. It can easily be converted into a hyperframe: <<>>= ws <- hyperframe(Striders=waterstriders) @ \subsection{Columns of a hyperframe} Individual columns of a hyperframe can be extracted using \verb!$!: <<>>= H$X H$Y @ The result of \verb!$! is a vector or factor if the column contains atomic values; otherwise it is a list of objects (with class \texttt{"listof"} to make it easier to print and plot). Individual columns can also be assigned (overwritten or created) using \verb!$<-!: <<>>= H$U <- letters[1:3] H @ This can be used to build up a hyperframe column-by-column: <<>>= G <- hyperframe() G$X <- waterstriders G$Y <- 1:3 G @ \subsection{Subsets of a hyperframe} Other subsets of a hyperframe can be extracted with \verb![!: <<>>= H[,1] H[2,] H[2:3, ] H[1,1] @ The result of \verb![! is a hyperframe, unless you set \verb!drop=TRUE! and the subset consists of only one element or one column: <<>>= H[,1,drop=TRUE] H[1,1,drop=TRUE] H[1,2,drop=TRUE] @ There is also a method for \verb![<-! that allows you to assign values to a subset of a hyperframe. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Plotting} \subsection{Plotting a \code{listof} object} The plot method for \code{listof} objects has formal arguments <>= plot.listof(x, ..., main, arrange = TRUE, nrows = NULL, ncols = NULL) @ where \code{main} is a title for the entire page. If \code{arrange=TRUE} then the entries of the list are displayed in separate panels on the same page (with \code{nrows} rows and \code{ncols} columns of panels), while if \code{arrange=FALSE} then the entries are just plotted as a series of plot frames. The extra arguments \verb!...! control the individual plot panels. These arguments will be passed to the plot method that displays each entry of the list. Suitable arguments depend on the type of entries. <>= plot(waterstriders, pch=16, nrows=1) @ \subsection{Plotting a hyperframe} \subsubsection{Plotting one column} If \code{h} is a hyperframe, then the default action of \code{plot(h)} is to extract the first column of \code{h} and plot each of the entries in a separate panel on one page (actually using the plot method for class \verb!"listof"!). \SweaveOpts{width=7,height=5} \setkeys{Gin}{width=0.9\textwidth} <>= plot(simba) @ This only works if the entries in the first column are objects for which a plot method is defined (for example, point patterns, images, windows). To select a different column, use \verb!$! or \verb![!: \SweaveOpts{width=6,height=2} \setkeys{Gin}{width=0.9\textwidth} <>= H <- hyperframe(X=1:3, Y=list(sin,cos,tan)) plot(H$Y) @ The plot can be controlled using the arguments for \code{plot.listof} (and, in this case, \code{plot.function}, since \verb!H$Y! consists of functions). \subsubsection{Complex plots} More generally, we can display any kind of higher-order plot involving one or more columns of a hyperframe: <>= plot(h, e) @ where \code{h} is a hyperframe and \code{e} is an \R\ language call or expression that must be evaluated in each row to generate each plot panel. \SweaveOpts{width=9,height=5} \setkeys{Gin}{width=0.9\textwidth} <>= plot(demohyper, quote({ plot(Image, main=""); plot(Points, add=TRUE) })) @ Note the use of \code{quote}, which prevents the code inside the braces from being evaluated immediately. To plot the $K$-functions of each of the patterns in the \code{waterstriders} dataset, \SweaveOpts{width=6,height=2} \setkeys{Gin}{width=0.9\textwidth} <>= H <- hyperframe(Bugs=waterstriders) plot(H, quote(plot(Kest(Bugs))), marsize=1) @ %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Data analysis} \subsection{Computing with hyperframes} Often we want to perform some computation on each row of a hyperframe. In a data frame, this can be done using the command \code{with}: <<>>= df <- data.frame(A=1:10, B=10:1) with(df, A-B) @ In this example, the expression \code{A-B} is evaluated in each row of the data frame, and the result is a vector containing the computed values for each row. The function \code{with} is generic, and has a method for data frames, \code{with.data.frame}. The computation above was executed by \code{with.data.frame}. The same syntax is available for hyperframes using the method \code{with.hyperframe}: <>= with(h,e) @ Here \code{h} is a hyperframe, and \code{e} is an {\sf R} language construct involving the names of columns in \code{h}. For each row of \code{h}, the expression \code{e} will be evaluated in such a way that each entry in the row is identified by its column name. <<>>= H <- hyperframe(Bugs=waterstriders) with(H, npoints(Bugs)) with(H, distmap(Bugs)) @ The result of \code{with.hyperframe} is a list of objects (of class \verb!"listof"!), or a vector or factor if appropriate. Notice that (unlike the situation for data frames) the operations in the expression \code{e} do not have to be vectorised. For example, \code{distmap} expects a single point pattern, and is not vectorised to deal with a list of point patterns. Instead, the expression \code{distmap(Bugs)} is evaluated separately in each row of the hyperframe. \subsection{Summary statistics} One application of \code{with.hyperframe} is to calculate summary statistics for each row of a hyperframe. For example, the number of points in a point pattern \code{X} is returned by \code{npoints(X)}. To calculate this for each of the responses in the \code{simba} dataset, <<>>= with(simba, npoints(Points)) @ The summary statistic can be any kind of object. For example, to compute the empirical $K$-functions for each of the patterns in the \code{waterstriders} dataset, <<>>= H <- hyperframe(Bugs=waterstriders) K <- with(H, Kest(Bugs)) @ To plot these $K$-functions you can then just type \SweaveOpts{width=6,height=2} \setkeys{Gin}{width=0.9\textwidth} <>= plot(K) @ The summary statistic for each row could be a numeric vector: <<>>= H <- hyperframe(Bugs=waterstriders) with(H, nndist(Bugs)) @ The result is a list, each entry being a vector of nearest neighbour distances. To find the minimum interpoint distance in each pattern: <<>>= with(H, min(nndist(Bugs))) @ \subsection{Generating new columns} New columns of a hyperframe can be created by computation from the existing columns. For example, I can add a new column to the \code{simba} dataset that contains pixel images of the distance maps for each of the point pattern responses. <>= simba$Dist <- with(simba, distmap(Points)) @ \subsection{Simulation} This can be useful for simulation. For example, to generate Poisson point patterns with different intensities, where the intensities are given by a numeric vector \code{lambda}: \SweaveOpts{width=6,height=6} \setkeys{Gin}{width=0.7\textwidth} <>= lambda <- rexp(6, rate=1/50) H <- hyperframe(lambda=lambda) H$Points <- with(H, rpoispp(lambda)) plot(H, quote(plot(Points, main=paste("lambda=", signif(lambda, 4))))) @ It's even simpler to generate 10 independent Poisson point patterns with the \emph{same} intensity 50, say: <>= H$X <- with(H, rpoispp(50)) @ \noindent The expression \code{rpoispp(50)} is evaluated once in each row, yielding a different point pattern in each row because of the randomness. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Exploratory data analysis} Before fitting models to the data, it is prudent to explore the data to detect unusual features and to suggest appropriate models. \subsection{Exploring spatial trend and covariate effects} Points may be distributed non-uniformly either because they are intrinsically non-uniform (``spatial trend'') or because their abundance depends on a spatial covariate (``covariate effects''). Non-uniformity of a point pattern can be investigated using the kernel smoothed intensity. This is the convolution of the point pattern with a smooth density called the kernel. Effectively each point in the pattern is replaced by a copy of the kernel, and the sum of all copies of the kernel is the kernel-smoothed intensity function. It is computed by \texttt{density.ppp} separately for each point pattern. <>= plot(simba, quote(plot(density(Points), main="")), nrows=2) @ Covariate effects due to a real-valued spatial covariate (a real-valued pixel image) can be investigated using the command \code{rhohat}. This uses a kernel smoothing technique to fit a model of the form \[ \lambda(u) = \rho(Z(u)) \] where $\lambda(u)$ is the point process intensity at a location $u$, and $Z(u)$ is the value of the spatial covariate at that location. Here $\rho$ is an unknown, smooth function which is to be estimated. The function $\rho$ expresses the effect of the spatial covariate on the point process intensity. If $\rho$ turns out to be constant, then the covariate has no effect on point process intensity (and the constant value of $\rho$ is the constant intensity of the point process). <>= rhos <- with(demohyper, rhohat(Points, Image)) plot(rhos) @ \SweaveOpts{width=6,height=4} \setkeys{Gin}{width=0.9\textwidth} \subsection{Exploring interpoint interaction} Still to be written. See Chapter 16 of \cite{baddrubaturn15}. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Fitting models of spatial trend} The command \code{mppm} fits models to multiple point patterns. Its syntax is very similar to that of \code{lm} and \code{glm}: <>= mppm(formula, data, interaction, ...) @ where \code{formula} is a formula describing the systematic trend part of the model, \code{data} is a hyperframe containing all the data (responses and covariates), and \code{interaction} determines the stochastic interpoint interaction part of the model. For example: <>= mppm(Points ~ group, simba, Poisson()) @ Note that the formula has a left hand side, which identifies the response. This should be the name of a column of \code{data}. \subsection{Trend formula} The right side of \code{formula} is an expression for the linear predictor (effectively the {\bf logarithm} of the spatial trend). The variables appearing in the right hand side of \code{formula} should be either \begin{itemize} \item names of columns in \code{data} \item objects in the {\sf R} global environment (such as \code{pi} and \code{log}) \item the reserved names \code{x}, \code{y} (representing Cartesian coordinates), \code{marks} (representing mark values attached to points) or \code{id} (a factor representing the row number in the hyperframe). \end{itemize} \subsubsection{Design covariates} The variables in the trend could be `design covariates'. For example, to fit a model to the \code{simba} dataset in which all patterns are independent replicates of the same uniform Poisson process, with the same constant intensity: <<>>= mppm(Points ~ 1, simba) @ To fit a model in which the two groups of patterns (control and treatment groups) each consist of independent replicates of a uniform Poisson process, but with possibly different intensity in each group: <<>>= mppm(Points ~ group, simba) @ To fit a uniform Poisson process to each pattern, with different intensity for each pattern: <<>>= mppm(Points ~ id, simba) @ \subsubsection{Spatial covariates} The variables in the trend could be `spatial covariates'. For example, the \code{demohyper} dataset has a column \code{Image} containing pixel images. <<>>= mppm(Points ~ Image, data=demohyper) @ This model postulates that each pattern is a Poisson process with intensity of the form \[ \lambda(u) = \exp(\beta_0 + \beta_1 Z(u)) \] at location $u$, where $\beta_0, \beta_1$ are coefficients to be estimated, and $Z(u)$ is the value of the pixel image \code{Image} at location $u$. It may or may not be appropriate to assume that the intensity of the points is an exponential function of the image pixel value $Z$. If instead we wanted the intensity $\lambda(u)$ to be \emph{proportional} to $Z(u)$, the appropriate model is <>= mppm(Points ~ offset(log(Image)), data=demohyper) @ which corresponds to an intensity proportional to \code{Image}, \[ \lambda(u) = \exp(\beta_0 + \log Z(u)) = e^{\beta_0} \; Z(u). \] The \code{offset} indicates that there is no coefficient in front of $\log Z(u)$. Alternatively we could allow a coefficient: <>= mppm(Points ~ log(Image), data=demop) @ which corresponds to a gamma transformation of \code{Image}, \[ \lambda(u) = \exp(\beta_0 + \beta_1 \log Z(u)) = e^{\beta_0} \; Z(u)^{\beta_1}. \] %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Interpoint interaction} The stochastic interpoint interaction in a point process model is specified by the arguments \code{interaction} and (optionally) \code{iformula} in <>= mppm(formula, data, interaction, ..., iformula=NULL) @ \subsection{Same interaction for all patterns} In the simplest case, the argument \texttt{interaction} is one of the familiar objects that describe the point process interaction structure. It is an object of class \texttt{"interact"} created by calling one of the functions \begin{center} \begin{tabular}{rl} \texttt{Poisson()} & the Poisson point process\\ \texttt{Hardcore()} & the hard core process \\ \texttt{Strauss()} & the Strauss process \\ \texttt{StraussHard()} & the Strauss/hard core point process\\ \texttt{Softcore()} & pairwise interaction, soft core potential\\ \texttt{PairPiece()} & pairwise interaction, piecewise constant \\ \texttt{DiggleGatesStibbard() } & Diggle-Gates-Stibbard pair potential \\ \texttt{DiggleGratton() } & Diggle-Gratton pair potential \\ \texttt{Fiksel() } & Fiksel pair potential \\ \texttt{LennardJones() } & Lennard-Jones pair potential \\ \texttt{Pairwise()} & pairwise interaction, user-supplied potential\\ \texttt{AreaInter()} & area-interaction potential\\ \texttt{Geyer()} & Geyer's saturation process\\ \texttt{BadGey()} & multiscale Geyer saturation process\\ \texttt{Saturated()} & Saturated pair model, user-supplied potential\\ \texttt{OrdThresh()} & Ord process, threshold potential\\ \texttt{Ord()} & Ord model, user-supplied potential \\ \texttt{MultiStrauss()} & multitype Strauss process \\ \texttt{MultiStraussHard()} & multitype Strauss/hard core process \\ \texttt{Concom()} & connected component interaction \\ \texttt{Hybrid()} & hybrid of several interactions \\ \end{tabular} \end{center} In this `simple' usage of \texttt{mppm}, the point process model assumes that all point patterns have exactly the same interpoint interaction, (with the same interaction parameters), and only differ in their spatial trend. \subsection{Hyperframe of interactions} More generally the argument \code{interaction} can be a hyperframe containing objects of class \texttt{"interact"}. For example, we might want to fit a Strauss process to each point pattern, but with a different Strauss interaction radius for each pattern. <>= radii <- with(simba, mean(nndist(Points))) @ Then \code{radii} is a vector of numbers which we could use as the values of the interaction radius for each case. First we need to make the interaction objects: <<>>= Rad <- hyperframe(R=radii) Str <- with(Rad, Strauss(R)) @ Then we put them into a hyperframe and fit the model: <<>>= Int <- hyperframe(str=Str) mppm(Points ~ 1, simba, interaction=Int) @ An important constraint is that all of the interaction objects in one column must be \emph{instances of the same process} (e.g. Strauss) albeit possibly having different parameter values. For example, you cannot put Poisson and Strauss processes in the same column. \subsection{Interaction formula} If \code{interaction} is a hyperframe, then the additional argument \code{iformula} may be used to fully specify the interaction. (An \code{iformula} is also required if \code{interaction} has more than one column.) The \code{iformula} should be a formula without a left hand side. Variables on the right hand side are typically the names of columns in \code{interaction}. \subsubsection{Selecting one column} If the right hand side of \code{iformula} is a single name, then this identifies the column in \code{interaction} to be used as the interpoint interaction structure. <<>>= h <- hyperframe(Y=waterstriders) g <- hyperframe(po=Poisson(), str4 = Strauss(4), str7= Strauss(7)) mppm(Y ~ 1, data=h, interaction=g, iformula=~str4) @ \subsubsection{Interaction depending on design} The \code{iformula} can also involve columns of \code{data}, but only those columns that are vectors or factors. This allows us to specify an interaction that depends on the experimental design. [This feature is {\bf experimental}.] For example <<>>= fit <- mppm(Points ~ 1, simba, Strauss(0.07), iformula = ~Interaction*group) @ Since \code{Strauss(0.1)} is not a hyperframe, it is first converted to a hyperframe with a single column named \code{Interaction}. The \code{iformula = ~Interaction*group} specifies (since \code{group} is a factor) that the interpoint interaction shall have a different coefficient in each experimental group. That is, we fit a model which has two different values for the Strauss interaction parameter $\gamma$, one for the control group and one for the treatment group. When you print the result of such a fit, the package tries to do `automatic interpretation' of the fitted model (translating the fitted interaction coefficients into meaningful numbers like $\gamma$). This will be successful in \emph{most} cases: <<>>= fit @ <>= co <- coef(fit) si <- function(x) { signif(x, 4) } @ Thus we see that the estimate of the Strauss parameter $\gamma$ for the control group is \Sexpr{si(exp(co[2]))}, and for the treatment group \Sexpr{si(exp(sum(co[c(2,4)])))} (the correct values in this simulated dataset were $1$ and $0.5$). The fitted model can also be interpreted directly from the fitted canonical coefficients: <<>>= coef(fit) @ The last output shows all the coefficients $\beta_j$ in the linear predictor for the (log) conditional intensity. The interpretation of the model coefficients, for any fitted model in \R, depends on the \emph{contrasts} which were applicable when the model was fitted. This is part of the core {\sf R} system: see \code{help(contrasts)} or \code{options(contrasts)}. If you did not specify otherwise, the default is to use \emph{treatment contrasts}. This means that, for an explanatory variable which is a \texttt{factor} with $N$ levels, the first level of the factor is used as a baseline, and the fitted model coefficients represent the factor levels $2, 3, \ldots, N$ relative to this baseline. In the output above, there is a coefficient for \code{(Intercept)} and one for \code{grouptreatment}. These are coefficients related to the \code{group} factor. According to the ``treatment contrasts'' rule, the \code{(Intercept)} coefficient is the estimated effect for the control group, and the \code{grouptreatment} coefficient is the estimated difference between the treatment and control groups. Thus the fitted first order trend is $\exp(\Sexpr{si(co[1])}) = \Sexpr{si(exp(co[1]))}$ for the control group and $\exp(\Sexpr{si(co[1])} + \Sexpr{si(co[3])}) = \Sexpr{si(exp(sum(co[c(1,3)])))}$ for the treatment group. The correct values in this simulated dataset were $80$ and $100$. The remaining coefficients in the output are \code{Interaction} and \code{Interaction:grouptreatment}. Recall that the Strauss process interaction term is $\gamma^{t(u,\xx)} = \exp(t(u,\xx) \log\gamma)$ at a spatial location $u$, for a point pattern $\xx$. Since we're using treatment contrasts, the coefficient \code{Interaction} is the estimate of $\log\gamma$ for the control group. The coefficient \code{Interaction:grouptreatment} is the estimate of the difference in $\log\gamma$ between the treatment and control groups. Thus the estimated Strauss interaction parameter $\gamma$ is $\exp(\Sexpr{si(co[2])}) = \Sexpr{si(exp(co[2]))}$ for the control group and $\exp(\Sexpr{si(co[2])} + (\Sexpr{si(co[4])})) = \Sexpr{si(exp(co[2]+co[4]))}$ for the treatment group. The correct values were $1$ and $0.5$. \subsubsection{Completely different interactions for different cases} In the previous example, when we fitted a Strauss model to all point patterns in the \code{simba} dataset, the fitted model for the patterns in the control group was close to Poisson ($\gamma \approx 1$). Suppose we now want to fit a model which {\it is} Poisson in the control group, and Strauss in the treatment group. The Poisson and Strauss interactions must be given as separate columns in a hyperframe of interactions: <>= interaction=hyperframe(po=Poisson(), str=Strauss(0.07)) @ What do we write for the \code{iformula}? The following \emph{will not} work: <>= iformula=~ifelse(group=="control", po, str) @ This does not work because the Poisson and Strauss models are `incompatible' inside such expressions. The canonical sufficient statistics for the Poisson and Strauss processes do not have the same dimension. Internally in \code{mppm} we translate the symbols \code{po} and \code{str} into matrices; the dimensions of these matrices are different, so the \code{ifelse} expression cannot be evaluated. Instead we need something like the following: <>= iformula=~I((group=="control")*po) + I((group=="treatment") * str) @ The letter \code{I} here is a standard R function that prevents its argument from being interpreted as a formula (thus the \code{*} is interpreted as multiplication instead of a model interaction). The expression \code{(group=="control")} is logical, and when multiplied by the matrix \code{po}, yields a matrix. So the following does work: <<>>= g <- hyperframe(po=Poisson(), str=Strauss(0.07)) fit2 <- mppm(Points ~ 1, simba, g, iformula=~I((group=="control")*po) + I((group=="treatment") * str)) fit2 @ %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %#%^!ifdef RANDOMEFFECTS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Random effects} \subsection{Mixed effects models} It is also possible to fit models that include `random effects'. Effectively, some of the coefficients in the model are assumed to be Normally-distributed random variables instead of constants. \subsubsection{Mixed Poisson model} Consider the simplest model of a uniform Poisson process which we fitted to the 3 point patterns of waterstriders. It might be sensible to assume that each pattern is a realisation of a Poisson process, but with {\em random intensity\/}. In each realisation the intensity $\lambda$ is constant across different locations, but it is a different, random value in different realisations. This example is called a `mixed Poisson process' and belongs to the class of `Cox processes' (Poisson processes with random intensity functions). Let's assume further that the log-intensity is a Normal random variable. Then the model is a (very degenerate) special case of a `log-Gaussian Cox process'. To fit such a model we use the standard techniques of mixed effects models \cite{lairware82,davigilt95,pinhbate00}. The mixed Poisson process which we discussed above would be written in standard form \begin{equation} \label{mixPois} \lambda_i(u) = \exp(\mu + Z_i) \end{equation} for the $i$th point pattern, where $\mu$ is a parameter to be estimated (the `fixed effect') and $Z_i \sim N(0, \sigma^2)$ is a zero-mean Normal random variable (the `random effect' for point pattern $i$). In the simplest case we would assume that $Z_1, \ldots, Z_n$ are independent. The variance $\sigma^2$ of the random effects would be estimated. One can also estimate the individual realised values $z_i$ of the random effects for each point pattern, although these are usually not of such great interest. Since the model includes both fixed and random effects, it is called a ``mixed-effects'' model. \subsubsection{Dependence structure} When we formulate a random-effects or mixed-effects model, we must specify the dependence structure of the random effects. In the model above we assumed that the $Z_i$ are independent for all point patterns $i$. If the experiment consists of two groups, we could alternatively assume that $Z_i = Z_j$ whenever $i$ and $j$ belong to the same group. In other words all the patterns in one group have the same value of the random effect. So the random effect is associated with the group rather than with individual patterns. This could be appropriate if, for example, the groups represent different batches of a chemical. Each batch is prepared under slightly different conditions so we believe that there are random variations between batches, but within a batch we believe that the chemical is well-mixed. \subsubsection{Random effects are coefficients} In the mixed Poisson model (\ref{mixPois}), the random effect is an additive constant (with a random value) in the log-intensity. In general, a random effect is a \emph{coefficient} of one of the covariates. For example if $v$ is a real-valued design covariate (e.g. `temperature'), with value $v_i$ for the $i$th point pattern, then we could assume \begin{equation} \label{ranef2} \lambda_i(u) = \exp(\mu + Z_i v_i) \end{equation} where $Z_i \sim N(0, \sigma^2)$ are independent for different $i$. This model has a random effect in the dependence on $v$. We could also have a random effect for a spatial covariate $V$. Suppose $V_i$ is a real-valued image for the $i$th pattern (so that $V_i(u)$ is the value of some covariate at the location $u$ for the $i$th case). Then we could assume \begin{equation} \label{ranef3} \lambda_i(u) = \exp(\mu + Z_i V_i(u)) \end{equation} where $Z_i \sim N(0, \sigma^2)$ are independent for different $i$. This kind of random effect would be appropriate if, for example, the images $V_i$ are not `normalised' or `standardised' relative to each other (e.g.\ they are images taken under different illumination). Then the coefficients $Z_i$ effectively include the rescaling necessary to standardise the images. \subsection{Fitting a mixed-effects model} The call to \texttt{mppm} can also include the argument \texttt{random}. This should be a formula (with no left-hand side) describing the structure of random effects. The formula for random effects must be recognisable to \texttt{lme}. It is typically of the form \begin{verbatim} ~x1 + ... + xn | g \end{verbatim} or \begin{verbatim} ~x1 + ... + xn | g1/.../gm \end{verbatim} where \verb!x1 + ... + xn! specifies the covariates for the random effects and \texttt{g} or \verb!g1/.../gm! determines the grouping (dependence) structure. Here \code{g} or \code{g1, \ldots, gm} should be factors. To fit the mixed Poisson model (\ref{mixPois}) to the waterstriders, we want to have a random intercept coefficient (so \texttt{x} is \texttt{1}) that varies for different point patterns (so \texttt{g} is \texttt{id}). The reserved name \code{id} is a factor referring to the individual point pattern. Thus <<>>= H <- hyperframe(P=waterstriders) mppm(P ~ 1, H, random=~1|id) @ To fit the mixed effects model (\ref{ranef2}) to the coculture data with the \code{AstroIm} covariate, with a random effect associated with each well, <>= mppm(Neurons ~ AstroIm, random=~AstroIm|WellNumber) @ %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %#%^!endif %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Studying the fitted model} Fitted models produced by \code{mppm} can be examined and validated in many ways. \subsection{Fits for each pattern} \subsubsection{Subfits} The command \code{subfits} takes an \code{mppm} object and extracts, for each individual point pattern, the fitted point process model for that pattern \emph{that is implied by the overall fit}. It returns a list of objects of class \code{ppm}. <<>>= H <- hyperframe(W=waterstriders) fit <- mppm(W ~ 1, H) subfits(fit) @ In this example the result is a list of three \code{ppm} objects representing the implied fits for each of the three point patterns in the \code{waterstriders} dataset. Notice that {\bf the fitted coefficients are the same} in all three models. Note that there are some unresolved difficulties with the implementation of \code{subfits}. Two completely different implementations are supplied in the package; they are called \code{subfits.old} %(used in versions 0.1--1 and earlier) and \code{subfits.new}.% (introduced in 0.1--2). The old version would occasionally crash. Unfortunately the newer version \code{subfits.new} is quite memory-hungry and sometimes causes R to hang. We're still working on this problem. So for the time being, \code{subfits} is the same as \code{subfits.old}. You can change this simply by reassigning, e.g. <>= subfits <- subfits.new @ \subsubsection{Fitting separately to each pattern} For comparison, we could fit a point process model separately to each point pattern dataset using \code{ppm}. The easy way to do this is with \code{with.hyperframe}. To fit a \emph{separate} uniform Poisson point process to each of the three waterstriders patterns, <<>>= H <- hyperframe(W=waterstriders) with(H, ppm(W)) @ The result is again a list of three fitted point process models (objects of class \code{ppm}), but now the fitted coefficients are different. \subsection{Residuals} One standard way to check a fitted model is to examine the residuals. \subsubsection{Point process residuals} Some recent papers \cite{baddetal05,baddmollpake08} have defined residuals for a fitted point process model (fitted to a \emph{single} point pattern). These residuals are implemented in \code{spatstat} as \code{residuals.ppm} and apply to an object of class \code{ppm}, that is, a model fitted to a \emph{single} point pattern. The command \code{residuals.mppm} computes the point process residuals for an \code{mppm} object. <<>>= fit <- mppm(P ~ x, hyperframe(P=waterstriders)) res <- residuals(fit) @ The result is a list, with one entry for each of the point pattern datasets. Each list entry contains the point process residuals for the corresponding point pattern dataset. Each entry in the list is a signed measure (object of class \code{"msr"}) as explained in the help for \code{residuals.ppm}). It can be plotted: <>= plot(res) @ You probably want the smoothed residual field: <>= smor <- with(hyperframe(res=res), Smooth(res, sigma=4)) plot(smor) @ \subsubsection{Sums of residuals} It would be useful to have a residual that is a single value for each point pattern (representing how much that point pattern departs from the model fitted to all the point patterns). That can be computed by \emph{integrating} the residual measures using the function \code{integral.msr}: <<>>= fit <- mppm(P ~ x, hyperframe(P=waterstriders)) res <- residuals(fit) totres <- sapply(res, integral.msr) @ In designed experiments we can plot these total residuals against the design covariates: <>= fit <- mppm(Points~Image, data=demohyper) resids <- residuals(fit, type="Pearson") totres <- sapply(resids, integral.msr) areas <- with(demohyper, area.owin(as.owin(Points))) df <- as.data.frame(demohyper[, "Group"]) df$resids <- totres/areas plot(resids~Group, df) @ \subsubsection{Four-panel diagnostic plots} Sometimes a more useful tool is the function \code{diagnose.ppm} which produces a four-panel diagnostic plot based on the point process residuals. However, it is only available for \code{ppm} objects. To obtain a four-panel diagnostic plot for each of the point patterns, do the following: \begin{enumerate} \item fit a model to multiple point patterns using \code{mppm}. \item extract the individual fits using \code{subfits}. \item plot the residuals of the individual fits. \end{enumerate} For example: <>= fit <- mppm(P ~ 1, hyperframe(P=waterstriders)) sub <- hyperframe(Model=subfits(fit)) plot(sub, quote(diagnose.ppm(Model))) @ (One could also do this for models fitted separately to the individual point patterns.) \subsubsection{Residuals of the parameter estimates} We can also compare the parameter estimates obtained by fitting the model simultaneously to all patterns (using \code{mppm}) with those obtained by fitting the model separately to each pattern (using \code{ppm}). <<>>= H <- hyperframe(P = waterstriders) fitall <- mppm(P ~ 1, H) together <- subfits(fitall) separate <- with(H, ppm(P)) Fits <- hyperframe(Together=together, Separate=separate) dr <- with(Fits, unlist(coef(Separate)) - unlist(coef(Together))) dr exp(dr) @ One could also try deletion residuals, etc. \subsection{Goodness-of-fit tests} \subsubsection{Quadrat count test} The $\chi^2$ goodness-of-fit test based on quadrat counts is implemented for objects of class \code{ppm} (in \code{quadrat.test.ppm}) and also for objects of class \code{mppm} (in \code{quadrat.test.mppm}). This is a goodness-of-fit test for a fitted {\bf Poisson} point process model only. The model could be uniform or non-uniform and the intensity might depend on covariates. <<>>= H <- hyperframe(X=waterstriders) # Poisson with constant intensity for all patterns fit1 <- mppm(X~1, H) quadrat.test(fit1, nx=2) # uniform Poisson with different intensity for each pattern fit2 <- mppm(X ~ id, H) quadrat.test(fit2, nx=2) @ See the help for \code{quadrat.test.ppm} and \code{quadrat.test.mppm} for further details. \subsubsection{Kolmogorov-Smirnov test} The Kolmogorov-Smirnov test of goodness-of-fit of a Poisson point process model compares the observed and predicted distributions of the values of a spatial covariate. We want to test the null hypothesis $H_0$ that the observed point pattern ${\mathbf x}$ is a realisation from the Poisson process with intensity function $\lambda(u)$ (for locations $u$ in the window $W$). Let $Z(u)$ be a given, real-valued covariate defined at each spatial location $u$. Under $H_0$, the \emph{observed} values of $Z$ at the data points, $Z(x_i)$ for each $x_i \in {\mathbf x}$, are independent random variables with common probability distribution function \[ F_0(z) = \frac{\int_W \lambda(u) \indicate{Z(u) \le z} \dee u} {\int_W \lambda(u) \dee u}. \] We can therefore apply the Kolmogorov-Smirnov test of goodness-of-fit. This compares the empirical cumulative distribution of the observed values $Z(x_i)$ to the predicted c.d.f. $F_0$. The test is implemented as \code{kstest.ppm}. The syntax is <>= kstest.mppm(model, covariate) @ where \code{model} is a fitted model (of class \texttt{"mppm"}) and \code{covariate} is either \begin{itemize} \item a \code{function(x,y)} making it possible to compute the value of the covariate at any location \code{(x,y)} \item a pixel image containing the covariate values \item a list of functions, one for each row of the hyperframe of original data \item a list of pixel images, one for each row of the hyperframe of original data \item a hyperframe with one column containing either functions or pixel images. \end{itemize} See Chapter 16 of \cite{baddrubaturn15} for further information. \newpage \addcontentsline{toc}{section}{Bibliography} %\bibliography{% %extra,% %extra2,% %biblio/badd,% %biblio/bioscience,% %biblio/censoring,% %biblio/mcmc,% %biblio/spatstat,% %biblio/stat,% %biblio/stochgeom% %} \begin{thebibliography}{1} \bibitem{baddmollpake08} A. Baddeley, J. M{\o}ller, and A.G. Pakes. \newblock Properties of residuals for spatial point processes. \newblock {\em Annals of the Institute of Statistical Mathematics}, 60:627--649, 2008. \bibitem{TheBook} A. Baddeley, E. Rubak, and R. Turner. \newblock {\em Spatial Point Patterns: Methodology and Applications with R}. \newblock Chapman \& Hall/CRC Press, 2015. \bibitem{statpaper} A. Baddeley, I. Sintorn, L. Bischof, R. Turner, and S. Heggarty. \newblock Analysing designed experiments where the response is a spatial point pattern. \newblock In preparation. \bibitem{baddetal05} A. Baddeley, R. Turner, J. M{\o}ller, and M. Hazelton. \newblock Residual analysis for spatial point processes (with discussion). \newblock {\em Journal of the Royal Statistical Society, series B}, 67(5):617--666, 2005. \bibitem{chenetal08} B.J. Chen, G.P. Leser, D. Jackson, and R.A. Lamb. \newblock The influenza virus {M2} protein cytoplasmic tail interacts with the {M1} protein and influences virus assembly at the site of virus budding. \newblock {\em Journal of Virology}, 82:10059--10070, 2008. %#%^!ifdef RANDOMEFFECTS \bibitem{davigilt95} M. Davidian and D.M. Giltinan. \newblock {\em Nonlinear Mixed Effects Models for Repeated Measurement Data}. \newblock Chapman and Hall, 1995. %#%^!endif \bibitem{digglangbene91} P.J. Diggle, N. Lange, and F. M. Benes. \newblock Analysis of variance for replicated spatial point patterns in clinical neuroanatomy. \newblock {\em Journal of the {A}merican {S}tatistical {A}ssociation}, 86:618--625, 1991. %#%^!ifdef RANDOMEFFECTS \bibitem{lairware82} N.M. Laird and J.H. Ware. \newblock Random-effects models for longitudinal data. \newblock {\em Biometrics}, 38:963--974, 1982. %#%^!endif \bibitem{pent84} A. Penttinen. \newblock {\em Modelling Interaction in Spatial Point Patterns: Parameter Estimation by the Maximum Likelihood Method}. \newblock Number 7 in {Jyv\"askyl\"a} Studies in Computer Science, Economics and Statistics. University of {Jyv\"askyl\"a}, 1984. %#%^!ifdef RANDOMEFFECTS \bibitem{pinhbate00} J.C. Pinheiro and D.M. Bates. \newblock {\em Mixed-Effects Models in {S} and {S-PLUS}}. \newblock Springer, 2000. %#%^!endif \end{thebibliography} %\addcontentsline{toc}{section}{Index} %\printindex \end{document} spatstat/inst/doc/bugfixes.R0000644000176200001440000000315614155343634015613 0ustar liggesusers### R code from vignette source 'bugfixes.Rnw' ################################################### ### code chunk number 1: bugfixes.Rnw:20-24 ################################################### library(spatstat) sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") options(useFancyQuotes=FALSE) ################################################### ### code chunk number 2: bugfixes.Rnw:38-42 ################################################### nbugs <- nrow(news(grepl("^BUG", Category), package="spatstat")) nbugssince <- nrow(news(Version > "1.42-0" & grepl("^BUG", Category), package="spatstat")) ################################################### ### code chunk number 3: bugfixes.Rnw:58-59 (eval = FALSE) ################################################### ## bugfixes ################################################### ### code chunk number 4: bugfixes.Rnw:63-64 (eval = FALSE) ################################################### ## bugfixes(sinceversion="1.50-0") ################################################### ### code chunk number 5: bugfixes.Rnw:68-69 (eval = FALSE) ################################################### ## bugfixes(sincedate="2017-06-30") ################################################### ### code chunk number 6: bugfixes.Rnw:72-73 (eval = FALSE) ################################################### ## bugfixes("book") ################################################### ### code chunk number 7: bugfixes.Rnw:76-77 (eval = FALSE) ################################################### ## bugfixes("all") spatstat/inst/doc/spatstatKnetsize.txt0000644000176200001440000000114414146324064017764 0ustar liggesusersdate version nhelpfiles nobjects ndatasets Rlines srclines "2019-05-22" "1.9-0" 6 3 3 227 3962 "2019-07-29" "1.10-0" 6 3 3 227 3962 "2019-07-29" "1.10-1" 6 3 3 227 3962 "2019-07-29" "1.10-2" 6 3 3 227 3962 "2019-08-08" "1.11-0" 4 3 1 227 3962 "2019-08-08" "1.11-1" 4 3 1 227 3962 "2019-08-09" "1.11-2" 4 3 1 227 3962 "2019-12-13" "1.12-0" 4 3 1 232 3962 "2019-12-15" "1.12-1" 4 3 1 232 4007 "2020-04-27" "1.12-2" 4 3 1 232 4007 "2021-01-03" "1.13-0" 4 3 1 232 4007 "2021-01-10" "1.13-0" 4 3 1 232 4007 "2021-01-10" "1.13-0" 4 3 1 232 4007 "2021-02-15" "1.65-0" 4 3 1 232 4007 "2021-03-31" "2.0-0" 4 3 1 232 4007 spatstat/inst/doc/shapefiles.Rnw0000644000176200001440000005064714141377564016502 0ustar liggesusers\documentclass[twoside,11pt]{article} % \VignetteIndexEntry{Handling shapefiles in the spatstat package} \SweaveOpts{eps=TRUE} <>= options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) @ \usepackage{graphicx} \usepackage[colorlinks=true,urlcolor=blue]{hyperref} \usepackage{color} \usepackage{anysize} \marginsize{2cm}{2cm}{2cm}{2cm} \newcommand{\pkg}[1]{\texttt{#1}} \newcommand{\bold}[1]{{\textbf {#1}}} \newcommand{\R}{{\sf R}} \begin{document} %\bibliographystyle{plain} \thispagestyle{empty} <>= library(spatstat) options(useFancyQuotes=FALSE) sdate <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Date") sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") @ \title{Handling shapefiles in the \texttt{spatstat} package} \author{Adrian Baddeley, Rolf Turner and Ege Rubak} \date{ \Sexpr{sdate} \\ \pkg{spatstat} version \texttt{\Sexpr{sversion}} } \maketitle This vignette explains how to read data into the \pkg{spatstat} package from files in the popular `shapefile' format. This vignette is part of the documentation included in \pkg{spatstat} version \texttt{\Sexpr{sversion}}. The information applies to \pkg{spatstat} versions \texttt{1.36-0} and above. \section{Shapefiles} A shapefile represents a list of spatial objects --- a list of points, a list of lines, or a list of polygonal regions --- and each object in the list may have additional variables attached to it. A dataset stored in shapefile format is actually stored in a collection of text files, for example \begin{verbatim} mydata.shp mydata.prj mydata.sbn mydata.dbf \end{verbatim} which all have the same base name \texttt{mydata} but different file extensions. To refer to this collection you will always use the filename with the extension \texttt{shp}, for example \texttt{mydata.shp}. \section{Helper packages} \label{S:helpers} We'll use two other packages to handle shapefile data. The \pkg{maptools} package is designed specifically for handling file formats for spatial data. It contains facilities for reading and writing files in shapefile format.% \footnote{ Some code in \pkg{maptools} is no longer maintained, and may give you a message recommending that you use the packages \pkg{rgdal} and \pkg{sf}. However these packages are more difficult to install than \pkg{maptools} because of their software requirements. So we recommend that you try \pkg{maptools} first. } The \pkg{sp} package supports a standard set of spatial data types in \R. These standard data types can be handled by many other packages, so it is useful to convert your spatial data into one of the data types supported by \pkg{sp}. \section{Caveat about longitude-latitude coordinates} The shapefile format supports geographical coordinates, usually longitude-latitude coordinates, which specify locations on the curved surface of the Earth. However, \texttt{spatstat} deals only with spatial data on a flat two-dimensional plane. When shapefile data are converted into \texttt{spatstat} objects, longitude and latitude coordinates are (currently) treated as $x$ and $y$ coordinates, so that the Earth's surface is effectively mapped to a rectangle. This mapping distorts distances and areas. If your study region is a \emph{small} region of the Earth's surface (about 3 degrees, 180 nautical miles, 200 statute miles, 320 km across) then a reasonable approach is to use the latitude and longitude as $x$ and $y$ coordinates, after multiplying the longitude coordinates by the cosine of the latitude of the centre of the region. This will approximately preserve areas and distances. This calculation is a simple example of a \emph{geographical projection} and there are some much better projections available. It may be wise to use another package to perform the appropriate projection for you, and then to convert the projected data into \texttt{spatstat} objects. If your study region is a large part of the sphere, then your data may not be amenable to the techniques provided by \texttt{spatstat} because the geometry is fundamentally different. Please consider the extension package \texttt{spatstat.sphere}. \section{How to read shapefiles into \pkg{spatstat}} To read shapefile data into \pkg{spatstat}, you follow two steps: \begin{enumerate} \item using the facilities of \pkg{maptools}, read the shapefiles and store the data in one of the standard formats supported by \pkg{sp}. \item convert the \pkg{sp} data type into one of the data types supported by \pkg{spatstat}. \end{enumerate} \subsection{Read shapefiles using \pkg{maptools}} Here's how to read shapefile data. \begin{enumerate} \item ensure that the package \pkg{maptools} is installed. You will need version \texttt{0.7-16} or later. \item start R and load the package: <>= library(maptools) @ \item read the shapefile into an object in the \pkg{sp} package using \texttt{readShapeSpatial}, for example <>= x <- readShapeSpatial("mydata.shp") @ In recent versions of \pkg{maptools} you may get a warning, saying that this code is no longer supported, and recommending the packages \pkg{rgdal} and \pkg{sf}. As far as we know, this warning is premature, as the code still works fine! \item To find out what kind of spatial objects are represented by the dataset, inspect its class: <>= class(x) @ The class may be either \texttt{SpatialPoints} indicating a point pattern, \texttt{SpatialLines} indicating a list of polygonal lines, or \texttt{SpatialPolygons} indicating a list of polygons. It may also be \texttt{SpatialPointsDataFrame}, \texttt{SpatialLinesDataFrame} or \texttt{SpatialPolygonsDataFrame} indicating that, in addition to the spatial objects, there is a data frame of additional variables. The classes \texttt{SpatialPixelsDataFrame} and \texttt{SpatialGridDataFrame} represent pixel image data. \end{enumerate} Here are some examples, using the example shapefiles supplied in the \pkg{maptools} package itself. % fake data because we don't want spatstat to depend on maptools <>= baltim <- columbus <- fylk <- list() class(baltim) <- "SpatialPointsDataFrame" class(columbus) <- "SpatialPolygonsDataFrame" class(fylk) <- "SpatialLinesDataFrame" @ <>= setwd(system.file("shapes", package="maptools")) baltim <- readShapeSpatial("baltim.shp") columbus <- readShapeSpatial("columbus.shp") fylk <- readShapeSpatial("fylk-val.shp") @ <<>>= class(baltim) class(columbus) class(fylk) @ \subsection{Convert data to \pkg{spatstat} format} To convert the dataset to an object in the \pkg{spatstat} package, the procedure depends on the type of data, as explained below. Both packages \pkg{maptools} and \pkg{spatstat} must be \textbf{loaded} in order to convert the data. \subsubsection{Objects of class \texttt{SpatialPoints}} An object \texttt{x} of class \texttt{SpatialPoints} represents a spatial point pattern. Use \verb!as(x, "ppp")! or \texttt{as.ppp(x)} to convert it to a spatial point pattern in \pkg{spatstat}. (The conversion is performed by \texttt{as.ppp.SpatialPoints}, a function in \pkg{maptools}.) The window for the point pattern will be taken from the bounding box of the points. You will probably wish to change this window, usually by taking another dataset to provide the window information. Use \verb![.ppp! to change the window: if \texttt{X} is a point pattern object of class \verb!"ppp"! and \texttt{W} is a window object of class \verb!"owin"!, type <>= X <- X[W] @ \subsubsection{Objects of class \texttt{SpatialPointsDataFrame }} An object \texttt{x} of class \texttt{SpatialPointsDataFrame} represents a pattern of points with additional variables (`marks') attached to each point. It includes an object of class \texttt{SpatialPoints} giving the point locations, and a data frame containing the additional variables attached to the points. Use \verb!as(x, "ppp")! or \texttt{as.ppp(x)} to convert an object \texttt{x} of class \texttt{SpatialPointsDataFrame} to a spatial point pattern in \pkg{spatstat}. In this conversion, the data frame of additional variables in \texttt{x} will become the \texttt{marks} of the point pattern \texttt{z}. <>= y <- as(x, "ppp") @ (The conversion is performed by \texttt{as.ppp.SpatialPointsDataFrame}, a function in \pkg{maptools}. So the \pkg{maptools} and \pkg{spatstat} packages must be loaded in order for this to work.) Before the conversion you can extract the data frame of auxiliary data by \verb!df <- x@data! or \verb!df <- slot(x, "data")!. After the conversion you can extract these data by \verb!df <- marks(y)!. For example: <>= balt <- as(baltim, "ppp") bdata <- slot(baltim, "data") @ \subsubsection{Objects of class \texttt{SpatialLines}} \label{spatiallines.2.psp} A ``line segment'' is the straight line between two points in the plane. In the \pkg{spatstat} package, an object of class \texttt{psp} (``planar segment pattern'') represents a pattern of line segments, which may or may not be connected to each other (like matches which have fallen at random on the ground). In the \pkg{sp} package, an object of class \texttt{SpatialLines} represents a \textbf{list of lists} of \textbf{connected curves}, each curve consisting of a sequence of straight line segments that are joined together (like several pieces of a broken bicycle chain.) So these two data types do not correspond exactly. The list-of-lists hierarchy in a \texttt{SpatialLines} object is useful when representing internal divisions in a country. For example, if \texttt{USA} is an object of class \texttt{SpatialLines} representing the borders of the United States of America, then \verb!USA@lines! might be a list of length 52, with \verb!USA@lines[[i]]! representing the borders of the \texttt{i}-th State. The borders of each State consist of several different curved lines. Thus \verb!USA@lines[[i]]@Lines[[j]]! would represent the \texttt{j}th piece of the boundary of the \texttt{i}-th State. If \texttt{x} is an object of class \texttt{SpatialLines}, there are several things that you might want to do: \begin{enumerate} \item collect together all the line segments (all the segments that make up all the connected curves) and store them as a single object of class \texttt{psp}. \begin{quote} To do this, use \verb!as(x, "psp")! or \texttt{as.psp(x)} to convert it to a spatial line segment pattern. \end{quote} \item convert each connected curve to an object of class \texttt{psp}, keeping different connected curves separate. To do this, type something like the following: <>= out <- lapply(x@lines, function(z) { lapply(z@Lines, as.psp) }) @ (The conversion is performed by \texttt{as.psp.SpatialLines}, a function in \pkg{maptools}. So the \pkg{maptools} and \pkg{spatstat} packages must be loaded in order for this to work.) The result will be a \textbf{list of lists} of objects of class \texttt{psp}. Each one of these objects represents a connected curve, although the \pkg{spatstat} package does not know that. The list structure will reflect the list structure of the original \texttt{SpatialLines} object \texttt{x}. If that's not what you want, then use \verb!curvelist <- do.call("c", out)! or <>= curvegroup <- lapply(out, function(z) { do.call("superimpose", z)}) @ to collapse the list-of-lists-of-\texttt{psp}'s into a list-of-\texttt{psp}'s. In the first case, \texttt{curvelist[[i]]} is a \texttt{psp} object representing the \texttt{i}-th connected curve. In the second case, \texttt{curvegroup[[i]]} is a \texttt{psp} object containing all the line segments in the \texttt{i}-th group of connected curves (for example the \texttt{i}-th State in the \texttt{USA} example). \end{enumerate} The window for the spatial line segment pattern can be specified as an argument \texttt{window} to the function \texttt{as.psp}. (The conversion is performed by \texttt{as.psp.SpatialLines} or \texttt{as.psp.Lines}, which are functions in \pkg{maptools}.) \subsubsection{Objects of class \texttt{SpatialLinesDataFrame}} An object \texttt{x} of class \texttt{SpatialLinesDataFrame} is a \texttt{SpatialLines} object with additional data. The additional data is stored as a data frame \verb!x@data! with one row for each entry in \verb!x@lines!, that is, one row for each group of connected curves. In the \pkg{spatstat} package, an object of class \texttt{psp} (representing a collection of line segments) may have a data frame of marks. Note that each \emph{line segment} in a \texttt{psp} object may have different mark values. If \texttt{x} is an object of class \texttt{SpatialLinesDataFrame}, there are two things that you might want to do: \begin{enumerate} \item collect together all the line segments that make up all the connected lines, and store them as a single object of class \texttt{psp}. \begin{quote} To do this, use \verb!as(x, "psp")! or \texttt{as.psp(x)} to convert it to a marked spatial line segment pattern. \end{quote} \item keep each connected curve separate, and convert each connected curve to an object of class \texttt{psp}. To do this, type something like the following: <>= out <- lapply(x@lines, function(z) { lapply(z@Lines, as.psp) }) dat <- x@data for(i in seq(nrow(dat))) out[[i]] <- lapply(out[[i]], "marks<-", value=dat[i, , drop=FALSE]) @ The result is a list-of-lists-of-\texttt{psp}'s. See the previous subsection for explanation on how to change this using \texttt{c()} or \texttt{superimposePSP}. \end{enumerate} (The conversion is performed by \texttt{as.psp.SpatialLines}, a function in \pkg{maptools}. So the \pkg{maptools} and \pkg{spatstat} packages must be loaded in order for this to work.) In either case, the mark variables attached to a particular \emph{group of connected lines} in the \texttt{SpatialLinesDataFrame} object, will be duplicated and attached to each \emph{line segment} in the resulting \texttt{psp} object. \subsubsection{Objects of class \texttt{SpatialPolygons}} First, so that we don't go completely crazy, let's introduce some terminology. A \emph{polygon} is a closed curve that is composed of straight line segments. You can draw a polygon without lifting your pen from the paper. \setkeys{Gin}{width=0.4\textwidth} \begin{center} <>= data(chorley) plot(as.owin(chorley), lwd=3, main="polygon") @ \end{center} A \emph{polygonal region} is a region in space whose boundary is composed of straight line segments. A polygonal region may consist of several unconnected pieces, and each piece may have holes. The boundary of a polygonal region consists of one or more polygons. To draw the boundary of a polygonal region, you may need to lift and drop the pen several times. \setkeys{Gin}{width=0.4\textwidth} \begin{center} <>= data(demopat) plot(as.owin(demopat), col="blue", main="polygonal region") @ \end{center} An object of class \texttt{owin} in \pkg{spatstat} represents a polygonal region. It is a region of space that is delimited by boundaries made of lines. An object \texttt{x} of class \texttt{SpatialPolygons} represents a \textbf{list of polygonal regions}. For example, a single object of class \texttt{SpatialPolygons} could store information about every State in the United States of America (or the United States of Malaysia). Each State would be a separate polygonal region (and it might contain holes such as lakes). There are two things that you might want to do with an object of class \texttt{SpatialPolygons}: \begin{enumerate} \item combine all the polygonal regions together into a single polygonal region, and convert this to a single object of class \texttt{owin}. \begin{quote} For example, you could combine all the States of the USA together and obtain a single object that represents the territory of the USA. To do this, use \verb!as(x, "owin")! or \texttt{as.owin(x)}. The result is a single window (object of class \texttt{"owin"}) in the \pkg{spatstat} package. \end{quote} \item keep the different polygonal regions separate; convert each one of the polygonal regions to an object of class \texttt{owin}. \begin{quote} For example, you could keep the States of the USA separate, and convert each State to an object of class \texttt{owin}. \end{quote} To do this, type the following: <>= regions <- slot(x, "polygons") regions <- lapply(regions, function(x) { SpatialPolygons(list(x)) }) windows <- lapply(regions, as.owin) @ The result is a list of objects of class \texttt{owin}. Often it would make sense to convert this to a tessellation object, by typing <>= te <- tess(tiles=windows) @ \end{enumerate} (The conversion is performed by \texttt{as.owin.SpatialPolygons}, a function in \pkg{maptools}. So the \pkg{maptools} and \pkg{spatstat} packages must be loaded in order for this to work.) {\bf The following is different from what happened in previous versions of \pkg{spatstat}} (prior to version \texttt{1.36-0}.) During the conversion process, the geometry of the polygons will be automatically ``repaired'' if needed. Polygon data from shapefiles often contain geometrical inconsistencies such as self-intersecting boundaries and overlapping pieces. For example, these can arise from small errors in curve-tracing. Geometrical inconsistencies are tolerated in an object of class \texttt{SpatialPolygons} which is a list of lists of polygonal curves. However, they are not tolerated in an object of class \texttt{owin}, because an \texttt{owin} must specify a well-defined region of space. These data inconsistencies must be repaired to prevent technical problems. \pkg{Spatstat} uses polygon-clipping code to automatically convert polygonal lines into valid polygon boundaries. The repair process changes the number of vertices in each polygon, and the number of polygons (if you chose option 1). To disable the repair process, set \texttt{spatstat.options(fixpolygons=FALSE)}. \subsubsection{Objects of class \texttt{SpatialPolygonsDataFrame}} What a mouthful! An object \texttt{x} of class \texttt{SpatialPolygonsDataFrame} represents a list of polygonal regions, with additional variables attached to each region. It includes an object of class \texttt{SpatialPolygons} giving the spatial regions, and a data frame containing the additional variables attached to the regions. The regions are extracted by <>= y <- as(x, "SpatialPolygons") @ and you then proceed as above to convert the curves to \pkg{spatstat} format. The data frame of auxiliary data is extracted by \verb!df <- x@data! or \verb!df <- slot(x, "data")!. For example: <>= cp <- as(columbus, "SpatialPolygons") cregions <- slot(cp, "polygons") cregions <- lapply(cregions, function(x) { SpatialPolygons(list(x)) }) cwindows <- lapply(cregions, as.owin) @ There is currently no facility in \pkg{spatstat} for attaching marks to an \texttt{owin} object directly. However, \pkg{spatstat} supports objects called \textbf{hyperframes}, which are like data frames except that the entries can be any type of object. Thus we can represent the \texttt{columbus} data in \pkg{spatstat} as follows: <>= ch <- hyperframe(window=cwindows) ch <- cbind.hyperframe(ch, columbus@data) @ Then \texttt{ch} is a hyperframe containing a column of \texttt{owin} objects followed by the columns of auxiliary data. \subsubsection{Objects of class \texttt{SpatialGridDataFrame} and \texttt{SpatialPixelsDataFrame}} An object \texttt{x} of class \texttt{SpatialGridDataFrame} represents a pixel image on a rectangular grid. It includes a \texttt{SpatialGrid} object \texttt{slot(x, "grid")} defining the full rectangular grid of pixels, and a data frame \texttt{slot(x, "data")} containing the pixel values (which may include \texttt{NA} values). The command \texttt{as(x, "im")} converts \texttt{x} to a pixel image of class \texttt{"im"}, taking the pixel values from the \emph{first column} of the data frame. If the data frame has multiple columns, these have to be converted to separate pixel images in \pkg{spatstat}. For example <>= y <- as(x, "im") ylist <- lapply(slot(x, "data"), function(z, y) { y[,] <- z; y }, y=y) @ An object \texttt{x} of class \texttt{SpatialPixelsDataFrame} represents a \emph{subset} of a pixel image. To convert this to a \pkg{spatstat} object, it should first be converted to a \texttt{SpatialGridDataFrame} by \texttt{as(x, "SpatialGridDataFrame")}, then handled as described above. \end{document} spatstat/inst/doc/replicated.pdf0000644000176200001440000204173714155343653016475 0ustar liggesusers%PDF-1.5 % 1 0 obj << /Type /ObjStm /Length 3747 /Filter /FlateDecode /N 75 /First 624 >> stream x[ks۶~N Lĉ8qmYmz8&,Oɔ-,b%,)"42e2bűXbGF_1qT0!ԑLX BSe&ĵfI GcTBSSZYCj V$t$Htb5i&43¤Lf}LDLQRVd֤1ClZ&KUTcH'il1z"ѹHQD&hȱ$F&NPӕHd &#PEdQĘTCc0vP)@0 4heӤXHQRڄ)H@aX %2BiHNbH֐@ $'ڠ-AL*d,n[[Zw5q-V XZ $+IL"Vc YaAd?ʖ`9`}'..ξ_gxv=rϳ2M E$`#kd~ fsYGmOgaGbϮfb8ϯ,}/.nK HCuX _O %ƚW1^[/zѩz)iKT(!!-2ԓA reJAb®&p̦|7ɤTEmJBs/0 HSk2\ BFdhVŵ&2L i<:[[RR72]̧bX–UM`͑:k7$F >$t/qJB<:XE!~?Og9?/+~c;?F`Wg"?'xgߓW8sf^W%7Mg|Af^lA6SE,o5jͿm.qzMj* c7vҴu髥*^-<{|p±@U1uASlTLPLlVMiו1ZEzu5PW|{{uRB4! I Eh8gHN2ᶛ >Zu`U׫ʛ$[)r{tM(*:"h^݃ Tn1QͳEX)|6 W<`A<0[I耼8 q=Y/%U|-U/.,Z&ZI25T$QA6QA6:nM vO6/Ni4e杶Ӻ-b1ܮ>Q%GOr@; 5ֻP]A>C>,yǣ YR_'2Q(l2baC! O bKP w4n/̵N#[$'0(BDyBTy y` !2oBs:_$frnvDItz/ǽ'>_e><؛G}Ym{pfXEVVVv| tO`#[ZnK4mvɺ?/{ѷ/q}^ZS9>c紽NzE*'~WOET,wI[.NhV۽rZ|7Cu9UЍlWgڔeH7`|rC:\c4/c2(_ߛaAL?ti05endstream endobj 77 0 obj << /Subtype /XML /Type /Metadata /Length 1167 >> stream 2021-12-12T17:58:03+08:00 2021-12-12T17:58:03+08:00 TeX Untitled endstream endobj 78 0 obj << /Type /ObjStm /Length 1892 /Filter /FlateDecode /N 74 /First 634 >> stream xZmsF_ffB iIri}=[,v0Ɠ;봷޾>TԎRIJ(JiRX 3K`{<Y䏔 x| +&7QVS;5l:fPGv;'O0:cJdt4Y%}, ]!j$Q% Ӗ 6c /\òc yڗ1lsJo[SB%D_>DGɻWF3sKY(틝-GrCD5Cf{  +G)bW4Oilsӡs){yTݥ}N9!G>\ezOǣ||R~Odp52!(4<SQa͋aO3g8T09Qmyq=E֠@PnQ|0IO=\W~;xAZ|( >Ί4MT \Ev!_h8n?6"'deB֥Ck(G3t>m=r2pJ-C6"g@"YB ]l::w5[?~qo/盡 aժFͧݚO 44JYV۪Wm?}y-|E"luN3TãzWr͟JmbQƈU-6fx|GY^h^+I./7ERWpi%?H. 2ar(7n{˪"]oY>SlR> stream x[r#W^GI^dmD®0Zefuw6fF %R!h6j|euCC?;9(p OAG΅yQ]^#E3Lİ{U0{\i%Jl7ÕJU[pT=sp=8sWjجCWzq8D޼Eƻ<ڥ2N#_X7@y}LY,@;V::殍aZʼu[mݲς?ʇΎ 7qXj+FW!",; c0 ɚ@1Oo_ H$ųŘg @9Dd~k՜[1 c՛qCC>e]kRI('z-dcC,KZ 䨲 Wֲ^R[ukyF6q`O'tm##3zO؟!q2c;ԚkA i~8^] \̳l׹WShW \(TM/CDogn$.@7̦Wy71Xٕ8$QSD&_r3&5FF,mCEыӞSX"ر Zή3(U )gt\᪦+u-)qLfsOQK(n%X~ӷXNlpՑ }dCT{cΙCGW"E~ []^4%Z\ln(ڶw?ʵɦ˻ m3]wx,fA"3cv-o"Jews4m{OYe+!%hW-# ^Yh\TksH=IiܙL0ۘӍ'z̢6f˔<9=y5.n{3OIkC$R 8dvd$d`BmT$7B`b̀4f2NH &%vpغDF]n1A}M;35/ό.+IT}mLGL.1X)1R__(Jmߚ:M,I'R Zg]^W*mjru*J. EbK *KkhMV+B6`>i2XQ3R$C9 ZL[TKkEl 7bن|&NcMgXE@ *m-o3:.W Zg E1" *N &p3?7X|NuI:yb< )'/v&]tB1O9hM֤h%FKi3h̠U^Y%ȧmk>V qlhU Gܝ y !s /dhWOEzs#3ވUEI4))qsѫԼ(0Ę >4P*w*rW\/Hh7ExzW[/Q 'TB6B8 Pyؕ~Tyqq+m_J1b#,?+Ɂl- T >rN~g&^Գ_t``/1bw&8 +Dfì7Ky{Tf&d{#Ǚv07[Gm5']X};[5Tl|bP&Skq^b3i03g%.=GEg?;r9Gai@xӀVaGbt 11mumWV;HвS~aFOm Y ={O͗sÇz~T"M<%q Nk=>D-*0^l^j{7oW)K-7wg$*67Sz,jBK wl?Ai~!?ChQ*Yo>v: @_m+K$yNayhM {D&A[&EfTR]eNc]|"D\[y-E mѤߋ)R|O#'H/RxKop9ߙ#`CWc~|qg/K?pZH7~9H (r{6~Ť;~ endstream endobj 154 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 1846 >> stream x}U{PT7J8z鈴E>ƒQ |,ˆEX*v]XuV0+(XL4Lhx.=̴W;M?ߜ3s|}CQI􌤵OV?&Q1+*r",-;RE $^\~ڕK6)"T.)JNؔH2U"(ߨV ReYJ[|D_SH2erm@*IKrR]k% yJUjmNj J'b'$lb3xH%$"҉a"Qu_$$$)⦷Bus:j6 +f^hȖU+P~0t@ C},0Ujp#hB&'7Ty``5TBƞ]#iƏ2(m8a^#FPADįF/eϩPSMGr[-N׈g۬Cʢn4nby "SA &1 YHD޹c[7M|:  k;`+@}zjA D? Zu#@b`ͽ;9(SqRx)(4@+l81%b1oKXX3 >:=-qD]WQ5s<By9+~ps RY3B=0gKR\f:Oe~w8Z*f=Rcpdv%=9}l Z[PHK˲W)zZip92:u7uI$"0>nj攽 1VD['>v/+vNK&k{, ~~Z3Hnۗ*~a Pшx`̤R_'rþ'7}%3 'CyޘvwK!q>>? DZ.ibT09|<21{!Ⱥre#@&vٔF؜NfMzn֞3'Z"س'\ 8 Ϳ?BwKVÔu%ICos 5vJPxh!F-`Ɇ2{hA P>{<--hh[w~.F}fjlq^Ή6bycc#-Ŀendstream endobj 155 0 obj << /Filter /FlateDecode /Length 239 >> stream x]1n0 EwB7,\%C > stream xMkPWw Ն(XL "#`}P2T`Ejᑄ%P"yHD H%ovp:V㫎\?tVtwC.Iʸ2~ /u?fEn R!/T桝 IrK#tVf+}+CC/Ԭ&Y+U4u dP WM3kV0On9j6OWI5ȷi:%B5YRWj s Mr %qD<NDQOb n W+b []]L.>E2D?.s|}H΁Z">e39&0ȋp7d#}a2A |@UJ,]]P(KBbO; ԛ'h١1,.do{f772rcX &9/MSf8$v(Ize=]/+8*Ejǔ7TԳ@CQ~=eFz($9oU# j9'͌\aV4+|(H0ϡj{xq3HCڽPC|T?uy++g@ns$f{u0h{'{Ñ/t'%a@[|Ql1 ^gumlJ}ѩIm-Iϕgk`e?P64a\](J%@P{z~EN (r$r!pzcP a*kSM'-.o+f ~3E3'*^GveFۭv{I<)N^ˎi)YDDS{m Ί%uyW8A{(2һ74ȍD]z6e3:Om]Nđ'4r/hU sF8o}!bdlnA\quo[ttC*p^"=`yBcRWTT75tVW1 ??5~UbcdXw|{~^۪ Tapx ^AG5B:t~}><~6ewl2ɪj:uKN(sD4"Gt7_;!nC,Z&'_SI'LM|\*K_yEPHi[#=h#Ըss0s] t9Dxȩendstream endobj 157 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 1728 >> stream xuTkTa`gHflRsj4$5ZRoQXqewvY*{dY,n厰,]bS/xGOC=hlc1M|L9swμ><I$I*2=zNzb¤QsB 2h ] YGyK $Œ$Ψ//0(W)7lHX\40W%*TA2r6P0^/0t][^^F)Yo[,/4(3A_&S&kE2]í'i5RWi z MbV\R2 cmb%b ;8VD#,w+ԯмzN{7_|pzR vK^1VTDIAK13(w~X+ GcBxW,L S!5>: RKg+p:fng5{I-S<ٶ`_֦ _MGI&WZ!f,%e"q_cG~he.YlduSaɮq=Ҋ3TDIKooP5db~lFRwt[t |9/k+jD)>YAhtm -雖aD[QܠQ,08>Gn~>#m֢ދJ 梟rQboıW̓f@ ݔ^c]0[*Jq~]`UP0V=tlUG}L~cJ:l: jۢq8 v68V zAsZ׮F+&{m;4<w邇{H_Dp5f|-tF$\Xk$FG x\RtLIq3v`lY@ ,vDc tb[1 غ % %硹C¢cZgٯ Y+\C1Wa_fN;>uy@^GPVZ* YL-Ht?'. y>?ߋCa'ݝ|2b[#)^':GVTZRW L1&ZAO%dh/Ol7ًtn4t%JZ*Y_m/8/ -@D"k'ڠFmݴ6.| Nk+dPlp&')J؁^mqiNW7r2+-52<)gaqB_RY' z<*둒#mkshܢO<-3]K߾Uendstream endobj 158 0 obj << /Filter /FlateDecode /Length 557 >> stream x]=n@{7%q1$ȥA˅oQ",o/|k?ޚi^ƭ~\?66/ñ:n_ uEuk?ԭ_ܶ.7&:,xFKwެוh?endstream endobj 159 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 5960 >> stream xXtTeھ$s/-Jz' "HULzh IH/O*!;3iR&= ŠVYuL_?90w->s%F"V:=kK!+R'{՟j #0¢W^_ƢQm4#HB"SWE+xn7{Ѣ̚nyODמ;= = ^-^>8)K3g9#4ק(6DDDx9( 37(OSOD0˖]Cc*{Qc\w&[ ޾eĴg̚=go.Xhp+l`&1&U5f cle06f*`1;tf.3q`Y*f63Ye0|fĬg2vR&ɼX1kf 3q cˌg^ gޡ `,dĐCZigQe2ٲ_^=f:~a~.~s#l5¨>=qGs^}Gc<;nl[cO/:x{l9j;7"*/E 8Z8Hp?&3A Qƨ+۠.x_U>9bMs"F; oG%ʌ%˅2kv 7YrVCJ-z>EA pʤb,^oF~D+wxn;i F9TvtCsȁx*%FQNO͗ÁT*=Mشmwǎ`Kvd,&qCSE&>1tb3u|x}{/d\!|krg9|'iA)pml38Crn;ĞwD֤6p bg%^Cʕ1@{(k[jwc-Eo德pܪ?"ŗ}e9+b&;JĿž?7rHjM@01mK{"Nh5biөqQb*&/L%+Flqr%Da΄E%Ă3b@# Qeؾ]3F7KвOPAФ`c=E 2½UsL{hGh2K2bxFx)?P:xUq:!ð\6L9BN+F^$ tzpǺ%ް<Bq 8ÌBreR!Nq-2P"{-LX|}ӆά>7R.XWv8LSz2lszIĢFW&mݧjtlL[ti%g^xF\?Ǟ3u~ǒ@e"kq3pMЬCuJvC'<14 i<13?sO5:7Ϡ=~:K/6JUp>.8# QG@kkL_g󎪓ՠJ#oQ^ pخ 0?tIC U sV0z6Hz~$6r2CeJV2K,/ejgU(C&Xkz8[*P+S*g2f!XveM%Ca6|y ˍN6QSrlHsl@_E #>À8CqidT [ؤj*Uk}v0pk]VX2YIƹDnàB4l{ t*"E築 Tt)^(Kx܈Nu`kdUA`4k [ PUF&&6xPǸ榙*hт鹻)]I=HkcitP?ı9y0TAԆRPTw  A44w Q9gܔ2TV}8(TN7z_^L6q5獒rd8+]`&VOs ԙɠI"BmiUp&)6/-R@ҔV@ Yvӓ׌eQf04>5-y(hyRb3#S/܈CJB:)KHZ`oe\{\pGSVRybB 9<"S2uatЪ\A#QhH.UvDc ưMD@آaQ1p7'1;I]S6fCQ_nLM'q+pqm|3r6#9s+Yj 'XYyQ QB]*Y1ϥ]VVeuܘ^oö*l#×`ջ@^[a ,#d ?ײãտrT J.l75']4Svho";2-1jKŽ}Z¼wna.بw wEUeNDOnW̪ h. 'KXcv 4*vʗ/~-{kkܞM%S@:lMǹE|Ut5sqTz2(::gd5}"k,]1HIw%h7Wrf\>D[l*$OBKI?f_y$ 2cwyzp?ZUj%@>9dc 0[#jeX1ܓ~>)6j+C+wڣ$2a{h=_|rǣ;dxukLE(hCխjCuzI\ro,e䀪vC]UיSw6@JW~Gn+L=Bt}J}z8#ق.BWAi287Bko^EkZ#gaa#@!h!#!l2xhu9|e *'y5sZrڋpq2X@۾{s>Np3|I9M+JE0e ۧ_%#/zyaWwEZ@['+2G>9/ڸ'j~uS_l@L^[DKl]E>QzpU8b8 _'!\!#> stream x]=n@^ Drߏ 8A PPaJ"0JS3vu=߻er^Oqͭ;tt_N_ڲo{ןrjini}k羯Rwm=wc,G<8W xđU bACN/qÉ1qE̺M?<1wS .qxɨኈFD8qD|oB`DKDU 1z :#pEB` "`!LU81Z-MPdo" &`o" &`o" &`o" &`o" &`o" uVf\AcEuVf\guV\::.밺N::.NC9E 94.S]~@P`@P`@P`@P`@P`@P`@P`~B; C !Ў; hB( (( hB (~B; (aM(5Mz֔7MXSޤ7aMyބ5Mz֔7MXSޤ7aMyބ5Mz֔7MX9X kn{Iǡcۭw:y ^|kendstream endobj 161 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 8410 >> stream xztä́― 6)B!;j{oݖlIG{/l ۸&!B(@h/!!;+&y&S)j*F-S˩ j&zZE͢VSS4Q MAR}9T?*SG%HI S)+JI(z Q֔ 5B }}ͤToJ-,(K-|CX[;7#Гi)3fz7*8_[[,~s78?p@WVťo|>;}0{1e6ރGFCfI:`',xwq}- I 6U;l9lkmķ#CG^{]4j(hc ˎD0F~NP1_Xɦ+3!Xu;GjZա~#CVH #x:U#T  BUiZILY|,u ,Y`-Zz+}λK}q)>B:C03|~|: 1$Oe"?72Pd̂^sfM^;eDuh̀!zZBc`MwOs}ߓPIho7%PK(I-:Ot%?n^}yo}â^4mfɧI}@S pIW6H$Ҵfj@xfb%Z'N|mx.u"%a0071l{Me[^{4J G[Z;:lj3q%Y$k֡@#z_'<LP:ɢF< fێMe$b34bKQ15p0F39۠ɽUE^c2G88O~.@?Gfv\gWB饭A^O~ v*FZO2@ƣ_ ^Lؾd7A1Msa #/Kn~@7JSdsH\n0;J;2ll &ѽ`z¼ Y?((c t./{VMY2@C5UaTٻ8F|\Mep6( \F4yuF&%!-;-"G?z;'D16ɗ O=oWeC.P8/]+QgftK&OtT  ΋УGWX%&u7-9d̯7%%aI!4]a5)qSpT2&Бg(Czj"eN\hr飌W_p6UѬx?]e\Sy-ɱ 'u:ih&FEہ~.DWRC-?Kn$x-O+? OCNs!ggGz;ls?Y4;b GX:rH+| :H"P ܢceU~hptѮP pcYHTJ̱ \..4Q."KD".wCw\Q䩘BnFԿ4_"2*g}]^J讐NڶaufHHcTE{Rď*k,DeF( G6Zu Sb}qҍW@ Z+1e顈( ;z:rxgɯ%q6?5L(En>\rcK«+uŻk)<q Z/''AJ.`x`{L1}e[W"yX6Q cZGAHY;:8أ/G* ߠ ^mrAT՝E=]ը=gv_AL;1C#Ꙙ6fPw~g2}f#ıTig ݆Z4RAdpeq"5j%Dctȍ"ZϮilbJA_tBUBO*QLUir~BSx*,*8 KM>M`$Gwaο -[7x6 (@cv"qĝ,PS}x`n/a܏9ID52BB]EGݦO4ڟy+HdlОJtd/(g\ꇨ[~-~G_`OF>0l=Fn:_.hʭïWO *C!cv<+R$Yy܇aA*ߘIR|X+B[<9ZctcHawCz*Yj ♨ZpG3\笕3iHbD:+Ǎ[M`5K'HV4i<;j#m{i%'EPoihXJ M=_c:]4ų (tޗE1(z arc%(?B9wo*šzu9 z x`7X]ÉM(,dRds8reDn; u"fA^WaqM;^,;¤z#znB=B^|_9H ,ʣM yzw~HűO+י. zCahZ""x,|0׋oWg@n IyE6H:$umuKeK+/?9;H}¯f)/儁=iUTIӲ&4~[R'  edKSUAl" ,~˸(pC=~!SALV95.-ӈΚ># IrS_bOw%W{jem]8+`^Mܺ3UN(z\ٵg5ں#F3{D| -=KGRrHoPsV\L0ZI|3WA~0W+*2RX+_yDAǤ5555DW{.C e:fHduh<X(RAa 7\D-F3&\P4 Jr KIAOi>R(UF#[YլQ^g>6uDDDF'5eD֨j)bZI 1⩜Ӈ[5e&@bVib&^*GqO0li͇}'% RFҌfqN} h=S7џ- sZdC3.u4=Uە5F&O:d@XŴaDvlvlAcU9uIk>)nW+xENk ֺ8̇ŋIhg_Ĭ;|eȇbФy~ "/_ X3\ׯn~pX*TjI`9M&3S?+zJ W$t38U2]'Ҝ%ft8i\2b%L^_<daM&OfZ>ͧ[:3,#*"ΞhvDYŜ>`i;|Fٲ&hx(Tr׳zLe!"$!%YliS\!;>zU8˴EYja qS9;Wɽu5'?pZؠ Ϙ͵`r3B9Y}U =V_aOpݤM3,81Qرd KAXI/B t&FQLo LKva/~RIѺS"t95j Ħ&/\JOINOMϽs!Ds/p&R oo`+F6,@}( kq&eT)[Rpm<1~_aϦ:M̖Ŧ&$(8e'h90]ģ%]HzAuG;K,Luya ,v8e.|MmK(\-]pk Nc8 glRJld阜 0VD"fz[MAAqBt-4aܪ?ZGn^t?5yĚ7nKOU6chhS/d: r|u!ƾ| QxfDSobKl1 @[\RY镤+h ``[l\%tj#EhE(?1!&9iO_ZQ{AB{/HnO?6~Լ5|5F=pƃgiL:5^.Q[JR*!IF)eB1OtqX+hw&i?pfgl|nIҷ+ G%}gvRDM>M2^R:ZGXqE<$C;Xw3LmwfZ'K% 3*B)mKvdڗ%i$L$EKA2> 25ڌ4.-hÎ"leį^GNj"^PQeJ18["1ϿGbkPgTohH/Ņ^~Q3CxANdn4Wʽ\+8Uve7r}Y,:,zO 9qA}v%FP\} VB,vff_^3|X/l18U-AZʄ| 1ڢy!U$Rxmm?;LgϲEWb}r_!sw;vb/[/^:yzk8} uv"BO;>e'EjZ1/0fKAA߽(Y̌vfћs#jo=swNԞ@W-Gҿ1r{h]d}i7bǺ(; n_VM1P7E#=M۸-sqs<۱7'shi-?ѰNG6!0聲ƪC{뉇.vM[ ;Mv'OLyBM+ h韯?]1?9w@~}15v=N׀Zes5Y[vAOן ϣ} [BB'}KKVa*94S 6ЀrњrAX]퇊#KHif c{vޙd7C^@ԃ'F+~HD#zзk)\@ `&`f3S<ŗ,n`u9 7B!U8Hxtq6u:[??h?7Ŷ$؞j#KozטH.Y "4x2kYzvdE}J`L pE0R=fE%69ߗ{~Ehendstream endobj 162 0 obj << /Filter /FlateDecode /Length 631 >> stream x];nPD{;w? n\$l" Z.̌)"pۧz?ݻu~X֝utMmX6ۧo:]ֶ?qԟvޗal0ͩr6O+7ΗϟU{> stream xyXT sKl&XQ(*00M}+V,cI덉(FKbx}{Ξ~Zz>"ʬ%$ 'N;B,!N¡¾7B, [m),`CJ,/ymGv̙N0a|W_[ mpڎ.CB1'pmcmrwծ`םK|]|\m ֍7Y$w:tR|~o\X$Av Bw8\bJU=x:z^Fo3v˸N1ir䔩Ӧ:s)j(I VRUGpj55ZCQZj5rPj!5H-Sԇj 5DQ){j J-Qtj95⨞T/75PsT??5PRj b(+ʚ j0eNZAFQp{Tď̦ 钁 0́{^ }bo}~+otKs˽ҞCGc{l{};jɪGmXm66z 6hӠA`~j7$aȋsn w_PW(Gߴ{ <Š)XWܧ]cDr"jT½K+Qr+~3it0s7D+$Fe iA(1xĦױ[uV/a0m@E;t,T cV&Ӆd=2oŴ؋N-[aNIǼq"_~=BBVt@pQsE~!C>_Ǵ ^fx@U" mpyH"fX&'9^g.z~y'ZpZ&S, +we7~gV,p0Pv%-}omu*p> ];WN ZR+*Xpo `Ocg woݾf?aü|7BXILEUUCq,,7\I0 _2KeϠq%,:qY,bT%'Hgza,9 l }㽁(:V|fnḠhmoUȧ#isa>$NytջL~Nrx!# ѳ@ &MΡY]r[q^c:O%asP&e?=<Oo(w$=4&%rTkzoVNDR=Q[k%ݫT',iG_ޮ GG` SaTmx,i? ʟ%`B=W~XlT[ְq+_z5X8z8TF_dFz z̙o>~rScs8Ciak;ttK|e} mƣ/jJ7Ce9l[!yݍɞ\1MY `C+1rK?C.%DQruq:KC9/=_eAsO3a.Բ0~Ca#"{ە&oډ"Zzk/4dtE,7|Sݰo }Ҹ԰= s/0ImlE!g}:쉒>m:rݠ]<'l^w_%& F~$sSfɵ$q&5|sDaVt$;LQB:&a\J=va: mܼ1#a׿o*T Ui26'F{Dp;\/ @ +|R6sCZw$ @0È!JwG)£gGx7=۝"*8S9#f:Sś }Vmr*ݕ])3&`p2ݴjG}dwUMҠRܡ:WJw[%كމf TH># ICCM[NkeITS&&(IgVT)/&4"|y[3A{ٔ nV,!C,`g4}<=mfbH&T˥ggb2D-Ex-|~S@ bad Y/~C;FLoUtRuCWw繣`Aw`.Ih'8ml]ru /tyZAdsj3)tSVQJ+N/g?QBky^ H  =r,.1iqSBKHy1Tڕ#ڑ%&.A_qVاyB+!4FE'jCuջd CT6(Y63RB)٨ -Xsۈ[c\Bd'kA5X>ŽLYJMIݝa[L?KR&tPl1(X_1'&C~rfL )p^ jەôv/H\Î׌̸|T 2LJ{/+% \Ct26f]oX:% t !(!U`j7 39]Ԩh3\ҕ7:tWyuCʃ)o Is{X4C=;t/E53,Zqo^k^hӧ-L0_-fF#JEݣMBòŪjdSv2$3iZTdeA%r6a5e 西p1# r`}q>BvAyhީlKo":rg[ԐU" kvGa?888dSQCt]A7\ړߊ"d-^& x@zC1dC_{rv6+k/?e nQHWFJcѩi)RɄ;fAkO?MlD,k\̇f?Ynݶ%c/,z_8\]\uJG4(a G9wx[:ٴf.WdW"""d*-|x{Č[4oڶϢ^ AȽP5}@wMpY.C(.UDF(2_eG;r4AW;is4um#;^i |ye*Gq 6<<@ǙHAJ2#ώLMʎCDOU=)jcŞF79Ԃ=Yp\ڰ*>.yW:~*ʎe^wn=xa /akhd9Ic/dڠr? ?Z,\7C [Ma1fRtXU*Qzu5غ),lhïƆ~AKY.擷W8L.-(/AըX08n{|gXy}z@\ w3uq :x-uC1x}k7`(*5"TKAasA`~I C ց4;︬iW:5PfoB=Z0~ 1o4QMڰ4+7<&Mw =|h쀦qyo[AtgMH99??K2~'Џ苷}Ց·5iT0ط_ӹpö"ׅ̍ߦWvI%MƿO­$׵!TrQkyz_"a8\@2~_w#ȍO$C'UsX) {oM_$q $;}~>B>  8ZQ ~.<ۄN*?HµͰQ[!GR[mƛ|DsNm#jQBnWgW.&\uZ9L?Hzts84%9KVJѨnł`]DPB{Q>XP%,TƤ0:sTGP֋k;3fv&y60}=7aKq+T0o$^r{i( Q;r0a6@ M>^2o] 0@F]Ɗ7ج҈EP|DdkI| 8Т0uyVQAfwEgz|8Xld=W z  ܉z({~H<C_+Dõη! QQ4pUp2cdEe2gMHCf0οJL݇:™{PqKHDJF';?җN|-ǯqŽfϜ6DSQRX?*ӟZfلsNY쾱l)V=yI[/)L W+w/88<:!1! Wˉ̏,PhۃQ*Rdt-pZJ^:@`úۃX IB4=#7i8Tz?[-hъ~KDu؝3] f0cs?^eLRceSK[ڇ3O0TQ].ov;7d ;s8</߂ГpN*8!0 C=٬&g23T tb*+h+OOO[,Ф] ڇTS</`ȳ$ˀ& ԥ#DN(_yޥSujjH:Gk"U3(vvñ3-'aj ٯk5 L7>{ ि ^rޠO'|=K5lΰki/^Ʌe˗حAz?Te֟i'<#QNZZDע*QRwy03@Ω "}fcpG!-%8=##0"ǫtibIj uźX> stream x\MsS=Φj'WV$%R9)VJʦјAcvJ2ͥ\:p4+땢Z]xUqvo5>WNr VBN/OۥF+֪*FoԽ ^+R2)t[j=3]u0ء^RRf™%n@3oZ\B]sY*&"u}t;K4 0(a 3]5ٖ# |#Q~rej4hE"KSL2ό?BZ]E2^;܄dʂ* c(m{ZVuϯM|dO(K,\Vd4MhA (+t\Q[}4';C8HDʷ=hy ="B9|- BYm!lsMqǂQJ Bׅvw&C3 Ѣ/!Icw>BPHTʁ ؾe&'q8bB|Y$B\?܁4:%#ll4n:J G!07"V)2lu2e@4`4'-5,K烷ȣǡXArco Ɇ ,21%rm:S=y Ptk̘o03ci淜QJD G*_U0'^7y|x=a!=t-' {_:N._?+㙻0^yƛo.[j-*rf6֣ u`El 5]4t*ʩPa#cCok2-eT fIc t9wlaMcƀPfkL)Ȩd.w3|,}I_܊LCqITFFڧ-5 i|զM0´(ϑt58.X][W[0$!>7Vp!G =fxDhOG}狾C_/'*L~rRZ9`J櫻w ca B8Qx9 ?'H)n?2P1o Y _:rE)_i"]R3^T[H-*QA7ŀE'BO=Ql&ܜfL*L:]q>5E{F/ G,H2 4t-ћ|uz :0endstream endobj 165 0 obj << /Filter /FlateDecode /Length 6425 >> stream x\YoGv~̏ 2yF`2ȆL y(Ѳ)^)?Yj9U]M=ٷSgR u _y.n噦o.Bu\\zƟ !ۋhpqٗ}ys>ry_>/M<:m5T҇4P* tZtxM}) xSԃgaǬYXMߟ]ݗ˜T:|AUJtxN)e-4Л u|!{ bsvzNǠC\O3vNqiNcJ<@T&)sgX<Xh0e{][É;Ҙ@mJg=zR!.~qZK),97˂rKہyZAQ@[j ah[ IrR%v+2㤭1A3Cye5s"<+ >u̍/Kɭdo***Mя)ҘKs*:|,JLu>QPp#}:®E L5!MMYhjimP@Do,4i F(%lyRt~,;ᘭ<3"p'Yf;zp;Z,Nw };L`[DZ>"ѺPoh>V)U+C"^IAغ}/6X65ܴLV^SJ{u Ix{sHZ륰̾^oSp}#nSN:5A4,RX$}4&MF,6ݝ 0t*e !er1NSSYaz&] l۹Q%nd]S蕮2,W 7E5LN=-uؓmhH3o/Izo'DYf7*h*Wb#p^sX7`ڄ!GVNt#2e\;KE DhQJ!TZMEйLCg]\J§̈́CeCe Rc1̠{/yu0'·3%m| Tymʤ?˷CUcvy},Cĺ<=>ukk_Zƅtr ORē+jQ , !u\2@ؕDjCPXDHb'2Q.ė4 C-ޑ=h-j i2)wktފb ihַ"nR1w2k0*8l۾b"lu2f_HL[(8 a/͟'cΆ_UnҫMO'C9m6Vkp1 ^[4[ѩ>*/XyW 3߀1&/PUۘNU?ZX̔%ʀE6h^0x?=k`8$3Cܳi76'*l Ԃ87͸vCFxL15$$AuYNߊ4hY;p>$P:2%8w={ &͛Fy{4odm9Ik"C^c΢oJB( f5[6Bb;66a@X@ Daz y 1XZ!\;Kqk,%6/[:i@mAѹ4&G)h3)Jֺehݨ)KUC싦Q( #\ЫE l$R C$|JgTq뙮JsNv3X*j?hBeO!2)Mi$,5!\mCLgNSŚ5Nҩ{m4X: @ob'KUa1 UATe+#@RߘgϮ0'y.*᷽Ǚ.UF>Lpf闚b$e9c_ Q3B/:!ϣٮ,&pmEI:ۤFZ',Ht=:KG`CUͲ5=I7_1tbJ[v0R % D.޵&1=5l'kRhnq#MSve>Auj4bN)].YT$ ƺU\Z!"H+a"0F{ş?M[ғyfYv,Z&k99[fKl bîҨc/@ Mh"M@ r!u(y\rK58IeEŧM>L_ߟV59h|cOgKus7ܫX"(O;ZC4lxMW#Twhmc 2[J+fbQ`qcJeXJcW%:idXF4 yZۣI|9`PHR^LIMhd$)Ep-X^41x{ ,[z5e)dEV@ndE8+u%+غȊ1djFNP˛`?htg+K,k?o3p"-p O [@vy{SP?Q⚺BMfmEO[ڞ%ƣ2 wH z\wP.;LRX&6+CLe{DOO G=ENERI{uuD"\@2Z^f,E{BhA]h g#%udI# vqޞ.념)$ 9?lEw/\hjZ+ꂖӄ6F$ii_JZ ZFf2p֙OϵjA2utKUd7I1fR'`&G${iAtW4C%se7<.ܘ.4~r&ۨRҋNwà)|z@"a!-o~y!-NmAyi"U Q>h9鼊5cT=~e1c=N%~oZu@JkY *&S7rm%g=z*ҼjԺt^0wө -ikUAV~ʒ˷ =zjxMrDvkS$BֵruVIFM܋{V&ǬwVˡ}>/,-' f?sق'tB?j Rq.v&fc>=ƻhߒ Pʉܒ( ڀA*vY&w%.x;P5^7"=zy 2QkCޓ.Dp?ۅ+H*4.H r/+ Ocwα܊@Ԏr(ßuZ-(\X@zٻ0eЄmCr~x LX~O_l(7|H|t}4w6XJSM9rX^'2\xuS?"[v-koiR/VxDkr=a)QlF82w=rwIۊaH (*˦{jI5wH_:C :! >U[~7Z3d2p3$G1xrGn =~N>tbUIY lkߛ*|`J 8*24Ơ7PYbӣR6:+VST&]m|r>>l|Xx\2\*>|OhD}סCsPI'xt.QfhyAH}@vԹ%.Qg6|ϯeiOlٗ1àwج: : z+*,KOijbb;NJe@ 0okef! 8㥁/owH ~ 8tucĘzCrʾ`79[f'&m엎` 4Z mU]Kڔs+9d@+$cEG`IrYDWAmw#Q->bJQԶ^[@I)=,<"|cQJ.eu-28U]h#x,.h+(ΦpP,Gæfoze`$[#5.sl ve^#nn rt+*Ie lvm> -@00endstream endobj 166 0 obj << /Filter /FlateDecode /Length 159 >> stream x313R0P0U0S01C.=Cɹ\ &`A RN\ %E\@i.}0`ȥ 43KM V8qy(-> stream x]O10 P ]ZUm?eB:gׁm_Xց$i, x`HSendstream endobj 168 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 5572 >> stream xX XSg>1K#]\ZNǎvӪuPBBBBY$d#KPE\A-HV>jmڹ3;NÃ(x"&N X,֤5[vm\׹,C3Q?(F"`Ml~Zn> JЬIe c/[O.]"xur% 3%<لt%K$), wĥʼn3b_JoJ _֤$2[RbB "ZN1s$JrV̖حq'Nړ$]L!>8%M﴿O@T >-XAjoOf!GdAj}l q#_&C6H1IC h5iXJʩ7ƛbG(`rJ?IZn2`ڡᐮw*K z:rcp2@WI [\c8A˻BChe5\ZcqcESi]{ye?3UC+<$7 -A}RD i(+/r.4wW"UPHI,YzRUe*TRje*_o(Oiϩ.U(7\'{I~zGC6hM OZc ffq > vaQLCuifh_W|uz;FqhGqL0sL$f5Vq6ga&^-D'\AW^+pv)f:ef>z~Gh:ϣ+S͍=yCǛyqȌG!pވp ]=pސ7ٟ13$.@ah,6SZMcP {Zd Ch->xh ܁b/L>4)`:3@Dt8r^ nFNh3F6|F^ {2#+f4sù:qfOL6!|cm3@>z8GVbv6Ȧv (k4`$GmgMod2js&i 9j! z}>":ͦB ^ L\*@OIJ3V3 VCD'4P` JU֙ xN 6u4ypu&ޏ0y8`40V(ke ȉFs/~ hjyR'Rᐺ+=69_ːQتrmMv]tv -t Yھw@¸GT*M D%)}d*4~Tybu\hL t D!">[yu哆)K\ȥ٣ݘ ?{o6lF2 GYMc}1s* zn!G̒ڱn(^e2d-)mןp}Z[/Bt,Wb9Lݞuni)[嗾fv;%WW5`IA8]o5_:C?y/!FpvtF U d]cݍ:磭P#´wzW".?@_r1.N\0a3SG׽G~pt O#w]-زrOzn~.7C}>VUz ^+uaW}8;Sۋå**\] LP`, *=&-7<6h6e>:HfHwU!g&v=\AU8t)`-daQ@JD}u{.{Zp@YhkH&YGP`Qչ˨YLTY.JW_n~F8fa@"i3+76gh̷z^h5a-ݭ$Ąl0+)%;nq1ZzR6Թ:NDoneS5Tjj'@7|>Nx`/^}Y4Ìóz~~;}6d`*/F_;w1yy ^vh|g\nV: mfOOneD5\zI2[ka9yg9CߘASجN63gpnøt@}!|C`w6;0&4l_EG.=9tD'˵ZGoùy3ءPR$+t'_y[{${[~ᬹHv%ND7'^/ap}zKq^W3F7bB#~?NvT6wPkBћx8h-U*rg0_9QA oW]m`#8a摹̺eǗyonRu@[]oE@v֊sHA&Uu+EquLq4SQtqJ5W];ak%yHȌJUy}}bf&_Ce260`ѯs^ESYYl)jҕU$% =v|-:<.3?e7e.ZAhhz\i|:1ޅ`*,.sJ,YN v$. mRPw~nӹa)|^̾D"g*ȒԬ$ylL{w~XMel 67]-R_6E$f>3gl;=]ETʍ`6[f[x3\s?}s7V:b~b㪣)9U5%N3UXւfʖꖞW 3\x.ay3l7G Tyϰ(_xn:Y\ ~'yS;m9p!'[#w}Z9HCmzBa(Q;I@&Z:6Z@ M[ ]@3;aP Gw$=QRˍ ֒vz Ow&">9Z_y]AzRɿS$7U}[ki0;)0Mr<0k :\F-Zh*SbwKQI 9}@fQ@+{r $G_]S meqԸN \/ 7%7&^p!@ZK5G\UNQ:+R앮Q5-P5-i >zڦ44  wV[ĞȨ>cL.<  EwoJ֕+',Ýt>wYZ,.޹ɄK&NICA.b {L2@c f ?3f<+q`trx{8QP_BU,p ւ|(Qq:iT d45#s04q##K7:vpF4J* D:1`±Qi.7ipR(%Z =*[o,*: '?is&x`1: 9:1 04=(il;DV[p{ B  9Y5­̊MV ;P?V/*P9ƅ3>B/#||2N_E*̅_@4ߣ}A_!yKV"HLNLvyZZYu ?I^.ilxI0z|f{Œ>U T (+8Ouc9]ugmdTT)ǁdVQn/4͡IW s i첆ZW˱C/)ɣ8}g~ҋSZ9/?Mt( BK!s3WgoV T[$9*N!; <0ꏗ~k>a·e-K7mY! sAw"wJTUyʻe ꭯Pɱ813d6L'J:qziF3m8Ͼ|c*k8YεD^D^Dn//A| =C`4r62 eeŚ (11W@l)*tUBPeϼ]ZDu ,py8Qa> stream x]=n0 wB7#1.钡EL"3}&HPruNq*&q\\Tt떢> stream xW{tSuO bљLU0"JG@yMi$ͣ-m޹{wڦMo[Rr By.ꌜk9/V_(9G$~?+L&J3ׯٷff{YXm0Gs{ ?AFrdTqz6k,C xɥ a'Ѩuʼ*CZ2y[j%%Cղ7LT"xłyRCIf^3 Vk+ y/4꼩Mjj j]zmZWYPR_mP4UJP+K5*D2rj եew2c<8sOu^:;Z ޹.7/eln:7U<&Hѷ/>9']p&{s5 ,;H )B@SD7㟀8.*[K}4xyP z7iZSeH* T۩48Ko$]/jI{` mC"EXV'HFʌa;2J' '~v\qk^7/->% lCm9Q0`b“ "”뭕zazE,|KwQ!Af̷^G?R)-wEd)^ ńE"z08vzd0>sH':[B=%CϢ܉ϠwB+2'>`[!Q|a/FXh%tAրC1w6AX0Ecp'牧7;SSÐ ;8oe `/?}0 Z"D!VyRj1vu A;l|~!\?Hf~k"էqA9zs!t> .Q7ho][$QuKT{eOB;$jB]u+CW>2V4Txo"y: VReyk@ `boBoJP/O ^뤽v7mӃTm ,2}pvl A;9S(tB'*֬- [FhL tA "teZ8ivIS_0 ,c4^7yԁ&r'F7AgޕGFZ{o>ƶiʠ.R(eg(F DeF铛buʰPrL)5/yf1d+-_F+]V=!}0CS}ZMC$YELZw!n#E CǷf J@O cP_6:9d4WW2G-4Û+r{aQ @a_m@aN wUSh*G}*qVCUUu#Փ!WNΑǺ1Bɿ$]_ L i(G+"QVPF偒8`<1`X֕hJ]{\T 3[5|*/2$AcjKuuuv+woނ]pO,IX۪tₑW8u<3 _vl]teBd± oQh?YL@EIё7ǿ,` jXlXROpNI&HC7cEu8q@y٬q`eX ӣ7#L /JSʟ?Du2ח8qؑ!,pLN 0w7m/[j-1x*,U1nԴO܇@d_ka.Ʋ ` L_-2`մ mkO+d:g$RcM)-G~fuVr[ΰvz;OA~>'rT)Heyzcf#`ЃanT9tn〘,WeLyU&pXYU*F,F.3GVbzUF5ཱུj?@4=e-'YN":@="nF3A$9w qD0b=vM)zNpaIJVpq,́gJ6Q2+;4ĻMG7eh)yRwwwttcZhGI)C!qzG1^e}1k)Bzp8~eX;J;5,nhiU6%޽x;qZ9WAyH ."q:҆SJk 6U8Q͇聞}Dh`pbDqy+~?,(7?VرE;?bk,{8{l4eAaR\BxAôH.~ ɻ[/.ۤ.!l}ļR\\]!c}WQmhu=q2׊Ɗg/5B\+.7^=N.&s!o_n݅6Yu-혯*+=&mk7R=v62 ]CKPVl$g.\ӲWQL$eѨEwDլ^VVCQ2a䬿sqhXL 4caC2{_/?[>FCĢT.COZj" 8E]Τ/sEa9#e~ld5_i-v56\Рmjli G#!2{)8YuM/>#B<#pׅ$ɂ݇|GHP.Q-F'}q!aB/}VӫvQeva*ǥ.e,y|:9K4爏bC~Rcɹgf#%-JQJԊw ]a[盰W~zeӓ/QUjL~4G!GTEgξv9{Y9²endstream endobj 171 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 1652 >> stream xU{L[ǯ17 *Kxu*K(ISmIڪZ4%i 70ļm/`y1- $HUdRmڪM]*[4\ltt`y@ (()-=unO;Ky \ݣ۠Pٗ tDϣ_(Q-M͔do>kǏ= 9rq \ SJJeT\!C=UCILQo:}PTw@B5K*K~A)-[kJIՒRZY/dmWR-TYaeX%v;þ!`;xX>vMpTE^[?_m[ɹ6͙^+DRtLDeM|ޑɫ>ThkHc+W,>|xI⌕6]keFF^G5^LU5r%a[t@Mijp㖐3CD9ǃNCkm%VY{ةSIk|B ORxQEI!ynÂd # fn? SLO}DWmZCeͮ4A\vѮXyz~eJL&('r3ЎN$9Ғ,ܘ?|d ⫵ٟvi 241iو,A77}t3' X_ءuAgdr;:성ZWQ8eIf"S128}^L!uMNF[HW'FhPj#GgS(aq妏eެod GC I3hző _qdf|`*`V2?m 5'Oj-͎g N"g~w!]vu|V.,q=c0_*BK!"{{eeTjp#,3lhk"8#&gM9;fĆĖnqۡ#ݛz=➄!9sϴPp.|dɗ晣v0J;NJX`?2x>4;<5~0qJHw+Sڊ BkËRĤF ^s)t ,#DeN*JK.b_mT3_ܭjW%UlKzz AId#|W1Nn[|_W(U> stream xcd`ab`dddwu041U~H3a!nnne?2W ~/^$Ș_2as~AeQfzFFcnjQfrbobIFjnb ZRaQRR`_^^[_nPYZZTWqr-(-I-ROI-+IM/J)I().Y000000v1v3032Խ#녋|gB~choܾ+'/ɱtFEyi]nތv?zPn߷O<{>kڽsaE^{sIw-GºyX;rN}\}HuMy9~mWsfVǻ]aJ\~e-b+r3˫ns+ǖuKvwN}Gl߫Z.XfEyl2+-Rùy20Pљendstream endobj 173 0 obj << /Filter /FlateDecode /Length 4528 >> stream x[Ko%vHAať(.MR_-% ؚ鮮W5Q ^dzz^urH O(<>y}DcF~\=VbRj-FjH5A70TRKg 1Zk5S|lTSnW S˓!ܨLq|VrocO pm678 a Y=Wʍ04ûv[xjS'WA(:A[烕hwP1:M5(ө^T]"?Gp&8{t8P"Ofp@7l˷ըC@%l\%/Jw׫ vا ZvqRv>YVY4lu &` 2aсvF*`:O"R`PFgRJD8HZ{?zRfydgѨH:)&qOBY*2O-Y6g@*YGO{jo:8)g}&ʡd[{ 6 _2:׉k|*\ÚgוAf6S,ꪒTܸ՘o)1x)@]D`-h#RLGB"s+A|t~յl$HEo/ 2KdORL&-* pi첸樀@P5=e*Xi"ō 7&(>>XռCMUmhGV بƴmUνY#ѩyTLzl>n osل2޿X=x`x'Iw(7 3ָN opSWexQ.0wMoXcb&Z;=K tx]Khh _H 3DuystW .y|X sMǐsaF~$R (b;$/eb5nj{1Fp}!Mۓ"N;AkJ*rFf1:1[H!M'FIAK Ѕ)rA8Md!6^/|4|$z$8JͧxgG'}setuz 2vr,8RVJ|QP%( Ŭ@M/VH௟ u4!™bB*0 zeB0T-9d9{̨D>J@4W<(3F}f]Y21#+kR:a?TΘ4+C )mu'\ [ >]O, |9gUB5nAh@0L S(DS S)ǧڶiYLXh[v8z@ԚUy -ɇ%<1}y&妽O^h,yCviوL*q|gVAtЗ,Bq$Ȇ8f4\9cdh 8MN0Nre,M*5(=`c[q|{vnG'O)DxdAC*s=jP8ɥpﺸexӺ䤮mlm\MTX afp 눺 :k+k!! FlRg!r]uc*A-gEˁ?/PţǓ ȫ?HEzёsm8k\8єI:&T! GʸQ#傈K Ug"}gPaFaFo "䕌=ҍS*9fl]2h9xJ "I/qRO0-._֐x6)\yF>RX ~kK/| ;VZŦ*9m/?>9D#eQNVd3%yw|Aɐ I`+iݤyl\)ONgŚW͆ӟnBhb(iر^`m(Ǜ%\nXQXHP*֑"/ *m=T*h y9a@}I3<9w\ d胵s}᧹oS1%$lU/ ?U] %F8D>- LICqjfkr m|+䣃auܴ\Wa U-1뀈*s=ey?ӗ[zk6פ "D 2seDD+!W;"6 Ȃ}Woҹi(ui1nhmdX., ,.#|)D9|!h :I}(]G_AOo](k|YHj nr&sX]oJeO2$_"Ȭb? 7ʵ8I[!s`}a5fP c_X5'9—,qa U'ȳlBԴNGܩ{ːW BQdJg*}@ⶠ2*W+vYE#ȬUENbW7<-$(&kra !Ĕ-2G*[]Fit0p d#h"p,4iœ]7>bL6η&veACޟ'O7#ֆH藓OEy[2zT1-`J@ˇT4MS7R73nJH4p {c-Fy5}17e ˰?yMbQ%Þ5dsS-VLBl^PnEOff;EM1 AjSO oKѣ myۄgnz G#{`3wy{;Dl.rq 6$-Hh7#-e╩va]Q끵V1Y>bȀ_󴑢5ڷ凃Lׁ~W=l`>N1rljj*MN/qV{"hDEQ_y( l6MdjEtuwqfcl<6"m]w>*4Ck(~h]TuTTQShuق3ԓ_R) |[40oI&g!p6]X⧥9E7hZk nkL۞F@^S+ zFL-DY"6m۰2 s*IL461+߆da-KMYe7<_T_2|tUOwu=>r;?HP:|ZS:ge󋖎L|}yj@}c80qq SoN ȫendstream endobj 174 0 obj << /Filter /FlateDecode /Length 162 >> stream x]O10 TXЪj8(Nߗ,N>~l#GpƲ5 HeQV-ƃ剳B7OfUiZB 'mQt1 l.kSIT @s$Lg)HSendstream endobj 175 0 obj << /Filter /FlateDecode /Length 632 >> stream x]nPD{}@}Ipq Hue0%rNb-|zy~av~p:[|ܦ>y^74e՚jTg6u˺k ul zh uj zl ꑵ7 YD]7u |QoR0*M Fk65Y) `c22lLFF#hd1.f'dv @tB:]NHB\Kq.űRKq𺘝^bv2;x]NCc=b2fspBP!R*C A~H!)!B`- !BbƩ9'M1')$s7ŜdN𦘓 s9bN2'xSIo9ɜLA&!#O=9o9Ōƞ{O}ɏ[(ȕ`Q W, JE\I(X+  r%`A$X,ȕR\J[-|גoѷZœG^}a|y;^|k@?Lendstream endobj 176 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 6719 >> stream xYx]!P`5Lmr,YlQdْ ؀!tH $!|? W\>v5{s=w#w#x<^UVn8uHn(֍{$ܟ,|л{ݰ?-[=>&-Jĉ cFL={քiS̎x19V**#!69*A!37!##uٓ'NNHX+ΊX,JɈX IP+X%Ŕ DR/J{I8}IeYQ+rDƬ[>q6'o7q;O5q)Se1sֈs~n.A ZbxE'" hb#1D%6-Vb1F,$&ۉE$b1XL,!Ketb9 1XI$VijCDѓE%zO>D_џI vē&pOt'b ) xns7#$&ǜ-\BX߰z{ =wrߞXo}vwscFS_ }2fzC*5z3UBF%|]1!C4C^J -ɰôO `1]61)wGpUw=Qr:+P*R A~QN~Q(a`c: >RERzP/tĢ!\DQ=e<@< 1*J2 CEtu{O8RIO-~D1!~h;.ٲ'Kfٝ[T ێk^yP'rR y5X 3t}R[nk #xo"ǎ$s] ?Gh*_`1,HwyQgP98X.#w\!ٕ>K_kOW?Aj'o:do۹0E@#0K">+[q~>xǻu6_sfaW&7XD}[H).z߿yプ7.8bHwCdu?vUZTA@G PPNyjז$BB> I%d3\ }pr'qvcBWS >{08vrZP(=w4`zʏ?RC };Q_M%@;&B#h ; wL=,{ 'B@'QWw (^9X"`%sKtlf I5o[?' {)=xEVzd +ZY]`0 J *zn^VɃ/`%:‘4N~d}LNL fs2)ByGo~tɟ|X_XJpm&sHêT]+(~[SIjCZF< 3?ЎmYMPw,r^6X +8}H) hh9ikv>glonP\-TgVg~>iM:gKʽEmL2>۠e_!G>@oljSzH;\hu.7>;-o_A~i kLΝP)X!&/K0OR aw#2 9N:`j?t< <:A`DET&Ccx4C;Hu&(daK !d$!G>(29%9i2k<ۡNBB/p{+&-ѫdq`5v]4ny)uzQ'im07r.+Zb|ÂKW*H^&upXȝu|C`Y*qzjVUH5߸՛ vw@]*gjչ*&#von@~y2&sFQo$48 @˞AFp*X/TXNA;m%HHH t\P$%Bs3v'PR^X* Pk0Ce?D#iNr,zޖhI7g5`oP T%A"P^$S@VdPa#lM /9\փSX-.?\ p/P"_ZRǷT4#"q 7F/)o֠1耊oyD65n+ ۿqbIV\~iHIrxh#3d GsC2s*.7]~hKHܡ@h'12zKC'}o.fpaZpp$z.A|SN#gȉԪG~bK˗]ԏt  kH#i؏o?_ Ƣ㷱31yOS"z숀.HowJ0GqD)3aoIzM雯ԨTl\b.@yeeQl7qP69ޓdҲ9ذA;c.Itc q]L ALn=u\V[MA?ִ.we<.!n/=}pPIA~wڹF@z|ˁp۾Ş  nW 'ThZf!!tU#/r-x`OwRX4L݉ ׀/Enxet;qe%CP: bX\; (g!^e\_|[ E+U؁b1 m}l4FTo){@Et3/8QOs]n(2$9(&o+6N"=-ӧό≩袚Y8L6 Vk5Ā}nC[ rQ %-7MqfVcalV$'ici2r˼k\ 3OdnHHh34+I+T&+G[^nO%ˇtE<ƌpSArsW]B'Zjy>3ʊfkγcaM&Qs`7n4m0YvPJ <Ѩ=EY4D_Z[e\;D7 N^Զ5>yڥb_E9چR`VUT5ty?[^nH%7?`Oj+wjR^$Wj%z-}LEx KK%bM~shp 3i-N*APeͩv-F^DNP#介 Vh5:DeV\PeMeeG'g}4" Kk$!x3`AS4# ]+yp{XCѤ˟00Zq6 Yɚ|=#Fh4X8LG#VPZ*6Y&?zž?|xHVKjCdSl˰'ޛ .f&DFъ[`- QH)@SBniӅ5ysS\Yp[cSgtSF}BbbrlrUᖖHdTUwK[;pRBE~!ӱ %nieEic;.FI+ oף(Sp(0ȍ|\ʑSѸIhU$ÃrL\;m*36E'T4GچF*!ITcpTXuj#&$[Ӡ^dT3IFp]Msx\rCԲw^6vM)}|7#(UJwP-3dA2I뎴W51;f &4"sb&R(k?FфcIC JţTgTt]sR_y|I} [FEW+UZڥ2}P|p(lsm)5@.쬋d(vCy&؉PI~qp;(di.`c w `/.7 M48j,^&%6SKurL'+ܧCc2WT\1U¾lku^ppTҍ3&аϦvY`6kwZĬ\JU揿wFܻ7d{KPGtmMh.,htinltxjLJ6.5Y_p 8̓ `k%y|Pd8s+`?+ dfȀHʝ6”n=ܦq**2e4{jʚ*pB0ytyY@^ X%t.e!.{Ip dWBugw83|5VBFX/) :a/*L9`μr͛6`J6)9;=أ˫Sv-onOY~}dm掮O\\|ûa8  *-+9ݾ"4 Q{xDٔ|N"jU)@M1dE@}U(nԅsrGDghnh4M2&K̴mb8r:l)Zة̟ ND2$zEa4P}i8P.{6M`jj&mz\kx, ̀{]~x02Qɻ9”yk0Rz$wdva,;M2qIA_]dl p</ۀڽ~ ~y܅EnX"Јqp#s= mE39UC{ ^_S7eb媂\ $%^-\6ˁ90LiZFېG=>5ǖA"'ßqv,tإM%RLOvN67UF-%q),#c49͕[w_g*֔ͼ Ŕ53*vEr)W x 8xQZTM7A y*)6Z簢\iK;mN'U@_Ǡ,T$^iYIV ,r?Ws bD{_K%aXendstream endobj 177 0 obj << /Filter /FlateDecode /Length 9910 >> stream x}Y]Gv;A2hԼpHF MRnJmYk+Nb!H/^|"3}/NJ+_^BTQk=^|%_L:*=-T?k\s1W/_A?fyxb^-1$G?~甎4-z⩩sTVGrןחZKc 5 p뼁 9jk{p?Zܹ57oO bw%Dz& D}/lHf;X&5St*-ֆ^ ă0:Zk)3$5 K2u]TORԉ9OFd'Tf-_|x.T9/u7^o8* IP{-q.+ct+co^w=Z2igQK<'HsCzfC̉?v'P} uKks\%L%7/߼ÏQHՒcXtU)V_߿eki%ZSLktszz1ШT^~KM|W@42;5_.OB  p?.g`Pq]nj0+[ ɑ7 ah m %,cs$-hgo7` ^h`NŁ2&jt ;,->X/^kjD5o>h!aQ3߱7l#kٰ)as -(>6l}&fЏ"լ>ްm8$/ q,ǍWEMw34D!ÂfS:VP4 8K')q`Zu#Mh{!A^k('/n!-܇(L£T 78Nښޱuja_7l.džIm`kf JoLV 785mZ.i픹M:h,V^KuN+ &h@ɦnXq(ehNK^oY8#T$KHy<;(3^ׂ$H^$  Fhs zIaAn!+MTjg`ơihNSP< f$2͂i:C CinKhnC Zw^ by?A7x 2O&QCBPf5}>, *iAC% p)BchI~ln@IyeP ,u,`Y88Ȁl`hG %$p7x`l@: mހh 2XSs'spd.Lͤ3׌c1-'M96 F (6BhhX*A3 V).O]Kq`=BDDOa-FmU7+`t:vNlnYpx_!QjF5)$Pڹ i hXiqP+$dJiZcCRj$"RaNZ6m%< c` oY8#8j g;֥3Ն|_7\.!%CkԻNrSzY8`TDZ'A6NcuFީԶI-wsyh&ꚩ-MF+ry`} :xS2^6ߑQe4)x$h>,-.a,Ա#\!15B>!P: &yrouZeT$X#h٧1Nv 70݇k'q*d&9|( %VOf3_[HHahzы#5 TWY:Ei8>hq>z HxUvW&V{mOfhq:f⢄!< $,F3pF!h]~5I:qhG\*4l 5^CHqyhe@L"4g ^ 7!i:D gxvLF!eGpwRq 5Fl>,G3JsH.\{ f?I7H&/fTkZiH KPY0Z|@848,PGkrBs1h&aQ3F16Z9TJ:kQ\7!_2M4{,->X8 w؈Qǭ8Nz뾧mQ=jşX4kۦA){Հұݐ6 a.bGbp Q2>y6A3Ʃ7~FP)Mϱ$kVNZwԂ5C- ){BaA!oy$c7CnO7o:8Kܺ-X\9#&p[vBGǧ7,%gG UA:kʍµ\ptU:|'a%z(i "lP@)Bi(h.A3 AFjed!FKwl<8\%mS񭾩-XA9YFN7 Wƒ]LB4 g'`pVLLfv޺qJo\B#w F [!ϐ͇6(`\^m-!Z ^k ՝@'l,܀Id} Y{i &`13e],i^bUB@v}#A& 8c\^+&2NC"Jr{͠T Wc.#l,/ tv pu!n@(72giơѫ عGfq͛@w3`q0DϋzofdJxjŎa;c YÆ6DUq%VZ,^ 7QyHtr Y @`XH|xd28r_pRi"e+8{Ii6l̀ vq}ZR>LBT3m,x+J4kTͧrt4ZS,B‡ Mp ,q M_C]0P*\B‚Tg a?qcVx|HS;1Fs$l*qDL14{ g`7_nBi\B4' R,T'#1ʎ,%J,8퓙st.r :W, ,J8 I/A#)Rޔ(GsKː,.`~#xw.A4f;uS7Z@8@=$<FVl4]Œ!WR+M?);JW e=ǕX%6DI.a9鉳6L Cg4 .k!g"]!MS`C\K,-.adh!s`c>D8pѺzsi9pU -p)r :,-.-ǎ8qB*Fh' _-y88i\pqKir37\mP0Ny 4, soip8h|_а0H+́6y2$pml0oaQEi8^ ӴPx̙BK%9Òi%16 FPuK+f!)>!QEi8vlv]qkP̪]4q" <,mDC-Z݇ҁ-$,Jp!(u˼AqEЗzw3둹&\vah ȳ-n^QGnp0q9tdH2>:W o'<$bmxm0Z\rHEM  [b3HUͩ,Р݀bU^w!7\.`!|bc0(9BufNh.VdvFV2@IhfAPaGSu7N Dsɋ˒L9)&!7XÂơiCYhGWCi0%,npq†CZnK+PZ)PizFhv FhGhՉV>EaY8lx(;%%pY">Z$!,qH#3 TY8pJk! ( 6}bæQU\*#*a3 ,8->6l!^!%,JpCMY,Og2m(U}߇۝Hs$Jwr4p_> >6Bs# Tƒ7(R7 AAyH/4F?-FqH+B9ia^a^i.5 %4:7pp%q$j&9ݩю)$0`dBrr!QdBo\5[H^JҕaphF]6 ҅S^3L9G13I[w Vcv~sn!51f\KNL͂⃁)da6B34$,Jpơyg10) 'Igt4! LyV~Nr틖J@rba0U)?. Q ܢ8!k 6fϧL*ԆAzdna xa`)'6󖆼4!8*Άsiػhi=%?\P^;#PUCi. %4Jp!ؚXSR77ixy 6(L롏bߧ>mB(aW.B‚6 g gGLr"8KiS9|˴JiK 9w FhKK\3Bh(X&aA3 AFSX{)o ']Jeت,㝏g\[9G[:Va@HXf A`"'4̰CSM -˴W +YhT6r)&4C`j!G O0 ,q0 5byj+oE_b4-UuD܀Hzק!h i^-yr78w: ۽;7$^Y03xIXfCuy4[<(09VitU..!F<݂'j ,F3pF!$[cǍm]6_m8!Zir[1̂)Tr \dyqĠU!#IN?O<ϕO'Ni¤yIW~?P [dR[:o霿rk;o0syՕӷrC#W~ IiGO#?/˔%pF] >|H7rNZJW,+<O = ~/_Ւ~i3') u7n?$A [x4TBwvcLy.'j;|JΗd>aw\٧f0?0;ǔ>)sp]¸vd?Y۷ts}0yO mп+}-C/8Qy7w]IϊVLy덫)~n[*J(ܭost&nIojkܸ[ rO6gKܯwͮs o;V~H~de]gm[@k |[_ޭ/ʾmllTV׻}電utB{"۸[A}^ov /ȭ[ޭ5c~kܸ{?|W[W"{{_m%Um[m??;Fnyr(-ޟ6>.~P+7O67wt@9nse6}?c}["[9}Űno_ ҷ!,{wricAr%09at_cl.eJmoz)’U%cafxTendstream endobj 178 0 obj << /Filter /FlateDecode /Length 360 >> stream x]An0E9En@1HaѪj{8U$Q޾.<֛a6irL3e?ݒmI*@OllCTA'IGIA'IGIE=4<5<4<59*3RU8SGƎ Ϙ2>e7`loj؂lt`"B$i4 4X` & F8[PP x\st[<=Wjz̪)~Mf endstream endobj 179 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 2629 >> stream xUiXWUdSQD\h Y .A4桙 F "hDb :e⒨1b.o^䛟󣾪=$#HL}7FGOHIMًRO+M䁫2Qi#)1?fiXi ҆3zYmв`'-HY!>6.M5mtUDgtj|lʚ~lNLYZҝ è=ROMKMLrs8i*gWY̼,aL Ĭ`~,=QI!|es6ӽ։xXr浛 ;WFNzX=2Aߓ &SF_C !xD\Ѳ̆. )8ߊmbV-$j!>9Yv7UGg/#Vn(l\{Q5U o٣d~MYp͢4nh OP|aG赦J] ^`Z"|N%;n}6uLB}\󟌃`uJ6Sa%$m:#{q{y.+V;)`O! ) KъZEx)_fH ZN&q8GdBCvĒSYJbs$k.dަ#_k t>F`oJ۩x$- 5.- k/̋ @{TT_K9yLzf9~I]|\PSI\'Uɷ``(+)f47hp`UL'G5hIЁf:~eURl@ 4۝0SCxG3Xp 0e X"s6km ģlV\=yMў66\-{ш|->e\j$`Ų8~.]YّAzuw}rtTPeC c]Z$~ )t(I;2{{VHCR2kyL~_~Hj#4l6~p*yMk$3 յ<0㱝--9 ?մ#ڢ͌hh\x&4Wk87%ssx*F7$u#Gw~"s|DK6?Tcg]=u0pűVnk$*F[ͩWyaEe)_ "ExJ'K/+24-:Ғ8ޒcp<eopD464e 20gTW5F._9z/ J ~R_s~bP 2hz "*A 0Z*~"6򻚲K3bCȂ(gwAɁ5N-K?LK'h4*34L9ھß]ZUBɑr__6/4/WtnEK. ^Йȧ'CBHfv0-m?C-f %Gq,7Sq8?RYC oq$8 5W╊kW81/l_>1\8 сAaQ4j;=Xw7WU5o64u.T fpPD{W >< &!鮭(yM%}[Ih_{۫n&5x TۀyMgK¼yeޏu[p~'q)U <{VJEm;p AodB1eݯendstream endobj 180 0 obj << /Filter /FlateDecode /Length 20503 >> stream x].Irv~E_18l`|!cH0F3˝YJx>"\&72"2322"_e_{{k~M~W}uq|_o&uv}a|K}ݶDžرm_?X_?_"xϿW_xݮw/˥M>%uWR15wCv߮?T ~$ͧح>ܟ?}'|>>Ji%o֟??^!ͧ>cOO|?}oma_ן7~`Xx4?_?~Zؿ^aٍYrx[Qy|ZZF;mf{?dOۧ/O_o?}TjWq{5~ç藟>_G{A?|Y"Ig/o -ZʿS◟Gv[YIx߯?g}.?>>?[7|LිO~L?+mO:־^w_ 9MW%Lr$[v#im\Ѿ ܶ>*P\7ѓhNm{'muZv}kHݮjgX4ܿ )o-hK)Ym{=EkǾ_*Gw-mJuo:6˷er:|sx*.iGlV̗Vy:zbn:/*wl#fvx;0Yd]WHlG?}GG /g^JӽSGnZ}v*G9FU2;拶_">G9(:Kthg-eݏ?pT47x\XRn,/:;\~^m[;N+So2f@Η:_YTo!">ZףFg達zYm+xq|Nj}.W;$?5|9?>۸?cש}eQ3DLOw3-ۧo>ynKC)O)q}0 .U/n!t=;t35 1?Ib#XsL8o懻ynvOk'6cЛkƈO1={.lGsfmo?p{o?x Gt|!y|cy'?֏M_aC˿R^K{5^ ok//˿}qcbZJrX0e}Y:b0I7C0g/1[o*ϘmxsZGxS'zlkxE0E] _s81-~n:5>sj~cI F/WpG( a_ޤ³uA5yxc~o˘s@qARsw}IEds }N^AGpĒ@ON**óXOb ̾ѱ=zQ^lŧsۯ2-Eql[o3Hfa:^L`0 =%p:.^gN> ̘>gsGsr }*nT|haLݠ`r(OO"F`h^cw.PH; G<m_Z0$Ad0HKh`L`ʗk?Qv~W`b9PSa,` gh^|s 0b!\ s#l.;z1HX"~ svdpNI[_cIa [Xizb%&7||x폄c*h`h`ViAz]mI CRXG3x=Gń憵91A=':09lka;r5\ifa@bbqfjTA. .hb5a9ѽOsD/؜qEkxf c1?oc i0<:16f'aϜc̘8NW1_[+7JbMCrX0eD c9dF㺀 1ʤERXKr͍͈e~⸌%p O㉵$yTs= SϘE7JDm5'8^A9,)A/0u 3&ۗ)9<{Ac>#2~L3>p\bӴ% Ū(Z5pxU'85mQ5l˕Y7-K)9<SVI0 #FA}+ȱ&L΃N pl[eǛ=d2&rmt:: `XWoS'9 McJq °;)98MϾ =+ahZb&Ns0!aʀ5AvK۴ks}I!-C?ط51gQ9x dNyc`"B0!uHh^ȟ{m1o'8Yby0^As7) a?GF?b / ܏s;/ƽ2 KMpln6}$}?'L1s]X~3 ޔC;i0Ehk2狆_hnb{sso RDY6} m섶+<~{a&uXg1d靜3K)@0́3;?1ᎹpʔsJ La NUKy/#&f#pc7xyNOz(7 RV!aa'iJ0E }d1q`:/.ɉ? ָ?>T,cHa$ Lxl1 CK`")9< ;Ɯ8(U=xń/a|)s890Dsħ$p%B0Ma% Zs)y`=EĹa8靼``sp&ǍbNQAJW%0wYa)9<{A7&~Hp~Ü:|^HijՄ2_797k&nuJb]j` k(.K.9B5~av:gMWp}#F1 SbpDvJ:Ç^phF5_?OlA so @ir ?a"%Ϗ):ɞ0f7SgΙ6&0N|CRZmG7|dZ'˭11d%Ap Ia t\$'6)C٪idKceuuvao7jO SD0f|\ejuA(z)q}Z57̜q?΀]c셶`LXWlE:Ô0V J0 /E7)9Y3E8R %`qfN-aEUJ:ózg[L8?ʄ6F+1qhr\󋈀sx+0D% 1 %Wc20-Ģ:{pͭs@MU?Z1$ 'DIicOĸd jSۙDJ"g/ƊB`1K%4¡#9a[cgaq3) 0ߥ[?zU^qWmPGso+jq\YE8C§o2+̱.$085$4G'8q-{.a0"b:ER ƪY*{ C)v$l5%* Ugd2@)|&"/U1Fb!Y*bqFƬNS N0e0sʤ7O\ϛ ˜t)9:j:Hܱ7ÒHaNZ˹dDZ$8 W;133`">vzr4q1o, / 3S|MlΤ~nYI`5L˫7sgHXF0'V0E0s : {c`% x*@n9jv]]1zcQ|mSP(`c10 Эϋz/!5H k(.WG$S saP+"ʜ'5(b8$k|Y 7b6'D1وcclh R=hgf੩)98!j!xT "ftD%L!m3v{hoJtov7`A2ԭ ?腑7zq?a1)< W8/ZD'h~Qwx.Zqq2n S aFؖ0z-7yf_W<:'&lp1<׈37>Jڳi9獃aɌ0–A>Ag#Aa-\唘}o90dqa?;8ۜPÄ}>\/nםHH m:KDlEcszLP\oqc`/ɠ<@>+L`d^bvcISx%ӞǸG̰=#tc Ia Q3Hwxt#5F̵X "Po74 ?46GⰝuA7u4g/}!ۃ_b@vB0t'9vڳNaчLA0xa*3T>>&xY%1ÔIgȜ/|cD~0g/6йs͘+5OsO04;rd0Sa haΐ̡"«'Utg'8'FN(-!epȘ`T`p0|LI(`2޾,RCR kYZZóڄ %iT$}S2US0a5qk\*aJQ. e*T054g8Na:y01<x%Lq1Y RD %5oN$" )9<;S)4o&jbޙ*Uj7S')ZG.xnSک)9< w=?c>‹9„ Gp"30FhRq,m9{,߾Iaً_y)7ER"9@>&'M߯X ۗD7t1h`}156gGd|n{93M`; lO9b6Ûzc8kc|dZ$L~hLKHP'\G:(a Q K} uLJJã: /Uضn8)}s0L0UQB9,ۗA[C~@{0؜F/1󙕓^tǻ%aHgl"̶Z ݀9hq)ۗ)$|f79&̤:SrO'wX1l ť30Lo_&V!M/ <{ʳ6廾g""Lce LԳ'SZ> |f&0)a he3 J4ЙaxH$Q4Fax0EÛoFnɓA 7LDYW${Um 8e:^ gIbڥPq8rAw 8vd  ,ccq-# UEZ3V@0sX>VX-DXk3xBe0L禰䏘+am~6EÔ0Cac El*ZY=," Zy c {Xuö#(>ۍa1#9"b\:kDC0c"6\D숩I $A=c (AJM9 *K ▚[A7v!JI#**qBE\H' .ƣPќ 1 p0?8 xkzTxVƆd)C”D.b>qAx6H%La%C/❕p;tΠpDJ 79;P7=ǭ5Ar!q mnld/8H)Rcq*Î+ S?["ж7Bq" FSlDr81 @p.0u4g/7jLtKLSb-BA9Bx==Iy`-C95HO٧dB=~0rDr,&v;"U &bMv`k[0mxL \2K SXKsx}x`o&:TAĥNci%*llǍ"׍a@ a6.C72G i@ߐn#ipX'qgIXcʚ,Ҧ.n0e0,^8&e`ߢ]6Ʃ,̅L;P0qD!aʈ̷qF s0ߛxA[E5 t,& >JXF[~r8i(t K[?,nmPtA)HXA3xv⼂k/L'J(;e8rb[]ax 77,'!%L` erzgQ||{$+8^m7)"SJ%0K` h^gцG"byISWqc^gS<I!!* K SXIsx"'`9nfmLȬ%L)).Ƒ'î0*,T߮ š)9<žǾvP- K; T"PeO)JQL9$l80Pc <[H-C?hDq֘N O-LE^x1J8.g*cSt&%E rⰡԒNթշĄۃ.e3 "{XHdE8 H;*ݒC3!8ZHN'"Fqbƅ?FN``2ʶkmc1H"^V1[,Oȣl8lY؂/+"Y^ctȝ!Sۗ9jwudзHoxoQ9=ߝa቎ !A|br0;FGzqcO_eO`JC=w|(” (ӽDAA7 { `'Kh`La C^loKm<4dZcX'L9/z,„ t8X)<{!+_qi;)GǵRaM0|G40e&Va2CNbh'1d6Z\́ q<'MX!d %t:']\DcNf֛AJo TH +mNpf@ (0etND:^ Bz VxњvӺFܾoC9`2`6 SÜӏvA8ZX SXKsxlь!@bb; ÀGŔ:ao{:?uOÛ3A^CXu Kl׶23 â%*4FoQԨq2IQ10Lo_& AoGdK0+Aaً<4Cx౳ 1QƉ!%JQ0'k.'9ǘs>0>/7uj-La-: v\,Š8A#0+.n 4xL T054g3v"W`47%g@v;q8n`8$ &A.qKaoH% ~߃KS~b=x)]gu1H"`l SS })˘::^ݭ"j} #D.ȟKeuknn O[m [mLaى:wf-̅k]6K8{BjSh&OO[_pp:E,tV͟fؙS%&nփbu{JqB8_ߣlykn1;,]OBq3T` k,,X*``"6 3Nġ9B_2UMlSHI3xtBKw0vu(pED5@h9XBG0kLgd7-Y/KSXEsxvB* 7 o-]U;x!7 Fk)]3uCm-EDϨCb6c~D,W4(zJ>1fXߚݻlC bҋ;%;:$u4g/:Ĩz!Xƈ4g,+8iv )a@HՌh` 7>-04G/~lOouTP>b#TzI8pSgrRsm+S C)H'ƤMq X2p%yd8 8ȥBRXi4@Gfb#D O$EҚ }Y8|-;,- f`kh>p[U0<\5a %+!8V}FmYҘR΋A$YKSXEsxv﫲~oA;LL8ioBuwN[CI)FI8 2a"}e1qA8X SXI1x=KR\z0K yV, a8悈7 F,}+ŀZ/z)a +)^gk5G.饆Vzh`Sꅻsڠ]d N9`[%\[5}*g%"25/tR;oS);;S\9-Ui!G2hD4ՀYJJãѱ>lcab]3qb7&E:fΪ/IqвK+O l1Mha%La% vVq0QȍR=%L-v6/z2()DO&°Xbd\"G +a h^[ka œ( UG\z!%Fm\z)iƩ.g5Em`xmv/AG%RVR T_׃7.LaFaab9U$yKˢXZU 3?3os m ZZóh),[1҆AFS.fniQ|7 ԋAIH|58 Ia ډxvd wbB@𢻃u"ȴ(Ô-gLPZ2G k!R>Cm/0 PO[b4|g]#L '\{%wANg+7ٙ#+^#65.`KM QH@ag9vp$lb,ŀl*!Q>݌;NгDQ0tg*yF ǘG-LnXG`MtsJqUMTQ>sY2?WԴ^^Rsۻ̣N& a@_ڡ@[sj߭[_Fsl }k`FA^[KOU"ΓWbacZG :|a x>dcg@R=hYs0LXG:oc%HI,\sç\)S #1v§"qv.Z4ESs0)on"b<䂿S ɺV<188ID á:p*Lq5~2Ç6yj8+U0U4[ХFqs槾0PqrBP~%sؘllq0Lh!́š#_q -)9<5*B0h4;E%\HJ 2};L Y+AA;NjD%%JótJ' |Bz~i iws[U|HEvkqH呂1Qc,iKa9e4g?hsw8.F'jq C` B. X,R1EMJMyY]E&5wZnX#Z|9XÂ)C<0ZEUdkښL8plNY<}8tds& w\B$M xd )BpI!óMGfN06e[!,ri2nb0Eh{b%@)VQ?o\zp_)nkH_I|^A @KƗDɸ0,B0BJJ6UL.ȁ8|U:o̸3GKh80 o ocL+`0'IqMі XDXk3x=2YJ(bVjM{wߣ8Mʢ獃 ÂcCxdmyEj)ʦ=0jwkkr5.g=F9fQu0E09tX BZ$4G'bԋ FQ}5ZX,ZF,)#Z$YKaj8fjSu^0f'M WrSC71H SXKsxH=?EӪ+ NEWdt"^&SDy`g L9u-eӁdU]YZZó7'l w7l>YMX}P'~8+aPϚʨb@AX=Fa% K.o1b3B4o|1d`"'0bq8Pq+EK@::Xr[/"1/8ՄXIqWW)e1&06zRVR Y0};GHo"B KA+K@g_R`T!)N_Mz>Ty*/7ḭb!Xpq\R=,77\tD2yKK/L! P 7 `KxkM8_I7E䞋qًA'pv>팫L7ӿ/Lԩi8H.=5wy(\ts,8>~6Agh 3b)Rm2 K%U‰WfD<8v]:T69廊 "h|6L6Sɀ)`4 "HmSnDɌw 7z!m֑Zn:Aj)Cn3 /K/K SXI1xB9t˂h]APQsQ80fAdtlaʪCwi|-fL ky9|,qI/ԕQ;\.ռLQKq0|??%PK`(R&9bq$GX- +$y5P9 아q?Kl*d &, 'Gq8vXv]& 'G-LZ2}I%L`ًKQ1,1;-(@U@ס;NpA"%!M?enWBZ&g?htax_po8֓iqN"M`@%f}- a[WEMZ\iN9X~^J`aD^0e}Ys'>I[a,zIt6UgV'}% QnAL Sp8T>e}ja ki~hz쬎'A$C<XY 'k z(]\h9uE#aFq9BW S+ab)&0+)a .@87/0M2#|g A,%-9! d.}o7 m~pZ;S;!wib",~T2h]/B\"KL R<´fPƳD^J:óuVU't$&n3PdD"]Y+@Rs,h!̜mt~᥍ڤv*_$ -^={Sj,/G̓-1o^ S$`dFjM3ڄ[E7vB<):6+o]q,O*X!i(jc(9.(g~26-[Y Q|iXxLIL? $q8Қw%)-<7H\#_jE}]' C|HE"Ȉ10܇i'pZ"o5br%v9L~ЕYu}(*q5/ʕ(Qh&FUAU)8'04g?Tu<&N`?3p~(%8kߣ|K;Vs#OS1hCI g8UH +mNhFy'{э SwCcǥ!`od) 0\)0 dj`+ȹ񡿪ʮRB{4Ycm%7F^7W1 b3,JDt߭?;꿟ܩ65 odbDD(}K[_۸:׷ofendstream endobj 181 0 obj << /Filter /FlateDecode /Length 436 >> stream x]N0aX_ڢNW~?>uI<֏u(u|e+Sڣ1,{b0Y7Y|UinV`@FB%`GDϠsC0a!FLDЈ%7sA=GFGGFGS'` VMZ9qeC8S@c@C8S@c@C8S@c@C8S@c@C8S@c@C8S@c@COS_c_COS_Sߒ%`!@(Hāx(6e rtsttuyvzvuyvzvuyvzvuyvzvuyvzvkz)|n[].z/z|Rz^9oۡendstream endobj 182 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 3110 >> stream xWiTfEDg&M@E"F" ¸`ĸčB>QcAPp.!DٝS@~3sTTw_7MP4My%S&.^Y &0AG B8e`!0QB"?aMCP5 !K,LX;OudG"7'qIRR1k Ss(딥BSҽk֮^>&cyl܊Ĥd K[NӦg8ΜDQL*EQ EBYR%RʝB)*<ʋJͧ|(?ʟFRzHj4eHI1O(GS"j<%l.uUCHC:U:LE!tua,yzدl3gs%ìggp8=3-Za{Tܑkn?sdA0Yӫf'e.ǽI9˯i1eqe;jvO4*< i+)Tj;MeKSceps )v1I“5x<ށ&s抌dؓnyO|s\q,JxY徧݉L.vǮj9'0&G6ɜ,qv(0n,=GLO@%i63.`)H .Xэi0}XQXM&817Ѽv66IA.vO -j5d#I?y>?5r8/8'FS)nߙ|e?9G[Iu}ŇΫm#cjEG7}eWKݹV8UA W>3sh>ݘ:]u@/+f o٫ߑ? MԚendstream endobj 183 0 obj << /Filter /FlateDecode /Length 4454 >> stream x[[su~2`7}T1)ʪ*Uĉ] (g\zO"mǩJGޞ[N){yJݼ+MO?gpoU3vsvD ٞEw6WOa9rӷ?O L7[v>8]㊨Ifz:'H]Ҷ##e!Wt8,sKɁNy/?$X}W :Gエ5J.M:Ƿ5+=X= ߓ#iw.^MYw>&lx)52s8Om*l ^^M:HYr=/wYL,my:n])gǬ- QA-4$RoH"hNM?\q:nݳ;t=xR#͎ngw:47N L;{S}-nd \n= RKE VxÑ$S1,ek:SZqJW ֹNS݄i2ww޺w]o}j@";8 Y5E),1,Y϶HzXo&rⴟߡXQlx w^9A==%>eAhЂKH1ho6:k t<0 8h8$Cy֎1s saZ`eEdR5JBw`XZ[BE%,SD=R]_ϲ>/肬T؏@򩽳2@c@OkqGOs)%7cmbuݶZy|DRa@DX;^,:ۡFuK9tndoB[s!}~j~{W{#BW $6&(CniSӶ+:Ąc٤>=W52S#^IyRyțd+ұz-I?23~"48"]S3 P2K#4#t]+pVB:V1]DQx`TLgkxj S HSAuuq-x%&VgA"gHu2E@z%S}2 ed7B(py-Ij) |8Q:I{/9:w6EbZ NYaދ!P47VʐUb/S-3`K4ݞ,~c;.`?2o'R5*4qtR_r~~qR&4K!K}5Pɥ󔁁ģB2QPR~%xɓpC՚\7u dy۩zlYy=mh8q.RbVzJBzP<,=1wzsE})32UQegǥa>n'w,(]?PVUzt%s~- x!.o6)?Vvħcc4龑rpʹ5~V+ʋuwd^ϕ̎MzN=R/})-X.E_fi=T33XDF^7򡑟Jz 0LFӵU |LO7OE?;U5\eM'P'|Z[m{|2,6)J/B8q"<Xֱ읰^l,S{$ueڅJ9yȯqOD&mژ {@|޴gb<[GO5W[kAb[KW&brɮnNr R_Qn氦˱@GiJ 0)}[v©1Wk9IOj8%AI2i9m]lj '%sb/ x1i+^v+C Ŝxǚ2&"^v5r0U+A=}2c[OEI}2M;w:w`鐲n]#^>@(F;ߺ±bl!=m.3f2OAu8 8ߛߝFX0`h"St֑kr\bm*dJZ=ke0r =DNuEyjǹsfL-g/ "b4@IJǿk i|D|QdVVؐΆbd?OW:ٜ s*jb.H?6 D:ސu ME1J+}9TຨF핡^֐ɬUN<_4e ɴ:,fREpi3(|6zWrRsׄ~3T&s'S s :EN} e8n;X*+ln5S]{wLŝ "]TYi29ť eh L2_aROcMeR MM˰wϞP&kYQ4Ȫz8"@m54M([{X'w!3葉m۝;l)CF7۹fU Cvec?/z:kx2GCW_0'(岅Voq;o ^l4un?Z*ωujRd-/L%݋HOagCKti)}Z⒵هRx#MM` v7ߨ1A63Tm-:4s.3'rjD/ݱ U_fѻľ. z`63:]"rI3\L% SDBWɰ x?Um#TY*C{Menn1ѕЀ^{V gـ^WStU㗼ʧuEҞo08HaZ]Se&f&5Wuz\ĒVǏ:H:i>^y\T;2qdm#nS8 <~ȯU#m#gQw_oH1*(,WyF;_ R3NS谑9xM՟?[>}Q_1zkA^0k?.jg>4]lg1q_gǻK8vJ^z/>#btao5erQl xD_f "YMOQ|>5F>c&F^y>!-6xE6}#u#jmoYL "PrqȤ,@йj_xxR}^>,lSVCS'DHJBz?⸸{?$Ԑع M1DF HivRk;_B\#Dk7% O4ciflxjF4mEoh}=WFo:AޛMo@ H7Ǯendstream endobj 184 0 obj << /Filter /FlateDecode /Length 162 >> stream x]O10 @ ]ZUm?eB:gׁm_Xց$i, x`FS}endstream endobj 185 0 obj << /Filter /FlateDecode /Length 4335 >> stream x[Yo$~#nޤ`$@(N|Z9FVקvajDDbί?u<_z}4_}qwz}чO4&u|_Q>``?>>z5Kڴ o y閆a '9Rj2I%Zo68՗ezmF4%71,$UuoӋ~ec]rĘZgMBvOvPWqxFXN֛qSX5Lۊ5>Mq8X`0  ^#І[^yP xjRQ+mIL {x 3JW[' _= ?a(4[8Dʰn q z mo5?JV+Cq,QCǵSѯnX7pR"-tdM5ju#磙䁭gW̳:11jK:xr1INk"T\1CIbnd4楫[:f75+>Iv,:C}>IĥTbc+Άh{*#G7Zm(Nȳx: c4 |s^S)lņ\uų%\d.}ĥͣf>Y8v4d-g]Vcyswߘ_%8a"@:p]c4(0>Lo&u-IִS+aᲯtD3>v^؎uKޑ!`F|s)8YGp)`vmUvU+Bؘnl0<cGVb64?c $9Al]2ـ*4>ڂ9}6zHC/ܷ+?3A 2(%D?)YVA0?Gqo\7Rŀ dbs1 :lM[XٓZԕrft` CZe(0WuY|6;v7c`>9gaH|Nh=31@S;ʭ_٭;{?(FHF^2AZ L2=1cNL (OX6 ^DP&zA$3CUO5 . I{oO@'Z-ն[+zu)Jr5yqcgI:`_# vvg$n 4h"씢P*S;euKu h]> Z*3/Md:cBgVv~4m9 :<%*?MRU;ϳկ&Fe.Oᶻ:1N=J^Mb(4e(\=Ȋ6y/iOagb!YU9#26kvQn@sLFvAOpd3W) R&X:mg; IՁm2ٖ16actpuUˢCXe 54;d/wU@%KJvm;p!(|cڜR *ebZVfҧ] Xża8'q^澦"$3磜:+Uޖan}^u>+íX47*2ܚ dW4eqLLv$*'4TbfRĻK@ u0%2LҪ-zKM4Qm7VFs% .w/U iN<+hpDnq>:KMϊZsS/u%뛥@ڃCu;t8^$_(F%Zc#;"Ʀ_q/ݕvI*宝"$20ǗPUGDZyD_PU UNܷ_=m@Z}]ޔ2L ^Lʽ8rWU^bn=F]œ`SQ~nu]E~F?°2.gecS$wd_xMmcg]< M}1^ 6#W~drCZ .輆ګv]#͝O4>1zz_תV~ }O`2&T|]D >߲A%rɯ=S!mDmjS:  ^R>V|5`8kGz19$1,sDlEQK$56h1;Z BXcb"J`2L` CU>&WSq;guQ@M)JnTvd@3H Kb#D%X5\uU5$ sK!XE{Vn_s^AQ'Օ(=Nij@{:[1o3؉~P0:W+eXw1T^&G(~ ѣb=(`{7[ =4oV߭[I Ei$@fN[fZd *mn/  @'Xuܞ\,Hc-uiut6gWS7>;Nb~1 /DNF%{l ,W[]|#)T}oiD ܾW$rQJ -!|=-}XuAJ~j~FEN8@K Uy*ge$kRFo7aPs&0m \gݹ0hc ՚y6Bm<4VTr()_qrn_.z3 CB3f*n>~,F}6 _> stream xZKo6 !gCmCvm'uuCZr4B=(X7oF6RF{}ۅ&Z_7.O)Wb1<c8tm׋7BBoCI'>^;eudqŻ,V^u/?- =4˟/N[=3fNع82f|9yFh.~gQV8%_j.~z qPHimVezEU<^qWJl=Rd+md:ȏ?2d@S֒Oe=)=}އv+<`ugvR]I{ ZJ:h c#sqc[={[tqc5 BVp$$]m\ΰ_=^AtDK|kPLV 0AlcAG86 +"#46A tgAR׬p3@TR:I&%2maxɗa)Gih|+\ e/ 7O-kӱR+nk9H]n 4Ą.qIԣMu6$I/$3cJEܧ1?f{h~7MufʇU%9S hӭ^rLk :Ro(P<ʱNb`U FT:a}YeLjH>rqI~hc {tK8l_']I=۬*k-Jufj ZH$ʿOLgFڌY|Uxź,c<cH=ˣ4p9 BsAs儀;FP\R :+Y*=#N솒 k",MhH`T*o.H\d$V5>&sTHBz6F.J=GT ȓDLcEjLbLw,]] IQRŠܺ<,;sjܰð8"1 D!;ĕm7߆đWQ {CBaD73#2ad F X iFM6v h*2eW]i0M'2Q-'![c<չͮ`2>u cN|m,Byz@ux-*ߞOjq.,x,ޔ>_ 7տ|쯫:f>Rq,gWs1T^hO{xYaxL$mkBe3@/?r%endstream endobj 187 0 obj << /Filter /FlateDecode /Length 1835 >> stream xYKo7 X9ݩ(=( &ko4~v^43eo] -EQ$}\0W>yg}:q5OFa[׺s W1[~ք0_=o6E<+⺈E<)ܶtRyդeTl>be|iE,IOՏE<' %ц0HbWij" ]r#Hᷓ6󥶭U)RZ)}sL60y$֨nʃe?Ic46WY(#liw !3ti7EmRεJk Nj֡US 5(tMI1g|_^؝$stD Cy=ð9J{2DžTM@OLxhq}%/'Z T~6Zz>;.? 4VO۫N+lJo7PtL/Gb o {k[ .}uE1' jJ+@!)o6{^[YǼQACOSn+QWE8#%.pzT]خw^čTzq8Q|Ho]>o~Zj.F0 B֦WH;a 7.DF*u08;=Lkt˦c6J,H~Û:(>Ѳ>Ĕ%h"`_QJ}c,Y '(ɤ1 :ۇD@Ie&!@ǐ0GqlHd4ҝuGi&P lij+ GqpO ȾIn8%0`ûY3(zB." JHO@3Ѭe e2p35kJdg˅Ô rʤgxiaJX+fQ - ÆоyReE7eo+xD)oh0M? ͝o~.-">/ ODcv]WD,ڡܦtw"^񨈗ETWjc{$Pkz/yY|QBm'oɝ[pOap+g.ՁzŸ1[ 4繍 P$HϴD]՞Ƈ ,A/ wK8f0@ńjn.("vH)H]ݽG Rt)_ȝuFh88{Z%cBz|z7xkK/v!ޏ[A/vqЧ!몂x؇Up^m4X <4Xz/3II%e~a=&:5shNً< ^6A5)F NEn1R{G|6s$hΉ8O> stream x}[]q;<{w0 F84@1#e萌HEѿO}uZr>UKue-qIwWώ/۳;/^>_A:V{3)ZUF2g$z~?ُ/nrqǺ܏o=˿yҥ^riu廗 ?=rY//s|6&o ~ڏc(/7#s^ge)j]jV >RSO`$[{A6Tw[7u*NnR>r5gG?#kƄʜ*\YNm`~IݷlzRϓSj3qyYenȏr?j?z?f/* Lf-ZTCDPEV\GatcN꭮ۏ/ y WZ*\ǩF:ZJG͚݊?* ߎzonx;#@ڼr{M ?3glGYKOOWe\Gj?~܏_wD18gMB!w6Bx{;_IKa?~ K;2\B AJ 8kg:AZ(j89a?>Ǎ&ZL(h :RQV@ Vte4Q?5ͺ*3[Ӥ x=R9Ss@?'rw@JYJURxoќc#OD˷S(q}{Z "|~ Lأ9jS HTϞz6٘̔o~ᆥY娥r[HNT/f:A4foK<AY`]PN!y5j_Ih 6DJ"At-ڽaH*zM '3"wDMn/nƲ#]R)>a>ܜ`WMGjey Xh&Xk*=SHʮGrWʻ.1p' AoQ`{ lֱoNӕBIX1?PBlw,V_EQBr18ڥ߇eEd2W{nͳKӹO;|sx>a[ V rIDff A5-Ws"zS&[5-Hi:yϕaH=(NOdoDKe.lT(N,pR8+y_3|˩^[G>)5a!Tu#ػ^yeJ▔c&n A"("A gU>pa_}zcPe18JŕԽ3A?< Bٳ [a8L0ttctH {rÍ:FLSi h)GNIJowC.$:Inafaz \;f6XN_zA=S p@|{*4PurfDihRin !|qL?z-P8)D?L%fk$ػTxRG< ׌NSy18 >c~ss s^%ۻ[ЋoNӊzw;IOgl(t5~`nXv[_-=Ÿn>Ö^Xbea/Ά$1i?_nӤw # !wyswocwi^ziCz륎)7{hik"4Jn8ç/bds1Ш0hF#2r!%hww|/}`.|/=ۏ fRv;i-r -9 [N7=7q< =Q/AkJ~ g4Zt(J>\CZ/ !_=s "g^=}heɶS k߼jZx[T:8 48-&S-K۩#`nكMC/۩I۩'mBwkŝ#(nҷO&Mv V2r6V7 4a [L\_AWZ5 F 0 G5B0 iN^c$giմq¸*)# QTgb.1ŭh19ת9 QB@a4g/N.gba٨CZU:x-&g#ۭPuJo\!wŧJc&iIlpUKq{9)A*AbҭLb%[hӐBs_W&a(MaK cơn+# DS7F\q3\%A1LJ? 3 4`4:P\H1`#ru4R1d.(Ai)op3:e4&(\pےb}tF9h'|$e)!+MV# jڂPΔ4A^ QBQVg'د&Mʦ &tw:QohWNrwN.ܫ8e~iBÀA0 g NGm$L㬒MS&aMb"5sNʗ:8KGHk駃saMs9 HK;G`@ =jR!4ׂP G`ߐmm:h14+J+]j'u 4(6P82,)n距2ًL2f]f2JG*ЪTY1a4g/38Ɗy[@5i`D1Mb#XBnL jM癋d E&lttnō7N<֋@*A ͵L𙆳7;hSW*{/-Qi%6ld4PZHUqe`=HKS~}W.aM',1s8QkM8wl#&`o:HBh1U32PzgfCi.`MًgzٳFlP)@ 24qn4Wp C`߰%'[3"=0*;[ u?5Zqh U@gz!ԸlSVCdXχ?$& 'a5ʃ-&P8_IA5E`&P &`M G <8PeOoЂ7.xqK h1ơ4'+em6F ahY9i;'m32wCnjO}ozOꁼfōMm؞)-k7 K(DpvB$'i0N?| aC ^i29M"g^Jj4Q80  0G `A%01pKg6TD&&'h8 F.=op THŀ\qj~6|Vx;P<FS%-M2u$6Y-@o;TlA9+2! DSpAܢ6Y2??Kyim9toUװift0pMnBh0&MAtA}&A8ᆤͨʉZɚ92#:qlߛb+nʡ'Se-q^!A4 g'p}m.c <)%n Fc45^F .7 jBsP EÕ!@Ns, 19hd]&RWM8 = Ah5qlwAۆҼ"(\BQ!v %5NuX0l86L6sĤykpMpF I< pY a@4 '/;d!@Sq藯;q@/iєcs D/\R2eL^)-tt`s' [ Ŷphʱ!A4 g'fyʲys:=l!Ȼ cHaF4-6P8lw[: Q@Tg/3tA^w#ry܉@9R*rtrH6@F7~/]_5!0 ChN.W&o//mz 4Y9M*HL%j?lXq Gٷl3E Bs)p v 2ax8'5gl'4`4* (ag[CMɕL0Mi1p:y D:Q5Q6YDɏJ-Q84:v\9`' )8 nQ.S&]k\kx)4M(@}8}Ȏ挃z!|B0 >_8c$1MڸRhPe_iXNRr`WNY9GkPA "tg/JP$ڰI74uʙEzD._JU$G==6wZ q*p``Ah `Q5\9qr KܳcXmBwmŝ1,qc0ԃcJ\B!+'ı);ȩĎ]IV-%gJk}&ѓoi)_G웢0 C8i x56)Ե*|3 Cn7,Lܾi64 W~o]3Fpk|p EZN(=VI"{*h6 S4A*[wn枃p iN^c)$M <М!dET :%-98jU7Ml (e,5]n`Bh0&a MɋcX=zu֫RbVK(p`[%\G6V g?7.gqnrvqXD]Y`iMi2C 6IJpC}|y|MQms$udH4#r$Fi0Zlr⪐8MbZ (͎ P#^5_].8dR%2q D4#q4f#a ?;-ӦE|&wfwMi+0.;%]Q/`4893{h^nZ-o7;7d&MCr/I!A4 g'ı {^sp2N߸kv5=w:LbB9r,(a(LPaƗVfX䲇LEž0s DAi٠t{ڗxTJ4`VD?\R\y%TeC-&P8 La h ,$ )8{!H'!i-6>Ɨ dr V(ajH)Ԅ(\Pਾ)oKo+8-G'rР͑ % i86԰,3ZU/ee"D?LѶ,s\܄/I(FS]S ꔝx^Gs^*cv~>f/2)S9" r@W4u0Kܪh1Ʃ| `Ah0 &aM fx)}F><} ZI]4\]bMZ\B9hZV"d% IJpC|m$.T}R,FadIH!>S N 0ṊZC g( 0?ۃ ߜxWJT x 9Jt} -&P8_r iP% FSp93M*U3 J 0Ut u{FnCiMPV W~|n!RlNbWnpd.]b#1#y—c&Qar5! )lt} C0( ;.mqohʉV.4ͼI:+~/>. szj~d$)=;JNa_5c1 F 0M~]k(>R\yq8|ƕKnVK(n^v=km"u B%(B=;ƕ\ 4^po4-q/wQ~3$58=5kߜ!)kH ׶!4w_ER5\2PIc~5cJ3%D\bLIZ_g6S&aMىcӾ9:Knwڷ"KpW}]iz!A4 g'1_X1p ]X?0m7NpXT7g/./leu"'nfjkJG&x ipZlq(5r5;35 pmPY|q͑O4]~JjWi,9&1`91a4g/3ocn<q r|h}΢w%MjWJ0位]YA(`L 'C^p쓘R&=!3tp%+PrFsb/M9Sզtp% i8 ^eҚ|`ŕYn6]ˇ&=V F7Tmn&檰D% *8{!QI09xPʗ> NLg-h0Zlq5 `Ch0&a(Mm͔ե/cɆ9e MVW)zm]% c7\Ѝ31|E1a6'ĭ$XMddM6B9Mpנ 6IJpC|vvsdض%[cәfVAm)bukWw 'ť!_y Rci:Z&-k.V%_9o:YīgsW]Δ& PϺ\iI QtqY/~+`VމF=ج7-P8o V}9Z0 8FVe<#λsU>MM6qnL[LۄMI(DSprA* =} W ^?4J3LIM (aq VA4J0셝>(o}W.Ө9y_g Pendstream endobj 189 0 obj << /Filter /FlateDecode /Length 49461 >> stream xK6;&Ot /|)59== l{υRdkh|IIE($q|#ӿ_߿~`?_ZG)y֏?/6)Oٮ_wg=5ow/q?g;?&~g}g9ۉnW}k?g9owe?{>ĿU_Jw~@~L&;Pb6&OSw>[y\w ?_e?|1Hozy?~E|xGnqcXCOW4|?N&сكYiп?7TES|ϡuGOb#ŭ(㓙h= R߂>/R|_m6So|1sV=?#fޭᥡ"5v 93+2}ig*y1D1W'yE?g{|?دe$9.;&oMbɣo>?c51`1ʜVϘ"ۜ ]>G}4Hvo%id}oV?2TK}r)}ƿ]vsy!,k=x7| vޟ,Q?a>J-1J&ŧs;=k,m̉;~s5qv0sݥ^_?~??rڑOdN1~>M6uo~AΏ5"w&|YG֟|٩=*^ן?_Z,yԏF͵j2q}_|g--z9Em뷿ǘ!{~{㞜u~1+]xs]Ǩ|Vg|4z~u?Ly4{k*>-6gL7ům>|N;18ЁR[DŽg=,f~ϑQ6-#Z$̏4;?!0CJ_ѱ>q^;+=:0)}wLǕWm㙓 a@aH۟sNAoLa=97s=s\gSBEQ$!"сŠIn"ZJ"w/б>D;^{~agsw9O ׃q4`Ɉa>d")9)/\+7̜5sGZfLQr9#ʢ/!f'sH2B1p>1RI:TQt'9sN pŠbNK%Rgӫm-f0,`4&H 59yN;s0f>{*6<56i6%rKFQ, SZsDa~71 1X Q,G?зn[|8-LL.3vl>j j1!_5-") kojF` kX7: L G9ᇟ.pc`Qi!#ZõO͏9EMaeRV=&uOm%f.7`rẇѺ#)!$戾-Gc͟2gz#掸2W+eZK1UM%ǹQHD Mha-L!% .a:z}diEXNuB=b ᘵ\71]AJ@`zb-iZ!0VI((X>mfhahWLe^g1Hi#L Mh`La f@(/x8Wl&H8L#&#dp![XNj=6=h`La`_3tn?ʯ XKh00ϫ;YsH0–k0Y e-E-~p:',\[ȩv̵B[:4Es:d)RaP? CmK`LT"){6 ^cXiZbLs'T1Ɩ\0ƽ(9?9,x1fڂ#ޫ8e")96ôfK |FϘl۹E7)#L9XſD])%La% ]1bMLkbǜ5W Ί0 cV,/Yy10Lh!iQo"bV t ̗1 T7̜uJx0 /:)z8haL8Y= ZZûAk|mK%oa1Uŋ(q* +)"16)C%0-?0>aZMzX2ZZZû{: 3@F}Act5Oa|_Ŝ@ %`?@|9eIr T0U4w'hX3f~xg m4<:cԎY cbQ97 XID\ g3^}т:$TL>^^V!,]&f`I' A^;i!R~Ccǧ0qo> n#YfkÇ_EG×=\wP)ׯ)9]5657$h92p#\zԍ5:bp'Q%0޴04w?;9;K0\JX>7qHј^(4imA&04w?r{\7v8 `͏QtÔM0&dXamҎQi?jb6 <Ӧ[*c9^Lۍs`21u0 ZZû>=BL{ ՛ xqn; cU4)ځU49$L0 7H (K`EQPGuo,Fv$f~U cJ I0@_ ΐXW X`m1Ej-^A㛜jؒ'f[9ShOXzoܘ, Sj̓ےAXMha ki~(2M=ߚ1R2͕|60 {q,h!̍drٗئQn 9H- 9(x0e`%\f1}Cr&0,iia ki~]m0tj rwP`G|-(*H$Lڛ3MG{p MxgRA?[AхuĊ 14w ,0s9b}F`P2Bx:v`!X>P")RkqxB}[8tozxD|Z rt'~-b"#+5H kh.p9d #̯^shUybsQ4BAk^ S0SQ ms7GeV 04w?0m|}oI\~nlaJRL74O)c6?`o:nzi1.pZh5 j`e]&=d-ׯ){AK6 379YMW|! `xiQD>Fx!aaI k`T<8X@셊dAz_+\f`"d3,C!2}RAM3u4w/'h'?ٖĄs"0AFҌ#;xy9{kmfZ#jh|%HSXA3xwA@~чgw,AC0쐷(h..Ӑ8΍A04w?Է(taOx;'z3f /zO223>D"|`#DFǨ  iU@`u3a"{kukQ{c`;+#je~G]/La s1qob3^aj3|a T[~0)9;RO+sWZ+ ѹPwdxN%L0$ $rݾVˆISXE3xA-h5>LX&61M{;´ϕzI(z`fq0LpS`Cضjf0қ~C`8s3=6>e";yڏ`(Y_ c˘"9D*ݗ 0DXG3xB)##<4f.M¥s>Ѫ> c?DEN8 ~q&`[n .Llk~D S41B)AᜍIJȓ7Ŵf5G0Hg?X#%CpHG?dX!xp:|ِuQr4 jpUb0}oî 3ZF#Fay!&V x~0às&st0JnnRsTUh靑_|ȉ|F6|eҍ1_UyDnIfw'~k[ġ]@ؕۏھ#H0喺98Vt - SR^/ƘAi604w?2 K\FIU0jj9OX{1E>,Ôka00'82ZZZûzoA8 01wg ~-`-Ѣc`|ZcK0{0ei-La-Ȼg]s7X2u}$)QZ RׯcO҃޴t$pR֛bX7| bO _Ub_G)57|yM|8!h@=` hNDpvG K?s#EL=] U^|Ӌ[ީcp ~M;}#h*\>ܔpɻT0l7eL[p&m0S O1k`21(8w0譃~n:~"T $KdrDzDz)n Nl SbsDV8{-09Wgw_ëĠ[I*5~lc8Dp[2NYK SXKsx}{Ð{w=]=N&|˪4IQ;C`h8td`.Ej)?Mysnl8`8 {24mL@jLL190enrřp[)96MD[8aZF1xkH A B}`:7U0E,>_"{~o K\q%&ׯ)9{fXŌ_{[~Fgf^PR<'sN0ED cX& 9DB&) 3SfU:awNtjU9 mK8 f S^::\*#ۭs13f5Rřp5<("r-)1$L˹DR")Rkqx=1̵`\[/XP n ðYϙ 8$|h4&p2%0mia ki~h9v3P$Df21eM&aK'Ozes䎩~, U0UMwڇÄQ Cs~k?'ߘ`v")k0}?z H-G?r. |op]?aP-` cy{fQĎ2 gbϺ m&u0A*>p¥4o8>_xx=?#4%wHp6]IA+ әaҰ vQ5G($ }orp+ĭ kJS[KQBM20H bqsAF0u4w/$zaIb_MW̍i䐰Y]0l۔A04w?ZᑱDNI3e8}[h6㑞S  eÜŀ;%b)9{y"=q/Lb⣾X,#I8>NqR2AJl,38h>˜)9{ex7P{\6G{d6v[5k퇽ߣ6ٵ57L0PAh1`hI -)RiqxwZ8Bz_;c@Y?C[.bCb0bS38l"kV7h>p$vc[0AX4,xr8aA2prQ\bA,F99@ YHV7e@\m<kpf70KIAE2Hh]H b#Kamȡ)9{!CVbc4Ϭ(Cf}>̶)0bpdӒ@8ZHXA3xwAlds<2kFR&7ѱŜv',f) ko٧@,~Oư_Ԫ[uKU$,W(.&%w>ʘ1Ll,d4uߺhM8t7BQ622 "_C”tC͡kj] H-G?x1<+lrtfXQwc`pⶋ 'S`LT!)9;A4j9 s*e(%؞ܛ"q06J1Eg2Mr0LXƋAC %p4b{v7loZZ[Bj yXHB;IJg$U Ap^k !G2OG'薤eav3ρr `P '͒9A[5]2,-La-{GFT'p|'EeHrH"`0P ˜O):|2:)CAare.J‘S4lYÔ 9ԇG kia ki~(5TzXn_ÙCGȰ |`\ .|@j$sflzdE!z1 D2ʌk~/Qf{KXSXCsxuAi:G13e4;9W±Ak#J4!"s`, tH h^8]8DVF m`݅p0h1`5%0$%L |)n(fLW1Oumkar_↧d P~-LG20g?3Pv`,R 4?'SLXk#O+1qdȰk؃JtL^лq}TAɊQiC #ݤQD$hs61q'W ΘI SXGsxBƽFa:G>Gz\8@zP5W^ B\FOr#W"n< ;xxPLK{ QbБK#/ ;*vrU s#٨%ܷLJU/-#޳3UDb%#3uDP{uD"io/$ҢPMŇBX/${H1pz5!b<;z!X{lCKfZؑxqaoHY9@ >-)ŁQ\p's`YhA-\@C67iZ0A[v |"ֹ;!jQ {f C%/pa@ aj-@"eB88:q8"tow'z?t:Jw LLMѥ {)>x'co*&A'>e` 㾙#8Nto +Xi捏l?4:-0|` >_LЕQ0'5tOEVu&^ I-HG0.#Ll SJcI uL*"w'hi]a/i`TY^]`"JO+ǡ1-J4bքIADwN8$|11?A$d.}1Y%y:7foK`s6C;a&|P SZfG2[#HƔ(*>hgvT)]WHxݺ(G \0m|@Y` WnhO3Ǖ'Xp7&v܈Ȣ T^p{pc /|ާemFAC204_"\p~)aZ޽ЧUiWUߖ1O,hn+K!Fј~.2#sja%rQ'4w?YZ%Stt'Fn8t+"΄΃QL8$ncn\x" SdFfH ki~(8qLO{dx$@`E4R-քx*)*0e1sqb;7ޤ(>hK MV*3bgKXϔu}D9`| 2& ưtVߝ?|dԭ bFfT6vkX 9/*[.lP ylμ)8$|ȧe W04w?h:F5ѷva躘Pqx]R4_:G%fQMax|g 0KGr ;KD@+1KgQ8]:{HS<';`2fN(.,#ŢGŘ #] wۤV˲ZoqRM)cUU2oqRXKsxCn]d6 Bjp%XXE9 0Q8,X^šJ _.,$[nQŒS5 o\nT6o_bF8v%C0 ")9kS`Aۢ ݀I3Yt)n!Cg}s"fq)gS>~rnV_ުK}"/| k.d ޽ RB4H *-kN*UR|oդdorUխs)q0Lxϒ!}H-G?43N~F dS^sei`/,@L#dÂݩ(?0CQm1v=xwDl{~cQ 8FAxjO:,1edPەRXC13Ko7q.^v ݪ*->ԡ_7* TlZ G(b6#&{Ǡ \$EҢnyH, \ '1菰 {x>*Xqa8:oz9Hi,k%B搰gT6Z2G ka ki~и K]S!6 7=7.=Vs "H=%A0T!)9;wE ۀ Í@.lg ^DHƖ0-8, iI`:Eg aQSXG3ы} %8򙗶DZ_Z >p`š$ђ|z)04w?'KTS~bC7p-VpCIbh;} G6s+6c#f 뭫utaNUU/<iH]* ,-La- !~yo94Q')U_\#2=b qq;<&0?ia k-Nh}pAl:aP7H`N ,s` /PbsI 9 P ~AO C \ ح;wyQ@͙"RxFۓC'{>߭;=)P …9YD=HN:`SAt+(R@ %z<kMa9)9;Xcu.֙0ɐq&mVQE0>U5ETolÔ LT ZAn2+݋"T8Yˆ-!gOjP_~o~b77L aWqŀ垗_ f_]EAa o\LQmkm(d@ɞ0xe' jn 1c2| H\(~n|ۅUǕGi*7]Ώk]h'lc`3o>>Y` hNˊ3 ^ٺ0}/qZj6]Oce[QUs/ӗkDI%< 3 La 1-Tw:b*ny^GL}ϘfN'=X$wTGLx9Q.:&X wlwfّbk8\-)#ZsX0篣m2G ka ki~)pc!./1ǵvsVbǫ`Wxm8 !f.M_9+b }As (.D*>h Hf~S~{3[$_*;Ed?0`8l2&fGcԵXҰTq+rJ7,%aM< WI.!!$[ z[b.Ϳ[agT#r4t0Qڇmob[K8\%! a9%cn'!XdQsCØ/Z^#\:GG`uEqB2(  sdY\"J$6w/nI㼑}qY''ozz*}[1o-s0Ѝ͵mLƤ(REq y/:;7̉Ls5=Oyg<4yiÚCEÒASxXG3x|E W(n8,0>A)$|ih1J:ûyv90 ݘH#bwQ0fB)8w/)c=F GDE*I?zw0R{d!0LJp.}%oqL10E#mb\ T?KllŇ` *m@ Ga%ۢE1A<aa18DT.L`4q *ǠeK\u87HMFS20LX9\:-դ"HG/4+"#'}bkk0KbN5 B|԰2ÔiQؿ# %Iha ki~ȼl<0q<αS{͇Khp)m)-odqКa&f:R6*ĒAaJ^;ڋlq0Lsv̡cdWGZZû}}*ԀDĕҡ4VT\$]Σ1Wut!#vk0E1r";=H ìP:o{N1K(UEe+0GEX`,PKk2 eW7Yma Ù0vZ/D.GZtֶ8q,~9$LzY'!x!8dHc?]Tò\X 0˨ :A‡ܧDZN|big[5S ^PDG%20J(-ّ?11C={k.[2>$SpT!)9; 7 SSΉ3AtQ\yCEMbȋ_ n["#$%La%݋\*]Ib1sqMzIkE+\d`)za*Hz& 4` h^ Fesȡ`Uª 7'Lh Lx# /Xn8X*"US PՏ!@aZQ 'Nw rdxR1kO(~.ءIZû4#.nHۂLp<׳&oܢ#s0Lh!"1%0<R ^P5b96f1 U\-pU w0-eF_}`2ByÁ+ ZZû62yf%&i \ sobe5ay7)ڭav`HGKA݉t4 #1SvG뒓W( !6Q8J^Coܛ r@ SXKsx2rÆ>Xj!x o܂}BFyRD>0Xa1 ,p1)??3*J;Q"eAC\kMqWpY)būbnsIA%Zɢ\7 Oq3~7>LV CK "N< O$ zq̳ g'-L!% Xia.텇\+G.uO[rIzvœ CgYNLK-La-w:75qD: BJOKXyؙR{5ƔήKġBoRC1Ίww 7{Td ENPz{.lIǮ(zבhapkln _[ɦ>.a.*֥9Y ~lWjnު )aHLa ?@8iti<Ę8 |.B`8- Ij~ "@ F(,11d4=R3a{xxmZA&~2JZ"+J$Ej-^Uu5b0&@d۟c 7ՖIE{W gk÷Y usuRXA3xwA0ݝg2"  q|JMΡ"z[Xœw/o a[ SHI1xwbwQ3BbC[a+xtVH)B 0cpS*v- +xQXG3x=U8jaIå̗W*Xk(ͻ)V'j,)"'ݑ V6x 866P1 s_J+rApH1|Ypm0ubreYZZû[1nZa5F'L0 2 T 1(±eE -"9K_K S|exxq9#0@HHi0Γ [{K=4|cHl.C.hta8ͻGz~QpOt`ټK~-Laeelo@ۄxvbϮE `6`)ߘPQmɨQ H 9*|F<֛1` 8e=cDY}ka.I{Y_BHAwVbܲ;i0\_@mtBxD·}cSuu}цu! ܨ$ YZʩҕj8ooTsa@=j@ƟG.F͵$5[DMQμs0‘ 3.'V%04w?7B8Z`#pnƘC¹l')-AnАd4}0W'د8tcƜqBXݵ+z Z399A+M{0QXksxB=;q;hpe´|@UȺƩqmQal W]0Qr d ^**qgᜬTWۈGhί(RGKfE10.%BO{r(* _RfN n#`:]ps0l0Krq{ll߭;]8`fL;8G8SqUK:E9P+'LEb86CT=@"%CZM ^Hy;-#l5( 2fn>r *&pΘphq<:{4WRmd̖_8'g7 ~~n{5?nr24Tv_iq _k3SEY!˓ab*[,Ce)8 0A MYџ6PևphN w 8? I  ){UM"D{bOLLP.2r,X(@ %t6U0U4w'رፍt8}`aQTv ¤('9n;,Lz8ʷlU,-La-qAK#li'\;a8 6a"i#ı.1Rb>^5q^x S<{n=J!p8b8Ƙ|S{RppH ;*O;0nKػ4Jɠa7& tw-yg pR8P 3z<}.1Db%^u2^!'D#nrpxmO S8/uƫJLÞO%P4`T;)4#kZW@ SDH́y&9DĒ(ȭ~Nu© ,3$KF>kK:yҍi)l28qa  ){Ao䚞̾7̃+ka2irQj a<8) A5R`8VwkBąb" ~ xQdO aH}hXȟ%B/3)_{eA7ɓ0upp1*rk{f]rJl\Uc $i2\֢qVQ,?;c8hu!@`!)МC QiT!(3HipXpDt)w$P&;(̿kx&8\a%-µs^0$ -!_m&v[)n$)Z8f19X}v [e|399 91 FVb\PM]lғq-_NMsxAԝU~`cFD~j/Z)9(djJSc.҃h\.0zYZ8E-o;E[ZV/r iHj~0!ܓ`,LΡk e֛v3x[_~? o')6'),䐰`ÛP? w0Smm*ca'u|c}u[G3 {p\9_9\Sǽ N*:͋~hz%<av9(+W" 'bRTNT)\EpX@FSYW`7eTo^0})?j[5AߖhGo8E,oh^˫Ik{A%)JeM Cb Å/pʸ5Z•e؋%G ,20f^sԴliB8& N)p%•t/+a`'V9֟"ĒJ,QAw~g;>9+e ?1u%DZ'+e2|!ǁyCy@T{X >)wp-}!@0UPZFD5cy0?|L>QRm^_h0CIa,֔r|SB5(\C1x[2FCkGC|J&KB0EX ̇s`ʔ,S ex;80V.nIDſc[-E8-aaOq.u)?+3x[AԉkyE6R"(\I1x[A˚. `c_Xj>ޯV:KQxsad4pOSISQSm7 @fuq`U;P\iMN1/haʀmtɡJZ8kvh<Ǹpq *6նPO@ &s4|X{Zoo״!5pUt/`ScVihn v ޕ0SXaʰ]?8ol-EPmG؆1vzոKcÕr m+@Fr, D!,=wE d-`nmaj#5-ulbmY`)-R?Ҵm4K5嶑8|2=JZ*cM/+芩} fc`nWh00WB 4~sB 0%E(P.:2 t3 b]ł0 %,a0n'd q% ^Y_2Ojk6&=j0c s,`0PH}H@B:ije5 O7҅RaN,YH5(N' X20Yȡ,+R`|EPmm\d8:6q%e7FOGYk֚/Boo!D?)Bg1x`f5K' p;y`ƨYޘhwH ؆VeҠhLrVQL$HSP)\K𶃶m)]rqnlrjWJ.e1V98 @+w. UJ 'Awi_&ЪDKn'ftf,{|3[\R)\E6U.Y xTܾOSET)&)&̍ 0M'"oH>t(J%>BB/t zqa80,#^FR&>Zg%g\`EAQ0Em>c+>Lp /CyfgyqO)g z@,\Ysx 0ss0bi4,NC)`y % <a֣/Rc@P~Pm2g?Hg`T;iokQX C5pfq ̇ЬrTh! oƾn I OQ8H1L_SDUT)f9nbpᘁ-|ektOsKЫy Η :w$]?r>MFmH o5ᇳ/+fbl9FX\) ^a|.0>isx{p߻ azU4wIaރ)C=̀Er2۠SmmS>'@8u(&ǵRc]>G^բRasq`I5車yMy!>K :;`hy|%D{=<,1hH@X~3x,R0% 6x<'z+5 ڠjBnUSpLeCrX%5IfŸ1TbZD[11M游sqq8Lh!̅ja6Dsc5m: $zDn[ MSl=k?88 zU"W9_$xy×16"Fc~v,xbv ʓ^M8Dt‡V03`r*J:wWћa2[9% tݬJU:M' ^`Y ~'_8ZI'pۄxPIk,OD} $wta:d1*|bsp21J:SFWqj8P+\;b`*0H>C y:ޘ̃J!IֲEˤ~wZ5nr;0kMjOKKKk*Xl'% o0'm1/M\ p-ڶ:峇c)Rd~A;^\8xUbRa1flQ 'H̜30qC+8v>axF,^;3!%=X&1}#4KFhsxۡ^+H}lM+*ec *d %(aEs^E(MP=,baa{+<'V\|+Yuz5;Aa{2`X|JT)\E6B=6y w[ށBg[i$%|A39 1! ze%m 5w, _KՑ0-ّ XCISd %h(.~$4$@SfyY/F`6dLCzBmȨvl΋Nb̄4 CrPG/eSmm."m0'duR/%xd! 0b`"+Ut/dV6im7>D vU%4k gNW8pS,f/[ްq c@HSr᭾*PlAH1i-ETkXtF&ڱ 1(\I1xW 'Ɯ[c: xIv;`,h$]sxA^fUch-'v9,C)N*]08=rbxaa5d5)«ҥN::>$[jpNXSZyB-SF/qfռwURh!R>^LU"e$0r컢Xt { İJYr`uB 'p ZfŸ/Y.1,,,wxs K[,22׍K +%VK^.Eh)mQ`jp/,<26G\FA< .{_Ƹ N*ڵ+f&/r)Ԩa֌56DqwLݼ|Y^ f>YJ2gRe2dk0 X3ذ+-嶛ԒQ!0e@Qa&( 1isxE{ ̃p<ҖEpAVeLyP(+Rpp2cPpR2kdzPmmkYbXaQЬe3;X%(l+1{Is䀚f)B5B*͌<+q`,)lRޒ ]ZA0 R:|ٜNH)0K*"TOF*[bXa!\rk`٘85gRpm #X1lG(+`O#HaXK \Ɖ}W EP@Eo~O{fQ'M z5J`r]=`FL*xR])ɁuRWK-"a[W2.t@R'6A(88Y)KhN!%( h%|X {P;-AWXA^*1X+exPB| wS{HUY暬eR=Vٻ3XWɁձBJuto+hٺkg%寚DEI*i hG^ ) )C^*1X+exB8|CK,5"S5ߛ;\J ^C+UpPZFh<"Za f+NfKjKN){İ Vr@HP.@?mBKdQRİLTcjOꅦ3?N1u<"PQ2R!# MA!-Vo9ˢ0s&2ب K7}ψ?88L1X*et -µto;h}旬ibPYJ{ +8$5j*6ɁUnRI-µto;̶n(GbTt[ n՞Ղ[/Q9VnIGC;ZKxP> 8a4maBS-t{qt!ߤGZ3̂痬i*LL,o,~dA$E\4@r`ڔlS p-6B3 Y";`, ,s0p"0P5BpF>Ñͺ%(lv P:XypSHLx2! &$vp((Iӟpb GuKz1Hy3Gwۢ%ΛO NJ֟pPXtg@kǁ~I}Ճ&@= EQ5$/8k^&Ъݵ /ȝuT% 7>qgy '{6RqNZۊlGØpO%@lr#nd7wث$C#RIUto#hD֋I ˽l^ hoGXJ{9ÚAaBF -"ͮQ^%1үչZTOpVG}ng+Hy- sWe-rث$Q Z8k)m{:4,&f9nN<r"'Y[6jW80 &;R0\wV}b).-`SrP4='IbX %9J+m#LlS1Ξ 2h7O/*<%ػMiWAbOCQ"4$O&h$zXI t  +ݜu +[``aj@I K$PI ^d%4pWM8,J5V)xwTsFlA8:JbX"%9J+m-zR$a!^ӟGz JtZ0గ I $I^$p 9mju; ܈]/}"[hH%pX[İFr`Y;R p-`*sWoL|5ƢKY[!0"GRRqIR0WKEcCap 9P-f5-[LLtf+["zP@`i> qu2llw iYsx^^_쿓WvNfK^k)ͫ^^t_7?)-2g'&ªTa$]JMv^yYkS \k-!BAZ;h7݌8807Ël=rٯo[uФ6f dG$f er+rp \Gg𶂖U.~,g]8{DžU5Xp p"!UlbX792n ۤSmmӱ7 -1{8rT= < ^gx%\a (6eh2bl10Ɛ%@F\X2,1VJK0@UB@ ڿm]<n3FO^/\a sfm-AC^J N*:z,3#l66E9}Aq2KRP fU CHYq$BBp% oY90vhm,o n1Lz?{!W6¼}d PcrI)B0 9eޙSL3*DŽB17CSHx :oJ"+R@Pڿm]*3i'.zDŽnKr|wtȅHxRs΃A X2c,J,^"aA-vo;`[LlNk8y5$!I v+-0)9K \|ֺ0rɏCc5[@7:0Ѹ48i7"1++`ȕS1)B>o; l \m kϵԍv ёUXdW+ aQW3)8%! a3NU1˩Se o\e[k J=5` f7Iqa78|i ̍0%cƘp-BJ:a.BCݡ]:5 `g/Y!Èhs8Iݰ :66W ^AtXAtNeL~$#JHJz*8k 6.[5ڼj*d /0j1DO0gJP f %C ,CZ w~0~o yoV.a\;:LIAdX , |!Zvж{˰#ǁ1jkK7)P}>Mm'A(Sn F YHp Zn7 <8rW4\험.mMBzr5e󀗜A3@qC`<:8|2B]F >=ٻDG Kh1g`Ƚ;9L3<(l, Җ.C0:M N!- O80LWEt\lp1V)PJSS͇2[ )3x[!j<S=~]| 쉢G>|y &]p *R0ZM[54٧x3}E(Z?"̚qBZQ@q5 p ZQcuZ%hp]+fa> rI,7xo&T)\_1HeNQr9YJBoZv0lBڤq}7gD砥z NZ:b2g ؘЅ'y34<c,YŠJÔqK9yj CJ)zsXsc^N\ŦX8N!%ٵm9yFerȨ&[g{AkBXN-|nH1ԩAPmͲըp8()tq+-r\K z٫yEၹv6EۂM?zjV_MLEvb9f!)ףymG %Mr{[ BR$ (0LJ"$OV2˼[؈4;UK:BC)Y/{)tv@NJy@ O&,~+|hc/螠g4%`@wS3P(¯K otp e6/=1 zۀ|#@{!`A`x%;X* 6& >^ p U3m2}Y \4v0 U) :AE׺1P< 2(L 5ڡSm-8V9AIyͪM//eF$O1x|ksķJ , ƽRIJ:4l" "`@h3[%)cW1! 촃AN;DÓNJ FT&B6ͥVvBuZ{"'=b޹6%gSQ܃SspIb$K2i ,%•g*!. ج(*ޚs fU8eCn?ca -I,ܘg_Ӥ{JktGOIɸ0DEnO*Q3y'ys2v4\%H)*RjsxA&Rm5E[ @[tl8u;^H\pXaP#.({jsxAвOp&}/Ќq1 &8$G8Y8p< 2jɈ0E>% U}2t:)Lg^yVj zMBR~vi^Hf)/:n:|-{3+6ECpfbl%nMIDPHG@ c,:ۭ2& M}Aa. X21Hbn%]`k!-"m V^r/\ ˇ@98L0M`W76Q:sռ[ydgd0z0`=t9ō٫Ň_) :J=cWmwu#|x0]4fN 6B%.aL~RZ_&Ъ r6Kn aID@ %b'dc~wZul/N6?+`(,/#;f`&Ngݡ%p 9e{a*203^ze"a]a s1Xvs@:Eh-o+dEQ%@x5No"a֏LPD0'[&V\0/i"Z!0b7BiLv@عV pJ:qn4$M U \Ag6Af x?80 '֬bGm0AY088&)J](CNSmg+.,,w --$ re85 Rb7?DG' c|:p:<*^ZaotX:A Xj$\xxd`WJ ނ N*: a8qXUqdw{ 姈~1)c)q<i;EGPqrp216֒@AI m-QiϞ &siߗTs/ C4; (apxR0H;0Jx0|j:*0"@Aѹ@ %\(j! ˝{(o#d/4 _ |U ea`xqrpVs/90cs ӤSCC)M58xZЎ$ ծ@PܕT"!E?(,Ҩ Ga*.CAAQZ8kv6sb[n`*z.%s20,+;Ž\"SZcG_sp /c?Cj0V5ޑAMhiU6V5( Rѩ7Wp Sm 0jc9X|@+xipÔM)_&`sAp 9pvv MLA7p-,`-`<@8*sQ֣s |԰<@TA Ղ[yde {?LZZbjnloA9 |L a_=FsBGO) &Y8xZcULouHExasrl-8H K 7p>A6uto+8 EQT )eX!F ؆Na9'CKId`@)b'(p 9Hd3T0\z~pz0ecl+ .}\J8E]~~gV3UuD9b Gźقp)΃ÝUѐ?$(DưNJ:4l/[V808e1sv4pK- s5-q,te]vc8gu礢nɝ: siƒ`ɀX Ai[qgp ׷0'\)WT+clU-wEa andz4(@0␟s h+U-UXULmgʠXhZpǨm\b2ue5a=w W9՗IbyXl5B&=b !8()dAJYr5G ˨DP𶂖YUy`Vb3b[3,exb<_(| S`2`iJ8Eh-o+`lOLAzjX:Rκ֢l!My K7b6:$l-EPH𶃶1@DbQVF8lb6 + Rc;%k"vPm,cҺqSD +zՒ9`R%>@ԤspRGL` La[(epx!{%$ h=`jgPtƄ>Y]B!sxۡ &$ (16``! {N3(A;2.t2L&L•so93,La.FwώyP0G۾X'`[&` %|!7.D rHUto#dŌtY+ #Lƭ꣛G7?)ad0E2\_HKN*__>Ϙb;5?Nyy~+7J<S+_E`?@`~ 1] Y]ǁǁ823 ?bw /i@aa@ awugP#El%•,e VB[_Jǻm[LNI7 S2ӔptlYS3b /`rg+)ؤ#)ݿ\|Gl-DP𶂖?sҙ(17zUQ^s,`^蓃ÔM8Nv|h~wfͻC1EEybvn`]QSw0xhpbwrz9Z@NSlV1[#(1,T;$fVGlR$9:9|1Jp'eW]R \Gg",k\(J̣ќi\qx9,(Qrpx)>17|"KBS,j=(\KCc;g16׬#[Fd\zZ[L?O~` ; f85}g.!<~vufrTl4wA] sox8['%'(\Gg𶂖D?&f0/96so,NQVk /\B %OæV[n :V7lC X夁CS0 r2p"cX:90\!eT %uto+h53cn l\ì  #61C/dPq"ކN::L鋙X*k.1%y^fQ]S˄t!0p 9fc1P8 aQ#D<;[|p @XJ}EjK%_S&)B0N!W/ڜW Bc&KfrelR2nɀ$ U!g wrie' W9a,2MlqK|PS-Uw'|1Y^bE P_N MT W9P=Dc SK"U4A. tS4f?9XAZNZ: ˯nWp D8}&9;svS?8)- R8 zz)3xAFc<3*R!SP,$W< Z0yt!/2 WR V5r?X ]Q6cA~Hm[>[p̥.f.cD:ۆ0bD c>}mU k$qPh/1(?t]=1n*r1.9:Ÿu fA%8ϥ x+EPm;mNXFkvcCo (nLlRY,a-iO(FRu WB3es;aV(sq"`0ve]*]Co?p%m_4~V@`&r|Λ$ yLIܣ9owCӇ> wI p-v+ڭX & l?w-v\$m~T ̚`KcqFf|BUL;UE/i{WNsT].spxd`UOUSa,SbF{,"0gͱG>`)d'Ȩ 4` cSZJ>J8Vl':F݊pܡb?Z4,d0EX 049X~z l}&%uOV.Evr)q`&]SKucjQgYb!ҝȓÔtF.SFS-)\K𶃶q?zhޣ'˂1 /|`dik0rkYT-$8gNZ;tz580WեpGmSاppMb* %0ƔAZNZ:/pE`*J.h 9;)&9̙fBDU Q-µto;d O6Am(CIïarGa&݆uI?r~7¯KWgUV{Q,/ُ?]۟ݏӜ=87F=_yͯq@~4g_F|_W__qZNvs}kbgi_G O׿Rؿv){|͏~>q͹znk7ĎE u= ?@Y!wTkaǟ3.mȇ2k~V:uɴ{ʽ4|GZÎ*'e^X_ϥv6|ږ3+ъfPktn/~DKcsx:e=a{~G0lG֬z֨xj<9Yuftמa)qfc S9l,W⩯ by·kgρtt1/rVj-[i@C{ݝܽt=ո__ |Ͽ%~a1WW 혱11b_?o?527??45Yb??Sbح?aC:.L1m\ρk9Kwgo_~ï+9{l^ß_:$k(M^GrlcF??1V,;ʶbSսl+')UEaE"-yOc(td2//`g7XIz@БP5ln[>InocIE#E 4?u-:0߼P,t/&Zmn%@ ;7İe3c1vZ&O{$\n#7gXd` l9f6s6c؈p/̈or6oV%wbN53fςGdlLVfG5wʝ`z3D%] cSաWUQ=XMew*L5EO],ɐ3iTGo4*,B;9;ǻm^ 3< .R ciMˆY mlVz [ lKd ,*VX9v_bښ$n&L u]tIܖ|-azf#̷h E%3F戸?٨#XVqA屜lu~c[M/le.1EW=mxZvn/hΔ |wըX@ cf?+CGO%h!oFؙж ]5 vdR5,QjFdQ1?"Gcf*]Κ[/˹'מtfy9?"1lA|zv{ܲ17'=CO&fS )&Kap\;$E7 dHP\k XcnwWavg<@_"yA7įkgSa-EO#V}< q }T6A A]JtIokR9҈;sR}gV5xOvƊvI6ǟPVn,;t`m`_wlZ96A<&=b'J zQT¼9X\%yQ=, pP sRIuj=t{?ٓ L e\>BCO=f1Rl_$z_3'c,kfӱ@.1!׬ͨ L:;VA@_N rhγ@:W FS\1q6pĴɐ ~a\9!Q4{E:.K^8W{}We’"!o 57 ޘµam8V]4dvZ-i֧m ~]yޘHQp07c!m,Bձ.ϭ| c)?+X*]QC&kLfDv4Ĭ UFf)sHAY=Wu\Hl1XWa%sTܜG2"˝U{"K% ՘ܨ| AjŅhB@4l@-~,z!uV"a#Bv-6Knvƣ.j:+^-39V7J`jijEvx΢L'Wwe!G nɌ˱4f>,.IX'\&}[1m ckۼAvzl+yp_\l̺Y))pګ[g՛1T-I~Ih.[-^?i4Lca3EuqW-ܶZ U+(Ls}BOl0 cC>crZ5{1}xٸ¥lAhE2'&M07b+%isU- }''Ю .rC冴&iBw/v;woͲ\,alưh,jsc/4*ٿ=XِŎ& ):H}V-tg94L^8@7PV@L{ՍJ+t{"1͢Qq&h婬!kg7: 4&f'{o\/4ג)$˿Oc1'漃1'I嘃*]jEMOzy>\/ctr-tAZa?1;TY2yQ^*aN*fo<%:E4:b/|̿ <|jf-rA\.r}5f)k?Pfe|! ª0ّăKsIOB!knۅewPe?J8tDqJZ릛s)2\9n(IJ2B6aMXTcRr9XCƅKsWA5/=U~{tIu_߾+7}ֶ-%?SGww'gvwvP}zٟ]嫕fO>ܜ孺sZlӿxF=?/ty>O^WOfӵ㟝o-u^kT͏fvG2endstream endobj 190 0 obj << /Filter /FlateDecode /Length 50176 >> stream x̽˒.IrF7Ri%3˴CCd2#%@%-Ys=3d#Z{=h==">3Qi;{y%32.|ٿoOO)l?ӧ(y;='5I|=|\Or~8oiX^r)חϾ}Ь*݇`}׫_/>lZ6|Эϧ?lcA@_w9mC`/<&lԗ|VW49yhcۙO!ue6L}/?)ʽdXs}X,k /L%hIP ŗS&znx5KGO~|WЭ`XF|JwyyB]=׭{-OT/_K9j9'lo#m|F>q?I;Kϟ򽧓}8sh^?ּ}/>|ry=FBV}:^u7.q;q W>|l,H(~D*=_-#Oix|=m"UDI-~2}~-ɻuR8*|ca[ MmOv;I'?[/L smKywv3_g^-ɺ΁nt#IR>f =x(я=Έ1x_L9~|_D7f+mT[˴I85W:st1P Z1C]Gg4֟}g*uC1lqh1>k{W^f/?ƁȕgP{M;l *㳷T\k c6qwEu1c8[LJ x_ y]XMZ?( !);[[ 8Fu~}i|H>~=.͟?(o>:"(3SMw??ϟ̟_̟aG5~6~5}瘖1eZ%+cݛWeGM=ߟ???4ϟz^ ӿvb~ns-cq\c~mco˴h}ˌcOs1k3_o&.c,syU绍Ĕ|xx!v_cvO՞5tg=OjI#ox!)'c>بz;!?r<\~'??|O?'?'_>7_|9/շd@_s?x?z>?}?߿7O)ka41s=/ms ic/Q}f:$M*lTXPfjc,u2Fu] QkL/ìTnZodp_ OЫ uh3&d0~ʄx_Xw-1~mt6j2)hn'k:D;0 8!g|KC3R3poEPu- 0c.2ksx+h4|PusxRc{sc81 x,Jj!&Eu0ec6Co2-2ksmcY6ϵ^5MGyurc<)ʐr20'yMiSaCm,p10`ǒOb ^=`acRlK[8fh<%PS`4p%" Yǻ;Y:1kπG{L =`~ h96CyrXeiSVJkr~csD?1& yXVc$yr z*[z{@3a`FGh ޫ2>g=98,h1,:fe4Sa^/3, y1bsA8KoO{k|N%u0E肓dE"0P8Vаj)s~1z9U9|cPǧzaY&XVCHpX""0'!x-"vFu-ťc::|k&xtWY(ǽppO &q!-\ nl;;]X:cK L>*>W8jNN fp(Z˶(\IcxlW}s_6cű,vvMyƎ>lKk8JQ`.)\?[q XgF?D`0,V1H9)EurX""0\OK)~j!Ԛ :f}tS ID ޽P`ٷr' Y'*C0ZNZ:*gi`OPR|9t I0S8fL\x¾HS`Bom|~\X5n´1#>?)ƒ. %-CP2K6-"6oC'^-s%1&& QcG0xQ0p:c:Yx`vcT A*n[Ǜ~_0~ &z<>}ߤ0p0<Sg;8V1 F*#}cx;0:ݧF1AbDCO>1X"6S봈`1xBXYId*qy?17FЄ+>;ӎs8H&&:bv`S;0FN!C0G)\Kۡurߪ|n2YSZ8f|9,M"C0isUqI}t##P`\;edpΫ֏S`p-"6CY|It68ǸWA Pdaɰ='0fAp#\dlNhep[,jGGsb {]&d[pَ(A1W Shps-2Q 4h|mh\Crؗg8}a#X2P?!"6K[81ϓ6am!-\ `7B5v5#fcj.Ham)f>_K11daFyr/2eZ8kv;E4 ]qb. c 3`T+ FJ&X2; '&f4C1*LߞFZ;|s6[,$1V\i0޷x&l넉\IL+)Zdjaqx+9 fOi+M}0Nx,q$~I1^Bjy2X"FV&)C|DLE} !/{]Xסc]=a` :CZ^ hZ8Emv;4y#fombjS. )Aw<| (g{=@T[zk4p W9&h1 pfȵH :W0(@6 17 N`n cPv!@40Ut :Hg8x_08ƭ>6c}`ux=:=t ad&,4&8\c7vO5R!}bW?'bb*?t>|#9&`t yedpuT}.C0?J)Boa1]UPtgL loa<-y/{O)Be㰛`ZZWLZ[ ξ|p0HX( @JP7b/'.tJF:+lݍѼ/Q XAz 5CA@[K'X<א K}S)\Ei;8I/T5:•09@NUP > l$증y#(i`* ZUe*i*qie=I`1q#7l0EUBFoW/? |U 1'+/NZ:팴 [\8˻sXcoMxUtqpX27̅d0|.B0@L p%np6xUi8x 1|2  qxO6"K0h* Ɔf rtƉg7jK#(8oہF'}~inؿ=บmXyD)b?_U Ѹؘ1]L M 2;%o\K.b1 n⃵BLSfAw퓋2^яi9qʪ1ك@P4%öE2ksmc)ȊUA3)PЇvcbh`NH3*U} QAN~)C0'I)\KۡXlb:I/,HL,qwc2N^]\tx)@0OMpƆNpv/~Ϙ/u364=w@en;#0̍&m SB@ѢS!"0P8V(eL) }_0H*BEwOEbZ#PS s lQ#1T72YF:+̛Ѥz`M3+~Fޗ柾'dz{Eѩ=Tֻ 2d<*CUqc d%]ǯeipqgdE`>7S)BiuN*0UR}i]ɿ1eQ|=矻bBXxt_< p W&MkIx^>KzUBPa9 b|c&,wCFMw-Zr%VrEyӕ,~Q;tq0N;Kh6pS`P>EF W)BkYl$ Z#_O"{„dL`W9sdvԹ`eQcL:2Tׂc|3]D^|*bq1b-Йs!5- 0ي!`bn+ysL7,N*zrm0G7E8aɆÌ<<;!d8!ZL i99v0*II+> C(kJQΰ5k^ڃ@]siݷ s*j\06s9[cIq2yrpX210&c!؎|SaCo Qla?1^c QBZG=|yQyV'MM`pUtziv9w017Ya'5 fVAp8S$0M k!-\ p-n03c/b3ZhН"㝔`‡q 1G, "C@|_0J5H1 df9O0>gQh8,h:"9ý/̵p 8+&7y''%Aq9NdSaBZbA`O%s3dRpCQ48EU^ppX2ޞ WCjv̘ )BoaM$ms\=Slg?vva!w#:=lM"Ip-nGmct|D%Y2YDm m;E׷ a|B`FNz&JMcV>Ѝ47kMDYz),Ξ&&:d}"A0zF hV^Qh]+#M ~VqqXhcD1b|s& Z&g5%j)\Gg`N\n9Q r72XW:@2Ycؙ1qerX28옓al*Cv(BK`U-]&E JH#?YMGH ȨPn"&#`2H •p8VϗE1ebVDkWq^(:`$zgq^|s!Q5TBO`p[ pa'Ha0̠& N^`b PxO8I 'nMا"O/!cLL̽Y 2T/(޿00P8]"))Лݻ TpP8FY]gmU*k)_cOc)swM8[<.l|<:1?]:gst<A1]bڤc6*i2F}a6*0Ma6SE@*lT8n6 Q $~ߥ"@ciԶ(q(Ũ{ѩCE׷k> DQKk2,&m~Š[^88L3SfL -\pbF@zhLJzY0tǦ*+5!v]<ӿY'J. hAϮ7-U(hcLnD!Ķl#!33i#Nfl &rPY0DD Bkc[AP.ZT\brsbrc'W;^ jYGZϓAa!=הp WVв7QՑ,1,Rz,;̓V8`;1`w 5t 3Rn| dlIuӕ0~ 8Vqh/n%[=udE`l^=ty~*#\ќ9`zOsp5ht>91ɡс:e4N-µtSVMejfoYQ .%x=`P a‰1&ʋ̕p W8Vаdutʼnxh:J7DPg-0ĢTE&% ٺ1%fΏH.l6-f2Bn@֛3PRN= [ gVg tmvQ40&%-P yrhtMm9µt5OLG\Ko*a-.օJAyqҍ=[tsO9§N :uB$ EUrf.LwSQk'_g\Mk 2B`\)\Gg[ʥ2 }\eL ʥaFE|3kz&|\ o;~ܵp 8<ء` @ `$Բ`Sg1xA]-7)k/#J\`1 $Oa$8L8)MjbO)&2(BK`mc Ϗ,:e|(Wl)BMs&t; A:]Eo!!D`h*8IX" /ɑpcCJ:xl]Yj|V|jsLU fW}/[ߚ.N/tU`|IA88 NLczS 0͵08<ء%cϊ@~쉑fʺ1iݓ,w"P"jw% ڱ%vs'%" >p?lrPPac֋~`1b]?&с3D^DF W)LGgi 6$ԙ0QpM UtV0aX`dк(!.΅U QwpxcXZEn3\Avc*M%d  &/yAE?BPa7BVbYdb/WmlX1z)~=Bx-u] ´8vhQ]h! icjESBz31TqArC0 :1jOVgjsMP_WE 'N̐`!iiq3+'EQ3p81JQ*"B0ZF1θ[!iR2T36&nQ՜mM0ݙqÈA#9ds4wW[&a'JC|_02wܮ<|n]98,lq۔$ƴ2 !-´ vɫSf1AZk^*mH=;yipt: *;5 NJ MW5 ئe':lyʻ\B䝢dDc&ĒIS`PR \Gg[K;%Wӝ31L(UBh& ׅ  NԚNtH0 n-;zg S0ɳjNeVvfW}4=B@4p5t 6+Bsb29M`u]$Ui0癮c ɶ6(XߞB 'nNֱ,(bxpKqQRY/#q\ pg<039d:(BK`9ҽ|"#xB::' XG+`:T (쪌pz5/!N4x)B0ZFJ m8><^,/_0\OFovgm0ݦvN&ft.8'S`.M pni݉=P 0+Ȱëuȅ`Hq뾇IamW>:tsX,̢ rH/t5X}j)x=@Nfn@&]`蓞"&]slw4վ ^m@AA:= tMρߊSභXu}'B'"tTB8"B0Sb[xsFy8ϹU\a^aAB`kڔ`E1J)Bkc[1hNLnȘ'2!b` zbAq1sp19V)Z8kv;8kc{IU:o#V"sx#Ȥ=ÒGEA5J{f"Vr u!XbmbhrMHȀg6.0  \00P@fJS`\Ln%пlCܬ4St܁@oX]m2p̿&D㘽Sh`*El 6'JLնoG" EFÒ;)C)BoU>XfAC˜gEE p/ Tuۀ:1cOVyvjsLX>DŽ,M ) E8VX^(:!3$XL54 1-b-vhKȋK,`:oa?Xwo5) gJcODOM~!Sn㚊ÖD@tƎ3KdsV-\c;9^-c*B0qQaBXVJ&Us+y}NN!pwzj."36ﮢ7ߍܤ&8hd$7f1&7ߔ"!ll ƒԫoOSJG ;E,YGDC2`a v P&ʧ6*R{(mw#4*rȶ~*)Tېo5$23VfA +)/^=FW)Bgc`W60Y/ʻ3QipXĸÖvuՅ@ `ҕ!2Ngs^왝epfm3Giђt9tV6sY΅AVebN fN:: Yn͂ccnڀ`bG(Y:o^\卉K=㎱'Q촒5-AC0T@?,`0Aj?@m̠7 hctZ F8ΐ` Bgc`g8eh!CG6(cX,c+ QIT0}4wXy mT`>C8fyMq 7u.9ƁhAa!&iFM>d޾׬Mg-&29!N`FvjuY#!V{o,ESSF⍜' xlޔ3,Q#oaEC``#*5 !2zpL4ȹ<.p WV\pdqbx2_p>3H@a~.A:b`:O݃Cэ.סC`Z"EIӚBa7"G`U'v֣98,l8P;e-HzyJpl^mǴ&t!59+5;V9Ac"B NZ ;eï{b'+{Lcx-oeI!`ɰ|2 )p 9<k# q1Y, wsLdsQ=;w tOm[L_`Y0U]jR3ڭA>Uz98,v%Lf"3Hm!i*V{C4(84~a8y fEr9yQOezsE`7LpnVRgK%Y;0 mSXtEW`` tzCC9e 9v;1VVDD .(;+;Xw]} pO[8L :+hS@f) ݃SfF&SKU҅ 8AD  ?xr.J p:e7E`*l`w#,YE'B<iBp4 .~Au v,C-µ6v8[#X/&DqJ>  02}spr8 ߞB -Ã^*RlUYJu߿TcߩTwEt_~uأq2Bb2(jT҆٨_SW*lTU{0*GPfBqT٨XEhe^'W:d ZٓN e]9|K=cH81a\ άBMN)4djaJ@GTFOc]`0Ut ܾ᚟fQl< 2Kǽ7&xPpܼbSdt`aE`4u0 Lpn,ǘ1譨]LLc[~m%g9NQtAjpp2 (59R]i)S pfJcʃR&`PUzį\9KCjI×]`~_a8>p8vKP Kd ҝ0 ".] WRA<1>5u r zu1,Ƹ _kH=ToM1@0{2h]rBn^Yrͪ51机a<͓ӤPM!+fzK) S`3>/VLLY|s .WK8|Sa7B/kqi[Z((ƻ]ެ#KFY<9EC&bpДqYaS 6R8NZ01<bt fQ~] n ` Lab0̀:8 v+bJ PX}H%sf]$3XW2hN&{ e*`1XA+)vp7`% tZt,R 8gpl ؖn}/&B N:: [v;981])?3~˩VJ uG]9o9͌в)T z}[U+0T5`×]b%[AkdprpLgp?a0ZAzsMyHWFt#LUV4im0=MZũu3pP100Dkʔp8VȲܕq%Rn <;^CzF9-42hM@-N :F,S-^#Rvf1)jdELQc ajqWv̀Aj)͇En;j M_c^Vc2ȷVJ[Z{+SbbNveSWǏc=$A&|S+0orAʔ-"4vQyO85^V\A(0ZN 7[%CvbBPftcR]pb^WM^rOUn2޶b$2(,)8LhD[LLۭ&C0uM 0%fXcZ^`^Up#9wSݩ\t~O.08p;6Se8S 0jB }sc=mݪg6ԳS4{ 6S n}1mS{ )s>RKop%:IXV _Et8Zb*[s0g4]V69-ΙU%HҋdX0zI Nz-q. 'r&y%|"|r'ӟC FzɎ噳b/7زx3MXSym^'"%jKv<ɮa|1E^6 %AXG>5D;;jWm+z#Y0hGZ97MLs2 éx1 1]alNut|[}50 G.X38${pgorN'j`aa0\SK ~A-ǩ{Vx)\.xcmjoFr(l,5`H0>C59'!FQL8(Kn]0NcD@zeHW(`qV`I!W^ }y!Ȫ ^jbTL:Z Plf7;yse5Yj5[DҭH  \Z]}1,`n^ rэ>hA} ]/#5!LLg`}M sx A*:݈X,G#W;=UA0n+M8kv;&%k;BAdcǤ ")lOQT%f) msE`nL f ]wWr#ڡPW,B;BA 6oO FIa @#ꏴ lFxmב;}?%<_p)o 2"֑zdV"ǖ~`閿b"}cqD5}cǪ2JU+C qm???` 73y'~ UpQ_~Mq5ױd/oXﴠ/?cx|Ct#@1^T2z.=rو/_[цM`=::#Gwd@#<_> cIckXl}_b=6=ęu< !*wkz5ڟ)u5D 准~Kz~1Uy̺U} Rb(]蝴wǾ{x,Z$^$}k}i."JmLџ$ }ͧPfh>({

    IǓb/۽N{-=[*i:f#6m؇1Ƈ~wg\G)i^}4e>7, ;z%*G*jtI1g:џ-ϥ.cWsl U7M\ŔW[ۏ.???>'Pfa˸}51 qGciz 6XQ|_dT:sf|??QgG9ÏNz???G_}``uOӧh{?4;>ܗwocr7'i4u!/jyGϟ{wUT'`\{,S rABurӬ#wܰ6ӿ7܄n:F(7mE1->\],VFA\ XF y$$ v)$\\I*Jg8 0Ms\IVp_u}E2b ,7,IC#ח<OK?T_!iP<..W{`Zq|?Bp=k}2Fu)X`2Fu޴Rfr]'ժ^};8}<x|?>0G/H1@cy_/*Upkr]X=n>qk~W/?O]}w\nʼna 6z-'Qj˗apb6L@(N7`q`}Ôױc0X p:8y6w#pz]Ns=q{7B׆Fd @݈R(ш=n4Vףf׍#{n_k97sh!GNQ6M.DSnOUpQOʊh~ Z\ce6 1.W^ED00pE0pA$w"p %"ODf jCnwD3:TbOLӊ`\;BU6 l<a}fB`?a s>U0n s s=Zqޚ&JV\ mhN6LyU zCǣtG#j| & >4 x7.(]& k7z1,b #67 /00фr=P|| nB=e[coa4} 洷`vW`n01S5N-{ +~ȄS^|^0MCՂM@@w Â95.[F&a`xç K&NƆW /nbnc,;9@b" j;Ȉb.`"De:}2k|b[nhM&#ArZ1& 6%#-#&bȆ7`DPHt11Ăi2b07%YqۛՅaͶ È O hĂ7`x̺a.11`b2È Na(y)Ȅcn eXW "qaM8p6d BF/EJLc ShKX1 kŜz +!g6 U- q,Xԟ=̿Z,"xDR 0O +$Jc8_0Ċi2`\L:d‚`*'x#"e/dĂW`xQ†2bb 7L*Jx sˈAR2"& `" 'ѤD;^ T/`i;}U9ax-(Jj0,ʹb?j]u*4Fܜǿ"Wb')C|Y`xԆd+X0l* P|v̂m4`bxAc,&.'V$}%  d,0]LLc!).L  s2mðȆ;XC*V.:PM6,{ F~coab*>lG95e ?w7m96! KJ&ˆk7L  e+FQ˟ $)# Ă L mQo  sɈ)&L(G?oaxKaф'[FLL7,a Fqʈb+2bd=X)!:%# V̙dĂ7`NT+$SdĂћ`^{VL݌Fob 7bnU f|0bM^Pa&x.wLaX"uΙAĊ8\aX0z+U`y}4Y`G C17L~aG h.-^( xi64^aGL9m8uּ`#E4#1cՊ̈a}ӳфiD6 eƄKs4]w FobA݄%ޏCF,{ ʈcob؀ԡvÔ cobbxYSi](f؛X0ƪcobbp#05VM k@mkg`P88M[6 w8bG^]9y8rS 1È /9Ogyݱڿz>?…}g{ibZG@t`0t`30q8v<Ly0b9`"1ӛm \ ^T r!p^~QQ9GET1IDwv﨨Z$IBJ+V: t$AJ'N2ލ+$tZ$Iw+J +[V:nEX$݊V: }hn]W&I+V:I5"tIh(tw?NM+~7!tZ$݄AJw/N+mVZzAXi_iJ GXi!IhJ A/NB+-VZXi)VZAX aJ A?Z A@v& ! |M)::ltp Th!PI 54BI\Eox4TFoDWѧ/!dxDHr!`*RmXJe~>V 1Nz-ùI ?PB $$4H a?$%tjH ׫) RB }H !IRB $z"ȭRB^:HH !IRBB Mzi)$tJ!IRB $z HHhI(wm[BB'NB VpB MZ$O!I( -ݐ: %O!݈^ARBH$4Io; : %t$OtqJ$݈ABB'NB ㇄: %tJ$ABB'N®H  $t$݈I(IRB'N_H $$tJ$ )wBB'M :I7!$t0@#3>=7{9 s$pI螅= ݳ$tBG pB= {,Y }9 s$t$鞓='A?xt6RYw$3stI螅x {Yܳg!pB='9x7"spIH񌏴13>7#d3>4#5 njHA.'];re!/Ӣ^Nv rP +'VN`ϾݡvS('O@69Am7ermE`6w7]r>0**YTrd!PB,TB.$.0JV=*Yd%.0JVdP'qc+UITJ\%+q5d%!&9 2P% J)*9 UdGGHd~AGc~;n>$B@ A"`ᐅ` q{|CNB,4Ph |_@VY B\ +hG d"T 8qt 8зINq,Rı($B @ZV̌o8q~n'P0@_8lp ƾ08A}m85q 7%q {S]|.%Hb!B @'$I,XB m;B P q7inTfJMr9S.@+YnRKb%&@+$>nhZb!B& %7)-qZb!B`I$q:P `@' @=p~N7 ^ '{ᆅ OB7,nXw PB\ )  'R_-C N#^8|dX #@ ' !k˩\- @]p/x,68 u`!@ 'B+:8 uZ$Bh僸`%!A$AG$VNX zB;a!pJ +^鄅 +q'E=? y HFԃ 0cb+_l݌?2S:;,"%u^@i+/d@Nr9y8CvPo?N4m1]ⲵ{XB[IL2oK0l둺%Cm[&x;n kC#lm?)o-wwc{/Һy߮% m'tY%a힀@y-`v谕3r07n 97 97#c#dLlk C~B Fn++@^@<h) LI|D4ڒ00 %aLk0Lo %Hrava# H<804[aLb g8]\nQ3Dac؈~}[-ذNόt{0llFa0y(Qn+Ƀxƌ F CXgQ" sHWEf* XAyBxa E:06 dA Auaa{{q aAg @~J0ckoAgaLnTj1QS3c^XLfg2Gj0 {j0DDf-S2Þ|w!%cE+1Ern)q>3%c̈k1R24f1ҷioɌr3 (3ujeQ3-c+`܊0 GZfˌnh4 ̌hY#3633fg: ~063:)beƲr,|UX &{ǪỀcr/`.ϹX/*!GX*]A/P20y;0za`qG=pɏ" 6./ p?x" 6 EQE!`o3R䌹"?>]y+`_#܌#237cD5䝍IfL&l;r3&`nonfW]fx6cncC~0:sq+3W\8`RNX4)5l,O_rh.c#EsYaKј{ S4WLј: Es`.Й( Bn.`O.L0xS5{0.aٛ: vm1VH\ $0O`CL: S46~aW }jA;D:\(=s3IuI.=sS΃ܔ3sg<27 ܔ|0 ߠ)6< nY;I:Gn[rV#p3Iw8m }6 xg}.Lqv#o3 )6|m&16*6F6Qa0o*,gw/Pl s۔D"`#~juyKv9l/\ )b.K Sc͟Υ h{1OA_o 7 >ϯӎXX+8K 7.#oe,$/?Oy|~m ?/vZg]ؿ?}ϿO&Axo~K7٨j7 .'/_VL웿?A?W{ٚwԏۦEB lwy/#l]<W_ff?+G )ϋcW5z<Fۡqύzۡv9??}qګ=g}Q/|ϟ߸3vƼ^}{4[xؐ,_.Sr{PԶun}j|*Pgc]=A9s~lzkb_Ǘ$3\4~/vq__=>l<=e+_1~ԯWQ=zte[6N*_S׹?KY/#*6;}-+qԺhؙĥSDL)uP%$>F_/J;OTI*BINVc%Cw .hDnŋF݈Fʻ$esyލk\A{7w# ވ]On' 7abzA,wHrP:B :Bȍ3At3Ij$P#'$wHjeFXn;FXh\FX jo} K{7qϻK{#j7 %WxYk7;q/!//=!dD;J WRQ2'I?$&(3$=J欷by(CRBB.oDaz#n ˮq;!DOq=LzBHAOi~2+MHR}d\ %>4n5`TPB_]6sYg4H wYYʕ)e# ,i6Iv\Jd2\7BwwvUMn97s'(Z}o%(X>;BICȲNdIDU$((3?PljCyJm`jLEV'|| AȚ ,# [W|:FIځ[oă .وVH}>5XA_'t)@O)--ħ '̼P߆~WXAź-]AW- qS+6$>PRPrNsu'!>5xpbJ߉O R|jtS ( Z,$iJ|Z&Cly9 +gTAF惄Goc_#XNH◢\>i#>+f}'$WH6YJ|VH3IH#lbvG( <\;INrLHR|~jFBn/s WSl{oԆ P)zP2&OҮĵ?7RMCJ/l㠬+<XOXm\*G6RQ&A7$1mKa͑ @H7M˛ *4A5m*_d5;XNNs%ZNba` rmvRW\\Smrj=T8h^':!T ֣ir'ʷgjGi$J`V$_8Pɤ6ok%+H'l{ q(=!+ GH(+ GVQQ@ Rtx/H)"! ׬!$% ) R@ A?$)+ dH# )R$B @@ AG )MoB T=B T2z H]*RH!I( @@ (K2 H! P@> (H!pA^(R8H!$p7b)Rd:H0"!}TS$HH6u9, %yz<+$UV9KRwH%J`TW T*R ,;-LH!0B`"%nh_TCE nH@OJ:H!!B #PF !BF K)*,d =N 6N2G?F ~BR(I!$@J-)„T&ĥHI%.%q吒J#@J>M?RRT2w){Bǯ 4:hБB#@G q ֽD "m.zu.R\H!p\"]pBE&|P ;]U7~Hr:A?/)=/5$د+}e( gK@s}k@*Rf@@&@8 ~=GhE)$}+q㚱2QG%%,B? ~ $0B B@*qd H%. R Hx RJ$oVRKS*Ҕ<4@!^2& 20 8ɍYAǥw Lr[<{ 싕Eu8Ihe/D& LB+.0HX$Ihe& V6I}7"l݈Iʻae&yލMލ+V6HX$DX$DX 2!;+[ }B$ieI}Bt$ieIʒۄPieIƫ9!ˊȄ$BpBhN BpBhLM AbBhNMߍ AbBhnLM% =! 'PZJBIrB(IN%yލ $݈J8.oH+[1$V6 , @'J6z!lul~-^aMll ac&#ic&+6V mX!92&I84 m,=M‰D$AȉAb"hN-6$Ap"hN Ap"hΉo94|X"cR: 22+1MBK26 d,od$Ϸ\lŒ߹XXړ.VtBbQ\\l bp(9I84 9X|-&$txI&67Ll$4AhbzX!0B%+&b &sq$4IhbĒM&6 Ml0Ihb=T `X! !4^;1E,?ghXV4h$԰BaPö4l{k԰ am01a@>T:! 5hX!аBap񞃆Ua0@ y`0@*2`0xG$U uB MB +V4hX!аIa@ 'chX,"6 5lj$԰AB&M|aw$5,IhX԰a}baVΐ ;,lZ$IhabIha& 6aaT=haY=-`aX$(qXX!B`a B 6-lXIhaΉE&MB 6Hh$԰'5lh԰Ba@ MB kO/as05NI  +5hJa, Vg$&~V4hX!apn5횋sC`n I87T4԰Ba}C&mlM ӿB +2O M@&6Dl|%"NMB$Dl‹M">_"V@"oE"v#)bIR>߉XmbbIBK6$u,IX$idIRɒ\1#/dB8Yd6 'Nm++JxU yz(p^VNUem%gjEmZ@!Ie /^B:/T{فdTh(eB e@ )+R}/HYV)RV.TVIpKK{ZBr|N[I\}x&y/ڗu'-.? r]Aۋ{]c1ܷ6& ?Z|?*[1boCC1I y[Frw\{F$x.v;@c)1Z/VjinvX)hzV<4bpgTvj^GVj0^kĝUF`$艋Xi1EU'aOܨg>[2\0~o`{ƶAr's5w,dW'9pXtUگ 霋lαlOpqLذ^3’pι.tεGs._/9X=9>2c+N2r`{rll c9wţJrn>D,(g,禾X΍|prgbrnW#s3XJ,byxX΃2_,c9o7yxsXuXO"r泿_#PrK tџ˱R~f,V=@'xoB9v_ʱ]B96qx?tz1 ؂~0cC9Ă\>B9y`(ǖ=PⱅrE.tr:ΈĬ݈h/c9VFeH 2*1SEs"9ќq9fWE8a70cw bA8)n0#52ι\DlA0ck;@637؈u3qh`eFsVќ)?\hߖ23C%^ќQ2 |2 U&"ӿUN9_8<9Qo?9|lWTlNm&9xl΍XlglN"S9 9]l-Hds RY߼gFsN dγ'sl'LԛY#3FBm:9hN\ͱg= Sk$f5FBΊ X(K$mo`e {'FtpY}ಚگݰ@;ߠ"sP` a0g^2b0b)K9Y_I8QÊlpF|nF9Dw6xU%??<8{\ײ6y'tYr|FEF`z09ƈHΉ;vDrlD3&SoDrs FrNq)~rDi&K7 ei)A{tZqJE"dzȱaQ{CDrOS|J$Y%_x7[HNYgCgoxAf'4ã_FD++ȹBf1PQK+&jmn 1O/kQ=Gy^(h,>{A=g/PQ2q+f23c7WR곣tyg:RQqLJd2s~4Ή9%Q}^DThSqLJLE`g2S86+AX<(ޘ9bƩq0NƱ ^ᒞa6 n R޳H{۬X[ʴN흙u":ު*Y=fGe#s12uگ‚ ~NyN;BiFNόXp26G2i*#s?;kS\l8BB(ʴ89X98=e猞b,(qqЈ84Kh8NA}Lj^2#Shq* (BȢ,0ؖ[,:c",.Shoh'bQW(6YIo> QP@g8_>ʼnQapgNKgGώ"YM곟lBhh'qN ęFo$qgަ<Ŋ$$k$q&n89ęaqTH'QZ GTg." ɂΞ1&Vg?:{V9=Ayr~XugzYzgowgo͟ <{ ,0&˳w?eyy˳Ag:>f:@fr8HϏ=X}jz.vXXcV'Z+$;~*7Tqsm_?\5WיQO/݋Fo~KJP^k<*m?wg_-1Ok .6>7 l>ad <WeW~~5>3ڣg>5OvMߛ?gۤfƾ?oOf'+</?4okŸz\m*v%c(w8rͯ|t~ԯm~ԯXdp ?Wlɯ~E(-WZmc^fw<@lz>шjD])cjq5v!J$+|{G:j *21QK`|)fnɷl-4鯶˫V|}-sG|ѮZBr_||]vBUK(J[OS|qK76,::_a|g<?;xmw[}VWqPխE*^+x<×w%>d3m7`CNxF:IVv#$J|Wx5FFXiƽjִ{/RLލ(>y7{z]wwOuy݈CBzy7}n~7bF1| ^uq௒|e~.^ܧ7B\!!=a?댴7WcJ|^ z7쾓F$_%7Qx%嵒Q"oO$Ňᕠ'5@dx#lV 줞"&$`%7ALFoD~a~e[}} @qxK=^/ݐ: ć_;+AG2F+ tHG+Ѷʼn#J'[߁k o=$92lHBeQF<7BHaZ`i 7BcFH=N4"Vy5.\)! !׷OYVI٨Y5*[#.$GO5w#7"I] p#!fpǽFj􄐕 VbY库r%!=dRލ z!{vzBtZ}CZS7=dX%szPCHϊ5AA <W4'K'l<~lK5R Veހϝ'%+ !$J.oCF,y# 4"퉙 f]V#YG"!\m`<+'< n\i\}uv }Tt@UQA-ogۚ\pMON/wp[B<\ބ$0ʻ !,i$Dh;hDtBvurވ*[\ҽ\_nNK@7R%(ΘrN9!s1~NOYL?'~. K"?'N( U=~N9!$sBB脒 Tz.:"PTs `@%K-V.\t*4r kܯM1]Pnp s3S% 'GK8pI(P>&%\ܭB% 'NOJ8!ky@aQtp %1_LC KB'NzA 8pI .N {A O8%p?{N8%K)Φ8%p% ($tpB~*.3wtpvNC:8!!ppB q' GjD88!ppd8 @gY N 7pfJܐG S# 8%ntq$0pJN2p @$S# !0pJʻ4p3 y8c#'΢~ ~G)߮ 囝~޹oBAB A|M䛐#W@ d7oJ\)q' %?B.,' 䛒jD9}L7!Sa߄@$#Nz=TPp @ HB' NzBDG TpB\ @O  nz*8!PpBI' 'NDh8pB%$2>12Nd\8!. 2NAdȸ$qBʻ qUR K'2N:b>?sqI\ƕD5ʸtWYB.>_{`+6pXmd,%`K>j>N|$qB >3 w2g8!qB(=> BN9%K)p'gnA89%䔸SNN;9!prA~fXZ "*I7V"4vAꉥ"ZJV-A.Ip!B%Bw#:]nDFt |7b%F݈.Iy7⢱KrnRc$4vIN;MBc4 iStIh쒌W#ҝ wHw~5"i$݈pIw#'ҝ^(P4 i$tIh ipI'HNF;MRߍ;M@w$i$t.4!NЛ6 @kJ@iLP1 l[.4uiLjH$ԥAB&.M7盺4 u;ԥBKt*tiR!!ХBK@+K.c2& t'&cP .B]i×&0McbL2^0mӘZ!/?iL%1@cbLИ&1E%1IhLИ&Icڿ3eLQ:iSicJbLИ&1MczwN1BiTz" tz$0B`LF*S!k7ʐJܚ 6UTS%nN5gw4 I(MԷx5r#4B{?Ş20]TObO&= 4 9q y4iMxgX,M q*7 >9UrwsH$J\ ps*ֆ9s*. ͩ;Ns*4 ͩ7`VxNsTi;@TiS!pvB`NY8ԩӁ±N T;2H6 z" ݩS!pIN;w*y5"ܩSNuʢN@Z)mW$J8i.S%dci <e'4 S!5\.$B\ <qTĝS!I(Ow#(O%fS H@y:ЩBB8(O%ZC 쨻SnO?aӵ3+71$J?UTJOc>NS!OП ?*. TX$Bګ7>B⣛b Rĥ.s j9ui>F.aNSnN7Rr{#9HF!7Bpm|~l)?BcG3#-9 [F݈ˍn ^[jT\[?4F4 э$Kbt#B\ބ$.F7Rm/rbt#;$8! :. SSB F=?#e2B*YJTiiצQeJTWBDUJTWB\bdDU}=|WJ\*q%pc TBD%0DJT(Q!PBDP&#uH8ҵ*0\KZ"IOAzq_nC|$xd&7LβUߖ kjUgIhDc˛i7Y{pl`ohD\9'X#q#@#/X[[+uZ4`Ku]hߺޯX4bjވͺ?"USw`iT/HE0 UѪG6.Zm2#PVl6504i)U!$l38o |9fUG=IDų~ `. r 5&A?xXC.|.Q6D4c4_^3B?6Qm2oC^m°Da 2beSNu b/y.\#pcs[ϛn<>cӺ@{FWh2xD:fۓ\n:7kFƆ#Q.F(}N87O8qK3xc3^3t[br7kOˈfHD&T݌݌=͈zVq vtnnx u51c7.b#vEj3vc\<"v3,}/TpD&9B77܅qTn+tA ` 5G&tnlTw)C7&@ytpE[-;ЍM>M tdO"s3 #ssc'37.)9,*37fnL.dK|fM\#sS u;R7%JnJcggܸ7\87v2}39PI2} p2}3p]@! wႆkV.`*+8}rsA储 xFp{Y7/ bD*W9n&G`fogdoNeIJ7ٛ8;p'pA̽ x- jb2g7s(LLזHTܡ#3åur7Br f.xƈ\N猪 f.X` mF,gnb9*zɃ .ЬW,\Oz7^(W(WQ } ;+?9 Wl9p-Wphk{4QDsNuE4;96Aηb4؁ͩhN`c$s-D21ɜֹ}L@$s:~#c#}ḺŃ9½~ymWȞl_'?M>oJq׫FFRSΡ ?F/Q_-/ 48mf_' [BBcֶ _h[܈ɚ t|L5}_6k<|]eYk}hۤ_~{lCՔkϏZw?pOX<ݮ04OJGvżz}׶/,ӣղ[;``1wWsmk4n:iv6ο:?f2Z`|Zdi8endstream endobj 191 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 326 >> stream xcd`ab`dddw 641U~H3a!O/nn7 }=\19(3=DA#YS\GR17(391O7$#57QOL-Tа())///K-/JQ(,PJ-N-*KMQp+QKMUMB9)槤1000103012)ٽgf|;?̿ܥ;~3>,}} |g|Waq6;7<_s/wt\7Xp9yendstream endobj 192 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 1974 >> stream xUkPSg>I8ca]B~8j]@-DBI[%$o!\Q @uŎv];uv;a!k83|w}}1(H5I%lj*E`S\x.\pZV/Q/Pȑ M=Za,2n_0s4;)xWa:!23>wؚj knMs_Q=|z |ZB-O393o/ u7b_AxtG#VdV\j,yYۤu@rmh6 zxCz _V`gGmts]W*hl2,<wqE[~@fo}#S!dzOkjPBbἣ}iҤ]A cs=zwɎgsWyב-3>O͏+8Oh֗ 1kN;*_cQ|ԓxS [[u$'", IICDW̜ 7Tԕg6}m}(ѩ%\VV^TUd*1z6 lPk3דJ 8VWz>K;-4%XLS}p;ڛ~E,KPe2$v{fo ΠxNwE">y0L&R{hV8mii J+3B1A4Y Y`{37 XP?$uқORϰ̣٧jh79Plr0q,P-ߠALÐOXUBɣ9#r<}+0 U2Tn**O.>\V[XXPc@/\:/P6hevSևL/R!QotA#ttw5{N1le2`ak9>BVy$vA5q^Noe8/v5;\$/O?$h!%B1.F!֊$(<:x .*ۡ&'Ϸ7׼$DgXRQ15kY'4PHA~-@\x9}ad!'6s]MCh$ߦycp)!֙ų]I+'|Ɯ\IA7%mj ,[aHT(G|)F;FX!81ZE)ߤ*0wTuLx _@gԞ AZ -f\wdN% ^ :wt[;}|h,* eiߴ"ݿ`P @Efǟ Ү;Y >s y/^!xh'W2k%_mN0f-X}l[@1ƻ__ny *Xl,J iw{ߌz,vK7QҙۖͪOH8_דӮpr-r =9Htr|@ї=b;xqE<|ɻ. ZfC8endstream endobj 193 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 39 /Predictor 15 >> /Filter /FlateDecode /Height 53 /Subtype /Image /Width 39 /Length 1223 >> stream xV0@7ԥ|+5ҖߓA0>G!y{{{yyL&F5Hԓ- J[ >==e[k/x ]ZWpwwwyy^ROOOM%0.\]]M:Vm0K;!@L)G^\\HEx*W; SCY[[LNX%h fʃl%8Ys DP>!؃ A6'S.Xq p񯠢pN]7aR9wJhVPZs}`Lձd]x^*O oREҵ`Pbw'E,=Sc0Ү`BE *O)gjPP/::0UgSAPL!_THWk S;onDlT07`*A}M %3V 9:0ʬc3X=bP=d=T {jih jTo±)[a,F&w\ Uܤ7<wA,7lUgLGK4zuS(K SU›0;o+y^47nd޸=;ʕZMV6/:n?FD< [ ->;U70Jk|bGRNTk:DlSdg0_B{%YhM$T6u[^O<TmeWy'aendstream endobj 194 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 53 /Predictor 15 >> /Filter /FlateDecode /Height 39 /Subtype /Image /Width 53 /Length 1350 >> stream xŘV#AE%<۔ #$"&!က/--TAWuUooov.?<<ӾNLLЎ 5 k4vh? {+ 8C{{{K A`vjb-L AZP+,M0;>>M%!S>"eKo,L/F 3|lc5DUD [XX ) L?\ZVT%*|www?䛚N("d|t S?J0)XA_da8/Y~d28 bkCv_+%cnnV,n~ /kd@iQ>S1eusYS?ĺ|Z0\oA.+A<<<kqqZ֍ .QAࣃ7!@r|Vamav{{{u@nB6;&*/e $Ƌ];'qсST/M:~p۬!@D<8I_&5|H+/nGo;WWWGkgc~r (*CM^vFߊGVu`> /Filter /FlateDecode /Height 39 /Subtype /Image /Width 53 /Length 1324 >> stream x͘9V#1E)f#v@NY F /u#TeDn:,z(qUU#kNOO憍;ʰyvvvͷ>???lYηPavη6D8'6З؟fc^ ݛ*7||||xx驩)7ߺȂZMA{[}~~fOj+3 | `8,z ܜG>|(quuSht|0,//ONNBv}} Q,/V\^^#ixFE)-l:Z£@ɮ|A$l5XQAÇr'Q+Aavc<9}} Ulu.fa-Ӕ)c2DbcP—8+Sq4AmDá)Y5RR *\>U>5/,7Hk|XO6Õ oIFO`K -|1}U?_ |l 2eǿYw  ,?p‡ZbXVM}؀p9-M|݈qzPO= K||< XDu,vJ  L:NNNİ`uGb2yϕXVk::: M\)8F|O%^i,d|HX(_\2CK{s5+A$=2f3)`M2}?88@?R>`B꫍|F6D[CHzvfRx?~,B9BfAf_{\1R>R?3)S"D> bk1f{k,6{O1ä ?MH~U[/Bѯ'Pj|;;;]H2) |آ`/܍h/Jyu̙TsSnY2>z/d*#okk+#AIKKC_!p+!#Pd.Rf~xU >[||4U53zw766C,ka NlW(V\8 /Ԏeܚ|X4 u.> Mendstream endobj 196 0 obj << /Filter /FlateDecode /Length 3731 >> stream xrGl4N~TYI\rʕT\>HC|HߧL7fKT:ݍ~Jr%_HΏ~;itU;^=?9ORqju("W.׾ޭN^va11okkݰވ^>Pֺ!9R#lONUW0^w BghXNe_NQH}6LӫNXp޹N7BrG[+zMw@gʌA%0uXil4;$t!軋< cZ `Q'^#I7l<*&. gkB` bBY_8gA(L 6WțثDVz6g5rHTO@ : 1DЉZ+@ ȂhYaI tFuċhT@XK3mPw/d­;ueDu2e8^YI +m>pN(MR,+PWҲ{6dB&Y"t;͜%AU T&.xgp [# 'C: iM30?D㸞1)3 ;bYBp#Zx=`]`n i`\zuʖ&L}[ ̑mzN})GVCҌsb I[DNΐ"%$ǵ踯t%+F>{XY*릥P}pn\xbqk Q6JZ?zcXL ,mIf3nsATM]s' 7͹&@IqsTl$#tω( 7'N'/f3']xG568#6>g\[[gAtAF%, hp{, 2p=L$$p'cp*KptֲR!BhJGwQpgF4:kԗCUtF^ݑVKY|nqff}>e}_6Ƌfqfk_7+@Έ~RU Լ2 vͿ/1yXOtSL Qi01s#L%w^xFlh~k?V.8 $)+S!^pIEOAlE1qR9頫0rx(K.wK Iz L.V+@ЊHkzl|t \iOwod=RBH4Y phGrQn s͟e ն\t\d >|3yaݾ#ٳ*%ǬIQGMfTr1ɯKn!*ߎX3\ UbRxYM 1}aX8BS '01TQ<بwnڏ);H02L<18M7@M=:(No'sHzGwtGd3B7ม].;8/2UsEYW▜;6 mXuHoƄ ŴF:`F.p)QWZ\ggU_""yĪCX,O U~+{ ZsYQ~nՅm?Q5>@xC休 S+$ˀJ)o3$ҹD&0!%i!,zA\ /h:ܕ)A*@td8:vAc^_0 |:V$~@¨-ٺE),"%kpp/0|Z{ Qb^Qh/Bag"|y*-He)(PͅE9m<;\XQso dEX8o/bOXJ5/x963 9{\Azⵘ'sđ@Len^=AdΚq<(Cp ?6)LQV}ۤiIysD ^cI +n'݁3` 3.< _9 -ԮP&$0v[OD| &#N>4i;k-vLVˁ !Ȳ9/ikO`\-Ni4<%ԯUuBSn{jpUݯWl—lPE_oI(,ZilI3we;]"%6O)GS@6Ⓢ!ibics!qsC ^vL]v7HöH&8zuwZY(b#!]r.̎@VXwc{?U^oN>,0(.ĺ×gGC9{g*dÞ %y|dž>83G)/UG.#Q4- .e6N=~.#ᶜWL>~,9"|4Rms_3MR/ [ewˏf%B\E`r 5cޅNgys##W; 8>5s{O 3&eleS|:f73eɼ-ֻ28^R^]ՔN y黐Oq49iVG7"$'-e1_SS[Pb-59{Rny k?ywAL}Sw$EY mO#C`0{|{ڽ#[=hoU&"-/ IR(@TKA!sR]PtȞ#em{ixe[=6H@{vֳ$3>ua_Qo)K:i0^ѿendstream endobj 197 0 obj << /Filter /FlateDecode /Length 29430 >> stream xmȑw17t`g>40*`PԒVTFcv<2U~AUύ`Fҟ|f~?> /Ňw{yGox7Wv>^^r=u|_ޏ<_m^hW{uۮ~pٶ]뗆}ޭR[%4_^g޶7bo׹W;5?k[[m+3ݶA_ox\oyxx[/s~k_ ޥ?:n&eum?6_R||6o>f.r߯obృunn_ﰌ|qs~ܶ_v.o˹G޽{d/2_n6ƭ[{W+mi;y}a'>zKTZc_8~H~˧^Quy^(?_UK{U8G=v?_/~{*pmtӾvoξh}_a/e^2v&YP揿5?[)wsvY 2>#x;lɭj(ߎҪ˽mlwݷRNԱR0ux#<}o:Rqm"zVV/hQ߸)7K»Z߫y"ƿm=Oqr)}u?ްYnwgZ=6O0ױnoJ.dtl)|sd 㿲y︰ \W؉?$]G+ZEW۹<ߑ˩ܽs rub78dPw۟\է?}ddw\|+?*)wܿ|%_~ʐn߿.Oy+DRϸ#}lDh{Kw>=}?p:w*"8OK{{_>{/O7f{qO}r7}-T 䟖j-'tZ6cy=ccO2Z]QngovŇiKQ{k)c3u<~_AW~?yxdx_R5{#|xQ-^~?96Rƅ8^7\w~޳Hge ˳HYq\,}ָY$s8~m`s;<Ч|mz}g[xs_zTwhla["V;*g֠sc+;ju\EGO92rޗVǗa_ZG<]^CpH p~drlsǹ*N]d-ԕwV2'r?깒+rp.TVbBe%Wr3Jg_8}cO]}]+2z֭ccO=c!mJ?QI^O䴣t!t/I}\kdDV^+'u{%f;Bvi!cg"\5u;t?I'e|"c[m;IS6JLҭ~O?+~='r=q_ad7ɲQ(+JN/!BPCt;y*m n%;KvIp\`T}%(VI=îhR ŪJMU+VOd\_+ܼM ZT+VBli%gTDPZ%aj%dT'eyM+!(VIXX /WPreqIX\ &Od\ו~%JH6:u-^XTQmf;^*Iݼ OJH&J\H$VBhBP:oAj%[w!݋yTn݉W+%^j`V+^ڮNTW+%^xc/VJZ ARr̫S%e^vJWΛb%ϫ^u^ :%]JVV5J@eL@WIY\KW^PO䰣z!^Yzmo+R,JD ARr̫.%^ É(%c{",JD ARr̫.%^xMkNF)}!vEDfR5J(%^\K(!ﲻ1]NyQk6Q]d5ꉌu-dԨ90&ﲕF i^DŽx/f'gK`5j_ jVR5또k#*A'jKDPF iT8ԭF`(FcQx(mq bTmעA۽yY-dVA,d:ӮvXpew wJN:x~:ɬS )vYrZ-[ؼ+T1G͝ē:jl!s{!N-Zlv缐yw9V]qR-BfZSuj!pl" ژf$H-d)%^2BPBPBf"YXz"Hs]̑@s PV`nn߀WvY22 :t!ݮxZaUl!Ŏ 9ۮCDS$z"L)VxR2j RR9TՃIƤ+TJR FA9T6J}NR)Je˵:J *@R22QQɿmxbxR22r5B.Z*os{/dZiBY̔tRBd^_/ M/TJ0`Qk?m:ȲP)B+/UJV)1gfWJ+%^xRJT2սn+%^Li/VJPa@%}J^Єx_bb0BP/h]O0Yi,PQ"׾y1/;/*!SX,dTWsJLȬTY/T*%^xRn`!s p!^R)J+T&.+9>JR)JuؔVߨ^<=JdVo:ӔX22/˨TJR)b!^L/x}\Prj#>ZuYVJ J~b߷ݪj/˯>1j TGh]VS$Lu^$4IhT'NBS$Lu$4IhT'@S: Mu$4IhT S: Mu$4IhT S: Lu4IhNBS: Mu$4IhNBS}: Mu$4I`NBS: Mu$4$iT'NBS: Mu aT'q SaT': Mu$4IhT': Mu$4IhTN@S: Mu$4IhNBS: Mu$4IhNBS: Lu4AT'NBS: Mu$4AT'NBS: Mu$0h7\ NBS: Mu7z)Lj!0B`X AbJj!nxr%M7w,WBPT S-JL .~:EuzFSS M:5uj$IPS M: 55IPS'RO+GSS+AJ*(UIRR%J4֠BS JBM- H8@SB T pU-Zdj!AW c-z* e-Za-X'N_z;q]-Ztuj!BmR{Kj!B@W']-Ztݳ]ZjB@W ]zev]-ZtuѩG9!¡@W']-Zt:uj!B@W Z5eZj*!BEsꅠV%AJj)2B 'kUS AmmW.ᨭ@['ȣ3@[ m-ĵh$FNm-Zhk!I@[ Q\ Y'@cX `ǟ.[Zlj!B`ǧ ԰B`V ͮ>_-Z`SX'N]:d@_CV NBY-Zdj!Blc{ @V+L T#j.J(Aj>bMWmPtJP<%F*Pʮ<弛r'!(OݺV8$` NB)ťU>|6\$tBઅU W-Z\~W-]pBઅU'W-}NઅUg:Z\uj!pBઅU :]j!pBઅU WZ\j!pBઅU NBW-ZjU Z\q[-Z|u+_=N'2|j!mý}j!B9M5UcWX?T7=jTT'NBS: Mu aT'NBS: Lu4IhTWT'NBS$Lu$4IhT'NBS$Lu$0 `T'0c$Mu$4IhT'NBS$Lu$4IhT'NS Luy}VS: Muj4IhT'NBS: Mu0IhT;4~X%#ZL$P?BXPS-ZU_?T `J#ZV$VAZ%aJ#GV$VAZ%r$QT aJ#ZL$4B`T $0v Z%qSJYLj!(VBPX S-ZLj!(VBPX'b%Zj$`& LuzS-JLj!0BPTi90/RsRU U:Uu$TIPU U: j*!UB@U' UM: UuP NBU: Uu3bRU'PI@U ޹NBU:Tu$TIPUNBU: Uu$TIU [-ZjBPW ]-Zt\ t$B@W g]ZjB@W ]:.CW ]=.+T4tu=_`j!I@W ]-ux{]B@W ]-ZzxZ+!B/ PXcU*Dux !9%jU=JٕOBPPOo';r n: t$tIM9i!pBঅM NB7-nZtG>;-zZt j!8j!'fqNBI$$uJ$I(@R IZ$Hj!B N@K-Z<j!0B`T'S-ZLj!0նϭNBS-M7`T ZLj!Pf,Zj$TաBU AU+AJ,VB#UWJP@(AG%.VU U-GO!@U NBU-G} TPINBU: Uu$PBU'NBU: Uu$TABU'NBUz޹7THUZT4HZ{@$aPB" Tj!PB@UNz VU-ZTj!UNj!PB@U UZTj!PգFݫU-: T+!^<=DU-: Uu1>z@@JOݘZ4uhj%R qMd1I[/_[#/̰voMGWO|x 5js 7pAMش±o92B8#zW±Ub@+Q3srp%C8cv<8oO±q5ο4Dᄍ9xε㘋u`]6ء|IpGo.^1"s*$7@PnF977Ͻٛ97Poi [APk5sG#:m;$}BcU 8q6:mNC8jS Ok㸭"z&7 7X"iܑJsoAP8@>3}iNZ9v\3ycAǞE=DZf`Sŷe5#~EMX0TOqHt e\0"6&oJtaOloXll]i3Jj, u9Wm[f{qui&%4sB5/37&g2J}`o>5rSmifʿ4rSmGnT$xslPkY]˅W+^;ǂӅcEz` 4|'X`z5JuYʽ2ۆV{.he lw6<m`Yvc] HZm}GgTfp–^CȏjGfpԑ \Trm8}sQjT 8Q[#{DNuM$pnEJ@-"TGĨ19V X#8Q"ٷvK-6>bfj@e 퍣LXzjQ6y./C`Qu7H@hg.hXR6B>˚6Q؍x1%1cQg\7{T-foluv=pCKi,i0`Io5\7984kM6h%)V40X`-V48ibEwKf+ObEdp6Xh`# X0V4;Éu|EqqF6J3eIبd[76*yM"aM"nFF{E4e-Iě B%yc~D~b$Dز׾)WIEp1ycCA%|ߘm7Ǜ-Kf-FEL.;m 7Ǹ/uFaă76x-# 76v:ec9zh'^l;?'] P!pn\ e({:ʔ b@:~(T6679L, s7s$ЁשUذ߾tamذunl vso b/T6Hn:eCzeY`-62QL#7݈ Dn;ˣHX`ݺ7،:oKȍ Бx::LFnl8iFڲA?^lmMۚ)m9QJa5W9UּJ1qS}1Pl F#č yfT)x2ģ|X{2pSl 7/k ~阉2N;;*eC]Xv*1U-@;=qQ< ߎJviV)ܝXy vhl6yם\X*ɍe̪X%)+R Ab%* X%)X*I&_IX53mJyr!~QJHzjU[ jx UB./Bnn&aIlċ:˙*!UBϓXw}l*!UV|Jj$VT%@bBuT*!GoK)ej˅f-BP\^̈́R%W3!ϓA~ $^,AOnt'QRg>Z $xokAva)褓Ns#8ԄĊb6aލ'rN vzj@D1W+% 5FRrGD{~3 $$#q-c9fDQȍ"csB=) 2'PVp!#ĪR<9ާ!_ժ'Q Z@D1IE!^j%VJ "qX~1 9厐 $^ZYrjxDQW+C~uR !VA,A=T+!>=!׳ !㣳V1xXjO YQUB׳$V$$UBNdzYxJ0[XB3!(TBPP AJ2 Ռ(nȞDz[ "OBG\XG$^{DQH:B 3(:qgo> Bd( 5rz!gtd92ѭT+9QLR{'I󌢐Bnp2/Y?("#3HKB.I{'H)zD^4&8= T[~.۶{xQyZHE@1I=uSej!9/Ox~ʊ퉜(&=B(=afԊyg~SHǛ\=x#RyPݸ^))͕4o 9=J-(QhxXN $bA~Z&u* S eC(cUX[PBPJI~;BB)N!JH Pf]sL('r=@bsC~syˎ xBfete^OLʦ^^W }uz'5ʦV ۂ3LVQ x*dVDS2YA즐y̡H)"e3kQxPxDQH즐ùeGRE*}'EJIEDA(BoϢF)b!W$i97z~Gԏ~$IXGԏ$IR?~$ Hя$IR?~$IH$c}IR?~$IH$c}IB?~$HHC6EI?5$ԏIP?&~LB1H$ԏIP?&~L c$ԏIP?&~LB$c$ԏIP?&~LBH1 c>~K( =z @1cj!9r @1|#o<7&oT[}F!BP7&o$A}I7 ߘ; 7&oLB$|c$I)1 }c GcQLD'!4讖a8&qLhV9i8 q┄Q#tqw1|!gtDs8 ~0B0/č G!0B`q>0#M(B`٨$$4B`8v(G!uHi8 q| Ɓ|!$4B`8 qr67 }F!B7gKo(1 }F!'uH(Ƒ E8 qLB(QG!0B8&q(GR8&oLݘ1e)@6 A֔B P (JdB;;nooTo"6=B0BvR1=`s)}9/F[H>BCrF 龊G!@6 l(I8/Qd\6 l[Sp!뉪QdF!B @6 ll!]c0 3&flO)(5hF/xf<ϾO(Q4cjF!Ќ4chЌ @3^և"5hF!ۧ¦f͘S3 fh+Q*T(!PIX`C3*qͨI.,ݑc-05lQfTQW(%gЌJB) >fTr$^B) u^5cJ%jF!@3 fLB.!+fؚϋO(QLcF!pB 6 nc1 u׍@7 n)վ @7&n*QtU=4QtF!Ѝc`lQtuF!@7n(˕q(]k*L/TB h vIӨUwJP *:6*Buޖ;dw\54J ARQW)%xRQTRJ $j,7Uc}` T$TͻͤiLxEpF!PB@6^Ȧl#@5ޅCGB5GUcF!BSi.g NѤ#<N׭J3*d=j!8 QW&Lh6(uI+F%Kre4I߼Ż$!B2e^>!6# uW,{"xxMB&}"^P d%:H(^P&xM5H$I(^P&xMB5H$I(^P&xMB$k (^P&yyxM>Ir'I$y$9$}O5I$y$9$}ļI&x'"^P&xMB5H$I(^P&xMB$ku}>7>Irf'I$y$9$}OyI>Ir'I$y$^Cl >LLiI83 }& 13 }&mݯR  J5lDAjа aP& 6 5lj$(U'R%6Ih-5lNbl23INlB;I 6 '~593 '~&$$&~&ɉ9 9dа;MB K6 5lh3S&be j ǎ^6-,@JX:X^ol`۟lÑ6 l:$Iϓ>pgLBs\8$tI`&MBf"a!6 -lZ$aag { { { KB {{2W,lZ aa&MB 6 ,lZIha{MB"6 MlX.*VTZ*6 UlXTIbP&M@*!TIbPŢq$3B& 26 el$I(c97el.c!el$I(cP& B˅SS +2VdlX!B c2Ve,%!cP&MB26 el)ci RƮ>PVBnS[26 elI(cp(cPwM˵R qjR M2t$yΧ`Χ %Jeɍ2v )cP&MB26 e,26 d؎;,dX!I(c@2wX!.c@ M2vez{R6eX!B c@&+2VdX,'.26H$ (cP&=0,el "cKBIT)c@Ǝ@ +26HX!?D&M26H$I(c"26elXDll$ԱOڢcP&MB@b&llV|X9>V|.c mXh8 d =1"\O lJY!B euY1IҎb  ˽--7Z&d[[e&Mn͓ok׸ ;1ȼV` _fDvO=/< =t{ؚy}\'klvfO lp'_j/~+\.A)zwqpDuƏ oQdSO}ݵpXlO*U:yz*zv 9C Vo?vaқϭd>:mSCGgV*K7%_q e(P,N a"G {vlNjwr읯7NAAzGPFLn*QF] |FhKA=C]*_ETYp̣,52b (TdR٪ (U˷ v̰ m[4MvY,&6GkUA2kԪrcTAz@Nw?c^vn"07,r7 ebT,)oV T{ֳʎMGXl* #wSH}nIb6#+WTH*=fAnn/;( uSei(Tl7&7 iL܌Aj; }$nځsJ$nځW$n,w&nBG X87VMiXS.77L܌RTAρƶA!177!#q3PcgK&n'7J$7\Z<7rT@:ux[>El(NfMܜF}YL\Hܜ'7g͵Pdԅ3qsz7쭎[ t؊=$H#]U܄E&NtMj#]3tDhupfJ:l\jf:.6Ad2"]&"5;+L;kDOu^kOudU:#YS6,^T ̞DO-(:/z|M#K@25;:T-=ա3_cl)Sf)t]O VgFlxXڪWwU?mqXڪAi~U~cg@V}4h7Uk&NG[u6c \7PGSRh 5*¦M+fJScvlAlJϦVAPM)ZzeGh޸VT;.iVhkglk") #!^c 6iqFK1^cHkUAf"xzњ=ڪLE_U4VEկ^%5\#)1\3SĊ쩜onhޣ956,ac#:Gh7X~tP55є AUGhRڪ76 `[SND^V}chs7۪۠#ڪۈ+zU?wE[u[Em>UߴU1۪~m%m+W!r}կ}/t7n.Υ zakuw4fgQvtV; Y}gl#:cXW:Wn謎~H#Ef i&lX"`#M7V4V'h1*#ձ-z$0M, Z} 쭾sa[X<4<85hwPb'a DʼnvV>GFInCnm}Cz=!YnvVYt:zYKY=Onjz+ƍQM-X pXd)nl>*(V9@Xgi~A.Z1n ƾ%:o*tHvAc?[;_qq"Oh΀ךG"kίhvYFFrin:9.l%qۘMb۶d?z:~f|Q?Lu֧ss!?|esZkwo.}ײz;0;~p)ʴQ'+k'Vt>+5lPy>ˮM֍gS|]EϪ$vv.='UPH ˃+Bn$c_Xv/ !􈋐+BG\J)PR*ɉWI.~d*!B+p>qUpkz@$:BZ#Nr#1lH 'ّNR*I\ #1Ė%{yc+(h~!OD$7Iz4#CspͯHhlERIn1Bh~Er{:ɹyZͯH'h~Er3x>/ɄC.Bf2_-[ZAI<%^ܞsgOוeJI˱s{L)2%eJ>J0$˔Y2딐kTJ,J'xRJ*!UJVE2m)!mN QJɍ]ԪN1?Wj!d^H0/f,||@|ؽ6r um)@B0HHB`F#sf4 ͨQ!0B`F q3*ݛS&M-V4hA3B EP )*RtPBEЋnzQ!E /ڼ{sjQF,"ZQ!B`E MB+*VTXQ!B܊&VTŠ ew񴢳oXQ!7TI+VTXQYaۡ E\!HCPP!p BC B*>T|P!BCЇ ~C =psDiC@-\R1Gz8 rǢ$16VJK:^ehP `BP&M4^rf %LI(A@.)Ox(A=LJP!(MJ U Ky|TOlZJcT ! B4 (0! B @.\I$I>B|L!#3}@* *T<$4J*&TLP!0B܄& =oo4B`B *&4 MP!0B`B MB*&TL76G,L+!0A„ A*&ޕ=P!(VB܄ڝ`tċUٱvP%^ -44iB4 X)bċ/VJ܄ UŪT%&T+%^J|e0J܄ UJ Lq$LP!0B`BO۝&TLP!0B`B&4&(>}![۷g(E6g34ѹ~>V<å|]W9׳tmqa_=s:C n)=pMv̱=,͆(KHs#o/ pBs`]_rO] u,?W>N`˛Ms\UXm>M5UBM|@^|`bqwj 5} 5}"glͿW\ɖ7#Ǎ3ksE]EHwƟJ3}+ڂr&wFck_jzʫ`Q ˰ta [pE&l\߱TS8Eٱ&vsUrT:\mo>CM|N!^b49l $gv4||۶(3~Y}JM XA 4c[iNRLH-nsL8l,T-"(RtI.:옌-4'nV~VШtoZ|Xyjeeb0lVˏWsh[Sj[V\u.7U=pZU&6TZ|IXE@444ZV/ąEf?F?44*hmhs@Is дmhF9HhJ3ig<U*FKfaд)@z<eu/J5@3^hמE{gŋFi#@3 eĺ99(4'4xV~J Uyw*e{ -鄆+3WSP4X05}IErFk6&"Z"D5SDk80њ3Ƿ(5vhM}h|"ZDlT,ٚ jvw(vn;mk6"Xͱ#XS8m;5i 0Xsp Xsc``͎BnDmneshؚm;l6бfh61 THf<" \ HlG*ƫ*6hޣOXFےl6af5Pp^Sh.v^odk 15l^oIm5pFtu踐^;NbEfܽ $copה<61  m)Ma5;S^g LXL={ T,.6:5K,. ^Z ='Z XM=[ ؊h#V'VSVliXjOjbh5`chGVWak챪IJgE^"68:"?3pc%3' ؼkgB3h{)}+ZpQ'4/)5]j8z|Hg)w3h9D휁M bA_z@(ەb`ƭ<"ب"ب2˞E;f Rlj`PQ 6.+W%,NU (7`Blz9l4*F7J@1 64]5lWzͺ=[C kMRR5p\R5Y?hЖs`xMcD!D1[5֞^;AbDJ TZqJp*QNT5nZL!3g5hPk*RkGj &AO{PsM=co-\r@zXxs:c 3`sr61j$am@;h=D4H2k 2Ŗ̏rA!֨z6kvLBQb mJA+t"ր햹#bRg5f!&[b6tk4mVb jլ8ʫt?a24+fujl'jL<žɗvu!QP׆-i#ޞ"&`.q҈q\c)$+mtQ^ z3NJ ط{q_as:?^t[=Te\`ZܦY>7iHo|{nR; 盬{ m׏t76(4nFt "T!^EaƱt0vc2b 0uan %f AN tM$A5rOs~"4.+,l@̽?W M{v3JLwћf7~$!"!2 QzߡW`I`!aOeA9fta80hsavP3$.L7uoS!6"ЍX)e~"2}ͿC `-Uۢ-X =vg*p >U_C* %\{&uUaa)QQq5ӫ.h9lݜ9M V>°F*~j&>4Xz{QTm&k&įa;.MG]o/P֍3u~nAkc7 N_H2w=>}\`? xuU;#~8V&ު'h#[~[75'6Q5щm&&ZQn"kiz 1K}Y^|6QŪ׊zʌ(ڑ&J%!YTΩ ITcܖ}1V451 `oEdE@lFeD lؤ3iL10UԻXseb[E;`tu?^|)p I0 {l_*x4 2lc30rEiza;ʴX?o{Zm-^J/.zvc}l09v^GZ,e3߱͜Ub0O//]DՕ~ K;`li`fxevJ V/؁=U8 U3W2ًE{ Q.◀Gs.+\h[eXaxm]6Vݹa Q3 .OBDyZE^$T޸{?QWF:A9pM jW5äY^0:{է> N0+AAE2ʑFL߾@zWny81X.rMm%-E\k Rc8}(Nex+ +cW(yfH0}2B7 kFMﰔ ߶|V+gez1q]V^e^y`h[_ηĉaE]]/Wu8?)l=ى-39b1m% !iu| A(۝>߯XQd' ǐ(öeoSzR}{ L2y['> stream xZKs3[fS1+J) oC._).P0lCv.@7W+OwGbuqHUtK#}QϏ're]^yxwk1v#{Zm aui4YBvB.aGzcaBZ%&YBWWS,;m=Q75}5e5U5<%s5կc*3cKK  PdT$;ibqר^W14J̃ÙT,;JJB/9t2!+|I4oW~=3=X«unīfAJPN|egz߫PH>GQI`GV>1ww_?}kN߰~*dB\K_].r>(qV` k3B4w Zlf՞5?w5+aL?e>îJ&W9y$ D \[vkWuK_(fx5xmύx5^ @@Y.bz%xMQm_hy*S¯dgTe$+%&ʁT^JN2TK:k!v &[~mF +~+!T%0tg덊) /mQc4vw0줳u8laqk!J}>J]BߥQU7 1}U~| 1/a:/ <ؽYopVwd F̸ FJ;ü] h/ -= 0lB3\a)t9&魓Sϋ- ]p*WCLPhkpR,N2}qr# ^> * ms{eǺkO1 PA&ѢBH꓏}Mkjhےy`IL5&%ЀȔa3Jc!isRiB: -\G2h`s *TY)0n bMÖ} yEJ^s);-I(Jb^ttݟ+>V}5/sW*oWGySb>L-⮚P gvik3Fc'tb##*mL.mj݈3"xk6o/Q^1z%eU JSOsY !\ ( . kR]()v*G8{ƈ06MC'(tK*_$nֺ=$ yGˌaQ(9ʂge&/Pd)$"0+6~Wh dJ$桩~IiΚĦi,tr0.9PeJݗ5tՓJeS)OyM;L- m$u%KX{MpR*1Դv-A±9+ӜvGF#Kϵ4]*#үMCNH< )Lq H0* EæoUj̀犷4J5 Iʜc =k<;#pnۊ4*Wz1ϐѿ8m%8hqzqE ZڑT~:ڿI5dMnk4 *h8CO{(3PU79Lw ] *f3X\kfA:/iiEpJ4(#1%9ਊE*Aܛ/3=CXi3UEaj7ZVn R$wy T;PVXtX^DqL=ؙ.;im<` i4.aM,whϡ*i_&L/TBtiEJ+_-xxc'*v'U]Gɗ^c#CeI쇢C螥#H調g׸a +P* PS hϽW0c>ہŗe'RI=h㸹'^ Y@lDb0uzLp9C)S)I$2:0c |>&lM"1"/'ksZ;J_#]JoU7p &_P>ɔsxmBAFxa9(Ӑtz7}7]~ĹUk.eT wlEf7$R  '2iK N}+f_ydA1& ͘&x3OB&np%=uD=UCE$1ByLZ \.*ܛPo)UI(kVJeK.Ouy˫6Z䧴oI~?#5PaSGFIH9gGI;MwDmٹoξ\"2 d澚D=`rw ߱ט[֤W fɼfM^?6|y^/߽{& {7R=ǁ],|Ɵ~%qA4;1!7ԿPiϯvRYlӝǸ:=ѿ0endstream endobj 199 0 obj << /Filter /FlateDecode /Length 31696 >> stream x==?ye43EAwIn9v]/4Naܸ_\Ι(/O>?/_?O5~~n__5y G׿]O%U|o}jlߥ35M\h]q)5\GZOܮR~OO}?,:sq]?uSuM#i3h3?ߍ9w>s>?sĘun9?MB`L$\C#Š+C{̭7*斔Q't_+y[MvҁI)?W^*VGm y{;>WgS3' o=097JEǿ{]0 abHxO+sA8+Fys̅fZcXk~uX 0 )p\Xc ɑF[{s՟R|ߍ=s~^\3m>A)!,aa阖.ʁ/kI(k! "]Gp<X:0”UPSa"9leJxCshI|pw K+.136:񁥁L_O#̯d~K03g"lO7wW&^2R!-!53̧mo(7r<|A4-l拨ͷB㬂09|4edzR!U0) 15O"eNpm*1 l_SHqu3n#x>s2rcX.N =pwjs CafKq~B*_0Wﲍ7| w1 1`b~{7>O^)մ;!~=X_|]B`SRJȵl+# yo4*tZu%4^oaU|uv]S> G/OX*GlW5z vthy4^u [cn$,LsDR{M?/$c0#ŠH+-<nʸ-n~_ޜ.6gbnsS$$2WA[lQp/Q5.{9||\{{z1Y!aL?]K1;"9leJxCNP'9$m:{ЈdC{΢dKCk`jdBJ?^9%=xzx@P wY1x!K0m@0y?{<}4R7܏{yuB߻މ7,Ƌ$e10m!l~aeHxs+$͟Est_܃gAOa.}/haxbxkn7d@2_@hmN 9?vv4܉"qL渗pÂҴaK gw: sg1ZD$ 3 |@tq\dϵ|0}οk8~eBZ!  68ƿx?xXVk2#G xT6vz ( |RxPv | mCpVfLon8͕0(sŻ<<Ұc{/K,a\rPLtzK+GXG9%e%1We{ҧ0 I9_7?gS 83,9 ,'.M/ƺ0wYq̓Qr BBb?1)䰄]0FV<;sj~f6/y'Л\AnBz /*G^|`1QV-)#\܅8Ps-5]B`S𿗀V,\mDp^1,6'߆er6$#9/g.g?2x X@@i ٚ>LaKsgZ3&a.xzס)8ݫV|LsrnS>M~G!n,a #, )ݘk _߿eJUŰ6zOt_c&.!t|rcƳ.I@cz)"9leJxCs; ]#l% ;g!Oi r "O~.ڒ 2K!d@2ؾG,} r0qQnF){;"0Ɵ{ȋr q#Tė}2\3uaF 3 YcV}nao˔鞜:5&8EDRB`p")ӻn*% ob!aEp!==OQߍr? g=1̕YoBR%a.ȲI ) sg\?:&U~"<\s.߇Io_t\&a*WuQ6$ sq!ZV#$WfvlL4:IUg( $Lw;n*]B`頓SJtsc+#<07$qxS,n#H>$#^wf7+ݏ?EmXg@Rq2M`I,7p!aEp!=|QIIA'f ~6URs3{%!upDPdæzwWZnI3 ? 5T, g0-ڍhl{O %7R~pxӄc ! SkTā/w7xϯBaCraޒKBC;E9n|-e0[i%ƛ+).||׭G<slx([[KƠlSWZi$vWF?v(/˦,ŽWE=;S-qhmJX볩0ِ aǿy s`ae3b6> Q0xo(L(WY;S À`=e?_w+2(2 /L\T֘U&%V]BлQhؒ ٲ"8nKxCsC=ϣS&~w7]xS3Ws瘋ݗ:I \/aيH-<(bCCWNTUWmQ/vjQ)6³9]k 8. _?u~Ω<]34aJIv0GU-T⻘kRȷ#چ|`Zl 4sJc~ROAyK1+Ƃ;T$1\i(a\zOy~BhB2Fp7&t1sweVqIM}b><0?ĭK>!^ٯoDmrVϡQ *#=1>ȇq|_*(8;H c~W2"9l xBnͪqE5pRO>P VLc]cNԊ{)|& T`DPPS*K0(â3=n<Љ/YN C+cJ Oz6 ʇlyM0?=ig!!lL.XO-(k{16UQ=7`m!e:(DEbw<œPo<8pKGr2$\a+# yhr`FH ~ Rc&0\ئoKToRBYˑ:V$L yè7~H\?.:&\qG;a:6R|2tFxC'pk /ƿ׫kX FCqBFtM).!tн KAg}ƈ"8nKx_3 85ii(Nb'4pKF]c|!* {`Yͯ\9Xe}`RDfYi+a8Cqu! }R됗@޻ a##l YhfN,syfJ0+O9vGMrNSӬk&f rOJYߍWDk4Zn-1}x&M )KwVGXŢpTN/{SLKq$\baڣ5>8,)!qQ|Q:RK´:1"2$%9M<̟(|vcA '>X 0\ ㄀)aEj01$'!/Kzbb8XKbF?8-KO!@04p)a&fb'XauHxBSTE0ݗhR'˨)GpSc86W9vp`K,a $rX]0-[aeHxCΓF0*D')4st˧m pw iF_<(cyQ[B@c~|/i) 4gkaz!8h xρ/Q N:$ŕj|jo.|}h2fOXrŚCBb0R-tҊXvKŸy`0suge{G, Š|&8.S@@i.)HM1]i%gq*hzrQ3]L\/;RFČ ֏]B`ϔ'K|ǮCE[aeHxC׵z2nq+y4Wrς)>%;RO k7uaeHxC֜g6ߍ(0c=tujML燙M\a.t}x<-Tv+%{vK'r3$c0@V$GXF),%]8yz#o#1HԪ19KGR^K!a~ϳ橊0GZi :lsKd.Ac,oGɔX:(8L `qTގ/# yW pkEmsva*{#c+AGߔz92f K0}[aeHxD:EV2)8mJ+̣!OKu)!t8L%}6C {ߓĆ*d(` :~y0 [yaܼG)!ђ0}tOȼFj 4ksqc;vhڊ-Jg$u; sg[Nna`E=S:q{l|0%ƣP` 9dKxMɱFxoE_B3s%3ϟЩlB xw )"Wu"í 2!w:ߍ+XP)y::0>$ǩFJmR:%AґmZaeHxCs{R֧/)tttrRb,Ř/s 0!LD096 teCpgھ+(]O FN-I'|r Kpp>Xyh Mr9N*VAy=0LGq51܁rpl$[OMA12N-VD#"H;$BVLWw^CO4scZd% puE))B74c{ Vw˩~zS9Bhӳ=%(bȓH$vQt :uJbwbr8Nm;*I@Zt3{JV$L y8ѭ:Š7dLa Q`q]l~jM( a/W # )ȋ*C 1(_ԁ QO 7gޙ]PJ,tr0ŸY:R.+#<8mrEMevR|^o.G9<0R7OeIR;O?۸ $yqƮj/y҃w5(5`SߍRXQT=Vt;T%_[QmVȧz7X1?Yi%5F;?&wb{Ea7b:$?qyFcpgxOpY ׮Ѥ{0 tv>B {ѻ~2_Xrt(E 2-xPɾ-S'kƁmI|m~ )ӽ]:/+# yhns5Tޢ(؈A:-ƙ1^Ih&!tp)a%A˲"8ʐ 4H;9-)"Փ{t]P<%9$NMiH2c|"ǓeouE8xcY{6]-J勰!)eHMx;$zbF#9ް8/5`2 ż8- XVbEeR%gqjaq KZ@bSO׎-%K#!l?F{>’rFFFgbmha{Nh ҁA_\ ):1"2$݊1`qMCt]h<ި>9 c|Kkmlť^4!@@b~< 4{p^>Mݼ8~!aaw\Ηx#!10GZi UX-Qx|Ӛ[{{nG8:ՄqNDpl*95igƞQ9S.=ns ĺm.K*=>$$vƢ :KIWiejH+-<`WX=o0WLm ]ꕘۋ,vrH0 ʁTJ1}a"9j xMBkPK=RNCw 8&q+aR%ǣ)!t`)H8a Hca+S{>rEyNE_Q)ovuwkn}hG%9>7/d\%T0+u #!l Y藆.:ZBh݁· y_D$z6 M·ia=59Vehr2u[*skw* 6tyV,sX:+#3F#]0FV<~̗&B Qk )*(]󭗔9#m,6XxZ&GmYxf̿g;\Ōm<5C.#T2~z{w1|FL}~GK0# 8𚂞лUB|0-V/ zcx`' 18b~=̋/9%xtΠ|j]tc_Fh*#ןq9',TNk.=l\}$PP#)[(OȨBߘBƹM@BW. V9Zї蛾,0u4W]q[;]f$Q5 T+bt@VPk7 e͑YŸu ؈`袇ExoCwq^r8)URh!!\PN\Nl3_paEp!=-Ip:OI b!hNTդۘAʖɁ&K@BiSxhǝt-4QۭybFƛCnzanOXgS'حEK6Kˊ+C{vSfFV$}zE# X%LgH [j.öc{lJS_Sw0[awHxs8 Sk@=)?O^58TߐQ9%$%iH-֑"8ʐ`P./]nARۅ513(i58wcSn^%xR!~c{:x0=l®} &'Ʃp(68PUKH|MRqI@禂'c{ZE]mS(LnD+)9ڦu X:1"2$(XEEY/UJ<Ҭ;31?Wlс%QS.'}_t:R?bH4>JcB+fQ؅7v!^y_w) {@-J8+Ug##l YhhLߝª/8#0Q?ъ ͢ct~JNQ/ VmΣدEVvA7A8Sێ} ƆP *mtn5V%)]e{xvM]9Vr¥+AP^(m`4iN|31*ir ʩ<ޝՙQpHI?Z^> v~d7$Ҙ$4gda# y(~ " 6 Z@,MSع/Lω$$\<[\^Z: +̑VZŸy8@eߝt:Z.*KrqKdrtK oFRN 꿲tDeEp!=-"7Q~(+ք#b"N.T&ýb(.۲པ(/$\ A a\} Ɔ Dt3.{(EM% uMH+# y5ۅ z_*IACUv}!!t|jp|-+̑VZŸy虼љ}5E_>9~t;jzT7 v>8'p$&e;ђ-w|mEpH xOBJ)az.H*(@l( F03Lקl %"Ts8.;x|Az6 l_ٯ8\,WFkᇡ .Wbyq4sܺ=%[O )ЁD\|l)-mIܫ3we%iMq 8|x`TMBTSBUL-uV<\H1%%Yyd&&H;qC9MZHx9Fttjn]l4Zs/ ߧ멕ɑxcAP\xY2W5y iX%q֕)M06"8H xBkaU"47utFh7xPpMXNMJ)!t|tI@f4VGXx7Ѱ[WY_RS[쨁LԊ|,%lp#Xc jtD4"F 3 =}%4e sd/<,rq$>\$\쩸tV< S_@(^Kx3*AV c5G)d~! `#+)P]*j^ӈH-= 8:;;m|W+k'vĻw3?#elHgʢs`]t&bU6,v%kǒtfxBObBMgUk \xn6RpeBpіNN̟, ѣ,L1t!v, \MTiagCXsVu="ʸWBJWB5X0 uc0Z2t6Lـ`}1e :ԉ]QݢR-œJ2;y!Sؓa(3&qАP׏IEueC0!= 'P G&- 4N·vF-̮sr8BI4{aي+C{틆ڣ.Ňx8(?h7{\v?KB 00+%T'i9ݒgoa~L v=y:A:m$^daApyGI珯U'I">U#=ʤ>*ƀm߄N: {ކ OL ̅kq\i~(-($עU;$`%|6 ;GXЋ]VWu~bRnALmnmv=ǘpպ%J ܼ%dRqF~agbqw_qMp<\3 7,R#]A$ 0 #VZŸydqXIpQR:0#U&e"KkQASBenFC޳q !tqf"8ʐ^e8-]ڿe1J|O ύ=#[e;0R6 `!,9v&w ͽmG(e<8P`H,\ŃR{ۄaFlEpFe'ǂo7CoǽP smt+h~D!: !tK Wc{QY⅖{cѩeb%VX8tƳ$.BKʡQH@0[aeHxQE8*p\uf֍LXj`xX %&L{ns6 :?v/5!`t# ș*!NH ~lS}tv)+ sR iƿwN>ۍRr%~0gt xb R`R?۬2[[;nydFq|L%@IH,Ln18.$2:CVGXi |WRnm]mL18Fj-$J{Iקײ"8nKx F>AtG$I)N =:'=N0۟܀Xy@]$GQ5-`du9m]R8ͻkpZv]E3AxI #Զ,%4RG-XZaeHxհ>S*`&3\#w7jqBlK r}RkYi%h*x(ƞ 8T@&Rb+ A1]8-GQAl4ZsRkN2? t'>>mvXa/ټmq45H )z8|V6a+# yj>lYb*/zXDw%+ԍY1p >x{qq| a`xONsҏ&ja #r=:qVb:48x.FWx[Y]YG'jUEu@bѳIH\R% n:?_iEr!=;V h-l,ҵ_ÿ0č6> ~rjbZ՗ ~3g$U7Eȗxw&ѷG7=o݃) z ¥q p (oگPrb|a_܈&a^ m_\Isq%I9$|^:sR28ʐ𞇶+U\u,8X 'օ|Y|.X.\ߖKp}!a3X)w&_5Ԥ^Lh  =zˣCMqr4nI3C0)"8ldxM"÷ $rwDO ?jwvlXlBQK?{;Jweg}1e_/A)|0Mvj3f׋z,\4W6 m&%%H^:1V$GXp_pQз*s?o^]˭U_.L Q? ǩ_2X߻$gqFQZaeHxT~OSPN.ibų ]O~Zq]B`SQݗ {ߓp!0Ϣ84(Yy<( ne0WQSes1&W_y-憄NѾtqžV$fžBvewƴ%!627lQ}u _转2$vɻnHnrl( 9j xMSMwwZRޙ-Pw vTvq7OH,!_)].aJ+c- !ʢC'EP:u>Qต!J㧤̟^)[*?CXsp[7 QBYRSzgWXEHefo'ktYxJ,vr9%Ћza̘H2$;A')^ė/N\yX5LG"tMKBtӰV<~ %igc\PݨspZou[N3$4 0B[BեC6,?nfh&\C~vvBS g,U#3I=B{02=J}x+`xyc@+۟ Mӈ.sr,,Qp Ygđ}4,ۘ޳p{Ilw#b}(\U6 ߻ZLsXYnһ B7T]TǙIA YJ{jXcsci>>4|6JfN3aB0hO2DuR |&y0Stsrܺ9%[G]g,!X15YawHxCq>ߝKݧˑgr?ÙFJ<jǝq-V^ju P]ȷ]w=P`r4fԤCi|%AW˗w+#L Ih 0wbgH|.օ?:ĜءڲJ ,3)sIy|Jj :1"0GZi aQtߤc>X/B`%Șn1_H@P'P,I?_6b1w> ]=ڑ$pYuZJyuʎ`b7pp!_a@0[4;<\w;u2u*) ]15<0{Oüߡ&5?;'E͔CTgb]`. qAuEOJ!0aq!= ':rkwFGa\6-b)!q6Az]_vj;GXЪ{](7-n)<a#8OcIJLR6SkacHx =wڠ$QB,7ؼ(V8_y΍إŻ\H V1r)m_SLȩֳ{Vk6p94t/= % GDY1,槬K<`w/a@0ؾ_dp ҭ#S/7aq ^crN6e|c`6OP iK1Oc- p<>|UXCscNK<>atDN .aMwaB0B.d.IQ#b`&MB\. No*?_=?ЪQI򜏆4R!/U ~] ,E)*I3֗# &$\Հ%߿;G;Vܱ!ˀyEF;~c W%&R3l`DpZaaHxMAs$D3)ko:f_GUe@JH\\]C%M#tYi%_Ώî|0)_V$W||AMaKܣH)$T:Z4L+#<63o6}^_6t];UtKXn3)~;V<\rR/\|. ĝ*u+70KB``@!(. C=9nKxyTC(t|He \v.U(cc ܟ"F| 1(1ciY֭osrhe\[K۩\x}06-eRoN\0.ߙ]~xKt_còN%X~n藁wcA=.m6e>)!p:I9oC©iEp!=&w#Kt}6|l?YX>|"'pGYkH-5)J?]~|kdHtF4<ݔc} I]q)uXrGWۂˈ(?}k^w K,AI0wm!ZVGXpWA: ŦЋ^8;%RՁ+sS@`i|-JA L|؆`15'7w JNǒ1ֱpfQqԍQmIJ,{ԗor9p2¥IY˜+ѴJԮ4s<`xj,g4H+# yx5>"91)8gs`NHf9p$$>2?,st, caJ+# !cG;SYėnޗQ 71[an+Ԁ39p. Tpc PZqJŸ4"E/2gO04]7𡬋ǧ(2"ƻlɧRx0|`S{dU{xIcV"劝7蔐Gø$w SG+ӊ+C{ng|4|aή;ov:/ a;mߣSOIhy7ez9Na6`wCQKܕNJ-x$ &ˋ!r 5\Ȳ?_I%k 񆟯ԟ 45Fov;裸EUe@y늅 s^C?.hQ Wg{`ѥ@KM!} wx}U"xi'|-{/]̓f^ۀM.ْ,*uɱsk*8 W)6 \Ul&{k ٍ6(`G:L`ټ: TQ74m%%:걇5&$CXsp6{IA8_3sl?Kj5с%[]R KOj!Ao}8kEx9U KA%o q"$$wݤ+g5~iEp!=ooPSiӯ+4 !𒐸D6('W!A}ao# yh DƄtʴ1uU ?*;#ע Ry;(A&\mKm醝6}ӅYƯm RٺfIQ}Ӳ"8ʐOPXdo>?)zlX]հj9M Wc7k:=BjI9;v13kcAupv {E0K-BjiEpݖG2#A;R{I9FEcW#7u&!t0aʡ+,-T_:;0v2$硧DͣQ6UѽчbU R'1(qw.JQ 8_KE`(>} ޳л o=vOMJSnŋpuVw}Q9_m縇c!:9. SsNSGfɑv[{Nx5.5oVe(]/,e0ߺMwЎP,,xPceCrE (VRp+{UdM]W]wCnlBI)&MοY%<>wMS@nhD<M\snG]_,{җ:AM2$硃eu{қo>])y[x'8o %" a Cm|<|M];늒k/_tG-{|O ( /z?{YaeHxá<~:):O{#} tgW6XBÙIAL琀Co2[aeHx 5)ڳg9ygŹ= LQpxn>I 0m?_iB3WKCQ|LWuʺkbvw3G?Bc fOp \*1F$G޳p~מx݊?(-Kxs r܌i饜|KBC7X, |hn2$灹o_ ᘹvfaRpk=gބ_k?O'* Ϸ?~?}sCԣww7 ?\>Wg Wij_p-|w^-t6s.4,x`E(,ceA|r0.\kB5|\4B e.d%e9JK3|O~Keڋ2#((~ڠH#3G]SKBEAX{ cS!aDpgda=\D )t4O9ɡ_X:0"(. .7ˊ+C{`")]]EВg ?yB.8\Xb`)ڝ.xQ6n[P?4}$,51y~˽w(P*:s r8%a l:#)s7\p3VKOaV2̏%KA`\g/a@0_=wg,>)7~GݍK΢c$y H|iQ*, ~!1g/ᦚ8mAªK x]&J,:9p H( ;G㒿koA2k_ae3rt';:X)0_a.V-KBG7ʁ Β0W7lEpݖ𞇾Cu-6 v+,.0>vr3$$>tT(p]^:]VGXp:}))܁LL ^#|ۢUX/(s_Jn:爰"8nK3~oh P-`g肠#UoCx~h>vK`8{I|F`QxUPHaCiH-=lJ$fYs]`n/s )) ߄pM&#, r\<͘{a,uca~ X=Mwp,$ X/s-_:c?^Xr. n .hE W1elD9\P8t^;seCp“ʎrجrQNޛTp}bVr'vul1cX:0"($4V/VGX^ҍn&݈s <7{Oc?BF(ճ)piFt[R9%>Sd`+b^xX.^8揤KG:R!4C1F؊䰕)=EV3tA#h"9c7He*z-OH:Mk4HaBp}! [yQteKN]Rx\I2b]B`S6+$.m!2$59a%$ Z-(zڐUXuo.v'kpG ޤrur9L/N7qYFApr\Թ2'. 6E) [tnjr fH -M>~l|n67;s@٪ ) anaq7 kS*ێ. mGk,V<FQ&`{nD}LP{1~ԚG{NxIHvk.<zsy_+-;9w4jrx+_ o\pH7fH$t=kz`- E0BMgj0j:jH욲!Z/3Ȅ8U-kT>L!4-33 ֢vr$"@l|vT>=8}"$!Q2rNѢqNjl5 d~%e!e`Zalnj*5N͘6t! QR)shDwҪds5VkI$AusArhwhHll%7FR շ0, <1KRY5kЫ D ;򲅡evlh$!XY`jJP6CǫEoV8?ViMD9+A8"آϥ8f8Z= XY`.C(!aއYO0E[!\KY,}ɜ; }ZeRd~s(ߨ{>cUd`a- K0CcYVݴW#t^Дͩ ;fd^>Xj NtCA0, <5.VYL,n,Ƹx[Y~ +WQB~yZz `Ɵtf FgN#TK'D8gI&6z =[Q:潂gge KCw8H`5 [|#2~>eؐXpDtA%s4RXz28*(xdxѱqħH~Q2R54!~s=oWXDGlqekV>d? l.VoR3pQǻ3sWZM *~%Gˁ:-CwEը}}HEba- K0CTu8VKKj)8*6Ț<" Gpf B/KɬH߇P,avsB58\8K0 2K.~x|h@TkѴ!p&G\O kaXyv9@~g7/p3.n4x9Bapar~kdzH|o b ]`5OJ {>°48lb /N|d[FY(D{ @ P+a\t.XyP-H-!(Q^NZk!^^4]YxC@в^aiq^UdXq~noqpi\^?c[KŚ-8 ] hmϊ{]P!hFQ%*g}27IB-zyьج/"py\Z>^u,z 㐱-Y^sxPg 7 D> 72aXXBǡ{FRTlkpS(WM̂V/yޢr6հ:k֢cQh:&fr阴,I.!ccKjZ>GSF 9; XY8^5BXc>oaXyrrz|$<?R (pX x 84 _c* țդ#M2ބQVJp-2=+Y$A劾):֠cQH„ϳ=Hh=p@\2%u Hzy%]Mn={G`- G0B%QHoi .WIͧ-QV9[Q-tr,}pB7|߫.ޢ-Q=K4} Dg'oDT^I!aYB/87o2 :<]߬ER!_jkXJbm-m8a7cKnzx@5Oص s1_XR'xFfcG[$-a;{=@sdnne[KDI4ư!{MV=&$fw+"`Ձ! P\͘ Қ74r #hZ Y-L*UnLY<9OXGA,Y(Fdz]|&؍Y47wn OlGsV'2WoKK x 8נ WvAK8U=?"܃`ެ'ƞD xH@ɠ|ˠ 3rȟʇo2JtGrC&Eh&FeYHABktYdP)NʯIWo?_okd-)ߏ yXmD,G_a|n|0}lOg~:]\} 0Ko`6ZSL*Om~돡J4&ÜJf=+ OceJ3BB\\ӆ`yGO2ki d. y^ 3Ů}]B8q&xGbc9->gf;]sܐhp*مsZl!Z^_W(0$luӘNdu;*%xw-S[Ճ/,~HLd9x*Ju S*1yE b=GbRBn\b1v{p t ND$A$\񁧆_%ňV|i!OGg L~F9lreO#N\N#hMX Cl-P^[+>HFߪ)v6IYo9mZF>m.ED6w~c`F1ybZEģGd6=z׉aȩ8ƢꖲPL{-g#ȩ 'Bob6ydB2/O6'$fЩK;f$:q}@ej[`m\ ɊǠa٭̷^ڒ*ܢ薢C3 R:Y$}:ixHlI_ "`0uKKU,KuveѻI%uN sgxfnljX63#uc߿$SC4,KY'6GϜ;.P1泲8&Dz86u]fe# BR٤eV^*,6Rv"qE%IEԑ YySŕ.qD*^{ScTJXN(i'-j^\#XV`5d1kLN|J~Pbe[kl{@Y_i+XVvy@$'LݽM p̆m"Dq򠎿IZאPgyJ>c\۷w;A(7 cp[!?SKVl1S3Jv%=;MlxqpE$ o!P'cPV/:(p.έCw,C;?~DGdt#!a*w7wn='Xd+yxX6c}'/ s;Q9-:Fsa5Ov5bx] a$,I} 厣;%n|F;kEαro7Øyq8HX!.]> rreXM{ <[`09Qc  S}WKDv~T鐔I1dw_^BG/~ʠj]6E$r2L%d%6g+ugl.jv; Z I$(@S & : 5xȸ|= MNS{)d9c(0JH> eYwBd" Ԇٺju+έn˝`vɖavދ {0{4.@>d PZIJ FA~))8;>~VٖTLlށYɷ ~!7XŽ_m6;%< Gĩ'] zOzmJno 8÷ Ie47*CtYCdQ OiӲDuvp'GAC "5oT^p ϋbZױiL3ݴx\g +658Ө5fޠc]u 9jI9v+Ps} "|r*Fp z>V$].\U9]F] ar%1I7n.SF8^NȋXc{M{D$%!wɶ&:=n Gy?g}Vr(A~7>8>ot/ YcfLcslC]P@e[eD3m ޟqMy^tU۟ʸn' L;!·/i|~in?Ϸv|#7jOwx7>w{ ~QjVy: ,4ם?9'rs9pE١%ώ!q͆$`1m̮!lo$w%Z 0endstream endobj 200 0 obj << /Filter /FlateDecode /Length 3502 >> stream x[ndnۑa^P?־:D@%ԐH${fHm??`cN8skyfaj Tխ[nEy' W><[<_X熨;/zЮ Iqwc`eݕ/Ϻ{LԱ;|KN0;Ul_<=hy7ns ZHYݟwu6Z >q>tou@} .=kUbGNtJA P!v0Mݻ8x߽8vQfq^'م;.z^?}x~a˳2/.:ou?/_y姯v}W?Ϳo>XH`xYbryꙥ b2.)؂ fC,h 7, - I n@YAFYIqe 0qё ȏ$|GZQ [>X(??TFn?ߒZ[o]ZA[AA[zhl!WB!sA)|OqP4MjV*EgREҢ5E;b&#+X>ZG""1Iv~>FW&zΰ^.CK |6ICr jHrR!CIaSsT4C1`rm0nhx GnH ~$vH=Iwx6F$!;Cb--Ҟ]&2*"(15O.h=CR>6HR>݃ZR-NfI zfDT9QmD͈v}>fD 6+ LtT;Gȵ(iP KQEҢ"Z F;?AEҠ <4I*a(v}|%dL@wdt0n5fwWcllXzFNc\[!PcƸ6c|BD* J8(o tڿ 5 F1)n/܋l5[ژ;Cw.uˡqQN!8*wxUҠmX%-*\M,iPWA]iGŦNW${JmyEEh/yVy_mB49dVI(=eA R=@EҠ ŴzXz/χ8\?0}~.=:}^ ]p;oBQNU}GV~l :R>6!c{WĤKt&no܋!V_܏3-MX(-25}.7b*iP^e4!">Nw d!.IQC>M7dh4t<0?i.&!m_㣼;7CLtm!B7h^.MT\y?$@2ӂF]G0&w| \/2N.v|&$#G6X|~g@{J[(ٯJHCtǓv73Ri2Ku}׵q,YNLҸ zO#GuYk?g!QÖ́Y( \Qqrgiəյkz>'܉~];m{FlNQ(پ2Vq%q&зߧm!lۆ:K\p~j8JaDq F@hRTߖUvU,?$zqB*kV3 iq2'M+)ThlCUڅ5&!Kx})D{g^DS-FA?Kn)w*|j!͹l~e{uhk^0r\[F@ nFFqV1յUTTӸUXez}*b$ߊqZ!ZC:״Bi i%['l.4|uڤeΟ=i`O%.ZHH϶*x0}͘},D7t[rƻf..+M?ڥ#Kendstream endobj 201 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 84 /Predictor 15 >> /Filter /FlateDecode /Height 84 /Subtype /Image /Width 84 /Length 3361 >> stream x\ y'((D"hTJ4*DP)h$QH("H4*?w;ws{ߕSwߝ{s>s_~]__h۵,//徭N=$۞d4 êqLmij[nݲe֩q'YZۦ멵Im59akg۶mK-:h5OHd?$(1DtLc?E0CQ&L8ӱB;ܶYhig1x18]ӦPbG=/N|"Ca/'O_|am E𫝁vO ┰hy|<h9scΙd6Ȟ#$9ہaOB&1C&O%#|;J=38aqʘ]'! r?yg'é1C gtBn'Ʌ] $!>|`]5?<} C2rwޅ ȞlX$<% vW޾}Um$QᔙBNMrɧJ?@o޼)0/;L;C9ͺ既ygpA E'ׯ9Qx xysv(Jt3ՔĿ@a;tA$ X긶s 7z * ߿?-ask^L;T7"19&rwMX4be?Jn{޿se\qw|-G$-`z3>L{#v-p/s)7˴R#_{S͛7A ZwƂw0L\[E1]~6k8us=G]HV <9|k׮]*`|-n4K'Y?vn漆V5< xGիiܩ-xIgWZ8LSw9g p\-$ 'W85{; .]4Lvl||Ӟ?UGJ9J/\0^(Q >w>08v~sU0XPAC9X^˜'.px9Uny&gV) qOxS?\ Z\Iɟ6~49- ճ%9z/jMr|'OÀ߽ .oWk`׹b!kC/H+W8qB3cQe0Y3?i? ۳*+9 S@ye&=z͓ U0r%y4|/{3?gH;tÇ{)K:rMg pAe ǟfV|$?6[DUWkρ |ݭU[mM ,<#/@ڱ՛,e ݻWԒ/. n,9l"0WY 8 ~:ݻwvLżh~$Wx\';y9;w,/.6o ^gڛL'#1 &Gر9aTg=U4&3|m߾r.Z,΁,5C1s\5V}/f92*.2r௭-D gx\3c|<=V=|d[IsI_AΡ^YUSTs s9]v9r^p(payޢI^]W=a;g\_E+d5ϴ\sBGL֭h'D!~)iBs({ Wҟ\⇅%3_G)w,y-;9伕;lmes.x}A:F5)_}dU3h\g9^sBS#Gƶ'C y^o,G;Ns\;ve:<'j)ZsI>sɺ|gڅŬ.{r {Ҽ[y_:uI]'~g>0 ?v0#|g^a4/^t]}-3S}Aacezw䛂yrF=}Utav]|:̏9/L1l \Acޜ;sF4bީ^<Օ76}˹fQq=ۅjp{&{o߾n;?{[y>-E6W۔+Ed=\ʳtnCUd{Eӷ\s]cÇ=)kP-CB~Y]"̻GdaϘ)E >W s^nmf ˙3/^X?QϏʳԫc3bHo h26T~h57f;ڄB͐6dpΓy^ 7 0_^[;-es7;ss.hݢg؛SF0im&' o߾qKˠv/|`=ss~&߿KK+'َ& E{jӟcp[F㟃Z%)Ԗ BgjE-Άyރ3Ä7ϟ?=yk?+g{01/ơ|M_y!Wb~ 0s [y1׿$yO%Yeø= "k*sFayo]Z9\C$D BC-gl7ߎU.'|N嶢>>!vyendstream endobj 202 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 84 /Predictor 15 >> /Filter /FlateDecode /Height 84 /Subtype /Image /Width 84 /Length 3742 >> stream x=ݽKkkV,DH1U* #*v$UHcB,4B`Bݏ잝3?0w|[;<<<:::wN:^p?0Zk.띬Vry ''' HaTN\?ƚZJb`Nblv_r%a]E*TA`WqWݲ_dM $ ́%3e>-d-73B;^1/m/01 =7x#LVDs}J[|3 y_*Bh57|S8QR` yb7x#Ykhcy뭷ȳb]HJJu?24b[؋'DG_~mR'` $N,6,B xFG7\^ d;CAAՑ0k)8OuNY >e> F~yP s>oF{,ٴQE`n汐uEHeUիl8#;ɽ 6^#4M1~G3*qʽIR '/ȋ|"q.'ׯ_9@2܌NEi'IƘ'OTm=t3B<4ܳ=^NaJ67O>EKy"4xz{ S* /' C;s~pϬP~F5mM䢽?ZJd^-ɭ!*Sώ5 V4W,X$69U@oWLwkj |嗹DW3OTNanSru#zܗGI[W_}͘gdD8gݫې3ETPkuvuHrۭ#f u D;ʊ@';UЃa^!ϴ5\ ;9o0)f5@b,g+nơE?tX1[/ *lG-C 'ڕĶj WޔR_4go<\ΒNy.b+ga: oݺ% eF-%xҒ[[fNDNYܼyŸ|{xi>OaLoqM֭\_Mth >ZXZ7F {FAA|TFSܸqc UkgakڐD~КSe?Spyd~:Gb1p {$xyY.%sN]qܶklrסORg3\-o7lHbI,2bC3ize >'^Otp2뾬)Cr||Ϡ=K3&~ֹ?k0a_V2&xa>މU{LL*KSL,.3OW7^`t;j~_84x:<2Ϝ˺} |,f߷"d:/h'a>ތK]YG}DÖ+bmg~&4a~sҾƘgyLu^nQOM,)ݔ~quj!N˄0rř꛽^ey\۷oi1u![/^b9(u^(Y v0.{Zg?jIV9EgSOh4Ø].GVBYܽ{WUa@^3L~ƿlyeoWb e ,twRU+S 72cTk"b-?uC%&KȳQOvj6'),R~G6^a0agԬ_>vumb]ѭDvW~7Y\&ȟO{Ɯ ݊jGIy6@&D1O}ci/ M-ѣG bA|AU*sN#&j'P7-XNPY`cvcgs5QK[f%c x!lꂝ/6+f 6H|sXfN)\i H09{ϓ'OYN0kv~5Թ͘L {:\9jo[BsW] Md[ʊuV?~8)MRK iټg|\d-|4umZi"к z(Λߥʷ  YVh&<2"9[^5S c!٠lcM6z{ճٯQYX-`}b ޼>-hZ93΅͏m sl+YSa>3-pfKm}TAU_J{Y8G34ŷE ɖiZN5*M97[zӧObxHҚz_꼬u-1΍5[ r|.FF0WVmsB2cvnVy"Y/?gW9Cxnm<|P+86|4ur]ʌ|JOs3Yޥ[~װr3{|nL+vN3 g&~>>3e71531ߡ d~s~"6n&& Kr3 ?= } 2uc!dF ;"h1Ug"7|c#Y003F8w{rkдym2!6o'֭߫[uW8"inn8n(orf^w<'8711/{ΰ__d`3~dn&xc |ɚ%.1 NA 8O7oZ0)/:gE&0k=$!/꧿#ca Ȑ7Ti<gڵk:/l!v"ϻOo_F`b>GYĊl,=̰W;dK\^2SmMA2vB%r??YGMq~= ~4~'ώ9Y^ʕ+Co `? ɗGE$ĩ8\:_xfJM9{ŋ7L%<{L޼hƌBHz7ߪwo D&Gxu m[A>#i3MTDI}-endstream endobj 203 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 84 /Predictor 15 >> /Filter /FlateDecode /Height 84 /Subtype /Image /Width 84 /Length 3643 >> stream x\=]ޫ+ "hh(hbddfbbb` Q~swʚ>'ٙS]}X?~؈l6W{oE7eys'8ƭF2Z$~Gy4sԍ~ ks~xG>aLj1Ř_vr+[ׯL{{c fy{}F qd+@ϓ `>wy*E|'fcf.|/.FG1/#Z 0ķcBGhgEFCrG]lu?2l a1!Dr;@u #Bܞe->|`org;A&y*@␃| 6A cʼ\o3s. 5 Ϯt: ¾I ~972@ pI# pႂE7o߾<<'>[ 1 [`xe!ŀۙv:`3>i_߾}{n/)5acRGvEp;KHqln/ [hd<:J7Q-` 6T€\vmn!Ƽs>Ch7{簏:N)\ti﷉B$/EdxbFDn;vK3+k.ˊȅv5GGŸSwW. OO3v5_rހ ׯ/V1V9yŜy;a˭[*Kj֐ picł$RzԹRוOܹs$ 86^ e^>k^ܖ9}{,we"OPԯoWu'b3˹-|R{Yr?K8y0#rKhfyN-bf!%=ȾHV<#?Ӕ1/ky+oMK@y?{ԓG>PnDc}`E^4?/^|^.㇛Ǐ$ ,fms,iΟ/οI۝ڋI ͡>6OX#P+8+b'Gf=/-0^Ei#˞›ybMȚiۜm'q_ǜ2.{ ?=jA˩쵩mǶacH= 9Y}<3Ϛdw;%3๼Z>icٛwp#}r&_~w}Jta^y5vᐄ3nb16U%A>'KXsۏ=cU,-j6CŹ sSqEzNj[)o9{T˹Ӿ59_is*˪o?Zh 'y|s|>|)3_@XGK}/>wcMvȑ#Xs!)ЎGᄌu.ޖ׶\L +ѣ9a?IX?wo}^g<)x?: D9vX_Ҟ0T@)%QquNڴ;i66cZգM5V*cL./'N}o@~n? /oUc^ ;++;ydܗDEacvlVˑ e7O8@R˩S?+P/I^~ȅ [Ϝ9[M9Q4pf$Ϟ=;u$ko۳CoSKz]Xvp,ܹsxs!~Þ?!™ϧ+N^ܑ.s d+ϟ׿Oe"BXS$> /Filter /FlateDecode /Height 84 /Subtype /Image /Width 84 /Length 3473 >> stream x\IoK眸pĉ ']@Xل؎Ǟzr:U3V{hn40oM䝦|żKzlĖw25gS}r71߿ |p7ڹ!Odv؊U?<]pAh춌y#proA>ϖaS-eȡȽ yx!gNm᪹;;Xּ/y_g>߫ Z#k.]2VL<l/!KK̯F˗ $Mvv70߽67gB\lvcΘ7Yy{c]qPrGwիW '@-[#法=8Bja(vqrhuH`x웡l9ro.?{.x~ Tǚ7X`پ^Gv}肒_D#v[v`~֛;z*L͛7&ol6̩^{lz\۷o1h 0#g)x|=W{̒#C/I߿g xC&]`f>ka*%%""wvvd;QӧG^vh9GowЛol>O}%i`>|A  ; 꼀gpWknbK ",y-`?}bk]MJ=?s^nEJ^|Lm+7 AkHx0&-P8H߾}!#Y94%Csh/I})u/?~4}/8ɛ82pە+s߁gzf(L;H7 MA^;ɹ g!xyGԎa7]^3KFjPg!~}V GAd"GsVs߇`!{>RuGKȧ4Wy⎊"B ,.ȹ C#l_GK^ SM߿gH%jv:v2QwR]"||*hȹCU 30@>ZhSI?}NNhǀ$wiB/owЕ ,0ӧOa˹]`sGyjJSt  4xx ~ww͜]Zm@^JhyG&!&:۸!ʸ x] G - ~VX3;a$."Rm#*ǫJ|𶶶ÀKKHmYl.HX/ׯQPx _*& gfd?=\ &1?'ۢOΕV&Zf4l<6 g({ɓ'Ͱȯvdxh 9FI3O>h|{VT*<̇3J͒y‡=>f=o]j'#laòj6DW M rЎ^缪sJ̗4/?Nu떏y2':**!~/˪RDP766%dN ? :7eg4sxfuEaStT]#cE 8zUۚ4KoEcP,֭ϯD73oD!z%KvKg{0A'iߏs&'!p9竄ݖ9#qCp Gr8Z)Eh2μk^<3/#7)38"GK.! (~]%n2~Ff旂~6<H۬>g4.6Μ9-QmcI9<9a~F-=nT1$p\r!togϞ=~8y^iyãCC"ӎml"J.?3s;/uL`/g ~3g 9̘3έċ3YFbIضc>5Qc8 xĐ/endstream endobj 205 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 84 /Predictor 15 >> /Filter /FlateDecode /Height 84 /Subtype /Image /Width 84 /Length 3344 >> stream x\G3e " BaBXFB6)cbĤdDD$Hgoꪫ^fٙzU^j8ǽq0wwwׯ8ڗ/_主+6ul6K)qX,bcs,GyA7gG\+-/ǣwX#M32r,,_ 6 |>֠U_,"6L)|FW6%Mk+dd\g5glLk6g8#aq8Nxipz<~qgy|N8xJd1 vp. x:uL>[/Hd<<4i|I?#ϴC2Nwl| Ѿy:1iXiyIX= G D#c;<"ʙ9|^ܒ Vzᨄ{W%D!x!?cSڍc{g ūr]fY]yC"C"5ˈע }I\JݲRckecA_a;C|y_mZ%5{ch^!%ud9aaJa̗ Jg^"|e~YXQ8{al6E8KCsɜs׼#߷wyXEuiݞ=jkq[Z|* ~񬀏U[nEN~O~r:ċ'T>KOl|`7oxK8"\y|ƿ@PoLגr /Q ўtg9;l S]W^~@_EG>Y pAa™yS2;yfΆ3lwp/_.UtwX\C_pSs:~I}'>]oG^%]u@.uXM??x;tA |.הTك$ȷj}ϟ;xoMAy|Yҟ)e+;:|.c>~XC%mrK'? :2fw{幃[(kzofcpj̷wvVҭ[z0Aδfd~Wt )|<$ľ~uȺ4WoHW^K@R@Ø>͖:/6 bHCd5~9m3&{h &?tÖ_~z1@ ϫrPٮh:Ki i#2e?wQ(_Z#ϭ}Ű2h/bS3{..\M[Z 1xg~(x1va_lXjDmxau.m|gco!7% Q?=/ys78͛7Lþ]qUȼT{a/^ 5ж.,vk3_v݊2 / ̎Gto bٳgRyy?3:w$"Z{&3 ^hg0XhXjHɩv_~^0a/ǭ-yǥΕ/Bv~Lx!rʽPnҮɉm k9O01xGR䱘hH̏a4B$5k9O>,uНݡ0EX㗈[B5C=f5h} Oq(YxB r>NLN(^b  gZQXpMoBq^6޽{ 䂟C>:~N~X'jgvK?+Q6Iwa!xwveCV9gCN_͛!Զ f∙9zh *U<ۀ]0+7tVAx?TUGuyn\|8$XOJc_򝎚Sj8 x~5UIfwu)Ο??ށgQ 馺 >DՕ/k̵vĹs:ˢ!BʷE|5 gKbnpTSٳgC3Dm8+S].ѵJt̙pJ$4͜c%brAChdd|6lIl%_sW%i"5Hvkۦμ"w򻲖!6>wlyA2vcƷ¼Dؕ)q]DB|j*{ԩSXĹO[@Y o3_~-}wa3B(H{C?> /Filter /FlateDecode /Height 84 /Subtype /Image /Width 84 /Length 3360 >> stream x[t""` (_ox=fZio9ׯJ)]FfϟXFÇ6qCnű6?C1;wƟtoi埍 ϟ]q086;a@!{hӡqǤK+ /<# %6A/c瀇 B$Y+//7$y( :!;~>3’ݯ R}KgKz`Nݲ # x'rXyYJl6V~X|_|-_5:T YY}˗T*K5; 2A gT;#,>Wi|0|+c,47K2w;SϋaQwfM4j>ה|r#kjYse_s :[rP:>K.m|7yv$测΂DryE?J׍˯hކ9t}nϻFO?z4xr*ϨtfFŒvQwj{K*Y&:'[[m]&QmSmS)=+f&<5A)"wn> 7NTTqW&oGdNm 76s d_ƣVN1W.3`ݧbEeI &?ʇFE0əة;)]w\6;KÄ,n-[< 5;.1ݑ\3K5YZP}e\/=H%Fqt:JxΥᵁ5zSf]|ZT>ܸGX2 TNG_a6[g˄i,R)>|(y^!DBNX@, Ʌ Ci$Skqx46߯sFpw۳tC^n˳tٟn Lox$wügڭF?^j۷ʽtL#jkca`&o<#0ƍ x'dw~yCـ?`aq3իWkC%g;ؼKp>r ]< kV/z.,q.]9Uq5zu;b 2Hzw!O9jL-G?^sçf~^O^|Foۋ2HÛ/Ksu{͆lOmfGn>soE T/XΞ=~p M =U~mVR@V6Ϝ9̋aT\8Ǟ/tJ.𬹼$^/,ӵ sx9{lr12hrq [3^yWʩS:k<1RdnÚ`x.j3ԂeɓL9ɹOx:_*? yg'N&Ǻ6v4?WSrq$yzIYg1}ǎ geTAg/Nk׮4>5<om}wׇWI9z(ʹꔮy3R᥼ |}rH`޽"; VOGuni^y#Z9tT{3ZOu Wʹ||hQy> /Filter /FlateDecode /Height 84 /Subtype /Image /Width 84 /Length 3247 >> stream xKū{-  >wuϝ{[5wuνRZuòaeXUkV]b1,ڰόf-V`{vk?ahG5?߿هmk{V_5;ǏWj!<T{O9 ~hj{j!bWG߿9N*?,ЇWÊQ|#q mS޾hP훱pf䮼 ?Y4+S4xc3yV*#1Sg\9m#?v2{Oaį>3s/_B qI|]Mm|M{asZܚu~޵`asS6=G=O㬏ӧOj\Pw~+mxl=ٞL?R|so<|sr vįi1a;C> MC);)捜 >[}M~.hyw{M]ԼSy%Oh˰=yLvYj~)[mRR Tv*̓T yS=6gV˨1z)OcN5<ؖC5"/~ `b[W|bC]@qw5.RWhV{LK+9~q}10ٯst:nj:w0GS=/).5į%ۇSS[o(GvET|`2}u}ޣh$Wve=W\@;vv8Òॱm%M) 8 <.t[ʵ>:ѣrJSW^=_R{8 | J5x_=y7ooʆ;_5AHH޻lӧzO_H03eWR`#IC= ~8 M!'9oS'V~j%F͓ϟsaKܮahHKj4Ύe_D;$1nnw;c#0/_g3=Ti6 /%gOr}Duxld4L^zSᲉ*p)%xRI=붝gQ Z ~NGۗTTH6#:BBK'ځȝ_O]JS><[wiV HB|I${13yU"ܖyVxDhBC )7^peY*LFXC7ӌ UPU$9\?0CyC/5û8K˜|ۗz hZ)gbB􆓓8K;BkOy~Iz$;.Y.¨KcP %}>!fk4VE ;6ʎ-T^3:mҦ5N]^7|+jKrǫ1d{R'0H˱ݹsGe~"7cmvy_%P0۷oC*J~<\!l<%< ߺu[t<hWr0LK7oެx]Gٓ,k>3|/ylyWnܸQ1<2Ga+uAxu6?{&讋WTm63zvi>Vڵkz }B F KOQUj<1I^3^\QORSf6uʕ+=Qz;Tz Sr_\|ݮ'V&a ZIJV1XTʥKt5[8SQ턽>ڋ/hJ7IS }TfƼpLQmDL*|Kjo::u*uhC&BrWN$'O>]1pu p{xቼ"FǏBLI.M iy9|&aOlNcǎcPy]oGJNOEO%m5{G1=9r|eS:10{@|m$>|5N`q7'cṢcPȏ>E +kCAJ6ImO͟o}|_u$zN9㗩 `X1gHs K![Vwg_UsUmlcc@S>&މ>+\)$1ź&6֠ԅUIxIW~/[Qyo+1OzsQ=='+/@Tn7>C( 9%WJ4(8;ֆ}qE yd{7{8? MW(tx''Iһ^5ciBEb# "w.ᔧrb~<44Q7X+׹^;{grhDJBœ `7H|Ч&@ dT9{Zih/DŽg{h+ =1`꡶4;… )4?I@7_b1C~QՄGaq0endstream endobj 208 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 84 /Predictor 15 >> /Filter /FlateDecode /Height 84 /Subtype /Image /Width 84 /Length 3240 >> stream xIUM/A  $H,X `bf3pm_|8y"2XXYDDӮN߿OLOZ۶vٱ`q'7 ~p!擭۷gN?%!h۷oCH;5S c` h]C#gGxFZ &7/r_'&g+oG6(o'<ʛHJ.H_~ļ/1 3/x~/gAyB(9fPՀ C{?&tA勑sjFłK3 rns8p#W(ϟy\g|mۓ)QgNgSv]|B2B4Fz-R2s>;\zq 1*9޼yDsRJuM-Hׯ_YYZ|boy ۬^x R/MPfϟ j/.aO5'UC ~Źtޟ6-H[[[ /3-J{Wy%71vȬqNXzI+_ ,ϸ |Sv ˤ?~JϻT\^ Bx>#_4ɘqE)EEeyZU-s;<V_} $Ƿgnc! ի`x2vGw,h( soˢ]Е x)Ъ yaT<]xz>_r%C-&6, nO# ǡ^zDK/<s(I%x3_ގFo0*$O >|WsI>1> #84ZgLy$7ۇ.X%+oY5ϾcE|_:w7ؤG){,8"056yE~]gr ׀:EvWcXY~\" ! Up-O 7nats' $-΅:^G|clgHÞ9'NN8ϗg 0U><_i!W]5E[nl Q, Gp3U{ gv.u\2\G-7qzKhF^HNI(jG*-{Or`ϟ>}*cLDR*l =?J?*N9LPKy#V%&2P߻`ͥgi2f{F*?{2CK݌.Eä7I %K=z6ySo/}P?>_fE|IP|Mȥ=Yzԡ$ W<׿ɫiXPSڿJ^Uhd5QYЄҸMaYhfk;? LWgWf($&K+9 <ʯ G{^'OT7+JKV\+VR#Rt,NWh_ȥ%j)~[GgϞ5y d؅"|xa[,EJZ5[d<@^ҘSxEp"[?Bޗ뜅\эG{)usQE Wu^yn*z]uro9!C/p x9nՍVDGE^)K__I aGl)޲$.-fm G_Wo߮)rXzK|mf8n׀7{~ԺǤ¢6޴`l&Q_+v<)`xw~wi=y𬹿m.l#__._D˗/d˒FvJ[9-M.]Ol^",i<^p`Tw%wɒŋKKҔ*VOuN @.\RDs.EeqV"]vk6d Žs|o}~ Ν;Ts.9dDv%$KkGg}N[4䡅1/坋9P}n3g=>e|\]Piϼ6gө.'0 Hx<:g'3 GjŬyFO:UՄr ܎Y~ ; y:w'O5Rpd 7$kQoEJV ȧ'N݌ص}xs2?kxiGñKrN/oaǏq ACvjc_LT.Ztر|fl<:$*GaG#,~OBwK?=z49ln}9#4dp*+ff6xȑ#Xq&;kpDsǏm ;ig7 |?υ#>|د܀x!#mIkgY?%s{x&Q;e o0eendstream endobj 209 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 84 /Predictor 15 >> /Filter /FlateDecode /Height 84 /Subtype /Image /Width 84 /Length 3486 >> stream x9oM5ؼ;xٱdM,XEDDDDHDFDFDFFD>|g6o}L?uqGu)aA߲bϟo߿+?hdfvزel>/--lyyy޽+++]޲.m| vd[,_]Zw;N ޾of&9Uf[ff4f!ln2' 9>}fCskpЂ+>_d|&D x>6Lz {W(3YY.GɞUD|Ӗo ~ɽ m/_H!QW HL1LRGsļDg{ϡO~vF| Wg}sv>`"1/"qZ̈'V 2߻ELyzqC ds'GVq.168x/! xgO䐝5(}Έsc/_<.`rPHف=yZE,'G;N֕ۇ ߗgQ/7|g{_"+SyϨ8k:rwdK.ۙobO#_2_5rBm(ukLQS4 qˍ KP'wQCqarBr <{ײ>l9UT1D<| &]YxpR@.s2N·rʛi : |Nl Үf}FC [**^r+,x1~湐߿?r`qKET0$EΓvʟ>}: •٧FDFe QP#k,xކ?w' q^s j7x^8r- s{m5-·װ|~̲&鍀lg%`gZ'~b>< Ѣ_;rB>A>_t흫:~q[>yޗi. u)\saʕ|W/8xV/Ca^8Cc}E>OxVg7ol7Jn"4:>ɞI.Ft`VNoBQYy~#;w<9|F!{mC7}_ ^{%Ù?{$!<:O8eV|f3g2ƜL˛ m^ ʋq!LEyRzuð3?=>oڡTy9ۑxa?ncmll⹝yoц]>T'y8Y/`1kC.6Bօs؛CA}$s%K0Kk1~iz W)>yU+K3-I{}ʻ/3t2,~ПC f\~Vy%Ɗ!%;ŋ%Ȣ+ga{ym#ډ~zMU\?C};EJv>1Lʇ qx0faH?YKqg>5Z]*gx<<랍7!/졵2ͽ桹Վj>.bz+i/c|翄9M@ 1)x? 13y_xt˾E ~Ag>`x\VzZʘ'%P|gx~oW'x_*C]EyK|ɏ.C8K~^Brfiy8I\sGǡvH\#=/ʝX<|?MI.8bWƿ7v/Pak.(ܱ]-5s+= )/ƭk]7|E[Iv^P A!={6$n²μ/B(#|Qm،ouuUf ^v_= OXۅ{]a| Kl"wd1 彧tAOk8d; en/#> /Filter /FlateDecode /Height 84 /Subtype /Image /Width 84 /Length 3183 >> stream xoKħ׆YyX2!@!DDBBBDBDDDDBFDBDBDBd.oƽ[:ݻ|WsNﻮkVl~i446fٰyv~}~cv?yygoog1~;l0xkСCixizxf_29@XS4+EthO1b˗/yKϚ56?wU@,Xv<>ʏ?Ǚ/j6Q{g#ӧOK AI68.Ked ~TǏKəg xbyZGEk!$Ç+‹IRLC\ ([߿gR;h~o{  J>T޽{N{[?5O)CS6 ?O -y̡ע&rt0}zPU9\]Â*ύ/9{ٗjgt<Yo뤐>v!Wė_j/sSJ ?;Evg ɓ'}Խ~-ySyVXj/#T~Ǐ{:EWBIsn<4Ks~<=FoN.NGs4ԗlL;Nzagå^Ņ(yƦL}^|WdiH~|{@(iSy<3$\U9P-Pٗ+LC~W&.%v>\+h_ɠ~8{k^B}ܹswҩP*L+ 9]Z},b0~a%Ç,ڏY6yu2sKCW`!7!L3-]۝zu1K5V6?Y=捴8M y*AGQ1쌮ϕyfX*CÇn5inuqEG oMѕY'nܸѕBEp_s طE]D(pŰsׯKhyȿTyn"%SCƷnSȹvZIj!~*|Iylx|">PWʕ`\ <旪=>`%x/a%tRX<Æc!vIv)%$N|Qq 򱺧 ޙq?lr6H)e{hx򕜇~\ k)템766:Zɯ/!HVK<%xo9|Iq~'Od3|VxZ‹杭ֶaspN'NceJ[QvC[]k'vBǏ+^|[> αc03=\Nae<%.$o+WQ~ѣG_|  %.:PkES`R'oJStȑg{S8iɖsI{ ~w{owxPjFZg$[: _[=džuwTK6p[GgYei?,]o1v<{qPӡ)y|bE'B<)ftpl >cB͙os-7T\_+<ReũG,!y8X.qg{EyȄew*ӄ&9N~8ROatQUHyB{Z19n!?wx\~ ]MT|EcxAҞgf/ ;·R.^\w t;+ AOr~kkr޷\Md'| =7zl+\ytV/@4*ӧBJDy]5t4t-8MuTə3g[L/TOx^F(ϾSgP\;wN$ }QeY8ã yJy/Qm#䬹 !w󒻙 }E9O,+F˿uu~^L|735'aLϟgal?{k8GfQxCn_&|br~EUO_&Cm#9.wȆ ?l.ó쮼 2n\|_Ç'.rγ\K˦+O/nz*cuC1ca];/uޏPx%*endstream endobj 211 0 obj << /Filter /FlateDecode /Length 35844 >> stream x̽K&r6_}UΚ0kf 4) }zDV><0鞽:WdfDL߾?>S(e?Zϟ9v}*om~^?Sw}Y>۷/oy_}[u}ο6Yoknoy~~˜%H\<&PgB?>(gڱF;q1zJ?D3gÏRs?RsG??}e޽}^U?[4Jaegf)Y( z@j*|_\{_]}kLK^j}/_J~/u~yOi~.ZCIc?a?gZ{Uuu5*w}3&ʦ_ޚjgg]5.ٯk=:p+'?r}YOl>˫[?,/zZsG=vўV2_˜5,\IFoomMNl;,B_qZtF|z_3)_ǬL^?~W1TfpW-S:d!R IlGf'Մ⮧ae}zεWkB>hkW{{ 5>AdG_K]׽:!_->ڼi8BƚBQIkt,11a6zy7UˆwY,|v`ϴ.k5W7vEYVָ˱15os,2fmjk?zBկ5q,쫾oGkIx*D(G64BŲm~!1C_X  pl ]mZy>L[3z * Dj@Tm~wfT|uJбzT?ei[L`mδƦ>pҼkkBUb)<ksM 5Ϙ*D蟨9m ;5=/~p5- w;Wg#z*7z Ě߫uoZCh1~}UY4LSY?Qh_m-3IjugB2vu: Unv՟kk"7[b}6@FBnN ,cDBěeSrR1)[]-oeȭ/@&BVG/`uj$η`A?zѵ,$a.wO )lc-BvAj`UNՄ_-v , e;~`Q:j"S9%|@')9H^c*#_OUsYtհHAU,˿>&W_xjbWswwͅt|B2FO!05Ԩ,?>gJ˼ =fY5b۶Ӹ=! suYkB־ B;32V`?@yh.~4iq[Ƙ(>fC`Q5x 1Wu:=gy% e 0ptKO|M ÏǬi!Ï\Cn!~!=:-z5~4蚭SD,_}ˢ.@g-R5ahe1̀-[ɏd28̀{aWҲr~0O5DlU j_Epz ~7"qjeF؟B<~# _45h9N:Z&Xq->iQ9wj-HM`Z5!ӿZT,߆͘YaIve- 54h2`hH5%9ɮMB&Gak]152?& 6h^jMJUS7!sh:|`5ǭWUpO.d[KK#Or6[HQM04Yi9Y+FXnp!e}dYH+>,U-BQ29ry|GT='M|Rυ';e`F=ҩa!s,te"ۥ m#TaYzƩqw΅K&-5lk˓Yfmֶ]ߴz/ϥl&}22ckNzo64oYbhpT - i}4)x~5ŰЯ0J9ÖX}U!˰AVrOov  ſc@l>'ļ[Q3wU/B)w[ T,>goČ'c4 Z+am٢Vs $ͱu [IU[M +<Ws g&=$`4H.oa8VG˒qH&)'@|}`Y[]@=M2NH"Zp͉*$cr$}CI}~N4S {7N^<&3~לWsWhe+_jxp _ȚJ%{:K3ﭸCNB5( W#ӿ镭܌4εga"Tw!S__ 4 dXﴚ70zf̰h85c=LE.sk-æZSm4Kf]ES{$i$LE  |j X&+ m)$ʹd@T._mRxKC`ycV^sC\^`Xdγ7x.,^yw4o5(^\Ur-$iEclݜZ0 L-DCpToIHB̲l?zrSKZu%70)꼹7 Q1<;[y̲#RџX~שL$cXpSݢ~e "eMO+?={cCwh, s&OjGOӬƐg/ߍ^v V֘R^4[fS46ޞg 4Bg[YyW`1)FMVeӢSbySb@ܢ0vy$[[4b:g]z>ޅGsffR90*1їenJKR`xøsFUsGtTeedNxw)0tV&/ppV Laj-C1 TwԞ ,af^Z* >j`Nc\XV(B@qY0Qz]5ڵ8UC+L7r˭X`*_׼n|H^rmk%WIkӣCȠGDx!z7~{)eͱk\b­1T+Ua/>U̶"rҨ$[25_d-thY-.U@>oͮم ?G Syv פk4k8ZYKҁi|gĬk*qYT$kqZ[/z n:}DFIY2W|(.5ɰ4R4Fx+l>>gT ǁm'L^Mg"bW8CKs.>ז4DCŁs@a-xV[#Fueeiz"VX}ěrl*qG&Vebh.bj#cFLvu}̳ Ï:0(ڈVս#FߐW!joD[U=* A@c\󬉨$>qSJxN;"#0`#:F33Bs"1`WƚI~EB21)yYoEgfVp2.$9' kDr1vBU}xD/07 F6 2Xbz,ԯ8==nHh;?~gJT[>ǃ ?ƍaώa;=yݿ8}8c9/HD׈}r1Wy|lx8Hg;Lcz`1)}gpO'5y@<7=/tަ- SA{xC&wyĜY#X:34txzmⒿ. q= LwyQ$&:ڒ"_ $o1\Eoh9FOVޯ==iDH }⣿ O2:N2珲pCND@Sv|zqB3Oqh/|\Dg㼈~)gJ >/܉޳gS qZ:>-;g apqƠt%|("=lnϜ@9Eb= Q o\pg\Lû=:a$ӮW`8  vMkS+zre~>Z?13zn`Sݽv=!ӿSI> ozE/6g=&\OD8` 8 rA ap _p("{=HT{S-X"[yz8&sTq<I#DtMDСñ'EK⸗QkcXD>A- 9eKhgHyEؐ!s)Ty5*hZ#q\OGS'TY=\DO} qr\vdHDґ#u21RL䈟ê@.'\gRa>\MUA^V9"8HWpXcŊ'qY!g$qRJ#?Q#Њm37nſ?oVe+Is응v`<CdFa }vS94r]T*vt;s"NDy篔[܋෩ijyG fTv(a( _)@BG -r^Y0@le(/\c85wN2 s{hNrPR'T# iDJG:˔~Lˑ' Ӱ/vbzFڢ;KXl@KZ?l.L;+(NK)y" ՑRDZJ;ylUuZݐϚ^pȂ|$ϝQ;ۦWbt'=: ~Hu"tU%"8~!GdBdH5^sǩȯ_)=$R(ݝ4Kr;ϩLWc9]QQ:GO;TiOɌQd;WwnO__9ȧw99z·]%@;i`ʼv&sA5~x5w"0h Q0nr'QL C|'D͗HzD : MƇ:I`x;O7Q"~ڗ2 v[@ŹN')J,J"\u%ODr's3_@._c˃ʨ['݃VbO_%'HdI@L1Q#D&R@IRdfOf 3$ht*s̴kf7`(hW܃I/ȉaD zPNDL|/M!b6/ !ȥ2 n+.y7HѯOb`.rFLh .o4QQ} f]c>^e~7O4lsdQB?5:IbyhS=كD\`izYDyp JS?]h2蕜AH j^} ARB,gلHr0CONV**aoHCEJB}$=T49,Q*RhDEm$̡-k;ŴDſHAFY!QpVHwTSU'D@&"k(ԙj#u^"IH"Ւ:֡lRGCE'u毱BJ5yfYEJPcv2[jVu7Xh^x S AIv׷ TMEzr6WB7ߨ2j8~W4;>B痶virېV#%7 4lxm2[!A!fE3XF=|9h4z `x4+k ,AV6=pvASvZ8ZqL&@LQe:f3v5~C go)D<-lqH &1AL.k$DA+)DԿ!< Ȭ,28L? ,S_"8Pjf Y P"8TifUyL þ@8 48>1:w b7&w >vq Byڅ\d1׹-e-D |'DD\+"w|҄S?rxE+*/'(νOUzO3I.:I>?&qFx@go;~'J'P vk;瀫C1%KnJ*A S3S콁X;bvQU徽BN-d\쐂KY_[6'@^'1DK#7=lOl0pp4ۙcG gc;zwO>AokoጶG }@ܽc>1u?e ^UY G*8Eo ΁XAByUprq<*8)['may*28O n-v['maIA:8N भ:8iB'mՆI!x 숆O;Buԃ*ԇ'; +Ϥa/vx 2;y<@,O@Гl_"8 )dy8"d>A+^-BF/$M=+DK֥qmg8ǐ+TL#΃;6?E*W@21I(E_:œXjR$"[@x*r*UI͌,Ms6~Ftiz (1BQ$#;]hNTt"BJ"ȿPFclxp;~ I<1v$,w"T7:;w/;ϝ]` 826Dsm+\; 8ȔpVFY<·PrX"TtL83 /,ֿ"a߬m7[?ox }m!s7!LAǿM -ҖI~o3bo{l!͐Aޥw-"gߤ{KXfkvnڭl 9gr79[Gm}~ȯDj %~ `zF$s~@ Cb W:(/!7-Cy6@o2. k.O{3erAY{V~ psl1r4"6S6wt',tZu,r̅hU@Ls1 )Iga+/ ~K cD{9'Ҩaf ~mX+Mt2 kK+iŮvXNKi~r?IjΕ9\] g`FA{S#r-Ae \_tLJH &55if%d0/(i&*iALڈ1ʥe*}$M X_^|ffE#Q 6ܷI[1x`BGE`4{@L67bXY0ӛ?\cΗ NO S^v(Sl% Km&=K͘mh>E9׏>fjƪ  E=3Gi3KJ XQ al'H $L6i`I9`_r;%!Or-ȯYY;$OCl=P_7XV-"b :u47TknhKa_ 90GF&Y!TDja4 yi5` 4NMPO$. Y, HlYߞ'vP!3$TZ;^-qN%X 4' N?oY/=hqT4y|*:5ޗ=WݫXg+(_ޔnJq/Lt{ߘLƴX\HAۗaͼ3 OglZ#exa1V_U8~1p͏XbOV ]믫U?O+U+Fd,Y$c>㼸8q*#YYHaPgĐPg!%O8 )(YHPG!D_ߴGBPgJiPg!EƎB 5qg~kT7Zh n2B Q,d(k|W!FBBᆣPgQ(W!*圅 u8BG a*D,T? *ĴW!,BB }x_^Bn K9_1r ,Կ F~a,c,3߯"(_ExYB)TVWesuw&2G~&Ȭ"71ґ1Ɲt}ofjt5֫sDgтza_fk%yji,.RGf (I=ۯC0lkD*z8ӫFBΙԣ8{2°QP釦4Liag,aTow;Q=yԄNyD)mQ`ѳA& Z1H<2hi7x͏w%엏G?#5nc&| G]YG:2g\uwI< !3ĺģy5!5!y["%0G.j9^\aLQ#$w"hFb?Rh6hRy#kU#HU!hR밍~抷wJr*!T*3 Shӏs%KJ*2fdXrE+Q"͸jw+|WD.%8 +v\Kh Bр\r mɕ E7 LKւG@2ijB<{$;TK<;}ƒ {>z}򸼚Ŷ#>FY3,L<ݯu_ցH绅b> Q{˼4NL/ȟEqD&z|OyT ?Y~cLߋML*V w,ۈEw,E/Ai@ヌfґ|Tb@x#{FM@=4xf ':ܣWg{CԣsyT=<,k䕗̣\$5-j|Y(GϽ4rJo];E<`pѪ:^pg[+~*-7i,}ԅt=kNLei$N /2ϯ5btkښFiuŒFXMQoӉG$ip<&`OqL/Xs9Qh[ȁMg;'}tPk7Ďn=z"^@>4^,nͳs! q͌a;o>g۽|],2HÛ-7h]@ؒd }+dZãsM]g(ic!xiC(Rn"Zj"DCFYHKl_ D "zv( +mdƂn?=::'H甿 %59t9A7:tv:@Cn.j[5`(ea*6 ^#;Ѽ){O3n:w ?EQ; `~B^zH5^HҽqMB渫.c{>Yq{{ss\ݓgz_]:ySہ(͙Y@bf_7Zz!5{-ewX~4eZrZܥI]]M$`IYBIVՓ4l,SW|Թ5\i9 atK 뙱ʊkJuTr>HSGNaz8]Ƀ-_![zCuzڪB9+8ܳj >G)gVD4BܫTюLuɏ4HJdy_Tq]fN9ƍUq5ͳNGm]3\]ވhWq8 hhXqk[ndmO+r"׭1>>U-t5 ܼm=yE'HG[`&WOw2xQqOX:gT\Kl畊D@*i*dC瞊+:U\g#xwAg+'9F:U\[l&'>"= usޮcMtISO'P":VY,[[v+2'{'=:)1=cK3APx!t:cB_ZwAĞ7:B>KIζ/l/[&K@ghN89vWݏHh8EۉDĎX9cg1"rN-J;S"b}cʮgF^8NNlw|yldy4 \YɵH'jCI1y1i쨓ɌaJ#:Uo}Fw%Z7K~Coػ'/BsU|"r'{OZ#&b|DGg)W;z(k=;" Vq/?`k!8Ln@VzU\1 cA#9{! -~9,aP(XT.z!M@Ұ8_tWtb[DrvE|XQ46i;淃qDf;a zD">9e,LSXq}  u^ޚc- (uPt}-w ~>\~pk"ƕcZqեsJ;1upȟp2+g66Eisb_H)5R[*sioMN&ig/ޮ)V|_ .w F69XcfH̅}eS = n},bds/`a6uk_H6ci_w!Vf̍[!NRrՏ-/5-؎9 nc)E4f1R8BtR P\Hz:>:ybFS98B`hҿrHw#֕ @+p% Q1$"!! d y&WQ'؈j*Z,FsJ>CD I!W!:[Q# =FuLtY <%$BۙqwjPDEC* D̈́:fln=R}+y:z) fB椎&P()RX=\F۝q5:…0K ޽YߥekT{ K'"Ғ*[91:MRwkP"ԭm*»!7#-W+9|tSkǝG*$zϯh:N iԵ !KBYcذTӷ:P {!eYu`Ch_Nn*~ P:KC`'LXhBœ50qc6IZ:x%Q4 Z^w5q0<[]ޤ{c+M7&ξ;~~oI5#!éWIHHʍF9foUqYb}*{ieq ],reqv&  ,I4#ItS I=,g5qӹUġyS XF>xųޢ8)Dqr[XዠWIIl/0Q֑(y Q >КO,s$q79iDܠ9I:5tHS H݉Kη$sI$ΉH|$qwYy8$qZ$SyZ'$q|o<}8'Sv-susBm \ݷoA  9ĹZClW `Hͼq0L JYC,s 0djN LBVjk<04qpp v4qx;<^&+CEqp4!ת8W)oj2!cX{8Fsa##o[2y=|K\oJݼgyNL]ƸȚx)i7z7x|}b?ˠϟGZ岋?w'n6xW9y73n&#_ޠnPq/R;/{wk߿Mmn^}z,o5xI ,f]~ @ԅ~F\Kۻ^ۦXp#_6%WU_Xqǯ6uOVm ৾`U[>W?O-27akB߆X[87!Ud,pܸǤ2{:xdP>gD{ ,׍p*|*Wn,4E} *ċBBՏ_̯2HB^^-_EDh:Rh~){O^t2p*(x9(d,Te*$P,48 z8 !U PbQ(B mvB.8 ]zܯkUKx4^w`?YȜPBb Nv2*PczQ(W"kM}"2xb QF-2=P;_ 5u! L? 8 PRkޣwC:3]Ac |g[LBe"8/kW4{gT+^{mUhn>(G^g_̯e~;})tZffBﳐW^6*DYY U.W64xbYYH|PB@ ,dPB_ֶ |)BPY Fo6*$ϯ K޾_t~G ܅6*IRYP} NpB=6*DYY΃xz/"k/Qz I(dUhrv2Pr4PҔ Y7 W!A I(d,dاPgކg_ ?^HO933;ЂҜPR0"('9. ry.WBnӾP|/Vw(GG8)$']b B̭) 'a܋X(e{5ӧ{T-?RHN`T!7 uV,^}T!7 n)&UrĥZM». I unnFz7&r9LYMB I8b*vJ>M+$'V&U9 #ZTQeB!9-$'! +$'!>S dBr$GuT!; //`'a oBJQ$z ~bBzgh4IˠW9K;zrbH:> لB M8y.'aMdE]u6Gm Iz] CLFOӹsԤj "u *&Q()9BnEGn#gfp5hk(o$ѢEY8ӠLMKԔϑV/ee+8@tuVhŁhg.v(}!9㹤xI$iN_M7=XS Kկj.-?ˇ iȷnFo1 I+$p`K\sz]HMj"^U`]$7] ̭[ؕ`w*xU㋾HrڙC~d9x+ 馆&D&.EfV$RG[AEuTqk`2A%$-0(UEx)\H#?h7HOpۤZAG RvJ˭ԮďBBRN !k3,3LNd6,ZJpo3tkdSAxwKFXI\El)g!% 5'%õL4}GQCzV$r(#$Ai$Q#j$Cg :n!7'XHbN^/OTi8'kHVӃsXI(K1LN^>}U{!' /~9hcn=\9I1ؠivDMM~4hȢAU> X 2vd!'i|\f2p0NF2 L̑mRJZ_35K hI5%bU:nQ#̴䅼$|aRu,@SHKZw´fԻ2?Mu rn%Yq 6d&eG^Lp%s4l%MLAv1$j!1Ғ-y.L[/Јub$Ax-$'u펇hCUSzr`_Uޯf7SV)$'1>dIBrG4"i]*ӥ&; o<c؁'r47FgHS |.\l~M5Xh PVS-ѩD IVۨ:3 0ď19Ì^ \~M qD^D% _9Z`jm2i!/iچx0 ~9N0)u93T ߼]`9ŦoKPB•BZ+! ?mN*|t޼cqk]FN"bT^phwUPnVp͏'lp( YIW@ +X0D@u$BR.:]GXITI@"R&g ) ﮾!T J{ȔBR}L楥'l,@>v> "RAyed- T4Yn1^2I { 1KVQ@@0 c BmwDoV>^5Џp?F){Ng!և)ƛ5H.KT/>tQV^5JTRj;;cd(&Ydͻk?7I2+ Nvik91 f(,dh!Ȕ[D u%'urt,ZK/S _4IS/늾L Zӷ^.e\qz胾cC8}$~`p!{d9FPvtF~SQ>뱐-1 )QBCap$` H'C !I,=nTycSn1"Sn1F6~KzFs[l8${di5Y\\XTyNWy݌ |'6G :qGeANi:` GxB"7IvY/ Ifws,d K跛Ȉo|\z6RfxΧ- \Ѥd+uGP>;>:°9Jުjm=ب̚1  鮷B./ W;&dWc5 ~'G='#XsF>9} 9iְ [uێkDH4 DÚDBly2"^xL&^]iUx=lwBDkU_3Nz Ak֭%^M/^ /JPw繴!%3?g+$dpda({[Xͩ*_?=o Xͣ7ȥڹL nymR0ӹy~t S.R손7#혜U!f05`Ǽ f߱Ky>#WD Ogro9ݭwHO-vH+J6kw oF&$269<6^|v9,5޲gwo{$@t:{23)Yq~I O+ȅCN4sв$1:9?svB{+ttcs.g9{HF9%80{6e^)^,"θ컄|TFd_{8N#Ы7DK&4N{dd"N5=! "/E7E3r_Q.ze^m'HLj+G[s ? .2Q堲Ovkp#ɱTrdZ *OOaSgrXQ y.՟#_pM2$U+4?]B9$lϭ{=X9I ~DK{'jJ#ld]DݔJ8=8b(UPPu~Ƌ"m0Q ?x; ֠Ȋ(XtX ^s{9ȍ Q Y:#aF0:8 W ;D,:FP3Vu_*V^[Dw\N9'~vKNef칝I4ξP$GƋC;o# ^"Sif{"I2sJ>>?KUjsދk#u8i`ͩ JTw'3sdܰv&_Wt 'ڑ:z#Ոґck{+#1H{vH5R)43bu amٝ%םWg8 j]nQ^ 6M 𝾶%wU%N-.֮eǎ#.oj"*+^؀ `04c%Q %;Oĉ̈ۤhhf(n=qIj-$(܁@^MXiQ^: )pX?!T%0AH6^Gsbpxn8'$] 5 U^Gi~: Q'T% xPLтTb!:a!ؕOX&0tT3\ENQ @Q 3bVc_&hVPE`{ @snCʁ ҝ)Vj9g 0vUbON!gsC7 HȨ6 9rew d bD:D-(~N^KQVe`ȱ.*t4$%POrLFŜόX@)6YXzgLRuvd ؠJ!`WФB84bfm pJ@Qb$a'Iyۨ!\B,J(Il"%I(J,Д•Q$Q-NL"XFx_Rvwc*,KD ΨlLXiRN ͱɀHҩ,,9rϤHe2rƋp㍰e !\i}9D>PNOrBxÌ -Uf#)fHUcFlO$Hr?|Ȍl)ʙ#`Ofz!/TY2™_9=3#w 4#AE'Yɤp e[I29J\~%5`6f#EgUma$*7cOΩd,2vNד#_2J gZ 7J((wc! *ޠ\fptgZyo6 GW~-oN2ϙ%[R%ҼN)$+m79ӶF)S:#)D/駊cEW⎌I3mTyobtK}[|(]֯HQuTB<gpO^XTT9l4pmdj8arsDp3L 'o\TNfdjdؤ&ܽO|s$gO `Ds0 \8OaBo:|/ l$na-Bo~(@V(u vZLAÚYLcmKk/E|SKqHpRX`aa u u_ :pf%`vpRyNIjQgqVNbP GίSBRb8iM gQM W&(fY5-`r+t)6e :ĦQT R8К2NS)0h+ݥpRZ8[3Z8X_S),ӝÙW)LUT)lS)L7ҠӧO E)qnhLڃ>3i>W*8 Q)<'K)9;H ˴6p=-qwI,'A^)K9XeQYtpP$ Cic7YT*SQ{xTӘTTA-QF1y&ls 򔧴*$˓(BgLF!h$֊* ^Zp"O"|։|)Ԓ\޴XBMsVtlVPzVXVP{dYMh+Xh;&8 )jݡgE+zG3E?pij2plz:`Fk]BIZd;AkLX 3icuSU[E"Wt:BqT:/`coeT`5#:8âmgU6k95Z> .Ün{V~ r Zt.H䁂4g3"`iA8 M< BrwCXPHQa%*0yDaN|Q&R+bSbA`1܉E`!҈oQ걆MŐ(_!E1.xfQ ދ- ̣xBnШ[;܃K+fB:(V80n I5)fi ִVg"H N`TKpAB X -mX6<“Tpb9 ;%e|D2 RAqlnd =1!sx+"Ûuz@C$#o C-Q(t݂CL&b" Et[@*ݟ+ 2CIrQ[rIqdb鋰M,b!!T?j%LhNu^F@^ʈ*VLFÀgjw0C.Y Rj`d: 8諄̋.u|@>Qfr@sK\R3RD+Kj "AKWfبJf%c*LF B,&hM *8Ȯ20,s 4LB~X 䔐R#,5㦸&}6pY"nƂAWV hADѓKj,2vPH3{1!rP"HA(S7I)D$^EiFkq$iI]IΔ&HM(@zBU&b`yJ ,AJʕP*1.PQҘR6!l/EJ`B:"Ic`QwDye̳%3h4]zA<=܄HfJG,!)o<> {raއK `1AJ]'=0 WC2ҠQe$F*MNtHDm7㓒ZG|\K)AhʡʼneBۉ5嚝+ߠ9Ek(/c]k0,fNfjTƥ5lpo+xr}{RvVAocb Ajc'ْP1["!l7D!&b#7 h7LԦmC= >jԴP2Ռ f *! O>*HҢb-Q(%(5P܃25 y.@G)߈&?ejZIdX&w%7/$Y;/ҋ@|1i|Us!tlSf]qnqE^A1=(zQF03#tHTQ{՞#Og?]_vG;S'Ńl8k,-XP&pU#`x euĴĴ{Nic ]=rc!ǬIAMvFc2D3K6_53Na;GGysJmI-S8too߳>F,s->lx]Qt!淿x|7?R+gq>lɉRZNX瓩p2SHzϒ^S8KzH^vs2Cpʗw;35 ީ#]!8)9?};HPi&dOdt;BrNfN^=Eއ.ERt^zwpNwsė!8p2'x'>۩p2'{{'S /wRmHd"B= iSr2Cp9EG}Ү}{@Dt\-p4'9 ;`p 8b睆z'B+Vu'iN#\z8]P$d5 IV]DCpBm迃K ۻiNN4x_u63#%$hN- ud+گjvگF>)ک_;}L- WN^9]L'Z!8 ; `43(pT˕SJ=irʩ_>d 98yMCp !8)9N9_3êiN=!8}OwR,s2Cp:bh5 ǨiSs2CpWog{d]u_3=N= މT 5 WN9_9&h=|46gHčmSUy36ݘR\vlS=po:S?J):Hۃryz{Z.66C=r n?ā?g muqN qgT^/Ozg½$*ɂGxKHd--/-)ggcE['=M#@2_⫿;PQ\pgM/p.-o5FliUd}K^㩻ؑz/Xj0 2NE%ohQu˻{긡{|@ڣoGʣGܼA]P_fk{ WyMe+S{{|l~&lRG(_2 Bu$y^޸ &"~PR}qS_[!2m?JLm.Ƃ6mdpU*$oi !F}7lW]/5ƣh t 3):g՚q:| `(хõmsG7w>{8>9Nݍ䓷94ӑ/Ooؠyoڱߋ[q΀ הt7w7_2S#=_˘RsMSZr|]z4Bia\CB߷/b:UK437+j5y91puz=E&߼үSփ{=ml8M۞e&!/@Wи^1VXݜ/#Qxy_|5忱zX~>||}Bjxdm=K_xwй|yx'= zvϻ?`c}]k=ut|[RY䨺"zQ^DT ?GysWJ{MwH/Ρ-7|{O5֟0e|X~iSd:OtgOnŇ?֟߮?^^>?Zg:9O7:~=;ω^|AewMtCXOcz(şGۘ$cR„= 7?Ŭpz{6ٳ|ر! ܖۘYpO~1,K8O~zL9Ο:%n'BB^-Bp5]5F1%W*(bo[Y>db@9I>Oϯسi\s ~[go| ՐŲb(1Jry)i\VQm&6y݋Dрl2$Fp_),>\zeͯ,#.G"y^g`qr+qˢho-j'hj93n>Z.W1, v|oI|anzhz?C+{Wf 9#j Q7m?0Fnpyl~8< <|~%qC)CY^'-A*Hڠe3ل& ;j<ۍ7k5}x\䃇M&4@vɋ8^? >_!? ]|3Y77f75,*EC2}9X/<.)X-m3 }K# Q>7t"147K jB%p?eщ |&Gg|Gd+Tp?> stream x[Ko{lCqb  +.I&4I%Td~@ЁٞWVl+#8ሇzד?k-V'Gf6^fur}ټT716 |LgHyÙn?3̴[o\MBq{tv-y*ʄ5'kgs<`v(ˣ?}gՂ1HppbgrK<4ZY. t?42Ij'Q*{kEg?Q-=3s t}բ>`)+yWJU%BøK3i :M.*1o͙)/y\5Ào<7L;/qwlbK!`iG/Rp L %9nz6eJ1B f! y%$W!#v QqmpLШ^88'Xh:|:؃f9f.5g HJ>V@{%| \°^Y@$%ˁ<7N;p&0 C },$b[xU#0jLN,*&6 LN3PF /XҮ ڼy7wJ^Ur!(+6Tܿ ^+D5:Y "Y4bPiwB(Mn(ڮ6p'glS*#MBIg %2 c/™MHfvuXXKYȇAI/9HgQOjڃ5jﺲ⬔hO Gq%xj_pֆ4ȣ.7[]\Oiyמ&g!{|Vے0$ \+iEAF*)AK^2,mas=<-n{S|  5t1eS(S-:)+)τȩ0VR L+kߡEI2 ybSfzہ ]=?(ް5bm+bL("SBDɭ Ae+3vrѮ-b*VlcŖڢ|aP>Kr@@dƹV=a%nk#|;W~hXtMcՍ&ܣFxҨ( 4֘dԴLZЅoc 7^p3 hKg]r=E.Q״+ ^^rs`$7G,AȮ-r*dw|pM)9XTp0\oRS,1}Pw^LEu-hYSL?SyS7Xj5XXȆ/wxS}]Z':\z^xLM}c0 A77] utM)]-) K#U bLfាibi;9C2k&&=M AxA J̫3SdKcϾNyKg?>?̰[ͭ\ڒI.k8tUuXXw|zasӘ8zL2?lmZJ,(yN};<=/C&Q$48^v<73;m kMd3q6>^2␢RHPc*/,o'Xᄡ{Jo Qʵ%#d[q)[(sIM#wv4IA{WN# ]B39j8ʆeNK)MLQmCO4]c%Z pPy%l٧ԍ'I0k@gyۺem\yS(V4ZYf=k. \~txwVM x< ȥ `:ֿ(%PWoeFh!SevH4'UJ}L$ !_rdo8A(_UQM%b8{!ݐU}|!yF&.-Hק>kG׶t<ݐol%b[ɫ!!$Jr@5 urUyֻ}0sUIyʃ!׹l⯆0$ ^gCyO·$x]ӻF*!>@\K@96Z4lJJFQ3ү#H̳Gʶ0ŞIO/ #_Q, OR+$^=anrQ@Nإ:Boq$ U4_8 _i RYճSI΅s29#c M&OҎBglUni`t|*,ƲRIGM R*1N dhR ?&iE=8}ϷEt徎|.Eŏ4* l{;鈄~6ioѪV3,Tk9={ѓCo/. {!Wӏ*ƺ~m E+zzqSp>}^~7_^t:gFǓ$fHjrZ3QyJJd(aS]6)\I2Е!f#T~j-&mBęSۤ|*ﵸ~d? rkH7#V~&ʼnkB~zV;42c Oѿ|)eendstream endobj 213 0 obj << /Filter /FlateDecode /Length 163 >> stream x]O10 €XҡUqP(/ СY:ߝ|reA>E0u- -m1,O)x@fw5|VS^[+x$E b'Φ2?M%K17MR{;RB|GtS~endstream endobj 214 0 obj << /Filter /FlateDecode /Length 3586 >> stream x[oEoVHbHز7my-&opȏR$y9dB# gl3ϮO/'02x$~g ˙vNO\+(BJ*ۮ_Aܷv*#r'j\9NOxa:}$9or*{vE$97,sD1_LİH _v̖r=aǢ rjﯺqaӯH,7L̖9^CWxC!E!͡Q[ (Lryt($d1YHUHSHKGY.(+ ɻr% Jc_Ҍۘuוum!ĄF{vu:q )आ!BB+$YtG9r9|`yv_WįUql)p4|g0rd,$ﺜIYo.qeuO]hTtQB0] >>u r3q;5^;k?ks#I7<WHf#sVSj&'7zYuKnj;-!I6;Ŭs*ssdAρ# 0"Zxgų$ЁbpՔe&L +p6(ƴWIi?aLx;!, 9X✲x^5zEt &F!xydCq@d;Wƒ˲NwF>5 AAJVr[k.&C7- Ē6W, [E1A+Vu0yʖCô|kYNԕ,j_850)*~(BvW[L9}qJ!dmߠ4U:}Ӈi4W@sUc-nv?IGb|!]!I4GH*` Dqon}|hh UWaV'6 0H |A8_Rd|x%F26-B\e8 vFqMUBhu@d8x۷>".q"Wd[/hQ)Peۢ6ia ]8lC0{OyMrR"E;aS;bJ>DQ]l| p.ƝMҪS{ > [;ZkDb$@qP:,ۨ~SlEfF E!1@TӶ#V3m"օC!&H+4{ 6CSZdJōjK7x]bl0?TE2oJerV}lEx`}p[ZmXɍFI A /<ecL0Qkpm : cPKAT ]`EQ#g-1U +)*{1@= S"Z+#T<'ߵQgkoVs=i{-aI\CNc~LY7qob^bmP%ȟF7a#x9I@'&b :\#lgA2>_a+ ' 0 -7^H漤,y^g\qc㞇v6p{S1ؓ]В{Zun_K4uؖ]fDlqIqt9iUxUXaKa`&WGM-3]7/Wx޴JNpwg ,P[&*z\ W>.0x/%ѲV+IhzCfaf` |6M D}A h|kW@Kbuǡ ӫW*:^Ϋ{TWPl׌_@B0*ુ 8x(t z4t'5vmKY's6o@8#H0F6\Jh:yb*5]%c`Rmb~E8!XvΒAa8sR]-+ͫu^foyՌjd AP+K4w=47aM>h0B+O-k901 `X(?ߩ*RM#ԼD$"sJ?G*fR]6pɺ:n >k,(|[ &Q(EBs8x-:2ߊ52LXn;ڗ(0Pǯ O(|6Hr 1rd6NKۗcZ4څ\_\s(#ÝӾ'+Fƺ.(FGH?YEYbѧvA_Vmp .+l]7&B +^*LUy~z36Z6T=I>+b&CYU|+͆# XϗeMBuQFH %==b/OU沛CXegUEPѾv<[t $9SP"Hω,fmϔبĦ!(3ډBز:?V?)\)\aƾT7O?6d7zwyc@Knis>X, 뼀^2cgEj#KZsvmhw?Ehԭ8aUf.&v.`vT;u&z(uBϜT1C78Ctt% ucSb8H *NXYz~҅P&B(U ~o*e|@TF|+JDO\V6V}J6b[>5 G^ $G~࣐ ,nx9B=ؖPy!%Wʸ7ҪaDD1C"wLa*@T4T* r^s!!^y2.,REnjGO#QƂ6$XU:o.'_Kuendstream endobj 215 0 obj << /Filter /FlateDecode /Length 188 >> stream x]M 4&6vMa!Eoa.x/kʋG +Ώ %|yVJ>:DnfYt|"pL]P> stream xE]HSaͱp6s-4 &b¥-̜&g9T!JѲ`bf<^` o8szPtr>-UHE2tQ'+NL#Qל =CUf\X8xí^Ϝl./kPIH p6?Gأf,+wM@tuvu`$L}@R\% Xv.Oo~5^.̄{`EB DlUmYJ(&ם ag霗w`GfO=,M22CϾv6&5Sendstream endobj 217 0 obj << /Filter /FlateDecode /Length 169 >> stream x]1 EwN C(KdhU1&bA }$:|KE?\rGĭ#qk#NjqvW':0tx@Q<˹>4`4!kZk;dVV> stream xcd`ab`dddu 21T~H3a!]cO]nn?G ~(Ș[_PYQ`hii`d``ZXX('gT*hdX뗗%i(gd(((%*\"s JKR|SR @bI?V3+_}ߝݿ:9w^{g倂'D߫>d3.yz}ƺgK qV 7qZѽM3~_+ۻsO/{Vw\B ۡ݇f<ʛUg+[yNƾ|Փxxe`Vendstream endobj 219 0 obj << /Filter /FlateDecode /Length 4549 >> stream x\[sI~/;M׽q8. -%e,ꪬό=vl@ˬ4 /Φ!ts\Hn\‚UKħGI\/~-&mMMr ".#A^K).Rh2 e x?T]mĎpyeI~wKpb >)A.@peoH wI" O _%ψ: o衟dbRL@"9͂h9\?=Xd_&fKFr|<UHcnuexYH5r&PB{O+ќVA^}\uu7 2"Z!׌QSm]0*0!|Ţ?\ Μ~)M?jEf i|'~l1eg$eq8e>2/×e<ٻl%& oM T_u I1A؍I8] !>5a$F|FzM"h/*LՓȬJLVu#`ѻ1d>8S# 64 v|äL@%9ʮ&=ɔ"(4db! Ƞ='ʑF[ nC,d{m4u/ Ш '.Tՙ\'ܞ[ `3%kgg褮sLOlz̵o["%L9 8on,Q PӐ`Ql&Jވ:(Ї,)G:Kb00 ~ht{VPiܱ8`Z*MWEBH*.5[Kymdb] Q!5|< AP$m\tY’'F0F~{TqXȈ_>a_(0*B!Ri#43:Q]p4\LL,"eԨk>LOƄ/3᤺h>#>WJUi[I! agV`$AIkEc-% q#g.TǷy{ؼb Ƞ6.ߴeCw 87P 2UNM8aQu4p;/I#&w`~Ѷ.mad[ Bx]u7vs Ce"=Ve3*3d#|bTQw]1;OO.ߕ܌b2d~vD @yM.ގZ-q1jy'}]8ˎ?'j ˛lȊ`XqpV]2[1`f)Uʌ,rv[siK[3 ?KH@h!v:0qlzOq[a >N^FUGxPOWҭ3%ŠMWJeo 6h`f%y"v< ۄ{R(b2%X rWTW4C0ݔg]9Jw2}, &@]_;I]5ߴr%㋮MSЬDΜKU.L7g<_26sZB?FV? 7sA.J!)(^ja uξqK%OB-dd*9iĉ;$PD>`F"HmxT[q39.ݹʷ0oX8؏"Yۻ"ޱ:VAڑ96ˎU{XuS^#M!ܓE亭D]WE׫%5u"^TAMW9%:9k~  vh]1$Jf2֯WX0_~*\yUת̦|~ ~Z6O~ôMV"_F7^y*eхWq)P|ołækv*+cΏ~mywO_QټU߮X[6r\FukKwn9i]a gB-vq4S†a7p5EbKbEksG0 COkX1f'*miQ(%2bx!1r;n`/&k &WcPXzgRo69D,,9W0n;TLbK4| vqЧlcdgs\E6ﰦ)8Fz8VI\}W06p B*UKJ&UՃT(Vqp^E!)3U*=RGѤ30|SCvr>AQ)_gbuޫdXq@!-˶[>s\DsapwiB]F"*S%9Sr~^v*Hx.}Mjێ6I8>6y}06 BU")Zv{ξ-еͼYlXyUٜ Fj(f D xtÉ ~_ױ8c[djU<4nQ0F|1Xe&BHY/u]5RklyavE`tS༚Kb@7K}fᰆ<&- -xw;\ohC6#74!63>!d⹫Wh5u9Qv ɰ3V'`98bݭ #-)e'z J\6~3=M5M r,bu9 on8;b;/Z޵e$Q Y}=Ӎ\1Ҕy=*1 krn~-`($`Mf16'&1&#nQېc]6VoOz9%+ճ=-N'{˂e1xG}ăaI:/t (gvKVQX_ox'i HYʏ<ҁ0)?䞄k^W*aJKH]9A[9Y#$ٟIr9B"{D#g)e%=IVУ/ D:j+> x5A!ha+rULշ>X# [4R;*A lXZǪS-* УMU5m-¥ VGʎ}#μ*/<] YUG2k :"-mˢX~m^7e-eW_:eX``%_ QRholexiY{b1 m̶ j#AWZ S)> stream xZKo +b3NޏE`d x\9Fk!ilIެ/!YMVF:[:*UXǏ~P^(GjqqH^/t|302d, "8GXqJw+Xsyy=OѰ|CQ[Xe;a%w,wd\8WHlq5mW$w,^x={,ju t=,4\#nX::mⶻLuxwOPCⵎ^<~SFl]7b] ] WL䄈}W9mŏM~M 1DaΗ!%`r4N Ծos{i)˝κvs`A;)A@KlE?{mo~K/Ob-%UE QO`<DvX00rq 1D~~h#0rA``i$<\..}7rw;1}BD<{yÀbD<*SЍڗ`Bko^ϋ5}lyL к4) V\ „Ϣ& `rw7Wޫ^nnVN,#uY;L9;Sg'$ U!,7h;<" v9f 9ep? v.T j:*ܝW(ת=<4$ኇ!+a5U- 9\q ;,8'H:rf>%YaE֭4 i3;]qQU/,D)P! *8Fw\uZ'*5Yb֙AMTV[ ࢓|T&Zbx2fv d/d踨;^t^"hN=$N ij 0J{O% >Ӥ3E#gӋ:vAwHQ*lS9=أlR]JTe J؁FbDX%v:8?}/mC`vZۄ}LTJ"3:d÷7ɚ}ţi'om @T\8a EMu W9+H9qYqYw\.&f)jlVpœ$m@-ܭdx*nDPPcm{J+x5QhmDʢ6r4F Z&w9y)%Bsn*{AI1˺77SM+a=x=Cp5>;EXx) ]iO9tfp$gzp{ FVds=1a'*&gLjX[HOIkc`}x0ڃVtԡfNQH~Ý+03ISfq7`q@Ueza/2`IŇOc3A{S.ŢW %тF6Қn2Mޔr{%#Az\)>)H'+f`Q*XQޤf$dt śNiXs]<$ rIexiE=(oaÛJ V,̻+A- V(ꝯ>e_8]qvr.4d'"XXv }pxYlګף}|pg'i48^=?b8gi ~/Bendstream endobj 221 0 obj << /Filter /FlateDecode /Length 2535 >> stream xZKo# <04~?Q$ |pkHE{zXCJZy7=VOuWW= k\xoOFZ<\\GDx9ҶҚ]y;N1+7^5|:㌱tZ?/ᯒix(8(0KÛ kgR> 3m͕\OgR;l72qr`Xzn9l5ZY!Ai1w͛0}5Wlx oc,>yƼcTV1aagLΣL3\  k(ҷ\b^xhL^)%$7؃yp0m# O*Z^Ů hNjӹ+Q-^2 Մ9NLwu,'2e >Do':dH"q^4{0zug1c',nKN 2ykbP$*&9.Rwp_.ǐ-^Lq̸l" o(y? vN$dї*s(d{ qE#Ud#Lu?}ZHLʕ$S\VlBK̇Mzj]}Ӭϸ}'dg8PXFHQ0<&\ )JT-8n.L قzHofxBng +pI+rt>C 7WyHkSٕ// \s隣r7h-o è-p"TQU w:I=/9#!ަv#(L>=v GlaY`l:X.T#!Эw R /4yUF/OU2E!!Rn#XDmy$E+#.¿L+a:Â}[-M ԟPY(9k%iaUC=cO%ˣ;2(91i"|>i/џ"#e?<'P"E>=/Tqmg=u|Wz|C9r 2}IW1ŒטgyGv|vkUI|;-j _ QZh;&N7#ݛ Jb8avzV{PuϘ3@]h\ 4jt>|frmi<>w0Z8xW#*[Q=@t$IM$HgU:džB$ٜy!금7e9➿kuB #O%IR<`PAp+^Jׇ?W( ^|(8xxQ >*~і-DAMD+YԚc%{oPkHcy3$(,FG_FQɡa8x?iDX$yڜr4{*}n==zD՚hBfVED_% S5*s$9O$ і:6ϻ)zΣ'kcGvL@e^!~Ü!깥C}fisJ5֭•gT:-x3ƤYf%XN !I'm̊?3 ^e@ZI;&*E ¨d؉: \T981-XPUBlyDCt%-OG_BqeLtpwX 2{qVbbI]^Q%>Hg"n"m )M"m;mفz䧠3L^F- p.*G79FPtX^MFM5[}E':b#n 3u݋^G'}ڟKl\fXGe[.j#Qˏ`k`eDNJ6l汼9^R<2^IvL o*9*~mNrh90;'p *)~ܹmSBd!DKؘ:p|h2av(c bdLa6 G]ir0c .M uu5ɞ2kb@f1P2\̉Z\mm oHs֙1) I3L-st>LtN}tN[ey_BDP`Mpu\?]rg:[w_\yZj:`.WMyi$tFicXkTmSwYS':UF=nbdtJSKa˅Ë.lpWVōh9m_5_OgO]*jeGg6a.<*Tؔ0qoiU'(tTUW)Fd8)y;Ip<}Wp4>.(>MjX ˼,j *\=|wWZ͡Ԇ)k^g !vendstream endobj 222 0 obj << /Filter /FlateDecode /Length 2995 >> stream xZKo3F~<+h~p8>8YHKaETutU.iQ XUu|,Fy,_󣟏d=.֛oNAZ(" Q{w|9qx0RAp:`̰a $︓;)?Fv"w$ސ"ۮ@ q$QɋEѯ񄗣"N] J lTiL-,հq3'@Y.R#M>dC5iiFmk_E3m ڵn3q2BY`Rx YK!_u<^J=ZU`:,DNmGgL.LOB[pt %Xs!9"<$#BȓNrXA$)Qx(UM.KׇzxثגxA+xNM{"[lN] i wRˈ!")fz/`yyMk{XeC]!i܄esE`uH0R{mQGk$֭"RTr9$X!q5ރh Nى5vQ/P5h)0ÒZ~2XvFx;htȆXa /`Y hrHWf`[BEjKzX,땪g0:F-/|*>-b p?Rs<@ddiaKϖ[v+kJPBC@פ 6oc,kuO`.ir a5}} 껮NYvK+D5YXG)g@ӥ$4=2S.մ Eh)J-A=gly:UZx-O[K:kkW"(> !Dw"l&!>ombi\l!knC6* xpmS*T:ȦM1q[ iNDHBa_@d5˲.vNr{O]2owJQ<s@f'+Y a`uB6Kulk(bOmtQFd<9>S4[h$aG&>~*1ajc>mXgMydjz%jAi\rTr$fblϊ~/k BLā:w| uF UсI4ʪ;Ӽ6}nbgU1Q6 YZ1 xg™dNNi &[~,]Jfy~^$Ls8VsJa>"oya&Q0C サd4rO(DViUx/t)`87nj zWAt8O:_ Qdٚٳ?i */_C vP)lmq !GZ%Ԫ hʲ rfSm]ax})Odٗyj]> 9ʼ ]Zx h-;j 0duN7ə[Qm+3|Y5\%/̰`gLʏ9׮)fyYZ"g,wJ+ H{䪚nBl/tߦ$u:uc@ \HVU2i¾i9[FpHhǟ;3_.][t代g?mw+`Fc7얮,Q6tWص#1늧|ݲBw[4*h]%ûk+>'x]6ER(V$^v ^sȢ¿}  @W4z]wC~xusosb}I*Q[tuc)s)榫%5҄hv̲S}}ꍗUmC{tdRb.}Qׅ>#؝LX,I~(Œh+V]g@N?a5pk2X;߅ j^w:8J@KcdSvP`h;ݳF;ڴb`n`ߺ_aۧ0'/'ٹbӞ~qi7MŁ=W*[࿢'qY|m^x%@庝G8q^* ع=yk.>7rT"Q(w;/tUMh>)Ss{nb'EMt4~>zz#=璢+whK;)"/z '2N1 c[..Z]q{*]1zʩyĭ䃧D?[:F`&LqQ7a% wi;qZko'G endstream endobj 223 0 obj << /Filter /FlateDecode /Length 151 >> stream x31ӳP0P0T06P0P05WH1230!U`aS027i`9'O.}O_T.p .}*.}gC.}h\nn@n.P9?47XΎEAmGTa?ߠ pS! B)endstream endobj 224 0 obj << /Filter /FlateDecode /Length 160 >> stream x]O1 y@BvX%C1C2 tpw'y?\gG:ikD&X+@[L 7ޟ@fOq>UkZBMĺ1R :EV,C\ H.I.` >l`_@Siendstream endobj 225 0 obj << /Filter /FlateDecode /Length 4367 >> stream x[IoӆL"k_d8@$ @lެFE 94IIֿ[^TIIN fu-oҿA*)O./_'=>ɐUևǯ}=66㋃V0/opS'עRyux>Jܛ:m OWjC4sm9<Z^M}ʼe.g^ڝ.{J:HtSݡ%u qҩ!42ʜf8鞂$D|bYwνTʲ;O&*Otهkk ~7.('DmtW]axᓏխ/l/V#?_*#{TeGJ_0|d״Ɨ&Q>|??Jg/VD*G=JGIC&7U0dl4>{yx}qz d @@x`0 &$,NyjpJH!z9ʜ7d8,JmvC`lH@fN9Z]=H+mhT,'X׸ HK ʜSc:0RD d 򬧳i D'3jd=T4;dlma:u u:'K<4Xmϙ (r)hMH)HʕF9TԠ}6H+\LK4|씣kIA@+0 Qnxhc[ i9YiL➲N%kmőyEh,g U :Fo+瀺S 6 e+G`5}9;"e4BIi"WBNY1 Xs² O >q`fgQ۴M$_w=_Czh-HȑpWG*x9 a( |DRWݜlr9 o%F9#5 a;s-; "WuXPx<W~$?Dxv2LBxjlG&0hvQ/i=kop+@ tX.QNPD"w= /'"aC[;t;!Zs墈EZEA745E8kO𬻅xMWݮt^t6H ,B*bk+䪮G]Y,ס>Mݡ`m7R==g.af`A6mS@0ͫ&.z/@01Q!\dU1uv*sshoZI~N?Wy\@ |(! rkb3A# ;1=S@d9_Uycɀ2 5XږD)o-S0qC ԁ˹cm,w98R>YRMJ^$4.m,LŔ@5Av5Į _ j AofuB."Erm=MAAV/F%gXK0DwO ;>0#@hZભr ᩁ(F7ͩ:hpM6ˁɃcS1RzSZ8$; J3Dn@WqVv}n[XPHSz7n MHQ>pڢLvžlŏaQ1e6,%uםHڢ]f2J_8)"Θ6%H?V7xg1܀6=fJ~_WcQ؍b*C 5g]Rg Ơg-9N蛩)to aA J% Tuns:v4 \; #_NooER 8ņr}~Ӻyr&C]cs~RcFnFarH!f;~[%Hsgb-=, LW,;\Ӌ a$c( -{ߘAIPdtePHu28=xz̞YK)Qt8$Pp::FHLl}єCXx ,IbqTjPrVG7/?HHMPy2¡[͚XT+&w#Rm%mt fr˝̎}tMaZ󀍪4848) W߳hl{ȵnHy(`!( w*Ffe_gYUgu!Qs> stream x\Io\IrYcTuw}X6hc`{0m%bM8"./#2+_qd5 x52/I W?|&ΟL_'GrwK _(<:~,G^ONI{wt|/FLJǵt0QzcPUxi#|YLb o໌R6F*}Q d$Vyj!W'Wh]ᣵ|cFMlZ+h"FS9GI]m&l0‹`SiaÕPYEV6 0I,5h<#{:>[aWԼ5RsK͓7%ʖq~ p ZNLV(|9LjnyB[j掚W|Al5agMþWR9)C\8H`\{ bNt/|j{8Gm 1b=r _L_Y߷&% !q,' LZǪZ5pKrH3A,MI˖t`BvWyl;#=eBSj@Fr=~H`])z%tRV@=!Cs 7t`c@ڠ=tt,A{{Q3Asg/aky{ mNKQ{wi)G/a@Bn=IQj!Fg*4 G[(\K7DdL)/!A َgo+mn0ty+|Q^CSt( \́l]"S#di.cG0 ˶(+ꂉa J&LQ.}w[p.NlP^PN:hY:hPȢUD tLNzڕ  }UWlVJkJ#D[My/s2<7-Ϊ7Fţ8$[bԤ`ب;_Lf93%Wی0neF^iО3>f+KoCc.s˕;xTso4т [[kuXjzPQP8Zjn"+R5#r2c#s5#1FtڛoY@o^ê2M./14%%na셽P2bT^aE> s&\;U[|vq<{\]|9N.gvj5χKawԼvS=-"\*ZEA̗/&] 9,fa^fA ȑf.LY,Z|ΖI&h4ܫ6>yo ;"OA3oݢ c;ͻ^w:/p+$J4# >Ya9^Q4F+p㜴 ҍ5g a]3.أjZbUXGDDwW(6;jߝ6OrP=0 Y`,oN"AjyO85c  :D=N׹:g?k. ]װߴ~0=σc$W88@@z i{B(ruw[k C݋aRٍ}Uټ_`d.hp6}pWsn{ۦ-MG5&׷ "SfmDS gޒWcu>d`[siBPKf[9J$-ꆽ@if>;8Vf#0]Θ9;<[jɜL[j掚W|I<[j~e;[7w,y3lse^S:cd{}}Y jNYHV5~| hF"ugRmUf,lISYjk@ٸJU4b4;VK![qu Κv2ZWOvF-`$K함p\- %5)._id7je*z5SXey+(=ل9u`-`- !젵O:X_.8;.z MD`Dz#?\(m1TJ>Hr{RyCZ/oB2L3?sӟ-☵]OXs/1`zߔp,H>+RX̑ \ mIŻZJ~M^2溬zygl:cB[)yZdЙT0>i^+lf,bt/틊Aa+~v{VґO8՞fTuHqOڔIxX&WK xt8Y[s}K. 毨NXe[Qr%d&MĥL^U7g̹8%uf  .{BXhK^ f HY W۬/z9dzwx:w=l^mƕXH2RmVVЛ7 t@F7X ,|?DVRA=@IΦ%쵐MF/լbxU4Uۢ^(jdd3TNր n!(C2b0v-][4&t^|6=k8CJ J3Mà1_ڴͶ:,T6Or"iu5gM1Z1"Y-Ze[گmKoZ9KD䷰>O ȲȷэH<NPaɞ4g~뛗N<ɡu (yet}>WsO ,Ŭ njT_j4G z DߎbʌM_W:oC&kJŧZi+}46w/^u·igAQ\X,ٓw)%JftE+aoaABwGtU=bwBiK]e?+$;>"\w\]6ob}C"w!)Z9qXHC`5o> cxx1w6H&VTl~]8M:Бg{GrMָFpk2@2LgjXQN}ױC٥yLx}0:%i8X!(1X״1# FΆW*=28EnkmGKIb)DVJ5%i-uhlW.ax[Q~[Zs&ӠMۓʫMzN _0WAL}7U7}[az!s^qPS=$VVqIC /{ZjJ0:VWÛa3HI$r(>b=_$Z뙹μ !% _ygS|VIUx̶'O 'lp )̢46` .hl&^}\SWacؼ7VbK͋a q\C.Sy_Rɵ[iV!r؏l~ϩI΂xLڅ\wJ7E ΚkILU>;~pڟ-NlaIxFlGJ]0#>;mg6~6jchL~絩3Sו#ޏ/xv|&?`h:ܳڧeFb`T&w[n`]@ _Њ1;O?,rҿӐ }5iiOvӭm0n+1gL~endstream endobj 227 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 434 >> stream xcd`ab`dddwt1U~H3a!SG$k7s7*BcG``fd/mq/,L(QHT04Q020TpM-LNSM,HM,rr3SK*4l2JJ s4u3K2RSRSJsS nӃP%E )Ey  L,~tk:s2n.wIȋ&Uevp]i> stream xcd`ab`ddpt24U~H3a!Ïnn?T'~%XP_PYQ`hii`d``ZXX('gT*hdX뗗%i(gd(((%*@s JKR|SR+"Y޼zƍ_cU"9kmX@::9~ Ϫ=e+]^cڐt߲5~鹙ݒm%O{ ªYiyQa2Nٰm %+ts|:̚v<ܤnʹ80e^N=U't/_W5G~Mf[2s}?O{ endstream endobj 229 0 obj << /Filter /FlateDecode /Length 205 >> stream x]n <oFI*EZM^8 ez>W⢫2/ZtzH4Ťj>twUuʤ 읪O跫zkrGMB@Eɿ=u[U25aQ88# MP0m1ڡI?y(Y Ev 9ZL> stream xmlSemK{9_b "ve!!3è D$jwb_ioۭ![iݮ/m/#n5[]ֱcP4Ѡ&Hߟ[xYW?<9y?I(dISg^wNK8Y3BA k<~PI Nאb2s^C3>Ukc:b;n=gfzNJl)rCCfszGt^l-yn;t9s\og::vcLsu;.9Ȟmz<bn T6JAIH d$LTlIi(?H^ۃi @+CO(Fq {Ѝ5,-zcCKh;R@!nUvo$ENuJjmm8>UFڂ8x_-Ld&X5r @ BQqOn$ )Y |:(IL>@|)ٶ)~VόcȠ$sG^? ǠF3/WLg'}pU_FӍ+%![ʏi(G6mh,Dendstream endobj 231 0 obj << /Filter /FlateDecode /Length 737 >> stream xN@~=`W]HJzp!P: I(kL&v3#RX Y8.U2,nl+[^z%%,|"Nbȋ0|~>3ƇCx E|qRp \G8do#ϝQ^Ga=:CwѺ|O xEq16މS>  `8 V/T涌jw]Z p kŔZ TOˤ$Lכ˹*A'Rm*hX SUM:h==vSSΞ-얳;gfuoPXԲ44rvow=\+Mm,kj{\]IWVv-uY$c4eU*h3㘸wy yĞ| U`H\U.e)KbjjwVӳEjM*9Nڛ_Q6`D;{8( ß=0:֗t= ڻ2t]599g!+9Z%Cf;]]wk8c5"ܜN_9*bʺ'*Qۤ'̽(>lʜ-|)wHvJ|iFh[|-/~LWJ/)D) p/RNx1HdhOvQ-xo@Bendstream endobj 232 0 obj << /Filter /FlateDecode /Length 7001 >> stream x=Muw-A_h6юlbG 8#- KJd~}Gu{ݳ|fOuիWŴ7?yhy#Co/_O^]ѯ2 TGqHMׯi0D?xO4ݷo/>Mq~J+o}MB3?xNNQͻǩG6g7Z}<<`aK1]^ٴJãG>i&Ѣp~?ٔf0LӴ+MY $4)MPd)7펯.s{Gp&=%oK)&ӡbp_w@;@ZO.(лG"49vqT/d """dNމ)(NE啍c"s$9KdLi!խ)-,C7u2 p:öc!A/ / 8-Rؽ&8Ifw ;)g;ȃ '1 6r0%K zxCr$f$*ș ^zںj3OA Hw`*`AXV4Q8h'HL ad-Ϻz7JW3f)369? ƨp5+\E*Il5p 2-/FYd}mFJ!$8>խx0UCdK4$*]RPnȕrdl*hVIz>x)~*DJk ;S(I[p+vmw6dKd=S%6Mk0fjdFvO_tɰ92AN󦛀ǁp+5^@myB5 eDxFKU- ={B JAO%0ĎH.K*Y@ΘrAEUej#*G3ކ#! z7}ӟ䕳'B344s;H,#} EwU_1xbu[\q&zMFq[46u3T~;| fT9'cm2$L:v0Im=͢Gpu>;#-*uaVF CW?AZboQ(˳-d;jXJ0D8/w VLOɎ"@đ^|Dax,0yxgKyr+z3sVT^YtG>/%^@0:@Op(b"OطUdk2t`H C6vtXg[@x$၂d#E#(o.I%PՌfdEFjT5"+~p/z.X]M+jX OKL.[2=%%n08 )jgR7D#.ۗ:hO*N Ppt mW@6TU Be#A[gyf$.n teGY uc:bbDMet"V @L J3VuEɧ#}j]켑`{=Ɣ(P7ƀz3fbS {">FOraNp@ЉW Bs Kgt:lq u$-t"WhQNVf}9t:+0ט# NPxrⴤ]cF OvNKw:Ly?*[yA'O:n~,OyZף_2|_$}|. *X;1 4^Z23Ѷҍ#CkW5-<%z".&Bv+Hf$c͵> ΝVY.Ht;8 b qiFVq_+ہSX:K32~Ef!ZGY*'/t<3q+'Rv#1 <m Rƾ[7 6r=TP1 KwyXQ3;JAOe0HƗTym5OqCw9]ħ4+עr@̢`T_眻HNQl59G|ZH+Si` 5Lquq u4Z " h`5JU1bg Oi2:&Q[Q8)=΃[ @dp+=fez6?9jML/O)d9ksUfNgZq_?L^f/`1WZU$``8 Wq$LI(POx)0̵ɇ*QEZ+=P['x)1`M1VKW%A&H(Qq*CgМtܘ4-"( yqY*s 2T=+S%Öh.C {[yAJ(Ja_\ڬ#ʭ=j9LvдQ6Ks*zʖ4 &)Z݆`e,7BV#<~o7}i i{Ї2CaVc'>ӅUFa72sLYyQiJfU2 /;i XX6NRm8)H1T?4GE3$l'G>r`Z*~Јym/>!u_v+!A"/KL<噋q\AP\ Z*Ғn]/R0 oPb6(Ō cmvT%Ne-t}qxhW$9#m!0$E$#ɍPy WFIY+ijANV&Iq\YՒ?O㇠<%gE8MԊلh}Tdf' a7ߌ=}Wh:F2WJp SċJV{k,4Zj^qՆ?`|5A%2䠃Ëj&氰ibNS1~feC[rțNjnD/,QېXvFzKte PM߄-qWr_ e6UL<VT?FF)+ʕBHgD4xg(#[ޙoQwf6eHXc1.knLf.lfESY\-$ f؆"- ׯEצ\)iN.&{6ʬpMm YgEyn:%|+U(=XӨ2`DC7 .3{ޫ͡3g:/u~28CjX!,&pptdHlJɞ噅}pf]͸h~ڸz$kjIOS7TPYt4Js߲Utm`*9ǫLsVkybKQ*L%R!f >jp,#$3n1VC_):c76;w<,V#Ep[7ß{E]?Oԇۃ>$-,5Ul鰧 nd@uגt)f~хA.}sBE`$Y0&mAo;Oo&m}; U\W,ZR&kY, U'BDܓGK'8oXg|{gYylDXj .iĬy4Scu#S"%%]nҢMc{9}(Rd +4]g* N8•z7DCԺjއiR`!X ɱj Q:T5 _P QrO5O2 Ҹvk6۱tqayA%,G;i0Xq] Tw[k_@e zJ`D`,k;WνX& QpS-f⦃.2?HR~Gh>l[r2H!2[2sZn} Њ6*y_ԉT鮳RYH*CHvA󲭭bclڸZVUJ2G%s`,MgO<7^jY>_\.P0˅s7+4 3ow3vuڞ(AN xYX3?S"#xܲWu|J'XQx>]D3e)/uGTDņѾhNJ$c (;滚8.:j H}TE0$ U2p <efkƄ4n#Réؖ㏮j('.OXՃ eE xЄƊTobaY^V06 K.Ӿ Vv$xjL%P[ݦMK̅MGsv7rE9X ( |2lt;X&aE l8A5NuZy3]\R+jCfrwD>rJ%Pm!t_ZOd~ҳ)Kv*bWbvH; t_!,s 9/"U j`Wm_H1|ZdɍG:zՙ\vrq]1 _:Ep}>_[:鍧ʩS}ENMQ 1|h]8Rek}QnR4}U}km ,Wn)|DsDz7s]݁R crر#uNl0f >ahq^fF ~2~V;u ._ԻLD{Y`dK[B/B.G 'kѹWTSͿxYדaUת "6/n!^'Fѯj嵜a\ekvދ .X9:r2eOeΌm'gLv<ΗSrV3zej,N@u =/ bQ\ a{"iB"`N~$01u*oiFmϗܓ#|8 חV&nۭufS 8R|^IBy!$@2&ƨIWTYxn:R/"@ůt(zȍ  i4=:w>(Ƈvzï5;Ej(L-sa$'hߜs݄_N?} JMlt˓ǚ<I+c|ȧ8]k1ݭb ⥏9j߱w~Gendstream endobj 233 0 obj << /Filter /FlateDecode /Length 4561 >> stream x[[odG~wo $^ dN~ Q" $$f=^qB(&SBFDmPrj<1A60te˕09 ~8h.ڊ0>!;kldP4u]:>Nt:#hs 'EuۛYrY2խ,I`dU+NЉ zuQ1BmI{p<  +v~jP+!s{B:OAAs$KVQɱn2 z.fw{oc0`eQhm\Z 8B)<":@ ᳁s\G`sF*ˬdC(\_I7 ۸i-`ZC(}`aYD-:Eoj{znA}Dߊ=?=ek!4C&U )E bgLގ Ĝ9m%xNO>M*:rWCt@QX*E)i61Ȗ\q tI <ܡmz8r)?7+GlDmQ 7ZC8(:vP/Qn1-Šrv$@WpM, -@m"r^O\5`ZW #Qo$#m( 0 7M6j2vHn0H~ui4q S)IvԦ5nJ4Ѓ|UEokVcSL%óِM1gꦨQ'^@ՋI] }Ժ)$rr!$1=!#R*regBT4C#:c7'Gdxa$p 6F+0Rx=HQܔ,P@ qD]ȅ{/xEI `]Ngģ* \}NzGj9Pabgיp;K:gr_ކBh^3/k;Z0eܼzYn\f!Z|2hւmKuH v.%7ӫ5zjј=:BU:!YゞbT.@ T+I;/hP:T^_2m]i^vjaҤQvY-7?(5ICVr]h[|(6k>6ٳ,̻\4&KFÃXYO*S[%t+.mvd*`A |3"|xmb .q%jóxҮVb<<:h3]ziBeuGtl-4?(P%m O;P TFFsIhv򲯽y֙i6_Jqs31w8 I f!C|f ')' >80v'k9f/b/G`1X#5aLc=7#p=9W瞒Vc~dttHT(0c|߇UXHiJnpUX y9C3CJxK]cu)TEq{|碭rg'j2^Sqp<\2x6v-xb YPUH;\\I:^PJɧkq[`ʓCN0#0խ\mj$Hki!]y7/I]r`fyACWObjgr;.F_+%Wϻn¦7T*;Sk3cR@eQ'zB`6JtrwFļ~^!~LGz_PP?鶄]OzQ9"fr|94%h @mh?D(tbӟ^D sav˽blM#CuKif™"QˏJ=p~J jk}"$exGjErgv)[U+]~"G^Pti^o\d]86Z'7yDkoo.W"9ic!fLiG8?q%|yۡ-g ?ȋh(ުLJs(M^)i3z1k8zPi=uHC3>R"GR{OjUkeaGeMO$7MԈ0(A0Ļ Q0Yԗ|Ua.U+ؑ4ǁ>{mLM~868Vj+=*7Kջx&,faYx|Z=?#~GZmTK ȕ4B2,#nendstream endobj 234 0 obj << /Filter /FlateDecode /Length 3646 >> stream x[Io\3$3aECrh(Y@ߞZuWI$K~UuUS5S?:}vÉw'02e O}Bpz~{3sy}#OI24ʫW\Y78Ӊ'vvM#b8ᮑauݶl]#//~২2km'9=<("q_.'FC?Pg bg|>юX7خvȄlwixB!W|-'\W)*BbDBW QKLxh n$Y'ܷP2[ SoL䮑O}~Ն|1f7[aia8W@)F#Ô T?ye3K,))ga7[Ggk5yB4Sb&)܂iلЁ9 S tyl,W8G}t Sv }AS`(ϱ5lxmҌN\>rbΫV0EwgbJ)7b`SaͮF;hm?ҡtMPat+?Q Lr4V'y #E)9y2|ŜռI3<&$Ml3 꼮Un2}/gCe|6uf\Iڠ G.lHFnHWgރiòw[3ӄO )w9)`4nhUJA%kP"zl06l`Gft,@A(3p1hZ;lUE ) ]`d0-mWU`EXkf^d3 b0HX#(`IݍU؋h_I1,_=88;}+07uhm#?i [ ni#jd-oNfH~O$MCfVm`BP< o3 j \4ufGʣ3]y!Es8g8GyNuo-,98 -UQO@2) ^ؘedj2pGi:pu=e 6+o?j6Vum~_Βf^nVL׫_,עrz 7*6Z3{3(liY/W~+wm BېI>7K'ࠧ*_ 2*jc B5j=Ք9}ɘeӽ D2GL"InQz[G_qb`?Oe<@юcH(Ze&1a7dKyJ:(z\Ĩ=0aڡbH* ҍChy-(3 - qc\QBSVCg)ҟތ%0R`,Y`,/[ h] MX@z+?=_d6tJ`:AVE^r#sɜ;Boo.WԥpӺ6CXZIdԻfZa~̉H*e1ˀ9{*]GI]-Fmx4ܲF cz]Wb sY feظIcl2 %7l '%/SĴIK\ \4e;Qrh( 7b兺KX3)G5Q2"&;&#FYLV%f9AvY$=|6Gl~qN*˱ϻ%k~cu\uLb K>|KV_nyQ.zaƳQ]}] A{YwrgʖJ?FeN+AV9Y~Kҟʅ|KMDwK`tr9.8(>H5|q׺;D WcN wuo}1zc"\f5u<,+ ,ͯP쒌6N,\:<*Mk{)#L$AEeQܚX} F_hx=>T Xݴٝˬf8A.=t8/4K+:w]}F-B{ [\5h p]&Xl 8y€Eax 2^6y/ AE>_(8uWinQ=vEL7*~{}|zqP+Iz`4JN6򦑗Cx1U9S>|Y8'ej245RD Nئ r΄0`swyK,}%(ϸQH}Gոo \^rR] UYwIt:sިQ'o!< `VlZ= ?逻߆r]4g0O/>d{vo]#96s :?"dĸj>;'tendstream endobj 235 0 obj << /Filter /FlateDecode /Length 4368 >> stream xn$;C5 @6#}]iH3K=*6YaV1|p-..Vq?<Wpt/1(^'кE}wG_߯Ĩv Vk1W[!X !-F [e>X J!d&geǔ$Ήe[54v4USyhZ'W{=m]a5 gc~UYlpژy >)o3cdc4 i6WtԔ-t#$I1w@`+)O<8{]G \Mϻ*U?v}a&̺1z|}dȾY!!Ru/AMYMj.,8Mj5Y[19ll nyv[*Ҷ.nD}Օf"v݃1"t'\ut͉PDe)t4TQtFoW3WK.gp.)ZKٍbѵ^XG?`"cJw#Ĝ0kk)iQ9<}?+rdgYWNƅMf{^AvMr"(1dD4T0V #I}\[M[8.L-K.2_1U6`oaEAr%K*+h8H/ӽ_Gϣt=]Lp?OmL7/?m"r#fC/3nrdQ6Tw:>Aп i XXs% nn~q!CҲy0컐&yx y`cJ7\Y 3|QǴ%fnrt['lx;vGV;>q0'b45k{!h*Y+Kn P*.x,P0eHϛ:̲˶)=q1`oY󎆅 G\Qf&;b6['qQs|-eYs{#koRb2˧ϦYύIZKk#<&΁~xFj&Ick.־[X{-ciCFr+ S=d[V1ۀ<憖äʦm+jީQ`җ=ag] #ׂe`_M8i'IJ^B ShlSn:|Va l~l{o>WSjuՑjyىIRbRkߌc/0'd~.:oM.=eգ>_Tuk'}|s/*07]lRV{9al\d׫_\:}X 9m)ʠ KSv1t[39@C&EC/iڸ(-o*9wE@Mo7# -Ӯ9Wn9gǹ9'QuMQҥ6EM~LfyWWg$ӥeXN\k,0#,C#Ymg7;aw"os9LoI7݈+݌9)! q/1~)uQ( Da^?8!Cµ†&8Q+HA5 SybI\4iU9mfXh.kDBʄ$.]KxHLN 5Þ*/kOp>!CEﻛ0XMTPS $vE5aOhW)c,A7lcQ>ک-"6H/~Up^VEy_~9vfUtwAzf>mm;mBsW:W6 { &\UYVm<7iZ& TLAbLGZ}w߿Igeendstream endobj 236 0 obj << /Filter /FlateDecode /Length 9248 >> stream x}mq %p|{=k4LE9`ˑH!%+#pO\_Wս !̹]޿x>x˧_<}/$<_r}S؏cd}l}۷?yÏT<=ċĝ3=,}<1?Ϟjy>gv 蝏>н~Wfx3]e轨|J=\%#WG;?hS:WI<}{LԦѿ{>>wy<}GO>w񍏾'?_~OϘD~ͧ|??wG࿿_{~C 648M֖g0 Ҋ̼ n8 +2ZkwL I裣uM9hut>R[ԣٖi)#,zCPa DTpCȐ_9~\eHBGۨ\/Z Q$!h!)dvd˄,e=]W`%#~ N/`!nyR=6ds k0lRJ!PIU8NHuT'!ʰ 6HAΐ dktS ҵDSae|Ȅ]mCR:CFKch0$ @ 1`1u 4P`)8U:k>t b>Í.f~љOHti)#5Z|AZDM 7MZy6keΑW[teRgeߴRM;Ym!i*R# Ct\;i6`wpn$UxSfZDڊRhVĔ48m6:JAP]6H#p 5p6):4rw9Һѕ&i)CbJAjJ:ySങPh2ׂ,=Da"3\}t7,%ղoryIMΐSA,9uK"K4m s+gׅ 5ޜ wP\ 4#=-XCryCe߻ǚ6SRVm>/7D!Q}$c19sbRܧY9}ݬ,n[[ Hop^O 1mboN@xM7LV0GfGa2 Ĉ :(WaF6 MWcӯڗ Z' B"!Xiu_UW=&+ /:kd]z M=#̏=}n/e] $AjAMjVu[[jDzj߻L`U)ͼG77X!R PVa0Bgsf̘eϔ4QLDW!h5ΐJ Tږ lp%Ij0`bD<2[*5/b6sup6-Ĕ.dS`$-@ 6ɋȊHk4\"SȬCq!8"|h0D; #.Qfվ4m&$Epp<#kh;nv%I*P\Iba0kSRVyG^@^QfCAj !3\iؕ2AZ"\1d:_6L0C/2J`H!ck{cFk7] D&RY<ҽZ[e4`хp€INN؎tiD[6̿KWҞtɂp#c#t}l1*npH'SI[)Gw,taFͪ.mYku ; A pNʺr 8K˄`J|2 .ŲؗJ} VS2yxfr=7 58m69k]i]x%5p(zv*SD b# 9g~ɍiMCAfBC2*Reu!$GWpEasR p8 O)Lz ӎ)ѪM\Cf))5 h4ыᆃ|y''ۆgzꅝfgﭜsY&n!蘤a^5hn`Ǔ6z$paV,=,N=4o%Tt'ϛ-Q]Ӵ) AZ[y75ppG`کɓg4;=NЅtsҺJ:u%2KC;r`IdS0P#a.{:W9zt1rW9E7 Ts‚:tX. ڔ/9E7j\4H#l8fd75pրSe|~ql6Jl)|m~b3zֲ4,wӃ`a·~.2$~zxhk!Ft`}1NIrxY rJ&)lY@ 9/rʧd{iANp9%=)<'d-eqF ^QYsC{MTOXmBƸЇMh+8e,?uHyr:y5K3^I_ tJ)rD/NaD@,ʬAS8]׭~ @9! -e - ܅pX؋C*K+ X "˵7Ċ] GgI4Ě!h!)Ӥ;4#I "$eh0l nӠ`{ F.lft$Nr `]Ci@  X#L25P2cʺqЃ3]%&. 4Wt^:2WP@FB} C'=>>:GP박ϔ5j56z (&ѭR3ڰ̠!eA^{n8 Ƶan朢%]1V4av*Pb$kRCf)ȑ G4[`P^{n8jg]6Hk.75pe0a#l:2J{<ъ(|I4CCf)|QSP1. Fn.{o.t3yX7X!A]Cfc- N`߇`eecqvd]QBm!MRWAݤ]"\d{$坃{) {9iv2&18i9v]ACC܄ӊI %Gj0d?KW1LB85)`.тIK`@IҀ;'OK>Z+Փz:2 \`u[ lwZ1qvI/X.@==gXV'rp n { vpۺ ^V+=qףS-f34H<`kwS (iNb\y\S5:Mk #m˽Xcðu 38}ZC̰ G]E ` 6H\@!SC&Hj]7\ | C6Fm-HfA)M ױK`Q6VmvF'!N/( ٰ{9۰9bpd{jIv;e4$Hhu. Rd`&(&n6Ks%Epqhǂ#s׶pɰՈ[5rC4;} ,Q„i'arn_0a ̥pml!P7TF(SIZXJcr`̰[ށQ"6d8Qe'N\w0;N xO|7v܅paG`_Ja9qxqVgL\0&yzp;S{oD.Gs@Xqbm1f^ uSHH5m6qF\Ak˂s =d 5SnxǾ0pOt׾&n%9joᎭ퉒ӎtB-a .@]s}j 69VP'SpZka`kJpqi\w{444+DVIx{wѓ@cf̩y13H3[MN2J=kL5135kL:/) Zw/YVhlI4ݧdzL?kFO-cXwaҀeD8H 7R[9GE&eL>Q SH3KCf)c 64vbO)l6zkPlzeE< <OiFө8‘afSp /d*Jji2\^+ I_ڱt"ՅK_377l԰hat$nQcaE  jկ d (lFVjگVC ɸPzM\ҘE FJ9iƋ$ pNщvhh4 Z 2gK*M#*`U1?A˖~T衠`,&2AKLRUOΆb<">7*^fUz2g.|[Ki+@,imDH P.5#,fv^YX; /U~;-+d Yj;L"L z]L:.*mO`1BdIɖ eWR"PXv6XڂIWJ6 SRE1Bi^-Y'5m6q,ѻaacx,ixk0l5ۅ5йJ} D Z˫ZKt#6HwNCΊi1KpEq'e;VUݬ ْ0CC 5[Qܫ>GDM 7m9u挩-ұ0pyi@;$9P1)l8 EHTp\α%^Yw ms v4ٴS"ɬW:!h䴡O}Vuc=l2z5p4`銕N D쭌Ռ& *@ n+gql2 ZV\6]~]CfCת-5Tۣ 1/\½t 7 ora60",<,7fY*xKOٗR8/L!iZ6Hp w v\ >7X`yt5vT}҇2AzC . Ԙ|38;lwŜs9heHcQ28M"8g=y?ٸ0@uo0Ut4t=36Hp 5poHSM-'Rv汞pϒ*ceif&SC۝a%KpáЦOѴӒڣ"sA8YŨ̧mA  m9ѵ  !@ PٯXp<N{yjQbx.PNAG9dz ha1JeK_68^VS\>~58M NR8@ɛWo6JswAGMppO[Z{$f<6HA;jԀs0REO~A`z˧"ٙYLw0#f :\|OlCjAQ [1}kz? VXKAa>D,.kHV/ڹ`@"%:A>56^{I 7e㈶Maa[縱΍[+4Df [x2uG0s&Ќs 7uc`%"e\2&|犌ɨm}H}jhc #]\ {:o~q2B=m9q2kP5g!%)E xxï޾˸}x7?AޓX5ßgiG?DdA[S2oʨ1Sw:]v)k7?޳KqItR֑o^`-9F{;惪8uTg"-K\ۛC2 $wt&dm?9eU$]?5}}7uaP䟻X .<-/K#Z5K;+/ `̱'FD-<+V>M~_: M'gK@j$}9)79T:Ǖs.RC)r.RR\h0~9đ\KxSRۂ߾; L*ρ}џ1ΪS[sL_iLWr1G;+1'\^sTрTl]G^&x E 9ÉUҒrE ET5`Hs†9)ޤJo5*< /[}5$koykh~"5׌C!暿F͵ δҰ)*d=Yؽ2|eل 9gp9=؄6Jj:0uifΜ̊!*]ojOz [Kh9oKVendstream endobj 237 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 128 /Predictor 15 >> /Filter /FlateDecode /Height 128 /Subtype /Image /Width 128 /Length 2068 >> stream xz,;L/]*p8ML&(t;z~-JkyPr$ƮkKTUmT^}}}4 *$ P14W([y:oxa  (5Bඒ6*_ ?:Jb?voC@`6Duʼt# +ILK IU{`7i ѷӣNT.&S1!)> ČnuH:j =  i Q(qR]}9?qXP ȿ`B9}ZSI3NrԿgܿ"ք\,M}{NAG1Ҵ::pp|2&Yd\ 2r|o.02"@m`Eid?@Tuq60(qKRo\_yM^qȶ^/<`ԹHPkQCf5ksLHsWɜ%s22[ F?0z "MRHv0HT:mI '/ [4?_^@ ؒBlrƥ< kGET]@4*.# j HlW뼋k$HуrWZs"R ML(@4#$/<Dj޴i` l%}ŵ>U9iǰ;)c2nX2 "۝\@2qG~+ڪC@ mr(]!]eSpY2ANnsOPɼ MU=F!;6TUl 2l *&9֬6ք`"Kn@N|)h`\X-Pq3sG6怚WDxi#eE `Ǣ) -aefcᕏ `:k-4Xb0Y`Ƀ<x1%;qdid0#܏07w /Ky 4e,.4w =6a>`2H{ɓ/;OPzY@d" پ"<`[AB@4rTy ѲTzZx81`yc`vH`KӭO5&w TNmE_&Е0Zi>dž!$l_ ke@q›wX[TC1Imo Udn#C܍| Ȝஞ@[`ؔFT Ћf@Û MFT;r(rXSѬh  YH;r@y7W:DNv逴 WV?iؐEB:G` U5p@i^ bI꫍@6>t4#STgU$j5_] u X0$3Lm E&ap$js0u}Y⅀tJ{ ojj$rE "P0 eVkmNdO*$7;~HJv&iE_4yǷ*ÛSe9Mcy?V0't6w[7V8X0[|f`eR350IZ = " ؜y"|-RE~]YmۏQZe7Q`(k!]%mK+7^|pUHc;:ʭl+&ttҥ #k?r|endstream endobj 238 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 128 /Predictor 15 >> /Filter /FlateDecode /Height 128 /Subtype /Image /Width 128 /Length 1863 >> stream x흋r EKOÝN :L=z^ fT̮KAd1:GWt`v.p> NpkRI T[gKZ -KѼI<9,g=6'^obO!kbc 5@ĠUx3ure0|4}u@ O#a,AVb F9f6 t i%|0@9 m\-,VoR]:6< הTl0 ;1ٵXbZw 4!TkW6w.OH;?t kp !h9`5`ic  {{;PgDFNg\>q: :3;Ix(rumjtp8_V6SeE{M5 jx$d@+Vײw O=p߯R㑁K5 >CYcƶ$7$b*x`V5VA}cx0p#Ywq@AD(p|H *H1c  ^ap2˖&^S[ψ{brXbn>@jPvU{P}7@o@Ojꅬ.k5%ƥ <ʼOdȑG lQ 12Ӝpo'> @ `UVVCvw<26q='&w% mY@1mD~tUS{ @KPH`4ScJ¨@6w!xnqo^*:@̖կZqv֬rwAZ+j.R/SD X^5.땠)Sޟ0HyƓJf7 ;L-[PC1 mGX>+l Nrm !oW@ݴxGeC9:bT) @Vv`Np UqRvԧ?O-@MJ+HY9}@Mb D5V(D/G* )t@]P%_ *?8L13 R?iUs:`X3ÙUG7HrTjl;iFeX,ԡyK|#82IJt.6kau!:V˝MYýhn[-FRp(7 Y6nzjD^;Ҷ_ IQ`(5T\s_?d0+/a@ q'1= Eഔq\6"^^jתH`T7A m|nuH @qJ=غp ˼6hCݞ-@n%(͌p# ZC@ zґfrAS+ ;w_]3jdejXr/Gmb% Z-B]{X|W yZkufxb j-A܇`dJTTw`hգ*DO3Ƚ5@; }.ʆ,ե7[@i02V| ߊp:V+wcR J{9// +A1 2|jendstream endobj 239 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 128 /Predictor 15 >> /Filter /FlateDecode /Height 128 /Subtype /Image /Width 128 /Length 1671 >> stream xz ;󶛭(oϏ>u^H;ٮw 4.G:* \JtƃXqAj60}E {>LyCV 7ը%9p E@?ԮuJЏ>\>!@@:)HaIse $sk?2uFIiD5@5@eQ%xR7<` TcE9 o:٨U@NrߛK.^s,H /< N.ldK`-joeJb٤*$c?}2u5TEI|znT2׀3ePl,sFp0-lIlmYZpn<%8jj >SvV ].j%})0tB q b~2\Udx p=Qn~8ع/rKM uXX~…}]rDEYsxjpI817&&v% e eUn tXrU0 v*-}@euo|i kD`%X @M6 4@l6ȸ=aHFc*PojO)AǯYJc/±@ǫHNVsM`ɾdCMbF En` "[f +J#%@^o>Wy =*\|dendstream endobj 240 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 128 /Predictor 15 >> /Filter /FlateDecode /Height 128 /Subtype /Image /Width 128 /Length 6306 >> stream x]$[?(((>uED\POEe5 @܇;]ޚ9f~7hjz{^߭GWavիۍ-knܸmnqaofl8G݈+NnlO>==N-^08>p8lۙ8l_@fj[X&|O r4FዧAah =RCۧ6} ÆLšDL@=O:}]+WpD@P(FE٢C}pMχɐy^ɟEw_t\< ?!CS(W蕃ZpID@`/QA_hۧA ' l C,? QVYk*B& 'SuPāE?>ʁ% !|@ q^"p`^@)}DaL'dЗGP 8^ N\o p{PiAV]bO3ͪ:AѬ "pEJ\a'jҮgo eh=YO~nBb)&} $3Xbeh?BQ<(5YS`%zOZxEA@~HAS Φȸ]Ed@gcZh""c:@C6Ъ.)iOK &܈xJ][i;Aш1&@ZKTv`w}>fQsHg>;0B)\p x(: ed#"N44x#p؋? ~<Ts`qй_~Q 2y)1)kwڜйE"kqb\ 8Rn'7M$7ld( 9XfݱA+Mо+:I P&2b(sp,,t RL1A" Ϝ9C6!<+%Am " ztGP#;@B'Zl5A>k=]|>& ާzA@+:-Y+\ N E1"+-JVA|#|dOy,t6| @Pr;K??q`in@3m@B36|/h% / p)'Me%Ѡ[/"TߤX(nCBS|UX_+0GBG}`9*uX/K)Y'tBL&VkQB='>"W_]/%!lC=DOPҴ7xctѷL,%V wf$W(A{뭷 O-"R,FeÄTбaXA{-8w}WOSt%^(W3-BZ/?}֐z.?Y!d:n?>z`bn C_ k);>#M^Q;T9Pе+- ;VED9;>{^!PP:v4YgM`ߗǗzY&t/h%Ѕ (JALp#=У,a?kċ? ׷>,@+%N:8UGgwcrע_P@@_|_lIr E+fHBz]ГveD@`/,|,?ݦ_&UY 3JngLLm5cI p #a d'kk#3W 6=.v1P: ~9y`LV; KH~!1sJ')LSMdkq^4Y/_ZA0EM3W7* ǯ(ۯodw? 3&ZdnKE#BnoFyX,뺚 "b? ?$)T@?`5F$$:U6p$ p].]H+w_Faٟo~+ ] ݱn_~& hŏ-@Ŏ9O?E]2,Z(.ucr""}4éu` , 6{gM0px%98Le@MP)TlXƤ/ixǢ OmJ[?1aM@)dKbKOM@q{wY \,F{ |[n! D+b!4+վ2ov 0pD4J0}v!EB86o~fPn^ v1Qؗ@ր!d$"HHc#Nn/^/V6wD,dKҠaFhH(qg`AB$c$VDK/4 zF@՝D jɑ ay#NRMPFАE(p?/e_AL{#?#ΰůS$'-F1NAM N&-,i@3'og |!m P jGZΞl>v CSkԂ=&cDH@;<,lհXjULJ_g|쾦ڹ% @`gb7j(c$Ad4菒 ܹs1r#`-DNP#JWW#⊾rBet3g$q!9-^h Nd1 2n$ G~}. A0:P??7yj~\@pTeW>?;u"X~#*jCa6(lf/K@GSrg* z82'qjBD5A3^s.& bMY!!#hߢ z?N=ZwmY*.8Pz"Izm~(Bjb:7wuW=%`@im*[NtϏ?gfn^sj.yf;k! ,G?@)QrDlbymDAy*$:싺S$ j1o]'bQdXi!:vk]C%F?mF&\aE'fk::LkAwKd4L.h@* UBӉThG-^p-}뭷 f]YYѧvS=%[Ѭ1 _;pͧs& FCX_$gHkzUzޕIi(x"?/|GWAأ/EHt0:UPqM9of-vٞv̦}lqf`Ş0.d9g?LH (uF"%aG@`OxY-EP'ANGpM@5^^a#XMi Pu(IVdeW寢[$ #&%s=kZbo>$w&=8| @?RF璡Og}gśA祸~E6E܋`k/qv@<@S&*J2sS{M.=CQeE\ qpa'u:BO"m%b`wYoPpu[ɿh>Ҁ-ր3'mPG61,>^o޶]h]&`z 9SPǥeB(ƝVВ%LC$`."w0  rR~0:`MSkяУ&endstream endobj 241 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /Filter /DCTDecode /Height 128 /Subtype /Image /Width 128 /Length 1754 >> stream AdobedC    %,'..+'+*17F;14B4*+=S>BHJNON/;V\UL[FMNKC $$K2+2KKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKK" }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz w!1AQaq"2B #3Rbr $4%&'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz ?SJ@<ѵT6dwIceq[M8P!]]W`H4łk?j1Y~j[ +Wba]N6:&RWvjheJ7P>> stream AdobedC    %,'..+'+*17F;14B4*+=S>BHJNON/;V\UL[FMNKC $$K2+2KKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKK" }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz w!1AQaq"2B #3Rbr $4%&'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz ?WpKW%~rMojW۶MgV>aTeN?P[mOi+W[bQ@sRUr m'Xځ4jqrk]vsXPx Q5fO'<1b⣖.*^* d̘r Ѹj9bk:E,kVhMV0sҀ*EMkX8A=+Z1@Zt{q[EdڨP*h Z͹}٢Yޡ@.bߚ˸'tk9̎hALMwm`ƛn_ "$sQ2֋[J>7TmW\Ք"*hdGQDԪ jP[ȭ1YEZ6.(hik):MqQ<)͸ҾXwsP|~8w {PA%;WW.:Uy~o&q\״nB7UU;WVl1@ 0 izT ֜G,LOMy@]6sY2jwT-Z@H{X-[v8 K#E-#^RMjZbԎn(h\`u;E2I z=&[;v9@=hs޹ =j@K?iL٪qEK,5YK&&f}uyn9@$pj ҙޠLκk5օg5!&<ܱn,i&G/QO7h]{kTnhD7-Y!&[PpVl- un_-endstream endobj 243 0 obj << /Filter /FlateDecode /Length 3237 >> stream xˎG4zO Ql [ Hl=]MaOu~VF<Ϯ vgN1+`ojc՚{ ?ïݰesf]WK`lzD ٨ӰǻN*9إ8! |X-ayA>ϫy|ݝ]"•?kFvtLt˰ \ Ldf =n9VA}᚞ c̈́Id){8pp vΨgX0!#0 h%.13jImgB$p#8@Y17&~{>LY"Ih%H9Q{dYn4T+8)G~ 0L(A턂c$:iw5&%6g%}]ؘf T蔭U@8Ӑox`NDb*p׎BwܣH*.5 Mq)b pBYRYCʋ(/8(sl92 0<3Y+gh,zȸ.i"HԄnG%:Bp0C#mY^W<,m!d9uZ]dU8M'#!8|6~!veIC7$6s1[QC)I-a!f1ZC !h4 ѽ@5SnD<8I`|rV6(n5nu,6>FDs6Fp1i O+,|}i #E.a;Yɥ*:{9`隣}a`[;2,  YwVG*Zf.PK\^wG=d]U(P8aͣmW<͊+:s ^1UmrN؉ւ6i0?h`+fJP{ $𮀗S +-2bNG``(~-!ůZkXAB +]AKY]ϫ& 1O} o۲epU@:pW&.-C]K3]`T0b O|SxYSji xQN6)Pj#Ԇ3x&>lANwRLms޷^pۤd @,}(:>ZOB^-DcSJ>#KXXoQ H DM2ӑd;B]*d}Tr1m[v.JC[R)͞7OACJlA!?κ|LBlv Q#ӽ0 w\TBХھQ9;U?w?˜:qWU?) |X/ܱFG, yM hd`+qǸW 2# M-\j LH~WVkWWm%ly Z XZ a͂jSp!5'a}=) >y9>*`_pD/? [{EE ɂW@֧$Ǧw={k '-ԏnxSB RQ`a^Qʸ# u^X)*-XJeB(VZXDzLPk DJ< %oO?{^#C7[\Olֆ^i9;KίٶHt$ C\&iyk!BڭcȔʶc)(GΚerCoը 1ӐuhBbޑ+#PBK&opB5P=& z\gV@ mGbq.zũ\FO|1bt\r+v1Lq%gt\Ӑ@lD:1z#ebRj.*f%s/,l}dO-zC^5P=U(ߖ {ϼrBr9Y&n@&Sm}zvV"6c04W)UЪ]p!dLpA2>` | 8bN~Ht6ʉf ߋU'?ܥ*ȧ8ΚƸ7j5)}+)R]WO-*`kV)K<@6tju>^ L}Iendstream endobj 244 0 obj << /Filter /FlateDecode /Length 50894 >> stream xK.ˑ68Cܪ|gaHl[jᜦc\+i[LuʬX(_//˯'|/˟'z>6G[˯g_/~e~w1Y~G_wekc.3o׿ ^{ uN_.8c~+3](7?۩_[?]h-O_ s+i}qw|3jέTN^}@JMiس[~5׿ne|jWC{?F~s+o:v_iza|Fz?>2?Ni_>g}[9#]?KC9Rşn_Eg@Moϱo_3?ǟ??i~X?t_şG/_?O}'?o~;R ~o?c?(ݏ_~e>}o[<O>ZCpM/GH~u?|>?C^G~O om_5vL̕_f)c}.KN_/]Gr'g:1S/6,_?ů>6=;qcI}||a^=[_Ӿ<oڃSd/;5ɿ}_k)wWaz{BfEEyW(׿iz {ܶ{ ~ϸp>D m Z%KԎߦg܏6y>Zgfc:w^_#eo0[z^G$KxհZjYmchY2*n%>#5Qk4> NM;,S;mPi_G^KkOwqI^mM<@ ër Ic_ѥQ{+?ܒѦ.n#}׏Kܯ{ I~V]E|wn(͕4NcoS9&^FYe_Q/;ʗ+oWT}ih'd~|+z'r?*z:ާtmyf e^,]wz^_x-xג%|j.wr*M3.>ط+RoƠY{kWAG)sܽG]H~w4yDxg?_4o3Y4&Gڝ(au'9_ew;Z_rK(V d !m]Y^q~0/ïӹ#v Nm;,S;m9@{mn}׸Y7>’akJ;]Rp`H9ˬP*tNBZ6a!,.wхq}Xyyy?;p"k7M^_VL_%ڜ FgHkPSdW5}F%*_)}x ~g@7fϊgje;,S;mk|L{zݵ&ϙH2\GKhdH܎B˵ǂVK\hctvnuXG+s+e6k)k` <2gt.MdiҴNw ]6Z]3iDyX53=®DϭЖ 4c0e0`YyӯtCR4P/ ۵ x6{xoS,3kTK;t(!Kx^˫`-nGn(wTVjۥw-޶Ko\Z(ѶQڗ(E[z\F߭w#a]f`(79ո{yfKԾCV|Em&r!Vd!~WI7Mص>?0:Z]F=I_YڲfW9rZxwL,Ue|4_wFj#1Z_٧c%=e2gZޞ`-w;mw[h]ç6Gn{[XZjzt]fOص>?0">̮cO|fauޭЖݥE&-3R:"$w^E=+LSoiϊGM ؎k6Sz-Ϸ;~V»ڪ+] d?ȭįȲ=]-Ӯ]wǟntT]#eD4yr7l,5] ܏,T~z{OncP*q^Q][Qm yz-V`W~"*mD}"\w< N߀4)O"GHwt" % r";Z6Q05!jwuoP6A pRV#s2`%2e\,*A"w.,YZeLҋȢ&HDţk/NU2BDY.M"HeicģMݼ] K?$\D A[tYE:%T`ЂYv` w|mHhu|P7kTCjnRD4\^Wp R YY]nܚ2ecdCX2<\- [q;nO }‹t߹` =cMT,ؽr#F|dH]vN}[7A:;{&2-0 ҉ gLLi8Є D4|w:6#SD٠""&cjpOvl|e \1j̱N} #Y2Uv7g[G#H @e1(Rۮ\@ڭdp\-8䖃UCǴ#tO葱#H}"]d&KEds%/2el 2.i"3q6C09t:)zi\DD| Y%O8D@~ܱvin?t>~ev9+h %O]w+@;i\A$W>n~.!E?bdי4{;o'ugqn qƃq;J'r]ݤЀtq>. Blnw|ݥ\V8 Sy5;U(+ɭM)ӹ C07Y;~lH782\J;-rs) HRFeoWLrgY|L`18vtNAkho Ib}I_PzvFDlCo!$G Pj}ԓ*V- ]&Gۑzp;}E1O'YWi}$Fc*C~y3>EOsII@ dFꔢ#3M;}qMHUї u>[D /L2 tKr=%(:qrtJ#*0tQ$~˒ VpT|mE Q阡iD B!҅$:2bS3{n%2gU[){|_a<|~*hkID]Q|hya8d73'fפ(t>Ծ MJW]}M,31S=.8g}uْHӉ7d3Gciv8 o=c wul=9B/ [=ߋ@(Biwjsi㷪y·6eĻ4 0F1+cތMM9nR){mE6m8{3^٦_ 5i>M@ORelߋfә-W1B`y_ڜ|iĬ{^˧QN_sm7ڎ)Hю;~g{2m.2\16po/"fp^sD+q;!앦ēΡy:9;[N0 pg6jt 3qv?*l809+.ĒL3A N{ONXHH$-7 FyM@- 67@{ +ߺi;m,ˍ櫧 Le];Ef3s֕`jɎS^Ih*6aݍ  b&#5Gd}펗{,g0V==LS}}‘* ƪiJg&R DXUcAkc? umZaSUbzT#`:^,+m\tr^[$l|lG nl]^^ڿ"4ek02UXƊ#sYl ]V>Zʚj%hbDougइ'>Mw["4!inݯל.u{"_4:Hq\ȍDtӰF! [5lxv }4gm..Lktz 1>$.\,D+-Y m'2t,{%#>߃NRǾ._Q<:*&w*"ιLg)|irWA슔TmVNpe&j=jqUb̰$+{(l鰹r'-3~eI 0S=/j7@6RT?:&_r/r .e_t,"S';w~pt.M nR6zXr] ?Tj[Mh&RzoL+uU7S=@|~(m ,RٍҐ! ݼ Dn;65/a"vM=}X2-&uͻaN;Id[5jkr#&?U2bVڴdLeqeYjj L {`ԗ~Q/dQ 3Y#oW,7GO 1\c͆gdj~(EX•,^1{aDO9WXWܽDͬym |Y7 /rˊHWX;%q#;R͊0%Ks5<~Ji|dLst_3[p&c K I;"nBI2 (#,;n0iL R`٦ȍK7d JB"y~tSbjg);}X.1:Alfjq+Y7l"NP۟V`i2L!j؆ȜI@=^,Ji ͕bO%/L~=)Wȁ`Ƣ!bOm[wi'Zx%ZC,XX[(/8|CI/dT\[W{򩐹NXp(Vo: B†HWwXkw]0NDʅ*Ph&,u՝},F4[$YتqףovyJleZ^a8aKX{^]Z|t^9_x>ZQ8lƫp~\&6\8[ql0lwDZq ã8syi,pkvǜJ~ml̡CUCkEiG76 V78%62iPʫt%62)Ɔj{YþfU{ɔՐ~ va:.ﷁ#a- FQ*A۰WuhmXo.Qd a~F e Ðum#_El=4(M2G۶I϶Q,HrLMVb N+EsϲZƎ[);!D8Gɤzi. 緥~p/YFUB݇n )F!U oȌWFQ#i# V8P=\)WZj1$,WA=9g8e8-%IijӾ-@ߏ Zax!Sϒx y%-bMTiSzr@MX;6;ԱUߋ@Ny\LJvOݰYpWxL0=(r"x@o-4JG Sy1c+o2[2 Tu؆` D<IANĠ3 KhjAC X1r׍uvY"̽(YF^;ϾTWǿ|]C|?~_~wi ץb+Whbf.Mb~m vtE`ܪ ET$fNGʐNF^f6ui)rI2e36@2L]쬨QqW;$ĞH)=S@H]pg x K-æ-mIiKBH[p0S?%!-(mdyіb%!-85thK F[BڒҖnÌ$%!-@J-ݖk- !m hKBH[pZ8ovΉKB\!uQយvyK\KF[qڒ#egQ*mH#| -5F[2%!-QըiKFdDi0؏(qɈ2LNeKa2$%#[2"ۿ(oɈ@t8o2^%!-Zጷ$%#[2ۍU%#[@ނVj7e. !uɈrHeo.t-KX.^%(oup5ޒ-ht[Dy T2ޒ-Qޒ([2%!-@ʋzj%!-Qޒ-PjUv'oɀ(oIy \@l%##-;yfQY "S]aI Þ]{-~W 2+ hDG]<`w9::2$Eqן8Oes#4%,Ű"u.e?%~Y_BY; */C_RuG\QKgky."pw2dA뮥Ek񫟵;o%ωqo۩p tਵ}-W rpB_@@J?~տƬsŗ?嗿7pQw59udkHImMop7ԏ1-7" z47'C4HS2T1DXa7U}= ݶaY,<7E#/IG˦)]j cmK3r"U!&E9~M2iy:pף=2gJvLO3{$'(#kd_e𤆏~` <@yJEǩт5ՙ=ԔNz{i%G|J~XՊX,85G#񱻝6yxqYo\4Ĵs#ÎR^{Di'̕v"/Ȳc8fX;0lȦ+GS=R0 =e{л)(Pl27Ξ.A (2Q3#ۼ  0G?ab< z/;+ɁM}=6%OxCfdDsC}ݚ Y] ;jX\Xzì #LʹY1uq HCe?`* [ 8q8dbxG̵z7T5@Tym! 铗}C- \YK=v?H3,sBx9` A X|RMg6g#Q-4˒G\ ]9vw@b<98 t@vb9w~v9@4S ug<t38<~s~)T#m͋<9ϙ j9qÏtGL[b7z48`Ԇyx5S@<#!Fm0j#ADm+?ïȨ;.$܎bt|אu,C^wtI=GUOZgIwH ,YV;ZwQ)#;A >J*=' ]wGE$Xhː|'g:}-E$ߥM=ZC/Ė*պL5W _9цa[DtK?`_`_cOS?Fh;HBzď,64 ?ZS,!wز{Y5\Z2dStV z_XxW%|jfV:}$~O%B.UN[sWasޱ`V]3D+EC$x^V *ޭЖ ͗L kUx-xn<3ܮC0ψ'`4Kx7B6݊u͒H|#9T? [G9!?k}g ;O /0x-OIyU[ LW$t9''7Uzlxp2Kk}~aHSPDg5Ԃwx-Y§vmGߟ'dH^Ay48Zڶlw K}LX#U6C ë>5BEl]VmE_:~6ӗxGQ;Jk}~awx S fǐZVK+m[Z}AECQQODr4~k>@~@d7,,Oർ!54< /שY~JxB[6$RǶ2dJ动̣ۢb͏RQ076ص>0Kh(8?Agm֤^ ^qH%C#KGH0!ǘv`i2lY wXw+eKǎ3tG!gޚ]hx#^«1 j= k}~@~b@џkyyZu>"LT[&@]&v-Xo/28L=ZfѲu>B[ 9!ҽ}OUdęx,^ICbS`S=#&ߡ^`{B0pE&Z;D[gaQIz\~ݪh?7"7,|GHYx>5}V+jG vDRu/A?˜ׁnUce0Ð)Q+ʈk2f&٢gȫ /VBs Z%KԎUJZ Vh4wXW:=wXܩ"U*KkhgVH(9s[P(Y=hFPfpg|eZsʹqU xƍpEO=q5 :r4Zmp0;orxo8"[yhB5 !ÿJu.SقWdqQ\Y[ ͚XҠ-H"Gc8̖І־tEcFo̢] ɸi+Ȫ|.m}/2`aKrUKu87_@O̭ *-"+-k(auLta/4-o_ ,`"%]#j0ȣy+*P ^%D>$t:|A^i.[фwсsʽ_ޮI{K+i9Et-8;U'hEEn lIqx;UZV W s]4HĘHu !w% e`Y 4SRU$״~m#˗Ȯ)s>uK~f7˖2im 1|u%"͈eF؝L%rӟ%)D?*l7]b- k͑rײ؉r٤i+&Tukyqײr!|sȊB%󨒉yȥf/s^l]b:LdY;eN']a0TӐujҵ !K}-gZ VhExZ5|ZH VUWZːdcֲ~$عk- eMf7jk[4\^̪!YL۱5l%3'Vu1w,emh4fC^˚쎵mӇ% u䊵W\E9OkYL6i"|Z72_ijg_xkE!~$ڈ+bZEd5 v)]eV%%Џ1<}E4+`1NH6-@Z O"vpQ:ϢIF"p,K ܬk-y.p,M`2_eb];XVWDlڋ*l?/THߕ̔5xX655sKxπ!ްDc./UkY-kk,p߶8%%Åqxi <[04!/ƅ*`3NGE}1k^{9XYѥO:3-R& "z!|Q5H-Ll}o:KAC::yl":ڏ2`[ rPy"͍m.D@^\V}F$rS-}Z}۾fKQT:i mt#zd5 rHT3*Lޅ@CĹVe [U`#T5%F\ ]6Nu1Kd*?ŚДj ӟyQGH˥K34?fPgA̙#z[GshMhUBݩ'U40ybVEȢ;L&tU$mfV%, ~WZ[VRZ F"93" o>qAC}klO8R"ګkfZmWEБDL{(٩1 +^4pnP)?Col AƋJ38\uTʘz4i2g*eT)_Tj4v*5|ڹqQMlʹ֑`Qa0F!к.Xע/7iF hJDt lBa V#KSS!z3!U:ʰQA J)Oij7*wDl/F;9-"*j)0m=%}yHa [㒍l>#\qDAR F T, syv̐"YxKUɦI'H{SD4$*(d!"+Nc4‹fQ8R!T 9Ewsze!'v BhӄwFbnN7H&&hM ݛFM+ZmBCצh}+ \^q0/% @ eG ]HccYfcmhkeH[Zb xh"٩$i@$ɜ=u?98R37& Cjز빵鿳U#eYu0E4w0X*dlW*uA"P A7DqE _2ڠqI@<N0&jLuBO;6UME[aVj MOawm(}# KDMkjx[wWkD~4R ޺!F*v}%X51tk]$fl^PM#g3/@h"!GcA}>q /~Ass!CPﹳG9p XLzA$ Az& Q"k|v63Ne3t zǑu5J2H][>:C}![qaVfW)ȰϷΗe9vFG¨ o1/msx,L7<񍭁mԭIJfd˽/}T6XP!%8m*/ Hwu[л^^(!ģ3f)VAQ4*ś`lw;uܙ0fg 8vOhdbSS"]:&{'(K}RmAW([3$'fs{nq9fFM4)FzLnQ wfZK.PˏB5=IC`f!]n5m2dfwuADW]qϱU=JI]J*zCg3 j$Ӊ?&fޖdb .n@h ]f 2#u b’ySѰ6kTYѣ03b BFsA}tpNU&F=K:Z=k^j0dcMV5=k("Ƈ{z1( Z+e}+SI$/3 XLDA˒@e7>8q<:G i"ey㡎,hHSp\2zfGK|.Ӱ4[Q\=])`.m!% $!fgK̽d~dWNKa&Fw0 ?# 0z)Z__k( ۟C,QӍiQ9v ;ЪFh0#Be3?!MV`d~4D'RU+ '$%J -Ҫp{ ] S9"`PlS1u-@LZ0Pɘ+bTt 2p7M ފ#@PlH헫[oEj]q[zdV$Qiuf> y,XTz+ :gV+Dmll#jpsł ,t_&AݚfkJ-r9l.HfHɖ+ nuff Seͺz l>콢콮+%,.>% @PXHx~:$Wwt9vO'X}Q='v+3,1ޢ]9 6Ѡ_>F5;]coZfGx&o(a?۽1%7K^:^ )na7=@07D.@#d 4dj9^Yχ[\{q+S`q<6b`}F6nrADڈVqAN&7+~Cv!޺fL֥>3[ޛl[]˞eޥڭf]=°f RQlۑaө*[읚6-HT"jTFwctE $?P[޷0'&=-] Fz;`2dXZGMo}u5 WOf+ok-zJ#[dNe1Tˈ(r2wdg"EK Dbs 2;b?e@LDvEdKƁdl 80KtF(br#.?}17Μ.:R/yzHR/,t%5o^ɤ5iX2˽:1E49.G@7DTC(O.$ﶭGBm>]SRIcY y%rL}MKE y3pwPI0]}zo]{*I Bv:wU4lYKzaY"AĂH!KޥYV~.Qm:|Nw&c!N'ߓ;-y֋q x5uuJz/zOsn IxUQT96Vce PL̢&wW |!ӬDSM6I$ F$ PsJ:$% hɖIyXu'-~[m]):{&a`H>((RTp*ۄ# =D'.y[O#|#Xμ4}@MJ.ېH֘3흂,=:E\t+M2Z֋I?AJ>^,ZI|y,=_[h<@"bzR[5>~ RP/W%gRp!gʷOUj35bhRT{X) £{2^-XwOjJHY [61QC(kF)fvP}e1J!ecǦG_[ _ |'7 9hơE%(Z}.ՁL2}(Z \3ҌDnbmq,E/xv-eOzkO]t^67˦ZaƜ6^ {̰yc8h~:Պ RґB03q5⾄0oO&>?IhRkvGIh4*[LT4RpGjS/T4UiQѸ/\E[-h;KR8l祢hu'fmݝ$ m@ PkhLih̓bz8ih$sx%32K*$ƖM@O,s0I >IE_&BTb7t *o~\3Y5!{If8q(dPkK!G!Y!F ٣"ajGzأC =rkW}T,LF3 o9쩟GϦ$9Q$~_=l/.~=s>]~ɾ+!Bҿ9//b0{{H}9r]` J.+Ra0s2.JY43>PR9\UbJF%*nxmc4Jnm-h$6]zԙ$LGW=sK7i6tse͕܁C9#6ue@?TiE,oEu  =ҞQL2"EK-R@iuiJ.Iy%4$M 2r٨5MZI[U4i MiH(IWR0Q`HC*^ɝ^sҭJ{t0Ky`ήq(S)C+q6 : CԈ/YdOIz%ç%kZ_ cP(]^ X*^9 JJ75ֿ KdxɗDR/oٙy 2^Rhʇ.xg/ȼS sB.drurtphz #iH|^V#K%ITˡ]]r RndR|d3,N)=JNW xeQVȳ^j+e5SBd5 AR3 5/xi? U'Kr]7Iwe$C/]-alV>x*Kv$^'r0,&!.abICN&MlDLYT\W]4B4K3̅tivU/LNI4U7W֧cܺvi:_7Wy3MC+JXLbC4/f2č9/5*FVnn;zgGfY,Zmh{vh*D ihC<&T˛G]*@`G/E'>v`#LOSc^fM~34OŽn45Lz .qWgƳ6I s2ST@'tx#O}iQ&4A Ő]t<:uf[7BN͜_ɮ'5q8?&k<$>.ϣ66Q>Hl!i0L!#++C$\3N@jyI$Î)b~h<3K8T3kIbKON4'S%:Eڕ˳&o5y)ɬͭVߖFJ5 *"m2hz\4Jf5XS):lԹ|,嫷iwGGhZ]cT[*SSar}u> Fe~TV=ąişf1-{&@oqs! Mj݌tGnD#븉 n}_W3@!FDBХ!̮"1Elj5=[BW{f޿`v߅d1)꩔ƪKG2"\UĔ^+r<*mf40g̏K.v\ytLͣA9HB}+37p£UR$Bd疩%zKz>gI'?Btk+c}]$6T.P@9@MjruSrsEԔ  "]?RNR.wMBrW%iccQ4“b)@RMp>OKU0j%WhD*cb&'AWH~59OI# +B0yM8Y~&)29(ohvvݛ>5JB;vu>{|tAӄnL9^(Ɂe_NpsW}ЭE 9"\ b}]?wnнIaMSجV7)e~xv:^Zw+Iy]YLТFM-5M39D<1!QҙIgKZopI~'I9T3i$4#RL[O$Mi둌)d9G;4%ݘeMi8O f#_١"<`)a赬)9!)Y1)٣BSꄦdUѬP6DYLCeRu)kJ$M>i^ T&J*摩PV(iǒ,n8|Ӿ&&9{$'- ɗ$H[Lymd Mđ$PHY0Li+LLPD%uȢITb$*7eJLM;8F֏=$=5nS<,x&@JzcTd]5A-86Q^DʋVFh5yfo3L)Sv;d16ۉ7dVv}`"qsS\N*Q^a7'Ig飂[|gT'l.hj *vR,HD́#Ǝ GDwLwE %uܧ{$YR"VQgGc6#j۠@d'4X1'gOaqW%x9]5gb{`w8\U Y܂juFH9`p$f˱-[b?@x%{$ZɉRf!2EPbYlU֐pb.刻KR#.,N]wrY>O$w']SarrݥTQ&sC&&Pr稣AJs$w$ 0&hV-C94/ [-eWxK1axKR˽FLIRRŴRwm=-,𖲯R[mѓH[f)XQsP2=P9R>,q>,cqO ڮS90%ñd߼\x gm]G R 3 ޺OoT$j?J>7nYڷ,!-郇;꼣 ,u(\[ۘ2GDDh:S=!czL%DS9Lϓ vc3kPi\]fLJ geJoDX}S_>)=K괷~$% $# jI,aju.RxIrF1>].A3%nʖˋ utga"!2b4;0#JGTstpg˘&-uNTF9S.J2ځ0rl:)7)})OrPԗ)h0RM6UȪS뙏6Ya2۶[Tl:zZ%٨;eHoFu4cQQ1?Fe4 1CgO3ۨנd"UFmNW~lTw}aݹ3\UKF*/+Uj2 3U>%.VB%TU*CX[0WUuM*NaB$-VG$+'kdwxST*aXUn:F*>ua& '[g]zdbDLDnB?{>Dؓۧ}ʺ/,V@0bu>S}*O9)/Sp.~Y.bd,VGY{Xt)ʿMhLx6af '!@aղ { rnvvhW ׏0ύЄSi9tn)GL~&[=-8 :ȡiNvwr8 ^<6Jajhx0 h&~}@sp!,'wC=Y WGkG^dUuJ"Snt\n;9/7<1`{>3;uM"ev>9},5= FzM!=>0Plf'mf-=~^4{Б4L>CG_lr|:14=n.bScCw?Ƕ閻$8q-w kS-N<[nf{#&7=Mpݧ;;sL 7= @9R cc)8#Pp/8>88Ďv4& {;ǩd>p>v4\Ҏ9[ӎ>˨8\ecSCv5PqO{ml+F=OƆƆ>*3sol 6676kmkK(Btk_Ø۱a봋"T\=kb.b#7 M}Ӿ .uSH{kza2? =5kא2fN; S9!wT.;:NdkA4MK c1>wc@鰦yU?йIX '3miLOz4w &D:':ȼ W>: '0ۙ|P_Ƀ&/,G)& !jg/-dH3to~2~Ӛޓ QA]&M˪5' :d?i,º̣A’0mx, *MB~ӟ}yf˿|]\0K (hVD|AyTkHS"tFD &#t̎oWy2!CgDtF_BW'D}h?osk@8#O #P6?AF#1aA'#S=J!jΈLҢ03F&ɐT}ty莣^v)w|ӧ?~IwY<8*%w[(ljdo媥 [MIr+ [ӶV@V*įET{ }ߒweܣJD5dx\,&1EO/oE?|\{?<}oE z<;F*C:>irzَٶ(oA#Ѻւ*4'o.!IrO~^Z#lɄ^LDn]h["e+8u*tL8{G?8 yQe' 7G"F>-8Ulr<04 qzHT cM"?$9 WuS22$R޼)M4ޟJ evJNC 8!Xt :Жj2XhYmL(W3ʨ\}oyZz9bF&ryx6j~EίJ Yk ^{΋CFœUFXM:;w:&R 󳞰e<3O|29=vb7LF$eb'/K!,3!8=5%MѼbx@ ͜W"UD}Ehe3Ն F;rqV=̏LsLm6ȡڀEw]&L$s@#ڑF@˯ i%ۼ,߃o&ĺ# 2YNQ4_3uMwdy5 R_L tF+%9J󢧃.GY! WLgհ^7D[diЬqxN@rzxy"8$D Hn%KC [9VSrt%.qi,@نcSML-#q5D]ga}ZȈVKBqoRW6~5.U; iRUL xl_Qg@yv xއ/HRGߴS΋8->-͎NuV phWLP?|+Q{ɽUmޯ+oAЮr?q[yֱVmcHN*[j/T4u>v?~-39b=o{@Ϥ(lfFS35'B35_~DgcWo1aIy\B_;zN]ZF+9g͕ꚦ ZitFequ&D<W*^#2[.y7a,b@EWMYG}pܦ)A՜YbmLZr+2 g-6׊gb@I%˻ds,Y5 ߈}R8WT,6њO%"O '5ߙpPYXcb^x^isCڕ_<*'Hx8/WP&HdP}UFL%I@!ǫҦ7O1di =K*KW0ujoGUƨ_˵j9 j%TaYςVR바] :,%WDSwYJ.L,RK*P|^S`J%)l4\R.`οIAtpINb<)Rɳ+D6XϿJ-)q/H>Tͮ{/URhaĭ}5ϙƇҺnٱ ds6]B<8yߋ0#pZa_0ej+8j' jzUjY/樌\f-m72hۊ6sq+')ք?|j'wLR'昤N3=yX54mXc:m9<#U(6.1>eM6œ{IMLZӲKe7;1MIk&iUO\4 46Nˤ9QFOF,WFf{MmbXnw|җ-1us!n L /@n^?~,9zL^ik=2{Z/%?Y`ł(eod`ɿXKyI7w%nk鈱v/5噊7t7d&E֙J>hGos@eP]KF3՟Ȝ]2\*B70,]]F.)/{z#6"醈(:6M6Y()݅B1% &ZsXV9,e9ڮ6JU~rHcUZ~V簤g0G~^{m$V_݅a< Kc@: C [BNeN1FMeHnS|m_m;<4{C;}A'b-l\s3NI`3[蝖=q;̍ sĹ( VSlS+S_369F<7i3&_ԝ%=B+NEݳ+d!_':Aa} 9@ԤLKϒVy-Xqkc? wZv":̊L~Z9? sf3r;'R[W+a*Wc+X򊳟qPsxrB-r"@\}n6tgn-&Sw:ZVGNi2X; >aRk HTNJ\)9`צR3Zݠz^&Ŋۍh En nYF4CL \ Sr]KRm$]w DҒvzO~$1 }xk`&; 1Iזּ8HoB@zW$9ŝ3SHMq魾`04ت陃J/5PC_bIwkIcSʊ+F6&tMK_d]jiVKoa-`*&w_T_ V93YߪsQ#^(Psܡe6U7M-kvNJb`YU1=vOnU-D̕g^4ixLcXd,y6TRd.ok mnv3uZp}W(r #Mן܀ 3 Ag-vxe{zhLX/w9,q3]$^ S4H:]dvSZ#]5[laaRMT:KXF{V%݉!9*1#-1uSݨFkZ% F(ҰͭaD Z!jh6ƀm-IЭkno~Hװ0-G\[f@hw ZD0\]3/%{˼_/ "Z_&[6ЛJd\./Z5wU\$ܬf/ECÿdAԮ  n}А+P-%/m`V &_49N@1Pd9o+i)ToC˿(-H$ nt`MC0&1O6oz ]k9̃ |:rfrN '{@",Vղ}*qZ)/yj,1c JE.G**K*|ha K%`%;fp"anb-ջeԯ脵9-QM|fp-fU`Zh)\ CTs{+i/_s1F|Q6 <ރowT M\u8rmJӎTp86UCY&\g^n26 C]èAqZEsQ m0A<* M75ͬtPFS zYaXcpB7sl }>_̘}ҫch@Փ~ F$,vu+X.&s`۽r#gu%]#} /l D,6<mf v e8Q,tXU7bm 79vo*:5T3^ VV:U|hijU3ejݺubaO{|P*ћ(7Ag6b<, m'|C0(*Uy`P5]}~e~\fEDŪkCLheMKi&c{%v_ i< 9Vo $mG=qj=?o2ǽ`z"P+ZaXBV$+ԈRs} bAN{$ej邅 'D!P,z+eje:bys$,4g(ʅ/5 VEvWldOX2j9 W$\/QzC" ʼn Kώ)~\Cô8 w,'IyЛ{'Y$HT }f{LB=u ~IWx塢PMգ*:![PL 9hw *MJG0^(3b4.= ɇAj Z^=YΆXAU$ GNJi <-J$di@Uy(NˡU$NĨ Q!!Vͩ Ozw.3hntҍ(9%91Yj-FAHb qIV{]x Wz;Jӊlhaδӌ yfxZַbtɓ>  [<kg/sR2ߖU kVuV-헽fUe7&J7Nuspm qR%CSel˘ձ`+;^;ѕýH@0b C#5KGB+bUi}Ru{1<;=! /6nu![]ݏI`ۍ!Qawi:!P]ܭj R<$7c9r *%ox1J;ɚ ޏ˄qw⣖)Ӱ:b~۬}bȱ큫`]t{;k㞾b.n pc^\+ϑeQ..sbMnz [86J9k`@VOI 27uM\2%V0z\_Kq!%‘ e"A4E!Aʶ%یUAtk<۶vx1 M/vxX|,^bl&*ӈ,fQ[*+/2(6p~N+ts?{2y-/S,}=||!/Iij.8H 4(S o h6@/`7oIe5nvުp4ˇDJYJџ 4;TW\s?@Cp`M:<!W J?E H9v]R7)A6pnL3 9JVMnY^@\9 0J9@|2x#99f:\}W\1`QR o,sτ+` M.ˮ-LԵM,%e H+m*Ĕ-b&Vu3+ %߄{|M|xF,[yk%ɨ$Ͳy$'`)fl$G.hKdբ{T q9r\Br?},.;p^u iXiydGr=3 god}^lMI>zoȇtބ !P[5E܏@OX9wςԏ= Xg!~.< 72sɳ{pYgI- 3рݒ^KVY-G}E0YAh[”\`mrF*LFFn/97ׁy{iz3}uӸri`Oq`W<(yAaܫJK .jӃQTnY%DePWn].G$]$ =Fn)>-H6IطN"9Xp+c>_=/7H cct7?9q_w hVd<+V2itHT Ht@tHGݤcקTAغʑOg yid1iWvPez! 4\n·wX8X ]xGb=(b]dRfԂy}<C7Pmu1Yٳ꾣ڹ9ަڽ Rj>:`x=  dUlӮ{w'4<.]N+Mؚms5:Nmz$[w&mKHǦ[Jt;<+hm7!_+‰>΅ }#>rH|E0.c; ٣P0[o0 \) $%ElYDMv}/;]͠mfXDЉrBF:M[o'LGN>a"_-F͉o։Ý(rDc)e(q-nGfA47B%fG1фv'mPbmˮEPND&_[D.&م@ !.yD]T[֐a*A&3W5`o<$4F`&be9C# L̉C[*nP/dl|EmṊAo,E'B!^Nn D;d7rX}7,ӑ(MVdHוYrX7Py 䛮bY)ɔx{+Ob-r'~>Y9@T2 Mdl Hf| ~"Wm!$-*D3NopDž 9flJsQmop3`&3%둓= OAcQ5cQL6cQ4<ƢfݶtkƢsK0<,fBcq\ŒCa,n)ta,#DF+GMO{A9 IG~#D C0"]Hm|, (!\t}'G5)h+/2Gzk'%++ C^3(F]Eч% >vUrl‡Id޷qhJd!2g V>s~^IB>58W|$ڦKh[=\m%MW_Aj󁆦lm9s6!dGdd]sAMktslcd|Lk[\(2. l悬`qAgګ#_u* A֙˯} Wߥ%H?7QYAf)YW\uYp ,eb9hZoHK÷pKvmNno븓|떼2d=Wve7|uO,$:\k("KN۵DCU`u\Cw$`=7!P]lp؆*NR aG58j & SG)ڠm"室6"=9!{LD,"31E$*&pl vK6R6,TaQMDtwZ=`"T-DP%mdfsd;<H<PEsH?ye?XsĔDZ:M[d kGFi+aRavh ukC uB=%ј/6 ȹY|bM7Ua9hua{lhu[Y " j8+j ` .`ݘIt$͋!Ϣ@^r|谵d}JV(^OD?yZ7.Yg51c-}s2!)+Z*kIeTk$ܒKѪou vYh>zV#H)3NU6l6R戳)Uosd;3/p]D""% z`<;:!hˆ흌ެFNp|$C(!f!>AF}7m7X=7# j28D(7MFr]'# d疬Ց}"[r-{ɠ$V+ZLcz1RBk3ږv2TpL̗4f>;p/+Z I"znт :.A;r!ۄ$Ge.@ iQÊ'AR,#'a+0yw|(6IM" Jr@@] R,x(DN'['QМ#&Q!`MRj.gp[gkp伏 )튜x% mB31ɭ[K 63jɀtXsѼF$y4(Rփn`0P!~7TRnPH×l&yGu 9$g:>Әl1p" *\.g0mL3}8Vëp9e[z:u 7=X$ 6:bJiFjrG2eZ;XĨyVg# q,S? YYjY\,P~6 ,govL@L'H~6'9q ڼ0oېAo 5:.֍$I͡y$wPqO-Հ, K3KBRa7^Aqm'%~u=0P>'lH $B&0([ #X<=q'KO>0׶F*SNKoƒOn잡 Q2nPXKH#9 BÌ`_H`wC'^ [iiYY[f1񣎝u\usl>,bդ 16݄2+7o낖*ĺ ^t$!a+Q]qX]qrل#~G=0@H&9ZT[1 1ڳ5|ոci{tYxUª 1Y/?؋{AfSl,,jyٱ"um-ƎXf!v3 LWśy=}])[%x:M2ۧ__OZ^^H?>49 Ig"j[uN&I i#XoO S7Of9iSL{N lʈEfdo-_i6&*k\)-Nc|V`VmJNfzMk5@B'HZ9'w2#e7ra[ivMlNe9bQ\C.ߚ{(܍\:P#0! -%#UqBWd pr˽2USWT/& (;ڎB/1'IBZE} YxWldh*%*HK ,#p93Y^-F`'Ċ%&:IKUAq&狮ܵlb- t Y<y%rB~K:(z:dFh;Y `HEMʩIH/`stBNS/(c{1 16]2>8ubIX4(Pʌ`vB. }m'C#V0#!m+w>h^3>sG.HxɌ u1;+2 Ł cWJ34#Ɓ3b%ubdA#ЮX2)h<4GB RsjjLj R#f$f0IMF >x'5#!FjbF2uԒIMB@j2Ґ7.#5󢜙dY {ra9IMFBR\d`5 ɢcnl&D& 8Qh&$2ɈҚdYW#AIhMFw53{HdDg IhDyMFGfե܈t$nǠ6 0f#6*bbS#tAl2`&! 6N:3Nlb#6ԑ\푓dĈWqbڞ$rfKଙ܈Ɉker}b#I 4d^>Hnqr#7A m$7!r#5Fn2b&! 7\3UG{&7 1r#71rӽ%MFdMB@nDv5 M$FQSM2QɈQpq9IGFp`қ[Io2b&!7Qz=,MB@o2b&#FoћɈћn Ɉћd荸Nzoy#qj%*Ro7lk޾+U.zۿ/l^寫H\YT !|_xzӛt?>}_݇]c}<3"hV#K* `I({F=R+xK$ֳ^;'ߤw:% tb-zW=Vʖ&n??K%.n뫟^Jc>~x+7O?7O߿h?x[߷÷_qǚFHqYvsNσ[fOTCtq[L`U9סG_"kͯ!!*\)ôL+7XΪ!y!yCbBR0ڦuU*ZHBAGTZXlCn;fi01pƗR'᭽7r/꼥 <G_:vdvnp#iMy9+M+72=կU{Nn 3:C zsQq5@7r9yDNidqCN9xSƇ c1|#'ÖN͙pqRO('wKZ9)4Kd>8(,quf-O;$[Gv> `B%rr( = Q:b_bwFf}Tg*Rz?Ŏnwm:x?"mΑyT쇨.GX-Oɒ0'4Vܑ˷YϙplddIs 70?9PKfu@{R=L3Hzӳ WSni-3vWcK%؁;x&1l;L#udV3 z6* QYDfcEGnPFr6~'8O `oi[d:<96LdI|be` C!"703z (7rB1'mnU oVq?:~퀗9Aze6Tkն{~}GPʎ* x6}|ũAԣ&#-':r܋c5 -?l50#!&N B`yWG 8֧SˎzP ea elJ=L yG*dda*"B1Yy y:4UR^u#5 9Y0C~{x"2P弧(b6T6F1jq{'sNB#_d3@^$k=Iڣ҅@^iaj؋9V/8fGb/v-8$i wyAZ!i Er< =w"b i 㜺,@Ѝ%I'-2@hIK $-8i* 9i HZmM=3i}#8юn#.Adksnd@nsڹhDdk%~ϚGdkUKMj_|֓$p^.5drU_[w%! s=q.6 4d2WZ2[ɖH*+,nUn$gnE$zDSZ 4O𓉛L|c|T&.ƿV{-r8gEzp7!r9v?I4'v$>JΛ>ݽbu$1U[+}_x\ǷhzZZ>ᣞ< DOn)l.k/w[nCKΤE|8/U_k]הSA^on~\mL^5MzrKҦySpi[J}i}:߇o:uTmS62zViծ+7}m6kXz/ZWiM\[}~߽77߻oVvo6j=a{d>0?zg_onkrN]c>SM#7s\칾t[n8 Guk?wVn^b;NCo,}!ѧ{<>CiqކlYH珟j{a/:cͲ.|Lmݎ_t<=3Amz6͗o%k垓\swG&yExԣOڕxJ ^Ww4 |o'\<ù~عg;E`^5?M]+}/ǟ {X27;y/ϢoSHm~~zGm=ŗhS})K ah?# Zǜw,)'˟j4O};?u8Y39mSWY=;T]C///65&{}RCMTNYswq߾'}OZ}/BDZ?yAr'O"V|u>14/TƧܵo J!qSL$^` ?3?mGs7W_x0{ޣS\+2c!J]St&WoQ"hst#sz?kMu[HNMilEd=0[6f'w.>?<??GgPO|g+?ğ?>lmu'߅_/_Q]~xxA~pG\լ]SdFF?SVM}Goĸď(ƚu5>l6sWz&ҟ#g?.#|!z=%:(ho}-?öC. LXۛJ:ц?տۇD}II*oEmQ1MŐx<AU?{DOW3I'%kIB;Yo*L F)m.|ng#.3I&*e3qJ$+DY[g{ *F߃DuKsɳYendstream endobj 245 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 128 /Predictor 15 >> /Filter /FlateDecode /Height 128 /Subtype /Image /Width 128 /Length 282 >> stream x10ѭ ŹYendstream endobj 246 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /DecodeParms << /Colors 3 /Columns 128 /Predictor 15 >> /Filter /FlateDecode /Height 128 /Subtype /Image /Width 128 /Length 2984 >> stream xݝ-Ho*(P8[áp8-C֭[íZC;ɛd8ϩyyut:/GǷOcv1]D=ʫK|]yo B<~-+׃g}rPIZslhg)<4X)1O: Vq)3\T^H?[ue縷7?~R-&Aҧ̰_Y^SVcZ?ſL@݌ƃ>Ԁ}<Հ|O_V1J J:,H l.A?:9`g};[\f6cW7%O)M^qS,2GЏ~kFMIH \_Bd}i-]O~d`ܧ$G}o%X|7o==k0ҋH4zbRJǪR7[E`b( [GɺYM4I 0Z`};| aߗ[(*iI:RS"a֟|͢$YA\'O5g;"$jlk}.h+3|J4Ur\f?1kd}_dd=D~J7:LsOgcZ_{Zdtr[ۂ0Ttdt tpjH@B! jC߀-Q' `ź >myYF3D'W/klvgvOc@Bگ+w#.QX Ob h%aX$U /:Bܳ <9D%P7rɇ :&2Q$>x=B533}܃jng4ٝ BT9^)&;2!u&h<<`@r%wg.;aN4 ["]E3U{P> wg)YF} @-iڪ`f,8KBk>1x7`ǀp cnƼxώc:qU'$sr &G<4O郌S}XwpjI<ס:c\`pu~|"F7e 6` <τi/Fw(v.N!i=d)\^a8EuȪI%wMx[nkLVu0-x0Ѝ2 k}kƧJqj"Q Ǡocp\(t*4vo m JZ6h_zmH(dn:ǁ\i~'o Os Z-#n`hy+Z(#77ņ<a\~0XuDD*XiUw\-x j1 ~C pMkӼ^^}BAhr"$@ ;8 ໞ0p j.D,4!g] ~]> O: ]]p?&b>Jner{."#_ $ =i^2VqG\s0d(ol.;ln!!5ieZ_(G@Ui3Mş:ⱚ `:қTpVz]Ɲ0U(l7O=g*b@1(mbw|I*-N aźSPM!T!)C{0M'1P辮O]C޸.gpC@.QNJe@~  Usߦ钏`P5yu;wo[1vGi=F MclBFzy>$Kgwp̤̈В(A@~NJnS%𺏴ܪ0SW7OAyf!j .势6l:k= o5 o 2bv@u$CxLsk‘J_Wn' NK @0]j qi]XoU_l3"g@ttW`& D\1%\_Cmz,U k%+n7h.WXMV2@D*gݡ=b@tZ{ӻ2c}?f܏00u }@d~s#ׇww?z*y_0/qOPe+Dg] ,f01/endstream endobj 247 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /Filter /DCTDecode /Height 128 /Subtype /Image /Width 128 /Length 2497 >> stream AdobedC    %,'..+'+*17F;14B4*+=S>BHJNON/;V\UL[FMNKC $$K2+2KKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKK" }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz w!1AQaq"2B #3Rbr $4%&'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz ?ZsUZn+ < -GҵbU-c[.Pkn]51oSm?}j~[f1*.n;#|Y^OO$G*+Zș1ւ\Uu8HfxoR7xrq_ pXjf43 zq= b<J $ՙNѰUY56w@s*IRKW/mO#'sL(WZVȪP-i/J꬏ΫHѴNBTSE]b+3S%|8T~7j:^O5|-y;z8h~Jl)h8l܊eں7 ZVӪM_ӯy {~Z3 G5zdvNkIXЍZTZRb4t(qWJɄr8"2:_q.L|z8 7k\i&$I~P;&!Ba\l ;W4r:zVµl:WuYjZZ,% ר_?_ MR?_6ufݞMQ'5zrk=_Oc[V`E& ^泫 VrI1<;V{EJԂަ"N]?{9VARh>#êJ/ Q;TX J-~q\mz͇Woߒ3qɦ3w[8V*YI⫥)h#0xikWyhꤲW\Ņ*]kF_oZ ٟ+~յQl}S".=.R'ڲ8&c:L>I֧|V{> *Kt]ѷǽ\zZ +3lG.jḾBMqTV<ꑱ&SW7Lò+2Vxs`i~yU[+tЯ+U9ZLJS_Usӈb!IcZm0Zċk,xHs`$4'.>wo5|`݌L9ΑYx^Zc~+fX5i7JMnHK|pdZj??ʼO6dı'Rn~Tf5 *4!K?#wI7ݕe5NSV&j+WvF-!V'?BFYQl0 s^ncGST5SL|p+^Mt׀:5ޯ\tp?bSjCW.G&l}=Q<-h?JɍjQR:U6\<TlepMgNqԿ+c'_sӓJѿ̧3U)Zq;DH k @VBX2Msשps\ɧ6f0'V zݻ(P~ -$K 5z5#s{tZCWYўj-Uhmą\d 8Vn#*Aըv1Vr2nYW/֯]?Zȹ~,TWCJ)ݕ'z3Z+׭N'J|c˭N6$W8M]U_xb`(2%iip>,͗Tu[jھc<^Vû6QSڪխ*^~N{'ZxXha)Oɪ/ɪ^8AN6DrkVrEf[[v++#oN$qW)Ʊ&M KP{z֙h7_ۊ1|U࿤fIֲ.d۹:Mĝk0>KTezgr5zPӉendstream endobj 248 0 obj << /BitsPerComponent 8 /ColorSpace /DeviceRGB /Filter /DCTDecode /Height 128 /Subtype /Image /Width 128 /Length 2464 >> stream AdobedC    %,'..+'+*17F;14B4*+=S>BHJNON/;V\UL[FMNKC $$K2+2KKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKK" }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz w!1AQaq"2B #3Rbr $4%&'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz ?u/a?P=jLy5WNLp|a.l]G:ȭK${Gaaju|WU1^z-SWFzƷNsXwkNb}ӲlYl"*+::\cv 5c61[qǯOroUl?Or֫"T%1V"g~Sg喍%VkJTRwG}9\ (;Ss֪9ÁE9=~3 0ʋi%[dijʈ-U{jrs^Z>B4 dc]d\Ml ^QgaBi0j0W]]6gus\S+[q֣s:Tc\TG"Y]r:ᾞdy%'2)yoxgNuZ˸J2|ʘU9Eh̵JEB )3`S[;kmH5F~j·OC.zdֶ'^pkХ#ԣ#erV5Sw=jN5jlY, AeѼ:[ Ka(u܂0k~Ett+S>I41)+>QoEw5<]k,*=~?PxLLtOON9"aA_A Ꞑ60ai+6|sz֦Cu¿ ``:  }EE"=Ү]7exꏌͲm(Iu3=-83O%kF_+/<Od;jtd}k3W-(QW' (_O Oњr":j~mX2WFtU9 KQ,9Udڷ^Uw:^/Ҵͷ9mGXЭ 8.1JcJ9KF;0ToY3&Jg>皬ǚacZ*eڗս:IIjnĻN} Xl$ qLg|NnQW=9&Tlo ғvoV1U.r9__[ $,C{V*V?zbb5͇7~G]m^6_Yk|v5j \Fhھ^JN}M \+N)KҭyZ6}j9͹lGWT S)TyFJ-DCUc*ݲ=*%*gB t&f7X8WT5j8]Ryw',_B79H ~kD %X92օU rVDmSW4qGniVzv6d=4{uY^aiJ|(^M?S8Dҳ %zTcy/U{雫ÊuwSȰsO2?ȳlk[h+^2ќW浏1-$ّq|Ʈ7ZϜnA_r?#mNV5 5EqZ#U+UڦHľR&zq9er2P ݚC|Hlkд>fS\e7R B&I]endstream endobj 249 0 obj << /Filter /FlateDecode /Length 2213 >> stream xZKo[ %E/FEAp)HZěy;s/ܸ^hp4g7+?LD+'"?7Wbr{p%L6['RZ5\+rb]뢞x[dw#u;M3)h9Vtt|+lpAG!o kVX8-csHFe=ТiY:BȨMN4q:Z'9yc/g Feop411z"pEn!4{^C5@: 8 vSq)xȠOU1S JG5О;}sLTD/ m-B <&̗@U0m"36DB fW֓mkxeF6U%8 CYg8Y X+@,xJbxळu! H TAu7eawm=ܰCΚ昭tf,"HE@@5;N{blB(4u+h-G4 Vwomc ۠RX՗?W +<"@rexDeOWH.]۰Iv1ߢo ˷69#@w !]i듮T33;Tdi6F':vEiUxn{K/ gۛw I2 {Q9br"93FX[7AJ{ 4ѬtX r[J@AS XS(f{,tS]1W0bQjԩ䤑tu 3bb;H:d/uD ߎCҐO̙BeT; ErI9 3S ۀwڱ}`'fYeyq2M (5)盂:5#?daBF T\2|2 S˴lG(ɀO5)e 3;2dl> a_Bgb#2 "H`[y{.dzn\ߑ0ZubQL3aaBhĝi UQHﯾ5jÂ@4,ɿ3;V޳3 Hް :prwHDGV?|G%zͶKA M@:x!95;>#`yQ.HeݷfT|ȄuOɞ 4ƿw)ڣ߰$'Yv Iܢp)E~FR"g51EχlL8RBxvVuol5,`\7,4XU>-vӉg~DQ/ywq~$?=}vEEoОO=fYGA-k5@V-o=[TgZ^3qܒC:?2X6W,/_?L=7,/SX 2\#yiT6MϳlCi{E> stream x]O1 y@vX%C1C2 tpw'y?\gG:ikD&X+@[L 7ޟ@fOq:UkZBMĺ1R :EV,C\ H.I.` >l`_ANSkendstream endobj 251 0 obj << /Filter /FlateDecode /Length 4167 >> stream x[Ko>&Ov$@8ACl30LJEҌ]Y%1 ?;U=3=d#|xӏz|Uu+1ȕgbu}㙤gJzx3D,}"W .~ޭoϾ] Θl_Τju[ _?C[6x!u}/Ʊn}o7^xGU~1սl77Dmj`3#Af³B|Z_,,&orV :F-M Zjt"18!BkyÍ0eh?aOl}DhC@7q]G Vex&T .@.{N2>aoO퇉iLW0\/#@d_NY< t`ҀlA[~ L'tR˘nzN!e$]^Ci~j0 Gm1p`iXgU1'+ c/6 98~K/feÿѯ:{&ä$ H~BSpV;&b4`&BEO:BC#" 膤F JZ߻u :9%NEqW g}}liE*I~-v7M.eB'g;\O8&xaea[!ohBPF!V?wNi@= &3qG;z, b$FE.MkDv-vj=JY.Z>Ѳ|gK6f&)&#}Hq3QOYͧ? `4q-K8[Tf"z -b+:WZ&V'|#VuNˌ!=oʨ#ulsːOS#؉6HXb]:m3c4BG k ;:Ӈy n ɓm icFpqIBZ`Pl i0m/L "|Cn:\}[h9~&h0*Uw GBl S偾j!t6$K/^ t*3xłW{*Uoce( qp.rs Z&8hI Bn@Z54v]Nҍ"z%bsb-{# uHW/lN!&ȠC*HZ( j tx\J $m~0S3Ah8%ӿlB:T(28X8 J,oVl(<0s ir4Nk;TH=`P`aN 3`hӪ?Sm'72 q= =F`482X  ea ,"\^/&. hNDc8a!#Ol6sd,)L01d Q _g@d`Q¶Â_08FM-3cVZh`']MR"If十2P @[B9cy;'ޢG+tSJZ3$U|pmmn̶p!sHr6ADg֠ 2A,A@/\&A b VE8%op_#X|NT3*0߶QC4lrR[f7/8)idi+xiX\l+4k:ӂ`wjL=foX(mZr"P I{&YݴQ 8PwhqLP O*)8wҸLttu,/(!~9~(G/"'_u\?)tGV_YAeVˆ*ߴ*@::8VKv2bdDflg|1M>}cӷL}-rݢn,&72x jD[礄J|^a式MTSˮk}녽6Ϊ4]o;côTX*AyA>]xL)TcM5Nh gyɛ$(rw?}><0jqb|p Layhjfg̩3kF~;x6KNҧ''c|3LAz3)?IEG: )R3E󖇩NNiaFHX>pBAk` },lH iaDi ]r)g!GXY2/{?f" 8t$'Q]}|S/0ml;_g˺Y}ѝm}d %>c>OmsݢgHB(gxG#KV~@]m}h2)a]g` 54SZT5wҼˊa<Üݤ`r"^_Og?ӾX 6(@OjQ\EmlO.Y xB>f_D <>ئ{*-xJ QWx'7 seW尿2{L #Yz ƵUV VmMnjᅄ@/^՗.]r5>g~(t*(5 L7Ac 8@Ĥ~~y?^wc횔+ Wºl^RD /::Y}|:~ )!QI~toyO,k${N |& lɻ Ts qHbh#L4ƼӺu P&Fܵ x8 }SHJCj h!yIQ$mRׂ+r8":rk'<)?DZ.UѝQ}Jq&ȹ?vvJPVQ 3:[YtlAAhv𢡄_B"2_٘ly$^FQۭ!E5ɔ@0ZqlP]oЇkVf c,ƕv8l\c)NJ&`?zovz&hP~/r3^(Nt0!>Zu}aGWwSpt)ftY-o-*saSaCB";vOa3!K ?hmQZGQZq7)Tԩc+jI*k=KZ0׫MsUb ^Q(Sb#]g*endstream endobj 252 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 488 >> stream xcd`ab`dddwu041U~H3a!OennM?B'~.Ș__PYQ`hii`d``ZXX('gT*hdX뗗%i(gd(((%*@ܦs JKR|SR* "@bYGߏOݻŸqw~.6cI%wgtwuuGQa=szK{kwg{wvͻ |:z.7[zUEzwtd =tTbĞI|g[5%miω5ݫwtraq{׏]3~OfхS :[T˺9c>slǟcط}_w 0Gq Nc;}w6n9.<'|g[Ńendstream endobj 253 0 obj << /Filter /FlateDecode /Length 161 >> stream x]O10 b C+qP(/ СY:ߝ|pFcpƲ- DeQV-Ɠ剋BwOϪ)> stream x[Ks!R)q7Q"$#AaEQ#KlZ4fwDʕ1F/j +?:S'{i/;:t m f}CưxjxRUxuƨIfx9la~jLN)M))#NIy3\Ghӭ U)n&(Mcwi{Sʓd}^cM .9 ij}B6lBXW<]>0TnνFtؼbn559^6p6wsU\@yZ٧`.WUց|O?|}(% ^-7U  A|)"ΧaCT |$6Ͷ`-3.L~'$9PL{->\ADp  XLqMp&6@SGr8ڎޥċopVh3$Jwb1OQɭ2-acVZrBYl7LBz*C^^ Rյ%Tfc풊G+o̴$] $qgq␊{cfJ2@Xx%!yJrUXM@d7xs Oe( FK3~4^ƌ^^R@CuXA5V0$!'s2%R0X4  SOΚE8$_BAuAu ^kZ !MۊR΋.>Ejh+ڍy:"/W9 ɇ`]3O>r)*PQIH9G݂~c\^7+!X}=Fqץ D)e$\Zz[,ƃG ڣѩ#_ɗM%Ɩ Nv7Ri%2CuIZx;JAԳa"Ga 0",9ysik&`0 vD=Y3]r `N__`fP(.qS-.$ Ц@K[fgf=.hUEB@>?N C;\*^ |8sXVd$@uaaiSSP)@HQCډb"kP$@٢QΘNQA+ 6o(4AesIݓUKpS`27җ'xޮDl zB5I#,)nnz}=1+ %Nj @ I>Ɯ(=mxN!#$2 -)C6.H?xs:@׋ *B}۴`hu51Lu5K wI~v٪L.-R4Iyq1A]3~_[`爃bW%}:2'֬DQvjweZ ,+dFaOb47˘jUc_\W ,m" zyZ"(U# .hf$q 6'h;"`ė4mLS~=ۄY- DԞUܦ-e D%q"tLCRo Z5)Sn0J|ϥ (DXF!Z-SBnAet0{k@MI7ZJwo=s)W6]|^oĄݢ&(<wvŴ(+nF/zOE3nU:jM8ɵ J=+9cОX{4Jh 5- ֨V;˓dFƽ({Qƙ jl]d k?Ux%Ax2dX':@j'&l+CAtsa N V)G(„:PP0 5L87<>xbD\vx2> GZ#kz$:k"dŴ)8X7",z3Iȁ՘7yXm}:a-Yj!zp%z}G k1UjCԹ)h6Q'DgOww1-@M-{C"IjNkyuW3YLjwJNw jf!<sV0<Y`sݗ;̃.¤z&L՜ǦKbp]v7cg *W L|$ϺqGm/ׇJ@E?eKm`elMQNc6 Fk$X 6Ғ2|=$gW?=y#ͻ3ʩ㛥.׉D qo=*eYMyfLQlN|qE] k|Rx[ |;D{2ȕTrabﵴZt8Cȫ* .Wo2Y]&:wNQ/^D@Jݼ]^ʼn˽|t7s6A-{zwF I?nR_Q^.TW?WyN<s I lxoLrBD)aGÝ)1~1z^.+7Kv `kOPj !8@0/ 3endstream endobj 255 0 obj << /Type /XRef /Length 366 /Filter /FlateDecode /DecodeParms << /Columns 5 /Predictor 12 >> /W [ 1 3 1 ] /Info 3 0 R /Root 2 0 R /Size 256 /ID [<3f006c0fc1c626676e94659832fa407e>] >> stream xM+Da 831c"; D6 IX2BNV^lؚ,11M46Ԝ~q/(a/ySm4WdŤwnqYtOD;$ȤEg[L^=H|'v,K1C.c1*6> stream xڽXIoFW=5N$AQE遖hK,}pQh'$|o߿)e |WW S~QFj+{j?5ם&m_)]Aկ@"NHNX-4~u5 D9̨X-MQh@@9cxq"{m C^Wme e+Q\}䅵7}}M'ҞI=r*[,W7H RV/EHs[! ~*CL,,Sja mB*,ިˬ5٦͗ 5 4:D[rZA76fL$=lC#5N6@6IX>=2]MbU{-B( HJdE^Ge{5r>/ʬn҃:n* <iS k=d[s w6Ix5!q:붂lfбo 6ۛa]xef@C` TYQ6;*܈ӅQhð#_eJSһ2EZ0"Qn$xI] *!ѫz{`K I!ycShd*$')ؔ`\;ȁ&px[lTQqXXp)=Ǡ[AOH!6&e\oF"Ít6E:Ì8Ue*@6آ@ ԡ@)L<1Cb'?G \Llyݷ(xPS!hL;UkV` b,3e/u=E 2g'_/"$juL]n -`HGw䛷n>#oL~zd.­ܨc#yR/"I]Sk?sĽP=oHÐ.mz{GiV`|7_w@4\U| H83{(P>-WoF>[o+ TN9-\;z';9S\1gڅVzH;\3jac85zs{"h{{]J0$~p&RcfQ7$Z@^JWuAgًGsdf:F 0-Lq0\e03Y ω+dEPD>lHfGSPkf>/;~/q>%Gk(]B5S^X&>gt(=ӯ> x@d[;MsVg$*RTvu%hH١'M4Z> BM%AZa?oxy$\?Җä 5IT%+XH 2JX9un(֥ `Zc70J7<̱32)KP ,P}n@Nx挷 z%9+ g%?H.9jeI]pՋV7 endstream endobj 36 0 obj << /Length 4037 /Filter /FlateDecode >> stream xڵ]Ks۶WhisEwfvȊYrM9n$d2%:o>`>~^IVi\yXy#3_>sCV ҍGJϿ>mklngHf[q)V"m4ܭ+<:P M:`)yn喝@Oww1Wwj |Ĕnn fٛn+gC6j 6o4j #RirlcGҠQ*H3}8R=~aa\f ޙ.HHʓZwhF=n> DBV_snR)NA'0JOe4t>} 2BHF PD\З %nX!Ju8YJ{ `Mpdtmyrh~",%%iE1)HY"#d)R65RI(H &g)1FzZv,U0GS$koӒS'0X @swD/G{‡_{}y ЦU`уil31sUNꘗ30Ę8{h?ևU_- *bgZ*%c XuKJU>@@G6l;Gm6{a>I$zu{>|[u$pȪK3,("MV'ԐB yc/1=fp#n==_Arslv篷y@dF 1@;8"EJ. P~HF Rbd yOc~*xZˢhb>[)vQggoL!a)v;ҙG-&]ϒi,f!jT#O2 y ەyt7vXz7UAҽYt"u5/c,U/ OXXOͳ7 ܫ.lL1 7˄\ͥݡli ̌RtbNBG6]HAGmliߞTqxHdGBMN#?cDi-g`ԃi)D2σ뀍'4 |1o*v`g #&zqFݷ ΁Յf)CFg]5 0"qk7'%08Ⱥv..,o]"42h|C·BH3,ҹZWM„ j b`$L5\L"7٨= /ht=Jلgf?؋=9j}?9`=\Ǣ] 9ǟcLLN0LPt`b CCX͖y"xZ(dc>'_4][%{ĝ_/_` Fhlvtw*}$)xIYT#feU"/T!TmYBU"KX1XXJQQ fx~*#ʗi@cL lNdcDH^~INتA1L jySfŀYE:3Ҷ@#G;ն}tţA1Ae"_ qt~ }12E<%UFC5器ulQûMBwtyq-ҰrKf9Ul"֧+0M| ԛ:PvÊ$5M+I FDəun MdbMzկƆm6?Ь0$ihC&wk(|.' tq v=uD87k_hv0$ې 6?|&Q,B/ܔ՚:>NB@hy(alMU'ƸLc-Y7(myqTfǕ4C;[fª B'AmU+AԼZlb@f}=.qfP_OYO9)kHY,h n*Toc<_VǸ$U1z?Hf3Spe>nS=(%2B_0=Y.`nk]]s c<>&p~}1.8j8Y$Ƞ'A t='=NMydВB[J+H5 hO YX"#d(VR!&ށgVn:hd_S|1mba͂[ p'L D.#䈕y' hRFs_7[f\/p %6[l1=z%02AO,#N? #vf_žI8<9&8GR'J}>R`"IX3]G| S}u󩙘Oi_n2Aꄺۧث'rPIS/L, k=ǭ/O!#)$8,bN/uL.4'3 ˊ)d fjnql>*o8Y TiUyY"#ŜXP)(|&DR~^KZa^"҆E2|_J)"lHy5z:ybjib~v^a+ư^Ԏ 9۝2Z""DJ9r[6A0fZ` u "KMD2~}&&$*gg_Ip< XVb[ ]!CCv5(B3]t QMX"#d`]ɛrHIM:_ 3 Ql У̶cf.iz %dbxnhat]1~e45SpyrrqI4^R$uT!R<=)ZUġ0E]RدWy%]202ʖU=1DY F]s/ܰ#;S9A ׊"l/yѧy[`L յ@ݷp1^gbw¸Ct8|J2?y&9N!d̗'5R"R$׏k̆p\ٔ=e6gi;z9 l`TG>>S*q^:|61=DKaw՜a wc\"! w?^xo>p[rO4[{I(>h}ffO0nT9֌ ade} \JaLF Ȑ){4(M8սUu, {,OM<]m d=WFe&Q6-] >M35u~8yf)W?&ni.#Ҁ5n$E^ tWH]q*)[WS{:v?!S  ק\r;'.=0ov w/ڐU wGURaS7|pΜ`?gDpV6۸!^G yF7›gЬ}4n3ka pzE`5۝+cCٱj˻~`"!e4:pȓh\;O1j9rKCCB~R\ endstream endobj 2 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 98 98] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 39 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJG endstream endobj 1 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/hexagon.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 40 0 R /BBox [0 0 98 98] /Resources << /ProcSet [ /PDF ] /ExtGState << /R7 41 0 R >>>> /Length 118 /Filter /FlateDecode >> stream x-1As^1/@`X^` 2E0T YA=qNOc?4M 9,T;SvzI!ŕehV)OkbJ#S|8xh+] b endstream endobj 4 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 225.999 144] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 42 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJN endstream endobj 3 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/irregpoly.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 43 0 R /BBox [0 0 226 144] /Resources << /ProcSet [ /PDF ] /ExtGState << /R7 44 0 R >>>> /Length 311 /Filter /FlateDecode >> stream xm=n1 =O0?}n #EJH6@ob%^EsMo? 'P*fvjqp}]",D <qe]X/pRiuS\ *qX2B*XkӜ\lDU1J卼PX]rrZ0CP$!7D,(ƃ[Q5C2)RHQ5A70=x"EuZ1m=@4)YJ9VL,6}9f,q^ѕ:'1V8'3&R[UXߑX | endstream endobj 5 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 225.999 144] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 45 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJN endstream endobj 6 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 225.999 144] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 46 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJN endstream endobj 8 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 719.998 503.999] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 47 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJU endstream endobj 7 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/mask.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 48 0 R /BBox [0 0 720 504] /Resources << /ProcSet [ /PDF /Text ] /Font << >> /ExtGState << >>/ColorSpace << /sRGB 49 0 R >>>> /Length 313 /Filter /FlateDecode >> stream x}N0E{|q[@Z %ZX+-)}b> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 9 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 225.999 144] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 51 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJN endstream endobj 10 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 225.999 144] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 52 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJN endstream endobj 11 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 225.999 144] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 53 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJN endstream endobj 12 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 225.999 144] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 54 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJN endstream endobj 13 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 225.999 144] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 55 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJN endstream endobj 14 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 225.999 144] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 56 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJN endstream endobj 15 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 98 98] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 57 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJG endstream endobj 16 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 225.999 144] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 58 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJN endstream endobj 17 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 225.999 144] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 59 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJN endstream endobj 31 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 98 98] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 60 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJG endstream endobj 32 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 225.999 144] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 61 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJN endstream endobj 33 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 719.998 503.999] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 62 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0B˥kJU endstream endobj 66 0 obj << /Length 2431 /Filter /FlateDecode >> stream xZ[o~ϯ0P8+(vv;hEyYcUrd'lu#|JwU>(BN6-&L3-Ծ z?ݫw?1OcJBTi AGVt="c뺹n$'2ULJfRmo~5,ϓD"<ۉV0k72#;(#*QPŸ@pr_zY/BHaO_EW ] 7^(̦*{6Ϥ#Ɍp:DGSeEB:$yfHA8HE$.wD>sdB$}#iu'{>UAx =k‚)Y[hɇ/;Q>- yQg]QtpI{_d=\'R5 i$[@%ΈhA`#ャPQhxNyhzlڵ"|c`nwr,cd)=cά S &ށl}PC13w|~z:8iЩ ^hߢ9# 87ެDϽ_Rhsל ɴKe&T"0zjաAKm.,yphB謯]є;vG~k +n"'VM1 Prr2S =~)m[$'}od/IB$UpǕrĬ1 H=G0XWOyτ_8E_ScC+IJ]Wu`WRgzVQ-1[s!\2q0Aۗ,` `@`F\Y|D27GǣS-,zVR,R($MZs̸96:)eƀa}Aryl|pwo#KuV ^1@xL!^fc F s\v0$S!m6C2+t\ŵ"CÅvMev؉?"(8|5& v$( ) Һ-}\L519:+ZYc"~Oѧ$pA^ײ{z,hѹ]@]~̾e[txU/35 Ff#T;P&Ґm;-~seyò !mZ0Ѕ\ 6 pk(k}%}?QRL[|] M! [Dt$Mw#~` ^XB·`oRoxa$*I ; 2S2LZ*z`X"Ȳ?yƄ.2g59pt#͠I5L"ŒP* ,_}囎CdP_Y!Z#13Q & J1_/x10bLFxtDUFdX) - `zb͗`2um7 ՛W5</ Neb!>хgk.KCN9IB E7"Qyp]'%MݕMpW[w,)L=p+$Tr\%FTv0#&,"ݶT@PP[lE8=j_{8L9e볒 n0?ur~ݭi ʭEcg>(RI]5kHmYo tcz)_*0#t-}T-MC-eW|<6ϑw2Đ8Nra9sMĻMt 4Ҷ4|vsicvFg:x)Q| 3W6B >ĵ p񁐲?2ݢ2$Tݪ'2j :\A`i%:i'S>G[x'!}MoAHeX?~m_J)VTtRK15?gl!RC?$ endstream endobj 73 0 obj << /Length 737 /Filter /FlateDecode >> stream xڅUK0WD"oly  mo,lm#ڦ4)y9M ڞo3LuG.SYig yP?̭Ha%3K |(xn@'LJ,FIr| H{X nro7wN(NSޣz2($4ɎV<,5! 6aM(zp:;"]3HǞa'ViC7gD@'z$ 0쫣>AFņ[Ź+fK kND6A` K(s*_NTYc\ˑ.]2,- BkwֹV:sZhl*2wA=}pmA0 hlEOsH2 ޯ)daS /=1RhQ`ꆘIlO["]V%:|$33m6yri)U y񭩻2pNa)4՝)6JH, vd;Y:.*b.7VdKʜD\SN+6ci Ao~g?GܧLȣk>(OL,?,o^49hoh5~gL15M4[2t^GC}ic yO endstream endobj 63 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-005.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 74 0 R /BBox [0 0 396 216] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 75 0 R/F3 76 0 R>> /ExtGState << >>/ColorSpace << /sRGB 77 0 R >>>> /Length 11615 /Filter /FlateDecode >> stream x]ˎ-;RW!L3i#@B#1@ Z-hDZ7B=""Ǿ__z_u/<]>%?uu?׏ן^񧏿ogi'_\T2-q3]?~7_7?}(o?yݯGng~"~u\&yU> <>SzT>;+Ϧ볨xNrٝȯ|}2bm\Om,}=%/O?I*Pڟ "(9ΥE9߾|-0Ö@m" ю]hV4c6Ilլf-l֩}zƉwWoRho]J>Vѕ淝J.2>]$h;/9f=';sڴ;=r6ws|ţ =hǻOMs&xmaجx"nY dVD=V41u9лtm.ϽibB믰3z-CeXʳ|E|ԣߛd7‚OFM3^s};{IwzJ(`ډIO4+Ia=|5ic|We9Lr c::Ac|`vOvY0=ne;'`ρa0MVSM󫱥:zI|[GϷrE?K Ϝ~σ/lulS==͹hhҤXsY:k.9I5l\(QdӰgvv<[<$Ϗ60d ~O=u̙r6x?jĎ>M1$ VI>`ت9дw8)fg7 BuZ1XڴEg.7&xf~v6l ~|X N"=ahe4 l*. Ix1`"EKϱV/~´lc}&k63,,Ǵ4n!$pEaR3-^sAi26́&*f3M%mM N_͙;%>ߊ"&8.8k9ÏMz=&ͮ O3Mg:Q/&g;)pLGsk[]&tÞxI1 t H]tNѢ1~Re%ʀ#IC{o}?uxvb-g\k$J P5G P-bs C:<ko?9ii W;} ykHb,IP 4ΙEn|kqŸL&6P0iM_L)Ùb/Q3 L*͈&V*M^V$rV/=;qI/qX$UBWOLl,M>9hٕ} LcnZSW $@㑦C{#}mC/f4cѬ+kkkI"-%dwFhbnxhXl ^D/ڦ7uk.F3ڋW¢zI20ӬAdF#I}0Y+)T[<'0Dv`~La\/J'40#8qƀm.SLut0m0{2:E9b<MJ $ۺ1#tuԍz[GD:R5=/L#l '}D FPW4 ~ii:JĤϗ}٥O/=}G&?"y{0a+xN`oW߃'l~Nx07٧.F.Kc?&~-obYSg&z0=4t9k䃢 0iW㙘,..gӍC9&9k̡ݱgkol6~g*N½G?M 0] m mPg-}#}"1 w,:Q'F>YLG:|<Ν}ʦ9H_#]pѬgT[ə5sU60e 3dÅ'oa3Ǔmڤې#aMt͢E]vN$D >XB'UNv;ѵiu<0_&i9uF漞ך=wM& pt#z^ӷOR&lav+4 HamTuödK!I3|ٙjpKtםnW8G^9Z8&Yj8x=OZgO⵲S_΅0" @l^16K30!?&p#x !%aǎ+r|ϐ+'|X|lZ R`5,N#t=$'Ai]/E<"a {9'15XNgEˤ=zFȔttM/V~P=D8}Gd\L9j%\H=k$ʱ~i {֤Gbi$x" E9Mhxad7s(1ciM2/ElJRX%[ ",aER]Ɓ`| dJNKpDC`0^kfp/Kօ`QT< $6ĝzRc6q$~ Ap"P*%f;wMU*]))!UG8I͸1rfˆ*S1_p"P* YL27cAbN5S3EV%wlwI奅pT΃5#R(i.8V$V{ܖRN]~E &\1EfqsD 4%5V"Z6D[^9C2J˫PJN]>g \*HdD -γq$P*%#EǾRe TFCWw)X/sIĬZa }4IIG8Ƒև"cꍔ pJ%GQƸCW`r-ߛ`)c{/%FQ((K_08 R;TQN%m+o8 S+cW c8K69m3)>%^žz{Z(-28'|ٶ9Βw¬ Ƒ닉_MRbSRj#ܡR43Zq"ڎղ­]ėI@Tj܌*ėFO}>ΜNxe`?Wb I0iһbAr|dAE^n,`߫\t1PRS]UH=]b'yV gYr- kjndNIllger-^}e_#tAkk경1B@o (K/awLt\Ov@Pv.Clʮ{-/-/?MN–cSWM*K.}xa*yӒD&:崧Ɗw1K,sN.io-^žzkʻ9Oތ #%,@b7P\yu`_Iw⦥TxuJ*;uagFG EaǞTp50Z}U֬gB:Co-|{{3Z޸STP1}\i}pRggXQ(Lecmuv&˥~.#"NŰiR.t\",y ԑvK Ԋ>2/[rE\D59^cqKKdHh`y_KcS(Sx, ;&e-^žz{"9;"RkmũJpo)iOa+]6)oXrEoil Pc7G|EP0IQaviͨUekqE (ONvǹf2 бmO6´#lleӬr%쩷#ʅk}s۶S9)OZY]Nڴ&ŲYSo1n1T$ vGlqw3LLw'&x5W^̜襤{%]7֋7]i.lō>{c|bKs2,f5WTzM"Mo%evplة3]MBtcEˎs!jler+S'쩷fvs [Rc1UXuRƖsr_a6UORWЮ%^ľw霽³ֻX^9l;A ±{h5u9 ?}M [/bֻ .sO{pizP{.oss"#T__Tc 2.쯨%^ľ>^bO{/>]>M/s<[:m(NT66IEr%.av:_%cEՕW22J-nɥz:Ax8DT]+rl*ꋃ1-Ƕ /Nva?z] Yz7 >ssDc͜?8I+Px(E-1ƒb|ZswMOn˥z9߭>8')e_RC˻#7`E>8' >^}l-[]Fʅq,&zv-m)``EGԋC:*vD\z {>})Lg{LRDsۮp#^P6&`36I}`{~c~n8-f8\c0 S_zܗ{(5U<-N^)Uvl\z {m;5r.t<""6)ښ!j+oa3L%8s}Toˇu8L(LP-ǰYXQ(Ogz(fVac.}r%쩷߅Z3#"w3nƠ O˫S*kӒ9ޤʾ׾%-JD+3p 7o"bCZė=IQK;BƀH1J1άR'ܡq9sf8Q :6) ؑ ).0D^x18 Q ƳFC=Nqlۢh 囹9S5$iMƹJ n"NX걝uZJm;tuf8g_5XqR4X6vZڱN8ĸ0+RI8uZJm;t}s`(-3\f)xN#%sgT PRiCܩ)Rb4cG2w N5‰(hRn'T*:%6Z-^^#9fܷSǮ{}$@'b!CsӾ߻zXFSW}\0v~A ],bc'N,qa#V^9LI\ .;C$VyQ*W{SSڪuG(.RRM ;zMpEf#a>bD8 ȈqquJH m;t4Hƴ.:*.?0eHcUnc$>9q{3()l\85vuGx0U* 7ʬ ܛ<6KU%,vG%5$\dD>ƙ(f,q,5oSRjCv竮dM:RA.Z$qXSu7(f s7[rE2;_q~e#n jΓvZOn;7ocw;w-^ƞz]7vx?u_/O0l3 $TgFݏ>خr/NJ*;Y9DYI[4Hr+pbG%(E`[]m_uR*m;u%\7OF ]%N7v{p`>#q$q &V&w]FCםF ^OW{)qR#vJ8kJӆRI|FCy&ݜWIpmG‡}{RH)iK \T<۳ֶKH:)6ĝlOsSYhɧ`yiP#/uKi.NsBɠ 1Ҽb9SijbOzLzz'"IꦅQU;FKWR]F٩<`IfDu`XUٞ#Z%kcd$$#TNAIpV7ĢPd wRUGR6'¾1yOkDt"%+Deq g-T* >Twf\f xc)ކv?ˎڕ>D+f8*uZqR]ʲtBfgjÔ_K^/ȫlE);*ʾB\z {m k-/XD}j]yɳ0!MB7.q٤v)ɥozM$}}8Qa %b nHww+r^_i,r٤ý/=~"7cwfwXˏxY1L,H0Խ"fs.x"FJxM,K.=ֻ4f?o\@mt>m wVĩ8hlETkASoni~VHy5ŠZio:FY7Һn˥. 'x vw^eeYqb.}&u[.M= L'eEy:'1 I\:Z+lmaX\XZe3Wnɥc gnq ]s;v%oW5ngka.{䕷\z 7_7"(\`(Uϣmܲ$XI{8HW/,.Xe_Gnɥێee2U~S `]8o)1޵U0.V$j[Rj#ܡUMZ2F*l~xܼٽQӗV|eʫpÑ%.^`gBRN]Ͼ5`pAm9nDt #:nT G"0.Ԙ7x}KfI!u%^OHt6Ɗ׵'),iЭ9X[c̀*Ez}Rj#ܡ蹥:fق`; R$ND[5b i*MZSRj#ܡR"&T'FNأG&z` ۣ,x4ĽBC2MqwZT|uZ m;tu߸N%I =pz/z/v]&1-waȫk)魫_;tu}WR lLq6< ZnH^8lh5\ȦRITi)1խF_n#>/j,L=kFسa)z4D_ӑKXjYޑTw[Kk8]&H1!_@xXS늂ũppe_̏\z {w[8~Cs̬ (\XTyXQc74~4Ԁn˗ ~4]ν4~a>Psj,WP]%^žz{dN+oNf,]LԴSI lRk}z]2ΎU>Z+3>nlt%H£e)~Ƹ[n?J[׺uuJБCW D{McMWb ur84݉-|KpJ,N:ɠ0[E),3H[2ąw9:ȴ<A5)$pU+)*J[Ӷ} 3.U0qc"X K1茫Zjk+@KwT* >:%6ĝJMZ*3=9 rNM**9J+W#.1=ݸ@i饭IJt HĥбVYѽ$PQqJ[{ˋ2H}ۚ7T;5e"j}1|q_U6 Ҭ+]~a|/qqk$e)O83bdZR*8?S=t/@^͍'9yCC\;} D t-)cHK (ݍFNJ qn}!S[ \.5R&v ۩l\o)KTuJJm;tuqZwAOc 2:-ѤƁ`| .~gJNIq7=F8h)~M8,1vYU* :kC[zĝZ$cX$.Dž,8N! g#3@2&b%.y\+4pwj[4W[ @+D (a4\F1C RV))!UӜwV@/F KO|&̟3%#nupeKuJڜ{˴b A#p&i)n6K \*\ϩT|uZJ;t4Έ` lƖ܇~-&w7X}33 ܮRI:-M-Q]q"s0 sb$5jv;/|x)X=Ԍ+bd&*ERGk^J-NtKn/hU(~-y]sĚN-~ra3H4Ъ[r%쩷'2m}N^_/\!C\ :G^\ xnM"Mo^m}l̓wəI_W2V.me]\7֋7 ]:Z/5ͺ-žz,2?&NVe^`_?t䝿!,)Ϳ4W,5TSo(G,GsAW gK$׵Š$87i[O*>UKSoWӬ]%qxX4^.ހ.UE%:zێw0<}ryQU)eĚkQ_dYSNזK/aO]:vrG^tku^y7b;/休b"B3s 'Q1'qTxuJ*m;u?>~7_G@~75g׏?Bt-2t?_@l&4w # endstream endobj 79 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 69 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-007.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 80 0 R /BBox [0 0 504 324] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 81 0 R/F3 82 0 R>> /ExtGState << >>/ColorSpace << /sRGB 83 0 R >>>> /Length 14140 /Filter /FlateDecode >> stream x}I.=n7KS 6ldd4v"?3PFw Yŷ H*__<_~>k?ho Rѿo?ߠ.ww>OuL#78{w=ן_/?_?N5_|_ï~W?nM0YhIUo(Wk*юL.1J-})w1R2F?ZIR)#nW}|s >nOSҧ|?q$1_Ӹv~ߗlRGndi|u8{}kŽ^E>=zRڿfhd6fHjSRYCn+ͯc~Ӧ'^b4w%^JZ:_8KɸA ׯsX+ ^6-ym-^ʳF-2wo3QD1O3ʓR<`H@+/%D'g= MIiptu>g1~yվ|wUxבop$q <۰VtѦ2V玗ul]#{5:{71[RZe%R0k}?OtRi%m!k{٪?{9J!ҧ+ƅ/f0Z}7lW'K# v¡!kK٦FVw:N2OUwttx;U/Hyó"TZ2Ft">⥗N4+ "n7}fvdaa)/hw %n@(YKipzrx>;玫D_\dTDW-%k y8 SA;uj[rEnڜ;]c9.'dOΞm)hVXQͫ91v9nRض䶔ؗ-:\1c[B\x$+ y8% ;bAj-v[x]oI͘K3kLD=0;O<Ċn^-Nca[XAj-v[5:~V~/ <ӭ}XdԏkY~ucEA;#pyʓIj-"ezy o?9=fm*A1whSQMͱÔGc8%FN Wmm/[IPgcd?:S>[Iq8e."*9gFOl&aIi/tꊩ/s*& -ώ'zyC)s)lM/sVXGnr1aw2TИ'F>;(ˉSE̎+NW3o+unmv[#l=윹ql,݈nSxcޞ)=>}aMA7RY؆ѺAQږ\v ۭkZ 3p7wuFgw= )ܻUŷgXQ-G!sJ܉{!uj[r%n9jsĔN#㭘9\PxgYk?wO)  yujrEn=ߍp >;([<9QVwW*)`؊%unrEniج1?i|k >k9mj t,7˒ c)pk,c]϶)]9uc,Wq}=9=<1ru#h~#RZ,xRXSճqb8aDfݢp5۶v>8^9慍\߮(57Һ`%.lޱ Rm\v չ}VKp~s`eқJ-ec)SWmK.}yߚ(9p #X3=(5شĊjv%ktcqҝ<ۖ\v rڡˡeNYtwm9ɩ(}%XS,]]ԏސh[rEnWF?\ڻeTWM |G nN^'y̒zbMggdlD'F&4۶v [~>;;$!y7TŵDpmIUgUkxGb6w&Elr%n9k5,yH-ޡ|=G3y~W]rL+g Wme_:5z̏z<1!|1yg|\$tk3ucot¶-]ľַ?ǣ}*%pwǹbF_b_cyKz_t;p%{ak-gnrEn,)+*8#rW#|pN*is>cn^-Na1u meo\ _g\ o0_p½oH,?CMbEӰ4"jݠxڦv[%FgDs9,)d積%Vul/lnR\!mm)/=,<eh>&]̉:)zI0XS=WT (ufےˮ'R74d ׌3+JI+XY¹(ᚁq[kp&V;K-fqh&byⷸ|LD@+`̞vNjJZѦƸVDZX~;dG3_GbĉSLiNR2Nt5#.h V;x+mB}Μ&{|R8!h3JAfi]!h)!nU/ρ%r56GjsG5t$~4#:Ht/tͨWbyg%בjRYCnBl!h1I|KO՜zE[c=o=^IDGD i$x~  K,D/Ę?.b i]TmJJkmR⊧=;KD2"&exeŢ}!j bbrcIQ5/&=|Ipv%< vOsaw09t%XQTd2!ԝ!l!nnOU/La|"܍\I6Wt2nk89p[IǺIq %]eӅsӱvꀆ8%]>eeu q[W #V{xrzv5uoNM9-"e?f܆qx3nCl4X}Ol6VT?O oZ mm/~je|vNn% ;c:H0.*q:M 8'W@\T,捅74ug>ۦvce7>;ۯbu3n4#sCuѢ/ڶ\vۡ)w -s[qx0ճocMAap06цkE14ŝQ.b_v߱[R;f9!aMoIΈ;XxSR7vێ88V9bķ2=xnm9frlN';=u\Mݤx5۶v-)haimI!'b)Ga^3g ht)o,))Tl,nR9K.K~?MNNUy{B!4LM*9 PuP۶\OBW5g.Y㋻f%-S{R>0X% &g G.{nRmKnK}ߢt9uVHm!HVlu)e8C83e MJe qcMNGcYgwRQ%XSM3ֽn۶\v۞< QqfYc0mcst9/vljqV彵ܶTn/nZwgj9vCϋ#9 )"3/;K̹uTXF{Eݶ䶋ؗıbY4ԋSc;CEq8Ǝ֔soClck hNǢ)"or`EoI\w(MWmmhƝѣ|#6) f^DlFGnri]ti)nuT\&=fDԘ=pdt'"GL#Һ٦V!$/Ɖ\fҿ[oǔ8#ŋѱa!-W jSCm^ܙadV<&|[j@P+/%Xx/E<6[t 8065?Ihb7p"RƉ?fۤTklu #w1:]g ZJLfk\2cV q&փ"^+tK+ lRXCVO\v׵ݛE^sr`P^HL- :og<4R]/ȶ%]vF [{mkƸ[z$?%g)cEoII,lM[meBX&õAȵuf3++\\bbY aEe69$ԝl[r%npjiѯƽ83J/I-}H.ݤ\mi^C2s11$;fB9#05a@Xz{ݶ䶋ؗ~WF9 fG6l R3F[m;) ˰uVX[v~ }ŃWʼnb%ҹ3W>cWWsYX{= MRb_v{{Í>Cpv Pr-( &UnR mm/\1r=q5B{W9 3X%zг9  вtogm, г\xYd>D4A)ܻvzsšjD&WmK.ʵ֫E)2B-Ҧ)E '&R~C$,'ضrg-v[.$JЭȝ}XP.+w4$TFsdMkz^ij d<{Pt@Ӱ!#PGgњr>3VԊ@- 0JwY."ؗޜ*>[ڜc#_ٱf[(@KĒZpˠ ><&ūAI.K~G:g'~W36ƾ$G:-g$SXQԽG:tvlnR{Sr[Jn\r|X]\͹ڦBǶ'sG k*s|"9ug.t-"e+m@xI.;#ћy;2id1=bM9\ ˈu۶\v}NΈ&a+*Z)zrĊrNb3;ۦv5l* cQV,mdI9FĊJGrj/WYzζ%]v"+ 'h?m 2Q%+ĉȼc3*]-6%5vH:.FN96`hfN`} 拔j.MYK%)3Wfj0qkusxZz.M)򍔲p$VXYqm`ԠVu%5mjZңUΚ@7wWٖ]\S eTemz:S)ioЊ}Q?e@sK|w3tk'b>8P8 KJ"Vv[pڼ"fcQ($8<ƉȳHn"LMKip9UqgcԈl&b+ ~\#pG"m2[ڄ>ZIRi)nձO{\++UkcL-E%]Dd=%q|JX*kmun1n*X$ݬQK#"Ȓv 7…V |MIeqSE`ˁ߅ytfYtf,Y$QP+N-ƅlK Ml fié֚]T[h)*G"fhp#NlSRZ#f?;9Lj4Q&{Ҙo_KcE4fs*ker.Ԕm;ogawWb]3MY|06[VےRb_v=cWj&c=ȲJ&s &%Kc,[ҳڶ\v1e._WW]>lva]b*l)ge._-N:Ei]rۖ\v 4q=jn{{QI(K޹E]XREcɚMWC.K|.a~2ϊ(-C[5%9avے.awDzٟs1}7" sc]%; Q1\>y wKp IuW9LNc#,CmK.}mg |?;so i覆ݹ2坙Ě@9d_^in[r%n/JgpybBJpmq+$`*dlijԽۖvA[srxˉ%F%{۴} *Xκƚʤgsl,{%!mi/dh-ɩL^dp}<iϵL^4VTs1{;hYmK.}.Dm6I?*.jT圜 kj=Es\ Ƣfv6嶋ؗ^reg\7fg0J1y)7VT&'Hfے.b_v6n%9Ms |igʕ+.[2( RwϪ-%S!]v{NgѲl9uBqs%o;'RTEcE,e6+% ;RmeݯUvDorPLޫ̫}[2pGup/VEksI}\4 .aw͙}k b#b{ 8\= yPyDZs.l$VAqYUf)vkK•[+FlLˋnϘDy~u%2J0MOdaR^aTMeJM)+%>uHM{{gbA+otۖRaw_9ߢ.v(֘ƋjIꕇV`fEKV/Zm[>nS`gD1zy>[Og% ]&b JVۖRaw? $\(9ՒdOI_$`N,ֽnrEnqv$6(sA8'Op we kb k*'ĢuJٶKnoT9wۅG3V/ +j6Nc/nYmK.~mQjg*g~"Sa=^I9q0vE"9L3 ֽݶnN,+hc bK݃rNkj,NO}8(k+h-?]{aw&m8ۍl'>L*Cɑ#.Ug S*|sHɹpWjp`,, p&|Hҝme)Skaնؕ{ɹOXQ+XkI,lMݫۖ\v 3'#b@Mځ=O$vĉXgQ Li]NiInU[A0s_8B‰V1b9c~V))nu3oNt<0Dt$jJXĉf`p},2ڔT@Pu?b_"Sh8,YƑrf4"Ii]Z))n] fd>\e2OЕ 5XG"<8qpNCU6[kŸx:ubc\۱#k8^kFg8u &Å.N+\hstdF( -GmKyұp"2\(jG3u+a6-5mz36ܨDWa?; )]]88#X8li2q٦FVnl٠ 9~bN)eƑX1@2⨘8!뗪MKaq8*`Y {sipW^e1#V<4HEzx]Kipmi݉wks,!;ûI]{%֒Px\T!aIpJV&H]53أ_R>\v oV^v|;JE*9|˚p[޸qXSN I,Ny qM"ey`g8~b5{ !",g8XQy<91I{[nEݤx5۶vAblUlWV= n)Aƚy5lݫ۶\v ۽vFޯtr Jz:*8v9?"Fďh=ֽOVے.a_v*OKr`O̩i6l%j3ƼSv52rš=*(+[VmK.}~39ʱU_ضǡd5'ۙT!ypݝtv'֧!s[JGUO+ 9ƒZG&;^UPVڶ\ ۭੱ8m\f2.[ɝg j՘w1_<Ɲ` ݾ,*'ؕ-4ut\MaiTmW k6^LY+*L" 4ugh-yQveweprԓI{K9=sƚʧlFLlc7ΧmK~} n'>0^sxn}y.3Vx+|8~ǢV9 S|2l p/[IRW6lr >.5‰NcΜW'\*$~(m0d q/[_/?:v|O~]߾ J%oo&Ƹ=;Koz`_ņV{Ͽ2K{ endstream endobj 85 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 90 0 obj << /Length 716 /Filter /FlateDecode >> stream xڝTn0+d$b\4[Ȳ#ԖY,4.μY*"la"k("4K`#n͢! U9HI C`i,Ҩ\FwZtq)HjEn 0'ijK06q<1F @]LFL|<@6yAic.i\kzA}0BϞ حh|z~L ;Fn纠Hv7Otw˺k=2ZBt-W G[,fѡy2¦ MhRPˋ{ḿjkUZɌ84Sdv]LʊLx~WE& M=nRBoKy#/w8m#n[BJƛT :qYjpe HԹ }$s$wfCEk00'`VC~V3LR5\N{wR_t3,54 ɲf#TP9/&3<|ěOH1`j #K/#Ԏ]썗3^_k/^-'98nz{ŹqMx-<*lQq \Gヷ j*qQ#M!*Yn o] endstream endobj 70 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-009.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 91 0 R /BBox [0 0 453 288] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 92 0 R/F3 93 0 R>> /ExtGState << >>/ColorSpace << /sRGB 94 0 R >>>> /Length 3727 /Filter /FlateDecode >> stream xZɮ%qݿK{Jl@ ]بזT'VZpHF0 Ɣ~*^x|'_߿y}oOa_JbZ1x}zO?R5!M珿z?0zן^o3ᭈ~l|kkckeqnojkށynG{.? Y^e;vQQAc}:1o|A%'a[}}V.(c'Es;ɱζyc\}kc7ulB J*7MRqRnV]hڠ wXԭN.(h7&M0֊iP>+'>.Yʤry}zq>ʞ4y BD<CoP[o7~,jI,4xve`NY%MKi[o{osX:u6Z_{XzU V}ιM(.s7Mα3MkK7N]W4o@~\^9`S F IS̝vA9n/$_SN\G׍u?唞.hjăFh>=T{$6ͱuID)<,iquɇ4v*I{\X4>56<ʀ,Ƣ9+mc cyمeoGz`oӲ.nFKӥw,63@-l A;Eimѿ-l xZ~P墁cn !مmoUG9eTQ"i\]`H@]'m\*`ԡĶJǦ15Cۇʟfim;Eow&9o7i;8?la;uXLk8# CMl{OeD(|K&=(SX`]4pp *rslSu"N"r sxpg`\&6z VxF̆κ񅗽ѐ,#O,A 4`WPP 'zH635ezlE C?#d<!(){@)A)Ыz:tS]wPHWWeX:o:Ĥtĵ;t<.> Lƍ<: ^:ZɅ!V/t&ʴb%LE I9 W8 .w)ʐ&]#eBs#ǴɄT%4TQr(T };/h\7&/ .Co{oxN'x z/z10ey3H ¹3ʉ&8z;B=hzNAHdR }qzCvL틮 `ڻ N?-r8넾!Q}WN8eIWS΄_pU *=.:y0dl1/l2M\t, 9%& P-Pl#rh*V1Aw=hV$mq{|O?,(Sϒ#C &*uH!yft6x{uKB/B^{{>2}rBY |T"Ð^3+7Jmuk(iW/1rS\ C1BbDJip IE JF~k/@12ӌI{*LFi$ ڧq/CO1~ Uu޶2> i۫c۟Ys7o#9S<˔ŽSV .L/Y)rM5ݴfm^1rqr#Uoz,(Nw,lӎZaB-er62o+ir{3e=mckdpj~ԼgD+Ty|ik.B;YKZ;C}]c=2,p>FabWͮ.S#KwlӚ@.r3֜ TdJ ~cqTlUqk$7yq&oȮf]҅m%>ļ rYfr$kՅP7ʹ@ڏs $^#M I:7NB^{{>2cH_b%=u, `q%NZ#k=cтyy4hrY؞FӧLj 4ܖnz#J_m?6&m QBvW{)w]Gٮrѿ4 E#_B`#OzѪx w!W>0Dq9"T(~Ըz/۫cZ;t1rwZl)WV j"0c/JIVf̲Xt'ԘvEp54{3S֬z4ªr`0u/Ĩ@gyY`=@'ӇZӘrϘ4A5Tdqn E\%-?!LGL:U@c torR&alIvT^iq^Ѽ2pG^s]qR t=z@KgZ{ʚ_ c= SL2ۄS¥L=9+t"=/BDt`F\ T{Ƭ iE_g&9p2f5.ɕ9?sY}WO: ^ 4M(sϘ4A5m_P[w Ҡy1;:N\?/bX\ T{ !~4?ԱegB|uYŌ'ʜ'z2kJ܃jϜ4I-QlR L'oyrV( 4I!YrȌ{Ƭ  B:,ݳVP]]m~)߉7}WakP0M@%|@Klm?V1o#9o)7ҭo_VMxρ e_}cɠXQZo?'o-2X}?|LJKEfY2E x}7K?aA_+wKWUȔ & 6L甂6VnXpҘupY(}QDOĢe In Y endstream endobj 96 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 86 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-010.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 97 0 R /BBox [0 0 453 288] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 98 0 R>> /ExtGState << >>/ColorSpace << /sRGB 99 0 R >>>> /Length 40725 /Filter /FlateDecode >> stream xK f˒WP'e/āxA=-}WFd䷾>AD]Oe|򞑙ǿ͏ǿy?Oo_O#L)?GOGn??y-(ǟ~G??ٟ3"l\/Yҏ_~Dӿ?~?7dMǿ}/řpLj"t+t+ ~y.Ľ~E ەᚗMI3 Ӥ"2%“.Ij(.xPG`ic2N`W(kp۪(梺S:JM›ȃOYǃr<.a'( lwFzrPG n>sel бCT~uD,uV[NɇJ9 Q,'VNm̰ب"ǃ_~#9Nт;Տ6/Du> ,3ʼ pr"x{c> Atj*>d8171A'6b߮CNW[B'c^DIą b&tQĊv떎1=9w>w "UodETŃ|.]PLO>ALO "ČČ'Yqu>+ 1y= W[x+*`g,:hwT^m_ns&ua6)w{p#>4Bez'+b_20>X҅Bq.Pxq3q,_D-A.{sw ;g} 1mۛZ#gjSoF?I0{ghwh{OF[?MN;쿟鎟 ]%nj ?Wy_BWcd} {|YUZcݼJ7;wJ]<-Цd,}eWdƌ=ݾ27c7?_NF˖2f#5Ο?OD˜P~9f o)w4l^eIy~e Cl=֛T`7D?h7DAƖ]䇍gCf}aWmVo.#yPc=[yȓ /j88oq};=kDlQΉ둱eftf}nQ0?9Sm P;$kL# _&hRY,|6eq0tTa~8K| 뇥?>qxiC;c!PCЄ1Lmh4ި;=,tXGΪa 'i&,pf#Ce.sEVכirTon֟bOȭZ@o)LJV9^&/Ikk)gX'OƟ6mpƿgHG9Y7+ra|\b~q>9Al~^6l~86Ϳ2~)l%?m}i#ΖPx|-JXxZO&%CIML^F{9H,oc2P/0*c(WE觢>L,;L^G Yrӯ1'?b}|dn^$u+_g7o5`{XOSOɋyE[zayzVnUvOy:r/^>,. F^?S 9YɉMnKfn])̽k̼XWQYWvl+X ܼmZKlgY/K,9ʗ3Jp{6"ɕ (SYܚvyOn[a;7OeY͝#)}1^<{Up򰳣g+Y|f"wxߛg8Lݺ*6=.nPYh=TE>\,'r}`)\\s0Tc}Ų_ycd3j0MiD«E,i@nf u }|^fxx^c3377eV~0z5] }.7AnaoofV/٭(9w,e]ΕYu9I.dEeտ^$'~2ʹ~;v)HfW\qx] ,aZ>ns/ۅl,A`ѯw 0p?w2>w#wZ>͹X}~p)_.V2~oX+G.W}Y{p^:^nqxq^<͸/l&vzS0F7/S`aiʏ%k/.=O^U+CŢ=A#rj#ja?}|싵nwXQuC߂0jdF)a 'a۸: C=қd~Q_a诇1_WJߛr -q9Cx~s_y"5)xs$,z$̫Qз~+>^F^2Pӕ)}ꭁ7{7&2*v3a{3,-^y?F,tپ2YV.g>E:P~Ïb#qx }}j7{^ͳg/ƅ7j?gw397/+Wo&2o{W3ԟ쏬|k|/o[Us㕱K7;u1^%._~ -,_ŁU0_=1>g }?yFyo`c><{η /޾>>56}~fU}/pͷ<{[ӓ=X#a=~_R/6k=5;S?$f'ޤ=PgY3ȃO}RXbvC z5yBXM?v.SvwOiW\zm}e9lͭO?m}P'VlOWڣ_8_(_xGn>l?9W+ρ&j-\l*pUrZ]^f9:g޿/qspїKn?b`a?x\+YYyxx~kq?UXۏoR eRaoK~pp1n|;0]qSu.mD'8O_3 ?oyAOgf{O8/swRIXڻWdiߑe}AXa5FO5$>n.ߩ᚜~3}O0~C|O!>U/Ns"U?ٿQgQ.o9Gd6~c֯B0P2p|o?yhbo=OUM8sV*˜*WxwGU1;q&ԟXL5TZd k}بozn+7ɋagC 1|<԰c|j|hr1d,ߕg|5x.S}r^0?Y/"C?s78?EysG|Qo? 9㼵`XxJ}vds HG8_|U ~ +΋=\.|Ow:g3C=sz/|/jz__ k؊>:΋C[Ϧe2CrMl?m<(v, G=3}7=H?끦 KCSEWE_T]8>iQ0ƿ-pq=pzCzϜ^gMM;YYlO-_[R2z۳>>sa? <=L#p2~п[+8S}hE?3nyg ֿ:A2,gɶ~>wҿr=}-;45y_ Cvyݟg~j738R 6^v3=|q~xca|M XoF[ {c.ù4}|?'r~׮SRKؿϵl?w/0M·|s/83o7yϝ9l~T/pac/p˙S㧼sV?>y_OnyW 'Ɩ>_dŽ͇ۺkKE'|~|oxͽ|ɟg,/3NJp ?LW,?s G@ |_co8E=7#c~101<7#B?=ޜ-?>oX^?KїC< rd9_ʔ/KWE'^|~X8[>U=gVb$ثnا)m>z.̧oF߫h褯N+/YFVqCU_뼹\w?^Tݸ Ս΋{o<׿^+7k/>(p~V9._P__>)=L߿7{ 7Z/yY}aG17|_)7+ Ͱo Ov}#}D:n8ec\?k̟ɿoyxY|ݬ_ԧ-=foT6;[+c- ۄ[O* dcg {"ϯ6nfO1i`?Q~逋یsf:yd7؛zyso}=Y7cEcovnjyY|ϊ}3*ؿ)({sLE_+_=/c>}3'.߯3_g*~|ы!?d/POc|p' /caE/ǢqDKI C8oسZye5Xg/F{ekY7N.<ߌͺqs?/ljHuY 1?F7D_tS#䭿~7y9쿯~^ ?B~Cȯ:xח?8X~Gopqn1lO.V /} ꌟ̟;,GZzl0 C|¹[LO/~oOXY~߲`Oy-?|x7{~4m*?/Sy+ di/XzodߎˏܮS>{swӊ/7>3ܗ} %p"F?O5&ov!zQȲg~Ù^?>켜\]> ,?WHWY˭ў0=C}b5:{8SMdOohOs55RKAl' ]儳=9=:3i>79ݾW[:f_y(OǾ'+}=Ց߇QxgPz`7-.O'ulo./ ,E?6x߼,a׋i(r,O7Gu~BJn-O#c/ѿ:rO|VK'371 \wL7aeCTGo;z3.-!,͹,gu,}HuC8W@ |_'㾮}D}m< <=pG;^^sL/ϯܬ|Ri䗜`(<3_C$7/( ҇.)'qC+V/ ܢߔ B9]OqzdzC>҇ W0^L: D^f gƕe]oo3ϜVrgwtxc7 |Jau o!DŽ}B>ZGW~_n-w|dW:t1O=/]S~|+Swӟ_7> ۋ\\g3{bl?dc^>csK󧎼/pʳ0~/_ut+7;W=?r!,G9ʘ̌3 ~2q-r;f~~ۊ |rȳg27>c ~s͡= />3ǾtN͡|{]?Zb}X~ gp*ӗw8FYlgS-;cK]~}͵{V޶59sY}_QQ̟s<7)sΖcy=5^/apOП?S)ʛmǐax_ex@Q>'~2!zaH*(ֈA"[M#0au 7A2"CF8?:eRG}= .B7B資=<qQb}_/t0XXF}/&P0nyginb<㧼fz3B>lT;{*ޣ 4kl_7=6^o{o/9~,_ʸ2 _Xg}_3=YS.߉9`#Y?^ͩ^Տ\[g'W;ѿpOvNuڣBq.) g|_)/o2g?ۻw+/rUO|i+A9yѧ?kd'ߟ.B}ӕL}ߠ m؈26/1.7E -س |_07EKlt#te:wΧrP>8:c~Ffl,>iFa=_0%q{^){X3jf5׌kmh5*E\kx8c \2;H˷՟G8lﳴ/?Y8qg:Gg8B3>:c`iuGuGxog8 \Q_|[x~0'v{}uZn>{zRMxpb}_ .=ƫޝ'p|g򖟤 Ԍ~ zsYc|:0+g8{޽0߯沣7?WWx73z,z*Z~"K`;??x(Z& 9}xr[~ckcr;w7^uT L$3Ϋ 2JRz[BP u578(9\%&CĄ|XNn} p^v}.qG7aUFVtQE]KQJw8vs0TJ7K'ynV:Y7O@Ů^ rjN#V9X),Jo )LwT+ lBlA WӚbțX &h~\\.eo8PByKCREˇ u?k˱dr![Tp>Xr-4您Aق)4 2-3b\˴4yV4)z[9rp\fq i9naV?UT"lfWF[}E|: :.E,=Tm1'wpΓD CJphaHC'vx*m! w,fD%gPd=VwHQ8Cyצ'VdѶ!OMӆՋNc.'}*5:l5$gXr]XLUy:&gI-6U6Q6_¦*`_do<վyuq׈=ǚߙգMJN%z:Z\aSKM̾dc%] T5 C:sA}M[=iEiuOD|*mPRgkoQRRkoƹ#vDžMM8/<@eTx+{ӈKźy񙕏XC8hpħa,ӈNTC[ĚCTV=Fa ο_~Kz6pY}F,D O#ʪy#bl!*uq O2Yݏ_i᎞Z߶|c`ՂMD||Wא gġ1Buz>'GX5O F0Δ`i$#z ?y 7}X8Ql#fሃZ9$>qn3[),خ(*ދ>:όq\ x"D|<,">cVlo`TkMa wfe'*Ǭ9V}ȅ>rQcE\*,Bv ml45r2c_r%3"Azux>F>n{-4}3&?sayþ. ?A]{c;lODO$\ б_lP꫾'*5:=6'*= nR|'t_ZjOcݴSMU>RU֝ ``&wCnXrH}hZs=/bPYGXvW3$.  MEUoT#Cҁ֝}g~f]CzdpFVGL'ky Da G@lGHM@GJIY ;#vwE*6C ۑe4âpvM8 8#8<~d : ŎuImAZ>إ-:>}8:cdD~/2Y lGJx@oXND^:~CS%ug FmEѶEotEk{xzPrkE-Wcß[3^"5f],{d?zC]abraa]yE( ~6)=o$*g>?#z=m}g~~qɫXrq<b0-??g>`xH,Ga1]Sӱf<Ԁվ1lߘ;|t)˅pDlaolcFq,t٫gmkzhO{q iȩBh;ꨥp\v*( aoA)H==̶8kXSJn|dSm9i,6G5QӁ'vA 1v\->6opd/S_ݖd;UZ+ZWT!&g^>MT_}#36|^ׅv 12@K7T]^PF_m>}:}cڶed>}e|g~ x.U6o :,*Yţ*}`-^v"\wsa6W6x[|3νŷS^z:s{LwAwtR8",;etC7C46]M6ކބf>_9T86bu-+QMsS !ٱƘ? tLWj>zP2kYPXd;6"sX) >yWWB[1Bi!OAMxXYU:ǼfGdУBske5][.Z@Px-q,\A8c c+ztK~Û(oPFV&6pF,MNQ8EᡙzZC2plTʣ<DvrQ YF-tzN)fHF9EP(6*|7j-+Lw)<*5xaVY ^|1zUoזcZS1dM >ܠ3ac8">=փ[jZ-R%_ ]13UAXгdLk*yk,+G]}.&JǥM\Q{Ʋԓ찎谸h,^k,T:4[~&<#>S^.\*{#[u@q>P^PG e _uq V]eTGXG׃zUĬޑEW'[}]{D}^ޞ߭o!QQ8MlQ5dd\%M\d͵xM#ƩVջ<]2JЀgjH#py ?SaMFMs/OG+7ujG"r%⺅n y݄>Jˠ_s#B44!QP)Ʋ@HNO5{b6; ʘpi ֬q̴_8n >Q(ΰu'*gXBhV+˯#.rՠ#7*ɠ'ZvB@93d$bਛ՚o˼Q1p FXP" g:dT<YtcۅboEY ڟhCP]tk(,*Ota*`:ro@/u.L@YMGIffsYV?(jVZqC9pa8 p( Vy?K+țZAIDhm_Cc8;dXm~A\P-vf.E:}fUl0N>ـ}mQ>F7o?UyUo(/:RkN7ᆪI"c N5*Fw:|p@Gr-tb@wu=u~"Tҩo1e\-,KǺbv7@,_4UyZ%A1{#^E~XyTEB6Wl(i-pKx..5e'r,KB *Ĭ{,IWrP=ߜbW˾|9i.t$v2c>7z ;ʓtD1[&DLsĦQy̧p*9$ȡ~3_jJ}7rȾnJ.oE*C #4 SS"ccwӝ !aY}0Ŏ 4bΧ]~&,bVNkLa2 e.dDy Go<$B~_^+Q2PBTHZcWar!J k('.p@yF~~QmfirEP օ{Rl.'m\8R^;}NT@ ~e*CT^ z }_Ž֮QS s?§z} g>EC=zrTฅ9q}(Z^X%=~CB߸ҩE!&L纄?pd| `^XwUYԎ J7vkAgUuPOnmڤ!ۤD k ]RB"=i~&_CVUdŮB[?2ЅeZJw!k4C#C/=༅W,nl&lXVܞKǼW- {i%*Hq4RodOѢkٺa^X%!t _H&\x*8%|!([^X%rs߭6h݄҅ךM.32fmCO^Is&uLR#>4N1'>2Y4iH~u~bU>Ue;buX٬2n2-bAX^Xu7voDš=bAX "]vbuV7>ɦy?pX+<+tE ?DbIJQ뺄s-?17fn§Uȕt!s  zRcQhBTDN5a=È8%tZ/L$-#~j'<57V@b#q!oD{3kZ}Kp~s@.v:>˅= P8;X[&%Dla"iX>?,f9u^}03Q^*g&`7C{zahXP'jC{PJzuR#=E;ͦ*/IYG)m !k0 ۱lԂ# 8o`~DZuX~( }|!m[s٬!lJc-`Mt>:JffaHkԑZҼ#]4\FjhJ>l| 6h4` ,qdSV1GolCeSqbʱ@R|WmD[KZD[cͪLǫ XKQw!>]Gаc؅H#~` ,.>4u s,暮P`OWqqy.? Ǫ1ǂZ^F}! Z ضB^ʶWlAXW _9omqF!/}fd v//C. 'ÖBhf[ 47VY#-E,\:a5pXLw(g8׏eG,ztN}C7ل/3\cp;;J~BĶ@  V0s|6CFB\8/S<H B±BTfA4C~7V%LILm SA]ia]uIqF;5~㴵sY[]wG=j ]Gױ=*i}y=vApPJu`{#*ٞ ,C/ߗ1M .Me"~ˌvጻ-8$pt㟞Wf ~6_A~za^>#_8 k2A/7~{wo~{ݛ~F7߽ ~7߽ kb\;7#[vym(? )įp=Z>=gߣ+-=fo;z3c}JbzUB~'/ zsF|W,tyI^@p|wXRrO+`ڳ[{?f>>>-w/ m~g__Yz+{C~ߗzN.hb2)!{y&1^ޘ_|׫~keuh17=y%ly8²W_'v G? tNj|r2,uY6=f*R0yJRarQ74خ@^tLrh)`C0 zZûzq'{K5F?RЂutD86VWt>-pQ^-u4o.Зt@˩^9~@ ҃|U2ub9C>B}^qf~]f/&X~Σsc3!>5z Qc~KW"⫛lxQ;l/WTaקS}^-᧾(l/`>TByc?'|o?6Ⱥ;3? O>8ߏ }~ol;65_i O~MVgC8ǫO ?[^>G{;7>NswkaڋsD^钟:}aO;o}Srg>ɔWǸǸ{sU_T4b~l}s!tpI`a}hA +\_['nU ?<=mC~C[ׇ}|H-cBy3?Ko`- Op-^>OoRg :<:֣^jle&tgߓ=~ʳ=1ӣ~S|_ml?m4_^^}VcqU~L_G8;؏5~,e {goY}tPȳgs1o폍jkV_y{nyy:cmz˓Y.>lI='e!`S YIS)s 6YG{^/v#.(/^}@v8ͲRh)eyg}NbE_,aʹ]Qnhΰ;'y,QS޿_[L>kil/0/Аy~GiRGdݿ8<-\SY$$~uW_L~m-5t.f+=~={_1.QkO ' 1M_;mra}O&F(Oy;'cO&o鳂П>B»w1{y"Rߚ>xG'Kk!郉5}O֎b&Ydf; +OK8uq} {Ffyy~OAH'+fCfylnƼp1{8"~L۸aτnlNf<,Cc,>*̸\wΧU-/N.\{ %Iόǒ^dF06iu%ez(!" .Levz>‹w'c t3>P`;C~g™za64֥Wf[f` fVFNS(|r /AᏈ>S7IJ6.Ct}gH_w&L|]-=У@/|l  t_HgHAK%#4B';f}2;F'C{~N{nC^a;o wbCSdS j-41Fl3B>m- C&|$>d7`E/|Zp,{#ϊq̬}=VGh:])T@*Cj7U2C:TC/XdSRO *"Cߊzisp1=_8ie^ǦK#$+Ԋ~ŬАdp LJhlu6ɗI؏]v4:bmgIZjΠeL]ZA7,b u39 a{`aWŤYPCzUɂX'.P:D\Mzl휻+E 89b`p囏PkA?j*؂*^3fحKĄa+0DmS. u.rN.#pB_A?a]mE҅ed5覇XQ)o.Pȱ!ZI["iDQVwjL˛X.2) iٔR=Nmw}Hʹ*5ӔkL!p3 il28 iAKw"zBboW]oslgkZn8r◲ado'ªt]  +'kBbb# mڇV}ń7pBV޷mUmw^Mi--?u%(ߪ>s ,cr$]Λ#b]ՃCH~=k 񩃓}iGk/U4.+[8/̃|A}y|EMNzT wf\V}\_yY}E˿YuA}? (= ]^]bR[>ED'\ޗ+7go㟘HW |ң^ev~ؿ0zu ެZvd?•b!XL8"Iɏa],& G^Ņیsf:O'3\By?o8t.ME\3eX^\. ,cuTFr/,&:/N] Z{EM*0W0z W_fO7|Ϙc%3NXg(E\Q\p^8`&1 ?1'_O?W?SQ;EP>ۮ+o<Xde9+[{[z3QfԯZPaC܋ W^p;fVS?֞S^u^^&o%O8,&WG|{[GW!zf/8X~Gh8~g'gyD`G&u lC G}ߣ?D^u+k,c=(sџyƣ]/8~ƣ55^>~[#{.z~ol7 ?l<+8za{'dq~NJ|i}pO|?{և{ufyn|C{xnw#~XGu=foG-ƇWI/:?E˿zO'W^)8Qӧ>}z$p(L>t+GZX7½ܜM՛uTp㡅+0ia?pbz|{xz2c+0w/0+/3ggz=Vw]g ;}p>ȿBPWcpg\G"G/~[NHbϿ#J糯c2ïc~/wo끽/?}zz=/%^O#=Df}>emXփm;/ƌEqZ_,Idh'TV_|Xyhf=dn]YRLV O58#Zm]%$X%hO]7ά/V{"O_5ScR}r s?/:럜|InKV,\(.dKA1D!bz&B1Bb?.'[^!;ߎC\i!lBŐTj xgca}YH9>ڿ!xyQ ɿ"G_,郐O_6쏱ǐ4C4|"W/~_sEN o}kSߎ[_ ylϐ!dx3Cvi!?G,^oXĐ%Ε}+lϫqFH5?hX?F5WtA.6>ӎd%/DIןEXkq& ߟ 7^k?lmO٢<]B2SRNy6;_",|yWٮWB{_ כlܯU'[#c>k1_$er 9_Jۡ-O=8pc]|$vf|϶:_[}g+hOSċ>Ha//h 0/4`8͠N~%w_qHC/9c~n;BZ>ϛLϦ?l/'C}צ=[9^|Byi}[~Γc~r>G?[ԏV r:l9oq]s>-I_A}z'vg>j9~|l?˝[=뷣}~\:yF}qWK|[d?q])o~zwgǴ}{h/p*_DǜOVR_xY?]+%Oq}{_G?lWU rK3WYg~;YyJ. +v$T`GKTʉ;Fy'*Jq|toׇ73^0jqO^F ,thlOę$$ghQY'S M_X$"uǖ8ْ֩bGOVOK}j4b}jd[SRYLB}ܦh3n_d-5Z[6{ȷd%"5xZ>j`Qru>ʹ4soMP;4! ve4z@ljq5(br]^xhXJQ ؾ$ ܐwbB)0QQՉz 5*#gu~V)֡c6l!Nƒn0XiE>#M4fЍ,nK -[DU-_q/'q+ʁ5S0t*3%i+ m籹 ^FkYvvsp=߯m#압tWfr{W<nĞ>^_Qٺ3?Qy}!3Ue'Vj8[DD,c6lU0 j|es&QfS.KCѪ&^wRnNP:Vei[ _P_R춷#7:t:gs9ÛIx^&fYK3 mڄͫGg)d7k}ʮ^ʔY6Yloax [!ۧ4u!A.,v-\v?޻Bpٗp~8iۏ^ S=e?]Z_ X4~#lP{iirkyw` /)~4Z} Ms+ z#X&N~WӉm6Гmtp4ظt1/ߊ5s;ˇwClrof7\U3}oceCUD+*ab !`@S;kIv] @%l"y#V;e󧰣Z|DYBUF' qE56;ZEOBzE,^*vBU QΪI,df/^Ֆ%foao3bXz`6tū!Ra12% ;o]Y!Ef ytb04B0;nq{H1TC yH! -;4XYCSvCoc#f!Qi %jnǏund:BѦjlnޯ6`HOz{o5ߣ|!J8yH%uƖ$FzmH:98DikT<$Wt5"v75in^NjpN] 1kBvBJ~Қ;jr_O!eQNq∘퀳[U qCiFơ o=220ffp=XXL!Ao@/c>́eڜ%ԕ[8ف&|BnOn?YGf_gOdbB&jZx^z=djۓ08kOCC^"3._F6߼-Uy~WI{^iO< )yo:N+~?ɫ)k=;{,F2[#?X#X (3aY;tt#WL]ȃ<t>ZTLgXK>U(͚9m{]*iEW7+r!obffϊqp@mfFG9=gE&҃{~ޞe+FvaHbSuAؒ/abO*9ؼ&AĈ# >xj'C^*2iQl)2¨|ܗ0)g[YQ?\_ Jd^S;;a9"#,X-1mYNJW]aX߸? #؃:&#v;Ud >JDnh.:Ha#" sdT=mb$l4bT,YY2cɄj==Q0l7OOXMSuwCNpO y31?X~t(d`u:nG K7PnX 9~~߫_#0՟a,l|"0C߾^օ7}V003e{_gk! ?\[~cx^{!D߷7D7}<x>{a[bk_0Ae/b}Yh,,fq7~=1^@mlǣ\bc[T8E[Q0/xk5Y^Ǘ ze< 4<掰Y?aN0V_~A7n`<̀՗$7m^o}[%w߫[|`Za6[br{=+l5*/mjkmq^MJHBkXXX0\1Om6ݸ@x:w/tt.aPy9fĹ\ 2184Oz0Ł^gXvyuYfڇa =r䆰L@fALg}c(웬߿FY_2$ypg_nVYKFy|gv6M,RmgX-m[u^_=Ih?YO-L;= lak>W2ԙe.o#l^ure'adu zi W*nxx?~7{g͉0DaN|E7'`~Z{ 1`m5s>'3L3sg} ?닳Oڞޯ^f]'_5Lqa|aeSϟaj c>X6>Ϸ~I-q 8gy~rG^xyH7fh(ZdT,'>G^1,0Vj}Êjċau ӵ  c ;U8(3l뫼m̰h?w@b}ݟs?_?ܿO~6O<8>x>WFnq=߇R}>7>Y= >Ra }SyX@?>8g!ටp3߯"`fqlt}1HΆ0 *XbHg}Ug [3 wg}OG0//-Gǧ)ݼwo ɆՔ|锾3T7o.gz8')& yw[BїCr~Kӱ!rl?r? / 3 pK'u#=5t{ՀEyb(=MyZq=$bϋV09iԿ%qz,x܃O-Ci;ۜmKMEp=k9|,Nb,٨jdF˘/^tYxo'oy+g1Z+LdJ/ #rKatt.sd #LGe O y;O:Kw a"sيurz6.{94?ܜSV?}r=9}a-΋G;\OU sC=qP%fTδ_\޶[Tay*ɰ^ԑsykEP>/WC>>-ƍoz+^Otrj~/y~H*'"1x[ f059'+򶷴!(Wþ!Wb}ъ\D?"܎f_ɲ!Vm[TAC,_vtǰ!ho A`̇m{ǥ9KUywOxQT`5t6`Ep/Ey?7'ϧ'uc]p%_%\SǮW0^)֯x?~9cOgO9ȹs^f=,s`?w{.hc<[z|'q=/ m1z^T'LJ֏~27拗ߑ1?N>sFx2e2~;tsO1 1JeO/!y]Oߪi>Dj={~z~y絨=͐Za<K`wVb7#!gjK'D=Q_ GC}Oa(on~`/^x?טzR{i{s=}:_zb/Ӭד^Ծ"}sTQx?u}jw{U\|Cԓ'8޺wܼJ61ѻ3< f?{I'O_rVy&mw}-G-ENW}Q|i(ּ\X^_WOC䟾(o#Hn_DZ?K~~/kyOݯw"O1俆#?p~mϑ%~Ak7 -&\)dzYOr!R"7>OgZ}15rW{T^7ˇ^Z-?1_4b˕=xCc< c{/Oo㏔|r=-~}( }^1&J $u`Hg]X[77@!(;)[8/r~l 5oIoWDStn5Aw5Z-Vj8NuFMD~$h*~ESEz`p^(`@Zץ5e8BSPHGG(Kp7KZ9 ##96U$BiE+s`8G0Vyt"_ԏ϶|o!uy1mZ<0zS2h[4bnRrG:`K0;u٫f(2̱e{u'WV^=y 7X(9da;!UX*3T^8xߧ D:W/ JVaA0/> ꥪA)jSQ3DJa2_T oh<(h XY*Qku-mTW^r7lj-H\/&ץ'e?A=)u &s7!.U9C)l8X:?&N+Llma?+_8ٍ9- "GVB9hwe:B*)LcCP#~۳ -:wkp~GՁk:y=<= ;w]ܮYlپiDNt#rag:y9S75s>aʍ=9j#"ǰ;_êj?˦7ޤO6Ji[zU] w ;]\YXڣwE6+>[\i]jܐRL[~Ipsm`m2:FDP4<b͒J{y9O t6*i}z;0,<1|'M YRV/2 {޹tl.$zǓ>H+d;m=<~]M]MV>[[MCY57mml֤ z3Omt>|v42nis}Z+O봼줧}YacdαUNS0~hok#8~8ez{h^i{~ߧi}ߧii p[ ip[+ m XKkqZkڣZ&MnkZf9]nkZ润9mnkZ9}nkZ&nkZf^kZ궦NkZ:nkZ&^kZf;nkZnkZ滭kZ& _kZfokZ򶦼-okZ<=okZ&=MokZf]okZ}mokZ}}okZ&~okZf~okZ~okZ澭kZ&OkZfOkZokZ?oo[& no[fno[x-no[8=no[&9Mno[f]no[mno[湽}no[&:no$eF6%/ĴSB,hpkSϿhpPY<#nin6uou{=jsz"Y G5(,!KD_} k(Q/$Fc(E+Eyy7&Z#E9N6V@ s%*RYk%-<3-$[Y, qd!K" '*#[f6AC ~Po2oY Q}32Ѳ-}ߞ¦z>ptOĈX/Je 񺼓H^7I찈3d'7R \v A{NqPFĶHKha+LE1/ Womļ(117̞",. Zz6r-= kiHCJdzHr̩tQ^3AɈCJ5#y|ߜ(3Y!Zfĝu5r3\Ҕ͛a ydCT*ko ܾQO,y[ ;J^ӄ?1*'9Q#}!R&9n(r4O0kICd}$/ju1u~Q+gyEo/`3E,#x!9du3U,GKF9ܾc%k+"h4! %??Ոe,G+<}9!*Hb' k !C=t$C8J6R"bG8u^^NTO,{1}RxD͢ "Gߴ9^'Il%zH^͎5\+$h)^W}+/cFrV#)֟F\-4pg|N/j$eErQ1 Luocrf-aIDXbf\y1NF9'1AXKhJ{}m0MT{.KgvCQ*J2ZEq}o G$y4xݽfm苰532IV:fzv|D, Q`p,?!qpߨn#j.? uL7VqyOLg㬼Ț|Gu=׭9G` ̯-`<//ka~6L_>LU#? 81?#lᘖq3$$/&Ge)/ԦfضߖԬ<`[)d+6M^r@0)vFޔ$;RɕqвX)k:PIkEXQSyloTTg}r"b0t<QcyКj(# uKy^ŕZUYSZZ˯.)!. ?.].{.葙꒷i,j$yxɈyȗyɦȵ{ć|ӏ}⇤~µ8vٙ\kWsyѵ_zvS^ډk?^zm.˧.겚zlzl.K{l. N{l.˶;l.ƻlKk{cI](}U!ߖlߌ= ݋Xpw-={Ҙ~V:(+!U.'ʚ~F:B(-G'Gvޯ}`mwMWQty c>cf9yՕ_L_['#ؔL=kj%ү,@=3qe=1/t=i&?,a \C ( N Ibr#eĭ_P"ifEt' my7 N#d(Tĭ*5 LHS_|()@d`GY|%ޠn"Fc6V{'n[tSiDqWCLpU_Yo)ʎn1bci._JHwkJS]G%T^YgefMf+0ʽ$@I(;z{ʍ)/(CиC'C{7$I"N)$.%Ʉr#qމ8~-i'Ib"T 'd,V5ACU+4'h U,ݨn pOȺ8ne\D E*kc߯ fqj>}J18q++pl3!Mb"bd [v0mgҖ%/;pIHdpFo NM *bg"S7/ ;̈́tiL "b\T!J}jĦadEmYl!iS^-$> Q*]jO7g1|?\ˇODPmP)S hob+|-#cw^vRGo/eo0({YVy:\23:pd /~f oQIc4ŏe-}0rN`G GTS>|Vkf ѫZ>_q) lĚs$mv0@x|,]#CUFi~e. w@HX#5\࠲ 3LɟaGv^*߈[%qYo߁{-,l#/6[?J9o'.M۩Ӆ:_h }/V^n,A΋Ѩ[ɽrk3^trǙ˓]=VYDkdX ~`u%lc'o 8}X푡u8Qٰ ^o;F#+~)-k9.Ɓ#T1\$ YyW G#k0Ճe/lBV*3*Y#)uEݤ <*_b7.ds.B9勋m>|5|NJsV.(uJJ;w蠲WB(.U-/څIbKT'q( @. s?*e Юrr3.dwDXgggac,3TYЃe/X?*t/#MU-u_/E&~4XQ"yՃ;*̉Z9}8Q*9Ճyð3^p!V.ʿׯV.g9ofLi$^jUU s]m|d,7Z˲x7}5ܠ,/V:/ #F E2)rq+vѧW9Ki`8PYt}*P {%ʢ+8uE>+ʮ3}~B~P9?PWf'ܢGbPeSAye`/pV|kS;1PYt6 "b)P0WAWS=r)~GǖKЈ'V@"~[z7bS._%[u?\ؾvݨ1qp\9 68|d),_ _$9=胃Хol@I4E5o;tez,ko'49&QM$yȥ콨^3jkvTWm8 X9k@&8¹ab ŊTC4aCn`kDz#f9:WyC♕0cr+JvBĺw|j0㋋8[{ʈ=3X7 Iy! MC"z݀=Xh/4342N ݅2LA G$ʲ-eKqD;1 |q5Vx7(Fl#6YqpdE.H v!Z"Ezˆ+Vσ"]üI)q(+fmQ"j"^J^QA߮KQs*0"ZLR{.\4ժ{0b@G;Za'n4m?@ endstream endobj 101 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 105 0 obj << /Length 867 /Filter /FlateDecode >> stream xڭUYo@~ϯ*o@ԊV#p<8W$-3;3koDeMޙDWȢSU =\Y:ҬUvO`e EyQ&ZZ:OἬ*f|T14|^XAR5@їiV ~6@ԔG!MYkl a*<3Jʑeް2rv2b9-SK1xzrpfF^'5'b5$Z[q2z^YLYbD*QߦSEy][2Uu0Z #T#V:Hrc{?7& WR] )) \arA {Svl#; 4bs](>py^P8o+|gTգ/`I}/u"!N#خ)9ߏ9)cW<>va; [E~y1 TtaV%;kQVVhA% t` PkhwK+ S'VC뷽ħl-GOU`H~+TWbdݱ& ݄5|+liXr\cm{QirgKnE{ ۔8mB ޥUkshn6] YۂZh< ֘ }hvVv^@+뺲M1)zf(pg@9k,,p^ xס^|Nv{!Z=|N78?ZЗ][= q=^*{#;Fd'ݼkJ]ղtaGP? endstream endobj 87 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-012.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 106 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 107 0 R/F3 108 0 R>> /ExtGState << >>/ColorSpace << /sRGB 109 0 R >>>> /Length 13967 /Filter /FlateDecode >> stream x]K%q.m JXJ! ,Df\]2/C/W,/?\h~_^}gZ?SŚ>[+O翱?~G|OX猯߿qW_}|ζcyY:gͯQ?k<>Gzg xXbεP!b/J so9asaJX;vi?s )9}g? x6fgGya{ <ۆFۋ5Io/>32׷!ٞmBڮ$cۢƿ x6hm~iTe;>' ^Nf>vGOTpeNvO\J)_c~/|%7,f8>x}|syX6וHX.8}뚅ϒ+>cṮ;Pi8G߿fɭ:vc7,׻1cGȟƾw/krYgDC x;4Sk:2ohFֹ8_lܫ`bN;gg ]/q.mC.h_< }).Eu\7pͅzk,{Ydڅ-mo˻[rȖDu./NpA~\ \ Zb3!1Lf襝6/ݵ/l%q/Вr=U/SGR!4muMʆ"eQ,``bec^yVC[1Aha(sH#4!Έi/M2TeB@kߘq*%p +k/K$5QO 7[NJPd*ep!2ݑ+^LDOg[[|[4{C; Ҿ +-Srk{"~)%d )p.kHM} _@:^~vKw:(hU~Ch١pS=3{Y$YȋI mW_&ڠoyl acF|2&_U榙GNj\H|O0DQu)Ċq)^p;cnECN4s̷IIB)kaĞ aa"`*/$Ouk3c%0i7x}2l:D *_a_d9Z5 ~ݗ(Y#⠮ 1-l5 E<@!T3@$+QۘA^mȮjS=!tBȰ{bU0x5D\d"b*epZ/uc3Qd-"_uW32U;Aw?wrnyˉ4bT=NkrF\Ok@YНawu*3;ŽiiIn}痝mƗW4mx(I2Ӱ3恪JILvSFFHRɁE3ceWf=8H褔YAJ] or3Aӓ-^jzuliRˣ .T=1ۙJ.;|HtW~䃑]=&7h&9ieDctz94fˁƀ,R ^|D(kRSSF TldhGuBtC4Dߩ"Oi Dɍ*5#+!M9*|f(PrB$nꫜcj=PcAp3UJ'(uݪB}dz<%3]LC@ZBsQ½3bpKgWi|v]b. fjfRB->!J\(U|o^W"KwʅjîWJs55c#ד y*v9_:P%dT99H hUܩ^e#ԒhLT]Gߙ֭|S=HJO=Ɉ<|r'1w$DFE@fCV\(UY;,rF )lEεV;DT 7>Rs;]JeVZgZY>LlUӈ 0%eLѸwn')zAC"[1t"9Y0BIt?Qe&j? G'ԏUiZ,N2.!3Tޙuȇe=ިJNhеxβ]f2.7Z` %Yƭ@ZU]MqeU?=J5VQ%Ֆ"lh_Wيcbс`;J_2OEd!NԮgrtdzE‰4bkEW5 7Y[&Rr+.!wWոr^CI8)@j){C2h%k&X`ꔍq']̗HCUQQEjm]=8X1N sjY%%nFW "[Y)f닪1fzYL٭Tɥ0qSޘrPKOIQ3:nO#UZMGd9YQlR#ȹj[ 024ē9phUocx 7;tz2Ye6jg7Ʀ%rzp1B9QbxlW9"U*F1"|9C'ƣCG9|H{ 83/|F**1 Su]ųb&[sC0vx2ml@-4V2Qib# }L:go,Zg}gٯGtt~,H n?i<bs.<T$o@L!p1c5d4 x䕭@]4Y|68PnD^Ie/W}F\Oye; /e( [.,l?My{?=GF$} ^~~4tB|_|/37Վ˵$1u> X^}~ 3: lxGʎ'%+]˛%?StͿ)f^#uR uR`}uRV%~}~{oCr >[R~{?Ͻy"u}}5m5ϵG~:bmsL_j-~cbq)/ne}3s뭜$ !=h;_n ϯI!tް@n7˅MRc)k=8]\\j}Òeޚ%'m1uKٵ[#Y2z8߇f6,hidKl\i3R]}f̽fXjs_UZwߺG "fA=.1qi.9H 7V5UeG@2!Z'p6&ȍTgHy(o3{=6|Tj}H<mn30 IA-憚IݻZqZG\HDqc$?p(ea)p*ˀ#"IIMeG/NQOS@K*%3$=X]!yiI)ȌGp㵰 +jp9ZTsd^,·Y4 A _Lif\ܤk"Tz?I|лQqi=::^M#~nsUoUyy)g\:`*2  #3gf!f9nK ơy_WU[mhDsT_( &9+5[S΢UTy)'M6+(M8K$9G<t5\ԃ: DdpME^Mǵ wٓL7RwwdnB rPz9OG>FʈJ"2TF,>. vAPe7?x*Bkh{2RꭲvOP-&C#CJձJƀDY\3osx*9 T R1bׇV}V晚1YME %ɥeS;k@*KNYvBm*22dP#Vxw\,ќU'h)AGV!M:R(4I<﮶vXUr5zCx =cD| pat$ņoTQcv>8W,"UK](:m[xc9{*}pYgu ?)'*CԩLXGCʀ^YXA++czzԽr,'j:e\MTP fڲèZۆ`ge[}'̜Mj?)Hay'nEBӻP+hD_\s0:JoM׊ AVZ0*K$6|Ǭ"hЪ!$Mʗ/]*>SKcW76xlĬ vaל.]6/+UP&j# mOyoN& th[A4ɭ!7G**H3$prw7G^ux@8Tvʫ&'M+D,#e$TF>@-'Y2v zRZk:SE0i:GNVf1{޷H9z}V]J6 LJ7K6Vxf4m a7"P̼m))UFѐt48K6LFdDQiX5onH#]W -I&e%l7ĥuxd/uB zKp%E}dY0,`e! T xT!yxL2ey|Uo+apn=>UFVOn$S䀘Ƴ;ERv[`ށ99("=I Z:6;HeYI\rAs!\!`pAynSԵzuO269__42lKpoUw8(DCY *>A u2\۹a#5okez@ {۞ER&F,D~UnN\_2uFD) Y$26g p܉ ЫALY}Gv&e4\iVw>+^^F} DFi+#v]ˉIx+['sdl4ljU F֒N*&k:5zuNt$.*ȓFtKWe%2P0I7ja,vzFzLDEk.a G *ǶKTՈ^c<#,O{ZmD {*7S+T7M2g?@H,#OV7H/ER1xQaыK>q:gDi)Ӷp8qTFyx:eUlrwR_xȢ%{XVaL}st]H?)L=1+9W9TU|Se:vG'4곘h/h ifHF{."lՃʅiw֚MlSZGEwB& a0jnJg?V,\$]rJb=)y˭DsfMrUDIIԬn'ma9ZzkBy|VKM 1f8NqA(Vlr٩ h4Zvx! ͠Ʌjülg";ز^,l3]ò'.-1ZgA 9 B6~ Vy:p g p\s?WA~T 4M6/r2rcq~m"?dFbA6\FnjS.·ZCY&Q灂uc8 G02Oy@5v%RLVrz|Z'*gǃQ`%TRL)L,~I&P6Q C!)Af"Wi@u~L:RN[B64W8 9x?X AnYPmZg"w@h%AocQk)&u웒A/)r)Ґ^7_swWE#iШ= :HDrJ/ implUyab"aN?G/= ٬I쥌#ɵ\٫²APU3=Vhٻ AT"xK.|VcH]r2K]nU"B#T5bޟY/k@Iu3Yh7O d p[a곔0DJh٨q&gU鑟 7! \II< {YNh8#d0 9ut XU0"K ԧe%ۮ uDvD*>/:T<m1Yn~րH cs<8ajf2]' ifa"g]"]+T E$2J3^!ܨDu%v!0 Fh!٭(+%Y*t̏m9\l/}ϙV;9A!wuiL1uI{0_hߖR#C2 Qt9@o8'I77#dVTL:T@9,&tsprVƇ%zfPʚmD]D]+D;@4N^9\LT"y'Hi13CC9ha t2 ]hp@A`6jKd#;̤YHBqZ%CbL3#GY ]a0U.Vx#̈Pht@c&=wpOf!xi4eA/ /PWGG'> =; l0R[\։QMJ|>(5Q 1 ;ׅ klNjMw Q}0OL04et nj/rb,{ѯp'+=>:<,xc~A6?hk{;X:AfH*$|@i~Zք6umtJ-Mg. *dKhj)T wJ4 r{L)eoU%ܫ0=R[}o -cxPDKMR"&rWaWAzr NE+Fc[8EP 5qiBzsO)mpQrȦ1a^CH'TL3{]Ovhu0h0o <9ʓI6s@AkUY*E_ ahz *:V4k wpz0M"d̞X*wm(e5(烹C^ˑ\fpe9 :?(A ֔JޘXr#.{H'ʮtqRҢ^CDUs.P"ɜ@A}ZP.E2>c+MurMYFx`7GAnjY5蟌t(d·>yPԣe)Dtdp,He|Bd+e)) 2biHqUWXU6-`t{&ꙻl"=z==f:3Q)>'?zqWū,Hj>f=qr;!$)4c2@t'S,ږA֑*څ1PƴEy[l#2 +D?5F 3GD(頃b*OW3Xj~([8nI~a :Z1^AG/ M\^X͝Dtc:cXls#O>TVSjؙL3)Zn(>BebWИ&/yHeMufVhh_*;R&:2tNxN} @{&AhXzkv\)vM>DZ9P%0;t.L lW[w*'EuAXGU4tD' \Q3eo&aG}es䙮c.ډYhْ6ذC$HiRWPÌɳQPQ=XQs0ݷ4rg9ovFxY̠d0ʾ+lG\Y\9X3qX 5^"gx'kN b`lIy&{D!9n5=vyWLCS@)gyc]F<6OzR? -#BFx*]:,jv3W p#ڌܓb|9"3>AǼSB o+3 sO)/N2 `č|=w`֝aG*6LզgbѼEʱZd)8:QSwWC5FM&jy;jw:M0}xOǩ(ZY`'yYԓ:a.k,nA&CMϲrqjXSWvp38A"d|=6 7;M6&eo_ Ģt͛X=#HK#<ഊ? %aۚXW5)lPY'm:X9Ys>Ikz<ueG YLfĈzt\`.J0f9RzNj(! Ťo+1p?eibok 4Ms4fOhy.Mtd|/Ϡz~SڏgX~J>_]!<0+)%o|p^?~G|O?8:>ן1~4ceӪ{<3B@3 `Uq*3b؎9Jk9{^$U%}9X+= 3|u_ΓBϘqO-$!Pv4W6>f̲wBAc[P~U4qzb9yT0=YluSL3=uܯ蓻|My8="=0S]=iUcd|Uyx: N>}t[=CHNXEOC8auH` l[Ҿ?ޒz`pJ|ߒVc`ʣM`~0K[~a65tF!^8SPqoI5g<[̩P?оMtqS{˦ȫ^c(^6  ;Tvs>HTrx/`S5 =pO#&ݨM06T6/]Ӆg\{RN^8f[)1׷&]9A|:6= ܋pk-*JV0kMUV]yeǬg louA{f'g?$3+Ƀ~>go]Q UIOyoDBTq eߞ!coI3k,bnDtˡHoI $;OU췤U8"acyqK:?HهriEyy-)x;o*+F: g{)1w9=iBNz Ea?6ܯxs?ScX-V]=߯1Xi\) (D-[ I­(?0 oGԖ[JLy(A@-?^D\Y y2FZBiŽf3,i2$uMrxF&Pt@ɬkZ4}rr"wr.9s#ڏ\ǹ$ HwrXCѦ  endstream endobj 111 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 102 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-014.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 112 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text /ImageC ] /Font << /F2 113 0 R/F3 114 0 R>> /XObject << /Im0 115 0 R /Im1 116 0 R >>/ExtGState << >>/ColorSpace << /sRGB 117 0 R >>>> /Length 197085 /Filter /FlateDecode >> stream xͮ-=߫8Ci#ETݰn-l]ɵh +dU??_߾ǿOǿO??}ϿTq?Ꟑoq/$b??gu$Z%qiA;???a}S_;y/yͧ/|J<_Z_GGN0/Zo6?{6+?݌hx>k,>JL߫!?Ō߳/_d?= "Ǹ3^kW=Ϣb?z?o>#j?{?}9<9~]w UԂ[T~Ҁ6/x?wgo=*[r@-_Qo{k⶿kT@?ySOfYUn Ȳ亀EoCq]X(13K~}^im="w[eߡXr@<:%WY\1kH,++mZ]v,my'{|K 4oz!=._tMs _CҢ7+mZ][ey7v+|KzQ~/;КBݥFה\ȽRțzEn7rϐ ?dE <@<)ODjDIڒ7s6~h ޖ]}yilt[z"=鷹\"_S2h7vEySoKn5nU7&hEo%g6=>fs~M8{U@]zZ:_v뽴u6Œh^4 Qck4 ;Z9v%zEnwe>F9 @7W#.pWywD[䴇[=M-we+~b})[}CͷJmFkהLܷxUډי nxw~oՁ8.%/z$Q>DZqޟאl]ق3mZ]vK@g$gw=k~_[\Tq+oa*KCd;&  ^óK]KkJY->6-ARpwYwvs\gڟor1~[3кbxk4(wW@kMw[eQq_, %g ] mw>'29 %i9Q2Zqߊ2+mZv,kD]r=7rxQԿP?10iהr{LS6PySoKfYޮͶRxHoOI&꘥Gfz?IA*l CKn%"ϷM:PI14z[5(]ͥEn!ɘiS_vnlޑx6$$4ف=]b;2M-%j.;ʹgsM="n#~C1I}Q̐ީOԀW.{8`Ѹ@r7H%g@?ySO{հslYfC@Ogw7o\kHh\innKEEcseƲoQf\\X%zZ n77bp音D%{>Y2D?$ޖۭxuDE1x=[(;sZ!Α #oaZjGQ;_#A~#z7i0OK xݱT'i yizVTrIޚmPsFӽ-_WqgiOM 7n%, U2o.>ՔFmKb - Ps>S~@O.K=KHJ?bgQuAn.Rɑ7էi*I>PLsB( nh{Ms'J; XӮ6]%&=ϥMDCVI"Հ20`׈K/Qo=aڧvΛzEnsg3z \@JVSGnCKthIGt@Nв󶞖۽c v,$glŶ p10iK:u@jǐ7cOH,ga("*=V%^F*I,۰L7_v뽜oW?dŏ]u>TMϭ9rvڒ5;qs@zצkذ}_z3S\>l}e ٮ9T?h+OVYfLc, %X t_@g֞c9gK4 IXAuCΛz[ nb3:Ϸnh/b6W玍DjkktT$sM="wXW '>ߒ+&6–v ɺx>MGqj!Ab-RY7/15=,AM(Gٛgk)*.77 Gࢫp4wR4nF $\Z# n!wbZeDwsXsq@?y[OKfY.,FFx$^Xb Gߗ&x0J 7Vo臖]~٭`&竟]rgw]$c'[n9B5%#|i/Em=-Pv,\9|K!Й[!QDž!cN\#N-h4iM="w[ez4?ߒc/z&P &ǶFMemw~6qCiВgv]e ',KI(zX,Iq =;mZ]v n^;.JWo_gsĸH_M,> 5ZͿ=v1SBΛznw՗׈~r$h71.׌J"ڳO\kHF 4贇7n}cK~i( ;^DQ;VGMi다ddSډ~hI--w[e9[ ݬ,0} ~ϵS(^~蔛&Oq1xvڧܬ7nElp.Fl3bxaٍH,](_[Er9aډveǸ?|K(w1@%ZrIrŔ s}yn]v,=ձ.crvH[?ЃkUJfNySofYNgٕVؖK'6}Ǧ2mŔܷ=NK_n~18TKp#Ӯ$+s4iUy[VY:V_KedeGx2ӹ[\)M휸7)껔7n=Ϸ@WֱZ~q%y~I\#v[Hs紁~huv]5[I]%="=pX:s+I,.w7t_v{ 7~rD۷ic{6=J5RKQwDu-v*/G$ >p`-x=e~wf`-sqi8vͲt%L;F%bȕB'Y>fY9$O Sn5o%$&Ƚ苻Ib6 CKe}/Y3rϷ䝲́>E^XM᠑GC'Anb ;;}*WySofYϗ x><yo># :՝|R<(Oj6[Y`Ar>>ӷS(_=Nlg׈-9c4M0} vۭ;}-9#| (ve~ ֣k룇S-s活{(M="w;r<( `6I ɣ7 nt;uB%ט+Kqe>vDm>iySoK{Yy&deKpsIz/nz%)mo8om),K&EH]ކ"t_4xJ=Fm]r5j1J s[z[:_vo_JS#m\!=rK7Q5##Ph\#_$5Sqs/ʛzEnwebtIdmzE~!G;f.K2@Ymvnf] ۭ0hMr;bPҮC1M:w=;)I2j7NCK"ҷVn%N|ɓYc;aŪh"(D -qe5%Nμv,g^%K2TWB֨Ŏx(COHL(Oj6[i~FN%80[؆=3ׂLd )K0/ ,3աNQyR+lpI?ߒ>Q-238@ZϘdJi>缩]v,<.-3M;TeKZ~3S;JnI4i۹ySoKV%8\(8qPgs7G\&9fqqiA:oi),KD~˶{$Ag/1s칄_{H\#oHʍ#臖iz/M ` Bڋ<!$Z(."lhEΛz[ nw;pY\.cq![K(ˀhC\&M2<ŴB8om)pȪCG ֤&N*q*ADv<(yR ~h6!o9GD_xy!AS\"Vl]ni{ySoKhf,<̒CH֍OKt,wV܅T鼭ei83$1m8 ;$q5NG֨=aɍ,+D?lˮ~ͲBҽǛ$1>ϟ-/~vpI!7I+7]v9:%Wrgl\n8v".!6I Ɨ:ޖ۝eA WKb-zi,HXP77xo#;oi)z/GZ%!_@Gag}/!F )mZ@WRpw^2~h*%G aFݑ$Crmz\`.#In=&#*ޖͲM82h!&= KtjIxpڧFzZz& ]հZGqTڧEw>~٭> D@l,%Txh>'yJza҇hI;]GsΛzngdMQ m,$,Q{d2q3Үg[Kn'$qt]8sG׆Dȏs\UUْh=?ySoKnòW:^$sf1Q! .實$-{3Uڧ.lsRpwU7[MC#/yXgRF\?xjP.*N*o]n%N*76y׎b@2."`\P䴛Hm="w[eA=fW_;{+Ϣ+{[(mzKn!.Z2&,n.(Z>Pީ][e<%a$G#v)Xȕ1rv+7IL oQz[ n |'s뚌Mc~W O"鱘bQkHp }v]%T[rf hisXBzvO+=E5GZCBqQvʛzEn y pUD?P^qsCi"^?.ALCHbʓZzMyO]XR<+ƍ2;bJiby]<-0Y.=HVրZCMp+C ǩ<ؔ5A5_f\z'2_߶H" 6ޝ'e^!xiiߙx \1]JɛKyR+lӇ+sɳONH0F7 9i2OͰXj\IiV=}8:IuoP>+~ Κ4x_ΛzEn^ŀWћPWgI 7:iO!=z@$hc~;s#dВ>w[\wyj gbC\#η#;臖D.rwUج-A@-v`Hα럻DqpppO㼩;N-m uӴJՇm4/|i{$͗~ [5>d-Y\L!#| K<+U/+Oii^v[0]e-AγbUZKb 2/昪WgjmMv[m~X\[+ gjQb'&bpUcG5l2\imXCn+?:l %x+/8rd O]ڼ͌<NJd5mMOG|6-ѾiDFH'ԢK0yy5)S=|+mbq KpF܊XM$(Ip_PQbzh?Ay$oU[p&,x۳Uǟ!OA~ibD{>yatzO $Х)R]yw^Z/yJ kto&qOk%},IR%<P⼩v,3OWjm( xu e~kݕN\LΛzEnw#=`oɊ(V|Fҳ;W|DuzI(.|lvݠc[e9M_ sp/<V>X&ju[wIZUr!]iyKoK[zXH֭SY\~>Žsڗ<&7* "B[2,7 4:H\Vecn=0uM="w?]JS`xQPeQzD3׈%+kUKvۭj*$ V} bsa(wzKM2gq"촽b켩s[e&ՎYsiBߓώz8[k.j(.Nicy[ߞv{aD9^(i Yq`VhN1~jxqϘ8;Sѡ7#AB~7.d(1,A;si;N~ȏ* .vlM`Wg=sd3J3Qqc [v۟S;J?tm7U_x Ǔ$o繄TprQrQWKƮ=ep,$V6/xΓ}ٵtפh;+_vXy~/y`ZfbHgh/sרA-GLiy[v,ڃyؒ;{? 4eZkG_\FoI7g;+Fơz[ nw9CgQ7 ]G:$}|HrIN2Iұ".:ySOWq>Dc .G=ՁKT.%^Rᮩ˙_ySoKVvkE ES]e p WG~ʻ^Rpwys) SڴWV 0X$0ſ dFҎ{/y `-y B3['2oo[e>|bϺ5W^ΚW3w֫uӯbO\8;]-kYw捭YfMmk=,}$ط|<ӤdDu2JվvʓZׯo[e)b Ҭ3'QW˾Y }X>CT/#{0K^X}YMޙu&S˚'2jyb!"[w>s.N"\#$!Ȋɴt.pw,rDA卪ٺ\֫ Iި*it.rwMzr%Jl2ӯ35؄Ǚ9k[{KҮX[pMnΛz>VYL&<8]$3+nx`';'jk4! t5q7$5iߚ:oav7wG(o_) jM?\#, mNvwμ]v,q_If&Az4mGq\w$n!Jʛz[/k}_-I z潷)ɺ8]!=2k4jpwom+n{^\M="w2l}v`#D"wm3=qZ -N`]̴S[z[ʷXv,dKnր'CedIW[6k4e:sv=OƉniQ!FfZx` MDxLrLu(].-w1q8od\ti}cz;\;rbI;`ڣMj/ ;l垥Dދ%|/7`}={|/ewsm.et?OqXsek%ޖ_#{oIvG.8 'F?\qאܮYM=ϔ\Bl[ G[(D9*֧3wDO6KV|j 5,DS3 ǁ%sq$*.9mxuyK8Kwoyf@݇H5 uH\6kHjVʴt.rwk<ۻU[2m .=!㨕) ȭǀ\mcjivƦ8)?Dt_Bx;qO\#]XҖv"ۮ~voJJ4|8<жva=&5ڞ4$7HW>]ewa*oa(99ci@GK3' k"%Vri;v]79υr\1@`Y"}5w/=|%:j+’wjn3JoK9rm#<Oc9\^M| ml-=/֔Fn}v )|KeRI֣5h̽M)nummv W<={;MCm 7myMDWcɚjnR0om隿VY &9X^/[y`Qyܐ-ng}DyTo.rw/GFX|K[snKs m笠FcwGE}s.rwMy GgwJr>˝W MHZpI\# ʵ rlUm$v]uut 1{لTY%mp_SeHT, }jE_>2ѪSɻҞme57 :]vhsk㔬yÕ!k?GqzἩ]v{Yyc~/3-1хUbkC2M5ΛzEnrg詠Xi@I\q6qqơTcOUs^i y'nh*RW$bP֝ ʼMfq"yޖ* rY%y3M$XBU  HIbv%.ܿÝ74_vH.cp*1:~T. W7ɘťN{xEySoK5Isf} 'qF"F:X& 6]ťN{)v]۱#1rxѕ9r菐=]4v݌Ӟ S_n% *l؍ZX5lkB?"w/}6I _m_MwKК&9>Ʒ齌i{-]gIjn5#ݽ물]+W^yyڑ35dWGqIf+.AtoS_0P_{vἩ]v,36~I; E>/IG0MWrk'-@-@}M="w[e3.ts/IxWK(KOWx-oI_ro|.Jc[znw%w91Ď[ȢnO ^bZ5Rݗ$미Yv}M="w[e9^qrI12tːޕ ;i\ w$==NV.pwR\Vp@liŞ͋c*U^MFoHqǶҞPR[ev>ߒ.gғ7}^$ѱ@IQqcɓ5`2w!pex&c M-w[eY'Y _B@yB\Yu M ]~CʛzEnʒQ݌ gƓcϛ\!(n8PN^Oծ̛4_v,VY("B %;?B\"d$S\]r伩l7n2Xz$(VziHwPаiH;f7JQ.rwytś%g8D`3քԎ͵^\uIQ\q3jM-/^z~$`=HOm#'v,iFd43Ӌ)hIϛ5r $vŢn^Pۮ~]%nIVQmTٕ>55 7([8oiտ0,u$"GH.ҧG+C+tjO|hkJ{sbR>jG>䑾O\[!kr]uR$iiҾޖ/U.6EKrlx՚ʻܥ"T)rF.*.7ư|{b֊t",m|S_SzTLqnϨKr\`wͨw~]s䕡r$+gOzY_[~zZ՗mGi_sS.rw뽜Y,Jrjo䓜Sc˧掼EI6 vv!n;aݪ/6 d W+9O칄dO6q:O +.:ۡ,n֎enX^p d+Z2aV\#Hu.rwk.vg8YH/fjbD6cUܕui̛z[ n%VM/Gתcm13HEIfcN{:v]v C-aB?[~qMP+ 4tsU@{㒏_vW;/>ɱ.Vͬ_"zWq\z?KUTڵS_Ucfng\X[O![+=5,;s}xF]U(I}M-wʢ\#p?{-U dM])ʛz[:_vWkwa bV x]]_%rMk"v M-/${=?_﫸FHWxszr<Q.rw,|V(i,rX&$w/ѱ%#,TVXySOVYϷ;OGz>#ke%8k.:{ʛzEn2gJ󩸪,ۚXͻZd]w(}-XI?溺Үuwm="w7{*@e7WUX'M;lWɭV }}cReʂMZD$1O8m?bQ-ceG<)9썒g6ɼO~?n||w&y8σҳw-=n11hUOI;{ɴ;SySo*Kx87쒉u.}yTJk%:J[;g7Aq Gm53d'}vIzCʱ#/zĮ5h(&飸٪,;ﮕZ/_IV~7V\=}D[H{|>kOy^v%n}cT1Hg :Z;}hCȵ*}O_#r_,w&mfڛ3󶞖/^0~`z=2|Ը!9ǮO\#IF>[rG>w=0oiU6!XI~yrΒKH֍N#J2rMnFSھ y[߳V|d/əO|_Bj7^je^ȸ>J|7OBI=hK+=kd}J#+þ ;_nw[o) a$>fGV..Q%cɴ[}̛z[ʹOٽ}cl*l5ivĤ-WV( Trdډjml9g2%Xͨty30~(b[֊{ebۊ-v]ؕ&Izg^ֱy4t"s͒`= yʴ{]ɼvWݏrVEKl=_)'}]r UTԒV;=N~;ej_5Kp*kq6R5<\#J\I!SzEnw՗x9nyvȫǤk5ҩ I \l"9SzEnE;.ug7!ӧ>>ڄD׾D ;O(w}kJԚ-R]oɕ+ yW#F\eNKKai77r.rw\y{WfZ/͉^D %\|r}:2ޖr=fYz\TJ u1t8yPZsBrTk6gr"xڙ  Ȼ3ۍ!6!oǽoRӃa w1;7$#}b\*hiCzzx/7Q_SS r0QN̻t_v׫PK W|v n]6d"hS"wf=%e%aLi7o)oiiVY.l?_X|KPuƆ#V2? XJanL'kr;(yKvۭU]I374goeo"ȕәNzż]v,~ȗD53ܸ=WVZ`)ʟŔsH%Gs"InXn'`F8,)E#.7D $F\L[dpډT"~]ex,YeֳdwZmrǓ8)Q+'|Vi'RڽYO[e>G%ɫ7| Dp^\ӎa%pRڧÔt23HQ;ǩ&yw.:@\!wڳFg;k+5:q:|и$X6hx!x_X*L`GuqۚFrYdhʛzEnwa })%(ھK+E]nOg&$qPL\O;+om)*Bň.*31/W.S}rtDA $i>]vo}en~G)((y\-"T,Q\#ҥi'{]vWrPq̶hXḿ*~-tT+ Iwoj>iطq iVݿ||WSGx 4^Y[yXqmhSv\IV c}yLGew/\RUa<՟3/H=F#sz_zn\Hi]*oiUq`waO ;V=yAAbrtI(C^vS5~]e[Bɓ-WW͛H2Yz 5Ē6zeeMjݵ[fO%hyȍw[s!Ѩfrd76R͗`(ˮ~{D-D{/} ccj%9\Rʛz[z~?pI=/-8_z l(P4sZdrui;*omlo p|K\Ϻs+q;6L.XOn!smH7Nvew]|zImS 9dsYI+T!uK2s;b)DJݥewaz }j @cV1.f~f-Z2+oi]cOsԑmё'ái*Oyu DJ2gq i_P9]eKoYcpMzez\~!G\Q-SU|\[`̑0zqʍ$).w}쫜țz[ ny{[B3w]SCm͵iPYܞ_$^Rީ/Ke\}\G@3k/#&ϾBɼ}QN;6ޖUn1}&Y{ѻ-!%3+A1qOH}׆]vW}yi}J2vcBUzԛKtTo nr3>g9/{w~vʩǾFv Hs0Ӟwf.rwk2^g4װO\^,.Q) w]ZBk{EK{{e^R\t%W񭼒{hK> q,Iowz6}?Ͳ4NoXʮ/xW/-` hㅂˉ4S=̓ڴV|OAFo+x~#1y )߂xa䥣-S-|I2}\ƄdOjەOkQ]'DA*L#'i y2?^3m4t8l[>fl].&/jmA0ڼj<ؗ4x j=т7IF+En sn!Ip2̛;WJ~Ժ8jl.QnRI⸬-v+UM-wjWw>'\YFx!ysfDžAZ #..uھTy[juyC;FszԚmh%QX'ƜM-]*˙- J= hSDÞXD7h5ݣgE=Ui)Um۴, b 8j\"7}^&$.QsI(n[)RRSe6:qY;qKeqt~q$r[3JҊku4E6uHUoμ]vCjk"3Ѹ,{*JEt\k:ae^ܕ}Ӯ|Ruv,Ϸ:[LqpD{z\[HSkIyUiXM="w[˒HrcUx0aG[ÞG).V$LB\\Ozʛz[ nwɸ <]rk#(f!wqjU$l{^ ծJ{9Xޖ(69mѾ$hVqi%!³k(}^+.Q&d>=5YjWe ,3}%O.FH} iY~Oz>Ҟ^WRpw kiYIU\tNLy[OZK`w%9NARtmzr3h;U܊].=j1ySOu:+I^r }CHs]^NIҋJvw7T+Vݟym|KGRVǃk$`JG .|O~H=+.|>wrqY%w.]zd;ɺvu5ՎQޜɍ硴Sz/ki:Ӌkym;>x^cv5Cρhb0%7>+ S_v]yUJ^?j-9A'n!I{a'cڭјV\v >ߒ 0߇עO![+}H^\d]vsߥ]Kݫǝy^GJI)Xu m'=Mi{u %G37*Dz[z_vW|w͑uv;Й&.8MB+K8BKrJ^WF<%]SvtN)qF}IiDueTI38ݝ+/>ߒ=ƕ>ܝ9MǞy偸Fm]3-&]vo}e>V+["bP}QgGHQs>& Ӟ^S.rwK<9vZ¯i;v]F.i_3\ E^\#M%Cb+S|M="wjK 0;]fC,!xAC#GEڃEyR֐ZÖ*V Vmw'=x 6JVoJuiJyR+lwKF } NJy1g3i-jaKwʓZfs})y"h@mE6 X1̓sRu(Io>O h'Iogr|6uq˓cnT- v{wi]-Hz,K7eާіZ_kiiNI!aoTRpwUqk}Kd@5nKyԿ9Ln!;Y\5;]vۭh`? ˒-Wyfx<'_B*$턴BO/!mp=wAiJfĆ?eny {2=OGwkF-|uKR^ob)|rkLld p~gL;"\W0a==+uW7#O+isZj06Gv"4VdռSSy#k(;¦;MY]f`^Qmkp-soCZA$c)lc؎6IJ{1m;w.N}cXb07oH#kEM):/~rźi7޼?ȹ4K^;X!Pc?ㇰrnÁQeRun[ςYOib_8#㲇B]7[7DׯIs3%ȯxӧBpe1o_SӖOVِv30y[GߊB}\+^$]..ËeQQ-*-[v"^|/{y??^{ٟe?|/{ّb՜U #m&޴XK} M F<^Ja/`?,qܴU'4zPP+榤v\6RYhV(8y糜gwk\8@P#@HriQa)9%O]{i7^JDlʿ[0sx6.B\"<~ԒX,%ϯl٢:uQEFGzDڦűR(4-¶X]Cv"Y_ggyA 7ɕXKrJlpݴ7yZŬyF>[Il-6c-\#SSfbgٗ+un^eK篾tޞ09 y(]ttҜra+V,L{;0g{ SKtO$JG(iǛ֒tۉ׆en{e̜QǏƺce_J_WJނ=oqe7GsjY qЧg:}GSaS ]q^ Qwݴ7!eҼFjoY?sߞXK3_ߔ,,nQVy˲ݼړ*&5`ݼG+H%|H3?#v=uN^޼Z[yǯ' ?eELceO-Ua;^pXñ#!ػ$]ʹ+\XK=G,]⺋$=KM;y{l4^^&ZjqُwU7E\lpix__lZ b>p; \/6pݴ7\#Q5Xi`e֪$L{ +i/Mk-a2uÞL[;%.nc0BwoÇU$=l=VUP|0b_o yA^e]NaM$eN5XKɉ?.$.I\7f:ޟg9k6ʋp,Wc)P3ZbX;{+L[3k|9;nDn(]/k|b'e14$o3Nꦝ"@w>K<]f"l;ЌD T3AjgvDe編m=7|ߏ;ֱuL@{NľJ_њ[ckv3eiɸw>9O~ $1;QVғ+7kjK /^^nʹ?s?qZJ@YՎ֎3948c,ME$@[m;w|fwSU,}OIg`'lRc s:Reaݶix#=S"feᢄ[4+-fRSl.dݼ{{:pNqe$L12ҵmM3IU\ӷnʹ?wHp<5z15yK;kZ]UF;TvU(릝'6TwӺ޼s|cgy:5D8aIjyXKWTS{&nbQMv"Xu@n/|-CR;8REXK[SKb٭)IK+i7/[ n)+S qEXg"O'瀃P҅.lƕXԒhu UK9c>8XqbO8靵"0tͲNZE/pW_|q,lЮHy&:pb*u8օu*6~d`xƤ,8"i)Y#)pEEd,%8u 6]\񌈆֣ΧDhGN6pSI+wqMoj*G rXGF|(~L1q|s<pfO:l^3> *" (+v!E~Y8K +ND\U I⪷?Ʒ8z84NK ^֙Ȳp(/ (:g qW}\Y^#fNKG:~fdML>}pm{"Љ8,f?$'g zI֐1@ZzдvmꏢUM=R"fp965 TDwDQ32;c#1'C8Yvnɋ؛wvP<]{(jEM~7)Czo{)(6Z ;VfXvsTݴWSg,' h9b퉞^>'6Yl,RJ\jM NL9K޹/rb@o\fgyqj2$ϗgy‡XJwء@Q^pݴi/xg7ۭ05 9VpY |/uZ!Qebݴ7 |ɚHs&k' tF&|:}iljIc)9ӥaH褲3L{DkaAW' ʎĊɾ(h,kya eVQ d:]z(ɫ5FHⲙ6i&3XJ&6rUL{αdU]#w]1Q$c-Oľ\h'.jv"طYB,+N|A|o=K8Z#5c%WMe sݴi`o^"8>Nzi",-KJ[M{,2H-kʓ؅e;ɫݼwa&c0ԜWk"b-Pӵ8l?.i'/boޟٿ֑sizX<iZ[SǪXJ55UWUkƺfd_``멏${ߝXJ=g<Ԛ#n9aݴix|pv&v#gAtlnF.FbVsJqWoŏD4 G:e?XXJ9@R3FbxvEMw>K$f>I1OIZc?O RVb Ѩi[xL\= W`^$-I?{8JjPӞV=K]YXwճi{5g ^H /U\>]su$#&fe#i7Ӻ7~-7ً$3f#FnwQSFbQ,{un^es8%ϪWY1i$imZ*:4ܲ ɲnڻNw.wlOG2+K+ft-Eúmv7I'yOke4ފҋ7^Spc-fcLe/[U؛w>)ۥԼ1N<{E_py$yZiJƻ3r#ˮT7Ulk黐ADO㨒.c5R.R3VbPPݴXxTf`YXL-`Kdo%֒}<9E>R%[Oɫk1K龎)A^tdZKXK5WnA9߳nɋ؛w.u;TLXF3>qiĵFprn}*KVi+1b\s Vɗ\P30\O [=gRXK: ! 65]Me/Pݶ'7S69K$$ IכXA+S0jzIlդ"j F}-%KܐVkٸ_7l";)\DWb;e3a{^޼?~4\vXhHP..m_.ZRRkjJ5v^eCᶛWxg;c8%5~:0{k-yO))3+<%]+QvSu.^~xg7N q߭yzzs$oR!!⪶@<~iz3\4QXK)C6Sszua3 FunyZI~i'5sw4M?;5 XKGPCGtRˉźi'/boQ^Swk"mɑNóda #իzmY^8]_`lm'S;׸ &kF8Π[C:~ U>v]++=:ݽQݶ~xtrCMGzZy$v1_SSeS!Yj{2\ȤA21= ,W61Vf ޖؓi/x zlYTw(imށ3ԖX\UvlU7f>0yrny46"OCWI+NXJyCjHa(TL9%0.M0.UښiyG|ENW]zeپun;\|3YύxdGj1a-wH$igd}JUN^[S%ۓ9:i#`d-Ц#IED/ 샀d@ݼ{ֳĶ9JԜsG_KR_3mqb-iCgp;M;y{>yHhp*%Zrϖ=UtYk}Y7ɴ?xRyB͋o8dΑ]n׸JXK)) eCҳN^;Xm,4o}xfF\Jj5}=F7c)6wjFO e6궝LG;T>eͮ5h܏]XkZƳpSyYZΘAĩy1=44ˎa-)85%Ã\e RdݴWy%"W~Hs9qR~R3:u 6]\ID8HWlܕ<&ȍ'k 'Aw.\l !*q}a~8g론 [qV׸W67I 5;oo.ʞTʛ;>e7pқk-KMo.U*^>8ita@BA?NTځc J" Q`C5;`o涿(ӯ;u pI.KEA/eZqOy#뿏!_g~3r@hI %nIȪX REs5C{qߛ͌JAw/p`I*.ᜓoeFO: ǎ*#2UXKJ&c{D 궝޼;>` ׈_2 +'؈GC2RKY6 _*;sn47o=KưKD\j<"#ّc e?j4Iqk*%i7޼w9|MxnJ97\PLIozZOipqeoOU7E[#0.g8n.)"9(㔑=RkeYpOXv,eźm^޼;"L @9։(|Џ/܆d7 w+kIi 56*]7E[_,Ĩ{bŴzpAB}YlJcҜƠCҜ==w .zip \CVbڣKiXjbq_ʞ~m;On=,y#ZsĒHgc^%LTN5$v i7Qe1P1uk!|uI^)#c-i$5ː = ƺe7Rq?fS3vpݞ>~¡ .7vrKof!㞝.ʎ3/ҋwISPؔtS4-¶plv[KXxYm${.{;C<' o1M;y{ιep4q3-[i=g$ 4gVpbjΓ ,\un&o>KBFsZ++ζf _QY!D]-n%5\IN38B\e7KNk:i.DU_Ξdʼnq#Q,rĔ>6NB@ qqTGNY'`CUoM&-.߆)be +D d7+N&ѥ,5OY'.9g^81#lF+'` kYl L\TuzwsUALfq9:烌dJ hMIPۧوC6)X5HLQ3"}YpDE Ujql!⚍7 1%|g1#bepmdAZ++"Km/Y'kc \PhKW3e|RXC~_Y'뗫~w[ll$oq&tgNQYTp4A9C}Y'`C5}POvC8z,aԜ  ᆧ/ސzXK:$;1dӇU7U9V7iP1l;扵PpiT KFછv"板ˉ03,L"´"Yw=NkojfR=r]vE;s椊iH-"H?F"IywzXKZI#I5>q]떝y?J.48ʘ#MCy.PTRʴMi+Leg&Mr6fzj۴Eʫ?[dvX"duv"c[bjN-Oy=IzAZΞH=MT<ŪBeWon gނ<\ZSOXJ+%~(ʨv3NVđbQT8 (E9oI3(,95u[_jlH^𮴛i`oޟT<^KM ZPSXH(ZQEӍI+5JעJd:F y4;csnHcJr+i3sb;FeO/U7f؛ey3 һYN~ V3'v;l1֘jf}$c^0NIm2agì5' ^g Y^Og;$M#t-C=${ɴ?hXZgi46?%Eڧ;`lq%g젰F\aVٹFVݴ7ϷZf=)doqM{ [eA4Cz Tݶaʲ}' :B;NdG$Pg#XK R'v7βjm{)y9|ďf?U%>>#SZ`#e/Pݶ)ɛR#DsoqһUHQWp1Y#XO8 rSpO$`嬓V!Ͻqlq$Wiq${4.qctW4Q~-A\WVhAyRe^.zԹ'VQjG8PP(.ET,xrE qXjV檷 "&7MpۂWxCIP'Z8+u*6:ϊxᱧ}5v!=E=$h+x}ĝ[Bֲl-Vw)p O}<\ K+k_L:i~^(vDaacv e}q!T)'kpOT. ⚍{mnq~Sq^o<Wޚk 'AT 70q1T欓V!ivM+Vq_vM}[pup ,qMI+wqͶ a+˴Xo\λZ5N  G>2,xf^.I85uźrYe9ͨ8qR=V!KN%wYnh7 [騅AVf\aA:mѾ\'tCV [cjkaw㉓b=Qҫ#嚓zwwkpiibߴ^֗Wa{Gϊ:%Jm:m:\EJg*z5N hu~6{b"J+Yd<\~iP`D}>G ӯI뻍0r8=,5-NZŦ/l3mM}APwY#pY0~ӳMP)eI+wqͷbUT`qqPk;OXF/9BH<^aEE):|CUjrʌQ {[YZ\vke`r&E!;K9eC^_z1ݾ+{E!~s\ik IW 'a~R]*V!*<4& N 9!JִG =L-\%IeGݴi`oSlć(34q`Z&~HR}װKiy*,:L{;A<118ҙ3Ԉޝ-5Һ45'vAe/O,T7f:޹U/kYxf$<=-kIQib؅ѝeY7E;gfm-7Mv%?Yoމod3uN^޼w;ep<%~mxwH2moJQ%)Jt?YD2Raip1p^]|ּBK'uRKS3ZbqiKU7f:א択O@pZ׊/./l{K_ij׫܏i'/bogٯuk,_1%3pLIxmY'RMOrh'l\vqmM;y{kuqiʛX*t$!鴿Ob)*5gKeTvuPMo=6)y5S3ulad'وS3Kbm,{8L9/M9?v(QVd,?M<+ٷ7OM %nʹ?)N̈́C?]YǯQAv֒Fribވ}H*9ꦝyǗҖ3Ə1=ȎCXJwohm;wɌwF 7>OSƛxt-UJL.8!ꦝy`,Pb\x^b&+Ibi'/bo|FQ~DՈGJF /o'ku 'AaITDl"GDÆS"v ;C/+u!8}hqnIۇV 5?8M(]g0 tXa{ƊJ\lD?.ہUwq'lзD_8 bfnŅ ,$0ZqWol >>[<qǧufi.t *T'`CUcMmGx#z hFN$AKLjJ6I+wq*T1hlܔ/yvĥpCǰE UnHl+ #IwMp 'A*p`84a] V!3H+ =^8p?=pC"jC KHI+wq}J\9 `JiLIj琁jFXK6KS^,Ά01M;y5䝃Myւ (q!/- bW[sB.p{6[E/לAKG)N7b-§wU7U޹'vgٙ=^uN^~xxߥ8H5 ϢX|z{~aQ,ԔX 붝;97S҉őqmִhZ9.{8nKun^nfF00 w6zFKvSJJy05&ceA+q3lcqfi4;zF:0" /a !=@DhJ,RLaOu{+U}5QB,,fJ׸o{Zn`_etr7ybW;{y_1 -fOq;fXK W2MϊIr:M)ƚ│ͬLS 6lJNA A|_E)(԰:N~z|5gL;vMif5$v"ʂeOGanؓW-xGri+8;ګR^.I+wq͎s<bƞw5Ep})-R:i1\yb`=σ?,sJC1oLY0=Cc.Wüh^|/b:zX?O{GfBԔX(FMy鎳^ߢHQD?$E}{ED^b-q}wi{6lg]uݶW`oٯiM*4G iIkZN-9U#a\dzzĻWs6W7ք+#H/!ڎէ4&G?Bm;y%~鬉PkzH]ѹ_s=f&:b㲋"\7f%yY<$.xP#qHBS{iIp Sq .nTS+FI*J-TGIdmȘȄUyc'DL%#%VuҪ$2> o㿏iu呂(NB &q=|,2Nrs*OxcD x (a{MD1:e]\)[$fΊW4l _یT'`CUclMLEŢ(&7O.kwie ߺJP<_>oQ p7Wяx^.ŋnTR/hy@+L[+Sq3:UwqMrQfl4(ՙSƮp!dT.}:e]\k'Ҷ[wHw\(kgu&>$*+`Cu*z~&})(uOteS/+G_ x pŵ*շNZE/\x$EG#oGPOH뻍вHFz6Pʦ*z7DBTŖYygo-IiiR KX66\vUlLwΞ_/gj>q;$H@ppw'RWI,_4nuN^޼O*fb**.v{ m}+N))UXsV2v<`ݶi`o9Mፚ|8%I#X 16%rtrn58L@4;0I/ҟM.IoQHۿv3;$6҉<ˮv3; Vfc2ShLD$&DKc*\7Eϳ_ͳc)]kڛؔr˻cv2m|xvy8^s+Ox͛B*yW8PCi͸k?S8R@E8g9n_mp|f- S>:m=>7AFATcAGvYc9 yΨpIJel>˫:+N$ŚXc|o!nE`qJT8 ZQM J^ձNZ/o"G p.4 vڊhA_+Be^.'O }»ֽWmߊӆCfY'zтs۷"pTlȺq5bb ܄NZzF" q0qs#;}\1Ѱ2\8黱8/(JA^.I?t4"/z=BA<,(C-)ߨSV)UFcbS|g_ h̴Φ:YЌ tT%N[#;.]囊H۟1M۟ķO+/q.N+vebXjFNZk^w"Dz~sp?9Ok$N6pJ9NX:08ϻw$Z\]!EKׯ5Iӛ N;pOBP'`CUqšbϗx^(z7[g]N|8=&qJ-Xdl_1v&TQ{2.?-fR!岂^[_9e;iyT<8d47oEtI8<+β)uDu*z~fGgO!*4_OZW>4ߧ"?U}i+:ݿ\ 3>k}K焹Q?ٷm}q5aƦk\ǓPo\7Fk[x=@"^Y.ag]ǸrZg q|;м.fha_Cޜ2 IP<#ⷈq_D:e 6]\sR޽\babqV IV-Q*ur..IB>x3.,q a[Ih0BsOR!>Hc qW_8tY(fAJ+غp a"/R!=䤠Y)+„C>DdP|9p9><,b)IP?,̀εPuwq͵.^\V,0{])G_%ȹ xц7^Eo :$:͘k Kb}SCobi+h$ߗq5/ 6rUu4&5Da&2fs]Z+{ѧ_c栈Q+C%G]¨2+:΋cgNKLb+Ez#9!|3Kkd9Y'˗k6_෾/"Ib sV O,uya:i.xph h_9CI)vY+pj2IъqnI~z|vƍReE 76VʣPWSq)ԪpIFE 0Tju0ljk=qQ g}F<NJL4>m<t mZq:|↦"mP1e\FrMԦ4gi.+>"rcΪiV!knq8ɴ0FDVc¼}, ʥ۸HRW~yJ}= 4:O-<ΈtjqF>ek;;I>>URZAu 6]\ퟓEw'U 蕞;h]8 د~nB??6]\skm.ݡa G+2Z*;7Dva%-w;+*{)Lc 1Wm{#K#u~}<%;bm?>Ts` D(.b`v@)=PZ Ē> pܼX\țނ3%k# 8 RJţE|QiW5 R)܎"7ؔ媕@%#I'u@)S+0X80 \DT_G:iڿ\EQC{p1'p x GVYq0*{7u*z~n޾ 4غ?~9 Nq#DZ8 uO_aBXjzS'`C5~ aT`=57JkF밉AZGLD[k?uw"E U>vʗUwqͷ6c'`bW1>KA+ƤL8 b"8bfVo;AEƱ DO[mG;@1“Lh&V!n>3~c{k㙶".ٗz#XcŅ*+lf= :1lGVϢ9'7'bjVp&a +wsa ﲎR1c ]PnU/7 \T}I*quIbǷwQBqc>^QV 5ћ֎#0뷔>p [aAI_1 RkGޘ_I}N ['K?,"<8 [Qq I뺻#Gg[] ,&^.+!3OH4!..*NZE/׌r+~_Š~\xVZ6>pCqlN[K/vpETt36[E7 =88`^=i+mD'&eYZִ+'a!]K㪓V!'RY"n 8;V1pX2-vTe\R}Urͷ_m}(&8{o zh8 %c~W0^ݸ P1m?nO*,U*cPd_VZ>i'fåd^/_IQbŋH*ƺQr>m ֊0+ a(a 5Rpߙ!n>mIA6cEW UY`^\s\b{;RL8S=aȊ7$^iUT4e-ݸk}(k{׋nrv_Ot mP0mk$¶׊߀>vNZE_WۏN?hFaEI@LCK>I+wq}l"F"bO[ N+ZtA>lƈkpfͧY'%A9 .:W)hEr3$hEH,R{.D.ᨺEX6lb=Fn~ du Z^)AcgٓBu 7 _c*NߗiQ:0v+Һ! gAM|@,5=DV Um?R}d5\B}X1qR3u z&>( ZnjNadY*KM+wqUٜG?GP99r#\9(sV,K_448޻ }0ᝢONWx胎gROlŹwU7f:9x鳐cy/%[2?7LejN+X,CYVlӣy Wjʋ,*kc5eG9gG\UvJwW;w&B\s3ι39fʲoiw8acr9nɋ؛Tӽ]mʚdԫy{ߴ[Rfi9]*:9ꦽ ;̮UijxI;3>"ļG*hJ^Y۾Rʹhj0]6$v3 ;1>ؚ>|m$y{$֒`߅ʮ='8%}WI;X^ErW3 }RxĒX\Z3$Ounᝋ 鹼(b"  쭘1twbbRʭԖ 0Rm;w>K;V# =$s#nRupjfK,,:TuۋBm씰OJۨFlim.tiXJgSwb;mv3o/8Y۞S@C#bTȭ{Ct "ѡlJve/cozHjlKnEwW¦' [pe<ƺi'/b?z£:XSCOI.RhjlAD .ºe7^̓ ?[I9Wme)]~RKiz9>=QݴixrS]Lҁ^=$]=bd#5|rbDdٗuyg\% [~㝒oQ1Y3ZUD޵MRsq:m\kܩxbN#v$j̐3}-Ax+blnՀ:i]\st=8&U.z:Xy[I,a<5%`U7f؛w~OIo*pX\o?wF-kBpoYoZ\It.8Eâ'N!*8M~$YqfaRs5:i]\I4VĘܐA$rs:|IxME8<=,5#GX'`CUocۡV=֊|)Yhl&KMO넕l#ca,] d it8㶋ފ3Hp"{PG֦A8 ŊfⰍR7NZZAHcXSIkCNPKTzҚ`#Um1ݻT4|Pg"EN h>A][R֬V UV%:dE E>[ 'zeHZq++~ y'Y&'X'wqU-Q<~~Ԑ'u0m3 @EQLŽ*ql?t2[U wkh2w(+k IhnqqyRӷ:i`jqZ0 x0-.$qp-8Yj(lfJC嶴by"]~ZF&΂\vP"?Wcy})M.m ߿T8u>xRPc1']V"ܹIJTzioGHQ;IIL{$2֒IM.T]un^e%kpޚ#-{KI؏{Qҵ:ze_ Mw.q~OI[tG6)oi{S3jb[3gݴi`oc;St\"Hg$ߧa{ܾd,$&Fz`e(eD-g5}8^Pƴr7\C+.!3V8&(U嚟I>>=EA?{KÉO[vҗ?j >UK3 Qp8"ΘBth$h ay]i+ؔ~c֌[GzwUllPRcPa)u视A5+nIuny~ipXE#=h5"%b,Ԍ؆!e2n͔K䝝re[3hwHIOI{dS5֒3M,,inɋ؛7v~cPGTA'ZuBƦZqKTI* bC.-˃+vE?h")Zg qפ?c{E?V띘R<I"_o+*g5wq83'Vt %Gؓ*˓d8 [qOשR!IG`Pbſv="5 gbHȲ=I*3ef{|?a sH^ ,eݲIPg*9:mŭfσtYW<.!C'[ ߇bVD?_ [%zLUFn,>ZC!Y+fC57\Lw" s,%Һ$k EJ}u*6rUٹ[qJqZ[3o#qDNlu%ْ:p+o 'FdIՑtiL#5<HJ\a8뤵3+j\ErV^y+bCƽhҪq Nq̩1SM,uC:i55qZq:Gtw{Z7fuTDpb=cP qל4ݷV㲳a6 |FI9iLZg 7i+ؔ59tNEM+ckd,ʉ|7+}9DY1RI-4O+~^7U}G1e}q䲢X'`C5)p%6@0KnMSe}"f `Ŭaۀf'>  X6qyPQL9I&..5/=f qל0x־NNLkXcQ砱;ҵz=R'kZKlǡv,nɴ٬NY<MMt5NDtvCG'c-iJ{W Iȩ;U_m,;}86֪׽mIژц4X+^Drt1K؛<\#߷fbYL,zuH{$1Re_hŹd=i'kgyUf6Jm/I^ִȿ'%ͩjXT}ꦝ0ke}k9R#tUS0XKDZT~uN^g93=7AFG4TIbwޥ3K)7R3jb3zCun6v6[Ǘ~/gkvݒ&HϓXKh ly$}/Qˮ䭱2¸>[-YՕ'OU<#.e1W y6S)Ρ[V ԪS;V jOM;1^N V!gܚD_O*§OX8AakN &\*Ԣl~|+N]28Gd]ghBU&TDU"W: ^u zV,4bĞj-6m#8 ^@O,>UzwqMwP 3Cg3G Ӵ5n7Y[ѫpE^wNYEoߟn?]dg9 EM|ApzTq}!<קKU M ҈\xM?/'V/Ї4q>U暿9MJœfp~APwr>%ZONBӣ3.*+|9̆k<'Pn*,L0kϤIp$EIq2 ,zQIi]\E?nrMR`<]T4}^!TFpS1U$FUQҪV Uc"R?]Պ0~IA OssVFC:|Q>_ 5稗e{m'޼Aŵ;Eh"ӑN^s~I{%v]Y{HjzKFŲ}߂L{ֳOE߷&hS x7:=2RSMHra+ڰlHNݲ7lc0uhUϿ0Oj M{1ROv7vBLe]7E; Sƙǿo]˓7\ZP%("-;x {6$֜-kL ÷[5tM[mI βU7E[%r¶ /͋ժ>1Q'mvb-MM-EYvAun^eX}Sj8?'^W~e]Hc-|/ԔXiRyIuN^ N9IߚT#Nb`JO|vXK:!JX.Sy=x{\卿jx ܱ*EwNmjb)mNM_}|"[un}o#BHghZA)#gXRBIMۉnʹ' q^4>1`\G8z/9}\? .kD a(,cUINXMnIԡ))#qZ! AOkwRqvIJuUZ*Z[RqR;?qD&ަ Ngܢ5N 'A/ʊYUbMyWSy*κ>vEL50 '/QTlvRVuҺk}c݊ O$ ya/;OYL qX*\(ڱ:a%n_;}w w)zLI-4=2<Kix15g_vNm'޼,%J[a—&>ɰ_R΢>L4Ah>bstپ(uN^޼Fq,c?7njx$c-ɩaQ3@uN^޼sp*`ytNO Ud9~qчVִ؉voM[D|4/:Cy$i#ɝ)',l.qS@\7؛fpԜg{+vd%¦$gtjNi;T3Zun^yYP53o$?RM r7Ҹ਩-{X7fZs=Z`2٘ {O{42/Qo LGmtq`5Z|zHj}3ŜNfD*a%9w=HsCRT7fz_s:gfEVx1= i:.pveOTݴ'Ӄr+7ԥ4^W;0O\1$POMņ um;Û .^'e˂7iGϢu-ie!$hoE<\Tu 6U+kR*ζHy5- *hmI`5.u!MZ,Iu 6]\ׯqԔÏ8*NuE8 ZR1{':tHPuZqW}qsF+_OS|Uq4Qʄqx[qBG:e 6]\G'~7OY=;=<7'Ak +PA\H1Iؔ5XM)vvw*yYjJEM+Of^\EEVB"GuǦ4%T6"eqXJzj&v#ɲuM歖G*ՍRG@qM$}u֜U'hlHȤ?{V{c9T[3yH45ǵGKbJIYe=c-iCSM=Aݼ؛%:vj{;<|GΚ+BK!]rΦfzQvnnɔS~㺦oDs<U9ԏ^o-8lז؛wN X@jzL-IjM“oMK)|,=kѳ2M;y{V~~jb9ϯqOXs6]GVt}$Ki'/boaI|2i{x$䰤Ks(☃vXL{?Rq1pYVt-AlU/4\y<8T<.{bN-ek6ajNdͧc$/4o\*%֔'粧ߢݼ[nG9\/󍭸K# Ur\#xXKC=+!߄Ja/`x'FaXr,P,%EK)-Qnַ?߫Kl I89\4-v"}gRGaSs66_vARy㐾`Ll0v٢nɋ؛w3_{ MÈG1mPKǡc)URSGbgi7:~xRCjSc#ƥDQ$vM;bITYB4{xr)ɫrH;a^K/ޒ<6״7}K^P6yZ얫k ^MΖg|9~E\8[>9ޗ ,Zj M6b]nɋ؛h]ip`W["sKoJGbCc)ԜXwaq@esMÛ2q[x.Ŏr! P:"r D]Q9 fުTDp3&,u*]UwqXykլEqOV-ruo|q=<8 N}ITp ψuZyl.ٽۈV|QКڦ/jW[ 'AVn\CIؔ5,CɒVOмČ&񚇭M0&)5{,u8u*z#t58B:xKiI !;X(՗NZ;`Ewf>I?W"l 4e} \)Z7bSA^\sT,=OF$ʩ?jOBMRp#k=E{4 z\1~d}Z]IiRqf9O' Zi䗒5 '+{2I+wqկ_x@.+Θ#kថ2B>q}E$ {bGel^,>PuZ"p?o«}(N֊5n`Zu8!p$hAEl\K]rN[0V))5\BMA-bzvˈgY<w9K]NZE/pW՘٘6< e~98n$'FkIki@.,bUv"x{gYtp~j^O8:'$=Y>%֒YSfbۭs3\un^e\Cz69qqCow\i˫N^:Y*9Eunuֳ8,H@ c\]J؟M cXؔf($,{Yaᨓe(]DB#G˘H=8%wC=яKix 5c'6pߢL3ϲw5y+( +AVW 66EAS\ZmM\!K-eNZ&pl<%nz.+BۑS)5&NgPs_9*Jm9Eb5g=/E#g Ag:tvKʼn<-Pp`#5=FxBxGcv.^{O+,(yX7f:o={剱y!C; ]."~$;RBn{iDuӞL},d^9^G;a~愵t{=)CIz/kyYmO͙?)ξ"sc)Oh؅d),{91ꦝyݳ]fs0r\,,%uZ%ƁrT7E;{ކX]o_m|(?Ob)M%4$v`ŲG[X7fYz{)qP^& n`1)r,IWv8׷]B,hSyN;[R9S;(Ȉ`;Zr&&>WOHm{"r\oՅtĩS_C hH ,{\!l,f;.vQnʹz}IDHjb.:ɗ*-I_q7EkI[ib؎i> `ݴ7o=ˌ{Fm=+^ҾqŚYf:ǎ ߚјbx!giozK%%"äޚPݴZ?Z?+Y < tٺIU)?RKM/X& {2凷Qs|^ntR5Lh8dBlJYXUvU7t0lČ\pj&&DsJ +֒NSk -aِ4h/aoUi!,zVH/gЅL;'sDc+Hv"杋ͫ_jx%I]#kE;璤^ִ7GfȪ+/D;8Z"GwKD7bSJkaFٹTݴWZ$y_.!d 5׿Q5Hj5g${ dz6܃ RW1ֽƂ7[w/k=@3$֒irEͲM;y{>t*ؚHiJʼnoFGRrKs:[a#v`MZWK<ٚ5Π$Ş/DrK&g;TvPݴ7_SUpkJ؊OXp)krFJ՞؂U/.K`ݴi?,-'Gx#gטne=YBߊHrU>lOt&b 'p2Bր8 hVD ۆRNZEUwTtFԊXv(֓h8VǸyR7Y'kZ{+&Ob}$0Xs D8v(5NZ_I;ckfR(mq 5b`Ch  jkO7²vw0َgE|dRuFd toXQ_ZY I_?N~tߗb`'&;EY#4U8 :CEn8Ĥ%l>*͉/FE%YǦ NoN.> =cQ'`CU9l]>ipc!mDLk!^H#jBjfKlEq]SPUtzE5$sҀ~#19OmR3!Krѻn͔דeګe`"aܑ"m]e-bmp2MjFI,~U𧤺m'Q~xkZj:v]{^Ħ(iFZ.{l mj4a[eܵeݲ?XJ<5r0LIn5F G\afÁتv"e2l{Auv&'asF@.fscM;yu^aNxyEGHI]ѧK)}pXTvT7f؛w v1/Mm7UaH' ;R\cXAِ<}o;k|9Kz|9R/EvJ_" %_(]f;bj'yűVFR~Ʀ"5 b1W夺m//ľcqp:;ȏG\]=VZ9b~vǖʆcveNdт8z11 e {ݯVcHR٧nړi_?^ RӐv}#\ y #j.ob+},暐uN5[oo/=fJ׸oYb!k?鱗!]fۡw|{1jf{)I#[nXjJlGbmLun}yrO_$, ¾H!loK)`Ea?sHuN[kv\б WDߒ.ߕ6+[anbͱv%DDo8\G JzߝXK"5M,"Tv3Myw>˙Gڪxxbljs3#ǧ Hbwv~^J ﵛ#"3Ψ47k&sM͆[e檊3qjXK={h$:5U|Q$xmKV8\7 <;. oXK-G H?{M;y{9LþN&;8cI2zϾt\""IeOWݴ7|~>\ra-Y}?K,s?l$onÿols<}ߒXK广gD=gݴ7|ݚ/ z +qb)mGfnmE;݇v3w@_s+ rږ!;n1$%yӤA5aMSݶ{z3 -v3c{gi1iiTsİfV~Kաi71xNnfKu"1ҭʤ[7s5%#U^Qnʹ94(؆.)ci265 z ]r6Mi{)xclCnfݲ7+'\}zfG yxe_XK^POVTȲkvX7E;9܇+{&Ϧ~W[#D3^&q\ƣk:m]\gTBNCRGoH OHI>n4sޙ؉neOwv3o=KYN2 )T\BbClrR!7Sv2o=Ksd NSmdd!c& %%Y]NI$=x{.Rߦa[Ⱦ!׽0a`<Z&iGlA&.Qݴ7o=˃}+5Degkct.BvP oH([M . ,un;nd!ebitLApVG6c)]6kfIlL\5acݴ,?^ف;nZ )9} &9nkf;CLXKR1,Yv^窺i'/bozc9͗S8 )i~1=N 8ͧtM-ƫnɴjcq( .}_l5RD^bڨ3Qunߛ{r5=Wr%$gq#f6 lYvRݴm=Msx |.;BbRwbqU|1v3w鱒ppLeKWxeW\XKФ& *{&릝y MvP 4&J ;_" 2 ,u*;nɋ؛>gi70͵AZ+*;onJ;]{jt D{Jr;xӎ{Zee/^e bݴWi?󽴥߭ ^"f.X>z۟'ә\i KU>y(Lg95넾M4f%SGf RΪ "6DۍĺizxYƧ}z7r]xun^yYG=z\h8H|" !בih,$3 KU6drL{ֳ Zcj&sლ޳=BT^uh"8[ⲻ>AM;y{ֳ *;ŚNqiGg!NZki.Wnۃ7o"ġK%RЍcR^̚dAȅ,5WeVѫO^\,It5{{Q@E;')VosծIq \E?+;T9J;L@NZKphy7PYjw: 6N/x>8p3zgRk|tƎpR8c(VЛ+Gw+4Ӂ͐JBeᶴ=}+ e51v@eCG&nh.S,?My&QqGSñ$OMirԌX&`y.%@yW QYS󢱟ЫJR}%OkԜ媰/$}JQW-?, rn V)w=4$}AmBb%u7LMm=v3 {a~˿[SJuRQt}/#I2vjj7#,β;g|Y˛Mz> gQݲ)ywt> ]>f-IQxp?r(rY8 <&.^JNUlwqM8$xc#NAQZ# pq5 Ԫ֦:i.)INSqgYGFӆuӆT,)H*qPNZ&pW_D4DoE"#ťN?xXJNEriH,l"q0GyY^S="kUl q:#%E)3^- )fپu.^E $/MwVY[_\&qk""RԴXdSU7f؛4H@a VLiyE; kitĖ&v v r޼,[4Ç6e sz! Jڱ*,%.Mdq#ytpm{yx2j N{CM{OXK=hح=%xm}/;KGhB͋6uJ/mWb-|/ԔXfl_i7xY9]2s#rN lJu;Yvx릝3ȗK%k,\JyEtTZ wb'rSlлnkj ,9S׭vd\{v\qŧشp7JvV2*q[B_'"hA') 8p)K :iOB?3AxƐ ԳT)c*uU**$RĉX# |>\(To 4짢N*MԪM,i+~ǿv88մM8[gLRy8vRNZEA暿&)Cw\CgS#]'?1 OdXwyeݨ/?x[!ѵ,4<m]MU𡽞40J>h:<⭡Ey(,& ds9Ξ'.0scXKyK`+lHԝK؛w(qꖽ)K~~x'tf{0!G];kIh ԝXFu-ڞzi?pZK p?q>fl58"%-[.ΦvNnM;y{g~jλvpİ %]ӎzDc3|`neWŹn+7ЙcJW8H}+Ii .a)Y#W%]t;Gמ#5/Oc:<[*N>M8 [RѫqqF.EרNXMoj-ny"W(g#3Cv+ZvSݶWi?,9VHSu3!^mEH%DRWuc~U%.?29uL[q5Vfɡȱ#}y+Vn=kIc4XsPݴ7o=K{)+?Io#%'P E8Ųgv Ufɋ؛!m'R~xu]}vλ4OSGrnJWuόؔ{mWHd/`xk>s{lijn܇(H8OqiJb(y|nuֳWk?WX^KA[d~@zM;X\lOy$՜=7Mtfa. wlym^S%o>ˌdgn̊=ma [w5NbEM\*u)5!*qfćYp?<eG΋?s|u3E…RP*܈c u*z&:~fP:ɜ:ssAؓN6F%qd:m=l !N9"q \a!*5i`$0$Y \b܊j  |l/q"Ê? G8OۋsSck; 'AI*hp`sII+wqy1TLwo~q~=PQ\m.k$QNT` B\TT qWOõDf \M3|i=.A&+6J,5X'k6ϟ! / )rtIoϴǥQVRv! fŧ޴c߄ [QZ~@*3Bۖ5r\ 8NJ)܃A AS7Wu?ZkB8 pgΜaDJzgVRnf"aMm;﯁x}ߚhXF;FJ`f{WZ_hgꦝy猞B~/<羒<3jͫOJ#a~w-m{"m,m却m׳2x15TLn$,;U L}˿oBj5uA"b-ɓ. Y®8䨲Onɋ؛wX9.S;wH/JwȮ{Ժ?ܒ[ͣG3LuӾ)7~,|cq}S_r}c՜RHOO9[~vz4O޹H`Xjo^%VH I= Zj }q =! %K7QZɋ؛wҜ?5vǜޗx{]w\^CSjoRyMawِՎU;vE 7J4m %EY<\*{7z԰Wy~xf⠌JipcDXFEQd>#NKXI3Jk8Sv==Vnt9_'s~j^x 1k${q9fz"?qfQݴ;]g"9k0{='/iNw&X {*{Tݴi_?F_[ _\f$)/V7R k\ȣE,\U(릝yty!d`eDۉhC1E}8a83NuN^]ُ?8E0Fx${#~"0 0v3mDʱҚ>ADA{gA۟R9LAGq-˞i'/box:p&JߚClցҿk\ '{<%l1s[®v"/\S>;3dOlB߭9Ypi8a-RhX'GlY! 6T@dN$(t,+\d*T{V!*+~+>>왞L[ 'A*bK87RWV]\E?uiJx0Wصs4QMXgA#g0&./TggRM-\~Лm hHs[zYOd;q4Po"qaRIЧ]\5lꯠ*0=OaVQyY??p2(Š@E,5"X'~8}ʊ/8Ɋzܖ=<~J?d p(pq䁥LP'`C5;50ȞyeG!pkidIM9 UݴW`ojIQlJn#)RVR|'7lM'ZҴ$5'Jإev޴W`ozsLpad)&b6|6e_Ԝ)8 T7f؛w]`ka`āFJk023FjN,L᝽Y/Io=QKXӞ6s-n47o}q 煇D#:[OI;7ȡƚ3=6쑣 L{{cMEjpeT7B MGBz68Ң;U7f؛K$]#9 \^yǩ3o0$4p Nꦝy׌ܪִ(aD|dEH|BKf5%{*ۻntƸ]mlbS9l0EMÔv KiTj){a֮g:/bnyi M; g$Mf| RG&geٹAar~xfظu`f6ob-)PE U7E;e㼞5vI2vi5  ˵˾jv""(gyy>rDĮ/=k[)QԜU8L`ÿ0?. t9lG a)Ԍ7겗En47o= &;VМ6Gl߮^vn e믩s.glH v3 ;=',}k^NPgvn&:#L_ 5e']*aMy}QvL? 2TN&k~IZ#ۀf/ =/F]dJNr+7k_mHo9K)7RWbqscAun}N 9k]a*n纒cb ki&FJm;y(2[0xhRYKbGzv3w zQ #IӎԹZX) \XSٙEOuQ;7|әϲaϛVqqiM77HS3Fb6@Y ҦnyܒY95/懜%5IW~#^]XK:2ՎT7WCUo}Jּ`W1wλ$v%-:a-\Rkb'|F,{Oun^/'/?wrtG=GZvuS|ݲ7+kFIl//f:Y3Mfa/Jr; PkzOl,Al3fHe=>5{]߯qFktRq?5$q_us7V~x 5_3UB^I^Ya-J,!Uvꦽ7~coM4$XsI,3>/7P@ &`= um=y{Nԯ~Kj^kc[ 3/Dv֒ikJ,]Uvª珧ݷ?0o5]}'(-%Eriuh!*wnʹ_+hx|+owykMN,ClXeO[m22w> 9v"vGm;Rjك[S{bA}L^w~,Ay R.3gr<dR1ډ*;0Pݴ7#y|ν$]؋ĎkݪXJ$5'PH&3mL.ց8\ Z$vk}k͔^p*;χnɋ؛w>KE bk"c@/#jNβ]''RwL ծ;*̍ؓkowkuqI붓)ϲ_5c79=3{b-ywȯHﲯq߳~'~~٫Ixo;K)Ro,nT'=z/Q^TZJvՁ^mizJ%wЭa?_E!Ev3w8|zxΉF^c^$;fPR֌XYzfJ_AgѾ@> 5S;`vJ_Ig- kbћ1;jGeN3~xi?4K{_3e~[25bg;n^ܾ kxz&r?lK ~X|.Xw}=%ƽfW>\aO%yVn$RYgmf{⪛v"=0fsϨ|J4|l9R1gC=^ŧ9o͓s]<Co[vki\0Gb`궽/sKgp᳴*[ʎg Mӈ&J疲Wh_,^r%|n[*,<$do,;Lnɋ؛w#.-KL?RL{\cZ`Q(u_jɋ؛w#|FAG:3ob {.#XJ#i5Oecݴi?s/n6ٺ ҜŽmd!I=IIb{L\vzE)zh6N檣JxMzljqͲ3jVu^Ђ>c%5Wc!o)N_Z~onQαuokkLs+LZ<85SU^AQA-XJ%We~c7WMfZkw5Yy1hc~*ɭf }a-]jLvCþo;y7Nޗ߶Iا'k~<TNvִ=^jfJj8V*y W]җ?vT.-*XͲ=V2 4V&dwkyEt 1%|g'Fʪ=".EunmRxKhV$O,v$.h1;4~$-NcQ)A^wޖяXK5܋hÓ1gQzkh-K\9|S)3t XǞD F,G:b-$ݓvO+n9\]6$iﺦ?%n"0b7:$";zW(]en?gq"}-[$I  u-${W CeoIMf-ungDhm?KE# qo.{O,ei- 4_~9n:cujc9kQs:PJ¯EKs%v#e?M;y{]ͶWU.?eVb-/?zW.'X7yx_>.5}h^3Llw(AIt_i_HCkKMY{Re7ϪUœ;wuk>|>ÓwU[ͺ푺 RrJ1dM;y=ڭI޹gq:wYPbn}f| i^y3f.<saِTvYi7K/g&0zR\BstڟXK׳PsIeYv⹤R̚!|^=b_gh'~gQR|7|;ϋ='K\S=a%-~+"Yv3sP^j)$S}M:CMY(;n!/0I_$0 eQBsI_I(qɤqXJ25'I&YoΌ@YY{ih'JL$Fq'<~ic>[3ƞ6_{6âT1Wjc3O)?#[s$$| .P mJoIr+i@Kc)e{Wdy='6l;fګ9ac7Gce~9CND>탥eXǀY7 kg4sh +STQw׮쉽yE :sSihע42>94 ,cXsźi'/bo~t0Em#!?jh/=wH0i=7\bAMWn8uq4/?=i,v爠9":R2GDQd:\']PsF7V@h+87FGZjɮ n"zZe'Uݴ7QJk^dHrXĮXK^WZ'x]Jm{UW/5W;pָ˿P/;Wfoo7ϑ k$=y51y?9h-Q1ଣ#XJ{ܑXJ-#NObE?un̾,cGΘ]@tcG掳GX¿U#k|IEFr:Zw:i.|[ggTPc\**6`m1G!WVnfd^.*?FPRO.:QA@5p 4_Fx3fŶ+8a9K+6Zd.13-AugjIBY6-Uwq%sFRLDtM̓)-&DI8 |!҆vg]`Mi\E?ج9l~~(3c3FEC5>$GDH\lLM ik]\E?.V83)'ZWŭƅI$Պ"gXj9I*qܾ<ъv> Zh!~:YwY$|R(N qlf Ulwq}LoH2~6z5j|/+XB&6"vЁCD'KͬVӋtq͎|(1R<語x ]cָH8 Ẉ@L6qfyu 6]\_}rX1޸AZkg?}z!K}NZfk<:;c>Ǔ1筎3=vki=?΂VpT`Fg,5oVi5sw,o,.1XZDlm|U.A)G\ˡ=Æk[}±"&2q80Z_-$\m|nJ'V(ų\> B]ts ?۷+Hgy±=I qSĦcgDL岗Dw~,OԜ|C~ uO:搲#HMbi7~xYF=Aei'11g-%`{BXZ Tݴ7|/gi,ODr|3.ʤ~a-]=whps5nm{y_!`{P^H>94Aخ>9wuyg;thJC.YCaY';bԌX8,Uv:4Ud:o= _/S3Kyxl8޾.iy2%KE8X׽~x{ # wۘvXYׂRuNgA,%i!iGhGER>zAo7Ӻxn:KOق7$vy4i]XWٙ@uN^޼,_S3b8{ C;[Dَ =;7q)foZp v$"k.LVߔS/`?zWSsKm?xWXS^·cY"Av_2c9ՉA@Ԋ'Oz!XQNo("wv~rj:ʏ?=}𬢝aO^#n?_dAII]>KbڐS '^!<*GocGc,z`9QvOIZ< zIj`Sz{o\ӊfsUqr{L,9Il~mk)c^w$MhCal?x__HeGrjGճmP͟ԫ}\. ]EmAXAѢ;oUԶGuĒrQ[sxRXUmUߔ<Ƿ8S IY"(xW(JzKyBXSԲ"nEWʙ/Eyd=\ 1g?64r,oKaXp::FlsvkOGo/&WD9 a"Dݴ(J* H#,4#Uc{örj5+8UgqiU\̫U\Ly\%S3cV2EV-OMym6(>LΚiGDŸNQM*O|R_̒mmɡMCg|٘"o$=zEe9nhUTT 2'B9bW'~.u?9mȳm_>NX".g,Xs)<ˆ0Re"ھ7Sc߱k,Kr,g,R9?c!c?cAp,3?ciH{|fA\arύ'/]7:㝯m;^yݍX:gSyg8&u|k5u&~81gjg+~?cYw\9x6.hCg,M.Eu}S.2Bzw1q]3e4mQ}v37UHpilۮ,H}SN"AC.30_`UT#"I+|Oc_J>]m3gT;|>㓜zŜ[=:S"kċoXm|?6MGP?6_c DW#uE5AwqvwQi[VcIU{"Ӧ^]|}}yui?z{,Ic!Y/SVaET~h&9 sMgLuQO˩޶%9f~cYJűr5Z{e߱喿t)9cՈm7_*5GLN4옜h39ɉNhTS-CάrJNVVr:oMgʱcٲ8o]˲HVYwnp,[WX?zX҆ɱuE{-g,OKV(YaX(OMޱN߱ycucKgk%?ԋ[Oeib]~?56~.s,+큢%@yYzwYi3r.KKՙڳoiz->._-wu3Ueu#!+Ov@vLgReKj;7r2v(N}Di[Ӿ~Y?^a—fگϺaV16{>oaYS^KE汐HI#*r&ծ05l7ն Zi쭷r&Vہtܴ3+*}NlR*Y RJ m?Y@}8]GO>89)So=KA7Z0n9K7vȶQ}/4ۿ 89 ϖ)w+,,- 6|,eTzmPߔS/z߱Y39zGhowLrCNF;6y"|w򲍽]O7BfΊ0m5&ALWێWߔS&幓\wy4m긏#9dB"8XrkcEaQEִ? ?TD-9ϣR|")hG< 1Ie,9C:V z[^wl̫ ԉ S_JW3~yL]%ݓSrvw)i]?z{.ɱM&ģt21-RuJd[5uKNoV-iԴq#{ ݠrƅ+;ir6zUN"wSS&ZO>}d<ϞNȏqGzĒ]$Q m Myjۏ_?XG#{싿FW?3kKz2?y+ةtPrj޶-7Z7I͜\TJlRV@h-HI]Q׮zr$8,ZpTP]H(uLLs/K}/Otoٛ󢇎wr{RQXSә4Ѷ٫S/`q;v:Mycq[=tcz9;}wWzs,elj.9a*bV*m *㜵cKjɓ9gw%,'O4Xks^eqdеnQX&5=r26 g#ԫwQ\5~6llRz#٬HFoʩˋh=hYJ\8E}ܫΠY>XSy[:9qة%vArU=wDSy]pn֢R*z.>_rX&%Ϡ8Q"3Dj{gP}C.譻qxc h?U ;Vn0RIxԶ1M9"[c᳉ s'33P$Hz@ݿ,UIlR8"K0wy~K{l}z,x*dX=X&5=rʓ؎ul(UnZoe&u"~w]EIXHsFX=P۾SNM{1B΋/InwY ScȉR#.z;5Czcywݢ7mފ'Qʧޡ&g,cq-7!j5Gocc,wL[KKzǒwl~{QSc[cY=>q}Z7ΟpO{|U\DnNa=7u}Ksi^tr6SĊ7oETrE쭷0'U:q e ]vҧXr 9ԶcH7i_?z{ 98Ȍ]Z"J޳y%HSsb aێ4Uߔm?L%7nyԂ3Ŕy.{.9⹫waZoo܋sbE\xM Ǎ׉Iű".\m;n;֭K+س3qLؤ-߅{Vuz2fƢ2SNc RS"'l%;6{[)hmë)d-T>Xs^QQipaw~yk~IbR>Xsj1'K?^Yo.wsYzXIuKڿ$/ca޿_{ҏ_عS[ޏe%?f9ehlCR=7?z_>%ފ)Ư^"JOZsOzNޗz5ƭ0'ӽ!g`ai(ٲk<&T%9s۱?a8)OM6N4gaGXa;q-uS|h&}D Zj۵87ԋ[oX%T9^\D"+ku]XRΊej]zNѶboSSuPbRhCܥ73_Gq)#gs>c_2As?H#T|Pjb_zAu镉#t<qNlR<׽۾*j=rZy(O"ڡ‹.HXRyhN/ƢvCMyjˏ^+&:"ߗb{Ukd!/={b)齉?Q=7Wy?}p NbY5x7ͨ*T΅ިӃ]3׶!ԋ[oVQ7}VXr|OT9r8oM!8i!ŧ>'+a~Ǣ5vS^ޟSu~b/oP#cHn|[t¾;?1zQYv;Ķ7i?zl)'8 _ȬH]e_UԾ79i,TVMyj߽S~3Fp.RM٧b ڶOE}S񣷿<8ߎSuwxNH5ao}W}SNwߗbdJqWEؤ2* ]7,vsW ٟWdlnqӇg/9|&=S,XdW38zuX[:}^Gλ{ME_%Ga{9ɑbFUr9зi7Ehqٖ(p0!?iRCbʯ+9'JW/=uoSzRypf%9KXaAGY劗LZ"MXRUʼn؊mW.7i`o?keX\lj=#u)0|c;gUԴ?s{8ּ!{yUG̹=j㞓6vv-Woc0#`9ZPqaϤ ??̙3CS mwj>7;ňCoDoFD4S:,4x|MaRKW"<ߗ󌠎R#~E\M~8ŮbAE%^zX񉌩ɉK߇:jj63s^o1)2gS17i`o5ڌ;.Fu;fRz E6&J,(&R۠[4^ݎpĖߗs^?=9\e-?a&%8]MllP7ԋ[oeslX0D5W%;}")Gh˙R AM9''N-V3DZ'K~\&’tr26Rgۏgߔu譱 =Gqաd=}q9ƒl <5Goc'~әo)*߃KFs&0aZ@}SmQM㊜3{ ڍJ㲤I7;8(Zjk'}SNyId ;*Rɉ5C? n67 ؏^56H8_@ź 䳫/ؤڛ/dgSvVϾ)^zw)8wNxv)o|Ei=+DbI;gN{Mm;)OM{5%gkPo^Q$'w(G[aI-{M{bl{kʾ)OM{Th>"gguEs)y;OlR-}ź=f쭷߱Q</ '4)Jo*K,lRw3QY*)^zqs+y-roMڲK]ړ^ظ{ +db^ԵeQ`E>$g6c `]l'";/'O޳ )JE5蔟G&%9œFZ JcyK[;ƴ(9 R;,wMjca+:V; 쭷>es\ yX;¨W#ljؤS&駰QF ̜}SNq89zT!+DSI})Ί#%aa m rE쭷rkxO8zEГlrubAI$yB64n6lvF}iWVT#Xsy%jC]}͖ =׷~ ms}jyϷ-lRX~lw W˹5._y~+-?1&KwpF F2l;.gߔS/boo'~jC>IBDbEt3]!s)OM\yh["P$B+kT8YXmoʩyШuߜ}׾7pғ-r'牣aIY7cYѭ@J-lbR8!PmR9뽖S/boD,b{q^ H" J')&+yrb#6fY6< 쭷2)"Yݜ|#BXH[HE9 K*_|6voQ}SGocgcn"}\ٖDIҜZ1ǖԫ`{!煭вp™'>]%y#ؤrc%ʶ k:˭Wy~QE+ =B<;uJ4v}0$ L8;o$㌘J-TU-fdW~"{ B,zI\G.7 8d;RhCܥկ=c!|2Z&X$Ѩ)c@DyMFLᬍfң qRlw}$c 'c Xw=8 c=n`2փ}R mtQ# %)#,ieӐ9K8#d#nĹ'[y,>)ztSX=CɀeF5t; -)4Dj%kjo>[-qRq͉ 뀔O ~KQQsi i=U.<5 쭷R['s~prMynq TKR^2{ ۮ{RߔS/bo?sR=><9+~9楔#>Aؤgj5 &WZ;޲:"d:)Ar"@diA-3-XR>y4gc!mQ}gvj:ˏJ]m301p2K695<`nm&5Cx,^'Pu+7ԋ[o<^_h+40jȫ('2'lݢ,a}9-G5Goy5F dKdmzS6Bv# mP)[o%ޞC} uII~ϵLaҜ,N-M,.c,T}SN;vΏzHg ;,GaIZӊ;]soFԴmE}pňT-%JKmx+%e߅9 ߄ڶB}S2޼fr.N=QETzχqؤ2N\&vD3 *rE쭷sao g`S"]#RzkN'AXRYpp ,awoSm?̹:3Oe8Z's lRxXKEeQߔS/booyNSp_"<\1.yUѢMi#96(.rkƏ~gȄhYpEwlYT(&"ʊ%OM{DI]1^(:ؤ9Qt䵚.;&IF#-*ma9"K$|2RBG%rAڿ\(K,Cfj{湞<5I`O:G80; oFQ'Ł58*6jxAJG7\Ur57z_>%$wayye*Jvƾ# T p!p5cab z{wlh(?yyruFS)&&Mq^b^䲣)^z{,gOsJ@ͳ :pߎpMʥ[rvQ1OcIm4`7i?z ?wsrƏK3O|#,ح׿ 95D=Ԕ AƲuدͅ9%[\qII8W6)m.A#6j{B}A1N׎4N0-)R)r$P65u86N8)RA%Im ?anNWP(͙P)%ux&Ff}yoSߥFz3ȜX$8{fg I aR85'e۠&{YNXj$q%,Tp6QKQBMB*7p@,7UG¹`)zX@Lzz Ki)yڡH謶}T):쭷"⿛T#j0IVTg<"Kx؂lxt9*{C^qbyֈO@15$G>jbE9ߜ3$aqJ7ܚF[o/$H7;k}^VrlsM*rFm_ z{}Uxq Nbf2DI=(uڜ&<Ԕ#^{3h`XJ|3XQ~rEja%Ŷg;ԴKHL`{sbfBĆ#>5RezmlR 7׍e5]}U}KNig΂{T'ٶ(=rikD_WO%mKT}C.-۲D9 Us^F"b,|k RI R(ȽD9~˩W?z{<[ڛ9 kR)Zr~{%T ؆|QlrGoE]W4E ay+%<ÂyShZ'jۥP7`?z{|9U_`*,9G*r$TcTsF5ö}A"rE쭷 ߈އZ ./ N$NXX3|aМY ;tSQOsvzUE魩OlR'^cgO TߔS/boSj _PH"*D-iEcMTAW-r?1-OMYz{N͠ Plv$i(CMjzO= yIMyUޟsHr/ZDqoPvR"TW܋34vUtm'-ebΆW${)،Jز'eQ1[uII)!UGHasCz6?~RO824Ɉ |=8EOZRhCܥ+oQ$i˓hߩ\,/$Eܻ-V|2"8Ց&ϳ. JuXS |gIv9Eۮ!^~;ؕҜ?ԙOxTN+oI鶛8Qj{eKozk,Nsg'֍] tryƎYrKXS.Ϩ)OM+!u./jOK,wQՓT Ksb崥[ԴLmU N$8T$Ў FҜ)8&VTX}sZ764 T|D!{Pt aHy"]Ӝcu*~$3zke`W0>Gս#y4gccKm{)OMG[c9ֱ4븈YDz(9La 9Ai"NmΙ<*GԬPa^};ʩ+I;%K!oʩޞYy^9&Gq)cWӑQr\6'MN!rĶۻn쭷r y}9Y_ N<-5t[ŒGξ)^zk[Yk9#Cn:3TklRrk(bRvkoSm;9ŭ_NT(Cμ<%ߗLMJubβmPi=S/boey3s `b"`hUTӏ.|ӜVk[4KCյ"gq=lQy56Z9Uhz#ƾvbm{oTDkoV ##O <"1~|rԒYv1sɩi?z_r}I΃xF]GU+{Kx朐:an_[Q+}DNnC J*Z’r,sx+H5K}SgVǍ7JW;*a0-[bEtN3l?ɾVVj:ڏ?L&ߗ3_Ehᆮ'IyY/lO` cArEGo[O}㏙0ܶK<䑶=IM~6tlSm?̋Q%*1#2IxUA+n&8S)IԶ3oʩޞ+V]4gyrABJlGod#6kGP#"wvnuڍXThދ=x>{1\X1{jYtS!c{׭7i?z{N|poqp}aZd4o[j+,){9g<5 쭷Ʋ#l̯lʏǎcyMybMHNIBR2z{Cg˽9E)r5WN$INyJlR;7r] ,j;W`owTwpޱ8m)UXRΚj߱|^QzǢ6[cūgvq| J;cXłKgvs l:{/niAy]lHi (]YPiXU7)w6 ]F,C-׈;3R^Ê3&̶krk:W!Om1&mFMVbV ρlW#M9"`ԝ@&ւ_v +޸^D=XXRg%9u!j{ <5Goc?Ny*1=xά*>sԴ9]i}CnMvruX8w:MخȊ.ʔ2\ah"Bm;B}Sd u:qpDb[{ė +"".M}SXf^2gDd<"*OTa'6)]F*M9:ޟ3 ɮ!E-G+I5{9 gU,ʜ,C/ao}^y-K]ˮ ~EɊo=qĒ*)vbOF˶A"Lyj]*exC-Emޖ=*X|ow.W؊S^]"N95<'PG)i/yA$6w,8 qĶ{W-7ԋ[˟ ru9o|I7,lRWRpB;}r6,֞nfk'ݙe-?9_MrCȺ۞r>M[/z3W7s!(dK<"ȺdAm`Im79&ve|tS*ٜ+\ {F*Way\KlR֐SrAxv=Nyyo`?=S;b}LWE<cM:E#Tchwsԫ9.uCimgY;_xZ8S'c1Zu㥮R0^De=_ֿKR҆ %^1 $p@٪ TI)_1 Kƃt!]#4~2j>f)=w GW8Φa|M㼂 Hڮ%NήȈS]RJ?*0B.]~\BJX?I 7q%Cl[uL"TU/OG!4M3Kp T.2ՒF T:jwA>i=@O BT8GƈFEՑ'ІKWOJ[U@څR5uzN(IJO\2HBJ7TU+MdL 7ո6?oƗ4. 'B6(G*1wOqϧ{#ZgϧgYq}b=tOק>ӅztSWAܑw1%WlD5ȥ'3q |+$ql'RzgsTSv;ru3-=q"2~ d >OJ qz]ZȿzA(o$geG9",)W91'lb'&[*'4A\"%/g Mlɼ(М6H)Fبsm<;U)f[K8)UVp|7c{~@ T6vK<5 쭷?5t 0T1w@ %f څ%P'-,}SGo= 1gP+V{ܶk\YC/bom[Kgn_Q\T`pcIG&UDym?W7ԋ[ocq[7'9uZ8JEؤg9_cq{Sm\Y7ԋ[o0(\ĊW\K];Uq]VXRʚ^l1UT]SS^]iܿ:,[QqI>c’ڹ1y`bMyj:#ڹGMƝ+[]( qt/,ѣa,P]fߔޱw s Lx2]Rw9klRˋymrzvG~K+X\c!u%6XZ+B%͉)Of$Qؙ$<]&YVN$``3m =!"s社\_ye{i(G}(gKlR9rr1SoʩW#z_%˿QVK_NY1%uYXəXmoSY~|bʛ1(f+ o|9;~)?6#/yjʵzl7;<ԃzu-S~Ēj &/cif۾签)OMۿKgAKG97ZX1N4\1$sXõ2015oSSc9α3VA9CIR'R628Col`KkSz{ą1qn=TgXSL,ݓؤg&rJ76Wh{f<z2q+6}Yha&L{c9Tamҽ{.lTz:K[7,N7n4Bl2Ƥc%ȧJ=a,GgYOƛ=} ̼iG]).;99cZD:<-OM[k%)aerx#^lM $q^ؤoI:􌶻rE쭷g4欪odjaqxQ’z $v4Z'li-mr62Ͻ  JN9K5䜌i;evo-9ۿˋ~~rHgEޖ?)E?>%8]S`Fێ~VߔS/bo?^]:؜kI8]Q{rR~?iM;(EQ rE쭷s/o߼jcaT8 )*-1|:9m *K;i[?zY;CaÉ.**c#q)/I+Z] 7}/PZ~cXwC1>")>V&~$OJc91JxT,F ~%Z"|Ӝь}Kt?>TFP.9]z onEى~vOֹc <_Mjz#G)Yz⯋}Sz1ŴV3oAm ͏KWp뺰\œE\Դ=~{X ]A=s=k3(iώ_XR%>E{)OMyNe=E 3KmèU<%c#Yyb~ud[ک!xj߻NUHJqEݦ[hjnF/"{˂C["Jx'2O[Sm["ʍ{ˋKl8&5R :%|;+Ez+z aq ^'IރU#WɀcOCQtenPz wӡug^=X?WMB=DG0bi;K@TQѶj\̰{i)*|'FSΛ-紤Ҥz3|ԋvj}R*x`>]1G0cA(;adg;ĔI>Nm:Mqn-O,9ݕT*'Ʋo"|cMe ~bY7Ee/8'fIqr29ݥkJ7=5uYm[6}_9+[c G^VP8MIǤ C#׺׊9~ -JvZ)7}qoAB\Ad8EVP e@H\钺.'JAo#:m}_9\ŭt41=/(aJXהʼnae1%=lTߔu_ylbg3<6ms͸8Q_?KD)P[E۷ w꾸nHY᧍/!l3!0um9"݁Ķ}Or# 7 %c5by>FĔ4GTM%o/l\ͻE@_qu^;ˉG*csؿZהvL~НQ\m/r瀋~) yq9#\L gysx!XRN`NjqxW۠yƕ?|z9֠ilZ("@r$)ݠS㏐OQڱzEݽ*7C̈/Bm'G|oʍpoy9 XzfdiҷO\׾/ފw}ݨoʉ/;6 Ίᡇf~%5ߘrzp$aߔi/*y.ʳkLewcJ[׽v\GUStuWۮ0qQOgt9JɆ J#@|En]BNW7̡n{zPߔWwAǫ'a{'l&@IKZuNk>uvt Ait%.龸K\k_No{k\qPNmT߿C.̯l{p4w.꾸?g4S_Ϯ -f,̗nyT~ErҼgŶOrJl_4S z||k/r*PEu@]}SN\}q%^MEf:O8"~-%ʼɸ.=}kcoʉ/nQ‹e,LQыk` _(tM;ugdP_^[ E4POltMk ܤ5v_⾻j6*T%FzVh]RD"dSmzr#  pv_/^G6CMO(]z%D 8꒺9/'jfSw*Pۢl=Wn=J8 0yeWrΌQes|7>u,$J qŁgp6F׫-uI]˩kXm_bMυDHD뷏.깔?UGүmltr#-ܟ;K iq6logS1JԍZfC1\jx\m}A?_sqrl X' J_4kJu)?BhnoM9qQŭecFߗy3ھ^!%POY^4 Qw=AoSk,c2v-{ RX'yP}(]N*Wj{ O]:9^~e,Gsn=P_%~Dk9Jtqs%UՇZ.,CjZ7F/n"gXIbdwgp]b@KD򘀭K*+asھR \mAWU]kK+*4|uA+X1K:[vuy%ɶ-r#?'u/gq)Fz#?6^;t5?D7^}w=պwuS E3Ia/Tķ <,h뒺P.hV}koʍpO 圛s9# &Ywlڽ=P1l!`W}q_K~EJC/1NG=m΢_TʰJהD݊um{+)7Z*;]K=w];TQYzv-ǮĺYnNm8AR8}Ho|k]_uU+mP{W\}q߳E/gb$)#B-@2VqwEk->=?bd^uzŖ5Xnwx|x^Ln0B_1~MENE_D]H3uM=HWwGEoʉ/; (LΏ;ZH[OMP[ûKn]S b*V=vwdސgv ץyCuWe+u"%͜.bYͤ-'Ҳ)t1LG FJQ>)Eھ)r#m[8pUL7}U y} NWm{Cˈ4t_<_֖Is&O I?6+,5e$9Dl]8Yr-r֙QYTc x5DU`yZ Jהldݩj;=s׽"Ҡ]6r6ZȈ(hoQ>+Ǻ&]S>u;6(-oɍ=wGybgG9 5z$9]wGyg(]PhQvz@smBv."wNn {N&c[x7sf+g R+!%X=x*L,!<<ԁiFI0uK32~;q ɒD^_pS>7Da6oAuG-]R.&D.&r#"b34M eآ4IvM倕=mksMlsVݯ}Snܤ^V8 &6ݢs8/,[W Iп/:-P=<~W"mL0t|rYTaGNN8D/<'pPz DS*ԉgN{}ah__ S[|D G a( /h mH'~yQ #4ft$q꜑BvGِ;3)-uԲ{*92`W]W=WQO纱mڊvG."UuësSص=GV/ɀ!%X ?JFQ(34T#]yCpx_F*k'4'F뻼߇'}Ɗ@.11 F/#mE]&ZeUM_yeMM.c?6(_JFؿ3ժ5@ꅧ)7.e JCm"GLdFEH/jX2f4{w>;{7vtȰA=IYz'mW .^_t܋11:.JZ sLdNҋ?[OHz/wpI\#PpA}KDՌZWcб!>%%ZXZ/j++֝a,%GL4[kHzIj5+hRb9gy$8oGX)-Y9srSD׆2NW5VERCڋG7Bh>Nv _eJzh>bUqRhRb&֊jX5E1R ?hꙠU_JoF5U:eW ^6 ː)> jKmc۟zQ\zhblkZ2x6 b[@=͇2^TT.>!5X=XkcsgD$qHK=' 3JF[6`\x%}$n/?WF;B?N.$Y0"WzڤVsWJ4{]F_fꅕĵ]K3}?& )iJ{z?Co <1cpYy?=(=y^UծG}BJ4{rk2~[3JqHfo< "Pz&#Ko :t>!%X!y#6?;l|AL­z$-./|Vn5:E}Bjx).Vo&ic|V;{֍ʔ43Lh쓱b-Zw\ܥn+ X6f"@ LKAH=OFJ/|e)@e#=ٖJ g}\gxUr6C+OyYDE5q/˭2hbĹP7y$c>!;sJ 6ݜ4 ]x53|&V6'DWݳAq]0)ełz$T-H =Ø̀:KvyOI //V[Oҥ51"s!%K $=YsyGHSXS^__qa‹KmEm i&~8x?祔/)_&泋sX݀ _97,z$YlOH /V'?*K}=s{ɉF,?LЙRpm^F;ZmކMzދՃg"U>!~jv˼9%GyYz }Rjx9XYmX_c:hb鑞$#tRQb VKJ}Bjx}zgԀYc?t]ǚ#}k ,x5~ɳUS2[d^__8"l!ڃځeGFF=vj_(T`4D- ^~e$Yҥ"Rc>D4Ћ-Z-M'D=o/>od04 $Bni/z$HwZ& K //Vo*fժM36 rB)Gt]z yt1Ea 1F{#(pr\wnX'/#7EJ|SRgïvdDL;{ u&aid.jx9Jq^_Y|k8NRJ,Hei=UP/VuTҦ2zX FĄы nȨGuV'@C?#_ƆM3HBjix(HτfeLJ审>3-5DϺ'ʯ"%*UHXqbDHz`P=@V}\Q^^_vt_CN5Vt+]4Y|Z֓Ѿ.&CRkӊH8jl*]*tb,C.~2".Mz1~$\2^UgW7.V'2}#>r#9$%:BuKL_cѹΙUDT8l FJr؍@vF6CKOZ:pejTT^_޲仭˘$WUUz\N/=dFQI/nԪԧf費V9q&TO=O Eh$L۞VȩV3OK ^l@&HPJƛĠW,I j&0f}'(6'r$N'3^w2'd! )ф|ҙaҽ&0U:ߐQXz"-2ڲrU Sb5\2v!)O]Nf_И6#UEGꊐ3M_ẅyc< 8Nnf`G2vBo]\aNWxi"O}BJ4j#Èc?G#ET2j^>ZMsRƒbOkSsFeSN6JQz$ faܨUOH !Lx=S t*t#MxZ=p1FN%lrQ$M純hJ.VW2fY2,.a +$M*[!ZD}Jh Me%dt%O!ul18a@uh\,48ݪk^FѬbg#M=bml FV6 #qbflETYϑ/ x\@SxTnA!Y!-'X j'<}Rx+=x6RPs_Fz֓oˇGMBStq &sJ 3ou K/ Q5R Oa_0t^|D}#+ӾUhF%_$P|OX$t"%/Ȅ!>:4Is֙^ècs]gx#Fyhh.Y: ]5dT3{V n kXmwdqK='-j(!TC{Ew0@gĿ}Ǡ=t~HʢR*u5M$^8F_SM|F㏩ӿT[2w`ǥy"!I~؞sj/Ȁ:>yo`N<+Z[_♿WvrQqv6|i|2dWH32α/gqP+EEeqM<'|MFp y6O4eTvpzu^PJ=:Ĩl/舾 <8f!J=lK|Bp]该\% ѳ7um ່i17:e<97w+fSSt쭆xNl%؞ 2a::>#>kWb:1FQꕟH+zXz GC ЋNjC}Bjxx+G*7F"@DG[32JyRGVA'@C+ʭS_oMbF S9~kS!=ߺ;=ڢ>!5baFx>H=JzXIP )@JY1+#~ iK'\ݡg"߭FzcX/^&OHz/V/[æRE 3#wfZ躥R鵓2WjujU^_be2q3KD2ٴ# b2N$Kh&#& en슣OI\\zw4ɘb3h(vˌ<.3(|bw QVE)mZu%>!%XO& >8.WBD$E'Z)>!4y?jh3:ފga_.ZZcr;Đenjjb%ѭH2Z$(WeZ4HnK=afaV/#'w^8#ƞ1bstWƙ爓RDRPToZ4@J:lLb)ƈ35hz"fFZ\pHe` S)T^O_^u6-d<Y6//0uX` mE̛3S}JJX/V¿_eK's$˖5H4.#o@ڶ>%%X bmo؉p_v_*i$Nm$g <[^Y_~fʬFFlRѳnY|yGc/4JV];V}JJx}[Z-[A0lNܸ"qlƦLz& KD;)b{aD8l*9bYuT- SH82^)g a>X9ޠH1a0/Ti-&NKO j^RMJbaOWX2J?l&IpfiIHCz9jvhb GGu2”7o޸HU*#]Mz"fl=XتPg0.X=x 2ҟ=VEpD'X@.~(E>)5ZXm9V)..h{G b)-RZ?%XY9 kR«;T2S]Ɗyz-fx.WwꙠJ^x"3hb1:?"[HW䬂@2^;ԪO6RXi56 =R @z K:_F+q1V9OJ /kc K ǪwL|LhQhZ/jqֻ.V NZuF$tH82Z^Q# N툤_BzZow"@w#(y2#{DHVR[RfHDÌ$G@\ѓPDCRǕlb0f[7B _g W2v3 e. D I:ꖎX=gBWodĽPjhbmMd |{\Ap#_%=;z]"DQLuTEZ-4`M}qa>qqGvxFIZT;U%.ws sJO| K( ͘a?CG![3AC/2>UR ^-椿c-m0qsٲQML47ҫ1jI}Jhb J1Fw~f !_3qo| GfJR29aqS?&>|Z`Ag(QB/bԪê'F?Us`1,s-ٮ]AdFֈVs}v],X ^Ɗf$l] BMK#L(H(RS3Bz~ hF}=&剚;lS4 HQ5 SDU.vll#= pCNH2'K;jBD8 x#=Z%!D~'jx3oa-OSgÞI@=ջ#p Z"}BJ4{^Ϩ35/c X*ȽDȔ],mO =`D"}ZRދVseN2J>Ya5vIc? Pz ~0rDϱU:$K //˫'}+H- w.~'H=|l~RV]]Y#ۦ2ZNTʏXNs@p@+[陸 !o}X/d7| )@j̘om"3_v -虨 FN*Vc> zSaQTKU1emFЫ]mK /PUxc("uY1)Ksϩ3ξ WSL3>o:a`{.y63b8s3w#WR೐$2zϜ)1od 40@QNMĤQme?铈9z@N*V]@g1!kNb{Ua 2a탏gxtKL~F̞}yH2#!u g=óh>"FOxy eOSt+ұS'r״1`_t|ȯAw\AX[yh> [r9oN虮yԉك9k Av#ӓ_oa0EZ𱐾IG|'Ƈ"=4ɿjվS@+## Iqb+%YJLk-f TVi|OȾ4x HT]FҫaWVjbUfZX&NyRDe}tV>!5<'mOѹde ">!@K= ~i="C ZYĈDzZ^VYY'DwҶ"NŞT#10G{j=H^#ޕv'gSf%𬼹K7-ʒF限! ;S/ji 'DOt#3HiZt XH Q>0U,Xjxz\FG ȜQq'@QC܉3)‰3Zu܎,8Gދc#IK3F"eR|F{pۑ4ugBK2W6l0'DQxc gFe:IpF!H#LkchEبZudhb5`Y?+6I)"+⡸%huKK PT69p%b5Ul.bd*4 T o".KQhXS]F]֋dnj ԧW?ݚ"A=,4"4@!3~QÎ>hbSaoP7qS 'ۧz$@ބVAFʃ ?cOW!c.U{ xH3Bgz?"~}RP~L )3UÿiC,{Of4_TYE*V \!%X}Kv#ip"xﱲC:-(ѳ‡L['7\J/FaRa"iMKQKz$|0z<.\xyDh16[[w,ilvG2N껥j>!5x ~QnY{}m$SҰbJD51R~j5+MhbX5bM93CZ D}X/|am2"߇TAK|-]TDRÃU7nlf0GMYF ҂FHr FbzP}Jhbn' /:e t.:Nbqt^ $#R6Uhb%<%% NPdp'Œ,|Yeju.Rދx]ƌ I*6)7"^RQτX4!6׃c84@yNXϞ0VD D=ȈIs-V]T}BJ4{ˡek!>5Ųu*0sXHp6N#qN5X5]b^.1Ʊ(D_)z"̌u DƬZjxu}WĴ1Ge{'BJl#s!Gz{XD\ C/RCOHz/vߪ_F8nBު-VWtr$}͈z7g"ا·Jzmd-f&#]z&M0PzHVgu{> #$c_ aߏV_Sy[)XR^b"4ioC yaZ ]X3sZM)?hbYw2~z+.l_!RD|S^F/[!BxRǕ\{[o*btQ !}Xo/>JT "fK /VJ ~m>ˡ+C8O.M's#e #^ѪRuw[Ʃ6 f{SqtBw[Mz&*)Y/RMhRb}ukf!HǀDs%qu%[p@o!$z>Som7bA^'Ai=Ů?fj7l5}Bjx~U'cI_U~Y"z&n"iY/l~j5۟}JJ4XSzt@DhY, u]z"=lj> %>X=l1:v9çr%RZ"f0JDsH03[c 4{o{0b~DDG43 d(@IRى'DsN,]EJƈtQ~՚P{Bev0ʁC$Y(Fv;OH&>X1qr>F2Xbicԑޮ%](HK$Tw\/E0٧Z;1c}Mo S|gn[ҌיH'Z/٧+}Q~;9[U|:9NE2gޑ(o̳c{S^%YyqV'Գ9E=3GP6NԉgNtԩQ?-#XC5Llm9z,'{dQ :z]tD7P'b<^W^0@m3 ߦdž3߯C>\=qsp4&mg{7 BGċ0}Xk[hg6gy_tJett|2d=z1lgF7N l/˱}A& GGĝwV,C: AGF@"g]tb`{I07_ұhuo٣7]T}qܝoܮղ{s}8S5o!t^|Dҥ?cމ3El _W}^~yѓ scj$Y`O5nYOi)фt}^ȓb$WJiZgbOzqnT͛g )@4|6 Qp>\\Iܽ•12Wf~)ncbqb0'Nv|S 8*@AkŹ=q늒>vyYJ4{z4NloKg$qQ"aZ'W>1 QbD>_kHS2r^?lljhy8(0LzIJ3A1]z}V>!%A4X4lVLq,?sL RN_]F֛VGJx/ /v=7L׻Jjlg"57ljuF>%Mz/VRdh̾gz+~QGffc*y}JJx}~>}ki\LM3)覞  H1R l4OH&qX=xx،D*!EhD K'JCτfn]Va b5iYɘkBiwwҁr3qz3?ܬb; f #|Ƥ!%XsEpia'K)E3Q>O4-g_)dZ.Vu5XaH%L߭v[ͬ͛x eר$Bz[qNk܊̲GoOI!EMꙠkef(V`\4?Vo2Vjb(z{ZD~\u}Xluev{,I8l\EҨ|+=-3^ [-_OH /Vٛ2[ܱihYai_MCat7ZͶwPտX=x2/2ňZ=i}W_>;!#%Kaϱ%%H=C%\C}Bjx]yagw_ƈc$%5<3QlCk}6vFF()> T$:Q7 ArNԻ:t r:Xr/bKe#bpBVw(4ѻ"DJ[g?IdĈ*(Au{\WqNSz"\2jJ]޾W J9e _HV"8eZG +.=c =Z͎awdqtݘ4u`Gʿ̖jb̌ڬ5jbi5+Ϸ/6 >Sl)RPDV(z̃j5))y~O צgjS?dC C)H$ѦV" 'ka>IS},̑q{%[0kat %"L$[s˱/90d~Y$! 4{^U$>P]C=m]>B=ךk.Bor(ZP9h$<\]_ո{q#Y!f˩΋˷AiGDugk՛6ejɆ}Bjxm|&kj0+U'15Jt$3,SJnōZ_OHz/{\!cd`b=.HS/ϧ Ӿڭ7cx>!5ڿXe=)V{v{E4b `% g{߇s*Bk|,A=?H*7xhJr{tӍ5>0B0D$_]I]z&x,4#[!жhb)[IqHså6uzGzRjQDƠ+rC"ZݪCe'D3dnUyNy#6=lч$md4K#=^'ZϞ'lX;3fLƄ`0qG.Q? Z>!4귟.ߐFD=+EH[3_fdOI ^/d 36g;ׅM1eiT$YBζuaͪ{^dNu#Sg>#yBozpaҎ1 =ZȘ7TԲ>%1.XYF_8 Bw "#K/jg{`'Me,%ZOvڙ7K ^z&th>S5* Dke;,`*CN{keJ4.Tu-Q'"! Wnjyf&NnDSD7 Vo&/V[N}-NʲN$:֦E0*+^Jnz'>%z/7rK;ט%CF{ꕱA#se|#bVSދ>x:` ]Wֵ!9DkiIc ״+=z/R+g]FNׇ"t ׃܌^m٫L^_oAq \߼rRUWj^u\EzǕ`Xz:D>u\ 4:\^MlE͑QS8gB'\` J * 3 -镨ZVA+RÃ-b[6i6ђA߄B]ٯV.KKd;fp2R^8/>%%ԾX_08P1KJ'dA4+=r(ўmND >Me 8 p+|S6WQORL3;H#RRI^y=S }MBɶ4|ĥ>K)n,zbu3U2rtD|-iH3Lox9^7pU;iG&+3'*kNdhl/Mɀ:>"u2}шaS}MV#>y"m[:I/Ȁ:>"^#3WxuR|>Pd"RGٌQ6tA{>y/<m钐tܡH|nM&Jv5=ix랊 >#CN :o_n> IlFAɦϳb'.}A&L5qɌG'?5I{BUBY Pud:gD.#DG 2as t5}rEwbUfazTxXBsG^gۇsٗd؆^ v.G19e!ͫ{si[5.#7{slvKWLas#"r71OTj/ic_Nq27Ehd<")("oո)rdT 9K盜BtA w3S/Ȅ<|6FFvR =65Fɀ(8!~}~FX<?< u !GQQYWqu ާA3sbNxp:0ű7 #]:vu+g%Y9 ,A{x暷->8*13;='dg^LZ}γQvddF;$ɽɝ4p+,'[[gFaNGKub0@g+224z X=D~ؽqcטP} 9oKjzn@swasf;#D('2gݍ\9DJ΅\DpUzWLAF$mLlՖ7 )@w>I꥓CR8YDF%(=+)g~b zLbP ^|aDͩW#b=J8!&9n?ғCz$c*SFU'2 ʷr ۿcbcvαH:ɧ%`7P9YytދՃ 2v-~f&Z&#"oKRz&?`]^z21S}BJ4{xOd̈;JrGhJ#Az&Ϗ]ƠFEi 'DSxXϊ7U2^'>#_I7@=L,+F^#ZMw> y[s#sW+8X1^M30H.ꙠZ $^jw*m{z=a5h}bZq# b dl_0mh%d'D3hX=qƕHԞNJAaL#Cі8Zu! SIrP#)q~j' Wk%D8e&$ \,5ҾX=74U 5nIh2b0Kix)@jKam XOi~g8H=:֓1eA" ZcS&l~|(3̼'t|q*vR#U0fzdD[JݲsЮx/VqHF .+?Zu-=f`Oz{h59}BjxzH7|vHT 4v ٰXәH82^C]h[ zX'Έys6Id84Ei%G~GqkjJbZxW=g{,۸I"t=h^FK4i"Hnd>!%X?gss&Ƙo RL3;qK/Lje'D'H2`F>)kL'w4FLdO/cI︴f Bghb?kC>{O&KBv+ 陠[1K/aVROOI ^N܇r'|KlK"8niKzd$ kZuZb8QJFb3c-ئwWCQNR (L=Bg>!5<%.VGaO41£")_qvÞhI)E ꑰ'eLM}BjxQ z-d+w$BP.Q|iHǰ^W ^`!q zr`EBnilg#1^zѪ 5OHz/V<iz11nF"4lK#aH ]W^F֋h>!5<̱P2s1#624ix %B=6h%5z&1PJ4{Ov>\ƊOD`8T$q6!!M.L4X(zcf_:|\a ^t76}dF$5I{#zȯP䚭Vg~'X?GUDGC5n.#"tGuDgcXjxe}@zg k֖cD,Ezoh1G8Dfw q0kn53|:FqTEps#eڹBQdV h<7go)t~dBM # q~&>ҩfφE3o" &Hg6$KɆ&DZ`\xtUncNoǑ0v8(-H y'd,nN3*5Kz/V/[flMdc/u~RH+24TPhzHXVwES sF8^m;Sܴ҅])sf޿[3c, 'li{z/֏}s>\)z&9}xteKa ߝ2xq)z&tX$#|m'Urěz/VR%%RX 4>*w:+ !Ef~X7Ȧʖ ^=ںۺ 8/D̹;YȽ7H$_c,zn z.bOHz/VV7׽ȼ}Ȝ҈b4z1a#4=j #MfϻໂZ彉q$KQGę_zс< zosdgeEʭʏ0gRI~Gz-Y/,jQ𰓺X??2oՙǺϡD!V}*af)%XywAƐc_|Y.0sZ:1"g8 l+Zhbgc)g)Lu 'n2jt4L0ef=eN>!5ԾXkl̀dؔ 혶 |Ѝn^ælhSVm>!%XptU> dx5I2Bvt-z&w \XQ/(jRH )$*wdTq3Hu(Dh^)SDvS1- UvRMFb*ߧfxg# b!ISҁz&[8knh\:R}JhbdY񞗱r} R'd f/2R^IcMj_דߌ ofW隄R#Ue}lRI[/a?YW;+/΀sy%F8kRu%e@RĝL[\/siSMuHgnLӍZKP ꍒ R1{+iKD-)5!\ mq-DԦE)ki}zАꝊ'QnlhYyy1 ,UkՐ;ODwR=rG};Y9T8 b+kܠv:3ԨsśIÉЧAZmKv?G˧!u׸ϖD zqB'5Dlk8n$L <tVj\r,. Eҫ˕ 76> v'M%jkdBABzp]):vY p7<;*mIgB "H#D8 >JK,g[SW0I5/(Ǻt@lMIp(y#'Ċ\$XVӫ5ODğ+E[h| ,#cwZX*gVӃ?vr8#sqFoir7Bq(l{k[VvAX궷6\ِ^o}:⭼a"50֦#pƺ4V<6K]~)V)5/51Oj⍲Olq/1ܸ)EL[;2&(t8䧸a=)+1zeqkϒS,WNFRɆv߻aM)_7U磘M#@=QD\ֳE ER*5vRQ'd38%W7؇^bϥp<#m/Z>:@8 >:v7f> +ws]zwJ)"!0*(hlڊbQpTǸWQ:a5|QTV{ͽzYغqPaPg鴖J??M:~~L4~>wM3$oV͞>o_V Xb )7X=a}WƄy. )!+ng5qWCKOT׸MGVڦ:фܦ560IHEi-QjV)s3\x.q2GߖC} I lUnq&&}֩#{<l+ӟQ؟Ϛ<lKVӳ?Kͥz2  8Wlt5QȨ+Vjܣ!IȥEfrcV9to+3DG08 0LLl 3pTpiRmNYcu5rY\q#O%;2i{hoWMLZ`yC[Ь 6qzڇu8{1>fr tb~ࢥT0Vn4G~^ e?- 7vdQhw"\=Z5Q\;Hl#9OΚG=(.2T8R\>' } qK6^ZM8 ]4}va ujzwsu_C  NlL'8QHVa\}I\oYq?#i:oan!#A0^HW`.~p WA- 6&Jyĥ`oM +:TQjM[&8T:i}\>#VM!Fw;;%%L)_7O]hTׇ_nv_ `Tsg`?xAenn>24n(j5,ջŪVӫR(H〚.;~}nͩR +FNPe\LT|Υ)2j RlnV-by$hUlmp܄ a]~0Tj\S~0UN{\Zry@] \&/Cg㽬1O*j5 ,5®3䋫 n:!aWl5 jnSdM vĂuJ6?Tr+EOS;d*wmVn,dh0 U4;i_)Y'dT)})VV\$Bq~gɪɦK.~^mtjH., {m BTnǮM/p1cצ:ٔ gaF*^8ZpSe^#QȡS͸XXT/U'ff+RW"c޾=:zNFQ8 kEeC+is+]HEıx ;mѥSqsY#pu:[)r@v :\ϥh_XI^~+Q]?*xӥnaw_Hjg#aG^qv2+([ViUNƻ%x^:e 6\3*{6ЅłX173= n(JLP}IPX'7ڗ >g+?]o[pNB6X("p!?r:R|N3 9`g19LAǑV&}x$Ca~co86$zD<$uYK5z,y!C[ϱ3F[lmݕƿ!y򷜱0E}g8s eѫmkB?X5&)gm I(8|*E7: "$לd;FG*62 GDhbt.۱=RCX w +ws%)EN O%Oaԑy`[+U} Xl.ĉYO;X;H y=L s"D心I2h WDbdGs$b!u=8tFN6cJ/Ex'wcx,ič=.U/~|c֑@L~c|d:% 0J#BA@@Z#Jt 0^\I)磘E)NP!(K޴ q7WelݧJ@r!ٕ)DEBku,IXtĤRNuJ6\IE@QlWǦ6k~X-g3SQq?pj6|~׽IFK $܌MN l"ZQXLxq+uτuJzregXwו+HQv]zyn0yp ҋJ+1Wb̦/Wz( wDxXYr+(u.*SVҫ˕WoD3L6E\n|X[l}qE 8 XѷqRboi^_>o}i Sm7oLwIJp΂:ZqE~B셪V)ϗ?]yv}pT[ 04L(dC+k\d!TujzruT88OqYOY,t E,LC#kV<\R1^X½uF:NX>#B[͸-)Ju+FrG^:Kj3W:sъ,aYP6Q*pϙG +ws[-R&ZFkOyT[78 ʎLϦLLuJz}fǖIϣNg2^ؠɝY8 m?wE:4wsuِgouT8p'ŕ))u/,hsa>R7X`~E -]Uc{!QùF\G |Z≃52-,.(l=rݴ7o= q aH';)ʰ=6荥Gƚe;L[ς8B*NNDi+;)i*YJ@A.b'TGVPn?KHD+`7 3񧁣u3VVkzSMWznB;N*a\9LZ䎣:e%g|~7Rr#s [w7oZIG…'Ji:a%n`nZIK_DޱKv~34g@KKu3)+WdDX>ap*ZVp=8R *Gs1TXF#\!UJQQi¥*IUg(M_@;\8<~"#pr+{qqΩRr -+~d+ؖljK-̎ec Ț#+KnMj&Y*>阗3K1#hbHK%|xckՕU.X Uր ϒnqϥG8)p;zr)-Ju3og']]ue+UBO9.r0q[ 3*!S!6p%6tIRHA9_?1T{II*F1.vT]LT'7ʗ+-BP3ďcVsf89UZ]8 [WRq[a.]UR>'j'Xߊt/e7= [:URɛm4ʇ'Q*Fg.qw5q(k gA0{M:6?FVyB)}J[k !Jz-EַGn˸pRV;+~Lp+\q !p(8 !^S (v-fT'痫Y:T\I?bLQA¿|RZñF8 <2/]&KA:in0rOW*~g:?s{VJ QQ,-eg"qժpqAPD +wsz.l4RD8=o6~텐N-X GR1qt* @ujzc|~İ>&"IM9=-v(tBu"'JmڡS,(G1#_k vH]c0YC WOM*j:a%nh}߄ 0!;?cA8)В.M߆ [ eݟ`OE o '^/_Zq&\ա$gnrh:Cz1e?vz9 w: 9.Uj:a5nxb 5p^&C*6)ORUF_r5}~+}*~uo4 Qpq%Bß}JLYjlf_o33sHA8;š̚N_5")G9ERT"JJuN kUҜ%^j1ႄ>%ÇXKeMcBalguݴ7o=K5rܚi9 }홊2QtlVIXJ[W%/96\b\vH*;=򇷞%IⳆ;3AnL-\A( ߥ9}'sMw|hv L[9cNk \p+$6sSk3=ryk^Ć/˶붽޼,qaL(tiΆTߧK&RI//DsiJMaˋeC\-;x {6Me'2qV q4ϸoM,"5gIlA& Iml>i7޼?q˥9:BEWx֒\v`Ėtc|Y D<9-"D2֒ژ4B,TvuSݴ7o.#ܯ`Uք2{pȹ$:Q4^Ҵ7HL{oNW |KA,ץ JXJ]Kvx4 L7`%MrnL>%Дʞ}/A/'D~Bc#uvfCU 䇲~/b/ ~ JZ9hU3Pg`--Zs҄Y7؛%Vp9ӃVG:~XT߉'{xpkI4U˞e_===x{/e+wifk/%nPNm!+PpjΝ b\6$כi7Voc _4>ȠU HD:NN&ٔ1gM΍ [Į:{4${vlkBbRאeNH-}Ks>.junywN8511'>Ļ0e|c)99/UfBqdmgYqˡLX"WģgAT$G)Yrksjp,l$qOuX؛w^1j).!"Ic-"''q}Di'/bozmxėyr̷_Oh- 3$MIev3},g.׫E_`Z)1)ec-15#l.q\7E;e!3J[8i=C}nRzxiΞQQُN\7f؛7'jcI[ l96ky!:q[#2p!T cΒGޡNYE_YHxZ$zm^O`-|؂ ,_ϛv"giS}Ӛ8F?k8\p3{^vOM>B9<&7&ol:ݒP_2i?I^cSҖ4',R*\ o=RbnؚJ'rԆ-[Ho# ֒ X)?>&I [mlDG\.F;C[;ˉk{ڱUnsv~sݶ/boW;G[AHg${Jں@qi؅ezYd[KO4?5g9~7<$w(aIq֒ƽ#*{xi'/bo,/Wߚ>Uuއ^4iLlEvُwv3m :-'J*$m=5K9/頄vEm;>|IϭY:o ٓ2jڻ~R99Ɖ~r~m'?V2*٪3JXi{ZXyة{KJɋ؛e"u=5~oG}c" KC1N8̺m'ӶqkIs: N qt`5$ϰ0(,%^mXeCL{[qEWm/pٻ Frćq|j<<5$ ]x{Oun^٠}[Mn)%[cҌآo1.u7lcg+[//ZE$_٦_l'ھWb-ynIMXJlb<.Wݴ7lc Q1dU&Ioz+Qy*N^޼snr#l=%Vp:$5e=r305u$v3|θ9OokmIoZ9O~d M;y{/s(5pЛ|c{|ㇰ"o_Vɲ„\"d, iʚX0a_5zi?}RHuibI,OM>k6th]&y7:o"eZY/'w`;=l wݴ7o= 27=/ 0'BJv0Rgp~06+έ}Mo+S }GzOJ׷械{maXXlBVݴ7\1ȵ5{%.a7j9Z)2t4EFfJ^)RY|UYlsݶי؛qY[4j&^C=Vs;6e8#6%mpKC@a XvQ)M;y{o?v"55}Yk-s-ƺm/37Ϟ|yi&Gҋy$k~=a-]#F\K,BenWM;y{0B-Jxi^/•4 iq#3k ,wYvq-yw>ˋ8|&tƑiC*fpXKp44{nwMy6FYcskF iNIzwlap\%RΰR"2GTݰ' Ԝ#}6fX'86278>n='͛ςlN&nG"8$0aa{,.4=M!)lqُMo}/HVEoaVhď$G-; KYRs ;q²!Ee7>ֳi>M~"|%Էtg!d*].RÈ TGkci`owVKpjZ#In3$䎟27\e/My񇷞O^j@L|>uKB}qp1֒\?Ss:0ae/nͫ?, ~=5/9GNr., z:kbMyV4nel%% yw'Ԍ{)?_ƈ c%V3mZS&O-Yv:OuN^޼sHq?5/exq1֒}kʓ؁qhNquÞƗ8{|5.=20؎1֒\6|rM;y{ֳ 9Vs4Qƒ/U* š푈XK fM00ÿ.>Vݴ7o=K99j9ގ3klS;GIs~i؁(,{_Qݴ7o>˜Եf)b'*_:dݱC'SKф:UtԠWf< %WΜԏoiBTⓣuCql[i cy:|:3rcUó!W + I, fԖ:45/lsŻv"歖׬,ޝLF1~Ʊ3lxhHZҞ5"Z~yYv죝/4'h+%kA 'A~Ve܈kV)Uk8Ƽ~isP/"J^GB?=EkI~i#do,]7E[T;!HӔk(ΔNRzS6E?{]선i7޼,;-M3T*X}_D_qvƎBQ|RcJu 6]\E UixHJHlG:Dq.,~jFI,ꕾ궝L{ֳmȏUh6 -gt Kl,ri*ʡubz>|sRS#WWE\H* $;gMꖰ5ziJI,UvרNs:.?,;ꄳԈ3HF<$O~>ٴXK(#,F<#ꦝy3zEIY|EY9ë4Z].lH?K؛O~.FF a(ֲᦈ)e*4n!R|IJm˚l[HgT#5wPdc:!,%G޺4c'6"llrݴxOqR 穿4/մq(^bwҎHZgmogٔSƲWxh~t_a'+TqGRj siZIldwUt\7fjcp[:w_1kNXˆ1PzS$Wˮ4FXK`MA$6"eM;y{g9L: 4:΍׎';C$+=%455e%g\7؛w~#K3Ž_|HҷdaXXK\["릝y4pɥaok 7I ~kT M#.'v"g4]e:< $O1 K{–l|} j^%#wL{ߥ?`kw(E؍jjvU]aDg%nrHtݴxl5YY3di.IjM;&UZh$Mܞ36ꦝyghQt54 ! \ WI$.uyY"D[3q<~نS7Kѡ9㝰#vvUСL[;ݿ(˕087Cœ 1'h%lJEONMS"/nresݴ7o.pmE[hxm4igb)M<4u&6tGYO\7fZ9hX(9옣kideca:[]%7|zYL@C$=Koi{Z*'O{fbWΪYe&gyT^rimh[㑤yYG>_Ϙ*[zb2vsm{yRki-F9DuFs :Ce=n e낦c;QlH^NgᜨŚcĩjLӕxdoE+wݒ/)XteSݲWxbVq-_< ;Fbˑs7e#XJ=֌خesnɺdʹeYY."iaM~ 8+{f7/M#6]]7f؛]96ۊ}v@jc +Ɂ/MmJԦn~GNp4->#F#cMn}kI^i"e;릝yYZ_΢RwNp*RVk6x1Ϩ Ix;XdvRS7\wf~xw)}M_v]YHVv-~~ّUXKZKbb len^nɋ؛w~"oȅ#|C-BaN b-iᙚ 7O]TݶWix>?B 2,kBzjJKFٟgm'ֳĄ4rۇfc 혿.)}%; BZxi4vEpQunyY{Wqi&ުHNYdIhZjoh*z){;qyg?VݏQ1&!%¦zi"ᬲn_[jfwcڞǪh4pJ$+SBb-^zb.7\&SS0j7[ʪzr[\!6%- A ak,{릝ҴKXj5"Bd[M,WjE{ˆei}>?KS WzٽoT|蘚3 &p}]6e76e9BW9d.=vx kuCX #*g]7E'w\jbl޸ߤtɶwlkɳEj bF[bWE7\7Uo:yYw1jɉF08'½q͙&6hdc)lca 4.XwQE2m,`$7kpmҚGpc)U&_bKWeErsݴi}ֳLDqhKK,p`W$嶿+c)ץ7T /-m,n4}[1{vI^V(K.VX]H]dZ޹(JkQJ@JZkMIJipd*,SUvn o>ˉmY-︵pnB9M^ E돡]ȳ-T0d10K揟E7%y?MVJJ#[5&tAU]ȴ?,68gfYĮ_vk,.oM,UvW:m{퉽ygЦK } '3}Z*Xۯv"YA^=Nzv?95z@Oκi7Ӿռ#,svrR}/ %9L^ynϋ~LN#FB'[#M\3Tv֨nL;Ox7q 5+6>ni+ZjُM_+e;j릝y,;F 4R/y$G c-vWb#^nɋ؛w>K{o,Lg{\MƳD~l}ZFVfbEe?i'/boُM~9ea 3ja-]sj8F=rú03M/`d?F g#7yʙǜXK#1j D_Y'v*? 23BKxY]c=<_B;%Zidw5+:iɢ/ TRvK [lTi?m;g>?_ o؟55 Ob-l5԰0J?{:$}/Wxg>aU='Z99TsE,(3oc#3LG_8(*{hEJ?L6fM_ʍ=S3f,\Ey3"=ӓ񰈥4W잿b>^76ֳ͂hhUh) rfbTv3܇Ҽ`tlI>{ڻf<{KתwpǧmIz=n^yku!ÚSJ S(HR%atH=b%<Ѹx .Ȫi'/boz:wb۶{wZx= rI>pj8$o4(E$UTUf؛5[Hr>v4;=$̎$-f,%'4p̝%E)w˒~;n'f"8.-gJR>d7YeMQiGDy)}r˹#˾斬v"6Kt/_]׿KA],]o杉{Wnɋ؛wcPsi0q_ڔ~xHK)ɩ9s]a1V9OVݴi`oLn{|PGv~يotI]vUؔrLBe癅ꦝy9e{jc]=W[# mJgﲺ_SvW;䨮v2oOOfM(oOfG.=TOn]X\Tُn o=R>F/E;HBT|I"5ߓ\vexm;2,'`Iӆ$;/r:N[egݴi`o, K.Ԝ)>=6Eo >;i",*jꦝy<$'5 щ?g2G ku벿-zz36KRxʺi'/bo,:HMę[%]7?izxAnkI[toGlh;53o;NjXPM9{# ID8 @҇vsRDJ ;={gTd?1gj~6wm_њHIldbqǼd66@I: +Z%m,oK,66WX ՖeWX7f:9~U_wfI\aδ_Iy> ,I/a,#켪my%V?__\keA`jWjqLe?}Vݴovϳ|3gyg_>s9g3珺=95zZSC&~\V=ܹt;$vi<4漞5{gy|YBmb2HVԫ-5%vÓeoT7f:޹;oMRY~Q%ݞiXK-G>>O> "+%Q?Ӽ=5,lI>Kj}}R M}[s%=͞v3ƨ[N+-rډmh5,WM޼s뱒w y=_I>/;vkiL g+M;ېPϷO>ZȲ/~M;y{~5}ʗ^U͙vܒTG`mjb{nڛBk .c IX5y1-^b-]\Xa]~7o?55\8ATH:=CL -`e?úi'/bo-`8!ioqV{s_XJ~5罏uNy9gN8'OW=9#a%MԜθ궝LwctgQ)B$wlXApX 'rl&Z !i\du n`gTR d ]Bp{*x.SjN] p7W"N&|88+ 4wmľԜ9<,(L{ֳLP8bog㤄tR, )E}Og-L05/6]vw0A {2o>qD82OL'"o H]E댹=q4A@K,K+p"}GR1}awN*kGH+x誋RoCNZEo/WwRqpq6v'HƑzPVQrBGgwq^Ʒu(gS"ZG:?p5" '7vX1:,uiQnŕk8OOS, /v3 i}]I\a o깹l~äxW ⩱&՛G3g1YR9#+,,xWuny:`5[W"4FJ/A.b)9`a~N#ai7^hNOKiy!DB7'Yc"5u*EF:GahN&VV*1YCׄxbS_a"?=GsT8FBNZE/pWqq EJŦXHEM8nюu zwsM aљ0YtڧSqy%cSbk)(l\wN a/`?,+# TR/lۈi{$G"0\E,l'`pݴi`o|ƫ8lF?1"tm8QY#pZ H2Jٳԭ=7I+wq}:i)>2=@ɟ}FxI~S*^qGVm6NZ&pW?;xŭ8?7 .'+˲|Y8 ("|{jiaCUWlZp>ˆ8 =d7Sq& _jjWki+*+WTDN \H6BpEe8 \KM$@o qWoLWlhG8Sti l/83!⵫5zryڶ]39Aڐl=%}hm}Z|Nd6Z^)qݴ7oQk/'ThuefO~u%">סC_nۃ7|5 !#"oq[.qβj]kIilWXU7_]7)g'`:xct#GOdՙpbɧ Yju:i]\E4;Tx:a:QeA8ESqFmJ ,u*z(+3)>ւw HGHbcSғ5(]\E9m @q9<NEsYE8 SQ^3CW`G|lp7™4j-[c`ns^?΅_*,MK-V󃌢dx[#*j6 (|YeNSQp=ذTzxlҿ\SЇ2Z%~o`C暟nF?_v㉷_ 'uO ]Lh7RnSNZEo/|Q~POߩnyd W:eER,pÉS&Vᓚ^*|~> JA5Rga$-QT*nҔ* -ұn \{YO NBS4XHlOغٔr͎២m1 BPEu)ƅ{U`8\aOW@k/:(LEvqv ЧuD8 5'NV>*F8Pٌ~gCYڼ".᷏x z9!T8X:y:m]\ERĖȨ +UT_[c+=~R=-p(b^.w"`ϥXqTc|EqZTo*+$0I},J}IQ'kv8qBVM]x[Ao.8 yx܃J}AQe9;IZ` k#kj0ta0}UjmAi+WT.B)b+9BL+vzYiAr LY0TQ^.8 (>+#NEY#+p?✼W::m]\]pD|/>rst KC8 Γa'J]:i]\sƹcT.9AsDc|(A״jzK(91횻R}K^u 6]\E?|F(6O(0AвLkNBE<RKu 6]\Iy3;\ N~((8dfXul~ڼ.K0b5JK+7CT{N[A/pWя69JYx#~!DEq[YЖEkZNX+飨y/4<ףN8[uġdSU'ǩ3uKu1Zqў~ ώ 1mW+N?I~Jȥ:i]\8^gT+]q zsYjk{SRsOu׸+#?,$2]C؛BT4"/a )S1"vJuEi+Uo?WQع=Սk\fb5nO[V|,>:i5:\c}X 4ſ|i V8^7+OV Uo?-ߩ8 t;pHg:rbR7IxUldoƆPF _(4Uw3`FsxCba1eS}I.>*uzςuҪiX. H0 l苂8jk\B~*2.T}T'חkviM.`;zz#t-ME#AuN^޼k8Y4Oy\cÍnkBMئ6Izvjz[S糤",N`FHDZj{4:45텭.UvuUݴ7O'gN @`;t#R:ZۑVCXJ9.lIM% |Q'K PKuAelitxu*z~lßsjUP#̸\sv`BTZ#-T%"Ju~ ͕  +msx7,5o5N T,SR V!*ѡ%')6b Nl>X'oy83.[ᔊxE9%:i]\E_EiaNgjЎXO(v5R A +!q (uy:i]\qzϥhr;#F'ݴp8W(9#&쁥ꬓV UY 8f /ݳ _~$h+B(\ tI` qϧx_}F}=LO0o5Nˬ(qebeV)=>xg` @>ݴ8 (qL\Z:imlIrURUp##ХSPE'*{545.TjkU*Xp)R t1]]c\:"[Zw5BώSQjώu*z 9nV UoƖrI]O UOA+-\8|ò:UwqV!)pD!oY7Wn(h`(_?tlL:F:FaM{'6֒ޤ3cVsIҺ7AĊnԚ!|-(JE<!%w t,{dʺ۶{צD՗L>>p_7֒㌬i"5Yq^#q J_Ob>/X1!([/CU VzB((jJ}Ku檷k^Mǿ.9؎3eBΫ8"qXJ5֜^a1Mc>n=SQ.SRyi׷qd%XypbOlxڹ7~U7E;gCfV.r,s)iK~M&5%v]e/G8Pݴhxpc_5qQ"~{tKz#['̓Y &,A]7E;~8nioH$^U=ߥJtXSWTX6$SfZ]ݜg{|yuiOa,܈ڌ~dxK'L {P^ zn=QH+Ό8Da:mX\\T9(Gpnd%q"kbN\JؘJ1E;'¨V {/WяSr Ɋ"3ʿ\s-Y ptIED(Du 6]\IDW6aj޸5"bZV̄J՟BM (?XV U'uVt?7a ~5n'A.+"0K]R:e 6]\E2XN>73M9`-ư+f(YqN0cdŘZòNZE/pWяM~Rq @R%ˇ%6AS1/nAYa]7VLj4(SF#$XG:i.c&\Ê}NJyMI~JyieB~%FGN5XjzNZ~e`/@+o̍lL$>AC1~+ngpc0qפ;tRtTT;t1ޜ]*X̞u*zcwZ4B`pQN#\?5Β J]CNZE/p/#x_QTѫDѠU'y>k_㢿+˖ՕSCi܌r/䮟#iNi4п<~>Q?Qa.}P`EP`+cgi)C::e%6^K r ~ V+JGjE6#F(fJ\#Vn%^\*l/rE{!~b}kcuw% cP!NYM<߅ Ϧ8W+1Qěo-bQ8 eEW>K/ujzUO\v+' K1QhPy*)f\bs%fR3b#uy0g9Y}bpW ׳z#4nnXh:X잣.Cvs6GLqc}j<-t-{瞳{4=R%mV}fӼpwBY`#]4ǻ /{] ؝_k?LG$ foQnέ_l.H9m;y K}ÎЃ͒Fu +鰻9`6\v^=Lށ7_c]oZy:]CdNV,. '=+pq88=Sdqq5&{ViqbAxXqOָ! Q[pROX\/Wwt:K{mu"$QvD VRn 3_Rvnզ؝>k3~sz͒qv+im.M?6o,ϲ);V,ݳy*Gf{e>]lpijFg,g{.{]{W_#}Lf1Og:TѰfA#F_5}Ńy5pJ 3픽v"ۂ0W'lv>i%]5!\jyS}VX&-,ASvw=Ly-7ͣ^@ώlo6|{A fc9tGRe?ݖQ>ǎzCGQb} /ー7MM<%ewen؝2^t|68ʛһZ LA%Lb+ea;lJĤ^v1-oV4- ܣ0TfW3bǭ`#)F4H,|Rv|R%mKt5B TsǁXXnƎ`%X][n؝Eg ds2fc%*fcO9vl4VRҘnj嗲/:n؝ۂ]-p8i.fX"uJB}tcyx X.;S7iax-Bs˥R%\"LM*sŎm`#ɡ.3?rݲ;|_)WS0OĕoHɿK~[E,<S`g0v"2JED*if(S~Հ#NK1؎7MeWݶ);on\T7M90A [JTkl$ sHo{!~ aw]8 y[;\;ǎ;aJZs˥;5tݲ);oվhj/ >[X_:Q˦`#Q M>IJ)\v2vt6Mcï\]Rij56Rkh"]$om/aw~_2Z#[u/ $}R7{%6VZ#/ *5^kd-{v[p_3KrRUme<{[^\=2{sݲq`_SBͅzj~w-J~%Aij~h;xKi&9`'\L-b{c53PÿJ\^Ka,;3{z9fUu.g{./߀~wQ[TfH3&~r+l&\]Zi7/bxߥ"R n\H}./G er)=]e/aw8 "q1:G£[ֆˮ>$,MތN˞$e/`ww q(M3s̓Iv{%46%vkᒲoIݲ;os<\vs~knRu"e?&v2Ӗ/[[fkӖ?m9?mQiiO[F ri{wc{k ײO~oX~ ]V ؝2TX |768<*;AqR%mеA鸋URN׹n΃RUXJ-h7MnEm6bv'yԱ:#T [}өH4.,vRvn/Jy=tӔ{/E׆G}nSyr!vI B ?|\7Eo9ˋK pk0uxyd#L7v抲-x bJu9Hn#KSu%AJId7';bɋkx/Xޫrw[vvdla\/ͣ kɣl=M_n|kp1%XLI3|-x ^YP3Kssר0\vZ' f(L]K<v` ѮtLuj?487iJ{RW@T44$;ʩ;v1=?W[j tX<RLevmc|h \^v"z_..T4{sh<ײ#E h㢽غw}AU%[mJ߆q)8m1]U3%)_*+׌h9KQ|]&Z댕۸>?!Q<_.k3r)|k7Ɋc'V,.uQ)q%KM/{]>t}kKaGRTpåNowNYM>a5jij"}MkbKKꚞ/{-.m B[Ρ-eS'&U%{h>G햦$$ϲ#oVbo\rٔSn؝r#:25$ G|>UCNAc_s==ؚ)?1ޙv[pRFO!SX*Hr?UQyJ)IS %+21TNvM4}i*yRc=LytiK\!'$}yiciXZy;1/wٔܖ\0jS,(]>:coj4ױ{a#ieT>c9tٗ7XRmi˶c8 J4tH)tI΄ReVBۑ+XIiXXHٹcS`wc8/omv4uK6o~=aobgl1Mݲ);?m}bWywE|dWaӲ/Ѡ9?)K#a {e|+ ]Җc1H}`+FL/nK؝ےg3Msph츎l> soˎ^]ytptM_Vok]}4XIch* ꑪ[0kߪ60cҼRmG}WvU.IlvFv9n(Hݲ;|Wsg`+ Oߥe˒eS`wn <9LLsa#bu/,U){o&u.^8_moU^mX_mf Ih,6Sv6SiSŚ0BPے*J%G?ZTic`k=|G.um=/|F?a.|K*+w3q,JUaW-jRw]Ly-37sTDvr/3ɽ, Rdog6 fX$Lݲ;oQ zy4_<^^(>\Ȏ}Ԥ2H寥/Xr[;vvr:|6M;[ R ud)dNXJ,[VeSr[nt?XyW{tjؔ0/gF,~iga'S}-{xv[i׶E;Cp_R_q+}*yH>pBgc9Kpu.^Ֆfme֩1ZǮuZ O,LR$e'*[]y-/{r.i Vos{qUR9+ ;|΂Y5>8rO\EoN <rԺ+ծpP-lI|vp} l$xV/3lJĤ=y-!B'ijazXJSr[ `F aijf*;Rۿ˃[ G]Lr%La~ٚSYwfeg0R=okPvR>n؝] &fٗ$ ˎ<"Fz bxM-}y,mAp sӷ΅KB}Lno;$/Mol|cV[n>rzij{7bnIcG6OT`qOG|Lݲ;oW}9Qo<K$}=kD}=d8el$:GG`$De/awjKO(g4]O45?l ˝[0vep.έ+d9Ԯԃ;B+iޖfŜ*eٛ=LywwYX%ґICώm1Lr X>dLݲ);o3X b'}Pu]g^D*JkDZ"+VXkmYufN?15ؕ “čbdqxl18 IZS筦WB|W/=:V_h6J0.swEט#Bu6嚧QڑGF|󾊫m.%E]Q(Tjvְջ>|1dtR`ws K Y$9wf0:~MPړZu*z۹>l7h ?R#2npbฏR\'W>ڑKQAp;/Amƹq^ 8KBu 6\$=J@>Kˉ :%h8fqj.êUl۹O9OYtV;Vl'a(oVV{GǾKUo6ږ`^/:.Hץ="=qŶ5h.5kV)5~Ƒ#]H1ۙc[*p.ER u- Jy(Vʋc["ʁc|{ig[q gҦ$60 [oXm@7yqt\ݬ\Uș ",w&%$&:֝iI(5CBabёT%7V7.GpR|uzvl.#B(*酇݌i%FE>wpYKp%zK_6۹QT6 ykh;_Cqhe'.;[1JͶuDb(( 9  F'BʫQt)*+)qT(NlP)k뗫:κFZ&FDϸ#y!P+(]V@ְ9_z ᄏGqSywu조SR8SEhoKP GJIsP*dgq1ϖ4ZL"RnK]ꪓV!n3|t)n&Q*}yK*:7B')0*|IYj:0޷޹zQn6zN8 PX֧mZ;aRx΋dsqg{&3'MTF#/>$9CJr:m\E2[o].9+JԋcF]tf.qQi痫a)+gQ1=|;jN!A?s݊:A3n T[ 4CU'as\Bo}8KQ0 qi+F"(4k܄ JT q;Wpg-Vn8^<8P= u`KwkG-w^v>Oں f;'=/WYQ6I:&FwPv uf1?O }1urb7ֿXdCfas-*jSa6~d|%/5 }'^ލǩ;}h3l#HdW BG⋈yF|<\(`yW"Xlp_xѫoԀ%8<ݻ0Uy V]a(wc įYɇggsqϱym+BACjr;ãUl۹*ɉGut<2…7[zVE$ o>: R\'{tfpv F Yb\RLWGKcvyaf/+͂Ӽ6ۃ 8z3:i q<8P@NvdD':j8 mHI!K=RyrӇS ,U_WV:.h$!X8L]in皾_9۽\RG:t-zdvq nh.5n/<}u9</k9ǍK4ܗ3u{j'!!5aRuz_W}⫄2 &/**?#A<F"|쥨7PRPKNY~iyyD|;>Y,:0Q^.̡0?1j2NO#ھVoTo0?vbR.́ ?2~02C߯eM[]5Wle ==ōu#.̩0< ߕy~k-o E^؎6;.5ٮV!n~r]FsHM^L$aOp3.BNuEХvw q;W/_ߥx zF a*:6ޤ) "i1cEt}z*JV‘vow) }`\EЍ]+x3+6뺮V!n窳A˗v⠻]ljwI㱄LJE(y^}t& #Ϫαx]y-8((Ɓ_hFO'AnqVRupy ,>L=olK}]!u.{\7~ ^V+MKDzal:"4qż eg֑e/awޫՄ gY՞Fw*'>Jaחtyp4s,,}Z\!u.ٖdwnĂ|+Ljvd HM70bG❻n؝x&޼4-%ײw46R;7X+e^K؝j N{ilzUIrB$7xyXvI80ٽ]iꖽx>*i͝> G=w^s-{a%Φ9\l8-wi/;S鸲{z<9pXy=Ev%ʅׅ$qXXI)sa{F޷%-{jE-֏’TFW7%<ˮDcFj95X;G.]:jˉ'Cv TهW%NĒc05zyEOrݲ);oeðe4UIZ? ^(%ևyl$a1R'h3s-x R+sknϝy?H{,]9~7@XIB4ͅ%-=3qݲ);oQN>97]a91J(HriϮ/ΰJeS`wwˌue2d| XIg"oy{Qg"nô?|a S 5ǼW??YXI4\X8tqKݲ);o_M 䂉{N`X&g`#)l4a/{˱`Sw%{sLq1NGmsJ:KScOlԸs\uW[35|֚DtT7;" Ӗsa9ukje9v[󫹘ݲ‚4RJI!|cgc#wz*q_XCLILe/aw[YW|}?(; ]Y?}/rtg}YѷXdOIɮcS}+o@ˁ_qNۆ :$g;i1ica,Jeǧ$m錷ҳ,7d=NyϽ,xLs^/M}fdםa=S<oF|v %'d.PZ]X|^m9=Җ3i,Vq[$ק9zmMѓxWþ;v1oe|RkYl 'F$&.F&}=ײxyc-eX.{]Znq2ԉҟ_MMQq޲x k߾͎`1ݑR%{.<3E3?Tf4y}XKk4%.4.ecSJۂezKS_yb uYb}O_H>ֳGsr@pXu.^15 A5ԫ3:`@0Jyv3N4)l,VQ%Rwb m=rhi^`ϔIQ/Z4V[9x-\=y/y5ϢtiIb;c-yjsɮ;v1՛x-AF]6и~1wKeg=FKƅ @\vm;y^eS`w]H_Mݽ=<+}7K|v5c]`#3-q-,:Sp=ysn׹$mm\#Jk\Xs3G[vvpZWHsR .C%և+ӵXIzyaq3e_y]a"lEY3L.o X%w5|liƽonq᭶'"2M{/B pJqAPW]bna{EqCԑ]])qk:)^NK|;| Pӛmm[6\a [1n9%+}1aRJ~F0<`We/awޫ- rD\ ]T8Wݛ@f}Zp`V{^@)+qUzaϏBg?<{a`uC?s:8>zp 8t.59\g/~V7} OQH4pִ*BLuJzcr5}F=Ng14au }IV| dk )K]y-GΏxisgpmͭ. VҚ[- ˹^s+-{jn󣨕XŵDeҋ H#Y,۫ŊLYL-v\jKuJ6m\M{*ٝ?n'GngiZ{^ˎ{JʍMS`*>Υ-{T4tyI;ۂi ܖ7C" v[^,nS6d\^F=/KU_ic'-M.cK<,[?1Qa^%}xDûTJbƩ$fkxl>\vqRaM 7<564ٲ[NKawi{fR9lIݲxom!׳PS_)*cfϻζf h}JݷcKk?ݖ4j4]1/K16s.7MPyXb2粇\@wf=y,I~Fwee}v>R]>J3'ޖݫ~H%:-Cye'/cwn USibL`5ֱ5l>$M98R)^S0-xq m5Yqx]nԲ\>9]=L{.ϯ5^L;CXv~Yd4it%l)Gۏwawz˛Ra< Zg-y߽8}6RFvtN1uw|/awǐ^(&[4VŷWBC߀}a%m_hƳFkt9vۿd-MS.3v N 'VnL#l$KS6Ğs-@]ma${nipAqpXXӖ sKkp,6Rv2u.^%t}*y؃yĩbOɮdFGZ<[a/^T 呺c/`wn |~Ś˔ȯKiɽf rpigaqspe{&On}t!^'>eYc#͖mSvnWT*m &/֥@$Nu6ܭWيY}y)p:o\cO|:e%6.1 g94+jI.ɕ^oqwaqؐ1umi&$F즹 GKF{v{=06Rа{:(N}:9)x v[!CA\x TI$> k 눗H,M (q){$J=Ly |_xedvm9-3ضIIݲx^]֔1JK_K%O_VR|7M-5g`ʎb}1mo.aϮC>]ǒM]J.{f H.;'[0npRajñjZ%Wn sq4XJ=E6Mf ]eqݲ/ ~nK4 '߀XP~._k5؛_}]yk/kRmLJ$?+E9`һlJ?#y᭶=T-KS{1@^ӒuzȎFri^\c6 \v[YTeۿ }ǹX4׵xM8KO#9fh(a#e" 7=z-y沋;}\#i)22=aw-lc}]؃Tu~'xjKyUJ;mgܐ.~9k2~5hhfMNN-{eaMJ@ lXJyv}^/y @);Ra {'?8?L3Cor~ۖ(`v,R([vv罾//fMm4<MZ|Z5.1m^}%lnx(i\%Zxÿx# ¢(ZR{tWQe.c%/Mmly)uY뗗[#g%wٹ;=a,Vn->k6{߶ lU}~5se|;7HgiVX8qHOs\%{uDijTw1.^ 72ndhNH>XG^[:?wvř4&qױ1o=6h/'"734[vv}+yrnJj.~mkOm Uzf|eK:׷1 }.,SvsMy{eh50 n~[\Y]t9 40屳^Үv"\*a4Y oGo@o޹ E4ZyEǒg v1޿؜<K_cLh9Es2VRBm1vAʞvANݲ);5)fSvJx8o/鱗Ssao}4ejzt[0v>@׽c< \Dn#H|l $lǤ[a)3kK؝2~MY&~|Vxg})8_/J]3})+q50nl|~AĽC UYT8 ͟RQa#ȥ^dS pWa ׆R P=Vr6K)j,;# Eע||S'zm5G6nCCM31JBe&ѣٙH^/[CW"c;.ge/awn prb+-.fE#f0EF$"M}=eS'&p3=Ly-"XTH@.<(,%Βܹp\[JycӴ{a/ǔFٗ/Wnôx>b5EÜ*pZr??XXIIi4irU%tݲ<ɝW?:+]o^ܯHgCM6Rv1zs;F*{fu.^Ֆ ΰ]sb)} N}XB}d'#+?,lMͺmS`wj Ȅ> i|u8P׋L㶎ZgSy*݄EJ|\/6г;o5;g?>L^Sbe;\Z3M^\a?eL]7yͶ r' Y E˺vomyg^!>ZpnXqU8*5[SVn_tפjTnLz`Ē܄-;ISh0G ӧU]y-\DӖi]i\[[iՖ?m?m=9i ӣT7\_`#|Ewa;m]y>6#VV9z(`u䱣g\Hm.S/ﺦnK؝mݿq2QLH\A+VH0΂>)pcC,o:L6)q~A:ḛi{OxȬ@ =xMBe'g=Ly-*% [z.fIeؒeKx-'f:j.t;K3%HK4ۓh_M-x V[s5ص7w*y ́ k0ѤL4)NKQ+8U*)l۸>!IycqS-$HUn-,]$fLݲV[h(X[FNfko\?dE7.c#VO}EuN^Ֆ^o&ZQD+Y:l1QJq`,x%/[E\ړi[uJ6Ƅ lԆ^(u~g%\M9woȟ*;9W NZņ;׍xz͇{p_Y_}F 1JG:e%6l>w7]tX]_q-Oqj)d.ufV pWӟ5\o^p*nf澹Es*Vb(4KRQ]KJ~Sn(%gŃWxq\;Q(E[qb{}خfJGujzj?i~S.Z.^S`Eh+f Y ,GTjnϡq5}w>uK L `Z2YZHIsS'eߍcZe_}~7,W25q. t["6΂gR0ќpD89NYF?8ӝͧMV0ۃޓ) S@EګGG!g&1=JM7)q5}L~g]j .L3tŊXQR|U8^5TqrupWqeå`=93`9sӰc>=8 t'$N7:CN[Ƹ迸|GQER ×]S@E/ يCY*Zg-]d#uדQ4 _/*O[I^gtx R Cq86q|FuJ6m\yzs^,??ڼ{pޜ&[)=V3BkХT8NKU*"PuJ6m\IEM{ y8Kџlqp \]moC)qudo@51b7 1\ַg|򧥸ه@uJ6m\M3h܏肋ZxeHai+即!Cf`:s:c-6m\M'g)jaRGK8!|ڳuCqpWǐPLߊPѦ[tW(1f󧥀qGs]뱮3ֳq5}6E@ KpE+|㍣pzYsɁK=:e5=6<7NN0wQ8)g)k\].K=XM\MFdn)ԡiƁXb -sg|@&Km̹NYF^9ue:4e#໶z}؅Xj"NYM_~v,P\l>pN 4,}dt)+q[oϏuK1N<5U pm},( +`U] \d#Oc<󣨥ٸO,;p΂fV ՊqRXSVnK" 8͹(\rE׆!+ G!w⼃=' USV;_{;M {[}.\H0-cogpqI;:e5=6vgҏY%ԉ?˭d8 5 wrĺC쒗_k.&}?}gvk$N&e=1INBvSV91ppuhp Vb boךg+(`u)K|:e5=6k> ~Cc-cķ8[y[L8 OK߸@,댵q5}dʨcs ~^u@Q/oq$8s :e5=6ߑ|O{wKUn(KbeG앹XI-ӾXxn؝jK oikgI8$fgRcc%7|iζ|]z]a [m?}WNkc83e'r]ywADDS{{m5iOˎ`#y=;x ^LzEdSKc96w}*{뜷.^F9wIqѕ.@ t%`t%[x83R)OQq|vi] b8[ *ֳYmV+}8Co|u*6\MoE3N(9aiq?-τC~::e%6U#~3&bs8 da|T,Ud#q\̈.DzOCNeC|{?R잪NYF3~,р3}%pS{7&t~xIi4a,y]vݲ;o!xv{^`b J"Ht,;:i< QٗDnK؝R7B(jy#8'p8 ɟ>;K:,?XF#!<|6!w*C9ĝ% '̶b`?οC\2:Qp r2Ks{5׺ )!Q82"&J]UUS,xu s#=m%6΂O)p8\px:e%61ıVKbN%Y]}JY, ccN]a:)F~cQJ,K9nHgXq8 g˟^TZ=Tꑩꔕl۸>.4{U*{.vܰ6]A`2u.^ٖYt^)G7Lc(<`l.YB8 :ζW4SVnj8&Tӎ aQ ߸8t|oØ6(?Fd#qD>8Z~r:@5c_R`0P&LfOscZpُt)j,'\ɿ댕۸.߆T(^:9}Gk t:{j-,utuj6ΦV$8jms)jGKo[Lm@#as6c݅ܿߜb,HllMWʞGJݲ;oab=3YtY0{X8 ~k9v&>գaRAe韚~JgaO[t,,NRvz=Lyԙyo-M:bND%W?FrߒGwIٔ N^闰;շj*_9t.h2$_K~h8=MsElݽmcS`wޫ-Ia#-m9:ܜ{);[ [vv~Z8?o4߀g3ܯi)r<_Zzw*oʾ}2eV[*Mh{1%7˥2U6HQfGH`%Ͱ[zR+e_*Nݲ);?6|wg%}ٿ,)͛|){Վ]LoeG`8__䉧YBEK9 'g(ěd) ÎxXI#^oH5%y]Cɳ!ILe Lr:xRI]L [m}@ρEĮ̓{NP 3؊ T5(WoJYRR :U G?*ze:e%6Ojj*]U~tHe\ 鐐KH>1ZzM팗{\wmՎsl>7>T'͔͛X.g`#y]:0-.`e/`wwm^^!Ctg`#yknO)^[ۮ[vv^*dbӔ͍ 'GuJ| Hg_C"$);I&R.k; 6M 1[58J(Ǝ^F4 ); R{/yvWs_S̈́$}7;rLIfN].{8_]y-nK4]~77EIYҿ?k._vƧ3wݲ;lhdb+ߥ lLm PvB؝'7E={okDo@mw`#w {k.;v:kL'1V6ƾZ=7òaz-){סk);VR5 _^~lJ,*{k NIb%eolހ'$rݶ9^mAlԁȍ(;%=K;ֿt;N~*{[ojxo]~vM뭎w )_s[:Ic-%39o~so.zկ- ָ,K0c-%y}li<}r=iO 3+na4ﱰ&[vUX*{k[vv筺|"DYHOEfƀ*q(>eDlQH3,J]VnjE3\VepTtS7Jb8 OF QBpRQ[޸~_ブTp^[/^4"e +JZJaOUi^v1v8ɻk_ J p 3I]Pq-H£A~b\v[)v FԻ[s1'އj|a]ei`%5,MƪV-l=Loqtc5~mU[F/Gxj@HjnDDb#+e'Z|.^]k *6^d*nbD* 9aߊ*^FÛuLݘni:YAnH зwƎ`BRbki+˦Ŀo؝C!gt7Gy3z4IO}JZa&"trqTy9S4#hLcc+6wUM@ʾ|20eS`wޫ{K!pi恎Ejv _KgxeSr[mS`wޫCR4gÐղӘ W>mG`#r5,G1.;![Yy|W{%Lt=>%m~4g[X/Lٷ=Ly.'?,E'?4 '.+~,耯l@ROڧd#?Ef?_'co}΃K*fy6g_X̮RC-x OqЂrDE% P3 ٟka%o Gʦe<L܅kxiRiK'J~P7FQhp$ؓQy:HJ+kဒ;sol$]e_>߲;o1zǬAM ,ݵ!XI´i=1Sv;f߱ygӮEIv܏INq0H4Lll9e7w@-x */Cz.Kjg[K?l06Rz#i;X$lHmF;x v]vgJ4*pQp{x`6n޸1/M$ YR&1᭺Ժw}KSxCZ:0^. *X]6MM5},eS'&ذ}*oFwlirL%Ǝ,Frͭfx6ܾc?ޅy.؁iq4Io3dGV̛jWg'4Փ{[sWE=Ly異2ͻMS'L(^R*!_E)K:P,l5Eη:`x"˺ ֥\cohvIyk9"cN]z:Ҧ \k%Q{g&l$@(_Qe>߲;6M$jpXnJd6/Y/^ʞc߱?`vG&3^+dfؑ58HבoE┝;x ^m|l7+JVJne+l|]`-;6Weut ^UYn'סП`wuKgy]XIwu-{v]x>q Np߆1le'9߅׷h߲);o%'{晐q͋oWTekF,廔]y}RۦAp K+x%?jIm5J 6gKs *;[:?U#t'?o%Uʳ#$!Ż۫66XtٔIyߥU\!ej: ='TmP+wˎOF:54Hol׃&vR9W.욎E ;t%,,=adP );";v1ޮ o_y˄%|cP,Q~r1XLٹߴ/07wv,(w܃vy)kCu^SvLvJeՎɷ5&-ު`SϮ&}ImI ʌF_hW6w ,6Sv"ŷa uAjS/M}JzR26o$ );G;X؝diTn:=<;H;EV'm ){oK؝b`=󫩹@DՈLбĎCF5\0.@Թ o$ *v$61k.XġK3}.^W]~@s"07κJαFovMJZť9".OYoxoXSp . tH{Z;v_ˎ\JʅMsŅ G-{^oՅ5Twӻ/״m=v>Pn')t2< L:"Tqe)z X\(ѧ/Wu4;oZqsd2v^k5wee$(jE8ԙ U>q2]-AODQyü8ĉX`p|C w\CIsӯC10MĆH7ⅳ0uWCiJkŋ>i \IɅϏb"FyQLjm}z+p8,X˛Is jem)*A@ X| gY38 ,E5&RD|zr%P,S U1}JXImy>ĸ0$E1m_&E mɋ3|˓ EY fyחlT_>@BϏWV6zYĊqXl~ryV!n77/M|~߇nU{G 㵀w'le "h3ҊQ8{|OZņ>^\Y_D&^&PwɊEPK!pzrTj5l#5my R`q*HRWJYв8b GSVnWSxDz,T́);LIk6`c'XqA[vv`o4ji3xz㺙ǝ|@0+I '! BQ> *u旖OZCp;Wѿq<e̿th gD^,k. 5-n,RvhǷ5}zV]ۍQk4jy =ˆ=cG`#qFyMi5tn[vJugqf4z1-?h%SfyZw=]]X>i=m߲);o֥gl4V(b< hѩ(J>Ȼiڹ8wb?W]kbimn4ZFdvϵ_Ks ){Wo8v]8aϮ*NIT;]#3ꈰn7 X.{z>cS`w^^ƪuW4CG-CGa ^7_5\2]vKWo߲;o.u5ӊiGTXmmxGJşFq% ?^F}jz~pMb5/OyUw"\YJ,>iv?O;l}|](lO_V>_"(|_)+ٌpa =vv.Uj+e .mjllw1}2e/`wުK 2qM]өЧ%>cǎ`# N{jn߲;oWh.&l66:qk)/;+)7 ) {2ʵε]Ly.%Q, Շh<*nl$mF3]x*;;vv0Sn4^c aW(_^Y]HG_CEs]-]y.ngJN ` v]pG  !>u#CUIuؿ8l$zLd2vlY6b2n/^UJ_wFSW4sݵvZh6R;k+XF)t݁[vvҨk-uFRCa%ץa]{a;~W[vvw ȟ_{2iϾHo菫m#OKJr44<.; Wv"ܞG(jÌ{iHadk΂c*وYȧC U-T[ E3cƸ3HOv^$ٸFAJ^4;e/ŷa:)0vd2jzّDnJ<+T"GʞQwg[؝͹>"1۹[;-7(7mW*Pa%MoEoܿ&RHo߱uܾ}׵:˼*҇%{eggc%uǹ46j,su=LyX>ifޚƤU:N&Nic!_>5{;n$gcOnQ٧4ķ%Λu.bQGhs]?)CYPd+8n`M)ۧd#U/ cn֘"͟%х)Dz>Op@K1ZpR@)q5}v+tɯ43eQhc_v,5SVk/WoC]8nځi\OKpָn;sIhx~XH ߲;&!,krEs;\pe U/v/<⥖GQi֨zv]_Nwi#|W4J_'Ϻ_]v̀5 S@c[ZJNn{)[tcnS+gAݶЧv3V#n* ۛ;wr^N~Kp6wr`g_c#i!:gNt]y.t5QԵPQ,MĠ__b,h`gŃsunPקd#?&D=45Nq'5=40bl$F "aN]y.7雬KQS7.B^7"(׍e[Bbd$H:|>e%6~^ˌ4ՖT4 3z!=q,.I MXOٹ߱W?Spa?jw3HoL츚o;s.ɣvX S]y.\욋G`GCDO_Z +9hϦ.X`H٧wb [u`۶[0d\JXSeEa6-1Cl%IknNVE+({]:5f)n}qtQT-R']|z۹~؞ U %z[MlE|F,(L% ~)+q듟_MuFi.J/K|YMvd*6R>hj5I؎~Mxv7I񖦢?bݣKβܜYsV7D-x v]0Cm+kƃ1 L%_L_KS2^/=L󇷂+8eW,Q?Jӂ ):4WR'c 6m\5BR`B\|HHYmEJ(LG,Zځ#0h)qg{_M)I#-;J|Vh_bo*l$Fjaʾ})e/awުKլ(Vt n\$o8QhkpKQ#kR3Vnj;Ѫc1$q:3΂Vfq9,mڧd#ov'ZoVZJ+Ng18̗]l۸C(ԽQ~0ˉ_@L |Q1dpxs).[)q]O7z*fOg5eǖ].aӜsaq+e']B|]Ix5T5c!pC.C%J)+q}^W]Q@~ް'%02t^¶pe)qHzR>e5\qa RT7u&e56?k`~w/- NN$gwpR`Fi\2<۸:p+VwfK1G ,/R&np۸.郞)N~DP;l̩ ȊQ8[GըeHz'|jzzꗇs})רO oǫw6 TȻX#\,hfE ]8DUwnp6өǥ4Q1XSA,{|pB `9hpWjx.Gsaߌ%jѕo9$a%%)9EΔ-{V]dϮAԅΔ%ը)%SBXoJ:Y-MأZ}zW|ootU jyJ0cY1R2BsGpԖ9|jzm\E UQ c2Ek p4Vd Y}ɥ8pĥv/٧fs<\MFwƬ8 =y2҃TbXm[ Xn νJI'pWǽ{z5l)͟Ȗu#{ o@G8m+rgS*Kt.ux>c%6b)0O6z1(QE [8 ÷⼂îK>{`yr5yZKSdֶCo36xcف5 )c?yRdK%qP.XI9rijheQ*;N[0v筺@ŐE P.!nDgMΥ80s73Vn*̚騩xhz)у5e}gpXe{bQR'q5[GWE `O j+I([&@.z$Ӌ|Jzm\M'Dzl n;{?X_$Lgdp[G!e1Jm"gpW_bE'_Fe%6?DW'3*(ڵYFNrlE((HR\ qRJDpW 8QT˃I_D"W /qD3XVw8SVnWђKsipvAq78m.ɼ*(5`^b7`1Kgjڷ%[oCuȃx2kyNFE{V lr8 -ES2@ʧu_KО,wX‹J$"pTopG \)}j6m\M1AY+pL o|. p}DֆpVN("ԕS>c%r5ޤ5۰8*݉Y*:LVlgMxp8A8 *\jۧd#q6yx/' cۊu,#o7REѧfu<)9gSz ެO7NYRnȹǍk#,%|~+˒]U%FV L V{~\ nnm%!6&ت/ +kL0$6} olo^XmN[pTwod?}3ֱw̥U q%i f6k%ψݼ: ًٝf붼rN)j-ow`g3p&ǥȎ}J6m\Eax& FhVY$b=.t:c0e'b|.^]1WnGx$aO .-tT #lJ }᭺\ y_a4_8QFŀ}a v6{2k:AEӞ۷%uсJ/,K<}uY殜5k}7aTb\9gSV9_Bw/YmL~1.Rн5\j:}jzjfx͙Lڍ: V3FWL 74Z*`Qc* |7.TRoc-e_oٷa ?Cqë TIw%?v,QO#-=Ly.7SOd욧ڋq3Dچjvl7BŎ'XI+a|+,do؝CP-s@=.-TyI11Ït'Ϧ7TM韘؝Wb !sXdvǵ uhE3vyA%Ӎy?exPH:~DWi, oK؝gP]AH*F =%{8:4pijk4*{:G|.`AGجA溒j:s#x0DXTIXKzi6qRJ}Ӿ˫8Ri'W,a")enj*H%s=M5F7EocS[\tvnÌ'\% _gg}o[HZYaN0UT߲;oeV'pm+&"V uo*ר8 I\V̥v)qOSj58=T ocS){1a%]Xx)=Ly.W49g"qljN<DzcBl$Z0"^ToK؝G=ϯ|0)ɵ&}Tvlɝ4%b#Vw%߶;oe'S|k"-MIK } LOŴ?vjmDuaچ{ګ$}v6ޱhyI{ʾŷ%{5]6{B 4zd}jl;iKRs-{x;+R7;[:7Ge{$ W܂tى߲;Վ)$ޘiǠHTj%Մ"\k.Svl:+J4b,%~(eS`wޫNԺ4}ˠ`_j&btiάWF:*|m=[=soK؝4>?Yx4%lќK;$vt3JpӠbK//Qŷa uN7gּRM Yvfj7VR۔==Ŵ?UYng=2~CzcR?&u )QI4X Sm]ywbPxݭ4#!OwLagd:c#G1h {2vN ]y.\lԓ^! ҩ\V56Rם|TسZ}zS#e/awޮ 8V 4|j453:%{c.HAԢ`/^Qٗ/uƷ%{av9zy8OqFM(c; )9NX SvN.ķ%u iX4h  uLɠl?K%yA}4xJk}qͣ"k><ϋo؝4qȷ|5&goyކ%+5-8\|=L߱ӣ۷a&/~ 48dZO1ɣ`c{}=Ly.Qo/~~5TT.́o UݛFihp=2ػ)i]y.8_ao. y:H Փ|yVgٹmb6Mn/e;v1v t}/KSwsUc;8М,S鴛-x V]trMaj?s2ϥPcyc1c}f c߲);o.7]5JjjH%!gz8\vo6WViLu l[[w[vv筺LFd>O4Ȧ '̉o24׉Zc#*K4 }k,N×Y[vv筺БSZbrg\ҟ7B I6{-l$f$5$!lIĤ~v IWSktID77_Kb$,e'H|.^]G6M upvu?(D|Atd,ήe}.^r~g"'ReǍ`#-5{a7>e>߲;oEZ+KlE{g:2Vleyc%/M}OƂO^5o؝w endstream endobj 115 0 obj << /Type /XObject /Subtype /Image /Width 201 /Height 101 /ColorSpace 117 0 R /BitsPerComponent 8 /Length 16064 /Filter /FlateDecode >> stream x]UoiE?b;3&'azǑ@:`k72(1B1c!H ' /όRjTvߚ}g}NVzussZ{~zpOg~[_^p˚1wpޒ{]Ë|,/x2ߌ/.wX ovk S3sxr=k .6nUKOs'g{^~zpuM ,}b>z;7n:'ݼeMx'w nMVa-9C8κc?_ݿO\-t>?n nPhVp M]5' tq8c|' Gv@Ex\D>zwÉ̫͝[ht=kZh=k+K [ ]s/_~H3/ `\s$q53Xkܓ p}Lm3)f+_ ׌'}҇8`|qdA5)\9W$:HW {%\n%\U8ې^U)\?Iu88pW<V * d vrT"W%ZGgN:!NseW7w]sЮc>L\ ~ h8ނErG{z0ȟhlbtES\*W $CE?Gh&JtUG+PJ\`ƹQ Z EۓT%zhVWlnВu iT"Z%WB-wKKkK o $^]w^ t"$h?ߵ&ui唏bn94>!j|-$>vsE0|`%PsqR.CȘWҫM!߹"ZJSSd+qEڗj7X?HO2B]h~`<_h57½Na.^k<"9p`a/\2]ʍ% 1pAwGL&OhI|+:ϔ>G*\UXK;\*<RIBqLq5d=RCəS6X&:H?.q\Ēj0GgOM]ZЂMpׄ0 t2r8z"Hu`%<.kN[{kOd1ᘍ)'SHEV]UbEpݪM3SE8]\cXqx1~הM~4RJ 5O <&0$\'JG#+U<8Z8ZjԸ4@3Dr;1~-E8]p@dBk{E[Z.0tz` ;62sWu\wK-qEW\*< 6Q¥"n1>-x#¡jGCk/hQ^GC}r^\‖ ׁ$\p,~'%="E:ad!>v<[R"UZFR. D/xZxweEZ/bv qpxn Hr Y Э \ %W8M  —"Zt##jN،]Utq btsu, <ړf_q-D|Y^\\ L$k~] DA@z"cR,bU!Y?3  &F Bo!Ѐ|u> AN9>o,:`1>%WaJH_< >vs( ݨ"`=t-b?h+X0ʥ雙G/ݟ΍ B[ԸrUI $ \'I>xr<I"vp5R*`}Gk, % *!_8ѭr8;_3/) J h'hkuIR lz-#g^>>SS*2phChX? 7י=@ .'nx(xWBZ40v/@ibfh]ur <+xy95R#E⊳3.Ē.\*cDa 5LH8>Bpdp(\󰔣"%zpv 0K.}]Eo:~R%hcti W hCCW"ox` .Iv 'ݼ[<}ނ7|EIAdF79Z,P8d X F>ApGLCԝ+$ ?P-W-E(ͺvp2~𾜫cmwf ɣ3[Ez88g  NuƓ+@WnqBk \wprMs+~;]mk2.A7stL\8 @ ~JtZIpre q7&KC9=ewn唏_sf4g20PפnZ 2s4MܣH78S(1 :<ou e~SNb|Ct9Z; $\{g}\zʂ]lO~T]Wd Ejh5>nc,x~h(É]B-DN1UgpúW_6Pa5]rb徴|fD~Oq+<X1O=cﴆDxl"gKtM u( ţ3+ؔ.UUD~ G04\\4#.)08 ѧi2""]@ 6 3Zpq5 O9tL9hh_<2RXy6+7O!~GZRN˅-SpiXNlX9+vqEZTc+E<]qᗅ v`ړWÓoC+C)!SVh(\b`ծT ZI}Z֐hiV%9]tIʩct=IU.|0IJѢxĄvKytS8]T h]D E` սi= JPF\y(D}xD,qϓ."kQB%JDZ^R|n5j깈- ckQ#tF7 +_)XՓCe|Yqw"f-D5XuMէaB(TC0=%og`}IdLKEn+KRIS蒅ESr.]t=Z.E!ܙT2PNՓyJEŸ-G. тAT~% ^LG11\ͫ^ @xҪJjRBT,_.1FHJϣ03n&+,hKҏK.8a| @KyGmV]+ܰmhZFkQ8مC]hICH<CB:W!bYɅ`J6ѢAOLE>Mplb@+wHݪU99!,t"W 0E_cr1Qhׂ5<"R?IbYMph)\e)wO׾RN S(zWŔxp1-@Ejx=ˍ/㥡tO-h&J.j+^zʇLV.HQ=˙SŇ96Zy)c\UJ0~r PO|p&V{P༯*zk;>_ sM'=ECPv)Y;qᇆKb䊱,fp"7'k &DmbȢQVH -JE`9RQ?lE̽2 N UPXS6W5&w..^t1QJ h+b j,]kpR_ES#\.<2nD cc4.hɍ/=NiJ. 񎖧=(& < sERYe[ɘ{e4fi72GʜW9T+0NZ5~U g3hmhuWũahHdncDD k=S-Bڰgujj qy]hx) 0.G.aZc|11L&$.W?|ϊTR\VH]\zvx{FZAklF+-e ˨qڋo![!hzs%ڄ5mEJ CDRյ~(Y2T,3GN\ 9&$ՠ}T?QGtɥ]!z&}UBk=7|,[Ç->l1Z!1h\w&}](lK ;oڐ:B?fTk%3$UTNRSƤ`dqh#3%Ex' ==..ÖCDW>TLRy,E)4bbHkd?BZ!Y@1)];(3'-D},e-_!i)![և bad=}s,.zT;u=֪X*A X} ֩ghZjjuSfڜ]V@\͙Ŧ4jl Z)̙Yo;N ]O2&-lnrTS<ݳFi ZZ;`*WU_+4^A\ZyK杖\BlrB%/1+;ITPx(;-Lh1~gFUEkM;~zZQ ܧj!O>i*:nh+PӁ߾fkj96_ɍ+-{w6xo 9.\cZ8=x8s;dG֐e;tC(YU3ֵax `{ A;oj!/;ɜp'GB"ZUwgZ ;(Z&R:lO&&Ɂ徍֎vjݮ~==hybR4-OWޛђA\WBM \ W1_2jhs$A=U֔̔] u!>&]CxPǭeeWi!hiihb"M@Ku]຋K_^U:H# ^]m܁wҨ2_:f=h%D.*8%ZetGv[u#E'9pIy'zZxijڕ"Dt5^]yp}[2_Y1?x#pōRV "TXPR'jk4SBj-pyõx2=.ZTA4тfݞX]sZ@ \A ^ũdK,r8˪&Zzp nW@TTgnCR\J:涜${|ٰOinakP/q\jQ jֻ+xD s%ܸ/ٷW.Ւ0#߻+5%E~;ڻR^PbySg.zNr|[ȟ*Z*\e!lصӅfdR#wBRYZ!)\h+BxY9HօgoI&(S N H ؆'}E+7Ӯ@DzRV~ UnG>&hu WuZL,Ws7i(j߅uiwEn&? Ҵv nrjѶ9yﰉh]t֖,[[-KMK΍%t@mvsXW1֗*Wl !(F Չ h|yQm!˷ w(ѪVh=;ڝ[8q"^i__qŭ1IjfGsMZ2]wZp(sEQ;u$Vj~+D:W m"Vi=F_FXEW(jh+'v{pqᴡZ*dNhaxO|ؖcr4Cd>~q_uICkM^_{%|k P9`0E}q~{jn[ĕV*Yr^.>W+\pzY,]=^ZEPUCKCCY&m+( !ůgڢFpG8bf?%Όթ$K[^ӿ48gVXE.h/AXnpГ3AI[C|4N '[=pyz+}8(Y;7lOhIOA(5D/‗< lq>@ cg4^n Gesju8H2WK??!Wl'N#[- ˝ JNQ ׉dGƳA'\$ Ka9cx:s.;ڒ\Xh}58g+H1獻%T-i` N ܺuUE%ՒO }bӥ"VK *O|Xx8Á8,a)`|6ޝ:+pm/$Kh $&9R҂.#Ӭ F2C{VGKsvU-[TXa/qڶa(U֎p9]2U7d0>֖/ b8>g]5|{hdxܛ` YaA~Z9wLO'pp202sxv&'btuVmJdMTɕŵMYj_V U?#b\+jo1rW 2~)ݝ~2F-%Y( ;wO^u57 |B p<6* Ϩy_xz|$fn|-#G2=WJϪgF-T7X-&8J׫}|{XiZpqF^ܰT;gS‚C-Y韇0`"F<>iK9 q -U.|NwLa]H/l}[-(sΞHtzߞUimtǐIh}yq8O9Ę)4ގԎfk›Z4P9W ^5q[@DBDוC ׼q:AꂪG:h4OY}ʐSc V>+}&vC~paSv9CdgPp5=Kg߆w ۓp'pMłW-t2c! "ݭp)rD{bhdIvg,VCB/zO\vW>-&q ` YoX(KxZt~>rgr`jZDXR˯EVe8@kI/rЂWƒ*ߏ'u"\U{'Lx`D{_a?I2v.17D`6E~[7[!sw#)]p4=\1:ƹᄩ5DqbqVYFѕ0 uf#ӷ҆O<4)*cq5>NMkL &nZ7dất&rC{Lrם\->s E&b^nړӮD ݒ^/9ZBh1{Y8YsQ-** hɀV- wNcajK1& UL{(U|'yzH2[qi yz8R) ٧tgNQa \K5bh:QwjSj&WɹYyʢŦ PH;Ȋ{$ h !@#ގCᘀ.` *#h/Ƈ*^?e4(z:.彷CYZ7!4qԅxNJU `(L'X!F"Qq,ߠMe9뒶w=S͙EFk˖t5dѰl[2;`UC]x3` P C;>ʶ$8<#%blF c : ٤G(o1m;t-- 9D bAޅmDp_>i?aˆSޚ,K,b_ hY>ZxUǡMܖ|%6\r!>/BB1^IR:|6`t}|x|хx5:T#̔ZЎ.(|d%ivy>,Xl1m{o퓋V~/d gM )srg6tx4ޏ\u'Z2@KkEy=\|2١b?+:NO^4H"|#fZʙ’@EFܧ&0(,,ȕݒG7ECx|ok.¶2!\qyHfx%m"]_V!8v&'gAy!شݢM,c%]-xAET>Չnll4%lx#7Eя2Sh_8 q/n˔á&7Ls Б@ߚDcEwUCnrբ^q';Z&Fé߆:rM#'0ӻ,!VF*1 b h[JvҕZZHnٗIt+UpNҕΟY1ɯ҄Zt'Nw]YyVPl9]X5h8 Y 0(xY[lZx1x*ȁR+H .@&>ؗj.d-|%eV,v =rsB`ed5%z 4sE#f~&Jq0>Wͬz>c >ahOr 069;߲m &CC,q <`hpZtUnCv}R* d8>Ӈi8cl jn-<4M9^B?gҡ$F?XcmdM]d{S|ߎ?.⽪Zo&/:SuTKf]@6W|=9k0" DzV$bY,q\js5 hQ@);R@ .aNGx GYգZTᒕo68NREOljneNf3Waa,x )U{pk5aTDҴ)lQAʝA*sE T>hMԩIwhhRCki*W=ݞ $gx@?r -\p犒Q-55->NJ¶PrhSX}lh`s&)q4ٖ`S [pBIb|OF^կ:YA 5{T[U+9ٹ3Jn1"`tN;+VLA5#$볃B&`Yz/մGD2(-:Lnљ']kGIc܅/q6^l|' T;5PBh#ܐ1۔.P .[f8=,tGr>moL 9f=2\L%~kU*02,\N@<3q,p58̦-iӸ8Z]۳uZlQP~Z{}I-qX lj8.+_Q ޔezo%*kVa'ea5vfgLro^t}9 ᯉ`n_\UxBtaɤW[o\K_FƼA7  k$jS/L>>xwg}y9[!_8>/lVEdRl]JAػR$~8mœN[s9_cڮjGˁ |{el볹ܖ YDLz x}ah,;ۦUfA㽼nJ;Gi\) 5=v9jŠKjeH\ilᘰ2 [Ӳ_+q%kTߝ̔qo xtU܉}g;mqbU&W.X~2 opvy␰Nwd?A&AjR6Qk,P]Ԡ?m~;js6zE.| u9WtD&S3>qu ^IzCB$W&F=wk1P5BK}$ ȫ!3i2v]rr Hc /Vi!NΪ&]2]$A?(i,ƛ1@T#עj:OZ]^9imen^T<˵a9Xy&adj4n\8xɲ. fXRXX|*UNLmTH7^rno)h{s܉݆}*Ra#Dҍ|A@! {c{h]uZ@-#ߑ89"Zùj<􀒮 /+,K '>{DoVbuKP/^6MKUR& hn|PmGk2z?W#\ӴN'ySdV^]ڿ6 endstream endobj 116 0 obj << /Type /XObject /Subtype /Image /Width 1 /Height 1024 /ColorSpace 117 0 R /BitsPerComponent 8 /Length 723 /Filter /FlateDecode >> stream xugP$ioQ.K23/!g$!BIBhHC$DB2BeD"#U3|=zˏ[iK/lM7F1W=9Oi-}B>=z'V&75SJ+i^Es@³xSD,닥8=KXlEVX8`P9֘e#0}$a(Lc1i<&c'cQ1 1l: fal<y猾+z.DE|1S77\];:/ùq t3> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 125 0 obj << /Length 817 /Filter /FlateDecode >> stream xڥUKo@W-[ﮟPA%Dn q"ӂg^mShη3r>;ʋ@'J*̗AAa eCAAa֢7!wGxԽNt: b7+>w=9(. /0z21 =%^rF]cX[Ǔ215b?Sҭgº'VNxLM7QFB'\'Y8ٻL|hi( 4dKnH>|+Nn ~^ b<JvªT*UhIyTZg5dm Փֹl~JchTPP?W,R6{AZ![1{'v'/ns:o΃I^<< svhks+qw{'HQ JԺ#7d^)0 _{jJ3hHΞ,8o:p:> /ExtGState << >>/ColorSpace << /sRGB 130 0 R >>>> /Length 14665 /Filter /FlateDecode >> stream x}K6Irgim*U ix1: }ƖF`\"z2Kdddd뿿_?8Ïm=>JG׏_?|? eޟ(EЫ_LZ?Kz>嬟,9*^/as}sӁ(y]{~B=8Wrrs)x㷋n-_/8sQ6(>)^ľs=]Ja=>[wX17[, SWU3;Q7wVφ7]gxgiW_j)yEϻ'ڪ~P6Į=w٤4\z ;z~ՄJY[Y.}O_VcثB}uk)ͧYإlPxuK.}D>Tkg >,< mfa p-U4v٤4\ ԛ?FuϹҹP|c.S裫M8~`El>MN .fݒK/a_z *ܢY?_{DB@\oߣ#wYzѦj76[+ eiqz|V]onɥOǻ״@1K#jVg7goO:V1c띷58o؎Ai-"71#cy7Tnici0?Xoܴ{|9Ӝl[m}#(ϙM<9>#}]6)ϙWr%So7Qð`hiǁ1(QRo9#ƊB|Z& lP|Zuzs^<.'zghƚ*s? 0lRX֋ؗ--ХƠa't]_6F>LydbEl>-Ii-"7s=Zd?c:^}jָvi|x!syU1 3cP&Ф/^QMEqeFgaMl>-N(~ cz[my`#Z3cˤ.T 껰\J?)P6[g٠\z [eaeڻXsN`;Fc.)vgk5j4g-e OnɥO1ǬQ9f׎Sc|cӚ/NLњrrjZ=$fUj,6#0_5NP6gB5aFsM6z6ƚc1N~6?Fsla (\Es-3Fe,'<`ˬvnTӖ_&p̛ˈ-KԺia:Ϫ1ÜWY )Dk {B {n՗P6&gM+.fݖS/czk88"̓o1!⭵c@ XQG0Ϲvw٤r[N}1c5oʦ+hC.WhHUFh]'ƴeӇDȭ/Z&50Eq蒹/XkIݲlN'Eۡ2"M eiqУ1̹lPUҋKo,X'ؗcn6;|`ڱ.(|ӗub3~z||(രU-k6S:FA˗Bٞ..vג.fݖK/az/Uͣ6U]໋#ioz٢ q !c0V`1p٤4\z ۾鴄ST| DA/;K#N[3ؤP61Iᷨn˥o^hF׬t /'iuSXFύyuULs̬1Ƕ8em:0t Soci}zgٵb>~:~61Xz59ص:H){􅔏X'VTIBǒY(>Sà9 l~Z>JzS~ {/cˬ[r%So&`mƺ'.4YkĊ^9s*=Weo\z l<6MSwݴl0Uh<9'LSsuI0s.S︶\TXQ9'#lb1f9gݔ[/b_z{mRه~rcY8XPP\?L#/+ eiVK&ŧYKا3z{QOND[^ 0ŽSRuJbEWrM,ʺ)^ľIͺ%^ľo#f}YE{9+6b稦d)F;|t+ղ9Z[ueUTا/;C}e^4 +a_ thڗ c4 sv5}9Ob*117bDk]. srXO~ݦhM60O4Ɗm56Aq[r%SoKNċ(s"&1,]חw,IFh XS(O ؆}PruK.}M?į[pb/3v|^^cl5熪kY"1"Lb3r͙&rW٤Ou[.wGٱ'VWA -e`ylڱL Ypqzh)}A,XS3: nD 4lR,u[.}qf0a,ÅI[ᗀiR"L[6&9닞'p58=Z@!zaI^iI +eiqNr05]6)[QҔؗ;.%Fz͸Ss:z5e+f`GI(%8؝K,&,m,M"7elጾe1vccWaҌK|rP♉ܚPh2Œ_"OaM/Г:‹s`,;fİHq<]+cElGtmĶXf٠GݒK/azZ7=f9ᢊF=IrTvbMM1>٤ nʭ/5" _9V.aƄ{v@-XQ{9ewdݒK/az{^;t)5EzPNlPŲ9/sb6pw٤Ի\ ԛ1'1/pE!kM:Tb^~r*>ZtnRE~;L9Wv+,.NoTX:r\6)oFݖS/czi=~r\$-yh>W:;ޗ#2sЁKl]6)>ͺ-^>fX}5<|]1kӰ/lc:aМ[}qM;^`~Mql*jsecMuA@RbKY6/{-^>|bTsbt)MDҊͺ-^>qgabhK}bb0q8g8D X`wEk ŝ+eQ<`,cUcUKاޗnӾtmХ5KM{>s>x!ˉ8G%LS fڿ~hso,͹'j.nɭ)/Zigj)3RDL u124eS[f@<//9"u]I\ո.}^sl927L|X*ę_0icqxysC#bK'4KF,?'VTX6( w٤lFݖK/az;.!Šq  e=6%ǦjtجUS _}/ 2PZc$=?0R1s˹e+߰9a®v٤|li]ű<uEFM{ScV3VTI8''>aOZ*1reSoXؘ0f0&aEDq a hcϛ4&Qzқ~Y젆rc6ͽODT~u9c;bu9lv [ 5rյȑkjJF1&벛㲳nʭ/e?P{u\8X"÷i)7Fon +oIΠWEX,ߒuK.}ꭶ7:ts8EO!EKKc3.δb͙!SeӬmc^nر.t/cLh=/7ms^é]gi-2˶2v#,n]->-(m'̿- a+&-ޅi%ľWZxL9[ Fga0(rx}MYYsjL'(>ruz֛{}Ť֛֊bR>#)m#P$ǹĊeI, ]6(>%^>漄= I~CcN(0R;+;A*XwS;"5u9V29A†aM*bu˻["O”לK2^E:bƚBٶXײ&E\zқػ.F<t$%MIu ѱэM3P 9# L;r$ipI7f׾q<ۆ _~btTǑ)ĭ.=S1vVM{/4+~Tp|b}kޟ0.,gݒK/azǷsT巩ߦNӰVVs6<:Zj@w=4B*.{h @!(3$8_>>F q4ht4aՍγw԰͜7O*NߔjTJRXM< Dxe!1\% ͂ZgGvZ䴰܍e8ҮriJKoy>:,ɜ틺@ Ǽ*4oz[+eiq`{sGnnɭ)/]*L" xp `EM#wwV4|dq|EXS(O 7hYR)%Ki}6's8%Slh3|"anDT-@cY6)<%^¾G}p2"vk*k.Y8_3ǡXQ;SrZ8-Kpݒ[Sb_z\Y.#2gt~leDzj le٤XҔؗncB-FXSS͜6g]vK붜z ,Q*LzJ?f|ljO9s {V.\z {'s#m~=nl]78 g6i88eBnɥom\̤9蒃`ƑQ:ltMKXS.9G6IJ얱 ط^ 뗑Lf*VTsR ܵbn0bMe ሱl..en-"~;9 BHhtX趰vTZ6 s٤hÌ֔ؗޞ_{ g'p1ppKNdWrcElLⴰ=]=`.-5%䓙+379[x'rEDKVBMNxzXQ;7^rp؆.TzCgʭ)/m0CmcLt5_˼baSŸ)9XQ,OS9r̽lR[rkJKotF3+ho2nHMl卙~5u #N>3a˝Y6)zK/a_zmt(ޯ+M0Ռ57鈃3s޳Q#ʥ/[x1ޫ|JA9xnd[CNxmYy%T_mp$vKIEn˩/=>r/&1ƌ fb喫%1Y729TX]lR_@ZOdV܋AҌ0]ZuZvi% k*s/3N ~f٤8&nɥ/wߏν [/GBd&^cMe@mcr]e41Nj>^k$Iq$cDZQz{zL6E>E~OWD̏2W9N.{fm91l ɬgk [ )[Koc pH 0qPoBӔGql9|+eiqGrq٤dFݒ[Sb_zh˜HN;ta ;(t !ỵI69Ho,lR)X۾qtsښss7MBNowMbg7'_S;mr&BhMenɭ)/FObGąXGmX*+EnNMXS֜bT#˾2\z [eLid Ž9`eP~­liku_GlY6)ͺ%^¾=6$z8߹S= 4b:Vl-yLKJe7ƛ h-ľ3_''/ax^:qV@D+JesR \اn<ľ Co߸9X{2w%wկb+2R^IXSA)J16jb٢hàn˩/l3L a<@h@DÔۙr/ƚ:B:](6ؗKTe7$-q%nɥ/9NGL>9ն`3ɵ oY{3morJXl[w%+]Kؗ^*Gxm&ѣ5S9-Nz\+xsPrlR/[rEKoc3C+yr)"q㞦ha]V\-\XS<9816,."SRڶ^2Nogө}u$w"%:Є551*9țclEdM{(^ľ>ؓ Ζ>S_Xw?L#83*vn ؂C.d7MNj [oc9IXQ;{rJʮwwݒ[Sb_z۟|0ke߸9 "Nc?K;|y0my=6AF.Y6)0÷ܚj꩷i/+ש6T1*czcnn)WnJaE\6ҦPu[rkJK홋>9gf:KζX2gD8/yYaMe.zs*WW2&ŵXw r^5Wf[퇉v3_r&y%@aalR#uDȥ/b s.9гH.3򝒲k)l$HqclR\nɥ/~eg \k~r@nod-/fT' 3M.X6)ͺ%^¾Z3?|)d/2Mդwkz%yƚ;S"lõ?.[$z{ɹo6}ҙ?/͒wޜ$S 9ewٻwn˥OgNs͑e4V~eHb;&P3ܚqz>0|saQR%-I+j)FQ 5&žϺ%EݏspT_>x]f9Ϻq:ƭ5&$BbL:HP"F_{2+)LN15s:v`٤8n˩/m[}Arx~+;2Qzhn-Ěʻ:؎KQ]6)jOcu8_:!NH3^J~~aMmlo޿1- -cz]/ilɉL1 ۑe{ʥ/c}7Drt.#fcRp"LlRy7Drplq&e\7zӷ(mr7r:f$ o"9F}aM5 Y6)Z [r%Ky7Dru89X'&py?bk/šHSsx=)]6).fI΍7΅,)dGh1%gY6vTY'KUKؗ޶wV$ޚy|3_$3gbM f3Gy꾧EQ2/ʸu,jUF&V=stݒ_yS˜0NpgΉd)q_vSy()Jx 9V:IEKe M 7HN}5r猑w$g|%Ը"֍]W$_8oXSy'99 bia]`]KؗޞOsiL6'OVQ[_L,;*ԟ]6)Z /~]^;>8sn0zn*2uIuNe7Mvkl*̓{'Ty1q.$=_EwfO#'ĸlR.[rEKoYXHΝpuuFNq~<ė5rH+2%Il]-#s'9:w"|/yC~,9w$P˾+Y֋ؗގCǝ;F*ŝ2`[Kʭ)/FFv\paĹqIwd0>9Z)/Ϭwer'Vԕə8K*l]Y6)Hm4%}H3Zͱ?zޖ߇Ea.a/ou٤-5֔ؗ;7(=䁛am}OK)* v29x.ca%L-vr)^¾~{ݝ-o ̟<).HXSywRrllcY6/[ =֋ؗ-ěTnr⪅SYb%WX_!?O~%bIl>-N5^3p٢x˥ižqc>t{(3_.S Qw:%th}iP(hB4%Ft8]^x-<9S\]^qN&N-,EyorkJOKowdlr1gBO ^tYѵ#'k*`sp l}-eGDs8n 9pɹ쇉[0\%K4,`h6nWr]K*UK/`z?X]SABR{X7s*xKe$bM]Sɡ6q.[y=\zXthu2n&2Dv}8Wwu_Wnݍ564e{[Sb_z<$y+2 @ gO+n(=xkރ5J9+j߁'T<'%ľ{|q/о˜snFD↡ȦVGy!cE;(*acnɭ)/w;|Ɗ(ٯ"xCՖwdI1VV'6;&ŲYTاޞ oV3\ ~;6Nk/Ծ,9p]ᨥ>Si/6Tef];a0}?ƺ-^¾\99o}Yd /P)v.m8]h53XS=#s0zZa\6){nɥ/wA|9a[r&{w'nE XS=ú~>2zvrp~pޓaT>\E[Noz6V B[Iq}[Ҕؗ-{ܥ@;997ՄYDB>&9K~ㄱ)疱.f^oaOUxH>5&y wbMe6j9cVIlMN[oej$CfQ}X|K!/4T)CsN8WeR(}fwX/bz Z̽S߲TJR.jB*IWq#\&zۿZgq1FW>R-n y=I>hN؆. &zۿ2$1sN{D>R m/^q,90^=Ouۿp͍ξ7 f{oC^Vдˋyz-Nj [-{2Q[\p d=?L_xGNʷ_Q{kj~c?c? endstream endobj 132 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 121 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-017.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 133 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 134 0 R/F3 135 0 R>> /ExtGState << >>/ColorSpace << /sRGB 136 0 R >>>> /Length 29899 /Filter /FlateDecode >> stream x|.9%)jGL] z`xPNa/A~ׅRA?I~K"P$U~_|u]lUo ^ߥ֯~?+ nw<w~\?_Qޫp6~Wş?j?5~__ׯ? tU=ׯn_?'~?uׯQU.KO^^?$Oei Gbܿk5WJNKpe[1R`mo(w"Y'NJd4wJ(KpV%TxɨG*~‡VD?} 3q"P* ۸8TTuZ m;u?#Tx|wvw>9DXS~ĉ@)5q{ 4Tw*'>yd򻮗h'}}wK*=SvRS22WJ?ER=]Ph ǣF$PzÝGd\`{uzT)TwJg|/%&ӌ7~@ JLQB'5T,uJJm;tŻ9=>(!)P#:J]'d۸+zKAYԆSWxI#o|_$^߷F&}H8(?%cOQ҆SW$^&?]3eKoc:ՙo ʟ6+*:-6ZjUQ~~Wݏ'DJOxݍ{Y* uZ m;tݟnT}8,_y0 qN#K%AQTSWw=Tc]SYS'YbE5/SbU+`Yu^-t3y#sַJ}$і~elWBY[qfDuDer?Hr`EmG[sZ߶nɥޟqF-+-Ha?ڢ1&3s+0'D]1%V>f]%G٠IrEGo`x?s(Gfڔ#FuH=QTꕳTw=4cayG~FEoXGb($Fq-tͻMI!NJ4q;q߫qo"<:YڢDTwqlвT^uJJm;u5kywA[I?v!B)8x83_͸lR ۛR,ɽyGo ":RܪwζknϜ YdnʭՖQ^"9\=uQ]&r+ eT,[eUKSo`(?ދ9|/&&N=~ovߋ9|^\KS?na۷-%aEr*(}&ure쩷~`1D]-(wP> {1PzN$nOfݒK/b?z-ѰWs`0S')IJ(_3,w<e\z {Fm&.z q%5:Qr5u,e}lR-0ҋ؏{ZW}D06,RIČaXQS9֑W&u[N=v[Ztk-<wq<m:RݚǦO16Ư16sMen˥jK7qq49-CJGgB}q"6EW3T49WL3ƾ#Se¯U֋؏n l/29*k̕&냕(h$VT-SX;fٹ̺%^žz-+&n̦ 9DWYϮ6S|%W (eJe[=$ܚζ=<هRg[Q[m϶nE-޻-E>t-6mۖs嶐:"Nn-,ۖ{ml߶wRIN1mFZQװZNccM-EwIlm[mbSȈ%8_X@]X GEG7@\d$Si)#UӀnt g3ν ɻ1$XIIl%ND9܌+e½JRIuNK qV?ǩmb0?7+Rw# X1̷ퟲNIpR*ᭀIX9Ɓ%&8^:O Ɗ>hKNÁ%YvY[-ԛm'Y.7\}5XoWa$64a$GJ, Yv0nɥ_^`}?CE!=6/IAO cE5'3Fb ]QuK.={$5hlގ.jrؤZ.%,xͺ%^žzіIr`n8w{cUu٭,Ӗ^#,vYv$\z {꽿XLlʃ;BcB89|+*X6)QȯoSo8ӈ8]|`(O!->EcM]{2!]``6!,L*d-{N-|n)ϊ+KR!xpp1xZӰl#ZK#l2CN[iTi熖Rj#ܡķs0:\[}dLO*85-bHN.J3ꔔwU;SL. Gĩ>Rl _ٞ8WÉzNIqN]SO㵶2& 3lĚT>sorkq.`zlR5\z { Ps08!,;OnɥBNpr) 9=8 ~ܓ'kn aEWrz, ת,;nɛOU=v[p`i8g OiC䲱v[̑>-(h!KSoy߅Zi 36+aތb-}?8+MbR5RITi)ԛ #? O;LHX}tQ'p$X*'c pOJ'TOCW? yd\jG+wGBw5Z'd)8I\*:%6ĝZ}J_FDla2KRai)vy?^6p3; ‰nb`1K͑uJJm;uNɐ]+Y?Z"WZ#Cj'Y>디w5 XRx>҆SWy`Қ˺(;ֆ ;G)vΘW#RS2`.ZOQFCW]ec!22^a1 H=rGҡ8,oG`"}3K%!z}{ C3`@#9 )kHd8a*uNKp6,!_8n{`CME4 'r(&TRITi)1XFVolv=CسRZjÄQ}2iEpN#K%AQԆS׭~EeƃcUh V7K ‰edѳTV?B$6ĝ?:OQvp$v!cwst-y%^ YB4wױ g{Y{T/9Oe¯Uҋ؏?Gl^j ֕ݲmA^˲/ nɥ ]#ڀvɺU:h7}p杦VY_@)aE5[wSYeoM"O0+l*;9ӧ:/>xވ5@O*G3O;`lA]κ%^žzCg9LKG[P_4>)355&1Ceqݒz-LŠ'3f &Y 09vƊ)$,e_6eݒK/aO~_d8y)Jv)5ƚ*y\k\eMen˥߶-pζT1-թF-o+em7|g[C-KSaOݖ씏8| (]J}cElZv*º-~eoU^1yºx!\9^T~Wʟ9XS}cfce{-^žz-cʃ0g1oƆ=OLWW?&kq*77\ebUҫz-0"hf-QGyC)ߙ=7|nC6't-Mjv'eWȳnɥx4F=\nnقPw{y^<F̕2qyTGqEOyɣYa^}V#KyøVyn˥¼Nݖ O<3;J+!?+ 5^ɁgwbaͲ+<\z {G[cm wo9AVCn \UDu:r-m϶@m{qu{G8h)o{ TlbMe_;XOuK. !ətb#>#Be9ø5!ATGbegDHM"#:]m*(\UP_a2l[8LXQ-؆R.ͺ-^žz("{4M E-ǻ^`CqϜ ۪ \6)-=v[ZlAS'w9HD^Šɑ{ʲ3C-Jי( !c9T] !#wn Xjf;rEGo܉jɸDe@]1vK@]-LTK\w(uZNI qdNuH9n=3& 1#L)7fFsr#( ײNI qv'I.%5p X@Ҫ)\XS(DjKa]6)ͺ-^ƞzۙBA0aXDKr+*q)81 He uݖ+[Sov9 ^'93;J/ s; Kj>'frNbwܚRJ8Ɂ`jWA$JWHumtL W,;]nɥގ-{6<NNaBtcwqkxȧƉ5u\x|¾ӽ&_n˩^&c.-i0rH oXX*$0jqsxn˧cE^vnr00nJ.J̜N_=age3Pl-^~v[)}"p%]/T$oϫ-͖lK9ƺ6--hR[NletbQ. -0XrsuxG+]Unz+'kN%Nu..|R1Ƈg_YT~šj(j@E\@]WuSnXqsl̈́b|aj^~#2u{GVX=w}m9ƞ,GcqWM/@DZ~Ǫ1f:- l#n@uK.іv5[[̡U֔!婰Ymmm1ciMq)^~&/΄ZyԪIHQ;&Ų 3Kb,Y-Kz-<;n<׻:O-_ͳ9['͡QXYUaTݖW&{>ţŜ<1~2٘2boA7?k e[;Fv3I&z=R.]1W&A$g~>)8 +*`K,,;ʬ[r%쩷- WD>([[iZmH,:ƚދ%™1I6uKnm_愌K9{䤈3R,ȀqƊʳ2sCk fD ;"붜z{ ^"ahp3wC]Ob}"X6-)؁TMen˥rsr[EP_vn)_X$x?L?eŖB'>*f].~0HU#eA:n&eSr’b1+F;!og$+t$T[ȍL 7L(wG҇J҅sDb0ypLRw))!f94cYn֗Jg,9̠#3eZ_nɥjˣP&$: 1]PI 9+rs"LJlCMfݖ_^ {,N3Z'nhx;BpIQ+ 5Ųkq4mp-r٤ؖ þbM w931~M9b9<5~Ɂ@bymN[;޻-J~E^yd]mQ*v}sDŽٖ)nRC{(hζuo[l}xe82?Nt[vIVcwƩ؁C=u[.=ᄱ>"ue-f93+h8҇Xʲ϶n˥޶uM)s46XnF;<5Vg?xK(\TSo?@r )9kS꺴1rݖ꫷-Ga՘lovl9*SWBsTZwZoo'F v.%^žzTu;[RrX{DG"lf-uj΄}^3&jmK0^!s:67B.+!Hil9a+j |v'ͮ[r%쩷BgZysp$kPkRHy'CXSǍ 27ɲrEGo͕֛ZcAV+qsmrQccMu sTb \vz,\z {G[-K0&%׷/Z>[WÉQuȝ9#WuKn lO$eKdX؅`vQL>[NwmcMM[Gnd֏[r%쩷}& eghȰ~c7nq J*Po9+jT290Y,Uv;%tsc?z;D vg[̑>0A>)+-;ZAY `S[`z:9Ka3ľvT d6g.u_;:%6~ V_ɍ mf9+*hINeMbqGwdݒK/aOl<>5C`Z`oSoF]83lMt]3uK.=V[3)|o^2}` ,[Q/VcM(_3y6MfݖK/aOb{9a1yGwa$)kp,7kX@,,\z} wR֫m0VʽŤZDrn =t(?qm9l)?Snc/,U\Y?\-ݖ´خO8 Vsˑ 5\L!O&_n˥^2ErQ"2 l>sQBXS>&G/e_uK.兹_m#s+Ra3&{B}E:AJ{cIlZm0lR5\ {- wlֶx[gwnl-sZ-vݔ[/b?z-O =/ WǷ? ȖwmX~.{rEGoekt7s-. ݉vsn9kj|R6b/ucN%^~8Nn]tʖ'7ZNocM[r:`[NnYKSoQs(]Ǒĥ<»o]Ɂe"#PݒK/aOnL gNEv0=T0 f[h"VTpA7c ҿ\֔؏nKu#9ռS2'3DG HL81$Ye},{mS%kΞ2Up&ԅ0vn, KfbIl6u|NlR5\ {;]~N̝v.ĨTS> Wi LlR>-^~v[Ŝ8hWCnrx+e{fgv'E&ea-5%'kqrdϷOO3(Ǵ)GĊC0]L؁&_n˩~/0:| 9~/w {K,Cƒ:ދ9+-k?w}m4ߴEA:ٖ9ۂ'ٖLm\m6o[$ݖLm\ {q֮tAc `r<ĊjNWܛX}]*#p-{!;Ǒiʣ,nml> e 8H;lQ֖KSaO?mP%Qg[,g[us4v`ImI923&ǥrpMԸ=㦨cLN9\cM ;&)aTն꬛rEGf,a ]t~)XSm`X,ߢ\z {K/}V q0xreTس۱w=r%Go-%xpﮡ9/Ɛ72YtƊ*s3z؊(CM*G5֋؏>x{}X;:|ǽZkcMMY%gp lAewYeݒK/aOf+cQ?#(jw\I߾9v,߾\z {YyF5QrIԱK9[%Ų2^_&uR.M{@9ʦ[".ъz</W-Qr\rXR,ۻ^pplMfݒ[Sb?z{?p %N _0jL-Dqp+MEb]!uK.=v[i8ٖw=o[pbzg[g[>f[P-[r%쩷n3V0jG: Dw=7(NbU17켐%.[zmu|>72oq݃V1LQ; }jbX2v*=2Vm9"sc_%Hg6WqB} LJ)oUXSc_%[q!ˮ.M" ݮI*9wE~իZ +^#Ns+*x8؏N!=M| 7'8ѧqD_"^k+je90.Ũr%쩷ۂXO%ٜD4]&\J J%ٜbcm>ˮ%^žzoXE9cl'j 5$C(XS#&ց^˾mKuK.=v!¡t{Xbt3x+#*-GwbEÊ^ TTݒK/aO=M>̜`sq쮣oRpdYNFxذxIU9ȩf1U J0LGH^f<{)9h.eYKSݖLNѥRE1rfMo/1]3k-m>t~/ V`p=. P4&!/Q5ט6@p-Snɥœ /ln'\]XQ;9LFa,UuK.=bRřt4΁Qo $8K,K5 ;x'Tm4mm~K`/a|3u,#7@}98L y~j-ۂ3O[Q[WAx8=2Ѻs-Xuh϶n˩޻-p/>g[dX4і~'uݖ~ʲmw[s>N[&7 )[FaE29=&v,;Yշ{DbNn$y=|9Xn7B8XqIq%^~yMڅk =ڌNVOgf M)9 K6%m4IpTm^JD*Dq܋xkj$H$F,\z {4֝mGmA\eDΘO[VxH1{bV-[r%쩷 Y_,\l69X/Cȃ(W J9+j',Ȳ/eݔ[Qh3;5]Ĥ\YEqADXQwڔAe\6%^~{љaW3hJ]fxWötq^$+=mٴ +h8҇Xʲ϶r`OD|"N>X3YWmΐېv[̑>ZW}u[.?vИN;dS]ȓ^ ] N;tcy*v2i\N;%^žz-*?b*1|٤a}+XS; 9 {qU=n$Ypq٤ܖr%>Wј\묯ߦe}uKnG|/c^ڡk{i^Ɓ^{P|/r`O" a.xnIqQgؤ._&+,aY(Y0Gz Kv~sJtc:ؤc:O_5rCb,,+Y(bmdݖs^A"ؿݶ 4vG[-Ye`bE$'4BrBMopn˥޻-Wsytv„԰r[p$2VԽVKDy&Աk:u%oT7F==L4X~WZM5^!ܼM;/FoS^Ug˗=,nNf^C(o<ܘ~Ղ755rfNGV!c/C-\z {X9k}1p^C~c`'سz|AɲkaU zϲEӵKSo%]gGSW}8 hR<鈅&VTI>rflӳlQu&9J쩷bcsrD 0 ߦ`ZxQ>cq|bEetYr]ɲE[/b?z}&q-_-xK("Kmٖ8j l §-_Ԗ3J}wG`͹Ъ=1#pxAǔO r +j gd>Yvs]-{g;ϕ9U MyvB Ckj2Gye+\n3J[>FgJt:(3gqo9nk*,Kb;8rEGo熢d} =$+S-jbEm?%skd,\SrݺpGzSOO[ɶ\犹h˵}*mϕ>WKm9V[bKJ^+.xB}lTu\Rre,=\6[r%n`1+Ң^X4I>#8&b YKSOr>c3G)]h=սIN+ e_nʭ?FCj4 zףJL M>i=$%Ųkq ;#P.RA.M]HQ6)]|>QP{x:{FLi{1X>wߋ\z {ϯpa8#,ܟ)6&帧4zf^3raKrݒK/aOLJ؋_m }WICm9#%Ųkqnd,/FlR5ܚmh䌋Wǡq݊(| 3szz$g"a#.zȪE5%^;]Üg]y)1]:]:>]nɥ1`kM?ˍȻS)ևj'q|tFvF.ͺ-^ƞz-q*첑'i*rQe"+\1.]6)u[.=v|%O}9&>^~.Gy]n.H9X^n\z {^N1rv ah)&BdiM4uC0bƲO1֝riJGoƑ1}!97..Hhp%LUP_=)0Wkj z [Bj-"\ \(/P8=Xc׋Ě̹8bIi͵}}:8&μ|v"QgGQnULrEGoYp]#}ȉc;$e.!qD{,zXR,! w٤|u[.M=q/SM]17R"9l -Hb+>ڢ%m EMÐCTcu2X8-7+j$82VeXm4%82kXN: $=VAqgyMƚJ~h"N٬[rEGo۔pTn;9HwzV˔mםɭ(9}]Чd٢u+N,^~f[03N<9iv6ǁcg8kˑ=2N<9N,Ϻ%^žzk/v~^IL W7ht -_ ?+W9!fV٤km92mMOWt>,P_&Ēb87>a3eY֔؏jKal_i^3е d#7X'q3XQsj%\z {0.੶S,)j)kw-g.-F؂.⽶z{b`POt:B}/|XQyXr[ e%sݒ[/b?zk{x/=3~No,zx Rk~ rWAlRӑ ,yugWoo֖ɡ•8S<,˔)˙YXQזD^'.ͺg~+>p{~ ǑxKibB=rtݒ[/b?z-֍]$Gn&8] qrz+*m`lK޶ m92l[9׹Җ>m}{TԶ%:cisIMo=86i)MSg9."r[ǚwR<&5UÛ 4PlR9-^~V[*sbmer=4?[S{1EXߋܚm"qj8~ -彘v`qzr`EՙY҉iͺ%^~zlּ͜DyU[vMye ͋e{N"SY1Vz/Q=Wsk,a{{Mkƚ^$jte۪nI/b?z-`''[ʻ T`2MnONd".{'n˥YR-#}*cfkc4xR>Vі镇V-r%쩷ۢ}! ׀l^m[WXQֈpShlŷk~rEGߑ9rpѭsӎo,;9 eݮri*쩷ۂ0G193bu1<}z; šJ#LpG1\zmYw~roQ{D}t˖kyNO/E|~Y7֋؏^?.6Ukq0 _)zr+j9wzr&Ú.G}z1*P/cU} Iuԇ}̾ 0tw5}\ҋ؏^p4s$6)-qfcElZECbDm%ܚmpaSm!V<+tá3(++epa(5yDzIَ<[.M>a̡- ;KSiiLͯKߚ0Ȗ",*ène{#|%̪917>Cƶܸk*Œs)X{}.%^~8633X vPyƊ/<_qu[>{~sQߩHO ;&q:ɇsd-r}%Χze-73sXIǹx0M(rz+jb,^V{qݔ[>-ۢ!KL(@}"t6R-.ٖ϶g[b؏n R.V>xaa.0?[^gw:nͲ3E-ge-ܧNN&]-bo}]vxVT˓asJ>G܎쿮rRr`O?pTGÐ'I&߅xNR̛'b=aM햛ӱ5dٻ[r%{ip9=x%lDM٧Iߋ]9sxv٤ErEGodU#'GĹA#H ]a\t"bq٤KS^.n%GvՇV7c5՝69Ljle)^#uG[:&G[{m꧝V?ԧ-Z؏nCqϩ=jmiJiVqai]ꥶzіvE-68yXQ#Okv[<02z;.J^gptuV\3-N,g{1s-k{1-K_E59됇Ҟ#>)>E qFbEr #,/seaTw z0T99 !bX-ODyP-gTaM1#]s㺫Q~v[4]i30M[\[M9B+ʖnWbx{Mfݖ 쩷r?աEθqQE>>U{n`}FPb-I׬[rkJGo/\~+ۈXO)"yC1aMeSr Cyabʺ)^~V[W0ч}JOt+nOXQW+_}*n˥^sƾ5sf[go>3-߹v[rf,c\}sݖKSaOݖC_]sgB|>zĚ>[aU^Tҋ؏-^{ɶd[-c~/ٖ|/k.|/jT' ^y3٫+fOJ?},Lv^{-žz-37{vo{?qs<֍5pn,.{]ҋ؏ΫY->$Ɂsgztt=|?|XQ5bØXlR5\z {`\,+99*=I>+o9+ eP'lyeQwʥjKAI}u sXعFI[Q^~Z!O2wa.E7wIתrEGoj;iYMb,/_b&la*TK؏޶6O?'g^o^YxJ%q)G2{cM {&[} ʮPuSn>ƧAkU 0(HtGJbMuL+-q*dAM"u/pZOGDiz/5-7/޷8~",m4<`F]9\D8| EXQ+sAnlÏ&w۹OOcO*0py(Q¨][޸!V^$cFq{ %~v[עc{DU|!W{/SksgRMe0ˏ3G-{ؑ#'a"FE|q9I帹.qΣe{fXسmmY\ V\%)03rйR^&TUr 2$ Lwny-"#6'GLř|vSJln9~?9uKe_ϺJ/b?z{=wB^ts~34\-_+ e78%UB.r[r%mAퟶLUU}+gr#tl٧-yE((erݒoz/bѵ9"ab"YKShK_0Qw/KD?paM+TSm1pY&>Fk`"t`Ƅh$ag, k+2 B\ ƍ3ERN<@F ^JNJ)zb2x45i9n&E?!L|f<|o'(%/$0i3\<%'rJp4z;< ӑC3j`Fژy3f$)?h ;I?ַ4SBpvÇ#`Up B.i`ٖI/d!BR1qI!;"nd $'+T8A*w^'"OYn= GIaQ7p .4 @O#Z]xy㕽$GaKĻь֞PZ%"[3y6<Yn O@d{G5hcѬґWMrxΞ)06 %6(&踛#H1!~v?CC0YTK@M b5rRËǜWO/`-2&O@'d/ƀ{@q[yy[?輽&y{ 'zc^nhhcX Io:ڀ 5IFp#~? L=]G{<ӿ+#ܗ"P4&x;|B9>`1":x5iC`FlQax3fgc"$E,9#W d#xh|8oo ~}qD<֊qI hz,=VX,?Ž:"p s"ŗPh\n/g4WdmM\eL\Mx]$s5^m4ZEwzW^\fal-˦8zuʌgmg+y8&TJ A?(#QMukx,dK.fB_\2S ~c WA `xܗ70%pI{}L\ bN~ ab[Օ`A߂i?:v~ec2BFs I_~?tc}?1vt!la+wL+;: Hmr|x~GAtd=Ge6&kMӧ041'~:R`1aF#t7樆gpGS`y{4o41D/kChԃIcy?(q,q!Ӄq$410CLzb.y۸9F"S;wôL]lACWk5[pr1oITWTxD#, f\]ilb Uxhl #vb#In{Ego>u ;/mI:<< &?ps$ ՝'z$HaY8gǀ0=PN[DrMB(88nN]9nElbrϵ m5f'psNL oc^VS(0%M vh`LNoԍ;Z2[H7ӞwWH)iQ_DvSib* ~b m0M;n5ѻcbYlĝp-N.7"^ ϙ ש$M 7 ^ϋ/M¹;դ}l|?j%g؃g, & ( N˄W/*a7Fs{|5K17xSѾx6} L߇L!2g'M'v! I(+IV6m MCFM[!?tQ˺9ǭpʜk0Eo [o<|1L4u C:[b#t~`xN<=?4F,~$^:͈X,>:iZhOMrq"inzeSLԳ'D=i[wU9&FI 2i t{hq  છnV ?wF!:ܔDbcsT$uڊ&^f|?X1Lj#MXCh~s +t&64B?Ia{`=4Y։aCrF;,s< 0!CʛƫOu1`/|}14<'ڛ%"#9Ƿ{o7},E8Kz9 rq \]˅?HÓC1XN>qA)?kjE'ib`EF(q2 ϫ'0|N\OZ~;iz!)~Ǻ*|]*[n`JeT ]{(cox% z ϛAj<:qK)ްvQL#K零ipo s{-g4uk܌L?gp3r`O7ٞ,> -i:;m󬹮 }k*uU\>7\ 41y.)nbq!֚}\G![ ']~B죙NזK -^[8/##L|sq;{cu{5/{yabibxK-CjGge /`Ð > d7װz>q%Hλ*װ'>ehxiN"++E'&u&u-0ҳ_Ke~<뢛X\Tq_R&sc}18(:08:0yPwȀwz`wzٙe7p"g1|s|s71l2QZm%L7M TcL~3=EQ5K5b2Ƶq`Jߴ]Un/fӺg]%h#ĔsʘUuUMOM CkѾɤc8Dz"Eg? 6 3DmLub2~s%o0/.&Ou{jcJO{oJҶvJF6<~UO+{z cfM)nʠCܠliֵ7xl8z崡,&ɻ7}zLmX=۵ibhĖ,K@25:t fxg~/ LÃ/ƃL_Ik#NuWH u: bᩃ}}FLJ?S6M /eC ].&6$bLJ' |'H<9Z c\A=ojUܷԗn;84)nw:hipYx+.M5ݭwEj<4l\cc`(h~N<[ \'GCDz2&oסRҕ[m:^$m OSœkRow&P8{ I 29: ԐnIӆy--v.ibʷpo 18:0`c9boM{Xp\G!B:_yZ y;~sGã\1z:pc1_Ʒ+63دz|t~41 vp}A*`4ȄSK]ymvvhl4Fa+lˠq#t}8QSs=fksaM{ib&#[o:DD7m^ܱ41KN#.IrΧ2Λ4޼W9S,xu_ bt%n7뻿ɱLy}ӱˤcYwFv`[ʬXuCx]e>u"ݑ}'b' NAVҜ;^DIsndq:~뢭sh{xŸ,IӶż3qų=mZ%gd=GߜmOlk7wڞܞ%GlK=A7wRw>_Y\X1g.XzL2?6&g\$q{L/m.h[Ϧ=^8.4^Ǟ#ҥD'iәxo:.gI::9G_f ߔ\>LƳN:)Tkū.ֱ;/Ժ*Gzi=s1~w^pFrg=4ڗ8Gvh3;I{nt`seby&$6yo;w9<ê9k8{.!4'Mxm5ضF1cK5fX'-z$з#1M̭o(֚tE407LΩ{t-&;L11"umKgD:4Kc5>EKc#Z/b"R={s cCiMs_̘99gtN Q!InGHQᄍq,Z9~㽘b D^sr ycVgTIS5|n\b}ʦNw9tqV{ݐyz1$v0#'+[ٵZ|-ߤ֎ט?X1ǀ1XUݔ.6 CQdُy9,c,=n\܃91 z1 MzQml^d_ j'ٝ5{oz.SEC[S o߇W8.L-<2=|sQnq{9q rNTt$}u :U)=P1Ŵl1WXD -o;wW6C)0Sz$<3ѳ/'ѩ2%EpD a# QGV}Oٗ2 0Uɱ(agD?яxH]Mj/ -LxO"u mX-򾋶ﱤ=k,ٱ?D/U#xʎD#S_Z/-\cǥL/2=zuR̒iclrC EZ$@$Oa+Cw溰~Er ᥸o[%qrc\wlykBxL&AZ' k~H\Sa˽o[gq>*ժ̺h7 EWm]q##V]a O~F0ÏߕkxlxZ3=XQtgVY+]Sr*b԰Z,Ţ+~:96{LR6Pp erd;drf ; *CSUlԁ[SRdZ5:>owiGnwLtOݡ E ``2]śVa;;se4ݔ\tYe%V ;X 5gb<(X-Tlq&=W"sab+tŒ ҵ 6]lGql00="I\+ oriяOgf0l9p&aV%;sVtT9E5+"(,j 0,:_RfXqgo5`51kOO |St\s\~tgJDTRp-()nqu_;8sE-u]Tr %%6twrIYDRAC;y%UC%n(0J^ #mS Nɠ~@d+EĎ'UIR-B[20?h!ˠ_<ahe'{jP>_ЏǬѭNSPשoȃ]cp`A=cQ77/L'|$ɨcp040UP˘ǹOr]dIq] 4@'$UK5Y+/l&8)z"oɕ0n(Wl(RfX Er0> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 143 0 obj << /Length 666 /Filter /FlateDecode >> stream xڥTn@+PW 1300DjQUwiplŀkp} ;ԪB3 ǹ3ڋўMUǞVye35SIO$b$?m;<,b6M3OG*r-\%ޢ@63S)AA$1h&'0\jaA1ڣJ +{[ףr0MaB MKkG8e1H(=~~;B=iѳIUKvX5c`_W#6|+I+t2z*'+>cF u, 70NAP`ފ{Nz f+!lDǡkRcaٰ_띜E T91Xװj>jQM8՘}Z&,26WMN\^Gm(%! ,6XeX|CF{XbÃR]x;&YNdV|K?Ao] u7vO"1P3vlm8˜Ƒ0vtV8&25]eq$"q9^,-a"1r/Jo c-N/rHZ9r>)&vhE*8'Up#w endstream endobj 122 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-019.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 144 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 145 0 R/F3 146 0 R>> /ExtGState << >>/ColorSpace << /sRGB 147 0 R >>>> /Length 40065 /Filter /FlateDecode >> stream x|n?OFutm$ $@RHp'+e$  OI1(i#puHCDQ_o/o~)_ۿrM;_-sϯ?woB?*׿??f? j!Z?ӯSyǝ~_?-jV~m{LYdmw_Ϳ{_Sn3~Qw[5Qw_ߩ>XR޶9*~yv ;)^z=K^ߣ珷"N+{Qw~!ȿ>k`Im59> akφmfߒSS`,|6w~ɟR?jUv.GhG'(oMBj`?]1A_oɩx|Ժ~"ΧK]VY*({Bt~mBri 7>BQTwjV%Rhpj5ıe1;۾ z譱̠D*>EJ33iG`?S%A>%^zs}n87o?ӧWnBU^ &lur>K@A۠6z2;}Y'?{b BlnghF%p^qK`yh,-95ћϲ (?ߘ8ힽe0Mn̓.u7%T|c-nmP78ҫpƼ7f?cpu &Ƨ֢ȹ |u_G"pmP"ѷЋGovk8i%}s\MoqJjZ?(&ۓ [jvn[rjWo16=m=0fX:o:Iw(oQ-t)Qz}esK۶i\+ř>C-o=1I~9#XQΩӶS7 Goߦs/&N6g,)ϡ'’@;aamrE쭷\EKAN> +>7#aٮCyv]1fh}S.c{i Ϣ?7yۖ#{ (oMvbm+6([Eoٖ=VS|3So(}i 9?bIeyı׳kmYo9@̼vIa{=s4Kٹ8޻u_&')eD۠r죷U`;ѧmvl0vV'8`E&0b4 >\z}dmfؼZ1Z-{,IB,=жv mB[rjjzqҳco[ϚM{vc g-XR׳F' moɩ)ukCq?F[ۓ/X. zj;^SbEyvzk}6} 86ƪ[O [-WpG5ж~Aɪ^ȩ)#Wmt􍑃5:/M)k7,g 6Ai_Goa[{]"?arʚXm~i`,|C9xU۠ᳺ}_osqv?Y Q߬Dz,^3J5h_8wjGcO{b =lovyʢ_-ja8`ݝmg7ԋ[o`^oKr7}8ϡB^TRXQ޶v|O9`ߔK/`6܋\f2h_Wk XH^J<8> K],r죷?{ эw=y?7ǖ#'س\oBmgQߒSǚ/e~s'4j.j/|&|NXR+vWM`zyMyh[oaw ^NQS\knmW`>Ϣ)>z=nδnmb^5U_ZCx.lPb'E짫6(F[rWc'z/Nѹuzecgڠ03u{!)%ONOrNAɟ/9tEq1&<Sf&߃K_3Dld J-yzoY˓d?00N٪[,e8 wױf&j<:[~voZk3_vK_3e Jg> >zkO~R}ӨςB6F, ks3E'~-bI%͕BW}E}SN־ʶ=Jpi Z}BazDXS;жvi~ C75%+gQ7L/% WDf Bǒ: 6Rv-z{ͱ?Թ86C|;φxI="_;6' ~SgmPri 죷/ dqtޏ}ܠ?aI5y:S963lM.|ޜ k3,-a,w}rj 죷 ?!Pi]뼭,+䌠$eǿ bMW;Dۤn]ԱI='l:!J7|%HqR*} "utXjKGcØKrl4sw gU% vFvB5`Ey:EKňM>Pv8 [Ιǂ3aR3Z|8ϚXpd.jN.G/`\Pҟd,Xwhd6FXQ&gs"zA)v`#^>z;#9$1kS'qcߗa磚 "ԕm_¾%>zkr?7s5VlJn5|I*O۠GߒC/bu!oۘo=s ?)>{Ɠ+*ƾ8>~;DZf5.ovX)^>zk}򍋳,v>/{ysQd'ϸS[VV֊ᜆO`jvַԔ[ gAYġ>-?L׆,f>zw=wc@$sJgweDx#8WV`M6mPXߒC/bs3,>qƘ/HMCG{j%*nbW܂`p֝'Mp}_r6?7ӭNcyHaL7b%_NAd6?5êVߔw}q>+;ƍ޲yN v Q[]((XRh[' -O~wmצKS`n- 9 A <5jP:#XQ޶N F@+;? \zUe''A_9˿,kP\(ز[KzQ椼mEL3\ c۠C=ԋ[ocبAepphp$ýy3[cK@ JM9"[6 CgOo#)2N~IiOJȿ/Τ eDm8WߔS/b5MΩ}ep;<?DO@9zow)j9u+"[8Qߔ~mGP?5 #6qG,Z 9Ċ0k}KN}ֺ? 3pci/+xʹ+J p_v.r}_ދ8r q^-i+{ "g%bvq(z䈴ږ{#~IAmM4*T$Jkpª,=b{cv}7ŠqkH擊(*XߔS/ber[9"–N4b1'5Q3hR>1O mibO"6r#OJ [sWt֙DXNp;Q݈ 9WcbA?M}5~ƶAi綎\u?OR` b4R`q/=_8Џ; -z{{gW8S ;΁Ҏ5Y+G80j)^z?w?7Q!@Lq\z 1agQNiN)^z #֣3Ԟy`b26(osH[?bVUUsҸgYpIGFbIm ;ELr]{ǶA7Go >ƂD-k ps,_ K*rsRߔS/boOegZ* yKse1Y|R.5Tg#yXU#>Y&GUE-oʥ'wG;S}VO|~8\!+*i*9K~s. m7=]JڋyJRZDw`q7TD#o%VTXkr΅fF۠CߔS/b]QYS(oQ^6?JK ĊgӇGb۠7ZGN}~n_1nl&,#GfHAP!ViCߒS/`{E?g oQ633B^#ږ9mkN۠v8):x>۪SY><%mἢ$`+r>z9c_e[VGC]ZDq"*v[r5~K`-jF۠"9"[6?"\99lS"?\TJ`I]ߘ8N`;6()>zi?cҶX_-l>)JC>D]c_B|F w95' t ⧫ߞHv]"9{['wE$"yh}Kޔ~԰:;~n5&c1TʑO5b NٱI[ao;M9Oρ}92ya9 LZyc?'҈LP13ɹmD6(5'ʸw}/L1ͼ ,`.c xX |XQUvq疰͝3j J[؄ݝ{9Yyg/_v GJ]4nACߔS/bb{ @" mF %lGIbEՓƤ6AGS/b(Y3k-b"AQFrgL؆υmf#/r2M4OKzU*] .WXPh[~ˁT=TƶAI:rj:#[ؠWs8,TV-no\Z֣ȸvm3bGA1T" vx=ҩN!0N=rG}ޏxTxV3ҧbV8rD K*E{a^7ԋGoٖ֩gNWn5%FXOIȑRXR휠<6\`۠6{-{ x {U8Q`b* 6P>~YuƋ8/v(M9t y8&B}G#$IVE]s8j"!mnupT-___Uww2tU 8/,:9b*@$߲T? E۠oʥo 'vЊ#6 V)ND-*9vmRܖhv99[{P \hI_,,O8[7V ƮW%8te۠S/2+z{x qtX%e(&)viKrS+*ݷ*gjENRXߒC/b= R|0 r"^z9Q|²VT:>BW}E}SNj>z8TqbaAk ,%gR鮶aIXn6(rEZy"ŽW]M_Uԋ(엦kp#?V`EȼFj{gaߔS/b?ͮj}clw"?8 6~V6((ri 747^y᷻qb[ -s=#VTJTzv=z{}l١'fK=c^_ľ=6,_r*n[¶E@ZoʥiUٯ순*l]]vB1GPX <:F>5xv2/z<o9+F-(^WѴwT UO?9 l2%Noʫ(*L"89ٹ`?~)(TcEUOԡ8HOla.W.gq\Bʟ7B\;ΔgΫ/B-|A-2 GggB5zUFq 7Ē'G9(/Jk:m_opB|uGsϯS8R8HO3Λ<JNXS۠r{)o@!MPJp@DZMbImY< 6la[xӾqt^Nb)MTrXRxA蕰p5~7ԋ[o.^ȱ/ϼ +A4(I,뽈u}IW JcKS`w#Ev|C,dVmG,,^Rg3TqZ{g{9ĒBkrP {6(<9\- ʌT.>7ԢN"/W2ĒB؋PX3w J1B.MCͻk{'o.0GV #7QcHpbIm594` \]l6[rjZjuxZ4O lCkgrqVT d*ez JV;]UQ-z%8(a%j`]W0}+*%8fpdzeyڋv.y {Q}+M#`ߋroʥWV!m*GǃeUvٯ +*dXXfLWlʔz-KQ4_1)5P8fr ++9y{r#^zkW+əH7jLDzϏإ,)0bl&S Da =(+ +*EsflϢ%^>zkphq"D{0JS5xv]qcd,6!:7+g^U( *'ݱ)\G’:E.`|'Q2]/zw!\˲*!Mo?Z5)+rR۠nZr{v/z/Lx-)v7tN)YaEՓ+kf跥ga5#D\z}|㉮'NÖX%fŏKXRYQ$/"6(5z}%LYis_8)35ؠ\*4k}q޲Dzf®\d|QF"OreaM~53|}E}KNM~Z>Xq6΂q6rv KjŮWM"6Rm_oʥZ_7 `CڈK<Ϣ#-v߸GmER8M~~9eߒS/bo-Y8fTC8e >$_O m85 b۠;%h2u-?LxSI|>gxW#TPkbQ[sr2oZ` UO󃂟t`6|-:%8PMŎAae4[v2ܥiDq*Ȩ龥/Lp奶qN؄WlĐ}rl};K{w%ܰ/kf׎Aizȥ)o͔u?=Sݒ﫱c5& zYz?xygI!G賰6O((v ZASPl۟2Dlv}}T$i֕iĒBTVbS۠7Go剗8ЮÍz||nգ8n[zs TXkpg٥v+iv?E7=} GP +)",8^CXp6(.MћRX<8lDղ,Q_C[ÈVyq|YA_oK747ee m{ۮ[S͒ӓ_#6&?8H6(-9r7Nqc_O QfeE?WbJ'g|ۖKmB[r%7K&~noٓ ږ'fh3k yX#UctS&WmP[rE7KA-4{? t{Ay-xofYqsšQmP[rj 7@.9aoї۹հR| VTѝDq ka)}SN}泤5UCG*{pԑ%(_H?J,(&agQ۠ri 죷lcWEpUְ6j %vD۠oʥ)|/S_"vzs[p3mSű02n4kMQQa[ x6()>z7&NڊNݑ)]L<'7w kWGF 6?\gI^P.8+"/ZwfM^ B`ImY|~v6()>zڞmqO;ֺ6/=/7"M9{ }KN}=Y{?7g>!uֳfBIT"eŎMR۠0з Go Оg?ebˎ/[w$~Ŏ *%8Hag_R۠cID^}x3OKxp|'V e[G5Ċ򍋓<NXԉVۧz;tg }|s/<8Yt͛Aų|6e۠E"ԋGo>~?rѾ`Y(V'K!ˋmPh}KNM?e͖j=c;Ygf2V! _%# {Aa)>zYjSH5sDgۢ*Rs5EfK=ӎ|VTaT۠Voʥ޴&2(燉)|)VTxb1bYm_Uٷ Go_2ss:|N &(H2U}^N`=䨨mR:˱#/6q'Iv{ 3.}WNjT ]cYm_'ռ79[~׈cup<&\gOiC &/R>b*ʊ$8 ζ[r%죷l"3%[@BݼI6x/>FkG67+wYoɡbyx鉖twJܳliѣ|_XQgeeh}]gߒC/a僝I1"Mm+Ǧ~ٞ )^%7&%+nP}Yh\Q$ǟl\;M|zqbA]lphaU{}K.M}m*v*G79=3m*xK>r~ fki/lw[ri 죷^ypks\W Cl;rlpe-r}*gߒKS`, s7F/{;e9H/T1BKƂӰ#A u\mγoɥ)ǧ_*ΑlmYֆNXnNԍΒ{aYaE](r[<=}S.}?9 1pp.^Lm:S/biHSY:*0{=у¼ڒǼiXQgf"ǎv`-BAzS/b~|%[3Y<շ\X![="YUX־dWmL-9"[`IT?0E}gycy,G؇׈4U &6(_зЋGoP|xg N'*n/3E{>%rnxvyh Vʅz-2\R}1q,1g9dbhM$:_Ixo `Ik_M[E}s}*oɩ)޲a` El&O ߥSc>#`%&_N,)&;aȪmP;Go_Pzr'uՎ< oJĒEЕm_¾)nl9fkp8bώYXQ1E-]}oɩ]l90B`_ib=rM20ĊhRXVۧbGzX[z[{1q4WcPa}cu+6y+X%3lv嫶A{}eQeggx8VvYȑNXQQ}\\aQ_UmrE{!gW|79V0qȻ7,뽈EH}Ioʥ)޲-`~Ec#7OhNHyF3bIg N9UmgQߒSSboҞKY~Dm۲^΢Xp%OaAmSC%h}S.M}m4;lٖ| W0vfuխ61k,)-k9v76(Y >QNM^,afgXlZҵ7=Pޑ!XRY ]y-95%!Ep<-󸝁|atQXybIw 8@;17ҋޫ[or-L[ 3GwO۬Ʊ٫} 6xrq5>ܙ쫷 |T8|9ᯛ37ȪxTrdvvn/`xgp^Ա[Vш[Ǹ.oQŠ|:~Y?Ď mҎאKPwzs*8ˋŕs~<{r?!H@B,)&Ͷ[Ԇ}>qJ3Fe8h?2t'8;`Q{Zm*rOxsNG8.QȽbXrr*qsBH֌OUx-9"[ 턟3lm1n`ť?V sP^pØXQ*êEm}*voK/zxE2V]3=[Iw@_'zSupz߸Ӯ:xEOp* aQ>QXQλ8%Ք6(ƽ2+=^Lw z(|HKvW#7FNK3azrE{?rB/b-m&)y'=XQE9!)^>zkP3oG 9SZW[[jT~VA.xg&r}'v_$6(Xori 죷JxNM@>T .Qe)ArXRQSr^Y-ڮqF}Se'k8ë Uށ$%wI$ԙ㳏O=q-95[~~Z{>Oc~zP|! "8} XWUۧz譱)bpp4`Y \IRۊUUa؂Sg]"F}SUױ|3zk C!Ǫ#R/!⛞GYXPh[90A)&[;{}5n{T ߁G~’ *(6mPj)>v!NTq_V5VĀ (XY++XRbp/Emڨoɩ)޺/6Djq|79ڛ+R융9f {bAi5K,ySK}S.M}>g^4Ƌ8h` jӔ#:%8~2,l+jd-yTck Fm($8k vn?X2Q5NjLmr9kS'n(IhGmgu{*jV/Azcؑ^>zYā>m1]{J,K,@b+۾}S.}>g1ɺ 6{plVG'T,t,,plSX[z0^6#gbvfaU:֐`EE}dqPYXUۧڥz31^2&k /5ۅcDH;ٕ^LXQQSXE=W}꽪oʩ޲*rԹ|˺'jͨLeUPcx Td š#F۠6z{}|JnGDMxGv"ڻ컰skHB y騣 )eE2W v2z-{l|}xO+JzUDa= ; #XQgG-Nm\F O)^>zS9څ@X;))ز!3>N}(,jSUQ}KNM}7$'/c]0fWʈ#ÙvpUmgQߒS/boG(!S ;Syc+pHbEE-l$FeߔK/`Ͼ#Wbec1 I;ChO5+hG- / JJt9"[~'85E 89:5U[ K@ ŠJ'&8Jkev JgַЋGouQ[08'ϭ;OQ]MqRTF)bovrEw<$%yPcV[!>B}wĒBkrr-e܂E۠3XC.M}֙bNZq#, Gaf[79oKꚙAUKO -95[u1qhL NaE7XkT^/*^>z+{NldBM93(B9+jl>"Gmy;kz-&y/x$;,X,I~qJH5+yTŠ:E\"Κ>uԷ GoO 9K N qrc_r$VTT :kjaSߒS/bofs8 Į6+9\HRUQհ{Nj kR o}S.}~{ OC_62E=({|kqx/Ik6(E6x ȥ޲-=7yDΊ3B^<OXQ%|`%ҟ[w_yj!͙y}ydغȘ*I7d}X^a۠*?Wt'׍WXll7ݢqYIXQQWTvYzj{UߔS/bUUPNqn7gY3k6e]+f K*jxdcvXM9"&.j]K)agyjPڿx5[q4āCl"j/6hri :8^|,,R6)˃zu꾉B~v<^䫶%^>zo朌^U[+(gU )o*XRvx&*BW}E}K>q}5jZ\plfv"LQ߅XRgpbPۧ\-;9<6U͋ >`3vҎwtU$ GjTWRߒC/aokuϢ矨33}&mPTz{jSߔK/`P.jYUyz?f ڗkűXRۧz}eM%88C]Sv/}{ve|"XQ^IȆIl}%+R}>9UXEKyHQC5*2UoRȹ 'ԩZ&AJ@ߒ7U2OU'Q:Q]v~4Nx)aɸhl~M4[~VO%84\eODt yUa+*q<7ԋGsgp|saIjxzXXv]փ wAE-Nq"elBNmM9[q?7%$ԯeOJ͛GĊ:q+XgE6)X<޷ҫ(_=i/qK*5ĩq5Q_Fm*K N7 KXԏPۧ\gnjjE(CVCh_ceTyK ORw")v K],rE7y=vqkj}eo˄u?8d k܈A_oɩVKCmZť%G|7O,)ުmcj<\R 9-%y]o ,B/`,뽐ݘ2A_oʩ|/=nehkvOF+\"~{Y䗕6(ॆzgY UPγ}[PuTO:ϲ}CIJ #AųC}lzM9"ћX^U'18&VycEȲJFq_EUI'yaS۠bG}<6Sxޫ8(X2VBYXR';yp=ʶ챌\g0BO~~q4̼ٛ1 j/R:]KzsdV)Jf#2͜x̚QĊJ NE22۾-oɩ|/m]ExBјS(|55Y%_I 7NIXτ[6)|I 9[keS^j '(ʲOs"??(~ .>Fr|da-7jfpDQ}{Y 9/]alOzU6coެE`EBe)CX@fWe-9"[k%Ox'ޥQl _ TqA)AitrȖ5۳kƳT/0'|9{_TPEZ}r۪oɡ|+M{1r1y%c*b(zWz`Im59 )`Y ljM4[]y~^!/=0Kda!{&`bJ3Ўo6(t.^zs0;nOeSgx %uFsp \aqBm|)>zNB9k3Za[`6^G}"VL?2#hf=Ϻ9"[ dYYY0NJ ވ>33H:6,KTYJE;}rܩoʩgҝ{08arҊp\z/|'Ē܃ V&,rj}Kx0նM&>39+$>VTO ajߩz譽#LxM/RB=䨻CTqI!j!^>zkN^5rcͷn#um _ )X§V%urcy}F`mPZYs 9"[q{ N7v֋f'CZ L"gXQ'kz=rRvJF-WO|$J+y!45WCN׬[jGzy YTdqFBWD@[_iMw96ж֗lf=Tm<)>zsW~xdF!H to'ؼZz`EELp|n0h>oɩNn%XlkrV!q}9KRi`Eu*[ R9RN}u|\1ۧ.IcAa%Ⱥ휙}(j|B۰ޒXܒU'Ӈ\:[ dCp 3'2'r2d f(UXRh+rSeM4ћbecC0++C+v 6k%u1qڲGXܙUNGz-p8Ã'Re0y#B`N/`I%4lE}roʩUg>J7& k@U,3*,sO\L)^>z/n&i^Wֳl1A-tYW7b%`#)>zL =qq')nτaڳϢ,Ա/M{W2PSO&;!4uWce,K`ǮOļz譜 w}1r]ZnWʬ?LiAs_,8F TW f̠4u쫷bs YS@a H 7VTR\8v]<,rE7|{ũ~<%ܕI^mquXRLp<)#[6(y9K 4w-Og"Y/dcE 7v dr>}6(yOKt>zk^ .NLYfGG\ڢD|N4speU'jV}KNM}Ϳc"΄/>#3##T8>.b3v>qCY1&^>z׌\m3e:flXQ)vd1jdߔS/bkw![?xϛg|W&~NXR'Y;Xm%^>zk Ն)dǰH~_SE+ mc[X̛Flj;}G ՛c~|qR+u|5s&+cm$6)޷Go#V3V!+ڼ<#({)oYK,KN!6ogcۤSx:ȡxögss=yQmoEiI^)2Wa${=?%mRhy{q7%fܜW},zwk=up"vxTyۤw]z5i֗^ɴ_ Ao=5%m㯝cڙf$`ۤwȫޛco^wliJvn9'ĊXࠜljH[r7ŜtEs8\6 GDy9 cMT6)uا{뭱g>egZC۾%Mw~:Ԕ=F WmwZGVDћ,ok«&jQ"Cu9!njkZ.M }K.M}txOӣvr}C]QAwueEBB6)-4ћ1ц(>_wo uIm;ԋ[o>K7[ Nհe<ޣ]!a%U NL,v쑣oʩsb>p`vH”CFu~Vp DI,oȥޚ7Zss;s'zVVn[]4K#*Fsp ʋ:tbS6)-ћRR=^1`zpGUc7fE#X`ImB޷Goco_ܜ$i P*1DAmOU4'RKv!mB[rE7d%Kp lʠf-v/æZ%8ؼ& m ; Go>Kf| fR̹5c:ss1yтH6)k-[YdqPq]>IlRG@ԩ@pPF؎tl;nD]\/bo,ݽ1ApΡ{p[͏ohu$BIbWoӡ%^+ʑe_lyP’F8P$mWߒSSbo55}wAp0nD}cʢ0ŁoC)ԹcƢ h<Ҟu#^zk_%C.S랓1''Y V/MNVŰ[ moWEo~xi"ֳ&S͏%IaR!Kj+8 v;𠶋7ԋ[o> RX~a Vj7y# y-[ mU|mPh}KNM֜{=8([K,_,^q'lmE}C.<&Ki{?ưԙǂA š\mP؋oʥ)|/7&*<+pRޟYғoL kQ3:[{dx٫83y>[vq}Z!XRh#Xfb+T+n0oɩ)Z+G ơt{=7m5c.,zH =uַ+)ћ2}t}q<3jb@{/S+}q8~[mBr7_?7oa5 &J{ (%Yl{Fn(M9"[{䊽[ՙEp&m;S\v71(ŝ6^NbymӟrA=zkxXggkc{VTQ8uA1bgm%^zk/憛}9<@-\.]٫%yVTT"a}K^5z }cgȡY0ʷe_o?̱"SFamPoY.vξr.ƯZYQUK m)DowZzm¾}KNM}k|v_+D57^`ȷV xaȎANj\r죷_fWr6Ywg %J-96.lPtS:wl;N7oʩW;-cp|+lBG]^4GbE EPa'6(ym%^ ֺ^#z/^LfeLN5a3J@sꬾ)^>zk=Bq>Ο`'U5-` P>1Kꌗ4غwW罨oʥ)y,@D[Neܺ E+VTdZ5HSA >C.}<~n ͥYݎ-@#uEZ!mPh^>zwƬhtBܱҼEK 3 wPh[O^(^>z.ΧO %fvvk{FsaI&8WeQ JNMG\xn7vs5v:+F y1; ޔ?Y}KN}œZ'eh=Hr׉HJ?YXR#"N3ᡓj/ri 9{ӝ1Y9KA߾&1<<9#Bu5,IXKq;mPa7 Go˘[]Jn%Uk+*ƾ8vvT]ӪIzoɡ?f+v48-vkoVd(NJp|s={wqeŒg&cM,[ʠK!}9>Fnnz&VyDkiݷvW'&_XSsse }T >|4=7}Jg)vk**8K6Rr~6T^S.\z{_n%oG<18xN-rGyXSb#c&EPX-6j,įD-8Zf=Fx޷`^6O8yal{hU.@-:7j/dŏ )<\^+b8Y-]ئ} XN9z m2K_(r(V_i'"6{#;H[c:|Z#K+c0m(ۖѷ 즷J}qΊg>^JOXQs0F{%^nzoeg)N7UC z%_I>gu&kz9Ha۰2چkm9z =c:3&8h̢ާ>jqSoc6+LfYc֙چbLߖbozۧDL ʹI5vڷZyo`M( qŶ5O Fߖ޶k|7.NǨk;.]zqZg9ļFP}\N^ 4W ZcS_~iZIT6]gPDߖK/aW c8@jϝ_KQ`\aaE6V8؞z[tߖKSaW\b7{(,QP9eGV|>Ƣ۞%`7}gG4ڈ \8{<4V,栏Um/Ϣ-®z{/v;'v{JvnSp^5 R%[uߖ~]+s%c_NҜ=307"&-V2i ]jgѷTUo+oNk9,KQXDK~=$lʛpv/ځ''ZBƍHaM,k0ރbq}L9zm?LgifVNfY'5f\הsLXSgEs'Be?L~ȥ36gV炝h2;L]d76{d }i/ǵ}N+ͯ-[%uE/pQ<چb}o8נd窷}f|ŏqR߻ ]\QšٜthP};^ mޜi2lA_~>u(9's}Ru#GKq*즷9oᴬF<"./Y<Ü)XtuYܷ ;%Nrd#t?mc{ ~kj&{SmC}[.M;AV)8_,dqk}7uڮF@~`M {ӊwFm(ڦo˥3N)烻_cA- )ϲzcXQs4CR[cIϲܷKU?nx'fY%/׉j/Sދs_Mjβ朔|:N3x-v>%YH؊btrer,U|KB~X`E-Ŝel=m)%`7{E[1'/}S2˔zes=1doTU)A6ꃵ]wE{[87#LB;n<*ˑP)Nf7YmC9#\ m{˳s{K/P3oxP˳FQ!jʻwL4v{ n9wFe޼E8d{_mThۖ>]ث¢h-Lgҵ?8Zm<1߳]Fs~e(,| H|})MG%#gw[9̲,%oUIlzڼWGߒ[/{_83\:/ܨ_0)g%T34~'a):tȭMo3^ĹI>jof($V^iF˵d e{-5m z{wjP\Q1ʟ|OW!ou8|\ƲUvۧ&TߒK/aW睑8ȅ4u&Ƽe/QczU܊'^UP[rk v۱=gp<u3O ;Ӯ:J>%zh[-5=Vx9wGqn(N =X>F,r(!S+hr%쪷}JD[87y%!{k8fx|+EXQm`r( O8RP-5=\ŀ=^3s 3Ts25gm(Hzvllg?9` "eBr E۶J= Ug)oɭ)My^yu'qw✭Ws>TsXQ5^̉F⨶|-`bWgBx+VvcFWtwlr+jLQ`擄[r%즷}vBC+kIrc˼YYIވ,`jCse!<>]jϊ`Ι.ħcƧoɥ~o V΋_(V6eR$Š\.s^چ7-zPҪ籞Cɿsa=ܣPYi [BqD Α=Q}i],i1ֲ(W]3XS3'W8cEmʽ\zO(Ph&pbe:7&Z՛5uUV,qb:k=:쯊%^nz{_y ΗA.3츩F#l3˙e֭ s1Df6Oo˥޶R; $+9Ttli$ܦLFUa;#T8M}>8,kʼns/?A ao$ܦ׿6seB#q|~Иh$X-j 8_.ʂ~?Q:!*{ yJ> G twdcё uE8 -Cpv,): <3>fXm 㣴jΞB87Ӣ);AI΅x*+DI;AZBVu@׈#C|bkM+L,oMpah?„4<J* {a(gwZ-cy=Kp{ah_ >n gJ|ӏI[%K[4ރ]~ }v؍䗮R5qT:[4~Oa Mgca9u>kmilVYE$6RtnQx #’9mhy{L"/SQ'PJ!pEUdb]@^<6x, G3ox ]J/9ٲ55ŜLT#̦j]}#^`7=ZsɫJǏ =J 3QQzj[,p$*.f{z/WU3-I1Iu kSuNM%^`7^z䖀R|(%qGaP,"`*>6s%ܚ{yoE NV=VCGTv_JQ,:S)[UE4TLSߖ[Sz/LXL?uZQ=9#0fZU5/ Sߖ[/z/kB[9OӳOJxkuHMcE,kΛ c/ȼܷ 즷&<bg/13<__ZNI~5XS6Vr 3cg -v[n3VN~(;ce- ۲dʰὁ5Uٜ'C}rﶡ!зKMoۖut;8CEwbo"$7TU53Nc#UPؖUO+KMowsA-ʼU1 )xoB*ix>W|noɗ/ k,OU*y}J0佱58糸o˥)Mo}YS[8qYY_T+y֭/"XQ_OuOuߒ[S^+kXq2 Vl;w Tb=\5U^d?cL嶡Eߒ[/޶-ɢ6ߋ9ooŸY*M6 1?5KqZ89vPX-5mE墪nRN"eY.A C~oRUĜSmC6}[^Ʈzۆ1+f?KZ%UBH;XYA8!6n{VOpߒ[S޶N74qB΢'#ٲM||^2'w!چ,5=6 kZ#yCIq2Tar۳Jz^뽘ȋyQ^7-Y ݲ!&7{)Nf1n{M"4go_>MjT:Z.Ma\xŠmZ<ŽiඡTJri v~c<k`l}?t^?ʗGXQ7fNݎԑqP^cʥ)Moġ  g`5z۽!הsآcgmv[oR&'˄pٿ#R'oqvp-;J“g mZU̜'o8d_)Ŵ(x VԬjV 56G E-5m_FVΈ9y~lqki [pyq+7sYmCaҷ+)q?d89%š{u*YS[`E6-Nfa3moɭ)MoۖUj)lŸ>MiTJ޸n:`MUdVc{^pP>uϔK/aOX2{|sjE5E5(|$i`ER,klO'ۆbeUu 즷cT^Ƌ8#WyVIJ5z+jP[3 %`7SƓ+o}U-F9osL%u}ˀEW=}[~vPbWm(e<,ˉ篦i?͔59)Scg-:7j8e/nRW7:K~\rG{UXSUݤ8X2Ȼ홫}[.nz{Js]Ʃȸb8?kj(c[n 덾-^`7:Ͽ*9,5c{]kH-*jlVؖ Z6-[r%즷m\5%əl81)˖=V-KsyΒ6uuYܷKM 9=Aq]ݕGw jU`MUm¦s΀P}#^`7d+UX3*KEa'W&K9vƊׅKve%?3޿|ɜbNF4 NdתY'NrV|s.X v媯[/W9-/.b/b63=lA}_qۅEW=}KnMnz۟Lͥ9T[QYćLŠw͡zʍ[rv>%ee9#("g7lÔ9/u$-}dnh3̍ۆ⯛vĮẑ|C<&NʁݮHVuC/vH`E-95n{vߒ[S^_\pZc-kMퟥJUgG۝.Y CͻmJ5U986mӷ #w{qﳭsecwuS,Ź 9t۞Y74ދQe~cjqΑk^"r6%c&Ɗsg̘n{tߖK/3"sBWY4}5gF@9"]XS؜ȸ3 {6Nij[r%즷}J3 9W~ NЩ`Ϭ~ަx6cfYX6}J5=ϑջG{QΟR겒_'{rGš՜3D{% n%^nz{N~&_a̹]E]Ǝɨ1ZeGQ3oeq:1&`&gJ-5aMUd̯GsP2zr0*nqr@w"g8G4OD͙I#˵0 }\z =#s{sF?RAj*q%,X2홹}[^nz+OXmoj[8_3}㴽r KojKtw`7r۳ɢs[Atr1^yL9WaMճ {zatm({mo8 쮷m*;pqb@.ߧSٴ?{oaMUv`sN4ln}ñ^`w2'MNV6\XUCCccL嶡tзKMyk[8gf\lr.Sc9o+Fq8noɭ)M{W2yՃt5My'K*ɸ\a/Tm_kTS]rif[9/חrj qT͂#2k"XS8{ig5 즷N;Bq^kd渙&{XSU+8WeūgBlMi;`;b{9.2,.TT:.آt\IX2陌P=KjnJ ?vǃr$͍?k6/+9^zcEU99%}ZxTq9/𘓵0P}9uS١76šl|jD\e/IMe'ٗ+mqXݎZFtJz\-XSVr J_y!﯆!0sIT:[]x! a}]ߴex{w{N;e*.1Pj[KQܪ.O03[qF4;~VWf0ː1wn N5,XQ39i6H}UߒK/aW,_F,Dμߪ?’z_c*{3qvjX3fmʿo˭)Moc~ijT$#xP;KXSy3(BmC_oO; 즷ˁof'3Țo8rQ]Ond d4͊FVۢri*즷dla;I<!7Y'ey.fư[a#K5Mߖ[Sfڝ5[0ޣxmLQr|`:k4#'/Hm(a 9 쮷߫4؜W"+Dچ|,mwzk5[ߘ9yN)~LZjšߘ9f3HQ=#I7v6Hּ m DVy@YPߠ?/Šwiib&=Poɥ^?>>e0?2O79Y)yܜ;-uct3}K.=ލm ՗Y[ٰ"4/BǜԼKWd,n{Foɭibwm>9-@=dx:$TV,`c qPF-5upnߘzП/u|T9E[o̹iai6ϔK/a7y7<Dsל;ow߳npS~q)("^mC1ѷ즷IØs祾8u /OzVmq?3e ZIߒ[S޶G"roO'qXqg̵;Mmw/"Є5m'c=3pmC* 5&Z".3Lg3=?*] m(Q!^nzOE}oLSk# 8ocM{yXmY}K.ke؛| ՞ɭ{J`NVF6n;,5齯D ke|\k=_ֻx-kj;sd%c)ge-p"񊓉ɟD??M.*::Vc k" YX%^nz{SIK+h;A WE=[8XcsHwpe;D/RtnSY[Ou`2ɰ@+|z8#ME O~B kʼnw_j^KNm*14 |5O 䱐_55?y8_+}bZJXRtnS~=r(ηaɜ5/|CdD֢)(-;zEͷ!?E!cIIMeH?.NV j#{Gl^3*)“OqbbMU_q 4"neVtcByRty(Z#'*X=9WnoRn\Ku=soɭ)Mo?KfJc_.oƳ?Q.+IN'u88:&Yfm9zgɓ+R&=8:X[= ed^4Μ-^IP< }K.ֳPt0J4 CNx$y=ۉ/^%X1VԨcs? p#wz}%^nzdz_?"Ey!G?o_?fv }Ϣ+=@7F endstream endobj 149 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 139 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-020.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 150 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 151 0 R/F3 152 0 R>> /ExtGState << >>/ColorSpace << /sRGB 153 0 R >>>> /Length 35396 /Filter /FlateDecode >> stream xˮ&&6O$;$nIghj.~}߅Rd\Pml' sO ),|8ۏ87mDz+,ϷϏ{Ogֿso/Cab|+PPV=UH2Dž@5hx_E=ϏpP*D;2Szh!jγR5ʷ }l‡-ۘFH uq7 |eŻM10{yxVQ{~ O'x^KC?r_Ec*Mp63TǓо]㹿u||+G9fįg||YCv}~#Qp;#Ƅ/>t+?_ׅߔ/0˟^RCyle6*yw,E2v Ql,*Vڧ"e(é_ȟ3@( xY{v23߉1Rf縨,B0gF}+[-8@S>#| yKT,ѧY-ʟl)݄©gL1]#R~Sߞp߻glGG{ƴu ?k0[߃c 10G%E)PMsJ73|wU{ k~+'{S/{9v90 :W쿆ko4=\L&}Σ1Y==T̍y=;_LE,qQOs柩jU>.ǁn4SМOwYI)Ab"/蜽T<2Fpl9gX9+G?Z __Q]+ghjȵ_o %FG ~0 h? _C~~ v?::8zO Џ~GkIM ͘]6bctI_fk{p_Лf+b6 %:5W8;D'6}HlfsE5߂4Q$P>fϹ=j1L˘?;9lfV=v`??ܨl5Pga11~=Y7fϡ٤Ǵ`s8lOp/Vٮku;㔼YrߜlcwE"{ׂC؜p!-߃=1ٿ5qsnb~/f٪4azO#Ig;zPG{qgl-n?j8ّjg/u^ ]0Ty5KZς>Xg36ж=ρ4n700p<tGǶ1akXyf8y;u.+>zvwcs|x!N/?>8?cySМO*\cўp|NEgsq,Nɟiߠk y+5U/b ~9/O擆Z/U=9c.^C~o~{1)q²SpoaE1<f#G|ȟc/Zܭ8oqGGk[16`oBb9QL6 8^ǎ6a?OL\Z~܀oQnSb=~Hy{v=xi|x#ho/aP;5asn繟ܟM}@ X {g<)x6\ܯ^xɆxeۣ_8via^{D炵Ҥ~sFy±>9g|rgG?xW7'|wk|.5/1P1?z limԷk{qAosZ~'9+_%֭?Ծs>:'|\uְ֯ўoajhf 7K5Ú\u?˺;ePg7;vmEÊZ'f>Nv_[JpHEuX.܏\c? {Vaq<ۉ4^ۙvWױq \?^=|8~ynu{28Ӟw {(Gm~pj?16='&ROv0?x^maxў }% u^]H?IoOb#a ~LM<6_Wc :/mN4ak'hhSbߓW^qQ2Şq>}\:6JaAc}`hbcSP8xM}h)过U.E.nos}w,6[xD_e sN X|[_΅ҽC0w*JVg$WQRO+C=g\}0}55lgj|ىƋ*s b={sp!Au6~:@g#~5G}ӣ㭇[@ú4'э}I~˥-F-l!/fsova}1=,kًf9p."u*9a$’0>b?E {ʛN`$b{Ogݷx=7 SMnx3j` O%ܡj @B `B?g禰s< KɃc)Ppy0C λ^9;e:[|D`ф玁u=HkXKECބ 1l@ߡ&U~ޱxEL:TfkF676:3^J1|!kKk~LpnUTs+˭샙.aW'ܛׂ<0ؘ (,`c_Y/?w X#lKȒaFuƼ  t\$g-"K/هb[~.l7< %\l r#Cs4xeHcf+5t6 ƯӼelm4w㦹l-tu y A^ 6Iـ.Ļ뭺Dw lf38vn.q4!W/@!(y Q6- fv\[6!e.MŻͺC vI NMNP/gœD_iwěd`36ϲE^}v=tڽap5G%etM[ lZl<{¾kلkm﮷^C2q-y>s%Ky ]%*yr;lѥxwUQb kq?btlWdv_lѥxw.װ|cY?N1?E^tg%   _%wZ͂n{/]8%`ndA=!kKyea^AXRA6eUKnX8/ y%ds཮ ܄&}ּ(=K6QTޮz; ӱEL p, N«8 l ʺd芲Mj_?;'1Wn;wrYcǐG3v=_<5WdĄ >ޖMn^A(w{c'Qs{g8c,?Ç'y Qkź-(ti*]oU?+YMHX_{Vi]SڛJwU٢[Sv]Nr0mvN}WeI\s,^Cm[;XvE^ؿ38|NӸR=qB鵲5vpq24/:)畳,wMu6^rx\f/n:5^9}3-﮷l۫i ǃp ?6!< O}%y۫&Sjلkm:3熹 й xXC>{Z(ۻ`AhxxdY[SV\8Y%/z%ۅu7!毅ͼtrlBzT=C[ox2 <1ż(u-y/XQ-elӥxws,ZNg MO<{]ݍ1h+h,X|˲E^=gjG1Ϗ>p\vWuʾ(}ڠb))e.Ļ&,7kK }W+ƃ(ឞ(`@9ݲ .MŻ+œQkt +XV''5TJ~yኖ\]Kޯ{F@k[8A=_qko߸e.ĻOj=7i*u#hOJ:K5u&'%]w  CoN`&kv`IG%D0hވ?aلk-5%K_.p1=Ri !X,^C_ =[u8]z{:l^G!0DUEK&t}1x$ިQ`]zwW ^`G'6ysn-~3o)[wͨcL޷ޮ ^㡌Ƌ1[񄔐 xFHAy'-﮷S<&7ُvky5`.2/)1yNjv]>Hi\bA(zTI}#yИ='sÖB5w9ދ.MŻ9~1SƫmHgՄ<ˆOxq`^Ca}Vn_g٤[/v4~Wns{`5`$书9y MM ['o))elѥxwWE9-lS;b0XND%kM?s.YV]xh2eW\f٤[/~=0wWJ߶}p ΍W}xsO `-.Ļ481~vXgAyۧtĢH^A Hfɋ7).˽ynjnzx3\vd${0'u |w/zɇ* -![tWe0Px9 \tiJޗo__.P0 #Bm,ż {g\x+%vϒt%]_.1θ&w< $v!p!{I&^CډO,WPn>dq>dt{n_xG7Z|a:WйnE%קݮMg;{s_3d0 (x"n^C5Ǿ13H|U6֋/=^nۚh 6x95EnG>j[W~YZdS.ރ/0$X7*tEޗ!י}gO7s> XWmܣm]z5 86?_O=gpmNND<\ myoTGQ>/FM^"S~C0nWm}܎M lBN,:2}o,׹zu!{`]+hW@h6zgIv[oUKޮ 9c} Ŗw[v.h7Ѽ)^͛MySzi^6XbO,{1t>f yه,{1m:2﮷,B;%߹~%kAEB۷'WЙ/֍Ax-=/]60xz3x>x,vw6y]93Ыggل6K/z.ͷ%{Yanx1H)0 k菭c,ڽA䅋J>[e.Ļ{-?= Bxqc=q IWv寉м%Mcbҥx_zwN]F`筏~¸NCNZ{+wbٱx >& y݇({c*[t%ޗ}Ufj9x / |cёk!ybJlNG[R>m~fdmد{Ӗ\йN$ yq?:BU=c?G ߎ.?\WQ]UռƏo^+m춿y5ۆu/(}Fig"۰DJFܘΕ\'%k~܋.Ļ "ִ/sa0!-I+"\t +eG S(Ra }M"Kb_n"5ؐUA;GU!c}>tݢ0xK v٢K/zuA}MOc  {~ӹ7<͈>Ҽ7bN[6}o:2X1[]>!K]1 D;vl3S[׺R^m:2X@}y "2NՐMc l/Ŷdr϶T޿b]rD=sf͏ScTqo9S;aǩ?Wk97] 7̾?y\1bl1b6x A?ڈF K]]o\Za -xo1c w.Wꊸ%F}d%~k/sۇ{? y~o?lm^AcY9K=Re7{-}g]uq y729]Z8C[ Ht3f&a lB[F٦K/zmQ.8 *C1sy1.a$zoPwݦށݦމn6Tt1neJnSe.Ļ{1$lboa?HVI1y|eL5>qʮ~e.Ļ|Oҝxb}ыTC, my<% VlAy'ӥxw. 7U}v=/?}zLgA ֫ۯXAOUK޿p]c)muG;Kg]tGm_Ǻc6TKv[>էm<ϳSFIu-]xo-We>&_lӥxw,7J Aܗ|~4nF#U$ 30/_܇C RO ._#6C"kL[ {(\yFU֙Ky|. /pZ?` ,^f8 l"A/0m4~KϿwԹz]E_Oչ,1#NZPCdN&KLc>v"SʮΟe.ws ƫз}0/񕇥9ᛰq# 遴lX?N:5ᛰ{'L٧o²lѥxwvp5qǣ=.<A9:D0o OH ۯ8تfT/>9֯dv룄U*b΢ | Z߬!LahЮ3FVݕ'}Ö BƊ~A9>E`ڝN\Ϣ3yAv y-ͲM^xx/x9m!8f!9_/t%\p<\QZ޿>tx)}a/Ϻ-kq16ϏE0tS }s@XrVa)L|1fXfF0sqG$_a| (3]ņ>7_'!p:t O_}ZU'4NGl\$ `䢃 B[AM?k^A+1⍚)[[- eeT٢Kjg,,δ& ۽ +0 ΄P^ţql &k8>X6!e.Ļ뭺tbSb ڎ4Em!Oxηō[Qsˮqe.Ļ օYbuT c`q` f#> c3y ]+03ޘ-QvҥxwQ ;3aF@&rgx5\sһ)lʀi s-tkP󂷺j^A5sZ$]}d\-߮!zDs~^L%k\vP%u{h>0~q+c׆#bd z_^OeX.kù^ԫ2Dve`*dd(?Jօ{#u!"g}:~Y%RYb :IDYAc̸cC_F *1M F`%ͲM^" Kk|mێWԶ4&xEm}d(A}\{'ߋP{eTa>w@b`G pA}0jN2Wˮu٢Wvmx>աA):3ƅ>F3vGFk &3*N}:# @ ke &m6k-Ѻlѥxwő/Ⱥ0:;cE]~c`^A+0+^EΕ-6]oŻ|+ u^t\WPfH #){.ĻNsƾ`~9B?F;!7/l$D$/Χ##|/XHx2ge+3錷l^A+zV^2]Kޮ Y_ ֑ޯiGwb\ސ)G$_1Y+c8,ق<#֔/]sƧ zDf>kPƔIهrY[A5^jbF߽]%7#o"EڥjtimԽ]~6_\jksp†[p̗_׿4g .^rGIٞղ׃^lѭy_z4xc#=sP ƈs?I^Ag/7 ɋ@<)dr-﮷yN 8֟.9'cWP\ɋsnspMzAv`7).7O| +_mJQB| m'حShS<$B S!Ca20iYvź:)Fzi c]5Eg8Lg[ZqKe8Y.tEޗ_pט^˯x+ơ0^WU Ux9V%d0`m Qבz10(ڨ)K-d<=y 6|~0^ kWM8.>TWYt|eP"oycv,)[.4﮷W?Ǭ f=%!ȶv/sH^:vZ6aMJ:E Zw6qqh_{G//i̍ P|g m^VHқ,mit c:4q챭g\tEޗ_9v y׷-}};]n.7VtDmM^ŏ]fVe']w{&xn3cAvV}.쵢7zZgЃ̼.}I^} ֥N,OsaT4Łt/!ܹ'l),^A#Ɯe^\֦en+jz+h69`3e.[t%]? @VL[ Ka6z'bdUV˜yOOJJҋ/gUcIt\ HEEղW]\KkK 3  1.!\[A~l OSqY6֋/\ `3;^qo"r%ksC1vœSv]E-﮷X1gaŘa{xo-khŜ5qc똲ǜe٦[/~v[1rf[,h{7ZkhjUJfU٢K/^aw梷5<7[K襄|*6yu#)Iok6zbKv[7*[t%]o7zEdPQBnFlߌ q:O^Ag'ɋ')8a-﮷r£wn7ߘB}:րnakS2!ǻ qJM^AGz SoC >&eN̻Xm疽\h)c,v-&`A^÷H f` lڏ+&em4%KTw\ܻT{ k?)B2hLbME^}J!'Fyo|'EGpt <ݐe9Hɇ}fƛ31sL9#MsrwE^"w!zqN(GBa|]8EabV_R?,M y0r);Ukuʸ0:/ǺR_,dݔۄݵ=2̇{d;\:2 =2J$89( Ecy;uױ b:~AX`Զ#nb3_hE` OR]F뻌7煄ѧp_W)9X}h3gX^f:Rh3WӔo7 %c`PWF:/RTJq/H-''<~V䜿B=zP1b6/"1s5a O #NG1':3-DI3g2>*yL񊿦evn8mܛ ].2xȭ/p?uVw r\ϒ{&I5ӑɼnD&1[ڑuOlѭy_zU 7._72RcsY\P"5h.:qEZ}xOQ.exQdӍ@1^{|Vo3ƾrq6ıXD W1[~y\hFx߯ժU#6DEy#h {}lf1#.ޚǺ7Z| $xC9:)1 39cƄ0\ '#y NJ  $/Rvk,tEޗ?XBan}YB;oe K(%Tt>k坉1 0ߙlҭy_zWv:%1,cQWJ =ɺ#A2@!l1D{1$o،9sT o,6-﮷/B:sȢgL.Dexwk|w-ǽyoP&(te]_.Vi%z /ze:yAfp2'YԓWPzs=,K^-,J|m:2W>Z2E_!(O5t]0f~;M(߱܋N{eOȃd0ty7 [ڼK:e+h~FOd/'-j^OM_$*H,yp*R +qDw+r`GkO-ͲE^} kAa8]=gXݎnȫ_'kk^{#xelm4﮷7O>;4޼yYK&9]So8xǹC9]\ oKğ^/t_Lz&'xjw= x9o^B[J /-(J\lR6}w[V[{Ϛ m{Kb?$;쵷tX/^uQ/.\硄̸d>#Éq;#g<\8#k^̲M:#z=̘6Lr&oun'`2N^F1e.Ļ օ6VS{~c`<nFWؘh!̘νx˲Wd0M"Koׅ(:$} kbw@BX V࡛y |iifJdW\K]+2/47"B U:G#y cDH db]Xҋ/{׾1_Z3y=\uoB5_'e0Ĥ^}&,3XBBPzJW.;xEbpHyge.Ļ%{Fj]wu;Nh ;ďx+YˮlN?7Ҙ3W2pĭsecx s1<WsN+U ]?8W>̋SiSC&wT!cA/x*4&FE٦S/zv9ϕ17x§G\sg+}}AD0vlBn(t%]_.?s>I0jۃ(Urųm?+_xa:{qwwNOA<Ks䓼[\ ί^~KSz/YVacr;Fav; y mx㔼VacnU%{*[tEޗo~fWchѓ_bEO~l F(^C: iY$<*[t%]?AoxO" _ښ ) V姤E^^y~\ψ9lo37gl1S ]'mlmH Kx.MŻ#J̓I;c?*!W~c1F0@kf d7\e٢K/zcK<:Y@ǒ>Q,Ǟg`1B{3]wms񞴉=}q&^CG{S|rmqv{K]}ϓo!qm*Gg»qt4'}JԎ#$a㷧lA]wuvCfW+]9b^A+1Naރw𒽲wƻ%:>Ddv'hKҩy/Tn j.st])[^ӥxw׺_K30H"ý{E5#{ciR$S*[t%]?Ǯ ^[0zO櫒.^;ћx kt 3jtlANϙtEޗ޿`]޽nwζ` *e^B?“ Q`لWlߑ5^aP 9Bb^/x0W#5Ƌ1x5^\v.,ޗ޿b]ysTa쮧OwQz,Sxo{%w{#eweN̻+墟F>^+Oztׄw#|#?-ڇ7/-5g{OcGs!Xwq2\ذޯM u=N,mĻCײK?a1*[HJlXn;">ko;|4+M;U˼oH;1xfa0SFYN4>^m_:׭-لPϾop{X{ }c{0y0vzOOeyy׫ ֜e} W9^\mk\ kȨ^+u3RZ+ULVG~=\$y<=t޳W=\Xm={8B=K%*xo_(D@e!̲ï􁓫y Q6- !eYő=B=+1HN%DF@/1%|A.tǻ=OODGʇ\F?3#H5T"#"Í.#?Hg} %ߟ#s;Ix\4V54N{36.[tEޗ˷G}sNbث\&c54v21J g>W}:ٳx_zm[6cQAe[}a MW` #Q|,{ecp٢mgoZw!1 ߻Hz!{};wsTTwޘA!}%Zo F^~K86^AgFN1Fs}=slҭy_z{%r Vd̺dfά2s7rT9.dzՅtEޗ޿t]jyr_]YLߢuJlcݦn? -yqKu]zw8dMrH.q"d:+ؽۑū8ʼnT٦Scd++̺9{Tf$仲e:3SWЙ7*ЃҼnT=ms%]3&ZBH|^< 9!hޱc3ÖHc;>F%rK/~Ej,ߤ%cFȽ&z{2<)eރ;[>^ ̻|"OE6Y|pN ?slUpXJc✚e=C޿Z]~vY9xnxf|Ntd@cv:ާMg5+0Z_K6O^l_xz gYyr[v& AyOHbdTo6η'{;guL׽x <Sy%Sdu2U٢K/^b}, b*2\i",?u77~- * a.g o . -5%KzVhYE")5_;ŚCh_Lze^AgKL{w[/~KEW腐ڥqR5UEJEj~j+W? n ~ĭcyTE Me@D?x PѲ;;lB9zXy\o=d eѵf'efLL)=d׵Wձƻ~U_ 0`^o Ǧy)Am8]Yv˙en{21vZ)ֻ ^޵VFLsGۯ֒Wkdok6]w7̘wԌzGXxoX8N+y$`L6\Y6! 6]z)R+1!!o,pQz̈l:s'˯DWb }C+^~%.{]3;;1y_jpܷ!7S@ v z^ [McREy&x~c!qcs82Ԯ8 .Eg M V] ~6ƃNj]^#Z;Տwp \?SpfY41p*߫NE |L_yՌngLo3#lѥxw߾gϜ\@f5ryk31'=[9$I^}Ue'첎7d:c7&Fśij}e]Aw,|Xx8 tƊ0t D$f]qxw48Q':А9Ȩ+8+!7Y "Oh7_QO_h4ȗ0q1C6?Ch1$?2͊uOl![F>63mo6u!~0tG.~ΑE>[&h{&^ڔ o㘿x=c=G <ه2.a1XY9=* f)x Y9R,K3jF]93jWFM}@ܻcE+e`_`3 ^N,[t%]ofYobE~-竗үQʼ(eYkfa)=v)rbؙ$Vҕ}גI;f'l9RQy k=ɋ7):T-'k4F:F5j+'U7Ɯo0⢝:|,Vت݋\mb*yڲIJlѥxwv1 ch/2 {Y G' ;1n2_yV[0ZcW  >. ߒA%Ҽm=5gQn vXGv70mHֶL1R"9eё[FyN끰-fIiX;z^_YJe\йwoat[TP/U_?su¯q)>*cGx?)N<d)+>F1ђ% hzq+x婲h0}9o&ozc $p){mDY0=.^C5W7PlBͲM^z<{|9{|d1#Flv n{)]F >˸/!,\sA5օJ*ד0hQ!'n ~ZZY$D{mm*%,6ܚkh{5ms mќw74<[s^8]_˜sNX`.ஶ&!{Oq==٧$/.FSvIM"Ko;n<lR}@W㙓U>ܼFMK%Rn7E^V]NBq u.ΆDaMYy;<,Nx <4Кe|I^}vU] S7U:N6Xt YOD0i&Ělӥ)y_z<1ѽmyyN@jnLv-&eETS٢KeR\c*ڒ/Ţ/ѓf7+dway1slB/eN̻뽢k]+oFn8&Ӡ"jcef&d(te]w]1#.경P]Df8R݇PGC]]{%L[].r9W].G/s\E-:~VC{]L^^-Vr+ˍ0=_aaȾa1WБYn+kd׻.zL_PŕFWM3 ƞ)Y:tc9_ƕ?Dc£맠mmN:^qcL}yOX7.tEޗޯ̳O$%,9[+71{lyKg^Ago2:/x9ZvYUKޯqQ 9bS;EUTޯh[\h򾾛#V byhձV[q dلu1/R CxWߋ\c.Ļ=d6\'AIx~)xjW97ymN],uP}\'=蒫92,}q"QͩJ˽[ro9+1KsJo{[t%U,{ϯӐ'ywzw<>g5uaF U߂,}NIŻ=u mHaŪA'0qL:_&sVf"yip߄c8I\]kEyh9=rLG:! yB!_5Ny侧6]rof&<gaqh*& V&ӧi1fx+s.tEއ܏sVI|W\Aބr}Lލ{[#6c gec*3gY9G>+g:}TVgwu4˼?+bƌ^^I?6ç-a:ϱb.nnuкnuӼnu3~cMhY7.Ļ>ų(WYUaue&9ALt9y ZУԼ(u=c0oG&%6rw62Fc~\gtdK[DnۑƜ=#l$a&dZ铎%'yhnx7x-=k|9W< $מgMNܼʼܼ< xl)yW?߳(L#NHײ^V#vObmLL?Sb+~H]r!̸sQY6V*Ҟa음n%dfs y 0H+J}w̱E\Ho34mJoBeMõkT^Ȯ |"R0NӴޛs#f}K|t ;p CJ}ґ!y=jLALF7!c9KO?:au &S@_c^Au)ȇt.c3.+h^KXL_6 Gz<3*qm]Y%Ϸηq/ϯ{o=z}}ui;|MZ-+LHϷ1p!+61sV=cs =cg=n.Q?g!>PhBdOH^Ku5&[ P&baCkA<>bB1K[]#wKL 0t y7a4&[aSgnlPa~3= x^C'4gF鮞d 2Gmos#a!H 7re?cKQ `%7>^}T:4yI=ďR *iʑ_Xrg^\ +UEݹRW*<ܹ+5_w48^㽞.h L ûisgF'L>TL? imf򣻌j*°X+4ن_A {yiTi9!VO9u xP>2Ww'NKvDfi\a:6nw:D3J 먶Xx3QCc=2ϓD5i9np= | )| 1]"J]?G4񙎄pqvӁ,vKknci\ѧ5Z*q $ PhIwaT&¿8 i wU({m{LQ) [+ulvX/|T--Xͦҧ-{y47ǁQ[(*XjAlAL %R䆗W)}}^=0BM0DksWщH:S݇,޸gf]G,D+O&y#e]毨E\]嶎BA• ki6 vQ3y M Nmu-n=薔m3 +^1^8W({rZx0i>xLéGE @c.ĻľS8 ,-v?*}hsU?YgIG21r9?=6開ςhdz *.C\7\.*]ЖwtmyFnIҷ~zĒ*M1 d2izL蛞<1J6a*R`M9˼ܯ[dZZbAp~~f8w;}(͗W3}c-t1+:"'Cݑ' co$o c՞sٰ"wCM5KEm.*bPOh ~Ump`l^A蛭E>y}W˱E\]ֳ4?*X!pF;M"Lg t :%FEPs}ȱE\]~{d%ҏf E _~ i_0ȍEx>X췾a$3}P Bl=$GʾCrl%xW߬,(}Pa>QQy6&t\U2cW V ՝yBepn_G&tڀ060M>aj=~* Vwמx7iL0b' &uY?}"~OpP ֻ ~5=׶ vzJ%`R bf r]*["wĄ"q@L}"I6fkaSo}bkm$.[\_'džr&8b8L$ĸM Xݝ:B!<'AAtz1KbL{&آKݩ?ٳK/Z0u0_?Y0Fз/Y&M^A蛭Y&E\Y&ԳoAlb4yW? ޲ʬeܙ^d1a^kk6]w=K{‘{0H1:n{@.LG4hc&.Dc.Ļ(*KلiL"z9ʿCEjb~r`p!67U(D]Ǚ2>jf,}5śs?d SPk"ܿڔK܏U'f^C1\\CwPՉ5trggi -"Cnc˱=M CP5O-zUIPa%3L-*fRootXU3UśݱSQ)y ofĝü<&tI*Uw9%w8\bYzpEJJM1ٮB?ԥ8 2%}zYFݏE_wYpl-yr? w/{sbx^^fN:{sb: Шν9Ǯ.DUn5`ӕ<ј2sJahuұz1(S {WSm)yrw;nc pW(:Y!)NaJ0q䍽e߂E p)yr!c{Q,ׂX~X K׷IGm jNRQ]5N*g|fqĠ@Qr<_Eeq&h5ōA=F9蒋,'ɝa >d1^ 6d9C#fK^A{ic6Hg^dݖtEއY"-+,npQIѼзT"N^(5o@]46開,,X1-Z<(Sr_4HzCy ưyY}I\]ֳ4 _p=1>w· ó|rS%]rUϵG(3~"EĊcDV#!w`ΓNJsĭ׼QOxM9K~ t~Ε*> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 160 0 obj << /Length 866 /Filter /FlateDecode >> stream xڭVKo@WX[ԮwH%m%P/p&vcI\ϼ6D(E#wfy~3YgL^x(JL{"%8{Pwُ>BA wu{*ʸTncWgQ^ޤ@ x^ ɇ\)p2qi o0IsQ!CԆo8?޴bPP,:LO#np"n֢kkr6 /fo@ .j&QoP~UjY B EJH ժl5[Cn)"H:.(N8=#lNJ^+V[/1PP%IKjس.&cE]qU K+ BY56X _"+'w|stOBlEhkJ%ӽ0n78뱕 gvG[vF֜Vv{.3jv6kdkiflSI NeZ8 -V+^<8=a44_$~@O^{4<mM%\!|^veCGnxn*> /ExtGState << >>/ColorSpace << /sRGB 163 0 R >>>> /Length 2517 /Filter /FlateDecode >> stream xYK&Km魺blXπƧ3L/o)#"j >tdfE*L)?ry::~}}4#c?C8r֎?iG79 J߿=~%?~жrW8~_^Hs9S:=jgmJW?_:>#tHR e,sԆP)٧̷[xŧP3tx>6e=6oI?1KNrzTt"I ›}:%g_8BqWn[; Z qWT>}SgC겁2hZ&A W| E=Kn Z qW/)$4g ˣlOIZLXG [ayZ6e=6<~Js)mQ`"Abe w{AXI_SSvUζ|C677sh5Z-D[e (%zц6JjZ6oH5ۦ]}ή0B5vjl0P-Xm do6=JʚԱa6较ۦysD0c5նX4hS:X4(%[#N>[KrMcx?rm^23qC,5/AJ,]׼mGnEa~G0?=r#,ږLy/ gZcuN[vub%suIX!^kLm.^>x?>)޶;vDiSrgJ*(֝RNIv۝K]u4 y#0(UW2FΑ$Ҫ+Am(,F^uڦy?nSL~$MƵm-Pnnñ)Ic/#}ڦy?&.Gެ] va)E|CN^A~xJo/B)ۓMxR,.04$qªŨp2gvr] vN K)ZLSZV-ƶiS`q%P;*ݞ,^+ Z[]׃ۦ]L}~bk,F",,;oAElGjE,ԶEkk~{ܯcܧqXIcܯi5qƏq_vJ{ܯ[Οq1+Am93㪀ONhV]) jCaQ7+6ϯUu endstream endobj 165 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 156 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-022.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 166 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 167 0 R/F3 168 0 R>> /ExtGState << >>/ColorSpace << /sRGB 169 0 R >>>> /Length 9355 /Filter /FlateDecode >> stream x}ˮe< O󽹧- [xh4R52ܒm_oX+{ ufL@  n>G~?>o_>~L)=7?#/u菖q<~o~ᏟЗKje>sx*rڟeOӷs<+3S>Gs%wKg>R9SRnK>$a2<Ǵߎʀ=GY:-nY;y%g/tJ6\:!ͤVtزͬeǴJX5msu`"pY'ɮS^]Gyte6~\U9`ӰBa9tk<\mKg-吩3h3t< \e]αF垰@Й߅w:Yk&ZSauJ'4:6}9/zө3NkPaeZdVlXְUܷ,7&i&u,]g_*gT`vu*u8ӶN[~ê\:m:pU:(:I:.$dʖ3,;gG̯ܵC`-Sv9]bz8Ɩ9><%ln]2ul`!1OiiQ_FϝrwU; ɡsRKsy-Cgp k_^V> |G`V{Ne砆o _i z_vjv z5 3m+xٗ@a)6|L䠼|rikbvf/YqkQAG~|20UF (fWOii^FN.{er7*dcXmIi2턫̯H c.>ExXrt(3i{> ^dJ%?\{cAgyvF e0g^Grz=*aNg3V_AZ&ϏD{̏leWZ+`J Ck,Y5ͬCvu"}=vaƳNP}e+ұK6~斱 *ѓ"e_;p 1Wkx?31kz)1netx+֣wN 7ҩcնs\ʸOF>ժ5[jJ¶eb_O6Ļ Ip[2cOx"}6\ 2TH&=)`2)2 |LE*zD0Mvzۺ;m~w[wvm{Իm;n"ݖyz^H\բ 7?V2{i#j}Ce#ZmWԭp:lQpD`\f9ƈ4dʪ%d~gpF&F{#U&`Oe}PpghVO vV#܀Y.8fq722LGO4n.ퟢgVA9KX6n-d9= cmes;nP2*&3i{sA=BTC:?X E,e2c 9(_\eլך2vJ9VNyBg߈.4 ?a=;"aPV`#axzz7"Z:"t=Dd(Gpv3 Dۈ0~1TW5[Ͽa=JWHץ@ ]y=] Aga]n^E>G!"t_0"g })؈pa?vD؁=Xi&jn+!~$YvD_X5GDBǙ6"D=BߵS~!B^"ݜ"sDcpD;[WD8;"\F6ns#Bocg:Bkg!?K{P/^G&uD2s"7͟ B;NmSq~! ؈G} BȆ21lDٌv֍1s#hB">Oۻvύ{'3u 6"BpbNc#¾|slDqxeڈoD "a}|E$/a_Q7"` !cNyPf>_O1 :\vQ̠de3~5E&Yn6ӽ^Խ՛<>m:auR0;NSy@ u=n{IJJr+.N"vٔtu~Y1yiOdrKaDC?hezG#F?&SDk52mU!ST}A<~ӳEOQ3e(pYS-G xqs9CZ9\xG]H0e5\gܘ$RDsYhD=XeqO<9vy|x30Y:0Yzc$ic!9,^g,^ǍYY\~x>,(9_N:is_Yu/;zM\Ŀ1KfryHץ,%&7fo{%kfo,=1ml,}l, ,jr,(ս JTr[= aq5QtwP @WQq$/w7 LvwԲ7Crw ԃ:CRxgos.%Q`Qa A.nuw Ȼ vwL~FQW(=Q/Q8F),FIYlU({tw>ݍFw7Z,w7 }hhĻW+nw7gF^?'m!Gw7P87ݍb݀򼻑ju传K0 WUm Q6~#%ɕЕde3~Җn1MmOW{nL۪j~ '}#{V-l/ ];Mbn}^/6f}ea:t#Rl6l5gЯٚ.!%Ĺ > _^KGAy͍>#qNY$3EY0ʙ_ldQ~t?|U]Lg0_dN -~WDsn)^ l'n"^5Y+^ϼe9"9v0X23 eL,gbX2 |&a3 oL,gb>0X7|&a3 eL,>0X2 |& eL,èX23 eL,gbX2 |&a3 oL,gb>0X7|&a3 eL,>0X2 |& eL,gb>2 |&a3 exgb>0X23 eL,gb,bGèib{>Oښ2Wq\+vc:y)ZLnY/Lm[s-1L0 t8keg9̖gPwwcߞաcuΛ$ mXw1"|0"gڲg2#VT/b b.n㈉9&OZ"i97%2Z-rQ>'2GKoFF#m·?LƠ FMrfvn6ޫ>Kx\tmp${ b%dABio3@¥/U6@lhF(ڀN|lA«Yܪ'ܖ_^m1˨6K=='vͶd#ڂ)_<?-bri^ -^FOl%_aU('*_t~) c HfG4TqbNAULEzD,Ccig,iu9O|o*c'eTO+FȶY;gN(`/gdN?LLN1u8h/vz_> /fH_ W@.WZQh_үB޺Cbu 7+{u)BrǷzQV(F/FѿD~/QߕQ_@b( /Fi1JQzCb4п(1JQ_@bп( /Fi1Jo_@b4п7/Fi1Jb( /Fid1Jo_@b4п7/Fi1JQ_4п( /F Q_@b( /Fi1JQzCb4п(1JQ_@bп( /Fi1Jt0AFqb];p4rG08dc2v\Ӄe6˨:' <:؃XJpu""0g䪴Ǧ`-L{Gx+Kew&d<,13-ДE_b,`,[]`?X9UUNjZ;~s?X,{R*?[|Y1,Rk~n~p|[骗t,oR,` ?/K1Ûkowe)[@b)2*YqR̅+K1g/ADtQ=` DqwX|fm&ߩ2f7ı%F5˘zwƙCt d%jT[#Ga!rLD֨Cv2I46]?9,,vT7܆St5ZE-j7샨յU̲P]eZ, *fYV1nU̲@bj,Pe7*fYV1YU̲j,PeZ, *f YU̲@b9jZ+ *^YVVvEbj,)VYVqFZA7ڵ֍rf endstream endobj 171 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 176 0 obj << /Length 971 /Filter /FlateDecode >> stream xڭVnF)#5ǜ!hhP@QZ]Ͽ Av }Fڋ==kYUſ $!F -JBmSf|/uy:REThoy;5[~h_.335D* $ Lؿ"vT~'b zfcn?d-*&GWq~= )h9O[al`yc@-*=JG "O"Jpk֮HA(|6~P9 ɮo gIjά6sو4u9,lv^Eבđ2FHJ۝D XEQyG} {c`W3F:$d4ջĈ9$2y#0鰖@o*$"h?՟0OT"aDQ{WagD=֊ɚD &jqK|`Q4|20ec놤*IXԶaN8,xnzr2LGD׻{*z)Un{wk_֮qȿ?RG)AyRuK1QXcu9a MhͰ{6PI+*)~2WΙͷe҈wf\±s1wH$ 6l) r]tBw] G8Dfu f2 .yaNnz8y6Val4p({+R endstream endobj 29 0 obj << /Type /ObjStm /N 100 /First 835 /Length 1570 /Filter /FlateDecode >> stream xZn7}߯&(R8v4mmo+ipgdl)+EAl r(HdI[Rړ##JG:5iC2R!CsX<"I,OR #xZ<Iu' Iu'I#Lf1p={ue:9ÞG]Î:V/'gHI+R*̣C$vvM?H9(IZ`A>hJ9 JyI턠zEg8"h "US<n c/cV"x]+ AXCc. )*'T&% {g@)4PX@N 0X G,Y31GG87@X`Hk)o, 0ˠxe2 0`  $>FTRWkxp 3Q]4b$GF1A`S#r\W6.GyWMv>bogq֣LCh7oS*^t]lbi; /^8Yۣ2Ź45S}R>p M a]Ƌ#L5u>t([:duV257:l˖bG瘷IE[ՃMlg%@O2G~{[wC"]sVOטUMWGjtGQіtzdo=|b,wwNMρ}0p/`piemPd~o1bHS :i ttU9wr>_1EHǐo^zY S =]q^|2$W)G i8ZXt03Gb1-"5qPOHŴzz9CYYsYYl6b*Ȇ=MKt^:5h gu"6?oG)( S^ Y⏳ǰ$˷-˲ey!#Gq_,sr1wڪ,?],8tzş^ֽJ 燏cr O؜ ռy:;KG~5 6Yi{ޭpXMq)/z:o^7lAAnCDpn)0 궛s%yьb5O^loxY#cnv>%rswK&o# :9A rquKCxV6n9J[rf_MSpvzK'gRڂ] N?–V#Tr T%,LeTK&-c7*_.[N> ~-ïG::׫jOIY>otT- fe`vwv; vaw׈I%IͤUt˿-QK=yVٝ=,][J+RBq=]_S@uf~kq͚\ endstream endobj 157 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-023.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 177 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 178 0 R/F3 179 0 R>> /ExtGState << >>/ColorSpace << /sRGB 180 0 R >>>> /Length 7702 /Filter /FlateDecode >> stream x]M-qϯKikl6, /gɲqǎ%A}ꜪG7~͛*"(EN|x헏??܃9r`6A8gY"n4e8DH^JY!nT&tDĭeVHEF$DLA,t"'k$mc}(BylQ˳éĉ lZ!(̹Df$DL̹<Ls{󐞴zL̹3Z3jCLXڜ=Lk|,""yʋIf je{YzF d持4[ԲDf|mTD .D\f_ F,BfTJ2+mmz-`{)]fι&zeŬĨD5,YYЀ1,`dYMʑY)*O 8@Thvl6+yy[8KWYfCE߲ؖYN"eV[K_C[x4$D\{_hAAl.D\GYv`y)]fqR qBRi2KU;>1q0LvӸvTm) +Dy eQm,s`KX@Zygzqg%b'CY( ! ḾXA "oG%bT1,6=D[`ud;#tclc%b(Bq۸SZcWDiyt%Ze8&g#&feDZD~J6F~"qzzV q6o`t%b("bdl<rG\f6]JWYfDeY!n3{cY͵Qf֭~GL. ToB qIw]fG}B԰~Cv8An9N2+{>^$DLmOd}B{ e) Ĕ q[MOz@ q 1[{Y".8ғ#GY"&r$]Ml0|Edk=DںqC\]uQqm;bu8jyTpY"RDP G924?-rvZ1r! /==sC=3G1P h`u-r)gI1tk?dm |q;buYBC["X!obGO2+ĵM62!:GOx~tCh eֈ,y>vq;bu9@Gum8ˬoŪ:%Dܼ;m+xbCt%ZJᾊ=^Q#Dú,>GAbzZ1BD- Lt2!RH_ڛ<ˬ(aR2=fXsYf˅y[ƅ*[g XG;L "& 2Of" >YжÙk5 ;meVyg=$`#X;+mJ\׼<>8^igb.W!jk%,#n#0k)KDUT;[e &Jm'E<_!9$V ~ UMlok2Ku%"vlP:cYfb`h߬괟N2KıR[ Gִ*ci1[ klmeVG U.~0sکh,@?Μ[0wh`f;麓vb -\jۺ MCh鍁u017ai(3vVFF2h3g$KPJT9g%bBn~ r-. jz6o|c~N)ؐG2;⶝:"|7,p$D*f% ˬ7 KeVAr2@shhh4/1-xFEhc6W-[X`~́D@7BMZ0gjB2+m䘛 gY!f|"lY!fZEn1sijGt߈*GYM *G,K뗉}מu|k,̺edHzaHeszAch O6@'m`Q2!v,6QRukq䨵x(gSc`2%Jms.MZCpĈa#CA` MQoȱBZ?1;Gl*_й}TrYw1fܬ 5xkWKĵKD/W}9c)@U ѽ=]f9>+gJlg3GSz<̵ҁy`g%``Fȏ0z 5FwwĔ q]GM2!Rz(D\ B͈Ry,=WEli?yd>BtKQ$Ċos WRA2"cF%jbq(uKDe-hq5s#0E>Ʈy,c#l98CܱFv>`YA`~@.roX_p8hauC1UʼnyRpm$J !{5Ew?ڙ$H?=<&Hn7GM.[W(.ԥ"}`fQ_wI/ۿ~49Hꋯ~o;߿ӗ~| !w8Ɖ/aS,O->M(hd&cI)ʶtɎo90GӐnxʏ:r\BRdtt5QLxS,#oRV"\qakDt5pk 4j{psq,Q4琦B=_̵nIs[zom;:M=苇zI݇<ӔW[*Ȉ!4dr. Ss VyvhʈG٧*κ+dk)##}hC^cҡx!4YQoΫ.ؙvۛFxCT='(`mU:rdm7E)gS}qT=J)xuw!o`|9:+cZ9F {-'2є)PxM|BǛ9lqoGtsHۢ "2ypuu65c7~"cj8pm-i/FSlMhr5ߓ:bO77xLhUӔActD&Kh-풊h{f;s "D;uުS&[qDng2_kgnUoOKN\^m<6Lb;6=Ocbp2b"Sjs2 ѐF_rM=wz;/56-hdWW/NιȽpN% uP2pOIj-upBnQÖF 6o{=Ku)ֱsҙ,"ʶ%si,8v0O拠a.tsBFl[ d7Zǎ;O)OزPGC0 cd{MT cliP nw=`FLuMIr0@ 9VH splarZNЋ)p뎚ѯNgޏxi0˰dkg_FҊwN6d~9hKΨ.m%ύ~u7| y.6mjTW{G!8)F=q%=~uWy` Z=}#4r|H:v:IݪѯN7t[#qxn_>tGxv5>Еm<%_N藣E_,,_,);yЬm>|5͗ϾqmvFꍻ6k!lϘ<zN`̓=4w[["wq~ŠCɿk}9ж݄Vڹկ(|\\+ntNf}iU6cGʵEwF;n5Z%4`fF; !nǣ}NhUf]lFp"jaF^o[66^6^m, _"W&KukNCz& '-P86C g{bӐI0,P==ZK-٨OD' M(hW*LO\-oͲ[:dzј)%R qRDc~oiy筢Zg9]fPt||ׂ:?'GV)o߿wX> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 172 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-024.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 184 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 185 0 R>> /ExtGState << >>/ColorSpace << /sRGB 186 0 R >>>> /Length 19687 /Filter /FlateDecode >> stream x}KZnݼ~ڃh l7]] ȿ&׃TUώF[-i?EroߌwWߦi>⿮Ǽ}y=}Ƿ6g۷}9?y]g}؏{ q]??3m<)s=?;s1l羅x]۸cZ>\?8{qt_:9qc>c^cS<:ze錆5yx_|_L\C㟐?i.Dzμ~y5y>cG=om~۸h?},qc9<~oX-Ͽ\},ƅ9sw}qtZx5xm{Hu9q~\g__gc?:|_5.O\F~sZ||7ј w}]zZCegbX6^|_ m>0qxy"泝s|xPNٱu|&qsq ѿ-הw^*cx;1@[l>^|q8o91{c;hxsc|,za|cWo[Rk#o|?q%o1nt!s*cɦ|!1mZjպ%r(#o}iq:@{ 1\H8SiwWA=2FmVZ炜Kc[Tj^jA[?l݀ riUzqEZީPx{^-n=䒌+rߌ&g&]R0 ]플+RdKyh> p?,aoÆRyqm! W_ڂOtmrH' n]Pnh1Z<ٷ  u`P/l7kP{n5Q9Ͱ&*>Q9&xmLXn.mcuRb98,ĒʒMYXBoگ\bq< \%_Y>%~)>)wgM@!+ءѮW6q dbFkFh#'6xZP҈Χ*5CE^vɸ"<"@LO0.'0/۞#8e,ڹ7jmC6 Erm(.V]r`ZrSG?zǕcl,/B }_|ڐg xM۸]HPmel ZC#6n ZC)5TʓH)OeERY)婬H_T~ׯS_~\Km$o! 4Ɛ~BԔ|˔ĸ? m< 2bCA|QWjq\q%U1z6^0X CW(4$%~-Ol[`=:8]},{K-e#M\Jfﷱmp!ۏOm hFӚ^n44x5rM,:dX,n¯oƗּxLm,9h16Ƃ!}Z`vKL$=Ncy^}GIFV z, g rY4=n܇// N-)Wi$>7){(7}Ǔio+boG{emC8)7=>c@I8H!K/ q! ɗ~muןOti/H(1nc-[$"`>SO1/k+k`IzHESõ /,@IGaA8&dcΰ kE?gl]{R 9KF]BmM~k4vs-@kW>Ez˧(߮|˧Hb{ wcD2)1(_ J oDXxwi ˅3r-hA b<7*rm/  P||z}4>=k\< zph AƘ8b53GؕL/@ Ej\ A-gaz)Trqm2 mfH{ZjHQdd8n)"X ު~ zZȿC8q]؟/,a "nf &ʇtK .6:׃79GmZ!7> `RϱE€?GT[=zHT@K)`R))/ìDI1eJS$n@ei21TRl@ 7| o=祂kۏE?KџP?m7E\|wg r J`h^8.*NH#pH)Mq-|!}i5僗|pg\[9r,<;} vP.j?k߇AZ?H[u€e Fjo4?N9rt6Ӏ97x(^ `M V{='gXyv/γ1-_拤l_k;4u>y>01> 77| Hn'4 Dr峛[Fq{Np1".xxCk]#B-䦫l`~q Z]Al6e&l6wh4}ʿ;wAzk]dR0fT%r>x@gADyEÃc<yXg~ /ρ$w8lh밴JaQ=€LՔpqgn ɿ΢#YW:Zlm cĭu&rk[&rk1Ar:U x D^m307K>+26_rᄣf\d|TU2/SUs}N} rmr$^JByQ p"$2E܉G"3_ߥ/(|WU[Z>>oǦ52mW~s4Id׫>0hqsQ:LQ'S!Td 9LAk<[׿ wkCPH4l1l"mQ=mt4у8z >R#"\^)ݟԍ=^/P B.&0+0+>\%Bu B:Ar:0I%B N*!ogZ suhMH&u(yA;t{BpKZJ#hx#ڏ\P~ \KT:Mub*SMiSɄ<5M^(RQaR4"Ց\V{GU7ؐVFYgɛr/oʚPn+ #ĕC"6Ak#eܠxEq,K,#_\o\w&ʵ(`)RÕ!5Xx@lH+ѝ:JtE((<:1z%᤽Ϙ=ZӲߧ'y'\.xaZ~F_)Tߒ"m o lPIE_"hSJA2MfAg BwRn._Jxld:l(ߓ 0Z8=l-I-l r./ƈ*jLcxc*bFKmJ)\L個)rҝambIJMPw=ux5cJP\AL)25֕BFc]6OJ{ֲ ĵLsĵJYS42n2%b[/y%J_R"\Ld inHi!ޡ`ۏSwa?*qr⣹R Q|$|#kZ5BxNF^mhл}zg3{h;~xLzŜO:82G8w4ï^zל;ݡvzzݣEm,+(G ߴGAQIZnovFFQ_a,):%lC4g>.LhI0-!#d-f6v3;bf-Wa/m~OoŽ%Qi'\mCØ ٜN(#VmԶl@DY*W%b,UBZ!h"eh@9as\p1bEF:1Iuml:))Hැ0.8K_I @A@T*.;Mq)6#\g!<\gq,@ya ߭oq+׭ʭ!ːTXF 1ɺ$.ޢBPFQ(#ʠ\ /Pj %$/ 1B;9ȍj iRց\u(iU Z:Of8p:OFfoTq[Kŀ_ٞ QgzQ+W̍̕or>JP颉ʵtJtN9[g}pRr(߾<1+ 1Q6,\,<.IjT-mš8"֤8u?Q;HS ena JU?tA+]p&MYwQi16lsltLc)ڱ7sti:rHPΑ9"Bz\Hd-ċS#hi_852劇|C~ R~> 7jŢv-Hߒm'; :iΠv31 vsX '_ᢊu؊}'}eob2ٳJUVRɞ\HٌR7 HuBP$DBՔʆa 2!wJ[_!WM'YӦ'YIE~{P+ j/ @. Agkez4}sH!W<'4u@'*?1KM9[(RS2HvҘR3&&7%L;ga%)wPY* c:D)|[S:DB)}+.mznN޺9妛]4P;' TQn4Kdoޑ{q OhyK+Xν0{y~yNwhePhP. nZ&/;6MnǦ^v,IJcK'KE.՞`|)kl!l- ؒe_(IX7CZ*?8U?Ls٤V[zkl])WgjW j\a:0w]Er#E\v-$]R[I-=.E/;-2*W@T}EqT_Q<WtxC)۟ˁ6 E=Zn@[r+GyKTڅZT+;qB'j]͙*)*R807R8te|!Xz͋a΋A~@.^Y儖>[_^I.l<ߙ.wInj|9}|%%oO>Rl\Jn\aIy+}{\_Hbwlotigȵ\2Hx&P8 Ž&gIԎ~- b*2tQPJUEɧu^i[6g]M|Z| B- -H#ӷ0mӷ@eW$>LabC*8Jm8Lma2S[[ Ai;)q:snC!ɲXXrwo4SVtEVK1TJ1$X @̈́'XCᨈI\s껖4ל *JvǗ^[x/1oJ:.@L, :B-D*Z8kd[|._z32rEj.ipsa5h֚#^s0Gښ95sNAǛ]Ao("$ɰ6-|4Dmn?͍(6䲯p @bOfa%ꇽC~oӇ31^_f 69QRL0Z-{N%c\YrYoB|lJ}ccal;X91YNLD`qGj1)kQ.+` f@TVĶDYt$3.M(Mr!i`# q$Dz !%rnȹ{! 1O@e23J Ґ ԧ,&>b"cI򟰘 CSˆA 0(VLMVL%ˑW ZH+ iG}B"feXҜfI; #mGںe?\ X~ΞG n#f~F:^q_DF& 6~Dm;JSrB` /,m68I-ZEl5>_b?n+Ũ yPGEh<(FraLYD;ӆ轙662׿ʯD *',No9X|0;3LbS5v;ʹ)CM|co8-q s9Rr%fp bMQ]l]U>kr/5]Tz!|q1(dT9);HvYfܑw͸_v Y_l藄s̟9~=˒bv*倴UfKQt܊ L{ ܊3;ⶏE>rE9d3m&7i+ ]֥TtR,m]ϺT:I:B/mE1rE1rB.~>ucM֘%e#ztKq:8[d3Ko:kWY`4P%pE0Ba6GPn8EGW? ~PnL}[4r ɞ-^L l8f2 ~J|%Jx72?bdJw-EYB;[yCS$#A #AV H2 㷬6`r /h&I![kJJ|%*;+;W+Zr.②ڲ⁑ZYX={[dQ eLLROFƋ7lչ_7\g꒫t g@ 2 U$P ¬>)>;[VP٦GV lY(z/D%3z':h$ UIAUIHof5Hn\ĹJGJ1Onp)|ᡄ!~F7!&d7lZdk Q(lCse ԬEɮ^ ~Ê^ˊ-{*B({Oޏ*hNJ[e)s{%Sβ}/ES?i( 8ȖKv0aLFxU_6 e~ 2>1ʠ[~pZGjLWEа*!j{#(uިuz]Z*$6H3g3gL*~ FA6H.FRcP%~PK+K*VBV +`x =x! n;_kyzWXDy"o<F˛'BDV Du+8ؿy{x%̸ #j{(7ye8$uҼ釫õq.?ƹpGBe|^lθ?-/?pex#2Hol=䂔 gs8S(8_KQoZ,=.>pEEIOdEGIZcMhŻn&ލݼP}S< -x%<ЈI,Z[\*-ݕEy nJ2kpy nRni^;IDiHD4$"( JC,?,JvևJ/NW CN erS쒂 In%쒂+&JMXL>a11jJna/x;Fh/)qJQ1{*$GÍڀ7|j%Vdr 06&D c119JOj-ӓzEc)׳Z a_w@;GGwG>JGw9#7՚4Tm۾!4%e +.Ed-_([6mf#=Ojϯ} tUƺz,Y$}[2R^v~J*ղ ȶ^mkmYRQ,? UΒe[lgNM=- s{L"/GWI(OcIX@e,U Ke,P7 *uJ]-g_逕Br#1Yá?+,K{ey|(Z I*#$8#XtEbIPptJzJjmVgPdl*Ho6Q fυ?S,\Z_rI>]՜9<]r~iX&RsHj+P'Fkodk=$ң\zIBg~k?-WJVǨ}WK=#}WHkUQ%ZjkioY^-֖bZQtЬ*];*v\neW^cB5{6Y9Eú7rPxc7R^6}GC`juj^N^2z&~gRJ-J; T65I;!w7ؾGmvP *[`8DR@-[ \YY,W==o〻݃ʵAF`2ÖaZ[V5'H46"hj%eh`(i\wsv@هLlꭌv/P Qn2u!8/%Ƙ>̀>PJ -|nj+)q$r_n;oEWybG5X. R?[7ba+"%d vZ{cȜkNx2_]to6ϳ_lﲢP~fZZN1݉j<"ٖR;~Ag[Ngo<Ŷx!D#=#xce=zJ{iݝu|VRWvܨ|j6Ϋ_h7 t^~$+^+i^ Ew:| VRW;/lMﲃzEHƼmoz N5s?T;R{jYcmz}p5/ܟkXHNA"wRϡd<Q۽j [Izj3~kZv ];x:)`bSل¢ѫ]ZqYZ_9E@G2wC` )0>tjK)ydʽm\*LRym{9EV#ɂ z aҎ̟)0~޸G[mA28:R)a]&Pmwl-R'}$Uz.:{:@duGR%t4muҿ~˔D:̬Ky\w?Qqmh{G䐠m M Wo<{ʶߜ 1H yfRWȦl.]2Vn 4Sg=k}aT$gG0!gN"^QVl:WYm)5INuoH~KtQG :,3VHfv,`R2~#GjTM7K<ŶR'WjُZ+TKV6T8[<Ә-tdѢ~Z-񽭶q^BG9Xe6PG%*\9{Om!޸Gΰ; WC-;imr|k~/~B/h#qΩakJzyB+lK dz푎{MC/:ϞvdR=vISZݥvz|u`4Ѯ# 휈=o{mgEQY;/G,{݆ <׻B½ǘPp2v 37])~LT4~{fB.:DOA`ɤu:2l+)yc"'Wu^BG]&m #M.nN9!`")iԄCA$S[JȚzr{/5"<~mJXz#ƔZȔ$:7l+)k~e06ap/}[EG/Gfd2VR=?j,m?ڎ~kL*xȑ,T֦pYsleyfb[Iy &oNIN>g9R<Io 7=uɋKƹmڤmV6ϳ_l6$+ 0,`\:X~#Sڂĥ{Cγ_lgIhHm4Gf/gCR:dǃ̱qm}p5/}aW*GY?i/.`ٕ>vRZ!ی6ҽ6o<Ŷ.ǾYo{j_c܄3*m)]H>"s};)>>'нsڧ'瑞Um7# 7tK1<{ʶ߲Ǣ\Hr3I>Qhw*:}VR:9}Z)<~ғזG?:*,]67@c[JF}d cmn9w]Um+($4Bژ〫 Dg\W;]<02Ow8ޠ]Ftrd繋~HgS'R;@hY]>q׫SfoԮU+ŔG>詃FiduAߐ:U{x>@oN| endstream endobj 188 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 193 0 obj << /Length 1101 /Filter /FlateDecode >> stream xڕVm6 ~(Ak%Y~{6mqq9N#)/wEX)> b"-t`&˃N$IH>H y/ܿkd?/b41".d*(s ׇ UEhKms=T~azw[wտߦB"h:'=ˬ;w=7"ɼ՚v;ǚ 9qx\,l,/PXr-0$Ƃ<LXv KisPkPQc $^jaNiR(MIUyǕ18/օTtX8amא, ݺoL/8ImX'(Wuho >Vy@K&'jf> 1H.|kps^rD }5ØڦZ$bbX53H< \LY2ah9E5E`?x  oVB7G Y 7.;u^,B$T҅jb*2J~{w7{{A^6,G`<+w*{X=[ʡBBiO6IjZd{\ j,r~L{fi7"ҧ&AҺU" =;"B<ƻ,R!l]3mDe2Ricu#ݳ/^#0PN>c-'i %j' RUS5?RYKD I8-N`̘qPsU= eψd~8ol?n|OjaZDnT.|ۈG<(҆=3*'XE> Q8:_eSU%m2_=lg:;IpG^݆;Hŧb׵buܟlqvN:\;n3ο盉㍎?m.{ϓ}Pid/ q! \jh endstream endobj 173 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-025.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 194 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 195 0 R/F3 196 0 R>> /ExtGState << >>/ColorSpace << /sRGB 197 0 R >>>> /Length 215198 /Filter /FlateDecode >> stream xˮ&96b˼_l%>-%:fdf޻l zwL& =ǿW_} ?B?#jƏ?J?zǟ_~WuL??w?}ˏ>?ˏ?|㿱7#o _=_k#|f1ۏ>'`g)ziu?rmw#kۏ;#G%1}#f*8lb=ۚ= >؏(c?g08F 6քznI0ZSvc-GgWi+#&n03(&d7115W` xYpd됰Ǐ.֋WF bp`g ݹ08lUpA66{,VGkZ괧[N0 ZH6E_b5kZuv!z̀|5 [ux]p9m鷚?^ň05mXc/ި#le6mbX+WNKlxlT &*eܹqTֽs`6u]seИJYזYslۆ]ZGGj]_ ^ǵVם[vV~4-M-Z.p-Vl[`a )Qs[٨`\fcr,Vmx1Ns 6aW~9 }W-c.xk0wӇa_26`A -EZHu[PØ՚L"r9]Ic"k_ă99WڪhYnQE}f"l~lt(d妫$VA ͈ Wz҂ )5}0XU$ƒ~j߂p cܡֺ݃LFsI*λR ;ҹv=wpvfc-V(AkXڃvXtњ5o+v9 .ʼ.El,_6FᛠjEk_ - 5 g{Sf&ڐ\@\ęoVqQ2aT$ƁChuvNcWs[&ڹmVxd܏ ˶}px~e$kE [krmx2n0qO:bxuI^0ǻzV~ uON,Ō5]OxHZfa_W=*qys>0^'#ܻkGߤp/ ,l9A|G tL|X?Hz7DAG#!4ށ^r" X/{^)>Yx[|_ƾs`}SĻ1'.voؾgg1.İGhaza\?xko~2_ofMb \hB?o*{~֩@rh;"Hï_ 5f6A sO|Z_xZAp&V;&> ~cAGߏ?7Alcgg|rp#'O0s}L9 S_g3wok#EÐx2.0uᜁ|q1=鹭"Yְ' 7o7\:+/ G``'a1< l:ǯ |?;¶_``>u C :o3zb3O|hbV;8@ko1mrf+1>`ҏ]{17ؿ \do}.5pcF/3z&}}=7XL;Z +D}qpw$O9W7;d6>Sz9lxd ibl휟;O<u668|0Q{">_z7~uK^ x8™x_+ߏ. >ֿQ|.Ez[lB#淺I~xW&kO>DL؄8&yj}\ןÂpt1p->~ϡh}*S c>C!0oj9&]6 g.޷ja;Ϭ?8SSH jTtTm=-vh1ӟ?LWHTHϦ彅m,LzUx|}1\M^[l]v&\ld~56۱vV:Wߧ/]9Bo3t6_fyi>qi[l\~% ]WUq~֤b|K|Ui3W `Ӓ_8yi0q֟נg2L~5yM;;  ~F~[WBN$RRqzMmV?aSZƸE <_6zeumKIe{uK^bp7a{Z(߃o|ep!z5޿;j /W>4`܀p|hAh:8;'u?W$uK?WG?[+Z]76zФ1l~\^4,3m}n5~(-'< m&a=;U~`adɯ_]AƆ}2 E^mf51+z2ӸSk#^ѿldm`Of\Y8^/,Tä/~H6]lzL7*M6C>L#|0] 4[-4\no"= ?2f-h26zvuޕ,G (xn7~խ ~#AA'B, F Fps{=bIUNs}c4rl*vѱm'W&(n|=%(s҇,l~m8=cO诙UܑiW;?bQ<__71-y)$7swfa[_&лkBe.B{S$bw~°?CX@\f]7O<˰|Ւyk_y8.i4 Pܟϯ_d"laMA?&0#n/0?1Cvs?zIwCaz2Upw;Kȁ6uB?f7p_:N#{"(LLgPee=-|7e'M[ W;Iln,:+CsS7+*L3r %{_PbXχ;wØ yh3?̳־go< mok߅#gws:o2!cᜀ 1 cԇ.{EO9B4Op4ΜB}agړD~m3[mܸ3 nO+A_lxa7sH5؛ 8?cޏ>"x=oֆ}cÉ+ah0 ~0i<\_kl0] #}ݫ臻S1caO?jf~絓3k~*Z~t5?;}z A-^󫮷n_°_gYGM5>fߏN֟I7x?* z^|ݑ]ϟgJa}筝W۳j'I/[~ȰIO yJ_n|W)lÚћټ`ٿ |<=x#30lxsxcԌƞ񈟝~^eSIWaw1,>xDfE#l~_+\MDw<{6I}a㿧쩆HoxOd_cOj7Ĥ ݟ2ۣ'ۄ׃?6LO#⏍>[ExÐ_ka/"*a9+0b?)6pbʗjq^1BW|>e2l {K4E y%_ɲj\/~>Qk 7Ae%(P~qX#G@Vsl_f}|VѰ^̰C_&\ٳ{=|^&}=_` y{O=f go U3&S!,UHp"FehW҃BGG ?5Q~d_+i$&}+7/z;p10g}AΧMg1=w#ϨΣpy8w;Kv=O'?6d.-b1 r s=x%#+~oͪv?:ǿ%,!`| sPP!iG3I!z_?Mo~(t/cף[ ~ҟi)J_e/_oͯ>ۼ?efϣ\oϗ|xs>&g6}ṡ3~΋(}P!cn8N{lR_Z7|bmJײwؿ7t>CɰSx3O_}6ƏyϺ'{p?@iIoLp}OHO~#{|7녩o ϛc?Jذ͡tJ փ͟'=66ڀ>M/O}kp y0IA3>~C"&??,,ԟ oNW~})wʛӾp}J]?\>mZk mH>=gsݿs0_~aW2m|{M/>4?~'ПK_[wgq=F/| ߷+_(WRO?볢'R?c8z꒯lgf0o}C>p?o2\~2EMa5Ѣ{~*%?,xY~7˩N׆ۦ? ko0l3_ݰ}x&ГI\}_}?,]L#D}R@{;)WOY~s~qu{;36~zO5o~ {ZPCGJϰmĒ_C~s~:kDce: 9a9~e|RDn}׏К?8-`'\?i'}nqr]k5#RpmZ?F\޵cɣ4'3Cw x3U852J_^Ñ[^'/+m?_ci`vAa&`*>0P-_->ߣ_e\oQBKAOe>rEO?#K}Z`C 40Lo-_[( Bg)T8&X;Of2_+ }*Wq}(? ST :T:HԇEJaFQ%OE͟_DSOUnw}sL[|Y-"0O#. a '?Gb'%Gi0>qϓ@y+)0q>W'0&K*˚#Y~~ 338{1+`wǦ͎n1HoO:n|G2>t7Jz'Wy^#Nz|ǣT*RϜ?k/$gckxp~쏙X|'pc8ÿ_#31Ϧ{>[?EbÔo=،//• 0}4<';uQџmgxMt[2K>BߟÐarW'_o(lg  _W-{hf>33=Zx%gNC&Qs>x/u =G+܏Y~ѣ%{9DO-}\Cx2 ?O]}x#~}{_+Ϥ/LjnFft䵽)8Qߏ`(7QW?&gf>1kp!I[o01|kQ].?A±6Ud&r1t,B{|$9Ajv?9uO/H_9o#8TiUH?B䏌v㈺GÁ6~o9E8"95?lP̑}|4]26>''+778T @y <ﹼlEs`;sM}|_q ~ǡ>ɾxsԩQ֤oA :%ɾ!IÙT?Ǟ+~48D{ʅ 퉤')|~@&^~Gҏ|fMEsZqg5 ޏ&zie])ݯ̿_W6zWo >)y,A[`21GT\?^s|WEgԷF}OK|.}?/P^}|JI{iQ~J|}N_{bؘKvթw(:$'4"pma:XO 򁊿A5/Z?|sf|GKc:U ؓPSBÍUKdU  6~]30_h|ស+Ӱkmy~|~0qb{wl\?+Wߗ=__&Fv~_+8?bFdaOf\~l1{B|X8}OS\>|+?>9?L<9 y-2Ɖoz^^Z #?uA>G(nu'._3_w˷<`۩_a1]_Z [!@"?4_ |:S#_r|Sӕ !87/2=)S/^@¶66^T>!xQFIإ3yãק/2l(^B:"-}QzG=h?Z=׶m=4^{RS|Ow} ?(Zf@ prX?8B} e&fz|z%ULǨXY"}0S D= l>""Tޜ>( gǝ66=j:~Vy(j W/~BCϒoWV|?E/LF~-휇J?%#yLz\6]u"vߢxk~A^ RYOEyv~6~D|o5w[ߵ/yf'ɮ/|?nۛc/e_(gdך^>O2~Fr9׷Ǽ;gTGЙ^ǧ湟o!DBg~* GϠlJ/WRufc ^~o9> =6`w\o%&秘IS~~БOQ_Sȏ1?k9!]en5 Vk>5kE}=SznCXयhX'D;2aꓘ _zuv?;cpyV -5VI A}S|xDâeק[=]H_Ϫ_y?U+aXOʠ'?H֩djYl#pT'9˷J1_t/6]ƬX=Sgu"9ۄ0Gz% z2綇%ڄk39/ Yc*9%AqD@3 "5X*56]C\Fbr}+b>|e!Z"Ba(=$nckn&(8hD1\mܪ AaȎp-oѐ˙2 _t=1hr;F},3`8:`n;,yMs+Xۇ;.ezl?mɮAD4I``[uנ d pLқ Qc;*A~nFtgvn/:aʄʌ)'gWoXt+43++:QmowOj#qc?$kYwW=ޫM+͙,9JgwY; )ʇ%Gt XU^J(; {| ewzJ4:Z  G7j {x@@^)]ƃezr)l䮓<֔v 3hJ؞%=H^nкwOa=A>U9nB̥`̌pE|wrhwꪩnp6|>^T۝iLf =+gj60hռ;Ba`y Í{Gzw]t{\!= ¦`bpB+ f!F-p[d̼ݷX#no's`AQ yBsw UW`-jz|SSx% ]=9Rgd9x("z3/5X19+@T^۳ZX&d+X1 +],LkX9jOܳo ۓgwrJyJ&RtPS=s=,|)ݓt|9 frz#;g4B;) a oq81WZߓfڕF:VGLjFD$`O1;ր[ڈ'KɚĚqgR$LN0'ee w-GY8oaij™}- ufqW$g6WyRlIY4؞I)x$Ƅ耺iGpǮu<'>eW`K75HXsdz[ * Si4lO6#c9Ui^AY82Fw*N=ɴAzC$dat7|؈̭% 'w"̠Wl1k/dM2&zӯ|Q#fszlj!ŢњL8yGrz??`+f|ӓcwb zөk:,91 9: L@?YP-,cAƍFd.("8I UX O*>,Vq2uCY"f{>'qSڳp2+f`0{y_h,O"X`X#0Y {f1&%Ѹ˙P;{| pd.j֖owm:ϒ<%*ǒd܃Hۑhò9=xU7s5' ߿bP] B&[̘pŠ;3k~~1&ۯ%> ?[{5MF/uY-ڬ}{V ,6BA/D$8ωo O-n*`旴7h]gcVX֞6PiX1A/Q!<(\g=Nv'] yUOgfU|%xdLb&,fL,Dm|1Q1"U5޲ xRf0\ Wn.6boqMg3'i9pi >l{DFlc"BasT7GU7㥺k>o>)q/dzNIFdM1dx~̋sEk*K~z0'PSj54-kFPX~ f}nA:}t t k, ̏zפhsV6E)}_{ 9}˕YXc~B(Qv#Qed1ׇؗ2x{DcD_̕Dn7ʾvooMsmO#f喘>ꘕ"YwfB|.?JrgZI!5֌/f@QзN3ӓ\nLMpNr@Ginf~ugҺs ~~aìYO6f_XY*ʪ_ 3| Ikk)ui)EZ [KaxƗjo/8cͭ𻬽yؑ,ic"HF^ޗh8LwD0a&Lr 徳=0diH+R`V ɒ_v]kx /bob1?7lҿn6I>j[8{ߛoGOxIЗ$%u ۞Z"_'b1bHbW4:F=Su<=]ռVo-0Kx9bէ O XJfqCmW|14ls+ۼ*+Qs_w1w3ɹ_n|cɱlX:[Y1SV):Ž OoK@4gԡ?)Z u*#7'kP&5/oϬBg.m6FV[nFy7xS JMy7pi/2_E;LmP~Q,ԧb RFK`ҕ2⤕y|>Y5/גۥa[Q[Qw,_΅>[eNVR_[o-{n,~sv2*tz}G vm[ff)C-%[6,nqFF 6C6cۨ?ٹ;C./H__]**ߤIyK'E%Y̒fhϳb\:ISȻKzR^ReNgvә E^lH*^)c?Gq{f+&gbR{7 ze6!zz2%ǧ%䁯%)UܩļC:_ %g2M3 F&#*hL /iG/UO q괬=ܩ{|ΖwLNEw>Z _Lm͇B|sѹ酗5-[ ~KR2gŠ?Qt3. As:ϙ L}r37&&'&=.MNLaNcz{y: [Rӷ-*=GH{{-v:wwB%8s=׉Иdby5s/;~s}ɉh{ˉh{ˉ?˾s\B>qۉ$N%ClAe.pǔ{] s٣\[a%{})_A vD!EK2nosm.9rli[ ~zzv8ߘjvxG3|b;hwqGAkys E(ۊX*.(r$]Ff7 nd 53i+ƝYCk~Ж^Ж^Ѷgoxәm+q /WNWxV;w>ҥdᣯ~{o/X,]1zUND+nC—|J􉇡%?= ˻R_}|']Q<E+U=ĖBV^hwEx<Zt.Մ>+(R_ W2RǤ{ 7}czI~g:16xd0mR d!R^p{|'gGMtGMkOEIw9o&]$LK)~Kl4lUh }TUmZ(/ L8ܮ' $h㺒.ݝ$Ծ+ƭv|=䣵{| 2A\Ubi(ȕh|d3^GbouԂzP$zW$z(icP߇i# ӱg{.,&Pe6/lefcaqʗҐZδs㝦T_~W+Gr4%~^? Kб$'O:ھw?V! hbzU^9O)5V\׋z0v Hc*zSN:(\k7s/)kw Fg} ֧_P8\_o(o}c^AncJIZjD4=s=.t ciOuѵw{!׵D?kupcuꮿX屺{up=onKV=V=zZ>Y An4ԋVv~SYZ@%Ju\y07V|Rw>Ċ]>2cUrQz 7XGw_,ίe8^pǸXw.^迓C)J{(9]H`GC3䓭U3ܿ@@Z$Nix*](N{OZ!{뗵а{~Hq=6>kStks6cmlX6sm{mj\! I6:ݹJyJR+WR)$PjpgځO%˺!'x "6 :r޽aRߌ_;MF"]1kq3z5Cr cѮw}iHp<~->>)kqxS0-EK8S"SŴnG}-Ŵ_.L}1-zޥ$ –txTy%{)l޾V(쌲 2cdgv׸?vNDi~.^˭g?4 թ&g0x+r>u|e4Lr41]jB 5ӭ&ljV[Mn5| gԄ|9 X?WTyNPNdS;Qm]Mgڣ"5*B̻HMԜَ:xT(RElɟ$1~b槹w5')b( &}m{gnǹޅE?̃e/"F/ s Ž/kZت^ݮxhr0׃r.knybyθ@utwQQzQ7oDN(I(/ע𽸟vKw>3먭.[zz(ݻ3{Ze{w^{Dk2ÑW+^\}-]=bӞùG> A z{&KZ 3lǛ}u׹]@vy#K><eyWZن0Q S+=B`^NhdRYa*9_YaΚsŜ5qjŜU0gBo~1PE,z@_ x}-}7g]ҵq8˱q S6;(ٙ^<\=;`%|9i6zl'mv٫)3VF|=Ƿ ^ ^ %scS4 η^)32%T˧.b_{_|{%-`N~1ŁdD;ݺ~yړڍ~1F}Whqe6 H1=w{ߩyϵ17s8~jK)[;F'מ'׮y;5o~Fޥ#˾"v1kq(9 *#ŤW1{rgQ%U2~*I*e?"XDd}pt'/?"޲ɑ{Fe1B.=Sڍ~Yg}1kqnx豯_3(Q ԞCBig&v#/دZ{?{t}dR}k~ig9:kRk}֘?[{%$=G8ծi$&pΙ ]/9;>sUK};*NiEbs>+>.֓?ip=.^ #\ 1 P`z+wB_ 1\ #\ #<(_kp| ß{ow}/5/XJob)Uv!be=,ֱϮ O/{+ h^bh@%*꼣*eYqUFSش,m*5^ӌdZ3UUW"9P^Kr~,;K{, ó4xj7 v.;ZPkޏzz~XJsǕY) Xe G:orWΓ˙^gv> Wܞ!_&ى=_w%2=Id|ǤZ V ].tz܏8Aocyr~;b?_9H;kOJ98)嘶7*Ѳ2'[˪Gjz+u0;$ww:U֙p|F W滴HTrjci_;Oܸkf*q㮙čz0u_:̗NOMI-ۯ=; a5Q{522FiE3xk?gAiH42kR L%<""o@.^%zU*iN|j';+ߝ^;gux-Zުuz#巸 bD r.;R]K3ybyUqw]Uڻܵ5嗹(9e\h7o5vVCi7 \eT҃QlIwstt Lڷ"27671̍yF+ <QjgK@YJsJ tZoLwoC)ȍp2^G9בbp)8}}}^^KHS凇g}xxWXKwTbyT❻rO'?Qkrjy^_?}y޷ߘ n<7_ϕS_nbWzi]/6HLxa֞|i*خ*i1/P|8F<6|~lxUk!Y6UE>{'JJnRm<(AY"c=E}qe.T5/wyܷveۚp"gѾwiٻ=s=)!%nƻgL ֝| +]=v+][*+]V_xg#=J}`JE^*={= Y5R"Jdgϊ:vĵMQ=NA\xZ3>@a]bͧa! 3oWl"),mMeU*;bcj~뮠/yoAe54Z.aG~n>,:\>,|Xvo|X_nϗR^F(hw*GC:ȝw5 (T"Ud>>oDsDsDtڂ+~/؎pJ7&@?N )mHSnk yMi l[.x\x\+VyUmuǣէDn]v$/w[ed_Gy/kݶ'ǝw{:q_ٴ;\;\z灛W8 qy| |H Sanui6q=գSvnҴTvBnT95V_\9y2=OHk|:_Z\::stFwI;ݾv\>ծq{'[Yݚ؟/'3=2#!ݙǎeEv{?3k%}9s/\']ke=B"V謱k}Xd{5}l]EREʢ~Ywqt,#rw{:(#fXţ,c3ܔEmn1 FeLpۉLkF*\_=?2W1W1W=W1s5=Wg'ۼ} _(Fepݱj7;_a(Ͻg}G{z`I2_,}F\όY5ʜ svڍkq+nBkIsگ8:kgtg5EV3|9s=vzΜh[Z¶6߿C0wV'_J{:½~A1];>KC#;.]ϛ/Oڕ^ d?7y uw;3{$@䵴Hj5.\{u^iokԅn:D=&D~w;~8较+aP^a Ixjo@EMih'}P4]4:sM:ÞqȞٖ~ or_Y-\5VYc4R<<4&pj[]?Pr,k7rB_;<)Uh?{xR<ε ?Af齇=ƛ&9;һRz;p A[pdn3S7PO6=JH\cWg  jg_Q:< Y2sݮccE2T\*Ssmmj.jr͓L9t; q%D~gRy)Eo6\{~;_anF!ڍ6\(]K`n{\x5}~A"p #kzmۣhkkfgMw{8iB4xSGNe<>sq)'?(Wr._O[ý{xDhc:,1"ZUNީo ZykCK='mu[á v[+쳘L/+1w>1DZy Y +5 y/rW-?vb'mu"ówƗg|zZ^Ww#fԽ=L:=+ ׌5uM /+z]U<5uy7 n>;AwIΟb^=phuG{ =ݘwcc7-rrnߡ;rrp? N N N&8mG mG = }ځ }ځ }>3{}V~Ϻ{|WUc1ke.Hj% ~l.~ <3 =_hK4̧h;_E93$*L:8'b 0KJYUȒ 3ٷ(n˵n˵vixe (d;kfAl煖KetXZ3XZiiG--)%5bi`i55pЈmEd6C76~:U.tﹱȑ-Vb+s\ !PѰי?SuζD.Qx^>; ar]p{VS:pf%w֤5ch'i5Y6XlhYN̆$$f [\e6W]h\ќka%MO)a)V/v"gt"^jbЃF|ds{a=JU%t 10]<@ψ_="7X#2lI@ZZzsvxo4aIuER#äFd3&/c۔vmJþmo6,n&盉ɰ\y H HGv.W<<^'jȧV!<Ӱ iw%_(/Hh_wɗϸmUp_{G {[JBUxVlھzT*Qe:\O{G{G{OO=}ރ~='~=?~!-F,!zHZon^'zT@G|CO-l_:S˴tr~)@WLk: :@j$dkQx gcr˞F\y96$o{{Ė0o@}Yᾄy_E׽Ro}/+ܗˡCဨ5 H̴g,hdGK9 HێekzvmiX7 4"hDP?A "ho$%@ՂT"A1t̀nd%m$ld%;KbgVY+GfڲGj˙\TUsq)g:N_&'hƼ/O0aعҁRH{@L¦O>eoO>IS=$I%~r7B+=N!zHƫx"u/Uȯ'+^;YMܪNm_Φ]!}͘_C@3 50Tsha|ny(Q= 7P˘cyF9R`**=U3&^%^^+,,´,-Ӹ] Fh"@hb=z1lZ2Oꁌ+ bN1GjOC.GGWwx5~wt{SJԟ2jbj?Y#1T-{ Ud6 T )+/4~-!ac411: Gۻ( ^]esDzW,%A2 @90 GV2A^jtߖv!(|_L:!J|:!J9&_y6U#q !X`OkZ\ǒ͎m.1[2/`;.l|]r_E*kfY{Y{< C[x<BתQZ)]+^Dw3HEɆ"6ioeq[hY!5nMBd.%~R1˝H ]ߐPbJZEP:|:OϦ2|:)|BF|:)lV+>TѧݔM45$9ytR'B&^0em*k`Jjw$xpt_x~ :x߿i>8޿*{N=FwpYK}'Npz7RSJ~xt.bj)He=z}"9L,> jW$V1-w:"+8r`ޫ={U4vA"f M j L7`/E`H}zl<=6F0FX p( w0@ߗfެ~ZłB[9bX jUfՏyLa!uR*,Hw! ղK~/a%Kqpa cNBXӟAx[wF-Xɭ (%jq_E3Ee\t`\tĸ_fThFkes?Q55iechG i^4.)A׺0AqLcpQ~[m^4 r~jO:}Ly~O[cOZV6ߺ.x&ϰ״) ɮR>c)cf]u.SdWcu:0vz Zg21vN 6S yށTvzV,r 9eR[78b۵ RlǼ L\y%Y d2VZɞkRӱ-ǖLVvy~g}m avCX(o-eÁhK x!a;ppVZpL~?K ).b:F ( @$c8.QE]Q.G E=*BB[uzs4ysysy7YͿ2 67΁3Uo7Kc`#Gq]VlȺ[-5Q*^V+emmyXw^5C{IS.A^kHѱl^߶vQ)/DZA/d5/vФl_>-K@kGHZi`nnt"nrފ> ˩cRVoKK/d 6as#9%ԴL5>.}'v!ioc5:)zl.DDyXw|a5pFP[+}K %AXi t,#؎vq~;ZD4ŚZ"*RKhi;[<:JQ!v͎M%]%cq=k4GJ$GjPCM\#M.ƉڜL,Q&m'2i!lG[Es~91g m!?a< 5WiFSm$Aw]#.>R{p4m K,va.8o &Ff)sHY+)k匔IDr H̴cޑFFC$CDDFRpX.وdcLD d#n3wnF>ޜӐ]·XC +^7~+𓚫ӎ |Ƈ(3m7 Â$$Eٟ(pN' I}&+{$łtv!נVRy` ,6\y;s-aȻ|3(ɏhc݂\}e|QBe^ss\F8z(s~.Rs9RoU1/$VRH$Ie .HkrNH=@{<yc{$}N]H֞yɪiČ4biӈ ȅo(=TK{< UB|e)פȮ/)# 4|xAL@]-yװ)I/)Iuz8D"ED"\$R(E75o52 keߐDkHIuil O|^S;*hR)m4ԏm(15mWGv+C+fd)v;W\V_Ui:~~:-R:Xy*N !'HzhNx "y0eSf=2kdӌXiwiw"~8SzTp -SéTg9C+O\qx .^Y?z A.󥺮(d5"T<.b9BNسֈSSJr#ĞPvNu"n݀\v?q*kp$^ln={=wvx6P槹@ - @ - ̓_a/ @~.Z7vA՜ ?:K~.P/scok͔⼿QƱEe/Ր'Kx^LW˦U 5-Xrٱ fm8osf[/d9  սZ սr:ָF8mkO ۀΎOȼOOP-n=n=ki@<@6q'rnnb1Q:Jj֭o3FM+z}mYKEtK2ͩxnNs\8J.\8N.o=\zLOeiQBCI#W<1xbvyb%яu$@{P OhWJN,Fs-7[of y7{ʼr=yOd^6"xO&'H d0lw1 ë_TZ.|7"-=@z=n:879MGϛ|;Pisc91`0OjgLY?\֓JٚTL5`c5qL?vPq deD v7L x4Q=`zhi"A=Uo/|K@K4r!%:J\lvW.ǼݔMg]tZ .%K@KC'4~e^W?=HS 'ɔگ EC3d,I< ?άzg/jMʸZ;(&T=3%#]ugՌtյgw׵򓮽c=T)?C{dGD0Fjǥ4JwkBw CY`[,PQ{"cZ>wmmyXwDԁ5STzsQQqa%5f~*FiѨr[n嘷#]1"'R=-ä+fy)+ ]1btxż ׌͑"9"E$W)%L}Mi+?cM[VGs?p6WJ8uN;N8M$Hs aӟL),./sL^0Zw~8}^<'+ŌetY VIMsueQ-']Ze`0ղG/:z!ziZP%jٱ#z)r}!zj J/fcW.WEt牺bX]ƟBoy>o qkt{G}*Ͱ-[{<JޝX޹}g-2/7]({ZZKOUYԫt/Ww:ֽZqiKss^wG\c~{Kv/k7MƊG\ smoms9<^C{;NvzIw^w2Vvrlok{EiwA^u=uI޴x :.+X.A^dc%oZ yn37@ U*૮|_ZnWUr숿 ,WǼ;/ͽMۏB*%7oJ1}쵷evl*w>a{|,˺ݗKW?K->*ޗQ2*ޗZ}}Yᾬx_6Hb.]mW${&ljfXBڱz2gdžy?)O==%=7GE'Ǝ*:wFNn a9[c[j[ ֠cnY[eya3 m4o6SP-Lf3`3E5O\h3w\=Wϰ*iu^մ,Sc 6Ӛy{v^gv^M/жmm "Ц #y3f3qΨGA;cZov v vF}ItC#K(%ekzjSDE6kgh+%:EOcSd&a̔ωA\A "(Z9RӒuE!(Bf1`͠w1͠y|FA)7ow3wx|$ޗ񾴂e][e%(/-ܷ|nT&UTP&ՃT2{9vXn P>nM{s{28sjU`oΛ99L7Μ8sd^dKgjWGbn31cM {m,gߖviKǼ 0kt5:̞,$`f>(vu%iyOu+7>vkl>JnXuر a-2/۷w${r' @kв1ٹ@v;D٤HK9`$f} HY~JQ"$ekbjk(7.DbsGa=r_96d,#c~aVfQRB!a=B+Ƃf7B댾@`eΈԖGEm *?h)YW 10 gGjfMU1yJ)7=\[Jͽ}Ky;6GfLi,.ÿ=!˒1[ ¿=a3+5-X aiKǼ\^7o!0x_X+@jd/c! _N0%)6( 6Cm|XN2s:Ҝ9 PS$c%H KD:yAH%=55E;w&€`'whk% {X=د-6,JR:Tg9W2*vu9F6m;`6r QPIcllذ 8I:$=]6* i9%P0FSel|%Ptɱ㹄s-2?ees snk⹌z˨x.sz؈&Hw H Bzґk\ mku,k6e:o96}o{{.>iأpveI<*5Ja%vǝu\tY:gwyYPgP]IKz̧5@h{NPAY he5;e3mkW3fb^{h^{@98q'c;31t2r:SA'nN38 Tbs`r-O,@r-OpklImU5Z`+L+bI ,@hZhnL>5vl*h2/ѷ#_x_Oݿi(& V8-T Њm\GUgrL{/[}ۅC8I|9KTP[>ӂlv=0l+~%\Ԑp Eមp1C pBĄn 5$\ԐpQcxv׭-5bOK]ж,ݢFƊ.~Z3Lk:1l5;I|g 9 9IZs["^.pYqYp}:QiKg u?ao=׹? 2?.SCJ-N&L͘ ^%n֫:+)]]*ADltDWUhUg |-]cCwlH<;d-d-D~jD%S3dTMk`>J)-j{ns #)d32,FZ~MqAc][ph phAI$5, ]Rv~ʖ8@LP-ӢɖQPө1ɽ_l9\]b.(ҔRIqXy ($V*K#$H|ɇU&:TIza}۞|X%AĘTA鱉nsVz6H7"J9 Aj2"OdQ0%?渽3/'1]PTT5-4ʧ=aWz0բy7g^iһX&A맄y|%hkעZs8A?'&W.rky^#gD}] ѴI*r h$K=) h'UdgZ~ F;|C y55Ps]4. GuApmkJ7 t"]{JHW %++)]t=HW@_~5_TϯyKؾ5|ͥFy}G5Lt38ieg=)20 ħ <-<y'ϓ'E& tħ <Ef؞cGq/K٥1&tcd1ԼEKcmiX8vS )=FyI6v~0i h M0vŅѥH!0e.F<>7.ȯ?-&aɎ_lZ(gs?9~z0fX(Jr,%QES neq 8hDݨ}}'AH-1K7ڧ'y/SF4+MC  S YtFgU ;ٿng\yFQs}+yJ@_cHu'fX:}x kec%Z n31ou'IIkH:IҺ7NZJ HZBִu擤VlOIZ}$BpVk8:2_9K \8+%zX=8-6SrJ .Q9P<;Lx{@ %N)ұ&u";g YlP.5+}' uoϜ&c$5W4W;cq1|Pӳ؛:'@sOZI6u6zM2ZZc\Yo B4 wo5W2Zl/2ZYefD۱Ii={C)?a8 d aN˼]fZ1/ ^x~Oׁ뵪kUõxF] jݮ *ȏtVZLk:ڍ]|#i{cw:wzlo[{vʚ0/;2i4L{L{<(b6ZM994hR}J{{}kWWa}n2)mv/@  G if$ dIi9Kx)ZLzbvXT̴ܻ:uKɃXZ~ bq# QtKh2(\:`QL.F2:{cdtd+2]8YRg 4#eM,i[=gߣeup a҂<%rTh}WߩwVecζmmOD11 QybCt!c@'Ð80$.dxAD6^Ѹ #/& /ɋf]3z`Ĭvog] Y׌=k1뺝Yxzsuw~sq~0}^\C$( 0A}$\!ףFI%fW Phh+=:N uYצ:&GoZkl5PbOe gxm%V? ݦ/xrT>9Jg_*+۳_(RʀnWRWP 5p%u{mzsW8]]]pE  qEv"&""">y eX Ԙ䠹@VvcLJj/%:s=yE|l l4z" ʘHSȬD-jA6\2?9`55LfZ˼R]$ <x&g`( AX{7S{)-sZ[d|/i3L1nhy%(S&3r@=&@{M~!A0o |>ũWoAzQsSx{Lݓt$LchÆoжgO;۹Ȥ$) $=aCޛOXY7)%%1$g|7Ca_2^ Bʏ33Ftg[DW'>z~qH%~ei_Ar_.tbʕ@!GFe )^!|J&:;N'='=eww̿þÿ\Q(**XQԱ =T^{1ُ@ُUe?(Ŀb݀?܀"Oa 0S~${PZhpH"9&#aNCv"tUIϤg2?>wfAp$Y?1,~cX?qF7㍤/;KaǨ=tǨ=vczh0klmwNH_VNiǕN? jh0Hs`*jPiBaOs󘢏󘢏<+PRrGΏz ZD4vG?iO)7B8,+ ;w2)W4*vVѠ zL iV%sXPlP*UmQ=I~SZ1f8Wi&/ֈ ;)\q>qq_}1ەo^{`< &p;3j/x Yvaf3SA&n$CMa& ߎ#dƀx-'#xs <uD:@"n^@G)hY-#`g{&1D;:/ko ūb//E0̿p9OIvrܿ=NB0^I|ږ$ST{=ݯb@TDTIs?KA]b/XX&,EWb)]\P+Zy" $tWPWpWxm="^[pXqXs1͵\-s"D>aBB48@.E2|/Wȗŧ|)1wBrrLV7J=') _@ />e)@z]J_.P!On< ɫ!NLkC F&ZNӪih><\u>o/3^gLJr!$fYI眂RFLmjgj'V o Z8o ZM0DwCw=/х̒Ncz~ߑA%$gw30ֶ cU!ERPW|dg:u۝oמ*F` SDvRŬ b_#}a߷<iJ)z~SbChkL3[A_# >큐ۥruUTNc=@ٙ9jfFjk`?t)q[=q`'@hu.;vT;s{Vg|{/Sq=z,g$J_6 @4"PG{~Ul e If$1~6[r?4W%E&D&Dtz7]{蛮=MViٴɦF@^7Q@=DDwfґ6ϴ9b =mfVtc5KA0UʰK$$_p d)M1],^mrN n5űKKG i=z#(kJ~p_"W{(W{<}x _(⡑/taf?+{;8ٲmϝst(QiFըE%VD7.Zc0{AF)v@v-ǷDfy,OI2.Y)xrH\"e$a.20V<ǯ;Vٺ? HZm_qw g;8^'q+q~J]#m|m6S>ϙcegq!{\c=]j6N N G\x[m91ݏcjcz:V! o~ 4 :"P\!;,"dYv e(jKт.9Zł3E )a$ox'L{:}i "i qeqeWq~fo(x,E˞VN•ܧ4Z~Ziط6 FjhQ>6$-khYWʌ2X~1=83\}XSk8)EmJym[^ۚӲ:r8zBvh' 'F%3$?q{v| \kjA[zЈ1;qv̧,}>(Xy !t{>>k)صCxՃVuuԼe&zp7 ~30ju]re)|~KL1"x!+~*1$8fcX~"yňq?Nb(`5N2zlws"!ğ(Ұ䫒/I*˚ɗo">j! YHB@!.5!Ua@z|5F'?bHDh(Gh!Nn^m҄nZ#yak;*8[*ݐtc7$؟xSq ׄ2a=:q"f{ vͅYD$CrDף/*SdwZV~f02f[:wzl!oKʹc_0[?xF~ɥ*QS."Sdcץ ;+ `:HAj|aGMhEw{a{*tB}OğPV8mELNJWDXX YV^?ʁXmGrwt >Xk zzvn`d 2N %W31ozYv'U;z՟MSwy0?- X$C +X:b-O]NgzMj`7xlb+#D;S ˅zMȁ(DFPE~lfz ǐЕCBWp ~ Qұ(@L{hL{X2 (<4(cppDs!۵l>2>>3Ȣ=WYd:~jW?s39c?Wlo#7* !Tè,e-,q=Rz<l;cĿ^B..Sևe3ӌ(:ͬ8ͬǃlȐ s1)4Pn2*єC\7%eʵ0sYq";hr-_Orׯ^_xFd)Q%ܲXJP|Me55^kX x b ϻ-n %CB$kZx-?j nPPO\ufufẌtʵr#Tpn5PǂĂ F~k/~gqDNL^#G+~C~2.qr-?D0X&k91N簝aȋg^<"/ӱm$H&E="OF[Z'l[*5ZQ(5k MvB2 OkR[jRӱ7J%qmyX 1ȹees\\F8eR¹ʼh,;R3~>ּpJȠN|R3j;S/X+'}1t,D\BjFoT@M'7QkX`kXFHڛB[jFeKzkviMǼ\\Ji5nޥa=Mcw]2ct)'ԼOG׎mn3m阷`"BxI҆qI"[+AtaiNޯ%;ҎM%=6˼d,ΛevW*H ofR-[j{kK);6Gfҧۼ~ .0p# CCCv<g=D1zbQ0bAG*B $c1 7JvPzw;(Aɔ@A,46;.P= fJ:{is49?+5ZhTXNkq,*3Pg9/r0Pgi;ZIg?H%G* 88fsӘ,[L~= F5Qwډ bf+WNLW3iHH!'Y 5}|5|,Vzl_f1oY&}\3q-Y<X{U [UBk|t,U2qt[EnAa%K?X֤ױVdXno{{>Vyglglgpi,n1i 1gl36363$RÉ$(_LޒwvJ:VJtl#R|,}TcoKʹc~. Ekڎ vk>VJ~_f_[}`zi]n3m阷2d5k:S_ޥ 퍠:JYhrf﯍J_WvyD@|*W`>!`>a`k$3f[Vʟ]W"ұV]ְ%cc.@[e^2D;-3m5,$VD٤>=Pt,/]A[m-ϊgOsssωgO3g_GrQϱ8^l'Tr]T!(x==;Fg، wG Jw4*=M éj ${ Ն€)M%X[ "25s!I_<5}c5uc~[e^2k##5]7[!ʊ+ׯ;y{ýpc6n~st~Fm3n[r3l6n:A Mbΐi"T1nc̩x] 敂3尜J7}En P9D(Epd*CJM?K"|AXx;L5AoUˇƃU{@b/ 5*sYo ֓b=iee![rwbM8pvO8\8}잀0oͯ|x.9sYs\F8q;ΥsY2ǹ,;vwKp-c<}'aKR'-XEvwia_H7聸yypƄ!=ٵQiGVmX+uRYڱރټ1ovZkZ ӏ1s}К@z#@tEVL2| H¬暐*nNOmZ yYFy>e3d" IVӰ2*xVDUL"o:MbR<9$vcm$X)D5n7J b5?cJx0Ma0a#p,>Kpړ.[{|ȇ0DBLq)_cPh>EmVvcXn` [1ǃ1,O~|[m#=5Fzr)sq1ĤWE_E_H4Ղ6sOW.O*f-L*Hx_vVE"$(HguG]ˉ3G.'W{ BF[xzK==>%1W1z:Q[~~]!h}O$S%bvE t^HX"/{bSnA:r|@|q>r ۑHʒH*?E _/zGTA@)=.Rzē*cQk\gH*jsH8e8RC26M}*c!qb%=XmXrc͎us kc^ccdoKK|V =`eJgck@%ˑ g_؞ym`bn#[3ǒUM{L]y?Yie(DYcb<})l%i?jckqˇp_٫*R,no}' ڬumg^cί27վ ~A_!/$j{?6tiK%PiL[*l=|SC}< KN|!r9'>K*56kjx2Lɘ󖭇-[[N ~{EDJ g{T=P…cN^S7 &-\$moxnN+ӌ ]Z_Rvۉr]P^u,zlwok͔e"j5@5sҍP}PRsʆRxMj:V>H¿m6/ynNRѭT0dw=K 4@cWƞ4[q9Xİ KߨJaZ|Rze.F(A5Уw'*pW]J.BYXcGTze1U+Gz 3I5 kеF{Z͙ Լ&5!i84aW9WZ3jcivlߖvՏy^b@z:>kU0ms#h f<,+Z4[8Ip"}wH2 4F48%_F4E# NyXm&n 'V~AX{73\Smz!f@TP8B=p/k ,v%.dċ+BF|y_hBs -7_h vyφl̆ G  wl8*]Jiרyߑe-QTLHN*D{_'Mh'éZa4-ҘmRkEIЌi&Lw,x:JRe[ͥԎ2\yH ➰hGUG~[tW ^|J= iY=y~WNQydp 󜔀GVY6o6Kqvl*˼d,K!?j!r#C4н_ LޙX%ʲ4 Pr>o@|ΪHDI*lphl1 l=hė/@N[sӖqg"=0!=&bhoܚ=^ǡSQjo5hCjOJv!1(' Q={r4 pV&}BkaAz(R{ 2yxt]<+IohXs[HZHZH{v\ okw1L{~m\ 0Lr0iaC^@}?Ꞩ/UbnyyM+4E 6Y5E؍(v#ƺȂ ƺ(E`]y>hk3@,,,D,.Fl$yhHV۶J>y_1@x_\o{&hR;*!EXlEXlEYl:QPb1ӞU/}RPtl#.Lb,Qq#Z⊳~ۇg iEl<$a Ukrgj;1 X)ѱR嚞|,ڱgY.3w3z}a:/z}ŔoPZqA;ßr]ۺsn]ڬ~vZH:+% P6L{:pZ ݅B r{Uٽ{XCý|[wG\wGl)HϠz/'W:K![+BcQxg2`x\eߤֹ}3ͅ,CXέyS4*qpϾjFˤ|Ys<ջV\ e5$V R- vm7\!GA{*=۾݆]߶=v }X 5_N')al@΢ Cr!_"#mo&!kn%YOMj%o4ؖtt[hƂ-|fnȉuXm%r PΪg_"!4RbCPmyi?7և  _S-|_V2C 1k|)ѕo+4d 2~.lk@wvdXRkw;JyTڒ_%y?RBT}!CKQ AX2P0/Ths2jy\׏%zyнؑﺅID/paլPEd9s[_zml#Y󸸯}Bvs)VCe2WĈ案Q-]&.Pqd;1K) tu"E %_B$ 꼈 z,7q7|2 ;UEA`X`89BSў"uC8(O#1),3x.n[0!OVeVe m㓀V~ڮӶ1Mô]?¸UT$QYErבPUwϮAV&}Н>Nd-ZNAQwu wi-,\jz= 4yvw#TwY2y& bSZN"}(6Nشw {2=RSy{{^zyK w>1se,tYM%8 ]IG‚"R()H&)4$XI,|aY-HT`}G1hWnA|(CPeKPǠʈ*ݕQ>\r~)W\rv,W顜U1n[.s-k$cr;A%?mr䖇q_S!* v1%Z:GNϛTuGhU^v ZiǸk#&ZMLf&G*7֖݋9W#kG9W'#DƘBcbLذQ:#3FW$ESQwU6Tld̲D,APF,(89Q#]XԣLe*5~x(BF-b^vNXHfy-xU(lS 2WpQ) 5I}C'5h HlGP#^-?b&鈙3Y2MGABD-"F ;9ZN\*CBͽxfуB^.Ze5ReݵPpvee&P=eu\vU5RUBUM4ܱXUPU/U5;TH@k|AB<#iZS$| j{0i}UZOqҌo>~tM)b Њ ¾ F@,XpD kGB 7.E')dKYF :9T |+MAC@p_F h *ב| )\s<ĐyG#Db#!iĐrĐxD!Đx@ 'Cڸ84??ʵퟤOSYt'Sc].k?ñ!_Ql|/y)\`ҦrJk"$*drUr_u_ɑ~3?WU^oXW&/mkA2 !Z^cGKq9ۥ]gl9nU Cn5d.m |/6  a=/б00XHO,4c( d"E?qC"~ʇMYxncHGl'8v<}yx9D)'јt%g_bA% ͲϩL$J$ ~ )H@9;d=/16R `C>dgO$Vꉦ ?@4ќ}iEE1pe1I?^Q )q>ebEG\Xd5&ғz"B> !BCw=b(wP) b~-Q)F<0YIQXX XݮlgeCllmj9"Eb!Ebt^$V1t)瀴=m90R&MF # sʮ ̐(2(cs \F|XKL(Q nW詳1{ъbHAIIj^p>͸/g`cxB`Mdxx$~~ Oi6JXxǹO[1jA)'Ek~ p/#ōRFiϤT!&sV 6BMo߷Z5IV(yI A s4ʃ ZHniT%Hys8oœ~R@L:SLAu~:`tEOE}wa]@LI0c = JYw*LV;+HyʿޅڗpW;]/M\#B W~Ú]Pð  y/EV r]x0q0aZwBխ~]Ac-|"\al0xJMQ8] Ja}~!fIⲀO ``[AgǔbʵYG~G.E!-eYcṄ@1/c^_bq3k1\bl}銫JYqh* KNފQS<㎹-,.Όt. U5/y1I_IAT""Ċ6+b!d-a^%RK6Y@Kb,ͬ/MT}\fg>L^rw{'J)O&WR L3O~q›̈́ (f)ǹ)¹)a2Y)xxװw8d־=~/ S {9x!Ob}_HʠF\Ϣ>Χyu{=-ťEʣ>Sy*|U. ĪܲcUn/r;U&Lʛvq[鰅ojqslfq2[-w̖wU?A>ϡB'IYR]&]po05zzlI3x܉o۰$`}@Z$ X<$:qqgwS;ZW:RU]4..*jT+EGXd^"7oѪ[ηh-ZoQ9 c]X+1DTk #|Ō8`ek/' &JoɨGd9Q9a}Dv>ja0D`wD*T8Pm#fA=~H#3#>Z,!R=׸.v\ch٘6υBl5rh9pkV.z]׺ ,P"u:؛!++ %y>B+CChZSmt YbQ ʐ m(iJ %[Xl^nG]In] w7l*a!Ej8Q !q$c1^HV .#R gwK+B$2)X/oU&0o x-w߹}H,$l$:0a`J-aE ǰo\_)ʡgDvb!xu吏~Zο3jzdܞs0nWzQus&x_H3#yf7 4J.+>VPA( /P/EaK BdHR:$tX5Ϊ/)`2ν *tb!߿Xo)/Xˍ9]nܰes]?_#7/"EvwE"f E@nֱڗW;6_-n~Dq_V F\-nv VV},c9Nu Mb!ӭX7cx4@/*~VyǸ Ta mTa mTq0ݯ;+ᕠJ0J0J0.+++>WRJJ7#߅Z]Uྰǝ}Bv/zmZ_?nI(G89lsC{}eG;FKFyiǸ ǐ ܽc5w=zyFxFx,߷[f[f[9|[[>s ]0HG>c$H_:"μC{z=N@ $ =S^~~DU Xjx[YbKa5Ԃ]j./n{|{I,{I,Pk^1,\]w}HG>\T*bUX$Ss~910bj-|ja/Y̝A~.sW ":[J2/ /A{,[v3 w8 43` ;GQ j <- s PA>0ڤ[fw?ljF P34fR|2+f2gZUW1.R1.OーCl5f/G>iT"D# :GwFP:T*wI_#lAKב|6`f-GSJ4IԂUZH(+1}UZÑD6ϗe}]T4 mQZ~ 9+-̑uW>>gEiUQ^\cv/W"B r|VAηF9>-ّܥ>G۝qa_?h^?!z#cվz֤#2uH{WVCB k/R-vv}<;lCIu(+(+({}G"|X銒*Oj1җ[tm#,/\'BMx$mÎ@ԷŠ x?Tp[# .]W8bWsENm\JFݭ<a zmY_?ߥ#o?ߑ7n#9$⩜) sw <';ATA 0SSWY&Q +M!ˆ&+E^:tG'B'`RV b T+HM*5 93c 9z}$  `'-ǷauW Lۯ5 -\yYYFe eܶN-ݥ淧H*+$,NFt"ilf@!JqX~Ij,fz_BY@ipyxZn.&pC;Ձ{EpE.#+&܅.NHVM\<Ÿ,Z ubz:@OZ/NOtB2S=TχW~0_PD{>e5 =n1AZ5VHQ)+*rf([RɊn@eD2j5S|:]ʎҳ"((=&5Pzgk3((5G8qr1" D~.t&HJHJH(qɐAQAx;],1~ur庴)wڿq_m6a'~5ʵ%6%7.miiY'ٔޚD.-I4b;)+S#Y_ l뵱%i=c{{az0pZ-8 FF?테~AK,_~K(} 4@'7gGk=rz$< ańZ,/2A赤!p_K*Fɨ#LTiyZ,<}$ʔ$SuE +KȘCS&̡ Ќ\$"#YƀD-5$9 AGtqpoI)% תk-q>+Yo>+xBY[q]|}4Ϳ8n1ݼWիœWHso' Q .bJ!ӅKlHLwR{GtV `ܪ'V '&Hy>>i?E6ﶥbk+غ/[hمP\().W,+j}7ѽX@`-PpVbt\P;K"նc;jݕvYRVRVxH c\3K\7E! @pJU$XU|$YF(@B+par  OJG2b22Kw_#@h%6 ߚk ͊Sl+cADR{e8yzO\-W ~FV?s_d#U#tht+ ) -*o٨?xx6QJ(#%hC%?zhQyh%7E?Z#$Rjy(c${1R,1R,sW]\YOXg~H =d3QB!lOuUBl@ҴUB#ߡ4Dr Ćq#oj\,ǥI.ҔҼR4|_h%$ؑT;.z1`o=_㾗"cJq!mOqD ߷ bX;;.v6*.v)MrD?8^wGL*T7i1}[u5ТoZmr X 0܎ ǎEx}UsU<4fT8}IgbtFjNj"5X1k󠷘ş7u/ +VͱbQ!!o^ qQ;i>g8 Hi`i% /+ ^ L-<ӫg$Q BL閅L x쳫XH%UFЬk)M<0G59foDͫM&$rhzWr`h4{^V(g/T25nYg+󒳘^~h@x ,*6\n8!>Tԛ'K)TFG- E4bUNb-J);)R>ٚQʬ5G:`0G@rP0kSrr$GeO ?KDV$GDVZ8(RBbeb;tq>l lzxzxz B!HkRݟIj!kXu~ޓYFP-8#.#x?G)Rkh<miiоVv(ܗYԒkli\׏ BGrt0r"9xٟrZ#Ǒk[H7oRZ1P+]!]D9ې}2AyA-A-1]DB"CbQfn'nZ۩TlkGN9hRߎDqxJV"A^`lZj{k%Yx[5e0HceȬ,cX"JCk PC%+mh~ҨYM2vR*WņUXsٝ~r.{.ǁR,.'ue[d[f{h4aN'Yx5b:y.żθq}z_"o?{/p #_J( tpQIҢFlQ#x ې ~l72ϓx8p0A?`AĜzf}𬟓ux}qjjt3jӳ#gS^ Q1z6lzг=lT'Pljлqq|Y;޳~g& Re4Te&J&%K:X 7$"^EKG ҁaCXY^qFe,o~+#4?RNwbO=\Uc?&8V~FtccĪ-|+?ʎUpal,zXUc O= ǏGꢢWe`*7 Nl3=w1-Y+> \> \~b\T1YhF|oioؘxړjdW]{B>4+}Oȇ>#6EYr!u A#B4'mI>lccG|$0ۛ\YCS,$)Y V80``2:kpŝK;׽;azp{>?DO&͌n1C.GLs3+d`SȨFEֺژƩc07i&w U],/R :(C ъ<- 9?+H@$faB>Lvb2Rlb!)6xH^+9hoЄ k@sHCTJٛ`p>+m! ~ヌ|AFA nGGq^TsƉgN [-B{#9,sXaR ~?];2nu-FNZfZ+Z;Zkk-Kᵣ|1WǸmZη~p^IQjyQl[n-Exw4)Ac«+1m?X!M,&aWG ֥0.BFaa==>iha}uc}ʺϲن2BO$PQ}yMXHVۂ|~p{b^dPj^xʁ|7"‚J+($E ف^X݁^ԂA/jz!-H'P)خFs&uw7K@yfDuMρ5^i% ֪1 *1 Uck.Yo Dxgv(<+:Yi³,yvcbYRmԚgpGșVZ!I#9W1ʵms~?+q5X 'ႁ c0QbW+FaI( 6d fFk > K&n7oSXLJp?C#$TZhPh7lSSn bܖ^, W&^VEAƔq2,{' bO/XfNc#:FDŽ V&0=U.bXv+3j211i햴 ̪o3 g{qƌόYV|Yc03Y[ pC^֗%40tN~j "!?C&BJ^<0So^T``/P`J* 1f7EH㓪nP J!0)5#zER^Ղ^ݬy_}#-oDoD/2|a);S e-VbJ_{⊡+sRl$# cFetTR*@ǻ#pY6]1h41czޢr"TE4/P2è㋗ږvz7'wdi˱AO..r^eƄ/Zˬ18}D!J(DyjV„Dե 370!u +s7ajM(ZG?kY`YFqvuOTv74W*%U?vee(BȶhTNlnqp+7O퓷AXh$k bA9cq,ADMd vԳiԳ;lA(p"7R''h,:s & 0Nd@,@,ܑADhsAo%{ # shږ5AG,>Ņ>8qqߠ7#)a^SEedo6-'\eYt-k Fњ85R"hHSXJpz`7zhoΜkn?,i$izZ>MQ(f)%+v<8),a $*"/~F&Rz7"#TJF;sIqz.m%, X 0di4$8i9fm?b;N5AcW/׏" LB^Q 7x) k)ѷm}zL; ipݕh4,%併DCZQ!LL<iRaB&"ؿ8yTlE G18(bĘ ĘX1DIroƊs|q 0R>\ -A~/-]o#i%A+Z h+Mz -zB,zB,\ĝL[}]D"joڧhPo1,T *@ Y6h;h=fv@ɰsʱsq4*\-/HnҌ.^zE(X5 X!`V%$'ژF;3[#BnO}yba"-XB>bF?? @-L7S6`!ܔb_kb~\.љb\JY#l=&ɳӓ_ G@QKjFF-&mubHYΏK^d^d/6H$s\8H[(-uHoރȷ/>y!y= dT5@1<\!yX,dpUa%PfsT%X볨7o+YJKgR~7C.R܉텿N":.w!ڄܝv,]$qn0& JڜXv{,2V$GoctV4@g`(iIXGPtCLO\ĕb0qÁ;$- i i#聯3A#4F^ :^ a&,zwJ$.+GQ E n{-$:~/7c&)/ `\/ ձp:&=d&ʲVrqFrQ6B9)|8UKx 5bΕ{:<{y~f~.*Pla ? ССG r"XNq")xG2Nњ(Mh}j(jV=I0qXu)œDžZ/ԡ^X/8s 7G tenK^۞#s䴻>Gn?=Aj^IcBr4Ɯ|'=*Hl|_IĶF2 =|SwXaB dgɬ岆|PYM0yVS5=) @;ȹ P(Ҝ` 7λ9Ft AdVKX_Q=*~M^G8!OaΘ&k&^II*rRInN6<RƓ6j ɄQ00Ld`J6MEMbJQMBe괺'VWxI8ꖶju9(>r=ʈ!vl1Adf:lN~vuF޵k Ff& ȇ 0o'o8eY[xSs=Rހ2ӺkBk@1 .ǔ/T +ܖJvՂja`wl0؁ Bb6hĚ൫ˈխѮFɲbbrm#q`cw*\c_%WI>᫔P +Npprj sQ"bI:A{\wAo3lT҈;NX&s&Ju˺5uk>[(or7_P_HFO@VRm)Isk=C@DWU(<; 8cq /$ъSj3lysp(qq82pfq[G2~t+(L2&TPIaOHae~YY䖅/k_cF>lql32ϔg|AArВ͓ ,-|Q4kq>,)h7$痆A_" {sO=et خ#U8<=چ}|X胠S'GHq'1v2=bezʴ E5[cTT"HIb9'' D-&jklCؚek_N҅awpsJ룘eQL`ŔrwkWxj81m>ZZ:y82ovNߴ]GtRa ֈqRx}bի^[HI |ml#i˟uaN2Mx#$֢sKp;^[wӦ}'zml#YH[:}O* J .JR<7L^@0"Q@\,$',Ŵ<>k=zؤj$ËR5NjEBȁԵmA]-,ݔ0 q!czAH:h S "; g wg}<2)DQk揤2%{`|~e뫭ԚߟDؒp;$ȏ}-VA.Bm/>~61G?{h ~QɠZ;EzX"Y)G^"}}1䥶qԃϦrT>_(U2ܮv"-Xj'1%tŚzx-zgX<CM3mһ{7Y`(PV^YL#+wE$r[>bGgg3T3lSl<uUbJ>}j8!jXC,S|&0Ce|K XS XS X='|9246A.ۓ6( Tt$c aT"i? w_H2@49`\UU#фdD%Ob#S47>3ůo;49.cwzԅ8\y `مdaFMĐ&./K%7hrnK0.`@f]mK.Zt/pQnӝrΞНh| aVYE)3zz-=)Q(̊Q凼PƦƘ@uH49XkjFjZ1F]ե_@qg Ӡb?7{IIJ/gn[Un9n1J]5gg}ΰ9ֽ ;ƺqEi&Y[)u,/l;{)/;X Ƥ19)G=ߐ-SjKq-T]Ky-:.M/wh-H٪t;iڗ[xm#-E_[ty׏G6: ~g z +n9(ݚli-.8RҋҶJx CF/BFjcGVHbʎmcGbT Y4) HQYz?Z A10~xDj/rӷgd f'(CBb&>l)! S/|Ǥ-Ւbp"#8qPlbe(Y\U,,f 3odog%GB-FU`ըopV0"bәxɘ5N[9C}#,|X`.HQ̇R-ePC4!a#s,}ѼطԂٷ"=yf co΢{̴o{hςH0@اyjTs`DjL p0;F$ q L*)~W5(ӏ3ӎj)u]#Gn2Ua6 ,Y09-JzbᒇU-=J<-'xgG|g1boǼ_Đ_;B~=vnDkvrW@,W@,W,$$¹HKJnJs om!Dβ)09<2 ݊hkTYΆSz2Baua33l:X2̬}<!X2FRs ?$_V?j|5e:5_;yL%sɎzBLrqPpCu#2},Bm6*k [-Zl;G?$*_npvԚ}irmj#ٟqz>ہ9z }."̄#vq(f ;~ ͈7^G1ۮ+LUX1="<TSI}ܞ@-@-MhnPԎ@<Hq"ub3!\G݃VlGɢ}a?<=qV-|EUGIƭrhTUMci(fβyᤳl^8,Go%o_*oXM 9}\Ψ`*^VBe%΅L־/&!45Gċ B r$Ҵ;Um}1 Ɩ\4;~k&ڴU"ޤhh}BJjr3[$CܞV-V-ona"4Joa 60%kE5,uQf`L4V"} ː\2$Cq*K~BU]*!(WXV( /RtZ"-(ZXJ3nr}uy&z}TŨ!V"x+C{q=Ai_'PO_%rȅC._BK@~; +kr79,ҒTLb!I xJbLMK$/FS#|Y\?_CGkH 1@gԂnjDֹCEz%/D<g#<|d# (2LUK2kvn۬ O\l EÅԂCQj(@o`>ϿX+Xb__\dz_2hm+CМC;Y_neۑϤ}1Ί'u#f<@XQyG dW,nX6f}k>}/zzml#az<#ž~?0uaa7] M4JY6]df!b1d~W֙r0jVjxD]l}exE;CKxDyiǸxrKkp=}lⰛub;c;[v l>vvԑ|,7A 8d+A3$P g"Ȣ|$~$611B9Lr*n?1a嫂.~XzU (zCJoh%-NJXN}k>}bؒgG}y^{#8d'2V h^dTҾM|ǣ}qzmzG}_+*ߎG DGP#P={1DoGY}uv|r^Dž}@Dt lN+$8*%}KJl:Rq7qvok4Ϗm}%syvso9¾~REEg(m=y6˳3<[9߅ݑ/=zmEi:Rҹ+|us v~-3s-G׎u|sμz^m}g7gq;X U q3+,=,VЖ #mX!AO  %Яۑج~'6k-wp\#-va 6H8 - ihp3hJ?(ǩBWS:8(%(y1y;忊A RtUB8W9rL,5-ʂe'B@Gދ 1HZ7CW k`:noȍP/ j2ihT w Bp&hzͫ=X9K|#-ݑ}skg[ϧd}h\oX.7!쮨(Bu acP4U~KcM3sa6 }&k=ҷ{kw}[v-dں9#ca % :2)@v~.-ܮh_h鵱%w󸸯7 t)̂U7:`]Z;hzkԚ.}qkc܇WǸ#=˿$˿$˅>>_WMx!bPjI 0<Ҥr`"5/}SMx${yws^a˽p/+˺ {ߋ˼ ½^ nn{#v/{{Y^f@V;2pSyr|Jw9BEk> /6G2ב|ŪsG^fce*/3 2/2ýL/̆e/<Җq{{^Xs;gZ^K^^feBT空#F9{O?{۔k*[J=m^w3x#BPLu-v~U뫭z'XzmlmxKvu 4NUmU|^G}۷g?~.ߗooo^}~oa|/{T#N)jyFlj~Fjk5".}8p[Q< x2QtX^nE<67 w:c^^z0V{^?{Y)boKý\Y$:?H=g\XjF'1}5,bGJIؒk:Ҏq{m_+S/y7IX3  =ϒSxy{gigiYZxy>KNYvxBܜ%85tF*dT8V0q˖ɮh_s:'뽵G} i s ǒXUU[]p%YyEn}jU[sh_@k&_Jc;;[[[wlwlw ߱1WiǸݳ۳,+]7н]}60n,,+<2g)? jU賰垅KYJ 2n%ϲgYghfU!j2zȬ!2zȬ!jU=d^YX_Pٕdf*)&fK߱l65bC.Thk%էa}YJ9߱R;֫LD߱ޱޱy{fxǦLDwٸ1W㒉IOCsn83D1U@V?eoÕ\EB6ZH\#g|Nґ:}uHgЭ;zn1uЭ;[G@uW?+nL \R࢜j_u-ĵHVYs|֜9mYsz2y(5ecifCrjy#}MYS0Wn)h,#Q2c̉bu`կj}*E[/B6azme<.m8_k1`8sF 3`ڕzȀ2lvϲnϲ³,|@ سeY,,Yy,x)YIJhf|u$_f%g.4,\IڗfJrom8|4RLΩDY*eH}\`K{+p_+_= S~ܲlF;-:Col5Wͩ;|gVҳ%ߘ\|groב|;Ʊl)gq,,=~GNMK>'q;m^VHKs*.{]%3Y=}W-{I a/چ{s}<Ǹ}b.]ܗ}RO~q髖}$ Kq]}ZJcc\±RBtb#JG[tX}JKRWiǸO(zPaIQW`Xz4M.[KS`Kʶ-^֘IedȔH獚 2W@&ж C=0Y4Ƭߝֹ'8Ù8 i_'= =quWk_zk%wVn=L:=K=K r{egٷgY.giYZx>#ەƤAɺS|]}!`.k.qv]GJ/[H_ɵ _'ziǸ[[m-av-o3 =~{>5=1go b+'v=ᦟ:ǸCl2 nh ylA|S[B_JwF 6ldc$@ɓ`19Rn~!Oq0vNE\Z;Pvϵ:y\$eubC3ɓ"6HE`&O^@J\+,Bg,:V4ҡs n n#LUBh[Ki,g@W$[F.Rb-LJcbJCI AS["+dT9LL6D^8ed5xUiJ~!S{r ~os\ \|΄b.Q#drպR2/g]6[u׏<|yx+E33CgfIc_Iʬ,ܗ@ڎ!myX_?/RB-3L~7K_\Hڗ~w_R#ž~Y7VX5vt(1GKh Pf`ը7VX5F`հq4D/$e~x@ɻ>pg+I e-Bp69\K ve+YI֗ږ$z)$jy8sT[bRzkY,%nX 9p3 RI;eb+%\ېroבb_?n\G)FzШlhhi-BxUj*5i?dD!WMkex5ű$"P.5-4"M0gmu5.HXڕjɵ4*3XA7%h S\1i-ՎU/prUܓki4ύRQb LttɚdA,9:7$ғj%;e"_/赇"轹}MZI7b:"-(4Zf վj$U|Zzroqz-SxxZ浢tqXCIRs h͝Ik[(9 i֑$Z^MqbLt,-^Ea#(J9T$ 8J~t@if (-+ m I6PZV󸸯'FJ:otM=V_L-rZH$ a$:_S_:_~MMW_T~y#_J"%##/zn_V8RT +)8g9x^n^3xk?i~~-ko6$F,HV҈-t x]\,aAb2r$6$7Wf>i30-So2sq;pN 2Ȗrs6tv9"#D0C82E0k̚fuQHq.!{1%"%7:| | <ž{x盏k{{sqʲ0˯:~<-U1ӻH'rF" ~j*R\%Ư|‹ƯONڨ+;Kboo~\?pMձ#)YPu1J6咳ʫ"q[\r䋴Ҭ/}qrm"\*i٪^,k٪>,kG|\|;qs4u_wu_:w|<\q?{`QͨnAn:[_nQ"G8o7w8*7x:(;P~d{n?$]³_/)5#s ]NCz!krNo;Bn+ 'Rjp:$)JQzóYW/Q-?Hy86J6|"J\MnڜL2m?_P0.2c1n1na4&bG "ywR%w[^H&` 7<瞘݇3W c*[TqQU91@'dN 8&?;8 ))k_/*,7A[r,@N#,/[3 [t[)n|1Ƙ(7`OFs$EyPQϯ2yt@L:t?Z`5PNQܽSܽ(^_D<\߮k/+&yfrRJ+:D@_qT)JDa^92CW_v"Hu٩^tDE `{`ŽÄq=b0>'ℑKNgĥkPM@ui1LZ0(;r]$.Rrkz5#Qtt&v.v$VDѽxh8Bi,j&*H)JX!` Hpeqɍq-t-lx]QGkH :K3Ǒ.ˌvɈҰ>9 I&?ܓs[D ;-=aENs~Si H2Qj #!)*Cx!~?t9;Hk#-iy?P>eΒ&0ooZ!JKAHp8^)i%} O1ͤ<&bN7w5?OƟMpM?G^{oy崖#kiTq$gۤmRIܤaQEojR%<#ϛڰٟ }*B&8xlvlVAQPDJҙ"E^kMX +Z7jXI+‡,[eK[iSv˴pJX#}i,׶ܛy\K^6O VBf8\WÀ񇃇m:i afW$za'ON!j<qQ e*#|ŗ,JU Ey,2 ׳ UK~sw/]/[i\׏"+͕|D3'4:Zth#͜|Ds%ѴqG^a+٤ 8 Z0_WجaPmҗVrmkɽ^U18VscAb\炍x?ϥp6V'( a Kѭ@MR6n;Cݟbyzhh#Nk֯ǭSAIrL+LҫOl;>};~u%. d渀NRѧ4>"Pk7TQqCG# Dӑ$,g#I!BE}/ |q$ADI@2Q=O[ڲj 9o\uk͜" IH_3/s&hA㇨*1Hzo$5ƍ< v19& *7",t3-xf LXKu!| n!|n xI5D2ѓ"jk`S}ԑU#Ց 95 ^: *mr ߜGgJVS:4&=豒Ep`ښAmwDZmN¥2NW/I,!!hH%}ndcM!p8UTB^z2d?%UqQo5Bj!ڑi7(7Jp!Τ::pk09p4qe☺@8Fi ) !g0֚<#A .\UKo*ʥNӄ4gjIl;]o #L͐-\"\"O k7 gG)-`SZ(f0A\!+k%ڂ{|vtxѭJG>ObCOk@ίqhS=xt3r f.X1PHҘ)QzР&ouN[#:"V}~$.IĩR(߁b/4}Lх*uas`R 5)q-8qOl-I~-h`c%uz{4Z\)EeQ 6?sty3L$F h c&;׫Ix34U_ώ{6MWۥ?/@p Q nwz;ѵՈ@GysHsnHnI>贓Ɲvv;+F>vY|,Y~ي+S[8pP %)쓏_ U2}gefiJ?"^z{jsq~DLS ~DiY?{h k=k Hk}Dz9R>"5e>"GTjb$h(ۯ "^ՁpZG+J ~Z<〷}mhf0.&t:'"E]J=C!G=G0SD2G9Y~y vZkhmDg銌y9Zd״I?g.XG.̛yCJ IDN/b1Wޜ}:bGusX pa 8~XJW96r"ꞟC<.acD 9P7x"(qJ |pbz2ppA}n BΟ>gu#^A pX[CG¥ΖDB<&\sx.}\ob/XwJ^2=d$^oIoCkbQYJxUb\.dpvj"5*mQՖouA;m NDe?#.wK;qfD\>ET).IOS|Qe4V.ܗhFS,z)&0<,zbWiikزzXZ,VJJվɵMXm3OQ&^(h'L·.ɩmbo>HFSkwlNX˃,}!,2آ-(k+)B@E]8c֫ 6#F'S6vS!lfvd!B9b1s XS(5*wVK%/ԴԪ(';I_ [Û?}xag4D&BBh1\{wҥ En%ٟq3}e7C?k1`o;RVIWHq`o0)>O;Weݹƒk BSA-?#ZOyW5\SE\׏vKQ$/e ]X{z:I_ҚKVNXh#{k=cF;U 7BL*$ۋ`fưH H_בk[Y҈qggYWgA0}%',+gk2³,=>K%]2J ,仔{Sơdt_5Y2%}1%\)zoqQ0F%@Jd]X ŪBd6X]Ø,y@[$$.=Z vHO+e}v v@ȭaׅԿ,A/^lwz1A{!hyߋ1*]X!,_"icEr`Ak!Y-DTk0Dx.b_8C~W>QU܅EXE HV)'ޯ%J] ŀ,--{K$#Hna;dR Ѫ/'<%`i>j*³+y!Q%RY/WRm˕ض\!Ps.H]|уw~Bb]BwA58b!j;'Y<Y.Q٪`u[gڳu0tZ^{vS{6_#eZeD*P9%깅 s }ЇSM__bpA-))(!O-VЇN>R">ӏӑ>r:YCZ2VBZܮ~7˖=x/Um"z)*GxrBTM%n'%Vպ.VO9aW^%l(\";k%׆븰7KxŬ jM /[xm}㩤g^@6Z,uziǸ;óH ;dCiY@:z5/[,V㑾4V=ܛu=@Ǯ뗂u~I DXޏxRDXצi5 i 6Zr휭^G1np^%*$`n=Yh &hEt$轩^E}øY #+ SP߹dJgb3S N"z_a>Ym%t>CB&r'Lcېi(͝ڶH1vy>|4=~u?aj 'XDGVo:~=h6TE[_a4[;[ݟep$P"-"-^)0ro:$vD"JK>s]頙tpl 5]B)>ϣ[M yF93QxQ^=1KN8_WQ;o7YPBPCe=G][܏Δ2{ȭJ~St>=g#1 7@n{ ( ӡP8B+4aY^SOBQuh^$wj \Udw*Y9ofmD5ܵ+wa<ɣ<ɣ<G-؈Fql(ixTr:nLُʍؑH1E9Jqrj8<ʉKv 69Ppdф(Si>GxOW O!!pC 090Ї-pDl5[ʫD-řc&f`X1mXNJW |eQ;w([:"1A#z yOCcáaM=N<ʨ-HQɍ[젎nܬ>7%_bo):OI r NA٧o3-rT>*S[cQښ|^Q<+ {\ N8UABMbnpK-YiȜ٧eL Ê̵/.c2=?`){Xx MUXZ y/#/ ae7.Oӽq Wwo|w`~:!t 2p$+M-/joPZ 'vPU#v/2?&Œ,x"'ZC>P>Sff WVyP Nm|#k&NhЂBj F5T3-`V㻎п d|6!~s[="dZpI"TMM\#q1hZQb eñW/-\nk)m!3x]1 `M!o0Ú6UhVO'5AK0ci1$1sw҄ p8vos8vaSA&wLу Og_v,h?_?Aox,}$aqTNpF’nDn :n "7MT;g ḣS~l–]"ƒP8m7:qȸ-v6\@5Q,^;myZkGIhHp?᫚ Skix5ű ~_W0hf mZRҏnS ZpOwǷ&N/A) Em1V9VM\_Eu-vMܛu6:kĽP0tp̑ZUmՂi?|hfWsceL2ր% FX-[AeoqҚKw]"o^{ `B:Ҿq b˜\K 'z[2a70]-!\U^t>dp&&K\+[=Kq8 x۲]P3j`5TBSI[vy(4d0o]#zoX0saXˆYr3 h4egw Nƈ9"V88X}K{%b9rNUn29HP`&\)ոXD-n?q?~CJoQ-2;uHH#2= i5]2fsg}q&g)患h{| P @@!7 IPHς%hx.ݵo1\D5a"ԐBl[[BdN!⒭ IA!>ӑryi`y`QЇ!Ļ= iàwʂwYoa#bⰑR1qȿttautnN 7<T#+Q@>Ŗ DUPkU6\g99B4F2J D*Y+e#k%a=zdM96>~1XG* W & s/1/;Ms!4aJ4 ]!AB\F}.k_‚*Rk8fcjH1ͫrkwظt\^.qǫqcDtx# 7F"ѭGGf (<2ۻT8v [laX4+ľw03Pj e?M^6)e"lBK6% I0ƑM`JδJJܷҚvR dzm%{k}׏өRj[v XLOS&uD\dFYYl"+EȌE/f0j| lB6Ѐg  #K3TXRxf0UKgz k_k TIRroqv[eS`!gnjOэ ~"6H\+3vze=eɪaO $D=ozdڙUE ۧ͂[FijӉÖ Rn7_ٚ)6hActTdTTڳ롅={p41l loooXoڭcܘ{3p eoua%~NwfQy~ߟDJ v($o'SZv8-DMZhpJ3,V33xUlIF(8ۂoMu(TspcF.p\O]8~.iM. or0r`9-¹&Jlo66;6،o61ހ݅Æx6RKdf-f}Yfƿ % `m "$tP:ԧ|Du+Zh灨x 5_`R}L IK gD}H/?)BOJEt/DޑZeEvjEɇ#+D;X!wD),,<56֔o&CCtdz*>gƺ +M) `o_G-CB``sMb^+r0r0Գ0Կ P7s8<;G݀v@ϝ!8k.Y$]JFnvC^;zg g4Y52_xO{m6JP^1}#v>~g~C$z+<Ʀi#`li\Ln\L3@$H a"4t\nQnf^5f3wf7 TEkQ7&Vk_3nll1ygQzń2n׎ ȰgdEvR0d7 <5J0V0&&PfAC*%} 5C Е_;WuLRv=-T{[ 3e=h%&?ꗻxgX+Q<9Ot ӻwI;Ӹ+ C萣!mXMcq%K kZ`;Ct.-3k4J1Ƚ^U1n`ꁘDeg糬⟅z,%,ggYYfxIꂐuBi vŒL"{KaKi*Iٝ~.d/+g{ 1NNO7e{+ߗ>C3 ȡJabH1&Tn19 g3EǙ߅O1'SDDjN~ߔȎd) A';&;WyW-!;U!Ɍ|Α3븰7O4L&,X=XoY00ܭ3Uŕ@XYޮDž}eZQ@=e5_C[ϨJ4B~S]~د4I oE*̳Ϥ3б+ԌI47j-]1;#Yh_k8.AWStRܽ%8;~qAwlc;z AtZ!L3h{][`k=>jh #cAHxE O-B&̅B7& +N4 RY.1*3|e>{9 g0B0 c_ȭW-tuxMЮh6 l/9)3՟3L TU#[mx-vI>mf_&25W]qw<LgE  g 7aA~GJG(J|MP ;}l"OAN(¼,k`v۬cL b/X9)CEa|ɐ- .4 ûwi H܇,_-e(䨖5KET%nB x_5-o<&2)^1= ֦D^#e7ATرHbxrUh|qfjHqI鋄Ia8q;8LĢ_{ܜ85xQYPtE,AEu,@%<.Quh˪)-DչErJ,,6֐DG!A QBcwJCRKCR!o'slE,ت7,؊XU# ȩj{s[:GonK\ˆ+!cQ6јjSp>.xgFڡ<[WqDv/\V:q̓W,,&o,38y %t,O7GȦ4O!5N|n{-s͢KbfU S}ƒk$u2RfRWj b}R9ɵȽ^Dž}%>6aș`U*Y'$bX Rڗ-Tq%ej4vRMH<*55J%f,LDiT,B18WUdm%n}1W]jό}?T2N TCTu"{ҽ*\x*^_.1v"B =0֍őO\z5'葭/{` Uiܨլ O`,J#)@4hDD5%y[<-^ '8 4E7o\#g!lg)#puۺa޸K Yץ˺.9_uDsog瞁H; sûN 3?k ^[pZRnJa@i|/ Lj)ǁdIk- r A0.ԟjP X^R2%pЎ2y_o7Qq|{1֍2|aFC03 @LGo{|x> dϘ$<9:{oxpb>g9v/G!`1=-p)yXrnjMp0m1 4!&5 la55Ube xOH7B$$`qpPgVf&nG}9Zﯶ]oS[ N:8x$+ yd=]'UX5}g6jUgI~37 zj^Xh˳Sݐc󣡓NmqU%RbBK80#bI-ڂ{mvŨ b&gHo)~XHdUCE` ꟍ :8`Sf?D5;>D1܇Y5?Y5?YS?60>or ƄaU0&6a;YGB".37rdKAIl{pRFB!E9͜h|K辉3|>>{j4CTy~HrCNPMx| *CfYLY`dmrj*īNԔLHֳmUtL=zv$ J :=D* 񯦇!FZ!FZ!8u~pX@5n);~SL93"0Jz.a LCuƲ* 8-W=.b7Ad,?@|'2poDFwrv0L4ljH~3:"kFrLxω4 Y4X:`:ȟ&II k_ ϙK =3΃ SPN .M(r@K'NUzLwL[y9U)fV/:~}~߯|{3HȯTD@7( DEBxafFNJbF_?D(^D2);9'I+D[8Vr]hழழx )y`4ydӾ JN$cI5edSMM.uhG?eL9m-M3fc[C՗ђ<7븰̀]^7$]엳q'Ӭw}IJ |\xIZE-!SldG_ꢏ_H9m6` [HgӴ]ҏ 4k$&lDSBrOa?7VKmzu[I7ooɯc[M~ɯ0=`j Xc0 i i =uS6)̯<`}@ `#fuyiBE[c֓ڃͫ$]FyKRߏ`KxnMU!KKƍdN,-|P\1(uTaRQZDiiO6fnʎ cFcN}X?frڥBgڥ:UT!IE#mwJ9*Pn<"`T!fȽE5rj$BǗ u [r蝨 UWE0 ТX a"ѫC]RVv9燂}_|! J- I?1֦TùH?<6\-&8 syo.OHsbݞ . EM1²Ŷ1v:9ؖi /lWK"7)T帰?0Hu峲[R&Z#E#aoLʃr6I"w%[|r2n]8Y.|l]KVcv8~ fn݌{yrG.ޣzLjuv"Ďzti%*!JEx[7}!lf=UJ%_V`6xǣ`ǣo)DLgd*`db! !;Mㅉ[P8,*8{#x+~ T. 6e`36Miъ;hE(ZZ[ }-:`' HHy[[d+- "̀ qa ߜGC;ҡƠzX}\9G̖#_G%)҂굅KpĐK뿾?csYred'ۤ{ڗ-6u0>שׂ5:d1pzYFvקljd8*`\5=UFg5t x;sscpO>&8VZN5@Sڐ:jT^ t:ϙN5@W-A NAH"E.8!FdЍpfI?5 0+:x]WTˣ~~2b,++]! ѵYO~dLI%~GSd\+-ս<|y,YSS(Vk NmZ4,r#E7I:ZcUwxSZ\$}ٳ?qjRґrR~,p͑%Bi[=ڗ&8W9p)zmv_#7?O@D'X`@GfE v#d zt+k_5җrmxoqq_?nHI 3r !CUD甅Z% 3P/&鵓齵>m-2Pv`o,FV0M_b&J=ik_jXl틛pvՐ[s~, _mS%._rMt~*V?p/}jY[s APz[y\yl^qV'X .C{3tV;#*M>UZscd\@Ŋ4!6dE]H?2,(\~vZP冀Y~.:Ϙ1U5-툩jTw9bT1Ց}L1cTgs _5߱c}?퇿~ }sEX2a3('Ua_"}6@+ߔZ&ŖQR=mKQ̿z[5 IBwSj! "tմ/hɵzvϲoϲeޞgiYYZxeRRxeg@24+nK0`MMqU.V?1!}ɢkKk.iYFMy-~F dHVdX4usG&'hp_BoB'L9a _N~2r5$8g7QqM1nS&Ǜekś~0RRȞ8c@/LgO"}Xhk[MަMa>6}޶3lGئs>6Ǖ1n[Sv=.55eۚššnk kkȷ55eWظݳ۳,+Kuî׎ϲ³,|B,,#< 2o2ó,||cfZ"IK(bOYS,I0w Z?H%Oo% }:ɵ>ɽ^Dž}?%"͂a߈qWaTb-\}E.jVsR\%C d]biaX}Ì Vf9LܥHjKM\\O㒾~ܟVJNN%ΎŧL0fZDCKF 7&eMD}Jz@,hɂÄENp[q\7CpUC5D8)܇L#>>pxL'X:Sp84@[6R >ט]lTa|E,e~ =O ,{)`vPKXJ*%ۍSǛ3 ;CX`-5}N<97 1"y˃JN.Rb +K,?ªK_Ϗ~#wh#pLjcDLjOP7uadZts|!T):2UNLr?#iȑA49gvxn\i!ܸq>-(:Y_0!k@.]kYWTЧrUѐe4>X*ޕB~-]2k4YGGRBk\m[i\׏;8E7 @h,^mb}JZS'gpe׶ܛy\׏%Ԥb`-%e=SCװdO͕}g&6[u-voór{wbGҚKYRnó,gA$J ( @og"jW-[s }+|+|G]}pKձ ݣH~|ѕ3g^R#maF>0#={D{0#am3f=:0;=~3r^thJ8[@I`=nqj1GK0+H&PIzoqq_?n4J`%Bx,d\%O:zQj_d}?k_Z?ڶȽ}ҽb'ydն>UmϠ'kD qh!.B\-%ZK[\D qG\ۂvoڽܴ{wAwߴ{w^wvo--h:p"w)A8!`>Yªz$оlᵩTb֟^;/z)͈F=$ȘeuGNP%v5U՝9U8k ޕ\/:#K)7H ?@T?dV?8 Q,] 9}t-iӵ}r$E*I݄EN1E א,qA8G8-I"^-ό^Ǖ1:nb?,)x9-FmMAVA^HZGj~Ol[[E2s0weL\c"'T*8IOťfKQV)0"㮆,{g/ܫ#K`Gܫ{m<{3\gB 1?6$iLvH0D@[ %2#gabq%gRsFaglN.`e"eEKQs2{m )oĔ)R N9^jQavhV[ћnzJHWv+#y1M'<-AX#d ͚c@%ZJ͢01赳lZ#3*bxR0f -2͵"SyC21JZh0]V:1R8YI^Ms.$g.)(} N|oqq_?k.k8 ydVwl"Gl,Z:'tt[/'r @Lj:%5kN^N2g2O,(%芈CXyCCŻ|.z"#,0TCCM_Aw%VĜq:|i͡ĈFkc\rɇxWrV $+9ifB~S;@ω<n╥w-gJ$53$(^2C:i " %^9QܐfA MCc0?6a1L72tL5zv DHB@L,/w2jVce;*}"R2'PAjP:r?"{$ l4ı~G&=AN7U/l`kT 95 "9L(1 9~f˖&.o"j{vj7H{>HJ8sV9~ ([([.J rz'_ۥ^G1n bK8>q8o;[.yw?{>nvi[CZS:K۝fŴ\.ngK˭!-d!d+= BBȹ *w~e߻O^k{>l\׏ySR3Ɂ:2|Vr-[n0`%` [ l`K-` C](-z# E2X@֏e}*I[c F/R굫\~ W~N(/ N(\PeSno+} nP8{d\+Nu P0B ~\a\yryA,roZY?m߿Ya.:x]d.~zeRBJmsܛy\׏۠wzX`+L!U 㲇E@eb`겾l),•d}VXޛu׏=h{o>ރ{0[ GwB%JV!w8Aj% k;(9[u\6h,u|`%ૹJrFR?dj%#eoiK߻\7󸸯{`=Xooon] ] ݼv;v;vǞN>=W2zASGsiHe'E+i[%H<֏qWzgYu xY*dAИ,fzѾj1/҂굓ɽ^U1nY!֍* Y hMwGyVK*}FKV6|=q?E#EG}|1F>֎jpn$+$*z$X %)ljxIڱzAT?Mwja' ZA:!`N/Fb]oQaD !ނA(M9m٥" ~㹇7q&uDW1~4&oA1qa}⧔,"Ed>VM!ĄA"(mfVEe'Wf's9< ^B{Z0PK$&YN#Fhӻu'qJ2~,©NG<\^Goo=gʬo=cھu_E78Mb㯱f6UZ%؄-" e^0,/x,%!&ODrh04^ "rr Ņ,Q_rm'R5Pft E6[C` g٤el\6k_P_6)pPwD,MD%mKlYrhcЇ"jP<}h|~O/Y:}>n'3e AjKL?pġ$ ; -}r{|gV*Dõ nBm$uS]* | ]@./[ʚ@i/hsDb+Lm)lQHG쮈~UdVzO$S p3}d- \@汀s5. 3h3!'a  ]`j+ DF6d$nՂ noH(96#>Uo: L ɥxYGhE8/V< @i!@i wuFAOXvۙ,\oXO+3oQk<'9E`-4\LF7N+ brA,ofrn;`U.-9/A */fATs?vI%c2bFbJr ĉ\"H#1"Ma3>+;rwblgr:݇'w}ÓOr; 8VšGzqQǫ0>yC چtOflTCW\U}rOl.׹5Ѷ}4wǽx! KFC@y9ׯi}*\%վ ^vR'ܛy\׏C&jG(6Xkr`Ǵڎy7_mor߀#޼GF hetY5 -*0]E=ᐐü35%hVACxuI"h!+iktS>gy8H+ <gs3:l4ı~B_ l:_a#챷o\Zd,7h=jj_c/%ԾJkw˽}?0i %eߎI{g$2i$]r]?wtAڼpl굢8牀w0m uf3h{n>}p@qC8 L)R0{N)AY!f@ߠ+/-XW[bË)"z Z!O(S{eȪH-iSx )jŖl[zn0%֔n)Hiam^smy׀J>g:Ȫ9dg-'cm`ޝp}Ym\p)6p~ !UGGbtNᐯoJ:>el޺J ,q-*?o?M71@+UM:i(-'-m꧘cgȊ<{گƆ|Q6e+tLjS hb ۇH披iE}bQ61~"~ZZs\KKkiKq-' 8yA^؍'j㻻mFḱ;GQV[)l>Z97E(IR_d5h0oN1[ז\1!z#rob_?nVJQe%@3q ʈQ;(}ꖫ%@3%} $uWU7%|ps2 :ݜ!He оa)zW׸`'[5&h+4&f xdfYiNqő;3_O* Ro| F Rgć83՝IadB2)g!ˤ(eRG6K$Bhs%crLqq;D0QApR'\?@.k4CE0|K &ӏ#|۸}6o. i!  i)ELSWF[>5OMmf_mfl}p/?e1eRL\۾~Vr2-^rY[m=_vA7=!r@倠Ot9 nt/K. PIW}q޷ˏݥB% 4!rš 1>[Br!W|Tv&ojhYE2:[^\AzcslUPuJK46LYpvYCn-#=%-[[!ԕԧCn>В7(9{ 'S H΢iWRӮpHͿq`9DvȮb}dɗ[ xBnjYc6w>ygjeHd;d8KrBu9֍5"֌1uiqi$wI׵zȶ0CEw&'"ojܨo fV1$Uf|bC @<^:?u.!t3}ͻ|3sPzM8 @iHdTKMBpEV -~m-6 o#J|>}kOxr'UW5SQW 6{]C|]&rX!0h@&dJ"g^X,/;cO:;0Ad])Nc] A_5߿h:44OSeh;j;=+Y<1`3C0N[]Jr׶.};Fq۸rf3`꠭*1guPJ<2_rM]:iSnnJSI7ŧrJMSKGjҿagHxC=g+ bSh8. picEhٺ &ݢ&0Cq Gp:l:Md- g]KDuY1C|MT=״|iF7U `*Ԋ,tDY,t.UPah.g t9Od]! 2,@ż5d2x|A'Ċ@ a9psSo#m2pheg90]9n5l 疰h JE:,;hϢUV,ZkT,$JnNu1N=򦭭YUeMam9@fK{k=Kqc. Kj˷ G2γr% ,K#BښUw]R7Wоϳ{k=Kq; {{{%~3zǚﱦMq====^].wJ(nW 'qL*S{k=6,I[I.'zq;dXҚ~%/H,ikV:Xx$ڢX[loXq㒶~V`)Ty6`IDsqAa2a9%ΕICVUfa5K1 Z"11i+2VqY,p5wacԿz= H8wHH4g7 #p;Ϝ_,x2yrr؟Sਲm'xof{LlaXRF,e}=n\5k~@S En*.Ru>"?yႜq\7'iy}Ƀk i+>%Ufɥg;^O[qSԕcvZ-Pj6 2KRM PɖWdIR+,m5f[+ =M{<Fyaԥ]HsT+p0WY}]^:t>~X:d zZ=Se~;?uw'k;'oς\ 9dw'Scy((}nEA+z29)<% q3C(E_-)ai!+ ~Vhѷ^-%S2If?*F~J 4<%B,@Qd5T?vYM’j)iEےE@ [,YZo#m8?ђXBqMlKA=C\Y;%g}m6.xSҎRn2$2l~ oWښ%r_-zq7BU,ؙ"ۆސR6Neo9QEEn4ldQD',CR`9\HˆWaq[Znp}>ӭGv%#++ʵ8{@7qA[>Mc5MOр-60=- zɼІq-G7_Gb3pԮX/: "sZKiAt8͒[cs8܆r 3sȕ :ㆬ(OozY[QH6ON5m26q;k]>9',+=O[L_ڕizg+w-6VqSy%?gUK }[K>mf}Ҿs>6R~셩BOxN/+yԮ"7|[yQ`Gr,_~3O3kSGFԔTUԳ9,K?[+N!y,(XUlmŪ9#[x-#;1;`IqhT9#)Ź2;;)g]1؝$! ۥ6Ԇ~6Ie^L*35mIU$UU9;0=I|+x-w GW!|aR>Զ>}3 8!o?%|vy33o[g 5/K'b21/Y$:…Ts m>s ǯgB9xiz=%^##%?" ` *˹P|vƌ6  ,`lW`A y$kp".gDZ5xψ \F\f!GنF䔕p\N1NX>(YY3ނ5/Q?F2}ϕ]={ Q 9w``V%S0BN*!SށWS_>&R`QEyR$[];R)p{fO9xKq QNIN jtNL:B c(!PW!²9)C?"$F;@bH_Q/^o־Hkġ)wdAHvp nGxl +(}P3!(~opFs;}AH_\jt/%fr} ̬+0s}/|.% 9 Y{SYg"ah[-NWvoq;{nSB=N\[N^vkF;Grڎg4ոR% A4΁fex9`(J IH9Vu$Ilidq<g߷8 m5f!gP2&BbZthvS;$YҒϽe#˸~ ! [I8גޱD OOlG>S?i+VSiۑP}wK8{Kk)% <%3--O;ix:SBcmˠdV_h9[-W(rсi_O= j[,%<JhY}:m_Vw+_Dկvڊ|Jz>mϥw:t ro|}/@%-/4lIN7~G=mʇ1z)r޾: fu%D@^顑ՇZ|z'(Y"j%􂜾 ڽ^%m(};ˮ䤻 :-EXY ڳ]N.37'hǭ, :<ā2~mjݮ㍜fKSj2q7>Ο]q}G^g%BT6$+RBf>zjۮxvV(oG%zi׸ֶ2Ǒ ڂU.;{[}6.iyr]Vvrj9 FoĜ,=14ɔ9q"*U'B="nXh  NGIns= ai=PFq Zzj=Pmr(oSU_ (!UuQmE[(L~eZ[:ڟKt͂멬zj74&:( "('P| % n}pZy~S0|ylDS0r3BqR`Ab0bpqBOY۱1 nvk@{Z-87RmCkOzA _~<1Om*U#Tf5;"f5U p# Oy O'`O15L>&^`${f I^b 0}VRZZݭ㦒DR*̲Ҿs;<.m}`#Ξ>^~O/K#vo|[|la<%ąل\3d!eZL &5K14Zc}轭>֏[#|2O7lz׸rL'B4Wvx9Y]#VRii[o}Ҿqoq2-/X"EV[=-\Ou,2OISvoqI[?e/Dz4NOh3`4n4@hAqQ=+#/S (_B$/}q1Sc^BeH'FJ">WPZ:.VVHm+8H+EXU{[k܇~ϸ`jل202jcc3-h N+^:{J8V}3+)xAdz,Ĵ$6\vj4lZMjqK+!ւ3M\]8vg Փ/@ۚ,Z-Ge[e\֏[ +&WRMÑ ݢo5pD4VWB3-ᕾa'#H۸~V׬=kVZc8TD_o=$c9jbHu$Ic~D>NQrteL:蕙):@Zr.Lޥa҇Mʚo'3yr;\1088qN1mƯj̦-fSMEw-[QoꘝjNcjى&`7>B޹:歊vlOĹ:؟Y0˰MPGX#sЊ} ۄ鍌ۓ<]qYt;z#.$M\ͽ?QE 1e1'ڋJ|ܴ7|ܠlv|Bl|2q/='0+-{I92Vq?lX3ja& ^TjOTeY2!b}6|q._[xZņ|390v9L>'}WKDL{>JQ0`y_p/~3Ҹd3sI?4MNtOnrb=9?<9,j0簞<@Kfsc$Ԃa3Cm-6@.@[M['rcK =o@  h Ƿ))y+9s"s<vwկk{M F`_\NdӀ;^6ͮ4b#h¾42DXBAs`(tw\ vnI{AC4ڈ%DnJIJc'و[{2nygG[ޙtt/]9TG`jF>I;IRHR::Ș,鑷 d%u&Kd~X`x'Jn"w+dW|;"a,Er3mQo\2C)I)4lnV tBKyAhiلCKǡŞ "@BMQJg_O5%F?KnމqѪlQrKb~<%5kKr4Yw׺4b[ɒ/Ro#E[?Ў ,bɀz/!y  vN٩2xvMsE&@U6aB5ILɠd d61ȳb)NGO ޲zg9׬5eUO@jIsbVv ]+hHִ6[u|gIحJf\#K"oI Ss܁b`j/7d!ebԘ2 =dƚ})j$'ܡy23'z"RDYuʢ><bAV͢Hx#17k=15FH%2SZ$F1Trh9|GTTw k[8`Ī 4e0- rC~r *ՠ+nu0"3@|(NuB)MSE9O h2JGh35Cj39 ^(γEoYӳ餹LZ41ųhAwq )! ƈ2%Ol_*dgiسTL ~~ń !άU숷Y oBh `yܛ 0?~ւZ۩aZ Ԯ0&Z)'߳(''F(9m|Tq*8 t~8l2VO R&' 66=VFXytxJlK RJZB$};$|[S]GzKJg%d-NT,iz9Y[YII,{-۸J}(ˈd(%S|Ta[jZRk+8iVi E-{e=_Ď^6>am4R"ˆ hY:iIaRLi ]l{KKq{MO kDw*enN=!FYJX~Jt\,i}W2{Kk[8S'ltR)RKI@!pX[z$[(*ue\^>;}omѦl<>P\fu~95F&GzKqo!?H;Xx(d͡1zb?\] G|ښU]xX-b˸5fNkXWE{FԆ8}RSPR#>g;.33_Z2f*6)Y{fw :ߨ{?YtQ,M6I`UۺjRŜ`N_1;6bu4i1 k{<^MlNp,(A,`w*bOSk 5wKx8J!ja3Tꚺ_M.ׯOs ӝ)R`3WP`fPZYY"BR}%>t_E̔reڙxp,_MD1":Bje2 ŋ^Wۄ_C*zPd;&SO-8F0m{b:!Jv t]LpN \`Q5UlT{B|C{?r.fuv̷N}n/|%Z-z%Wu {Ka/v}R\[T).V)) ?v={}}6w6c⵹Wxߢ8e>٬؆'%98Ygvs]A f;܋9"gHVyXPbѝBp^Q< H[з^-%mYGnz)qc(ЅzӅ͋.lF0rt? *;aμ*W_1L<<(8ٕ 9ieK91GH=ki[$tJHNb RoJ; #p Uk`$gSTAT#0Wm u]}'tܥ*w;֝zljt[E }-K_Y^81wsbS'.-_.].$XZ..tu_bUh m]U}sIyֶb#ٕ<6vҼg}O ؽ^F~oL'e;TDTG{5'f1ڔL{eƉ^]8`yf%â3%G X/:ZZCkkv:h[ 癩s˸J}T)0IUf{RAU,U*Xaݪbu4ᾣYVww%`sR$8oZ8t |ڊU,zJ.oE*hX-6^qoP 7Pa (lb~LAo!DmkVvimX n0훭d$#O[?wb֐k|JW?( g4wGS `k-AymնlwJ4m]g$ߧ*vQg*V{x76 fI++NfsJiQt9|v/vZa/A6`!kprǯzf~>>]t_b2ۙX < s"j9 =^eG?`O"$੍5h5xWc~qPhrޠ% MobCm?o!1+G6nhGcdmHGY-ʌ0Z/_-#Mi8.7Ni `Ua L"I3W{'gKtlh1[#FhNf aj73=r48+^záR#?'(*+fBZ_= t?űV~O"kdoIO%FF;vywk1*Xs 4t 4ਭz$h{ZUΫf1HH)cn2@6\ާYu%i}n꽥ƅ~" .u@lD6cvbz%<:w&}=4}rd9v^+>&o_Ÿ[%qa#qhfF"Sh![fʆ$= +mwn`gx*lpr fműA۩(i+ Cګ:LHi<\X߼*]YӀ泌$od~OAjԹ4SBsEă=2s]Na{ixnV^y!\3=ł ^b`1L@'hB<~"@y@ * KP'Wi<>Xe^9L%4MYPfAR(Χ35vJ mr2[=Kqo)2ah䭄)[a Hb`I=Sk[dҳ?Y[ZVqI[?7^ʉSN k6+Mjƥ B6-,E9c<1>bg4 Nb_!%ͅ7yO7%s0?ASvVj%Xe#7N)Biv^&4>:r է$]\(αwBƶkl< S8551['gnkP VBN$rӒN96[tī//R?Tj[зr^H mdSo#E[?#`~~}L#F`#,$,J5çC:?.T?7Q;c<#R6֡v4ۨ_̩ 61VW a.o}DDEE@,| eՄ%hHWf+c} m 8B,尒ZXBiUZJ85yX[NSMJ>}/{Ro#z,@F]V2,XTk5eZJR{}9zqWҦD$$!szb /VL* \g#r.{Ji?38s<~V0Y1r/df&Ӕq]3!ͮx85hvjC*s+y쮹ji(/)BJHUkƔI!xMPܧѳ֬j)IŔi}۔jzqTBRPR'.:(Gs)G+G 8b6a.XlסC̼^ֈǩ9Ժd L&mI z\luz\u\B&^ '3Y-dKz-VfLӶ1Txgm\~`I<x+`DVWߩ@:.Q{)^h`f fxHu6o F/:F#Dbmp;0k)9Q@ѕWDrkPۥ)RFaF6кHL.DG.:E$V .NJItJOo].ۭ!W8P1ӓsj@=&7{{8xv|>R/ÐDSf_mԌI-ʃJ>))%Rh6nQy{"'sSKh^/񢱿'I٢OF{qDCQ,<ϐw\ɲXQы%#b"?a*Qt9&أxM!WBr\#9n?B:I:d+Ȱru`$c6$bu&'|X&΅A0b/8(5Ez[=5+)P@JpjXY#voqI[?7wP%aB;?&. ?6[{7#Y/,8^c{ɱ&1p{97わ8Irtc%񀙭%A]$֢m x-2oX=^%mߑƁ S{f; +bVXI^T*gE'x/പ"ݘZCN]q_̴iqhcK8},^X{c2ye]OFGOv&V7]Yz{quf)Gh'L@ Rz^KZ: &1"YuDW[i<7.ag;-D*=D*$WpSvK) =_"##r!:*éxkv؟z^Nb$Ug qߕjDFl5ߕ!f就z~%WLT -QKWpXݪ'nĭzfwq}y} }@+8(9E:uAo!$hR \Jl^9;{q G !Q!۱:Tnr mSJ+ c3b?ڐjSܕc+2(;J0'G@G(K0=YwJL\$E+cf;RW 8d bSb+3l=&yɥv#OnUnot{Fa6 Zr[1Z5X[ K*B9yrs9 #j/1!! tE78A4bOzZt8?h$z(DSзo籙k4ä%*<>l{o"T¿\N.G'n9|xza ǹNIl3P -Cy'<Nښ]=ȲWV_i}ez7S9iY9A85Pf]Xc-["bc]X\(BӅ#i$5wtwpF}.3sjuGThƞ{rlnB%m#f41@ױd/S蛭m:Xxbu)ifzӮ\(ql<%&Sh6Eɖ1/Y,wioke zF]J+a獪%qΟ/r0XBb9d9Jf٧ 9-Xh%,}j}R/㒶~(.8'09]+̺/ b?LzX9$~KRf ?c UR=eM!%{ 6~"GHLu)g2K]CxmFv)2&=]+u4Lg` O5n^##ÑCw_ 2[gSf,oDqF2q.@q\J\j1[t3їZB.!1l}A-]jY-[d̮[4 ~/ίQĞU(P2=YzH% +бPͮ?<8oG:ƺWBa /(0p+>ᓛOn]>+bY3΋(S>}ں pAx ш7!PxCk~P =?e/ ߕБMb,XR{|d_ZWԦئf\*6G!,jwqœ_D's%#&q k^+ଡtɂI-ٕWQ=C=gVO43mGxtΣ6=sw4Zr۵%w_Km>t'۠ \z u%(;E_![wJsgmJͮFɤGnmo}O3꽭㒶~ܚӊlZ6L&F$SSj=kkdmV4- -qҽO}n020W23,:8Xo}=<,q GX[ZҶ~*8kJ5Q|rLjK-f̌,Y蛯ǫfm j}Q(z)qh @ >oZK8y̦y7=ɸڪuO h[΋־O޴e=_ߒgL[KFM[*BKeG~H qNpqѓ$/[cfnWKcѶ *-_Zo|/Adꡤ?փά/|x&+Nc!z,Nu/{KKqˆv\ŒG6 egט3I;)I[~/VBomHx׾qSo) l4Ͳ! vJnR9rÜv9-wa`%X'|ٺOctɒR>kkDrXJ=>@-2.i冥p"VEZ+wJWW}N3J[ z-zvw^sZP',<?XN,V|,Y%(C\7d$˸^͑cLKkuE>ԝC"A~FY_O,} }E:%+"h-t0m4_ikVkvF"r;zqc,2"/ hCtS}y8S  _Ft+_(3bE&o |238@O+.RK-fxJ~BJ+tvfJYJW|JҞryoR`&T@&sD=|-|R&?x| ,oN#"K~:Ex,)ԋ5\1!},.ه.^ 7s|X>\bC{zżdnbgOO:Dё}@67[K5$}%xvь^%rfov1]IV)Yjꑡ(mBzzbyRo#oV-.rO9@OQB!I=V|\6}]+펮+BW"tb.O,!i6RKI4i1޲ OS>d IరkRXY.vS:%ж`Ro#-ipcR]Y)%E^E4EGG5KwNܖbVӾN mפ<6Y%ԉ-;{{9WGzXSB몶]4ZKOvo0,aNl;R8O)JSU }RB da뽹چqcNe;>,#[6_V_±o$L dV ɬ:'rpݾYh{b鰊8N;"H/"Q2&$*V]z;Ǽ8uθ8uNSSLSꏀds\uFr:} Y!T i Zʇ,NOdq($T=t$6JP*uAh8`7dGY@%!iΗd8d$.'͙qW5ߑ,x``[dww$K]19;Ȯ`fˈJ5iz4OniO@6Ks {TvER4+!Ad||o?{$~BH`Z47Ԋhɖx>6to ѽ+'86cޓ320+q1r^>xfVlMghai Oؚ}%Iy][+[;[nZ?akǀ~gq&]-1_V[[ch89/>U2>%?E+E{/&z+TH[uJ_&L}Km2ҮqT6̶3;g-̧:A"ٜCle J)ZI;ikUh<7!쳿I 7a݄3xߍU'} 5x\K cY3^`,TC, ?%/l;h-L~?ѱ02VZE)cBjW| c%zkI.'T8TDZ:f^bۼY|~e<ߏـsgϰ*a2j gŵ|=C d6T.yV@g@_r7 Um +"?HL`s*ki-.U|~RO~9] W7jjw y׵^Cף}rq`s6v }-Gh?-G#,G3,Gi9a9a9rTrRǭwhZjWBm(>b.pE.=XLL.r]YKI\a.pDJ g%=k24K- ~2Y=Rijqz Lkp.ӚLDI^E&l&6O۷%\zΠi >MPklG(@q~(ΐ& } )k\OXc\db[lA\sc^m;ab ?;ojObQ" {QQϋmզ6릓)wtl:S"fdT4(U`iwjARc؇q1>(n>Ysi_7(t٠&d̆c(v3<:Nvam }ͦSmcV6ZW6S{o4K$K'bDӄ,h'O6^P|P/٩lR?+_/c)K|?7ԋٱ\̎]Lwh) Hy+x1P4߼c|08db]rdӇQXW멏q1>f}rrc>GLT}/5=}/^3xȷA/@/KL4Qu-1ZbŐ&,3r+1t?mҷ˒Β%[Rd+aKʫLe[k>xy]nwYmsbHGt[.bs C";&|Ը7wc+=q1i=q1ic}kӶ49_Z5^>(e?x`oQT`? K]wpbیK_M44ا@SeKzaPxM Ьx} l-}qAʾ'yWzsxB HG7'ԓ+>ѕcP ]~^E7mh"qlMKoaۛ|ooV[\jlsaX<Ʊ]4qF8f/<@p~?rrʓсG4FvfkzKIh;$hÄ%Rë)5_pK8A9) +\@uOJRO_Ą)n$gט'p1c<]bԿܸym`gF~U@H!k%>>l ȅĖF^i̓ }kTWJ(m`g}7E*ڽF57Ċ3>>%x{T.LB7؊Y~Pٲh޳ vn,SAN=A?A@+!K[D:LED:LED:0L=|@rVs["g*;+tQp{*B<*C`Z Aa@:TMfxI[N=z;Z~Zg)]60+!Ԏif}ZN qj87NWq*.\%\-uD(gQrt,5ɢ'dQ}ԧzl k_\J3 ϶*c7oy[Mi~_n޾&!$+%a@K%; Pw%/ӧG=ѳGO7} 2(ʑ5@]gvSѬ6qb@b7L%o~%q Ê07.:uIFuIsFjK|Wo6ǛqW`뷯ߎ[9 ^|{CP>? ɖ־$ڗ$[pHb.MPŽrvHQɌh, I+>% |/4Tvc!0^6%J%.5v@Ϳ'J]^Yi4KhgB %sa{d[`l dm" lj*UhzքԶfNmѶ0tvquXȞQx=<9az$Y0Î.%ƹ秹u4mΟM뎦i|1_1aX+o_"⌑c+6F)dq&Sk 5 FGg qLl?%'%g:k {IН:R$GR*GV=t/W&bӽc vխbz6qAh,%C̝$(s (*"_mzV/Jޒ$MЀqh%"z N¡ ^Dž 'ӯ۱GcNOnݎ9ҫ(}uPXxZ]{(N^Gc}zqΡms:ZJT2 2̼Ro* *V X((0(@{wjP}#""ƞDJ4K%rV$ۼA%.z b1YS>6 I]@ƒÏيZA Tt p(v֢z`wq_} Fky0ϟp֮{:zddd{Ve OqhK|2/ Y)2>ؗ:* T]g\P{Dp0S[#)Ѯ’zT棡XFb1Q]1CFM8~!G{+ٳ@\{̗kZpq{<j~KCq]3fƛ^=11nox(W-A 'ɩ'7@0+H ,xY7hr<7N"|ⳝdڮanJr0{DUևfUƇfoYWsEss˞e_js6g%bV[?"s'mz=77]=Yf$?+AW)+p-e|{+\6jc}Ftabb*S1JMnql{&Ů'aང_L޹N#)t)>y}DI7nyhZW gw([wV7`ev䂀AxiUİsF18usN?99r6S5oCibwHB[nL;2; h-꿥*L[J>y~ J~B?aBz'LYH8)j;”Wn}%Uԧ}%U/*Yf{u4Sׯ=kuoq&96Skm>^Cx:"!B!?LB-KBzƈm'1O9%< SjߛVR jK$[_q߬!44 )R733#+3y9,.r~]9.#ON?w_E\w811&1.jpڙ|%a1|΁c:0ڶ~x]h{?Y݊&RR&CpXMӁt^uH7'P> ݝ@ x4 F}\F m ?y;s>eAdR>MOT4c}1 f>5B SkVHWk:F~]'xId|+/rb ^Z~#SA!QKTh5*`8 ߃26dy;l4Qvpxce;}-wﴮ ؍Ǭ]{NRkS땂\H\BpTXs:;嘝S˓(BCwgH ;hKB~{MޮI 3>0fȡ캵ywOcZ3@?Wq~Olf[k;D? MN'"&'2ϣ>ODu eD+y^ HWr>գO4=).MPa}PxI$X2カSJKO@Zsc}n++|~q,{rqH mDq}\ٰL066XY(c6omsHUTC_tXϛ}螀FnW +$lz'lQ/Wk?6Ha,j_Jȫqك!";1"`Paؑ,sIio>rܛsh}kʩu1]7Rٛ.s^\sOolUcVw~yx`߄%fkˏ}I#9;EApg$5d:t5PXiGH k+~>}#c/߾q}X;E ?4DX}Y9dJWEJn`q? I V6=ʲ%a%y%鐼+Lʮ y8ɖ4CPr*uma-"p8BD|- ' t!0݊F4-/EgmsgxqD 6 mu LۘbqX `)=%Ș٨6QLʋJhF4zQB%._[o<.|f+!kwN.^F_s-5É3ߔȁ {43 ZxV2΃F]wO5OO2'sxzR͏,dSw{Qnؙ(~'u8Ry0A˶HЋ4F5+':Qtn*tI;jѿՒ 6q׌ rE.W(_҂N@ (hf ڰj- xU۫r^wyU.)Q!UrA<#.F`U}}Mf*EX3,˚t\[do,f9,^ZZ}LJKsw-s5w啕B=w.<ʎv_brMnI!2peƙBeI(oOȽN1ոYdrCo šU O 䉧mg͠HE*>|4Q8SQ:~=(W!grf(Z }O^6(ے$D=5#uV^4#ɽTԄBo7hz:9NZXg-ۨV/d~rSXT[Ot,"~oXu&(a>鬆S<)<"aV{/%= QP^BI=@&&M,#yhg3GV<3+~'QrIrE!ĕx*#E2g^7B3pYSQ-W WW>$ƎhB[zP +9pb LCK %f? )tТĤQ85 by)vGJ*\z\Z ׳G9  r޺?< ;teG5?n ! *KXT? oёP`]u;N;y-"l̇PNO'lW`s|+x=u)dj~QV2I&hK<S5' 2,'F-|2YP9m1诲Y w~ BR=B:Sz<Xl-%Kѝz<oyqSbՠ80aoV< -YhLnWW"PWg}@ݗ+Ƽ5y)GǶl 6>l\J&)۲C ]rhS=) ncDSԍn6 趿0.(XZ2uϰ)a^%/˖ Mun,eq,2J|j %Y>T3^|]|Y| {rƒCcɯD*vdj'bQMbs(sb1 $@Ǻʿ;ɂ燼nq{,w7#w};\W[ hJ|Y ƺebMИ߻>e:/i"dU A0ٸ:_Ƌ< y6+Wg~Wh׼++Lւݮ l*dϦσpK9Xpo\Z^?3e}Lsq}YB+s-[ԟ8ZʐZ4u+j9 cq {ò{㳵_cyMҲv[)KV%u3 >jel-uX٢3_96BXms>]-e)kq)-⸌BU89st3vȑu1yELFy]`VckCzµBViBtLN]D69u%9uTT$Ř,yuV+0Y(>i{c(fsBr r0+ r)8]>(gHrjp@m 䦪孺MԵk3}l{d~ ߇,E}NEE}! ،IfobY}DNON`-BwݵrY9V(o7A%WP5e]wscUnۄjl㶿Gr{oJyGN=+dxl;HeJz6MLyߕ5n6bc .8~7Ov ͌]7c+a7\tp*R ނㇸmXQDT'N[j7s{OڛU@F0Ia5ⵀƧwm%E}H~r"%Dk0Lʂa=9{s '+'Lqab}9f>,r^/S{3Jڽ{)Cf VhWlW^|K&%Mߙ}ﴤ%GMdAylvq=iZcVx؟V׆ ^;ͨ+6xbߞjƖRx^ gſ{͛j8xRڬJ~!e)ɱvT겟 J.z8 DAh cH, |!:kyE̵SB Zfkv2-zA M:"yE@^ rkM*T7*<ђƅ% WbDfyMNyXP"͇5L>mfK(R?A*w|G!w|O؍񦵙d>O;7lFyqêo&(#^VK;SEdn1B939#U*"f.Xi\e]OH*[VOUS0`~W0RL`!Ճ^ܚ^ܘ6{ uMB"e#PY<5*\hWqSmOo㓷=O?j++j[sL fIPͺBW.]&_ 7Y=x,yp^^xM5i!\H_m[1hWg~.E Rp_l13YTљ2k=2{Sg`e*a~ph&k\MDP/7@k*Tٶ [Uv7' q%@XoW:ȯc7MW 8TP;|5n\Ь4YUYU~ M\8:y?s.>Q<'|1n4uKr5fѧ7hG #/<0 Ov*mwdQZ-}Jvφ)=O)HteFcԇ/^.^F̥OP?}v Iwg91p+nXOy0,Ge.,', U#fw+{_Q)^ic5!+!̇+O`~*fNo0zGR$gD,LFR; ,% @[d+G/3'^,`ʬHYIxީggKwehܴeh@*.<鈦#&T#TnS[ O,uz\3}c2]h\\(܈8PvqH_EGgHg||_"R{P沟Ƥ~eC\ aL#ȧj7pʰB|YmsK>O};e=ޮ Ѕ抒SR?Ensq6ڎ8Y BuJZEM?}&sk0"܇( 2"HHRd|#52oW*UDk-Kvl, #E="I{?c vGŘlPB!o(q煻FXV4,2uCQG+\EK =Qru? msH`1+X̳,o[WrU|K[D|en?UW%(U&(}AhEuL/jD`#(via-f'=EGfKKڻqb$ |~OWNv/WaĻ֌԰ +>z;Rˑ]}(;reIW7h<(r+?*L'Pm)a؏ =ZSPݿ5fi+E58U£I8#j ]i ;1qed;m_.9eWr+{P8 ^x>%+KfĀ*zYRI>0o3ϳ3"w0_td?B Y Yd쬑Y +с~®x$]lcCACA1` n0VCM\7 ǢVo!qW@JJ ,o6jAu\#1! xsz9=檄p6(9kAvFpV%gTZDa">f Zr^cg5B\q)mu.? zX]%KV@;q?Hcc½yncAvemLkW5ݐȑ+m)OVޮN_y;C WȺw@c$KՋԊ@I?Wx~VxqWx£1D1D\DG1ou Uz9BB@B3FĖ%ʼnHX6ț W\Bބ  +s%P,Ke== q26~٫uzDC ٵ3_-H4:dҰFAtyUMȣ1Oss#&76U,9(B(>4$VVz8 84V:"di=J=G4PG?+ -k'[UIgh9]HEjmuBóلg?p2f(`(pQT[6fykvZYI,t̯=%h\>`߸`[i9bsvKKd c\ -c \|K_֩RTi:U4QHdڼDZ=2h%o5 ~U]Y&v.bj< vj /6WgF6s5;ȀmdF6 ކ8+P?01@URCV Hv@CaD_AMD|J"؅ܔj6|R׾&c! )9%J@Q<?%fe?E y\^_OMFqYKw&O\)r*=Bi N,) OXZ7<|lEMsiL,p$R]1bs#Mq$!)lf?S:1 x<> Y'Ɛ+kr1*RuGڕrmK)mOsYNrnʹ#j@~R}-"ȡf77u!]H#Vg9U d; wێ1T>\@Hn?x1MW'-3gWe]OR럂E4*qfÇ O ?hCe/N%`v*L1tm[>RRDkAX( .vcDOP xD0 Z8 iFW*zTxCTᒒWA%SЙf?q4~Q^/sqgHZˬNVKpQ%P?X c{od/p(8Ff3\ĵ@y7 0~.2{#+r?FE&'7cdw] [TT)È-ihIuHg-3hŗ=}@OJ%d;K TH% as"|6S(љ^scޟko&yځTI,IC]vK)KG]FePw;}PF2>YEb<K~,zf%Q/KRiEegj+jpܩsוShlf%;Hopfu RpeF'oxZ)KJLl;ww;w 7P=U"_?kfHRԄi SS~E(",1 v|˧]RKt8Y &&!5E '%୤m+?pa)A WDjLY۟vbRyLReC.dK|_3dK)<b1=_ y˵_q 2O(4*LCCr `;6A< \ 畹Lp2[RtH`SPC6v8$.Wə'5etɚwɆ_4f\-^-s]V4%"gG}K.yhJ;D%y~<8JGdǹc.Ye?1kŖn}$,68rLY)Y3sqՁnoThs.Irnw)Zr ݈gFg -UA#38: m`-6}X`Q`qEwN$!⍌OmRI 埫$}P镱=~a*DžlR)lG~^|J $Wҫ]i޿^+eu>Ѕ+L®( SK-qpHO` z.zHN`2H܁$OIʄ3$e ")S3I鏅`(FV"`4툑ΒנBTɳ`}UZ[OCCܙM*|Ul1ޡt"Þʶ`DN*o$*SZl- CkӣPHAT;JLƸWre癖X*};sc⸉c>cr@baa=?w8<@8plT38/%#Q~KN ˑ/_B|Bm|iPgvw٩X$j3l:Ɂ0IV)oQ;'؏ H25xhHgnH#fӚyoA6|ʬ{` f:(`ѱnWk\u{3yi筿KB[`eNXDkTݥh_#Acݲ'rHؽiՙ 6:TyҀOsRRhybMk;)-RDǺ+"buVD"}D$.ւXQF 컓YS 5ǚ{7Y)l,*ްLO[u2.%qЅ%@xjZ*k%WU XްLu\g L|f/YԴƺ_>)~sگұ+pE#шIN,PsfgW%?5(_ >C\cyPb̳{ bH.OZ5Q`mMï֖cQ)ūgZ5o{)X8u|Aے2Hjzd-l[VZ^[eaՙ೵5o{ji7 wlmmU ۞_ɌgmI!Kߨn%Y]Dlze5#xd%#B/ffϸƺ+ǂ=~筿;ykek{Cp055àX{Y: [ !6.zw2j*Uv/Ut4X;Qm[ 8@ŎMkK]"iȖXL]};O֏$uKomX=yly}[$,8@l[%:(  ASY/>eZKm~5+ kkژ( L|֋5>ּsgjM㶹>6hĔHWJ:f1)Za4 mxf 5u~X8Lj U ]`w?[}01:XGYAHu3|WZ\'o#1+$-=jLvUik d{䟭>y?C#[}'&- Z8o ^ x%W(-,)QJӥ?:֭jmyřtly|!؈?G|# :^iyOIy ye1DP-<_Sܦ*'T }ҧyIj/Z;Vkqn䗲!T(5Eلz& fe%zB@ ђF0"JiЀjxw]~&lR:n;(nl% ~ŬV6،7㐎vgz/9W{xpyAP* h!d֋ƙUq !mw4}6W G^4tY}/W E?hH|[m ^;~m D*xaԏZQ e~ XLa6}L;!?u^~#QwR h^VifkT~4X}ڂEF~A&Am!YkiT`-m BSfN_-a^ a@ي.XLET$.VNǺ_X џxlǼt>'B:d'"Bh'~ጨ/uK?0~4_ajm_ >[}^(z6O U la(/´WMl[}o-:، ݛ_ɬ煱-Fbj-BPhUhIa-:L4VjsU;c>SmKZI׿@ %Zm e0]#u9KǪ  c+颟>4y"e$KUb JkB&@[CĻ Jc%{{?[|xVw &綊 k{n?LϩHTX.30qZ*hv]P"Ϝȇ+Kb)ۮ,e+0 %[y{ "ܱR)&Uk0V!l,Sv°~i׼"_-&1XK21_ƺe)rk> qoɈQXS[KKJu^\~LsU_d7e?0( !VqA-!ByIƺpí%X?8}޶vI_h Q5zN?{9ιڷߥ{|d55y~X/6 ='Z6qE3q\m Bo,fbJ jQ$dzqf闲AT1t0F^ML\m J՚r@9pqfӗ$,QMJ*:ڋظmhl-;&Z{WXy~uEZ[mc<~֟Z{))B93G,)GccJB^-@ :Zy/O9Sk=e<~x7Or=aI{k޶@:0F)dG?oz 83Er9DJNŭmkkݍ LM$wO](FDr<|\Ż3@{ ki[hl ԫr/P}_@c¯ eX BgzTV$Qt& 88d!m0j /0+}YN %joi|H5dZ?&ɔ3cͪhZ$ jcv{WC4g{}.DQ3 ^4:KKbqNkONYT˶{/>1/{Mf[BB#m),X u˝{#cݲc{ gkK󶽈Y RMAXRҴ_ɃkcV6Hn2:i^Klיv2pQE֡uBfx:iI5+c2bGfc W{/>[}^{iHE>-H`> ZLk~Pdc2k\~B|Heȷ,V.d`1X-%B'Ze%Q %UY|N·^FqטOT-W2 B';1;_cP_PޝBN^ YFĊuԦ2q*ELqٻa$v$UViJKZ(݌=gnD 7ԛ\ڭ%!PXI839&GZD.x ƺ1>X<ly|ۢlTE7$= G6J%(`cݲh@cA&N~/I l+t' J& Y@ %gE Yh{ː],X`c~nlyάsjQ4FVK|k̈/<2_|㶹Z8(Fģʴ dTDֆp6V"ER6K;x}LS[l ;[+B xn3 6nj$hh4h|VI]UZ4ҭ2{Vi:y"OK_35H)&ٓbt,eP 윉s,Xv;tk \).J%-&)Rd:}Yr [l,T ޯ3-{J--h.?e 4`8Z|Vɛis 9h JZjM-}onByd4u,)U޴Sb\FQYF w6>܀ v;ZMZ AxO\g넩UuKNG\61p1?e DE{Bc&5 0y-CW u3^`+N.(љXJ~q&T6M(،.Pv>ӄK!B5 g֠|<t]aM=*iT*t^KǕSAK/h;(5QZWJֿ-D9q/g.?˲?_l$ɒl7*Vs慓-$~`WBK FcI!RxmԐ|!A0TCݖVɏt/8Z|~ׅq&Fv2Jp+~`:gĥ[) T~̷v}N9?GEq[F-^>G:1~S\NSAr IޠAbpPHe፛aϛ:Z_g fHP f'쫍u+%-fޏy}6rmk7wQTv <_4] HrqDz`*k+Cv:qT(R 0C|13-7G#^i`մqԴ&hմz,,igj9k۸jszCj}*YQ՜UmUm$ͥuMEM0 CF `DrvI*mz]P}|sʬ)Y $hiMb%ZfZV:"6\3~oXvV4kޖSk "uZd5*2հDQ>-WTX0aY:y[mJB1Zeϋ?Vdtlݛ_ɘ5ohB\3X-M8k$fI)"ԔױnZ cA~R &$=w6q? v' EV&Ce w'ϲFa( G dY+u(iZ~}_U_,׍VAP^#ĥFxZM*JR>٥v(TKչ΀ljgeOy ivjrʊ\%qz9)dD. ˛ZBP`6L}ݣhF N8vG<˦!*IS|Dp\ y)JSuT% &6Ș&Ӑ@tm)e3NdxCUۺ[ǢdkNSy9B kLxoWEp\(,\TD'S"ngavoyE{|ݣ|Ǹ1> oRÛlw =ˆqj[iT"\BD]"#RmWhGOw(, qlLXDP76ٙT$)!["y.is ID=[C 㰓eue\RQIlꐢi6u*7a+S'ҧsۘ%[2 *\FżwrwkOaIJyz_+䶇޳V A L=8VeP@/`BPQ+TN:M"cxVW+<3>y&C;l-7QME$-"e>-'Z >6Sg:/!@.g paZ eᛮY\`bOpLiZD]%|ĩbzE~ıjӝhpGj#a ̷H^ ^kjO i&q"Pѥm}XfV@PXPɌ#Lץa6gm@vt.QFW.:*OCWՁgq qXVK%\zWwXZ Rl,N Z쳵_cyS.6o-.k/DB:i?бj'Y-]E6wR{lq4(i Mqft,g y~~x02  +` mP P`)A$ְ ,5Pg{?5m[Fc-g.ߐ߻;e}t>_a$*^uW 'IxïPXNsbiAv1~cRsDa0Qw)1)c{ڲ_iS{~"VH&&#!lpte[LAΏJ]c +EИ1 M .H׋u/ H/r"l@ H} 6wQՃ7!u:}Dht_c\Ws:` >Pg7p,[Zgi:e@C '4d!W1&|`4t-1@t(}U{In'^n>NQ?"SϤX4R+IS-o%"~)? 'RB&&jXs[ ޒRB_UjTi{U;Y ҾJ>,k5d2~ǪUky>3wlb>ERI-bA gF@V\ĶhAN&wұ #MætZy-dF[|oZیOZ[JZc#쳵gZ5oS#JΖN H<Ъ,`1~XHwmaٽ_ 隷dF)z ej!:&; usc,{K kl M;,Ylpj~XV;u,jm)i}یL?}%^~(+d [$ذG'Zɾ~/Գ C%g*GFG}H$QtEqAq$cyn7(9TBUy ~EԢ\#>Ϥj3/|&9P82GڌVvIc +;(2aQqUڏEĆei4Pof[lX" ÞHL(BN{Qڟ"՛LK5j[5zm{ʹ8qKgRE t3[ }z(Q~s^/dz՟[Vѵzs ͦFWNyS` ZRA$~|[ъ0/B7wZUly}ދYS4X- V1hb鲘'~}[vX j>T]>(cy/M7 p? z7bY }[vnX-;ױ7voZ+0vߞ/wk)|N Qae'/(떉0XKa,!~d$گұ3WWje1UK3x*YEOcݪ&B- Աz+}bmgؗjhg%V%#Z,V@q1:-]⻵izگұ\1]k KN3 /VfqK@Zƺe{jBcؽղ{Dz}^[2I,{ $@Y-TOzmU+" 66F短>yBwuX+ nWlw2TwC h&㢕bTeVYXYl,j >Үy(B1lj病= :4JhQER)92dRk3{{g>ӲBgLk>54}>xL֙oqUh𮿥K9o)R2eϙQԤ~#)FIҤSaTJ-e%?0>R)#즁;m` #@Uyuwbong5 듵wM*k lJs݅0@$HO,ppԼ<5=5/ }ꋥ?\58걥hGZVyo<5`z b(cf7ʻ/2ղ } ;OnM4oɲ-)^y"$$R|Hp!QBuO'B#PIypx2ǀy8!{&N '%BRa1 't'*&*!C쟉 RXKGlnUݳ1HNU{&cd8&eI?B@Z_URe$ A9q{=KRȮH<9ٛ v$cOm([&Ζd]܍(i2HW0/еmy Ei Zw\@ලƕKF{ 8bY ~x*?@rJʨvP4hu(7@8b~OwZ}]VOVnAEpN7b O,{]cݲzk"|~mt fkiD%ăbS`J GրXpo^-r =voXv4kK^DwY-M%hviN!cceC 7گұ߇'F:o|a/oK]&*6l-!JК,KF*3UuZ 8ڴ {7~)eBk0 rkP= t?,Z Id ץMOAk^}꼗=f^.xu *p}+UŧhtBInWkTcQ^lyޯ ᚷ-B5@􉅥1iZFDgc2&kF߻}c^:vA`Hm6t-bq#.MMlZ?X6ցa HD[r{U#%G'/RfgdYCV OF[$S Sp\Q_Y:2=(ɮGg"ſdmiLKikއJ/MIZJ\ec2TjLEۥ5!3 <ꤩvA Eo=u_Pd.0xx Ϗ) ~ܫ-!?Ba|Zikމɥ̭L1 \g'{V4s}kmǯx 0(cvĊXٙb\yæEfm,)~oǯg{hk>U%֙,}`T–]' {q4Cdk13+w0tIp-% LJOEV>,ۮ{5S{= L% gr J Ka?ߒ;ةE _ߜljcZ6LjE@~DiX9k3]#8cUcxC 6n`w~ϴ^^ \" &tE3_D74;yǝwʿ;51<m`L|.8SFc0nsNH'&8Pf 쩊eڨ%GFSIT~*T[n^55IOoJ [f%n3_:X.pRŹ<כHt^nׅ F0[?)S嗢ٛi;u5'vJ3B"!LS\wB>;Vi GҢ -,@ ]n\Cr3q1]텈Aƫ8զ%\u$_؂q.'CFT뱮)-;W!¬xfW˝؉m  W"7bF^:Rk D&\m.m`lZBkc$*U)3^2M林X84麈!f.kUad#e/}5 xu@G:S/"aƍFj^8vCB *6:Ϲ>_jPfm 榹Gj#iCGFHGSS\ XB҉Jӱ{w+}݌FD"Cl9>KYXʊ#km,]w}B`%+ 9a0; !DËUh-,a?9Y%8%5;短>O% (\40Wl<.$HlJN DN{h5HR:fH`wcwBtrRY"VJ~x[ 聒&*>VjLN/wq|Ng`^ 7m!GQ5K tiWjϋSO)iPJ\lQJvXf?׻ZW]䙧XB3nt:#5pI ʢQjm+I"+S Fix~:SP_Haа,l'Q6?rE"A)$o5vqe?<-"xЦ~f;|]`\O2pc Z*,%ƽdmUX*,$)EBW5)-Y)RLO_TMci hD>*SJ}O)==ǭ`'K3nJH>+"M|%37² yЮy_-1jئehZuˠւ*;y>[u^:vD6lT yCB6p?!+x z wR,ޑD~K!n3jhő7 e<3i~DX ZBLk$7οUx \'IJ~ZOY)$^qr,.O i|:Ah9>s!Q'%:"vkqW[~v(vɻhoxdlbCEg\H~iKq2~&" 5`&Ed 3x- l~Ve4Q`69j^L?Ie3K~J}qm^J%+k1̬_㖶9iߨ7;ͩ!@G߰M|׵SrsܛAjQ`;d(ȓ#22{sg @A-7lt뺷Ǹ`{e2"K۸'<(>SzQEFbiiφŜkǯ_EpB#!bezx>x^^o¢jd$X6^D:4q(>4!T5i֗Q"XcGhOAl i.U8 &m\ _ҿPbs9nfq\lZL3Cd]<|.ctc!!’7Aa @Y)%,$"1Jߥ?1r@`I'iP׶s L00D9cBv3&8rF{U*+mSz)s&\jenaHU$MA36f6dɫ(H?jxGlB_ KoLz ep!٤{+'  '%}M ŭ ,/rm?OU&WzT{55?3yrt:$etg9p'k,~X\q ~mڦ$x\2\W8r{#V eSSt۸GM.SbgQ'u+rѥc7Z;˖ӟydOHԲ )H% $ygq}cH\UT:+}s=(5iكe֓eѝ{k+5R,eK*Y_z-K&{&ԬBH QTm Qžm{ԯ kN=\Wr]xSw?KHiSk~j~Qֶ B\+.1Ҷ㖂U|K Tt9asm#_vjQFm3'N\iMqw^x C3T!yG$wnQ=+toԐ%s|k1~]KՐD@1iFeŧ8Dd4ٸv fz;}\W~L,ҫ_Ў4zynW`C9Z-A iU/t#GQ&bϲE(H|]!3Xw `!xxTy7 ;AC3%<-Fp쏀x: 1$BԚPeׁ&mBkBv?FZc/oWQs%B&%w䬄Uޭeҗ] \cq qI9 TEk&%tQtq1ķL3 =`ڙc$0j+s;(8[}Pηgl+jO*ݨQ{ۂO#oLЌ9{x%]xRLPըYgchnL'{qIƸegErpUXX2ϡ} ׁU@:ıBvfgn>n`DEdrk fEʭH IoS;Rr(ꏊkb>Y_̸3y̽p،օyaDy}򾮈90=yGw$CX-1gK̝b^ҹ?Gy.6ܣi_yj|zm-9t$9.ٞ~/;1ETXC~ E\OD) QL .wUMX9`;W?~ Ugc<F>wK"woa,NYz‘ޖln߯j66 yj#:3(lHy m Y0cx*iM"EˆL yD*Tw/𙍝N6ؙUY*Uv5o}m:v_mc~T Pb׸~+ޙ{|JX++ͳ/VwӬ$4xY3~taFS=oٷP QżSAjyi&|xZc@aeT&uJiׯUJMOUп(\ohNjwKQ xK N/!j|jħ$E+H sʵzʵG)M\9g=j\t9jyWs+ nۏ<i OqƬ:=6fֹo>/O~7O'9ǁv WSWPpk\LQM)vkn4ŃPўŧ%4s_Y&ߪGպz qrz(绺W?b# 8um]PEc0g&u.#[jRgK=( E:έ40έtXmiݦ\ *p10QYj>F~ 7ݸ>cߑxp g0,x ;x.}z4=]`wvĿkݹ,ضa 4I C05T-Gn:144 C%SL aě Δo:V_JK{-!bX|"1pa+?5]#lKttL6Bp,wH9D-; :aB46QF26 -|6"N9"~ۨ΃ДбN1΃4pA)/?NG,oUG\8Jn:sܝut:F>us,l%zvgaCNnsF&~N건'rewfciYs s~ gGInmM q}BJ叚P_Dx!A DzhHőT[IvO*B,0nɂhg DY ߼М,ޡFt1\Ykڎ89s8y~֑ ` dx2dgǮΎ]7&FҶ4&ƒh|%ϚO0#Y뷵 瘿łHm˵!14"( w;#( {A)^3u:S&~kG>ĄXsB, KFŀ$tab"րB9O6IqvvV iۭ3gIaݦx*F6;T Quc%f޻LM*܈ړmg$[6Fm@B{@s5;-skXq30_NLDa(_~2 z2ud9눞d-eFcVj6 6мs0_$`EZ4Riwcũyg3i.CWG_>[a[{ҒN ){k(pc gX) qL[7>)y;=m?(/2+Edڃɜ .سёD(5hs"GU󝷪Qvda;Y곂7BCk~6 2Nj=Wg_ s;\4!mO]'Ȅ'X8FE,@-:9]f`UeZQW "#14dtkՀ\jG0ꯣ}S9 JDewh%LGMj^ۄr _2r.p|F$=JA eU0ʞq0$ Е/zÑ$lT(?u)ݟsp`nT$ұ6KGy6:ՙ_!Sw`:?!6B?_R=x|QTI-X1IeEaH bQ2CԫGo~ JD;ȟE' Ln'Ad(y/ي~k!zq O.E!2lыȰ<ʴ!D6~ҜXto~s ޻)۝2m UkN Ց$iN U7QEc1T^8ux. p #+Mg>ySOqUK0lNN oͭ~  22^_d~~>CP G)GMJ_QwVF/(ZL`t`/w=)/7bJ,;RĔ"ɩc qLkkkJ7$ uH?\ŚhrR}6gvxDyJrfPIkW%E|3׿@Yl4˳ܘ _^w/'?8`ڱZW?)^X>3AxR5nS6[9vr&vdۑ P V8av(ȤhL}kE^8҈B܏"`}t~_0 Μ50vH qо'G*TDH_0AY'I (,Pe@x;Y&,T$]:6?A\u1r4G^oI[ݗD'2NON61Q8&򰽷PKg,d람ZX|;rĨ;뱭H(i%Ǎy& O:8V2B9C731+pH7lN.o-i:lfqm>~ivV䫳~Fd2m-f 7;)Zm3/J\:>.=&y$OBSk/HlYx❬|w|y"Sj^L)I)S u?eJĵ6e:kcjcx9z@9P %zx |>t|##h"K9M'j߇$73mKk~mfL&ҵS1R؞:]n1'"{ȉNWCh(l-d@RCuǸ_ ^0*Np!(NVAj3e7E&=4<<JB9ο2#1̼뵍鹽^ck T(*ǐN">k)wJÑ>& %#;^m cD YuC^K."Emm<GzOl=K+ᬉ{ÉYHɠ`yBS r$"Cpa:lRiONңNq栝Dyp;ގq!*X!1Vh%Okti0srG `WuB99+#G)Qs9HnLd'"̪,ى~m:b E:S\?*1t=uwDB_V3z,@ŧ+aLE݈k3$lqBAuo\ 2#o`;͗I[-=8]efE۸؋o{kHhitbkJlDiE?j96DKg>vaǵvqoqurqiٗ8SQB'_ 38x/ĻK[~`]]N`…Jtc`X)Te>ͨuggn"WZC @3~qq8=5gRT!˧Ģ+Tn0Xwa+G9(d Uמ{lo~|_z|wֆu/ףDv>JdN=^ަ{,;`Y7lnP{ʥe`J@JAw_/ﯗzuD(wE=$wᰬdSD_4ԞQϯ%hóm9V_^m{Cb /lwh֧ۖeMG2#m1#zn2"Ch]1.=-El[9Y;e#tEk?fn$R݂ =W|O7R[ҌS~K O CޏC|3>-V"[HĵG9lT_S#B C K]~FIyJ `gr8B;CH{<Gglmn1l׵^i~KSim#)kr2TY,TT wrAvn "]kYFs q|qoumxX- =ؓJV0S9A:)OI8<s.=-g BPBay aE%58v6:/npu_eֶMvFk'9"џ۶=3ǃ60/rz@7x̧\Ur";rj\v4G=ˬ?1Ǿ0Jvf+dVH=6&%*tG\g ,dwdwd';r;)*fjA3nX`_ȣWSR TF|[>[Ȱvk㺮ǸwhNu Ԉ uB%~Y E&)+hsxE4s^3Gi_$ť)^/,6R YW8eUgc8qwf'f=a[#嬂L*]DDܿ#"{Dą\ig?z!9wZ;΂1g~IE⦶S޲*T$yvHvQ?Wek"m-imqq1nO lP'DV;EVK&PjK-&.[ ŵ/IŽGZc/{Ka9=z`1&Y@r"'gq>~O_-}y_둾|Cr V+&X,U)imt{ׅw!fLAZ#v][-qwABqwIvLUv(\@ZHo%'5q.uNs]ld"ԿJI#oRNy;S%*v);B&żl&yIqeRP0=# ﳳcUd4X%c' @H^e'h4ACRZ 쎱$ҹ[l2iPavDԨbg Dzh!l߈kwrs/ә"VGl\Ҹ7eIbm rBn(+7B00$AC|u~U{?د˫_*1)%v6~Iא-)]{kg yn s9a*Mm(En+kb:Z>_N4l Fgz\` @~-|@}$wmqe|䯳kYcg?Q v#m1n2Lr  ȲYr洨*a(hD +k#1n+jNϐR a M"0rQϱm5%:-'v)lq/<(XE[,Ar);3 Y+55s 7؄wa~3dEn-Euoyڜk x*+ l1FNGQv?d(ޑ-mwQ^(*d{ wg|N4H}m@)ǧ;Y>3Q"u4~۞ֻOi,]G)B 1qm"Zk"׎`Dc\R0Q/WuoiV3&Ce!IvTq BT秖{k_]rs]@:EbDZ@m-pbwaQioZƵ~H {sJ+d(NĜ$uqϵmW ,vw_~۞Kg8w & cgՄ#Zѿֶ b<3l\;1Tُd,V_qltOzW|[е~H}\Wyi]т2C˫ &Ԩ-ѿuT?Z>+,]ڏ{{ǸWǼ}[GsmpO(L(QYv[G+c>-cgR%*E O󺻟|ݾ˝z)7|fm|HDNJkp#1]R:UGzgB˧bZx?hGbykiN(Jc/Z*j>Fc' NSQ&]v*YPJȢrFj!GvW֌D{noą::Zly.Vgu6WoD Aq{{mq/:Ț>S$_[@'$G LIeU]Y/|-,\hR>o k鷅fB3n M-4BФ[,:_YVέ"~QnIOfk0uO o%ooA[8->9αڷiqo%TlLHMpu",*lE8 k\;Hx{.ڿKfJS"}w:\I֧m# wǸ嫨8{|H2=R:3[MmHఅ8wmq>[+b*>. ; F1w:#E"K/~wTr[GeDKBq"FHa{rg\C*Flޕo+}Ŋ _y-xIO9g1||/&^LθP OB L!EzDؔmblgk).{GʏqLc!-mM2r=G`$>ضF q`Ȉ{{mqqTFqT]|APXg8CPGFݖTнj z"s"|n":-pm`--3Xtor%bjx YͭN DC8Q5-O{mCMGbVǸ?Ȅ"Ƶ[,NUн,n@qS5qm>A+Ǹ_2UsfHC#28PFfh,<Dh !: !鶎.GKIu0>Ғsub=ٲl;tJ+ ~/dQt[!\3_m W1ҞqZ(ghg/K@g{{.%? BMقΐ~PB%~m`]X.M OE7 so<

    .=ǭMF$F g N -DѷH=Z*tFW_;oMD@=DMe.r萎[!{#-'@QS-X3kvoǸvF:,ZPl '|m&EUP-Qhk7Z#1nmLH^r${r'G  AD2\FX(/@J-&[ 9"Nu=]0,Hk;ftL:]R jW˙#/Aɤ»[4{g"H DnH)%m;X>~9tp؆ZiGdZE_<7=;DGZMT't^Zʌd+6GK- 0qH{{ǸScҙMiqw!& rOzDz+,uΎ{G?wFb9Hn̖^jsϼm)ZIMמ]{{mqkIju@83}n;!i9c:A[Zڶ]K1RH[zeol>^<*fB \;tܱg5/Al$Y[4giYDQa> eЃq# qX&NY3 qxM\4ja&lek->.=r(% K@ *;x4ܜ.ǺX+O{q=xD0+\9?eȊdOmZ^Ko!$@)JqعAr+׍2 qXjmtTY`en+;1|>$V ~#/bҢ݈ۺߓP\&61 G13*D_!jn T3I {:p e?9kDzcgcjc60Z&/_rIMJnd֐?y¥6ưHg['h'Eyk7{ Z).[kty ^¾B5,[G^A[,Z鶝5:~m"~VǸHX.h% :*Q1RF?%^q+uo.'vBhT9Z hDTIѩv[G-ܶţi>v 1R؞Vɢ,Q[`+m)x\Z~a芨nȫ68u|[1֩IYGQ 0v?QeHjC U%;S޶wEh&3-e|Ѹ,0[RnƶDb\{Gq˳@&?^@ƅmJ;JhE5tǸvn1n֡K^"N^W+[v ۿk#V1-x> `'*B\*I:-X#6发f>jwx0Bg;7AmxM[$[8K{{Ǹ{ v2MD!@.fY-XP4@Fl*PDMY)jq1kՔyX\] m\dpթnN5u2d^cK^X0m5d:RvQ;lnO.&5v#<~OhrF qMv,:GCG@wZ=qco"7n[,7 OgԵlַJ,b θ_x-ɡ?<01KGږKKiZ\D bXcŘ|2l}5ةf>0l}-OMDSpz<4}*3b-<]$$OdH)U1Oي=|OŞ+3C=›-G#TB-\>2g `c8q$!>Y[z, ktA`y8j Ytv:AT[ʇ_ޗ!XS]4}r5ۻ|PK81'ѼEwqYyScOEu(1e{q8ਫ :뇂򹣡Iϛm.a# *->H-qˡ{{mqlr.M }A39?yZ̃eW:Jjl/`7WSux/:^FK >_~Qv"~ohm#qk=DžD7s>H\{f4C38ؔdkEcH']d~M]1xlB@N H,=|B){~w- 2 Bp\qG:9&h~BR5AJTIJ"ϗkg,roKOPL 9A2O᮷ TvN/ g,v!jarK{h>5*=cޯ4Mqj7CDD'LUo")e仝Lk~/3Nvv/#F.NЙ‚p'CDA5?ʓb;lnL ^,d=gpXą O2JЕjooAN|Okz/lw:Z(_|v3z bEN.z[(;^UC3DU t=ի~67]2o(^lMk VEoaG(12x,?쎱Loq2kpk =ؤ^" yn1z0Y*'yK B~%l#,5E-_&9M6lU킩hAv̳2)ՏBװ dOVD.{{+]q+B"ҢX$ K z~-HDj s-q4~oĸ`{~-"AB+^j^긡2b%nKQ];M{~lqoBIm['wP~1SÌ;w6O8bkh}\n{[Sc'%Me6{15QBȰ~%6P+io1KGŵqZ"2t7>]<6;b)3lH8Dv껟9n(22or-.꽐Qk5!ܯHVƧwKIR%<qK>Ғ%v ThGeh︸Ƹ)xm}[>rwk2Ha{gآ _X2zKυߜJY_]B]t)Av :*/jN8@a ьBzeXg=Fwм` +>dŠ``t¨[dv;?My W=lz56c}(1bŝTWr'}c4\[GuNRb4,ʥ+@x!ȆgK>3S~Ʌ7Szr##;aׯ??_ȶNqdg'-%5|v_W_,iC|9.v$;I>EqB]T^&XyZ&.x'iC_.Y*Ol9b.(ق8(=DA~W*q¾O)e)Sϟb?8)f>~ &X }v~(yIq0߬ͪ*}0q0?n~hOiR"2'B0ܰ TS|[>KEb{G*q+b XUv ;cpQTnuv-Iu{Glo>^|E%,Ws1xEWH?_~E. g??o9~;u I>c9z,9u_s~s~kehY6lKݐEr4G$@m0-vqoq {>lJ֙k)$Knim*4_;:m;)<מ{GǸykK.=S{z CNﱵymhq:ֵXV_qoqjۅ{ !I;h,d9FĔ\'j9>-|FlD}$ ~Wjqq1Z9(2*9{!cβk;p,t̓SΪGv7E[@'dDt#|K%/m 1ΐ-9t$w`{%  [G,vxrwPYwuo6,Â̐U)dO ahVzDUwq*vJ"2,3QԲ?A3PwvZv_b؎9"龆m4Tƾ?/@@Qw^(N P$yxī({F펱Qn2 Ѹj^퉌? da~fT\pWTe@~f, e|. `y`1oZ;OLվ[UQ@A=>CV gdxKPE2^VM63 p4pF)$k`X%ׅ$f&;- 05^V #Wq݃m5?m `. SmY=f["C/#=U0Gk1s3Sx,S|1[]Da+=kQ1ּװŚ^6;Dmi -QRd~+fB! T \ޟ_ A|U-uz3I.@F64kG=¯>sx Ưut ['r|b#/aZh9>uX9ob1,@O`V~wZ&[u'Z4'acPm)T7y.c١UWm:=t<%gy E4vy]X({ƾHkXYv8ҙ,^5Ag~W Km3N81Ά939 yR"oV zJUrƤLo1ڎ1Jx2E$ңJQH6=}aPX Uoⴊ$ gB,DpB_x Vp x &= X"͖ʗ#c/(Ldg0hhCIBeI!XڷPN5FyFysȱs+N;1ibaђ,CNL0T'X`*[GW2 jȖA] Afc=-W;~TR(?Zaxͤ~+/m )?ot"׾{ҽl헻Xr'LFP$2Es-qbWC .j2ۋ~hi׶0ĵƸHa{[DXT ΔS@FUpf'#i/ᶁ- \òMsDzd{}߉n1Ět'MM@Qm %~um۞~l^im;~WI~]šv _({i"Abr1~Yh(ϯ=]rxEs7xF2}Hec6 rJ~Zl;*uvpp;jDaxSkqEy*&WȚl)MXcfgug*w;VGT.kTk'|K:k_Qu=Q-q2.`5+YM2Z6o<,jsi)~.msiKsM|$|D6~/ Ϗ[$K~ ^EoDVZW0,HRL ulL"űY*kƑtⴄ4I1հ4IS+ݭ +7^4g!uNu,~m/ݷOwz]7 Fa &xBqe;!w (L$,Y=I b8uO+1qr<Վ" ,'0N`$%k!ӍNtWu vAwL}2@UcP?xClbe^x?uǸ_j,Y(&/ ?͍.?Hʃ.=I;2ZgJ%:M|v3c{CHRC.1Ϋ-{zFsX]fO- "D,8R^ \iޟx|3 ۏvrp;}z{OAVp0Xư"o#UQ6䘨֦5ue8J`CݜHo\uc- pl׸vVXc=ǭKϭk-v.f"{ A'@ҳ-oۋ~혝J1nHl٫YE,B)қ: [*^!b׮2{ǸwqΧ%ҍ-8Ͽҍٿ-ݸnoc׾#9FcoMsbk}gNv>g5\U, 7B]F<&y=Xx\d9W(1)]V972uaΔ|0hl.gt 5%>ĺ. gp& gt##igFĈlK:*W?%]o$(%mQYu؏d mJGBE[lrJxb%H^g\aQi +l~Q]{hfE۸ 4 ^>KݱWc ۍ'.NŋڐĽٯq6ݤܷt6Oqֆ Wy9_H?*<, VJUEztvՂ<ܢ(<-N?Z>2]ީc=N4RQ,^gnq'g$B"G IGixBG“XxڶD>-5-Ţtm>vǸ7њܺ#IhVC"<\yK;c)m{XI3o^.y|*ChJMOrirhA%H&ƵSџ˶=}-㯿eq[o||--|[_˸-23')2F7l g4ԋ7+G6PBѣp-ACzqoq1n1XaZmt8iCHaj a(x|& k\;b.1ҞN?-O9DГʪ#/lM#-Y/lkO=q- TÖgnw1}(kB_ {? aH9 >l-1qܚܴK;£Wӫ!\GoGS!vl6BT6Dtm>9.ٞ~IG'#ϥ摇!&hԐNey¯j"vMJgT"v"<&(&Z< "a? AIF~dC( Ġv$pICNMD4X!#P)G@9zRvQņ U 5u8ћZc8-YQXϢxj(>m ]㬐-,tw{G|q9ȍlAp44A~cn[GEpGKY~v#-1ZD|[sdpl1'↱aW?e\kǮb{{ZqCƁ dǬ`pU]َ7M9jbxSAem\q*`ZN|3|ޜ/ /Ϟ^< {WjX~, ec rT*`lb-Y}Ѕ hژY|/צK-j,H2y 1 AIfExc!!m>dҏT]~y<_8.U-,D8߲Pؼ1owMV 'J3i|DBK88-1Уj=H]T뷂wj,]ZхZ/;}.Ң *{̘7f fYM@ߔF 4]X8ؖȳS&L/kǫN@{jؚA0H핂/l(TWR?Tn,Wa~2PR[Bl*k2_52kʚTd$BP-rBm^ҵד?# w=R>e̒ө5~#kITGB婍J|n^yxJ{˕)wAƠt`av+0RA" H73=16Ɠ>tQ&vu1H"~-7Ҟ(͋!PxΔ0:&@JQWڹ=;#hb\~]ޥs B1>AK$qνyd.D@t¨tL6fĴ%0Qn3@:r)"^.9M߬eе_-ծ@b -c~[e_ڍ,0!|w ddN%Uk% xx\-W/ 4 elc@T7V9ZG]hka<8,u(6XA2r:S1X1JSg +(_f#RL}hBZ ܡa+1F$AF>IP2t\a\m+|l66M6 :'59c3q[1֞f fUsrśZ5=_3A6;Pc~N+\ޓ~AۡĂĪ}Ta΂gD:n1dxVY}ИcOD'sBvbs1Pk~5W5›+=7W o^x'DO@޺4/;?TL,DSYqebɁQmB)!ֺ.g'N-9IjU:]wCQ4l)EtX^Lk_;E}\|ꉵ+rs?RoL"7N f2tXcpނ朂@L,e4vkb:)KOK0c4\bKO!%q7EbQ2ݶoׅ:F0Qݥ 11X %*Ġ4p%NvJ`1_t=' CAyVyVyV3;^/nZu Gmu~N$y XWD y;J2 v1ێGUyBM-WXv)]p-KtXct}luDbl&+a}yM'Hr 3 eX 0uTJ] }0P ?K`ӡ<$lP&P]Ұ/XE0^аA7l',[CEnC1"W(*8!,C LC4 ཛP$HWJ4ʙX\q9=3"7y׮鷩%bQ'i)խd J/O%Y!>SԤY߾EVd~[FE}o0͔}q×/\ƦSR+c~fyVJU:i}wB[%&'MҖԍߪbᦳS!D(ԫM{bbUd7hg <|CX # !s.ncp^ Cn)W[ ﹑x/N cvw%6yt$htc ́_~؝}ap8-n e2 껥Sd<Y.rS\*ǝɈ3{u"Æ/U\I͙(lŵ{fyfO%Nt%QѢϢMDcVv|s9d ?-# k,0Z<%HeNBb#RTx$a"b mڶF[LC ߋkн?ƕco&6Qpby!ܘDeU&6_U^ҹ2^-rZLR4N+(ޫx-|[i ! Y5ppSVto,w| !F}FXxo14R~ŎF r8V>' v8:S)Ċ#VOe?5$/45-dϿsjG&>e 9-܍ [P.V~8>wt8wYvsdݍL".?+ J?+N&+#~G ͧfd &jY b1dJhAU׮Jō{{_"n%KcMD= \ҦfIpPǛw5r]%+NZnq+l]YXעp|,AiL6@{KXAczPkd$ItLtC8AjeRWeGK"VW*:Ӊi9H]cč;)#R:){-hTהCz#|ԏ Ā-ȧp qfuoq!{} NToPgVs 51?*(;^r(}/g[iRhv!~rc6+}-QL6oz{ *WUڟUvEӥL*;=j3ө2 \=O|_mU tմ1]-gdsɳa78J݊վ}jGjh)q3X^ޫt :-[LppQHq]mgy;,l)ءko=}\n{[ _X/E uFd'["2pLj{?VR-)l"k'ͯqk鿋ZLhhXE˧ϳ߼n+4I8Zl\kWl;^0e_IVv frp!(݂ܦ0;:m"h'f!Yzhqoq9L׵l u Vlmak>Z$ێ__A{G P9XVo)c~iE%4* %a֧"Sk-~iq+ZESŖE6ƃpʊpW&rΆQ XY٩28!QJN.og5d{Qε<9xψKMT1BcĜ,C,; >{wBJrx~x4׹[L̅>CʩIgklߞODH1W'ZkF%^?@Zx Fy c6-Zrؖ>X*j/g:źyQ\c8)eU )Nq7߼i]y +زj˘l'yAGa֡EE,AV:$m{2})I UGk,W7.qҖ ˇc^f#4v7woz&\h/jD8sx edI5U5h}]ʋ: iCY)7 (B8P ӀLn9z(;P e*j3z c/ÊLT e Ł߿`Tbx3iD' -';1xC".1c}y FMØn`~,2z;:ZfXñmqne,z~kw]1:(Q14U{+YFrQwkpQJco&ߧ͎P>o(O7>߳UL07"Ջ -8`U-;#ˑZjVc+@3k N Zn'jSL zl8v'Qo%E}PdаtY Jh"|!?m[zIT;g13y"!l+҅Y͑N"5>-~>*qWKHq,J\`:z`hKgT^$r=¡9Ww}+m߰e:,*?S7'Zrb22nK2w7iRsOs"sc Ϳ|=6c;X< q[q5'3mŠ̪ԞOhF<] Tu_x$o 9\,VM1|1_"yh1{NW/eKL[tŒ!%"}??\o,lZTӝn~bY*.{ Sٕa}S9h0<=1&^& H- '\O(Ti!x.NLсDSH"$,DAsp{˛6P_iۂj;j|w*yOz ?T| NjoYP0{2 Hp8Vl}&)l1Zb;LA|ӻ)iVsG[~SKpu]u~./6m,Gq9d\LVM;d] ?ךMM ~<h8%"vri.S--4*KyT%'ðLr6S+ӥjR~7k|*.˰-&=}c*4_C0ɗ*+'hx-qeT%Ѫؓw޼uhj l4ʥt|oƯYşwD zk_lXxWr}[%ȁw,W%?.^6ٙm6$1\2Ph՚Sx'&3EBepVX#9~+ T3X&1PxaEFRTuK )+Z.k . JYaHgKձsddvL.SuaKYњNDe#Q0SՈaA3(ձΑR+UN3)@ "əY=h,xJjJ 'pV>lYߒ!5J|;TII4@Sej i&6rܼA`wX##78tǼȫlgo9A^b4?$②,Fc8X+e])&ɇ۲u-|T9g6/8wHxӶk9M:DQFjISE{oK`za5ysri%"F!%qђ,^ӫ/*u)Qrّ7f<6L.Im6 sDBp˪ԍ 0qĠ"(= o+Ȩ|UoN +7ZY&{Qd%j)u)()<&bhź9G=3pëI'C$o"u$$M[눪w>XIs >$OKT]d @G[X<{%A8<&(e :V&-VFNAI"xZ״S 5})x,OTNATMM.xV0*뵷Ei-S.~~5Dz)H*ҽ@ROuI>Jub؃.+ 8JR8~dSdQ&}b҃L*Hu[eT9v#h̜n2fKE>=-+_gXTLC5\>PMpQ8JGվpUga 9HraѰdstzi";~"N|tʡ\E׫gd Q&d[K)%1{NKdw탟]f[5{-n ~|'mkr)b/w+HjXrmwwn qTS$X;`Hemr_GP\B%fQG Y%4P穖"cr|8~#@|[bYh3=Zml&ՄW n[(\@!?TG/y {U n[cɝc'ov^r.I*&ZGӷ0:e:DgngrJw<[dc's~;ngƗ~|.Z(Z$*&MMR+}ܔ.4Db!UsԄcg,XYR4g֗~hqXÊ \[aR >ez; 5sE7ι&D2 33v$d!夵,0f@kà؛$>2by4xCD,uT>#uNnbJ>szZ$_Pݪu:\eRr[ B9ɀQ@P.6EZ,h(3c?E[D*YDU..uqU0/AQ:0@կM+*oR *p&L~i+h9ЈJldJyߚycCJ).Cr+a&)3wR*tT^ҶYw6*KmFE]vOؠE5tOTwQ1 18(y6񈗯߭7˅/#v.^!DwY Cu,oUΟ. (v>(F(,_دԇ ᝏsş3D@]jmC݋ z>X4< ?K@y_ViAG*M77Xk/ 6LHF bQl`ZI/%]zvZ~N[7\{փ2jMT+ uά4nS<+2̪g]c w?c\Y]*'3x|P8T%-b )@QאOxlm˰!]EL9~:tNԄ3.sx)x%`u S]clIez6ؿyq=@H5˖$Zi4#9W"oo[0|wy?) wfPoR XW0,Ta;+Lc˖:e"crȮ@a[8X* ık[w~;/{?&*R%_64h)z, 9 ^cJ?JRQSk[*z uybG1P9$+?v~9oW\ވ|rC"wB8r%.}ۊ s|ڶ\_cű[8 w~;/óKʑ*~~V*_41$c\m6Q6]k[\*;4=RC* +Rж%fh:}oM] .3&T4(])6j3[T0D”c' %"հH <-ARKz9JyV(8]MUnFh!'a^.#ʈ}KSURRS)rH kNӺ*N>u)Ӳ=j08Fb4zwK S[NF*Jn5dOUZ ba]ɳo֑da 5V]cBxCmao(X*jCI&!3?O+ /PcZcZ̯<\ĵbt_J 3Abꑤ]a^EZ7C+bm4||5?) 0i<#7oJ:ܑmفUTG6Y{[xsrjl[!d#T진_ JRmecIA}wq29~IA_[Z=!u??Qk 墫^}/ZY_};Nm/j4 {VG!&U\Rr;?$;fşK/tSرA6K*/1/]@ώΞu+A׮}C:&m(Sg/5AQ*[?qQ \ګqs5P5YreA5!]žV16Pji(hcc,ұ?3~HsMJق*]s!%h>6jOW]=Xq ؟{?'*2}BZ䥧蟨_ڝߴ;xQF^HW(|\C Ѧ8q׽@oل}B'leXـ_s%i9@im <gٔzOo~ir[DQL?O?NǑ~T>M]gS*&Nm. f~ˌǂoel&Iz?{qrn&gqrs N۫qs} 2ł/̧@,p4U[3ZcD3Z9_J6Jct3tL0!ӳt_H&&uի0wkZ5ѴlMޗ ` MIyəS/#!lقkS*V!dYK<[{ c3coV|wJy?d`5PW~`?<9+h$ͮ xvs``/zm+]mwL1Rkjq]uJu,MK%1=(~`E/҅lT ΊEb *ȎP1ޞ[:0O - 0u'_ Mpw: 1vrd,{z#A{` $Cs\!59p{ȿKrBY9yPWc;3߽X##^W:Z*Ֆ2zǐUItVj_#>HV>{5qy|$ĹLA|u$Qs"I!ַUKوnweKY*z^-Os|@_b[s%gFVk[ lxgg]x%J;1vpI"#~- Me=٠;~[>@ىm1v"cO~?/}9+x2MiɻY t}bɻ-wbر>6&_Zkdr#qmYvHI)uՈZ 5  [a54K\,zvrN=ifG.68~n5O$e+k'}a<6lWưley gD@零z7G" uʟ@})/]E b̒BE8æ*C`+zWG`Q%O]crEPq յrr v.PR  ^eLR#6S #dd捊 p[(5> 4aqQw8wjU9e-Y~v溦$}9γwf%ҡa$ xGO}s}SI-C6IKhpl[,A@eǧpDZw~;/{?o'do1dvx cv#/&|j3>m[r:c9oű~mWN_ۛhqRyR5&Z+}S= iۂܬ[7;L9~d]Me51vy)UQ8q bX-דc3_~l!`ݾ?Ϋ/mKyقN4Wh6rq} ir>Ə-hgi_۟զe ++|0ᘾ+eBʉe*]=Mϱ+%BȀp,=<  ZlYY&A)ԫ#Nҥho$L m Jb>vQe&cqy弟_?a]Y6n՗fXƀMl(YLM=bP}lm놌V*yJeal If"/M=X*#bJ op++TǗ`R=Ӳ؛@Ձq :zE@}!ѥaEôҺiُ V!.%ֽ(!9 l}CoLQU=u5 ژ,N +B Gɧ%Neoq!i`4|caՉȸ_@۫(E1ח/)^bRKJYD.ҙ́Na:5PNM۲#XCa3MFJdsV@Mc?c=;尸uZѳ&\a"M2[cfDu}ҹ4)uR (0Lo0<! cP9Dj2i|TH6+*QNYtS+bbä!1vBI=s{V- ^:c􃟘=)fBO_Z8Aoݕޯ׮/_fDom1t֮qtPZc uC8~:߼P T/ڇcH' g^2A;b*фd7 ӄıYhJHU%97oitZ#d^ Fo"b}=B5j37*a/JL ?M#^sűs,KbU*zMi\g4`zxz4~at M*E'QVINi<:dv!<ġ[Z6I"1u&I&+Rx3 7C98&K"b}ID%z$H}I `p,1V2i Sz4ot\|Cש8RDX:H9Fgڋ?Q1&S^J!gU m:CDO06<˓Lm̗K]UF2Drx?u4-^!nu&fpc-]qmhsݛ߫3H+αoU|z›KSBs[xO>/v0jA_s1Ɋ1}\¸OzWq6 ODX *ld3y?%]<9U l̤esKvk)&ɭXi3O5]j'24U,ɫ~.zk8@OU2ܺ,Q+9wYR|Cd= vV{lp;IVy9;|bQR3ǨE>}̺s ϢRզA٢}֝yT(՛U(*:,|(yJd,R`+x. .x=ӔFPn|&ӡ;/Z4ό Q&b}-c $y%+2x@ F$I~IXS=$ۛG"^avxw fP[qRcp#RkkB}1q*dY؊Ms]Ѐ%?=,pbƱĠmZɜi2&~ :;ҟR]ZArʳ:= ]B/BBo!*$DQ˸tB=T:#gKUJ,0 ZԧЖ xz Y)OYvy`ԇeg]دjc/GŶMfU)cqҲ~N`t%W6v69Tend<♪´J\D>_\}Zwp:j|oHI|}^U]kjuqԻt<޵H_Nz2g:9ձ&F%.X▤U=nW\K:W YN`1HeF˱3Z1;Vիo~՝ޯ_ֽ*C`gk'5lUHp2bBټ0>aD_uC!fq#3d3?W-aULJX<~ H#3 -z.Ʊ% OE_7z|ڶc%A&d?Δc獀_>__8%\/?+~d&JSӦ~9@fdd~_?0EBȅ!?F礏cw?ȿ6vz endstream endobj 199 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 189 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-026.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 200 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text /ImageC ] /Font << /F2 201 0 R/F3 202 0 R>> /XObject << /Im0 203 0 R /Im1 204 0 R >>/ExtGState << >>/ColorSpace << /sRGB 205 0 R >>>> /Length 379 /Filter /FlateDecode >> stream xSMO1Wq`ۏh$` FI$M;7n#@X–i=ac ! w5(7Oq#B5 %69,{Z WPCUP<o /I}j%Q>|, lHp^F\) WEОʳ<^iw ްqUɉ_5<Ъͦ3{!#KAyI )I(Wr{4FGZflYF|ӓXA +Kid$~1L8ЄsF]1"UܙpHF cGǣXb+!B*\-э8/inLGqIik \@i ! endstream endobj 203 0 obj << /Type /XObject /Subtype /Image /Width 100 /Height 100 /ColorSpace 205 0 R /BitsPerComponent 8 /Length 13206 /Filter /FlateDecode >> stream xu y?'&cUlr͖ݤAP\;JC]qk\Ƶߍu3oU.v^gu{-~'}˽sz^CnN4v^}Ǝ;۳}7v5zϭok߹o%oطl8g~w_m>u67k?bӿ΅?xϯտvsIWϮghUk7pߟz~˟tWmp]:A7w"d X=w{H㆗s_mt 6şhnoà}m^``}<ppF_';xOӇ]g>|#5vph|]?̓S`xCI }lGlǂlwO=Ffpn2W8'xo 32Gs gbj8r#+$ռג7_>2/u-Hxn2`R5||Ki!<&#)$}IC@N@cO5Oⲵ \#HrX? ![Xy6:]t َ~-P#0&0df"> 1@F d8ÌIBHQQ)_'wd<ޢxKyW64 PS!^hi3@fb2@)&}WLC%C;DUAw/28&P8T0S?-1V=$gT \Ls.M5sFq9;/AE(x ?(9H"^x JLQN'([g:>M;tTЂ@+4QNP{/<\AHoi坁,j4^ef9\Qz B la% `ىk` Ǝ'E++啶w),=afC-HS?&.[M\_Hop._/F>#A3}kT@<6ny'?A&ksNס;<̜rգ5@0GuW9R 1X@:;%Ui!-Y9MU@i,73w9_.$װaْ 3 B{cI;/pKF Xل:ٙ2VFMd E"IW>FȀO1C ͨ}Z>Y.?x4+6JI;7iJŧ)x9Ktn@i=ǰ,(|a0S殌{g .H`4CyD=HxD=p42uC`eXhL1V#xl"k`4UXM49_1jjlqAKyK8T ֽ. \qQޅWn'2 i6TItdL$*o! zt#QjIg /Pie'3yUyšEz&u*@U4JaJ FUfKz=CoOׄ1K{)v@j=S?2 &>o|^ATQŊvCO\QGȺ6ڱRH"70Fe%ttȒiz1ņ, BJ#|4Kȓen 1.Ԇ-w,8V8t6J.&qcY٪MVt*knJX5Z_y?ۙ 2_y91[{.^$ g ~/C=aRz4nk_JOҸpl8g-V)x$s ztL| r{[eKxR?XD{x ER~>ٜOÌ|Qф~VX)GԪhإ%:_N8_L[u0ܧГPMç6QňJJ]ia@(@7[ ,.f=pCveyUq1:c5$ڭz2\*Su.l|ŁC0fF<9#*ù?ي6ҕftJo 3(>&LPhXL'.M%3 8?d4)V:L`e)mxV+RêU!XǢk˨tY˙_M3DΐYjca&;^l1uoBjjHWIpMsXYųIqVT4.9pGSnBZtb|@NDXЁIA9F Sa3q1ـh z+ӱqŎ!mVRAzp`=T5P5ੂɂՙfӟ:RX[b0k&Ҵ3q)[bǐ#M1CIN _{sa-)s Xh+{2}^9N]kQ 5u ݘ`!r5!l"Մ`&]ݰJVѧVK誺@/%kBhc8/ ||y  0!jT5jJ3]KFkF2n/A(J=PBN#HV34wYZ2= 3sCA`KsMO2 =wͫF4iG/4>Uy%d<+6XaM,ρbkkaZ+֢eт%4]fEfi\ pNvUeVūFZLa-|z.|v\z@$$'늭@8v|'V VS}@UJ^l(DF1P .3Fowdz=eYs ú>b*u2h,B6xgz:8L.>CXwEpYaSgO+$d1%d> %hvKޥvu&3m7@NfT\V*N-綰GOj*Kդ'=/cZό@?50e(Ӭj 4]R TM#}m(?d_-{. c^Fڙ%=UnMj鹥ճ>"y~<8,xPEň#HrZ=wtWaL3/Y2XN7Y2>U]Jϫ܇%kf2U:*kZ՚fp{Ҕ5$x}I{bAYjssOk6jVb/8[MsT` ijL ^ohY$rZ^ƏrX[&Q)?iqE(6D㊆(͵N\Xq,գ',Z,fOa.M8ݡbSS2y vXc\C(qXͧuNJ>e)bǐިB =f<xQF uq ɤVW[Nut{ł+Qm7ϒrQ#D)D5PHyH#&jR+xEu婒,-!Ј!聕;7;ÃH/3H\?e 'Ec@R\)ԥَ@[mE^B[q 4c"Dy_YqпV2{UZѼgb( >&V-"˲5sߤc͑6kPpL5őByT<*ʓj9T2*p62J !v`*Gͤmֳzxy&o[ re;s jВN>|p]sӔzs ZG.Y 9⣦*ub5JR۾VzDvfTE)"LavbP!@ hsCHu4 ({*Z U["!cR=TcZ|oǖ ۲֝WXɬI0Ѵ6 Mn^l0 ,:f'u b>UNTiуvJ:o} GJ.LJJUqԐiER+>hg jD(E}T,M!̡}mlPlFZ p@X Z[XgI<ܭǍ 4 DǍYvZ3qYZ2~a| a#'Hc=}/$gx^6k% 58ci`r+f&@֧d%G`HV7DL%@PL;Hݹ]$ŝ `"eO@{;\*3!U cfp\ 0Pr.t+\xnRHt#sP1i F$Ls.˶(5D1PԮbb+ןa3d,\[͑Ϙq.X҄6Ds" &uq< CzPlɕZb2bA~!NK͝ \8+qr_5-@lE76ѕ60bh<5&Qih-nwtAӗ #F3w@qX  E@T63.#q31_ ݗpu8M(;wrS|f:lpGC}Ej#bM9bdm詙zubNUCQ7vo.c/{ *P~y[Y I3̔_\@)>&N2K5zMp6<؛4,>1g1Seoj"+3A:suQO5AкIĖMiP_BCzp" r.6Fz:̠A< jv:c4FrgJ:f_5b{ڌj{+2fz(oK7ӑ1pBDf4_Ye3QG nj́Փ_ [}y:cF\@EZ  t':ܥcpU6T64I) Y 0lMexMvzMwg&f!8|;4A BLY;oguzsZ bq鍃=aF=}3 ֎{^92~N)ACsG A?uF b1Yʆ%q㥊EF^PnYYg.Bj hr wfhm&+HWݞ dN2zq=E Ui3s,eΑOaM'r:o#Y*k~yRr]t{@}g۵Z1Xԑbn"Pu(u͉h"ԅ<+S rK%1vqTv$}:qM ffNa5Pk+pJ`w">xEkl i#Qaqz 5v"3mnlw7=f,Ni/ȃZД *,7>1˦tM,=53F4觻&tRJxU="[FAQ DJoKVS^)1ՑۡuHb ÄCр c.E.aJ?üuC7P8W$骦>i j_i"tUl a=ǬzDힺ?Tna)T\},h/51}_HI m?0#K AJ!AQ?;rE`4Yrfgr.HW,7vs3I]iӊ(4͙,[A#1#ݐa2AaU[h#KKC>a@/p8ƎT4ROs5Jϙ6 L |K BOGcDW^(T*# ^VlCŜ貜V0Nee80.w%5}aEM̅lkEpZr+(/FWȚPG~|iOD1wOdFA1åy׼1Ov)+Bdz|E 螙KZ  0\tϢfy_M`K>ݿ-\U7i:"b0m=7@ޫAgPL0?1п`ލ(Rrh2pYcN5\a܂x1o.~WW vspCѬިyfZCU3LΖXY^7k;hŊz C1c݊ޒ#+/Z8Ig}(NJ8@f85h\Cӹ5[W^Mٲ 8RXm*2#V^Вno/Tنg "#U \YU8SA`j|LmЬTtww})H5g}g>b!ձXǾ=h/[`3W_V.2Ԡ6t EkH/J!6O^kN%u 6RhjuoPAUsfu?yfiB z(k9o2vH" >ᗍwg'̭J5RWV:.ƋL s T'u=\+8x,%|_ϫyUhvp3QsGD`>ԕ#R L\4[z)igmz0LFHaT.34`nqM }nF&VFtД'59/dXgfP~W-[K;\Cc3G vӱwe4N,j(D ՏkUvٿBץd61,{ ,nXwd?qdY^L ⚂iL*%0su䕅 R%tu:%ADwdTJX1 wr" Qb8u ."kq/eSj;VԘәYLHR(F 235 A+p{[^ҾcNVk*Ej-Ӂ[l *X~B?r^rR*~J.CR3 W|WZ\`]E2&IsCr4]~Qh0h-*|qcV m*Ӯҟ\]xV'9\ىH囚>t)OpTxrI@w3TEIMdk̳r{%JVpFa (U>+*kg{sa<(Y*ݘ*n1P3!U!M%].+Ii2vi`?R *cc&5\)9XQ? „3s^##} :tktIha),GK/jHXS09[dł;5:OYc LTE^>U+:.~1GifD4yFwraq_3V 50-O4K`#D-u/J_#DŻBqֺ%%HpǶm1+9I ^s)/MOF,qŸvx>PP鴰#OWMG2fXiiQ d)eF݌mYZjpvmurn`ƄiMe>f3+!#eU#CFLa蚎me/YW $Wt 7"/|]k?hrSa-@ݯ/9Ԝ4Ѭ0=a ?TS endstream endobj 204 0 obj << /Type /XObject /Subtype /Image /Width 1 /Height 1024 /ColorSpace 205 0 R /BitsPerComponent 8 /Length 723 /Filter /FlateDecode >> stream xugP$ioQ.K23/!g$!BIBhHC$DB2BeD"#U3|=zˏ[iK/lM7F1W=9Oi-}B>=z'V&75SJ+i^Es@³xSD,닥8=KXlEVX8`P9֘e#0}$a(Lc1i<&c'cQ1 1l: fal<y猾+z.DE|1S77\];:/ùq t3> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 212 0 obj << /Length 782 /Filter /FlateDecode >> stream xڝVmo0_!$\x8 hH6i ODz]1!;ws &{uSQF*#POcDrS$W|r❤S%+e}{way.I*֔)rnޫ>n0NuR߅kǍ uҧߒ̵KXJS(a6=$AnM]qzjjmb0?8*SA4S: vnQ~?KFIb?2Ogz 0p> /ExtGState << >>/ColorSpace << /sRGB 216 0 R >>>> /Length 437446 /Filter /FlateDecode >> stream x[s='ll& hj@$23V/0@<:{r ط??/ÿoÿӟׇ`߿׿d~}?ܿ???o?|O\xz7 /77 {y7~?nπDž#||?7Q^ۅmN[||~|qimɄ'ldB O&?٢Ʉ'LE ^CoǍ(>ߏ }x}}| o~xUU>Ϗ; }‡B!}Ç>>G^3|H?C  C[PoAa_u  /t 'U>~hVZohVZo(VZd 4R+ @# 4R+ N_# }+VZ` 4R+HWFjhV@+X# }+P@# }+H@# Gy||q'o_޾-ۯ+ۯ{/zmZo%JO(/䒊Ma!6 bSHMa#5B.6RS(䒊Ma#C bSHMa#`B.6~B.o.g(5XjPjPj[(5XjW?Ju Ku zC]W8xNu_'É≿_p _H]H]'M?o~O~?Ov ???Ov σz]Ə<\|=|1W|FhE +Z_ы/KhE +zѕZE+Z_ыOs-E +Z?Lg"&B^tt^B^tT_BWBWп]5Wп8hE +zѽ-hE/Wп]z ha^B }k^B {-<؃'"[xb [؋\o-"[xb }*"[xb }*"[xb c-<鉽uP艽uP艽uP+|^ρ9{?z @E- sx~\kۏBl?םuz]~bqll?ם͟Wx]_w}^ 7RLFy0}0OYO) 'E<4"J }eʺi0HAڢF~&4-kTiB?HAڢF~&E MiB?H[t҄~&E M\a& 4 0 M.i-raA0\4H[4ai& 5 ҄¦A0\4Hg"[ e- ҄"ϖE0Hg?[ M-\oa&Á>Cy"7 Cy"7 Cy"7 CynN>A 'H;aix7;aix 0|4wB? 0ix' oA [kWx ֈkWx ?&|ނwx >o; 幾[z \-X-lnyo?e[Ėz'OBļy=#<1Gxb^ļ~ҵ~ҵt-k']?Z ':(O':0%~ë?e0:hY"L-,Ke0<,YO%вd[ZCS-3<Fn@;ah;W;2ze󥶌*m2c̖Q-"[F5v̗2eT`|}-2QqJkU2*cw7BA Lcy>A4O70i L!n`1x^ti /:4o`Ë570i /:4o`60EF5ҌflBlyxi OL4'&o`70Y#<1 >z' OBļy=3`ԃ=SL=3`nru[cp&zԃMmu[cxb1<1ynk OL^ ⺭1nbu[coy&z1nk m!o0x: 5x- i[%xc[c>/\{1_= \U xcfsxW1_|>omO|B[L[< oO1ma'oE<ɴ7"f }E]ܢ$%(-[JBPҢ$Ewq.NJBPZt?$EP?H.N.Y-r]0\["8aliE vqp.N\ åK8avi' /$E?.NJBPZz 8(-r]?PPP RӊO&jҊoV|X5i' UV|X5i' UV|X5[/V|eӊoV|eӊolZ ×M+>ai'#E>a'+AX-b'E+>axъO{G+>axъO{G+Eh'+>-b'E+> n;)Z ˕V|r0\i' /WZ ˕V|r"[X S?+E+ŠOz0X S+AX-r0`[z +>a`ŷV|r0\i' /WZ ˕V|r0\iŷV|Šo-"[Z CK+>aoi' -~ --70&ބ|ecmw'͎:2^o2{皹djٛMf/5s&^jkN+Mfo5s}6旟2{Tf2d&‚}/7)A=h_oē N_p/7iA}#XXS)k7}F|F|}7}F;h{c\j`aMF.5~My0\|#<EXSK_S W#)֔kʃႄ5tE5A;h{ozהc}콑_SF~My>֯)Ǟ7Pay0xXpkjjj|!xX 5C/U߈5CR`T}#xX 5CR`CT}#!X uCA;tz#T=hNBT}#T=T=T=T=T=T= ~F ~z0<1az.UڥA;|#}T=hÈBT=ٰT=ٰT=ٰT=ٰT=ٰT=ٰT}#[T=z0T}#[T=z0T}#[T=z0T=z0TԃԃԃΆΆΆΆΆR`oaFT=[X -,UC KU_[X ] cֱCWAZު1U1/=a{Ղ1zk7^\mW%=6X s711{1'sbcBn"BZ \xi+os/i m'ֿ\tM?ѵ蚀AXn K] G?ѵ-7ѵ,7rs?$Xn CQ"HNE`) ŝPi) Pi)Eh)Elh).t-bEMt k-,7ѵBGo`-ہ֢x;ZTnZ.@kQah-* Ea-Ev"ہ֢x;ZTn| C l>Hsm>HSm>HS'CB?"m>uEOax]S^Wm>uEOax]?ͧo>)ͧo>~FM!m>aFEl i) 7| 60ͧ0h) p| CEE6 6\oa)Lml>S,| SA|.rͧ0Y\z Oaj`6fSBͧ0S[|.bͧ06S[|s-m>-z{_6_ CEXahh+ mbyPp;͗}џeᚶ:1_ʨO,61_ʨG,:ėz:2jD^1߆QRFMH c)2?ue|ޣZz1_ʨ WBb#[0w-Q6oi􍷴a[0-mc14hr-mcjpK+z[ԠVA-mcjpK[[Z![6 BmL ni\oqKۘ46 [-mcx1^7ƍ im|%kcx}1s1W3f6XEvco<16c =p|+cG-ژ|vgc=٘oΎ=Vc3;1ߗ {c B %$CEZ#LӇ syo:LHa/;LHAG xQfBG B?RXK2B?RX{2B?R¢LHAG Xz ALCB ahT(3?e&ኤ"^+2QfBHLIAL,I a")3W$e&ኤ"^+2pERfBHLIAE,bX0xECX0xECX "`@,BD9"aRDaQ,BEy"abDaQ,b ">!  EbSS,BG "aDa"Q,B4ECFE b\o!!L "B,B4ESAE,rX05hXz aj bԠA,B4ESaj ! 3 E b\o!! 3 E,bX00(bR,B[ECKao)1ŰMKPE,b´X"B!!LPE,:b+\pEOw)᱈5O aO a^"BCX[{wKg}^oc#eoW1_􎹚7cwջ1_ 11W1濌cŘ,Wq}cĘ" c~uc>c~uc>c~uc>\ 1`c}1XocX? ĘmQTC(o9j,E5[뇢QE(!cs,5DQ sc"j} E5!!-"HX[E(!cE(!cs,DQ sc/(jc(jC.!cs BTc-D5/z !ahF(! <Ǧ0\X˕BpRcl yJ!a\)1!E\)! +<r0\X|%\X˕B˕BpRC.Wq@9a(! 8 8&@C.qr00 }(! cqr00 (DZ5rB 8aD9aQcr00(! q8rЃQCz0q,r0`Xz 9a DZrԃACz0q Bc-8"[qS9E rԃACz0qS9a ! q,r0 8(DZr0"[qCK9ao)! -8 823m3!DZLqFrӄ0m5!DZ{Mq BC[qC{B[~z`W_O(s aa(" }Yᢣ00\tf,pQE.: EwMo #L`s0<(# =sb01RFwC] c +2PFC2J7B].et/_F̟2:ets_FǾN}1ڔ2Rư~bҥZ1)9?R9=~ NLc58=#߃3LcM8=S!^kiR# xqzK4\>L#B8=SF깅xqzzF깅xqzKB8=HåF. L# i$K34\F.5pI4\jR!g\o1=^i o45hOGk!޼i 7/Gkx8Zn^45њprF7/Gk(ho^b1ܼi 7/Gk[7/Gk\0Zn&`1rMhMc8Zn4GkÔ5aњ0ihMc5q1L8Z#䚀њF4GkЉ5aњB4Gk쉣5aњ0hMc8Zz0b1`rhMc0Z#zњԃa1`)h-FkS![4 5'iL=FkSњԃa1`iL=Fk5Bi r1L?8Z#zњr1i -GkCњB4O1Z#*Fk 5B^b1Q1Z#E*Fk 1Z[45Bi PNc08: 4C9B>i 'vq!)8Oc\9.W4˕;QG~)JoEIE(# %}Ϻ~ֵ%}~%E(#"^~зxRGqoϺϺ~ֵw!%}~%E)#E)#.u-Ϻ~5IE%}yq{ŀk0MZcB1 a)2ŀZ" õL1 a)41E)$ 2ŀZ0\Z|%\Zkb@kb@p-S He õL1 a:($ Wŀ Ā&@ H A1 aMQ HSŀaBE1 aQQ HTZ1  èb@0pM" Ċb@00L($ s+ CF1 a(b@ԃA h-Ā"[ S1 a 41E b@\o!$L=ĀB Hz0 S1 a $L=Ā0`Zz 1 OZzK1 aP h-ŀa4B1 ao)$ -ŀ Ā5]!ȋW b@|0_! X B H[ CK1EM m!Wj_" )z$ ] E+0t5=G= G| z4#a)z$ :EB0\T 5rIT $L5rIT $ o^% ÛrIW1Ap8/17sW㘟qߋܵ8o6%1??c̝1y%)131?c1;c~3;ccvh{iA.iw@c:^cϘo~a\Ҙ|a\Ҙo{ t ' 2K RfI~C, ïH%a)$eᷤ"Y2Kx#RfIsB?[| %b d_ˑ2KB }$e~0w$e~0'E')$9-]I%-uI% `nэ ~0'A,-r̒0<<($ O, MnQI. 4-@0hZ;MpgSiΦ@0h@"h;MxgSIl 4->l 4-MA4 ÝM&a)$ w6ξpgMi'at(NpPi ҡ0\:vKN0󢴓0L($ s/J; N0" H; }I`vXq`|!X aFi'aQIfaviA04hvZ NԠAi-A"[H; Si'aj 4iEv N\o!$L BI4H; Si'aj $L A05hvZz i'aPi-aBiEv 0vNvZ ܴ̅"s!$L ]H;-JN´ԅ"u!4i'ao)$ -RIvZz{B{B{fBT,Qj'fBTBJ% Q CD!AQ C@!E>ߡO0 >BT'PJ3]tE>LW3]tEBK #D0BkD0BkD0Bkן#_e%Q0Le!Q02QwPF ʨ5xF_F?et羌}2:cx1UF1*AW͹h5_]e4*WuRF2oe*~ڵ1*fz2jư~b䫌1*&e2f0e';a9+&ߞb笘Ί5Yp8+VY1!Ί5Y1!^kf#5O1+H!ި+ĬX#=WxrV+\YFk rX#5i) b4l/YΊ5қM,gHcM4XƚrŬXcxpV1Y8+^-\o1+&3YЪqV셜k w6gńxgsV1ٜXc9+lΊbVLgb欘lΊ5;b'QY1!ٜ+ĬXc9+lΊ5;b欘 wu;dF Yc8HVA2!W 5dF Yc8H&i$k 45ikL53qB>kL53qBs+ 8mxdY3EQfmvdY3Ndё>gʹ92L̞5se_3g_f̞|=k챗S/~ ϼn<"evf'#;حdv\'Ӻ5sKNfGuk8.e\3Fm-er lWgd5>'9˭ap* /F<;Nވgr逼p> /'y7pH /F>&>/wNocAz#޶Az#޸;hVxB^޾/^ۃvzF|!/w>gAL|#;h3xNo   7 ̇t;.tӽ/t :ވ tÅaB0Їވ tÅa7aB0G :ވ:>Lw0\;.t : to tÅ~]B/ v]I;OڽKO w$ v]I.0000A;u;u;v\jadI7rIalI7rIatI7bkI'''''''>iF>iw0v>iF>iw0v>iF>iw0v>iw0v>iw0v>iw0v>iw0v>iw0v>iF>iw0v>iF;f5{#[H H H H -$>iưwNg{#}`Z>yv'+hB`o!iF;vѐ{#[H -$) fA 8fA fA `h '17g3zCqи@`h\ w04.; Bn"7r57r5y&♚(DtDtDƒ.7']ot 1W|61߷s{O%|6{ce RcsG|̟1=?cpsg{1>Rc~y=q̏q̏q̏ 1 ^{Nx7c>1&OH  Rǰ~Bjp E Pp E PpE PPE !R"p(Rg"B?1l kobBP_{xSP_{B[+"B?^["B?")п0vHп0BP_B\t/La s"\o!R( O c"ܡH0.t.NA ÅNBa)R( :E BH"^) "xSP..t # -HaA#.r00܂F[ˆp RQnA # ˆ000 (( ? #.r0ЇaHaDaRQF|I`#)( @ #.r00L)M!)0 )0"[# SSaEFˆBqˆ\o!(LM!BQB#.r005FˆBQB# SSaDaj !ˆBq-)0"[ # Ԉ000Ly(( -!ˆ´І00!(LKm# }QF\6!( -0"[ # ʈXo)( -9q[1BQ41.XbРQq A04hc" 1 CC1Fahy(( -0<cb7"&q2ܛ@Qz8 SoGaM (L dRo.WHGB:R.WHG E!)L+#ˆt0]\t_U1w5Vrwc<殅1?&]o"c>Oy#??cs{1>?cd} 5#|x̽@tC80tB( tA ґc-1$ |{}uc1u#at䘟z1O?϶>BnWnW(9INa8ޔ\NINa8\CNINa8NIAHr.Y$0vJr.y$0xHr.>dž$?xm$ $9%9+El()3E ()hG/r$п%9Bw{G ;Zу\z INaxQSf%9qFINaxQSYy.飘0\۞bpSsO<ᶧ0">y mO1E)) =<G =<񶧘 <ᶧ0۞bpSso{y mO1E)) =<^pSTOʀ.r 0ܟ2pRTOʀ IPapRTF!'e@AT30 0:)* NʀBT\aIPaPTf5'e@c "w21BT:FȀ.r 0u2]z Pa!21Bt-d@c 0u21BT:FȀ SE2Xo)* #e@RTCe@a>DPao):E=d@iqPaZCT3´ "!:Pao)* -e@RT]zKPao)1Ȁ C[~-D{"N) * D@@T7 CFA.r50C~Q@T! C?DQa( * e@7 0&]2ԛ@TzȀ SoPaM :E&?7tgCttgCTl.rMh0-]Ra!ZkeԣK:2jP˨?JM_˨9-s>ya?et耏]FǻNw1h.=eԉF2єu_e4c-kMXZF2e--1/ּ:2jMZFmyucX?1ZZF-0Z:e4L-YO cX?jx  _ <`s 1|+|W~nb1|'sV9kÇsõB9\w pmc9\+įõ4,bB 6Ұ@kiXH!6Pm剐K*ki@H !T 6ҀB.m-ki@H P4Ҁrpmcxr1c=Z1혟sΎ옟s7̎1wݶAwc?fc=o鏹kv7c?co@1c1?=c~;ǰ~Bw̿(a 0J C0J C)0J C9" CI" CY" Ci0Bx EPxk EPx EPXg!"k!م.e/zBX%B?/Yz bdK~^"B?/yɢD%!^z bax SX!0EALbaxSXŔ/Vō/Vŋ PXZ/Ѥ|0/VŃ/^ģIbah(_G Px Px[BXZ C+@bah(_, |0/^V Px[ C+@bah{h{h(|ȅpgSXl  ÝMca)|, w6Φ0)|, l /raЇaMcaiSX>0̤(|, 3F/ra0̤(|ȅЈRxԈBxQ S# E>FԈBxNj\o!|,L(BXQ/r05>FԈBXQ S# cajD!|ԈBx-"[  C#JcahD)|, (a&EA/b03 |,L  SDB>9A CKcao)|ؠ"[  CKE#AX[  C{~-Ŗ"), }ŖAlY>- CGA-/rز0Y[6bˋClybfQlY,- CEeahy(-Ė"<[b@lYZ- SA-/rز0 F-LQ SbBĨ91AQ CK1jao)Fb"[Q CK1E9AZ[Q CK1jao))- %0v֎ҋ\j )- %@RZZ;Q/g1jah(F- mŨ͢0Y6bPRz@RzHJ SWIiaj )-L] $ $@RZHJ SW1jabԃba@zK ĨÀ"Q S1EWjbcsGo̟1Nnx1Ώc>OyĨ??cs{1>?cd} 5Ĩ||̵ckM|O@xσ|O0 F= cp%[a?Kᘻ;a?a#AOQ 11?ϑcX?!F="ǰ~B{(b- "P(b- Չ"P(b- "P(bU"P(b"P(bՊ"P(b- "փ^ĢEka([^Eka(]^Eka(_Fk,bHk(e@X j-D~c%EَvBZg;\o~#,َv~3E5EMkaxcSZ^w6EMkaxkSz-寅O" >׋xn)- }寅O RZ_/⹥0 ^|% ^>׃>'PZ_ C@E(- }O0 ^>'PZ_ C@ka(b- :EB0\ "pSZ.tX ÅNkaSz #D>b- 3tX "0G Da`EkaXQZV\a`EkaXQZV^kajD!bȅ"ԈBzQX S# kajD!b=EF"֋\o!b-L(DBZQX S# kajD!b-L(D05^z kajD!b"ЈRz-E04F"ЈRz"֋Xo)b-LX S$" G)EN@z"RZ[X/b0DD(b"RzP"RZBR8[B g CSHlah )- M!HA8[B g/rp04^lah(- Ap04h"փ"֋@ZX SWkaj b-L] D!b"@ZJ0RSA_ Skaj? ~@z 䯅"_~G0]Fv2:eԈQ>o2 +(`e e_FǿN?et}2:cп.{7eoQ]Foʨ.QrM| PFs2#e.BD eT(˜PFτ1.70=e>(O g#cX?1]Fo1~_vP8 'Cvc(^n 勓ۍqr[%ۍqr[eۍqr[ۍqr13Nnbr[ۍqr[Uۍqr[ۍqr1T7Nn7ҜE "'iHs![Ln7"LۍkE-&idH##![Ln7HA#F5HGF42jQ!&\o1ߜn oNn78'ۍ vcxr 9Nn Ovc8-s'pr1 .-'Cm![Nn7>BJ mOiqa)-. =Ņᶧ0۞pSZ| #Ņ>-. s{J 0͢ ŅaEiqafQZ\YiV #0BZ\Y05_iqajD!-ȍ(Ņ05"[H S# iEF\o!-.L(Ņ05FԈBZ\QH/r05_zKiqahD)-ЈRZ\QJ C#JiqahD)->iE Ņ)iqa @Z\”E"Q ->iqao)-. -RZ\b)_zKiqao)-RZ\[J CKiqao)-. -EqOQra)J 1R\:FB|+DɅc(0v%֎\j J>Qrah(J. EɅ0<_@Z\ZH Siqajy ->iqa -ZM}$!-L}$O">ۋBr[Hn/b@g5M1wywca>澃1`70?6Hn;c1';c܏c?O1w =[c3|[|uc)=ox| =懽cs?Fcomڏ}ce?c_o1 1OHnOHnArv bP )=nazHnaHnaHEHEHEInaX"Ju CX"Ku CX"Lu CɤX0Mu dNu D%\o!-EE/B[BB?Zz n -rXO~*BB? ĺB[W=ź]OnaxS[=ź}OnaxSr[Jn/b@ma(疒'Pr[JnBr{-%O"[Jn C@E<>'Pr[Jn C@ma(- }%O0 ^>'Pr{Jn C@ma(- }%O $~>bpS{&ĺᶧX"WMuB[n{u mEX0 )- ,u 4b݃iźaEnafQ[YӬWMu 4b݃.b݋\5!-L]*ĺjB[Tu S Au/rX0u^z naR!ֽbԥB[Tu S naR!-L]*ĺKX"[u S E.b݋Xo)- ]*źKX0t.b݃^zKnaJ@[2* ĺ>-LAu/rTb݃bR{-ź!BEb݋Xo)- -źX0brX0tb1R{+ĺcX"W0u CHE&нQr[7Jn CFkaj? b-LD0^"~;"”-0Kӝ AX ӝ ka!b_DΆ"e;"֋xgsucĺ1_˨}->1gPF_A}c(Oe.`̟2:et/_FGN?etؗѩe.6uweԤQZF-P˨A-1fc.~FhZFs1?(Z2|]FscX?1b]F0b=#e7Ѡu 'FhZFmOXQ>#/ÈnP@ r81Pg r81Qg7JPK9)C=pvcbMpvcb]pvcbmpvcn مbpvc(bpvc(bpvc(n ٍ4rpv#i%zFZg b8Yrpv#͓i$zF' b8I4OyR#͓iTl![ g7i<ٍa"0pvc p818&n Opr14bDpr[ۍvch"8]m!jNn7&B<Ԝn M'x9Nn7&ۍvch"8Nn7&Bl"8Nn vch"8-&ۍvch"8Nn7&ۅrvc9-ˆps8[ȅمn =ml!F g7R81L8Yn ,gb81L8Yn ,g7i4ٍaB g7FB.nL(\1ݘQ g7FمrpvcjD1-zԈb8[ٍpvcjD1ݘQ g7FٍpvcjD1-zԈb8[ٍp-C#Јr814n ( 1-zƔmpvcJ`81[0HqpC..pvco9[g r81]8-zr8[ٍpvco9[g7ٍpvco9:Fg a81tn # 1- 1r14hru!CAi!M J7Vҍtcj0(ݘZB a1@c 4].,tc"1 ݘHB c1]YtEbZW$eꆃ,b;1,g0濂1s =?c?O1wG̟cs??ܡo, pc%1~p̷c -Zߗz Z1jqR J-!NQj2G$:(ZLSj2ODg*AB\:(ZCBeR J-"Ї8bʐ,AB⨥:(ÖZ蠌[jףCBG![hףCBG![hף`2:y -t?:؟=dB -![h@-tPʋAy:(B]Z蠼 P j)wʞ@sPʝ'P=rCn)wʞ@!~;eO[ʝ'P|-A(wʞ@sPʝ'P=r ;@sPʝqO9({·'P=r ;eO9({΋;9({·<!wʅN!Fȝ!wʅNsP.tʝy0BsP(wʃAyyr!EsPB*RѼE!)(R[JC -][y1jhļ7hļ|@ bC 1!^oDCַ̻gmά]h~s֏Z?kYyA!!>Y!dEX= zb s VOArb5VYcկ|_Yc>Vѯ5Vrew}^g妏Ջ>VX-|g_!k>`Ys*V_b*V߮ʟRrjC3=dX}:CX}Ǫ3=d՗3=d]LPY LQY=d}(Bև2J!d}(Bև2N!d}(Bև2R!dE> !/`VY+eBP,"XYʔqBP&-Bև2m!d}h󶇬󶇬󶇬󶇬󶇬󶇬󶇬XBևww/!Cy<@P d}(>gYiBև8!/⼅VЪ>UZՇ @iBPVhU?MhU*/ CYUE4U}(eVЪ>UZՇ @PVhUWhU*/*CYUE\U}(eVЪ>UZ`oUmoU*CYU}(w6ȃު>;ZՇrgC<{M ZՇ&CyV5[Շ&CyVIAPޤU}(oRЪ>7'C7x0VIAު>Em/`C[D{V-UEU}hhoUmoU"[ՇV-U}hhoU"[ՇVyV-UEЪ>EZ_y CYDU}((eV,Ъ{8oU}hJoUZ[ՇVamUZ[_Vު>ZՇB8oU}(B8oU}(-ZՇBP[hU~ CoU}(-eVy x"x>ԴM6= x>_χ60z<0zF<ajnֵ~~F3:%!Yg3:" Z?k~Fch|F'c\|F3:kP|Fg3:щXaݟknε~u~F7gtq~FZ6?[340^>g}FAk8?1^p~b=?  3zZg3zY_w?2x _Fer5!V2LaFes5:(A\qs5:( NdFe&s5ĩeFe2s5!VA\xj4A\qHs5:(cA\ }-VB?H/AX }-VB?H/AX yb5:H/AX {5:H/BzjtPF-AyMjtPFMAyUj4AYUAY 蠬\jtPVFir5:(WA4UAYUAYUAY *蠬\qjtPVF p5:(W p5:(W p5!VAX*蠬ʵa\ʵa\ya:Ha<;q:(Nʳb:(Nʳa<;q:(NʳA}ىAyv0tvM Cm0tvM C<0 ] ڮah-kbyaڮaڮaڮah-kbyaqr:(&kr:(&kr!AW^04 V`AX0 rǂa~aqr:(?ryaqr:(-r:(-r:(-ryr5:h OF(Φ Vb5:hA&Xy`5:h OFm`5iB?jt߻k}nݵ~L)YY;#kȳv>jtglOƳv0XbgP3֏Z?ځjt_ݺֵ֯~YWoյ~>kwZR]cP碵ZߊSZ)zѵL 'TkhO"zѵ>֟jt g8?]Bp~B5:UATj4(ӗCTeS5LhP0UATeS5YL!NcF2=ĉLhPf2U8 \j4(EFq8S5L!hF2=!MhP4UAT![F>؟yB5FD!>FkB5zȳѠPmׄjtC5 ڮ ![FkB5zѠPmׄj4h&TA5 ڮ hvMFyB5]CTeפj-UA5 ʮIhPvMFkR5+kR5z TA+X=ѠU,Pr"TAo ~K![F*U8o ~K![FR5ѠTej4(-UAo=y G+Wn+?6q g4A-4"4A}иmAzȳנ>h\5hC}Ը7)q][Z_s֏Z?%kDjPއ(T AyP'Ay'yP5h#< T j6FU!T=Bՠmj6FUyBBՠmmcP5h#A!T ![U1BzBՠl⼥P5(#A)T HjP6F U!T=U9BP5h @BCQ T]P5(-Ao)T=yKjP~P-Ao)T=yKjP[ URBՠeP5(- Z[rp~Bs '4k}}1hn;FmP258 dg35Ae>Ss MmPf45AeNSs{۠jjnqZSsyM!Nljn2 ԦvCetSs{Û۠ojnqSsNmP85AE[![hn7Co*![hn7`M-4![hn7`M5J![hn@mP^ ;5Ayi6(o 嵁۠7PsjnyBs;HmPn{jnrSs{_5A=į۠GmPn{jn6(=5A mOmPn{jnrSs۞C mO!嶧o{jnrSs۞۠嶧vC嶧6(=5A ImPOjnyAsmPއ 5Ayv۠Qs!jn>DmPއ 5Ay'4Ay~ Gއ m6Fhn1Bs{ ۠mm6Fhnyc6h#4n.uv@jݠƈv@n.uv@{-ԺA=jݠ]Pw˵ߡg*}FZ?'1NgtHgtB>gt<ֺXg3:X3:ѱNZ?љgt"kX~FZ_>m3Z>]hB&-Bנh 5u?o=}F{Ou?5X~Fz k5X~FOzыOu?3Zp~bmk8?kX~F_ZwP2׺A\dZ7kA\|ZwP&4׺2)͵iu8Y͵n5׺2 ZwPf6׺2k nuets͵ou8ε qumc;H1HAXү1AXү1kL-ֺk y y 3H{;H ү1by1p;[u坁kAyiZwPu彁kAyqZ7kA"׺A۞kAk ~}\mϵn>uZ7_׺rs;(=׺rs;(=׺rs;(=׺A۞k \mϵno{uZwPn{uZwPn{u?Z7kA۞kA?yn'ֺrr;('׺>ĵq;(C\~q;(C\׺>ĵq;(C\ya;(C\y!umcZw6Fu<k O0umcZ7#ֺ1bymXƈmXƈmXƈn-ֺ1by˵l\qr;(#׺1r;(#׺1r!ֺA)P,AZ7 ֺ`kAKQ rX~˵\qr;(ry˵\qr;(-׺r;(-׺r;(-׺ry}??}&lRdc>!ÃIq><(ÃIq>]Wum]WZ8m񠦓v]a[!Ńv]a[1NqP9LJ8)<09AeSx!Nu 2)<>NqPf;LJ8)<|8(x9$؟C9-![`a-Rt`a-Rt`a)XZ-Ay8(OįGqPn{ 8(=A)<mOqPn{ rSx۞C)<mO!嶧o{ rSx۞嶧xC嶧8(=A)<^8(W$Ň<- m!)hDm!)hDmqP-Ay8(O@ CR CR R򐂶8hK!A[ -^A[ ->-򼅶8hK!A[ -RmqЖBhB[Cm)-AY ->yKmqPBjR[,/B[|(%(rmq2h9D8h) Ň@[mqP-~Km![j'Ň8o-~Km![jR[e8(-Ao->y mqPB yHAxCR8(kAY(<ʚEqP, fQx5CJEU!CP%.:JEUr.:*9hTɇCCJ7J^+Z?(9Yd~H3֏Z?!k\FqP.t 8(:A)<ʅNqP.t rSx C)<ʅN!^B/t rSx \BxCB8(:A)<ʅNm!!hvA[|sh->9mq>hy8h{Ň}m8h{A-mq>hyB[Ce-A-GmqP>jQ[mt$@[|) AI->%rRm"Ayȡ8(9⼥8(?TR[|⼥8(-Ao-~KmqP[jR[Ce)AY ->!m!{hfQ[5⠬Ye͢8(kAY[C <-!`5ԮnA!<-qnA8@x[C>G4şaXg3: IZ?1Ngt_ø3:k>_gFg3?3G0.}Fkg}FKZ>3>o{Ѻm{k}qgd??w3z\TFgĸ3ZUk8?1..?5F>h^q_ø3Z1\8xP:ǃ2ҹ<X\xP&;ǃ2۹<w.esyLy.8<Iqg=ǃ2<yXqsy<(C }.esy .esyPpy<(o\+ǃNTpy<(o\yby1nvk}[Z략nouk}[;ݳҭn/t>7Z\돕krTgm%]Z_H~xoc? Z\믓p~B?֟&3eOǠ^Ç AD~8(3CeS?NpPf;AeS? O!xꇃ2>9OpP&=Ç8ʴ~8(EqS?O!}ꇃ2>OpP?A~8_R%%_RyB?I~8 ߤyB?IoRApP^(W-Ay~8(奂ᠼUP?|`o)ʝMpPlJ!>oٔ7DpPlJD8(w6%A)ʝMpPlJrgS";C)ʝM!ٔΦDlJrgS";ٔΦDxC)ʝMpPlJrgS";OlJv]A"|ȣOڇֿٯYǠ]ҳ,]iJk}Sz'5ioIڒw"=kko?=kǿ֟ubxk}{ܵߍA 'ko= EZ[o}p~/}kO(rǠ]?Ƞ\O\7(ÞrCeS{#rݠ }u2) \7(rݠ u2)= rݠ\%@nPu"\7(WA (]\ur#P{wA(={rݠ n\7h/)rr` -Ptr` (:y ntr` (:ln?-B{rݠ<]P u|AnP0( AyĠ\7(m\-8e\7(:A)]\?0urS{A)=rݠ\B\7(:A) ʅNnP.tuB\7(:庇xS rC) ʅNnP.turS rEuB\7(:A) ʅNnP.turS{ܠ3L>d%Zm%Rwh%6_3zn^[g-Uk}VhZgN5 `p~b}Fkk8?1>5~Fjk8?1k~Foj:vPc":vPc2:vPc?:vPncN:vPnc^:vPncn:6ױr?pA# -u\MuX:vP cxap;(WױAXʵu\\Ձu 3H? 1AX1AX1sL-ֱs yu yu 3H?+s !ֱAXʻױu젼mp;(\ױu젼qp;h-ֱAXR;(-A8; ~Cʝl!`6rgs;(w6rgs;(w6rgs;(w6A9; ʝll`vPl`vPl`?6w6rgs;(w6rgs;(w6rgAyqvP^\8AyqvP^\8`ŅAyqvP^\8 4vP^\8 4vP^\8 4vж7 `m{C `l\5aظ0uІ16Aظ05AظqSE׵~֏Z? k ݯ~G?Z?cok}Xdzzc/k}x֎uGgo1h\ZP{[ik5m/U:WQ= Z_Ơq}׵_Оu?׳g8?q]Ogp~B:Z65(5j\rPzw5A q=נԸN5(5Aq @kPj\v5(5xCP;C%q =AkPn j\q=˂נ\ԸAkP j\yBkנ\Ը5q _\Cи/.Xcӏ/|g_Yz+Y0bu"V׋]rEgeՇX}7;+ƭR5Vb /f`KYY'buՍ g/UcuZ^+Y>j^?ml2vbW/C[EC_E/$W 咁5ׇr@Pn_]Cm}( Ɓ΁:п";п>_Ļׇr@P_E}("y\Fп>ׇr!ATTT7_ʫ ׇE}XׇBPeH\=qEL q}(2$ $Z3\ː>kׇr-CPeH\ʵ C!qE!q}(2$2$ZZ\ː>kׇr-CPeH\=qE!q}(2$Z\ː>kׇr-CPeH\ʻ $>wH\ʻ $ׇnCy7@<0zPM qE=q}(&">wH\ڂ-h?-h=qE=q}h ZO\c-h=q}h ZO\ڂׇ-h=q}h ZO\mO\ڂ_y CY qE> ׇAP4H\ʂk'ׇVu&=q}hIO\&=qEMzCy7@8o!q}( B8o!q}(-$ׇBP[H\~ Co!q}(-TӤWe{loP{R$k q]Y;kl񬝌~0XY;kP3֏ijv" q]Z_0~׋gmXZ-j%ٳg$kl=k­`7gmXZ_uZc> Z%[dp~B_3ױg8?!qOckeG._rPCOGkP._?A=+נ\BԿ5(A eDkP#_B5(Wx)QkC DkP.'_=נPԿEkPn)_yBנUԿ嶢5 qwCп8gt>X3:X'3:ѹZ?ѡgt$kؿ~&hVhX g?|Fg:X>_3z_iѣg&m\k}hZgk5_p~b=}F`k8?>75ؿ~F`k8?kؿ~F_k8??r}\~U\f\uUmA+ pU;(WAظAܸ덫Aส+A个 5U\t\vP.;jxqU;(WrqU!VA{ [j6AA[A(A(Ah~ Ūv~B*,-HeqPA*_܅T&A,>܉TV8("A,HeqPnG*~8(7$ŇxGRY[C',MIeqPJ*,>\T򼅲8(&ŇyKpPv0Q<`/B<|E/-{x8h }x!FpPF(>yKpP~x-AC-x8(-Ao)^>=AYʚE}"|#KËex8(KAY"(Ae"Ň AYǮ(vu@Y|A&E(vu@YC>ePꀲOA:,>SFeq_~~RZ?&kĻܮT$JErPnX*rRE!^T$墥"-AlH>y ErP.\*rRK\T$"9_̂gCP$n![(g`-![(g`[.B|䠼Q7!**DErPޅH~ Er[(BoH"9h-ɃT$Z"?*r-S| AH>τ\T$Z"9(2AHʵLErPe*Z"9(2ɇx-SkCHʵLErPe*r-SkE(Z"9(2AHʵLErPe*r-Sk\8(8(8(/BtCtCtfAt!{fؚckDA[ :>m͂8hkDA[ :ښq,fAt|㠭Y⼥8(kELJ8o):ʚEqP,fQt5EqRt18أe1r"DAY(:ELJ8o):ʯ{⼥8(Qt|㠕ce8(-uŇ|+&E]qP6)+> ]qPꊃ'PW= eO]/Bt|DA: :qЮTBtԤҮ!:qЮBtC> EA:~(|F'a|F3:k|FgaX~>3}ѷ}k>>5 ?ohYvhUZ~F;g *?7'_ð3zgmk}h]]ag5 p~bX}F~k8?1,^>Ǿ5F/}k8?1,kFO ?3p~pH+AtHkAxHE\\$"yP.`. q<(0Ƀr s<(1Ƀrs<(1Ƀrs AHE\\$b"yPf.r"C,x?s<(74AX$-Er-ɃrSs<(w5Ƀr[s<(5Ƀrcs):Yֿ?kZ?g;_k#־/Y?u?kZֿg:x/=γWg˵_c޳Z[/ycPgQZ_Jak}#}ൾA 'kn?= uZ[Ovp~B:x ൾ? uZ_ 'k}m䢦8(W5eŇQVYqPkʊrcSV|eA)+>ܔGYqPnoʊrSV8(8eŇxSVC)+}NY!N8(:eŋ򼅬8(W;eŇy Yq$?򼅬8 yBV?򼅬8 [V쏮Y![ȊEYqP^(+;eAo!+~ Yq[ȊBVol8h-dAo>/ܼT@pPn^*Kr8(7/AyKpPn^*rR9CyK!޼Tro^*rR9ܼTrxCyKpPn^*rR9ܼTr8(7/Ay88(/%࠼DP|࠼DP|࠼DP|࠼DP!> qp!|>qp!A|m88hAۇ >q!Cm8-Aه(>yKqpP!Q}C/B|088hE -8!>DqpP^"(>yKqpP~i8-AC6Ke'PZ7(2UA ʵLoPexk3%A7of<$A?6!=oPG-mCof<$A7h3C>mC{|$$?Yֿ?kZ ]O|ֿyY?e?k$k}uy6e?=k%G&֟䞵Z{<w?ƭgOõ;ܳ2s/p~B_ }ߵߞwg8?!]np~B;Z_wk}ߵ?IoPnqrSߠ6GrS{$A)=ߠn7(;A) OoPx7(<忇xSC) }OoPn|!=y oP}yBC7( AY( @oPP{`-t;y o?7t;y o?` EyB)BEoPި( ~ o[BߠAo! ~K!~ rR{_Ay) KoPn^rRߠܼKoPn^7(7/忇xRߠܼ7(7/忋KoPn^rRߠܼ7(7/忋ɀ:ݠ<P't A't A't A'td@"t| !$t@{ nt@:ݠ-.mqNt@{:ݠ,.⼥N7( uAY\ BnPt=yKnВt@:`tV@{m tɀ:ݠ<P{:ݠ$F![tu8o Ob'1*_rQנ\tT墣5(PmjB!OM(_65| Ԅ5hSǦ&A5 "APmjBzȇנMM(_B !^*_}vP>kZ׾?g[_Z}k3u7??kZֿg^Z}cPeY*㘵T!P @5hC}mAz'ՠ>Tds@u}ǾֿSC_g5 T?|'}kqFgiF_ZѕbϨERg|FoUSZ3zީM 3zZ2}F/Tg>Wu3zZg20P]g*=J@3zp~bF@ak8?1Ph_g@3zp~r:([7p:(;p:(A9l [e5A$8l]A&8l}A(8l n^ak7 [e5_p:(bya렬yb:(Aʺa,a,a,yb:(Aҏ_W-W- = =yb:(aʋ&a~a~ayb:Ha?b:(-ak[5_rr:(7/rr:(7/rr:(7/Ay9l ޼ako^[uPn^[uPn^[?İ57/rr:(7/rr:(7/rr!An1O9OA _蜧L}kk_O}kC־Ad?g_ZŸ|k^_qo{k~>1LzÐޅ,YhG!k YN?ki6=kAd֟KӳZgZLkY[Zbz"ӵ43 'Dk]i?+= ZSz"1L 'Dk}_;3OL+ZDz'1 PQPԠle5(x6(@ vA! PaPzgԠleϠ5(A5(@ ʶAjP Pq5(;uPC<(@ AjP P!@=y伒eS:Er;pʗ?>]LdTcYA(@=TcYC(@=TcYE(@5eTcYG(@5TcYI(@5Co!@5ńCo!@5柷Co!@5柷՘28l̏8,[P孌Tcy-X(@5Tco!@5Tco!@5Co!@5m[P15J!cScj,ÕCǦX+52\15J WjLeRcj,ÕCԘp+52\1=J WjLeRcj,ÕScԘ 1=J WjLeRcj,ÕScԘpT|es.| SY>k,oY>޲|-G[OZ:cИr>dCˏ$݇,g\}#Y^dyGZK_FcИ;,?C"Y~7(Y~ZK+,?@ޟИ4kxBc*O'4$oNkxBc*NkxBc:, ,ޟИޟ,?1 ޟИƲmPj,ƲqPj,;ƲuPz7ԟA!Pj,Cl ԟBl!ԟBl"ԟ.B!n#ԟ>B!n$ԟNB!n%ԟ^Bl&ԟ ?=ScYO?=ScYQ?=ScYS?5EScYU?5eScYW?5Co?5Co?5Co?5Ԙ0=ñ1? ?=ScyGX^Ҩ?54Om[Om[Om[O?5Scowo)N5Kq!SeRz'Tc8X&/ũ2y)N5KqL^SqRj,C8'/ũ2y)N5KqL^SeR*8'/ũ2y)N5KqL^SeRj, qAq!MS#C>G8ũ|4!N5pS#T!ĩ|4!N5UC^ N5U_ q*qTc[ N5UTc[ N5UC^ N5UC\(N5UC\(N5UTcY(N5UTcY(NBz-ũ@jl9 ĩ@jq5-rqTc8X>)N=TcCo)15e*RcTXU2"j$vIAbjl$BHL.)HL풂.)HLX˻vIAb*.)HL풂/)HL풂HL奐C(1$kq.ˇ}-uY>|es.| SY>k,oY>޲|-G[OZ:crౖ>ud9C㎵#i,vOY^dyGZK7ck,?&oY~J$Y~HZK+,?#+ޟ$kxBb*Gz'$t$/GkxBb*FkxBb:,1 ,.ޟޟC, ,?Qbj,%ƲoPbj,%ƲsPbj,[%wCl%Ʋ}Pbz?B B!&B"6B#FB$VB%fBCo!15Co!15Co!155ScYT(15UScYV(15uScYX(1=ScYZ(1=Sc[\ 1=Scu[HLؘñ1?ñCo!15w4JL%ScyK[HLm[HLm[HLԘSco!15wo*RcTpX+U2\"=lHPpX+U2\"5J!WHeREzÕ*RcTpX+U2\"5J WHPpX+U2\"5J WH?5N!eCEj,˧4| 5Oi EA(j,˧4BEA(jlBC۴PcC(jlBQc۴Pئ=6!5i!O{EmC(zӞBQcⴧPX=2)5iOL{ E}K%)[e)s(jle ܦ@(*PX>)5Oi EPX~*,u< Y~,u< TcTc:С8Xũ2t(NBjl#ĩHq]q]q][q6{b.FSb8.FSb8.FSN8X>N)N=;ԯeSe?N3:|֟QF'tY>ƩFGpY>|?N,gt~F'[aYzFa3BѪ$˛3Zў$Yޒђv$Y2S 3zg|^, \8=[}Ʃ2?1N}FOVJ'ƩV8=U80N}F_ 2?1N}F kA'ƩSA'ƩqM8=L=w/pul"]p:XWF8\,[ Fpul&op:XWˆ`Q8\,[ eOpՈ eWpՈ e_pՈ egpul->p-eup-e}p-epu,15p:XVW2᪑[ WB᪑[ WR᪑[ W6#߷ң =* =*ңC W|b:X8\,lw6W~`o1\l-mpupub:[ W~\U`\U`\$p2yj,2yj,V#N^ZՈ2yj5uL^ZuL^Z!VF\U`\UßYxZUCZb:XM,_ܦe./<l K#O$,/DrM$,/DrM$,/DrM$,/<l K#N$./D҈2,2,ˇX^q"qy9z ,/[q`k.reX^![-XY빼4`y!_X^qpy9XF:\^ݚe[L#q9nM2|kb9nM2ۭY`51lfVkvkb9nM2ۭYoM2/Ĝe,s|]qi 4-i[<ѶxylY8˶xe9Ń|α-c[*/Gec2ۜe.Go6g o6gmY7}Lc2~Ŷ,Yb2~Ŷ,s~l. bl. bl~#h6\,c2\,c2Fl. 7Xfseh624e,CX24e,CX24l~#eh6Xfseh6Xftk2:\,jOc=3C-Lm1מmysͲ\{.YͲ\{~#\{.Ykosk6rfY=,˵j2ˠF[s2=,s2=,ӘkoYbeP{.#מ-ȵb=[ko#מ\{.OL='gy懠sò|e,W,޵txǠٔa-mD>$Zچdy]HW "${ZZƠٔA-g,9r氖YdqXMYƠ\MYEDYMY~uG5?ٔ5?fS_fSdsa Oh6ei Oh6eId}I,X62oL!dƲPi, e'EY,%eeƲPyZerBY'e˂BY(e˒BY)eBY*eBY+eBY,eBYC[(4ͅCo!4텲Co!4 Lca(4-Lcc(4MLce(<Lcg(<Lci(<Lc~7>Lc~76wnln,,[2[2啍Co!4Co!Bil-dƶBy-d~ Ye~ YOo<ē@奱L^*/$Pyi,KcT^X&/2y4K!N^*/eRyyKcT^X&/2y4K奱L^*/P^X&/2y4L*/e:Pyi,ӁKcT^ 4g 2Lcy,x!4g */mAyil CeP^ 4Y2(/mAyyKceP^,fT^,4YF奱2*/eQyi,K!8˨4YF奱P^[1k@yyB(/+K!ĕXOqLA+e R\i,SJcW=2<@!Ic <ħ.J$풂D/)H$풂D.)H$풂Dؚ2H$*k$BH$.)H$婋IcDX>f(4J$cAJ$??$|eD^KY,fY>k,QDRZ:Dz|eC,gX,teӻ${f-5V#KZidyF:#ZZ @"с,7@Y DRc1H$DRCYc OH$eyH_DRDr IY~ZIY$/5?!5?! Y~ ZIY~w5?)t<Ŀ :RA:ƲZPx:zA!Ph,+ƲdPh,kƲhPh,ƲlPxƲpPx+ƲtPxkƲxPh,BqX Xv X eXv eX e#[e+[e3[[ט_1BCo!t4Co!t42 X(t<BG!ƶBhl-|Bh):~ : !t4*C<&TAX  U24Le e,Si,c*HcTAX X2U84L!e e,Si,c*HcTAX R!e e,Si,c*H2:4A! PA  *C X08?,gtg As3:Ų|~FG`Y>>N,ޯ+g^֚g(5 򌊄g$<AׂgT#<A'VϨD3ѯ2?|F?u<_:d+g4$+ȯ+g,$+g?'!ޟXA> ޟXA>Ǡg$+gށdxr8X?犃esh̹`8W4)\q+$s8Xv6`8W,犃e'\ql+q/\ql+q7\ql+q?\ql+sŇ+qM\q, +qU\q, +?6抃ea\q +s6p8X[[ [-抃L;HϴL;HϴLsE#߷+3[ˣFo1W,[+\!抃m\q+\qb8[~C~췜+̹`˜+̹ 1W,cs29W,cs29W41\qe89W,csE#eX\qeX\qebhı̹`˜+D0W,s2:8W,s2:8W|`y\+7 Nj`y\!抃 s60Wl s60Wl s60Wl sE#2,\ш+Yƹ8W,s28W,s28W|g犃eq8ز [8 劃\GH\$.c=eq8Xeq8XϟgyY^~1n0l -`el7Ö!Fel7Öq`2 [ [Ƈ2G2n#Fe,?shč[- ?*|eD^KY,fY>k,QQZ:Dz|eC,gX,teӻH"YއdyZKې,/C *6Y^dyZK/Z\AkYZ ˩, kxB(˙kxB(ˋ,kxB(˿ kxB(FkxB8-, -,?{ޟ2cޟ2K,? -,#ޟT$"!2ɩH<ijHELs*|Bh,cDcT$"X?2H4CoH4%CoH4ECoH4CoH4Vc~l=Lj̏B("ј["XH<Dcy"[(P$ƶBx-Ɯ~ EP$~ EDcoH"X22H4LE!*P$X"X22H4LE!(e,SxcDcT$X"X22H4LEe*P$X"X22?)S!_o)H!_5:De"QxW r'@xw4B! :BiWyئ 6e4)MAhhBhlSZFc2qZFc2≧X 2e4)H-LAj2X ƖM@hl2[;-rE!CSh,rEcW+˸\XBYrEcy\X??ϟUIc!<Ic!k,QDRZ:Dz|eC,gX,teӻ$-L0Ydy[K,/`6Y^dyZK$N kI Y'dXKk,N ,wcH ,/Dz ,/Ʋ ,('$cHSޟH;,?C ,A ,?@ޟH,bI!& eSx'BGc:⩢X22)t4LLg e>Sh,BC:˔42)t3+Ggt`yNa"Ϊ,gtRAs3:}FGgt@ex>1|F;,hhC{F 3dy={F3ZΞn&K3̞b&a",P=Ϩg]D_ OL$rvcޟH>2?1|F?D0|FT2?1|FTJ'&J'&u=NDL=/qLU.\qLV.l!er8X,er8X,er8X-F\:a˥-erhđ˥`\:˥C,8yt,KG#N_. t,3K2t,sK2t,K2t4}`\:qLe.|b8HFotAz4Az͇X:q7|b8Xމt4}`y+-t,F\:'#.|b8H`otl-m!mq\:̥ e,s8X2e,s8X2e,s8X2F<&\:̥2e,shı̥`\:̥`\:̥C,8t,2\9,#3H#H ,#gP)`P)`P)C (s F0,1P€r,PHč`HHč`HH>F'͍Cl$7/7__|~,߼e饑1l12r]Ƙ^ˇ^2r]Ƙ^vcz9B6L/kZ6L/bz9X>8,e^;F\~9,e^p7,ZY>|fґ+VZ:|Z 峺,TY>k1S*ˇt-QY>|BeRW'{,}kiOw>Y^ ,{kiRda-}r "%, kir"ޟ^r2ޟ^-+ޟ^-ޟ^򮽆'c^ ޟ^,n ,?m ,kޟ^g,EQ@i,ӑJcP˄R I (eLR@i,JcP˰X%80)4I!M (elR@yJcPR!O (eR@y3JcPl(eR@i,JcPP|B@i鈱P~ P !4JcoJcPX B(e,S@i,cJcPX 2)<ıLe (q,S@i,cJcPXX2B(e2\)4IH (eDR@i,#!}PWˈXF$Օ2"4IuH+PW,/)+孆C4+PW[ Օ|IA]i,tSg,Ӂ"?ctXE~B"?c+/ ;`jkxvԓp-mN(+Zey!}P 2(˻ZƠԓOYY]KSrr Z d7` O(dS| J5?ԓ}\5?ԓ]\W5?ԓ=| O(Ơԓ1RO0ROXJ=YBXJ=YĒ/1_b);bX,곌e͢>7곌e͢>_?25C|>Z賌f>z賌h>X@%>X>곌e>>곌n>>곌e>0_g#-'Z,te4a峼,1dc,˧XZ:ò|e^KW,^Y>kxvϒr-퓲N6)Z%eyMRɵ )[ZƠϒOYYK>3, -?B@_>K1>KuY>KuY>K5?>Kߵ>KeM{ OdA{ Od5[>K?d k,cr`˜K :JeQe,,cx`ȣX%X8(2G !>JeQu,c`K !NAJeRu,c`4X!%X2)2H LEJe.Re,Co!2H !߷`˄[H[Hܷ`#1?B !:,cyXl(2GJن,cyXn(2JCo!2 ,co!2,!$XƶBel-$Xƶ)-%X2):cB ,c˔`XX2%X2):cB eJ@e,cC˔`XX2%X2)2L'X'%X2(2YF!2 e\Q+e,Z)cWJ˸VXRBheP+uRnB!_J˻ RBh݄ZC02jJ ~~G!!b !,KR˲D!j PSHe,B*c9R !BHuȿlCHe,oRRR˛T8W(2!eTVƲIQee,UVƲIQee,UVB*+c+R2&*+cR2.*+c-SZ*+cY 2*+ciT:č*+cPYdH?3:ϲ|i~FeY>$VV1~FbY>?,gt|}FWg+gmvgj>MSgg>5m <|VV}3'3~g~d3 ++ޟXY=M-2?zF[3Zexbe6xޟXY}VVZ'VV=[Y=X?jޟXY=OgeJ iŭClVj,nVj-nVj.n8,[)#0nVʈC[2Ƹ,[Jqq+5XRFgJ ƭgReq+5XReq+5XfReq+5XRFo,3[)#߷J 9ǭ[l)-R8HO8HO[)#߷J gn R[­`y~VjͲ|e,,'y %Y>k)Cΰ,aY>|+˧W]dy]K,/Y^Beyt--1dJ?Ͼ,+˿@|nIW1nI|YnIW|YnI5?[nInIߐe y Odx OdXߎnI?d k O*P&H2XI2L2De&*e8Qt$cPT&∢2XI8L2AEe**P&ⴢ2XI8L2Ee!N-*enQd,$c]T&2XI2L:$cbT&} eL2*2ɘ 2ɘ 0=c1? L:$cyX2XVL2*y$cy`2XXL2G*噅ʤCoL2ߞ孅$cym2X[LBdl-IƶBdl-Iƶ)-IxLLBd,c$cT&X2X2IxLL2Le!*e,Stc$cT&X2IOT&ˈ2G$IBetPBd,8%D \'$DrRBtH} !!ABd,  !!2;*!!TBTBrB%d,{UBƲ'P%d,*!c9T ˹JX-UBH !!H孆Cu"cyXBJ !!2C>}A ˫%D*@ C\y(!2"c . !2"c. !2u !!2Վ"cy!!2C\')!2i a !ZKGZO,hY>k8i,gy-eY>c9^KXO,te ί,_Y>|xBB${ZZSeyK%UwԵ$* ,kiATӵAB$_TZ}V_geٵOޟ? ޟ/[ޟ/ޟz'$Dc{ޟc, ,? ,#ޟ',aGR_d,"cX̢XE2/2E}!.ꋌezQ_t"c` XE2Ǩ/B_t"cf8XE|a@_d,C"ck`XFE2ܨ/2F}!߷ˈ[苌eQ_t-Ex-Eh/%ј_%Q}!߷˫ EB}P_d,o/ EB}-h E|B_d?LC EC} %D2)!Bc,wE9rQ#\R%EQ\R%Q|SsGcĤFi!ln,.eq(_,.eqX(!BBd,%DWF QBd,e_%DWF "c[V !2J "cy !2J !!2C>}A ˇ?%DO C\y(!2"c . !2"c. !2OH'$D K M?mI{Ą{҉^Kz-oq^Ky-tGy-d[L9t!t ^K{~]Kw-oó~Ե%u-%a-mkiA]KwAXKZZNہ-&DkGص'ص Zv-m үko3&Dkiշń ZZҖmxƄh-ki6?cBo3&Do3&Dkw-~ޟ1!ZK߆gL+Zz6?cB>ַG/ QN aY9!:,S+'DenL8rBtXWNB_9!:,,'D!ΰ)2rBGYN0 _,'De/;!&De谌2rBtX[Nx _mLˈ _mL˘ _mLK_mLKazI x^KbLBocBtX^]rBtX]rBtX^^rBtX^rBtX^_rBtX_rBtv,&D!߷1!:L ay ay ay bL{LN~öƄ1!:lퟲLޜɛ2ysBtX&oNB< 9!:,7'D!ɛOBL,.WB qJ \ -((/?Y]'|.e?ڏ4 gX,b 9,{B.vBrsXrycsXrygygygygygycsXs19,O#9 O0eOȭ_G3>eOȭaBϭaBϭaY\r[.">ak#bs>M,MsXJ][ö 9,gthљ}FGVO3:>*˧/ÜUY>>s*gtH#N3:Ĝ.BexbV/ÜG'˲|I<ٍ,te^KGXO,`Y>k++g1ndy]K+,ovY^eyyu-⺖1ndKYr-l)˿Z򏖲ZZ dKYr Ond3` 5?!OYXY^ey_Y^f Yur OndTOF_NFMe#k Ond K?4_(1c(9ijGY1FM 5jreQscmp&X5981GM 9jr✣&X&59gML;jrcx̣&X5921GM>jrqQc,󏚜Co1HM!߷+!߷+12WFc~e4WF!49|Bc,O2ˣ 59,CM)1!d7~Pvcld7V)@vcld7V*@vcB!1 ٍM^nNXn񃘲c yndH-Zϳ,te0Y壼N,1ndS,ˇXZ:²|e]KWO,^Y9݌Av# ZoeyV۵#j+˛,/ki?VڵAv#WYir-K,,YQR\YFf Ond@?F d` Ond` On  FHe}t Ondqt Ond+K?Fdk ϗ59ƲRPc,K59ƲVPsjAM jreQsӏc&GM!Ajre Rs(&1qHM Djre$Rc,Cc`&G#5929HM Hjr&ǘ &ǘ 0=A1?A 9Go1jr͆cy&,hrm͂&,hrm͂&[hr1'jrcyơ&GMPc,o9k59ƶBcl-49ƶBs-592\1JM!cSc,ÕCǦ&X+e72t(BvsC!5ƲSY# 5ƲSYc,k35xSY#Xgwv91Z 9[ Bc,3c?6;4BM!}ˠ&>jreQsct%EM!!Ac,59M<6PsH˭IMc1MM![hr僘c &X>1݄!49Pc(49Ɩ0@clc1֐ Whrp&؆+49|'@clC &X><#-'gtq3:(I~F˰yFXO3: ~F'gt~e>rv2lrт+3Zov[Yj6g~gre<&Oh~|FK>%ey)xF?J>$exb ޟ dxb dxbe<ޟ<g>*g8*g>dxb󌾰 ?ye?W+[ >F;!>eUg,+\ύKQ6'` 1-g@erda`qr4XF.g@er3 #]΀ wf@erd;329,3329,s329,3 #Nc΀< Ȉ3292} z h^=Ә_=s^=bd3D`y$ h<q4v0̀`0l;f@m -f@  3n`y9 !f@3|`y@ he~rcO.}|΀ !f@F:\ UKXqtp3XVu.}f̥oj.}b3X6xSh`#4~Fh6BF ΍`p#4XU>?@ h :΀x1r4Xg@Ft AǥC,}瀥`1>=K#9`3XnMyX!в|e8,ˇYϲ,te A#x-bY>IJ|,XZ:|zeمg bY~YKﲼ*+ZdyATӵr*˻ZZ _eƵ ?/򯋲ZZ dEYeq Oyd3` b5?!OYXbY^ey_bY^g bY~,YbY QB\bY~\bYʒ召5?!/,YZb1yeK(Bc, <ƲPsnB1!QvueRszc<^X&*:8S1JUuh^X+:g Xuzc˘^X-:2j1aK[uqRc,#zCإ^[ua[uaӘ6æ1?læzCo1W uzcy ^,um͂^,um͂^,u^ǘ{c[15 zcy^GQc,/D:JDQcl-:xR#WXQJE|,+?C[X[\}K~KTG c5~F<~H<J<~L<N| Rϻ r#N,hY>ϲ|i,gYZ:ɲ| rcN,bY>k ,w-_Y>|xeB2,?b7 Y~5Tе#*+,oki?SϵA"?rkECYIN[KK,'?ǭ ,oc ,o ,o , D.'D.Û,'D.ޟW,d ,aޟ_Y`1 C#F1T&C!-Rc, 0Hl4T˜FZ*`qRc, CTȥX.0B(` cT=02}9?{(`eSc,3 cTX&1029iLc*`q"Sc,3 CT!߷P1zWOc~4WO!0|Bc,ODT#0LDYPۚYPۚYP} 1olk0ƶfAc,/GT1#*` cy@X1G$*`m[*`e,13R;c,13ŸOc?~?Oc٩9;c٩1co1co1%9:::B/C1iOL{uQc,*^:29AGC>P F![nUcv1HjgcvX"1ŅcY\B;s_\v 36W1c \vF팱hgm@;ssc+\vXVXjg~ Y>kD,y-fY>̲|e(,y Y>k!3,`Y>|~+ˇWV.3cZzY~p-:(Zdy7A;#{Zzѐ_dW$5Oa|ERXsdW$5ƲPXc, 5ƲPX#")1a km@Xcl-5Z#ac56 9a|N<#-'gtq3:(I~F0yFXO3: ~F'gt~e>rv12 k,~<Ǐg>dyGxF[3ZN'3ћ,/_a3zxF35~˓~ȓa3z72 kdxbX6gpİz~a3za͗aX&dxbX~{Fİ\'Úg>dxbX󌾰 O k#ur;3XngClg˒`Ys1*3evƈ u󘇘 iy)1ercęy` yCcNjy`2`91/1er3X,1er3XF-1er3X-1F y.1ercy =lؖ%c۲y`y˲|I<y,te^KGXO,`Y>k++g1cdc- !ovYޓdyM-i-!oki9Dz!~!! cM1ۄ CsX9?*`б@EoĤX>1)r1OL\'&E._"cĤXv\e7Xv\ ]ە ][JE]ە !_ە !_˂F˯w@"Gz-hY>в|e8,ˇYϲ,te A"x-bY>IJ|,XZ:|zeمe "Y~YK{,È,A_Edyj-"""ki9E_CdǾh!?/}CZZ d ޟO|c ,'˿ ,'˿ ,2 D.°'D. ˯ kxB"ZkxB"_Y'D.%XkxB"_WcԸC! R"Xj\eq1eCsRX*2T1F0*UqQb,cJCdT(RT1qF!!Ab,#JcjTXRX*2ڨT1F!7*UeQr#JcrT☣R*hψxјP} Pb,.T˻ *ƶ@bl *ƶ@bl *ƶ@r-*;-.PC *CJcyRXcT1*UMJcyRXeT9J!(rSSb,75(rSS.)Q咢/)Q%E1\R%E1\R%E1\RJcYT9PT1JcYT1eY%X*X'*XG*X9c1{2C 2!d,rQb,e,BPr+=D1!n5W$(Pb,_VC1|ERb, (ƲPb, (BQb.FQb.FQ{Qv1B".FQb/FQb/FQbF F#N,hY>ϲ|i,gYZ:ɲ| FcN,bY>k ,w-_Y>|xeB21,?=A?dC>Ҏ !ki?GY~XK(,-d0?,gt cgte?Cΰ,gt~FW3:>+gc/=Mѫ3z4=<g`"3z.yF1,/_13Q/9~|F?>_ey)xF>exb~2Qdxb~{F?=`< ޟ< ޟ|(B'(=Z}h}e=,ޟ0'w; #}r1X>0'GeKHcli_#i -#r1XT4Ex'p1X.8baĭ ,8ۏ7Xp R1~ȿ` rkr1XnM.8`y7È\p [ {˭-GlۥfǦ}E\"E:'*O1),SNJ唓r9!&%rI_Wdv юcR2ضqLJbRbmcR2ضqLJ6I`;|1)yI`1)l8&%F1)l8&%F1)l8$%fZZhey]K+V,WY^kiblDZZPeye*˫T,ѵDey d#rfY~7gY~5YKs,g#r6fYFd9YKd#r6pC,(?_plDld OFd?YplDTdEe OFd9e OF 委5?!wY~FYYL و,ߤd"'d#|K jC(B6b,e#2P6re#2Pa,>Sa,?ƲS!w?e-rPqc9(0c9 (0Ӏc9(0C<(0SC<(0C<(0c~_35c~_;LkfkB?yX*(0 ?层cy?mN?mN[?ecyX^/(0 ?A IQa,BH8+X2J8+X2J8+2J8+2J8+ J} w J}!ɠBa,(2Ra,(2&T"!2Pr#! ! ! !\O4P4P 1͘cٌ 9/cy2l*Ce32De!= 1SO CF\)89 1'r!/ˬI̚!89c; 81c; 81!81_c; 81C> 81C> 81!'流NªEkkYX`mqr= ,'TJŅj,,S[\Hmq%j+rpb5gaŷ[|,bpbYl18, bpbY⏏ۣ-x~[w<3','gp98ś-^p-YNlm Î-ާp-^p-ޤl"ugNle3?spb73?7Y,&edL#Л|'MDIb!)Y,;;$%ĽŲCRA!)Y,;<$%䥙ŲCRA^9)Y,;=$%ed,ŲCRX|HJ>>$%e߇䃸CRX~HJ>?$%ed1-_ 1'%6'%)Ibyd_$%+ARX2HJ>_e ,b;(ee,b2BXFXQ󿲃`, 22fAb*cY,_|rƲ~b'g,1cYl?OX9cY,d,僸'@ƲX^\ c ,2wy惼rXN`>+r:]N~ mn˓D7dэ1G7D7efe9YlgYnYcn>gYnYvfe9Yl Cnkβstβ,,G7,G7,,b;01U3Zh}F g\ey>k<*+-gNey>U3ZD }F YYF7=KggQt#s3nQtYQtY~bt󌢛gEE7g,gˬ On+ѯat#gtcyF<3pTdbtk<7,< 3Op]dbtnR"%gtzF(< ONgD`)81W`+8,33etƈ;43etƈ43etƈ;53etKә_s:3XvlNg˞`ٵ9,63etƈ{73etƈ73etƈ{83etfll!3Fo1, 'Ngˣ3Yә`yZtf Q#﷘ ҏ十ә`ygt!3婁ә/r:cMәظ ρ#~ܸe룸ȘȘ1?Co!.2[8ErXn]"cS\d,qFNq~ q1r1X"!Er?Xn R"d, !cY`D%BƲ(:F,0JqQ"d,')H(帢XʛeIDY!!Ȓ,X^(K2%ʒ%eI|fCdlg6dIvfCdlg6dIvfC$,lȒ̆,lȒ̆,*Ȓhg6dIBȒ̆,lȒyׄ,lȒ̆,lȒ~޷YZZhey]K+V,WY^kib,IZZPeye*˫T,ѵDey YdIC@DB>DD^DF~DH˞DJ˾D!LD!ND!PE1+1Wc~1W!CB?d,eꇌL\2K3Crm~X.ՙ!c5,g`z}FUW3Z3ZRB}FT3Zh>5*Kg@Яa?TYѣ3z|F,ϨzFnMggdy5쇞{3znwgڞS,p~=C2?zFWgt3>=ۓ O쇞I'C3z3P= O쇞eJ'C&.R2?zFgt3ApDh0 =qDhl4qDhl6qDhl8 -p"4XNÉ`z82É`~82ĉ`ق82&ĉ`ن8AzB9!#s 1'BN̉`s"4XŜ 1'Bn̉`s"4XǜyDhrIDh\9,eNb"4Xʜ 2'BȉCLDh!N8,k!#!NDȈkV:N{'B1,Oтl:NłrD!&Be hL\ !V@eb hL\C hL\ +21r4X&Fbd+ V@W(X R4~J ?`+rs4XN{'p4X~U Ȉ=W@ Ȉ=W@eb hLyQc"4X82Dh<;q"dE`98z`ygq3Xއ81gqcCvccCvc3N{ }i`;1yO{ }i`;1l=>g!>gycgyg }ҪE+kVZZ`eyr]KU>TJ*t--SY^Hey%*+TO} Qt-<˥,>kiGdl-r&gkiG_dl-]eL_dl-\&˯ekB#Oec ,_d'>| ;h O} pG/T|ZBYL ,ߤd"'>|K j O }eX }6Cl4VCl6vCl8˖Cl:˶Cl<C!n>C!n@D!nB6D1?C1?c~1!>8Qc,7b }NL܊)1{1>r3XBcSs->i%Bc&Sc,e }]Bc-S3H-,jyePs˄ZcY&2X Qc,#>21Rc,#>21R#2 }7}W3 >C >S >c >B}eXF }q7X~UG }eG }ebX&Ɵ21Rt+* cy W!1BCo!1BGZZhey]K+V,WY^kibGZZPeye*˫T,ѵDey >&kkig5Y~U[K>&/jk/i&˯ik4Y~J[BY~Gg O}d#W5?!{,_spG8kB3,澆'>|ej O}d&%5?![,_pGoPkRs<ƲPs; <ƲPs <ƲPs; <ƲPc, <ƲPc,; <ƲPc, qEGѵ4 *s,kiEY~ZK3,?T;ZƠqG*Y~ZKW}Y~*Y~ZK,Nи4.kB"Yͬ ,_ed&'4.{иA"˿E ,_d>'4.|ZYIEj Oh\d%˗5?qNA2C,(c12C0(c1-2C4(c1m2c8(c12c<(c12c@(c9-2cD(c9m2cH(c9ĭ2cL(c1c~1c1#2X^Kl)c1-e,rX 2cRb,\Xywo!c92cRr-d,r㥌X Rr+2cY JXVe,Ʋ(c1@2cY e,x"Qb,/e,J@!HKe,rSƬSb,c5.8fQb,c5.q11cq11cqBrccc cn\Wh\wh\иJԸJ@!ԸJ!ԸJYԸˏ y搿` CV 1' `[Pc,/.ˋ 0B!/M`e搗&06 @sȣ06 @cl06 @cl0B`yF`mF`'X6 @#F`mG`m[`mwc#˫-gfђ3Zhj}F0yFKUW3Zh2}F-gFey>賲>15 `ќ*˳3RѐfTYQg ,3zzF[޶3zْk=g-<_ <3p]eMF'0l0N%gtzF)<˔ O `M]dbnQ%gt5XyXW{X˗}X`c,;w,eeܱ };#ܱ ;#ܱ ;#ܱ =;AzUWAzU1WAzUWرqe\Oc,TX;rIe\Sc,UXU;rY-v,T/ +w,`r;rqe\]c,WXJň+;c1JeXc,+;rň'w,ܱ >w,F,gX ÑgTey>֩,/gJ"}FkT3Zh>+Ñ_pƲ< < h.9Mh(~F3,h"~F,3ы,= W-.f[\ga)J6YXƶmq5lKW-.೰~mq{k7!8UAgj[mq> C-Ӷ8N4}[mq> Ӂ,!8G}^-lqG0bbm 6Dې3?sbm-!g6Apm-z~gnCd  ۖ-^pm-޴pm-^lugnCle73? P(<cR(<:cT(<ZcV(<> Ųb Y(<˪ーns>G?a`1> |0< ,Ƈ0`̅qc\X,((<E rc\X,)(<˅ rーc1^bYAXVPxsXWPxYUβ2r} ‘ŲL  pd,G>‘ŲL  .Gm‘bqB8AsB8XnEJUbР* \, 2AUX4JP, UbР*Y,T%e@d hPsUAР*Ylܹ*Ylܹ*Yl/ݹ*YUb{U;W%2AU_%W%䅪dP,rBUXN^J*Y,T%UbydCUXfJ>mJlUB UbM* GqQT=bjGY,S (eeL5У|ܣ,&(,(m=bjrئܣ,&(ܣ|ܣ,&(m=bjr~=b M5G1eM5GYlSMQ>SMQT{~{6iz+ zeyE,fY^̲R<=,㵴ey"^KkX,`Y^ki+ˋw .()A)e p2X)ep0H1YA ]čxr2HAE|.tAURńr5 e\N8H,RrE e\R8H,Rxr2H? )A/rs2XnN_؜ r"qs2XN$nNˉ͉O$nNˉ͉O$nNˉSNx"q9ˑrQrmc9bC,Gۊrdx,Gۊrdx,Gl+#x.GˊrĈ+ˑ2q92Xf0.G `yg0.G0#yˑ@ ##`\퇂C<)H1 X@%c=O})7iGvDiGrDRc,CU9LBc,U9r,Sc,2U9r,Ss˄c99eUTLUX)O9k dB@&dl dB@&dl dB@&dl dB@&dl dBP&d, eBP&d, eBP&d,#,eB2R&$LGXʄ2!c{L؞!2L^!:{Ȅ K ~K<~-eB2R&t-eB2R&d,#,eB2R&d,< +eBO!﷐ >eBd@AhV>AhV>AhVX>AjVX>AjVX>AjelVJ!JJ/JoJs+el?_@+u?`@+%VXfjelV[j jq}Z)cB+e,35R2SS+e,35R2SS+eJoJ~ A!>SP+e,qP+u-R;RKRBhyJ!! R F!! R F!`R F!B*c :=B*c 2 B*c 2 B*!T'@Hel3T6AHel3TV@He I BHel3T6AHu3T6AHu-T6AHu-TCg1>g%<Ag<} Y^h?/ˋgʗ3ZhR=k,O!3p<3nd.!cƐ]4=Cu-]2CljgtxF R=ƐJ'T(zF! O QHeCgb.C!3pĐ]Ӟ-M'T&Cgt?{F3R=*W98,g'X1,'X@ki` Crq5X6NWk|$` τp`e &XaāAzw c~wAzx NՍryk\8,8Nrk\8,9N8p5H `;˰lgVVlgVV,jeXY +rq5XYN8z `h9,3-'Xkٜ`qq5XlN8,g6'XF<9,g6'Xkٜ` 33.#Xv /ˮec5ؾl,ۗe`l_6]Fl_6]F,_6]F,_6]k|\v /ˮXvqke`)ˮc ]Tv S2/*Xv=IJkL\v i.#\v V2~-]e!]ek\v 9ˮ2s5Xx.˛]Fo,?pe.ˏ.\vyŲke`ˮXvyŲ!?g,g_e@k h} /#o} /#o}  /#o}  6a54̾ۀC̾a`54̾ۀ`0l f_xif_1lf_m@f_m@-f_m@ˈ-e_}ǰYdKa-}W ZdK?ey_K_׾,/}Y^kie/˫~--1ȾdN& YD#kiۈ,_Fd.& YEd-c}-D/!kG | Z'd!˷5?!d_kB%ٗ,g_kB%ٗ, ٗ,? d_|S[/Y-m OȾd'd_|?}l ÿ crR0f, cBƌ `XB ƌ0`XC ƌ@`XDjŒ&Cf,5a0c ;Є#!N#Ԅ#1?rGc~0G!4a8Pf,:jŒfGM 35ar&XnxԄ*+c;:}*+c;2*+c;2*+c;,c,):ђ,!$X2]Re,%%X2aRe,G$%X4)2#C\`I !/MH判XHJ判XHJ`W9"):=-c 2=-c 2=-c 2=C 2=C(2=C(2=-c(2=-c(Bu{[s[[[oۯ"o"o !2-cqCo)2!qxXo~K\(2[r=xXo-cyx[g-cCo!2O(2P(Bu-[Be@xX4e@xX4yÀxX4yÀx4yÀx4m@x4m@xK!ooۀ hoۀU+ok4oۀ ho ho~ ho~K֟ -Yҷ ˟, !@?Y d#XK߀,coֿ,/Y^kiڗ/+--|Y^eyկE?,I҄!7Y}d-M|ˈ,Ed!7Yb -Y%d-Do |YK,_?d'[|xk Od9ޒxk Od9ޒ5?!ޒ5?!xKojkB%4Y ,_pxKg|=[-Y}}Ñ.c92.c9"Be,$]rNRe,'%]rVRe,%]r^~}.c2.cĨBel_].c~9Q.c~1b/ "G*Ge\2]rX.9Aީ!2Cީ!2,c۩!2,c۩!2AJe<DJ`ˌH L`˜H e`ҤX2JqiRe,g%X4!2,c9(2,c9(Bug%Xr}Wnon&on&on&on!&on!&onB!&onB&onB&o !:݄-c9-cA-cI-cWwoO#oˏ#o~K<Qu-[rx[bA\,(2[rxX.o[Be,?Pu/oO'o~ |BBCo!Be,[2Qe,[2Qu[2Qu[6Au[6Ael[6Ael[ByÀx4m@x4ZxX6A%x4m@x4m@x[m@x[~`>Yѧg!w>g<@g [3ZFK|Y^h?eV,/_xIdyxF7gt!yFY.m]F]D'gtyFY+~ gt yFY~yFWgtyFY'>db OQ-o='g.g._xdbi&gtE3= O׾e`9:2ˮr|ree`9B,(]k\v ˮrr-#xk|ao-[+xm1#*o  C8p5X.}o k[Cۮ`5z`5l&VVmjXY ]+kr5Xk&l[ YFjz}`jl[ Ym>km5gy>km5gq>kl5gq>kl5g p5XbeĭY7ۯg R5~>?}`Yr5Xr2~}`~-YJ}`p5X$g + YJ}`peYF|l>k:}[/$g Hz}[b5X4ˀ}`и,YF0,YF0lYF0lYm@>k hg  gy>k hg  6a5k4b54ۀ}4ۀ}[ۀ}[~Ƕgp[lK,|W`Yl>?mq? ׾-.}[\ga⺷eo,,zYlNr& [#gaۈ-^Fl.r& [E,g-/!g x Y'la3?seWYp}-Yg,[|R3?seg>K,[,[- g ggg>fx5AXNUh˹ b9YZ,g+[n-ڭrBXXh! b9fZ,-[Ɯg- Aeyb yb| N*g-@1Yĉrybه 2<냸A~yb#YGg-FγˀyyybrA0rg--Ym@ybreyyybrg--YKyb-Sڀ,cγۀ6<<-Y__,Yҷ ˟, !@?Y d#XK߀,cgֿ,/Y^kiڗ/+--|Y^eyկE?y,I҄!7Y}d-M|ˈ,Ed!7Yb ,Y%d-Do |YK,_?d'Y|gg?^?a,އ`l{Xmk}X`  ,#}X`  ,#}\` ,#}\` q5X>.C,q5~k` A*X`,b5X~kpe [.Ջ ,#\` X`zq5X^\` X[,#\`% XFo,?p5X~"!XFoz, , `,3Xl3XFl3Xmk`X`  X`yOk`X`  6a5,k|f0,b5f0, g0, [, [*yKŰւ,/Y^ :e ˫@ZZƠYe_K,򗿖>|Ye~-}cP`c-M|;,_9t!Youc-M|ِZ+Ơ勆,3ҳ,2d!w4N C/kB%˷1(pK ,Y.pK_e| O(d| O(ƠP`5MoikB%W5?,_pKf|5XNc*<XNd*LXNe*P`LT`LT`MT` 2@!ʘ_*qʘ_*0TKjC^PCꐗ Pƶ2%5-Am B elKj(c[PCGM5_Xe¡XfeʡXeҡP2P uˁj(c㩆:@5TCO5TCO5jC>R e,pTCPG5 YeD"ki囈,_DX1,Bd|d "7YqB|X"+YzAd'DV|j OdI]_pJpj "+Y ,_d'DV|E["+Yl Odn&W?AMT`aMT`ˁMT` 2S ,c92 ,c92ӛ ,c9B*e pR` A5!/m9@ uj(c[PCrؖPƶ25-i2iCiBd,#5M2TPd,c5M2XPt55M2\Pt55M2`Pt55MƲSd,15MƲSd̏+ok4{5MEMyQd,^4˻CQ e,W7y[m[m[m[m[e[eX[eX[PC~K55551P3PCPB jCo27 qX.mTC~K5\ڨ2KPri{j(cQ u-PriJ5A5!>6P e,EP u-P{PPByX~Xf0 eXf0 yOXf0 yOf0yOf0mf0mI! < `< <kf0< `< `<~ `<~K,/dy)J兰ց,/Y^%0,//_ZeۗO_w/˟,kIkiK,9dʱ Yp}Ckiˆ,5X1,_4dud!˗ YcqBo|X'Y]A'O|i Od\pI_pi 'Y~-_'Y-m Od'O|?)RJ"3<3.#."b4>g]`LKl vI3.i}&%}ӣrsz4XaN1`99=,G1G0Ȉ-G@Ȉ-GPȈ-Gjě GecȈN1!GFpz4Xވ8=,D w"NKG孈ӣZ`'ſe; NF_`;0wlNti; sv:`dsv:`dӁsr:pdӁsr:p4XNΝ`98wz~~@?!`4~D?#`4~H?%`sr:p4XNΝr4X8w2~˹`Erdsri"9w,HΝ-sri"9w2~`s'cNˏ ; 8w,?8pdsNFo1w,?YBdl,'4K ͒}Bdl,ːGY%aIY%ˁIY%ˡIY!~%IY!~%IY!~%!@(K2;eIx ,ɘ=%M$cyˡ,X^s(K2ʒE$cyӡ,X^u(K2ю$c(K:w(h2M A+4۹A+4۹A+4۹A!+4۹A!+4˹BA!+4˹BA+4˹BA+4 !h:, h: h2 h: h2 h: hBd, MrPt-Md@A!4Co)h2+&MrŤX4[yX~HIA@Aa  ' yX~V[je̢f鐗=4K2fQd,c5K2fQ$f,hyCdlc4K6fAdlc4K6fA$f鐗=4K6fAdlc4K6fAdlA4Kƚd1 %!4K6fAdlc4KA3Z6xF+C3ZhYdyyA$ˋc- Y^2u!BWZZ&dyIXK b z&YXC|KZ"g2#zC<"g2#zC<"g2#z&c9"g2#z&c9"gBtX~Zh-@tȿ.@dl/@tȿ0@dl1@tȿ2@$XHꙌ判[ꙌɀzCog2#zCog2;/Lr神X3˝z&cRd,?@Pt-L#Lz0!g2_"g2"g:z&c=zCog2$g2Iz&cg: =LR3ʆ&)yeCdlL6IAdlL6IA$W6L6IAdlL6IAdlLƚkI z&!L6IAdlLdyyA$ˋc- Y^2u!BWZZ&dyIXK b z&YXC|KZ3G}gd9<'3?sxdݶx;3Gx};3Gxwū9<{-^p-d-£27@xE!Xvȇ_Ce|苸C>Xxȇb|[r_A.g很2Cbyr|h<:@>X Z,-!2D@>Eos>2D@>Xȇ1C|h?£r h9V3Z6xF+C3ZhYlCF^X y6a=4!lCmzhCX 4Gy롇X y6a=dy6a=dy6a=dozHW,/Ndy*Eֈ,/Y^!@1+Y^kimҐ啱, Y^*Ң5!KBWZZcP`-M|9廁,_ !Y`-M|);Z9Ơ ,,d2 w5?P-` 5?,CkB=$˯۲'C'CcPP,h ,_pzHn|u[!Ym Odζ'CS=d,sC29P=d,C2=P=d,CBezX-4@2P4H%lTI%lT6I%lT'<ƲYRsPˆI%!nT˦I%1?tC1?tI%1?t 凮C>1;Ac,!|N{|N{|琿>|>|崧O{|崧XN{|崧XN{|rSsۃ=d>d=Cs!1Ӟ2c9)92cSs-e>rSs-e>rSc,=e>rSc,{>e>O!﷐˫>e>)#0}|i2cyܧ[|偟2Co!Bc,#<1JC^P%!/A(ym䁒F(ym䁒F(yPF(ym䁒F(y-SXC6@#F(ym䁒G(ym䁒G(ym䁒[*y~ JY^)P:e"˫DZZ#DdyYKC<8ڐ!+c-- Y^,dyUE!kB, ƠZ>dy_4y/ˣ,Oki_4rA#3,kE~Yey_JYpG1(ypGKY.ypGez O(ydz O(yƠ5?WkY~^JY %,d궆'<|okPmjC1ـjc1jc1j!:2&Pc,572FP9c,3Ʋ%Q9c,3Ʋ-Q9c,3WF匱lNTD匱lPTE匱lRTÒ1?,!NzTÒʙC123rcrXT˭c7S9c,7g*g判rXH*gyrƘc9"1#c9"B9c,G$3r R9c,i*g>MYJ(9OcPVcld56 @Vcld56 @Vcld5iBVcld5iRVc,e58 PVc,e52 PVc,e52 PV#dyyA9#ˋc- Y^2u!BWZZ&dyIXK b Y!#,O<௥C{Yey_KS,<ٯc Yey_K(q3eyxF#3р/˓3t{Y:h&{Y9>q3T/ˏ(hF#3ebyq3zq3z~F2?1yF7<3p8۞ѵM'11___a_c_$,/e{elܿ -Ipb?[_F _f _ˆ = # =qeybbɋrwe,W_ reb,X_Y[_,g/,eeܿV,*zFH3ZBh=$-gzǰbyF G3Z6hyFk-gbdy<3Z-X>3ey2yFs3ӟє.S3џш&tYH|sYG>)V,h6F,<h,3eba"+gT3z`3z]~F2?byFW;X<{3pĊѕN'V,e\e\;e\[e\ 5`Y\ u`Y\ W;W,esb`Y\qs2H8FbwAz1 <ĊňW, `r2X\ (W,*`r2X\ +#X R2X+Xq`9by`;b,SX+rEe\Rb,TN\Ńre\>8q1Z!&.m6e& 6`b䵂`M0q1Ze&qp2XfN\l‰`M8q, '.1q1:1ql/䘸J1qy`M8q, '.Fo9q,WiN\r2XfN\r2XfN\l‰`M8q, '.e6e&ye37.|gn\dqŗ3?sb |gn\l ܸ|g/|x;2/b9!c"~Q,32/W2/d,Ɯ,bY,5 bY|%d,eeBE\, q}BƲc#d,9f1>|Xs1g,_Q2rYe\!cY,FX˕2rie\!cY,GX2/~3Ř, 2r\AƲX+X9cY,HXE2re\&!cY,IX˅2/~3r勼-Jh\ˍ/΍br&ܸ,I*7.mʍbr&ܸ|Wvn\$/ʆeLRи|W64.eeLRи,I 2IAb̍ˣ{{uύ=7.=7._ܸ,ܸ|sb̍bqY,4._r勸BX&)h\-4.퇭ܸ,I 2IAX&)h\$bq"ﷹqY,4._ !bqY,oи,Wzh\9cY,=d,崇Ř3ve9cYl}Xi3vŘ3/ח3ve9cYl}XO9cY?>g,Ɯ,>g,b;sE>sƲN|O{Xi-/X%&+l--0Y^_dyu%kK,dy]A"˫j--*Y^SҊ%IZZMdy-RZK+iw^H cYGfY",˲<-qEgeYҬ2,ɲ<&W YeyFy OXdy>^2YX cY2YXd9cY2Y~75?!c5?!cE{pE_zew OXdw OXd'w5?!c ,p/(79ĿyMdC)B4b,_?E#S4b,+cY*hXE#(1@!F FØ?qhĘ?`Aш\(1E#r=hX.hcQ4b,4FF!s4b,E#rP4blD#BFFш\(1E#ruhX.oCo!1+E#B4b,8*JrAE!/{(Jm̂,(Jm̂,(Jm̂,(JyCQblc%(11C\T˘EEYT˘EEYT(9,C~(9gp(J!C~ DEYT˘EE!T˛8%RQb,c%RQbl1AQb,c%2fQQb,c%2fQQb,c%BQb,c%7}c(1r*Jc9)1!D#vC4rD#vC4bl:D#vC4bl:D#BFhtF@htFmFvC4"htF@htF@htF@htFtVF#ƞ{F+L3Z_hy=%ˋgʒ0yFJ3ZShIzF gdy5=3ZJ>ȳ~\g4?XGg4? IJ<7n4Ǎ`0GǍ`0Ǎ`0Ǎ 5Fcg87 #h 7.č` q1XCh 7Nč`q1XEhyFcr9Fc\,$n4b1XHh [7č`)q1XJh 7Fo,7&n4b1XnM?ke{mÀc`p  6a1f0 8  8 8 8 `8,3e!F8lp h 8ۋ4p Gi 8,C 8 `80~`yÈ-eÈ- 8 `8,3ec`pyŀc`pec`p k8ˁ`99x`;10`;1l:@ǀcp<Ā@ǀcp #3gvcvc1t 8|c1t 8|c1t 8xs1XiVki巖V,/>Y^{ʓ'NZZuƠ%V,/8Y^okij&km--5Y^idye6u,/5\cPw,Zgdy^qY4,ˣZdƠ9Y*!C,Ȳ<" u,kB!ukB!u,kB!ˏ滆'ໆ'cPwcPwK,? u, u,eB'|PwQq_B;cX>7;僣X>9;񣣺X>;;ãX>=;㣺Ø"Ø"!p;!Bu!TwMc Qa,!;>Du܈0;r+XETw~ u1r9XGTw!rGXnITw=c)Qa,w%;Du!PwˍCo0[-r=X.T>E}PE}PE}PE!CPE!CTGE!CTGE}TGE}T(9,C~(9gp(J!C~ DE}TGE!T˛8%RQb,s%RQb,s%2QQb,s%2QQb,s%2QQr-%2QQr~7c(B4b,g6E#rfS4"hlFhlF̆hlF̆hD!Cۙ шۙ шv шzlFۙ ш ш шMш D#ki巖V,/>Y^{ʓ'NZZu %V,/8Y^okij&km--5Y^idye6ш,/5\cX,S,kiX'bY,#,OkihDGaYÃ,<'D# ш,G#c ш,G# ш,A4"kB4"ˏ'D#'D#|# mP/kB42F!~i!1c(1c(9ďc(9c(9ďc~8c~0懈C<)1!D#xS4b,7!F.Dш܆(1E#r#hXD˭cQ4r-D#刢cQ4b,$Fc%Q4b,$FDшܕ(1E#B4b,7&FyhXnM~ шܜ(1%r7)(Jm(؆B(Jm(؆B(Jm(؆B(Jy؆B(JqXB*JqXB*Je(XB*Je(DEayoP8%BE!CQblP;9%B(Je(XB*JqX̩(9c (9c (1c (1c (1Co(1TPHE T(13c9(BQblg6% AQblg6%vfCQblg6%vfCQ"䐿!(J̆l(J̆~؆Xng6%B(J̆l(J̆l(J̆l(J̦Xl.J> gZxFKAW3Zhgg1,!Ug4>  <[<MT\g4@*; O,gVXx<7VXx| g* gVebVebnh& gt;{F3Xx| #~i\x9.;.=.C8܇`0lsFmÈFmÈÈGeÈGec}q #2q##Cq #`{Ljc"1x`8,sGFo9,oqqc}qqc}q #2q1X>8`80~`80`,2wXN!vXNȟ vXNci c;v,c; #i c;v,c1؎e4i ۱C4۱`;0򱌝`;0򱌝`;0̝`9>u4dy1Z奰V,/Y^ *E0,/dy>Yeo-}/ZǠӐ~ y4dy9t-<*3Z-dyt- ci)Z)˓,kiFY~m\: Y4ƠX: Y4dX: Y~J5?Ӑg5?NCPpNCOet O4dt O4d&5?Ӑۙ,_pNcǏr?įǏrQQ&?@!DɉJNePrb,kcY=XV%'(91UD!#JNGJNØ8qĘ8HBɉ1qTBɉ(99ɄcQrr %'BHNeXxJNy]xJNGɉ(91%'BHNGɉ\(91+%'rX}ŏCo!91%'Brb,@JNyX.5c(Qrb,W%JNyDɉ}ɉ}!C!CG$юۈS%i>?1B/;B2DHZl,se}rVNeP됭e= e+'`{ӗC՗EY9g+'`lP뭭no+'Zom,sj}rVN2 X>[9g+'`l뭬eôKVN2 Xڲ-ɢ-ɡY9[[eY9[[eY9YCo˲r,+'`k˲r,+'`KeY{k˲r(+'`k˲r,+'ޖelmYVN- ڲj[e[94ZZ>k?K}-|QNZ>cVt!_gY:kt^ˇ{-ghZZ>\ZZ6,ky\˃Z3a-Oky|1Y+YZ0Z/tgihXOkEY{Z^+gZ?ed-嵒gZ?ed-?gZ?ed-?>)k%cVIiFHi>L맬[Z=)k%k/`ϴ~_~L ~6RF XFH`)`>o,Ok,vY. X>Xe'k,. X>[e9vY.ˡ~ǓCl̏'`~<9vYx(,:. Ou]\&mP!e˅vY;.ˢ첀;. Xzl,vYr]\0meQvYrǴ]2m,LeMvYr״]6m첀i,^oe,Ne9z+,`y. XS.-f.^deQ]6ʢ ؆BYtP(.` eЋ,m(EC-R]H٢ XB[tPh.` m,C-,ʢˡ)[tPh.` dl,yl),z .]2ڢˡ[[t˓-jE r]2ڢ XB[tPh.` m,C-e(EC]XB[tY]t^eK]Ee[]C? +,`뼲+,`뼲˲(,yelWvYyelWvY. XyeeQvYyelWvY. :z]u^e9k,`鼶w`ee-|ܟӾZ>k?K'}-1eYY:k3,|_Y:ktýtde-gzee-ϓky|fKØ첬!r-ϐҕ}-Oky\ˏа41ĵ8&,ϴ~.ZeY˻,ϴ~.Z~]ϴ~.Z~ }SvYde->),kt->),k OeYgZ#e_e-߲%kIуm +` la,Á-eWfk,`dm,mgk,`~>Wm,۶Yum0?d,`~>ɡNAEf9IȶY|rÐm:i,:6 XröYe,öY:lly,öYrm\1meQYr˴m3m,7Mf]ӶYr۴m7mli,^oe,Nf9z+,`{6 XnͲ(,`6 ؆Bf9"%,PY66 ؆BfP(,^dlCljm rEʶY26 XBfPh,` meQYH6 XBf[ ,` d,`dГfYm жY6 XlPme(mCжY26 XBfPh,` m,Cmzm rv26ˢl6 X:m,6 :lImu^f[mu^f[mEf9+,`뼲+,`뼲_Y+,+,`뼲rWYye;l6ˡv^fKmgRY>|?쨯ߦ,1_˧3;_G3;Z>ޟgvm5=׺͓8glfl\g6H~fsZ~n|fCg6C+g6A~fgI3{Q\g='6fY,6gͲSY>AtMn|fkZ?u6gSY>gtMn|fOJ5P|k"`黾&5{}Mk"5`|Md| &2X_,_:OȠK ڻ3 ڻĠK:WȠK:ZȠK ڻㅯ ڻć&k".k"k"N&2XZ:|MC],DK5뭮 ښ`i&2Xnn&2Xn&򡮉 뛯 + K k ^ouMd\|Mzk"Bk"[],:_,:_PD˭DPk")]PDPk"m(56` uM"k"m(5P D@-R&2XB_,C DPk"EDPk"^D뽮 ښ`{5ПuMC],C D@&2X|Mzk"e(5P뭯 DPk"e(52` }Md &z52P &`i n 檛 ud5WlU7A[sM\uC&`k 2ؚn 檛 -M檛 &`k 2ؚn\ud5W&`k jsM\m&Z>k?K}-|QNZ>c t!_gY:kt^ˇ{-gh&Z>\&Z,ky^\Za-ϊkyT|1YsZ[ZZ~7|j a-?1yS6A&ZyS6AZ~|S6A3 2& kOY/kpg<_+҉^z-|Ӽì,|9~Z>k3,|^Y:c3=gƵ<2>KsZ򼸖giFXZaLa򠸖gZĵr`-?Wgi*XokpLaiuaiu깖=iuL맬Ì:Z~|k\c,ʵ|(d=e-gDti\ˇq-g(哸Z>1|<ޭYky[ˣZ장^纵<=K~LSLGg_#Z~{yY3Zq, 8kyY͘Oo`ox ǛCm"np e, lP/غv[7u0,inC9m/`~Y>.h`j#u0_~|=fh`{ |=Ծ`` np} lP;غX;غXnb`+nb`+npV nb`+WnpV ru_g[~|-?g ~k4V~kX3c>)f-lFlY=3_>e-7ߦg6??uϵ??{ A?&!8DC֖5h>ڲ-k>ڲ-k࠷e [[|e [[|x>ڲ-k>ڲ-kz[|e Ao!8mCҖ%ȁ5?g׃9Xݜ_Z9K8`qV9 = ,)g`qJY/&,vИؗؖؕBSbObKZpCKz[ؒ~0%=-alI?ZؒƖ060ccX06 al,KݔprJ0#>??`w3;%$\~/,?B0^X~Pa6  $\~XZKspjwpa.?,A凥;Ht   W$\~XK_ppa "2K .9\~Xr \e6pa%\~Xs  ]za|GA9\~1\A9\~ze0c~^r~}9?~澜?ls_Ώ/ܗmz6I~}!ɏOea$?~X>ɏ!ɏOea$?~eu2I~}[ɏɏP'ja$?~X>ɏOea$?~X>ɏmΏO7?*ԟIϿ@@@a$A?9~hh?lsB9!ۜmNȁ69!ۜmNȁ6'@ay@ar 9~h?lsBh?lsBh?lsBP 9__YBgWkgz-gz-OHky@zZt4_#k.,5Cr YYj k1faj`n`n}}}}(2a``΃΃΃Yz+2Xh˗J IC/`~g;[ɗ/9_>z+2C//J |`$_'2>ɗ6I Oe}/z|lsˇZ,_g!˗2Y e}/e|yQCC/e|,s`,_s C,_^|,s`,_>zk2X,_>zk2X>˗Z e}/e|,s`,_g[ɗ2Y|Ϭ_MgY>/J|]P zy˛և9Hl bC$![ml`?$!և>~Hl Cbk[m,N[ml`?$![m6~Hl}`?,CJsLEEEE0A˘C9-c^osJ F05jնn˘j"I1ئ7IXR ͒C&ez,ӛ%`,)fI$ŇZM,)fI1X7K2YR ,ӛ%Ň:YR(I1X7K2YR|֒b XR|֒bLoj,ӛ%`,)fI1X7K2YR ͒Cez,Ò%Ň^$)sR(I7I9)>&Ie?I6~HR|蟃$`?$)!I1I6~HR(Iml$`?$)%`?$)!I1I6~HR|$`?$)>CbaI1XOz~f%3Pk@}f3+OYuZ3MYi{ 4hiJKӠA+MV\4 Zi`.0V` Z3hKHtQ _Gj$:hj4GA{TsGAjAT;hS-5vЦZP;Ggx$:XGox$:X:Gj$ jHtDKHtDKHtDmP#t<,M#QFM6T zHtЦZ6hjzHtQ z=^o5GA{Tj$:hE[DCM=A/zMS6i94M=ۀ`4l M=ۀ'S2y js hzS2y9X4O=?Ԃ`<,e@sR2y 燚zS2y js x js hzZo=,e@s hzS2y9X4O=AzS2y zysR5i9h砥7M=A4,㇧zCSO?M=`?4l㇦mCM=A?4l㇦msz!O=`?4l㇦mCS6~h `?4usz9$\%j-Wg@ZNRqZ˵i-1K=Sisisi:L ̥ ̥ ̥0&0&0&0T\%=L0U0W0W0WT}-=_E`~q;_E  /n #`D%<$A! 6IyHE  la`$<$AX0,<$A! 6IyHC$<$AءCm P! 2y?koYm}fe3zkϩgV> gV>r<\sr7hnݠA+w`.wV ZsrkV~kPB9huPB9huj6hu`.P7huPB9h Jm0̃ `:h)õR=\,EõR=\,õ5\R{6X*kR{6X*kR{6X*kR{6*k6` zpmµALA `:h)VõALA C݇~4"lW#y5"lW#y5"lW#y5"$hD6:Fdv^K ` ` هy=",#y=",#AK ه `Zo="'y=",#y="P#y=",#A@ ZD6hV#A@ w3*US3Ыg^55?C@ Z~6hUS>`i R-[P+|`R[Jm!X*|`R[J-!r0^o%s뭄|`<zՁITF'QDu`ktՁITF'Qݡ7:$;FgQXEu,K,΢:4:,[PEu`itՁYTFgQ:4:YT(QXEu`itj̯O`itՁYTFgQݢDu`~}:zkQ:<\YT+xeQX,;z+QX,sTЫDu`jJTnQCՁ9sTwUS:9{E0Qa|}E0qԾ#8?sja,R%A-Ò=,Xҿ6$R%A-ƒ=,XҿKcIb,R%{X^os0?6c0?6`~C9{:Rc#aH9{:Rcc##ILt$~P;tKGaH=,Ib#IL#ILt$$1ґ${c#ILڑ$sLt$$1ja|yzX:tKGa|yA=/O?VbIbzcIbzc Jb:0t3tcL0t?U3tcL^5sL0t`~ЫfƘa~ЫfwaIbeXa$iRa)t۰c7t۰cԗTa)t?}a)t۰cmX1r}arL K9{؆=lR~Ї=lR~Ї=lR~P%ac]?53>k-lFlZ˵3>k-ߦg6s}f#Z~ߦ^4:ښ^4gr3zg~ǂ`ne Z+V6h ̭lZ٠Ake`ne>X7z,8h`s;h`sƂ >7h;h`sv{=cAW ڽԾ+K XpaA- B -cR={,8Xǂ{,8Xǂ{,8Xǂ{,8h Ƃjfik6ʸfik6ʸfik6ʸfiq[, 2Y`)㞥Z=K,eܳR=K,eܳR=KP4P˸gi{6Xʸgi{6hY`)㞥Z=KPR=K,eܳ4Pgi<4hC[yhО@ [gi5dzY`y,mxz,mx6hYڠeiWM-Kjj6hYڇ^55K,mв4Ыfi2пOi\6!@4.leC y_߿_v->Kcg)Z,ӟO2<ЭyY%ky[Z垥>'<=KMdL2<ŭ!Y3m-~cμ3}J63}J6[ZRC^x-1S;s;s;>L0c0c0c0Ԏ܎-C+~%_R~WjهY rJ=P `~?~N EH&(0?/J( GC-,#=sP7C,7C2,K_PP;`;Z( h(X:jP,-BQH E"-KP,-BE6jJ )&تD`mjJ )&تD^5%[ՔhPE`mjմh,UӢMTM6R5-KմhsQCmjZ i&XE`6R5-<ԪiD`~;zk&Z w>0jh,O`mjh,66rih,66f&X,-ҢCmi&C/^9<(%EI/0Jz FI/%b%X (%O\i`\$"% (6H@(Pmpl`\$uJ .Pmpl`\$!Z> g_?Z6 n??5lZ]=3U?Q3TrlL]ipͨو_>3 n?i 3kP3dwg6|fSZb>3a~`am#̠06 fFAam3X:ׯKoeW`jo-MiPۆӃqx>=XZӃy|}_V5K7z`>Xڈ6?W:+ģA BA @=jPA @=jhB#Pl-4}^/ۣ2xQ`XXʛg⃥y&>Xʛgj&jyL|7KyL|7-,2Ay&fM38383rQLz`(z&>X.g`(z&>X.^o5,EO-d%j zyd{ВAKA/ol`?<,'j=ƏO?4l&ۃmd{lC5d{lC6~h=XnWlC6~h=M6&ۃmdC6~h `?,+Sɘk㱖OZ>klC- 4؆IPӆIPK !BC}lC$ЇI !Bh @m,O@mlC$`"$! @mЇI6DH}C%`",뫥#,|$^Y:=k,|rYY:6kԬC̳td$^晞Iȹ'g7ys-ky|Z5,51I򜹖gVgk9X˹kyzkILגNg-O?g`}̣G4ye⿥;}ѵ'˵Ҡ,>e6smt)˵ҧ,K\{Qrm4+˵Ү,Kò\,-rm4-˵Ҷ,>bj6XZڇڼ,K\PKއ[ $P?{ %su`NDgo7C-#,㓅އ[ Bo Qze,ދzg/`%>^E K ^h}@?{ K}`->h|@峷,`-^P?{ r,( r4X.P@˟Ћ@ve4XnW@j,O@j,+ Z ە`]Y ە`]Y ە`]Y}Vhܮ,cs|L2f0g̋1z33C`铤l^C?}Ӻ$`c%`zl^bu{I%)s%`ZxQbu{I%)>n/I1غ$Ň%)[P%`W.k-gt5&)Z>ZZk-gXSZ>SґZ'j-|4&)Z>L,IƵ<6>K}{-kyf\#ԳgaIŵ,];Z~_˯Ry-O ZA<6Y̴G1K/a 3G42yd0L`,a^4_f3X`l?jo3Xڛ`ip?Y(3X`s?Y ^g3X`w?j,=Cz?Y|Eɦ&X6 PkeӋM9:Ԛ`4C*0TZ,sHu5i0T`~:Ԛ`4X/˦&X6 ˒WjI^PK(+$`;ԒPK C-jI^v%y=Cm+X%z-yˡ,w K^r, K^%y=Fg+X.ba+X.9y[$Z&$`XX %Zo-y˳%Zo-y’Cba+X.ba+X.ba+X.z, K^z$^$ys +`ْl=[SlOֳ%?[ϖtQCْgK~ -)z`y Wْ.J~ -)z䧇޳%?[ϖ{`ْj϶,=]O;|̎Z>ym~fn-}fgn-}f3;ok}f3;lY[Gi5=g~fg63 ?3 r?Fl"\i3Z|f̟gļol3g6UAl& ^A?}~`;}ӧ`;}ӧ+Ov4xy:XN2^uÃru\9PSƧZ|e2~|?iZ9iZ7:M+[Ӵr5:M+[ӴrFVȨ5:M+?Դr5:M+[ӴFi`ktV4lNJPlO+KOZ>k\c,ʵ|($\GY:k@,ǵ|a\gY:k$僸t $\ˇAI2򨵖'giZsZ, YkyZ#ֳ4aIft]k]v-?>K ~3IʹHRεb(Xn$.Jz"P\I,˕"P\I,s 8@ N"E@R-"C1"Cba[@r, @r, @r, @J "P .JzuH"P0G"Pe2~X v%A桷+ 2֮$[ lJLEd51jJE 2֮$[ ە`kWdz lJC>-K -HZ>kX>Kr-1 2|NZ>k<>Kq-Ƶ|Y|Z>k s,1 2!|gP̵<0yY򴴖<+=KZ,Icd׵,IZ~z]/R_;1 9Z~[x? 93Iȹ_³rm-hcr_BN0hiD #ڡ6B 9X嘇)-\,rLK1aZ ,=rLtM17-\,rL4O1>-K,-rL4Q1 [ Fj9桶R1L-١mP}fGr-@~fq-4~f3;k(~f'3;9\iB5=P}fg6G13">!3!Mߦ g~=gx~fOk=~fMӫν?M> 4n۟e{-WU3i6ϠK jϠK j ϠK ^ԠeP]x5XgPexfPkx5XgPsx5XzgP{x5XgPV ϠK .`#AI<,3AC͠@%/~. ZL.Zjk\c,ʵ|($YGY:k@,ǵ|a\gY:k$僸t $YˇAIur^mYki垽[Աr^YI_ܳt5Zqk5n-?=Kע_$Yյ|O}Ig%u-QtfRTlKYR-eKն,uRTnKYv[,RpKYR-eY,URqKYR-eK-,RsKYXn)ˡVuKYR-e9n) Xj,eQRCso닒mPK,`WHU:d̡v$`%KG P)-A -A zs}ł09H9ԾbA 0)W,HˀjA XFT R2Z Aʢ)W,Hsr}ł0? I^$HӋ)"Aʢ)`e P)`y P)`-H9zkA Xx R2[9ނe ,s)ZViYɡ=%+KlM=,K֧V$XlM7I<I&ǡ7I|>4G̎Z>u١Z>rىgvqNgv>o3;hkz4GZg r#g?.g?ת|3{^m3{̞>W|ި>'|m=zI,K7R,K`oj`ox`)?X o?eK!7PKboS,?7P뭿ڛZooj/{N!Ġ= .!`B .!`B .!C5^!Ġ CA{ay1h/,j/bBA !@eB Zj/bBA !@eB Z2!KbTM!KbBƢ!,B|!`B [!s[!CP뭇!`;x1XB !ć%(a4:K(a4Q`}έ﹭hF h0JF [(RQ`+5%z=J,Ƣ_P"QZ>{k=K'o-1{NZ>tk=KGn-|y{Z>mk,1A{Lr?{Zfk^, {ØD kl-?=Kw_׳t_XO_kY,okBkyJyѿyFY#3ZOx2|0ݡ[,Kw,t_c,9.c 4_j,KeQ_q,Kϱ,]_y,9c X/,KP{/`B9s(ˡ[_99zk 0/Zo(` O_̯~$KOd>`鼖IgQ2t^u,JXP[:`#-9iXFIu2LZqbAu99icCm9ss-b0:jaX,bFuR-s.uKbEuR-˕bCbCJbΡ[u%8[ -R-K,eBE%8ܾ%%۷"ؾ%[\lߊH.oErC=ԖKn_\b-|ޘk=Kn-|枥#OZ>pk=Km-|Y{ژk=s&Z~$ZoDR\/Dkh-=KZ~ZˏC;&Z~ZCлZ~z޵$_iw-/kLM:%u-7۔c-O6۔c-5kyyߦ `tKXz `fYf9Xz ,sf9XZ `in,Jf9X: `qY>g9X: ,KP `xjϳ,]r=A%9zk9s0 Zo-sP `A~!!IPPC?Cg[rgHlKP I( ʢ$`I%$i! XO I2ZHBCe P$`Ij!ɡO I9$9i! CJ#NI$9 d򋌓gEc}IeQ$1GĘ#=A$97$B$BXW(⼥Hb,pIqR$1$B2of2of˼!`q[vn!X`al![vn!X⹥`a,,>=QBZ:]| JZK'K,tdT3,(Y>P|q(!ˇi D Y~4dF_kdf-횲T#/5ki(!4JLY~'Y~YK ,Z.eqf3R Y\5)-iجob,o5Ԭob1c~1Kb!^33&a,w!ŌCP0a," c)f˥H1C1XEr3R0b܎3~a,7$ŌC#)f-I1IrSR8Ļbܖ3徤!qb1 c8o)fs0qb1njCAA1C>}A嶧 rȧ2AABBB0͔JT:e;a,)C\tˎJ/W*\:tJØK!^T:ts8˕J7*8ިtxa,J7*\:EJ!AB0*1C/W*G-!$ c$e0R0HIB#T!Tc;CP Au83TC>CP僘!T僘ßOhDzF˰:<%'gtdX=S3:S|щzF'Y>N_&%i{F*YTѓ,/}_<Y^c3zKyFO)=g"˛3zEyF(_I2X+ k3&,Z> g֊gp`xF 3wd8 V ҂o _ ˓kOV k`CVõbj`HV k`LVSkH%i-1|,AY~YYK#NUdYE_U҂&o*1")ki3Y~K委C,L_Qde3 (cP2dn  Y叺5P2dyZ9%C!YޅpNP0-0ma,+CZddJ%XW*ˡa%X.Y*rR0JJܵT2嶥a,- cqd˝K%Xn]*xR0J!޽T2q/ cdL%C%- c.\2qR0a%- cYTd˪B%X8o~GBc~$4GB!4C9@1GC9@1!A @+@0b!^+eXa,- cYo)V R0Xa̱e+ZXa̱˜c!!2(VXa,sb!2(Vs0EBX>(VgŊC)V*˨`,p`l!xK/: I/: IOWcd#ˇGZ::|rdYKFO,Y>3kȌA,VcZTT!/P"Y~W A' Y~XK,O,N-H&dib-@0!cd{ ā1!s,EG s,4Ҭᜠ8`[aڊܘbcY)JqXnWrR8_crR0k‱\宥8`,-co)ˍKqX\rR8{‱ܼ8`,/ŁC) LqX`B8o)s08p1c8o)ˢBqXVƲP0uϲPV0dx<3:|4xF Y>_PL3Fey=xF[wg> ͟3ܔ G/Gg);}fp3 GgX?B-ңC|7Q?^|,NjoeYx#?`3 =V 3+~gh#^W =HЃ m늟ˉgh#x~,'gϳecY6Əec|wWޓ0+^?xEc`;`lɃc?&OzL|Zx0cY2]KZKe # '@,ҟ_ǗZӏ,Ʋ!*ߡkinW,7Ze T?@҅>Ʋ)k2OOYϵtg,uU9es3qme*]c,˟gk8{Ydl g<4wxhE5=lNtɘ0};eNrC\|?+zh6fcXuzh6l,;=4NrC\l,<=45O͇xC\|==4uO͇xC\l,>=4 -=4C1?4⼥fc~0eC,fcdXvzh6meC?ϲY8oqۘ} ?m`iOSO0QHsq[,l,K!%RHo~.g^ +!z>?d3z_3zxF,eћ,? <g dy F1@wg^ э.L%|F ?/j%|FkZs ѧ ?_W9LWAy[m!AOZ#K1HOd 2b, p01H)c,(2ˊ)c,)2b,{ p, p, p0)cl-2p, #.2)c/2b01X.NF2)ÈS`Y8e S`Y8e ՋS`Y8e S-q01H?cy#1RxC ; u#)e)a!c,9]coOw'1b?6^˷ňl/mË^˷#e^.+W#2e&p11*3XfW28 ;CL6dc;`;^۹O /ﻬ$sFZ:>!QN!}iŘ7BcFh,?/ǯx j6y~w1w>h6Bh6Ʋ Q1}!Nj6le)fc,k5cYnDX#j6ƲQ1 HleKfs{5cٔDX%j6/Q1\WllqR1늚![j6r]Q9yKX9j6ƲQ1tlefc,k5Clefs󖚍1![j6llyHA1fsC ,lyHA1!?mA9,m>:6 fc}tmA1[mVC}y򓱜xOx4)? !?g'c tG< S~:ģIX>(?Ѥ$]^"Mx6e,ڔ7jS2ިM6%S•,.eqpugY\Mۡ65m}t-[3g␱c#,L[0ſYCr~'p-Y-YÊ-gYObo*gI_TlAS—-cYLŧ[|Idw-^mx3Y9?r~ō gVO~3+'[\pfdWG9Ц6;z1nq#\7pjM- tj-oj-Ϲ9/>W-cZeɂX,Z߈C bZeׂX-Ze߂eUk\PUk]PUk^PUqX0Z߈+TŲAF\àj-E bjsFPEUqBZ,Toy Uk\tP˖UkP˦UkP˶UqBZ,#Toy Uk1>-ǡoy U˘7j1o9b \}#ϡy)K>T6rZl/W6rZl/Woٗo}j}#Ͼ\Uy媵f_Zm-b@F<9y-o$H^ 7⹅X!y}#[H^ 7⹅e_e]I(ieBIF>- %h撶XF*2R- mlRٌ9-M 27&](dy(YK.Y$e< !f2c}yA.3fD-X~HPSKBK3(jiE-54cyvZ|@QK;CMXvpSK3yK-X-4cҌeRK3yK-퐏&4!4cq\f,Cܤj.__g[3%h g4G)3!h2liFg^_,g^^Ë,g^]d˰='g".nxF-E?r[3zj/gY [3h=,li莑–eҞ"Ù--h–y,li_-͈'[`9Ҍy?lAόy?,?ni-mt-!y? pc䓀n>"#'+Cpi䓀nl~\nl\nl\b,K Wr, W r, Wr3Bn\ጸr,k!W8#.\nܼ\b3 7Xn^pF\Έ+`y +`y ݕ+`^ +-WAz##[pv4HoGF\bh6HȣC`Y8y`h,6# mmah3mahl C`oڌ<0=660 C`ox Gk|p25X9zq,+x>>Nw_eUvp 7Xv_eDgہ`ԜCD7X&5':#0 I͉nLjNteR?VIq3&nTW;Htd!Faҷ,7N/YgdYÙN5Y 3 ,W,Ht 32!Bpr)̘w0cy;L;4(ˏ2<(22F(˯1?1Fg9s11Fg,5:cYGX@jtƲRB3-eFg, 5:c>H7BjtƲR;ĭq3Fg,25:c ⼥Fg,25CZFw\ZFg,25:cJXXjt8o#17Ceɘ_qRB3Fg̍G 4:cYFg,5:6ޠxFw 7ht<ޠxFgl 7ht6ޠxFgl !7ht2ިz⟌R:?U/c%([*UCRz˖J0U/cRz ze,!>^2ze,>^2z ]Aʘa|}JGZ+J,/U,&YMk2>%/k&,?KZZeMB$dEb-_Y%,_|[e Y*dXyj ڕ,k8Ϡ]z,3hW`PPze, %U/cY)zRIXJ^ƲXRB2ݒlTee,&U/c1z˖IL^ƲiR:]lTqߤe,:U/cЩz z⼥e,:UCTBu󖪗\TBe,:U/cЩz˅NXV_^8oz1WCTz![^&%eG T/cYze,U/6  %1c}ČmA3If$C}ĄČmA3>Hb< $fl +c]OXxjWƲkRB2]ajWƲk~*ǯQB:FXUCoTeQ:FXU/coTeQ2FX6 ^+e$&/kߺ,_ؓ婷̓'o-]&cdb-$h!od6hY~ Y~XKg[/Y?$&˗,kBoY8db-=Q ,?PYd $&˗,%|M.YGdYyIl ,_!k8 z,3HbQ:SHX!eôJ*e̫1Rx){u^e,^;e,^[x?UŘ_UU吏&3c~U1WC>̄̌9ф`f,&3cY8)IXN fƲvR0B03͓̌e`f,'3c@)JP fƲR0;Mq`f,3cY( !⼥`f,Če`v󖂙̌e`f,3cY(*@Xc f8o)1Č9s0;yǨ̘9`f,C5̌e`&lj!BM35#4cPy0BM35#4cPӌm0BM3 Fi6`6H}XV;SBSƲQ:L}XV;SƲfQ2iB +c&qP2iB +c&eP2iBX +c)^Oū'u>l=YMU 3ZS˖O!rl5H{ Ygs,˖\o`p,.[ekl _ÏMlNȇ = É56Pc,*7r,*7r, +7MllMllMllČr,,71#M̈{,7Dp,K7Č8o %-7Dp3&6Xnbe&6Xnbe&6Xnbe&fyMl~qr&6HM̈ =&6HMȣ`Yy`,7b3?-66y0bl#66 Ml Flbm0blo`&6#6/&6XV;nb Վ17q,q0{̈`5̌8j8 Q̈`5˨`6XF 2j>+`Y8 R0;ҿvY~i(& k_,2#,1>QLXY~]Džӂ,,Zseg-1b|򵳖dґ;G o n1Yd%,|]B/ Y+pfA%,_|I:3 +c91ԯЯck1=Ƽ!~e,ǘ!dWr_a~e,ǙhWr_ۡ~uW1-c~1C>Ę_@CB2u'▱,e夸e,K'-cY;)nIqKqXvO[Ʋ}R2▱lee,[(ŭCC)n&JqwQ[ƲR:}▱leà%u▱lqR2 ![[ƲaP2 ▱leàe,-c0(n⼥eoqR2eq--c~:y ˘!!(_ƲQ:9X>*_6R! !b6R!H,fl#!Tb6R!H,fl#Tb6R!H,v# /c| |G0/c|>b2j( !⨡,f,!b2j(⨡,f,b2j(˨,&̌eàfvȿlhf{GZ,73Y~XKY~ Y~XKc ,[/˯h!oki,?X{Z:ܲ|k򥵖N43YdZK|]m%˗ZdB_('7,_pcd6DtM",hfcdYÙLoYUpfQ3SA]L]0=Ƽc{!TbrTa.f,ǕXbrdˡ.f,ǖ1b'!^Ō}ĘGC3c~9]L]̘!xbƲTR3,Ōe.f,%u1!t1c/ˆI]XvLbƲeR3=lqפ.f,&uC7I]wNbƲuR3 ![bƲaP;yK]X6 b8oˆA]X6 bƲaP3 lŌeà.v󖺘1w1cb8os3.v󖺘1Zuȣҗvy@2ՎҗTb6RNb6RH.fl#!Tb6RH.fl#Tb6RHF2R)}jGKXV;J_)}jGXV;J_2M(}4uӄҗLJ_8M(}4uӄҗLJ_2M(}4e,ӄꖱ T u˘CBY.Xа3,2#ZcPda-MgY~_Y~]XKˮ,-ӂ,,,˗,=kAG ˷,_:|笥+Gd-a-T|Q=5J,4ey_ùj *,5KPdyuq U*cSB:L+1(ƼrVc9TR2J+U*!T*c9TR2cKʘ?x˜_+˜_+PC2 c~8C !J!ʘC!jQPC2e,!(c)DˎH!J!XD QƲ(R2UB,e]e, #C\)DH!F QƲ8R:ՑB,e%uB,qR2%B![ QƲDP2%B,ee,K(cY"(D⼥e!ʘC![ Q9D⼥eLTBTƲQ:LX>TƲQ2JXBHX8j(a˨uJX8j(a˨e,jMƲ Pk2*_cNzF('=Y<Y_5gN cXu`5VX Pc*dCUh`Y E`Y =*4X=Be*4X6>Be*4X>Be*d͏` q*4X?BF `Y" =*dyUh,\8o %%-WXUh,\Uh,\8o R*dyUh U!#[BdyU!V!#!Be*d9Uh}??ۤl{ aOl{ aOl{'56'?cOl{`ؓۤƞ4&56' IUh}\b,{W!cBe*4X>Bep,3Ïg28q&p,3Ïg28 @'"-E?$OlY–4EƠZZdZ?ez--z]-˟ղUPDؘ!M("B("\DhB1"rG1cY֨˺FEX6*"B("ƲQ1mTDes"b,cިFEX68*"Q1-!qTDe"b,!CTDe"r󖊈TDqR1UTDe"b,c;1CTDxR9yKEĘ1CTD"bXPDe"b,{c?\blcr!\blcr!\blcr!q%6!\blcrq%6!\blcr cGE0c"b,!)z/!)z/!)z/)z} zr4d+Z?ez-͂19Y|gYx^K,:,8=Nǧ,Oϵ4< zɹ>eynؔ婹,LYޱҊ%,1\Y޺G3}Fq=A,/3qi&3phx{F4<-4_! Y?h<#Y=/ك!_?$<Ē`̗ ]zt ҥg̗ ]zqI00Xr$ DZ?t]8H߅F>C p |0űǂSq,0ʱ`U fű!#[X`y˱` 8o9 ;c`9 ;c`Y9 R,0X0Hc łAF ) R,0X0Hc łAF RȱC c`Y 9;ѹ9'>8Z~Ze[KcwYKCl-Ͱ4¾'Z`ki [|_Kw񳖦ϷY+'>ܯpćfx^ޣ>ӝwt{;ﰜnwra9yy~?Lh3'aD wnA>C0|az?,S~?,S~?,S~_eeeeee .SSą**xEwòVwòXwn nXne_yӻ?6wn08oazywnAʼe)e)e)loy.e{{wYy~WV!++vq.ט=?ȗkrsa\cr]1{s]1{5fc. \6 ?er8,\˕\!ᰜl5!ԏV_j>+[Cj>>VH>޵:,  Kě,?Z E,_ò k,?:ZZeAZcodyT^K,iYӲ<*$˛,/Bkx#[4eyT_KC]gY^fgeSIśC<1wE7Ƽ*a̫aZ%y0UX#c9oHRB~?ěCS1!!7n| !!!7g1cٜ(DX'7B7Ʋ@Q1⍱,Qoexc,cY(2EX)7PQ1!^oexc,!ěCoΦxs⍱oqR1;⍱oexc,$c78o)3![7a8o)xs1ǛCo9s9y X>I(xc,K!!ěC&oe{xc,e{loy.e{{ t(!t(cިC󿲽lo??y[~@2򖱭 y[~@2! [ƶ~@2 ,!,c`C,c!QB:cBXezjYTe͢d,k$!ԤZt,Y~ZKMdK74ƠBXbYe&^Km *,_k%,w,_k,ZeD_N %VZZdyIiPo*,/+cP>?;T(Y-T(Y~;Xjo\ŵt,*Q:ēFJʘMc^#ak1rR)PY@u^@e,7;*c~0c~83Jʘ8 A2'C>CX* TƲVQ2ŊVe@e,*cٰ(PˎEX, TgQ2M!Zeۢ@u *cٸ(PEJ-*c)P⼥@e,w6CΦ@e,w6*cY2)P˚Iʘ_NqR2旓CĘ_NqR2@é-*cT}F3ke,~gtA|F3e%+ˇ]9Fr"S,/3@J,'߲8 Lj㍛`j `j<3o5B ƅ,9Z$Mܴ,?6AV/۵t MN,߳|-N,߱| jY~ƐWTA'˓o-]|ɯ,c}djm-]l>Go0Y/tQ,~Q9CXf=uôM6e۔1oSx˙c,U _}c,0Ec>| !k!0>q 1Fkaz0,H}}eGc,[Ecٓ(˦DXv%>Ʋ-Q9}lL}qgc,[EC}esc,E!DC}yX.t>rS1 \}qRB1E1Gc>A-DcsWo*-!cL"d,;C Pe"t3`Te"d,;!cge_Ll;$*c Qv0HTƶA: `yDel;$C Q-$*cBˡ ukTPS:đJX,PƲfQ25**Uϼfz$4.dyb- Y~1Y~[KsB Q/˷Z:cd_KT/~Ye_KGT/}Ye_K7,_|߯~ ,EYk骗(3Q5BK~  ' ҏ,wZd+L?(_ҏЇǠc̻'焀c,e 8B0o2! c, eCj(s1 sVRc0B0Ɯa@1'C>&a ae # c,{ec(.@X0ƲP12!ae+ s{ec (⼥ c,ec(!⼥ cOp2\˔aqR1k21g!dc08o)s1Ca}-ec~0Ca}X(s1yKX0ƲS10B0yK˜![hƲOS8y XvjjyMjdvMjdvMb4,Gq4,Gq4,Gq41h2V;&F5Mjȣ`[0 C&F5MjȫFa41~`9C>.9?~WT?'rn1¹!rQ,#1rQ,#XTEňc?eS6?OyA{~2$4meyn-ZY^dyn RZe &~#[Z: #Z:1H5겖6YtdΑe Gjdyg#˟ncYvO11or1B1raY&cmc21Ę/CL(!s99Ƙsaڭݘٍ0}715G9F9Xn:1rQ1ێrwcƣc,wC(˽G9o>1rQ9yK9X?1nB18o)71⼥c߲-{r1⼥#c߲8o)s1sr1\⼥cq}r1\![1ƜcyB1}r![1ƲSS9y 9X[1ƲR1r?loT\e{b,!cިFX7*.ƲQq1퍊loT\y@q1 !O(.ƶAq9iض7(.ƶAqBq9iض7(.Aq1 uc9 U?'cIsBq1-!nT\P\eKb,K!cY RHEXB*.8ƩRr  j5Ʋ~P1j絏y),ߛk3ߚ|iAqTdXǨ8_;*N2(G?Ce,3ra/4Ҙt_})e9A9GӘs1?haz0 c~0rr\ɔRe,2(c)GL9X.gQx=S2 r!^є咦ur\ԔAØ4qR2}c?yK9XQ8o)GB9ʘ?􅐣C-(cQƜqR2旇C_qR2c~y8yK9ʘ_yB2er![QƲpS:y 9X[QƲR2r췔eurloy@2rloe{e,(c(GF9ꐧ (c G4elC&m{el(!C&m{u(c G RT2ZJOKQXiˮIQXvMJƲkRT2]ved,E%!D%cY(*0d,CTq&Pq2 !ʠ8 kq[^_ױV%hgG>?a2Qh}3ZV'Y>Mhm3Z$˿/g/􌶥g,=]IQhQO˟U.3]F׸ 6gtg>[ܪ˼V5X&@ت Ve7 ݴtMk_ت5/[ *cgU Rc~׎Az#^ܪuͭj\ܪ˕ͭj\ܪ˵ͭj\ܪxus,7*#^ܪέʈ[`ĹU k v# ,o3ki ˛,/ki [D.Yu]\2 )r4el@"g\x)rm!t\B\|ie,7E.c\9r-٘IĘI"e,W9E.c)ruNX.t\rS2K"!^buW;E.c)r⼥e,;|td䬥#f b,/VWZƎ,/USJF,/TOy3J)Yޥ*%˛,/RG$ˋV d4!k- hY^dyCi cdy;e,z&Q|' !9?$'ctgLZJNx(9 !9%}%m̗a6d0Ɯ99azBr2wC=)9IoPJNrRr:[ܣ)9UJ/SJNrRr:Ŕ\¥$Q\JNƜ֥t󖒓ܼqRr2wC]-%'cNNƜqRr2t󖒓1?C![JNPb%8o)9C![HNƜ99dI-$'co)9~KX[JNƲRr2췔ed,-%'!$'cY(9jGXV;JNƲQr2Վvy@r2!HNƶAr:QV;HNƶArBr:QV;HNL1_܆咦6dmȘې1 6dxQ2!^vԆ庣6t!c R2[!{Ԇ6t'!c5 ˽ImHm-!c< ⼥6d܆qR2ׅCԆІu-!cnC܆qR26tڐ1[![jCbo!8o [![hC܆ 6dmHm-!co ~KmX[jCƲR2ڐԆe6d,e}‘}epd,{#c(GX> G< #c pdl{#c  !pdl{CC)˂FX4?ƲQ1!$C0ַ^__AX|_s0槑7_Y"+,o4ki>#n-:Y>t|dȭ'n ,1|ݾvYeb{}-]|򥾖1|򅾖sYeN+Yo5Ax Ơ_U,7ƨ4󇏱* /JAi8TeQi8PPeQi0Ԙtuj̥XS* \4si8L/_B( y8N`,c4DX&* x;Qi0J!PTӘ8v`,c44⼥`,CT4si8yK?dqRiBi0CT4si8yKK![* \4⼥`̥K![* \yBi0`̥-c. B( 3Rgt=d2|?Sce`F'3j n?=A0 aA| e`p,#`3ʘϨA:)3 A č9< >HAܘoMtk,q#IA܈grp r p7A|nMtk2QA|6qA!q#[ nyA| q#[t4  ]8o9R nyA|-A č8o9R nyA|-A č,eB `5yal&z#>,mB?vM,ya.}Y˚ŝ}Y[>Xgbg,3;`ٍccg>g7PwY^='ˋ,v'RHY~eq\KO,?ceQ\KOyY>,Y)G,|PsRIY>%!9}^HY>!eJ5|W95 ~ hCd9Qf7i@Xevcٍe&Pf7@Xevc>:LG1Q| 1#21_CbאÔ}ٍ9cWcqSf7NG:evc)\~>|1櫏1_}4n, evc9Q( !⼥n, eCٍ9sf?yKݘ3![B|;yKݘ31gCٍ9⼥n̙ݘ3![Ɯٍ9⼥n̙-dvcƜyBf7.~2u)~KX[ƲRf72췔ٍen,-eCٍe~2췔yBI?%XI*<ޠ:I%]%I(<ޠ: %tc[': %}l5Temlfj jHm,#!T\j/Կo@^Ko,DyY>#)O,?@Yۘ~c>񌢬mk1iB6}21gmc2)k\m,fڇ8)k=Ę!bc=OrP6![rP>yKYۘ1gC9k⼥-mC9ks>yKYۘ![Ɯ9k⼥mYۘ![ƜyB6mY-dmcBڇy YX[ڇ F٘+L0ȟ+,?}F,?X}F,?|F3zeq|FOǰ"?gQg$>Qgt|/ŕgVdyF3:Ϟq&˧3:>Mg4ec)~Fa)]?5xZs 6k`yk`y7kq-Ycijk m˃-q^q ,k ATN 95xLJeVr 6_Ħ;V;lF5tjMȣ`YH}5 1UcW]_b|,`_wu`_{/ ׵)'ˇZ:dCl-aD)Zzei*ZzeIQY> A0aV3Zںe9rrP*˓q O|P.1Ƽ,kF1R 5Wb!lCC}j,o4yh̳g?PcCqFP 5)A1XPcrn1Ԙc1ȯic6٘7ô1R 5٘7ô1l1ȯP 5sb CCqR 5j1-PcCqR 5{![BCqR 5j1-Pc8o)s 5zb1Pc8o)s =y 1Ԙc1CC9 !j,DƲR 5bCej,-Pco)~K1-Pco)j,-P!$McY(iil $C4mAy߲a|-C| J!>TJO_0 &ڴZԂ*j,s!j@c5j,s{1AOY>;eo-C'Zzd*ZzdiMY>adYK4VY'kiv"D4ֵMZ/cX:F՘wPcyYjRc=Xmzf1~cAyj,!j2%˜j,17VcnX o+1ij+1i7ޘWxc^qkj,5Vc9 ⼥j̍՘![j|2![j|:yKU՘o@8osc5z17CXsc=yK՘17CXj̍՘![hXXyBc5{"5Vco~KX[jƲRc5XezXyBc5J!PJm͂Rzȯ=Rc[r[*Ʋ'P)5=J!>TJPJeO€ Q5iUXF eTc5Q'jXF eńY>ex3Nt',?sk鑓'n 2,?okqMV~[Ȩ|V1ȨHҾ.yD,Ǒ1Ȩki{˲,ߕ s u21 RF=Q5z/"eT!dTcy)H0~cƼf?@X&eCQeJPF59AX&eTcΨƜQ9k1gTc~?H՘{c~o1ƼBXʨr2PFBF=yK՘31gCQzdףCQzt221_qRF5j-eTcΨ8o)sF5z21gTcΨ8o)sF=y ՘31gCQ9 !򼅌j,DʨƲRF52췔Qej,-eTco)~K-dTco)򼅌j,-P!Pc[  1ؖ%x=!ȨƲ'PF=2 QeOj,{eTc+{5Vc]-xAcBc59DX5C=sc59č7wgt@>c|=S=<ّG=9VY~lSFJIB,V*,/Ϩ< ,/VnB1l2|9y7,/':q,/'Jq,/'OcŃ4i%Qlל`y9yU9X^vNu9X^xN<)yR4+ %AJƼ m?H[ mq9Hӈ`<8o9yR-'A Uƈ ]e8o9y>9HW#[Ntiys-'AJ<8o9yRiys-&AJ<9X[Neiys췜<dYK,?9cQB4WT<(6Ql+ɔ<]i,o3%O!$Ocy)y+MX^jJƜ<9ysP'N.byN`q.mYP'˻ur]P'N. byŠN. bN.:ᶼb?nBN.%ÒŸ/%qQ:bNsAP'Mg1t~-xY7y ur1t~-Ic8oN.ƛb [8oN.:⼅:b?b?6X'cAN.:iuy:urP'me:9XFW2z1XW2AzsLzAsepl`X=iās UOcR9HӘoT=z-| UχX=8ozҭmnmF\=6H6#[tk3 ڌ8ozҭmnmF\=fys UO#[T=zqriys UO#[T=b49H`ozyb,-WO#[z`ozyb,-WO#W=K(+'rr5r$:XWNF9Õ`9\9Õ`9\9Õ`9\9p$`y9מLq5I; {ٰ, |0򹰖&,?c=eXKφ,?o/?,k釗,njA咱}Y1dbz1c.\8m̅Ø aڸ_ps0q6n!Vc6TZePi5CXfVc:TZePi=ĩD՘7QcLTZe4Qi5DUXVcPTZeFQi59VcCPZqQi59DVc.\ZߘK1t7j̥U-Vc e-Vc e-Vc ⼥*j̗CTZ2h̗CTZ2xJ1Vc.8osi5zJ1CPZsi=y ՘KJ![(\ZyBi5J![(ƲRi=y UX[*ƲRi=y X[*8or;j,+C'PZpz?6Vc9\JXW*rRi5ÕJTZpTZ嵧j,=C~KnzO֯w@ia-M Y>d`sa-M Y>Ơñ YeWݵo 5UZzǠrXK, YN\*<5ݿ g>/dk̵Řk1זôsm1r!T_c-\[o̵EIX"%ace4R6HIX#%ac>;yKIؘ1'C9 $lIؘ![HƜyB6$|췔yB6![HBHƲR6![HƲRSWJ‡y JIC$ac9\) MIXWJrR6Õp$l,+%C<\)  XlfS57n33<F~Yh 3z8dxF?3}~]Yq3j 3  ?j3#2ݱ>/q-3H!fB1_ ) R1CŃb)`B ˬdͿ>Ao>lm,#eoc9){ IXH|-0k!?Z`,/eoc9){L[XNarS6mlGdC<:({ArtP>ģ1gÔa9{]-eoc-eocYM){⼥m,eocY({*@XVƲ P6U![Ɯ9{⼥mۘ![ƜyB6m-docBއy X[އy ۘ![em,-lco)`~KX[ ƲR>y {O9?n nIuXOۇ{R6!Tm,'mc9?nIuXOr~R>aK=Pe-fK?Qok-WǵKq;k=\rY~;.˯,k,A-o>KPeՖ7{ z y)mA0-9Uqۘ1ôs0 `A0-{LXd*.S>ķʷʷT啦m,/5ocy| |MҘo|30!0TPfpȏ&oc ۘ˷-Tesm, o!ocY_|Cۘa*1\}oc;|R6!tT堣}oc.߇ݘoB(߇8o|Xz*Ʋ P6UʷTqRB6UʷTem,CT|s>yKۘ˷1CT|mۘ![(\PyB6}ʷ1oco|~KX[*ƲR6ʷTqR6#!d判}?mc9")nOFqXHrDR6#ⶱ判m,G$|D~I(C?,=3=,} 33gJ^g>>Qg2>wQ_g&~ 33ze,a~F/3ze,a~F/ %hA}F,zmK ]RoKC׃tK1/tK ]yK ]b,`\8^?z=X2 ^YzL^8H m`z mF~4^voG p, p~zl=\^Rzm valk#t\Aڈrq6Azt\j>HWX8o^kk#[׃ezmyz\*z\*z\*ڈ`p6z=Hz-AFX^R6z=H!k#[׃Te~ H²O>Ydy[K;',/|kiߓuO'˫oc+ocbj!C1ôs0pS!pc~ÍeQ?H9\9Xf pcÍeR7IHQۘ~c^y?ģ1/A60emQX2ڇA6}-EmcmQۘ!e,=HQX2ڇxQ6!e,myc !j⼥m,ڇ8o)jˁNQ-Emc9)jˁNQXtrS6qR6 ECCQ-EmcP6Emcڇy Qۘ![9j򼅨m,-ECe=HiX2JӇwKiX2JӇwKiX2JӇw iX2JrQ6Ҵe,~eGC/KZ:SdyΏZzeagY$,ϱ,?k)X<Yߵ+<ey %l-`& +eyk-^z浖/Y޻dyk1*ec0|'7;1ӎhwrcј!C~ԗeQ_6H}XF ecԗe R%6-ژhcޢ|J,Jl[!?&Pcؘ+1WC~Ls%6J|%UbcćxbR%6*!Ts%>ē*HPˉDO$r"Q%>*HTDJ,J|*F⼥Jl,7ć8o˱LXer,S%6c*T~B-UbcP%>yKX)TqR%6 UbcP%6 Ubc\PyB%6J|*1Wbcćc#,:欥GY~mdYK/,3ʬ7F_1H˲E_YyW -MW7Y݄,k,omknBZM7&ZdyY]MWgȋe!ec50|7k1_ZixcX2:\l,F2:|l,1oƼV~G'Ug!Tgc1l\:c٘1WCÔT@l,.UC㊪WTl,UC<:qEX+B·8o:E![rY|󖪳TXl,2Ugc9:˱LX.TqRu6 UCT C-UgcPu6 UgcPu6 Ug!TCP:l٘![ƲRu>yKyXy(<|rtP>ģ[g??Wŗ譗xY~៕ 3ZeyO|Fk3e8_p?m2/XzC,h5-h/|Fk,g~# UAƼR*0HU3#`\Om!F29b!AZiU7)!AJF1ER6)zR h#ؘ)ER6)z,՜Z)z,֜j)z,לz)ڈ rp6)z:xp,rp~)ڈ NуF)ڈS`Up6=XWNуp=XWNуp=XnS-rmy)z58Eqr, Nу)z98E[臘5kcY˖OX|jևxRQ6]!:ԬСf}5kc9tYˡCZjƲS>yKXjև8oYJXWjrR6ÕԬ2@-5kcP>yKX.ԬqR65kcP65kcPB>y ژ![hփTqQy6FgcoTeQy6 ~vg>_Yh}F[3Zzey5g~F3ZwѶ+h}F,g>5W_c~F;3Zqey>hig}F3Zl?{,(< }Yh?~[hp~bkhp~b~F[3Zbe8?g? V{3Z_*=hsĞVOhg}F+,g>}9g9ۈs`sG029g19{ *كeTq,Ê.XR6~_A*F=XR,;s,;Xzl\zl\zl\xq,<k#\˹ڈ rp, Xxp, k#[.փebm?JXqr~z\z\˺ڈ`YXqr,k?k#[.փeb=X.փeb=X.\b6b=Hڈ󖣴'G28Jqq,``(=X׿z9ij_Ge'ey.˛Z:dy5\t(AB|--Z: dy[Wt-{Z: -;Z:dy[4eyۖe{-~Y^eyf,Y޲eZù ]'Y>־鷅.gOHce\Z ]jYުp~BBz '$tYާey^ ]wiY^p~BB=z '$tY^ey^K ]7hY^~.˯d-<BMXjrP?󀚾Lo,¯?X/o,Nj2=)sB7le{cxQ7lo,r]lo,Brglo,rolo,7rwlol3!x2)lo,Ge{c9:( !AX8o)˥![rlo,G$e{c9")IXHrŠl󖲽\3(⼥lo,W 8o)u\8(˕\:( !lo~8j˨n,׍C}ݘ1tyeyi.+Z಼0,ZceyW^K[7eY^eyO^Kc[dY^eyG^K#[7dY^Ҽ.۱,/kiVj,˛,/kiNZ,[ZZey'x ZMRdymx uY>dxZK,N|6>}]ϥ5eyw 'uY}p~B_W5eyw 'uY^xp~B_mWݵeyՕMwM'(yc9*yc9蟣n,yc9GIBeX*xP7ʼ!N2< ! !sB?ē1'C<(sB7%tcPB7;%t!$tcPB7%tcPB7%tcPB7a 1%tcƔ@ X. qSB7O Xf<%t!$CЍeSB?[%tc7PB?yK XЍ@ XNAJr RB7S"(⼥n,7 J8o)m![Jrn,w Jrn, JBH]hӕgg>W'3Zp~[Yh}F,h}F0lzF-h\Χgt<gt6p~bgt.p~bF[3Zbe8?1? VC3Z_*!hsVO hg}F+,g>}c8A`98>XN4NF<8 Nns`98?J>X+W2Z9R7I!|B3}C`p,w1kr1>XC`Hnđ!|TFEC'529I!!p#NjeRs7⭁C`7p7>XC`?p,rq,FMC-rny!|(8;r>Xb7;Hw2#gAʼyi0}c2,/vyey[KSF:Ydy[Kf 2,ski6'˜,rki&'ˋ,qki'KZ)cyeyn-Y^dy{m-Y^dys[K,mA]KIoײƶs 2,k}o WW5y 򚶆2,h+Oȼn2,/f+KOȼB2,cQ= Jט?q]NHLJS=6S걱Tأl,e!C<(-GiYX2bcćxR 6@| bcr@l,w r@,@l, r@l, r@llSMMć85)Ԥ@|SLM ćxDR 6yKX-b!CeR >bcqP >yKXnAXnAX: r@|A(⼥@l, ć8o)]F(}H( !R6l g5`cn܀{;d^Y^d9rf,fbd^YҐLW2YҀ}L1Yp]LW4 &kZ &+Zdyk-_}5w-Y%{ZZdyKwom!µ2d^Y^p~BMK5yeyZ WW,Yްp~BJ5yeyZ W*Y^RJw1ʼ8A)s=!']V rR 6!> 別@|,bc9fa,&bc92) !IXM B(xQ5{'\c.rYk,*ra+k,w*rkk,*6ޠxkl J!7*2ިxk,J!Tre0R5H%W%#\cTrJA%X.TrqR5\cZP5\c^P5 \cbP=yK%XTrqR5CTrA%X.TrA%X.Tr)s5X{b1bB%K{,Xk鍗K+Y^>=Vwf%ˋ,Uk5J*Yީ+.,/Tk+۔,/SkݖUJ7)Y^%k,oQkiJW1kiR'Yޞ$˻,N9}o =Vצ5cǠʴz,K.+˻O豲(򞴆z,/I#+ O豲rz,FQ= J=֘{!QƼ !>pyȦ{e^c9) !MnʼrzS=2Ĕyy0k,1o냒k%H*\rA%X.TrA%W%XnTrA%&\c`PrmA5 %'\c`TrqQ5 F%'\cP5G%W%g\c}Tr2B%X#TrqR5+ \cP5k \cP5 \cP=yK%X.(TrqR5K CTrB%X*TrB%X+c␢ky>Ug({֤g%=%Iُa}F,h?zF3ڎde}F3Zf$/3ڋZ$oǰ>D>Chm-ChUmBhXY0g 6g=GM-gp~bgp~b}F[3Zzd8?>G{3ZwѶ#=:hӑOhyF+,g<1FcqrUmVw89;X6μF|9m3C̼e!kĕ3`Y 8*{7rs~ ؈ 7yׇw2^μy3`p,7μ1K g60 wM0̼mal 3'g28qq,3'gr;Xgއy88g^#q8[g^#[μÙwu8gr;Xn@g<>h--h'GcX*BY^6g *6gրg| K,ϨT> -|?}o|?scX*ѩ/ėR{O,FG 'gt?c^K3:e8?T>Y9߱T>RJǸTqrRi!ʥrJ J#_A=n9Xne9Xne9XnF|q%nei `YFqu؍@)R5t`p,z!r:F 6j0Qt m`5:XF P#ep5:XF 2j8>j3`p5`q5:XA@E` q,!:t\8qr,"F@ň-r9:XG@,/k鹔5@Y^39S7@/ǿ,ka_~Y>҃(,k))g,kė_{Y>i/ˇ,k騗^1hk阗)ˇ,k鈗^xY>׾鷅)ˇZ:eh)Oh|򡾆,k8?qq.˧Oh|I,k8?qs-5NYn8Ǩqi̍(5Ncn8qR4idzl%@e/j, PcM(vB/ ƲP=l)@-j, PcU( m1QcxS5:j,"r-:j,#Br7:jlsꨱ!6:jls!!2:j,s!!2:*:z=Qc8Q=īQcª,/k8?!& ˋOª,ok8?!/au-UYV(ja(UcVqRX5ja)UcYK(EaXV rQX5ªªl(VqGj,[ C~ ˦BaXv BAu5j{\]DXLT]DUX.NT]mHAu5!؆TWcRP]mHAu=!EXUCRT]eHQu=!EXUWcRT]P]qHQu5[UC\͊![rj,+râj,w,rˢj,,8o]![rߢz󖪫ܹ~)!N02juS&`{, hxF32k gke>^zǸqr^k!ʽvz Z#Rkq7q\)qr, ^#\zRå׈%p}w6\zp, ^#Xzˎåwl9\zb5l:)R6x2`q,W12!fr <&f60 xM0ma6 yKXpqRz6kC_ʐl,C겱 )ˇ8.ː|CPWPWꗻn,um_azyPey=L:\7w*{,e'rY^dy#[KB1Y^66\w1Y^&&3NG,O4dyx[KM,϶1(kiQ/Y޽%˛,/^w}o \s5\5Pe`si 'rY>p~B)I5PeyŒ k 'rY.k8?r)RJ,rY.cTqR)7R~CJ1rc.8Hs)7R~ÔJJ1Cэeݡn, etcYy(C_[ƲPF?Շ2,?兌n, etcY( ! X j؍Aݘ17CA-!!؍&GXr؍mAc74vcoqQc7F5vcoqQc7FX5v!4Co؍eQc?݄\⼥n,=jrn,W>jrn,>jr~\⼥n,@j샔эeQF?9DXetcCхq}-k~W^:P7ׁ!Tu:w~yeyOww>^.,o{쭥lY^dyӓEo-y򖷖1H򆷖_ys_A\`, }.0W>+H ߂2vIY{~xF,>5mhgB> -?>m<~ ? <m8>af3<ɟ Fs\3h ? FhUM-hO|Fk~[$ Y> 1$CY>Ngt0p~'gt*p~'gt$=I? <}O蓀 '~xF'Y$> q'A$0(OI`> q'I`> q'I+,0;˟ß''#>I`,?I//~, ,+x''#`q9`qA r m6{`} 8{`} {g/,qro /0{`r#N ˭qr3F`{`5 Q ˨{G /,'/0 ~DŽ~DŽ~DŽ~#1a1g]*w_Jxȯ࿒)L0? |x-=cC J,,/kuXaY^.,˫,okio`Y>d\ci-|(򙴆|i }HO#Y{ey]K[,/ʻM-|t-|Y>KQ*',|o|o|}v+>p~·Y}Y}V!K}8 J>y8!J>ۇ18AJ>ۇ18aJ>Ø}@oBa,; }0>o^C7ͤƲCn7yOa,;}0->o!yXVq'|0 ca̟7qr c c c c}yf|07q c}yg}0G7q c}yXf}C}yXf}8G7G7Rn{y-} c c c cCyX.y-}0?2Ɵr\f蓊7rn铊7b,>!7b,3>LO*Bb,3>LO*2蓊r3>LO*8蓊DRTbR/52K!PR/Gqdy_K|Ƒ-=w/ˋZzdy_/ZZ3,e_CY> e(\K,|EOAY>3Z:e^r/˻,kgY>.'|Ƒ{-߲|z-gO#O#˧,k8?3,زg '|Ƒ8k8?3,Ƒc-r1Fqqgc8qgcc̟qqgcc̟qqg!|188P31i!|1>kIqe8Bc, }9>~Cq8Ʋgcr3> qeա8~—C\1K11/5fЗcїC\5K\K\K\K7Rcl x/58K7Rs㍾x/58K7Rc,㍾K!7Rc,㍾x/5r/5G):RsKKKKK![Rc,;Rs>c!c,W<+ }1GqIqegc}Gqqgcyc>kOc嵧1cyc!1X^{s=}1Cc1cC1Oc,s>6Pಖ1";Zzdy^\.˻,kiu]Yeyi_K;,[|j򡵖 Y>dZK/,W|\tXY%k,okiI]WtY׾鷅.cZO1"gZ:eZ5E5EOfY>p~Y>eO"\p~Y"ˋZ+dyb>.ƼU.Ř? .o)}pcr>sa7cY\蛊.M_>b, }S9 CTo*Ʋ7cYd蛊+Teo* 7C"蛊1S1o*I7cb,1"o*ro*r#o*r'o*r+o*67r㍾xo*8蛊7r㍾xo*2蛊xo*2!7b,6rrgo*8o雊ōՍ卾⼥o*ro*8o }pCX$X$+?J߉9c,_}1yKqew!|9yK\e&c Xf}p1@\q&c g}p1] }9 ː1cR5X?R?1TT>3x> b#gd||6,=Md||61gD#x,u/#F22X_FKϿ{(Ms &<_,<俖~a,Mְ~DgYID",#ct69 JgcGĘcGlb{1MlrŔ&B8 *Ml"ˈ teX Ac52r \FeޠˈLte䐿ACV+Mlbgc>b˧1Mek&Ʋ8XV':DgcYlb, MMMMXMp69Fgc)ot69Fgc٬lr\-Mp61 &ƲcX,:˞EgCt61]{NgcYlr5&ƲX:z@gcY>+e=q:Kq:?\Ec2b,_6]F˦ˈ|t9I.#R!!a,5NRa5g= -Ngcs-8-8~p[mq> ӷ,0lq,tY[ضXm^-)bJ-'Zm1m[¨m-ڶ8g}ѿm>a}fl[eaYmql- g>ab=O|ma' [a g>a OgaŁ0~+(0J E[єtYhDF3e_og4pfo{3ey0Fs3˟Q{a{32xoyFeO<{3Ȱ~[dX?-"3d m|o1b{ 2F,|oAf#R r3Hˍ)[e-F,|o{k*[e|o12k [˼2q![e|o13X:cK[u> 1f1F1flq|1ǘ1fr|,c>ǘ1ft|1bc`|1bc`|1bc`|,1czǘRoczǘ11ƈ c1ft> ǘ1f,~|1bcC -b-e%{`YI2XV -e%{`YI>~11f4> #3Xce||o1xR,=T'Ie||R,=T~ N*<< ~=<.CZey \4-Z"ˣ,Okrٕ+Ew-}\re⮥oP,18'Yey^K-WmYey^[8򌽖FlY"ZeyZg5pRN*{ea,TdN*|RY 'Y>Ie-ͭ< 3F'CtR1A(Ty1A )Ty1)TpR1!T:Ik_X'!TeΠ!NtR1YN*IX :A'!T[tR9oN*b,MN*b,N*|R9?-Te!!tR1MN*ƲIX9:>G'cb,;TIX-TIX-TIX-TIE'CtR1zK'CtR1UN*_W)Tq6N*b,݁N*b,T޾ pR1N*B8g'cYIb,+ Te%$tR1N*ƲIeN*b, N*r:KÈ|t1:a,'>_n}XO}YoF(8D Fdy^KYeyQz-MҲeۇlt0nƲuaXFaXFgBcitj©pj0ρN 9ЩX>:5dyF]K%s N ė20`e o_<_Ǘ$}~I~,K,}!ey#=}~lU>?X*~,݊vey#N>?Xv,~7bR5}ވUKR5}!j`Y}ވs_W)qN>?X 󃥯C|,>??^|,C>?!ːOe'27+`n2~e,_Kn >_?_?_?_<"4<򭥉O>Ydy[KӞ,{<򨷖&=Ydy[Kc<'3Z\qdrYKߨ,WY.6kR#˓Oz)_Ư7ezq_+'xc X2z7o~:l~<`+sZkeyVgڵ4D+Zg ^YYfR;)SkZHerr\K_,MYa ~-}/,Ok*ˣ,Ok_o o\e&rI^K,dYk DW1So*_ <<HM_\f, ]׌ep뚱 .t];ĪI5cu}t]3_]׌G5cuM5cyǣ!f,No?f,No?_ ׾ kh3.rvKYa=-hmh6gTey}FUgTeC|FdY o,h^|F3eyX|F3Ѥ([<=1Qg4$~מш(3jϨC?-gԝeX?Z32x^{FmdX?k2x^{F5@go+(i1b 24ym2|^3b1C< Ukt^3bM fĺ]?=`|{,=ooKm Sm__`07>A< OoOOzt x,+'vIo,^|,'=#|, 􌸂Io,a|3'Iob|{'=#|,X7Xv2>Iot^> 'yveL竝2 QvFj7XFu QveT`j7X意Vg?-[Mk[Mk[M` xl5Oze`7Xq>q`g}>>>ckR>+72IO1Io8X>1s`8X>1ρo8X3?k&/oF%qt{1q0wey]K?.Y^weyەew-dyՕMWݵ+[ZZr(˅YZj?\e(rM^K,WdY.k+Vg11/PXY_ey|]Kӫ,|4!:i,]'e]뤱,lt4ƲuX6NAIcY:y]'e}!t4ƲuRC?:i,]'uX9Nby뤱lNKϦ뤱l:@ OCi,s< Ct492X:@ ZMj5BN_V:y5V:y5V:il5V:i,s<]'e뤱t<2ugwĪIKct&.j]Xf0k FwMci,35~)_=+!~et4X2:z i,t{gWX!\a+}p=_É֘O,t5NƲ$҉XD:ˢH'ZcYD{he]!.t5N8ЉXF:H'Z!hqlt=G'Zc D{NDk,ݞNBj@WCV k,]a[+t5ƲX Z5jU8[5wq wq wqت wew㮱t5݁Ʋ;q7:@C>W*5]~RX*5]~X*CCn2XBPH7cc)t3>fl,/݌㥛|t3>ďn?^3݌q*tP6ʇLRtP>92IA/oÃ3z/3z-xF@=WgH o߆g Q/N:3jϨW3j>I ߆eY<g4&g4?]ExP~Fû,ht6<(?][3Ϩ?/geX?:3j2xP~F5{O<(? '.VY"oヲ+(i1b 94Ay2Ay.K(eɈ5ʃtP*re`+|P,ʃAyt>(alel>6f#6?k` xml5F<|xm6O̓e{k`X:݈O#}t$x#>"=~t[X?X Kc`)|7bc`)|7rc`yc7W>?c`Xo_ˬz#&|,f?/?{SZ_iW~Y~7CY~#Y~YK | bdì-Eۋ,wyroֲmYn,u-}ײr! Z7dyݐmC/+,okiѐ=c eAGYdy`X W~Yְ~•_GYְ~•_Yְ~•_kX?/,o?ki@GW1b+1HXDo1HXHo1HXL/+1_ҕߘ/zXSoW~cb]+1_e44Kۡ4K4K!6 K !6_J|U[5|U[5|Uc[5!!<`,K)e-,0ՔƲRxXS EcYQ)>K, eeL!I052 }B&X $DcY(`,ǟR/UjH3[4UjH3[4UjH3/ V!pȿH3[4!WjH3[4!WjH3[4{f0u ƲQX=J3˺GiC)`l >W_k RX RB9C}0.H9c邟J,ґ(Aq0D CWt$JPKG)JPK)JPb)JPrF(Aq;%(0Bj$(&@X&cJPdL cy{ A_0+ [Ü%+l_W`oXe/Xg +[\Bx-[l?ga&c[YxHm rjcA b9ʩVsjc0o(6[ϩSrϩVsjc,X,"6ˢŲ(Bjc,An9ZdNm?W!X!X'6Kb韐0bb韐X,RƜ0bHA|bHAWɩґ X:6Kb)RX,E R?E RHAjqb@j0b+_0Hb+9ұ Ft,"eHby)W^G aL?_oa0,aaY~Wgq,Zdyْ]k-}Ucr_&]m-drG[K M,T2dv5aT.dyJWZ%[,/Uk_o aYިB%AdyZKs,)<򐲆 'SXeL 2&Ү(cb,2&R(cb,2&R(cr2&R(creLe=!WMȘ[ՄUMȘO2&VM creL_yUCe(=Pdm@yFY0S,y!=EMg=-M?o3yϨ3wϨr{F:Y'Ϩ=0"˵-eh'{F+,odh!{F3Zd_og*6o3dyyF33a#g4Ȱ~b.hta3["g4Ȱ~byh˓xh6re2#Q P6HC )Pi()PbeF,@k*P)2HWa#U Ҩ a#> a#> a?9 2XC}/)#y18FbGa F1#ccd4: F1R8F2XjHKkHKw ݁c$F#lc$bRdL RII;H;Hc$b$o1,a1Y~˓姼C,򊷖:Y^dOn b$d孥F,;Ynwkr^,w:Y F ,s2v9Y^dyEnm!F"[ZZdy,opkiFGY`ְ~BDǗ5#EG5#Eǖ5#e 'HdyAp-m r8F1C#1(Hyb3 )Hyb3!S!Fb'C,#1!TsĘOƇXW)Fḅ#~GN)cb,2&(cb,2&(cb,=2&(cr} eCؾlۗ ac! r?0sؾlۗ acFIC ARXKJ|DIc0))r3%Eeˤ %EeѤ!1e"8,QRXNJII!$EqX읔9ĒJIc=))r%4bS#9ĂA1cY>>NEcـ(cb,;eLe 2&eCX ʘDcY>@C11@!dL;@C11C AغdL;@DC11C11C112&ƲQX6:ʘFGc(cbl2&\!cbl2&11CʘbOʘbOʘbOʘKOʘ!crؐ11FGC|14:ʘ?6dLQXeLQXjeLQkeLQ ʘbAC11z c_Bت H(QX^(Fr?jH>ߨ_u-Q b"5sBDe p-}x(+,oxk飓NZ b"-O;Zndrn,:Ynukrn "&k6'˜,rkiMN9Y־"&ĭNW1ʽ,0<"&Db1"&|>ĂJc>DbM1GL}u"&2Rk+ELe:} 0 0 pȿ!3s~Cf07a!O˦BycU(`, e_l,W8ĞKycZ(p{ es!v^+Byc_( !v^+CyCW0E B$Mc)`,7EI0" X(Xpȟ  e`!,0ᗂ2R@q K`q r`qoV!Xpȿ![`q!XpeV!XpeV!Xp,07) ˫ ]2Ecy`Hr`H RX(XppDC},0IC},0Ic,0# KC%@X R)upȿHKԁtAJKaԁFJKa!FJKa!:0݁R\!u`lRV!u`l_y}l,0, k )X`,/,M,?ZA@k`,cZdyǓO7]~'ˍm-}Tc,&Mm-M7drC[KLۙ,wdB746'˜,rkiMN9Y־ĭNW1ʽ,O)<򌲆 b1`|>ĂJc> bM`1JK!L `,Ү(`,R(`,8SXxJH c)pȕV!`lV7M&Ecy쀱IQv`&ف*o3ωفgډ,h{F[3Zd|F+3ds6<~ڡ,MϨ>^Z,wgQ63پ <)=kh]m-khW{Fm1;4Y.hK6<M3oxOq=x`Y8`5z#7 00WyS8X0X8X0X8X0X8X0X8X,,V,FEu-Q X 5sB@۔,w=(˛,/k[QƵ!A@۬,wٵ4r+v-5XY^Rw*{ &K," QDYey=\[nJ,oc,h-{Ydy0h ' dy(Z Ydy Z YdyZ Yְ~B@ Y$K,c,8 JcށRw`cށRw`cށR@cbA`1чXS)X`c1чXW)X`,) RXS | Kޯ?SCzO{G c @al(C!H0}H0 !AB c #a,e$[,XX8-2ƲgQFHˮE cٶ(#!! 02X(#!t0ɝBH:NIcH+,t$_B?PL R52~P&JtqJWKt! ]ale\!]aletqHW[t\!]ale\!]a,g8lHW + F cyGtQFXv$Hbt$HbQF e$QFXއ(#a,C0挄QF (RX:/(]QX(]QX( !(QX(q (@a,[(eƲuP␻(;@غ(;@غÿEыC"(za,o8 EыC(za,KE/Qg]K1^t 'm-UYnVV,R0 Ynвܟp(Y,Ԛe3rc^K}Y۲,/cXK,o@AYeyyqm!z!ˋZ*6ABTeyJ'5qj 'D/dyQj 'D/dy1j 'D/dyZ Ydy~ZK,OOZQ+(E/y>"J c^y>BJ c^y>bJ !D/b|?>ʞE)c韔"BX'H||IC&?1IC&~.5wN9SepN1q)IWi))("p5:O) rȍ) bl)Brp5:rpR8 !b,/N17Q KϦʟKc+?9ď'ƲQ?^ʟO'FcΟO,ğRrX+%W~~RgjJLM)C(Eb, JSHeTR$2SK*HBJ*HBJ*HʃEL"&\)bb,o19"&ƲP?^2#&*#&*?'FLQWxFMA 3j hzFۖ,gk=UK+gg=5Kgd=X<=W<=-W7FLdy:{F3Z^%˓3ڪRv*b-T\:c k\Ѩ&g4ɰ~bMi21yF#3dX?1bƳg4ɰ~bf21yFs3dy*{FC3ɾord\#Q Қ;Hk )GLi5׈Ŕ#&1b2Hc 1b2Hck*GLi1ڈu#&e2刉k+GLt2rdL1,3ߥ]C{be4L8bv±P82XZ ZKSX`i+ky#WZ_@ l10b fF ˆV11_[@`Y^9s f1ˁr ƈ bˁr !b8q f1 ƙqe,}y,kg^K~C9سEX:/bb ft^μ ʙ# ̼ ʙ# ̼ t(`1O4el(`9J3Xf 4q4Erȿx Q#1J3Z$Fi"1J3Z$Fi[(CEbfHEbfr,/,o9-3X:e}rZft$N`H1iqZf<#rZf<#rZf22F>9-2e[,s6rƈs6/C8e`93X| !C8FS83X<`Y8cJ!V13*5p[`yU``|,k,k, w@q|`Y(s@|Gk:Y;ld׬$˝FWE cT 2^E cV B*]}vDCd萋1D92dl"CV!2dl"CB JLCV(d,k1q1TƔ :oRAƲS*XdJ !teKT?Ʋ,RXE K[e b[%&ci!HKlHKlH4JRA(tȿ[H4N c)d,8eTS*XZ$[THH ck : ck 2 !EB*Z$RAL/džT<(S*X)c,튂? RX+ 'Hc(c,?1H 'H!R*X:/R*X:SdH!cY(2d,Ee=Ȑ:l z@CdžȐQdk?h}g6g~Ʊdyf~F[3ZZ*˕mha}F,Wg>eUK3. Xhrg4W>RXha83(<)qg4L>YRXha83")33!m2b8 =>rkX0HF,zqAXP95Hck*DZi1ڈuXe28k+DZtq2rkL,3*DZ˔ߥ>lLy 6)/#cckRNy f)N9S^rؘ,]S^rktVNy )2rsŔ`klXt6leXk%WbjTL\ UWȉmsʈ6'͉+#9q5XnN\ W1qeĉWeP`i,-CUErjHUP`i?4'ĕ{'K/`e,Wq8,MZpVk4j ݁Z15XgK`it,gYY-#lZF15:/fy15:/f[ŬCjbVku^j񭆳Z雳Z/Ƭ`y`y`邜2'Y9eOZ rVˈ gFYqVk?ʄa8apx!˄2apxlL,[y`Y8<6XV/ Ջce1<6XV/cucFel caxl2 ^᱇3r/`e,l5ecl8Yf:ɲrd&[d'KӁd[~Cz,qd9=f3-?[~gbwP mq,BYNVmKYmqōPmqm,LK*-鱳0mk-ngm+-nglY(8]rzg˳Pmq39=fCϜʼn39=fӤ-gX?sz'39=fc-NgaGH~+(XD!=Csb!b|Y!?cƜ[bAbk*㨼Gĺ 8*/cƜ[,)| 2Bzl̨[,S*˜w|Y,rgBlt`ȝ- IΝ-> IΝ-^ IΝ-~ ґ!wXz2KWܙ;[lm9[[1uy-ڗc^??A AkA\!XVcy Xcy-b^A Xdy-1ґ X:ļKG 1ґ eI e$bAsktHr w @l1fŲ@ll3 b邐[,]2` Bll[,d[lm9g[[֖slAn9r΀ [lm9g~_\ X!\oslgZ R3`R3` b bi:d?p %-N;Z*kdyy-4Yޞeyy^Kl r^9⼖vY^eyky-1Y^eyc^KӺ,˲.}my-M겼+,˛ZeyO5YTeyG1q-nY %#Z*۲< |(Oylr^<\r^<Lr^<a,O< YPGAY(ur^< b1?y!Ry1?yb1r^<bA1ÇXS)e1ÇXW)e1ÇX[)e,)弌e>L2r^2RX_ePf Ksg K! f,MB`4j oB`Ҭ)f,B`Ұ)f,-B`¯ֳ{W; !0V5!!vȿxH[Մ,Ŕ2r^SXVcyτr^ƲSXdy !u弄2BQ.c+2BQ.c+:į\W(%(xr Q.c:\R)%]6y@9C(e9/c(e,弌er^(e,r^(e,弌el:/r^֖!u_6伌-C2伌-C2伄: 9/cy!PX)ur^M9/cyWyKs4WyKs4Wy !u 弌e,P2GOysX=)u 弄2r^I!C?(f,q3B`2~PX baB`ƲQX= ˺G!0cY(vȿ˺G!C%@Q  J!0c3.!0c3.!0! Bغ!!&uHBL CC3 CC3 CC3D $d?p !&OZydy{-;Y޻ey^Kn bsʽ}Y^eyߖu{-9Y^ey^KN7mY^ !f|Y޲eyɖ{-a-Z޲] J,Ocq-mYeyxq '$dyp\ 1Yeyh\ 1Yey`\ 1Yװ~BBLGEYҠ(s,c; J 1cRB̘K )%ČĘKRBL 1cRB̘C3qؘC3qؘC3b2RBX&TJˌJ 1cR)!f,s*%R|X6njsS|Xz7nj{S|`3NCA|X81c3^N1c3~N1!Wk[-dˌB-dˌBleƲPSWjʖRMٲC QXkʖjM2!dq(t Kwt KZRR)e,%ZRR)e,%ZBHk Q\_ Q.c)e,:EeT(2AQ.!DuPXZEuPXFur˨NQ.c)uȟ=D ~.պ D B됻 D Bغ D:.Q.cye(!>PX^)u\LQ.cyo( ERX:/ERX:/E:O\ƲPX^')e,2(NR?Ar !e,#e L2 ZBHk˄Ai-c0(e,K!>Jk !e,v2ZƲQZX2Jk/ZƲQZ 2W;JkIi-ckt2Fi-ckt2Fi-!AZAKQ.c2\\ el \\ el \X(e,튣\Ar}F 03ꍲ\Vgyr1|F{3Ze~FVnYgnr|F3ڵe=M-߆Q.Yіgc|6g`?Z30р)˥߆Qg4\r~F3,`)Qg4Uʰ~bha(3'4)Qg4Jʰ~b͑h) h6rrkfH#Qr c =rkKĈŔ\15H *Gi6bM( Ã4rkAX[95XSr \eB(`Q95XTr 9\F,9-+F082X& ήq`082X& ή +12XjgWK`}],ή gWˑ+F%`ve8b_fW˱+F592zfW[/`e]l +1b^ٕ02z0-e[``ٖ9b 0b 0b (l`,[dsr\KRsYey-_KRrYR`,/䲼q_qY^ey_KQ7qY^Rm5\1_WpYey_K,߲}򽖪,<}-˳[dy\Ke[NY;ey\ Y9װ~BEMY7װ~BEgMY5װ~BE5l!Sg̵4b)[RŘC,l1ӘKRŘK)[l1q *[y>ĚJcy>ĺJcy>JcN)b,)[eB`̨l1)-2R+2F#!^S+<^Ck<^m'^ԋR/}BؾOHIcٱ(r[[eϢ`!(b,[eۢ`B&_L /dC%Pe @1!(8DPŘ(2DPX%PHQE c)R@1"E c+R@1!(2DPXJA c+Ɛ@9jՊ1$PC؊1$PC؊1$PqiQ-$P (\o!b,`@10JL!C)db,35L4t 'H!c)db,&21w sXF 'H!!HeN #19r$Bȑ˜@9c(Gb,sEEHQTXEEHATX)*b,1g{?6DE鞢"8RTX)*rC!EE#AT:DE#AT:DE9QcH1QcH1"ƲRT+DE]AT+DE]AT+EE]QTDŽDEd?p *"Q{ZA-Z=DEdysy- 6,KZ*2Ƽj,˲.ATd-M겼+,˛ZeyO5YTeys-nY= *"˓Z*۲ecXF:0Q>j1|(@RX|X|KycXF:0Q>eEj<|,rcp5>x8"[80-|,rcd"[80)>eJct𱈟 |>c~"~ta,:0|>XF:XO>pa,s|˜@2'>eNcC7RXt[cy;MXtӱȿO0;t,G7ƲgEؚwk:palMn:qN7tct[w !W,~ W++IغW[wA0@? W},B{,?Y%VY~sZZXTBNfdY~#UߨR,?PX:ki0姩,Leaz- Ų,W,?J-ˣ,OR9p +dy ʶ,π<x 'Ww 'W'ˣ5p_!s,}װ~},|װ~},|<]K,O{<}"VP0 "Q0ҘgE,t_ac0,b1 !W8+y^ĚJ<8u+y6qxk+WtJ2}Lt_a,3*W˔J2}"VZ0Y///p|a,_(A2L  cl>A8ن}pa, ]f]f,s.3AD2XEt!|(YrXĿ[0n:tlB2&ta, |lB2"1|Kac)ta,>pa,>0&ta, |lB2"&tal>u:[뀃ckpa,5:"[80|,rcY"[80ɘ>4t:XO>eC cc?A:0u |:>e䡃c>0>!|˜@2' t!cX׫σ~*UAܤJctb,USjy<ON9F1dy;F1)F|2H#QNrK#RNu CXL: ^ ҨlĂ)4*u ʃ4*u ʃe4딃x2XSN,)_ Sˌ)eJ2u+-_ YS):e |2XF N,_S')F:e}xF>@,C|b 7g`yVe|+|2X>@,  oP*SL5|bĩZTw-Fj ޵ ZTw-FŻAk,%ZKI廖RR ޵ w-eỖ2]`jeL5|2Xk1Tw-#];޵ :wHx2:޵ ]ߵĻ#[k, 9k1rŻ#[kls޵ 9Z˜w-Fe,qň ߵ Eߵ他Ỗ2]`yeZw-Fte|2XF>],ӕ2 `韯W|bZK#`eO>z,%^KI壗VRez1G/%#x2' G/`xr^`y?^<@lMP`k:xbďPKӡ?Wku Sdsq,e|-Y~" YRq.Z,cp"˭];4r_.˯ki"7,?q\IJkiǰ,e)|-w,?/,lRɗqm SdyXʽ,j^8kYZ8k1SC)cyq<{dD'O'O'O'2]?e~~.We˕EyrXF\Yđ.Wpb,#]C++|b,U.Wj励TM\励UM\1.WecyrXF\1.WqckWp .W]"֮re-\˦.W励lre-\Ǝ.W励Mpbl\ q"~etb_,WF)ƲȡE8X9tb,S TC)|b,S ,WF)8X=K!Kct'ܟKE\tWtb,USjq8Xetb,2:N1w,J)ƒ|q"Ntb,, )?8wp'[cyE"pbl}Oc+p'ݟK_OdZGYp"o]Y~^K5DΕgT?drwܟrk~- ޲erWnY~ZeY+˯1?mY~VҤ-YY~cZ +i0H#S8u F|]1Hc F|0X&)>I,$IA:,K㫃`;:, Kވ)Ge$}>z#>9?Q`}rT?X~'GQWeϯ/K/ #2,/ ^ ^2 `VBeF`lZ`Z`l[`[` |0X0eFntx0^`ٿ`A0r #[,0r 697!`ycsooC߈ e6&لCA l!ؖ9,ms|#eؑ8,QwYQAK~8,2˻.~87Q`Y/sToĉb'F bT?غ F ~]3FV0p,B܍`>8FV8p,+ wYgQ pk ,e x-}ϲ,7k[V+˝Z p6+]Zeer{-ߵ4sO_{c_K,?d'kivg,dw~y@Z*<A.˳ѵTey2HkX?!pOey"OeyaOeywYdy Y"`EDy Byyhc/.EҶ)B+*Ֆr_cKťXj.Ru)5KTRzbX~+o[cPzk,JoB魱V(]WԘק8zRkSc^.IѮtv;P+hXE(]O]cvyȟ Dhw?AvMOѮ)5w=EhXveNhwvO")5W>E\o!5>E֧hW"[vO"[vO"[vev?JoF"~ˣE(5[c?(5[cNoeVO`zltWitWit.bӡXBHoPzJoPz+؊.Xe˻[cyQzk,2Jo[Xv.PH魱+)][c낐[V"Ck<(52q`)5ge_3dz-A+2XYaVJY~CM[ErÔ~y-}cr^y- )eQrQY~ZDe]&ϲ1`)Td$ٵ ,?d5v~s-|Yq Z*U21C 9C3Axsr1. d(Ɯ\,P.g d(2x by@A> CX0|1\,P>6g(S21oy@roN|.bL|>C!$>2 rMȉsns16˫rFE2F3m+09Fcԉdoo57Y;>Fu6Ynlohcdy;F=c=h{Fc]Qs}F3ZQg=FUYns1 #-F3#c4/z\ Ums80O3bT9,?W.iyk-#6'.i2bb7rtqb9,?x. #/Z, ba 10bW\c FlLk ba FlNk R1H1\È%sA5XR9\c^F1`98`9,3?e\ck ɟs2sas2saz`ypaz`yp1X^k[k =`yp1XFX5˹9bA.`080_pbÉ1'w{nim,lE//v~Kј_R\zHhc~) a5vR\L/Ec~)Kјwыi7]1y종6]"H6]"6E.ژgEl6֘gE 6yv2q.XfNEIhc;im,'q]L^z hc@ivƼ^z hcުavƼU1"[EE Q^Ŀ[(˜@E Q69ƋXiil,5Riil,RoiiRoiiRoi/l,‹Xh/l,‹Xh/l,T0ZV"H52~qXկ1~y+"5 Vk)Sgk,,IJ\,YT`+˕Y 4OrY)Xki{|*gUnqh1j̋.6ŨƼ]Lwe\ꍹ/`̥ޘK"Zs7RE\4׍_ c4j1w ` `ls5He}k_ }g6q8H@c~ p642HAsG mihĪAЈ޲~1Hȿ_<фd?-;XA}+mWoիk<^i:AsK`z,UWq:HAZuc3 =1vWF켼z, ^«2u .zի?$\ ^!uVF?x:HAZ]u+^]u+^vūҮx:X^˻WeūW#[\^\oq:H`yWmի-^iA3H #[\Wo`i], qj?0ޮՃ],Řq:X1oW|ټz5W`yzWFy:Xl^`yj_6^˓ NRl eX_;tկ<^K"<,σ8(Ӡ,LeGz-D`)-ӓ,O$ˣ,ON4/7k?@[,wǯܙS4d̝i1Hc~jSӘ@SӘrg2δ?xخsgZ+w&!卹s9_Lܘ˹1E^ޘX i/o{yc/b51,f{yc^~1=7潼1?DKSE ao,myEb+c^,_l?IE7y^ElWK,X*5eR) IA1,EA1etX7 ,AALoFALoFALosP E (0G!,X )(0.HAcKX )(0.ڥ`-sPcyQPc? (0!\o!(0u1BP`lS2PCKϦ,`( 0MYXRi/HNcio, m"`o, m|_O6 Fٰ7m􅰴_ĿxZ}WdyZwN<]K#,OtKfo 7Ƽf›2msx3XmobxcOÛ2psx3Xno`9,77f<9,Ouo8qx3X:7Fl :7sx3X:7sx3X:7sx3H 7F xy9,o^o˛Û6`xcz`y01rf6ǃ96rf Kr3Xz6';11';gssU>^}b3X>^}g|`x9,/>11˱`x91˱`x91Nj`yp3X` O+OBH}Sc,}RcȘDƼ$ZLKAJ}S곈5Rc,bX8e7X)B<#xX>{g/cgcg9Yyc)Yoc)1ɘc)1ɘc)1xF񌱼)17538fQ^gxX>^gxXvRaa3-|k_>[Qlq[ Ӟ-{8⨷&=YQlq[ c-Ny8⌷F<[db[ e-1߸ŕ-nD7Cmq=b+AAiCt1q1/`h b|a_/a|b-.ap1lq|L],_%S?L]1S?8[\C8\C񷒃q O9b`bL}0SK%`b .`b >)c.⥋exb| ^2xb~ ^X.⥋exb\r}0,/],bxb],%BbI,'$HƜ ] Ř }9AŘ ] Ř }H.ebo!AX[H.ebL9AXv ],H>$HKs\!AX+$H \!AX+$HKsbi ],q }1.?6'HCr P\ost9AƏ sA9A\ost K9A [H. -Cd Bd B ],/$H BAbx!A ~ ],/$HďbYAt,^ # KgDO<.^K?YeyVeyRIkiL)QDYq 'YPCYey8fCY ey2XZ\e2^KQ߼KVo b0Y^^ÿy*˛1K11# ̘Ƽ&XLϘƼ&05$!`< 󀴘^7< d,5b0c- `< ![?y1IƘ'o@ f̓"rK X0`R)3BL1"bC .c(21.c(+%][X-JI\t-e YRo)2zKy>ʫQ^%|¬E}Rea1Y0˘ìE?(20˘ìE?(2歙¬E?(2),cR)2),cR)2),cMPe|/,cOPS Y?)ZIaO Re,,cfK0X'Y?)2}1Be,= Be,= BelY6~@%0k-YƼ7}"[m0k2IQ^ WK}Iy|W !2ŔWIy|WIy"~WIy"~WIy"~WIy"~W˖*cp^¼mWPhF]cv&ÿkΎ-mew1cH:F{qt6H FF[l0&Y^]Y]Y^~GMWlc,_=%%Ƽ1e"SRb3CdlwOL2$cє!K IjʐQd">ʐ9C2 ikeHƜ! !CZG1gHX(C22E(C2 2Er)CBd,aʐEL"!sd,bʐaL<)CBd,cʐ}L)C272eHJ XfMʐBd,&eH\o!C2Y2E!ˬI̚! !CZz ̚!-r ɘ7Ʋs XGiWG铱׳t;P4e,݁)cMKwhXESBHQ'c}>-XjOR(}2G">JQ/OR(}ZG铱>J@d,+WJeOE1߆1es*1*9FeUcTde{*1*\_߆1ey>F1-c1}fnYn;Ǩ ScTnQb{j1*oJ 1Ǩ*+1*Ǩʰ`uʫ k&ZoDjeXC0: k&Zh_*1Z] k&ZhQz2!hK6cOîR 9,.cb5HC Ƽ!|A8,mî8:a0,݁îߴl &DFWho|>K|>KlɈŒR.9[2bliLΖXj8[lɈAʖ)[2bli-p4HْK gKlɈ'gKlɈ(gK1[,/ZΖ˛%#N- R4X- -gKqA̖liq9[,\Ζh`8[2rliv-b4XF;Ζ\o1[,gKel fKF- ю%#[̖㟳%#[̖z^< ^`i<up4XV<up4XZO_0r4X #OF,< 1O0r4X #O0rd`)<iF`4X #OF&< (Oe7J-C$˃O<_K?Y\h,YY\d+%V+,ki4Iki.\rYʯ\GrYe\KmGK\Q*TKR1Z*˥T+5.r*z K\Bapi %YapI%YapIװN@$RY^^:,oJeyQz Ŀ&-4t,,bEwɘGEפɘGpcn˜Gpcy_L# cPd,=bE;KߠI|s|m1oˍy`E Aecޖ k:`R)[ĺN9TvM9TwQf,r0csr0c-b̘sE)3/rE)3/rE)Bf,lM9"ϔsf,lM9)Bf,mM9<)3Yr0c5)3YrEˬI9"[e֤l-`2kRf,&`BBf,&`\o!3=`\o!Xz`ƜK/{=J/X dW($3-dW($3B!UJ*%hXR)A3J 4c)-XJ*%hRR)A3J "TJЌRȟ=$hRR)A[4c)-rXֿ ,c-pd r~2\er ,_Y.\}~ 4Y鯥^zYeyyYer߹ڎ,wYn:cr,ZY.c]KV,YYװ@&%V+5!ry5ҵ1Hd9]55YNdy{ kk55Y Hdy*kXC ]4UwfVY޺=R)\R)Bh c~H,݌1?$!a0F9"6Qr@cp.bpBs?xyqc̋ECh̋c^ >>R0IcLKO`X(B0i,E,LKs`X# )4IE,LKM`XjR(4@&ekA-(4`ҘIcY_P0i, &eAIcbP0i,{ &e`X_ &e`X_ &B0i,/\o!4ᗂELK L !\z L.r`XV<L.r`rIceLs0i,E^Cji,MREl:ZʜREl:ZKӡR[J-RjRKcZ.RKcZ.bX-Ro)Bj5RKcZ.rMX-\j 4:ƲX]Aj)<_K?Y.ò\,`Y.\,W˯,WkiRkiܗi_}YQ_'}Yn1'1?AĘ )4HyE쌔wKos#-b8cߥRR)5$fL 51oYc^j,lnM"X@ѭ ˟&EBne:v E2!Ptk,3E2%Ptk,sEBnPtk,[c)KX EV0 5 EƲX7.㋢[cnRtk,[neCѭ[cYPtk,s|19p*>X>N`87©`V87©`87bT|LfٌS2q*>X3Nb*n:ĩ`C:ĩ`C:ĩ`CeiƩ`Yq*nG/⃔e{Ʃ`ٟq*~ST|t8,/NKST|t87rT|t87rT|t87rT|t8,/Nb*nz`yp*nz`/r*nzz^Ƒ`eRd>XzGFNq>X:FH0t#v$bd>X-GFzˑAK܈GK܈#Ro92,#&`d>X-GF zˑ F%|(2>?qefAd.ÑJ+˅Zr*+EZ\beyZ 2yZeyڗa_gkiԗ#ˍGεvdrӹzD\OeA,~-SY\Je^:,QYװN@,.% u5.VWװN@,.{kX' %,`aX\ubqY^^:,o^eyz-ͥvWA/bqc!/_G(B,n̏c~,e1?^b̏x1Nj1?^X-BR,n,bE칏e|eҘ(3_D4' ԍ=Qn, u!ңZ1(~29[ xc^p2ym8| N !7Orzc)7Orzc)_Orzc)_Orzc)_Qrzc)7arzc)7rz!X(7"E9)鍥HQNo,Erzc6q^9l(7]\o!7XvʎrzcYQN/X^ӋrzcyzQNo,O/E9<(_z 9<(_z 9<(_z 9<(7BBNo,O/BNo, O)7vEQ"(7vEQ"J !7CQ"6%$(~EWK~-Ro)BNo,rE܇RNo,rEKX-B`@No,rE.K~K ƲOX = OB|YcZr}-d@r}|-UgY.β _[@ԗd-rWt-$YnIܑ4!,#Y.IJ\ ࿖,aY\a _,kXC { kcJ݅_ĕ5!ey{+kXC ͭ,/na _װ@/+[Y^KۥXzX[XzBꍥ]PPEz1׋1^Ř_/zYLci !_ľIAtN wRPo,݅zc/KXz \ 7>CA"!ꍥ<̘2! Bo"ј7 BoLG5~o(&],IB0@RrXj]KMˁE t9`,5.&倱Xل.ecBrXP0HBXHRrX #]Kac)t9`Q"&t9 cY倱,r`-\倱l rXt9`,B倱rXނt9`,oA0 ][.-H\orXނt9.-H\orXނt9`,oA"[0 ],rco8X:,O#q"Up |DW8X K_c+t`,%qT:XĒJRR8`wt`,%qT:0JB8XRR8` [Ioeq 8XVt`+ \m8@k''5ZKc-YTe8/#4q,Ҹ/Ӿ,<_K}Iے,w%YnJRO$ZjHcp H,18,aY\a Y\~a YװqJ݅Y^V״װq,ha Y^~8,fa Y^^4ЎQo,]cK'Xz (_%(_L;c~Ř(bc~,1?P1Rci/b{XB(7&BAo,ECK;y) c0L1d1#y/\:rxE|Gg|Ne0Scac:e)7:e0F RX2,bySc)otʰN)"Yt`,32L RX*52a+52KSct`,NR)1G\oA Ʋ̤ScYg)"[8e0Sci)l5[8e)6Xt`,Z:e0g-2˳NYK \oXtʰNYK \oXt`,Z:e)"[8e0N) $K_c>H0B A;A"v:H0;,t`,0AF:HXH R aWt`,0AF:H0H B8HX R a $ß  cyA$ Ǩ р/?cTQ1Ǩx-ß'^+M<Կ H/1<,7cԳQ:FK1WǨ]rz^+^uZ,okY.ǨB} k^+|j k^+, okcTeXCZb&V5V5mxuph*ZWh*ZWhzo˂R`l,,U/ K˂R/,,՛/ X`^0 4a/Azi K ^e`id|YpK=Rx`t>,U\jx`Tv>0rRQx7I R$u} ERF>x`V:4:|W)5_<R|RsUaf0 enk7љ8<5Af,KkRoa[f0bkRo FaL|0Xfqf,Kkx` u5`i|0XZ_3 :5Af,Nf,Nf0rkAf,;Of,[Of,{Of8 e ) ) ) ) ) Fx0X|`z ) Fx0X|0[f8 Fx0[f0rfmfeHce|Aağ-_P ^FA,+KҮb+>8F|^1X*5WRy`|^q+K #.UbTj>0bRbTj>8F&x^1X*5Wy`Dyx^1X6|^1X6|^1X6_JUc_K5O/ ȯ~-}-Uk_KucZz|ӆ-^\Kq->ǵ>v-k]KcofR/ZlZcRRӋkz_KZO/}-a R֐xzaR֐xzq-Y'ǰӋkig1!ZZŵvZO/ǰӋkik*Rybb|^Xs>;B5:W,bzi4Kc14~_饱^yV+KybbT|^Xv>X,;W@.5bT|^V5y&`1ed)#+~ b1ed?x^iih|*E^!f,"3.Ì?|XT>8SÌ2UÌ*e·?G|q1f,J3K·RÌRaJ3K·?+u>X,3z>8Ì2Ì2Ìtabi:0bX,M'f,5h>X,|XV0c,Caz3abوÌŲ͇e+3.ÌŲ͇3#<f,Gx>X,|X0r3~ xX0rmmaz3|` 3 3 `jc4|6KW?xq1^m,F6K/W嫍^R_RIO:K'?k|>X,5>t\'瓎|ұXj|>XIbc|q1t@.5c|ēŲ'?c0Iba䓎ŲàIǵc?'\ޯ,W~Y.[˾,W}Y.g 'z˵4I,\,4YniѮ&Lۙ,wkr/Vv-u18>&mZzrY޲\ev_'\en_'\a 18} ktkG;װI,ta 18ې啰,og;mTPXJREbt}a,/p}a,Ŕ/1? Q(0GbzBXĮBWX*(XK  ct`a,u,ҁ1v-r5XsֵƜus%E˜E˜WƼ\O,y([O3 cyB=yetb,UAj9AWF R5dq:1A_ tt"sc+tb,}A9:YľB Wd O 89tb,-AE9H:9"[81I "XZ$KscY9,QX֨tb,T:Yz 2 9"[81*,rs[81VAe+@ Ʋsc 9"[81,rsc 9"[81Ams!,rsc_Lm+cF;2+cteO21IW&A•LҕH21IW&Witeb,LuЕ2YAW&:DW&:dYteb,LuЕ21AW&B2YRW&Ʋ+E.5peb,2Y_6\jLҕ~e' ʵ;?'(\߇,Y /C{,Y~4]KY~2IL3'(Z:,7w-18A&'=Zzr7g&\a3Yܲ\a3YװNržuLd#˯kX'D:װN6~pJ"˫10EWRX*]}KE^ta,>Շ0XLC1y%'[3tb,: 1'AJ~*.Mτ.MRӥTj4¥"ХTj4Yđ.Me(KoW)s9],_<]Xz]K/Kcetib,.Mѥ24Y^F&4KEXtib,m.M-ӥe4¥"[41L&ҖX2]K[KcٔҥJXtib,R4Yz &2aХ"[41)],rKcٝҥlOX6tib,41M]&.M¥l"d-\| &\o[41.MpioF;41.MmKcF;4ccitLb$"dD8&1s?>80JMRX*5vKctر;Ra".X*5v,bcta,;pرȟ=v&;cDa7XvKciWtavC'Ǩg<8FuXr)8Fctq(8F/c@9FY3v'5cQnw1uǨr;F9Yns;Q;F=N#Ǩw <8Fn <8FU[u;3v-:uq2xq^2xؓ[0b;RGˆ,K-;xg1X Y`))|ga3 ̃43

    w`0|g1Xj Y *wF3|g1H eSF&xg1H :GY%=nuۥ3=߱r#@,qTq6 3/u A*t; #b #bnȟ xSˆY R 2XNb1OYq}|c,~1X?x7e #o~1X7?0~JI|È?x7ˊeE"`Y|È+o 7"`9 #n~1H7`|o m7lo |7G >x7[-`v|7?Ge# #7Wˆ#Y ,8R`ˆ#Y ,;2R/`ˆ#Y ,Hw񝅑l|g1X l|g1X `+b~g1X {;o"v Yb-{BkCBkB|ZZcBWZxdy[KN,:Y^uki=%';n-dy6o)dyl{AQAQ63 (ҍCl!a=H7FAQ63 (?)!p#6K*|D]K*|?K܈_e]qOnu=`YWܓ+|+˺!Fʸ' xx|DVɍesO>Xb+%rO>XB%DpO>XB%DpOn=` ܓ1DpO>H= FH=-%pOny=`I5ܓybO>XR %pO>XR %pO>X ',ܓ$=`IRܓybO>XFؓCɍ-Fؓ|=--bO>-'l{r#bO>آ-aO>آ-aO\Cx|H\:+!qEl+!qE$bEl`9(rEl+rP؈ӄ+2M"(zҟ@,6YNmkE,&qMZcPrT[KIM,4Yik)rH&m-%4YhVVWw,dy>u,/1(zey,W(zǠH^YSp@+Yj gu .X~⯔\c<)s[~V\ciQk,?.rE]!5kXc=ąC]1_1_1_1_Cʠ5+Cʠ5+Qc=L' !td5(K]!.0rX,uƒh-!f0j%Q 9*bc}P[rTƖ"ԅ+늚g!4R|C<K!~<Kͳ|< y>İDͳNy>_4r852y7y^KYƠy尸e9*rR\vhey唸,gDY`YZJe9r4\KP,BYk)r(L4ϲSdy8( E,Mdy.y g4ϲ<p@<ͳ,'5 ccL= ccL5t>Bl,qcc ؘ.%R,[2֟%dQ|1ec ZT.Rl,YC\tT.ˢrO*eQlwc> \>ec>T.X2+ƒZ\>āAec&T.K6rX ƒM\>lB岱d*1Pl,لCT.s|ecCT.rXˇy 岱[(-!!(-Allec}P.rƖ\SoTSן> :k!tƲ訖6Ϟjic쩖6Ϟjic쩖>Ϟjic9R-}?0XK!6F!6FNPK?,bcPKr\K2e9c;Ҳ\Kr\Kc]ӥ,KYΖkiA--r-JY*e9TL)ˑR,ʵ'e9Nr\Kar jiY)RR"DZ&LdyU2 eyHᜀz *kYk8''o Tֲƨ6_!;ZX~TK yBl,<˿35/Mͳ[S|[gc5C <e1_e1_o̗|*r?(2G3|j̗) \6PI岱J*qaPlwƒ-\- !HPKKȢZcZX҇訖6EG!~TKˢZژ|~B-}_6|~7!^6R%R-}ji!\6B%P-}jic .TK⼥ZژkicqR-m̵![%IQ-}jicIRTKZXƒ6$E1|!o,wTKm!6hG![%Q-}jic9Z-r{HR-m,jicɷTKKZX-҇gu}32e3 IJG{Fqu( yFQ%geyv(r~FEge9?3J~Q}FWar3Ez&zF!Y^Ch =%$;װCMW  ;gGe8'CFaeQ ˯K?^z帗,;_{AJ8iA5^znS6unS6՘# ݦmC쥍8븗T#;L7HgX L%ȃt8X՟%y[F],e#nKv],)e#nvو'˃%pcnOgGCc>~J$Ԟb*Tl{jOeS{j,۞ScԞ⼥X=8o=5ԘCԞs{zSc&ԞX @eQj̳@ЁgvA*˟ZrXhjeH,ZYγgҢTZde9r]K1VS,XYΰk)rt^e9*˛H,dy ZK;HW,o1Gey]8pP[yXWjQ՘!N j+9Ҙ/R1a^Ϙ9J1'K1 !Q9 IcYsTHˢBXVƲ쨐4uG!.<*$eQ!yK IcY{THD>*$eQ!)B041 A1u)%P!y1 I!ƲЩ4N,t*$eS!y IcYTH⼥BҘ Ic.$qR!i̅![($%P!y Ic .THBX \4B1rcC![($PH˵ rqC![($4*$ IcBR[*$%R!i, IcɷTHKBX-cn>5[x shf1j>)eBAܻs˷o{>ZŲ [hΆolhcA-Ɩo1|y -bl>6|%@A[,Z-bI5-T-bI5-Ɩo\@A3o܅@˷XnC -Ɩo\@˷X.E[,"s˷X-|%B˷X-|%B˷X-|%BA[l6|y[ŖosA[l6|-o-ܗ[-1|-o-ܗ[Ŗr'[,kZZo 3ϘCWX>{>[,Z>[,Z>[, xn7~w`~yF_:EPY< .X=:eOY(y>r,{FS33(q>)yg6Qؔ3J4 g3Qʔ235hyFY^3h<%kߴc~AC1fhP!6CFs34Ha͈un)=)C˟X 9`T\ Y`V\ y`X\qfq3X?F[\ ?$.g/.)˟A*)%RJ6b gR d7PJl4C,˟AK#[.˟A*1gʟA*8o˟\1g.! S XNT_11FS9c138o1曊CTs9c![*g1r-3ƒ1E匱(*g%Q9#r-3ƒ1Q"T1ǺC)GwcuƲͩ1}Z\xTʣXU6BleQec,*c}TXU6Ʋ99BlAlqRec,*CT6X!U6BlqQec,K*CCT)XN9T]1%*!T6\⼥Ƙ+clqRec̕![l1-U6٨9yK6l%Qec,э*c oT9y 4l:Ϙ%Qec,*c}TKXnr1lyBec̕[l%Rec,*!T6ƒo1|K[l%Rec,*cɷT-T6??i)ӘS/?3m^:%c^1Pt$c X75HƲA2N lqjeSd,C] 695HƲѩA: F lujeS$G 5HƲܩA:QC A:|axJI 17H8oA2ɘC st$c ⼥Xb"5H8oA2H Ej%.Rd,$!4HůwM,e4=||_Y>}-%Y>}C1s!~Ls5zedl)@dl).1icŸ|6A풱 j%hP$vXKƒ6]2A풱$j%sPd,ڥC.KvKƒ>]:ĩI풱$j%P$vG KD]:L(Kװ^zF+Qg3Zh>u(-g *M3ڃ g43^hvzF;rG'3xhK<Ѱ{VfK~3 26zFwj@&VV^]  ]<Y6]WVF:#~\Y Riď?t;6a/M` a6B؄ ֿ%?% q6X7a%q6X27a , ,ш ,񈛰 3&l$nŒ ,A0#nKX&l%nbfQM`L܄15q6HM 5aoO&l0#> {M 5aF܄ R6HM-7a%r6X.7a%rx 3&l^nK&l$_nK&!6aF؄ hM`v܄ hM`v܄ 嫑-6a ,}܄ >nŒA.'HE4WdyWM>1hdyM/O,(Y^Qk髓%IZNdy74,Q$˟,A,_)-|2ZNM,_Y),c?y&^Ym,5І0Y嫁5ІhdR@~Y6a|!p0cQq(Pf!JV G;-hУz4c{cg0{cIgԣKvXhBь%Qf,z4c qԣKXhG;N=91Qf,zC5ԣKXhBqPf,zCwԣsf=7͘{Cԣ G3滪CԣK@-hG3L=eфУKV-hƒG3L=dfь%5S&-hG3hG=D;ь%Qfw~~(q--GYލf({Q (dy'J\9ŗ,pN@%˧xY>į"GxY>Qu/c>Ⱐ˘1ǓCT|s<_S+&VЊZ1cC+flxhń?01a:1!sjŌG:b;ıN@jqS+f,!ZAjŌ%R+vIZ1cɂԊ⨡VX bƒB+vZ1cԊb0V̘[1cn?%b܊⼥VL1_.⼥VX3b8o3MdhjŌ%ES+&VX4b8o30MijŌ%PS+f,юZ1!bLgnc>sۘ܇8S231qdSdgC)ۘ܇8S231qzSd,9:Aꔌ%Qta:%c{)4NX"uJSBtc:%cS:HF?%wJ)⼥NI1߾⼥NX2uJ8oS2Ldꔌ%(S$NX2uJ8oS2L$fꔌ%3Sd,:%!tJ?1d0-c>?r0 fA!Y0?<|2aJ|2Õ1qRy`̇+c>\W8{<0Õ1qRy`̇+c>\ !a*9Hs:LY9Hs:ę@偱)*?<<BypØc.<8H偱dF*qRy`̧CT<0K偱\*%Ry`,IʃCTKڥ-ƒx<8yK偱^*%Ry`,ɗcɾT<8y 偱d0*%Ry`,c TK[(<8y 偱[*%Ry`,cɷTK@偱[*%Ry`,cɷTKX-gac, Y.lq9 Cg-%ų-Wh![<ɠ`9h1>AA09h18G~g_G:: W: WAp:Ap:ApcqUb51|0ucYf1ƚgW%Ub_W|ApUb_W*8o*1?*$U_,YKZŒW*8o*dV [_,?KvŒ^*W_, *?IHBtP&U|D2#!NdGCT'(U|D2#!NQdGCTsV:aJ1g%cJdYɘ1gCTsV:đJ1WBqR`1WJʘ+c8yKT%R`,I*cɪTKZ X*U8o0J![%Rp*cɮTKz X+Uƒ`Bp*cTK X",Ua0K[%R`,*CPK -Tƒo8y [%R`,*cɷTK X-]C?--e7lƖMز [6[~c&p [6[CVX BƒMX K6 X>{?*cT=!Ur cUr OZ_<Ơᵖf,.Y\<ܒ%Sk- -YY0#!NPdGCTɘH8I0tÔ*cJƜʘ1g%cJ8R0t#*cPH +cqR`1W8o0JT%R`,Y*cITK^ -UƒY8yKVqR`,ٕ*cITK~ X,UByB`,*cTK X",U\ @[%Rp*cɷT X-Ux~/c>xb^|:ġKł1uc>xb^|:Kł1u3cN`8X0f 0%McN`Ɯ90b!c*XBpØc.X8yKł1 |?yKł[*%R`,cIT,KΥbX. 8oX0K![*%RpcIT,KbX/ ƒ}XBpc T,KbX/ ~X0|Kł[*%R`,CP,Kb- ƒoX8y ł[*%R`,cɷT,KbABzB"0-D@=`l!CQC=`l!CQS=`,!CQS=`,!c TKz@UlJ!;0+uxH݁\;8$E݁\kw,8;0ea_F,Oa_ư,Og4 ~F#X'3h}F g4{eyh>+Mg4tey<&3t:4dj'4dj'Sc>1Ld*XW3a:V1iqSgc1u6|5ut:cUTƘϴ8131iq8Sgc՘!hl9⌦Ƙ1Ô9s~5z:cί81F!Njl1-u6|b7*8o1K_l%Sgc,:c K -u69yKalqRgc,:c K,X1u6BlyBgc,ɘ:cIK2X-u6ƒo1|K[l%Rgs:cɷX-u60Lc>֘ϴLkgZc>Vττ0-Șч8ĩ'2-wsz"c>G;YN=l9qSOdC9ژч8֩'2XḻG;DqSOḏؘca:rs,6XḻgWaƒ$ZN啼ǠHuey*^KX,ᵴey ieyA/WZzey]K^O|"0wc>0pc<|7C1PP/Pzd!R(WЈ AK9#[. Rndf. KjЈ ÇX̅` \̅` \qra8XB4F\ ͅ-%Lsa8X4%Psa8X"504pdj. Kpdj. Kp[. Kp[. K o04p[. L[`se9rYK̲uƠݔ夳e9ȓ唳ye9rY[h7e9rYKr MY6mҚ`#˹f-HYN5jd9Ӭ(W1|3FaڎƼySMe̛ʘ71oô&Ƙob&F'a69|_?烢|PEZcN5q+Zc2qkZcNƜ<E⡨5Ü10wZc>a|;EEE10w|3Ü1q]QQk̇C\WTsQ+-|i8o5OE![*j@E5SrXNTK-r-r&-r.XNTـZc9PQ+-r*j Zc9SQ+XTE4r&rX_X/~5K-Qx%Rk,A*CܟTsk,A*^c TKw*^c T,Tҿ,%YIkYST?,'$YH?,#YGko ,'#YFkiɎA+˩HCZZd9*yH,YeGpƨ=Lk̘ט1ôƌy35v֘11O<ؘ!?Y[_q:?2 _Jpc/ !!7_4냆\ 1odžܘ!ntjȍј!n!7/CBCnl_64eCCņC\Ԑ)ژOч!7S!yjȍm̧ta̧hc>E)=5|>mO 17BhqRCn||rc9j rc}Ԑ?4r\ !?{|jȍlO !fMjȍlO -g{ύ%S}~B}n,ɘC\_?%R.nX",ua[?Kݺ1wa[7KݺDX[7"3J`(ůgd'ׯa,?b3J]O23\2wgdyu(k=%kgdyg?B3X35ݍy go AƼfhnfȘCi}FG-Ͽe6,32u,s2y72|7/Ǯȿxb?HA)HG] ݅R46M76MlA0b>A0b>AA0b0qr?HWteny]`9qoy]`9q?XBw%Dp?XBw%Dp?XBwF#wFcwFw0]`9q?Xt?Įr,o,o,o7Ů[Y|k"ˉOZyrOC,'=Yzkg!1OS&y,Gz a,CrrO!lO!r5111CKগG饄nz)a,CBBx a,ɘCK211?0dL!%ccIbCc2=c; ?[ }l1->[{gaiOBb; [Lzl1睅_-<[ yg!0bijńg,Y~ aY l1ٝ`c-l2W B|0Ÿj`Xq5.ոWz1E-ƻŸq?B,ƕWq8[Ų2-bXYϯ(-b_|~Ec~EAWm0Wm0Wm0We1޴,ƛbW僘biY7- biY7-僘bi &)xEoZq+XF,S)X,RxEXNb$ xEA˜_Q,(K€W%a+Œ0q+rTWy (q^Q|-X,GVxEXb[b9+ c~EAb9+rrW%+Œobɷb[xEX-X,^Q|m~EX- b[xEAbɷb[xEX-0~_Q|?b!W-W)Xl%Xl%Xl%Xl%Xl%Xl% Hb .CW%+bpW%+\b .{2bbb9r'b@'O,>AX,?xxȁ3>8cxxXr<LYƘ/Ռy?aJAy:@Ay| |1!Έ?ˇeCc9=$CcY{x+b]oE9ފsz?51tcN"65!ᭈMMx+blSފԄ"65ᭈ1_b"|etފ1_ҘȘ1f[c2:ĘEoEHoEq[c9[CVXNV-1AoE%D[c VXB1AoE%D[뎒Lr\ o,alYR7vH]E=i_2$"-eEe![ʊ,KYC1y"2RVXfZʊTKY!dEBVXZʊXKYco)+b,-eE1"RV-dE![ȊKKYC1"RVX[!rg ֛@ A78![oqcM bl A78&1 |V bl A78&9ބ қPXz?J8!1GqC=!b,=A8BXf{ 2S{MlOqc)"8!ޟcݎw;c]F@XFgcI(b,# ^e$؋ {1b/2XPX bDc`Ac,(b,^)b,+^~ 7(Y.QϨF 3e}F3jQo/_3Qc/˟3j 2ϨϨF ,ϨFݼ Op\fAX#8._8Kc4F,`8K3Xn% {4f,`8Kc AV00h3 mi^xAAcf#E F1h3-mcf[ zAVo1h3-m1Έ}m1Έm1ny;Hq7HqFl8h3HqFl8h3Hq1hczA2rƈ6ࠍ-mKAapft,mKAapƈ6e栍-mA#[ I6e`9h3Xa<Ġ-m@Arf,-mKArf,-m\o1h3X[bf1rŠ`o9h3Xۿ߭,C8`f1q,`k?0KcY~`flfi[Y~`f1q,`k?0Kc4, 4,ÿqf> A2sf,=mlA#,=mz`9hc^6e`\9h6F\?>)V00coS8`` p˼)#C, p˼)2Xpƈmbf ,mIqf6e`,8h3X  mJA|6!Tdzd ˃Zey,@%H Zey,OkY@GY+s,kBGgYRS8!Ye_K,|\/rYe_K,_|Q0|~pcÍ77C,1[C,1?l:@9c y6<2@9c ME c(c,%t񾢄:reQBX.-J˵E c(sw+51RC.51RC.5B|ǘC>1)䐏wyaS![![q[q!vt1'Cl(cO|wgO|ww-weB![˔LC1;Xo)c,w1;~P|Xb9zKc)s;2CS|XhMc)#![(Mco)c,-w1;R|X[r9z co)s;R|G[C>1;| clw8@|[ck? clw9ck? sw!1;~P|G!wQ|llOc)c,=we!1ٞ;9^;2S|X.W!s+w߭|Rc+59?Vj s_eҡ!}1I?2;PBXfJ@ c(s%t9c,%tevܟxmW.`\ ,/Y dy.XK_,O<LrYdy XK,cޑa`-}޲< $ ˃Zey )` kH Z #w,_kF Ytm,˗,k*X/1Jؘ/bcElOhOXH)cO6b11_mx)cW!Jhḥ!Jhḥ_+wC=!1d,#%,7$%ĐCrMRbX.JJ UI!c,)1tgCV 1dl CV 1dl C< !1dS!H TtCƼQ1萏$!H !c: 1dlW$Đ]2WEc~U+'2D|V Ndl ĉ@z[oq"cM Ndl ĉ78&':D֛@{KoBqCM(Nd, ʼnKĐCR(1d,=%eĐ2ٞC2SbOH lOC\QbXf{J bI!c?)1d,'%:CBH [5ĐUH !ct(1t_$eҡ!}2Ir?2PX&@Cj(c̹c(c,~ ~Ͽ%%J+dR}$ݽ,7krk/˝,7kr[/]ZeL,wkӗ~^yYg/˽,kC&HxYnR7 Yue]Kw,_|㮥 W[Yne]K,ߵ|ՎQ&0]|U{E2Ah̏XH)d̏xŔ2A|L1_{X(dß1X(dß1Jܩ&2[DrRXnVJJiC])M$4\&2+DrRXYJ [a4FH[a4FH[a41ZBHuDH52F| jdl D A[Q#ck\ jdl Dq5.5:Fָ@h"8"8R0(c,1Epe  1"82S4@LCPXbBcW(c, Ep9{㻌1"82P琿>x@C c,Ep41旂4Rl sX_ KKAc H3HAc8H}QzF%J+3*PϨ>pd:=Ϩ5Ϩ}F,g>^W3t 8Ϩϕ#g>W3pQ+óg>V{3sѕ+73p}+3meZYjM.1_t;(pnXH93HpgbA.x93HץKpiψe84 gR9 atg,1Gwˍѝr'stg1ѝ,W3Gwѝr=stg\y#T # #< MwF>;;莑Fwuѝv]atg]WlFwuѝAzJ#6Az4U TK T`y`yCrtg1b`i?8czѝ~ptg,GwKѝ~ptg1b`y#-Gw;GwXo93X 83X^ 83X 83X^ 8;F,-GwKѝrtg,-GwKѝrtg1r`o9czѝrt;[Wݺ s=F>el] z|03غagu51)\`j03غ s=\`j03غ\~-;Fѝ2stg ,1Gw@ѝ2stg 1bѝ2stLj ;F:83X ;1cī,zibg,z2;p!zibft1A .36K`t0c󃜱,el>_ +,Y3kr"3Tbd9T[ӵԙrc*},kTrS*=Z:RܑAFѵtdfT{ѵtdFt odmM8Yej\K7,_|/kQoEYeN\KW,߈|!Q+(o1(o1͘RƘӌ1)o*=OcJPƘ7c PƘ7c(4sp9 9r_S8p}reS8/m !c,6sp1w9z c9c9!syyq9<qp1//y,<c s9vA82]c clws-Ҙ"p1E[aZ[!17 +s9zKci?(s9~P8-sp19~P8X KAC1 bp<"P8-s!9@cyLp<'P8GC19R8X[ KKco)c,-sp9z co)s9R8-s19@8Osp!2[WC>e19| cl] spu519@8غbWCc BXf^Kcy)c72RXf^bFcy)s@C(c,ov7B!bc,El냈L1 "62PX&!b# @ޭ?xY._,k[O]1.H YdZK,7@rM-@dYK,w>cg-=r#=Z:Hró:Y~đ7Y~YK{ B \ex-˥[+Z*ܲ\elr^KE[k,1 b1?b1?!R 1?b1':a!Jq"r #ָ@|Gq!$[C>H1#ָ@|[ck\ >bl G)!b,'"BHJ c\)!b,+%DerL1ɕ"IQBX&WJ⺇"rPB/J@ c(!"*}<%D1>"ABXxJKO c)!b,}<%D~Wۏr.ί|Ҵ"GLO,tdxZKKϖ,1P+YdZK],7USrKM-DRdZK,wScI^j-RIr#%}ZZd&j-,#O?|c c ")|]m. Y+dXK7,_|O5n Y$dH!VP[!Q[1b!H1߅rR$Eciy9@ci>P$ŘGciFP$ŘGciNP$EQ:ʫKo@yC!b,UW9 W9F*BȫK@yc(b,U0]f9ac rg,v@ Yf1C>+f1C>+f1~c~?ac?!rg,vBO ac?!bl'Y0!f1'Acy0WPX^,(b,of9zKacM(r,қP-Y70![ KoBacM(b, Y70&f1 b0hP-YU,Xo)b,/f1 Y},Br0f1,RX[ KKaco)b,-Y0![KKaCf1,ָ@[aC>Hf1,| bl Y AA05.f1,ָ@[aci\(b,*BȫpJycN)b,)Ue8%ʫpJyCl(b,)UqDycW9OycW1OC b,8ERHtI1n")ҍS$XJ ")xR^XZXʫK 0߼?ENYd|FGLY>\>c)˧gw3]dFM3깞Q%.ϨzF~[ <^K[gi3]Q%m3겞Qz,YnwQ^dyFBYC| 3]% Y . Yngt󌮞gt1b re.ADXH92H ]F,+ r Ҡ4H+`iP2b J4(p fAXD8 ,`c f41)@p  S0`i#83X N VS0ࠋ/ .`02. .xAAZ8`eF>tE -|02خH Ġ`"12خH +.Ġ`"12خH `yࠋ+82X,8bzAhA~p!]Xo92Xret1~~pň.12X .`yࠋ-]ˋ]Xo92X^58bzAAAAAt1rŠ`o92X[ .`o92X[ .堋-]KA#[ ,7, fY[oY֛`!fY|V02z̲`e&e1Y,`M02z̲ ,7,`M02Xz*e`192XFL *e`19bĖ*e上7:W,e*F,W,e*s\UKOq#`W,=5UKOqSs\e.,K,`R92XԚe/w+zY>|Ҕ#'^,tea_Kg],7lcYK,wkܬr>YdQ>m~[rz4Yn # Zd=LDrk&˯Fk7#Y~2m-]ncMot&ZdR;Mt&oDc9 J!c~#:"J!c}=BJ!c}=b'WrCc~;1cP|ƘC,;1͘C,=1͘C,?~f5ҎPFٚC>H15| [c,} ekAXzKwBcO([c, ek_.ct xcloҁ]:1K72QƘ|V xc̋C>+1ń]17vBFc\!xcl+or]17vB{  o񉄂7HBC1ބ7қPFC1ބ7Xo)xc, oRXz KoBcM(xc, o7BC17Xo)xc,/)9zKcyMPX^T(xc,-o9z co)xc,-o17RX[ KKC17\o!>clgu13Bc0 >s_c,g32(R|XEˠHc)>c,"geP!6.1A3 qbqK!`1Θ3A|X:cKgLc)>#4l49k5҈R嚭_nD.\L #˥D+Zdr*,Y.!k鋓"mr&=,/M?Ynd[B9O1r۷>Yndo-fZd=Id\KWrd”r-]|[eB9|SEIY~@1 bP1_ۇXD)c׶1_ۇXH)c׶1_B!jИ'C,+1+ ny3 ny3+ n9Q:!wsgr7vPKAo=<ך㔋+(\7b treAbeqF,)rE -XV82H+ \iψՅS.4 g A# ,F>d,Y[petd1~A `082Xz  .,ʽArsp!Y|u`e]dlWYՁAvu`e]dQ!Y˨AAz~# C`?12O ,12O , `?12O ҃`y rep[lpl,|ܶbocYmž,5rL{bGc/@q'ly_'Bdo4a/gw嘆->KYl gilwYhl1"dEX/bbcXH!;)sLc1~K 4i1~ 4dXY '8"Vi,l1Nfb!4KW1_c/bo1]@L b0 Xz i,.W6 xq@Lc]9|ub:rLc]9خXlWGi,#4i18d"Xؿg%4cLcݟ9XlgisLcݟ9Xlgi,34cesq@LC11_ći,i"[i,b714~-4Ko1_z 1қ@LBLc&X, 4Ko11 11_z 11_z 11_z 1&1*1BLc0+-4K 1_zc/r1BL昆14K 1BKyv|t,[Y>kC+gVZ:=|`eoXKGGYn ,w 0r,w ,r,w (Ydy<_Kӹ,FCP0(0 )0Cc^bI1/Xyre Ƽ`9Bcy:BcyBᐿx K@C!`,e} 4A8Ƴci"(`,me_b \ A0ˁ2B c `ldv A02< !`! tzg2ƜA0+2vEBخH !`lW$d튄 ]A0+2vEBX^1(p}8e%2Acy͠ ![ KoBcM( ![ KoBCA0ބ2Xo)`, e7 @bc)5!6RCbc)5!6RCbc)5!6Q62JӆXFibkGbcy3}+h>r-yFUY.$?gTFQ~ՐgTBp(]6gtner<{]g4>iP+3(( ?g4rxFC3(3'3f?Y~ 7h{Fs 'n'g4=Og4=ixcm AjXDyc=H- `F,lZ6b 5C\J[/~X@x)=HC\Jť`y)m҃ॴ^J6o<,K`)Ӽw,qlJ{Vq<*5[ƽ`Ըwl΃4,?Ľ Fq\- WFxlc;f!K;`#5Ǜrxy;X/orM`9,7e8M`Ny;XSYM mrpʛ2&w S0Xr!BZcJ!˅b-<0&˳Z.|ͶJ,k|w-YdJm-Ydyk-YdyZKD1XԵ,\>r~|\r}Cre!~5cOZc95cOZc95cOZckiYk,c--kee!Y5e52ec}QP'Ԙ(5q-1rAp-u$<'Z*K|ej,_|w-#YFe^ki-"YdN+i-!Ydy[KEHG1򠷖 ,y<򐷖,x<᭥O;Ydy[Klyeyn 'lyey[ [^Ydy[K Ydy-!VPscwEscwsc'E1w&ܙsgrŁ~nX#h+]\Ӵ®?0]MCiW+*5cѮXjѮXJj=Zc}5Zc}5Zc}5VZcjdž]1OҮ֘w<Zc:`W{Wj]]5vvuX&tˌNC59v8ӮXfub]봫5VvBb]=zKZciW{v2ӮXxOZciWk,cS3/u)˕]1܌r{F3'5)]|FW,WgtA>QK3 7hBg4>PK3 h(zg4>P3 H(g4ʰ~f hU3Qc5b F,vqE#RތR8HC\~RK3H-?/?1b =c/?~+ry9X50˱`9ؼ|+L#l\a+vq9N60`;ٸA!0i4~㏍+A- sV4c`4r`lUWj sUM\aWe-0+L#Ρ,(0Xoy9XQ^ayWqiz+2 ӈWe0-0p+2 s ,#*0ː+2 ӈWeT-0˸+L#[^aW`oy9X[^a>-0K+ s,-0~Wi\~Wi\A*߯Ҹ*C>H,C>HlMnQx5,MǿD%/~Լ,ۼ,MoKDx4~67RyRSεTdy,k-˓,k-S:-O-O򨽆òK`&|m&Xz0ZWKFjch]m,=u!XW[?C>6~_>~BXWuC>~Ѻ~lZWK?Dj!uxZWKuxZWKuaкX0h]m,o67 ZWbOMjc^WIjc"i]m,'i]m,'ղ|-'˗Zdn-]pc'Y~aXK ,/u*˷Z*|U,_|z-U@YDe+t-U?Y@es-U>Y:66VfX,ZKEccihul,m)O9Sƽ?eSNC{]\!%Ø,Wgt>]\gtrU|F3z~ cYH3zzFoBIHK3zzFA2xFA-Hc!ɰ~bL=ɰ~bL= YVQ㘀+(4b frL`̇;`yeooWk`ye?Xh^oWqeoWƕ`qe?>j\W4;CC\dW4;Q %dfW4; dĆW4;g %We`xe?X/^~ `7+2ވWe`xeWF,Xoye?Xf2^~e,l+2~g,Xoye?X4^~7b`oye?X[^WC\gi`ixnË,ȇY`ix>X%^fY`ixn|)g!Ye}`y?H2 ~)CM8&c?7Q!€`i9`` F1`0Xn 1``态?j  o1C0jf``> ڇV0C0X8C0jf[ `y `y [; R`v!,gKk `i(C C3Yd9l-]|򥺖1*Zd:T/ӵT$e*t-UHYGe Z|*7Z|)˷ZX%oUk$Kddj-CY~G*Y~ZKP_dj dduJְ~B@_daj 'ddUj 'ddIJ_<"},c!8 Jcn3RLcn3RLg_>03@C<>0s@c9 >0@c9 >B8@؎8@؎y:ނBHu?6y:nS!>0˘Cl5(}`S!v>0uc(}`,#eh􁱌m>8zKc(}pe|![JGc(} ![J$GC>0iXo)}`,eLu>02QXf;Jb>8zKco)}pRX[JKKco)} !,Q/Y!^HKDC>>0f,QX%JKDci(}`,R@C<+>0Y2 RXfAJsXfAJboB!h|`M8 ҍS4_?(`,8EhtM0n B&c)p_YndB^K,_Dz|x 2 |M4Ye[x-PYe ^KS/`Y Ӱ*,_|ջ,_|򵻖*,? Z*5Y~ZKR߾dK_Rw/Y~Z Y~'5i.Y~Z Y~Z Y~wԄr*-eR[C,i0Ԙ[C,i0TY͟rp( a,GBHC4!JC 4!JC)4#JC! q v al v al <bWBi!!y;<bsBic~7YJC,g̳!6)0Y-!eң4![HC˴GiC008QX?JCb4 0BHCb4̀8zKic) q2 RXAJC ,G,lK,~xE mY(x=|-Ͷx5r,T\[mZ[,T[[mJ,TZ[|WgPfmQM#vJ->{->jiv3G,l!ΰ~戅->39bagxvW[]muABb1E"u]/b!bl]LAb*_,s c_,_r X/b9d0/)vrbXl,/)8 ",0b윿X/bŸoX/b8 .bm_,16/(_zee"/L2BBbLX,!/9Xo!XD_"[_,!ePb!XE_,qe`b!Xo!X[_"[_,bo!X[_,X,-D,K@b<X,-D,9bXZX,"偈biy bXZX,"BHQ,/R(D)2AbLtX)2AÀ1(DQ[X,"廅/ҪCi"U/AҪCb0~V"eҪCbX,X71/~Xl8/[1VsbO|F uϨ9Ϩ30ڂg1 2'A4`;qՈAbdU7ؘqՈ=Ai52HN Ҹ:H㪑-Ai2?rdL,3$Ai2GrĈ e4IN y F,3%ATi1b4`-9 bzi2^rĈ e4`29 2XLN A e4`o9 bzirĈ 4-AKird,-g:|01Xt ac4.0AL`i\81Xt ƅ3qL`i\81XNfY~[ Y~[ Y~~-5rK?FC.1(K7 )K~sJc9=9ijJc9=9Jc9=93Kc9=1sKc9=1K!DOB/DOB/DOBĘC(z"1cCX;H=1ƅ'| zb, EOq艱4.=1ƅ'ҸPd$xgSXf$ ˌDc(@bc(@rw6H 1$BFC @b,1H 1Θ$Ac)@rȧ $SX:c !@rȧ,d(@b,1H3.9o%EC ]bl%V!]bl%EcԐ.1J cԐ.1,JbSHcNKSHci )]b,M!K)]b,M!K_9ү)?,k駔_RHY(˿,p .IYne_K ,[mrz-YndZK$]d͒.k-òcr%Zej-݌\ro5It+rc%},UkFJ{*Y~l\ IY~i\ I1H+OH,0a,?/a,-OH,?+a,)a,ak)˿Z)eRǵ3(?,k'0,k}^[zYRC/,w[l^K[-YR5aYndZK,Xbr.GYdZK7,7W[Ae-݊Xr_%mZeJװ~BEװ~Be ,,(ˏkX?!"/kX?!"χz,t(/kX?!"φkX?!"#,OkiBNj1 b01XD)b1XH)",ǔ,xP)b,G,rX)b,Ǖ,Bˉ0!Y ˩0[ ɥ0] !rȇ,vx!bl,vx!bl,6pYf1a,2NR" XfJ TIac+)"0f1,2^RXL ˈIac2)r,2hRGM ˰IaCf1,2rREaCf1,Xo)b,'YRXO JacA)b,S(Y0f9zKaco)r,R-Y0f1,R^XʫqW9yci?(b,UW1R'2PXFJHBcNHBC")u"ԉ$:1R'P&NKԉR'ҥR_(ub,]*NKԉt:1.R'BHԉt:9#cR?˵Lc)b,2ERI9 ")V!bl5")V!b,NI1cI1cI91")ƒdH!}I1")Q$X>\~F?,~F,W~F?3e'~F3+?a\2m1:gr?gԦ=.Mgԣ=M;ø3ϞQ{&33jΞQoZ3Y8Qc2Y5QWø,ߘϨ#{F 3d|F3jƞы 'Us 'U~ *P*=ʰ~b\ʰ~b\=>AO`0 |>?KA !$R?0H0{%'P.H0 cyO]`0  v@.H0bK cYnS[J0{%'P]bCt,k+@  ,k__|YO?Ywt,"#ZidN;r&Z ˽,nkiM6Ynҥ*M,lkFM1H7T5YndW[K7,wjܨ3OH7OH7AA߇ְ~BAdmh 'dah 'dUHְ~BA_dAh 'd5h 'dy4d- & I%G薒 01ѫN#RIWX6OT7˼}P7{ 냺Xn0 uXn0 uؾP7Con0ܦ[=Con0 ߆u3o@~_3FWmX7 a`> ` ><3Ӈ60}l3Ӈ60}l3ӇAz0CLӇrK{> *`rӇrcaY9},VN˽Ӈrsa]9}0a_9}0 ӇrӇrad9}x-:-J-Z`r0X> Ӈr0X[N8o9},-F> #[N~`o9},-e|W~-ߕӾ+]ʧ|W,/WF\q +#c8b1X_8C 5>ġ`ra-wˡj }C #Cj }CqC #A 5>ġ ePc|8,_5ׁCjׇ`yPc}0l 5``1>j F9,Nϡq5F9,j}B15dg~#Z /@eo_e~-ՏA!k,yZ,wޭN;Yu B Y^dy[KYdyn-}Teyn-}Qeymn B5UN79Y^җT8YdQk 'B15d5k '%/Yk8?!Ԑg5j,?aPC߯dj 'vB Yd-]Ld^"ג1 5qRaגCjĘ%8H)0kB c9jPX8(0!@! 5ePqB cj8PX2(Bq3B c jLPf6 0槊C\(Ba,wT 5J!Yjsa,WU 5J\W)Ba,7V 5JZ)0{+rsPXj⼥PXj B cRqB cRa,7Y 5j⼥PXj⼥PXj⼥PXjŖB cRa,-ƲRa,-8o)0BCj~K![ 5ePX[ 5ePXG*cP!>:Pq§}t>)?eg<ƲSSa,;5ƲSSa,;58)1c9q8X!x8X!Qb,;!ƲQ"8'!ƲQrc^?M(GsE刱|1#B(G 刱Pۧct@9bl(G刱TcyrTs #7 O{[KcP)KZr),/k#.,ok .˻,cP,VVJY^)eUo '*J1(Ud9o '*'Oyk8?Tw5P#,REdn '*|Z ,_d&.B|k*8AT1k!Q*UdנCT*J dXfe,2(c9@LXqFPb,S2CˤXfe,2-(c1yA2Cd,60 c1\^)c1+e,rXF1g,rXn]2!d,rX.˕2cRb,ZXbK![XrK!^o)c1 .e,8o)c1K.e,rͥE![XK![XK![XKz)c12co)c12co)c9yK췔⼥X[XqRb,-e,ƲRb,-e,Ʋ[>Wq?>`sE!Acl+`c\AsȟO\k6k2(1:Ɯۿ{Asrc;Pc,wu[F^uRsrc9ݞrc9\XvMueפ\G!Oueפ\':Ʋk~_59-<ͦ˛J l.J!N enP t!c@XBBeP tC!c# @XF B2L(B t!c&4@ئ B6M 2im)2-Br@74 92K.Brͥ@X. !2.Brۥ@Xˍ!cR d,^ qR d,7_ K~):yK܀)2;0BBqR d,a qR d,a qR d!cS d,-BƲR d,-BƲR t!co):yK⼥@X[ e@X[ e|˨2oC-zl2oCg }ˠ:oC-oE6 -z !c3̠B=d, bA!~(:IO @@'Br>)2]!!B|!2]C>ˮICB d,l w IQ tȿ[M!cy@>[k!ct@ dltIQ tw$ M#Eg_3A?39 gS_3!?߱,ѯoX~+?oxxex>TY?3}>Vwg>VoxhK3iJ6ZY^ >YY 2voxHg>5Vg>Vgx~b<^J gV 3z$}Fo2=RO3zx>QO KgtzF+Y\=3Z}CF ʈCr W%#`4X,=`i}1X2 K+, K+i_mR%!FRmRc$I1l2m#I kGRđ92LHjb$5XfGR_#282LHjLH!FRF>I ͘#)#Af̑OY?2 ~pAe5Ty *#,k\P 5.w `A5X]!T``Ae T%>KTy *#^,kTPNW]k.?vYO}-e>u,ү\_K?qY\k-˿nYqo{-ǠGcY-˲,ߕe,[ZZey'x--cPW>,Z!2,˻,kiiEX൴1,KUk8?X5PW+˻OdIx 'UcPW#Od-Xp~B]%k8?G`Y~^ u,?Od*Yzk-]d%׮1qR]e׮CTWJu!ReJ "J^,XW2(2D!$Je*Qzus+cL^lXW2(2 E镱(J^؆W6 2!镱 )HmHAze,WfJL镱\):y 1WrwXnϔ^+!WrX.є^5+cHSze,WiJ2M![JBM!^)2K5W8o)25WrJ![J~M![JM![JM镱췔^~K镱췔^~K镱췔^⼥X[JqRze,-W8o)2+co)2+!Uu|訮:?xCGu*cA]uPWۇCA]el:Cu_k>tڇ_k_} 13/$fTsEfl !(TdBȌFG";ĿO ŌeQ(vB1co b2(;F7 ŌeQ(&POb2(;S !3eB1cY(3eB1cy PL!!3@ ŌPŌPXPL}: 3ObPX: yPX);)bC1[,mnu[_-e9şYg'np[,mm?n[m,b>ul/go~[,,ŶJ|Ylqu,\mq]Wᳰ4"l{Ylq %XC3939w3939P p~P_m gl gl_p~Pm glu3bxśYx]2~'(b8D![,k(b?BŲB(8L_E 2 1[,S 2 1[, 2 1Af-yDl4H~$feAbX&$feAbX$fƜ -6rb[Nxˉbo91[,mHuryl1&f bwCbXnސsbX.ߐ-7$fbCbX.ᐘ-k8$f?r2bCb8o!1[,WrH˥3cN~-$ff⼅l!1A-ŲBbX[H~ bo!1[,-$f?ŲBb8o!1[,-$f?ŲBbX[H~ 1'f?91[,:H~sbX>tsb>t91AωbCˉb̘]Nۇ.'f?-ݿ>t\[l\-].ۇ.kBۿl\?[,=uĿHx̘2 1A|7l7H~$feAbX$fƜ 91[, 䃔2 13l,K-e Ų,AbX!13Gb+nrbؚ-&'fi_sbؾ91[l_ rbX H~91[, ^N!1[,zg+Y> |d( Aρ,t dA~&G`-Y>_K?Y_k/˿|Y~- ?!?oY~XKo$ / dy_uy--c,˻,k!@eYޓeyM^K ,/ɲ#L1p~B~&˱,k8?!?X5 'gc} 'g-ˏk8?!?5s,fLe%{ 'g|3[ ,_dV.e|'+g8A)?3+!Qόe )gƲR~vן2ݨM;Fm4cqԦː6Xi2M;QGm ;jqQf,ڴCyԦУ6Xi2M3GmڴC}Ц6fi6M3m>hӌ&NmԦmڴCЦsf,WrjӌRNm\˩MBf,7sjӌnNmΩM39irC6XԦ⼥6XԦM4cSv4cSf,7vjӄЦ⼥6XԦ⼥6XԦ⼥6X[jӌe6X[jӌe6X[jӌe6-iƲRv4coM;yKmԦ~KmԦ kᚱ|)\;׌+H5c Bv+WµC Bfl_A׌+µC Bfl_A+ᚱ}!\; kpؾWµAόFG(?3ggK )τːF(?3!E!)όeHQ~f,C3!g'@~f,CC>HːҧlR&EᚱlR&EᚱR&p퐏kRHᚱ:[ᚱ:kӾ+ !\3 k]p퐿+KC!!\3B Jᚱr}IyFgtLdT.m?.m@.͈s2 x3,mLC.ތ8x,2x,S2x{ś#om0b6#om0b6#om0b6X\ :oś-oT :o`srmm\ܹx,Ww.坋r}m\x3m\x35r͈󖋷rm\x{ś-oNś-o^ś-oem\ r6X[.~ś-oe͈󖋷rfy`ox,-oe!o+` r6X\ oF[m}x3 o+śX o+C,ތm}x3W_A,Wm}xWb/#Oˈ{ ɱ'^|r5X'^12c5X'^F{ˈcDpe〱`Y"82qk#|D 2,t:dpXKGCO, Y>kXC!gb-1d@yK/˲|W^KWeY)EYki[,/kiK7pY^XoY޾ey^Kˆ,޲yK1p~B%+,ok8?!u[5{Ux '^c{5x '^,k8?!W5{,Kew '^|k[ ,_dƶ.l|_^8A)2b/cB)2=b/cD)2]b/23H%!NF*PpX#`2 3I%!I*eLR vJ0cTⰤX%`203I% M*PԄئ&`653 %MM(mjB f,wx*O%;y %1`rXT˅J0!`rXnT˽J0cS f,w{*vO%![*O%!3[>`8o3>`rקL%![*O%![*O%![*eX[*eX[*eX[*qR f,-`8o3JCT~K%T~K%J0c R f,_A*+H%|;(+%!@ fl_A(+%}3 `B(+%}; `쐿PWJ0c B fl_A(;I%O*UJ0c9TX'`r>B v%O*3I%!ϯ+21c0(;lYLX^(;/[/[60-LLQ&f,/hⷌ21ca(;odbF!(34ľ!HZ:E|d ZK'H,Y>>kLZ:9|pdܬc#˧F,tdd󲖎$d|X@B&˷lYd;,_e-쵴ZAB&˫,okb-{,EDwvY^p~BB&$dk8?!!]]W5.kOHd1Hd2Y~B5OHdXp~BB&Ʋl2YѭLs|[K9YUnCJ lJ l.J lqJ!TόeR|f,C3c`XF+g2\)>;J XqR|f,CCˠXF-g2l)>3qKCۼ-g6o!>3y [όmB|f,όCs|f,Cg@3cy X(>3όM3cyX(>;yK񙱼 P|vg8o)>37ό啀3!g8o)>3qR|f,-g8o)>33co)>33co)>33co)>;yK⼥X[qR|f,-gƲR|f,-g¿+H!@|f,_Ao3c R|&ؾ g쐿W3c B|&쐿WC B|fl_A+}!>3 gl2!er/;ċ?er/;#H}AˌR_&2c9ԗC_f,GC<ԗX6  A|f,g| >34 A|fl g@|fl g@|fLg >B|f,/h g-X:[񙱼Q|v7:όs3:F|!zFg!Y>A=󌎏,gtx gttd<΍,gtjѡyFgF3:1<"0>{FEggt~FlYc?+3a? ,$znײ|ghFk,_Rvg"gp~b|oLg?=^g?^gp~b|m= 'g  p~b|e8?1>{FoXgne8?1>{F7:OϞud2r*mqr|6XvP`C9>,(gell y`qr|2V9>,2Z9>,Õ3#Wˀ̈#2d9>3l Z˨l [˸!gF y` y` y` ?g3#[)>, Sg1>, ˋgM*`ÿ6_8>,qr|6X8>,=̈T-gër|6X[~`o9>,-gër|fy`o9>3l r_6X>tܗ eC}`q_f?xۇ2#/l:ˌþl}/l:b_feC}?tؗ eFa_6>tؗ eC}JB6XN'dFsB6XN'dF/k鸌AB&ˇe $d|{ZF-Z/Ѳ|^K;,ߠe1Hdy~-ݝey^WB/OHdyl '$d2Y^ey_ ,/k8?!!Lk8?!!`Y~^ ,?L_ex '$d+ˏk8?!!OHd:'˷t廜,_(!; J 젔J 졔&J 좔6Oԗ˰X-e8p/B_f,32cԗܥX&/e8{/3K}!_ˌeS_v32cԗX&1e2/B_v2cЗ0؆1e6/3a } cˌq2cy-eܗeJ@}P_&X /3ˌ幀2cy0X /3GqR_f,ԗex@}![ˌ2cyBL}![ˌCԗ~K}![ˌeX[ˌeX[ˌeX[qR_f,-e8o/3Cԗ~K}ԗ~K}|/3e򡣾X>tԗtЗۇAˌQ_vwˌQ_v2c9eԗ)L}!>erʨ/;؇XNexʨ/3SOًCGelT⇎4c0L;#eQvG4cKjL34cjL34cMkZ[e4cyA2X^ШL;#eD6T4cyA2otT i~P1ZKH,!Y>Bk#g-Y>0|^q2M(d .7t,_evY{{--$cP@/k-Y e`--"|O(d0eO(d 75P/O(dy_ ei|^ e,?! O(dx 'iv,Ok8?LwcYԭ2Motk8?L,eNr|2'(iƲRf,[(iƲRf,(iƲRf,?e Sf,CŔ0lX1ek2)[3Lٚ e֌e,Sv5c͔plX3ek8)[3Mٚ i֌eLSf,5!dk3D!=gr(>;XgoAgr(>B|v2όeOXό3cyL!Aόغόόi gBό3cy쐏 gP|v2όCQ|f,`}?د|d[K'L,/Y>^kt%Gk-,Y>XcZKJ,tdD󴖎,&Y>L|Q0M#d.t,߾eYz{--+cmA/ k-WY)Ea 'i|KX a,_ L[ a,_dv4Y` 'i|-X ai|^ a,?Odx 'i:,ˏk8?!LaY0Mo{k8?!L嫞,EOy|0'(iƲRf,[(iƲRf,(iƲRf, ,Tk2Z31M՚ jqTS&jX5Uk2Z3M՚lqjSf,sCTj7Uk2Z3 N՚p֌eS&j8Tk6ơZ31՚q֌mCflc5cP˳Uk@![֌Z3-5cy_jX^ZBf, T3Uk@՚<5Pf, TsUk8oZ3'с5cyvj-Uk@՚<>P&j-UkA![֌ej-UkƲRf,-UkƲRf,-UkƲRf,-Uk8oZ3CT~K![֌ejX[քi0 L3iBӌsa! L3i0>W 4!i0>W 4c\Avȟ+ӌsa} L3d򋧂X~T/ Cu(ȌO!;d򋧂 2cSAvx*ȌO CPAf,l*ȌMIQAf,oRT ;#-P[%.P[f.sLIQAf,oRTX*DIQAvw$*ȌM $d=#&'gt3:[hzF۰ {FJO3:TLzF'gtd8=3:K| gtdx {F/,gtO~FgtK}ݑYoÂݏXon 3"|d2X=3p~bAf 3p~bAmX=K 'dp~bAke8? {F/V gJ.|2X=۞ 'dnz|{Fgt6.Ȍ8A ,;(de l\ M rA6X_:OܞC؞ 'ges{fĹ`ܞ `ܞ Clόl}=ll۳l}=ll˃gI3#[l=,ܞ ng=,ܞ  ng呂۳L`ÿ۳X+=,ܞqr{6X-=,ܞ=̈۳r{fy`o=3lܞ ۳r{6X[n~`o=3lܞqr{6X[nό8o=,-ge!gFl|=3gsCl 3#=l+lόl}=l+lb{fgs홑?W؞ gF\a{6>W؞ gsy`Qs^fvǼl9/,?jb^f5eGÿ?jˏ̈n7۳lIq{6Xޤ={홑'g-l1؞ 8۳`{6XV`{۳&`y۳p{f;gM3#ޑ=,oRԞ}3Y>c| &KZ:]|dlZK'Kg|ҩC%gj-)Y>Q|d<$˧I,tƠ=僴3Y~ٕZ(=Yɲ|K^K,ߑe1hd~,t;{,_#doCb 'g|l 'g|wOhd ׆5Оa 'gcО%x 'g`+k8?=5ОK,?ԮL_ie·3YLz|[K=Y5oڳCԞJ홱lԞJ홱lԞ.J홱lԞ =3N홱wjόeS{f,#ڳCԞ =39O홱LzjόeS{f,ӞڳCԞħg>g2=;ĹO홱L~jόeS{f,ӟ3cԞ =;g>О3c@{flhό홱bk%k-.Y>\|dh%k 2Y>VkT3,(Y>P|q$ˇIZ:JcPAZs,ex-݅e*,7aY}E| ^Kd|Z=B|X ,_!p~BA&1(p~BA&wY:L |mX ,p~BA6,L]eu 'd了 2Y~o5P[,_p~BA&˷5PUOozk'g2cP^f,c@y|(/;eI? g2c0P^f,ˌ@yC:@^fl_ˌy} /3euؾke^Ay![ˌ9/3G ˌق2cyLy]P^f,eAyaP^f,⼥X^2(/;ķ ˌ5CˋeAyC~Ky![ˌe-eƲR^f,-eƲR^f,-eƲR^f,-e8o)/3C~Ky![ˌeX[*ȌC|t 3d}t ;dс?:PG 2c@A&?:PG C@Afl(}t 3u`X~}ԁCf,>_¡3_u`Ё˯:CQf,><}}Ǖ CPAf,W*ȌJ<QAf,GT ; -P[%.P[f.sL<QAf,GTɆX*2C<QAv*Ȍ ޏ+te[KO,=Y>zks'n-:Y>tcP[K'N,tda島,4Y>h|1L1dyV_g=Yɲ|KKZed,7䵴ȌA]&cY˱,ߍer"w5Pd |-[ek8?.,_Hp~B]&˷YLo"k8?.L^p~B]&˯躆2Y~q] u,?kOd6(˗5PMp 'e| [ZPcTXvPˌe XPˌeXvQˌeX_˒OeMI~E!_˪wٕ~)FH!}Bg,G>`BRwHg;cPRg,JcI!$I!$I!~63'wX>;!wؾ;c~BglO }?3'wC![3ga;eB'mqmqX^y3wqRg,o=kwC![͇;cyN![e-wƲRw;co3;co3;co3C~K![e-wƲRg,-wѡX>:GCC>:G;c@w}tBw!t3wс>: ~}!'_eX~}r';V;cQwȽw}˯;cYyBg,WJ!~W3#;cy,gt{FGOO3:x=c'˧o9Y>q=&gt؞YN3:h16!=>YY'?k3%?K,2nȲ|wznDz|9~Fwgt5~F7cODgt+6d8?{F7gt!FeDgt۰{F2=Wg*3zq=>VOm]e8?{F7AO5e mqr7XvP`C,(wenl }@qgq`Y838o,R~M!o5o|,_dn7Uψenb7X> 37`@sg`Hsg`Psg`Xs7X> 67Clo}lll7o}lll7͟-6 $nc79 }a7!l>`ۇ,oKqr7Xޗ3 7卉?#[n;7奉qr7X[n8o,-7F r7X[n~`o,-7F ?#[n~͟-7e!f}Y`p7X+'f}Y+ f}F`7ؾ+ f}13w]w>#W0,ߕrg~} wA @#n9,[ pn1,eZp|,eZp<;q-hg'˳ׂF>X \ k,a-8ؒ%[`͖ZC˳ׂىkA#{KĵA\ g'x Zp|^l< ϟ-plٳţwN-<[ wn[r/g8?s-h3+,ׂg8?s-h[̵-^Ulr3ׂxM9kAYmr3ׂ^kϵg8?s-hog8?s-hN{3ׂx\ M gmhp ;-^eP NP bB\,{(ԂeZpP .mjŲU+H z)bY %\,+eɂpY.Ei=Q6eBw Ų@˅bYP\,eBq,P(. Ų@|sX(}.rυbYP\,+eIBq P(?mO?xOȅbr\(.=!mOȅbr\(.=! y X(.+( Ec.ۚ ŶfBqYP\lkV.ۚ ŶfBqBX޴PA|ՂBqkA8oP\,o[P(.-(PAP(. y boPAP(. ŲBX[(~ boP\,-? ŲB8oP\,-? Ų߾{Bq|WP\,(w ʧ}Wrؾ+P\lߕ\(.J.w%?ߕ\(.J.+P\lߕ\( Wrؾ+PA|.[*DeKql!.i D biBhr#ӄbiBbYy B\,+Deq|y!B\,_^H!.%_ B\,/K! 7P9B\lT[#VBqP9B\5TˡrhbyYq,A|sX(o:!.%!.o6E2Dk㷖N,>Y>{|ɓ'NZ:u| B#N,8Y>oki&gm-5Y>i|dc6,5 w|ҩC7,tdy[KMO,6Y>kkI&l-1O4逆?pۧNct@)?pۧCt@9,_"J!F 5uQcY'5uQC>DQQTz3RcygDGQ!Jjغ6Jl6JnkyDBJ彏RcyDҹQTzRc[ *=5RcY8*|F?Y>}=,gtѹ{FNO3:tgtd=Λ,gtڞa{FgM3:i=s&?cT F"1|yFgtyF/"<3"1*}FWgt嗐gtyFךgtĨp~bT.;ROJEsd8?1*}FgtǑ}gtĨ?cT.72>gN.Q3z$Ĩ?rOJm]e8?1*}F7AOJ5e 9*5t-rT:X6QJ.Q`F9*,(GF݋}qT:X/JQ`8*,[GF#RC,N|8,F>X킋S8,etl\=ipq:Xv .N<08,FXS# ,N`<8,e!F^?8lǧXS#[,Nũ-8lAS#[,N8,b\w1.NۂC,Nۂ`[а8l mAt-hX S#[.NSF|,tԈrqjy`o85~Jo85!et\rqjy`o85nt|,FnF>nt}5nt}}ݨ?؍vr_z=_eԈrq:Xeqq:Xepq:XF 8,S#8,S#-XQ`&\9ctL.N`q:XI.Nt\uNrq:XIQc F@Q sEu<rsT# Q[9`+0GlM樃uvq-!樃1s9 樃sajsQ: G]KPϟ,tdٓ壷N,w|ҩC79,tdy[KMO,6Y>kkI&l-1QeUo9|YKwY GZ.#wYEf rTYg-]e#wYU;k8?!Gk8?!G[,_p~B*7 YUo?k8?!GUo>k8?!GWtY~D_ 9,Ue| '䨲|OQe&rTY-p-]e(W1QqRj,;(ƲRj,{(ƲRj,(ƲRj,(娇89(G5݋rTcپ(G5rTc(G5rTc(G=9B9lqX6 Q8@j,娇X6 QeǠX QeϠX6 QeנƲoPzrTc9(G=9A9A9rC^? G5֏O[? G5rTc[? G5rTc[? G5rTcy-Ɯ˫.F9-h !G5 rTc[ G5 rTc[ G5 rTc[ G=yK9Y>||d譥'Oϝ,tdЍA*Gn-8Y>p|q&ˇMZ:j|d9[Kl rTY>dkx G廊,_UME/* #˯0ki,n"39,_mdf.Dz|k,jp~B*W5Mh r5-H/Ak8?!G,_p~B*˷5A*75+,?U_p~B*\Uo|\ 9,p~B*@YK,e 8F9!NPQeXPQeX6QQeXQQeTũWT˂EũXT˒EũYTˢE! *NeqP@!85Cqj,KƲFPqj,ƲJPqj,ƲNPqzScY)8=ũTXV *NeX *NeT!oPۆũma@qzSc08=y ũSc0857/*NyBqjũ<|Qqj,O_TB(NmA4(NmA4(NmA4(NqRqj,aT{"F![*NUSco8BqzSco8=yKũT⼥X[*NeX[*NeX[*Ne-BJ,D2)*=1NQqJqSTj,cR!D6!*=1QqJyCTjlcRc !*=1QʥEX.mT⯏ScQqz>*NeG*285Gũ>*NeQqj,C Aqj,CSqj,C[85 FQ!(HQ!)HQV *5Rc)*5RcRct@TjlOt|ڧRct@TzRcy=DVATjl]DVATjlmDZ R!DGQQTzRc(*=iQ-KDQ,K~bT*gtd=3:z|{F;Y>u}F{F7Y>n=Κ,gtҞA{FLٷaT F:n#|yFwg ^adyyF7gtE0*}Fgty3<3p~bTn-2>GoèTgt zF ] ]d8?1*}FOJ gtĨ]{; 'F\gT<Dgt|FAOJMPgt |F@Y>;3~GFrT:XPJ&Q`E9*,(Ge!Fet,XdqT:X,JˢQGůSpq:X .N|8,F>X킋SV8,etl\=ipq:Xv .Nnr/_qT:Xe{GFirT:XeQ`R9*5t FJ`t FJntL0Fb7:X&wFs7:X&wFW}`yslo\q9X7?qq9X7?i``:>iO6aP#lLC[i`0 l}P4t6j-R4!a0iG V4ȣ`jĕP еte[KO,=Y>zks'n-:Y>tc[K'N,tda島,4Y>h|14T1HCeR!wtY~i凖%E(ki4T/(|?YKXYD&k8?! 姕5k8?! +,ߐp~~HG|;Z i,_p~B:i,_p~B*w"Y4Tk5r!˥OHCe6(˗5Mp '| [ZPc4XvPJCe 4XPJCe4XvQJCe4XQJCzEi,XˊEi,Y˚Ei,Z⨠4X JCq4X6 JC8@j,[4X6 JCeǠ4X JCeϠ4X6 JCeנ4 ƲoPzPc9( =iiAiAiC^? 5Pc[?>mHCm4-BHCm4X( =y i1*FiQj,/c ! 5 Pc 5 Pc 5 Pc =yKi~k'Go-x|dحS'ˇn 2MY>rk󶖎,6Y>l|Q&MZ:fci![3,/߯^LdDK.#ˏ%|XKd|͐[ZQC|X ,?LS_G \ ,_d2MYh 'd|5Z d|-Z ,߉dJ2MY.'p~B)s:2MY ep 'd|\ ,_e.|+e8A)42McB)4=2McD)4]2McF)4JLc٠4JLc٢4=JLc٤4]JCTb@%JCCi,X*1?%,TbA%,Tb*A%,Tb:A%!O(1e ƲVPyJLcY-4JLcY/4JL!a@ilƶa@ilƧma@ilƶa@i,/^Tb˛Bᣱ .>B!.> !|4Gc\(|44-HcR< UmPE*X< UeYPE[UYPE[UYς*RUUZTE>UMPE>DU1O_ZZcdy&K,dymҒ啵,1eyUE%kJZZQdy=rZKI,%Y^Jki%A(+GYeyL)}-eeC6d]c-+!˗4A(7 YH,_#d!˗5?!|嗌5?!|g1pQH|CZGYh Oej'c>h OeN$W5?!|Pa OeMpQ/||[GY ,dy|͓[Rh,3(2Rh,s(2Rh,(2Rh,2AQh,32EQh,s2IQh,T2TP)*T2YPyHc.<Ÿ Hc04Hc249Hc44YCj4yCj4Cj4Hc<4كHc>ByT6~@ilT6~@ilW?<H!TFU O0LʄLS& e :\堣:\堣:\堣UtPAtPAt_:\=!/cM}!.cM}!.c>Xc_Bk, c[}~K Xc٤(=J`eVũ TPH!T 85Sc 85GO*NP&ũmRPr6I}@*N1C85Sc+85&Sc85.qP 85QScy !(N!(N̆!*Ntf853ZazF.Y^\hm=V,/g~ gdyQ=5,gzzFIW3ZLh-=$+ǰ8}Vh}F3{e^^#3zcq0<YU~ g4?]/ShjFC3ebq^dbq~ SX>wgl.gt=zF#_t7zFW#XZ$gt'zFW"X>)X>g0%gt{F=X>˞ O,NM]dyc\qt̠\)2rq:X&Q.N,`F8}Q`8*,cGePtJa2.qTQ#؍ـQ#؍Q#؍Q*؍92)p7:XfF˴`,wFM,SwFM,wFM,we~ntL܍ч؍ynt ؍!6D`7:؆6D`7jч؍G-F˳wFontmq7:X^,[܍>ntMo؍ 6a7:ئ7F`ް5~`ynԈO^܍G/Fr7:X[F|CFr7:X[Fr7:X[Fr7:X[F|`o}i'e,C^e,ǟ2=`r,WeuC\y+2q:X桇>W!\˱̕e\˱̕e\˱̕C\۱=VX+v,c+v,k{+oǿg \#7 nrx,oqr;Xlnr˙M`99,2nbv;nCg8}H\˕`ar,We{ulo\'`;L`'`;'(e!&F0l&-vEzLR؇92skM qkM v~bkMr~ߟصey[KO,=Y^zki“u'n-:Y^tc[K+N,dyb嵶,4Y^h2>V1ceyBtǑ Y~׉4ۄ,?MAf XYey4_K<,?I },G },?FA'kB+6 5?J/UkB;},_p>VoS|ZXY~(ZXY~%G5?۠,_p>VokB+@YK,e 8F}! J}LJ}L,J}L 5!Xc5AXc5aXc~C!5C!5C!5/ 5!Yc#(5AYc%(5aYc'(=Yc)(=Yc+(=Yc-(5Yc/(5Y!ijW 5w vq`XM(5w v݄A v݄C\˜@ ˜@٭[cQvk,ųƲQ<+XQJ`qàV lˆA lˆl>ؖ 5%}!_eT>V}!y[}%z[}ezkJ=c˨N}}${}<]R{;rQ?صey[KO,=Y^zki“u'n-:Y^tc[K+N,dyb嵶,4Y^h2>V1ce-AҕBdA,#ˏ1cey{-=,??A'O/kB+'|Z1ce'|Ւ5k OceQFdp>Vo|\XY },_e.|+Rk,3(2Rk,s(2Rk,(2R+>X$ceL>X%ceT>X%ce\>V}L @}C⡏5C⡏5/ɠ5!Xc#5AXc%5aXc'=Xc)=Xc+=Xc-5Xc/5X!è51cq>X[ce>V}!|K}!|K}!|K}̷|K !/AH`e $2P{KXcy(5Xcy(5Xcy(5Xcy(5C^P˱LT˱LTPPP۱v|CYc;t 5CYcyTxXU(5GgqȧxXU(=݄YcyTxwge xX& ge 4BHCe9Pj,ˁPcYr4*Fnؾ>Fnؾ>FIQco=l Qc נ5t Qcנ5| Qc ZݨQco5Cޠ5Cޠ5'=Fq{nX}kѳmq; -=[\zga³ug,:[\t܍; +-lqbŵv-4[\h2n܍/gaū-mb~f[, 2܍ogBnq[m ܍U ܍,wgnme ܍⳸-Q[/c܍U ܍=agn`gn#l9 ܍m/gnognx < @[P/ bA],S(tentLЍ.Y2B7ji/B4tB".fHC8i/₆4ԘrCXN?EnsXF?\.1_LP"PsX?@b \,CԟȻI?`/n2@s P.2$@X?Er\.9!ןmNbr\.9 EosX\,WP.+?ԟ Oc?6sMo\l[?6qsiAbyׂqs̷P.Oc?[?| /~ boEo\,-ԟes̷P"/\._%2@sXF?by\,#ԟes}Oه5nt,AFnt,AFs}\lm?\.6ן__?| /r|Ŗsh\l Z?[Ś-ן\.2B8'@X4?7\.'=?7)?˓ן?a) gdy=3Zz{F-;Y^uh֟h{F 7Y^nh=֚,/gҞB{FL-21?ѣ3z39]ѝ]eyyFgtAǰ|FC3e*&g4@?Y'֟/ggg!g!Ggt3M=˔ O?c O?K3zȐ3 >ˠ O?MP'֟n| |Fwgt1?r9XfP?`C,(ןesL\>[Cːi`8 ,eT4t Kq2p:XFNCbj2pj2#pj qP4!eV4tL y21pj25pj29pj2=p:XNCi`!8 }iLCi`"0 lCm4t ! y4tkq:X^8 ,o[-NC1 lmz4tMo 6a:ئ7LCr:X8 5ыP#2rP#P#P#2rO#2?TW֟eȫ 2p9X?T`j,S ןesL5\O#rDr9XHO5?]}XQciQci2ria94?[`аZа|`o,-ןF",AןF",v\qsQԟki巖V,/>Y^{ʓ'NZZuƠ%V,/8Y^okij&km--5Y^idye6,/5\cP,?!]e/˓Zedynu- 2cP*#Z*,kB)˳P ԟkB)˯߲'ԟ!kB)ˏkB9_H!8>Lk"m9@y_Tƶ4U-"e(*RU! ߭ʂ*"̂*,"ΪyV볠Bi,C!U2RyUjQyUEU!TEk>5&KLWZZ`dyyZKKז,/-Y^YkiaQWZZTdyI% Jד,/dy1Z奴V |7aY~4{,k>S, ,? ,>O{kB(˗5?!|回,_=Oy|wP eXP eX&Q eXQjeX&!jeX!jeQ/OC4!_4SC4!_4aO!/ !_4Ec9)_4SEc9)_< Ec9)_< Ec9)_< Ec(_4)Ec(_4IE!䋇< @hl6 @hl6 @hl6 @h,OS/勇BhPQh,oT/+Bm@|4m@|4m@|X(_# 2r7XP$Y`E9,(3bgąY`83boCqAs7XwYCib7XNyib7XNzÞ>#=Ĭo 3rs7X}a`7X~a`7Xa`7XfY`8,g}13(Y`0lf}mo Q6 `7X8,SyŬoBY`yoRq6a74ۀY`0lf}Ɋ># g+pY`yψ-g}eo̷=Ĭψ-g}eψ-g}eψ-g}eo̷\ ˽2ap=#X ˽2ap7X& .˄`0,{eroL\rw[٘ Y`[٘ωYC͕rso\9,7W8Iq7Xnqo\93$Y`r7Xn=ro̚\ Y˽2krg!,ˬ\ Y=#&X Y˽2kr7{FLl ˽,{e@r!{FLlEwиlQ{FΒaR-ZC,ˀ`и3`i3`yrϘ7Z@V,/Y^'ki*E"kd--Y^!@dy}!˫c =Y^kiiʐ共օ,/ Y^(Қ%!+B(dAt-M*˯SYOey:t- ,k[?u-߶,k˖[Vk ?,?k)^5eyΔ1s-MhmA gl Z8c[eZ8!prXn-Z8cER wS prjI-!N5-Z8cER ',$r2NR(g,$r2NR(g,$rB9c');"B9c')mB9c[gOm}B(g,<GBCL 3tB9cG!CkATA('PX> eP! %&P! )h'-_,k{YfYҷ,˟,ɲ!X?1hd#^K߰,²X_Y|e]K|ZǠɵ4,)ˣ,OkiB9RHY"t 3,ki4NGYc,<;踆'p<7 -,AA 'p(ϏkB '˯"('p"'pckS, -,? -,JWkB 'w5?動,߫ҵJoU|wPjeXPjeX&QjeXQjePX&! ePX! eTNT ;O*:c9婢;O*:c9驢;TqO*:c933*:c93s*C03*C03*C3*:c39*:cBEw-Tt6 @EglTt6 @EglTt6 @EglTt6 @Eg,ST~]ާ3*半*:cyNoV?g>}>}[O}?3Ne3}F_3He}F3B*Cg ey1 ,ϋh\|F3eyxF3Ѡ(3є(˧a(Fg4!{3xC=P'r03zb|F/2?1{F"QD'rED'r?3z 3z yF/!2?=pP<'=+3ApP]db(N$7gtqzFPΈ;(rePnL 9C2r(7XfQ4ʡ`G,pF\=Ģm\¢m\¢m\¢m\,2mF҄Х*n컭2ҌmAf,HҌI]"K3[$uir.ҌI]!N5ԥ-CjK3[$uir.MQgBE6c~h3ᗊ6c~h3ᗊ6c~h3ᗊCLh3ᗊC|lX_*9X_*ڌe}` 3}ZC3}Z8cۇ3,jeN-!`[-5I[-uIk$h|K-̷-L($,?kG?Yvҧ#_,8ݬF1(dYK,1E,m)ˣ,O~kiMǾ4'3,|k@O=Ya,Þ,zk$M=Y,Oy<򌷆'm< E,?mAѶ'm)˯kB&ˏ-ֲ'mв'mcP#P ,? E, E,?f O(d:#˷5?hP=F1k#˗YÌQv;(m2Rf,S(m2Rf,(m2Rf,(m2R&XD*XE*XF*XG*XH*ڌ吤XI*ڌ堤XJ*ڌ尤K*ڌL*ڌФM*ڌढXN*ڌXO*ڄP~ EP EP EP EPˋmBfE崧XN{崧XN{崧XN{崧XN{񴧊N-$m!}]. !3"rrQPX.EBC\(3"r8P(g,E qpPX.EB9!r2R(wr2R(g,/r2R(g,/r2R(g,/r A(g,/r@ r. KBCF 3*:cRBEgl[*Tt3-*:cR37eN!/茭 *茭**eXqe d~F3ew~F?3я,˿3/~`Y}c=W-r%wgtzF3zQ{3)DJY' Cg4M0fg4J>IROg4G>1M|j>|drh~|F,?^=͎ht3eb(PN'rh`|F2?1{F<}G'rqG'r?3zؑ3zyF:2?1{F/:2?1{Fwgt3wg?^QvdyyFs3{#CϏavFYng4Vg4YU?TѠT]=!U'fWhB}F,ϧh<}FO?ٕwPή `B9,s(gWej̢] i2rvr$rver,rver4rverjG>jG}`'2r}`',$Q2r}`'2r}`9,QlQF^G v:`5N{A$,Oki-ˣ,Oki-c,Oki}=,Ok_გ-Y~ZK3,?kr$ˏZkiDGY@2,kiCgY=Ҷ'˃,>>CPc,<;>Rc,o=k>C!|K̷!9co)9JCX:*q堣X:*q堣X:*q bC<(Blc,7m@(16x"Qlc,7mDXnD(16ϩ9~IJc1IJ!82IQc,82IQc,82IQc,8Bc,8xsX&)*q=X&)*qeG%!'P$E%!gP1JC^P%!/A(q؎(q>ڃFXY_.ӫ, Zڸdyta-Zc SZveyfA'5?!qa OmdyVf OmdyN1a Omd_epFpf bY~CXbY~@5?!ǃ5?!O5?!O'5?!o Omdef-]d_ e (9bcA)1)bcC)1IbcE)1ibcG)Blc,G"6{Blc,"6{Blc,G#6{Blc,#6{Blc,G$6rHRlc,$6rPRlc,G%6rXRls%6r`RlsG&6rhRls&6rpRlc,G'6rxRlc,'6BmyOmOmOmOmEbCo!1Xu(1mib!6CPlc,/<6CPls-6C!Plc,=~K̷|KbCom1sږCsBb, -Yj[\[C^+_m|W[+_m|W[+_m|W[+_m| JrVtj*Z%c@Qd,(jE!*ZC<ЩU2 JxSd,(jE\U2 GIXFXXFXeXFXeXFXe鐿xX r2c*C>r2c*'c9rBtTNDK!P9 !GBdlHV G2r$#?:GZn=;3R<,u>6!_3z1, +}'L<>ǩgt?s]gt?C|G@4F,O(F'3:eyozF3:eyc1,NpYYgtzp2?8zFaq$gtf?#['GTѿppǰ8zF/2?8zF@'G @'G2?8zF3dMv2?8zFgt 3?11.rq4XfP.`C8,(GehL\ yrqTd rqTd rqTd rrTd3r rT4XAIQ`9 9*,!GE<Ȉ'"GELȈ"GE\Ȉ'#GElh 󑣢rBrT"# #vDbT4؎HQ`;"1*lG$FEĨhdn-w|a'gZ: n-s|)'ˇZ:dNt&˧Z: MO4&ǚ,jkB2#Gy6Y&G9z OHf ZkB2#˗5?!,_pdFoӲ|^YI Ɍ,_e.|dwPJfedXPJfedX&QJfedXQJfedXN=Jf'dXN>Jf'dXN?Jf'dXN@Jf dXNAJfdXNBJf,dXNCJf _吿>_吿>_吿>_vEዱܮ(|Bb, W|E\,(_1+r|X.AG\,(_9ăcXPr[ +r|X.łcX|rxm 2 _eXI _eXI _8Iዱ8IዱˁNዱ*Xt _NዱrcዱˁN—CN- |1R _9—mmm˂LGdg-}?|U囊,_Tҷ#YZndg 2Y~Y ?, >RYFe/t-}}B#'Z: ӑcy-ʲ|(,GZ:e@Xta,gZ: ӑX4),ˇ,kB#;++F'd:'d:c, ,? ,,? ,/s,k,Se:Rc,3(e:2Rc,s(e:2Rc,(e:2Rc,!}뿏2{=㿏2}QƯ>r$nU2ZCnU2ZCnU2ZCnU21Z$@!* U2qZ%cU2Z%c U: *h@ *x@ *ˈ@ *˘@ZCoU29Z%cU29Z%cU29Z%cU29Z%cyV[h+-JBd,/X*~ MR*$MR*[JEgQt-JE!jQd,Z* o!~C7|CTIT1C=1CxY> 3gt?]gt?2?1yF OtѡcpL<3:̟3gsB'f:?3z3zxFo2?1yF2?1yFB'f:=TpLRpL=Q< Y=gFR9y`a9,#,>egy9`3XFX|r3XFX|8,#,>eg eze4ȈӠ򏄜qr4 #.^NYi`98 ,gAe4h # #/^Li # Q{AFn00 ,}4hqdӠm -b74ضmKnh0o_nH_Mdd-}d"/&`WY~.Y~,YKߪ,?A7$˃ZeOx-}+˟Zze㕕o4 A7$ˣZdy9@ǀ4 3,ki@tA7$ˇ,kin_~Y>pnH5? 5?^5?^ao OdId OƠ5?Y~ Y!Y~Y!Y~75?Y~X!Y~X!Y~减tugY~nwPꆌenXPꆌenX&QꆌenXQꆌenX&6qϡnX6ꆌennX&7ꆌev oTBX*eH!/$(e&G2Pqt=`M8:ᄊ#!G2Pqd, G2Pqd,S Ga@qd, Ga@qd, G8Pqd, G2Pqd,S G2Pq$[(mp(mpw6;r(Mݾ|bIn@,6z@nQ\;6j"-I\82l#\82l#2J#B`fȰ82l #8Ȱ40 [@Ȱ40 [@Ȱ82,62.zKƑaqt!82,6w Ky{Y&LhdX&LhdXNH#:҅|@GB,d qdX",G%’qdX",G%’qt!?%’qdX",G 82, qdX",G%’qdX",G%’q$^H>l K#]7t$ò{$B٤#9H&ɰt$ґ KG"ɰt$ґ KX"ɰ%ґ K$B٠#I:҅8%ɰ%ґ.dt$2 $ɰ IGB;@G2,@ґ.,G` х\582lU jiUs8S<49,KO <09,I<.<,9,G<*YƑX>ŇC,ϰX>‡,X>bNX>bqtX8r˭^,wR}^,yKM^,xK~Gb~Xb.[aX?8}0`妾 ð~q$XaH,ob0`aX?8ZƑX#< ˣð~q$ aH,A 0`X#<8 'Gby!בX{22. JƑaɠdJƑaɡd$JƑaɢd4JƑardXHbA"ɰD:ґ K#ɰ:ґ K#ɰD;r.+a1* C JWɰr.+aI4*]+aI5*\CaI6*lCaI7*|C҅\MU2,\ dXrJb!Wɰdr K!Wɰr K!WI\ ނd"J-d"J-d"J-dXFp*!JrW0J-dJ-$aKo*aKo*aKo*Jb%WɰUt* ~7kL7k(Pxȏ?ʰ\ u ?ʰ\R Kb$5Ȱ$FR Kb$5Ȱ$FR Kb$5BdX#Ab#5Ȱ$FR. FjaIHjaIHadAυxy1,{@.Kad\Ro1,Ro1,?1, cX?sò!$Bv,1,5 xA.d2^ #>raǰF| [aǰF| [a *Ã0C (.0 (.0@ 0?0><?舋>0:bx=0:bh=ry2Q~aQˍ~aQM~ar2QF],Ga܇QoF] '?èaDg5'CG '?èuOѮlİ~3dbX?y2C '?h1bX?F1h 90saDg8шC '?h!a4F :Fa {2 dP’CYX(? KegaIl,,Yퟅ%ͱ9D:PYX? K C-,ՠ%4 C-,Q C-,q $V 14ՠ%Vj~X 2RjX 2RjX 2RjX ZXA Kb5haC D5Ȑ-A [B5haC-lyՠ-!T 'HEbu"ܷTtOM,/ RX޲%aX?A*ð~T "<8 'HEby!aH,: RXs1aX?A*3<8 'HEbyqOpC,6K <Ke$]"ÒAI*2,)"ÒCI*2,I"ÒEI*2,i"Ò8+G%qt!V+2 K#Ȱ$>2 K#Ȱ>2 K#H qdXG%q$х|y82,9 qdXG}%qt!"282,#Ò82,#Ò8K G%qt!0 KB"B.5`DƑaIdDƑaJd qt![0 [XȰ%0 [XȰ%0 [XȰ%0 #2#B`fȰE;0 [ȰE;082l#82l#82l#2#BdGh#R5IG2,Ut$R5IG2,Ut$R5?K$WB*+Ha*+\_" ċDaH ¿;'ڕa ܤ]Mڕa ܤ]Mڕa ܤ]]ȧ+IiW%pvu![Ү K&ʰnҮ K&ʰ'K,Ò2, ړeXFzd]מ,Òɺ=9Y鐓eX9Y鐓eXr9Y]eX9Y'˰>r.w69YeKNօŀeXd&9Yd]v hWvehWryʰ7Ю.ڕa+oRyldԮK{p^#a-yK/C4bl⇥nb<ᇥ~X:_tKt?ada\G,jWٲK԰K]aYzg>,uRbfQ:,uRb懥}XЇŰ~FԝϨ]ZYԮϨ]֍mҪibX?vuXZ3~1Q2aiŰ~F48,M;Ϩ]F_ gԮKsҘaaiqXq|1Q:,7Ϩ]48,mͲv KՅ%f’CvuaIYdѬ]]Xh6.,Y.U4ͪ KfՁѬDlV]XB]6.,.U`ͪ KfՁQ,O Fy’d<+ K_`.,&S^(O]XRM.,&Sd Kԅ%dy’o<j K_I.,9'SA&Qd,O]XN.,y'Sē<z [ԅ-Dyy,m|0<]}Xbe-a_v-Xnև^-[XԇF +ܦr>,esܣrԠr0]޼ ð~w%7byQyOR,/) ޕXPe]aX?<8 'xWbyqOC,9 ޕXraX?ð~w%byqXzцX^B.#B] JޕaI]JޕaI],JޕaI],GޕaIs]I2,_.ĔJRaeXƥ$e %ޕa`] Յ\2l we*xW |4w59b W0z 7X~ 0z N-0O0:b>X>x=X>h=kQ_myuaԔQO-yuaԐQ?xuaԌr/~2Q'FX,gaԆQFMX,aԂQ0jOޕOѦr-*Ű~w5hI)aՓw5FbX?ѻFa40uaDj :ќC 'zWh1fbX?ѻF1] 0nw0m %䓱we%wP’DٻZX({W Kejar]-,i%ϱw5%ұw:XػZXU KPaʐoU KXaʐoU K`aʐoU Kha ժ%ZDVj_XZX U Kaʐ U Kaʐ U Ka U Kaja 4V-,ժ%԰Z5*CV-lժ-ՠZTTj–jPZR U ˔ժej![TZ4TjPjPZU [@Cja hV-l ժej![V U?Jd&{W Kdja]-,Ujw5+C]-,W w\$VjrX2䋄jvP2aLٻ’ٻZXr<{W Kgja]Fja]b_aja]u`ja]-,9%dzwx y@’5ٻ2Ĭ2 dk{W KdʐFػZX&{W Kdjai]-,-+C ]-,-+C|۳wl|ٻ2Ĕ2Kejaw5]-l we we we* ˯oG,pG,wR}zxWbX>bηX>bt}X:bh-ax}ԖrWMY,RKY,7d܏KX,wc܌KxxWbF|Xb .,a,;aX?wxWaJ,10]X`+< 'xW#ð~w%byqO0]AXs+<3ð~w%aJ,O7pˣ 5ebXnb׋VXbы>/aˋ&/{a/L,7xKrs˽rgˍ0宾 ð~_&7by!{O6V,/c ~XeaX?/<9 'ebyrOE,^ ~XaX?/ð~_&-byrX b9迌 _fX2(e%_fXr(e%_fX(e%_fXreb"̰d=.jE~a{G~a|G~a}C~م|/3,I _fX ḛ$.|-̰ K!̰$ K!̰ K!B.C~م\0/3,9 1_fXe%_fXe%_&~م\o/3l2y/3l2y/3l2y/3,#8  ނ_f2/3l 2/̰4 [@̰4 [@̰4 h ޒ_& a)]2RI!3,2RI!3,2AP.[F ae[FdxH!3, "BfX.)d97)d⤛22&K̰x K'K̰x K'KB>`O؅x3,9, :%fXr㇥#.OX>-X>bpζX>bd}kPr?,u{r˭r}^,RM^,R_ Xnb^b.{aq.aX?A!ˋe2t;ð~B&byzOP0-L,h XΈaX?A!˓ð~B&2by*sOPHF,Od X2<r)db%̰dPR K %̰PR K%̰dQR K}{+2/e%_v!2 K$̰A K $̰DB K($̰D. ~a9]2u/'e%_voe%_fXBe%_fXe%_fXer̰ .~a A]12/3,Q2/3,q2A.z ~aC<~aC<~aC<~aϑ_fX&t]2~a h~ e-_fe-_fe-_fXv]27,U3A.ĪIa$Ia$I g$̰\A ̰\A2 $3Ͱ\A2 $3B`9i3ͰL3,/2 4 3ͰLi@fڅxL3,/2.@fayfX^di&V֠5hk5A K2&mͰ$c.dLښa]v!! K2&mB3@[3,m5ҖI[3,m5ҖI[3,m5ҖI[hk-v!N"H[3,m 1SfX& >ZmB@[3l )p. Na Na NaiAUQxFD|#qQ,a@FaEQpx2ކatFgatF~at2ކQP9ańaQHaEaQ@`Ńar8x2ކQ4F@,?PQ.F`Q&F@ ' ohd(aDmmX ' oh<bX?QxF_1(= oh#a4F31( OކѴg {İ~6&=h#a40z8 wX~6 W0z4< oXAYx[X2( o K emaɡ,-,I%𶰤QvN!V*vN!V+vN’i[X2;m Kcma}-,)6C-,I6C-,i6C-,62tTN’ki[X ;m KamaI7-,6C.-,6C.-,96CL:-,Y%ӶvN@t ޢӶEtȃNyi[":m [Ama<-,#8v!;m\oi[HNi[:m [@Cm :m [@Cma h-l -Ӷ4t;mXoY[[X #kkQ[3RY[[X #kk Kadmma) D3m i Eb3maHl-,ʹ"\$6f!_$497i|?L[Xfl-,9ʹ%dzx6f!_4f!^6f!^6f’L[XrpX b9;pXJi˹A,džF,rd8,5K20ഉM2p NX%aX?i`> '8mby{Opږ&'FaM,0ഉQaX?is"<&: '8mbyF$GDaM,χ NX~ra!b fX2(9m%fXr(9m%fX(9m%fXr9mb"Ͱd=r.jENa{GNa|GNa}pfXb 9m%Ȑ&Nۅ|i3,i fX 9m>fXR 9m%אfX 9m%ېfX 9m%ߐv! p K!B.CNۅ\0i3,Y6Òvi3,y6ÒxiB<Na<Na<Na<9meGNۅ\oi3Na hNa h f8m-f8m-f8me4GNۅXoI[3, fXjikfXjik&ښ hk宐fXiu 3Ͱ\2.@fad fXd]j2/kA!3l^(d,̰UMP. a]U2V5A!&)dÁB&ԇXA a)=嗜Xb9:X@!˱t˧tG_,^,{|K~(db9(rX b9%pXb9" a)x a),L,G K r,˩,U,^ X^.0奫X޹2pð~B&al(dby(tOPDH, X2< ˓ð~B&@by tOP0'X~qb!H!+()d%BfXR()d%BfX()d%B&ard]ň,1 Yb%ґ%fXBYb%֑%fXYb%ڑ%&aI*dB Xb-K̰.[a -d][a .dBa /dBa 0dC؅\03,1, `%fX YbrK̰ K!K̰D K!KL, 9Հ%fR Xb-Հ%fR Xb-Հ%fR XbeFa%fXld],1la h` Xb-%fXb-%fXb-%fXod-$̰7.F"a)o$F"a)o$F" ^ēeX-\ܒeX-\ܒu!ҹ t qvL: \b1&˰_ҹ.bL:a sK:a s-$˰_ҹ.CM:a sK:a sVze-^2lZp.-^z8Iaz]q\/2#B`z8IׅX2,͕\/'2,m\/Җ2,m\/Җ+^-u!>2,K]rA2lt [˰Duҹ.ĨN:as|@2lwkz ׅ\52lU\ jeت&^b$1M \/|K@,|r|8,XA,GRra^b96οX>bX>bX:b܋c/Oa/K,RN1A,KA,Gr@8,r:8,ezh ai#sXb9:X^ aX?ez\/:˛ð~%צbykzOp0z-K,O XiaX?ˣð~%DbyLtOpH, X\/ϑkD,?F[d^b%˰dPr K %˰Pr K%˰dQr2,Q\ eX^bA"˰D:r K#˰:r K#˰D;r2,I\/ÒUBezBׅ|2,\ x2,\/]2,\/_2,\/a ^%Ɛu! p K!B.z8Ca 4zHCa 5z u!p [˰p [˰p [˰2,S6r ˜\ ނe]/2l \/˰4p [@˰4p [@˰4p JRB,ozFa)ozFa)oz weXyW wexWb&ʰLqɻ5S%N=eX$S%N=u!7 K${BF`j0(w0( #J,aF K1V mQj0TEOTіr-)Ejm(Ű~ZoTvR 'Uh4FIbX?QFs$1V !0!aDj H 'Uhx$ժaXFoTF/aPy7UXAYZX2(U K ejaɡV-,Iժ%Z5ժ%ʱZeňժ%αZeժ%ұZ:VXjXZXS Ka{ja#lO D{ʐ/S K&a{ʐ/S K.a{ %=|’P؞ZX2 S KJa{ʐkS KRa{ʐkS KZa{ S Kba{ja,lO-,%=5)C.hO-l-=\ОZXhlO-,4QS\oўZH–ОZ2S [C{j S [C{ja`hO-l -=e0͂RX!V0 ƂRXZX* R KcAj :P I`ʐO:P ˬ@-,VvɴD;6 ԰ɴD;6h&dz7L KcL Kciavl2-,юM0ɴ-"dZVh2-$iaFdH4ɴ$)6$&!&)6iLdZXLXdZXL KbiaIRl2-,MɴO6 ɴO6 &G+h2-lM&CݢɴT6 1ɴI*h2-lM;n5ɴUM4&V5dZت&LYI,1˧@,|KG@,Sr<r6XXNS,X-X>bpζX>bd}kr8,Er9r !@,gR @,RG]Xb6beYI,JN*by?xOrpJaYI,/^0 +奠X d%< 'J@Vð~$EbyZtO0 +9Xd%<##ð~$CaYI,GsˏYF҅XAIV2,d%ÒBIV2,9d%ÒDIV2,Yd%A K#YB,F$+8G҅XHV2,d%HV2,d%HV2,юd%FHV2,qd%A.a$$+] d%ÒKHV d%ÒMHV2,d%ÒOHV2, d%ÒQHV2,)d &dX JrMYɰ.ļBaI,$+BaI-$+B JrpYɰ [pYɰ [pYɰ d%2H#YɰHV-JYV2l d%Ö@V2l d%A [Yɰe0 [Yɰe0 [Yi!J$҅XHV2,d%RHV2,d%RHVȰD*[$?%,s!^^ KX"ǰ% KX"g!?%,s! KX"ǰ% KX"ǰxnad6f7Ȱ-  dX A%t!r ܠ 1dX A \ 2, \ 2, \ 2,]ܠ dX]E [1ǰc [1G 1c?c?Mǰ7x.a+o \۟ a)bG)X9>.a& ${s!X߇-X>bpζX>bd}kxr>,lܲr ԯrZ,7R˭Z,wR_\XnbK(bYXxKP,/0 2x X^}aX?A2+; 'HjOY ,@Hˁ%r`% X ,haX g,زIXl$ ,l[6ˁ-d2)2+2- rˁQ`9Ŭ,bVXl1+ ,Y`9Ŭ,bVXl1+ ,R@`8R@`X@`9T0X, KR@`1ˁ%r`& |A+ X ,_ ,llˁ%r`& Xn6,V'- \[l;lضpn90-E\[ bK0n0n9 rn0n9$ [ VM[, K0n9$ [,;:[,[:[ WlX6u`|A|}yXj@`M#rR,7RQ,wGKQ,FKd,b-xXzJeE, ,bY`9,uQ ð~"I@`9 ',by$IaE,o0 aX?A`YX<әð~"G3aE,eX0 噌X Xb9Xb9/#B$ JaI$JaI$,JaIr$,GaIs$t@iBH ҌaH Ҍa3C@1nugEiF,>F0pg3>a F?jO0jbxQF=Z,aԡQFY,aԝQsFY,'Cif5fܗQ[F]y5eܓQKFy5dmQ;FX,'CifaԉfI3HFҌXn1h5XbX?QF'CiF 'J3h{5WbX?QFa0ZaDiPF+1( u0aDif͊İ~43EhN$aׇQ\0bX?QFA}tӇQJF!X1 ’AYYXR(K3 KeifaI, |+9%ɱ4d9f4’XXYXBK3 Kcifa v,,,qC+(,,C+(,,C ,,,уf@XYX"K3 Kaifa!,,,AC(,,aC(,,C$,,,%4fh@f ޢ4efl–MPYز J3 ˜eR2+cifa4c$,l1 -f4,f4,fPYXbK3 KcigS,,,C`,,,4T0f ^!xb^’0؋YX{1O^’0؋1Ą^’0؋YX'{1 d/f /xX}Yhom¶JCŐi,l4T_ y@T_’X}1Ĝ2as/ KN`&/ KN`ea ,,9՗%'lX}YXvmrDeaٷ2 / [_Aea+'WP}1ė+/ KcŐ;/ [GBeaH,l ՗@ea5,dܒrG mr;j"[XćXV_IJ"՗R˻(: '/by ԗð~"wPbyuOP_I, X=ԗeaX?A}K'<: '/bytOP_,H, Xb9 Xb9bXNb9/#B JaIJaIr!"R_ K#B,F8G˅XH}1,H}1,AX Kj ŰXA`O<,%RT K'EŰt{RT K'EŰHQ1,[/RT ދ bXv_*M Ű5W.t_1lMÒ_1,AW.FaktFaktgϩMQ,b;<,}b}\,RM|(*bX,7pܿK[,woܼr>,nܹr}Զ"ag-;Xn؇!۵XbYZXnbS2PTr]4#ˊXVTIJrXby$MaEE,orOPTI,/ X0aX?AQۥð~ Y: '(*by$g>aEE,| Xb9wr> '(*b9pr>,emr^FʅXAIQ1,ÒBIQ1,9ÒDIQEB,D(GʅXHQ1,q bX")*%ԑbXbY(%bXY(`\ȇ,ÒBY(%#r5X(%'bXY(%+bXY(%/bXY( ŰP.@aId\ف,ÒB1,,Ò B1,,AP.a `a `ahbXFZdY(eEʅ\oB1aC`<aC`bX(-bX( ?J#EB}Gʅ8~"EŰ>RT.Ga}Ga}hbXB&%DhbXB& I41,!D 1DhbX.&Ph"ɅxI41l)M n Dözk)M ۂ D yE &hbX:&bC'İ 8H4:&hr!6tM KC'İ4tM KC'İlH41,+M D hbX6X$hbX& Ʌhbؚ&%hbX&сh"Ʌ@41lD@41lDS>F0&8aoP?z6>Xnè?z&è=!FvafrFMvabr}o FU,a]QsFU,WaYQcF}U,WaUQS˥ Fu5T(FN0rB.aZN0<:!bX F;aZN0 u:tBѮG,TѦ F{1 %0aD'dfİ~220bX? Fxc1 l,aQ.˱xaC,,y%1dFvBN@tB D9vB 9vB D:vBPN@>Yڇ![>ڇ!>ڇ-j K`ca },,q%D>Pڇ!_A>`ڇ!F>pڇ!>XXXBk KL`c jPXrj [N@ca },l9e2abca1D [Aca<},l-E>E>ȃ2b ?JUj0TMFR5Yˆ!VMFR5YYX&kxYXXBkxYXXBkxXXXk dc jeMD}mW֖Eom[¶/BÐ7F} Dcai},, Cl},,3 > 4t> 4t>YXXS},,)>k\PXXTlv,,}͎hv,l}ClX  KbcaYlv,l ͎hvr/Ccaehv,l ͎XFqX6w! =v,@6˅Tחl a.KX臥#X.b Xb2 r˲aA'e,e0 ax7A6ۆe wdiˋRLkeK@,oKX,l l,w by 7 a@,O Xmb9drb; 'b9drT;,%5rN[FXAI60,dÒpH60,dÒrH60 [0/zC>aIl\5|Ò'0,|A K{'4x '&˓Op!y K'[ K'{ K'| K'} .+>a\ݟ|'%O`XR%O`X\Q|'0lQ|'0lQ|ü~-Å\o'0 ނO`}y'0l|y'E [ 'XH>X5'0,U|R5'0,U|R5'BI>a`XY%  5YP߰!Z_XV m yögixˋyi!v^Z ߰t^ZBkmWhmX K_aYZ۰,BhmXV!־; :چ0Z[چ0ZBlam # Ka6lڂ־+5 [a԰6̕15` {X*Bb$+a针#ˏX> "kX.=۱ ְb5a)5X^Ê5ax` +紇+!byH ְ"'by@+糇"by8+g=g kX<=, XvaP4##Y<RX<= 'ar)0C,'ð~V,Njð~V,g -KB, +B5̹B,5̹0OP ;Ny_jba}aXh_jXK K|`iX*m=/ĖJ[OTiy!UzJ[ x`iX+m= K{ai4,-ӰYz^ Bl4,햶båai4,MӰ4^z B4lӰiiz6l= Ba^yy![z歧a .4l-S-Ӱzm=B4,UjӰTMzI[OAz^UjSvҰ4t].ݥai贻&. ֓ش4,?lZO VŰh"[#ʅ#a&U1,Մ*VŰ0تVB>`U1l *5h/^Osa4Fs~\ќќ_,ќ~Jb4h,d8!y$HbM$r@Fa4Flq?Fb9Aē~ ,arFa4G˩caQp^?0*èj?Ϭ z r ,w!=ғrғ]CWCo,yH~ίdʓl??v|էb/??+G9]i.ϙjxވ-L?>^g%GS+ϧ=7^~>o;^/C&}_1O{n{Ƹ_/M>_p>)?B/yV͛VDg*_.CԟHyc<ƛ< VC,C1nMyƯׯ9Z瘾Q=9^'o|?Cs7h[ߟooIߟi7~ޟi˷׏_|V=7FI|M+[_3=N0+A{b|Mo}yˇ+Lجg<O{1ogp}ؼľ+~NzFkF?;yI_5J2RO^ΞcyR73+ѿH b!O RsNLfF~<_Gkſ^:z1x)~ۼ= )zXح}sƎ-7bH2ϳy>d^%v=̫٘gux~&Qכ3J}_&o^ny? <cW]Ч^Q~g{A{}89ŏCؿag$x}'|-~%>}1g_&o(s7o(g_S}EyC}ϟJ/cޒomtgc/`XSt;į}igYuz_QO?G}>O~~vo̧Lc7|`3E=FѝGyp7j|[ zJ3|~~gNwo'fA~x~ mߘ;}0 ٘z1gCTyï3~7bYx< endstream endobj 218 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 208 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-028.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 219 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 220 0 R>> /ExtGState << >>/ColorSpace << /sRGB 221 0 R >>>> /Length 6226 /Filter /FlateDecode >> stream x\ˮ-mxTS7 ddt hl=k-R Ƞi"E(b+~y_+SJ翿~P#7)Nӓ[H0Ѳ%w.`?gO? ;__{L-髶^Uwgv OTc7__Wꫮ̈́<0zfPi}1髼 16yud bk;讗x?Dif3ПکrNIk:Djxzd ^{Cyl)z-0wB47*rxlvLyzxz&xNwwegbR|,c=@h﫰w̆Ў2s+ހ([[hqd XԷC/~cl`z7K`LϦ${Cec<w]/}cɰ/T<˶g7)NAucĤwlA;讗>XZlokgcoKg'O햮mAڦ7gc2o*#[[{Aw |{K`ؗ]u<^([Sq7o~lB1O鮗>XCk׺-ݢOZA6lv:Dj-\kÐ-HwХW>}W,%03]'Ґ$ԋ{Zk{<8o@֎)k![GNwWNdؾfZkl A xC)d3c扻;d RktOcʚ 7OcXJh䀾})zo!툙J78EAwMТ}= ̋k=tq?ڦB[QZ;lުٿ޷]/~cZَ?3Z3qQW#gt>i!yԧ^blلvOUOCcirWt.7сN|ݠOPV`2o⟐MHo^;ƒh=p?0lOcW* R;uZyl^[9v,+xzXZcqUwI1RkkEQZ;7eo^bNh~b•OPCtסct[AHCj;7zmާ1hq'Fdw%,[ܼQvsqnzd YEA^;Iܸcq9kOc,N ?n.[, wpztހS-oOo^;bDK3L3l0@R@/l VkL ;让>XLd^0Mg+Ukv@ K tuH5ӎYwұ ق"rCAwMweĕ ~b:UCZt9 io zQvb LPk&nz%c,ު1lF[7ec*啸eUdߢ^;~FhX`+HJ@;uei&&@m:dGNwwĕ(y?1L!3GEtt:z-)y:T«ޘUtɔ^;讗>,_c~b*f䏙fs@6WJ~R^([C/ya-!fߛz9S ~ 9C0bn^Q: FPAS+H #[зG顩x?5'sL:9LXƎ0?סXסc"xeEߢ^bƔqZ' >\1vt>~P+P;WxeGL6o^;rl{~b\Xά֮quz:lLUy˻>dRk[KzX:𥳐 L>HִTbkWZ:P>/*IW&CSskN<IkOO ##k!F,nʹN,9xׄ#[зG;y?d=#yoc&gvȕEPKf07}F^Fi@mס]#׷vO\y %\{Ю{:?*s%Ao<1No|޷街x?,SƴM]Pݚo@u&cglޤeGߢ^;8OLq݂n-S=kp ^3I3c]/;~bUYzF`R M6*o3ޫv;רbb%0Y$nG@q×u:7c%7mv(}ctzlÜ'K̒QmEV5]~ݼILW6>3ѷ]/}x1bs0ѱ!x\YK=t+H 0nYNq.{8kO qM|c7^~Nj q~vyģK}}Ϋ0ٖ{+8l^~y Lug9޷]/}}X\ֶ#fE]\王7Cap bknhh1<;Ґ-h:t׋zX&BɈ3y/CڵFWwCcg;oe 뎑o^MsOO\lHWSu&2qPDț`6Ce*/f]Xs-+iVz?}yA{&{/P^g@^啈78/@c&>lA޿6rO,fRn5+73Cl<8ka X̜ʠvTEpc ˍ7 l)^wNwwӄFΘXKv T/`W\7 Ɏ]C-ۭkOc]RKC~b:+M=(!iLjd'Pۯ5)< ȐkMtyzǺ\9@DAx詔k@q!ʎW;b\M\Dlw ݛ]81wfs],^OƋX7|,0ų-(}]zS)h֢o"B;wvQs}$je5Ǒ-Hw]S}4̘>d-a1f,ʗÝD;-UOJ{3k}+0KM8}ʏ\tPRGv;dKCRFY\ 2DeW8`[UZ*6 oqA@>!!k9Vv⬝PNum5YFbEXYUl=6$ׂʮ# j*Ĥ( I@F}U9CWȌ5`J!덄ş^Fǻ?teS R6%;[,A%\SƩ;.7CjJ>tT?7墽Hq)[|`nհ0C*>7oM\htax^BS`dtʌ x>O*[ͧ@#7`DzUx%Y18E>@2 f/ZE[ S̺c OC-_ZBm S/tY JXs rejĨq,y Qh{) G%gOfyHx|zԗh0_ڀU6÷Ql6^%]|"|&d~{Hd/<NGmЕnʻŘI1/[eQ.ڀ7C~񊭐x/EN!j8dY*o N~D"ä8ml,dB4[3Bs qH$H- 0].~{<J/㖡4l+zqLc1V`<º!lnKuQ330yN-:^SIS|k^a>1h( 1kjGA U?$Š+i:Ecv Cl N4H ^ab!j% ^剑Pʙ|@ aXł峮#9c3GF J)S\|>07{ }Ewmzݫ_ gs FdE֗>c:ih|&Nk_xd! K[-`V^;qO]𾟓ר~RxS{Yp)Z2(կz]q^CD*k'Ҹ`gQA1X6{0Gsi5Fý2*cCUU5T߮Y5%mg݇M]6YI_`\vP=xxqFEVI3jZCɰY/{Kl%z) &i+@2Ijy Oz. 3Tޅ0uGb]iGC:3O->sJ3 ˦ }dp3ެH5ezUD/Zz\ӻ'i|SA.u~ƽA{l²d?v6UӏelUs*,-eE3|=WVƲ8Yb9A&a2qnO*: 2J V/"Xx(qp_?Ƿ:љK_(4_@@W03^.yS&dq,-knPf-hh$c2c?iLŜ-K_u~OcNP{I*&ט~_1z͇zϱ7\2smjzq|4MLy%tbmFS-O GSPM5fuT|+KomNI{zEv_V TEfdz_tG笑AJJCO `b˼!'[4q*U~uA0RG."oJh9hsݴ)+XUwNO^,br0oqn5y{9}ͬ@nH,Ȋ_] zUP^O,_acrյ;k揦{ k`_m*B%w2%ή@*#\iaf>Wb!Z endstream endobj 223 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 228 0 obj << /Length 827 /Filter /FlateDecode >> stream xڕUI0W40,ZtV5N ! R)0mo10[Q`Qt?,$0&/ii/;T(vbNnE1Z\^gyd\R8/` ]DVuV~: "-cSd!$㽳C]8'% z+֢֠!;|B0t{Vz# .P{&Q{u GG6ЩE1V0`ٌ1X<)Pr{އщ[FCOyN<d8Uȗ$s﹌[Fnv=0JLTM] H}#UzBP:"qޜ}Q@ =v 4b0# &"XE8dnV@F96񜱽Og#I3>`:&-u"Wմ |zИ6y pՉ=Bi%@AvMn,1"BC#&[x+ "@eqdBT%q؄jlBZl{=-YY e$r-8 Z{$Nx;gD'{adX>4ӗ,A, ]\^br0m Lþƃ6] 4;Pk;qn@.姿[,TFhןt)?il Pt7߁]gBAف@(߁5}*Cr#LXǡ:ʤX-5w<4\ȦD>=ubbǷHI' O%S endstream endobj 209 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-029.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 230 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text /ImageC ] /Font << /F2 231 0 R>> /XObject << /Im0 232 0 R /Im1 233 0 R /Im2 234 0 R /Im3 235 0 R /Im4 236 0 R /Im5 237 0 R >>/ExtGState << >>/ColorSpace << /sRGB 238 0 R >>>> /Length 19193 /Filter /FlateDecode >> stream xͮ-Kn8Oq[Sݍlãc5 A۶oЪ*M2?Z ɨ?G?~R~5?o?_ϿE_=KtWk???_G/???oڃ:l9[ȟ51o5q~{~uRm]_Woo{}w3ݿww~L[Ho)K#z_y룰+j븂yվz? }\5{9| }^^~q7ZZ<_=7Ex6BY W_ P^l۸n?v} 0YOϏsSa3 j~gʻ~w)]k y8-Vr ,ؒ.b?~#"C @cŌPR%q$՗cSb3u՘[e~{>n~s1_cPi) ֟~t'tjq;ڋ}=6嶋Y/xbN;ooAs+=ݼZʫؔ.b?g׽~9=PWPWY]=sHC]#W3_c|u❤%]~<=CaWL7pgˤ_&bq'c<ęָԌq*jLJe q4ٞ{Y1ڏǣ?&N ,!3No^\{ZARI!_ SZ7)^ͱ-]ƞv볔x3g6ct8 ls ĉV\*]F_3{C\$c="+6ƥfxv15YL1)5ĝ7a_ŒA? >w١Dhťb97pڟiTS+R&cEAOݦO/(%kb^;z_;gSq,bRҥ|V^ Yj_;q{2ZEी1-5}ت) Z(.xrm O#6ND VRYCi+gB;I??q%'1ȳ$xV\Z-A̅[7Xbhzg~7\<AcG"FyZR GZu魀2{-$p)ǔTwJ73?$$y<3Qb.?d371ϤLǿcIF9d;"Ӹ{ON t<\F|y<#'S.lRͫ)oPnR qlivvox6e^Gc[ y?wLXXHpq$qEO/\ZIA1%yĝjcU8ofJf^`B4pNq&ƆF\)ZIh1ɰ5}تGIWf1|S⊵@E@ [cE]cWri[r%iEf6"Ur9{7WӔW31I't{5ҾŀUNTf+]~uݞt:fMƆ~a0lS1ZZ8 1 nСᰐǤTak-97݀G80FK}>Eoͫ26f;ur%iCx`U93|KP ma?-FI(tA9%]žv}=gnTΌ\4>tXq"J̸ &%zSR܇Zcܮz1<7|g!,܇Q|[B‰V\*pbJ*$anSa=0>6/g7Vxq:vȌmNrE`|W57ȼRP-hiMSf65U<#YX8OI7)o ؖ.a?lŻ0"el\5Pxa]1z'^1Ɗnb30N"ū5Kno{%Ҿ $nA<3Z&mk IJNDiF@k%N!W ֜vt:;ZccS+1[&VT4kN[;OMWsliڨp3GLe+^Īg.cJ"9oα%]~e !v)s$+(ɳ.7 *ן+G@=W3Ll8u[r%i܍5_V ^\,LxO^n)(Ēj_ m$>ZJ; ֛nV{͌3Lp=B&B;iJ 8ų'qIvJrLIip _iF<`,/N;ASYMz Y312cǸ.?ZRY܇y31tGnm6 I*'zߌYJBZWTwj?dsrE8܈5^+[bMA7ߣOurEݹD`HHi'$P LXs wq&2cCޡgyLJe q~m*#3gY-:U" JA!=ܚAމ}(אkrYJoNƥMŖ9<4.,⦯>Lx|3XQͫ46\Ijm[kejAOۑ|]τ{p[[jX'M }NQ@s# b>NcQF9s(.'V3lDjWe3¶713S &Ȕ֞SRZ#aU83n,{mI`y&)Saq99:q.嘒N[Yb͙,,m? p)Þ.|aM6g lclrG{.<6嶋(8+fs N7^^x?'Zcc!Z3cR*k;mUoo?yD0?UM`0KpIh2p*J' zJe qz kQAw+(ҊMalo*) lI6 $i-#{"/jĝf6wp6 )^ȌlXf y_)X'z>7[TcJ*k;m QI$s_P>74#)nqbE]cf3c3噺I%1KnF }0&sg ̟M¦-‰E&FKT"iE1)5ĝzJ̤}r6k:nWizK'/eNZ-yZZ/vk&hZgT ," GR8Ɖ~Q!ܼL$p)ǔTw*'f`/RH[hτ *"w'G; }kN[[ /c#<5^(߸ok0B?!MQBHY؅;&!_$T6a9}c[*P ?M!{P)u%Nb1p#֖RYCin<\|l%VU9sbqb!g+`bJCǻؒ.b?Vi!h)lx둵PE ™V(>1)5ĝ1!hzՓGm%j>7iަER~''cEM} vؒ#FV=1 @io]O-U[M)j # 7"։ƔwwPʄOoՔ6%;֗MĭufX[cR*k;m}K cYYb)( ObdháBʜwo+&^.cOS0|]rK-XŌ/S \:1+gs4v! hݤx5Ƕ\v {m'U7]̩(YՏ OSt4;3]XQY,`MWsliݙ$iD\P{ D_p%q"rތo\vѥFƔTwڪ]_-nQ\]s+gN2$M ÿD%sb[yuo\H`NF%\,ܝN(,򍟌T>+.l]]b.#=cK.=бb/37vJ Hl$RYQ@bE5~ObYn=7v=Kn{Py1WJ̋(TnNS/ 1++jg9 SSt,ǖ\v {-QtIֲ^#% _ m$>p"Wf]\kvS<&V?"_o 1gƕpćE<ہh _Wo 1B8ĐַeƔwWk;[ÌM*oSӶtT8;@qzRǜw[(ZHA>9g!)Q"7rD+jf!%i>ǖ\v {D5LBt &Ŭ1.,*>Gr%Kӛ_T'!Hi$uq)|P3V|z!M, ;[r%i#WS*ԈFdmŝۿ(ڮ67oV\cK.=l3f7O$,cئ8`ݒro+jg`\+7=K7p+@pX#WfѲ,2TowՔ}_9#1‘"NgOuHhER)燰1ujp.'n&gnRcKnK;+ s00QRbO_Z&bɪIYD!= cJ\HQ\WZ7Uw)f\HOLlf ݸ_iN>l Mf&WfLS n,v{H(dl n.KN[ g-FgWLDFAϳżg)fH]nmvʚO[x3Y=STT\#Vm)zgb 6{L0l pz]o5-vLQH+f;)GO#d'ycj) [Xwgc[.}ESGaiK >c̃@N,1/Е~K:]$4Sos2˙?n>HkRڰÃ<ѯb }^1Ж콂yE Oy $q>.Oq ~I[b w'5|w5|c5o=rd-/jtG&//.f ڔW]grH SCPYף hXQuA)Kb[&Sws]g-[aKޘr"O i2hY1Iؗr9x% ˺KyylevI͢n0zD7Ia<֞- +:s3936~K&ū9Kn^Ożn^\B2b-Q.;XQXrה /˺g:a[r%i3+_ݙGA)舤B}Au4N/x,y՝ytpJyHJA[򴴔_r'S5 Rx#cY).*+D%g27hc v쭻dnǖ\v ajΜƞ#(\p#YH>xVjer&VT}S8(lu7#+$/v;OiQ-hr\JuUR0kA{TWΐƊZmlIͩ39Kn}%3d}rsl A譳ArI &::!ǖx/vٿ܁xcVWU,b+jdQ9=Ķ5u7[r%i _7&YEwˠ.6+N9Ɗ93~)_#kʗ36ZN?XQ6b%i9+ǖ\v {ڭߥ)}(ܜNP?Tw%ue9ZrROiWyle^*ɹ/.M]*E@yT)YpbqCꞹk5E [@&g{u%& >wLw+j,k¢#uQ 9n}*q{-fD1yD|h,5A&}Zc*EݼZ;=Hx'--%n}Vĵ6^zCvu2f_6԰Ǔ$'=[r%i]U\9!{ ApϲL &X&9\+^+ureiΜ%-RH ԋfIg*\ؒĢsmɱ%]žvۇn"$ bL4ز/SJ s7YY7.O\I%WynHlO6g}%G!n5brFѴ`)qؒ.aO_G/&u@+ԝIg,WbMDSX؂&ZMс^_92]y{WSټ*"=m# M:[DpcILM[Q [إJJc[.K=?s"mh]i^͂xG-<͎4QYIINF{:cK.=ֳ&6>cT-}jNSnF)뙱GX7)\%~m:4U^3iŌgh)>2R$a~WKbfOȱ%]žv{c =>9J{h>A8諒؉º;ؒ_ݾtSg`|AM;:ԗk!!gcIܩO;l3a<n<Թ.g'\&%?9HHlEdкk֏{le;8ȈG̍]ULy$h'cEeBrgX$aqcK.=v1`4ٱcKϾjXB~A6t?uJgrEjsDv=uw|7k_ a~+=Kn?5M> X]F>HK9&6||~Ew~9KnQ-tpkE cI/GM -Eݾbﴈ [ºIj=ƶ\ad_rzt ^㻮{0kj9h9XK6ǖ\vaﱊ|=<9|1i_9wE]%۬mxcK.=ḡ@5ɹh *V 'oW~a2VTN'g>cN}α%]žv;sq 0A9~JtʼL1R*DXSDG;ȷnRivSxFH;_*hEϊcqdKx+DMqJjLƢsE9KnvwߘZ#R-+"Ҧ3}+i>/j+jTrЉ)hRؒ.aOSF,ғbJğ*jO?#XQYT'᩻g-۾%W fa`zT6 mȡ-x7T}u̹7yĎtŝCnKJ 8ONrL!(;#S"lZs/ؖ.cO}ܤ0ON񍽫6Ly_ HVFŠj.K'YT]\{cSn۟(gGn쏶aC(βM9v~+jz-9m EbIؒ.aO7ճ.9( kE *+g*cE39 7u3ǖ\v {ڭRON#+h$4TL9d[W-w}=A݌נ:O<Q,'XQ-saldqsle~.t'j^"(XW8gr:|*ch88Iب/lݺEjih -tȝ]<+ .īo>LcE3tjq.>պEj%~؝[s#w""W1*ew옎W<+ʼ s6r'-8lۺI.b?~ו͔51/uP k?U3*;8),O'yl~*,2Bm"5"[w  }T&9-Xǖ\v {=>ԭGV$& , iE)55s29M,/csleݎ)#n<͢#vٜl6g7 `5Kn.s^šl^mtu&8-XS 79HI,;kؔ.b?v5v;8q<+MHừ܇\Š9,3Yx7YcK.=vLu'sa(}hr`N/盺sslR`O_nnT}rPߦGSoQ^ >LOw!%]žv9UXr0!~�]) KĈ5Xr܄u9KnŖ3~1k.듉FMhN)yfbMs1bؒ.aO}!!>bu:x;u+yr4Y +jwJQ؉UurE~c^j3C1xZDd&9Wo%kj&198 7֘[r%i_WI3󉼓S͔w {yC1Vԑ"3c9YS{l˫mwcT99؎\z<=ML+<"LXQÑD-ZXw-"wN־ו栴&E԰n۔S>e/JqrL]nR"~y LoiNǎD9P7vL./)k~rs*Ec 3[r%ipOud苳QC!kݤc[.=v ֔}Òs틕5C8prk7i1O&ū9Kn_:j;0D|;b)Q$hxY8wr>rV,hh,(鶷X+pdۺEjrY*i7n)1vH**W 2URTwLrpkb=rleݎ[u${IEХqw]j-'9aƚ2d$ǚ{nrEz?ڎɹ߉N;Vw559Y.gƚnYȞ1^u^ncK.=رr;o<9HvD6X~ }^q` hx"!y?{i3O??Jm~_^coP~o^?Fw$gݪh0}rЀf$N~juHg+rcnRZ{v%/oXtP-[f\T6HywNsX;ؔ.b?gqJmwI^:{y-\wac%T-'vƫ0uWyRͻ^#k]#D@Xiݤpƶv a>Kq|3x#0@]AmA =z`ĊT$?{yo/ǖ\v {ڭ2Qy9-U5zM3d9$2VrTrС:سIݹcK.=g7.Mu!Һ~, t삕I]&c ~&Yc[.[krV8;:sGMHv,gVr'Kc9Knc}}pؘ8~1qWwM\Z%j%@VdY7)^ͱ-žvwY<ޮJt{ VCez- +j(9h9Xm3]+\v {{s`9GA|;#&/T+j9f=ɱ%]žvۇaM#'рu(jb=) ŠNBK,<]ʱ%]žvRs#b=,]Q4LP5Wn_}w{qnRZc[.K}kf䠛d)E_=X~HbEulVɭcK.=~JZVə5mNPL̒\~`>_zBaoSUrzmK͹V9Kn.Flfz-&N|Q E\'V:vWYK\=׌j?6b/=u[r%ݚ6})va"kqތNwsw/w׃eI'%g1#6a=c[r%icT(c`b3EXƊ*7pc NnR?e=^ysg]ح2'i%}sdGԊܞh/;?J0T40&ū9n$'uS|O<,&4VTvLgpagpn-]žv۷axg|Le7Pֱ.yWĨHUXQAy3Oc[.K}$zcȧBF{6S+GbbE9E>Euؖ.cO'Ǩ'`ܡUSqEr,+**Ƚu]cKn~Lj>98`݃\93 ʙjD1=Rw̱%]žv{] aQ1XsZ$ǮNXl ;&sQZ|z8<9%^^(DZnRؒ.b?vbUCU&A]XɾL9 Ěʺ628\z(H,5\صvnf`Q7)?HǺ~1X6'Ëo0;O[WM?7$5QTDU[jlev;O7sߓ{涇ޮ3}3wXQ&Dؔ.b?~c}ݔ,dAixoo 4[3[;Jw}K-0Pàs.|7xrgݯ-3nB6O3#rEo/9rDm, oOw߶|#m{栛~brle>raĒڲ.h;8y\^-55]'%ԝ?sle~Uv[R^,-=ii)9V}r"a"z,Fr }uvbIXQo9+O,Swnؒ.aO8rRV8Lc@9-r#'fZ0VpfrHXN*[r%itIEw)׸'ygZXRSf7ahݤ~ʒ{Gg +$ xRQ5u(?}oif~@d_ScK.=bw<19$;*͙%zK^9# Ɗʳ8ѺG-]žvG( 9O͗\%ѦĤ|KJo߅9 rֺWؒ.aO\z䎒3;:OQ|\* 5G$Y[7Uh\ {}>89"qLit/ KjdHr4vTIjm,ỳqd'Q}t>p/v|Uv$Tv_JH,z"쾔cK.}^oa o{7S_rulT}3AXغYOݤeo_3~{fkgoۭWxn7kƲͺ7-oŮΎ󛃆Y5xDj[aĊCê cYa+[r%i7zio endstream endobj 232 0 obj << /Type /XObject /Subtype /Image /Width 39 /Height 53 /ColorSpace 238 0 R /BitsPerComponent 8 /Length 2605 /Filter /FlateDecode >> stream x{eE4j%cf!cD4Hd*r(%T<"""!"hJS)ҬҦlN7w9p g}yZzz'L+6S ?vCh^_~e :ۺ۪"CǕ!;²_>|?fl-W@1ow\y)-]>}kW //b9̉pwW?(nxgΫ;u_t%p렲eK~ԥov_8㝧t]=\uRcşO>e?,nxZ:˽>{*ΏpSc/~l,f!՜uZY-JrSC\r}-VTdqC|G<7S[܄/͏s1C}yCǔk/W(-{byzuNyƮ1\Ql2\TLs'R6dsa NObCwg4R?+Eceuڠ-l2[3>[.p{kظh 8<;jNy'Sߍ<41I0b=p)  t]Q(n85@>(!㝓iyYvH;:9?Gʰ,;R־Mz}yQkntZL`ۋ[w~H{ V512_?$&IӞA 8p R#(hGE% >*S+Ph`dyGp҈я A/ 65suM]PCUW*h5Q5×) 6ɐ鄒GXJWV|S{>AM1 YjͿO89Whd ׋.݁2~*c90ҋKJdVhXݐ[@k IQ#LXYTQڀ$P^V%c,##U" b (> )n)_j1ʟ 1OPHQWM?2i6~C 5ACQh'!Ҩ_x0RC6CL&>Y8 㦙a),H,Fћ[(1ϣγ5"鲥5ʩ4f=$a#.H&ap*FH&I-+OV:2aQ) )\0ZOtՆI.z8ZjytIS0gM7Elʍx+Q?%x{rº˟$F0fMg}&#ʌlrn Xȭ NXjէm;&ԆL0žÆ<ݫf`NƾMSͫ>eW|~Ūƅ=*k RE mbmً-5ujlp(m-q6݁N;F)e<Ѷ|;]g %gL"]AWT38TFqFd+3c@u#ËIQ,z #^jJtqi]Vt_StYRtU[dL턩*DDt{ Nu~pG5t!_=5tQqu{q,'XkL΍ې ;pطIMNݭ :{Ioas&RXp[T2D`J2q%Ƀ&B&#/ݻRxF:h2 `24n˹I=ln7Ie3{W|RfIjni&<&~űaAͫ.#Lttܒ7DhXN镼,\竢 TݻL7@@0[5&Myz4eb˶aCmϠS̱USbDp\+˫/B'SBtK+P˕du9I\"j٠+ܰA..n$Q'I{1:Iw77 'kr(ʮhP Լ@8lL Mޕ=?_$$~ Tw6eЩxX?ȸBr)HDU?JՀƓF( u/acZLD'݁êN4N3eP΃ÚN56L< SŰoYۨDZ[PSum)~Htrm4w ɪN-YÄb-7mXBaa/vZ endstream endobj 233 0 obj << /Type /XObject /Subtype /Image /Width 1 /Height 1024 /ColorSpace 238 0 R /BitsPerComponent 8 /Length 723 /Filter /FlateDecode >> stream xugP$ioQ.K23/!g$!BIBhHC$DB2BeD"#U3|=zˏ[iK/lM7F1W=9Oi-}B>=z'V&75SJ+i^Es@³xSD,닥8=KXlEVX8`P9֘e#0}$a(Lc1i<&c'cQ1 1l: fal<y猾+z.DE|1S77\];:/ùq t3> stream x}VeÇh" RHeCD6JD*(" " (-Y1F&1PB556dSY3쾻ܳs=u_u?}=wO}~e3~ݿ;{llVִYYgvWt\}Meݶde.+Ns::/ͺ بNo=g팳Vobuk[/Yz<\K(VyHhв|+c,Qesum6X"TՆ5nw?}9llΎlenc;>ry[YYudU)XKE n{6lx6{PZ'f.[bpN0+?tk.wM~#lzТaBuלx%墲 *9 |%y,Ol I+=ڗTRe[0~xx=p\7=c׻.7RD'77lE°Ұ0wPduИ 5RL2ԏ|j@., BD%OUKQOfHiޕA WqxcU\luȤLnQ)'WT E6 قx:~vv6UD5(.h"+pEԚXVoW~v;mz(i_E;08AfrSyˤZmFiK&:FA) 0[iC+L>GpjFw||U8zjd&řGS|o %vxT, 3Qr->iiCSA-9tcivB)̶xQj P0$>7|Ac4N)™%sdBI%kb0icy*82yIt&OD#}qhiyDFZƜBr2QtyJ3LlTcqtdYi}:ljO8vsb͓6+!ʆDA@ #w =WD\¸ Oc?>W06'J}x2|h-)",|#Ÿo Ogon4ݑ4ᆹ: Y3xL-SOg)ҥba0Sܷ(!-cd{>^]>jCQs`Abp }4CoJ/xuy8 owKEtWxFăF`>sy@>B&xx. E3;%䔹Fu[q9Y}eʢA"oix@ݥ8ة)p)U*OǜKkSwKT7 ˆֵ;}K})\ A0w91 !fR!Ge $3 4*.DZ;>&f1.ZDLa'Iv-aT*hW4LV,"2W0[7E BϿ;ދR)/5-^qtiWcp~!v6Ʈ.Mxۤy=i+GϜ#8TP>S'$*~瞪h tǜQU[x=M'k endstream endobj 235 0 obj << /Type /XObject /Subtype /Image /Width 1 /Height 1024 /ColorSpace 238 0 R /BitsPerComponent 8 /Length 723 /Filter /FlateDecode >> stream xugP$ioQ.K23/!g$!BIBhHC$DB2BeD"#U3|=zˏ[iK/lM7F1W=9Oi-}B>=z'V&75SJ+i^Es@³xSD,닥8=KXlEVX8`P9֘e#0}$a(Lc1i<&c'cQ1 1l: fal<y猾+z.DE|1S77\];:/ùq t3> stream x{eDD.KM%d̐!B52YpYDEX qE%+Lj"rpG I)딓M)M?2s߾{ss~}gWM?mɟM}쌳Bx&_zXÇo썴eLYRYz23cv^DSvPYtyTEM?(Q[+WOr,xo- GsHf;=zQ^* >R\"|z[o\>~a0EiAṱ2<]sEj?a}4< d  g͟E ʏ_DMn[?3 4 G3ڡ͊ ᔅWI99<Ÿ{vajc=ɪ'2e,6XDz}*]ye?S!kJHI)-Wo{4,?{}4⎫UW h4Wߺ 4OutW^oDiwBTTgF "DL* <s9z W+QoJ?"C6\1@yiT\1NDfe5 ԂȔ's{uEH pcyґ5o~?:|rϐb<+gǐ%)vpnV 6$I&ww<8x~!B2SOׄ70erVlҀ _[HÏNvu@b]Lv+?ey͛f#zLh.ⵀ+cO[$YD-s5FS'ΡsC{>t5"jCAȟ3T."8J9FAx$LsiR\k BvjLʜhthXiv% _ ILrɿgd;Ŷ(d+3n<Б&@bH֚Onᵼk՚!'A8[*Obs3d2*)9ؘ/Vͽq ߟʐHPrH#gIרBǦbDlar0K^!0lh3+ o Td극Fdb]#\s.E!^ỉ$zP,!F +^7-"'6|4_Hs"F$H{b[M1kb]FuG-ots> stream xugP$ioQ.K23/!g$!BIBhHC$DB2BeD"#U3|=zˏ[iK/lM7F1W=9Oi-}B>=z'V&75SJ+i^Es@³xSD,닥8=KXlEVX8`P9֘e#0}$a(Lc1i<&c'cQ1 1l: fal<y猾+z.DE|1S77\];:/ùq t3> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 224 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-030.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 241 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 242 0 R/F3 243 0 R>> /ExtGState << >>/ColorSpace << /sRGB 244 0 R >>>> /Length 4932 /Filter /FlateDecode >> stream x[ɮ69Rߧ%l=KH-U nJux}9̋?1_~w?>~7_p}?~*/Wnw_[YwW맟?'1SW}S__2rhK.?pG|[~?ӕwG18_u޳\_{+~\W^@t1k]US&u{<:6헏bL4^П(/;cN݅8?*yykSʮ.{3Wkwww]WUaaƳ>q]]9bw%lh5RQ|it",cMrRs)zԵD3s֥w֏ z%aA2vz' U&@!竽r Vjg'ǝnP&Yֽ^;{NwlA^lPo$G v` 1ǖ2$4𩡓ws]NPk[Հ ՜k9Kl{p :K[%rk*@jo(d+y/vu4y~[$ӀZPc>-GM}hDZ6>\FMn,/`@w`~cLǀf҄) HV&EPBX1,]LZm+w\FMn.uM58зM9qzyZFp'!#7_e"/ᴁF{ˠ Z,r~xh;].&}˨>Or0yrrzoӒ;qj:tsd;WjsFqox"3Uqoz*`WiBz5UOu4*ӻi΀P5Tn9W6TsF cQVď‘QS%N|j蠦G$נ3 6T 0l^It/Y)>C"zyJ[;ל-Eܱ ;&X hbԀǭi2вUHdD0tэ&w~5dmL"oC6~irۆx^m崆E-5!0d0)̴m.:z,,6視ܹ =OIt/Y~ѳW_D {`ox4^EwAg@\?g]f\l&ӽdʋ1 wؘlA @`ju~$`:DoX6ilGo{/VM>2;0@*hvg`v][0\RnTUXJZ~ERy78?i(,'dvq0& ə+ Eǹ˘[Ԃ#0 rBtzWqh=hU9lm!~۴L;V0oȪ0^V%kN `, 9eniO?{M{*.3)Wb=d0MakZ"5rFSH 5}w‚6P7-Me6dɝ&~3,򵌸#2vRKې߭`ﴎF(3 O;lm!~[eФl-#S*'vXe`xǶlqĥ?]e,즆 Xثb%EqI FeZR%f8-JK0lVZOg[̺h])9vg"++^|>䡚n"EAKJW5*k |? 3[׻a D k+y3+vqy ZMв6d~hmf:TEUtf1ܺffaAkHf ㉛7C먝RT.UmΧs{oNWÂW %,RpLm# Ɔv; A蔳NK:]~irm ZҍJU![1GOQ;Z:jxƑՊwEgtJRTbk]&~[.tYrMw/8r/FJEE7F P\=ҥot@3nNK(V7OЧC.&j.Ջ݌a*Ȳe[5!w KκdsPƏaڶ_W+3b>O$g#}u.Ι\rzbK%-;!ObW_U=XKwdN33D~|xhwbE͌Cojnwܪ_t 5.p^_gUc=تAcʼn]VJc.EK`/E[4XXĉ^%A'N Ӂ>\ P&ӽd ˭خy4@ 4ڱDc 6LjNFaAg;oh\S+sqszIt/YU+`,:^NP!3QO.">+}J`}*͌CM/r@VzX [ᴆ Z$m ,;]R}w> /^e`X))\s*qt_u{<[Հ ՜k9KVyZ10U~E*))"iE)}qyLL-UҌsAH?P0i? i.~[*c^grYVV/:źQ`sŪd8rkdELneUJPΈh (t{ňF/Bǯwd!2cp& ݐx? >zHth2w r~ir[D_e>_pO׶><|vD腦b)=,%B`lCDd6;tt8ZKor++ E sd%`gZh<-/yg秺aeѫIz7TƃO&2ʗj"2n~Rϙ^ V+8"C`OVx_EXKKU={٭VY*veޢwNQԱz]R}핃І?-7M k.#e_zZXӢ6.ӾV7FSqm,ʛxW<65DWzOS.֑xhkCfoC6~iɭ 5 wuK60zaG{,%m#E'GLrt@F8@G7uXP]ϿYV5+=bePw`QdJaU5hz^7nYz .vGģ+qnw޲oTBTqQ$@{ ZG[cЯ6֜C.&w|JԗReW `b@+ҵdzPl8`>?Z쾬kr_@`QZ /r6P9n8Z˂w:n8hҵN-@C?n@`~> ¦-%V5+>5ZӿT ZG)?ZxSeې ڷ?XCUo-PX 1KA%IWY endstream endobj 246 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 251 0 obj << /Length 928 /Filter /FlateDecode >> stream xڕUKo0 W9 66ò]; kaCvzp$qI_?lq jE"?>R/.[r<=Mv$ ^nͺCq'㷦\?[ֻaliz4<{W493J"QIFJOwI1APuEf4Y1{dd$[rO_gax endstream endobj 225 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-031.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 252 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 253 0 R>> /ExtGState << >>/ColorSpace << /sRGB 254 0 R >>>> /Length 28331 /Filter /FlateDecode >> stream x%9.4﫨+(ҧqGߧs{:K?ρ;q?G[?s,A|=S)'zԟO X9?3ʉX| }Ao "[ɉ7ĶY'=nmWӇ=V{8r'z\xOUn7N8%{xpIpdɉzepwĻq8Sw9a'cG|:KhHt @,;g:9kc&GXG%G;kՓçA!y>℮g16Nt7%6Nx7W~t{ʉ1k(;{;ƉraWc{8߿ݚ|m~WɡE|wj[CM=+{)MNgzrVN8B1Þ16O#s+{ո yN(οrdgʉ5Õ{KrRSĺơB}bK49\0kOtk9㈽ i;?Л=jnu[C9%߱WMsr=/;vWos]v>^wNhq=(=s8ѣynqě&y_{sOz~yZ.+Gh=usA蚺X?[9c蚺#π)Ήq.ostsH3'z`ʱ'0+;}Fms'$ιL{'zq;Mk|6XgõlWoIZkݓb.n7ۊ=xwX9SK}ϓprxM7Λ [i7o8O7-7Ф'OCfpVqxz$vmpVo8azW5i^9-Jm>W.sda={D{X9ޖߣV@5t'zuU#&X9ѣ9|fݒ_Ue9JomDAoNsh h>=‡Lnǫe=l806 'z&KnQbiϸʉB55$δl\9F[w=9bfp =Oơ.h8?bӿqhɋh>烈 `ʉ 6H?V}kwbUNvpwSݣi" >sY9ur+=wI8 qb?9.m^9x^qHlqElᙻ1aV~Ov--y'֜?o;G=7wWčqrlTҺơ?bٰsE83jrBjXM|0 wS6Nt;}CSCQ7a6wijƑơtVC/`软oYi_qnsp݆KsӍ3;,aʡ?rN59\Qz=WKvn:lq _;7Ok;wW1 ιÛx(ar0={ָqxkу; =NC׫W6q.vnƧQÁh 6m 1m8BKRrP;fnkq}2v0ƨfp8o|78tmmj?q>S;=^8z[7uw i9ێS39| =VNpF<{+'zO07wm;'2Hٝ՛[yjaȻb y+X9MHqx;[M֥6WOl8yD/;BllGI%5C];N9Ӎ-=Vay`jb]9IΡg`;GӍ= Ch/f|pqC(5q οs>xῼS$~Cջm+c59X`\n"[HN8Tޥ6wE(صƌ 8_A?j|ʡO 3WcP|5pƶq豊}njCZO:L+?jr> x͍=z,؈X9Dʾ7P)8ƩT۝s=4><&G %tNڱ=3pEq0e =4#tu8?c[gd\={L=EƆ=z,D8X8abaZqơ,vwu;q15=k fA{եlOz=*m6X>o9Y78( kSja;'z 6vOY9%>}9GA[9=a4筭n0[9=(16çDbS&=b2;G=F|:n𯅇hGXn"Ͱdɡ0f>jf>nz4nQV|6ze{a$b=v;Gʸ&vQ}$Ԓ=&b+/B-aOΉE̞\9V>B=V{dox`KDqɻa19Q啽q8ʬ,A茨9fV2vQ)%19q"_SzAVϨkaYY?6{ѯXЏfs#|+G=Q{Y9ҫ@[VWǀ̽ppgaGS0#D&'za:*"+G1$^vᏉdav):pZ6{{)u#Mxt:1޿>)va6p_qBKZv-hEgʡw~ACgxv C30|û{ imݣ"fơ}*VGp:x8 y+8]&||2dGm"qr;oz^]8\0fzw}kk'zȂԜ5sKHX\3+mоu[:d>v|#~#Cb=ONXFGoijs%oc8>`(8oZ82s|gǽ;n+ơ6Z*?qh1zg8*6cye`z/Tn|nq-+֞hwMphm8V~W[vNuVMi'>=Vks> ]7κ%휏CAxV'K߿p`}ׅ}H˻s>jZq>k%rN/|sɉ_vnXW_9Z㻍OS;lakYU9\C'!䪜76KmY+6޷=hũc:{ һq,S:}r>.XSq>z[m÷ם2NwEK8+!{Y9J+jh;8WqR4o3mh;G{8b9}{0ds|`ԉ"73'| s>0oƝÿ%0aJRͽQ7ϝA0 |䛺wCCnj8̡ ?qfơ!GjJ;G*'m8Ûs苎1W=9 ۤ~AteH gDVd$aV &" O+0V:Cfȿeп?7ۇqxi/+X b'u^p6NNEMΉ1sqx;SC8/]$-3Q5Vo'}wtӣw9.x0^>W/qV~9 COΡo>n7a78ؕC{bz'qlqi9; dS=άkoUuciOֶ6QWerqW}ԊuIOK{|[IX_@ 8rZ_|sWzvuQBo}P׎}>2`Pݝ1F;8<3e|ຊ @]tgl+c=r#s@qab|}AZ9\3{81 v<8_"ػ$<ǴL6ƌN88gr_l01V9o{amgzw·Qe[C_-5+P\y9|l{w\&qSy|2RMkpOxb l>Y޵W@?a0y?2'\G|EGdW 6evPqip zMlMktv#`Wg[| gH܎ĿĕX1{n׼$BL/>Ќ}ԓ"@<7sƺv7{;W ÈUDd;|)+ c790 #cbo>휗eyo;+VL<4trD8ʚ];Si796(yQvPbJϮv~e;d/$eEalSؠ~iuj׼$[K~Cߘ90#A{^S0_^ + c8EIY96(s<[횗dy~}xFqc4 WѸOnæGϕ߮ρe璮@$^2'y V@`!:dEal/e[l?96(ֳծyIvcB>[iEv`Ճq:_ϖ[Xv ]cbo>횗dyo؟K~V~Q1p!R?b0yj/%YSAdo",~5/n{)9>  =w#ȡ&Ko18܎_ʒqJA{nL%Λ na:PJ͂|zND5fYQ]0eAvϋۼTUFCDȬw@øՅ_QKq됬)&Iin/VEm޾w<Y9JË9'ur֥,ؓwI%l C cj׼$7} 7W~BND_Ӹ3UtIߞ9}]rEh@DnSH6G/&נ۹Z-+ c{?õcḇwj},9HrOY#=a@>[횗dyoT-!.ڷiFD:2eQ8_=t yb8tGFΰ?ֈDn ?Zo: gm-9 xt;D̈]%eEu)"oV|k|lk^]p 8\T 8TFrћCh8q˄He|ӑc^c;r C-\0~"²Br.$؜ZMcn׼$;x"F ң!آvCt;qc,+.l)M:Ǯ]j׼$˷T2]c% E;"u5+ΌM#1l($bRDAEK?BUL̝ M3([rY# 9q:.Ɗ33;iYS-}cT INǾvK뼧S.Z97dw-bHs;,k csoV LZ==]6ysjD?kޜAn@00bݔoNaksMɊؾ9 #&eyYv7?s&I ps$KtQŨpl9\ qs_STI9@lG&K3zgEmzQ61JZ9PY/4mD#;ϑYn->'ປ0V}g>o[d/.,ەyVV#|Ή;m=?5mJR c{l(HhӃj'* 6='GˊTsPƲR]Uv%u[nY[e9J'!V@Dj4eEql-wx=Sn1>֋9Um_yfuƩQ9SaȱK~5/nڇ)`i88_>C N_ B6;^@AlrlR[lk^=o`m畃c6_4sgC߱dE]3SR sal>[hۼ6CK)]Vʓ6\َ;KʊIDcO+vKDD0gAD\I<3۲ zܘIծyIv7O3#V-ь5(b}$fonwr)ƺD>qQIX`iɁ{XQ<:+U} at0Uؤl׼$+nأOġ7+kn cjHt eMdE]i4gGZ8lk^]=oᏒ7$z;Q @W#J ) p4eaHɱ{~6=/n)b5p8*Lf hNLNˊ-,-&|5/ɮau1 Uf$c.)Ոxvd>c2i6L@:mVS5eyo/V4`Ŝ_D7%@i{d{%eMU[kՔ=hDGZl{^潜w˜'+`vz :LXflˊZġ²Рr쩫j׼$ڗAr8BT@5?"}*!٤zS9#ك3pw>dy܏p8@ABkP)j#@̮i=PMciTyYv^CW?WDfI uW :ӞJ3Aө72ۑ"٤Ɂ;eK,/lpr^*߮QC ;' #Md-2Gx+ݻx(pu_q¤Hkx(đNilPlk^]-PaEߨ/UWd~wPB9!n ]l5NK5u;#92o$=&[8gEmnHT%Er_˛R_nSTI{9I,˫z+lk^]{eT5&Q6zz >ю@lONedc=횗dyOy8>+ocP P.qǹ)߁F(h, j]g]:okŵ>cNZ^S2o %űE}aM7x5Sɮ߂pTD)O]ʊx*jbʱ38dy[3L fmvzM+`ObKHVh5sؓ hevK뼽\ae*ϰ chXӳ eM 2Yge,n֐l(ۑD ;3̓, @;3QpܳbdEeyr[ݪ;-dlk^]?iGģO*DE4}yڈ Cb>a?q_UkX'6';>R1ۉ`YQwę{e/\<6)yAv-1%qVK2rn>cvJˊ(4$[!cJ;\{Ȯwwp aNR$'; Arzʶ0-|9/ˮed9 ̅;FffI/}62a3ɶYt{n׼$'J. Ά8HB@DGsPW&a~|'`U2e9PHr7#ǸAl55&ә!ƓEcgN>ey ooj C4֨wM>`Έ]vx|689/C$>sWFykW/){T3J9_<`* sd~ǴˈA [{SOt%u`Yu4TitlTMy}Žv\SVT*9XU)*vK뼭"v"'"N`iF+K#˒-6ɖcbo>횩dy+nшqGɚ"}č@4;9֪iNjkT~[I;X7dAeDĞz8AYܽ-+\sp@, sz^ {f`F 6}ġ몫zmG;=ng5\˒j3mؤ[jL%[v@QoQ6^!AO1=37'oIV;9piX6n5&|5/ɮv_Qdq-5vSVW"Uߑ,cEƋ+F0h%RǞH~5/n76Xf9 b9AԂ"fU{.eEM8s1 N{lk^]e}Fr1^ % }B}w{ B\N>K1R <H 713ڲܓËeYDcWծyIv-ݘMqz[QkH7o-84=#ls^]=WGFz1?(V2)eB9Sԙt/qzY>[ey&ؑ/OZD LgEfi(3v~&s J{n,{+"&9]avvI6sF爃) ;1i  U16p|+5nG jFM0ӟx^@nDsYݶȊ- >lOLc3ӳծyIvԕ"bg`*ou2`bҺR#0lk^]{ 7FQA@ꨮ$w'R,k$ 9,EzMcn׼$eCs3v=;.'1Yڲ.AHI=H߿vK뼵0 Fdu:*JZb.0{ĊKbS/9v^G; u*+>ֈ+Sn,  ԃ` 32[SVfoqr*3ml{^=y#~^DDL^EH\)|gB,v$+/Am)ؤ؛v%u_ΘPpiJi4=uM"3'x]l=lG:eM! K|e9)X:l{^=O# D)4冟欦UˊpNbEps]V%u޶wP/+Shfx>f;PSV1ZLeCjcbo<;1]=s3fr x;#;HRno\HV2pzؤ[ j׼$˾|="P Yʤ) ?J_ȭpPus/$.1n%Ʋtd=(B"g횗dyGﰇWsT]1b.d̉nDl⚜ԢEnylk^]mJ 3.˜VhՔ-^O$$+jeu,ƈdfIJ\c6o2H?CM"8ÀXƲolo$YQ}NV{lRg6yhA :swbo8o(^B6+9)D=Blx^ '@%MdFu/mItIJ߳?θ6|VVIV _% ;3>'YQwZsh~,c.=yYv}ȄfAmkXNS.FLeE̵4&R[9~5/ɮv2bԲ28hq0ݼN ɚ*)sZ&G-fl({)W)(8C'!J]}0I09LY-Clk^] E[iK9؃`nјN@[uka>p 9ڪV9dfr Jzum ;239:d ȸ]?[횗dy{u#@ADۆZp S$_˒-jY^,ȱI7vTeI$SOz#! MKQ}'kϣj'eES䬔Z\WfEm?e޾Ww (m?e&'XM qq55o_TJr)vK}Bňs9#\PTsp߲sޡaovG7^)GBW{^-ڛgQot1)^0a;Z918QqʆK1G$k&4[횗dyϬ̰Ց:1p:j흲FF;eyg]:1t>|;}4i\Q[M6cKˌ-[uHYg `YR:87K'QeIyg5SɮOWM;9nLL9LnhQ޲jڹaic[j/yԿE[7)Ѯ~.CojH~`BDQ_#tbP㟢uT%W;NԸ|5/ɮSB;Y90fFm`$|o(ՔJ_Mr.FSm=6)ݮyIvﺃHU]7j,CR?g;3-+f sXԲziծyIvmð<7V;~KL0m_G eM+NuChs쒱~5/ɮv^rs۾Jŝ> ks߈R^)1,HV%u[b!UI+\(8gzQ+MbRJVԬ2b,*#;ծyIvq#as0oXsDǍ=VЕ-+j\˾yؤg}8'd$9548j kHti5Qz-oʚxefRj̋ۼ%puqZ?L;b݌D@+Y Lf"3f]TXF"&r{#S8HHO{L5»Ñ~9ZjlwM^5SpjqXGm{n׼$Vrm_*Bgv/ znYQnj% db=nĂֳyYv*=BGqL9PbCWT:#fHUn?鍔 c0q(ۄñIٮyIvXګ0 R( uM{NaX7lZˊk (HcI5;:t Ӊ;k0hXZGnԈcje7\s6Q3O=)5&84Xݬ~fy]YYy5[Q@Tf%zu1KzR`2"9V5|KwoQ|l܀$+j""┅2cbo=[횗dy&<A ~5OZh][4$}1?;D m(Y9p!t J4e}3n͖3llE ]FvK뼿ǽf<ԡz{{Iq`#N?YL};XGu0`8~o`o,ue9AeO{s"nL% vX/VO/VV.b>x%5~I'}5؜ea̱[slk^]-g'HNX-2.O :'ρR2=ҩNm5ʻnչhKu";2=6nβܿAm,M>[횗dy9 0I| 8E\9#''ib~\^=# !x':HBZjʊY`Jlk!~5/ɮqju?/N؉oXc%873B$+*!*dylRS5/ɮg1^9t 1& +ہɈG|zS?]*3k*Ϗꈨ|x>7@6b_8`+t3}Jh@Ӳͱbd+S5({˙ey/V ɂ~*L~ɚ[ٞ_!9Y,|9vzGj׼$Kfx L4n$ ʰWtu ]4+@J7P)1We3[N`>~$OZ Y9]e(ˮ#YβD 3Ճ,&g]:odV},W>Cp!s+ZDx`g֣v˲뼽V)3@}"3"֨2B3_؜9- P=\M9vt̜a0jX4 Z7 5 E]DU.S0g#g eEDt"Ѳ,?IY9/ˮDY4lDxL񖏠loJ1ߢ9c-jL)۞S?nGkJu4=Su@/܅-Kc*}li-Y횩dyL~8<BwFCTAދ(6Q-eE29a{)~xؤ؛v;eu*wb _B+o( X"팊U`G;N|ڻAv;Eo"@b]4nu)D43"A q5#-LG %9^ >O!"rIQ{2>dITڕUʱ%j?R|ml,8ԋ5bIZqdII,?)([\_ġ,##Iؤ؛vf*u ?9bȅ2p_i)\D1LleXcg]:/ZK{XCe+Uqg:,%a/z| ZaDp($9H0B$ZrpX' T+*l"eE-06Ӳ5j׼$ەO܏t9qaAxHE} pln;eM ΒmBϱs[j׼$;ZfǷ5:Q #OYQXN 45DK~Ԍisnԉ@s•O k¨ű[yr.ؤ[VgJmޣPOrs#)nFXvW9N!ˊ 'e9.S泅yQvhm7+`0ݡ| z:c@ oB&&//+o,Oc^KhEٶA^go\!#f.j 'QI*}npx­?"h@{>D84BI6x#2t ht’y3ʢ`A(ya|&3ml  MMcvcLYQ̉XO OMls^] Qa5o "J.V ;3)ɏu94!gYR;}b=6)ݮJvwC%> T o:P(ьaDYG.j'gtő%LߋK1v]?i]ˡANdW˿tMOc|n}=lVH/D^$TL.8'3"1okG/'" u33 vY:)kFZ<-Ivϋۼ_%B.1ꐖ2^%]:dEC<+ǵcTݮy$+j$9HfHنy1~5/ɮ\_Q+L3tV^7KyehlA`qup 9=n ~70f\e!SKt.%e;un,kd9bb96)lk^X/h{N٢6MʷQf;+YVTI=QcJ=5/ɮ6O&&He rgԎӔk{β8ksP=6)gijRv NN[X8h4E]QGcZgbYQoTEsV#˔m-x5f9oqs:m ӌcn x_"E ,=I3w &~I`Lμ f ^ަ ^g0@w<µI6`ۤiHȇŭihun&ߑ[e. _C2rvX>cC 7lO(^y_gZG^]űm~A^A950lk LspP byb 9Nc2Q4eE g"%aYƥxg]:8sʇq$`D[Q횗dyTP|ΤL_NP<ܪ0*8G7M*ʁH FzxCڏ>wwBnBj. 0|}Лcwpr8T|VaQA!sW&; 3zYr>+^}ST:b5NYQ-ƚCS&sbo=;u1/ɮvC0=5ܮfw;C<cbF&[d D4{Ί.F۝4֨"af&˗]_^lwjYQWmrN+H'F=V%u_xcܛYb@~_h53ܚߏ?nqoqIٝFjGf4kHxI_F2]<6nZxX7٣N{#MA~)s?4 ~5>k׼xjKh̒5ud~8qS,ɱI1vv;%mRCGۡOadfiѰ,)e+ Z<6)\'N9qBNb_V^x|$~}ե9 ŝ߲aN=?gp͚16/=lݕ0"O!жMǸ i04")oR»#bYViЀcY=+`j׼$o%DŻڮ<60 LFAaXL8,GC QX3wI(t86{c_e/z+ulc@v}'*BjF:<׬f>>)t+:_wFا#G'loA-S涄J]oZ~VR:P7K·UUGVc鵶̡wαKVծyQvVC}a΅EH`z"g{@;k,+)s`HYXrI>[횗dyûXaYi-ڈ/D}9G77ٛG̽r|iĹrnn6M̼2ɨ8}g_FR1^EDoKjg-I6,8>ꉦY=F}e>3daL[+ma~I߆M[FdES7Ve}g]:on8@tKKݪ a[y )] "lD|® T.9,L7с@v@a_Di7WvQm 8UGȳ0pm0 ʸw]ˊi0%-˺{֥ծyIv7U ÂYX'nf|hɬ8$΄0$O<`X9YI4r+,D! zn;le=ꃅ?:|`2$]鿔1лF ѥ97B~_&7"3row UD WU|f ~i/ӗ&g?I0E b6^?R%B`̀zyGd礿ed|qݦy2?Lb?.ݯo!ts h2w:ZFP,t4F+=aHYQ-Nd gvK뼿゘E{"5YDMc/ jz @f!,Sװd_u_ʇ_ǝ1 :Pqێܢ`1=qюmFI݉}g x#c"lrr^kïֽ~?{r!Ѐ7-̀_ ީvl)+{9 R걻zlk^] rP_rMh)9XqN!A܎MrbX O-RN++`̡3TU56 ٮyIv7oѫz!wzkpdᾴpw#Iw{0q| giy_D@Ϙ;|q^>j D Wt]t^0D(?HK#y'+{c{F "/ɵyb7 S"/ ug%$s.HiMYNO횗dyUS#q۽m69x[8mI;z&',="w, SX(8V?"Q4!aUK2Mo}fy!.vؓά8o2 DTncX!0MJķ|[ɇ:hT+PuPmJkxL߉`B4Ϳ6#p 4lmt 44eFh?6C4UGHH's7ݎ459UE,K#=lk^] }=9c_D;I|@ >fܩBXss zTY8ҭں;{dgO*?Ą}lV3H[e1t U$َ T2I#Jތ-KiMbϿYuI< f,r5wf61y~e쒮qotq۾0W:k66m}؂T!Gڰ3nZBPz#/?̱VSw(!U` xIΗ9d6rlcUgNiV n_3>Segt=Y'ӇL<׶ y6eP{TAq_~q9Cw[{7>X.@h 0t/jIދpύX&ls:|YMyz]I^>W֚@畵~U^{=ldw]+q\WFu]5f0kGRdSH:N{Jc [8 i֓;Q[jDmEzU'Mrܵ7/˻4פ}4>s9qV4|UIU:LPy%ͮ"*ݴ3#p=YC'Wϋ}ѯtx Gc񁦋ZǤ] f$/3Ϙp׌ gt.R.>?XճK25i:_`TqG_'>/ֈ}>t 1iA}p gY4DWцm{97+K; =Xc;mwQmU(7?ii'Iv##۱yq.^iGyL~R=i]Y`žbD5R~#c8i(RUD͊DT?#ϸ[o"#g!{t6bl!YD_!ZG|@AcD>Qő4hqzp$H_yIӧLƻBLwC]f&?Pmі;y™47{u ]g0H/Iӯ RA0W3cжHzrR{N[ L"$:X®L$G #[*~l+V V̿®"7Jo7u6[yT˾s=i5/V&M{Ϳ}ڠ>랴}$aCmQl؏LABE[ŸDn;2#bgu&/@[8'(|Q#-E.iaz%Xt#8DӥP^sLfc!VZOA| CscST& b EISo9פxڻzL{& x\F=mZM9j (eEl)۝Ժ)ֳyQv;s0W~{ ),تLY=ᡝ{BU Ў}(xҎM|`ю-;pwL\Fݜ1SWș:zB}:d曦.~O~ 9f6J)UƸ}X)n@b`E8Ā.(}Z'G>1cX? 1 {=tYrXb*(握#r}qu剟Y ݨlWۿ5&͹!) XeW0 D Z ؊!*Vv{IXZ;_v]Iq"ޕ2 FV:rr-> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 247 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-032.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 257 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 258 0 R/F3 259 0 R>> /ExtGState << >>/ColorSpace << /sRGB 260 0 R >>>> /Length 16017 /Filter /FlateDecode >> stream x}Kun]L:~tm!iKkϔY|!#ij͚U*C믾_˟??/;O?>M]^=>_/?O?~wrߊZY9}} XjOW偤j_򪔒[y~7__^%W㻖/4EwغHgUN߽=T6~\K>rx}^Fٔ.`/~_e>4(ZQPkVΙzڰs$OliݨKŞi}u~?osVv~u!߳,(<>TFْRbv.՛~Y|(塖)2L]_y:Eyyc}XPOZ;y~b&xْR`/Y_=_(a6c|P$nԅn}|AA7kG9-%m견++}Kgkfu,OMY|(e|U XRЍ6H/@A(rY e7t5{ݟ7P݊ן! u{!߭,)׍) W=,re7bϛjL F+㡞V+jrCJ K7(eKַ4y<LضQ+fځA?ZĒZ:rVSf`( JM9"[XmG7XYjB GnMFfXw.K*Gb~ Oli۷VD9Oo?/NG4+u0u+Ϩ ˦v{٭=ysw_4k06w͙6>!x<3By OSK*S_6\Aalnm)S DaΔ#9tbeS.Kַﮓ>*}rP[wc֑?48u J5/9":ӖC9Ն<6(ե48uB5A.(rEeR6RV鳞R^~WPw9Ɂ5 }l5tR]liaqϛ̥0>]NƏ.(OC85VԌCaY`;Jnyٔ.bvXj?/3)3VӐ?L,)V]3[a)ݠT+[rZJL 9paf357s%vɽtbg6w-9-%m793>>/!ڨ>4ֱEgQ|4۟g!3AA7ʖg|^yZAVs K*َ8g>t J>}i){jǼxkӰx>nQ=r! + S} *rY ej^)N·-7-J3=RXRg^)N؆)ūlioO|st?b'Aa<Cx3U}dͩ~lO\J@al|y'V<M}`w(rEe:hs&1rIu+ϟg0h*>Bob"ݠ䏹M9"mRoڼQ^@ƺ~۪]Ȼ}%5c*NGS# > eLݪKvAc߮$Q/y OK* ^A>sҶB7(ܞv[uIaw.iXp,~d^ׅߖXRE$m>vfn,[rEn]gޜ^y~ide>\ȃRGn^,)/8}f뙨e)'ַs Ӆ2&C|K>r +jh Nxoɲ{|%+uomlp|&YtR|!yĒr݊v/."ERfQ6 Wl|b&<^{M A1æny%i>TBЃlico\JwANYFgĊrx|}䴋ne{n_ȩå+TgE{Gޭ[tf(iZٔR`/tkex׶XOYoM"= Òo%zo֍Fْ.bv.cΈy8>6 0X(}6FH]aEƈA)\v5`ݧm|^U&aCt[rPn/M5XRЭX Q68gشFgtS-|]؇zU ;._?oNfH>[ZZA)y(VXQg vx'+FV-9mY/Y/o-5/Q(/i bd%Ǣ')Ky%LNV]/YԔ8zLˆ9 J{K>38Of% Jb:rEeX^}g,.6my"JmŽn=휉EWb{Y6¶K7b}'m5t;LLMAyyEInkABْ.`/_#/4Z4s16@yoi%UOR4_zd]|pM,[W<H5*mOyK>uaK U9>JߢnP?l!9-uysW̹XpoBa_土+*i.&SX|Si䰋nSskSp?VEA[+)+*hD ϗAAwSr%necf(Y ²eKz-aIz&էU J5O) n u`3h^Ɖ`sר&bOAὠliwҌchcQ!K ir̞XsV6Vv{} e{a|ⴰװ<]DE2g?ΌZ{b| tn-9"m V|~qh,,'Qjs܂-z4cvr:zutόl^gOwH|~E [4u*rEn/!trņ`} JG>4#;{'ms&̨گ?䉚]¾>cMR8}0 [P_Ƒ?VUc/.ݤ[|ioU?$g30:nibGW;0^}Sc[l]ItKn+q7,l16?l$\7&'DbliݬU"NǡӆeXZOS^&A,8 GyR81Q-9J:}{xEZڷgƊ3ec\ 8KĎò+(M9"ԅQvG·f@vk/Ċ:I'^mA.(reژ/6qq2,fmX*1OS>|[XR)w ~#tRCaoQ&3_ @oEʫc%ƊaE%yoFҝb]eSN>߾l^Ꮡc3Ux//c!,(VsC>_z<cv. GB{_!:>"J_sGtԪCiŁèlioƲϴ)Wc:v WmvC޸ XRЍG3e[SnPh(rEe7Rqr WDJ|9ֽR`E}kSlaꓧuCMf?do}I!pXR։SpecnRxj,ɾY✸8]2Œď܏ܶ,*qNH:Jw9'~Y䰋na4ҁ=$Oӵ97}ڲv⺼` XQK~p<,,I7(ȭ*&]^vY9}m@ؚmtPh! ~žK 49X?\/;n}/UػȩԖyG6O7yԈ5b8'+l|6B.cX!jqJF_ NW[OO(%hĂ1΀lҝcʖ[> Η5_ 9`,60؛މcRXRM=Sp<(X_` N{ِ.`/U]l$7:Ka%g?-Bp<$ȡ=.`/|?ł@ᘅ b|jR+NO" ʖv{٭qs0ܗFBτ8kӆe8}C|/tث%]¾VHHz/qo|[RA: ,N+*nK,1ߡy䴋nCF\Җ|+)AM|qiMyҭ>-ys|g`֗ vc#AQ"1엖|bXROw= ;t(re1>?u"8gt7GٔO=m3l,3R;V^Ý\.Jc ʔmtc|!`Nltwj+n83\/3ŮKk u(y[OK8Ol녭n_ę^|X ^qsPXcX`j1CzVIw57M9"m7 `-<_KY6AcP6ZXRKgy34&1vlioٖeydq/X_.OSsnMmxR^ݠԏz䴔طݪ'7CDXݾ|oN(,H8G8a[k ݠ;rEe|~.y:xuf;r$A-”{aEu`_Zn"Y6 n%B O΂&5+ Q1w +*L/)aLݤ4Uek;ËϚn~=Y<_~(n NBڱHQr:v'kv(g9rY eK=#3v #Tq dJ _ Kttk9 W=p}0bPx/rY eް``_kh_AJ}丵NXR#2im'RwܣeSN}}οr # 4܃R]O2(kI,\ 51D:(]^v{ɱK3EʛȧGzN q1B7(<)^v6;T_N+r<[.fQ>/|#>K7(<=KQpx8q*ifWQ?t ^49S?;/<Ͳ)/\QH֠ϛ&4PQ(YF(:ǡJ$%NM;NltG(rEn%{:{`偒urO Fs%EdEAWM) neb}N2BSyP߯rxXĊ:7c;?z֮C< aݪKe^\OJ4/!2vH5E!4\#❓B]P6 nե{Gɱ33뿰㗷P/F+$bIA7R=j`琢)\le)ݪ 57~8B@.y% 5Ċ!qPױNliݬc 0S &UGJfWnA7g88a9ScْRb/.cʯu9pnmt]6޹7efvаbmۚ0lX[<~3vIUWNyʶIFh,?O/gG2n>]r :R_qLA߸k/o܀HGϬ!YQ'e\p ,n$nP?n ʖ:]ఙ0W84{>TSg|yh#-U’:)Ia/(H7(FْRbv.rqdϧco WoeM%uR ̖tY6nec-RƑc`rMRXPq3*mI7)˖\{ͺ4,qlwz[)=sc((y6{If]~DA.lR`/Yg&Ố#e8 z~dQ7ꒂu ngdXR'e\p<ۜ[AwBٔR`/Y^i>ok0Sn'U.96`+*N_7vJ7(N(reꂻzNʸVBEXdq*ՙK)ę~ӓH7(eSN>XSƉoTk{haIq 훰H ''eʦv{٭H?g~C#B#@^'VTg*Qk-9Ӱ{٭o"i ΰ\&.臚6)"Uqov.b/^#2.8f:v_chbӈaG⮅rH'N6{llc*rEe7ߋT -}!QK x|C':)[ nqʦ\{ͺXw]^)L_­4һBy8B$,H ZqMʖv[>Sq"n!Ԏ-OC"6][7dT}y8 s?RqI\paq ʖv9[sTOʸ]OҮY׮X<IR16HG-$-[tI-ndGv {٭8 r%qKPlyLW1_k6Q^pPXQ2No)է JсQ<+BM[cW2N?tA)Fe)'6Ϋb2N[*3T}I}r%\\ ,2.8gZrx!^v. WDʸ4{ʣf$LoMQz:koK*RƉӼ Qw&*rEe'P?f ӨUD[\rxp/F ۰jG-.Vٔ.b/5\)~`cݿ(ÞאㄛNʸ$Xz+Y6Klݯo*>m")U嫌9V8֑%6~gZ+[rebNJwǝ}~8gw`EEʸd]{O%]^vk|J^DY^,曛( 1 HVI,2.8X% *ƮrY e|˄6)̇+d[֒DZ)Faiun%O=ݪKFH'%?w(.[8*VI`-kݠT r9-um9)'YFÔbO`C’qa_+5U.`og]y8~JhHzճ&~g'VT B$-tB]PYcF8qV0<`Ei}t[~%uR΄>glVٔR`/O#{2.8F)y,fcu /T'6naҝՄ%ϊ9mb~+e\pȈ͐*.ծٵ&J֍#XQ2NK]l+M ˖v{٭D馺F7fM*RG#"e8NX#s@eKGʸ lMHāycJn=q`ۛ nPK "[ .q٘g~Jq˙)iVbԢCnF H'N:$ݠPM9"ui oҰVa-g4B]VTz\I7(1v y uxvzP_+"e8إ/l֦Jŗv{٭`M椌!m왦=,O/Q7Kꤌg'_nP ʦ\k\v.>| δ [ Hb XQ2N惶Tu*rEet]Ae_EFKݞt[cIEʸa%;eS^4qnO9RƉS}[y{tMQ=QKꤌ <,bwҝ_#zٴnxÀS;FáV_F|w%uRIكCw*rY ey/=Һ}ޜ~ya#$SqBXQq.8 onP ʖv{}qe]m~5g#_syo+*R]ba*ݠ4} ӏe&;X\7xQt%OQ'w8&,2.8nf^,[u2.8꙾UnB=_I>Kʦv{٭p_ '67_ŧ%JK97+V8r6 @ɧGf]l?su9'g6!!1M[ӄ)1{RlUI[]^v.X>)MZf$6N<|"^L(8?+\))]^v.i"e\p|Y]:?0&ciXQ2N]X` ݠPM9"[u餌 v̈́CyR:HĊqL?6&;ˤy?rEe˝2NW5E5|L?ID ]\/?),2.8c@ g\)^v.f;Zpi9.n))X H$mq}R5tB]rEeދ/_"// Y~׶n|aNW]=Mc0=ʦv{٭wRg3Y`:/EPK!VTgJA.([rEeҴĔq1'ZI^s/v4~RUXQ2N^؁/A.(rEe7벛'e\p|XgB3 ֮̑fJr[)xM~UAy]X68 ^Vu8H VlֻދYKꤌ _<+,hHI)^v. 3H1m,-x6>lf^km@P隿W`=aὩleݨL礌 v0z~iS学4`l2H'[VPA.b/U?Jf# IHњFKaEE8q63 ꇿ^!]^v><2b! ySA,4|;HXPq7o"&uXcn~2.8~OFp?~u#"e8C.? ݠ'[ٔ.b/JE4!RƉ$p*<'gv*PfȫoIL*,H9%{8m9)~[i3aG0aIq+ #tpRv{'e\pɆ]>z|O:]!_ֈuvyK7(0~ڋrEnBFM?m ` d;K,2.8^׃;ʓʦ\{٭6V,RsXH g6⤪cq!aѐi6T +Kݬ Oԟq$oQ-JnJ'm>AEʸxra+Roe53e6O=Vǹ;كXQ2.8c6r'ݠ4߷)]^vEʸ3n͂B8 yAH'NaanM9"[uɸO=RgSݒQEɇ+oXQ2N^kAAEli^t+e\p<ӱwgq7|9 Gr܂.H'N2b:أV䰋''Z䌄 kW3-fq7aΡ"P^;iݧ. ´FOgϰn"zW##&C x#lejcCi:&8Y~X`^mm٢PSXQ2.8RǞB7#]ľXY")ę Go3)uQ1#uNʸxLsvPV]HT5k)~us̺Q *R'RŽqAicoUjqao2ozDO>/uAyb:)Sa=H^T6Se_*ZU5~d(#YͰNʸLv)^v쎴ngU|qKwJK6ݐ`rVuRg^X{=C#/_}/ŷY]΢ai]))2"e8R;}t|F(rEe}q{X,v*(o/X{|pxbߢ&8+n$VT o$mMJ-r#]^vغRƉbR)y cbϊ}W Kꤌ#nMEXĽTDvag|2.8|,n8ދaq6%7͝o#w>H'=T8k-#vg`Iq);&SBgeܚjrY e^Aymڂ]!/9g`ұSnR? ǑR`/^r N17v6"e\pp2y>-JG p%)S}SN& egOoqvSߵ=>J>p("e8uMa hMI{9"Ilτ`܊~))QvcĒ:)a9SnP?Uy?.^v}SƉC;HD8I 6>qNq-9-:+z ɏa43Mh(ᾨ#祰zܸ/N+^/t׸LeSNV]< Bl]QފwfoB1yaEžง%}=},[reꂱ7{ϛ3ڙg_VTۖI%MMA.([rEe76.ڊ&XpMPY#nף<#H7{|(v/կHnP?l!e#V] ~^IMbGf& ,)K{fƲ K{muWIՐ3ՏߚK`g~kR.ٵ[r \=2r ׿ endstream endobj 262 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 267 0 obj << /Length 924 /Filter /FlateDecode >> stream xڕVn0+$ bDRk%AHTEvȒc*]P-5 &9{wN8NE,JR,, ca·'sI6.n6"v޵g|LY..˂;UW,ICgy|qw[vzs}[~JXYLdvg.=? {-Am[뿥K)Џҽn{ =g]~D:#_,Jct|;X5*ѮD@Uޚ(_׻\ F!hJiscVܙ()6 M':QY@pH[_(0ρs@T ~י^(n-BPqst{H$Cą^c^_t%D(Or#/Bɒ,\K$kdGeÄ: Y.:| Q`XEQC[DEe[ӢEnj0@4M$Q\(#iR7i1Y&cEa O3&5j(4om]okO춘T+n(ut]Oӂt,6"gB&63lSO]ӘƏf!zge4XK<"3Sq VeĬ{gfM%i2PAB(7x :ۊ\5ûaTZ4AjЩɄN,)Gk&7荮HEPk}𩇱c>(,7ĈkdžZP7tØ~6> /ExtGState << >>/ColorSpace << /sRGB 271 0 R >>>> /Length 93190 /Filter /FlateDecode >> stream xMϭR8?bA1%nK W1@P@wKǵ֪DG9VU.G\ί?}߽yë%j?Szj{??顧?OۿyeKpKg[^}o~?^"m3˫s?_C?~So)&w9PJ]ӗk|rX}_eOGYq?6J ?W??J_,UkS `dw_~roz\GT=5ߔ{yPB,w{?%%2el+鮩z7' QQϒ -ԥ?< Yye;}%2MJ+[ &kDkjެSƯ]vmf:Js/~g!ېN{뭺 .Q}P/6ʫ9Qd+7) &VSSRQR;m7O]jBjtkI:s<;dH^V] 8IꟗZZj v?u_WPr ~RLw;KWh]2?KX3Z:HZ/Jt ن;72ρv.Ay:A{zluF CVCd#SZ 3mHtxoU#AfZ -G(ovJ_g@ܤX]jR۾ө))o?k~qJ6^<ˑ2tFQ_ZW(O$l܀l N=ҡxo. _A}Lló u>+Mև$;ySLwM;>ԮGҩ}l;c{/RwZۺ+l{3J>f+'P5d_(۟F+ Q6(o9s6XٞNR[d#S' VYֲ֫~fc:sb{%N[-J_fec'{lr6ϟ M3O?;+}up(OGqe+Kcs^,(O)DdJ%C5AY-˜{Ei5xl^SVeCޞ>lhW1h7Eݖ2MJ_5ʎ"Kǖ0J6?O+Q͞{B]7(+نgF {ߥ]kBʱ03D^;#߿R!oK_X6өyoYYm]=_һ>!lg_қYHQA[l"/*[oV{}رkyƾc0?쀀Pt;t^x},.{HMmܸV@#ڿҰ鶲 a ])2(ފʮy*w%]siwY̯)$ʈ_y娹~]=x+,^mO֝1i/?NY)gs/UtgI;ɾuq4G^)e%R6|2] [z yYn'ǨWKފ+1+KBեV[]ߟ 5噶Z02a##}EQYp &-iwm& YS[fcoBZ)yi=&;ȺlC~#z[vه8+lB G"ݱ G:{:jsf65K_Ԅh[/R+RӃ:ڽ4TCjZ"mK^Gb+-*өWN_zc|qlűd&f^!k/QqcQ3jjǗ. #O9%l N t,@hfn7ۡבz(-M^'.;zf:"ﭷ08SgeeC9_'c%Ždzp:rSR a!;txo. )ˌɺAgw@n;}%_ӹ;D!SstxoFu~JOʀ7Zvg=; yHA4+x',=c`ٞ^fzG]簓'e~H_!i[sE^GZaX9;m#F*鮗zWa`\7\$=Ķwpw}nA1}b^'/rKzPj^AP=w>b'[־b{r/o誋SX㥮}Յe{])z.}r/Q3# fi' u$K(9M.{e3k1MdqmtIbm|>$Qe.lJ!N3ҩyo]m@g9'x= %}Yşe^RۥݶuT6J3sf >*ԋ޲)%kN;|R̒ܰ2H+HGA+x<./jbe32[o%-ɢ攷 ?~JH?b-]txowOUJLxJ𔨶LJoC#EY;~ yQs4sڵ{]Hе`u;H_=x&~m+WdJwz<4ZrK/<ÓL!7Ɲ~[l&=څN׊t״/?W _k4xKf'ktQ |I'%ﭷΒd/tz)w^g[D}=}%5}\v\e355[cg>ZzRδ ߻vyEzR.ofX[G7Yٞnzӯu)Gg] ^Rygk';]ܿ}hOJxe鑐<֞~V% eҩ?%lZ/țk]tv ѽ iKoym<(/m%;uU6]ھ>S>FJ~v ynT(/`؂:]ve{:a/o<#ٞRnPfvBnnGTLwM[u+8b;,PA"QP:O7D%S1[ಛ٩l{ua.Ծq.򨽥O6%2M [5+#d_e{:5K+Z:Y) '8 /G hw(Y҆v3/IvSL^f]}t_kQ;Զ=NHoK4=(g+^=wԥA.QSEMFnWNmN+pkW\ߢf:"Y}SWZ?غ?utD_I WJ=VJjw|륦2gmt@jgbvD;#\H7#on]JR2vsй8bM38/Q=MSٞNMkқCI9ݳ:& rwkH?:.xm\$;ke32[y3?)ǁAgFII9Qm{z3Kvѽ$/ԋު ~Ck7=vfSӡCiN=xt袜mx#E/鮩z.x%ygD[[1ik& 7mM+/^(Vs↼dWfVU-CMj)pV3~F}^*/[-{akjǨ% IHmW>s:3Z:5WV;5t\_zǘlknuabİ_kv_ɯUQ)(y3NS)ې~]3G:"˳L['Uψ~ ,v g?,3} v~ Wȱs9 [jnGFR9"2ϥja8Ya#D~ šrNb6nsd%\z8s.}e_26#Ěo0r0o: ~9.7(X1Uʺ ģr~3a` -Flޕ#C*[ aU[ewEOh3nF˱yZguuVo;ֆc!],~w{tr4a9G w5Ԃy'0rTfU{9cH !~ O#AЬi W@Kk̞tBRcjИ+ 1qTAlWz)ÆM6•c`0x~6E >pWm8ZP 9bhmcm-

    tAcUarWԥljg]KݗVo KMVᙇp&n6`a #G97[%"@_3c酶!FjFbd2 .9A|hvBhBTҨgX{F89֍ZYH?M b FPOjS[^mjnS6-Q2My#Ar BM0}B]E zrE`g8O!dHm.".7q/'.Vx\#3%+q=[01,)XL+3ar\}& $ᢀ5:tPUytoR 'FmzdpMBl'$K ǬR-L'9d8d HRPA n|9 CW9(ւ6$PSj ==6ٔb,a䇓oC@ r׺0rl/_78G)%+6VIMkŒp5Ufk]0#;n2hkMWV.Զ,9k(K+-_/jm3 m]C2CA̱Ag8:Ymk s'F6G"O@bm-uQ9N:24{h-Kz4 hM#B7XMX0=w6Wht n{ O@ /jbGs0Ma4rl#[Bh^A^ȑ##"F˄ U҇fh?brh,=ח[ʍd\BUmC)m&OӂׄWqGZiaҋAa[E9ӂcFƗU1/_]uٸ4: N!®Xlm aE/s2.9`7%(CU}cs$<#2gUU`7: 2g4~_eozXsb%`% ^Ǻcދ>͘l3e$ݾsrwY=̄TBZ 2ƖU5>|>Y5PȁB=p{Q+(ys}TX HWϤygwߘd7VGxjAϰŃvwYS R^@3Կd1чH3%q~*xlB@<}Ϝqtxr0Ra!)rT}/ΈyhMԿD+"g g8}e<`?&db v謍xfC3@dXz96V'3}V(q9JY-f#,<21rkTƉCOV P`}Rzq[wq#QǾO(8 ֯~cqs,XfgkX dY^Oȱ4Nxzaސ!c`{X; q i2xj 3G1.%t~v.Owz~Dz7a1p58[2nk#nx4k Q3p0~ !b;$TqPE !F.vÿCjO^5:4f|#;Ƹ=bR$mnN 5ȁGslX'榋fa pMݷRZ͵9G)uy`\:߆Xq&7.]~p8vp9 kh\51x0/^'WG+u@r lY_i`9rtZ$` "̵q +qMa$څ+s7&b͓ ҋp V'aʵ N {\,XV)3pX&UZb[6Űӥ9OJ-ps߇'ϾP+.G÷wn#WK-Y<2X axgUz@=pyZHcicphӔ. O^2F˫*"U; w "{l<¨[2jH92}^Mg kT1? ,3zQҩ9=g=hj5hdYΡfAQ a:Ҽd4v<ƴ}~(vd1Nёq 9*F;ዂbHA[勵sؽ Buy[ gw`&-]p^k-^={F,^b |CN+sE>;rǶ9Gfضπ?.y#7G†d!R, /&=6;5wW[;솎yH0 >Nxl= (#`3֤$tFs r~FK(F{+!"pbԗ%Euݚ2h rA?[h \w -cŀvcecKX[[͹sPGR DžE)<5Ʈ흁mQf'vlg+R`2^+b*SXˁ821֗~ol9K ƾ,1[_'Qd"R۵byDX3f]쌺cI풁goǩ_2CƱ7.[uatuiV]ΩZ[3Cna!opi<@b ϕÃyѥ"BfXeE5īI~?#k񫬈!ckҴVE`C)vm vS:RUȊ|;呡=)jCSԘc7,1#GC8!6?wcd H{dg@5~VaKq,Ng,eai:BЃ8RSuiSFA2! q7府i,1!䈇MQ`C1+&F8"߈v9nnkN:ϔ#k~2#i7<=Ƕ? Ѧb'+rh'(G!V%Qn h\vog*5T'q5]fS# e n/9\%Km:_va4k79)1xө]طYuUt"#:TXGm~De vңؚ֣Tڔķ#z%e,ao|)s 1|m]%Vm l=U1nɇ(.a'q-}s csx3r`z+Õ8ɄY+'p&Vm'zaV?=%R.󀲡khCD6腌nAo=e_2lojt'wa. pb2b65MBF{`Bbؐ%  nDb1ca䟈nݱ>V/=b]9:4Ú jQ;鈫N  e.GG.y.gܔ"Fk9W)֍Ч 9Fm`E3b1Q^u(];U_Дq4_;,nKw 4!G¡ .K .C8drvG_e t 7ߋe"22i .\QÀ6#7'21䘴0r+z߇lQc(jYa9p (pkȱAir/'8J/ e0rtPZ\1<3~s/a&'LF[=a+&[:f==z%+Xk6JIxƕÅAv}1!!/`mrl>)ð@At6'4b XZm>/fî/#DƁ9>jۃ&-؀^qk4g-Ax- ]P8X6v|&,F1FYet0ʤ7st kGޑ609SVۧ1hX p`Mm{=-d-cO.hK},`{.XB\78 BMxX [>G%ymZd6kxr %\>L= RovҴA3z?ɒϘlK, L=Y]%{\=.Nt.8̦AeREφD,Z$O/DpHs* rFKV_۽i,&^f, bs3BF‹mơP# k1KV>v!5+2#eVwPEUunpA ÃCنOCm;G,uauϴ o $IG[(=o7[m*Gh`%髟:et(ޖg_S <ݍS_x9$C8d լp}tZcm-i=`8,ZX(Zi% kW,'ZL B댟TGF)d _W#* Wզ/=+`ͱ8Ӆ)JKpd>jQڎ6|H ޾ri3fmLQy02dTDkw"f!kmqMKN@esX 9llm#e+pmYnt,]n(^v^ 5L !L }\-<_6c딬7 Vy\c زբ-|m7WO!Q.f,sU|+g9lQf`#Fp Q!|:h,0k~۵xzjs򡠔{׊C9Wܣ2gZ7۴y'qps1:+}`v.ӈ[vAฤ&|=l|_q#U׹,x.'4`J&):IƾEtQStNr}VGCkZ;vxx: 1r4v:qu݆IU0&!V)gl-":SXztȘ!3 , 70WTr773" ?1AiGĦ1ں ^*1rlPq.9]F4­w*‚p9kd`gL<4,6Pm!%(:^nV ΰ'17zJ xl:WЈbYUxy_ٺgaV3=6Д9{]=,φw kjkF!O q{VF{TiJZnރz9`Ƭzaเ.hcU0Jumӄݨ{"[ -A 6Ezzy~ѻAx 8E:\ ~?JEKl >.YYLN9[?~sĻ*߼G m~o~w?oMOk룘 {QRr^ēl FJwR;s.坉蔕_/J)΋~"WdJwMK[up{՛9z֫3 ]q9(Ek(;Ԕo]t)]HD]6߱B*;AGQﲠݪR1e'=e'dRz.Ǩoxlҋ1Zj~ܤ}/jҝN[se+AvO1lXt. ЯɊ:JliQl]6+lS/zG]2ʍKF AӪHY:c/Q((/|%o_e{:5-Ko^;(MseP&|T*1ЧqF)^GjiQ+=P=tag1R6=u.T"Қ)H_Ǎܤ\QcٞN.:F|N@"w)uF|mײ){S/{v{ͺxc_D1Ӻ6Y[q sdGU6]SZqw}sOW}EѶ뉕oPzk%߿Œ?/LwM{[uI΢imKF&,Hg K:JsWh0z.|4!ռH^KV[s@;Qf\IJ{v;1V|k{rE|sR[&Pv1Re355[oօ%?{Qα AU^cP:#A=( Ie=e{:2[KC$2.b *l\|(3u(xA^eW_lSު ~خoTJ>RyyD]dq^"- JMۃm5N5}Ǯ[5>~t!]uqJu9.xrqQa% qCBuEbXW 8'd}fzS$2;2pzQlTD=3p^G.뼸**ԋެ9/}S'"5j&dWzDQw"v/i_z_%E]zڮ~eY?蔶JvEe35mKo;ȬKPΑ+nZ3]BX.Q^{!$ f6$+ܑN{unF]z$Îޤv yw1/Fn겻F7b1X FI fh+K=cnw'זNAggZ[zL o֗a4IA.½~=k:rK:);Ҕ=’β"7C[vU}LO{<axxY"̂/rXPJ @ʞnSSnxoU<+%qEh. ʅ/VnRZ ޅ]hW|StxoY6pT%(gh_M5]odtx=בzMPwv_T6]V]:T?Ό"K3'6y(.Ae355[.<^Hɿ )V8tAZ̑URk6QCf] .)'(9_?F +`SuA6r; MJ$;HwM;R/AѼ7+Eӧ#_}EMzөW_zk=p[`xf:9šiI H(*]!N)ҩyo9ﯮcSލőuD@67ČT{/J[Qzv/QEi3xM}՜e355[oՅw4lJe.C{)HTӯxѦve'c^6өyo 8p./wxtݙxU}R.;kf[{1VJAzqCsNB/J#Hb7W$ې,P=yw+dOJճ34t]:miXnf2UUD/J�l^^;?qIٰ6< !-twuC;Rr f;6ҝN?wֳE;pXحDbvce f9&W{_mtd p|ٙX0M^.pܓ۳g8*aϽpV>Ra}U>l9J](ܒ-V/WY+_nYu k~+M9,8awc}t8 ,8VFe߲sܱ:~/;ڛM9تrj|QAϙQz㡸c47dXNsו*en|нz&1qߋx}ɤA24e/s̎[F 4;1r༯Ms"ic 6Vjhc[;xqx,Z*evVF.Iux,ɑJuɼ39J-̞dGCobhM7dY/nHr6%}=2wC2:MN.px:k1JB 8+ԥtaե@F-K |:t\=p_-!NaAÆo XrF{HFPyI[B4b39>lavo 络cɰJab=d2WwvaX_<7JynH,Fw{u]sv@Ī˙_V9ϜۭTzaA,Ȋu悊U䰧щc&Whtm)cRӑUu=eh65#cZ0bi ֩nyҋ|rd-fQ\Sjөiʑ hZ1ƌq}K>gɪ0rSJ|ϱ?PQ֦1DtQwt`'3_Ͱ ^c`44CzzgpW 7UbO8̦ kF6 p!6-M@gF.®؟;O6(=QӔUۄ#BpWǣGEh=z&,=ZӍp߀Z r4?*C7 -!;1r|ڭabOt(S?QxzOG>V"ubRfq"5л-&ԪKªKƻ^ ]c;b;ǎc٠Y/tWXlY%ܭ>uxn[tJ g9s{y8Yzu=c{6:޾(vZta_U ^T`8gk #ވE-.JۢIӕ}M*ׅw;Oke`*&^ fF Uo㌝EKo {kIh(ǂfTxx<)8V<)w=X/dڽs{n<դ`[]zhH%zw ½_S4h0aF3x%c!%c!>$ 带#t$V5= 4Xh!$|=c: #Lv8B#ңHUjt$z\b` #1jxOVM|UzaL6oϰs2ڣHS=?jK cNKioz~!zzEqw1YVݳoZݦ-m6]IF:MEXzLh'=pͱTݢX~氟#bs,6 |Jz$=ؓ676%%ޅ]9"OYX22[,SF A㓣naRB:i1"\OVm{r[ck,RǚZ[iw_]%k[,!CCJID"qUu̘'}Y3?*ߎV8OסH#݆Ga.š+7m-75eF`?ߖ^2"5([2RjDt[9?"MW}ݏ "[lэ}XְV-g~R Swk!vI>mt])ѾbL(>^}CѹoO% 9J؟uaB>ݡ8/Ohu!Ua jN0r;ڒxANA;;o*VSբm*rTS__4~=_כ>^cӀw[ؓSf:`O&nzHJqKF*l255q+ϿW>{'¾ڲaVs֊>Kj`C|mRjiy }lSf`d/F,~+L'dp %=~p>]{ruphX95sv~)u@/^:klt%[oeM%~ߔ}..L-:\ԘF^%ZMBaClO}魺IsvweW_-Ac <[FKvⲗxLwM[upۺ>|QeAm]bz:2ׇbo9\U5/K [oեJW^W(ϯ#Mőq8i]~Q"f{뭺>(GmAז !+=ܭ;8fM΋~"wDّNM;]>W>[yw MJl(@*w1}}o2RwtwlFW)H#QvK/cL.N>_up=בץky+dv+!>g]b W]&^3auGKJ!7V ʎ;ǜb,8 Ruu+7\>;u.([+a>f+梻|#w[c'ot:u<ėy-z({ͺ2vI9s:#+/Mux1SkOչ>^6өyo.D>?qQΌ,~9rUCkI2"B8#>?:=/ /s[o^S]xjU/ʹ <]wB$u|꼁Nvⲋ^6ҥx?lZwPA1?ǃFvVXu۬͢k]ZFQEwOʓp+(8Nl{뭺`]g̕N9aLDu\TC2}uR΃ϕ*ԋ,_ۻO q|w|Dr% Dke\P*ԋ.6Y.Xt҆Cה@!^po=|tjj1U<+ƱJg@>]W !=}n:1:~r}E_l\V;b?) Vg73xGZc%ނtM-ʥ{{}XJ+/FIx`d:!kVt鼎`((yj>$GW^_zG] w[{phʫ#'yރצ | =w̕#uqc3XG]C9 B3rQz^e{]lsDHlE bw|Yٗݚn6K^C -%^Ǐl{}Ϻu9.k͟u L%Ӈԕ?]}˺eha>.xұ'0q]{ٞNM;~/aS^H9Ox96$_@uRk..{)$tE[o/v3вJsU5 ) nJzCxeY:H`*k.{>e3z[uI"E0<^&B@j:*s/f_+xlJܦlN-ﭷXEwjhP鲰۝ίtR[h;_Ԅ_]/[~)|O]ؐ%-^G^>Y殫C߅ hgO\dI:;#T ٪ )8oSNqR˲7RRҚ)Pv.YyNL=WNK(]uIk~/өi_zG]xŎPtsPPrƝW:ҪDtΛ%;e3z[u)O ?)O#9.rNpV)8/m%;uU6өyo{{y?LP WyTpѭkJL)x5 e8cL^f]KP>Moי ׄc]uqJ]K]) fkj&}e%6~- u ށ"e=ie߅5@{Fi7#۵ i&--^G:ϑ'th#df:s[KU%A nn#*ֲWnKT۹(uov;^S:,_y[y 3tBnH윗< v-xQv .fkjު  ؽʃ6Z/߼:7Rݡs^"Qz ^岋֖^6]S2УQc;Ac(Q]2[#x NлzToQԋ]?(LҌ /!}=# 95i{V[fKԆT/*T HqV+bs~E{1"22#hm8g-Y6ԋ.j4R|dh#ޮI`PV{ >5uWo}>zmʐ5H Y  {mB|jחުqtXPd*dڭDžs wkFbrRvccOY6˾z,{(f=徫M/>$^%H؎O"7_dO\[vGWƇLgFY7?)h/'n2\;޺es^]օ )O#u3.,;JRoե9y'N m*\SCc ۝.KN<(}lǝ7y'βM]՛up1l X__]ɏ.H+_Q&4e}c6^;wD]S 卻DVyCV(%eΔ][e"?55UoE+I-Ȑϐ?zm:KF%VAKאK;ը^}V]0NK'"9*ldu!u;;츣lC/}_*lrE ‚xz RT qGlā)Hg];Vf[g]GM )x)]M |; K4<&eK\#=Lx<8qČ39bp;9xɴwr0;b#ߜYOp\7\N{҄}>rF/\ZHacj)AMGȗ WOȗ E8C KEHy)Ad} bp?3ۇU–|Z(48£F'"XF 8E) XCS4X:Lܭ] $~|N  nrpb_C \+k`Qؤ QIHC"Y c-ɸ{iN0RL9R .tp"md> `*M7ZaChM[PR 6.ޓ:hF v. 0~_$X @+838XGX,h@":(~m\#:A+MLp '_Z2׸VWeWM& }#܂[9":¢`,VFGF(5 0;ॷZmmKڛծ#p汚µ-weM_ZВ[HjOϋ0RҽJƊ ţ@L|+Uj4pS0 _{*~^|Tq looxںj_Uٌ s63g3pٌ7 F-YmZ8_9a_n;Sl8Fs5{N74l1C9vX4 Wj_majl:ߩCu[L|uO:UTq"HSGIwE=tg QeGś O&|5cEw<_'Ӎʜ8)p/]`xڱ /R^0/6|!p?Ok8B!:f}8+q8w6>t}xY,6&Bzu#V}c!GW bǯ4*k8)Wg[ZeŠ) -BV3t%RyreKxbi=á]i:2R`U^X 8caQ4:- p9ΰ9toH1Vvr-|# {[s,2ê)sLo i۫)p!q_qU)l.k쁎nsJc mfTAN|SI省׍p2xXvWkW.uZڜ=uQiGiӽ{_%CZ(;e_Q`8+3 KiE>L?$҂!(|EWoeKPXu^] z'.DO]I}(K]G]yR v֥謢.&g9.$jK[=Jt_@o]? ~SP, $ N>K/ cuKj[1u]ќB/w$ L e )iw#o ]WCS}6vhn\bsR3pC>"ے@J6hdBv\Hy/:zI[a0z.?}Hc ø9 T{|i[);IyEMnM~ﲯ&ݟ̢_d.$˹y?s?rWom5?/0&lo#/%zZdPHYy\lC>~N}${3qP@jcw%d>qS #.Q6˾z]ߧv䳷S6VoIY7yVo98?4]Klc hcL_ⴘ뀤ݞztಁ1R<z-@]L5&zQ;G"tP6[ф&wO@t7 Y%&GW|u5Q|R.VC]:jB[;Q6zWRZIYow.M~ʗ<@\Ӆ ".HDI!8rez쫷c_?śč y+rhd啙eC!ۭE=NT6˾zҊBe_G pKRjʺW{y>*K6QRΡܧ.lC u rG6u^Kml6k1Rnqߟ PDv% 4Ԗny9Jj[՗ZĐ6ΨtssA %Py(SIef'?55̃o)=ߐ`~HbhO!vK0 4FK}|տz Z.WaP7VݵZlx>&>H6V>!뺾Y_qFʾzg]^8 . "Va S[+0R(B<[JS>f[~~(8Z;`! Zpwɧ^}V] V6, 14Ͻ(/Δ ~BW 5ahM燦.ͺس'Œb'^#;IvP dC7eS]/vʣׯުҫC5{'9@+E:(#du]5GS/ʾzRg]B}|uuououyNDq}B6겿²_RKCY=_njiPhW^n y+5)v2(Y^F5GSzg;ۘS&Ґ?uma EyߕDMAvJ)XR1&?4Ko/C=-I:{e?z[NՅ|e4sˠ-T]ygT䇦.¹P?ֶS~zF xloI@mGQw wgɧ^}2>9ۚ)/:.m!<.d.@BWuQYt3\nkIǑ{_\}OM@qBJïH٦PNvI>jqp2oba1t]/gPj_H5e1W֙ezw)wM=`&L,Q߇V=(д/UVϽ)~ˊ>R;8'nZD=bI;eaD]lCӾ1Uɢ ?p}$qQ53A)K+(ƷeR]J~hʯzgv=dR6J5q.I]f[N>ӽ^sL׼;e<ɲɏw.u|R~+F(ZJ>K6PȠ=rez7ҹF#V1vE W&Vou/%|jjz.ߺ+ZaHDO]u,tUYM~hz-\Ǘ ʬC:ݭߎB>)HS֣DCQ6ԋ6~?8wB_ArnolwivS+Y?#{ i4 |Rtdk ā071{RLJ)Cs=Uez؄"'RpBlb9rM8!Yr(p'>Qvi-R{XyOYD䇦mMm)|Xő9R)';EM(;G lSS[mM*nف6FHޒ?0S(Fb7yHeV%ý(u=~օnȇ=u CYʼSS}66ơ_گކ/ΐH+e}syG(t/wV޽> {honi[xw7eIi%e}CyODlC/}N/yӶYmτ 7l#|A>\HVjRHم}^cs|֎{vsu{SC V(K>w{ {ԓ!^q\;rkYQR zw5"kW?p2J@%-Co!"oGKoɧ^}{gµu ebn&%(B ,ueO]zwHu71NKOM C7GJHJ)mwTv˾z>꒔w&Sߙb2R*﬋&?*K {/ŵ+x2ݹUHOլDGZה#s(;Դ/.BBψ}gO[nw*bh!]Ha=$٪z#]Wy)VުːC˪VjwmC @jGߖl!kiwɇ^}eKSw论%tnj6׿f}P[>>R)#Z;jǗ޹NmBPVƶUoηhUo lgl\X'zkH|Οw]RPt#*-8ѪB::% /)KuPM+]uewDiCʆEwl-jy;8 !>$e*D7 Yy;]/ʾzLwՙRPnwD&‹xa[$hL)(u+Ea ez쫷ߵ.AD]J?WHڵ|YmWL{hf_Oʾz`+RhsC\U_>sSv˥m]8g+Y6˾z.Jo :LmqC;PkNjI("d[(oTvKOWo݉O[oֆ.-¼~to]u ě,<^:珲ɧ^}zlKw z#_m'l'6D@zU m#lWKo.nI]:+]ɧkmURjIm*G;-Xv˾zgk.A>Ϻ'/֦lKP\RWԅez;ˮu!]mYӒ5KPXRWe.ԋuIU?KPX޺YuYuYO;l̏R/~;oj EͿ[TovKDG3-vCWjqaƲMsS8R.l6~K0N蚛|8%QP >Oe쫷~Q0I B sWA7a8k*9(wqjF#e ݅p igIj9-sf[E'^eෑYjײ8ᗸ.lZ|=z&?겯_k.Aa]nе~esB@ϨW[fyGO]~R]KʾzgoCY<}#Sjc#Q+/mlҸK|/80|Rp=b#Ut@ ^HU#Uԋު՗FjOG])U/z>p$=d+~²UlGH";hfSWD8%A3 )oɪ\;ځ$&1[YjΛǕ"HY@A#e=rG]e_ڏ/Ua.I*7nj 7?#e[+ej|EWo!)QbC-C. @:%% ;eZ_zg/pIvfwr*;BԼg=&NyS[0퓲%nyGREZ)ml~zVUUh57w 4ԛxw]RM~岯ުKA%,R<̰x+nZW›,[rk7ADU'uޑwuM~h겯:wyH߂Wt*:8q|DY(PD] v59#i/_z._wIQL~ o|ca?3eYy0q묲ɧ^}N)oŹ53BX#G:,'3ynIJ)/wMhoz;#E;nרv',(/)Kwu;lzlCS}V]t3%RrWoa6PlR\WCuޞghB%)EkuO\;kԅ!*Od[F+$Y"š 0=]&?{n[c2(Q m ۡ6F9'5Z\K6e]ޛ^e[vC! yPSǩq|HO|0l HQ@I*FKQ6ԋ;wqb?tkgv=XJVh˦̕~yoFs}Y(oo`('Dh-C@z ߨAeO(e %r~S0Ͷ%Q^IJPfI٣Wܥ SM~h:˗޹~>)W;b3*E WZڮ7P|W4w.5w}A]̚i7Q=) 6CIrNC6ֹGwح/n4z"|' 8@98%,~~E->w6d]t~bߒ $@BWuQuW\[z(IfR{_Ȑy_Mfw@Zٞ({,Q|R܃e+;7M~h겯xa^ڷ୾5Ngx߇_D#nke\ytM~h겯Z'/ p s9 \DS/J;)uPM~h겯yZ%(.]}Uߺʣ|KYCi'e];ew]\,ý/8`7bRDiՔS(;Դ/ Ukl,Zw!vaV #@A"/^lʼw^[BUdI6{Š7Bfaԟ)hHMJ])6*;ԫ/e7R=NC8V쫷شƿ|<1ٜgsDj$ߟl CFq5&zQ[v|Aou!tmzB\>o.htPHYeޏ`M~UǗެ;.I1}Ai芨?o](q @KRHY誼.*e_>!2`6Ca֘JZL)$_kʾzwDׅ(_·w,QzHJ?)}͢S~~1(8`34~VD#2z?W#|ͪSѿ {O}]ڣ3EȿݮɯUʍNY6΅,, o2*;쫷ژxhoEjxST^+C1 my}(,NlҽX|j˗ުZ=P\hHޚgJ`m)vo⍆7*|EW|/6y#ғpq`m`GJh ٍ{g| _z쫷l&FQtOeF@'@U̔,щKRIYߒE;/*e_ӗx#D.AnO!}:?=d]/C~q7e쫷~>t__R?XS[M\H@-|k-+3;sL:KﴵUx-i'{8"d07/O#e=_-KȼK-BF%WXːlO= ^3C[.OdiOJ!-.Pe'zwZ[UʂM;bʹ^>)HEezYySɧ^}6<3a38sB*oSFW֜6S༘yGwѾVEWoَK 6(~ah@W8a7qRO#"匲OM;w]v{)u]]Ne\ʺ$u9O]. 5e]Rﴃ9LǼvir;@j$%KTÊ*),NVwlew'1C{筋D.jάA;"D০&}xtxlE1ЬBH{Gq@zU>n^y8PS/ʾz,)MH &؊z F#By~xJ@ۄ٨l]߷ k%hTKAS}^aiϏHHpϋž?(lźt}L֒޹Rx8Ѫ3Tw=Y2)}G-U6˾z羒#&'^Zuq챖] !+v3)c,ObۄOӨ˾zgh5D'v_io#N"{C ])H'twJa( *|EW]t߅B[ؗBv KlQܕez;DhKqѝ Mܳcsަ)ZOԤ.Qvh_zS>[%] ZFoQ(PFKYW_ew_Pt^;>ƸJ@5o 2pOGف;hqDzɧ^}~m+ʂos %}Ub_lsD6),lw*Svq&}zŌ]F.u>u,Q%)n;AYUD M~h겯5mKo*4NZ& 5/md :_D'B({YyV.qv oq,(c٤"#4˷]d6 YbW$khEAqΰsA*93nD%##BW;t͕F-~h겯9%(B!;+ɺʷ&߷!Kuy(,tUY-~h겯O "?$IYUg ]ƀ<od(@;d=`B]&zQ;ԥ=29.]l/ Ts|P}R3*whKʅ_`[񵆗җU8l %l$v}*Ы/5&_h5lzEinkg%N{!By=B5FMH`v{;T6~o(I]=G]p)~ӯTV.Aje]wEeG]?;?/O7ۘ^Fmxȟ{%̑Q"z/ew_aD!evE6 ɇhO` $΢=d+" T6ԋydk"ݟO [ _^awzo!9)[y8US/ʾzkޏwIIEgwIwWq (%xwļkKR^&w..Q}G]ܯ,jUH/ZBORlc$5?eWy:;e_fwN-D!B{`8R|Dz3)lӋ1wYM];/-֢ d~5φ<砠WB:),ʼRe /vQĎD+%5):G{X6˾zW!(~@ˑBxTs%TI+e!Ry?d䇦}}魺u9ҷu5Q)K%(},ug[&Nvf"21 GYr0 ?l8..);a#G,|EW﬋Rx-v78{+o|ޒs[._Q+-S޾};0ݫ(mhTڐE0/(C7sw}HYhI3eJyES䇦._|׻gWRfogZi/ $]h.Du8u6βɧ^}V]m'^~1%J w1c Jzd.CqԋF>ί|CV@V(,d=e OM{[j/mEq} no]gC@ |Rl#Yظ+ﴁ'Ϋ˾zgj~^ ̃uW'_v!}^)K"I=eݴ7qjM];Y%(!4tE]KlyG]lCٿV]JיRR&~ن6tˮ"VSJ7f ҙ(x_ Y=P6Ae?\;mkM[8RdASWx2 sGD5ɫ> >k7f1R<&?6'i?&C#PRLmX-&?*K/#^ߨ0KGIh!Ry$PvD2d}OèlCS}/>;Lhk5Ӎ;1XoQ6PୄdBy?"~k)5~*CWMz/?gDݭt](HIqoːmM,;e_?=b >t- D1:CRg┨eGoPڅ/dBV;/ܐ;2g'˷o3|F3M?#l64mA;"goAyzNꔷފ{w!р5@/eN=r{;^xG>5uWm_:lG!z̆ӟfCyud*Dl?|zዶ}κδ =xaOnoc'@q/Rދyc^u}6v02 CY oe/ 8#&IR'%6$AaȺH6$Q6ԋުF[1W&Da. '_y\;񒬛G3{>rW)m^Шoَ_l]xD]w-ԋ=ujCC%Q]-֗{H=e+^1lC/}}J7cN6QP|Bqc߰l8!&,3':&zQ;Jm\IDz̍xf;+elc=fVyxSɧ^}w}+G^+};ER|GJ(ŇVy篨M{;b;#D X܀}X4DҮc!YK f>m.&?4KoݑѶȤxfC?/ 9d"C#e ރ1X6i_zˮwScřRRn~wwt!HIq~XɼgT6˾z.韗KCm$Ryk{Sh +){W_T6i_z;#$_d7|@^*l X,|0*Ѩɧ^}κIR{b>{v67 _1)֕;E|岯lwK')>(m0~CjZI@z!{*Zw*e_5Sep~I(\/FP6nRZ;ezmF>bNV\so#S(zH~\I@3=bd:JVe{mPm)6gG>4 GRfM-n ):w/}}օ:e˾u!,ueuYk}}6l>)ger(TzjGJ)!;|J~UʗYV.zގ:֬_ffn kEjR w({m ?4mKo.o")!5p|_u9 G8\)Ky5M];2P̺ΰ`'M˳$|glu!Y~X6W]_z]S.ON{DvG*Ky?PNjnκhdYI)=e];ezwR8EZ͢1X,~~c13?^pjB؛ۍm[5apZ&cbJYV{ǬHq@iJA쏳\S)^oӧ0Rr?O߁WE)1 Cx)DM\=*vҴ"-~ ߣ/a}A )eQJ1􅘂]E.bEUOcx,R,B4ut?zؾB=~┩ )ꖿRN ϟ~py ›G% n6./mN ~uPs\kq%=[# GEop'FQkKk s?[}XtY 7`9 =s-~ z-׭u7=&.#9HёC~{t:Ȍ0R kSÀ҅‡I$<,{&<0jN tNrݚ]M|aQ?3O Vb!V$0R :W?Z:q/S+R1R\hWX0 _#oB+z@\517[7#|1=1RLQ|\_kʣ#鄏RΟa+ku &N==8Y'Vsh;Nl%`̷;sl7oSSi~?\F\u Q\k$~k8uWaO/R[n<Xz8eb W?d$`Aa|1c1J< , >꫾=4aHq)GN귵)[)o[5b#y{SNt4ZwS+X<&sSmmU)swQp"P/1j(\Ѳ{Pjx϶QBْg(PcDhUyDosm{ P@YE3? 0 zc bck0嬏p+Xc)E]C48hyN?e2g#Fĉ@'Wc~yX/<g۝G ~W "-O y51RLECdX\m8(vqC9c 1F:? ]4c }36u򌍿!jr.B YoJQ ⦳Ok QīR1#|#pk'o5XvG^ ^q3qgs'V(RMXhrwYX)':N <-k-C~#KH|Ľ>~br#' !QҔqv+2|XGo5#[뿗_ #*ō婈@tf`bY}!֢Z}=6H ځcEw;/ 4fRf1)6<[)-,WK)JYr '{㝷2-VXF !,OMƴr-3 (!S⮠WĘ){6)-Tj\Ѭ ( kT(O[oF.LN&Zľ tg"F)q9pST7*ʳ<3t*۩iąb 1`잡3x Q FK)!nV Ѭ-NlMXGYJa; {kt<; SI~oSR?y_^ sV+V؎;OݝdHәpa*)ૣO[f;OW_y J4~= s̻Qm o8p6L~}_g߇͋Ѻpy8bLnsCXl莖,<<6Vjk#֖Yv&}kYѲK[O`5L;G 8 /6X={@w0+Nwxfsš[pl+Rlg>b_a߀_}6t#h嚎Y{dG6go;~I/d-iy\g#,wYX?;"S8 Z7 o;w@vUJg_)„?F oyW$45C q#878sw<Ϲe?8t<Ǯ`mPRj_]x<|}qJ o=oo/ޙ؏s174@= pme xljbw'x|Q HOo C؆%o.՞V}e̞ܪh#9W״'5f1_v+Vx|kceK zWx17*SVDM+rJeqԓygŝ@'y񁑢t&M>= N7)65y& /տ)[85wPun՞\ 7]AƉ5]/=dO7^?Nt6U46jk>qsNϸsj`: yYps>u,<"@`0xDQaO۞ sb)NY ȶgޫk)ε8?,"rR,z22%ȁ-Vɿ3e)(n3E5"le__տ׿wT+f _oix-pz~P?o_g#{edUc&L_GQ|-Wf?KYd]>ǙCW@/ /AO~ۿ!u8x܅? ӊG%t RqöMr<' KNODAXr~^\^̫Lr ]V߉g*V XAF+~D*IϽk8yURȽRw#%w)kc_bwuϏ%'@{"G=zBѕ7RWۉ N:vT6|%9 o$Nk~Xq}"955rO+r-]cq";K %4D;;ڔwW'ωXᣁOxJlM.9p;>BkSz}|J[𗝄5Fw- _/ADUrHrUOUrr2ɕz|_?4-|~lw/ .@iԇ$%PcmqCچ]V?TJ={tl mߧ juSN@9 n}f=JˣogonnY˷0hݔhr󛄱C_(&π*\7m߿ayǬ6L.Z7gw3m==OԛS[?=B?PDF5r<('GiFD,l+]SFpk }tj3n&9ΕBk69@p\J}7ݿx6AX5~=z@\?@in*bD6{tͮ; ]ۀ L;21@lk:QnbERF9?SC7*\r~RK Nw׍.L$(V A3e<93(Ы/Q ?4:⬪߀ p[X|q%h.)㦬We? :py5R&]HlI{8OC(ے(|EW<-C藣HWCu^\O}l @47ՎΛrR[zkUm#lvrfi(` u݌2Xj=z`K>w1vs9=gY^i)K4:v2#*e_w97,/ځ{5d .wb߽]Z?yRV{j:ϗު{҇GAao>cl $\+I);e'ߊ4 S{z *<~2ƒb~Gk>U5s@J7^1zSVV]6[DqNQ 2 QĈPY [,Q8.(%F |j겯޲'VIbP0-raҷ[J~i0dݗscI^;b )ԧg]*F+Vє u!ule׏쨋uI4viF]PÝdɼE\I6W],;mwօy )6`vY<}7\7 ԓt6;F^Ɯ^"ݼ(0Տ;%KNJ){aHew.mhB[R\U#oM@%E[;ep}HeO(Ʈ;̏6v>6v6F@~iOyͬQ6Ѫ;>?e}Zg]օ>e+kwH9.VwϥqK@Jmc}sL?2UlT8>bl/Uj5ʺw!H+Ral(&/j6o%Wo].xPC6^rmXu<7},QQbBuwQ(e_w_ u%KP6~HRWeƹWY֚R}(͚g~օtwZ݁oe͓zzȻ]&?4uWˀB쑃b3SAn!7?'e*)8g5oX6ԋ޺$_ÕO u~c8[h= 7Z9 J&ՔՑw>jK﬋??L\hoˍDn՗{=R_=R֝D- |T6ԋު{KPدg}ŭK u!P6rg]Xv|Cf_{'&m̎m?%XS_U3 *Qv:dYFe/ wZV]Lʆ) P2#V(HEQpY(Y#*fT/5e_T|0 JmZR;h#[ 3eLywKK|岯:h_DqDjcBVS֝@D-fV ~jiD%)ss*Zzq,)W(y40+'Q'ŧx61w{MlC^VYh744-bPTݶ|ZDI`kȻ[e쫷r]u+֜'5ߊW兡 l p[! Ȼ>&zQ[m h?H ?pHz@YoEs=-㎔6ygRS/~ͺEKRL[dp>W7 lX}$ ]wEe/ wQK`1R#GR !)$,L wZ"lCS}V]&V3ʠXA] Pw5/2:{Jفy+Y6ԋyT+Kr o|x{?ʹ J/);ߚo%q&w֥p1.K9a.i;qn'k̆DPMYި0F,;Դ/ƪׯy󟗂AF A v|"~;N6ÍrYx^>5{ۚ+=E6*n!@B/@>@DTcرع5ǜ1˾zAL1P+&:-N~()&ϔ 4PJ(COjfC~e{8DcU24)w'%q%YeWdM][m)gdO(%||̭>Sܝ|J5HRHY1Q䇦.mi#IH}?hqgޓ_#]6N:DC,Uv S[ .|Rs6p]}c<3S6PK,LUv1RuO(iz/㘌Sv?ȷa g-#e-&T_WɲXF䇦tJܡm!l,]7lzq"YIh) ]UvEu-h~*j_˜& ٕ|dI!J#9즤Q7ԋjX Uxuj˖Mv}A'kȢPף\]l6W)g*{/&K{}2g[B} 6=mmmqQd~º!V[pږΔ=_KZ &ZK{+,QX=URGKgJQw*?ql9CdVD!3dn+-N|GYʤ+,*Tv]SS}V[5xΟ{(sO' PbQW)pʲrzI[q WߟMSNy}m%ЅƱDE#^30[މnd_^p֋e?[" IAC%ߓul Y&mFe-WOE&\^ LiW1~.:vm^ S6-{JQ&8:<^BYʤ$YٖS뜿rG=wm#ueO[Xwz-yŽs/'V' ]m7pN $F{, +ݤ8nQunCS}g;9%aߥ] ?pwB.EB.0Mp_a=b$r9ttYb"cv= Vy%ZCdeǤuzUs ֓ Ȏ WZ=q}lBt4K|c|j/)->XoA}6 XE DER+:dPv|PcUl˧;-fmcyp^ ׬H٩adJ\!9l 3Ko(1ߟ "WG6a g<+ADRSEUϨ#GzQA+y}DŃ Z ]Ԗq ͚(x!ʞa_Zʾz畋V"eR3慏uM>$KrRHYXK嬛д_zbŬ룤0gzJDz`,d,)~Pp5R銤_kʾz [ދߟK)Ya>c4=y0T7e:w]ve_3h4ψ9*Ysiݖ.-[պNG O[.jٖڹw9Ms;Ch=)sDzTvM(>{>F>0y 7ufW'@Ư5h!;.Wc4䷕ޟ.3rlv[n@zfQ%>Q$HHI)=dXc$-~U/hߟw:f[Ɋy }R )[ϲKෑ9,d# AvA qIioPD5yoV3EOW~KAߊ~`B5jtN0jIJ)[RS>m]B$8;By ˷d͜YI%e+ְeЫ_z?ߛR ʸ>i_1%d葻l^e7?^}P~@NΛ{[yr#dz ]G3"< OM>V[|:='e# ~}G|$ W+w5#_ߟMdL]Tˮ&k'MԤp\-fCS**yzASpIxjBҮs!FDzSZ*;BLE^&wm[a%.P>ۮD cgyxlAx({ed^.ꭶ\ݒ)R,:Xg|ɸp}" h)<p٥H->[&7I\S#ҾRGO%ne_iy?)q‡i9OW' y?)1Ĺ$˞ynɺjn}ݎtdl% 埞@32nNw۹-'?4޺:bpOǟc16Et|C6Nmxng '5S/KVhɢTioקIs|(KTbwRXv jM~h겯0R#gڛﰂl L⡶CcG_uO(d[PP=e tE*2|q ͠RփG%ne_}/5w4po $^JYlUv |~!w;XAv1`X9~PO}kD鎐jЫ3|>5ޟVMW$RmZ"ʓ{@K -H4IJKtU GM{\{ JJ`xk}/ 9)K,;KM~h겯^hEtPh5)uMQv]QwW]oaQ2#Q:B-gB@Q &@MOc3ˮQOMg2)~g9i1C>BI~ $KQ#Y&9`O1M˾z-8\=ƃ2_N"1P_ gA)=eξ8g^.mm1Gm{~z#W7jnm)Zfbr5K|k3j?:!׊2/K,F}5ܝۧP_O "UMF]~uB/| qSN<(<`]KwT7nݟaSny _YVg"ڹ'u84^'8 %`WFps+7rΦ'L†?P`qCҌ$A @ of^<y-痒 .{K/4oκ|eo; խ|d6.=k^Sʦ~ݝ`xLo E39=$9׃0?)>KO5,㟦av,,eűqrĒIrMߚbHnTdc)% _kC6$U1d}O@r7a [ѐywC~!b;B4a]|7c) 1_|S3jJX_NH^ovx~=gw== ֚[|@ mn;)ŚPSe>&E*N[gEŠC(-ߡ4E[X~ۄUU= |/@K#,xb߅P߇% - /לE!HaM/zb/,/C))٠||Ma|"@}_ .&mc"wnfϛ[o/qS%7Ka.Il/p|7Q^nKC׀gkj|r-@B򀱨pBo<%4!>`,y^Kd)׼zűկ0ճ1+tPwD"soE3.+OIcW5+t[㺭:!n=p3/ f ^P4qJPnX?ewߑk9N^!#ּjPMyi 18G?b 1nDYMIwwgGA?[ڪ¾W'GSA~~+׸p=ڊ A{s+Ixc=y}DpD#߇?l@.^`'_VdS몣.&պΏxzyjRN6 -yղr]M; ԺxozV}?Mk*I?໤̵|?1^+;|[=B Һw+y eMG%9om78~v? 4~ p8jHwtg4v&7/E+_u<4>վ2O 畿x'LyY:RY~ؑyc8Ysb7}ѿ_b@q&!~p5Oun庬~ce: Lh-jAOcG3U/v0Pc:| T|TGϮB0;bXQ[{˫u-aŗ@^ߔT_s~@1$C1T笷i]fVڗl/au%}u/@~]78o<7O$l;Ͻїl'?c񜐖P?$$=>~YB^pd$zd`de~x~4_v\14_!(ϻ:!xf*R]\Lj_Gw_l#T}I|8Fj_^KǙѿs_kT][2߮"7B","1s=B0/1cdGmt\! M - w.h-1Y)&X{\-JQ7ʽ3 wX6&Ylqh`tZ*O{nh񰰘&~VV=jCmMN/"'.:E])JK(l7lcu҄6R9w:o2 _1Vd\3Bڕ)ᕿJ68/ԕ7jY2 { 2Ԣ;T VkԔL/W'Ґlg-֫K >zw ׼ 6O.z]V7gc8Ki5hb7>įZm-x_߼!}{(+O"Y\9q~tF0DJڃ[ m) &JnkN&hŻx#5KtOs. 64 |s-~q|K2z+,=Qc -kV>Scb=IMźJe { `m4Q88b8"/0^i$eWrgDO!yGS󰉫Pk1 Rу<dft RC؞]m4w뫼[ e .}ex0t:ːw `4^llg{Pε-/Q~AgOGkRHR\VO&Q|' yws;0;!>NUu NvWy Tp/;ֿsK >y5P~kW&9pa>@!c^Z& 7"]qU$81-Xխ_匈k҅h׭z('| QQۘݢ k/;Ь.>1*SJȅ3dZɏxLϱ* /)5i51B]?;_އ8egG~E[-~Q>N[qtmOy"D-~ J_ yzFlF-sE E V4*^xit亴!¦Ϥ#ֺkBsamKXsA4K|ym S  /\;N5N S _"DKX;Xk y)-[3*f}l#macNY:"m}AnG~QnM!UXhf ߱/)L]U.D3,Z*+"c| 1 M.!Z!ӁNx.h G1*/w,|ַ虼$nڪ)b{:r$sʾ z߾9`5we n nS#g=V#n Z0"A\sshOy!eDӞRx*z+ HRc -9ϘMEDO)## 3LWRHДf, '݉P!j^9i(pougǖiUNYUE;wZ6:kqµ.ijŏe:rDP.ˊjZ+ 6maN-]z'g0~ᇽ3HvyxniﱄcRqOIl*Fd5Mqs72OF/[D1Cr, n)f$11`N(CYy~b ep3*̚N%83E^%i>p/7ϒqXg=Βsg4E p)W0Q2">$`6x,)Zq.P."r2׊.q*_YU+7sZiM sqK[dkyhkAn!= ci c#@l IJf s/,ͻ_X̣_U EDca-zEPīIw]8,O(fp ^]-̿_o?V߾:ɕz. u}.O_;b 0Y9Uj$LP6.J0{+:~CNdEpyhRbΩNr ]Q?O )x{QA]U |uH AANr ]~}uZxղ=*G%tlI=OF&IsGW}~r==ba`nȒ0336 tĻ\}&$LKߐN}&\hCGW>/Q.xtדQH E:U?L%p> 6PK:ɕz.*{v^LfYL5S~B}I6L_EJy>uMPc`"@x ϫ(Z1Cn@6Tzc~CVC}l.~ >=t:'_4 skl,Q*8WsGWۆu[ N6`QA`~qm%$'ISrm X*~u+m\U1c1Q *2˜wo%`r" M܇Tyֆ go%ЎP}QMrO+i!G 'h#GT\#o XtSy@<GqVEQyU'RoO]\׶< XK8;@!@p?0q=$  ԢTP q]S}F'8\N!PE0`_Tg2]3BTj[u-=Syno}3Đ ]@c^u= h4 B!|*h:ɕ6.}tMK:2<Du1<v\w<ϤJ={tMR}#]G6mqH #O bAK_F 9?xTbb[zq =lAR.'%[K?;͏\.*7@1B+"6zwϐ00+@mtUx[Fplrr|ݡ ,0p/o,$ ( ;~Xgp Gy=F#xR ֋10$\<$P% }cLԢ3PO]?S> sk; }x󎕒TJBTY?cE_U'EUy?x2':>qu#3 h% 50WNr ]_EUg>zvZBxeE35;OA_Yy@Xaw"7%pVp OrsOA; 6{Rm&rMݟӯ^i?R_ rܵ-nXF9/5G'r\ Ԫ 3PoO]oSH}M0׌M9*OrX Ԫ1Vu+Lf>({֋f|>?~p%h;!ߏ00 S=#f#Y%GB' #K]1Nr=Rㄙ07ng` xEp׷q(KMc: LՕw?U9/ G* q|Cr̛){KmeT֕ n!hFp_ Q}SWvMڂ%p84톜mTP\R߽0nS& E<~&@E=2xLEqPc*ԙ6CU~%V O%<~}cWڮ{}HJYR}=2$ꪧp%އǞ9Z97OٺV4sч]\n/^]@Li7pBX*H]Y$"rnR20Nr=J}g^A>%uP{? J}G8fNe"qYpgpVr5nJUԪ[*9S*T?Ʌ6|*m^E= (E' J}G-oK^$}G.:"݃qHBS|\rR)Կ)FO3r!Uo#Y&%KDwe_'5+SZV[&B`@M݄ZTd{g'L G95jRLYe׸IU^u;R񤙤5(8+op~FWC'FK)IC%eG*ʮSPR^~_:lZg,Y%jkK)%We_lRvRevOzT!=i=އjK@eGh:))lG*S/ʾz{ѣ']vǭ-KJG[OyѨ5RZ&u)&?*޿C',bYٖ{ԕtZ,IٖK_RXIY1'g3|El $&CG#lTw[OWKu;?7w3C .{ )ߢʞ1ne_ ɓrpW%%~(>21R6.˓RkN|vhyO~U/e*kOq/w3^~Y'Җ<=S("m%>ge_ݩIYU !o]GSzbGHl3 Y˝)ꭓنwOͶH#لpOC ,{i4&?rW_kHQ<C|~:g%6e0)sF︢^;mK-@܏KWX m?-I1}$ ]UvEu쫷RCRT@n=7^)HxMC}BIMf}w~/ &_{!eΈփR+$@5}NIYt#[~OƝS~m) ?-gg]#P7n;~eiw%lYeXh%m]̢ic%+_WRMYgj Դ_zpʶ}~Aધ-g)=U=#EPMY課uwaJ?=0ЬJ38Fy^>S((퇓b[(~Bu쫷%D[B_3?kaſ({5E[P6vF[϶998JV!N$jଛt_zo_e} }s̽r" /y>b>wL{H F iwSv非B)Q6ֳ(;n~/ vzxBd/%KT¸X)[> RKo$ߟ_+ ie!/i[$SbU J e1\eQdgB[.[iVFlrR7e~ A gEJi!0*HeדЫ_z_*|RF=Du}1؟H6,D)XP{-nWъ&V[:Ӗ-wz-t.SpF}QIƲSݖ޶ Щs]1X -csl x@j#Gďe_Yz̧O+4%r+ 6Hceutu/(;nC/}e׬^&ԔbͶ%~D?ߝ].z\viurA?y(A>„VUH{&%J#{]so4c_қmU{⟢!OuxJyD=bk|Qw˾z-ӷɒmI2MyZ"@[3Q eB\ܯTC l ]Vd_[3!{6 ,x#dJBאWww $K)R4;H`"+ҤsH8qCs y} yx& O%Uw|EWoY=[.IsԎ rHih\!nwې 斤T_HFَTv-ɧ^}V[-ݒ$mޭu$i%#dIkl1 ni+Ⱥɧ^}γ>{I¨^bTuyU#d쫷v3z}R|{.Jȟٚ[&#~&`솛v'5^;iN>B iՕ- +~p@RF[hꎶ^і[ˍdbg7u6o3UΰNUJ&̚[{J'*{ʼn?2s ZaHDl QzR6̖R{5jFuz쫷2hJua78knpDb&.#dWOcA;eD#U7˾zrG[D>"Ӗ[Œe[2vBW1R쫷?sr?Ղ%Rj]"6-iJ1e_^U2,Agjb$LV(M~NY~y(mocpMbd~)ß4WH8Ѹ~"}wMYPWϔQvaM~h겯Z-$YOFt[$/ܔ UIR>H,{0&?*޹I@ ):o !qEtN!;/F =CURJIZ\ZϘ|ad=crP8o+."PuwLc! ~pMEkE#Pf yWhO Lf:1# ǣ@"Vs!3RnPn[^?VZ$;.pG#U=7[Z;ґ̭ɳG'<{й1Ydtsxer_.}ۊ?g[U?`ק~j Rr~/g@_\x4IO0?eR1~P'4hhdp*!}0<}| ;AN?v{M/spg|x.%-ZDUyG+M|ͯ|S]ٛBҵ;Bc{5ٿ wa-dmغ໫\_nlP.i7{w#5@uE{ane6YǓ{Y ߷`,fwM{`|;n`?E@=rs/BDmWs Ja8qu Ym}  Kؕb/<9,I#ҿxbOf$fTks6B&c}O}Bg-n׽vEDAό(o: $p(}0V?Bi#@h'aÃ9O-.7sK8}C-䚶o3FFImm7(vIw?Gڟ/ݛF^@z/=\B}npڿW7ٗWu @+xJ_RAT1Eo9M8}<'ɄmWMF遐]~Ʒ<߰#j=L}nX{Ke<ӑ[/$'!!u7fl xs vK!ۅ4!r!a@̎Tҡ]Bph} F޿ᄆ؂ދ>5h~>򻚿 Gݎo@X{N/!/yS,: GOĖ%;Թ_yq`|z UOxSG#?֟F@gQBOE =|'c?_+X?u)_3!4JV.p cAU8%[. O<~aa x1 {_Rq}\x> oTWxbb |60[WB P {ep Rp _x{yhI 0UuمM%9p.$T2|vZ ʵp_n1#~21~qy WQÌ6\hI3Ұ (.bKg N|cE_PW:b|g7&hRybY5viGoMĻ"JmweyU[N= \u V:ĵār@n:j\YH]fp'/uWU˭Z\8ySKۄR G[©coׁ ~ұ@p j 8~jͧ68Qc %v];MsJ>XxFnf^h[Eϧ8.t_v=*D XP ‰0c㕚 AЯvak4 p S ޱ1xZ5x uj%13OO%tnsK7{:޾S¹H@P-!@@s"wmOIys؀LYps`)& W * qceEHCVARj!у G^KǑqRUÝD``ݻf 3 Z&kssztd#` 0~9*"~bxǨ )z!l퓫0{32V컹p`s%~T\|i+'j :hۍk:} ``ڡ+{PbD]9v0 3Ma)K!wl[G+cV_t6nxvam?t͕@mqK?E[<zO뮱D;"{avW5ejփ.57W鋧Ot+gYqhWڹKX[X43{p_B~/MaڇUNj7PNl/ht\1VcaJXH 7,1Tn879)z8n1JUehGXps4l3n_aFէңڭyπ>53ѰB <4Z,nntc //(=X02`0[刡kf3^*W\n?y4 N Scx/چ#` _ Y_͎Nm_{8 xyW֮ %lm[Z9vkmI;t vcy(V΂yZ;qxW5pFM|N ]O/=c/P400W6#V1BY+hy>L⟰Q[gϜoˬԡ%.;"LX]"26tzQ<,lZ4ruQq\nڮ>W$/( c%75;y[gYuw%S8nGp!W""| 82e\*8˰ "b}}5/*r湶=V=O%?lxM__Vy*݆O&Rn"w⻥G۰(M$[|&S@*C/ɾz+Կ_o?llQ?_ k_o_~YÆ_/W/D|AIG[7:ׯWw_˧VH4,]ǿ._8?ﯿ3S1P_BAs;+?__X}sǴcA?o~E߿S'hx,_?-6)-o>ܾf67~Kb`ncF+\W0fR9Xuܫ+guq() c9n`/?Һ{"x/תԭɪ3 ]Z"Bbu%'"䶻yԭ +3 ]Qn$g㙍r7*GS%<(@f?cJ{t0pc|@S+~ 'n59Ah'}*u+D$WܣkvgN-{Dğ1™uT]~gQBN7+~RvwD+>]&+w; truOow 'U@\hCGW߯~L**8<:>`ב PG; KMY'r~,IqU ~ I0'F _ijT?Å6&ꚝg[y&1wZk6=kf_y'SKgylU'R@*kIX~^$]4?r7@?8\V6 PRȽ5gI=g!% m\q|3RSKO-&^;(z} NtEJQs$K ;: 5/x%aCX г ֐W/LutɽJ}7[S1`<BBrZFx(u( nm!*{~C\@\ 9C} a+:Ku+m\5tR , nuF1Nk<\ấS>B]fdJ>>uJ$L9sS?k$' f.-T'R]SVq_ U4yےv j<܃h(u+݊$l%te}X_1qSNsPvMJ:ɕ6.*t!,߳‡= .|$(0c.9+RsNr=u'7#5G 006?+n%9 r'h]u+\ѕISrŃsM79۷[-aE4+ҫQh*Ci#e? uٖ -&u;:G(8ͥTbu?({* m|jjz?Ihg&ś`΂WҒ_t<"_?(y|Z/> y =@t"vœ(L\%"Hvq^S䇦.ꭶt$?)JjPlS׺%%'[˿'eiYўVBůT6ПԄIÜ$miLmiӍ{ûDŽ.v|&ui'QUj2nz(ĤMNƒb[OpZ:–6O;{8`ّ&&?rWoa QIHdM+1"˿/$ul $"H֯@Qw˾z-C0xCb`-fwt38*d~ԞöiQ>ٖ{֚.mHb$@іԞԕe?maŶl 0bcymjq4y}vޓPB6F=QT(d=lbne_ٖ 됶-f $XeH4?7Fpג C)%e'=KM~岯^*ڷ{J}#Z}0Or+=֓=Ph)MC#e(,^JuKlK7uRp3b?(Bn3@D+2WʺqH+&?4uWc ]wZI5nH7R?#\l lQ5U7M~˾z-m;.Q%@nn5('مxf,{M&zQ[mRW'N^lxuHp;7@42Y!({)YM>쫷o[Q4mw'/^qɷՠdv_2vIcM s8H/죤IW('vODRNY݊wOnC/}ּϱמּJq<fjOR$G Y _bmQvD;e_V%8{(q6$qs9;/84_OO@eį/ݒU6ПdC/ɾz-V0A͏x -[ߝt5N m3FnYK^e[B}<.\Wғ-Tlc4]MuO(mGFR:rb393n$sdJJ)[}nR5.M~h/y6lc~Ј$2`[쫷ڲaI[A¬vZs#ۓ(w'%-uϥ(;D䇦.{ɦ>I: ؁JZ,шӻmdaGSS}墼s{QTqCeZW&[NY3V#છe_P㽐b78~׈g^!=~iE@@J)/c;ԫ_z{F}_r4]?}Z%eޔL!}/s|j:/j:͍D#pr. X)l_bٛ.ܝo"`whݘ\8 'H@WpTdo m[rFA&a%!`w !n2* v56idߏFpvfVȄz6j!J! 5q㴁?|?Pc\_f۴[ BoB7L{Jh1&(Z~Jh! -l~pFMYs6wY[`5gqh<1,6{@9.o9nafw]|Jެ+O7 h c| aGhp6`C}Έ#a ЄXݩu؆MoI@h1%؉xps!D<8@qh:Lp+F=#D(L(1] %# ~ GEh|ȏ&&iG1xlB^EWW[(ʟH'掋أc܅~?pw6@l](mn#M(ȩԌ!OfEXþIBF ߗ[!+.BͿ*@a ?p|o LJ }~g5dYt=qLB͏npp%<Ç-rU8?YWE0@%ۀh|hQ $Q|dVB `|~4Jh! -foB'Pa&T 6a4P]}B}qm= v;.!dWfb%$'!ᯄ |+k~ ھdU^n~ڣRL l<(s `Մb($aI!mm),gZgw>/?OР1 g‚zoأC ])$ψw^)P>m 5v4}EG}E~q׷}Bo1"OBgApBy_ ?|f^-S>:C3S #RHgL9y~ F遲? =_Eqz"׺  Owd$S (<18|灛amAydz!\w9nT&.-A7F>~nno<Y<Qenqx` Ԕ0a B#JJ ?3` ?Dl#z2?w:A?,"Ϡ z=Od`L!4rO5lQ?&pC>C\[wA{t>1TC&tLx:tRtBHpOV nW'OaD+; k)Q_oѝp/ȗ*?0/>^?_i~vu_w]u3RaÈ9 |EE(В|Lܴ?2Gp{9wH ˬ5?JbpѡjZ NyrZ/JX'2猄>!0q|E+K wρC~Gz܈%p'?=3pAB;] Du'9$i<8!M{-d 89"d=4GK be$K8_l/#rg(m B ? /P0ׇ0dDc8cZ~m d=Osof&yh}jo eNs)x coCxi\Bٰm$?!6 801bs![qn;]~j8klE;Hrg\GA83~; 7(NNsCojj }(1lrC 䍩0w;}ɸ9<kӈ3n;}J^FJ20Ukșn$YVbīxJcxfw͠6+ ,:9HGRiq2 ԏW>^Wz,Ƙ{26>5vIpDYmn?)2cUds0?KV|=#lP4c ^/H~_$fb?sg8f#{uCV|G3g%a;V Z?m,oO5R!V94n:Ur%ts32V֦stRٹ1IBЋ_2Ø3U'C7rr{9m/Ƒ0qyʉq[hBq3Ή5LV  gVޝq,2ǜ6f6vQ[WQWfF|Zs1yg|ϣԗ!=/}1ї"/zmTTȇ=i\Xa=3oHoЖYK1P2sYWd%t\C$ Ds¨+ʠqɎuٕ(wWb=;!pD?3&K>n {|grSM6E1:6okоmŨ5Y6of(-<7 3E71f29.c"0l('dx]rK'hFG-3O6;#sgN!ncUCx:.?Ahfb)Z?3};X|x9S,Jr{~m)i'~AZ}Ws[1[zzuʹl]ٓ֍3Hp-9g-9g"Dޒs&OޒDO!| Ó/$JYV!LNy}2ifX5c}6[czgC'C=CAzb9,/Fϓ/VfSƑ/}WB-˱ZGDŽ!\^="\<+Դd[H #T^z!K| t[Mź-;r?񩠆KJSq0X.4/>e>⾯ٛ#.jum6=Jk!=j'A}4g)ӣfDƑ';/I`>?Y |6f vWz8lz5*3sLЅ&c8;JPxzZ5et G n])tcKYa^cQFr0^qJJvƟ'ʙIO'qgμMZGs1Qɝ0s/3`>evCSd̬$oi;–qG}[#kdeS#w[j~|qPaĮ<9h_2Xҳ/㱬C2cL'sd^/#=ϧls݃`hI̾լ9R:{dF=zVbBѮ\6B|Ά[7\~m ĸ}!ܤQ,|Jf0{K¡ɾLE+[B-l9&KΦ>Ԇw±XRu65|vvA> %L>B>b=Xg{5^XaNO77cڙ9zh~fԦdM33tۈVvn VxPˆcQk^{&mg/j[AK74ssXOwsX/\07|RN汥SW)FfS8JSՍ>SNQʟQ?<[w%́bZGq7}s/ASZ*ߓ?E)#Sfߗ?e,j||OY?$0zu9ac)/E7O -9-8F 7 YEIQCt ;s 4]mZ%pg܀Χc#zבs|&rH {1LkOAOAgr7y:g܀eP[pl722c>IΓӈZz@;]bVϭF?SFtڕ@7G;NmyJwY87#àN:36E>AFtan]vW߼j'h/lB_kbE"N(03hg΍t;xsz(ʙ %Lvٯ-jqi:fuElXdo^l!9?Ol\g :MăS j|(5ٯjr\?3QF6{~gL͟x'}xFȹ3Pl"tHVCZ{gs2~Wm2 J~1fE}z{> 6;\n#ᩴ) :(8Etf AWi;!8[ˌE3=*t [3UKnDjZ|whap}R. g ]36קe?eyy px@uf}I6Ǫ}=@duL4jsU?3j^߼~OG`3kRIA_;&ϔ vg#rטb {)y5!N3H;z `m:(p?3j7{xն`2q*85&crWY*Dg̐.@p1ZNg܈#W,!0G9B-\b0f| ̃8@-H;` V#ӆZsW[QT-ëe/\NVЗxז0A19΢":?SFtwO?OA,|)!z]v0_ ~A{zE@'@8>cJVKZpcW<)1-8WKjwL kIm:Y0a1$SskvO1e`z\֘  :꿲h H(wZYgZ;7ܹ1Ua0I#4Rj:ѷp&:0V}?ޡ{ynSctO!6*%h:X8] B`EQKn@j=`d.*؈xE@ njAG:[p"qE5{{xgFN~ ȵLgяԃij3Ukn@j0w,@ߐ` Dm/=k@]2 r͢z%ڗoM a~&nGndJ7SrsebvQ/NA}Kq.i?2#:o=-LyqFw5jyzvԗyi_}JB~K~'s6_~ duK&EBѢKvdg^|y)H12PKFFm _A RgB٪o~}{Ah/ ޾9}rcZo_lՋ/Ѿ|tƞY<(Jds,Ҷ Fn=&L($K;iҳ^|e}Qk]2筇v*hE_D}򪶿\:w_Dcki}\^QV/*IҊ:2JKp< ?%_иWiUOWRf$K{61o}ڗ&HJ6{F^7Kӣ@*N^}H^|w5+ž"NGAJ@GyB+t̷c4-hF~Sо|{^~K_/iŴ4T_|et}Cws?8BV~LK^Ku)h_/;soI_2a"@1/¹m8Qۗ}'}YO_ho@՗Em?}[}_}Зeֱ[)kBmWX6PF*Y7؍V׹~Kǚ]2Vݲ\NL/@LZ}<;zI}kr:UK*ˊqJƑNu `2w3JƠDzhzܒ.m㷦Wr ڗ;K ̌ k]Z/QRӥ%nώzqZ/{Iz 3ދJ|%c0+ƝhYsP+zvԧvi_29c8`2Fae_6ֺL+4|ui!G0leZ"!O\MD ,)uVO$,}@M+}FI]6cg>8lFi5XTrn{f&q^Fܛ ޵Ԁ6PoviM8nag> bw%5¶촎F!~K+m+a_!aVg>8˷N;»)9Pcs?{%#<2kb pe{JF Z:zOz#k2])wɱ+f>ރ{#3ch$KK_}]il_}}Qޝ/[ق?&JnV.P&)Ґm_;;?[)h_=ǨgjL,]3ꨚl"3b i5W٫LaJF%Y|߾$qޢ/*TsJbuFEMASEh;2Ƴ>ՠKb%F]KꠦhFh # IYE+4yJھ n{Xkώzq/9PY {F}ᬩȳf[_F8ܒ/`/=V}p/qoN*Ь(F~^o=i[)z[]hj{==lNr~e%d-,!QIPh򖜝ܴGDl_}v_M[*G y|/c_^O$DqPqA+4mui'WgwNb^o_rw1+ou@~^ɷY`6;[NS3dp?;s/߷/m,!fq%Y3/mv}"m[.gGb+_|oH0sQLGw:#~~(M[REhm+Sо|_HL]'2J ,wB5d[r%M|vEt<[i+~<"eGN#wLR:Kۧ~'>w.G-w =nT ={0V|p0vն 58뻐\[QT~ *B1m/xŗh_= )92U *^j)YwFm c.-i^w٪_}v_e w (בA n=m7ugDmo=2˷+![!oA%>C~K+’ri}Im;7?;3Z~}rN#_(ݍ۾w;~ŗh_#)+8#ůgpKrzwr~'(w+_Zp:Q_j~m8G~Kz64ZD~imO>G;jH?[h_{iE%,df73yy1o~J`w<ϝNqgg/6Y%؆17P$ =6PNQEDh;Yώzq/eq =OKjoSSsuGlZ|w(fBvഏ_|h$s|/*G3vq20/m pI|Omg^|w|kr9]>!J]xdv׭5i^Tǥ͌ gG mr %7~MPz2P [RU*fni辰4SWb^VƖQx׺Rڑ.-Sm }yJ>|u>2FR'J?>5S<2NF>C SM S[KK /=E.=य़'=F.zޭIo9|s𗫋`[rE 0n]X*4x>W,ac"=YUB CuZ&d= u1`Å Ӕo2x!…`QϼkAϴk==C_01T/t 뗟Kز z(<1aU".6?B'&v&[v{7`Og Bz۴|YƆ2?Y_ȵ3őǀ)# z~ #aq ~tM鄤vkMcdBKXy;=iC^0S„'|"`O:W:c0MbJJް:Gyw,p^w'31s=?B7s/EV %'$̏!umy@:vuA3ranxHrgoLh挋&{O$iwLxc"Lx'챿M#إ' z-?wOПa`ϫnz}(z\w~3 ~0b5XN_/oRAs"ak.O˜/34a}͌ zذ| y\PvA_Cz8c}H&3RLhd$=#d Q({uDY= 5g^Z1 Z_ mFe쯧90Z XѶ\iM!G"]S{?$\-M2,P3*SCAv\G83i~,5ٙ,aN- s},{6ܚ/}AVKnj zà?R3<>% 8~[AW^@r=ra#V:m|烨D~-}Xg$P?^I?_V՝]&!YP{HX]>xY v>$d=`ze _%к #t2r Ә4W 3ڟ #a󛁤sX6~oɷg&::LZR~"711+3謨!d=M3 l}H.IFz3s&Cq-G/z/|y}ֿ "/gAXq^d!o`a$3\@>~b =?JS?+{>-?W~?,?/ Y=-2tx^)Z?WȷI}sx ^&0.t`j}oj>L8߀~ uP/)俁]  nA#jBpHaF:2BwMM?#:#mA iq=̱?߻b5~#ʫc)63k.Aߎy~7rȯ )9 [ݿ8s_ K&X |sa6{/T#{}Eȷ>|!fO ?&w0~ (:'a<{',3/D<'qwSUKt Xn=FNYz/z$1sv>MD}t1dP?3ĿW1`df~ d.OLoxgVx\_,ylGIӹ`X|ئi82 +oWoEI/^C_]һ~+A 쎗=40 -sMS_: 3W Y?;{}x~c~c=n&^ %z ?Nr:*7% ֐+K"#Ӗ-2`|_#ń|wחK? Ƕ| QT%:])f*ubzPŏb5a0 q77Cs"7+ 'q[F#w<~}G02fcA„|:q~#1??^YK`',NxDt%ap!37 NVr-?f"?\z`zMGڜ&lpa1Kb]}|SڶB8g*~l}<|swjSxVr BIE}ףXNdFnot Y?© 8p֗_CKySHfg$3B_ 3;8z},.%C2F,t?Mv4=$\g&_NnxJYm/<0q!9U9p!0_ # §‡Swh'Q-ߏPZ'ܡ XC[xE?"2:ԶGcd(>>;&sd=L)Np(Iؙf"nP %'O,LK+ n>mx=2p3)3P~iR&8bdO|5c siˌ1b}\Ч wBt?΃!L;>|ZMǹt>#aۡW}S|@Aקc;e"sl:-Dw} {#7p*OLƺ7|sp]ĆIr0?֖ Qd%edѭz'G a4y:v6BWo(4$L?| O OXpZYlBX>^z-77uGs4=btt"πVρW9a|/ Y+ǰ}P=cCh}= zlWFɖofH>ߗCoUlŎgfR? ֨?(>}`MF]BgBWE^'Xv[|`IL,Ӝ; Z "ѡo<*rOgK# /(l_G˺)g->յRHi!G>[Œ1>ϒ2DuOFG# ~Pv%"zVC Ϸ|5l?BoY'8dwOjׂGnFy0X}E.QڷTX_)0EZ+́bߵm/s]K';k{; !iqUA:|K>Uz\Ry UzRu~#-NVбС"稯۲K 58k~^^Rt"v: z/ +#o]07L8ޯ֫?eN"O|8ߡ? s?1 l<`ԠR=?,n  "㮯_o~8  aGh߁ݗ~_G􄗾#tI#Q=$]ߗ=${ZQSl'>,0;00ĀP`yHh!OW? Z 䕐Ca88Ճ~߸y zK6t83d=A o-!apDj?]"K8p[? DJkA&'W;/$[W?15?_v_ńxO^Eŧj#_'92l 0K+G`8tM`d&WF#B4&W3v|l.6 7Ee$݅Pvj1y,iI85^,IN]&jgso}10~ ^xBZ{]nqy:+t{^'y_n G;J@[j C Iy涱+Aa|۠N66GZhܯ2aN z7qzs3.$O w97Bd[*s$ZM$?ѩ | Fa@|[&ic&7O8"-!'K8[ rrtˈ>q ~᧍|0-ig Rzb,.I뺪i~"<}ٮsɷ/BWLJcoYMS2`"e#6?pgI(5lH .rY P¶#ziq.@TZ@`%C@t cr)p4M }C2,Y^F3"ɡi#^*fk\˫C  &^9(HѭO=ϱ#Ta3JsW9QeΨ|eҷb Ξ$32W:BP$pZMP8яN8ɱd&yc%պ  ?E<5w1+ 8FzO.Նm.0aԩކ?yt/ <}w神 0 _6c{}B(>.z@NpxmJh,YaWn+A'Lli CX*Kdx) PV)i {VT-/;۰>m`Luy$b_Cd?mĽR#82Ī$k^"%T9.7̤ı~U %C iʳM,I6b:sJ`e(WOp1;L``_b FL<ܰiAwFg_Tr}hVX--8E Cxv0^1ic&m6j(Y7uli.V g a?:ugMxƖ-{[בYfEl6ics6_r5ylo|/$9 ^Nq #dU-|G=s%g7G)lʌY|Ǔ˖htΠ:͗%LB4`q}J7)U;?kF~ 6Nߐ^%( "3+ϩ _}>mx{>-,ž|1 %}Fچ8&O\d58픯 rvoRT&9b@0Q?`|$\E|96?ۘwW?jAƖk}<(6–*9۶VS8~s(hH))i8Q8--g'483!d 1ݶfwwۘ,/kɍz<أ XPbkՉ/l xҚ5xzzN&>˒2D?*a5$MZ'h$9럒aolrOuÑ% g!J}SluüwftZm>ɘ P걟?-ըk.1јp&߸.X!Xu%4$e>bdf\9yN" ?Śٙ^&Kc\?xVo)ƴTrZ}LG[kmlDmGI⨝Gqܝd`~dd_pCOBy)){/vT4|z'@>`)Z/xsT1 uBN=N_ywXwcO =wYl |τt8mm>f hH#T-N2m\s{<&2o;jwK-oMٿ2u[ 핹sQ3-!kgdvE9FPj ϛ(цNW[qc6]!h#p!WccooLAj*n٥]ԆEm@k"R="OVjLƝv(]7VpO([tLmd62OцF)NhsTsq82UVv&Sd?[<ܩw;Cvz?o_I%Jb_0v_Ҩy7-Jtsw&[՘_Tz11@ѰkdTB7^XX ?Rў'd{xz C5YEP=FikQYO/zϟ®0eSr5Xު!Xk Q Tj{mM,䶉'zY=?oӿ׿+_o_?C.R˚3O=?_/GR/ӵ endstream endobj 273 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 263 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-034.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 274 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 275 0 R>> /ExtGState << >>/ColorSpace << /sRGB 276 0 R >>>> /Length 6994 /Filter /FlateDecode >> stream x\Immܿ_q͵3lm$ $ dx|n#1|۱ ?d1d(j(JW}o?ϿʻO~ݾ:!_G޵F?|Fq{g???~zOՌ?o߾~`5pEWot׿~~{߾w*osww}_*94<m5_(:}}Mw=]۫]]\>FAjT}6{}F[V곿vf񾽼^OO=m~_M_m oF!j4zV?szooʭ{A^,z5kA7d3Bfu_sD[;zav0{YN跆k'yG7Q7xrxֿO߽Zwf_fx3}9m?.Q?3fUܦתʻ}7OSd~{/t~1qA1”1|XMgal137 XjBh3|ԽA|y0F&)`$ZlX I 2*ޜocxha?FZ/`4nFaM%~{#C,$M.һih Zщ : oGqK.N8MEjWgkL.hp{gXw_ӆ z`E?L&6.ʭ,/6Vs yۘwֆ7ƹ}ocC3xjk+6B}7C1#F>ު,fuϘZw&\uq5G:+[L^߮=^GOʭ;X8s]|;]ڀ`p6؊E6hI@'æ9;>:xsIc:X+NWozql]VOuƾAp>l-iӰ}{ ^= MX6ŽM}|7᭺8fyn޴ukH0Kԗ}+ͻ(_r5ZK7/X²IK}5ZX>;zk^vD G k%6(a%l󹝺A(;aW`wU8flKp._D}E(K9B:8ϩ)]>f]쎺t8nΩ9t v"R7(~e< nw &b9dMK}AUlk%o>*:8%%I7((rEnfg-ӷdu{|R*H}Jbndߠjԅ䓭li_&fx1&6Va} ŵ2,maEAWأtQa#ة9h GPf!gX&($y!uʈ\؇ck8}h2W[8M$|ːؠ+b pGQQRwP)îvkeqlbZ3Қc"_8z|F>_Ž>'6gM_Rbv.w^r`V_m4&J~̓!0UrFk>nRc^+5Q9t1ɱl;AOy*V{D@+9Ēn~$"\nReKv[uoa1q}pLJ{ ɒ ԙQ8}u-ݤ5"a؉sw8hnD? sɻŠnvcgy&;)/;aW`vxQ}v7>J}0=MJs>Òq- 5O)]>OFGlᓃstc4xIk7NAZsxDXOk/ݤbuuîv_*N%CKr.ֶ Ϸd<-^ H`{h}ɲCvMVƦs߾֮/bͳyb)KXrugT2jKl=|nReKv{/$?.N7CzdQ낔C%EpN6揥˖<, n "|}&8`/2FQeLyGKXQ+qH`K(]eKvE 2.zƺ/ ~| ^y.yBXQ#Wrq:"AkM"a8{ɼy(}'6K'9s RM_lîv+<~6)?;<~~9A!kjג˅:8ͣVQS.}ؽNc̏ZhMQxQAՕ'vۉ|M_쐇]}ؽr}fX>;3v!d{q<"\_;S;ݹ1@Lպt%}ؽ/ 8l \Iccc[$w1GZ)8x6YZAhenU[IĴg4\1C;lNQJA%6(b/ݤ%]v.0?JTߺ&cOPRՓؒ$ @vl\Iie\v[ȗzHD]O[tȒu^$dԐK&wRw˲Cvv;KgVloyKh Rp6.䈖ԕ]q@fْ]펺WHθ#ڱ`byZȧG j(aMbO]3)]>VLTӑ LR f>3KH,IU]JNq*Muaْ]>^Wu8lۆ+-#!+~$%9"ŠZ"VXt~Qٔ.bv.Z/Cʃuڅ p -ݤteKv;|jmc/Np7(WR;AJPžp}Ke\{=WnY6f}[ѪtO5CRs.9GEJ!sL`/ݤJx䤥>V]pۿh[;7^Xz-2(Ku$8lBCvv[u"O hݍ w'EԗzZ Jq ˵PZCvv[ c{B\W՗`EܬSp$֧}&ue\v[s{^H[Sy؇ݚx@ҙ˳soRWy΅wbj]RX8]슲Cvv[c4-'Cz= %>^XQONυU6岋؇Ϻl"%_X/Grڪ> -hF/*rE/>fy4889'8N%pF-lPͯ3k*Asz=y=FP)$IEqohIlîƒGY=E¡#.]P[ؠ<OB7_Rvv[ou_2tJpQ.ko]!ݴ}qvvp]cQveW]0wG%>m7.HR}/9M ԑAX,{YeS.}ح b}vm㉁ 4/)y& !A;pMG>Sْ]펺𨯵u|  >#x(9 ճ.T#,/NIwɺ쐇]>쎺 ݖ q=&M< (8JlP33t<[SwLʦ\v[G.5AHi~z7{)?7At^&ֆZ_I)eKN펺(2YyBjC蜼ڲ=p,‚ :8V&CwPe<, n72=pkv9%qBuٹ9Y&7 %U3䅄Iw͜ʖ<, nw?X_5Ÿ[ظomP'`j[bE7Qv.bvG]ߎ8mcmcc,m%$1B6Ƣci?O۽kێ7ڮtQ, K+Vԡ'N]s?yEn;O| ~)aoT=KlɻvvˏUxLT'~pDy~c'S~0lP+s96нcQaW`w>/`+<OGOEؠrs=p=r+QG*7: ~\8KA1*[#tJlPU;ࡊ'^K7xʒ]V<܌ָ.Y'ߢXB3gXQΑ3/Sw+*r522t3Cxن+8p|K7YXK5tq*9m6+-ժle-"ľR~|Α(G{xaEk|@`NG{uQ؇ݪ ow ܘܪŃB }JJyvFx.&ũ %bKM+ZWVBvv[uAD V~A,_ϐq֧>EhF_쐇]V>?wd"ƽ(/TiEV*3s6)8%*a{wM_쐇]}ح3q^ lΉ3܅O]sm:,8DQ68iW VWH/_?;hq"7,V-qZ lPWF@t璇]Z9pa;3⣟I<,W)?yXQ"83нYDْ.awU?^J=ZMF:p_FX^yꬲC~;[q2=}[x2 \Hp> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 283 0 obj << /Length 920 /Filter /FlateDecode >> stream xڭUmk8”z!v$YKv=8wWɚz[Iȿ)B1Ʋf3#)xt49՗UjmnH>HH6.^w D_[P*TMTdinY*nv?fֱ_y6/ƤVOz[m=2̹\Em6<{1GL,uN~f3TAQ v&zLl^'u[7t`QiK|V*Y%s>ϟę B# !t )<$>[$ND+At_a8`IDYi=|L?$9+s7 ٶ0K[R(Kϋubmvd+*7@>$mx'Ft-`92CSJayI9Ls#5=zFi1V[d~/;L~Pah(ڢƎDx8އd? 3sͺ CxڣRGAω8I J(]lĝGY%Y$( R4εS}䁡YÝ$9"McjMdߊU+*/`HS6yf2p ̂~8gD$JvM~ш_&2gCniygIْ'FXRc;">t/ݰo6:0( i'aU=sLz";1QV(\Z>.rd(˶r~ُMCA񘦚\qf"25,|z:\@џ1vjor4nQpu B$ !'D݅aODK%vwEZ@a.|? endstream endobj 264 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-035.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 284 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 285 0 R/F3 286 0 R>> /ExtGState << >>/ColorSpace << /sRGB 287 0 R >>>> /Length 28886 /Filter /FlateDecode >> stream xܽKJ6 ɧ|39mA *Cs Rv V 7c=}zQ cE02cx֯U?o?ʯR߯_%E/__o.uCj{] |~̿Ǐӿ_/1?U??*4_X?뫏Z__k_{_P{Z u^e_]3~|yV~WǤ:g?l?—}_^^4]5~Q~1_3^:{QC5V|Knx^7ǯB2~W;~`_\ĿG LiV\k]:f5quoN~NY#ͫI~:S {l"\ŗ^}=u3JoIʊ{܏v~KeW_y/բ_s޲-y ī5KO[ic!דNKɘ}^О2p .QFI6բ\_eۯ16~_zA]o>~"u1Gb8ߎ[Юl"_Jǝlu1ŗ^}zv,`s]_s|wZ z]O_o;ƍ+{kO^_굪˸0nݸVoؼZKeʆB@Zs/$ԛ5V֯yrƢ7\wZx\ 0ߵqW,)+y(+>R=6K/>oם(>IٱnϺhs5/o\}-Goͼe066z^ZyMı9KOw@۸n&%y߀;}_߀e04(+5WWkneoq?\_OU a~W!+y( );{l"^͹ŷ^} v}%:/}G>绞ҍxt%g-e1S+mGe]wcburrnb_'o@۔G"al^->DmbD\9֋oz:vׇj7זnSv^Ξ_ڙqN,բHZ:xDs/M%[pU㾾Yg9XB](qb5AUe^&՚|E7[*M~_p75~Ƿpn\^08䏆Sd06*5euM5ҋoz8c\G|^'y}.2īz3u֯g빊^Ƕ\?l/?9;2 ~?+IX,+ım1wq~soM)֚Mh\[nܕ].q`INƲBW-[cScj-So1t_gls_Oʊ ;qģ1X~Drݦ LY!ͫEؤl۬xn~ۏSoz,zu~2/ޑk!8ǽyg<)+y(#y) roe-Sou8[L^0Юg"N>-+y(=~RI96K/>oٿuo)F0as=QŔ-x)rmWKkDsO,j^% y4oodI5ekrj{y-So?c I*_>ݵa㥐ݒ?+l5ظڔB) 'I]mɹŗ^}rb=8VN;oˣ|B%QdSv,x5_zIMoſl5ŴZ #=awIal^M?eSC&՚[|%7[Fw}'I[!k-^0tM_ZVcjQNc>a)Ss6| >`Ʊ ÷qWGO'I[^[XKbwc#6H;c|=ҫꏱ"hJfM8<׶dY!U,>9%" ٧gדhm#>0eD]DkəբxS.' d _zQMoGb[zRph w` _KFok[cjSmMǼؚ[|%٧-nX;u^J u a| WHYRRwlp{-_/(~u}FR&, :7g=߱*I(Ii0[?0}FM޶@ZݮVHeF6ƨZoY'ESZliSƖ6ǮyR[/ʾmLB5 3HW|AgM{P9"۵ve>֔ؼZoeksl!^/M%]ׁގx<'Os ;ؿ2}Qb}l\=6K/>9gfx1DsskB qlcEI{l"cndz KlI3já f+8kbi7@emIlV]}˹ŗ^}ݚX_OʊW3?Xo5zsа?)Yۥ[/ʾ߲p8/Fq#~1vY»eY"ͫEP׶cjm4So_*V/צ/ D?].1z `D1 u[Rlc[rndz1-|}b@d 'ϒr`w}O{LATi|G 箇g~HOg%+e˱9KOwY(>#'B&DJ_FJ֨x5%,-ezM[~|%7WRp2݇KRvKk*vqN]A;¦c._zI0'mb3d'eq ލSyqN[ZVh:Ks6=vu &zQM{CA%e]xb9ojɿ}e_R&_7͗^}wKI0X7$ϝň;ߊӠRK֨y'|J,{豉R[/ʾX 3C<' ĮKlG&޿-"jsdYԈHlﱉKKO-bXqa[6a98󰄯ח16<׃ytWӏq>ӯcʈe2<qwmKEbs,kԟ#;}A=KO^`_ 'Fam3^=n>)+ DI,x9v}_zI)T+kOʤe5#d}'ǃ'%q7)-lvc׌K[/ʾm^uӐ8iEUis0ުuN[UhCv9jjQH-&՜|%٧޶NzZ&y=)a{x.7.idiɿfh-R`&Ys/(~KEBML yd9S/˾-{|}IiXkzV#De>#$kT5eQN묱ﱉp_zt-85 ^OJOǵP> 7FS֨sbJΔ0{lߺ%_zIMo+qLw7 #T<]-<+#(dB E_eyMw16_zI!I9#B-(yC4:2n${-=6.zweBm[+/rjp4o͖Z~2w,=ʹŗ^}~q~TDc;Nɂ@D6#2+iBxe;=6>KzYm1> Mljd3nYx2ד6GNYu@<"YUsJYY IAe .XY>Ycw TSA9OW[Vcۚy(dLj}]]-SoێN*'ebdMXjD h`βB;YL̲wMdkf-o UGP cq+zeJ5=|)+2#הbD{a_^M26nSz'cTPv!+ci>BSVK 6/)]Ǯ~rndz=?I#=T|ψҪ=n>5R]‖c\)<7֋oz( P<)y`6_J RI" vA1_|BQ;m>}%5ؼJFV=6hɷ^}yo8"_1bQgvY?Vfs`|R$+3Д1a]}f͹ŗ^}߲ sky?)Y+Zo\D3ڲB}S%d&՜|e٧wf13ysg0c7G O[" вBֻTGIC0JZcsndzRT#)3-:ё4.pc!;=kBû؇,9v.!_zIo":23"|X}{ލgFQ˺:&eطso(q̩3eUe}ю}%=cUF=sLi,&Y$%s<7֋oz>&~5adEJkRL ǮcKb jy͚Z0Iv!D1~A0 a ^aբ{l"9֔oz3ax5B_OJc ҂)$vpVr::@JY#EibZa鱉866zY8gfE#Zv%5ei is8866_zIm ?UǺ'3kjnD;+f4djfߚRӠlNcs/$6nʴ=?ԛ?q}2!^ݲf_zI}S83< +RTg'ŊF3*MLَI3so(m닚Xדr0rRC}[|?DнK0e RҲх%xndzCfT?r<)Xv2Ga!iGZ cdd]4a4pe~V|lvR |X-KT_n NW-k}qrrm4So윌'd |H?8#?p?;,Ya~R:cjNM-mrBE0DZsm'D&,Y!ͫEQʪ&՚G0ד_0be9юOe҃Vư,9vzsnemauL8(e4N 1lWC?[&Y8)[l=mm%zQMo!{۳ؙ\E]@ju|@A5ٔM]{,)X,zRZ+a3 8qtm ^|_RV(\ϥZlcͧ^}9W [*Ә!2}%'3?gJ/Ҁeʬ0zWy̽r#e|bCϧ߽زn/zG]pҴ21h̫gח*f̫u/mtnjXDc27Z;$VvD9A(XkC&7!G&:,G)ﱉK}Soxʘؤ}7w_`G ^~JHD_- -=N1vO@[|%٧>*בKI9:ؤ^]*f3%SubCIյ'ܫCsz1cM;Fu= ʵ0)vRoUaodH'PaQcwߚRMObHs\1loZeqvGmϤ4}}6]n~geP, [v!mcs/$ں]AbKqss0# 49mt8>7tmdy$WvoNIp.=6KS>u8.ׁ3?%|צO RpZԫQڢKYpٲFQݦtTlGMı9˲O}v]rd)'"Vu͌דY|BJYH Yv&՜|%٧ޡ$]1ޡxiksoHWyce|~Ƣߢ؏y]6u9" L1Ϳ>5*iA&,aRDS/ɾrs&)\ω NUX4 OؖPk[=r"s/$ӷl!)>EY{{ їqE> wDƬftzi+V@fkℌʍ>݋=18|2^h|_lMXm Uf:0~.o_=IA 4T=qMNH˖W/E dIkǞ͗^}{=(8ozMú_XÛvs|FZcmbU;eDs/M%|~3׍z?-XngAc#LwZ{֥J *qMgIZF~&Xau*eqsɷ^}CNV;0bdv^_Q7.*Z{u?"ÈӯhiY;J,sq|E7?;3ٔ`\QnRN>SV(=IA应/NOb-SO%Mdh ?g T0ؘIi(:BL:ߜUWx#]C;LDe3cc߶a _)YTGTDD牨_"7<(dľdznR`MYMr쬞sdFk[~V{Y9/H|VU僚>bRu/1=kBw ۓEi̧lcWG̹ŗ^}xkj, [t@IpauhY$LAe[ݲ&zQMo׷\aFyڼa:\(ktdS4e0αGK/>v / 56?x=)lpf8x[MHDwUQXjWVS/5exET׷H Koq o{{cwUnj S&G?_zQMkMF 7/<_cRfcq?%EU%!'-kT3Ŕ{"v,(=֋oz߹&% `ĈsuFC##en+(jZ@X}d/Ym>Sok#)Mdb.'T`^߸>Tq#)؄YvG="XNu-k4j G,}K/ʾm?.ٴqTv*ddbSbZڣD~?7[QUĒ=^_kO$cXhi%ψccڂ[|v?c ESW&qo=|%٧0pa=_c zOƬ0Γ!k GՊ##ysX.*ʆqRֳKý0X2Ȋ4xOi+zuHANxLyB!t]ƼeoZp CS̅-΂dWN@~CoY6쵏;RsntygIiH ?egH"|u!UTtlEw]6zY}BHO^"Zk0œiB|HY}|L1Ӳ6{cw QhK/>#b:IA|MP޹ǕťWƫdv[6ewd8=6Wjmޟw8dz||вWcS@|TCSd4Wƨglcм#b 0ךƼ3aYՒ{ 'oa<036{1@ CV|TNY8E D>b'>So8ݎNvY'oyC$YVde!g޵G5֋ozu(q\Ycޔ Dm(xK#ucY+),mY^O=7֋ozx`M ƎmBl6HOzts ZK "{:!= 6 3ځ}JOGLz,ևd7.j3q)\˽ >1xJ]`u!>g.FjzR&rJ<5TN _Ɣ5؎R|!S"YDd99 CModUqUcR˟=7և8Kv^,~oP;‹e#Wknewd!a/2չSgTЀF8*Þɨq 1V ?[+3/¼bl|:r#ioe{s9_]|E %p)Vo17_nό첖V/4pY.xM_cԪBՋ1`^ZIORTao`XIaG8'X=&·-{[ڲB33LKY$=c=KO?hÎfݨ~98)(vg+pEa)[W 7oqKQ ΞtIeU'זZYiŔ ehqWwq>zRP4"YW#zȃ? YY4֘lE ]G&zQM"soc?)Q!/lmvH?>wI!G8+gi-XwQ6J\kOD)\¯J{Nuem[碱]Es\$dSԙ*W9;yY"MNw=I{.S/cRyc:ܨoʔJd }Oos}!.PMSXT=MLQg9<5Y۔Ad#=9ҋoz7sf) GgH`M(FNώ3yL\s$ [҃ŗ^}aUZ $Ә1'(oa6ªs>X cR[X5_o$~.7 95GU=#dw"ŧڲBʦla`]l -SO1-'gg|)ב.r]4_]YLeC_ Q|#1G>AL鑏8iCQ۰eDa^q+1zAKrr1 "4qd7ԛ ̦XNS99#Yso(W3wG_<̲dv0{P:R1q'ZAW?rlE _{EJUG wPnH.k%?ŸS'𸅉 eY빢@'Q$+T3єzmHDp޹o$$~ 8Pp$Ǎ^u9Au { [h/7FG=&zQMO4̕u> Jo +ѝ3ݔ $HG}~W)sfQl#OULI{x˹}útѹ_jaEc;·k`oUj+_ؐԕYƘQr4{7d+$mD{%֋oz87~N[da*6Ö[w`w"ElHeiX2vq-9ؕDF5Oe㱉q/GSOuCHMYA!nĸw{PR: 0!G:k3^/TdrjXZv5FB5ʛeBt<63W SoٷOYU@>f=Q$v'DFmYeVR'e'Y_s/$S>Ec-P } WȉUUZr簯5l s:YꗝDDx79BXg&MQwanO LaYNK-VdE7?mmڇ.P--(O`-b^ͨx菮ꨔ(.agx΢V}JCѵt~61T01> g]!F*gJl5eVDsO,-|0ƙ5"a8k!3darbQP RBFB;su{uA:K'+aWZZt=}L byc,`p>7ӹYH +;G96o.bnevrS5M-•وUha )Q-l]EBF;MD6zQ]j xQb⫰:Wlhx'`{Bij=13p]$k0}oO mGuMw'Z#a%-Ǟ?q}]8LS;{WK/>=* _W۫~~d=I9Y*t^Fu>?Ov ڤ,zVhGO -ޟm!ƴ6d^(Tuߡ+NQoLg6V: z͈/m"1/@ForRv4e+3U5v][O?aKouaBSV?1Q).w[-Soצd_OIAN7+D0.lwlI"e=9KO?٧EEnm#ݲ_qЯ+~Gه}虶y1`fnx'Ɣyh*i2jt33g$-NMq}Ce`T4';e;YoľC9S]A *l'd'*xl"RK/~aTj0h_w!ӵNZsvY\b(7(VE$\Fwcv̨ݹfROM}wK/>](1΃))]rq0$*c ȥ%-b9cۻ#7Gl@$d'#%jqj6.py 9''V|w%fZ$c JKS>pfH/4v{w֛N;w#w)"['ȂJ¼u+6/Ⱥ5EAXQsd?v#W]̇?&eVV1 );X Ycŗ^}i@X3!{m*sa^__ݧ=kD.3y2`V cd82}Ƙ3o43j1:{z|Y?{ǰ]^(؇"?3Ae]^6Ndxl"^͹ŷ^}:XýVcL{#pT]!dPFПNT-XU0F|.(;5)u$[#ʹ+e#$,ERzV]؃u2u)ߢ,~ &i do͗^tFf}mOG8,G·B<ݍS1}-8z6@}zuF?+zؼZq$;籉x>KSʾ^USqJaLV++\sf%b^zKP9/)'Kyp-<}p4o+{OEe5% oh ;jr}՛.ha[G7*˖ee]ɷ^}1!f?NR؟vy`b}kF9=R6 ", N)[P cŗ^}1skM1ʜח^~e[$fpt|;4#+rV5o)d;Wmɹŗ^} =GynTWRswr!?|( gVw=Q͗^}o[d jJsfkʹɷ^^cO; F_Ø{1揝Kq+'Mhg_˘ʓmh?՜ٜ͝~;5۹3gdI X`5v^ٓoM)'Eb(^l5hE9pgV%~FؗP06ڗ}DŽfדg݂nIMBp]߲FfU\fpzl7_zI͚K I*wqFlY=DzBYI:)\<%{pGV[/ʾmcPRh=k"208yIYLiܛH!9vU[|%٧ޟuDXX{;+ WcD!jԝgFg`+ u 7| ~cw q_;7X3c JMc1a:K󕢽JWJN ky?VSUVSMUx;t{Y('p5Y9I'Gڽ֋UDZ^}aiIb-kᄇGvQlk6_J'!(+Law~Ⱦ kjL'1`g|8W:H):o;}Uxo8`,k)HNَSޱK/>tZC븨:yԵ_VETVDto >꓂ZN̴Kܶ|r qHMT$-8iIc㎐3zYO=YSn|C_zєusMaY>~N=KO֠QwRX]4]b53ݰ՛OeO[IgYȱKyne=3ncftA(ƳG*rb"U{“nNV{z,a`YO)XZ,[xl"^͹͗^}}LOFQ#sAAl]Yhh/e;%F" kŗ^}(FM):{Ƙ"[ q7Y%+2ΔŻc统s/$SMRz:; )̘;Qdz(mS6"oVfĘs̔:+˨5#~dzAʸ>S>(@N 2>}hYq}drcyndz:_7`38=/c&v>_1W!{;u8a4rT*\<`@QY30sfW¾ĉ3G f1C&7 -m5!S{ l.F0:m;W'jx;!r;+'_feWQyBM癪?+X@G_D?526l tW Ռ7r˱x5NSoחRDJEN9YL]E4dJAE؞=6w(Gޟܙ;6;DƱ,mw`c][HоA4R͝'iu+[Iod7t˲ڰ&՜|i*٧ޟZOfO k,٫ yܳ8YᆘW0r f;LfK5说o䩕{?C^456,{ե 9<^@ Y_зdFTSC+RWؼZ[Yҵ,K/>v/H6 S - o=`; 5*y''G\ʖcsnez̻Q(zP"`IQ}%rN7ĮҲD`b+&),6_J{aqlSʦXL&,Fv"Cr#ǡ%FS֨9Z;)H۲ldcqlmSGR U=‚ Ɲљ005|'!)V-ޟ]ԘHXNհ^0{:%㷬Q1)KYss9ҋozYb؎a2ebw߰L¢i;~S[ Kıtsԑ}Mī9TO?|Ǡ-IyS#nk<Ƿq o^ep„{o1f[}lw٫DYvW&˽^}x+!lQ-x(,բnnR=6[TO?Nf?tcƘwfMdj}3y(+w4c^CTLt\d5bGbG=wԌ<UȪ ؘd>NV=2R#vq-k,<]Iz앵=Koz?]\fc~ gbhܣM$/"ᐇh8IY#f!ق4RM]zQMoAi(L7%kWYFU&~kA`i +?5kR5ï@@+p?ƁB5\OCv#雊J:v+p|v۳>( w=cjm>SF\ <)@><+<3c@zfN:jֲͧF,:yK/>s, n~W;9K8쒾wq;2+S{Ċ ]ㅣ'#ެ1֊9|),Sff1yZ)qvc^.]u{G텏F~zVM!-`TsWzRɮM =ó&=>r{I$18=*M̈]yvrcJ.Y()D NIE+"Jk1r<V7FPJ "- e] m~֜ 7?[7Vg̀Ȍ~6 duHΒA醌݊=!c"醌 <[V _++}ej̿VCǙq-Os`F1mLj2w:fg^ k ݸfS+Fnt~A3VF,YWIx>~ wէxQmkztzRt/:3_HV8FqZ!(cO,uz *.j7F jmyQrU%9T)[b%ʱ9KO?ձd;j̝xc Q&;m7x0w0Z8,dk.O:9et~eE6\ejy(#/%x^gf{4VV*_TWZd^w㤹 h{LJg"}[̊2u,kv,v9v!&zQMoVlI]F9'wu*x!8>'3Rԇ~EFj]DB%+ıy(hi Ӻ&b,CKSʾ)FROWj>#$32ψ]rdsvW[$ww86c^ȃ{}oߜ_uQ2 qo߯'V%)h*%ٰ09coUw|%٧ޟ5aX0F c_.LDNal =Nok6ۂdd$-'{msl"AA|E7?}S vZmw<к%\ڧۢtD<`Tje|Ȏڭ1YgͫF,rlO[/ʾo ,ƂVE|'z5=uCvPNCVh/ZcKﱻR9KO=<\G9J r҃]=,w(kQ'IA0m"$nw@M޶l)=)k1tHʰl_@eә@%Ge|&EbD0Y@rᰣdbG]l'b&Bvg>3<,+3k ,9vOϬ_zI'[Y˭`ha鎬fʏ9g'2✬GYC*Cf*=gƍfzl"bn}/}so9،Ƹ"lviLqEbg>M]O Έ84EaVsgǡ6d->Fߪ|XIQhLv*WwdgL3֛)+Tr);,nGc =e٧ޟ팰gaQGоxgyBX5mȚf/z\Y+pׯJ LGDňM|orzQq*SZݲ뱉;>Koz~򷌇zQNj7(; {`RVcSQ}zi=e3jc!BbDu Ŕ[&Y]LMij.5kyn- S.1&{2Duw f+R)+FB!ѱo0c#_WZ]'* ͓r"^pZa@?iEƶgM ޠB3|E7?C$N܅GGӠ)L~vfKYmgBlR1eJdWκ*TlN5PUBgS!QgVaŏݜMYݜMYpI6bﱉpzQMÈeGQv[n`"o|>h*w=Ny,yF5Oj2}M&kbR@GD%(N]:'#ݨ||Ť>}F{d>Mz|5F_k [JfP;`.kMave?Z-S{,~*5U7s1Eefc XJJGxbkX_ʯ fJVL-]b5ݓ22#~x9A?+P(k':O(c}rnWu~^{ ;R1IA8t)0Mf!A?d066) O9_zIah0`կeaͤ'ʸ5fH`D~~W>>1>/oi8npڷG7ց' &ũvYXD<>Ϝ. `%e/YYߧ{^ _ŗ^֎O:ŗI̚wOw|в?)0 lgO,X[|%٧ގoׁNIѴBߙHY`;NOKH/ʾ)Ϟ߯')q FGQϖKgO>H0.JCVec?:kndw#'ebmX neG!o>%ZV(ے) wwm9U [epY&C5 =wV})۷[{6L[V[/ʾ.jmw]T)CWd$Gē>A?_F ֵ.o]ԛ}LjGa vo (C-B}FuORT $"FwFN?\WubJvv6<=W-ޟ_Ζ#¶MWxgD9dMb^ s?Ɠչ뮱Gm#9Y]QrMeʤrʢKa]\/_zQMǑ٠lomg#c b+|o/~0ζ-ڝg!ֺ~JhߵLa>d7s5khndz;q,w4QP<9ʹi<ړ_឵Q7)()vfG?uԏe>GWu!~.H͗pg\Z$"6ٌm<5 `eن9O0&@Gjh|C^@GE+!/0[IF5 e,+B_zI}\aF=~[@e3ɓҘ&ʜ*]3s/>연; O WZ'#zJKlEYDHl]cTʹͧ^}gf|?M>a;hT {k~Ww<6wyucWmɹɷ^}Kf?]"Wk= !g*5I˺18Xjfq^l5C@X>:6:Q 3:y7$+T3-L=]͗^}@OlQ(}Ú07w ;RwƼ#c E G.];S{W, 3qWtLp%p- { LpԸ!/wp)cbXjջj7v+%ez)L2ez5[|%٧?K^G&[cE'=Fa|lnŠPXWl U"j]:/bG%[Κ)svF'"<Ƨ=ZJ>P]iyoݫ&>OsT%Ƌ )gE'JX֨Uslu]s'zSRT8ii1rnS:}9ZVV6l􂪚ݣp{S.y 0Ko:"/83=x c^ѭjq!WNS5lN3- 'I =2 v%^-{+ۦ(L Ù? **B(^O TǓVhN,Q>3񍥬QɮVlapMgz;Z |%7?M`x&;۟|ڊ|ӶG^՘W>M ~OqG_Dh<13tx iX\%$g!e8#wיu% ﱉ9͗}Þ! 9A/1mB.w> fiWm{=) f BTeoc|^HYݒ켡c3sntO e/+ L{ h%k\V*Ô5 pIAjx6 -=7֋ozB+ml܍@:O286ʊe #2e;&k{_zI 7IqYS1aXL,A"D-+f$E(Z]\8_zI>~g7zt8ML>,S*` w~_a'{JVB9oV6<cjm>SYut;nG`QUɻs%}l+OI|z\-+ra JŦ,}{ndz}tT\qIAuQ>?@] +TlJglE&՜|e٧-mM哂tFdG}*z)<#ߞ\]ᬌpt߻vq]SwIabz>5vɞ@|E7?u~TnjfE7|늀 ܲ맚a53BcE8x,{Qn`dcf/2c07#E^W,&חqd׃zJwf&V7T*Ux5MF̱)ӒF+3LAՔqαGfyndzvVk5D؅V/e|) g s1ˍ1}-\# DG \OZ\gj#-/%e; xl" bndzgh%8,%Zd13ZE))JpYcg͗^}9*r2IVLO~xnY(ݤ !&eʱtsneȾ1f}c抮#uH~zh1IC?~5|'8g;`Lni[/ʾXlXQ+TOƧjOD3Fі5ؼZV1lSӶs/(m:gRN,nSy'A-ktG|E7?9*{6g=MV\;SM¿yfgz+oXd"ۧZ¶ꖦ+0'=[znO>dA3_bWf@SgH!8Y u' ;ʊFX7l?ejV0 Dɿ&՜[|E7Y_ KDL(;QT̓c?g86uNDxl"^͹.-٧޶2vy`e'ȜanQDW8˲+&JiJj7?9dG/>  G |}d\eaթ5oAya^]st`ǟ*k)\"w57we5SccF"9xnpLN5 +ຍt^iz2bivN5#sLA\e#csndz0kk2Ëu!jG1bį8#|9+Y"m3(bف4ҒoM)k{txJoIɎzBs!bmcHYݽMAedG=Mī9KO?%.@0fx/VxrxzQX͚#r$X1ӪoYۤ,fS`Mī9űŐ}/>]r0#ocײcǍC̬WT[3Π```yTEߞC%|JC|1)&\ Xas:Z2/x;Ds[:(A#ܣ( [?1)ny;rcw/>#e]dލz~rE<IeA!>+̔~ZF5&$8-{G{|DqzLrMڋ'mՌI2`M7bl~/ 'P]?-w<3^LK~ę(6ue۹gΫYgi;PmS>Ϳ,#u-%՝9xb$ }aO=i+4IJ9vE-o_-PX |A6ZպX-Ւ0.Wsnl~?#d,[12f̟/Ljl"MIMTfy6ֶ5f'N W` ]~5ZU譟ycdt%?yyBg0ʷdGUbAʐE*;CI $oiˢ2sSoh{yF2ns!k{ su%HRߕH<2Ց9a虺/ʜ+mcgNX-o )AyWȼP3d.u0+/[S$϶[MY^~3>ٓEC.ڍP#Ge.oz{KGFӼbyҡ\ >Lăm}$A Aރd.gf|XmjՒO"$cwWN/>ˋ<}!Azz~;ѩ.K;/=Vhxx륜[z%ۻf,!OT2ŝ;eWy}Nlm:@kDՒ\E[#f{xGv$7-幥/^k|r}Zƫ5UDZ+ʁW[3٭: 5b>4r2v5,r(,; W,ABugIm>jl"/~m֘ZIǿ2l;=@  % u=:֣D %S%m1f&՜[z%˗__^| ۸ϟ_׷IS?3ϸᄐ}?o^b?~Uo{^ endstream endobj 289 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 279 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-037.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 290 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 291 0 R/F3 292 0 R>> /ExtGState << >>/ColorSpace << /sRGB 293 0 R >>>> /Length 15023 /Filter /FlateDecode >> stream x}K69nٜ)]JU6` n ËϤ$v #>J5EICՕ7w_׏8?j/ tW)<_o>??g(OG؆[Ŵ1kϿ/~O{7?~_>qY15.G~IgzVo,M<>5/5:$GN, hdv&}e6[||կ|11ͨ?$G SѕX8Ghq׮;(RXcf=5@A}/ hdL#q^ZAQ))nOb(2U?d+,aaT$NQ2&4VԊ2-5mY#*ƸzYwVvIЦ;׹p$ѣZע&[+>2%5m.[嫍4?5G螯}r6 4?A8ЊGɘ_1*=qJZQƸV?h /{~]Ӧ&@AW,i:GZ(WT[jeJ*m}oh?KYβo) $Nэ+1Y+|Je q4]͘?l]E2#95?謅5W_8Gɘ1n6đZIQi)nU_Ɨ8M}oG;UGw>ѿHz}#zC1JlUV|eJJkls8ns0ͨGk|QcN;Hpitp$Q7KkAeR*km;{sr Ɖ!`yP:K蔍#r F qi-9iP6[e~7FM ccF}7 0G|!IgT'Z(Gh~0VxeZJkm󧟒kVJŸaai RL4%IhjYVXtL[ FeQKυ٢Tnsfl GXMi7-E6[mm|o (R>sO, [%8q"q`JAniοGJ0D9sZKyTFV [@b1nL -t#IKS8G89 c2) ʔ۪?ѣ~٥6ęoˆ21O+Z5ŵ0ǒX+h)ysK7)<%ľ~aaBs}0^mK9Ċ4g<96Yn}ZF֣jjQWf796dћ'VTvdƎarٔ\Kn22wz8FyD'ڎ%Eq,*1TE%6Vuiq.Κ_nRѣlm)/[]܈Zq"'fQ!E M;j8)6Op5E|ZCM˶\jDxۡK;>Z>/} 8tR'#ĊjK}Nc&7-]v]ΪwZG闩4ǒhƊn>-Έ嗱K7)>Ͳ-]v{%tŭb|gˍKHXQ$uX^e[.KֻtL[ʙyr -^k3KPމUL(`2X̆Sw?˦v[rl6S+z>8Byc?|p,ݤ4˖\v [28'::ͩ\:J{VVa=VuH:-ľֻ̙}13&9O0_ί1g0E랯q|έ5uꗥulez '\'B4'׍|XЉBys{cMA7alEAU6嶋ؗݯ:cb.Rs@Bc@% /IY}1q LV2%5ULϽZ9O[cSO/jVJD{cxYbErY*n'o:2Ei_rѹ9Xz4D:̀85.SRZ#fkӌmt`>|Xͨ}.jDk (Zӵ2%5m+:p[kn"FMg%6%-'NO qO$~SOJap2oO-qŸcc5pgmZz8G$¸2kGYFW74}Kl0Hlݐh1f!iuCv[Wݟs0ľc{*6k"?RZLqqّ<[,R'f<\vq=?9þ0Aπ Og%x>6Hyҭ2%5m/;IÈjRz89i0qXkN\FVO b`,WLmKQ^1鍥fƀ#YRl W03%uŀLIeqot+zZÅDs-_8ڌp-F2kGY lmO ߋiEseIpvniJ  jd xi%uY*mGy; /Ӵ>bsMtI`q*H 3*b7Z#1\FVC&ܞ4Dzr0Xtt1QHDỳ8xr5<.SRZKxjh12G\"5FQk,,H3/#y5D|ߌ#: ސZIQ)!nU!*7_q؏6}z!\҇NIH/p֚_eJJklR3N3jc`ϒw ۽^9Fp+MOle/_kʈhm_TY^c @Qۺ2X:&VtoKK/ Mj[]vw)[|6K`lJŎ`=5>52v$90!ֽbG\e;y"N(-]4MؤM{?*leWZznKrmw:q]Lp VT.5ݺ-]v]]ro51QtlEql/n/QxƆq&CsH-%eޥrlXr\Sc*R~lt&Yޱla_d,)^˶v 5o10HbB5.o1S=Vhri,Ð{Ōlm)/3z5K45`Љm~ss(cEe_r#&Ϻ{Fleݎd?F4s`Y/y0"HaX-)3"twOlescwm\}Ct+Q\·h]A1^XSqc9xĂ8%tw-]ľ縭Irp )sA@QϤP޸S*Ċ^$" k]Dɲ%]vGED`,5+Nj8U;b Ik =OsXIim,vu,j3#g%&vʜE *N,OK8W̌fٖRaw. gjcδ'6vCŃkP^7OE|Z0v:nRxZeKnK}Q[_ɹw2?6͈'ݍ?8k 䜈20у!{`YKnSx\#kׁAAbƊ:#`N/K7)>Ͳ-]v{GCkdqn',8oXQ2a~c Ǻelm/gwᶟ u~~'Rۻgҝs!,FԽ2lm/_9;KVe4/g Hc>#0;^i)8m, eK.vJ' `xZc`-<2/XQ+=9a,SX)]ľʃZ; !)ω ,DٿA;+j%2'S\[{rٔ.b_v{-7`ZW_AHY>ܽ<S?rL,([LGORaw.[܊0sspkvD [XSk` eu˦vJdVC/q.]7o+a\/%1"$VTƠ%dmLJ'eSn} :h^#ssEcuvo#Ž59'ֹvHeK.}ٽ"J<0|XFѹTSD)R#Os0J؃TM;-92v/|⃞wEj^Š}_Fdsْ.aw_ LoYqf3Sba5mۺWwuK_bn'Uzc(LIʋű #Jq)[ gݤ,[r%n5'c55G|ƊZ9nkwٖ.awi ٟlV8x58n|Xd|m ;O6A Όa]g˫<8.+) AnR^!]$$hO8MufDZueR˶\ 9/6aރoY.T +jx%9g'꘎>Seݞӧ_{99}k9,[rU97[J;ԊgiWE jl>?' 1=\g>'g䏰bgz]岋ؗݯ=mOnKk\׾6k_;NX;,[r%n/ΐJ|7_[9'8hw uG׼ۻ;` u>2˶\v;uN✼~ļ[71; )e9fYXQ-o1=xb9˖\v ۽qJwF4Oާ)6^#yXQ-or11kpeSn}}z M>8[Rf\5VT99 vcqܱ sя#1يBy<{{^a ;%]vrCEڏ=7Th37TcȆ7Byd9s?k t>;sC5[7)psGZL =grƂ{ͩz錈ϔ^*{I 7p{I.[r%n) +~,9>#a/yS( oY8r+9#oZ- \Iqe[.}ٽ֕q3bF+ 3ZYIe=,GrĊnBhF,LR>\XQGSoވzfٖ.cw0~7[7Sa)5ͿK95j5sN\g,.MmU6嶋ؗ6w1߶Vvl}XL `y1aME}[aݥ{]TKؗݯ|}-sΩ'~NTbMl0W$7TXwM"e.8:\1Q扨-DJ4SP/ 9Wš[o3Sw^|eSn})k]s;vC>#`+AaMelrNzĄPٔۮ޲kldǾ>snZ>K礯Xֽdm:'<˟ɼ6 Zs"^bZz\Q,Zv52ڜxiczXk-v-9dsدt>n}ù5dsد>׺W)]ľ~yƤ=0fek/iG.&a췱lֽڋ˖\vvXؗqs.W.;n7N<οKݜĊJwEr:# wDNwE-vۮmzŁZ$.) #D$h&֜2~k]eW' )-+)Ɠ3p/2J~kq}xb9ĊN1$)J,V:Mv-ynKp`rR1mѭ$VTg,5uw!DXrXQ3n-csٖ.cwfUTqq w*&>TxͲ%]¾~˅-wpi]J38pXQc*t7 |c:fX^vz9w\3|8F8nSt,VfJ9Z`II73=[q4<ľLFŜA"']mbouq9t?鮙>eSn}n}[9Qkbf˙v'_b}75SyxNƒu]eK^ ϟm_8`-9#f]Xw5JIVĚi9 [pӺKtٔ.b_v-]ιP=t5)rեN9c5x&R(VKWgmO$.` 昫VhE;)gzgcM5{81N݇Y䲋ؗݯcU[dsXGYG:r^&299/$){LvْRb_vwGJ?٪+wѕ@aEmbVJ.*[r[J&X9Hk}9L1GIu9b}UKnoH́ nR %C-΂+q,<! HvVtgE-v>Xnyq_qL8;r\#L υ%-u}rYJn鉬>jY1G?#ǛN܁qęRNDn?%qT'G_I!n5̟| :_GBE{qͩ G|DTaG%n&* =6eZnxnDq}0K/[ ޹a'#wP"s"U`_>b5DfWDg=J 1qMͨhZ$}V[h}œdP+c#| F @<\,L&!=)7[u8:D& ==0~/$^:烀ϗ7H.>00_`3~l H?.=I:OU >kGL@G\ u5^XN*l40.=yhv8"1}A=:b4ў;]dTl^"=?d7,40rr2.no|2Mg)mp=tܥQ&r'R' *q ^\^ L?wҶfKZqnp8t=SymDI"r7uB[1ᥤsN4L;cckp)ƺ_{_rb~;ysU<~Ś1ib/a9Ľϟa^1uc{_`?s=8iԃfm!.iu?'12oDqN̕giGVg5w~}kn7;WZh Yy4AT53/0ŵz93oo1h` {R}қGҮræݿL6϶00]y4<ԍu49T?[ޡ '죿kx9~,’\וmjb$TcrI4"%qs, ̰.H7u sw1~gcoX"'ۢ^_)ME "8*ߔz4l}ވ2u^t#;̴`)>fl:vGXM9ӷzXpt$Q*<^N--m#NۘƬ8&[t=1L4.8A!7+N E[8;2 KS{*W ܍z4͌Cc64+s\fa#AqԿyդi~k$.|x]Hs%|GLc}1aIiwu0^ ^?9Sƒ؁k<#0fƒu+X+_8hXV}CƈGs8KT;KzR^KӞbq 7|yx.>cnq~0ZG؈*0V3,56J-~ӸVh lvDDŸIB'=|U9Ͳ%]¾}ݯ׿|cV?񻿚ϟxÑH Lߟr?ǟo˟QmZ%tO x endstream endobj 295 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 300 0 obj << /Length 862 /Filter /FlateDecode >> stream xڭVn@}WіwH*@ 7ʃ8i{KJ E[wwfgϜ9vi*BZl:E=5SQZ-Z$0p޶/|OB/M@eAIḆQ< ;L=n]``v7wLo9i(\x~ 0a~z&55G^r`Ķ9oeS˙|E|'X80bXk%?I0"nŧZ̏u/be?nHf,5cMJ:hDm%声:TVnpn @%~śWR CQ6]98b׉4KXשV둨Gwף0GϘ7w>ٓMo(c/(ĊFYb*1s+U;me z'Ȫ$ԏ$=wU] BӪ `t%.dG1ED:RniL';U˞\[/:]bzً EЮ=VV8R&"褗?w1. endstream endobj 280 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-038.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 301 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 302 0 R>> /ExtGState << >>/ColorSpace << /sRGB 303 0 R >>>> /Length 30938 /Filter /FlateDecode >> stream xMivy3@2sϩـMAL & {eQyuWٷy܊*~?ۯ߀W߂{s|>I}Gk?a}OxEQyxT~?.W~: ߾o·m|u}ֿCoIxO~>?7S 7P uo> cz}|c}|۟>>~ssۏ?Lcc_:|׸q^o:uxcԇ?d?@}^,Wx_}$Lj^^^Lx}3m̄׷1^Lx}3}̄1^Lx}}׏j^?>Iu}9?ZD~~HR#I~$5C_4%{bzb1M&~L?ď]Ǿ.S/w+xS8ԦpP7MP6Cm z3@o )jS8ԦzS8ԦpqPePCePϡ_sPO.C]uTB 11Pܖq5pR#F^#FTjHFTjHFjFj8\! \n31J831J831J j82peP]-Z. {xRp1׏|||| X11ױzb=Vrc%+\z.=K.=A`rs9\,\,j uA_vW-̂@_\ื-̂0 l+5?=AAȠgd329X22edp\qZFEj, zF #S Uv:X4shp̡qc 9b01 z =I=Yg̓gȅc%yVc%y<?1ȕT z*=J%JAORSiRS)T z* T z* }끾@zdj 7`yO񨴄zB=!%!AO'Db@C !` -:z z=#mI'Db$D" s%Dp̡1ZB er^VS̳c%=VQMQd%@?FOc#|z> |}%<@O'S` OUq?^P|}hKIh'E S)?<vG`G'` O-<%@G#Q#p,@G`G#p̄rWZ R)9%$%U>$AqZpb/o=8@N1[=U T, 1E\-rK=U@OU`IU*S T, TiR8JKU10Z=U]J|ы{kTTTXIU1111oA}cK}S\Sc%||O]I FKR=@Oj@_` c1a,X2X~W~WO:H}}%t㒵,%`I/ L+-:nO_A]Ѓ.A7_ykvٖAO-K n)8X*q jUp W10Z\ z\j$ _c- 9Ԃ.8P CsHJ ~_$F<<<?VRpSpSpSpSՒcc+I7?;8%邾AR_`Ɏ`Ɏg`m$K%,ThCud`ɎWUq;U")8C-K$} @_Z߽OKma6crII z=邞t-Ke]ڒ.8TKR-cHK=邞tAOo-c ֒n$]pt1 -[ kal]tctct1'rL.I7Ti*y*4bJc._tyPO*vu8Nq4+;up> z<Knx8K< 8ԑ#D{#PGC'C:u+X-PsNC:Aϥ{C=<Ը{qP.qPm/w5j=Ը9vԒH-YpԒ>.Y{qp̾wAc{8f_1J=]CwA/}=ѫJ0yy y0}ϘϘJyyZZO ` Lp<-`> AOCЧaLp0sK=`0%`0A` YЇ,C!,! }Ȃ>d%`K=`0AO` L&OԇMAGSp 1{z=b%F`Ѡhcthc49X28.CK-)KR}8>AΠ'` àa0a0,a0 z= K= 1[0 0a0,a0 z= la|Y - cR0,aapap$w1R[Hmy7X.8Fj˻-wAϻgHu?;X11$;b~Tc~Rc~P|I@_A_Ads299Xr2 }KN~Zm`I8|-y>&%y>&A` K%p,p z=\K=\cp i%8I &-\K=\.A[C%8[ o-\K~=?%"cͷ ւ8&X z@kǵg-HH+c%zA cق8f rA`d5гY zV zV=K-kq ű`ce-㖵8,q 8` 8e-K $t3ИnhLi0И橘L͎fovL7;=tb:@ceL>[?VnC>z^8IvP'yP'١NCd7qwq;Iq3Pg@טx51>$xqK.:׺CEc"||CгءfCbǨ)YPwYpL+Y ,v8T[@[_ӯ15O@8Z/8奼~瓔Xx1111폕Xq1111z}OK p }D>"%@o>@eϲ`Iz=?x5G -cx)!8fE-1hв#M,M &&m1]\,x!8f_@y@y-c0֢8Xj5%<<|>VZ'mmlc%|>VZoo̧c%<<%>zAqZV zV }^>%@j@I`jzV=@}X\9p1`Z{9p̘C}e8CpL%1+a>Nc'T,Tz*Ǥ.O;, 1b'8x,%Y,1[|GpqLZxygڿkO +g[u,)zJ=~<㲤ĘJJ{~CG8ṗsgsVI`I`I` ` HdH$2XddD3",ƶ;2"8nmˈ|wx=zF=#KF}K ǜi1`5-˓1MZ=@ %@ AHp כd__ džzoӤEOpL=1MZ z=z2yRs)8I˥&-K. \ z.=\)\rifc%TPLH>V~Yc&"ɦ,E,,-,p _%yS1S[B=1)/ł CG[d"#Ory<,y< z=O'?p D10Z $ ]ڒ(8iKD1Z $ zlI%QpL͖D>_?l1#u7333w󱒙ccc+9=w=W=7c~c~c~c~+9 &&s#c#S㱒c~c~+9>>>w>%3AnG` Ԡ'%ГRjp\g% (ܢ88sKxʻs@Cu: zS2?0pܕ*qWZ-Hr^9@٥r~]+zLS*RMR9@}H/#a pdVVbZYh}ø8BI#%#>h9~dycѵgSc:pqiaX919191)!X91111xtpqiX#~AN'3z=y=@bx}V}Qc=VzX̯^o^/^Sc<<<<:!~A?R@Ok`ZW-ЫU+X'Xz=K矠?pl= ׽0p\Âη[zX0pq[n= b ѪU ,m Ӥ`iS&Mc6P8IkS)m*Xm 6T) )X 8[+L0Kao cu";Nz' Nz'މ@D҉'['iKplV{oj61)1(1'1&jK;+X6191O919189I7@ OTzA =^@^@ y#X =o7\c:ԃNcĴ:!T)p̙V1iZc}y@_^Ҙ1Zck)X8&X+E$q[nM75 ЛD4 ЛM&z& ֚D4 pL$1Z& ֚8&XymLA@ w;$X:zKc1:HtpA[ 1c1b1a1`X 111O1 9WRP@_w;-X zAKA zA zAc@1RP?.1&S_y,p VPlpLVPc1T>hk 8[k/oK{x+l, W%lp\q[f X z,=K%KARciRpKq?[,l[Sg^̏^̇c%z||||?Vģ~̇~g~ay ~dOЇ3 p}8=AϞ=rC` SЃ)`,L?g]+XR++3XR+8VK[->R+8FWK^-Kjj5v[V`l5XR+8cK-Kj`l|r,ly7X.8.o˻RЃ)` z0 ` z0=LALq[0lWSp\Z5/D_`/͙-3c&3(gP0MgNl`?9sfWe7gOvQ}MOvP5 MO6?&FO$~=QwŸhOD{sï8hfDKh-jDKh-CM>2M81E|☣whaP8gOl5eOl~{-5|Oc܃'1c{p?c{p1=jp18ƸO>pk=>#xđijDh}|>ql8nO7'+",cbb+?{cb''w'W'7Rb~orxKU$~*c@1xT7"X?M}S%A~~?z~О&4O÷UpV1[U)UCUЫU!XU|y=mK=m61[njo=3p#G#@GKvh=ۡplVd#촪Ӫ8O <*,UUp\Vqy[U-kU3X 1U1_U1TX 1R1_RX 17169F~JA?R#@_1W ?XjD}':Dz=AA}>y?X>>A}pLЖ1C[my?X>hoWhOǿS8pk 7`i 7ЛB4F4ac5p1[SoM!XMzS)KS^iM{5pTdhD/ $ZGj1pV@1Z  8fB+ c<:OR:cc|?|=|;>V:F;cc||=;X1615149~~F~@[-Eԏ`io7 X zaKa0@o7`i_zac~ 8fhk0@o7 ϶) zzz`z`=01[aJ8q+R"@/K%"XJ%pV"D0wA1][=zGhkUpVy# *OTpLVy1ZyRc|||>VK̋cļ|k>/=X)51111R{k[Y ;6X ; }K  zm^[@-R[@-oJ7%2Xj ^[@-c~ jKk zm)f,$X8T+nW7`)|c0,z|^>|^>@/p,V>|Hm#`)᪕pīV>Z8&X+R>1Zkj+\+R>bAzǤjA}Ѓ>A?cjp %W㮴\ V}+@Jฟ-W~\ rujs5\ z\ z=WAR-WcH z=t',[nC78@ -t#,9np%tc B7-CwC7,9ixtab1w^;Lo;Ѝaz0n1ݘ^6LW ӛFf}7Po/%j88pqPqD~|P7%:SFC G·ct|8uILJPt|PZu(p5j>||PC Ac&{ĸ>V==]%]]%.pAOLJct|8[ILJc g͗X1_d}_J~DGG/ƘJy]UME~D__J ./ Kp=F#%8K}͂q˓.I fXɩ8 -$ r*1?=1X11181716K;X111O 1 m%2~A`oqp\q[|Ul-߻pq[*ǃR!8 `TT,Tz*=K*= AOBSaBS!Tz*dz*=f/(a{ǐjaCMp 61ZBm Tוa{䬘b-bbb+9+9++(( (9뱒bb+y)y)y);4+4?*y  -K^mjy)X8.TKR-/A -,1 g0pqZ ق@OZ'-ГV$-ГI z=iK=i@OZ'->c1,0[ *w S8pL15[,s8fKwτ2%X i1M̿51%TP, *p\q ZǑm 3; , %.p,`I\'. , W%.p\@O\@O\'.+Kbq 8-\@c?}K=ȁcR I݂8&u r-ȁcRk`1O>\>Z>X>V>ToH48NtK8/}ġ'h4 ,  z{z=AK=A1MZ i48IK&-AAOР'ht$h4  zN.( |YKР'h4 :X48VGKJN%AKh %hp:ZGj %hpPϸ,:$gc~Bb~@b~>b~<b(AcX1cW"tL+k,B}!A_AC_AϝCT-ZR;8VK`I^x<{=?{cN K~3@`k5,5zzFKF^#15[j8fFcjzFKF^#@׈R#z)KSǺjM\!4`i XW)c]u՚85X:cc鴎|:8vY&]c 7:[IWRo)=1?1?***Rzb~b~b~b^zb^z7"b"8T)RG`)RG#Hz$"z$= @AصC@_فcvfњ8Gkv`ivJW%f`kvفcfN fNNkf,fz fzKف1[ f1ޚ8xkvفcf,])t%ZǤn\!`)5ԭԀcRRIJ 8&u+51o[Ǽmp$Vj cR, `$xb~b~+'7!!1'XiC1?1?1?1?6666XiC1oC111\k;_- }mA_Ҿ@_۠m+X ȂYCF:У8c+uԁc@RJQ!XJQzDo3:pLV1Zk;`)u:K]6{[6{  `mXcz8@mJo76p UKo az8qmƭcaJ8m+uKGn3k+uXԁcRR'`k-yaz0A^ALO2s1ycz1mAL` mm2ż bz0I=o@o5(jP8ԠpAxAP¡6Cm7Cm)j)j89C41VKS<41ZKSVzbOrrq̏c'Ƽ'Ƽ'<<ļ'>Vzb/[Z̯Zoc'<,<+e5zV=+}}$>Dj@5CMHC Pz=K=Ԁj@5`)HK$%,=z"8vRJ'rvacv&8FfkaKl  zaKacÁcn 1޺)8xM1[7o ø5Lp 0Ka0Ao7`eH#϶4ؚ8`k^o\ rR+*,{,kRb^b^b^+*111Rb^b^bcc+*)))Rb~bbbK=&Kփ~냥?xA_/^o'/ z?嫥?A_٠lWv' z *86KH-"^"cgy.X8fw+Wҟ1[`l ' , 18xO?c, c'pi$#P2>8bI dj}ӀtI`#b1L%L7)U&taHuuXu? PCA5j? z? P3fx3XG%T2XI%T2XK%TE#XM_p R H-pR j58jz58jpplR @c;jp8CWñJ5`,L=m\RGG*upd881y_iXi1111돕Xi1o1o131211Xi1ߐ1_1ߏ1_qK}K}m6@_`) RzRzT^*@/R*@ߝNw'"]?,"XJ8vN+:cj Ҫc7\Kon!1w 7Ko7K=Ã1[ a2<8q1[0./9ט}7cސ=93 %-c&NhY>pLV1MZyGl q':gX)O1_d1c1_c1/O1/OscSX)O1?1?1?1/OK;+X)O1/1.1-1/O󌐔]0X }^G@#HW2+ z :,u$X8x#81t[m81y[G4`i&qKqK5=zK5^ 1[5jت8c5` R7$@/?p VGc`:V^:Q?!ޯ]1*ffffXi1?s1?r1?q1?pfXi1o1o1?1?1ߓfffffXi1o1ɦ%@_G#(Xr:9zN=KN}A`Ӄ%c,QcEqp 1Z( Ӣxm6i;Xvd`̠gf33,Cefp 1Zfǐ*S>CN,9CijAӃ~V` 5-ăcԴ,!xp%ăcHO?cbbcc~"+?111c~c~c~c~+???G;';cccc39?>X  n}K}[A߭|w+z,T8n`icJv9ApV@/`)R^@/ @p V1ZǐjCp VcHV  X @`)&c@ӤpLVIEHIK Ltļ`o0]7L '2q4bzc^0=DL"HaP졆Y졆C})IPȡ.C]"D@ODu9%z=%rKP&]-%R,apfǍ/apfǭ/yPU*yzyPCͫ1jJ^=1jJ<NS%uk W5WAtJ=Ӥ1MJ7ICI5^xm 5-?yD"{Do/GJD)٘o/L*CϺg]гnd]г.Y7X,; 8 z};@NgANo'зS,pLg%΂c8 QP~}8.u  .W׃-cZ y6FKɠdSr`  aЃ0A ,A !Ղ08T-΂c`8 l,˺RpJq[( z=w;IdkC'V+5oy(Ђ08FM Q/A8;0+0cbbb~b~+ALcg'ZQJh=ZAZA`ɥ|siRsi?>pq[IoIg_8-#I@$o7Ƀ-#Aψฺ-#x,t,zF=#%#Aψ-#K z =Aً%~ْ8gq[=*<́@s9\98}Kz'=Гs`_/ȘǘǘoJ njfŋ{$oJҋ͉>z|=>%>A?A`r#8.H"->㒴k# z=>>#ycGp1AO'Db$D" 3%`IAO'D" 1;cq?[kQE9УQ(z (z=ʁ%ʁHHOxļ/ﱘoJ̋ yDOJ͉ʼn`(1z=%%Ɂ>AOrh1]B%t]Bgk̏kOkW%t|>/|a|_>]i̷e̗ewe/qNwi5_(-4=͡/||UГcP#ܒcGI'GГ#8.BKq8-K}_@/`Iq8S\8S8gKqฟ-Klq uvW[Zkq ס-p\qZ z=n@[_D7$Jyy|$ɘȘȘ'Jz$/'Jyyފ=}%*U_g|\, zAo)n*XB BSfC M&CS"p%@_/A XB , zh=4!k,13pLCqZ k1Ő`!c1vslO}ԡ>GJOV/bbb~b~+)(''b+))bbbGZi`I[-V-i gsAp-ʵ(KТX&NbG1УXǽ8(k4XBk5 l!5,!,!z=ı֎)9-Xr8LiX4-〵r8XiqZN=c鴜r9 zN eLJRNz߮_߭b+//bbb?*Տ͏ŏJރ~A zภ5ŇpAA"Kn=7%7A͠fss?ϯ tK4.I%QЃA!X(AQђh$QpL~5c^wC=A!Xr39Xr38nvY^:uh%PxqpZ&78.RKH-q" 7o\qZ=qc ^#',qj11_81`1_888!qcsGGJTy&y$y"xDOJT̈ȈĈ-)QnQ,Qם/GУ@4 X zKw4#Ou ?c~?eZ,zXk3Ճ`RjƐǷ17q˰lWp\lSp&J_ D 8fB+q[_l}ɣpdWq[_! 8nv+pW10J_[x_y_`W0`ޯLo ӻŴļ`ǘL{G{Pi&4`:b?ua:0E"L'Q;s1tOށu ^su PjΡkΡ֜Cq(P;СvC}Pӡ'ӡFCn5ޞӡFCncY8kñʋAr}pďG}1m[cƼļļV I I I I I c|2|0|.|,[

    !cT^rH|/O9ԧ SI?pLV1[njo\٭t`鐠wH;$8CA}c gji}c r|iJcj 9Ԫ)8Cc9:!oO}8b}P[AﭠV{kVp̾[1;^Yx+7%$$xcb+ccc+m1m1m1m1mc&b%b%rRJR~)AnW7PPR ,z^P@O(R@O pV1[l,X  zǀm,X z=dݕz=|@>Aᘶc޶#ׁc^1z]:{`uXUHm#>K_Z)}{1^>5ccԴQ:8FMX5cKcޱ@Xw`)C #|`EpV7WZn^7J.ku=,X8&u"ԭcR.B|.zE:ZhO#na*8q8e15KIi4a0M_1 i:o#|0}PC=8C]`u;z1:z18}qs8nPi0s8nQi0s{s{P"{ȡ.C]&C}f>5:;'yj1j1:btPPw1K1:1K1:#ЋѡC-FZ^^)pR^)PwiRj1:bDbt8])Fcѕbt8折+Յӱ:J:TCTRj:JuP+plR,Ht@_p8]yO ߣX:S X:x2]xXj1O11Ϙ;?`~ZȐKAA zr=9ƁnA_۠~k5.Xj\_ ,} 7-p܅ַ@_ҷ@_/ Rq=[}^RzCQ&K^@/c`)cE"8Fj+cc2X1e 2z 28C+c`)cDZo޷@[Aoc鴾8ފ{o#Ip%Ԃc鴦zSKS@oj7`ijXcF+[55plc w/<[C؂KSvx_ijXic1Ϡ11Oc'''+@@ cE45w18Xe 2,e,X{^ 8N{[`[>W_FHTO}Ч>*X* U*p̄V@_&/З $X*J*8f_T}RcJ, JzR^RcJ1**X*cV@TW*+ULTXRcuJXrYTW*+8^T+R^@TR@TW*+*X* ˵U*p,Y[`T؂Rc J-*5elV//܂f~ת|#=QԸJ{Tטט童1 `cG# $ooq XV z<=@oyRZ^t5p@jw`jTwjDj $X] u5p @Ro)з[*X[ -غ8cj^ǂ^@cKǼmu 1X1p @jw5л]-it5p,@jw5pfZW@jR:ZK^@cױ`c1pV?[ :E8]cXtKǢku 1p,VhNWc| VGk!X-c޶yB?8m O@(c~+>>I1D[33c%jf=5yYQ|?Ȑ`G# ~A?N@ vz=K}K}Kc1@jw py /'З r ^AҚ8}k )ڷkߚ8}+R@/e2,ep V@/R?.e2zgYe2,e~(7&uHBc1cc1:8x1JjVԎ)p,Z) <"]4cJs8N4cJs8N)&*&_>RJ|4gGJ3y31~ XiB1O717161oB&gu`2JK%@Kǥ`3COH?P8Pu\,+o+~7/96pLVۂA1ZmǬ+z8]LCڠo`*cQڪ"8i*c0, 6PzK ,*X* zB% uAPW(+*X*fPBKh  U(p,VZ"ʏa*8qPƭBc a*TT(pU_>ޞǾyyxJOyzo/JO#W].,,zzzYH@voW8c洺8N;<<u }K4lupLVw1[Tl%XJ [[KKb,$Xz 8P%z@^ @/R 1R[Hm"X 8Fj+@c:8&X;HH @1 ϯGl"L@w<#cgpL,**1?A1?@1??1?>1?=c@N̷q̗qw1?1?1?1_lJ|||<ԏb;1A/}K}K郾a%A~8'cRyr8f'cZyr8'cbyr8f'-M-?2CˈCm6>6pRoCֈ8^8^Z~hY8&Q}[C -(?<ԠЂq4[P^Y ʘg%(c~dc~bc~`c~^c>xtpl~/V>111m1lJP<(c1ʘe%KPA46AMk3XjϜ8, zmKP%A zPcNf f8jԚ#5#8RkFp֌1Z3ތ7F4#Yٚ_P`C{A-ZZkLZz.KKz.\rYɥ?|z=+)ŢV̇VgVGֳR1X1WOKJ|8B>eb>db>c̈($ xV2#c S C 38g%Ob~b~۞< <ƗR<=A`C<=A`C[#?:C!8vÇ)~jӇc6}8bUsǰm, zN#,8FVop͖g0 zGן#*GK]PG!uhu סu58CkpDM`kp\VขydI蘏g%c~c~c1Og%c~Eb~Cb~Ab~?b~=[011Jz. !~H%AkAkA`kg|)AkAk=Ahp [@cnǔmu 9[v8&mrp˃˃%1R[zc_TS?ԏ;9ԗ&`d,> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 296 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-040.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 306 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 307 0 R/F3 308 0 R>> /ExtGState << >>/ColorSpace << /sRGB 309 0 R >>>> /Length 7012 /Filter /FlateDecode >> stream x\MmQ_qɉ4 E)%Qp(D$" SUk- En.ɏ_=㏏?~?/?~gJq>~վ_=فr=s~|?||z?c׻<[=?_~w?~w{|+uUǟ_Xo~:>~Gz#?~e#E1symE1li=L>>F*>o>g͏23_d˦ZmQ{x ~hp<,ۥl{!z|ᖟLzl_^yzzpyil:ܬc s̀FO5_=  ߗ 4cV~1p1գ?6Uf/:T-|p0k+?au#ؿj:øܶk5~9mi_s\'L~*WCOg5z\3/GңԐ_v^FX3I|̷y]Plx#l8;:ZƳG61Yy^zx<}A<6XfYGď3;y?Eu]E1ߩydW7kF߿NFivWog Ƿ|S^rz /IJOvٴ&ykl 뒺0=`|S8}?njO8Ľ`B7msےGb͘4'M! }W2x,6ftqjܖX#G(U?+4-Gpꍳ-3v5OZv._l_; |͹/F燯 &w3hv̙aE}אsPcl1]=ZM6uØ/䳫AI(泡_L5m\A1v|㟼pS']=ֹdW7^GK3Eg#Æ}.QS4A^ӭ5[;5A{l@sk1y5%;4nyݱM (s9vL.SR6yk~EܓnŖ[|auTߦn 743iJ0_veH 5[B Pc97EpZjO~%Mz-瞧d1F7jOAkOYbl|͖D\c1IqO1O;mm~6p&mw>.xHco_'ݒ.Lf vӹ ZA>M"cRD?EI}n.э4[p[^܏}-;-}S%ck$?5sۘY$'\VwR ;fZLq RKNI­5v@st[rM7–:ۑ7]a0/D?&Zbl|apkh]}b#.賥p|a\`M&J G*Fcm9I)qOc} %B8]ŵWtݹp ]uSa[;TЧ~EܓnG#Ψ1+.GMS+>)r[&u %Rܓ_Ƀ5v@f?oRJ%vܛbn/q.?}s) IqO Ifw&yL-bI;yFFP7۳=]jp65v[BstkHO{k1}I.I[{K܎}} V?"IsZpo:] VwSOʝ v`t._''ݔ9CK$^gKڼbi%.y E_b+Ȳ ]=6s_t;b^nk-i6O㚫|c uDE WД Zzd)5FXHfb1`.7M7&)GE06f#\3i _cnRѭŎ 8kZ F]1v%˒FKdpc?IKr{ ĕ4 ׸xXqp Y- r)#@']=fʮ$l)qav^+ %f-vJ;-k?)stnٗ;emNVKH"$Q~< PYZV-' ==6 |O{-H$w_gKԹ>O1b~m\AiE$l)A x#}n.t~\rJSd?s쳟M\BsZzd!Ao\$']=VҲ8rTow ҐW\i\B- ̥k̭~Eܓn03BF0amn{_:Vbl|͖ȏ 7E~\c( ot+TSwuL?Hty3@L?9=Ap WKspz']=V Q;T bÔ!Sv_ǥf bC2nG\ɹO{< cncp mS !}V?"I72+Wf b~υLD< }a̋qO\A;Ö< q0< f?"{؜;b_GCuvl=YkwM;r֩74Ĩ a^wui̩^PCV.(|-/Ԃ=l%879K]-%r;5v@JEW-Օ#]ut3vrmd@R]p @SKp͸wyKqn.tKD"wjah#,3,to$nSMAt0}3,]}[NW!45)Uкuha/qMWKǝ4pkx/s_tn`>ĝ|S.U~g6A *uJZ}j;kuf?&eKYGhLJˤx#r!La2)sk RtT(o: Vȝbwi&.}.j hn.t+|Ӧ%*<{A x<Iኛ88yu} !s,ܢ)΍~7 殶Eˈk;=~h]\wv%% [{ k']=Z 4KiK^҃A!F9P_~w7\ԖyᶐݖhnRtVJBVRH ڶTf:PcsVj*_薭~]}D%N:@9Q *ˑVKy#O{ҭkCjVKIy[FhqXyj4ݫq+NJ0,{Xin.tVvE-HwŜ1R/fNqک0}B\V8z/+8Эs0xœ):O'xtDAt";.KhԒ#E'|c']}[uLN^-^RsG+&GW)~/%@sM]v<} H[K'JUθmqI:[oJa1Jĭ_mF-FVK4p8vȚ otVޱSM}-7RF+JPB\Bs1EuGl SƴEp~/9Ԃ;biQ,Dv e>8IqO%U:Ԃڢ:'MAuIv]ZEGK%QicොLgQ=QQޔ+z3*:{hn.tKq7v >[(ȄJqv >ԏ;;:-|R9|M']ذO4hY~NAp -ZMN};o,}']}1OvqsgxlG{?'+hZ'ic'cS;x[WtՏpa3\/Ø{?f妧V'_jrX t*RߪñD C&qTmX6a9ukZ?+x/DDgO[_xf2&8.G"z#ܬ(2Wc1OQ:4sp|Ao[Rpp,+INnmF¤Poy.Os<Lȓ^QkV)?-]3(HR5-mf%г%O@|d^bt[}ij0Xbr~3{ak| *N=r */~;]OOMUL `>zIpg_5Bg:٦`5 M8ig): *G]|jzu v׆O-cދO}: xgn3ڕZi\Mokoko^,Us0ƲCd3/yQ<5,wDi<:HSl o !3p[YC;ktEUE+O8(kL*9FCˏyxֻ/KCܨr|/K+"WtR)x6ŋ޵k_c׼jd~ٵW+oU 57yPV ye{ fqStd%:˭w1M q N-8(]8ûrǹPK7)Ja =䊉ȓ <,Mҙ8^ġ#T?B7,\t گګCJkMR_~aYy@nW*tu~6y{{mjJp1K/0; Zz. ,n`Wfï }뫟k?{D<5^ߵDYOz6ioFM>rg`wDJp7_Kj; 62^ˆKo:8"X0Sfqt05;s݂u>Qכi r&Mtڟ8lPbb;J(h/EJn#VB"o jMՂ[Keɨo]oE7w޻_큊 u{baȷ'[Ƒй{ʈ0R߄D"f~aЌ˙w#F4?IxIx} 9w&aGs?[ ,^I;w\s~Sa|啴%~V2?Y endstream endobj 311 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 316 0 obj << /Length 626 /Filter /FlateDecode >> stream xڥTM0W8q8 `VBH8IZ mݴ=ii+v3=GuG'PEerOi0x~ 6ܭIu$#(*t2xMJ'&,Znyķo+ؗ'/mie*yna!MF> /ExtGState << >>/ColorSpace << /sRGB 320 0 R >>>> /Length 4484 /Filter /FlateDecode >> stream xZˮ%q߯psTVm  A zL$8c4 YW({YՕȬW~~ӯO?WJz/o yV+p]_]xNc?|Up}saӒjNPowS~_zt[?enZ1kL?lϏ!}wߚSz]NEoepu\Z-W+PkIxe2_;_uJ$k֫z^H͍ޒ+Mxe_iRR(1$ Kb$eaV40D˯RDۯTtU$ ZwڸgI`v`c0ϱԎr1GZHt,-'6M=^Ms`Dʴ5%~%!_0́Mcu+(xҠX#XPH-IR{u8[Q٣Dmj:(pI7{lXڧNZǫ[!U^.lS/z | 6v V6C/z/LWYt &BS *ǒނ౧$)I`ױ28Ro  Mغ㇭^޶^R u[X:6A]zڸ?)4vㇿ.JsGGqehjhQ a cgu 8x > S8tY<1lfϡ<0oS*llC!ac6L>Dў6=٘Վ7SII6-)_DAu̢]7lKC(Ns+}G!\9,رjQ4t,hm1,86I47o5ϽI8T~xJ,O9rsI9,g?>HûKQTld: >%]GA|G-l acaAXA6 'jݠ=4&/ vY#GQ|GOh`d%6r$:iLN<2mNV [Y_•&ΞLÑ`1>i tѳ N Ĕ1c+D&_KY~o8]6^h0#qFrɥ!MV%b GsAA|_Tty;1;wc_2JD"CNa+fr&h" Mb:p)/âM6oJOlS|ֱMa/8qA[~OrHhОOq̰Las>&0ECUlS'賉AXc\\13Y?4`n'|MsAN%0V򃥎jT+PѭR.{X9͞{M>9͞;, 1UDs@cMb1*=iLOt1i٨j[dñ$`!\iC ùF PFaS J^gG7PizEm(PizQ#-MB4QԷ^gd49$VW vl< KzQ4#oRmltxhw̵̲?6:t6 TL5~`__GG^U=>-jtMbXM,n^v$h|;veaoI]}w;xw=So(|X{Xb`밪?]*F ]__-tD^,`:l?ɯlì<~d|z^bd$jKo剳!Ӳd["yMB,\y`xs^x29E0w |hVȘ<DWG.K 8D'YKVt2 &!PeH \S׆\Ƹ¥U:<(CY}z }lŲ&h"nu2АM5kCcGqTǭS~THò$DEuh}R'MGE(MI"a.XEUbj86 52|Ƃb9ηo1[?e$KcuΪK`m| | F}녥{}#?˨ d5DslёHG`,gx,L*f ?47:6  [`[}ßut~~o:4lo)u% XC݈mna#д 0 0svıNڞqC?☵ BJNjDzc3/ {W+(N0l"ym Ĩ"+[qn-Qs63Sws(<-%l[x3a,8˕&_+?re.32a|r+ZtfTy(0IXYOy6~O(Sglz(`# .'9q"3 !B]OW4jxx% >Ǡ=Ia!o{4`[\a_0\a"'\aV#*%I,*K[#x ѫ:Na\@azyd[4tjz<;-‹Ȕ0 bw/1x.~$7~U99ͻuy8|4}+YU_ -=$`y0"J`x-[u;Ƭkx?8N={hݽDFQtϦQtdОMw;~ u`u>t.,|?M^|AeMW ȝW${X-~+V3Ϊ80ǰڔz}m'umo<Ɛ0o聇aED7To]g| `Yj9V/a3˺\Do jeIk0Vý7֘-{3ݰ~y6L=7]7[8z*m5E`auEQGZY9 Ǔ; `S^{MnQT/{v_ڜ}5'[#6RfY 8h#y 6g M#erՁ#|Ewj?)q)ű/Nt… xicusˑIIx,?vrKItoT+Yx{BsTm҅Q0'!#qڿ!Ձ% { A/yVE#O^sY!aY%[̖{egMMdz'a6^:z:?h<&{K\"kM;>>aiefWHhiY;x'aP lmud#1|/d0u)a\d+^I{atlvT(% DR2$]x_F?N?/a}*"u9UsCx\dHwO{eG97 L!,ˆNtIt?0 qmoEgƼgy$ȱ*R( ݮw-a#Nqu7[ӎX-a#f-8"mHSL/-? 2DIӚZ>֐ms1܆L}>Oo+gOynt0 /4A=î~]Y6|9OMǎٕelC:L@~C"ś’.rVL_Яuįby~Vh:(3Y71֑mTG"h{nCws_}nz[}݅w}+ß7_Εw]鬉?~wx\Y\O?&7?/1o endstream endobj 322 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 312 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-042.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 323 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 324 0 R>> /ExtGState << >>/ColorSpace << /sRGB 325 0 R >>>> /Length 3761 /Filter /FlateDecode >> stream x}[ˮ%I ߯8K*_U[ ! b h`>NG5B,\ٮpFVG^__>qx?4{_i^w)^O_^?{~ǯ?nW{3o~ʑ1]~j]?ǯW0|寯8>ޭ~|zwQןtx}zyk{}/[a ڙzuhCG(˝pjH^]G&`\coxIu8})wL;=L5<(|GzApx {%p]W(ڤlK\I~޾}T{Wo>|Sao W< 1k}Wx۔MK4ݷ xCw]@ֶqΠOp5'HmGPZcKo׶px~o E~u})kAK\IBR1<9ǾRGW=\IFvLЇ>^3c};xoY 1^Q*{\™^!)+CkܒETX]4^"8}R}dq+8]ͱT z q+2vC_i8Gh8 A_ wG6eo!]Æ3eM ]*!8u.ۤl\IlkPOޢ]~ӫ-6bM8S/6eWҟ}Ee+l> `Rל1ސq=nY-pbg&^!)+y\>Ey>zjy?4Q ,-iBCU#;AiBC q+Orذ`5' v+˦SœO(J(x`)o8 ߇yM;yy/bpJfYOz 5AMz7잍45}7wS^a/`l%4Χ[5ҭy[m&} )X/6g˓x3Sۚl@Zͼ7Q>sE8Ƕ,$ƻhW`eѶdJl16=I~GPcl\azڠj>1soT kEν}Ch[v2%6~QBJ{phR*,4> Xd۴ɉ}|vRJ{ņګ7KiGXp x싽싽ºbFA}\4TÄ:$m(ứa/`Y[y&9++~<(]+eRCY!V[:6VP쇦 l[b?ڦ}.:UÄ{6B6}cJٛ\4UÄf@,b]l x;?dZ_*nlxw NORjZC×$}hmN^fޏW>_upcD)-˫RriUmpX~U[!RZ~Qw [ν|w-;ua%w {]m oϻ/q>Š\50/j^CHї8:}i'/b3o M)sѸS:s\)jy,4y*|Gi'/b3ožƵ<&MǙj/mÓM`)cEĒ+}mɔ[kh|̯sZN &,Cxa/`ѥ:94^vGcT'gqN׺:8|GmN^>x?Q~r׬Gq͊}G)Ɏٱ'5rh<[>"v"6~#FipVU#bnXJCb F-;x y?jW$S NAʇ^\XI]urh|%o x୾t_C{)k ,mH3{*[A^6Vҡ=XizK` Ѷ%lX﷾o_IkTn7&a,ipJ#PJ}ŋ2DZ*oXoC3UQtv? ,CcLyhvN )ͼ{;wnGK(( ٱ7!$.VG؂FE92ڦ}f_,l"JU^jZ//,T$Gb R}GG۴ߎwq5/%nюK}Rx z<hv"6~ôv4B;=#+a,Dz vb-nSmtj?$_q]؎CS݇'rn8rN^mx?b륌YzG%s\/QJk1ٱVR\ s*Ji-v}^xc^2ei~zIv/ iKh| x/jv1$Khݎi}6wRHgRD۴n 긊w(:uElKiE\{EmN^fc{_瑦b0_>_Ē+}mǪ?:7)IF}Ɏ1a){J*߻/j[v"6~ܹJ\aý'ExὩbKi_c^Xă|xQ۲? ב endstream endobj 327 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 181 0 obj << /Type /ObjStm /N 100 /First 899 /Length 1402 /Filter /FlateDecode >> stream xZo6~_a!y=fеh l@UfRmrNl, [#yG}D!%tBS5 ҸJP.0V8kqu%\hʔrN$6h! S mB` ZE!0$;RAK11AChA wXŞM` X-,!*D_5Z+spj޽ M;NAMA@ɰAp,䁣9`G+ u%_^xÐ<#H›%EF _\*(r#? E@†Bˉ @ &G P X Z ׉"D䁐BNgH" ~DE*8Wp#19dM 1Bp,x/)OVs!&a89dq"%Ollo@1 z "<x t!É!apt@B>沫_k'`I!_-{Wwc?O˛u5ͼCi;WyʥTɭU'œ' B>oo-+u!-'\F|Z2<* SS^poIOh 3n2ְꪽn~lfTy&.0n3@@5oNmUf7e/ [)!hx,0t~Vfڴ2bz4zG_Lt.,+പVosϑS8:al]̪Bɳv>2-T/1iI\((\rf ȯI_'q'^[y(}kf6Z5aѺ> stream xڝUn0 }W}Y$˗K;lm=H.eiZC [H> /ExtGState << >>/ColorSpace << /sRGB 338 0 R >>>> /Length 49992 /Filter /FlateDecode >> stream x.;&4du:}i%JbͱWIPnvBBb׷#t8G??o?_ׯ~ǿ/_JCW)?q_~ծy3oyljwTk{cmDkA]WK'W|^O3Mn׼{t{Dύ=n+} KT%َз)\jOxoB>15/<س>LޟXZ߻2oz B߾1Mk}56=/~+nW[+%;*K;YAR< 7'ù&d VEϼ}^fPM|xqB#izG7'%$o@r7'0wNMc]39ow' 'ݞ#Xt܆L7c}aWWJIKиq Fn׼{sǻ>{+fAǽv5{q'w&tٮy3Mu}>`\{Mb.Hkpf;nTtj\mfEϼ]Et^$7i!Z*Wm'7p%oB.[)q?6M~Y'/)C1җqoZO%`^o@V%sޟ%K-5Db?KH\B_bG1}:{|2*q~Op *}{2;G Ƴq OtEYAԷ Js~wNECP}WkUJeJ_r Bߞ4pƽծy XF?ξ<<>﷮6o\A_lklk=JXj/~҃;еcZ6 mJᛃ%}Mn^5s]* @-N ސeGp¦“EEܐHv߄.Rj]3%g]. m<)XFY뽚 jԔiV;׶q ])IHWvjm7!KvKy{xPk>P%ľ]4=]q@+ZN>yڃ]Sw߄3vKyW+t0zo'V:{ GǛV}Q$eEi~n+q;t\omvf*s~A~ #0ؗ1% !(+9(4? w@֦ilk^=+gIO*ΘW+3B]vޅT<(;oB]v6m}xIKn]z Wao7K=z~}3o@}>x7R[&2Fv{bLjjV2n!K<6=/~wi/mCW#oO/{ ]P{x }d{.n|ř} ¯9vS~z}>i`b;;C\ae Y̋p oZOHKq?~;I4YOBǵ@D_/E1!r׺ڸ7~' i15Sֻ zMhɂdTE/=q߹}a k(X>>1nr=v%s~;u蘟tx= Co>=O\A-j?qF$Wծy /+%|kYcV8(|ް+܄7]mqyϓq#v߄x86x^tqAi|bmWx2 ۡO\A5p…R<̱ծy Kf-ɂ ݯlwcxvMhZ~'=.mOwKc]w>/ W^/dr_B@مR 4q4B+\C蛿r߀LW06=/~}WOTaz%;]-A݀]_޸7' ^޹o@~svK.nOnF +l];}&a\A%uz~C-q˂I}o^w;es޾+'le/{DdBQ]v8BEWkh$eӸq?ܠ%I1ga&ľ95/ֻ`8n}>`8=񧽷iSBr<7;WeLAjETvϋy{[UG]Oj Y^q憈23vHW+}{wz ܸv߄kvKwyO`gkA.8EaJ qxl2O*(qa˾Vq?yn?q\Ew—P~o!X!4G; +96=/~ b|Wwѓ+:q-׮^(_UYG#qaeߗslk^=+Y|^d@@-u_ `) WPO'ƸwТNծy ޥ%ܞ)0nq&̲/%t!xAB߾o:vgqd߷695/~2h%'a:(1ci7FL"]PKb}&NnvKy] /1?qV83]afaJ\AeS=>i07!F19/ֻxO 3FGpu΅ΐƥގ횗py]O`mr$rpބ!Ig;=kw񓊵5.q?6M~i['T^OJ ۛ}V+h++R德c"g~ qcaϹy"Xy&A?~,Aܸtcn,2>-Fllr i|Bg\R=|c]"gǮҢN?uѩtұw {E{yи6"NM<5/we'+}cوZ3!v{n}>Iɸ4);.vϋy]H'F~O:f9ᅂz}pvWPu8T>ƽ8;}1c]9o7߶CE>Sea>a]컝niN{gPׇX]9oT=>@C{dL7o繽)Oz:])fEϼ?mAn_6;wta\.e'[횗py]ݣYo 5֧[wPlփW}1g+t+fcc~{`sX^i+-ն^&֎*< uzw/lJ?Řnlw/N_9/ɧ8#[)`<ɤ$?A(t)3zLr6;pD!r!M0{I=%#ЬP{!ν+=Z9s8ִ}Y)w4Sr x?~xPTfT+g#c~H6MrXz8S:"zB>X? ν'npoBc29o 9E>AL^+?` 7_}~k\Ay( qywq[횗py"`1-$w _H22ʬBzހ+(dXw1c]9oW' 18|L^&/*Ʀϛ /^clI p■dwoRvϋyX#3wC>A^f %Jngp y>AEn;s7l yD6|AMaJtx7ǻoB}횗py]c~2BĞO@N=g{$Vظ7)`tw_vK}^~w0a a3}Wq `>_70N[q?ֻLf@~qZCUI?ݦ=g7v*q+( G sN[횗pyO=KyI AҘک("I2MBdvϋy]VF7= ɐ_eK1i?S4>k=dn܆`2ovEϼ.{S' ׸>k^=wTFP>uפCrn0^`S{)5k=$qve߀.[)J3oKivkN>y{0 Q}6 q7!ͱ޼=wyyp0>O4f!\+=v\+x=|]45/@$|*FoLx72yp UğĽO}Yϱծy ߅!^;Oh_c81޵'[KhpMc8=oGϾ|8'-$q)!㺑ނgs;C+}2 <" TצgvK.QRAc=? 5fnkt䵒2]ՠ i*[s~s;I>in$L"H>qe[>5B\^y3o4R,'TAז_45/ !4 ƿ{5ngen缌{&c{lV=wRx:۹+C>AE컸FvK.O:> ٠A=UxAYBn *vK.U|2 3lU aE{z WP '.Bx ʱծy e¥Nd P~5S~ˤuyd ZDIC>/gv;6W Bd[&.cA?w h9'<:8-^!vdZ" Z'{ 횗pyǻ8wb ̔H+I0^)dG+5{nh nГ=B.t*FA"HgT1Kqa{uQ)^w= 8h<ψcrJp1h72< E JDxG C÷^> Xu;rYȈ<3nw|hHnM'5H`@b#>o#D`tvF/,iO*;b޽h0E-.ӍdjZRcȄyA7O,+w/nx| $uE1`T o|p4 x^z};]EƙηNak:caL8F<1oN^.{Ǹ0Wy- K8 ܑ0brN4җ_w\so8Qr-Y}Z6AØ DR kæZĒlE5{$q"gȜ>Bd UM2o};s IsBTofk8aOd Ձ8\ߣ7M.! jqwYپH9+Ã9E=Nxcfc sY:$0Kl(0_nA }SHZ7& sn#-_!=A#ݚoa*2Lzg w 舷J8d#$9TK,\dk&9a AolU8ϳNJ%qfG0׀FV "IXP0qTskV|=p*0.֠1;kﺱpIA;kpuq0Ǚov ]\bG TaY܄O:ݜEGcMZt4ოDbSOec'MQ&%onE1PgۙZNVέ" jDGW9Qu{nӜcU1eKȹF%'oAOoS,ZA%VVARI{e1 9ndz:: r읎,%{4Y읨l: #}m-F(R%k7~ǿkСzT߼Bcnsa6|jɵs'Z>mu;ZѺ o)zEI qmo>ۺ>oۖ% [.}1o)m7}3l9n]xBu ɹDC>s OI)Cf:Ɓ̴ǡGt4AGW=5|p~xzʹ^>׀Yl^^YTi -5φ9"hG+ ΊIylaqVyiqH})ZcP2T©ewIfkݸ@7yĺ*q}6 lOC>xZ5ּKZ.u\4PuY˅=&a7+:ajp_wL7cAtawV\3|hQżlb_)?[Lb"Nw*p}g%luM7m(f6k\oZ%7Ԙ@:ÆCVRQ~R琰u()T6#3(Maj/li-;Og- 14)"b0r/q~+M۵XM*Z*Zԇĵևđ֡a%qU' 4G4>>%i|nղsTď t2f50ly3(c5^^q{ZkQ5Twk o8ɓWF&Oq=KxWH}S/l*P^"ʦ}o> FBUmd}u[zXN~ DžC VRObq?4o7}~Tw*j4,h:ʍ{Pnrw4Ve=w,p^CPd}M>~k}f-*咄ϻ1@wc^nInF^>;Os>8t,Ӝ/_tg9eͫم4~㚢ڰנc}Cka\^LAX*Ϲ-sn)6OqbVK3zfc7}n}SYMgNgN9}Y9L}s07U>l9%qm[j\?iI il{IeLK6N1zF9t r=*->~ROH^e>d}(C}D|`XFųl+G7p0  >J>q !rq΂ F [ {C.{- S(mS{6ݣ'ΐ83Wsʈ;sl8 Se|quW^!l8QƍB -k}uB na3H qƢk$6ߔ }mBng }u,FbN"So y-C:ќxE7^d^{e̎m8p"~9x</J?y(=w8_KK9BI]ړ[Lk1[WeV췧es7g{*8J?ptD~x^lGoM {Ua׌] I]3OC{}ds. }>&N'Ohۍ M|p7̹uV DPo&6 )]C4tPDsIGgnT6b243;bFqb%% {?.'8Q0q88:N}~p&޹t%َ6L_N8,[zAM7}r ]]&u8iH򯃆Ԣ{N4İi-n>,%}X"0VX\Nt1נC^t6yH[)( _l[mRLnA~-hJ2\ubSC#B {kty8.B4{C5>o 갩3>(3΄@& U`Dz%f=}0&ss:N;xLR߇i>bpϷ+@w׆CvK %XLa!C6#Ճ?0Aq_p:C&η?$i{% }.,.Y> Kyp>LX߄r>hUS$Z՛Μha\ܘu  xmZ6p:Jچ]̾Aw)%@6=wOɲd¤!_D{"*&6M5[h5 [჏&]xmށݹ2$9hwS{Gv=6d҃mC&=ڐ߻3虺1I!\$qLq6|; %NTn~'aq1Oe|!W*`¯oڛlj =4}9}(}^~hUg!5D}r}zWx&컱~t7zQ Y](J{>`1h73pœ[e|Uzh6LA.lßJ8ǽlyE%u/,2{[{7N8؎'%?p>^nڟu/=AOi|‡q(;ogzJC -[w[>?u 7uNḓGҡ{4B^uG>H;w}]ʽw K>HwKǜD>6w& %|**jJgI=Mj΀ !I5BdyCwE˓_]0q_=B`?#M}ߪ÷*aZ„}`E\˭|נA0pB:UQ5f5Q;84WV\GY}iAC/#A~IoԳ5 }g_iRq!RW$w%M#OQD̶Jљ1<6'С&r) ?;eUJ)9ۘ /͈)K3bPJCk|#V3 {&ohJ99NO Ü[oaY>1qp>r\8.^fapZl)1GjI~+uoKܗ7$5UzZ9]gu#::Ymi}ǣsz shqno8k̕}ii}ࡺI37y@s;s>ȹi|֘>iȠ~PK3*s3!\>.T}Šs> '2݃{Q*9ztz60 Aؓ7Yy&qxj_5k}]{қC#X=2.i?{-o;%U9@ ׺jާO63aB{g:77M'lŹUZ,r>8b^?^qźfa2D$h8(ѷ0qX\m5bڵz"O=ژXg Fy>oSaٱ*hbxR418*㰐݈ pk:LtrxQw>]7\BM_7C3]d񻑌)a2wi&>{z;˳և]yxl:^dJsdHSdӒ"NftZ5)Y$v{tE 81n;"7źjVbQIYD~6=H(m\ ,4V~8m19iLJw= s~L.Y.KJ8K=ԗ hP0aF½5 {i'ƳKX'c90l2Ƅv%yCg!ƙ^'thO\&^"a΍^ЈaGFSbCV7vDT/RvcIҚb$I]:s$>0O)-͋CP[W~UI=pX#* pB$,ǚI"zApbOC__A샇Op xq2>GCV[솕VL; ;gXu'Cgmgu_s}깝¶e`V!O}2*R![ ~ oeXf"}+2[\D3գ)b 8Mi6N;2;[f~di񞋋膾a9<37 \~,B|_2V MhMqovl٣_R]}@{=b<4s#C#F0_al+sLtL ኯ+#'ꕾd(wP+A"U)52^t7O xM_wf¨'U`{=U{|xٳ!U{<>xaM_=J]V(I1t"&K0a礥wۦZ$q(8YdO;2!.fe:䙄> q-j q䋚V27KDF=CoZً" Gbcn8<"-7ON6 LYyAca q:J1qR~Z?rsS76 PfGRȎT k {I= HxKr Ҿss4q1gg4 K!{оo9XXZFµ>Tt#qq#ݟg֋ֿza!cqN=5Zp4mso1IOOFߧcmw}..ܩ96:G>WtNغ˘KuF]MG xEx7EAEt->Ϯ͇'X! [2*\D$sdW{mVo:ޒw2jROFIJDM>^-{n>*͹=  #Q}# ]ܶ;-&xd8tI.5:,>DCUYDfGy_j878xSg wQ|bnEĞ{)Ψ֞%ɎΘ"cG> /M(I5Q]6ڎf |s fؘ 抌j Fav'a*X{Dgʿpjƹi _(8Nkq nqXx;3r?" ofYN"S8Ci338"TGjge)QUqn?3,zE]5t_8412ݐCD/F&41{)^GVz HnG1IRd{(F$%ZEGc#Ut4a3m*;3Ό}h+#w`愹3x̊ikʞtonc7|ۘM:hm(M;\-~4sJh]>_wtN%;q^1|۰}o[佝i앚||hZ;~Nj:մQgTR{L|/7s[j[.X}.QHe,^&;`l3;a8ʕWArxC>2aј>WBا{!hSs]{m"mǿ~3%fE߉誩-A#GݰvLqTy {C#f&h|MtwF C QMg }ݐk7|X[>$YC>(p˭sɭsǭ# \$)&}g/RulH.TK S.MUTjeO+j異iGD38o@D5ßuuoѵwEz؇T=C#s޷x}Wuw򗍻9&?+^Zхp8};zJ+zZzʟF_?M1Q4R!#L#A ksv|/&_(fNc PmECpȴSB].O pLZ9g{Dꁨ>YoHggs2Ցa:P ) a6~)f_}ėG#hPnR4&j{'Q`?p`?p0gHr is' V hڊMQ{kwG`5քx9۬zwDu2L$dmH*ҎlpKk|&A!\gԍ‰|& g)KJi*L sۀԧVl.Y(޿.Zqm`GihbKE ##jn1N9axj>YCn}n5Afgy֠ }=.-b} }#7I1$Q"$ҨqoƘNb/"ȍKhN(A3LxHgس!)Ne{[B{qza9GKr3k[RNtkgЃQRޛ\G0q:^=s]gn sn QڊD#1.g5Zxdͭ}9`?Ds' Lgxay: %˞0ud-Go;# MR -ԚOvGǮ~hzsvctGkՔl7||9vc}?紌>V9,c_i{n[ xm﹯`K9FF-[Ag#2v^k}ޏ\wjꐹl*ӛXwcznx<5%kJ8Y55Kһffǻf'͓z'OoLLozf? Z“.Jޖ͏&lq~oQmܷ9qC òuvQ~Rgwɜһdx]>9wɺһdD]>u#} ||YA$gӡK1Y2Fz6Kx:vAܖLےiS[2s;dw׫hL#:EGoMNul9 >D˫tYL:լa&ꧦY dQKk_o6ЏV>N6>i=iMC9krzҊMOZ9+ITc6SQ>xփp=/鄲~tBz^ G(Fd17? (糼cYA֙}kl#^3AM &zyCeɻ|u뢽5fbg-3-y*{֛Vٓ޴<]3+5죞֑>cE4%Ug=4ֱcyU2⫖2%(SM3LѪ:Qf·w4=w4=OougyΥg t)H&8i?QِA0hK%7xv`\$?^8?B,y {s/y=u^Ҋٲ [f^m/u=-a0GhSb0_cEa8. >*Ou9a塠{:*+CK:nw& )LX08~?2>'y ~bԾ頖#~XpN~ 4ܬ;4/X{#ScR\l2}Ji~E`n\ËDz1#_4VA=FB!9A|&eih2ODO3JЛ:Z0"x-zyP zNЀ}(&ݯҡX6HRD` E4H,}v cӮ2̷):^yp!j3Km63`M̰Qc=J!Lm3Yae߈pc8$dV OSL(Ty.l-ȚX+n*L|+9o1wII9O#M C2 #N_"y"A*>*j>>`I4|@~"v`HZR@gnUԇm;ǨSԟMM &w+7u67כ {A8IL$EB+sE@Eڨ /1L&K|u~ n!5ӍЂhg&ya{C6h/l|(ut|= CGG}XD /쏁$َLj/qW nKF@L&(˂QZ6 S' 0>C.HITInM&f/}S5}_K( .Jб rYV99(? \sc|zLm,N8O8 t㼛CC fEd.rw"(J\$BиWGy6+ĉ.;K9QP!d: {dža#:o6 {נH@ӱ\”wE=tapWUmϻ 7cwK5UtH}@TqB 9PrQ"Y`kG>}_!6+X$޼8E$͍כ}^IKV}BN,P ֌]#w2T >i8ygǚ0I;nfEL!1eC@`σ9 {ydrP>6>n&aOƈ{43", 3W/2%61roA!!-"*+_YNL۶BwXe)Sx T$y /e~~xbx`^V /<-* Mfq}pafc>|:vAQWL(>w3iqhํ[U ݜ7d2Ew!| 0i$ˆ'7u̚g+ۣ3'8ʔ4'sԁ3P̰FW Ý 44%ʪǰ6qc863Oy>gP1c=(| ^4v3ܼo!=~)f?`чz!c02 dq٘.~tN8>NA P?љf@VcO~l]_~lM76 ?t)faY% S3}}Uʂ{װgyݣ+wa-r`K)mU~ٍ2kRU~r(~ɏ*QR~/l"|R'Y3~eݎ>Xy!胥fAi0t>T.2uof6ö́Nԓc#lnK4g64.& (3%|--,-(ŒYلwha=tXOz0? lG8 C|x|iT<,ٷeVN=AQh]$~<8KD/Pf ܛהNA_0AuzǻVHcDwu`gcUOpߓ6-ʂ/5}[*Re^霆(zi4LZ/0 /M\iuMmXeX \>@} {`q=X0yx;St-Yz$_< k;-=C܅y97o56Ogxtc/_{l۷U˷-m˷[[|@?3zԵ H$v!%$Ǿ^(݊5BXui¹CZзt܎ {>< ܎Sږϙ2aߒ22s ̄{% -JΑ55 J]wTJy^Eogn d)O2a[2C& z(Yy8n#ᜇ4]촦0]o;eEb'Cb ɶ5]b}z=t&_Uz A|3GD^\`L&s|LJ_ ~,VG@V_EҼ>8WKB9rsm-s(Y~.j%J6|f^Lp]^M? צ55Φֆkڮ;C[ %aIpM +BRp>NxVW1|;}7zMI>UACZ:@ A?Ŋ>k [)jJ3 q-KJ2U[ d,|߿3S"o U,;51e!Slg@M;8:č갣 D/Z8,WT>/<}zDX|T3@p*X?}N/Dթo#vEeTgfi3H-gn+H)gBp 3?*cԱCnyW>Q<͵XJ|L(91H0hSeH`쒒NDbN$nʍW;=F:kEglQ[EwlQ\&r I0?lavۓ>GgQCkn-Jhrl}22[)]w9wE(7?{1 V}:v/w|=õ8xe;^* #ыt@K8}V:|M^dbf7laqQ=7mYjY8g ?E^ ?}T&%lUG>iR@c%4$SH;H-اSF;1(C\̷r\̷) KGi2$a$(6{&{GM/L!H!V"Ssީ9A+F8[oGϾccJ`K1JߣVOjYXSww絥Y+9czWP葺 ct5 G9{ȈudH˝ս둕_N+%Cwpv "^Q֝vl@4<$x Hہ##&cƁt{y4~IwQډ>5C ^}<)=y XX>LgF1N !C٭7@0ϑm}Z]ڍ4,t-9Ŧu-Gm:JNccA%ayNX|] A9c/|OrT &v[1y|WkDŒ#^ʯ{`,Cmo~[:\vd<#Qw}XجIFsA9߃k/ų-}h /ǝhdԐTwA>%֠j^7ہru.הS5vO#U N?օthv=,ރ6]ɒM'9tKH{L=6<ryBE#[{.$'g]=h;{lkfԽǼ77Wb-@̧ jrH;i4sρ~u^_p{4khx!9݃^˸dIgA6`sm:fFyΜUا#y=ڒuiVX'qg1;]tX?Ogca=O%>]{v]DKWzԧUi >W jf#к^-@ G+QXMԏ)X~lKnk>ŗ; ~}clTd>?m2{m]&.z}(Q.8GmZq,U3cQےA 7,'-*uDƥ}n>u\8xb s6=5=|F%%&S yԱ|-Qn@Y`F2[7=>OaZmk*- #^T^`ӽ3f5|ٜn .eܺ-QDݖ˷n \x)Ϧ=.)zGq~}ق^_h;>aI];尓gm;gm9/G}Jw{ )ڢO+}0dOSKd%RHku[T 8q LG(J=rF!qkH|u9)kV>eŠ"}*yENѬmxţc6)S"!xeXvf'bue60 5U"sz{3'9-fNc~SG[FW0?SV%^UX7 {b?$/aXoA({ xњueFn\~[%ta[yqMǸbhڸ/گiGuFWUe3{R*Ea5śy yڀ>N?3"S8}>(iPY ŽUE]?o(m0жmD3$. м횦9hxѮ]Khp+xlgg?K~t. +*@n:* [y`<]!71lWuoXO ˭x+?pQjN^.\0JpH\$F/rV>ljrTuDx~VQY4cMGo <ڿX _N=w„@f:]TqT>rK(eRr?Ō jY~w.Kǿ?2THOuP >SwAJvfn x*LIqRGT||<AXZ^2 $ qw4!`9~Ϙ>M"~gR3 vZtKY)d%nd1upJvetEmeP9eD̙T#&pB2}ДLr>`FW=R9vE9QNU3Am. {z4,C3\h$FP; w<HLpd e_j*F%4A%9*RiHĊq@_crVIN < p Yˈ9=1oc42zCr {4tK%{XǴHƎ6WNƗBʻZKNEg d*>S*\@.=6CM\<˵ʹHod~NJx\Z 9dD俬/9 ]X2575vpRSf.j zA1=-V"uB2==..~{nUN7l:lOan JNaa~H3d1Nc,$aćNxA|<{HM"e"q6utt:0vгp$г9nϲqgԿ[J[-QNz6sYpxrx  H)+=-wOؽaʝC!NL->E ͧhqS/i[, %oQn"}vjIեEqZ/ų/6Py( m-$-JQcyYehm-n"A1әfbozZ/௰=JM{]0m+JZ -Fxb2m_n ^- gxq?[ u@xȠb?E@&R2Ja`wՂWx 鄕K;%Z ΆJ T{q^`j[ :* $'ʼɿD ]pCI';-tGȄ_ uHKbzQZ<C p?fLk3KjQ.2vௌ!Z,Vۍ"F$Т T;-h+ٮۚ_2zق-x` ߣ\87ݣS1n +p*܅{%,\_n ^a-鷇N*&ʼ?~Çz)ZoqÝatJJ=r׽r[8ǗZ,ѷ6vj¿>A9E 9ϣEx-Dž"neܘZ Rs{0F"nO4ڃAoqAz-RKlA@BB &or[ :鞞ɝc+˥)m+m{Mc|x-ZXXijhV ^/gZ&UʕM4Tނ-x Dt#ֱoBZlexi׳NC8cZ0^}?{[[ohx}Fpbi ^ג^2 ck?OGRVV=yjQ6k {~( iRwY _ψ'y﬇NR;{6}CSG~p9-C|)Ҿ5(`0vsn۟\]1yN?gRv/~]ݲ2҄psV^@%?#׏ndn-/ YMZu= leqI! =X}d,R^=俭_wø`E=ʿgLt|H͞AzO=,(A!d) ҿW|2)a>t;ܾ`6έRAзΝr2xq&>L`ơgcpZVx^pp qW׿c<EY6>uî), = ;> ピ6>PJGV !1:]=Ka5!Bx_F6hZ _mړ0e?@hݷ aiIЋRNZԿG"v)qYY fٕz27-*we(R.1ґLp=,>ر=6%C{X:yuj*ҿ/y/$z/$*_=}Mᙜg|J/~"{y_-ѩ/2=|e*5MNkѽ5QNd׾x֙eM4L69WgLrUҿW_Ӝ>[I-4}cƘ=o5*QGI?( iI& A7,8fS JK:t>sKgc)Zs4Hg52=a;sxu6u[XG7z[K+`0෥/ni/3VlY-1]]~tvCe|1βy Fݯ=/_gO'a#odF 6S=T03-KnJsȕ4b^?AQl&}c9f2ٳ3OM7Ļ6g|jmmnY߫g Y9`PZoJav/Xsi ,πIm4_ekm]~mCPMfc+ZX&e;>>tP~U"]s"=|CO:q`F>ǩ] mc6VLz`FgT)RMnzB=Xiի:>+CvZ׷eٟqIaG7s+(<af|0{O>N ([ '[F .Oyk>yKW߫/y9sc>'1Aսl,96)C6b=6kĦϷ 08(*hfp[Ȑ."*8-cG.lK?^L0m Aq*@Ou@ג7{°Ȓ }")=!p?c# =||t=2#:Zm3^3Avz5F=|E'hI+:w܌Ww-wr ,R%B(2q(qBھt3nxi@bB-/g+hjߐ|p$!}fTW)G&>hlHϴF  ~t)Ğٱǣ NX{}멍y q|-O1|467:=rКݏkwkoÇ[ٚӹEHweD@!9Maҧ,Uϸ@9g؇y_1~tk=!0-kf#'/"7p/y ]Ox0yNDcrO}hf#w֛E&a'C_& |I(b 47VsIqWz| f0wCOñQVu'Σo>{X,vsiVSEm:?d߁g٭IYjNGf\e=X;akI=n]Vo9--Ǡo߶mk| K&s&'(٘Tp4DKϨ%8ݰc{iݒW:V~:OA)IԾmp^'x;OYbXvbN*afs8-~\qG}mxӲI,%t_-Gl0̟]i96?|mҲ9?kǺ*짏sϟSGXTCڙndu3Ca)uX#ub=`n^ͪt2x )LK>z D| )Яޣ'/l9`O׿__k z};}rBCS{aVFm38CNyv[,Kut;HeA7w y6ևj 5k;scG1ާmMSԓP~k\9QNuOX<w9Gfv+2CpXmۢN3%\x2PsXIcku'͹j>&UGf(2}$Ԙ'ЗlGo#99E֥C?zX8+X 9\c`9Fxek2qZAԆRך&e$ зs8A,j D` )C?uw{u3n-{i]ٮC?FZBG6}s}sGbg@bj!zu0asݘǗA4!ۉdYiEEy ysH{cž :u..~,#ٟNȝYFĭ =Qs,ּZ~g·:J)Ы_Gת[U9BP-+1X8.KS]{boL{f&V#=[2QMQ7mL̇g{=)߃HM26pj 8bظ6[ ۏl>JʽKDNŪ%sH4揧)}VM?)MIV=)m|bCyߗlo=int6Rpt:gC z4Ҧoo盜f7z(}D ~? c^`? ud8sg3q2veļ ݴP"v籘y,mv\R1iVAB4H[SZXj )Գ0q8)iI#oy;?OiS| ƴgw nKڱyW!rnԝop祴y9NgM4/hҿvna XDBsn&fi5yWjv]ͤZUg'RR㦤=&RR\SRӂtS1DȜj#S%s Q ~(PK(>(`TfE:$ω n,I9$qp/Ka*G! f"a zE3G9HU6Pv,Ȥ̎BzoDZ3u\'ܐr>?]5Y8>,*ouMC_zLp[D]pHt8,Pw]-PQE½9eYQT Lpq[5%PJЗ~k,9#m%78=qAjK1o A߮){Cpmh_ˁx{Oډ4>.<>c4>\4s-;Ag9\otE2kdz[t]-Ac!>覧 ;XckubžB` hk۪uPZҿD]8q9w`;st\8ua}Kiv)VQ=էP/OŎnrcNM.vgA?Fu0%윅@ ~ͪqB]\f:ȸe;b.(Fe=>w]Ǯ uJ]p]2Ej'\ԿGc&Gf3? RŝLCP/.◍wNE۲90w{{V8!zc.7Ycoл7qZv&^XS8{B_ocEĞŌx'Q[-J,,rJԢI2K߫Od|$t!HA8!B. "!XGQ$ if.CzS))S|9V!~=ȺNv*'o[>Vn8ņ}]@}A}M5YFtc{yцv2ƥC/X?`ùdGdNgϥ/Kq)%(RYʚm+n{&I/I=aJD~x[xsCpςLҿd |4]l=A\,׿WyY5~|ըCk:C"]?3 ؚ{;>H T|MqϹgs\܈='(l^Df+Foɻ ȿj 'bX L~I 8TswMb= 5B SY/ 9(m/sP@=6,T @9pcs3\3|<ɔSS^a׏yUDg^ijůoW{H1^)+#93<8Ƙ& J~dlsp|Cxa )~<~)I{{{ 4)\F0AGzck:PI/z!H >Q[jy7Qo#\&k~/9rm*98o[AK6,kg _6d_| ZԆa>z@9nGB(YIgNYFrNlcQЩEWڙeS^re.%Wa+is!A!7|HҾɇ'()wň;b\bzQ?3I|N2I\_oZDs ?f95wdPfi>9 D7_m{0$_Ee (oNYYs}M@6oN{QP0ҿ8[ =9+yC稆\XEP+A7г@g/EjR5J|\K|&RVPa v\DQ {R7"=*o"1~ hq h-KJ?){+T>T+"d7٧$(P6>7_][b[Ч]-^Isw}M4zrKwY,TZ9֜続H+ױR#:S=6S㹨1⾇vFnm7\OMHM.Au.t} 78N{S^}=:MhLHͲ߫/)Ie6,fjP;QPxms/d*4 Y0{Ĭ՗=@ NǓC3[K|C/TGܤz#i;!qU3wz-e8f.Ì#f!9ᡈƣ\hspX3DytC \d`=D`uG^퀯Ew(K ڍ5>ݺ^:0p+|$S@]%ԕ0l9>,bxam9/4DNe` 婺m~g՘2ypGx]BBuK:3#ןHD|cn1^?GؓТ1댨8"d% !s.! rFsefɍ0ɧ^ 6WV佄ɁAILt|BxJb1;nc!F"X~SZm\Wa UvϕyEq$t؂.;^fTpɼ2XsO0 X,|D4= G >"N6fBm ~wNh³gO-AgB*̼rf=B5K1~J2>vNcTǎgəͽQەy ;ϣoҴRu8U@~A7 WfsnoyiNKpvͼ ݵ *岿OY\De92hyzѺ'T/h̯PC(ȎTϕld6j'J|x#8>~S Kor8s.蛺w޿is$FQs#yWN۵_]cc&\|eoR;Ljo h"g[@D+kZkk25C)B64FwCOw2 AaaT2z,r;-NHe,B8inb"Hbq<"tʐv*Bt|l`ovC,?C +av(a6s5qr7܇5 K k[bI~SB!qqD`:doC8I!K{<'A{.o}+fӚX1c51d ]{peg$c #)g(;8~H 2Ưm#]%~M4jI/ l&_GC5$6mgޯcoXxl$@I+g'vVH75o$ӓ7ӯMD6E s*b}Y3daCl^niOg+ʼfXUw*¬˵ s)HuQईs<nˠ; HZy Ѹ^CzUBُ4ytzlۡWX/׃8efYkU_Lye;̱Hv6ʥZ˙PHp D|I}{=N?}{VyhʱATkD?`('!٬12VSY ַ8pJe,`|ŬOaAkEt1{ؒdǹ1w 2 Ĵ^m_:޲ۚƨeqv!!79ɝTHU?Ō}"5~`wx[U_̲ ɲ:hMue_abZ-Q@A羯[ټ0ߟ-k,n  uQK~,_{>^kb\-;SXβt֐}ǸeЮBپ0Ia~cri 8wpsr={R|^V-ER-9]D}ȩqו9t>Gk.G$p \ءgS1F}g(R<)LC˱{⹧#k׎^`&{ X='U$|M?Mg0p*|2EJ"d+*, |bnSH`E/K/ֆc5~e^c.Ln0>̉=:Nboa}V6r^xA9Vy>urDA- @}@t?%W-cEšVp"B Тmh=0`]ħZ؍s8|YyAe0Ӟb"/x- z_mvNڀE; nUN,Ƃ8t+wHH}qbR`G|VHáI52 !GЕ>?[(@t9䄬3 )g*SRT$C&ZHFFUKF"@h ћL T@Qu⸳=j_!̹EK./Lu2E)[i-#x% p1\՜%ΪkCD S5EYUNS;4j!Xc&dv"l,Uo xj8ñpR؄sjP!XK %G>4܂U燬t1U;s[֊Bd[woqU}wX]ay GGo횡b%lEΌXpx_KLLpZ+0bGeu$ݮUﭬaCPscI,sX<Ԓ;Vk7KC#xqbQP2wcmo[0R,v 97xyxk)־0 %vTB`+!6}5 uȾUߺ~Va}.=-繡;|D Jx1l 'd>~sA;,cۅ}_zX9:zHq1~{|GwٽXkl|"m'naKЂK"~ Xq6/6fse@ AxT.bJ uJB?'V1<0@G@W3~@2l~C74}žlMk!_H' @l,m!Ag"L1/myF~k 5d>@ho<*~gW5nw H>R Ǒ :{*Jڳ 9-"e Φ6rʔcX`#bx|*"MP"\94@,V xHiȮ@iwFY1qqƻ. Չ*I`'2<=E[zg!m;1DFn?82 ưF^]b#>^l C|]|(0:_Gɫ\R.+P̸/!Vg/q@XLIOR<`@ yyS׃oJ~c'w% 2H-< a- "(Fޑx%tfD.2 ɑٕ1xtCi‘7R{@77$o$S<YSuʀų#j2Ah %m JKlڃǹ=iOu{dIq9l ,x2 Az̝<]8jHx5̧^9( xB}R04ltBTt誖٪?3-aCa뛱:{U%jppn "Lr L zx e )D$x w5w]Q@Hu!ozZ7EXO4dۀgQ,SPhȾ :6TB󧱈exk5_N**>xxB0x þoxe{@x9A#+~= cNۅIg .vҫr@O h*"pyPi݉֝øoxN^sgȼf23)<%>\p~ڽVQ4 7d0Nа MRsa bx5o`MDp`?":; 64}[ˋ{Bo}7|1;OaAW")") MY$e)0r$hiBθsl)5fHkaqG#*>Q`YQ*F]Vgd'e[Udq 0Q OSp@\M@ҊѷugW5Na3d#_PeD-}ƠzwC?UA$ R~],s P&1 ( w j[]&+V1?l?Jڝ߅Fk_eQe9K rse~!)HcM *+[C א[w 9,L$okcr`[&/Ũ:lf Yrh*dXcl,֜!A&&Z_pdsh4FY %2<{ jNmr< -0 WNk|DGDJkWjrZ7ÆM.Cd&;7XN6cFųٶb?PslFy|el7advYKi"SŜ3Pq\Ⱦ&'Dq".cY}_7)9Q|鬼T/?Nl/fžP3r_טFe%hඬh L sH\EFE}m~DL9YobcE ?w —63͈f_ `hWcЅy #EE؟<9FD`2{R5.G'CU!␤CW:JoW{r#/ Lɟmh0??3ȟ1 3̺}PNHv>S8Jxi8} "m&%L<6CZxynY6s`Tj0&|2@VJ ֑i(L'2f2sz-ߑirn' 7?'nkqL ]>%uF;~ q]79lJ01)D:bvS͒Bz at{IG%$b,2ue3i?w0b${`ثapoBã[q28 h]Lb|96oWnB/`ŽEN\8rD( ~B`b!9ܐ>Vn7?})`;f@m`s|]K%7Gh~|LTd} N1S9 ,[2;=N j8 Up-y^ho h+c<>RGDqq^J 4P 2c8ض6xR~ ltCv;5MmN ^ߴ1}#`б"^XLF"@UdqkB5hgcYiy4W}8/vuwA e9ij6d$q4b,W^lf%G;փG)^׹=Il};aV9X}Gfz 4vee>v'g#8$$k~#%,UQ7;Sm(?ڭ|ŝ+'ᷘ< Elj3O]ì({8SaMp %|3ߠWz_+jNJ9$oSk?Ͽ_~/?w?_Q/W'43߿?_Ͽ=%a|f_A@jp<aIYv??Kn`PN`?_?oY*?׿>#ooޱtXvǍ?}ww? endstream endobj 340 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 328 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-045.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 341 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 342 0 R/F3 343 0 R>> /ExtGState << >>/ColorSpace << /sRGB 344 0 R >>>> /Length 34575 /Filter /FlateDecode >> stream xK&M,a3:"$z (Yi_Wbrhʯ/ů_?_ݯ~KH{.W+9˟_ٯ_?.D?ouFoۥW_QU _/w_?S~߿)Gu?k1g&u__F~s:6cůƸ_W/K IO}D@+~*{u_ifԊ2%5ĝC;~ٌ~%^"X]K GZi>﫛'ުOY2VVz~t/ƌ5}_e]_Y D@+k xl5n/X+ eJJk;mW}!cz[=oxWwG]R:;q$?%ݿZA,SRZ#a{g*E/okȋ#oCM +o}Z/s?wbӺIQ7˖vuiaDޚB}G{=K3^Xf_[ǕXQsLJl.[7)ZeKnKͺ[E]3Bu_ʅ;S^F߂46)Ưy 2uMlrl_U*99o>gw byw(9gćd;T][7)eKnrеjF.Ji"X֌l߰q$3^[+ ?LKip6.h1`FGA"ؤ IG3qHz2uL2d q[W.0  ԏ:bրw(>P/ XKip\6Qu5 sГuÊֽ/ MP`Wj+ kpG ۘL?46 1ٟtao3U$7w) *JK{˲o?ޏl[7Ye[.K=+y; 9O>Ң13K{ך{*Q |HK?e Ns]L٢ ^zxz }֘ˈba5C(yª GlR`OUwoz(1&(D#ч2yw8#ǰdq]ZG*SRa3jvX7},I!)mgbp-PZG6P)xvot+f.;]!U/'v*AvV6,Kip6)`Êg)5#fC_KRDijShf/ٌKe.C]$P;"R‘Vƽk~2%yĝQVxbޚ;h3,v iф-p&WCb6fܻ4/ZII!c~Es0fcz 6ńtX>N:Mw-= Vi)UOO׫wĄftZ|5 M1tQ8ʟq`&\ŞOY2V+X1GŒϲƗc7We^f] HP+J^c7ZI(RGioQsS~bʿzY"hS -P#A)MΝ%j9U3(]k[\\g#$hđV3R8bH+ >})# ?!|f<1c?cu)<*_e$fq&.3Zl W%57T&瀳?c^>1wn|7Ώ$mL8tZrN[eٙ>]1X؍`+qNDiѰ6k%LIiptG'>]0 ~16$=nߩbtj}cY+ j#UNJFV1:wUb|&P;g)}ec jOɸc,.ZI,RGiG#a蟃Ye}'б$q&6tN,^q{+@ˈm/i%AQFVpl5lFl8.t`B8wCf I+ jE8̓?H.4-pnRͲ%~v]*)j99+zcΊǍ.>XD5UlNll,*nR?VIc^Pc:䠓/a ׊ _)|k ~$"nu[^M؏ݞ`Ki&7F^+r;v?Gb%Aĝ̞S1aDcoiQ? AE|bp:@>4-VRDixn34Ƌ3qfU{|Ǯ;8I<20 Cube[N1,yqr<[^G+{kq^5Jřt_{⥲-]~v]:kU۟X @\70HpXSНX.ժIx 玔(?F𮩱s0&{ѝ n)v@+2T݃~:^P4H\`xӌmL"p\66 ÌRQ8%$2-)$r3-5u ^ "fC}aMˊsc&I.,rEn&/l99#v Gc͢${POɴ%tζ&vĺglePAɁgn^ u8-L̽-_p7VTJ&.ƲnP^i{B&GߠbW&z{/~IqUJfXQnYayf8eW.aO3>IżNof#u:v1ڴ,/6fbEyKNh$Yt}%~޻vc4-m}X5](1Jr:+jq9 ^%6jנsQٖ.b?v{UUs՘,yr]Pﳴ%,;'gN빍Bݢ!de嵎NN,P|e8|2TF%_1q>rnREْ.b?v9N ?'g;jHf|/sm95Β\36|{&9-c> cr9oǓƸ8ß{ܟ)Z>ѻkʍ$qxlw&峠([r%nch1K> 9ί1ѳngt׻Mbḻ9P(cʲ\{8\%e<Մ¥66rEr!hڏۻ`sط߈K7)ݳlrR`v{ခ'Nvӈ@.,Y $A6T1<)]~1\5O6ga[`k_זϘ$VVcN:EnRYlm#Q߯ssp;|c3nƊj4T=pHݗlm,l%98 66=8HкC{I6֖I*[ru48}sb^܃܇Yj",$HE`'F_Tu¯Y嶔؏vaĉyH48N4\nH¡_+9Lr0 R$Q)e[nKحĚ;a̠w#N6gױjWIw`"u%v {} 3%&0(7g9⤍E8`FՕI-lm)^|Ү22 &/;<5$̩0JM*kR.އI0p ē &s<݅50؎3y%]~v]*NLZ8y:q(E|cKXSmNGbt^TK؏L' x7w>k 2R(oab'F68cX72H>Kngs`_ ig+$0ul1^sQ)Xw37r:+kq@8+꩛~%~eg997ⳣ_ek4 ȏ3=r/[#ÕXQ_c;ߐ˶\uAC Y 0`1ݝOqlh kBrDVX/֝K-nn4`q^1)x-R^XS'0~anR\.bvq2s~sC`WOXY9Oؤza2N:T7˖\v {kL}yW$.}hV`;YAj8K&E,rY*i#?̙t]~'ea('V0 NpeKnKB{瓋*&-ʁ!әwA;Ec9a559 +-uFr%nեu΂YLd3_ē jE< Iv9 ȹ9(vI7)Ze[.ؽS?srcÚm,}RZTz3hlG&EݗwB.1sr˯akdoY!yO+{g%97rd[vuSʦvDa Md80v RVn툄. '!01n"ζQF}L1ܧGb錜 oWmq$u,q-{2%5x#ȫtbSl ׀?Tk9#KiP8W.n$ꃆwjJ`0"KɥEC},mX 'ZmS0ƃX=J?eN[yՎf422j~Hk#F8 D\k4HeJJk;mGL"f 1XDĉEDةNKǥ48z eRWߵbE))OF92cs%4fW[J"gOf`n!b}2ᆊ w8{_wv#k惄1$ÒFebLl 7QF3ӰLIipgyX#s5Bd7 yh4QclS/ EҠꤹZpRJFAA),o6 kʌ\NVԏBSv N9GBt@YEEybdɟYolj'{V&E,[r%nS tsimӺ)~ncS1p=H+9ZY1Wmex|Qu$J+ wj[`7S:av#ml-/p"ȾՎC}j%AQFVϘjy3:l$Dɛ0{n)Ս#Qs "Fq7zYeJ*k;mNdఆw 7+=nJZorL#qg # YEaYp Rʟ,kY1.L~b%An2JT +4^dtñEw~‰[@D=QJ5ORZ#iÐrMR3En5b"-LR'biVni%/i)cN>Q yE;9x@&iR\K" .ΈI$h>a VpX#sp+ӛmqK|5=OZAb;_t]-ui-NEpx\(L?ecE$:67_x-yZ i~/Yq5ߋ8BN5S?&6Z:q WȲS.v;m1*krDsJAy ^VS"ȡ\9/cMQ7-NENmb ݻw*r[ ưTkiIh#8 eJImX_W3'kˍ>⸍Ê?0̃by[bEM$k"XNoeK.=pN$b N *;TGM*c'.!OTi)ݮp>sqNԪs}Le]937aڷ%l}oŋ_e-yZzٽW;`HeFIDѺ>OFm +jf栮2ueْe'Z.!NwL~gl`df Ȍ5uܟLS ;IQR|2*r%~_g'spCυ'DŲLWIyi'XS;ߓ9<^`#u;}e pCp/s{Ż, 9z/o qSɩT(@x`ѯ)kbMeܔ9Kڈ]*IQ.a?voAǹ=y~ˮsO=<&Ky 5916V[7)օe[.KR{ iWE<zRwr&4TaVaע+ubdٖ.b?v.K3_p4~ۓR7p؅9{߯t=N"cP\YoߜżP6N!6.NM@.<k{o<97؇I*N~c@>?'g0"KҜ)ZƽNQš2cߺ{lrl_w]fspB }\Gb(r#qC^no+jI'#ur]RҬٶ{/mXEU&M^\չzkjǸӐ6\K؏~/rg&'Y8[4e*]3'e)ũ}nm,k\%dnws:.QZW@C1%AJ:&Gcoj˖\v 7!n* ʳ5;[}$I0n|/.[r%i1\##ĉ8wrTNeG3:R~+$۳Epn{#Wu;+ʖܖ{Gb0N?vE擘F\m+Z0j8K3Ͳ%~vb~t~9+ߤʡҙ*wV"kf8vK>ը:;_Sy#3 se[9+1; F;eKkeJ +*KvBD-y^5;=8ɽg&4D6I.|ƒ,̮#6#ĺIFْ.a?vT~>9+׀vreӴ$V}s#o}yϲ%]=̭m ؟Sȗk̑K'*H<~)G|~bE Av1}Oݷfْ.aO]l3`yA]^}I>{rӛ/|Dc7982I[K%]~8bMzSL (pϰdbEte`=XSwl-{/qѺ}ᒳrsz䠘XYwcM̪bReЙu6m{/%K3ٺV^tn8Iy̹{DUS7)/.aOyG#rdNJligZZQY^IyeyaM=A莱\XIQe[.ؽpMgN1rG矬JOz֔G ^M(Ѥ MuaٖRb?vx"97bV:[J&)Z|y'u̹9RMo[.UU7tp0?\o}C:H=&f9$UKn,aWq!d"JNzZA>uX}bX惱nRYK"cr;߹ߋ9 7;pK3tՔgVTE;Mշ\v {ڽ}e>Lr35Ll:)Jy,5FbM՝}P+\_;sbcٖߙ[nEӇ?9}72>6˖Ok*=s:a'BQ{fЫ˖v{BKerZ[/!zQ}ڳ}KsV. Z7>Hc/@|_|rZxwԏfN9Im `Q(/@HO#eݮ y8bcʾm饰y*#6{R(]rY*iB7O3r;(# LZ)껍8KVtʖ\v50ݞ'r)Ճ KаGIƒnZ{úIy4½v.7,ϗh삋"\r _'[Nvۭ,SKOspbFFLܙm]c!kc* 'eK.=ŻLAywzsfqovb改L`cerU_v.2_ o:X&C+^\tٶ+W[!!]žvk2ΰoq^(~ަPCSk*w*eOQ,;ٽþ+G ɠ7 SnJy!jՈSEBԝ ˮreNQ^ʃ_ְEOyID2H,Dݢ-S.vPi?es{:NL1LA*I{1m ԝqYKnCP)kaO}w&}'.\ {DѺ9-$=>u;Gا!trە}ߓ>W ɍV1/r6-=:̔cd,)6]urDܖ{B{;rc{aZ}Ml-[S#V;*lm}M}37'v zuxc {$_Eb~9pK.uɲ%]žvy2ҥ8>s`sՋT#u?<`gřuc+Ӹuٷ됧v.IspjߴhP:Ic?mc )ec&cͪ%O=v]nzg i`LY )o`!̗{pr擖;Yi)ݎKzݝ*7'Rԣ\!0,!/&vS_Y쫽Eԝ_dٔ.b?v.H"TZ#ϣ\9wryu_{kljxHVIJwԭ_C{ڽc{.4F `kbyJIe<8۾Y2ז.aOcxlN#M*+ӗg~naX5{ȲS~}סua<98EE؟SZH$vw.lRIΠuƢIJr%i }%LP1w2esWXQ-OT6GkblJ9veْceҰ8_61%,6˔˻ږw&6)lN[˛y;d)]v7VW/8x,)W3ؤڎ'zN^첯 nץtZilHtT+uʟvbEls ~{үeKv]/]TNJ&'N )Y}ܿN9NMʫsഓX{]K}Fs,ܢ:1p󞫘PyNy+jwkcϒbgInyZv]..)%Aq1QhKQ_m=DXQ{J' E,hX,;nՅ7#!jn>,$z)j;R^zvSuf].&|}]eSn7' D +s۽ItɹҺNeKv]/]wmNиt5)[S|O)ecWae`C9>gF?A?>. Ao3`M鈖1#u|,&vB?'F'T%iz-QXQwDnNCcڕht)n]&b].Π.q+QN(mSl5{-yiĹNEﲘ=NDD 7GNCcu[wt.[r%ne49>ӑp+fAzgwm9zcEQ3^shl$\~%~v]l5j8^!)L"kzue_\)_C2VuI+ެ\P'ub]X䶔؏ǔA١\1j|_vqf_\Qja`)JCXS93{xM Vْ.a?v6f2q]axc* JOy*(A^Gc?кwB--%cU Gќk{i,}bTq' iم57T%bHݤ\+嶋؏ݮB2}u>` f*dzĚw b*sBfٔ.b?vOS֫-ӹ$isUި!==ȉ^&Us e-uNGmxFX^Ҋȉ<r'VTɝAqil8[ݩWȗ{6WִgNұ Dx7ޣqk snFPʶv {7Ϝ/Qp_([Ѝ̩]܍#~U䶋؏{= )֪9M 5VTٻY'y)ݤSDْ.a?v̎og0gEgՈ O mQ[mĒq598źI.ܖfa{y9։˺kqtle.;e\ ds&'"U rrbEyhs}bu,a-v0s297 ~egrNydtXQ9MNLJs*r%{=pLNHeϮS>;ořucH/β)ߖݻvǾm_PH*[rԽO ؤϚe\v mg7cߒsVbVgW a"lRY\ݦS^{}ugz1zwr"kjΔT֕Xn"w-"c^W)Ν '|gCCs{rJiuSvuuqFݤkm{ץ2 ͩmؙ-#$lwV!S|N0wTZ~.[r%iR2˖1s4/^hڡ_\޷W3+*M T=73?g<\1"2etE ]ncX,X䶔؏ݮ #F\ۘUqFSn& {%TY8cG&$痩ikL<9>~MFfmga*,ղ}˖v,KF{(Syvl9 AHEb3uwͲ%]žv,Sϕ9pk '\/ kby%5>2CX[ϯ/ڇ:}:oy`r֙3 C+xo2T-%.>d%]~qP; C@a]]3$u$ IÙF;U}HֽKrْ.b?vpGzd4L}#F6Sn%'NwLnҧ$=u>g4Fic= Wk*,S;0\HeK.sVmLJt+\'xKޝC ,ZXQQIsK-b98K.T,Eʻ&omdM13[>o-{PWĝbyJr&S*LS.nAGAd/柍x/R,!{)lؤ΄ Na6(a9G=q)]žv?}~9! YN֞'6;/\u,G'Ks 5wºKzile3Žr9 EPk]%_K(acHnGI,:{înͧhwœ g A.ߧ 5Uq 06<~%]~v&Yk"x w]5KObE"fZwɼ .[r[Jn177BFyxpĔ1B/Ae꾽keSnؽTE՝֡]޸B'"ܾ0ƿk*cf̺IQ岋؏ݟPq(Qs" Ae6_}cXR3[S%ur]U"yZ_v,u=[)[-U[ؤMfs+<g.̿>rC1i|y<"&hd'-umV#ݷ`ۭJ{ڽsv!#+In9>Ċ9ބg^OewðK=nV:3=?V+ 39Fw-,(,)zbj?[aܖ2\{E7gΙ➟śI_ORؤ=KX ,%Sw#ʖ\vmv][B1s;ܻԠk{ˑT'{us|~{ev=Y ߢ̗{+s7N,gD_賍U܄؏ݮ \jABش87Mٺ9N̥3Qb#wnR1"cL~Hs+R#9ϥ9&5z~dR>2ٵOXĭϲ%]žvpvʬANorFqS?[m y$SNo,[]}K a.-w{c-ygGaEZr6=ŲnQ5ovg>_̙8Y73ѻW}#w-oJbNG d'.[r%il[q}˶FVIR>cf[s[ǹ@XymNlmꓫsլpUQ-.K{yʖ<-/=bTSY܇*3EJ3rJĊ M8KWXI *[ nץ:.,/f3ג7Zؤ_s]ҝ/YveU{~/xvAM\F[%8UGX-o{/\yCL'ϱR使hd+|1ӨyGA\dؼ$u%oygRaO]}},[M-ޕ;yOb,mˇW7cn,-Sww,[r%irc~P'Z"nֽyFVEk^1KȡzJ,VWu¯Y嶔؏}>\|yW(˫= j,y3J.Z7)RaOU=='ŽCl8vǐ4ag[Ɗ:؉U%%~V]_SXѧyuBBySŠNas0.O&Ś˟r[Jn훃6` ފ)٢q)ƚ߾9=n#eK.=ml1s6Έ T. vbnb_H=cM->0nMmeK.L߀ qknR7wKb]O%ym'T;`G؎M>&>rsRb?v{adS8jBVE0e+1Šn:y e[.Kؽ0{Œ/WMy?zj6l&Y7)E"cVZ$ Lu7_7ňh{Ě*k#NO g&eK.v^G74V[O䝷G;EnYbV"N7ԏFO?m)*ϗ +\2Ep5QANݤŽSѫ 5]OJJ")vw;M{,[r[ n+uMwXrFcR|*HڏߖNcEn s|qْ߲w֛Q}ߏr3}98yQ ?-foS,O{;)Ďj8@,mʿ-OKn8C [\!FOjMʷlNd]4 #NuMmg|'ne?qDTo~9NSO(J9n,R5kr%{ץ3~Rӓsz.-EXr o?VTN?8L,SX7)e[{9.Sox\Ң<Ϩ͜dO3[wFdْe0W!9C+ᙦlUi|܁Mj*SelIJ_7]= 6VTEԝ9l}.6ÛIЉ`wIƗ7 +*cx11 IwmLeK.=v].Gyerp~z 5mzI~$Y',κ<5u%r%i#7Nxr!gP0庌go~5UAdI,Rwoeٔ.b?v0Vlc G[O[>s{˙ؤӹbsu{QK>'-uVh{])N7 Si=}_[n|756˖\v {ڽ\td|ҕ3!n;V ˦vuѸ}qO"lk9rNڼo_Ga[7Y|KRaOU"LL䏎f)Ӊv dsy:ںI*[r%ne,gTHrZoN^̓OQ,)k+*330؁XP+%]~V]::VܷL72+wߞWp+HXSyK\rRXJs]-"c {qy?99-uLFa \c5)ZTdm"lN㧱k²%]~{o'ÍNxq>gW/nٛ8!\t?nRʖ\v uym}a޽pKp [W==XSmtb]X䶋؏ݻ.Ȝ*bMӤl][\šTsVC[ ur]r%nե[#vb,S,;cE?zNyG޲-~{Y=jƉp?AeR,Ly5\ %gJ cEՌOd,F&~ )~{xz9Wgr0Y7uƊ'U)>9g(OkJCqޚ'n{-]ƞv.7]]ŜѕV5eycWaMYʼn.%8vnRͲ%]~v>]?'g1gWCcP9$jbEͼUqsKc᭓G8qْv.=hB^>hg)7ƖwV=hέeFo-{슯q$:Pz7&vV$gĚJ QMui5嶋؏ݮ2?'g!GedbNc&L)ׅy\bX#oʖ\v {ڽ_໴E4.1Ñ/0gs8qvbIQ[$8́,l=ݏ{Y䶔؏^n98"^9&ctbyI(쳉Elc0E؆M*Tup<-xI>; \bcaJw'*r%iXt"sxabPh(ԏzpsŹq"l{吺[lm5VV8ջ;V49OԸ6pV+)~s<^ϕXSݱaؙݺIQ7˖vs84~,9H0W; #;הC,5u3^pffty˖\v {abi~?3p+k|h7g+4<úIQ7˖ܖ[uuX&Hajq TP^HrWk*`b{BU䶋؏~/HTSR&;9.-ތ"$HXQ顕DE[5)e[.=v]3}rn wv[šʜ4x0Y7K؏ݪKѧT{1W aƹhW/ߋ97e )μY6嶋؏ݮÍ9ru}\dM6LѺݝHjDAx^lC}esٔoKua>9W!x Uk>Lo,uoZ-uAB֙Z'BL%8W 5rEm׋s&E,!i10MS>|q~_L K‰M*}G;G@졄دݪ<<ɡm+0p:iH<&!\ؤ2O9kѽ $-]~~2Kt螂]Ӊ}||XR3 qp&l!-*wlgm)XI;j bzoq(YHM->ATq,ԫu%'"c'?B8gt^!ឯ(F2TϞ$6lIݢ8Dٖ.b?v{ܯw &g洌A8;^OD5 +V]5)e\v ulW' ify-_<|'ԕ։3=3_˖\v kA9=ĕyߪ6w^ϖƚ*y.=ŒںIyO4ʖ\v k㯚m̜AwHQ޹82T6&c&ur%]~u)md$Yp5d;:'ȝJajc%&eKn~ڳ= KşpX|7’>}}${#lm)䱇{M=]?s"OZ[7%l#Yn3cu^\k>ٽ)5F^<kEq)ץS>ƒnZv!u%򴴕/e'_S})9/Sbm }9W2߅˶\vuŞ,ܐ{z1V;4p7ԏj^ǖO"+j{̛3A|Ɨ3o˖.`O]g.si}5tHwbyWR|XS.sIJ8/-CqR]6]Sy4tnaKr]v>k9r2VTf]L^u-]žvwr1ؗL$t녱Ѥ=r%a{y^_T~5嶔؏ݾg$ہN⤠ܾ.fƥr]g˙mXQ{12CnR)fr%i^']$v^8szDhIByʱKZ_Paakκdْv;ubd41ጕ)#VS(/bS-?cE͉婱JݹeK{8#ftE}%23 =jr1%Μw>iHݤX-cѭsdn$0[|\% Kb7u_UnlsՔʖ\vu]p!_27zbyLub˺kqƵҝYi)ncVz8&DVQbG5ƶ'vSOg߲9k7a2:K d\.ddR$϶ h7k 6w-7v|̾i_~ }_!p`p">o׮]'OZh \X2k1~^(oM/fDF%{%CtRs%,뻸[}nOx# c!`Ƒ'*)ѻų-JѨ'~wNKطߗp_sfaf"xy~XBx ;ƦT_b͋-p%'w qz;]4H[*;Owϙc}hؔȗ&c/?NUXFv߲_TJ[ɫ]hgt`K/6'ζ}_o G/[v%oLqR[)5XZBA׎aaS}^X1Jm/ݾaO}B"4c%ekj&El;+f߲/a~OL 3=XPsj2]mve7gXNP@mJ/Eob1J[s|ܘG%.(\b-%{lj646B[M [vE˟,.[^ C,tp~{vVB06zY2Nrb7;ukfQ]D|[ƀL`G,2ٖd^mJgY~d(ro'tFkڻk;x&jMØm,9vߕl دZ}-5N6KcJ3J֪Jz o;8ޫ\d߲/`~_ ٷKطߺW̕5mp i(?ʎXI7*55vzǶ)')}-dEr<8ZWz!NAiigXv^KctfO,G[_}.O}%1VWg:f&hMqK|x"z.o嗰o}-QY\cBJHXk)~H!,%fNL!6%5==ȿZj9x:k٪rip ϶yHo嗰o}-|ljfs75'$) N&v&d߲WG[28s=͹5C*=2 <M/ˏ5L=%iGPDb% D;FٓmS򕋛=ׯJ2G ¥[Ǩhb25(Mi$5tu,TʢR_osw0#!Cԅub[*tV?SXIAҚBa;S6%5~qL fx#)%9[XIl>4ĎnXk5Ar1LV[q˒+ڗKOm2FM%^ ݞG5Df`m!++͒ 2^OIld^;۞e~!c9U<>ˍꄔ`pt9UuMɣy.}.$ucԄ?F+;<¶KUoi'Du؞ԐR`<ķ2T#!a1n[Rੑ_~JBUs yF֯S-ѻkb{.VRfʥ6yQے<굑vPƷߗ%4 VAboSȄB{ZAMx`tݗamI|_:hoj 6ߞZ9c &<*/ikiTQH}[v{Jo_KgdL 6ls/,yG"f+I!f_:ƕ"۞#e_~8p2T27ZBlnJXIipRB:ԻᯑݞɈGF ^v+m{'} c3_Mgݞ$k8g$5: '1ii+HXK7zښSLgl{ޚ?vEo_ o\5 oR`x1e'n\_j&I_yշ؏߾.~i6i7nl>[l牽V^aԣ)v{*B߾q{ d\#׈:*Х!zMXKq,Fm匴/a?~Z6&57(vRb ÷YXKwcv3ݷKط߾z8& Y_J^,ѻ$V_KxLc'Kyg [v{JoYp,Y5XÏ E7ickr Ts']bNv۔;Ko_Ot8]C t*)cLZ?>BZVM EM¾e~v<[v%יM`^k_7iKwԮ+fؚU|nZ>؏Zfy-Sȼ{?MѻtlK[Z3A54mJ-Kڜ*75ʘz>%ϭLS#j'#nk}ܷ#h~pc䇱ya»9hWWMTF:c6%+{®= b?~# %w!!?`D'8rOg#s,ɜb7a%m4|5NEԷ؏߾/6;5<,DՎ3mBJJdL LTݔ_~\j.k>%i޸T>dk"ʹYZU XeY%]~Dٺ֩I{ -rBYn-K+w!3:5 I,*9[߾j_q5OM6f%}`ؔ]~ Nd1wGj׾eYq*xK/5Ja+v[v%o_ wD#1p?2Ƣ}1ZXJw65 4U۔Ơ3b%0I 6X%ߦ۾̞[v{JosLg_oZ"hEךXI3;RXcc0mJط؏ Z,;=&5:q|>K;1y'BZ羄?+,eʽh3}.m>X齾`C'X`xe%7-;34חdE&l3i_~}@wxjX7+d< LVfk;nܚ{byۥe_~}yx饦=xQ lg=zXO59'vyzd{r۔x-[v{J; RO(:5(yV_!퓄'Z:#E8bk3j|HQDfwlj"\`zS{Yg%|-bw}NmƧ8*5 ;'<~2V&2b-XY3' SLݲ>]~ ײy +t𓼣]lL 5;[v%oa\8URy빣 4y4>fN&jA0uyw ݢz\lл%eH̰#v~%Ϳ 52mXm{1%N%KԒk1kj 0;<sOs[״IkՎܑm-Ex)Oko(vK[YpD ʭ N}2oH+4+ՋvɈ-r'jԟ\<ԫjET/5Jf.|hn$]~ [rUq,5"\؟$w6{4ە?!-ۦKj-"㷯:EEKy_$?rȾkiK}"E-6%]~ ;??ۿxo](y?OUz@D_a- endstream endobj 346 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 350 0 obj << /Length 986 /Filter /FlateDecode >> stream xڭVK6Wd⊤HM=4uCVdѵl"8"QpfFQ  K y%8m),R+RɅ K=)!uR壨ۨ@ӎp^ZkX~_k&+eZ!-ci)-I.l Ā1!Sx}o!i{*`qޑ7r4gu,(7gG>o`^X7b:{>Kܯ TfegU~Kֲ-#RTTxh 6]L>mbTV+2u0!pROzͣ&ܣv7w{cָtR%5`ibOAOk4QH}Xt /Qew8A<Fݽ0ko04 YUQZ%g6 endstream endobj 329 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-046.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 352 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 353 0 R/F3 354 0 R>> /ExtGState << >>/ColorSpace << /sRGB 355 0 R >>>> /Length 25703 /Filter /FlateDecode >> stream xKv?b5ζpν@ U/NH;HqQ|q>o?ϟO?]_u}О?!uZ_|>??Ck|/?ogѢ_wUy?W?!~_>*}_O_c}*a\Ӊ_}3Zs__<= \_W+_} ƣ=}w+}v{}+{;}qXc<| S~U~_4%@|F ] _>v5'~.뙱g > m>h}]o<[;϶@ߚ[=c`ꘀ⽾1k s||ߠ j9c5xC5&}ZَrejힾKJ^N5V _~V?tg3)rjW? #XB򝼫Ѱ{g<+8_WvP^Yӱ vZFޘu#ha|NΉV=߭ھǭ߲:q}u_)_|Vp}8C ٢#!us˶BOJ֧ږ[$ywǸ{^VPşgB7qM}<}i9.}[Yy~|pҢiVz0s".;\%b|ZWlMħnH=n-}dWcoBݾ~%T[[W*^_7iޭھǭZ,  s>P So1n+ľnȻ&z{lc-;H[-C7N6}mے]K;\W!X*@ %U;Sˏڑ2C7(r4jgnfЛ}sc;ۘ؋j'˽&w;uQX=†ZB {*cc{>잀/1 ߝݎzLυ #Mue]^c Kp?*h|1K4Ԩ![qv앏 vj+;}cXVƨނ~ty7x㽲+tbo#VZyʄZW1D%<+F݆҂e a}Wݺqq[Ӭ#40F;͙"1+0{m"ͧue/vS>u_B۟6a CtBЀAwpTDMP>d[WFWe[06(u_R0>\ I&a"q UB߶VlO[l}Km>H*?_|1wL0Pgi֨FWMmy_RoeO;|e9..d9M!r_@sh+R6P&|}Km6MF!w^*L=Pef1-m +5l[h!T&|k\j+j #]JWl)˷;nF?"`ٖ}i]YݶЍ7u#eoi|;ʍUX utng[C)|e2mnRݾq{ҫuuBE!H<{7Dw;zţʏv{nP]^c1( |.}_`?u` v(SjG^(.w.Gvj!>u C i=d.ͥuܽeG; W|w{^ (ڽS?e4-^0uXtY遀Vd43_#Fz]F^c_tIwÊ_(qNh5Vs 2ķ;Eɢ#> !j'pD?]h.j̽D?Sw9{!.Lm\5BbL켻v"2/4+{;uQXuo.C*~]P@wW5 #|o|wv;>taSg;Jzr4j 1ͨ$esF y`eq}_)ݺqqS,П}厧b ]M7ݹr³mv.r_ܖZw[=.1b^iPWII* Jd2!e[aǶ=,Bʾݺq{܇=dKKe^1ud%2^F^qq~W*n[at5-~s\n cZ{֕`N1+48J.<r*wnpM1U:.h#`| &lw~6|kߓkF{Çoxa!&L-"0`ji->u7|{DžjLJ㝾{?OJvWjw07 i}5*icLZC1{}. 3>CELօ@~7ܟ-Н_R7<_zrj0C}T gRy +낡tx}$Yv;xnG^K]c'xd&N =DV V`#`-]CvuOa>qDzb |A!Xj 0tDpfBrp}q>$' ;%}8&l ž824;t<} [wF1OP0b &LÛPvҷ/O]5t*MLGMONR80OGK{:tx oD#D'c|KC&oĠb'&1.[F^Ѐ1Li0 ]_9a&LlM0|7f0< iL+jPeZAh8R >s=-OAɻ"}C耾ǍzM]M}yxā a8IC7d-"/!F3%‹~F. x mD9]7@O,6ȗʅK5Р4vEC<%/2Z>g.DQfJ8b8q?b*Ÿ%>ȒG$AO}s|+Na4Gwr#jC\cac 6b7{-˦E<07uJ?1YHCL+;0'0pA܊-aL>-laRe5I@;hJnw UNأtGk9;hv@FyܠhTe??Zp􎜢wg\9o.A,.Ijela/eR[nV:mYv4gD)Μ-S|=;[8#SjSR{|ؕs ˍ4VrV* 2_`:i>6|_H?ĄyS" y6_m>G  ;*rM$>…=ҠӴPxI \'ze %9{>}!V ?~db/UPb=_ڍ9GCK_٤KXMO}3cDd #8Ry}Rb;[-AA+iΒd`47G)v?2JJ40}~;Jno<oVݰ\ؙ~&Mm0[lmT|z2tprmXBR*CCR> - OnqMޠռAް6tcY-k7|)8%䩴?B!b}4=;ycqk8>'vuښlpZuki;{C[B3o`ry~ȣhC{>ϾT'чyvA]g> .Qϊi.,8w\Ġ^#yvt9H/(}ε.<9^y+t>e5&l{!m0@P-qZDsJq>ad0k}x Ciaqe1f|fT9SehAH@ +L@,)\ TKܣ` [Bys]TJx@YFj(I1bZz}M\9~'79-Ŭ)A)=H:uX͑kwsO9>k_~Z(u1zY_9TDž<]E?Җ-'tQy- n'}ϪNAŒ²r ,'6טp(Zfvf5&۰>L#apmK:pغ4qE2ώDlm)6qkj]P ~hD'a>(E8Lu񣇎Eqw}1C¦0ʃxk>,w1g=TZYRLCe+펟)ȚaFxE篛{+(X1+I7o"y% ED26ۅ0 |>]mTESa>_Ӻ[LEKa-Hl8}08>ሱSÙ&[*8 GWύ&t" Z8PJj'QSv{T#C`Wy'#BϞ[AP٩YowP8wɧ |bk@ JEQ .y|a^fMd JfMuG.,p7p#_)X<2siaĐ@ҝ.~ەDդ"&)PC.p8, nI$vGa3oJM[ɢxV4榁[Mp_`>4(~Ս\Y+ia.nlEF(HE0 Wױ)' +в)\fWzT"9a]NjDb%׷n[<'pjW9SE MOx'+EpT:#Dg0S~0%ֻgZ쳝_ c L3>.ZKΘ\Ÿ{GQqGI@\"IeHGjepc 9aAM8T!'D qa>1Eųd]Cw¶D|5e~X]/)k'`N89rQ*|u4ab]^ u0ש__+?>y.cy mϷn@39Pᴡ-`:B00đ#< sl0a4rVId*\ɓɣꕉɁWzeMdOi|!0@F9>u$zT s F Р! ҫ 6Tl+X1r;=%BʹS;مҐ$ ڜa[*T=>$wZ{u1L=O/c>q*]C0pVaT鷣[].4.Zҝ1( l0 ?dĔt,vgtLEbQ7S󌃶8&+zMOCX;+hU}ٖ> %gJ^߷t1oy} ܬyG-lu0Y%bQ['$Љݒx<ۣPo (nMUv>wg.kqjlC"S7}EPSj>"bJ"x$:XKu N+x'u/1S(6G^Rs 9+p-S|I OS4h V|7K;|H+wP1R燯BIiVX9egJH7I┝"I.>Z5v!kD?*Q-^6-uOU/փazQ}Ѣ?%Gi15?oSHR=AO_js>kZs-q{5ZUK7zDH1?mKq>FL>S+x rIRLmCr PVn@ +-@^]=[1wQQ"4Y;QẾ%C8¼qN=[`@8,}c<<$ZELjtвț 2}/JR*qGv|+xb}K`tJuq0pI[<<~Ê?njB먈Ԟ"E Gl }\\p*6JU[a3ܴI*nCAfNe4-а0An߂,W*1F B~&VB!S@DCAxLA Ac~Tq6FzM۬x1V)4Q(=3\v%}_߯Ra&FA %`,RF=?#'|44B'H_ܨͶ }ĴA EW+(}$kKвF^o! Nh~oFLom  e@T9F8]3_Ϻ9t(vj K4LEs`Hb0D*$DHHv/Bg$!c3F[#7Hqѫ/qE?T~[!T>$D+~^VF} ;ڭ(^3ԝ]IveLrqťLo3~~4?@]=Ӫ0KV%\Stz{5\Z:00'%aU06[hH2';QBb'P?kT۸2Е$?A*m̷dxfJNVĐ?f72.Ֆ!oidv!MSDK>RSF`|[v&A.;~W5!nilvP릚]L ^0Jճ7#44;ڐh v)+vd]՝lRzG*ҁÔwfT8k#\ #  z+Qp 8_)&}?,}1ӰrxZr(W4vwA3 WHf胨JC s~ 5LԼ/}&'|14 LJ r G_b/-:cWhGz6$\׵ۈthuMF\4FI+[g_*XYK2P"--gϴX8~.k"U'(o'[>+ϝBz+㦥}F -$CYgs#F%R UԩkU"ޕ%:Xbb vC ?-yqsHKmۄW aTMco!-HL{heHDD,6 =i;X[n [."ugUqk2-eG'=0÷Jl%ҿTҵ; []ڌ֯G#"!^|b2EyHI'戧eSgj*豝z9"[ Eq.KvZ{YFQlrƝR{0zPcյ- o1k+tkaS$3 ~ӱ1g 30ԻߌT%04ligGE(;19>[p׋>*tK(iF*mn,*%fa#GH{TGP?iP;ŘO FNhwp""ZW8eyƄL#XY2]r[@ܓ}Z̳*P«*\cqs(z|#7fr82uh^Gf1݈2#ma>sʝUYx Nf] 3ih 2=DA_ؕQߵ-Yxsfdn~+|mrOwFf c0~[`cIi$"+-I-mIs_) {Bic1FֆfHf6Bȝ ToŹlTO0PU+֎UJs8l\ǠXip-(m#ngG 9+cL: ;&seE[Zؒ~=Q*qGÁn1bl>vC떂kZ6ދ~(7H3'ts|ua>A6$bLȑ"SO eĐSާ)Jy3鬕ĵ}:Dp:AJ/Ny "|}Nv+17jGMxk<LW(]LD DG}xĂ*[zq1u?x`jؕOlZ~!>>ձN #ب}QoVэR%Q EPMfBHB邸'l sX甸Yo#"vUFIV9alKLodiNxNSv쮊j6ưbyeĹ'3=݊qH<[:1%P'~uLe^s ʒͼ\jRQזV!Pϰ*K)jt+jI+ڪ,o|<2:BeX1D6ځW\8C Å-,IsL_YfbkbG9Qx{"2ޏTgX¯,>G\1,W&rb~kn+}iqrqGJێThrY@{R8,/~0QݡG߇WKDWA5N4le#Zb'C8}kCH0Y7<#NPQⱎS" k 163ECH":x<7"+orݛ$ӟ+ȣF( iR7G7~K;L{鷴o_- gd‘p"FJr ,`FD-5]j pBQ,6{FRC#VGitCoùa77}^)ܻ} t> ''l[EVqoб>2PMOZ=~Sj $7j [IzC+WۋC>oRC[p3`aȈv$߿4R'M.'"Ȯ|n#̝?KfJگe1cƙ0PQ=O m0%B g3>'Y/Q6ęͬ3s|*1Rf F*\27Wo<'gyZc<䏎'3WYnB7ene.qfRu3 2y2 v.]x8-@(ek .>f=m9kƒg}#~3-{4s?;N6r}6"T86ܙ(SMo(%n⑝b]-7.*/txW?4fΩƓ~=x䮀.L@n* z^d˝лYPk >D~Js :!O$ɂqT|kӧWPlAއ`?gFIc(Rr=4̈>,ϭuD/ Ӟ"wE >XG T_!V"s'o /8VŘ:5݋9m__|Q. Y\Ɩ"@Ō3[QqNQ*"+ {ΦXtqHJtQ|CJlan+e!CtەQ\rYQ2p!|{ɉ>ST\|' "+8yĀc*.>Lsa!2?T~vM?! 1U)0kocMBe+YKy (^o&BLRe21mГ튐!7fb>`XBއq!!8M`q\aG1Mt&..Dт@xn/Gd^LHVY%Q?K{ Aq 9R7"B1I]%%/ziRc}_>7"D\x_ifxl4W I44[ G(rLjB)v6%TuɌ$=3Ě8Ѕf%|YB<[^B{{x-et_)O~%8xC ~J.7 L,0rֳ}4HUu.Tf"J,݂$ jj -.h VqvbO1~Oy^Ibid!it>)i1x\jMt0)>E484BU%Q 8̂Cȼ} 7VLp[#^R_rɜ/LI0OW#Vp&wf }>h+љLV]hc[@SMKJH6s1a0yCW?Cň&.Ԟx؅^OOFИP4xq &bVLOpV<&>3SҺb|=# wp͜kۭ\9.c>ѹO,34To[Y GJ Z>0qIj6N=lb6H*_uj5dwʸ-Nq}XDDǁJl2>_Y'8Gȸ!R/cK2GXoR)8Xc+=RA8F[u.m}<RvF p_򬏍, FI w XE\ pg15j%Iz4θmאAUبYuu4 ƽIʔigЕ0y㵦; :i-;A΀$ B8eX##[.(L95V‹n UN ί($AO8S:Uc8zT˘~౸{W6=_Gxi/G께?Zc7Nͳ.5FozCxeek?~Cф{ ym5V=(3GEX5r>Ǚ@\Փ(4)hJD%L_!~ FlbzKD@#U|t9`>*#D񡬌- bQ-;Kh|b1R^%,N9jޢuY/m\3"V^5Gl(iW"Jh,-^ YY]85௨M*/ƅZa3)F_Dj!DdYjs1+CވեXG;07ե2-|wJ^A" Qt'V 4都ۙUdrէ*ZW7>+6FդD^0ao[YvP_:_:#}mҵ#i1W>$>{5(ցV7_gKrǹ6oau5RaUHRز%i܎es3:ucK'7L_<XP=~Xu2˙8@tZzր_嬠(Y<Mk`㙦(N˸:įCN_ɣFcQɣ_7Us6QĂ؜pg:mu#wsr]_٠goֈ7AwVa Uv8c41q[>ڎz|h`Xijz>F G*!ZUHܗ3E/ECb[) TN1/k cd#l-Z9qmrT=sRn *YPeY4#iB!3h|ֹil_?(( G<5PJ*8. ?}Aj\c49b%xOs2ԯTEX>ZxǕ1 HU%bQ0ҙи/א,h÷gUHó5axuލke~+oHsoX2CZWݷWHx-DURR2>k҃Jlkǃ$>v!ܯԁ&bHA0qQvܛTZD RT%+hF{޷fDkFÉhp–""t«̿XNsg:ak'iS/ueƮ|ٵ{tV_vml#k$aq2ީ7C, ťSOLF.iµ#3":{nZMK{8h7 XE+0.|]sʸo#s㚁>1u;)ŷDk5^5p'0a>(N=xpG5h'|NuR~v "Λd9PE bE+mhԯ\i+,yB*]!W #(e.Fn}˧wi--)X"%ޤvŚZtBR'T{k"J!bs<,rU {XE)MV_ Kt=ri_w#g_^-S0 ORĮ#V yRU0oⓆ+}~$迼 @$IB_Z)WFA6='CB8ߨ k ]^> w tӷ~L^̪X>©Fu}_,[eBWapEa92( ^fI@% S2ሹs#R3ҷucr:dA.#aH$a3z H\ QH&U ;lslvv-ŀ;yExmRC9XӦń! Fii&1ԅUSނ"[]\ Y96]slĩw_Ypk|@yFZ[<~TǁbEB_yPaoil3?o|7(@O,4RnSmo` ;,bll~,VSZ0*j/k0ڙ9tˆl|_G -[^\ѝƹCsD;'tN+][+ubY;-Z?_:K-,'¨v?YCd˘__$"V ,82Q~G25>Qq%U+rWq+-ȹ)r [Q#A|ݬ4}m>da2B<)UD)!4WV׻J $q* &~(kL#l n#(/Mqd/-L{4ՙ6&jݟL{GECߐqrQVUcSUAԸچ#WT괉¯L}7TEKXZNcT0 zz:>]"򮧿p2b .dz WG Fx2T,+5#khZH#RF4"*4T[1"QHGׇYeؘVY>w`>UFS{YM"uUa':ͤ^{l/2狏jlm`>۰V))PgU/ p" 8D2EB 3|HY2̋q[b.SXaSgI-u(U]Lȍɟ[LSmcHoJpKT4Yxkj++@^ l,6Y̜qI-![BʞS.vKXG۰#BI/bK.YGwGxj@S[aKUl2 r$X!D0UoHsoVǡC}%cZ |ibʡA/ɿ mnQ^XKN|ؚ9gMݫQ`f%z1SY70̏a'XjkXr{s+)q^%Z5k"6+ժpQ>nVө>a {},Vo ʇ^^_zC#Q61ZִP&3mL̵C;0!.F&(i*4}tQE03ma7G Oo鈜S\S#thMX-u(FL=Q~ɸERƍʜ㜿Mּ[@aA$C Ư!ice5ٜ mY淭*[Víf5voCP- IQm.'A֯XR(dXJ,pyQj)Jp}UVt+_9M_=#eidQ{ JºuKFqkqRޱ.[dD`a]8ƣ-rv6m}Iزvpȝ=>}B8Ǝ4>[Gؙ6c\#ѳ.뵘砪.+eH;0_!2Ȃᾌ.۶WzIۖ$LGkLGL!EU RԑTxڷkdoW~1~!EY-M%[*-wKɱ0N篅7zzz10VDZr Ol3AoǕN=u7/l,c>:xqI9-℞S;EbזT+!V'raxa(VLyx>XuilxXN`^b11Y)I uQLJ(flf5A99cl/99g +}>.րel-:.KV'C4 㔅.]^y<0'\o'Lxk^z,w9mUCvKYvKak#~Jܮfu{Z<_B+}f|7( ڗ'C'2DX8=E06Aghz3->я'ŷt{S ܕCKM .B0a ]Xs#ktS{݃Q<:%9(BjS,)-1`+FJt EǛ)}T1C$aY# d:,rd:AFm9z!RD#eq s &qtdᗎܺ\M%qĶ4c{և"38`df8It4cZrgk3O;*ƜSx(!__Ėf -KnDhC!rij7~Ah9 !B\@ɀFj|{<"b'Gܔ*IZ갞 SHd\Wֈ A^(`?+7%!Iؿ}(|%8},dcy8k]rZvwc>15]_N A~9ƹ8_헓1Byrd\rMOIr/_扼/g7ԈS#s+KcAc]ڌ'?+E\SR2 *(0 *R`s)dPIsɟAk&X'DOv6:-/{"Ϭ8]4Nm5xYkD#A0` H+xt;8vPnpB/ zj"MDRV ,QxΌ5>O_8EscY/@|| {Nx\H %[>Pز` _;l9n!J]8b cIxbT7O'obH^&5Y}i+?GvC$cD6^l o>+n˘mMħnߗ Pm돿?~՟?Ͽ_)? WC4Qd/Oo??SYQs':?_n Cw\YϿO:󥑾>*}_XY1D-g,x;W^ endstream endobj 357 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 347 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-047.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 358 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 359 0 R>> /ExtGState << >>/ColorSpace << /sRGB 360 0 R >>>> /Length 113182 /Filter /FlateDecode >> stream xlI&M [ dZ6«630-nUe291?G_~/o_?G?u]~s?ǿQ~o}/sE/-?6x^zZao?UpƏ8g<\?>Ӯ~>ߒxY~.|6sW?Kq}plKxCσǃϲgן_~>OGL \p.…x~?;Im='qGO?K X[)%|0x'ۿC۞~*\ T-BhQ)w-x+w>1 \_/)K~=w?r!~YpK`X {"\^|8•7_s4(]8O`Z}z*|ߖyp{s?ݚg}fz}Cl?ӚܽskwU^!n^Lz3|tgޑ ׳Vg[~l-?ӄs=j\/}h}Ot|m۬o_?)h)f?o\h=>8#Ƈqi?8#ƛs~c<|z߯ۗy̿gzOY6xyqg5lO!+ňbn g=baoiH[Gh;Ly3_]׃!wW?{wʛ)'G=8fs}+G빡gcy P$fߡpʯ,.~_E<'ᶷw}vDž@;W~~9?3u^%JN{}?#3?Mw'DN|b/OÀq{<'!?b~΂w?azV_~?ny3^W~C#x+?K. \GMɻ;%o`nn>x=̇ԟq<P|p?)f'|?NcNO:}~HR{=Y\?p6s ]bC?xlsڣx{XXk} o81q~;;y>a9XnO7P> 8)ۈ=@}y,[vfؒmgyqF`~yc!ϯlfNy`G`mOSQi<&zG}!Xn?멯xc}З|Iũ@?Qr|ӃS_:6Էεt`WG3>Q' Ĝ_>mI}1~)Du؞aVڟ>J} 4?nO>k{QگN ĺN{H|HO~-9G]pzl/{^`uXF϶=o&_Nn:;;wuJ7Wc>B)'ր3Q`yp}q|XhOp7`)¹>kq{a}hAh~:wG]s.h؏˖'Xk8%>/[/w8c\=UlOIg% 'hkP>xY=IM_Ly`SPg5[۝/|?fo}~c,7߷=ka+F{h:ު||}z~}?Q>0q밧w7p///nox~Z{`c /(ܿcA/‡aAF7p8wozzoK'7kWȻb{Qί?+ʯoI;sXꃋ\<* M X  z?ZxW]A [dž7=v_md$|ר'hԿ71%^<܁5*DьI=v}K6=A<y!/[0b`Xd,U'Ԯ_㦡X8<)'0Ombz2T`tG?Poyx玺Ops}O?71G'~(?N\)_v)?҂ڍ0#p֐Ty{v㨚߳㙴SI iM,w ` mGP=-XϣS>i艧Ny!1Jo ۃ:cc#H<0,Y sw.szR4Sb|?1sRI'ԣ\Uߟio-f4?-Ԑ[ 1ݾŻScO ,S>bq#uύ5ޅi>o#uby$8?-y=0QxIJ'l^GbQ -qq1|?`&V{CG|x. #zz<8~Hzpq#c|[/-hAM\(߸#'p5nx&Vۀo OGI(Ꟊ#'- %a- G/=?=rg[ `o5!_h_׹0Pԭ?-ܯV~;XZW[-Ge\9cxÈ#ǃ?oyolo֧s?G33nJO'ibm`8΅EgE$wqmI0EsgUne1ѹv 6x'y`,G6?xy}nB2ԅF=N uQ5 [훜1M'B0N8![s|DRy"9D"DYG+hp>?|F߄qp h \]t }"`#쓜<|ߍ)OPoj;Vw( : i|1cd;m}qLk7Plq.ؑpP=4 |aB9~9OT>ZucĨ <^'-w`bҢEaZlZde4"N~^ߚzjgtLhiꡄa'{%tی18PU2Wțp%V }c>ڀiӞfΰE;-M1WF |⵿w{m寮.mqszq}*>[LA Op)i_pe m)?Fs;>61i'FqkO{'S#F;v2fKgϥ3,|3u;ʊ'ؔ0̚V.F)mF n N|;jiWGQBmE9JXG+<\"3>j3*`J@bMcڸw#l{yh̃ތٟ2wPp 1L<>&-=BOUV_y%Fb~} V6SiX{N2{NQϜۓR疜sSV>]:h#D,9sU%q7HMbd3W8t$Fګw X;gSOל{80"8SoFZpxy84ٟ ߟkr I}#{p?_b_L_3T>ih'EB^ot>97weZ~&-SI]hw$^73=e@t{jA[+`;M?~nnF1Tܒ)a;MKOǖFO,Gvs[^;crSdm یSDjǖ[YD_T8rܳ>Wu;{v)FO۪߈}Iq[Ӷ6]Ww`XWYgu=eC;ɋ7ƷNt qu|HxwYTd:n#1R;>;R8>U޿{[21/*!V [J]d: -(\d\bj߅7ã0b"V"C#^< =~]I;J򛒕]b`7=JIIQ=szctSr:c06t$yCDY&ڷ,a/Y_7=\Cc>o-.}0qӢ1+"nHFQ14m}zQfY?ԗ̍Lqʶu$7mJ6(ǭ+v,I<἟"i`<]3цN K8:8:ꣶ<͙7Ҷ"9#sZy ޯv h~L/svgTfuGqץ"?H0Frw3e3c~y=+#q FOgAa~[8V)C k%_)q.)'G}+ QP_[QŰ~W"y7OFڿSYw3iq$OΟ};?*#Sa;㝶(SљZݑZ._h_Μ! :D~H㸒iY3/5?G鶊Wey=Sֿ8gap2C}=˶_'O=Ow}22)5ց 4<&;FnXG`.su!'W>\܃1|8#u\awJf L]oXrlplL /f7kWc'`fT[revtdߜ-io}:cZ.לMmk.Z;ޘq0;5v2Ф_:ܴeϜMv5P_X3ޓ:G8XWVl=f\5o,~wcz(=}l=8٭p6k׳!`gԏe0M^HX c]Slo]#ǧ_OW mf`W:x"kGK%Ǐ3@b ĒRF4{ҒlY>/_.=Eu;9ݒ͏k+RZhȗ3Сؾl'?CD -vɌx@0xFC(w90X֐x  ~b?4'>yu i޾>jpzp<"vS6v=|1{yG݃o^|xvmaxg&Vl.!s3[[s#1#q#,>ٹYvpPO܍>O׫+2iiO?(˙Izֻ[h|;Cp~D)|xt(%? 9Jϝ pE^/ӳxpXg`kbA7ޭW^8,[o(94ytK~FYo|y2%^;Tb/xÁ>:7.x:'x cq\b%\|h5b?i_Χ@~R\G$_p+0}(1?͘X!V7?}n.xvo0a'=nx3B9?v\_;^p}GuFiN1vȇed{ϛ |:{TG &BDm!q)jꞨy|ddFU>X\HOyX`yQ,x3{Ge{beg[8Z~H4Y-'cgCb4ѾhwE>Lݝ;?] FvGW?y.K("|? n6b|mSxS8ډ1*`L|d]y8sdi&#班)_~_>OE?#>8cTKj0G?LyvσW[](0y$Ѿ׏?ʫ/no>?,ʟ~[u^O׾T`ʏ{H}[•j7_0^0,E#"!?;)|kQ^X8Ǽ2\ayv>J\w¡!UC,?$IƅQ'nW^eyFK]WAS,Ok\ [`Mׯ_8s_}㍿@{L._y~o?AS[ַkgѣv~+ xr\G~n>|5|zurƧ"/n~xg@&΢,ܿǦ>Oj{F(vt>8#_oomľ>p>3|Gްqw޶_Q^n3.(.>8Y*WRpЈ# W$&ˍc]FILJ}BaYQAm -PznX엯|p/QmG(X j'/ROs| E7Z~$H5#M'/2&_8b {C+f䫛Ff{㨇eP1ߌK*bƦbbcvS}}!JU Ƥ A2Y u*.}b_|78Qe` Ff3w~/18{Q.T  gIT?F=`pmPq`p`{C0E@s/bByت`OuKn7U5qhU0ȩBe,[$:ҧfy0}ʪf,2תFo\J˰ɈocXh fć,3zFbof`٭,)ilW <fo >|?0?-J3֛ʃ(ZU"c?g#漈 ['dzd &bAT1+*4X98ۊɧIa#!X'0z^]ocayAQ9~` ޏFbq8=Sx{?t;X8&2")\K9x}1]:0/y˫>,ry~s>?Ta{+9o0fMy۞Uf dܮq>0&מȸ9._MV*-f-#s[}>Yd\_}^{&6286~__FF3mO~߃q'kWVַ3f:۷0B6ٲBI5c5G>" shcAۏ3BNۗAD=6W~l¼_~31 x }Οp :_|jN׆ga9|@EwIؿ1q=? Cqxɾ' /&.>H+$O}u|*yc1nWGF?__?뿀YPX7O"}1wB?z~c}Xs/ _OO}/d| C&~^Q_~i~r}{1?F2w\oL0GbbE#_Hi=f0YocB9/JulM@s)r>7-4~|[;RE.?1?]~ u+8+W17k𼤜Ɗh@9/yOtW~U*'GɼPfg)#<^~䯛x0 7LF0J:iCZ(YoyAn yG>ugB폱|??X"dx!}DĺN{yzWUJztU(Q^'b>{xTuXagoUŧİo*y8/[vj)PA|*"v/W V1r7_-d[\Vw"-h#yTn;Ƴzl'Y%!y5y7+b{r1'wTO+L;Si=Ve/O?(lo7Ea7[IG뵟w:aOZ0I؂dn)Gצ&{[㵭a3VOyެL&ON?7VOs]YCi BGb쏽|?ߙ<5uYê#+诃*hfXĜ__1('V}wNV;~ߜoɅ|3UeL82~8i1>l/ Yhワ/زt3>a;߀a33õ>@˟@9ok=8.}Y·aEJtagxG, f|r4!'b.d<졝t1⅜/XAM\>o]yx#WA&_A:0r9d_aX? 1w(]o#qc|?߻<}kb|.YQ>χ9{|?Ǎ(כ홞 :^B`G'Luٖ'_oq JΏ||䉿gQ~l|g\yB޻>3ߗ66r3y/>ẎYB1}̿]a1zyAN5O|9K#g| 33tc?GS7/L4|>;Rr3~w:t3a;_3èO*ㅗ=s/S_o~gerfEw~)1?f}Qߓ!%}ꉤ|j 3^-K[|V<T/6,?kϷAϓ|U 8-C||Д׭99S_y^||Cig#n78O Kgj̧>?u1Gy' }3?;3ncjEqy;?sz|Go{oS)?IlgZ\_e3o̷I $X8χ)7|OVTt)M'ͧozd?`;wYj?z= ֛]}n}lȃ7??q|g{||Ƌo؏˓kH mK^uw ?*Ձ?-N\[WΟ+/XoW>ɟzd $ɧ!ô{;wݟ ϯDJ'GbG50bx=B _Q%syอs8J~7O~y}!u9$3-2qXԽ#|@|&G!:?V1O|ՇIa~*pq}x9^ C|.o's=[ X'?Nw%_z^oO&WXo6:yZxg=+G6:LG'Gu =_`Tڕ:_Ց{cҳípfP`1["y=a&IIG nyEG`jME*x $c&MNT$',4#gY0ug*R߫h2^8r{2rfIϷ$U123u+c2]u#S:Auªv"8f1Way)3Qj7&+WG2Wו׳ S _~%Ozq.Q=r6NbNpr4[k6ձ𕱈/87;W*\F_̥R9ڜVm.(չ'QŹsM\M\a8ePuesTd,P5u*E)Auo.N \u9(W`fI]obs ֪XQB G:[$Fcq>8!yg+C\Isk])#+\UuY&WƾZq,fM۾m0|4F$+@Z*(={ysFWfUW]Xn3a&ތ.Z_+QzՌpm9BÚu.`xz=T>TY_d VkH֯s0[2$7[gm 6gjoAoɺJZ t@u xOb69b({Ug3%nu>23?We^T]淒¡G}<0dUw,&t>/9Dao>S"iw3GX+Qv.A՜2q2{}pκRH; ^f`iܷ=3u"rNl,U8'x0&MMpb9B9-7A1VO<|d{ڹ-ތc:F:cfaVqYE( EuƝd;GQuY`ٔ`~U^)Mb\Go¼=*_q߬:YG=8Žv?8Hĕ- y{f\Zy뎋 8~ޝPʃn6x+5=w5n\;GxS\頮g;Njb:\9n:i(8UHoK l&,_KW7]_G7Xr qXqH|pzc\au|^U/!Z+ŝr8Μ=xN#e}OT̛3SPu<+|5)A.5scV9!h4BbΐafF,Xᚤ-EsLkPkW9Wq+X/&uycWo՜S.񉕻%޽o\C>83nrjoݓX%e+[xG&+\S76qv|~P~_[8~RsOVv.-,:7370" oDm))8uR/ƛ3̪E3]HSkF솉*zNgFͮ15(KtC[#z•kM:^Y52WP.ÝW2B8"F`F_v^wqV.rnыx}kr^x n-1~9qyC?s;b\jQ. s>˒%^Nh91girƧaj1@}9` Lj쒔(<[jU +W`T{zXan8I8 [Ө2XaǚnkSZF&e!)\Qӎ_v/ .zJ(\9Ǎ;_ҍW?U8$|裘r k<-5ЄxW']&\pU7l#v1ڏvQ&]~ol YuĈ|ל&s 2ktue$}F>Yb1f$F搪 ]!agǁ+ Gy1SIi7SOFfڍ4SJj̩98_Hxz²|_Hϣ]BU25k$K!#_ Ҋ}SK^IP2=@̨ܠ~xsx #r+:3NP f?GQefFXm‹A<ѣ[q3|w2T #+]43!hv:03ޠ3#wdp\[8C302DuL\I{F('B*W.}Axf4b_ƒ3vy|*qGyuW^V8,m]Xz [g *J۟ShKw־8 DjA &ē+^>oboM((8,w WI}P9[Q,#YG<^z>2J6畩[Cʬ5|#=of-bVfU-Y·j,t%(}M3.a|<ǁO͓nE]-B~wjxW~_βzb+3/r F8^ն55hxC/F^Q[;'QdP7.DI>:޵qqgm(N#ӝc;5Νm+:9lTSv̅Ht;l3oln&"ڨvxoްbD6ʠƖ.o x6նtD{8&}6%͖#Hxr^iܖ춢it_}?Pzg5썌& &ȝ;+5p:O-/_OñZñ^}o}Y|}%|Ĺ[9*wG TC4׃Pv^ss|6| ݦ# >y#X._uc98w^WM^O${{2;RzJ;ctg1X|Ph?4jeQGC]xZ1|(aG :>% ̇mNǠ>8?1w0S|Da 8O7|UvJbͷ~]o@b%m7y>sq*`UzޕǗ j㉥ke=mlZw 1wy z(Zi?6zp! Y\ߎDcYj7lx{ wU 04~9j?ʘ&~8?ȗt1sxz7nRHu֓~_x{ 77gzw>5eszg>|fIy בzS!Zw~]VUMW9I\'y둁>]/G~r;Q -"|sz:MXW9KgZ~V^~ߴnyY?Db\^op-i>s=]\UZv}sm-gk_9fT ,G=X^lT}iǒt֟U{y6Q+뻖fਾ4O~^o=\zɕ^-z%$c>Sؾd#5v´f5AoAb%;_|A(D@~q;O;/Go{W=!R4ԭ_!|d$HLBL郾މo^,4S86?[n~|ܾZ9jzA|a?9ބ\ς~#`! z0H_iǒqn-2'_[%p=x>~R~b:ۆG=ּ狂y5B)2{?'IU"tuZ)oVf3O2kȓBU0H`7S^52gN'5&Fʫ-j5 Ґm>+q ?ߊu[W$V9Zyw ־Y ݨ5}^9^7˶.70#Fx-NgmNZui2g9@ c|9YFiX't"EP:QgTTj ~y(ь ~!eǡ]Q!&c}xpaW]7֩;*CWGl Ge} v%xu4z YHoA^ ʶȊLi>7Ty*ywbz*^:ҫŨ,{O07R^9]8*B+l{5پh4+-{Ta[MLf[޸^t6UP~JE+bbƹ[1,Y,tnZ$^EPK|H]BY˺EYyNYRwxxV\[rC7Qֲ ^͂ז=Co'7=.Kv_4r9[!EWTŻ9cVi11sYJ)X،~ަc&9֊d/|vZ4O {{-6eg0~Z4nj!NY,1'׸+P2/3мh)i/cPۛΜ 2OJWf>܌l`nGP"L3²,IhPBLU, Nl}!ǽ^?dp*Vay ',&m~WsSz,EE|ϴxug%r7ceQ?UQ{+]18A8S`RY>a5kTs11J;eлunj.@0P0 7pU2.J\E\l:Ye,UU>SW4,տ/|7C $/ƲZ2/hsM|(5#6 횊QEtEUUh{ RI~̋Y:cnt_j<\Kac4XC<#d@iT#1nJ74t앋&#/'IlSLZCqSl/,ͮ|Ȕ?c1ޞ1Et}X;Z§-ڗVY>ӓƻwj ֺx6zq.Q~[Tr4iaF3x0vNmMՂ}w>q|[-\˕{rjNˡ齿yUWbzU3b:7l'FrMH_f3D^:ɳw(cr#1EsNc;5Boy2Gs$ ϋqg=Fs74-3& R;,g *Q 1nK`̦u;1wOV'f}XbOLZ^_:AA6va 2wMZ{wMaHC dK'g]:1 nb;~@FՐ.7 4nnfrAr,@2ԀUpM3n.$o P\?07N F$c\n O'L (Q\5yrxf5s.w}ڃ1G>~kX2Ck(\c瀫C1B:_bmzARbY'~ujPq|85ʪ5%?s$*ujpL9-[C^F u_Bfs<=d%x1c0)'X-1{K7!U8&=TuSHN U"R ,q틞VuJsjǾy'Y~P[~S ozr)] rj[-<wYaZٝwa2%Nٵuf4ts+uޥgufvsu><+w˧w?_z#=fɈk!B _=~vKgf^؃7Tg^Qeu;?xQ/^_O=rz]d\b|H.oQ\WndDZi%iZn86]qzgEWh,wn֣<" b]ӨG12"~Z=k0 ?^ܿO+std,s0w]Ks$0v}ps@:r!eVu[9cVM5>=<܏*?#P8=W񯪭8| צ &\۞0+ oT'2r[͜F{7q,RLM݌-̫Ę^,ۃsrGy(hN{^#̼+SYꈾV\y.Kw~}a죏%\}a-fOA~obqڦ8hMٶ)6J뭼qz;O;Ȍl8)i_\Ivs̋m5ETn9L\m*Hޗf_Z|_Եr~-\W1so )qJ[ԧ|Juv|iͻ/qaNC7s?<~Z@{W37t'Fsj_iFf.jTMsolډpz|>`ps>ioM7sftKukfGS^c`^?ؾawVvIpFeWO^C1m;Rۮ|"錳0ו4_p}nHAʨ8pcs}׉0A&6'.>zMՇ>V>~1WRWK4G>vPz,`$Y `N@$܅sVqny&s5$1:!TQʴ#s>/w֓?o1Ν$ybdn0<<1BW(q \AR!W77g\h3_Egh(נ@5@\g{]g^3 (̊JĜh wb _xጬ,'Lq k8]OtqY@k{(h6aE^nUD@GcOTq>(2.<|=/S'f-iG6 5'@M{m6(O?s6TO5h"[cDEn/m ,AM>yik6x<W`ūӪ=]aMד/GƔ9~Ws=1Vq C~dX׽*;OoWAU3\6)&z!cZ,ۜSG{2_2+ Ͽqw!yS5?KI-Y".g B֡(b/,q \Hp#z`e-j@o6o~Vaװ{#sͮXNVe.~^hQFUo?/kOA$QSupTwUiLW4i)WSXT>{U x=0*d:S^f'h5ٿd`U hg+@&uz׻K]8yQxǎp~|ӪȌ_܂[]\lK5oT Ѫ0$vOc34T)_5i!FVi |}rZ~Cmّd~?]~^(ƻ#|3Q!FV|&>|[;r1Gb8?f1fFrnbqw3U[box<_ȖL#o]$>Թh׏r 򓘿svZRb̾g4-Kt5 ̙ J`o=3U ^?1G)}*9b[W>箰7buJGݥ8gw6y:smݧ&ώ6UwlE9G.`YBFMc-S ֶWe68XTPƍO󙶥N~EĭP)+'<ívZR2})Zm'@#UWI36Pn/ĪMȩbIPc̵~{w[@.zm5łJS?|JU^!W?ӵ@zaٿ`z itZ)%'u8kzl?ezd!$˅8ŷY0(mx.O:eǡD|ﶃɒww9#L)glc͜a|&ӧmEcv?@pĩE2l̙aVsq)s8bq|ʓD 2$6*y|8By8<|y># %W>p +7n5 |r_ꐃ #.2)z(brP+E:dئcHSV$A"eEX__|#(sD926d\[8 :,GqWdlps^œ[ir#vD9}Vyp}ʱ WkcFh,3Q!ӗ g| -"2?Ro:7UUdd< 5(9BAD3Ur'EC[,6 Ow`?LkͦZ8>̤qeyMųA?OuZNU$#oCϔES:XaO3P0VefYTTt:|ާufu/|"˘>.k+&N36ŵnEHĔ3YgWdH-:KlW2ѣHâ> )c/KiuNoV6mBk_J֌&e )B,Q-k#zp7s9R5X<6 ˪=IM#8Bۍ"ҩ+1*8%@}cJ&VFuB^ϪNyS>~1dx63Bc5ɓ+N{==HBvɃY{M.tkB<x86z2 K5)4rnARW;sge].+et_"xgw0-" a~ߚ1`+<Z,RHXhAs`lgh /|lءvW =\]ɧZ+M`wt;p/ox3 |T~Jl{޾2wiMTOq;AA|Mq?GM:bT&Dl4W< cȥq+.a٥<%,?3\=ZQ}~ ㏻4'&NY[8gYe/gFؔricbTrT5DAsB̬9!ޢJ90魙R=ǵظy?b(+O+NE]ޗ-ku̗:CR V?͡AсKAdxLHRp4ˌ7m1X ;sr}90!Uh;BgRFq%RC7J56є#FqcMyOci%3lEGY&Z!ˣ7 |KϿ|~a\0Moo)d}8eDеnx0S\(1`A卫 H.S"u8.yTK DlTD"DweNIsN3vKxɚ.KZbF`G? פFؗ@}K91?lpz6"I)+)=~//>-W{ XWzx>Q?zPvi紞j:od߅Ͽ%WOx{=?ӳrw[3KSr7ɍ~r(*̟_&phJ9yK,>{LlT(o7 >w+>Sཨ.Ƿa`80"# Ȳ|Y;i~M#F}Te9>7xѐB=U/4[p<_Gvv2y8_mGäHSC~nAdp22ȪRM4reTuP_AS|>_&z|)+k"דx]糩0>)'g.?yL0K#滏;3 J9h/i#T)?.\TY' ~&\`bōギ[p`)낸jI4e$@4 OԐ|Lł IG ]A'vj{" ,QM\HE܂ F:D,Cc"'DNA]ɔ 'Q5.;C/jhn~nz\&)<Z``S;@XIy|p|FsrL!ĭYߕ51c9}2 ^fla*egAeKAE۾(@CiR"ns>i}t< K\ ~c~c$ sxw̧a{.}A&hR(Lޖ"XŸW ' )Ӟ(߆sdʷuXB gyKj΍"fȾ-Fi:Bx1i<},Gik,',G ɦ&)~`|gg` ^b6(_{;?/2) .RA=@)_"b27]o Vr6>fc8&8珛Ivh_) "LH!qDN'V) Lߡ?`0o]/%FBDrBK,O'DXGlJ[L p.LHM˵N5䅐^<oX&-#Ք~e͟܏5c{=Zw/CnӞ9ܜ `~"iҜF;*5c<ۭ>ZM>1ݤ>aQ"L)1Ož~hIr̪rxI {'ա 堬I{wxڣ$ )`ڀ2|dSfI|7 xTr\{lmϥ}}_ ۟i?SRBP Gt>%w W6xAVܖo|ZޯۿBUjz$Rf< @!AANXJ['*`:oPiu_+̀DTb~6peo_݈7,oŽ`e<#?}14qO_?4ˈm_ 6)'_70(QJq^ ݲ}x?%7GWGC6)hSB mb׆3V5FֵM>PhH^=B?)oJd#> YXy4~hoz<2Tln!XmYdSr09U9iIqOuY2dh|k<\pUO(L2Wzr.#-)G3wT%sc9Wmk~d}ahrnLΚ{2ORf2Zq!˝=J hs>\| Mgy?$sF&GlK%ȳ r|?8Œʄ{S<<^_ wJ19z|>εߟ͜ݞ +o&?<{4'*H950wD%Q -L02g0v$s G&ze:s\2ǛƘ|LE7908dLAxnoiҙۿNkB0*X`C& +s|l@ٝL^X 6A{ye9s^cS|3 W Z7y!w#ݭ?,,|gy+b|2 [}( /ȼ7VerhDI9wbu3)/%3{jOSF=إ)\ϫqGVSA'_Qwu M' |wؔs|Jz^:"h?Xv2WU*HƪKZ·oS&NA _x[uTMُد+dD9ۓ`m>ቍ!}oWSL^I'~ o02P/5sqL+Qpփޗ`m.Y|*6C~JNI{g]}r<=R.wИM}1-ױ:+2aL๭O}Nh> p/9X\1/4QpNRS_hfoY[ޏ1~W n@b_76O^?{6+/ܣ u5|@M1KeCpX RLg;hGT.y0'>\t'k/v۫l&2ǫws2y?\X %vBEWOq=*nfǰOyKJh~6VcؔťJ]MLXtv,ęFdu2ѓׅ#q)YPs1gp Y7g!ϜCgql)ҿ)ZEGxILta>hRVMrRfp}qkrL3p8:Yz `lɍ 2D m65Xд6_jI+g'${)7Y%fo:礮ǨӵG2WaFid(ިyWxBFFUN tD\ :>|2N-Orw\:A}В.}eЭ@sre0\qul >,ؗ8\I6ɨ2vx4"ܩ|)AGX7a}ui,TAl΢4W"y9=@8X^ (>!=+]JWwƠ bY,jK )7͙"0A[gqN.B%Vh~o^; b7Cb˶٪)X0Zs<+}ucz{wnݧ-zp9;b3ZXZlgSZl[鍙0ԿS`Du/qwXVWJYduz=;IOn)*apҠy,:ף .X fbt{]ׯozznzCTE YX1U2jFFlp/>"f3ܐbJ,aQ=G9kxMETn9u2-dn84Ft'~,&=!2f̰ɦ B7uZ&^ q)wAqAy-e9 Lw<'`zkA^% [oD0tBj8Brx/ws&5dzC_,^EDv7@o0XԵ -;(Wܘn SEkA0yg1訲H3=lm/a]Lev <;FOIm0m4c'0uQ$6Lϯ,[>H}HD'V&e̹榎Aab 2,BT#ÌbBamhD.0YHÅa1nB8-S.su.N'xMÌFZx[XEoF;SmxŐ/vEn*M9Wj/_.Zb7`[̑WXŰBUCeW C*c] zO10w(cI\C7ܫ{|]9ǔ7aN}]x[@9ǚ TY^} ;KUԙ"Z=*juKslUo0|HUݘe^yވc`K"D[h[q'斞xJUAwg2?6gO8[y6G0̮u!oFӳS!RFه2W#IMEUy`g`CYq'-lN\!r< }g&A"er ϯ#PIl;BLGv_<ܡ秧T@#ސD(IT y2 YPrY b;=W ߰:fI2:Hzgs\51F,`zar6a ir>4뛬`"ܿ%6oD6G_0[-(_6tEFr{\#g }ޜUStyBHWȝ oT.37|Y,: Iw׵,̨p\yNGJBÈKZSrqF*/QcW6e%3_z_is9"Ͻ=QBɸ ޗs\UI=m06??9!ΔUIY%pQL^_$G OAx&wZn$c R^xgfۤQ]kn^8xܙ6r]'. \:ʅ?Ǎ 3*eMjWp! ZU:\8C'j{4p]8qdLSǯ~A\>ewBȢ'r&]~j|Ý?[\G{mT~_mKlHe"|WX٦O@1o\ǖ|/5v9n ʟjj '~iaTxRkġGӅMe){tC4KZr<[1k*K!E0 3]Z| Wf}[3W,Mڤ)6- ~棙dzaiC4䖛 E'EZL45#tH Ьn@*ͦJfwzi4؁]i>5?]<Gts6}!q;` yӊC/eV"#<aȆR+T"ߥ\Kpa&Aݓ6khZ nf$xM !EJg^ @wjO#I;K ,b_'i_wn^HUlOO|(y}hUdaP9'OJ}GS_:{T8uk^_6:RI.₨N`B&BU7O{ ZnfûIa3^UbUg7#9ۧoDo?ln[fͻ-'\n. CRN4N0OaeNhp "O!-ş3ve\OCEc>:?']U&x1Z'|av[fYX7ʯEcH1o9{a^`ܘ[ P0\RU('8ʱ g1<"ӄ3cn pԗV`i[@UFER/x\ N}ۡEVTS`bۉUTYMomٚu5 uXnvz f-POk~ffŧqQ i3H4z/9=+`2(FYwɸre*/v#>Uk)VUa29(Pflw9 ka_BM:N~{ay}$\ws\ fo85N*[u>&J\Π@r:%Wh᝗W^.Qf+l;RzQJl}o]XV3jj]ĘP:$3} ;SHWǠ2 V9奚N=[+)bxW6$-*h(Ŧ* _ y禎LIx3_Әxˉݱ6Ry5]6`-QjLfzљ+6 io40U}/eByRHxx`ck9 =Ǻi2Rg.#H@a 3Q(j~3LE](+d!LC=ڙtI(7zt`#LGuϓF8dQnKm^[h?o40aT2&#B(9r_<ꏔr6:0hltp)1 ˿kL"%5lԊ2K᧼|QȎߊ(|GQZ֭6+mEɼJܔF{|˔a$Ʌ2UyY<>8$LaTP {ʿ=:4A{< cq>_z-ȫ|~_]KY [ 7>|rOwj-;q)c>_cy;15g\I֒9>~O昼? cL1?x(ǯ'=Ie /=},|OuJn|*d۶XjByĔBn`rvh.^J9'X*] jSz[)i,|l~G6Jd=)lD@χ y_A<*,ϟleHV4SqݪC"[y* y}Yq0~_$t$Pezÿ+ʍ",/O2i5OMGrAy|~ߏN4gYyA( *5,~(ʿݚ '.'y|SnsHR>_`|@o5c!z%x2{]nM^?k>cx՟lriIsKs%r?֖L{wg%xa-w>ךXAis~@&Yo}·-~dE)9}U>]xBc s\}Hs/M}^0'_Yߡ8A}/&l&$LndrbAiHCεߜl]7nʄ%eiFuU\wܲI>IN/eMM~xq>~}=O8^:^C 1G^O*loQQastSs11~->w5#.ӞU?kVzFr}h?c C$N:^ړ{D)1u%p-3>:<2tt~rlo8@19B8 )`xʀquFP M6~uKS~@ 1)|6H69~I3Uor~?c2~o([rqߐL?|)Dz^R"j5nUCys pzR9.71[W,yZ. I=,J x+ޱFiyA1_둘^po~a+?:dWig^C+_AiwJha;пm `J3$VC_ǣoBKɞu(vW}f{#ٚێ$ duQ`s7SSߔ rj?1S_/B`'OG7Vߗ*@r^Wu;uFPx7( {\oh;XZ}_ſ WApPq+e?S_ԂG͔/ J K[Հg(;+$VO?V%)SQ=dS4< =Er(~Joqp`~:wjrQ=W<,Xt?Sqkj :XL-Os<\~ʃ<9JPkIy(Y,}8HLQf|~e}۟jh;_#ǫ1|97:^q|Ǜ{5ǃ0zx ߟVݏI~ Ϗ?U߯S'*!R>xz\//ο/~0'|ؐ?S׫P͜0#/+/Me| ?'+A慔5R2V7qןrO_ߞI^߻z=6jC_<[[k`&FkAa|Tޘ k`>í b>Sm[~<"e?`S)SgʹKըD1ecF ېGGRIrW5tߧdċY`L\S>HGp]Lygr $`4Rz13b2#<6 Lʩhc 3U<ג糍$}6cT{?}Ӛ>{}@ubͻ\9)#y^C1/1<0h1=o0f=8 h+rLYԢo. G c3fM^{yɧ 4^Z>s9YCp=}t@RD-N4/tf WgI/s8rɯ}dpɁ}Smcms??a.ZF,h1R϶O>BwdoO}? X<>uOlocQ\lٙ̃l9dW~aNQ=l >]$y/9>da~l}ܟ$:)Pgt*}_V!rm;e76ڗ={v<@?7%#ϡ}%ʔg\P-iO waLi(| *QC=O԰=*o'buS#%: ZF~;43ϋ1=<65y0ǣ2Ap x1^3くڨTw>risn@y8|1c1ag.) J)#`n(oU.3e'hCt)o1Bʛ2F.nQy2Uy\#St1!Y|"H[79gR g㌗G[$qqtܰ/yi m޸boֶʾ/;W9 /ED+Ѭl܍N%XGȢQ_]U}^>._s nO/9Nۊ4&h,0dKr͹?ދۥ|GYcMc6k><. L5^T#rc>$4U=QO'1\Cc_oxu{a5lC~/l39[~ޜS1no}3L.yݘOwΨ%As8U8GMNsƩrgqD^哷Ƃq*bV7+T\>wP L-+ uaFE%y[{ޡ]xD0yܜK=.z:6v=r^SWd.LR^[q!߭xU@5l(rw1EcG5se [5)nQYTl=yX^-w(/KK{IZNڼ:rRgP/nw3e26קyϭsRuc&oY#~dn漆澿Sf`ߗaעVX[:|~!jı;ΰ` caժ0 /d (8Ӵ*lU(֭ }w=1y:0?gߋ [ñqf2c Ӝ7^KYvWǍ\+,?C0e۔u_%]ƞE=/G _t8csn>Ƨsw$IޕΏ F?u_y0FPM~{n.4y,onq!B2RVMp~ ?ƛ5e&SXI폰ի,c|/8 oflKv)WkoOb&?Sb[ u&}n`+^s"CݤR^\)֌ 6ư38mrbxFEe8^ʦ2X2~ډp"Ƌfwbq3}Z{Zɪ+z"%P`m6s-]g̾潮ָ;c֌=eO7f)㍵`pi˥ADw1y.#bx_ƹκ7kq< ׽nbݵ#*./so-~kZ3־vcmZx(/硘aqΩ'f8*o`!`kZw`ǽߧXm }AŒߏ3k e!ѯz9ǔ1~kmx,ޗ󱞗h|[9"_~>Zv@0㫅[J]=r߭q/w'JY]r1g$_3q·6mz$u~TtmW}|Mث)Xキޣ߼.^\>{sgOI٪i|Abzs\ :F0lU+"v7̨&;R~ e[~"[hWk]]S>mث8lp)rD[*穐f*-r2ɷ7媁9w9pƯiAemDo+˃8Lnz'erܸHQO|>wx8D3qfd;HG-q3>蠘 [4Gxljxa|H*(٠6hqp /F9׷ϓ?LxkpS6C5xkmrP)v}<0y~x64C=RwՍ u;rq 0rٶu7w|!ܧ}^^*ޞϼ%]Lx-uსS]q3[\qל8ߓ?r`P<)kgmv@]|+y{ʤt= 먥|Cv)񮥾-Z>2s 12yY9/⭫k:) ?_<\Cp4j~qE\rۭ]7 k5oyx,:e<Aึ}Hm]^ō)߈KyY?I߻zQ'߂Q{{˂'e]g7ڗ6qSS>0u8UAuE[{~ϋ*!ox6cy_;yu,/l$u'STk :++q6ebg 6)7}fy#Cz4%QدvuPTHy>^\Ys9_=WΏyCp7s<||~rDٷ߇/uA㩔wgېӽ k* :N܏9F񽮼!Wxc ԟk(ϱ> ?x|xDƀr= )7X韴F?R 7aBQ\}@Owq|Hr*ѾǏ_CE|<߱p u^2^&5?o~ ϝ-Z?[r^ˊxCzo@=R?E}q_bq?)@yvJS'όz;Ւlx,/VN]}uEz,լrs>͗_j/ ڗxx ޭ櫷{}֏2^1&kR]( eΖ@E uM|e{XrTR!^r*_ ^#Y/69._ =5?p(q7IxZT,'8XT9X8ieW%NH)Q= \w.婞 syڕb:xR|b~%Wߏfϯj8xJ0*k.\Ust qUrEȟzO* COG*1 ĂƣC|b9d/+a xpL%w-8AcN=.قckyj-WVwmb}N+sRsr\9)/'1?ı0WYR?gysw6UG9J<)PYsRuGyeqF"<7+[a^٣ƫ.rz+V<3'\/Q٪$ucT󋸕#J>i~)ŚHj\ "w=+O8H]?QR~ Ok~D<_u<6Rx[n竎'ŹGCS{A>ƅ-1z=\?XW뒿zveػ_w\ 9~\'e| ִ7YAR5p;wnbϸ⢼x"'|Vd}7ٓ4rrx[H|){1O9׸_}|̞U/Iگ8%ׇsc]Trv?Os}V֋7j s>9`Gpo>cNXx[0 sZp~k=̡XXW1@'F' iqد] \X񟉣XgSb9{T0q|>|n<zOK1{ *KnVzָPp|뿙W?H{׹?^>gNk7pngG9?_޿YΏPo=b=,~/? 8^]7?|7u__(_?ͿSoχ$Ӽq`܏ŞG_Ⱦi/3XҬO q~rh-lOW< q7Ev毁Wǽ 0r mS9&:Q]S#z4b 7gG{hPOпs'|,̧v3;9\1O~BƯMǞ?7{b~;֦ve;o9{1_!fn|M|)WG򇉗DW9q:{3V0Ǯɷ寣:kn |ki%6Ln/f?I:zVUxI=%~ozj>){|~S[wpL5?Wo0f\Ux"Z볊Mno+y3q/U7^׺3CX>yQx!{Dr:Ɲ۲p]Ȁmi{6~l,ַ;Dh lucq|,ϗLdɅƃ\Y-}ܤz[=9Q%㝲-#9ީ1Yr:fB39YߨN?7_uuz>U?{1 w{Ezb]о +s׮!}8_XA/t0`9Dfa@k||ҟzzX5~z NWOPY9P)#:>eN}֟*lv%~PO=Eݗ%$kUP(} 7K\G캮,Z8M @ߧ_aܯRP$"]Y+ݳ܌z>~^-oϧI/?Ch)W5V6k1^O1x^ s,^xO|__~e^h?f|>~hd݈z/ qN /<0-Eu="~o{{ci~c֍i0f"7LP>pO(?g5?=T{,u?xqC3$+{xe4z/4O&mDy jzĈ d~/$W~z?:葙t =eί/8OyU7H2| ++~\krVa W'6ajCQe/9(+| "y<O_@C|6 pKzB |4'xðg%C2+^mxp~#T k_x&CI d\/G`fn۠/7~.} ?[nc ~`?~i,inûGɅ:zc{r~>K`c> _|_qO\`r>~a>?qǗ^sx<|Fq߲>|zҐ9cؗ+.\%?gIk'u<0?6W@$-}~AY|߬?#Z]o;Pv?Ϧ>4_<,soz_'k6#8Vj~/Ο~=?8s??O>߿#_ l8 A|/\~?l_p_J_h<x xusl\RgXck<.|HUzOJZwC6mKqWz>׽={7^:CEu=5Ƴ?lD(tۨOs}ki'-q(=T>q~wO뻎7J{o>= H3zAuƏ~+Nn^mۿ5?#=Yo:gգq>;9M|h<}:?2Qwzo;CǣCSQx#~-z_ -pxcYO9? e֏'I}W}{$f=YoOav>s>{۲iǍzn}Vx+Wa}a'!qY՞>~zR UoXo|~?Am=֯w YϏ{~_?*L̺߳o<3W_rT|byċďJn'/~Q|mK_ {`<|5 7[n}{o ~t\3}S| }E# ?W&~@}IaTβ~sXW qg~!q~;'<. !i5O"?t00bz=F ϒ3=k'mi=.T,}Y{9^yP+ѫa`VXC'>$|c%H^:n[Rȝ+nk]!_9uEW<k :bo0K,qrd`}<ª_`/z'<?ƎJ~؛:W~b1VlPZ&vF˽ 6r]{+W#}CdxuEqYofp6Kκ0.>Kpu]Fgvn#}^]_|8ߙWuU /u>BypZdס`N5u5!]6ƚC^k_18.({]p)>N sr9㵦c.}+k0$W7'\uY?zz5;ug/?dfງ$0%TW݇&S+Lw L゙3fޒT݃\CB ;kUq @uOĮ22,@*)c0{Hk½I}C\w>CvmZzĽCs}cM(<.I,e kýB"wxv-hߐ_`HBJ3w"Gu"{n~SFQ?(/]#0dMQ?3-/ğ Q,_XX!~^zG%~|t 12w Uw%Y.?%L[_~cqo+g ]TT}MPSP}s%:CKyALUw /%̴=4F?6'KO?|c~Ganǫ\.HAs-P 7$w)ǵ@5׆iPXvy|\X>nŵ= |N?Uև^~zs_sc"?  ٖxT7Lm7K4|\Ѹe&}fǗSg<{5ϻƇwi/d+&6KW,;+x5ǛܚoM< oB);a|c^7琈79?g&>!ߤMߏt& wS7Ƹߚ!u$O}.}Lֳ{|^ FFQ17'ָ.fC.n.nH O50l;~vz=;met?8\ۇu߀ϣ}<}>[>3μ4Ə^ZOo's]=♶x&6w/x<=|x'Լ'Q^o7;w=/w|q?0u> ˇ㷍gz h o0ęno)X&̹9]Af^F&N:fΓOw y(pAcLgl~ 9{G7zpQM<>hX≽oZ;<ᔏ$oEzSv?Cmi-vmC\~c~y+;ɶ~\%Xɵ}67̕ckƵ%qL=E$O13{p%zf}6Q?AߺL>DjR,Kّ.;S&_ĜRwK=; q)y+_0!|/䕾E3ߤj,jJFz vC]0dws!9 GNy뱦I7Oɝ>1,vΧa5Vy7ߛ]5{sy4\s׿Crߚ@7Ah2w>anaɓ؏ lJnLWlS 4;k?\+̢ugɘ/[d%OR2tb"?Ǜ&Fc=|y>yG5ȬTZ=I`jήj.:{fq-sNcm{.73~/m¦F}< Եglums尭ieQJ-smowx *@kmy;Xױ8ǎz# z%|w쒜֋d._p7?YԵ{7q,OZQtnSkt6/9v![/[ߕ<ȿ˵zķV**I\5Nh1Pw p2(}y!k69L,zQC1 OpQ`8;9`'kHU#)rͪ!.y5)/ _9'Iɨ]q)/pL";9HYûqr>S?m?8Eyy˚#V5J"LN hB95BO?AY#b'f:zoz^qP}ك*2@N>Ch5 oy9x>{?NfW'gqɋk^O^o{|5]5) 6I =tT\كQwuo|x [M璃\吳\~yzA&:^ o^K5"CXgzd@gOZ\a-4[9H΄m#,5 {RoПd+5Bu}hWom }{q5j|=QE,Ôy?dT OX0%&'.9 ws/7kUSY GqkʩcfT,o”C>܏Hj;9Q|,s!|Ys%Wl0}{?dlC݉ˣNsookViTc$q/){Ql;cOvO,!+٧皗/7:?]'+v,yq6#=0e~8v6uOVi?كqU=yij= )v;j~J^ԷaruuN2m(k|`ߠk`_k Ǖ0Ǡg y%㎰lK(Jz;*\5ZpQNK[>}$J<)3NrD5w%2߁~¡vORo Ӊwts$:&?a:IYҽK^7/Aa/#_' Oe}سD?_ypUBR=A9bƅq/~XyQOV%ޥ,>[#m'$^?f=~>ٍm| i~f;֛tP swz쾾|Xޗ1c| MW2GQ_#]wE>Y w&_?ccg?ѿj&F>m1Gg| 1&B?Ch+N?/ؿx;[w۸f>ށA?BK'4>ݯs^U/a㜜K|D!nGOVƿ|o.Q ~ʇ<;w5/er!>ۼdkOĪDklFy|ng c揚$:}Q3e[\h.C'#mm?YsMuwɃ|WuPCO {_Nϟ[z2{6a_Ku#>KRş^j~~)ϯ_]R,WnzTW~qɇ/Ж'_J}טd/OʶYRmKItApRWQP? q/{+'wR+Emʷ8;:F?ǧb~߷b;}}X_Ib%7_۳*TE"읠~5;?wk`? Wk:\3 ~뺉%{eٛO5 XhW}}}w ۻaj?=%X%k<7:ʯ=^w׾0лaw?_oOE= >fl߂5$|duٿ`ʞHm˵9o5>_f}_Gʓ|ezGD1^8ΐ_Dmox]amWY{km9emz O z02?}xTkLZMkt6m{0{@显^zq>z1s%9Ϋ aΫz}=z81*59Gg.c^ŴE8gh_XcgC~+wɏ~n.4b+Fp c1:Fa=ԧ}+'И/J +e)8 ϓy"T5 :nY0VC燱8iFt͓˵r#/Y\W32[]5ctn1a?ߚ'_i:X [/luj/-@errX ɧ6GVSP}~3+߂=ҏpl~eGl,c#m}ɏゴ{6dw]3~׫m{o<跑oGK;pΎN=oK{A=:xw~H~xbMد;?VJc~5d|%sؐis>&'{0gxS{xx|k^NslNN6_-e<+k^y)I59K}s\62nV|*l1&GU.Eqa<4~v\s{ý7rRsm,+Z-2Sn͙C(;yl?bcyv>͜dxxqϘN/c8!\}(3˞8oxsb4Le9>*!~U,e}r͵!\0| ,ݍ5v}@}C~c9OKk 9<%Yx1#NrdO07J:;OəWK#= Maޢd`R%˵h.(8ָ7W;Vdp<%?^=B =WJ5( B%$w\S2竑8/<6Yo||9iC <1ylTLr mΓ Iyyj#jryL4Ac }8xf` ԰FnΏ6q rzQ>Lsp6 b yyv}pJ`^ɾR>|2Olʾ~Gy<}$;&kDξ<yZI\p-dd>)-*itqE;|>?O2L[iƬ{N]~y4 w>&}VMWotӼ19t_ pp{wGRA^kRw9t< ʓt`F5%#>z5^U}ka̗@ٽ_tΡn^z`fWh`}3: s^W iN>GwwwV5z<73oˆ8q:@!oh'S'ΰoo}Θd7Qđ'h0֏/tuWwA㋳<Æ%NB:/ 1ԁq.|}{c~?x}OVs!s|?xԇ`M~?s5Su?d$w{`5@2rr^|cBh_䊩` 0OzC`0o{~>ȞYDb>}|F~O`}8oz3@x 3^Ex|{hOΆ!Έ˟%ZZKedL_oƄhǘ]'} s.l`Y?xX]rw=z[+xɆ8?鴧CQұ@w_ }zן9<;/ ۯ,~"n9Y_ zPL1܈:uӵip'uzsC.qԉdԙ=S'%WN+C}w>bdi/[yS"U 7>N/Hq|)w ~Kþp_Jr7qb!N;vAxퟴ?*tXO2q|i#sz>1ff*sT y>r^`$;{;9,R%qoXA{F.'O`p [2].ؘ+GrP83#GVzRY &u(yR\߿)/[mގCIڝ#F l j ^`^5ϗo_.y7o|xC9xcs戆-^a[?_7;9̷4m1>4+<<>۠H>?1C=JV7Sn8x͠>ƜPNȘ89_s8?-LJ=ytcCJ΀29 g0`؛{KIwVl(=yI.?ʼrq2rg{t dAMe$L6ֱi;`5}8(I%w思˱Bt!f2`_t&8һ}DOkOy=7Lw'ftauOq~ZS_a8>+>a~9W38Ǜ,?Kl?ƀPWvwGc7Z\ixX;w2ϐjs8ը!&y;7컾|($ylܒ|ycn2Q}됧yjg̻{5f"MBÃdCƞҦ H$5wCv 1:o9oOg )͵Jr9'IhIۓk ?E׃,, /^<6i5rLC:OsF0ͥ1T_4"4nMD ĥDLA^ؘ1OW /=ߏ;jP>斂mi\Jq s!uU_@77n)Wh<rUՙh~Ϻ]n~\2=DHp+YSΑqZ~Gyz ׻yz8ǚ;_9cق&}9z;rߛin`GP?y=.$p-8V܎Sؘe}bO#.b=[lMsa6w)}r$mk~.>L[r!e*_ԯĒs#wQ6q!6AeS͂I1$Sr^x~ _{{?9s8oW 9!K;nFPkr?~)E>"P}HK>^PA38C|wl&{(\7gO/ y|_~G^w')n<<lr{|3tXǷ'0j8U!NF?G{}8ͧ8S4k'9P2T>?k&[yxY-A*y-_n]ļ _>޹5 ߷W ʁxQN1][ڇ} ۮm>i VM$`9.Ja; zǶd m~jQ;R\,f|ieyy#8 W{~axu9zmJZO|Ѷ-H 3l F.ȖIa{r)< %0U}/ĵ d|ϧ-[G9BC9u? Su}hKƜz(}OWU a%Co)32h20']e0V/y5BWǛ^ﴅS_=ŕ!c. y>=_{j}Sg}}Bv^99߇amwo q-cq] Ϛ0f2nEkO ;}zS&Kq->c>Ӱ|JZg=XkY<4sޗ/C l$HLjA>B6J;8CzNAU.䚛q;* 塰>HT[2^F8%q$pm%?n\%grW=#9/qfosG?ɤ?Wa=];{AD!&KWd|Zِ9\b| /9W$ƛyxMo`Sc?ǟI]D%ÎY%ۄ|<^6p' v)8xAL_} Z>`r<d=tGϘ*@nI]ϫ#z]q$߀h|_Ac1/r%_h1vS1 | @NGKVL*E0d Xߺt@h1yF{fwqըLնc^&[ry4h7Ś<\{9tg{1Vq8<`sA,}s9#&87u 7 m;Fw%$:9غc+% AߠtRG4&cdiN9b:Yc 13ϟ8>?|k|(N0 ;b/-Sf5Ma :XX@?S9~'/3m1lwwMLh3my}l\y}~um?A1x5#A8oh?kd \zf{p]4C5)Pny1Kn ?^1=stɥߢ9N[6TMuh|~>֗a=}/~=kqlCa%&1C]}لp4)ȸ1 +`g?P\ /9ӧ=W2c`߆~h#7?SJn>^6~򂜾_&}QSaM|}~x_Cϐ7^]?&?ۯrؾ7",9lGd˰/ٗj/ חyþ e'FFAO8E;74|/MCesaگBp\ O&/6tS'mm?fQ>:X5|wA}ˆkOyhj__#fQ/4ک)d/=цᡝ*346G`_RΝ#CζLySHK"=ķu=>[[z]2]QZNUx$sGdqe!\zP 9OdS-Y8'5}5;mOc_ob{o85ޡ?ӄECC<S~ea?6oG<?9uuqMŒ+o8_9\m7U򾟯6dbK1MJSn>-o:ċ4MIJ֜&?q5 ~iM,=+}l[;?ϛs#[z40mow=P<`?*KM` .ɗkPZ~QQ=!϶.P>~3[dd|M 5}Gש^$-7CpuM! ~m*!*AJ"ۅ U.[> LNY7w3Jg+1P B.o<Ŀ.J[mG|Z%Mk6%x3_Ls"~ܾ!(+[G{08?߿~ſ?llS 8hCбal2K;إNW @ϽϜ.Sq%;&B z T?4 %?֍hQRRG,珀FQMZ--Y/f[^q-輺q\~J.%Qria:v(Y),9||))bFYr:Ysb\DǬYUֱب'uė€Vu>ף!8lMhĘjN8 "pd &Z|Td"w1QP2'ؼZ<:d2+>N%S/x^LҚ%?`zR"\ K "Mc]6-ߟN#yz/MCoK/1h״s'x4q ?ڹlD9kzW|B152i}MWJUa&f$+mgw >7x.7+Eľz%/Wa׳5O*Yk)o.g%&k6 _Zo_iO^]z:}~.Mܷ2?S>]Oo~E }⭙%\]r$<L/>9>xGC>p{M(x!g^=}`gS=xJ{G{pg,BGeBn#G+L֨8;SQeEG*9_lixl΅w;km}|Iۦr/?c<ڕAaŖex K5-M 4z1rR_SN>ʈ_g|p]ݪ 8M[A<e|>* \r"qFsY'{}|> N 2R$ ʏ ֭|~ji5NL8XAX'V>+v u%a}͗ү~Z =Ou#R5eF͗ ye= tt}"m%|&>4^+`d A%b"i@gv;1%GU)K[8jV>zwK`;V,v1߻)Zdseᙲ'W4__nQO/[4Bݺ]|_81-(CIѽ0ev5Jx6Ի)P;>'` Gj kx/paʤkv0(O3Bwx ;^b/Xec$䚯3<ioi} /S5If1uHɴ'i!{7YkEVPվ~5F+d6)2eN} iX]4 J^>^u=9{eFc9}öaslrdgma[?J?m pkn,S۴, K3Ğ_Pk~Y6$6b)9=_N75._;WfwpȘf_/6`W]~˿9E~xåj8Ԑoc{!n7s8ֺ0;?qqLr8./&T4.vw*,_WWuɂ G(k\Q+;UDɂw ;M׫xuiㅡQP\Ц;t=?6t g{'WSߒM?iiΤy4եٚ2=~%IMPq0azCsJ~FJ^ze9>G$T%BiMpKLz'x#0;[5jntf! C?˹KՏ.m\Z .=@L%!5WcE_M+︦S8'A@ 53 P =Rev)A2?_XBw3gJ,PjT ~qLit0_OyS_v&˭K.t'fJfIf}ܙ 1} {kϺ/vDɤ،q]6=̡}+K!k}7wHgFscIVI?ǚ2={7ϷK$eOh~5 `~ye:F;*=c<ۭ>->>a'SrL)1Okž~iIrTe<${zvT~qBf(kf>^4=E>6 {x?f<}nYZp9E%e`i"UzwBgOϞ>!>/ϲi b%?u??ި#?` m*_}@ɣʦ%oۊ׺PXj|+6~7_Nd?C%3ѐ1oP 'H,<,/j pׇ7\Wƃn mnXjtv_\9W jp/hψO_?m_LSMd_?/=2C*tpA|IpF#Gj|&n%JR<_Hn;^2O Mg#;?2O}|bg_Mƚ9;YKP?KItAH2J]av_b܇nEW4=R3 cw$״g ª3 xp]fUQ=$Tõ%Ep?C,)lp$;>E:bм/2]l|H|BgAp\vM8&NF(OY{z2L]o<ͼ(Gi`^ Z#&0ptͰN|ߍ1Zy. `ی1yqb ܮn<ȕ͍>%MOo-'NϺqbWhF-DRk.3n skί-&҆艤9t-v]Cqo;+`2Np~RsG0Ώ(V3^rMS#ugW}!'~chBLĿ-l Ъonzn@cއal(^9!;qq?\a`g_qhס!F(؆!}|4.>3Ș!1p2 ;xFy)1ww" *yf<f Ň{SϿxx[k«9Wotѣ)Kg=uϷ9 ux9SPV F/'x8׈Ew)w#o:i>>9VЋs`z؜3ݛ>48Y?'K/U02kXsBxs{S+y|0>`3&e/sg/s+7>_y=E' = /da/$)lF>E-eI&by?i^r2\ ]uhu?$uNAHl+'p%sUrz?8Ō΄X\Z<=^_ *3Iz}>?l?B#Iz<O>L y :h>/&MUQri^_XlEPLP "d.72bn F0 kux-nEr8J A﫠Z/fPY]Z=ho~0 |iDڇ Gu|kxb jB2'~ǞJ~2o#g_4oM+]3iLŽ3AIX/Z}#=?4l|$g(b2G* oȼ/ w2i95ޛ"Wޔ\{qe3h?AWu%[JVIݹ'Wtɥ?nwa|)  ~{lɵ]S~{i+r=odatlk_6@}_$e[Oww17~PA59^M~B=䦤SGIu ￐M "hoxac(9l;W2#uɃI,o KKj-q rt֒U8u$(j4U.Abi dp0Cd͟bx?(`A㰽%s,0.㇧vPW#A?:GPoP=*f8ɰOyIL*^j~vVcؒųJȽP;TtK_׭وf^ä c|0 W[Of`}w%G)\Ֆi?Ⱥ7u~CIP&n$u0~Ul=< %w# Ùkm^_X,t${#Z~ ٛHȹmS&HXWzn}Q-ä](',9.Aiڃ0hsF= Lwܡ=h3Wkؓsg 4&{}>kp?`|R77>j2|>.lu&p6>ld}lKc`fQ"K|4lƘ R՗< ?:y'#Xt]nNpA`L]wv7Iʚ,n:c_cD.+}IQ;DO=+:搞:祮ӳgr^zʷ04d(ީ{o=xHfH)& |$Zs$i1~PM]8Byih b('fǠf7;A]^w/l9XR %- 〸ߟ&gt$As+NA{4_w+Cym1^q}mb, x]SH6ȹ]2 Ox 4&ܳiC'G7c <8>>8ͳ8S=FqeMvtq/qc7h?')}7*W/ 8b[lm[!%w͛&1Ags^n-=?={ 8SvvNl5U~~q8~w] '|pQ37f3vYpmWFTX静p@ oN[3Fbv#nק}A8J-Mrٯk=A@g_B9XM]r8/{?_O7,ÿUQo.CQe 4P@D,T?ȉX@Dkr-8i]v*ƺ|@%m"@5>Kgw:y7#4c>b ?mXl:vr?o]Aq]E&yR+|=}Yt}`PWQ!+poL0tn8Fry@wt#Z|)y7E_ |ȝ퍐yN(=7/j%%:O۴77.x IH ƜP>)[5cD |:O12mC9(,>{ d;KsW 4YJV*iֱ`474&,Ň1_qb9+T ?c*p6rO+Ea\x\>|GrNs{Z|ŔNb gt٪%ךvE[ |*>j4%\4+P2^^0']D+)(uD&/N.Bj 8vPàC~.[|Z/AE@,uC1B>/ :T.Q~o=>+ ho>6INF&$ihns_l3.rݲ OkɇLT8 4͑! }M*v^x2b4˞)}X(cqưϳ ˯溺]33a#Y~g'S>[yǝa^xWl68ϺTpdO[ &{[J^w><`1sZ%Cx~$P`Y_HR7&#Ird|2',\M~,޹^lƈm,ГwLBa? asS_Kܯ9\k' {Ǥbk a3Oqc4A,T(IḞ_1_$/EvH#:$nAg(7w# =&Z""Vz8rLxYB3 =*ch?LETo}/>k ?{ЯAzf㎒d7q ,+zGrHa;3~mݓd{~8Z7~7R?M/ o<&qIigq0Y~&ͲW?ȝ2c)GT xާ$w'ʩ5MlaQ44jo.]Ca3|:v&c^?3c#l5e[|.[ ᅴ[(c Eςp`V^c u(WjOP \VmA׏1Y`e^7q.Ij\u`ǽ Xi'W݃/Dۃ=5&eZKĂKy<QK[̃A rb? iphqI=\39}|O?am}GT"t~%I<|byv>9 Yo;V.b2|Fݷ} Kqz{R6O@9qW ~"=EOKmHwknn ڮ5IOO&=iIg9K{vz]3e}%z^(V4?jj [Lh][wKNikfRizc #twt/kw$][3HwfIs}(IFLW t#gi8²:u}" Ir[?x.@ Q5&&P4znnv$\7(aW){tPtG|kD{1*+1"1.>Wf"Ԏ=on)f/@N cFPtd:GDؼjN4 ;jV6 :@]Üs2uq(~EP5z?wo*7\%Lqn0ї<%}qRqӋS03{Mc$)(;S]ʅN7jf9< HjVC8="h&~F`ίB=hx@ Kiq\i ~P$&GqlӗeF(^^,QLpxMį1|) .V?:*BQ:jX3:džXG } 6K-ld 50IJoxߔXcDւ9̪`ҎnMCO;i1aje|t mاA,FgSrX2@a6e]7/tT.7x}#?XBOi&y4Q?WZ6TBVߗ]$qȫęZ7}o;*,7eO1B7 ϸ*^"h[? S~U@ry܄Vp-N5pՀ~ !eIu(ǬF"BLTM<&&'zv{3V:=B.;5&X8t~$d} ?g|d˾$҄iX; +ű؉ yhvM]wuvXVαz_[i3Hk:B6x:) w^f׎SFUl_Wݷ Q)HW(HSk) }@5P6-X,Jcv#;!챲ecU~QY,x+ ~aG6R1}#h_y< N{=2 )꣤)֦c$vuxn6m"'ۂ;tmqG6մO=baa4xEy9bKn[!4j *XklI'_W=mVW18AzD̫ 2G?p£ƪ$7h)(,`ę\Uk5'vk]XWØgIf~^_^ R`=VVR [|xĦ#հp׉ZȖ4Xޫsh][#hC*'3fpN ZdweU2phلk0߽!< l͂tuEgΥjW8؃-k&E9XvI9zsN,܃6mm@<[E,gY ,ls-Wo hǘq^F1Ȇ®<'ּnVWjm*(&,J-" k f2kVKpY;$M&ܟĄ.@ZZk%;#v=dw>-Wl|8ejg ~Lڱ3alYv+3m3Nj@V8qԐ`U/qcw0$LB7j0[n"Vwm{@+u?-@Bl#XӍ oSc2j7H<\ڣL6:T.[HiSr^גݝ[cEd+wʁyZq흩{T,I R $gkε:($,hÌ?vqz<5_^s߳rmQjyIga X͚f8؎^Ƅ҇Js:7ՁޠBU/t#DFMb1U  UNݞszllؿZIth<Ɔ7o2q⚿k%?pZkP_[sI*qa>4Y!Sq[7,y"hM6,3z2v1a}11<҄\`N7Om bE,$)|, tw^%;kh0ܓmXBGY,ǁwذpBt+SQ-z#(˝e,y,+Lʁ&CaD]~7QCtivt+)GEA 89[ s՚@fqqDXZ^N7&tڟ7e6 c;~No<:t{>/TMT{>Cl*cP;jIRsҿ0'$EYO#ɷXxDjG(;խ䝾|~!Q󝰾R ;HmG>7[ʿvſ*"~MU Hϫ߁m0x.Y)/n}M?:3PB%MH$}x`Rn#K4=%49`|qS9y: gG!r>v2-Rzab<I$3]F8FM?b2K`J#:k [U?hF|$3&ǵ<4 &,ki? 4 MsUʣobo1!' &&|B ++CX4#`Hʀ Dc?.Ḗhf;mэ"4Q-I [9@)(PiܐYZ`fd1&],r`2)NK%Bl⁙R ,󸡏[1P | i0D6HiMZdǏ,20,߂BGUl-lژ&#jX)!2_hAw +,FL۸Eh p0m49m J/&3+9z5D9o#ײ7eY…D~YF۷`E淼8< wgײZ+]}J_;ڴ_M-k7.c/ʴh Beu iqg<,)=3(YXQ8Hc3ZGi49xڜkkҀ,'+ZegUaot}64^+dE p,k`)NVמf49ؑv1_7ղԏ>c(@x:6b-`g_KҬ0{l2 [2ޮ_/CK_OJ}tx:+`)Nlpi6(_YlYs_I%m2X9On+?vo:ylxk7[h{dS}k`,: WgngcMH^_ܯg1.Bÿ7bHXirhiNubQɡ |m^n ogߗn=p+Mtq6L_*mZz3U ^Xzkm? Ci[cCJVZ JxjkmMuI7XW:G!Riu~u_Q#+gнn^ڗܳgC!tGW/uW2Pi/7ut{EC]oꬮ?CU]>_\Ko@U~ v eBg=ryL3d&*mϐQMF3xA!{_oLڞ!axqug(9hJq-:[-k49PCޣS:(͆\?r] Fȏnk3' S<: מqMj3L_ g Jirҙ%.PuEfZ_*փ6b9g ]( o3p+gf|Kky)6y8P OݰbԕGh3Їo],)gu_j0zOӓVQirחZ4%1ju V,Ң|v@\gfBL15i+}LV]p49 g,g`ˤLoS|!_I Z[ݰJo:jZSJAڬv^4iJ+ Ae]r(}YcQJkp>京K3xzH4 t]7mo* # J1af5:}mʷtA:oy^KhNٰ 2W}\w7u-)+~49Vh?wF3PgFir tMތw)ϐ5v; 2Hۘb^[v|,OѮruO;Mϫϐ#mϐKݲJk\[2Y=q{45祿>Ct495ڞ!:˞m>nC+3ӕM{)}\˙=.Q vyLSzQN1[sf s7ٴ+MdK3NW~6-=0}D0`gPg0:?NT|P5M//Gtݥשh5 Ȟ#m3'gxU6/ӑbu%_lPʨC{g<+7a'՝lwpW2TwHQ8H3c; ;"K |ƽF3~xX]ai垛h{7R: {KS).Zb+MU :SIe-JMҙ1_1N' LJQz<-R(tMJɍ= sTז`zy @z<raЀމgTz_qnS] 6,~]W-k7`AJ7봐). <_[qyJ.QroW$Q{텋usi_ÕjFn6-.#4~m꘢pmE_wmh|3jJJyI}XF3L+?uAo>kI+'ևcKTHQJN'5W:x¯[=^Js\8HKɶ[-qط4bd)Q‡"nll2SO)L8:oTsւ:R}t<5Eenta[/It6k׋ Giu*r-Fɛi}:}]J1]nMkzb%@ЃւC ZRrFɯv:snb?X_8PSi>S=}}g/xAatLm E:0h-ܟ7y`+g` ݶ͂mtr tI2BJ C 1Qi{3hУeW_g^Dƣyڣx\J 5+{mo*)45mR zg6qy[C躣&3.^c=dN b ]=dפ%R-OL˃ ץ@1bq[J3wl4erZcg?+gMzx-JS[5Wڞ!;[J-? -4P}NgmW$8B2zca!tJ#e:KE4S4WDS]om~& ]BkCjp T =u׍>,JGggҔQۖnTE 7[FL3Wo8g=6i]σ_+gv˄ OgřdI PH:.ݡ7|9|IKr|76 %ŔoIw|n>;G#oѾoL>=!߲W6k׮n0M>1㚯qq|nb$$ .ajc3:llrZHS&Ps~Ni9j5m]?uGBfoI'^$).E #L*mijFg)Bk@ᄋ>C}-!9D/Ԓ@wz[.Ocw g3|l)}iY=QtƓ#]ۭϸh{ƣgh* fW5IMe!i1uлLiS%Nc՜dmsRip4tC}r"[H@f)o9&KH2H>w}6+ Ggucxr23܌&"AU+ #{# ĹC3S~{5jvm3hC49y`Vk$@h[MEcK#ݔ~>zdbP5yGӨpڝov)b B2Gx䘚oXAxWpq=ʼJ~qĈ3 U͌UhG,ܠVyV|׉'iD3D%<]49Y@ 3' ]7&jH\FdQUv/Ojrۙc޷EQAy?ғ:}[(,?م8 YђFl<5'o'Ϧ3 :i KTz!m9Wk]4z!iEi-eMͥM7n#/ZgP''fa4-Ywc"?QRy|-UxƁ{N(35Q@.9"#cCz==^\ЩegCJ%zGRR鑕O(yͿ6~ Z}"trF-I{77= ˦սo.gCz=#1Y1܌׻=ԓQ}#4 7H/|3G+ͧogd\A!͚""u9GN~^zCF8xxR]E\ۙD}߰"fr[xeYw~jVDaˈpt>3e%z!f9D꾮WD8-Et_Qdm` -΋h~rmA>Ď.? ³^kTVfz'rgX3B 1~~i1ʜrȹxf '@iP@´3'p @>s1bO B/6Q.ۡ H>W^&a klYH`k@Fx]K+pFH\hZ׾G BIz>.pU?#Ar6初OD%": BýoLg8N-lvYuME\sx"lX <#O1Ȃ,9p4/\KXuVisݶ f V@\΂X8n pL/+dD"8m䎲xf\Ƚh)r`;e7ΝnGAԯ=h ?Iլ 8#Ắ9yQ/EµqU:lJAg;;[b^[h9^VpB|>vqiu5`!FK@> Z<+LD7@p&-׵ Ik^]e2'!XJH+ql *"֩zAՄ^^Гf0]=#z<գ@,+ 7`v8^x!jr=Et=¥"agA$B/G^$+Zg|[2B?_q`6j'!%m5 B+DrF>#{= 3>˧@!zЊ(gVC;c ˁu< n 1?e#dc*ųb2BcQ>e9;,䂨clgA1)4Cl!3WpCz8#և#)p}##@K Z2S3V{vAC}+3BCo2BWv9G #WVP77 |F<׃W"}|}Dg_i;RweFtӋwo$JfDڣ Q*9aEw@dh jk sn^ gkug kQړ|SRF>Vzu/eg^ecR"kpe +1Cw2}AȁSBNjf*9t.f _xۣ2Q : 3QHF>˨-##:ji61wsdyVk)<1T[>kW3¯]<=2#39 {<"׍]6crk3B(N ~ޔuڌ R[C94#v5. j& gڮqt|^3(#zK0)U딍Y;B^*BI%#/sQ)]ʌpG=C5o݃ϲǍ!'dP s#VrF6A{pωФ3Bh"m@ոTmuyy BX緹+#OFeΰB+-+9g'g 0þ.o [FxCU)V=T_Usf*#t@ȁ \ALΈ k u[sw|W$# @Z9 [2gwtCӌq-6#zm^"g/uC3^Zȏ+Xo#rte/2|DF&ITh,}8XQoea/l,V|0`8Q+SCF( ;W {r Sr >8BL',P.Γef=e!rZ=2>dN3mFH@~p7`MȈJ ޴ R*wHƩ`zDUAT3 %|7Œ|5/"jZuduk3B]k- љhXQZy3K3{|pxCgC,K $]A>sNT9ȇX8.UnwCPqlqr_ u߇$9nm2Bq+BE>AHPv9+SfzݡP-xҊPBc(|^!NӂPstgiF(fGNv ɈXGAC=-8!ad/{CB ;_ Bx@i^=bk-޲ y& C&\lfYCk( -^15Krj9fZ^RA!qKRG zk=V9SC{DfoFȡ[RÊ2Y/jWozXƼ+!Ꙥ9PaD͌pLKtkV;Ш1t7џ  Bǔ`‚|WʺC9#NoTyȇn*wk rd,ȇjI(ȇxȚ#;SW9P=9#8iӂ|c@Zݒ;{F1EAkG]9/zv\A1 7Qbv1La s[ ]52BºU3֍YzXj8Oh}N7@{_6KsA>r`eD-$sP;B g/9ρ_9j8񵇕$qIRJ~c˺\r >Ǻv_9^&#7^6# ZQjwe-_?"F ȉ4{dD@|^x=  _AAx>@ȱ^!#Qcͯswƹ~#Ye{4ǂo1$Qg=~%+QX7*~)_o<&JVD.{FWmϪqr5+QL}  3iAA9>gE[NY!\{e[pg䃗Xk@[fN+mA>_lflׂC,Y3CA>9hXs B܉|gS-!ǢzB&#WYc BI2yu B/UCwcUQ!&RFB:2]ݷ6?rYurvX rާv@_,Wz~Џd[V7|-߈ cai㖬gG>F_p2O#|XG>B'+TrF_c*AF1ٝ%|Bg-~A8sG>%e#3Yx4M9p c!9V8x@7 ψrPrT- ؔ+r vMSNc73X/} z"=G^ B5NV]m(ERv*#=̪ a40FqDgCl;c>Č|ne':Ses+hʂU5WMѻޒe‘t{q'o[T8\Z eDMʫd$rޥVy'נψSeD̵~/N:#CA_l\/V YR@4B[#d3p7*fJz9Xwsmn3BR7rLADrMe[* l'bi}Wدi }{tU{D'螣r;>S*g_άޕ8FF ׼WdEtlvu8_!G߿ٯd;ed2=jUځC<?++giX.*\}rvIZe5=3(VcUr>Ư֤;bC|= oo\_FD iLѹ]x6$ m ]*X|XxpUr` +\W{ & BtA+atUTܾ%r,~ێ oVZHsAAo~cQ9֣R佡k޼_Qͮm4rl(r >r4$=D3&kh_)w;cD/1#|;kYyZ𬁂1y='%? !sw q[2[l4]*#9kL:ͺ_FL2} 1W>&;'sBwK'9SZ~,$g+gdU SeaA!tC3^ jO BH]2"gЯ`Q۰ TPxrۭ *-삐C;/Wdc6vmG%8 :@7t4A=904mܸ򫦴YͳYٍ*Bۮ,ȇJ%ޮ[X ZԈ(ǎa #h+ 5^ȇ:β[hй |q.+3N3"wfVc|,!ǻ+ȯ_sKy^E>x4G _*NjJAG9Ht<sݒGYi BC.֌ЛP/rfFp99>`&Q p?%ۑt%9XZpBTO^|{>F 2B#:CY:i xdWF>ġ=W##sie|Cm1ͱ Y_?o*91bv "M*9DrŸ]m#rkjQ {0/jhC#ebY`E "0ʷYEkz;IՓ 3[O?M3B-XmWAxCZ|.82:eM BE+G ɗv6/bxnO.!#~c ]?g›hmNWL&#<.i= G Qu Is=. ^CץTA!|}.u[NEȁ$],^/s=b xI܂DQX|+֎`cb !Vά. !Rvq)6Yec 낆2R #KZK- <]a raЖ#αr~v 7.!GDDFhȝ|^)n/ȇ]I®[RA>2B=nY?xPq-V'1xӲpAtumF>nc-<9bx&uE!_ }Fn^͢"89ɺK+mI+V+q&\Fȡ6k,r& [r e]j蘾إ)+>`ۂ{bT *-զ76_c`BRdVQ *tںzXUOfw‚}" !3RSmeB!GDˊzGAȁpW/--O $nI}ֈgeok7o3g|~9DDUAx+S7f~5 E<}kQyOmbxZؓ3Y{r 2Gb 򱃡f󞠏hVcԆ29R_#sM!X/!n+=22Qnψz4/D1/l j iZ]9ZxٿG V'PA9b:]AqxV P~%##*ـE6jpJ7̈ d|+ZXQ[\յv{v kSVjғ+!XzrFk/j=QgS8MQ]k.ivV{)1v IFqd|f9,@a t.}ɘ vzDXɁHq' qϤC ~=D^!"hݱ!+r-ψr<6#$*s<.#G >rg}ͅ ؜Ouܙd{xM|k9D# toA!gy,\A5Ox$Q?ӯVGgrкN+Bɪ<+(GêT{rEWVe @VoI!|땯+\þ 1+8!ޠP}9.Gr*B9M0k`EadoC Aq@>gҞrZb!G@V}ӌ|tNWX[r`eoTȌ(DŽxf!w+qDB@4gFhL= zo!YwDr@pA߲SE kl#[/ TȾ#~ . ˜^5Iwlセ-Fal͢+dEui5#F09-31'QIkb9#3!kt+!kQ.U!NDC^l4 IA>Hl4[NA>db@j=}r\^ #=&Oh;ȇGwzdS92BCU$25Z *:WyfF>dYɌ|/?EzFǾ|-#GDtgCu^"uOO;"bR~L cGΕm]2ʶG^3"OIGF>fB(ȇsL+&GF>?Њ_Ьoh3Bm765zoȚ;^"19#G\/@8sS'p}dGwpקWpviA4Y5邐CιcGeCy!h,+Rv8]"W#}5B0>]E!uP~0tG 3G6du'FAT]zFt<@tL= B)%opYa㼘72S5שcPɷE?ϊCvz#;?#/g IXvI`‚pgo)expfDG^tC~8B1-\'QdP6yC,'hr\ATj|6́nz$s9G qA= ]s.EDA {ӂ7ÁCR< ##3fD8RJCnsE'"ʍmY/ZUěf}A>v^ZƑc|3Bw|@3WsteM۪>ßi2ÿmzԴrꈪMQ\}yT *|˯g;cJL(g^ݴ"PsR[VFǾ 2YI##~R !-3Bc,̈ʏ˳38, )r]ìֿpD0odA!v cG9UO'Z%7ɻd/Q"Oh7ȇ8 [ BK c 9cNFht::}DₐC)0s1z.TvY>c9@h !9)9>\/F̕XLB Bۊ|$AtrlUF/ȇiT.96U\LRIAȡGec*dCv-'#ك+: Ss5'+S8+(.R/GգjSFESX#Ge{U2½/Zϊ pˊʶό~vk^ǥvA#`_v>9qd,{^./jdB~Z߼)dAzVF]V,Yq 6JsA1yyF[#_ƽktx;m-D=Dϛ%vٷ@Qã:+B }+XYD .*Bq|^D8НQFGA4r㶭y kOAȱYIX)Q<?X7zdD2!X?23 FsO@A!6zgDO1j*9(kPT9DE9#{%CWAbOPr@t|E?Z6ZƧ[,mF)-A@8 @+K q挐WCWTq_r\7bzaʓd=uX+)ߖ([{>ΤED)57l}(Wvgdp[=dp&Wٷh,~}薁h, 2;{܄㽩om:"jD8PwP'{&yE“&‚Ckz~)p4Hc+"QI=j0D8p9Y0xAa{:prxA㥌޾> PNBޣ 'Bxd~)p䳬}c+pl;wRxqY9!q`K*pL"\XB*B==C Z3"5KeP~P}uF{ABQ x0 ꟣?F5iI_LΗ9Wr`wx| cz^ɉز BAZ5|1j9Ի-+BHO\zIJ}KF!jvϮ9$|++\V@CvG{#/#1(=Vr\88_%u7a DoZ<_vpBMmëfq{7HD$ouyb6y;Z2#rŵyTEE!_<"䐳-Dy%`aQ:;PEȡo'rE!Zq>4^##-by9^eRbnnS9&s#rM/"EG}Km ԛvl=T-6- ؜ICά*BE|VLUxG Jb,hu"䐨x0bc#䐻<8G 9߮g6TkFŠ|V*Ukr`FpAȁĨgCY 'n!Xm[򛢇Lug]hC3y͂Ѓ'' kKkɕl! Os IwOHx[Yd$"Zꍞiu쎞bQō/=M){:)'jR\Fs4g ="\/fU(R3igTAȁV|HKQի" u+B^ӭ"hI{oVrȯ>׵C"D\;0@;r B-(< np$_!٬>c@$G$=D_Ft-F̑-rІ3ya?jz[S=='"wg" WFT?fQ[t.o7>ɒtZ3rMC6s!=^n ϲӣ"'Ҳl|/+{vD98!X]caBln::'tID8.!-]rV<UrL~3BjX BKͺǯ7q#QA!=D-#~ZxF {B#ZM(2lѻТY?=-&+Yfr<îsB֭w9p[Y9y*ȇH&?=rWE3T]3b=~zKeD9::LD9Sr<\o|m ʱnӛB lEDD Xot3 Dm}h<#9G ݒP`Lqk2RBnYϊ\\/9D|}KE!|}I/@W,$ЯW$l(gqVD-$/m!G㷽a >gdc vk,/׭[H2BIy#z%&,$! {R_]$o9`^V$+mE1)GJ zZ@F>FGF!ubc^޼‚9 V ǷETEF>ku@>++7/vHƑrƓ*ew3Jfm0GFȡ~Tdras,=o/"!G4Z8FWD-FpyJ-=1XyPr3Zt$9ǯdaEE֯aVgBf? Ȗ͊׼R=?_e #&h9!ǏzOC*z*B99PnC4d#rV&į!5F9,2BF˒yu')s8Bq0 vK*r,'8!K{\ʓ=^ "Ԭ[rfpBh4؊:1M"c+"I{^Pr)]*B ߴ Bh%K8nZ>A#ϭ">겢<)#h$@-?f|K 䘔-4i}Oq8/|qHf ZWaEqfRR!;@*ȇp32BֹsؼD-#=0}jWTTbҞvvEjJ{RE~zdck?#_lWVcy@'{FF1:CʁAvEsle"[on3GK5 "'/PB_Q(p"y|Ȭs@ާx~A5#sE*"/Y*.ײ9 IA>Ԅ:B o 5ZЁsh=6_cAiOQF1!^G'v zF~d#ϲZ?} Gʛf$qt(z@ 1u$=E(J@ȱ( RJ  }Wv ģ] 7ccLM ^vO?KZhO BY6T_/S`L/96iKnPr܍yzs"KTj̤GFȡR?roUr\jW!GMG=#O+#|2G Г`{BHI/=%Fdw9VpQI:oZBy[Ѥ_cF;7 DUxQ@ird|̲XeAcf ##Xxӌ|i]*r߽_Z/__&GcA&/#N[J m{V37Qao*8H7,em"zV.?3BߒY4d1 $٥fDUdD9x(M4G _'q9|:PM2z-&ׇ E0l O\HX66:`yY*ZMO^lL1A2+һ c(v?a%]-Y41os#Z%g$ȍ`FbNՍ`g>Sg uלϑ`f9|@[KZkD~@<8s V?qdf(O-F٥Jicۘxi6|J{K>"mv9%hlApF_W*4[ߢkƔH~qg^N#bu%т?m5 iCi0|̪} ;cl@#`4ǯEvSl'} t+r4[ 4^Y- ~Ueun?-Jf~l^pVhyl2W7'2 AGXm=c#AڍIe)A+Ǧ|A(g>ՂƋ]RQ 9 rI3CG> `e1R2to/r{ Fb˼-hB|e6vzza^$+/ص#241* xa_eI/>Nc8)FjA fW_:m$;ƈTsS%3w/N y[7`ir 3>j3O3F2+ٙy(9~]J"^;hjJ yA=O:ͮ锄w>skGN 46ާhدJ };ŋ$qu5 iy횻r$žU甄/}~j<gZJNnbl#gH>G#݂TaA"Oo#mߢg\sD[hmWVIb&q4`ƞ}:p|k[?irjl^4q:'VHdo5lV} Tv$LJ'A֠J~NF##H|D&B[$Z_-ox6W: qDY#pkթÍDnW23m#]In/2 k1$FLËBY1 ,W4 UŪyRF1Тj+4|ܫNL+@(ndjFtՉi6 1@ãP[;ƽh0B1]'hA\4ZZQaqكD /vHۯB?T$FǯZ҉<?}N\uxVP4pT]ܣ~NLOWۯH4bҺXhƅ7əx#qߵ}#gw I=^U1NL>C 4GFL'v>n#K#:״\WNaW9݉i/h|ӈiBҜi5b'jܙ0KwF]I>q]+#Jh?>UF~[*M~Z*"gtfv1dyI{|f{=x~ΨiFqk;E->;nOGʳ4H1`\F&čT^Z%qF hؚ][:1 hi^'UŃN>̝Np{ 4b~As} 4,{l|/JBco! g^K#fI(k׹zGndbv]CIR_s$68+1mrHA?f'lcd筻Ia\]!yR. =}>cX!UIh 4@ ~ V,svقf4ND6hX`$v  4ܳAUNf'~ZF ƁLV$4Y.A2xa# Ng>gl~H0˷ƌZWϣK#3+Ș哓Hqkaq3rZ76YYVC- :Ĕ@c S'!u:9[6AVn'<~5 PNFL#" 4v_f>#~Q5zvIh E-$q>~PFypxueN#8gY؈i\"8kN#0edFa1*?hџ7ba1긏FL*m ˍLd!a`F~y|PVf#t΁uF:i)z|KJgTCTn%|&zrM3ۯy4ټYFq:[r#Ul6#WDdb)9vO0y,8@+7+Ɖ'3`scTۗNokI_k1Źvm-{cFaV+; ǯ7KmW|Hy*s^#0@Vգ:1 <3hXlg{Z6V2\ gs(ƃ2AboZ?L&Ƕ]^X׸J6Z5Hqg;mzs-,Nq f\h|x$ 4ꬣN=;k `;FhN"ђK4y%P}_ ں+ 4?j4g힅1_x/oO|ލk੻ْ`Nh%bJ0'_ϊodsG*˸,,~|ow,}<^=BUn{枅FL%?Јii6 kQ?264b߮ꭍ@cC{FLc֚+H8yv ֩Ǡ4^(>{,Mr&MzK 7HLF>oҵ$787lj 4lrp#pXh&@#}})/AۮQnd(6z$m{[$ 9I]j$f2E3h~73 >gC$аIS6ѻ8% \l]~ѳ/R*߀eP ))|V \'<m$>& 8 4,ݐtxQO! n&-./d%)/0=RLWKQ @W @u $ǡ7w*P-r$[e71{N#aT<ʫm~_F~p:8L,(j#s4lxc FG-FP >t͏Z,F<܏aD+(p(\x#1)=q^ ZXyy _̉={l\e>%W(fޓ215j|U+4Ha]lJًRf{{Kgo8QG5jxV1 innnN ,/xņwϐG1ɁWdDd Fݷ4H\@ý3%4lUab\V텫{e޿ZV͇y|Ƭ^^֊P:, så롾uu!S{LlX~Go'Z֮0}S>9qCk],ύ\9DZ ˷r0~ܝ,^+nWȗA䫥6`Vp9Eb _/~@nvnulkXk<_SqPm ]fi/ܥ,k=v6m_m wO,A.劼l >vYO@lv}`=qb`Wsaee@ieiA @Fwרt!w _ q ;cB /+||ssރkb }vd Mӳ@@>9լJ@87‘8^N$@++5O[|Dwz?!i \=3D95=E^S7ǝ{ `ffY]^Al`暙 L~e<qHo:^A/R|k?N& @*u[3 D"}VYֈPH];b3>\͹NH9yz`fgLssQ,X~_n^@ ?)/0YNy%ISq@~v9XQkVH'}wV0Q r32hLxR8)0=Oq/p o>}L/Yu;@LT3Kǚ;ڲg FR'ɛ\k7;(/Aд }=ȑY B>jN]Ol;Ca 4^ x?ϭ EYQ65(g3s \(77<L1E+N ]S. @>u\,0=ݥB4 7s}r-@wj _^g\s_{E_1gQ7U6ci_@  qm:W P~hZnsٺ/w[H@`֍ o "[k0GLP<\kR)ew\bX ۽b+_w05@o] aP!}8==p4$0DXǻ[H9 m ( i 7w|cJ+"wfSYO@~yr|.e^.#+|9P L~Ds[7?ȪY0b BϨn7h?]_`?;|F-qypl<,J,5' |ɂBywdI>.Mӗ7wGr|VϺ[p- |9*zx1!}L >\<'@~~?@=s%QK )LXA?^j5WjR0N ʭH g@=ȗIg L92'$}2~ߢnIUO}+K\ 2~`zrK( /w1 ȥ9ؾ @^-|w`ni(m?7K*.M5@@XMZ~ @ɪV.y0䗻#/? ?|: |!T @nMq c:{p=?/oh\ ;wc0o [62 |;lRݥ6 Xswm/ȭ?W`rwYKЌ _ qL&wGtDp<_Uy4 |;! x]%1VrwnnoQM`lu >0}h㯂˟7 Vr4g _of0wQf!/GRRA [`?ܤ;벒L2^#WZ9qG|q qAD/O?,sq 0}fWp0+w90;m2~s-o/ Ry\*vw/@p_kNOӥZܹ!/_>TطeƭK-QEy_@nᜇSܝ= ?N]?Qk\UۦW pׯ}t}RNS㟯ƭ*@zҿroIAe n>ϕ ս7U ;cv)  Ý{P(4/ѹ+}z\= r*~U)8 Lv3ׯS7>.S/wuŽ* &jxei5`|[`]Vq.1>emuRt˜(K)VQN?/s|}5Sߏ@~{sI\El5YAȇ7B\>3w],ң`z|ť̯+ko%EmW"/Oݻ- OΔ7],r/~xOnW_UY;=uԟ_ͿI%O7  ?~\2D(yxwbD A">z\'Q~e_;^[=_]5i@n f./>*`t`|0s̪ 0>Xw>i`|X ܺł0~?l_Nc5:ҽf_k 9~~S>\ _WssO@Sz ˊ | Owof5`b/7Z); Uj_l/źíOȇ brwO'Y_SP y=Νb~'1|~ly+y߿9BA_oyq}Y@krΡ3?a<B~[sݹ>_ \7}m%O034@k _Ջ _Q{ b~s9{͜] n.G{w}1_wW\GgYՑ6=N@![@:q|Aur _ IyQP%/svp~ ic̯͕|9_n D\| 3GeD|0>i9׍++5FW @nu+P䯻c5ڟRP9RKA׭e boC@?*JY endstream endobj 362 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 368 0 obj << /Length 824 /Filter /FlateDecode >> stream xڵVN@}WXZ/]_ԴDj"u(&6 "wv</c@ٹ9{q[cp+"1V[W WPx? L3`CK `J6aI6aƯrp xdBfF-; ߟL紼ayBs뜼Lcua wӯg\O^B]<2ΩpњLSrC[ R"ףεլqp8Y\5Y pB// [s.yt #Sècd2 K-ߨOǑ0!q/yRJ{&—[$"^M {DBcA4:fFj62z,ttes<:Sj [3 P{$hSAS3T֋n[&4 q_6/Dξ8ɽ`S"#W'.x¸_ B"_:ڱyR8/UGPK<0qzR.K8T;s=(  UT4ymu va–z%vL!y_arJK<.Y"×HHEZ3Յ}Mielܸ89ɘ< 㛪;'J PG#"vlq7qAe_IuD!K6Ro{8ϋ]n/ڞ" ~]d׻ث09|1S;;|/>\N$qZ"}ux 0pڣl endstream endobj 363 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-049.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 369 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 370 0 R>> /ExtGState << >>/ColorSpace << /sRGB 371 0 R >>>> /Length 115 /Filter /FlateDecode >> stream x3TR0TR( b. w'b.=d89K>$MD*! |c = CK=ss\h "M#dMC YX endstream endobj 373 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 364 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-050.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 374 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 375 0 R>> /ExtGState << >>/ColorSpace << /sRGB 376 0 R >>>> /Length 46620 /Filter /FlateDecode >> stream xˮ%͚$4?O0e-@j $#1@LDՀ}w̟#$\<}G|3\˿~>>˿oG,?vKƏ?J?z>毼7WW_-3OK=rp]?~?y^?/G??%1P?g5k/j6nƄf,YBc66ӏyfyWjDgcԌwϕ\W1z1ЫZH?ڼG)֝돡kV>FnZkSYT>dJx}@sΩ`tmk'_0U j_u#E4dS|*g1ʏv?4y 9y^}ݬc;wݳ9yYx99 e=Ua7= ΆY0n1פ~5ǧfËɖyhV??n {5x͜{`;l];8kZkú1R{cL?*V]Xj]큷qO9Bq} cٞka3X.q}6zaYf_Aj ,n;Fcnqy`;~AloPV5^+/j&4m=Ϻmo3ԎEoM[gЮi} l7;x\UxR?~=-cƾfLrbOړ|{cgkcq|zOϿ^ߧq"ǻUX<8z{Ɨkv>ƿxбDž0}C|4<ߺT;\u׵ys fU>ƃf]o_0|P|o\\Kc_>ZRxֶ_cy!FxDD;(hA㱆Al ^p_ncb;^_y֡O1k>ծ{}`>63?cb?>\߯?7~{^con~#>ymMԵ.g=g$JkshЫXLz4 5M}ckcLjsJO^M~\0n Yqmkbӹy8'{A{eW`ϞϏ<4V.}1_0ɞXzcϯu|5:_߯g@yvQ['3xߵk=P*m=,>!k'Ey S?kY{ژ}ܦא~/bpK'EcYM?0`Js[5kmB5qV{~Y'{q=_ Ew=X?=ZK~zj3.U'0|;ښ?(y?k}M{ݏO o /Ym?Nci,wϼ jYژr١[1Y#ami;p13tuOsIJU{uds?Zfg3Y=^`q}9\ ;+~^=nZ~ӈtv>:3yzcMlχchog_uPggh)|0~[%z ݯaf}^߱?}j{ c>}yߌM缙0Ds?eს9s~`s/0 mw~_eX _a2x^M?ot0J!зa~g+#uudNB]xY 3>n3^6cW E7^Bǯ,C}?遼GN<MgM{9Weh`>@X=?2l=ש0wpy9^px|A]K{ m7DOmhBihM+ΟƯl9u3sn0dlw~|N^y޿I{~p/~ACO2B}òh@_G;6m6ӿ~(}{;6+s݇}}\[&?5AW?51զC/ڌgFqvM_?oB|33^m+]yRv;s?BxS9'ݿi]E׼MmΗ̨7Qxm? <B]/_}_@קBOcQ<$Ym폲~#j#Ps+ 7[i ;G3i{Տkj}+1k=U>_+S2pE+)޿{?P?~>L~Ⱦ~y3*Lvj8[Fh{72/(&zYRSV%{]o5(t錂V\^qł;Ce7|Nxm>vkr̃F+ fϧ\ };mk00VXM}hb$#YjĿ#(֡jҞ;̠QB[eLNehOhҥV}F!w}C-",se2ۻ=>c͐_Õ1¥2n+ܙenYl~©;-w1Nslg݉qɶh̽юJ ; vEI=}6}h'ĸ>Ѯ^R;wO.hܱ8gv9x+ 'Ԙ8 so;qw ʽ'q!{??k>k>՟ۃ޴KO4g;\ Hi瀉6k~}2өQח#,kNM)LS.;b3!vRC!v~4D^.kL\q˗tO68v)2NIrO9!ƣ.sտB&rmv=ߔ.IY6t!Fڳiv!:0v)5h Yu̱*ksB~tyIyUhN"J=) BÜgN6C@g6L?)hHHaHRx?@<~>?x#DN{?-?_SO:!PHT{~ޟ!g~8)~B~" }q&ys/n_=OnU.g]^_b{ǁpV˒۵`cLP̱mx]VHc /[s- =kMAg WS~6BQ'-a2l*ֵkɟZlX2k阷0L>iɿj>׮u-:{98z鏹<i>ٚ=E´h$Sƴz<~m+?az6},;37+pHjFU;YӌMhFWQ~5ỷ  ~L5CQPw;R7)NKZgNC˪[5^;OLz mP0Jm/eڭdo8vٶɟn|ͫa:Zhg$lFjQZ9kܤ&~}n&1\/Suԗ *0z:{K$ri1~8';G87y B]QYV7s.tӦ,>g3^ #І̄?/[@=_7(AgB71[DlPә%X \ן}JIf&Ҍ.uMl0 +(9̟N@a<_ Lb ^@x/3|sԍuR6\\$GP'ѩQY,B>:òDOpƘD6)ˢ~l@:Ibsc*>J#K<_3,Ǖmv~% ;f#KV1e}@X+H&i0^irc~eIe%q[r4Kb7e.x{ O H-^@Ob;:& `.ewRH`ʾue*e'CM#»1Q0q5d'ēٝe~'戤NFq*Y;pósC$ hSedn'I<Ɩ$}@F0MDͼ' hBcߛ(=״KȻe.T3;1p`涝OÅ>MOE542 tNvBkfr  ~srj³3j׌ʒhb#!nWV\eNHA,1ue,DQ<␠@5!w$at,ÚDf}a:)bm|l|b5a{t޼b\cR3x_;鴥hA@a1S712-ѓtPeabIa)߄o٣"bnȲ`z6Yc"*<:#` 5*db{.fV) c&_;5zM>4X (yf`z li Qlo2Ak┓T*_VEtI51}]TM739uWF6A Dt[I*涑8ʳJdB*$2$^ i>Pu :F7Q=-SyAF*sX.JXKnLE IoZ͗6 a|޹8VR%6T2 ±6i_<&498([Mry`cSDrUt)zgf|6mhZ$ eMbJ1E7&1/AN✭EkD7D8ll &}iu'krfNڣMr mAd. ?6-A$¼6ZZ+0M(2WF8H 쪛 7YfmRy`! ܠ p+i,s]̣VH4!tlcHӨd$P/ɨ)^2ޢ8V'PEfȐ+Pti,8lo\A"'1?MYqf9dJsP<ᧀո IOtvyOq31J1f 0oryLn}8;4c TM.@ʜ3J2(f #< d ˑ\~B{L'WR =o'R*dx;?dG\•@ؕnmvd,%U!?٩R*UP("DM+^Lo3W!*si$%ϩyf\$ۀO69IWmlz2R+p?38.&OǶ P_׀ t29 X# ?Nmn5d0) f!Qc[]:yLz :n? Yx.LQt~'u,fF?Kdӱ3긶B… )A`Drx)VH3UT(M~i;z[R%Ss$B1tGB]'K]:⥌Ru22Du:Gio-IЇ2YfD`BUݝ+C%g]o+d oLXG~Q6: 6?_"cǞ٬Uv<|ξ+X_f~fp:uu^d'B3 X3nR՟sFIK>c2<KaHk5 +*.eL&WVGISC_:Ә&IcQӋjpEFQԐGE U(P$g2-Z 0g %?n;FfeXeJ]6Ll+xʇ{,\lN*SbH͵/ [ :@%C0Ap;F^a MfMX +}F7p7BN3 ,J`9,٦H+4çi Sr̓Rɲ_$Ju&%?Kg9?ÄUUGOL.i/X9,_;KݰpJc7&هM $4Y-SG!6Sp X4 mݴ /uށKCw63|Z,{-&rt-¾&UTbupH: < \eXgQމ,U˜*.)H}rݯtgxS2qK,W,f܇|*B5)m "EO| $ww%WV8ft>C.|x[DISdL-POKP`.P7LnT%*o|@9883}+oH򇅤7΄8al߯,jө}3$Bp(u^Q4ֆ 7194A-?@Y3s1zzOI l%> g=NmDn" `{1zzUC27=l7>u$q2@y%4.S*4~μLJ}`" #:o&$6*ƭ#ô޽1D"d [ͪ默qSu$Ə4$=P9򒿊0n$D%mZ ,dU4k}FL"S9,wB3gő릙ʝ]QΑ0a끡W]VKa* GbnI퓤f{J8wUsDaTLhM”ƙ ^" A G.AEŞ YU!7r2nuxWss~JmE^\J6zV涒RQd3͕u:1Q0|kC߼u+FԢ'WʘY#d-]q(v߳K9 IɅtBOӫ5›ԡ,)ʧROVuL,+4(E‡*k?~ |n:S+U-Vvp3*p UXe-a3"G\W9K+֣IɍRTՀ z+'TnW|5)mf1 w<|ǩFod-' fH PڙZݞH8t bfW+/ e. `dmQlbe1nfttEbFL[4aD;D{= D A͜E.r_Ǜ* w$NTE}&0&Ox+=SR6(%+@j9$w8ت {*ՔdNv$]ɷoCҨ&GSD#)$ 82ԀmTe²``Jt.hzO#Y) $m7DThgTup˨AΌy,줢` vոrE؏D@HRn+y"nL:DbV:oqXQ>RV~+ɱYR.]T(+ĩjgI#}X4JuÎ!)+ٌ#͕ O."+%k$ l@\%4a7oMQm,X;L&NR"`ڨyϨ:ѕK1R 7'bƟޞ N yؒ*dsp"%M_aBU7L3. RSi[acgW6y[_mMF?be!\ 9g0!_꒤S$8fxy*ִJiEPRZTEcD}[z&X]zm Rƒ]X;7 2Kj<d涚*eϝDPŔl:N@. @8œX@Q_X&Q6DɎچ6ޔU_%?Z9Fx)FVgw%4UB p.LVEqi1X;ewUjY1/3{okm )G(O1rpb*!8 TJ\ߛK`2HkE/%ֻs;')G4ߔ{$^nOd[y"Ѯ _ecGhΠp&` &MQ}jؽL0p`ºjqU"ht[}z LO>3uX=`ΰeEL*~g[lk2%meyʐ͙;o@[~#HN%tʱ6q!N,*8S)/oc,}LR 0ʿJ f[-IV.o+Dջ4igc:|dԋh48SGt$jw3u5kAV)Hٷ|:pE"!}څc& ʆw(;yA@l+4n6n*ߓY"veSL:N3k§I퍬cS]:9)6DH{JYn:^Y3;mr{xsͻk-{qS&-q[gP#o5t Iw$Ns(ĕ~"4'*3$LLlBǠ5wYm+:^^c3$ɌF4VD_TN\sSr 2(31Ց T2|]QɁjyUG:oq$xK3#h%cN^Í@ t{v=;t]F^y[;U(8[ A@a =;3|_=S طQEpu3_0X$~_ aLVA^i&R)rVxΡIKؚБR.BѮN%V_"ImNIiY DU&q"y*,5a,E+-:Pd {n~tDܱ7qEo*H e]%@яlLFWdīGw>pAnS*^hq!M̘cv`5m*Hbf!z-V.k pFy,2{,a3\"H>vB 0[V>agK!!Ƃ Sw7%,i`ϑ Ftx+Y>Juh6x܀Lj0]^I]#an+ U]ָ/U(o[:b y钏Y #H-; Wɶ)|8V6I>˒L:PNe%I@s7 1D!Nfz߀* 6C"Up[i,5)L!Kd3$XŋI- G'D2!.\WAjD*?V M>//$!CqAHKAXV +/$'}YO .^^Q+ J$+t4 0} 1~HkF xӗRCMEzj}ZRBVq5(8K*4#UqVOSg5² اYj=LI 8FIv d {W'A90a .Y4-XkN#$)g)hi.IɅ|A_ LhJƃ\\y 79_‘]P(A>lBNxnn#RUE>Rai)akB¹@Fto2Q)&WQ FB SN-SЀ {r3)܆ѰY.C+ .(, 1DJ"΢vWeZ`ʍf(Np( uG\"]ONQ|/U|:13ԉt)9+#ՂEͩabjXCn :fNco .~3wS1l8B!Dźp"YPR ]\<@0)ud$/ aa1Aco B{MCځR6K%w:pv]w5}1PPAn8j BAkX& zbUa|Ǽy;|8#KR cO.3̽ȧF9Ŵ+ff@.! o4 @Eѣ ~%46%* kn|̩ ѦBeN3;bZC@u$ ]@6jl;²|1tbc"CdM\&QrzʓAoѦ3"º7i{39$rֆ8]8Zz@|kH>\a$N朠Luk'*9X]y,[NҸyYʞ͖ښ.FdقUh9xr'We ɬ&i@fhvN2#2B<춗Tՙhy\`u\j7K9F{KѴtd-kA=E%|ՒUd;Ye<dvΖ(wPW ӊWt[' ], c>Ϫ69؋JF/Lƴ-ʯWRY!Il y4(dؖB? lv4*NHؽ}ۆꔕv* l Z:] *  Zp$ m2}ZXv4!l122;Dmk'ӄD )X;Y3w.V92ݩ^EԀp7@4szr})La] okԨ4R"C68eTлƞIGWlp]jFeF^%\ Yr3LvSVPsaE㒷(Npӷ+4G} F>з@c|2lG%`|NWGe~#caՇ My*B[ޡ' oTUOL[&.2|dl}΄ c-U35++S7*Ron$k:UdںcqTbK7}QuJTRfIҲѾA9ת 98v}) {n$8"MnK싨fqaTݦmU ,xC D ebCU%@5՗Ԕ l3@sX (KM8*V]3ǎm){'$^H2Lwۣ;JPkz2{Vl&2 M"4l/ LVK8Ҙ{jN}l@pکY%!vK;^VF JwBCSJM.wTQj8UE$u+by;VyPlDg|LUvlƍRm $}z^$F7׹w341BJB@Ex.% 0Ņpʅ#t/sѠKul)8LʼC|M鳻+3K4iYx';k<ļ 1/BJbkX&)T N1{ej1yT  CU*3 ; WMU"#4B$ [Vfc(Ϥ kA9";͉ s"rx2u^ Y",nKLKT 5] _C"BJPYGD.W8Q pS Ҙ-i0z)&oTz:=yŵ7/8Biע6]wHҳ p 0@Mbp~[8j:x`TiN~5\3D)nK7*U JWX X,USDY)Qjdbٚtw{ځMU@3S~9IdN^`KxzץH9eP-f0wHVɡhe_4mP:^Vee=\i~ކդ`^Քdm!%)&A:E2~G֕ p6R\|jd[gjF i> Ud{)H)P5+'5|vůsWǎcUY9vm tZ eiC(,nZuw`K_sHQ,/z Şmo#n8xV"P`FHIÁVp h#fE@Y5*+ͤfkW5]S[2U7srSG1GKGRy'tuVR?!&F$ *IQha4'R5LuRp12ᗓ5Ym Y5SB~)v| N#^"AE:uL$dX :h*6H<$_e |SqU ۽ XCd/GBK$[揳0e"չJJ<;oR+w :$b[)s`* kDmښNRR s%dt"B}<h.NB;FY&P6t'@qȏ1"]zm$ :apj3bT c^=xս(?X;%Q*cuEZp\])NY ;U s XUzH8OAGw%6 0ݞE2ExK xFPZExb+ :񱟝3c(GN kh㵝:FY.K3omAN֪'F>cF,z#J E[-J$v !ȼUqµ5mH귚4:HpJ^-E]oNa OfȈ P8Lbe9sDĆJTҸfX%) N^Y8:\+!nKn!PqFRA`I)u^]kIj)S֥#xtV*= e>D !oۍUBe lBL6*AaLVXJ>vG rQ$Պ5Cibfippla,Ǒ ) 4)"R9gt$Ϭyh0z̊CQBP9H@zLt{Le+1tBbyFT+{n}+sz ct'mAߕTIXM`ˁc%6 &/E7"48ʪ4QEl_+ۙ|v+ qo#߈<8rPt80$62T5U(H#D:^>BArr-2+U Sڄy_ Se-DnB(y٢vw(^:V͛P `8fZPpʿ*a\/Zqv EP>:b)r(ƙ- *_边-٨ňPL1X]z_:ok:%;wKGa<3C$ o>~ή̱)+K*KX IaQEa'mӰW/d).{ c׽zV*NVfdր=Q=9[_?DB-z>ᓻV鐛5B0 cTFE֣cNfbne_PSx΄6q'c4ۏ}|BDNlmm[jΨG} q!֢cBA$sAK9otLnxɳ N8ŊsN0| vhcohN @IWL ObfC~z]qWz*z{w{%X_XY}a:s5 d*lU8^)ÇNy 2Yߥ/Ġ#V( J#C1 Я,R.|?ҕ6̡λdy)dEc§s8ۤ L,63j+We|v&oq4ŗ &ou`6IHuq|2ܶف^F%=z\1ʼn8v^!2kkjԶp0q]4I_|웜*NԌn$Iލ[g#P+V&rorvษHIX]gSKjQtm!D# L>,E3aV RJLWOLvUMNBAcV1_uNuS;ۣd ETQo.$: h5rsnp/sTA9 `e5ۛ(%ec\ ܣK8pƐ8r~UQ)wl) \rT`ey HO?7VWVĿp"PsFΨIKZf= Ոp#8*mi 2NeAt}ςd9zHh`WYClGPWŘW"+p0(;k#if♒q$NQotfj^=WYdU4LCсIȟ閰y+5ejz18SW; jz@ʊ$++V\g/8"ŸޅÂ{m/Q݉}E4n%ϋibeGBu;ԁ ~9U2o20hƠ)p]m/;W]gpdb+nUO۝5ꁺFM:p\!{jN'Lf@9qf:7&, OA) Lt?*0էpY9ieb02S|pp]+D1O[eEu$rƯ4r+Uҵrx*Bn՚ۿ٤dz7AR(Ens:qaC>%2DvŲzۈKSr%}qfʶ+]=ݞhD'$1TJk5Qu1Sdth U)zl0ԦC?*i8;guPl2n+-$dzu^R*~9oƯ+%@ n)g1'-S !&L_|D4ZnGLkلF 7`dZs d;|CYͬvgVݡm =J%KWc5p. [LDaqySOO (V}Ox1*XtU n hȀryIfvUgkEU2cEvVO ES,6"`„): ;M[!$U3" ̏ěXh_ߖ}̠PM}v\:xLrf[U~&dAAF)Slط..H7DDV5+96oѩIda- IVy4RfqW=7㷻""1T!Z{jnsj50ZK"=wWM_;Lo밶Ջ} k3l5> ݡA#5֘"A3*7nohhtU'QM0t(fm:yiΑ7Uw=6c2(ɮyg5Qt $dl@xÜtZꑯ+?r+A =-!}5㪘nkI9KR_p7'\U/;Vt:\LtH9$X2vQܹKueu=%ݪ+GSEA,K6 A ''4N[DέAݑ조vQŽl ԣ ]+[Wi@ $ҍNٖG4_5(odn+L4:s]]h+t| n]1<~93x 5̞p31(m,J9 A.l5ҔJ]xtjf!_DZV4L7AcQ-4FVG/o#7%~s]L'-O")cOMm)up"uވ8YS2@~09o*v Ic7m~Qթm6 LR.׳ oGLU4$^mO;D |XA!8CI!ɲx\8uҵ˺*Z\\=o\T9&T%^oK>6qLR<-Je]]*&X ;'ǫI/&J`:Ͷ`­HCQ>5'g|/M8C1S؀A\[wU!P1, HSۦV 5XƌAΔ;V@}Iҥ(;?vcOֹi˶~U3<]:b[he ^Q eovڝݔ. bn* ؟Bm|OؼYֲbn] jjZi)0-VH !}ZRߜ o+fVJ0N>& .3_Z7l$w~(8csʪTUĹlX4##[bՕR!9x:6qSBwp/[,dR~ Q#5ZRB&XIc/GGԽ:kbÿ.TELz$Ug g Zu+G8RvY#` 85!Z4^0B9`Ja _09d\2s{)k14 FR=]Rf̶R8&d|ĨDQ|R8e&.! ]Ilsq#96eI v7 ?;35^8sP;1~$W(H(bԕ^; 1]x1k̞vOpcl_k~NG43;Qlf.$X\Mۺv"{y׿YU ĸUv_5ک0뮝~AELQCev7˕G5{3LOYB~$"l>vT:7qi/hsB=@1 ȋYTxs$=kbôۥ&omzIT֩|YD ;9ݐ(sCnO ad诓Q j\ AW7-{22.ٳAQ?x~_7MWeN` n;1q-N 8, -K2׋E'iv>N ItyQ(N>{P R۶H*ܖ^"`&e!w}Q$jZiF3yvݖR%uGH.pk1Gၰ` F~3LQnQ{/7FRʥ8sZx cs~S9)8P̏ZJm( ׭%]cEgDPnRkObG)uojU([MҰ+Q\X_FتU9E7.x%݈Ajw6!rʌ7h 3!ܔ |mW}QB0ܤC+woErxH}&%E}cɗ2`c6W`2c A(d܂QGgw&գk:4h"*Wmy qnŢe~9i K8}waLN*P+gFH R8 1fptǟ|/7W=a ILgZ*^Gnխ1yҡ -ѽЕkɁZ6xFeul;'Ҡ.(p9rZ `IHU]iozʅ--(GaݶƠ?iwo48({VA1PY]4Y[$8.ԨDWt[ ƧqSQSkDqdyt 2( +([&}Hۚܞk#$>aotLEbcEǑxBzХyyp% !+d`q"'L?p`w0˾_x&=Uu((,QZ/`g1iDOnżl)m,jV~makA+?nɝ >KT6޿7ƑjJv'Շ8jx/kZt(0\6P6x= kPo/BŎ½Ex Pb<^ v1? xy {toI>NJW+3> )od!3fp2|sg."!P .ziVY`Gލvq]?mA2<HNcGIӟ? J1Yw J#&!ƛ?c WCg!L}8XBd2S0Ow֑R+Z[Kox,zG1Hɥ>~XS_4r²IX .{h)PģC] k?;V'l 0y֍o> 15a )Q΂eQG˾6*)N2, 3tYQ4&0m2_$72J؛gM``tDasASm mN0g JfT04׹#lDM&A5ف\G.H '#駳 Ҍ ~ֺ7ZBwfHŕ>ԣH- X$~SʗUm3:k Ǧ9ǣBH"R{u5 O/=~1%1|CCW.\Ód^i1%O?LZcVh ̴X>iE=}mnZH8o-I۸jsN<50րicM-_c8LkeSMNe+4Gǎ[#:}-v}|\W{m&29I iFZu"/S̮$Wȍ.x * D*9QG񷭣/d(BIťģ{Cx[',^W=fu؆NRzIf~{nL 6E6̔ȩѩ:-=L}øTj, ~]Uϗ[}(-=YR]QReO7Isk!\FYt[4+#&l> B+JmH|R*Q]߄UM^6Ѵ%_r?x?{R=WTD\`ovֆv_9cVs!yM.dnP ! ʴP7k *KSeU+ kG#TLljUOxMw&Y:b[O37n #UcVQ`Mm(d:wB/x,:'F店8ts/KQ A~߉z? P& GA~f H ~]^iWosA%O[͉,尙CN:鼌Q4DA 428:EVsVBq5~]_̃ݩ93>ȜVWf< *CQ DSnY(*`+ A@QE(_蕵Zţbq!z meuAxֆf_v%'$Jvi!i<ʦvO+)*g10aa($2bq#n= nz^ijr$o_ÈbnCϦ #jHPFu%0?G~D܆2SV߉=\$vK| Ee߿k`V-FmR"JЭ0+eIWGօG#qs1T+Q&hY B]󅬯1h~˺HTUm4,GgwPӂ(2$5B'|8'D$kJ($C?K(x>fS7%30}G3o/Ov}Ȟ}fA?<Чhh%HJtDnѝ^'Q/& |p zSZ`$3?5LN"MT鹀>ڃ3V)AWUmYM{*Kt2ߟ^Bsԥ<^%l;WNu<:ibz6G[$'=o؊^'Aw> WvsL)T;u1zM w;s%= _6rVwIS9Z4mSl7ZK-@p)rWՁ?U]RleQ]eʠ?di$L|#"!(ky[!0A &9,,?s&2k`XaK`poY5g)\1꡾ypHr2(  3ekg{2e==<@`] :iǀ:4ejX2~,^\ =A~wÂG6HB^fe:ոiUL١|Ԁyf'f ҄O5[99;3r'9ޭ§!KWofX;T3O@ry+(ejUD"j5pM5sֺ7J|9LT>r*gÂ~b6a^!G[ï2O}P܍2c /.eR;FѴqyZ= ֝6u S,;y66+X,j]\uxEޘWv-><>ȲʨLYy;T=J07*XΏY%-yt*晓,,lSpaTkT*Zi{ >cTP&Q{BTlB|ѯݘ JFPz8~#¶[lBUDqٯZa ۠ɓT$0"\´dxPX6΍e`ឋi>B2uwAxΨ74f酅.<+:1%QzuLh*~ڛ"Ӱ[6~@ $|J_dбM 9L 7$::GIwHMWgQcɏ2h4#[!$)"6rNg-;U:W1&e-PԼ' Bh$T/7a!R澀J:]*P?{+%"s͔@Al*`f1:=V ;q"q0HZѾ<Vi%jP}ogh\I}3P8 r *l!ֹG)D[6BPH{<6c(h4sUB16{Q]y[ '/w|!V*aS68+>V2~X&!4GXpcVŒԀEEWhW}DIŝ s+ eMAʷ79Ej>Ap}~jEsv^< 3ëс>LH*Q^ 9K%5[22dE(4D {\eJ'A@.Bn6SdMC4jÖjnQcM}2tQ[>i:> ۑzE~Wk':b 7x:<<7j@ ٚB uf_#u0#F l(V/Zu'$Kqv1]RŦ*6hs앜JG|{: TOÒ }BpQ{&h7xpMݧѢU~3(w#f~&O~wzBx[%SUn5Ԍe;~t6ǟAGF  FPbx(ԆH#gIXGSAYO%Qe$ +¶A $塝X{g0oQQR im7U'7[jQnj#% ROYb4?_ o @ 5 P~@AE#; PU8@^9B5Sn78;pF qws+e0Rxpd_#WV$[BhcT`c|6;:/*"{< jN!zƲAIOE/ж-.}3tw%@b@lV"!Wqή3. +Q]ә2 ݑҞT,~$_؃j֣׉\oߜY U+ꃃBb;b7Õ6F277/ dI8.A u#nM#ŪgZ*=BW&  "j[P/'I"&SQ[~٧"^8,C27ڝ&T&o*RHs :plb\a J AT] :C@>Z2Jc WA滭/ }]ߌ7bq_WT*_P.WҤ3byhDؘ'spbPc_;WdWs07BKWEۅuU䨝eZ+pCۧPIXɮ/-J-|Zۮ˯+ebַrt$_V/뻚Qa04? ~G ]Q,Lcx9CP IqI4z m&oEq]\LGe  6`yPiTᠲץ,TQDfBR:)TWl>quGזl*(Ì1-9/£̠.­K]zND~Ŏ6~hd{:-v kU6znզލ0T.Emt-1~y%jţHJيśQ2W@we]Ib_$ƹjg$7b:I4GtE&"4< `cca[xLONWxl%!;55WJ7:&U̙ΏQK>?~Ph>X9vn?AixIJ)z= *BA`JXT’ifs,, kz]|nZ R/͓4$jPn@^Ƥ([P.am !}N(Hڄfx~VAA١~o7Z#e NHCd^tI՗S+lIU*+kYoUR3_3}@ȵܟW,ZYEҦ =͕PSq U!rGۛ@׽RZ{$}Gi;%"v:`AdL. ^mz(u%}|VEiKAJBK T6үYbUthP)̆ QgT-j;j=$ͮdٴ `R# T/o\&Q@#rk5?ۨǁtV 1]<ސp]u\i10' NnŷW@,V{v>y=_Y}Ͷ}7^Gal68w6(I` }l$C`aRY}W咐deA|F>#d*j^!~3$19_=mIR(踚W#[oC '`b:U 5z2DUԎXwRLNBr*R%gAZ8WJՄB3whЯlt)r˷HuGQF `>WiPAٻw=~ [zl4!#}^G`#`~G'CtMR?&'n:'^]R~R H(ٙn^B  z)]Hq'F6n*iG=~7n rQAJXo)3&ɵo;e 9Tn9݈Vig%zMM{+m IyWt <l QS\:anj:NF#Sl&aRNA"n:mxҍ~ֱ|EmcbZGi GqZ0%NX!; d$hF7Vv V; k4gĕSo\jW @'* ((ax_^%QTVJ2"1*Tl,?i`~ = whhx0o}T@?BgqO77My𱱬k ~7Ek'T6޼+rl=#dnuPa5LΠn}2z3H\N"@"!L_T|fV][ ))/T\ꐽ.+5ۍ"lk?{.E:TҢ:3DP"$~9H("a2[[#>W`{@Str^AUְqR8^_!G1UV&+~|{eCl:C7Zܯ4lGɉ_;oAܵ:ÑpЫ)6 sV/λP+Hm]N8ͷp^G j"N7C/l* 7EWe8 UO; /: p[7V˻[ĨߝSŠTkg;(aaHxA6+V؀途 MP8XϠאfv:bCHwH թm&Yxlomzʙ|2[-C ٍR-1o!CZEJ;NǺȩ,{ܢ[ 3Wj\6alCo2ɪ|T%'DZD;fo9vYѯsw? f۬oD ý?c\ķH6"lGzU2)V `IJ0΋fYZ9f(XŖ$JS]_? HGꌳT6-(B wʖ+Qj\Xl(g3Pv/p0μMAeErWn9K(WASpٗ&q!,3V!2@K`So=NaZLQS Ղz}-`0*Ur&pJAsHcD: vޛj; o#NYyho4|H-j'0Q9VOW6r^ ە5l A!?Wx!8ӜR= L"4ԕYJ/cQUtbOQ9DB8qUH{. #^Րwq0 AdfX r˽JO"XyI?u 5X}[b@K{])*+ %襳m6tC)~Zh(sŭmo.O+|o gQ{YE ޅR-;{.?l2f*OdAw^aΑAQqmFhG"3'[zOtrs&0E. /Lrt4oU_ 5;^(ewS^TfO'Se',gڣ4n7!_F%.Pp@PD÷6Z- T6 6T ,El>x PAa \saWM^۝cǼAILb IT@{ +her,!lrBev]Z`L~OtO8\j j28%tܦIEcN"QPhW+(_~k蜦9M]"вi/FKI A`(坶 ]rq{>K)ל9ßb#9'x YJLs VtTJV,磗oORg$"XR}.yU>>4mpMڅ Zu"ȼyv7| OFͬESF&_-8LVaDV،=s=7Udr 1 | l*Ti,}(N~M`u%ePxpMWMSqt42Cg09(W357֟rVhTJ VNS">19'> W^S.$+<5I۲9ÉxWo֧5rPAE{fܶGF[:.dY?kjA:uEֈ %xR0~WvJJE?&cAౡ^Me]oV:VBj72RKްm ?A>65AA(kbd(.@r@$4Rdc:d,oA%| 9,fZ$XeP(ҠwЛǍM7%\&bv[* R vAͰP;J+]/vϪ~Cm},w[M܂; oJt¢v8h1VSnM ]^@Ԓ5cὉ+j5&LzQ4JJd%jgPQڙ0|5Y!fJ"UR VI$.2IՕR_J[, ^5YRju=JD0&*85χwBkT/1"JFA] 2N *hk )- &]Yꍾ0ՙU-kUjxn0J,]|4p"a7PtP:xX(=oN4*QOuoi#i4iZ׌43R7\/KGd@B=U \/?i@__;xjB亩|3)g/CEz.6֯qztG˕R$l0qpi7Jܹ3$kO >Xv٪S'~[mE JI[5!:sX.,ÕZOB}8Cn(g(=~F JLΞʶ&+iEͅ9 9*~ou.*E=jHmQg!}'y9ʠ!69~oTay4RCs.kڑtSthAd.7R Z`1b/wh&>gYGTjŷ3S]Pe"< 7tk ]:p`HYyQ!? ?~`:ZxR>t{{* alJ~8V+XlAI:1~%%;+qJttR(ewׂiQ.$fNwKed(ٝVG;i_W&4Cc F E\e݂]-W=T,$M&:nPpm}[&f#@ܺۓXʆ4< T< N4$Iy%P5XjBh?Z&ߟ%sqh >UU@Y~SX1Q5~eЭ}Qh/V,9+tTe'g_etj,VabTk3cqi\Dۧ )䟭WKt+э!4grc'oF$-:Z}j6Ur Q8K?4ߪ$]w]EtZoFR!7 \@m_IT/ۀMϾ[[DD8xblI5ϴLZdQpg~ }+OtJ 0Ic<[?t _G6L_x\i }HZ}}4$G ӚZ&1N$- A H[V;"nG=@Z\IdY\ l6p}Hm?jAyeH'6 g>^pq=Ze'J@Wj`Ë 9s+QP AI?;FN*uw1H!3?\xh]}!&ic$Q,7~ "_SKr%URP.y~KTݨ3v]T|Hh/dOKz5*V{vm oX0ۄ1Sx`3vP+=w:DN$[S%#1J$"W2q/]VF=(S"zRK[njTւOb|A VZ]fJ, d+T2U&n5I|k ä+݉`A/ExhUZOa"FS;HrM2 P>U # P`IoEnjok!kKH?I7Jx9xTeUvzR3MZ(V MmDEэ+\pMSP?>fetv(c;)Rlj%˖+AM^ J,ɍ~d#u[QXD4_2(@ yPNaW2wnh&NcՅaqyyVOTaUgwY; "QaYap3910^Ko?k'R ,j&y `ރva5b;L |Ŀ &g("LƒyQy<:,[qF迬S+|O < 9ȯ~&ʝۙݭ T^W>E29?^+j6I8~_*i sAYlj#g!_٠x>SU^Dޣsm!-pCl|]A}UѢ7芔5ۻZu`|)zOHۼl= ~FMS$#jO3`U:ŨK5zq0 Ky\+o_c~$(PSSpFրbR=sb^m`y]wR])/xWSD;ˤstQ֑SZlLuzO=XOd[M1U&>°a3ƖYkc&֣5٦ƭϾIU$EjW ]>sko2nA HՊ PX_;f$&t tӳ=ۼ17kS/}zz{ yά/>]M_@IoZn5tD\|Quۊx.o,A,kKHՄ @ ABY1a^oB'W#xaZx=LNKVF_1AtqFWt2J2AV^`4~aK'PjN G7$Nb L*-S^2 8r!КnE Pw6ID;<$$MB"=yl]/\}w >n2$ˆǤ,& J U+@h/Dj P&\=i T4ԉ4#W5EڰiRJwKۡLBbwJ%OF ,sQF݂TEƿ.MgAڧPʑSڒwHʈÉl)Q&g0 ]3O6`n<*A,{pѳ4Nor:_YMH AEr@l( cf[ۏ{C9eC}쿚p@6M=/a3 &N&jm!%X)&,* aEL3m?1|.l endstream endobj 378 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 383 0 obj << /Length 846 /Filter /FlateDecode >> stream xڕUN@}WX}#e/^_ ZUqJNm;cZP4d3;{~PtD$ ¦YPF?G" /?bU,f}]Ĉ"I%E.sL_4, 8:8XEwb)K|z2؄`8178KS@83u1tYB>7HaY@p 'MU3'| [R,j.nРڝ!fKo.+vPPW8r"54Պ"EvZʇU *P6(tqܶwjӧ.Ȟk*(p/AHP֣G.`?|" F~d1B,G*{FrOS`HNL\;7[r lt>vI }gx%F :l-f'{3YqۊsQpEupep~Vn14mf~pZ4_cL sR#t{IݪyXfGSpZ̦+Nɶ' t͚)Ld1Zv$8%n- ]c.- w3XSiQB!Q9}F>/( \UӂTL&| դJdwõgUY"EQjm5[tvhaM6,9č''&ړ:sz{o cgbHP} / o8o{[qM}m3tŞްA8p_OO)\&"ż=I#;ZtBA=YU `2hh/ 2V endstream endobj 365 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-052.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 385 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 386 0 R/F3 387 0 R>> /ExtGState << >>/ColorSpace << /sRGB 388 0 R >>>> /Length 21744 /Filter /FlateDecode >> stream x%Irݛd5"-Ĥb&EJ$Bo?nOyEfn'/v-_U?ӟ8/?7moJ&VW/w?:w[7*w?7?poױW@_?dn=\?hj~aw {??_O?Q59^ l߮5۷Ҿp=g~o ]`t55Ywmyc b⭿hߎk^gT sk!;xg1x~6[X/aݿv|ţ; #x~yFu>|_ř1zBxƃ^/ɗp<Ͼ^a^Ds+TYk<7Gx^q?o>M__z|EOxe ߹^,Ӛ7+Z/MwM5گ!zw{ Z.oϳ _[o<Ϯ7Og/yn^< CB{|su|I/Gʰ`EX Oȿvo'PŸV+ۯ[Nmes}|>1qK|hKƒ<~/l %>K_+Z˥p;~X}xaʃ\'7o <ky,x Oo}1 {(!(o>S>{r7.w3>jXr>}C翖q >&iH07V5oyWX9_)8փ&zcX/.;<4*:*kG<=sLO 8{W+C1th>/>=ֲ~{[s~y6GX絾\~݀~̿i5Wkz9|q0 @ zE݁Kq[O=-A[Ƕ3c z6OMO<φ<=ڟ\ck 0'.N{nс}׆<x8 k~nZ?AzyֆO"|ybϿ[?hu@m{oV<p]o Krnc-8h>x :߄o<}c>ϯt?O-}0֏Xu0>]_u2o_"2؛֫Ay׻rn'1>u~z|Fz50/V/\|p3?:Ώ1_'8oW|ߍ>yt[|({*BB:E'`|m5J-\UxM⺸Q#/!E{ ^D|??LP}ϒg=Mu~?O>oqkSްÝ0oЋ}&gZ1sC^>ao8o|<_x C(w??bkxcy.6^29F 0>8/}FkU 8?L¸8`[wxE;>XoXŎܧC~G k&{xqPymq\q?\cb/3>}γgWi8)j\yhk G#qOxj7/U߀՟j1Cjsj/ʷ&Ri:y 3q_G_670#-8Mv쿺?|C*~i1_nhCJ[]'})08h8B~Uz3AcܧB|rWYvꐿ\yP03p cb"}VC_T=}>[T^)߈= ^G)p_8 [ `_o]%]e <~x:e9H^hJ<G! ؾ.@ `f5: !& kJ\U5XWSST_k itO$'lZX:8ة/t@SzޠXTЏa;䓌Szo8pv.Yq6XZZ_T$6CfZ:kO.Cv5LZ:a,$Ylg=dL Mݱ R E 80v4!gɼ0{Uɼ]ϊ;xݪ鸪{A}۪m: ]ayUWx揣LLN=)AzT 6tkѲ۔yt:vNnk)9Uy[Վ5:v;6Uq&=jYyd<qUͦēєV`S/@>ϧPW2nBAoΗkh>Ur%yaCU2`W#1zԋ^ eq6NǨTz>;g+s4~G.Pg-PML'> \5E׵#!ϜѴ9P]anz;7m('RMVx'SR`N旓Xi~k7{\e9HV`48:/E0w\VA5ǏƩ=bT7=esMX  jK4l^-Tg>I|XC^yJ%uhTMñ/YX/A gG7>~Mzgz?mTj=L%ԯ~X_lQ}XFzP=뭿a}o{v9QpO@Ow?/S>B}[ Cx>T+ՋMkxgp V5H/kfՅ:~-64~cѳz~qR^h)*:"CzPy8n\mLB[yHal\>e㝏KESڱuaqk!c?xtX\m6!O ='=Ę%TNR\ TP͍K ఺,]oa:bxb^3'S(F^@K9r6y;XrX:y$/e h6á{_IG}fZ1NaN[+ËbHGEjgA9،Ϸxa=/#~$(,D{B1/5V)p=ۡS %C*mjXKê Q!̸+UAKaD,UoKm^xe[I1n`{T|u(,h7aUI˧F k?EO5/>1~Z6}=@k[]]׌v \m 14l06`#&CR7/ʄm՚ؠ+—B-J`'>[2ZhV_E4C 7o) Pk 'bl5@zbxcZ-ơ#4ԈN1&2 *dtO/;jm'\&Ā2צo<+;qթrL 0dE>"?@Wcw7j>H,u`51 <880[~)t4/7?XϙsJo`7QQ>'-0|R/jzxǂZɁ`/d㗖lo7-ޱNؒLq^uY (^v̍kuBYs }7.c߅6fBl- \[xQ߄Zc.&2wz"1PzGJ,t]0^3w 7[ Et@ 5K[ƅzuitã9 *? o:q_zFĚ;*xT`%Z%/[kl%xw?<+^›w-pI>j(,x5TĚTZkl)x|/L޺}>dw>ܛ+h2Z<;[t%]n88 iC'".DlJE<!qnJ:p5ٚ`uq߄[8Kor{/D3&3}=xxM]gDm\/<11u%" }&+7+}{uXNw1KZ+N7 1|c2"~G iQ^ٔ̇{3J)*!./rk *7ByjScnmxT4"GfBl-̄Z[k: pl%y߲/>ۑbuM",/dnZp㟸b kc@Oᙄ|%Т zۂWfkap/J^(o@C\ia%y}ylѻs0wF0'z/L(W5I҈']' `e^A웭yҼIMcnI&G7f:tx5 -3}^A蛭yϾE\8E "y2Gi`g"93rrGe` x6oq0b z^XpŏK#<}׵}0fVW@ pqξה r:& butV i!OւR PDh0Dm軮q4b:|00A߼CM*[t%7?`f(f"dflbGf^;2"I7~"@8-i;t BlMLyu>}bkm:2..-ۥ1^p&1 0 Ph^o@~N[t%]f&*1Ak ]ïTmd:+}f Bqˌ.m%xw?|7<# _7Ղ9>~'Ra|Cs82 7V?HA|WP}'}0?x=+1t;ojl-y<ᢆ͉AdIѳi#5yBߴ {ybM}sl%xw[ R`xS,<+@-WYc` N^#WY-. vxE!CW P#I2\ŞV#:GLd&2?yZ)|Es Ocn&gŸzCYLBYn5r*ꄃ DWv5<)*!.UΟw $ f>FXZdؑHi^)jC2vp/¢ǘN}ꧏ̏Pb2hOĩA0u h@Xͽ=&|{#!ċG|ugG 'DH(>' .ꕀW"*.WQe>6 M}i,qL\o7 >yM1J6^1E4d&OCѕLۻExM'O/I|kN0ȓb){%*iȷ*o‚qiaGv֜+@? ~*^Av bv轏LySZcr].q6oW04]7$#ˆ )[ojD#fkb i}bkm:2.N A?1G3/Y ~u˼oL|4oa.iئS.r[k~:쒆 օ3!@pәļ7[W5ż:5qrMn'ЀX;c \93rA}+!JdXS{k^AGjg9ndM9˼܎a I^;i =svBIyj^CW꼍L4[t%]n=oLz OrC|vH:u+g1HPHg%o[t%]OrX]S&ahOXC6xP-ɚ$S`?kOjN~ tyZ>2&4=yKb`M6tw5W]acu6OCo.郕]K}0毾 56]wVƙ#j ?bxԵAgҪvw:xcBeފ hM9˼,R S Z\=q^p `Lq\~?QL:#C&jhu߆3t+eژ(>3u뻦ectxw=p> o~ݘԮ\LEv5y%ľn`u߄Kc.IŻ3pP/b–OnחӜFDv5K-; f Aޚy3IL*d='']rw>Ⱥ/\bCu4yҳ2^>YG(Wz|1@n&4k /ɋܳwOE}=ܾ7vo1Pa7>e*aed;N i5;/U߄ޝZ- m2;1CiBki&!T=y?}s՝'loAjwb1{!otr%oB5-uҼIP7-1)Y烞3R)ox`R-Z0QЧsNݵ&2zЇnwvV84w u&rwSxx Aspx[ g2bc1ȜHӑ-o d{Hx~"׼4&ӐAǼMVte]Y/)֓Fwx<;fkB< ϢC9e8EE 6ͤw8ocμʾ[y{l%yͶI=(AcZ 35 v*LcGu kLA&Ҧ̚W<2<>3`%[>̱E\~Fy:xnYOFY;;/PfH eYrl%xw[waMz&&Ar# ^Ci:eWPy⨄avDQ߄r]rwge0b: yP~CˆWБXa{ _ur.[|gјVXz#G\s֌NљطˤoB-zQ"{1Hƀ;2_%u#{114/P#~-zzWr{'.v 0WTwXWtJIΌ3f,M^r߄ؚc.};ױOg9/*I5c/W5]Lzgy<kf[5oE-%]3ׄ]r\նsBqa[V^3S,M+^A;o g3yyv߄g-)yNg B2n{ /xK}0<oA8M9Tܿ9ϟQt ={!qѺ-ZS+m, 6"WtԌl1ן:irwͺJ2P㍥^_10@ ![ga;?-So^C5Fc 5t-7 KoB߭]r!5523 0(*X]΂t^gyʼ,{utE7w<'IsYPnjǽtЦ#*26]rw[9K)v>c&g -=jԄ,œ6` ËH\ȑ/6M9Tܿe+:lJ2Mw#HJu%2~iW| sm۞+c7.OH7mX1t]{LwtI*]n`Aёy'e~F3#2%lu+ɔl E QdJآK.r;ֽ:k׋PɉM aI?]YtZ fJ6/3%n-l-.S&lp,xT=9{s; @LOQ;y dLe-fƑ>-.яQ~lEW°}k^cZ.P'n54lO°byO];sf=7/V15q3aͨl:RG$")2_{ÿmJT"vO"Ϲ^M"L7 ԫћ{?tI^AܘGvϓ"원o>te]ng+2 u*s")c ɚyռ58foBlͱM\vhoLn" HS lŘM`*^AGV{fbި}Mg[t%7?مn_pʳ(ht >Pȃ^pf91C8-LlNRPjA5T20U[xb6/uwsl-yvNMp> iD Fm]:t7m߆˭ogj$Pv_[߰(wu 5}8;ukh>;a 9~E\~ |V76z=n#\ se(VnM\oA(Z?4Xn{©XؤoHiWPI+c7b Yc.Ļ˭9ւҸp2憗RJ7S ̃gä pJ {}_M-wi^t=Х4J ,YIMPUϼ-&պ6ηc.ĻDiܨ} ҸQ[< CbGlK^JRgpzzxDѬ^҈oQ׮]g*\MyUZ)>.!B>:kM҈o!~AҫA֢x(klm~\8%F+ zΌAU2}oAgt%]iӢx\*/%EZk WM; ͐q판"vflԵ󷓮GaHOxvw'R+fΤEcy]1nx QAtx'L >V^7!ئK.r%Sy9Щ(KtLz<XOL?b tk(K$yY}?=6開orN)8]74Hiwx'JIԜ71H[P}'ͱE\b ̊#YE 00[ pTāq"= ւ9 ވQ-r({ b@ΊET*.x"WykAӂ=NB'6nAӂ]48ւ9k`1~"6rb'E qu?_Ϸ<-Q}yׯ.pyxmD6jĊ|"  H:s'/!"[sl%xwRF~S%MI#i. 'dWM&y])1P&dt%]nVU*t1(EjAwkꥲ)Tw)ȎglcJiķ:J5.Ի6DݠHca/T@u#jDtz%-ji*9\~z-T*2Uoq \)/4>HKVu ;eb8Dkf@~M֧J|F#=ꄀm롭=/Tg*ocu3tB4skMG:I!.(O&8i ?LyBԁM]|F.B %*FZsԘRm>w#Ġ1KB,q Q~|cD08cJiķ}sc!n*b.0z2Wę G|`7LN^'w14҈oջ.k}<@2ވ+)ds],H*>%D*>WF|ԺWK ,TPY?%k\>|'ì1pnO^>'ì&z*ǍA~PQVZIwn ʺD~MM9Koroy,%L{e q 6 B6_*:3&n_L镑JTZ+]d: Z3lp^[t%]0t|DL|FfkqGn6 NvL>9uf^,: B5 XM^oBlͱM\N1:%XљY-Z㣂{T)dU0؉4艱f~j5 QּmbL wϪ[tE7m,*k=W3Q&5bS9-4PY! {@T.S)vY.6L~! 8E赽\Y9B֚i*K|=+ps1\tטYq[>YYzЦt"n?rm%Ԥޱ{eS"NxL/+6ŘRLQ!y=a)r]αE\W⇅#A,^* Ɠ"6㒜"1T&te]n1Q(1UÜi9:~9̼J"DjrD<Σyw?lT[xg0@ȫM-*^IKCl-Q#Jm;qeKŸܢb\f-a8%EVY9k"|CTm^@ ˪ 8\914WN-GSoCPM=tR KyM9!UnH[>8 >{1O rWf1LLC~8Т"gaբ!%x;+.[ e#C*j`BҡqfilV\tp.?1X&ŕ \7-ybP%k ׶;=rlOFMndv6F,\uN;}8Cu eS_4iSݽ4F|~x.m=.'6e\C@^ ZR;Gq$b(&< |,9F|?ݚ;#D ap{?t`x]+xy[sl%xwv]#B\)p#UZxVݙ-ђO)!7>'Ґor};lR4!? ӏϼ$DU/9=}I 蘏K0'}ZԊC KtWLVc:=TztC^0Kܿ2񔳫1H#]zAzܗo޼MWA0cH]K"]rw+/iRa@q~3EBuƨ3Ǽ7[ S;ؼv}E\{TLWK $pEAd7/Ι0Vp3=B^CӮx|껧W~&qwDb6wر];y g`O C1͋:l-. Fidb~O {.̾'=: ˙PfL̄BAy&±E\}W~qU]{f^yqϾJ9KVk .PΚ?(oCTP"3ȁطT~5 Sc.IŻTP`0C&Q7r# wp$&M(u'ļ'u#|t'tw<[q9t02梃nem<$3~)Gwhl%pc9CGK9fkI\PeXodG .79O2+GcbY;NCc.BΌ4n5q߄ؚc.ĻIA~Ql}Fd 3Ǯ.7Y+ .4TO}x5'["7J]cn&0J5|혉`uDF ΄l-g t5400J$oU}([.&aVh +7:tIl&ozCy Y VӸyIq9nͱMOI鿒ۉ8#1<_nc MgNyd+4p[pgr%g]rw[Y̼~#[>"šqg~h iA?0iK䘏}f^D;1Ǘ#NyTD&dick%ľZ"ҽ}?tI*] ;U, sA5a w*8>RADDa^Aϋt&o$ƾkGyl%xwa$ -voJ՛eg?L%^7آK.r?s ܙvc.)?4<yܼfqaꡙ7k뻥c.ĻƈJe"OEԾ2"躔t !&dL`S k*&񑡠ư&{e7voWVؓެ%^C#CA1/-tE7M2rR[[TB8h\)]*_(4wɋLow{5K-*&9Ѿv " ;_ƛ5H@PM#c1^"7!ئK.hw"-\01NCO JjwW!8")1Kބk<杈u߄76]rwg} -䤳Z0;1O r`FǏ.0{FzXN1|5.j /NeLd?i;F@OßNsuN_;f`5jtXBANqIdzI^AbOռŅwc.Ļ/O??|}/?7|_%GJwϯO~??gJD῿ ?j=u~_D\õ _ endstream endobj 390 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 379 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-053.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 391 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 392 0 R>> /ExtGState << >>/ColorSpace << /sRGB 393 0 R >>>> /Length 5137 /Filter /FlateDecode >> stream x\M5m?.ugwom!g^"xfBr1#霣6YxK#uWWIU}~z_wy}x~Oͮ4?{ޥzy׷[8E._j]ϟ|33#~/=O_{O_%hWiW߭>_g(~؟d^~z_e-۝l݋I}iΊI>e K)|jjvcoHe'/bw߿\n#{33=UXJ{X\d'/bwޏ\Zz|_u_Gi%5Kxe.͞X!my+>0c@~vMj>IGni?nJ{Pދ?ra%ҔwnW7$زi}O1iw=#^\>;eJ}mpmXJWSc8 b|wش;or[}Yz0(l866nGyB="q+.DnHAĤl۹t?ƞq=qze! l&i~熥4J]+kNM;yf.WyϦgw>Ol_}BX3{Bxťp FLYpjwXMΪ ҖBڃeb)-jC5 iK$EΛ4ӯQP[zH7 mwhRQ Rxu{)kn_ƿ<:+KX!Kb% k/G[!mLy#jR, ]c4I3j%~TXJWS3b =flɋ؝r9~r#?b-yzXma'UʻYmi^q)VdU_51ivߎx}kf@l<:V!.)Y/3^ta)o\MM2՟A W36E[\XB.sט#Zo;gu/{K ߸{`--Nn*67sQx18^$zy4)wP3_dN K)|jj=|YK!jƦy+[{g2jn-k?UCZNIoD$J4ƒh,47%r}f.VlEgL`^9TI`wCNw:7y5H W36E[Xblrk?`n5S)0rCRij)ش7J ߸gb`'!)}(ޏ\Kmӛ`w+i'/bw\l;G.6Zy 6K3As\\lV_3w՚i'/bwJ{<4}1bs^𶰒sVXw^Ei'/`KoRRDKԬtRJ5+֘^ ͒f+ qWҷ:ԋ?Ϯy-^cC7 ^N;fxa%9|konY!7b޵؝rRaSלVF;uWN̪:vy l+d1i%=v |v3ՊI(m)=X +)|oY2c2b>oH["5MMtmhâkmvۏ{j7/r]mj3]|Vi/`-#Vʟ`x\dWb) w]a+i洠\l.eRPʿUuGKwO{co<{JMt@(}gi'/bw-C]sEf+Bͷu[yb%H3Ӟ|iQa/`ĞiL?lINcI}oK)OrR1'9v"v\jjEÉVJV|#VvΧ?YJq/[4Bo\MkFlɔ؝#_#m?_ZƣXJL<8ϑoH[.i'/bw̥EG*uj"v}knp!QXHkydLZI+h|gcJ+XaF~|3f4/Q[MUrƦy3 %o][Gkzz6y:Ol5K)|jjWȑ)ꈝv"vRXmfWX7gc[@s\\>>>>v'v\oo 5#FEoIWlAx3}J ߸;z;726#mG+5+EܱbmG|dWa%VjbWJXXRl orG߰m`&6=gؠwE-lIK)7SЉ v"v\.,xJO^;+.p[wRX_78 S÷R^[ ܃+#f\$5q1y1sQbِĊ"<IMmsE;7s2ɵ.Ekm3s~L??qr]G';Vn_p5QA+.#C?5wTNTݯ;+84z|RWSFfx%1D7:=>b#>VRlj/o-^i'/bwe4t&1l1Pd(ӎ a)X!)k*6E[Mc]#z9iTIZz߸Ka)|[v2x.k×3mM+{a8#B*(ELh TLZGcPWϦQU2w E0[|ML,$Ԝ5"7$\ش)!u׺  Caq Ae'/bwx.`Aq\lbhӹH~ J X-v/v"v\8_ۏ-D^Uܷڗ!r15(,{m?*6loj~am{վiXJY&WaQ}[v"vx.~ǂ15%&r?\]XIG|.6nsT=;ZsOorWlIf=<ԣ{`3{qOl~bXJç&ĢڑU )6ELK̷Vْ(=bR"+6s ּ8R-#Q,[26EΛ|VoJvMBd|Vqk"^s:a)}k/aK45]Qlɋ؝KfIj֛?ďDR R{ٛN"IjN?#Ŧ]}sE^gTN|h3N6T!)zlor7ܫOMd>+~zi븖?R><ѣ367sgl{[(X+tGWl8 ?wy`>[-w b)7aE7$ش)̥E&Nqg']x{c(WdJ)8uز;g.NVU'J,U'&^aQ[v2%v1֢TSq>z>A4b5~g$^z(ypM=xƤl۸5љ+v&pĻBI{T/]}j3Olt;M;yf.Ϯ9ȋ/Ci?hTXJ]_Υ9GΟ{dlɋ؝3u:8a?):UXJy:8aoN[v"v2ilUljV B=~l%+7=ɔ؝7r9*JTN9 :Ax56ß +_X{ )flob8O>ܣQVQ$q"ca)M _۽N]{v"v\.liI"DEQ%Q5%qrI"E撢 p;'Elhm⑆_ē"6ㄋm:y-"&dAtVjl2-GR- "ĖoH[")\?S>\~ؗq|)6b #0>5qN+v{UÊM;y_???@bĿo endstream endobj 395 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 400 0 obj << /Length 877 /Filter /FlateDecode >> stream xڕUYo@~ϯTo<7ʃ$i GH#Uz;7c" ?LeE4[~Tf?"ujw -IOhrahUDe;2U<_4n4MXç໇[3U8?qGa%;8gq[3P;$|ꬦIY3 6~֌ 8 dvGqĐ{BLìrYɵVY3i!@GbrgXq#<c)XKQk5l/\G*AOЛ͉{+xG\ge /CTӱex9& )T^f3@H6iURt>Nŗ5 zpI\ DMfb^@A 25 zĎaN%j[Q`djcb3C[ ^z o[qڷ׌v9)YJVmYԄfHOM[j%ka zl=mu33J|~ڎ0V*3=9z*if a%\*yF&ϼc0vImo*I7š؜dIS Jgîc-(]4]|L.6 exh+~`y'aKI[mXlnj*ji䆾5>!F=̚u^ O\V<.?1 endstream endobj 380 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-054.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 401 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 402 0 R>> /ExtGState << >>/ColorSpace << /sRGB 403 0 R >>>> /Length 3479 /Filter /FlateDecode >> stream xZˮ%;!H(#^D#!uK4%1@6 O{ڃj])piᝏ_oLw9G=fe/}h|?G):yJ<~O}g~z|_+gUˆuh~|8Ǐ|Z}i>(MFzO<6yǟ1"y\Gyͷ--c:ƙ2[T_L#딡s6[jU=Z<%w}Ģc$r.d J0-ZׁElLhMɅ\ĽlikqwɃk8рdB8wٗ^s Ѷ q ̶y]mcl7[TPA&br*Hzz925ZSP+sۖm"mm}2}~HDĨ_ΪLG?W T-$qΒmyқ_4/Q=_%SfZb_Lf.A\qDq}Gn<5W.ZH gn[־]~9w,D\=u#(ҜA1A5TVZ7#Q D}><%wcsgF@LSf\z澖43~ˌ?mCo[ W\8j6-ohuXf1/vZZ}ɿҮij&ѥf|Jǐ3r.m[t@JtL51kȖWۇn=غr/"1 n+Enmqmz˸ߺϻ)"uo ]vfA@o& ĸ ),$gVַ/mcY9r Q+D>T?k}q Ѷ6d -M0OطSrwu,CvƎw@ئ$ rDz|\5I6܄ 6}xJ%ܯއ7\VGgz ^{_pA. IA .Cmz˸߶ưNj&$oŽS~]H 1C/7G iq+lخ~׎Mo~w"M4'IFbFt;#*?A$4 V]ϒCp Ѷ6 |D}<%wKZEBV$XM_ѫ4H@ydp;whlUMo~w";N }J#$dK*UCZbY3drcqB+*"KNjZV07c'.{5Kq`̂DHD @!C^1pd%aW-}2WX*VSAg2ᵼv'1ڵQy .? W qյЪ{mn ܅Xш.}R"/pKz>moO.|QH<8l_~C6% + Ve!-2]6f,ny}><%w N$OVk)<-7KB')<db;gmEZve/C%.\'F,JGYp ѶDBԝ+VGsw|u .`o *zb"lu$Z,m=֖̓><%w+G|x[˕ B:mz>m{kJCCvբoӛ_S YKOZ!@ijF Z [Z|н?U؍kj]$o}& lԃ$DzK22s}n`}{)H(]RQLFxˊ!- (Kmm\ˏ 6}xJ]qfH%˒ +Dwvd֑~8 F qBEߡOsqwT"RIVc i9");m{k /aS|zO~R,TENrCL.ddRx᭴砬dDMelvJMOӪ7|*cZЅW[$.gTߜ(ٛD&DVVAID&˒`辉ƝBpVIsy(AK  ?IB 0Ov8OzS7J0Чi=6_;D nlN7)`Qv0y h՛ΛfU6eu|M]0]'s zbx #13 jZGV t^Us@tG櫹 |HPŘO3}Ykn ‡ .7a{}2G/!.Ld@>4n<y}5xw^S[%Цڧimz|MZLvHπ4ϡgy=W!Bm܁M&ַ/~?+ӑ Z yezM&o, Xmu[(lŭ('#3t+Iѷ-^kW endstream endobj 405 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 396 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-056.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 406 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 407 0 R/F3 408 0 R>> /ExtGState << >>/ColorSpace << /sRGB 409 0 R >>>> /Length 21848 /Filter /FlateDecode >> stream xurOR ۀ4 7m Ɂ>%Eo5INN^ź}Oߟ??~>_PO/>?_9Z޿?7?U{j_mWW~ÿ_ϯ-߲wOٿj656T~y0K?:oJj[~>u_|jo֓񫴃ԃ:Ŋ^zKm49[iJ|~?~g+LמqO{JURճ~i)Q7j;ȿEs~rU֧mү]^_~%?YRym/Q[ x߲ۯnm_ʯ~;fz{g|Ux^DYF֯zBi[/}og>Cv<:oB~M޺B6J/|YkKiFD^/7%_so+[ˡ$3zv/W[BR&7|9 y(;'_k6߭~{>֕y*-LNx>Q`Q4QӶ#/w9_ttY藝ӭ6rz_Ow<ʿƭKQQ}|o8/ݎmb4ޖz|6@h4mD@(w9{ʺoEq>4;i2~9RCϦmFՁDeς8#Tm45#mn=gOY7Foy9Z;hk ahEWѕ[WFir։T{~|7_o~Dg:R͎+鵣) αV<#qV2]Us~6suoiN$F~_sfq4'zw|N΢.%Y%=,ݶPsu~[΀.Cn?ݧ})W]FѶ#w9źo-FmoWfl|6aKلлa6O[QFiz&DѶ#bݷs%ٸj:n\Ѧ`"t,[I^m"oY@QbWВjLqtNkE|>AXFir>ugm4ޭ?vpNcS6CZMVSAo]!o[ܛ=ru~~ˮ*8/_ ΫnK 5/ֻu%~6Q7ٸGIs uo9'T~A=m{c.^qk|wy(_dhJ|~o~˙3g>,6} =?%QrZQ7Em4ޭ淔nh9oo\cڋzP9?f[ˮDpρg$+Tt/:&maEz~W-Frq3Y}Ps(y/k.%u]mG(w9źo-xNۮ geW}F/ى}l>eGum/9*mnּwdҌ?ov>HBno<ƈE]wdj;Ysu~k^i8/%;%qF Yo[m)%za1񯺇 6Jz~{?Z.-φ@r}Dχ߁UW(Ee*Q7{_voѻbݯ~?3`cj0rmڳf 鏞U1n] eF|Xm)~[2mD;eBm: KJlyF%JFAQ]]$=/~rh|nѣQ6_6d%wzHι?DcyݬB6JaB =Ͼman>WPasF?OV#!2O|jk#("I,nVX5O{;Gs]J^CwW[iTJ|W.U=$ (*wSO dpRM*v,v?4m:dqU[L' x(QQdTIrh3a7^﫯WwC nv >GOM9@`=FN=EX~wٸ"HXSIb>>]`PQZU-+uSOѽ%aJTwx\wtB 1iHO7#V%PX/ԕxޠWvΛ|Nů_vt%>YaGt<_ģ.Fi2}nqPsu~[ϷKڠ_zҖ_V=&"sQ7JWڀ_)6su[>vQ؀!:T*$/x7:B(]Xs |ޫ#= p1gڊ_[ڡry:l $U[_u֖~  tw9ź_MÅXMlO,Nw.z)/e{% [[/}o=Du݈_FbdW[ ͨfWrBum/^uhۑֻ\Bݯ~K ?gԞï\Bf&?qD="N?@7z^VtS޾J?)M ~_DAX-&X/3xn[Wy_аaymBx[/귔#>X(GK­ Zc3vy}=7nJ/[m w9oE\PRB!~|Eh9U fϡU]&BRL:u]I,B/}mr2u &ϰ;j~:b*d{xQD ڭtz(]1]%*6 u>+6daGST؄ ?Q\9gYJ,8s%FnRV=5%y?}[K:fcԅG/f֔Ė-&a$~>i,Px`r% 5A;7B}K_ġt%0ڨ.?1)1e%0kK,s+F b,6mb3p·Mm&FL)psڰYAu-vV̮|]b<2]PGM6|K_ |s}#P~|% yS\ZڙDl%r[ 7@@ķ 7Z !ۏ=Va_VpuJ,Pl70 .>fvU(0n$[<(PlcTq )σ6Z=̐l~c%Gzךᖍa̙ p sĞezm( 0/ć4k^Nm4+V.Smp=(~Ko!~e-F0X9:엺I^8E8b¨Da6_{nH Dsv @ŬϞ3JYxL\\.[`5ҏ` 1U%1ooձR1/y6N!m%F Pzu-&ژq)7Tm K9kH2k_Ć rkF+An m| Pbb& &#ecaLQX$4%}>Xc9b1bCTvYVak<:865sNx][pݥXg^rsdU*hc˞mlp%(o1M& .t Br} -T.FM(80mޘ |-1#f~C9x~.i)eF 8]8>‡%G 6=n*$U#[~"۷؞o)nջ}7>]JW1%p )jij̉rK{F k57+-wqrum%wE!5[G o }˙e=% ?uU4I 2pPbԺڴ[qZt ZC&ݍ{ cbB#| Rʉ6HiB~q F8<)=l10Jtzst-MBqk}F垉fq-Km/"@Ȃ/N;y6VF W˟sgߎۏsZ Ґ| QډcnEKu2is KlHS#f. |rjlw$VBA/킛RXTOn`kuf|2D(a + >ԯw28GkS%&XyG g;$F gUY [>~Fzяӳܕ RE M%l| K.4~H%ap+Zt %42!э۹Msd^Ʊ R8ϐnT޲%.)񌙫85gׅDssՅ" zjNB/^`0PyIC*L6y.jy A bp`rgHY*7=n;+%6:-)>I-~lVu ƘQcN]3gxTÜEů@>%t fcC뗸ۿDu.I'/esiv,gH`|F}K߷ZQ(S[}e&0Oӏ49+'_j~rN]#c ]a#NmS?\Q> ^X],RnMxӭm|Q}\<_6Fncl6=l+ w]. QoқKקR-4vrK,grpyȴ z s#ؾ H~?aB~~tt}?t}Un-Y[ȏƷ^גHkQ!j"Xf(IwjjCڸ4:A#wbpasx6Վ;u!l%Մbu"ku7ѳ0psVu%d v./S% tNخ&ѹ,mcAÚx6ng;1FTmvhTqLp۹vCwbsV1`t89C42f(?/D\vaApO P*h"(A9à.T{]RrŭtIFvM=E%Se@4x3XyQ.np\Sir֘:o#7 3vjEZ@[x˖d[iƪK2SW]臫QLhqzL?~85&@mBrYt ? }`_}^Ą%(oQKs3.nh`j5p+ ~Bլ$oiJ5[fZZe 6 MmFCu3ԷS\_yF h+R֘qט5~5=TjwLlx)SxIXwB;-6 vs9 p[c;ٱYۧܖ})m7 YR b;m!. $%\МF]٬΀ `p|O>m4y@?F _hQ :z7\S- zQ]!.l F }k4GKj^F 4(.m*dkbh.)P'!y L: PD tާJ xh()1"n n>S _C%y1E|c^ZGF N1ZӞF+j·7u0;[83ahؘN8n tVEXh] L7i-4l-65lݢl{^;; Em 6*F50y@X+F>EZw'u72ow^yר=~M!FfB~9~z DDz>e' +4# AbplƝn!l6fFOKmļOb^<>}$z|}Oc& Qѡ}oq)!e?מ`nPK#l9n:ݞX0 y7q7.xNiWZL:9-Vrc] njB~o^qVZ?jv;ԉ%~Ǯ <=xz +Kˤ~(nA ~'W3&&]7Ψ&/\hyx;p*]3Gq- 鰀Q~rzy }Ϲ"]lc%aa5;m]q9ag[OSZܞD a8Wk׸2z2Ð _ 2)mk:5_ aCb7(Vf3R[ڔTQ~eghE=%Ny;6.~,X czȢ{4_!Q?L(SFF-".~{Ȕ"/c-oS[> fS@28ۖ𭶯KВ[ghg5`k ,!֩6~،5E#86i!(x#dPj <[tJNhF HvrBEdk^YyEEҳ+QvȀvXoa 9QM`&[^X0¹J'ƠEܕ'ַtoXv-k` \'n|_?fzno7i8osx:u z b8b2ٷYdk#ַw LO#yЂ}k,y##wF #Y1"WDmFuAC`%'Ƀ<ԾFbSvA u903U7 ݏXǻُX]P1?m!ws~w{!3.Z;I_b+mѽpoAѱ$۞ujWI!ע1 U8(LHwɋ ,lKᰦ$2I۽EHs3֏_!ǽq{Czx(1]w6N0 ~;lU1A/arO!@x~Zbcd9bfuk}b_KlB'Η;|B/)Ҁz͓8'Yc^qVC_sȽ%%44qPx![\5sԿ};l5`eGYɴqYL$V!u Wۀ<6>-Rp oRbR,؏sm* v !BBA/JU̜ma$ᒛ?lxy1w y1d#Da엾S1b*촌[6s*4suZcV-RwD[z߁&-݈wD6aWXmXÖmS|]΂aQl؟{i_fnקY4wt"š[wnc Moڰտ7@#(<)ݝRp-e[ı ,m& [^ࠖ*֩Ʒic-I/pP))lc_`z #QbUaXB}N†D{A-;uR\ â#j޲#{s lm=Wc@땯F,Wn_gT gsFU䕋3>'B@B^RYOxa!{xQ++X=l~f#=:SX=u 9G|# tpl L6Wo߂߲-@@ȱg ҁ(yBTDj $j'lМJ ƚr@e){ƴϕ\_CLt6rhĒM܅uuYe*m{5Fvd'׈a ddaQ>sw"" f1U }nnVG<=[8[CI^2}>ag>wR#"2-ֶɓh W܁*x\9Vp.Ge*܂y(!$W(NO)"7Jh2mXFLY۰. pXWH]A%GCy+gR:Tn>aeښ%R#'qis#9-9ZSTxKQa;M= EƷ8!Le ሄ `uw;f15c-Nƃ8X/?<#ֲ.}-ΊBV"+kj(ޤ;xGD)og1uSFYmFl18--{C-нz !Z;c{{/\EBl%m9uobІ3z$3ބەJ%z'bh|N1RkK[lUaa3+ #5hxr_cx͞l -㰙y-RK%xȒZJxЮ4D A~Qw륧V^z{—D [TP_"=_q/ɯQOIQ+Ck>VVǔ]:ibXʈgeژ`6fpQjĀWdAlPY u+QTzV 1oK"Rqm51J 7U"jSFU*YψZQ7Fhk ittOEXv#Z#"*Dnho͹V ̾s3Zs+|_2yO͉#̩݆8AF{)bpkK=uBѥꐯ?~`8!78{G{T9@9k.MLzC'k>A}c[OSty-gIL<\% { Ui[WdI{Xȸ.qD u_9K1\E)PK3Jat\Y܁R,`J<[b7oh=EWζ鋈'slYA}Am{N柡RC8eSoxeTb*>]b'oPwj z@&Aշ뇋֓|-f ~)#E:eQ8w{I8Z#~PTSX=]w7`!`!V/@OLu"/:QAq_\DX%N(3Oc :|wI"ԅfN}t8}a>AC?t]yX+B;#y>s#9Iɏ+5l@W J݊byB^a6A-з\ߊVߊܺ);O?s[bUkb#~֘ixTĦ}c&g£WnC\ͳO![ 0΍K5lGYW6UYh.V6*6ĕF P(ޗYRdk00[qH̉inM5MbũJdقЄ~5F}WR}_eHf_ШX&+]mHj4W.zUw~2d^ru+C&~d\!1׷ߒ65Ն`}Lgg},|-6z Ls]ī94~\Iȑ l3%s_[: @kh {#޷FPqЍ xr:7ᗣDC͈\tQƝ?ݡ>S6cs~ͩr~>'ڬL"BQf FWh:*e$&)bpo=#S!4^K "VU,]xŽ*pS>bֻ( qyn_2ȢRµKhmY|\8ӏNbp`9 8ۑ, @Ӊ%\+1plCN'bԴ57*ߟI`ƴ `&v _H'oĚ۴`6>m>F k=t nHk8hI#1Jx~ kfǰ^}%\i0Bõ#hÝf7E3r6 ފCl'!D4#*DZJ;Rz)\Moi)$6wZsDg. (%Ʈs`WkcolՆ  0 qqTƮ`q"F:QKqe؂*6b/{X :/ 2 *j#A\ij˿C:C"ַdHQ0/<,_d{"b vm:<[\`,KRln׈ 9֙Yk]ubX Bj,D.f]^"p[ e7c[s3(iuoOZ^h$פJ uE?|uz4e8Ae^;ED2S$Vy;$ P7}B`1vxdZqC9<'t]Σ}Hól~߷\nw?{M!dbs~#M/؀#r'P}+z1d(~C+1Gc,w"]AQxk;;*h!h՚M <MN*ro>@sge-72!_{B!LE׾N3x9MQiz#R2*Q_C$>ώtCeLjG7>hU?WSۣλ>Z߄53]=ȄzA)lg{EG@E_a 7BoV7Dx,^kē6_Z:"b_rI#A#$c08O(7LȴsҐo~1P?;3TAneB.1)&3z-$Nv38忮Iqr M q~uE}Oܬ1ͱ57΄'&9 4~+n{`>Ÿ8|НJCHOLTz>2XM =%Ʒ{+adV}?ֿb pb@|";ܑ_7];~dmo&翸nlU?w]{~RyS{s6c(Uog4d3alVv$!5- `Y 7}>7Q)W$ Jx^@"uNZ?@h?pJquvP6}l)ۂWnxwԯ~auFd^cv|&?i`Dž[90q~>WqêWU3GMpPo&|߃-o_PևtGZT/:B`h,O6Eߚ3D;>N:,D};[FՍf݂sFp+X?q~a<L_js~_2a]nG܌/@Zjzq"S󀱳AEDznt>zϽ|mJhۍr z{e7 W܏Ya~-q m@!_\5b>We>SUs(XE[^[qoПҋ;5ꭢɸ?įzs)}5F3P>cAa gG3 cIaJJZ(j|4/}Ra o^uSj/Ϙ. ێv]6lٔ~+?z.z!'?GI b8Lȑ sF/X_0g ؋~xb-3a,ax|X>3}B1kY']ЫG|:Ty sӑC a٩<G]5< E:hh> N +,,fq$ x&hbgRO\*< p wbG y^G +ЖSP,Q4gn`n`X?uAg:y9,or  ͩ-/jGs L؂CgڔjoYf·ިZ@^}Q{GJf= {V()!VH6#l^H p+T Y7BF+P ycW?$p$ 6` WJhcuzPuW&,ڀ,E!]jm̴mb2̲Lffi{ɽұ#3j9~L ?rDZΤT(Z;=EI|>7=fB'=fBHI|c؈Q;395/?Ԓ*1һCE)}}֏u9)jj]10$) kb^2R\󲐀7IL୔Ny"y(JbzsFp-G`'F\͵.6pSRGXK wg-<>Jpt;[vOXcV5➟wLcZ=c )QH ._#'W>EaS!ڒ[O#"g?)}p.ߍcZyȩMF)mGI9POY%oa iyLpxƼHn2%MqM~[|n)Xsc=3֩`cs4a l,yb.62(@dK%ҹ$~6(oGEzntw^Lc^yk,ڨXcOoypmt$EvH z;gd(}WHm'Z{t>_fA8/2`^Ɲ6yԨyeUvY' <+w7(PCk]^焗~!K? <]1J p$R yY g^p[t 9r^:ҥcԍcpx18E\~IW\l=v#1J`{޻w3'QeQ>%]ANMCԮتNu:e^N(y!3ߠo!{V2Y)|JkeB@_bQ_`O;gpJZ䶴։N9%xBG*X@]`yCYBAxt .^8G4KoPC[PoS8Y[܁zG0ȸ`DtΑs뻁m.Ho7`9̚ó*0Z5q;O7BkqH8DqFp= q7K-@ey]bųf`B9q-.)|VGzUT6L.^ QFiRP" ]9ooo~ov?b?O).1 ӿ?9_/t^({HiۿOPC endstream endobj 411 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 415 0 obj << /Length 1331 /Filter /FlateDecode >> stream xڭWYoF~>P@&@H])#Q dL9n;.Ir F\|sP/E4MUәr.3>hA&xupnk{;Z,竳YЉ*R/V۠JbYU@kV/^f"HT9 bA~[k`\r_ 9m RiXt&Qi!ߴѺ: ;Mvn ,ECTiPCJ|D]bhCI7ra#sZj(Nm _jPvxBkRWìU!bZ/B6\Vȭ0sس ZgSMA b]p'"E{L1u+nv/I6!>G^_+'~ #Ecɹ;<Ԇ&1y'hLodnͼޮdz.E0uJM%G҂GAnWa s|džӸQ`fOEV}DHTdpLNvtnC^7i:{;+'pF?0r9[{O @/΁V@@H!ƪ$)O@W2(n'T#? S[ n77bt-+{{f~d^O>#$#KAzM F>8I%zU_\8UDs> /ExtGState << >>/ColorSpace << /sRGB 419 0 R >>>> /Length 6748 /Filter /FlateDecode >> stream x\K$mϯti廲^6 ;FK c^ڃfudU2#?~z߭}_퟿{~)/돏ܞT[Ϝ-z|}?~x/6Y/?Oǯߛ孑Z约jǿ?~^~.xO_2/gr/#,R?Ձ(rg+s!Zh=Ϟ~<%m%~+ mۑ_mK~{㺾\WZ^?jV{\D/\ڛ[ߞ<ﲹY@~5ۦ~{{Yo1-=E +YX}^Bh/5<cBTK~N/!aubi"\!LJ]"a[WSbY܄a!@~5vԸ~^V@jY/@s&DޚmʒB77Jm띸mыXһ_~+{x/g@$ug<-r`[WCRgsIm^~9oދu#cKIZ_Yh =3L\%%N:7Hێ^侷sx\W`g>Gدso d]\e(~zEiqFؖLie]qt!e$׽ q7%手dۑ1kzD4I |a"G'ߞK3-=B=wƶO=ֺ_- *sF #lQqo0D3b-8=m;mSpOy/ed6{5 _m\3~-Bhoi~B!0;W 3Զ˹~kW-rIc?$).4q #) [n ݹ$c 箛mG/zbmKOr v#x]|v;Y0SJ_:r~5%܅ʶHQ-==%[{6rrHr_,A*zvsEX%1^$cmӜeMjW<)i>L%BnmtlEH!}5D!)/D4m/ȩK;$ЪݰPv5G@ IBBʯǶHQMrʑ _sdJКBу)-y-%*HB#a;+s_~Bbg'KrYQ/MDL!/LI%ո͗[n{?msI%oP-et7jFk""%/IZBjDn 'M bj@nmSO=V9@\1$Y_m;R|dmK~{dv- MH^;KB?, .ѥh1$鰸Âʰ=mSO=c,1'oͫ+^+XH^%CGwn ɒ۶#Y/~9/01LHDZsIxDOl=BE=2$fDvVv9~|Xj))VnKN*Ү͵cg%v* n©l ڦ><uf4KGߧ+}MD~>Zo$ͭ8m mSߊ-#|}3Ok%gI&E>/u5$6]nێX/rO57{ޟ06샮٣L!]VJ J\ߨjzE1ns\+%~C yc#.D{֣d7;~Tض*F!Bb{7VaՑK݌KKtH n!l;RfmK{B/m!ػGyzùH{+~ΛK}%WVrm{өv+qlzCg?+(lGTԇ~shɊ}JYhUZ9@60<5/s~jc,>ZFC!>] TtJI‘1϶H'ֶoɨںoPX>B/"Ko}2@n:r%8rѕvb ڕ}$pXy}nl[1[y>PTk|=0)x`U2MWЪXmJ+;|!Ӿ>^e*!hspz\70ŐmR+rU'ku₆R5g`[66a69׌Z+ AT9阬=}I+W-XQlZp+^lWXZ,9(q+# fjZCYͥk_멕\(]ˏߊPVq悒' z=_u5mT;t\d[.n/]sN( ؛ 1C=FֽۤqNI%}GNm}|-I^ vI<7.Kn+TԺ7}ʧo'Ktkᵹ kx,8,j85)O/U=_~ǽb}*80o2 \6G8N9U]+"/jVRoZO_wIM}\\ J&\ +)Io'R\j #/:`mRސw])6)`|2ě;DL퍂_x! ykܪ^j^dM1VlnCE{cXܪ]N!QrپLmKOO=fV@;^4Z.|cAꞶ;Ty"X4bkx.Zm/~{ŀ!ASr(lzJ%b@I d{Dw=潬&55.Brۚov;rښZĬGN[h[MC^/CD/rO9^VBĦ앦GvT | n/+lwmF/rOy/vאJ4ދ$Ŏ} ݞeovHޚa['jJUFp퀆BhzEK+`qBn@,>sO% CmnG/]6o"}s!A5tGZ[[6O̔]]CO҂FhzE)$Aar[:JQYV/ڙ0D\iX߂Pk-ێjo[zKouOXާӅn/>%}g}_\m+I?KKmGwzKoJ<ì~7EUꇇ0; vv|mS_Ȁ{2 s./_KHḦ^x1>:@p": JRݴG/rO9^%YxH=4CV,~v3|S3 JzEf2hS~Á E7v&ItK53c.M (;&Qܤ_~^*N'<$CK u1XA ̈c_MնyCУ7#ߐ4 .]umSO=ֺ>[)A)q-bkaNqwIiM($j[o%}J.%uȎt{/_XLX- @~5ۦ~{Pf傌%Au[kRTbՆ"vGJ#@.QW!}sɄ"h4oV^Ocy%%^~vj?FTޝВz/!W(Q%Uڏ`lێZ/r?{V(iEuW]@VVVya[-;x#DW8((Qpm^~9ocBź ;9YH>v-=jK5GQ}Gfjq? 5d,t ~pȟ݈!c .QOZ=[ȯw=V^, -(~-T(P·֑~6BW@.$8S߾)T)Խ"[KBB5CW!kcX)Mr }Œ>_~kk O 6?\VzbIH3~q@“hzEKl k %r_ZQŷCփɑ]~HpJ߰TmS{>5X BCqBih n_Cc{7% YZpQhzEV51l^b $k =JpI,Kc.P/rO^TNQtuK8Eeͦ(:gO%Cfࢨ,lGYM}x b~lLTjun èUwbo,CڎwU]j풧?XuZwyV ;rp|~&^K['S|*ް"C!ڤֽ!U &_-le& 5kWvZƎxܕ ꈏئ y<E~ȢS FT`MV9s}[`<jMjx\+RAj P,.,50[F --X$B[2ZͱBMj^n)?*}uE`+Dwco': U]Tk8UJQZꧯ< [C` 5~y[OΔ hTQY6uo;|ód]}H|hKX<I?FEAU~:xȦ֫;|#vZQl`*X:B ]ۓGPu$( jQ-ڤֽ!U[C1OmSH> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 412 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-059.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 422 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 423 0 R/F3 424 0 R>> /ExtGState << >>/ColorSpace << /sRGB 425 0 R >>>> /Length 40039 /Filter /FlateDecode >> stream xͮ.;6?WݓF@$4<0p^m؝ H>һ$CUIEQ׿U~_u_{_]_ǿ_?o_O-!BKׯ|o?7o?lꢢUo4ɰango~_Oa@?>V}?c> MWbrQ~x_k(nI'hy}w-x𞯠Z|f^ eG|lkq^ u_mɋi}~gxNGW+FDu7>q"J}kw$$lSRZ#i̯5Vf`a:{D]/>i)}uĉV)%ߔ'6)5ĝwi1|}/\)/~D4ĉhqx {G՞ZA|I!DL914o!_1O~G/}kwIwb~fF9͸ZۤTwښ?ޡ` U1]߆4!VO錷ehş8<3I!U#0i#Fw{}MgWc|3S10W;jRY܇3F`iB0z~z$`;r>‰ h21[k<6)5ĝjbnK3ï |F݇-q8i08hiۤTwxŰ]cqZ|`ʾ(3W3K5U1+OXmK.1@'j(3" xx-̵u:pNbkw&ſfۖRaOU 8ǰ}0Fo?AA|Ɖ@dqR8ݣ-TyZswN[e~>m3c P5Y]X:c`O*ƌɸC&֏muOh}NhK}!rNĝKZ^8Vnj YжZT3Fbx wDyXdtSM@+T =MJd>mͷ?dxoPMo^fC4nz1H:1 'Zh1W3VzhRYCi>0a0sr[׷$KSNYJ𚸷 BS7ڤTwښ#OTaB<`<nXBx#b#'z&&DS"`܌UN)&V%Fuc1࠿7DE%ũ)X$ 'Z5ɂqwR+/6)5ĝz{f΂7^Ո_0 L9ebEOj[qR7(ږ\v {ڽ9i18%~X^*6EorƊ׍ջ$MhreiePڜw{A- _ʟK?c婩m[>2b|= 9^pU⃋֯b~)b I,)owMͶ-žv{y⳪'8q:#W|(NyBbEA8AE#uo)]~g|7msw.*xGz)G`fA=1HT+")ÝJA*9UɣH7/Ym[.=NEwƈQ.B{>c4T@bV/;6嶋,cubY܀m pps[LcW`ꍸ0S+?ۖ\v {g'lQX&9ok1{؂LPlYJϋoXSa4Ac%2ٶKn=K[M+8;Hwז/+;D=5]mK.=ֳ+qQbΌA$(ť!CqОu7kq/u%O_]߅3Y>C8#a(+v 1בr{םX>5ռK"V]s\qے.b?Vػbk`i}r :躯g.S_Tɕ%(_ӹ+KiIٶn.:1Bhoߜ^za{y1⻫Yt5HN lcF6嶋,>Og}r2,‡' -z}wwƊ^9$yb;ſVے.aO1~' _Ae I%g`*ȍJ(Ί c7ԗQ<{m߲ [32ۯU'OX~ֽ}-[RZ3D%rs"NR7S"n 8)ؤIvq[)O-ۿ˅_vG$k[qC6>ygfy&epm,RwGdے.aOLlkU[cəc7|A=AHS#>+#&h tmz[wˑmK.=ܘRs3auչ}5DLDmM&HAմΜX}j[r%i}ˋٕ{l_>2u4fYJ9R +*30a*̲-]ƞv{~*|ή1ٜ넵>? ᢾ4;ĚZU3iL71un-{{kxC:|e\e//i e/ޜNebKt]9mK.=ͩxکŜ}GQ@ʞӷ3YWXQ3grsxr%K{e~%cL$_{8푢Gr+j8\ec;rf^+5 F}r&.zI@a\])ǒ,7?u'[^RUpv>9t/LFd[ƊʰnrX6h^u-{? ÿ;kރ'Cٛ’n.ȿ.f2gϖRaO=!\*6O6};@YFƚ2&Ny 23W&qmK.};\OqS*fR^]m9%VTk1q9EN|Δl[r%iʅrO΂W[L|nnőJzk m]ᛉmZc;WWsfuے.b?qEǂ+T /y en9ccEuJV fmK.=?ݹAHD:9C:+표󝱢279/gsdvYg&!Kh@j]XJҚXSe['΅h[M[LI._{I 9; 5lH5j[~ +*3KVD9c h[r%iȏmL΍NJsVz1_{ڻCL n)]~gw16V={~.叿b߭|ֽ-R9_=w!})n#뗳_b1El-8f,)uYxFN\Oݤe˫gֻϲಖCqi|5OARv^+aĚ;!NA؂d.pے.aO,:+>͠&, =kZ[`ue^s&cNN<{fLmK.U&z4/A=Jx0ӶbdԕFcK}eۖ\v acm#_T Otqw2c o..3;`؉Օuό meYn;4X瘻Tc{~Š}ӯ7۶E-sv;>:}sDxDߙb}ǩ!>kj5߶uomK.=ýZ>9 =Hwb#YԹ3leީcnSrے.aOw|Qug|y5[/o!bX)JXSB&aUZDA9>ʖ.aOQ7 X:*D[|bTѴsl,"i}.aO,=1s,Uv}}#ʉc0elwt!ږ\v {ڭgag1!I7C&/yc̷VTd{ gme{-ySޜƪȔGd]{ܜ8XPͿǯ~[ҸSnK{Ů>fIه 8wGNMa?1}Ⱥwsےˮ>6:s߅nl`>xN].R~W{ݿ9zJ{ B߅m\ {}̕C't}9Sms%P> kj}:cIkݗKdے.aO,c kǶ3Im5'w~v BX~DrOmK.=ȕߧs{ȉ93-;t=ze\II^5A#g m\ {ڽaR5B Z$w E1 &nKB̉UZ[.={k90;x 18kXQ(uS7(ȱ~D¹pޅ97Fnj( CbE̻0j] dے.aO<-y|KmM^̷IΒrEyLזߘ3b cr[.=H.cQf⡧};F$DwrB>nk*C$rص 9#zUK^1+0X9$nrEO.LEwPJ7dR-XQyF<9>'wcnr%izDrzw_yʟ~ꏳ RD}'OHؕ'rzr(dݤlr%iv~%3¹Yߟ;1އxV5u3bjNl 5uWKdے{_zx*AUߒs&ߕDDs˖chK,KcCm[N=\t$#Q|cUi] >0a MkpJx?Ū(u_mezOЏJN ^т.t[~k6VTRs6kJqۖ.aO,\XHzUX$8γN Gr8XHy#ۖ\v {ڭ1F0r$Uމ?~ҘS7ÑY[~EH,wɶ%]žv{~A:hNΩEAMtF8j1HĊnupڃ% e-m92Ұoeגs#V:dhߙgp+jyU c9%ZmK.=kE4 祘K*g">]d9sEkq00X7)ږܖa%THRE 9ofqZBƊ0絠6Y7)?zn,%g1|"ār'9E-gccE{gq#M΅MK3])]~qlĹ]|CբPHKyi5%g"8g@w}l[osǷ_\)98=dl.߯U26>M-]žvYI}ry_X|}=unDDXQĽԝy_ٶ&򐯈|D{dBL˵ ?cE]F7} [wwnreiϛ2<>YL+ϖΒռRLN'j,@cۖ\v {ڽdejLAǚ{8&`͙+4b*u_OmK.=ֳ,B%>9p[b|8A xRvu,5unɶ%]žv{]uK3e~_5Lyջږ3wXQY$9\&uܶK 2A0A ÌԽ}qn`'uxcM"n7sK&z, zޅ 0#ؤwB耱kkl[rEχ{޿9\lߓ{qvf|쾹%=UaE2"e5cn[r%iXQ)Q(sfT % {-W0aEAaĢ2g9meK8>&N|Rx5՜+cڷuPyr+98p/,vu_Wxn/,M:P2rUs,re]DUV{בr] |qʸ9H_خearTNqKsX8i{fmK\ =&WPjrpr:ŋ}:)q,/.PXS5EsJl}A]Emv֕lǷ778毣#>}lAvbQ1ugl[|3n+G栞{ {\ǓI})2^Ff`H,}l[hYx柹5c`s~ϱnj,c?Kt_g EW+i@]nRc*~1_ ^J^eś(59-TB)HKZ9zJ֒rONa]Ga/^2$W2%]žvYx=j5qjuF cePmxzšR'gw3ԝ{6嶋,f-䠄,Lڋ{˧/hr>*"u,%]žvYXwœky"j5Shx"ygEaE;sϓ+~}yݑmK.=-S"ao$z1b*g+*3͉c%v ϺGfmiY&=3DBfςhu՝v=`sܔXDRwql[r%ie-~ ȸֈ[5>XS#u/DG-ʑabF&?{K$GĊŐֽ/tۖ.aO,-J2 98ԣPJ=,b9o1VtfgrF|ԉD̶%]žvYk]6'%K؂1d?WJ0eߒV3MYwnreio Ov^b%5) {kEpa;YwϚUnr%icՓT$9/Rqd9)99Ɗ*I.a}znWۖl?z6}?9_@a5TQ>tr־}c?AMP%dmK.=x)upTБ0/"9!/< '{^LL-Waܯv^ POliUJUsdl\S7)/ѶKn.ausr5]'Ŋx?*|9T3rF\ζ%]žv{]GMpXvZlywNNr4; dے.aO?cT?ce7U$]"u,gXQ3W`K;QEDzmɫ/~m; z2zjװ[^.׸[XS|uݶiU~ؽw 3܋;)pTF[L+*oIO 1uomK.=8vQ_Ijě,Y''VNNrurZ7Eg:9ٶ䗟|v19b!~QrP(ň>Qsb\}Y-XQY(98ULEٶKn? }(ǗK΅Oq-9R@|uP3_C1XSwM"n߬5\'98x8upBER޻ꖣI-kKۺ϶I>t#?dU=dU敟:d\Ol'nRޔ tUؽ0ǪwzH pz ^[ÍuqڶEԝuqmeݎ] q3|r0|z6ucM.ɻ//bMy?ۖ\v {ڽcwESm ]]iꦶ+3\b|2%9X{ݶKnY7mMװK{Y%E;RwޖmSnÌ<xχl"VMy߮-gۀ3|%{݌QuXۖ\v aef`yGUrΌޜ$3VԽc0Dk2Jݤm[.=c+}8T¸Wc~;aM`o Mcx\v {r̾+Mz|zuq3\{̉ٯ<& A1cޙ n[r;?TgkLN 畜ڥz{7aT Q28 gLlg gSے.aO|jrP2&EհMyLF]CyXQy^59l6rHAݢ<&ϹKn?dsU.1ߕk^/u&sf3ڞ+ũm̅]rtےO`9F%gp&y*} ϡI)%OKĚʳQSγQٶ䲋'?(<A>PUyfƵϞ#oycAaEuGm]c+|l郻mmvdTRq_[YJ™xew׷٧tQDy6 sT^tn>^r>כr./x7VT<a/}qEmK.wGS% g7yXSmgZoj7wے.aOwNZg}ixPc]yNj}ѷ:aEyibq5uyl[r%iY2ř<&NgpVrz+ ²)g-zcE $3bn3eے.aO>畜zxbmEe )=+ں0bbR(X-[r_ξ٨ju34pr)sSvHO]TXbq*,udے_ݟ2/'K8THb9m5Vݯ|\DgyY$žvY:|AэpZ^IHΘ+l&UASwq/ۖ\v {ڭgi{ix\B{MU$g>8\Y#ۖ|9>?ֳ̕:8og꾝 &o޹RkoqAbPr!$]?ugT-˜}\(>f.Xk jqr%+v\+9+;6zdݤJsga}lirpX/|}« V|2{VXQű\ф+>R7/yS\v {gYwk3s׺Ys4;75U+|b{$u]ٶ䲋=ܾӸz~r(;{87fI^|r%93ĎHJݠoP"nc=>iNG&[g()7|*Oƒn8(clCǺIۖRaO,>>t P{gBk+*XrO{gx^ѶKn= Y7_E{ 5_+-g%BcEu*=uW̶%]žvwQ.t^qro2fXQ F:F[1AsӘXI=W;nrEu_H+Op7dPŵnY!ov"9+\"3.mvi1Ǎ2M1q ޫW14Xӝ p<(_Z؊b ].۶\v {{SN{{[NXQy9;Xޫmmm92s%\L=Xaoaj͔Vq:ޛ9p#u\OmeۇSma;!qmn1˚}:\7 w#MkcQ7*ug]l[r%irEJÕl>AY=T2j%שׁ(⌡`؂m&ſ.y~2`wȚrX__GhOj!dXSY59XWMY5ۦva% 3\ɩ&.S*zDD N+809z5㬻fM9-"n++s4(:)}g ϳ# Nr XIy'ۦvaT̉Xc8GӠ yNrh0TɪIAQc ]ܕۖܖafGT<ٜҝa//F?)Jgu @XQ5WnyI,Bʕۖ\v {w~k_qC~8ΌraEo~۶mɋ~߅_cdQklNC3mx6X[8x&&Z꾼mK.=!ngD_̩#,iujݤm[.=];c>Mľ˯9-.냺36n{r%iz _5)]y9tT1ٜ1Y1Yնenv&ksc-\3JWOy_A޹nr%ib?\OnfFb5ˎD.趜#\5b/I5۶v{ڽb'_To'9(U( Rc+զ:cCJ,Rá%/>w+8LW6DtD`Nk55yRMncM-g?%bnJ9weے.aOwb/f{Fcg˙f^;\mm[.K=vbFMc<"M3fbqTSށ9mhXS^šO%~dۖRaO,7Ȏabk+4b}w-Ǖ55҇1cd2W>ۖ\v {o2`/%Wa4"[W5ĚrKNdkœ;gE݋=@םs6W-r[wB떍5sc0Hawޖ%]~p| g=|7OL<ѭÐcM];u֍š=l)]~gS3:d&Egz&4>zKkO55.廬#XfXwwFu-y)㮾Ċm~l[r%i<ەqpp "͔#+l6oo{])?`Z=wԆm[.=LI`>9ѻa.r͹/@9Ě fXuw1#Č1vL5c77}b#(Q\}n9+9k?9؁L,]\0ۖ\v {ڽ:y}r}nnU+ĊZ8-^{^M" "OJŅOuj>S)*Ae\XC {?uu-"r'[%(γ|߾b>}7VT'-|vܮ'Gے.aOZL_0hd$zZƖ?&uoߖ{qEBݤ-žv; ̻soDdk|IgZ7O8-V0Gӵ-ϓ-㡶$x%DM+M9/+겫mNl>hГIٶn=KD߷<8ra׮2%\-"V]\ +ju栦wbQ;u(ʶ%]žvY֊@'ED[-YFD43aMn&VZ>>37ފt>5=}16^)Ae86%5}rd fzf}a"$NIq"VVI~cSk^:6)5ĝ(d5uwUbM(MDCì{Qgbo1cr孵;mR*k;m8[/$}o;\\8 תd{GBGZR}]HVS)#7իxv3,ՑR/DScv|L|I{0Ɖ(L%Zk&[px!8[,Gq&"53N:Jk}nRYCi2Kh3p&CP 3nd* gh3P/@ /J)Va!wM{fྜྷ;؉z_"`C:pq"gj30K֞{MjRYCifw; lhFCg/$]]Ɖ4}`.lJ+ )۔Tw]d pNʕXNXQd$-;3^mevLj.zSqPO,.E=%Vm?9(XԓKlrE~,8/Ԝ?~P7;(0EG)G4Z྅rfűl[r%iwXb8f <07p#lM,Bߢ1gԁ?^UMKe|VۉJw?eQee_6tWDfXp:UMe&4}#љilu;^PRĝ]Ȍʝ#A5ۤTwں;񉍼m91N` gdVJ˂+V- p#zoP7ASBrJ)1F'b_({ \ $lSRYCi'+ƃM2"m%8$;ŊgY6ZIO٦|X~[#ƍPqPVAu`^~Sz탡-,~)#5뱖՜hD,7C#S/ ҫDH<*:6)5,ښiny>mr4wEh0GLK+p&71@D8Y7*͋0U)O.w_a~rޅS E>ŝLf`k[kt>lc:DZ@4"]~b؄tL٪ h(Xqf)Aĝ٧SC9& Ԕ/ohrm["\meٙFvљ {!H!t-3"vgCь:{ZI3RZC܇`Cy%fO(;ꩉ@(,E8+fH 1C6)5ĝ4'>%a'xK݄PYƉk`]&cf:w̌mJJk;mU癱'r㎈AU+~3SUnAC8^3 k欵;mR*k;mHI?ZmwzkAaPԗ֣r\XQE'pb=ζY~Mƕd`WJPOP)[>"4VΔh$v{?eے.aOEv FUwmAg_%P7o5$8yQwI%LmJ*k;mg48D G͘jr8]fq8]YpJ8#kaR6`kmyڤtطYV 9;Uqnkv$Ν{d?PñW뒃K %G?k [u9cbR K0&%KkiڵZb (?x"'v9sFkGzsʑl LߌEԝd۔.b?ֳL!ҳ:V "id=׹KebEMH?3$Ml[r%i%.'b[+ q#.؉KHir$gRp4ۖz"kct0o_l8R6lb?E)fJbRvr",yG۶\v {ڭgRjaЁEj;&a E+CbE2K XNTW懺mezwtTЏd*^x-9=ؤF-щL_-˜ԜOa AEy C(ZWMK?aO`ixa;KKw_mv &;vq;m&_@Epqb?ĔEbE6mrߚXn[}l[r%i#1xr `QxɨVʊkK1;ߖ9t.&(ڶv{ ŇG e3rM_#=x5}:Q3XS'9FNgے.aO %v)9/)#TEI ?r'VOrpkFY7/Ym[.=kdW&umgfɟߢvIVtmUU:9,wOkBc ͳ+d%Ee>nmK>[/J~\ܽG{\bf,əe"ݼ4Kn=KCx \Forz; vƚNH%]\G3ۖ\va#|spy C CkbD GR u\rН;Ikl[r%iZDcUGĉ]ވ(L[•֢@qc/S_ڽ7bƊ9R3l[r%i|X8&Nm8u1Κ3h{XQ+V'\Y7)]\aI"Q1ne1#a3F$KY3ƚޜKnL,. M 6嶋WO$|>~ꝷ}'6Փ;\;}l Of;oqOߎ?^i鞉csqE1TO W@q?O7FTr+jG79bBN&lF6er%Tͨbrp؊Xu׌*mezwR!=uJ(Dqsbb j&VȌspIrbNQے.aO,g!yz-߽'칒?M}>5z]6 m,w!SSfɯ,!x{ݮ+疳FSf2'pumK.=L+$}F _hTS\[Eǿo3 ^I/]ٶKn=KggTޡhy/QbelHXQY *9䄭8/j5AmeY4Hs[<&~{LQĊYnN6 i-ݶc?vkyfN tP{pvlLb?h$%E_꿋GZKlTkI-[R. ]b)<ˆ(q+LxQrXQ%6lbI-峌waJV[ѣzU&-)v`lAI.Ym[H,$,xkx]:F3ed-ǁĊ] RWߺu-j-U}r 뮠 =W8zPylrp<8tSmmvɥ;FdW-81c_6VTw.98Xl@]-yaw%cR],5&aE]ށQXDſf+zxt{q1$@|ܻ)fY| XQԓp8LſnKnho,(7Ȏxk5HGAݮ0F{:e&[.=뗇^<F-p wqT QIg2RTk-k$ԾۜŹtj.׾[mKnosv{8Cj31']:1{P+䠘IbUEKK%]žvy4mSP)!TyPZ{9vk%z(c/kQۖRaO\bNp1_-eK[S^.?uaúIy]Rb?o99 {Uq}8S^Q(V1ul[[~s\Wu{GJD#q'uyg۶\ {ڽ:jjA,ncna]5#kfxnնnϕyw%啃Y"|ܻ/ͬwr8c7,.yrlljekrnsDyRlWm,n? OB>8<g}+{;J>; K'wb_MKDۖRaO,+ ur" +tBu{sXQ#w|Va1ʦzٶKr~yjXhF s~؟Z[B#ƊgM,ԝ~-s-kr=;/k-cE];a0O#n[r%iGMA^` YU,/{Tuoy^a{8fN JS;+Qeے.aO,0\%9q3؅8g7g3$X$0ɩ˸]L)򁭻dۖ\v {؍>9҈C(:q)rSa DXS;@0؁=z;@m[NqLtsB~8ʼL9b[~򑰢f.0_XM=3me^Bɹ )km9+jiL e<ʺwmK.A;- zW}?ng qzLډm,*yK}-"=cܻl9(xݜ1d4bk'aEe9EXX۶|WS?޾d aCTbjͥñ#}\?7]Sٶ䲫v\ew)% /_}b\Ɗڻ02ҽwݶKwcA-W use-H9b\c'&sSے.b?zq5漋s'|GS|WV#TV?L&Kԝmmv;SPo&;i]i,S`wK7=Re+lƢd\Ίrٶiu{?Kifٹ T~NfaieƊ*;WAsW}-{b E&yLjvx]#91rFz޺zmK.=޿KqelLkAE؂7fl}m9Buel\8䖺I}ɒrei}FN&^ 0Q;Ƭޝ_,~cMe(&yG۶\vab9^9Bz Xl]֖WV!TVH"A.ugMlrE{~Go81|6w=p?(/xwfܯLϓRw<%-sl/Dc}䌋;b'+vpHyzMKgdr}^󦱸D>D+V nMܾ'|VSk-n=¬O=98]o/ƫq_:g9G&VTFܓrXñnRkݤ)[2y~}Nj:3kl|{rK<kN,<<mK.=ֳ DbK8~(k{P#>)W1+X8-"+umSn[﫾s47 Q|+{V€|BI=;Js22&ſfۖ.aO, `I:{5d6WkE։5[lWkmi~q8(9cuń>L^9K+jNNĶX;UJ-yqc(8NX.B9_+m`E9ůō&rh-~ug1E‡X?e9MG^}oj~ 6(SA}˽-]žv{LFxGߋ9HŸVw8 .+e5U5n[Bi.鉺mmv{DџxZOnjl+m9VVބ F^hNXtݼmK.=cK˶~#ϣ9JXSmI'Vwe-YE[mɳzm?cOgx8RQKlȫ!^5Z4sP (WKw;6嶋eNҕ]}x鍧2k\ r7VTuD/9wH ԝomevTxk](9>cP W:HaDx-^3\v {qqa?p<}_a]>\KqU ܬruRb?\ɺJ[OdVpEq(+y͛jzg"9#<4mmmvۇ|u5@KzA~Xe6 >S5kT79tK,RwImK>\uvwTϓWÓ2@UݵD!(K7mnNťv;/˶)ߖnc>F&'4LzI7OvzP6Xߚ[B2t;7ncd"6i{nQErY*i^W.n=וnNgKo4S^Wv cjz `S=h"u_˶)]~ؽ㖪լ| @sm}{Th'/tVpDr\M,©;Ϗfے.aO=_[^+ v%p-u[rgH#n)N xȠږ[zHarP>(Y԰wN>Ssݍ}19J,bLէmɫ?ﲐ+NckwJ=5QХ&T'gѧ"g[[m[.=޾e8jϜwyՠ>k'2%ϫ&HcyպyUm,>RӽB1e5n|qx,RWu(M8aݤ[ꗀ\ {򷟜;^ݎ^%Ko?9X$=gے.aO,F}r:!˚=4gG&PhbEefUrpCb3*ۖ\v {ylrplx8HRgwKAʻdH(=^!de^d[wΕ株hͨ01obs3oƊs4ew)g&e-]žvYھ$鑜Gv_#gyrӋ'@v﷮M@NP bPvp?K#^> ѽ*ػT;W劧,Y=%kҦb5v!mWr06י4[H,|9>{n٧s.[oŘ XG}X!\˒k;NԎVJ?>ֵ,ٓi7/bx4۔ `'/tON_=Y6VrKjfI,vs͹eo'?x?_RpE)U~RgscGٝJ-Z3…X4ͱ{~[v}UAwwƕ6%C%&ٹn7VR9\T5K,#yս\`/ao~/8F?p=_C7fhR2q̮=ǎE4gMdzXlsw=-x {} E~#3k8F1xf`I8[v}/}e2 :<^{Oj]'wgQKNj3ĺ@؅SZ.^޼+]L~> zE;ܲ7oovn8W,Q,0훳 94gNn|cᄒwo-?Xhs5']6+:V֏[A_gïKZLS2[v<$5H'i4oZV3Sb?ܴ?~'Xs7-b4]GAXK;w֠ʬͱ)qlu]y7xS92O8F5c ͮ;85j2y9vܲw7yS"57ig D:\lw#n*S\0Xؙs.^޼Odu嫦E#c> OK{^zG.&;k}67:;ԅݼ}k|Rjpޑ=ω *8J:HA-#cYc:Hv}Α*/kWU?$5؟]nŧҠHbQ$!97EoO9ui v'TӟlMOXBƾ"M5UC{xt*285O#OGcQ?2qgʱ\L^)볦b cAe%kQ!0VN؉{f]U-y*1`Y=(0_ºwIϝta,%o͚DMkю]Ly{=}3TF?`縋|=+W/zI}'5LlzU-7ۣjӥc coKz ;=JjllZc\yn͋'Vagf* VvcЯ2%a}g$u4vғljܲ7owl{>[,zXQz_K"Hc4]'e4HIHcSܲ7۬w6+@tyL֩t,>ZeN5\U ;^FslJ|5]y3 <DwoKYXIݙA cb]yW@ £|H>JZ z9E[=2js^ ~s[OW<-Ӓ~WK3^F}ؔ󰏝yXO h;u*bTjcZQ.)T&|v"akAԭxiPY0bVv&=Y%E;J%Vj153=}JvqM{f6D&P|Mv6V8EN>b[c7rnūs8O3G7糲.|RZ|k;8&V:48O,1$9%W6۽Y<vOuN?7ݽ%( -o(#4d"#nAe^GEE<*;M: 5wcYAc/=5&e^ dDt86ұL1IBZ6,RߏOE)St Q¹(17?wꉋ}sdGbA;f8m*%o$̂8-ouK6r G%_t=N6i8θ9,u`+2Gi 5F{NYF+D<>GF`g ֌a_)hch1{d/[j.ȁ.ũ3q6mQno}D t(c%" 4^#IsF\cLK$~۹Bp[)1Ŗwɸ S4m@OIE܊>Gacuf.br-(F)- o4m@O_$4/o${ƩG~+]!T:2OsA`n~dp + g EMkqQҊQhZLjq5jISV?cg92,Ol\asrWXSx*(܊p{}{N(DX5,aVzbau@#7K cK( w}؆@6 ÿkPFmNapL!\1??05Qs)*lj_; 2B Gn'QG,4d#ܲ[v(6ܖ})^x4CZ5ht$lZEM+9t.甕lNP$l9^D'j魒?}]=޳h.ȁǧ]2rDVG|쳷~| `;kU8^I碍iAQx\CvZBh偳bi^JGA_e5mχ*q F^q  [KN=|UHf1 Sx's) v&蹆KGr/1bMB-ԍ҄pV0z]8kn甕lGPTyعŏX1TBJZ' GaS#qpWr-)>-$FӊQX bb(xQKyNYuBGQReojs1Zme<(d*+U>8j=6)+4xi>yS9\ǟxTbQbO+/\F->pW?Ah}nkNXl5–PrE+zj Wؙ֜ q7Wgp++E"XlH+@.f" 0{岊2ALˈ+E9ssL 3bز7B-;ِ* pHbAM\'r i#'b.~A(sZ% WbfTۘH Y]2ZxY RsU1?-q_ήKHy˕%JiV]3֕r1HxYDsS9m֓_E1x"ɓQD qZP G|]~(#Ehv`.ȁ^AȈSQs1:s7l KFa!{05m@/7>}\XkL5Fr@r0;'d%{hkv\Plaƒ1`xlseC%baw2م&%cE9sstbb:&O$ڑ4/GDΌ"AXtL_#2%"x RL8'F@7PBz3Êf)Q f k+9 wް+(@~EoDA_V 8gxԌ𜴊 q7W>+cG\+hx K GI>d|}Vr$&SvoZ 9H/+4l3H~28 v^4j;s٨cU;;?|n Is̪р} XK% B t(LhW+8 CYo<{8իBD\%%a6ؾx#͋:^FYni'nz_۽Ub`ƝEKKCV24BV  5n=d#U_<&+߫ 5 R8 {kʩxXSVwMN#lJw.t*BsءE`QSVU*cYڕ8I}%prYcj'  ^j,9in&]4Vu[fΊu qu+/$PY-ը+kjN[IO+Їa\W=l9QcGZor㓾<{(2PNC (@F{EƝ8 jYcF=1V*s)*]5%]n:^Eu>:EGx축p M4*9m.θ +Dua5 J:p2 RGF Iws5}4Qz.@uAXųhN\qϩhb=j69pW\EK /:*Q2e(\VYGa*Z xX hԑh)kU4\E; eY1v.Ѣ1[\2*VĜGa8 M1Lsh/WG..PgB,}c5]8mE+[(\IGq]55j{NYF]A{*]]ٞn}e<n+{_EEeߪ%ڜ9jzNYh}rvz˥2ROgg^Dl' q-H5n3ңW8ps)XTMNJ )qKf+-+nVq攵(f>\^tÊXNj$ 9QǯθAL.甕lgt*s):^ ܃(SBg~Ӵ{>N5='bQ^0S!l}3CcVZQ8 pVTX WyFQ =d#+NOd"=E#.ŠP$dd0GD&iNYFWX"EVޅS}#2L+G:L Zrg9e}X/WyW;RY3=OVi7Bw%ֱZrNYF[l]]Ƴmﱢ?`FM+QӰB"+OGGVR=% 'NJ+3\LߊgpQK^gSVC4H1[CɦEV4BOOl/Qkz4gu`g1o>.rH{؊K8 %R<^""~**Mh/ єV"8 帩3Fg4GmqSaN[F#"X{1|GF]iiEq2! d9 V!J qK2!Q`W\iEq[Z.rX|%؛֮rfkC.\j&|{ךgElk#.iUQ5紕􄻸zVS"/ڰƆ= ̍QP#qH9*{N+ wq=+ν +=?~quGmq\q6[YY8 >.λ053/=8.ԨkzNYF7ϥ*2>3oF|i<# 3 epXx,'W3Fwd#ROXFw'EDա 75Al]1q2̊F8k$甕lv2Y7?SzsmQXQ8 Y; 6Q]4`ͦ#{8c\S5l8C:zmèRVƗZz*W] T<ܚ/]E yH/=eEn, ͋FW Ķp?6p.$ͱ $ǚXGTT'7Z,~wmws'ob"&EY5[>:j,bgd"qz,b9e%.JnWLq'(EIS53E`>8[(d,2 ϥ@Q^Gebd,|Fʧps5aF{,a.羿 ? ~z. hвCI-=d#[u1m^uVGGMA 30*e%.^4<+pWжh,'ZQd ՖֆkHG_Rqpg{Ulzh‹2Q9!fVZ GaiwU9*wlA/ζs%ŋ/{jG{=ėYgZQ8 ;w[Rp %<5*sJ6]\M>JY&\7}FȊ[q.Tp&z_}i+wq=}.b{uܡazu#;S8 GVĿp 5*GKWz qܮQ+2]a^YߦZ2 8 5+JsNsl9e%.ᒻK_/Kߏ%} ! jC_sJ6]\,2(V߯#PA[q4n.!){GҜpWuV`B.{PA9YBro\µ|>zsJ6]\S%uobkf(=u)xahnY8Mi~)+wq|ʭӳ̏8uV%;` ypgSV!FR :C']dOMkR8 V,ZʽGY@sRa6L޽/Q գ9#[Ѿ_{Կ`j|^ =Х;44_ܢw%pkdk=kꣻrfYMjFSZj&`0EX؜0[K*iy¾)uX h$Hז-dT$yϳk;SIbq؏rnK؛ *ߟB<Au!Lv0VR,FX.c\ |)(gòK1-FK_|4ӊ;q6=wks֨ ~SV* XpDoV (ⱞp.ڨ#+2N5#O=d#U{%nF;Ɓ5NlEq]VFq8y9em*X_nM2fa* ulo(::u,I:\H̛qx<45jwd甕lRϥ`䉖&ek=X(ŵЮ֪jQV4$G=jEs*6\E1Υϥf߅N\ ݸlܸҬI""{򜲒pWvV8ͭy[ل:tH Qxb;q I9m.yeEk?b?]?]Od(ieB4* +ws v/XqmUƋ(@g+?E(L/ۭC\GHFT{NYF&ZV`i lVVkeŹqr= gIFNl>"͸ 6J/Ŝ%%yFKA&EmEq}q"Q/V1.E PL)}F'v KԴ"8/}edž_0֋#EϏ">RL7L1]*+K r¬_8=j甕l#Ul6PA.Ád>`X8 #CYcF=!0V1fr- ]rri*eC`GͰ_)P9.pӽ]PP Wxr/JZ]QbXQxNYjz<bc"H.,lEqV8ָ5xNYF<`W4qbm|E8V.#\Kpܘi9inZq+3}*ҍ ]~ uۺT(9BM' )+wqOw!I>g8|,5% úq*#*+xN]$9bsJ6\MGWT 6XhG5NsV |liZKYd✶q7WotE@H\lTU'#V(54s+jQ{9e]*\e1R /0H6?ޕVH 4]4jTzNYF돧/;ڬ`:w`Vpyl/8 +ERУ%BۻXWRMe&.g5p(bߊEw/ 0-6IILaE+(dľ75=jVpWGNW\ʘuݰ!YPPVpPr)m׸,E8d#*Ҷ+}a, 6i>8 !0V 8v~Ш!0S֡8rc 9 sn1U$;ߴV'xCGh\Iws ;>Xt߸ȍo[>Һb=eSS+k=j甕l?1y*ZJq0Հ yqOkA4$dX+P8ԀY!sJ6]\`~US+ԹK>fU_64]C QIlWQPRK1`c]zu6bޗNYOW G5)+wq5}%jsʦ,jH kg$o,y@7+84ŁnSVba+Rltzs+L p i"8 [u+25=olj :@Ί]7{.RD%Xcga#(b\GP p?\ZX"0uM[iq\g]$H xԖGSGz hc1^Q :n`2o5&*;p GfުWfUZEXa>LVV%?)xe[Z3BUlH\a GJ}l>*KY+:N|yٚŔƩ}I+G!# *S֦]\]a% @D!l6]~$AlŖ8 g %p!ȣf甕l@MJQxzre]ۓV6(>P 9P|Ru[F+_3, endstream endobj 427 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 433 0 obj << /Length 932 /Filter /FlateDecode >> stream xڭVoFB}EﵑDxh>Q;'Xʝ|󝙝BZޝ|l8=Ueeɂ -|_#P[FݞUkpu+yR|X9=a*3Hdk@=:^cpҧH'syc)ȎvU_u&ԴvI-u|v:/`Y 5xl|Ӳ΅S9`-6++MТ6uV*Qk3ur\"\lYFy>B'SZ܃)ACeW$nx )w6TF6 $'-^. 쓙JasCL)l( {#K?RYCe֦˷Ee# {729Pb[J4cS)KU_\RضeRnE`p{V;Pv}J8 ]lޫs# r6kQ1&6e"/r pN!;tŪpz54kۓ(]-KgjD÷X^R%Wo=&焅2) J5}h|)4Q]c# U~GZ-fQ` ~6s-Jy@G@, Hǖ%>,+fɴ8GcN޹a:,d܍6S #u]?Hh endstream endobj 428 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-060.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 435 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 436 0 R>> /ExtGState << >>/ColorSpace << /sRGB 437 0 R >>>> /Length 6962 /Filter /FlateDecode >> stream x\M.;qܟ_.Ǟ-(H+eE ,js^uSnMW}ŏ~_|o8_ӷiЀ |Z׏߿~׏/?>o6~?w?׏r؁9?^_~__bV/g;5Ƭgn29ߟ^^R6wKM;y[y߃˴?Og-REvpRXoH5K[|̖m6v9RZmLaц{1 xF,ӞyzIMz<weͳy(ilsU/*[v"vXD]ݟF,XӤ|YIWH`D;E"RƯ1"Ob~e'/b+=?2l$:tg"; K)|XF+wH5ɋʛX^5M |d?6ҏMؼ$R}QbJُeٴ_y3{mG0Ƥ⿆7׳vicXRƯ9?ﳰ_~Ͳi'/b+obc׋4x6?^l>zY3E<[a{Ջʆ]xﱬ>95ѯ\d\}rj_Ml;,vvR}imW}\}i w[׻a/`7{,u{~<φ{H5XIb\mORvvXNo6ֱfDAM a<%E.sab)jciAR#h:ϲa/`7{,=*痦zN XdWa)+7vDX bƛ+'7Ss},Ȫ[`cD)ʳrwojJS3|Ny>gٰoXvSo>Q>سiqDRaZsݺca%oᓬĞyʦx33YX!U\/-ǛS_ojTb bQٴ7cG񡣍 kngg~R 55;ƈ|C¯QElun6ewj,R%*,]cy̌QREv"f,fZbE{Ռe6yzbmz=d?$`AϨG?Ħkj;Mk>ri'XvD{ (џw߱'ҥzIp=V>U/Y6ƛX48T\Vcy,+i"  ]baٌ*=K=7x˃Tc\ԏIOKsTcx3w8Z/^xp&6԰^eM;y[yoyr{O2Wm\Rɓypb)zSM쁎y xs~9Bn}y9ˎ^XJMK"bybN<_2؍[:-y%j/;rzb)wϞ~Y!՜v1vb?ȩ}YeNVވf+Sez }ٯH7c%5XHedi^>#i&ƈ#MJO}F/t/6/r|Qٴf ŋDx{ˈ 8hM k $pvB@V#pՐFg2Z.!KUU8;2r y] Ur kJ!(v"vhP/M=7whQ qBXJ]Zu¶ءoHE؍vw.²iS`7QEr-k#,KjFbQٴ]q,R$E%XIƤA;mHWSٴ}Mjuw$J}໾/%yڸQ!J}Lr4)}x^/MJO烔+ԗXIW.KHb#Ig.l ؍ou斋4S@.t8)ʛӏCXJgnHHb#I-\T6El|PO˗Is?2_~@Se8k"l0YG\ dX8\} b#¥4X8#\3 ,VrB ;Fx }+E ug q+7P0߻<IwW᯵p!< {1ג'LZIʕЇ4|9G˵oZߨYB( H^ })+Wni 3Z4"NO34C!W`r#V||_Iz8 >~xO?ʔlXkgץ)bWo]7{ DӃp.H{柼U&d\庝, #A+qO8'E ug q1!)bߞK#2,z8Ci/\lkS2i WO|^Gq{X֗Y :BYH;+~H#<#ǵGhk x/8Ɍ%5glX|Ʋ ,2dٴ7c9<{>+hټ$dAֽ_io^fzIiSM;yf,64schUGW,ye?}XJ+iGXpʦ6fh[}YRmc K)|66b#1ɋ<~h> ;7їgx\XI&|b}Hdٰ=RDІTjc#;+)Xj$6P6e.^nM`kilm2m=^vߴXXI^]Wlɋ{?=zqMr>A";;wmc XgRz]|X8PPc9qGθBJ 5Z_;-Cx3op~m/bbp{*+ _)%vm#4# {zϕɱlɋʛ+.|_?9Mos]E )ʳ f_' K)|Lo쉍M~Ͳi'/b+=H6O|ti/#; Ki/Ҡ²e'/b+o9V&;~uq~$R#9rLͅ+]Xs̲a/`7ތŦqfb}W{(ejrSr#NzAyHlJ9I3>L#/ީl+;or`) 5 8bӌ\$CTôqPDXJo Xߪ}7we^>3]֭/s=JsCh,0;&,vvbY3J5XIb3@F!m.^lw1_*ŵj(֪oo,õw!h^ Z}o*q«֪GTΕ^!k)kp^H_!AFPP^Y aƤ8=S׮R q6[:4ڸ{w .k AeX,p#Rz 鲂 qЧ4LVG>M:aѧ4Az]Y&`C\9"NՀk Γv-M3l]ںnݝ5j"BOlJb4~&t$֤c([vfUx;|.M.>>wz{~%ݣ3a_I,_S~BNߔk\b_x2S@͈GaG|cIGQٴ˚Jp ;aFc9%Y_ Ry+qvwYF•aqe)Nױ]MOev- Wr>_DpLП1ד5.saѧ4Az]Y&`C\JV㡢i/O,umX"P'%@AX 6<4)kp%gS>$' 'vd2 ,Pp$>ʔuA WFi:k Cqhˤl+\W,Y6nw^lHM-#\z}qWSH)RsJ$X/e'C) XQqEˎ/4C,weN^n[4&7S=w~I>fƧw[.ײ_VxS{Wg"oM;y[ywų'Y˃Tc\s&b&1BBT6ElX^\>@͈Lˏ8X@ f.H{ǔXJR;5=4 /wl ؍3>jubd~ܮ+2N{܉4MD5\!#*v"XCj|lo)@mLv!aS*u͌~Ž(ˆ]xﱬ=}~[GvpҵfĞ~bc7}5eٰoWV'$._[gfRuړXne'/b+orxUc|F {ݧ" +i" +]cy醰cm^/Ґό;zybm4m&, 5Xr ˖zlPZ/+LiHߐj^nqIM;c463e#Rg`.gXv;[yo7Wa*/KɕXJceotbsK}eo,v"X~ endstream endobj 439 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 429 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-061.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 440 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 441 0 R/F3 442 0 R>> /ExtGState << >>/ColorSpace << /sRGB 443 0 R >>>> /Length 11684 /Filter /FlateDecode >> stream x]I.Q_\W5mmHnV_,=gj!K,ݎ:'!r嫼~ϾoZ񇷟]ݫw^R^o:7߾ן~W_W?o/#7{}<ط_^P&~OC{7[yrVګQžN_߽^Z\5vmCj~N~.XIͧiNlyߐҖ]]y1/ôxǡHsğHz˵[bz_|Z5Җ]]y;/%^ GSӶ-~5${?-MeBo|3[|kħvTؕ7rlWy yI!wmﵽRwHk 4 =5}SJ[v"[(ڝO1ki #m;w׷cO{/XKͧQg" O;mŋoe?)~̋4gzuHh1j( %Gh$ wbM O+mŔGݯY׺_׿zp)iiGN$^~=FQ"R.^®M -{m褮ҫiL3dk0;\E샷G^jZT}4wk^-1= 29fT~Gkߔi.^®]_Z4 uT/ ף%$Gab{KpPb%Y_5A/J[vv=r5 mQE;5~-9/lmтTfcΉJ)9/%u@mG~/D!iaҎ%+- ̾Ri.^®XhےzF춆ڎvXIcv[Qڎ.^®~8bUIXj(}4уt}4Gs{/-cikiw<Lbk]eڲh> äU+a(%{=>z>clQq5}SPi.^®DWG4XS WGN ];b&J2/Ԕb(jWħv++o/-bx~TUsAF>ԳҎ+ AG5NߐҖ]]y$ bQ}f$t\j\chae1wJo>-hlĎu C5i.^®+rx,5hozt}(n 鍄6=ڢJ+]9˴i7/bUƻv1kvhkNr0ҧ۳ii*zVc zVħ6E샷2:15{${|o=ìB(\rlM 0-N[vv2E(c5j;Z.XJ6GD5Iߔ2&x eіrY_hyxM$L% #lk 4=+7%FLv"X4?/cҠYcX6~E,%5#xI;ˉ;{ۢKߐҖ]]y?.|4 _XcnXKԀOb5}g^2m͋oe *WLM[G0~2#گh+MN Zb g|仸Mδe/aW~?{['o͔~vRE-f=ȹ}SZ}Tؕcǒig Gm#y|m*5JZb +Ei.>xM>bp4ԯ3.1Ö]n^gGM%ҌR&GqIߐӖ]}~_≲2G_3^kiH15 *7ev"ʎV}o'[=;w#(y8*_'VR8ٚXXH2Nvڲ+guk'κm2gi(6H}ؕWF\I+dKEm.kiEV\{ɋҶ]yJ-9OlhǾ!i-xeCOTRsml c4ż$ߴdb-7E[P/!iMyn<[Ӣĸ:jd#Z☼GjYaJzG`cߔ>4i.^®]_2[Us`qo=^xxh;W=6K^#i1`$vDڑsħ%{%255QRmmQr^""a%m-)]Ɩ Mym'/cWުeG1飥̰+‰Cm>J8357j$$B9(9J_A]A/c1e<Ҋ5h(" W#MYF+*):#> NR!%TYXQCwW HV=jYHY1)-CGcȺcsp;o)!n*{zHVnGj NE R`1'#zQ"l7*+%^{M)+p"{[PRԜm5gtjFOlmxI2tb+MQl%V*<9h)Gl֣Da*~G^ѶGf+EA_A܁yGd#1D?s߮n@J:B|Y#LzeXMV;+zEp Wysg JqQ{t{q>GzDzQ8sP lX0cfP^{N*MYF묺xǜ8Db i 2WzFlcNP9'qB^ۜ/` -\ #{BKS bX0N+hVziJ6-\UxF1ԟ٭>Z#:xūF,.EC( 2MYF΂^WsxѯYDMӨ0~9Ņ^镂=C/+ p Q6,Z>ޯ"I Ga_8k^4e=VB pU9]sk+ , D^LVn᪲?>*~*nQOyr~BG+)7^W$$nd{8+zep Wuأ7=u'xQ9K'E^!Gp WxÎ+§Q1W$dm 'pEHSKpEiJ6ĭ\Ϙ#O\;y;/XK3/҈*cW-x 1X2/6FGG.m;X?3/m;YeXy|%Wyqڶ+o#:xj֚[%҇z`XKWNZs% 챻 ߔXE샷~Oܮ`V+hJe`QZ:ruD Ee/aW*cMU0 C],4[m?Xt`}" Jnaʹe/aW]nDHGϱ5SS[]Hr+{i,J9!6hc1MyUu[ -l"Kk7kDlDmx n(h'+"J z?+N8ٚћ;7ĩy-x af^R>#q̋k)b K=e/a5~A%5G]͙ı?{bSʼXC>ƒ}ϼ8mؕvq5USbs}~3Fghd)t 8Rfڶ+o~L lG,7ksD>f)s4n)N[vʬ]ưOL &Ab-x v! j.L#&7&O#:-Fzc)rmj87;bwʹe/aW w:)5'n1)=쀓54mǎʹm'/cW_Oh~̚TUua?؍Qy$lJo>- Ρ4JfJ샷~'GjN)5س"m*%;G+Rjv܄-"7%>ʹe7/b^0FuNn+KfEҋ0V}h wVL[vv孼Ds4p繘62얐^+}1XIXjJTX-x v^dlO NVBֈ %_li?XKy^5>n6v)y!Nvyy1rj.>?p %cmsJi⧥=Fδi7/b=c͒k'kcdet#{$LkXr-x8yc蔧+ѱNVv!X{vn<0VRJ,dڲ+ocKj\#/#iYjyI $}g^2mKؕxs4Σ1z9-6Lc-͵l)y:%vvu#Ýds=>XJũ9Y"\.>xp}8I w9)Qb[}NiQ+p QrǑ}w06{"\|# Q ÇJQWĮoOl6&5XI,]dڲޏ򖼤|tZ4%/:.8 /'>IyK^2ؕK;j,f͎qu\6VRϱ5OXlYH%bN[vvܼ.N&68AÖԴcXK-?Od'd-PrڴaO8J=a27 kdl)(AXM7%fڶ+o5g͍ Q**Qn%NU9G$0c/|fߔ\"#mŔoc i5_9i0 v1[pe@m۫hМ\":v7%b*yB̋5Sjէμ[uf^Rs \{i.>x;;Qo.~qSb Z0<k)[ћ7rӖݼ0k^!΅+Jּp.%gIkGXq%/Jvv=/sJp8۰ ǁE@ewLB3mKؕ 9wŬ98ɱX)W[#JʽiO [9֒:bJv"_m7/lW\5YN7F2=i.^®zmAcP8oZBz_Jb%,%~F-x \߁x^p{T/`e 3lŒ|xcnb-^OΞ/s/\-x69Ff`JGۇ{,[Vv۔}Jo&cw҇zHv1%e$5Ji${lR:~٨{!r-J=$&bH=$%1OsO@sWe>9혰L=HUX.T7e>v"[KplIsÿZa-7|8mŋo.߹O-P7 Ɖ~ZbIV%c)<',5'zVaI~ZLv1vb|wWiʆV4av1ŘXI_p}SL[v"k|-7Fq\͛U+Hg_=%?H:7x#sOiw~58}o,7SZ}ٯ+!N؂t+o.ŶYPS_XCxRiSXI vhkaT%y]ާ]L]yM[yD}I"ûMs?-Λ$w$in^csڊI"58 &gv̛")$L{,7IA$q)O&L[vvz͋5? k-V ~[1ѳoŰ4oŰ7[K=e/{.7|X#>et8 r OɰJZ"",oyÇӖ]]y121ra{Ŷފ1ѝ7M#5XzVL[vv=O:yׄOܝ^MYIJ›-T?k6~yO훒Hvv>.]nHMnVXIy+5XzaV m;ymue"ͽƃ"bSse \b%7k4X2}Som ~Y 'S_5{%he"k)|K 7Ĺn}oNvv-˷Ys 7w<@%Ʊs([䚾)b*eYi-qgz` (+EXI48kv^-,O|y Ӗ]v_]_n+n$>:o+$>z;'VҼ$58XFbm^p\<%5󆓋&YG>O\#.+)w7&ajͿK-x r(#`Smvp.79Eua-ljcM9in^f^lQȏ6zK L鱔~X`c)o=. sU@)yOGm v^:yJjNx5ho޼.i'VRBᜰY3;o^ɴe/aWSxN`i0>8aݨ8CٓrJ+*#QaOC蛒W#mKؕc%oV}=5 ;lZ_gv4ҖiO‰l)RM;y /1 ,OqΓEˮ ,'D$*l?)v1v}JR:c;>kiOb%AK͗棬2mKؕ󂅓Fe̚ OzbqMHbz!8?OK_coJ|TؕrӇWRĻ|w{DڔޅmpN'K7%昼} !*xN~)g/{Zq qr\8MYF_μ>*_𞶃ӊόp'IR蠉Ep W?yOE҈K_.V$I_ Nu邖&_>zy?Dd?e{ڊ~8 y;?o%-ze&bCqx׼_ xNך-[ypr_Sz{ed#uȲ[gp;D0}Gl-")X_=_÷х|?7/ jT endstream endobj 445 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 450 0 obj << /Length 521 /Filter /FlateDecode >> stream xڕTo0 ~@\Vi:mon=upRv GoJ2$ٱ?B HCkY޵@4+R(v.g%, e W;&,*b݃T @H!1NI5Ͼq:Qz"(:`sXgÎ[x|0ሉ]>ƉvQ7 z+ ~he!+lpK9hcw9 pg {93-31X@>ڤ"S|F"?hOHx`/O,l5DCo[{u=UC3ƅa5Da?5Mc|gvC3~4b%ҩDȹYML5 endstream endobj 430 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-062.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 451 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 452 0 R>> /ExtGState << >>/ColorSpace << /sRGB 453 0 R >>>> /Length 54247 /Filter /FlateDecode >> stream x}K.r|5rS[Hp1\Y2wߧ+#"$}#sEU_?|^S*yJ}_˿N_S+[a\k=Ͽ~ӯ;l{R~8}fuY(%?h~c.JOS֥\wה4e³ni/,s~Y$Srw+הt{q50mZuC/}٭Gpj_g:Fwyz6 Ev"F/ded>XgeQnB.@ YkJ)lCתz^ew}~- ?JU`Ggp#f|?BP6uKĽֳz/~_2!=Rpl=@==Ozꖞv{gył6%-ݶz~Fz- (j?#$XyF`0KXS7[SSنY.p_v)[ }I'.Vu1Hm]?\#$|VroGن;Y.roYZv.]2zzB"׾ }?sP|8.ϓeYYv=Z7YcLcD':g%eh[.͹z@k-=-%[uO%~.[@OOX^ }/deT Fem.rocnv b&3P !-vS{I>VJRm󳲋3}1[mHc娮]ֳ3>Og%tA yu7ޡ֊%^L~njmHM=";Ӈ?ҽ3TokNBoG۞\3QJͪm6VgzEmw- k1,g`Lz:0<斧o޺ %aiʲ઻iZs_vG{3m=sU|ҷFk)qoqVv>uSOȽ펵Sl3ɄǠ-wd!Z :3qYeM$׹eZꦞvb,c{~j{do;GOC7ml*tٸ.."ɰߖܳ^6uS/}٭66'Eeiu׳W<˞\xI`e_º]Cs[~a=wI3)9;<+Lȥτ\\o%Ŗ*fTvַuSO}gɘ>uK-󲹦 3u @+]b& 6򺩧]J+OyPd{vP߶9. Yג k >mhu/HO~ꖞv{ۭ6fӍ%xrΒt',%NH;m\"+[޻gI3]N5׬zEmb==ݤVng^Q8 ɮ\"+MI5ewӮB,%sKƈq,!vO?C0ۮQ\# nBegz^7n=˶`%d}Xfk̡7Os|[:^ne/w[1J8]~nW?f]oBVz {NnFe)T7n}/qcZLr<ފ+<^l~"S䴊Tude՘v8ĝEC@^P #/F1k$= Q_KVܰnwsN.r_v5sm~.G/~$eEg:8 ~{}=I'd5l<; Z~lVlHtm1M=";ʳFFz@g<;% ͙f٫Dÿ}I}>3eXiuSOȽ񥣼||1@ >:+6q||١ﶞʖu&1?sseROauSOȽRa sK:ﲢ,~3Ol%uek.tr1,M=*/IJc9s1qɔK`=O}B>-gWh㒮>r`O}Bjvu9_~IK\eYAfc3R0./E\YTvaT7O+]}9@~jGOUztlytnc@K =-%;yE (ϘP9 Bjc'>c\J* [M=ew|_{"8ZC?mI&.Q5+jb.rocssK%.'as$w!WWy%JIҶֹb6P6zEn}-asK<_31L[!9cy!:JnɭLU6yv;gq[өsK+^zݹO%\ON5-RUfo&1spVنkx/]TؓV|x?M հC/s['I͆mH..p_vl% ?Sⴎp.!C?m(.FIFSن4o]v_.zVn7Li+zф4[oL%ځtY;{U6s=&mKEֲ`hqH {WsWֈaE9GewniOK%ƀ3u `2ZaTVC+()rbn) 6m@,^7kn9j.-82[;Zd-vBC;O.WU\C=N^vuT|_omVWuHr>SPzF3,: RehT.ro,88ϳoP2l$jg+Y5).@VF[b VeғoߢuQKz[ҏsKc_snٿj5 7[6{I3 ܗ^IdJ z!kT^8ؒ{ O^C[KůX8s#y9"|mFpLake|]kɭezv g Қ[Rb1ӱᙷ iTmQ;jtL60n>z/;ꦞv{g mOn 6괞*T n K%;CPΓK0/7cVegyR.ro,Ǖvc u ~.뺭@u$1qL*z?]vY <<8 ΈQ:,#ޢuK}&  =jר[zEmw< Rϒp4츫xx҅,m~`|!ֳZ .6Tv9!zEmeتA'K]fqgeV6B}GѠIݳ"IjA]uSOȽYO$p 3s_yGOz?fܡy~iI0$^6xJiz,$CM?d-gy0rbB;= {z^xL^x ڵc6!<<~]ӡƝ:Xwls ^{/ zNv뽴sI>dbUSʴ‘=τx|9ZMw󵚛 \Q$a1JM^o.rolvnIӛpPL^Bz/ܘai%CYy%֤jRIWgovK2JbgcȢ{l")%vعeDniW}!F/8;I(7qkN!\e %e$!~(^6~hgϷ׷O[s| YlNwJ ˸C,y"%8FnZ*KuSO F6dIlN=",Q sWrGKR(n1.T.roc><sK,5-=ot]<ﺶO[Kw!I-qy#Tvvߛꦞv{ۭgX'hbGʃ -db47QeiNKSr^X#CR'Lb6XfLmluӆ٘eαfUA=-%[RWJbNNLBW @F.QAJ NJ.|*HO^ga1ݨ>g 鈫0YB<qRDi@rɹl/F=KX$8h9UPֲI7[$AQQ~~^veDe:14`Űt'7QC!qd7. ĵYo@=D=VTeEd. mޢWEmwckc֎~V fĹDq.I-gTvES'M^ntK:ZX@603r5!}c"J\/I)nEˎ]vdz͟ea0^06%zݹD(6rTʂ,k;?aueŠ=֕# y6~Kt͓a6OnZe'na1zF6>ƔMIBz0BIAnVXc{v{ұPo\W=^.x,qƳ=C?'.ш=>J$l?uSO ]gmRXS}/l|ٺ4zBR8hy$Q6uKOȽ5ij@-lc ̳.949bQc'A\tJM ɭe@Z =ew6NIV@ͺ8 qĹD=@nnT.ro^m=D6;|ay-%S6Dl 5\/}'Tocd L]dכعD9<Đ4P#nC5ɮ]v~ْN%nBVWn7O'W()JmKڅ|ONmw|MRYY6voZ|^^B&H1z'/d`9[-U囁8u!'/|J]B;QvQM="[ !C%Xч r҈q^pLjKYۺt"~m#\ВY;gUvDhnXj/7bxj}$W;2n&fpz~4CZd! k*){E-=-%;3j|gbI#CDWIIE.:+$^,,wmI*R``)#,zלĖ\/dGd{zٕLcY/e}-(<R?vE_D}48vɭsHX]ֳL,IAY y} ZG؜+T}dXنpcdeOTmf.M%zz!@-v f ͹BIwsHe e;uK}٭gA7- $n6-=o@ ɧ3uݔ!Ui@zՔ0*>x'$9(;;[G qPzp M MeXni)ǰF[y$|x[%" +tG({*sP0^ݏ(O_2%tcң"W(f< };sβGxX7kм&9~νWI:nkrJX}ˋ"@47BͳpIR'hE(V,suXH1M$ĸ5% >N>yEm{þ-)rrv"K_@' (܎mIݣ`.r_vMNۗc^T ++e\!%%EsE~K *ڨ ^ަZKA!kǨGCqb+ f "QʎLz5^h^֝R/Y68; ~;n%4Kb|ɭxr o1Rv0 %_'<8 c E(ka.qo,߾$^[}'q,7Ytȿ}H%;! ,ƷϺ]vk:g1W_UO"{V"G$vsDe7v0nm^&8]/گS"yV^M="[ς}GQIN G(ڶ  y)%TzYv]UVpocn-ra xAgtBj ij*EXIJ5TI8~s^P,%g<܆nNH-;BٚØ v/ ǹ@*%M)G)Ghy+Tqz\A/mĕZWu9p~Idz{S^NI떗 szٕ^Cʐ#^6/n{ٸ(,]HtݡȧI.QDhQXǭufô({Ev{ 3_rmMŠ:"_wdh sBF0'dmWl10'd+a''} ȝ\[jwo˳^hWC*/AuSOȽ/ C9YGq>̤e\=$&S8ʮ~/ꦞv{/Ybބb /itrIonŮ$8l(./Tv󜦪zEme+0.'rr 'n!RBߐQl2RU3<܊9 ˮ1a.p_v_kdd>$OC:~wX-B[`~ M=jr+Ʉg"r~k gv-P^6+#XN[P~[vk|AV1o) .2v|ADiiĨ)Q\~KIAq[/]vY'1[JIib{g\{WDII\+[_uC/}٭gv%H t~BL0?Kn}*IUܢ׬zEmc|JlmaedaWmBy!Wpj"t.Y6r meY?}dz/l-.OE ۈ!}5 lgg&(B?lu^vםw@H ^Jk@ۢ\,D#$>> F.ro,Y#Vm[RϸRh9(b\b'"AeGf,n=KG~l\4-je?vksWe:^}fo.X6FRro,sKIxh^ʸmi^C߁j74}n)I:Xe7[ni+zI`ϴYV={xɹB,qaʎgQ.p_v=? >ؼ-{HgqX`UqOz͂ԯzZJm%ኧgy$zd8h#7ț .Qs/$ڈ .~GuSOȽ,Ν'ӿˈmsq<@ TBc(j#u _$*sv&j2(P-J\P/zn=Kҵ#U̦3Ur+[ꔯJb'~G ~* ix<o<7K47.Iq35\c}2B-^\mH4[8 oq{m]6yK< b%!T]p&\Q2ec-ao>yo1o؜'!VғK=3$βר[zEmw'<>e&/O)tK?x3Bg Sܦɀ]rE{F$_봫3[56]%j@cxXv(M=";#,F) ʆ#gk#U\;,w6e ^i/cOx>L fڃ{Wiz0cJdHM\fa@+K,2jwsS6w_?6p} _/o_~Q_+_?7Ͼ/~5nCh-ٴo(~G /?7+[Wk0|}< <5?apu_/ H9^,` ˮ~\b,^v[릾)4zֳHb-Eԥ_HdfS2\hHb:DŨڱ7m7<u$)vJ;8[(yr:.#qqf.p_v33|nOϯ.67]θ\^xUNni^ cj2mW;og; Mkd.Ϲe{j2z^JMv+1%p*t mg!XRE=/$/jc~!er^v״>+L̸lcXxb)I-~`b|[]B[Q%7qP6z8P6uKOK vga[GƁR0 !Py0lX\rl 5^v2Aw`r^mr CD84!.Q2%x@s`{@k-="; G8 K Ĥb# 3;䴞{=:{wn!SeS{m!$YvkȸT.G_$+#eE4{M/HmeB;Rj#ec Qz^-.~sYq,\b*IVl ]vk|pd-\bNosoZ[$_S\*~[,͍r, }ntkځg٣4Ku0%͹({@,. j/IJ1lȱ[bY+HpG \d`"(D@n1"\ewO]{a:d=0 h/l_V\"x%Q3V@S]v{h>F]Sjڊބh{\.gv^vm^7U2{ۭ%ܒyτ6U4! }Lq^v[>ů q9_!Nl sۍ=cKWĚsy~M="[>% ܒMxDN >Q 1z=b%jlq-ɜkK2/;+ݩ eb~ոKl/o+҈tj%$Ӑ,Ee7Q.ro]Fuu;ok+oD++xܹeg򺩧]jjU?斒Lv׉gΚ[69_3 הX,Rר[zZ:_h]s5u!/.@\=ɽDQՕ\^"IP͖Xeh+ ܗZW2]%7%gnضW`e.Fε+Pll릞v{ۭ~̦vc$xdR4O\2O.I 3ݴuSOȽVXu[J2x>:v0o 2%χw{RjǑ@tsްߖ mJM}dI,yl ]/K {!F6^m /UZ+u!Kڙ;Bni/?f{KK,B; 1 v =XZdXJnU6čf55za)+ K idH}fP@ώ Ǎ+ÓNE\{e@="[mgwm~^1-!`sDP,).ieg{.ro sT{| ۧc~l㫭ЇVu޶.K#Kk'=M="_0j%ƗbNrBDGډ> eeRC_4vk/i/X6pmI{ΎgBG?3W( %OOsePV@PܗjcvQy*|/nڮb9>ZJdNm_%Ά{ $.v{qMs7^SgDKOxJ .ъH JM#7ÛƲH -=";^;L] %Q!M:&jĆ+<Sj)l_++ +ci? <_EIKA9g'N ]Hz$($)xrrWIJc/IuSu⍮&+0%i<'| }sIT:.)ǣ\Ke{Rizeܷ1O>k>O=-\vm!|s 8hElJei&v>{6q ?X.%wZQR0#71M=*/T|35{`~ZSfXs͒X4q%R@S.p_vcs%ɲ=,"OθR}Hcz&hz̕$_w|(H3COȽVCbjG5?,Akb =-6*q`K8lCZ!XӮB,וEI?Z:oZ2tn;l)P,$DZݜ[<(וܗݱOJGmxFkzɍs񯙫泃NnIJ*ȿzEyvz-} !yta/[4I=s nN.n/r%E 9a0L8-.ъ%%\Rb%U6uKOȽ?3s+}Ikw a;k`lOiO<s% ];niჵh"sKƘ\z3 OqD򄌒LT\ITّQuK?<[Ƹ_S'O;Ec?z\".QU* %εqq릾搴`u΢lp?F]y%BFJoN%j\RO\˯e򺩧]vǸ^۳ψX=_X3ݡM mX៯܄t qRroc_{E8%q < ŅiDB }qD>im\q]&0쪊 O3X޲oO[?wS{C̊ \"Muw9,n^7+4HIXjBFOt&ܸStI[se'ni/u ߞ-=9k,0X]x"ay+.B03xJmuJ k[^qT眡?ێq>ѩ*O\%ò_:.ne/:өfIAEufbҏZ;!@ @HNdRSl@KkmX0ThKҋ[V.93gOd?e>3\d Htβ^7kv_IO>psf;$Uq%\q.Q,~T&\׼l 5ꦞv[=lf~\LE"⻭e jSiͳ*@TQbnF~ I-!5?+tey=g/TsRZM<_vtHw(T'ָ/AL#0:-L;3B_+C;Ij&QT7k(@حCZ3,@Aƭ3QO iȣx1` =xyQꈙ֬5ɟ(X{EfeqMNl1^8Zf?ZߒkXER4I;$x#Sf.[5i]%:g=гsw]m{:xBW ut*ճNjaMSJ/WH2gA XA2;d] .ʆiA.q]ƢP6ꖞ{ۭχc0O8 [o᧛P*e(nT)mGmSZ$|3d gF~Vϳ|t.Q䫗Ŋ[XvWӮB-FM1\󰜙3?>ta+vBjr g!*iE: k:.lmo,6n&:Pб k xu7 r_.+Itܪ.Vv$TLI}٭NSn6IB[Yq}x̳({>=i`*S':zI:5]F%'YErE"dNd;o@y7;#/.R=n ̇&La,J..yyN)+:hh%ݮ1"1퇍.ro5pɧH%6KT*SEN8j^Eͅc*^7nVl֝7 gؙݳI+;J޶KLsu(臫SKn~/$$!K,W 1Oֵ!DXر~[\!Kp񺩧]vkfki7N]A5ۦ97sP;#4@@ў(^@tI-7`yܪX`g ϼyϜʞ^G{C-*z^^0YmĸB([=/7*RsnȉzZo?dkd\*Ig9 ᓴ٩mv\"?!!.P~릞v{ۭI4fsKKf!L,-|ɹDur%۬ͫ_ꖞv{[gb#]&ۂtz.3!M~ڮoYoKພDۓeZjin5`G $ZJYkHt@>nBC~E(.nISM~w.o{YCgv^LK|=CN-r{CM={'wpʍ'ZXCe5P%Rl -ȑqVgŎX!Wv".q rE|#^7 ܗ39mQ|{pak^\]l4 e'?*vNZ!q.89_:H lN_Q/$AOf!zvGF]p[G#vy`JTz#.ukGBl?2uSOȽ֮f3/<;{iP"A.nt.QWإK$NzUa^7ńj-Bg1pBf N:ZH2re_iMe&vsq4ҷ7fv*Ch%MnͲk[zZJmwHJ n㙅38O깹'#%BM셑;&ቘUn7ܚM3{ JpNDgD%̈ ifo-1"܋أ]}Yw_>/ ]- -[G#X}گ'@Q`Yt)5ZuR k.~w[5[Yw d[nPSZ&Pnw2.sYjQ'&ߠܷ7D-* M^lFЄ4{3vĹD%$=M=";"N>` ^BաMþd vpuWldE^Nja yzs pU[&vƊ!L0-Tjq8֐wzc;%8AXʟONy$@,\Ze7??]~?DvLH-n|k[i#XqŃ7R:5ݶ!"_vm=cg[*Zˣ+K㐥aImg,.[Ւ|h͗5!ϳ!hBW-%n$mlQ*;{>m&˲oJ{k d?;j-2i;({d$I#nH $Ov{gݎ`-hAwrs i﩮yyVs r[lC`]vgo(kfKB\gm#3eĮ͆ZfqbFTm:e-VY7 ܗtg [FbwoMl̹Dw$h*;گꦞv{ۭ1Nm,:>1P* {Lt旪*~BSrW&QSܿ]v5x Y6l;{ݎzeKQQXNcQQ&/Xj[CsOsK+Zzϋ}CH>k!FdK]F.5Uʺo/3üPշߓ곴CE%CRqܺ$oAp^fO @ ,`bsLM۰n#DqDMkN3(;{ x-="[jWF.Irw5j]HB?A.Q%6C=e%UR:c_8o09[MH_l#.Q"I%\.V]vY;Vm|IyϮ a\!+MI=-v'.^v[G}DI-Bi5GĮuI=M=";b;*~;?pEIm79XB-㊵^PcWT"h]릞v{ۭ XS>a@&p')8J +Ug12w*]$[-d %Gd ,K ]qr $.dY8S=1t)%#Xhd= 3Lz^5PGJ*57{.ro\/sՆKP۳d@Ɔi]PzLuKOȽ֬<#\+y$vԎc>b ^_AӹD̥YHqYKnqڇo{R,0m;h_/Ui]BE%ewUHZXmpS۝۞ %C߈<ɢ"uv8!+.Q#J,s0N릞v{ۭqZ~=]* N0A*t&Ac^\w`$.IY7겉;NWWm%],lO].J#q!9A"q̶½niqR|n BrM;օ48z@M%1ǹ6x9X7$مewĹdl{& &CHn3ƢKx=.REߢM="[~crIwĉMY6Ǚ 糠lBtfGų*Y}I-!U#@'$1 C>VҮWk'**B)1EJLꦞv;VO*?ف Jlg%TRaD ;͸ceieQaܑn$QXKn5ݡKXj`&XvHuSOȽ '}s.ׂ;ʈHU\l .܃2Onǽ,eni)ZEv90Π&/%#w"eOO&PhGM+Q!X-/s/)[ma4;M;Uk.8ݮ"Va?mH[r8ȯwI6૲_+]v"$|B"qIW2{Bg, >"GTRǜNja yWÍCrR%}.d?qB>^[_B ;'s F.ro5<eu :UG8VO]a\/;l Q%m&aI 6\a’/َ+yl$IfOnL/h[p_v^ v, <=YN cqls1Q#((+rR$1n&䈆%\|&6[H CϘiP_ .P\TqSuC/}٭Mm=c[(ށf:pGD3,\z| wH;ŭe*#JuC/}H?&F*r/B u_w, *u}Cnr┾$8.㔾ꦞv{ͮ|vG iȉ|݂T?/=ٍ˦=xoY;8J?EHjA]j찓h{+!#R}J"ۦ6Na0Ql@(<,xӘRK T FXN tх\+Pl~wD'bi&n+T s l 791v6_)}|9{b M$K2݃[v]=I.roY&j 7+X]=~FS1.[\dCS?]byrQbUP^b?<;Y%Jba N.G*;b[z%m-:ٔšO;]DȊhMH'"=N I1-wg_u;eҨSi}aw|i~V Wt/;A$?l)Teܓ_c\94niݑ~YǬ=6r&m+F9\Jm?xMa* KMRGSVV VO, .9#;u~IH%')kтKT=Ѳ$KNMBNdmͺ]EWXEь]|;&>3>wJ."ɰX6uKĽ־[ӝ,]~6B؁Bi^+8NM8v:5]j5e:˻@G$89,+HIK}SE4t[vd-|YMOȽV8/&~$.ڼ )J+:#Z!jr4s#!nMvmw;bS[b!LR*6I qFqgE$%YvqX7ܗzfp0AOݶ8EFyǚ#'T߾A$^ÑQF8Nji9_Ra<.vX=qaumBxSP H.kv೗ F.qocWu?Gxa-p_'ϪiI#q*fXSX|8Zqy.{q^+{$ls{a/tQ[,v?Ҹ۵]|k&;[KRVv<bݚ+UM ir(KWH=i@Tq4^=.Ee(̚@Ė{ ]Ls.vw*i{iOCh"b0hBs{clJim'lu2_@,0&?k+(HQ;:3;sJ}AZbĚnSW*=sNv:iKր!ݦ4vnэj$ۛ=4W|ۓ!@,ɻؾl c%Gf9-G&/rYm\v"w I_&graA Uyj,yYDl.Ws.O[*Tof}AL8ߕ:~ >\ҼE8Ǧ[*ceN/o~߂{Y3 \TsBķlťndG?avN{Ms.H1QݵE;{ qG OXվt<)(yKvxB[v%w8C2KTG{z6qı}~tvʁJB.OS ,n?cxw;Zw.yţ.~mԢ{5 ,BclH>`n嗰޶;j\'6oRY1Z2 "2vFq~>}Ĵ=>Lؔu!˯461$(oR-B9RFX٪GFL̣>qe9i7ݾc("ZSܮt8TF#/UU#Z/VwY7ԄfDpdҨ0FW?IYvI`{f J~Y R) QQI!u.eNh%M{5{֯]# _`% qXT]wbn嗰W̺٢\e$`srm;3؉ )Ylic{lJք_~v೶fϕ:GWѧ;,2ԕXI#"tRpL3Cc8xn嗰{"^/T <-~'૶:ŠcqZPIQI@\!G-q՜._+$z(Mf$bv0VRKfVYK]KsD~ L[g{bY2Z*O9M_ۊg8 YXVL,P>3FNn_\zTJ+/^Kz#3ɚdUblJNm_~$nEpTʝٰ ScpZ*dPXKVy욝4Ё۫I"{ \MAxc+ĝtV'k^F1,+yv.#~_߷ ZY8 +[xR PRQGf>pNZ qYײ05dH_ɎY(8QIygE6"ƑY8NjNYM~qIe N,0P~M eH[O)ɼ!+4|^v%S!(itCIm?A:ݶO̸ƚciHL9v6ܲ/ao&֐nC+5V.R ʾH#uŠQc_DvEoжE? SZS1&pgtJgSݟWJΡ)&wdOͭ&zm ihsk}^&Iilw'n m_h2VRƚf.AyrN[v%a#FfҠ>j&eky> o4noܲ/b?~{Xzb͆?:U_K\k XXIo[Yn> ]4ؔF>#Kl]arשg%,lظliζJؾRok=|5Ʀoݞk2,oF$WATqDl#iWPJwT`7Ğ;2U+znB =b)B=\)TclMaR+e3cSÛv%c/c[xyqvo_{XK#47}j[aM"㷿/VSYT8_R,{|۱)3~+@i#ƥŴT!Rfu}!~cQQAJLmle³`q̤7m90ws[$;v:ǜOb{b~{E/'w}Ɍ[v`nFKEV'ORt'/ O ߥe' w ``d+ QXI .p OSVGa c?r@!Dm'>TrmݧFPS o|uDBмg2HL (Ur$Eh&݅v#=Kooz@tbt2ϟ'|A忋M3GŜ6׼ٲh0D4Y.unL`X¾Rf֠j%L}xbn}BgBN[C.eOki_E5hXj9[v%{NrR/Q9ud-;wp 9k=kpN[JA/qwҀUGJ3ܢ>U>ʧ%*y>ɨ"=?Ù.Q&㹋;͒P5[uvz 98΃J/H ~clJջQvKʼGds;Lh3z0)LKLv…VޚAK?Mn($Z9 q꒸a(xe;+"44A zJivEoӑR4vE̺F8 5:@ OffrNYMqW5Y$u%a^kP%U yۙfo lq{zn嗰~^ҌBoɞ7'vbt3a0u#k^ zؔ%W[z*wOFIkDRńɜjr„OAXoω41VL4vrxJ;ϲc}aAڮA1ü,>!#4 bgО[ E$l%)24I< 7 kiFsdkЋ8Ne_~89F/0*Sa7G[v:rrb%]d !7+R[ۑ*ج`ZYz]fwi?3E3}^@ Zsl (n+'E,H>.hԒ )+!5Q*4xNOPz|ө3g ̍x̝4v`:y=)g~gcgs.];糯>'Aj`<@,Li5dRȚ2ƒ)c'~;y*s @'~<51N>[A'_ẫ?Ϩ19i7n&WOiUp!zZ=qV ޤHpWL$d'))P`Csw}攕wA2{5͸CΰUG!`Fp s o|FGqkxޓ[݈(0h/cCxh* (e_#Gɔt/X^TK<5W%ғR"g׶i|Ҽ\UͥW-y!nKsYG%}~*elcS[U'lO_ nOҕƟlXI`{—xk"_Ʋc'ɔ]~ULIgq ) 9З MObn+ČD E Vxc(&QJkEc(jZwޒ>]/I A,uĽ>7*h5yl}5DП,D .f$8Ir#EBkh*+C[cGBkM"-Cg )~j/.Qp0daf8 -*Ѥ`VXq'98FWozOl5?gnj}$Ec_8 ١^f7PQ{l4F|OċWȕ):([eķ 9l4"T`MqZe_~_\cU~?B{8ܗop]BleɊpݞL Q)+p&Ȩཫ4m'zpVbMTѾؿCXKiexgƾ84Ko'/ W|y}6%dV9V i= <v`us} pSz5?OzJBfOZwj?. +qE5iN@3Zzn闱ߎ IҐòp^MOezvq{VL~yQ{hN[Q5@5ҷ֨8o^w' ~05wnswVdr.T*;Rq~0Mkusuq} A'Ld_LGE *R,;!i^[7|7\]DhEy ˰oo66si 7>jk'<|z.ҚKY5z|?V/X%̬d~L#LĶ.=VmoZqGN+>!zh"_$6Q&k6D=6%iw~o:hfwQR> ^/.uWGJXg!lųk'[3s<~N}+n u(;o {ފY(ְBJX5v[qm"woo[Sng2g̬ 4 c-E*5 ,ž۰cSᗱIS0ykiF!9@7ĪT-O CQEa]`kn婰yHeZkHֹ69Y>C2 UZȇ5Jov0Gxnjok?-Ґz76$Ul TGۗR),?M?͹m_~gD:Jg)L>Q9$DDtQ(ba"5*GDRƸ$9Ya5MbKJ4WåeډTm&;PIYl]~ {7N Ml! ^{P@5!"hڦŭk#F]h9m7]w˩D-T:By oyRVZ3/8]!S֓~ٓew*ܟlt&Osj[>¯ w*a?ccGh-nwV:f>T+KS6 2ʖ{^t} -.2/,kH9i7)kvP f1jYDٖmb_4q5/Y2s.ObYC n6S&G0yhO 9pjEJp1i,Wל._s+3*!7F1y\BigVc%]_2iZ%7e_~;U2[ԭA#{yvNy˒o3 RZCcs.Σ.v5^kTv̭&oRZkl֜ƆT:hTr),y'^-;N VTXCkK~J48~ WA޾ܿfZĨVGkfON[fO*=z0{rm08 5/ӟeV҈*krX֏zwU[v%w^uCk !1aTeJ{$D -'> q3Ͽ:LY{6+ǿ310u!TyC7??cǿb(yZ⯿˿_]8s/q[c/8wG?Qo~Q0ޑHr aHA,?CB,k?& Qv1_g$`a:Uց{?$/x{Ѩo0jN[p ſxN hsqY].SLvߴFXIut lTDv?u5bl;FZ(e}ێt;XKg 6ž$ƎmK-{T^o[:N'z[Pk~K=Z;I%aF/a_Kc:)qlJim<]iQkk@B㘈Xhj;&"*hdWQg՜n_>3aQ?5(JL-V̎-Y0v6aRt BwzauMf-"^خy14ef[怲#XK[Ѐ 덱3cnwi9/$o\ Aߍ96{kXl8 $.D2p uFw7; ?Vgt$ N3}3ތIn+vn $QGD,5W=I7ZXdR_N[X:Ž R@f @yn婰rUO.4(<%;% <=J*& Z6%M?Wۯ#wc%ZD7 \{Nʺp,{*juVx#+.,77a,c;Q-aD;pĆ4n ʮMJ  hΊ4k ٙ4yO˦04vQܲ˯Z9"skpx`[& (!(d m~H e[F$Ʈi_~+|;ɟ[X`y|kG>Ӿ[XIݻs,R+clH>O嗰w,@=4hMaɿv˥'G`c{nX} Mc` !&>L16 M9"'ƎT[v%-+.kʣ(V&vĕi쓒86zMVB㍱kjyn婰<& uhPd8J'f0%1ΏFlii'Jm],e_~]҃a44ޞϭ+`:ٽ]XI0 _asn;=Dϥ`?z+ |7spuL8 Qf ợF甕wWdG]~@N59i7ݾ~clns)y%gutV\GuM>=V5j`՜._}WQO$|>%'_lӗ%FIXI۷7N=ݾ~;-E @Xj>pxݒ;gQXI<,ƎMj5x'PB(%<M{wUOH3o@MsNb[~q6 MS0}~gT [b< +ƹ2(Q{4FW '1Fhpq"cUi/fXrTmS+)1Bq`ܲ/ao}f<⢟hQ\הx^ 6Ruahpa샫Mcsn嗰}A-W+ןdPn:q(ojXGՊPO+F}XsJo|kThHGE9F%/[cIq+p b29e7ݾzŊR?Ґib -OK -/[ +q5L0 JcSOsn闱>=u>Qǂ1G*ȢEmHF ,]AؔTe_~Jg! w]B:ްvQ-SↈN1ȝ-wAz|3x ٿc!C`La!V3G}" 9e7}|?fIp|MOe)Cix `v_J$ M ?m~vMhCS%@"w[5NuZzտjC ~R5K؏Eϥ@ $0O1uF +R̍b4WȕnORbN[Xԁ||oo0x wzmՅqݥ)p5|"5j攕w qVi( Xr`fXI#Ϊ "X#5ΪvEo?I=swAs}1<{Xs^޴B4Z;4j혻\%`Fϥ`"`+f8yB맅ı,mž cSSb?~;4‡'/zqEr>> "ohj kQ)G1tO)XNBd^GiWAV k?0 pT(/c,MtKШ32hNYq~I^xX|[e}[F}TKX3$6,{jMɻ3ToҠ/⌅fW͠.J|e}xlJim;2AަR`3H#: p;~akEZpJ3r3 `4*J0FLC:mW|ϥ` Y'ĮHW}7`hB)_r)>ģkNYf__V,wb /*d A^YjҌQT^ZB!Jto݂F,ojEErI#O%DBdD;h.TJwokCgi__l|gK:HU+9Fσ>+< G-F5sʛʕɖ]S >=l@lHQH``7Nbnh/`~E`})z(}pD^Sۙ/JkPdCǦWsn%qCxk gn)CW;87w,&'Ʀ%{̰Sb?~Tބ3픟ֲOk VOөJb0uR؇~Lxs^7/۝e@ JT$^eq "$)8SVz#k"n:QжnOs+-KR!kVbl[ǦWd/b?~gl1X38e0mZ%2Zi2Vi&Kh,#Β{~ {N M>8'Ƀi qѵÊDB(H"C7G- 9e7]z3 :KF&'w .6Qcft"8 ͩHV'@JQ"yNYpytf5õtvc/nMn@Xcbܲ/aoPCUu3ș^kaW2ݚQ y[v>ҝ"5̹n˃ǧt$ܺlQ+`*i֙va%X6Js.G٭ | L˯;nSiAɗzbd"O+5A'ʥa}hؔ#K؏>1v'\& )н"eZQ .qA)MoVzCkw %;Gw0YF۫v +XMwS0qkS 玍=e7-$9ă8Ǚw;\̧ܹ=J6>Wki$4XÝcnK߾=Ni*4[8L,#w_:+dr4;}6;/"sS~=LGy5vJNI#B$'Ҷf`% ؓ{SblJim;2ۯae`cqs0Vhޝ,75Yv n{dܶSaow(ա!C%${{QlGvo`%nZ[c =vq&@-Z5ƵRlGÅj\BbfwB,]=FW'R~U/.7AN`iJK 2'+#nGR)pK!F]AB9e{ݾ$PK7q:;Q< <1LVfGz ĞCɣV=wd T0%R -R'Umx|˄&G 4S=q4fºJε'k<9}'[y-'gczc)f1cÖyܶ&5ޕlֱnۧһ8Ԭ_o`-ų lchܲ˯fv8r3[WY{Ӓw}k)A]<6%>`vEj_B|(=T>4H1,Br=To]2s) \.%:$Fn|yLbUpkyT \._= Bi /r&-L7$c%=J"MC\M?͹m_~_gwrN-?A 6%gzp;+rCE5Rͤq :FsJo| 0 g0= 3 %߳( kijg zpgknco~'?b-RmlFUٿ`i+@RР+b*dZd Tf[3~ݝsn_A?'z#]ã40Djw@ѵ[;`oXE̹$noF_X{%8JXQ(lKRSָNd圴ʛq 3I燑 KeS*x+J/%ٯ2NVJa%]hKKZ`hlJ޲*xT[o5"&418N2V|ûĎ"{r̔"&4{d4w;Qmsgxv"; ۱CwkM`I&7֠U`k=7؏t;fMgLu U,aJ?9m7]:R¤Dq5P;bRcV%5ڛIIXIOLPaccSOsn闱;Q$!aO>R"Rp4+jyn5<_~n;Li T?b,ӗo"Zcnܶfbc8zn3+Kw&Z-U'SrD4WQcRJi؇ӛ~LZJ`?~gmFZoZFuFJpE!k}[AoT U\Aқq jatѹahCq^%,fIަM:ƾGaE}ӯSQG4fނF5-CIf*-\8x"v+섵6W.y6gU?Rb(ad+X[>@8_2B 00Zw VRtVkQCUwkϥ@!tJ9#ϵ >ܰ2B8 +I`n߹;".8F|NV3a .F_z'`I$dwn32VdgUfl6c0vxnHJ?Q$+J8Tu Ǝ7`3˗lTJ>KsJ|45b  zVOC7:03YQ{VsNYp;oRk: J:l:ɨ%~{hgMc-XAk`4]~;'3OjA9휤,ۺ@uRd#F} C._**+%O;GRNx46NBKt)D7ȫT_sN[p'U$*:uLБݲ7؆ ci8 ѥbD8Q5sT f+w/˥ xYD奉$7K|$()TS۝~U2+/b?~_ {;&-c2=$/1oXKd ӊmL-U=؏pVHjݢ:Ն5 \#6j+\$b"@8&hH9Co}2X(އ\ԅ`68wZs `1HQ39mmʢ/uq/uq`# dge ى (b )?xGN)kQ g__V}j:шa %Nv\QHiEhؚ\"acg;X-;(2o'J3p2gC6yWۢdjTޣ [xִvE !95h!~޹Ѝg'D)֕H`ƊScSOsn4}}$H"{5kZWyNNc%l'# 0ƪ.Icx3㷟 4֐ǩ|PkۃWf: 5gh SmRJͱܴۯXRH3e"y Lz_ĶLk*oecg4s.uoz#Xu>uSͮhq>ؓ)/ٹmv+}53QG1XcSOsn嗰ߙsvPqBO򧺩IG{ S5ġWmX;Qb].n+M!|a~wKb-+d5Vғ|`=ƮyϦm_~ɼsT`ĚbY\Q-Ϗ(P,[Yk1P7}] {0R|YI&996%4] {o)5i>"e߹L-+ꖞGc%B2#ai'{f.Z`Qy5t")zJz2U–vfsmoXh s)xxV3|n E GRphQ攕wU!u &^Sy<¶33XJ?2f,2K-M?͹m,uMTT@(òY%ZO A8 %RpfRm!5RgYX10gݒ$h.ccG[v%wY\< N.&h, =M_JJz2 i =GG[ +|2v997CAVԦ!ɔ}N5%NIXIOH3gk1]~ ;㊓ofݜp߹"dd+iĭ5( l͚ǮKܲ/ao"[WKәuVdb\Î{R+N~ONؓNclJe~=b.!4?Ojy9w'ㅒ= .f/su:clJ~"#;2U~#! $v"E0+$HLIzFjX9MU)_ݰ9*h?tOW66"qi=7\+), Ǝ@n]~ {}),JxǬ%>͒w"5!G)%50VYzӭו𤽹uZZg@+дe.h{^b`kWVCVV8ܪy#VyCk)=r6F kY`ZiQXI3!ݽ1v[v%wrD$.;]z7 $٥p6t$t'UYpF9e-hT'rHfs):9_*(CW/aI\+;zMaT d7]%\a nJ FCiL܈A[1q͜Qǜ甕w]-ˡW,PB*u HNB~IݍpѨ%n5?;سv$S$E$N`JXCa4Hrm{q N\ 6 a -Y $lQCEeqlQKpNZ q>JK8.L. U<uˇ]mb-YxDy:nGzsM:4 /t|j`M ɶ u3{t\IIԽh9's걃8]~ {W*'eɃE2ٵV M\ `( '-\IAna3dP^:7WɉIx'8=Ш|o|oxCkz}`(~~q0۳v$ '! JqШ.-fqdĦ% K="D$u7=|wwGVҌ5vn=v]~ {[)пŚv`ҠxC;wX-EJ"MqWsOH+Δw]鄣Q|UEkBORਘV' 0q)V `Y;ij%D+&|‘F&攕wYf! NAB)ޘcua{c%E34E7A;y&K~'xB4};X̀:nnDtM`[ B͒Io@Dh5,zPCu\nvTMî*7t Xsk:bz3|vG+/!Jj,i2Kzn嗰ߙxcx~|g|~~686ZmկoI#rmGfx=9b }_' 5-_VÊ6u5t"$"n򢂣XM4k/{VIa݄7XxO;֌TL!a>|ܶ/co ?635 q[^` f>Y'$^M,Y2cg>~ۛyl&J!~.xV~4 `O[G:j@VP0QG5]q]x%N7HX>to`)* |v=j7HSc?̔o r-I%)Ґ0+tdKR6?"qM%[% )>wKRd%)z6B˖N+.&,MeS4y4-OKd5WcSwSaoE)``oҼ9{^>Q:}xOQ$51VRNog*ܲ/ao!Gyi5:5Zv1dFɔEfik Ջ~3O`mj'85b !w.OcE"*PT1rm Mo +8(f *3u[40*)?qpZudo Üe2<%V`ږec%e_kp lgt=~= o\}$5dܖ2nYK2@3S?]uhaERqU L xSVz#kJt hܺIKCM@VTG!MY~LʣF))kUo2zUDs0+4]#]gYX?a#Ց%N[\=@!l!u.li_~+煸H<51wFVaB&xw[T'zԙ^*| $q\r{4`d݌eL͕l?a045vRG&ܲ/aoi_$ [O} |H*WGaDW CѫG՜n_׽1QshOfjW q .'afJ ;(,"Jo}8#_2d btϨQți)alҚSVz#k>;dxn3A;ftb1 7ܛm~Dvv~@e)H8 3.޸NaUH԰қq 3;cF[Cb89n.dؐ.i&;"]~Mpߎ<ڐVظd8ڊaz"YmEqެGbWp|{T Qi-z|yP<Z62XLb3qJK7<*9m7]Ibj" 3*يqM}"HKb(,F৭=R=m޾ .NE?g C5˦p VVE<'׋MMf3xu+WK<Ā$╲ı}%^U;&G6ܶSao0C/rh:jkOV%ע2+Ua%5Ρ2W6.~cnm2Ѓ-5;h.z1[RJм7c'{] {߳C^'yF"o+rТP q'Zb/9e7])EKUQȨϪ 2c6[p0)1$95*XJx#U" 1x:Jo\|supFlsܱũKsJo|RZ2$ d(}2~cS/+Aਾ,nӸ!MJWå w5 72kW #[ Q8/fiRPTڢI攕wz]vqIM5;N҈k:;M K2bdŞ[v%w-dEznFN7$8[ NBrDIQb-\a'+Z@s*o}6${qmE#4atPVgmW-a'q2ۊwjE&洕@7/~Vz#i:%&mqJs\l\NkyX _Rްɍ/)ԎWR +/SQDtœm)p#Pp/3hT Mn5FW`Q<:,K9nWuͽc`E8 o0JQ)Fc>ԹfEfu_sثMx>!6Bݵ ᐏQkl5FjjA``u4n7h&pwEQ-,B?lz},Y/Ɇ&l[klVXK=cil&l=F1vu)RM"_. 48+ T>~qlI/kk*o2˛cQs.kvbCs_Nkv^~r#҈dAk:vj6J;ZܴۯF&^G{~Ae6l=(R"܃N>q9i7ݾf[CO3{1tRto Oƾx_.U]iV/N9-yeOp@XK5x0#laz.e_~WdFϭ Wzd.5ݒg )=TY f#sbYp|G Pl h)% q'!/V84nSU圶bWLc&Η I%Y+[(| ~%+G*E._i,8԰UiHlUc׽EVM+ZiaA>cCOkn嗰OWג%9 sǘ7GuE|$v+)AQ`3s.La^OBYY2mmLiT ~jYqIۜJ\ ѝEM2ƘM/TH1fBh<ꈖeSVz#krV$Im-PU)Ago[Nn>IdKRbN[eh\BƘYsN@ՊE^H im_3Ҍ 5Dvj4[vE$gLs38*Г~eyUNzALIR\56-4^ 49ʽpm=%M@\HXte[FE,cg ʹ?dvX*i< p5)(ždcS_sn婰>ՂA &gf2a'i, ؾ0V҈56k[v%35Y,/` 4e_xK3rjacys|O`t%vgֶ~f;vdY_}{/b?~g@SᤘLilPl nw(L8j{w)+i0T ]Ѯ;2!qSpžaE qjJADHQcQs*o}ͺ1t/њ/ۄAFoGl@9*ƆԳRATV2~kO4Ko_vgK(b O.˅u70Gu&s6n-,cT q[J|=_K7 endstream endobj 455 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 446 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-063.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 456 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 457 0 R/F3 458 0 R>> /ExtGState << >>/ColorSpace << /sRGB 459 0 R >>>> /Length 26993 /Filter /FlateDecode >> stream xK%uۯ_R̦{m@ H"AӦmߌva~uCw3W1|ԏ/u|eV>Fۏ/ǿ?~)_K)/y}G+}9>h_Gu"x?Q׫G/q!?9mWzOz􏾺 ю+븟&gGGo~]zo#c}9V9Z+O|vX{z@=opۡigz«5{ޠủR{Qc`{hqO%@pkj_ >l`4|<޶WU2@*N 1WٽVk\+Kxy5pjd{Kp5CE?[zݳGhiC ߳- Y5;^v|{ V*V=S {{{jlW ۤ٧Kf-^鱽G9nP[߃.Ayj'<=ME_X #tjPuqucs`)8hh~φbRo^(t\=^&W0B#t@ovlWT7xE. r`=>G:^F\xy_ 443`v ,1yElWY+{AvfKV{͘jMmǶ mDxv;O$=`1i=XeݻIEPц1S7ތLX[}ڃA>fw;ۡyK'^+YR}f{~;{l=v^H]?#,)c{v}l `1'W`2| `ޠv{|@ {|L+uw͞;gYo'&D&,h,޳y+'w~Z-{ҡx7GC`I,<+\ O.;m456ތP+}4ހUnlK<i!zIя 6 8sw =ے9YP-lo휂_vWQyNa=}I=Xxlƫm? zzw廕] jRYzQiCCuf _9 xOj:<*>O8M({:HT/Xܩ rY'&ijt&(V֡Ah _8nbPB f*N*OOD47x du[| OtMֲ';wfߺb}QI&ܠbo{.>gt ޠ-F ,ǽuW Ov)p7ZiRùr{9t \6gb- ީyvi=]s!pKooyi9y7wl[{%ms20'V{+\pI}&~D8|D mh8qGLiJ0c@p89tmMi!ںwoӂ_zQQ`u|l ЖzzC@GQ`}lAC˔9_J < AĠ:9FUvx+HqP= 'V2~Y'*)vJ@6a]^Ark!(e&o dWuIl$:ٽ<n+ekm~L-ƝOlVr61/V手7J:WV Anphc\1\xY2?h8x'̷U^paPEˆ-zZp3&u!/ӄ|0> Xt0A%%97xı=i:&m#P ©,cZH|cG'UO;r7Co^ 3gDjRW"Lh3;S U ߠqa2L+@;w 0FƖw!cZF~Y+ݎ?opMH_̆9m FfsO6~O2?=:޺Ԟ `O֊SvfjwsWcKkIwqLr2PI,>Cj^Ǣ jK=i7ȶzIIKL\;݃fRR(˜%hjqBaIJI,NqOh¾'$)q&=j& x:v'$;=-vX/NuKB\Iꨀx0kxH=|6 3Bּ߳c a4wͪU"ϧx ԐU޳{V}'[,/P4Nmic oTv$,~ZҶ@8"zUزGe,s m'sfOvVJ2Pm͢{ o6Y<.#rx"e:9X}:5`:NqAkEFoP*!pPJJ| {Nޙ8=BMoǩ,g֋i@|9hMSDX,{|$>145<יGg/ǛҼ]mƌ%^yߢӌ_f jjގDV t[s Ulpt3a!JzOgQ @f|IA4QVAȹR@W)i9^ZUu{0͋n, S@&d§}ZeKofJ8fU#0~~eUș+%ӹA @B6Pb΋Bȁ$s\rXqN N/xc\h0(FfDN|m:n5iO94 AS0} bQW*ܥr-oSLؑi!ivP\isƖ1L̀tDu Fw ez2?I xnwOeIx۷鈨;8kpI}oNآ\i m5ׅ6{:r2vƶHPKM,_%>=vbfj` YfjN:"al :QXN)Ήa֓Gi'fMfIqTZf֔so&ZimY tWċxf'vu%hm%&O %}4yEtpdפUcR MXǤ{`C1)[5@JOW\>+Sҳ$\ʋ2{5@i=9`L1>P.UY #dse85#cxNC]H*WʓÜV'n0yh9c܁XeÖrJK6Fk7 H-Ft[᫴on6Fo_E) !0 N{^HکfSÕ+UhR5r`\N>X+$dJDEXam8$~OV=~+ .fK9EbCbxJzm [N,?, :3{ъu#:ɜL `ՌoKYno؜*la%P{&R7mz*Q$Ε݄I[KqxesI&N_j4z*#?ej,Dt܇B Q7:7sE|ڑ2zToi<(ؐ+ݖ,5&Os(h'f-!ڀ-2Df=+7D+oKǕiMc->"{K68Ql$&N7^#@כSHȨ^[xkAIn4ܨ l Tτ7Ada < @u |O2'suzLi P9IwIrtԁ53Uzg;jDkaM\yNTF $b ּ=>1x:%Eפ%X-В  b{y˒xj\)g M|6vo DoyIG+i!&fw);90|㒠 f9YX[_`][nj[Af]oFy\J*sDańL(K)ї4 !4,d` ܠιHkb@!$x0jii9PnU44@e8Q`~u9+KJs3(>S!b]kw{-{:rxs4>-Fv9^3B-PF@zy=W3˵@:hX" cQP 7U6^!AsRXBP;T{tmpJŧf*=WL3Huh-C y齟 Vi)+q[6џn봳0I0{'+@;PyrZ!'fLAY"{GEtxjn3F/?9r$u$sRՑE6qFmxBMe#Km#⁹ٍ>*&UZpF5M`lD4/ݍ&L2Vt[;<yXkY]}9s8(~`Vz 6YF4MXoYZ ΏI%'v[1'%1K{wySLү6`2:r K/|}cD,,xWŹYdjХqPBx@ME *Y[zeBHЫpXV. hK6'j='yځ@[눛4%SԨh^#]4uYtL\ɩ9+Ie[|eb*8K ,)܃}22\q*3(5nx$Lp lC+W{ܵ7O[CToY%x c)U3&,e3bz ̝^~$, f j$$ػϊoF"1-C4;}l;j3P3 gcDp"i\4%@Iiah[OuEQb=U7gnhh[T#PS2,h$ދ0 nWYц jD(*8z鑆m"cpQsa#hpږ'}n<ޙ*['izϤފ,SbYk&}.?&L *BW$u((œM'5;NHTA2X?&.~2`MJ7WJMe>p7]sk;{"Vak(z(ce V!LkNŽ´g$л5π_]~ݻ*#EyQh/a-e5VlދG_9pzvwk o_"6 ;t6) .{hAHd]SuQ @M ;:ޯB;5 a۞nDR) iOf]AP=Wv*h$A]GIT\Sik>=cx'mEu,EaG UeePڏP P@%O&1[ffR6=: ,<@)*cL*[PYFϞğcv-0as_ڮa1f⺲`{D'ݠ0y()7Lk뢍HQrK?Tj P:jf^'3|ҷT%P6oBkr բq.t$~hd"vflpY& ~V}sx'+^2c'kVQmEh(ªyV Ոe$i# '%(R%jlIA?<甮++tHsoPkvp#U0*u$C{iz)møg3u g@ήJNݛP%Z6Xw%Jcv?{0f0ۢ^g  S(vۥ\ ^ʃ{@;OW)3Y"p7r^uWjs '$ < 98|Y!'H*67Ȭ78l=^U5<,*@j ɥŎ20KK7n:فf7# TPᢨLqA T[0STA3;s+Pf:˭&h;U RvxυIWT;f@"yUΠb*^MMI6ϣh&F.Os*MXf;3<߫m[ʘDzu$[f gcJ 0>SLvEe[iZ?Vp3d9ЂOb<I)hSpws)GnVKkU:Î4 T$^<Ԅp_ Vӫ$}Pe+왃RQy3g!Pg?[ ,pxz3U*؞ly$x-pՇ\O\C 'Bkxi(&PAisv;W#v%24S-tzR+i317Gܿ6X`$p7i&x4 *.ts 즢wÎ3B' E;aEm}~U W]qή./#zR"PnD0tdmSQy@}̃D` FaY{5pDu;B!}\O&>o*:gaWjhY3#QCi_Djjvw\|N. Wx'e*Px. JYj^T*LIdq$ē(7a xВ U ԲyQVx=EKT6Wx{z*8)~9׮[t/omcdmjpW Uꁰ L`oHs T}fz+f /4s7@AZ܊{9HxnJE]fڌc;^4guL.IonUF$2:  XH3a~A=,|>$yo~5a)??;>6쉐+Pe9 aD(ۺ'7gt_kj6=W:Q6†Kl4Vxh@]ԽEJ-猉.| Fh"X.rTh*&V/'Wx'E=Ig a)|&3*ׄJyB t%L."b)@SeFuk7g=3Z_jL8U%sFB ,*܅0W2 ʲi&⮣\c!>[fm+|pzT V3|dufa𭇽FO x*r|#=KƃVgtASf'R128!q*fi0#^,H9|86t:ҹ䋌aw=LV^ ̀4hQJ8XHC%Hd#9F`8mfD(C|}&ë`ųXv"c$4I_B}v=FNHJT"P ekm^0ܭG૘N";N`w<Amp˶mļH3F{YmuS^ri2gM멚15; TX;*, htb0,o ^| OX84i$_:I5|#I 9s諤Pu $;{43yz4V>Ǭ$ymw#iG(Tg>|دn[s܍^˝t n!XbޜFݺ<a𽐗NENO_j=r)צE#xUZݓ i_/;`E>cvS) ZDe u"\lmP%ŕ/p՝Tm8+ekwⴰQ3M3+!838-* vU`yukAO#9nZ@ëDq4>ځ3ae;Atj T)d=M3=IqBYszڮJa!&2'iɀZ`jެ[ UՙvNël 7._%%&! n2!W.CEVLjh0 PsQ&pjFt͖P_1ҾXB@"xZWYHT6o'`*h۔1  tg Mѥ YIOtn=$]i%0TM O0p&*5G5}ʹ\*RNIZ(p.T[ V5mV/l;F0 i=&@jIu),q`𞫵ܳji ; ÞPG'j llzF*iXRvD J=j:XCLg`W+QjR^$A3୴>'}V?2?i6ֱݘ4Lߠ聬u.q!KUmW *Iۃ޺Mt΃haO'QvHSDm$7ЊV'\ٽ2IZ+K3gF4҂ΚsƓ&5̑YqKp\$(9#԰(nz$M*=V&|)m\x4ֻW<(m|Ykt"["K-XI`r)fczCMŤS {> Er֓oUҾV%v͍h}qL>`$"ʒ:klel%PQ_̽^ q)IߣS_כdp5ߵ6T+[I]]!]3~٠8[v['W)]B\/:T EmUb0\:DMd+ 08i;⛈t*EX,U9bL+40=AzYwS>{t2WlAX" _69we{?+gvQH.Μjs? pw-So3i2ȟ`hb3y%|FDrF S0Xȷ.v7Q)Y(Uf Pԩ ,mĎHAl&bF8mj' iD`y;I[s 8gtdGQ0 }|^Ҿ&KykM$I u;x[^/+ Y%Dk:5`idѣ|cGJ7RIGrB}B94쮏@DaW8q%@h~mΓd͹ADí+)@Hr/H>*EV >S=GҫH {X=Vƫ;J%g xexs/jy23V,&ɶ|/Li0_ @}v+`F$`u6c@Bz2\9 t$sj{|ڙ+Il3hpX؝Jʾdldd>Yoe1}ϧ4R)oxF: $h_T&eڵzxFZ @H8di$eGm}{g;gf.܊6vvYՒf5M!p4IEŃw t+d"Mn#p@G5'|bBC* S{%6y0B:%I&cg A * OWTP3@{O޳ΑS 锩O'y}`;=8mpTq}}v^Sa",3X:&Owr`9ow`@ M@-ނq*Z94H c`=#b; gt焤T:~2FT* < Q(!3`i'E#nrd֧z(A\)kt8M犈Y\R#1arV*5.*p7uGJ阤#+t+W2JNs&)tQJ g"5iz|ZILGf0]yF`6wQC1_Qi,32=үT$cFD9p8w& >[o+pN!,0q%9$}8QyR- Kvz6̚e0ʸϑoǧ//Qc SC|Z}0 qn5YoN*i3c! LU@3uL' >tN}hRS\O+I[:|4o[Ġ;ZV` L0{:hWQj&PMY&OfF' 1҉ ҡ٭ اO"7hR)q:–w "\}Q^u@N!SصD(!c֢&2<}D6CGb5fN%V <Ѐ#؝2;pK{҅ڹs VTB20m&uhNbɾ@dMpc#^7 qb)0}G)ܫÕ2Rm|O4Ў#ei@8ҐRIݤ+a̭\rEM }GEUܚ_XZ/lL&@:]baPݴ! zln)RbR+u{·4iF}r4יN437F=6i |$0W#u7xpfUv5à0 z$^5^)iWR1(PG;LאF=^rݽCrW9$~LFDρ~^HQpeˉKdą ̃ȕh܋*UҘ꤆uro&Qq=<on0n^rGYoh(ؙ K6eGݬCK8Bk !@a%qG:v]X;CM^`'V+!]-"ڑ<]?Py)&@b_jp+$iCl'ӽ6k=$#3`'cv}D)pLbbZ:D_lEj?l%~*F6ЎN QӅέ3JEҤݭ/Ag#cu M & HY>6Ngb#F j~548Zs3w4 F*OGϒg.ڣFXr')nƠU*ܢI&JnRI`qR,co4z^*#s(z8bk=Xia]HV:aci> =;QlGXFDnfK[*]Ý*!˨* Aשce܃rcŖI_%VYQ6nl+|IIL4x 2G*ObQފ0BİN1lK`~*F94 EX{&B%vs|pJlx%|U%%% cf ;cFiFD *pK&碾EeyZ̉\aQ'txtrj9߬ TaIo*ƮrI%JiJڨ׈¶CVN#&e/0mҳ0sD2dUrcIvwb|2`FmY8Z!<9Ά(5#Zμpl% DL qTVjql0Ȉv>gٯmP?קxJ:h,l Gʉ~.C.^8 X"3&j?S_\ U?_} "T\+}Hkr;ef)I8zd(X ^R灶[] 2P!*P  @ᛴN?T.J5e=ēl G/J:>iM2s&M$m YrG#-oz@ +>P³lCGȆ i3Iv@,i*r,7`MvЁ.j5>DgHȖ-jC8(;fč/M FIbaNm9֜L_sARGan^-BA!Ԋ@@Li&I;_CKG _et)Q%_Z;?~AbOK9y`ػ9ӓ&:صC]lQ{DdfNAriQ#f1ؔTң ]\KS%áuZl .ٜ3PE-:oP{e 2y'LmB%kAsmH_<4z>-L(u'hYP̴}R?;ak Ԋ ~ž -㢆o4B;σYps+q1Q]ݔH$hأ}G'Jk32fCTL$$C+h>PLE5WTQYh/1OL+6j=6u 6Z5[j%9#pPՕ=0n{"">' 2?jzy4T).@= X߯¹[x N9ȚRͅ3²}?]R &1 y4B80uȡ mڊ5~Zn{R̭:roUF~J 0RU,$˔h($ō41(~W+z5`O4$ )*dE {[?BԈ󺕯lɇš/)(vPK&"n%]Aˉ0{6q̑VPHZxRrIGJ8c Z& D>HQv?}L,T8D Jq3rR/Ul>ӛb4KOP@J˜IiMnLJj i+- އ9mm(PZI7!,8尐C@qOʺhzP~#Nhuq= ,a>(!pelxNR<{O:m4E/Ki„IPPРrJ I)E݂jUNjXi\+R* iӳKR\IJ5-"& TP*kpEn5|gh3yvpV*X.C9p9Kr !jڼ`>QsXҜ&ukp#+Uܯ1RaZG)P3:,fZI4&mglNG-J7>|~ fi-GJ{y4 ^׀@eTiE M !p=@0"++3m&g 2ӂS0ͷLxP`q3!e$joTn) :qQE?{L'G:".P?Sw+@9]zpdP^TF'>*NRd{Q 1oU *(`[nF |-RIoE}4vNa4.͕'eztDz֍ $gSA;6]+ UjhcB1뤉I@4xWrtl92DF;Hxū)iL_ U_V.'|/JS_x_ ({/[_D`(ms$6)P[)ިVW|Stnš&) XKBAtJ"3uPN ~sKVr['RaOg76rl͐A1lym0zjf+{b$%ys]~3Pwi#R.4؝]Q`@{=Sz9yئg6B\KرbpGgRW'kgؼșL`Y3 7O.@XPX`5]_xGYuD(7MZ٢PǤR%a5zp8&pP q+e FǑFA} ֨ZK,0X<@ե U7nR (pDwPv#Atԏ#\)!۾>ٮ,hA ˶7a֌FbjO3F`a LC)][q)%]e pށ*cK-S)! Fg -j\ hYxJѬWe`x ?"ђcʄ/mZae$el\y_@D/G^# T+ !4MfJ1|3蓥^T'6^鏍>]Z@-Ȍ f034q'`v}WbZY;* B*BIyы6xV<'GȞrTUxҌkmL߱%VYw;FXu\[V⤊]4rȮzJjNIsl:KB ~"ls%E^>]G'nHj~R5,I,Aة{B=mZv%r%]GNW=a졀^* <@ɷsʳD1͡0E&lR!ibڝĝQ| IOkmҢ0W쳆\&9QYݲ/*t+ ;𴶈o9+8x P!X[B;0mbC@6'u16m -IGn6^Sc_>ΓbxcURǦZ.F}" ¤>Oҗ-SxO*t8$ZGE!W([!lnb:fOlH&PJD{)|o*"Ҫ0@=j$z.pWa{'0qeKdWKG|r> }߀E_9e fN`td`%:5I(@_ _0'_v\v$rITgXEu`~}goxZ0B* wm r8(6 Ri[Җc\$'P6G?3s,ii81BEka/#YnHyv0|KQ|@.s/WkцZJI[.cx [x@nb@̞`ibyY{Z_iv[g{$v×*7ݤJxjgi RqbpN58tne?}5 %(Pxř:v+rk(?OH *R*]g6wMcn θ &PqJkc]㳃h0(ϣLnCNx t=a!<֭ރ+~U- = Vzƪ|p9(7Eh[??odd:WAGoZ^~8^*}[琋4QJ Vj5"f{k%OIg0M(({܀̯xfRCQp؇q IIAplUaRI@MMa z9ax td @fJ {cX.AG @o/i+>陫IGOX2%H_9O?GFABrXx:k_Nn裘O}ְs68¬n gÑ$u1 j1g}iC?HܹPDŽt FKg64 Tt:Riخ=BX$ YWWzU_;0qbA -T*{t^1*HGjSU9NRjHm/RpdPweG4s9,[}5XJWբvkXax@UUj=#51ODT6T\rxOL2O[ISӑS뽨@Z%O-TdPMN[<#y:PvʜuY(*}ޭs ݦ:\TKdn3|~fTa & au2peȩHpWgR ”'{Dx[SO-*z~F(ܶA%̞@mjsS>-=ۺ5A^whCskiZ!Қ%h[egT?;VKVfG6k(> {Lj! ֑[: oR1ȑH`II81 .["߯ 8"hS^cHrVvb?ڋ$FRiA'V=xa$=?%*[ԅHٳfQ~1a/蠴2^Y23 BE;CN-:a<K5w\ةmU%# dpA'M lo\!_`*b$x U?n9E]Y>1O:ʊ[wD[Dh1YmL"*r%^@ﳲE#7ei/iFx ײ7ʏ㟃`Ɉh>*_#nzQ[:`j 6>acu6ljyr%O4d j9 e9: Oۼ<@$ 7M}_-yXit&Mj){.A"-j5$BQIfgT.Yc\HgZJFsR1]/֝޽5y yZ$.,LCzRL`>5,]nmH7)PfmCYN:RMy87 6 3쓓d$jr wql%P6V$h: ]p ?zGUOmSč4+T&P.)8P LO5Wm^缲=i5TSПKHןNwr20,&ߺ"N }h*s0-G~4J)\H:x?iʇJ*7dG (56-{&XƦk`4'ܜTvg8ejT?*5ƀOó=k@ t =m$rG:c'HB]`CL% 3796梉9Lr3Oz@w˦VI|Q4<៫adf\ < c5]by*Ǚ!0Q-GMEP7 \'j '؃pE_nU0Ԗ7teY</`nA]3 QX9zρiWsvaG*o$)cEԒjs8$%~-b/QgF jp|ͱJكO"D4JT[-WN5Vz5g v'K+GT/ٝ}>m8@SLӍ(r2d LjVJїZ=`k~&\RXL(rK.p== ,ےBm2WDJq(spPs!\ٺHyݰ Y_5sW'v4,Qz_rھV黨24JMW> 2Q[ g$hw2,SQ˾#A GXugi:#iݏW0JP4~#RN%1 {ɬ$tsN]Kt^=ϸN4?#yQL _m |ߴ}'ߢޓWP~???|_ӛ~w_} %7?;o%cb|/o/տ&8G1?\~n_?]lq\6c߮~LsOxzlx -M~?ydftP/mӇwuҧȴ7ޠwx!5On'?3GqOoMn13?Jԟ}N ׵Um?-쵈珮1Wy}wu[%?xnטo珮ْO, 鷫?;?g^pѽxJ7?͕kݙ ]?۝4oI￾/;t/8}yד}{9ӥN?\Ց]Ͼ /nϿ<ğ(~GPϙ+ ySSkvYʹט5sDwqo׷M?_O֗ߦ8n?|v Ŕѹ]%K^:7Z[6?3o,p3ӟWXO;z;XLvB|UT9HW+mշ隕zϿuQ{,9oX͕y QtC|9 1f:130T}yMeEKK?~p\ " endstream endobj 461 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 466 0 obj << /Length 575 /Filter /FlateDecode >> stream xڭSM@ W@*a>HU7R^ҍYR`g IR> /ExtGState << >>/ColorSpace << /sRGB 469 0 R >>>> /Length 11969 /Filter /FlateDecode >> stream x}ˮ-ˎUjBgV+*RI H4.\, .Ox<WH4^vgfv8?_0?~_۟u|7o?$?{?|Ͽ?׿??qe?Ƨş_Ͽݟ?O&?/??*??+ǧĿ_g?%MƟI?O%uRקߓz>u~#W k y8sm{ Wme/Rh>Zq$sR'|=sSquG3tjsg< >m նKnq6{}wy^>eLjT7Kr)/,)✟J|aVۖ.b_v3x1s35)W7cW3ٳslAQږ\v {fU_̹?u&SP1F)NOKXSͫ]v.ݶ䲋ؗ-N]>wNeɼLoXQͫ9>yΥfۖ.aw#3)Ɵ?Sރ1rYVlXQͫ*[,ݤx5۶vq{Ω1|9 3Iܴ9ŀH#S5WӞycsP(chrencs=Ιb[1_6 }w1 |gš9c3GپS6ݠFmezǮv^bFvgMoV̮HogI4lH4?3JS }zȨ6%5mzOԸ+ar]k7λOƤԢVSX&5G2%EݼZĶnRmm)/==61ӣ8-qh/)^7(;tlr%n~%9=1]C\͙uU)7_9ǧ PbEA7g>gah"uj[r%n{R&~\7OLxX/v@q2%WsolLqK7)fۖRaw_杚bnMeGjH}^;'Zy)%:qGtzk^6%5z:b XLp[rh%KѦFV^&`Ri'1߄* }T){ll,'l^ۖ\v ۣՁ`s1މGm#|;%?1+*7&"xܘdے.aw88ܬ${[opu>4l%Ԇu$ǽMlKM"eF3\C{_2*lsWŔE[Yhb3R0bx7ZIx;=۔*ljU\=Z[sŸ1\$y) bII7犝[f)ľhFT V1;i%e>yۜ_E$0W|RKc h`LbaHܸ!i%KѦƸVXh [byxc!sa=b @wev=KyƁV^J?Nni%KѦ4OֵA8B>ǃLy1X[,5ݼZ' ;M"eSg1zS],FSusk(v<dc&uom/+g7w1j'~ ]l IR\[<|IšjWbouxmK.ozNm?̹1'wkO}ǽ :6XXSЍYIl:޺y-v[=F}+1]ǜ&pzXKKڰN> # ͙yi ۔j'v|ߍQ9CU]L% WtDRxONLڴ^qb%=eTg̝j+|E=e aMA7&tc*/ݤ+ضKؗz:vX|wΈΘ+X'ͽ7ޢG[G ݼZĖxLxT϶)]ľ㆏qvNslO9q? [3S1+&9c[LV۔.b_vkFK=᧽}2'0RsᢈA4IK,)&jbt},ݤ0#mrR`v\xVsCEyi->ߚh/R-X縰I/o@nR-69io_[2[21q;S"ѼmRRbE]^&g =|WmK.V'|ޥ9+&zf)j%i5ujq"^I7)^Ͷ-vvT;k0 {^)QhoNz+NO9'a碣/ݤx5ۖv[cr]qsN8"l7g=,vRVFX+j؇/HbklRwut+ۖ\v ۭ2/lr?r~I\}BOj'xL<3Vtjr!ac۱tlren>AeF1P&axH'CS)G*tsbe=ul[r%nٱb7whḫv{ #|K[1~R>caMuޒSĖ0+u޲me/_e(5F3zcvtZW,EW0DTnDGK,5mg R RScZ>e·2V0e57Ɗ*guy;ұtlren79 ]t,m#x".\:cNXRͫŹgQMѶTn{ WCHrJu.X;W Xab ?V."Nbf!6V gūvʋ^v!65[4@)(&Dۊ.X)š2cTz˒.aw[ID*7FF~#uN{ul,Yq$l9/E6[E3ߍ'b:~ݵq$q!R ܅ЀhRXcf]wtpiɦ>WMLѧPÿrxh5սJN#u/mm/(.<ؼ^rDs3 ϵ W[LTN[r0u:曜hͶ%]v;^ WFrx1eR tK2r$cEe҆8JVIҽ%mw&IF0 _ޝ6b_K+$"iv6;ӷh p/[_k9 ˙mF V78!$I8nl1:~pTZIl+*Kap+賯hɞiUz9܃~|Qϑg9 ƚ^' 2oEq+S.}mր9#pcb sa|Q Tq{C)msb1nPԭ%]v0.l]E;Cpu.(RvJ>aM]mHƮ|&¶-]ľ~6py={rCQAQ"-r0ks:mXX7-!岋ؗΟ[ʃ^ؓU[۾HG$8=6i( ?nRͶ-vXo=9#RnpآB{X Ɗj^'MM쁁ɺܶKn/8 ǎ,!pKa@ -ǐlA0i2EٺW ۖv^ʝnq2oJw8'c LhaAq&yrNyƊc[=nPZmWG^)󆮼&3GhƙKd^StZ1+k2I\Sk5MIi qo/Г[\q0 (Ԉڼ@)kn,}>Onqռ@=ŵHr[JnO)IU5RiD*2*KߚL'HcE*9[nN]rS-]vbe^Up;5qtGL9Q ˱:M#<Ȉ4rS3 gÖ&v_/bG\# GZ+(yXS?:9=Eb^Mnme/ٺ6uiFd(l#gh^7Ě5@ℰsKx-ݤ8l%EݼZ 琄VK7)^Ͷ-vt#F"bTN8 {AdʑVi=|r: :ء[fۖ.b_v{ᩀ4ߝsǖ:QX}6/ w`myCWS:ɜhۦv]af90m{s`3Lq]3UXQ5{9l$ۋ}dZvqȽ<=̙/`ԧ2 .Z[REݼZ+`a#Cn&ն岔ؗ-wLX9Bz ہ$'ι q'oSvbE ;G%FT1uWYdے.awJ p)I°>g梉ݝNBKցRs'XIumK.+әux^nd~+ӔjbE3s &wceA#ۦvYs@ T)i;bʮr,9s3eNs}N.r۔.b_v&Hg~wR1{E&^ADȑXQgfے.b_v])%1sZ炩N۔tl-`JcS6 nݤx5۶v:|#G 3O#/2FyXST''xžĒy+99a+WYw͓\nrY*n+Q{ꒃp~-!R&ƊP]re%Mwmeݎu "X8 *'Ǿ@Laq `b]W6umeF$M>aͳُ^bqƔ#XQ+}@;!cOme]?߸ [8 I#nu 8Շc(ܗwpKG))!nue,!2' Evbp*\53 XQת!J(WMeA6VI޳O+Ep?:bUMEE>P|Qz 8XQMWmeݚRh:mR|qi;.%8du 6Ǭ{v۔.b_vs1]ۆꣁ>H9\[aE lLNG:c1ХmSV+5F2q3$a1a)ljĊZ1.qV1,b\jrenT1 N Ml|gtxKyS#փYsibEѫlDbq6"uWoYmeݎqt{/9pхǽC/J]cw1#2j@XQK\t-ateے.aw_n//Rn;rPCbs!IJp"03%;6yd)!nUVz O|w9o()GL"N%|=+mK.^ ͹Xa rGuSՖ NJcM5=9 \$PےˮVϦOZn=rˉ;'-ccL kk +kgcMO1ڶ\ Ȣ)+{q7ًB\.bEQ7Py~EI¶%ľ 3Yew0Y%C,FNbEJ#Եtr 9ڶ\v m'`e<lSc܈@682{!5.<lqMmhٶKnozI9gLNT@8P"<0LSYXš*`a06 i,ݤu\v ۻGՋd8sT>/./$GYbIQoL+'s~,ݤx*JmCABP8KCp7C2JXƊJߌ9"ĞXm92vgmP0lQTrzVq^O VI=h7MSxzFX(L݇me>&ס|wnZsI籢 ϱ"3XQk!bnxbqSwsFq-v'#]̹LBEX\cpg1XiEFŠbNG ,2mK.r`w ܛ-wyVuv{3%{+%WbU ZmK.v߿;W'rIZ\ݟÊGIg4Ǔ8Ӌ8DVtX.iXіVꙆιVgʉRUEy]qxR^V!ԙr*1Ej[r%nW5AJ@MSws ((iELP8%=btbJα٦FU>1ۙs{ܨ:3yf̀̀8'Vg{;3-]ľ.ygƈdssE!Fώp"ڝe"KHksv[WRdxW!}sX ?| GƸBH %* ƲPuBn[r[J(:P#ݎ_d~e CJݎ̀K8xTl=)ݎՏeo\<,z!ᇹ\[ܮ̾Eš\LM=Z^nrEn?',iU nʮشZ"AUIi}S5 ^-QF5V=(1>qG园TuXĉXP]'TZzPlRXcf\T=bDeE ̢ G<7'`Zy̸%n,:\۔T:QQ?NdD(tDA(gq{5vMA--%es:g( MDڔ>8h?Y/Ck q9ߡ3PCTے.aw]c)$Y 7*pJ>wʨQ#;ҏ)+g DdYT3:5.c5kMIi qaǮ~,}@b  /b=J 'Z9dN/H8R+ &pVIa,;H`*ƨFsKR|F.IJC8Z_S7)^Ͷ-]v<-S39<9273Xgj23WG̝C%ֽ2569Ke7{ fz[(g%Zk`=d,JֽRnrY*n HBxs-n o/]gO1TAIwٶKn뽸OcyM0E2:=VNf~ ^prv[(KY̱x14sk'DX(Mv:L3Ě1d}xmK.}.{778q,J8\WK)|ƑhXc WؠmJJkl]ڋڋ%*ϢEV*Gn>)Z:@)f4]˴?-v{JJRDABwYŚF3VTJ\֝嬲meݫT{} ~驩h=?E7KbĚZ2{SP֗Զ䶋ؗ^[!Q"s}b"Q^4Fœc JH/ۖv) eq8\ 73=/HMGaRc2u3XCYJ.awW%jb1G@Xǻ)9P5uj6{Suȶ-]ľF$78WT>JSEye`% uaM 㮝oJlrEu,ߝOfF^}|hӌ PN sO&O;?0@X~`ӺIj-"eo;rsDōX+FXQ5,0+lg$WI9Tm[.7,yB>[T[FL֓s8*[,JKVXm[N}ٽ-=ZO3 9 72q gے.aw_][s%ڛ! ۛ!en6V9Juغme S4{si՛kk%3)XRWJŲ3^(ReWrۖRaw[p7U'O3+Ӭ[oyZ_rdM'Vԙ9szĶx eLmK.^J7۸uk,ξK' Kb1 K7)oӢme>Ȁ @Mqw!8Y_< %G"C}ZHƑHOVs/p ٺU\䠜r (i%)aMmi<'letnr|8n]D 3TznNF緢;)-ϝ5u8YIџ-]¾iqTm}O.9&`=ߎ(QbRr,+*'_-(`%'I}۽V%j98R̂)NkxRSƚj98:mlai&Elr%ndžs&wTxwZGa!pCNe#cp={`ݤ]kr%nuoO)?`7]<9$OCieKYnfx^c5ʮ6%5mS3$n Rֽ҆e9S%u!s$ Vڶ\ ۽ g.3f-G7%$eu>D\f Hl֞gԦף^vĚ7PQۣH9~JbEUCҙM˦f-v{NoO6a9lm$CqXQ "-xKb9u5\6-sۖ.cwhW_z˜Y1nj?8\"81YD!ZKʪMIipN>Cߝ4}L!c4\nWǒM +9L1Gfۖ.aw-Ĩ[fi ^AK;?C X WAi B)!nUt/ũ\ Fb?.'r/9*%V*eg-ȘAmm/_=O0H<1<9-gXS+O<^y*n[rEn ­jrDH)Me/,9~RbEe!䠘ibDHY5ۖ\v ۽> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 462 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-065.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 472 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 473 0 R>> /ExtGState << >>/ColorSpace << /sRGB 474 0 R >>>> /Length 3867 /Filter /FlateDecode >> stream x[ˮ-7a2t~LA +1@n@""صVz!znf[Yo^Ե?mǯ^~Zu~?vl˿?e]ؖo~؆Z_^᱾j]|vp`rk^`rv`rZSϜ_L~}ُ_*L}][?t&*>yL_dž0ylPXЉ<&߶#0Vt"OC6$%#` ;`GBbMg<x:@K<8UU5O;>طTFB\ã<}yکSGyƒ&42mQR qЗ)_a3y?3ڧPTFF\ã<}hBTFB\#Dy>Υ*O5{|$5Gʠ{!2 M}j$4BdzT#!`'CSf1C;NM5b/SbMSgqRG)4Uy(OS  quC;z0HkxdzT#!Q|3GyN(SSFKꔯPTFF\_g>*42C*O5!Ç)t.Uy(o>#!>r|UFٷyM}h'CoS 1C;0Hi(o>PԇFFL#DyN(SSFKꔭXTFF\kPTFF\ã<}%O#WeHkp5 M}j$5<Ӈv2T=a(o>PԇFF\ã<}h'CԩFB\#%u\iL##QqR2 SiL##<}hBTFBL#Fy>Υ*O5b!ʛ:Hi^a]"oVK&^vAÆ;Ac}h؉N?y@lO' 4I[)x*{vZi =BZ{Fe [3j߬hT zF[L5&g~Ԟz|iT}՞_⇮_&|Wzqݯַ~ezo?a=Z/ekW_d_3Yfi5p} :mqYTe@`w܇]zNT%J?>쫉{gkhjHzisLy;[ T\C1JLWЯ}%'u__[%ړEsu/*cQ;T\bR҃] d~`;XN QLzmOdAzuRУ]J*>8WkJ,?fU$9 '#Ax SG[*GfOnIstטfˑ6Jmso*/ZKZ@vyLsH6^>ETk{-G-ڊ.]t7bLiy-^Q-p[R{{ #b"|\շ碱UN˽A̅త\{=gFN&?T3[B.mɕC.r2mRx<EȾ͹\Z9ǣ#᣶ા=r2m\ɿ DžCK1#!U(Ж\;*'SFs!B>x>)Wf+\ͷb!W^MKgՐ"s\r%K7,\mu(>j sؔlo=x.9pw 툹U vՑb1[j-M9y6}l1Cxkprϱ\|1Cč WmXl02ovj)k ג{kmrKyH|CHT}ڌ mҏe"|8$ׂIEn.|:\ >f+\ͷb!W^Mur1ļ,N F26LŤrd"|VobSN^xOsjcj9V3dWc>j sؔ02o}iX\ >q^1VbVG!l\,6EțYS.O\73t[<EGmU}{.rm͵_NED䐻o{/Z'ũ./eڨ-!E`v;X-#Y[% }{px'* H[7&,C"mXlɋ>_Vl&3< )QG h8cGm"(Gm7ٌշؔm#orcg (>]µK]^ɖ6\ >f+\ͷ碱B.w^/!9 :=*z,Cv/>{ѷbBo/ߵE|jd_kdYo7YjˑrQ[RcfЎ/&Eda$w`ml_<U~ɓZm9&"}]orm;\ >|sc5.?Y.rؔm#o}"|Im}igYϥUuUsrd"|VobC`xگgoh:gg{q=-G}UdP}cmV9y6f_Ϙ!§Cx̂ksZ~;`UnNM.̖#᣶ા=rmsE)ks3XZߋsQ|hKrall^R.DgŬ M!_P.l9 a.%W0纻mc.+c.6yz-G"C[r chy뽥\ \K %ׄ1ٵ{N[y.mɕC.rmgˆk9'"lK`hg8L~ȻH|m.K1ۊgHO򦗏byY{u\ >0σr}D>0%;Kȥs7nQE-wȅUNG.~ endstream endobj 476 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 481 0 obj << /Length 603 /Filter /FlateDecode >> stream xڭTM0WH7Ab,܀ChҦIK¯gfƇmây(@b.j'(;JӪgHfHtƟ,16yzoAUpy/Qmے!FZ O]GHFm~P*5kVCgT[{3dM U1Cg Z/zFV V}mLL͝w޳ENlFK,"ۺUpE]| }qVGlUN VXjF4ن3rUʩ6O/|!bw&PeۄEHA W<I9O딸A>vs= 9)=gBhSzmCt&|h톁 #~ endstream endobj 333 0 obj << /Type /ObjStm /N 100 /First 898 /Length 1433 /Filter /FlateDecode >> stream xZo6~_akn}Z6ȃ*+6lh}'7+KZ@]Ayw$>~$E{oQeÓsϨH}V$ObxzD26AV;h,+)^Jxu͌~\x6lCrvF4!d V IP)"0$%u"l `Cb !A'ȰJƪ` <,%" a&U` LR!d Y!k HaɽCAٲbو,:KIVdfdSZg#Me1P@!@GB@TT DĢ H0d1B{yXa[)$J XeMxIٚllEɖD`"*r̀ Z%{@Ty`(Xc%Tdacg$5,dJ$ĈK j) q&Dž~VEyQtSe_ֳv>Y?QS>i?7Rr8rq"{YOS:Lkiӟqbk;uӍQR:-5L=wWU/h^S#{}jG/+ۮB[?Ks~RjQz,/5VF~OhDLF>g+m][,.ɬ>mkdAhӗd>yB$=j٬}jպj|\]3DЁIYUH5hbѤFm]q,|7\帜wh'?*쪬 [Ǎ>FǒY{e萱Āre]\u0vUx7YoTU!*SЩSz*YJJ{N3nN,dJ&awr,k7@r$9.(nDrH&8!G`]LfLfOFwN$@7;-pF$ %;Ci<á}ݷk;;wZ+'ߒ]$'R9\Y,yO޷I.o8m^o2ک=|![UN/d$wLfIirQ )sJs[ np*8{o > /ExtGState << >>/ColorSpace << /sRGB 485 0 R >>>> /Length 15075 /Filter /FlateDecode >> stream x}ˮ-q~vO+U5 l/u݄@&) +#2 zvD앹򝕏W/_8>|_]{~?{>K<Ϗ>>~/vݟmn?/?~?~_>&{{-OGo~?9>})y×J˼u~2C~AYϏ\>g; };'9~ gT?QOx>/QXoϫ@>ߞ|Z!}=#B>>Ǔs<׮ [+~r>:qw3~?'?r3 >{\~PsE.6ϨY?S~=;W{D~F@\3=$4kgGDhmVgķV8/վCٟjq/Oy <5ˊO0W/"}e4_Y+JJ/<}oyhm)ޫ|t;*>xoc?rDWyΪt@٬yO:U1`>Z?UB}506s &Y]W|6V{m ͹idkVgVƪ+qi;"r?%Ɯ"rN:AH畺PzX:`gozw: Yu4dГUOCSVM ]Yu5eЗU_Cc6 t4fЛMOCs6Mnۿ6@O"R]Б>S!*~"w6JB4{ Wؐ >Ń;o_~ߏS3"͓SSKdvG[ؔkh|a1nfؐk-x vZVMi+*$;F i6-M z ee/awN :링vM`48FI㻢OK}Ib%!lZ^ ip Vܲ;o%CL]S]ӼRoc%!lNb-)–_#n͋7+-w4yz.L.c"q}ϮˎBzc'3^]ƆTÖ$Sbx;-O9g׮9cfg=dHM%C3MlǧÆi7/bx+-OGTXS㟐N%Qga`vKF[lb%!lZg}Q2lJ$]y_ii/?NH(޴+ a;-7a+͸m'/cwN r*JvD~ZSe񍨰i0+ at'c[̷2lHN9]y mQ }bŒٕc'M닽O.c. Vܲ;o*F]30&ENޘU~:㻢OMvJB픣u غ6,{K؝=S?C}5->}fҲf3>uf$_KS01aCre/awNˈt91A} _:ƬBg+]p~G'V毥;c]"Æ#nK؝.LI_:2ї %{7Ic-!lmaaCr>!nٓ);oݵv !ŇŅ5RIXvJZ)Ƥ2ao)Wܲ;~l/kK2׼C_vSKW8nٓѾ֏g(K]{־ciN\gh]&#ŗ¦ci'/cwN˅WtwW֪\\3a[ˏH)5l[8YZk][*G{Zloiu==S=-Ԙ+)MQfg|bG|f#5^i9>ٚ+>7b'z/;&¦}rj&Ea>qO6/o^"xenkcNni>0K2VҖiaiɸeχ|̺ױp쉽e1UN'k:v֠5尳eܲ;oeDV.(ogtV šw 34[aVJ]y;-g|{kWK^6ە4*]zh؇O2lJΧy,x[iyB}_R1,j豈7%4i{S1Xq{e[iiwlX57IgԡΞO|ײ4O+5'ꉰuHaSEoRRs݃9\,4ފ%Wb;5c-MfDHlgvZ_My[i\lʕϸ^ D Ն5,;v{İkinS:lJ5]Ly;-N4 O cB͜'٢dv/ՆJ^JMa&G|d؇W2nK؝RMW۷#(uJfʲO|+ aXt4Ræ2m'/cwNˉ6TG5 ߱ebi5%WG-%_CӢ$۞6$Eq.^ľvZn|S3փ_ >ԃJI"/x+ۚ)% > {x}7ݼSx;0C*hx]2o`|b@skiШ{6,{K؝JԶ)6ְ2;Z=`${,R3+=vn-{~}ii" CU:[Vyۧ+iz`A(29nK؝Kvc .zƎH>Hp( //Qף;T{մpW1i8BioƕKi4{QqJ6m\]q UՀ(ʼnQ<ԍgL΃gEO"#8 ?Auvp qJ6\EcG MqgLӍi6fI]Ϡjk8 [Jch8-SVnjAa)pXqSrk2;QhkjLvp ZּqJ6m\ߦ wUI &pߞ#Pئbva}C.,(T Vn53Ϥ9# r"ٽ瓚X6΂?x8q 3V1njDcQdMfq:=#VFgPp,e 8S8dujyVy.n .f[8 u<nJ aVBmʪqO>q u})+qbf׮8}ǡξJZ_Ԙr&u%;f-x fZFM?#3_āq`,qw~q[Bgl/8U$'X2)fؔk-x [iy>0ﲍV`\χqGLfG=4NBVാqjS֩_:=S1bGܧX/ tV[k p*JENŸSpZ=Aw q;W_ 8pat{]Px  ➀q8q8P8.vs]?:&#s?w|ETN^Ԕ,/&Yq,L8 ?=O U]d ۍ۹n?̹>⭨1GNq6 WZ[tQ(+KAH BVnjW5šwL!DZ v =6l JDfP*()+s5}ljnMWat8買GN$+pl u5])+٨o\E jQTA&: kCF 'ꢯ8e%Lvr5INlka6blMF!z qr2g&eaPs28e%6?sXi'JvXxjO[ZI(ޙk ]X,)sqcwc]SN.O"XJ{~r/.5GN7;d{9n͋7J.飻8KMKP8zf娖N2Jo9bM e/aw.-4Ec[y o\wMxeq'XJ ۿ>'|;lJ5]Ly;-<5;JZ!ّMp\fj"'4l֜T3lJ$]}q˸ASbJRG<+s\ԛXL$:QQaSr>]Dz;o^.(oq*[32Egv(1~0XIͳMs eO>v͌ԉ~T|Ɣ[B|1nγ%JZ) >J]y\@"bqjN剓k8wQ)eNiםna-MR3b988a+%iٽvcRg\(]ab"rk8`,')Wܲ*#.?Sϗx~<|1ϠV&ҎJiN hc{L2lH]y+-Qص+>~fj}*kӧ:O>S +gjp'8afܲW>51I=C.F O!c)1lZ+@>|aaSb*u w x9rI׃!R Msma7pȸi_Lc…^ +r#vfDv7&~㮈}s uaK̰2⥍[vv%57Ӣm2-qٍ3D]Nn ;%iJ}ܚ3! ɴ}Kf7zİki..aEؔIm{K|Q4dk ^`+Ësa\.Wj]ba-Nd ;caOQgܲt}YQ6seȹpoJݧ.f%KTr|q˞LyImc !1e`Ug~νc%Ca9]y;- yzk"7,D|1BQrZ?}獰5(^gei8{X58 ҥ.͉혈%Vҕ5ؾ7baSrʯkK؝r84 O|q"Pe =C6o}6Rl:rm<5XN,־3\ϸe/aw^\t§k`fj L$3_ OkMj?>IfMk}v"Z;׮Qz_:&>Ɠ:ihbv\kO$uKhb[27+}ix3'{mҾni;%M=58ҟj]wܲ;o֕i|$^lv2Vd'lvٌ[vN#--҈OʉV|iif{jH[ZI>׹*--[vv5X|.zmHSwb*%uXvO,%_\sG6% Tb*{'=׮9bs3BZLs+ipX3N,a-x vZ5C95'Wy26kJo`^n;Ijkj49vܲ;Uk^ r+7 y;LJ;C+iYʓXT a-x ~߳~]+^7Mҵ;}UMɻCրdbA+.ʔq.^c5J5w \t{UO`WVR͞ɚžB؂9.9pܲW^\ac>v9Px}N+Zpx֯f[|&Vҙd& Ƕ6$Zq˞Ly;-X/צ)8/oc?sK'-ͅ’~OLy;-c{zE'~ӣgI/~xYq -)5-$v̸e-t~[i9gS^jpԦ&OxwS^?G/k)=YCow^ei󁈽;-T;~b[rZvba-e 16{Ma3nK؝r0_Oby%~N$Wioc%ysi3l-{2v筴L\@\e\+\[ w߄Mi7.4 [pzaS&&G;U.Q[ZNmxxV\m;y~c"Mg{a9ǵ+:dŚ laTe-x v\Ro~<͊%˴֌N1=JjI  g2vM"[vv]ZFzf±;qi|dWa%> {UqܲgvZ8"o29n2XI[HVrQܲW]ZrFyo+]\K |W[(n3yh ]y§(s(o%ofrf8잾%i€5Q`/L.d|md_#;0R\N^ZP[%{SϧOmpC ݖ}c%޷bzq`ؔ\.ed'KӸ&-;o)qkijvb%յ,M0 d-x vZpEmcKdĥMK;.$1kXOerث9n͋7N o ]oѐ{VI_ 9DXKGZ@%l<R2lJNK-bzx{nXKM)]w{aKi/Eie@"㶽=vZUЗJ7?ZԶo^+%gk K_^=g-x vZ bb R*z~ɜKIXI-,YNî^G̸e/aw:Nt±iAy~8l?_R7.KbSҬښvp=q8nK7J˅f/74wA|WK:%ǚa;$6%з6ŪM}x)]y;-i>7hjWo˳ԜH&l6%qn^ľVZ:tz}!57n7{!=ʌƜvHb$73eq.^WZW=6̀[!|z)B?%Ǖ o)\1|rm vZ;Ő_U"+%↲4(NYtEi:Vڱi)r-eWӂm9--y)$W:l'$aSjyR=XȰ!9-;oˉ-584v0~Dv8!vJ4&vЍ]vS[dzx;-\ǬC/)4N%Vґ;]KƑ3æ|mOWZu~x|4xPme_,jk)d4צ%¦Dܶ;oQо|"5KHhcf쎺s`S5`lG{xqܶ;rغKG Wɝ3ߍܻ\s *ӋgDTW!q]%!>./֘i|0>Ťx\L;Yki '?qý^Mb7l^I >BIz;_8%WЕXImxXxȰ˚(nK؝ӒUT^3r@7mfF?i]xJt#):nK؝ +#߷ǣb<~3AJa4VRu*,Ve؇"gܲ;ﷳp~Ky:VQ$!>gg>7 H Kv}̸eO}Xc7}3xݑR~DzTb%I=hXt[vvʥNʯ5qh!y XM#yXI ۥͅƢȰ)e~/ UW_g1&ݹ$GİUkbݑaS:V]L}+{o'Y\>+ڶXI߅5ljgwm/awޫO>5OGm{ vbCb%kk&J4j˰)9y;-8\CiB,'pknCے')t٢4g,{æ)]yryyw;oy{S&^.Ҩ\u0\b*iaN=`g7XGx\V e/LԞxj0*$@3ِq.^q ]kl^m {+h f {ytܲ;oEyo(kNlaޝ.Y3}Cñ{[t͉dR3؞S> ; gܲw:ݼ}6_H(o0?L;掉KVc.-{2=w,+~͚,ܯig޳HeOEG^0<*/o{{FYVǰvI$VVҨ:ưK1=|xyrW=9O[=0CrwXzaS4X~-{2=w,=m{=,Z;Bi۳H;$İ=wF[>o{l8w™\Cku5mkNd0vn{r.x ~[\`\|Tm/椰)5J,eGsܲ;uu䊵`-vm&+ {Kδ;K:b|`ZWLkeXڋ]Ly/c԰/* ݜ3e/L{-R&0α2=;{I=Ԝ\~}r=$۹Wd{]bь3잾%%v{Pƒd;:} vJ;N;8%VR]vb sZa{Pq.^K kt ΆtMiI[{XK-Wicyaeq.^7w[- q܀~*Rr 9 o6 W6$ݼ}~/׮9&|Łzc>B/)9coK Z,'KH?$[v"v]~%4p{Ϫe>{ig^b% ߜH Oi~pJ.r.xu{\UܭX:'=ɋĭ՞*\%V^a7ae/awNKw}+Mh˧P{Xb|wm?gJhuba/_M[vvoj䫀ƈ:"~Uv,a$VֺCªo3[N{o`w+-qj+wEݦ\Oo)JfaS:MsN-ue/awo랸4jL\.u,;'6ck]Xmwؒ\.qvJ{ݭay469-9Xv,$6U9G}~]yc7rj4?D_o`57JfiKa7r=r^uLk/U|:~b)Gcѻ$Vқ/= "aow"К|,o~"gZ:C}4i뒥mYO45x6gv3P[vv ljNNzCkJZI,|2(g]yW.WQ?gM=荃yGi/ەJ/hiN{?{/aw[{[Ӈ<9caxmM_Wϔ"f76%PDm wؔ-q.^zr}3S[w:۝XG1vV3VRI }$wB23q.^׽Ѕ#BvHLo_'eD,wkRcFp-x _hMo]/;!aHk]obK{N^wF%oYk޳fO|`aW%iVǬa=G!݁H^}KZuLaUV%o>$3f|qgq?2Oēz>m K鵃%k-#_?q)"[Xk[vvʹkzVK~ LƳ7'~_5毥.Ö_ӟb*}2CrbL 82(͈$cSO Vg2[v"rĝ;=V1(x(!eb -|:400Z[&Oc4[E'fY~,+|}oޏXd-=2㹑uK'~Xr Ɍqԧyp\0w5} VSJ7e>/o|o, Gʌcv"4gch\,E>1f뭮>0xUOx:'NMXt\p;cmq\21#}|1s Ƕ)bA80 ^ @\[_20ʃow`@Z<:oDx%̃RLnv$A4P>Y[Ln|}9"t-\O 4qx&_d_5SWu|$&޾a,eK3-=2=z#cEPGk_21}/b p3œm^Mw<*o );=1ߝ9Wynܴgz[f÷1o}Ƞk]ޅ\duK'OqE^r=:-3K~_+kbQc,uc8uupKAx{cxh>W=HĊn9 =%s̺tLO]|Odύq#eN_ yUUk_έj[Ev.n:WEFU)h}Ӡ NRWԸp?㽍 ^x]~&=Hv;m4՝Nӳ.ywb_ߚw^N{4DvT_cy׭kzWVu>XM{'͢ܫ^6ӽ& csmeb/$4T5sLS_u8Wݕ":8x/XD}[۔ M ~XG'w6. |Hǎ4-b.vٗĵh,uCm zMu48aS1\sؔzJeb @7T =SR6&} |1s,8GLyzsK8Xg}29Wqz脧X[0:7׹dzB=5 -L8x%tQX|4U=kuF{ۼw)罫L9}/Ә܈0nO-u˞ljܼ퍀sn-9x_'ϿY4aic9~ey=&21x "c: "s.^8Kv]Z: ۾֚œb=Nn%;1v 맚Mer`>pL~w?|ۯWfd.'ǟϿ˷ˏ_ a*ȓ|sV*⟿OkyÝ~Y5;5X5a ^blI/0^XKYS"-Xfr%;nK؝wԆ=S</xcㇿS?|_' endstream endobj 488 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 477 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-067.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 489 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 490 0 R/F3 491 0 R>> /ExtGState << >>/ColorSpace << /sRGB 492 0 R >>>> /Length 8540 /Filter /FlateDecode >> stream x]ˮ-Q߯8ClWfjj ,d%Yl B>!}OGDwfc~?|Ǐ߭~__~8__J{IHzJj~/?Ϡ*}Gb:??|Q)OK ~-_?(po?-jubar{JJp7{sj֟yGˎ|&ս?+)z9cxtr>嗰JjB5rqnU@HQ3 6> 2q.7FN\3ݥ%Zj1]6OGd#8́6%7mR\ғ3ꮣT3sMj 8|$,_sFNl}ůe[r%{Z6F3k͂_{Q#1 |(qZ̙[1nP`[r%e1D)wNY.R TE# yW1̦|XSO'H쪗˅%_~r([ܥ^˜5VE_ ^I*zBgnZΚ].H$ݤ5m[.vhzGy{`5<&nk|X]}LsF6Z tkqjΌEKIݤܺ¶].5zhJU9+h(G֤w@s-ZnlRn:Mo ߩuӶowsY oqeR XSOolNyLI1-"o˿s"68kzfu)`HyC/V1Vu3-tzG03ueb!ds,wlݤ؃Ӷ].7BMԾwBU:WeŜ>9sĊ.L8zb"'2Fcے/b?v{WR4V]X^6)[:ð_3P]&Ŵж]WnLI;y*Xk*f+t,9JœnPZ)_~:1rLgkfX}+/Rߪ-9њWaEQ{ p&z&a {&&!l[.Ov\QK ᑕ5Yr8H8\R‰x|1 Fܐ6%7_KØkƉ5ٯHC 3:wHP+?%%ZJ$،`RGWb,ρ[ bF0cm6=ƚjٗS{pX٦~rq'Y$䤤[U#FR2VTRص nR-_~+-+"P]q`uBokbMnvrP{puqm~+-u3slEFy(;)]mܔ]Kꙩ$i욉ԑIkږܞҲD#gysa6Ym[NF4t?r+VF)J7)|-ے/b?VZT9 p| bcMuy'ŠzN$g܄-ZwٰmKnO[iY\1*kWb8˕r5uz59%?ac=xOŔöXATEQz^E9ْr:u8`NGZX7)~Mۖ/cw5mI*Eɣ/si[G~ܤ2bNlm闱O{9=gptCED @@JᬦgTcMuI"E+uM"ocg2bt;^18Rs3&sn|j~K̙R4q&cc~[R7)m嗰߮cLk|1bٱ*8##ʭa;FraMl]zc>R7)"mK.i'NM :O Eo|H Gn8n B#VشjU|Ψq`@Őkj38yF E7֬;SJo|u :mG_hb 9 JcbШGۄ;3-i)nUO ܃#7U sDVzrr$0ԝ[fD7Kg dR(pcC܈N_1yX~0dM("qX>.P($S.O[iYyG;ƭ/[[00k)ns)he<) [0!"6 y)B‰(>i3;Q7DJI)nճl2_7V}G  P~#a;3 :7Z?MKpv'wX$zN:)OuPlcE INb,}PMږ\~ ELowF5<; ͇0;Vu95{aúIP¶'-Ǚiȭ8[zadOŖcݟXQՁ`nq^R7oͯqqOr%ל#&xys}۞(V.XQ9S4 t`l->&r#_~+-qIm9s @PdVsD ւǾkM'02v`úGnض].sm`G9Z&u"')tb54{a7ںIۖ/b?VZ؉FXPAysnΗL;v-;R[c#!VԕA8nZ7)|-ےSb?VZʹ8 ZٸU/8f) &RbIQ7 c M_Ӷ^N3psP۸QeBPI8+^ADخ@=ڶToeFa c`".zсO^o&z^_&\9%']\Jے/b?VZ:EXXiNxLXŦD 晴xbusZXQV\b B"]mrEN Ϊm䓃wC0k;qHcXk&aZ~ckXQyMޜUqbQ؁3M_Ӷoe4"v{pY^ bU$G6k ]Y-gA-JwyŲ-ocs"F;zuO.ȴ1M<+΍mjA#p[3 ~ Bq[w=o#2e†#El82YpSB܇M2 p:1ZMPh G񄊇3<:~ExrܸOYLrX {ΦTyS-SN{kJ.}4"34 37&5皒SQō-k'*6B;N>w≼;hur6&#[d=p`ƺ%mK.v6|\Թ0{7wq\Qr T1'6Įm,aree g}[ɜzFxQ);};jUgqScEQ7wY]R7)%~8:/9'5g1(!,K?aMgΚF&[MireRpFE3OmCqho`2mD7V8%GSUږ\~ \wKМ;ioGF )4^vI9XTQQ#urvKg}b;*9猊J 'Eѻo*Q~)k 98_-,eźEQ7oX.vת")ĕE`@-INM@o]&{Eܶ%_~\8'\F^Z12uU$z-mp"C!Ӹ5Ս`iFWФ-]3Nn60x-ŁVHdΌCqIeMKpv˲ MKhX^#9iš*^&wv=ur#_~ī][i#"&| '=Ɖc9XEpr݌5 ƓX#̶-vrGDsWWzCr<7XQ)EqaYwײl[rE. cԪN94.q5L;\dƒzMˇ,Էj5<vi[@XEYYOSnaM`٘XLSw\ mK.VZaW)<;ɸ4`/@)o|BXSJ1'؉#M _˶K9'^|:hs\1yk6Z^?$gFOjle1ٶ\RJd S;ߜD vVLD`C/k*_NNK¢CHAږ\~ 4,vNN|67.Ϯ뻷g|Fr7T )iYm[rE߮cOS+SuL Q^gQq y 5^M9joę0W7&usfے/a?~K`l9mlpwsnm_~mv5/1-%Xw-vulw[=n3NΝ#9'w?i57W[<#(7W8QkLY> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 499 0 obj << /Length 722 /Filter /FlateDecode >> stream xڕTKo@+l)^k1CFJUEBCۃ(w^k y|O{6U02z*IRC)8Enn~NJİfߦOGj 7znT Oh,@f y{;0I"@Jr $5W( cCaj|!  r>KnnP‡&R6K97v(+dJ_ endstream endobj 478 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-068.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 500 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 501 0 R>> /ExtGState << >>/ColorSpace << /sRGB 502 0 R >>>> /Length 4200 /Filter /FlateDecode >> stream x}[ˮ%I ߯8KQUH0-@A0⎀^؎gcW8W}}?o~w)>~no]Z_Gח?~%t;߿ữcD߫wХoGw=?Q_mU^~gx|:忽x﫿}owL2LM%}O_Җ~ }ij1t%}S;dJۏ-fȥ{f.]+-R [.̥}oJ[.i'/bw|fkڻLQvJxzI{{ +)|ih,^k! IcN^>x?rG[m$cDB剥45]щ;$<ش;or>|A0Lm]6'lJOS18[cxcbW Y3O o_Y{x4H{0.xţP8kS=BSV#n*wً4&Yϼw{"W mG2R*)VFlɋoR7ڢ}Vwij6C%%;}(M97q[X/SĦy?sڏsa{.\dWa)by@sʞ|G.7^ (xy>N >=d]Gajb4-o1i6U箱xǟFx=RJe6H..^k| 67s,v* {?}Vhoz"6aneD_XI*4[BLUdƦ}V.Β=ܢzG4G`}v5:pJ (8x Aob 6\I\yl>'ԴxOVylmY$;n|E, ]Qڴp/ߐ4b^] Qi\^ 4sRijonJj٬)47|,ߐǖ}f.xgDi0Yf<[}!t/XJkF{[vv\R"͉ws.)!^Ϩ酕4Hs%}.M;y~`?ތC;+i`|]i'/bw]sĴu>7fKR$E<_~yR x%&:.Y*6E*SX3V̓*,UKb^X|Ʀy3k~`dʩZL|? Rij2eG 45wjam0oHxe'SbwVH°ac/[n Yc8#V*[AA,Ʀ]}f.5uD)kT4juD{f+ n^^MlJ۟NM6}ߌM;y~lUrXWlQr\MPQխ-@n9F*6EKkK͉e,+\ģB +i85X;Υ﹖-;F.omY8|qXVE.^"^zyKB[TykPLZ+ج56?wq7 Ymmw@l_R`-N۪J x¶_[ņ]}f.̙HcacRLQ1~V[")YS?b)4##j>2ņ]}f.FI,BUzbKz.+v"v\bـ͢Lo'm7q%%ċ=Ӵvjb),JMų|Wv"v\5 h%h,rEoH{g J," fb9K606b 3]+\ll ߙ R=v$woH{.)\Z[mCm;H{.+Z1ijbm0oH{.劕v|89.(G+֚q:W;J8u|ز;ob WOֿNt/}o~_8%݌}!ٯ腥45KCa-7$<ز;o2cUks7XRʑ ~aZ~y$7MΗ4wbS`IMMa}`\[v #uKNp g N~ :"l^/c z{pQIЗb(qnᥩqn!88+5NQph3E!Uj`WLX+ ߹VBb+=P˵ǶRn&A363I#qx5$cz/Sx+jbTXL4׌4j\T}Ce1&dΕg okDiPwp̉\#7I~pXHkX 5|5bNC'ZCY|2y[܈tP15LQw͵b.^>x33nμ-Eܻضq%{quqƍXY㲬pqZ-yW[1i6f]JM\ְ5~kNu*Wj:VbVΫ\v"v\+E}B> {*ipٟXJE(p{M;y~-SKnr:GRzjb-,-;yV.g[;TX c-vUhǚ;-.Q(N`WwT*D/p,5qHGmfZyMD.kTAȉCA^sPLZv)5qkxO`XJy)5qk)ߍSƦnKܫݎS3&F.g ,qWW}GThQ64)#M;y~> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 495 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-069.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 505 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 506 0 R/F3 507 0 R>> /ExtGState << >>/ColorSpace << /sRGB 508 0 R >>>> /Length 56722 /Filter /FlateDecode >> stream xMJ6 RIv6`' v6Fk-<8ɽX,Ib_~o|~W_??k\?Z9_~7O?.5ai/?wj?<~ۯϿsu~}8w7ٟf4~~at?_<9z_>J?VOy>~Wz?u̿CFX4z=]/jg=<Ƽ~Cσu}]?ߡu=홏uqߏW)ϟz~ʻ~c_;~>_"e~ƧOM˾=ǭ\Gyʵ셄K*Jq0 PsTٔ.bݪi|>YCNٻ|(̮˚)w%9aIn9O/{$n~/rElu9&.a/G߱Ł[䗷_aj8kŽv7-)]VMv7-GinV8VswPgޢgnPXQgɱ^HvJ5!OK}^f]l:4Tΰhu>Oڦ(Xw?%k0 N%{v[{ixV',kЭ{TH C>Ԍ8gkơ)eSNv.[53-ޚmfM(4UaIX|*l,-V;*rEl[3iƒc3}z`L'ln }ͶFr p`ҽUٔ.bj/͆Z=y>UkYk6"JwEeSNvg?fOXWstP>Գ!|ؒ,V+ř6vQg+U6 ؗ>}b_|4<j,9\b'nj~΢۩'S.}٭olzfcŇg|8&(6S>Wؠ4'"ǜ_eSNvvYRvlclGűT%Ǹ.,)]ӏ2tai?>ټR?0>t c8ڡ{X)]VP^"amM ;˝SK~.Vc/a'Zu;YMyXjW]N^u4+q}7zBԫ.VbIgvѽ׋(j3?Y>2Chg\ȟ~J]'Ha5^U6崋jwfq9޸ 3S%JS˼rݪssv˒nT/rEl.4|#;@պHN[%_uyF]Jݠ^u<,mn>[O~r])p{ꚾig),}Hyyb6 ,_r kVMyXj72>P9@5APH_{0!Ԑ88]vTJS5˦v[V]EU3~*0oon_ul"P(oH}’Z \NwaHSMyXj웵ҧBvEOoӷ2u mx(?u,)׍_ܑ, vJ5-崋j_S8@o֟!J;凯 GD"ΩRNv.6~Nǜpl#NŸܦG=SS`3~ Sb`m>uMKlin͏Oa0 n|z=;=#\Zs;%>Inԯxٔ.b9Tls/nu7v~b[wc lPGօaeSNv.XO'}y݈|yTāNX;}}*rEl[s4Oi3d_}qڟ}rJXsCwQ6ii{Wf)_ĹqO5P܇]k’:Ճg-+EVeo}!`Ǻa]ʧr燲mЎf }ʹ{S ,CƋS{;Q6崋j1wu[5?s4Ly ~H[9uimA(rYzi?{[Ss\?Dyϟe=({ԩe#p ;aMyXڎ/^nl >śG^&ZbRs6(׭_;`mbAE? ;7<99>5)éY:)si\~M-(mnkMyXj뽘`{Ω3,v{ ycl̤Vq&yb'u-ǘhcv. .f9ip1έxvgʱ6XIݠԃ[ْ.a9V=>sx(2ssVl#\S$aE]q"^Na7ZuoWِ.`_v쟁V'gySԧ@F9.%5k@} #6*ԱnfaOl7lff`:V؉gX6˱oss.O\.: ,}^*XRgx6,s/.z,;zgV_wANE^[c32|L, rٛ-\ĢnPeܗv@X3zȨ}jDBk'krlPA-,i(9 O_k%6^}FϬznPOv [~#K]C{+mESrQ|aj93VBw ʖvs .mTΡwNy$t'(}sK܏*,QL=iN̨{Fʦv[f{ǔelp3S9]>`% B?’rupzOBu/rFٔ٭ M_pc2 Zg%Š 6Å>Jw;ʦvq#ڭol!~kysD OQ$1o6'-RY¯Y6崋j{(BN pēr R T,p|c ψUْ}~ٝ؆__ ›XCݷ(}c :-sJg ?v#]QMQ6 ؗOGos XéL7bk)C%մcOΤXF&%clG]v4BP΅CmxDgZ0mH>WN,5ON߉5Wٔv._8 _pCЇ&w9݃m((rn/d7cUC{guoIaNmpB,vk6ʦ;]n>ϛs"2%@,&ϓnMJ(q< _$u@lin뎺$62OۺIGhg͔ox *daBx}+[rEl[u~VxS'6Wsx{Ryf;0aI]@nPy,6acݯ>ynO ;~TC>WXRbIlRV^wc(&8㙯͞]uW$%tq:|vQyٔ.bݪ "6mh'?Z?Eiİ@rl ˭[łsi{qnP%XْRb/G¨%J/'GPs^!]V]-f<@Us 9m [́lˣO6(}56eSNvھcf݊?3*m?b֝Ԉ/29%#{|*򰴵/^M;wjC#M6}R ` t1Y"!VW>ܕA-RVULWӽÃ=,Gg)*K=v=z>.snP9Sv}{Wkܷdĸoc329{#JQKsƲ)]V_dz>B̒@ T'Ky"pX;Ayrv|ٝ=|sɛ^!NxaI_u?~?M9"ڭ,)xSnd}.?qXPЭ9'؁ݞAwlPْ/y19;?=4|* 91S%J}|"6XRMH@t J~D+[r%l;b{Ǵ~S9K+ <>}nP԰/Uؕ8˗MOe{xu'=ZʑLEXR3O',Hw=>Myח98f9aɉgs\)uT<+ҫ &s߫liKHF%9Ϋf(}y(6I,aEXshekEQ6 ؗYMDz ʍG۽%lO%qtR]t/_] :Hotr$/OXRI ;A__i)t@>9Q*|`K+tPL9n%գgaO,vTEʦv[qߎ6*Tv9u]1gq)o`ָ, Y6崋jw~T|c>mcH9f’jS$2 [uVْm~ͺ,ou/I%a=aKZ~`0K;K%{Ih?XAwKB!G"ludǂ^sHp?JߑgǩBlPeŁc[X#gC e ʟ"Wׁ'yamep,\7qF`݅Pٔ.bݯo< }7r|C’Zua鎜 Q6崋j2[8pl[uA?. 8NFL8ʃ_rT"96y\t)T6ai;V?7/]9;f(?.o%5r| Fb;9lin9uN<880i8|{ &(<;۔YbEX!$tX!ؗ_u9 9ցKFWv~r lRxey*,ITƢ(|Ƴ-xxɏu6?dP~T)gK#Mw_ʤsKM9"ڭ@88<_g8(g888&V>)]K#Qt8:QlMWg`GS}GK=p1[E=> yZH+_ubU?!'}[Er +g;sX>u<-mn/X"2;>ɾ"ل= 'A?&N Ai|#崋jrCԇb8lǴEgΔ߈!ԌȆءqMK#aio_v.8w'pxB<Y@];(!Ԏٛ8¢H7M9"ڝ yhrއ(P>TE1#vEsp yZǗX/гW9:-aIɟ؆;OZVs]9pGu!#BX%JJO@txR7(FVai?V]5hl\P@8!ߺL#PnA؉Eli/ )?9| G:c{(4-Iau:*NvXy`sAgj!rx#<4e쐕cWXRrAǓ!v'Sle/k'Yɍ#s[Տe/mԙXQO&j/p>YesC}ٝ ;rn&!nK)5~R_slP1bqȹs*rڵE\ ?8ʖ֮(U’gTt羮ʦcݪ{|G^u!gG3% ]F z$ړ8$ݙHeS1q|\ڡݢdSXĊ. s9[;ڭ']i}эol 1ҀRo|Q1bw=sθ!M9"ڭrX \?#~-f%rNݠT}v [~Guڋډ4^$G{Ξ"8>"=Eo)K[~Ď|\XBn*;qZ ]eb/Eȫ*-Wٔ.b]SyHY&1[fuQ16?ԙXQggbuSl~~ٝŎA~*5+>|Ck"P[R~Kj$vppLX\ S'liK`Gy_%GZXaI^YXe<묲)K[{a䆟TDkmmpE |%<&9v%5bB$J~Ͳ)]V^/p|`'lL{$^6%_'?tRoaa_vglS)A>CڼlN.%>y#"Ki;Qwd))K[V]6?4E|xZp`R+SЦcɱy,"=c*Աn}DBO;{.̨{{)("ȹb7RR2reKNKv. \0&Sd1ٰq:Kr*K6e.N.:Y6ؗvbπIlrNnZfzŊS\rd AiE"Ƶ|#*rEl[uqП1qR3P--s~PjF8؎KG\NvȘ"΍ sQPz̪=uVeSKԷݪDhκL $Sᑼ뎞gfPyJK*3Ws  طUهRvg|RP41(ե:fy(q2d+ڋʦ|l_vr"\1< 8LP(uܽ݁up<-F?JZRV'^U8a(֯DeSNvzt'&ݏZﻄ+|6)H,XqMyXj>mEiFA}Z~aISrXIwybٔ[u;cj52v/, 9x=v_(%崋jر_)Vs՜,b^)GXR;+cÌ~Y>bReS:ڭldysaKiOQM9v%uDd88!/,&ҽ"ʦv[~*VȞh}iihcI5roQvlPlgu+EUtg^MĬkZѫ8ү[3[R+9|&/rpE:׭+o\(-9"ڝsKA.kJʹfHۼabGJsY`!Bf bI]U Θ}Ao[Rew7=W:Fy|˾3%5qt۳qʦv[ݔS9gg,yHiq)_ uvֺr7ev,|g)]V_>+]q޹Ǒ*cGEXRWx:YTInQT]qe]}y;uޢM3帮Aؠb-FNz@nAkӎ.b9mQLJ01cD~s)?Ԏqw %tq)]V^|u4pS98hepNT ,+kVun2)Ygg%NlP=Ŝs5NL{ ˖v]/k? d_2ȾT$G?%,1JnQٔ.bݯkrX 9Ϫ磘`f;QC>?Yu+۹=_X䴔jw+bjx#PZc  Ŝsb=EZuk3崋j⟶^1W✺ȢA\=o67)7obbEe$8^Xd@eSN}^##i]#31s %XXR+WPE*dӡ)]qj/^l.[OΉu[HIJOFk=Ia؆ J5)]ľsL 90 j;˄h[遊rTш_k'R7Wan/ ywB?^)\L>rl!A2INk؇T,[򰴵/Uo>oQrM9"Z+T6(q5~ K8[!sŵHҽcƣB΂v.$}!eZc5- ۲ރoB8HD8GH֯D M(rElhO1$|)Om Tlݧ\8bIZ۶Y~{zBeSq{hz6*hCώTy/!Gb?K*( .bݪ =geuQ(o#W4=[ɳ#>''ʦv[7;_@j 9ؚ5v` }vaLҽc_LeSNv.nFN%7;fH#9v Jkdr'R7ߴ)]VUw90٭]ʻw'&~Ăn#v% FْRb^&S\^ oék7͔jܱo~u(,%/ ݡ;f Q6崋jrGup|0bL3(^ݳXRk]8c%cCwZGٔvS~ޜWKCW_sD"O Ԙ~ci#ʦ|)icɅs^lgz O)]V. u!f[-̥)?uyW*F#rcJ 3G#M9"ڭ~ [\Hۑoa+?Fe`b4@p:Frbчh(9aWGV -O@պHN[ w].=Yӆ̨˩Q]}۝㋧ɜ]cu q=~QAr̒ J; E%g˖v[V]c-&"eX]chMTJp%a.ZL t6̱eSNv7֐G+R6lpJo*{c nK+qGzf{~|湲L[’ꎈ(rEl[unT1T8A_÷Fݯ;R&J;n6)--{ܒeSN}٭o vI_}ݸCRΤ_;()ŠL->ީoZrΐ~ڭtsA/3ʿe1-Šʈcq:v7-)]qߴ#r:G<ѽC}ˉ$\%}P8}vO3*[/_}_krRerDK)2pF=&u*}ٝ뗎s_=X(Hib{Ӓb#>,|}E >7u'i^]=مX/?U񯆾viT%tA\U)l1?nPr%l^ze3K=NVr-9ڝkd%Kb^ξ϶63,tnkݤ{j'=XcwU_ 6RZXJ= q;ڡ;wU6 ؗݪ_bm,]\׾G밗}iRjk6EΉ}C1gӣliש.{|ָw]Bg'.܋ ,K>mA=[e!:|9}޾rOk(%r> kaȩT+=a)r2. kCn3mc2`qjjͦEbEũ偊)]V]nO}-ŏ$x&utALjQqjϚ/&{X[)XR#bGχ*rEl[uAW8[[[L*9 JAq<^`=_|}Q6崋j{8W<T(7DlRQpoQznPv [VޜwF=꽉:R+s%̈8ωC=̈ʆ\v[u9u0q_Yn]LVbG-H %lP!"6T3vTeS~*KcݪKÅ$<ʙ~E9@\f4>rQϔ%Sp<``F#ny)]V,28Bᢽoio| ؤI&;[Fٔ.b&Ί3rYO AfnMH%6vǯ31$=tV4ʦv[{!rW>6O6Z}#r.\T %5u+Ip%,"V(rEl[uA uTg/\o\[5Pj _1XR+trZKy_)K[V].#l>:10 SMrD`I]u嶐.{ nP';崋jwcD'lմom]5F9!ݠYWӮK| f^[ 9K>:ΦTgGNXܟlԝ*;ZHl/zE 8y3gCkҳYSK*N8FݤE^W~٭bNT$KzIx>3^j$U8d%o-yXڎ/;-0dpvstgVCi3I-a:⦨['\>Q2:rLoTm/=TobށXO_g-U6 ؗݹF>2s"}\ L+tRϮ3'ۈ=6grNX<ggVsf$^r.|kpY7Ҝagw&cE!]|5wr5c v \- ĂnVWCaǞI4-yDew+=:O*O䘼w5(!ŠZ-8~R=lʦv;}e;8g!΍~7v֐ [~WZlΊ&^^zF<+=Gɱ)lR:-#Ny8 *yVTeSN}٭u8~} y6Y |iy’걮XJYnPXْ.b9ϛ㽺'hէeAJyA5-m`ưVNyD={P +Ӊ[uGA%UF#~c;lRVg#qC"g]wiggdz0(yH|z<28c<$*r_3=)cP dW'=!).stQ#t _BO9-%j~#(ţ}*m?޶KqR5*rEl;,yNaq,djf9<\=<"t:\A.r~R`_ve]؞ࠗ~+~X\STgoT#9\ x2GeSewWr.8c;kIiSE  ~L8%K;c9?9[x!o)1vOK9?98+,v{土e/ vٙsaoĵEihq\D|TO?st0s= eknϡ{>槟T[|!XR#wkeL`ч7M9"ڝd~Zdoekbo&,SY1c$kԃ{[#]zoX!xWޗyaE}njTY<,MXбbUbs٨kjN*{z=s`I{/H O*CWM9"ڝ>XL:٩VY zk;t=& +,>9Llo]wl~~ͺvDsq8<l@˳W0R'Fa>E[aT6崋j7벆R|epLϭ=;ug.Y|`I']rM9"ڝu8t\Q}ƦO,H.N9u%cE-g'g'-G*rEl[}2" #c+'G$/:jqwFs&QMҝqv*rEl;ҙ爺xX0R]ƕrwȹ𜐢쨛V;v^rZJl;aFSrpڔWޞH*wˣ(ɑJXRq/Oݑ+Qْ}ZW"yסJ"ya;ۋʦv[V& ~~qg`GVPjGOFybI͈㏰wT{Dʦv[r!Н)c-3 xgڼhPb)>qeUt7݌)]~}~s,>'Ck SLNs~MW;ߋEn3r݈sJ$NmĀARr$'VTvI#a} s!]V]"j[&Zq/jTG !-wFrqބuYTٔ.bݪ˭//l)؈[-zBPz+(9R KEu'@^1le/s|{t397|иV}5DzS˘HZ2 KRiye"Ɖg@lҶV]Cm7b{.]<Š87BXĹJwlR%_1?u.T|G?MȑRWؠ?&bE|tgʦv[5asS8|U@ܓLJ7587 횅coXlK7(eKet=ϊ&2(al8Qz=_7Tя7^e;ϊlin1p}GTucp˅ 5v0zS}','ZބĪ{(rEl;1;uԬq瀞xS%Sܻ^OXf qoM9"ڭ3?o~smWy[)?=QA,8G#a=WqGeSNvkܿR8q{n  VTz==s+6_.`_v 4|*H6&;uZ’"rN&{nR].]Vsop✞(ˮy"_&}0fʇgj#{g ˖<,mǗݯelOI N9*K},bq{҅IGʦv[ nOq V褴~|h +9),Hw9ˆ<-5nŇ{!gxS=%Lx|rls?[8eSNv7q0}sCە %U`A,+s˲%VՏyZF^qGQ'({GO@"%KX%.ʦv'yb.gŌcDBLV4ZӼb-fHݠZ,Kjw`x~Z8)m<ܷBKu;f`'NS̼ ,rElO>疏[7ΰng?/,+w9v#WuةUٔ.b9K]2r<0; L'F> ԨkdrHl{]#+ai_vo{T6 ؗݬ5O/%B߼WtYS^±Ra}3tǽQ6acYx!BS9X0O/}uN9’Lq gCwWٔ.b(A 57~`Ien$ݙJeSe7벑JROkވwMBt~_`I͘[Bw]eSNv.<-ldty./Z; B؃1}lf ڭ%z/xko{{n=cd{!qt$Ǣ̈́]~PWx:T6acݪ vDN?_{isz]ÚPޅ[)Ёl ㋰4 -*rEl;1U(^8=尿}h:PƬ<ɗGJKꌽ$q{{I*rEl.w]pnZwaK]7Nu^uRUbݪ˅셾.To(,LK'6x1]VTB,a}ms)]XAKu2NIdRd.dȼ<3?,r?,XRgޒcKX䕒;)K[~]ic>oW9vKq]ؠbCv%ݙLeSNvg]ly+0޵B:E.‚neYG`͝A.|r}V5dKO tEFmJ[6iDž2]YН2T6崋jwe QA/Ӿ(%wP`I)Crx,nP]waw\r&o܃W%G+lP'38(yFPeSNvgܐ>v\Bneɛ{ɼ=+j.9RlyݙLeSe1_Nl|*$ZXҪR9܋{mн"2[eSNv._n3m35zY[^ԚM'AL$ݙIeSN}٭>gp5ާr:AI1- mn%?MXR-ܾIlstR1/.aj/W{x3k].$ @ =GNN_Et=Q6ii__vg{I|*'p}ӖeL]x|{È!vB+0,rEl[)_oa Jk5SxiaAAVW|bۅ AWi)4u|gߑc:HCXRG4Et%li|/vZd{!B}<{vv KRFY59[`w(J9j/կ^.ɍo MY yʽ=6sE]Ti/!]V}])5_}rytEdye9ⴁU1ǯ ,gJeSu/Uh:Ƈ Cq{1 :|z䑰==ZGwTٔvg{g{^(z|vwtI3> ,3"FbqTޚ^[V]5lT΁xx54[T3 ,ْNx{YMyX/_d9dE8#˒*d1snk^Yؗw7{v;{$]4r.v {ܺ/r͔.bheSBr|vyV'uO}2Aj+7I˦v[~؊~{CB~"o!A8!؆=5nƲ)]VsţP.>tnij]ӜyWΤʻ8]H$U6bq_FdTb^b񨒻1{K5E 7Sn}d-1WᾶC3ʶӏW̕%tdٔm|ٝmn1O਀F]n yzK k`N  JʖWP{>[Y%f͞$*,s 񾰖j?uR[%]V3] 甏k/)*<Δ&o`IGrE,2Jwpl6f]nS9Ǥ`Ѡ2D˻O TfN"N3NeS:ڭ "83}?i2RHɺc<KjēЅc/IeSNv.m3]ZpP#è09ϔOؠO^(rEl;b{ Xz*g c;&$]Tq|^bzKeSNvĔTέozT9<߈}\=G K o8ި/B*M9"n8~ysl}ǔWrmaM?.9}ʍeKNvXpÿpQl~h"\~@b-8ۖ1= ݇VnQ6崋jH/&]e~i͜+{彏XR-=ϯ)]V4K1#vnd Z8ho~Ӳ J=fRؠڌ_߈ = b'[t4SNvksxO0̓#͓pXR&VT‰x6a& )jn\Gn߽=kؠ =c)]VUܗys,&sK@Wr\kAl>"Wtg.5MU|ٝS9/lx<~kyqeOctcыv?6(닚н7)v]_vc+Cmfa{7Ǹ< )J,crFO,H3,t/scQPX1Yt\uݚْ5ƙw KL>.aw]3/ʦv[{\j͟}G`-%u{K~zڭrzFx//l%? c6x!_aْ.bݯq9rϛcsh%{}w=(rEl凱X#< h_TÄ|@bYM\kdM9"ڝu-.kB+rQ>PpN`f ̗w!# lin\oO)8'gcBTW'v J1%a]@[Tٔ.bݪ_iw)нoh(Ywvyy{:Eeiv[ ݤ~snwRVsni+__p\{FSi.3H~'sR7(}mv[V]DckS9k(mR_s)_6,8?nS嵉)]Vof#{G_RS.Hpq8uYtgM9 Ytk>f*&TX榿ͽ@>ەr<-bE.{yEqʦ<-JO)9{lZ"Uc%lRS"a$}eL˖v;07"j~rn14V9r왶(s~įXCw3eSNvg۷i>oyWϴֺIk H a 95bY5+˦v[~q*68ظN_' %XXQ` gn{Y{˿eSewrMi%97|RI||xV0ap,X\"Gڰli/s_3r$<[\ 1A;bUY2)?rX>5DE7ؠћr4bه`~l/YȔfe3E66_j ;oFT$]Vs|o=qq6믍=oOeGJX;S~ zCl'NBNT3ʦv[~]gB>u%GIdO*9V’3t$*,JwITٔ.bݜ'3 wFMv>-UKyCG9nh/iz㮿(rEl[uALD !C,?%(CU;BwܮeSNv.e[qXL>7[X{'XP+Vc;.?_ +N2lRV{Y&PfyS=;PH.,(XR7^$VU"RXy%-cߴ@ zYI`=_R|JQ6崋j]isٛ}.c61hgxR!e6) !.4λT6崋ؗﺴeZvXlC4ṗ=V`E'o S(԰/Y{͠ qӰ7jR55;*l߅mCwFٔ.bݪ v6+Ϣ2d#K*NE;lRV$΅7f/<Mfs,|53I1;Fpb,qObM9x/Yl.Nqp恍'޵y`ëi(&,pz,ڔSeKew}cyXըw}wzM`O(pFQ-tMK<~rZJl[uk,d3IOwzu5}뎵q,g> ,41mqRv8VcHmcL}K.=e=q L7nPU'02$ؤz'?$IGʥ?zYNO9nj*w\DyXW#u#!qq;F[r%쩷%o.Yq وYz#$ŋ;6jGߖS/cO,0p~N"wqZsՐbOYQ/FFvxvhf-yj 쩷""΃]z5f]caZ/FkYO\zK,Y}K.=}jgrt̤,[Y38[[6Ko4}KjmO1&y'A]z!»"uLQv3 Pmʳ]SèFgrd{]oYѷsvG^"sk,qPdjQIQ^fXQ=utcK6\ٷgf,*ZB%V+sQ'3oD{+j-9*,obqз)?g<5֌yBKX2v9o$K,o<:ٷKSo^zs@u ,R jzsm׳oɥ?{rǞ?"׍,>}cϟEo,Ng,ѹmRǞ?TS^[w~/༶xݤpN]s,Fy7UAsn~^me}K.nhۿl8gx]34-S/b8-_4VT=r*,tv=<5q}o,GA, 3B(~uR>/ݻp&VS+qnx0۾1}Snѻ7|WNEy)cI]Y:9W?b/ԞvWVvߖKSaO,xspF➉wb%orX6cIm8m'6+TۤrKGek;};v%|-:)]XS|ig)/Mw"SVgb7̅ߋ~ȹE*)U+cMMGR;hRۣU[S];.Fy̜ 8qXTwLUA0-̶+}K.= K=sc3_& aBJQWã`Fas.0Us^9GGoxSi}A>NÔ皸,w.j5u_Oa_T >o˩?z׷WR<Ɂ'F1,4LLD  rš`D0 n{fȣ4,0{1a{؝EcZ~/%% XQW~/,d16 56)ѷSo1 GzLX$ žUIDyτ#5FsDoSS}6]`@p@IKvezFɱKJlR6>+۞qߒK/aOkS}1.dYEk*ɵ~[gpq&2pem:˩?z{Pj<Ty^uRVbEͼ``;xR#q{] ;(t‘',E*9$V9(qXLn;KeߒK/aO˦d?t%ֶEv$E6M3oQrKivnv[SD(}Nsb ׺ hƚy"1'4e=2}K.>5\4o=8ޱ.\Õ{7UrxJq}P*m?YJ}[N=u?JD;9CM4F4QE,CXQwڔn،N\z {3WΛ6%]\s\ \rSMؔt;m[r%Bɹ&wf *+qb9ǐPr3N,eYV(\z {]Kt.N/L"ؾ"LS6?%G|}bELgN؎)3\z {]K$.bщ/eFyi )(!%3I]s@lIQmro˥e20U#9+YUnCƣfҔ#/HbEe9sXRXpU}[N=}rߊbYcҚ(R>ZKlRi~ c;jr%쩷/]<'gHj6'۔O$?+9Ym_WۤҾ;JN=4zh>'GV^L\[Xf`JK9^MՈ|0c24mW\z {]c<Õ OA0%$F.Z ãq& c3REw []VR]F;\:_Sᴷ7#13]#{Hӳw*|[J$\% `'Vԕ{a# &4WSS`O,7,4UdB=p aEep6iLЕ}K.= \B-#栾:yaYMoSVT&K"5[Ioɥ~M39o{/OnTfM%yF428gD-'eqYs1hP{m)INM3L+݊<5Ի%~+&:o~n2VPisf'c1핡[r%쩷1"6ek3q٘k/I}Zf䊼VȄCX|vτC[r%16JaqbTclsLZc c+5b1vsOSc Uz_߾m*yͤ9~lRH}v:{>cGgW /lPX6V(gl6V>J>9&L6{p{2m_y6pߒzwy}ݥ4͡%|",'71q>v7Eyt?%GLzbEX'. ʓ4 ~:'q\FĢџ LQq m\ܷ)~X:Lw1N'0[#7fcM8v+I[rE y>' `b|19VE,U@D}j{f;6s~N/&m"W'qfx׍UGĬg,Nvݷ]If/+o&S@Z+>9*e<ھf]rkSk 2o39HgŲW8ع=S/¥xcE<# [3<5Իemn)NM;90cޜe:MS(8ȤuPߒK/aOkQrG'֤蠟-Z(#GIDb.^Xs˶eߒKs?}N99Lx7۔XQWF' Imܣ)~ؚ;3}N $Bo $vLlց538-,26g#yݷi{]%xDr'|> #ėIFlQvՊoaO+}Snѻ*Rԁ T|EyCI<ɷ ]<39FKƉmL%^žz{!'b A.9ى)M.gqߒK/aOkJ~1ƣ4X** h;pnȹoɥ޵=}~9-,Rk*&6)Gۋ^Z;O6)[QNr%}y1f ̩hnqj5šT50݌LE+U\z {1+OEI,CvLrD$VȈo1%OM=]_X˹k}5ԹXؤBĢOV%^žzؔTsrOvvQM)%VT͹Ҏ%^žz_T4sr:ϕ8C4Cq~I9'ղ(9φ^<˖y`O/0%̙-'Mr xJHche !SbW2O;|K.=[)a NL!aʟ3J!dAnRoɥ?>"jǹGĭokcO׻+>}DվVm:zY,JaYl_8(zpPÔ/$]1V\s&W a',n{f|\z {gy7Wٓa* Y>I2%ox*{8dahi.eOV+ߙ0g"2$Zx77[fLA䦱FYӒV"c;bv/k<5et$JC|x7oӔqg3 kAq`AWYܷ)D4wo ꡿ VyO92}%V}9.an{>}K.hhv&Jp9cqd,ݹ-Z|^rxWrsNVk}_TdtcsnLX""ê"&r܅L*bb&moɥuޏ`!/r {TfMlRޕ쵻mW M"GKDWb xI>Q%$Vԓsvu]vw-"GZK]uG{&1>^rE =Xʶ\W-nòBFri[u-S0v_XQ{Zm}K^uی]Vٶ,+rي%,&́;,,{apߒK/aO6:̈C$&g)GĊ:< Gnbζ/m˾%^žz]62׋93on\ݢ?RGEWXQ#gYX\϶{ެtߒmѻZ.yldh8 $3Se-V]3Sr]؍F#%OMGo W7.Ko&G$7:S 8mcᶝꮈ))|Uo?O7).tʥ"HxRT52D'[ ]z哪OI͕jՑUfr~LDt\[ߝ➇q&EƢ犸I[bReoYVc3p|~QfO`!q,8de-CԧFCןؖJ蒽y ' `Rl#2ɈjVgDcJǨe'eT7M̋(t4rtj,n{;}K.= !%&A=/ҤE{YBYasp$l;kfߔҜk,=8-}1A\8-N˾y[ɧ A]kNæ؆MnYi}[ޜ So1؎"Cq\r@ Hʉ}Y_l%Auk'kEVlB%^žzwi Usro "4)b4EqB'S\ +j:vpD쩷‘`KeN,@)b>a*QpM`ҴY1%!M_r%쩷e9ph'}bݍdE;>e01[0՗v&Io!HfߖKSaOkNFdܠ C>^oDEq'۷߶F }b;O$j;fߒK/aO,F({KrX.$XȐRf9Dm6Sńm_yvߒK/aO{ q$ %8/BŃzIDB_l%gHضw%<y); \>Ìm)^aV" ]f-kPXRU,96f,+T-žzؔ8ei>(æ$lF&|uX:̫k[Դ?z."`"6f:`}AaH9l%iObCOxطi{][my__\ywT[w%v죶WԷKSoŤ987Gy{7HۻHKnIHXQwò2^huߒK/aO=SjhEsP;My(aQ,aX@%^žz׳4&pt sXJ^2gio9+Tsn0F۾R\z {]ӻ$>q*AmRk'=Rtk*/R'YH}K.ۿvbc89ǐRc wS̏u1q4N"-9޿{1}5:9;yo;+j:"9)'[r%wc#,dϜāXLAN-C1ļj9>ĊJPr`,cv}K.=ðP#kdMY RrQMa%v3B-Իl_qqd܍(z~E6F;Mkp`mL%Cm/)eKu`Ok?8jF_`GE>Q,aS.`WaEe iMmg [r5ZG^[w:|yǎI(޺Ý76{ƙRAƣ=]V|>-6O^(azy /c!Gm#$G՗DE9q1ի>#)i{ǯ"(ˠGK+z b"%6ĝZ}9_%̓4*)w+#[&Ol5OI^o#=3O1 \51~ ݿJy.5?b-NOI޵~uD.i880Dp# j"Xʇ:%]Soɥ~q]>&ҤA͒JfĊHamQ~b9J쩷e1 fuEfК>SsbE (Nrcon{u}K{gɋ˹)"l$ SljBzJEbEsҜ C\v9'ݷKSo? ",ӕ98l&X))OS~)9i%VTI801<5۩<&eJdGb{cr[]5 V {:7ikg.oQgrz8v  Bg,ћ՛V۽VNM"G^1˔56ƣGMײ|!`XQ#gfX$ɶ{z[SocJ;3'D/yڙQ=5K#ՓCȘmgF[r%w/r=A:,D`8 )?K,g tPs#lOX֡wۤU w>'FhҀ5!a[ƚ6Q}0v!,m pߒ?G_< #ھxp53иwx:Zʿ[آ6Mbg-۞y>pߒK/b VTrW cH 9FY!S38 r2-OM{88*>'96(²M*ycn;wx"SYoʭ?z{}U\%{[&k@$&e9-#qWOܷKS}r'G@ hP{YR>9+NCEq;NNC<5c %#ĥ{?&neP(+*'s&/nitߒK/aO=Ɛ5*ĩ:orP{5Ak8V+Ι80} N<5cl؄ٴ4ܛ_N赜^cE=`o]Lh;]fٷdm{#|rQG&诿%GAĊLmNAoɥ5~2ȜVȀ7璸iIc,Y2 3*;Tm-OM=X?t>g޺N;0\2(~7#,ض+%6)w%r% `O=\zcAXp/K3Z<bX>PXQ#'lil ^m?9V (j8RBaMegdzs}K{4;]Q"ks}|a[QOFb>lgaꧦj㶽tj9H3ksMy% N5aol3׎̫[r%쩷J1]yːp^Wc" )olRDq`OE+ΜٷKS; };d yG -p$ZH'C{!m[2@Z}Jjqjx{Yq7׭gȷq8jKTwꑄ+W{3_w9ol) ƙ]31i* oR]e\9xs7Kđ8'Cj'Pɫ6W> rg9jKK#W$1̣~2ڛ8~j5OI^{u ͨZŰLB Qƙ*%[:ϣv))еwFrۜyw$qhUxhIn*MR=]Avߎ~s`&G z&MdNy 5UIʼnXv7)zyv %?|ܡ|]tkM,NL-[ϲ.޻AfܛAثyfق)tr 򲃬8ZYWmg[So?Kg7wtF˭ Nt*GrKm}6\Zwۤ(4[ϲqa99 I^'zcE ;3bm ;sߒK/aO(_N˅pD}!(75%\ۂ,dn3EO}K.=`JDm`Aѳ/ nwVg.ESRj#ܡk}1}-] ,ڲ/?l !)[z28YaKgZ#gn=Gёs6]v0r)ƅe08*J}J*m;u)VNɈ8B'N+KR#jH)8>ŀ8jsR]41G J?:Q:Rj=*FC,p vҬ>%6]Lv5J,bp.WY-elHiP jOIp?jBF#A~8&NK15 ' Ğ^>)Moi ^*C.O׬\iY1ƑDib6C%6ĝEnӔNADm29{.b[ ]h}| cs ^oZYҋH=1:/x(/r g!ibwyEFGcR]>92m8>]Kq 'b>@ l5-IiSfS~&<0w!MGbdD٬V{٨OIp޲gge/'nQupo Qދ MlR*k./6)4o˥~o.NXqdrq,3}KgbϜ(GvߖK/aO_gIӘ9rEa9a}w=y%H0wߒK/aO,b9 sH틇CoO9Rk.&˅>.&oɭ?zY^\3#a(x7mE;? kjfbq$,# ȐEMyi,+痃CϸsOz;Ear`9ܤK.\z {gǍ^/ec67/b8x M[Fs&ݩktߒK/aO=08tesr-cF́!j3aPaeq,Q֮풣zbE1Y؋&oɥ?K{WQӢ%+z `L]Wܷѻo1D>Mz7щk3dޔ"jm#ݷ)z2ʼnqt^C*pz ^|敷yR3Q ؉bn}[N=%]GʍY!b-WR7ߥ%=+j؜AG=%^žzw,X ̹2wcfzd,ܔrL22.{<5m5%V1pP6#*)X>aVTQ#k@]] ܷKS]"D/@= ,n\#.j΃oa#cMʿKm4gooҗm {*eʱw4TOo9 np)^]zo2!a bCUڠt[RŠ݌mH[EgoKӶ;srf"]+ŋ#OmMqߒK\G2 5f^z+QZmq 걩"lı wZG$zq`;qw>S7ƑyhVSRj#ܡkY[b&?R (94$6Vp1M]O-ςK,|x{eì_yn+NĝF_1Oׁ0՝F_))gb GmutceUi qv-M|SRj#ܡ~y,u8h%us6VTw")j9SoSѻξAFcXX;_O嘲-1 MG+$&?EZG *=Td!C=|!HN{ {}~-yjrmO|7Uڌuo [7UDKakmSw޺kߵR]}e-ú(/ެm+7aBÜ>,H(/ ';[ SRjCܩS LxܭHF_Ǜ[LLQ n݄ۼfVaQկI)1#\oo^畸yDOe57z\cR]KwD~~nhK1M3b,ݭΌ@TR]SzQ^T?7LտPg^HX>  R_}JJm;tC``0%†fF.$ܑԠѳ83OZm^OIpoKO*V,v2"n9)zHM\kN(nSjWךye8̘U7ñ܉"8##1:±Zi5Q:, CןO>]gDg>u8' Z8? 2ZOnպn>%zZ~~;I<E;iKOb 2/Ej'))!;數` ?6^y(‘3Q 02SRj#ܡk¾ع}(;0fu5fzRm]8-SLOI^{u qFu)o@y2 swo) V}m)plY)zekцY"ޏFvzl; בJP86R=]+u!1!ТDpb51ĨȌx80)‡~w2A:B@xIA$~RH =VWޣPR]#z-.#KQy8uT pIȭ9OIp5s0`hUyÄ,1d%c)y83T![I>%6JW~WCg=$ᬿH=:{dZdÉUiACbmW-ςr/~9,^49F%Zΐ cƜ 0 }M_\z {]KukLrm& ]{'=?h/;UzaVIԷ)~׌sq} sGל[Ɂ;8t%^t%gA(}s.Op{=o˥{`SD w~V}*쌾pXQvV6 =ˠܷi`Y#C&у쌢rm%,R-V rnԴ4 tM_)92Ի@]@@_j%ǩ42aXe@}K~쐎Aj5zgЮ#yjbEegaQ:ٷ)~y̧Efw!}5f6X!\.lw_+92۞̾%\{vo)9z&nx3I5so&;)X]XQ=CAM6AvKө<5g<=sb׳ Rzg9&1rhf,vo˩D┉" /''-f>27sjK0McE4]ںmP]з]3/\3̝w0Y^|LA];d YvSv= xwY( @ )ﰐ_rDa$VLXqf,v%Rpߊ_HMa;2U?'gԋL|MyL67 +j,'b:e"=3}K{0_a1M^,`lRֈUXp#[r%9tosXԠ7ϱ38: jE((ms5zZɥbSo/܏$T\>wi.VRzG,iaMu[mhݜ3\z {]gٜˉ]I$uoSԮ!@rIlRcL,ndY9zw-c^sjXY:8.9$TAĢuoɥ~Βy{֛Eaq'!r*h&w¢l;oS6]g#l4u05L6:q)8U+*9aDiEm_F}[N=.E9LQ98LSy:XHy=[O_ VʪIٖ߫]{W9 d~qAδΝAjXQ] g]A[Դ?z&Az:@rh!;>G8L$Eݏ#H/2RaxlcҳUؿ yɓ>aKHTw+HT1=17N/V%=))е~\`Au?Fj$pG-)2jA 3V+ȏ|ccaȻu4 vWvZ$N8O@F?pȭYN}JJm;t+ފa0{poi/`<ɥLC8#&ٳՙw'5u+b4qsi;l; JUf 0˽pYy*_Kpe b1Rܠ6EmHns,gE`+↢EFc!իL_My'еq>ӈ ) gG~s,ݱ4DIFlЍV+?k."S&% vF_M YTh-_cdfCZISs%alҩk'v0{I3ĉYrt`|Y;ĉ"qV3Gw*yP_Tީ v-E~DHT8*VK}))n7Mf;< DS DL\#cp9'}Z mѵ2|X4%nz%"爙R[$tnudg$Y>:u~ՙ [q$mf4{cbq-mmRi쥝aj"f,N0 NU$CbKM7D(F{9l5dOI^{ug# H)p+*j6`Uf Dʸeν*;tjx!>k8ƾўsь[ٰ$>Uv=2U2`mL 7cȳޓRT(7DMq3TzWT$ܾVQ d].FPgYYU\D,d ,Zu;}JJm;u0eֱ,soiwBX]q${#n\[%qy,z՟.K2.ܭd~ mj[Iq8`4p_5lH 6Voyd!pȈnFxVc'[So?Bbv=87QC]6ëXQ%9GE]gQߒz]zNʼn9@Fξ~'`sfRc/Ln9}K.=ֳT@2\DPq?n'>haS!,aM=%N 2v~qYXĀf-G<5,A!,AJ; D%YQ!,fi7Z!,G!*nBXܷ56yLKV1tJψ}'VTf2:8vb{gf2rߖz{N^ZM+Kኰ)L7 YA\H!ަ&o+cF oJ$G3!|26y3ɣvaMU9 0v2P[r%쩷E]j]7K:-tF)dz]l ;m}[<޵lt&.ϠHw(v{.Ŏ0ݩA=5҃gcͶ]}KRwf}$sX݈\13ZGGFrnudw꟠qݶ/w-RSq&zg!Uм78˱Q wZ#h0 ثOBaSZ)ETq$tc Zn5ڻOIpV#+N-zz×DqAAړ1 G[JQ_89e=q @}JJm;t=8͜;~0:"b3 ҇;3LpƑ@~\lC&zޚwZ3 m j>ԫX;ǥ TQii%,Uw4U^s0ۡu Fxqs0Ӈ(C5qT(N<Ϣd8ju#()7uU1pnCݽ k\Ce^3H \n&Z]yJ}ZJm;t-d@ ^mTT6aCpV[NzJ}i)1е(9,,fF0\kMyV,,@I/Jq$1Dfa1TCYXܧFCן(|~a`qp3iq)98_~!ן[ݹPR] Kq?!Z?3cXak#Ÿ[u`R]=x2-xH>Dx*|{OqSRj#ܡ՟~~qݝdlB0g"ȸyM31[u}øoܡk_Idź%Ꮎ=[Ƒ"b?wוRj#ܡ(Kx=񣾤Vճ\3&FT͗NnJPRhcܡk'ud 2%6 ^]&#Dlqg)Ƒ11A`jBԧFCr}s쓡1*wϝ=& DcX8nz}Om4]ɒ6zqcfa(byS ?q$vVjuS}Jj!a%6%@E Tc{~ G m7q7f,z|>%Xx_]>L|SN3 bR]?Sbn1D+q+wSRj#ܡkyBbf AYFӵrOun GbeN1&#fK-0D+rgOhGwj#ܡ>o }$ 8)8V_ E~gwSCן#<2/q.b$}:Gx$S,E̊pIdt s$Nl iw쿺.[o%c!!|zZ`V&cTY=1e⥵lIjg(qLCV"FcL#'NH4W*FofoOIpuXHW+,t>^uNҩMTZ3"K i}}γn)ml_]"Sz~ƃş&0.{J`-;7 AE^U))cK>-A ^83}%Vؠ'NDf1 aφ}JJm/9tqxa` D'HP럥3D%+IH8KZ ԧFCW}$b2tMz"u=JcXPuqp%Wp]V;O@_5Qxg/VD_Yz"l$v|ǚd(=ae 2'}+' w[ g"i⑿/it#q =-՞8YRZ!aJh~+ }Z m;uqP &/EE[:(~!i_MM 7jϡ>%6ĝz &'a٣%K%6fMv3e UWEdW0S$2nw/UfXJm;tǃ cA9.=wKퟹd+jܮyX;t#W)FqŊFN UaF"cBf zXCFViwjaG:{ǚ/X訧t"p&lBNU UR]GR͞i1%=D mI8J i5yCI)j$*b$Iw<-%)G$ep$F3q=zV{3ԧVz~usm|~dTmܭ\I L)\g‘bl#i3$ ;X/b3YqfL|1/<{If4m4'R)FXZECxob &qXWBaNM`V照B/x&3v!t/1D?LHaK17;l]|c"r1]/\ۍq x؆}-dZID &oܫ B&fǗ Y=<0gD7߱cG~"ik\t|y1牸h78P(c1L*nFlp3FshbcAq;7& +vu6؛;>/f# i`{{/&7D '&:K3FZES7,?}tZ{=`nD&~BgwD3#ƽiboM|^ `@'y=Lq1lkmܡ˼99ibZ/}1RTo?}TeyoS}l dLkrwuCX'Dy"?y7|q-=041710E?/0q^oxf*9K/c&%80#BbN1LIS7Pgy^ȕcy%qƷ08Ə}]'$Z€_xg:y/9ib~yE:|F`gN[NO]DU?I0>hEpW-0Zn<W;mQ7im76;'MD/}7A{|/s?duaf%@i8 ^I|8j05Xdvؤ^`p2mbc8tϸ(r>h9AL(GtψwAL`BEc %ioЍB*nPr8ߌQx4yME4AQ xfYE9p􉱿j$Mݐ__V rZn5M8 \"@.|@WIσY3p=0ODY-*Ko60&yCɱa|'xS4gw({;偤5(?*sijhIt%dqq1q ~̅?Sh +"owMy3*`O=x<}=Z&^ǝ c&J:7ڋ7{7^l0MQ{w%i{?xn~.\nfFkm<ׅ.m<41(И{;iL*gh3 &l؉6^b?q.aՉ(rI#295s?E"lwVyJ!}g1;v&Y )*Fl? o K0'.9p5+$M0kױ,|EvzI:^c~cچw*Ruv7^E%4၌0*m!M[t n)x焫ۂgCg^X,5BpKZ<Myю a/_|Yƃ;gӹ7O mV)sҷN<7OwyE G~ףy3eY_/ZΛC_vov/PtiNvUoioZs],43ڈs)+pjDY-!+ԛᧄ15 y{\!nO'=-pJdVrJWݪmd0BxI3L.g qZu2cQm݆ ˭+xTy.nIg0 udS"W6w 2`fMgҺ]Yӵhc>6k%e(%(PZu9 4)Jm֚xP sM&&m˜[یME4Kß2'MHǡc.dN ݦӔv՛E;zkWxiw؄r?Ii-"OG@_ac=&cI]\ξ6Li*;B.A:\s`{9w+U( _/a8v\Sؐconq7c/R)ˎ^LɄ{Vݾ`q~-/ VLlH$OlE\uxk jjGԙI8sqWJOl4 Fk5UR4{ɹ~2.[uR|nTjgJpF>b42e}rc^&S.,CvM/i'[^J_VKlZs*q]JMٙD|=B{h5>gI^O{t_ 's;.%g%lc'wCi:ٟx֚]&Jk kŻuE8g('k.㻬Lz? 牢^{h=+R"uW!neړgyk7Qlrb.><9:]Qfhn & _M,o2fryNN3LNswhߥRP.ZC3lP4f&A?KZP Z B^u!Loo 1 c1 c!7ݣ/=GU=#W)Բޤz iÇ$J,[Ca|a#a]<NCG:s1'DO)yfM:SN*}CP4K;î,}&6i2`.0k7,Wj|z\нA*WrA`+Z';ZO2lHC=)MZ W?I P`Y0Y"]@`zF,Ӂ+JOmB҂T#WVxO~5gHզL!GɪTs 쒇7;s;$qRB+tr$WȦ7/WH+Fܨ>7Mgh)<0RݖPXnR7J^Ź+9q;ԝ6Fzw+><٘>=1BKO\T5>Wt>J#xXe&Ѝ(㾙T78$1aL83~|LnC6H  i-" C_Y|qoT?ND6N+qE;I-?r)9ἵs=^=N?oAGq>n0<$^hr77kK./UuGd_}T[V!zyx:6)dH0Iw%|,tH ԢIt0p)d c=wcV$/q4m$i c٥%R\(O)06wڊ]g |&*NGʾϾM}7=Z~Uh!S_kW eQ)OU j$w0=X$B*5[`iPD,4 5ݐPMrҁk|r0B袄@}qT   k?4y/,Hc`EZ:4y,bW\ Eҷ=o@p{I;ʂLP_y4ɘZ<X@|f1FsK 902:sLSFZmBeVLL\Z$W˷Czz̮ϗ,q7)#/0BMoÊ"SR";o#hMf .k0w`md]ȬW,c=˨C\U%ZtFp.ijHCzG>~~?s՛/~/CQPD endstream endobj 510 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 514 0 obj << /Length 937 /Filter /FlateDecode >> stream xڥVMo@W,5 TmU=Kbɯ,IT؏7oZz!I/6dڋXIMW?EF$UlO`tiO" 3鍯[ʈ$_h`00e Q,aEoaFٶ@U-Jc*qjPk|lS42Tյ}KÇ'8]tMV>:4;ôaABa+Ewp,_@؜UDIܢlxyCY! Ee4ʒ)lxTe/j;y9G\k=3?q쿌#<岳}q64z٦;\V%"岓<*;H~['ZyJB Q [l;\r\򚊌ZmSm4ōzj24"ԱS5J6E`ms[6 w%#.w&ʾڅ€R8m݊!QڠqKڹv*+@֥ ,{f=> /ExtGState << >>/ColorSpace << /sRGB 518 0 R >>>> /Length 29783 /Filter /FlateDecode >> stream x%r6?OIj*6@l^@B$JH~}WM9VUY(?|u]???y__~_IwY/׿/_o~Ox'/j?Gwj?Q~?Q>݃~|s,Kg]N??~hWYe&BY,Ÿ^QWe&n\+_"pXMo^oV}@O +( h(?8 ?ĵϓ^!hSVj#~Dz,D?G-DAz~>8 ?bոwBƽxO~@)wpˏ1~^zSey}k*hi8 Wۯx&;{W7ڔl;>ݫz{ϡ?{j ^]ޟIHQW)½rWS)+wpۏ~їF/[?oogzG^ jIlSVJYS#:ϡ@O[;S~>umy~?xW+_ 60ྸ=~ϩ~_~%eS6m]?8?bE'=q-J6m%=yV>ŏb߯gt333z$\畾w04q` {mJ6\E}R })f<[>mw (>m{J(+q 6e%%r}V|`|b~2'Utµxj[6e%v{Am]{!_k hh<ÝPϋ(܈7^!O٦d#=;x=£~(ށӨSF\sG ЫPx΅{Y/}760=ྸϸv4"v5 ӂa1B#A]{RzK?a~uG\4>8f//d7jaqJEZ8d;l;~^bEup􆶮xd~? # T^KyԦd#=1lEbN;x= l>'8?^)J1+1wwc3ߚ騭58G^(R &$Zr6iN>}>[Tw(~wk^`0~F,闾#ĐXHt?Ꮠ038(AΎ;m:X?pE.'HoWoXb%찬yG>}cGǪh[vgPbƩȈn };8I췟m;}?Z_CΑ{bcvP7%.^ž}-J}*o/P$yFwĦA\%/׸M_h{*]q}տ4Ľ{[Ddmx*TEvbϝ)7ߚEt>5Gsjfq GCKF̵O + &WqI=.-{2k'+ ]Kj0!͒90'62C;Nߐ~I'Byrm?c4E;6GLXfm/17R95cPoH6Eo5 }֭yaGmZr/ߎEa%Mɡr~;y>~NM:7it"vۣ5V|ecL%H-{27I-ϩ=^)zwD};`%.J{Lgb-Y3?}#ݶEowl{mM{dCeɃ1O376%pph—ܾ!qox {T|;'[ 4$Lcg &޴Qk a(lMyWe/bx{:`W)ASwV\(zJrd,;ǤWWKLmؓmvu]55o U Iho ωJyIcߙn_mN^ƞ}-x̚0{Mc2%`Di-GO!lL׾)}N^ƞ}-#g~NMndx^Qɼ#“v"+>^xr6ۖ]=ypÛr |qx# Ft1:Gŗ抧"fFXkM3h[v"F^2 MEO<1&e-6b Brm;`J*9ۑ&ִKboJmؓr5b4e!֬Xh\{i )zQJw.6%6%SS"bߐj[vkA챼zZy" ?6yKXkb3bSo^x8X%Zvkrqrګ|K#wZ%c#eOAbSʵ>hZ16Ǿ%yq'o+'=;WKbq^ga)pS7}_|i7/bxsϩYXN!X2p?A&xQMi4bޘs^m.^~ֵO|[kr9NN͊>Cm`$ͽmnb% ScڟXwFm͋/{mg-VKkҴXzw1fJ#J9C07%G۶'=S:35CxS@H*i2[rL5K>n[}{^5υ h/_ISen;.))9 ĚxhoH%>2jò4ܦkcto#V? eZG36 E\\!"AZIߔ}mI'o%x,5bbĨ",y2'>Ʀt;yg`#<7%Ţmۻ=p71 sR Ҽ,زl;tg9wɼ2-x {~D?ޮ1Xk3O0|?mq+ie vk"2h,W8{ʸۦ}3 o_ rE}xlknfr~,]>0e5vKI|+]7;䛒mK/Zڿh V!:#wqq7g ZkiWby-9g۶_=N~MMU )@sOF^+)GoĶclXbME_]φ|A҄$Lw[XK;bk &a<7}3jMy{gGE?o`S^Ŵ ,<'Zc%; X ;;"M'5 o;9?FAɵWi'1F8.3ɉ{bn;eD^KoK M) mSaO~_*&w) wZYuuźBN[;cTh[d {N< ,W+UJ{.c-ͽ!B>{Fmܶ%K3S~_R3Qhzn$9w76ANWb;i݃g۲'セ$hE?Ĕ+x*RlH56%QKuBپ)ejnx {xP9`"(A޶>cSʚI;m=y{i޾(湃bN#b@cY?؈b,%a_Ugb"|S-ڶ]L=yﵤ㣯X #+AbI^K϶# '^-Xn[vb޼Z|>#V[4RGAׅQk| {acWnxs۲'o_ Vv@Lӽ=Jwv{$6W ;2*3sHܶ%{ǵ0m0D9&3ŸOl0-Z> Nj)zv"ώ9 eqcKpC%sriO%R?f 'MѶb*sd|Ec`?BH\-"y,^li"?'}L -{2mow<9R?SS:_Aےul;_Jo54 ؋brl/GKؓιo$pdPG/I#ߧ!XKk1Lkl;m˞L1|c~jnwqOܱ,ȒJlJjf g+]w1m;y{369s5N?r$J"f;F%MhXw;שж%{uBO95[XV| K~NێLJ)bkXݶɴxu\ۚT$tsWr]Iֽҹŀzvfwj[v"dКzd^pUnV&7Jvq/|W@m.^~9q7Q65/I;irHb%\ᰦpwW۾-9ƞ~ o94!K}qx3 vyM1&r?*!%בݶɴxRNMZJoTn#Nߔ2NV6忻w%@X|)ɓ)v65+Oe/bx1XV,>5Q$R5="M)G}0 [3pqk(soڅMְv2(e/aO!w)~Gcְ:c{fP %}ʝB]Z)ec } n[dZo}-).5_㩊U]_rﹱ)9Kck{dYE-{ocҴŷ6%d$XI}D9+ %}Sj.ž}-E2>fM-عa uyecq[2#,nߔ26޷]Ll޺oK:F[U@KZ]+\ #6rs&bCU\ї`Xf'{ʊd(:Hqp#-oڔl;>5\g+:3^!>OeQ|$؊hq =9LՍkL׶s٦wo~xf/EOQљ3PqK2+E~+_"N+nqWѿQkiT,@;pq߃H4?<ﭶK4Q{7Yؔ^)>ڔU;~UPZǍh^b;qfvR "ڔl;ս3= BBӃ#Rql8 3G~5q%$V+GypTڰw̪zElF^zg5^n+Ga5%B%+3)wrBOr[Q4 R>] 'a9rbŌq l@)+wr[QiAw~D;',;2OfeY7+LaRH_p1bpW}fq!E+Z|zCnb7j(>ej⹲W _fy~P q'W?<%^%ϡr\?)FC@*ik8 TE}lSV_#κCxx*)1_r,,/(x|$AGeD#KM[Ƹ#9V4v]5_ˍޮ{ch+`P^G1E^GfM[FwEslv:%W+{L 1L+Uf+8KW Si+wp3>CqGԣl,Ƭ4ta`V0bf6鎽lmJ6\R-~A([_CtBY ӯSPDÊc\y-nSV$sC&^XĊj>NIF" 7V}N>a 7%~,ضbJ=^z?4.[âc|Wd'XKu5AG؋-c-x{Eg|(N9:ϘxQ,y_OyM+܈7Xq\)wmx {>1rc-nt<]q 5]3Ϛb.]s۲'o_ ]Kj"|cPq-0y_ 3%~-x { 3*OIzt3xg0Ltٶ%㱋QXӑm!a|Q$1FGk+e-A]؊X}̍s۲'k{HFsjnbZ;Ӹ9@DMȇXK+KAeϾGp۲'o.HY 3[SCj* kisf!#7%'%#"t5аNjDP\Kg" LumǎJ;W"5#,seO uk&/HaS$ E5luޚVSjc'n[vWȑf0ݚ'<*cH:fic%}pOi7/bx%^2{hbpO=^7+;)_vD4R !LՌ3};e/aO}Y[3)'ƞv8qWo R/gcn;m.^žw?6XW.c4,-X:׏IsdegEGcn~ݶ4_}-rF:W YUI^[s'zaXܶ%cd[DsD#*T3mOqoMs1hXrk-x { ᡕ=OͭV{cɣŶ +nc~kXTsNY9N;xrckŵ2|XEV%cm;&}"`kߔ~Im {ֵt)k^5h'ÄfmWRaS91UwVȶe/aO^iL)]D,%X- gHTYsƦlpj,6oH8V]=y{q+Ԑn:Kcgyb-7ScW.mٓ)'o/W F#*O& Gwղ\r&Rwuj/OǓUm͋/1t*3ODf!}f@ KH+4D,vb3wmŔ/`ejlr仚%vؔ1&*lž[aܶ%dtoC`oNq^<[/a%a4$3wj6n[vAs1kPsWGdmP':Js1kXOڍ|S˳Uye4r&2u;xrN=Ħt6hkXV)=v۲'oKb7vE-HH,{gyIb-15Y^mWf6m͋/{̏u,&|NvO!r1)y1m_X|{r,C%lp7%aض%h+&Y!KUDaXFXK++&m 2^k>6_d ۿKGZAe94pmH8}nvx'Jh15M@lMv1-7]Tpxlyh)RG-n{.K} cSrӚgLX6a}Ͽvܼ[{SaP8$cUw=>d'mMdX[[]n[dZxZ7O<OHy]ו]L}Բ5;ׄ-&%mKؓ+>Śy)>V̱}[g44#lcn(-yȹbmsHO1֧gVGXRd]-ƽ?YQѐJVۖ]=yxrg62Y_*j3C--Of*ֶW%]OٚQUa/\}_^{Ͷe/aO{J],Ƙp f/9 {>YEM#sc;w{Fv_U~qޱ-mͬxoDn5-edg['*XT\@۴_}ZP7K=[:㤶.]+i3,-[x˺37c^9%5r/{:"R_m  +igXbjoltIw헃=Gfs\`^So<-q M)ZA_b'_S'{{ϩAodHJv|15VR_\Ƣ6PAٶ~Q_58+dp'JEV{91VҾkv|`n[v%50BR?x:*Hgc%Ԕ)5ݶؓӑbg JkI:=c}dZnnM7`z"ۖ={kUm<{Oy֧$Gv_7VRU;kE!W 7$&y {޹OiPءA,O;ϒ|-)yΚ6w! >vV2ou-Lz9\N/`3Wa-[puaǡnSV!j"ORt|##D"#`q}L+QhB~%!wQ^ui%~}s58*XN.*O{?EpWJ N_cb@ GNr[*6Z!V,|P²^)OѦd#qRؖ,IQ`C8V@Q+e/?L)+wp5}9 >&Yk!Oާe[b&T+8A5?MZņ>zt{ ,T`jowP !8 Zp |Ԧwܣ".+ E5j:N)Rp\JW i+wpM*kVkby}!I /K5@p8,k۔l;?oqJёc)l]u5BL5[mJ6\M> }[`C8֥8sR`UD%zKn+ wp%QX(% ڢa٨+(*KnSVj%^8h+`*P G$,(Te͋nd<WmJ6ofr8m9܊xsF h(r%gZqq3Ѭc0fi)+wp5}g ǥ0Ftplҹu:tFx]mjz\g4`iB@"KteE^wlp̤By+JJskmjz\ nBR4$[.0a{P\xb GY6U짒W pWѿQh:&j"@N娶8!ۜL(F"FD1gY^w)wp=PT-ս}D9mEz(*i)aZr|6e5=_XG g[R s<BD+MgB+9H*b #dוC)wpl DDjT0;]۷Y4Z rrBLe_\˛6e%N~uu|?btc@Ԥ%)!  lECfL+E_띾)A oo08y#;(Ft[Ga D6.ǧH#ڔl;>%}~GQ(~@(\a)uWMYFn;Kzx'Qa!\cw)۾kf  'A"\SpmV"g\;;!kX.<BlvyhVNΖ+jEzmٓi.ܿIJ/lK(@f{eXaSk1&*kvKؓސH-MY" I4}FOvH,k/R[?Ŀf۶'oVk%t-4niGaǘ Jm<ۯ<4dby}SEi7SbxZ& !95%_"*c0ƌf :c;|<,mN^ƞ=u`aY\(5H7lHO:SI'мj+ߗl[d {#po7 LtUz?GeǩMIRsq^ f}LrնuyNy{d(b[ K"'.텄(Ҏcm6Gw&te۲'o瑐\4xh0̹6c#Xb{}ȇHlJWͿ^,d[b}7}gqlv"n%䅨¹Q0FfÎRo_4qȀ<ɾNnd ub }aTHe.J}f 5XnóKtn[vwƃhG뇠9bXK9tK }Sr Ke/aO{V~mJ)}`uL&֐(`يq}+pXqXם\60ྸ{LeB`rM!mŶR(TL)ġv6iNܱ *ol9xpdf;C']lq/k(PWM[IOwJ>o/7_J@+*؎J*{%ͅU/blH xb#L8vnMIMjPm)Df۲'o &`w,< tJx(Z)s[M]rm;y {+O.KR+JbCYZ(47ؔb K0{wm.^žݏ-n7Dd\؎~Ͻ%?ӥm;Zy5zXp]mn^~~k(+9k*˸z½`gk+α5Le)>E۶'oPŲ/Sݽwj-ph_bSݗD-<#yJkveb>>"͢6Fñ0Ӓ# vTc}; >ɞO=I~\AM>Gtm}@DvnM Tc5n;%{/F|T,ܘGaHPFRvKAAs{#ž)km.^~뷱"U.48;lb4x^yuE RxJY(6/ìȄe/bx~@ְxO"1#;"%qȶXIy\jj,ۖ]=y2Y>Ŭ>Ky˴TSc%ѷIAc{J(}A͔/^Xv{ FY v!ZIF)m]+q4׽}$mٓu{__2r2Xcܳ~vvB/*kK5cd[O\=v۲'Re"@DLn .lK ) 鯽n '&M]h]L7ﵳն%{_;,M~8b{wŜ} Wc-hkX2X<{V -x {22E x*ǵ1dniRM,skɱږ]=y˿kA/{$}-k_KdJ+~k<2Ͼzn[vwC܎5x™qo@%mR݉а3Ssi7/bxZu-r'}-밗g2r츯ҷݼ⽯ekf[|33}-*9y-89XK_y-,}\Kˣ6ES{J j>g[O8%XYO,x-bKi7/bx2ĝ𷎰{H7HŒ3Ny+HW^*p۲'Sp5Qi:IjglJ- km.^ž>}A%7g,ֶ J:XI^p۲'o_ˍ9-HӸ3k6SxXv{'FĦT}-~bQV+}g٭l7}-(\?5ܪp&8QY_ҎaSZ{cfk,\o2Y")LE -T@WKdǶ#?S6^|on3%{uQ3:ߪʵ-.4~"; %VRݑԾ9dn[dZo ꎲ-90{@$`zxJ*9ٚ6*|Cʙ8bZow2*LD$E /Hɨ{(}=XJ,wjdZow2*̬a# ;/D@m(/i,&k^ݶ5y9cwo ?(XX;9փҾX&XIc况aF- M ۖLcJunΚl8+y!WCxImǑOj ǽۦݼ3ۣ4Kjx^)&Be)\/ܢ*(>k؂ ]@ۖ]wka5ʶk)gF.}{g;w='~vDϷaEcmd; 7B.pOw&ż76~_KsՍwͱNx]7;$&k3sƧ"ۣdv؎xb%5aM-Aݶؓ˾h(ҳۣk붳tƮ %1^3Y8ۖ]=y}.boy&$LےeǪ\bS·I b 2Ⱦcoٶ ؓ.yqduɎ(3YA9eMkhK_M{d v.yF7Xv0{C`_WCJɿKvk}j*V̥s65E7o_ 3YUp$fᶂ/E:"m;+۬.R`%Ќږ]=y]겟SŝK]{g#rmZsΚh7( n8~|Smŋ/޻TbN% Kb[ˊQzOkWK\TwAhk6[}m͔/;h̹9lj!B%4'܄Jڙ[Svږ=ocbn԰| ёTnw>e}bSqVx֍H^,)+wpݟǘeVdByCV@g* EgU,aY!mJ6\}˓z+P-DA?|Kʢ=IXYbP&[фqȻQF.ֱuMYF;U=(i8Pi`+h(8$p/y۔l;C"tDQ@C7Vm%xJ-+_"0a}wp5K}gba2<~+'ޏ_A[2B n^kuW)OpW_M/rFX}Y"ehPKqEpC~J=pWyu+L[gA(pKhy }̣$q],mJ6 >2Y ]ٶ1Aߊv%qzME6e5v}suu a?[ÉFFJ:/UM zewBǭ+/VaOq>q`ԱOudӕ=dcV¾#q(ny۔j~PUXBPFOYYO.^gj֤7J K9ơsp23 8b+ 'fX /7݉^q q'W}DYwq)1$sGsG1EM^ ZM[IOxY!s(KNs ?+.3Bܳ$\uyUp=Bّ+S&(vcjez(y5ǶcXIWLlMFyn<&kFڏ+*=v 'ﬢc$0 =f i훒S|)d/aOQ&v#PS,xG騇7"t~O~ǡ\ՖVzŋ/]#qsjލu:v}Ԩ5ҝ5X 2sT.}նEoO C}5 W- )F QIXҎJX@Hqlv"x+| բ lʫ~׮Ֆf97V}XiaW>OJjnuԁJ-ǍAxY$*Hk8vjMA0c^Lm.^~ֵ߯Vprٻ%HdcȬƻk+f/Q蹱;%$26e5=\,94b! {PX8\A£ddGXJEmܘ7%"e}3,}k Mᯑkq!iY}-DQrsעH-f/ޞa 7iޞbHXYTQ}ba<=58 y=nv"$GY8N4I[T~b'쐼ℕ2n r8ʾ)ٶ%GTԍr Y c͐0#0$ͦZNAĢl.s۴_=lY[R0tœQHұƢZȚ1mumK/]8|VXJ1vy{VڣJi .tC0OnPi/aO;8X4FĢ ,SsꨨU΢9ZKHD|fe/axc>ߚ8 ڻ]'& }X2;EhMe8[rIm.^žlu\{>c,Nolug}lXKs?c ru̾^_R۲'ݏ}-`{Hs^([Eeggc-}]4W؁T}-^s۲'S`O{,(NPj q\Œ2Tv +i)Kj, tg-{2使(y-< ۼ $i ' ;3XIWF緦^߷vK|?o*/ $Va"a$-x {3v{ 3++a *N{EpGXK5'kl6Em,7!bѠL;êR-īObY(۶]L=yϹ}CkaTO*NMWn CƢhmكmKؓк}i47J-.V %FG)Iۚ37}9ڶ]L=ypxoknJ& %CO!Z)֌\ce{E7C"lEƣR(ymG2)9&ˣ;-x {A.kaRl- s/Zj>lRs]-{2]yޡ}iJaV˭kv1JKQS~cdkm9fr/,5Y,os],DץsrhMob#kJߔvdwߚTlỘ;e6ZSs#6<ž%92%}2N,~ ØQ1oJ/{UR>}ؓ.%w-.%Ih`m{lPPDlv佷R,ŚyBC(jUE"ʖQr/mYI%l57ak-Fn[dzx{]e6 2g P.߻\,%; &6kCӘ),ǎǖn;%Xqh95ryi*pw_^QGXK%{ k.n;Rʹ 4N>qKuYr좷ӾM)+)L;k%n[vxd fcE>0q7%J7~z>5T^^[-ݒжEDWJ/|oF YmNm`XK=G%fR;r[{ۆږݼgn'm_,|A; *(mGĦ4i/l}Rmߗ%ۓqKitcb\dvێSl苌M1%hAi,"n{8=y{<ї'Zo̊^+Q>XJXI-όN͍Ƞ7%bJo^˼$d+>̋pL׍?yIX@r*ڴl;n1UZbi\|:y<74{ZgxX_5 0:<|vpWoi'=|؅/BT9#R5Y*p2 .2!H/-cjSV~EI+YR<8s-v l7lem&(\_Cn$X)wp3y|XI;!kJX]Mm7'{iXsjD%$l}j#HL;v$VJdbYž8-x {3OԠ^ڜ(ZYx`uIs#XJMݱ_a5cm/aO޾ƊHi|A b@Eh/,;N;։T2jc ΤI}_m\ ؓV,U̥1!Et`+~("򣱖J&A؁^Mhv" ϩ!!Ead0؎/M?XI˓b`lC1\mx {ރ+v}Mhl%>,yܻJ'{a%7ivbך}SH3ږLkD0sZW''3R$q7XETJxkpebK\R.^hʶe/aO{*:~*w`#}l,# "2gܶ*>fQ'S7T((seyxnk-pXK}/j-߹+ۖ=jʴyZ )5F` k8(;Ҽ>x@hVp2/>_ -RSȖ"i8 7%)L\U{- ppWO6T^͉;} C|"pcO$qjDҎ*MskSXP{_ۖ]=yZ&Kze<"TdHGن)%1:ĦPjp~S}.{Hmn^~ޡW&Yƃc5–N"J;2uMi4<؅jM#IMyۋ(-U- 0m}'Zʕحؔ;ڌQ Orp۲_=B{3DXy9{gTʻ(lJYSO,m.^ž}-Ǻg F˗ɳ$}vgg 6v$Ydmx {r8ET_q{L_Ӓg(.&{_rCS"o%}LvL1ZNzme\.xߋ9Lvgqk3 ƚjF0m泯-]ľF+#sWH?ٙnژWͤ|泖cԮgȟlMMآԇN뵶䶔ؗݯ^G>:{ٺ2&ذ(ktrdkjL/8Ȃ5.ѝNYrEXܟD'yPd[9lt'T}#>;a͹cYw:ϴڒ.aWgԸ ͣi@W*H'3Nn+j{v6?# &sN92v۟ ; m=ٌ{WVwMjiiRb*#Tn.TKK~Ksnz^pS%,$߷kON=_ϩ[kK~K7cܷM[W%Rg"g7MX8M,jm'r#}۟KcU3F('M->OLA7VTZr`'3!kK.]gjxw_a΃[8hS;'g<[Vƒn8{bo4;ȼtxo5^"zgp9-N[ԇNo{bCgs Eh"G>E--M}-329,ʡfQwaʱӧOY'DoqS\غ5kE%<5\ =}G{\phNPXNyG@.]~lr=+%Ĝ 'jb։EvKYPy&[-1(XQԝ{=dZ;rnR~ږRb_vZz]eh0l\f3yFaZĹv܌Zfֶ\ =cht$bN99W zNStr`E`7a{~K-V$*;T@{DQԇ<1p,KD}ᔗS*=yk[K]^ӟzk7zY^XSw \a/{mʧb- 9=M}>q'ARzS}Q4 g{EXpEw*KGߺϕsqEg|E(& VԙɩEc1"38kS>--϶=Ll1Ô׫ yN~s.xeu_n%]2^ؗݾT{#Lb-6yJ7ǔﵥ6TWAqV [w -v{\`Z+.ŹxjQ YR\b=8*`dH3^[r%j* ~̜C-}̃^?^1cq1[ID]k[.K9FeSµ_f, ө;dBy{&+(rD V-NN?&y?kKKn+D +ɩ&+;MKuS>)Vc s8k6(tֶ\ =?:S_ibpN^G/FvEޡ]E†J68 tc16[G^[r%j1#$s0(AvQ:b3Viǜr}S.]A>pe yCyܞ)G`Em'˱M}Xڞ/v{oCvp2YM:3cC;ѺwlD%lDf󘺏 ڒ.`Wyq9Y~i<3EԋVP(56Q4V# ˜ 9^[rEG~%Rr)օ"zE%&ާA`EmUO[ߡ3I9<)vr7drT䘒VMhʤ؎)G>XQ{Aerny{mc)ݾ8%؅ӼZo>zQ\^-Uqu`;c[7)_h\V|ss3֚X?L9b\SHugC|{>/^[ϋ"e>>W 9ḙ?77yH V͜e"A)gז\v ڽ4gM8'*H=){re ^>%4m;hty-Z;Mj\t(Cw¡N-*:KÁݭ+*Cw‘VX({󠚬-v{\~=#}"7/ɿlu:\0Ư]>pmS.]~K5r~-iJӎM써mP^XQD6 6cZX> 8H>9 Yx/XS 896 mn^rEn_ r1|Y[ڛ)|":`EG9|M{ZrY*jOl8sHMk̿ٺ\ygoa'զgpcqOT.cWy-6WNcȍ 4ZmD^)쎶M -]¾`eH*J Zi3mqԽR^]2`Ed5s1&Zk[.K}ka.G+amOc {⇩˽E^˻p FMu])]ľz{`lc<8w4&bq=RyH`M 3$@-oݾ/AF}CT\x֝c-?q64T<$ka90Ϻh>m9ew]o~jL}'[,J+}P>n?A?YDBO+k"|޷߾RՍ endstream endobj 520 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 511 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-071.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 521 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F3 522 0 R>> /ExtGState << >>/ColorSpace << /sRGB 523 0 R >>>> /Length 3109 /Filter /FlateDecode >> stream xZK&7MvѽMH# QVA0Su!.}e'oo￾߷\w k9}ھ۶ۗ`SX?[KwV~YԐ Y=̈ۯLO#O?Imy˖Qʈꏯޫ:zhܾTf e[^R>8>. z]VZ۫+}0{Uӹs+Cۙ#CGne/jVxanNi/yxVR~6)R0&msPDS!ړ,197Gbi+ݐ w_~}ذ)-_!>~2?'$#=,qiԊŐ3 *Α\ܐLɌ*a.س. VENՈ}?vrlKN5sfJE&hq+66̘-6|XBRŜm,I$w T3`H,9]UG,#2# I7uݤ@@"{<td|m"܆МѰ\r/{|0l4e1czՄ-AI1bbD#ԎX_ʃ'LRW9ˁm66W%Ǯ[]N:CV9<Klf7ܺ$I+TokiRhO/2,) ^2[\]`dlgXoS௕Ӱ3NqP4!j3m?,)vmr8: mPMߔ3.b׸_EK(ki l%X=O|7vmrUI`mܶ6}:璵ݵrlP[ZrZk,XRZ1*qM9"v*O+XAK ;tu@$ROB^q) ,Wb"۶SUMyDGE>XfNrZ|@ t[UI`5eX9#%vtյrmY[m'bPӺ}6Ndb'ۮMNV oϸR!ixD0v٧Rcδ`klrP' wo#R>~#w=KZs XRbkrNۤ\Bq97s-6o9c˲|]3TVAnlP=mL:rv rGkBϖ\`۵O&V/'ko#.>f.EZ9s)~^5]!י_`۵)vEX]kmPMߔ3.b׸=;FKGصrF7HzO8f-olP$j۶SЦ3.> > VNċ!U/.NFE1<`۵x66(צokܜ%t6-,}HzmE١Ք`I29V]z !g\Įq3ݠm4 nvAnve<)bg֔WM,)vmҖzm\}Sθ}\c[ ^&X_IїU+0kSt]Nm&giX{8޶rmrFJwX=k^3y{{))/SSolP#nӑ+]۶SQ;䌫OQ>䮕Sf6_j{5ϗX??}GEjvu| NalΏbon ֩:ϗ؊#ly3Rb׸[s'OuiJܓwnԼ'O{=7˱K~kr:0{!ZꈽfR׼rT<9b'e ʵcq3w4k!VON]^4SĒm&>bk7匋5nϥ%!~VNWCKXESeߐgۮM&dbmPߔ3.>f.]k Vw>xo)+{ %KGfrHX-`ږLߔ3.b׸c^`;9/αǎbCS)蔏SS:cxVom)v!gĮq31{J} oJNE)c ,S3 }wk>GYYU\+g.u?wːO֐ W;9+%M۠]q97s=^a'{MOrDpt&Iț `bɓ{H`_~r9#%vs RZ9MyO”;qrܷ&l69r oN9"v4/86F7(k[9Ēm&'X-m)v!g\Įq{.C =y=Au$ٜc)Aa߳-;fNZ^mRv!;/19MY: ,kRw%ۮMN_mVko#.>\!M;-o2?D>h~X4k͏WLQYLNj4|Sƃ6J4Gg1\o~(?  endstream endobj 525 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 529 0 obj << /Length 932 /Filter /FlateDecode >> stream xڽWMo@WXx5*TnHq҈$qJ YnM U+ooޛu/gUE2yhR%LFvYx3N丂X(a;z~}^)I.Ql,V'j']_@Eq!7š[F_0hƎUg(|yD0iӘ JpJye߰Y4_sny0s_1:On*‰k.)8$ulkV;4bY/ Rp )7iOYEմ"e\2'r ޑsBGj Vu;>J=' boKҶBN#8@(uf."BD\#ᴖ6oyaq7{=`v 'Ҁ܀1QY)ᤁI*u0U"lnYaa:lǤ=֝`6NKj)>܊1{͵\vv+G#}+* >rz;Us|mwM+ˠ/1cs(/P .Y-̅ "M@]bV$Jh?O K&x1:? = "$qɽ{' PYn;*fyo03kwFhB\B=F +jf|Hqc(uN\<$ζzo!l´ߑVEuí7 ?Te5or7B#`QV>3.*lMLFv5s:x}lq6šN"T +2܌~1!~1}3b܁ r%>)-?!ݿ endstream endobj 526 0 obj << /Type /XObject /Subtype /Form /FormType 1 /PTEX.FileName (/tmp/RtmpsLZ4Ki/Rbuild373d6f047311/spatstat/vignettes/datasets-073.pdf) /PTEX.PageNumber 1 /PTEX.InfoDict 531 0 R /BBox [0 0 864 432] /Resources << /ProcSet [ /PDF /Text ] /Font << /F2 532 0 R/F3 533 0 R>> /ExtGState << >>/ColorSpace << /sRGB 534 0 R >>>> /Length 6708 /Filter /FlateDecode >> stream x\Mq_q"ǜO , #$F[]] 1BzY5${xwxǫMf߿Ͽُ?}/:^ZU֛_ඎw/ׯ2^_ׯq6^oǫSZ'm6{N߸ʫY17ע0!o~f=x~a#Gޥ^Qn[2'׷W9߭]E'R.<_7%}9^9wouήǭ\Mr\SIn44^7S@Q榟ЭnY+3v@] U'E,^nY-yh5k /oJuurB#vguʑ?sZL\!ĎbOA z؁p5sO]>t?Rm>^'jyQ#ʒ~hWhh왖fJc E~ C7h;qz9e I%hOr9.emRrw,SldżXGdrcnj^ǝ |^Kغ3v:rO]Yk1+0ML䚧i]"w24LɋQPu7Ԑi}/6s_| +O]"*K[)ۼbF@[AO]I7²Geʗ:psTGӏYd( tPWpYu;ZE3DB"B+j6WzrfE=U쑍rO]}fY|MkNnDh}% uOK45 M#c@q5sO],~lAQ_bmv#-X-}bմw]7f J~"w׭~ :XZ:V\?g GoÎ:+hsKnb5ڙ~ C7R042+6BG.V#Zf>O?^˙zXع.rw,KXtZ-.p41 |X$u5,=p(fn]rymBCzp{YL\[7"oFx#^RF-3T]+WJH%-<|yɫJK\mZ&;6*AKWpY6/,,}Z¢jB>\ݴt|5c7-fn]}w>w Yu5{Jr;6{WCM?us2nt>|?b11jB:_Ҟqq:`^3px$+oh .]|A |EX[=el7b:D5UmR#f}_榟ukf7TCcs;5vZl [!u7M,FR-M!*v.rw^ߔN_s[glK7mٖn6^O}i܈?٘n`0bdxse RQ04AUL .6+o{oU9=fhPvYDWbx q5- ;oH|*6*Y3R܇nmuo|AE y7]9x!NVr"t\&18@\F6,þ&=wmy c6\b0tKTsƳTY+7E[e0d<Gf|vbeB>WoE:I'M\{#؁P禟}fYNL}8}Ƥ5xDn`\,?ޑ5펥Ⰰ'tVY:zk_YlbБZ=twbD!DMT0-^c2vѤ#sO]Y}җ0>w˅ ]U{a(~l%hi7-'Zlr}Itd@qu䖟uk߾b5ub0[+o8#pBnq_?D+[WYNX wN(v:rO]e)xؠ,l~e?Kt.Y;ڥSn{#*> 7lh,@"\hE/^DKPOȳDIo!oCk}g(Wή\D[ҿbMܥk!n.vD3vfn]7φX)e.-X6 AL{%B츚^r637E[eiXy, kքV"!ai%jZs#c}SGY(W ]1YBxu+ĺ٣CQl%j۴QzILKM #ň̚ lя3u{r6&۾&(j?^\qr:-gJUeM?u~blū񔙯/Z%VY0CJnu=%gn],{YllQ]@{YݣY07h/Ee91g&iXL䶟q>/%oZ[ž'-?ufY.Wu T/D['/K_rY{-?VY /p}*|ߴG".QվeZ ι{N+5M?u~eۈoۇơ'К\{` K oōb妟u,(fCO˵|EG׉&R*K\F܆bS~"w/i;-Až@{}?ꃸDMiQ- O]Ʉ 3҂</3 ''%,Orʐs=#sO]UU3Ͳ_P`Ma }^9Oր5y%:sm&eKipYnXZ^I=cWj;';Sn}8bڐSTUSmSfȿL)D2ӎbJsʒ\OtkvXW޼=K36o/y;6oW-anlk1_JX8E/ξQujvQNzC yVOkoN-R uo'dÿtXT H &ǒ3vqM?u뎲\KmMZpbi%N{l<* qP\&-ɝ>ZS;~"wͲ'-Tz3jV)Xq 䳖{^%NWhOZ$y6$27܇GY8Wx8Th+U\RY.|"ʥJEPOC7biF΍ϴ`rר]Ͳ"} !_AW?8)Pn|f΍~ C7b|2}+ Z|(5_IGeo|v' >3vOSnj1R5fB [k7 W?q5-D6]P@O[1GY|؋r,4]3^$ C^/@q["VWNzC yVo_Vp4p02h8!.]`Y6q'ceVn]7bc:,؆VG :yt !6၉$cW}.rwϲQ7ϟeZ:3'wa^e?tVYzc8}s,?Q2CjigD-@~%:Mg;Ѱ*+sO]UzZ{Wpƿwa|q&i9}P%2v|%܇GY0[{YځOϑzh+KKIp>xI<-bO}/]}fY.T%~ࣿikLN!Pzk\<oFr]g{`SnyLci9$Ó&΂8GӂJ.~}(cw-eKWpY?sKY~ƞ%NUGDķ+*&(?7OK-337EY{5('ʏh/U@{/e6'?U@{YRrw* 3Cs-u E*eq&i)f$`>4SnbѺ2 YqäUR@Ny}x2;|<&Io!oU E!񍺸DIJ$Dz26VSn7-.|+еFw=X0H.Qp̙Ց[~"w׭`ƿjWi~gu E_Xehh4͇Qi.rw*K|Su)D`g]i~ݥ4>#!ݥ݂e(ݥ(7Ee3@6LjKZ0.={|6!6"XjO|\ĞNQr)w+ݏ7}\HK G%*С,@$n^me}fYn,,wx}ٿBn>W|H.Q@Zŭxkj sO]Ymm|nBCQ.f 6(bմ伸_}؁-Q[?.QeZ#~p9j8=XӏI.QA,Cq Z&.9Qn]ʂrڟ -}mNx#Ds%-=斟JͲ\ s&KhoQ|(E,?&%*}s{q}J=3v:rO];fnj,T_T{/K[ mŤkU;PĎSneiOr) Rk_/I_U.BSFi9f|~N-0܇ngI2-pUW.3/>(ʴN.Œ}e榟u,g̔b6ժWjꆷ(#2Dpv\Qxrjk&7G endstream endobj 536 0 obj << /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> stream xwTSϽ7PkhRH H.*1 J"6DTpDQ2(C"QDqpId߼y͛~kg}ֺLX Xňg` lpBF|،l *?Y"1P\8=W%Oɘ4M0J"Y2Vs,[|e92<se'9`2&ctI@o|N6(.sSdl-c(2-yH_/XZ.$&\SM07#1ؙYrfYym";8980m-m(]v^DW~ emi]P`/u}q|^R,g+\Kk)/C_|Rax8t1C^7nfzDp 柇u$/ED˦L L[B@ٹЖX!@~(* {d+} G͋љς}WL$cGD2QZ4 E@@A(q`1D `'u46ptc48.`R0) @Rt CXCP%CBH@Rf[(t CQhz#0 Zl`O828.p|O×X ?:0FBx$ !i@ڐH[EE1PL ⢖V6QP>U(j MFkt,:.FW8c1L&ӎ9ƌaX: rbl1 {{{;}#tp8_\8"Ey.,X%%Gщ1-9ҀKl.oo/O$&'=JvMޞxǥ{=Vs\x ‰N柜>ucKz=s/ol|ϝ?y ^d]ps~:;/;]7|WpQoH!ɻVsnYs}ҽ~4] =>=:`;cܱ'?e~!ańD#G&}'/?^xI֓?+\wx20;5\ӯ_etWf^Qs-mw3+?~O~ endstream endobj 537 0 obj << /Length 117 /Filter /FlateDecode >> stream x31ӳP0P02U06P06W05WH1*24͡Rɹ\N\ \@q.}O_T.}gB4PS,{h 0T0pzrr۵& endstream endobj 541 0 obj << /Length 155 /Filter /FlateDecode >> stream x313R0P0U0S01CB.cI$r9yr\`W4K)YKE!P E ?0? J!DH" @ l%r38 H.WO@.E endstream endobj 557 0 obj << /Length1 2206 /Length2 15976 /Length3 0 /Length 17285 /Filter /FlateDecode >> stream xڌP[ a]kn%$8 wsޚ*}{սށTIA$io ea03123"PRY؀#F99[@ ty]66 '/ /33 x@7KS<#@@)fdin&4.DlAN&@;<dhP7x/..LL@[gF{'sAz@ rr*S#%@; xXWڙ2rE?r7FYhbbo3Yڀr.._@g@7 ́IeldliWLye ;S1{[[3_[:L޷ݓ韓wYڙU+HF?&"?2s r鿷ϗI^V]4?W'*jfd0r0Xs?o7J@2vf}ߦ? @o_ ] Pir=ff?,[%://oMt[MG {Ӻ_SM?C+jocu2.13&Z:KZzL,]L,͘HKteb~q87*v& +'Dx?wxO)01ٻ/ 0wB<99L"!N0!n$XLR$L2$ޣC{t?]K(\{.*=?z_yu?z3y?%sf2g l"?^Ϳ_Ot]/wY l/W`/3w~?\iW_d{wj>y8 9͝o? #q>HL.R}I0W5x +׌:9C7"2AX7 鼯!tg؝̠a^rr}DMV$umu[Fx6=Y0QevaqgxHaAMϋF5dx,gGWnB{A)ʕ]_9?!>W~gU ,AY` ƅFl"q,[kOj5V^| |p +FE[G{9#jV$!Mh1.fni~\ va<ki,j5L%6:[#cݭnx(זUmc*BќؑcWJgbw\5N:@E?m }r,">oJ$ +U=E7oBY1ރ=GMn.imW9bR}ETpC䟹z#[pJ\kas{E% OZӬAs;6kd|7Y@t7S|W ' N>}و#*1\3'̌c\R>ke}l;\[hO {1َ= -8!! V'VO/2ͼYW6|U;_o#8Obi+R,v;كtPT@Qx2*ٖԴ|=3?vpvlMfXXi)Kn,dbC~![}sFO}9lw`72J6+zNUDP̑<\Osg֏ұ?Їn^{\gr~o>FT:vayk_MXG Qfn^{.g|tqΠpFeCSzɇ;m~pbc1ś5awa8n{Ta j2%^rS3Zh`ȷӚٸB~ ! 饩!5/o'7sLۻ`3{'ppYED[l1yt2WpL.tw*7QO"ڑ 7*ɘimFB=yQV*dc߱ߊF6;4W <ҀT톷6kMx[ޡg(3© 5#\m{`>G YtϙGr(OefuCkׄXOBx/1ˡC6꽌"\$'j㰶+uL IzY$iM#We0EΈ{[(GGRI/iZ-a.1Y*iԾB2 %Z4;f;`O?\{p,`ŨChũ^Z:!MJREZSq?Ɛ L XDj ~3($ u3df4.NS^k#9TBvs{Fx C(y|Q GF7p൓K߫D^VTtVy `2bD,&q_9Ikʩ-h_i^RÜIBaU+(琡C}ȧ{>l"ٔVud<{&{"\ݲ=TXarb"/S`X[{܏yOu2hDߨHC$V:B~5  ,(@ε{GU)=Me>7~?Z~Uz~dknt5@͉߭: BO-wy]!IW n)gHVwT~q9ξͱӉJd:jj̓ϏJ#eB;z30m=H ķا*?i]sTM%?G#Xj [)v\bwе|rO*ز:`zFQAؒ`b%JQ:kKUp}gzO(Xz{9E2fėgګnNmYZm뭩6?x4b#=p"d5"L0DNInBdon;a.ֵ#FڊĞ5KeF>Q44"}su+PUR' g6C~w"Xsۘ }Q)(GN/;nscpҙ+ }(R$ EQѩV޽>$w(-w};Ǘ $IɺcY(GK(Fܜ<XqCQr=Dp1e"c|qDgAS T)%79ex)y-a)Ċ~={Hi.#,Z S" xT?\1$ԟ3V%%O rTdh`]P_sRbA;vZN E!gv:S%1 V✔* DO%n6 qw>@=Ki#:5!;|JXxSa)iz+!E0kS|9jm`|g;Q- m(JOManTjg|y'vIނii.}Z/R;Q5{.e&4/-ޱO*x;9yB"wY<9HWUduK뜛t fĎo6GfэJzޚ ߟC=:[6qZ S7Eש.~is~D 3ϨZpYY 5GK l0}ml`N盠2#:=Zj5AQp^xBU6ݮ O`B%eRl^-dn˩8CXh7<F>M+Ǽ4Qay0e5;m &n/EݪuwXHvC4Jj%Trx$ Nyȣ R`[Γ7sV걥3!%uwY/hξ˘liHR)#iʔ*o1 "5iqWUu\Mf"OHưaHuz$TM'vЌ8/ZN= ge$E7pT&+!W QœkR8>{2"% ^}'5>7i]Ga; \+e9/;gTV``"~D‹_cy=F;bc:Ű?Tj|߲Еl]x(R7`=?d[]qB (OGXYj}'Fl$"O3Q =n!`ciCm|J~7Obz2:%hOqN8;ˉZ#5l2gk%?e&4nk Sb.Ȃ?] Nw /Qʘ:}(h4_VFWZy~ ^Ctߒ"Hp(X#ḱ2dg !EpJүE- 8Q“q8j " $hþ6o?ѬѼGC`"K:j=f W ?$cȰɧ$7)˒! 8>6~wn'^B/FA<^}QWǸsE%%y81;H8xJ p6wSu/BB c YIׇ њhIxfi#ݧz#dk?3e^FDYfNѐGA7Rayr=JyI啌Š/vhbJDƓct;mfBq/K ZFwݒe=Qbmz*#L=ox~;&{Ib`ްfW;2h8F(g syqoQyGSLE?;my=5GR:a,dCE(zigK'AЏf hDU d]$rw{e 2T3 pI>xkK~Cר">_ÿc 1,F&>Xo 8:et =~s DV8db5R.IGyW MýWfؓ H2\7m5@^*|abP&,;fl0{1<=ٳ*_a{8d75CK ^EYV ]k 4ߥ"q#r1SME-J^`OXTE>hg-?'ak%Bn=| ^-͂o|Z/;b1fӆݜx^lްAR˓[1Mqa͟;J Q{Z% b$j8;f}U(r4=2fI 6lMX!KR@/Ŵͫ.<.P3zfď&"&"=271Jx}w8zhKNXФކ,Qxzo"3ꇯ3b|mND@<5D'AȞf~t)u !r8ێ{"_C #5651F(j^-^$QNR. }d?ƥ5Β(e*o>=᤬#aYZo[ R5T 4w[Д  Dfx`ʈ {U|'im~IDoh`lʶ}}0B NQBG5Ƹ%&Q)T+M{2}*sv5 e%ZX[fyA!z *KSŸ~"mW/v(Lt%?E~ڈfz̼ϻMN@h6BZ"60.ߙfpT"r54{]~[+ QJb;ʬAMBr/n`-6UX;*[(KʳǤYVuB#^Jpw$8+eVYܠJ=41 bIzr@"Ӡ'K64ܽ,{)T kJ I< Y nqR}a9y 8"R~eHOew lL{p%SBC' 3%z~Q&z54+vޱJpKy@[:9CP:3v@ fQFebz4ΣWDT?-᩺"MzTճ|_5s}KKNgK N-n['jOS䈇nxHPpŽ9 ~F" cswwg7-r{h?ol\F l:՜,_>Dp#Ug= iFk).{Np^ڵXY_eٳ>6E:R)JWqi8 c9Ձ+ja%}ɓ;~J\:@Ԣ6I;\wU fstaĘ~K9޼m*AFy7 G{7Ȋ7q{̷kmIQ-zO]v'gbAj]yżyD?bܫ-|?h+(~Xv8})|(lHؾ&d5l'/<55e\V$4HmkYtfʁT&%]h{|­@q`*Ls`¡K(%ƔϘ>u@侚8n) cTC!1EײrM3@+H8qBFl>FC-B'2zv`;'&(v(Z%k jkA;,=M=ZM o瀨yVş)aیR189 . 4j b4t/ OVrHhS  xM4P6D<9I >d${MoiTH)q}\z}-zxA>3sʬoz57'.uN3h>YW7zHKds"a_k?!>aDjW_ppa?)&n5lєyUYZ.CN_P)RY)45oQͰo}vE/k.¢723h$oo->b򈦣b .˺yΒtt ky٭4bjX0zHSIܳk%i214x.kXGƅ,[$Fgz(gzkbH%I+@ʏ0jfFHC " !1ae\^u ?oXV$5I'ҪLN$px+90q=Ygx`Mu@-_fAJGf [%NeQiOWVs/)Z4IEa[+(7K'~5˺G.sy/DC|k J4mAw G$ ˳7qD _$e[Ph{*IS e69Lhdz)_fqR PbtX|VH:jS脬OXΘ$b ^V)ʚf=IboIsN& q7Irp^L3zcv8v8#1aĺ" _^|}<%k~5 x"솺u! "iBևv0D bVJ?e{IKx-?piiT,V*,93gEsVo("U^(!~MI?)Hps9I5{Ң'!!FEs "NQrT[vCj/0WG[=Mð_ &ʹY٤(=PrWu[6)'(Wgq?; `WZ\&5$Ouaa"a)˔k{}ؘVpBq<Rfx'fWzFC L=i׊K)IPm)Ŝ^?Pt& qk T -ZA TFP|U]R&BX[s II^k]kxtR;l(T߈?DiB[,H=R76,421341Y kě*eXKE%Ԑ1x)Yחd;+ ûB @öNYp'gklGPub~ iKCӵ~da4K]= }pld 1%h44X0FM fCJWrEK8ݜ6:93@u_V}ٯ5ъ&]!b-4 Ɛ-3PU ( #yi_*,hn`XJ#1Gl0gFANaDRp\'#?Qk+lW5ȼ1llͤ`ި1 9~D t8^6]BeNiIg PfߟL*I-G# /aM%H: xs*y\4K1V+ |\q}ҐmLd%nk8pJ2~s#>*-w2.gD>jk[:Ɣ#yY'b´LC\HqN0GtEd:ٿ@}RgN imc^%;ӕڍ2&=֖#'=[=BV-,28Bjeq\ ~&Q*-I?%icHG}׭kŔSaC0kUձJmlN3Y=~?9^O6v/1.[\.;M/-̑б3J]ҥg3agU%| 6xXt&CNXX~WØ(KUfI{mkY$ !À57/8n1&<ɠJMAdr/T5%RQAJz{5g}6Q ƒH,U']Fꂐ4E y̾[}ZD*3 "EdPKD9?)eظYToA(nľ_*닗HGv-;Bj!DCٲشnh@¨M,>·N^ч_(dKV cNEN2M)ASUoq48;ido Oc JA 5.UM*gW‰,"_O!(:ljE ~ 軼9bU ⩵eKxw7nRH~7dCtHj}Eu> +dX$|RD.o*]V%[|yߺ}m.gL9r9 ?5s>VBT^C+ߖ¡+uY_b" X6{dX=)UR\~.; j0n\qCI¦C,h}/w#} |XAx^?mjy.ctpI HȐŻq\JT*=ĝ[d@pA#2]_qob{b <*28I s ;51!=o!zp'mG4W!j"-0WA4,P iݠ<*VS+{<L5ȳ'|~2l`c+:5ed(*qFɤc,^ 挲_U`Rߗ龋F{k+K.4 inZl@a_wtrTWHSo4&:ID:rKNMDrZ%$8 a总/z̲xhI Ax-\FoSưib 固![ڇnqH ]p|BS'- }Av_umIdfAf6x}!?g-Z0.?)tZM}5E<X,=ra$(S>*?͊|>iDv{ͮ>yC|k\/[C}JnDnxj%Qޔ2u+`|(@3=x/)k!ctFL;vBNhRIAv9e4 k$tjݸW]ayB+SނYooI6TIG?E8F'3u|hρH=j+:[x+=Uqq 0% JK̪mA.kЩ5 :5^h[L2s{M rIBh9}DOoK8}x.jN#QpO1fgEI||p5ΐqPs8,<-rӽ閭X鋹_5D+sZV ~E(ͤ.7R&J =\hReV/3LÖ܀!~_dzVm6䎨ȡVdZF$bԕ>hpZh8,BiC%F(TŬ4xilX #ϭB zEU@Zo+N@15|-е(p(›k#'ϺŢ>4qC|.sC)P?&X.j-&C'$Iв]ey:OJ-\K%iUF w%60Bds!y w0}9')g:BFL'32abTd ܱRՀ^뭀E|C~zoC$b8@&Bk7^2,,yd$CP=Xdpjˋ6HC i:5,HL~TƯ )6fYvsK*O:yWJPrEf<կ e r>.Pa[UxU2g)/*S6#q56W#HQ"L~&{C)B7ִ\t=̒Xq1$z0,%Z?\ )u4>!6HaPnp LAʉ(T5%|"q;\+n? __g99xn`i(`8W1Я$Vx\Д;՜0ZFIwHFzW40[DSYNU>n;*KM4+ԶK. Sװm^BtbFژ҈|Sx#͓h .bSU}p&/U6iqABiGlEQGR#qmD g[0w1O)i6u[Tzqwۢrbb!3CpVbBRȴMMLz3C~٩؄Q9o1e6wKNӯc)&б endstream endobj 559 0 obj << /Length1 1513 /Length2 7678 /Length3 0 /Length 8679 /Filter /FlateDecode >> stream xڍtT]6JHHwwww C H%ݥt HYs}}>ڇ^׀K (a.>n^q/Wpc2A0P\!@ҦD Zp@ 'EP0@A.ޮP;{rVOLLw8@ a- tAP_)X%qOOOn7N E!nWi6WoxLC{-  NP憌q!5M Y'q_@yCav[ɍBp0/" zN@$w@l@PW< Y V;;C`7_)B]! {u0'oh m5vw1AC$!MxA!^QA^~ ䷓م `l |݀Oǿ !6;( ?ّf)W@>+Kpo@Y㯞ý|.~!^@w] :~U/O9$l'ӆ# GB ,!?KRvwrM`P'?)H#G쿩&?X ;W Dﳄ)C `](df7'( wzb\|C! 膜8[!șw J0k@WW7H)䔂!^ ]-- x~~#QH x"@!?0+Dv@ ^4$PtQ.Gɵ1,yta5ѥ4n üF\'Smgi3ǾtUނg\tvt6oNS3L֡d$ӊvDʀ X*:f,%WaǹQ}aս]dgJ QBW?߲S~YGz>W WQ[&x#n*ȊO^; ;|.k/Wɼ_ Rw~,m Rwr,=nߍVfS~qPn^U<#dEoS'csMu*HAWP3qG +^݄OJt8!3sv4-KJ'Vu& )aG)cfJ|ŭFhܩ*U<EGwHqޤEh/Y}'!Y^sl{TʾQ$ "29GV2_osrԓg/---PM"D1fk&zv **E_ػj _$6 uPA"f'4*Gw)*Gu |5%< 3˔|6yc }\LY&؞z_tBmD U.S+uA-ّn_.$,iy`bZ_ה.OcMX ,_/QXM6^XWmОz$ޠÁQgMwB.#(_ޗʛe7=#  OG3bU_ʦ^| +$ Ӊom`v'-|J½2j>$[RO%-?+ z6y:6Xf`dnaj7yUKÐfy5nȒL]SD#kh5^Ns˅d؂{*gVjiWzÏa9Y2^gGx-O/?|B"#z3.o#Na'ūnܙAb^Vt[@AԏQIY'x qh!ATI08UoUJUQ E,'.Y~Д0p]4#9[.ypjf+e+l3*xIӕ}XE-<ꣂ.KZ r+$OditO{5U $qɼ ILuy=VȪ89>cuidYXJrh_D$Orx+ `+Q~6. 'r60 WuK9>:CiZ?ˎHH!&, ,20%xTI6#L)<ȓǸC LJP#VΔ"~JSd_ -RsXM85tY 0PZI-odH}'/sБh-whI!`@5woDbFPҫkKbzUfGAړvtsɱp@'}RWLˆGw'}ьۏo* s(ktǤjӏf !~#l4Ev3 |Em;9,r? C˷uGK<'gj/~=x8}TmGS lkJ5(?Íamf6A!i*(-}.aT J= ?la{RX ߛ*:CיHL+GhE=%"ґ~a`j2I!k4!z蒌d1LF{|ˣ3Wh gjuKН/}~.xYSpU:^ÊR Q[DȻ`|N4+0>s"BV|x63Mx6FIRy=^zDי- O&ٯ_#DŽe'hh5ocvbb$eE?:|~Q,sڪ]FzS^{@))Ed0*wN܇oCՙXa(lsnVfb:P0Rt{4r:xj i!K[q!;T7;OYǗ<_hd/ ړ*<k3SƪvQ viV9}FH:I\Dxrsi@͛Jl.3{|W^Z=?R([%*ϘfIίWR2] ehaU9l+\6Gft'Sp ozf%o{d$޾<(ʢ{pj-NAw6(<]ܚL@x_I[%JAפ2pc zT , |Ô/>M{a}&, ;[{aиvTlLk]i$ǩ~yK૤IZ^J idNNbLK1 6v]Mv"[;nd){ǒ{6sNav*cYiW5o& q҃qy:".F1m%$,"I⌢U617H^ fQL#qtyx6B'ԕ d ^S-$T56}O?,~O_|QԒۻkKIGrI ܐFKʌgt80M0a =^l06Qod +e794WQM;V*kS{[N +UűMtO $_$tݕ R%N::;(ӛffJiMZ7 έۦ#7ǯP' 1585HCϕ}3I8xE>mwiU~tyl4'X?3|j$~4M뵹k_yۋZq V͜Np:Yz9HCNwW? }$͸ lݾWy՛Uf;D1i7`bKgB :/ad;|R+MTsIW - 6N< pZ#1Jl}-,붣S<ܣ?SI=έYJ?݊]f+=X*<$4Aͥgv(NHcL֌y"r[D'h8MnBwLqseDdcW&ydҹטgU 4>;#Y+47|#`) 0PPBc=ܪX˻:^#YFyM(<ʯ ӟA m|VdsQ^5eŃu1eYQ̱ST]c _=BwTN[Fy@Wl-řzpq}Cxy^WA+w4#QNK6mXf;q} ϞZL|XtrNd|XAcHkodV+ERaLcDvSR0+bꀗpq^Oc#9Ȧ3&:+g }+h!WUqlo5 Lt"ˬ`ID~@X:=y|܈e}(L <$̔Y7lSz"E-F4ÖJ34)7Xt*y=tHVT~ U&"+49<{7ͮV˴ g3+T<82zC=Vr<NI`^8.Q] Ļw]JU -)ϋ<&?֩KQvRifArI7o; (8S ^B\:#u O]7LW_Tzm:RYia?LImqԴ=kbGet?=)gop*rؐhCY,%Z:q͵l6<|BZ!6g^lA! ٙ" Wo5_~zQ7_v#E1\L!;9gϢ+`9^ma"I{n}Uc짳OTO)I!ĸCR blCviww4Rx^Si=RC?'L5/2ex}N.u`?}eҾfx;_a7{eiizdpZJDX8Y1 U}ie9jOxz7P;wf$hggUtk7f1vӏ?\ݻo madzbpS.tí; K [p]8k ݀H@;"3B ÝDR<,a뜓a8@% l"wVD}) uV 5@YδAYCJtQz hfjZ01k)3ԟky>"/flcǦvqӛrdL1٢roH Ye󗋖(Ln\Q p0> stream xڍT 8T{4nʱ%۬ftɾ3)1slfa$Kn!JqS7KJۂtvI3hgynw(>&6tNa Lph==_XzTLJ9l7; =(@6*dx"7'-8@H#`:\9lֳpxppiXK3$\:`Âx0 d b!i `H]C.Ā,> 20"aACs| fĊ qX,-<|9/&fEB.vB. ą  P8h!Xq (.4ċ1\` @10B|0qKQY~Zd̽r}^DP T^@۵ԥgoNk][BN-z.|G>H).Sەa$Peh[lc Lnm|@> ַ*A)lPs@+6~fC}MF:z{rZG^wh/}Ooںm+pӔwt1fMì)OSfmCiWօvK;N&_Q[>cYHjMu֐SnRigpQ}[bOU_:U{+W58>zJ$qQI_:^U좕\Bk7a(&gӉF7nrYaVM[3:2lЧk.[0#w'jEi=Ueg VVIJIM,ϖg. ߀;kZuRs ELU:Ӆ?kMܣyc?ό^C>0ܙxmKC(ۘ)SUަ^lyfjD5ۀf79ʴP*ڙ ;]䆞xӦڻ70QƓ|O;rz4 i}!>#yIxOoշz*s?6bRۥucs%55TχLp[PW\u@:thtxG:ʶ(lN %摺0:N,Ev;C- e뻇=2l+JlZHiMʴ)^x92]U*eW9 ⟳rIٳkQ]P[>JzNǭ|0f U/8$֦Gv>Us"@OTˌo鏑7JgӶWP(pUbڨ}L/ նWW~o^htq\+SyJ&iάS]am:r#\.8>l~k*MC,5n]땠|A\EA6D>" 6wdlc)l$wܙYDr}[ >YͬRw{ku6inC%~(Dmr=숆Z6vPv /Nx.7 endstream endobj 563 0 obj << /Length1 2605 /Length2 22750 /Length3 0 /Length 24222 /Filter /FlateDecode >> stream xڌtk-6۶mٱ ۰il6hlsӞǸwd=3zzMA bh ttpc`ad)0Y((ԭ(4.֎M@6q7P@`eef23O /@utQ9:yX[Zj3 _{@ h:hf t5/'+ = tx (ne]̀ ws t8@MFt;Xz?0KO/"kML,v@<=W#(r T?幚X;2Z* b@7W_ĭ]f{3} ks_E;1i8X;e ~,nfff.62bE `*gmu5\܁~:XXfnSovh7]@4{,_~3IANKSD:z|ؙ _C_ed+`[-Mg9hRtM-@{9@,ϣW߄b $ng/mbomOhh@ Z{i+fZKh*i4Wv3{Zk2;k t5Z-3[У4fV`b dv@)Py~ G_7`eqD#.o `xL".fo`XLҿI7b0F -rHoҢ(F -J"nE7iQ@Z~#E7/|&"62{'ЂzF f"4cagek2@{, `W?@[ ? /hl3Y~~;q(]+o'+ 3l5Z?%;fq;w;zm:-~7Th_s= rgwG7;KŁ|. z6_?P@/¬_Mup]'ΘŎV2 KtMEzˍH`"ac 8wOF1;pX}y"{ a ԅw=; o|.K΍~#dinS(HilӌR(7BZ3/)Wb:8(|_u3>+ꬮ为8h#sE}^ęI (i֪U# m,Y `*>z #R%̊ft*6[ ~JˍfM"Ϗ﯀iDCN>ۏIMwC[~ZBB,VzKiI%no;2( O&!x,y̺ܐoFN8ޝ+=Sl[FD3z T|5mO:;õb0NH&MW *a:[/b/&?'gޙ+ e<,h‘B}0_0 scy훨!OG2P\amJ)R"o nfaMɎE=H룑F; ojeWb K3iʩ<^ٷkǼFBA^!St$×s '~V%y0 W<>C M'=ԐIV8"B%jp9ݬJSI2v?J:pwx0r#s>neGpS+Ǧd}Mm-@B6>V&ԓ+eF3<~fVF)TyJг5n<\Q_!-olQfv\8_ՋxۙDGmMQ᪫cNlG{~ALύ Vǒ5@ѳ0~$6o- |9L7m`*P(GށC“p⫔]U6s̓Cͬ)\lҺrTG^kcN^)B2$q!tOvZuw]+k6/<. zWܵ ;rxjymHIXRd`n_yXulm#"/9*N%iĴ"zo+r˪2l5qJ #r͔&yN_MDe07!իn_3) ͮi`9b^S4ZKoO IJ5.}ij*VV~kdT?xIr~<ĤDޘf(*vJVGP=p>e/UCC;Hc:;_<[#a lN6<5eI\QLQ>o,D%Qh tN|WJF`Tذ55[FCʕ[ӷps% :b)/.L* 'ymӦَβ3cGY I~L̰ v{7Mg‘|@q4$NܽQJ\sJ<"xe_(D-78|T9TS,"31ʽ;10ʼn ʎ9 .f*5wXӯx]bp=>"3lo/7WXDJ2DsYM=ny'@<+^踜\ slX`Nv DEb?OZXDziz_.NfI*tD r3["FР#V&Vb.Lv[ 6ai:BM_nt]5|ex|Ү7e(Ok-} [%|i%dckU9ҍrxeQW1>hu?X"!ݐPk%~|Us%H5wT }hTV`ػ$R 6t0^_% _dZL099$gcP' Ue O•*I֮-ڦv9:65Y2~y*ܴwŒL^5Aw 6Yv1 T7{DL8 Qn).3Sr99äMtEAFբ>C2?^ yL@=lԭ$w&.q 4׎$̷)ev?K`3mHN}ӃcIK96P)qdm}ue? *TGr+rm%V%1Ġ }. iuU!ߣ*jH*jb~(kN'Cbmd 4ssr-G&ޅlUCqJ-YFr(=73 :\Q`۔D!# V B,1bk2&8.z \&i߷kWq-MǺ (>h5\*km7* o߃$ƚ0T~.Uj<3{Kvc/ 9fG~vĄ]A2K{"[5Qxo C vS0DMA&{'E97Zw4K&҉e뺍SQ~={WEPID{720:;ESrf GDi #2jP,˩&T+=V%: ;\^M8 :R3|D<Qœ:`X!+kxpw1A6rP\1]0v'f+*mz(+S+/_h,&%}Ҍrdդ)_![bO `[U%l&e"$-[St_Hr M^f6, HQ,\'4njtzj (lFIN#_aG?E)T`LG]D%f%L|<\y.WjRZπ",O;G75 P.`dKs:6Klz7Qe=X"٩yʾR:ρH>s27:T7Ψ?Ir{@(v^&wH\Lp3s~Ob0qA_-fךW"M)gPRy K}A7t'kH>EƱ|ϖ!h7fCNP=l[-֜gUôg*~{F4Q.;'b8Ye?k *9ҠjX ݘ"_֣F6êXBv-J,y z*h -|*Rf!j^ߵ}:yzM' otԢ9j> N ᐡ =fII`8t+\,n0j\6`\R[|\oZwVD1>]_,; {QzD9_gȉ{,`1\b,Gۈ.ON#"|l] y`l4?ʽA^ȻZu);\?'3;""U \F$ E6q;1OR> k(sNV]K< hc1gU6M-BZV:F-jL^ZXl^#5ߍPR:+6A"ќT gycuz{ .#i/_6puSh#}k[> :HP-qT2xA1MJ+ƅԱCTCyjHHcAd_nh{c3 "ub9GjN|+XɞP8mIlsM)Yz=,WRuCbn7VȥD>nl@Դ}yaA~-+mP׹cMqٙwIMM~b.}"8osc IZnbԳ$oo R`;{ݧ9_Uz'2TL>]ؘ/Q4@3 e+htzT6Blfve܃s8eOH+RQ[W)t\HO^Mw Kb)Ciw0W4[kB[4J[E/1WKc9@L 9!^>JX5}sCnEg8[QWgTwTڱ5fQ8eSox5 0aMcœi,oK[,\+ H| F|O)?Dt]7!oX vOoquDdh"-{2n@]H_nLzx>EɌ}KaicDu~BZXg[kZrMB!f u@4l3 _qw.ϑdN`Ď0<.q>~jF[Xau'|EU[%Ǽg-%F2 ِf&]5NDl!혴(3{{x %D)I?$[0;z߈K8loӏ YaQ"fYg{yq[ #cg + ,2:Im 'L$'99;AZJďPic0STj'O~v5oOL1yrEUKJX Ӳ$[&,AߞE3 iD*^u:sV]aJ' >Jlo(@gcno֩|?3(5>iucЩؿFka&/^2ԉKtI;5µϒy/7)2o+KjQћ>}v/I獖tx9E ;^#6KB1~䛨XTC8^^3L2`iLMo^ >e64r_ʽ^A=)%2h/mئ`?mCrU=FhL~?S޷(L^T'7~>}.Vą?91׾xbOH#5;^*&˱]Gl6s`iVPAOTX\:-_ M⪻aNP($xv6l)Jomܰ87 'o'2Yq*K7q*is/? KU>$O4]K Fd鲴Y7WbB;v '"I3F|SJqަVfay!9R7^elذ.ޛRG6 :O4O!?dưf?WxR4(q\Sb[/-_/lNu%$UU@"XZf[%r\Ei-lY 뚎|{|iVUiTX wPq INߴ[5ߌt!1_LmjF{Y Clc|'&vt=U⽽quJ\&z:t]s$YW{R{$ӎFyYmc5S3H,/W0~!d!8Xc RuTҽ ᡧO(E=u3;n"!؉!7;"bbտ]҄m }9a2Blcf4e#rhB5 \TbF04'b~˷Ιs\.BPQ20J+\# ѮO6,Z3$ FTgO&=?<?ڛ[bᒿi:,ZlƄXldVSnh7]Q!d6_(?׬d\/_ [QoQQpFDak"0= zq$fZ)q&ۤ{"q|[a_uR9[iȏ0vH ^}M׆@('A8܅D&TKȦ3BskpJObyEO)taUd2FM &J}AߞH^d&djH%+XE/wlg,y[7N/vqve#:'`\-4ncX윥Mg_9i%Ao9M>mA;8R".ch$)*}w/4 @CR9IN߿WV7̒! j*|K~CA匪‹hxFZʉ'bGdHtEj }{S&"ί& Jg2CN|Bs #~>ATD )xdSFy3~H-!R$VW.)ގX˓0VmC}Mz>kr[Q& *(ja."YmIluS HƪyMREZaڔ}8<+óE_U ls!džX adZ79z #o=7:/|S>%Y`ߓ b&72[p~6q@#t2ފ_dA7R κs@c %z+@FTǎa1U4xv۴{"}!E8-Hn;ʯCɬ u$_ 6O6Դ0զ\2 mOX~*Eڻ-vjgonuܵ?v2b|$|2ɉ?bG|8RμUL 쇿t܂9TS11sh$Vq?4!&XW5^$OP:ש&tJg?o\bB@ c"m\7PzPvȺ hT{;ri$eoV)!6;"p!.Z#=݌LGZ/~WkTPp8Y\Y|h&1l@xr伄S{e9O14xg Q)e$̀ 1CfœhS>uV|ohwg 9nZMw1]7Tc⾻\9Im %N]2 \CB  zAUhACe!"в%ojɈ^\|2? Ov>ѳ.WfR` R@*.?e%s?s8y|7GB/r͆{-.@Ki˕?GpqXDgCZ筡 ;{&j,%7L$, fD4`hyE2!fMB|t9/b;\xA%n~OŚKth}$Q{}lF_ |Ú kNM/ܴX2nX}nk l$ 6Nغ-7pl:8oo_52 &;y҈-#Uϩ6Q!"R_R*ziu~ն&*lb|op2"nHMDWBx!8uq㽓8ת/zuک{z H6pUj_E[52p^⚬(UFĞv\t14`ұp,!~=2sYJHf_KV5@my9; $Y['pv+Bw/Yl&C'I0L="W@`KѠ.$D4F R~|ʏ%z)]F1QM T3'!R K(Z$Ca]D']q^Ϫ@J|4}욉x$B0SL,H5tԇĚ=|=KHhِ:*89/Q:( cFBJ2bekPK:K*?(,~+pF$hԣRJ?@"OG9Eq"qʚwCW#La~SMGi #.sz|a;0#4\Y} tT?./];^Z戫1YDy=҈df[r- ܃b#9 af{+jHɽ}- EѸc WZ3TLI3M&գ`vbT8caƠXߗ0A.oA Y!AqcXh欂#) gޏ 9\{`I2j99_"8cIA)JA+Z ϻ%#_ҩ3:g̱klP_3P v@B" Ǘ#m" ٧Sd%{b+q=guqL8@+=##i&VG޼FE^A_܇ןN8xitlK̈́ʪ.KVWhwp_]T `WnFQ&G6zʢD ܨm*1 d<-e Q^yS$|OD:cni&*'㥮A=(מY,b[sbsGSkxTnx/M4'垕|69)zͷ QS,V+ݣTU:ᢘ> WɋWtgR]-TBւk3gFzwj5!QkNh.jU\Q@|/}a&^ۨHꄜG9U05xXpm97.<8\DܰK[9g5W^/u#{[WUuy]#&J|j UF\;r\Y5gRVdO-;,ב咲-Sj` )>Sx?٠ c!M3(zT1 ĞYRɴY;k( wnR1ZQm4HΆAC-J}#߮[HŦO{;Og'+BhĠl* 6fg'g!1qC3 R\9\~6L`f2HObr儈BbA{2qvSdf2#i|t-)GxvcMzRMD(tP7CIʩI89?'a*=-M'iXFC{V}zθF9䮲BA(a$R$ʾN'v[Z%uMG \TLˁXG g&fMurоtQ3T* R Hcz25J b:c{HѱO韦fґXQZP#o ӫE{ۗ<ٲM>!߱/>m!v}ʮ.μ 3(gUDsﺕT2ѧ)J A&ov\w߻4 .APr]HP[ ӓ,1M`}ָ jv:n6FZXAGݤTFSu@=۠D`Vf4c[y6C }]5UE_.̧%)Jf[-)'xTѣE2Ɩ3> 5ȝa6&7q$;րx׉1Sz)UQHm P9Fh'# Kw9J{^$3DTgW26_^C~TmQ*?E}NQoAP|~0" Fgatc Ij)3Kj~*UON|Ҽ:7OOt1Brˏm)(Ն/!"uzG m*%Ko,u: :KRmϘ7޷Dfo_;OCT,ૂײa$L;bMr!%ס̆8ܣ~MZЏd}Xذ2YKI,$٨o_5xU5Լwmڒކ6b!u\7͸}D=ryƤOj#.% tVPSn)3-1<ݠ 9Y75FJ|r'xdZJduFmcq<4+랒]xΞjS܏,D(r&pЕ@jVؼ@7HLj;…69O<oƓ k+{ ÕÕ/\fܓD2W=a .\$GTT( !a$f8|RG9w3.L;B6b\d83K1%η>0(񥣀({wa-e<^l5"0_f4Š._s1v8 ]rpB֮eb0 j{y=df^178 ƭl?i&'y k6T}쪜\'68o?+eMNHNM t 6BCLqdฯz\Y֟\p8/RQ2*<'n`W`%Ҕ6@Tj; @{%gp\ӆcocZ4D{p_XuB")"YQBu3R9ts]ǰRZF\曨I߀Itgԓs&H 7qŸO7QSQ&8<ƿG-47OBp`i?ʋ#%"rԨ iIlS춘vm~b:Abt)sIg A# thF)04kQ)9 *.m-l遧/ Y 'ޥ?橷/y_i+$K⨧="7wjo5j $|m𚽞3\夾XL} +kf!`^'|@)ҢBsAd@P*zfi!u*Bm"_Ը@ }UW4X~hrֻw D4/ȸ7gXY3ުXϊ} A,CWlCD 1S W8_R,a H _!3D) 5Z!U͊37)x$u;p4i( ݎ kO+t GvT/`a$ ·^mr8_sGd[)b j%* 7b?f6p<|pYWo?O̢!nAl1W/߁0˹jV6uH #Ы~ H[;v_m(z19ڴEy#}W87ܟ/bG/#/|$$[gf%N⾜s:p[L.bizg #og1ZQƞ꧊@̇^#!kɖ|JHq FEQXb})mQ_2g!BC~XjkB*XuO||ƺPwV|:8>L<Ҧ 0x:u)xk#zQ5hO15ڹ/Ɓp5$j>HWE! *r~! 9qMڌ:U0b gEQ^N"c3ҡ OL5r֍a$VqV`vϩd$؈%`P"]qV2s]m$b{"Y$0*J۝6jY@kL\TQ%s*V;̥#vf<.Bm_{5/})HL1:_<㻥BZjwlcrL8`(B@݀HA!8)@21?8U|Q^ p`;?SE0Q͓o FX6VLgSKleU6M!stf#l&bgQpP|8")Sv( 8X,޹ˎ:]ݓ -= OFGOٶ-%}X><7DtF#M<^KFy7B,N?\`mUJ=׬DG a0\q5 /P7} J37ffksL,_\ \ BV7iM|SjGK|) bZd}#c[vZz s9G`C.R' E] 6nG39ӈ:ކG3},KHAW*Z4~k2e7B̞#ml_6hd`7Y/yM;6!/K$¯GF;RAV5/g8лv~:'7ŵ694Vg1ӵId$oG&ͬ>]<2 +wO"E%Cz.]wWFI/'ײ__kaniqmy| †SE,굔Ki? ,Ϗse*k E~BVn!pԉr͖ #D7Bqx739U\B0qو3XDUB n`{lyY%Zs"Bqzc}y,)[O\}bklDmav\[dX|^7lY t"0+`Kp|ډ*-4U{^@mE;b#q,DB'8\ɞ1M3Γ+q"j9ۇU;4 jD:Q]- -D lכ]L+:Y0TF8W>rS%~S}F mDڟ$y`LJx'e!8zg{HvĖ %s!{uCδ ?F-gy.b&ws`+CYT:5qw"yZ_LPG,;[>r < YF).FF/Sۼ* ϨV&~"8,#Mٺ/ tdބ]~Izayҽ+0 .n_1)6TyR~dS-Ɍ|[~G >rδۘEnb1f2{B9kp03iO"oӶ/(\" C.jC]put*၅ O{\IiNh~l}K%فCU{0}HH+&tZRf~@:MV?MMg#:L+ 8xa}ƈ 5Z5{ Mu,,]PMKFQ8p+A!p2CO%dFۏȹ[57`x1;=mƐ]3_M0^3.;}U}QU:mj C>>5JQ"h,m gcӢ~nAΌlFws!ky T}8t#*䝥2@1/8ʼrF6X\uMV=`st^yu$kv: W<[x%(x8a#4#z8 3ž)p|c_!Գ1#\\syevqꛖ1"Go_6E6m3Ayv\i25jiAdGs%Op|BW&R&I3d%\6"1n踹S1a) A};DX A4j OqJcEס<b$?zwNAU⋦, :ъlIR6$]~(͍ Hn@+LU)濣g 2\U[834ISG1#HZ(L9uoG .thb~5 Ы|C"b4$Z# 2Б8l0lw@=l+ڪjSiG8|I*Wݍe D g#Ty^$pw[/Q. U Ф.yy9 H*AЏǏ!K^Ͷd^kvgG6]HĚ[6л{=5YT)Hf'CcHi@Z-͐wwa7<}Σ*k`fF~$MDzy:>6F5}r rD]?jթ\">?4zeY cclI+d$fB #˩KІf^*oFW`3pPh'_o%#sӟ!q:*E*Xh󄊋:x>G3 /ETpe)@Y ;(Ln ql`Pol((`no$I&DzoeV;g^E&m0iYK!P}3R>6bXbH)z7>Dw -~r!9|{"/F ؊LأCғ7~n\'kfmJ/v%0WE o/ 6KwS_cfV<'N*1 qRkzae/*Yȁґ8-d >C!y_il6ru9ۗ2s| KqjetA|Y?%ذI`vK5$-Vz %6}<-MAsx oLnui(gA? cV" |rY\`FCBlF/ԲgNz9L%&¹u{Ṙ8qUtWMZ4'^C#Kb|L;r2 / g>G=,yQ}1Pk"\+opQʆ()uU58cl,:nr9O֘dn#қdX:huB7qf"aJ #X?H";L33Y^?6֦QŮ:lD-3TɃ3ܭUAT(핟hZqH(%gUrZA{)bUd@/? ULˏ d#XP0Ui>#+8?)]ָV"uQˆ}زy(J.DyF5p`R] 2CX M۾$=_}{q ʫ#r(  ȁ py+W.uzmfCtVІf[Q>`̂yk\r@D6Bp&SNȃa¶66Ea|Qw3kR+ s`H5kSA-ݟj%p *yFF=% j-v,uu*)KZw~Hlt*c>ܜ6sc3ZZiR\̢%o5:x*5zFC#aY >dFQ$50 -Ď2} kPA1τ])T f3P"KC[ښCt>\< Z">-qMwNijQ&.Ps]k.3Olx1P9~SSBDcSxgQEO E3юY~(Va8?Gϝpޞ5IC_(7<>xQF`KMoK OLNljŸt"d.8ås{;[/CL0^׶l'CTNpdJn2C=ϟ˛)[5?KLHUp2"7|QSmzn6:BszV]{*Qg<@_ŷU6DQZ_3ޠq0'BAEVܐoQsƭjYLҊ͓Vjm& "*P^M vU+zgj䋆@ֳhPW-u-b$X;0-4qq~FG _dn5'O-O9I6iܭz*)'3 /RqP$ƦbOFO);YYF=dW?6fM3naRڧ^2ɀ|d/Vulֻ͇ĞӥW 6$ gTrbsݲgullc_P&ܒGaLn}zsC;Fh p endstream endobj 565 0 obj << /Length1 1688 /Length2 9894 /Length3 0 /Length 10979 /Filter /FlateDecode >> stream xڍP\.%h[%h 4Ґ-w ' !ᑙ3sWWF]M,uad T49@ 7;ȅNG q%FÜ!PH '4N Ptpr88@(CG@`gt:)G'O)>LNAA~?`\lO-@-G B0ظ8 qpa֢Lw @ -vƎNж8)rrq'= u~pZa-ew@pYX8:85 b*x@P߆ {g'b22r@VBzj-`'gvg9~y:e>i ltN XAVtuЁB޸2y#x@ ^ _o'G'S`_ r\``_+sr,!.s5O'1O4|`|'^P{/˟txqظx9~^ UUjاSOn͟`w,U'҂p xf.-H5.OWq|Y% .=Z}gYRba'Y^2{ }8=m?T2P G` OtxyޜOh v˓ =_# DxE">?H!78dF\Co$#'˧k9,9DV!OR9A9 >U|/_)?)c =]O `¬pm}pm;ΗWSt;ziLl N{ldkkO[2W?[Q5&'tYqC᜿ܙU-f!s൏HTiC@ i/ر|&Y5XY!lj6lߴ~_pM310}5`ٞ"qkw |2]SSڶi w YׂdѴ3r[1Mw12kom?JT +DGkFs%^P WbʼnqPZKS>uZT^ /`c//6fd޽0Yֵ?t vMR=S51Dt@c ?|=~҂@,X7G[ ;(TܽZy8p܇XE L:C  z;~|1$­5IbU 7KLUyȖ;gs[lr}Z' 2giKTf ]nS}ƟVSVtyoHڵw|v%11!VzV,=լ N.j4JŸQ*jUnFWN%̞tTObię<}RE8h1m+v#Ldܱ|\1D~LbERrSt M62ˮ+-U/( |2{u -ƪK6d!q-5MQQ^wӹشPclv8mȢEB߫$TuN 6,OHG[ ̏kILU!C JJ%"x(|L#Ø@ ;`, S-d1}zwxrxҔB&br[yΜa`DXL;3-јj){Qlo&huQs}"U"akD"v5<QfwtXe)|Ƙ *#A;NؤAZ4Uq;/|fnD;j7\Cj Uͮ_p4(/席) w`X,ۏ8rLٸrL}GGo}Šy5Hf.qR+4QHWǨٍxTT0OKLc":v$ѡZy"4x?k F Uan>"|r .oCD7cHj/ݒGv}9+$j𞥤'dܯ_]0qt❝Tٌ+J g4t Ly22(8LU YҞ$)O4=r{iB,i:5123rQwsI- {_ WUa}U Ejͨ| E7C3уCUվ.zFԴ36(65詿YJc\5,>8n-6QZ sP: Wo=VNPi+#wZaHx^ c0PcYx~ʽypT(0>)(bޚ~x \ZbkI0ɬ&Ums|ޭKܔ nK'̌CJ\QEԜF],fr71}  ᜊLd5ISFb2N117xF5w>,P~U2ȫai5X}7y=:9S%PnC$y1zC;ũ{d~ H?_*\-@ADyvb=Nc?7\)iL9S}zK̄-į,;#pZxH@#.( VrZ#|Neڊq|Zz_g-N$$@1!E|x%/@ɗV bӶ. BQ ry9(p#M|HҰDX`׀_7մ vx*|A*˩v:ID8 [SE) EpU.V:SmMpz &mţv' }%Ş%ĔZJLg3\xTSⶆOCs_j>}>kZxa;vp1r!&qڑ4(ɑ {Kd !b*C%N𥥴׳w_{m!>j{2Zm^qC4M\֧|Kc4x=2Nl?kP3&vh|eD+AkWz&c}2~T=.$9 1#I i]E]4q/}?vw/hp 9hBDЊ?A~*̈́}HzD޺p(KX}%MzX;9 m(m[5% %Y&dԴb1-l('oSzڞ&Ox&F;P:gE5b0ȿ|CM>볋/H{ Ə_- saIAj详 .!yݑ(򂻯U\jDX=42;f ,!,vk'@SNG'AmDR)N ޭhpٳє;,j붏:nE?#sX^hy{Y*Lȧ)z=Ҹ<氺@Bwu۞и򕺔oò)+Bap\rBmT'Pê--l0֦WLplȟ[J6.]r Ļ%MQ)5{PKeIF~z"3GhᾔǀcWD5_I\U<-0ƪo{.kd?JGO99SXsq]P>_YN/*mj%оii}0@®cꮺNS.nǓ<* gC Zx?bE=C-1:H]+]:5w)P:pZ~Ls^TOh㖮VZA0'"QEcnl;*8w)Ř0@EIYmyF \rfc澅t2e>DkGPI}^Uhv4g!}f KFg".s  =k +YN8H$~_˘jʔ ӛ-:YJ ba j;5 @, ΅;5Wp}HPh/tj&c4y[4tq=(H"9z5g6/?StUa8o8!+'g_p:zee3. rFwPn\#v/Ij <Í Ir׺T"ȑrGP3$z&F*s K%[WxWo b7jvIpꭌb\b[wH:$P7EgsB6}?7o="]2!}͈Gr8kb^&tbFa,u0hl0܈4rTBlɛ38@tsЦ^ZmqR0 >a,~\h%Ŵ++'uŋl^\ oJP7 3Q7[iy_z^n|yfE^Y&̷rӟkZnXgر2`Mn/s3tiؠoO+JM-JeΥډ`ݮA4=Z%SeZFDy(2S8?ێ?h r'j>,\kMӽT"^%"^@WȂee~fݏ(͚k07گwSXFh@_ſȂv9%FCYH|(L-zuhа(z}rBzVv]5J|}O}'|KܨiA #ur/V17~^5n!w&Ņ AIeyOBT)p)Sn1F#r@~k0s[VJETC}!@DAA攷TbXZ,.˺6كًy@ڀ]{;.Lz ^"Rnm%V<%-EjLưN8c(1Tqh# }Bx2*Oiɽq/Ţdyb NM*'kU@irʭO{6DQ>J{_߱2*mM{Έ"gLH|74nHBd3{JH?)*a)UYijpUE3ұ_ct' g_7B9wl8P%fֺ?-apUB('w5Wf[l;8ȬG݂JOoj 򿜟d^he tFMwg䫮9-zb;cWS2јNR0 J# \WpYzMTR:.ȷ #_d4 jPJ'q޹zɒPA((1^zU1fq ݖw/"6=r+-ǙtG~T:"-/h'"=t/vp;KkƏ0@g28~~vfLu5ue+g?(}7l,QBDEsdVQW :x;`P9%'FdKǽ# OЙ// ph0B(3=NCrG4\P볆jq̐8e29 ]+}hIш'ꆝϜC^[YOC|T hMd/x5>l6 RkI.wNIg/4=;0^LscHm+%PDqX.ܢcĢYM,9eSw D&<]'KFmMޫ o|3o/{C=pERԌtLfza;3ʛwÇ˄:yĥl:Yr_*{O} ɪң 1Ӆ6[i Jrڣl6p}Y|LZo/ޥ7JbR7=Dcd$[E|J :#XE8On+wS0H< U }sg'd$qezspO, Ul,W!{LŨe^J8Wc rٛ XfAwFÔ8yXk8$Wlk7]"PS/lK,s{ ̾]#YĴXe(Jת}W'e[y6p*D(GƦYiS1]t8 o%SK2ba%X_saq2~byn'EMDSg䗲uTL__Ḙ'-Yg[d#qK?>xFRZBKԭׁSn74^@aK;={Qe3ȆϣSiQ[ >I;Xp AUmh:xjߟK$0̘HV ikRE7%']t(Zt3lന%75|'B˂ޥՖ\9 `?b<σw+œlBy*qׄ '6S|΀gS"pG->XJ_N!jՄ˿Zu.W,W82bZLhӥ,J tcO ִIIr C<rjƟmbL$SS$UfFIQT``c|5 hήe#jL̬lX00|>84FXsGVh$N_[մ̏a Fwlާ)֌O4aN!D~m $v8i-Jb[:dTlVolpJ}$<17Uxӫ>zW6Şؑ5ad%kB퉺,}nXnJ07jb#V*(Hr B$D|)K\<] Laɟ@V\jCAo)2Viw-(\'_΋{-ݳ#&$̲ dj_u4g58f{@cpQv4{]44 [Ν4K{tMGӧ6V+{X&4#9Y+=;z`Pg;.p/kC޽( 725 }#M_RQi~7T͋bP0>)d:}pO ̕ЕJL,|0; A1%V<īM;bzW&r'{en2pʍ~h#ѱz3hh̋ؠTi(LlbP;8M`l֊Kf?Wb "xHk%zYxx]:n3Z;Y,#gF\ɓZN"]!aqTɇBcKeRj$gؕ{|bʯ(y~Խ P}?8FfH3+|MϵuEK/'m[qtB1}>0# fu1E5n##7SڸphQt"ј0hBoɈk1/`pa~z{] 2i@ 2-L^d5a ;g`cF/euзS=臉q\k;M{Aet%m-GeWK2eT1`w+NGo{3zPE%/eEs*}Vfҳ!psJ=H7Sox_*_ JKPgXy'Ii\׉J,H'#_ *l9'd#rzEwh#=`ˀe;9 W4u7Cx&`+CsN7O"&=GTì {+yp Se8qc>r6[K/Dm?Ys`Y?3)`w.߬,Hl3v}{hh=H(FG>+}4[I ָN,iI \\g v|>d^}{R+A1oh1gHeujjQO\@J̐ṵ1iC{K<&א$5M0V&ChW?i*i~ue ȓ̩OoWۯ틆Dwp":y1M`δ_˜|,j6V?{= endstream endobj 567 0 obj << /Length1 1526 /Length2 7823 /Length3 0 /Length 8834 /Filter /FlateDecode >> stream xڍP-C`mp A !. !CGrνUT|{uWFC]j B`\iU-.''''7=یAruC! H,`O6 O (;x\\œnNN 5@0襡ޮ`[;2z0Y1$@`+ @frzZ ` , zzzrX8q@]mŘ`@ rY~7 Pp=@]jp `+)b r<-VT; U"׿;' lCl6`G@]NcX@-ݠO`G 'Ÿ-rn sp;n;.BNN  w}2`WӶ{:Y7Cm~7a ԅ]A2SLق`>NNN!>N m~ yj=`Yx0Ww?0`+d `'d~:|WI{\ߟ?< qU uTY>))  ;*8*iUl0;I 4YB;M[7mvYwؓUOS_>诙UYݝ׫xI㿷&YkaVv/!sC@P7[?ɲrx9ܞz^Rb=a| WW o '!q|FG  { <b>Q~AP-~A? |8Dv]b@?Sn4/n d8 m$dOcfYtmwAMf ^sL܃%t!D}S=jD;_wf ZS;_&&~JSSH|w r@ߩD.Q@x'U_u4|~G[2]4{n쫠Y|9RZ;%  A#R+~{u77sWuݺȌH)/F|vSH|J>5sp+eGa|Qa2 WFٿ\f| CA;~-&]M?Pޫ[I z@i8l=ٱ)3T" &a=ҷ~l^_;m d\{ q4fē j tdvK31C;mk%#q ~y;/kB}Ƌ)o#$Xj+?[l}l {OuV QJÖo%צtoDg3pcC=]{E*;Jn\o#`~Gl N *ǰ 9->-KP.wWKZ^;f3Pl>/1C%S␵??9]ɶ-kpKV;>=˯'5MOl=Y 86q:MFe'qQ-٬y1Jb-s+Eсwz:8fF%+ t˶EϖX9EeKY5R mEYWn=۲ 5gYÀL8n/LD_ڡv+-YoםH4.VK"sJcKx'TS&@0>uY14IwK9v.v\Gf-.i+@9P#'TKQR;d3޲Eku{Jxoƭ*O @;:Xz(U i응Y:9Z^t<vɕG,& 5:Gtӆ]mD_jd'5x377`EwvOCu XNJvZZ0m\[U,Nh7/ѣ:z64 E_вG!4;Rs fgT5c<wø,=R 7AFN_f.E`Qhl#W eԛLonYzsQ׹1 7r# |81$2hsP-k V$wX/ 7E tl4^/YP-#"`Z2Rf'GE jJÊs,7 /A)!35hN'Hk _);벙i>ϰRlEB)2J'\dB \|Vr 1ke&="[iZ lcv-Yzpy+/j5\]wlr'އ/egn_ s]f0ԑ$OwZ/)$5{`y1MTR$uwȼe߁r7`DO }[Wh%Nih<}c#2~ l"OL}iӂ ni;NsЭ0j F$'p$rnmjrnX.O5LZ)4,EpXARq}tߒxkP]-t" ~j) \VdV[']eb `Z^}6Kq1/vS-dEJ`;`F#ULa{-kIIVH(hb}sZ B2å[UjZ. ."#+) M|.ko]Vg-YbgS8U1uH-_ ۶B%y uEQtzjMӲSIJlg3n+@61(j" H(GLNt}Ť*BeC<ׂE"?2rz?n ;ơ؛Px4b^9u#?/D=|bf->~q%-v>?waNV%"\gSܛ@F}9g UxLsf76v$ ZVxçu5 &Yʘk/T6v/|0t܇m,KFck4s$ ^UK;& h~bsTՋÈ"cZhO%r;Ycmvh"[/|䈗@^N@ p'IۀS\:Cq}JQژ{WYŝLKv'Y}:]:xJ-BJQR'.CYӼ mȆXs\h4\5ZO0/Vl3Q?gY!c'tȘv-^/ug2C UgW#L}rpJȑF%enɐP79+Vu[r%Gviwǵ>A&IcBC*e/8C,Z h;9KSӨUi]HOӲ$^L}Ix0 {A$Y3`Xkk >.S~CZdv^+x] șs:,z$Qݶ@~)=c (Whh89+wɈoG׃ ʥ'A8}o&/VDMk4x\G Do(}_S꿤^OFWMe!!O}>vDK}"=e&g+" GfR~+4~"ZORaVS(3Ҙ+5Wg`XrFI:z6?_nr 7?J`DCAr}T6?M!hb,;;z':;LMjz鐅g71g7^n> XxfڗNE$,w'1:Ś 덅5-CieFq]*ھbQ!i<9\'P&a1ęBiμ7EvkueLp.~)[^f 짝'L 0Q58CFgtDL r\)hVmQ=-m5Rܹ^OA* ~a {KޞJ]:EzsS'ECC޲% h k!}33JbVoq!'FXg^*MNJ'(J#g %93,rԦh_-rĒv|J g"|v9,ײ1>ѕX#VyO+4孵֯_X^3tb <0&%zi 7I\s/X$)<V>VZopGOM+i)w̲ak=6yP1ά-3Vg6Qqgh[562 l5AeOXE*Ge‰"!10ק.D㗳?_A?7<,&uVo&{z‡Vn H󄌉"|hE?GlrPUlP@ ryF^Uxa)P+xR}E\#;S"lRKTT?AMߛZmΔJİTSRq"`U)y~AQ]T> stream xڌeT\;wi݃6w N hp !XpΕ7̏YVw?OծP3;YX ,v&6JJ k7; с/qH&a2UttȹX\||,,6:$L<L9G+(hh r]L&nV@{PF3;5BX913{zz2ػ29X 2<ݬj@Wl=(V֮V;Zy `teN@+ۀXX ߁lbfhdm` ܼ& M\A&&v& 7HL@5BW3k'7W&WkU2j=7? kla`nsw'fMkgw@"?2Kt@g̊w o'࿔Š:}R@[`nm0ZZ; -ASbg !+93wtcfVёRbb^_F6#;;@*&!򗫬#|A/g 𿱔A wN3װc/')w;YeabomAT-V[_ h-D,Ao\_coﵳv8Zj,,G53[u U߬fw `b*6NN/+h9́^g3`h8̢EF\f?,%A,f?,e PL?S0+x@1U 6pAYՠiA| ^P?3;f} Hjbe0u11-sGǙb[#?8A@_ oֿg]vPvv&.YXY')o;hzoDՎX[~06qS cVNV@,@2 _tZAPs0uуZinF?8A@?@ΎUG z:ϩrGg ASe8@rs-͂)Z47PXAҿ ֟ Ʈ@{6@ zC W;Wݬ\>z7Oǿ@1 y* o (_g?@|.N?מ nzBw^@3EG30ưzQOƽI.7wx;]&/JE7Og] |fzMS3:>3́S!5x)Kxďsr^RT,è ֓ss2*ExwA "eT# ?BRS-cDfONT,g-{:o0cQ'JAMaW!0Bb {kW{d 5t2ҕPF5!OF{N`01~ɉy"iV{';L/ +qnj,5̉y!`*7 MCkUAy5yeR0~\᠅ѽ;a_(Lz\09L|PALb"?ߒU)ܤbI"Rn%'qجtz$ƗɋxeχWQ=(ĸx6-g>Yݗ'W/?zRpBV}Һ=$P^lHֲञC ߷&ѰSLI7yd{ݮeRɒ8^RzWym1Uju'kY$E0UˊBi1,wkhfs%z UxWSC~ ޙdu~s.삏m](Vs\Dc&;,6Fx-B_Db( T#98;Ųp?*DOc1,~ 'F\$>`!Zz }>S/{%*d>=f__̺A˨T03AHR1;:|aHn)j ۣoAptYbV9} YaT P2/_fg ltYӧFs]NX%S&CM^/ju _Ї$7:daeRp_g'|Iy7+]DOn^µYꦌ`-[)&Òd0vr{B޵ڑ+RB?}gtWcwE:hA,֣ rcȗ㴹rޗ)B+&qQ qS*Q{a؛! 6`ߝ}>G3o5o2b5uYbxz~vA4$S}h^ڊ-ܔUÿ)~ԑqoyRҚǮxRودM-|]#~)Vض HjXa"_E JUeqDMr}0Z-_+NU~FhӾw5Ĺ!Mҩ;wEɸ y7Üަ׋DQTNF#ʐ)lDPp $Jl56"*qٴP\-e3iZF.iz_7oB0qd`vtpfƳc I2e%:d#?b2 3ow W@r*q 5[5٠7bo k}A!Nuq; j:Ĵnd]2v/Շ-{1/`7\bt*M>nv<dT5dEb`se֨~h8y#[]$u*J z0qv.A;6NDÑ9_;5,`u uogqZoBuPzC]7# z7O0'JtheNӃV8eڡ|/θ`gVIX3c * f7J&lc @̘P=Xjb69|"pa2]<}Hk_n&֢?֪B}]@ ~5|%uǔk6ǎ{w땩ú6Lnݟ{)@B-+ ,6IK]8_Ulۗs;<3h9`ܓWBՌ^[;w0 k^s)J L'FA.RQBfȤ(c8v},t=r3l`M"zފ;0]eJr uVi҄QvϪgV!]qhR6{!ר|>~'G-5ӹuTyL, w{˾n̰_Y !DiC'/C!Ǎ ֌Tdἠ|%dͥړr^Z=r3%řFQlC0jm;|$ln9BJ-Tu1::\…K3s4ɡ&yۛEczu_FrػgIbrpU~M8rO Q>}mQS|z`Woɣv}V#rzܗ>Rwy :HWm<y67gѝo^g%i!tߜ޹cUS L"ay": Z1\^+ >gk҉Q()} }Ƥi_ aD\R>[:;GjP0see5MP!Xo/CW\vՖ;;ȳTʓ0G?~C1r-0v\ {JTVn_QRQRcNTXtlJeX{A/:沭7/Y;(`YW\I5{4q.- (hq#6lysg"9%ʓ3{XG'RT@k)pkpu2&WJsa0{fG"g|)7'2M*/G+>Q][0g2<_᥊:_yYӣ!2#j^ H]Mʍu^nf\yev3X&9'/S* ?. \ik턉_MF6ˆᇸUh %|\;nK|ievHzjQ;y(TlGwvA׻%$Ě2TR(>')"dH-OĪ:RvH^_BǯkܔH!G=w5.BU'=/T6kz1pa{܌[xh_N9P"q̱?Uybm2@v6ZABl;I+eq/(b'L_v ů`(XêbHx ƞB`n@YFz߱\ IY=) +u2]Gs3}5Lfz}'1CvMNEݞE(q \j7}3 U=j J8Y+.jJ?Fη$46(p[5 wTMIs`$sX d7٭ |1B$)њq_w{+[:,/iR 4檷l y,|"Pv{x{H)B Z3l|,|^?>2b['2Z?]&0|DV;̖9(WM;*Ʋ;vI#]'0mMT ^Y`rr# ?ZXGV qNޤ1gi Xx :4T!~Wr5 *7b9|'FRtlU3xn3z+.';u~"!G(RtI+6u4{ש嗰imYW3J*wNPٯFi AYSG6;;;^iz߯a;u!V2o?\,уFgTfhFކ,i,KKa^#CФ7ݤiEVm}Q፣%^9ɺjV-Vߏ9OZJICa(i%fsqKzlH"khHN!үͱ=U:$*oH@cTHlQ:Shkt([Ţ^6}4^2Izmnj,s֟?.UL X[}HU,&kl#q;TGTX<& a0ȨqjFgس=k݂(z^Ԓ.2Tux sz1 ͎X^ 8 gYyܴjudKq8't{m^<é8xDž%tWT>m"!׮tw< f:/ ]sz'2RGqst-ʛcm l:Z;O.,a, -qG o~.uVc~tvnsQC8:+9 6u9dH4Leb:a0%w'FF'`>xMn#1V}d xt;]t"U)Obֆə04>} [ga(IŎBJA^:=0%3qFE6AļП8D Y,Xd`ZMF~!X73뒒r+ q}(U@n@N];{0[f8pU2WN.ϊ+9,P=ïXa Gݣ0]]N˽?POΥZ iMJۼ2;oE;}WMS[yjFM ̮{i˺_o$9>2A)BL?^ScIt)߅ yΆ+ٸ}IdjeW@m70e :ge04E3q&>sl=)&-~eX44(>D|_GǨ7o`K쪨.)-8iCӇ܈>KŶԿ!RAIs`PZk Zz/jo{ ޾2#2CXp2T0e9!~)rHMcେ֠d)Jj܇v0v5Lu5$]™;nڔr,,`WvAv?j0㟒w>*b6RhHܐ0{;'N,l+9tA6; WkXGڋN+ICg%O}y+ҷ*FMHc919!Ÿd1?2SCW,ŝ#?sC/>g_P$ŅhNG]ޏ/TYvX4lݭ%p d1p91oE}0͍ߌG3uf ++Tӥ5̃&H<1xc1I9~Fnb"mms˟'8Gݕ*"1U_N![jb `|C|$a?3}jd}g9f󷕁[Խ,ĞܟUNy噘p>B_,eC 8[);t-'+<'\L" 5Zby[=e2g:qJF(JTeS݅a&Fdr HU'Z6corOg8VTJ謤=2ƿcOͪI9E58Z_b&!{F➑kZΏ2O2akC./"-*A eyNF?44o oNWݓu&Sؼ (c*gԂMAd {&1ə]ew> UzmP@YTZYc23t.X_' Mw!̇m4R=sO_3%q]_c'Z`^)ax70r`}O~q0Q̱^5jzB||J[?G̉Ƥ(1ȮٗxGr5GnC|)j6ىB}&2 7R gE$&C8X!?Q%UXw2yϩ{b"86$LRwuVW{=R6߽7,kTgx,Y!Sz5:n"z$trRo]H jӟBrk<y1w}Q sXs8v,w3!@zӄ C).08i$^֜ I)(^5hw#w|٨ F>}C}oI8މE?K/לq[d=ey{GAZ. on`V}[9ÿ0RtԔ$"bf R!X6?%7蚵57;YX1.wʾQ"38 .=L#7D֪g(f]z4O^Hۅ+|O'bY)CZqb %ү{|́G)c~y*fUr _%debRIj_ZGX{*5#ȗ;?`J;Z<$- D9cMIo1ϔZ3R#:-4f8&b5Cpj6r˩ٯʁ5xQ|_쾍PaY, \juέ USE5;J?h&ϞS[iԷ _*.p2|eq=""ɱ?E~`ץ.(n}yLL5`so1G ЀwTƲL8H=U9]blӇul+񺙱y &8q8m :NympaY Au_4 9wqHP.ق<]u絘!$`p{ q xK wROxzH_|Y wrHK<#هf; d,l@Qzr ;*n;8C/MRh2v|o礘_ъxL:ywL7"\78Ƣj =Z ī[: rZ;I e1^d=ۆ6:f0=遺VQ-^wYȡc;*Tn$g[@^w;Mif.tTち_x5j@y˝|%vBL?{_qӥ 3r Nt{'.5H`a[s-J[~޴ >^/w›8ʥV6qi 9s~GKB:_n't6 ZzOji!hs)#}nńO鱿h&y&jǧ(fbj5҆pF[}~\j覊r@]<ҧ {3殠FU`˫yՖjsXX᪟茀m)WVNϏam1}\H+3=mN@3X#Shn?$1hZ)ى~9t𲞯p]%cGDeax)HlOkE~{đ67)ãZ+9ќ&ϯc  +֙ VPøib䪆P qXN59J~1"9&aԲ0$=+ZY(h}7ø* &) Am\~hCjܚSfx?W7ţf9|ȝ"kBL߿}C3k=/:xW^+ ׍v`Z_38. šmIo)w^>T͠L(L?_y"占o\54'f26K|#BHUD:6yyX=9-f&>{;hX;( iܤγ͛Ë 98ѧH۪zV?Ćqf4 hԞ>|C{πjR{#j V]U!변'jM NzЖS2쀆y Wzmߘud ?QUQظG[CVT uH(["..;jCƕN:XkOVK@#W<AR@m][]NAUet6FTiRaGZb>`wO7)jb̷G !7Ͳ3`[XhHNs-:IjicXbh196=B] j>&Ixd- ۚDRE?J<\ftnYS;? q^k1|:ggPmaV{_muƹU4d>Wƭ}']¹͛8jGW%ow/4l);8AR rTZS*BMKL=7 G 4kxp}8AxOIXsKO%\C+wk.{Z}O?X|G 1O+2FdSy2bvC\=kRܠoc>?"ĕ8a^)lҚDƥ rI#FNNl~Ri^!8ĕ 3nq@'JzDqcm|5LW8}k({xe'B6hѵ[:^"ԼлmIl欮,!wHNI~ޝ ~v>.ȁ$E)lZ32x$գKQ.ՊA]i>w;lz0)#/BbjL~zDpmwۥocG;!! җţkJ@g璧&pik|(2}сE)M-mjw' |/Sttu}=9۟m#m5g}D*,7 xG[g-3OV@ʈaڲ2:cINqK!_CZ 10}Gȷgs{ɾLL]+RtRY91S@bVY"wP]Pr-3.&H^80#S+>=݈ 9!eICqI%eԃ_ٌf.|`ͩR:IpeҹfsY,Nx /FX(G䃑 a/VoK{.c>oX?ʾ2/Q}zމ **xe a׆id2ec;=w7dY0N(=I @ ՝,r6ӽeR;t=1}up&FUtsf:Kl݆n)sS2*< ɖ{m Br4:xDL.hc/_4xe!T~.S'$a, Xaζ9^|AOFekRܾc9Tz@tF@:x t`:?Ȥ\e}}ztMT'LER˄LQ%UNx_j߾$%<4@a$Y+%ng;D!rHt[w{6r<kp 7 b wfהO֬` )] F] ÙJ;/ظ{9> \AOg~/ssKq +nqt3F:ڃw.YWv+0Ps./;dd8gTRa(q+\`%Z)fm"̇KN,~>gl߾B<B0L5اڰp&ܤJe^Zr,@w}x,%4i"bYmiExVRO[+8F _r.\H_jѲ+!df'I_*5P^(Vֱg9'K.=llXܽ4jb`/\h>,N1ۋmQ)l'ƞ"am/a5LnVy QXWR+z+N=-ܽN-k:i1ܸ -4!QycFB1s\:b5 υEV(frlS/bwaRN8nt| md[ӣ7O aާv33'\le̟`1AHx՟Y˖;xC !U^k-Y3XJה(- 6H(8ܰǪ8+o-V͍ԉp5'7=5s2 ;Znv"p]1 㾮 ~*x5O1:̆Ξao+65c 5Dێ2r34}{0ѻt6hās9&x=y˔L 6mOyuybin ڎfeaWiQ eBn4fɆCRS9lM@_poDW.ir 0MVU]9 =dg|eû` v@|R-WMS;HZ@s x-c1p&S'󞭑Zu;2#y94 ]w&$o| Tf2-77`ZStN{/,ek4 ^;lcc l+kK301XUO JDcM[SX 2x8'pSG֦t@$j4X8"Q¯mx;%,/#QyKG@-obſ.Fc=|r n"DF5,XUbM:~IZPG3p_1G\j Q^sJf5oLa}*1]9@Jf`(!2'4;2.Ç2&Eut%|#ز-aeoڻD߹=zA[V!#©v]>1;1^EyP`,_KrϟdQ_ؠڸF->l|JXzPFHU o3gTgp&W=SlRZUhgy٨bv#TKItLuI~5ZUj}f۷H,): ,fǘ82[^mc,VdN36fKI8)6eoϤ8g_|87-b_ȈˀF/H#yA1 CJxv7SB'sD`NwI =X3#G0_ɚ}7t?GKE Xݛ֢Bg%87sM @Ƚ/)(Upsm$DmLFoӁG¹@x gT^ N9yDK>4@Iah[ 5no?̅mA#fN\abBH$`M@Vo?i<ŸM&OBJFV£OG 7w-yY0-z Ƿж^5#2K;8%3݄+~oOD2x=YcL]—ݜ H嵲D5Ja[mܭpaMYYBL@L0 s䝭FwPcKDљP#D"(y|Ճs}?4堙')D/ TkjMcwgwoZS !`\(΀3%N IsW5|\B)*Ş%D ˹Zk٫N]eu{5WF2?8[ϗv y|W:bCf fXK;(D+vYJL)Vͻ] l<+/-6aUOo8EAW5Qjoӛyle)U/?O؊kUnXYtt!'Qjjt)-z=P x?̈Se]I:E wX@0 h[~ Z0D8=ӓzBKLu|tee G9n"н3* <[b/v o%jGxgkˉxnCΧFpKzaɐlO&蝒*TWgc!TpmK9oҧe-wj?em-#Cm>B?8"oF>(Kn}"N@НyXCY"Nv@`hKG'J/V|겊fX]_v /`Zm0z`8!c :@+v~O}k*~M0Q_T}G̎K?- t(Uʋލ Nv+AK P~Q{EϚ.Ng7f+[Q#-ZX7NĈyzī%?>GHc-u J{dST\ѺG~: hS4(A>iTHjGᾐ83̢lyVk p-ʎM̂oz3hBwT`Ac|˖l|17/ x1~D{{C9x_s ]N˗Z n} m--v Ŗ? JHYHͥv}s'1GP;P Κ#U|j{ЍΧg5oSsa@vJL`,_aP!z\Z'dREP,+ˀLhGd ^E6:Z8sjKf8nU>R%k<26(Fk̏}^¾K9@N,O8D-+|hVr2akK[I_#hq\%ֳg ҏTE!2T%͎ h&%xFjgV)t۷5UqhrD^5g_lߏ^hzC&g+XkqboqfCGj_F*]kc5PÊß"8lA@2Dd2f|rډ;3+ ^o d_;ܩvv |" 8E{NTjyg9؞Ҧ@5E4?UߊY;E*qpCjulᱨc!F&^vj7Q*66KJ K}LWsD:ƁiG|`Opi펣cR \1CpiA>]pI> stream xڍTk6 C7HJt 03 ] !H7H+4( ݍHw7~9=}Ykڽ}{a搲YaP7'P @ GŠ vC`P?,d\ ĽL7TAJn^1dAn+*'@ ñd`N.[}>̖,naaA)G ` 6FxWf1[Iݝ焹H![vq[~ P9nc ІY#A.`b ]\V`}v @ X/vpsr'޿AA0G'XCuyNZ29a 7dqot@^J.'q#ׯ0cZPW}=>\{(@a qv+ms/WfF@v=,m~%tVrsX߷X_Xppqzo X"`b_] #=_Lf:xk^K077 |;w*BaῪ?M߱`1hy.$Hᷞ/q➸%PݯMm* ZE~6$.[i@/_5`pȯ ~,=))堖0_k/<\xs7\Ppߞ/Lx\ZD /pY Y\?}`?}d=_Ȱ?}d? xp!B.?}^hr&/.0l5= RҝcrsDAW8?q2Vagis2d Jֽ㶌$l\׊Gnq Fa3(BIgnj7q"λ^ _78 i(RYȑ4ˈ1.F):/o#!1ҟ/=WbRdtw%U( %"'R{q\RQL$w)+fljffJK}mڄ*QB"0ywq ;<`[jqtc$~Q)jfb BWQc< hy@PTU~r\k> -HTFVI\ {硓we+Sxӌ+ޗQ<$5yVxaڄ,N,q-}*M,}}:2ekie,p ` j" Sgw*bf8eN{܈6lۛC-KO6vXo=, 7u_:I%0E1>7YΩ .QcXleTةOdYf%-s8!M4ىGSJO9YL.ۚ|FR6!kvpc^h|yh*euY;Aiqfe*.ĉv0e ))'y9B z9,VWQmqTq^/q,gR@7_1$1zZNk|ZQ-ԝLH؊6FGߩug{ wL5*l-ߌ-, >?e.cAij9I+kD8Pq 'HְnMխ r ƪt7&%a[vє+&|DS$1)%u'! z,IGM$ yW%`VDI^Gզ滋 X1k_Df'9dhR G#(?sݦY;Rm 35rvb9^Lpx,I~JmK8[ZP %4m!Kɲj!_-ݧd6~gD,K|ݽ"8| 0z-.:aڄӱU r`r~%R0@Ӝ"~N U'ą-2̽ԈNLN.C:׉jQ7;vZ!,pF9^:dAV^0؝DfNH' 5)9;>_ҕ6RE0`ɥ"|<&)V9sAzv=+ QO#PzėNg$FMRsgBț.1Һ]$ N(u_ y >y?џiz~2HK/GfxVȑUkoi#(uʘvIhX8GգR}]MENR!ķ3v$U^%2/o64 gOgŴْ~5:" ? 9FfHNј6.>DJ}vGu֮R3sErL9|3dc?S?*#5t6}K&ƲK^xz(Rst>ΫInQEafA#4 KNVoAy6oӈ-O+cNz7S@ x1MenM)O0tTb?x.]SPH?Јv@†ػG$n_6/{7_L߮M6VHo968dEo-L7ѯN\ s}27%10f _|<,I%Kn2@1>Բuzb^tU Չ˿h>Ym(In%Aˍ{s=\X{+A}9>tNj}Xk8SJtS8RELs4Pb$AiKEb]UCe=Kv~J Ywa)x`AEU׮a`hz {Hf@,$Nx @wK%l/w5pĊ)Gԑsn:p)Cb7!K`&N`FErd|9^ 6~ʇϛދ% A>˴ƐL@R#9N2EJ9h>ퟄK<g~UTBFdQL+r x_ߡ䚤Athw ,bJ>q&0̛L0׏#\`5WNBZvDw[8=gAŦ*,ѲC(snHhG=|{͛[޸Ќ5*qYh .a_O:V1"kޯT.3=(.*f[dnz$Dx3 Zj];q1qH\ (ju c\ЭP&?P`Q1Bs)#b酞~˫kY& LE(:.VISQ;CU bg"SnwI 5Q.gZ/JVv :Q9!w Ԍn.?<̽{ޖwǀLMcCS55k|%jW2ci,*K658AǨWA:1_FLI;a^&M|]{Q#ß΂mZ&?ҝ5fYHSjfouKPn,ND#žZO=tq&bq)74LnG$/WBk8ʇoʒ oS[)3,sJQ/Q J&b;59>"[N9ִZjs8;MيRYy{ 7kkSlM˂+rmGs>xM B:@5rdLN :"[j!3HQ75y\XfE*FC&ښ2Lǘk,׳KS%ܠF Yb5BG0Uc$(a. !R` v L*JX$i< >\C?^@/Ѕf<Wdmp ;율e!ҸPeTEjyL9,\ |X+k'/? |*[ 'ǓC>Ox}ZTW\)ϺQe?l<7Cuc=k?WAC:9nAPK:u òO_:fu`sPQ\廃WCL{~S ~ԩjphN Q۪U:ͣ쎑~dƎ"/j` ;`b|CG³Q :7r4 )Zw,دKYE뵆Oi/+l/ƾj0M36ӧkZe8_g4R|k,cWbԜb 1KEDjc4\>]"p;c|Kwʁ&=˞rZSE*B,r9Z;hk'M m<:>N[,SԔlɝddz<"V5NDKE&8ُ]f]&'JnvXKpl>I/aZ ‘q'Μ|WrAx6׏6258Kam"IMYZx'i3pZ%U#k)zGQ%e/(N*xF^8{ݢ s{Jziq-Ɂ [U 0+WB [uL-\dV/=x%R/ɞ|EyۣP / nPLv({aجhK5Ky:כ8}_նCe~]fOL*Mm\)2>< ;~LoAGhWw7[D(ŧQlUUev!4?%03<.%Bz(~FQMX>d 5({|?&4™['k@HбcV]cዉר__gJVOu~ۆ-F?76{Ҹם\WFةy+$_Zp+$Oo0i+K뗈B-7w·Rj9LJ2AçSR9tw_޸?Ѵ]_[S^la)É?CdpVzAf"m?j g6L~BiD'kj?Ƿ1LפP`[飼Yܐe(;^vUK耞,,U 2-"uDf:v[ ZGl|MT4 \:y åoO) r\ Rppy>gKK!s~ʂ\TsSVDيdBzݼkiWd}]I5ޜj/b >Xu04Ιye1 оL`">{4)w Kze6TJB1 2-q'81h3Gr :'ζΟMH3/}G 3Җl(R\2"? 9#d:1ʔ;Gt=|A\PX6Ssf6YL1@]Ҝkc( 굸ֺZzn0Rׄ$1_L[y2$oڎ[%iUbqSy$׳d..Y[a];|^Vn"描Pm,o?.04"%g  MNj>iе?M= v_ ։(8ȕ2s<81 S3Sf-cUU C7ή| y2ň|;; "8M<|qC؅f~,k#UdLccr+ EjEzf^gЦGƯ_pRpVG,XT!"9VxFn6+sS>F2&*0z$3gVћpOtR+qWrZa*m׀Ї,Z[.á}NKpUP-z父H?CɸVDG-xBVs5K|,:_ګwHU\q,`_ַuPFeTc&WO w=L'æs54%>6;4J.ݸRU HLWaZw6W?M=0Tցv?Gٔo{) ??JHvD^Yg)V(WOAs]OG=or yb0;Ìݮ.5M|rѱz7diԑRv޾Ta9\rz.3`АNu_9EVrT Xqr Y.1,[lD8.]oM,hj6^HCXC-Oi2\j*EBUQxV.%s+ ,Ԩ=㫯[BK{o"Mm>MM֦ a] +^ǑU_WkR$^.54 潼Z1Dя! +hM [ʧ{UE_moun hd^E׃!|WJN TA6ud07㇮$^H"z\RSB0Xi-u.UUn;Ӷ(vCW6頑;ƽ5dw\7Ud+9N惫_g8>ۑTq5݀#M+rh`غ%TBeID]ӀY}TIBIs$oHπmn*P~gGB#}Sѷlט +R13(D]YT+tLsKt'wbC9Co LUBmũ\q\|£=T.ETTmu endstream endobj 573 0 obj << /Length1 1413 /Length2 6039 /Length3 0 /Length 7006 /Filter /FlateDecode >> stream xڍxT}? @] "1! )]Jt+)] % Syy߳s\}}vad*A:B50PDLoj Issprbn ' D'Ah>%@)Y@\LLoE,@ Ew([ svAc22B*PO.PwLD00EaP?\ɻ>>>" wY_CL(7U24bn 0E:}@PF z0:zC(⏲!_Er/G0oct!`g jꉠ}BKG!1 o r(NT10U @DP0EYQCChaP0~ A}r! Nʀxy#`:`D9CI1))I  ` cj @z0e@`NPq =A D  00u!#:9c ؈az0kX U@UU/ @X\ ,#%RiiI@?`:'$@O>_kAe0 7I1o3XJH Qp; ^h#1oUKՇB`^AmPA8c- -"v҄B!F04k!Q_7 JL0̒0 CC#!M\R cf9I@} *@1&LA''bn2Q0  D=0SBB0 ׿{yzb$$CP0<,"NG8jwl@$=F Q_.gj4UrALΓҏc)RYlpmx,"{%o>FmݓJ)82 *{؏9V#)>U2y:YP3qSpztVeŞ8n}9}:d MMiё<Ci!!}O*H 6),5֒,0řd!A^dFLo +ˀZ6R%dj' a wB.MP7O_i.XTNC]dX^նLr`{ '~:k:*RiM ^:uo0%~_oƖvӷscj-!ΈxUsdڇAXsA^Y+gSWͅP&#TT 25!<2$1_P"X.Np%wt{6\Z(iy|ng;) ӼHGQ+C~*ȞÇ{[coFR['͍[i]ۋݬi@jg}giwy{:;, YMr4OJےfϾg5֣6q>g,p\Z3$ 'U,Fx;!&.J,``MJ 7JD/f_|bbB=k)39kKV%Z`z/_@48ݧw|q ͠S-U{k8Y,O Uk @6<^n/OUmHgKϫW}(1^V}ksFZB n 1#٬Phy]|KE!g137o:bn;Q1b$9,:~4iS}U۰Hy/[;<*J~و7ѥ`9AFN2}=4io KF@Tкy3TIcXO wڣL~ƥmbҳ3dDZ$Ͼ?>=u Twy&Q1;bJ܉Woy~se[0۝zp1W ~T)ϛRÅ>!5-oa &|c[}dG[O'wI-6Wkkv9fC@ثՇS t]ErIW^vX*'R KވlušN j[QqࠀaLG,90`Єbxiq\@%AE֑ 7kq3O6&{@9gJsB$'"xZ TO^2|dSѫd6OWr% 2{7dH(隴S<ԇ߮\yS&rԔ8J|83ǥFKL6[dvJԸ],LZKy91(z9~==hd+b=;/MHE\=7N <(|()̽ALm? @ Fe{7Y?u^6-~FQPoEKnf`d@sA~[5!sǭa`ܤ7{DV<=9z6vښ"|wTGk4߼XI{+ZsJ^Ĺ҆D-5xnqjI6T_Ƨ nmY}^*K:1[/{(| ୼=e(a˨:b}м?w/"-VmabqLL FW4^e\hUHo{ՅwOh_`&Y#b@INX>n.҄I0΄0.1օU}J*Xӭ;=%~f9 }MCW90-lϹ!,Fm9X=e + *pX&~srNQҵ@׵]HRX73IN.\]DE0yy+?eݵ^J hHz `VGߙc*F)k5Ѓɝ]c y@;j0޽z=؇g^]A4"ύ[`,L/FPؒ~"VI8,3?o`CnUUcq bZYWĶ$*,w#fh[zT+~*;{+v&3p[oR=%m|J ftP zZ%.I6&e$( EȎf93pۨXq&$o=[JCf1qrx7٨\WxWe&Xl͘vG!ױFq;]#[%@v~^=ElO|}*ծ/&GW^.On"c~t6O? YQ;)T6qs,dxv:>'%L vѮJ|-X;|ʋrI]}<: >J>|'Tƃþ̸ݗ R\ƣU,E2񗮶TS +ŻEJ! 7 9l?w+D]bj&]> !bN݃< H){ȸM)Ek„;wrs㲽WK{ vj-VKѡk|2z]";ܸIfv,j9鍦',fi5SLAQ!Y쮛/'?S~nk{WU Zy.DPBܝ`t鬭 cuzJf2NciP[$aլwcfBl4*x$(_SQdqK#݉(n4X_9! ̜(F ZG89ˡ֦l'ڬV!;F2!'\o2O,ȵ0d4\Haq'XsLdbM?4wI7lXC@R.8~p>xOvTtN}/6ns4nފ-rj@G7Wl/r* ,k<;L'.Ջs)Nm_@JJѮHLzKw" U=(.ԥ\߈^?p)vOj!]hyTU]ޖ>@JXKC>X 8eةQNO_wT1~+릅:S ]#2yρj#5+u\G^-SZ Gԧ.ߝ٦ΊOSZ||>vFj.>HS ls% }ge[R^{@ͯ;lv*DCk3,7I}2k]6*y \9.\(zmN1De߁o R9 YR8fC[J햟6oRӖd:JW9x|ڏ+e Cp6vccorf_zr(.I|kL|j7<.[80p8Iyo#=B3U穔k뎂\η\s,o^zx铴(+By^>ȂĢM/6YCE=L._Vr27ygi@S%/PeNxiʾd}r1~tv\g *t8$32x3bQ,=o@Su~AK TЧGRY||&;d(>ݪ8 y:زIE*k I {T ٍ痯wT$#:+qyJWcq٫ H Lf%3+jO<+O! ||.B4~YWw-,<XTu(/~>= o8u~?\R1!Y>Pۚ{I6nl;U4*vqrULgљx\oq{5&w3K{0xam\> stream xڍPM-w  ][p` 2kp '{NpOOv{kh4&9HcbHh)pq8999ttZ`_vt:3G3 l6=8@.v.n'')@g!+PttR`ks-L.AA~? gb?w0h:XA0*spssc7;8[20 rvY P5Met9;}NqX ʀ _>;׿G!0d3 {G3b ہoea0V@3;s9ϭd%f p; P9(|2K){{Ec`g{p}7׿bi KGm w̳ ?6k ) w ?hy8tra~z[нf O#t..%0Y!lYx,?.fOW̡c.7;%%^lܼ6 /' ^w53G v_[v[k:<+` 9y9-?\r3OT w$bglwijr]`S< 5* Kz`f ~V4;'_v0TT,lR_v? 9@0Y{2 W,?]2 ? 0sv6@g zJKbpC`)g>+g?.!OP784F AſsW?~g s+[>'8^ϊ>7r|\L?\O_'n9/[,g,^WKrc9 ;8Gݒ!uVzssƝ9'1+f XdGik)D<_ߊde=/rUvRjo70XZ}v.>L/W6G( 1F"QH1InSSޤy7JY)D?t)趺dHb[>0C5h3OO4!&#JPId3l 3KO*e(*+#ECT˞\30gM̘J)`J#hT<5a6 fFrF;G '>MN>7ᰜ 8(y;~>\!im,Y_P\X,zWxf2m[qIvce]܋>d\"4\={17zh$ 5z {Fy_dqL]3lQ3el,^V7{*^[SzAPw=}=72Kg^=VlnywZVW_<4j_W b3/Igw ͈H19M2,SM%>LS+Q_*M)1g/0# !r0Ҏ蹒1~FxT=j QO"xxnak$^/LsGl>lSQYx#MlҷmJ5^h\VxTYޑPwx1~aWզ"t!TKhS8R!8]+e5K'25 -# 7{aܻ2"9rA(}c??*ȏs,TϸȕTrL@fi3/Ďdm``_ZU63}MC1~nmS]K.HLS/|B_ښa(| /A.vq2Q&cM+-LlFËf93:ht%.?#bRwxtk=xzJϻ-LqF,~nS1z!*r# ^Ӵ^<-c>-{ZXŗז[x9] #dԔw˥q%bU2t 5/9EAnN}!G w[!Ty>vN q vcvA2@U>M-2滖WCJ\L4wҰӻ]-% Qd!yo*FV-zvVylsn})Iz_"N5QId8yRG^gO.[D5M9MQx Kw lpQ%6{kfm-2v=K+WH>ӊ `gil7ʜן͍|4%Ri\7egmXKˡ.BȠ4 f얈h}?g*}>Y>&-ʯ(/In|Y`}Iv JQZꐌ:%4IiICiay[KQ*}0ZD˺Jx.G%]R@%r "@7.RuޫKjpiٮę7˿qzh)3Q{/ . U[q)4M!"( ,5m:6, l`uqDZ]F9Y~pv0@ tytK!YP +-HR`ecXSlؓ _it:G('\uN~A]Fm8tu4JLآ;o# QZi O= :5:dPGD[6j1.AnYmqAzXC]:vb!DpK2W|fFUk]`-Tk0sG@f}CMgx{ʯ*:.|]jG{@3W}5T(#qFqIØ0$rD 5ӎc-YwG=Ztu$muM*WqS$]Do^{x25 kMc:Y#mٍ{ZG:%xG V?=R<n6fԝ+S&l-F/3м4 <(b3"t١aؗpǮ.9;XdrBj fs-T|e,A`{7::QzzOrjl[o`m#qr; +eo>ӚndeSik֫C#+<:hKg6zҋTظҹSHTx1;^)zz`9gQ+U\+0Xح d4밺{T؞'h q6BijlFtƔe%O-Xq: UIab~{ԅټD^uc1~g&u }6Dd;A@?=KA&-7AQlH˚Ev*?J JXQ?j5UxdEVh~F⧭kMT+g\, g!/jKܷG#Y7y9X\y$2 {DP?Jj=~S 1WcV*ʹ\(TiȶW AMjL8 PL1gycXe'Z=(_?~.nrtF$ͱZPϸm`%Fq\yG{F3@]ke ޡ38z?ZSF@o;$nQk<>ށՕ[N%p9F8qmݿ$v}ӓ Xvum<=Z&^|Z8Y 5ڦEtRxQ zݚs@Z꽽շAtۭ@;?¤I)’L|_rߘ@[WS].d89nOȚTU'bHaִK(גMཥ`@$h=rbO?N>5"-:CX=yfGEBi /ẁ4ш.079@ h/AmpΏ lіkVșɃ*v2 5'#!4[{f)2wxInSKpf"?mg|BVƓҾ&[f ˺м1Kj$T=[tCŌm~LKt;\ۢ*{ Be^G0[_^qkqEޭD./?9^ c߇W `_Vb;%I t/!H7Jvlzp=˛%PD'u MTMs,-[O&$&Iwwu1`Qu7w%X&MHjK{w)J5(%J,QD;~L, i᪫lMn\0(1AҋKeIJd:Fq7SJkʉZ;^= Dqo+ QL#w4oUR٬/[%guU VMcP2 B"0Z2OϘgdp&45G`oJ SQD8'z/z;(#/aebRujV/.SЖV;/PɇӐeJ|?:R}:MZIзe ޸VaYh"y?1\M> [tW1w I˧66pK겏cCY!@b<'-?'fѳ*M$u2܅Oo5&Ԇ!U H%$(ؼJs˜ξ6n!rx3oh4 HMj#I*u{en$mtO:< ݖj^&n}iб  c2Ǐ("/7ޫb^o8R<{x­C;Gll`+C&/Ӗ-+"ev/2Q3aDGG'Q{‹:K׍ǒt$S̀! U}7=-88£5Kxj-4'T2\k$ @GUI}|3<ߘY'KPB%1|[Ji ZeKD(*Ps26Z0U1˼ZOMS$9?r5&EoynIpռb!/ $9/>4:¼y諫Bz`^WlsAQ!"sV^|5J+h]ڂI$b+\Em];8.>@ŜJ1ѕ>;\4W^ )E&QþLUM$5`1aZR!?=78 E ;<<\p=K?26nf *KfzOY,;M jyˬM-uMR7MGs/=}OLV? gkx#>3Jᒷ]El^0: |'zm7_dy7]#SuܫWo8&iډPO3ѳ;/N:2^$!Hw4UN7OiĕQYrgߵ|תv№ _b(CkIk,:#D$GH&# Z:DY>2{o] i;eL635x$v3,e}i"sTw`5~VጏzZU鎒x2y)t`6O_!'ɇ{lJEѶk3 bOms 3Or# Iq7Ĺai_ ZZ_~OS˜?~;w3aD-r-p 5B^Y|FwZZ,,l[t]U͸&s^ĽFj-^UQAD<&{t@ uuՂ"\sZtV:Ьi*s~^WNN˹l''i\&ǥSz{ &ak4jwvChUW4wCitPDqI{QƔ~:m{zIarw+ nYuQJ#g@l7&-Stm>,JdŏZL{D^^k o|['0 ۽|^n}Z=+bU*.V{A{7b졉[[i9'VBYJSŠOO*'"~97g&`˦b\d#hG1ÚɞǸ\k^]%e s#5wJ8a4OE2Q f-zVp/wm .2E)Dx{"L#,:%988 OA[7;0[|wb~`}EJZS5L'po:y_B=xذRxLGk 'KވZhJFM2P;/Joק,^Dk/^W;4R =|]{?9}]&ҾNخO;U2i!pS+|F풼Ql"Ƹ|^^d^ G`;2 E0c0%hոz@7#{VS'?tN aJI`|Xkq:Xozŀ69JM{drp 6}W4.@GF :ClƣFQ=š1k}WhHmdEoJg8jMc[O~zԚ͙qDe`;vR,:o\&:i̕Y.IZWsћ  v1 c1ü7gw7%N l}T׻ -K}1T1U&$~/8*\e+EYSvIW_h^z j2 -#MR{euZG7 GBix$k|e 21 w^yҐڪzwU^G7o*h$c B7͑opB/:y! r: !1weSgky&\)caf<&S@#0G,32 XdH_e qwDg;?oΏ|]v0PTxPoMn=tr2ؖA% Q3YIۨ;/p~~Y  ji%:k"Y\4J"ި/ 1uxom\h8ly$Zn=,'6.Tټ:#(' 7A':܊ȻXDl>!P[PHr)Zz x/ѹ}rApl`y/Ҟ$OƘlݓctQml2u^kW0ԌQOPmUaI0@.ʊP>0G,L$RPē[d( x?LTo/J*Fgp-6%0W8U=97>w>/DF4n?xBH8X`.B [`lD,+q¸$se.O2 =Ln]dYPI }sN{"`L xa(c ߱bNʍTqs{2>3" qv@'r$o`GVBG"Nvhq]A@h\X Rdo'2yQʑۡXYT,DѱBH^vYQ7nkj+{xJ}* 2HdЀpA-$+d!/r]0Dc6r kZd;5U >0'\ǎiOfmuN} Tkå$]v5|mu*w °˅|`n汱UmrkEȡxUeF~Q`Γg Z](ex|EZLd}Xh.]X q $ytnQr9%i(I5ּ(^! zJBCnSP5BĥGC?Lytn^Te"CzE1DCe?9_bV6LKlNr-{(t& 8N 8Wq{_mtA0^7lD ^Աkg֕K@ׇߠYAim VAxk)jO:;15'ڗ(8醰&t~)n >K*$SrԾs|z$O tgq8z:B%Jy}Q憹N;|ae+97NJSaj'ha6a,`,N^J/Qw2{ΏYM#QTQo-bUK~ipt"WNz~#<+?UfXB_l$P *>hQbҠTI`!*Gwl@퓮owu#q8sPbk_1X}ND/ >:0j%x2w7Bq:ow&RѾg1ۮΑQc09XJ݂֕N?`I}+əQ ݄zg\v*fb3JVB?^ua^5}O'6j0pМ@JU:NցZIWľ3qkkۏ4W#B endstream endobj 577 0 obj << /Length1 1947 /Length2 12678 /Length3 0 /Length 13887 /Filter /FlateDecode >> stream xڍP c 6Kp\ww [;!8r9jYݫmJ25FQ3{ `aagbaaCTm#RjAv|b;o6 cQ b`errXXxCwHL9{;3"V??4V^^n?@'@l }hjlP7F vcfvssc2ufweU3hcd-ј) j`7c' `29ؙoj e_d tGdg``DcgxcWc֍Ro= cF?Ҽ-G '۹{0}vnv^A ;3?0sq`ְ9e%漙YNv6t7dO'|oc}@/D/gcW "++ d -@vd3or豼ɏ翿ffog+fR{:^F6vv';7 YTAwHY;s{_;v[4-s)ٿGX8YL!4GWߎ\llEۂl'1^lUl=7T^bJ7sXh 6&IǻNd1XlVy'(|:vՌQܤ 썄!܅;ћ))yxm6Lyo# n㬵KsV%.,귚>qwsWX7< G,f}iM"Ta#0TtP6K(9Y7>E#qxw3yk^u%UTj|y~dڼJWbm Ui+c# aZTz TͻD!*>>] 7KVLbː6ō+ӹ~YөIŞ:YCarŪw0b=?ba/U1Z'meskF>EZpVjy%qvSj7Qx)y_Ybn\un5'eH&h1zPv}OC}ՠK%Bb_K#y;c8XL!e9.\NPt:?gf}̍}Vݔ%ly$knl(NwYN[1{>T~mP%\G_0K+Տ̊$򚊻5AK9> 1^cmF.5,98׺^ 2[J_ e*1;%7 )n'$/ {H:nƞGDL$uG*8åLض;aLXc'Mreò"{=4ND1_/_;J=,y*38v]*P{-6U3y$^/g ٦z|HcN `zStKraW_SCQ!f"2F9׳TlEF4< 3MqI QsU\U%ߩfVrp-zE/<,vL6L{$WJE"6(]L8A cΆ.ۧB$tX|,7:˜50"hIM$FFߞGȒTQbSMK>du8J;ϖīػ<#ۥ4uuC* LkmeDFlU;uDJ#"`|A>&ФޘWYesJiv*Bj?Zœi <? +uRzH94 ږS&|/d)ѧN%TybyULk 2e,_IXkp5هHG6y-z1N,пV^Vx6R҈%;z5`'%z/H˽z2fPwRGB(Nm OB pox*8Ӥ:[c >IW/zj}up}啬]ZrI&idO5X{9N-;˜tJGeD\DM)$ݞXLZ л+>1]mq뇵nCJV(0/Jh3S%Z?*_V_5אӔ\`y_qpcDyHllDW{m+&{Wyw=l? O@􄜟e-EX5`j:&sCna2z7o'2Tz13GBp#T3|c+vr J(NYɒ* $:)YV̬bohj1EJC D0RDծc$26.KaKZ f1ctIdx,`VE(hmHN . V- V]67o.z d]S#`\au*_}qdx͎$ SRwm,Z$'ܨda';U0;G/pU!_RReG3nwLrFy׾KOX?.h7kQN=J&̷yWm."8R癑 mXҦ>J C[1>(sxŋ!D "ܛL֍cR9ʞb}k3€@aU;R3{w CqbD[W}3;.;C^SFJF"$G& w2)z*ZׯJӝᛗA⤩S6}MkhsMȏ*Le@2v>ǗVp{'/A* jM]*c#̹7SRӴ#)SwoKpE`VI oI=·;m%T.āOeCPD:I&Lg ̴s=cG뜏I2xTν1gyd^'1#W=pBk6ONvJrG/QW󤪭]u)[uvG|8\E[qW&\ܥx&OIkoXr XM#X䃙&{QλM[gs:k,l|cS8ujv/E‹ 8e7npۣ&5],~%ΏZ:CIIy6Th&Ȝf7`4swG1' }ۘ]^kR.ߡ}OEvl\T.5V!hFFaTd/lLpo,Q+*8አv/Ε\Q`$pyۊWIӻ!u4OI?HLpzj-ypFG*kK.RvB ~lnLD>$LvsIZfk䧾)ydP&0MsﱗS)ȃnoD]z!t-``MVNCd.Xt,\h҃YhEP6wL*-ё(ę`YcCuBlv B3l}nt1.@EP)rLE=Θoi%q*(碒I]uzԀK/JEMA@So!MG$/$26|0?gQoӫo|sy`ǒ).iɠxKD^%0qbo` ty򧜿wK/; YP2"iak=hԖǭ܊XVi!+6eV^7p ?N[F۰d5g0y֮?b,Y T6'kghnpڛ8 vhULv(LGoDCnQ \OPF| PMM e$8<Ѳ7 )F>G%Yxc´k~ʽ%D#6k9ʴ eC2ۼ(&<ɢ+PAJ ^jk<E@;(b;O@ڵ)`+a+TDNzXr8U%ۂ1*&z {v.%~s5&6 CL(GL->K󽦳ϵ^?+2]O־lNx.] <"MB\~)\p@enIK8X<k}[[*\a#U)Klբ#ʌT9R G8fi<_4kZiU Jc_]eͤ"+^:*;I9F]&)׸^ oRj7>]+C-F)s̶"*P ٖz!8TI*=_d13_@4hy|z> G%Y}Ygy=@0FOYKbϵj<'^ :Ur8mNa{ܴTQ ZPvh-n[B%L&3|}5KfFDS &zo\AL]Ӎ=@(8Y sGpln>ʗk+4؊=K53.Q;{OzYwS ʗ:U"FK;MZUQ+%IjP1lPq0TB'ZؼeL6֕^kNFk6wiִ[lr$1i8Q˃I|%,}.txyRQb 'ǻÔHGHsf}}?XYvr<t}l_DPÏvLb/CyfO![^L  ;'.j3MOK \ua5S Ɨp=x(z`S=qFNaR)~:ӯ4S pmc Mok%/hkҀuz1H4q9FUF MM23vw' 컶/j fd &+4vZ.6@i$ɉ? {I3nZ@-3CŦ-++=)?vLwzrkm11.|n$N~|j^?zkpAD.?cB A{f+vA.F^}DĖ \ow [OMA(j^fLz?LR6):0\mfvXo8E@eK O*f'b;DfXz\Zktle'UMQvnv9d('EOwYB2^l);3YOBew>&{4EfP*:)3׌U4&àzh>;?of.5{xpiJ9;;D7f=/}!b"6^CcV$6>5aWՓ&ϱ}Lpwxsf*<ǒn6zaGCݛym$"h#gZf' - -~'[0Aj&"JCz+>h_RuC \-Yh,h᭐}qSd=eA=JpgmH&-.lIJ:yi{ڋM´hlyI~I׳7wQeT=#?5 5# aג 4Q[ s?VVI٬{xb':U[xN:,_.eU ϓsVj8.}E<5'v$;qWwHe¶|\QITʪ[y4 R!K<%˔_~$ r>:`a{T=0XKr>RTslpb^[9K<xWAKk`s<:^c>15aJ{-c|)caA>}9/|lm\hb#o '>k$J98[RWhK>kF'# /_b/Ug]ފHM$7!'ы; yR 3^zO /G joZF-_Se5S ޅrT۪[UNEfXiXuSPMwx-Nw9:?,rHH+XT7T |M-$z,껆Riʘ{tlO;n 0`mc>ȽO]Y(Ml6B**|'р~䤝Q<@W#gWɔYX:}^ gVB1;Z)a@e^e!M K\HcȼV*=iV]JO>.οB?e#]d3 Ew}m=S+b/fٮU!}2Jw. g(we{߽ L0vىa,GB%頋Rit( rq2^H V+tQ^9#00TS pK5; ^'2~1Tvu>5I:#AEJa3}|$]%m/) l<ήslf iu ŲH -_(U-=6,Zcc:K,=Ey:ʌꗐS #+ xvJn=ix(mS)]7Q .ċ2ǕP 4|oz`J;E>3 R4p "4LXx)7D-(ߓSZ破lVy.bPTVK&GmH|оnzMTw `] y@u¸eݫ$h8e6gŋRDtڼʨ+$j~\Dž#^|jĶcN\9 ;3:BζOZH$80u6%JEӱ?_>ZŶ aXzI5Y' e\J,6#5exyAC$a7^& |t2t1<E&O <m0-|{߼?#kVj$X+LRa̳?Slexi零sPymVCd쇐Zx!&;1ˋ}ۉ}M[cJs88~KbN| ;n7ym;[%a-l9xyY6D48[}]˕wr7)B`D 6ENyP,hﻸd,&k s7AREw 3&jpG:_[h֗bc!"}"xR5@Fs9CFOaQk±^eFϥl<{'yD6WظNj̊,% _^\]}xwbF &ѐbK qp\) ,s).泟38B$Il8[ƚV5cΏwr<*;_d$}ѽ?f؈U^ވ=~F&p:1GIbLkS_-õbkTlF|jzA_ |>UgU|/@wŷuU=7Iﺧs0$Ѿϵ9B(Y9a~?s0`d0ICR`@+`z_ʠ\ˮ}n7[uPɯc狦^bXC\ ¶UM}nP$j]B[~j621ia\µ cT,GR{=@u[p[v'O? ZC/0Q[Gݲ:6D-C+ NrK\Gl)c}vEMլw #t><<𬮫&fVm[b>\qBsss`,zV67$<⊢?T؉M_=@ G>4WR;8E_*[זp-E]}6CGJg:$0wдMY̞lOE7EAhYd/%,+3g[P}{;ciHTvpvr_X١q(8x)!pg^ʺeYyimMvvwn|uتS5z)0TU^\.Aj"AMƔ^xS0dmb'+oW ubCn60nt3b" PD}nPl1G^ 1,;|*/DW೚_A숖Ċ3hLn#*KG~[8qSYpP¶%%,Md[}V菪U]tE<6x\ ͩ `r٢xR/ bB|| )Cv&UPVlDyLf $vkm DH$mO8+Q'%WewQ$u+[83=FZ(DoJmWD],EI赃i,d\()ϽGRO1ʉhREƽI %K 4I: 6 ⹥rHil?|Oe^#jnwn6v~j s3/$L}ĖUHΗat X+`cL! * S; ,iVS/ iTvmBR 8(=.&'+,B'zFg14'J 2HdAeFqFI.3$NEc{CWP)}Ez,Fy:1*go*/N*zsi2iZđ%3t)mc^cI.b:P?IKdNoKk U>Zocҵ!lR]* 3=iΨtBe #< ;qO5qq{q%$ƝQF)>""{ WlG!h } e4fWJnKIǂbPUu\?ޜ^ ?Ư䢬qI$K/$P\]PX+nƃUtE^Io_mZ!8s*V:kazbIo]rnq(TIz?M̭MT˿yq儙Uj6Ѱoр-^k~YÄ ͛zmY3BY@i W{;Qh{[&رAb+4ȑB_$:T\I怬1Z+;Ysڤ |'j̰>.pjB~N2Y,42icDt`6 G.yN1@ gwGLz`[bF7vgV6ҙYR?*?Uq k>~}2KP\(AwM+W&n++F( D$q6[J$F{Z*6x2ލcUk:1u2u'Rҟ`vH-&cC4_#;\\m09eÊ&lɘ?-  endstream endobj 579 0 obj << /Length1 1502 /Length2 2445 /Length3 0 /Length 3408 /Filter /FlateDecode >> stream xڍT 8k?ҔJ޲Mb6ee %*c2ޗY0i*K-"KB+ehgI)XRYB֓T_]s]*vk9D0spu%A G 0** ~1* !f,A1s %: 0`eD-c@5  sJ0Dp-lcA ηWK u5Q)0@0tE* Fkp %CX;j!l Ҁ]pi4Fpe@쯉Ba 0!*.LY:p d `p"RB#^,PH@ A/@ hir4 L[ RlS &%,nX8t¥TasaFB-`6fa /]?a": cиx7 6K|A@&zZZT~aW^ $. @$c|06%8,.{C$4|@_ k? < am?03y?Wwa{ߓH(I4IZ ](.?*m`:,zJ6=?څ{* b_,4;2yWS &oA=NI~5Hp(L`_ؖP(Hs8TƢ6n >cB0脰/ I$CEGlT)+ZT`2YX*D&aDԍ40tQ#@tYR}]OY#m2gADTJ 4B Vs<EB-!i8*B?toCA*3=zb !}Hc'&Zu03ʋ}aR;ZjtKu݇{YvW#8,e4;̶|׽R2aܲuFǾA+C՛Sí~{rY==UQL2V(njR9SH"ԶkAolڑ6P#o V[%`#&Fc}.h]*/pDn\~\p$xsngbnMx\< {C"oa䅝Jls6a{TsfV->1\?FU>NŜ|36lNqUia8갱OcJU oͽ> H#+S/~wqoWqC6Sd=2gmQOs 1:yD ϕB_9+RC[$J N/`5끫-*7I:ԙ2!RʩjXM:0q ^fBa'ALkINP*c?lɎb%e;"kx==*hԘݯT˸uej̊c7>O\rg}? 7\ŮPcU( |ʶp8$u7'[g;R}nQf)7=hIH(Ti6OrMӪwK gbS35=½gRr}|Rcej=|IM=4 C9*.lUԧi}.|ךjj߿1,h, lS?pҵjMx {m\g*ꤔeTw)R/6T0;=ư8X!s#}f3D+Nr"/]&i1)8W?E4ſSxԻw/ЛkJǡ\ly\?}xw>&mecrG[1F/om+tVfNg-}m6O;6g)5d·ꙗ dZL^e`D==s2l|z;qJLAO.7EP7anB]IJn>Chj~36PeH|č|ѢFe!׎7V0VLA]koT?Z9ύpί^Bqt&NEU=2;tD%&+d>&H8q1%;zrDVwH|诚" ԷMхU>f5b+Cn)+c爕. nf︻Yf6cvB-hw =9w:4j3ORU٘.~Z fӏ8u2rj]/[2Dj4= UV)^yVJژƸV޶Nͯ|GWx9f朷p{- ySeکܢD&5U:ŏҾt.3LN T͆i/Ot& JtlRRi;3 fДڹn߫jPZښgpN0R%Rm]vlئ+$[on33h`qLTKDQmۢjX}ݗ^ĥBHn1` endstream endobj 583 0 obj << /Producer (pdfTeX-1.40.21) /Creator (TeX) /CreationDate (D:20211212175750+08'00') /ModDate (D:20211212175750+08'00') /Trapped /False /PTEX.Fullbanner (This is pdfTeX, Version 3.14159265-2.6-1.40.21 (TeX Live 2020/Debian) kpathsea version 6.3.2) >> endobj 486 0 obj << /Type /ObjStm /N 92 /First 832 /Length 3488 /Filter /FlateDecode >> stream xks6~>6sx7N8W3HF\J]P"HI4kcZ}!%˘ [3)0<|;~ff:d:߂9y-[1oeODa R f % m2$Fy1&6e"̼,d1$ImY a pO80{@&%\g@8H hct ,r Q0ʃFAWPB)3-`A8T )PIkkj-h0`]tCfDM& 6hOC+cQ&r|A-H$MFt}2Vg ňHu9.dz~Pb<(fӆ_ B6TŨ8Э|8f% Ut0:xUɘCW|XY9| Ql/j+>|#u>(' 4> =0?X:PEaaa8 ?JpSsKTIQUS.}_D 9 Ïd>EKMGm7e`K(^g-'TTGO-]Vfۺku-ƇnNu d/,kN]E?}=wJ6dv[*kinNuB%˺B|S]+5܍آ?)}ZC7MeoSa})&pnkN Y(%}?܂t1()Pz} s( +$;#Yڿ̧L'7au9 @J$zLET>=E@iVs~M[0(\j)lb*[JˮZU3id7109\c PKJ8~Y/\`*r Mi=jeoqz=X"㎴h"]dmAJkxֵ HJMx`FAvS4X54*qvaGE %9;.t2w +ՁA,Y8"\_Ɏ ƫ&JFM4RXE{j iH^lq`ǫ"*(Ś` .^!nF)9:G#jMHЁƊDh jd`4Z2J1h|AR&CĤkIˢEyc7:m34wiK`-$Wj'>茒LZeҖγ:Y<[ [&D:Tf%Ogu8fu5Lc{I xӂCf!y[SWMѭhN%{X_5v*ع@XC^ -  J W8023Ekx+lÓ珞?OO7%@/p&#DK-]F]4B͆z4b~uht)tpT F}We,&x.1Kd)?16.g\BFH_,jg7ga5(v(I(6~틓\oE)p/qRmIM&-Z m𹭸F''ޞn*z0pcōJR%wM Vc[*7oz'O62kpTS9&aϗjM惘$$ACQ-tNF|do|DS#z |ZLW_u~=ϒry嫧oO6.dDkboon29XFz]6jzዧoQӷc;@\Z<./p iUmQWg_ tHö__?5O7L=/ < Q=1esJ7L4%wޝwJ۪4ppJjo\:.| &K*uٰDIhWjx'ъvZj:odv+/,Lk{-ᾃWzJ詶& =݅GJV ۳WCu*&aveMe;3Wvx>)zFnϾ;tfS3kO^g?.x截5GY| d1蘏}b]D<3ńiU <ⷌJw!R&c ࡍkڡQy(*]ӊOL <7F259C07256805479FB5C141F8A459AA>] /Length 1619 /Filter /FlateDecode >> stream x%lϛzTzwo@ -?+ZXm1f3̺ա1I?95Q>Y~dd-s1>Ks9>7<}}޽޽1|.&')<yy2xozllj4ᜧz6zd|iJ}).08 ^9'55=/+]Ց=0c!(B("J([ ꡫn5ArJ1 b?֑u;edsA-ZcO^5"Թ-^Ϻ a3_n4fhykS7vhY kVS%a$F7H({X7{;JzF?;a' Hh']0C%}a#un F$tiy=+E)8L>з1)`ʟ7pV 7r8(m1 s0 pHG_9!<"{#װ]5J1"Ԗ[Rl%|Hd6yL["ԒdU@-ɶ_.F%Oy L"oνY|Z&$E- %F[)}-e lJoXCJGH $`T#0IY9׿aeF?_\;e!lD?ђnAbg=:GmkVMBf=ի ¶ke[MbyK:GbmĮՒհ[li=^/m3({3/:BXm[֒56JdvYa`$~ϻQǏkXqI7 5}LI#ϞuLK22%k`Y{;' ]dW]lG?Hc)XP!)/"C1)F*־# X%ꡍj([aT(Ġ kԕ ATsՐw, HA]i@dIM<u%}(k Pk%]>tn=l2ނIꂎCr#l&h] -ZMүѨAߙ6 ۠$}aYۡvHX̓ox޾:@_2OB;avd^y.G$s5e%uNOh]A~ ȏKՙmpa$;W<۞OaQ-8]snLXBd_PK;2 6>V(+MtGAw++!gu.^;J6H[tW&AS:B]B:-@vUJ oGvY Qw-d;H#n9B6@^#f :Ȯk::y]Rs\f?z#5wӫRU|2W;$֫>^KnSr|ƀNi.-:W@r܌Ԗ=`6?ch endstream endobj startxref 2368410 %%EOF spatstat/inst/doc/datasets.R0000644000176200001440000004376414155343637015623 0ustar liggesusers### R code from vignette source 'datasets.Rnw' ################################################### ### code chunk number 1: datasets.Rnw:5-6 ################################################### options(SweaveHooks=list(fig=function() par(mar=c(1,1,1,1)))) ################################################### ### code chunk number 2: datasets.Rnw:27-34 ################################################### library(spatstat) sdate <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Date") sversion <- read.dcf(file = system.file("DESCRIPTION", package = "spatstat"), fields = "Version") spatstat.options(transparent=FALSE) options(useFancyQuotes=FALSE) ################################################### ### code chunk number 3: datasets.Rnw:219-237 ################################################### opa <- par() ## How to set all margins to zero and eliminate all outer spaces zeromargins <- function() { par( mar=rep(0,4), omd=c(0,1,0,1), xaxs="i", yaxs="i" ) invisible(NULL) } ## Set 'mar' setmargins <- function(...) { x <- c(...) x <- rep(x, 4)[1:4] par(mar=x) invisible(NULL) } ################################################### ### code chunk number 4: datasets.Rnw:246-247 (eval = FALSE) ################################################### ## plot(amacrine) ################################################### ### code chunk number 5: datasets.Rnw:249-251 ################################################### getOption("SweaveHooks")[["fig"]]() setmargins(0,1,2,0) plot(amacrine) ################################################### ### code chunk number 6: datasets.Rnw:260-261 (eval = FALSE) ################################################### ## plot(anemones, markscale=1) ################################################### ### code chunk number 7: datasets.Rnw:263-265 ################################################### getOption("SweaveHooks")[["fig"]]() setmargins(0,0,2,0) plot(anemones, markscale=1) ################################################### ### code chunk number 8: datasets.Rnw:278-279 (eval = FALSE) ################################################### ## ants.extra$plotit() ################################################### ### code chunk number 9: datasets.Rnw:281-283 ################################################### getOption("SweaveHooks")[["fig"]]() setmargins(0,0,1,0) ants.extra$plotit() ################################################### ### code chunk number 10: datasets.Rnw:291-292 ################################################### getOption("SweaveHooks")[["fig"]]() plot(austates) ################################################### ### code chunk number 11: datasets.Rnw:302-304 (eval = FALSE) ################################################### ## plot(bdspots, equal.scales=TRUE, pch="+", ## panel.args=function(i)list(cex=c(0.15, 0.2, 0.7)[i])) ################################################### ### code chunk number 12: datasets.Rnw:306-310 ################################################### getOption("SweaveHooks")[["fig"]]() zeromargins() plot(bdspots, equal.scales=TRUE, pch="+", main="", mar.panel=0, hsep=1, panel.args=function(i)list(cex=c(0.15, 0.2, 0.7)[i])) ################################################### ### code chunk number 13: datasets.Rnw:320-322 (eval = FALSE) ################################################### ## plot(bei.extra$elev, main="Beilschmiedia") ## plot(bei, add=TRUE, pch=16, cex=0.3) ################################################### ### code chunk number 14: datasets.Rnw:324-327 ################################################### getOption("SweaveHooks")[["fig"]]() setmargins(0,0,2,0) plot(bei.extra$elev, main="Beilschmiedia") plot(bei, add=TRUE, pch=16, cex=0.3) ################################################### ### code chunk number 15: datasets.Rnw:333-339 (eval = FALSE) ################################################### ## M <- persp(bei.extra$elev, ## theta=-45, phi=18, expand=7, ## border=NA, apron=TRUE, shade=0.3, ## box=FALSE, visible=TRUE, ## main="") ## perspPoints(bei, Z=bei.extra$elev, M=M, pch=16, cex=0.3) ################################################### ### code chunk number 16: datasets.Rnw:348-349 ################################################### getOption("SweaveHooks")[["fig"]]() plot(betacells) ################################################### ### code chunk number 17: datasets.Rnw:354-355 ################################################### getOption("SweaveHooks")[["fig"]]() plot(bramblecanes, cols=1:3) ################################################### ### code chunk number 18: datasets.Rnw:360-361 (eval = FALSE) ################################################### ## plot(split(bramblecanes)) ################################################### ### code chunk number 19: datasets.Rnw:371-372 ################################################### getOption("SweaveHooks")[["fig"]]() plot(bronzefilter,markscale=2) ################################################### ### code chunk number 20: datasets.Rnw:380-381 ################################################### getOption("SweaveHooks")[["fig"]]() plot(btb, which.marks="spoligotype", cols=2:5, chars=1:4) ################################################### ### code chunk number 21: datasets.Rnw:390-391 ################################################### getOption("SweaveHooks")[["fig"]]() plot(cells) ################################################### ### code chunk number 22: datasets.Rnw:399-400 ################################################### getOption("SweaveHooks")[["fig"]]() plot(cetaceans.extra$patterns, main="Cetaceans data", cols=1:5, hsep=1) ################################################### ### code chunk number 23: datasets.Rnw:409-412 ################################################### getOption("SweaveHooks")[["fig"]]() plot(chicago, main="Chicago Crimes", col="grey", cols=c("red", "blue", "black", "blue", "red", "blue", "blue"), chars=c(16,2,22,17,24,15,6), leg.side="left", show.window=FALSE) ################################################### ### code chunk number 24: datasets.Rnw:422-423 ################################################### getOption("SweaveHooks")[["fig"]]() chorley.extra$plotit() ################################################### ### code chunk number 25: datasets.Rnw:439-441 ################################################### getOption("SweaveHooks")[["fig"]]() plot(clmfires, which.marks="cause", cols=2:5, cex=0.25, main="Castilla-La Mancha forest fires") ################################################### ### code chunk number 26: datasets.Rnw:451-452 ################################################### getOption("SweaveHooks")[["fig"]]() plot(clmfires.extra$clmcov100$elevation, main="Elevation") ################################################### ### code chunk number 27: datasets.Rnw:463-464 ################################################### getOption("SweaveHooks")[["fig"]]() plot(concrete,chars="+",cols="blue",col="yellow") ################################################### ### code chunk number 28: datasets.Rnw:475-477 ################################################### getOption("SweaveHooks")[["fig"]]() plot(copper$Points, main="Copper") plot(copper$Lines, add=TRUE) ################################################### ### code chunk number 29: datasets.Rnw:484-486 ################################################### getOption("SweaveHooks")[["fig"]]() plot(demohyper, quote({ plot(Image, main=""); plot(Points, add=TRUE) }), parargs=list(mar=rep(1,4))) ################################################### ### code chunk number 30: datasets.Rnw:493-494 ################################################### getOption("SweaveHooks")[["fig"]]() plot(demopat) ################################################### ### code chunk number 31: datasets.Rnw:508-509 ################################################### getOption("SweaveHooks")[["fig"]]() plot(dendrite, leg.side="bottom", main="", cex=0.75, cols=2:4) ################################################### ### code chunk number 32: datasets.Rnw:517-518 ################################################### getOption("SweaveHooks")[["fig"]]() plot(finpines, main="Finnish pines") ################################################### ### code chunk number 33: datasets.Rnw:531-535 ################################################### getOption("SweaveHooks")[["fig"]]() wildM1 <- with(flu, virustype == "wt" & stain == "M2-M1") plot(flu[wildM1, 1, drop=TRUE], main=c("flu data", "wild type virus, M2-M1 stain"), chars=c(16,3), cex=0.4, cols=2:3) ################################################### ### code chunk number 34: datasets.Rnw:543-544 ################################################### getOption("SweaveHooks")[["fig"]]() plot(gordon, main="People in Gordon Square", pch=16) ################################################### ### code chunk number 35: datasets.Rnw:559-560 ################################################### getOption("SweaveHooks")[["fig"]]() plot(gorillas, which.marks=1, chars=c(1,3), cols=2:3, main="Gorilla nest sites") ################################################### ### code chunk number 36: datasets.Rnw:564-565 (eval = FALSE) ################################################### ## system.file("rawdata/gorillas/vegetation.asc", package="spatstat") ################################################### ### code chunk number 37: datasets.Rnw:574-575 ################################################### getOption("SweaveHooks")[["fig"]]() plot(hamster, cols=c(2,4)) ################################################### ### code chunk number 38: datasets.Rnw:585-586 ################################################### getOption("SweaveHooks")[["fig"]]() plot(heather$coarse) ################################################### ### code chunk number 39: datasets.Rnw:590-591 (eval = FALSE) ################################################### ## plot(heather) ################################################### ### code chunk number 40: datasets.Rnw:601-602 ################################################### getOption("SweaveHooks")[["fig"]]() plot(humberside) ################################################### ### code chunk number 41: datasets.Rnw:614-615 ################################################### getOption("SweaveHooks")[["fig"]]() plot(hyytiala, cols=2:5) ################################################### ### code chunk number 42: datasets.Rnw:624-625 ################################################### getOption("SweaveHooks")[["fig"]]() plot(japanesepines) ################################################### ### code chunk number 43: datasets.Rnw:634-635 ################################################### getOption("SweaveHooks")[["fig"]]() plot(lansing) ################################################### ### code chunk number 44: datasets.Rnw:641-642 (eval = FALSE) ################################################### ## plot(split(lansing)) ################################################### ### code chunk number 45: datasets.Rnw:649-650 ################################################### getOption("SweaveHooks")[["fig"]]() plot(longleaf) ################################################### ### code chunk number 46: datasets.Rnw:659-661 ################################################### getOption("SweaveHooks")[["fig"]]() plot(mucosa, chars=c(1,3), cols=c("red", "green")) plot(mucosa.subwin, add=TRUE, lty=3) ################################################### ### code chunk number 47: datasets.Rnw:677-680 ################################################### getOption("SweaveHooks")[["fig"]]() plot(murchison$greenstone, main="Murchison data", col="lightgreen") plot(murchison$gold, add=TRUE, pch=3, col="blue") plot(murchison$faults, add=TRUE, col="red") ################################################### ### code chunk number 48: datasets.Rnw:686-687 ################################################### reedy <- owin(c(580, 650), c(6986, 7026)) ################################################### ### code chunk number 49: datasets.Rnw:692-695 ################################################### getOption("SweaveHooks")[["fig"]]() plot(murchison$greenstone[reedy], main="Murchison data", col="lightgreen") plot(murchison$gold[reedy], add=TRUE, pch=3, col="blue") plot(murchison$faults[reedy], add=TRUE, col="red") ################################################### ### code chunk number 50: datasets.Rnw:703-704 ################################################### getOption("SweaveHooks")[["fig"]]() plot(nbfires, use.marks=FALSE, pch=".") ################################################### ### code chunk number 51: datasets.Rnw:710-711 (eval = FALSE) ################################################### ## plot(split(nbfires), use.marks=FALSE, chars=".") ################################################### ### code chunk number 52: datasets.Rnw:714-719 ################################################### getOption("SweaveHooks")[["fig"]]() par(mar=c(0,0,2,0)) plot(split(nbfires)$"2000", which.marks="fire.type", main=c("New Brunswick fires 2000", "by fire type"), cols=c("blue", "green", "red", "cyan"), leg.side="left") ################################################### ### code chunk number 53: datasets.Rnw:727-729 ################################################### getOption("SweaveHooks")[["fig"]]() plot(nztrees) plot(trim.rectangle(as.owin(nztrees), c(0,5), 0), add=TRUE, lty=3) ################################################### ### code chunk number 54: datasets.Rnw:742-743 ################################################### getOption("SweaveHooks")[["fig"]]() plot(osteo[1:4,], main.panel="", pch=21, bg='white') ################################################### ### code chunk number 55: datasets.Rnw:749-750 (eval = FALSE) ################################################### ## system.file("rawdata/osteo/osteo36.txt", package="spatstat") ################################################### ### code chunk number 56: datasets.Rnw:759-760 ################################################### getOption("SweaveHooks")[["fig"]]() plot(paracou, cols=2:3, chars=c(16,3)) ################################################### ### code chunk number 57: datasets.Rnw:768-769 ################################################### getOption("SweaveHooks")[["fig"]]() ponderosa.extra$plotit() ################################################### ### code chunk number 58: datasets.Rnw:781-782 ################################################### pyr <- pyramidal[c(FALSE,TRUE), ] ################################################### ### code chunk number 59: datasets.Rnw:785-787 ################################################### getOption("SweaveHooks")[["fig"]]() pyr$grp <- abbreviate(pyr$group, minlength=7) plot(pyr, quote(plot(Neurons, pch=16, main=grp)), main="Pyramidal Neurons") ################################################### ### code chunk number 60: datasets.Rnw:807-809 ################################################### getOption("SweaveHooks")[["fig"]]() plot(redwood) plot(redwood3, add=TRUE, pch=20) ################################################### ### code chunk number 61: datasets.Rnw:812-813 ################################################### getOption("SweaveHooks")[["fig"]]() redwoodfull.extra$plotit() ################################################### ### code chunk number 62: datasets.Rnw:827-829 ################################################### getOption("SweaveHooks")[["fig"]]() plot(as.solist(residualspaper[c("Fig1", "Fig4a", "Fig4b", "Fig4c")]), main="") ################################################### ### code chunk number 63: datasets.Rnw:837-838 ################################################### getOption("SweaveHooks")[["fig"]]() shapley.extra$plotit(main="Shapley") ################################################### ### code chunk number 64: datasets.Rnw:845-846 ################################################### getOption("SweaveHooks")[["fig"]]() plot(simdat) ################################################### ### code chunk number 65: datasets.Rnw:854-855 ################################################### getOption("SweaveHooks")[["fig"]]() plot(spiders, pch=16, show.window=FALSE) ################################################### ### code chunk number 66: datasets.Rnw:862-865 ################################################### getOption("SweaveHooks")[["fig"]]() plot(sporophores, chars=c(16,1,2), cex=0.6) points(0,0,pch=16, cex=2) text(15,8,"Tree", cex=0.75) ################################################### ### code chunk number 67: datasets.Rnw:874-875 ################################################### getOption("SweaveHooks")[["fig"]]() plot(spruces, maxsize=min(nndist(spruces))) ################################################### ### code chunk number 68: datasets.Rnw:884-885 ################################################### getOption("SweaveHooks")[["fig"]]() plot(swedishpines) ################################################### ### code chunk number 69: datasets.Rnw:894-895 ################################################### getOption("SweaveHooks")[["fig"]]() plot(urkiola, cex=0.5, cols=2:3) ################################################### ### code chunk number 70: datasets.Rnw:902-904 ################################################### getOption("SweaveHooks")[["fig"]]() par(mar=c(0,0,2,0)) plot(waka, markscale=0.04, main=c("Waka national park", "tree diameters")) ################################################### ### code chunk number 71: datasets.Rnw:911-915 ################################################### getOption("SweaveHooks")[["fig"]]() v <- rotate(vesicles, pi/2) ve <- lapply(vesicles.extra, rotate, pi/2) plot(v, main="Vesicles") plot(ve$activezone, add=TRUE, lwd=3) ################################################### ### code chunk number 72: datasets.Rnw:940-941 (eval = FALSE) ################################################### ## system.file("rawdata/vesicles/mitochondria.txt", package="spatstat") ################################################### ### code chunk number 73: datasets.Rnw:949-950 ################################################### getOption("SweaveHooks")[["fig"]]() plot(waterstriders) spatstat/inst/CITATION0000755000176200001440000000472614141377564014257 0ustar liggesuserscitHeader("To cite spatstat in publications use:") citEntry(entry = "Book", title = "Spatial Point Patterns: Methodology and Applications with {R}", author = personList(as.person("Adrian Baddeley"), as.person("Ege Rubak"), as.person("Rolf Turner")), year = "2015", publisher = "Chapman and Hall/CRC Press", address = "London", url="https://www.routledge.com/Spatial-Point-Patterns-Methodology-and-Applications-with-R/Baddeley-Rubak-Turner/9781482210200/", textVersion = paste("Adrian Baddeley, Ege Rubak, Rolf Turner (2015).", "Spatial Point Patterns: Methodology and Applications with R.", "London: Chapman and Hall/CRC Press, 2015.", "URL https://www.routledge.com/Spatial-Point-Patterns-Methodology-and-Applications-with-R/Baddeley-Rubak-Turner/9781482210200/") ) citEntry(entry = "Article", title = "Hybrids of Gibbs Point Process Models and Their Implementation", author = personList(as.person("Adrian Baddeley"), as.person("Rolf Turner"), as.person("Jorge Mateu"), as.person("Andrew Bevan")), journal = "Journal of Statistical Software", year = "2013", volume = "55", number = "11", pages = "1--43", doi = "10.18637/jss.v055.i11", textVersion = paste("Adrian Baddeley, Rolf Turner, Jorge Mateu, Andrew Bevan (2013).", "Hybrids of Gibbs Point Process Models and Their Implementation.", "Journal of Statistical Software, 55(11), 1-43.", "DOI: 10.18637/jss.v055.i11"), header = "If you use hybrid models, please also cite:" ) citEntry(entry = "Article", title = "{spatstat}: An {R} Package for Analyzing Spatial Point Patterns", author = personList(as.person("Adrian Baddeley"), as.person("Rolf Turner")), journal = "Journal of Statistical Software", year = "2005", volume = "12", number = "6", pages = "1--42", doi = "10.18637/jss.v012.i06", textVersion = paste("Adrian Baddeley, Rolf Turner (2005).", "spatstat: An R Package for Analyzing Spatial Point Patterns.", "Journal of Statistical Software 12(6), 1-42.", "DOI: 10.18637/jss.v012.i06"), header = "In survey articles, please cite the original paper on spatstat:" )