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{"cells":[{"metadata":{},"cell_type":"markdown","source":"# ** DIscBIO: a user-friendly pipeline for biomarker discovery in single-cell transcriptomics**"},{"metadata":{},"cell_type":"markdown","source":"The pipeline consists of four successive steps: data pre-processing, cellular clustering and pseudo-temporal ordering, determining differential expressed genes and identifying biomarkers."},{"metadata":{},"cell_type":"markdown","source":""},{"metadata":{},"cell_type":"markdown","source":"# CTC Notebook [PART 3]\n\n# Determining differentially expressed genes and biomarkers"},{"metadata":{},"cell_type":"markdown","source":"## Required Packages"},{"metadata":{"trusted":true},"cell_type":"code","source":"library(DIscBIO)\nlibrary(partykit)\nlibrary(enrichR)","execution_count":1,"outputs":[{"output_type":"stream","text":"Loading required package: SingleCellExperiment\n\nLoading required package: SummarizedExperiment\n\nLoading required package: MatrixGenerics\n\nLoading required package: matrixStats\n\n\nAttaching package: ‘MatrixGenerics’\n\n\nThe following objects are masked from ‘package:matrixStats’:\n\n colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,\n colCounts, colCummaxs, colCummins, colCumprods, colCumsums,\n colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,\n colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,\n colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,\n colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,\n colWeightedMeans, colWeightedMedians, colWeightedSds,\n colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,\n rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,\n rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,\n rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,\n rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,\n rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,\n rowWeightedMads, rowWeightedMeans, rowWeightedMedians,\n rowWeightedSds, rowWeightedVars\n\n\nLoading required package: GenomicRanges\n\nLoading required package: stats4\n\nLoading required package: BiocGenerics\n\nLoading required package: parallel\n\n\nAttaching package: ‘BiocGenerics’\n\n\nThe following objects are masked from ‘package:parallel’:\n\n clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,\n clusterExport, clusterMap, parApply, parCapply, parLapply,\n parLapplyLB, parRapply, parSapply, parSapplyLB\n\n\nThe following objects are masked from ‘package:stats’:\n\n IQR, mad, sd, var, xtabs\n\n\nThe following objects are masked from ‘package:base’:\n\n anyDuplicated, append, as.data.frame, basename, cbind, colnames,\n dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,\n grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,\n order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,\n rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,\n union, unique, unsplit, which.max, which.min\n\n\nLoading required package: S4Vectors\n\n\nAttaching package: ‘S4Vectors’\n\n\nThe following object is masked from ‘package:base’:\n\n expand.grid\n\n\nLoading required package: IRanges\n\nLoading required package: GenomeInfoDb\n\nLoading required package: Biobase\n\nWelcome to Bioconductor\n\n Vignettes contain introductory material; view with\n 'browseVignettes()'. To cite Bioconductor, see\n 'citation(\"Biobase\")', and for packages 'citation(\"pkgname\")'.\n\n\n\nAttaching package: ‘Biobase’\n\n\nThe following object is masked from ‘package:MatrixGenerics’:\n\n rowMedians\n\n\nThe following objects are masked from ‘package:matrixStats’:\n\n anyMissing, rowMedians\n\n\n\n\nLoading required package: grid\n\nLoading required package: libcoin\n\nLoading required package: mvtnorm\n\n\nAttaching package: ‘partykit’\n\n\nThe following object is masked from ‘package:SummarizedExperiment’:\n\n width\n\n\nThe following object is masked from ‘package:GenomicRanges’:\n\n width\n\n\nThe following object is masked from ‘package:IRanges’:\n\n width\n\n\nThe following object is masked from ‘package:S4Vectors’:\n\n width\n\n\nThe following object is masked from ‘package:BiocGenerics’:\n\n width\n\n\nWelcome to enrichR\nChecking connection ... \nConnection is Live!\n\n","name":"stderr"}]},{"metadata":{},"cell_type":"markdown","source":"## 3. Determining differentially expressed genes (DEGs) For K-means Clustering"},{"metadata":{},"cell_type":"markdown","source":"Differentially expressed genes between individual clusters are identified using the significance analysis of sequencing data (SAMseq), which is a new function in significance analysis of microarrays (Li and Tibshirani 2011) in the samr package v2.0 (Tibshirani et all., 2015). SAMseq is a non-parametric statistical function dependent on Wilcoxon rank statistic that equalizes the sizes of the library by a resampling method accounting for the various sequencing depths. The analysis is implemented over the pure raw dataset that has the unnormalized expression read counts after excluding the ERCCs. Furthermore, DEGs in each cluster comparing to all the remaining clusters are determined using binomial differential expression, which is based on binomial counting statistics."},{"metadata":{},"cell_type":"markdown","source":""},{"metadata":{},"cell_type":"markdown","source":"## 3.1 Identifying DEGs using SAMseq"},{"metadata":{},"cell_type":"markdown","source":"The user can define DEGs between all clusters generated by either K-means or model based clustering by applying the “DEGanalysis” function. Another alternative is to define DEGs between particular clusters generated by K-means clustering by applying the “DEGanalysis2clust” function. The outcome of these two functions is a list of two components:\n- The first component is a data frame showing the Ensembl gage name and the symbole of the detected DEGs\n- The second component is table showing the comparisons, Target cluster, Number of genes and the File name. This component will be used for the downstream analysis."},{"metadata":{"scrolled":false,"trusted":true},"cell_type":"code","source":"load(\"SC.RData\") # Loading the \"SC\" object that has include the data of the k-means clustering \nload(\"Ndata.RData\") # Loading the \"Ndata\" object and stored in the @ndata will be used to plot the expression of genes \nload(\"expdata.RData\") # Loading the \"expdata\" object and stored in the @expdata will be used to plot the expression of genes \nsc<-SC # Storing the data of SC in the sc \nsc@ndata<-Ndata\nsc@expdata<-expdata\n\n########## Removing the unneeded objects\nrm(Ndata)\nrm(expdata)\nrm(SC) ","execution_count":2,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Identifying DEGs using binomial differential expression"},{"metadata":{},"cell_type":"markdown","source":"The function ClustDiffGenes identifies differentially regulated genes for each cluster of the K-means clustering in \ncomparison to the ensemble of all cells. It returns a list with a data.frame element for each cluster that contains the mean expression across all cells not in the cluster (mean.ncl) and in the cluster (mean.cl), the fold-change in the cluster versus all remaining cells (fc), and the p-value for differential expression between all cells in a cluster and all remaining cells. The p-value is computed based on the overlap of negative binomials fitted to the count distributions within the two groups akin to DESeq."},{"metadata":{"trusted":true},"cell_type":"code","source":"cdiffBinomial<-ClustDiffGenes(sc,K=4,export = T,fdr=.01,quiet=T) ########## Binomial differential expression analysis\n#### To show the result table\nhead(cdiffBinomial[[1]]) # The first component \nhead(cdiffBinomial[[2]]) # The second component","execution_count":3,"outputs":[{"output_type":"display_data","data":{"text/html":"<table>\n<caption>A matrix: 6 × 2 of type chr</caption>\n<thead>\n\t<tr><th scope=col>DEGsE</th><th scope=col>DEGsS</th></tr>\n</thead>\n<tbody>\n\t<tr><td>ENSG00000001630</td><td>CYP51A1</td></tr>\n\t<tr><td>ENSG00000002586</td><td>CD99 </td></tr>\n\t<tr><td>ENSG00000003402</td><td>CFLAR </td></tr>\n\t<tr><td>ENSG00000003436</td><td>TFPI </td></tr>\n\t<tr><td>ENSG00000003756</td><td>RBM5 </td></tr>\n\t<tr><td>ENSG00000004059</td><td>ARF5 </td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA matrix: 6 × 2 of type chr\n\n| DEGsE | DEGsS |\n|---|---|\n| ENSG00000001630 | CYP51A1 |\n| ENSG00000002586 | CD99 |\n| ENSG00000003402 | CFLAR |\n| ENSG00000003436 | TFPI |\n| ENSG00000003756 | RBM5 |\n| ENSG00000004059 | ARF5 |\n\n","text/latex":"A matrix: 6 × 2 of type chr\n\\begin{tabular}{ll}\n DEGsE & DEGsS\\\\\n\\hline\n\t ENSG00000001630 & CYP51A1\\\\\n\t ENSG00000002586 & CD99 \\\\\n\t ENSG00000003402 & CFLAR \\\\\n\t ENSG00000003436 & TFPI \\\\\n\t ENSG00000003756 & RBM5 \\\\\n\t ENSG00000004059 & ARF5 \\\\\n\\end{tabular}\n","text/plain":" DEGsE DEGsS \n[1,] ENSG00000001630 CYP51A1\n[2,] ENSG00000002586 CD99 \n[3,] ENSG00000003402 CFLAR \n[4,] ENSG00000003436 TFPI \n[5,] ENSG00000003756 RBM5 \n[6,] ENSG00000004059 ARF5 "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<table>\n<caption>A data.frame: 4 × 6</caption>\n<thead>\n\t<tr><th></th><th scope=col>Target Cluster</th><th scope=col>VS</th><th scope=col>Gene number</th><th scope=col>File name</th><th scope=col>Gene number</th><th scope=col>File name</th></tr>\n\t<tr><th></th><th scope=col><chr></th><th scope=col><chr></th><th scope=col><int></th><th scope=col><chr></th><th scope=col><int></th><th scope=col><chr></th></tr>\n</thead>\n<tbody>\n\t<tr><th scope=row>1</th><td>Cluster 1</td><td>Remaining Clusters</td><td>1052</td><td>Up-DEG-cluster1.csv</td><td>678</td><td>Down-DEG-cluster1.csv</td></tr>\n\t<tr><th scope=row>2</th><td>Cluster 2</td><td>Remaining Clusters</td><td> 0</td><td>Up-DEG-cluster2.csv</td><td> 1</td><td>Down-DEG-cluster2.csv</td></tr>\n\t<tr><th scope=row>3</th><td>Cluster 3</td><td>Remaining Clusters</td><td> 2</td><td>Up-DEG-cluster3.csv</td><td> 5</td><td>Down-DEG-cluster3.csv</td></tr>\n\t<tr><th scope=row>4</th><td>Cluster 4</td><td>Remaining Clusters</td><td> 1</td><td>Up-DEG-cluster4.csv</td><td> 1</td><td>Down-DEG-cluster4.csv</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 4 × 6\n\n| <!--/--> | Target Cluster <chr> | VS <chr> | Gene number <int> | File name <chr> | Gene number <int> | File name <chr> |\n|---|---|---|---|---|---|---|\n| 1 | Cluster 1 | Remaining Clusters | 1052 | Up-DEG-cluster1.csv | 678 | Down-DEG-cluster1.csv |\n| 2 | Cluster 2 | Remaining Clusters | 0 | Up-DEG-cluster2.csv | 1 | Down-DEG-cluster2.csv |\n| 3 | Cluster 3 | Remaining Clusters | 2 | Up-DEG-cluster3.csv | 5 | Down-DEG-cluster3.csv |\n| 4 | Cluster 4 | Remaining Clusters | 1 | Up-DEG-cluster4.csv | 1 | Down-DEG-cluster4.csv |\n\n","text/latex":"A data.frame: 4 × 6\n\\begin{tabular}{r|llllll}\n & Target Cluster & VS & Gene number & File name & Gene number & File name\\\\\n & <chr> & <chr> & <int> & <chr> & <int> & <chr>\\\\\n\\hline\n\t1 & Cluster 1 & Remaining Clusters & 1052 & Up-DEG-cluster1.csv & 678 & Down-DEG-cluster1.csv\\\\\n\t2 & Cluster 2 & Remaining Clusters & 0 & Up-DEG-cluster2.csv & 1 & Down-DEG-cluster2.csv\\\\\n\t3 & Cluster 3 & Remaining Clusters & 2 & Up-DEG-cluster3.csv & 5 & Down-DEG-cluster3.csv\\\\\n\t4 & Cluster 4 & Remaining Clusters & 1 & Up-DEG-cluster4.csv & 1 & Down-DEG-cluster4.csv\\\\\n\\end{tabular}\n","text/plain":" Target Cluster VS Gene number File name Gene number\n1 Cluster 1 Remaining Clusters 1052 Up-DEG-cluster1.csv 678 \n2 Cluster 2 Remaining Clusters 0 Up-DEG-cluster2.csv 1 \n3 Cluster 3 Remaining Clusters 2 Up-DEG-cluster3.csv 5 \n4 Cluster 4 Remaining Clusters 1 Up-DEG-cluster4.csv 1 \n File name \n1 Down-DEG-cluster1.csv\n2 Down-DEG-cluster2.csv\n3 Down-DEG-cluster3.csv\n4 Down-DEG-cluster4.csv"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"### Plotting the DEGs"},{"metadata":{},"cell_type":"markdown","source":"Volcano plots are used to readily show the DEGs by plotting significance versus fold-change on the y and x axes, respectively."},{"metadata":{"trusted":true},"cell_type":"code","source":"name<-cdiffBinomial[[2]][1,6] ############ Selecting the DEGs' ############## Down-DEG-cluster1.csv\nU<-read.csv(file=paste0(name),head=TRUE,sep=\",\")\nVplot<-VolcanoPlot(U,value=0.0001,name=name,FS=0.7,fc=0.75)","execution_count":4,"outputs":[{"output_type":"display_data","data":{"text/plain":"plot without title","image/png":"iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAIAAAByhViMAAAACXBIWXMAABJ0AAASdAHeZh94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\nzJpCYcrAZKeMBPfYAQAAlE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hWLraNus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A9mX+7Kuf2tw5tfRIZwqziDtaNXVmA2WYwV5qvsRtU2DAy/uVqAoxRG/01Q+oM0+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\nY01OezBveTCTxhifidiRsOLby1Sc5OJdZu4eu2NXh2/0z6slqt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4AQo3wgBl15P6H/E81FVy7XhaD5nkDzPtj0olfE2Y1WkYbOgiyH+TZ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\nddKura0dMGBAi2mPGTOGEPLll18a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4. Identifying biomarkers (decision trees and networking analysis) "},{"metadata":{},"cell_type":"markdown","source":"There are several methods to identify biomarkers, among them are decision trees and hub detection through networking analysis. The outcome of STRING analysis is stored in tab separated values (TSV) files. These TSV files served as an input to check both the connectivity degree and the betweenness centrality, which reflects the communication flow in the defined PPI networks "},{"metadata":{},"cell_type":"markdown","source":""},{"metadata":{},"cell_type":"markdown","source":"Decision trees are one of the most efficient classification techniques in biomarkers discovery. Here we use it to predict the sub-population of a target cell based on transcriptomic data. Two types of decision trees can be performed: classification and regression trees (CART) and J48. The decision tree analysis is implemented over a training dataset, which consisted of the DEGs obtained by either SAMseq or the binomial differential expression. The performance of the generated trees can be evaluated for error estimation by ten-fold cross validation assessment using the \"J48DTeval\" and \"RpartEVAL\" functions. The decision tree analysis requires the dataset to be class vectored by applying the “ClassVectoringDT” function."},{"metadata":{"trusted":true},"cell_type":"code","source":"###################### Finding biomarker genes between cluster 1 and cluster 4\nFirst=\"CL1\"\nSecond=\"CL4\"\nload(\"DATAforDT.RData\")","execution_count":5,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### 4.1. J48 Decision Tree"},{"metadata":{"trusted":true},"cell_type":"code","source":"j48dt<-J48DT(DATAforDT) #J48 Decision Tree\nsummary(j48dt) \nrm(j48dt)","execution_count":6,"outputs":[{"output_type":"stream","text":"J48 pruned tree\n------------------\n\nMALAT1 <= 102.794044: CL1 (344.0/1.0)\nMALAT1 > 102.794044\n| CA1 <= 0.103233: CL4 (693.0)\n| CA1 > 0.103233\n| | SLC25A39 <= 6.310579: CL4 (17.0)\n| | SLC25A39 > 6.310579: CL1 (8.0/1.0)\n\nNumber of Leaves : \t4\n\nSize of the tree : \t7\n\n","name":"stdout"},{"output_type":"display_data","data":{"text/plain":"\n=== Summary ===\n\nCorrectly Classified Instances 1060 99.8117 %\nIncorrectly Classified Instances 2 0.1883 %\nKappa statistic 0.9957\nMean absolute error 0.0035\nRoot mean squared error 0.042 \nRelative absolute error 0.7976 %\nRoot relative squared error 8.9321 %\nTotal Number of Instances 1062 \n\n=== Confusion Matrix ===\n\n a b <-- classified as\n 350 0 | a = CL1\n 2 710 | b = CL4"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"plot without title","image/png":"iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAMAAADKOT/pAAADAFBMVEUAAAABAQECAgIDAwME\nBAQFBQUGBgYHBwcICAgJCQkKCgoLCwsMDAwNDQ0ODg4PDw8QEBARERESEhITExMUFBQVFRUW\nFhYXFxcYGBgZGRkaGhobGxscHBwdHR0eHh4fHx8gICAhISEiIiIjIyMkJCQlJSUmJiYnJyco\nKCgpKSkqKiorKyssLCwtLS0uLi4vLy8wMDAxMTEyMjIzMzM0NDQ1NTU2NjY3Nzc4ODg5OTk6\nOjo7Ozs8PDw9PT0+Pj4/Pz9AQEBBQUFCQkJDQ0NERERFRUVGRkZHR0dISEhJSUlKSkpLS0tM\nTExNTU1OTk5PT09QUFBRUVFSUlJTU1NUVFRVVVVWVlZXV1dYWFhZWVlaWlpbW1tcXFxdXV1e\nXl5fX19gYGBhYWFiYmJjY2NkZGRlZWVmZmZnZ2doaGhpaWlqampra2tsbGxtbW1ubm5vb29w\ncHBxcXFycnJzc3N0dHR1dXV2dnZ3d3d4eHh5eXl6enp7e3t8fHx9fX1+fn5/f3+AgICBgYGC\ngoKDg4OEhISFhYWGhoaHh4eIiIiJiYmKioqLi4uMjIyNjY2Ojo6Pj4+QkJCRkZGSkpKTk5OU\nlJSVlZWWlpaXl5eYmJiZmZmampqbm5ucnJydnZ2enp6fn5+goKChoaGioqKjo6OkpKSlpaWm\npqanp6eoqKipqamqqqqrq6usrKytra2urq6vr6+wsLCxsbGysrKzs7O0tLS1tbW2tra3t7e4\nuLi5ubm6urq7u7u8vLy9vb2+vr6/v7/AwMDBwcHCwsLDw8PExMTFxcXGxsbHx8fIyMjJycnK\nysrLy8vMzMzNzc3Ozs7Pz8/Q0NDR0dHS0tLT09PU1NTV1dXW1tbX19fY2NjZ2dna2trb29vc\n3Nzd3d3e3t7f39/g4ODh4eHi4uLj4+Pk5OTl5eXm5ubn5+fo6Ojp6enq6urr6+vs7Ozt7e3u\n7u7v7+/w8PDx8fHy8vLz8/P09PT19fX29vb39/f4+Pj5+fn6+vr7+/v8/Pz9/f3+/v7////i\nsF19AAAACXBIWXMAABJ0AAASdAHeZh94AAAgAElEQVR4nO2dd2AU1RbGz24aIYVAAklooUSK\nKC0KARGQIkUpIr0YFClKVZ5EKSKKgqKiYi8gggiooCAPBRSsPAtSxQIIKojSRDok2Xnbe3Z3\ndu/Mvefu+f3B7s7Mzv0+9nzZnZk794JCEETEAG8BBCEDFCSCYAAFiSAYQEEiCAZQkAiCARQk\ngmAABYkgGEBBIggGUJAIggEUJIJgAAWJIBhAQSIIBlCQCIIBFCSCYAAFiSAYQEEiCAZQkAiC\nARQkgmAABYkgGEBBIggGUJAIggEUJIJgAAWJIBhAQSIIBlCQCIIBFCSCYAAFiSAYQEEiCAZQ\nkAiCARQkgmAABYkgGEBBIggGyBeke6AU7uGtjJAY+YI09Mbv/HLjUN7KCImRMEilBKa05QTB\nAAoSQTCAgkQQDKAgEQQDJA7Su2NaJkE/3+UEwR6Jg5QHqXUoSIQ+SBykjXtMqylIhD5IHCQz\nFCRCJyhIBMEAChJBMECyIJ3bubpVaUFqtXrnOQ6SiKhAmiDtXT7z1tZVABKTSwtSciJAlda3\nzly+l4M8QnIkCJJpz7JJ7dMgrfnAaa9/fjjQT7vDn78+bWBz86btJy3bY+IglZAW7EH6/bUB\nlaC8ORjOr5ngx0h7zcErD5UGvPa7TiIJ+cEcpLPvjakLlQbO9/ypFuLJhr3zB1aCumPeO6up\nRCJaQBukS2sGJZftNGebzy+00M/ambbN6VQ2edCaSxpJJKIIpEH6blxmwo0Lz/hb5eprV1DQ\nHmoUFEz0Wu7B+VVDypYfsp4OmIjIwBikww/mxLR77Z9S1joDM8V+i3mO13Jv/nmtXUzOg4fZ\naiSiDHxB2jo4PnfOodLXh3MbxaE5ufGDt0ami4hqsAXpyy6GDv8tCbRFePcjlfy3g6HLl+Hr\nIqIcXEH6vrPh5u+DbBP2jX3f32zoHGznBOEfTEE6dIux2/agW0Vwh+z2bsZbAvxoJIhSwROk\nosdT8j4NYbsRpY1rNyKEN3+al/J4UaRKiSgETZC2Ny3/YsBjIwcn/A9r9913J0J5d8mL5ZsG\n/9YjCC+QBKnk0fheOp2gPtwr/tGQEksQLnAE6Win1Df0a+2N1E5H9WuNkAIUQdqa02SPnu3t\naZJDF5UIVWAI0prkgTrfkXduYPIafVskkIMgSItjp+neFc40LXax3m0SmBE/SItinubR7NMx\ni3g0SyBF+CCtiH2WT8PPxq7g0zCBEdGD9E3Zmbyanln2G15NE+gQPEhHqnAcRGtolSP8Gidw\nIXaQTF0an+fX+vnGXeiGPyI0xA7Sq0k/82z+56RXeTZPIELoIB2v+ChfAbMr0I87IiSEDtK4\nBpzHJbnUYBxfAQQWRA7SsaTlvCUsK0tfSUQoiByk6bWKeUsozp3OWwKBApGDVJ1LlwZPnq7O\nWwGBAoGDdAS2BVh7HiDmD9vT+gCrbc9mAvzkWF3OfWvbin/cb5hd6z3JrF+2wt9hyieiCoGD\n9FH8xQBrz0MsPGh99oX5mS1IppoGmOhY7R4k+4qzBRaSoK/lYYf3JLN+uRi/LnwHRPQgcJBm\nNwm09jzkNKphvV46NK6LPUgfwtDMjIv21e5BcluhKDlgv9fWa5JZ/zTmfAaewIHAQep/W6C1\n5iDNA8u3xb9JNxfYg3QzfHk3LLWvdg+S2wq3ICmeg4P759YBKmUTUYnAQar3TKC15iD9U6av\n+ckLsNYepL/i6ig7oZ19tVuQ3FeoDdLT9VULJ6IQcYN0JuazQKvNQVIGxx9TlLzqJfYgzYJH\nFKWpYY9ttVuQ3FeoDdKnMX6H6icID8QN0lYIeC3UEqRN8KR5s+mKLUim2saDivIMFNpWu4Lk\nsUJtkAKfOyQIG+IG6YTh20CrLUFSLmug3Gn8zR6kDdDJ/O+x+MxLimeQPFaoDdI3hpDGwyOi\nHHGDpOS8EmitNUiPwidp5pDYgtQX3rKsuBneVjyD5LFCbZBerhGGdCLqEDhIPUYHWmsN0l9x\nVWG5PUhH4h2XWjsqHkHyXKE2SHf2DNsAEUUIHKTpLQOttQZJuQksl4esQZoDecOsVDT86hEk\nzxVqg9TigfAdENGDwEF6LynQyMG2IP268mvFHqS68LVtzVSY7BEkzxUqg1SS/H4Y0omoQ+Ag\nHYBAt8eed0xpqdiCtBGutL/ab8guMq+OK7CxznOFW5C8Jpn1y0/wW9gGiChC4CApFQKN9+0d\npIHg7CveEVZY+rTa6eW5wi1IXpPM+uWNCuFpJ6IMkYM06mreCsyHSHfwVkCgQOQg7YvZxFvC\nxphfeEsgUCBykJQ+7XkraN+HtwICB0IH6Zcyy/gKWBr/I18BBBaEDpIyrfJxns0frzyNZ/ME\nIsQO0vkrenAc69TU4wqO47wSqBA7SMoPZR/j1/hjZX/g1ziBC8GDpLwVs5JX0ytj3uLVNIEO\n0YOkzEz8mE/DHydym1CGwIfwQVL+k7SBR7Mbkv7Do1kCKeIHyTQxgcPUeSsSJtKULkToiB8k\nRXkk5nG9m3w85hG9myRQgyFIyluJg3QdgeTMoEQ6z0CoAkWQlO9r1tuqX2tb69X8Xr/WCCnA\nESTlZN/4h4v0aaro4fi+J/VpipAHJEFSlMUVGn+tRztfN66wWI92CLlAEyTlrwHGYX9p3sgw\n4wDNGyEkBE+QFOWThikPnNKygVMPpDT8RMsGCGnBFCSl+LVq6Y/8q9Xe/30kvdpr3OcIJHCC\nKkiKcv6ZqmmFB7XY88HCtKrPUGdvIkyQBUlRLr52eVzfTwIN1BUGJZ/0jbv8tUDzmhFEQNAF\nSVFM63rGVLuH4XWlrfdUi+m5jnoEERGAMEhmjr10jaH+dCbjkvz2VBO4fPafLHZFRDE4g2Rm\nz4P1DFdN/uRCJPu48Mnkqwz1OsZMp28jIkLQBsnM9/e3iC3b+YntYcXAtP2JzmVjW9z/vaKs\nTu13lrU2IsrAHCQzJ1eOrgPl209atlfNu/Yum9S+PNQZvdLeFWh7jSY0MDEREciDZOE3cyzS\nIK3dnU+8t/Nc4E3P7XzviTvbmTc2R889OkfbZv9PU42E7EgQJCt7lxXe1DAJoEqrm++Y9vSb\n67/btm/f0RNnzpw4um/ftu/Wv/n0tDtublUFIKnhTYV+vr4u3pawkINqQhpkCZKNw18sfGBM\n/+uuzAZP4rKvvK7/mAcWfnG41Le+FDuO8cUpIpqQK0gODsHmE3/s+/k7Mz/v++NESHdFfFS+\nC909QYSLnEF6v2wYNy/tqV/3J/ZSiOhAziDdf0047/r3xgqchv4i0CNnkLqOD+ttxYWxTwff\niiB8kTNIWYHm+gvE4jIjLjFVQkQJUgbpd9gd7lu/zLz2CEspRJQgZZBWJId/f94febV3MZRC\nRAlSBmlK6wjefObm5PeYKSGiBSmD1OnuSN5tmh0znZEQImqQMkgV34zs/W+X7R+k0x5BeCJj\nkPZDpBdWt+U0+Z2JFCJakDFIb6dG3GvuaOvK37CQQkQLMgbp3usi38eFW8uEey2KiEZkDFIH\nJlOEvRRXSN3BiVCRMEimdDZzsnyY1lWzwSgJ2ZAwSHthD5sd/VLvyl/Z7ImQHgmDtLQcq0GB\nTnRIp6HAiZCQMEj3tGe2q+LC2HnMdkbIjIRBalfIcGevxFN3cCIE5AuSKW05y919kdmauoMT\nQZEvSD8D2zMEfzSt/QPTHRIyIl+QllRgPADx6ZtS3me7R0I+5AvSxOtZ79E0O3Y2630SkiFf\nkNpMZr/PZWUHUHdwIhDSBa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R/Vo6GiB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\nhr3O53htB3GBpASjwgWSivJD4CC9m7fJ9dynMwUW20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TWw2c1kiAFcYHkwyMX4rjwQ+AgVb7B9bxrZZ/VSIIUxAWSD49ciOPCD4GDFHeb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"},"metadata":{"image/png":{"width":420,"height":420}}}]},{"metadata":{},"cell_type":"markdown","source":"### 4.2. RPART Decision Tree"},{"metadata":{"trusted":true},"cell_type":"code","source":"rpartDT<-RpartDT(DATAforDT)\nrm(rpartDT)","execution_count":7,"outputs":[{"output_type":"stream","text":"n= 1062 \n\nnode), split, n, loss, yval, (yprob)\n * denotes terminal node\n\n 1) root 1062 350 CL4 (0.329566855 0.670433145) \n 2) MALAT1< 104.7847 344 1 CL1 (0.997093023 0.002906977) \n 4) SYNE2< 12.34286 343 0 CL1 (1.000000000 0.000000000) *\n 5) SYNE2>=12.34286 1 0 CL4 (0.000000000 1.000000000) *\n 3) MALAT1>=104.7847 718 7 CL4 (0.009749304 0.990250696) \n 6) SLC25A39>=7.9044 8 1 CL1 (0.875000000 0.125000000) \n 12) CFLAR< 4.819648 7 0 CL1 (1.000000000 0.000000000) *\n 13) CFLAR>=4.819648 1 0 CL4 (0.000000000 1.000000000) *\n 7) SLC25A39< 7.9044 710 0 CL4 (0.000000000 1.000000000) *\n","name":"stdout"},{"output_type":"display_data","data":{"text/plain":"plot without title","image/png":"iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAIAAAByhViMAAAACXBIWXMAABJ0AAASdAHeZh94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\nU1sj6lF0fOzLLt3MnRfNqV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Bw88PT3N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ftHOZbuLuSV+fn6dOzfy4FApQefCTlFR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\nAACgCRR2AAAAADSBwg4AAACAJv4HFxgibYC24XQAAAAASUVORK5CYII="},"metadata":{"image/png":{"width":420,"height":420}}}]},{"metadata":{},"cell_type":"markdown","source":"### 4.3. Networking Analysis"},{"metadata":{},"cell_type":"markdown","source":"To define protein-protein interactions (PPI) over a list of genes, STRING-api is used. The outcome of STRING analysis was stored in tab separated values (TSV) files. These TSV files served as an input to check both the connectivity degree and the betweenness centrality, which reflects the communication flow in the defined PPI networks."},{"metadata":{"trusted":true},"cell_type":"code","source":"DEGs=\"All_DEGs\"\nFileName=paste0(DEGs)\n\ndata<-cdiffBinomial[[1]] [1:200,2] # DEGs gene list from Binomial analysis (taking only the firat 200 genes)\n\nppi<-PPI(data,FileName)\n\nnetworking<-NetAnalysis(ppi)\nnetworking ##### In case the Examine response components = 200 and an error \"linkmat[i, ]\" appeared, that means there are no PPI.","execution_count":8,"outputs":[{"output_type":"stream","text":"Retrieving URL. Please wait...\n\nSuccessful retrieval.\n\n\n\u001b[36m──\u001b[39m \u001b[1m\u001b[1mColumn specification\u001b[1m\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\ncols(\n stringId_A = \u001b[31mcol_character()\u001b[39m,\n stringId_B = \u001b[31mcol_character()\u001b[39m,\n preferredName_A = \u001b[31mcol_character()\u001b[39m,\n preferredName_B = \u001b[31mcol_character()\u001b[39m,\n ncbiTaxonId = \u001b[32mcol_double()\u001b[39m,\n score = \u001b[32mcol_double()\u001b[39m,\n nscore = \u001b[32mcol_double()\u001b[39m,\n fscore = \u001b[32mcol_double()\u001b[39m,\n pscore = \u001b[32mcol_double()\u001b[39m,\n ascore = \u001b[32mcol_double()\u001b[39m,\n escore = \u001b[32mcol_double()\u001b[39m,\n dscore = \u001b[32mcol_double()\u001b[39m,\n tscore = \u001b[32mcol_double()\u001b[39m\n)\n\n\nNumber of nodes: 174\n\nNumber of links: 451\n\nLink Density: 2.59195402298851\n\nThe connectance of the graph: 0.0149823931964654\n\nMean Distences2.52208201892744\n\nAverage Path Length2.52208201892744\n\n\n","name":"stderr"},{"output_type":"display_data","data":{"text/html":"<table>\n<caption>A data.frame: 174 × 3</caption>\n<thead>\n\t<tr><th></th><th scope=col>names</th><th scope=col>degree</th><th scope=col>betweenness</th></tr>\n\t<tr><th></th><th scope=col><chr></th><th scope=col><dbl></th><th scope=col><dbl></th></tr>\n</thead>\n<tbody>\n\t<tr><th scope=row>74</th><td>HSP90AA1 </td><td>29</td><td>818.84444</td></tr>\n\t<tr><th scope=row>85</th><td>ACTB </td><td>24</td><td>389.53333</td></tr>\n\t<tr><th scope=row>134</th><td>RHOA </td><td>22</td><td> 0.00000</td></tr>\n\t<tr><th scope=row>83</th><td>FYN </td><td>18</td><td>105.71667</td></tr>\n\t<tr><th scope=row>125</th><td>CD44 </td><td>16</td><td> 55.25000</td></tr>\n\t<tr><th scope=row>24</th><td>VCL </td><td>15</td><td> 0.00000</td></tr>\n\t<tr><th scope=row>31</th><td>ENO1 </td><td>15</td><td> 82.85556</td></tr>\n\t<tr><th scope=row>79</th><td>CS </td><td>15</td><td>237.03889</td></tr>\n\t<tr><th scope=row>127</th><td>RPS20 </td><td>15</td><td> 26.20000</td></tr>\n\t<tr><th scope=row>20</th><td>TNFRSF1A </td><td>14</td><td> 98.58333</td></tr>\n\t<tr><th scope=row>72</th><td>HSPA5 </td><td>14</td><td>160.82222</td></tr>\n\t<tr><th scope=row>87</th><td>TFRC </td><td>14</td><td>191.15000</td></tr>\n\t<tr><th scope=row>105</th><td>EIF3I </td><td>13</td><td> 84.65000</td></tr>\n\t<tr><th scope=row>52</th><td>SDHA </td><td>12</td><td> 28.73889</td></tr>\n\t<tr><th scope=row>114</th><td>ACTN1 </td><td>12</td><td> 61.95000</td></tr>\n\t<tr><th scope=row>43</th><td>ITGA2B </td><td>11</td><td> 76.75000</td></tr>\n\t<tr><th scope=row>66</th><td>CTNNA1 </td><td>11</td><td> 47.00000</td></tr>\n\t<tr><th scope=row>113</th><td>NME1-NME2</td><td>11</td><td> 56.28333</td></tr>\n\t<tr><th scope=row>128</th><td>MDH1 </td><td>11</td><td> 24.41667</td></tr>\n\t<tr><th scope=row>129</th><td>RPL18 </td><td>11</td><td> 20.25000</td></tr>\n\t<tr><th scope=row>131</th><td>CAPZB </td><td>11</td><td> 0.00000</td></tr>\n\t<tr><th scope=row>144</th><td>RPS5 </td><td>11</td><td> 0.00000</td></tr>\n\t<tr><th scope=row>12</th><td>PSMA4 </td><td>10</td><td> 0.00000</td></tr>\n\t<tr><th scope=row>30</th><td>SLC11A1 </td><td>10</td><td> 10.25000</td></tr>\n\t<tr><th scope=row>119</th><td>RPL31 </td><td>10</td><td> 16.48333</td></tr>\n\t<tr><th scope=row>35</th><td>SEC61A1 </td><td> 9</td><td> 11.36667</td></tr>\n\t<tr><th scope=row>64</th><td>ITGB5 </td><td> 9</td><td> 26.03333</td></tr>\n\t<tr><th scope=row>102</th><td>SLC25A5 </td><td> 9</td><td> 26.06667</td></tr>\n\t<tr><th scope=row>104</th><td>CTSA </td><td> 9</td><td> 35.14444</td></tr>\n\t<tr><th scope=row>115</th><td>CD59 </td><td> 9</td><td> 23.00000</td></tr>\n\t<tr><th scope=row>⋮</th><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n\t<tr><th scope=row>172</th><td>TPD52 </td><td>2</td><td>0</td></tr>\n\t<tr><th scope=row>6</th><td>CX3CL1 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>9</th><td>SYPL1 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>11</th><td>MAP4K5 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>21</th><td>PTPN18 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>29</th><td>TFPI </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>32</th><td>TBPL1 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>53</th><td>DGKG </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>54</th><td>MGLL </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>70</th><td>DCBLD2 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>78</th><td>JARID2 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>97</th><td>INPP5A </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>110</th><td>CD99 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>126</th><td>KLF6 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>132</th><td>ELOVL5 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>140</th><td>RASGRP2</td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>142</th><td>STXBP2 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>145</th><td>MRPS24 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>149</th><td>FCN1 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>157</th><td>CCDC88C</td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>158</th><td>ABHD5 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>159</th><td>SH3YL1 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>160</th><td>KAT6A </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>161</th><td>RBM5 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>163</th><td>IGF2BP2</td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>164</th><td>FAT1 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>169</th><td>JMJD4 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>170</th><td>RNH1 </td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>173</th><td>ST3GAL6</td><td>1</td><td>0</td></tr>\n\t<tr><th scope=row>174</th><td>ST3GAL1</td><td>1</td><td>0</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 174 × 3\n\n| <!--/--> | names <chr> | degree <dbl> | betweenness <dbl> |\n|---|---|---|---|\n| 74 | HSP90AA1 | 29 | 818.84444 |\n| 85 | ACTB | 24 | 389.53333 |\n| 134 | RHOA | 22 | 0.00000 |\n| 83 | FYN | 18 | 105.71667 |\n| 125 | CD44 | 16 | 55.25000 |\n| 24 | VCL | 15 | 0.00000 |\n| 31 | ENO1 | 15 | 82.85556 |\n| 79 | CS | 15 | 237.03889 |\n| 127 | RPS20 | 15 | 26.20000 |\n| 20 | TNFRSF1A | 14 | 98.58333 |\n| 72 | HSPA5 | 14 | 160.82222 |\n| 87 | TFRC | 14 | 191.15000 |\n| 105 | EIF3I | 13 | 84.65000 |\n| 52 | SDHA | 12 | 28.73889 |\n| 114 | ACTN1 | 12 | 61.95000 |\n| 43 | ITGA2B | 11 | 76.75000 |\n| 66 | CTNNA1 | 11 | 47.00000 |\n| 113 | NME1-NME2 | 11 | 56.28333 |\n| 128 | MDH1 | 11 | 24.41667 |\n| 129 | RPL18 | 11 | 20.25000 |\n| 131 | CAPZB | 11 | 0.00000 |\n| 144 | RPS5 | 11 | 0.00000 |\n| 12 | PSMA4 | 10 | 0.00000 |\n| 30 | SLC11A1 | 10 | 10.25000 |\n| 119 | RPL31 | 10 | 16.48333 |\n| 35 | SEC61A1 | 9 | 11.36667 |\n| 64 | ITGB5 | 9 | 26.03333 |\n| 102 | SLC25A5 | 9 | 26.06667 |\n| 104 | CTSA | 9 | 35.14444 |\n| 115 | CD59 | 9 | 23.00000 |\n| ⋮ | ⋮ | ⋮ | ⋮ |\n| 172 | TPD52 | 2 | 0 |\n| 6 | CX3CL1 | 1 | 0 |\n| 9 | SYPL1 | 1 | 0 |\n| 11 | MAP4K5 | 1 | 0 |\n| 21 | PTPN18 | 1 | 0 |\n| 29 | TFPI | 1 | 0 |\n| 32 | TBPL1 | 1 | 0 |\n| 53 | DGKG | 1 | 0 |\n| 54 | MGLL | 1 | 0 |\n| 70 | DCBLD2 | 1 | 0 |\n| 78 | JARID2 | 1 | 0 |\n| 97 | INPP5A | 1 | 0 |\n| 110 | CD99 | 1 | 0 |\n| 126 | KLF6 | 1 | 0 |\n| 132 | ELOVL5 | 1 | 0 |\n| 140 | RASGRP2 | 1 | 0 |\n| 142 | STXBP2 | 1 | 0 |\n| 145 | MRPS24 | 1 | 0 |\n| 149 | FCN1 | 1 | 0 |\n| 157 | CCDC88C | 1 | 0 |\n| 158 | ABHD5 | 1 | 0 |\n| 159 | SH3YL1 | 1 | 0 |\n| 160 | KAT6A | 1 | 0 |\n| 161 | RBM5 | 1 | 0 |\n| 163 | IGF2BP2 | 1 | 0 |\n| 164 | FAT1 | 1 | 0 |\n| 169 | JMJD4 | 1 | 0 |\n| 170 | RNH1 | 1 | 0 |\n| 173 | ST3GAL6 | 1 | 0 |\n| 174 | ST3GAL1 | 1 | 0 |\n\n","text/latex":"A data.frame: 174 × 3\n\\begin{tabular}{r|lll}\n & names & degree & betweenness\\\\\n & <chr> & <dbl> & <dbl>\\\\\n\\hline\n\t74 & HSP90AA1 & 29 & 818.84444\\\\\n\t85 & ACTB & 24 & 389.53333\\\\\n\t134 & RHOA & 22 & 0.00000\\\\\n\t83 & FYN & 18 & 105.71667\\\\\n\t125 & CD44 & 16 & 55.25000\\\\\n\t24 & VCL & 15 & 0.00000\\\\\n\t31 & ENO1 & 15 & 82.85556\\\\\n\t79 & CS & 15 & 237.03889\\\\\n\t127 & RPS20 & 15 & 26.20000\\\\\n\t20 & TNFRSF1A & 14 & 98.58333\\\\\n\t72 & HSPA5 & 14 & 160.82222\\\\\n\t87 & TFRC & 14 & 191.15000\\\\\n\t105 & EIF3I & 13 & 84.65000\\\\\n\t52 & SDHA & 12 & 28.73889\\\\\n\t114 & ACTN1 & 12 & 61.95000\\\\\n\t43 & ITGA2B & 11 & 76.75000\\\\\n\t66 & CTNNA1 & 11 & 47.00000\\\\\n\t113 & NME1-NME2 & 11 & 56.28333\\\\\n\t128 & MDH1 & 11 & 24.41667\\\\\n\t129 & RPL18 & 11 & 20.25000\\\\\n\t131 & CAPZB & 11 & 0.00000\\\\\n\t144 & RPS5 & 11 & 0.00000\\\\\n\t12 & PSMA4 & 10 & 0.00000\\\\\n\t30 & SLC11A1 & 10 & 10.25000\\\\\n\t119 & RPL31 & 10 & 16.48333\\\\\n\t35 & SEC61A1 & 9 & 11.36667\\\\\n\t64 & ITGB5 & 9 & 26.03333\\\\\n\t102 & SLC25A5 & 9 & 26.06667\\\\\n\t104 & CTSA & 9 & 35.14444\\\\\n\t115 & CD59 & 9 & 23.00000\\\\\n\t⋮ & ⋮ & ⋮ & ⋮\\\\\n\t172 & TPD52 & 2 & 0\\\\\n\t6 & CX3CL1 & 1 & 0\\\\\n\t9 & SYPL1 & 1 & 0\\\\\n\t11 & MAP4K5 & 1 & 0\\\\\n\t21 & PTPN18 & 1 & 0\\\\\n\t29 & TFPI & 1 & 0\\\\\n\t32 & TBPL1 & 1 & 0\\\\\n\t53 & DGKG & 1 & 0\\\\\n\t54 & MGLL & 1 & 0\\\\\n\t70 & DCBLD2 & 1 & 0\\\\\n\t78 & JARID2 & 1 & 0\\\\\n\t97 & INPP5A & 1 & 0\\\\\n\t110 & CD99 & 1 & 0\\\\\n\t126 & KLF6 & 1 & 0\\\\\n\t132 & ELOVL5 & 1 & 0\\\\\n\t140 & RASGRP2 & 1 & 0\\\\\n\t142 & STXBP2 & 1 & 0\\\\\n\t145 & MRPS24 & 1 & 0\\\\\n\t149 & FCN1 & 1 & 0\\\\\n\t157 & CCDC88C & 1 & 0\\\\\n\t158 & ABHD5 & 1 & 0\\\\\n\t159 & SH3YL1 & 1 & 0\\\\\n\t160 & KAT6A & 1 & 0\\\\\n\t161 & RBM5 & 1 & 0\\\\\n\t163 & IGF2BP2 & 1 & 0\\\\\n\t164 & FAT1 & 1 & 0\\\\\n\t169 & JMJD4 & 1 & 0\\\\\n\t170 & RNH1 & 1 & 0\\\\\n\t173 & ST3GAL6 & 1 & 0\\\\\n\t174 & ST3GAL1 & 1 & 0\\\\\n\\end{tabular}\n","text/plain":" names degree betweenness\n74 HSP90AA1 29 818.84444 \n85 ACTB 24 389.53333 \n134 RHOA 22 0.00000 \n83 FYN 18 105.71667 \n125 CD44 16 55.25000 \n24 VCL 15 0.00000 \n31 ENO1 15 82.85556 \n79 CS 15 237.03889 \n127 RPS20 15 26.20000 \n20 TNFRSF1A 14 98.58333 \n72 HSPA5 14 160.82222 \n87 TFRC 14 191.15000 \n105 EIF3I 13 84.65000 \n52 SDHA 12 28.73889 \n114 ACTN1 12 61.95000 \n43 ITGA2B 11 76.75000 \n66 CTNNA1 11 47.00000 \n113 NME1-NME2 11 56.28333 \n128 MDH1 11 24.41667 \n129 RPL18 11 20.25000 \n131 CAPZB 11 0.00000 \n144 RPS5 11 0.00000 \n12 PSMA4 10 0.00000 \n30 SLC11A1 10 10.25000 \n119 RPL31 10 16.48333 \n35 SEC61A1 9 11.36667 \n64 ITGB5 9 26.03333 \n102 SLC25A5 9 26.06667 \n104 CTSA 9 35.14444 \n115 CD59 9 23.00000 \n⋮ ⋮ ⋮ ⋮ \n172 TPD52 2 0 \n6 CX3CL1 1 0 \n9 SYPL1 1 0 \n11 MAP4K5 1 0 \n21 PTPN18 1 0 \n29 TFPI 1 0 \n32 TBPL1 1 0 \n53 DGKG 1 0 \n54 MGLL 1 0 \n70 DCBLD2 1 0 \n78 JARID2 1 0 \n97 INPP5A 1 0 \n110 CD99 1 0 \n126 KLF6 1 0 \n132 ELOVL5 1 0 \n140 RASGRP2 1 0 \n142 STXBP2 1 0 \n145 MRPS24 1 0 \n149 FCN1 1 0 \n157 CCDC88C 1 0 \n158 ABHD5 1 0 \n159 SH3YL1 1 0 \n160 KAT6A 1 0 \n161 RBM5 1 0 \n163 IGF2BP2 1 0 \n164 FAT1 1 0 \n169 JMJD4 1 0 \n170 RNH1 1 0 \n173 ST3GAL6 1 0 \n174 ST3GAL1 1 0 "},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"data=networking[1:25,1] # plotting the network of the top 25 highly connected genes \nnetwork<-Networking(data,FileName,plot_width = 25, plot_height = 10)\n","execution_count":9,"outputs":[{"output_type":"stream","text":"Retrieving URL. Please wait...\n\nSuccessful retrieval.\n\n\nYou can see the network with high resolution by clicking on the following link:\nhttps://string-db.org/api/highres_image/network?identifiers=HSP90AA1%0dACTB%0dRHOA%0dFYN%0dCD44%0dVCL%0dENO1%0dCS%0dRPS20%0dTNFRSF1A%0dHSPA5%0dTFRC%0dEIF3I%0dSDHA%0dACTN1%0dITGA2B%0dCTNNA1%0dNME1-NME2%0dMDH1%0dRPL18%0dCAPZB%0dRPS5%0dPSMA4%0dSLC11A1%0dRPL31&species=9606\n\n","name":"stderr"},{"output_type":"display_data","data":{"text/plain":"plot without title","image/png":"iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAIAAAByhViMAAAACXBIWXMAABJ0AAASdAHeZh94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\njZF2kUjEZDId7WsCgD4KwQ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Dr8uVEYK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jClEBiEWsDumAyH6xq+FHP8BOGHHwdECEFmQ2z9XMUQRMiukZXduMBgyMjKOHDmi\naB3Uqnc7YsBzNxlrlpHgVktEWDgcDovFYjKZzq3bExMTM3LkyNatW99CENxW2DWjsbHxu+++\n27Vrl+eLXbp06dmzZ2FhYV5enslkCgj26jUslgg7z7QPz+g6u91+YEuers7kpAqVwflJnaTB\noUKaBwCgkLSPDnjOR6a+8eh5g/JYB5t4MJFMuLJhr7Z0TqpK89RTT1VWVgLA5MmTSUChwZKb\nWUCkJ+oW82tm4SRSek3A+vm8uFT1R4ffcwf1Sdjb7JTT0tJef/31Xr16adXaxKOJlJAiBzJa\nrrZ58Q2xWPzUwCHTHhhx0wcjBvj29/3Lt292OhyFn33NsBiAxSzDNmU/lOl+FfNDfGXdT9aa\ndTb7oBBvCoH7Wc1iQMiVH9EUa0chBAgoRNGk0t+tP5p/GZZ1HMjpnqrKutcT+V8FY8wwTsyy\nLMuIxNKlSxYdPnKkvLz86JHDEqmX2WxAAAAUICwWyyeMH3fs2HGlj8/x44cxy8rkSrNJT9z1\nMplyQP9+27ZtIY92udz7icmPr1y1gpj/JFIvq8WIKIqiaIriAdxfXw84WgRO2HFwtACldZvy\nKpakqjR3w2jndDq1Wu3u3btLSkraThoolojFYjGpOex2bnoKO6YJkotgNptPr93l5eXVo0eP\nvn37KhS3sqmQ+XfdqT057C8Juxv5448/PvjgA4fDYTabdTqdyWRiWbZVG8PUF9/xCRCTPFm3\nsCPzLD6m27tIw0O8kMEhqn6qrl27RkVFiUQiADDZCk9cfhjDdZ0eksLmBXsPYy04p1cOaTKR\nFqac2yG02YQZhiFFUgBg+/bt5AGmKXy2wXwKAMSC4B5xO/Ye7eI0WcDfCACqiMUFVZ/2Szzs\neay0tLQtW7bw+XxyZSot9rT9l2q2vycWi3e/+a47BP0mFwK7nGojlr2LGObcR5822WOw3dlQ\nUPVpdNBUAe3zcXY5j0IvxgeyTQHuZFsWAwLcFGQFgChicqEoCiFXbOXf/WjuNnd2w/y/B5MH\ncVN+OMM6HR9+9NGMGdMBY4eTEfBoiczbbDJgQAD4hedeWP3ZKpIUHR7euqSkcOiwkV5eXj//\n9D0GMBgavLwUI0eO3r51C7H3SeXeGGOTqQEBSunWa9iwB955500ENEXTNM3nLHb/SThhx8HR\nMrh8eVMKmHombmtcC+4ZY1xfX3/48OETJ07o9fqk8f2kSrlQKHRrO8+/zsQJS1SdzWazWq2n\n1+4SCARxcXEDBw6Mjo6+RYyds8559Y2rNYv8V+RWfdVFcKlqRYdWH97xnK1Wa3Fx8W+//bZ1\n68bLhRf4lJK8ldguJjDEOz4+3tjgrK3SAwBN0zwrT5QvCioLihPHBQoChUiIEFKOUga/HExJ\nrlkUTLarhdVfVOl/AwBLrlmcIGl0MIcb1Et6Ljl8cUiHiE/8vLrfOJnVq1fv3r0bADp16vTu\nu+8CAIuZQzk9WeywFli79vn0YtV7MlF8YfUaL3ECACSGzQvxTnOfyPDhw9PT021FtstjL6s0\nqshnH5dKpcsenRKoUCBiRLvh2djUFAJjFhss5te/X0ez7LElyxGCy5WfNFpyO7ZaDQi9dLLI\ni0cv6hzu2ggjQBhIsiOGJl3nip4nWo5Iu/szKIoTdncMuVkY1smyDMswYon8i88/e/TRh8kD\nWirzNpn05C6QyhRmUwMgwE3REAjBQw9P+vGH71xN6gBGjBi9bdtmAGAYxm63z5nz9scffUDu\noUWLlrz99puIommKR9EU8cbem3PmuGtwwo6Do2WwOeoOXxx894x2xcXFv//+e05OjslkCoxv\nFdZL5W4U5tmtgag6V5Kp1XZ23W98Pj80NLRnz54dOnSQyW6V23H5ocvBM4Ln0/WPRvk1VI3o\nGLnKS9zmn0zbbrfX1tb+mjHAB80pLy83GAxWq1Wj0ZSWlpJSLARvb+9nn31WpVK1bt3ax8dH\nIBAAQOXyyrqNddh+7Q8UJaHid8TTChoAtMla5VBl6PzQJzIWPBayR2+5xLJmMluEeD3j0oV8\nvxvnM3r0aLvdDgBfffVVUFAQAJwcv77xnU8MllyxIFjA8xuQdKK45tvLVauINmsd8HR0wLPF\nxcUvvPBCenp6yVsl468u0/syEolk3tiHmtlKrxlNm5SYO9hx3safLBaL2Wz68sVsAEhVaWwM\n7rE7+7m4gCfjAv7JFb6vyCqYEuA9oJXvI/d6Iv97YIwBswzLYtbJMAzL4tra6ti4RIZhDPo6\nIuxIPWyJxNtkbADw0PYYHnlk0o8/fu/e1ahRY7dt2wgYJDJvk7EBIXj22Rc+/3w1xrBw0ZK3\n336TQjRFu8LsOFfsfw8uK5aDo2UQ8n0BAGMmaFpQi9cr5vF4oaGhXbp0wRhfunSp+tLVyryi\ndo8MFEiEbucmsfO4zXUHv3xLyetJ6oZ07txK8ubhAAAgAElEQVQ5MTFRKpXe+ij2Yrs0WXpw\nV9H76oj95Qa5KP4fTlsgEAQFBUW1EXcM6VdVVVVTU9PQ0JCYmOhwOACAz+dLpdKKioo9e/b8\n8ssvmzZtItZEX1/fcePGpb2SFvRKkHtXjUcaK96vyB2QCwBMI2MvtdMKesmMmqlvzujq/7bb\nVqQzaS5WLD98cYh7Q5oSh/tOiAl8EQA2b94MAEeOHHnqqacAQKFQvFH4RleVJkOrNtmK+bR3\nhlYdqhxLAsXqjMfPFL10pfpLABjyECYFUOgFCi+nk8fj1ZtNFEVRiHJZS5uZPdwpjphlWFYs\nFruscFiQ2vbYF5eqv7hUfWhwgozf8oUP7yHJ0V9naNWcsLsDMMYAyG2bBcT6+fvp6qulMu9r\nY1gAhKRSKSBACDCGnOzcxMQEAMBNgZsE0lAYABBCD44eBwB79+5bs2a1a9/E1Y9J/g1n2fkP\nwgk7Do4WY0BS1v7s5NTHNJWfVLb4zoVCYVRUFI/Hk0qlly5dqq+v1/60n2SnJozuzZcKEUUx\nZofhctnHW4+Nae1nMVa3jvQODw9v165dQkKCt7f3bX0u2I7ddVAxsC3io7lQMissoFdISIi/\nv7/VaiX1h0mBPR6PJxQKhULhCy+8QOQpAFit1mnTpq1Zs2bNmjXunQwZMmTy5Mlx21wObq1a\nm2xK/nng2T47HdIjxcfMuYHitVqk9ernFfJmh5SYHz0noCl8prj2+6Kade5XlKHqzVvXC3g+\nTzzxxDTdNEmapE0X/ZDRrVNVmRgz+7O7lek2AkDvNnuJWGSxk0cN4MuOxL74lFwul0gkcqms\nzmwiKQyI8iwo15SmCAAeeY7EBsmy7PNfJAUOzbEwrCbtbpU85LjfqK+vWvjBZPcd7vr25WDf\nX7Sdpl2PYIqiMGYAAQIKENOzR58jRw433VcIABAm9eigurpCKvUyGfUsZpO7dDMZ9YAAXZ8a\nT1EUACqvqDAaG0jlu4GDHnDtB4CUsEMIIwQYI4xZzmj3H4NzxXJwtCQZWnXPuHSqwufSmEt3\no/SJ3W6vrq7Oz88vKCioqKhobGwkOik9PX3YsGG1v9YGTAj4tUT/lCqizr5+cPdP4uLiwsLC\n3L25bs3fTYn9KzTbD75WlBfgZtWVm2E2m3fv3v3NN99ceyXXHN82/sVFLz5+BWvSVAdzelFI\n0Ct6n267rmJphee2wlhh0LQgeTe5x2tsZcNebdk77gAlS65ZEBX2zWenjJXdAOC7775TKpUA\nUFSzLr9qFQDIRHFupdhu5ktSqVQsFocEhuqNDepWUYgm8W43OQVMqhEzrKa4kFTps1qtRqNR\n0OfZ/7Cq48LsPMnMOrRxx4fuBPYOqj4ymbK8sqDgynkSL2G32z9Y6GruhzHLMCxmnRizlZWV\no8eM79ih/apPVmDA7y5YSMa0b99+1MjhToYZkDq4d+9eC+bPZTFasHAB+Z3q2bMn42SOnziO\nABEL4DvvvEXuTwxw5uyZ7dvTSa5GfFzcww8/QvMohLjE2P8gnLDj4GhhyLNNq9YmnUhCvJYP\nTGYYxmQy1dbWlpeXV1ZWkszTL774YvLkyTWralrPbv1Bvn7NkM7FpldG9jjg7e3N5/P/ou2t\nxYUdBna/tksLPumLZxZn7c/a2X7nH5eL4xRiBM5GS75CkjBz5szu3bt71uez5FlKZpfYS+2e\nmwfPClYOV1Lia4+xMwMzGlYsqm38QyntWF1dZTAYAKDsYtI7r+3h03IA+D13oIPRAcCsb7pQ\nIrFMJiNWRlImOkzpQyFX47Drz5yULMGlunrPvhpGoxHZ7Jnvf9JSF+R+o8F0QVv6Rs/49Hs9\nkXvPq28OFYvFSm//l59f/Wdj3n3vYZvN1iN5TNrQSSQgk/hRWZYlUZpAyhA3geAGBYbcA67d\ngQghzAKiEMaYQgi7mpVgIGWMEYDLxsejaa7/xH8QzhXLwdHylNZvTjw6KjvlrjQZo2laLpdL\npdLAwECLxWI0Gq1W6+bNmwcPHly4vrDd4HafS4tTUtTOfKG/v/+9TXnbr+3aN+FQC+6w8WDj\n2NNjP9qVEEmh3UMSM7Rqld/R9evXv//+++4xCKFOnTq9/fbbnrnJ9kp7zdqaivcqKt67ZtWT\ndJbw6gIZtlEp7UjUp91ZX1z7wwH09todYQDg7x+gUCi8Je3DfR92UlvlQqFAIBAIBAovb6vN\nQlFUZaMBIcSnec0afLEstjNOzy5qAMCyrFAobLRfpzX/Y3hL21odLR+H8D/HrHeGy2Syl575\niM8XNhp1gJqbdYlJZcZzqzN+/yHzzHZt3pHXX17j0lgUdrlsEYUxixB9XaIEvm4NECDEg2YG\nGoQoEr2JqKbKQhQCwBTblMNNUSShm+O/CCfsODhamFSVJkOrDlONBgBnvZPn0/K/ZQghmqal\nUqlEIlEqlRhjmUyWkJDACJnIyEh+jtnLy0sguB8qVGEe3WI91rRqbZtDbWqsDhuLjw5NytCq\nQ7xHBAUFzZo1a9asWe5h69ev37Vr16hRo9yvKBSKuXPnxr0ZF/pmqPvF2h9qa9fXWi6ZJeNf\nBwCtRIskqPXq1rFtX4od+RIA5Obmzpw5MyyuKr7zjqS2Z0SiASKRSCAQKBVKmcRL6eXLOux6\nqwEAACEGyL9NPhAK8RAPmgKq3MmzJK+lpS4Ix/3J63NHSKXSxya+ZbOb7XYLNFU7vH6UKyoh\nRT204MpZs7nhu58/fGziq65uYUSXYYwQdV3Y5p/jufem6jiAMW5K7cEYYwQ8aOpkQbZxV5S8\nD/5WcLQYnLDj4Gh5eLSXpvBZtebzu1H6xBOi8ACAoigejyegBDRN37xe7u1w6p0AUGt1xMqF\nZlsp/GMHTW7pIi9x0j/ciZvsXtm0N82T8R5I12rSVFdrfwaAxLB3bhz52GOPPfbYY+7VwsLC\nd99995VXXnG/IpVKBw0a9OSTTwrCBbUrd7Zfn1Zc+12MY3jJGyWFTxS6h1ES6osHvgh5I2Tu\n3LmfbDgjTBaS2oEsw8rB36CrxzIkl8mtNuufzRk3QYQdxpj0/LXZ7UKBoGWuy/2Ht7RjuW5X\niHLovZ7IvWHBe0+QQEy7w+xkrMidNw3gaWpr6ucMmGVHDn1u265PC4oyASHPHq7/Gpyq+4/B\nCTsOjpanb8KBDK0aAACB/oBe0f+uN9CMiooym82ieJElx+In4AGAiB9ssZeKBWF/cQ91/8fe\neYdHUbV9+Dkzs303vfeQkLqAwIbelIAIC6iIBeUFFCsg4Iug8koVFStgA0Gs2ABpC4IEpCsQ\n+qQnpPfets7M+f44myUChhQC6Dc318U1M3vmzJlhw/zy1B8rA5YGfJhSOi7INbdyfc+gjzq4\npMKabTcruo6r5LAJRx+N1hnYMQEuAJBe8l4rJ+/SpctXX311ZSqOe+ONN7Zt27Zt2zZLgdmq\nKELj1g8dNP7ppyq6/tT1ymkY8hbmVW2rqtpaNREm+vne9ZPkIumKJpc4ZSflCTwExLpghrNx\ntuu+Fx2vbmIOIcKO53mJRLL8l5/eeHRyxx7JnYsudH0Cq/v/KewwxgI2kYbOJnO9ow7Rtd8Q\njDFgMl4QBEGhUGCMX1/x0PKFW27LykX+TYjJEyIincKl/IWVDX8Miz7Y2UY7QmZm5jfffDPn\nrjnmdHPSFOXpisaHPbfTlDLUa1orZ2B1bMyRmBFH0xJGRh9I0g3XnrpOpHYbwAls3M0SduQZ\n/pxT+Q5bTBI74rp85azs6FM9Ebs57vz9azf33vd9YHNflru7+6xZs3S6K91pH/vwnSrMqdVq\nhULh6uJitfBKibLOWK/SKGxcSzFz9jZRGJMUSJI/IeeF7fMWdnDxdzL/b3NjX1/xECmII5VK\nu8cOpZD9D8C1nlii6+wlrC+whywWS2NjY5eAPo8+POt2rF3k34NosRMR6RS6Ba4gRjtKSeUt\nyAtaGdSplwsICDh79qzbMrfkIcm95nq9fq7wtW4zjqTe13phBwCUkqq18fYszw6pOkhg44ZE\n7e/IDA5YHet8nzMAEFV3JnsGQlTHVZ2NrwcMEokkurt01qTdjuPp6enr169fsmRJ88HG/j2V\nTk4SiYSmaYRoiuGtyKxQSzEIDMPc0GJHyg06LHYN5kry3YgNWOLb1LvsX4aAOQr9/3q/EMMb\nCcSUSqU5+Rf8vMMpinKERji+JnZzCsYYQBCEvIIkUumQ5/n0nBMAorAT6RD/v37wRERuJd0D\n30lg+8QfOcXq2M6+llwuJxuCUXCXMbyAAcDKlXf2dVtAyrh2fJLKzZUAELg8MM7AbhwQCgDV\njSdvijXocMrdPsovrz0eERHRPMfWaDR+8803WyoKSSkyiURi46xEzCGEblgATBAELGCKoojC\nI5MoZU7x2sTK+pPncmckFSwBAA/1wLtCVnf8pu4QBkRs+z1l6PCY460cb3ccYcFe5RC17EfC\nGFMAQLI6BYybCs4gwIiiKAz4tpTwWLbyMY2TRiqVEpc9gFBWme3i5N28McmV9BpyHxiqaorI\n18kRgllbW+Xs7Hbr1y/yr0EUdiIinYWX8z2QLwCAepA6dXRq1J4O9V1tE7c3wKKkZq+Edrnx\nuFZQvLJYm6h9/o9sDNDdTZXA6u6J+aPj0za1bmopZhxjvHLlymPHjgGAUhtJe3kSWUbTNHkT\nU38t93/9yyBsLLMiJ0oilZDqJzRNezk5A4C7pi9RqHXGlFOX/0NseC7Knrou6zt+g7cXpTQQ\nC5bWj0cIBF7AINgzRYUbfX+RAKQGL6m+izHGQJqAYLhtVTxkcnt6DWniTNM0RaH6xnKGkTK0\n5NrxVqtJwILjlwTisrfZbKvXzVg0/4dbv36Rfw2isBMR6USGRO9PYHXxqxJvgdHuzoEt+N9N\nMaqxcWzo56EAcLqyMVGvPZg0SC7xo6jrvCPbygG2z/DYk0mQcu1HP/7443fffefY/f77752c\nnFIK8pf8totIOtJIoIW4eAcY48ZqS875suA+LipaJVVKGcSYTKbyxPP67XoAUKvVP/74o5My\nmnSnFbD1YNIAuwcfye+JPdbxO/1HgDEGBAIvACaVeTEABuF6QykAACwgiqIchXlJMQ8KUQKm\nkMAjRCFAt95oJ5fLHX5YouCbbLpYwNepcUMzNIUpIvc5jiNmXZlM5rC+i4i0D1HYiYh0IlLa\nFQBsfK3/Yv+kfkmxf9608h//ei4/exkwqHqpdAb2j9ExVluVgM2DInd2fGZOMAFg1KyuxNmz\nZxcvXuzwkT311FMPPPAA2baWWNOnpJvyGqhZFNMMR+Vh1MzL5piQTGWpstisJoUPXVtR6OQT\nw5VYaTXDMMy3qz6SyWSFhYVLlizR6+0xdsOGDZs3b55DECdeftqeWA2g67LRRdm94zd+K5HS\nHhX1Jzw0A1ocdaXYLsYYYeAx3rVzFyauSwz6MaN37b4S/jh2zJhdO/cAgEIhHxE/XMCkQpzw\nxoq3AwIC/jP5CYqmaYpp6ol6S8uz/Xn6V2kT5BtCUVRzm+5VK7lS7wRAEATyRZJKpWKlQ5GO\nIwo7EZHOhdQrjh+bWLi08Hav5W8RjAKltFs4rFy1jPFo91SHUu7RBrzV8SUZzxi1idqBe5J8\nFBIJRSUkj7xZiZaHkgcTC9ns6tkKvaLWWO2sXNSjR48VK1Y4xqQ/km7Nsqe7IikKOxhG7zxD\nXtUOYed4bf9d8gTjxSix0ifIp6HWIqGolMuZQd19KYrak9hP48wMjz25fr3d69rQ0PDoo48e\nOnSI7E6YMGHaNPtHF/IWJF5+kiykV8jHbuq+N+UhdDZDove2KTeW9DYFjEePue/Y0WMDBw5E\nCGEMDz/8WGN9TdMY/NWXX//88w8AIFdojMZ6EAS5yslorMUCVig1JlMjAgEBoih8wzbEN5c/\nE3eqNUqi6hw2XWhqw3r9cidNuTUOCUgyZC2WNnixRUSuRRR2IiKdDkJURf3xyF192DhWe7qz\nSp90pJN3/bF6dT/1D5crno3wKq751ctpeLun4vg6H5cR7T6dQDrtkiYThuGRCawuyP3xDs5J\nePvtt3b/Vr1KORZzOMgraPkXz2VWvTYs2gAA5V+Wl35SSoYhCQpdF6rqrSK7yVkGaKoCTRyy\nDl/b3wkIR3ViQRA0rshkMkX0DTWZTAihPiE7S6zvHEjqQ0Zq5FG9Qj41GOz9Vffs2fPpp59u\n3bqV7M6ZMyc+fiUAFFRuOZszgxwM9pjc1Wf2TXkgtxXHc0MIQCCtFhACBBSN7PF2zUZhwKgp\nx/T11xdizLu5+zQ21GABA6DMjFQil0h3N9Lw45bdCUUD0XMkecIROdey9Iem7wnP82TNPM9L\npdKsy2xYl06vkSTyb0UUdiIinc7w2FN26wUGwSQ0b0J/E5HL5RkZGcruSmupFQEUG61KWTDH\nGxlaecNzSz4ridwW+eRvKV8O7JKd/82QqL3tW4PJUtTx2KakAUkSHwli0H170xL12oKqrQAo\nwnduuyfcvXv3Z599RrbrLSl7d11UqVT5/8tX9VSVlX/j/J8VLMUCAKKQ/+v+ruPtybyCYE1g\n48j7t6zEeubdhruXv0WiphzCrrlV5iocJU44jgMAiURCXt5RjVaOE3qFrHG87H9PHnQ49R6y\n7ayMve++jaNH26v7fvzxx6tWrVq1ahXZ/fnnI0ql0mqrOJI2OrfiWwBQML4Do3a2nAVy54MQ\nkF6qNEXxvIAQjQWMUFMOEALUlO2C7UV98fLlK1595WWz2UzORwB+fn4ktxYwRgjQLVR1AHZV\nR/4mtEnYka8QUXgMwzQYq27l4kX+ZYjCTkTkVsBQmuTCN7WnXmP7dFa94oULF+7Zs2fy2Mkl\nH5Qsmum/u6DmbpcR2RUbunq/eMNzbfk2AKi18oEqWRpX0e41HM8Y10GHqa3Mhq040hCpM7BP\ndHEHgNSit9ox55kzZ5YuXUrUFQDMmDHjvvvuA4AEViezyTIfzazZWyPrIqs3+wdPCvT/35Ue\nspfyXy2ttVfgU8nCeod+tnHDz1u2bJkwblw1aePZ5JB1eGPR9YpZXFXBzuG3VTSar3rN3x1j\nT5Kobjx7Nvv5A0l2Z2uQ+6SZM1+aOXMmAPA8//777z/88MP2j4J0b775pkxp+iPjoQQ2DgCU\n0oB+XbfcUaXjYvxfT7w8Xddlww1HYgwIUYCxADxCCGMBEDkIAPDaq68jisIYv7liWXFxydat\nv0yZ+pSxsdZ+MgIgwXoII0Tk4G1ICnc46K+y5raqIA7G5JtDEin+rjKiiEgruYP+FxAR+Rcz\nLOb3BFYX4/8aIGi80Kjqobrpl+jRo8fChQtnbZ1V9lnZmICgPrvZyaMePnN5emuEHeFO6EKT\nNjpNm6jdmVeNAObE+Cawurgu16k2d10aGxsfffRRh7SKiop67733yDbmcM7snKL9p70UG1JR\nKu1Cy8Pl2kRtAjvNX5tYWL0tpdAeYEdTikGRe+USe5QhSW7YtGnT9u3ba/7M54d15XmexEKR\nNMbrplDgv8LzPM/zHMfJKqvlcrlEIrnum9tV1Wu49iTZLqs7dCn/lbzK78nuXcFr5s+fP3/+\nfLL7+OOPP/HEE+Qkf3//NWvWnLw89mBSP/Lp0OgDErrTu9jdED/X8cmFy8l2o7Ge420IISf1\ndaobkscnUBTCAlCIVKQjeg8A3nzzjaZh2NfX56GHJjz00IQnJk/79puNTz/9lMVikUllgNDM\nmXM++eQjjDFFIXwLbZgcb0wpeoOiKLqJ5ha7loUdUfyOXwCIuY6maWeN561avsi/EFHYiYjc\nIpyV3Y+ljRl0enenNhmjZBRXxZEwIxnjZrTmddKFruVw6ogI35c7MgOrY92fcAeAZRcLE/Xa\nU1n/AaCcld1aPuvNN988ceIE2fbx8Xn77bc9POyyrGx9Wdm6MsdIy9LvB0zcRrZPP7Tp9+QX\n6kwpJPk02v9//q73N58WYzx27FgXF5fvvvsub3te/Tv1XLdM3C+wuT3GMdjhcXP414j4I0mO\nHMdZLBaLxUKdS3Lt31+pvLFz3Mtp2PDYP8l2dvnG87l2dU5Tyh5B72/atInspqenL1iwYMKE\nCQBSAJ/4+PgRD9UdTrGHSMYGvOHrMuqG1+o8DhxUbNk2wpFJAE2+aZ4TPl+ScN1T7LKchNoh\nAACKarLCIQoBIIrGWPjll1++++6r1as+VKqc5s+fl5aWfvTosU8++RghqkkodiLJhcuLqnc2\n/1VIJr3P4YQlHUqIjfaGwu7aGDuGYYICIzt1/SL/bkRhJyJyi4jrstFeokxOFX9Y7DvX93av\n6CZj46qD3B9p9+nVu6sBge8cX52B3TiwCwahzpT8d07Y/fv3r15tb9WgUCjWrl0bEBBAdq15\n1itVAynwnuntOdUTABLYuLguXxxMGiRgMwCYHjH6ygfwgvG6l9i+ffuGDRvWr1/v6+vL9mMt\nNku/r/vV7K25sGlmlylrHRFR5EXuKFdBznW8rTmO4zjOZrOZzWaLxcLvOejs5ubv79/WQmWh\nnk+GepLEWDidNe1szvNkGwE9KGr3tm12qXry5MmVK1cmJFgBfABg6kz/JPhfUsH/AKCr96xg\nzyltumgH+XLLh6fT9kqlLp7uzjMffcvLLcDx0Zrv5+cWp896e7TFYvl88QFyULAXGaYoCg8d\nPITHApHKJlM9AEIUECvc1q0/EyOpydSAAGMEJlM92CP0EKLoJoV9M+9FwNaCqq3pxe87jlBI\nFuQxKcLnStznWeFgYWli8xi7VpY7ccTYkaxY8msD2biZ9yDy/wlR2ImI3Dq6es9JYPvEHzvF\n6th/mbAz20qhY+1lCxcXahO1U49lUQDdXZUJrO7uv/akunjx4vLly00mE9l98cUXR44cSbax\nGWc8kmHJsteJcB7tHLg00OGNO5c7u6L+eL0p5fTlJ+USP13oernUm53KahO1jlpxzXnggQds\nNhtJU2V1LFDQK7FXZvbFOvjWSdkVn2PNvexGRGKZa176xHHQ4X41m81msxmlZtE07efnFxgY\nSBqDto+4MLtj2mKrOJ/74tFUu0HORdmjb98vfvnlF7L766+/fvLxJ0TheQXUj5/2VkbpRwDg\npu7XK+Tjdl+9lTy7fIRCLr+7z7hxQ58CAEBgtV0p4fHcxOWAwWI1Llk37YUV966eb5BIJBRF\nCYIAgAAoTGFKoEljMQQUBtTUkg0hCgEWAIjoIYZpQCTEjpjHENyU0sQ55V/lVHzF8Q2OI6Ge\nT4Z4TqWpK9bW77//fuvWraQ6idVqnb1gJHHI/l2lQ7iqpVizDBtynHyRKIqy2WyisBNpN6Kw\nExG5dQR7PpFRugoA5OHy9PvTI7ZH3O4VNYGAu/K+ac978VjamI6kTbA6tstXXQCArTEl6rUJ\nl/rIpb40Jauurp4xY0ZdXR0ZFhsbu3LlSrKNOZz/Wn7tb/YgemmAtLmDu7h6T1LhIrLN0BpB\nMI/ucVku9W55GcT96uTktG3bNiNrvDz1svfz3p5PeZ5If6iy5vIDw788fPhIWWGJXK0ydQ3F\nGJO6ZQ7bjCMEnvhhHR7YxvQ/pZkNnp6e0dHRXl5eN8VRKJN49A23R+BxXP2JzIkOkernev+o\nUa+SZBEAWLhw4frlFwCAYoQRk34orT4qkUgYSjMoajdD3dgp3Faef2OkSql8ecoahmbqjFXX\nMaA1leZ95clP3/161kvvj39nzhaFXAl2sxZFUQiQ0FR/GGMAhCgEAKSJA2JIh1hwBNJdsdIh\nhBBFkmzbSGXDqXM5LzQ7gFzVcb1DPm0+5vTp00uXLr0yAqFevXotXboUY5yXl5d8eetVwq7l\n9iTNC+IAQPPfECwWi9h/QqTdiMJOROSWMqDr1gRWF//jHdRkrOGPBnUfdbHJ1ttNVVzza8er\n0LWVy09dBgqUWqXOwB67L6bBnF1UnP/zGi8APQC4uLh8/fXX7u7uZHD5xvLST0sd54Z9HaaI\nVZDtOlPK2ewXOKGe7Mb4L/JzHUe2E1jdDVWdwWBYu3btihUrevTokTY6zVZmI0qRCKYxusSy\nsrLKyqozZ87UpGainHz+noE2m83RP4q8kpub62w2m8Viadh7kLZWV+EjQ2M+jIqKUigUN/PZ\nAQAAw2gcFWpqjOcTL08vqt4OAAAoxHO6o/ByfX394sWL932Tzki4ex45fTknODAwWMJoBkYY\nJPTNyeaZ+eZotVrdJTDaaKknGktB19uQM89jQFd69DpEzbMPLd2wbdmrax5ZNX/XFa8lIAEQ\nTZGxFGCgKIQFASEk2K10FEU1T/WxW+5IVFsrl1pefzSt6B2zrdhxxNNpaKTvy3KJj+PIsWPH\nNmzYUFFxJU980KBB06dPdwRxOiCFVxBC5JvQPDeWHL/WFds8wM5hrkMIVRV5iM0nRDqCKOxE\nRG4pSlkwAGDgPaZ43PQsir84fVp9VuVPle5PuE89mbuuf0h24bJIv/+29boX8xd4aoa29SwH\nxgtGbaI2ctOJ6vzsh9a+op9+9OD397777tLo6GgywJRqYkexdlGAwOtpL69nvchHFlv54ZRx\nNr6a7Loq+/Tu8ulV8yewuj5h31x9VRpM1iKVLITsjR8/nud5h/sVSZA2UWvlqo+kjnBX9+8Z\n8hEAeHh49OrVy2q1JiUlbdmyJSwtPWTSRJuLxmGeIVMRYcdxnK2+Cg6fPbR376RJkwT1qd69\ne3t6enZ21VwX5V0O02l2+RdZpZ/llNubWPQO/fyDDz4g2w0NDXPmzCkpKek/5kJqmp9Kpfbx\n8e0T9uUNU1Va4NfDm+UKmUKh6N9tVKOplqKQSiWrt1osXA0CTNmKBIk/OAx2GDAWeEFQKBQI\noRdXjlmzYLfjK3ydZ0TR1z/eaupMKedyZ9m4GscRJ0Vs37DvJYzGcSQ9PX3hwlkOdz8AREZG\nfvbZZzeU4xjjM8eNd9/nRDzCRNtRTZAxzZ318NfSxI5SdgBgs123S66ISGsRhZ2IyK3mnpjj\nB9i+8bMSK75uf8W46xIeHp6UlCTxl2OM1cwAACAASURBVACAn1Ka02BhKM0Nz6o/Xh+8KjjX\nkOsmY86bWCdFm7VmWe2B9vlhs7KyknRJX/b/suYRdUm/CT/39GDGloV4vPPc/c8CQPoD6dZ8\ne18vp3inwDcCEWN/NSZefqbGeJZsM5TT4Ki9LbdBc1LENN+t2Fzh9ZxXcfV2T6e7AUCv1yOE\nDAaDtciaPi7d81lP76e9T2ZOrjenDIv+naHtz5BhmICAgH79+snl8q1bt0ZGRha9tNf1QddC\n/qT36PnQzBXb+OFheTBfZtsb5KlXKpU8zz85cUda7SNhzM3pitZKQj2fCvV8CgAwFtJLVp3J\nfoYclzJufcM2bdhgrzB3+fLlF198sYu2IKvfIADk7OzcT7uInNgmEs5sUqlUCoXCaKmlaJqy\n5Jpsod6KnBprF6ktw2qjQOkkoTibQJM6wxgLAi8Qn6MgCDv2fz9+xKSbd/dg4crPXH7eaM1x\nHJFJvAZEbFVKgx1HSkpKFi+eV1h4pd2ft7f3qlWr/P39oS2QZFhiqSW6zVHupHn8ZXOIv54M\nc+RQJ52rUisDxAA7kY4gCjsRkVsNRckAwMJVhn0fdnONdnq9PiEhYdrcafmv54/7j+tvRTWj\nvJ7OKl0X5v1sS6c1ObUo0nq9jbS1HmxlZeWCBQtKSkoA4KljTzmHOG/bs01nYGv12rzyH9lz\nZtOUgSywACALlcUci6HkdktGUdWu5CJ7hBNNKXqFfOamjrvh5Q4k9dMGvHHVwdIPSrv+3DWz\ndi+qnDvnKf2zzz47duxYoiNjT8UiCiWwOgB0rVqVSqWBgYFKpdLV1bVbt242qU2hURQXFlEJ\nx8jr3NjYePr06aG9h1oThR4PP96Afly79ptly5a98cYbeanIxldLGbc2Pa6bAkJUpO9Lkb4v\nkd3E7KePptkj8BTSQF3o546GZjt27Ni9/c3a2v8CvAQAvaKf6RP5bmsuMffd+5UquUKhkEql\n6anfdIm4n5K485a6XKurrfYwpYp0cXEymRuMFh6AtIfAAhawgEkqCcb4KLu5g8LOaMlNLV5Z\n1XDKcUQpC+kZ8pl7s+9JXl7exx/PT05OdhwJCgpauXJlbGxsu6+LEFKpVE5OTj99fXHy0zpH\neReJRAJNuRHX5k1fVRDHarVaLJbM9Iphw7QdSa8RERGFnYjIbSBem9imFumtZPjw4R999NHM\nKTPzFuQ9tTwwfl/KE8FDTmdPvYGw6xgHk/oOjTpww2Hz5195m0ql0k2bNilqFOkT0rWJ2ru+\nPjf6CLBL2OwFy0JX/tx1a1dZsIyMNFkLTqY84UhOjPZb6O/2QJuWhzHnc00tN8xhaaB00ZiL\ncrTySvYrgCOoTi2L6Nf1++tOKJFIFi9ePG/evK5cV1mwjNZRFtnPgc4hNpuN53mKok6dOtV9\nQPeGEw19h/fNbtjds2dPX1/fpUuXvvFGp/yjtwNdqN05a+WqjqXpHSJPI48eP/7b8ePHAwDG\n+JcdX55NmXs25XMAAMF1XL8Tfn5+fzenREqT2stSqdQsCbZZi8qL0rwCutWUX5J7DijKOuXt\noaQ1UWSw3Rcp4LyyNCJiSK5JcubZmPBebbqXPzImNVoymv9C0jdsk0ZxpQ4cxnjGjBm5ubnN\nz/rkk0+Cg4Ph5qFWq318fDIyMirK67y8/5Iz4XCzNk+vccRiOgrimM3mH7485+Hh6e3tLQo7\nkY4gCjsRkdtGSc3+mGPDb67RjuM42oUGHgCgxsYrZQE2rvZGJ3UIjAUJc/0+B/v27fvoo4/I\ntkQiWbp0ae/evcmu8YLx4sCL8ij5ykkXrHdxc/oGX5w7Or7rfsVEf4ut4o+MJxot2WSkh2bY\nXcHvtW9tvycPjvZ//XqLBr1ez3Ng2GewFFkyxmU43esUtCIouWB5Uc2OQZF75BKvFqYtLCyc\nMGHCBd2F+w/fvydx0Ixeuy0mwWKxEGG3b9++ESNGFKwr6N27tylTplarv/32W9LBAiG6ov6Y\nh2ZQ+27npiNl3O6Jtdd2rm48eyH3v47U2lDPpybc/zzAkwCAAf90oPfOU9EAgDF16eB9ixZ+\n4ONzJckguyBVLpfLZDKpVCqRSBiGLsr6klL1zMm54OaqMVnrXVwpXqK22RqaossAANc2VpAO\nDY6yf1/tXvHO7K0tLNjG12aVriuo+tlxREK7RPktCHB7yHGktrb20y8/3bNnj+OIi4vLrFmz\n7r333g4/sL9FLpcHBwcnJyfv2Zb2yJTuDg3nKE3XXOdBUyCmI8PGbDansGU0zfj7+/v5+TGM\n+GoWaT/it0dE5PbQ3GjHm3ha0XlRNZ3YKiy96IPmEUsAUF1dPX36dFLcCwBeeOEFR0t7AEgd\nkcpVcwBgSjWp+qii90VP3ZeUrI87mTnJWF9wPGM8GUYh6bDoQwyt7uDyeMHk7zr+qoMFBQUv\nVr84Z9EcZZdlaePTbIW22BOxSIoS2DgA3HqLGg20SqVydqXDu0QTtxp5Z6vV6tDQUCNjVKlU\nNG0PmdfpdBMmTNi69eQdYrS7FldVr2Exv5Pt6sZzZ7Kfzi7/AgAQ0DEBix4dfhYAMBaOpt5P\nUXu2/7lbEFDC931cnQO/+OKLtb/8T6PRSCQSUqFXUr2j1Ozj6xNen72bUfWz1KcF+bvWmBjB\nmEHJfXmBJy1Sm3faFQRBKpXKZLJrF5ZcuKy4Zg/GnONIjP9iX5fRCF35kfnwww8PHTpEEhEI\nL7/88uDBgzs7VcUBwzCBgYHh4eHV1dU/fHn+sWl3QdNNNU+aJoMdTliHB7ai3Hj6RK6Xl1dU\nVJS7u3tnd84Q+XcjCjsRkVsKxgL5jR0L2FMdf7l0Y/Sfk/MW5AauDATAf82bIyFvpMm5YI/M\nAUCkBCt2FHZAyN5qqT3luxy078y8qu/jtYnV1dWLFi3Kzrbb2AYMGPDaa685xhS9VVS1tYps\ny0JlXX/uWm2oLlldEnMwpvv2o/MD30hgK+tMKS6K7j1CPnBX92/3LVxFAhvX1efqDN+pU6dW\nVFSsdl3dbVy3EzEWm8qmTdRizCWw/VSy8P5df7zhtAsXLpw4caIpzUQ5URgLFAXkze0YoFKp\nGhoaGA0jWAWaUtWb0zTyyCVLlhCjHUNr0orfj/Rtc+rxrcRV1dOhPtOLP0wqWJxUsBgAAFDP\nkI+HRO8EgJSit4ODvysuPrN2+xa5fKzDYleY8VtE7L3+jPvlC5sDg4I9vLzqjXStBTE0zyt9\nAWNnFVeSuVcdME4QBADMcZTDaGez2SqqSxu4fZmla5otBwV7/qer9yzHPsZ4y5YtX3/9teMI\nRVETJ06cPHnyLXg41wUh5OLi0q1bt4qKioyMjB++PP/IlLuIf5mI3WuFnc1ms9lsVqv17KnC\npAvFTk5OMTExERERnVEQR+T/FaKwExG5xSCMeRJjE+O3NLPsE4wFaSBjyTdJA2RNnTIBAyAQ\nBFJ7H8gO0XZE2AEAUAJgIIW7BEAU2D9qm0LDHJaFytLrzO4yCcc3Osnb4BRetGiRX6/MVa/o\nAYCiqF9++cURG1S9q7pwWaHDVhidEE272KWPjW9If+uQ8ee3Z+180mJzHxw8JaPkgwd09Tel\nYcBfwcEejzXfJ9LKYDCwOpbVsXxEoXb7xKSCpcU1uwZH7pVJWsqrdXDhwoUVK1awcaz2tPZA\nUv9BkbuuGvC///3vvffee2XVK5kTMu/edfhAUv/hsX8AwMyZM/V6vcHwewKru8OFXXMifOdG\n+M4FAAzCmaxnzuXMIMdpSj6mNwsAlfV/rPtlg0wmIwF2LnKLVOlz4Y/NAR5CY2Wmwq2bVKoq\nTvreO2YyDcCe3IR5qzbCE1EWq6WRUXggdKX+n0wmW7/9hbi4XD/X+6P8XqHQlTfUvn37Pvvs\nM467YrfT6/XTp0+/c7yWDMMEBwfHxcXZbLbc3Nyfvj4vlTITJ3d3VLFu7p8lws5qtX6/8RxF\nUU5OTtHR0b169fLw8BDNdSId5E75kRAR+f8A0XMAGAs8BsAYuyv7ldb87vnCkJrfaiT+EruU\no5picZoaEBGDBsklBGRvogQUAoyBwgA0gNC+9uf5C/M9Jnusz62aF+tzNmdmmPczLY8nVXzJ\ntn76UV3QrucMQ8hu49nG9Bnp0FRa1dGkFQBsXH1i5sx6cxIAKB9eoF6X1Sf29Cs5SWkTtQeS\n+mnk0Tdd1R1KvsffbYJjNzs7e9asWffff//06dNz5uaYUky9inr9nj81gf0OANrjG8UAABjb\n5JKrW8P16NFj4cKFquUqa7GVjCHHR40a9fHHHwOAWtb1RPrEARGb23drtwsElC7MXiGF4xvO\n5bzoCMiTSHRE1Xm7M7Vl0dW5BkASl+DhEoUXz1k0Spln31EZl7Yg12EyBoCWZBfZuno7yQUL\npun6+mylMgiaHJcmk5r8cyQkJKxbt655SbmRI0c+88wzd2xLBoSQUqmMiooCALlcnpOT09DQ\nsOmLsy6uynvHdZVIGMfPJs/ztdVWwy8sRVEymczV1TUyMrJ3796BgYF3jk4V+ecifodERG4d\nCGFBsDtjeZ5DCDSK7vWmNI7jmCDGXGiiPWkAoGh7j3lyFoUoATAFwGNMnLNY4AFjXiC9k2iE\ngKaY9sXSNZ5uDFgW8PP+wvnd/A4mpbup+147xmq1Pvjgg47dyZMnP/LIIwCQwOp02iFJ/ZIw\nZ7+0LFjWdWtXx8jzuXMq6o813TsVr01MfyjdqrZqB0/UGdhEvdbClWHM9Q3/th0rbxlOqIv2\ne5VsP/zww0aj0ZH9igWsiFbQznRdepqrqufdMUdaP+3ChQsnTJhgzjW3z3W9ceNGvV5vMBiu\n26P2HwRDq+PCNpLtgpJsVvIBsUvV1IObd3hlhatuSDQAICTw1noLrw5wK86mBblxv0/E2OrL\nhruGTr147nR4pDMg3t09ktjh5IzNwjASiYQYVgEgMDDws88+u1332A4QQhqNJiYmRq1We3p6\nZmVlVVRUGBvNm7+91LxFLDHdKRQKlUrl4+MTERERHR3t7e193RBDEZG2Igo7EZFbhyAAAAIQ\nMMZKpcZkrMMCVkmD1WqXhvpaldqpvq6a53gXjYexoU6ldj70+wEM+O674xsba3kMKrWzXC6v\nqizBGKnUzocOHUAI9YmLo2gKYwGAEQRBq9Xm5+cDBdZCa5hGVmPlAMDG10lop+suia/jKVlT\nywRscQSkm0ymhQsXpqenk90BAwa8+uqrDpND0fKivKwd1mFSdiorDZCGrg2V+EjIR3mVP6QX\nv0+2MUZ3BX/g6WQ36WEOW3Os2kTtwD1JMS5yADiaOrozMglOZDzo7WxvjOZwvwo2Ibl/srKn\n0neu7wXDe3vO3R/uPbN70Fttmtnuh9Wx2tPaQynD47p81abTvbzsybaB7o84XLT/dOobqyUS\nCU3TxGinVCpd3HxtlgYfzWVT6dlqSw8njfJ8mpdX9ICG2sK0P34N9HfOzDrv5FqQkVnXJdRn\n/75vu4R3CQ7uy/NOcpnRJJE4iur9EyE17cLCwtzc3IKDg/Py8kpKSmpra00mE8dxpPSJRCJR\nqVRubm5+fn5BQUF+fn4ajUa01YncLMRvkojIrYOikCBgARBgAZpscghJSF4gACAeJFKmsaEG\ngwAAcXG9AaCxoebihYvdu3frptVeYklnLdz0KSKFXhlECQKmKWr48OFfbtw45825VduqRo50\nXp9eNsFrRmltQoDbg3+/riu88847R47YLVhyubz5K7buUF3evDyyjSSo/uP1o3ufhakAADau\nNoEd3jQQBXtM6+oz49rJk/olaRO11VbeIuBvBoUnsLoQz6ltfIStwmjJG9D1F7PZ/NBDD/Xp\n02fRokX5r+TXJtRG/x5Na+g9u7tJRkndVf2C/hqB1zYQcHyts/L6IYlSqZQ4zQWzoJSG1JtT\nNXJ7Cbft27cTo11+5U/tv/qdhFQqp2na0R2VZhiaphnGJfncKa/QAD+ffkVFe/z8RgOAUs24\nq6xWU3W/4ZbsTHlA4D3FBeljxz994cJmhCwMwyCK/hfoG4SQTCbz8vJycXEJCQmprq6ura2t\nr6+3WCyCIDAMo1AonJycXFxcnJ2dlUqlRCIR4+pEbiL/+B8hEZF/FCQbApNuDS/Ontv8Ix8f\nb2cPD8Ou7UOH2k1cgBBg/PqiJcuWLt650/Dnn8fOnD3nyI9QqVwAwGSqR4AwAIUwIDR06NAv\nvvjC6XWnvFfyHnk25vGjGXOiJxxOiW9B2G3fvj0jG/T6V/TTM44cObJkyRKdzu4oNCWbcmbl\n8LX2KhI+s308JtszDIouoVOXp9YZWbLr5RTfPejtFu48eXCyPEoOACN+S0nUazNLPwOAcO+Z\nbXp8reGPjEc8NcPmzZuXmpq6efNmhUJxVfFhXCMdMfrMgeS+LsrubZp59uzZU6ZMaUhsoJ1v\nUJtm1qxZS5YseW3ra2mj0nrvX5t4+amBkTvIR0S4mEymu4JX37GlT9pEqH8kwzLNoSiqOO98\nbYM10Gkkx1mcnSVFRb9jrHRzc+I5LrbfkxVlMnfXckwzVUXnC7LP9h74sNViEgSuecvdfzoU\nRZFMYVdXV1KFmBTEoSiK6GBSw0+UdCI3HVHYiYjcFhAArF79AVF6Gzd+CQBZWemA8aFDR5Qq\n58bGWgBwcnJDCL388n8RQo9NeqK4OK9r17BYbQ+WvdDYQHqZU6tXfzR3zhxAmFjvGIapq6sj\nzdLVEqrQaJPQTsQc2JzKysopU6YAwPSM6Rs2bHCZ8F8S+GUwGPhGPnlYstBgP0XaRRp9IJps\nYxAu5b9eWvtrvTlDznibLAWt1CVcLSeYhPDvwnUGdnKoBwDklH/RSZqm0ZK1Ym4jABgMBsxh\nVscy3kzU7qiSmt/Ygtd6BH1YOtUVHgeM+RtOdRVZWVmrV68mBaV/Tx7UJ+xvQwPvvvvu999/\nX7ZUxjfwMomHyVbY/FODwUCMdu24uzsQhK4oFVLag6ZpY125UiGvyt4Z0G0qooKcNSECyBiG\nin9AW9dgyc9LUavdL51a3avvvTbsxDAMxnIBW2iaVkg7WrzwjgIhROyYYvycyC1DFHYiIrcO\nkvyA7WmvgDDCgB0u2ZrqchcXj6EDBs+c8QKpe1JXW2k/EyFfX5/KikqMcXZ2DvkUAWAkHDt2\nfO6cuQgQYGg5tdRmsy1YsMARNte/f/9XX301uU+ywWDQGdj8V/JNvY3sVBYAGHcm7NswWaD9\nVZRf+UNa8QdNyRmoZ8jH53JmtkmWpQ5P1SZqP08vBYDZsT4JrK5/+M83PKsdHE2ZsGKOecjA\n3kuXLi18s7D6l+qw78MUEYqDSQMFbCFrLgW24xfiBbOTIrojM7AsOyhy97/AaEeaKzgMUTRN\nXz77haW2Xql2LSo1ltZuDgjpUm7NdlEyRpsq5exuT2cLpY41N9RodWMsNs43KITjOEeHhriI\n0Te+pIiIyN8jCjsRkZtAfk7pvKfWEicURVGk2irP8zzP/Ziw+Krm3wBYwAB2RysCIM5V5B8Q\nnp2dTmH6408+XbmSBPXbTzQYdl/OSiczPPfcM4CQSuVcUVESHh5VXFwIiJSwA1Ll7i9g/NFH\nH0kCM0i1OXd39127djnWU3e0zpRiOtv3kuI+c80po/QBuaO5mclalMCOa5oFBbo/5mghb7VV\nNC/6f0NYHev+hDsAfJ5enqjXHk4ZiYBRybu04fm2jqVLlyYcPr9/T5JcLr/K/UpR8vjYDumn\n2bNn/+c//2k43UC70RhfbQFtK82NdhjzbXqedxpWqxUhRIQdSaGwGKtoigntNu7ovi8inBsb\nCnLTC7G3M7aB2kkt1/j29fAOslpsvK0hsGscaRdBurFRFOWlCb3dNyQi8s9GFHYiIh3CbLJM\nG/eOVCrVaDRDRnS/R3+Xm4eG54Si/MrP3jHU1TRMGbPSZrP+sH8RGU8hCgNFUVBVWQaIoijA\nGMrKihBFGY31F5MT1PIuVefLEKCKihJEUQgAEIyIHw5AkRyLDz/8wGazmoz1LMsWFxdQFKJI\ndWLqSrzOrl27+Az+Ff0rGcOn7zuw79nF/g7HnyXHkv1MNlfFAQBfy3tM8fhttvJBXtDM+C2W\nXvhn5uMN5jQy0tNpWLfAFRS62oV0JG3UcO3pVj6fsg1lAOA7x1dnYH8cEs4LZhtf1Rk2Kr1e\nb7QWLP84hKg62pmOPhBdWnvgUv4CbcAbPi6jOjh/cz9sAtt3UGSrHKlIhqylVoXE32KrlEnc\nm38kk8m+/vrryZNPHEjq+4822lmtVonNlaIwY0+bYOJGLT28fVnm6fVD7nsh5/w3Ln59+nVx\nDY3oQ8bv3PpVSHiPWr4iNLyPIAgkqM4h7BobGzHGYuSZiEi7EYWdiEj7efnZj0vzG1zdXFZ9\n+zw068olkdBdInze2TAdAARemPHoR0+MWrFh2zypTAIIEIWQgFRqNQBgDBQSNGp7XJF/oEQu\n5VVyZW1CrfMIZwAQMCIFFDAgBBRCNCAslUoBo27duyMECBDpKlZcVDxj5kyO4zIyMtatW/eS\n80vEx2qYa9h/vnf6/enWAiu5ilwrj/otCgBYHRuwxG/zmcNz/RefzbmokUfKJX53xxynqRvE\nA6FWl3ErW1umTdSO3J8qpVC4k7wzPI8mk2nixIkhISH3P1fSI3UL+x82dEOo6i4VqRXXOZqJ\nl0t8Wh6xYMGC2bNnv/vTu3n/zeu2fuWZ7OkDIrY1H7B161a9Xk8iHS1chYxpVd+LOxCe501F\nTmqvOgBwOGRHPrIice/rF46uu++xtwrOr/GLmPHzl0tGjX0UI9mDj0wXBN7DwwcDNDfXIYR4\nK221WkVhJyLSEURhJyLSTqaNfwthiX7igGGjutdWNQKRO473EW7qTYDhrbVPvT7zq+cfXv3l\nzpcxAABFUUgQAAHCCCN85R3m5TI8q+wzF2W0NdPG3yVIvCSASDcJCgNC9s6xFMaIOHIBqPUb\n1qelpdfU1DY0NPTo0WPBggUTJ040GAxsHJs3P8/oYWKXsOYFJq6Ki9gRIfW3t/wqqPolreht\nhfHlw2VTcxsWDApff/ry1NZooCPJI8O9595wGIHVseE/hVt4ocrCJeq1B5MGOsljWnluK1m2\nbNmpU6c2btxYyW2oGf1qIVPocL8CoPjrWRYR02bRsHz5cr1eb84yU4rW5mwOHjx45cqV0gCp\nOdXspNAarfnXjgkPD3/ppZc++CDxXxBpRwJFidWNhNz1H/t2btrvFEU31BTv/3mRlwtOOf2t\np7Pg5v2ORCKFJlXXXMalHzF1m9DCRURERG6MKOxERNrD6hU/UiBVKBU9+4TXVRsR6dJ6jZkB\nN/HfZRNXLd329IQPP986l6IQxkBRNMYChejmHSMoDBhbkovfip31v7x5eUHvBdGAAATAFLKL\nRowBEhIO/vnnSYwFq8UqlcmXL39DrVaRrlx1R+qc0pwu6i5as6wggO8CpTYxtjLVLzTB3SLk\nHmGvVG4LcHuYU0YP0CY657B/V4/tWqxCVYjn460ZmTomFcmQPExOmkzUmdMFbOkT/k0rL9Qa\nHMWHAUNmbFcXn+iYgzE1xkuJl6eFek4P837u2lOMF43SIKmNq3VT9Wn9hU6ePEk6zGoTtb8n\nD+nX9eaUoFu1alVTlwWquGa3r8uYmzLtLYZhGKVSuf+rc2Ofi+E4jjhkiYM1NHo4RVE97l0V\nWFnq5u6dmXwiPGYA+YkgtT+aN061WW0ymUwul4vmOhGRjiAKOxGRNoMxvniqUKlUTnrm7rpa\nE0VRdrPaX0x20NTeFcjbS6FQgAmmjFn5zZ5XWnhzxQS+ksDqutNLjX+aKzZUeT/rTY4fOHBg\n9erVgmAP21+9enVYWBjZ5iq41AfS+Bp7/Y4nH39yB73j+dDn+Vr+hb6SOUdWxmvSDiYPlDEu\nzsruvUI+oSkFGcm2MT/UbCttZVNXwSZwpZw2UTtgT1KYWgoApzIn3VyjlF6vd3V1/fbbbyu3\nVGYvPycsSoh5dOLhlJE2vuqe2D+b949vTu3eWs8pnmdzX4z0ba3d8Sp4waiWhXVg4X9hwoQJ\nEydO3Lz5VAKr+4cKO6lU6u7uLpfLzSZL82730PSLDULIxdVTEIQuUf2InhOasNlsNpvNYrFY\nLJa9GzO6d++uUqlEYSci0hFEYSci0maeHPeeWq1WKpVmI2ezYPIaYxhGYlVamAbHMOKcwtj+\nJpPJZAghjPGqN36a879HWpg/xGNqAquL/yNxb8+9nxg+cXSZHDdu3DPPPEO2uTru8pTLxiQj\n2VX2VnZZZ88zDa4Peufhhf0f2KGcMpcb8MXRyufe6X/pVNYTg6I6WjjtWNqYVoqz5P7JsSdj\nU2tNVgH/NCwigdVF+L7cwas72LRp0w8//ECkLRvHAoaaTa/EaxNbE1RXua1SO1/bkJSqkUe2\n8nJvvfXWyJEjbaU2aHvqKsdxtDPNN/AUkgFguCY2cdq0aVu3bgUAGeN1Me/VtrY4uxOQSCQ+\nPj6urq6/fpE29rkYIuwAgFS2I8KueWI4AAiCwPM8KdtrNpstFsuJnXkKhcLf31+j0dzOmxER\n+ecjCjsRkbZx5MAZhUIhl8slEkni0cuxvYIoCkkkUmMtZjS1NsFGMlkdLb8dwk4qtccVJZ8t\nbvkSK149k5lbvUqpN5vNfoV+n5/4XC6Xk4/yXsmrS6izj0MQ9VsU42b/KS6q2ZNSsBQDDwAm\nS3XfsL25yPJIz4PvFbJSiYuZK7npj+LvSOqfJA2QIho9cTQrUa/NLFkDAEHuLWnZ1jNu3DhB\nEEiSL6tjgQKF4QQu4xNYXaD7JEdNlr/FBgCAMe8wW96Q48ePEz9s7KnYI6n39gppbVv65cuX\nL1q06JVlr+TNz+vzwTcH2P7DtX9eO+ydd97R6/UGw54EVgfwzxN2FEX5+PiEhISUl5fv/Cxp\n/Atah7nOUZ2uubAjqo4IO6vVajabK4obKosaQkJCQkJCxEK+IiIdRBR2IiJt49uPj2g0GplM\nJpVKeQ4a6iw0TSkkjEWohVoI4SlrfwAAIABJREFUMEeUqrNtnI0MJuoOC0JBTiURdqS+3cdv\n/zLzlb/0+Pr66683b95Mtr28vL768qvs+rnx2kRWx5oPmzMXZtrHURD4dqBzvDPZqzenJSY/\nxQtmshvg9kiU38sAsEqp1yi6ArDQPILvr2AeO0xQgmC5odC5kPeyl/PwlscAgCnZhG04YntE\nnIH9b4wPAORUfHNTnLAY47Fjx7q5uX3zzTf1x+pz5+T6/tfX/TH37YmD1fKw4bEnO7saHKKQ\nlat0U8e1cnzPnj1ff/11pzed8mbnhcq1GLjrDouJiQEAjLGHZsjRNP3g1hVSuXNACDk7O8fE\nxBQWFubk5Oz47NL457sR9SaRSEi83VXCThAEouosFkt5Uf3RrZddXV2jo6P9/f1p+h9c0k9E\n5E5AFHYiIm1DLpdLpVKJRCKVSmmaLsyucXJR1JnMvgG+iGbKa6pCfCMu5J8HhysWcGVpA89j\nhmEUclVdfY3NZrt0Oh8ATpw48fbbbzvC5j799NOgoCCyjS245P6XWJq1ldkyJmQEvhfo89yV\n+hpHUkZa+SqyrZQG9+v6I4Ukbb0RI2uUhkgPFNWOD3Qtrz/urOrZ8vjyut9bo8+y/pOlTdSu\nTirGAI918UhgdUOiEtq6tmvZsWPH+vXrifs1eVCyYBa0p7WAYM+FKAFbOy+l9LXXXnvggQdM\nqSYk68TAr23bto0dO5Z0deu8q3QeDMOEhITcddddJpOppKRk28cXxz0fy3GcRCIh2s7hjXWo\nOpvNZrVaj/2SXVnSqFaro6KiunXrptFoxAA7EZEOIgo7EZE2MO/JdTKZjJjrSAgRTdOmRs6F\ndzPl8hmXs7wiPST5mLNQVpsFAGxWnvRvJWUggp0Dko31crmc4ziSDvnggw8++eSTZHLexGc/\nl92Y2Eh2/Qb2zXr2kfhuiayO9XnOJ73ow7yqTeQjucRnYNh2hTSgI/dSuqY0bEPYK4lZy3oG\nZJWu6xf+t51PWw+rY33m+ADAt9mViXrtHxkPMbRGyrh0cNor2a/E/YpAm6g1WQuPp4/n+boH\n4xo7vvK/4+LFi2+++SbJhz2cEt8r5NPOuIpEIgEAo9EY6bsgge0Trz3VGVfpPBBCGo1Gq9Va\nLJZz586VlpaufeuNgYOe6T7Eu7nRztGRheM4U4Nt39epFEU5OztHRETExcX5+PiI5joRkY4j\nCjsRkTZgMQlOTn8RduSNpdIojeec1Sp1F/egtJp0rWc3tjSNYXiQUJXlVS5uzoyRUWlUAoNl\nMhnG2GazTXlkzsTJ8QCQ/3p+7a+1jkvEnoxFtN1okXahMYGN49dy2Zstimhln7BvO9iftDnG\nC0ZaQ+c3WrUuyoSCLIqStjA4gY0bErW/5QlLVpUAgMcTHjoDe2RUNAA0WnI6bkvT6/UURe3c\nudNSYMm4P8PzGU/vZ7yPpust1pKeIWvO57YzubUd2PgaN3UbiqQAAE3TVqvV4fI220rlEu/r\njnQ0GUsrXtnBdd4WKIry9PTU6XRyuXzLb9MiAh7NT63OSaoAgCEPRGo8r+TJ7v0inecFhJBc\nLnd3d4+IiLjrrruCg4NJrIKIiEgHEYWdiEgbuMoPyzAMQqixUaiRVRerMtSgLMotqW+s3X/6\nlNoPeXi5YbnFWe3EMAxyQhKeKa0vpbFUqaDVCs3xX7OiV/sAACAIWB7gcp/drFVvSj+b84KN\nrwEAmlZZbGVjdLnsc2zs6djO8FL9XQTetQOljGvLIyq+q9Amah8+lKGR0EqGTmB198T+0ZG1\n7d+/f/Xq1fPmzRs2bFjqqFSugtOe0gIFjuzXzq7r+/LLL0+YMMHIGmlnug2PqhkzZsxYu3bt\nlDenZE7JHLbx8B8ZDw2O+rWF8bm5uQMidvxD6xXTNO3h4dGrV6/0CrUbDMzNza2urjaZTH8Y\nLpNaxACAEKJpRqmUaTQaX1/f8PDwrl27enl5SSQS0QkrInJTEIWdiEgbIJJOIpE4/LAIIS83\nhVUwq3mPRq6krsiHUau8QhVpp9ORrwa8sVuwEmMoyShBYUhKSVWMprKhvMFYz0glpEcCAGDM\nH0waJGB7DoSMcXe81xPYuOrGszF/3pUUl+QYf0MQQkVFRfJIua3chgBqrbxc4ssLZpqSt+Ou\nM0vXSRn3lsewOjb6eDTGcLnBkqjXJrA6hSywHZF/Dq7rfhUE20G2v0IaODBiW1XD6Wurh7SM\nYBRkITKTtaiVJ6akpLz77rtN/WF1/cM3t/UuRo4cuWbNmhdffDF/QT5DqyxceQuDHUa7tl7l\nzoGm6cSCEePvWYe48KKiouLi4vLy8rq6OovFwvM8QkgqlapUKjc3Nx8fHz8/P09PT5VKJXpg\nRURuIqKwExFpA5JmkDoOFEUJwKnlzqfKE3qpR+XhCwH14UaodHL28IxWp+em+Eq71hTVCmBT\nyBVu4JrXmO+kcK2rrpdKpanFKwsq7VpBQjnHhX2pkXe96orx2tMO+w1XxzFOrfqZXbx4scFg\neHDUg2Wfl/33MR9DQVUv9cC8yu9DPZ9sx13nlK9v2YCU+WgmraZpGa0zsCfui6luPAcAA7tu\na+GUltHr9TRN79ixw5xhznws0+MJD585PudzX6qoPzI4cp9M4g4AZ3Oeb6tZq+yLMqfhTkU1\nu2L9F7VjVSp5aDvOaiv79u0bMfKPf6jRDgAQAj/PwYIguLq6dunSpaGhwWg0mkwm0hBWKpUq\nlUqVSqVSqeRyefOEWRERkZuCKOxERFqLIGCGYZqb6xzpfhy2Dhk6uPaCNap7ePrp7AinQKdI\nKp8tCO/dhaKonJzcXrpeHFhLuTKaphsbTa7uLlXVVYVV23qGfOKu7tvydWlKyRYs1iYuJaaj\n1iy1V69eS5Ysmb5lesZDGWPm+9y9L+X4qOnncma1Q9hhfJ2yun8ZwGNzplmbqNUZ2FCVVEpT\nR7KfbrcoSU9Pf+mll5555plx48Yl35Ms1AnNer9eKT5stpa11VwHAPVH6kM+DblUunZ47Mkb\nDn733XeHDRtmLbEiKbnQrdAfxGh37733AgDHNzK06hZc9CZyLG28r8tYAKAoSi6Xy+VyFxcX\nnucdqd9EyYl6TkSk8xCFnYhIa6EoRAx11wo7hNDZbTne4erK4zioW0DOmfquozyduwbyVuHi\nyQu6ob0s1ValXGECEwDIlBKj0cYwzPDY65SrvZa7Y44ksDptwFIAaDjToO6tbsVSKQCg5JSt\nxKaR0AAgYzwazBntuOsDbJ/BUXtbGJDUNyn2j9hL1UYA2Hx3RAKri/Rd0I4LAcCjjz7a0NCw\na9cuhBCrYwFAm6jlBNOh5MFOiqg+Yd85Rh5LH90O7WjJtkg8JVAKral4d/jwYYPBwMax2pPa\nQ8n39AlrZ9Yw+bcgSBk3s61ELvFpYTzDMMuXL3/99U6PIOwMzLbC2IAdzY+Qpiy3az0iIv8P\naVXbRxEREQJFUQ5JxzSjKr9eJmGC43zMzmXGdJmLv5qWUsY6CxKYuKFxDMO4SJ0ERpBKpM1F\nYeuv66budzRttDZRm/Nszk25EWOKUR4uN/NCiEpW3ZDoouz9t0MRJq7P68LGsfIIOZKgaccv\nJ+q1SQVLAFCg+8R2LEmv1xuNRoPBINQKrI5V6VTaRO2l/NcOJQ++O+Zoc1XHC8Z2zN9OMAAF\nnFDnpIhq3wSTJk1as2ZN6LrQjAcyegSvuZj3Ssvjt2/ffvIkMSiiWuOl9l30tnAm+zlNe5+S\niIjIzUIUdiIibYBoMoeec8TbXTqV7N/fuTynpktAlKuW9uulkUikJbmFShdpZUbd/m9PYndw\nWPscf7f+ur1CPrbYysh24RuFHb+Rml9q3Ce5zzmVu6xnQF7lj8Eej193WHHNHinj8XeTmFJN\ngCH8+3CdgV2g9QWA4hpDvPZ0WxeTmpqq1+snTZq0c+fOy9Mvp8SnRB2ICl0beoDtU1r7W7w2\n8aquGL8nDxke27mV3tasWTNw4EDezHd8qkcfffS3335T9VZZCizOiqg6E3vDU7p16zZt2rR4\n7enTl6d1fAG3jOrGxL7N9LeIiMhtQRR2IiKtRRAEiqKILCN6jmEYKSOrKW5083TzDvSwNghJ\np9MYJagoddq+Qp8gP6lUWmEs79Ovd5MStKs6iqLUTm1LUI32X3iA7atN1FZvr+74vVTtqHId\n55pY2RimkZXXH/Z0GnLdYUkFi4b8vR8264ksbaJ2xcVCBDAxxD2B1Q2NbnOTiQkTJsybN89g\nMEyaNInVscbzRm2iFmmEBFYnk3he64u0clUACKHO/b/rt99+e/XVV1MGp8T+EXs8fVyPoA9u\nwqStrpfy1ltvlZeXAwBCTFbp2ptw6c6nqGoXhcRCdCIitx9R2ImItBaO40gabHNXLC2hGDlV\nnl+ad6Y8+3x+gCrcO9A97URxdX1NYBd/iUQSN7inT3cXogLpZrj0fXn/pTb0j/J3fQADDwAK\nrSLt/rSO3ow9lh1kNNW+Cm2sjvVd4AsA2/KqT+u1R1LHUEgqodvWZEKv11ssFoPBwBt5Vscq\nuyu1idq04nd/Tx7QN/yHQZG7rz3lSOrIdhgF2wkGJEEma9HfCd/OY9q0aQ8++ODw2D+zyzfc\n4ku3j+SipffEnrjdqxARERGFnYhIq+E4zifS7FBm9s4TiPLy89BPHZWZnu3rGir1hcK84l4P\nhI15drCjlLFSKXM4bR3txXr4feem6pfA6g4mDWzlAgZG7ExgdWFfhdkKbG1aefvyD4+k3qsN\nXHHdj4reLgIE7hPddQZ2T3wkxzdYudI2vdeLior0ev2QIUMMBkPunNyUISnRR6O7bOySwMbl\nV/4Ur028tvILAHBCJ3YPc/DWW2+NGDHCmm+96TPzjTxDaQR845knTJhgtVoBQCENSLz81E1f\nyc2lzpR2a7KGRUREbogo7EREWgvP85hpBOIIbPLJYqulLIH6Y8u5ob2H1XCVsUMDIqLDHRrO\n8bcjhdZR6CH5yeQeQavitYkI0Qms7nTWjaOpFFI/AOAFo89sn6QBSS0P9vPzy8zMlPhKAMBF\nyhQZrTR143Ta5li5Sh/ne6/7UdWWKu1p7ajfUgHASy45lDKsTUFvzz///DPPPLN58+b58+ez\ncWz9sXptopZW0AmsjqLkLaSCHkoe2kFznZWrkf191CDh+PHjs2fPTn8gXZuoPZY2tlvgOx25\nIgBMnTr17bffDvkspHBRoTbgjTPZz7bmrA8++ECv1w+M2F5jvNDBBXQ2p7Iev3VmVBERkRYR\nhZ2ISFvB0FSOi6Zplavrybod988ZmV5+wVcRaDabm6s6Rylj4od1VL7YdeKd9yveP9vnbPbz\n2XfHHInXJtaaLiWwuuLqlvpNAUC8NvH35CEekz2w9Qb+0/Hjxx86dMjraa+ilUXjAl2PltYH\nuT+WU/51K2/SylX/nQ2G1bER2yPqrFyFlUvUaw8k9XNX92990Jter8/PzzcYDFJByupYebhc\nm6jNq/wpgdX1Dl13T8zRvzsRY5LK0E7LUO3vtW4Pu5XV/e6qaoMH3Gwr9na+p31XdPDQQw8d\nO3ZMHaeuO1zn4TSwlbmuERERAMDzvJ/r/YdSOrqGzoPj62/3EkRERK4gCjsRkdZC07RCoTib\nt4nneY7jMMYYYwCYNPWxjJS0/qP7KkJ5N09XUtaO+Fsd52KMSZlWcm5RceGqTauW+S07dvwY\nq2MrfqiI1ybeHXM0qfD1BFbH8zdw1dUa2fAfw9m4lvIrx4wZs3v3bk1/Te2+2lnR3l9klnk7\njyio2trKmz2SOiJeex0jXEp8CgBIA6T3/Jb6f+zdd3gU1doA8PdM2Z7ee4W0UQQ2hCI9FmQg\nIEVFEaxY7kXkosAnWLCBF7AgooKKV0SlExYVXLr0lTqphBYI6XWzfWfO98dARASEZBPKc37m\n0WX3zDlnJg/xzWnvfp4z2wowdneMnXctdTY2NvI837lzZ4PBUDy5OK93XtIvSYk/JG7O6V5Y\n+t9MzuSnvfKpKwCbcjJasoqr7L9lfgP9SmpWJ4W9epVir7/++oABA+xFdkp74388rlixIisr\nKzVimltsuNF9uaKteX3JcB1B3DzIuZEEca0YhvHz81Or1RZbfdPUqvxRfPvEwoMnrWYLTdNN\nh+xjjCVJkkM6l8vldrudTqfD4fh50ZzUwtRp06ZNmjTps88+2xO95/k5z5fNKUtclpjJmeqt\nOVvyugNA/7S9lz1HN5O7cHQtBskpUYorxh8ul4sJYsQGEQBqHKJOFW93lQIAYGACmTKbU0Eh\njEUVG3mFCi4dGxPNolgnciau6/qcroFaBLD3+KPXeIjuq6++mpubu3LlSqVSKaQLgIEzcQDY\nKOhZ2rdfyjVFbC3Zd+mudavT1GYhl2W8r1LswIEDBoPhQn7YjE6xC5rdYsupVCoAqKqqujP6\nv5tyMq4lYcYNQhbYEcTN4sb/SkoQtwqGYUJCQvz9/fce+85utzscDqfTKUdskiTVH6HiOkSK\nl+NyuVwul8PhsNvtjbaagL7+fd7u83bN24vmLQKAEydPTA2bmrwhuWhkkaAXfDRpmZwpPvjZ\nTTkZm3O6X7YnCOhjZfPS9qTlds+9zpvAAFD2aVnAsICNJfXPtw/KLZkRF/z4JYV25D8QH3SZ\ndWB5ffM4E5dfZ3Nj/GnXOKOgvyvmmsbqeJ7Pzc01GAxKpVLQC7Sa5kzcubqfjUJ6etw313JI\nilFI7528+VrauhLsasbmX9Ffl96SRi+BFEgSpX8udxGDwTB27Nhg774XZqJvLkYh/e6kf1g/\nQBBEWyKBHUFcK4RQYGBgXFycRqPZlrPAZrPZ7Xan0ymPw3V4JMwv3OvieM7tdsvxnFzAbrfb\n7fY1+0bVupYn90zW79bPqJwxLW4aTdPHjx8fMmYIZ+KCng4S9ILQRYgPfjaTM3mp2hsF/e5j\nIy/pSX9u7+mqbxGDAIG9yH69N1K/sd5/mP+8vLLRicFV5p3B3vdeUsDhrogPeeaSN3O65mi7\naAHgsd+Pm3gut+QdACrQq9s/tFVfz/M8x3EGg6F8QbmgF+IXx6dsT9mS2yv37OuZnMlHe8c/\ndhhjEQBffaTNI+bNm5eRkeEqcyGlh4egnn322Xnz5oVODD339rlOsQt+Lxh07dcihPbs2dMz\n6Vc5Ye5NBqvYoBvdB4Ig/kQCO4K4VgghLy+vpKSkiIgIhmG2HJlvs9nk8M7lcjkvuPi1zG63\n22w2q9W6PffzxIiRHdLuOW0bp1ApOBOn262bVTNLPpA2OTk55LkQzsRRWkrQC/n98tMTFmdy\nJovjhFHQ55XMurgzajbi9zye288VPVx0vTfiKnXR/jRGCABcYh1L/2W3rNNV8/eZNVuBDbtx\n3GdxeoPwSUYMAJyrXXPZRXgXmzp16qOPPrpy5cqZM2cKXYTKryo5E6fhNEZBL0rWa0+Euikn\no2/q79d6ey2wYcOG6dOnFwwqSPs9bWtu7y7x//NUzYMHD96wYUPA8IA6Q52/Lv38nPi1Wbdu\n3TvvvKNkAwFAlK47jm89m3IyOsXcyKlqgiD+jgR2BHEdaJqOjo7u0KFDSEgIzdBbjs63WCxW\nq9VqtcoDcvLInMPhkF/I8ZzVaq1vrNiR94VKpYqLi7uv9ysD0tdvykkvq9/ImTjsxglvJ+zd\nu5fn+aSkpFGjRqVuSeVMnOSUBL1Q9nFZJmfK5EwltcuNgr7afD6W6pG01i6WAQClpKqWVHnw\nHrcXXOYE4OOPHudM3HtHSiiA7kFeRkF/d5Lh6vXwPH/06FGDwaBgFYJeYPwYzsRVmncYBX37\nsP9cb3p7mrq+RB0tggEQuCWLtya17Rq9KrVa/dlnn2Vypi25d9/ovvwJY9Hfy5NT1QRBtBzZ\nPEEQ1wEhpNPpOI6z2+0HDhwoLy/fnvt5fHjHaP9u8rEmTcfUSZIkSZI8G7stZwFFURqNJi4u\nrkuXLrGxsRqNRt4Dcazsw577fsm/L1/QC7NNs2fPnp2UlMRx3JgxY175/RUAEPRC1XdV7Q3t\nMzmThF2bc7oBgBwVRQWMMArpmTv3C3oh8LF/OJutJQS9ED07GgBWFdeaeG5Lbi8EtIoNvcol\nPM8rlcqVK1dWr6gunVmaZEhiQ9lNOV0xdl9vSGcU0vtc+QwUD/r666+Tk5Plnc43m+XLl/M8\n/8ILLwBAo/24TpVwo3sERiEjJvDS1ZkEQdxwJLAjiOtDUVRAQEDnzp0VCsWRI0dKS0tPlx85\nce6gWqnrEDeYRV5yYIcxLjfnF57dhhBSKBTe3t7x8fEdO3Zs166dRqORy8ixnVHokrlhX72x\nXtAL7de1Lygo4Hl+0aJF27ZtmzZtWldTV1elq2BAAQCk/J6SyZlKatYaBT0AyuT2n6leDgBs\nJHviyRPxX8df0tV27dqVlpYCBWKdGKVVNjhFAMDYfZW7O3T6PyE+mRe/c+79c4DAu4/3hSQT\nlqvPon722Wc///zzp59+Ghsbm9MjBzswZ+IAwCjoEaKvN6oDAADMUOrrv+qvVbjPh2sIXfGH\n3qpVqwwGg5AupP6euqtwGBd5+awbLSFJUtMst1uyMJT22q+Niop6+umnFy26sCf6xhPbhY6/\n0X0gCOJSJLAjiOtG03RgYGDnzp39/f3z8/OLi4tra2vtdrupaFnTWScAQFGUWq3WarVBQUEJ\nCQny4jy1Wt10SAoAZHKmzTndjII+M9PkY/IR9ELA6ACDwZCVlSWK4jvvvAMAa9as4Uxc497G\nvLvzAIAzZUX4Z+07PtYo6N2i3SjoM9eYBP1lzrTr27fv0qVLn3ztyeqV1T0ztD+crM4MerK8\nfhNAxJVurcq87ZKgoWZlDWfiMjfmKxAEq1ij0O0qUQXP8wBgMBgAQNALwABn4uyust8L+JjA\nJ9qFvnjtD1lmFPQZCd9f71V/5652KxOUlQ3bg3T/lPUVA6WirM7Tob6Xz7rRbA8++ODKlSv7\nTuh7atKpjHd+/OP4uIx2S6798gULFsiPFwFVXP1jdMDDnu3edTl8eqJGEXMDO0AQxJWQwI4g\nmoOmaV9f35SUlJCQkJKSkpKSksrKSrPZbLfb5diOYRiNRuPr6xsSEhIZGRkaGurj48MwzMVR\nnaxf2u7C0rlGQd8vbQ9n4gS9ULeubq1x7SeffLJx48YpU6YMGTIEAAwGA2fizr5xVtALTADT\nZcNiANiS07vWajpSPDlg6Picbjlpu9MurnnAgAHLly/3Hued1yfv6dHJT+06+Xjc0F2FWSHw\ntYSxF0Nh+IcTNAS9kPRzkgvjOqfbxHPGo+kBV9gGK4piVlZWcHDw119/XbuutuStkqj3onzu\n9dlVONTqPNOSESYvdVKzr21SOqc0YkZEfs3HUf4PXbbAggULunbt6q652nBmCz355JM8z48w\njCj7sCxWxZkd+ddbw7333jts2LCVK/cZBf2NDewqzdtvjlFDgiAuRQI7gmgmhJBarQ4LCwsI\nCEhISDCbzWaz2WaziaIIAAqFQqPReHt763Q6tVrNsuzfQ7om7cMmJob+e3NO1/T4xZyJE9IF\nQS+MN41/5JFHnnjiiUWLFn344Yc8z1MUlZ2dHflWZG7vXEEvqO9Q9/1mmyQ51/zhX5G1yWfv\nFIC/BHYsy9bW1tI6GgC8FczJRoda0Y7KjfQd7Jt9prajv6aifkts0Jim8puELne3//nCn3Dh\n4ELam2aD2e4/5+wfmFZt3kVRbFOSCXktmnxTy5YtW7p06eLF3wQGBuX0yAFJPnwYNud0R4jO\nTNuPsbwHF/39Wozx+SeDMfz1ERmFLp3jPm/2N+hiDZsbImdE1p042Cn208sWWL9+vXwucequ\n1N3HRqZETPdIu541fvz4jRs3AgCNNKbjT+kTvroh3The8SVDt/rRMwRBNA8J7AiiRSiKUqlU\nSqXSz89PPr5OjlTkTLLyXoqrhHR/1oNYecmdn1bfef/nBYML5OQH2dnZgwcP1uv1BoPh4Ycf\n5nn+rrvuemfbOwAg6AVBL4RPCfdOTu6Z9Mu21+5dt/z1e4dsl8/FuBLFzGGBywJXni75MD36\nUNGIize3KuhABRMgim6MJcCg6qIMfzX87YMnX2jnJ4quczW/9Ura6nY7AQBjAMAUhTDGH3/0\niSRJK1YsB4DTr53Q9lVHvhlhtZUfK/84OfS1IO9Mp8shbzSlEMLnozoMID8YhDEg+TNEwfkn\n1/S4pOvK6/oPT1hFSZLjn4spKIvjRIRflqfa9azp06cPGjRo3brtN/BMu5MVX5LhOoK4aZHA\njiA8oCk/LMuyLannwnaK9Mzs/dU/VQt6IWVrisFg4Hme53l57drgwYN5np88eXJPU08AEPRC\nKCz+/ePh9/Y4+Meb63ck3w8I+qftv1I0iRwKVaIqL98WqGIBsIoNkd8/XfWjUhksSRLGEpZw\nzY9Voa8El9jsCVrF8Bi/4qqfov0fkaSmqVsMAG4XWr1mdWxc7ODBvKvSXvdLne9IP02q6kz1\nKpfbnBoxHWMkJ1UDAIoCDBjjC4EdRkAhAApLEiAKMACWEPVnljajoO8c+0VLHua1mzt3bs+e\nPZ1nnUjRdqmxaEp9vfsnACAjI0N+nl6q5K25vfukbmud3l2R2X6SJBAjiJsZOceOIG4umZxJ\nzqAa8FBAyuaUvD55lV9XGgwGiqLktfPZ2dnLli2bNWsWz/O1tbWciYv/Jl79zL8Od9rb4Yf7\nQp9YHBv45Kac9C25V9glcIXTPE5VLtLHfiVnuK031qjuVEoYn7PYh8X4NliPadhYFRuOJfHC\nF66oqDx0+GC/fn35gQPN+8y2ApvfKH9lkqKyYaeSCY4OeBSLWJJESRIBSwgwlqQLQZ6EJTmP\nriSKbsBYwpIkSYABYwkuOm3ET9fZ88/3cjZv3jx58uTCIYVpu9K25913Z/TMVmqoX79+P/74\nY8T0iFMTT6VFvpN79q1mVPL111/zPJ+RuMQtWTzew3+0t2jE3485JAji5kECO4K46WRypgBd\nD6Ogp7yAM3Hln5Xn35di1+2hAAAgAElEQVSfnZ2dmprK87wkSRqNxmAwfPHFF6NHj+Z5XpGi\n6J47ov7udfmZ+bY8W7zPc5mcScEEGAW92XaNeSmw/NMAY+yscAXzEcokVUmjPUnHPjCAZ0CZ\nEH2/f0CISu31m9EoSZJKrYuKiu3atcddd3Wyn7aWi+VB/UPVal2j47SGjYsIzPTx8V+1ZhWW\nJAB88OBBlVonYYwxxpKEJazWeGHAWMIgSb9s+FWl0mCMMcIAIGEMAEYhPTViWis+4itzitXB\n3pn/XK5ZJk6cuGTJEr8sv8YdjcHevSsampP9Njg4GAAkSUoIft4otOn5wKJka8vmCIJoBhLY\nEcTNqGPsx10Tf9qUk9FoL+RMnLvaLaQLH3zwwSeffDJ48ODTp08DQEREhMFgGDNmzJAhQ4YO\nHeoet5lau8b7Xu8/Av8oeqioR/vV8pnGRkFvd5ZfvbnNOb0yEpdgjBGAPdcKABa36KOkVDSN\nQVIowgY+8EBlRamlse7xx5+02RwAYLHUWcx1Af4BbDCT2vvO+oZzZvPZuTO/ra8Bs7mmrqbi\nkUdGA2AsSd17yGOHGEsSxtL7M2cdOmjCkgQYSxh37typ6VO4sKMCAIX7DWm1p/sXX331VadO\nnVyVLsS04Qxjy05BXrVq1eDBg+OCn2ppRddpS27Pfml72rJFgiCuFwnsCOImpVMlZHKmPUWj\njhS/ypk4JpgR9EJ8fLzBYHjxxRc//vhjudiIESMMBkN4ePjcyf6TX/o2aXWSOkVty7cJeqFy\ncWVKYv++KXsd2rObjfd60XKaUeR011zSFgZRyQQhhMsWlKuSVACAENLSFCAJIQoAlq9YIccQ\nxaePK5UKAAAXxi788MMjQSnvaaUppHt/5gdPPvUMjSgA8Pf3k1eDRUdHWxrrbDar3NSMGe+2\na5eY0bUHBgkA+/v5AQDGGAPCWALAO/IHxAWN9fDTvHLMtnr16hkzZhQMKEjdnbo9/74OUXM8\n3HQrUCgUAHDmzJn0+K/bbBeFfDgOdeUTngmCuBmQwI4gbmqZnKmiYfPmnLuT1yeHTw4X9AJ2\nYYPB8Ntvvw0bNqyp2Pz58w0GQ2O9qk9m8ubHNyMWpe1NK/+0vMfuHnPfntvuyQFJpz/upP52\nwuYJDO1VZzkIABhLCNEAUFr3s5IJAIDyz8oBYSaEBYBAb1+N1ler9QMMgLGlsS4qOl6r8/3i\ny4UUhQCgW89eXe7uPm36G6LooGmaRors7HUAUFFRiREChOLi4hBCW7Zuy887ggACA8MwxhhD\nhw53IgBByEHo4uNNMIAEgDAGUbIlhLzgwWfoOOVg/BlRcnmpkq9SDCHkdFcH+fT2YNNXgd2Y\nQs3famMwGJ5//nkfzZ0e7NLVbRIy+qXtarPmCIJoHhLYEcTNLpMzAcJGQe8/wj9td1pOt5y6\nX+sMBoPL5ZK3UzTZ8tvRaR/pNm7cOL52/K7ZuzgTN3DdwK1LtlZ8UVH3rfRS+uz8k0Ncyoql\nRyf1CPaqt+XI+V5zzr5xd9I6LGGrYA8eF2KqsgCAxVJnbqiwNNbJwZfb7T518pilsW7SpMmS\nQwSAvXt+37PXWFt/nKGUDQ3VP/60fPDgQQCQmBCPMMaAjx0rAox5Pkuj9dXofDHGgNBHH31y\n+PARjc4XADAGjOF8cIflP0oHT/0rOnCUZx9gw9aGgFEBuWffiLno0D7ZTz/9FBMTIzkkRLXR\nPOyAAQP+97//hb4SWvpxafuwSYeLX2l2VSzLrl+/vnfK5jYbtKOQom0aIgii2UhgRxC3gH6p\nO/11GUZBj1jEmbiz084WDi3Mzs6OjIy8JLZrHzZx4qzq1QdWT/9yOs/zgbGBKBnRU+Gj9P97\n8/0HI07N/ur+Hw/+HObcMm5nwcD0+MVNFxbwBdH/jRYxWEUJANxiLUUDAGBJqquv//nnX2ma\nlmwSACAlDQBWV6nDXaFkgwBRiYkpDz080ul0Hy8q+P77706cPAUADQ0NGCG1Wm1prLdY6vfs\n3gmAXpv2uqWxXv66974HEELyIjEMGGOMALsla1zg0559epWLK4PGBFU37vL/26l433333fz5\n8/N65iVvS95z7KHk8Nc82/Tfvfjii8uWLQsYGVDzQ02k/7DKhi3Nrmr16tULFixgaW8AECWr\n5/p4GZuEjE6xC1q1CYIgPIIEdgRxa+gUO79z3JdGQW+xn+JMnPOMU0gXPv/886lTp/I8f+7c\nOblYdMAoCbt8fHwWdl+YVZ318Av3hXWm5uW9oQpUenl56XQ6Ly8vby8d5dZlZ3ca98aj6w/F\nc5FvFwwsoNQUraU/zivtHeoNAE53A0KqispKl9vt6+u7Njtbq/P1CvKvq6uRF9uJYqNO1Y6i\naERRBfk5Wq1Pp8768LAwikLDhj+k1fqaG2r37t1XUXGOohCNqDs73BEWFnnHHRxFUYhCFIV2\n7txVcq5Uq/MBAI3GGyFUUPpxgLYbXMN5ztdFapQAwC01Khi/yxbAEqbVdKPjeKT/UM82fSXX\ncmb1tQgKCpoxY0b/tH1XPN3GQzCI/ro23YFLEETzkGWwBHHL8NN2yuT2G4X0EJ/77jC9K2ee\n6GHqsWbNmiFDhmRmZk6YMAEAurVbYRTSM7/b//7rEwJV3ulcz8cH/fvvtdU31k7/9Ll12R2M\nzAdjK9/vsC/9sW1FgyJ9KESdLlupU8cfOngIEPrttw2A4dNx8xa8Ol+VrDY78s3WGquthkJK\n+WBmAKxUKm02C0Lnd2geOvSH/KJbt24IAQIKAFOAKipKz+/ixBRC2G6zYMA2WyMAIACEQMIN\nccGT/kwy1sq+++671NRU7GzTjaWe9c033/A8jxAFgKrN+wK8urRGK9vz740Pfq41aiYIwuPI\niB1B3FpQJmcqr9+wJbc3Z+ICRgUIeoESKYPBYDQaH374YQDQKmPLStFzM4Zqtdp3x385tP9o\ns7W+8a9fZms9RaF3x38xoOcwFw74dMA78/c9YxFdI2L988tmuu0hq1atUSpVnTp1tmyz1P5Q\no0vXaTnt2dof66wHQ7x7MpSGpuSEaRRNUYiiaYpCiEZAI8RQFIUQTSG5AAMASE4ZRtEUYhDI\nV9KIQnIxmqYRRZ+u/pqhfBACqq2Wu/30008ffPBBTvec1G2p+4+PbRc6oW3aPY86nzO3hTIy\nMh555JFMbv/B057ccXIxp7smPtjD8+MEQbQSEtgRxK0nkzOJksUopIdNDEvZkZLbI7fxYKPB\nYGhsbOR5vtFi3rU3SqPRTBr7ntlaZ7bWm631Zttfvhpt9WZrvdlS3zm1R+8u92s1OmGD+eWw\n/2zLv/dk8YEflmwZOXLEHXd0KHunzPK7JejxUEpB55571yGWxQWNoRCFKASIoiha/pJjNpqm\naYamKYqimAuf0RRF0TRD0TSFKIQohC78kaYpimHkaVmgKIpqsAjJEZModP6HkkeCnmtEaal6\nmxAT+FjbNMfz/KpVqwIeCahcWJkW+db+40+1pLbp06ebzWYAoJG6sGyuh/r4px35D/io7/B4\ntQRBtBIS2BHELSmTM/lq7zIKelpNcybu1DOnTjx1wmAwJCYmTv7oCa1WOzbrJbO1vtF2hS9r\nfaOtwWyrN9vqUhM6KlVKhYJqKH0qr2Df7Ddyug39lZLY/G4F7nIp+u2409VfbSvoERM4Ii3q\nNYZlaVbBMAqGYWmaoWmaohmGYWlaQdMsTbM0wzIMy7IKmlXQcjGGpWmWYRUMwzLs+T/SNMsw\nLM0qWFZJs4rDZ14SkQVRFCAkHzrX2rOxCxcu1Ov1rkoXots68+nTTz/97bffhr0cVvFlRZjv\nwHrb4RZW+Pzzz/M83zdtR3HVUo/08GIOd0V6wjcer5YgiFZC1tgRxK1KH7ew1nLYKOj7pe3k\nTJyQLgh6wZFVrFVr1Wq11dFIu2hEISSvhJP/uUDehYoxBoxFSVKr1QCwYe/yMPTK9k1vbh81\na8+hldKPS7g71xoFvTz/26r3UmvZ39pNXGLt2rUGg0HQC5yJ21k4JCX8/9qsaYZhRFH0YIUD\nBw5csGABAOiU7XYVDu/efoWnai6uXIrI7/8EcUshf2MJ4hbmp+3QN3Xn5pwehWUfc/s5m49F\no9Go1WqlUml1mC0Os1X+cpqtjkaLwyyJYm2p1dngtjoabY5G+U2ro1GpVKrVao1Gc8Z19I+g\nP/wLB3bPHWGnSlft17olS2snfT946iUvVVIrVY7dmAliXGLDVcrYnGcj/B9spQ60jQULFvA8\n37XdD1bnKQ9WW1g+tz+3z4MVEgTR2khgRxC3NppSZnKm4qrvjIL+u3vmKpVKpVKpUCiOHN9j\ntTdY7Warw2yxm612c2OZvb6hwa2tcyjNWo3K4miwOcxWu7nGXK5QKBQKhVKpVKtVIAIAFKxd\nASD1S93JUFqjoHeJda13C9WNOzMSv2+tyldUa9O1FQ3bEi7a17l06dLU1FTRLN7gH4EXhlAx\nbukAXlRUFABgjKMCHvLUecXVjbsQ0B6piiCINoPacoUyQRCtxyikbzSm6nQ6lUqlVCppmlaw\niiC/cACgEKWiNficysLU0To3rWYoRLlEF8bYLboqa0vdbrfT6XQ4HBaLBbvoe+45asmrj5v1\nU8KSRHWy2mwv3Fs0CuQcGJ52+PQr9XahV9IvHq9ZduLJE+HTwnfa+vZK/pWlfeQ3eZ43GAxC\nupC6M3XnyUGJwS+E+Q1spQ5c1nvvvderV6/4XfHAAvVETlnDb3dFf9DCOu12+/Dhww0Gg1HQ\ne+Q75al6CIJoS2TEjiBuE7/+mqxQKFiWZVmWYRiGYSiaqm4ok6di7bVYF0m5tI3CgSJngYY+\n52u1m6sbyuot1TRNMwyjuMCFbXaHa9CI3JStqccfOy7oBS2VmMmZEkNfMgp6j2evqjRvab2o\nDgCsR6yqeBXGrqao7k8YKAXlcJW3cVQHAJMmTZo5c2b4q+E139eE+t5T1bC55XWqVCoAsNvt\n+rivW/5tEiVby7tEEETbI4EdQdwmaJaWx+qUSiXLsgqFQo7YROxSMgq7ombX0Z0SdkVHhVLR\ntZLT7sZOOQSUw0E5qlOpVCqV6rM3QnmeBzVwJi78/8Jzu+cKXYTYwNGZnMlX29ko6HcdG+aR\nPh8rmw+4rX8KGQyGoKAg7L6RkxUKRaskXV23bt3w4cN9tXe2vKotuT37p5HVdQRx6yG7Ygni\nNtG0uk6hUDAMQ9M0ukB9Itwec9xSZlfF6ahQjBFyxtQwDkZeiSFJEkKIoiiMsSRJLpdryusv\n15RZsrKyAMBgMPg/6F80qkjQC7QXrd/yBQBsye1lFPSR/sOTw6e0pM+nq77JvKOtJ/s+//xz\ng8EgdBFStqTsOz62fejLbdyB1iOfEXPixIk+KVtbPpGKEPnNnyBuPeTvLUHcJuSQTh6Eo2la\nHq6TXzfEn1Iyqi49O6NGbe6uE44qyXlGo2BU8qcMw8hXsRdsOZQ9ePBgg8HQsWNHnufHjh2b\nuDSRM3GiTRT0QvGU4r6p2/un7Ttbs8Io6Ksadjavw8VVS2lK69mHcB0koL3oBpsQHfjoDevD\nnyiM3R6pyGAwjB8/nqF1AICx1LxKjEJ6r+TfPNIfgiDaGAnsCOJ2UG+ubVpgx7KsWq1pWmnH\nsqxSoTzzR61PWWR5YaXNag+I9HIpGyAnsKmMXKxpTtaNHXK1b7/9tsFgcDqdPM//97//5fZw\nnIlr2NQg6AXrAVsmZ+qftv9Q8UtGQe90X/e22cKyuX1Tt3n6SfyD1atXx8bGtnGjl5WUlLR1\n69agJ4PKPilrH/bSsfJ5nqqZpuklS5b05/Zvyml26lisYPw81R+CINoSmYoliNuB0+1oGnJj\nGEYerGGVjDw3hxBK7B66z7grqW9UBJN2eHOBk7GqxOoEOlSegcUYyyWbQsOLK1+6dCkA8Dy/\nbdu2yZMn99zf013jzr83HwC4/VwmZ6pu3LM9PxMAXfuJd2erl1OoVdaZXd1XX30l74dN3ph8\n4OQLsUEtSufVEnPmzDm/ObeLwI1/1CjoPTUpvHbtWp7nH3vsMQBwumsUjP91XW4U9N3arfRI\nTwiCaHtkxI4gbgsImIuwLKvWqDROTdM7FItS7otyYeehXYdDuIAOPZOjugQxV3BJYCczGAwr\nV66cNWsWz/MN0MCZuOiPo+V0F/7ajEzOFOTdyyjoN+V0u5b+5pfO6pe2y9NP4fJEyU5Tmr+8\nhYHxZ2os+xJDnm+bPlxNM+dLryYmJuaVV17J5Ezb8+9txuVaZYzHu0QQRNsgI3YEcTug0fl1\ndU0oihK9RDWlcWKHnFPs7OmzjKROju7M+Is0y3qrlJh244tIktR07WVbUSqVBoPh2LFjjz/+\nOAAYDAbOxJ19+2xOeg6lozpsnQMAW3N7GwW9lzolI+G7K/W2urGZy/KuV+OhRu9M71qLSadq\nBwBLly5NS0sTGzyZzuvmNH/+fJ7n5ddldRtCfe+7xgu35PWOCxrXav0iCKLVkRE7grgdeGt9\nm3ZCNI26sSzrBpe8cq6mwhybFIcqfQKSldIZ9swWC6NgmvZbNDl/LXO1SdJ27doZDIZ+/frx\nPM/zfOT0SM7EMX6MoBdOPHuiT+q2TM5ktuUbBf252uzL1nDw1Ettc/Jt2Zwyv0F+Z6qXcREz\nAGDp0qWzZs3K65fH7eP2HR+bEPJCG/ThGnk8JeugQYMeeeSRTM4knH3t2q8SRUtCyDOe7QlB\nEG2JBHYEcTugKKopqrs4UANMU0CzDFuw84zTbgtMp4/uyMe+9nC9TuFNX7wsrwlN01pNndl2\n7OotTpw40WAw0DTN8/zzzz/ffnV7zsRZD1gFvVD5bWUmt79f6s7ckhlGQS+Kfznq1uo425pP\n4i+cp51e3b2qG3eplRF/+YCCBpsQF/Rkm/XksvR6/YYNGwIeDqhZURMd8FhB6VwPVj5u3Diz\n2QwACsZPODvtWi4xnXw6QHdNM+kEQdy0SGBHELcDl8tFUdTfw7uKXGvF4Uaaprv06uiwwhHD\nKZbxwme1Gh9VfYlDLiOfe8eybNM07vcf7n9g4P3ZezsZhXSnq+Yq7a5du9ZgMJSUlPA8n52d\nzZk4bj9XPq9c0AvOIpzJmdITvtuS19Mo6JvSoe46NqTNElVJVqkpH+uaNWsSEhLcDW5KTUmS\npGHjRdEtii63y+V2OZxOu9NhczntTqfN5bS73Q63y+F2OUW3U3Q73W6XKLpE0S2Kbvm12+0S\nRbckSS3Jyvjmm28uWLAg9KXQczPPtQsbf6Z6qWdu+6L6Bw0a1Cv5t7K6X6+lfJ3lUMdYj23O\nJQjihiBr7AjidnBxYCfHdvJSueReYQCAEKqpKcelXrooZee+7WuO2/ZuOHLPY12bltbJlTSd\nafy/xSvXrVv35du/WOynf+159/3DNDSl65u69UqtZ2dni6KYlZX15Zdffv/995yJ+3PbrInL\n5Ewnq77ZlJOBENMl4TtoCrXa1qJFiwwGw9GMo9xO7o9TT8eFPI2xhCUsYQxwPj6jMGAEGCgk\nYYwRAAYAipI/RAghhDFGCGMADAhRmMLytuNm98rtdiO2tR6IXq+Xux6g676jgO+ZZLhK4dyz\n7zDU37KuEQRxqyGBHUHcDpxOJyoLRt52ObxrOqMYIWSz2ZUKBdczob7UcvIwlX+4MCoxKq1X\nDMOczzwhiqIcsVAUJR968un3+tydXTIzM8eMGTN69Oj8/WB1Frnn6BGCCL9hKRFT/94BmqYN\nBkNxcfGjjz4KAOvWreNMXPlX5YJeQDRK2/tEXOATphNP/3b0rlCfa13I3xoooIDGTndjsFdf\nURQxliM4jDEGDBIARoAAY4QQxoAQxliUozoACYCiKJAkjDGiKAkAYcCYwliST42Rn95NZdmy\nZfKhKv+YPfZc3Zo2G0klCKL1kKlYgrgdSJLkcp6f67x46I5lWW9vL5VaVZ1fXSjkJmW003fv\npKM1CUnxl0y/ylnFEELF+2ztU4Jfeq9MFfvmmDGPAcC0adOC/Dp8PDX0oymhv+/50SjojYK+\nqnH337sRHR1tMBhefPHFQYMG8Twf8lQIZ+IoH0rQC7ndc7nId7zVKVZnsVHQ55x9ty2fz++/\n/67T6QAAEGAMNFJijLGEVSqtWq1Tqb00Gm+M8bffLZk1678YSyCJKo2XhCUM2M8vSK3WabTe\nGEui6BYlUa/PsFisGEsIMALUdFhgW97RNdJoNADgcDiSwqdsyul6pWIWx8k27BRBEK2IjNgR\nxO1AjuEaqxu1Wi0AIISaDi6Rg7aoTpHgA96BPhXnqnSMlmVZeRJWDkfkF/KKMSyiXqmrEhMT\n24ctTUz8yGKxrN/xmMWSDADPPffc559/DgB+QW74z7/lpru3X6lR/OXYswEDBgwYMGD69Ok8\nz4eFhS3cuBAAcnvkHrhrR+rY7PBXwwHAKOhL61Z3jJ3XNqv1Z86caTAYcrrlJP2cdPTMK+F+\nWZKEMUgAYLHUI4SxJE+84rfffvfVV/8jL5zDkhQdk1BeXsLQDCDQaLwtlvrhw0du374JgQQY\nMMYSlmiKbnbHMjIydu/eHd49vO7nurjOz+SWvJ0aMd1Tdy0zGAzyoF3BuZlXKrP72AgyXEcQ\ntwcyYkcQtwOWZb29vQ8aTzscDqfT6XK5nE6nKIqSJImiKL+wOe0HTIci4sJOlRS7XC7xArfb\nLZd3uVy71hTqdDq1Wo0Qigl6LJMzZWXk9b7ff8LMskcnHvniiwVyc/XVio+mhH40JTRQm7mr\ncJg8hndJZlI5HVl5eTnP8x988EHK70nWZbNqltcIesFR6sjkTP3S9hw89W+joMetcUTvX5wf\nS8MuzPgzddajEf5DKMAXhtgwXDSJam6omTBhUtNl1dXVDE0jCiOE27dvDwArViyTJAB5EhcD\nQtCC7RMwceLEOXPmxHwSc/b1swkh487Vrm1+XVd19uzZu5MuPyFrd5XdqIWPBEF4HBmxI4jb\ngUKhCA4O1mg0ewzHeg5NlSdV5WilafFcQvs4gDhRFP1CfIpPnY2KiZADOzmkczgcNpvNZnYG\npQV5eXldPLGYye0DgNySd4LeXwMAO35R/LHNX6552r8FgNAuXboMePSEnJk0QNe9Y+wnTddm\nZ2cDAM/z6379YtY733L7OXe1O/++fABI3Z6ayZlKa3/ZJHS5rnRk1wg7MR1I11mP5PyhCAoK\nuugTJEkY0PmUD1qtr/yu1VKPABBCixd/+9GHswHklXUAAPJuiXmffIjOb6MA8fwCPEmSKIo6\nv7eiGZ3UarV2u735N3ltmgbtAECSXBT1l8wivxfwZLiOIG4bJLAjiNsBwzDh4eGhoaFz587t\nfO+r6M+IBDctoUMXtnWGhAfXVNbIg3bycJ3dbrfZbBsXHw4KCoqJiVGr1X9vIjViWmrENAm7\nAbr1HFAGAAveiHY4nACwcePGfft8AUJXrFix+0SmPCzUPmxidMAo+dp1hnWbhPT3pswEgBUr\nVnAmzrzTnNsrFwA404AwvwH7jj9pFPSeDe/OfXgufEr42Zq5P/+INvzyTU63nPbZ7Y8UTw73\nHUBRSBLPh2IWSx3CIIdp8oX1dVVDhg6Xn96f1SH05lvvGH/7BeQhPoALuyUwulkX2F0MIbR+\n/fqBA01GQX9xGHfJOCtBELc6EtgRxO2AoqigoKD8/Hyapo3fHblnzJ0AgDGWz6hriu3kwhhj\nrbdWnqttGqv75asDKpUqNjY2JiZGobhi5gkKMXLstfvYw8+/VQQAasez77+RDQBVVVUDBgzQ\nan2HDBkyYlTG/hNPFJbOBYBOsV8cODWuX+quTINi9+7dw4cPhwvpyM7MOCPoBdqP7vLb1wCw\nOeduo6AP8urVIab5R/Wue+utQ0uXSo2NAOCd2D78RRtLBwIAdmFFuKIqZ3vf1F0YixJG0vmV\ndAgQxoABwfkvCbZu3QYAgECelQYADLB7925EyUUoBBjw+a0Y8kO9yWcz161bx/P8wIEDAcDh\nqlSy54cwN+V06Zu644Z2jSAIT0K4JctDCIK4aUiSlJmZOXr06K1vbLW77MOX9dJ6aZRKZVM+\niYsDO3ntnby0zuFw/PLVAYZhYmJi+vbty3GcSqW6xkbN9vy9RY8BgIINrM4d99VXXwFAUVFR\nfHw8RVFr1649U/P9sbKPzfZ8b3VKn5StDK0DgKlTpx49epSiKHmiNi8zT6wTNZwmfnE8AGzK\nycBY7Bg7P0CXce23X1tSMi8jQ97n23RuC8ZYnm52ud3DQn/lTNzmnK59UnZhLH/iVqm0TTWM\neuThPn16j35slPwzUaP1sVrqASFvb3+32w0AVms9AqTWeDdd4nBYKcQgCtE03ezAbsKECRMn\nTpTmSN53e9f1Xi1JtsTQfzWvqqsbPnx4amrqjBkzLh60u2QAjyCIWx0J7AjiNsHz/Pz582tL\na1c8tMI6zFpUsjQ6JuPekbycMezicKdpR4XL5bKZHZt+OMKybGhoaNeuXTt37uzj43O9E4sY\n4y253SXsAoCeSb9+8tE327ZtO3PmjCRJMTExfYacnvT00cPFr1Q2bAEAnap918SlAPDoo4/W\n19enpaXNmjULAAS9AAChE0MDRwW6JcvW3N4A0Ct5g4IJ+McOzIiKUioUCoXiiV9/9YmKuuTT\nA//739b333c4HCEPx/R8aWi70PGSJAGWJCw1pY5AF2YkMaLOL6kDAED4r+EaAowQkjAghBGi\nKIqmEAWIkg+Lua6H1sRsNj/yyCMGg0FIF9L2pW7KyfD4csMmTWfa3RUzL9Cr26acrp3jFvpq\n7mil5giCaHsksCOI28Hjjz/e0NCwevXq/Z33s1+x23et2/XHgkD1g6IoxqWEJ3ULkWdj5cJy\nYGeusU0b92Hv3r0DAgLCwsI6duzYoUOHgICAZgcoAHCs/LPTlV8DQLB35p3RM8eMGVNSUnLq\n9DE/3+DExMQffvgBAHbkD3C4KwEg0n9EcvjkQYMGYYxfeeWV3r17w4XwLml9EhvCWhwndx8b\nAQD90/YhdMVevTeV99sAACAASURBVBsTo1Kpnt+9G+RBs0uiUowBAAOsnzDh5O7dLpp+LT9f\nkiSMJSxJEpYAA6DL/hg8H9v97U15fR2FEFAIURSNKIRx8wM7uBBvCXqBM3GtOoT28ssvV1RU\nfP/993IrZLiOIG4/JLAjiFue3W4fPny4wWDI6Z6j6awJmRXyo7GLt/PNoqKiqqoqu90uiiLG\n+EzVSoRQ/mE2IKSeC3nIftgeMCBgw4YNr776alpaWrt27fz8/FoSnTRxS9atub0AACEWY9cd\nwWufenJcUVERxjg4OHjt2rX+/v42Z8nOwiy5fGLgtH89vQgAfvjhBy8vL1uB7fijxwEBt58D\ngOPlC09WfkEhZb+0nX9va2Z8vFqtHrViRdMu4EtjO4wpihJFEQMIy5Yd+PFH0Ghe3r9fju2a\nNkicv+Ivy+bgwlsXQxf+g+H8dhQKoEVRHbRhYAd/Dtp1sbnKOsfOD/cb1HptEQTR9sjmCYK4\n5clRnb3Ijp04bl7cb0f1mV1nsmLnqKiokydPlpaW1tfX2+32ajuDJSy5ld4BrvCUcPMec4eO\nHfbt29enT5/Q0FCNRuOprZ0MpZFDk4Onxp+s/OpoRdbCJW+F+Q7cs2fPpEmTunXrBgAjRox4\n5x0TAJTVG4UzUybMhJpK8aGHhlGUYvXq1ZyJO/ffc/LoHWd6JiHkmd3HRhgFvUYZ3b3dqqaG\nZsbHazSazo8/bqusRPIJL/CXHao1FOUnSdhb3VDf4CVRcb17569ZY7fbdy5e3H3MGIqiMcYY\ny1shrg/GcjuYQpTk6V+PWzU72ZgxYwYPHpydvW/Vfi2J6gji9kNG7Aji1vbggw/Gx8fPnj1b\nHu/JO/d+Sc2qTG6/JEl2u72hoaG6urq6urq+vn5vwQS3iDf86NPl3oIR92RXj6/u+kvXZ599\ndv369RdvrfAgo5DeK2mDBI7fCwYBAEv79k4xAsDixYvff/99AGBZVhAEuXBh2dziqqW7t9iM\na9z+3qmrV68GgMIHC53FTmWMst3KdgAgH6QS6T88OXzK/HvuEUtL1Wp1z8mT5SxqCCGtTtdg\ns7EYA0CJ09EuNKzM7ajBkp/Lrm10SRjvnj3bbrdbLJb/FBR4/H6bbdSoUdOmTfNa6qXtqC3v\n+rlO1S4qYETrNcfz/NQ5iprGfUE+d3dN/LH1GiIIou2RwI4gbmGnT59+8cUX5Vm88Knh/sP8\n/3ZKGXa5XPLuV+PRvliChe8G3Td677ihJYV9Cu/ad1dWVpZ8bm1ruKQze4oeabQfA4DOcV/4\naTsDwIgRI44cOQIAffr0+eKLL+Rie4tGzX37j3Nn3CEhISt+2AUAuT1yJYcU8lxI0NNBcCG8\n071hYTQxSBkY0Kub2amU9y84dd4qa2OOxi/NWltkLtB5tw+VoBBZk4PDnOdqMMYn1q2tray2\nWq2NjY2vFhW10o03A8/z69auy+2Vm7Yz1Sikt+psbH5+/tb8jOeG1JM1dgRx+yFTsQRxC5Oj\nurJ5ZQAgR3V3t//54gIIIYVCoVAoNBqNrx8DAEqlUq2hdDqdEilpmvbx8SkrKwsNDfV434xC\n+sXTpgDQNfEHALA4ju8+9hAAqBWRy5evAYCKioqePXsmJSVRFDV58uSxY5f+9C24RHP/e+/q\n2S/hrgzFhNUvJQQ+J3QRyj8vT1iakMmZ5qSlDrqzZs/JAKXSVVxiiO7b93yyjZoaJ6vwamjc\nweq6+cRDQ73D7ra6G6w1jgPIu4OXzallFPUKefuIx2+5hRCNsKMtzsNDPuttjUoACPMZuCWn\nV9+07a3dIkEQbYbkiiWIWxXP848//jgAVH1bxZm4bXn3MJRWpQi+bGF5a4E83Vp4ICbv3Hux\nC2ILhxXOmDFj9uzZrdNBrFFG//1drTIhkzNlciZRtMpJZnU+joKCgoKCgv79+7///vtJSUn9\n+vUryDu9fdPxHZuPHzsUNvbh/y5a26Fs8djQVY7jo44LekFB0SXmIDlmZVm26o8/nLW1YoO5\n0OZ0VJT7VZTVHti39WzloTrxpMieKy6pskNtRfXCgz+VS2blBXNSUlrnxm92Z6p/eGbICZ7n\n06LeErH1RneHIAhPIiN2BHFLWrFiBQCMHDlS0AtJhiRRcrjE2mucVjt+JOpc7erU9NecxU4u\ngcvPz/d494yCvlfyr1cv0ytlIwCcqV6+69hQAPBVd/z004UAcPbs2VGjRg0bNoym6ZSUlF9/\n2dzY2Pjwww873DWTZ4+DxWDZGKlcqrSCf3CgrvLMGlVoFhJF87Fj6sDAiOAwl1sEi8Vby3ao\nrtlf3SBQ6kiHbW3jsbCKgwNTktRqq7XRKoqiUql0Op0ev/Gb37naXxCidTodANTW1t4RNdMo\ndJHTARMEcRsgI3YEcUtavHixwWAoHFpIqSk2lN2S26N/2vX/v7k1V9gqmMBrKRYVMCKTM/VL\n21VnOyQP4IVFBG7fvr2goKBjx44nT55MSkoaOnRodHT0pJff+GhK6EdTQou/Od7jrlCbE6x2\nt2/40IgAS2iCimEYFTjcRQUnG+sprfKwS6RctqIGd22x+agiHNVXW92+p+qrSt3lKp1KqVSG\n3BFy7Qk22kBCQsIff/zh3dvbst8S5NWnuOqHVmoot2R6/7S9AGAwGEaPHh3ikwlA0sUSxO2D\nBHYEcevhef6LL77AInaecabuSDUKXTSK2Ksc4dvGjEJ6RsL1xSUUUmRy+zM5k78uY0vO3UZB\nX1y19Pvvvz9w4MCiRYuUSuXmzZtfffVVALDb7Wq1OueUvWke1iqF159DELzTpTtWXSvoaJXB\nenJ0o3nrqaUBqm8ej4XHxIrhvtpKVXJHd8Dvx3cGxoQG3xFmO21TKpVrn3uudZ7Bdfvwww9n\nzpwZ+VbkqX+d6hAzu7BsTmu0ImH3Je/s2bPn7vYGo5DeGs0RBNH2yFQsQdxixo8fz7JsRESE\noBfSdqfVW48CSN3br2hebZJTYlnW0wenYS91u+Zd2Sl2PgDYnGd2Fg4tLJurYPx69fytZ8+e\nGOOsrCyHw3H27FltWJiycZPCe6iCZRRKBQVmlcp3ddU5zqvBmRCf5FU8uEFX4RVeytbG+ejY\nOuTUwJKTK+70u+O70hSUxi6yrhxa3UupUTmdznLTzbInlKIom81G6SgstuI46uacrhfnKzMY\nDPJ5xQDYLdkYSt16TRME0TZull/xCYK4RidOnFi9erWgF2h/GrFo/4knmnFiRUzA6IKyD8Om\nhlV8WjFu3Li33nrLU90zCulc5LstrEStiJI3WLgvbLBwitXZ2dkbNmwYOXIkAPiqkVbFsqyC\nhu+qKw47Qr6Oq3ezalc3TR/XLqEIb9nAvB/sHxnb2Pmbiq/8Any9QlRHFAeejkEZil7DRX5z\npMCoWJZllUqlJ2761iAn871k1y3DMB9++GH/tH1bc3vekF4RBOFZJLAjiFsJz/MrV660F9gB\nIGVjilFIbxc64bpqQAgDQLuwl85U/RAwLKBqadX9999v8uTAFQ71vc9TdfVL25nJme6ImrUj\n/36joN93/Im33nyTZdkqZ1TF4WU0w1Ds07R0HMoe6BDVL8n1uKX+rE9Kf6dYc2eNdy+x32Zp\nz93qXvNPLjGX1DOl1CLtur3uk8uYHQ/U9KHdiGVZlmU91dWb3+acbv3Sdl3y5po1azZt2iQn\nRjPbC29IxwiC8CAS2BHELYPneZVKpVQqix4t4kzcyYrFADgm8LHrqwXBhWjG80vmN+f0SAt/\nw+PVhvj0lwfwGu0Fvx3syjCMsqE4KpBlGAaBU+vd26fBEhAoge9Sn0angqZ8pFTKW/ILDER2\nV1JE+xcDRz/W/uEuXbsP983ExRXeGqUSHCzLMgzDMDfRcpT27dsXFBQoIhRWwRrmy5+s/Nbj\nTVBI8fc3w8LCHn300Uxu/96iUR5vkSCINkYCO4K4NZw5cwYAVqxYIaQLwc8GA8Dxik+blTYA\nq9WttZRKwo4w/1ZMP9ovbde9nffRNB3a6SGJoimKwodXW45sZ84eoPPttdYQp1+kqiS/9Oy+\nhhrX7lMfD6b/vVVc/PnZnYHe/sEN/jY7iwL7Rlclnq5z0DTNMAxN063X2+s1ZcqUd999t92q\ndifGnkiLfPNE+WcerNwo6Hu0z77sRwsXLqyvrwcAhNjiKpJhjCBubSSwI4hbw/PPP28wGGpW\n1QCG4GeDjYK+d/Lm661ErYhECLRabW1t7fm3PLdlwijok8Je8Vh1V8YwzFnTT2p1go+z0u2w\nebH4pN278kQec7oI//Q5btfZt5pR+DlCg2I2ub9BWDE0Nu6jvcvaKWLWHwlH1bG9vBIPQ6Qc\n1dE03fW5rjzPP//885J0g0/9CA4OrqmpQfT5bwkGD+fGUCvCr/TRPffcw/N8/7TdhWWtdFo1\nQRBthAR2BHELGDRo0ODBgwHg3HvnOBO3t2g0TalZxvt669Eo4ihG1Gg0NTU1wT73Vjbs8O7n\nXfVD1dNPPz137tyW9zMq4KGWV3J1GGOapkO6jPWP1+/bsTFIIQWyav+EqpBej9t3SjZf0V1S\n1KBwV+VASfGZ52LHu2qsDU72/7qPVSgV7VP2SKEbVIz0cIRNDuwYpdL9mPvMf85sDt48ePBg\nnueffPJJt/vSM0FudVvz+iSFXi3mfumll+QXCibwwKl/t0mnCIJoFSSwI4ib3ebNmzHGzz77\nrKAX2q9vj7Fotuf1Td3RjKp0qnjfwEa1Wl1TU5Ma/n9HzrwSPSu6bE7ZkCFDNm++7vG/i23J\n6Rnu14qTsE1EUaQoiqKoOuSlH/Icc89kX/4570Po5KpP1VqFOiDGK/EO7zLw7wAKlYphmCDV\nXTuL17Asy9DMQ9oe/wkextA0Q1Pn52FtXb6Z8M3+pP0+9/iUTSnTvaUDgCFDhvA8z/N8eXl5\nG9xRG3CLjVGB/xBzT58+nef5Xsm/1jTubpteEQTRGm6ihcMEQVzW3LlzDQbDyWdPIgVShCiM\ngr5v6u/Nq0qrivcOMAf4BdTU1DC0Dv/tuNpmE7EtNcLz2yb+zu12I4QoimqaS23MO24HWsfg\nygGsUlehXTy3OgYsB0ODu1VtKF2QFT++cPehtw7/BhQFGv97U4O5+GiaFuVKZts3KNHWFwe8\n+DX7NQb82BuPsU+yEaqItfq1CxYseOqpp+RGn3nmmaysrDa4u4CAAJvNpkpUNWxvCE8YfK5m\nbbh/S9vddezBMN9/jrkzMjLO90HXdVtev94pLQr0CYK4UciIHUHc1Hie/+STT0ACywFL2q40\no6BXs5E01cxcWDplnG+AJTIysrq62oOd3Fn4YJBXfw9WeBW5Zz7cnv6HPGhH03TxphVlew3m\nWIdvhweQt9trsc3vxelp+9C4AS+fOqILDFS8NmN/x9iAhPjkx+/t2aV9zEbT6Y+XbKNpmqIo\nhNCE1zotWrXoy6gvp4ROOdHnxPdvfb94wuLqndV3Lr/z6zu+NhgMBoNh3LhxCxculMfwFi5c\n2Kp3N2vWrEceeSTxx8Qzr5xJDp+SVzqz5XVaHcVpkdcUc3/77bc8z3eM/dQlNrS8XYIgbggy\nYkcQN6/XX3+doqj4+HhBL6RuT7U5SwCgR9KaZldIU1rvIEtYWFhOTo7nugk2Z3GP9qs8WOGV\nbM7p3lBvSwqfAce2yUNu7R54dP+Cz3SxTleEI+L4A8czs/OrptqeUNZ++n4580BY5PaZb/X4\ncH7e5Je5WrMU7Esf/IN6eGBnikIIoWIzY3kuKG/l0AkzwW0L+fSthRAKvXv3Nj5gLHqkaOqw\nqal5qZSSEh4XBg0aBACnTp3617/+tXbtWgCIi4ubN2+ex28wNDRUXuGHRUwhBT5/pHDzHTkz\nlaX9rrFwQECA/CI5/NVNQkZ/bm8LWycIou2RETuCuElJknTgwIHs7OycbjlsOEtpqJ2FWc06\n3+RPNKXSeduaRuxoSmdxnPDq5VX3c13//v23bt3ajDp3HRsR5NWnJb26RkZBT1Oqftw213FX\ncR0tp0FDCN094WXrt/VMcVRgpG+Pzu84nW5ss0dNfee1fyWbfk75ZnHpxH+lTpxqWPHLH0cL\nzr79Qt/ECDXGGGM8zrT8C3bNlyNiQ8cu1tgUE2aWvfR+2bpfPx82IWtxn8Xrpq7LfSb37pq7\nUxempi5M3d57e7gqXB7Dy87ONpvN8hheVlZWVVVVG9z+ZWGM5X9jLImiKIout9t14d9ut9sl\nuu092q0X3S5RdGOMAbB82ZUqXLNmDc/zkf4jPb4nlyCItkFG7AjiJjV48ODly5e7a93YhZOy\nk4xCeqT/yBbWKc/hhoWF1dTUAEDvlN+25PTo98HevH55LxpffPDBB/v06XO9dVodJ7u3W97C\njl2dw1W1o+D+lIjpEX5Zh+45ZDllOTJYneh0nt8AUV3t43KH3XHn+lcm3jf73cHx8yynT5a8\n+lLEBx//d/Kg//usZNr0ram9Mp4aEOh2u2tqGxQs5XK5KsE+bGjAvnSrfal9knmS8wnnB76f\np/wvac6XE+qsh2e8tLpnv9XR4R2/X7ICAH6p+OUF1QvSOunjnz4ObwyP/Sp28eLFACBJ0qRJ\nk8aOHQsAFEXNnTs3MTGxVR/FJZoy/EoSxlgEAMCShBEAAMYWxymtIkGO5xCiJEmkKBohgCvn\nBZZPbK6tre2a+KNRSL84sSxBELcEEtgRxM1o5MiRgYGBarVa6ClwJu5M9U8AODn81RZWSyEl\nAGi1WnnEjkIsBgkxSLJKCsVlchL8o13HhnurUlvYq6v748RztVZTf24/AiToBUzh9KXphd8X\nvrp375zu3WmaRr6+Se+9J4riAx/MoYAS3e68vXs7zpgliiIAvD0utLjU98NPDJ/WdXlisH9J\npRge4LLZbG+dWJzckR0X4P/x+JOF95iXLFkyffF0x2CHntVPnf3bjs1++edmTvr3Vz37JSAE\nS5fNEkYLpnrTcynPucpc498cn3EyAwDCp4U3HRMzb968CRPOp3f797//fd99zcyrRlFUaWmp\nprPGvMvsH5ZR07jfX5d+lfLy6CNgCUsSBgwAkiRRCDCCemthdMCToihSCCGMEUXLI3zoyoEd\nABgMBp7nDQbD+eE9giBuKf/P3nvHR1F9///nzsy2bEtvEBLSy1LdkAQCQhKsCwgIiB0Vyxv7\n264oojQVsSMqNhSlqcCioKFJCJAsiDCbQKghnbTdZPvu3Pv744aVN01KAvy+n3m6jzjZmXvv\nmVmTvDznnnPEUKyIyFWH2+12OBxff/01n8lrrtcAwP66ty8xCEvxZ138U6D40nC4jw5I/LZT\npjojhfyAVoepQGeiqk6Vo+q7o+/777+/fv36nnq9w+12uVxut9vr9Xo8Hp/PJwhCzTtvt2zb\nihlGOEF0GDd2dIbF3ubz+X74nXe5XPMFIb3nA+atKXFBYW8ESWYXS6L6ffDb+t9+K/vNHGce\n+8TY4QnDFXMnGlcc2LLhUErCoInjnh+Sn2Cpenh+lG7TqE3zn5h/73v3fjftu9o3a3k9z+v5\nww8cfuyxx2ig9p133vnwww9poPaZZ5650FtesWLFww8/HDcvrvrV6r5x7+46+si/jSCEYEwE\nTAjGOCIiOja2p4AFr9ehkHRPTEwKC4vYUrQFE0wIwRifj1xjGGb9+vVD0/4s5PUXar+IiMiV\nRfTYiYhcdYwdO3b16tWtq1uBQI8ZPQp5vT5+4ZU26gz8XflfKRfcRZMTIOv5zABp3MDk5Q2f\nNzQuaEz5LUUSJjEYDF6vd968eX9s+OMm81froscihAghUqkUY8yybOAj/xkslXakIBCCMcYY\n907tlp7o83i8U0bHL2sVrOus2S9lp6SkfDr9D6Nx1w97ss3tf7WVKgOksctW/R4g7T579uxJ\nn0+CX+CurLs+X/wtALz77rvvPr/W5ip6cnr+7EAmQNr9MfJH4XuFOYE5c0PmHrz1IK/nAUAa\nI01ZmmI0GgGgpqbm0UcfNRgMABAVFTV//vzzaU0rkUgEQWACGMEiUA/rOaBCjRBMCADg4OCw\n5qZ6AhAQoLFYD4cHX2O3WxGgnIG5O7YXE4JP+OrIuVuOrFq1ymAw5OfnAwDGHoa5GG+uiIjI\nFUEUdiIiVxcGg6FPnz4IoZrXa3Qm3Y5DdwFAYECfLlpOxoXbnAdliTLPcU9ERMSuXbv69+9/\nnmMb2zd3ih/xdFpspl1HH85O+EGlSDIPNBMP0Zl0AGAwGFQq1eLFi18vfn0pLJ0QP2GB0/ug\nw4ExFgRBKpVyHMcwDHa7qdoDAHrK5/N5PB632z2zaU1g4PVRGVHKT5QTTBOqqqoMBoPRuP3m\n0pt9nsqnpMLav1NYRvrok6YXXnjBZrON7DNyUcIiuUz+a9mvTz/99JYtW+bMmkMAP/xq1Zwg\nRACm1H69zbJNPVe9MXsjduOyQWXmHDMAMHImvSj9559/BgC3233rrbfecsstACCTyZYtW8Yw\nnRMtQQhhjAkhBOPeffo1N9cTTBCAw271Ck4AAEIIIsVbtxBCUEfmBB35LzOHhITMnj37+RdK\n1/OZl/gp015tCHUEjREC2ryNAQKnPgeMMaIX01uj6SGoA7aznpuIyP/DiD8kIiJXEUVFRQAw\nY8YMXs/HfhCLia/dWd5F4omiT/h6b/WLsW/HHrrt0MKFC1977XyLDJfXzJJxEV1h0tb9o3Yd\nfbhAZ1Ipkng9DyzoTDqTyWQwGKZOnfrjjz9mF2cb3caVt61MTUxVKBSvtazY5PM5TuB0Ol0n\ncDqdTqeTvm+32z90u32sxuL7JffR3PS09CPDjrzzzjtKpdJgMKzJXGND2tdtgWMy7UpZ4u97\ne/9Uqmx2rdpwaMOGQxui1FF5CXn5CfkymcxoNM54c+aC6VHvvRAJdbOWpTwyOxDabLuSfldm\nlfTRmXT0pcpV0Sgtr+fdxe7Vq1fTQG3//v1p7zKDwUA/7ksEoY5XRcUBQgAQEAQCdksYuc1m\nUaoClcrAXX/9RYBuxSMEyPk0CP7mm2+KiooQIABote+8dAux0JG8izEGIhAiYCAYCxgLGGN6\nIAgY0VMCxoIPY0HAHRFkKkxJRz6vuPlPROSsiB47EZGriNmzZxuNxkOTDgGAeqC6kNfnZ5R0\n6YoKSbjdfUSaJBXaBDhRPuN8qGld0RWKs5DPBCAFOhPxEnOOOezBsIgHI8aMGePxeGh8U1+k\nR4BMeSaHw+H1eiubv1a1afcKwpxff104enSY3e4vPkxvRxAEr9f7OcYYIZlMlh41imh+cCin\nDVi+a9/AfeYB5iUlSwwGw8iRI7eu2qov0g/cOrB4UCkAHGj4aOeRyTuPTA5SXrNwx58AUDS8\n6IWJLwBA6DWhRqPR6/WOHj0aAIYNm7jzv/+tav5x1O6Hkn5XIkDGXjOSZ3d0X236runYs8cA\nABCE3Bby8ssv0/d/+umn2bM76g/feuutNLWWEhoaevjwYXmq3FPlCZDGNbVvCVUPPuPjQgCY\nIABEANHifP8UQEHAANhtFgDIHTy0eOsWBjHon3H/TlZW1r333vv116ZCXn8pnzXN7cAEAwGC\nCSAMBIAAAUCM34uIAANikNAxBANBVMARgqmjDhM4cQPnZb+IyP9N0Pn/HhcREelSDAbDc889\nNzh3sHmAWWfSbS4fzjIBuSkrO2t++uf501+0D99iPZH2+M/7vJ7XmXQnv38OKurm1lv+GJK2\ntrNsAwABuzeWDQpVD+4bO6/y2cr2je0Z2zKQBNE9akajsd5VbzAZ7u1+76NxjwIAIcThcCxe\nN0DlfmXatGl5eXkMw1DXjobjIljWC3DE5aIxPI7jlEplZGRkenp6eno6f/wWiYTL77Wd1/Os\nik3blGYwGOLj4z/44AN9kf760OtnpM6gVvmwY9XOMADgWNWIfnUIMbVzaid/PtlJnIokxRdf\nfREWFkZjrP37958+fToATNv3wvfHPgSAdyNTYrTX9o2dR6dq/7O98ulKeqwepI59P5Yel5SU\n0IEAkJWVNXXqVKvV+tRTT30649NDEw8df2Jf8ab3ghQ5Kf37Dxt/Wr0bQjDBgiAQ4istMR0+\ncnjs2DECbhuYc/2OHcVabWibtQkIAgb9uXnLsGHDWJZDDAsA5xnTpP89bCob2i341qTIRy/i\nY8UYE4KBdDjnqKDDBACAQSf+BCEGaKQYIUz9iQghIJiQjmPEMggxLMcgBonRWBGRcyIKOxGR\nq4KXXnppz549RqORCixMhA3mrM51iXWisLtEF87pHDn+1aHjH+dnlCKEeD0PCHSlHZvqYmNj\nP/7447t231VuKzfl/s+ih+q/OFj3bUbY4nHjxj388MP19fVtbW1ut9vn89HyxbSlbEBAQHBw\ncPfu3RMSEnr06KHRaFiWLeQzZZKwwSm/8npekaFI+CbBYDBcd911jz/+uL5I/3rS6zdH3Hzy\nWqtMIT7iAoBBycYI7bCWNS2LXli00rFSkaxIy0h75513qABlGGbVqlUAsKx22ZzDc6yOffMi\nk+UMA4AKdCV+VxM/gAfcMbOuVOf3QI0YMYL+To6x28NUKrplsMNfhTEhxOv1egVh1q+/+g0j\nBGMsEIwFLCgUKjr83nvv/uSTjwoKri8u3qbVaq1Wq8tlZxjqy2Sp2D2fz2X9+vXz5s0zGo0X\n/YlTpykhAiGCTKZkWRZjfPjQgYiIsACllroYf16+9Pobr0cANTV10d2jACAgQOuwtxEgCEFA\ngNbttCGWZRiuow6f6LETETk7YihWROTKQwihqm7fjfu4MA4ANpiz8jMuU21YllFh7AEEQpsQ\nFxe3f//+lJSUc1x/5PhX/5qteUFsLBsiYAfVDbye5yK41DWpy5cv//rrrz/55JMePXroi/QA\ncIqqA4AjTZ9e3880cuTIefPmdevW7fjx401NTVar1eFw+Hw+hJBUKlWr1cHBwWFhYaGhoRqN\nRiqVUk1ToCst5PXm6td1ptd4Pd/0XROt3zZkyBBTrklfpO+l6dVD0cO/1kh9MwBsKhu2tcIA\ngEITcp/YdBLifgAAIABJREFUu/YB0wP7H9r/TMUzN2y7QRIs+eWXX26//XaDwSCTyVasWDEu\netzWlq1PlD0BAOMCGOAzAQABq4//SleiAwCCyaG7D/GZPAAACwlfJaxevdq0cePqefOkISHd\nEhMnvvqqTKHw20AI+emdd/aXlk4bNar/TTeNfOghAABAAAghBiHicrY3tm/TKNIljAYQFBb+\nTn1f6ISUQ4ihh1T4/utHk5+fP2/ePADQKNJKDt0zIOGb8/xM6fz+tAksEEyIpbVRKpUSQl58\n6ZVZM9/kOK7N2kQIDB4y7LobrgMEBDDB5MQMGACG5V23Zs1KTAiDCUGYYIRY0WMnInIuRI+d\niMiVh/rJiIeYB5p1Jl0hr4/Q5veKmdO5q5zNY9dgXV/dsqyP+qOK0RVhP4W9+OKLX3zxxb/O\n04lWIcTlZ2x3V7oPjD0Q90mcaoDKH34FAH2RXskqN+dsPmVgfetv5prX83Xb6b1gjL1er9vt\ndrlcXq+XVieWSCSyE7Ase7qUoaVkAgP68Ho+eWWytJvUYDD8+OOPKpVKX6QvGVTCoDPIiC37\nbmyybSVE0CjSclPWyiWhfCY/zzqvSlMljZQ++uijixcvpr09Vq1axTCMC7tyi3MB4L7u9+VA\nebNtG52nb9zHoaosenz0P0dtJbbFoS8GKKXakJDJ77571v4QhPz+5Zd7//zT6XS+uWYNAGAs\nACGYEEKEo43fxYbeDoShe9c6/FsEGIZBDOMXduf/Adlstttuu+1inXaEZiVj7MNYCAjQtLe3\nsAxD/+xotCHtbS30uswBOaUl26prarpFRwOAUhVot1kQQgFKrcNuGTjw2u07ihmGOeG0Ez12\nIiJnRfTYiYhcYSZNmqTRaADAPNCsK9U1tG0AgE5XdecgQpu/t+p5rieHnTgsLKy+vv4cFzdY\nCztrXY+v+c9918eF3Z8Y8ciBCQfch9z+miYsy65cufKvtr8m75n8ZsqbN4TdcPpwvmZqgc40\natSoxx9/HAAYhqECTq1Ww4ksEKoAzqEDCnSmQl4/OHWtzqTj9XzGjgzqt1u9evWWnC0Dtg44\n3U0IAINTfwOAivp5h+o//XV3rEaRGrRE/3m3z8sGlTXUNMx+brashywoKCgrK2vkyJEAsHTp\nUlOuySW4crflfgkwOHjwvPR51S2/7D46hU4YFTgy45NX35w4UeWTDx43Lm3gQLvF8o/dqKNF\nGJzIJhg4Zkyva6/9cebM10aOfH3VKoQYQBgJpKLhPZU0DiGOJqJ2JMl2FBU5sV3tAlWRSqUC\nAEEQeoTcsaEsNy/9AjJ5ae0VhAABYgDZbdb8guu2b99R+MfanJxsOClZx2q1EkJuv/2uUzqg\nzJz5BgHY/fffJ5JCMCEMvZHzdDqKiPxfQxR2IiJXErfb3djYSLfWKQcqAcHeY891aX2TS2Rv\n1QudYt7uyqeb2v/0h18Rg3QmncPhGD9+fH5+/lNPPXVdyXUtnpYz6ioA8PhaqFIRBOG66647\n+dS/irlToNouP2O7rlTHZ/I6k+7nn38eMWKE0WjclLVJX6Q/mw3JkU8lRz5V0/Jzee2MyubF\nzfbtzNeSoWkbI3PfI/XklYpX1rauBYD8/Pzx48cDwLfffkunytmaoy/SKxjFloEmAHB5GooP\n3PLb/A0cjlAolT3S0hwWiz94+j9+O3+1D4wZhlEplQzDzLr77he//YYQhmEZq/2v1OhnaUQT\nMQy9jHRkKiCEEL4oMeRvMnas+fsLGkgAENCkXSq0YX3hOgQQoAp02Ok9AgEgmDz+2GMIwY8/\nLIqOjgaAAGUgAhh+3Y07dpS8+urrLMsCACGAACFE/CL1Qm9EROT/AqKwExG5kowdO3blypW2\nUhsA9PygZyGv79NjbtctRwOUF01j2xYGSS7djPV8FgGhQGcimJgHmBW9FAlfJcyZM2fLli0/\n/PCDWq0+26Y6P3/uu65AZ3rooYcyM8/VR/U8GZr253pzdoHOlLw6mSaRzJgxg0qZlxJeOoe2\nA4BuwaO7BY+2OvaWHp7k9jat29NH9nlwpPbmmXfOxPW4XCj/Zv03AMBx3N133w0ATzzxxLbh\n2wBgYPFAfZFezao35mzMy9i248D4gABFVFycy2rtqFxyJu/aic6wBGM86NZbty5f7nA4RhhG\nBAYFPTktjGE5hia9Ak19ZU8ZzlyCGLJarf3jPj05IPvIOw/WtFbT4jIYY8Bw3/DJo4bd8s9y\nDIOxAAAMYj75bMGoUYbwsAjwN7/ocECCSh1kt1kIAI0aw4nzW7cWO+xWQAgI3H//5C+/XHhi\n95DoqxMROSuisBMRuWKMGDEiIyODZdmjjxzVmXS7jz4NwIRpru26FWmjrbPBKBjBKigUCkEQ\nqI/kFP4+9tQluusIIevNmRJWe23aestaS/Ur1alrU7lQzr+pTiCCvkifEJCwpP+Ss02CScdd\n1NTULFiw4FLsoXBswID4b6lkiZkZw+v5PqY+Y8aM6Sj20Xwuvx1FG9CrQGcSsGtjWS4AHG38\nSv7xGgDoNfXr2VWzAWB63HSaqzt37tz333//7rvvLh5fDAAjS0fqi/S3zItVqVQKhYL4fK72\ndirsGBpPPQVa5ZcQQkhrTY1cLscY5wjCMaWydO9C4xeDAQzz58+PiYm59MdyMn6nHQA0W5vv\nf+ceiUTCcZxarVbIFCzD2l12jPHirYu+3fyVlMh+eH0pHYhQh3vtkUceuuGGmzdu3BQUFORw\ntAGAWq2OiYlXq1V2exsCBEAYlgXEAEBwcDBimGeffZoWNyEE1q5dBx2llQn6RxuK8k5E5FTE\n5AkRkSvDwYMHn3zySRqE7f5m98AbAju9hsgpFPL6nJ6bF/0RfUryBADUthrrLb8m17/VsqKl\n9a7W+fPnf/rpp6cMb7GV7Do6pUB38bm6VgdfevheXfc5kYH5+wr2+Sw+/6Y6pVK5ZMmSFXUr\nZh2a9X3f71NU50rLLeT1eenFb789r7q6+sMPP7xoe06hsvG7Aw3vFehMVS9XWddZdSbdAw88\nUF9fbzQaC3YUWL3W0tzzundakA8APN4WqSQYAIL/uEf6/TBAcPTlo59+8SnGuL6+Pjo6ulev\nXrNmzXI5HJ889JBSqZTL5VKpNEGvRydKnJwcimUQi7FPsEoiJN2s6nqn23Z4506Px+Nyuex2\ne9aDmc7A7/J1O7799tulSztE1T333DNu3LjOej4Gg2HWrFnTl7+KOCSRSBY+/Y1Mcobk6OVF\ny37assztdq+YthIhRDAmQLAgYIIJxqf/zUGAyElaze+wQwQhhqEBWEIIQkCL2NFyLWJvMRGR\nsyEKOxGRKwOVVtXTqi2/WnQlukJePyT1DykX1HUrbjDnXtN9zQ8be5wu7OA8qtldou7cWjHW\n6an8Z1OdBGVsy6isrJwyZcrkyZNHjRo1cOtAD/Gc2zEGAIQI681ZBTrTeZbcuyBKDt3T5jQX\n6Ez7R+731np1Jt348eMdDofRaBxQNAAD/lfzTmaDeSAmHoQkhHgBwNeEuz3zDQKUsDRhwpMT\nMMYHDx5MSEgYrFKp1WqlUimTyagbLDw+nmOlAvYCQlJGVmVu7JfQjyiEZl+9sjFaiG5pPOBo\ng/1ej4c2wHU4HDab7aYDL2tv1Ma80eGr27hx49y5HWF9um3x0p/PLVMNCoVizgPvqAM0/5PY\nQaHpDQBAyOPzp7icrg8e/SQyOLLDw4hxR1uzjkAq7RtLh/ubTJATs3YUL0Z+3UcQ8cenEcMw\njJg8ISJyRsRQrIjIFcBgMDz22GMAYDFadCbd5vICANSlqg4AWDbgovfYOT11l7J0Ia8HgAKd\nSXAK5YPLg8YEdXup25QpUyorK1euXMmybEejsPOQTevNWfkZ277//nu5XH4pJp2RAQnfbCzL\nLeQzC1aV8nrenGVeumOpwWCYOHFiyQ8l+iL9GNOYn/Q/nedseRnFALDBPIgAsEwAE4Ybvp6E\nndj9+LSZ9TO7v979490fb9u2jTrqOI6jqo5l2daqqqDA6OojLQmJUcHOkOZ2R3V5g0NZGxil\nrVf8DS3gRFZEgGVZWhaOtk1L/im5YkyF9TcrAEhjpcNWDBs2bBgA1NbWPvjgg+vXrweAbt26\nXXTwesxrI1Uq1XPjX/Bhn8Xeimiy60nBUEL/IQBApt395hvfv/b0p4//8PIyhBDGgFjmRGZr\nx/X/qLITMVWEOjbZEVqihQVCEGL8Pj1ywlcnJk+IiJwVUdiJiFxuPvvsMwC4/vrreT2fbEz2\nClavYLkMmbAcUpx7j9052Fox4mIbD/jWm7OVsvicpKW179S2/Nii26EDFvyb6mw+29CioQUh\nBbPTZp/nnAhJfvjhh05311GGpRdtMOdsKBucZ9rCZ/L7bthnXGs0GAyPP/646QOTvkg/8+DM\nlxJfOv8J8zK2AkDJobvbnGUAkBb/wv7Z00EgtRt6jPr5jetuyS2t/E4ul1N3HcuyHMchhBzO\n5rAARaut1mqz1tc3OZz23lF6q7cOa52ugwqZVC3p3u7PWqA1/H5e/v4E07N00YpbKng9DwCA\nIPmnZP+zmjx5Mn3yCKHPP/88MjLyPO9i8luTlEqlQqHwYaHN2Xa23A7qcyOEYIzvu+GBr9Yt\nnPDm2CWvrBADpyIilw1R2ImIXG5WrVplNBr3Dd8HANJIaSE/8DKoOp9gY9kAn8/HnCkrgkII\nJqjDnXJy/oRPcF7corWtq8tqXs9OXKaS9zTnmImX+DfVhYeHf/nll9P3T1/VuKowqzBQEng+\nExbyAwYkLKqqqro4e86TvIxthbx+24HxOaVLeT1/7PljNHXgu+++M91p0hfpcwJzhoUOu6A5\nByR8CwDltTP3170FgPL77FjPZtfn38u/m6FRa6RSqVQqpR475kRKrDSIOcY7OBtytDvCA6Pc\naVUswJH11ujgIFmKw0f+uZIQIpfL6/eYC3k9Qkzf2A+Sf8kGACBwdMrRitEVAAAMxH0Y9/nn\nnwMAIeTVV1994IEHAAAh9MYbb/Tt2/fc9juJMyAgIEAR0O5qYxjG38vC77ELYLUC8bgEx4ms\nXSJgISAgAADGTR+97NWfL/BDEBERuUhEYSciclkxGAzz58/HNuxr9elMukI+K0Q16DKs6/VZ\nWUbh8/kk3JnrlcSFTapsXBz+wPCaGTXTp09/5plnaC8pANhUPvgiciY2lA3G2OnfVMdq2LRt\naUVFRbNnz37rrbfS09Mzt2QSRC5o1xoA1ijSbn+k83fXnQItbnewYb7O9Aiv51t/baXaTq/X\n04Zj6wasC5GGXOi0adEvpUW/dLTp6/V8FgAMSFpUIXlXegKO46i7jiq2piqL1hWu0Yb6sKfB\nUxlVndXe5PBBraafm7CIwxwhxO+08/l8crm8QGeqqJv319FH6XKJEY/FfXIPPa57v+7olKP0\nOPLpyDfeeIMeL1y48JVXXqHH991335gxY043e+LMcTRpVyKV2Nw2xND+FbRQMACAzB7U4Gt2\ntTkVMQzTqIZwh9vrdLodMpmMeu/cHrdM2plt6ERERM6GKOxERC4ft912GwDExMTwej6jNKPd\nuR9A6Bf3/mVY2ovbWCbgbHVMACAh/OH15qyCh+7k9Xz/l/u/+uqr9H23twkALrSuhH9Tnbfe\nu9+wn6b93nbbbTabzd8ojEXsjtwd5z/nxrJrkyL/e/z48Quy5KKh2i5Mnasz9eL1fGBeINV2\nK1euLM0tzSzKLB1UenHbvOJC740Lvdfmrtx+YKxMlk19dSfHYSm2dm83jepwfXlWn95H3Ifb\nal0VjWapRpBUB1uVTZXmmrShPagBGGM6CX3sCHESVquQdq9omHew4UMAUMoScp5YEvVEFAA4\nDzkPTThU/249AMiSZPf/cP/9998PANXV1Q8//PCXX34JAN27dz85LVqhUMhkMqo+rU4Lx3EI\nMQhAJpV5vB5ASMqpHHVuEmPz2dWV9RXhaqVP8PHH9tAtgD6fb9Lcuxa/uLQTPhUREZF/QxR2\nIiKXCZfLRWWNeaBZ2V+JENpx6I7L1mTC67NyjMLaYmXZM//UI3Rmwbdl/w0XZKTX17Z5X16E\ndnivmFmHHzzs2OXwh18RQkajscpZNXrn6Ed6PHJ/j/sv6BYEbI8NndgVybBn40TDsd9ow7H0\n4vTVq1fTphTbB23P3Jp5ge7G/0Eliy3Qmb7hnqSOOqrqThZ2bZVtrWSnNkL+51/bJKzS7Ts+\nZFyf2sqasoo9UkGly0pDnJsKO0EQaO5Fgc7k8BxrsK5rat9hdexhgAMAQoQ6y68/lSoBgEES\nlTwp8pfrw9RDVZ70ylstdCseG8KmrEzpKFPX3Pzggw/SrXiBgYFE59VoNHQLoEQiOdR4MDIo\nSi3XMgzj8rgxwS6f08N6PeEucEM7tGvj5Q63vbL5KMfR1YkgCBe9uVNERORCEYWdiMhl4tZb\nb129erXnmId4SM/Pehby+t493r5sq3uxlUGK5tZW7izC7oxg7LmgVcqq36y1/DIsfQvLKPhM\nHgjoTDqM8ciRI3v37j1z5sw7/rpjv33/jkE72LPoyLOxqWxo96BbMcYXNOrSydeVruczC3Sm\njO0Z5myzzqT7/vvvqbhc1m/ZvxYu/lf8ybCne+wCo7XaKHVUT615XZ3b064L79dc3uQRIDIi\nUtKskQZjQji/sKOTVL9eHflkdM+wyT3DJp++loCdG8yDHK6qirp5FXXvaRSp8HHHKWe54+Bq\nAMyyRJ445I4VK5YDIJ/Pd+uttwbLNH53HcdxHMvJ93WL6Bn8t83UzabDwa1CoKPV2QwA3jYk\n0RCXt4lpQ5yC8+//EwRBJpN9uuqTh0f+51KelYiIyPkgCjsRkcvB2LFjExISEEIVYyp0Jl1F\n3TwETLjmwjbgXwo+XxvLKKxWKxcmEbD7X69HCAmCsLH8AhI7CvlMAFKgMxFCeD0vjZEm/5y8\naNGiJUuWfP/991qt9l8bhZ3LfmxL7fYCjYRexPCLBgEanLqO1vBLXJJI6/xNnTqVartHYh+5\nRG3n99Wd4rE7xB/rE9rXl9QKAL1v7u5pwxV/Ho5FSTXtTe2kZvCNWTJGYRfa/MKODrcYLZbV\nljMsw4A2T6serB6auUMSLgEAc9VrddY19KSu+xuRuhvbnfsbrOvrzX/u3/rZfvgMAKTRsslT\npWtKwqmwk0gkKrnaSzw2lWXLkTJ1ArN264rEzB5aLvDInqZuvRRer4z1SeUowGJzStWcnFN6\nBTcChm4BLDm0/WEQhZ2ISJcjCjsRkS6nsbHR7Xa///77vJ6PfjUaAI41f3/ZgrAUD7ZKWLXF\nYtFGsAK2n/EalTz1eNumkDtTGhY03H777YsXL47qd77zF/J6AFSgM9n/sh+ZfCRpRZIsVuav\naQIA+iK9klVuztl8EcbvOjqFZZT0+Gx7BLsOGRcyIGER1XaRz0byej7LlJWdnU213e/Hf78U\nbefXc34QQnUmC1cfyI1yAun4FW1pa1PFC/KYdsfW1qGGnKIlO4N7KFMGJFGXmF8a6kp1py5A\nwF3nrptRZy20WgutJ50YFwnjAMDjsxz21ey/6VnvXRujg0bk5v9IT7caW2ueqPnqpi9kcYI/\naVer1VpsrfIYZ9Bxub3F1f/afjv/2paszozNCiKEuL2YSDyeVhyVGvh3CR8dF83IQC6TYSII\ngtAVdQdFRERORxR2IiJdzqRJk4xG4/EFxwFB8MjgQl6fk3S+RW47C6/PKmNDrVZLCCvxCfbg\n4ODTr8lO/G69eWDe41sPP3Jg3Mdjv/zqvcHJm3xeNwCCf2qWIX//dgKAEHh8LeW1M9Ojp0do\nrzs2rVKw+tK2pxLAU195OTs764UXnj9orfij8Y/vdN8mqhJ9Pi8C2lOAQSdKqxCCThyfnItA\nCAHaL9XlaRiatmncuHGd0hn2ItAo0uLC7ink9QUTTPYSO6/nXzG98vDDD1NtN6h40EVrO/YE\nNJZKMLhasd3hlYdI7W1Ol92jDdFIlWzlnjoXtqXrU/JGDwSAoXdkNRZKJRLXyR47lmWpkqZI\npVK9Xn/NNddkZWXFfRx3xtWd5c724vb2oijnhgzfH+Ms7spiWAYAHBMQII8FAEekXSPV+NM7\nbDa71KUgrOS49Rj2SQ5X7eyZGiMLdhIX2b2xUh3GxCdnaCPB6XUm9030ubGj3SVRIYlEQqXh\nRTwfERGRC0UUdiIiXYvBYLjvvvsA4Pjnx3Um3Z/7bkCIU8p6XGYzvD6rUhbf2npEKg30YVtw\ncLDD4aBlxvwQQhAgQIQgRAhWq9WIsJgQQJghCAMiAB0tTDEBBghBlY2LPL6WXt3eAoC696vZ\nQBT9UjeXy/n1N18XDC8YNGjQ/KPzlZzyvphJCCGMCQBmaF8BJAAAYARACCIYnyG/lAAAQi22\nYoWkB8ZYKpF069btcjysM5EY8Vid9fdCXl8w12TOMfN6/lPTpyNHjjQYDFuNWzOLMrO2Zu0Y\ndAFJvgBAnW1+fxuDmPbDLAlql7jVYf05l88rEeSMFFYv3BASGOJV4KN/VyXp4xsbWkPCtFE3\nYEI6KtfQSRiGWb16NZV6tbW18+fPLy0tLS4uPls73fHjx0+YMCE0JTT8/vAT7w2g/1pvzmkj\nXqa8u8QS7e+KIZFI0J6wKl9FWlp8XFS3A+X1+owsRsPuO2pWOKJ6hMZKk9sljFfBBR3fIgTm\nCogBtUxOVbwgCKKwExG5PIjCTkSkC1mxYgUAjBkzhtfzSUuTCAgeX9NlDsJSBOyUsOqWlpYg\nRTr12NXU1CQlJZ18Da04SwggKTrc8FlIcCIhmHrRBMAA/pZQCCEADLUtazgmsFvYRCwI1t+t\niiyVWh+wh+cbGurumzSJ4yTzj36iYAPujL6dYMAEI0QAiI8gpqNVKANEIIAQIZgAAPjbE/hT\nJAgCq3Nfr5jZU6e+8tLLL9HmU1eqSejg5NWbyoatN2fnb9tuzjKbc82rilbRhmOlP5Tqi/T3\n7L7nm77fnP+EGOOoIUOce/ZQZSaTydpbGHelNukGotQoa6vqozNC9u3eH6gIDo2MktdbPEfk\nkhyJq80liQ6lagkACCG0rPE+1fG3ioZkhmQOCR6SF5bnr1R3CocPH969e/f27duXLl26dOkZ\nSpBoNJrevUdlZmYOGpm75ofn/DFibxtRXWNN8XV3s46dayt0feJUSok7zBncHlBZvzcnf8ih\nbd7owfKyzfWM2tXz6DV7j+5OGxZt8bX4Z7i4xy4iInJBiD9pIiJdyFdffWU0GivGViAJksXL\nCnl9fkbJFbEEE7eE01gsFpXiGre3ISQk5DRhRxt2IoSAkTAMkqtVagELtLkAIQQhDAQw0O7s\n2Grbq5D01CpT3E0uX6NXmReAWHTgwAGphBs2dBgA/NpgTAxIyg8ZhjHBWGCAAYQxbRXKIOzD\nLMsQIAhA6FCP4PO3ET2hMpstdQquB8aCWq1OS0v3n7qMT+5/GJq+cb15wIay3LwdRXwmX3FL\nBS1u9/LLL5tmmPRF+ncPv/t0/NPnORvG2CuTdfS0ZxiWZZ1Oa8z1QSVrdmEJsdvtcQ/06D2g\nV3nRbwNuTgYAwYcbDlqSe8fTqr80zcLn89EyxaFJ1+gChF3WXVtatrx58M3Tl0OAHuzx4LiY\ncSPiRpyxEDEA8Dz/zTff7Ny5s6ioaN68eRm3pdAYMcdx8jDu4L4DzkZX/4w+miCp3e5IiEtb\nv26tL9QT0623bTcXnx5fXXw8Ji686lDd36QkRKfgFBLWwfq9khf92EVERM4f8SdNRKSrMBgM\n7733HgB4Kj06k26DOUcp7Unr9V9+MHZxjNpisWgD0uzug9Rj97+XIADQBGS02P5ydDsai8aj\n8HqlUmu3WwGjV16Z+uabbzww+cGVK1cfP17p9bVuKKy4feKktqrmwJiQ+fM/hh3E5XJNmDBO\nrdKER0QVH/7z2uBr5ayCEEIIViq1o0aNXPz9IgCkUmttNotaE2SzWQAIARSg1Njt1t27/96z\nZy8A0Bjs3XfdFaDS7Nm7oXevm39f92tBQQHBmCD2ind+z88oKeT1psOT9aWf83q+ekY11Xar\nV682jTDpi/TDQob1055X1gkhxO1209/CNJbarmg9vLvNx7lxm4RhZRzHmTbtCVRpOI6jcduY\njDBCyMnuOn82STgT/m76uwqF4vSFDtgP7Lbu/rXx1wXHFiw4doZ9iiGSkF7qXkNDht6su/nt\nt/+pwvPSD89RWQYEcRzXXZlUV9O4/9ih4Ghtc5VNeY2szemLs+hihgbUbbM01TWq4oLMjTvD\ng6M1EWHaHlIntnEcR8vsXf6sFxGR/5uIwk5EpEt4+umnOY5LTEzk9Xz6tnSb6wAm3pzkZVfK\nHoG4OFaNMdYo0pqbNwQHJ+zZs+f0y/r0mLvryGOyG6PsG7O7j+n++7pf77vvwS8XLgBEcyaQ\nw+HAWJBKIm6fOAkAGCUDAHfdebvP56PSZOacOVtKNiUEJALQlqGECrW1a9cB0AbxBAjBGD/5\nxNPz3psLBP+5eSMQAoTcfdcdfksIwe1tLQAOAJDLFf369gYEVzYU64cWLq5sWqwz3c7r+aBR\nQVTbZWZm0oZjG7M3qjn1v85DfXXr6utvVavpt47jzoyxqZlhvbYV7szOu4bj2IHX6T8r/V4i\nkQB9doQAgCAI/rQJOtW25uaMhISzLZSkTEpSJo2LHnfGs9tbtn9e9fnu9t2bWjZNOzDt5FM3\nssOps02ukHMcS9zYhRy6HkmWVktiRlDDEWtGRoa7WlJf7LM7XTKVMq5XRLhdvXfLEUm9NjRR\nQs3DGHu9XtFjJyJyebgyzgMRkf/nqaio+OWXX8wDzVw4x0iY7QcnXpGtdX4E7OIYNQAEyKMd\nnmMhISFNTU2nX8axylbbzuT4pwkCQMTj9S5ZsuQkFUWqqw8zSAaEDC8oAAAkRQDA8+b9+yvK\nysoxkOeff1aBFAQwASCAgcZeAVpbGoZfdyOcJMg++/wLBHDbxDvi43sCAAHC82b6am9vRwgh\nhjArx7qGAAAgAElEQVSMGgCCQ4IwJv447ZVVdZQCnelA/bsW+986k+7IvUd8LT6j0fjAAw8A\ngCnXNGz7eVUoRAgplUrEsh6Px+v1CoKQ2K9HubGeEDJwuJ6TsAzDAMCDL9/hvx4AMMY0FCsI\ngiAIXq/X6/U2OZ1KpfLivGLZwdkL+ywszCo05ZpOfpUOKpVyUirsaivrLMfbXTZh0K19g5K0\n4d3CYsJifKxP0RxR1V4RnC0Q5PY0o6balrZ6+zV56QnDtKcUXmZZlpwUahcREekiRGEnItL5\nGAyGZcuWuSvdxENSf00t5PXx4Y9cWZME7JJyGgBACNndlUFBQU6n82wXSxgNAAAgIMRuswy5\nNg8AaIGT4KCQkNBIp935y8oVQEuSAPTu3atXL12GLp0BxALDMAgIAJAp/3l84u130G8A0N69\nPFVkVKA8+eTjBMjq1WsQ6ninVy8dfWk0GrrHTqnSHqs8HB+fgBAtj3LlJZ2fAp3JdOR+ATt0\nJt2+6/YRL/nll18MBgMhZFP2JlqN+dywLBsYGKjRaL7++2+32+12u8PS1P0mxPp8Pira6AHG\nmMo4//t+PUdHffnXXyqVKjg4uNPDnbf2nUBlWc/k2KjY8OTh4VKp1N5kqzpS72jxHdhdXWOv\n7Dc81W1zZ92R0WCr3VG41+uEvVvLEWZOVnV0E6HYWExE5DIgCjsRkU5mzJgxWq1WoVAcGHtA\nZ9IdavgUAOLDL6wvaqeDiYuqIoQQIe6QkBCHw3H6ZRvLrg2QdgNEiIABQMACIGQy7QxQyBAg\nAkRwC263OzomFk7EBAHAK3jdghudUF0YdzhmPv74gx8Wf0e/IUAa6qp797kGTsjBGW9O37Kl\n6MuFC2iEEZ0INZ7YQ+YODIqwWBpZlqWl704MvIq8PnkZxRvLhgBA2sY0c46Z47iFCxeOGDFC\nxak+1n38r9oOIRQUFNStWzeJRLK/udnlcrlcLqrY/JJOOAm/vDtZ1TXaLBzHRUVFhYaGUg9f\nJ8IJEhov9nvdtm0wtdnbGRk+1MJn3tEzfViEvdktMD6pVJoxqKcMZMfKGwIc4R6Xr73a01HG\nhWEYhpESmSjsREQuA6KwExHpTBoaGjwez/fff8/r+ZC7QgDgSOMXVzYISxGw6+N3n++bSKY9\nM2rrN93fn3Fv98DGV58e8dLjN1ZVHvjnOoLlsmhM3AgjYseCQFzuZmtb5dvvvEcAEQ8gN/p7\n906GYdrb2wGA4yQAUHHswPGaxuqqGgDU2NjU0tLS2NjU2NhMpzwROUUEQXNzM0LohOMN3XCD\nYcKE2xjEACAAprqqxv/y+mx/bt549Eil1+ej/RUA4CqIwf4PDJIOSV1XyOtZNdvzs568no+I\niKCFi7MCs8ZGjv1XbadWqxMSEkJDQ/88cqTN4aDaznMSvpOg71BJR690OJ2TN71fhssSExO1\nWm3nBqkJIQ6Hg+be+qsoD7spN7VPapOl4Zq8TI5j61vqw5PUe/7iOY7rFhsl0XJu0h6Wxa3/\nZYsmWk6FHdV2Ue3dvV5vJ5onIiJyRsTdrCIincn9999vNBobv20EgKgnogp5fW6K8UobBe/O\nfKStJUgiOaRSqbIHj9T1G8KynNNhW7fy8/q6o19/8rzH43l97soNZYOuifuEZZX7a99Kvf2V\nlnUt/TKDamuPJ8Sn79pR6j7knjNzJqNhZRaZqWSbRqMtM+855Dj0m2m1EikFLADd/u9waLRa\nh9MJAP4U4LKyvQxiCJCamsqjR44ihMrMe/xfNVotQigjI722tpZeb3cfjeZyEVNX39AglclO\naEFEyFWn7aRcSP+4Twt5fUF/U8SjEbyeN5gMe/bsoU0pii3F525KIZFIevbsmZKS0t7e/v2e\nPXf27q0mBGNMywJTXxeVa/5kWOqx83g8Dofjtjlzxo4d+7P858TERJlM1rm3Rpez7rSrh6pP\nlnd1NXU9dYl7t+3xuXDOTdkl27fnFQxxO327N5cZbs9TKOWAICk1gcaL/cb7fD5xj52IyGVA\nFHYiIp2GwWC4/vrrAaDhgwadSWc6PJlBMrkk8spaNfUpg0KhKLjpzpxrbzn5fU1g6N2PzKDH\n7824f8aL49xEXfBWf0Kw01stYKejqiFgoKKirDWqwRHmCA3IVwYwAcVbiwGhgQNz2rztR7RH\nk7nkYbr/SRSIT4inFfFo6ipCgDH07BmPEEKAASA+IREIjk+I77gYgGEZAJAr5PRbAGiwHpVI\npXZb+7BhwwgBQMAyDEKIYdBVtc2OEqzSR2pvKuT1Bfea2ja08Xr+JdNL9913H9V2Q7cPzSzK\nLM0tPeNYGo3t27dvW1tbeXn593v3pkZE5Hbv7vP5/O4uvzbCGFPXndfr5ffUFrtrGIaJj49X\nKBWcluv0OCxCSCKR+Np9dJMfNYNhmB5xPRiG2c/vRxbEsmzOoEG7S/4+dvRYcq9EbbCGXgwn\nAu4AgDGu3lLXq2dYp1soIiJyOuKPmYhI5/Dbb78BwGOPPcbr+aTlSQBgcfyVl7H1ylo17ZlR\nSqXyP8981Kvftba2Vlt7q73dQl9eq9vebrG1t9raWu9/7O1bJjwWIAl644XxAMjmPmyufpmp\nVwep+h3eddi11x18fTBBsHjxjwBM7qDBy+pXLKlfkh9WEKuMYxB3yotlOYZhOYZhEAvAsgzd\nZoUYhmUZlmEYlj11yMmvI01fapUZDoer8lg1QohlEMNwBBAtlHxln+fZ0MVMV0i7F/KZCd8m\nMHKGH8B/+eWXADBq1KhN2ZsIkPzt+Wcby3FcTEzMgAEDUlNTNRrN/uPHPzeZGtva7Ha7w+Gg\nX/3Y7fZ2u31BScmaH/gAaUC/fv2Kioq237r95r9u7vSbokm7SqXy2Obqk+PCdLdfii4lMCaQ\nqre+A/oMyh5cs8158l5AulOQbgR0HHdqNBqx4omIyGVA/DETEekcPv74Y6PRePTxo8CBLE5W\nyOvz0ouvrEmvP3uLUqmceN9Uh91CQ2kAAIAUEoXL58QewSt3CoIPARIwDg6N0mqD7Lb2ubNG\np91Yd23q+qP1R2ueranFdRHzogoLC3fuND355FMymezF8ucBYFbanLOtS2veIQahfxIdEALA\nhAAAQ604u0Jzuo8oZTGz581+8cUXaMk6BAghhgBB6Ootcjso+ZcNZbnrzVn5RTvM2ebyvHLj\nBqPBYHjggQdMX5j0RfoH9z74Wa/PTh+IEJLL5UlJSRKJRK1WHzx4sLm5eXlZGS1roo+JiVap\nPIKl1cn89PdH0cGjdjS5CMuNeSRNukh67y/3Pvfccyqlqiv8mAghjUYTFhZ2bOexbk6n33dI\nIYSExoTSinpet/fA740598f7c3hPTu8oWbgrOjo6PDycVuMTERHpUkRhJyLSCRgMhrlz5wKA\nrdimM+k2lA2SSSIZ5kp2PX/92dFKpVKhUDjtVuouo83BEIAL2jiQMALn8FmID2HGRwghmAw3\nTFr7ywKHQ5CygdY/LK1LLCm/plQuOHbLLaMBwGg0AoC+SK/ltOuz11+ESecTINhUnhcfep/V\n2rZ9+w6W/R8dcNWFYE8jL72okNdvKh86dPsmXs8fGHeAFi5+++23Tc+a9EX6JbVLJkRPOH0g\n1Xbx8fFqtToqKurQoUP19fVtbW1ut3vv8eN/19dXNi6NC5+QED2xvn3puH5Tvqj3Dh4y2Pez\nLykpSSaTFRYWrr92/TkCvheNSqWKjY2tqKgwfbU764Fr6P8e0KAw3QJI32E4JtkQLmDBvwuQ\n+upcLlfLQYtUKo2Ojo6IiBCbT4iIXAZEYScicqnMnDkTIZSSksLr+bQ/01zeBozdg9OvZM5E\nW5slIEChUCjkcrnL2e7/A4wQ4lipT/ACgA1awEOImyVSH20RgQVBoVAQQkp/jPUmjM4z/VEz\nvaauvq6mpsZsNq9rXPfy/pcX9FpwjfaarrPcJ7T1CLuT7k7rulW6DtqUYs+xF3qbZvN6/vjn\nx6m2GzBggOlak75In6HO0Kl1pw9ECMlksqioqMDAwNjY2IaGhoaGhtbWVofDsa/6494Rud1C\n0gICAo5a1uQNyFtWZg1Mzkj8VHFo2KGV21caDAbjcCPpgkIwUqm0Z8+ecXFxNpttxxc7syfr\nqaqjwVaa7godNXSIv2yyPwJrqbdWbDwYHh6ekpISFBR0NVSWFhH5fx5R2ImIXCrFxcVGo7Fs\nSBkbzLIB7Eb+5ite3+TjOQ+qVCq5XC6VSt2udoSotGMAgPFIiPSfqhOEAHF2/En2uB1SqZQe\n765T5IZ79q7c+9h3jy1YsODabdfaBfs5sjs7hY3mweHqs+5F+/8LVNtVt6zQmcbyel41REW1\n3eDBg2nDsXM8RpZllUplQEBARESE0+l0Op0ul0ta9vGgpJkSiUQmkzU5nPW253feuzH7t3LT\niF5Vvio60O12Dw8dfu/ue7/u+3Un3gvDMOHh4b169Wpubq6url4268Wxz88QBEEqldLiw/6k\nXQA4OQjr8XhaD1r2bTigVqvT0tKSkpLkcnknGiYiInI2xOQJEZFLwmAw/Pjjj0KbgB047fe0\nQl7fLWjslTWppbmB+uqkUqlMJjt2aLfHZfO47W5Xu73d6sKtttZ2t8vW8XLbPG6bx2XzuG21\nx8roELlcLvGG3n777fGJ8SNGjChvL78Mqg4ABOLsHTvHYDCsWLGiq9fqUgp0pn21s+yuIzqT\n7vAdh32tvtWrV48cOdLj8WwftP3cxe1oQWCFQhEUFBQdHd2I38xIyUpMTIyLi4uOju6T9DAr\ncXIcBwh5MFFlqyqfqvzpp5/Gjh07K3UWb+M7/V7kcnlycnL//v1Dw9SchClZuKuprtafzOH8\nX/wJH8ULSvZvPEhVXb9+/UJCQkR3nYjI5UEUdiIiF89tt92mUChUKlV5XrnOpKtqXgYAad1e\nvLJWff7eEzKZTCqV0lpoLMs0Hz/idrZ7XDYsOMDhI4yd8flaa+oVNinZp5EC43bZmhuOcBxH\nPTEymUwmky369isGMfoivYJVXAZVZ66ehpiOTXWdXpLt8lOgM207OA6A6Ey6fcP3IYSMRuOY\nMWM4xP0x4I/zaThGQ+c2997s5IX+Fg4IIaWsJ1/96rab0gf+ao77KK59S7tU2rGbk0PcmuNr\nOvdGEEKBgYF9+/ZVRP00qN9/N7dtXvHptOIFJZZqq/0EVMzZbDa73V40f3vpl39xHBccHNyr\nV6/s7OwePXqI+bAiIpcNUdiJiFwkbrfbZrMtW7aM1/PaG7UAsL9uzhUPwgKAXC6nwu7kLuwO\nW4vT3ip4XA7BEhYQqPAw3Z3pNRX1ldV7KzYecdpbuBNQRSiTyb54/wnexa+8ZmVcQFxLS0tX\nm11nMeanbxsxYsRHH33U1WtdHvIyigv5TABIWZPC63kAmDt3rsFgCJIGzU6dfT7a7ljTj+i0\nDTMDk5fVW36V+GvCMeAod7zxxhujRo3aPmj7axWvdfJtADAMI1NaE9MDhgwZ4urhio0MVSgU\nf07aWvrlX6+NeaN4Qcl/X3u+eEHJji927vpmj1QqDQwMjI+Pz87Ozs3N7dmzp6yjxLSIiMjl\nQBR2IiIXydixY41Go2WdBRDEvBFTyOuvifv0ShsFhBC/sKPajtK63yPhpOGy7iGK4Ob2xkah\nsSl4n8Nlsfsag/twVP/R6+lAuVwul8tveOcGz+OexYsX//e//+1Ss6uaf2QZJbU/Li6uS9e6\nbDBIOiyjqJDXSyIkPRf25PV8SkrKPffcYzAYCkILBgYO/FdtV1H/Tr5u+5nOIIy9j6aED/mt\nTFeiO3zX4X79+tG+vQCACe7sW4HSIxPHDNo11TX1tgFtY29+IeZYTEp+SlVVVa9evRqYhkht\npEajCQkJiY6OTk1Nzc7OzsvLy87OjomJkcvloqoTEbmciMJORORiMBgM2dnZAFD9crWuVLfz\nyCMAEKT6dx9MV/PLkg+kJ/C761iWjWUyKjbVVm23umuxVqFhGOQ47grPCErtlSKVSmikj3rs\n/NpOJpMF3hBo/8uu0WgaGxu71Oz9de8MS99sMBhee63zHU5XEBbJ06JfKeT1yj7KkDtCeD0/\nbtw4vV5vMBg+0H0Qp4g7h7azOP5GcOb6IPkZOzaU5dybFO4QOjQc8ZGMjIxZs2ZtydkyYOuA\nzr0Li2MvACCEWtnWoT175g25p9fBXqOfHd3U1DR58uS9UXunjpiak5MzZMiQgoKC4cOH5+bm\npqWlhYSEiBFYEZHLjyjsREQumJKSEgB45ZVXeD0f81YMIbjVXno1BGEBoO4Yf7Kjzk+9vUZ3\nfaxKElh9wNq4lW056gjtEbRnHR/gDA+SB9GgLVV1FDrJ5bG51b7H/7soMzPz8ix62egWfEuY\nZkghr496KkoaI+X1/LRp0+RyucFgWH7NcikjHVB0Zh1mOnx/vm7HGU/RBGdCSJxSOmtPddqm\nNHO2ec6cOVu3blWwik6/BdPhSQU6040lN6ap01gJaDSaSGlkenp6YGDg4MGD1f3VQ4cOHTJk\nSE5OTp8+feLj40NCQsTwq4jIlUIUdiIiF8z06dONRmPlk5UAoM3TrjcPuOKtw/ycrOqoVqOu\nOCGqece6PQea/zpmKfdhITEuFkvxHXdP6B4c7mx0nuyu88s7qVTa3NRwGWzeeeS+Al3JxIkT\nR40adRmWu/z06fGuVBJayGcm/5yMFMicY16+fDnDMOPHjy8eWIwBX7/j+lOGeIW2c885JPWP\n9ebM5cOSVxyzsKp/HHsVFRWf6T7L3prdWca32EroQaOncVHfRfSYAYa6hAMDA1kNGxoaGhwc\nrNFoFAoFx3GipBMRuYKIwk5E5MIwGAxPPvkkEGgvateZdJvK8qRcKIOulizOU/SZ/2u8rodu\nUEL6DTFhSZp9LSW11cdV3iCP29Ha6MY+cvKVfiQSSWtLPZ1WLpe7XK6uMBgTDz1ob2+fPHly\nVyxxNTAkZS0AKuT1GVsyiI+U5ZatWrXK6XROmTLFlGtq8ba8su+Vk6/fXJ53bh+wlAuiBwjA\n7hPCp4Sbh5iNRuPTTz/dP7C/j/g6y/JdR/9ToDNdt+M6Q7jBK1gRkghOgdWwTqcTABBCgOCk\nhnUiIiJXGFHYiYhcALNmzQKAgoICPpNP25zm9bX7cNuQ1LVX2q5/oL43+pVhGHpMCY8Ilykk\nSq0yMTU6JFHddKypDTssIdU+glivhD0TDk9Ft9e6VT5fOWXKlA8//LArDN5gHpifsePFF19M\nTU3tivmvHgp0JQBQfGCsrlSHXfjIQ0dWr15dWVn50UcfleaWrm1a+3P9zxc0YVTgTcUHxu+4\nOePateXhk8KJo6PzBCEkVZk6df/US7e5puUX2sutxdsyLXna5vKC3JQ1RyYf6TG3x2uvvfbW\nW2+9vP/lR2IfufSFREREOgtR2ImInC+EkK1btxqNxn037GO1LKtkN+8bdpVsrfNzsizjTuN4\nQ6NcoYgIjty3rZKEelwKp1KNMePkVMzJ+RP+GG6dd27QiKD2De3Dhg3bvHlzp1uLsQcAEGL3\n7t37zjvvdPr8VxsFOpPDXclXvaoz6ew77S1LW4xG49q1a/ft22fKNc04OKPOVQcAhbw+N/nX\nf50to/t0h/swgxAAEEKkPaT1H9QvWrRoxIgR3/X77rfG3y7d4PLaNwt0pUOKh0yJnQIAAETG\nBbv2uZT9lGVlZenp6esa190fc/+lLyQiItJZiMJOROR8GTFixKJFiwSn4Gvypa1PK+Qzo7Q3\nX2mjTkUilZ6SBuGnrrYxLDgiLqH7Xzsqe8RERcdFSyQSS5OtW1r3U670azuG8wFAF/Qg7WBD\n2cC8jG3vv/9+ZGRkV61xlVGgM9Vbf623/KYz6WrfqnWWO41G4zPPPGOxWEoHlY4wjaCXyaXh\n5zOblAs61vSDMT85c405+afkpm+bgoL8IVpUZiu7FFMPNXzCsRoAcGDHpJhJlzKViIjIZUMU\ndiIi58WkSZPkcnlQUFD54HKdSdfUXgxAMmJev9J2nUpq7zx/NPbkTAhWkHD1KpVS2VqoHDw+\nI6Z/5LG99RKJRKJQuC2Cv8TJye46hmG6oCDaPxBCAIBBkj/++OOLL77owpWuMgp0Jr56qst7\nXGfSHbrrEHZho9F45513CoKwdeDWD7cr9fFfn+dUQ1L/qKifG6mQ+t8RrMJdd901bty40tzS\nu3fffSl2Hmn8cmjaBn2Rfk7KnEuZR0RE5HIiCjsRkX/H6/U2NjYuX77cnGVWD1UDwO7Kx6+2\nICwAPP/8808/P/uUUKxEIln59e/HN0gCerA7lh+I7Ka1NjoqfmpLzYrf8u1f4QkhVdusp2RO\nUFXHsqzX22XOOoD15swhqYV//vln1y1x1ZKvKy3afxMhOKM4oyy3DAB+/PHHW265RcbIEpVJ\nBbvuveAJIzW3bqzQlerK88snTJhAMxsuhb8rn5NxER2Th+UDQGPb5gBpvPuoW54sP3bsWGBg\n4CUuISIi0hWIwk5E5N8ZPXq00Wi077YTgcT+f+ydeUBUVfvHn3Pv7AsMqyAioGzK4DogKqUo\n6luNa5pvmWVZ2mJZb/qmlmWWP9fKt6zM1LRFSyUXxsrCNdwnzRwERFE2FWWffebec35/nGEk\nE9xw7X7eifdu59xz7gzOl+c5z/MsiMgy6dqH3UG2OkKIXq/X6/V5eXmLFy+mIYoNtV2YT6Q8\n3HHsUL7ZUWU6acrdURwR0FYikcjFvkd2HS+tOd3QA0slHcMwBIn95b3Lqtb7DfGr3lA9YsSI\nZo+fkIg08+bNMxgMzdvtnQ8C1Fd7YGtOMpKg2B9jTTqTSqWaOXPmorV+McFjJ0ZOvJqCY5S0\n9ruzTLq5utanrS6oj0wNCgr65ptvNidtTsq+zryAF8zb7ovfrMvWfd3Rk+LkSPFrPWLXnBxz\nMvJ/kdOnT//000/77++/tMM/yNQqIHBXIKQFFxC4AoMHD+7UqRMAnHrmlNaoPVr6BgC09Lsj\nVtfV1taOGjUKAEJCQpYuXYox3n9oIyGEqYfKuz5jdJs/3TtoQn8AIIScPa0p31O2d+XR/o/f\nJ1WyRcdLxGIxxpiepZXmEUJna/2TQp7489zQ3lN/y+mW86TxSb1e/9JLLzXLyLfldE8Mn1Ne\nfivy5N2ZIGC6R6/NMunStcaoT6NMOlMXY5cTVr9Xxm4xGAyH6w7rsnXG1CtbhVnGk2rHV8yu\nPV05aF2MSWf60vilXq9//PHHyXUtkNxbMEIhaU2326nbNTyFLVgUJKqsrPTx8alyV3Xy6XQd\n/QsICNw8BIudgEBTFBYW8jz/3nvvmXSm0CmhAFBes+VOcMIuW7ZMr9ePGjVq4sSJBoNh6dKl\nfxb/N8uUnFM6/ed9eQCAEKLCjtrhhr7Siy6k+35pZkm2tch9LLGtruDP02KxODqhTcMMKSzL\nQv0COIRYHjsQ2/wpyjBxt/BNHzt27D/QXOdFKYuKDnk5y6RTJis1D2iy5j/aJqxPdHS0Xq//\noP0HIdKQq7S3JbX5Msuk2zqg3VzTWWnkxZSKNTU1L0a82Gtvr2sdmNV5qkfsD7ps3fddvr/W\ntgICArcXwWInINAUL7/8ssFgKJtdBgABwwOyTLr743+5vUN6+OGHnU4nAGRkZEilUgDYltOD\npvntm7C3UH66Ii/D7XZzHEcIwRiXny0PDgmWSqW/LN/X/V+d/d3B1VxV+1BdgEYelxxAMKH+\nO4QQIYQQwvM8z/NjJiz08fEdNmzYzZjCzty+bYJfsFgsN6Pzu4vIwCfO12ZlmXTp7xr/2PCn\nbOT3Cw9qhw0bNnDgQEOmQZetS9mdsq/nvqY78VUkNtxVp6oLhhVkZmYOHDjQYDB8UvTJNQ1p\nV+4AhSSSbrdVtL2mtgICArcdwWInINAoer3+qaeeAoDqjGqtUbsrtz+DZBKR/20ZTFlZGV1I\nFxYWZjAYDAaDnc/LMumyTDo/lS5da0zXGllWrFQqfXx8vvrhqMvlcjqdbrfbP9C/+GSpy+lO\nHtBJfc6npSZy8CvdC+r+DEiSEEIIEJ7nMcYcx7ndbrfb7XQ6HQ6HXj+QYZiRI0fejLm4+do2\nwU//+9///ieb67wkt/1KxKgMh1v7xIUjFpmSTT/88AMAPPbYY8ZUI0/4fx/69xU7UcvjjhT9\nd/cD7XUGU8TCCGex01sKIkAcsKJkxdWPx8VX9ohdp8vWbdRt9B7MP7ugdcCo6p+qfR7wyc7O\n7tChwxnHGRESTAMCAnccgrATELg8K1asAICHH37YpDPFbY7jsdPFV/VJyL71I/niiy/0ev34\n8eNfffVVg8Hw0Ucf/V74QpZJZywcmxK9Jl1r7BzxkfditVrdsmVLqVR6urTG6XS6XC6O41pG\nhBDAqhai3UeOHrce4Hn+gad78g1w1+NwOJxO54p1R3x9fRcvXjxmzJj3JtpOnjwsjZXWbq3V\n6/UbNmy4wen8lvfAJRYmgd7td7i4Sjdfk7AvATDkpOZkZmbW1dU988wzB1MPnrCdmJE/o+ke\nurX99oJ5m5T1/JPOqtjqzOr//e9/AwcO3NJty6KiRVc5kp25ffyUnriNMFmY93hJ5Xexoa+W\nTS8Lfzt8wYIFs2bNGmwcvKP7jmudqYCAwM1G+HtLQODyrFu3zmAw5D2YhyRI3EJMF7nf4jGM\nGTOmoqICAFavXq1Wq+EvXtf9CLF/byKXyyMjI48dO/brbydCg5XUbCORSDDGLMvqHotIZqI4\nzlNIlPpqvdqO2urWbs6RSCStW7cOCQnp2LHj4KG9BjxwX7B/pxlTZ4zdPXbEiBFDhgy5kUk5\nuQv3xf+k1+tXrVp1I/3cS5gdeT7ydgS4AycfTzZ+Y9KZSt4oMRgMer1+9erVxkeNumxdqn9q\nelB6E50wjLTSvP/Tbgk6g8m4Q2vSmbRGLV0rCQCV7soAccAVR+Lm67pGLdZl67JSsi57ARIh\njuMQQgSIjJFdx2QFBARuKoKwExC4DHq9/vPPP8duzJ3ntEZtlkmnUXS+ZXfneX7w4MEAIHeI\napIAACAASURBVBaLqbOS5x1ZJmpHkTatL1mWbdWqVWxsbE1Nzcp1fzw1ohNVbxKJhEbIonro\ncYrb7aau242/5tWaHWFhYfHx8X5+fgghuTT0rY80/5vqfLny5W3ibV5ReH0cP/uBiFHRbR8f\nnxvp6l5i/4nH6duaZdIdK31Pa3zTpDMpk5VU26WkpBhTjbps3d7AvWIkbqyTPu13//3Pjy5d\nuowZM8a4wng1MbY7jvUK9x/pJm4A0IiENHUCAnclgrATELiUcePGsSwbFhZGbR5V1kMAoGvz\nxS249Zo1a7766isAGD16NF3fln9mfknV9wDQruX0MP/BV+wBIaTRaDp06FBZWZmXl7d8zeGH\nH9QG+vEcx4nFYq+2oxdTcx1dXed0Op9++X+pqff7+/snJiZGR0dLJBfrGWRmZi7RLtHr9bW1\ntTcyweLKVela46BBgz744IMb6edews3XeLfTtcYsky7Er7/WmGzSmZQ6pddud6DngeTdyXt7\n7BUzjWo7SqRK+vrvxbOz25t0ppnGmXq9/ipHwmFrXMvJumzd5cI1GMKTmxEfLSAg0LwIwk5A\noCGE53F5efnGjRtzUnJkcTIAOHzqBa8VxOvYohYv+tPbuP6gZ++abuz99s3MzKTCa6spmQAG\nQNfqAmZZNjw8PDk5meO4wsLCH37KwRiPHdmFpiCm+e2g3g9LzXUWm3X1xlyz2RoQEJCYmNip\nUyeNRuPVf5Qesh7jDOPi4uL0ev31BT2UVmWwjAwAMMaxsbHX0cM9yc7c9L4JB727VNv1ardd\na9SadKaE/QlU2xkMBmq3a8Lwdn/8r1km3breRp3BxHT1rLeTyWS7du36stOX3XZ3299zf2Nt\nt+X0iAudauEsCNAlURH7TzzWsfX8M3POhEwK+eKLLx555JGfz//cTtWusa4EBARuI4KwE/jH\nQwiPMQCmCm3hhx+uXfu9o8iq7C0Pe7fVn0VvJrb6gHO7AIAAIK9cQ4RKOow9Sg4hhmEQIQgh\nDIAQMIAAIeYSeXQJbrd76NChACCVSjMyMgDA6a78LX8AAMjFYT3jNjbRtjEQQjKZLCYmBiEk\nl8sLCwtra2vf/Xx6S83QHl1D49uG0BTEGGNCyI79xZ8tWZXYzRbdcpRcLm/RokW3bt1CQ0Np\nNjsvDvc5hVZhO2IbMGBAfn7+9Wm7vDOz07VGvV4/derU65jXPQkhPABc8iGh2i5da0zYk5DT\nLUdr1C5fvpw+8y87ftmEtpOI/DwbDPq9whLzQeuc7jnr9q6jbXnCNzESTFzhAQ9ftnOz43iQ\nTy/TepPWqN00cFNmZuZVJk8WEBC49QhRsQL/UOotbfT/CMEAhF+3bm379u0QQOVPVaHvtKyx\n/iGXtPGVd+YxhzFPMCbAYcxjT4YQHmMMwBPC0wRwBGMgGGOCeR5j3iP8ML7sAA4dOqTX64cO\nHdq7d2+DwZCRkVFUsSrLpPstf0CbFs+la43Xp+ooCCGlUhkXF3f//fenpKS0bdtW7SuSy+Uz\nZq8cOXbO8jWH3/nsjS/X/rEy48/Ss+b+/fufLZaK/H5asmTJhg0bwsLCxOK/OPvS2v+2t2BE\n+PzwkjdKZs+eLRaLZ82apdfr165de/VDsjmLvVbMnj17XvfU7jG25nRL1x78+/He7X7LMumQ\nBMVtiTPpTMHBwe+9955er09UJ45vPb6JgmPxLadmmXR7HkwYv++0z/0+pL7aL8dx92nuG3Rg\n0GVbZZl0XSM/r3RWoitZmhuaqAUEBO5ABIudwD+UehsJ8sgywBaLtVVYS11SUm12rU8/FSG8\ni6sL1zyCscfOwTAM5gggQAQB9cESTEs2MYhgwgDCALSEE2EAECBa3OuSW7/22mv5+fkA8PHH\nH0dFRQHAnuPDbK5iAEiN3SyTtGiuCcpksoiICD8/v4iICJv001BZx19//ZXn+RYtWliIOCQk\nRCKRqNXqgICAo0ePdkiydurUSSaTiUSX/rPAMnIe28VBYvc5t1KpBICOHTtS/+DKlSuv0nS3\np2BYutb45JNP9u7du1kmeA9xGS0lYuVdoxZTu13olFCTztTJ2IkmMjQYDEfMR5Kykw6mXkYR\ntvJ/OO/MbO+uJFxS9N+ijIyMIUOGGAyGJhShn6qrYIcTELgHECx2Av9wCCEEARBM3n777fvu\nT5PLVUF9Q8QtRRZ7YXzUUIXSR6FQnz1TBgTLZEpCMBBMgJfJVITnqKpTKHyAEEQwXbTmdDpk\nMiVpAL2Tw+GgX8wlJSU0w3Cr1v40wzCHbTTDcHOpOgpCSCwW+/v7x8XFteuo7Nu3b2BgYEBA\nQJ8+fTqnqPv27TtgwID+/funpaX5+vq2CJUS9uzEiRNp8dmrwWAw+Pn56fV6h8PR9JWk3glY\nWVk5adKkG5rVPUTW0aTOUYsbO+un1LUKGJll0gUMD1ClqEw603PPPdeyZUu9Xr8oYZGCVTSm\n0kSMsvDCsl/6xesMptj1seZtZlqhBAAkjGRX5a5Lh2HS9Yj54azj7GV7w8SNQMabeVbDulwu\nevCKhj0BAYHbhSDsBP7REGqAA/LLL1uUSqXNWms5V2Wz1qjUflKR/5NPjraaq63WmuiYdgSI\nSCTKzz+OMSY8bt++HU8wwZhg/Pvv+7/6ZhWPMQGMCfb19QcAQnB9IAXZv3//oEGDhg8f3rdv\nX4PBsGbNmqKKb7JMup25faNbTEjXGu+P//nmzREhJJFIVGq2VatWtC6FTqeLaa/o2rVrQkJC\nmzZtWrRoodVq5eb39598tF+/ftcU9/r1119//PHHw4cPX7BgQROXbc3p1jdh34wZM2JiYm54\nQvcQiAQoGzWhAUB86GSltE2WSRe5KJJRMyadacmSJWKxeOjQoTu772SA6bOvz99b9W6/s7D8\nM3+px/KKxMh21DZlypSHH354T489/8n9z9+bKKStBxoHXtZcty2ne4/YNacnnI74IOL111+f\nPXv2uwXvPhX+1HVNWEBA4KYjCDuBfzQIAQE4dixXLGZ9fHz4Gh4pWUKA53mWUX3yyWcEARCw\nmKuBAMdxnbvoAMBstW7b+gsQAITuuz8tPi5u3LjnECDMk0O/H7Ja6sDjkIWVK1Y+/fTYefPm\nLVy40GAwvPrqq7/lPZRl0hWcW9ir3Y50rTEyaMwtmymNh2VZVqFQyBWMXC6XSqUikQghtGDB\ngrlz59ErpVLpkSNHLmkuYn1cXBWjYghHfHx8CgoKvKeioqIMBsOOHTsaS6uBiRsAEBIZjcYP\nP/zw5szv7mNHbu/YkMtorEvoHrNGxKiyTLr229sDA6Yk0/r1691u95AhQw6kHqjj6kb/Mfrv\nrRAwdteZ1xJCU3/KSdibUPhUYWpqKi0xDAAu7PJemWXS9YjZkG/Jb2IMcklLe45d0UFRUFCQ\nmJi4sXzjCxEvXON0BQQEbhGCsBP4p4MQ2b4tq3daH2IhL7728gsvTggIDLlw/iwA1NZcUCo1\nSpWmoOAEvTgwMBAQCguL8LQFOHToMABoNBoCGBD0Te8PiADAsWPH1q//obTszBdffJGRkdGm\nTZssU3KWSefkyqnXVcyqbtOMG0UXtWzbsZ4ZGRlvvPHGJac6hM/NKZ0R+VHk8UHHv/rqq79f\nYDAYgoKC9Hq911vnZVtO974JBz777DMhI3FDON7SOvCxq7myd/sdALAjt4/2gBYIFAwvMBgM\nHMdNmzbNmGrMteTOOTHnkiZ9tQd2Hx/0aFSAg78Y6xAWFjZz5sw9Pfb02NOj4cUKaatRf4wS\nVtcJCNwbCMETAv90Xn554htvvIEAYTtevPxTF1f50aL3RIwCEIhEYpulhgAoVRqbtRYAiopO\nlpaWisVimsiExtQqVRoA2LFj18ZNm7J/23Ho0B8AIBFLhg4dgpCozv7HH0Wv8sTZwrdPh9aX\nfgHfYliW5flGc174Kjpg7LzsKX9V0qHTzys6KNzn3SKRyGaz/f2aL7/8sqamZtiwYUlJSW+/\n/XbDUwgxmzdvvr7sd/cke44P18g7Xv31NAHKwZNjkowrTDpT2f+V0eCVH3/80figUZete7DF\ngx3UHf7eUCFivj554dGf40060+fGz/V6vYS5mHc6y6S7L+6nXy78wl6uPJ2AgMDdiCDsBO5l\npix+x1SSTxAAACGkTXDEool/kVbvvDOTYZigoMCKHyrYQJYQl5szK2WRCGD3nr1RkRGhIaEI\nEQAgHucqSUjoWFFx1uFwYCDJSd2tFs+KNKXK90xZEQCRSmUAEB3TtqzKUGPbZ3EWpsSsUkjD\nb+nMG0EkEjUm7GbOnPnMM888McnvbM2PCxYsGDhwYGZm5rX2r9FoqODwJrrLMiX1jN2Ul5d3\no0O/t7C5Tve4xrzTVNudurBCaxxj0pl8033po+7QoQNNXLw9ZbtapPZen9z2662mbrv+tV9n\nMI3WB9GDDMOcPHlyRsyM3nt77+i+AwCk4qBp+dMaM9dVWQ4qJZH243ZZvKysrEwul1/nhAUE\nBG4VgitW4B6kxlz70JuPDZ055kRlsUKlVKvVarVapVKds1wYOnOMfvqonMI8ACCEHDuWs3Dh\nwtI3yxAChmVq7SaVvA3DsAixPXv2GDpshELlq1BqzpwpQYAQQgiQTCaTiCV0xVpubh5C6HTR\n6eLiIo1Go9H4+Wr85Ao5AFww73RzFYmt5/aMy1BIWt3uR+LhkrTDDenSpUt5eXmvdr/mlL4V\nHx9/I+nKDAaDVqvV6/WVlZUARC5pOWnSJMFc5+Vk+RIRcz1e6XSt8WT5olq7SWvUnn7htPuC\n22AwPPfccy6Xy5hqTNuXxuOLqt1H3o4ADwAMgrM2V/CE4Nz03E2bNk2cOFHfQm/hLVkmXe92\nO5YWL1WyysbueOj0891j151+4XTkwsjXX3995cqVQ4xDPk74+DoGLyAgcGsQLHYC9xpD3nqC\nEbMqlWrpyx+o5Jd+YzlczqcWTpz+7Vy3y4WOmNesWcOVc7yNDxjsP6KqlZhVMgyDAAGDCEH7\n9+/zmOoQIACbzYwAKi6cAwAfH1+C+V07t+/fv18skXbt2vXc2TI3X1fryCEYn6vM1ii71Kso\nBE0Wn7hlOJ3Ov+eoawyWZQ8cOJCcnOw9Qkh9hVk7DggIqKysDAgIaKz5nDlz7Hb7AH1iZOsE\n7exzNzLse49TF5Zca5k4L/VFKQ7SgmNao3b9+vVDhw41GAw7u+/stqdbQ9tbmP+wXXn/OvDQ\nzzqDyThGe37Ree+pVrKwRZX70lnV4uLFV1xdx9fwokBRTU2NQqEodZR29+t+fYMXEBC4BQgW\nO4F7ioFvPS6WST4YP/PzlxZgguvs5kteLt61eML8pa9+KFcoUBeNTCY7ObYwamFkpXWvw1Wm\nUSYyDIsQQ18sw7Isw7IsyzIMy7AsQ8+YcnIyDYZNhs0hoSE9e96XrNOdN2cVVa48V2tQy6KC\nfe/3U3VlWW8/t/uh1ONwOJoWdjKZrKSkpGvU4u3H7t+4cePMmTMbno0Neflo8bS2K9sWjiuc\nNGnSnDlXWC8ol8vf+p+m6gLfq1cvwVzn5ULdDoaR3kgPfRL2Z5mSAKD97vYmnUksFtOCY0pW\n+VHCRw2T27VrOc3FVXh3WRVb8W3FV199pdfrJ8jKStnwt4+/HSBuVJ0LCAjcjQjCTuDeYfCM\nJ1Qq1ZynpxOAGlttja2u1ma+5FVjraux1dXZzHOfnq5SqR6Z9YwmXYMQKqr8Jq7lJEAMQggx\nDEIMwzCIYRjEogavxZ8tWbTo0507dw0aNOjhYcPbRLU9Vjb96JlpVZYdbYKfjgp6UiENYxDD\nIPbiL9cdU4HpisJu3bp1zz//vJ9Sx+PLxEZEBI0ur/tFniB35DoSExNzc3Obvt2OY70jA8dk\nZGSoVCq9Xn9N6fHuYY4UT+rTfveN9MAg9v74X7NMOkbKtF3VlhYcmzp1ql6v7+HX46nwpy5J\nXFxp3v9VatvkzaZ2O9qd+/Ccv7+/p0AtoPXn1m/ptuWG5iMgIHCHIbhiBe4Rhr3zlEKhUCgU\ndXYzQogW8kJ/N5cRIEAIJpjgYL/A8qoLz5unTMjJSY5exV4qei4uRztz5sy4ceMAIDIyctGi\nRQBQY/vTWPA0APirUrpELrqpU2sWWEZpt9u9hWvFbFNrvFikLK/dOn/+/KFDh65fv/767shh\nS3TIBL1e//vvvwOAXq8PCQlZunTp9fV2b+DiapqlH4nIr0P4fFpwLHh8sEln6mnsmZqaSmNW\ndlbs9BYHq3fdGjH9AwOBu9zdqVfxNwuSOv5HtO7MuibuUnDu43D/kTU/1vjqfXfv3t2uXbta\nd62MlTXLFAQEBG4SgrATuBfgMS+VS+VyeduwqDqHhUEMQoBQfcBDPYQQqK/yhQnWJ/dfvWs9\nAPy4vUW6NvayPS9fvvyHH34AgIkTJ/br1w8ADp2eUGXZBwDdo9coZW1uxfSaAxHr63Q6aZI5\nh/ucShrdxMVpCTupGnC73dd3u/0nHpOJQxseuSRa9p/Jrrz0615ddwnBvmlBtWlZJl36s8aq\nzCqTzjTFOGXkyJH0CXff071hMVkeOweH+w3Mys88qP2zy+G0r+QLd1WcqzsXrWrqY1BUsTJd\nazQNMiXsS3hx2IubNm1Kyk7akixY+AQE7mgEV6zAvcCjc5+Ty+VyubzGVmt2WOocZrPTanZa\nzQ6Lj8ZhcVrqHJY6h8XssNDjdHv/ycMymUwul5+xXSZq9cknn9Tr9T/88MPq1asNBkO/fv22\n5aRmmXRVln192u9N1xrvIlUHABLW126322y2Nm3aVFkOKmWX/0bv0aPHihUr6vdIUFDQ3y12\nSIQIRy5jDW2A2XE8NS5Tr9c36A0MBsOwYcP0ev3hw4evfyYC9XRsPV8ljc4y6eI3xTMKxqQz\nff/99wghvV6/t8deAOi/rz8ApGuN24/1nN4x7KzDDQAWx4l0rbEIF4n2i7Ykb2ms4GxDkAhR\nWy8B4i/xv8nTEhAQuCEEYSdw11NQclwmk0mlUolEglimjqo3h7XOYRHJnHlFtbV2i7le1dU5\nLGaH1ey0mJ1Ws8sqkUikUqlUKn167su0N7fbTQ1LdXV1BoPBYDAolJIsky7LpGOQiBaNYBjx\n7Z3yteLiasUiX4fDQQjp1atXlfVgYxa7adOmrVu3DgDS2mVnmZK+/PLLZcuWec+2CR5XUP6/\noOeDyheV/+c//3nttdcu20nh+SViVkO3AwMDG556+umnDQbD9OnTBw4c2Dxzu3ug6UWat8+U\nmO8QYrNMSe13tUcMyumeQ7MPjhgx4mDqwSquaqhxqPdiBGA8X+qc/ZVJZ5JOkwZuDwyQXGfk\nxGWz4XiM4X878neu76YCAgJXgyDsBO56PtvxtUwmaxsll0gkYrE4v7zQ6raXVxVdKP+15EKd\n2Wl1I7fFZaMvq8tmcVltbnveuZMikYgKO5lM5mS57777Tq/XDx06dMyYMQaDYf369fll87NM\nuu3HerZrOT1da6SVne5GXO4KCevrcDjcbndqaqrNWaRWxDTdhL3cUqqo4GeLL6wKfjK44puK\ntLS0/PzLFxgtPL+kV7usQYMGzZ0797IXGAwGhmEaqy17DyO6CXXk+ibsByC78gYkHEggbnLi\niRMGg8Fut7///vvGVGOJo2RlycqEVjN3HOt9UK99dOfetMGZhdbCbppuAFBdXf1EqyeG/T7s\nsj0jJCIcgQaWWRmSEUIw5nme4zmX98W5nZzbxdFtzsVxLnf9Ls/XX8a7eM5Z38TN8xzmeUHk\nCQg0O8IaO4G7nupqc3iIn5psd6iHcBxhWfZc3QWl1OWrOseQn2rcvQljsblYAJCgLBfp6+Rc\nDpdTLBZzHAcAGGOpVOp2u7/59ttNmzbRqIutOd0I4RFimmtF1O3FhStFrI/dbq+pqfH39z9e\nXdH0GjuKXNLqdMVXixYtGjRo0KZNmwAAAaI5b5vgbPVmBokBAGOckJDQ2GUbN27MzMzU6/Wz\nZ89OTEy8xgndfWSZdPfHb7tJnadrjVmmpD9Ov9zJ+JFJZzq/+Dxd0ditWzdalKJn5+84bKmx\nHkEIHDw+nHz41fdejTZE0wV5X5V+9fc+DxaO1Ya9d3bu2bA3wpYtWzZs2LBdlbsiFZGEEEIw\nIpgnxFOUBSOAi/qP0EItgAgBBECIx2dPJRwCTM8hhkGMYFkQEGh+hN8rgbubnw5kSSQSm5vJ\nL5EGSDeKxWKxWCwSidxYnnfyXIXVbecclZYyiaSipmJHRaXZDW6VkheJRCKRiF7s9caG9o1x\n8zXU6yoTt0zXGvsmHLjd82senK4KMetrtVoBgGEYF1/JMo3Whpo1a9aYMWMAoGfshhPnPoqM\njPTG0l4NOWVv90nYO3jw4IkTJzZ9Ja1aNnXq1Icffvjq+797kYiup9rEVZKuPVhh2VNSuVZr\n1J5fet76h9VgMMyZM6e2ttaYavz34X/Lpe125vU/PnxEi7UbpG9JHScc3rZqkfrbsm8v6bDW\ndqSFJr1qfZXfEL/169c//fTTk/Mmf9P5GwBCMOEJEMzzPOY5TAhPCI8xT3gOYx7zPP2BMeZ5\njnAcxhzGHOE5zHE85jDPY4IJxoQAwDV8tAQEBK4GQdgJ3N18vzeTrq7zDXqgsoaoRT9R0XYi\nd51GjYgkDZHztvKdVpcmwJ/39Y0C1wGrQ0yvoa5biURCtR3Pkt/y+7cJfjZda+wZe505Pu5M\nHJxH2IlEIpZlCeGauLhjx44VFRUNj0il0s2bN//lokYCJ1x8NT3H8zwNIm4ahBANktXr9few\nV277sfvaBj9/s++SrjXmn51rd5drjdpTz5zizJzBYBg1ahTHccZU46LyvZjYAIAj/JS2U4AF\na451wYIFer1+e8r2D099eMX+EUKYqjEEhGCZXGWuq8ME8xg/9fSzyck9CCEyuVquUMsV6rLS\nYsD82nUZGDDBhGAiU6gBMMFErlDThXaEYCDoDsr0KCBwTyAIO4G7G6rqPIY3zWPA2aRshd1S\nEtmSqzWLRCLRyZxdZZUy5NiTc0Jkqf1TKtfKma0StkBUz8XmUmm61tgmePztnlPz4+IqRKyP\nxWJpolbsZekek7E1JyUjI+Ozzz6jRwJUPassBzQPac4vPT9+/Hia1c/Lrtx+6dqD48ePb1iL\n7IpkZGS8+eabAwcOXLVq1TUN726Bx/ao4LG34EbpWuPu/IcIIQkHEvLS8gAgIyNjyJAhADDa\nR1nK4b7ZXcbEcL1/ztXu15568lR8fLy3bR1Xd8X+GQYhqNdkAMEtWiIgCPDq1d/RQ0lJSVZL\njdVSk6DthAkhmBBCrXMYADAhSpXmt992ABACGBoJwhAQELgRBGEncHdD7W1eD6wdPci4s5zW\nHYrAweUVbpFI5HRzXTtHSTV9WgcX+Qd3ZyT+pafOK1VRFed/U4gKaSsq7MTiuyzW9epxcRUi\nVmGxWK6yVqxcLqdGO6U0wmveow7ZDq3nHDr9QqsZrc4vPq/X63/++WdvK0xcdKOsrOytt966\nphGmpKQYDIZVq1bdexEV+woeC/ZJv2W365Owd2tOEmIgPivepDNJpdLPP//8v+8mKMT+XWJ/\nGcAc+UT3qIXjAQAQYAdOTU2dPHny/p77++zr4+0EE7eIUXM1HOvb4C8BAoAJACCCqV1WKpUS\nQoDAhx/MJ0AQAPL8B9VV5zf/+FN9KklPOkmEwGKuBkIX3CHAhADBWNB2AgLNiSDsBO5uqCzz\nrpnz8QsrPM2GBSG5Miyl9/Msy8a0ASTraa1ee6qY2CwF1qo/Kuow4JpWrfthUfvKMoNM5ulB\nIpHc7tncLJzuChbJrt5it2rVKrrMDgAU0qj8s++vWrVq8ODBANBwcd4lqey25fTok7B31qxZ\nbdu2vb5xGgwGhUJxj2k7i/N4h9ZXqKvbjDBI3DM2M8uUJNKIIhZFmHSmsLCw5DTngsnKV469\nEiAOSMrWdfBTvHawWHtQeyz12JQpU3Jzc1n0lw/Gzty+yW1XFE0sivgo4sUXX5w5c+b8wvmj\nwkYBA+CRbgQAqqrKHQ77qtXfjxv3LEKI1HtYaSd5eXkA0L3HffQFAJ6PDA2gAEwQQd7YCgEB\ngWZCEHYCdzeiBrAsKxKJ2nV5tq6WuKrXMYw45+AXLdq8WFP6hX/I4yFBvH/Y0Mo6t9vFHDAe\nE4lExce/aKGplEocLMuKxeJrdVPeRTi5CpaRXb3FrqHxskfM2pLK1T4+Pk17zWi0LIPEe/fu\n/d///nfdQ12zZs3777+v1+sb5s+7ezlW+o5EFHjl65oVuSQ0NuS1LJNOnaLWDNRkzR7dIii6\nQ4cOxwuOP6U7M1Z88k/yyM7yi45XlmVzc3NXdFzhTVbMY5tCGmHPsSsSFEVFRV26dPn+zPcv\nRb5EsGdFHFVjDEBQcNgzz46nuw1LvVRVVT/675EAsHfPLvoCAK/rlfEoQ4KBCEvsBASaF0HY\nCdzdsCxL9Rz9WVLyh1opC4l91eWsEItqomNDxWJRSPRLBTkZkQkvlx1f6qf4E0k0YaHiyqLF\nLQIYeYsXON6Xred2z+ZmQYiLYWQ0Kvb6wMQdHR29ePHixi7YaurWp/2eb7/9ViqVXvddKHFx\ncTSP4D1gujtTk3l//M9Xvq65aR34aAufflkmXau3W9nbHfIbteDXB3/t+lvXQQOHRCvbMsDk\nmfNq3VzY9LBj9x/buHHj5MmTi3bXnRuf0CpubHj8M08N79QqbuwT5iWX9us1rxEAAAyAMR4x\n4uH6Wn0e5YYQCm8dFRYW5rn2ohXPI/wIACaEYASAGgvEERAQuD4EYSdwd+OVdJSYmG4WW5Xb\nVtKizUQRYk+Xqbf+uHDrjx8opefPnFwUmfBKWPQklRR82BOsWBMQMZH15DwR005ozYnvv//+\ndk+rmSGEZ5D0moTdo48+umDBArqd1n73tpzuCxcupBGsUlFQtfWwT1+f2l9rk5OTd+7cSS9j\nGMnq1aszMjKaZcwGgyEsLEyv19tstmbp8NZTZbmd6XISW8+WiUM3GAM18W0YFWPNyfi/vAAA\nIABJREFUtW5bvo1hmF9+sH8Y3DI+fE54xia/wX7Yhoc99s7RwpYTX/9WKfVVq9UtWwYHBfmr\nVCqLgrRJfP7IiZDjBSUX+0WIAAJAQUGBDDBlpadXfvklAsbf3x8BU3jqdEREdK/efa3WOkBI\nKpUBYhAwCJjAwEAgqHVE2yFDh7du3WbQoCGI8So+wWonINBsCAmKBe5uGprr6pfKtcBYIxYr\nzDUXAoKCLOaqkJY8K4pS+bQWiSWH98yLDXfZXcrw9s8S4il4ynEc7SQzM3P37t1z5sz5+uuv\naf8pKSlvvvnmbZ1iM0CAFzFys9l89U1GjRql1+snTZoEACzzFyPcffE/bc1JSZuxJ/+B/Ld2\nvKXX690Bk5PbfFVUVNS8w/78888rKioeeeSRxMTE2bNnN2/nt4BDp1+4vQmuU+MyfziodPEV\nT7735PyZ83O/y920dZNer4/X7TY+eEG5eu0E00ubrA7pMenjI9Penf7vv/fgdnOdek5+4OHZ\nLpIIRwEhRAhiEAKWKSkpJhj7BwRScbbl5x8BoKTkNAJEzXkI0KDBgwAAGAIAJcWnPD89VjuE\nwJOjGGPCMILhTkCgeRCEncBdDCFEIZYzDNPQaMcwDEIShJDFfDpB2y9Bm1Z17teA0P6c25n/\nx/+F+kMr7QxMszBgTFd801YMwxwrnZOaOoXapQBgy5Ytn332mdchmJqa+sorr8hkl6m1dYdD\nCM8wsmvKM3wJKlls/tkPli9fTrMKE8Ixcoa3eKtQYB9F+8de1HsfXSPDIDRbxiWr9epXaCHq\nx2vYIiDAPzMzc/To0Y8//vjXX9MCCai+FfXp3aGCwOYqQeg2u0T2nRgZ5jfE7Dhudpx86JeH\nTDrTqRdPGQyGhauCM355tviBD3SpW5VK5Y4f3wGAisq6vz9MAmTHj+84HK7+Q96NShh3Kudz\nhAAYBmHCMIQgIORSXyrDUIcsWx9OcekFnvV5DAAw9duC70hAoNkQhJ3AXQzGOD00ebfV5F1p\nRw1vNL2Cj28MDQJQ+ib+cegnH7RfxIhaJTwhEolLCveFRSbzPA/1q/RYlo2RqYsvrDxb6/Ek\nqqSxAwasGjBgAN09e/bss88+m52dTXeDg4OXL19+OyZ9PRDALHPNelQikZjNZrVaDQAp0auy\nTLo47X/+HkJRZ8+PC/2/8vLypgbgEdK4Xtj9pRNPLgzvWD1hl/WlqACv+PLLpUu/WDB//sSJ\nE1kRC0AAGIZBCBhatQruvNDKPceH3vZ6dBbHyXStMSk76Z3A8KMlbyQaZ5l0pso1la88dv6z\n9b7J94uVSuWq5RMvVNSBNyVJAxVG6v9HCPl22StPjv84vutLucaPEEII0Yx2iJC/NGFoTAQD\nCBACz0nyV2VHC5FR4x/tR0BAoBkRhJ3AXQzG2G6zAwC1t3nlHcMwDLhbhrcHAISQf2BU1y7q\nmsoWwa16Yt6KGHFUbCo11wEAz/N0Q8OF9m6/mxrkLpizc0rezDJ5ggQ1is6J4XO85qi8vLw5\nc+Z4LXnh4eFvvvmmd6n4HQgh/HUIuxUrVowZM6bhmjlC+MjIyA8//DCxQVEJQnB4wAhadbSR\nu3vWyhOCCSaA6Kr5+pMAAIhhCMbUtIO8ZaYIQQBAgCCEnx77lMvpWr/hB39//96906ipCBDx\npEe7w8BN1va4NWTnDwr26YMJJkBGdjqSZdIFq9O0xnSTziTXyt+f8bhSqXh1gv5ChZlhGIQQ\nAu/zpxCoL/yKMSEYy2Ryux1iOr1w4shilhVsbAICdyiCsBO4iyGEuN1u+imm2o5a7BiwMyI1\nQshcU0bA7usXI/JpqfRpSQg5U5YX2jqZEELNdRhjrxuI53mvJSlIndq7/Q7PcWzffuy+3/I9\npjuWUaS137VixQq663A4hg8fPn68p16FVCpdt24dusOkBiH8dbgsfXx8nE6ndzetXfbWnJRF\niw7q9fpuD7W2Ok+LWoi2/X5fRJuA3377rYl+EALq+wZaUgoTRAsX1MMA8JiacOqbEEIaxksS\nAACRWDRk8OD9Bw5u3ZrVp086IgwQgli4A72x23JS+ibsv71jcLjPpMZt0mXrdqTsAIB0rTHL\npAv0ydYatW0TX1AoFXK5XCGTVVXb6K/ARZtdPfQtI/XmVu8iBLvdIZfffQsSBAT+IQjCTuAu\nBiEkFovPGHJjRyZB/TcTy7KnT2bHxA80HtiSnPLAJU3CIrswjIiuNvMGTwDA3MemLV2y9LKC\njGXkXp+a1VH8Z8l/vZY8qTgoMXye11JVW1s7a9asgQMH0l25XD5lypSuXbs287SvHZpkDgBu\nZIEgy8q80YsxQTOPlkztuuyrqj4vf3NsRLt27Y4ePdro3QkhBBHCE4JlMqX3uM1aCwAKpS/d\nHTZs6Ddfr8SYV6n9GIbBGFuttQCgVPoCQH5eTqvwVqGh4XV1dT4+6u+++zYpqZufnz8hd6gv\nD6HbmT1nZ27fiMAnbbwNAFQiFT3YV3twqykprf1umVwml8ulUmnBqfNBAT7Us0qfIwNiBIgH\nNwCAp3rYRWFHl8116vnf/EMf3ba5CQgINIkg7ATuYhiGUalUUqnU4XDQlCXUbhfZ9l88z3dN\n6t9QugEAIeR43taYuH9Rix3HcW632+VyOZ1OFrHjxo0rKCho+o5KWevuMd95d7cfu89Y+JR3\n9/74rfPmzfPuPvPMM2+//bZ3d9GiRZGRkTc+6+uAEB4AOI5TqVQAoJRcbWWILl26bNy4kdac\nAIBA9f0HT441GAx6vf6VOedM4v8A0xsAMMZNpD72xEAC0IKhVkstjZtUKH2t1hoAsFlqAIGv\nJgiAqNR+VksNILCYrZa6usSOXa2WGgBQqjR2a82TT46eM+f/tNqOaWl91q5dV1paOmXKtOt+\nLDeJLFNSt+jbXPTWzdfGhLyky9YZUy+u80OA0rXG2M4vqdVqmUwmkUj27C+8r3usxxWLEADU\nnan2baWoLrFKVazcVwL0XSPA8bxEIqEij+f5OrPVR61s9PYCAgK3D2GdhMBdDMMwfn5+/v7+\nOd/scTqdTqfT7Xa73W6O43iep9KNbwDHcdGxA3ie59wenE6nw+HYOH/c888/HxER0aFDh19+\n+eXqB5DW/rd0rTFda0xrvyfYt8+uvL5ZJl2WSbc1p9uZasPSpUsNBoPBYMjMzOzXr9+ECRP0\n9WzcuPHmPZbLQQDA7XarVKpq60F/VdJVNps5c+YXX3zh3e0U8UGt/Yh3t9K810cWp9frmxas\nGBMAgglVdwBAEPGu56Kr6IAQSEnpRggJD2+VmWkAAiqVUu2jPlV4vOEc5s6eBYQcPmx0u90j\nR47gOX7cuGe9HsOrnNTNh6hlsbfx9ltNye1avlnrrr3sWZlMJpVKaX1kkUh04FBRVY2tstpa\nWW2trLbJa1pVVFokfjJcHFRZbausslZV2yrPufL3OjSWSNpKKpV2S3vjFk9KQEDgKhEsdgJ3\nMQghjUbTunXr4uJi49KtyeP6UVcRNSCJRCKEkDdIgtRzia2uZFe+SIzPOGdmZJx+9tlnX3rp\npe7du3uX0F0lLCPpED4Pwj27fxS9cqzsnWNlM+huh9bzJ06cOHHiRLr7ySeffPHFF17B9Mwz\nzwwZMqQZHseVcLlcHTt2LK/91V/Z40b64bGzc+fOq5cuf2J8O3qkYQmyy0KLTVHlpVRp6EGr\npYaqsZTu95WUFNfVmQEgL9e0aZOBXkNtdbSJ1VJz4UJlUFAgTbBhtZql0qApU6esWPHV8OHD\nFy1aFBoSciOTai6yTDpt+NzbOwYCOMx/yCXmOsq8D1dLpVKpVCqRSGjeR5ZlTxdXi0SMj1jB\nIb5GkQ+1cORgqSZM4XveB6Rc6W/uC87S6KQwh8wq4SQAQH99bsfMBAQErgy6k/7MFRC4ZjiO\ny83N3bJly6lTp/yjWrRJ19LvrQY57S4uCccYY4ypsKMWvorCs4W/msLCwlRRy0MjLzzY5ci7\nby/esGFDfHx8cxnVTpYvPnVhaf0eiggcHRPysvfs+vXrGxZFfeCBB1588cVmuW9Dsky6dK0x\nKSnp888/r5O/1jXq86s3KV0S7kpDSdK1xtS0sOztZes167U/aj/+7uP//Oc/jdntMA2qxBhj\nTiZTel2rNksNoRvW2voITORdxsdjfsmSpc8/Pz44OOz8+TJPVxzPiEQul1MmkbEiMWJYhmEB\nYMiQIX5+fitXrrzOB9Q8EEJgd/5DPeMM1IbYyEXAMKg+i683tx8AeBKEePPzXV8ITpZJ1yXy\nMyJpM+DAgL8Lu449/qtWq+kCBvo7IhFLeMwTHixmq6+Pz7njVYkJcdguLj5WIWJEdmxTStXV\ntooQndzhtnMc53K5HA6HxWLZsXmaTHaj5eMEBASaHUHYCdzdEEJqa2v37t27Z8+eyspKua+i\n3fBuXoMEXXLnvdgjLjiO2upqCs6f2HFUo9EkJSXdf//9h88+aHbkdAifv3OzdN68eTExMU2n\n270OTpz7rKhyBV3xBgDhAf+ODXnVu8r+p59+WrJkidcW0r1798mTJ0skkhu/LxV2HTp0+PPP\nP7fl9OgZmykVB1xl20OHDs2bN++77y6uLMwy6TpFfDhk8Oj5i3vMe8US197NihHjKSGAFcqQ\nqdO+oHqrHoIxxjzHY14mU9KQiOXLlj/62L/lcoVS6Wuz1jKIwUCAIIVSbbXUAhCny3ny5EmX\ni0tM1HqTa6Sm9srO3qVU+jrsFsSwLCtCyPMWDx48mOf5Zn/LrhJaJ/VI8VSFuGXboOcJajxz\nMqH5WRCDCCDAGFBDSevJyef9k+SaV8vQ9/qy5joASE6brlarFQqFTCbzWrVVLpVCLJeIpXXW\nOitvkcuVxw+Ucm4IkreyuKqtsgtRXVp6/yhyu912u91qtYpYbmvmW9c6PAEBgZuN4IoVuLtB\nCPn4+CQmJprN5iNHjlRXVx9cktX56d4cx3nDKbyuWK+5zuVyHVq2nbZt165dp06dNBpNv8AD\n24/1+rNkclxq2saeGx999NGHHnpo8+bNzTja6JDno0Oep9vnan4xlU4rqfQIpmDfvg88MPeB\nBzxhvEajccaMGcOGDaO7Xbp0eeedd24wiwrNXUKAv3pVR29tsVgaHvFXdttTMOLVF9756StD\nl25ilpU2fMg8X/fezOEul2v62xlSqQzqneDgTUSMEAJ45tmxcrmPzVYHnsIDDIMQIcRut8jl\nKgBISUnZvu0XucLHe1+bzfzII48olb7r1q1BCNEMxd5nsnHjxo0bN+r1+qlTp/bs2fNGHtQ1\n4Q3QIYQA5toEPYeBB3xR12FPJhfCMHSloScrL67P20tTzQEwAAQBQwhhEE8IA4QBhlzTm55l\n0iW3/brCWdHYBZJ6vPWREUJOsdPOOViGATWc/rO4TWx0aUUxw7B1zqq4rlHK4ggxgzDLeyu1\nSCQSl8tVV2e/gccmICBwsxAsdgL3Am63u7S01Gg05uTkVFZWchxHCOk0ppdI7ClEAR7NwXMc\nV7DhkK3GwrKsRqOJj49PSkqKjIyUSj1OpT0FI8/VbPaRx/eO35eeni6VSjds2CCXy2/q+Cvq\ndpvKpnG8le76yNp3jvpEzKrp7qlTp6ZNm+at9BoYGLhw4UKNRnP1/VMrTlxcXH5+Pt2+puFd\n4o3lsO2d6Y9IpVJ//xbPv/jJ5VqQ+XNHOZ1Op9P13v8Z6hPcYoJ5WsgAE8LUpyGuLzvBgKek\nGKFSEKDeW+nt1BNwgQCAQQxiGJZlAZhLpI9er2cYZtOmTdc0xxuEEHL6wgo3Z48MfIoQXF/a\nHgMAIAYI9vwERIUtQohKP4Kp3Y7W2SAMIAwEIYZBLMOwDIuoQfeS+O7GaNpcBwB9Bs5Vq9U0\n1wnLsgxiHJW47EhVdEhMtayoTevIs1XnxBKx2F98ZF9O51Tt2dLykLBgSa3Goa4ihHAcx3Gc\nw+GwWq11dXXZW6Y31wMUEBBoLgRhJ3CP4Ha7y8vLc3JycnNzz507Z7PZ3G43/XiLZRLEIKfV\nQZ1bIpFIoVAEBwfHxsZqtdqWLVtKJJKG35ollWuMhc+o5bF92h/Q6/XV1dWzZs3q06fPrZlI\nrS3nYOEY7wotH3n7pDYrvC65oqKiSZMm2e0eY0l4ePicOXN8fX2b7vPGhd2yZctatGhBd2e8\nNVgmk014aTEgQHBpJVAgdOjEYqlZvvR1l8s5Y+ZGjDHBGAjhCU9rSdTXnKIryghNQugpYQXU\nX3m5yraEASAIIcQwANRodxln5a13yxKCfy98uUP4goa5+u67L3XLz5v/7//mvDdrNgAghKyW\nWkAwYcLERYs+YhAiAIRghcLHZq2ln0BqoTxzpiQwMBABw7AihOAqHbJZpqSU6LUnXbVj/xzb\nmLDrP/R9KuwkEgmt1MIghmEY615Vub3Yrqjo2r1D+elyjcpvn/Fwx/viFUoFxuTU3vLWKf5e\nYed0Om02W11d3XbDlOZ5fAICAs2H4IoVuEcQi8UhISEKhSI0NLSwsLC0tLS6uprKO4wxIUSl\nUonFYrlcrtFoWrVqFRUVFR4ertFo/h7RGR7wiEbReUdur63HdD/+eEiv17/66qt9+/b94IMP\nbsFEfBUJ6dqDdNvFVe4/+eTWnGS6yyJ5t5jVa9eupbscx73wwgujRo3ytv30009bt27d7ENa\nv3790KFDqU6aOWOoSqV6fPS7VltNvWP1r8quvr4oQvD02P/7auVb780c/uZbazEwQDBDWEQI\nIEQAEwAWMQQBYupTnzBAy455FqD9nQbeXIQutdV52bhx4/bt2/V6/eTJk3v16tXMj+NvEELO\n1+4QMXKECMZ8Skq3bVt/IYT0H/AgXT5ns9QAAEGgUPrYLLU07S9tqVJrZsx4C4BgQmJjE2zW\nWkCgUPg6HTbEAAAGuPpEx0QlixxrbNRcRwgR/RWGYVw2t9vhPuk43loZf5avNp91llpKC8+f\nVgQpc0212k4scouCOijEYjFN640Q4nmehtM2w7MTEBBobgRhJ3DvIBKJ/Pz8lEply5YtKysr\nKyoqqqurrVYrNd2JxWKlUqnRaAIDAwMCAnx8fKRSaWPKQC2PeaBjwdZjKb/8mZixfvvDQ8f8\n9NNPhYWFGzZsuJUzkogC7ovzmJ0c7vLfT43fc9yTGEUqCu4S9cmSJUvobk1NzaxZs1544QXP\n+NXqqVOndujQoVmG4dW+M2cMVSgUCdqedntNfbGCS2123pxyBGNMiFwuQwjefmvoOzM3ADBX\nYXpir0HJNE5aWlpaWpper//oo48alru9GRBCTpR/nBK9hud55EkOShCCDh0SAQEh2BMZ4bFF\n0ghYoNLWYq6ZP/99euyFF8YT4nE4Y4wRw8JVF8LNMiWlxv1kKDeIUaOpZ2hdFqrJPOY6hnHV\n2OLDY5XdFOUHXNE+uuoTVZFsSl1AEQGodrpZJDpTWaZQAOuv8cYheYsyX/8jExAQuGkIv5kC\n9xQIIRoSq9FowsPDXS6Xy+WiZWFZlvWmV/UuvGsCEasckHg0y6TLMiV9vPzNl8duyMvLa6LU\n/c1GJm7RM9YjKwmQgyfH7C0Y4T2ri1o6f/587+7rr78+bdrFkgzj3rLe+AAWfvi8QqFQKBSt\nWsXa7XX1AROXlhilkRL0B+ZxYGBoZeU5QojVWqdU+jTe/U3BYDA89thjer0+MzPz5hXwdfMW\n77IWAmTfvv0KpQYAfH19318wDxCaPHkKIPjkk8WVFeUAAEAAE4yo3qsPLQGY+PJLvppAf3+/\ngoI8xAACAoA8YbJNggkHQGTioBkFMxoz11GoqhOJRDSJHZghPLBlwYWT1qPyiBYR58SFIiI+\nUX7U1+2rCGGDHaqSExYXa49r35GavRt2IljsBATuTARhJ3APQhfSiUSivwc9XOu3Oy2d/mfx\nf/+7IGXua9ElJSW3Udt5QYCS23pytvG8PefMTOOpZ+gug2Ttw96YO9eTI5fjuOXLl585M1mv\n1zudzsGDBz8+qfo67piSkuJy5iiVSplMVlVZ7OMbXB+X6o1n8FDvY6QGO8xxdplMhjH+aOEz\nU99Yc/1zvl5WrVqVm5s7cODAf/3rXxMmTLgZt9id/1Dv9tsxJkAAAUlJ6bZ16y/vvjtr+vRp\nQAgCmL9gLsFk3tx5CAhBBGjxDY+uA2rKQwiUKj+rpQYhUCg1TofVW1Hjih/abTkpae13f1b0\nmYxpqhYwIcRrbBOJRHXnrcGtA84fP68IkJv9LEeLj9jcFow5IuLtZnd57ZkAaUhij9Z5h80i\nkYhgQuCisBOJRHJ5MyTiERAQaHYEYSdwL9MsRhqq7S7U7XplTvzPK/rt379fr9d/9913tO7q\nbYdl5R3CZ0P4bLp7tHiaqXS6qdQTrtgu7M1x48ZlmZYYDIa4uLh//etflZU79Xo9PTt69OiR\nI0dezV1E7DGZTEYLjJaXF0ilcoZB4PXFNoDUp2OjSYnFYrE30Uxx0fHWEbeh1la7du1ofduf\nf/75OkT5zqP73sn4mFomCSFyJFnw5LT4iGh6lsd2BiEABoBHiBBgAAAReGv6NIVSY7PWAEKE\nAGIYIIhGfgB4qqsRWo/DEzcCABcd25gAe3U57DjeAgAsI11Wsqxpcx3P8wzDeLVdi4hAlmVD\ntS13rDrUVpXYIlBdUltQgUt8SIDdbZUgmV1cm7enWPdQB6gPKod6dcgwzFOPdb7KWF0BAYFb\niRAVKyBwVWSZdHX2PB95fG3+1GXLljEM884773Tt2vV2j6tRCMElVd8fP/s+ANTZc30VCc8P\nqzyef9IbFZudnT1nzhzv9cnJyW+91Wi+2ffnP+5Nk0E9cQGB4eDN3nHprakzFiorinmepw5x\nq9VqNptfn/rd5bq/RYwcOdJqtV69tus/8wlGxNJM1wih6OguNlt1aelJmjcnTB28/OV5vx5N\n7pd4gBCe5zEhmOe5tN59t237lQD6+uuvRz7yyPsffPDGG1Np4C+tMyGXexLZ2Gx1ivpEfdOn\nvzF1yn8VSl8AqKgo91GrESNCiGFZptFcxwBQH/L8et7ru6t2Z/fIbuJKh8MxYfL3jEhFLa9i\nsRghRiIRA0D2tzlWroa3AQ9cZEBMvD6kpOSko0jO1CrbPeJPMxHSyssul8tms1ksltcndIqN\njWWuZtmkgIDALUQQdgICV8uOY2kW53GZOLSV6OtJkyZjjDt37jxr1qzbPa4rk2XSRbeYkN7j\n7cXrg+rsuT7ydhGBo6NDXvYa27Zs2fLJJ5/QsEcA6NWr1yuvvOKNmbBaa1csf02pVHrLtdFF\niiKxVCySXhoUS4AQ4nRaqcXOW8DNbrdbLJaJr664ddO+HKdPn54wYUK/fv28pXsvy3c7Nq7Y\ns0Eqlb40YHTfhMuU1p218bP9BX84nc7Jg/P6Je4nhGDMY8wTjAlg8IS9EriYrIRG/kL9WVJf\nQQyQ999h+iQJgxCwLIsYpj6fS6PCzumu/C1/QNO567xYLJaff/751z2MUqlsqNERQidMp2sP\nsXKRCsVWabt5rKrL31/dNaVTYvc4r83V7XY7HA6bzWY2myc8FdOxY0chhEJA4E5DEHYCAtfA\nnuPDLY4ChhH3bJs1YsTjTqdTqVTe4lDZ6+CSPHZdoz7//dR471mVLCYlerV3t7S09LnnnvPu\nBgQEdNDyPj4+tMAozX/mrXjVmCcu1O0uY1lvUmhaw81sNt/Xa2xCQvLNm+lVQp3RjZnuhvzf\nOE5EOrdp/9qDYwHgEpd+/T+ZhAA8/fkUh8OxZuLHKrmCEEIIT+Wsp94rBmAAgPEUfyWepXXe\ncImLlXHrYRhCCDAMixDDIAaulMSOvrPjjo7LMefs7rG76VmbzeYff/xx236xSqVSKBS0BAX1\nzBb8eSq2Y5tlH3z7zGuPe6+vulB9bgcf/7A/fR95nqcVlq1WqwSKHxnatXPnzoKwExC40xCs\n6AIC10CP2HUxoa8CwO6T6YtWDJNKpRcuXPAuWbtb8FN2Tdca6atTxEKH60yWSUdfh06/FBLq\na6iHRtrKZDKpVEpjir0BlfSnlx8qfl9VfYhoJHS34tSJtQXKjQZfsVhMG4rFYqlUujXri9s9\newAAg8HQtm1bvV7vrefh5dEFLxEp07FN+6d6Da+y1Vbb6mrsddW2umpbXbXd7Nn1HKldMGqK\nWqUe/elr1ZZaT0UMxLCsCIBBiEUsixCLEAOIQYgBhqGKDSEkYhkRy7As492g2wiJWFbEoHot\n2OQKNrvrHN04VHvoiqoOABiGEYvFKvaIt8IbjYBhGKZdlxixWPzc62MavqfBoUGiNlaq46nL\nlXqTMcZy0Rlajuz6nr+AgMDNQ7DYCQhcMzZX2Z7jgwGAZeTv/9e3rKwsLCzstofKNsFVVp7A\nxLkt52KVVQZJ+iTsAYClS16kNp6GzjuvuU7ho7Cb7fQrX6qA0rovHXW4tgJ8lVG6ri1KS2Kp\nC49aeurq6p5/ccmtmfUVcTgcw4cPDw4OXr58OT1SeuHshK9nyuXy1x542muVpPKKwzIR46CX\neaJVqXUO4wU/LrPZbJmTL86rXjnR7Uv1WRMxBw0rz15RNtG3cvQfo6tcVZuTr1zU2Ol0Zmdn\nb9myxUJ6eo12VKB7FZ73pqSehhWWac0Jt+VoqxB+2LBhbdu2FdbYCQjcaQhWdAGBa0YhCeuT\nsHtbTk+nu/KVOY6FU8L+n70zj4uq+v//+97ZZ4BhB9lRlG1wHRAFcyPXEdxwS7NFc0lNW1zK\nrCzLFhNt07TUXNLKXBhcQU1RQUYtvSCIIJuA7Msw+73n98eBkZQMzT7p93eej8fHx5k7555z\n7uXzgFfvVavVqlSqPXv2yGSy//p098PC3a+gHU2JrJpPZyy6Urw4mVECgEAQjRUAFgGthd3m\nnAMzw8by+fxS/s80S3nxYindYj+XWpMHX2g2V9zmBAKE5QLHcdj3d6+Bs2fPnuHh4UqlskOH\nDv/Sg7eJWCzG2bLWEjab1zwj8e0ukUjqDVqabq7A3KLtmnh8J9ZSjaxlSAD+sEcKAAAgAElE\nQVQhDrEcK5FIEEIjVr94aOl3eOXWmuxeeXYfxWb96m9Vnc5YiAfXtNf+NroOw+fzXVxc7Ozs\nGm8dMfBVras50jSNNZxVr7cWdhaLxWw2Y3VuMBh4lkIXlx5yuZxY7AiExxAi7AiEhwFroGRG\naTRXLlyNEpa6A8DEiRNXrFgREfHfx5DdC8uyAoHAwjbcP8XSilTkExmwGwAyi9+pEOhae+is\nwu7r8n1zQ8Yim8q82p+7wMssRX11qbabY14hv8PvlRVznZuzKfFk3IdKIBC0Nm3qdLpvv/32\n5MmTly5d2rhxY5snGTVq1IsvvtiemtIPh1qtnj17tkqlgugOA2kY6mqXbqIaTU3NPcv+1LhM\na72rWfMgxLGcSCTCAqi2scHB9n9UhPlc7rgYhWaMZkyUQ9TfzwYAAJqmXV1dPT09L1770p5q\nounJ0CLgcHuxey12VnMdTpswGAxc42G5g4OPj4+trS0RdgTCYwhxxRII/4hkRmm21Av48m9X\n+ut0egDo2rXrhx9++F+f608kM0pX7vvp06f/dm5nQeW2rj4fP9C91VdjrJ3jrcJOU5fZ2yfg\nUvWmMPELfGSzP53rYCe4JKgT2gjCuFqllyfFsq3LZOBsyoaGhm7rnqN4lCxcZhNpYzfQTujZ\ndp3boqKiy5cvp6WlXb16tc0JMpmse/fu4eHh0dHRYvH9CvO2h8bGxi2HEziOzeYoR3t5H1tx\nvdSLomlbkVBrMlvNaAAtflaEEADHcZeLr2FTFi4Csv/Vb/7hSdpDZcOZK0WvDVZcaE8ybGsM\nBoM65f2Dh7baoDgj3dXO3u+uTGes7fAjYlVn9aQbDAZznVooFAYHBw8bNszX15f4YQmExxBi\nsSMQ/hHYbocQ+9KKmwc2h928UXnlypXHoTvFXWRnZ4tEoqrGs27yIe2/q7ByO5+2sbaQwiY3\nC48ViXhcSQ6l7xYue5WiqM/Pci6iugwj8E2WV8Ncm8w2AFCfn2DbcaH1Px2tK3Q50qXyy8r6\nU/VNGU3lCeVt7us4ydFjpofXcK+4uLg2J2RlZW3duvXixYtnz55NSEi4d4JYLH7hhRf69+8v\nFovb0/zq/f1f3dLV29jYiERCoHlnG429nM1aPVVjtJjMZus0DuxoaGhpmQalDVU4QM2a//u3\nGz0S/ihaFKPQDE4bPNlj8gPdKBDwkU1S7MB1GzduzM09NGbCEh3rg625rW2x0NI7BKs6bK5j\nGw7x+Xx3d/euXbu6ubkRVUcgPJ4Qix2B8AjAsWgAkHvZK2mPhaZpjuMeH22XzCjTD4w5duzY\np1s6Kv030JSo/TfGKDT7f33H3sFeYM9DOrSz9KeXA2e39tlRFFXTaN6ruTUXnTIPeg4AzLfT\nJWJBQ2myqMtr2GJnsVisFrs+I9/1lLXdqN5YYNRe0jamNGrTtW1O4Ml50m5Su4F28mFyWtC2\nsMjJyfnjjz9OnTpVVFTU5gQ3N7fQ0NB+/fqFh4dbL8Z/scDW1lYqlQZ52ZfUWYLLL9aK7IUd\n8kySZ9iW8n4YM+cgoGs5jm006qx1QHBigVarNemNu+e3ITQfIUVVP+ZVfD0w5MyDmusAIJlR\nRnc+mZWZ+/zzzw8bNqyhoQEhRNsOt9pirT9ZnBeChR1i9eaGZD6f7+rqGhERoVQqnZyciB+W\nQHg8IcKOQHg0nMoaYOG0AGAyUl+/4+bu7l5eXv6YaLtkRpm4KSo7O/uNNdWDQ9Moql2m+jrd\nVU3+i4ND09WJ79va2EqlUpO9ydHiiG1UVtPOXX/gWX1D7ulvAocsbh16b7FY9Ho9zopdJYxv\ns639RF/HaQEu9kKe+C96aWkvaSs3VhpuGNh6ts0JlIRyn+8uHyTn2fMoftuy49ixY7t3725o\naDAYDK2vO8SF2NjYSCQSbOHDz2isZyQOXe9dRG8WSgQmjuNaR6FZlevuuWvb3PpRgdW2MlX5\nmv9rkz0fwGKXzCg7u73q6zJl+PDhCQkJGo0mOzu7rq7OYrFwHMezHUbz+HcJO8RpOe1piqLE\nYrG7u3v37t27d+/u7OzcHiMogUD4TyCuWALh0TAg5NSlmy/XNKULReiVj8rWLYOYmBiVSpWY\nmPg42DZu376NO0lQVHv/JGvyn49RaCZNmvT0fKm9pTufz9eatXxBs1sWAFo74yiKYpuqaakj\n39ZRMfKt1jmVAIDD83k8Xg5dkaFStH4hRVpjVr3hYHHNnsKaPYU19x5DLuAFycUD3O3GdHf0\n39hWf14EhusG7QVtzcGask/Kyj4pu3eK0FMoDhY7jHQYMmTIkCF3O6Mr66qXHUzA5ZdbJ4gI\nnHvI7aQNjfq75tvyOQA+QsjICQVIb037ZVn2n0f73Z/s0k/5dPNLeCBVd+raAB4t8XWZolKp\n3n77bT8/P5FI5ODgkJOTU1FR0dTUZNEdt/zZNolD7iQSiZ2dnbe3d0hISOfOnZ2cnIgTlkB4\nnCHCjkB4ZPT0/6qwamdu+Vo+z2bh6vKEpckjR44cNWrUypUre/bs+d+eTau1OjfbpTI5ZMKD\n+vp6f+HTNKfn8XgePI+7EmOhlcVOYO+OB6iltQLWOniAky7V9T99d3T7V17BWBp4OU7wdhof\n4+42zNO/zWNcrm769npFXqPxQlXZx0wbis1RyH8uwKm/t9y1s5PzNOc2F6lV11bvrG7KaGpI\nbmhzwjdT9wrdcTEWYetoMwDQ6c3WSrzXmmoKPOTlBnOIRRBhoRFCPMTyhE4mfZ01zE4oFLan\nBN1DU1KzB5vrPgx8gASdm5XfW1htjEIzatQouVzet29fAPDy8rK1tfX09CwoKLh161Ztba1O\npzObzbjoCY/HEwqFNjY2Li4u3t7e/v7+bm5uMpnscfivFAKBcB+IsCMQHiW+zs842fRJuzHB\nxXbAwtWnEpYm+fv7r1ixIjQ09OOPHyAX9T/nRGbfwaHpS5cuDQoKaix1lrmX4T/21kSKO/V7\n/+yNteaMWuuiIYSsk9cEH5YHyadcmfie7xQPtqCk5qeSmp/u3Z3Ps7MVB7jaDenuNO6bPm1o\nPoQgX2u4WK376WbV51m3P8+6fe8cd4mgi50k1ls+QOXgoHK4dwKn4wx5hoaUBr3cZCuwtRbq\nEwgEbfqaQ7x9FfU6mhbrODOPR+PH5Cy6A1eMsWFCHE0oFAqrG2ud7Rwf4p3/LZcLXuHzmsup\nDHF5gCSYvNtfxyg0n332GUJo586d+CKfz3d0dLSxsfHy8qqpqampqamrq9Pr9WazmaIokUhk\nY2Njb2/v5OQkl8tlMtm/V3GGQCA8QoiwIxAeMTbijjhVtrP7qwtXf77xAyNFiTMzM+Pi4g4c\nOPBfn65dsJwRACiKxzDMnj17jh49ajFZKHFzcwKrtvsrYXeXuY5lWey8Kyqq/fLrhWfOnLnU\n7w9lqjJAGrC7Zxux/zVaTVH1Tq3hRk7Z6pyy1fdOEPDs/Vymu9n0jff1neDXtoRSF9fuLaq5\nUtt0+nYDQPG9ExT2kikdnUI7Sj3D3HnbedYOadZODG08XZMJ+PyvSgo7uTgPFUgB4JuDmmB/\n95HdfQS0DiGEpeH10oJ/SdhVa89ic9360PXtvyuZUQ4KTauvrz916tRdQZ9YwAmFQrlc7u3t\nbTKZcG0aLOIFLRDfK4HwBEGEHYHwr4C1XQf72FnLDx7ea7iu8WdZ9jEsg9ImJ7OiBoemf/75\n5+7u7hRFCQSCxKTCyRNDsWKj/wy+xVr8DGMNrbMa7RBCWdmmSZMmjR49es+ePZpojTJVGZEa\ncSH6wl27O9ooHW2U954KIU5vLqlpzCis3pZbvi4X1t07R8R3kQp9fFyeUXk/pfJuw0qnt3Al\nOlNyaf0PeVVvXirBF8P/XH75LnskAIhEBUajHx5PcPPYl5XJ79nrdIlh2CBlYVmDvZQzm3nW\n25tMugd41+3mQt7zArrZXNfXoW8770pmlEEd3qQp/jPPPPNX/9+jKAofXiwWt/4hEvscgfAk\nQoQdgfBvgbWdVOg9fFyxb2fNsV29Onbs+KRoO4rinThxQq1Wm0wmOzs7hGij0SgQCLDowXOs\njSVwQyq4p8EoLpaBS4FUFGobtjU8c+yZuXPnjhkzZvTo0ZoZGlWGqv01OyiKlgp9pE4+Xk7j\n2pxQVneorDZJa8j9o/DVNifYSUJ9nCZ7SILnBPnOCXKrqal59tlnAYD3bB/sZbZyl6OZ4zoL\nWiq0/HQjb0xYt/XH02kLXOUJ5g3tZU2PxaIwzC/owd51+2jQX8Xmuh+6/9DOW1KY3jxa4uU0\nVqVSLVmypD23EDFHIDzpEGFHIPyLYG3HoyUhXT1tHS7u/QreeustlUp18ODBx9a9lcyEPxV4\nPDU1FX/k8/nOzs779++vqOi7YF6/1lY6aOlVf5et7q7atkaj0Wg0qk/mdgjuUDa5LPj3YNyh\n9fDhw+q96mOVx5SpypORJ235tv/w5B3sR3SwH3HvdZYzGC0Vt2oTiyp/YEqWA4L8m3nYpjh+\nntjLy/tILtW6CDN2xbau1QcAPD5ozRYJxYdQjS+ERim6AE/a10eOBSx+cHyvjUDyDx/kXtJy\nJ9mIA/E4xCakPbfkV3yHgB0YciYuLs7e3r5fv36P/FQEAuEx5DH900Ig/J8hRqHhkBkAOvqF\nPrs4a9WqVbt27YqNjU1PT/+vj/ZXIKHAYfXq1diySFHUwoULvb297ezskr+9jhuGmkwmk8lk\nNpuxWQ4HZlkHuLUonoPnj3g3eW9ZU49FPXrs6ZEZntnwW4NareY4TqVSDXEZkt43fWDawM/z\nP/+XnodHi6VCHwfexIRlrglL3ROWuRddeHn26PrZo+ufG3Y7+NyP3sViq6TDUWU4PRYPMDxa\nWGyDfsr4HfSWbH1TteeR6ECpgM/H37Z240pFj17YaY03IgN2hqeGq8PbZe7lkCm/4psYhSYh\nIYFl2R07djzyIxEIhMcTYrEjEP51BoemnczqZ2brgv2fefn9xClTpuzbt2/MmDG+vr5fffXV\nf326P5GSGdnV55PS0lLrlZ9//pnP57/zzjs7xu244nmrR7W3izNl9bdiz2xr52zrjgW4weia\nr7+c0DHqOGu3uJD9Y6jcUePIKBm+G39f0r53330X+6ZxyN3e8r1n+559tE+EEIqPj8fliAMD\nA9esWYOvl35SWvNTDQAgQJN3Tt1UoW7tjbVmgLY2TxZc/mXSoKnHykyV1WdGhzyfcmZPna5o\n0uDl+FuWZfHbMJvNIlF7e3u0hzM5Kjf5EA5xCJC7yL09t5zI7Dso5LxWq01OTn4iXP8EAuFR\nQYQdgfC/YGDImcsF82/XH44M3Mb/8IWpzw1ftWrNW2+9FRsbe/Dgwf/6dHdAyOJqN0g1pTkQ\nkOO4H3744dChQ5rpmo6SjhWDKqasPb0qPkzZ1QM3GMVRd1aXJRZ82GiHQ+u2/nC5oekWT7Rv\nw4Qdle6deh/K+nVQF4VGwSgZRsm8q3n31q1bKpVq8eLFmqc04anhD9Emq01KS0tfeuklPI6M\njFy+vFl+lX9dXvV9FR53/K6jtJsUIZR5sxD7Xq3a7t78ibfP/hTcyc2OZzu0Q9TW6lU2/AmU\nU9m4fnP50FzlzqpxjUbjoxV2RnN5mLdamapMj2qXlTeZUQZ2eIOmBZMmjSGqjkD4/w0i7AiE\n/xE9/L4oqztyMf/FmLAL1LLeO36dEhv7ysGDBx+fdIpTWQMC3Oa3KmUMsbGx+/fvBw74mfy4\no3Gqr/cIJDaXM0oTD3+5/NX3RCKR2Wxu3WDU2jsVu2K/33qZz+f3CJzNc9pVSS0aH3hpXJB3\n76TMfq62azWKrIFZjJJRaBQ45G7z5s0ZP2TMvTr3H2q70aNHWywWAAgICEhIaG7bWrK8pO5I\nHR4Hnwzm2Ta334g6lGm0sMay4ikKCms7q7zD3TXupFCIap/xmNOor3S0cRdKqHpjhbaMzXe4\n2M17FG47gV+C+22+2Wx+6MPfy4nMfv7OL7GIBQBeO7qGpGRGAoC300SVSrVy5cpHeBICgfBE\nQIQdgfC/o4P9MDtJYEpm735BR2Hs0CuX3u7S5Rmaph8TbWfhtH4u062HGTVqVI8ePfh8PqNk\nuqV3+6O6nheg+LiHz5EzSwVC2fdbL1+79vunHz+PlVBrYdekN3+9RWMynnax79mhQ9ewsLBe\nvV6qsXyXkhkxOPScRqVQqpk+SZnnT4bWJtYySqbLgS5Y2+Gt85vylanK1YGrY1xi2nnysrKy\nWbNm4XyI6OjopUuXNl9fV1a9vRoAgIKOWztKFVIAqDVZhqozOUAAEOVqs1bpc/268NcDV6kR\ndljb3VX0BAAWHf82TjFEIhYfObshJmqms9z3TMX6F+I+QxxiWRZnkDTb9urN3J8bc/1DOKTv\n5P5SO8XuzYrNCFliFJrRo0d36NDhP+93QiAQ/vcQYUcg/E+Rifxxqmyfzr8AjJfafZ/0Xb//\nYarsXxazOJMz0k5yJ93yww8/RAi9//77jJJxmeFC8+mZF0ouvjD0Ss6+wnqpxDj79u3bRUW3\nv9tyCWfFNjQ0ZGRkDBo4qPF4o+Bp2/O1xmmKiQ2wIzp6blBQkLOzsxf/HQv7+omsvqGeKzWq\nEUo1o1QzmlEKh1EOjJKxG2zXWtvhkDtJruRM3zP3eRiO4+Li4nBObuveHsVvFdcfrcfjkLMh\ntKj5rUYkMRwCAPCQ8A8Obi5KknNrXXre5rzS2u5cArTU+7AKO6zt5vcc6ePqxqf5ZxttnXNu\n1PFK5CwI+AJrBebmWn0Gi7X/2CMhmQkP9Xqf5dh2zs+r2BCj0Lz99tsWi2XTpk2P6hgEAuEJ\nggg7AuE/AGs7b8dnBIFqePHMqlWrfvnll9jY2GXLlkVFRT3q3ZprkYjEfEFLQ6p7MZpv9wtM\nUqlUO3fuNJlM586dU6vVec/lUXzKbbabUs18FeknFAqrLJ/OmniuuLj45s2brq6umzZtGjNm\njMVikclkHMfZO9gjE/L39zstNEZF9S41H+jRo4etrS0WrHyeDD/4zapNGtW+1VdLlWrmwkgF\nDrnLjMpUn1UfO3ZMpVJ9/fXXmui/DLkrLS2dNWsW1nMDBw587bXX8PVbq27V7qvF44BdAeIu\nYgC4rTePPnTNzCEAiOlgt7qXD56QW76usGo7ACBEKbt82njzRv6e9MBp/Vqng+AtimrLT1zL\nmOkyBgA+HrPk3StLnhYPiOo0zOp0tpZ0KdhzISoq6pEG2KEO9sOVqcqM6Iy/nZrMKAeFnm9o\naLh8+fLjYAAmEAj/CUTYEQj/DVjiiPiufXq+BDM2jh8/HpusOnbsuH79AzSM+ls4xAKATCaT\nybV/JexySj8T8pv7NMjlcpVKlZiYyBk5PaNXaBRKNcOjoLeLbTKjHNYzAxBla2vr5eUVEhKy\nd+/efv366XQ6k8l06tSpyMjIiv0VPWN67r5S06dP7/M3RXZ2dndZsGIUmmQmPJlRLg3TvBLs\nHpHErFF699coMntnMkpmiGbIkCFDVCpVr169Mt7LiEmLsWo7k8k0duxYvEjXrl0//PBDPL4T\nP0eDIkOBjZJmDinVDJ7gbyP6eUBnPM669WFp7a8AQFF0/6BTAr4NANTX17u6Nmzfvt03Prx1\nBWYej4cQ8pK7zuw3BhCUaauq9GXvhn60q+DDKG44y91RdSaTqfy3axKJxM3NTSgUPpIfXDKj\n7OH3pYWzAAD116ZW6+Rgj7doSjBlCkmYIBD+v4YIOwLhPwNruxpt+qQhpyWSYfGTnlarj6tU\nqtGjR+/fv//R7cPV13LBwcHV2t/EQt82ZxTX7I5RaGJjYxMSElQqVb9+/SiKyozKVGgUF6ub\nACB9pOJEZh9bcTAFNFAgEomcnZ0dHBzs7OyioqJwQbstW7Y89dRTN2xudO3aVViWY29vLxRS\nbfolYxQZ53MnJjPKGIUGh9x5Scv3p4eWflTKKJnQ86FY48bGxiYfTN78+2b5FnlEUoTIIBo5\ncuScOXPwIiXvlNQlNedDBPwYIO4sBoAKgznuxHVsnxvqYbeqZ7N97tqtj27V7sVjpf939rJu\nrc8jkUh8fHxqamqyvz0ZOifGGjCHM2StIXROQjsnoR3HccGOYZYWsK1Op9PVXCsNCAjw8PAQ\nWJtU/GOcbCLbY65LYSIpEHg6jlGpVCtWrHhUuxMIhCcRIuwIhP+SGIUmJbO3Jv/F6UPLJJKO\n85f2SEy8FBcX9wjTKRBis6+YO3bsaChMcrZpw89bWpNoKw5jWXPv3hG/X7701FP9Xlu0qPCt\nPJ8NnqzZ9OvN8vShXcqrjzhJByq83mVZEwAAB0ADIJgx44VTp06OGjWKoiipVGpvby/jycRi\nMfB4ZgQCvoOFbeLzZPdu2qfznurGc8mM8qmg4xqVIiIpU6lmNMsUbovcMvtken/svWvXrvDw\n8MDAwM6dO88Jm5O8MHm4y/A5gXMKXy1sPN0IAJSAUqQrgAcAoDWzVvtcNwfpd1Ed8Ti7dHVJ\nzS8AQFH8ASFn+HTbpYMFAsHy5ctff/31zD8yz8T89FTKRACwFuS7K+0XIRQseNpoNLIsi0u6\n6HS6nE2n7O3tu3Tp4uLi8kgCJZMZpdJvc4WxAv7OXFdQuQ0BG6PIUKlUDg4OERER/3x3AoHw\n5PKnXkAEAuE/4dS1QRa2IUahSboYdo2pmD+p6PXXX7958+Yj0XYWrumFuT0mqD5nbr0x/7nD\nMpFf628R4s7nTurdaeeGb74ZPnx4Wnra+PHxtftqWC3nNNV5R37VcC+5k1BQVL3dx2la63p1\nNA2AACj6448/fvPNNymK2rXrR6lUGlUZZb5tLnzJ7pfCmsVdcsrrj3b3XfNXZ+OQ5URmpIvt\nwG6+nz5z+kZOg2FvmO28efNePP1io7hR/77eYDAcO3YsMTGxeFnxsE7DRGbR9i3bO+/pLOoo\nAoBKg1mVcp1FCABGeMpX9vDGyzIl75TXJeFxRKeddpLA+7+iF154ob6+ftmyZbvG7DLFmbJr\ntHFLVCKRCPefsLaOhRZhx3GctbuGQa+/9u1JiUQSEhIyaNAgPz8/XCflH4LNmX+bDMtxphNZ\nfWMUmtWrV6emphInLIFAIBY7AuG/Z0DwibQbzyQzypG9rgqFyi2H3ebPv5CXl6dSqfbu3fsP\ng/ERYqtuI6lU6ujadJeqA4AmQwmftkEIubm75eXnjx0zltWbea60PM4uraI+0E7gKKAqG1O9\nHSciZEGIAoQoAATAIoqiaBo4R0cHjkM0TU2aNGnMmDFjDo5hlEzftz0XZBR+HjGEKXnzPmej\nKT72Rx/5vXv9J14iB4+uuSNeiOg7OnE0o2TgW7AdYBteFj44YPAs21mZGZn9Mvo9t/a5Ix5p\nUS32uV6Oso19/fE4u/TjkpqfAYCiBP2DTgra13yWZdmKiorExMRzPc/17NazsEPhzwVMwDfJ\nAdN6S+X2VmFnTaewVmA2m83nfzhsq+WLxWJ/f3+lUunp6fmoVF3vgD3pten033V9xKpOq9US\nVUcgEDBE2BEIjwWRATtLaw8mM8qnwzQ01ftEVjh1+5MdO3aMGzfun6bKIs5ioqRSqZi13Pvl\n5aK5UZ33//zTz3Z2tuPGjefRPMQBxYMbhQWxYYHlpcXu7h4AQFE0AJTeKr6ee717d2V4eK/f\nTp3MzcsNCAiwl8vNZpNIJOI9uAuyqKho7ty5AO4jnj879fXaSQPULEK9kwJe2pS1AMCQZ9Bf\n0/e63uuE5wmVSpX00hE2fmM5t8k3petbPkfe7NocP/dH0RuVDSdbXuMeG3GnBzpDXFzcvn37\ndJd1tjzboVuGRm/cH98zRNBY89v6JZ4OY4Om9+dJBVZvrNVcV/pjTl19SeqR4xMnTvT19Q0P\nDw8ICHiE+bC24k4vaybe31yXzCgDPZYAwKRJkxITEx/V1gQC4YmGCDsC4XHBwyHWXtYzmVEO\nCD7pZLM87ffFy5ZdxmkE3bp1W7Vq1cMtyyHWbOabTKZ7Y784ZKKBhxCqb6jz8/NpbNQ23Krh\nyWjgQxPLNdTXc8hYX9/YpG3OUUCICw+PbGqq27XzRwSIY1kAGDFixLcbN86fv+DvrEt3KCkp\nmT17Nh7379//jTfeAICskpVJR8N83t261SyaMKnp8juSjFHK+pP1zKic119BDbNXX/v4Fdkn\nC0tOHTewhujz0a7ZPfwslwGAogQDgk/xeTYP8XJGjRrl5OQkEAhyXsrpqum6+vdiacfgqR3D\n9hye1MN2dkNDw/XtZ7CVDgCKq/Z6O4/7tbBmnJ9T3a91HlM9RCJR9+7dw8LC/Pz8ZDLZI6lg\nh+MO95XvE1D3S8JIZpQ8WurtGK9Sqd57771HWDyPQCA80RBhRyA8RkiFXgNDUk9mRff03+g/\nZCZA1MQpZVjbjR8//pdffnmoVTkK+FqtlhbfrbxOZ8X0C0rZvXu3gM/v1r07AFBCiuKDGSEZ\njwZoLoGHJQMCoADqaqsogE4BAdCsdpBUKjUajUBRHIfuLy+KiopefvllfNuUKVOmTJmCr998\n6WbTpSaAsV6yweVfv9TF+7Us5yndD16x2ZERZC/hvU2tWm4OGODodyZl1qxZg57u+uZa4Wp7\nmFO0q5NdryORpx/qnQAAVFdXI4S2bduWGZHpNs8NAH4pqb84qe/xy0Mi+vo50/0KCwurqqoa\nGxtNJpPFYhFLeDKZjCc1ubi4yISy7j26nzt37qmnnnJ2dhYKhY9EWnHIDABCvsOqG6vuY67L\nu70BAAaGnB49erS7u3uvXr3++dYEAuH/BkTYEQiPFzxajMPOfJ2fnRVXC+A4f3EvtfrimDFj\nHi5V1sw2UIiv1Wpp6Z+UB4dMAEBRvPPnz69Zs4bTmwHA1qW5mh220lGUAAB+3L0HAICiJk2c\nAABSmf3y5W9GRoQDACBAANCiaVxcXK5fvy7pJjHkGzwl/LSKxg4Oo37P2bD8teZjx8TELFy4\nEI8LXyts/K0RAGgZHXo+lBJQAFDQeO7glR6G7PV8evPTnvLiJlOKKjozY+UAACAASURBVNhm\nDC8j7FhpSEb8Txdzrgg/X+y6adOmXIXnX1UwbifTp09Xq9X1x+sRh1yec1GqmWMxQQjMtLAu\nfnBaU1NT586dq6qqampqGhsbDQaDqOiQwqdborh2wICwenV9j6491L5qBweHR+iBPZHZJ0ah\n+abwGzEt/qs5FlZ3s3JzjELz0UcfWSyWzZs3P6rdCQTC/wFIViyB8JiSzCglQt+oLns37Jfr\nGsWvTrv98ssvFxYWPqi2q9amTRy/YHL8LLvOq+KfyrdeP341IkZxbty4+G7dui5burTxcqNz\nH7f6hjqKQnya5hBrY+Ooa6qTyuybXbEUUBQgDiiAyurq6qpqoOigoC48mr97z0+hoSE9evTS\n6/ULFy788u0v81/MF3wjUB682v+3TU9PTXeDDfHx8XjfG1NvGLINeBx4OFDgIgCA23pT3Ilc\nC0IAMNnfqRsaBUDFKDJScl6afeXp0S6nhzqfd5/xHVh4Co2CZdm4uLiIiIgVK1aMuDCiwlTx\nENouLi6uT58+S5cuZZSMQqN4/mx+Tr3+3IjQZEY5KDSNpvjWcDpcf9hisRRW7bagxlJqamKZ\nNsHWs+HnhspJldu3b39UBaU5ZDyRGfW3ybD4hKwFjRlDahETCIS7+bcbUxIIhIckRqHRmwpT\nMvvMHl3v5Epv2C//6quv5syZo1Kpmpqa2rnI2eSDny/5MNzLMevc/vpbd0ehzZo1t6GhYfny\n5VU7qsUBYgAwIo5HURwyI2QGAITdsBTQFEVTNCAqsk80oihnZ6eUlBSKAgoooNCUKZM3bdpM\n07RMJisoKBg3d1zOhZyFCxfKHewPHDgUFOwfHx9fMK+AUTKMkjEWGUPTQhUahUKjyBOyuGns\nyJTrwzzlGpVCo1K8FtrBTT5Ma8j/NUNGWbIyR8ec1M56r3ibIq2bU7wTo2Rollar1RcuXIiN\njT0UceiToE+Uqcqbupvtf7cFBQUsy2JV5/e1HwBcrdVhVWcj7kJTfACgKIrH44lEIjs7Oycn\nJzc3t4jQV3RwYHyo3zUj5RjpqP1NGx4enp+f/zebtRus6t6//r6srcp/mGRGGdRhCU3xx4wZ\nQxImCATCvRBXLIHw+IJ9ssmMcvrQsn3nQjbsl88eXT9gwICJEye+9dZbffr0+asbt3z5QT6T\nJhAIaJqWCUUgFCGEytM6v3d2tNlsnv/et1erRgc6bSotXe7r61u0uEgULOLJ+ADgKnfEK+ia\nGqAluo6iaEAUAEVR6OpVxsvLr7a2Vqerz83JbYnBo0wm04QJEwwGQ3Fx8QcffBBQHqBWq5Vq\nJndCrj5exzzHAEBQShBfzgeAaqN5xNEcFgEATPZzfE3hgTdNy52kNd7A4xHdcw2migv5U81c\nHe5OoVQzmiUKl1kumX0z3V93x6GH2D2dFpUWeTayl7zXxrCN7Xmx8+bNU6vVpatKAcAmwkap\nZk4PC9YZCwAgMmDXvfOt8XMUBRRF/RtuDpY14sGBigN/Za5LYSIpiu/lFK9SqRISEkjCBIFA\nuBci7AiEx5oYheZ09pBkRjmmb1bGjYUb9ssnDSy4T6qs0WhYtTBeKBR28PSZtWw9/eeyavU1\nFRs/emXTRwsMBtf1ZSuEQmHCrHUVm2+7Puf6S0FVWklFV0dJg+53uaQ7ABj0WgSg1zVSNA0I\nKJpGiDPomxBwgAABFRgcXFNdo1YnFRYVFRYWPvfc89OmTcN5HhfnXmSUjG6C3lLNkwRJFRoF\nAFyt1T2vzsYnGefruCysWc8xxW+V1x8FAJoS9Q8+YW1oK+Q7YmnrZNNXo1r/wtl8pZrRqBQK\njYJRMlXbqtSH1evXr1epVD///LMmWqNMVbYn5E6lUk2cOBEAavbVKDSK6ENZjiK+lM9Lzh4f\no3jIcL1/zslrUTEKzRtZb8j58jYn5FdsRmCJCdWoVCp3d/eAgID/8QkJBMITARF2BMLjzlNB\nxy4VzMGtCEK8F28/7NcvMAVruzFjxuzbt88688LZE4d/XC+TyRa8t4miKLPJcNdSYolswcrN\niOPWrZjR09v4Rykqeask8GjnoyW1pTrzOF+Hoqo9duIgHp8HLWmwCFEUhS1VgICHKA4QX6tt\nOHPmtNlkbtBqFWFhL86YkXY+bfuOHeF7wnXXdIyS4Zq4oOSgDhdy/V8LLMjiIpIYDgEAzAxw\nmRXkhg9zPje+ydjsP71PvZIWs2XE91EXsur0SjVzNKYL1nZMOLMgY8GMGTPi4+NnzZqlGaWJ\nOBtxf2135MgRAJg2bRqjZLoc7KKzcAaOS306JIWJ6GAf+9A/o38IB2Y8OFlzss3DI2TJr9gQ\no9CsXLkSAEjCBIFA+CtI8gSB8GRwq+bXa6Ufxig0CNDG/faedi+NGvRpXFwcy7I4gj7zj4x9\n36+WSqXTFqxq6WJ/x4WIK5fgAiUIAUJoa8Iyo9H4+qLtfG/hS2fzN/X1yyv/1mSpDPL8U68I\n6k6rUur69Zx9+/YLhUKBgB8RERERHoEAaIq6tbK08Yx24a2F67zWpcWn6VjdtJBpeYnVE6Lr\ntWaum/zWRMePn49IxatcLlxU3XgGAHiUODroiKB99edOZj7FIl2MQsMhFJGU2dfFZn1vv7zn\n8vSMPjQjlKIolUplb2+/Y8eOT/M+3VO250yfMxJeG51hsev2xsQbxkJjaFooNgFWNab+Xriw\nPea6tBuTFV4fxJ827+gfUD+3yPlZ54TfEuLj44ODg9vzFH8FVu0zr8zUs/odPXb81YSmpqaJ\nEyeShAkCgXAfiLAjEJ4YTJaa09lDBoak8mjxhv1yHm0zM/bWzJkzy8rK1Gr1qoXjJRLJ2Ode\np2iKpmiKoloyH1oavOKqdAg4xCGELCbz/h0JZrMlZciKwzGBgIyXCub38ttAwZ3fCQgoAKqk\npPiTTz7lWJbm0VOnPtO7dyRCiAIoXFRkqbNwTRynRV0Su4yNH3vgwIFyvSnq6WEOS9YvWaSv\nSfLZlFupUSmSGaWI7260lONlB4Wco2nhgz7+jfIvC6q2YvmlVDM0wAWVwlBguDH+RpcDXYSe\nQpVKBQBqtVrP6vud7/dGxzcmekxsvYJKpXr33Xd79eqVGZ6p0Ch6J2V2sRNv79cJy6b2nKFB\nf+3arVWdvLcOP56d/nRI7uhc112u06ZN+ydiS2cqOnd97H2SYZMZZaDHUm/H8Q9X74ZAIPx/\nBXHFEghPDNaYs+6+CbNH12/YL9+w337TprpDhw598Mo4mUwmkUj0TQ00jXVdS9Jqy+2oxWaH\n+9izHCcRiwHpoxPf5A/Zl8z0Gxx6AbcOw5w/f94aw/fss89OmDABj/NfyNdd0QEAT84LOhZE\n8SgAOF/RyFQ39tpznpLZOosE6aMUzHuMItAtgbmYzDzXoL/mIJW2jp97CALc5/k4P5PMKAPc\nFmhUzz597FrrkDu7fnZqtXrhwoVY/eCQuy3FW470PoJvx0VJlEolo2QUFxSFWiOLEFZ1oZ7v\ntfMMdpLgRkO2s4iPAGgRba40Ozg4PPQTYbCqG6MZM9Bp4L3fnsjsK+DZY1X30N1HCATC/z8Q\nYUcgPGFgbecuHzl7dP03v9pv2C93rFohlUolEolIJDLoGnBXU6rFHXsXCCHEIYQ4luPEYjG+\ncvyqsqPrLKzqbty4Ya0hPG/evGHDhuFxZr9MpEcAQNEUToYAgGqjaejh63i84Mstx5e/rFar\nVRv4p7IGCnVzk5nnLNwSfOCBoQ/fIsKKkO+AV7txe/3xIZpN1yuUaiZ9RGhzyJ2SSdAk5Obm\nqlSqHTt2aKI1rSsYHzt2TK1WZ/XP4sl5QMO4U7kalaKwagcA1cFh5D8/28NR2Xgav/ZiQ/E+\n5b67vs0r38gh06Dgc9jR3K1bt//ijAQC4UmCCDsC4ckDi5t6PTNnbN3a7yMKcjQymUwkEolE\nIr22ji8Q0rgsR6sgOwBojq4DAIQ4jrtdkicUCgGAZVnNlo78UQGvvKjC8+bMmTNyZLPWwXFs\nAMBz4gWlBFFCCgBOlze+qinEExYEuz/byRmP9xuLkhllva6WQx1sJV36KjTyAubfefyIZEY5\nU6GZ7O/U+1DmrM4uMzWKrKeycLXhgwcPxsbGKpXKjHcznvvjOWWq0n21+/fff8/pOa6JU2gU\n4WpmvK8jAOSWJ/yHmbAA8EfhqzEKTdS5qEkdJt31lYXV3qzaFKPQrF69GgB27Ggj9o5AIBDu\nggg7AuGJxFrirpf38sv5+8VisVAoFAgE5YXZrp4dW9ywAHDHbodadB0gsFhMZqPOKuwsFsua\nNWtefvnl4cOHAwDiENOHwZmalPiOfa5Iaxp7rNk+tyikwzMdnfCyp68NNbHVAMCyuhjFlaRu\ni4IdF9e71WsztMM85IlFtT42A8vrj7nLhzy6x7+QljsZx8bhKndb8qrOnQ4tX1/OKJnQ86Gt\nq9zNeG/Gz+N/puRUVlSWQqP4vUaHAJaGeSQzysiAPQ93AB5FIYSsfm6dTieVSh90kYLKHyiK\nDwBGzvh6p9fv+vbUtQExCo3ZbE5NTSWhdQQCoZ2Q5AkC4QkmJbP3pW2dbG1tpVKpWCwWCAQ8\nHo/H4/EFQpFYBnCniysAtKRPIF1TA8eyLMs6yB1Ky0uNRmNTU5PRgha9vznv2Tx9lh4AePa8\noEPN9rmTZQ1vXCzCSywO7TDB3wmPNfkz6nS/AwCPlkQHHhbwbBYvXhwdHd2jR49ly5bt2LGD\niWT8zwSrUnJODgtpf4JC+6lr+l1zc4ay43f20m5KNQMAGpXCUmvJfjrbdZar60zX8ePHGwwG\nADiYeDDsu7Ce1T23L9mOI/MuFy6saTw3WHHhQTfNLvtUKvTeVtIvSC4ecIozFZuy+2bn5ubO\nnj37QZfC7yTybOQcnznTvaff9VWwx3JPx9EqlSoxMZHUIiYQCO2EWOwIhCeYwaHpWeIXsBNW\nKBTy+Xwej0fTNAXIbGxqUQN30icAACHE5/EQTfN4vMamRplUhhCyWCxGYwOjZPj2fKt9Lrte\nP/VYHr5/YbD71E7OAICA+y07xmypAwA+z/YurfbJJ59gI1ldXR0AgAVkAl6jhfuXHt9e1h1b\nLm3FgRrVzomncpVq5sLI5pC7ys2Vv6T/EhkZ6ezsrCvT7dmw5/mE52VJIZtDTgNAdWPqwwnN\nzq7zTucMebvbJKWaiX9OwUQwg98evHbt2gcVdtdufUxTIgCwIMtdqi4lsw9NSbGqIx0mCATC\nA0GEHYHwZCMSiax+WCzs7sqcaO2KtQ4wtjI7uokqg3KWZSUSCZZ0KaX1Sy4V45krunnGejdn\nfV7Im96gzwQAHi0ZEPwb/6/7mf6Pwdouhem9Z0B6Vp0+IilzQ6SfUqNglEyiY2IXVZd169bF\nKmNfXPniDFf1G/Uj1pQOc9FBv8AjD7cdjydhOf2dzw+rWm/V/ozNdSs6r2h9Pad8LULmwYrz\no0aNsre3Jx0mCATCA0GEHYHwBLNn8ydY0mGwH5ZqRZuxFlZhZ4Nk1bwqaBQLhXqBQBCeeBVR\nFPwpfo5NzRllMJdBS7GV//EDtpMYhea3a4Nbh9wF2Iq2nw9M90tfnLX41tO3tsZvnfvj3Gub\nfmg4dXFhWsic0qLfgySi/+7AVwuX8igJAFiQJdbtTscLC6cvrtoZo9B89NFHCCGSMEEgEB4U\nIuwIhCeY+ooiG5kEqzo+n8/n8621TgDAVuCgNdQ1Nelk8jtx/ail+wRCqDivEhx1IqGMEwiF\nQuGqEPmQTj54WtqNKVrDdQDg0dIHss8tX7583rx5AGA2m3m2PM7YbNESCdybjAUykd8je/g/\n0z84pbjqp2RGOSD4FNZ2Ll8mVRVOr95UXfR6kf8m//Lo1X5fLVapVAtXS1cqS/un9Z/hPWO2\n7wMHxj0Sbjcmxyg0vc/2Xhe6rvX1U1n9YhQarVZ79uxZkjBBIBAeAvrvpxAIhMcVmkKCVvBb\nEAgEIqHI0NBEa/kyiYzfitYz7ToJqWonCngSkUwgEBz//O2fUgbhZFszWxej0MQoNANDTj+Q\n1zUyMrKgoGDx4sVffvml2ytuJe+V/NCv0/Dj17r5rMm6tfLfexUA4O08IUahOXVtQH7Ft+4b\nltoJ+ZFHsiu/qwxvCj/zTM5znxlSDh+SOV9PWOpux7fTRGs2F2/uf77/w+3FcgY3saDKYKbE\nFELIw8MjJyennfdeLpgnFnQAABaxUQ5R1uvJjDKwwxsAMGnSJKLqCATCw0GEHYHwBMP/M1bF\nxuPx+MCnpFCnrbWztxUKRdY5zWmzLdgGsCJXFlEsn8+Xyy1fripKWOqasNT949do3G/+4ejX\nr19KSorjaMeGYw0hckmlkbWTBNbrrjzCZ/8rYhSa7JIvhz57vuhl1YRdlqmvWHQWdvknwgFa\n8fmwXxa+1X3NmjUqlSo3N1cTrWlim8JTwx90i3D/7y8XzF+i6LDyyq2O33fMis5atWoV7mzR\nHqq1adGBiRFnI3Z0v+NpPZEZLeDJvZ0mqlSqjz/++EGPRCAQCBgi7AiEJxirUGsNVmxGs+l2\neaWZNrF6oCi469tm8dfqdj6fHzNkyukTN9TqQ2q1+vnnn7969aqqhVGjRmVlZbXzVHZ2duXl\n5f/qg9+fr1f4hIR2PvJb9xHX+elTurrsvjTV3yko3Y+z0dpOXhEYGKhWqxctWrRkyRJNtCbU\nNlSZqmQR2/715bKudbrLT7nbnavQSrpIkBG5uLgUFha25970G1Ptpb0QIA5xQTZB+GJu+Vcc\nMvQPTlGpVM7OzqGhoQ/z2AQCgUBi7AiEJxqRWNZaq7WOsbOxFXBNFqFMAoAEAoH1Fhxjx3Ec\nTdMcx+FgO3yj6G1XRs9QNGU7yHbc6nHjxo3Dt9TU1Lz//vuLFy+2LhIaGnofq9K2bdvGjh37\nrz303xAbGztkyJDBoQuOfz6+fOtz757Z1ctJtuNm9XfZJ66ce7bm51pGySgyFLiCcVxc3IED\nB/Ka8nqf7b256+budt3/vYNxHEdRAIju6fvl/D9eTg4/xlrMAIDA3NiUNSAobfv2baEhIas+\nXMVxLMchCnAFZASA02CaE2JoikJ39xQhEAiEZoiwIxCeYNw7hukq81r7YSmKwtpO32Bw8HIs\nuFbUUeFv1QCtK55wHMeyLEVRHMdhddjtt140TVduqbz97W1G2dwKjJbQvut9165da9300KFD\nW7duVama+49RFPXOO+8olUrrBIFA8F9VPr969SrHcQsWLGCUTL8fdxi9iq/Vx03pteVy4cuv\n5LwXnpSlmaBwjHNkwhnXWa5qtXratGm48J4mWqNMVYbZhm3ptuXfOBh+Ib8XvuZqN8TMWTzF\nnjY8GQIOAHLK1oX5rNFqG2prald9+AEA4lgWQUtbC4SAojgOSzwKgOaApomqIxAIfwERdgTC\nE0z3vsPS1RusRjs8wHYdobMwMyPX2MgKhYK77sKqDiGEJSDLsvje3vt/H9XRbcXzni7Pu+CZ\nllpL/oz8mzNvNt9Jgay3bMSXI0aMGIEvNDY2vv/++++++6518Y4dO+JoM7lcfvXqVXmMvP5o\nfR9n2cnyBm+nKbnlX3R2n//vvZBly5ap1eqiN4qAAnFncbTaeG4Ec5Lpqjfdyhw3cubZfNx2\nAlcwrtpetf309qSkJJVK9csvv2BtF3E24kLUA7ejaB8IOJ63Y/yukl2L/F7hWA4AyuoSvRzi\nEUKpqadnzZ7FcdgjTCHEUUABRQFwgCiEgKIAEEXTFNXyiUAgEO6FtBQjEJ5UEEIVFRWZp3bY\n2NhIpVKRSGTtPAEA+N82sXpgLRaLxWIxGAw6na6hoSEnZPz2Uj3X8ivBRcz/sId3D6c7KbFV\nu6tuf3EbGZtnUCLK51Mf27621gkpKSmbN29ubGysrq62WCxarXbDmg2ua1yDU4Kxokpheg9W\npP8bbwMAVCoVbnfLKBmFRhGhvuouER0c3CWZabYmxig0WXW6Z1Pzv4jw6+Nqk9knE5mRQqMw\nmUxjx46dNGnS1KlTB6cPrjfXa6L/pmLfmezhYT6rV2U5qLwcvJdXurzgsu3SNhcXl4kTJ94z\nFwFQHMdp8mf6OE6Wy/qk1ZyLtO9LU6hel0UBbSsNysnJ8fLykkplNA2AABAgisJWPooCxCGK\nooCiKKBomqZoHk3TNM0DAOygffSvkkAgPLEQYUcgPKkghAoLC/PT99rZ2clkMqFQKBQKcSYE\ntAi7u/7qW0sTA4DFYmFZ1mw2GwyGpqamirqayKEznZ2d8UytmY09kdNgbq5CRwEM7iBf3cvb\nuhSn4/JfyDfcMEDLDIlC0mlLJ+uEkSNHlpaWenp6zjgzY3O/zWcGzxjPJE5e9Me/VOV47969\nW7ZsUavVjJIJPB7YJKNijmVrVIpkJtzXeVpn9wUnMqM4ZIxRaBBC4UmZbmJBUkxgwdwC7QUt\nbrmhUqmEQuGvv/66rWTbFwVfZERl3EczIYROZkV3C/htyukbR58OYsKZ0AuhY8eO3bdv31/M\n5zR5c7v7rDtRmTzMS6VQhGq1jQUFRU1NdWVl5SNHxgqFwqtXmc2bNj4zZZLUxn7Ld5vybuav\nWrW6sbFWJpOHKRRAQcaFNJrHo2keTfMoiqS+EQiENiCuWALhSQUhZDabM8tQHzvAoXXWRNfW\nqg7/2zq6DgBYtjkJ1GKx4MHxaxubPHY7OgsoCmQi3xCvd08MDbPutetmdUJmmVJdjz86ivgr\nu3tF7r7T7ar2YG3ZJ2XWyDxKSHF8ztPTEysttVod+GOaQWO4cSM3YakKAGianjdv3pAhQx7V\n28CqLntENi2hBQ6CGDWjUSlu1R4EQJ3dFwDAoNCzxdV7khlldJckXMFYqWY0XysMuQZGyfis\n9cHpFDjkbqz72PCz4TO9Z87yndXmdhRFccjoJOJXGy0AAAgoijKbzX9xOnT2elyA+2tmZJHw\nJABwIf2shTXwaPHZ1PNdu4alpv4mlUgoCqQy+8lTJiGE4ieMB4DBgwYBQgCQlpZK0RQCxHEc\nRdEIIYS4+xhlCQTC/7cQYUcgPKlgMaczNks0HDCHVd29HWMxrS12AMCyLBYHHMeFeC8bGDrG\n1dWVQ+YUJioj73nrPh72cVP8l0/xd8KfLRwanpw9L72g+WuASGfbL2J9HWKbu8oiFuVNzzOf\nN+tv6Rklo8/WX4+/bjvdZufOncmMUq1Wsyz7wQcfrF+/3lr7zdbW9scff3zoV6FSqT777DPg\nwFJhUWgU4Wqmu70EAK7dWtnaQOjtNNHLMT4lM8JdPlSjWhV9KLN1yJ3AQ6BWq2fNmtU6neL7\nku/Tox6B75hDyFkWvaXou2keUwHAwhr5PPGaz9e9smAey7IsawGA5h8LQgAwf8GiL79IiIho\nrrFnJ3eSSCQVFaX4J4oQ8HjEA0sgENqACDsC4QlGLBZLpdJTl4qGRAZgW53FYrHmxsJfuGI5\njuM4DgfYmUwms9k8ecEnH3zwgVAoBACaEjwddid7oKDyhxu315fW7W/eUeAR6rXi+JA7ObD7\ni2o/ulqqVDfb6uQC3vKuHgN3BCTqE5VKZeD5wCxFlqXcIr5oSP7sqmm6+Orsi15LOr7zzjvW\nFTQazfr1661ptjRNv/jii3Fxce18CXipoKAgRsmEXghlanUIYHN0p2RG2c137V2TKYqOUWiS\nGWVFw6nUEWd351cp1cyRpwOxtmPCmY0ZG3NyclQq1YoVKzTRmt6pvZWpyr8Nubs/pzKfCvF6\n34xMAM2prnZ2bgCwYsVyHp9vYVlnFw88s6mpDhDotHVVNTXBIWGFhUVN2rpfft49fPiwxgat\nWp0UOyoWAdAUCaEhEAhtQ2LsCIQnmLq6usOHD6elpT0zJEQmk0kkEqFQiOueYANea2+d1VzH\nsqzFYjGbzUaj0WAw1NY3fvDNgbq6ulOnTkkkkvvvmMJEITBaP7rZDQvzeb9FrgAAqJJzyg3N\nHsmaFS906j/01+eXlr5ZYtru/WV2xWfdjWePTPf6cDO0/OLhd+AH7g+kWtmfVq9enZqaav0o\nFAp//vlnHDjYJtjAltknk2fPCzochI1wOWVri6t3xSgy/vJBMiMQ4rA9T6lmRnnZv9Pdi+nN\nAAvWkDuZTLZnz57pf0zPbMy8V9sdvxr+dFgG3i5rQFbQ0aDYcbFttgI7mRnVP/j0wsyFnwV9\nWt2Q7uE8QKetM5rMAwYOPnf2tNFo5DhOIpFSNAWAEAdUyy/m4JCu17Ka23VQFCWzsdfrtTye\ngEfR6M8/XAKBQMAQYUcgPMEYjcaMjIyjR49WVlbOHK2USCQSicTaWIy652//XbY6nA8btWrv\nylEDJRLJ0aNHDx061P7dS6r3ZpethhaNJha4BXksc7aNtk7oN2R4qc7osHT9koX6jxMk1+v1\ne/p3FtTFWN2jjamNxW8Vc00tKRo8yv1Vd6eJTtYVrly5snbt2srKyuYJFDVlypTJkydbJ6hU\nqp07d8o4WfbT2dgJO7OLy0td3JIZ5d9maVwtXn67/ohV20l59OnhITW/1pR+WNolsYuwgxAb\nEdVqdWZj5vQ/pq8JXtPf6U5v2ZyyT2lKklk9In3FPD5N082VSBBCiOW4uWu+9PT1B4BkJrKX\n/1cNlPMnuR8v945HyOTpPKykKF8gEnp7d6ytqTSZTBzHSiRSiqKAAsQhqcyuqameApDK5E3a\nepmNvKmpftu27c9MmSyRSCmapmkcRkm8sQQC4W6IsCMQnmAQQiUlJUeOHLl69arJZHppTLhE\nIrHWPcHxdlZvLK5ywrIsy7JY1en1+u8OXkoqbax26FC0Zml2dvbq1asfuv38b9eGmNka60cX\n20FbEwwXL/5++vRpXH/E6ceL/rai6Q4TttX+BAAKe+mGPn5i3h3pWfBKgfac1mrM47nyAn8J\npKV3Jqxbty4lJYXjmoVgYWGhn59fYmIiXj/1dsPCjCKNSpHMKPsFHRLxXf/2zEZLzZnsIb38\nNzvIukcmZVoQ0qgUAMAoGfvR9l7LvSZNmqTVavE7UaYqvcRetbBEsgAAIABJREFU+5XNXmmj\nQf/BtHihUMjn80ViiWdAF++g4Fu514uvXzPq9Vg6L9vy47mCQTGKjBHpww/22p9bvq6Ty/zX\nXn9jzuyZ/v4dAaj167+Y+/JsCiiBQIgtdRQAh7hevcJdnF2OHE3Ce3Xs2OXYkcNdggLpZkhW\nLIFAaBsi7AiEJxu9Xn/58uVTp07dunWLR1PTR3YXiUTYIds6PdYaXYdLnGBh9/7WlRTPPCjy\nzdPygORKfcnsoZmZmR988MFDazsr5XVHmZLlAGj2mMoN+1xkE9/qdN5uxGk3rLpiFJoztxvf\n0BRZWn7/SHn0wmD3sX6O1hW0Gm3x4mK2oaWFKw2uc1xdn7+j1bKysiZMmODn5/dC6guFjoUn\nQk9cGfta4fMDMvJeaDBcGxx6vv2nTWaUMlGnPp33vH25+PCt+rQRIXyaZpQMJaRCz4UeOnTo\n66+/3r17t42NjTJVSVP0hagLH8yYxum0YrH4tU078CJW65n1V+pnM6eajEbEF8SsfWXljZXv\n2jv19N+sa9KdO3t20KDBdwIgKQAAmubhynUIL4CAQ1yrCEkaV7KjKB6Ppqlmcx0iRjsCgXAX\nRNgRCE82CKHq6ur09PSMjIzKykqWZV8Y1cMaaYfTY/FMrOpwdJ1Ob9h++IpAIADJxY4hNTPG\nZSz6o+LnjKunB/lLpdJFixb9c22HCQwMzMnJSVMc0P74/pzsJd8Ef9ygv+bv8qLC+0MBz8Y6\nbcbZ/N9rddaPQXLJ15F+doI7cXXFbxY3JDeglurJfGf+a/Ba0pEkU4np+ujrCo3Cb+spr3P7\n7EvzVDPOqDf34/P53333nZPTHa/u/UlmwgFQjELTYLIMOpb9VW+/3i421pA7lmXj4uLi4uJm\nzpw56PygvmskUqk0fuFiVx8/6+tt1bfNOkBGXdPmtxcbjcaBKxpCPVc6yPqsW7d2wfwFFAUc\nau4GS1EUoOaeEgCAOA4oCvC/VpWIKKABgKbuQCx2BAKhDYiwIxCeeFiWvX37tkajuXLlSkVF\nhclkkttKx/bvgo12dwk7s9m87dAfAJRYLPbw8OjVq5e7X1WJ9pMhXTUfXrn1cUrGOyh//Pjx\nc+fOPXjw4D8Pz+/Zs+cXX3zh8YOH01SnDfZauZAfLf2moGqLSNBcCVnAk3fp8GoH+5HWWzRV\n2vnpheaWX01iHjU30H1KxzsSTcfoJoybYINsltst11/TS0IluxeIjtgbsTmwf/DJW8XVq1ev\nLikpwfMpihoyZMj8+X/Tyiw1J85gvmUNuetkK97TP6BkRUndoTprOoVUKlWIOCGPFxIRqRyq\nulNRpuV/zSCEWrJVMs+evvxbioUzL/v+p3nzXn711Vd9fX0BEEVRVosb1nfQbMRDAMBxiAIA\noLABj8LdxYAGaKOKDYFAIFghwo5A+L+AxWKpqqrKyspiGKa0tLSpqclisWBhEa7ws5UKKuv0\nTO4tAKBpWiAQ2Nra+vj4hIWFBQYG2tvbm9nqMznDnwo69kWOceWx9FEXf9m6devo0aP37t0r\nEon+ycGSkpJWrVp17tw5HAYXmZR5bkTQicze1syG9Lxpjfpr1vmOsgiF9yoh38F6ZeGFgtQK\nrfVjJ1vx2u7uLz0zCZc+dhzviCzoaVHpT3skBQufBQp12rqr07ZOQg+h9Zbt27f/+uuv1urB\nPB7v66+/9vT0vPe0t+uPXy1eFh2YJBa44QIuGpXCXGbOGZXj962fTU+bqaNHhTnIJBLJ8Bfn\n0DRFUzS0klkU9SdzHSDEIY7j0OHvvjEYDFcr6/nOblu2bPkn75NAIBDuDxF2BML/ETiOa2ho\nKC4u/n/t3Xl4VdW9//G1pzNmOIQkZIAQIISEBEQBxYKIGrVCVMCC1VprKxWt1jqDtvVeBxC0\n1x/X1mu9dcLirWilWnGooDggouJQSMKQkIQhkAkynXnY6/fHDsdcqhZs0Nvd9+vJ47NP3Gfn\n7JOH83zyXWt9V11d3Z49ew4cOBAMBmOxmLXUwFoh63A4vF5vVlbW0KFDi4qK8vLyvF6vlUtM\nGX+jetLYgqXvdBz/o1Vvn7rusRUrVlx88cUvvPDCl7QaORLWaKwV7KzmIF+0ZLUj8PHHDVdK\n0bs2QldTRgy6ZsjA7yRPqOkMzdtQ37L4pwNuWTb2fXP6M7HOl4b+dkfrM6cWFXjMN7dOneJa\n33hNY7y9dzsNRVUy5mTk3pybvEJTU9M999zT2NjYe4KiTJ48eeHChckTpIy/Xj1pUNqZYwru\nOe3Vmp64uamyXEpZPbHaUeB4LvUXVluZSZWz1D5doA+roEn5WXMZ0zQ3vrgqFAoFg8GFT6z8\nR95JAPi7CHaAfUgpo9Fod3d3W1tbS0vLwYMHu7u7rTZpmqa5XK60tLSsrKzs7OysrKyUlBTD\nMA67wtqqCbm+c/erP7vgmTenrH3k+T/9adasWda6ga/8qo482B3m48afHPR/1irZ5xlXPmTR\nd2ZdXlRUtGzZsqoJVU//Lv2321rDCbPE5/7BgLlvRl/4zxOHDvZ+Vqvbf//+AysPiOQCjHR1\n+O+Gu4a7kic8++yzTz/9dCTS25lPVdX777+/qKhobdUERWhnlL+/atfBxVv2rT5jVI7bWHzx\nRZ40h7Utb9mUU1VFVVRFUVRrDPV/vXQphRCmNK2SXfW7b0Wj0UAg4Pf7f7Hiua/6RgLA38fO\nE4B9KIridDozMzN9Pl9BQUEoFIpEIlbRzirXud1ul8vlcDj6zr3ry9qVwWVs2njZM5NVbdas\nWatWrZo9e/ZTTz2Vnp7+Nd/OCYX/lTzuCW1/f+f3V7727a5gd+W85g2j/zjw7sRd4+a+2tS1\nqbJ8Xc0pujHhD7WRmet2WOcbqnLxsIE/vSE394becl10b7R+fn3d3LreKyrCN8M359/nzJkz\nx/pGW1vb4sWLr7vuOiGEEDmV89Y37cu99Kz90wf7prxSMy0nNcejWu+e0+ls/GRT/qjRVjeZ\nvm/k5k9S/eHQhPEphtFpFeyatm+1hrOtRjPH9i0D8C+Pih1gW9a/7mTXt8/dZOxzra2aIITI\nG/z2mc++e/wL/7l69erKysoHH3xw6NChX+FlTJ8+XVXVXyV+Nfyx4dM373zlzFHv1543Zsg9\n6Z4xR3spa5OJ5v/XvPvxT7v/5xdXbV3wYMm9iogHo3vOLP/E4xySPPOeLfue2/VZU718j+P+\niQUjUj+r1bX8tqV9ebuM9X4AqqnqsAeHuUd/tvHGiy++uGXPwoy8va8unxyPqdrwsopEW0pK\nitPpdDqdVpvA9OwcxWpD0udFBgP6hveyzzijSUrZ1drct3Gg3+/PLBp10fULjvbGAeAIEewA\nfA6r/UfZ8A2n//njESvufvHFF88999wlS5aUl5cf7aWqq6u/+93vbly+sfWR1tDinJ9+0Lim\nYsS7teefMuqVo7rOueeee8EFF1x22WXWqO70tdtiplxzVumaLccpilMcmpmnKs7CrMuGZ/84\n+cT9wdh33twRSbZKUZRZBQMWjMlLnhBri9XPq4819a6uEIpIm5ZWcF+BECISO/DO9rNzvVe9\nunhdamqqx+NxuVzWxh69m7Zpmss9yJRdiYSiaVJR0t7fuKu93THjnIxQ6GDf3oFWR+ju7u5k\n6zsA6HcMxQL4HBXlH67ffl51/bc2zN54unvRjPNnLn/88R/+8Ie33377iSeeeFSX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Va4o6qEnSevPUUVRFUWYicQdd94RiUR1Xfelp19/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\nrkJggg=="},"metadata":{"image/png":{"width":420,"height":420}}}]},{"metadata":{},"cell_type":"markdown","source":"### 4.4 Gene Enrichment Analysis"},{"metadata":{"trusted":true},"cell_type":"code","source":"dbs <- listEnrichrDbs()\nhead(dbs)\n#print(dbs)","execution_count":10,"outputs":[{"output_type":"display_data","data":{"text/html":"<table>\n<caption>A data.frame: 6 × 5</caption>\n<thead>\n\t<tr><th></th><th scope=col>geneCoverage</th><th scope=col>genesPerTerm</th><th scope=col>libraryName</th><th scope=col>link</th><th scope=col>numTerms</th></tr>\n\t<tr><th></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><chr></th><th scope=col><chr></th><th scope=col><dbl></th></tr>\n</thead>\n<tbody>\n\t<tr><th scope=row>1</th><td>13362</td><td> 275</td><td>Genome_Browser_PWMs </td><td>http://hgdownload.cse.ucsc.edu/goldenPath/hg18/database/</td><td>615</td></tr>\n\t<tr><th scope=row>2</th><td>27884</td><td>1284</td><td>TRANSFAC_and_JASPAR_PWMs </td><td>http://jaspar.genereg.net/html/DOWNLOAD/ </td><td>326</td></tr>\n\t<tr><th scope=row>3</th><td> 6002</td><td> 77</td><td>Transcription_Factor_PPIs </td><td> </td><td>290</td></tr>\n\t<tr><th scope=row>4</th><td>47172</td><td>1370</td><td>ChEA_2013 </td><td>http://amp.pharm.mssm.edu/lib/cheadownload.jsp </td><td>353</td></tr>\n\t<tr><th scope=row>5</th><td>47107</td><td> 509</td><td>Drug_Perturbations_from_GEO_2014</td><td>http://www.ncbi.nlm.nih.gov/geo/ </td><td>701</td></tr>\n\t<tr><th scope=row>6</th><td>21493</td><td>3713</td><td>ENCODE_TF_ChIP-seq_2014 </td><td>http://genome.ucsc.edu/ENCODE/downloads.html </td><td>498</td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 6 × 5\n\n| <!--/--> | geneCoverage <dbl> | genesPerTerm <dbl> | libraryName <chr> | link <chr> | numTerms <dbl> |\n|---|---|---|---|---|---|\n| 1 | 13362 | 275 | Genome_Browser_PWMs | http://hgdownload.cse.ucsc.edu/goldenPath/hg18/database/ | 615 |\n| 2 | 27884 | 1284 | TRANSFAC_and_JASPAR_PWMs | http://jaspar.genereg.net/html/DOWNLOAD/ | 326 |\n| 3 | 6002 | 77 | Transcription_Factor_PPIs | <!----> | 290 |\n| 4 | 47172 | 1370 | ChEA_2013 | http://amp.pharm.mssm.edu/lib/cheadownload.jsp | 353 |\n| 5 | 47107 | 509 | Drug_Perturbations_from_GEO_2014 | http://www.ncbi.nlm.nih.gov/geo/ | 701 |\n| 6 | 21493 | 3713 | ENCODE_TF_ChIP-seq_2014 | http://genome.ucsc.edu/ENCODE/downloads.html | 498 |\n\n","text/latex":"A data.frame: 6 × 5\n\\begin{tabular}{r|lllll}\n & geneCoverage & genesPerTerm & libraryName & link & numTerms\\\\\n & <dbl> & <dbl> & <chr> & <chr> & <dbl>\\\\\n\\hline\n\t1 & 13362 & 275 & Genome\\_Browser\\_PWMs & http://hgdownload.cse.ucsc.edu/goldenPath/hg18/database/ & 615\\\\\n\t2 & 27884 & 1284 & TRANSFAC\\_and\\_JASPAR\\_PWMs & http://jaspar.genereg.net/html/DOWNLOAD/ & 326\\\\\n\t3 & 6002 & 77 & Transcription\\_Factor\\_PPIs & & 290\\\\\n\t4 & 47172 & 1370 & ChEA\\_2013 & http://amp.pharm.mssm.edu/lib/cheadownload.jsp & 353\\\\\n\t5 & 47107 & 509 & Drug\\_Perturbations\\_from\\_GEO\\_2014 & http://www.ncbi.nlm.nih.gov/geo/ & 701\\\\\n\t6 & 21493 & 3713 & ENCODE\\_TF\\_ChIP-seq\\_2014 & http://genome.ucsc.edu/ENCODE/downloads.html & 498\\\\\n\\end{tabular}\n","text/plain":" geneCoverage genesPerTerm libraryName \n1 13362 275 Genome_Browser_PWMs \n2 27884 1284 TRANSFAC_and_JASPAR_PWMs \n3 6002 77 Transcription_Factor_PPIs \n4 47172 1370 ChEA_2013 \n5 47107 509 Drug_Perturbations_from_GEO_2014\n6 21493 3713 ENCODE_TF_ChIP-seq_2014 \n link numTerms\n1 http://hgdownload.cse.ucsc.edu/goldenPath/hg18/database/ 615 \n2 http://jaspar.genereg.net/html/DOWNLOAD/ 326 \n3 290 \n4 http://amp.pharm.mssm.edu/lib/cheadownload.jsp 353 \n5 http://www.ncbi.nlm.nih.gov/geo/ 701 \n6 http://genome.ucsc.edu/ENCODE/downloads.html 498 "},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"############ Selecting the DEGs' table ##############\nDEGs=cdiffBinomial[[2]][1,4] # Down-regulated markers in cluster 1 \nFileName=paste0(DEGs)\n\ndata<-read.csv(file=paste0(DEGs),head=TRUE,sep=\",\")\ndata<-as.character(data[,3])\n\ndbs <- c(\"KEGG_2019_Human\",\"GO_Biological_Process_2015\")\nenriched <- enrichr(data, dbs)\nKEGG_2019_Human<-enriched[[1]][,c(1,2,3,9)]\nGO_Biological_Process_2015<-enriched[[2]][,c(1,2,3,9)]\n\nGEA<-rbind(KEGG_2019_Human,GO_Biological_Process_2015)\nGEA","execution_count":11,"outputs":[{"output_type":"stream","text":"Uploading data to Enrichr... Done.\n Querying KEGG_2019_Human... Done.\n Querying GO_Biological_Process_2015... Done.\nParsing results... Done.\n","name":"stdout"},{"output_type":"display_data","data":{"text/html":"<table>\n<caption>A data.frame: 4145 × 4</caption>\n<thead>\n\t<tr><th scope=col>Term</th><th scope=col>Overlap</th><th scope=col>P.value</th><th scope=col>Genes</th></tr>\n\t<tr><th scope=col><chr></th><th scope=col><chr></th><th scope=col><dbl></th><th scope=col><chr></th></tr>\n</thead>\n<tbody>\n\t<tr><td>Ribosome </td><td>66/153</td><td>1.195049e-43</td><td>RPL4;RPL5;RPL30;MRPS15;RPL3;RPL32;RPL31;MRPS11;RPLP1;MRPS12;RPLP0;RPL10A;RPL6;RPL7;RPS4X;RPS14;MRPL3;RPS16;RPL18A;RPL36;RPL35;MRPL9;RPS11;RPS13;RPL21;RPS7;RPS8;RPS5;RPS6;MRPS18A;RPL13A;MRPS21;RPSA;RPS3A;MRPS7;RPL37A;RPL24;RPL27;RPL26;RPL29;UBA52;RPL12;RPL11;MRPL14;MRPL15;MRPL12;MRPL13;MRPL11;RPL14;RPS3;RPL15;RPS2;RPL18;RPS27A;RPL17;RPL19;RPL41;RPL35A;RPL23A;RPS27;RPS20;RPL22L1;FAU;RPS21;RPS24;RPS23</td></tr>\n\t<tr><td>Proteasome </td><td>25/45 </td><td>9.261661e-21</td><td>PSMD14;PSMA7;PSMD8;PSMB6;PSMB7;PSMB4;PSMB5;PSMB2;PSMB3;PSMD2;PSMB1;PSMD3;PSMD1;PSMF1;ADRM1;PSMA5;PSMA6;PSMC5;PSMA3;PSMA4;PSMC3;PSMC4;PSME3;PSMC2;PSME1 </td></tr>\n\t<tr><td>Protein processing in endoplasmic reticulum</td><td>36/165</td><td>2.122271e-13</td><td>VCP;HSP90AB1;RPN2;RPN1;DERL1;HERPUD1;SEC61A1;GANAB;LMAN2;BAG1;CAPN2;UBQLN1;SEC61B;SKP1;TXNDC5;SEC31A;PDIA3;HSPA8;XBP1;SEC13;HSP90AA1;HSPA5;WFS1;SSR2;SSR3;RAD23A;HSPA2;PDIA6;EIF2S1;CKAP4;DDOST;PDIA4;DNAJA1;CANX;CALR;P4HB </td></tr>\n\t<tr><td>Huntington disease </td><td>37/193</td><td>6.230550e-12</td><td>NDUFB9;DNAH1;NDUFA11;NDUFB6;DCTN2;DCTN1;COX7A2;COX5B;COX5A;POLR2A;UQCRFS1;CYC1;POLR2H;NDUFV2;NDUFV1;AP2M1;POLR2K;TGM2;COX8A;NDUFA9;NDUFC2;COX6C;SDHA;COX6B1;SOD1;CREB3;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;VDAC1;UQCRC2;SLC25A5;SLC25A4;SLC25A6 </td></tr>\n\t<tr><td>Cell cycle </td><td>27/124</td><td>2.241324e-10</td><td>PCNA;MCM7;PRKDC;YWHAB;PKMYT1;ANAPC11;CDC20;CCNB2;CCNB1;CCND1;PTTG1;YWHAQ;MYC;BUB3;SKP1;ANAPC7;PLK1;CDC25B;CCNA2;TFDP1;CCNE2;CDK4;CDK1;MCM3;MCM4;MCM5;MCM2 </td></tr>\n\t<tr><td>Oxidative phosphorylation </td><td>28/133</td><td>2.399141e-10</td><td>NDUFB9;NDUFA11;NDUFB6;COX7A2;COX5B;COX5A;UQCRFS1;CYC1;NDUFV2;NDUFV1;ATP6V1C2;COX8A;NDUFA9;ATP6V1G1;ATP6V0B;NDUFC2;SDHA;COX6C;COX6B1;PPA2;NDUFS7;PPA1;NDUFAB1;UQCRC1;NDUFS3;NDUFS2;UQCRC2;ATP6V0C </td></tr>\n\t<tr><td>Parkinson disease </td><td>29/142</td><td>2.477250e-10</td><td>NDUFB9;NDUFA11;NDUFB6;UBE2L6;COX7A2;COX5B;COX5A;UBB;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;NDUFA9;NDUFC2;SDHA;COX6C;COX6B1;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;VDAC1;UQCRC2;SLC25A5;SLC25A4;SLC25A6 </td></tr>\n\t<tr><td>Protein export </td><td>12/23 </td><td>3.326536e-10</td><td>OXA1L;SEC61A1;SPCS1;HSPA5;SRP72;SRP54;SRPRB;SRP68;SEC61B;SRP14;SEC11A;SRP9 </td></tr>\n\t<tr><td>Alzheimer disease </td><td>30/171</td><td>5.527120e-09</td><td>NDUFB9;NDUFA11;NDUFB6;COX7A2;ITPR3;COX5B;COX5A;NCSTN;CAPN2;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;PSENEN;NDUFA9;NDUFC2;SDHA;COX6C;COX6B1;TNFRSF1A;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;UQCRC2;CALM2;GAPDH </td></tr>\n\t<tr><td>Non-alcoholic fatty liver disease (NAFLD) </td><td>26/149</td><td>6.371987e-08</td><td>NDUFB9;NDUFA11;NDUFB6;COX7A2;COX5B;COX5A;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;NDUFA9;XBP1;NDUFC2;SDHA;COX6C;EIF2S1;COX6B1;TNFRSF1A;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;UQCRC2 </td></tr>\n\t<tr><td>RNA transport </td><td>26/165</td><td>5.115286e-07</td><td>EIF4A1;EIF4A3;TPR;NUP62;EIF4EBP1;SAP18;RAE1;EIF4B;PRMT5;SEC13;NUP133;NCBP2;RANGAP1;EIF2S1;EIF1;EEF1A1;EIF5;CLNS1A;EIF3I;STRAP;EIF3H;EIF3E;EIF3F;EIF3D;RAN;EIF4G1 </td></tr>\n\t<tr><td>Oocyte meiosis </td><td>21/125</td><td>2.185197e-06</td><td>ANAPC7;YWHAB;PLK1;ITPR3;PPP2R5D;PKMYT1;ANAPC11;AURKA;PPP1CA;CDC20;PPP1CB;PPP2CA;CCNB2;CCNB1;PTTG1;CCNE2;YWHAQ;PPP2R1A;CDK1;CALM2;SKP1 </td></tr>\n\t<tr><td>Thermogenesis </td><td>29/231</td><td>1.278000e-05</td><td>NDUFB9;NDUFA11;NDUFB6;COX7A2;COX5B;COX5A;ACTB;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;NDUFA9;ACTL6A;RPS6;NDUFC2;COX6C;SDHA;SMARCA4;COX6B1;CREB3;NDUFS7;NDUFAB1;UQCRC1;GNAS;NDUFS3;NDUFS2;UQCRC2;FGFR1 </td></tr>\n\t<tr><td>Epstein-Barr virus infection </td><td>26/201</td><td>2.089389e-05</td><td>PSMD14;PSMD8;CCND1;MYC;PSMD2;PSMD3;PSMD1;PDIA3;STAT1;DDX58;ADRM1;ISG15;CCNA2;PSMC5;PSMC3;CCNE2;OAS1;PSMC4;CDK4;OAS3;PSMC2;CYCS;CALR;VIM;CD44;IRF9 </td></tr>\n\t<tr><td>Hepatitis C </td><td>21/155</td><td>6.423047e-05</td><td>YWHAB;DDX58;STAT1;MX1;EIF2S1;EGFR;TNFRSF1A;PPP2CA;CCND1;YWHAQ;OAS1;PPP2R1A;CDK4;MYC;PSME3;OAS3;CLDN7;IFIT1B;CYCS;EIF3E;IRF9 </td></tr>\n\t<tr><td>DNA replication </td><td>9/36 </td><td>7.730573e-05</td><td>POLD4;FEN1;PCNA;MCM7;POLD2;MCM3;MCM4;MCM5;MCM2 </td></tr>\n\t<tr><td>Human T-cell leukemia virus 1 infection </td><td>26/219</td><td>9.099964e-05</td><td>NRP1;ANAPC11;CDC20;CCNB2;CCND1;PTTG1;MYC;TSPO;BUB3;RANBP1;FDPS;ANAPC7;TNFRSF1A;FOSL1;CCNA2;CREB3;CCNE2;CDK4;CANX;VDAC1;CALR;LTBR;SLC25A5;SLC25A4;RAN;SLC25A6 </td></tr>\n\t<tr><td>Cellular senescence </td><td>21/160</td><td>1.021684e-04</td><td>IGFBP3;ITPR3;PPP1CA;PPP1CB;CCNA2;CCNB2;CCNB1;CCND1;CCNE2;RBBP4;CDK4;MYC;CAPN2;EIF4EBP1;CDK1;VDAC1;SLC25A5;SQSTM1;CALM2;SLC25A4;SLC25A6 </td></tr>\n\t<tr><td>Pathogenic Escherichia coli infection </td><td>11/55 </td><td>1.146683e-04</td><td>TUBA1B;KRT18;YWHAQ;ARPC2;NCL;ARPC1A;ARPC5L;TUBB4B;ACTB;RHOA;TUBA8 </td></tr>\n\t<tr><td>Spliceosome </td><td>18/134</td><td>2.327610e-04</td><td>TCERG1;HSPA8;NCBP2;EIF4A3;SRSF1;HSPA2;LSM5;LSM4;SNRPD2;SNRPD1;PCBP1;SRSF3;SNRPA1;SNRPD3;HNRNPC;SNRNP200;SRSF7;SNRPB </td></tr>\n\t<tr><td>N-Glycan biosynthesis </td><td>10/50 </td><td>2.330233e-04</td><td>GANAB;B4GALT1;RPN2;ALG5;RPN1;SRD5A3;ALG3;MGAT1;ALG11;DDOST </td></tr>\n\t<tr><td>Vibrio cholerae infection </td><td>10/50 </td><td>2.330233e-04</td><td>SEC61A1;ATP6V1G1;ATP6V0B;GNAS;KDELR2;SEC61B;ATP6V0C;ACTB;PDIA4;ATP6V1C2 </td></tr>\n\t<tr><td>Necroptosis </td><td>20/162</td><td>3.387172e-04</td><td>RNF31;HSP90AA1;HSP90AB1;PARP1;STAT1;TNFRSF1A;SHARPIN;FTH1;CHMP2B;CAPN2;CHMP2A;CHMP3;VDAC1;RBCK1;SLC25A5;PPIA;SQSTM1;SLC25A4;IRF9;SLC25A6 </td></tr>\n\t<tr><td>Adherens junction </td><td>12/72 </td><td>3.477573e-04</td><td>CTNND1;ERBB2;RAC2;CTNNA1;LMO7;ACTN4;IQGAP1;BAIAP2;ACTB;RHOA;EGFR;FGFR1 </td></tr>\n\t<tr><td>p53 signaling pathway </td><td>12/72 </td><td>3.477573e-04</td><td>CCNB2;CCNB1;RRM2;CCND1;CCNE2;SIVA1;CDK4;IGFBP3;EI24;PERP;CDK1;CYCS </td></tr>\n\t<tr><td>Antigen processing and presentation </td><td>12/77 </td><td>6.536642e-04</td><td>PDIA3;CD74;HSPA8;HSP90AA1;HSP90AB1;HSPA5;PSME3;CANX;PSME1;HSPA2;CALR;CTSB </td></tr>\n\t<tr><td>Pyrimidine metabolism </td><td>10/57 </td><td>7.019624e-04</td><td>NME1-NME2;DTYMK;NT5E;DUT;RRM1;RRM2;TK1;TYMS;DCTPP1;NME1 </td></tr>\n\t<tr><td>Cardiac muscle contraction </td><td>12/78 </td><td>7.361984e-04</td><td>COX8A;UQCRC1;UQCRFS1;ATP1B3;COX7A2;UQCRC2;ATP1A1;CYC1;COX5B;COX6C;COX5A;COX6B1 </td></tr>\n\t<tr><td>Citrate cycle (TCA cycle) </td><td>7/30 </td><td>7.652426e-04</td><td>CS;MDH1;IDH1;IDH2;IDH3B;ACO2;SDHA </td></tr>\n\t<tr><td>Glyoxylate and dicarboxylate metabolism </td><td>7/30 </td><td>7.652426e-04</td><td>CS;GRHPR;MDH1;SHMT2;CAT;ACO2;ACAT2 </td></tr>\n\t<tr><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n\t<tr><td>epithelial tube morphogenesis (GO:0060562) </td><td>1/90 </td><td>0.9923565</td><td>TACSTD2 </td></tr>\n\t<tr><td>positive regulation of hormone secretion (GO:0046887) </td><td>1/91 </td><td>0.9927602</td><td>PSMD9 </td></tr>\n\t<tr><td>positive regulation of cyclic nucleotide metabolic process (GO:0030801) </td><td>1/91 </td><td>0.9927602</td><td>GNAS </td></tr>\n\t<tr><td>regulation of cAMP biosynthetic process (GO:0030817) </td><td>1/98 </td><td>0.9950485</td><td>GNAS </td></tr>\n\t<tr><td>detection of external stimulus (GO:0009581) </td><td>3/175 </td><td>0.9956065</td><td>FECH;SDC4;SDC1 </td></tr>\n\t<tr><td>tube morphogenesis (GO:0035239) </td><td>1/101 </td><td>0.9957925</td><td>TACSTD2 </td></tr>\n\t<tr><td>detection of abiotic stimulus (GO:0009582) </td><td>3/178 </td><td>0.9961518</td><td>FECH;SDC4;SDC1 </td></tr>\n\t<tr><td>positive regulation of secretion (GO:0051047) </td><td>6/273 </td><td>0.9965193</td><td>PSMD9;MIF;GATA3;KCNN4;PPIA;CD276 </td></tr>\n\t<tr><td>membrane depolarization (GO:0051899) </td><td>1/106 </td><td>0.9967926</td><td>CAV1 </td></tr>\n\t<tr><td>central nervous system development (GO:0007417) </td><td>1/108 </td><td>0.9971226</td><td>S100B </td></tr>\n\t<tr><td>anterior/posterior pattern specification (GO:0009952) </td><td>2/150 </td><td>0.9972471</td><td>PRKDC;ATP6AP2 </td></tr>\n\t<tr><td>regulation of cAMP metabolic process (GO:0030814) </td><td>1/113 </td><td>0.9978065</td><td>GNAS </td></tr>\n\t<tr><td>regulation of cyclic nucleotide biosynthetic process (GO:0030802) </td><td>1/116 </td><td>0.9981361</td><td>GNAS </td></tr>\n\t<tr><td>regulation of purine nucleotide biosynthetic process (GO:1900371) </td><td>1/119 </td><td>0.9984161</td><td>GNAS </td></tr>\n\t<tr><td>regulation of nucleotide biosynthetic process (GO:0030808) </td><td>1/119 </td><td>0.9984161</td><td>GNAS </td></tr>\n\t<tr><td>complement activation, classical pathway (GO:0006958) </td><td>2/162 </td><td>0.9984634</td><td>C1QBP;CD46 </td></tr>\n\t<tr><td>regulation of transmembrane transport (GO:0034762) </td><td>7/327 </td><td>0.9986252</td><td>LGALS3;CLIC3;AHNAK;S100A1;ATP1B3;ACTN4;AZIN1 </td></tr>\n\t<tr><td>adenylate cyclase-modulating G-protein coupled receptor signaling pathway (GO:0007188) </td><td>1/122 </td><td>0.9986541</td><td>GNAS </td></tr>\n\t<tr><td>cilium organization (GO:0044782) </td><td>1/125 </td><td>0.9988562</td><td>TTC17 </td></tr>\n\t<tr><td>complement activation (GO:0006956) </td><td>2/175 </td><td>0.9991867</td><td>C1QBP;CD46 </td></tr>\n\t<tr><td>regulation of cyclic nucleotide metabolic process (GO:0030799) </td><td>1/133 </td><td>0.9992587</td><td>GNAS </td></tr>\n\t<tr><td>regulation of ion transmembrane transport (GO:0034765) </td><td>6/314 </td><td>0.9992843</td><td>LGALS3;CLIC3;AHNAK;S100A1;ATP1B3;ACTN4 </td></tr>\n\t<tr><td>synaptic transmission (GO:0007268) </td><td>10/434</td><td>0.9993561</td><td>NQO1;HSPA8;SLC38A1;SYPL1;GNG5;TSPO;VDAC1;KCNN4;GABARAP;AP2M1</td></tr>\n\t<tr><td>pattern specification process (GO:0007389) </td><td>8/385 </td><td>0.9995267</td><td>NOTCH2;NRP1;PRKDC;ALG5;ATP6AP2;IFT122;BMP7;AURKA </td></tr>\n\t<tr><td>protein activation cascade (GO:0072376) </td><td>2/196 </td><td>0.9997107</td><td>C1QBP;CD46 </td></tr>\n\t<tr><td>G-protein coupled receptor signaling pathway, coupled to cyclic nucleotide second messenger (GO:0007187)</td><td>1/153 </td><td>0.9997484</td><td>GNAS </td></tr>\n\t<tr><td>regionalization (GO:0003002) </td><td>3/247 </td><td>0.9998335</td><td>PRKDC;ATP6AP2;IFT122 </td></tr>\n\t<tr><td>cellular component assembly involved in morphogenesis (GO:0010927) </td><td>1/186 </td><td>0.9999556</td><td>OFD1 </td></tr>\n\t<tr><td>detection of chemical stimulus (GO:0009593) </td><td>2/499 </td><td>0.9999954</td><td>AZGP1;PIP </td></tr>\n\t<tr><td>detection of chemical stimulus involved in sensory perception (GO:0050907) </td><td>2/465 </td><td>0.9999955</td><td>AZGP1;PIP </td></tr>\n</tbody>\n</table>\n","text/markdown":"\nA data.frame: 4145 × 4\n\n| Term <chr> | Overlap <chr> | P.value <dbl> | Genes <chr> |\n|---|---|---|---|\n| Ribosome | 66/153 | 1.195049e-43 | RPL4;RPL5;RPL30;MRPS15;RPL3;RPL32;RPL31;MRPS11;RPLP1;MRPS12;RPLP0;RPL10A;RPL6;RPL7;RPS4X;RPS14;MRPL3;RPS16;RPL18A;RPL36;RPL35;MRPL9;RPS11;RPS13;RPL21;RPS7;RPS8;RPS5;RPS6;MRPS18A;RPL13A;MRPS21;RPSA;RPS3A;MRPS7;RPL37A;RPL24;RPL27;RPL26;RPL29;UBA52;RPL12;RPL11;MRPL14;MRPL15;MRPL12;MRPL13;MRPL11;RPL14;RPS3;RPL15;RPS2;RPL18;RPS27A;RPL17;RPL19;RPL41;RPL35A;RPL23A;RPS27;RPS20;RPL22L1;FAU;RPS21;RPS24;RPS23 |\n| Proteasome | 25/45 | 9.261661e-21 | PSMD14;PSMA7;PSMD8;PSMB6;PSMB7;PSMB4;PSMB5;PSMB2;PSMB3;PSMD2;PSMB1;PSMD3;PSMD1;PSMF1;ADRM1;PSMA5;PSMA6;PSMC5;PSMA3;PSMA4;PSMC3;PSMC4;PSME3;PSMC2;PSME1 |\n| Protein processing in endoplasmic reticulum | 36/165 | 2.122271e-13 | VCP;HSP90AB1;RPN2;RPN1;DERL1;HERPUD1;SEC61A1;GANAB;LMAN2;BAG1;CAPN2;UBQLN1;SEC61B;SKP1;TXNDC5;SEC31A;PDIA3;HSPA8;XBP1;SEC13;HSP90AA1;HSPA5;WFS1;SSR2;SSR3;RAD23A;HSPA2;PDIA6;EIF2S1;CKAP4;DDOST;PDIA4;DNAJA1;CANX;CALR;P4HB |\n| Huntington disease | 37/193 | 6.230550e-12 | NDUFB9;DNAH1;NDUFA11;NDUFB6;DCTN2;DCTN1;COX7A2;COX5B;COX5A;POLR2A;UQCRFS1;CYC1;POLR2H;NDUFV2;NDUFV1;AP2M1;POLR2K;TGM2;COX8A;NDUFA9;NDUFC2;COX6C;SDHA;COX6B1;SOD1;CREB3;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;VDAC1;UQCRC2;SLC25A5;SLC25A4;SLC25A6 |\n| Cell cycle | 27/124 | 2.241324e-10 | PCNA;MCM7;PRKDC;YWHAB;PKMYT1;ANAPC11;CDC20;CCNB2;CCNB1;CCND1;PTTG1;YWHAQ;MYC;BUB3;SKP1;ANAPC7;PLK1;CDC25B;CCNA2;TFDP1;CCNE2;CDK4;CDK1;MCM3;MCM4;MCM5;MCM2 |\n| Oxidative phosphorylation | 28/133 | 2.399141e-10 | NDUFB9;NDUFA11;NDUFB6;COX7A2;COX5B;COX5A;UQCRFS1;CYC1;NDUFV2;NDUFV1;ATP6V1C2;COX8A;NDUFA9;ATP6V1G1;ATP6V0B;NDUFC2;SDHA;COX6C;COX6B1;PPA2;NDUFS7;PPA1;NDUFAB1;UQCRC1;NDUFS3;NDUFS2;UQCRC2;ATP6V0C |\n| Parkinson disease | 29/142 | 2.477250e-10 | NDUFB9;NDUFA11;NDUFB6;UBE2L6;COX7A2;COX5B;COX5A;UBB;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;NDUFA9;NDUFC2;SDHA;COX6C;COX6B1;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;VDAC1;UQCRC2;SLC25A5;SLC25A4;SLC25A6 |\n| Protein export | 12/23 | 3.326536e-10 | OXA1L;SEC61A1;SPCS1;HSPA5;SRP72;SRP54;SRPRB;SRP68;SEC61B;SRP14;SEC11A;SRP9 |\n| Alzheimer disease | 30/171 | 5.527120e-09 | NDUFB9;NDUFA11;NDUFB6;COX7A2;ITPR3;COX5B;COX5A;NCSTN;CAPN2;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;PSENEN;NDUFA9;NDUFC2;SDHA;COX6C;COX6B1;TNFRSF1A;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;UQCRC2;CALM2;GAPDH |\n| Non-alcoholic fatty liver disease (NAFLD) | 26/149 | 6.371987e-08 | NDUFB9;NDUFA11;NDUFB6;COX7A2;COX5B;COX5A;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;NDUFA9;XBP1;NDUFC2;SDHA;COX6C;EIF2S1;COX6B1;TNFRSF1A;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;UQCRC2 |\n| RNA transport | 26/165 | 5.115286e-07 | EIF4A1;EIF4A3;TPR;NUP62;EIF4EBP1;SAP18;RAE1;EIF4B;PRMT5;SEC13;NUP133;NCBP2;RANGAP1;EIF2S1;EIF1;EEF1A1;EIF5;CLNS1A;EIF3I;STRAP;EIF3H;EIF3E;EIF3F;EIF3D;RAN;EIF4G1 |\n| Oocyte meiosis | 21/125 | 2.185197e-06 | ANAPC7;YWHAB;PLK1;ITPR3;PPP2R5D;PKMYT1;ANAPC11;AURKA;PPP1CA;CDC20;PPP1CB;PPP2CA;CCNB2;CCNB1;PTTG1;CCNE2;YWHAQ;PPP2R1A;CDK1;CALM2;SKP1 |\n| Thermogenesis | 29/231 | 1.278000e-05 | NDUFB9;NDUFA11;NDUFB6;COX7A2;COX5B;COX5A;ACTB;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;NDUFA9;ACTL6A;RPS6;NDUFC2;COX6C;SDHA;SMARCA4;COX6B1;CREB3;NDUFS7;NDUFAB1;UQCRC1;GNAS;NDUFS3;NDUFS2;UQCRC2;FGFR1 |\n| Epstein-Barr virus infection | 26/201 | 2.089389e-05 | PSMD14;PSMD8;CCND1;MYC;PSMD2;PSMD3;PSMD1;PDIA3;STAT1;DDX58;ADRM1;ISG15;CCNA2;PSMC5;PSMC3;CCNE2;OAS1;PSMC4;CDK4;OAS3;PSMC2;CYCS;CALR;VIM;CD44;IRF9 |\n| Hepatitis C | 21/155 | 6.423047e-05 | YWHAB;DDX58;STAT1;MX1;EIF2S1;EGFR;TNFRSF1A;PPP2CA;CCND1;YWHAQ;OAS1;PPP2R1A;CDK4;MYC;PSME3;OAS3;CLDN7;IFIT1B;CYCS;EIF3E;IRF9 |\n| DNA replication | 9/36 | 7.730573e-05 | POLD4;FEN1;PCNA;MCM7;POLD2;MCM3;MCM4;MCM5;MCM2 |\n| Human T-cell leukemia virus 1 infection | 26/219 | 9.099964e-05 | NRP1;ANAPC11;CDC20;CCNB2;CCND1;PTTG1;MYC;TSPO;BUB3;RANBP1;FDPS;ANAPC7;TNFRSF1A;FOSL1;CCNA2;CREB3;CCNE2;CDK4;CANX;VDAC1;CALR;LTBR;SLC25A5;SLC25A4;RAN;SLC25A6 |\n| Cellular senescence | 21/160 | 1.021684e-04 | IGFBP3;ITPR3;PPP1CA;PPP1CB;CCNA2;CCNB2;CCNB1;CCND1;CCNE2;RBBP4;CDK4;MYC;CAPN2;EIF4EBP1;CDK1;VDAC1;SLC25A5;SQSTM1;CALM2;SLC25A4;SLC25A6 |\n| Pathogenic Escherichia coli infection | 11/55 | 1.146683e-04 | TUBA1B;KRT18;YWHAQ;ARPC2;NCL;ARPC1A;ARPC5L;TUBB4B;ACTB;RHOA;TUBA8 |\n| Spliceosome | 18/134 | 2.327610e-04 | TCERG1;HSPA8;NCBP2;EIF4A3;SRSF1;HSPA2;LSM5;LSM4;SNRPD2;SNRPD1;PCBP1;SRSF3;SNRPA1;SNRPD3;HNRNPC;SNRNP200;SRSF7;SNRPB |\n| N-Glycan biosynthesis | 10/50 | 2.330233e-04 | GANAB;B4GALT1;RPN2;ALG5;RPN1;SRD5A3;ALG3;MGAT1;ALG11;DDOST |\n| Vibrio cholerae infection | 10/50 | 2.330233e-04 | SEC61A1;ATP6V1G1;ATP6V0B;GNAS;KDELR2;SEC61B;ATP6V0C;ACTB;PDIA4;ATP6V1C2 |\n| Necroptosis | 20/162 | 3.387172e-04 | RNF31;HSP90AA1;HSP90AB1;PARP1;STAT1;TNFRSF1A;SHARPIN;FTH1;CHMP2B;CAPN2;CHMP2A;CHMP3;VDAC1;RBCK1;SLC25A5;PPIA;SQSTM1;SLC25A4;IRF9;SLC25A6 |\n| Adherens junction | 12/72 | 3.477573e-04 | CTNND1;ERBB2;RAC2;CTNNA1;LMO7;ACTN4;IQGAP1;BAIAP2;ACTB;RHOA;EGFR;FGFR1 |\n| p53 signaling pathway | 12/72 | 3.477573e-04 | CCNB2;CCNB1;RRM2;CCND1;CCNE2;SIVA1;CDK4;IGFBP3;EI24;PERP;CDK1;CYCS |\n| Antigen processing and presentation | 12/77 | 6.536642e-04 | PDIA3;CD74;HSPA8;HSP90AA1;HSP90AB1;HSPA5;PSME3;CANX;PSME1;HSPA2;CALR;CTSB |\n| Pyrimidine metabolism | 10/57 | 7.019624e-04 | NME1-NME2;DTYMK;NT5E;DUT;RRM1;RRM2;TK1;TYMS;DCTPP1;NME1 |\n| Cardiac muscle contraction | 12/78 | 7.361984e-04 | COX8A;UQCRC1;UQCRFS1;ATP1B3;COX7A2;UQCRC2;ATP1A1;CYC1;COX5B;COX6C;COX5A;COX6B1 |\n| Citrate cycle (TCA cycle) | 7/30 | 7.652426e-04 | CS;MDH1;IDH1;IDH2;IDH3B;ACO2;SDHA |\n| Glyoxylate and dicarboxylate metabolism | 7/30 | 7.652426e-04 | CS;GRHPR;MDH1;SHMT2;CAT;ACO2;ACAT2 |\n| ⋮ | ⋮ | ⋮ | ⋮ |\n| epithelial tube morphogenesis (GO:0060562) | 1/90 | 0.9923565 | TACSTD2 |\n| positive regulation of hormone secretion (GO:0046887) | 1/91 | 0.9927602 | PSMD9 |\n| positive regulation of cyclic nucleotide metabolic process (GO:0030801) | 1/91 | 0.9927602 | GNAS |\n| regulation of cAMP biosynthetic process (GO:0030817) | 1/98 | 0.9950485 | GNAS |\n| detection of external stimulus (GO:0009581) | 3/175 | 0.9956065 | FECH;SDC4;SDC1 |\n| tube morphogenesis (GO:0035239) | 1/101 | 0.9957925 | TACSTD2 |\n| detection of abiotic stimulus (GO:0009582) | 3/178 | 0.9961518 | FECH;SDC4;SDC1 |\n| positive regulation of secretion (GO:0051047) | 6/273 | 0.9965193 | PSMD9;MIF;GATA3;KCNN4;PPIA;CD276 |\n| membrane depolarization (GO:0051899) | 1/106 | 0.9967926 | CAV1 |\n| central nervous system development (GO:0007417) | 1/108 | 0.9971226 | S100B |\n| anterior/posterior pattern specification (GO:0009952) | 2/150 | 0.9972471 | PRKDC;ATP6AP2 |\n| regulation of cAMP metabolic process (GO:0030814) | 1/113 | 0.9978065 | GNAS |\n| regulation of cyclic nucleotide biosynthetic process (GO:0030802) | 1/116 | 0.9981361 | GNAS |\n| regulation of purine nucleotide biosynthetic process (GO:1900371) | 1/119 | 0.9984161 | GNAS |\n| regulation of nucleotide biosynthetic process (GO:0030808) | 1/119 | 0.9984161 | GNAS |\n| complement activation, classical pathway (GO:0006958) | 2/162 | 0.9984634 | C1QBP;CD46 |\n| regulation of transmembrane transport (GO:0034762) | 7/327 | 0.9986252 | LGALS3;CLIC3;AHNAK;S100A1;ATP1B3;ACTN4;AZIN1 |\n| adenylate cyclase-modulating G-protein coupled receptor signaling pathway (GO:0007188) | 1/122 | 0.9986541 | GNAS |\n| cilium organization (GO:0044782) | 1/125 | 0.9988562 | TTC17 |\n| complement activation (GO:0006956) | 2/175 | 0.9991867 | C1QBP;CD46 |\n| regulation of cyclic nucleotide metabolic process (GO:0030799) | 1/133 | 0.9992587 | GNAS |\n| regulation of ion transmembrane transport (GO:0034765) | 6/314 | 0.9992843 | LGALS3;CLIC3;AHNAK;S100A1;ATP1B3;ACTN4 |\n| synaptic transmission (GO:0007268) | 10/434 | 0.9993561 | NQO1;HSPA8;SLC38A1;SYPL1;GNG5;TSPO;VDAC1;KCNN4;GABARAP;AP2M1 |\n| pattern specification process (GO:0007389) | 8/385 | 0.9995267 | NOTCH2;NRP1;PRKDC;ALG5;ATP6AP2;IFT122;BMP7;AURKA |\n| protein activation cascade (GO:0072376) | 2/196 | 0.9997107 | C1QBP;CD46 |\n| G-protein coupled receptor signaling pathway, coupled to cyclic nucleotide second messenger (GO:0007187) | 1/153 | 0.9997484 | GNAS |\n| regionalization (GO:0003002) | 3/247 | 0.9998335 | PRKDC;ATP6AP2;IFT122 |\n| cellular component assembly involved in morphogenesis (GO:0010927) | 1/186 | 0.9999556 | OFD1 |\n| detection of chemical stimulus (GO:0009593) | 2/499 | 0.9999954 | AZGP1;PIP |\n| detection of chemical stimulus involved in sensory perception (GO:0050907) | 2/465 | 0.9999955 | AZGP1;PIP |\n\n","text/latex":"A data.frame: 4145 × 4\n\\begin{tabular}{llll}\n Term & Overlap & P.value & Genes\\\\\n <chr> & <chr> & <dbl> & <chr>\\\\\n\\hline\n\t Ribosome & 66/153 & 1.195049e-43 & RPL4;RPL5;RPL30;MRPS15;RPL3;RPL32;RPL31;MRPS11;RPLP1;MRPS12;RPLP0;RPL10A;RPL6;RPL7;RPS4X;RPS14;MRPL3;RPS16;RPL18A;RPL36;RPL35;MRPL9;RPS11;RPS13;RPL21;RPS7;RPS8;RPS5;RPS6;MRPS18A;RPL13A;MRPS21;RPSA;RPS3A;MRPS7;RPL37A;RPL24;RPL27;RPL26;RPL29;UBA52;RPL12;RPL11;MRPL14;MRPL15;MRPL12;MRPL13;MRPL11;RPL14;RPS3;RPL15;RPS2;RPL18;RPS27A;RPL17;RPL19;RPL41;RPL35A;RPL23A;RPS27;RPS20;RPL22L1;FAU;RPS21;RPS24;RPS23\\\\\n\t Proteasome & 25/45 & 9.261661e-21 & PSMD14;PSMA7;PSMD8;PSMB6;PSMB7;PSMB4;PSMB5;PSMB2;PSMB3;PSMD2;PSMB1;PSMD3;PSMD1;PSMF1;ADRM1;PSMA5;PSMA6;PSMC5;PSMA3;PSMA4;PSMC3;PSMC4;PSME3;PSMC2;PSME1 \\\\\n\t Protein processing in endoplasmic reticulum & 36/165 & 2.122271e-13 & VCP;HSP90AB1;RPN2;RPN1;DERL1;HERPUD1;SEC61A1;GANAB;LMAN2;BAG1;CAPN2;UBQLN1;SEC61B;SKP1;TXNDC5;SEC31A;PDIA3;HSPA8;XBP1;SEC13;HSP90AA1;HSPA5;WFS1;SSR2;SSR3;RAD23A;HSPA2;PDIA6;EIF2S1;CKAP4;DDOST;PDIA4;DNAJA1;CANX;CALR;P4HB \\\\\n\t Huntington disease & 37/193 & 6.230550e-12 & NDUFB9;DNAH1;NDUFA11;NDUFB6;DCTN2;DCTN1;COX7A2;COX5B;COX5A;POLR2A;UQCRFS1;CYC1;POLR2H;NDUFV2;NDUFV1;AP2M1;POLR2K;TGM2;COX8A;NDUFA9;NDUFC2;COX6C;SDHA;COX6B1;SOD1;CREB3;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;VDAC1;UQCRC2;SLC25A5;SLC25A4;SLC25A6 \\\\\n\t Cell cycle & 27/124 & 2.241324e-10 & PCNA;MCM7;PRKDC;YWHAB;PKMYT1;ANAPC11;CDC20;CCNB2;CCNB1;CCND1;PTTG1;YWHAQ;MYC;BUB3;SKP1;ANAPC7;PLK1;CDC25B;CCNA2;TFDP1;CCNE2;CDK4;CDK1;MCM3;MCM4;MCM5;MCM2 \\\\\n\t Oxidative phosphorylation & 28/133 & 2.399141e-10 & NDUFB9;NDUFA11;NDUFB6;COX7A2;COX5B;COX5A;UQCRFS1;CYC1;NDUFV2;NDUFV1;ATP6V1C2;COX8A;NDUFA9;ATP6V1G1;ATP6V0B;NDUFC2;SDHA;COX6C;COX6B1;PPA2;NDUFS7;PPA1;NDUFAB1;UQCRC1;NDUFS3;NDUFS2;UQCRC2;ATP6V0C \\\\\n\t Parkinson disease & 29/142 & 2.477250e-10 & NDUFB9;NDUFA11;NDUFB6;UBE2L6;COX7A2;COX5B;COX5A;UBB;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;NDUFA9;NDUFC2;SDHA;COX6C;COX6B1;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;VDAC1;UQCRC2;SLC25A5;SLC25A4;SLC25A6 \\\\\n\t Protein export & 12/23 & 3.326536e-10 & OXA1L;SEC61A1;SPCS1;HSPA5;SRP72;SRP54;SRPRB;SRP68;SEC61B;SRP14;SEC11A;SRP9 \\\\\n\t Alzheimer disease & 30/171 & 5.527120e-09 & NDUFB9;NDUFA11;NDUFB6;COX7A2;ITPR3;COX5B;COX5A;NCSTN;CAPN2;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;PSENEN;NDUFA9;NDUFC2;SDHA;COX6C;COX6B1;TNFRSF1A;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;UQCRC2;CALM2;GAPDH \\\\\n\t Non-alcoholic fatty liver disease (NAFLD) & 26/149 & 6.371987e-08 & NDUFB9;NDUFA11;NDUFB6;COX7A2;COX5B;COX5A;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;NDUFA9;XBP1;NDUFC2;SDHA;COX6C;EIF2S1;COX6B1;TNFRSF1A;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;UQCRC2 \\\\\n\t RNA transport & 26/165 & 5.115286e-07 & EIF4A1;EIF4A3;TPR;NUP62;EIF4EBP1;SAP18;RAE1;EIF4B;PRMT5;SEC13;NUP133;NCBP2;RANGAP1;EIF2S1;EIF1;EEF1A1;EIF5;CLNS1A;EIF3I;STRAP;EIF3H;EIF3E;EIF3F;EIF3D;RAN;EIF4G1 \\\\\n\t Oocyte meiosis & 21/125 & 2.185197e-06 & ANAPC7;YWHAB;PLK1;ITPR3;PPP2R5D;PKMYT1;ANAPC11;AURKA;PPP1CA;CDC20;PPP1CB;PPP2CA;CCNB2;CCNB1;PTTG1;CCNE2;YWHAQ;PPP2R1A;CDK1;CALM2;SKP1 \\\\\n\t Thermogenesis & 29/231 & 1.278000e-05 & NDUFB9;NDUFA11;NDUFB6;COX7A2;COX5B;COX5A;ACTB;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;NDUFA9;ACTL6A;RPS6;NDUFC2;COX6C;SDHA;SMARCA4;COX6B1;CREB3;NDUFS7;NDUFAB1;UQCRC1;GNAS;NDUFS3;NDUFS2;UQCRC2;FGFR1 \\\\\n\t Epstein-Barr virus infection & 26/201 & 2.089389e-05 & PSMD14;PSMD8;CCND1;MYC;PSMD2;PSMD3;PSMD1;PDIA3;STAT1;DDX58;ADRM1;ISG15;CCNA2;PSMC5;PSMC3;CCNE2;OAS1;PSMC4;CDK4;OAS3;PSMC2;CYCS;CALR;VIM;CD44;IRF9 \\\\\n\t Hepatitis C & 21/155 & 6.423047e-05 & YWHAB;DDX58;STAT1;MX1;EIF2S1;EGFR;TNFRSF1A;PPP2CA;CCND1;YWHAQ;OAS1;PPP2R1A;CDK4;MYC;PSME3;OAS3;CLDN7;IFIT1B;CYCS;EIF3E;IRF9 \\\\\n\t DNA replication & 9/36 & 7.730573e-05 & POLD4;FEN1;PCNA;MCM7;POLD2;MCM3;MCM4;MCM5;MCM2 \\\\\n\t Human T-cell leukemia virus 1 infection & 26/219 & 9.099964e-05 & NRP1;ANAPC11;CDC20;CCNB2;CCND1;PTTG1;MYC;TSPO;BUB3;RANBP1;FDPS;ANAPC7;TNFRSF1A;FOSL1;CCNA2;CREB3;CCNE2;CDK4;CANX;VDAC1;CALR;LTBR;SLC25A5;SLC25A4;RAN;SLC25A6 \\\\\n\t Cellular senescence & 21/160 & 1.021684e-04 & IGFBP3;ITPR3;PPP1CA;PPP1CB;CCNA2;CCNB2;CCNB1;CCND1;CCNE2;RBBP4;CDK4;MYC;CAPN2;EIF4EBP1;CDK1;VDAC1;SLC25A5;SQSTM1;CALM2;SLC25A4;SLC25A6 \\\\\n\t Pathogenic Escherichia coli infection & 11/55 & 1.146683e-04 & TUBA1B;KRT18;YWHAQ;ARPC2;NCL;ARPC1A;ARPC5L;TUBB4B;ACTB;RHOA;TUBA8 \\\\\n\t Spliceosome & 18/134 & 2.327610e-04 & TCERG1;HSPA8;NCBP2;EIF4A3;SRSF1;HSPA2;LSM5;LSM4;SNRPD2;SNRPD1;PCBP1;SRSF3;SNRPA1;SNRPD3;HNRNPC;SNRNP200;SRSF7;SNRPB \\\\\n\t N-Glycan biosynthesis & 10/50 & 2.330233e-04 & GANAB;B4GALT1;RPN2;ALG5;RPN1;SRD5A3;ALG3;MGAT1;ALG11;DDOST \\\\\n\t Vibrio cholerae infection & 10/50 & 2.330233e-04 & SEC61A1;ATP6V1G1;ATP6V0B;GNAS;KDELR2;SEC61B;ATP6V0C;ACTB;PDIA4;ATP6V1C2 \\\\\n\t Necroptosis & 20/162 & 3.387172e-04 & RNF31;HSP90AA1;HSP90AB1;PARP1;STAT1;TNFRSF1A;SHARPIN;FTH1;CHMP2B;CAPN2;CHMP2A;CHMP3;VDAC1;RBCK1;SLC25A5;PPIA;SQSTM1;SLC25A4;IRF9;SLC25A6 \\\\\n\t Adherens junction & 12/72 & 3.477573e-04 & CTNND1;ERBB2;RAC2;CTNNA1;LMO7;ACTN4;IQGAP1;BAIAP2;ACTB;RHOA;EGFR;FGFR1 \\\\\n\t p53 signaling pathway & 12/72 & 3.477573e-04 & CCNB2;CCNB1;RRM2;CCND1;CCNE2;SIVA1;CDK4;IGFBP3;EI24;PERP;CDK1;CYCS \\\\\n\t Antigen processing and presentation & 12/77 & 6.536642e-04 & PDIA3;CD74;HSPA8;HSP90AA1;HSP90AB1;HSPA5;PSME3;CANX;PSME1;HSPA2;CALR;CTSB \\\\\n\t Pyrimidine metabolism & 10/57 & 7.019624e-04 & NME1-NME2;DTYMK;NT5E;DUT;RRM1;RRM2;TK1;TYMS;DCTPP1;NME1 \\\\\n\t Cardiac muscle contraction & 12/78 & 7.361984e-04 & COX8A;UQCRC1;UQCRFS1;ATP1B3;COX7A2;UQCRC2;ATP1A1;CYC1;COX5B;COX6C;COX5A;COX6B1 \\\\\n\t Citrate cycle (TCA cycle) & 7/30 & 7.652426e-04 & CS;MDH1;IDH1;IDH2;IDH3B;ACO2;SDHA \\\\\n\t Glyoxylate and dicarboxylate metabolism & 7/30 & 7.652426e-04 & CS;GRHPR;MDH1;SHMT2;CAT;ACO2;ACAT2 \\\\\n\t ⋮ & ⋮ & ⋮ & ⋮\\\\\n\t epithelial tube morphogenesis (GO:0060562) & 1/90 & 0.9923565 & TACSTD2 \\\\\n\t positive regulation of hormone secretion (GO:0046887) & 1/91 & 0.9927602 & PSMD9 \\\\\n\t positive regulation of cyclic nucleotide metabolic process (GO:0030801) & 1/91 & 0.9927602 & GNAS \\\\\n\t regulation of cAMP biosynthetic process (GO:0030817) & 1/98 & 0.9950485 & GNAS \\\\\n\t detection of external stimulus (GO:0009581) & 3/175 & 0.9956065 & FECH;SDC4;SDC1 \\\\\n\t tube morphogenesis (GO:0035239) & 1/101 & 0.9957925 & TACSTD2 \\\\\n\t detection of abiotic stimulus (GO:0009582) & 3/178 & 0.9961518 & FECH;SDC4;SDC1 \\\\\n\t positive regulation of secretion (GO:0051047) & 6/273 & 0.9965193 & PSMD9;MIF;GATA3;KCNN4;PPIA;CD276 \\\\\n\t membrane depolarization (GO:0051899) & 1/106 & 0.9967926 & CAV1 \\\\\n\t central nervous system development (GO:0007417) & 1/108 & 0.9971226 & S100B \\\\\n\t anterior/posterior pattern specification (GO:0009952) & 2/150 & 0.9972471 & PRKDC;ATP6AP2 \\\\\n\t regulation of cAMP metabolic process (GO:0030814) & 1/113 & 0.9978065 & GNAS \\\\\n\t regulation of cyclic nucleotide biosynthetic process (GO:0030802) & 1/116 & 0.9981361 & GNAS \\\\\n\t regulation of purine nucleotide biosynthetic process (GO:1900371) & 1/119 & 0.9984161 & GNAS \\\\\n\t regulation of nucleotide biosynthetic process (GO:0030808) & 1/119 & 0.9984161 & GNAS \\\\\n\t complement activation, classical pathway (GO:0006958) & 2/162 & 0.9984634 & C1QBP;CD46 \\\\\n\t regulation of transmembrane transport (GO:0034762) & 7/327 & 0.9986252 & LGALS3;CLIC3;AHNAK;S100A1;ATP1B3;ACTN4;AZIN1 \\\\\n\t adenylate cyclase-modulating G-protein coupled receptor signaling pathway (GO:0007188) & 1/122 & 0.9986541 & GNAS \\\\\n\t cilium organization (GO:0044782) & 1/125 & 0.9988562 & TTC17 \\\\\n\t complement activation (GO:0006956) & 2/175 & 0.9991867 & C1QBP;CD46 \\\\\n\t regulation of cyclic nucleotide metabolic process (GO:0030799) & 1/133 & 0.9992587 & GNAS \\\\\n\t regulation of ion transmembrane transport (GO:0034765) & 6/314 & 0.9992843 & LGALS3;CLIC3;AHNAK;S100A1;ATP1B3;ACTN4 \\\\\n\t synaptic transmission (GO:0007268) & 10/434 & 0.9993561 & NQO1;HSPA8;SLC38A1;SYPL1;GNG5;TSPO;VDAC1;KCNN4;GABARAP;AP2M1\\\\\n\t pattern specification process (GO:0007389) & 8/385 & 0.9995267 & NOTCH2;NRP1;PRKDC;ALG5;ATP6AP2;IFT122;BMP7;AURKA \\\\\n\t protein activation cascade (GO:0072376) & 2/196 & 0.9997107 & C1QBP;CD46 \\\\\n\t G-protein coupled receptor signaling pathway, coupled to cyclic nucleotide second messenger (GO:0007187) & 1/153 & 0.9997484 & GNAS \\\\\n\t regionalization (GO:0003002) & 3/247 & 0.9998335 & PRKDC;ATP6AP2;IFT122 \\\\\n\t cellular component assembly involved in morphogenesis (GO:0010927) & 1/186 & 0.9999556 & OFD1 \\\\\n\t detection of chemical stimulus (GO:0009593) & 2/499 & 0.9999954 & AZGP1;PIP \\\\\n\t detection of chemical stimulus involved in sensory perception (GO:0050907) & 2/465 & 0.9999955 & AZGP1;PIP \\\\\n\\end{tabular}\n","text/plain":" Term \n1 Ribosome \n2 Proteasome \n3 Protein processing in endoplasmic reticulum \n4 Huntington disease \n5 Cell cycle \n6 Oxidative phosphorylation \n7 Parkinson disease \n8 Protein export \n9 Alzheimer disease \n10 Non-alcoholic fatty liver disease (NAFLD) \n11 RNA transport \n12 Oocyte meiosis \n13 Thermogenesis \n14 Epstein-Barr virus infection \n15 Hepatitis C \n16 DNA replication \n17 Human T-cell leukemia virus 1 infection \n18 Cellular senescence \n19 Pathogenic Escherichia coli infection \n20 Spliceosome \n21 N-Glycan biosynthesis \n22 Vibrio cholerae infection \n23 Necroptosis \n24 Adherens junction \n25 p53 signaling pathway \n26 Antigen processing and presentation \n27 Pyrimidine metabolism \n28 Cardiac muscle contraction \n29 Citrate cycle (TCA cycle) \n30 Glyoxylate and dicarboxylate metabolism \n⋮ ⋮ \n4116 epithelial tube morphogenesis (GO:0060562) \n4117 positive regulation of hormone secretion (GO:0046887) \n4118 positive regulation of cyclic nucleotide metabolic process (GO:0030801) \n4119 regulation of cAMP biosynthetic process (GO:0030817) \n4120 detection of external stimulus (GO:0009581) \n4121 tube morphogenesis (GO:0035239) \n4122 detection of abiotic stimulus (GO:0009582) \n4123 positive regulation of secretion (GO:0051047) \n4124 membrane depolarization (GO:0051899) \n4125 central nervous system development (GO:0007417) \n4126 anterior/posterior pattern specification (GO:0009952) \n4127 regulation of cAMP metabolic process (GO:0030814) \n4128 regulation of cyclic nucleotide biosynthetic process (GO:0030802) \n4129 regulation of purine nucleotide biosynthetic process (GO:1900371) \n4130 regulation of nucleotide biosynthetic process (GO:0030808) \n4131 complement activation, classical pathway (GO:0006958) \n4132 regulation of transmembrane transport (GO:0034762) \n4133 adenylate cyclase-modulating G-protein coupled receptor signaling pathway (GO:0007188) \n4134 cilium organization (GO:0044782) \n4135 complement activation (GO:0006956) \n4136 regulation of cyclic nucleotide metabolic process (GO:0030799) \n4137 regulation of ion transmembrane transport (GO:0034765) \n4138 synaptic transmission (GO:0007268) \n4139 pattern specification process (GO:0007389) \n4140 protein activation cascade (GO:0072376) \n4141 G-protein coupled receptor signaling pathway, coupled to cyclic nucleotide second messenger (GO:0007187)\n4142 regionalization (GO:0003002) \n4143 cellular component assembly involved in morphogenesis (GO:0010927) \n4144 detection of chemical stimulus (GO:0009593) \n4145 detection of chemical stimulus involved in sensory perception (GO:0050907) \n Overlap P.value \n1 66/153 1.195049e-43\n2 25/45 9.261661e-21\n3 36/165 2.122271e-13\n4 37/193 6.230550e-12\n5 27/124 2.241324e-10\n6 28/133 2.399141e-10\n7 29/142 2.477250e-10\n8 12/23 3.326536e-10\n9 30/171 5.527120e-09\n10 26/149 6.371987e-08\n11 26/165 5.115286e-07\n12 21/125 2.185197e-06\n13 29/231 1.278000e-05\n14 26/201 2.089389e-05\n15 21/155 6.423047e-05\n16 9/36 7.730573e-05\n17 26/219 9.099964e-05\n18 21/160 1.021684e-04\n19 11/55 1.146683e-04\n20 18/134 2.327610e-04\n21 10/50 2.330233e-04\n22 10/50 2.330233e-04\n23 20/162 3.387172e-04\n24 12/72 3.477573e-04\n25 12/72 3.477573e-04\n26 12/77 6.536642e-04\n27 10/57 7.019624e-04\n28 12/78 7.361984e-04\n29 7/30 7.652426e-04\n30 7/30 7.652426e-04\n⋮ ⋮ ⋮ \n4116 1/90 0.9923565 \n4117 1/91 0.9927602 \n4118 1/91 0.9927602 \n4119 1/98 0.9950485 \n4120 3/175 0.9956065 \n4121 1/101 0.9957925 \n4122 3/178 0.9961518 \n4123 6/273 0.9965193 \n4124 1/106 0.9967926 \n4125 1/108 0.9971226 \n4126 2/150 0.9972471 \n4127 1/113 0.9978065 \n4128 1/116 0.9981361 \n4129 1/119 0.9984161 \n4130 1/119 0.9984161 \n4131 2/162 0.9984634 \n4132 7/327 0.9986252 \n4133 1/122 0.9986541 \n4134 1/125 0.9988562 \n4135 2/175 0.9991867 \n4136 1/133 0.9992587 \n4137 6/314 0.9992843 \n4138 10/434 0.9993561 \n4139 8/385 0.9995267 \n4140 2/196 0.9997107 \n4141 1/153 0.9997484 \n4142 3/247 0.9998335 \n4143 1/186 0.9999556 \n4144 2/499 0.9999954 \n4145 2/465 0.9999955 \n Genes \n1 RPL4;RPL5;RPL30;MRPS15;RPL3;RPL32;RPL31;MRPS11;RPLP1;MRPS12;RPLP0;RPL10A;RPL6;RPL7;RPS4X;RPS14;MRPL3;RPS16;RPL18A;RPL36;RPL35;MRPL9;RPS11;RPS13;RPL21;RPS7;RPS8;RPS5;RPS6;MRPS18A;RPL13A;MRPS21;RPSA;RPS3A;MRPS7;RPL37A;RPL24;RPL27;RPL26;RPL29;UBA52;RPL12;RPL11;MRPL14;MRPL15;MRPL12;MRPL13;MRPL11;RPL14;RPS3;RPL15;RPS2;RPL18;RPS27A;RPL17;RPL19;RPL41;RPL35A;RPL23A;RPS27;RPS20;RPL22L1;FAU;RPS21;RPS24;RPS23\n2 PSMD14;PSMA7;PSMD8;PSMB6;PSMB7;PSMB4;PSMB5;PSMB2;PSMB3;PSMD2;PSMB1;PSMD3;PSMD1;PSMF1;ADRM1;PSMA5;PSMA6;PSMC5;PSMA3;PSMA4;PSMC3;PSMC4;PSME3;PSMC2;PSME1 \n3 VCP;HSP90AB1;RPN2;RPN1;DERL1;HERPUD1;SEC61A1;GANAB;LMAN2;BAG1;CAPN2;UBQLN1;SEC61B;SKP1;TXNDC5;SEC31A;PDIA3;HSPA8;XBP1;SEC13;HSP90AA1;HSPA5;WFS1;SSR2;SSR3;RAD23A;HSPA2;PDIA6;EIF2S1;CKAP4;DDOST;PDIA4;DNAJA1;CANX;CALR;P4HB \n4 NDUFB9;DNAH1;NDUFA11;NDUFB6;DCTN2;DCTN1;COX7A2;COX5B;COX5A;POLR2A;UQCRFS1;CYC1;POLR2H;NDUFV2;NDUFV1;AP2M1;POLR2K;TGM2;COX8A;NDUFA9;NDUFC2;COX6C;SDHA;COX6B1;SOD1;CREB3;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;VDAC1;UQCRC2;SLC25A5;SLC25A4;SLC25A6 \n5 PCNA;MCM7;PRKDC;YWHAB;PKMYT1;ANAPC11;CDC20;CCNB2;CCNB1;CCND1;PTTG1;YWHAQ;MYC;BUB3;SKP1;ANAPC7;PLK1;CDC25B;CCNA2;TFDP1;CCNE2;CDK4;CDK1;MCM3;MCM4;MCM5;MCM2 \n6 NDUFB9;NDUFA11;NDUFB6;COX7A2;COX5B;COX5A;UQCRFS1;CYC1;NDUFV2;NDUFV1;ATP6V1C2;COX8A;NDUFA9;ATP6V1G1;ATP6V0B;NDUFC2;SDHA;COX6C;COX6B1;PPA2;NDUFS7;PPA1;NDUFAB1;UQCRC1;NDUFS3;NDUFS2;UQCRC2;ATP6V0C \n7 NDUFB9;NDUFA11;NDUFB6;UBE2L6;COX7A2;COX5B;COX5A;UBB;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;NDUFA9;NDUFC2;SDHA;COX6C;COX6B1;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;VDAC1;UQCRC2;SLC25A5;SLC25A4;SLC25A6 \n8 OXA1L;SEC61A1;SPCS1;HSPA5;SRP72;SRP54;SRPRB;SRP68;SEC61B;SRP14;SEC11A;SRP9 \n9 NDUFB9;NDUFA11;NDUFB6;COX7A2;ITPR3;COX5B;COX5A;NCSTN;CAPN2;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;PSENEN;NDUFA9;NDUFC2;SDHA;COX6C;COX6B1;TNFRSF1A;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;UQCRC2;CALM2;GAPDH \n10 NDUFB9;NDUFA11;NDUFB6;COX7A2;COX5B;COX5A;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;NDUFA9;XBP1;NDUFC2;SDHA;COX6C;EIF2S1;COX6B1;TNFRSF1A;NDUFS7;NDUFAB1;UQCRC1;NDUFS3;CYCS;NDUFS2;UQCRC2 \n11 EIF4A1;EIF4A3;TPR;NUP62;EIF4EBP1;SAP18;RAE1;EIF4B;PRMT5;SEC13;NUP133;NCBP2;RANGAP1;EIF2S1;EIF1;EEF1A1;EIF5;CLNS1A;EIF3I;STRAP;EIF3H;EIF3E;EIF3F;EIF3D;RAN;EIF4G1 \n12 ANAPC7;YWHAB;PLK1;ITPR3;PPP2R5D;PKMYT1;ANAPC11;AURKA;PPP1CA;CDC20;PPP1CB;PPP2CA;CCNB2;CCNB1;PTTG1;CCNE2;YWHAQ;PPP2R1A;CDK1;CALM2;SKP1 \n13 NDUFB9;NDUFA11;NDUFB6;COX7A2;COX5B;COX5A;ACTB;UQCRFS1;CYC1;NDUFV2;NDUFV1;COX8A;NDUFA9;ACTL6A;RPS6;NDUFC2;COX6C;SDHA;SMARCA4;COX6B1;CREB3;NDUFS7;NDUFAB1;UQCRC1;GNAS;NDUFS3;NDUFS2;UQCRC2;FGFR1 \n14 PSMD14;PSMD8;CCND1;MYC;PSMD2;PSMD3;PSMD1;PDIA3;STAT1;DDX58;ADRM1;ISG15;CCNA2;PSMC5;PSMC3;CCNE2;OAS1;PSMC4;CDK4;OAS3;PSMC2;CYCS;CALR;VIM;CD44;IRF9 \n15 YWHAB;DDX58;STAT1;MX1;EIF2S1;EGFR;TNFRSF1A;PPP2CA;CCND1;YWHAQ;OAS1;PPP2R1A;CDK4;MYC;PSME3;OAS3;CLDN7;IFIT1B;CYCS;EIF3E;IRF9 \n16 POLD4;FEN1;PCNA;MCM7;POLD2;MCM3;MCM4;MCM5;MCM2 \n17 NRP1;ANAPC11;CDC20;CCNB2;CCND1;PTTG1;MYC;TSPO;BUB3;RANBP1;FDPS;ANAPC7;TNFRSF1A;FOSL1;CCNA2;CREB3;CCNE2;CDK4;CANX;VDAC1;CALR;LTBR;SLC25A5;SLC25A4;RAN;SLC25A6 \n18 IGFBP3;ITPR3;PPP1CA;PPP1CB;CCNA2;CCNB2;CCNB1;CCND1;CCNE2;RBBP4;CDK4;MYC;CAPN2;EIF4EBP1;CDK1;VDAC1;SLC25A5;SQSTM1;CALM2;SLC25A4;SLC25A6 \n19 TUBA1B;KRT18;YWHAQ;ARPC2;NCL;ARPC1A;ARPC5L;TUBB4B;ACTB;RHOA;TUBA8 \n20 TCERG1;HSPA8;NCBP2;EIF4A3;SRSF1;HSPA2;LSM5;LSM4;SNRPD2;SNRPD1;PCBP1;SRSF3;SNRPA1;SNRPD3;HNRNPC;SNRNP200;SRSF7;SNRPB \n21 GANAB;B4GALT1;RPN2;ALG5;RPN1;SRD5A3;ALG3;MGAT1;ALG11;DDOST \n22 SEC61A1;ATP6V1G1;ATP6V0B;GNAS;KDELR2;SEC61B;ATP6V0C;ACTB;PDIA4;ATP6V1C2 \n23 RNF31;HSP90AA1;HSP90AB1;PARP1;STAT1;TNFRSF1A;SHARPIN;FTH1;CHMP2B;CAPN2;CHMP2A;CHMP3;VDAC1;RBCK1;SLC25A5;PPIA;SQSTM1;SLC25A4;IRF9;SLC25A6 \n24 CTNND1;ERBB2;RAC2;CTNNA1;LMO7;ACTN4;IQGAP1;BAIAP2;ACTB;RHOA;EGFR;FGFR1 \n25 CCNB2;CCNB1;RRM2;CCND1;CCNE2;SIVA1;CDK4;IGFBP3;EI24;PERP;CDK1;CYCS \n26 PDIA3;CD74;HSPA8;HSP90AA1;HSP90AB1;HSPA5;PSME3;CANX;PSME1;HSPA2;CALR;CTSB \n27 NME1-NME2;DTYMK;NT5E;DUT;RRM1;RRM2;TK1;TYMS;DCTPP1;NME1 \n28 COX8A;UQCRC1;UQCRFS1;ATP1B3;COX7A2;UQCRC2;ATP1A1;CYC1;COX5B;COX6C;COX5A;COX6B1 \n29 CS;MDH1;IDH1;IDH2;IDH3B;ACO2;SDHA \n30 CS;GRHPR;MDH1;SHMT2;CAT;ACO2;ACAT2 \n⋮ ⋮ \n4116 TACSTD2 \n4117 PSMD9 \n4118 GNAS \n4119 GNAS \n4120 FECH;SDC4;SDC1 \n4121 TACSTD2 \n4122 FECH;SDC4;SDC1 \n4123 PSMD9;MIF;GATA3;KCNN4;PPIA;CD276 \n4124 CAV1 \n4125 S100B \n4126 PRKDC;ATP6AP2 \n4127 GNAS \n4128 GNAS \n4129 GNAS \n4130 GNAS \n4131 C1QBP;CD46 \n4132 LGALS3;CLIC3;AHNAK;S100A1;ATP1B3;ACTN4;AZIN1 \n4133 GNAS \n4134 TTC17 \n4135 C1QBP;CD46 \n4136 GNAS \n4137 LGALS3;CLIC3;AHNAK;S100A1;ATP1B3;ACTN4 \n4138 NQO1;HSPA8;SLC38A1;SYPL1;GNG5;TSPO;VDAC1;KCNN4;GABARAP;AP2M1 \n4139 NOTCH2;NRP1;PRKDC;ALG5;ATP6AP2;IFT122;BMP7;AURKA \n4140 C1QBP;CD46 \n4141 GNAS \n4142 PRKDC;ATP6AP2;IFT122 \n4143 OFD1 \n4144 AZGP1;PIP \n4145 AZGP1;PIP "},"metadata":{}}]},{"metadata":{"trusted":false},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"name":"ir","display_name":"R","language":"R"},"language_info":{"name":"R","codemirror_mode":"r","pygments_lexer":"r","mimetype":"text/x-r-source","file_extension":".r","version":"4.0.3"}},"nbformat":4,"nbformat_minor":2}
Datasets
Models
