R_ProstateCancer_DESeq2.ipynb

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        "<a href=\"https://colab.research.google.com/github/SanandhKumar02/MiniProject_ProstateCancer/blob/main/R_ProstateCancer_DESeq2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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            "Installing package into ‘/usr/local/lib/R/site-library’\n",
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              "'R version 4.2.0 (2022-04-22)'"
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            "'getOption(\"repos\")' replaces Bioconductor standard repositories, see\n",
            "'?repositories' for details\n",
            "\n",
            "replacement repositories:\n",
            "    CRAN: https://cran.rstudio.com\n",
            "\n",
            "\n",
            "Bioconductor version 3.15 (BiocManager 1.30.18), R 4.2.0 (2022-04-22)\n",
            "\n",
            "Installing package(s) 'BiocVersion', 'TCGAbiolinks'\n",
            "\n",
            "also installing the dependencies ‘plogr’, ‘png’, ‘Biostrings’, ‘bitops’, ‘RSQLite’, ‘KEGGREST’, ‘filelock’, ‘RCurl’, ‘GenomeInfoDbData’, ‘zlibbioc’, ‘matrixStats’, ‘AnnotationDbi’, ‘BiocFileCache’, ‘BiocGenerics’, ‘GenomeInfoDb’, ‘XVector’, ‘Rcpp’, ‘R.oo’, ‘R.methodsS3’, ‘MatrixGenerics’, ‘Biobase’, ‘DelayedArray’, ‘downloader’, ‘biomaRt’, ‘GenomicRanges’, ‘XML’, ‘plyr’, ‘IRanges’, ‘S4Vectors’, ‘R.utils’, ‘SummarizedExperiment’, ‘TCGAbiolinksGUI.data’\n",
            "\n",
            "\n",
            "Old packages: 'dbplyr', 'processx', 'tinytex', 'nlme'\n",
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      "execution_count": null,
      "metadata": {
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      "outputs": [],
      "source": [
        "library(TCGAbiolinks)"
      ]
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    {
      "cell_type": "code",
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      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
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        "id": "wfDdXlMeFCnn",
        "outputId": "6331e9a6-48db-4c73-bd7f-9ceb972f2647"
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          "text": [
            "Loading required package: MatrixGenerics\n",
            "\n",
            "Loading required package: matrixStats\n",
            "\n",
            "\n",
            "Attaching package: ‘MatrixGenerics’\n",
            "\n",
            "\n",
            "The 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",
            "\n",
            "Loading required package: GenomicRanges\n",
            "\n",
            "Loading required package: stats4\n",
            "\n",
            "Loading required package: BiocGenerics\n",
            "\n",
            "\n",
            "Attaching package: ‘BiocGenerics’\n",
            "\n",
            "\n",
            "The following objects are masked from ‘package:stats’:\n",
            "\n",
            "    IQR, mad, sd, var, xtabs\n",
            "\n",
            "\n",
            "The 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",
            "\n",
            "Loading required package: S4Vectors\n",
            "\n",
            "\n",
            "Attaching package: ‘S4Vectors’\n",
            "\n",
            "\n",
            "The following objects are masked from ‘package:base’:\n",
            "\n",
            "    expand.grid, I, unname\n",
            "\n",
            "\n",
            "Loading required package: IRanges\n",
            "\n",
            "Loading required package: GenomeInfoDb\n",
            "\n",
            "Loading required package: Biobase\n",
            "\n",
            "Welcome 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",
            "\n",
            "Attaching package: ‘Biobase’\n",
            "\n",
            "\n",
            "The following object is masked from ‘package:MatrixGenerics’:\n",
            "\n",
            "    rowMedians\n",
            "\n",
            "\n",
            "The following objects are masked from ‘package:matrixStats’:\n",
            "\n",
            "    anyMissing, rowMedians\n",
            "\n",
            "\n"
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        "library(SummarizedExperiment)"
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    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "z8t3exIeVOpW"
      },
      "outputs": [],
      "source": [
        "library(ggplot2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C2KpF5mEFlLC",
        "outputId": "c5573d11-0efc-48dc-ceb1-1e0794c8c097"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "'getOption(\"repos\")' replaces Bioconductor standard repositories, see\n",
            "'?repositories' for details\n",
            "\n",
            "replacement repositories:\n",
            "    CRAN: https://cran.rstudio.com\n",
            "\n",
            "\n",
            "Bioconductor version 3.15 (BiocManager 1.30.18), R 4.2.0 (2022-04-22)\n",
            "\n",
            "Installing package(s) 'DESeq2'\n",
            "\n",
            "also installing the dependencies ‘formatR’, ‘lambda.r’, ‘futile.options’, ‘xtable’, ‘futile.logger’, ‘snow’, ‘BH’, ‘annotate’, ‘BiocParallel’, ‘genefilter’, ‘locfit’, ‘geneplotter’, ‘RcppArmadillo’\n",
            "\n",
            "\n",
            "Old packages: 'dbplyr', 'processx', 'tinytex', 'nlme'\n",
            "\n"
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      "source": [
        "BiocManager::install(\"DESeq2\")"
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      "source": [
        "library(DESeq2)"
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      "metadata": {
        "id": "qwXUTclyrVxG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Function to get Up-regulated and Down-regulated Genes**"
      ],
      "metadata": {
        "id": "FK6RKIVDkCbe"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "J8yRQplwI872"
      },
      "outputs": [],
      "source": [
        "get_upregulated <- function(df){\n",
        "    key <- intersect(rownames(df)[which(df$log2FoldChange>=1)],\n",
        "              rownames(df)[which(df$pvalue<=0.05)])\n",
        "    \n",
        "    results <- as.data.frame((df)[which(rownames(df) %in% key),])\n",
        "    return(results)\n",
        "  }"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "qqv1oPvUJAIW"
      },
      "outputs": [],
      "source": [
        "get_downregulated <- function(df){\n",
        "  key <- intersect(rownames(df)[which(df$log2FoldChange<=-1)],\n",
        "            rownames(df)[which(df$pvalue<=0.05)])\n",
        "  \n",
        "  results <- as.data.frame((df)[which(rownames(df) %in% key),])\n",
        "  return(results)\n",
        "}"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# ***miRNA Differential Analysis***"
      ],
      "metadata": {
        "id": "hiyKRDXlkZTT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Downloading and Preparing Data"
      ],
      "metadata": {
        "id": "g6OiFXf9lgJ3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "mirna_query <- GDCquery(project = \"TCGA-PRAD\",\n",
        "                        data.category = \"Transcriptome Profiling\",\n",
        "                        data.type = \"miRNA Expression Quantification\",\n",
        "                        experimental.strategy = \"miRNA-Seq\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9CDbbXQ8khmj",
        "outputId": "3a934ba4-65a4-44b8-b5d4-ee75c90722c5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "--------------------------------------\n",
            "\n",
            "o GDCquery: Searching in GDC database\n",
            "\n",
            "--------------------------------------\n",
            "\n",
            "Genome of reference: hg38\n",
            "\n",
            "--------------------------------------------\n",
            "\n",
            "oo Accessing GDC. This might take a while...\n",
            "\n",
            "--------------------------------------------\n",
            "\n",
            "ooo Project: TCGA-PRAD\n",
            "\n",
            "--------------------\n",
            "\n",
            "oo Filtering results\n",
            "\n",
            "--------------------\n",
            "\n",
            "ooo By experimental.strategy\n",
            "\n",
            "ooo By data.type\n",
            "\n",
            "----------------\n",
            "\n",
            "oo Checking data\n",
            "\n",
            "----------------\n",
            "\n",
            "ooo Check if there are duplicated cases\n",
            "\n",
            "ooo Check if there results for the query\n",
            "\n",
            "-------------------\n",
            "\n",
            "o Preparing output\n",
            "\n",
            "-------------------\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "GDCdownload(mirna_query, method = \"api\", files.per.chunk = 100,\n",
        "            directory = \"/content/Data\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wNmBUiQiktwZ",
        "outputId": "de3bd25e-e0e5-4c17-fa3b-43f755b40c08"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading data for project TCGA-PRAD\n",
            "\n",
            "GDCdownload will download 551 files. A total of 27.635813 MB\n",
            "\n",
            "Downloading chunk 1 of 6 (100 files, size = 5.016283 MB) as Thu_Jun_16_10_23_19_2022_0.tar.gz\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading: 800 kB     "
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading chunk 2 of 6 (100 files, size = 5.014826 MB) as Thu_Jun_16_10_23_19_2022_1.tar.gz\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading: 790 kB     "
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading chunk 3 of 6 (100 files, size = 5.016307 MB) as Thu_Jun_16_10_23_19_2022_2.tar.gz\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading: 800 kB     "
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading chunk 4 of 6 (100 files, size = 5.015151 MB) as Thu_Jun_16_10_23_19_2022_3.tar.gz\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading: 790 kB     "
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading chunk 5 of 6 (100 files, size = 5.015926 MB) as Thu_Jun_16_10_23_19_2022_4.tar.gz\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading: 800 kB     "
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading chunk 6 of 6 (51 files, size = 2.55732 MB) as Thu_Jun_16_10_23_19_2022_5.tar.gz\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading: 400 kB     "
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "miR_df <- GDCprepare(mirna_query, directory = \"/content/Data\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iI8Ie3DPlBSo",
        "outputId": "f3bbafd0-fdea-409e-9c70-bfafb5400b88"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  |======================================================================| 100%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "## remove columns we dont need, keep counts\n",
        "rownames(miR_df) <- miR_df$miRNA_ID\n",
        "miR_df <- miR_df[,-1]\n",
        "number_cols <- ncol(miR_df)\n",
        "subset <- seq(from = 1, to = number_cols, by = 3)\n",
        "miR_df <- miR_df[, subset]"
      ],
      "metadata": {
        "id": "o2w6TF7Nl5r_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "## Strip read_count, just want the 'cases' ID\n",
        "colnames(miR_df) <- gsub(\".*_\",\"\",colnames(miR_df))\n",
        "nrow(miR_df)\n",
        "ncol(miR_df)\n",
        "head(miR_df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 633
        },
        "id": "Q-HXCqqJmB8H",
        "outputId": "5d7bc8ef-8e9b-4b05-8cc4-0cdbf0bf2a22"
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              "\t<tr><th scope=row>hsa-let-7a-1</th><td>51384</td><td>37734</td><td>32491</td><td>43522</td><td>84251</td><td>23004</td><td>29078</td><td>25262</td><td> 98606</td><td>85102</td><td>⋯</td><td>75660</td><td>22796</td><td>33406</td><td>31259</td><td>34031</td><td>47400</td><td>28772</td><td>62357</td><td>40116</td><td>22182</td></tr>\n",
              "\t<tr><th scope=row>hsa-let-7a-2</th><td>51537</td><td>37846</td><td>32453</td><td>43443</td><td>84336</td><td>23173</td><td>29154</td><td>25285</td><td>100143</td><td>85016</td><td>⋯</td><td>75424</td><td>22665</td><td>33020</td><td>31219</td><td>33921</td><td>47397</td><td>28290</td><td>62452</td><td>39838</td><td>22410</td></tr>\n",
              "\t<tr><th scope=row>hsa-let-7a-3</th><td>51277</td><td>37554</td><td>32658</td><td>43446</td><td>84391</td><td>23213</td><td>28906</td><td>25584</td><td> 99437</td><td>84939</td><td>⋯</td><td>76109</td><td>22841</td><td>33212</td><td>31711</td><td>34118</td><td>47301</td><td>28696</td><td>62960</td><td>39901</td><td>22063</td></tr>\n",
              "\t<tr><th scope=row>hsa-let-7b</th><td>35001</td><td>28807</td><td>31775</td><td>27308</td><td>86219</td><td>21941</td><td>23735</td><td>26412</td><td> 98270</td><td>43293</td><td>⋯</td><td>53446</td><td>16914</td><td>36323</td><td>29629</td><td>32603</td><td>46076</td><td>20158</td><td>57235</td><td>40825</td><td>10417</td></tr>\n",
              "\t<tr><th scope=row>hsa-let-7c</th><td>15057</td><td>18857</td><td>21198</td><td>23882</td><td>47062</td><td>36790</td><td>21241</td><td>23683</td><td> 95837</td><td>41608</td><td>⋯</td><td>51912</td><td>19811</td><td>32768</td><td>22696</td><td>28238</td><td>28752</td><td>23028</td><td>62909</td><td>23682</td><td>22380</td></tr>\n",
              "\t<tr><th scope=row>hsa-let-7d</th><td> 1095</td><td> 1511</td><td>  602</td><td> 1008</td><td> 1654</td><td>  866</td><td>  883</td><td>  805</td><td>  1963</td><td> 1412</td><td>⋯</td><td> 2214</td><td>  902</td><td>  761</td><td>  837</td><td>  956</td><td> 1216</td><td>  610</td><td> 2103</td><td> 1287</td><td>  643</td></tr>\n",
              "</tbody>\n",
              "</table>\n"
            ],
            "text/markdown": "\nA data.frame: 6 × 551\n\n| <!--/--> | TCGA-EJ-7321-01A-31R-2262-13 &lt;int&gt; | TCGA-J4-A83M-01A-11R-A358-13 &lt;int&gt; | TCGA-EJ-5501-01A-01R-1579-13 &lt;int&gt; | TCGA-V1-A9OY-01A-11R-A41R-13 &lt;int&gt; | TCGA-EJ-5497-01A-02R-1579-13 &lt;int&gt; | TCGA-KK-A6E3-01A-21R-A30I-13 &lt;int&gt; | TCGA-HC-A6AS-01A-11R-A30I-13 &lt;int&gt; | TCGA-HC-8260-11A-01R-2262-13 &lt;int&gt; | TCGA-EJ-A8FO-11A-11R-A36B-13 &lt;int&gt; | TCGA-G9-6377-01A-11R-1964-13 &lt;int&gt; | ⋯ ⋯ | TCGA-H9-A6BX-01A-31R-A310-13 &lt;int&gt; | TCGA-2A-A8VO-01A-11R-A37H-13 &lt;int&gt; | TCGA-G9-7519-01A-11R-2262-13 &lt;int&gt; | TCGA-HC-8260-01A-11R-2262-13 &lt;int&gt; | TCGA-HC-A6AP-01A-11R-A30I-13 &lt;int&gt; | TCGA-EJ-A8FO-01A-21R-A36B-13 &lt;int&gt; | TCGA-YL-A8SQ-01B-11R-A37H-13 &lt;int&gt; | TCGA-J4-A83J-11A-11R-A36B-13 &lt;int&gt; | TCGA-M7-A723-01A-12R-A32J-13 &lt;int&gt; | TCGA-G9-6370-01A-11R-1788-13 &lt;int&gt; |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| hsa-let-7a-1 | 51384 | 37734 | 32491 | 43522 | 84251 | 23004 | 29078 | 25262 |  98606 | 85102 | ⋯ | 75660 | 22796 | 33406 | 31259 | 34031 | 47400 | 28772 | 62357 | 40116 | 22182 |\n| hsa-let-7a-2 | 51537 | 37846 | 32453 | 43443 | 84336 | 23173 | 29154 | 25285 | 100143 | 85016 | ⋯ | 75424 | 22665 | 33020 | 31219 | 33921 | 47397 | 28290 | 62452 | 39838 | 22410 |\n| hsa-let-7a-3 | 51277 | 37554 | 32658 | 43446 | 84391 | 23213 | 28906 | 25584 |  99437 | 84939 | ⋯ | 76109 | 22841 | 33212 | 31711 | 34118 | 47301 | 28696 | 62960 | 39901 | 22063 |\n| hsa-let-7b | 35001 | 28807 | 31775 | 27308 | 86219 | 21941 | 23735 | 26412 |  98270 | 43293 | ⋯ | 53446 | 16914 | 36323 | 29629 | 32603 | 46076 | 20158 | 57235 | 40825 | 10417 |\n| hsa-let-7c | 15057 | 18857 | 21198 | 23882 | 47062 | 36790 | 21241 | 23683 |  95837 | 41608 | ⋯ | 51912 | 19811 | 32768 | 22696 | 28238 | 28752 | 23028 | 62909 | 23682 | 22380 |\n| hsa-let-7d |  1095 |  1511 |   602 |  1008 |  1654 |   866 |   883 |   805 |   1963 |  1412 | ⋯ |  2214 |   902 |   761 |   837 |   956 |  1216 |   610 |  2103 |  1287 |   643 |\n\n",
            "text/latex": "A data.frame: 6 × 551\n\\begin{tabular}{r|lllllllllllllllllllll}\n  & TCGA-EJ-7321-01A-31R-2262-13 & TCGA-J4-A83M-01A-11R-A358-13 & TCGA-EJ-5501-01A-01R-1579-13 & TCGA-V1-A9OY-01A-11R-A41R-13 & TCGA-EJ-5497-01A-02R-1579-13 & TCGA-KK-A6E3-01A-21R-A30I-13 & TCGA-HC-A6AS-01A-11R-A30I-13 & TCGA-HC-8260-11A-01R-2262-13 & TCGA-EJ-A8FO-11A-11R-A36B-13 & TCGA-G9-6377-01A-11R-1964-13 & ⋯ & TCGA-H9-A6BX-01A-31R-A310-13 & TCGA-2A-A8VO-01A-11R-A37H-13 & TCGA-G9-7519-01A-11R-2262-13 & TCGA-HC-8260-01A-11R-2262-13 & TCGA-HC-A6AP-01A-11R-A30I-13 & TCGA-EJ-A8FO-01A-21R-A36B-13 & TCGA-YL-A8SQ-01B-11R-A37H-13 & TCGA-J4-A83J-11A-11R-A36B-13 & TCGA-M7-A723-01A-12R-A32J-13 & TCGA-G9-6370-01A-11R-1788-13\\\\\n  & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & ⋯ & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int>\\\\\n\\hline\n\thsa-let-7a-1 & 51384 & 37734 & 32491 & 43522 & 84251 & 23004 & 29078 & 25262 &  98606 & 85102 & ⋯ & 75660 & 22796 & 33406 & 31259 & 34031 & 47400 & 28772 & 62357 & 40116 & 22182\\\\\n\thsa-let-7a-2 & 51537 & 37846 & 32453 & 43443 & 84336 & 23173 & 29154 & 25285 & 100143 & 85016 & ⋯ & 75424 & 22665 & 33020 & 31219 & 33921 & 47397 & 28290 & 62452 & 39838 & 22410\\\\\n\thsa-let-7a-3 & 51277 & 37554 & 32658 & 43446 & 84391 & 23213 & 28906 & 25584 &  99437 & 84939 & ⋯ & 76109 & 22841 & 33212 & 31711 & 34118 & 47301 & 28696 & 62960 & 39901 & 22063\\\\\n\thsa-let-7b & 35001 & 28807 & 31775 & 27308 & 86219 & 21941 & 23735 & 26412 &  98270 & 43293 & ⋯ & 53446 & 16914 & 36323 & 29629 & 32603 & 46076 & 20158 & 57235 & 40825 & 10417\\\\\n\thsa-let-7c & 15057 & 18857 & 21198 & 23882 & 47062 & 36790 & 21241 & 23683 &  95837 & 41608 & ⋯ & 51912 & 19811 & 32768 & 22696 & 28238 & 28752 & 23028 & 62909 & 23682 & 22380\\\\\n\thsa-let-7d &  1095 &  1511 &   602 &  1008 &  1654 &   866 &   883 &   805 &   1963 &  1412 & ⋯ &  2214 &   902 &   761 &   837 &   956 &  1216 &   610 &  2103 &  1287 &   643\\\\\n\\end{tabular}\n",
            "text/plain": [
              "             TCGA-EJ-7321-01A-31R-2262-13 TCGA-J4-A83M-01A-11R-A358-13\n",
              "hsa-let-7a-1 51384                        37734                       \n",
              "hsa-let-7a-2 51537                        37846                       \n",
              "hsa-let-7a-3 51277                        37554                       \n",
              "hsa-let-7b   35001                        28807                       \n",
              "hsa-let-7c   15057                        18857                       \n",
              "hsa-let-7d    1095                         1511                       \n",
              "             TCGA-EJ-5501-01A-01R-1579-13 TCGA-V1-A9OY-01A-11R-A41R-13\n",
              "hsa-let-7a-1 32491                        43522                       \n",
              "hsa-let-7a-2 32453                        43443                       \n",
              "hsa-let-7a-3 32658                        43446                       \n",
              "hsa-let-7b   31775                        27308                       \n",
              "hsa-let-7c   21198                        23882                       \n",
              "hsa-let-7d     602                         1008                       \n",
              "             TCGA-EJ-5497-01A-02R-1579-13 TCGA-KK-A6E3-01A-21R-A30I-13\n",
              "hsa-let-7a-1 84251                        23004                       \n",
              "hsa-let-7a-2 84336                        23173                       \n",
              "hsa-let-7a-3 84391                        23213                       \n",
              "hsa-let-7b   86219                        21941                       \n",
              "hsa-let-7c   47062                        36790                       \n",
              "hsa-let-7d    1654                          866                       \n",
              "             TCGA-HC-A6AS-01A-11R-A30I-13 TCGA-HC-8260-11A-01R-2262-13\n",
              "hsa-let-7a-1 29078                        25262                       \n",
              "hsa-let-7a-2 29154                        25285                       \n",
              "hsa-let-7a-3 28906                        25584                       \n",
              "hsa-let-7b   23735                        26412                       \n",
              "hsa-let-7c   21241                        23683                       \n",
              "hsa-let-7d     883                          805                       \n",
              "             TCGA-EJ-A8FO-11A-11R-A36B-13 TCGA-G9-6377-01A-11R-1964-13 ⋯\n",
              "hsa-let-7a-1  98606                       85102                        ⋯\n",
              "hsa-let-7a-2 100143                       85016                        ⋯\n",
              "hsa-let-7a-3  99437                       84939                        ⋯\n",
              "hsa-let-7b    98270                       43293                        ⋯\n",
              "hsa-let-7c    95837                       41608                        ⋯\n",
              "hsa-let-7d     1963                        1412                        ⋯\n",
              "             TCGA-H9-A6BX-01A-31R-A310-13 TCGA-2A-A8VO-01A-11R-A37H-13\n",
              "hsa-let-7a-1 75660                        22796                       \n",
              "hsa-let-7a-2 75424                        22665                       \n",
              "hsa-let-7a-3 76109                        22841                       \n",
              "hsa-let-7b   53446                        16914                       \n",
              "hsa-let-7c   51912                        19811                       \n",
              "hsa-let-7d    2214                          902                       \n",
              "             TCGA-G9-7519-01A-11R-2262-13 TCGA-HC-8260-01A-11R-2262-13\n",
              "hsa-let-7a-1 33406                        31259                       \n",
              "hsa-let-7a-2 33020                        31219                       \n",
              "hsa-let-7a-3 33212                        31711                       \n",
              "hsa-let-7b   36323                        29629                       \n",
              "hsa-let-7c   32768                        22696                       \n",
              "hsa-let-7d     761                          837                       \n",
              "             TCGA-HC-A6AP-01A-11R-A30I-13 TCGA-EJ-A8FO-01A-21R-A36B-13\n",
              "hsa-let-7a-1 34031                        47400                       \n",
              "hsa-let-7a-2 33921                        47397                       \n",
              "hsa-let-7a-3 34118                        47301                       \n",
              "hsa-let-7b   32603                        46076                       \n",
              "hsa-let-7c   28238                        28752                       \n",
              "hsa-let-7d     956                         1216                       \n",
              "             TCGA-YL-A8SQ-01B-11R-A37H-13 TCGA-J4-A83J-11A-11R-A36B-13\n",
              "hsa-let-7a-1 28772                        62357                       \n",
              "hsa-let-7a-2 28290                        62452                       \n",
              "hsa-let-7a-3 28696                        62960                       \n",
              "hsa-let-7b   20158                        57235                       \n",
              "hsa-let-7c   23028                        62909                       \n",
              "hsa-let-7d     610                         2103                       \n",
              "             TCGA-M7-A723-01A-12R-A32J-13 TCGA-G9-6370-01A-11R-1788-13\n",
              "hsa-let-7a-1 40116                        22182                       \n",
              "hsa-let-7a-2 39838                        22410                       \n",
              "hsa-let-7a-3 39901                        22063                       \n",
              "hsa-let-7b   40825                        10417                       \n",
              "hsa-let-7c   23682                        22380                       \n",
              "hsa-let-7d    1287                          643                       "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "## Match to metadata\n",
        "miR_meta <- mirna_query[[1]][[1]]"
      ],
      "metadata": {
        "id": "ULhDawMBmHGb"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "miR_meta <- miR_meta[,c(\"cases\", \"sample_type\")]\n",
        "nrow(miR_meta)\n",
        "ncol(miR_meta)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "id": "Y_MQ5pkixhH8",
        "outputId": "20cb400f-7c9e-4c20-b0af-8d7dc617d8c9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "551"
            ],
            "text/markdown": "551",
            "text/latex": "551",
            "text/plain": [
              "[1] 551"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "2"
            ],
            "text/markdown": "2",
            "text/latex": "2",
            "text/plain": [
              "[1] 2"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "miR_meta$sample_type <- as.character(miR_meta$sample_type)\n",
        "table(miR_meta$sample_type)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 71
        },
        "id": "JZIAMix5qa7L",
        "outputId": "bdc5b1ff-ef98-4788-dace-f17f5abfd84e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\n",
              "         Metastatic       Primary Tumor Solid Tissue Normal \n",
              "                  1                 498                  52 "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "metastatic_key <- miR_meta[which(miR_meta$sample_type == \"Metastatic\"),]\n",
        "miR_meta <- miR_meta[!miR_meta[,2] == metastatic_key[,2],]\n",
        "miR_df <- miR_df[, -grep(paste0(metastatic_key[,1]), colnames(miR_df))]"
      ],
      "metadata": {
        "id": "dY4mMdn7qmf9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "head(miR_df)\n",
        "nrow(miR_df)\n",
        "ncol(miR_df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 633
        },
        "id": "6j-3K01r0F47",
        "outputId": "653abb71-c996-4a55-a5c8-4464ded58484"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table class=\"dataframe\">\n",
              "<caption>A data.frame: 6 × 550</caption>\n",
              "<thead>\n",
              "\t<tr><th></th><th scope=col>TCGA-EJ-7321-01A-31R-2262-13</th><th scope=col>TCGA-J4-A83M-01A-11R-A358-13</th><th scope=col>TCGA-EJ-5501-01A-01R-1579-13</th><th scope=col>TCGA-V1-A9OY-01A-11R-A41R-13</th><th scope=col>TCGA-EJ-5497-01A-02R-1579-13</th><th scope=col>TCGA-KK-A6E3-01A-21R-A30I-13</th><th scope=col>TCGA-HC-A6AS-01A-11R-A30I-13</th><th scope=col>TCGA-HC-8260-11A-01R-2262-13</th><th scope=col>TCGA-EJ-A8FO-11A-11R-A36B-13</th><th scope=col>TCGA-G9-6377-01A-11R-1964-13</th><th scope=col>⋯</th><th scope=col>TCGA-H9-A6BX-01A-31R-A310-13</th><th scope=col>TCGA-2A-A8VO-01A-11R-A37H-13</th><th scope=col>TCGA-G9-7519-01A-11R-2262-13</th><th scope=col>TCGA-HC-8260-01A-11R-2262-13</th><th scope=col>TCGA-HC-A6AP-01A-11R-A30I-13</th><th scope=col>TCGA-EJ-A8FO-01A-21R-A36B-13</th><th scope=col>TCGA-YL-A8SQ-01B-11R-A37H-13</th><th scope=col>TCGA-J4-A83J-11A-11R-A36B-13</th><th scope=col>TCGA-M7-A723-01A-12R-A32J-13</th><th scope=col>TCGA-G9-6370-01A-11R-1788-13</th></tr>\n",
              "\t<tr><th></th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>⋯</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
              "</thead>\n",
              "<tbody>\n",
              "\t<tr><th scope=row>hsa-let-7a-1</th><td>51384</td><td>37734</td><td>32491</td><td>43522</td><td>84251</td><td>23004</td><td>29078</td><td>25262</td><td> 98606</td><td>85102</td><td>⋯</td><td>75660</td><td>22796</td><td>33406</td><td>31259</td><td>34031</td><td>47400</td><td>28772</td><td>62357</td><td>40116</td><td>22182</td></tr>\n",
              "\t<tr><th scope=row>hsa-let-7a-2</th><td>51537</td><td>37846</td><td>32453</td><td>43443</td><td>84336</td><td>23173</td><td>29154</td><td>25285</td><td>100143</td><td>85016</td><td>⋯</td><td>75424</td><td>22665</td><td>33020</td><td>31219</td><td>33921</td><td>47397</td><td>28290</td><td>62452</td><td>39838</td><td>22410</td></tr>\n",
              "\t<tr><th scope=row>hsa-let-7a-3</th><td>51277</td><td>37554</td><td>32658</td><td>43446</td><td>84391</td><td>23213</td><td>28906</td><td>25584</td><td> 99437</td><td>84939</td><td>⋯</td><td>76109</td><td>22841</td><td>33212</td><td>31711</td><td>34118</td><td>47301</td><td>28696</td><td>62960</td><td>39901</td><td>22063</td></tr>\n",
              "\t<tr><th scope=row>hsa-let-7b</th><td>35001</td><td>28807</td><td>31775</td><td>27308</td><td>86219</td><td>21941</td><td>23735</td><td>26412</td><td> 98270</td><td>43293</td><td>⋯</td><td>53446</td><td>16914</td><td>36323</td><td>29629</td><td>32603</td><td>46076</td><td>20158</td><td>57235</td><td>40825</td><td>10417</td></tr>\n",
              "\t<tr><th scope=row>hsa-let-7c</th><td>15057</td><td>18857</td><td>21198</td><td>23882</td><td>47062</td><td>36790</td><td>21241</td><td>23683</td><td> 95837</td><td>41608</td><td>⋯</td><td>51912</td><td>19811</td><td>32768</td><td>22696</td><td>28238</td><td>28752</td><td>23028</td><td>62909</td><td>23682</td><td>22380</td></tr>\n",
              "\t<tr><th scope=row>hsa-let-7d</th><td> 1095</td><td> 1511</td><td>  602</td><td> 1008</td><td> 1654</td><td>  866</td><td>  883</td><td>  805</td><td>  1963</td><td> 1412</td><td>⋯</td><td> 2214</td><td>  902</td><td>  761</td><td>  837</td><td>  956</td><td> 1216</td><td>  610</td><td> 2103</td><td> 1287</td><td>  643</td></tr>\n",
              "</tbody>\n",
              "</table>\n"
            ],
            "text/markdown": "\nA data.frame: 6 × 550\n\n| <!--/--> | TCGA-EJ-7321-01A-31R-2262-13 &lt;int&gt; | TCGA-J4-A83M-01A-11R-A358-13 &lt;int&gt; | TCGA-EJ-5501-01A-01R-1579-13 &lt;int&gt; | TCGA-V1-A9OY-01A-11R-A41R-13 &lt;int&gt; | TCGA-EJ-5497-01A-02R-1579-13 &lt;int&gt; | TCGA-KK-A6E3-01A-21R-A30I-13 &lt;int&gt; | TCGA-HC-A6AS-01A-11R-A30I-13 &lt;int&gt; | TCGA-HC-8260-11A-01R-2262-13 &lt;int&gt; | TCGA-EJ-A8FO-11A-11R-A36B-13 &lt;int&gt; | TCGA-G9-6377-01A-11R-1964-13 &lt;int&gt; | ⋯ ⋯ | TCGA-H9-A6BX-01A-31R-A310-13 &lt;int&gt; | TCGA-2A-A8VO-01A-11R-A37H-13 &lt;int&gt; | TCGA-G9-7519-01A-11R-2262-13 &lt;int&gt; | TCGA-HC-8260-01A-11R-2262-13 &lt;int&gt; | TCGA-HC-A6AP-01A-11R-A30I-13 &lt;int&gt; | TCGA-EJ-A8FO-01A-21R-A36B-13 &lt;int&gt; | TCGA-YL-A8SQ-01B-11R-A37H-13 &lt;int&gt; | TCGA-J4-A83J-11A-11R-A36B-13 &lt;int&gt; | TCGA-M7-A723-01A-12R-A32J-13 &lt;int&gt; | TCGA-G9-6370-01A-11R-1788-13 &lt;int&gt; |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| hsa-let-7a-1 | 51384 | 37734 | 32491 | 43522 | 84251 | 23004 | 29078 | 25262 |  98606 | 85102 | ⋯ | 75660 | 22796 | 33406 | 31259 | 34031 | 47400 | 28772 | 62357 | 40116 | 22182 |\n| hsa-let-7a-2 | 51537 | 37846 | 32453 | 43443 | 84336 | 23173 | 29154 | 25285 | 100143 | 85016 | ⋯ | 75424 | 22665 | 33020 | 31219 | 33921 | 47397 | 28290 | 62452 | 39838 | 22410 |\n| hsa-let-7a-3 | 51277 | 37554 | 32658 | 43446 | 84391 | 23213 | 28906 | 25584 |  99437 | 84939 | ⋯ | 76109 | 22841 | 33212 | 31711 | 34118 | 47301 | 28696 | 62960 | 39901 | 22063 |\n| hsa-let-7b | 35001 | 28807 | 31775 | 27308 | 86219 | 21941 | 23735 | 26412 |  98270 | 43293 | ⋯ | 53446 | 16914 | 36323 | 29629 | 32603 | 46076 | 20158 | 57235 | 40825 | 10417 |\n| hsa-let-7c | 15057 | 18857 | 21198 | 23882 | 47062 | 36790 | 21241 | 23683 |  95837 | 41608 | ⋯ | 51912 | 19811 | 32768 | 22696 | 28238 | 28752 | 23028 | 62909 | 23682 | 22380 |\n| hsa-let-7d |  1095 |  1511 |   602 |  1008 |  1654 |   866 |   883 |   805 |   1963 |  1412 | ⋯ |  2214 |   902 |   761 |   837 |   956 |  1216 |   610 |  2103 |  1287 |   643 |\n\n",
            "text/latex": "A data.frame: 6 × 550\n\\begin{tabular}{r|lllllllllllllllllllll}\n  & TCGA-EJ-7321-01A-31R-2262-13 & TCGA-J4-A83M-01A-11R-A358-13 & TCGA-EJ-5501-01A-01R-1579-13 & TCGA-V1-A9OY-01A-11R-A41R-13 & TCGA-EJ-5497-01A-02R-1579-13 & TCGA-KK-A6E3-01A-21R-A30I-13 & TCGA-HC-A6AS-01A-11R-A30I-13 & TCGA-HC-8260-11A-01R-2262-13 & TCGA-EJ-A8FO-11A-11R-A36B-13 & TCGA-G9-6377-01A-11R-1964-13 & ⋯ & TCGA-H9-A6BX-01A-31R-A310-13 & TCGA-2A-A8VO-01A-11R-A37H-13 & TCGA-G9-7519-01A-11R-2262-13 & TCGA-HC-8260-01A-11R-2262-13 & TCGA-HC-A6AP-01A-11R-A30I-13 & TCGA-EJ-A8FO-01A-21R-A36B-13 & TCGA-YL-A8SQ-01B-11R-A37H-13 & TCGA-J4-A83J-11A-11R-A36B-13 & TCGA-M7-A723-01A-12R-A32J-13 & TCGA-G9-6370-01A-11R-1788-13\\\\\n  & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & ⋯ & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int>\\\\\n\\hline\n\thsa-let-7a-1 & 51384 & 37734 & 32491 & 43522 & 84251 & 23004 & 29078 & 25262 &  98606 & 85102 & ⋯ & 75660 & 22796 & 33406 & 31259 & 34031 & 47400 & 28772 & 62357 & 40116 & 22182\\\\\n\thsa-let-7a-2 & 51537 & 37846 & 32453 & 43443 & 84336 & 23173 & 29154 & 25285 & 100143 & 85016 & ⋯ & 75424 & 22665 & 33020 & 31219 & 33921 & 47397 & 28290 & 62452 & 39838 & 22410\\\\\n\thsa-let-7a-3 & 51277 & 37554 & 32658 & 43446 & 84391 & 23213 & 28906 & 25584 &  99437 & 84939 & ⋯ & 76109 & 22841 & 33212 & 31711 & 34118 & 47301 & 28696 & 62960 & 39901 & 22063\\\\\n\thsa-let-7b & 35001 & 28807 & 31775 & 27308 & 86219 & 21941 & 23735 & 26412 &  98270 & 43293 & ⋯ & 53446 & 16914 & 36323 & 29629 & 32603 & 46076 & 20158 & 57235 & 40825 & 10417\\\\\n\thsa-let-7c & 15057 & 18857 & 21198 & 23882 & 47062 & 36790 & 21241 & 23683 &  95837 & 41608 & ⋯ & 51912 & 19811 & 32768 & 22696 & 28238 & 28752 & 23028 & 62909 & 23682 & 22380\\\\\n\thsa-let-7d &  1095 &  1511 &   602 &  1008 &  1654 &   866 &   883 &   805 &   1963 &  1412 & ⋯ &  2214 &   902 &   761 &   837 &   956 &  1216 &   610 &  2103 &  1287 &   643\\\\\n\\end{tabular}\n",
            "text/plain": [
              "             TCGA-EJ-7321-01A-31R-2262-13 TCGA-J4-A83M-01A-11R-A358-13\n",
              "hsa-let-7a-1 51384                        37734                       \n",
              "hsa-let-7a-2 51537                        37846                       \n",
              "hsa-let-7a-3 51277                        37554                       \n",
              "hsa-let-7b   35001                        28807                       \n",
              "hsa-let-7c   15057                        18857                       \n",
              "hsa-let-7d    1095                         1511                       \n",
              "             TCGA-EJ-5501-01A-01R-1579-13 TCGA-V1-A9OY-01A-11R-A41R-13\n",
              "hsa-let-7a-1 32491                        43522                       \n",
              "hsa-let-7a-2 32453                        43443                       \n",
              "hsa-let-7a-3 32658                        43446                       \n",
              "hsa-let-7b   31775                        27308                       \n",
              "hsa-let-7c   21198                        23882                       \n",
              "hsa-let-7d     602                         1008                       \n",
              "             TCGA-EJ-5497-01A-02R-1579-13 TCGA-KK-A6E3-01A-21R-A30I-13\n",
              "hsa-let-7a-1 84251                        23004                       \n",
              "hsa-let-7a-2 84336                        23173                       \n",
              "hsa-let-7a-3 84391                        23213                       \n",
              "hsa-let-7b   86219                        21941                       \n",
              "hsa-let-7c   47062                        36790                       \n",
              "hsa-let-7d    1654                          866                       \n",
              "             TCGA-HC-A6AS-01A-11R-A30I-13 TCGA-HC-8260-11A-01R-2262-13\n",
              "hsa-let-7a-1 29078                        25262                       \n",
              "hsa-let-7a-2 29154                        25285                       \n",
              "hsa-let-7a-3 28906                        25584                       \n",
              "hsa-let-7b   23735                        26412                       \n",
              "hsa-let-7c   21241                        23683                       \n",
              "hsa-let-7d     883                          805                       \n",
              "             TCGA-EJ-A8FO-11A-11R-A36B-13 TCGA-G9-6377-01A-11R-1964-13 ⋯\n",
              "hsa-let-7a-1  98606                       85102                        ⋯\n",
              "hsa-let-7a-2 100143                       85016                        ⋯\n",
              "hsa-let-7a-3  99437                       84939                        ⋯\n",
              "hsa-let-7b    98270                       43293                        ⋯\n",
              "hsa-let-7c    95837                       41608                        ⋯\n",
              "hsa-let-7d     1963                        1412                        ⋯\n",
              "             TCGA-H9-A6BX-01A-31R-A310-13 TCGA-2A-A8VO-01A-11R-A37H-13\n",
              "hsa-let-7a-1 75660                        22796                       \n",
              "hsa-let-7a-2 75424                        22665                       \n",
              "hsa-let-7a-3 76109                        22841                       \n",
              "hsa-let-7b   53446                        16914                       \n",
              "hsa-let-7c   51912                        19811                       \n",
              "hsa-let-7d    2214                          902                       \n",
              "             TCGA-G9-7519-01A-11R-2262-13 TCGA-HC-8260-01A-11R-2262-13\n",
              "hsa-let-7a-1 33406                        31259                       \n",
              "hsa-let-7a-2 33020                        31219                       \n",
              "hsa-let-7a-3 33212                        31711                       \n",
              "hsa-let-7b   36323                        29629                       \n",
              "hsa-let-7c   32768                        22696                       \n",
              "hsa-let-7d     761                          837                       \n",
              "             TCGA-HC-A6AP-01A-11R-A30I-13 TCGA-EJ-A8FO-01A-21R-A36B-13\n",
              "hsa-let-7a-1 34031                        47400                       \n",
              "hsa-let-7a-2 33921                        47397                       \n",
              "hsa-let-7a-3 34118                        47301                       \n",
              "hsa-let-7b   32603                        46076                       \n",
              "hsa-let-7c   28238                        28752                       \n",
              "hsa-let-7d     956                         1216                       \n",
              "             TCGA-YL-A8SQ-01B-11R-A37H-13 TCGA-J4-A83J-11A-11R-A36B-13\n",
              "hsa-let-7a-1 28772                        62357                       \n",
              "hsa-let-7a-2 28290                        62452                       \n",
              "hsa-let-7a-3 28696                        62960                       \n",
              "hsa-let-7b   20158                        57235                       \n",
              "hsa-let-7c   23028                        62909                       \n",
              "hsa-let-7d     610                         2103                       \n",
              "             TCGA-M7-A723-01A-12R-A32J-13 TCGA-G9-6370-01A-11R-1788-13\n",
              "hsa-let-7a-1 40116                        22182                       \n",
              "hsa-let-7a-2 39838                        22410                       \n",
              "hsa-let-7a-3 39901                        22063                       \n",
              "hsa-let-7b   40825                        10417                       \n",
              "hsa-let-7c   23682                        22380                       \n",
              "hsa-let-7d    1287                          643                       "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "1881"
            ],
            "text/markdown": "1881",
            "text/latex": "1881",
            "text/plain": [
              "[1] 1881"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "550"
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            "text/markdown": "550",
            "text/latex": "550",
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              "[1] 550"
            ]
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          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "head(miR_meta)\n",
        "nrow(miR_meta)\n",
        "ncol(miR_meta)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 321
        },
        "id": "6QBX-dTT0Irt",
        "outputId": "8ea971d9-23f2-4d3d-dfe7-179aa806edc6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table class=\"dataframe\">\n",
              "<caption>A data.frame: 6 × 2</caption>\n",
              "<thead>\n",
              "\t<tr><th></th><th scope=col>cases</th><th scope=col>sample_type</th></tr>\n",
              "\t<tr><th></th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
              "</thead>\n",
              "<tbody>\n",
              "\t<tr><th scope=row>1</th><td>TCGA-EJ-7321-01A-31R-2262-13</td><td>Primary Tumor</td></tr>\n",
              "\t<tr><th scope=row>2</th><td>TCGA-J4-A83M-01A-11R-A358-13</td><td>Primary Tumor</td></tr>\n",
              "\t<tr><th scope=row>3</th><td>TCGA-EJ-5501-01A-01R-1579-13</td><td>Primary Tumor</td></tr>\n",
              "\t<tr><th scope=row>4</th><td>TCGA-V1-A9OY-01A-11R-A41R-13</td><td>Primary Tumor</td></tr>\n",
              "\t<tr><th scope=row>5</th><td>TCGA-EJ-5497-01A-02R-1579-13</td><td>Primary Tumor</td></tr>\n",
              "\t<tr><th scope=row>6</th><td>TCGA-KK-A6E3-01A-21R-A30I-13</td><td>Primary Tumor</td></tr>\n",
              "</tbody>\n",
              "</table>\n"
            ],
            "text/markdown": "\nA data.frame: 6 × 2\n\n| <!--/--> | cases &lt;chr&gt; | sample_type &lt;chr&gt; |\n|---|---|---|\n| 1 | TCGA-EJ-7321-01A-31R-2262-13 | Primary Tumor |\n| 2 | TCGA-J4-A83M-01A-11R-A358-13 | Primary Tumor |\n| 3 | TCGA-EJ-5501-01A-01R-1579-13 | Primary Tumor |\n| 4 | TCGA-V1-A9OY-01A-11R-A41R-13 | Primary Tumor |\n| 5 | TCGA-EJ-5497-01A-02R-1579-13 | Primary Tumor |\n| 6 | TCGA-KK-A6E3-01A-21R-A30I-13 | Primary Tumor |\n\n",
            "text/latex": "A data.frame: 6 × 2\n\\begin{tabular}{r|ll}\n  & cases & sample\\_type\\\\\n  & <chr> & <chr>\\\\\n\\hline\n\t1 & TCGA-EJ-7321-01A-31R-2262-13 & Primary Tumor\\\\\n\t2 & TCGA-J4-A83M-01A-11R-A358-13 & Primary Tumor\\\\\n\t3 & TCGA-EJ-5501-01A-01R-1579-13 & Primary Tumor\\\\\n\t4 & TCGA-V1-A9OY-01A-11R-A41R-13 & Primary Tumor\\\\\n\t5 & TCGA-EJ-5497-01A-02R-1579-13 & Primary Tumor\\\\\n\t6 & TCGA-KK-A6E3-01A-21R-A30I-13 & Primary Tumor\\\\\n\\end{tabular}\n",
            "text/plain": [
              "  cases                        sample_type  \n",
              "1 TCGA-EJ-7321-01A-31R-2262-13 Primary Tumor\n",
              "2 TCGA-J4-A83M-01A-11R-A358-13 Primary Tumor\n",
              "3 TCGA-EJ-5501-01A-01R-1579-13 Primary Tumor\n",
              "4 TCGA-V1-A9OY-01A-11R-A41R-13 Primary Tumor\n",
              "5 TCGA-EJ-5497-01A-02R-1579-13 Primary Tumor\n",
              "6 TCGA-KK-A6E3-01A-21R-A30I-13 Primary Tumor"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "550"
            ],
            "text/markdown": "550",
            "text/latex": "550",
            "text/plain": [
              "[1] 550"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "2"
            ],
            "text/markdown": "2",
            "text/latex": "2",
            "text/plain": [
              "[1] 2"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "## Rename conditions\n",
        "miR_meta$sample_type <- gsub(\"Primary solid Tumor\", \"Tumor\", miR_meta$sample_type)\n",
        "miR_meta$sample_type <- gsub(\"Solid Tissue Normal\", \"Normal\", miR_meta$sample_type)\n",
        "miR_meta$sample_type <- as.factor(miR_meta$sample_type)\n",
        "levels(miR_meta$sample_type)\n",
        "colnames(miR_meta) <- c(\"cases\", \"Condition\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "id": "7jMt21l5q6Lf",
        "outputId": "eec6510a-5587-47b1-b51a-75076c23a30a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<style>\n",
              ".list-inline {list-style: none; margin:0; padding: 0}\n",
              ".list-inline>li {display: inline-block}\n",
              ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
              "</style>\n",
              "<ol class=list-inline><li>'Normal'</li><li>'Primary Tumor'</li></ol>\n"
            ],
            "text/markdown": "1. 'Normal'\n2. 'Primary Tumor'\n\n\n",
            "text/latex": "\\begin{enumerate*}\n\\item 'Normal'\n\\item 'Primary Tumor'\n\\end{enumerate*}\n",
            "text/plain": [
              "[1] \"Normal\"        \"Primary Tumor\""
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "write.table(miR_meta, \"/content/miR_meta.txt\", quote = F, sep = \"\\t\")"
      ],
      "metadata": {
        "id": "_A4V0dZXsezE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "nrow(miR_df)\n",
        "ncol(miR_df)\n",
        "nrow(miR_meta)\n",
        "ncol(miR_meta)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 86
        },
        "id": "eNA4P55l0XCa",
        "outputId": "408b6558-a233-4908-cb0c-46c9000d377e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "1881"
            ],
            "text/markdown": "1881",
            "text/latex": "1881",
            "text/plain": [
              "[1] 1881"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "550"
            ],
            "text/markdown": "550",
            "text/latex": "550",
            "text/plain": [
              "[1] 550"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "550"
            ],
            "text/markdown": "550",
            "text/latex": "550",
            "text/plain": [
              "[1] 550"
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "2"
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            "text/markdown": "2",
            "text/latex": "2",
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              "[1] 2"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "## tidy vars\n",
        "rm(mirna_query)\n",
        "rm(subset)\n",
        "rm(number_cols)\n",
        "rm(metastatic_key)"
      ],
      "metadata": {
        "id": "_9IAtxihrN4M"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "miR_dds <- DESeqDataSetFromMatrix(miR_df, colData = miR_meta, design = ~ Condition)\n",
        "miR_dds$Condition <- relevel(miR_dds$Condition, ref = \"Normal\")\n",
        "miR_dds <- DESeq(miR_dds)\n",
        "resultsNames(miR_dds)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "VbJdpmxkraZu",
        "outputId": "b75dbdc1-3957-4fde-f9ce-a9e3118585b9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "  Note: levels of factors in the design contain characters other than\n",
            "  letters, numbers, '_' and '.'. It is recommended (but not required) to use\n",
            "  only letters, numbers, and delimiters '_' or '.', as these are safe characters\n",
            "  for column names in R. [This is a message, not a warning or an error]\n",
            "\n",
            "estimating size factors\n",
            "\n",
            "  Note: levels of factors in the design contain characters other than\n",
            "  letters, numbers, '_' and '.'. It is recommended (but not required) to use\n",
            "  only letters, numbers, and delimiters '_' or '.', as these are safe characters\n",
            "  for column names in R. [This is a message, not a warning or an error]\n",
            "\n",
            "estimating dispersions\n",
            "\n",
            "gene-wise dispersion estimates\n",
            "\n",
            "mean-dispersion relationship\n",
            "\n",
            "  Note: levels of factors in the design contain characters other than\n",
            "  letters, numbers, '_' and '.'. It is recommended (but not required) to use\n",
            "  only letters, numbers, and delimiters '_' or '.', as these are safe characters\n",
            "  for column names in R. [This is a message, not a warning or an error]\n",
            "\n",
            "final dispersion estimates\n",
            "\n",
            "  Note: levels of factors in the design contain characters other than\n",
            "  letters, numbers, '_' and '.'. It is recommended (but not required) to use\n",
            "  only letters, numbers, and delimiters '_' or '.', as these are safe characters\n",
            "  for column names in R. [This is a message, not a warning or an error]\n",
            "\n",
            "fitting model and testing\n",
            "\n",
            "  Note: levels of factors in the design contain characters other than\n",
            "  letters, numbers, '_' and '.'. It is recommended (but not required) to use\n",
            "  only letters, numbers, and delimiters '_' or '.', as these are safe characters\n",
            "  for column names in R. [This is a message, not a warning or an error]\n",
            "\n",
            "-- replacing outliers and refitting for 59 genes\n",
            "-- DESeq argument 'minReplicatesForReplace' = 7 \n",
            "-- original counts are preserved in counts(dds)\n",
            "\n",
            "estimating dispersions\n",
            "\n",
            "  Note: levels of factors in the design contain characters other than\n",
            "  letters, numbers, '_' and '.'. It is recommended (but not required) to use\n",
            "  only letters, numbers, and delimiters '_' or '.', as these are safe characters\n",
            "  for column names in R. [This is a message, not a warning or an error]\n",
            "\n",
            "fitting model and testing\n",
            "\n",
            "  Note: levels of factors in the design contain characters other than\n",
            "  letters, numbers, '_' and '.'. It is recommended (but not required) to use\n",
            "  only letters, numbers, and delimiters '_' or '.', as these are safe characters\n",
            "  for column names in R. [This is a message, not a warning or an error]\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<style>\n",
              ".list-inline {list-style: none; margin:0; padding: 0}\n",
              ".list-inline>li {display: inline-block}\n",
              ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
              "</style>\n",
              "<ol class=list-inline><li>'Intercept'</li><li>'Condition_Primary.Tumor_vs_Normal'</li></ol>\n"
            ],
            "text/markdown": "1. 'Intercept'\n2. 'Condition_Primary.Tumor_vs_Normal'\n\n\n",
            "text/latex": "\\begin{enumerate*}\n\\item 'Intercept'\n\\item 'Condition\\_Primary.Tumor\\_vs\\_Normal'\n\\end{enumerate*}\n",
            "text/plain": [
              "[1] \"Intercept\"                         \"Condition_Primary.Tumor_vs_Normal\""
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "## DESeq2 results\n",
        "miR_res <- results(miR_dds, alpha = 0.05, name = \"Condition_Primary.Tumor_vs_Normal\")\n",
        "summary(miR_res)\n",
        "miR_res_df <- as.data.frame(miR_res)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ilLNwUUUrxJL",
        "outputId": "b65f7f9a-8072-4764-cb46-39174842b40c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "out of 1513 with nonzero total read count\n",
            "adjusted p-value < 0.05\n",
            "LFC > 0 (up)       : 169, 11%\n",
            "LFC < 0 (down)     : 201, 13%\n",
            "outliers [1]       : 0, 0%\n",
            "low counts [2]     : 724, 48%\n",
            "(mean count < 0)\n",
            "[1] see 'cooksCutoff' argument of ?results\n",
            "[2] see 'independentFiltering' argument of ?results\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "miR_upreg <- get_upregulated(miR_res)\n",
        "miR_downreg <- get_downregulated(miR_res)"
      ],
      "metadata": {
        "id": "bfOauFNQ1koT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "miR_upreg$miRNA_id <- rownames(miR_upreg)\n",
        "miR_downreg$miRNA_id <- rownames(miR_downreg)"
      ],
      "metadata": {
        "id": "MYl147e32Hlf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "miR_counts <- counts(miR_dds, normalized = T)\n",
        "write.table(miR_counts, \"/content/miR_norm.counts.txt\", quote = F, sep = \"\\t\")"
      ],
      "metadata": {
        "id": "O9QGABDB1o4p"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "write.table(miR_upreg, \"/content/miR_upreg.txt\", quote = F, sep = \"\\t\")\n",
        "write.table(miR_downreg, \"/content/miR_downreg.txt\", quote = F, sep = \"\\t\")"
      ],
      "metadata": {
        "id": "mhR7jdox1ylU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "with(miR_res_df, plot(log2FoldChange, -log10(padj), pch=20, main=\"Volcano plot\", cex=1.0, xlab=bquote(~Log[2]~fold~change), ylab=bquote(~-log[10]~P~value)))\n",
        "\n",
        "with(subset(miR_res_df, padj<0.05 & abs(log2FoldChange)>2), points(log2FoldChange, -log10(padj), pch=20, col=\"blue\", cex=0.5))\n",
        "\n",
        "abline(v=0, col=\"black\", lty=3, lwd=1.0)\n",
        "abline(v=-2, col=\"black\", lty=4, lwd=2.0)\n",
        "abline(v=2, col=\"black\", lty=4, lwd=2.0)\n",
        "abline(h=-log10(max(miR_res_df$pvalue[miR_res_df$padj<0.05], na.rm=TRUE)), col=\"black\", lty=4, lwd=2.0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 437
        },
        "id": "Xl49m6aNDZdL",
        "outputId": "7a4da581-e80c-4537-8b57-f2c83b93425d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Plot with title “Volcano plot”"
            ],
            "image/png": 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J5AXcmmsBNCODg4TJ48efLkycXFxRcvXjRMnnB3dw8ICHBwcLi3z9Tr9fv27Sst\nLa1mm19++eXePhywNtwlXy5onpAL9inUlZwKOyMnJ6egoCAhRGlpaWZm5sWLF5s1a9a8efN7\n+KisrKy+fftWed1eBXq9/h4+HwAsEM0TgFLJ5lD8P//5z927d5dfSUxM9PHx6dq1a+/evVu0\naNGlS5ejR4/W9WNbtGhRXFysr9Znn30mhFCpVCb7wwCApGieAJRKNoXd9OnTd+zYYXy6bdu2\n2NjYoqKiwYMHv/zyy2FhYT/++OPjjz9+9uxZCUMCgCxoNJrw8HCpUwAwPVmeihVCTJ482cPD\nIz09vW3btoaVDRs2PPfcc+++++5//vMfabMBgIWjeQJQKlnu2FevXj1z5szEiRONVZ0QYsiQ\nIc8++6xGo5EwGADIAs0TgFLJsrArLi4WQpSv6gzat29/5coVKRIBgJzQPAEolSwLO19fXw8P\nj+zs7Arrf/zxR4MGDSSJBAAyQvMEoFRyKuwuXLiQkZHx22+/5efnT5gwYdmyZeVv7XPq1Klv\nvvkmLCxMwoQAIAs0TwBKJafmiTVr1qxZs6b8yvbt24cOHSqE+Prrr8ePH//nn39Onz5donQA\nhJ2dnfEnLBnNE3LBPoW6ks1/K19++eWNcm7evHnjxo1GjRoZXr1x40bDhg3Xrl0bEhIibU7A\nmsXHx69evXrMmDFSB0ENaJ6Qi4SEhI0bN44cOVLqIJANlTIGKhQWFrq4uNTTL6CJiYmxsbEF\nBQVubm718fkAAEBGSktLHR0dU1NTu3fvLnWWihRyKN7NzY3TCgBQSzRPAEpFMQQAVofmCUCp\nKOwAwOrQPAEoFTs2AJPR6XS5ublSp0DNaJ6QC61Wy433UScUdgBMJjIyUq1Wr1q1SuogqAGT\nJ+Ri4MCBarU6KSlJ6iCQDQo7ACaTmpqq1+vT0tKkDoIa0DwhF6mpqWVlZenp6VIHgWxQ2AGA\n1aF5AlAqCjsAJsNd8uWC5gm5YJ9CXbFjAzCZ+Pj4kJAQJk9YPpon5CIhISE0NJTJE6g9hUye\nqFdMngAAAEZMngAAWBCaJwClorADAKtD8wSgVBR2AGB1aJ4AlIodG4DJMHlCLmiekAsmT6Cu\nKOwAmAyTJ+SCyRNyweQJ1BWFHQCTYfKEXNA8IRdMnkBdUdgBgNWheQJQKgo7ALA6NE8ASsWO\nDQBWh+YJQKko7ADA6tA8ASgVhR0AWB2aJwClorADAKtD8wSgVBR2AGB1aJ4AlC58tLwAACAA\nSURBVIodGwCsDs0TgFJR2AGA1aF5AlAqCjsAJhMYGGj8CUtG84RcGPamgIAAqYNANuykDgBA\nOZKTkzMyMvr16yd1ENRAo9FER0fn5eVJHUSuzp8/n56ebmtr+9hjj3l7e9//B966dSslJeXG\njRtdunQJDg42rms0mszMzL59+97/V8BKUNgBMBkvL6+IiAipU6BmNE/cj3nz5r311lulpaVC\nCDc3t0WLFo0ePfp+PjAlJSUqKury5cuGpy+//PKSJUtUKpUQQq1Wq9Xq+88M68GODQBWh+aJ\ne7Z37974+HhDVSeEKCwsHD9+/KlTp+75A2/duvX8888bqzohRGJi4tKlS+83KKwVhR0AWB2a\nJ+7Z1q1bK6yUlJRoNJp7/sBDhw7l5uZWWNyyZcs9fyCsHIUdAFgdmifu2fXr12u5KNUHwspR\n2AEwGY1GM2HChJycHKmDoAZMnrhnXbp0qeViLXXu3LmaD9y6dWtcXFzlQ3rA3VDYATCZ2NjY\nJUuWLFiwQOogqAHNE/ds7NixnTp1Kr/Sv3//AQMG3PMHtmzZcvLkyeVXfHx83nrrLcPjmJiY\nRYsWLVq06J4/H9aGrlgAJlNUVGT8CUtG88Q9c3R03Lt37/z581NSUuzs7J566qmJEycaOljv\n2fz58zt16vTNN9/k5+eHhIS88cYbxluosE+hrijsAKAKBw8e3Lt3r4uLS9++fYOCgqSOY2I0\nT9wPV1fXGTNmzJgxw1QfqFKpRo0aNWrUKFN9IKwZhR0AkwkMDMzNzVXA5InY2NjExETDYwcH\nh3//+9+xsbHSRjItrVZ7+vTp8jfChWUKDAw8fvw4kydQexR2AExGGZMn1q1bZ6zqhBClpaWT\nJk3q3bv3gw8+KGEq02LyhFwweQJ1RWEHwGSUMXmi8j3JSktLU1JSlFTY0TwhF0yeQF2xYwPA\n31R5obrCrl6neQJQKgo7APib7t27V1589NFHzZ+k/tA8ASgVhR0A/M348eMrlHGvvPJKaGio\nVHnqA5MnAKWisANgMsqYPOHg4JCSkvLpp59GRka+8MIL69evX7x4sdShTIzJE3LB5AnUFc0T\nAEwmNjY2KyvLxcVl3rx5Ume5Lw4ODhMnTpw4caLUQeoLzRNyERMTk5ub6+npOWfOHKmzQB7Y\nsQGYDHfJlwuaJ+SCfQp1RWEHAFaH5glAqSjsAMDq0DwBKBWFHQBYHZonAKWieQIArA7NE/Xh\nxo0bn3/++cmTJ/39/ceOHduiRQupE8EaUdgBgNWhecLkfv/9927duhnvSzJv3rwtW7b06dNH\n2lSwQvzGBgBWh+YJk5s0aVL5u80VFxePHTtWr9dLGAnWicIOAKwOzROmpdfr9+/fX2ExJyfn\n3LlzkuSBNaOwAwCrQ/OEaalUKju7Ki5tsre3N38YWDkKOwAmY/i3rcp/4WBRaJ4wuV69elVY\nadWqVUBAwH1+LPsU6oodG4DJxMfHh4SEjBkzRuogqAHNEyb373//u1WrVsanjRo1Wrly5f1/\nbEJCQmho6MiRI+//o2AlVFzaWaPExMTY2NiCggI3NzepswAALFRxcfGaNWtOnTrl5+f3/PPP\nN2nSpDbv2rRp0+eff/7HH3+0a9fuzTffbNeuXX3nxP0rLS11dHRMTU3t3r271Fkq4uguAFgd\nrVZ7+vTp4OBgqYMoipOT09ixY+v0lgULFrz22muGx5mZmUlJSWlpaZ06daqHdLAWnIoFAKtD\n84QlKC4ufvPNN8uvlJSUTJs2Tao8UAYKOwCwOjRPWIITJ04UFxdXWPzxxx8lCQPFYMcGYDI6\nna78PVphsWiesARVXoRXYVGr1V65csVciaAEFHYATCYyMlKtVq9atUrqIKgBkycsQUBAQOfO\nnSssDh48uPzTgQMHqtXqpKQkM+aCvFHYATCZ1NRUvV6flpYmdRDUgMkTFmLNmjXt27c3Ph06\ndOisWbPKb5CamlpWVpaenm7uZJAtumIBwOpoNJro6Oi8vDypg1i7oKCgI0eOpKamXrp0qV27\ndh06dJA6EWSvhsKuoKDgwoULTZs2bdiwoXkCAZAv7pIvFzRPWI4LFy589tln+/fvd3R0HDhw\n4MyZM8v/g8s+hbq66469Z8+eLl26uLu7t2/f/sCBA4bFZ5555ocffjBXNgAyw+QJuaB5wkJc\nvXq1R48ea9euzc7OPnv27MKFCwcOHKjVao0bMHkCdVV1YXfo0KG+ffuePn26X79+xsWrV68e\nPnw4IiKCZmwAVZo0adKhQ4cqXw8OS0PzhIVYsmTJpUuXyq/s379fo9EYnyYkJBw4cIBTtKi9\nqo/uzpkzx8fHJzU11c7OTq1WGxabNGmSmZkZEhLyzjvvbNq0yYwh/0av12dlZZ07d66goEAI\n4eHhERQU5O/vL1UeAJAdJk9YiGPHjlVe/PnnnyMiIswfBspQdWF34MCBqVOn+vn5Xb58ufy6\nl5dXbGzs3LlzzZKtovz8/HfffXflypWVb+oTEBAQExMzdepUZ2dnSbIBgIzQPGEh/Pz8Ki9y\nqAL3o+rC7ubNm3f7D0utVhcWFtZnpKpdunQpLCwsKysrKCgoIiIiMDDQ1dVVCHHr1q2zZ8/u\n2bNnxowZSUlJu3fvbtSokfnjAYCM0DxhIYYPH75o0aI7d+4YV5o0adKnTx8JI0Huqi7sfHx8\nfvnllypf2rt3r6+vb31Gqtr06dOzs7PXrVs3bNiwyq/qdLrExMS4uLjZs2cvXLjQ/PEACCF0\nOt21a9e8vb2lDoIa0DxhIbp16/bFF1+8+uqr+fn5QoiWLVsuX77cy8vLuIFWq71+/Xr5FaB6\nVf/GFhERsXjx4p9++qn8Yn5+/ltvvfXll18OGDDALNn+Ztu2bdHR0VVWdUIIW1vbCRMmREZG\nbtiwwczBABgxeUIuaJ6wHKNHj7548eKBAweOHj166tSpHj16lH+VyROoq6oLu9mzZ7u5uYWG\nhhpquGnTpj3yyCNqtfq9994LCAiYMWOGeUMKIUReXl7Lli2r36Zt27bMqQQkxOQJuWDyhEVx\ndXUNDQ19+OGHK9+vjskTqKuqCzsfH5+MjIyXXnrp/PnzQoijR48ePXq0QYMGr7zyyuHDhyU5\nz+Lr65uZmVn9NkeOHJHkNDEAyItGowkPD5c6BQDTu+vFs15eXosXL7569erly5fPnDlz+fLl\nq1evLl68WKoz/YMGDfr222/nzZtXUlJS+dXbt2/PnDlz8+bNw4cPN382AJAXmicApaphSolK\npfL29raES6FnzZq1b9+++Pj4OXPmdO3a1d/f383NTa/XFxYWnj9//tChQ0VFReHh4W+//bbU\nSQHA0tE8AShV1YXdk08+Wc17SktL9+7dWz957qphw4bp6emLFi1asWJFSkqKTqczvmRvb9+5\nc+dx48aNGzfO1tbWzMEAQHZongCUqurCrpqBsA0aNGjQoEG95amOg4PD5MmTJ0+eXFxcfPHi\nRcPkCXd394CAAAcHh3v+2GPHjpWWllazwYULF+75wwHAAjF5wgoVFhbOnTs3JSXFzs6uX79+\nkyZNcnR0lDoUTK/qwq78zRINSktLs7Kyli9ffujQoeTk5PoPVh0nJ6egoCDj01u3bs2YMeOF\nF15o06ZNXT/q7NmzHTt2LCsrq3FLvV5f1w8HAMvE5AlrU1JS8thjjx05kinEY0IU79qV8P33\n3+/YsYNLLZWn6v9H7SpxcXFp167d3Llzu3fvnpCQYOaU1bt169YHH3zw22+/3cN7W7ZseevW\nrevV+uijj4QQKpXK1MEBQBo0T1ib5cuXHzlyRIgNQuwWIlWIxJ07d0p+mAb1oYbmicqeffbZ\noUOHLlmypD7SVCMmJuZuLxUVFQkhPvnkk02bNgkhvvjiizp9squrq2E62d24uLjU6QMBwMLR\nPGEJDh069MEHH/z6668BAQFxcXERERH1910ZGRlCNBXi2b8Wxgnxj4yMjGeffba6t0GG6lzY\nFRQU3Lhxoz6iVG/ZsmXVb6DRaAwP6lrYATCtw4cPjxw5MjAw8KWXXmrevLnUcVAFmickt3v3\n7r59+2q1WiHEiRMntm/f/sUXX7z44ov19HWNGzcW4oYQfwrhLIQQIk+I0saNG9fT10FCVR+K\nv1GVq1evpqSkvP7665L8TT158mRbW9uOHTt+9913+X934sQJIcTatWsNT82fDYCB4T6XGRkZ\nX3/99fvvvx8cHLxnzx6pQ6EKTJ6QXHx8vKGqK79S+WLuwMBAIURAQMB9ft3AgQOFuC3ECCFO\nCPGTEM87Ojr079//Pj8WFqjqwq5RVby8vHr16nX06NE33njDzCmFEB999NGBAweEEE899dSb\nb76pUqka/sXd3V0I4erqanhq/mwADCq0zBcXF1dzEQUkxOQJaWm12mPHjlVYzM/Pz8rKqrCo\n0Wi2b98eFxd3n98YFha2YMECR8ftQrQXorObW8bSpUvvoeMQlq/qU7GGEbEV2Nvbq9XqoUOH\nPvHEE/WcqmpdunQ5fPjw/PnzZ8+evXnz5o8//njo0KGSJAFQmVar/emnnyos/vbbb5cvX/bx\n8ZEkEu6G5glp2dnZeXp6Xr58ufyijY3NAw88UGFLtVqtVqtN8qWvvvrqc889l5aWZmtrGx4e\nLtUcKdS3qgu7rVu3mjlHLdnZ2SUkJDz33HMvv/zyc889N3DgwEWLFtGvClgCGxsbe3v74uLi\n8osqlep+bjOJekLzhOSGDBmyePHi8itPPvmk4QRU/fHz84uMjKzXr4Dk/lfYZWdn1/5tfn5+\n9RCmtlq2bLlz587ly5dPmTIlODh4ypQpEoYBYGBjY9OrV68tW7aUX3zkkUc8PT2lioS7oXlC\nch9++OGFCxeMh1FCQ0O//PJLaSNBGf5X2Pn7+9f+bZZwt94XXnghIiJi0qRJs2fPljoLACGE\nWLx48fHjx8+dO2d46uPjs3z5ckkToWpMnpCcq6trcnLyzz///OuvvwYGBoaEhHD2CSbxv8Ju\n+PDhEua4N15eXmvWrBk9evQPP/zQsmVLqeMA1u7EiRNPPvlkcHDwtWvXAgMDIyMj6/vUEu4N\nkycsxEMPPfTQQw9Vs8HWrVu/++676dOne3t7my0VZO1/hd3atWtr84bbt28bhrRajqeeeuqp\np56SOgUAERsbm5WVNWXKlHnz5kmdBdWheUIuYmJicnNzPT0958yZI3UWyEOdd+zNmzd36tSp\nPqIAkDvDGBjDT1gymifkgn0KdXXXyRPXrl1bu3bt77//Xv4OisXFxVu3bi0sLDRLNgBAvaB5\nAlCqqgu733//vWvXrlevXq3iDXZ206dPr+dUAGQpMDAwNzfXcK98WDKaJ+QiMDDw+PHj9z95\nAtaj6sLu7bffLi4u/vTTT9u2bfvEE0988cUXfn5+KSkpK1euXLZsWb9+/cycEoAsJCcnZ2Rk\n8FeE5aN5Qi40Gk1mZmbfvn2lDgLZqLqw27dv38SJEydOnGi412i7du26devWr1+/4cOHP/HE\nE1u2bAkLCzNvTgAy4OXlFRERIXUK1IzmCbkw4eQJWImqC7tLly61aNFCCGHY80tLSw3rHTt2\nnDhx4syZM3fu3Gm2iAAA07LC5omzZ8/u3LmztLQ0PDy8Y8eOd9tMp9MdPnz40qVLwcHBrVu3\nNmdCwCSqLuwaNGiQm5srhHBwcHBzczt37txjjz1meCk4OPjjjz82X0AAkFRZWdm6desOHTrU\nsGHDIUOGtG/fXupEJmBtzRNLlix59dVXDQcpbG1tJ02aNH/+/MqbnTt3bujQoUePHjU8jYqK\n+uqrr+zt7c2aFbg/VR+KDw8P/+yzz1JSUoQQHTp0WLRokbETdteuXY6OjmbLBwASKikp6dmz\nZ1RU1IIFC2bOnPnII4988cUXUocyAa1We/LkSalTmMnJkycnTZpkPPWk0+k++uij5OTkyluO\nGDHCWNUJIdasWcPd4yA7VRd2b775Zl5e3tSpU4UQL730UkZGRnBw8JAhQx555JGlS5f26dPH\nvCEByINGo5kwYUJOTo7UQUxm/vz5+/fvNz7VarX/93//d+nSJQkjmYRGowkPD5c6hZns2rXr\nzp07FRZ37NhRYeXixYsHDx6ssJiUlFSPyWph69atcXFxhnNoQG1UfSq2a9eu+/fvP3TokBDi\nhRdeOHPmzMKFCzdu3KhSqZ555pmFCxeaNyQAeTBMnnBxcVHM5AnDiYvyiouLDxw4MHjwYCni\nmIxVNU9Uee/VyotXrlypvFmVi+bE5AnU1V1vUNy5c+fOnTsLIVQq1XvvvTdjxozLly97e3s7\nOzubMR4AOVHeXfLLysoqL+r1evMnMS2rap549NFHa7MYHBzs6OhYUlJSfvGRRx6px2S1oLx9\nCvWt6t/YevbsuXTp0hs3bhhXnJycmjVrRlUHwKr07Nmzwoqjo2O3bt0kCWNCVtU80bNnz+jo\n6PIr3bt3HzduXIXNnJ2d33nnnfIrDg4O7733Xr3nA0yq6sJu375948eP9/HxGTp06MaNG43X\nnAKAVYmPjw8NDTU+tbW1XbBgga+vr4SRTMKqmieEEF999dXq1aujoqKGDh368ccf7969u8pe\n1/j4+G+++eaJJ55o27btsGHDDh48GBISYv60wP2o+lTshQsX1q9fv27duo0bN27YsKFRo0bD\nhg0bNWpUjx49VCqVmSMCgFScnJz279//9ddfHz582N3dfdiwYdXcAk1GrG3yhEqlGjFixIgR\nI2rcMjIyMjIy0gyRgHpSdWHn5+f36quvvvrqq9nZ2YYKb+nSpZ9//nlgYODIkSNHjRrVtm1b\nMwcFAEnY2dmNHj169OjRUgcxJatqngCsSg07tqHCS0tLu3DhwoIFCwIDAz/88EPmRgOArFlV\n8wRgVWr7G5urq2vjxo39/Pzc3d3rNRAAoL5ZVfMEYFXuersTgytXrmzatCkpKWnXrl1ardbD\nw2PIkCFRUVHmCQcAqA9arfb06dOcfgGUp+rCLicnZ+PGjUlJSfv27dPpdM7OzoMGDRoxYkRE\nRATzxABA7qyteQKwHlUXdv7+/nq93s7Ork+fPlFRUYMHD27QoIGZkwGQHTs7O+NPWDKaJ+SC\nfQp1VfWOHRYWtmjRoj/++GP79u2jR4+mqgNQG/Hx8SEhIWPGjJE6yN8kJyd36tTJwcEhMDBw\nzpw5FUYLWCeaJ+QiISEhNDR05MiRUgeBbKgUMBunviUmJsbGxhYUFLi5uUmdBUDd7Nixo3//\n/uVXJkyYsGjRIqnyAFCA0tJSR0fH1NTU7t27S52lIg7FA5CHgoKCBQsWvPTSSzNnzjx37lwt\n3/X+++9XWFmyZEl+fr6p08mMtU2eAKwHp+0B6RUWFl68eLFFixY0J91NTk5OaGhoTk6O4emH\nH364cePGCofiqlS5fNHr9SdPngwLCzN9SvmgeQJQKo7YAVIqLCwcN26ch4dHcHCwh4fHW2+9\nVVZWJnUoSzR58mRjVSeEKC4uHjt2bG3+t6rybm3Nmzc3YTY5onkCUCp2bEBKcXFxX365sqxs\nshBfl5Q8/95773344YdSh7p3Op0uNze3Pj553759FVYuX758+vTpGt84bty4Civ9+/f39fU1\nWTJ5onlCLrRa7ZUrV6ROATmhsAMk8+eff65evVqIfwgxT4goIZYLEfHFF19IneveRUZGqtXq\nVatWmfyTbW1ta7lYQWxs7Jw5c5ydnQ1PPTw8Dhw40K1bt02bNpk4oqwweUIuBg4cqFark5KS\npA4C2aCwAyRz4cIFrVYrRJdyayHnz5/X6XSSZbo/qamper0+LS3N5J/8+OOPV1jx9/dv1apV\nbd47ffr0vLy8KVOmCCFu3rx548aNgwcPDh48+NtvvzV5TrmgeUIuUlNTy8rK0tPTpQ4C2aCw\nAyTTokULJycnIXb8taAVQvPggw/W5kCUtfnoo4/Kl3ENGjRYuXKlSqWq5dsdHR0///zzCosz\nZ840WT650Wg04eHhUqcAYHp0xQKSsbe3f+2119577z0h8oXoLIRGiPQ33lghda57V393yffy\n8jp27NjXX3994sQJX1/fESNGqNXq2r/9/PnzBQUFFRZ//fXX0tJSBwcHkyaVB5on5ILJE6gr\n/lsBpDR79uwGDRp8+umnf/yR3KpVq7feWh4dHS11qHsXHx+/evXqepo84eTkVLkTopbUarW9\nvf2dO3fKL/r4+FhnVSdonpCPhISEjRs3MnkCtcfkiZoxeQJmoNPpOANbr6KiotauXVt+5fXX\nX//ggw+kygNAvpg8AaAGVHX1bcmSJYMHDzY8trGxefHFF9955x1pI0mI5glAqao4FVtSUpKZ\nmVlUVNSmTRsfHx/zZwIAk2vYsOGGDRuys7PPnz8fFBTk5eUldSIpMXkCUKqKR+y++uorHx+f\n0NDQXr16Ga5QrnzFMQDIlJ+fX1hYmJVXdYLmCUC5/nbEbu/evWPHjrW1te3Xr1/jxo0PHDiw\nZs2aP//8c+PGjVLlAyAjOp3u2rVr3t7eUgdBDRTZPJGenv7555//8ccfbdu2nTJlir+/v9SJ\nTECr1V6/fp1fRVB7f/uNbd68eSqVateuXd99993q1at/+eWXwYMHb9q06fjx41LlAyAj9Td5\nAqalvMkTq1at6t69+/LlyzUazb///e/g4OBffvlF6lAmwOQJ1NXfCrsDBw707dvXeNdKBweH\nWbNmCSH27t1r/mQAZKf+Jk/AtBTWPKHVauPi4sqvFBYWGmaNyB2TJ1BXfyvs8vLyHnzwwfIr\nhqdcYAsASqKwyROnTp26efNmhcWDBw9KEgaQ1t8Ku7KyMuOobAMnJychhHwnVwIAKlNY84S7\nu3stFwHFU86ODQCoJYU1TwQEBLRv377C4lNPPSVJGEBaFHYAYHWU1zzx9ddfBwQEGJ+GhYUx\nVgTWqeINivfv329omCgvJSWlwmLlbQAAcqHVak+fPh0cHCx1EJPp0KHDL7/8sn379uzs7Pbt\n2/fu3VulUkkdCpBAxcIuNTU1NTW1wuKePXv27NlTfoXC7p5ptVohhJ1dFTM/AMA8ZDd5Qq/X\n79y589ixYz4+PgMGDPDw8Ki8jYuLy9ChQ82fDbAofysvVq5cKVUOa3Dq1KnJkyfv2rVLCNG7\nd+8FCxa0adNG6lAArJG8mieKioqeeuop4423vL29N2/eHBoaKm0qwDL9rbAbNWqUVDkULy8v\nr0+fPtnZxUJMFUJ8993nx4/3OXr0aOPGjaWOBsDqyKt5Yvr06eVvp5qbmxsVFXXmzBlbW1sJ\nUwGWSTa/scndN998k52dLYRGiHeFeFcITXZ29jfffCN1LgDWSF7NE999912FlaysrF9//VWS\nMICFo7Azk19++UWIxkI88tfCI0I0VsbEG8AoMDDQ+BOWTF6TJwoKCiovFhYWmj+J+Rn2pvIN\nv0D1uITfTFq2bCnEdSHOCBEkhBDijBDXW7ZsKXEswKSSk5MzMjL69esndRDUQF7NE926dbt4\n8WL5FVdX1w4dOkiVx5w0Gk1mZmbfvn2lDgLZ4IidmQwbNqxxY08h+gmxSIhFQvRr3Nhz2LBh\nUucCTMnLyysiIoIrnyyfvJonPvzwQ09Pz/IrH3/8cYU5SUqlVqv79+8vo/+zIDmO2JlJ06ZN\nk5OTX3755WPH4oQQHTp0SExc3bRpU6lzAbBG8mqeaNas2cmTJxcuXPjzzz/7+vqOHTu2e/fu\nUocCLBSFnfk8+uijP//8c25urhDC29tb6jgArJe8mieEEN7e3u+//77UKQAZ4OiuuXl7e1PV\nAZCWvJonaunMmTMpKSmXLl2SOgggJQo7ACaj0WgmTJiQk5MjdRDUQKPRhIeHS53CZC5fvvzk\nk08++OCDvXr18vPzi42NNcz4UYCtW7fGxcUZTvUAtcGpWAAmExsbm5WV5eLiMm/ePKmzoDry\nap6o0QsvvPDDDz8YHpeVlSUmJvr6+s6YMUPaVCYRExOTm5vr6ek5Z84cqbNAHpSzYwOQXFFR\nkfEnLJm8mieql5eXt2PHjgqLX3/9tSRhTI59CnVFYQcAVkd2zRPVyM7OruUiYA0o7ACYDJMn\n5EJJzRNt2rRxcHCosPjQQw9JEsbkmDyBuqrtNXZ6vf7333+/du2aEMLLy4u/uAFUxuQJuZDX\n5InqOTo6Tp8+ffr06eUXFXNFGpMnUFc1F3alpaWzZs1aunSpoaoz8PHxmThx4rRp07jFPAAj\nw+QJqVOgZgprnnjzzTd9fHw+++yz7Ozs4ODgt99+u3fv3lKHMg21Wq1Wq6VOATmpubB77bXX\n9u7du3Tp0pCQEMNQlytXrqSmps6ePfvmzZtz586t/5AAAFNSUvOEEMLGxiYmJiYmJkbqIID0\nai7sNm7cmJyc3KlTJ+NKYGBgYGBgy5YtIyMjKewAQHaU1DwBoLyaD8WXlJS4ublVXm/YsOHt\n27frIRIAoH4pqXkCQHk1F3bh4eHTpk27fPly+cULFy5MnTr18ccfr69cgPzdvn07OTl5+fLl\nR44ckTqLmTB5Qi4UNnnCJA4ePLhkyZL169ffvHlT6iz/w+QJ1FXNp2KXLFkSFRXl6+vr7+/v\n6emp1+uvXbuWk5PTp0+fZcuWmSFiBXq9Pisr69y5cwUFBUIIDw+PoKAgf39/8ycBqnHw4MGh\nQ4caS5yoqKiVK1dK0my0Y8eOzZs3l5SU9OjRY/To0fWagckTcqGw5gkDnU6Xk5Pj4+NT+e4n\n1dNqtc8//3xSUpLhqbe397fffmshhS+TJ1BXNRd2Pj4+u3fvPnXq1I8//njt2jWVStWkSZOQ\nkJBWrVqZIV95+fn577777sqVK69cuVLhpYCAgJiYmKlTpzo7O5s5FVBZSUnJ8OHDc3Ichdgl\nRCsh/rNmzayOHTu+/vrrZk4yderU+fPnC9FYCNf//Oc/K1as+P777+3s6muWIHfJlwuFNU/o\n9fr333///fffLywstLe3f/HFF+fNm+fq6lrLt8+bN89Y1QkhcnNzo6KiNwA7WgAAIABJREFU\nzpw5Ywn/oLBPoa5q+/d7mzZt2rRpU35Fp9NdunTJz8+vHlJV4dKlS2FhYVlZWUFBQREREYGB\ngYad9tatW2fPnt2zZ8+MGTOSkpJ2797dqFEj80QC7iYzM/P8+fNCbBKilxBCiJlC7EpOTjZz\nYffTTz/Nnz9fiFeE+LcQ9kIsS0mJWbp06SuvvGLOGLBACmue+Pjjj9966y3D4zt37nz22Wel\npaW1P6e0bdu2Cis5OTlHjx599NFHTZkSMIt7/8X90qVL/v7+er3ehGmqMX369Ozs7HXr1g0b\nNqzyqzqdLjExMS4ubvbs2QsXLjRPJOBu8vPzhRBCeJdb875+/YSZY6SmpgohhHhHCHshhBAv\nCvHB/v37Keyg1WpPnz4dHBwsdRDTWLJkSYWVr7766pNPPnFxcanN26u8qM6irrQDak8211hs\n27YtOjq6yqpOCGFrazthwoTIyMgNGzaYORhQ2SOPPGJrayvEIiF0QgghfhVCExISYuYYf11p\nVPLXgl6IkrpefgRFUlLzRFlZ2blz5yos6nS633//vZaf0LVr1wordnZ25W/yBchIzUfsevTo\nUeV6aWmpqcNUJy8vr2XLltVv07Zt240bN5onD1ANLy+vGTNmzJw5U4gDQgQKke7p6WT+a597\n9uxpb29/585EIZYJ4SrEu0JceOKJJ8wcAxZISc0TNjY2Dz744IkTfzsibm9v36JFC8PjW7du\nLViwID093d3dfciQIcOHD1epVOU3njNnTnJycvmrt2fPnu3l5WWG8IDJ1VzYXb58uV27dpUP\nNty6dcuc1976+vpmZmZWv82RI0d8fX3NkweSu3LlipubWy1PtZjfjBkz2rdvv2rVqitXrnTq\n9GJCQkLTpk3NnKFNmzZz586dOnWqVvuAEHZC3Bk1atTIkSPNHAMWSGHNE1OmTBk3blz5lYkT\nJzo5OQkhbt261aVLlzNnzhjWv/3227S0tI8//rj8xr6+vseOHZs7d+6RI0ceeOCBUaNGPf30\n02YLD5iYviYHDhxo1qzZ1atXK6xfvHixNm83lUmTJqlUqrlz5xYXF1d+tbCwcMaMGUKIhIQE\nk3/1Z599JoQoKCgw+Sfj3mzZssXwu7iNjc2AAQPOnz8vdSKLdvz48Q8//HDOnDm7du2q7+/y\n9vYWQrzyyiv1/UVABYmJiYb7Xnl6er799tslJSWGdcM/DRUcO3ZM2rS116BBAyHElClTpA6C\nvykpKRFCpKamSh2kCjUfsQsNDZ02bdqWLVsq/D5kY2Pj4eFx34Vlbc2aNWvfvn3x8fFz5szp\n2rWrv7+/m5ubXq8vLCw8f/78oUOHioqKwsPD3377bbNFgiQOHz783HPPlZYGC/FpWdmVbdsW\nDho0KD093dHRUepoFqpdu3bt2rWTOgUsi8KaJ4QQ48ePHz9+fFFRUYWj+AcPHqy88aFDh9q3\nb2+uaIBZ1aordvz48ZUXfX19b9y4Yeo8d9WwYcP09PRFixatWLEiJSVFp9MZX7K3t+/cufO4\ncePGjRsnyQ1gYU6ff/55aam7EClCGH6vaH/kSGRaWlqvXr2kDQbIiEajiY6OzsvLkzqIiVW+\nNqPKAxDmPCoBmFl93ae0Pjg4OEyePHny5MnFxcUXL140TJ5wd3cPCAi4n0a/ixcv3rlzp5oN\nrl27ds8fDpM7c+aMEO3/quqEEGGGRQo7S2C49XH93QAZpqKk5onqRURErFu3rvyKu7t7lU2B\nOp3OAg8NsE+hrqr+b6VTp07VlEq2trYPPPBAjx49XnrppYYNG9ZbtrtycnIKCgoyPNbpdKdP\nn759+3b79u0Nl8rWydmzZ2s5QkNvrjv2oXqtW7fes2e9EHlCNBZCCJFiWJQ0FP6/+Pj41atX\njxkzRuogqIHCmieqMWbMmPT09MTERMNTd3f35cuXGy4GNSgsLJw1a9aKFSvy8/M7dOjw3nvv\n9e/fX6KwVUhISNi4cSM9T6g9VZX1ir+/f0FBgfH2jLa2tsZTn46Ojnq93nCvk8DAwLS0NLM1\noqalpS1cuPD06dPNmzefPn16p06dfvvtt8GDBx8/flwI0aBBg3/9618TJkyo68f+8ccfxcXF\n1WywZs2at99+u6CgwM3N7d7Tw0SOHj3arVu3kpIWQrwoxGUhlnTt2m7//v329vZSRwNgoY4c\nOXLw4EF3d/cnnniifFUnhHj++ee/+eYb41M7O7vdu3ff7T5fgEFpaamjo2Nqamr37t2lzlJJ\nlS0Vt2/fHjhwYO/evb/77rtbt24ZVn744Ye+ffuOGTPmzp07N2/e/Oijj2xtbV988UXzdHkc\nOHDA8C+34ae7u/vZs2fDwsJcXV1Hjhw5ZMgQQ9W1ZcsWk381XbGWRqPRdOjQQQjh4OAwbNiw\nnJwcqRMBMnPnzp0TJ05InUJ6le9sLIR45plnpM4FS2fJXbFVF3YTJ07s1auXTqersK7T6Xr3\n7j1jxgzD0/Hjx/v5+dVvwL88/fTT9vb2GzZs0Gq12dnZHTp0GDVqlK2t7b59+wwb/Prrr66u\nrk8++aTJv5rCzjIVFhbeuXNH6hSALG3bts3T01PqFNLbunVr5cIuKChI6lywdJZc2FV98ey3\n33773HPPVb601sbGJjIycsWKFYanXbp0yc3NvbcjhXWVnp4+fPjwwYMH29raNm3adOHChatW\nrQoLCzMeMH/wwQeHDRv2448/micPJOfq6soFxcC9sZ7mieoZp1OU17x5c/MnAUyl6h371q1b\nd2sFvXnz5qVLlwyPc3JyHnjggfqKVilS+ZFioaGhQogKN2Hy9fU1tMoCkIROpzPbL3u4H9bT\nPFG91q1bV56ZGxMTI0mYKmm12vKzzoAaVV3YBQcHL1my5KeffqqwfurUqSVLlhh+m8nIyFiy\nZEnnzp3rPaMQQgg/P7+srCzjU1dXVw8Pjwo9uWfPnm3cuLF58gCoLDIyUq1Wr1q1SuogqIGN\njU2zZs2kTiE9GxubtWvXDhgwwPDU3d39448/HjZsmLSpyhs4cKBarU5KSpI6CGSj6jNZs2bN\nGjx4cOfOndu0adOqVSsXF5fi4uLff//dMIZl2bJlQogpU6bcvHlz2rRp5gnau3fvVatWvfTS\nS8ZzrxVuj3zgwIENGzY888wz5skDoDLDFSdpaWmjRo2SOguqo7zJE/dgy5YtCxYsOHfuXKtW\nrdatW/fQQw+1aNHC0vrrU1NTy8rK0tPThw4dKnUWyEPVR+wGDhz4ww8/9OnT5/fff9+6deu6\ndeu2bNly4sSJrl27JiUlGWaLvfDCC/v27TNbo+8bb7zh4uLy2GOPvfnmm5VfjY6Ofuyxx/R6\nfUJCgnnyAIB8aTSayqcgrcqKFSueffbZlJSUCxcu7Nq1KzIy8ueff7a0qg64B3e99rxnz549\ne/YUQuTn51+/ft3e3t7Hx6f8XYvHjh1rjoB/adWqVWpq6j/+8Y8q7wyemZnp4+Pz6aefhoSE\nmDMVgPK4S75cyLR54sSJE5s3b87Pz+/atevQoUPv54/wxhtvVFiZNm2aRZ2ENWCfQl3V8N/K\ntWvXzpw5c/v27QYNGri7u9/P5K7717Zt2++//77Kl7777juz3ScZwN0weUIu5Ng88cUXX7zy\nyitardbw9PHHH9+xY8e9/at05coVYxeg0blz5woKCho0aHC/QU2KyROoq6onTwgh9u/fP3Xq\n1IMHD/5vU5Wqd+/eCxcubN++vbniWYTExMTY2FgmTwCAVP7444+WLVtWmBL0r3/9694uv7lz\n5467u3uFT/Pw8MjPz1epVPcVFNbBkidPVH3E7tChQ08++aRWq+3Ro0fr1q2dnZ1v37598uTJ\n/8fencfFtL8PAH/GtGlRUhRtKGSNSwop0iI3S6grKteahGtJ3Ivs+7Ul2fd9K1eJQYSsuSlb\nRSKlRZv2Zml+f8zPfOfOmWpqljPTPO/XfXndeeacz3mGZubpnPN8PrGxsYMHD37+/DkuzYkQ\nQvJL7ponnj59Slz78d69e00r7JSVlT08PM6ePcsbnDhxIlZ1qBkQXNitX79eX1//9u3b3bp1\n440nJia6urquWbOG7/2AEEJIjtBoNB8fn8LCQrITERZ3vXJetbW1TR4wLCysuLg4JiaG83DM\nmDE7d+5s8mgIyQ7Bhd3jx48XL17MV9UBQN++fQMCAsLDwyWfGEIIIUmRu+YJGxsbFRUVOp3O\nGxw6dGiTB9TR0blx40ZKSsqnT58sLCwsLCxEzhEhmSD4jf3jxw8jIyOBT5mZmRUVFUkyJYSQ\nvMKVJ+SF3DVPGBsbb9++nXdWBGtr6yVLlog4bLdu3dzc3GS5qsOVJ1BjCS7s2rZt+/79e4FP\nvXv3rm3btpJMCSEkr+Ro5YmKigoGg0F2FqSRx5Un5s2b9/Tp02XLlvn7+x87diw+Pl5NTY3s\npCQOV55AjSW4sHN2dg4NDb127RpvzyybzY6IiAgLCxs5cqS00kMIyRPuyhNkJ1KfBw8e9OvX\nT0tLS0NDY9y4cZmZmWRnRAImk/nu3Tuys2i0/v37b9q0KTw8fOrUqQoytRt35QmyE0FyQ/Ab\nIyQk5MaNG2PHjjUwMOjevbuGhganKzY3N9fQ0DAkJETKWSKEkFikpKS4ublVVFQAAIPBiIyM\n/PTp07NnzxTh3A8vuWueQAgJSfAZOzMzs4SEBD8/v6qqqtjY2OvXr8fGxtLp9BkzZrx8+bKu\n2+8QQkjGHTx4kFPVcSUnJ8fGxpKVD1nkrnkCISSkOk9lGxsbHz9+nM1m5+bmVlRUaGpqGhgY\nSDMzhBASu9TUVIFBNzc36SdDIrlrnkAICel/hV1WVlZdG6mpqTGZTN4N8KQdQkgeCex/lOWm\nSAmRx+aJZubbt2+hoaEpKSkmJiazZ8+Wo8mikYz7X2FnbGws/G51LUSGEEKybPr06QcOHOBd\nw8DS0nL48OEkpkQKuVt5opl5+/atra1tWVkZ52F4eHhkZKSinTZGEvK/ws7Ly4vEPBBCSAp6\n9ep17dq1+fPnp6amUigUJyenffv2qaurk52XtGHzBLnmz5/PreoAgMFgzJo1q57rZggJ73+F\n3fnz50nMAyGEpMPZ2TklJaWgoKBly5YaGhpkp0MObJ4gUW1t7bNnz/iC2dnZX758MTU1JSUl\n1JzgGxshpIj09PQUtqoDbJ4gVYsWLQROr9OyZUvpJ4OaHyzsEEJI4WDzBLmcnJz4IlZWVriq\nExILLOwQQmLDuZCEl5Nkn5yuPNFs7Nmzp0ePHtyHHTp0OHXqlMAtOe8mExMTKWWG5F8DS7LE\nxMSsXLny/v37mpqa0kkIISS/rl+/npCQ4OLiQnYiqAHYPEEufX39xMTEf/75JyUlxdjY2MPD\no64vWRqNlpSU5OzsLOUMkfxqoLArLCx8+fIlk8mUTjYIIbnWtm1bnLJBLiha8wSLxaqqqpKp\nMxTKysrjx49vcDNDQ0NDQ0Mp5IOaDQV6YyOEEOJQnOaJgoKCqVOnampqamlpde3a9dq1a2Rn\nhJBkYWGHEFIUbDb70KFDlpaWqqqqlpaWhw8fVti51hWkeaK2tnbSpEknTpzgTEmdlpY2YcKE\nhw8fkp0XQhKEhR1CSFHs3bt31qxZKSkpdDo9JSVl5syZ+/btIzspcihI88SbN2/u3LnDG2Ey\nmaGhoWTlg5AUYGGHEBIbGo0WEBCQnZ1NdiKCbdiwocGIgqDRaHZ2dmRnIXGpqalCBslVz43s\nUVFRgYGBeXl50swHyTUs7BBCYuPv7x8eHr5z506yExGgoKCA+O2Yk5NTVFRESj7kUpDmCQsL\nCyGDpKioqFiyZIm+vr6amlqfPn2ioqKI28yYMSMsLCwsLEz66SE51fzf2AghqamsrOT+KWt0\ndXVbtWrFF9TW1m7dujUp+ZBLQZonevXqNXToUN6IkpLSnDlzyMqHz8yZM//++++CggIWi5Wc\nnDxu3Lh79+7xbSPL7ykkm7CwQwg1RW1tbUJCwj///PPx40eycxFKixYt/Pz8+IJTp06lUCik\n5EMuBWmeoFKpFy5cmDBhApVKBQAjI6NTp045OjqSnRcAQGZm5rlz53gjTCZz+/btZOWDmo0G\nCjs1NbU2bdoowhl7hJDwvnz5YmNjM2DAgDFjxlhYWPj4+DAYDJD5lSe2bt06c+ZMzgdaixYt\nZs2atXnzZrKTIoeCNE8AgIGBwaVLlyoqKnJycr5+/frbb7+RndH/e//+vTBBXHkCNVYDExRP\nmDBhwoQJ0kkFISQvJk+e/OLFB4DjAL0BIk6fXmdmZrZu3ToZX3lCTU3t4MGDW7du/fLli6mp\nqY6ODtkZkUbRVp5QVVU1MDAgO4v/6NSpkzBBXHkCNRaeikMINc63b9/i4+MBVgP4AfQFWAsw\n+vLly/Bz5QnOZS+ZpaOj06dPH0Wu6kBhmidkmbm5+bBhw/iCM2fO5IsYGhq6urriPxYSHv6s\nIIQaJzc3FwAAOvLEOv4MIvmgIM0TsoxCoZw7d27MmDGch61atdq9e7eXlxe5WaFmoIFLsQgh\nxKd79+6qqqo1NacARgFQAUoA/rGysiI7L9QICtI8IePatWsXGRlZUlLy/fv3jh07KinhNzIS\nAzxjhxBqHDU1tbVr1wJcBugHMAWgu7Jy1saNG8nOCzWC4jRPyD4dHR0LCwus6pC4YGGHEGq0\noKCgs2fPOjjodunyYuzYgY8fP7a1tQWZX3kCcSnIyhPNAK48gRoLf0VACDUahUKZNGnSpEmT\n+OL+/v4ZGRnq6uo4HZeMw+YJeTFjxoy8vDxdXd21a9eSnQuSD/jGRgiJDc6SLy+weUJe4HsK\nNRYWdgghpHCweQKh5goLO4QQUjiy3zzx/v37iIiIFy9e1NbWkp0LQvIECzuEEFI4stw8UVNT\n4+np2b17dw8PD2traxsbm69fv5KdFEJyAws7hBBqAIPB4CyGKwwmk8lmsyWaj+hkuXli8eLF\nly5d4j588eKFj48PifkgJF9k9I2NEGpOGAzG2bNn//zzzz179uTk5JCdTiOkpKS4uLhoampq\naGg4OTnVf/ny1atXw4cP19DQ0NLSmjhxoiyfZ5Ll5omjR4/yReLi4r5//05KMgjJHZzuBCEk\nWSUlJfb29snJyZyHK1asiIiIcHR0JDcrYRQVFTk7O3Prszt37jg5OSUlJenp6fFuVltbe+bM\nmWvXrl2/fp1OpwMAnU6/fPny+/fvX7x40bJlSxJSb4jMNk9kZ2dXVVUR4/n5+fr6+iIOXlxc\nHB8fX1lZOXDgQFNTUxFHQ0g24Rk7hJBkLV++nFvVAUBZWZmPjw+TySQxJSFduHCB76zbt2/f\nzp07xxths9leXl6+vr5XrlzhVHVcb9++jY6OlkaijSezzRMZGRnEIIVC6dKli4gjX79+3cLC\nwt3d3cvLy8LCYt26dSIO2DRxcXEbN27cvXv3hw8fSEkANXtY2CGEJCs2NpYvkpOTI5tVBZ+U\nlJQGg1FRUZcvX65rhPfv34s/LXGQ2eYJS0tLYrBz587KysqiDPvt27cpU6YUFhZyHjIYjFWr\nVt24cUOUMRuLzWZPmTLFwcHhr7/++uOPP3r27Hno0CFpJoAUBBZ2CCGx4ax3ybfqpcC2A+F7\nEUhkbm7eYPDx48f1jNC5c2cx5yQmMts80aZNm9mzZ/MFQ0NDRRw2Nja2tLSULxgZGSnisI1y\n4sSJM2fOcB/S6fR58+YJPEPJS+B7CqF6yOIbGyEkp4KCggYMGODn58cbHDJkCN9mOjo6PXv2\nlGJeTTRhwgS+2+natGnj6enJG1FXV69rd2Nj45EjR0oqOdHIcvPErl27Vq1a1aFDByUlpd69\ne0dGRrq6uoo4ZkFBgZBBybl9+zZfpKam5sGDB/XvFRwcPHDgwMmTJ0ssL9TcYGGHEBKbBQsW\nPH/+/JdffuENbt261djYmPtQWVn50KFDqqqq0kkpJSXFw8PD0NDQ3Nw8KCiIeNqmHoaGhtHR\n0VZWVpyHvXv3joqK6tChA+82I0aMELhvy5Ytf/31VzU1tSZnLlEy2zwBAGpqamvWrMnKyqLT\n6UlJSWPGjBF9TL6fyXqCklNdXS1kkFdwcPDTp0979eolmaRQM4SFHUJIsgwMDN6+fbt9+3Zf\nX9/g4OBXr15NmDBBOofOysoaMmRIREREbm5uenr69u3bx48f36iVDKytrRMTE79//56fn5+U\nlGRjY8O3ga2t7dq1a6lUKl+8qqoqPDzc19dX1NcgGTLbPMGLQqGIayg7O7vx48fzRjp37jxv\n3jxxjS+MwYMHE4O2trbSzAEpArxsjxCSOC0trcWLF0v/uLt37+beL89x586dhw8f2tvbN2oc\nvguyfBYtWpSdnR0dHV1UVMS3WPvly5cTExP79u3bqMNJAY1G8/Hx4fvLad7OnTsXFhZ2/fr1\niooKOzu75cuXt2rVSpoJzJ0798KFC8+fP+dGgoKCevfuLc0ckCLAwg4h1Gy9efOGGHz9+nVj\nC7t61NbWuru737t3r64NkpOTZbCwk9nmCclRVlb+448//vjjD7ISUFVVffjw4ZEjR+Lj4zU0\nNMaOHSuzt2AiuYaFHUJIbFgsVkFBQbt27chO5P8ZGRkRg7w3/IkuJiamnqoOAPjuyZMRstw8\n0YypqKjMmTNnzpw5wu/CZDKLioratm0ruaxQM6NYv7EhhCTK09PT0NDw9OnTZCfy/7y9vfki\nRkZGDg4OYjzEq1ev6nnWzMyMeFueLJDl5gnEy93d3dDQ8MqVK2QnguQGFnYIIbGJj49ns9n1\nT+0mTcOGDTt48KC2tjbnoaWlZUREBPchx5kzZ3r37q2mpta1a9ewsLBGtVYAgIGBQV1PWVpa\nXr16VVNTswmZS5pcNE8gAIiPj6+trX3y5AnZiSC5gZdiEULN2cyZMydNmvT27VtNTc1u3brx\nta+ePHmSO+teWlpaYGBgWVnZsmXLuBtcvXo1Ojq6srLS3t5++vTpxPUPnJ2dW7VqxTuLipKS\n0q5duwYPHtyzZ0+ZnVdWfpsnGAxGaWlpmzZtyE4EIRmFZ+wQQmIjm7Pka2pqDhw4sEePHsRJ\nSdavX88X2bhxI/ek3dy5c8ePH3/06NHz58/PmTNn2LBhxAUzjI2Nz507x72tUENDIzQ0dO7c\nuVZWVrL298BLHpsnCgsLfX19NTU19fT0TE1Nz58/T3ZG0iCb7ykky+TsjY0QkmUCV56QWTU1\nNR8/fuQLlpWVZWZmAsCzZ8/27dvH+1R8fLzAxT3d3NzS09Pv3bt369atL1+++Pv7Sy5ncZG7\n5gk2mz158uRTp07R6XQAyMzMnDRpEo1GIzsvicOVJ1BjYWGHEBIbgStPyCxVVVVDQ0O+oIqK\nSvv27aGORWDrun1QQ0PDwcHB2dlZXi4Ryl3zRGpq6q1bt/iCe/fuJSUZacKVJ1BjYWGHEFJc\nU6dO5YtMnjxZRUUFAFq2bEncXmBQHsld80RaWpqQQYQUHBZ2CCHFtXr16sDAQM4NTBQKZcqU\nKXv27OE8NWzYMGKrhJOTk7RTlAwajWZnZ0d2Fo3QpUsXIYMIKTgs7BAiX05Ozv3791NTUyUx\neG5u7u7du5cvX3769Gnivf8KTllZOTQ0tKCgIDExsaCg4NSpU9zZSbp27bpr1y7e2m7WrFme\nnp4kZSpmctc80bVrVxcXF75gYGBggzvGxcW5uLgYGRnZ2tqePHmSzWZLJkGEZAYbNWT//v0A\nUFZWRnYiqBliMpkBAQHcbk17e/usrCwxjh8bG/tzQcyWANCjR4+ioiIxjs+HyWTm5uZKbnzp\nS0lJ2bNnz5YtWx4/fkx2LuLEYrEyMjLIzqJxCgoKfHx8OBfKTUxMzp071+Aud+7c4fvK27x5\nsxRSFSMGg5GXl0d2FohfTU0N/Jy5U9ZgYdcwLOyQ5GzcuBEAAOYDxAHsBdBycHAQ1+BMJrN9\n+/YA3QE+ArAB/gFQmTlzprjGJ/Lw8KBQKKdOnZLcIZCCo9PpBQUFQm5MXPZDTU2tpqZGohmK\nl6ura4sWLS5fvkx2Iug/ZLmwk6dT8Qg1P2fPngVwAdgNMBRgLsDq+/fv5+TkiGXwlJSUb9++\nAYQAdAYAAHcAz9jYWLEMLpCsrTyB6iJ3zRNcysrKQrYes9ns5ORkvmB1dbV8tVzgyhOosbCw\nQ4hM2dnZAF15Al0BICsrSyyD/7yjToUnpoy32SGQw+aJJqBQKJyZa/gQ57hBqDnBwg4hMvXu\n3RvgBkD5z8BFJSWl7t27i2XwHj166OrqAmwGKAAAgOcAl4YMGSKWwZFck7vmiab57bff+CJy\nNNcgQk3T/N/YCMmyNWvWKCl9BugN4A8wGODkn3/+qaGhIZbBlZWVDx8+rKz8L4AJgBmArZGR\nzvbt28UyuExJTk5evXr1woULz507x10QDNVD7laeaJpVq1bxTlXo4OBw/Phx0rJBSCpw+TmE\nyGRvb3/37t1169a9eXOtQ4cOM2funzlzphjHHzduXHJy8okTJ3Jycnr16jVr1iwtLS0xji8L\nwsPD582bx2KxOA/37dt39+5dTu+k7Hj8+PGLFy90dXVdXV319fXJTkf+Vp5oGmVl5WPHjq1Z\nsyY1NbVDhw7iOheOkCyTv8KOzWZnZGR8+vSprKwMALS1tS0sLIyNjcnOC6EmGjp06O3btyU3\nfrdu3TZt2iS58cmVlZW1cOFCblUHAI8ePdqxY8eyZctIzIoXi8X67bffLl++zHmoo6Nz9uzZ\nkSNHkpsVk8lMS0tTkELHxMTExMSE7CwQkhJ5uhRbXFy8ZMkSAwODzp07Ozk5eXh4eHh4ODo6\nmpiYmJqarlu3rqqqiuwcEUJS9fTpU868A7zu379PRi6C7dmzh1vVAUBJSYmPj8+PHz9ITAkU\no3kCIcUkN2fscnJyBg8enJGRYWFh4ebmZmpqyrkPqbS0ND09PS4ubtWqVVeuXLl3717r1q3J\nThYhJCVsmV9IICYmhi9SWFj4/PlzclcnU5DmCYQUkNwUditXrsy69TOEAAAgAElEQVTKyrp4\n8eLEiROJz7JYrAMHDgQGBq5Zs2bXrl3STw8hRApbW1tVVVW+k3b29vZk5UPEuWmET3l5OTEo\nTQrSPIGQApKb39iio6N9fHwEVnUAQKVSAwICPD09r169KuXEEEIkMjIy2rFjB3dNNgAYPHjw\nokWLSEyJD3HxAwqF0rt3b1KS4VKQ5gmEFJDcFHaFhYWdO3eufxtLS8u8vDzp5IMQIjI1NeX+\nKTUBAQEJCQkrVqyYP3/+6dOn4+LiVFVVpZlA/YgTB7LZ7Js3b5KSDJf8rjwhHTk5OadOndq/\nf39SUhK5mXDeTdj8gYQnN5di27dv3+AbLDExUeA84wgh6bh+/XpCQoKLi4uUj2tlZWVlZSXl\ngwopJSWFGCT9MiiNRvPx8SksLCQ3Ddl08eLF6dOncy+Xz507d+/evWQlQ6PRkpKSnJ2dyUoA\nyR25OWM3duzYS5cubd++ndgBBwAVFRUhISHXrl3z8vKSfm4IIY62bdu6ubnxXhhFOjo6xKC2\ntrb0M+GFzRN1yc7OnjZtGu9NkGFhYWfPniUrH0NDQ1dXV/zHQsKTmzN2q1evfvjwYVBQ0Nq1\na62trY2NjTU1Ndlsdnl5+ZcvX54/f15ZWWlnZ7dixQqyM0UIof9xcnIitneMGjWKrHw4sHmi\nLnFxcRUVFXzBmJgYb29vUvJBqLHkprDT0dF58uRJWFjYyZMn79+/zzsfqbKy8i+//DJt2rRp\n06Y14VRBWVkZk8msZ4PKysqmZIwQai5+/PhRVlZmZGTUhH27dOmyf//+uXPncj5JlJSUVqxY\nQfqVNWyeqEtpaSkxSPq8gwgJT24KOwBQUVFZuHDhwoULq6urv379yplEoFWrViYmJk1ePig9\nPd3CwkKYqbBkf7oshJDYff78efbs2TQaDQA6dOiwc+fOunrz6zF16lQnJ6e4uLjq6mo7OzsL\nCwsJZNo4CrXyRKMMHDhQyCBCsonSnOqV4uLiHz9+NPbX0Hfv3tW/ZMXVq1c3btxYVlamqakp\nUn4INXc0Gi0yMvKvv/7q0KGD8HtVVFScOHEiJSXFyMjIx8fH0NBQchk2Sk1NzcCBA3nbtpSU\nlO7fvz948GASsxKLGzduYPNEXebMmbN//37uQ0tLyxcvXnCmxJe+qKiomzdvrly5sl27dqQk\ngASi0+mqqqrx8fGDBg0iOxd+8nTGLjk5efny5W/fvjU2Np40adLs2bP5Lrxu2bJly5YtjS1V\nG/ydNSEhodG5IqSQ/P39MzIy1NXVt2/fLuQuWVlZgwYN+vr1K+fh+vXrb9y4QZwihBRPnjzh\na8ZnMpmHDx9uBoUdNk/UY9++fXZ2dpGRkeXl5YMGDfrjjz/IquoAYMaMGXl5ebq6umvXriUr\nByRf5Kawi4+Pd3R0rKmpUVdX//bt26NHjy5evBgREYELiCEkOzi3kTXqttT58+dzqzoAKCsr\n8/PzS09PF39yjScwjY8fP0o/E7HD5ol6UCgUb29vGemWaMJ7Cik4ufmNbdOmTbW1tREREeXl\n5WVlZTt27Hj8+LGLiwuxfQkhJC/YbHZcXBxf8NOnT5mZmaTkw6dbt27EoKWlpfQzETtsnkCo\nuZKbwi45OdnLy2vs2LEUCkVVVXXhwoU3b95MSkry9PTk7ZBFCJGoCStPCLx3Qkbu/bWxseG7\nKKympjZ37lyy8hEjhVp54sWLFyEhIUuXLv3nn3/IzqXRcOUJ1FhyU9jl5uZ26tSJNzJ8+PDD\nhw/fuHFDptaFREiRXb9+PTo6esmSJUJuT6FQ7O3t+YJmZmZSXpSsLlQq9cqVK76+vhoaGlQq\ntV+/fjdu3OjTpw/ZeYkBjUazs7MjOwtp2LRpk62t7dq1a7dt2zZmzJhx48bV1taSnRQ8e/Zs\nxIgRbdq0sbCwWLNmTXV1dV1b0mi0mJiYwMBAaaaH5BtbThgZGY0ePZoYX758OQBs3bqVzWYH\nBwdL4hVx2qPKysrEPjJC6MuXL7wttJqamnFxcWQnxa+2traqqorsLMQpJiZGT0+P7Cwk7s2b\nN0pK/LeSHzlyhNysXr16paamxpvSlClTyE0JNRZnyvH4+HiyExFAbs7YeXh4XL9+fe/evQwG\ngze+YcMGPz+/pUuXLly4EG8vRUjumJiYvH//fvfu3QEBARs3bkxJSRk6dCjZSfGjUCh838Ty\nTkGaJx48eECcf/7+/ftk5PI/mzdv5jtFd/r06ebRlINkgdx0xa5atSoyMnLevHnXrl27ffs2\nN06hUI4dO6atrb1r1y4S00MINZmWltb8+fPJzkKxKEjzBFvQzZqkX4p9/fo1MfjmzRtzc3Pp\nJ4OaH7k5Y9emTZuXL18GBAT07NmT7ykKhbJ79+4rV6507tyZlNwQQki+KEjzhMAJEUk/JSyw\nEwLbI5C4yE1hBwB6enphYWE7d+4U+KyHh8fHjx8F/n6GEJIOGo0WEBCQnZ1NdiJNwWAwvn37\npiCfIQrSPNG7d++QkBDeyMiRI6dPn05WPhw+Pj58kT59+vTq1UvgxlFRUYGBgXl5eZLPCzUT\ncnMpFiEk+5qw8oQsKC8vDwoKOnr0KJ1O19XVXbVq1YIFC8hOSrIUZ+WJ1atXjxgx4vr161VV\nVUOGDJk4cSKFQiE3pUmTJn358mXdunWc+8JtbW1PnjyprKwscGNceQI1FhZ2CCGxkdNZ8gMC\nAk6dOsX5/6Kioj/++ENLS2vatGnkZiVRCtI8wTFkyBAZWaSOa9myZQEBAe/fv9fT0+vUqVM9\ntaacvqcQibCwQ4g0lZWVFy5c+PTpk6mpqZeXl5aWFtkZKaKSkpLTp0/zBffu3du8CzsFaZ6Q\nZa1atRo4cCDZWaBmCAs7hMjx+fNne3v7zMxMABUAekhIyN27dwWuYYUkKj09nXhfXbOfe4LJ\nZKalpXXv3p3sRBBCYqYQ91ggJINmz56dmVkG8BCgBuDZt29M0u/pVkwWFhbEu826dOlCSjJS\noyDNEwgpICzsECIBg8F48OABQAAA59Yfa4CFT58+LS8vJzkzxdOqVSviVdc//viDlGSkRnGa\nJxBSNPjGRogELBaLxWIB8C5moMZms/kWVkHSsXv37kWLFmlqagJAhw4dDh48OGXKFLKTkiw5\nbZ6g0+k7duwYMWKEg4PDqlWrysrKyM4IIZmD99ghRAI1NbVffvnl6dMDAJMBOgJkAezt0aNH\n69atyU5NEamrq//999/bt28vLS3V1tYmOx1pkMfmCTabPXbs2JiYGM7DuLi4a9euPXv2rJmt\n9oaQiPCMHULkCA8P19L6AdAVoCtAZ3X1nIMHD5KdlEKjUCgKUtWBfK48ERMTw63qOJKTkw8f\nPkxWPgjJJjxjhxA5rKysUlNT9+/fn56ebmY2cfbs2cbGxmQnhRQFjUbz8fEpLCwkO5FGSEhI\nIAZfvnwp/UwQkmVY2CFEGkNDwzVr1pCdhTgpKSlx/0SyTB6bJ9q0aUMM6urqSj8TacL3FGos\n/FlBCIlNUFDQmTNn/Pz8yE5Esp49e3b16tWSkpKBAwf6+vrK45euPDZPODs7q6mpVVdX8wbd\n3d3Jykc6goODIyIiJk+eTHYiSG5QFGTFa1EcOHDA39+/rKyM0zSHEFJkO3fuDAoKYrFYnIfW\n1tZxcXF4/750nD17lvNpDAAqKirr168PCgoiOymkiOh0uqqqanx8/KBBg8jOhZ+cnYpHCCES\nZWZmBgcHc6s6AHj+/Pnff/8NAJGRkePHjx8yZMi8efOysrLIy1Eo8tg8AQDe3t7p6emXL18+\nf/78hw8fsKpDiEj+riAghBBZnjx5Qpxr8MGDBwCwYsUKzsP4+PgzZ878+++/sjyfiDw2T3Do\n6+uPHz+e7CwQkl14xg4hhIRFpVKJwdra2tWrV/NGiouLZ86ceenSpbS0NCll1kjy2DyBEBIG\nvrERklcMBuPly5f3798vKioiO5f/x2Kx8vLyyM5CgmxtbYm303Xq1InJZPIF79y54+np2a1b\nN39/fxm8lVkemycUE5PJzM/PJzsLJE+wsENILj1//rxHjx79+/cfNmyYsbHxjh07yM4IAMDT\n09PQ0PD06dNkJyIpHTp0CA0NVVZW5kYcHR2JS81ysdnsAwcO7N27VyrZNYI8rjyhmNzd3Q0N\nDa9cuUJuGmw2+/Tp0xMmTHBxcVm7di0u5ibLsLBDSP6UlpaOHz/+wwcGwAWA+5WVzosXL46O\njiY7L4iPj2ez2Y8fPyY7EX4sFktcp81mzJjx6tWrjRs3Ll269MqVK7dv3+7bt2/9RVJERIRY\nDi1Gcto8oYDi4+Nra2ufPHlCbhpz5szx8fG5cuU1jVYaErJmwIAB5eXl5KaE6oKFHULy5+HD\nh1lZWQDHADwB7AEuABhfuHCB7Lxk0bt371xdXTU1NbW0tDw8PD5//iz6mKampj179nRycrK3\nt6dQKCoqKhcvXjQyMqpr++/fv4t+UPGi0Wh2dnZkZyEr6HR6UlLSmzdviJ0xCAASExMPHDgA\nsAQgFeAJwK3U1I87d+4kOy8kGBZ2CMmfb9++AQBAl58BFQCz7Oxs0hL6SdZmyc/Pz3d0dLx1\n61Z1dXVFRUVERISzs7MoZxqqq6t/++03LS2t0aNHOzk5GRgYrFu3DgAGDBiQkpJy/fr1v//+\nm9iU0K9fP5FehgRg8wRXVFRUx44draysevXqZWFhcefOHbIz+g9ZeE89f/4cAAAW/wyMALD6\nGUQyB9/YCMmf3r17AwDA+Z+BDwAv+/TpQ1pCPwUFBQ0YMEB2Vp44ceJEbm4ub+TDhw9Xr15t\n8oALFy68cOEC96ouk8lctWoV51yphobGr7/+umjRosWLF/Puoq2tHRIS0uQjSgg2T3CkpqZ6\neXn9/E0Jvnz5MmHChMzMTHKz4hUcHDxw4EByV57Q1tYGAIACnljRzyCSOVjYISR/rK2tx4wZ\nA7AEYBTAVADrNm1aLlq0iOy8YMGCBc+fP//ll1/ITuT/CbyNLC4urmmjMZnMY8eOEePnzp3j\nfbhly5bjx4+PGDHCysrq999///fffzt16tS0I0oONk9wXL58ubKykjfy48ePa9eukZUPUXBw\n8NOnT3v16kViDkOHDtXU1ASYBfAG4BvAAoAMNzc3ElNC9cDCDiH5Q6FQzp49GxKyqlevr6am\n9728XJ48eVLPPV4KS2BFdfz48bCwsCaM9u3bt5qaGmL869evvA8pFIqfn9/t27cTExOPHj0q\ng1UdYPPETwJPzsnUGTtZ0L59+2PHjmlpvQHoBdABYE9gYKC3tzfZeSHBsLBDSC6pq6uvXr06\nOTn58+fP58+ft7CwIDsjWTRp0iTiEs+1tbWLFi1qQheFkZGRhoYGMW5lZdW09EiEzRMcPXv2\nFDKo4CZMmJCWlnbmzJn9+/cnJSWFhoaSnRGqExZ2CKFmy9zcPDIykliN0en0+Pj4xo7WokUL\n4uKkKioqZmZmMTEx8tVQic0THL6+vh07duSNdO/efeLEiWTlI8sMDAy8vb1nz5798x5fJKPw\njY0QEhsZXHnC0dHR0dGRGGexWE0YbcWKFevXr9fS0gIAKpWqoaFBp9NXrVrl5ubWu3fvT58+\niZqutGDzBIe2tvb9+/e9vb3btWvXvn37qVOn3rlzR11dney8/gdXnkCNhYUdQkhsZHPlCeI1\nRyUlpUGDBjVhKCqV+tdff5WWllZXV/v6+lZUVHCfSklJ8fX1FX4oBoNx+/bt48ePkzJthCw3\nT0RFRc2cOXPChAnu7u4TJ04MDAyUaA1qYmJy5syZ3Nzc7OzsY8eOGRoaSu5YTSAjK08gecJG\nDdm/fz8AlJWVkZ0IQrKuXbt2ADBnzhyyE/mPmpqaIUOG8H7ubdmyRfRh9fX1+T5OKRRKUVGR\nMPumpqZ27dqVu6Orq2tlZaXoKQmPwWC8fftWmkcUEt9kMRxUKvXYsWNkp0YOzunhxYsXk50I\n+g9OHxVnrR1Zg2fsEELNnIqKyv3790+cOOHv77906dLHjx8vXbpUxDFZLBZxuUw2m11SUiLM\n7t7e3qmpqdyHN2/e/PPPP0VMqVFks3kiKSnp77//JsZZLFZgYCDv+VGEUF2wsEMINX9UKtXX\n1zc8PHzLli22trZiGZC4noS+vr4w1zezs7NfvnzJF/znn39Ez0p4stk8Uc+KqBUVFa9evZJm\nMgjJKZl7YyOEkFzYuXOniooKbyQ0NJRCoTS4Y2FhITFYVFQktsyEIJvNE2pqavU827JlS6ll\ngpD8kpUlHRFCSMaxWKwjR47cvHmzpqbGwcFh3rx5nEuHKSkpJiYmc+fOFbIhw9LSUkNDg+/C\nYv/+/SWTtWCy2TwxdOhQVVVVgbNAGxoa4vRyCAkDCzuEEBKKl5cXtznxxo0bV65cefDgwaFD\nhxo7jrKy8o4dO2bPns2NqKmpbdu2TWyJCoHJZKalpXXv3l2aB21Qp06dQkNDAwMD6XQ6b1xH\nR+fMmTN850fr8fnz569fv1pYWBgYGEggTYRkGhZ2CCHUsNu3b/NNOfHs2bNjx47x1mfCmzVr\nVseOHQ8cOJCdnW1paRkcHMzbJCsFNBrNx8dH4EVhcs2cOXPYsGExMTHl5eUUCoXBYBgYGIwd\nO5bYgyxQQUGBn5/fjRs3AKBFixbTp08PCwtTVlaWcNYIyRAs7BBCqGHPnj0TGGxaYQcATk5O\nTk5OoiXVdLLZPMFhbm4+b968pu07c+ZMTlUHALW1tYcOHWrbtu369evFlx1Csk5G39gIISRT\ntLW1hQzKBdlsnhBRWVkZsbn4zJkzpCSDEFmwsEMIoYaNGDGCeI/XyJEjSUlGdLLZPCGi7Ozs\n2tpavuC3b9+IQYSaMSzsEEJiY2pqyv2zmbG0tNy7dy93Pg4qlbpq1SpnZ2dys2oyJpP57t07\nsrMQM3Nzc+KUKD169JDZi87C4LybTExMyE7k/126dGnYsGEWFha//vprfHw82ekgAfAeO4SQ\n2Fy/fj0hIcHFxYXsRP4jOTn50qVLP3786N+/v7e3t5JSEz/3Zs6c6eLicu/ePTqdbmdn161b\nN/HmKU0y2zzBYrE+ffqkpqZmbGzc2H2VlJRCQkKWLVvGG1y7dq34siMBjUZLSkqSkV8h9uzZ\ns2DBAoCeALYfP96/dcvh1q1bw4cPJzsv9F9kr2kmB3CtWITk18GDB3kruQEDBkh5VVbZFBMT\no6enR3YW/K5cudK+fXvOv1S/fv1evXrV2BFqa2sPHz7cr18/fX39IUOG3LhxQxJ5KiYmk6mp\nqQnwKwATgA1QBtDN2tqa7LzIIctrxVLYbDYpBaUcOXDggL+/f1lZmaamJtm5IIQaIS8vz8zM\nrLq6mje4atWqNWvWkJWSjKitrc3MzJSp2+z+/fdfW1tb3hnsTExMkpOT5bdDpZlJSUmxtLQE\nOAfw28/Yn2pqOysqKuT6YnfT0Ol0VVXV+Ph4IacllyaF+8dACCmOZ8+e8VV1APDgwQNSkpEp\nMtg8cerUKb55iTMzM2/fvk1WPoiPgYEBhUIB+MQT+9S2bVsFrOpkHP57IISaLWFWblVMMtg8\nkZGRQQx+/vxZ6okgwXR0dJycnAA2ARwEeAmwFuDixIkTyc4L8cPCDiEkNjQaLSAgIDs7m+xE\n/p+1tTWxTdLBwUHgxrm5ufPnz7exsXFxcTl8+HDzniODRqPZ2dmRncV/CFzfzNLSUvqZyJSo\nqKjAwMC8vDyyEwEAOHbs2ODBfQBmA/QHCPHy8tywYQPZSSF+2BWLEBIbf3//jIwMdXX17du3\nk50LAEC7du327t07e/ZsJpPJidjY2AQHBxO3zM/P79evX05ODuchjUZLSEjgNE41SySuPFFY\nWBgXF1dVVWVjY9O5c2du3N/ff//+/cXFxdxI//79SVycQ0bMmDEjLy9PV1dXFtp727dv//Dh\nw6SkpK9fv1paWpqbm5OdERIACzuEkNhUVlZy/5QR06ZNGzhw4JUrV4qLiwcMGODl5UWlUomb\nbdmyhVvVcRw4cGD+/PkCTyM1A2StPBERETFt2rSSkhIAUFJSWrZs2bp16zhPmZiY3Lt3b8mS\nJY8fP1ZTUxs9evTmzZuJk0IrGll7T1EoFCsrKysrK7ITQXXCwg4h1Mz16NGjR48e9W+TkJBA\nDL58+bK5FnakNE9kZWX5+vqWl5dzHjKZzPXr11tbW7u7u3Miffr0wW4JhESE99ghhMRGflee\n0NPTEzLYPJDSPHHv3j1uVcdFXN0V8ZK1lSeQ7MPCDiEkNtevX4+Ojl6yZAnZiTTamDFj+CJt\n27a1tbUlJRkpIKV5oqioSMgg4qLRaDExMYGBgWQnguQGFnYIIbFp27atm5ubwJvYZJyvr+/C\nhQu5/QQGBgbnz5/X0dFp1CB0Ov3du3dZWVkSSFDMSGme6N+/v5BBxGVoaOjq6opzxSHh4c8K\nQggBAOzYsSMlJeXs2bM3btxIS0sbNmxYo3Y/cuSIgYFBjx49jI2NBw8enJaWBgCFhYWbNm3y\n8/NbuXKlTE3JRkrzxODBg3/77TfeSJcuXebNmyflNBBq3nBJsYbhkmIIofrdvn2bb5n27t27\nX7hwwcHBobCwkBNp2bLl9evXv379+vDhQ1VVVXd395EjR5KRLJmYTObhw4cjIyOrq6sHDx4c\nFBTU2NOiCMkCWV5SDLtiEUJIVMePH+eLvHv3btq0adyqDgCqqqrc3d2rqqo4D8PDwxcsWLBr\n1y6pJcmLyWSmpaVJv+dXSUnJ39/f399fysdFSHHgpViEkNjI2soTUiPwMuvr16/5ItyqjmP3\n7t3Pnz+XXFb1kIWVJ6qrq/GSUYNkauUJJBewsEMIiY2/v394ePjOnTvJTkTaBJ76UlZWbnDH\n+Ph4CaTTMBJXngCA2NjYfv36aWhotGrVaurUqd+/fycrE9k3Y8aMsLCwsLAwshP5n8jISG9v\nb3d393Xr1pWWlpKdDuKHhR1CSGxkbZZ8qVm4cKG6ujpvxMXFZcSIEQ3uSNbKCmStPAEAiYmJ\nbm5uiYmJtbW15eXlJ06cmDhxIovFIiUZ2Sdr76ng4OBx48adOxcfFZW/atXqX3755cePH2Qn\nhf4DCzuEEBJV9+7d7969a29v37JlSwMDg/nz51+4cCE0NLRjx47cbYjdV0pKSg4ODlJN9CdS\nVp7g2Lt3b01NDW8kLi6OrCoTNUpaWtrWrVsBZgF8AngGEPvx45ctW7aQnRf6DyzsEEJIVAwG\nIy4uLjs7m0qlmpmZjRo1Sltb++nTp9XV1ZwNOnbsePv27alTp3J3oVKpmzdvbnCtMwkhZeUJ\njvfv3xODKSkp0s8ENdbPW0KDADhzVdoD2D579ozMnBABdsUihJColixZsmfPHs7/P336dNSo\nUaGhofPnz2cwGJxgRkaGj49PYmKin5/fo0ePVFRURo4c2atXL7ISptFoPj4+vE27UmNubv7k\nyRO+YOfOnaWfibh8/fr10aNHLBZryJAhZJ0HlY5WrVoBAEAxT6xYS6sTOdmgOmBhhxBCIiku\nLg4NDeWNcJa351Z1HB8/fty4ceP69evJuvzKi8TmiZkzZ547d47JZHIjffv2HThwICnJiG7/\n/v2LFi3i9DurqKhs3rx54cKFZCclKba2ttra2j9+zAU4CmAIsBPg9ciRc8nOC/0HXopFCKH/\n+fDhw6VLl2JjY7lXURv07t074rQdAjs9N23aNHz4cL47zEhBSvMEg8Gg0+l2dnanT59u3749\nJ+jq6hoRESGwiSQiIsLLy8vZ2fnPP/+UzSVlk5KS5s+fz53Fhk6nL126lHg+stnQ19c/ceJE\nq1apAL0A9AA2+Pj4zJo1i+y80H9gYYcQQgAAbDY7ICCgW7dunp6ejo6O3bt3T0hIEGZHExMT\nYrCuBRXi4uK2bt0qUqLiIOXmibS0tJEjR2poaGhoaDg4OHTr1i07OzszM/PHjx8xMTGmpqbE\nXVasWOHh4XHx4sXbt29v2rSpT58+BQUFUktYSDdv3uQ7L8tkMm/cuEFWPlIwZsyYtLS0EydO\nhIaGPnv27OTJkxQKheyk0H9gYYcQQgAA4eHh4eHhtbW1nIcZGRkTJ07knox59erVyJEjdXV1\nO3XqtHTp0vLycu6OxsbGw4cP5xstPz+/rmudsbGxEki/caTZPPHjxw8XFxdODcRkMuPi4pyd\nnXNycoyNjX/es8Xvy5cvmzZt4o1kZWWtW7dOKvk2QnFxsZDB5qRdu3a+vr6BgYHW1tZk54IE\nwMIOIYQAACIiIvginz9/fvXqFQB8+PBh6NChN2/eLC4uzsjI2LZt26RJk3gvv545c8bV1ZVv\nd26NyIf39jKySHPliatXr/KtzJGfn3/69Ol6dklISCD+7ZG1Skc9BgwYIGQQIamRv+YJNpud\nkZHx6dOnsrIyANDW1rawsDA2NiY7L4QQKCkpcf+UOwLvips6deq+ffsuXbrE+cDhioqKevny\nZf/+/TkPDQwMYmJiXrx4QTyH0aJFC74aZciQIWJNvCmk2TwhcCqT+uc30dbWFjJIrnHjxo0Y\nMeLOnTvcyKBBgyZPnizGQ8j1ewqRQp5+VoqLizds2HDq1Kn8/Hy+p0xMTGbMmLFkyZKWLVuS\nkhtCCACCgoLOnDnj5+dHdiJN0a9fv6SkJL4g5+YwS0tL4vZv3rzhFnYcfMUfh4aGBm9cV1f3\nzz//FEe+IpFm84S5ubmQQa4BAwbo6+vzldqjRo0Sc2Yia9GiRXR0dFhY2K1bt2prax0dHRcs\nWCDeIiw4ODgiIkK8xaKi+f79e1xcXE1NjY2NjVxPrCMkiryswZyTkzN48OCMjAwLC4vBgweb\nmppqaGgAQGlpaXp6elxc3Ldv3/r06XPv3r3WrVuL99AHDhzw9/cvKysjThyPEGo2Pn/+3Ldv\n35KSEuJTRkZGWVlZfMG7d+/y3Vr39etXYiOFqqoqXxtseHi4v7+/OFKWD9+/f+/Tp09OTg43\noqOj8+rVK4E9E1y3b9+eNGkSd6a9yZMnnzx5ksT1bZGcur+KCwAAACAASURBVHjx4syZMzlr\n2iopKf3111+rV68WfVg6na6qqhofHz9o0CDRRxMztpyYPn26srLyxYsXBT7LZDLDwsIoFMqC\nBQvEfuj9+/cDQFlZmdhHRghJyOvXr0+dOkWj0aqqqoTfKyMjw8nJifg52aFDB76IhYVFRUUF\ncYQxY8Y0+Knr6uoqvhfaRAwG4+3bt1I73L///su9SN2rV69Hjx4Js1dhYeH58+f37dv3/Plz\nSWeImqWMjAx1dXWAwQAvAT4A+ADAjRs3RB+Z89tafHy86EOJndwUdgYGBtOmTat/Gy8vL2Nj\nY7EfGgs7hOQIk8nkvW7VqVOnxMRE4Xd/8+YNsRRzdnYOCwvT0tLiPOzXr9+bN28E7l5cXPz7\n778rKysDgIGBwZw5c4ij9e/fv8E0BFaNYhQdHa2rqyvRQxAVFRV9//5dygdFiuzIkSMAAPAR\ngA3ABqADtJ0zZ47oI8tyYSc3p7ULCwsbvDRuaWmZl5cnnXwQQrJp69atZ86c4T789OmTp6dn\nPY2obDb74sWL/v7+gYGBUVFR3bp1s7W15dtm2rRpAQEBOTk5z58///Dhw4sXL4hrvObl5V24\ncOHy5cuLFy+uqKjIzc3NyckJCgoiHpHvzjw+Z86cMTc319DQ0NHRWbJkSWVlZcOvufFIWXmi\ndevWenp6Uj6o/Hry5MmKFSuWLl0aFRVFdi7yqqioCIAC0O5nQBmgjWxOdi1OZFeWwjI1NfX0\n9Kx/mzFjxpiZmYn90HjGDiEhMZnM3Nxc8Y6Zm5vr7+/ftWvXnj17Ll68uKSkpP7tBS5OlZSU\nJHDj2tracePG8W45a9asr1+/ci/Iampq7tixo8EkL1++zJ2SjUqlLly4kPsU3wJTenp6WVlZ\ndY1DnHLFz8+vwaM3AYvFysjIkMTISCxWrVrF+2Pg6elZW1tLdlLy5969ewAAsOnnGbtbAC22\nbdsm+siyfMZObgq7BQsWUCiUbdu2VVdXE58tLy/nvA2Cg4PFfmgs7BASkoeHB4VCOXXqlLgG\nLCsrs7Cw4P2Gs7GxodPp9ewi8NT+3bt3BW58/vx54saxsbFsNjs3N/f169cCP3D4ZGVlETur\nLly4wHm2trZ269atpqamOjo6vXr1evjwYT1DCZwJ5fv37xUVFc+ePUtMTKz/tTcPAiuY2tra\n48ePu7u729vbBwcHFxYWSj8xqXn58iXxx+D06dNk5yWXJkyYAAAAfQEcAKiGhoZ1/ZrXKFjY\niUFxcXG/fv0AQEtLy9HRcerUqYGBgXPnzvXz83NwcFBXVwcAOzs7SZRfWNghJKR27doBgFhu\nYeHYvXs38Rvu0qVL9ezi5eXFt72SklJBQYHAjQMDA4njr127tlFJ8l755fL19eU8++jRI1VV\nVW5cVVX1wYMHdQ2lr69PHCokJKRNmzac/zczM7t3716j0hNIys0TwmAwGFu2bDE1NaVSqZaW\nlny/HvD1EZuamhYVFZGVqqTt2LGD+GMwY8YMsvOSSwwGIywsrEuXLtylz5SVlbdu3SrisFjY\niUdNTc2OHTusrKyoVCrvj7uysrKNjc3BgweZTKYkjouFHUJC4hR2NjY2Xl5ec+fOffLkiYgD\n/v7778RvuL/++queXdLS0rhdDg0Wan/88Qdx/I0bNzYqybCwMOIgo0eP5jzbu3dvvqd69uxZ\n11A2NjbEoTitGFxt2rT59u1bozIkIqV5on5//fUX3ws/c+YM56nk5GTiX8vy5cvJTVhcoqOj\nnZycLCwsXF1dOaeW//77b+LrnT59OtmZyqsnT54AAMBEgC8AXwAmKikpifjphIWdmFVVVaWl\npb18+fLly5cfPnyoqalp8lDp6elCTiaJhR1CDTI0NOR911Cp1PDwcFEGJH7ZA0BYWFj9e6Wn\np0+fPn3AgAFubm51zZHE8c8//xDHb+wnvsCZftetW8dms0tLS4k9ChQK5cePHwKHOnHiBN/G\nfFeiOY4ePdqoDIliYmL09PREHESMOLOC8b1MbgV89OhR4l/CiBEjyM1ZLE6ePMn3uiIjIwX+\nRJ08eZLsZOXV6tWrAVQAKn7eaVcBoLJ69WpRxpTlwk6eVp7gUlNTE/hhV1hYWFxcXP+E5nw6\nduwYFxdXf99ZVFSUwOtBCCE+nTp14p2HlsViLVy40MvLq8nThnt4eGzdupXBYHAjmpqabm5u\nDaZx+PBhYcZ3d3f39/fnnJXnWLlypcDTZvXo37//tGnTeIsPY2PjO3fuhIWFdejQgbikmJKS\nErGI4fD19S0pKVm9enVxcTGVSp0yZUpFRcWHDx/4Nvv69WujMiSS5soTwkhPT+ebxhkAUlJS\namtrW7RoIfDnR+xz0ZMiODiYL7J06dLU1NTly5dv2rSJGxw+fPiUKVOkm1rzUVZWBqAGwF2Y\nqiWAmsB1YpoHuSzs6rJt27YtW7awG7OWBoVCaXDa6PT0dNHyQkhRED8rq6ur//33X0dHx6YN\n2K9fv8OHDy9YsICzIES7du0OHz5sZmYmYp68wsPDJ02aFBsbq6ys7OTkRFzsVRiHDh2ys7O7\ndu1aWVmZoaHh6dOnObVXbm4ucWMHBweBhR2bzT506FBERESPHj2sra2XLVumr6+/efPmy5cv\n821JvLzbWC1atBDvX6OITExMqFQqi8XiDZqamnLOdw4ZMqR169bFxcW8z7q7u0s1RQngzInD\nF/zw4UNFRcXGjRtdXFxu3LhBp9Pt7OzGjRvHvUUMNdbAgQMB/gYIBwgAAIBwgFKB7fPNBNmn\nDMWJ86uP2IfFe+wQEpLAqkjIZQbqUVJSEhsb+/Dhw/LycrHkKVHEafB4v5LNzc2/fPnCuz2D\nwdi+fXvXrl357h7u2LFjaWlpYWGhkZERb3zgwIGi98bKYPOEj48P398b782OnJsCOXEqlTpv\n3jxJ55Ofn79169aAgIDt27dLqAm3pqZGRUWF71Vra2vjzCbixWKxnJ2dAQCgJ0BPAHB2dmax\nWKKMKcuXYrGwaxgWdggJiXhLnJ6enlxUY2LEWcaaz9q1a7ds2XLx4kXi/CmLFy8mbs8REhLC\nZrMzMjK8vb2NjY07deoUGBgoliJDBpsnSktLfX19OUWwiopKcHAw31dvUVHR5cuXjx079u7d\nOyHHZLFY+/bt69Kli4qKSvfu3Y8fPy7kjomJibyXevX09IQ/aKNMnDiR7x8dmyQkgdMbO27c\nuHHjxoWFhTEYDBEHlOXCjsJuzIVLEtU/VztHdnY2Z3JU8R76wIED/v7+ZWVlxKmqEEK8qqur\nXV1d4+LiOA+1tLQuXrzo6upKblZS1r59e+L1tQ0bNvz555/EjUtLS1u3bs13Ex5Xnz59Xr16\nJf4UAW7evOnj4/P9+3dJDC6KHz9+ZGVlderUqWXLlg1v3ZBt27YtXbqUN3L48OHp06c3uGP/\n/v35JpOzs7N78OCB6CnxKSoq8vT0vHv3LufhqFGjzp07x9fWjWQQp90nPj6+wbu5pE9u7rFL\nTEwEQts/n3pWDUIISYGysvL58+cTEhISExPbtm07evRovj5ZGVRZWZmcnEyhUHr16sWZEVNE\nfB0kHBkZGQI3fvfuXV1VHQDk5+eLno9AUmie+PLly+PHj5WUlIYOHcqZB0cY2tra2traYkmA\nzWZv3LiRL7hhw4YGC7vS0lLONw6vp0+f1tTU1NX10mS6urp37tx5/fp1RkaGubl59+7d+TZg\nMplFRUVt27blRvLy8tTV1bH4Q3WRm7Vig4KCNDQ03rx5U123JUuWkJ0mQgrN09Ozffv2JSUl\nK1eunD17tuxXdRERER07drS1tbWxsenUqdO1a9dEH5M4QzIAmJiYCNy4rjiH5K4SSLp5Ytu2\nbV26dPH29vb09DQ3Nz916pTkjlWX7OxsTs8Nr8+fPze4/K7ANoXG9i7ExcVNmTJl+PDh8+bN\ny8zMrH/jXr16jR49mljVAYC7u7uhoeGVK1cAICoqqlOnTgYGBtra2i4uLp8+fWKz2QUFBY1K\nDDV/5F4JFh6dTu/bt2///v3ruWsY77FDiFxiX3lColJSUviu96mpqaWmpoo4bGZmJl9B1rJl\ny3ru0LK0tKzr89nf31/EZOoi0eaJ+/fv870QVVXVlJQUCR2uLgwGg3g9t23btsLsS7z5Z+jQ\nocIf+tChQ7z7amlpvX//vmmvgnNmbvHixQkJCSoqKgBWAPsB1gK01tfX56xQrKuru3nzZmy5\nkCZZvsdObs7YKSsrnzlz5u3btwLvU0EIocaKjIysqqrijVRXV69du1bEYS9evFheXs59SKVS\nDxw4UE/15uDgIDCurq4+f/58EZOpC41Gs7Ozk9DgUVFRfJGamhoajSahw9VFSUmJOPebwLVM\niI4cOcJtwgUAfX39gwcPCnncmpoavhVNysrKgoKChNy9npTodE2AWIDZACsBjn///r209FeA\nPUVFQ5ctWyZwvQqkgOTmHjsAsLS0zM3NredGupEjR+ro6EgzJYSQ/MrOziYGr169ymazmzxn\nWH5+/vLly3kjLBbryZMnxLk8uAROSmdmZnb27Nl6ykERtWjRgrgkhohYLNbJkyfj4+N/ruD0\nH0VFReI9nDB27tzJYDBOnDjBZrOpVKq/v/+6deuE2bF3795paWknTpz4/Plz586d/fz8hP9y\neffuXUVFBV/w+fPnjUud4MOHDwCWANxeXVsAXwDOUiXzAEbt2bMH70dCIF+FHQBwTjvXxd7e\n3t7eXmrJIITkWq9evYjBqqqqT58+de7cuWljvnz5knedDI6nT5/Ws8u4ceNCQkJ4+yS0tbXv\n3bsn0XvgxN48wWAwRowYUU/fqDAzG4idhobGsWPHduzYkZmZaWZm1qi2jDZt2ixatKgJBxV4\nFNE7Qrp163bnzimAfABOI8U9AN7vO/uvX29UVlaKpQEIyTW5uRSLEELiNXnyZIFLRdf/C2T9\nBLY7aGhocBY8FLhLu3btoqKiuOftunbt+s8//0h6WQixN0/s37+/nqpu5MiRDS4EJzmtW7fu\n06ePuJptG9SxY0fiqdZRo0aJOKy/v3/LlnSAIQBbABYDTAN4yPP8QyMjI6zqEGBhhxBSWOrq\n6p6ennxBa2trfX39Jo/Zt29f3pkpOD5+/Kinp6erqztw4ECB89INGDAgKSkpJycnKysrJSVl\n6NChfBtUVFQcPHhw8eLFu3fvLiwsbHJ6XEwm8927d6KPw/Xw4UNisEuXLk5OTjt27IiMjKRQ\nKN+/fw8MDOzataulpeX8+fPF8kJkEIVCOX/+vKmpKTcyfPjwDRs2iDhsjx49YmJi+vbVbNHi\nT1XVsK5djQBOAPgB7AOYCBA1b948EQ+BmgmyuzfkAHbFIiQkqXXFpqSk3Lp1KyMjQ8RxSkpK\neFcAMzc3F70rlkaj8S5awDf7pqGhYX5+foODpKen//rrr126dBk+fPjZs2eNjY25I+jq6iYk\nJIiYpNhXnvD29iZ+vxw+fJi7QWVlZY8ePXif7dOnT1VVlRhzkCkVFRVXr14NCwu7f/++KONw\nu2K5kcrKSiaTWVNTs2zZMs4yJ9ra2uvXrxdxjSzUKLLcFStn99ghhBRcYWHh5MmTb926xXn4\n22+/HTt2TE1NrWmjaWtrx8fHx8bGvn//3tjY2NXVVfQZaJ2cnFJTU6Ojo4uKilJSUvhmvsjJ\nyYmIiJg1a1Y9I9y6dcvNzY0zcXFaWlpsbCzvs0VFRVOnTn39+rUoSYq9ecLR0fHs2bO8EWVl\nZd5Tj6dPn3779i3vBklJSRcuXPDz8xNjGrJDXV193LhxkhiZM4cLlUrdtGnThg0b8vPz27Vr\n1+R2H9T8YGGHpCo3NzciIiInJ8fKymrMmDF8q54j1KDZs2dzqzoAOH/+fLt27Xbt2tXkASkU\niqOjo6Ojoziy+3/6+vpTp04FgBkzZhCf/fjxYz37VlZWjhkzpp7lKADgzZs3379/F+WSsdib\nJ37//febN29eunSJ81BJSWn79u0WFhbcDZKSkoh7CQxKQUVFRVhYWFpamrW19dSpU1VUVEhJ\nQ3QtWrQwMDAgOwskW7CwQ9Jz9+5dDw+P0tJSACUA5oABA2JjY3EFXiS8qqoq4uIQ58+fF6Ww\nk6hu3boJGeRgs9mjR4/mXOWpH4vFEiUxsTdPUCiUixcv0mi0+Ph4dXX1UaNG9ezZk3eD9u3b\nE/cSGJS027dv//rrr3Q6HQCOHDkSHByckJDQ5D5ohGQNNk8gKaHT6VOmTCktNQFIBagGOPfi\nReKKFSvIzguJE+eGcd7bxsUrPz+fOJNlQUEB50taBk2ePJmvl8LU1NTDw6Ou7R8/fsxdD74e\nFhYWIp6nEXvzBIezs/OaNWuCg4P5qjoAGDt2LN8VcyqVSlwZQtLKy8tHjRrF+wNTUlLi6uoq\n5TSEx3k31b/0HEK8sLBDUvLmzZvc3FyA9QBdAKgAvwGMFuY7TGH9+PEjKCioa9eupqamkydP\nrmsVeZly/fr16Ohoyc2SamJiQpwntlu3bpK7lJaenn7z5s20tLSm7W5oaEij0YYOHaqkpKSs\nrOzs7Hzr1q16prpNTk5ucEwNDY2jR482LR8uia48AQCvXr1ycXFp1apV+/bt586dW1xc3L17\n95MnT/LOOcJisQIDA6W8XkJwcDBxosGPHz+WlJTU1NQ8ePDg2rVrX758kWZK9aPRaDExMYGB\ngWQnguQH2d0bcgC7YsXi8ePHAABwE4D987/JFhYWZOclo5hMpr29PQAVwANgGoCWkN2UzV5Y\nWBjfh9i1a9ckcaDy8nLeU2ujRo0qLi5u8mjV1dX1rHPNZrMZDEZZWVlkZGRdn9UTJkyYNm3a\nmjVrvn792uQ0uGJiYvT09EQfR6BPnz7xTRpnb2/PaeTkXaeLQ1VVtbKyUuA4DAYjNDR02LBh\nZmZm3bt3DwgIePXqlYi51XXqKzo6mns1lkqlLly4EJdeRfWQ5a5YLOwahoWdWFRUVGhqagI4\nAJQAsAGeAqhPnTqV7LxkVExMDAAAHP9ZBCcDKK9evZrsvGTChQsXBg0a1KFDh+HDh9+6dUtC\nRyE2rnp7e0viQLm5uZMmTeJ043bt2rVNmzYCK4/169eL8aAsFkv0yWLqsnDhQmL+9+7d27hx\no8CX9vz5c4HjTJw4kW9LKpV69uxZUXITeFOvmppax44d+YKHDh0S5UCoeZPlwg4vxSIpUVdX\nDw8Pp1IfAhgDdAUYZGSku2nTJrLzklE/J7PgfrH1ArAU5jqdIvD09IyPj8/Kyrp7966zs7Mk\nDsFmsy9evMgXvHr1Ku9VvE+fPh06dGj//v18s3g0CpPJHD9+/Llz5zjfE6mpqaWlpQLXSLCy\nsmryUYjE3jzB69mzZ8Tg27dv+eZt4fry5Qvx8uijR4+4PbZcLBbL39+/urq6ybkJXEdu7ty5\nxFsdrly50uSjIEQiLOyQ9EyZMiUhIWHhwhne3v23bNn09u1bbNSvS4cOHQAAIOVnoALg688g\nkriKioofP37wBaurq7kr2e/du9fS0nLWrFlz5szp06fPqlWrmnaghISE+Ph43giDwRg5cqSR\nkRFvcNiwYSNHjmzaIQSSUPMEAKxcufLJkyfEuKmpKbHxhWPixIm9e/d+8+YNbzAhIUHgxqWl\npaL8hkNs2Bo3btygQYOIW+bl5TV2cCaTmZ2dLWLDMkKiIvuUoRzAS7FI+vLz8/X19QG6AFwE\nuAXgqKSk9OjRI7LzasCtW7fmzJmTlZVFdiJiQJz/wsDAgPNUUlIS33oSAHD79u0mHOX48ePE\nj2UbG5vc3NyAgICePXv269dv5cqV5eXlYn1x4l95gqOuewQ7duxYWlq6cuXKer6MunXrxnsb\n4smTJ+vaUsQ77a5du9a/f381NbXOnTtv2bKFTqd/+vSJeJTp06cLP2ZNTc3SpUs5bb8aGhor\nV65kMpmiJMl1/fr1uXPn5ubmimU0JC6yfCkWC7uGYWGHSPHgwYNOnTpxvmO0tbWPHDlCdkYN\n49yoxLv8kfwiXoo9evQo5ymBjZxNe9V8p+s4fHx8xPpSBJBQ84TAc/AdOnRISkpis9kVFRX1\nX1BOTEzkDpWVlcVZTYuPoaFh/W0ofCoqKnbt2uXj47No0aIXL14I3Gbv3r18lbqOjk6j7kEM\nCgriy3PNmjXC714PzjJ9K1euFMtoSFywsJNvWNghstTU1Lx8+fLx48elpaVk5yIUqa0VKx3R\n0dHDhg0zMjKys7O7evUqN7569WpiwTFr1qwmHIJOp1tbW/OOo6ysLIVvCwk1Twhc2Co4OJi7\nQU1Nzf79+6dNm8a7nC7XzZs3eUeLjIzkmxpGW1s7NjZW+HyKi4t5V7+gUqkHDx7k24Z455+a\nmlpdJaBALBaLWIO2a9dO+BHqQVwrFskCWS7scOUJhGSXiopKv379yM5Ccbm5ubm5uRHjAwcO\nFDLYIGVl5StXrgQGBkZFRbFYrJYtW1pZWaWkpNjY2Ih3LVc+kmieqKioYLPZxDinz/fz589J\nSUkGBgbTp0+fPXt2RUXFhQsX+FLq06cPb2TMmDHp6elxcXEPHz5kMpmWlpYeHh6cXx6EFBIS\n8uHDB+5DFou1YMGC8ePH8866Qjw1W11dnZ6e3r9/fyGPkpeXV1ZWJjAo8KQjQhKFzRMIIbGR\n9MoTMsLV1XXChAm8ETs7O19fX77NioqKHj58+OHDB4HlDpeRkdHFixf79u0LAFVVVU+ePJk+\nfbq3tzd3g8LCwr/++svNzW3KlCk3b94Uy0uQRPOEhoYGZ9IWPvPnz/f39+/cufPYsWNtbGz6\n9u37/v37NWvWaGho8G7m7u7OtzQFAOjq6o4bN27Hjh179uyZM2dOo6o6AHj06BFfpKqq6uXL\nl7yRb9++EXcUGKyLgYEBsZG5ffv2YqnqcOUJ1GhknzKUA3gpFiEh5eXlRUdHi+u2cbJUVVUx\nGIz6t2GxWEeOHJk4ceK4ceN2795dU1PD+2xtbe2yZcu4t20NHjy4/uue+/btI34437lzh81m\n5+bmGhoa8sY3bdok8kuUVPME8VYzd3d34i2JPXv2ZDKZ79+/nzx5cuvWrbkXcPX09PiuxorI\nxsaG+Bd7//593m0EtnTcvXu3UQcKCQnhG2Hbtm1ieQnfvn2LiYlhsVhiGQ2JiyxfisXCrmFY\n2CHF8fTpUx8fn6FDh86aNSslJYXsdKQtPj5+wIABVCpVVVV1/PjxmZmZ9WxcVFT0999/+/v7\nb9q0KScnh/cpYqFmbW1dz3ezn58fsbbYsGEDm82ePXs2X1xJSUn0HknJrTyxYsUKLS2tFi1a\nqKurT5s2jU6nC+yoePPmDVtQU3CbNm0KCgr+r737DoviavsAfJZdlo6ggoggSBB7BUVFYleC\niqLRoAkmltgVayyJ3djQiEGwx15Q7GLBqEGsgAV7F1BBQRAUKcvuzvfHfJnMO7MNRLb4u6/3\nei925syZZweXfXJmznM0P51UKl2/fn1AQECXLl3mz5/PmT7866+/cvq3tbXlPLGamZnp6OjI\nbtOtW7fSLjshlUoXLFhA33S2t7cPDQ3FwhWGDYmdfkNiB1+I6OhooVBISDVC2hNiIxaLr169\nqu2gSic1NXXRokVjxoyJjIykH/nS3KNHjzjLEtSoUaNDhw6enp6jRo169eoVp7GdnR3T0tra\nmn2tfHx8+KlMx44dbWxs7OzsBg8ezEkEx40bx28fHh5OUZTCaaQxMTGfcJEoqpSTJ+7evTtm\nzJgePXpMmjQpJSWlVCf6/fff+fGTf4fE+vbty9915MgRzfsPCgpiH9uoUSP2AmUFBQXs34W5\nufmhQ4f4naSmpv74449fffVVkyZNfvvtt08pLqMv85zgEyGx029I7OALUa1aNUJaEZJPCEVI\nJiG1Wrdure2gFJDJZJs3b+7Xr1/v3r1XrFhRVFREb4+NjTU3N2e+xWvVqqXhyFZubu6ePXs6\nduyoMAWhVatWjd1bp06dOA0aNGjA7FX7lGHTpk2ZsKn/VpD7j1gsvn//PkVRvr6+/MPj4+PL\n51Jq4OTJk+xSIObm5tevX9f88Pr16/PjNzIyOnHixB9//FGnTh3+3q1bt2rYeVxcHP/wFStW\nsNvIZLIDBw7MmjUrLCwsNTVVbZ9nzpz5/fffw8PDnz59qvnbhC8NEjv9hsQOvgQpKSmEEEL+\n+nd1WoqQ30xMTNQ+bVbxOIM0rVq1kkgkUqmUf8vv+++/V9vbhQsXNHwkf8KECfQhJSUlZmZm\n/AZZWVl0gx49eqjtLTo6mh3GzJkzhUIhvcvY2NjNza1WrVo9e/YcM2YM50AHB4dPr1dcUlJy\n9+5dTVryk1QfHx9Om8OHD/v6+lpbW1taWtasWXPs2LHMpVA4gYBdgoRPRWBSqfTFixdMHbvQ\n0FD+4UFBQWW6JJRMJmPPiTE1Nd22bVvZugKDh8ROvyGxgy/Bu3fvBAIBIctYid3IKlWqlKqT\nClh54syZM/zv8jVr1ihcsNXJyUl1b8XFxc7OziqSDDZfX1/6qJKSEvbQIIN5OOzq1atisVh1\nb/wCtnfv3l27dm1AQAC7mbGxcbt27ZiXVapUKVUhN2U0nDzx6tUrfuQmJibsEsGbN2/mt6lf\nvz59K5y/WpfqMi6jR49WGIlcLl+4cCGdJorF4nHjxhUUFGzYsIHfw8iRI8t2TfhPRpqbm2t9\nGRWsPKGbdDmxQ7kTACCEEBsbGx8fH0KWEHKMkDeEbCPkr+7du5eqk5EjR65Zs2blypWfKUii\nZIF5hRs1kZiY+OLFCw0bMw/ViUSitm3bcvY2btyYfnaeENKyZctz5855enqq6I0/Ela/fv2B\nAwfGxMSwN5aUlJiYmFy4cGHVqlW7du169OhRhw4dNAxYBSMjI03q5Jmbm/NrDpuamopE/9VA\nnTFjBv/Ae/fu0WuC8Ys516tXj9++bt26PXv23Lp16+rVqxVGEhYW9ttvv9Hl4iQSSXh4+KRJ\nkzp16sQfOi3tP1rG6dOnOVsKCgoULg1SkYYNGxYR4Ng3sQAAIABJREFUEREREaHdMECPILED\ngP+3devWunXtCelJiAMhP7Zq1TwsLKxUPRQUFDD//5kovLVnZWVVp04d/q1Y9lgXx4ULFzw9\nPRU+wUbjD7n17t2b+XnNmjXsKiS2trZ//fUXu3GbNm2Cg4OVdV6tWjWFpY/v3LnDX0I+OTnZ\nx8dn/Pjx7du3nzVrVrNmzXx9fVesWCGRSJT1r1bXrl0TExPVNrOxseEXXu7SpQuT7b1+/fr1\n69cKj7158ybdODY21tfXt2rVqk2aNImMjKTXneOYNGnSkSNHBg0apHDtCkIIfzht06ZNjo6O\nGzduZKa8CIXCmTNnanIfXKGioiINN1akCvhMgaHR9pChHsCtWPhySCSSY8eORUZGnjlzpgz1\nGipgSbF79+7xU67jx49TpZk8wZ8Ay9avX7+8vLy4uDimCoZQKOSv6ZSXlxceHj5+/PgVK1Zk\nZmayd8nl8lmzZim7G1u3bt3Lly8rDOz58+f89k2bNqUo6u3bt05OTpw4y+GCqvPw4UP24GKD\nBg3YV7W4uFhhUWKifLFUhfNkb926pSIGqVTKPIDI9vDhQ4qi0tPTd+3atXHjxk8s0LNgwQJO\n/0KhkD6FFmFJMd2ky7dikdiph8QOQEMVs1bsunXrmGRCKBR+9913ycnJdBqqYbmTadOmKcxF\nCCFVq1Y9fPjwypUrN2zY8ODBg1OnTkVFRT158qRUEaoe6fT29uYUNGbjj5B17979wIED06dP\n53elLEFUS/PJExRFFRQU7NmzZ+nSpQcOHOBPpvnuu+/4gYnF4uTk5JycnBMnThw+fPj169fM\nr+Pjx4+NGjViN544caLaGPjzZ01MTFRcxjIoKCjgFJeZPXt2OfZfNkjsdJMuJ3ZYKxYA9Mzw\n4cO7desWGxu7bdu2S5cuRUVFRUVFtW7des+ePTVr1uQ88iWXy3fu3EnX7u/UqdOQIUNEItHD\nhw/53Xp4eAQGBqampvbq1YveYm5uvnHjxgEDBpQ2wk2bNqnYe/Xq1XHjxhUVFeXm5rZs2XL8\n+PHs+8t79uzp378/+z5pTExMTEwMZwEu2vXr1xUurqBWbGxscHBwdna2Jo3NzMwUZm+0NWvW\n5Obmnjp1ir1RLpf//PPPDx8+zMvLI4QIBAKKoqysrJo2bWptbd24ceMWLVrk5uZaWloGBgay\n73ErM2nSJE6t5rFjx6qdoVIqZmZmV65cWb9+/eXLl62trfv06dO1a9dy7B+ggmg7s9QDGLED\n0FDFjNjRFi5cyPlrxi/DIZVKOSVwO3fuLJPJ+CtfEUL279/PT8gsLCxKOy+ypKRE4X1DZczN\nzfv27csunCuTya5fv86fT8q3b9++sl298l15QiKRXL9+vXXr1pq/a1Ka8bCHDx8ePHhw6tSp\n9M1xW1vbWbNmle9wnSYkEsmZM2d27NiRnJxcYSfFiJ1u0uUROyR26iGxA9BQRSZ2DRo04OcK\nL168oPemp6cHBQUpHNHZvn37vXv3OPVKateu/eHDh/79+/Pb79mzR20wEolkw4YNQ4cOnTx5\n8ujRo0uV3zBmzpzJdCiVShUO0bFVqVKF82yf5kq18oQKKSkpAQEBxsbGyiY9qGBkZPTs2TPV\n/RcXF7PLFnp5eWl+B5lx5syZwMBAT0/PgQMH3rhxo2zv9P79+3Xr1mUi6du3r7LM8ty5c0FB\nQV9//fWoUaPUvkG1kNjpJiR2+g2JHYCGKjKxU/jMPr2ul0QiadmypbJ8gq6UdubMGXpRBIFA\n0Llz50ePHlEUpbBSxsaNG1VHUlhYqOJ0mmMnOoWFheySInzW1tanT5/+zNf4P48ePerfv7+T\nk1PdunVnzJhB/z0sKCho2LDhp7xltUkzv5YKf1xWNbrqCkMkEp0/f15Fe5lM9tdffwUHB//0\n00+7d++mn92Uy+WNGzfmRPLrr7/yD9+4cSO7jbm5Ob0qbpkhsdNNSOz0GxI7AA1VWGJ37do1\nfpZgZGREL8mgsIgxY+rUqUw/b9++Za/iwJ8XSf5drp7j6tWrS5cuXbly5d27dxctWqTidKUS\nFRXFnEJ1GbzAwMBPuYClmjzx8uXLqlWrss/u5+cnl8uPHDnyie/32LFjqk/t4eHBP4qz0q4K\ncrmcKS7IaNmypbL2MpmMU4Zm4MCBFEU9ffqUHwZ7EbmsrKybN2/m5OTwZ1v7+flpGK1CSOx0\nky4ndqhjBwD65/bt2/yNTk5O9O3LW7duqTiW/UR8lSpV2Hc8J06cyLnDO2nSpHr16u3du3f6\n9OmhoaHPnj0jhISEhHh7e0+bNm3ixIlNmjThjAmpFhoaWqlSJWV7r1y50rJlS0dHx86dOw8Z\nMkRZJRFCyOXLlxVeBA3RteU0bLxq1aq3b9+yt5w8efLChQsK56BozsbGRu3MD4VF8t68eaPh\nKVJSUvgTRG7evCmVShW2j4qKOn78OHvLrl27Tp06xXn7NLrnnJycfv362dnZNW3atFq1avn5\n+ZxmmtQLBChHmBULAOWGvnuo+h5iuahRowZ/Y8uWLRcvXrxt27bHjx8rPEooFE6bNq1z587K\nurWwsEhISIiIiLh8+bKlpWWfPn26devWtm3by5cv0w1mz54dEhLy559/ModIpVLN8xszM7OR\nI0e6u7sPGjSIXkSBs5dZtCMjI+Ps2bOtW7e2sLC4efNmVlYWp/Hr1699fX1v3LihsN6vWhqu\nPEFTmCjfvn1b9ZKvtra2ffv2PXz4MD94QoiVldWWLVv4w2kczZo1i4uLY28xNTVlP+umWuXK\nlekJueyNNjY2yv6JXrp0SeHGadOm0dVV2NubN29OCBk2bNjBgwfpLSUlJfzDbWxsNIxWoQr7\nTIHh0PaQoR7ArVgADYWFhbVo0SIpKelznyg/P5+f0KjI2OgKwzdv3iztiX777TdOV5qU2DAx\nMfnll1+8vb05jdetW0d3GxISwjnE2tra2NhYYW/8p7sYY8eOLdsFLNXkiSFDhvBPfejQofz8\nfE55OVNT09mzZ8+bN+/48eP002kSiWTy5Mm1a9d2cnL64Ycf9u/fv3Llyk2bNml4O/XSpUuc\ny7J8+XJNDoyJiWnbtq29vT1/qZLhw4crO2rKlCn8d7po0SKKolasWMF5pxMmTBg6dKjaWSMh\nISGcwLp160YvoRYfH6/2jSxZssTb21t1AWeoeLp8KxaJnXpI7AB00I0bN+jZD4QQc3NzhSuW\nMsaMGVO2s2hSc4QQYmtry35pZGRkampK/ywSiRo0aDBs2LALFy7Qfebm5vLrofDrErMpq5/S\nrl27crugyvEXUa1Ro8a7d+8oinr8+HHnzp3p5KZu3bqnT58uLi5OSko6d+5cTk6ORCLp06cP\nc5Srq+v169dLe/akpKQ+ffrUrVu3Y8eOe/fu1eSQw4cPK7uSnTp1ev/+vbIDOdX4aAkJCfTe\nQ4cOde/e3dPT09/fX8XKJexUr1OnTuxC2Zs3b+Y0PnnyZGkvCOgCJHb6DYkdgG6SSqU3b948\nf/78u3fvVHyXE0J27dpV2s6zs7P//vtvJnf8FCKR6NKlS0zP8fHx/Db8hW7Z3N3dFW4PDg4u\n26Ur1eQJiqIiIiKYVMbd3T0iIiImJoYZdcvPz8/KyqIo6urVq8z9WXNz827dunECrl27tlQq\nLVvMmuOPcZqamm7ZsoWeNK0au8ahUCj8/fff+W0UltpheHp6HjlyZO3atZzpt3K5nDMHhRDS\nqFGjcnvbUIGQ2Ok3JHYAuu/69evKvmjNzc2Z+nYaWr16tbIycmZmZu3atVPxva7QjBkzmM6f\nPHmiMBtQsc6BsjOeOnWqbJcrJiamcuXKpTokLy/vwoULkZGRTA5qamoaGhrKNMjNzVX47CPH\n7du3NTxjZmZmSEhI8+bN27Rps3jx4sLCQk2OkkqlCp9IoyvaaCIpKWnZsmUrVqxQeANU4SOD\nbOxa02xpaWn8xkKhsKioSMPAQHcgsdNvSOwAdJ9EIlH4LJq5ufnOnTtL1dXZs2eVfWcLhcIN\nGzZIpdKhQ4eq/nbn8PDwaN++/YgRIx4+fCiXy728vDgNli5dmpGR0aFDB4WHDx8+nL+RXW6j\ntMq28kRGRgbnpjMhJDY2lt579OhRTS6F6jJyjLy8vK+++op9oL+/P/3cnlrOzs6ckwqFQnZd\nm0+hMLETCAQikahJkyb79+9XduDHjx/5t9TLcf0PqEi6nNih3AkAlBuZTKZ5KYryZWxsHB0d\n3aJFC+aln5/f+vXrHzx4MHDgwFJ1tW/fPoXbfXx8EhMThw4dmpeXV9pbtI8ePfrnn3/WrVvX\nuHHjhISEqKgoJrczMjIaOXLklClTHBwczp49++DBg++//57JAIRC4cKFC+vVq8fv09XVtVQx\nsHXt2rUMZTjOnj377t07zsb9+/fTP6Snp6vtwdjYuEmTJpqcKzIyklM97vjx46orFDK+//57\nzpZevXqpXcmD7cSJE926datTp84333zDSfSrVq3KvxVLUZRUKi0pKWnUqJGyPs3NzTlF8ggh\nnCXv+KRSaWZmpuaRA2DETj2M2AFoqE+fPgKBYPv27doKQCaTPXjwID4+Picnp8yd9OrVS+Ff\nS6FQOHr0aPpRs8qVK6v4u6p6pqS3tzf174Kwx48fT01NpSjqxo0bAwYMaNasWUBAwKlTp27c\nuPHHH3+EhYXRNy750xcIIdOmTSuv66ah5cuX88No3749vZcpCsPGmRe8bNkyDc/Vr18/fm9L\nly7V5Nji4uIhQ4Yw9Vy6d+/+9u1bzd/mjh07OOc9ePAgu0Hv3r2V/XI9PT1V9Pz69eu2bdsy\njbt37672m8XPz8/IyCg6Olrz+A2bRCJJS0urgCc1VdPlETskduohsQPQUEUuKfb5zJkzR9nX\ntmo///zz+PHjFyxYkJycvHjx4vbt2zMjiGxisVgikbDPeOHCBU5Rj02bNrEbSKXSr7/+mt2g\nSpUqpX1wkK20kydoa9as4b+dpk2b0nvlcnlAQAAnyCtXrowaNap169Z9+vQ5cuSI5ucaO3Ys\n/1ybN2/WvIf09PS4uLgyrNbq6OjIOa+HhwezV+0zdmlpaSo6l8vl165dO3DggIbPGmLlCUZh\nYeGECRPoqt0WFhazZ8+WyWTaCgaJnX5DYgegIcNI7LKysjSZBEAIMTc3p38wNTVdvHgxv6vc\n3Fz+6J2trS3nWbHWrVtz2lSqVInzpZWTkzN27NiaNWtWrly5Z8+eZUjL2MoweYKiqC1btvAv\ngpeXF9Pg48ePc+bMadiwYc2aNYOCgh4/flzmCPl3Xa2trT8ll9WQwrUuBAIB8xXAKZjMV4aS\nLiogsWOMHz+eEAEhwwn5i5AB5N8Sg1qhy4kdnrEDgHJjAFXyMzMzT58+PWbMGE2eopNKpS9e\nvLh582Z2dvb06dPpjXK5PCoqatKkSfPnz09LS2PfeqP5+/uzsz25XH7jxg1Om7y8vNWrVx88\neJAZH7K1tQ0PD09NTc3Ozj5y5Mgn1mEp1coTDIVLTbBLsaSnpyclJT169Cg9PT09PZ2/vpbm\nOnbsuGLFCqYcoJ2d3c6dO52cnFQcQlHUpUuXtm3bFh8fL5fLy3ZeW1tb/kpuVlZWzCN6bm5u\nKg43MzMrlxI5DAP4TJULqVS6YcMGQn4mZB0hgwnZRUiAwiFkwIidehixA9BQha088ZkcPnyY\nvZCrsqUgGPXr1+f0UFxczL5nKhKJFi5cyF6eoUWLFtnZ2ZyjVAwQWltb79ixo9zfaalWnmBI\nJBJPT09OhFZWVvRjgvx5rHZ2dq9evVLW2+3bt+fNmzdx4sTdu3dzhidlMtnWrVuHDh06aNCg\nWbNmxcbG5uXlqY4tOzvbx8eHObWXl9fp06efPn1ahrt1/Mf7Bg8ezG7Ar8/H+PPPP0t7OtV0\neeWJ7Ozs4uLiijlXSkoKIYSQzYRQ//5vsUAg0LAITrnT5RE7JHbqIbED+BK8efOmVBMnCSGR\nkZGcTpYsWcJpY2Ji8vz586NHj4aHh58+fVphnjFmzBgVZzE1NeXXYHv06NH8+fPHjh27YcOG\niiyElpqayh/Qql27NkVRW7du5Qev8A41RVHr169nj0K1bduWeRdSqZRT0k+ThUOCgoIUXr0W\nLVrcv3+/VO8xOzu7U6dOTA/+/v7x8fGrVq1at27d06dPKYrKzMxkVtQwMzNr3ry5p6dnjx49\njh49WqoT6a+jR4/Sw7cikahv374q0vfyIpVKLSwsCPmBldh1cXV1/dznVQaJnX5DYgfwJVAx\n1ZHh5uZG3xy0tbVVuGipn58f/6h9+/apPnV+fr7CAxnh4eHs9tHR0ezZpvXq1aMX+NJc2SZP\nUBSVkZGhMMLi4mKFq7r9+OOP/E5evXrF3GNlMM9L/fXXX/x+VH+DSqVSFWt81atXrwzjOsnJ\nyYcPH75z58748eOZrkxMTNavX083yMnJuXv3boUNWemOq1evGhsbE9KEkDBCphNi4e3tzZkP\n9DnMnDmTEEJIX0KWE9KNfIbxUc3pcmKHZ+wAQD+kpqZu37598+bNnPJm5eL27duHDh3ib2/S\npAl9I1UsFjs5OdWsWXP27NkpKSk5OTmTJ0/mt1f4aNft27cHDhzYsWPHkJCQly9f0hs/fvz4\n6tUrQkh0dHTbtm3/+eefmjVrBgcHf/PNN/we2CXiCgoKhg0bJpFImC3379//7bffSvV+Y2Nj\nfX19S3UIE7bC7RMnTlQ4q0DhYmhXrlwpKiribPznn3/oHy5cuMA/5OLFiyqiKiwsLCgoULb3\n/v37CQkJKg5XqHHjxgEBAQ8fPvzzzz+ZjcXFxWPHjn306BEhxNbWtn79+px6Ll+CNWvWlJTY\nEhJHSAghiwlZe/Xq1TJc4dKaN2/e/Pnzq1T5h5Ap1avfCgsLUzh1GjBipx5G7AC0LjIykhnj\nMTY2VnaDrwzy8/PXrVvXuXNnhX8hf/31V6lUyn54ixDi6+urrIzW77//zumB89i7ubn5xYsX\ne/XqRc9d4C/kwK9hSwgRCATDhw8vKCigKEphiiMSib7++utt27ZpOICkduWJO3furF+/fteu\nXcyCsDR+gWIVrK2t4+PjDx48eO7cOfaYWXR0NL9x586d6b0jR47k7w0LC1P9jhTWcGaUubai\nwjU/1q5dW7beDEObNm0I6cK6JZpCCPnrr78qLIDyWkTkU+jyiB0SO/WQ2AFoSCqVvn79uty7\nTU5O5s9j0HBlKtXS0tJq1qypLBuwtLTMzc3duXMnf5eyZcqKiorYtUuEQiF/8ildwEIZU1NT\nhWujkX8fNVM4oMXw8PDQ5IEn1ZMnJk+ezCx9YWVlFRUVxeziP0SoTL169YKCgph+XF1dr1y5\nQnfy8uVL/oN6v/zyC72Xv/KHSCS6efMmO8LDhw//9NNPffr0CQ0NLSgoSExMDAoKUlEX+saN\nG2qvicKcmL+IBSFk+fLlHz9+3LdvX1hY2KlTpzRc6KxsSkpK3rx58/n6L4OffvqJEHtCcv9N\n7LYTQi5cuKDtuCoUEjv9hsQOQEOfaeWJZcuW8b9cp0+f/uk99+zZU0VqEhERQVHUxIkT+bsm\nTpyorE+pVLp9+/axY8fOnDmTfRdPcxcvXuQvJksIsbCwkEqlCpdkYOvZs+enXBN+XiUWi5ky\nv5qvzzZ//nzOFmdnZ2asJSIigpPyVqpUiZkjwl6KVygUchacmDp1KvtABwcH/hqsbL169VKd\ne61bt65WrVqEkOrVqy9evLikpITZFR4ezu9w+/bt7P8eaN26tdpJu2WmgytPaOsZO52CxE6/\nIbED0NBnKlD866+/8r9cP/0sMpnM2tpaWTYgEAhGjBjx4cOHBQsW8PcuWLBAk1N06NBBRcKh\nkJGR0ejRo5XtjYqKUtuDubm52gWXVEye+Omnn/h91qtXj+6Tk1SpwCl9Qjt79ix9FolEwp+D\nzE5J4+LiFixYsGTJkuTkZHZ4d+/e1TAAQkjlypV/+eUX/l/vt2/fJicn09vXr1/POWrWrFlM\ny+LiYm9vb/beIUOGeHh4cA4ZPny4Jv8eGB8+fDhz5szJkyezsrJUt9TNAsUVPytW1yCx029I\n7AA09JkSu8OHD/O/s0u1upRC/xZQUOXHH39MSkriPCcnEok0qdWncNkJTSirRmtpaTlgwABN\nDlc7CVTFyhOBgYEKu922bRv132hNGe3Zs4c+S3JyMn+vvb292quqcM6sMmKxmLNq8Lt37777\n7jtm77Rp0/hVlzmZcVFRUVhYWN++fQcOHLh7926FD+w7OTmpjZxx9OhRe3t7+kALCwt+0Rw2\n3UzsaBVZx07X6HJih1mxAKDrevbsyZlS4OPj88MPP3xit0KhkDMrgm/79u116tRZtWoVM3XD\n1NR01apVnDq97969++OPP8aMGbNs2bI3b97QG+kbi2UITCqVKtyen5+/e/dutYc3a9aMX0yE\nQ8XKEy1btlS4/e+//6b3btiwwcbGht5oYmLSoEGD6dOncyrPqYiN/oFZjY1NRckShsIDlZFI\nJJxVPYYPH86MekokkqVLlz558oRzVEFBQWpqKvPSxMQkJCQkOjp6586dNjY2q1ev5p/ow4cP\nGoaUlpY2cODAzMxM+uXHjx/HjRsXGxur4eE6pXLlyl/gpGA9oO3MUg9gxA5AQ59vrViJRBIe\nHt6jRw8/P7/Q0NDyKjf/+PFjOzs71X8kly5deu7cuefPn+/ZsycyMnLZsmUrV65k5gFQFPXw\n4UN2J5UqVUpMTMzJyVF4D/dzMzMzS0xMVPvGVUyeyM/PZ8aTOLp06ZKenk5R1Pv37+Pj4xMS\nEti/iFOnTqmObcSIEXTLW7duNW3alN9g9OjR/HhOnTrVokULsVjs6Og4Y8aMx48fl6qONPtq\n5OXl8dNZ/gCkiYmJsoGokJAQhWfp2rWr2mtO49/5JYSIRKI5c+YobK/LI3ZfMl0esUNipx4S\nOwANfb7E7vPJyclZunTpkCFD5s6dq6JkRv369VesWMEeLvrpp5/oR/I7duzIaVy7du2qVasq\n7OezjnAEBweXYaEwvvj4eGXjeR07dlR2lMJKZsbGxo0aNWrXrl1kZCR9f/Pjx48Ki9tVqVLF\n399/+fLl7GQxPj6ec2P6m2++2blzJ3tIkj/BluHs7MxeluPWrVv8Nvwb3yoemBsyZAi/B7FY\nfOfOHQ2vrYp0f926dfz2SOx0ExI7/YbEDkBD+pjYsSlcFIvBz3U2bdokkUjU3vdkNGzYUNkT\nbGwWFhYLFiyoXLmyht3SzMzMli1bNnny5E2bNqkd0VS78kRYWJiyZ+levnzJbimTydauXevp\n6akwwfL39+f0TN/SVaFly5bFxcWPHj2aOHGig4MDv0GzZs042ZjCdLlatWqcGhyFhYX8N9Ws\nWbMZM2bQwQuFwhEjRnz8+FHZZVm3bh3/RMpq3yh09OhRZW/cx8eH3x6JnW5CYqffkNgBaEjf\nEzuKojZs2EBXslBdQYPWv3//UiV29erVo/+ecFSvXt3MzIz+uXLlyvv376coas+ePRp2S2NP\n1KhZsyYn/eJQMXmC8eTJE4UPvV2+fJndbPbs2SqiOnz4MKdbTWY/TJgwQcU4HJ9QKPTy8goM\nDJw9e/aBAwfCw8OjoqJyc3P5b4q/7hldSYROJekS0CpIJJI2bdqwD//uu+9UH8Ihk8mUzZVW\nOAMDiZ1uQmKn35DYAWhITxO73NzcSZMmffXVV46Ojt9+++2jR48+fvyo9tk7QkitWrVat26t\n+SzRBg0azJ8/X+EN37Fjxx48ePD48eOrV6/u27dv27ZtSzVLgM/a2vratWvK3rLalSdonCSG\nEGJkZMSu2Zafn69sDi/Nzc3t7du37D41WXtKRRkaFSwsLK5fv676HZWUlISGhrq5uYnF4saN\nG6tdxpevuLh45cqVgYGB/fr127x5s0wmK20P+fn5U6ZM4cfv5+fHb4zETjchsdNvSOxAx926\ndevAgQPXrl37rBXwNaGPiR1/BMXOzi49Pd3Pz68MuUWZNW3alKKoQYMGadhek0Iqrq6uyhZf\nUr3yRFFR0eHDh1evXk2vk8vWqFEjdktNsrTBgwezD5HL5arrQn8KY2PjHTt2lMM/i89v1KhR\n7MhFIlF8fDy/GRI73aTLiZ2q/9ICtq+//trIyKhFixaRkZHsP6nbtm1bvXq1wpW/aSYmJsuX\nL2evMpSbmzto0CB6VW/Ve5VRHQaC/HKClMlkOTk5aWlp9Pavv/46Ojr6xIkT2gqSvUVfruSi\nRYsePnzIbpaVlbV69erFixefOXOmpKSE2W5lZaV5VYvSunXrVp06dejV5TXh6emZlJSkuk1K\nSkqzZs3s7OxKdSUTExM7dOjw8eNHhX3evn3byMioatWqnTp1cnd3V/gMHMfZs2c5v265XO7g\n4PDu3TuZTGZmZkZnn2r70URJSUlwcPCiRYvMzMx0/NNNUVSNGjXy8/Plcnnjxo3nz5/ftm1b\nfpCco3Tng6M7V1IrQep0nRdtZ5Z6gPNMDD3bn8EpZ6UQM8mfxnl4VvVeZVSHgSC/qCAJmUvI\nLULWEmLWu3dvLQZJl0BbsmSJ3l7J/0cvgdCgQQNN+qxgAoHA3t6+fv36yoqS8JXqSiqcsqoi\nGLVtatSooWz128/NAD7ddevWJYSsWrVKl4PUiytZ7kESjNjpu8DAQJFI1KpVq+rVq7O3L1u2\nbMOGDTKZTNmBpqamkydPZm/p0qXLpEmTXrx4oXavMqrDQJBfSJDFxcXHjh0rKfEkZA4hhJBG\nhKTFxIQeOXJk69atWgny6NGjSUlJ3bp1Izp/JUtKSlJSUubOnbtkyZKLFy9yWjo5ORFC/vzz\nT4VB3rhxg1/VtgKIRKIqVaq8efMmMzOTrnBbvXr1Hj163Lt379KlS5SiQS8PDw9vb2/+tQoM\nDIyJienVqxfnSr5586ZUb03hSTnkcjlnTLRp06YmJiYfPnwwMzOjF5A9c+aMJl1pyN3dvVmz\nZnr96WaCHDBgQHJyMlP/WTeD1IsrWb5BisW668aBAAAcg0lEQVTinTt3qohHm7ScWOoDPGMH\nuiYtLa1Hjx7/Vt9YRAj17//WE0K+wHUbSys0NJSZ7/nNN99wpimIRKLz58+rOPzHH3+s4D/U\ntKCgIP7GxYsXFxcXKyub5+npqfAtKJs88eDBg8/8Jgj533E+Ozu7fv36KWtJP2FWWps2bSqf\nfygASujyM3ZYUgxAz0gkksDAwGPHjv37dEgUIYWEEEJKCNlZrVo1R0dHbcan87Zs2TJ16tT8\n/Hz65YkTJwoKCpi9JiYm69at8/X1VdGDskW3GF26dPn0OPnu3bvH37h+/Xp3d/e3b98qPCQ5\nOdnb23vs2LGc55O6du2amJjIaSyVShMTEzWv3lJmFGtwLisr68CBA8pafv/99w0bNixV502b\nNv3+++/LHhyAnkNiB6Bnrl69eu3aNdaGZELqEjKQkPqExIWGhmotMj2hcE0nRnFxsbIyY4yh\nQ4d6eXmpaGBiYqK6CEjZMLXu2J4/f67iFpVUKk1ISIiIiGjWrFlGRgaz3cjIyNXVld0yPz/f\n29s7ODi4qKio/ELWiIrbYX369Nm/f7/aTJpWpUqVyZMnnz17tlQ18AAMDBI7AD2j6BGoNDOz\nQ35+7idOnAgODtZCTHrl2bNnqhuonW1qYmJy/vz5JUuWdOvWzc3Njd/g2LFjUqm07CEqoWF+\no1BmZuaiRYuYl1KplDP+N3fu3OvXr5c9uM/j/fv3Hh4ely9ffvz48aVLl9auXduxY8d69eoN\nGDCAUxjZ0dHxzp07y5cvt7W11Va0ALoAkycA9Ay/tBghZMCAAZs2bar4YDhiY2MPHTr066+/\n1qhRQ9uxKFWvXr03b96oaKA2M8jLy1u4cOGJEyeKi4tbt2797t27d+/elWuMXEZGRgsXLnR1\ndQ0PDy9zJ6dOnWJ+jo2NDQ4Ozs7OZracO3fuk0L8bDIyMqpXr+7u7u7u7t66desRI0Ywu7p2\n7bp9+/bMzMymTZuOGzfOIFO6Y8eOnTx5ctasWXSRSAD1tP2Qnx7A5AnQKSUlJT4+PuxPsVgs\nTkpK0nZcFEVRtWrVIjpfTDUmJkbFn0R7e3v2ygp8f//9N73mGIO/hmy5EwgEvr6+zNTIsjEy\nMpJIJPS74EyeiIuL06QiXQVj5lj069dP4fpgXwI6n5s1a5a2A4H/gckTAFBuRCLR/v37Bw4c\naGpqKhAIGjVqdPToUU1qMlUAehYCey6CDvL394+Ojq5fv76RkZGdnR27xJq9vf3u3btVrGc1\nZMiQzp07MxWhaSpqnJYXiqLi4+NjY2M/pRO5XL5582b6Z2byhFQqDQgIaNeu3evXr8sh0HJC\n58rUv3Ms9u3b179//8jIyOjo6M9XI1o36cVnCnSK/t2KpSjq+fPnz549oz/elSpVql27trOz\ns7bjAqg41apV27lzp0wmKy4u/sQVRb9Mffv27du3b0lJCb3M661bt5KSkmxsbDp16lSpUiVl\nR+3du5dJjPTUhAkTTp8+PXjwYH9/f3ryxOjRozWs/lqRjIyMOOlybGwsndc6OjoeOHDA29tb\nS6EB6Dp9SuzevXv3+++/009UcHbVrFlz2LBhU6ZMUThrDMAgCYVCXcvqXFxc3rx54+Liou1A\nNEJndYSQxo0ba7I0wpkzZz5zRJ9dYWFhdHR0dHR0jRo1/Pz8duzYQd9R0jUq5smmp6cHBQU9\nevSI+fUZNhcXlzt37nDu/gOooDeJXUZGho+Pz/Pnz2vXru3v7+/i4mJhYUEIef/+/dOnT+Pi\n4mbPnr1///5z584Z5POzAHqBvfKE4ZFIJNoOody8evVKF2bbKPTtt9/evn2bs1gFW0pKyr17\n95o0aVKRUWlLbGwse+UJALX0JrGbNWvWy5cv9+7dq7BGuUwmW7du3dixY+fNmxcWFlbx4QEA\nIcTe3t7f31/bUXwubdu23bJlC2ejpaXlt99+u337dhWDTB06dMjJyUlOTv688ek5c3Pz7t27\nT58+vXnz5nv27BkwYICKxnl5eRUWmHZVr16dsxYWgGp6M3kiJiYmODhY2cozQqFw9OjR/fv3\nV1HBHADgU/z000+cJSX69Onz8uXLzZs3T506ld/exMTE1dV1+vTpR48evXz58ucoWWxIfv75\n57179zZv3pwQEhQUFB0d7eXlZWVlZWNjw2lpYmLyhQzXAZSB3vyhyc7O/uqrr1S3qVev3sGD\nB0vV7fPnz729vVWXEqWfQWEvbggAXyChUHjy5MkdO3acP39eLBb37Nnzm2++oXctXrz40KFD\n7IVWGzdufOPGDXYllLCwsLFjx1Z00HqiWbNmCxYsYG+hJ7gQQlJTU5s3b56Tk8PsWrp0qYo5\nLgBfOAHFWrNPl7m6unp7e0dFRalo07t37+Tk5OfPn2verVwuP3/+vOrE7u7duxMmTCguLhaL\nxZr3DABfFIqiQkNDDx06JBAIvv3225CQEH59u/379w8dOpS5jVirVq1evXr9/fffd+7cqfB4\nK4JA8P9fMVZWVi1btuTMPunYsWP37t2zsrIaN27cr18/FSOaGRkZy5cvT05Otre3Hzx48Gda\nihdAcxKJxMTE5OLFi23atNF2LFx6k9hNmDDhzz//XLZs2bhx4/jrAH78+HHZsmXz58+fNm3a\nkiVLyvfUly5d8vHxQWIHoJZerDyhXRRFXbt2LS0tzcPDg1nePjc39+7du3l5ec+ePbt3756V\nldWTJ0/YD5aYmJjo5vRVPrFYXFJSIhQKO3fuvHr1aisrq4KCAhcXl5KSkqFDh+7YsYNu1rFj\nx127dmE1BbWw8oRuQmJXDnJzczt16nT9+nX6v/ycnZ0tLS0pisrPz09NTU1ISCgoKPD19T1+\n/LilpWX5nhqJHYCG3Nzcnj9/Pnny5OXLl2s7Fr138ODB2NhYuVzeuXNneqLowYMHk5OT379/\n7+DgUKNGDRcXFx8fn6Kion379h0/fvzDhw9SqTQ/P7+wsFDFTI5PIRAIrK2tfXx83N3d8/Pz\nX716ZWlp2axZs/bt22dkZHh5edG18fLz842Njfn/BU4ISUlJefjwobOzc/369T9HhIbHwcHh\nzZs3s2bNmj9/vrZjgf/ocmKnN8/Y2djYXL58OSIiYtu2bf/88w/7z5axsbGnp+eQIUOGDBki\nFAq1GCTAFw5V8stRYGBgYGAg81JFsT1vb2/VmXRJSYlAIHjy5Mnbt29zc3PXr19/+fJlqVRa\nqVIlDw+PVq1aTZky5fXr1y9evPDw8GDqvUul0rJN+FDxX9eurq508gcawmcKSktvEjtCiFgs\nnjhx4sSJE4uKil68eEGvPGFtbV2zZk2MpQEAKEPX8q1bty79skePHvw21tbWHh4e7C2Yxgug\nj/Tyc2tqalq7dm1tRwEAoK+kUumjR49wPxTA8OhNHTsAACgvsbGxvr6+2o4CAMofEjsAgC+O\nkZERvxoLABgAfLABAL44Xbt2TUxM1HYUAFD+kNgBAHxxjIyMMDsVwCAhsQMA+OJIpdJ79+5p\nOwoAKH9I7AAAvjiYPAFgqJDYAUC5oSufof6Z7sPkCX2BzxSUFj7YAFBupk6d2qJFix9//FHb\ngYAamDyhL6ZNm+bt7f39999rOxDQG3qzVqwWYa1YAAAAYOjyWrEYsQMA+OJg8gSAoUJiBwDw\nxcHkCQBDhcQOAOCLg8kTAIYKH2wAKDcymezNmzfajgLUw+QJfSGVSjMzM7UdBegTJHYAUG76\n9+9fvXr1HTt2aDsQUAMrT+iLnj17Vq9eff/+/doOBPQGEjsAKDcXL16kKOrSpUvaDgTUwOQJ\nfXHx4kW5XH758mVtBwJ6A4kdAMAXB5MnAAwV6tipl5SU1KJFC21HAQAAADokMTHRy8tL21Fw\nIbHTSHJyslQq1XYUX66EhISxY8du3bpV24GAGrdu3Vq1atWmTZu0HQiocePGjTVr1qxfv17b\ngYAaiYmJW7ZsOXv2rLYDAS6RSNSkSRNtR6EAEjvQA2fOnOnWrRtya9134sSJvn37FhQUaDsQ\nUOPIkSPBwcF5eXnaDgTU2L9//4gRI96+favtQEBv4Bk7AAAAAAOBxA4AAADAQCCxAwAAADAQ\nSOwAAAAADAQSOwAAAAADgcQOAAAAwEAgsQMAAAAwEEjsAAAAAAwEEjsAAAAAA4HEDvSAWCwW\ni8XajgLUw29KX+A3pS/wm4LSwpJioAcoikpJSalVq5a2AwE15HJ5Wlqaq6urtgMBNfCb0hcy\nmezly5cuLi7aDgT0BhI7AAAAAAOBW7EAAAAABgKJHQAAAICBQGIHAAAAYCCQ2AEAAAAYCCR2\nAAAAAAYCiR0AAACAgUBiBwAAAGAgkNgBAAAAGAgkdgAAAAAGAokdAAAAgIFAYgcAAABgIJDY\nAQAAABgIJHYAAAAABgKJHQAAAICBQGIHAAAAYCCQ2IH+mTRpkkAgGDZsmLYDAQXevXs3ZcoU\nFxcXExOTWrVq9e7d+8qVK9oOCv6Tm5s7YcIEV1dXsVjs6Og4bNiwjIwMbQcFCuCjBGUjoChK\n2zEAlEJSUlKrVq1kMtnQoUM3btyo7XDgf+Tk5Hh6eqakpHTv3r158+bPnj2LiooSiUQJCQmN\nGjXSdnRAJBJJ69atr1+/3rdv3+bNmz99+nT79u1OTk7Xrl2ztbXVdnTwH3yUoOwoAP1RUlLS\ntGnTJk2aEEKGDh2q7XCAa8yYMYSQ8PBwZsv+/fsJIf7+/lqMChh//PEHIWTp0qXMlqioKELI\n5MmTtRgV8OGjBGWGW7GgT1asWJGcnLxkyRJtBwKKGRsbd+rUacSIEcyWwMBAMzOzu3fvajEq\nYGzbts3KyiokJITZ0r9/f3d39+3bt1O4e6NL8FGCMhNpOwAATT19+nTevHkjR45s1aqVtmMB\nxVauXMnZIpFIpFKpk5OTVuIBtqKiotu3b7dv397ExIS9vW3btlu2bHn+/Lmbm5u2YgMOfJSg\nzDBiB3pjxIgRNjY2ixcv1nYgUArr1q0rKSkJCgrSdiBAXrx4IZPJnJ2dOdtdXFwIIc+ePdNG\nUKApfJRAQxixA/2wZcuWM2fOREdHV6pUKTc3V9vhgEbi4uKmTp3atm3bkSNHajsWIB8+fCCE\nWFhYcLZbWloye0E34aMEmkNiBzokNzd3+vTpzEt3d/cpU6YQQjIzMydPntyjR4++fftqLzr4\nj7LfFNvu3bsHDx7csGHDw4cPi0T4U6MrBAIBZwv9dB1/O+gIfJSgVPBPBHRIfn7+unXrmJc+\nPj50uhASEiKRSCIiIrQXGvwPZb8pGkVRc+fOnT9/vp+f3969e62srLQRI3BZW1sTRSNz79+/\nJ4Tg16SD8FGCMkBiBzrEycmJPzXvxIkTe/bsmTVrlpGR0cuXL8m/30MFBQUvX760tramv66g\nIin8TdEoiho2bNhff/01bty4lStXCoXCCo4NlKlZs6ZIJEpNTeVsf/r0KSGkdu3a2ggKlMJH\nCcoGBYpB102ZMmXFihXK9k6bNg3VT3TKhAkTVq1atWjRohkzZmg7FuBq1arV7du3s7KyzM3N\n6S1yudzZ2VkoFKalpWk3NuDARwnKBiN2oOuGDh3avn179paPHz8GBQV17dp13Lhx7u7uWooL\nFDhw4MCqVatCQkLwVaSbhg4dOnz48NDQ0Dlz5tBb1q9fn56ePm/ePO0GBhz4KEGZYcQO9E9u\nbq6trS2WFNNB7u7uT58+HTduHDMgxJg2bRoWrdI6mUzWoUOH+Pj4Xr16NW/e/P79+1FRUQ0b\nNrxy5Qr/VwZahI8SlBkSO9A/SOx0loqZlc+fP3d1da3AWECx/Pz8efPm7du3Lz093d7evnfv\n3vPnz69cubK244L/gY8SlBkSOwAAAAADgZUnAAAAAAwEEjsAAAAAA4HEDgAAAMBAILEDAAAA\nMBBI7AAAAAAMBBI7AAAAAAOBxA4AAADAQCCxAwAAADAQSOwAAAAADAQSOwAAAAADgcQOAAAA\nwEAgsQMAAAAwEEjsAAAAAAwEEjsAAAAAA4HEDgAAAMBAILEDAAAAMBBI7AAAAAAMBBI7AAAA\nAAOBxA4AAADAQCCxAwAAADAQSOwAAAAADAQSOwAAAAADgcQOAAAAwEAgsQMAAAAwEEjsAAAA\nAAwEEjsAAAAAA4HEDgAAAMBAILEDAAAAMBBI7ADgi7Nr1y4nJyeRSDR16lRN2gcFBQkEgpcv\nXyprIBKJWrVqVV7hDRs2TCAQPHnypLw6BIAvBxI7AChnO3bsEAgEc+fO1XYgiuXl5Q0bNiw/\nP3/BggXdunXTdjgAAOVJpO0AAAAq1OPHjwsLCwcPHjxjxgxtxwIAUM4wYgcAX5aioiJCiJWV\nlbYDAQAof0jsAEALUlNTBw8eXKNGDbFYXLVq1YCAgISEBHaDmJiYli1bmpubOzg4hISEFBYW\nOjs7N2/e/BPP6+fn5+vrSwhZunSpQCAYOXKkhvGwHT9+3NPT08zMzN7eftiwYbm5uWWI5PXr\n18OGDatRo4aFhUWTJk1WrVollUrZDYyMjJYuXerm5mZiYlKzZs0FCxZQFMXsTUhICAwMrFq1\nqlgsdnV1DQ4OTklJYfYOHDhQIBDk5+dPmzbN1dXVxMTE2dl55cqV7B7UXuE3b96MGTPGxcVF\nLBbb2dn17t07MTGxDO8UACoSbsUCQEV78eJFy5YtCwoKRo0a1aBBg1evXkVGRn799dd///13\n27ZtCSHnz5/v1auXnZ3d9OnTq1atum/fvqCgoA8fPtSoUeMTTz1nzpx27drNnDmzT58+wcHB\ntWrV0iQetgsXLgQEBFSrVm327Nl2dnZxcXEBAQFGRqX7j+SsrCwvL6/8/PxBgwa5uLj8888/\nEyZMuH379saNG5k2CxcuvHnz5vDhw4VCYXh4+OzZs93d3QcMGEAIuXbtWrt27SpXrhwSEuLg\n4PDs2bOIiIjY2Nh79+5VqVKFECIWiwkh3377ba1atfbs2SOXy+fNmzdp0iQbG5vBgwcTDa5w\nVlaWt7d3bm7uyJEjGzZs+OLFi8jISF9f31OnTrVr167svwAA+NwoAIBytX37dkLInDlzlDX4\n8ccfCSEHDhxgtty7d08oFLZq1Yp+2aVLF0JIYmIi/VIqlXbo0IEQ4u3t/enhxcfHE0KmTZum\neTzfffcdIeTFixcURfn5+RFCEhISmMajR48ubWyjRo0ihJw6dYrZ0r17d0LInTt3KIoaOnQo\nIaRt27YSiYTee+3aNUJIQEAA/TIyMrJ58+bnzp1jDg8PDyeEhIeH0y/pHgYMGMA0ePr0KSGk\nR48e9Eu1V3jUqFEikYhpQFFUWlqalZWVl5eX5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          },
          "metadata": {
            "image/png": {
              "width": 420,
              "height": 420
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# RNA Differential Expression"
      ],
      "metadata": {
        "id": "djekwbjTf8ns"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fNJ4c6naDAHs",
        "outputId": "745fa73f-ac6c-4c87-ee7c-6a398451f986"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "--------------------------------------\n",
            "\n",
            "o GDCquery: Searching in GDC database\n",
            "\n",
            "--------------------------------------\n",
            "\n",
            "Genome of reference: hg19\n",
            "\n",
            "--------------------------------------------\n",
            "\n",
            "oo Accessing GDC. This might take a while...\n",
            "\n",
            "--------------------------------------------\n",
            "\n",
            "ooo Project: TCGA-PRAD\n",
            "\n",
            "--------------------\n",
            "\n",
            "oo Filtering results\n",
            "\n",
            "--------------------\n",
            "\n",
            "ooo By platform\n",
            "\n",
            "ooo By experimental.strategy\n",
            "\n",
            "ooo By data.type\n",
            "\n",
            "ooo By file.type\n",
            "\n",
            "----------------\n",
            "\n",
            "oo Checking data\n",
            "\n",
            "----------------\n",
            "\n",
            "ooo Check if there are duplicated cases\n",
            "\n",
            "ooo Check if there results for the query\n",
            "\n",
            "-------------------\n",
            "\n",
            "o Preparing output\n",
            "\n",
            "-------------------\n",
            "\n"
          ]
        }
      ],
      "source": [
        "query <- GDCquery(project = \"TCGA-PRAD\", \n",
        "                  data.category = \"Gene expression\",\n",
        "                  data.type = \"Gene expression quantification\",\n",
        "                  experimental.strategy = \"RNA-Seq\",\n",
        "                  platform = \"Illumina HiSeq\",\n",
        "                  file.type = \"results\",\n",
        "                  legacy = TRUE)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mxrqTei1DHiU",
        "outputId": "6ca98357-6656-4081-b6fc-f4a894bff83f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading data for project TCGA-PRAD\n",
            "\n",
            "GDCdownload will download 550 files. A total of 834.121914 MB\n",
            "\n",
            "Downloading chunk 1 of 6 (100 files, size = 151.869266 MB) as Fri_Apr_29_04_28_55_2022_0.tar.gz\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading: 61 MB     "
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading chunk 2 of 6 (100 files, size = 151.619367 MB) as Fri_Apr_29_04_28_55_2022_1.tar.gz\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading: 61 MB     "
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading chunk 3 of 6 (100 files, size = 151.62918 MB) as Fri_Apr_29_04_28_55_2022_2.tar.gz\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading: 61 MB     "
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading chunk 4 of 6 (100 files, size = 151.582944 MB) as Fri_Apr_29_04_28_55_2022_3.tar.gz\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading: 61 MB     "
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading chunk 5 of 6 (100 files, size = 151.708686 MB) as Fri_Apr_29_04_28_55_2022_4.tar.gz\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading: 61 MB     "
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading chunk 6 of 6 (50 files, size = 75.712471 MB) as Fri_Apr_29_04_28_55_2022_5.tar.gz\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading: 30 MB     "
          ]
        }
      ],
      "source": [
        "GDCdownload(query, method = \"api\", files.per.chunk = 100,\n",
        "            directory = \"/content/Data\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4YWrdvp5EWRz",
        "outputId": "b4f5b2a4-0ad7-4487-b90b-37ab536e7840"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "--------------------\n",
            "\n",
            "oo Reading 550 files\n",
            "\n",
            "--------------------\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "|====================================================|100%                      Completed after 13 s \n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "--------------------\n",
            "\n",
            "oo Merging 550 files\n",
            "\n",
            "--------------------\n",
            "\n",
            "Starting to add information to samples\n",
            "\n",
            " => Add clinical information to samples\n",
            "\n",
            " => Adding TCGA molecular information from marker papers\n",
            "\n",
            " => Information will have prefix 'paper_' \n",
            "\n",
            "prad subtype information from:doi:10.1016/j.cell.2015.10.025\n",
            "\n"
          ]
        }
      ],
      "source": [
        "mrna_df <- GDCprepare(query, directory = \"/content/Data\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "mPF0I6dYEptR"
      },
      "outputs": [],
      "source": [
        "mrna_meta <- mrna_df$sample"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yBANGIsaEvg4"
      },
      "outputs": [],
      "source": [
        "mrna_meta <- cbind(mrna_meta, mrna_df$definition)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "H-T46TqDFE54"
      },
      "outputs": [],
      "source": [
        "mrna_df <- assay(mrna_df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ghz5fsA4FI0R"
      },
      "outputs": [],
      "source": [
        "delim_fn = function(x, n, i){\n",
        "    do.call(c, lapply(x, function(X)\n",
        "        paste(unlist(strsplit(X, \"-\"))[(n+1):(i)], collapse = \"-\")))\n",
        "}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_qnEL35MFLRN"
      },
      "outputs": [],
      "source": [
        "colnames(mrna_df) <- delim_fn(x = colnames(mrna_df), n = 0, i = 4)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "DHbQsgyLFNLo"
      },
      "outputs": [],
      "source": [
        "mrna_meta <- as.data.frame(mrna_meta)\n",
        "mrna_df <- as.data.frame(mrna_df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "hVuMJvKyFQ3R"
      },
      "outputs": [],
      "source": [
        "metastatic_key <- mrna_meta[which(mrna_meta[,2] == \"Metastatic\"),]\n",
        "mrna_meta <- mrna_meta[!mrna_meta[,2] == metastatic_key[,2],]\n",
        "mrna_df <- mrna_df[, -grep(paste0(metastatic_key[,1]), colnames(mrna_df))]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "hteTUGmgFXLp"
      },
      "outputs": [],
      "source": [
        "mrna_meta[,2] <- as.character(mrna_meta[,2])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "id": "nuck1srJFZmU",
        "outputId": "9aaa8b19-c9dd-4c17-bf3a-25a9a07b3965"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<style>\n",
              ".list-inline {list-style: none; margin:0; padding: 0}\n",
              ".list-inline>li {display: inline-block}\n",
              ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
              "</style>\n",
              "<ol class=list-inline><li>'Normal'</li><li>'Tumor'</li></ol>\n"
            ],
            "text/markdown": "1. 'Normal'\n2. 'Tumor'\n\n\n",
            "text/latex": "\\begin{enumerate*}\n\\item 'Normal'\n\\item 'Tumor'\n\\end{enumerate*}\n",
            "text/plain": [
              "[1] \"Normal\" \"Tumor\" "
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "mrna_meta[,2] <- gsub(\"Primary solid Tumor\", \"Tumor\", mrna_meta[,2])\n",
        "mrna_meta[,2] <- gsub(\"Solid Tissue Normal\", \"Normal\", mrna_meta[,2])\n",
        "mrna_meta[,2] <- as.factor(mrna_meta[,2])\n",
        "levels(mrna_meta[,2])\n",
        "colnames(mrna_meta) <- c(\"cases\", \"Condition\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "U4x7Mqmdd5nV"
      },
      "outputs": [],
      "source": [
        "write.table(mrna_df, \"/content/Results/mrna_df.txt\", quote = F, sep = \"\\t\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "M9Z7VHydeOaT"
      },
      "outputs": [],
      "source": [
        "write.table(mrna_meta, \"/content/Results/mrna_meta.txt\", quote = F, sep = \"\\t\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HzR7aUHiGYrG",
        "outputId": "b6d432de-7d40-4923-8843-b42d6f5f5ab2"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "converting counts to integer mode\n",
            "\n"
          ]
        }
      ],
      "source": [
        "mrna_dds <- DESeqDataSetFromMatrix(round(mrna_df), colData = mrna_meta, design = ~ Condition)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "RLaCduaeGjPQ"
      },
      "outputs": [],
      "source": [
        "mrna_dds$Condition <- relevel(mrna_dds$Condition, ref = \"Normal\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZjDTyGb0GoZQ",
        "outputId": "4cecaa4e-1ce2-4c82-98b1-6cd0c335494e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "estimating size factors\n",
            "\n",
            "estimating dispersions\n",
            "\n",
            "gene-wise dispersion estimates\n",
            "\n",
            "mean-dispersion relationship\n",
            "\n",
            "final dispersion estimates\n",
            "\n",
            "fitting model and testing\n",
            "\n",
            "-- replacing outliers and refitting for 1439 genes\n",
            "-- DESeq argument 'minReplicatesForReplace' = 7 \n",
            "-- original counts are preserved in counts(dds)\n",
            "\n",
            "estimating dispersions\n",
            "\n",
            "fitting model and testing\n",
            "\n"
          ]
        }
      ],
      "source": [
        "mrna_dds <- DESeq(mrna_dds)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9gDgPD-8uNGI"
      },
      "outputs": [],
      "source": [
        "vsd <- varianceStabilizingTransformation(mrna_dds, blind=FALSE)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 747
        },
        "id": "Cp4QuOVf4GS9",
        "outputId": "fb7542b7-2c6d-424c-e417-36db44507e82"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<table class=\"dataframe\">\n",
              "<caption>A matrix: 6 × 549 of type dbl</caption>\n",
              "<thead>\n",
              "\t<tr><th></th><th scope=col>TCGA-G9-7525-01A</th><th scope=col>TCGA-EJ-7789-01A</th><th scope=col>TCGA-EJ-7314-11A</th><th scope=col>TCGA-HC-8265-01A</th><th scope=col>TCGA-EJ-A46B-01A</th><th scope=col>TCGA-HC-7819-01A</th><th scope=col>TCGA-EJ-5510-01A</th><th scope=col>TCGA-HC-7080-01A</th><th scope=col>TCGA-CH-5769-11A</th><th scope=col>TCGA-KK-A7AY-01A</th><th scope=col>⋯</th><th scope=col>TCGA-G9-6377-01A</th><th scope=col>TCGA-V1-A8MF-01A</th><th scope=col>TCGA-G9-6499-11A</th><th scope=col>TCGA-J4-A67R-01A</th><th scope=col>TCGA-KK-A6E7-01A</th><th scope=col>TCGA-J9-A8CN-01A</th><th scope=col>TCGA-CH-5762-01A</th><th scope=col>TCGA-XJ-A9DX-01A</th><th scope=col>TCGA-KK-A6E5-01A</th><th scope=col>TCGA-EJ-5496-01A</th></tr>\n",
              "</thead>\n",
              "<tbody>\n",
              "\t<tr><th scope=row>A1BG|1</th><td> 6.008894</td><td> 7.355672</td><td> 7.672604</td><td> 7.907780</td><td> 7.380921</td><td> 6.189704</td><td> 6.560988</td><td> 5.889730</td><td> 6.145200</td><td> 6.520872</td><td>⋯</td><td> 6.584258</td><td> 6.959848</td><td> 6.889952</td><td> 7.406567</td><td> 6.830122</td><td> 6.074995</td><td> 5.411722</td><td> 8.238785</td><td> 7.448119</td><td> 5.840184</td></tr>\n",
              "\t<tr><th scope=row>A2M|2</th><td>14.977996</td><td>14.768960</td><td>16.052200</td><td>14.783020</td><td>13.568532</td><td>13.518895</td><td>14.263595</td><td>14.022247</td><td>14.657321</td><td>14.457274</td><td>⋯</td><td>13.784273</td><td>14.996586</td><td>15.086310</td><td>14.495920</td><td>14.170037</td><td>14.425412</td><td>15.190929</td><td>13.686582</td><td>14.506364</td><td>13.316533</td></tr>\n",
              "\t<tr><th scope=row>NAT1|9</th><td> 7.369287</td><td> 5.967220</td><td> 8.657079</td><td> 8.214435</td><td> 9.172845</td><td> 5.967724</td><td> 8.689489</td><td> 6.183797</td><td> 8.645634</td><td> 5.524921</td><td>⋯</td><td> 8.042378</td><td> 8.220037</td><td> 9.312656</td><td> 7.235903</td><td> 9.267809</td><td> 9.088459</td><td> 7.819305</td><td> 5.980150</td><td> 9.675646</td><td> 7.288150</td></tr>\n",
              "\t<tr><th scope=row>NAT2|10</th><td> 5.153428</td><td> 4.052769</td><td> 5.213812</td><td> 4.687886</td><td> 5.166692</td><td> 4.522975</td><td> 5.095599</td><td> 5.115032</td><td> 5.176564</td><td> 4.514181</td><td>⋯</td><td> 4.859166</td><td> 5.722875</td><td> 5.025388</td><td> 5.173697</td><td> 6.807294</td><td> 4.465588</td><td> 4.052769</td><td> 4.052769</td><td> 4.774214</td><td> 4.706704</td></tr>\n",
              "\t<tr><th scope=row>SERPINA3|12</th><td>16.425500</td><td> 8.755545</td><td>14.887241</td><td>16.042970</td><td>10.837725</td><td>14.793632</td><td>15.035991</td><td>12.389362</td><td>15.395851</td><td>12.833889</td><td>⋯</td><td>15.029958</td><td>10.727668</td><td>14.168768</td><td>16.990727</td><td>10.022932</td><td>14.148247</td><td>13.947195</td><td>10.260316</td><td>12.506878</td><td>14.000804</td></tr>\n",
              "\t<tr><th scope=row>AADAC|13</th><td> 4.408430</td><td> 4.052769</td><td> 4.558712</td><td> 4.052769</td><td> 4.052769</td><td> 4.052769</td><td> 4.359825</td><td> 4.052769</td><td> 4.521184</td><td> 4.052769</td><td>⋯</td><td> 4.052769</td><td> 4.052769</td><td> 4.052769</td><td> 4.591437</td><td> 4.518895</td><td> 4.052769</td><td> 4.052769</td><td> 4.052769</td><td> 4.416300</td><td> 4.052769</td></tr>\n",
              "</tbody>\n",
              "</table>\n"
            ],
            "text/latex": "A matrix: 6 × 549 of type dbl\n\\begin{tabular}{r|lllllllllllllllllllll}\n  & TCGA-G9-7525-01A & TCGA-EJ-7789-01A & TCGA-EJ-7314-11A & TCGA-HC-8265-01A & TCGA-EJ-A46B-01A & TCGA-HC-7819-01A & TCGA-EJ-5510-01A & TCGA-HC-7080-01A & TCGA-CH-5769-11A & TCGA-KK-A7AY-01A & ⋯ & TCGA-G9-6377-01A & TCGA-V1-A8MF-01A & TCGA-G9-6499-11A & TCGA-J4-A67R-01A & TCGA-KK-A6E7-01A & TCGA-J9-A8CN-01A & TCGA-CH-5762-01A & TCGA-XJ-A9DX-01A & TCGA-KK-A6E5-01A & TCGA-EJ-5496-01A\\\\\n\\hline\n\tA1BG\\textbar{}1 &  6.008894 &  7.355672 &  7.672604 &  7.907780 &  7.380921 &  6.189704 &  6.560988 &  5.889730 &  6.145200 &  6.520872 & ⋯ &  6.584258 &  6.959848 &  6.889952 &  7.406567 &  6.830122 &  6.074995 &  5.411722 &  8.238785 &  7.448119 &  5.840184\\\\\n\tA2M\\textbar{}2 & 14.977996 & 14.768960 & 16.052200 & 14.783020 & 13.568532 & 13.518895 & 14.263595 & 14.022247 & 14.657321 & 14.457274 & ⋯ & 13.784273 & 14.996586 & 15.086310 & 14.495920 & 14.170037 & 14.425412 & 15.190929 & 13.686582 & 14.506364 & 13.316533\\\\\n\tNAT1\\textbar{}9 &  7.369287 &  5.967220 &  8.657079 &  8.214435 &  9.172845 &  5.967724 &  8.689489 &  6.183797 &  8.645634 &  5.524921 & ⋯ &  8.042378 &  8.220037 &  9.312656 &  7.235903 &  9.267809 &  9.088459 &  7.819305 &  5.980150 &  9.675646 &  7.288150\\\\\n\tNAT2\\textbar{}10 &  5.153428 &  4.052769 &  5.213812 &  4.687886 &  5.166692 &  4.522975 &  5.095599 &  5.115032 &  5.176564 &  4.514181 & ⋯ &  4.859166 &  5.722875 &  5.025388 &  5.173697 &  6.807294 &  4.465588 &  4.052769 &  4.052769 &  4.774214 &  4.706704\\\\\n\tSERPINA3\\textbar{}12 & 16.425500 &  8.755545 & 14.887241 & 16.042970 & 10.837725 & 14.793632 & 15.035991 & 12.389362 & 15.395851 & 12.833889 & ⋯ & 15.029958 & 10.727668 & 14.168768 & 16.990727 & 10.022932 & 14.148247 & 13.947195 & 10.260316 & 12.506878 & 14.000804\\\\\n\tAADAC\\textbar{}13 &  4.408430 &  4.052769 &  4.558712 &  4.052769 &  4.052769 &  4.052769 &  4.359825 &  4.052769 &  4.521184 &  4.052769 & ⋯ &  4.052769 &  4.052769 &  4.052769 &  4.591437 &  4.518895 &  4.052769 &  4.052769 &  4.052769 &  4.416300 &  4.052769\\\\\n\\end{tabular}\n",
            "text/markdown": "\nA matrix: 6 × 549 of type dbl\n\n| <!--/--> | TCGA-G9-7525-01A | TCGA-EJ-7789-01A | TCGA-EJ-7314-11A | TCGA-HC-8265-01A | TCGA-EJ-A46B-01A | TCGA-HC-7819-01A | TCGA-EJ-5510-01A | TCGA-HC-7080-01A | TCGA-CH-5769-11A | TCGA-KK-A7AY-01A | ⋯ | TCGA-G9-6377-01A | TCGA-V1-A8MF-01A | TCGA-G9-6499-11A | TCGA-J4-A67R-01A | TCGA-KK-A6E7-01A | TCGA-J9-A8CN-01A | TCGA-CH-5762-01A | TCGA-XJ-A9DX-01A | TCGA-KK-A6E5-01A | TCGA-EJ-5496-01A |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| A1BG|1 |  6.008894 |  7.355672 |  7.672604 |  7.907780 |  7.380921 |  6.189704 |  6.560988 |  5.889730 |  6.145200 |  6.520872 | ⋯ |  6.584258 |  6.959848 |  6.889952 |  7.406567 |  6.830122 |  6.074995 |  5.411722 |  8.238785 |  7.448119 |  5.840184 |\n| A2M|2 | 14.977996 | 14.768960 | 16.052200 | 14.783020 | 13.568532 | 13.518895 | 14.263595 | 14.022247 | 14.657321 | 14.457274 | ⋯ | 13.784273 | 14.996586 | 15.086310 | 14.495920 | 14.170037 | 14.425412 | 15.190929 | 13.686582 | 14.506364 | 13.316533 |\n| NAT1|9 |  7.369287 |  5.967220 |  8.657079 |  8.214435 |  9.172845 |  5.967724 |  8.689489 |  6.183797 |  8.645634 |  5.524921 | ⋯ |  8.042378 |  8.220037 |  9.312656 |  7.235903 |  9.267809 |  9.088459 |  7.819305 |  5.980150 |  9.675646 |  7.288150 |\n| NAT2|10 |  5.153428 |  4.052769 |  5.213812 |  4.687886 |  5.166692 |  4.522975 |  5.095599 |  5.115032 |  5.176564 |  4.514181 | ⋯ |  4.859166 |  5.722875 |  5.025388 |  5.173697 |  6.807294 |  4.465588 |  4.052769 |  4.052769 |  4.774214 |  4.706704 |\n| SERPINA3|12 | 16.425500 |  8.755545 | 14.887241 | 16.042970 | 10.837725 | 14.793632 | 15.035991 | 12.389362 | 15.395851 | 12.833889 | ⋯ | 15.029958 | 10.727668 | 14.168768 | 16.990727 | 10.022932 | 14.148247 | 13.947195 | 10.260316 | 12.506878 | 14.000804 |\n| AADAC|13 |  4.408430 |  4.052769 |  4.558712 |  4.052769 |  4.052769 |  4.052769 |  4.359825 |  4.052769 |  4.521184 |  4.052769 | ⋯ |  4.052769 |  4.052769 |  4.052769 |  4.591437 |  4.518895 |  4.052769 |  4.052769 |  4.052769 |  4.416300 |  4.052769 |\n\n",
            "text/plain": [
              "            TCGA-G9-7525-01A TCGA-EJ-7789-01A TCGA-EJ-7314-11A TCGA-HC-8265-01A\n",
              "A1BG|1       6.008894         7.355672         7.672604         7.907780       \n",
              "A2M|2       14.977996        14.768960        16.052200        14.783020       \n",
              "NAT1|9       7.369287         5.967220         8.657079         8.214435       \n",
              "NAT2|10      5.153428         4.052769         5.213812         4.687886       \n",
              "SERPINA3|12 16.425500         8.755545        14.887241        16.042970       \n",
              "AADAC|13     4.408430         4.052769         4.558712         4.052769       \n",
              "            TCGA-EJ-A46B-01A TCGA-HC-7819-01A TCGA-EJ-5510-01A TCGA-HC-7080-01A\n",
              "A1BG|1       7.380921         6.189704         6.560988         5.889730       \n",
              "A2M|2       13.568532        13.518895        14.263595        14.022247       \n",
              "NAT1|9       9.172845         5.967724         8.689489         6.183797       \n",
              "NAT2|10      5.166692         4.522975         5.095599         5.115032       \n",
              "SERPINA3|12 10.837725        14.793632        15.035991        12.389362       \n",
              "AADAC|13     4.052769         4.052769         4.359825         4.052769       \n",
              "            TCGA-CH-5769-11A TCGA-KK-A7AY-01A ⋯ TCGA-G9-6377-01A\n",
              "A1BG|1       6.145200         6.520872        ⋯  6.584258       \n",
              "A2M|2       14.657321        14.457274        ⋯ 13.784273       \n",
              "NAT1|9       8.645634         5.524921        ⋯  8.042378       \n",
              "NAT2|10      5.176564         4.514181        ⋯  4.859166       \n",
              "SERPINA3|12 15.395851        12.833889        ⋯ 15.029958       \n",
              "AADAC|13     4.521184         4.052769        ⋯  4.052769       \n",
              "            TCGA-V1-A8MF-01A TCGA-G9-6499-11A TCGA-J4-A67R-01A TCGA-KK-A6E7-01A\n",
              "A1BG|1       6.959848         6.889952         7.406567         6.830122       \n",
              "A2M|2       14.996586        15.086310        14.495920        14.170037       \n",
              "NAT1|9       8.220037         9.312656         7.235903         9.267809       \n",
              "NAT2|10      5.722875         5.025388         5.173697         6.807294       \n",
              "SERPINA3|12 10.727668        14.168768        16.990727        10.022932       \n",
              "AADAC|13     4.052769         4.052769         4.591437         4.518895       \n",
              "            TCGA-J9-A8CN-01A TCGA-CH-5762-01A TCGA-XJ-A9DX-01A TCGA-KK-A6E5-01A\n",
              "A1BG|1       6.074995         5.411722         8.238785         7.448119       \n",
              "A2M|2       14.425412        15.190929        13.686582        14.506364       \n",
              "NAT1|9       9.088459         7.819305         5.980150         9.675646       \n",
              "NAT2|10      4.465588         4.052769         4.052769         4.774214       \n",
              "SERPINA3|12 14.148247        13.947195        10.260316        12.506878       \n",
              "AADAC|13     4.052769         4.052769         4.052769         4.416300       \n",
              "            TCGA-EJ-5496-01A\n",
              "A1BG|1       5.840184       \n",
              "A2M|2       13.316533       \n",
              "NAT1|9       7.288150       \n",
              "NAT2|10      4.706704       \n",
              "SERPINA3|12 14.000804       \n",
              "AADAC|13     4.052769       "
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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bpkybK1XexFSKbjhOQQ85BaZw+QpCE3bI7aj5BMxwnJIcYhrTtAhjfPW7Bg7tQm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\nQAEhAQoICVBASIACQgIUEBKggJAABf8fNx02FUwO2yIAAAAASUVORK5CYII=",
            "text/plain": [
              "Plot with title “Histogram of assay(vsd)”"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 420,
              "width": 420
            }
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "head(assay(vsd))\n",
        "hist(assay(vsd))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "id": "If8YxYkBHdBP",
        "outputId": "81916210-a971-4a53-8deb-73d24574a71d"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<style>\n",
              ".list-inline {list-style: none; margin:0; padding: 0}\n",
              ".list-inline>li {display: inline-block}\n",
              ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
              "</style>\n",
              "<ol class=list-inline><li>'Intercept'</li><li>'Condition_Tumor_vs_Normal'</li></ol>\n"
            ],
            "text/markdown": "1. 'Intercept'\n2. 'Condition_Tumor_vs_Normal'\n\n\n",
            "text/latex": "\\begin{enumerate*}\n\\item 'Intercept'\n\\item 'Condition\\_Tumor\\_vs\\_Normal'\n\\end{enumerate*}\n",
            "text/plain": [
              "[1] \"Intercept\"                 \"Condition_Tumor_vs_Normal\""
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "resultsNames(mrna_dds)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 454
        },
        "id": "0Y1n8_sh2qnY",
        "outputId": "ed528d65-cd6c-4f5d-a4e9-7aa7ae8bbb5b"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<strong>null device:</strong> 1"
            ],
            "text/latex": "\\textbf{null device:} 1",
            "text/markdown": "**null device:** 1",
            "text/plain": [
              "null device \n",
              "          1 "
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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Vs4LSUiIspBce2xo/dZvmdU6JQ+4Yn21cSPyPmD9L23LBERUb4V1x47es/pd5U7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\nbB7LvgHnAEvBl9sYS0TnmHggLy/PxcVFcFDU5ObO3i96raCF/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M7OrmpDJA6napGjqKioiooKZWXl9PR0JrrxvWX69OlE5Ovrm5mZOXDg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\nWvVI0PkAAAAASUVORK5CYII=",
            "text/plain": [
              "Plot with title “Dispersion plot”"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 420,
              "width": 420
            }
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Plot Dispersions:\n",
        "plotDispEsts(mrna_dds, main=\"Dispersion plot\")\n",
        "dev.off()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "k4Wgwv5jHhTx"
      },
      "outputs": [],
      "source": [
        "mrna_res <- results(mrna_dds, name = \"Condition_Tumor_vs_Normal\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 437
        },
        "id": "dYgyPMx9Sp83",
        "outputId": "ec09fdcc-4ce8-4b25-e15a-3f224b8726b2"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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RJbbSVWrRoeaMwY0dUl1q4VjYY44wzx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ULOOO1Sp63TSac2CPM6og3KzLPflZUU7z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\nAAAAAElFTkSuQmCC",
            "text/plain": [
              "Plot with title “”"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 420,
              "width": 420
            }
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "plotMA(mrna_res)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "L-Veke1AUrBC"
      },
      "outputs": [],
      "source": [
        "?results"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "AazhRvpyHwPc"
      },
      "outputs": [],
      "source": [
        "mrna_res_df <- as.data.frame(mrna_res)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-K-9nFvnVhoh"
      },
      "outputs": [],
      "source": [
        "mrnaTable <- mrna_res_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "94ighOJsVxxt"
      },
      "outputs": [],
      "source": [
        "mrnaTable$Gene_id <- rownames(mrnaTable)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ycjzWeB3VL32"
      },
      "outputs": [],
      "source": [
        "write.table(mrnaTable, \"/content/Results/mrna_res_df.txt\", quote = F, sep = \"\\t\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Vf5qIRGiHqno",
        "outputId": "2eb3d9fc-6ebd-4ef1-e1e9-5496038ff817"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "out of 19669 with nonzero total read count\n",
            "adjusted p-value < 0.1\n",
            "LFC > 0 (up)       : 6878, 35%\n",
            "LFC < 0 (down)     : 6338, 32%\n",
            "outliers [1]       : 0, 0%\n",
            "low counts [2]     : 0, 0%\n",
            "(mean count < 0)\n",
            "[1] see 'cooksCutoff' argument of ?results\n",
            "[2] see 'independentFiltering' argument of ?results\n",
            "\n"
          ]
        }
      ],
      "source": [
        "summary(mrna_res)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ra1b4ZkCJD77"
      },
      "outputs": [],
      "source": [
        "mrna_upreg <- get_upregulated(mrna_res)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "PVyA1wTvJGCb"
      },
      "outputs": [],
      "source": [
        "mrna_downreg <- get_downregulated(mrna_res)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "WD-xItjBJI_3"
      },
      "outputs": [],
      "source": [
        "mrna_counts <- counts(mrna_dds, normalized = T)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "LJAXWJVQKa9s"
      },
      "outputs": [],
      "source": [
        "mrna_upreg$Gene_id <- rownames(mrna_upreg)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "fHqADzNtKfHU"
      },
      "outputs": [],
      "source": [
        "mrna_downreg$Gene_id <- rownames(mrna_downreg)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4Td8q1lLWHky"
      },
      "outputs": [],
      "source": [
        "mrna_res_df$Gene_id <- rownames(mrna_res_df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "XzadSEvvJOIq"
      },
      "outputs": [],
      "source": [
        "write.table(mrna_counts, \"/content/Results/mRNA_norm.counts.txt\", quote = F, sep = \"\\t\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "X5ltTRW9VmwK"
      },
      "outputs": [],
      "source": [
        "write.table(mrna_res_df, \"/content/Results/mrna_res_deseq2.txt\", quote = F, sep = \"\\t\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "30aK64HeJkFb"
      },
      "outputs": [],
      "source": [
        "write.table(mrna_upreg, \"/content/Results/mRNA_upreg.txt\", quote = F, sep = \"\\t\", row.names = F)\n",
        "write.table(mrna_downreg, \"/content/Results/mRNA_downreg.txt\", quote = F, sep = \"\\t\", row.names = F)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "FvjU_U9hZkdZ"
      },
      "outputs": [],
      "source": [
        "write.csv(as.data.frame(mrna_upreg), file=\"mrna_upreg.csv\")\n",
        "write.csv(as.data.frame(mrna_downreg), file=\"mrna_downreg.csv\")\n",
        "write.csv(as.data.frame(mrna_counts), file=\"mrna_counts.csv\")\n",
        "write.csv(as.data.frame(mrna_res_df), file=\"mrna_res_df.csv\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "USjr0shQOeJw"
      },
      "outputs": [],
      "source": [
        "par(mar=c(5,5,5,5), cex=1.0, cex.main=1.4, cex.axis=1.4, cex.lab=1.4)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "with(mrna_res_df, plot(log2FoldChange, -log10(padj), pch=20, main=\"Volcano plot\", cex=1.0, xlab=bquote(~Log[2]~fold~change), ylab=bquote(~-log[10]~P~value)))\n",
        "\n",
        "with(subset(mrna_res_df, padj<0.05 & abs(log2FoldChange)>2), points(log2FoldChange, -log10(padj), pch=20, col=\"red\", cex=0.5))\n",
        "\n",
        "#with(subset(mrna_res_df, padj<0.05 & abs(log2FoldChange)>2), text(log2FoldChange, -log10(padj), labels=subset(rownames(mrna_res_df), mrna_res_df$padj<0.05 & abs(mrna_res_df$log2FoldChange)>2), cex=0.8, pos=3))\n",
        "\n",
        "#Add lines for absolute FC>2 and P-value cut-off at FDR Q<0.05\n",
        "abline(v=0, col=\"black\", lty=3, lwd=1.0)\n",
        "abline(v=-2, col=\"black\", lty=4, lwd=2.0)\n",
        "abline(v=2, col=\"black\", lty=4, lwd=2.0)\n",
        "abline(h=-log10(max(mrna_res_df$pvalue[mrna_res_df$padj<0.05], na.rm=TRUE)), col=\"black\", lty=4, lwd=2.0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 437
        },
        "id": "eEDRpB3gvX6A",
        "outputId": "ed571e1e-b8df-464c-8a63-9b9d090963c0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Plot with title “Volcano plot”"
            ],
            "image/png": 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ExMjPXp999/HxkZmZWV9cQTTzz33HMt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\n1c18FYcOHQKQw/fI1R5wdXXlcDhsNvvUqVPDhg3r06fPjBkz0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Xz88cfmndyxY0dy5WNiYr7//vspU6asW7cuidtKEn755ZfkBG6BAgXO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\nAAAASUVORK5CYII="
          },
          "metadata": {
            "image/png": {
              "width": 420,
              "height": 420
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 437
        },
        "id": "AC7a4TU1OlOp",
        "outputId": "0015b7f2-1aeb-46c6-f525-3942bfd014a9"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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gAAQEIWeSpWCDFp0iR3d/eTJ08GBgZq\nJtu2bRs8ePDcuXNXrFghbTYAAABJWMwRu6IePnx4/fr18ePHa1udEGLgwIH9+/c/cOCAhMEA\nAAAkZJFH7HJzc4UQRVudRtOmTffs2VOmTaWkpIwZM+bp06clrJOamiqEKCwsLGNMAAAAs7LI\nYuft7e3u7p6YmKgzT0pKcnV1LdOmHB0dmzdvnp+fX8I6mnsyVCpVWXMCAACYkyUVuzt37sTG\nxnp4eHh4eIwbN2758uUTJ050cnLSLL127drGjRs7d+5cpm26urrOmTOn5HWWLl1a9L4NAACA\nismSit369evXr19fdLJv375BgwYJIdatW/fWW289ffp0xowZEqUDAACQmMUUu5UrV6YXkZGR\nkZ6e7unpqVmanp7u4eGxYcOGNm3aSJsTAABAKhZT7N54440SlkZERIwdO1ahsMibfAEAAIxC\nJk3IxcVFoVCkpaXduHFD6iwAAADSkEmx05g3b57mHbIAAACVkKyKHQAAQGVGsQMAAJAJi7l5\nonXr1gbXuXfvnhmSAAAAVEwWU+zi4uKEELa2tiWsw8shAABAZWYxp2KnTJni7Ox86dKl3Geb\nPHmy1DEBAAAkYzHFbs6cOf7+/sOHDy/5va4AAACVlsUUO1tb27Vr116+fHn69OlSZwEAAKiI\nLOYaOyFEYGBgcnJyCRfS9erVy8PDw5yRAAAAKg5LKnZCCDc3txKWhoaGhoaGmi0MAABAhWIx\np2IBAABQMoodAACATFDsAAAAZIJiBwAAIBMUOwAAAJmg2AEAAMgExQ4AAEAmKHYAAAAyQbED\nAACQCYodAACATFDsAAAAZIJiBwAAIBMUOwAAAJmg2AEAAMgExQ4AAEAmKHYAAAAyQbEDAACQ\nCYodAACATFDsAAAAZIJiBwAAIBMUOwAAAJmg2AEAAMgExQ4AAEAmKHYAAAAyQbEDAACQCYod\nAACATFDsAAAAZIJiBwAAIBMUOwAAAJmg2AEAAMgExQ4AAEAmKHYAAAAyQbEDAACQCYodAACA\nTFDsAAAAZIJiBwAAIBMUOwAAAJmg2AEAAMgExQ4AAEAmKHYAAAAyQbEDAACQCYodAACATFDs\nAAAAZIJiBwAAIBMUOwAAAJmg2AEAAMgExQ4AAEAmKHYAAAAyQbEDAACQCYodAACATFDsAAAA\nZIJiBwAAIBMUOwAAAJmg2AEAAMgExQ4AAEAmKHYAAAAyQbEDAACQCYodAACATFDsAAAAZIJi\nBwAAIBMUOwAAAJmg2AEAAMgExQ4AAEAmKHYAAAAyQbEDAACQCYodAACATFDsAAAAZIJiBwAA\nIBMUOwAAAJmg2AEAAMgExQ4AAEAmKHYAAAAyQbEDAACQCYodAACATFDsAAAAZIJiBwAAIBMU\nOwAAAJmg2AEAAMgExQ4AAEAmKHYAAAAyQbEDAACQCYodAACATFDsAAAAZIJiBwAAIBMUOwAA\nAJmg2AEAAMgExQ4AAEAmKHYAAAAyQbEDAACQCYodAACATFDsAAAAZIJiBwAAIBMUOwAAAJmg\n2AEAAMgExQ4AAEAmKHYAAAAyQbEDAACQCYodAACATFDsAAAAZIJiBwAAIBMUOwAAAJmg2AEA\nAMgExQ4AAEAmKHYAAAAyQbEDAACQCYodAACATFDsAAAAZIJiBwAAIBMUOwAAAJmg2AEAAMgE\nxQ4AAEAmKHYAAAAyQbEDAACQCYodAACATFDsAAAAZIJiBwAAIBMUOwAAAJmg2AEAAMgExQ4A\nAEAmKHYAAAAyQbEDAACQCYodAACATFDsAAAAZIJiBwAAIBMUOwAAAJmg2AEAAMgExQ4AAEAm\nKHYAAAAyQbEDAACQCYodAACATFDsAAAAZIJiBwAAIBMUOwAAAJmg2AEAAMgExQ4AAEAmKHYA\nAAAyQbEDAACQCYodAACATFDsAAAAZIJiBwAAIBMUOwAAAJmg2AEAAMgExQ4AAEAmKHYAAAAy\nQbEDAACQCYodAACATFDsAAAAZIJiBwAAIBMUOwAAAJmg2AEAAMgExQ4AAEAmKHYAAAAyQbED\nAACQCYodAACATFDsAAAAZIJiBwAAIBM2UgcoM7VanZCQEB8fn5WVJYRwd3cPCAjw8fGROhcA\nAIDELKnYPX78eO7cuatXr05JSdFZVLdu3TFjxkyePNnR0VGSbAAAAJKzmGJ3//79kJCQhISE\ngICA3r17+/r6Ojs7CyEyMzNv3rx55MiRmTNnbt269fDhw56enlKHBQAAkIDFFLsZM2YkJiZu\n2rRpyJAhxZcWFBQsXbp0woQJs2fPXrBggfnjAQAASM5ibp7Ys2fPyJEj9bY6IYS1tfW4ceOG\nDh26bds2MwcDAACoICym2KWlpTVo0KDkdQIDAx88eGCePAAAABWNxRQ7b2/vCxculLxOXFyc\nt7e3efIAAABUNBZT7MLCwjZv3jx//vy8vLziS3NycmbNmrVz587w8HDzZwMAAKgILObmiU8+\n+SQmJmbKlCmffvpp27ZtfXx8XFxc1Gp1dnb27du3T58+/eTJkw4dOvzzn/+UOikAAIA0LKbY\neXh4nDx5ctGiRatWrYqOji4oKNAusrW1DQoKioyMjIyMtLa2ljAkAACAhCym2Akh7OzsJk2a\nNGnSpNzc3Lt372rePOHm5la3bl07Ozup0wEAAEjMkoqdhlqtTkpKun37tvaVYvb29rxSDAAA\nwJKKHa8UAwAAKIHFFDteKQYAAFAyiyl2vFIMAACgZBbzHDteKQYAAFAyizliV8pXim3fvr1M\nm01KShoyZIjehx5rPXz4UAihVqvLtGUAAAAzs5hiZ6JXinl6eg4ePFipVJawzqlTp+7cuWNl\nZVWmLQMAAJiZxRS7sLCw7777rk2bNu+++669vb3O0pycnK+++mrnzp0fffRRmTbr6Og4adKk\nktdZunRpWQ8EAgAAmJ/FFDteKQYAAFAyiyl2vFIMAACgZBZT7ASvFAMAACiRJRU7LQcHh4CA\ngOLztLS0x48f+/v7mz8SAACA5CzmOXalMW/ePL2FDwAAoDKQVbEDAACozCh2AAAAMmEx19i1\nbt3a4Dr37t0zQxIAAICKyWKKXVxcnBDC1ta2hHVUKpW54gAAAFQ4FnMqdsqUKc7OzpcuXcp9\ntsmTJ0sdEwAAQDIWU+zmzJnj7+8/fPjw/Px8qbMAAABURBZT7GxtbdeuXXv58uXp06dLnQUA\nAKAisphr7IQQgYGBycnJJVxI16tXLw8PD3NGAgAAqDgsqdgJIdzc3EpYGhoaGhoaarYwAAAA\nFYrFnIoFAABAySh2AAAAMkGxAwAAkAmKHQAAgExQ7AAAAGSCYgcAACATFDsAAACZoNgBAADI\nBMUOAABAJih2AAAAMkGxAwAAkAmKHQAAgExQ7AAAAGTCppTr3bp168aNG6mpqRkZGe7u7tWq\nVfP3969Xr54pswEAAKAMDBS7+Pj4BQsW7Nu378aNG8WX+vv79+7d+/333/fz8zNNPAAAAJTW\nM4vdw4cPp06dumrVKpVKVaNGjfDw8ICAgBo1anh4eKSnp6ekpFy/fj0qKuq777774YcfIiIi\n/vWvf1WvXt2c0QEAAFCU/mIXHR0dHh6elpY2bNiwDz74oGXLllZWVsVXU6vVcXFx33zzzc8/\n/7x79+5NmzaFhoaaODAAAAD003/zRPfu3Rs1avTnn3+uWbOmVatWeludEMLKyqpVq1Zr1qy5\ndu1ao0aNunXrZsqoAAAAKIn+Yjd16tSoqKgGDRqUciv+/v5RUVFTp041XjAAAACUjf5i9+mn\nn1pbW+sMs7KyLl++nJ6ervcr1tbWn376qZHTAQAAoNRK9Ry7I0eOtG7d2s3NrWnTpr///rtm\n2K9fv99++82U2QAAAFAGhovd6dOnu3fv/tdff/Xo0UM7fPjw4ZkzZ3r37n327FlTxgMAAEBp\nGS52n376qZeX15UrV3766SftsHr16hcuXPDy8pozZ44J0wEAAKDUDBe733///Z133qlTp47O\nvEaNGmPHjj169KhpggEAAKBsDBe7jIwMHx8fvYtq1aqVnZ1t7EgAAAAoD8PFzsvL6+rVq3oX\nHT161Nvb29iRAAAAUB6Gi13v3r1/+OGHc+fOFR0+fvz4448/XrlyZZ8+fUyWDQAAAGVguNjN\nnj3bxcWlXbt2mg43bdq0li1b1qpV6/PPP69bt+7MmTNNHxIAAACGlepUbGxs7Jtvvnn79m0h\nxPnz58+fP+/q6vrOO++cOXOmZs2apg8JAAAAw2xKs1KNGjV++OGHRYsWpaSkZGVlubq60ucA\nAAAqmlIVOw0rK6uaNWtS6QAAAComw8Wua9euJSxVKpU8yg4AAKAiMFzsSnghrKurq6urq1Hz\nAAAAoJwMF7v8/HydiVKpTEhI+Omnn06fPv3LL7+YJhgAAADKxvBdsTbFODk5NWnSZN68ecHB\nwR999JEZUgIAAMAgw8WuBP3799+1a5exogAAAOB5PFexy8rKSk9PN1YUAAAAPA/D19jprW75\n+fmXL1/+8MMP/fz8TJAKAAAAZWa42Hl6epawdPXq1cYLAwAAgPIzXOw0r4jVYWtrW6tWrUGD\nBnXp0sUEqQAAAFBmhovd7t27zZADAAAAz0l/sUtMTCz9JurUqWOkMAAAACg//cXOx8en9JtQ\nq9VGCgMAAIDy01/swsPDzZwDAAAAz0l/sduwYUNpvpyTk5OVlWXUPAAAACin53pA8c6dO1u1\namWsKAAAAHgehu+KFUKkpqZu2LDh1q1bKpVKO8zNzd29e3d2drbJsgEAAKAMDBe7W7dutW3b\n9uHDh3q+bGMzY8YME6QCAABAmRkudv/85z9zc3O///77wMDALl26/Pjjj3Xq1ImOjl69evXy\n5ct79OhhhpQAAAAwyHCxi4mJGT9+/Pjx43Nzc4UQTZo0eemll3r06BEeHt6lS5ddu3aFhISY\nPicAAAAMMHzzxP379+vXry+EUCgUQgilUqmZt2jRYvz48bNmzTJpPgAAAJSS4WLn6ur64MED\nIYSdnZ2Li0t8fLx2UePGjWNjY02YDgAAAKVmuNh16NBhyZIl0dHRQohmzZotWrRIeydsVFSU\nvb29SfMBAACglAwXu+nTp6elpU2ePFkI8eabb8bGxjZu3HjgwIEtW7ZctmxZt27dTB8SAAAA\nhhm+eaJt27bHjh07ffq0EOKNN964fv36ggULtm/fbmVl1a9fvwULFpg+JAAAAAwr1QOKg4KC\ngoKChBBWVlaff/75zJkzk5OTa9as6ejoaOJ4AAAAKC3Dp2JDQ0OXLVuWnp6unTg4ONSrV49W\nBwAAUKEYLnYxMTFvvfWWl5fXoEGDtm/frn3cCQAAACoUw8Xuzp073377batWrbZv3z5w4EAv\nL6+33347JiZGrVabIZ/sKZ9SlAEAgHEYLnZ16tR5//33T5w4oWl4jRo1WrZsWceOHf38/D7+\n+OOrV6+aIaX85Gbnrmz41j2rWrZODtcV9Vd2+ljqRAAAwOIZLnZaOg3P19f3q6++aty4senC\nydimRmNG/7Wstki2EuoAdcLoI5+v7DJT6lAAAMCylaHYaTk7O1etWrVOnTpubm5GD1QZZD/K\nDr+3RWfY7vCGZ63/x77zP9eN2OnS42efkXG7eNUHAADQr1SPO9FISUnZsWPH1q1bo6KiVCqV\nu7v7wIEDhw8fbrpwcnVuy8mOIk9n+II6QaVU3buSeGTmOlXKY+9+L/ecPlAIsXfOlo4z33hR\n5AghRI7I6b9994wfX/10mPljAwCACs5wsbt379727du3bt0aExNTUFDg6OgYFhY2YsSI3r17\n8z6x8mnSq6VK2NgIVdHhbas6595b0WnJ9AiRJoQQp8T2L3r0Tdvt9clsF02rE0II4Sxy6s79\nVFDsAABAMYaLnY+Pj1qttrGx6dat2/DhwwcMGODq6mqGZDJW1afadteuA7J+LTo8Vq9TryUf\nV9e0OiGEEAOy969oOXFUoe7tKU0L/0y+nuwV4GWOrAAAwHIYvsYuJCRk0aJFSUlJ+/bti4iI\noNUZxctnV251610oFEKIPGG/qs5rjl3a1hCpOqvVv36uQFjrDAuFwt7ZzkxBAQCA5TB8xC4m\nJkbz4f79+8nJyenp6VWrVq1Vq1b16tVNnE3OvAK8BmXsSYlPuXrgfMtBL0VUd4pok0oAACAA\nSURBVFvV/4viq7kUPv3dpnlH1Zmiw9M2zYO9q5grKQAAsBiluit22bJlfn5+3t7erVq16ty5\nc/PmzWvUqBEYGLhhwzNv5ERp1KhfI3Rsd7fqbkKIJqM6F1/huqe//apv7wpv7SRR1FIvm2++\niAAAwHIYPmK3ePHicePG2dvbd+3atXbt2s7OzhkZGdevXz9z5szw4cOVSmVERIQZgspe0MB2\nq2q/FnFvrXaSJLyCts99oX2jhy/HrYxYoLiVWOhb+9XVk0Lq1ZAwJwAAqLCsDL4ZrGHDhn5+\nfhs3bnR3dy86T0hI6N69u52d3eXLl02ZUHpLly4dO3ZsVlaWi4uLqfe1qt/nVQ/95pafdbt6\ng5e3f9qgXYCp9wgAAMpEqVTa29sfP348ODhY6iy6DB+xu3Xr1ooVK3RanRDCz89v0qRJH3zw\ngWmCVVIRu6YLMV0I0UHqJAAAwOIYLnbu7u7W1ro3ZmpYW1tXq1bN2JEAAIBJbBj9fe6Rc4Uu\nzo0/GvrSaxxDkCHDxa5v376//PLLSy+9VHzR7t27hwwZYoJUAADAmJRPlYc9uw7L+/tJF3mv\nL1u57B+jo+dKmwpGZ7jYffbZZ2FhYbdu3Ro2bFhAQICTk1NOTs6VK1dWrFihVCrHjx+fmJio\nXblOnTqmTAsAAMpjTfCUyP+0OiGEvcgbduTbP/YNebFXCwlTwegMFztvb28hxOnTp9etW1d8\naUDA/1zdb/BWDAAAYH61r8bpTBzF07hFeyh2MmO42IWFhfFOWAAALJqtWlV8WPg0z/xJYFKG\ni9327dvNkAMAAJjO7TqBIv5k0UmBsA6M7CZVHpiI/jdPnD17thzbKt+3AACAqYXFzLugCCw6\nWVV/FDfGyo/+YhccHLxw4cIybWjhwoUV8DF9li49OV3qCAAAOfD0rtLg4ekVQZO2u/bcUCVs\ny/hlo28ulzoUjE9/sXvrrbcmTpwYHBy8b98+g5vYt29fcHDwxIkT33zzTWPHq6Run7+12bNf\nppWbW62qF60DN4z+/nm2dvPU9ZWdPl7RdPzmd/5trIQAAIvjUsUlMvabAZn7hqVtH/z9GKnj\nwCT0X2OnOfz27rvv9u7dOzAwsHv37q+88oq/v3+1atXc3d0zMjJSU1Nv3Lhx+PDhAwcOXL16\ntWrVquvWrRs+fLiZ08tSYUFhfLsRQ5R/XwnRrPBao58++KV21b6flecv76a3l3b799TRIl0I\nIS6LqBU/tb1/wKWKyd+NBgAAzK+kd8VmZ2d///33CxYsePDgwbPW8fLyev/998ePH2+G96hK\nxZzvihVCHJy/q9uU/jrDXc7d+mUfKOum0u6mquo2rikeFh3+VO+NNxJWPldEAAAqMUt9V6yL\ni8vUqVM//PDDs2fP/vbbb9evX09NTc3MzHRzc6tWrVpAQEDXrl1btWqlUOg/n4vySYq6UHzo\n+zSx+NCgmIX7wv631QkhGt/VfZQRAACQB8OPO1EoFG3atGnTpo0Z0kAIUf2lRqLYlY2J9rWa\nl31TuamZxYeOhbnliQUAACo8w8VOrVYnJCTEx8dnZWUJIdzd3QMCAnx8fEyfrZLq/EHf2E9f\nbF3wR9Fh1rCB5dhUm7e7K1fa2Qll0eFV94bNnisgAACooEoqdo8fP547d+7q1atTUlJ0FtWt\nW3fMmDGTJ092dHQ0ZbzKyMHFwXbnyoOD3uuWd0wIkSKq7XnlndErxpdjUw3aBaxo9lbkxf/e\nVHtPeL244wujZQUAABXJM4vd/fv3Q0JCEhISAgICevfu7evr6+zsLITIzMy8efPmkSNHZs6c\nuXXr1sOHD3t6epoxcKXQvE8rkRuTdC3pwZ/3mr8aNNq6/FcxRv6xcMv4F8XanW65mUle9V/Z\n8UmjFvWMl9SYkq4lHew5zS/p2hNrx/ttQ0YenG1jZ/iIMgAA0HrmPzhnzJiRmJi4adOmIUOG\nFF9aUFCwdOnSCRMmzJ49e8GCBaZMWHl5N/L2buT9/NsZvOhNsaiiP2IwJT4lp3H7UeoEIYTI\nF+LokS01LgxO3y11LgAALMkzDwXt2bNn5MiReludEMLa2nrcuHFDhw7dtm2bybKhEtnbbWqA\nptX9x+CMPXvnbJEqDwAAluiZxS4tLa1BgwYlfzkwMLCER9wBped970bxYfKuk8WHAADgWZ5Z\n7Ly9vS9c0PNAtaLi4uK8vY1wrhDIsXUqPlRUcTN/EgAALNczi11YWNjmzZvnz5+fl5dXfGlO\nTs6sWbN27twZHh5uynioLDI7hOhMsoRL63+ESRIGAAAL9cxXiqWnp3fp0uXcuXOurq5t27b1\n8fFxcXFRq9XZ2dm3b98+ffr0kydPOnTosHfvXhm/TEzDzK8Uq7TW1RwSnrLdWhQIITKF647+\n0yN2TJU6FAAAuizylWIeHh4nT55ctGjRqlWroqOjCwoKtItsbW2DgoIiIyMjIyOtra3NkhPy\nN+LB5qiF+26tj7b2cGn30aCI0MZSJwIAwMI884hdUbm5uXfv3tW8ecLNza1u3bp2dnamz1ZR\ncMQOAABoWeQRu6IcHBwCAgKKz9PS0h4/fuzv72/sVAAAACiz8r/SQAgxb948vYUPAAAA5vdc\nxQ4AAAAVB8WuzPZ/uWOHa88zNs1/ce62Y8oqqeMAAAD87ZnX2LVu3drgl+/du2fUMBZgy4Qf\nwxa9YyNUQgjxRIj5h1b9dS9i5zSpcwEAADy72MXFxQkhbG1tS/iySqUyfqKK7YXF3/zd6v6j\n667vhKDYAQAA6T3zVOyUKVOcnZ0vXbqU+2yTJ082Z1bJpSenNy68rjP0FsmXDhh49xoAAIAZ\nPLPYzZkzx9/ff/jw4fn5+eYMVJG5VXfLFs46wwJhXfOFWpLkgUW4ciW1W7dof/9jr7wSffZs\nstRxAABy9sxiZ2tru3bt2suXL0+fPt2cgSoyhbXisMtLOsOjdm2r16shSR5UfDt23Gja1PbQ\noU43b7aPju7Upo3rihWXpQ4FAJCtkh5QHBgYmJycXMKFdL169fLw8DBBqoqrVcySk60HvlwQ\np/nxD0Vg1R0/SBsJFdmoUU/Uanftj2q18/jx9pGREiYCAMiZgTdPuLm5lbA0NDQ0NDTUqHkq\nOt8W9XzyYrd/uDo99i/XpvX6zR9l51iJ3q6GMsnMzMvMbKQzzM1tkJCQ7udXuf6NCABgHqV6\npRiKUlgrBnw9SuoUsAA2NgohCoqN1XZ21hKkAQBUAoaLXatWrezsnnlQytraulq1au3bt3/z\nzTcr22lZoGROTrZVq15MS2tVdOjsfK127cZSRQIAyJvhYvfw4cOsrKyMjAzNj9bW1gUFfx+E\nsLe3V6vVSqVy165dixYtOnHihLe3twnDApZm27bqnTvfLyj4+75phSJ1zRrO3QMATMXwK8X+\n/PPPjh07du7c+ddff83MzFSpVDk5Ob/99lv37t2HDRuWk5OTkZHxzTffJCYmzpw50wyJAQvS\nsaNPUpLbyJExbdseGTbsaHy8bViYv9ShAACyZfiI3YcffpidnX3o0CGF4u8W6OTk1Llz506d\nOnXr1m3OnDmzZ8+eNGnStWvX9u7da9qwFiIlPuXcxuM1m/i07Gf4tWyQvRo1nFet6iB1CgBA\npWD4iN3mzZsHDx6sbXX//aZCMXTo0FWrVml+bN269YMHD4wf0NKsbPiWSwO/ntMHtuzfJsa2\nbdzOM1InAgDAVGK3/L7WK/ygQ4f11QYdWXJA6jgoxRG7zMzM1NRUvYsyMjLu37+v+Xzv3r1q\n1aoZM5oFWtl55ui/lml/7KA6EztojOrJWRs77j4GAMjN3jlbXpkZ0Vo8FUKIPJH/zi8bY/8v\n/Md3pM5VqRk+Yte4cePFixefO3dOZ37t2rXFixf7+fkJIWJjYxcvXhwUFGSSjJajwbH9OpPW\nBX8c+/E3ScIAAGBS1WfPcdS0OiGEELYiv+2Kf0mYB6I0R+w++eSTAQMGBAUFNWrUyN/f38nJ\nKTc399atWxcvXlSr1cuXLxdC/OMf/8jIyJg2bZrpA1dotVUpxYf3f/9TjOth/jAAAJhO9qPs\n5gXXdIZ+6jvXjlxpFMpDnSRjuNj17dv3t99+mzt3bkxMzLVrf/8ttLa2btu27Ycffjhw4EAh\nxBtvvDF//vw2bdqYNmyFd93et0HuLZ1ho0EvS5EF0LV3b/ycOXcfPLBp1Ei1eHELX193w98B\ngGdwcHHIFbZ2Qll0WCgUbjV5qK2USnXtl/bVYY8fP3706JGtra2Xl1fRpxaPHj3aVAEtSv4/\n3s6fe8JW5Gsn21x7Dexf2fsuKoJ//vP03LkthagvhEhIEPXrp5w4kdSuHQ+eBFBONnY2MQ5t\neuVGFx2etm7+UiP+YJGS4WvstFJTU69du5aQkHD//v0nT56YLpPl6vvZ8F3vLjlp3TJHON+y\n8vnJd9Qr19ZIHQoQSmXBF1/4C2GrnRQW1hg8+I6EkQDIgO+ehVet/vtszluiTuGKbyXMA1HK\nI3bHjh2bPHnyqVOntBMrK6vOnTsvWLCgadOmJstmkQZ9Fym+ixRCOAvxhtRhAI19+xIKC3Uf\njJyUVF+SMABko3Hnpk8eX1g16ruCP28p/Gr3+3F8Pe8qUoeq7AwXu9OnT3ft2lWlUrVv375h\nw4aOjo45OTlXrlyJiooKCQk5ffp0w4YNzRAUQLk5Our5f7pCoTJ/EgAy4+TuFLFjqtQp8F+G\ni91nn31WvXr1gwcPNmrUqOg8Li6uZ8+es2fPXrduncniATCCzp3r2tjcU6lqFx36+cULwaUw\nACArhq+xO3HixLhx43RanRCiZcuW48aNi4qKMk0wQIbu38/+8stzH374+6lTSebcr42N4v/+\nL83KKkM7sbe/sW9fE3NmAACYgeEjdhkZGXXq1NG7qF69eo8ePTJ2JECevvrq3LRpdQoLWwkh\n5s3LDw2Njo7uZLa9jxv3YufOaZ98cjQxsbBFC7uvvmrj5GRr+GsAAItiuNjVqFHj6tWrehdd\nuXKlRo0axo4EyNBffz2aNq1eYaH2smLbI0c6TZt26osv2pktQ6NGVTds6Gi23QEAzM/wqdju\n3bsvXLhw586darVaO1Sr1du3b1+0aFGvXr1MGQ+QiR9//KtIq/vbpk3cvgAAMCbDR+xmzZq1\nd+/esLAwLy+vxo0bOzs7a+6KTU5OrlWr1qxZs8yQspJbM2RenZ1ba6lSE+zr5P/j7b6fDZc6\nEcosMVFZfJiZaW/+JAAAGTN8xK5evXqxsbGjRo16+vRpVFTUL7/8EhUVpVQqx4wZc/bs2Wdd\nfgdjWdHmH69v+bBT/qmG6ps9c4/0mhuxZcKPUodCmXXrVrX48IUXss2fBAAgY1ZFT7CWTK1W\nJycn5+TkuLi4eHl5mTRWhbJ06dKxY8dmZWW5uLiYedfKp8o8p6qu4n/+8R+raNa64A8zJynu\n7LZTnj5V67fRfewtnsXX98SdO8HaH62tk69etQsI4GGeAGBhlEqlvb398ePHg4ODDa9tXvpP\nxSYmJj7rCw4ODiqVqugKHLQzndPrj7cXugd1mhZeVylVNnalemuIKawZ+nXo5m+CRJIQ4qR1\ny/wfvuz4VjepwliQq1fbvPbakehoj7w8e3//lDVrGtHqAADGpb8c+Pj4lH4TpT/mh7LybdNA\nLaysxP/8FU4VnnWka3W/fr5t6ObpduLvK8ZeLoi7Mfath91PVa/H/dEGODnZbt8e+p+fdB8M\nCQDA89PfD8LDw82cA3r5NKt7xLZtaP6posOjNUJGSBVIiMffrNW2Og1/9a21U1e/tuEfUkUC\nAAAa+ovdhg0bzJwDz+K5c8mZvqPa/Oeiun0OnXrFLZUwT/WsB8WHeVdumT0IAADQJdkZPZTS\ni71aFObF7Z27Ne18vE/XFr3G9Si+zuOkR8eXHFA9VQa/07NGfdOeEn3gWVsUq3ZOQQ1NulMA\nAFAaZSt28+fP37Fjx7Fjx0yUBnoprBW9Zw551tL1oxaGrvr8VZEshHg03/OnbhPfOPCJ6cL4\nfTUua9TeojfqnlM0ffXrN0y3RwAAUEqGn2NX1I0bN44fP26iKCiHs9tO9Vn1sbdI1vxYRTwe\ncfCL/V/uMN0egyNCD09besq6Rb6wzRbOO5272+9f61LF3A+CAQAAxZWt2KGiufDFJjeRVXRi\nJ5TJi7aZdKf9Ph/RThWXl/bISZXZP3t/k64vmnR3AACglLjGzrJZJ6cUH7pkpJlh13qP0mU+\nzDw4Z0vOnZSG4R3aDQ8xQwwAAKBFsbNwLzYUxR4mneFbX4oo4tcvtgd8/MEg9S0hROFOxYZ3\n+w99sEVhzVFhAADMpGz/0P3Xv/519+5dE0VBOQxZ98FZRdOik3gr356bppk/SebDzBc+ntRA\nfUvzo0IUDkvb/lO7yeZPAgBApVW2Yufh4cELxCoUJ3enKqd3rqsx+LqVX4JV3S3ufZ78utO7\nkbf5kxz5vz311bd1hv5/cKsNAADmw6lYi+cXVN/vwea/P0sXI/NGUvFhFVW6+ZMAAFBpcf0T\njKPpyFfUwkpneN1Fmqv9AAConCh2MI7mfVqtqzG46CRTuHov/adUeQAAqIQ4FQujCb+7bsUr\n9f1PR1UtyPjTpYH34mkv8cQTAADMiGIHo7Gxs4k8/i/N5ybSRrE0KlXhnj3xiYlPeveu6+fn\nIXUcAIClotgBEvvll5vh4flPnzYSQgiR27Vr9MGDnaSNBACwUFxjB0gpMzNvyBCr/7Q6IYTD\noUOdJk48IWUmAIDFotgBUtq48Xpenu69w5s2cSgdAFAeFLvyS7ubutJ/TIxt2xjbtitfePNx\n0iOpE8HyXL2aVXyYmelm/iQAABngwEA55Wbn3vDrNrrgvObHDtfPnPQ91/LxcQcXB2mDwbJ0\n7+717be6Q2/vNCmyAAAsHkfsyml9v8/b/afVabysOrdh0JdS5YGF6tnTz89P58VrOd99V0ua\nNAAAC0exKyf7i1eKD20v6BlWKHs/3XzQocMdqzpnrZutaPsP5VOl1Ikgzp0L6to12t7+hkLx\noGbN0xs2JPbuzRs7AADlwanYclK6uolUfcMKbO+cLV1nvW4nlEKIuoX3gs5cWt3g/sikdVLn\nquw8PByKPN+kpoRJAEBOrkRdSjh6pWlYW98W9aTOYj4csSunGqN7q/63FucLW+8xfaTKUxq2\nny3QtDqt1+5vTDgbL1UeAABM4fb5W3udOjfu0qzP7PDaLQPWVR9cec5QUezKqfeMwataT3wq\nHDU/PhFOq9u91+OjMGlTlSxQqdvhFKLw3M/RUmQBAMBULgb/v95PD2s+2wjViNSt65qMlTaS\n2XAqtvwiz3x96UDE2e92CyFav983suuLUicyIFlRrU7hfZ2hVysu5wKA/7H1vRXOS3/2USbf\ntfPKeXvUoP+LlDoRyiAlPqX302idYeit36TIIgGK3XNp2r150+7NpU5RWn807tj60sWik3OK\npi+P7ChVHgAwp2vX0kaOvHT9uoejY+7gwQX/938vKxRWxVdbPeirkds+0nxukveX+O7o6sTU\nkVs/NG9YlN+1Qxc6ikKdYR31fZVSZWMn/9rDqdhKJOLsgvXVBhYIa82PacLzWpWGfx27Zro9\nPk56tOntpav6f3Fq/XHDawOAyVy5ktqkiSo2NjQjo3lycrvvvw9u1+6o3jXbb19kcIKKrHV4\nSK7QfabsNUWDytDqBMWuUrGxsxn+cOvqHjPyha0Qoqp4PCJ1q1en4KP/PmiK3e2avi6zdvOh\n/x4bsWt66xGh62oOMcVeAKA0Roy4XFj4P3edx8aGHj58R2e1uxfv+Kl1h37qO3cv6g5RYTm5\nO23wG64zjOs7SpIw5kexq3Q6719mK/K1P3qIDPWEGUbfy8NbKS2/mOIrEjU/WouCESlbVnaY\nZvQdAUBpxMdXLT7cteuezqS6Xw3tXXFaT4Vjdb8apkoGExhxecmKlu/9adXgiXCKUzRZPeBf\nETumSh3KTCh2lUvcrti6QvcPstb5l4x+H/iR+bt8RJLOsM7pGOPuBQBKydHxafGhl5e9zsTB\nxeGQU4jO8JBTiMxeFxl/5oZJr8ORnJ2jXeS5BQ0Lbzipc1oWXNJeNFkZUOwqF+cqLsWHSmFr\n9CsPchKSiw89VZnG3QsAlFKXLrrFTqFIHTHCv/iaTY8uPW4TpP3xuE1Q06NLTRvOjPZ/ueOs\ndbP6bQNe6BB4TRGw9b0VUieCkVnehYRqtTohISE+Pj4rK0sI4e7uHhAQ4OPjI3Uuy/BC+0YX\nrRo2U/9ZdHjCsVUfayNX/IDwDmKv7vCme/3Wxt0NAJTOmjUdzp2L+fPPDpofFYrUr7666+PT\nsviafkH1/fJj9366OeXE1RrBgb1nyuf64Junrjeb+o63+PtfvBupb3h/9/6plxq2G657kBKW\ny5KK3ePHj+fOnbt69eqUlBSdRXXr1h0zZszkyZMdHXWvjYCO5K++qjFlTE3xUPPjI+H5qIrX\n/i93GPfpysERoRsmhQ17tEM7yRbOtirlz3UjfCYP6zyxtxH3BQAGKRRW16512Lbt+p49D6pX\ntx0/PlBvq9OSU5/TOjp5xWjxP6dT3ETWlX+uoNjJiZVarZY6Q6ncv38/JCQkISEhICAgJCTE\n19fX2dlZCJGZmXnz5s0jR44kJSU1b9788OHDnp6ext310qVLx44dm5WV5eKi5zymJbp3JXH/\nmIUv/b69sfq6ZlIgrH8OfCvyyg9G3ItKqVrVcZr/2SNVCjJrqR9WFY/+ngub1R0/HH1krhH3\nBQAwaFWd1yPurdUZbnPtNTCz2BkWlEipVNrb2x8/fjw4OFjqLLos5ojdjBkzEhMTN23aNGSI\nnn+LKigoWLp06YQJE2bPnr1gwQLzx7MstRvXsXKw17Y6IYS1KIi4uixqYd/O7/Yy1l5s7Gwi\nf58nhFhV+7WIpHX/nQtV+NEF8WdG12+j5+oWAICJFAT4Fbt9TmTUqiNFFpiKxdw8sWfPnpEj\nR+ptdUIIa2vrcePGDR06dNu2bWYOZqHcz8bqTGyE6taqQ6bYV6MHl3UmTuLJqe/3mWJfAIBn\n6bH4nXgr36KTh6Jqm4XjpcoDU7CYYpeWltagQYOS1wkMDHzw4IF58lg6RaHu61aEEEKlMsW+\nCvX9z8xK35t8AACm493IO2X16oP27ZXCLl/YHrcJOj9vhQW9GBOlYTHFztvb+8KFCyWvExcX\n5+3tbZ48lu5Rk2bFh95DQk2xrz9rNdGZ5AjndhO4f0KPzMy8/v2PeHmdqV371OuvxyiVBVIn\nAiArL73WoVtuTGFWRl7ao5D82G6T+0mdCEZmMcUuLCxs8+bN8+fPz8vLK740Jydn1qxZO3fu\nDA8PN382S/T64blHbNsVnaz2HtFz+kBT7OvVE9+eVTTV/pgvbDd1/sAvqL4Rd/HHvvObPPtf\nUjQ8bdNiZeN3sh9lG3HjZpObq/Lx+WvXrtAHD9okJbVbu7aDr29sYaFl3N4EwII4uDi46Hus\nKWTAYu6KTU9P79Kly7lz51xdXdu2bevj4+Pi4qJWq7Ozs2/fvn369OknT5506NBh7969Rr93\nVX53xWqolKrVvT51PndBZWtn3b9z+LJ3TLev3Ozc9f0/t790Nc/FrcFHwzq+1c2IG7956rrj\nSx29i9zDv9fxld5Pooy4C/OIjDy2cmV7neEnn5yZNauNJHkAAHpxV6wReHh4nDx5ctGiRatW\nrYqOji4o+O8pKltb26CgoMjIyMjISGtrawlDWhYbO5vRv31qnn05uDiYbl/HB82O+N8nM/V+\nenjX9HX9Ph9hoj2ayO+/6/m3rKionFmzzJ8FAGCRLKbYCSHs7OwmTZo0adKk3Nzcu3fvat48\n4ebmVrduXTs7u/Jt886dO927d8/Pzy9hnczMTCGEpRzafJZd09ambYoSVlbVhnXp+9lwqeMY\nU52H8cWHqQfPCksrdi4u+u5oESI3V+XgYEn/VwUASMUi/2nh4OAQEBAghFAqlRcuXLh79269\nevX8/PzKsalatWp9/PHHT5/qeTm01tGjR9euXWtlZcF3ca71Cn/twaa/f5i7fPXK3SOLPaNS\nErFbfv/j620iN897SGi5r/BLt/cQSt2hTe3qzxvO7IYPdz9zRnd49GgnR8fcli2PR0W18/CQ\n1WvIAQDGp7YQc+bMiYqKKjpZsmRJ0ZdMBAUFxcXFmWLXS5YsEUJkZWWZYuNmsGHMD2ohdP6z\nZeJyqXOplwd/9FQ4aCOtqzawfNtZEz5f57dLEVVv/P6XcdOaxyuvHBZCVexvl1oIdbNmR6RO\nBwBQq9VqzX2cx48flzqIHhZzV+yMGTP279+v/XHPnj1jx4598uTJgAED3n777ZCQkLNnz3bq\n1OnmzZsShqyY8vYdLz7M2nnU/EmKOrHqyGsnFjiIXO1keOq2Vf2/KMemXtvwj5X+Y5Ti79Px\n94TXkXFfNGgXYJyg5hUV1WnfvjsjR8YoFKk6iy5efCkzU88t4QAAaFlMsdMxadIkd3f3uLi4\nbdu2LVmy5NixY1u3bs3MzJw7lzeQ6lLoe+yw3qE5XVu8x17o1hTHIyfKt7XR15ddP3hm7bBv\ntoz7d96Z45lxN9bVHLKiybgrUZeeO6m59ezp9+9/v1xYWPyVx3anTt2XIBAAwHJY5DV2Dx8+\nvH79+vTp0wMDA7XDgQMH9u/f/8CBAxIGq5jUIa3Eto06Q5tOrSUJ81/ZT4rP7PNziw9LqUnX\nF5t0ffFK1CVF206R6rtCCJEiMrus2T7puwHfvFHuzUrCwcHG1vZWfn69/x3nvfwyz98GAJTE\nIo/Y5ebmCiGKtjqNpk2bpqSkSJGoQhu59cNfnLoWnexw6TFizftS5dGo9urLxYepAbp/T8vq\nZt9J9TStTgghhJvIavntjMIC/XebVmSDBt3RmQQF/e7iUs67vwEAlYRFFjtvb293d/fExESd\neVJSkqurqySRKrg+mftX9Z27ybPfJs9+q/p/EZb1a5m+XlhQGP3D/i0T2gim0gAAIABJREFU\nfrx25IqxIvX74rXN7q8WnZxVNB188LPn3Gy7J+d1JvVEYuyW359zs+a3fn3HAQOOKBQPhRBW\nVpnBwdHR0XqqMIDKQPm02J3/MLGHt1JWvDRlrVf4iubvxp+5IXWcMrCkU7F37tyJjY318PDw\n8PAYN27c8uXLJ06c6OTkpFl67dq1jRs3du7c2UR7T72duv/fmwpy81+e0MunWV2D62+Z8GPO\nrqNCYeU2qPOAr0eZKFUpKawVEbuml++7pzeesHrtnU4FfwghVIts1tYcOPzeeoW1Ef6VYFDa\nzp/6fFbl2DGbgvxk/yaDoz53q+72nNtUCD2PG1TllfScwgpr27ZQIcTt2xm+vu5CdJI6DgBz\ne5z06Jc27/ZMOlBVPL5s1SBu0JjXN0+ROlSlELfzTLWwsEiRJIQQD8Sjtmv3fvrv3jMGS52r\ndKS+Lbe09IbfsmWLZunatWudnZ0VCsXp06eNvuslS5b0Eq2TRXXNYycyhOuK9lNL/sr6KmFF\nn1Sx2ivc6KnMo0BVEKtoqvPgjeXN35U61zPtceikkzZReBWoCqTOBQBltsWtt84faOtHfy91\nqErhgH17nb/yl6xeKLpCRX7cicUcsVu5cmV6ERkZGenp6drn2KWnp3t4eGzYsKFNG5O8VTNM\nONYUDzWf3UTW68e+3vNJyz6fDNW78vpRC4c/2lF08nryxq0Tuw/6LjLhbPzhCUsUD1KtWzQM\nXzvJzrGiXzJ1cvXRkELdG0ubXToiSZjSqLVxXlL/vtr3xj4VjsfGzAw3xvFFADKgUhWOGXP8\n11/tlUrbpk0z1q8Pql27gl7Ac+3IlUGZe3WG3mtWiRXjJclTeaiUqpfydK/qaaL+6/qJvwKC\nX5AkUplYTLF74403SlgaERExduxYhcJU//x+S8QU/dFW5D9atlM8o9gVHNTzzI6sXUd3ONh2\nmPd+pHgkhBAJ4rzLqhqXD3o3qtD3Od6P1XNhgVeB7iPWirp78Y5n7SouVVxMFqokLfu1Trp6\ndsWQz10T7+R4VG329djwge0kSQKgAgoMPHHjRgfN55gYUb/+rTt3FDVrOkubSq9Lm080Kjb0\nz9e9rQpGV1hQqPeqnvxcy7jSUSZHMlxcXEzX6vRyznr8rEVWhXruwVQUFrScN72qptUJIYRo\nUXglJnicScIZT8uRoWqh+y61a3b63962IXLRVUWAz4u+DlU9f3UIjdsVa/qAeng38o68+P2Q\nx7veSFgZRKsr4tSppBYtjlStGufnd/y77y5IHQcwt5UrL9+40b7oRKms9/rrxV7kVzE06Na8\n+PC2dS3zJ6ls7Bztztg21RnesKrXuLPusGKSSbEzv3Tf+s9apO6g5xFxBb51fIXubbxt0nUP\n9lY0DdoFrKs5pOhEKeyU0yYWX/Pg/F1hKycHqm8IIWyEqmfeUcWAiMyHmSVvf+3wbzdUHbDJ\ns/9PPT814kNJ0pPTc7Nzn2Q8WfnKjLVe4SsbvW2JN8Ya14EDt15+2fXChdBHj1reuhXy3nvN\nIyJiDH8NkJFff037/+x9d1wUV/f+na30jqKiYMMgKhp7xxKNGkWNxhZrjLHEWGLeaKIxMTEx\nCb/41VeTqO8uHZEidgXLLk0QEAREBEEQ6UhzKS67y/z+GB2He2crS0vm+Zw/YObOvWdmZ+6c\nOfec56AbHz40an9NNMEI99EiHpwL/3jSnA5R5t8G7ukjL4A1+W89ME7f9X3HqaMlOjrIrwvg\n77//PgGmUIMoczDHkuwSFYdcMJ5FbR9k/sGNI2Fo+c9CYNduZ6EzGiWNguFfpLAGF4Put3gT\nLn0bQNss0ModPcHAjX+q6PmcxQJq45v8iYJhnwdaugsHbHxw5b5u2p7f7XWfNUQBWK8AvwaY\nkZ03AEPfpR669fnPgJ1dPPL71L//vsjQMJPNLraziw8KyupoHRkwaFts2xaLVmHu3z+6o/VS\niuzYrKuG0whFJcBY4LylozX6F+FpUq7wnc9CzOd59l2PvpI6c/IEY9ipx99//20GTL17LE9j\nvZOJDQi0cs8UZ6g9ymfxrwHWi/1tPvRfeRTHcUmlhGpnEHLZcHrbq99OiOSOQQ07wchdytoH\nbztDU+j+jdQB45AvBNrqEHXmVh0wVtZnJbCsKqps3VkqxcW9fnd440uBbSrLWTDs80ZJYxsN\npDNYrDLl1/u1nXfpUk5Hq8mAQRsiKakEwyTQnf/ll3EdrZcaFKQ9izpzq76mvqMVYfAWjGHX\ntfH3338DACQSSSv78ZpzSA7Y5HRSBmySL+ifnKWjoK3HzrPfetVWRh7WW1sd/Lp/pLrPi/v8\nW3eW9Lh84KwU8KgD+XVb2hYDtQY83lN1hh3u4NAZJykGDPSIr76Kw7DaN/e8fPRocUdrxKBL\nojMbdkyMXfth7bUDd34/H2C75IrRDK++6+uT7o1wV0/OUldV5znjOx/7j4Ujduix8IPeYfGf\ndVLAp25JYznP+XmVsvY4R01GtiP+PNZLrJUO3auLVDdolsm16lBD8H89wQMtsqVWlofk3nvS\nFmPpjKFD1SfTlZZ2bwdNGDDoQPz227iHD5t27ozbsCHm6tVnCQlTO1ojBgz0jC5Dd/LPwHt7\nFoA9CzRv/zQxRzp2zno8BwAAikCtm1foF0c/PLahrfRrBWZ/vTDwsccI7/8bhOcqAPs2f4Lt\nuf+nopKEzdJp4PAZ1X1Wff4TWOemuQ7lZnZAORPLS2A6cdv7mvemOd5pyoO2YABP8RH3Hzuw\nLYbTDZ9/brthQx2Ov6ahwTAJjsP0XSYmte2uFwMG7Y3Bg22OHrXpaC0YMGgrMB67To2UmTuI\nPFMC5uDlmOMH5E1t4nZqPZZ7fj6oOScvKbe+vGrWqyjV/sj5P63wclirusP59be1clLa7l37\nChjQ7pIBbtjc/9g6dtO8N81RwrZFN/YY3YmsurKy+k2bTEmrDgCA46YcDpymvWBBQ/vqxYAB\nAwYM9AzGsOvUGPUyDdrSGxTH+XTewg8AgL4j+2lY8nVdvte1H4I8B2z0clzns+BnBWCjbR4G\nxWo+9Htfzg9b81su5kj8G80Z5eW4LshygXfv1XGnrq69ul/zrrTCw6Hwak4Sa+j41VPaaDgd\nIBA8lsl6QxttbIoMDbPe/CebMEEsFE4CDBjohB9/TDI1zWCx6vn8fHf3yFev4O/PkpK6WbPE\nPXrcGzgw5scfO4bksp3xMCI14dxdPRI5tR1qSmuEI3edN5vrb7fs8v6zHa0Og9aho4P8ugD0\nlTyhA4qAHRrifvvY1fbXpB0Qz3ZFTzYxWJeEtazoTNV8NPqFQq7wtVsmAxxC53j2cN3UxnG8\noqJ+0SJx//7RY8aIAwMf60vD1auj0FQJC4sUmUwRFJTl4ZGckVGhr7EY/Atx+HASdHeNHdsi\nKSE/v4bLfUZtMHWqqIOUbQ9cPRScynJ+nQcG7M+u+29Ha6QKJdklj7AB5G8jB2zBiB0drVSr\nUFVUeS8wtk3ZCTpz8gRj2KlHBxp2l41mQG/jCmDdCak09ALhlG+gk43kjulopbTAFc/4Bean\nB7PuslmlffvGJCQUa9tDTk4Vl5tPuQDyTz7RD8PW6dPpqGE3bFikXjpnwMDMLA25weSlpXVk\ng7FjxWiD6OjnHahz2yEnPrsYdG/BJASMIk9FdLReSuHTYwX027wC/Izb6R2tly4oyiwKMZtL\nEFBIgLHQ6VOFXNEWA3Vmw45Ziu3U6B30Wwl4m6jYBHg3lu4zMKEPI+vqWB952HPQpnrwumhj\nOH9yt5ueHauS5igvr1/8me2l2k8fNY9XNHfPy5s4cWJTSUmdVp0sWpQukzlQNrAFghHPn6up\n3qEJPvnExcamxeIXhr08fpy+NBwDBtpCInFAtrEjIt4mYj9+bIE2CA193qZaQcjOrrp5M7+p\nSdHWA0V97dUDlFG3GIGGvJ9823pcneFUnglt4QNpyunwDlGmlUgate7Dl9fYQAEAMAH167PP\neI3d09FKtTcYw65Tw3Xeu80ZSZ7Om8NMZvv0XHnvzLWPg77saKXaEOsfn1KUF985dvVpwpPZ\nr6LemTq4ozXSFP/5T3JTU4sqczKZw+7dyVp1kpNjh2wzDgl52jrVAACAxcIePBg0alQkh/Mc\nw6ptbRODgkqnToWj7hgw0A18fim6ceTIt0lFPJ4MbWBh0ba0DDExhYMGxRgZZZuZpfP5eYMG\nWc2a5WhoWL11qxaRuzqAlQ+nJQEALKrK0I2dBDKM5odg8Xntr0krUfSocH79LWjj6ORrHaJM\nB4KhO+ns6DXYfv2jvzpai/aDma3Z9C/mkv/Km+RXvg2oSc/vMW3Y7K8X6nGgx5GPHl9J6us2\nxHXeu63vLS2NJj764UPtOmGxaHwJfL5+vr569TJNTCSTPNQTKDJgoDnee6/k8mUn6hZb26TB\ng99WzZ40qT4srMUhGFa7cmX/tlPp7t2iKVNMcRzOB2putvnrLwtn59Tt213bauzBA8AzeFuV\nXef9jsrpM3TS0xYefQkwGffFvI7SR2ekX0zsBXBoYz+cxs7+Z4Px2DHovEi5mPjQ0HWhx9p1\n4Qdn711002By5XPlPHUa42XFy1CLD5zchi70WOv6wchrhtOKHrX2ye/Th2Zj797wFKMaQ4aU\nQ1swrHrJkjZ8+TFgoBecPz95zJhIAF675bp1SxSLHakNAgMn2dvHk/9iWN3evY8HDrRqO5XW\nr3+K4+ZKdnKOHdMiTKJZ0Swc/59HLKd6zCSVPdh77o+q239waksmNoC6pQJYj/n7C81HbGcs\njv+/GM5bK/wVMDg/9+u+I/upOKRzYuSKiSi7QjbLsSN06VB0dJBfF0AHJk/8yxHDGQmF9AbY\nLG59t752y6BuLxjPamWfkZEFSA3KuoiIPK06qaioNzF5SA253r//XisVY8Cg3ZCfX+PllaEi\nbejkyVR3d/H69dGpqWVtrYyhYaaK6nnm5qmadyVw2QodL5x+QPUhyRcTLxtOfwlMGoGBiDu2\n81MZKOQK3yW/efVeLXDZei+wMyYEaIiz1ougH8tz9g9tMVBnTp7AcFw7p8K/EKdOndq8ebNE\nIjExMVHfmoGekHf/qeOoAVhLv3oh6GGPF7ey51Ksux1o4RuTAW5j+QsN6feU4eef73/3XQ+F\noicAgM0u3b//+fffa73i2dSk2Ls34d49qa0ttm/fwLFje7ZGJQYM/rWwsblfWTlS2V5n5+hH\njyZr0k+zovklx8oCtCjKkos59m+G683QHitvkvMMu16wWtfFy4qXYe9u+6DwmjWoeoo5RE5Z\ntV58uC0Gampq4vP5sbGxEyZMaIv+WwMmxo5BJ0VhSl5fJFrCGtTIm+Qcnqr7Nmy3Fy4IMn9V\nW2LdZ4TPPpeZw6h7X1a87IbUHeMCWVp05sjFY1uj8DffjNy5U3btWjaOgzlzHE1M0EwI9eDx\n2H/8Mb41ajBgwAAA8P77Df7+ynY2/vJLDw37Sb2aPALApfb64c+qi6sse6pZSmaxWZpbdaVP\nSm9P+mJ6eZQlqE3hDC7buWPh72s0PJYBCTNbs7XPfQEANaU1/ewsut5ysj7AeOzUg/HYdQia\nGpteGdmYAQl1YwLbdYz8gYqjhOP/syH+d/LfamDxJPDqmGUtvqiyWf2d8BapprXAzFRezWIz\nIacMGPxD0NyMjxgRnZY2iQglx7A6AHAcNzA1zfrtN3zz5qEa9lNXVce1tuEDKXVjGbDtjsMR\nsa3SVtF809httjSa3PIKGER7BL335Xw9jsJAj+jMHjvmTcagk4JnyAsZt5m6RQ44xbt2qzik\nurhqefxJ6hZLUFOx/gAAwH/F0Vv8Semsdy4ZvxczcCZ0YOiQ1YxVx4DBPwksFpaaOuXOncIv\nv4z38EipquI0N5tKpayXL4dobtUBAEysTK6aToc23uwxQ6/Kgtv/d5Vq1QEADMCruu9PKmvP\ngIEKMEuxDDovNsT9FvBxz27BIXayinzD3pxvty78ZrGK9jF/hs8HcBn7YY2PhaO/3JD0B/Hv\n0IYsWTZX6LRpWE5c/+bnBaweyRMXrhP91FbnwIABg47DtGl9pk17m7LO49EUpFaLCfeFl4av\nnt9wGwN4M2CFWHyw8OEZ/ekIAABFN1PQjY4N/zqejk6I8F8vlNxJNXdxmHd4ZVcJl2QMOwY0\n8F9xtFvY+W6yyjzD3ma/7Jy+fU5HabLSbyfw2wkAGKJBYzN7a3RjPWb0UdIp6hYukDk/TRql\nSAMAWALQZmRWXR5PnlTl5ta6ufU2MFA6Ubx40bBtW9LDh6Bbt+bvvutHfYkyYPDPgN1AuwX1\nNx9HPnpyM9XFffRHoweoP0ZLWL07ACCFHkr43UbofSQGGqO6uCqpn/tsaQwAAESAtGO/yYI9\nWxmK3U7o4KzcroB/DN3JjSNhZ60WXjeY6mX/caY4Q1kzwYgdUNHAq4eC9aVDfEBMiNncVJaz\nmDtWOPUb/VbxkzZIn2J9oFz3ULM5KNtBHTDWZOja8toXBRV61LCrICGh2MYmkbhaGFazYgV9\nVdnMzBdcbgH1Zvn2W4afhQEDrSGplKSx3oGmKf+VRztar381/G2XQL/IXc675N7OTHfCGHbq\n8c8w7Lzm/UTURSakCljEeovRZpJKSQMwhO7mSO4YvegQHxBTA8yoPfv2WK6XnklcOXiOWn47\nijM6+UICatjlAXvV/USeiojkjpEDtgKw7rFd9Wjadn5IpXITk3Tomu3bF4+2HDgwGmqGYZUS\nibT9dWbAoLOhLLdMMHhLmPEsv25LNZlA4vyiYt8wd1YDc8Ho3e2g5D8YWdGZAWuOh3whqCqq\n1K2HZ6AX+u7Iic8m9jKGXdfGP8CwkzZIq4AFdIPe4E9GW0b8fhG9lauBuV7UOG/6PtSzArBS\nr6XopXMSJdklXnMOCYZ+HrT5FOGWi2OPgMb167ZU2eHJFxKCzT94BfjU9i+Ald717LQICspC\nCV27d09AW7Z0172WgIDM9teZAYNOhdyEJ3lYb/KpkAO2cNJeTQ5MD39w+/g1SWUXft10Bghc\ntpIeiuegR/DW09r2oJAr6oER+jYU/xVONOjMhh2TCdjxSLmY6PfR/7u0z7+uSosqN1oh5n+3\nLUENtHGk9BHasrsLTYzUC8xSL2o41cH17FmgOd1HpJfOSdgNtFt77cCGtP8u/WsTkevKCfwz\njeVMNrjBnzIv9TTxd9Bnp7z6rvd857NbR68CAOL9o/stnLmk9grEbmANqu7v+rdU7L1/vxrd\nWFNDew/QVMhlsbCWB76aOVNsZPSYxyvo2zc2MvK5frRkwKATI3H2Hkf87a3OBoplMcc1KV04\nZJbr9O1zTKwYai3dEbjh5IaMPw1BI/GvPShx+3Pfk7vZWnXCYrNS2YOgjRJgMn6tm16UbFMw\nhl1HolnRHNBt6bCF4z8O3rPgyMfFNq43PS61xUAm3WhqJjYAA3TjsDnD77PgRIV4u3F6UaOK\nTaOG+UBNmUJ1xqgl496pexC228t7zqGbHpfefxVpYWfRrGi+YDL7o9Ob1+V7rc86PW23u3DI\ntvJNh8zBS9pOzEr+LRlqbm7d0I22tjRVevv1K4C2sFgv5s9vwQnq4vLg9m23xsZ3ZLI++fkT\np083Tkkp06O2DP4NCAnJnjFDPGZM5FdfxTc3tyv3anVx1bVDwdd+DKkphb+NVcClJhPaYgQa\n4k5e16tqDOjBDoPzUGxA5d3DQdr2U/HVlzLApW4JHrO5ayTGdrTLsAug7ZZiBWP2QG7eJ5hj\nbXmt3gdSyBXZWF9orCCL+bSNY73FDzEnSjha7wT2sBv8yV7zfmqlGoLhX0A6PMX6tMX5agLh\n9AOQMk2AWwB6or53QoQDN3aInh2Cnj3joWtz5kw62iwnp4rHe0ppVn/oUCK1gVD4EL2WI0fS\nBHcy+JcjJ6dqx467S5dGonfasmWRAMjI+8fKKrmxUabf0X//PblHj3gjo0wHh1hqLIHvkt9K\nQDdi4CJgp3k2QzLLBZ1Dwr7y0a/a7YzE4DiB63ZPx3X+q47qN+9NvwjnT0YvvsB1uw5d3TgS\ndtFoZhrrnQjeRP9VLX79zrwUyxh26tF2hp2YOxa9/y4fOKv3gXAcv3oouBTYkqMks1wKM55T\nGxRmPPdd8pvQbb/o5I3HkY+uGbiVAlsFYFF183RY2xodFHLFOcsFVKtO86SExOA4/5VHr/98\nXibVYk5XkdMaYjYXvfj5mD2tVVcFLJIv0ASZ/VNRXCwZMULMYlUC0GRk9OjXX+8ra1lb+2r9\n+ujhw8Vz5ojj4oqgvatXR6GX09IyuY3VZ9DF4OGRjGGV5B1ibx8nlcqJXXFxRQBIoVtowQJ9\nfht89llMy/5lJ06k4jgedeYWFGUlAcZxflGa9OnTcyV031cA6y6dYu8190dqXt0d7rj6mvqO\nVooeXn3WoHN4yBcC/Y7CGHZdG21n2FEdY6T4LfPQ+0AECjOeC6d+Ixy40XfJb9KGFqmLQZtP\nlQEbUocXwJLWvpEDtgqeFA0RLbjjNe+noM2nqkuqNWnfKGkMMZ/XDDBCh0TW0KRQmgxNKqqK\nKn16rKgG5jgAeVhvodt+tE2Y8Sz0BG/yJqIbU1nOF/f563KqXR/k+1UTlJbWrVkTNXGiaO3a\nqLKyOhzHDx5MQO+jvn1j2kxfBvpEQUHt6NFiA4NsHi93yJDIjIw2sUtKS+tYrHLoJpk377Xp\ntn17LHoLde+uN1YdhaKZalMSYmycgeO40OlTGsePy1ZNun1RUHGP7Uq1CCF/T9dCbsKTl8AE\nuhRCp087Wi965CY8KQR2VFUj+JP07mJkDLuuDR0Mu/O7PD0d1wn7bbj0bYCqZiazoUelGWDt\n7xkqzHhOtepUS8Ca4+2snme/9ZAO8ezhqg8JMv8AOgRdRxaM3o2e3aVvAxLYw6hbqoBF8sVE\n2lEYUBEensdml5JXjs0uvnPnWUFBLZtdAl3m/fsZrrsugPr6JhOTFivpPF5eaWmd3gc6duwB\nOtNYWr5OQt+2jcaw69ZNb5NkZCRNZjcA0sZG2VnrRegOFQn1EGRSmc+iI1591ghG7OjqOfX+\nq46il0LMHdvReilF6rWUIIv5j7AB91lDhP0/0ZnxRAUYw65rQ1vDDpoOvO1XKWsZ6y2GXP1P\nsd7tH3N2dt1/NbTqcACuHDzXzurR+jUfXFG6OFiQ9ox075GSyB4GNWuUNEZyRlPb+Notk1RK\nCD8fVS4bzWjjU/wnwNw8lfbdfOZMOoUVpXHuXCbArmtg16676ASwZAk9VXVrsH//PXQgI6NH\nxN7IyAIAmqC9tHdRaGj29OmikSPFO3felck0dc8UFNQC0Az1z2KV43Qx0DgAwsn79HXiXQg+\ni46gl4LK1vsvBGPYdW1oZdjRftmE7fGmbVxdUk1G5pLSDLBnoJfwnc8aJY16PQ+l8Jz9g4ZW\nXR6w18ruLMst8+mxIh/YS4BxFGe0bguaL4CVVvbl5QNn0fYywCGJJUlIG6TCqd8Em887a73o\n7PoTOI7fOBKGHlsI7HRQu32QmloWFvakwzmBKysbqOHtb6SptvYVjuO1ta+EwodHjtzPzHzR\nsXoy0BwTJojQOcDJKVrvAyUnlwIghwZycXlrQS5YIKbuMjNLQ2/4VauiqHeghcUDzR8KS8tk\naHRn5ygcx8vzyrKwftQdGdjAtvD9qIakUiJ4d+cF41nnLBYErD7WzqMTSL2W0gS40N3g3XNl\nhyjTScAYdl0bWhl2vt2X0Xzk9dtA25jWBCHFy/5jvZ6HUsR4ijSx6gpAT20TO64ZuFF7aACG\nt49d1VY9yK+GA9AEuCrCkHMTntDqf4/tKpzyze3j11SNdSoCPTAXc9BWZ90QH180caLI0TF2\n8mRRUlKJ6sZxcUVWVq9fSBj2Ul+uFN3CqoqLJQAokCsnJyLtGHRFLF0aiT5GkyaJoGaxsYXR\n0c8ViubWjDVjRgsjks0uTU8vpzYQCh+OGycaMiTys89i0LjPhIRiAF6hxpmGfrv4+CJDw0zy\nQGvr++SK88ObqcHm8/KAfR6wD7KY3/oIY21RW157nzWEemI+HWROCVy2UtV4hA0oyVYzR/2z\nwRh2XRvaeeyQ6nK48mTSwI1/qjCkGoFBW6cdleeVEVkUkNpVwKLyTf5ENTA/a73If9VRbVO6\nbv5xBT2pUNM52ip5ca8f9LGozFAmcdlohrKrKgfsQCt3ZYG0MqkMLSMTaOmurc46QCB4CEA9\nOSyG1fn7Ky3h0NgoMzbOgE7uq6/iWqlDa8KqDA0fQ/oYGz9qpT4MOhCRkQUYVgd9UlHvyb/+\nSuPxcoldXG7+H3+0Kozs4MGEPn1ibWySxo8XZWdr5xWjXTUGADcxeahhV1Kp/PjxB5s3x3h5\ntbfpphpC583oian4PL584Kxg+BfCyfvSwx/oXZmwPd4BNovDTGYLXLe3v+eys4Ex7Lo2tDLs\nvOcfRp/DwI1/0jbOTXiC+repEnXmll5P5S38Vx7NxAYQ5uN5k9mPozOF0w+E8yffZY/w6/5R\nVnRmSXbJ+V2eIV8IdP4so13hTWa56NDV5QNnw/mTn2J94tgjhG77IbNMIVd4vncwnj38Oegh\n4o4N3nr6keghGmbXwjRUXt4nbI93JSUpOIU1mOCFCd56WjBkm9Btf27CEx1OQS0MDOBCXsbG\nD5U1DgyErSigj4hy2hekuXmqs3PU9u2xqr0yXl4ZVDsAwyS0hml09PMBA6L5/BxT0/SFC8X1\n9U2t1JlB22H//ntkviqG1Wza9DadOSmpBMOqqPcJhr2MjCzoED137qQ37ADAHRw643tXc1w3\nmIqelWDcV2hLhVxBpXCSAOPWM48yUAHGsOva0MqwU8gVVwynUx/CYPN5KtoLBm9RZnzIAKeN\nvoou7vOHDMpoziit+OE0GmWvH3pSVw3c9DsKjuOCIdugUc6u+y9htiqT6wZTVXSYm/BEMHaP\np8Nab/dfpA1SSaXkFm8CeWwlsAzafEq/p0AbwQ2ArLKygbb93r3w0Sq3AAAgAElEQVTx6Gnx\n+TpanAUFtcXFElxJWBUp3bvfU23bJSWVTJ4s6t377pQpouTkUrRBQkIxRC3Rv7/+Y7YY6BFl\nZXUnTqR6eCQXFLQIrqVdqG23zJgrV3LHjRP17x+9YIG4tLSOluvujblZ28pl4o7FRaOZNN+l\n0w6gLYWT9kLNJMD44c3U9tf5XwLGsOva0DYrViFXeM8/HGjpftZqoSakdGfXn7hgPOsJ5gg9\nludN32+d4kpxgY7CTXOuYA0hqZSgCa2+S/XM0idtkNYBY2iUZJaL3zIPFYbdA5az5+wfrv98\nXpMhPPvCfCulwFa/XKMVFfVo/DgAr5QFgIeH56GnZW9/V9txfXweGRu/Xns1NU0fN06s/Jrh\nAODbtqmaxTZsiH5DbtIwdGgkYSxSMWwYjTUQFtYmHlAGbYqRI2lulcGD9Z8zi+LLL+OoebIc\nTlF6evmSJZF0TxAOgIzI4OmiQM21RmCQGEwTdHG5pUOBEMZp13ZgDLuujbYjKKZCJpV591wp\nBTwcgGaAhZrOaaPQ1Ic3UzOwgegU4PneQb2PFeMpIlk6XwITwfAv9D5E1Jlb6LlIAU8mlQVt\nPnWbN15FlTAcgNu88WW5ZaqHoBKNkqKiOpCv76OePeN4vFxLy+RduzQ1tszMYLoQKyullC44\njtvbx0EnrW14UHJyKYvVwn/GYr2gxvlp/uauqKjv1w+i76dZBTMzS0P73LyZ4Svueli2jMZG\nX7y4zT12tbWvMKwGGrd//xgcx319HwHwEtplZKQ0ULVLQCFXUL/DpYAnmPA1bcvbvPHoE/vv\nJGdpHzCGXdeGfg279PAHfss8gjafonX5VBVVik7eKMqESzPpBbHe4rucd5W9tNuOoC4xOO7G\nkTD0fL0X/HyDP/ke2zXQyh2lZY7zi/JfefTmH1dUd16Y8RwNp8sH9tQ2ATaLVdh25ywXqB4i\nDRuEHkXQo6A4fTodot2aP1+jt114eB6Vy5fDKVIdsVRaWjdmjJjNLgXglalp+tGjWoeuQywS\nhLi4RKFlAEhxdaUx7IqLJWQQPSRQUm2vXnFomyNHVNmvDDobJBKpq2skym7DZhfl5FS19eg+\nPo/QW4jLff2k7NsX39Jv13Ty5D9hLTJku0A4cKNg+Bex3konE0/HdegTKDp5oz31/FeBMey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Q2bBTyBWCYZ8TRegLQE/BsM91zid6mpQb\nRSmuEMUZrYzxslHSiBJm4nQ8cJrAr9tSZdPwOcsF5GLEM9DLb5lHfU39He44soEU8AROm4hJ\n4R7bFe1BOP0AMUqAtaparjgA1wzcNK94FrJdcMF4VgxnZLD5PLSAWAMwJLqiDaoTTtqromfP\nvvBKrhywS0A34m8FYPl3a/EJK5XKP/hArNb1BQBOrRJLCuESk8kUqLsLANzAIHvv3ngcx7t1\nS1DRM+QFOXEC5jchUyUSEoq53DyK4aVm+czCQtPX8IULT5R1YmDwpD25bRm0BkuW0Cy5kjZc\nfn5N796k5dc0apSYSmhXW/tqyJDIN/EGctp6xHfuaJ2EPmOGiNqDtfV9YtC4uKLhw8XW1kkD\nBkRTq5vU1zdZWiZTDlGYmaV99FGkipBWHMdDzeag967njO9CTefc5E30tl+lrMCgflFbXkvO\nNqT42i2jtqGtix3hcUmT/pVVJyJKk9Gyyt/gT26TU201aEux6xdSqbQ/6MMYdl0VOht2Auct\n0GNAZB7ojOuHQ73m/XT9cKiKNrXltdDHJQ7AK8DXLYuitrw2hM48wgEQTv0Gx/GnSbnJFxLI\n9gq5wn/lUS+HNQKXrXF+b4NszlnC5Vap083TpFyU1g4e7g3LnWoIJ+9T3Q9p2AVZzEf3qi71\nKOKOVd053vITdsoUkbrmpKAuPdzAIPv77xOysippzT5C9uyJW7BAqS/E3ByuFIf64VisUmIX\naiCy2UXk6jBq523ZEqPJL4LjuFQqJ0nOUOnXT9N+GHQs6uuboFLIU6aIyL19+sD+vJkzRVAP\nxcWSsLAnxcWSpUthG9HUNF3b1OlLl3KgrxQA8GXLIi9dymm50ion79UPPkAfllfx8Wp8z6lK\nlhRIKQM2qdfaloJbJpUJ3faLuGOp/O3x7OGQBUON/Hs7Kbnt12SIstyyKmCBHi4DnKqiSs9Z\n36O74tnDcRwvyizydv9FMP4/qt9N7QOh234it68amPv0WNEa1j3VkEql1sCKMey6KlQYdiHb\nBYGW7heNZgpctqKfCGggmop684Gf/BlsPu+6wVThgI0l2SXaKpmb8CTYfF4tMKV313FGatsh\nFeG/XXgJTKkdNgDDcyora0GID4iBKD0vG82gNijPK7tsNEPF1BmrwSnU19SjRi0kkdwxROPb\nx69RKzziAERyRquOg4ngTVTdOQ7Adf4UonFjo4zW06ZEGtFXFHhtUUlU5DEYGGQ3NspsbBLR\nXUZGmQQ3MgmJREobq5eQUKxEW/n9+6UCwcPY2ML09PIePeJJlSAyC7XYuDGaWicXOndmQbar\nQCqVb9wY/c47USNGiKkrp6WldSgxNZebr6wfhaJ57FgxeTeam6fGxWlRuobAxx+jyRx4nz53\n0ccBw+qWLYvcufOutTUNtdDOnWrCPW/TFQ2CJNRsjrb6aw6FXHG9Zb7aI2yg71IPdL66TBf0\ncnbdfzUcyHfJb7RnF+FxKerMLXQ7EWpM9SNeMJ4FkR60J7zm/QRp2Bp+FtWQSqV2oBtj2HVV\nKDPsoOTtLKwfNX4/N+EJ7ROSmwBHn+BIIYenWB+t4gxkUhl1oRaVq4bTdDr1t7j0bUAh1iJv\ntAlwtaI4Fp28cdXA7TnokY45efZbT8st7rfMQ8wdC9E4v5nIBnj1Xh1iPg/Kk6AiwuMSeiDV\n3VgKbKmRcGF7vOPZw6WAVwksz1ksUFvPUTBkm9r5nfiExXH81q18Za3eJCu8FXv7uDlzVAQh\nSc3M4DC7NyKTSuUKRfPBgwmTJ4s++EB88GDCjh13T59OR+ONFIpmlL4LAEVpaV1lZQOtZQmt\nk+bn11y//lTbIk4SiVSFxw5QauYy6KK4dCmH9r5VHfSWnV154kRqRESebjSHKE8QALiDQyzd\nTU6Zt5CNEFkPCrXrAHgbM3R4L/gZHdFvGU2NMq+5P0LNCoGdVvUen2B94QniTanuQCt36vZy\nYH39pxB0uha4bKXtuSizqK3j5xKRPLxmgOnMM68a+Wl5R8FUxrDrqqA17B5cuY+S9Pr0WEE2\nUMgV1cAcalANzNEwuwdX7qN83ERYg4a4fOCs6kmn9aG+1SXVaAnXaM6oVnZLi0xxBnpBqJ5I\nKrMJFckXEtBzf4b1EjpvPmu9SDDsc9onXPPvy0ZJ402K0462pm2AzesksurqRmWprP36xZiY\nPCT/NTFJT0srw3H82LEHLi6RhoY0pMEzZ4r+/DMVdYpwOIXff58wfHhkjx73+vePtrRMwbBq\nAKSmpuknT9JklvXrFwP1wOfnEm9fY+MMaBeP91TDK6Ma/v6Zql+LfD7N1w6DLgSJRIrWuFNB\nIKKXerJXr+aiXyMffxzF4RSqM8Oo0gQ5tmnh03MlOSnl07F4JrGGtP6MlMGv+0foiN49V9I2\n9nRYS76b8rDeqsNLUAiGfg4NdNH4PWKXTCoTjP+PmDv2IcupAPSiXR3CAYjijIb6vPnHlbg3\nMc2pLGeqRyB462mh82bBuK/Sw+G4ER2AvnNxAC4fONv6nlGc23oaZ7Jiuy5oDTu0FAQOwF32\nCGob3x7LoQa+PZaj/fss/hXt6h7bVXMNocL2qPgt/0OTfmRSWZxf1PXDoeiy8vXDoWi31cBc\nkz51iHKAXJgoz/sVJdXY0NIXpKWlLwSsPubpsFbgsjVaeDu3ZWhgDTCjJurTFoEFAHd3FysU\nzSdOpG7YEO3iEslmFwPQzOU+W7MmCsfxESNoXHeuruLiYgklOP21oM4/ijSgxcHy82uMjGAz\na9QoMY7jPj6PWlaMeHXsWIupNiGh+PDhpICATE1yD6n4/fdk5UriAOAYVkU2jo0tPHEilWEw\n7nKYPFkE/axkXg6J/PwaF5dIDKsCoMnY+KFuabBUzJsnpi7xd++eIJMpBg+mSfJQInLNC2Ck\nhz/wX3X08oGzpTklhYibysthjVaaK+SKxOA4DT1YlxBWBJzgkFKh6sqj53d7EQsjWmUSKOQK\nT4e1RJhKM8DOm74POfxeFFQ8wgaouKYPWM7U9rkJT563ZAmtBuZJofHSBul1g6nkRgkw9l3y\nm+Z60iKZ5YLqQ7tKhiIxOM5vmcfVQ8EaEtOE7fPDGcOu64LWsAtYfQy9gcTcsdQ2kkqJf7cl\nxMdTE+D6d1tCy3uClkZFu1INWn4jQmSA49VHoxlHdPLGfdYQ4qhaYArVfnh4M5XGcACGwebz\nlLH4ZoozwkxmNwDDZoClsd4J3Pin5meE47j/qqMXjd+7wxt/ji7LQQ7YDzEnz77rIavx9vFr\n1DyMSM5o1SzHrYFgGPxpWwvMqJNIcjK91XXjRh7RYOpU+F24Zk3UZ5/BTjUAcKLOLJtdQjHL\n5DzeU9XvLSenKFTtvn3R/ptjYgqHDSPfkc0GBllUxgqZTDFsGJnSiBsZPbp1S2n4FBX+/pmT\nJ4tcXCKVB9jhAOAYVm9i8nDqVHH37mQCh8LJKUoi6bBgHQbaQiqVu7uLudx8AF4ZGmbt2gUH\nrikUzUj1vFcBAZmtHNfX99HUqaLRo8V798YTS7rFxRLloQs4APiQIZFDhkSOGyfSuYTx+V2e\n5RRWkdu88VrxSXnN+4mkDonijKbmmdEiG1kexQEI+UKg+qiqokrfHssJJ9ZTrI+GKRQEJJWS\nqDO3aOtM+C3zUDXpAHDOosUCkXDSXrSNcMBGlG+1GpirjYdRDcGEr6E+oWBuWkgbpFQKhRTW\n4PgA9Rld5QVlPwA3xrDrqqA17HITntS2zCfAARC+8xl6eG15bbTgjorHviDtGZqLJHTerLmG\nkkoJlLclAxxPx3XC6Qc05AevKqpE5w6oUiotPwgOQCMwoJaRINAoaYxr2f4V4F//+bzmJ0VC\ndcnty4jrrrqk2neph2D0brUTXytBWwzHf9VRsoFMpqAr//WKyBWQSuVELQqqcLn59fVN6Koo\nVZYsEZ85k56dXcliVaicYHFTU5qCs3w+TTiUpSXMxU/la3V3h52IRkbq/XYLF4pV23NqZdy4\nDisnykDvCAigWZHv379NcqIViuZff72/aJG4e/d76KA68KqgyE/J83zvoGDo5yHbtZtnwr7y\ngcJ4MrCBtDHHBGRSGbXEDiniv8JVDxRsPg86xHv+YQ2VDPlCeIs34QFrcKjpnKTQeOou1CCj\nShmwgRZVvXuuRJuFms25Q5eSErD6mIYaKoPAZSuRqCcH7BDzeZqU0xUOgGuI32cNUctNJpVK\nDYEhY9h1VShLnvBe8DOVp/sWb4LmXGsQ/Jb/QU3nvMGfrG1XicFxJBlHKbD1fO+gVofTUlNe\nMJ5FbZN8ISGRRV8NVoT4FwXDaOo9B5vP00orAgq5Ip+ustnby3UkTIdulaFR0iic9q2w3wZv\n919ULyJT69uS4jW7RXlZdDXW0fH1mywykjafoFkikRYXSyZOFBkbZxgZZaJMKEZGmfhrfjvY\nLlQ2FhWoDUeMi2xpTE0tGzo0ks/PablE+1quX4cj8CorGzZujJ44UfTxx1GBgY/REEMDg2xT\n03TViRRUYbOLW/VbMtASSUklkyeLHB1jJk0SJSQUh4U9cXCINTDItrFJ2rMHXlfFcfzChSfO\nzlFWVsnOzlEoFTaELVtoXNEcTsG4ceJFi9qqfHB2diWbXUQdcezYDv5aCEHsLRyAc5v+VnEI\nWpu7GWCqTZaCtGcoTVUCexht40ZJI3VRGAoikgM2VT2/5X+g+j/BHGM4I/26f4TWrkULjuMA\nCJ0+pfUUeC/4We0FVAuZVJZ8IUFzHyotnc29QDUWG1N5omtDBd1J8sVEwajdwn4bNM8nV4aM\n2+mC8f8ROG8J3nZG507yU/ISg+NUhwgIpx9Ix5wagUEW1k8wejfxXUL77MW1DBnEcVwmlaFZ\nVzgSbBfx+0U0s4S2Qw1xfpcn6h99O0dMOxDjKfJ0WBto5XitwrUAACAASURBVC4Yuas1xEXC\n6QeoKRFFoPvtY1eVNfbpsQJV5gHLmTqhFBdLqD4DW9tEkuCeNt6czW4RzkLr5ADgdW1WJSYa\nKTIPj2RUbZRCjJYtFgCcy1Wa2AuQOgEJCcVUiw3DXqKH9Ojx+tP/r7/SFi0Sqy1uAYCcYUJp\nN/j7Z7akf2uATPMPPhDjOF5WVhcamv30abWHR3LL3IUm1TFztAVIqDcMFNOpL+TkVI0fL7Ky\num9vfxddIG5/RHNGoecvGLtHxSFe9h9D7cPVMQNf+jYAHaUKWEDN8lPyQszmEh7BfGDvOfuH\nG0fCUIvwBbAkPVhVRZUPMSfq3npgpMJ9WJD2DKo5/gJYpV5LQWPQ5YBNZUVtN6C0zzgAajkf\nGMOua0NzguIrB89dNXB7hA24wxvvu5QmF73DgRpwBGcybbEa2lzaGE8R2vIp1ofaBsqKJyXU\nVFOqJ9QNninOEAzZloX1Q7v17LueulSRgzkqI4IvyiwSuG4PsF4scN6SFQ0H91z9IQjN0niE\nDVSmZEHas2egJ6qPcCDMpXz9+tPvv0+4ehUOH3F2hvkaDAyyraySR40Sp6eX4zheWPgSzYQl\nkw2Dg7NofWkA4CxW5aZN9ItcCkXzkCGRLbulpdBTvYqqgJhQ7Oxo1rwgIQ07ZacPCYfzPDPz\nhbLrz0C/MDZWa2dLR44Uv+GsbsawWqgBn6/KaSeRSA0NVeVHs9nF2ublaIg26lY3BFrSTI+q\nC0/X19QHm88jZ6c7vPHZsUozjgnkxGejo9xvmbqrkCtuItyc5yxpYppxAKhhZ4nBcRH8SUSa\ncBo2SK0zIurMLTF3rAxwFIAVzx5+9VAwjuOFGc9zMMcWM2f/T1T300ZAeQrlgK2WTZYx7Lo2\nNDTsQr4QQCQdgtG7VR/S/kALPBAMLAq5AmLflQBj2qwI716r0GceMgEj6Uj15ICt9htIIVcI\nRux4ivWRA3YO5oh+xaIZxE+x3miKOy0pZZxfFPXLrBqYX/0hiNpAWWWz5IuJyhQWjNqFtm8C\nXGrqyb598b1737WySh4zRgyZKRUV9c7OUW9srBaGFItVmZBQjNMRlBDVOQlMmyaC9rq5icLD\n85TRSRDbFYrmESPEtOUuKG9ZpeUuABL9piSaEBYoA/Hnn2nYYhFpnDuXibRrc5SV1bUyIJIQ\nFRVXcRyPjn5uZUWmSMNfLADg6MdPa5CeXt6/fwyG1QDQaGmZ7O/f2kQNvQClRr/LHqFJ7E16\n+IPgbWfITIuizCLBsM/PWi0UOn1KyxWCkhVDJRNpv9Izsf60Py0UaYfjuKRSohVDnqRSAi2n\nlOWWCQduvGbgFmT+QeAn2mXX6QX3AmO93X/536jdEHeVp8Natccyhl3XhoaGXQJCjfgSmHQg\nBzeKFwUVtMXBCMOlJLvE125ZHrCvAWZ3uOOUFYehrfrqu+R3ahvaT1JPDZJzaYqwjdwFtRE6\nbyanxQxsoBddoZsaYHZ2/QmifX5KnmDsHq/eq6HlAxyAh5gTtWdlhSVuH7+mTGHh9APKXnH+\nK4/iOO7mJqJuZrHK0FiisrK6U6fS0Ii0AQOicRwvLa3r2zeGcKphWM2CBS2sHDYbTrxlsWhW\nohWK5iVLIjmcAgCaudwCWqo8qmDYS1rWFQBwFqvUySlqyhTRhg3RpaV1Bw8mmJs/wLBqJWbi\nW1vB0jIlOblk3DiRjU2io2PM4cNJ+OsST41kzyNHig0NH6Ov/G+/vaf25mFAi9jYwrCwJ2rz\ni2trX5Hl41ojhoaZatmGs7MrIyLyaL8cUIIenYEmIWFYTXS0+lB6FAq54l5grPivcN0KM6I4\nv8szkTVUBjgvgUmo6Rx09UAtEoPjyLxa4l0TtscbalOY8TzEbC7BNlcDzARDtkEN/FceRX9C\niJqEECng6X627YKqokrB6N1nrRcJ+3+iNjyOgH+3JSQVXzHoHsMZ+QRzvMseIZz6jSZV3RnD\nrmtDE8NOJpU1AgP0eYg6c0vZIckXEwUTvhaM2NHK+noX9/oJnT4VOG9REQ1GohTYQho2AgOt\nZitaw64eGAkHbSIfhuuHQ6E0rjTWO2pDWRVyRSWwpJllEOSn5J3f5Rnx+0Vpg/TqoWBlLxkv\nhzXXD4dWACsVL6Kc+GyFXHFu09+CETuopEqk1AEj4mM6Kzrz4l4/KDQ4MTiONmENB+CK4fTk\n5FLUC8Ln5wwfLv711xYEy0eO0BQN4/Nzqqsb+/WLIW2mHj3iqR6R/Pwa2tPKyIBpq+hKZNII\ni1WOYZUWFg/Cwp4EBGQqWaKlvv5V+Xi43Ge+vo8mTBANHy7eseNuQkIxFMw3b54Yx/HU1LKD\nBxM8PJLLyupwHD90iKY8mqNjZ5w9OzmuXMklLRsMq9qwIVp1e0tLNXSDql28pOzZEyeTKY4f\nf7B5c4wKPpE+fWKR269SjyGVtDeSDpkT1w+HkuyYpcDWa95P+tKQlv1KQ0TwJ8FTGeZI27K2\nvDb5QgJt4HW04A76+0VyxqAbG4Bhp3JSQMiOzcrFHKjaUtkJaIESozwDvbTixmIMu64NDT12\nBUi4VTPAlPFPCt32U73xZ60X6abbWauFlHcsm5ZvhQofJPNc20xVtAdSBMO/IJv5rzr6BHMk\ntIrgT0Ld+CgybqfTdqva2y+plFRQCKWoogAs2qhYqsSfjaGaqmiMnXDqt1VFledN3yecnc0A\nCzOZTSX8FIzZQ8vAnsQasn+/qrCzMWPevmOEwodoA1PTdNRtZmz89k2pUDRjWBXUAMMkaEQR\ni1WpySuZFDa7+MyZdHSdVxtpgGLhnZzQiLqmrCzYv7h2LU3gnYVF21ZY/+ehoqKex8treRnp\nk2lI3LnzjM0uptwDpba2JK0gbmDwhMfL1eSnHzgwikqCbWWVXFxMM3kmJZW0dNpJ9+/Xp192\n/nyaj5nu3bUbIj8lD/JgNQEuFMKhOepr6v2WeQhct/uvOtoaO0kmldEmk6Ve0+4xUcgVaHiZ\nJ90ayEtgoiFtb4cg1GwOpHA5sFbtsECDC3EAtGKuYQy7rg0NDTv/bkuguySSMxrH8as/BIXz\nJ+cD+0TWUMGYPdIG6b3AWNS95zX3R20VQws2ywBHNfeHpFISaOVOGCLNADtvMpuWglIFyvPK\naJPDcbpqiTnx2Sr4mSBIG6QSYAz1+QJYqT3Qf+VRKGZFQ8nABqLUA80AawaYDHByMAdiOfWs\n9SKoDRRT6PshTe2QULM5x48/UK2Cr+8jHMfz82s+/FAMAJxGOnOmiMV6gR61evXbGLvRo+G3\nl6sr7JPIyFBDd0crHE5RXl61DstzlpYpEyaI0DUvA4MnaOOff06Cmvn40ITwDx/OhNlpB1of\ncP/+apx2ZWV169dHT5okWrs2qrS0DsfxCxee7Nx598SJ1MZG2a5dcOETWqFah4QMGkRPwFtY\n+HL+fPGAAdETJojCw/P0ewW+/joe1Q19OlSDlgTAv9sSHfRJvpDwmBK+lsZ6B2UG0RAKuYKg\naoNEh6pcuQlPzpvMJkgMCoGdcPoBHMcLQC+o5wj+JN1UbR+gdDA4ACi7KhVJb9j4qaKVO5Yx\n7Lo2NDTsqooqqWt5SawhD67cv3ooGIrK9Om5krakdIjZXG0Vow32RwMpUBSkPbv+83kNC62g\nqK+pF/b/BB26CXBb+VWHnhG1/K4ySColSaHxqqvcoFIDzC59G4CuTRNSCSwD1hzDlcyhEmBM\nPVOFXHGDP5naoAEY3j52taysjsUqU6HFokXioKAsWuutZ8/4wsJa2gBzooSrRCJdvjyyX78Y\nA4PsN0uiCjOztKCgx9D10SSzgbZu+pkz6XPnarSGS5UBA6IrKxuoCmRlVY4aJaYlQDlzJh39\nQXv1imup2+s8EgaaY80aWsenqhf/3r3xpqbpLNYLY+NHn30WQxsqt2PHXQODJwA0KVmmpxcW\nqwrtqq1RWPiSw3neUhMp8SmlOYTOm9HzSWW9o4M+4jc8o6RcNXDToR8C4S0nHByAl8BUk4UR\nAtIGqWD4F+mY0wtgdZfz7tl1/yXTbH27L4N6LgR2tD1HC+54zfspaPMpraputAXoDTuPSyoO\nOWe5AD0EKgEibZCqCH9kDLuuDc3pTnAcv338mveCny8fOEu8+NFICAVgCZw2obeUsuKnKhBk\n/gHaj3DgRq3PUHtUl1SjTHUZyplBNO/2nOUCwqEoA5wAm8UqwlAUcoVg2OfECngB6HnFcBqk\nj7Ia1a8AP8Dmw1jOSGXhcaR491p545fztLty4rPLcsuETp9eNXALMv/Ab+nvvt2XFYCedcA4\nkjX2F/dTRP7pjz8m0hpnhHz0UaSh4WNoI5dbYGaWyuXmWVomYxits01aUVGPlnx9I02LF8Nu\nCWWZEIRMmCCipaw7eDABx/EdO+5aWSXzeLn29nHKB20hpqZpJBkKyhBLCptdCpmAr2+D6sYZ\nM0SGhpkcToGDQ6yG5csYUPH33zQ1tYYMiVTWfudO2Bu3dCl949jYQvSmJcXcPJVuu/zeveId\nO+5+8km05p45haI5IaG4NWXlQkOzKfkTjcbGj2bPFlVUqFqh85z5XRJrSBmwucd29Vn8K216\ngQKwNAlopuJFQQXEmYADUAeMdV6Qjfj9IrpM8Rz00PBzHSI3kAFO0OZTOI5HeFxCzxd9p8ik\nsiCL+WQqXi7moFtVIX0hxGwupHMZsFGdaJx8MREK6T5rtZDcW55XFmC9mFhYKwfWgnd3oj0w\nhl3XhlaGHQTaDKP/jf4S3SgYvEXbzgUT6Tx/bVxHi4S/zYfwKUz4GmrzNClX6PTpedP3vXqv\nTgymYa6nRUl2ye3j19TGsQoGwym06axB5N+NwOCBkiVjnCDq1MRCAQAHoAmZkUtAt8KM50QQ\n4dvT77+Ryg9naJgZEZF39KgKDmHZyZO0b0E1wufnzpwpUq0yVAagtvbVkCFkwVYZVIvM1jaR\nzgGjSEkpha55aGi2JrQmAOAYVk2wS4wdqyy79sXx4w/KyurCwp4UFr7U8N5goCFkMoWV1f2W\nv0hdREQe1OzXX+/37n3XzCwVw+BEHAyrRp12paV1XG4e7Q9qYvLwyJH7w4bB9NfEDUm5beQT\nJ4qUqU3S9CxZEvkmflQ2cGB0QYHuPiEHhxZZGgYGWbSfEziOC0bC7EWeM76jjdPVZGGEClpW\nOTlg68ymjnrsCNGECq48rwz96I3ljMRxXDB6N9on6llEy2TnYg5Uv11uwhOh237BkG2EvdjW\nyInPplLiNQBDTUqTJYXGB5vPS8MGRXFGC8bsoS7ChJrCQXvCKd9AhzOGXddGaww72hpcMZ6i\ncxYt/MCpLGfNY9FIBCHO5Asms9QfpifUltd691pFLFMWATsqcxuBWG8xNa2hARjq9yFHV1HL\ngXXQ5lPCARsF7+68FxhLu16sFxGM3o2WnZABTh/wjLrN0DBz1644JX3I584Vp6fTl3yA5/+W\nW5YujbS1pcn4g9qgV6ysrO7KldzZszVaXeVw6IkhkpNLJ04U9e59l8+niZlrefpZuJJcSxeX\nyMzMiuHDxW8MSoWTU5RqVwoDbZGfX+PqGslilQJQZ2WV7OMDr0KuWqWGIDo+Hs5b2rABLpFH\nypQpYhWePEi++w4uMBAW9sTaOgmABgx7aWIC5xLZ26v/LPTyytiwIXrePLGtbSKfn2trm/Dr\nr/dp05KIdGyZTJGUVELm4SbcK3qBZNDnYI5hJrPRE/B0XEerQ31Nvfiv8PiAGJQvg5q2SUgq\ny1ntSdEiU5yh7MpqUvP+ysFz6IFEUQrhVJoSRGHG8Gslhq6aIplTErz1NNUZdoc3vjX5vxqi\nuqRaMHZPgPVi4cCNmi9J06Iw4znKC5bCGgw1Ywy7ro3WGHZoveRklgtBCOw5+4eLRjOvG0wV\nOG/R4bst8lQE+mgF2CzWQclWQhlDN5pvlQ/s9TXo06Rc2nlN2Hf9lYPniDaikzdoK5vRkvlp\nKE2A69NrJY7jtIUOPwQh0LZff6WJYTc2zggIeB26ocz/QZXu3e+9cQQ2DR4cpVA029nRBIZT\nZdQopUHiUASbMuHx8qADAwIyFy4UL18eSaymicUFKPcedKVzcqrs7WmG27//3sSJImjj4MH0\nIfYM2gK1ta+UlS15I9La2lfQUWPG0H8VYFgNn5+j+ZME/dYpKaW0kaZUycio8PF5NHhwpJ3d\nvYkTRVROn+rqxu7dE2iPGjCAxhLt1Stu2jTRGydi46hR4rCwJ/ZYFs0dDDDUjYcDELDmOHpJ\nveb9RH5tpmNORH0FEmfX/Ze6GisFPJR5TkNc3Oev7DL5dVuq9nBa/oE0bBCO4/cCY9EAFeFU\n2FlFG9BMMIxUFVWiPk5N+H47D2gptF4CE6gZY9h1bbTGsJNJZQHWi0m/933WECg8U2d4zvwO\nvfl0LsaqdyhLyNdXKUCFXKFiOfUmbyLhAfV8/we1gXTaSgWwzorOvMMdh+6aA65B244eTenZ\nE7ZsqEmCJ06kAtCgcsBmqKTsli0xaL1XFUNA6N+fphY7nbyqrn4bpDJqFPWN3rR4sVjdcjAO\nAJ6VVfnZZ/BwGFaZnV1Jl1bSyFSGbR8kJZWYmakJA3B0pClJt3w5zY2HYdWffqrUk0crEH/N\njBnq76WpU8VU7zWGVUVGFhCHK1vuB0qygtAixRxOAQ9I0bmiAljX19THs4dTN14zcEMdcmie\nXCGwg+iuIjwuBVnMj+SOCbR0jzwVofPPR+tSwgGQAc7Fff6a9IBmcgidNxO7BBO+pl6H86bv\noyeLejEVgPXwZiquxOhMZA+jHn79cGiI2dwozuhzlgtUUL12FGgvbzLLBWrGGHZdG60x7Ag8\nuHL/7PoTN46E6ZEK6Oz6E+jzc91gqr761wTleWXCQZuuG0w9b/q+37K3tXEJona00hcOAPHw\na4vchCeBlu7PQY8XwOqagRtR6wxdDKUK+eVakl0imLj3Jm+SmDtWGb8qNCOrFc9Z36O+2Bpg\nbgUgujhFTk6VpSWN047Hy5s3T0wQzm3fDjO1qn4zYViVRCJFX05UcXaOkkrlq1ZFWVndNzbO\nGDo0kgyY27JFQ8MOnzFDRBxy8CDqDpGpSAohhMt9nfTg6iomG2NY9U8/JVZWNtCy3aJrfz4+\nj6ZPF40fL/rxR6WF3RhoDplM4eYmUls9rGfPeGpY261b+R9/HLV8eeR33yWQlULeSH14uOpY\nUlqR//LLW6Yba2uaZwS57eHgzp49X6/PqiPYa0S6QmkdmwHAfcHH0FZ/mw9xHK8trxW4bI3g\nT7pq4CYYuwfKeKgqqvR2/yWaMwod2GvOoTb6HQMpDKaE1AFjNA5MGTJup5O2nQxw/Lstob6b\nYr3Fgnd3Cp0+VVbBNs4vCvpu9+m5ktjlu+R39DpQa/z4LfOgRvhJAe/iXj8dr0KbAc3GELrt\nh9owhl3XRusNu7ZAUWYRtaQMIUXAzsthDZU+t+0QulMI0c4Rz7b3/MNFwI52fs3EBugwUH1N\nfWLLcm2lwDbjdnp9Tb1/tyVortnr9wZge753kNrP+V2eKub++jcpZsS3GspUTBWBy1Zpg/Q6\nfwq5RQKMfx7zE+RaGzdOhOM4VG6BKgYG2dXVjXfuPFPWwMwsjXa9bOBANQ6SpUsjBw1qEUHF\nYpVmZFSkpJT26XO35XtdaTkBU9N0L6+MysoGV1etSU8AwFmsFwT/cGVlAzWQ39Q0PTm5lMMp\ngNpj2EsoWv+990RUVfv0iVVbroqBChQU1KLha6iw2S3M64ULxZQ1d+huaV66VIzjeE5OlVpD\nHxHF9OkiYggDg2zVjaFEEPKWJg6HkoFayqtPP42mPkRDhkQqu+fNQc15sOjNeWKhhrPVhj6L\nTt7IA/bKxlbLGK8bastroyn1uBWAFWo6R23RehT3AmPP7/bSjfcqPiAmxGxuKstZzB0rdNtP\nevVu8WiWMqjFu1Em/yTWEB0UaFOU55X523xI5B2XAls0ghzHcalU2h3YMoZdV0XnNOxwHD+/\n24s26/ZaK+iRNESExyVai8rz/UO0YW04AC+AlW6M7X7L/6AZ6E3QxvkvvZTNqk2AS/0WTAqN\n1+q1gwPQAAzrgBG6vRxYZ2N9fXqu9Fv+h3DQJuGgz4hw3YCAzB494rncZ6am6atXRxEOOWNj\nVa41Q8PHAwdG83hPoe0GBllcbh6LVaZhHSeqsNnFtDHjI0aIkfe67IMPxCrfizgADebmapiW\nlQkRpY7ahaamaatXw5H7s2aJqL97cHAWmqu7ZQvN+iADDUEb70h3T2aRhyivLPdaHBxev9jG\njxfpcIccOpSI47iRkZqsi549aYJKSZcwtUIGJETWRVJSySefRI8eLerTJ9bRMZZuffZttKgD\nyJ8CIh049zT5ilDG1k6I3/I/Wv+rJQbH+S75LWyPN5mC4OWwBhqoAlhrSzXfFvDpRVOX6BXg\nZ9x+TVeZHv4AbdAEuB3OhEcLmVSmwuoN/38X/w9MZQy7ropOa9jhOF6eVxZuMAV9VKC4Xa2g\nkCu8F/zs1/0jrz5rlPVzxXA67URGmy3VDLAQs7lPk3J100fo9CnNCRpOI/aG7hSq8K4FWrmT\n/UQL7qj2w6GSjjkFf/4/FUflYg4vgQkOQCMw8Ov+Uf7jkg0boseNE61YEfn06etv/SVL1MTD\nEUKxrqQYVquNmrC8+6540yaa9VYlSYuaMM1qbVwSQtR4ZbNL0V2ffBK9dm0Um10MgILFqhow\nIMbLK4NaDI32ujk5qamdwEAZkpNpfgVaITzNBObMUeOsNTR8nQYkkynWrPn/7H15XBXV+/8z\nd2MHFRdUVNxFxX3fNZfU1DRLszK3T1lqix+trMys9GOf/NVXK8P8zL3sICCIgguK7IqggiAS\nyCaCCIqICHi9XM7vj7FpnHPu3LmXi0Dd5/X+Q2fOnDl3mDPzzHme5/2OE84QwDFwYCxCqF8/\nPSvQxBnh5va09Ds09AaxjkcqLWH5FF97TWgajhwZw006lEpL2fImAbt25qrAoFMkbgbJcOOm\nrdf6OS5hnz85VE9GTYEo2K0rbKrLYn47HWY98w+q93npcHrslsanCXku+g/xOuRT3dk2pTml\n+OP0AdjjaXzNYiVZJaFbvU7uOiKmjNez6wpkDsW2XnN3d38HJns6LTNV3YNp7bxsBD6X8GSL\n4E00PXiDcsZ2YQdLXavmVrPWg5R2JRDs5VA9iXP4GtWPuP0h2Br9QamatQPvkEmh49Fs4ohS\nTGD7CWi7yIAXDgACeAwW6ZIB4tvvg/WcV9Gjzp2T3Nxid+1KGTcu2ghtLqMxfHjM118T1jBw\nrjLxMO5YR8dLanU98bdT1CM8f9/a+npsbNHt29X5+ZUvv0xwKSSSsoyMcuNupH+47dsnatnV\n0fGS7qIZArhEJFVVjwMDsw36LHF2Po+ergs+Fn8UALK1vcaVoCXWeg8d+tTzy8q6R+q/FgBR\nVOXUqdE1NU+02obvv7/88ssxH310vqzskZhLGnfoLD6yBqDKoH2gw0sCogUijR7xEa/zG5RL\ndUU1cZnQf/UveA9JfgnKvut827+inPI511mJPRj56NlEGp9OrzVytCcspxH/VOcU47nN8GTE\nMOuZjTy1SYwet5VNHMynuods9hBuf9R6JjI7dq3X3N3dmT92HVgGbTjU3MPhW5j1THwuBaw9\nwDaoeVATyRE8vgftgt7/XVdveG2/BmRMsQLX4jgZHiwegfURuxd1PYn1zhNdlpuUw6ufZ3S4\ngz+g9T7+4+Sj2X6IHrAwsqleBrV/DBZvgvd0OKd41pUZMyamsPCBoYsZRmPTpsTCwgf6AqyG\nQSYrWrYsVi93HQ+dO19E+oLRPFDUI2aBENOwf4oOHcxVFMZYaqqYFTs1RVVYWf3x5ptxGo02\nP79S7100d25M377xUultiqrEyxT0Yu7cp7w8P/xwxcoqG0ArRq/Mzi6Du7iLEJLJivFmq1fH\nf/NNykcfnV+7lrAiaG19vZHM2Bq1hqdegABi5GPF95AZlaFyWRVqM/uY9QvJ0iEl4HRBOtxz\nwS5mL/ExG7EzMEY2Bt+OO3ZeS77nipJfo/oVZz4lpzyGvTUagDKuso01ovoqAvBavIfbLCXo\nAlcz94pkUG5STmPOaxIL+VjFSy4qg/aszBrRlL3WILNj13qNdewQQB7Vo7mHwzefZXt5E6mA\n6sZdHlP1Ws1rUAoddRVYHCfFWJWTPuM1o8dt5bXRgkQ1Z2f0r6dqSElpCKAxpU8B77hzvy/T\nJQOKM2/hiSY4yqA9PeIjhnSASDQqDGVfQhRYDP6A/gMhk7vNzy/rypU7mHil6WFre02j0V64\nUOLqGqePqMwAODhcRU8V0gw4aty4GITQm2/qIcLVDeIqTkNh4QOj76V/rO3de0VYuZiHmTOj\nJ0yIFtHSYGeOg3qKqurUKTk09MZrr8VaWOSJrMCwtHzmjZudjVe5IgAtxyslVAHb26c3/qp6\nzP2G22kNWNMTPo38IUyMVljUvghch5oBPf4TpIsubsVPIbaE7+cjdnO5nd8ruosTQrFEp8RP\nVjFqDQIW7DAf79ODxGBX86DGZ9leeviH/qt/MSFTRGPM33ExPnjVnJ0Ch6RHpn4D08yOXWs1\nrmOHALJiMptlGClBF66eSCXuoge9z7pT16k+p/aEcvfySJgYhG71InZFdOxwrTCEkGfXN9g6\niZuUM7sg57/mV7x+ogLaNqZWNwTzyUJs53h2ISTqElEOjpF7jwWsO2DQOwcBeMz5uphUniIG\n12CQhPOWmjIlWqPRfvTReYYWX6ToqhFYsiTm229TTOjSMfj884sIITHcyBw88fDIDA/P0zEY\nkUWUhGbh4Ubma/5DrKbmSWJicU3NE3bL1q2iyiaeRR2xFtVEqBH8rx4wAVzW8vMrSWmgehJD\np06NNsnVPr7dP9h+3jn5uEsSN/bRly4ZEP3rKeEDBWII5eCIEDppORX7SdTVE6lEAXsEEGYz\ni+087DMfvEHGn7QjxGToRuq9xh06ywvvHjdcAL25OxgcTwAAIABJREFUDL/USJ/Op1qttgRL\ns2PXWo3r2DUAxeOcfA4WsO4AK0eTQfU7vt0fb1OUfjNks0fk3mP4l2IGKe+NmJCBEKKHf8hr\nqQGZLg7JnMTsoA2HovZFcL+6fDssxR9GvNV4vXa/pELpuv6k5dRQm9meL33He14ggEdg4/3q\nf8W/ChhBGHr8JwapxDZGowIB9Ie/ihVsbDLt7Li67I+7dr1gOEOEfrz+eqxpg7AAaPjwv3Qs\n6uo0r74ao2OdRiuRMPqeiKIedet2fvny2M6dyY6gPu4xFoT8vOTk2wbdTv8cq6p6PGJEzJ8X\nrW78+GhGfRUnlxEDvcp1zQTtr7/yg4ZWVmK+lP6K8LZtm4rrajTGlNO+5J0si+pDzMGvq66j\nR22OtJgkXMt1wTc+G0tlLgTn8oIy1Zyduo7yXvpf5iyhW73wvZlUX2Yv/pzPovo0stQDIXRq\nT2ikYuId6JBN9VL1eNtoJdznb8T4DzejCTczj13rNq5j9/wZdxI9Y3h0cWXQ3qBVw8A2C3j3\nqxoUutIaAtcf5OlD+zgtM2jAWaTwwZkfw0UeHvwBHS0fJ4Yx2Oc1fgxaGJ6L/oMQqiqvqtIR\n/hDGXWh33JpcC4x08N5Ngr8ye3DFJIp6JFiRUC+XFxheHvvkiy8uGv7jhDByZEx2dsWOHclf\nfnkxI6P8zTfj5PJCgeWQ7t3Pt2/PdQjILXv0OC+RECNovKvEp6UFQHv2XDbonvzn2MiR/FqH\nYcNiCguNK5ppWLbM6Bh6E8LGhvD0CwzM5t5OFEVYAmzTJnXZsthp06K/+irZ5ISIuIIiAmDl\nDVnT1mu5/Je68BgsPF/eQ9x1uM1Cbb02zGYWca93p6eP6/KCMjzO69/uZXYYfu3/qre9TvWJ\n2n/CtBek8ZZxOu2I3dwScLoNnUJt56SFN8msL0q/6fvGT/SET8qgPfdaxclGC4eJzY5d6zbW\nsSsBp+d/9+MZcgiAHrdVfA+ZURk8KuMScMqhegY6vJRxOo3XGFeq1pULHL7jsLLfv5R91/FW\nEIl0nce3+4ds9lD2Xqvs/w4vUsw1opwGEYXgjGs/6AXDfodLGYoEkaLvOtW3JKsEf1g/Abk9\n/OWWkcjuieDJi6kNiVJpli6NDQgQK8QOIMzs+hSdOl2kqIec8Rh38fiQy2/a2GQKr1lSVKWN\nTSa+/dixXPH3/z/HNBotRT3CLlfD8uWxAPh2PejYMVkHPw4XjUmwMxKs4ATPcnPvL10aO3Jk\nzLRp0UT2k4kTo424qveK7ipnbFf1Wq2a/bUAXzExMKIcv/XqidTwHYeL0m+GfKyi3Tb6OL0m\n5keG2cyiXd8j7mLJQY7azMb3sgoQCCHPBbu4X8h/UL2PfuKlnLzNc+FuJu505Wiy96t7j33h\n1/i1OpNbeUEZt8YCAeRSLuJJmGse1NDDPzxlMTlSMZEevEEXfYnP8h/vgiPTvwZkGVT/m9A1\nm+rl1fn1kiy+Cg7PzI5d6zZ3d/dFMPbQ+K1GUHs33o7Yz8Vnrydn9uJ25sdweshGesjGyL3H\nmC35l/I8uq88o5jI8/BuQlduZJnIHvkIbPDwLi+/zavz6+wu/FOyGmwCHV5i/1sPUmXvtcSR\np0oGiny6e8z9hqiWKwwtSBJU0eFW0034nmHI5aP2n+BVjWyD3Zz/NVhZZRt3BpmsUG8bieT+\nSy/FhIfnqdX1rq6iaPMY9OhxXgSPnRiiO9NDJitWKq/h4qTW1llMeNFsPNPNVPekbdsr4i77\n0+XVDh1SXnxRD9FJhw4pvXrpkacjFqs2EsuXxwpfBx0R5Ibz54sNvaSJnjGFnC/VPKqHLrXr\nUJKbxeZyGJTUEamYWJR+03spOdWkASjmTRS8iUAL4L/qZ+6o4ulzqh5v+7d7mR69OdDhr9DN\nPWjnv+rn0pzSoPd/D1x/UK8T8/yNnvAp/uuIChC4aeu1ZxUTuAcmykYSkpROp+GLmr4rfhI5\nQrNj17qteQmKla7r8ftbOX27rvaqXqvZWGo9SFUuq9hdfiv3E7rqs47ZmxmVQVzerwI73oo0\n8YHCUqikhV++Ax3Y7fUg9e3Iz7rTgAynPlbXqkVqtsbJRjEDJsrRCkM5ffuVo8m6hMjwJ7IA\nNCDz6fgqe3Hi6XMhdi9egaEn4cWlEMRtO3169JgxxqhyiYREcg8hVFX1WK80EwatXH5LYB2O\nou433bB1n7R62rRoJlim1TaMHfuXpJWNTea5czcbOaf+rqbVNgjG7gmLWDzMmRP9yy9XP//8\nYqdOycQgOBdff51MFIR4FnpEacXhr2h+ly4XeEQnCKGMjPIvv7z47bcpubn3P/tM55Dc3Q0u\ng03EigyinmVlQwjlJGZr1JqY306zsoSGIlkyhB639exP4QFrDyR6Ps1nLS8oI9KFVoHdeenw\nMOuZwZtob6dl3F1s0SvPyvLKzmKR4odgyyYc34c2qtlfG3pxmtTwtwbihJKFzWsxIYqNvzSJ\nSwNc9TNhMzt2rdua17HLjs/ihQ5zqJ66yH5Dt3jidypbr0qUcGAKlypLK9Op/sSHzkmLKbyz\neHQn5Jl6OL/JNsi/lKfq8XaE1XT/di9H7Az0a78Eb8/lPQ7Z7OHRfaVHt7fKn81yEECSdFg8\nfc5/9S/sGqReX40BwxHluWA3L5WQP7xhH+rSRkMAKpdVoVu9znvHeHV+PUE28qTFFOWM7VXl\nVSH/9nxZ4tEdntF+lUjKqqoe375drZcEjhPxNAwdOiSjp8qqxhyu4xX+pH37FL2SACbHiBEx\n+Js7M/PuTz+lHj16A99lNq5Nn27kPQCAALQAj6TSO+JqetT796dJpbeb5jb4KyGhU6eLERH5\nL78cM2NG9PffE7KsXn89lk1XoKgHcrnOFe6zZwsNupj3iu7iT4k6sGQDl/SQjUwgrxasfDu+\nKj7gwEPg+oPEASSoookpyyyUUz4P3eKpclnl0WNl8Ac0sRNtvfaUxWS9Y3gMFi0qzY4evIHw\ne/u/I+ZYImGCnyPf66WHbMSbnbScKnKEZseudVuzS4pF/3oqSjG+FqyqwSbCclpKEDnFBCGk\n6vE2fqd6dF/J7FVO/Rzf+wfVW9VrNT3638TZXgDOeMpqBIlh3Lvzcl2jIhbnH7F7kVn/9+kk\nKukERxbV535JRXlBWeD6g75v/BT5Q5jeQ9SgYEk4Q7d43tChn4EA/N7aF7bN96xiApfhk8V9\naHPul5M3oSt3I7t8WA/S/4MPqT+XGRhiuf3709asiR84UCgbXSa7ZVTEVnP06A2EULt2IsNt\novDvf19ACL33np5YGw6J5J7R1b5yeVFRUUtUjWwtplbXG8JHo25c0qRIrQj9K4U8TJsW3aPH\neUfHSwsWxAj/Xpq+JjJVwNIyR2TBRFleGZOgUphagK/c14OUKfakx25p7BwDaADK33Gx8HhU\ns79Olg4pBie8or8K7PQS5p3cHSJyMGz0BrfwHYeDHOafU4z3bf8Ko4vd1HYxIJFRa2TxCGwS\nVNFijiUuYXCXHhgL2exBuAi91ogcodmxa93W7I4dYyH/9jxtMTmb6hUjH6uLPcS783L8TmXr\npK6duaqL7KMOLPCNF6TD8Hp1jVpDJNU8ajtbNftrYn27csZ24knvQAd6IDlBmEEu1UPZ718V\nuglKlH3/FWo7J03iep3qmyAbpbcq4jrV55j1zHSqf4x8bMCaX0tzSonNNCDLismsKq+K2heR\nInUjttEbNX4X3Nn+RLPW1cXEFLVtm8r8V3xJ7OjRMQgh3axjtSL74UImK7awuOHqarD6p1FQ\n29tfHTcumhHY/eWXqwsXxqxeHW9WDzPCamqe2NpeE3nlu3dP3LgxsSky4TjgRWP11FtIJGXc\nQ5ydzws4ZOPHR4u8mU+ezNd76WJ+O50gG8k4c+lU/5CPVThF8BOQ34ZOx6xnCnwWGoRicBJQ\nmucaK3jFhV62PF2PXxy6Irke877lrlw+AhvxLAeNMf9VPxdBF/Yqic9+O7k7BA/ghG7xxFtG\nPJtvnU91Z8U59JrZsWvd1hIcu8D1B3l3KjGNlJhb4LlwN9sgYO2BYnASOc89eqzETxFPnxM4\npACccUVdjVpzhqNpxgUxK+Vwm0W+K35inh2qnoSiYKPB+/4+aTmVLYniQuWyyttpmUAoVgzO\nwExDD6KoGoTQlSt3Pv30ws6dyRMnRov/ZRYWN3RHchsaQ5gnkxUNGRKrUOQpFHmjRkX37x9n\ncvq9fv3imRirWl3fpQuXSre+e/dEkcKdZmNt4UKxCZ0KRUFlZZ1eLt/nC35a3rp18cSfmZp6\nx8IiV0SHNWJuoRBVSgF05x5WBXbKaV/oSrdtJMklF4FtF1aV61+ovvWnl8MFrgPG1MyyJkZ6\nkQGRiF6j1tyDdryWsfIxekdrEqt5UBO591jkD2G6ylp1GT3sg8d/rlY8AbmuGG7NgxrabWOs\nbHSKxM2n02siPWzGzI5d67aW4NjhMnzERXicJOm0xWTePL9XdNd3xY96n1N1YElMubgSliL8\ndEiQjcSPuhx6MV42SmRtxBH7ed5Oy47azFb2XXeDcjHuWXmDcuEt9REfxHGYIvUZxUQxYmV6\nkQ5uhh5kZ5fh5hbLebGZkEviGVeMR4pBUQ+kUmGxqacBO4nk3hdfXLxwoeSrr5Lt7DKMGIlM\nVkyUjmU0Q4keiY3Ntbq6FqE71FrMxSVR5J9DoSjw8npOEsZiQFxr7N2b4Nh99NF5ErcLGZ99\npid6uG5d/BtASFAmUoqIRANQvK9xAV8wl3LRJSzEGF53jwCuSAZx20TuPRYtH1sLVpXgEGo7\nh/H5ygvK8CKzKMX4NIkrd0s61b+ytFKj1oR8rFJO3x62zZd5cRC/5B+CrbZee/VEauhWr+z4\nLINvUBOZtl6rnPp5snRIEXSJUoznyZGnBF1QTvmcnvApvtZgEjM7dq3bTOXY5V/KuxiQaIQ0\nnkateUwKlRITDjRqjXLK50dtZh+1ma2cvI14OmLuSB1Y5v5JYlcCTiyDOW7C+bz1IOWph+H1\nH8Lgkv025rOYHvjerT8FwarBhsghnEe5+LVfwjx/tSA53Gbh/ZIKHimMcfCElYYfZHohCiI6\ndEixt38qg2Fl9cfvv2dkZt4dOjTGxiZTLr8pfCxFPUpMLEZG5unXvvZa7JQp0aS8qEdFRVWO\njpeIB27Y0BKfni3WBg0SS3nj6hp39qx+Pp0mRa9eCU5OF52dz69bF//KKwTP3sUlgfcDk5Nv\nG8TMx2rLJiYW+/pm3bnzCOut9n+wFj8yXUIuKSOCyydVD1LeswuXz+HhlMVkgb/pZezbvg4s\nIyynRVhNpwe+d7+kIi38Mm9p7arEtaq8ili7VgxOhakFPp1ey6D6XaP6+XZcmn8pLzMqg7uC\ncF42ojC1IDMqAz+8FDqy4pNakAQ7zBez4mhyU/ZZxx2VBmTBm2htvdZ/1c/KvuvosVvw5UwT\nmtmxa92m17FL8ksItZmdR/VIk7gqe63BSSyT/BJiZaOZm+8OdMALy4M2HFL2Xku7bYynzxFP\ncQtTLG0ASnw2AG5XJIN4HUYqJtZV18UdOnvmx3Dhde+Tu0MEHLUGoPIvPSPlScz80wXhYlWD\nUAV2qlk7Qrd6Baw7kJd8o/rZVFwGtWCFECovKIvaf4Jhh7pXdLfxp34ENr2BDRI9J3fNEGiL\nix8WFz+8cKFk+vRoB4erUultieSujc317t31L/ZYW1+/fbv67t0aw9lVhPLoO3VKZt1NHiSS\nsoqKWt59mJ9fuXv3pT17LjOZeWZj7MqVOyJZ6xSK/Nzc+1ptg8k16AyE+v/9vyuDBsVaWOQq\nFPl4gzfe4K+4bNggdkmSvfHOnCl0cEj787818+b9VZaxaVMiAIqAefhhF0hC2yziZaPYqlif\njq/eL6m4kXQj2H6esFaYLlSDja7PfuKnOBcZVD9iKahyDLkqDgHkJGbzzhJpMYnXJtR2DkKI\nt7aHAHIpF94WNpP7uVllaSUeAkqSDouWj2X/WwV2vm+Izcwz1MyOXes2Yccu43QaL08rwnIa\nt0FVeRWPSUQDMrY0XVuv5a72PwE5PWYLfhac1OecfBy798yP4ao5O4M30XXVdSJ/1Jkfw+9B\nW7a3QnDWRbxJtJKsEtp1/WmLyXj6xR9Ub17jGM5ME8bhdnz1s0biMVhE7Yuoq67zX/VzumQA\n3iBN4or/OoP0ZIkYBX9RpDZxZrqRCArKLiqq0sENob/MsE+feIRQZWWdoCqawejfXye7Sq9e\nzyzbrFoVx0biKOqBeUmPMV/fLIqq1Hud+/aNX7kyrqrqcVnZo6CgbEdHXWU3poEIHh+ddHeO\njpdxPmqctlofGnAx2Y0bn94za9fGA6AgIBCn+XR8NVk6hNjjE5AzimEMjx1CKGpfRBEpDU4k\nHoNFzYOaK0eTQ+xeLADnG5RLjHxMqmRgITifk4/Te3gm1Zc4SGJjLmkLY5WllXhjhsQ0+tdT\nXD2hS1I33KMqg/bP5Qb/y07tCSVeQ96We9CuiZQFzI5d6zZhx47I1sFV2SLS+YbYvcjsVU7h\nU5CoQYHnBNwvqeCSjCRJh2WcTgtYeyCwzUtc0o1Mqq/YgvAB73LXxgLaLjLomignbyPygDwG\ni+BNfDolIid7LalsQklSCdOALF426g50uE71OWYz09A46T1oRxwqg+tUX68l/+VmKxKlPgxC\nNvTjP10b1R8RDV27XujUKdlYWQhNRUXthAnRjRiAFqBWLi8gLrEYjQ8/PC+Vluraa22dlZV1\nDyH00kt4wO4xw/nyTzZ393RxhMCPBwyI9/S8PnVqtIg8ThOsNxvh/Ts5XRw4MO699xKIzIXe\n3oblBcpkRfjG9u0vMb1FROQBoE+BUHnms/zHrJhMNt7CogrsVTO/Qghp67WxByODP6Dzkm8Q\nVcXE47x0eGFqgS7XUG9SSt6zlR/CCLOZxfz2sG2+x61fSJG4nbScSvrbS5i8mvslFZ4Ld9ND\nNvqv+vnSkSTi8IiUCE1n2fFZ+DCIr5XD77g3xQDMjl3rNmHHDp/z6FktV+Wkz/AG+VR3f8fF\nStf1ESR5K+WUz8nnOhjpvfS/J3cd0dZrPbq9RZyxWVRvj7nfhH3mI5DMd2pPKF4N7rNsr8gL\nkhJ0AXeVrkgG+nZcynUrizNvqXqtPmUxGV+xuwMdlFi56wXp8LBtvvgvKn/2W7A489ZDUtl/\nY/AAHE5/fxQh5PvGT43s6hHY9IDnkbTUoUNKTQ1ZKkoiud+3b7xcflOXQG3//vH5+ZUCVK7N\nhZMn84uLHwqWZTxatiyW6L7MmRON/tlmWif7TzSIUIw1PSSS8vfe46fWcc3VVYgS8lloZs0i\npO4pFH9ljEyaFN0GKgvAhdsi4U8dKlxBO5/qjhBK8ktI+XM9T28RPe6ZcR/CD8E2cu8xIgEb\nC+EI7zn5OGIqNo4qsDtlMYUe/4ku1TIW16h++JXX1mvxaowblAveUl2rvnI0uenS7+Kwly/x\nsz+f6l6Ubnq5GrNj17pN2LELtZ2D30lcxp2wz3wEZg7xcUCP1qOIF3swUu/sTZG4ZZxOIx5O\nkxbGdJEYMVaaU8ou3ROJjsOtph/7wo8tF89NyuHx97ILhLegc/AHtEat8W3/CrvxvHT4lbCU\nytLKu1hs17vL67zBhH3mg4eAG4lKcLhfUuHV+fVG9lMOHYZBqkmHphMzZkTrirsNHBiHEHrr\nLYGXXzPItwujXbvLDGNZVtY9weGRdw0frofM9u9qiYnFM2ZEG+LoGIHG8Bgbz6Uya1a0Wl2v\n0Wi//jp50aKYf//7AptqqdU2rF+f4Ox8oX37FDs7QmqmldUfjo6XBw6MO3Ysl5iTZ2ubWVz8\nkL2Mu3ZdGtc97H+S13OgVzrV37PLCiaEl5uUQxxcomeMSKkJXYttAe1e9ur8+nHrFzyc32Se\n1URRRxZVYFdF4hBlQE/41PvVvUTxHvYxy/tLCIQymKMC1h5gr4/fW/suSQarQVEAzjwlVgSA\nJ44rXdczxHsakAU6vNQU8dCrJ1LPy0awFznYYb6/42Lib4mwnMYLPTfezI5d6zY9odhle3n3\nUDE4ccsa1LXqBExwUBiRe48JDwkP4BLBzcN75vBni4kYBLZZQGwcsO7ANaofAngC8hOW09LC\nL9OjNus6oxYkh9surK6o9nPkl2JpQKacvj1owyHuin1mVEbQhkOxByNZTpbgD+gKTvLfOcV4\nYiVHeUGZx5yvRfKniEQW1cckpRvVYNsTmmLthA+Z7JbA3pdeimnc+/i5QiYrCgnJYf++a9bE\nGyoz+s47Qgs8f1f7/vvLrKDW3xJS6R1upbZMdisiIo93ESZNisYPnDYtGiFUU/OkQ4dkXZ1L\nJGW+vnrYOu6XVBCXypS9CVW0OASeUQHt+AkwPO1X8QixncM8QnMS/8D3npcOD93i6duBkESo\nC09Arpz6BTswnEg1XjbqqsT1AdhfkgzmUqUyRo/hy3IctZlt1A2ux7T12qh9Ef6rf2FyxPOS\nbxRjhYYMCqhueJpQY8zs2LVu01sVqxzwLvvpk091D9vmy2uQm5QT7DD/AdhrQKa3YEpAm4s1\n1ZydYianFiTE76SgDYcIz6mphPhv5N5jvK+6VMnAY1/6C5/Xq/PreHE+AviD6hVhNd1/1c/C\nv64wtUA18yt68IagDYeEWyqnfWla385U+D/4kLhHZLmiIRBYDjEm/U683IW4MRgAmax4xIiY\ngQNj162Lr6vT/P57hnjfTi6/WV2tR1vp72dabYNUesfUd1RLB0U9nDEjmss5vH9/Gt7st9/S\nEUIvvBAt3JtCUaBXauwOiQQAD0fi0Aomxvm2f4V3ouPb/Y3gRWdVzhgLtueX9zLcVf7tXjao\n20yqr7pWTY//JMJqOnEhMDcpB+kwvFKtAaimiIfidlR3iOwetMuMyjDVicyOXes2MTx2OYnZ\nAWsPHN/uL5xPUF5Yhq9+NwBFD3o/xHbO4bYL/d7aJ2ZIHrO/Fjk5LwaQb7sgh/ncZtHyscSc\nPOKzIGDdgcA2QuWrD8E2SZAmgB7xEdN/XvKNuENnxRfzPjO2VT8HtF10wmrqCaupxJzZZoRu\n2YkWFwDlwtY2IyvrLleaTCK5p/coe/t0ky8NUlRF+/YpRCpjfFQSSVl29j0jbqHWbpGRBc1+\nzzQXFIqCSZOihw2LWb8+oa5OM3lyNOczoH769GjmEuki0OEiNrZI+DobRNjERR6lp6CBeRKG\nfebj3+7l49YvKPuuo8dsIUqHCYPLXXKv6K630zKmtP8G5cIGSb1IfCjCwAlQuBBYAKsmkfad\n3HWkkTe8GKurrhOgNVBO3maqE5kdu9ZtRhAUV5ZW0sM+CLGd4+e4JORjFXdXrHwM71ZLlwww\ndEghpMS+RxgveQW05clOcM1z4e5Ah5dC7F5UTt7GLQvNv5RHD93k0/FVetTmeEyYAQHQg97H\ns4l5EF5IqwWr854xLOHQfWjDLTcRY7xkuCyqd4vy7f4Ha5t7CMZg1qxo5vKuWROvUOSLW/PT\nPOdQYI8eiefO3ezW7bxEUi6TFQ8aFJud/VzL8VqOmYhbWCORVLQwVTHDYGNzraKiNjAwe+HC\nmEWLYoKCshFChYUP1Op6S8tsvYeHhuqpp85J/IPoqQijHiTCSWwIoBpslCM+4m4pBOdY99MG\nnaiA6kYcNq9MlRioaQwuHdGp55FB8YmddYWPmsI8F+7GqwMZqHqubkzPpTmlYdt8o/afUNeq\nzY5d6zZDHbuyvLJrz9a9K13Xs3sTVNF3oAO76z60MeI7hpi05+20jHc366quFbDIH8K4dQm4\ns4gAeKt9xuE6xrqkS+P55K4j9IiPlNO+ZGnEI38II8zYHm97Or+paz4/T9SDdAoYyrPVQtCw\ndGmsQpHX3MMQGmFu7n1D7+q/q2m1DTJZiYEX8DFvi7V1VtMw8jxXTJkSzV6Wd95J+JM054kI\n7uWGV16J5V7VK2Ep9KjNyl5r2KQR5YB3m27oeClrQNtFvMozAdSDVDwHr8plla404kLKmbel\njBR+ZRErH6Oa+VWkxaQL0uG+HZdyQ5zenZbhZzGUUauRFrUv4rx0OD5sr8V7jO6THvnxwz9Z\n7jOpvsd3Bpodu1ZsrGNXklUS9pkP460LtMeJSDQg49L/Fmfeoods9HNcQru+h9N/Ey3u0NnD\nbRYmyEaG2L0YvuMwsfYnbJtv+I7D4VYzrlH9IhUT9aay8Swv+Yb/6l9yqJ68bnlJgemSAUSK\nlsbjpOVU3pC09VpuzLcabDwX7EIIEas3jlvNwDN2mwV3oJM9GJGp1kLQ0ldu+vaNHzYs5osv\nLhp0e/8NLDw8b+PGxO+/v8wV4Rg40IBiWIqqMLQkpbXAweEpA8C2bUmGH675/fenfonnov9w\nJVmjFONrHtRcxaQX9HRH+ry8BZ31qooxSKf608M+ENMyVj7G0HWBmN9O0yM/5oVcKqBtLuXC\nHXYlOPh0fFXXeSMVEwPaLuJuuQMdGN+OHreV17gepN6dl3MFmdLCL9OjNyv7rONW3Zrc8pJv\n8BSbUiRuRtfGBqw9wPtdheBsB7Zmx661GuPYHRqykV2Nv0b1O7UnVFd7nFwHAXjM/66qvCpy\n77GLAYkC4VGiHfvCjxvZrAcpPepjXh7GWcUEQ7vlGj16s66HjhoUNygX5ryRiomXjiThFa+G\n4jYpGRkPSeO8KtVgc+3MVSI1YKjN7HMK/fzszwdfw47mHsLfHy4uLfGR2hSm0Wj79ftLk0Mm\nK/L2vo4Qqq5WG5S1yc2e/JuBdeyI1Cd6MW5cNEIo/1LeA4xPRNVzdfmz2kI4CqhutNvGWPmY\nVMnAw20XEivkTlpOxdnsiS0vSwZp1Jqzigl6SYmP2sxCCOUkZhuaplyaU+rp/MYVyaBrVL+a\nZ8MydWDp1XVFdnzWmR/D8UoOetzW7PisiwGJ+GD8HRcjhKJJOkNcxn6vxXu47xpGypI7trrq\nutiDkUa8KHFLCboQZjOrGJwKqG7+jot5WpeUEJtWAAAgAElEQVQG2RE7AnH9PBhtduxaq7m7\nu88Dvq9WQHUryysjto9SjMfvAL/2S1gWjyuSQVH7IsQPANe0uQ2dIn8IO6uYUAFtC6hu3p2W\nCacv3Cu6e3LXkQs+ccQKidAtngIRTEboJi/5BpOxkeSX4N9ox041awe+Mcx6Jm9gx6xn4s08\n5n2b6BmD5/ARJUCaCxEwr7mH8I/Ap5/qzPL5O9nLL/P5deXyoqqqx6GhNwy6XAMGxEkkZM7q\n1o6hQ5+GU8UoquHo1y8OIeS3cj++rwrs8AJYLUgSZSOegFwNilTJwMvSwTeha6x8TMDaA/F0\nFPEc+VT3ytLKExwBIV1P3aM2s+iRH4scOpM5owZFsMN8I8pOiRwoGVR/Zi898mM2UlwPUo8e\nK5ntngt24UdlUX0QQkT5DaYsF+lwnbmpSl6L97Akw9eofhE7Axsxb0xpeHI8AngXJpsdu9Zq\n7u7uPjAR/6P6r/6F2P6MBb9xLVjx5nAe1aO8gOwX8qzmQQ2RT1y8tCs9dgs7l1IlAxmfsjjz\nFj3+E48eK1WzdgjzG8XLRrFdKWds15sOzOKU5RRiQUO41QxtvTZJOpT3oPR7mx87PqMgXPZo\n+Vh6wqeezm9w0ziiFOOP6ub2FKaYyaO614r+USLhB6+btL9/OBooqkIqJSSTWVjkJiYWi5wI\nrdc46vV/wcMjMyfn7+mlGQF7+3TmWikUBUYcTlEVFFX9qpwfbtOF61QfevwnlaWVSizy6Nee\n/N2bS7mUF5SF2s5h1uEEVuOUkz67IhlkxFU4aTHF0FuLmIiGAK6eSGUapARdoCd8So/ZEvPb\nafaowPUHiUcFO8zHC/sagGLLLPze2ocfFS0fy+w9tSeU97IrASeW9J5o+ZfyClMLVHN2BjnM\nD7afp5r5lXHrfD7L9ga2WRBqO4ceu4UYrsXl2hHABHAzO3at1dzd3WNgKP5HpSd8ijcO33EY\n/w4jyiT4rdwv5uzlBWW4Y9cAFJcDWcDwzIBcyuXYF37cAg4Bha570C72YCTT1bUzV2tItRS6\ncOVosrIvnwm5FiwzozI8uq/E22dTvbwX76FHbQ5cf5CZnCpMdox7BXhbBPiftCARCKZUg43q\nha/CrWaI/2l6kQe9rFs6bWxLz6XjonPnpBkzoom7JJLyjIxy0bO5VZqFRS7+w11d4xBCjo5G\nR1f5VRStHVJpsYNDGkU9FNGYfPN3hWKDTllIOePP9jLOo5WLYIf5gQ4vienWo/tKNknfUIj/\n4GeMKBGLAE7uDkEIqWvV9OjNsbLRaRLXw20XpoVfZo4qzSktJaXTIAB66CZeBTETokUIZZxO\nI1KunJcOZxoQaWVUs3YQRx62zTeNlPt4wnKagG+X5JcQ0HbRedmIY9Yzg97/ndno2/4V3nhw\n3+7K0WQei8pZxQQKKLNj11rN3d39Z5iC30DcvAHWRNKRIwB6zBYxZz/cdiFhJshGiBw8kRgl\nXx+7EgIoAaeTllMzItPZrjwX7sab6WIMYiohiGwpYmQzLkqHHvmQjpON0svnLBKH9RHvCas0\nGoHv4AuT9mdymEDc/bnBwiL3l1+u6to7duzfXEyse3eCIhYA+vrrlMGD4yiqhX9CtDRoJZJy\nXXuLoFsjeycuxVWB3bUzV58DJVPAOsPKEZTTvsQ7qQMLhpD1cJtn3j7l4MhSEwRvool8e4fb\nLow9GHnMemYO1TNZOoQe8RGTQqd0Xa9Lytar81PRyOOkr2tln3X4sNPCL3MFinjwXPQf4o+N\n2hfBW5u4D22Ib0OWaZVr0b+eOmk5tRQ65lIunl1W3Mq6Za6KbcXm7u7uAs68NItTFpOJnwWe\nokkgQzZ76D01MQ6rAVmSn1j1pERxama64gLpkgFsyFg18yu8wTn5uCthKVH7T9CTPi0GJwSg\nBkXQn9keRC3FAHEE6KaVlIiVETIkeDPchKdDAPEwyaT9/aPRuXMSQmjECIKUOwCSSO5u3Zr0\n+uuxW7Zc4Kp//j3s229TdK1CtXbZCYmkvKV9YKwAX5N3+gTkCarojNNpz+EHGLpihxDCk1ho\nt40IoZjfCHR6XElx4ipGsP08/BR44IhFDtWTjT6peryNN/Ba8j3eIe36nsBF8On0GvGXEtPf\niQizmaX3urVkHjsJmE2EFUJx0l6PU5ZTS6HTDaqnp/ObI/4IlkgJV08yYZiYDuPkYxb85w29\nza6fSbcANW+jFLSuM924W/ze+L9Yxbh8iUu0Yvzhf/3G3VVk303MeChAxO1uDX+cmLr1aRsL\nOd7gprPr8IWjZmyauyZ+T1dUmp98o6G6aumD8G5u3QEg26Evr309yGo7OYkZkgKeiGkmxjQg\nBx0/kLW28MBUpzOboOn5QxDt7t0uDg7pOTntiXsbGtr/8MNYf/8pe/eO6969zt09o3EjbEGW\nnl7+1Vd9EbIj7tVqOz3n8ZjWGho6UFR1c4/iGfODFe/A76XQGQAQUCbpkwLk2LPjwBfcKqCd\nocfiY6gDyxtUT2LjMxaT0n8/rRz+Yei/PcWfYtGjSN/Xf7woHVZIdYuVj/HouYaqqVW6bcz/\n+SjeuGdlAftvx1en4w0eDhlCOEfoaXzbJYmbynV9m/ykrgOdmS2j/7f5Ljhy26RJBi4+9D5+\nrG1picAv0soJryoAGPokW+Aormmk5B5ajTW3Z9kKzCCCYm299qQFIW7Logas/dovEVm+pK5V\n44zneVQPbhvl9O38TxwOB2OiZwwvXQNnqhNGnGw0Qqgsr4wtVmJxi+p8r+iuwPizYjJ5Ryl7\nr43+9ZSpPk/FQAsSI+QXG48WH4r920IqvV1ZaYxIXQu0995LaPbr+c+E6scEgWCfLhBjFAjA\nt8NShBA9ZKOhHXq98j3++DphNQ1veZvqxFV0jVRMrK4wQC0JIaSt14ZxVu+IVMY8tlEe9VW0\nfCyR5JWYwUy7voe3jP71VKRiYhXY3QXHYPt5WTGZxKHSg94XuGhs8hzP9AomsWB12ASsJa/Y\nmR07/Wao8oS6Vk1P+FSXyp5yxnaDzq5yWYVPLY/537GTFve3blAu3B5otw3GPNj+xDnFeESi\nnUQAUYrxesefl3zDs8uKc4rxYTazGG2JuENnGzMekfBzXKLq8XZgG1HZyiZHCoxq8cUTf2fQ\n9DWDZlmLtYULY5r9Yv4DIZGU/W/Cp4YedtpicoLyHHHXVckAhFDAugMG6cBWgd3N9Jt4njHR\n46zBEvhUPd426GZTTt6md0jKaV9yD9GoNUH28xmBogpoSw/ZSMxQUvbhV9EhgMD1B0UOrDSn\n9PA77v6rfs5NynnaYV+dKdFeXVbo6keY/4EFMZqMm9mxa91mhFYsY6ctJvPumPPS4YYWY6tr\n1UrX9begcwNQTzj1tjcolythKVkxmfh92QAUl2NP/GcKeSYPeBchRMwwTZG4MafQqDXiGb39\nV//SmPEcsZ+r7LlG1XNVmO2sk5ZTL0nciqDLTXBmRXhqwUrZaw1znXXVfDUpHoKdI9xr+vOY\noRO7dl0yaJa1TKusrLOyymr2i9maYVzpd903n8bgdGt6oQVJSVaJLu6kMJtZd/URHfOgnLKN\nSPkkUjjxkmSwmNss4pug41YzrlH9SsBJuMNcyoV3LO6xMfl5PCvJKuG9QSItJol8FXov/S97\n3arBhh675YJPHJ6BHS0fqxzwrjDv3b2iuzEk/mQEUAxOyv7vKvuu42q7a9SaK0eTmToS3MyO\nXes2nmMnkn8OIZR/KS/Edg7zvVUD1sxqvNGGV5ieVUyorqjGqysegD07Z4ozb+mlL+eB2z5a\nPrbmQU1pTimxOjWwzYIrYSnhVjNqwPoJyBNkI5kieWFLC78sfFIB1INUAzK2caRiYsgWT7bo\n/TFY+LdbdOfGbUa+hh5NUB57PvgN1jfTmc1AAJqsrHuNmWstxMaNi27uK/mPw3wIvw1Ohj4z\nWVSCg0FVX3jNVj1IL8iGh9rMDvlYpesJdhccxZwlm+rF3EgatUaXdxLysUq8vnbMn4RzjGnr\ntfj4S8CJeKKcxGzfDktTJQMvSIcr+7+jazw8Swm6wEtG0oAMF+1EAMcwfntdFrLZgx67Jchh\nPlshm0X1wd9c9MD3GOe+HqTBDvNLskp4DcyOXes21rGjR29mtOfuQxuPbm/hGQwlWSVR+08w\nCg2sVZVXpYVfNlodpaq8ih6zJdDhJdy1qgPLmgc1uDxDkMN87uHCjCF3oINPp9dYvecblIvH\nvG9p1/c8uq/0WbaXGXZ5QRkx3yL6wKlMqi93SwW0vRKWwpxao9Z4Ltzt2WWFcsC7HnO+VvZ/\nhx7+YaJnDELoiP0z8ixakBCFaMSASPjUANRlyWDT1tUahBzo20xnboFQP+czzp4dbdxca2lm\nZfUH6Qc+ae4/6N8BFEVQc14O/s95HKmSgbgTGbThUPAHtG/HpUV/RiGMQ4jtnKyYzFDbOY/A\nph6kVySDgjfRvHsMlzUSgEf3ldxjM6MyiM14PlDswUiPud8Erj8o0pnjGlEWPEpOKG6NsJpu\naOdF6TdDPlad2hOK5wXS4z/h9Y87jmbHrnXbU63YcXyBed+Of63AleWVHbGby0xRNSi8Oy8n\n5pDqtZoHNWwaAUKoOPNWFtVH1zSrB2l5QVn+pTzu8nKkxSSuvJjH/O/0TtdqsAnfGXhyd0jM\nb6d1aQ7egi68o1IkbkRmO0Z2prqiOoHEtKIGBT3+k/slFR7dVxaCcx1YXpQOPfyOO3EC51Pd\niNzOLR8l0KW5h9BC8FzJLCSSe+PGxQQFZRsx9VqUBQVlz5kTDeY0TRPjKSezTHbrp59SLS1z\neA3uG14t0UgQH5K61CAMwl1o57fy5+uSZz68a8GSq2apUWvEKwllU714wpUatQb/ri4HR26D\nYPt57K5cyiXyhzCDJgKRAIWYYEMMARtteBFMA1A8qVmzY9e6zd3dXQ7y65iDpQYF+wmCKwQr\ne60x6CzZ8Vlh1jOZAqgCcPZcsAthjNg8pElc2cOj9kX4LNvLVX1hTCSvHsv9zZhq5leZVN8n\nIM+nutODN0Tti8CX/Ty7vanstQbv6rjVDKQjW5bBY7C4GMCfDIWpBTdJn6dGx0SaDmKGdBpm\nN/cw/9Ho2DG5rOyRQROw5diMGdEA9c1+Df9+GD8++vvvL9P0tdLS6jffjOva9QJAHbvXCmqf\n89OmBJy8SQrXRg/jCciP2sw6Jx8X5DD/moSg2YoAzlhM5N5sxaS8Ol585gHYK3utIeYg4Qrd\nHt3eYvfSA/lsczcoF/HZ2AghryXf48Ojh2zkOXxErYjGGNHfDd9xmNvG7Ni1bnN3d/8d+GUQ\nDBhHqrK0Eq9ILwBn8afQqDW8FDoNyII2HLpKkkxhUAeWx77w09uzcFk4i8dgwU4MnIj4FFYF\nggAirKarZn+Nb/fssgLpkExmoZzyOT7UePpcnGy0cU80U+E61TeL6iP8YNUb4W0Aqh9kN+vv\nMANR1ANHx0tffHFR/DRsCfb77xnNfun+xlAoCr77LoWowyaFemLCiclxD9pdkA736fhqdnyW\n74qfTNhzqN0chFB1RTW+DMGiHqQXfOLY+w1Xto2TjQ5Yd4DpQQOyUxaTBUiPq8qrfDssZV5/\nTKiKG/O5QFp6FJOHzZq6Vs3j2M+mejGlgUEbDvl2XBro8JJy8jZdgSbjjKiEy8p45l/K8+j2\n1lnFhKM2s6bAULNj11rN3d2dOEM0IGPS6RJU0cT5I/5ui/whDO8h3GoGkRXpCcj9HBfji15E\ni/nttC4hFy4egq1GrWEOwYO/RFfmuPULRek3ectstWB1ctcRry4rhBNy6VGbiaMlfp89T9Bu\nG0O3eDSyk3zo2aw/woxn8OabccSbrWXajBnRzX7F/u7QmaR4GUYY1NHhNgtULqtoESwhXPg5\n/iXeoK3X3qQMSKQTcD2vUf2Y91HEzkDhTuiBTwnkKksr7xXd5TJzXZEMYpOki9JvimTCqyqv\nSvSMwRsTOVP9V/8ifjpE7j2mnLE92H7uFcmgdMkA3/avcFOVmsh45HwMEmQjEUI5idnF0Jm7\n3ezYtVbT5dgFOrzENKirrsNFALOoPuJPQcyES6f64wvdDALW6hEELMsr8+68vBCcq8Auk+r7\n6FmBPBws7WRddR3x2YE7aozW7Zkfwy9JBjNbCqhu/qt+5skLEsFkWsTT5+ixW+jxn7BfkB7d\nV4p5umlBogbFI4y6ufEIbLNQfI2YAL6FLykjqRZaEyjqQbOPQQTqNBojS5eev/1TK2FbhLBY\nJ7hjkJwrK+14VjFB5CHVYBNPn+P+xXlilQIoB0ciPeoNyoUe/D7rV3kv/a9wP/7tl3h0e4vh\nEMmnuiunfB75Q5jH3G9Ct3qxn/dGW/Svp45bzcilXFIkblewhQktSK6dueq99L/K/u+oZn7F\npeXi2f2SCm6k6LJkMOtxNrXh9YgIQOWyytP5DZzLxuzYtVbDHbsnIPdv9zJXdMGjB98jUU43\ngIhY14pdWV4Z0SfzmPetQG/aei0veFoLVsq+/4qWjy2iulSBPS/UmEP1zDidxh5eCM6802lA\nRruu5zp8py0mV1dU08M+iJeNSpO4BtvPY/IPxLCr+Ld7GSGk7LOOdaGegJwevMFz0X8Mcqpu\nQ0fxjcXgvNSw73VhqGCVSUdnhvFoReUUX355sdkv1z8Za+F/Ips+BFuGNODwv36Lk48WeO6l\nSIfcg3Z1YJkgG3l8uz/3zx37uyi29v8N3kCP+fepPaG6UlxuQte85BtMnxcDEoV7K4BuvC2q\nWTsQQveK7ip7rUmQjUyQjVT1Wi2sKkS0ePocj52El6Tk7bQsjZNfVAJOkXuPEbvC88sZDaTn\nYMr+7+AXjbdQx8Ls2LVW4zl23kv/i685q2vVtOt7BeBcD9I/qN48em69plFreOllGpAxpenE\nZWFukgRC6IJPHD38Q2XfdcEf0NG/niJyMHI5UCpLK2PcI5WTt6l6rlbN2cn7Oaqeq3nHhti9\niBCK/CFM2XutV5cVPsv2IoTOycdx29yGTtnxWce36+ELSJIO1dZrQzZ78LZrQWLQt7LJUQkO\noXYvmrbPyRDXfD/IjL+we3dr4it2cjL7do1Boxb/JkG8+NbJ0iGJpLJWHrw7Lyf+oc/8GC5y\nuY71Gss4omH8s3RaxvYc5DDfoJ+dJnGtq67jpcRdlA4VziYqLygL2+YbsTOQ4Q1FCIXazsE7\nj7CaniZxPScfp5r5FY/oCgFco/oROy/CeBjwutQmstKc0lzKhXtqAbZqs2PXWo3r2F2RDBKu\nvhHmqwvZ7OHnuCTUdg49ZCOP7i4nMfuozWwmm62A6ua56D/M9uz4LJ5oGHcCI4SUkz7jZtHp\n0kVNkQ4R+XvVtWqfTq8x/TQAFWo7h1flXlddF096nHl3Xp6XfAPfzovtBtvP83B+06DnTlPj\nMVgkyEaaPHX6E/i+uX+ZGQgAnT5dIPLmbwmm1TYMGBDb7Bet1cJ4x24wZDSFrjQxwFJZWilQ\n4mAELksGsxxb1RXVygHvpksGlIDTOfm4DIpcIcuiFqxUs3bg2wUEMFVzdrJcVMXg5L/qZ4QQ\n8UT5VHc2IoQLYCKAqydSeZ3r4mGJO3TWNHNMn+Um5fh2fEqnHNhmgcClMzt2rdVYxy5aPvbS\nkSSj++EVqGZRfXgOE0Ko5kFNYWoBb2NOYrZ3p2WJspEnLaaoZn/N9R0vHUkSSUR03PoFg0Zb\nlld25sdwfDAIIWVfMpXJedlwhNAVySC9gxGv9GWSjLfmwv/Bh809BDOQQpHfwnPsqqoe9+4d\nL5HcB1DLZLdefDHmt9+uNvt1a53Qy96sM/N1wYKYCOl0XYcJ07wLIF42Sl2rzk3KoUdv9uj2\nlmrOzqKrhcrJn5WQXBwWwh+Zup6KpdCR6ERyyeSIuEb18+n4Kr5dl1pS5A9hvIq6KrC7cjSZ\nF8ZhcVYxQVuvVc3eQfSbeUmHjF2UDuU1qwI749hhG2kCCkbuMNns2LVWc3d37wydss5fb0wn\nV0+k4ve0gFyxSFNO3y7y+eK74idDO8+KyaRHb1b1eNtryfdsUm1ddV26ZADxFInSERmn0sQz\nXop5Jl4OSfZ0fiO3cXK3/KeYDoYnk+NH+Pi5nMcMnZDLC44dy23kLGtSKyt7JJHcwUbeIooJ\n/jmgqOrqajVxPakxOKuYcCnkYuhWrwoO9bGYyIDH/O+I8twM6Amf6iJdegLysG2+vHtML5up\ncugmIvOoLjZWoqgXPWozPeFTYv8akOlyLsvBkVixgWudMeV6z98C1h4gjjzIfr4jtDM7dq3V\neFqxxpnX4j34nXFeNqKRY6PHbdX7jHgE1vSIjwztOXD9QW5iQYrErSyvLGr/iWu6V/XLded/\nGIFsqhfDG4QQEsgsacn4APY19xD+sXjcrdv5HTuSa2qeNHKKNbW5uZmjri0Cdnbpebp9KaNR\nA9ZG+IuH2yxM001iqufYtgt599ixL/yEQx/KAe+e2hPKW3p4AnJdnHNEL83D+U2EEHHlTxfq\nQeq1eI+uqRHxTVC41YxMqu9ZxQSf5T+acNIZZJWllfhbz7/dy2aC4tZtjXHsDr/jHiMfWwxO\nWVRv/LbmaSobYVH7IoRnzk3oWnC5wNBuqyuq8YeRX4dXBPTNTIVY+Zgziok3KJcasCoGJ9+O\nS29cyG6NAVkNyAbBteYexT8XDg5p3357ac+ey7//nnH6dIFaXd/IudZEJpffbPZrZQYAGgcX\nWpSA4X1oY9yB5+TjePdYyMeqCzIhmbJzivEIIXrc1po/SRhqwFpghYx224h3wkaB8ZfdfVKN\nSB7Vw1CFseayJL8Eth75NnTyWrALmZUnWrsZ7dj5vbVPeAYq+7/T+OF5dX6d2+dt6MSu0l+n\n+ugqJkcIXQlLCXr/d16BLWMndx0hzkNdP8RUZQeXJIMjfwireZbh5YxiYibV1yT9P098Ad81\n9xDM+Aty+c2ffuLnaLcEk8luNfvFMaMz3L7bOsMCOHiJcUQnjAeWSSQzKsNz4W7PBbuunbkq\ncNOWZJXwIsWXJYNZdoXA9Qd5n+K4vgUCCLaf10RzqomsOPNWWvhl9r9mx651m9GOnfBa+jn5\nuMbI2wW9/3uSdFgtWBWAc5jNzGD7eWHWM5V9/xW4/uDx7QEBaw9EfBOkq/+q8qpQ2zlsCf0Z\nxUReGXkYiaGRGGl9DBZ+jkuideTMMtCCxKfTa/6Oi4UfLhclQ2oe1BAL9aMU45v9cWkoPoT/\na+4hmPEMKOpBUlKJ0TOuiaxHj8RmvzJmbIBfTNKRGJmfJsVDsE30jGHvrqyYTL0SiAjAo/tK\n4bvUY/53F6TDi8EpTjaaKYC9eiI12H5eAdUtl3Lxa7+E9wY5uTsk1HZOsnRImPXMsG2+KUEX\ncDYrYTbWJjJtvVaknIZeMzt2rduMc+zUtWpiBZBH95Wqnqt93vgpyS8+J9FI3tSwz3x4nYfY\nvejvuJhdOTunGJ8dn6XrcFzQItxqBkLofkmFquequzriEcSfE2YzCyHk3WmZ8INDAzLft/bx\nFt7UIM+U9GXLzbQg8XdcnCwdgh+uq1yjJeMh2DX3EMzg49VXY42bcU1k339/WSK52+yXxYwf\n4eOm670BqEayqDDOmS4BoWqwuQ9tGM4mnlC9GC3aG5RLeYFOBQhEKgv1WvK98I3tv/oX/3Yv\nB9vPoyd8ypDhKad9yQ3F3ILO3k7LBF5SJreM02lh1jOrweYJyC9Ih4tRWhc2s2PXus3oFTuc\nYlELktKcUp9le9ldydIhUftPCHRSmFrg135JAdXtDnQIt5rBfI3xhCWIOKuYoKtPPH9OA7KC\nywUC/hPxS7QWLGMPRiKEYg9G6hX4yqN6eDjza6kqsDySSxI3wm+Ri1XsaVHZeNZQ09xDMOMZ\njB4do2tSPH/Lzq6gqIpmvyYtBBYWN5rx7P+C35uu93jZqJjfTnt3Xn7UZrZ35+XHrWYY6ucp\nB2+IUky4Ax3wpJcnIA/7zAchpFFrcBZVYq0rD/SwDwXuUm29llvSy0BYMJOXHXReNoKJHaWF\nX+YRXd2BDsIxX1NZdUU1T3i9CuyYNKSo/SdCbOdckgw+aTnVIB1bs2PXus1ox86783LefDht\nMfnUnlCek5RPdS/JIkeIcDbwUuiYFZMpkO7GBSsyw7XqimpiSpxXV6GSeGK9mMplFdtt8Caa\n8Qs1IMuQ9Cd2IsbrSsFW7K5TfTwX7Bb5BDz6qTcuiUaE0cRU4tEFSpr4DGYYhrVr4w2dxU1k\ndXUas8IEAALQ2tlldO16QaEoaMZhjIDLerUQjcZdcPR+dS/3rx8vGyX+8PvQRpfyQQF0Sz+V\nhhDymPdtJtW3HqRF0EXZey2bhHPUZpbe/rkhUXWtOp4+d3J3SFV5FbPlSlgK4W8GElZtgmen\n9oTi7enhHyKEMqMy8FdAYJsFpp1ZhakFeA4SMd/d22lZ+I7DvFA1PW6ryBOZHbvWbUY7dkwq\nG3vHxMrH5CRm+3Zcit9hukq+fd8gLKSrerytSzGQB101R3gtwgOwPyFIGhwlJ2S5+a3cz+u5\nJKukuqI6dKuX0Q/BNIkrPXYLq7RzUTqUoa9U9Vyt9zM3xHZOWV5ZuJVOltHniWqwbe4hmPEM\nFIq8srJHhs7iJrKJE6Ob/YK0BFDUo2YfAwDaCD/jW024/F8NNhcD/vIA6GEfCLdnv71vQyfi\nk1kDMp/XnzKAeC76D2+vT6fXmF3n9GUnPwE57baRYZI7vt2f5T0oB0fV7K8RQpWllfiDtxwc\nEULXzlzF89XokYSg9jHrmUjH6yxdMsBUc8pryfdMSccTkIdZz+TGeXnqAAwiLSYlYBJKD8FW\nWEiNNbNj17qtkTx2l44k+a/+hQlZIoROk6KotOt7xGOJasQRltOUM/i8xNVYJPQJyHV9VHkt\n+Z7XOJvqFaJbKTXEdo7fyv28jYXgjCtnMKZRa4h6tWJQAW01ak1VedWZH8OvHE3mdhv72+mH\nYEd8CJZCR68uK5STPqsiNUCmq9sVjyHx3V4AACAASURBVLfB4/me0AxdaKCo6p49E5KTbxs3\nhZvCzKl1AAigvrkH8BQH4D18q2nZTx6BdRm0D7F7MeN0mrZeK+xynVVM8Fq8J2DdgbK8Mp6M\nOIsTltOYe+mSZDB2WaX3iu4ihLz0URMzCLafl5d8g5ei8wTkTMbecasZvPax8jF3oAMC0IAs\nxO5FbuUEPf4TvP8Q2zkIodAtnviuRNlIk0wonNA4QTaSVarwXvpf/NS+7V/B35sIIPrXU2LO\naHbsWreJd+wivgmKtJhUDE5pElfabSOxKJWXf/D0DtMhC0HU7/PtuBQhpOq1hg3pxsrH4F8e\n2VQvXeMMXH8Q7zag3cvEOe/vuJj5nqOHfcBOg+tUn5O7jghciqL0mzmUi94HClGmInLvsSth\nKTgdOXE5/Q+qN9Py5K4jRnxhF0GXfKo785AyIRqA6g9/mLRLMxqFFlU2cedOi1imMoPFd/AF\nvrUOLHgv/kpoEysfI0Y1UQDXqT73iu6qXFYJtAl0eIm9W6IU5AzjfKo7QijkYxXxq5XhFs6O\nzyqFjmJGRczGY941+ZfyuLwEvOwgBBBpMYkdbZD9S4TOp36OELpXdLcEnPi7Brxrkjl1jMTk\nwL6kyvLKcikX7q7HYHFydwgxbycrJlPMGc2OXes2kY5d5A9hPDfFz3EJ3uxiQCIvYSJVMpBN\naOBZblIOz+d4AvJjX/gFb6KL/5whGpB5d3kdZ7PUgOx+SQWxW2WvNfjdfLjNwoB2i7hbyqC9\natYO7oElWSWhW73O/BguRrMveBNtXCyDeU49AHul63q2N/9VP5eDI944ReLGNNArm0NEvGzU\nEfu5TZFeswn2m7pLMxqDx0VF5Fn2/E2rbaCoqua+IGb8heFwRUy7TEk/jVoT+1tkI8/3B9X7\nIdgKNGBz8oozb93DahcYXJK66Sp6bQCKkfmO+e00rsdITC+OtJiEb2QXBRFC8fQ5/9W/XAxI\njCWtIDIq6kSBpVMWU9iqjuAPaK6M0HGrGXXVdaf2hCr7v+PbYalPx1dpt42n9oQaMaeI5GKq\nOTvZBjG/nWZd0iLo4rNsL0LIt/0rvEOSpUNEntHs2LVuE+nYRVhOw2dXxuk0QsudgYmykWpQ\nPATbMJtZwmVBoVu9blAuTIcV0FY5Y3tR+k18hYk4V4lnRzoSDhhay5O7jtDDP6QnfJqgIggz\nG2oe879rpM4Yw35+uO1CXQ1827/CnCuEk87YEhAPk5p7CGY8A1fX2Kqqx42/qxtvy5ebZcRa\nFihoCAOdDxkujtjNDflY1aSjYbS5GPNZ/qNAS11fpAx9lUatycC0sKrAjpgnU0PiUiHy2+Fs\nDwggYN0BhBCRhVQ55fNnDk+/6TH/O3r0ZoZwRNl7LW/FsR6kYlTUtfXa/438OFIx8ajN7KD3\nfxdesWMtL/kG44Mydq/o7lnOgmgm1ZfI2E80tVrtBB3Njl1rNZGOHW+llwHD5Ug08ezEddV1\n9OANaRLXW9AlWj6WuGaOl02VQkddHZ7aE4qvpekKBzfSiKuD4pEuGeC/Wid3aDXY5CblMCei\nXQlZMs2IKrCnoKG5R2HGM+jRo0U8ha2sspr9UpjBwzBILQT9bAP3oG1R+s2my9n93/BnyEfE\nqIHzcI3q90fsdYRQPH2O2KAYi4cy4L0UysGRuOhA9AuvhKUghMKxbDwEQA/ZqGsiRHwTpOtX\nCDOPqGvVhdQzUdTTFpN54z8vGyEmsoQQitgZqJz2ZeD6g2LKJrT12syoDHWtOvQz719gitmx\na60m0rHDs9wQQNS+iMYPAOeHxJGOMYwodZRtMxUVtOt73GnA5FLotQRV9EnLqZXgcBccj9jN\nFUNBJNLfKqC6XZQOxbc/AhtP5zd0HcUddlH6TV3Uys2CBqDMPHYtEEFBRrKCm9DMcdgWBYqq\ntoXqHBClW/gE5Aghj258Sk5T4YxiIvdWCd9x2IhOblFditJvEosVGJywnEpc7TunGHcLOldA\n23OKcV5Or3t3Wqac+jmv9BWP/0ZYTWd2KV3X430yNHtcC95E04M3KKd9KZBoyBb2Eu2ozWz8\nELr/uwVUN+ZvdNz6BZGpcuJNo9Yoe69l6vNqwPo61ReZQ7Gt14Qdu7zkG/TgDb7tXzlm/QLv\nPsug+ov8YtBlxZm3Qv7tQSwFxadB6FavE5bTiqiubKrfeenwuENnma7yL+XFyscwztxdcFTN\n2XnyPyFnFBPvguMDsI+Vjwnb5is8mNykHF7qawbVT1caH2tE2VkcF3ziyvLK8IByqmSggGN3\nxO5FhFBhaoFqzk56yEavl/fUkqoxmgXZ0K/lFP2ZweKddxIaMyVNYra2Gc1+Hf45oKhHILR2\n/sjNLXYxhIjsTgMy5aTPNGrNH1Qv8YMwiJH4hOU02m1j4PqDTGpahFH8TUdtZ5fmlOo6L+22\n8bx0BL5d6bYBIRSw9gC3auQ61YfJ2GNNNWtHATgjgBqwDmi7iOVhvVd099qzwd8Quxe5B9Y8\nqOEm8wk8rgPaLhKYQcSKEG+n5QihvOQbphIN45lywLv4Sc2OXWs1Accucu8xLit3DVhzl8Hq\nQRqpmMiN6Btk9KD3iXkPCEutYFiLEUIROwN5dIs5VM/ygjKNWpMP3XidRD+7os5UCQmMh3hb\nc7NTiVbzoMan46tcj+2Y9UzeIBldMoRQQNtFvP5PWE47akv4OGOQJnEN2niIG4bWpbrz/PEK\nBDf3EMwgYPv2ZOE79jnYkiXmHLuWAguLPBub658AnwFKGKpZOwyKD1yn+iqnfI7rpQojXjbq\nXtHdytJKZe81hhKql0IHhJCyL1l5wm/lfuIHc7xsVF11He42nbKcErUvgrdOUZJVgnMXlBeU\nKXutOScfd8JymnLyNl4DMUoYDJg0QV3GEp1ycbidkC/IWIIqmh7xkdJ1vRGSYsTkQrNj11pN\nwLG7jBEIpUsG8D6S0iUDdBW9CpjPsr0CN30ZdKBHfBQnG50mcQ1ot4gtkvAnUZb4rvjJ/20+\nCx0RxwXnEpHozqPbW7raa+u1Xp1fZ59lVWAXbD+fWRcM/oA+Lx2uBkUlOJxRTLwccpE5pLK0\n0qvLCmbS6mKk4+IRWOtNdnkOChNcqEERC1PmwonneE4zDMKTESNi6ur4L6TnaQsWxDT3RTDj\nGSyCowYdkCoZiAszCuCI3TwxDzQcRdC1EJwLqG4CDzri8tU9aMfcbPSQTbxj0ySuVeVVeck3\nHj/7gc3g8L/cdZ0oi+oTsTOwMXf+eRlhmZAIDcgivgnS1U+SdBh+SMC634TPTo/azF1TEF4U\n5Nn9kgriOM2OXWs1XY5dSVYJ7jQQ3YiAtQcMPWkYqcaHBVsKyrMoEuklPXSTt9MyMXNJWAHQ\no/tK0gNrrq72wfb8CqlHYMPUHFWWVnJFdSrB4fA77txjD687YNDjj/dE4P5X5bKKSbx4blDC\n6ud4NjOMgYtL8wRkExOLR46MkcsLm/0KmMGFAzwgymHrgq5yVDUo8K/9cmiv6vF2U4y7Gmz8\nHRfTAwmZbXGy0exdF7LZ47JksBYkj8HiuNWMlKALzHYifyexAIL7W84qJmRRfaIU4wVKA3XZ\nVSIpSY+V17DqXQTApbviyeDGK6N4z/kk6VDhU8cdOqvGHFmP+d+JH/xN6Mo73BcmmB271mq6\nHLvizFv49CY6dvTIj9W1at8VP9GD3veY/53evDSE0HmMBJLFcasZunog6pUFrD2gi7uch3Py\ncQJDiv71FJ6xUQeWxBKKJL8E4ikYOko8CnAHOnB/lKrXavxYkU/eAqqbZ5cVZxQTj9jPDd5E\n11XXVQtSRjUFBoM5iaql48UXoz/7LMnb+7pW26B3PprEfH2zwFxP0yIxGpJN1VeaxDXUZjbj\ndtSB5XHrF2oe1OAZ2AjgPrRRvfBVnEyUPiQPt6FT4HtPk/DKC8qKoTN372OwyMQey2nhl4/Y\nz60EBw3IysExU9KXyEWlAdkDUqCTiETZCN83DKBTwJNtnoA8Oz4L344AlL3W5CXfCGyzoALa\nPgaLBNnI49v92a4SVNHxslH3oN1N6Orl/AYeFOYZPWYLfgouEbRewwsBP4NpZseutZpAKBYn\nRSSuz3sv3pMqGcj+twCcWYUxXcbjCmZAD/tAmGUnQRXNo0r/g+odufcYcU7exfh+lTO2C48q\nlUS57rnoP3hLj/nfEU/q3+5lRAphI4BjX/glqKKVUz5Xzdnp0+k1XY+SP6hewnzCkRaT0sIv\n0+O2Kvusoyd8mi4ZIPIhhUwXt02ECaboxoznAVvbjCtX7gjf+SYxO7v0Zv+xZhBBLJ4opjqf\nspjs57jkpKCONo7MqIy66rr0U6k+nV7LpVxuQecibLEHAahBkZuUo1Frcqieho74zP87zr21\nrp25etxqRiU4PATbLKq3ctD7sQcjtfXaqP0nAtcfvHbmqrpWLT4M6tthKb64JQCPHgS6O6Jl\nx2fxyFYYOU1cJBMBhNnM4qlcVIMNIx3Os5O7Q1SzdgR/QAtUK9KDN+CnOGozW/z89XB+k3us\nFiRTYKjZsWutJuDYndwdws3ivAftvF75L09/IlUy8KjNLN79dFkyWPikuEBFBIcEXMDCtvmm\nSgZyXR+ceRwBPAD7BI9oNlOhFqyUvdfq7ZzIYERczSaqliEAetTmRM+YW6Qs1CN2c9nVdaLU\nGAuBErMGoBI4QV5DkSIdYvSxvBFawGNT9GTG80C7dpfFTK7GWE3NEwB1s//SvzWMp43sDbkC\nu2vBKlo+Vjx3Xcxvp/1W7s8XkQGSIh2SbPgzpw4seTSoNQ9qTu46ouz3DvvWaACKHXA9SA0q\nrVXN2hFPn/NwfjMDY9EiQguSiwFi/ZvC1AKPHisjLSYdsZ/L0BojhDRqzVkdymk88PSc7hXd\njVRMZPemSwawgWbWcpNyVDO/8un4Kt4bPeIjkcMuzSnFb4AzMMLs2LVWE6Y7yY7PUg54N6Dt\nItr1PUYL2afjq8znTgNQGVS/y6EX8bUxBMAy6+qyqP0nTlhOKwGnLKqPR4+VjKizGCMSwvHA\naMVo67UXfOLCtvkWZ94S0zMeIVWDgqGmZKw0p5RZeLuVeQtP6a0Ba/FfjQKPUVaKA0cW1ceg\nRyQXBeBM/KozDh2g3EQ9mfEc0FBY+EDk/DLONBotRZnjsC0XKlglsFu8V/cA7LnxmaYAoxLE\nWuhWrzzS17txUIPi2Oe+oTaz74JjJTiIXLrTS4/As4zTafSET+khG1maLY1aU0x11nuiWPkY\nbj+4Jth56XBuA/9VP+N6mwySpMPEywSEbfPFeygHR7Nj11pNJEExY3ggX9lrDZG1BP+wMInl\nX8oTk/mnnLzNiM4rSysvcaKoWpB4dV3Bzg166CY2EJwqGRhsN7eR/Oz+jouJCoARVtO5v6ge\npLHyMYfbLhRZ/FtAdeM9rRqASpO4ejm/6TH3G2JCsRH4/+3dd1wT9/8H8Hcme6nIEBAVVxUH\nqLi1VetGtK7qV61KW627dbZ+raNaR6s/Z1ttIooLrXuvCq4q4hY3iCBTWbIh4X5/XM33zIUQ\nIBgTX8/H+w+5u9x9ct545+4zGtJ9fawG8Y7i5Mln+jwPeYqKlELhS4N/TURJYUb5c2jJXWqc\nSE6pJQzPqks8FNSpjPKxV7xcsgh2HpLw8MWusRvknb4/sXR/VPgTfV2yGKIiEsu8J2p8yaM9\ntg355d7p24mPExmGycvKu3HwmpZRHIJ6LcrmVBnaZ9NDqVAW5BboMra4Wq04foMGhvPQ5EVk\nHP+pSoSw8SHLrjKfqbpndQzD3DigoRbmTaqPxM5YlSmxY7tt5EYm2fAHpUik6mrNfCro0YUH\nsrazZA3Hb+72I//4KyApt9elnVUCyrR1bnctORk5srazzpi1U7Xef041ZK2mn9P0lraCIa/3\nZfDA5fzpabzL7rbqgxidO0NmiI6bd1L1eJdDltwBuW8KG5apI4OS4jr56Ht/ICorBIKsggKF\nHs9HNYcOPbWyQqJvFJGXl1ekryoZaqG9crD2KCTJlR0XCnILzq4+yh2+shxvctXigrjl1v5L\ng12GyuuMPb3yiLzeV2VdQw5ZxpEL+wWjyYNt5ZZLFltch/HTu3unb6tVBGeIZL5T/9HUXlBt\njylJuHeKnGEYpUIpazPzjrCBxl0a+ttJdlshX2nouiVU4qcqzNk1x7ZX++yoxcdB7iNKHamC\nX8KZ1AmJnbHSPbFLi0/VeJzt+GIt96GdgkTBA5frsYTbh6/idpLEf3j+j6h57J3nW/r9LO/4\n/bn1J3RZZ1p86mavsU8EnuxZGi3wkLWZyc66uuvS63fSznT3uD8Yhtlr05M7UWPDi1dURf7J\nfxMfJ+jym08V8eR82LJLNu8qs91x0A7Hzyo4zmsm2Vb+HkLoJ4YMCdPj+agmNTVXKo02+HdE\n6BL29jfXr7+tsT6WwePgnO1FBUX6fSJYSBJ55x+4h6taA9tSI4/MtbyZ4Xd0uqXvYv5izwXq\nD0TY4KetW1yHMSX0ls/Ga7JWNaHY2n8pf4Froibs3OCBy7n3izSyv7j5nJYT+cbBa6rcTkGi\nHVX6C0mIxM5YlemJHb9iWS5Z5GXlRey9sr36wDPStiEO/ieW7tdj8eIfxL/S2gd6HpmXtVfJ\nzJTMG5oawMo7fs8wjKzRN3q8spQUqvEHGYbZMWJ1sMvQra7DNPZLqYp/RM23unxe8U0rSSj3\nmXrql0MHrD4tx1sJNpLIqfJ3EkIPUbt25fZpt3LlTYN/R0SZolfbw+VoqVrZEdT7p8Na+zct\nX7wm66u7Lh1duOecxE+txV5JkUVW25wG65JiFpB0z4RN3NNB3vF7/mIaH4gcsuoSKVAfwLeA\npKkvUvm/xlUh85uu2tatI9f5SSfbC2xRQVEyr7cXtYF6+ZQK5db+S/dZ99ht30fWdR4SOyNW\npsSO34vvrhLGObl15Lqs7SxZ8yla+tfWhcb2pzeFH+2z6XFB3GKXQz/tv0I0kvlM1XjOsD0Y\n8+ur6jHiyfmcxG9b9UHnNpxUK1VJw+NwQ173S5n3xMeCWvlklkZ2YZJWZzR12qxLnJW2USqU\nKc+Sy9TyXxXB9J9K20kIfcaAAaEVOQFLNWgQxpkwmmhE94Jo1D/U+oj0451VAk5L21bk/ake\nQ8u7iIqXcIvbcC2pkirCRU1krabLP/nvjUPXyvS2mtu0IvS3kzp+6oR5R43X3h0jNdSlLibB\nabN2O0asVjv7Ntd6q8FfLLmyNfAuyP7mrySd7LRXUpK1+JabKf6CV7HGq0yJXV5W3janwWx/\nHEoShtj7a+xMWP7Jf7kvZ0tK/nShcfCxiNK6U9FO4+hh7MWlILdA1npGBa8j3OCeJ7eFDULs\n/VVTLop9bx+7yRYpMyVTl9es/J9c+74NKnfZYgWuoRI/7V2xa4wYqimhQv3tJEQlhlCYUpGT\npVRCYbLBvyNCl/CjK2qZhF6q276DuCzyeSioE/92F3G6h8aBH/gh853GHtK612ZmI5Gqc8+I\no+a69r2Swmv6oCDR48uP+M/hYsm1pBNw+7BV+60+PS1tF1RzZMzNZ+zEGwev8TeXQE5aTuRb\nR67zO8lHYmesypTYsdLiU0N/O5kclaxxbsTeK/zRoDd/Or98xYs8e5ffr1tJY47paEe1ARpP\nsyhBTYZhkqOStXQ4whDlk1mw85D9Vt3Zn5IKEp2VtpU1HMd/rRkmbiWv9+Ux88577Htv6fcz\nv97uRbHvzi/W7rbrc0m3flKSqRq3d3KW9tJWRsRQzXe7QUSFonPncxU5X7QIDLxg8G+H0DEu\nUrtK30blxLk3DQLURo/MJiu2s49CkuSW3DlotMBDl63IfL9lt6Kxnpz2UP1EZ0rICzX2Tsq/\nZey3+pRhmMO8H9tbagzXchoW5Bbw28Dy+8baZ9NDy0o09rqPxM5YlSOx007eeS7/+NB+SJWy\nwoZvjRUYQ25R4U8qUsKdX6zVeHKqBu+7deT6fqtPk6maxtFyVY2SoiOiTizdH3vnOftnQW7B\nzioBqh9bzwTu3I+fNOtQplEiSgoFidS6nSzpzXKlhh9deefbRJQ/xo69UJFTRqNLl16gU2Jj\nCSEp+b+331nEC1ziK/B08Jyk9cPzD7YGLD3201555x9OS9tdEzXhpms3hI22Df5F40vbaIHH\nMd2G1thn3Z09sM+uOcafW0yCXLK4LWzI34qCRCnP/veYIycj5z4vqdpt35e/znuCelvchrPP\nyYpJsM+6e/yDeIZhYm4+O27WkV1GScLd9n1L6rvkn23n/5a0Zm86RSS+JPJR3Z6OL97L7Snm\njqC+9vtmUK9F/BIisTNWek/sZL7T+MfHMd0GlihJyFe/77brc9y8k7z2GPbQr6Agj5Hcx90F\nJAmqOVJtPL7Hlx7xv0gRibUPhvvowoN90zbL28/mfzZbU4d/WqKkEcDyyYzbdl2pUPKvI5Ud\nmyjw3W4QUcEoDA2NrfiJo5Kenmdu/tjQXwqhYxQTMQllbBCq7xIIroqa7rPuzu3iQMeI4bQq\nTSLHE0v388cNjyvh26WRvY4ds58XtyzILTi+eO8J845qswpJsnfKvyN6HTXvrDb3rLSN2tkh\n853Kzf8KSLrnm0386/le254Mw6Qnpp9bf4J/X7tx8Nr+6VseXXhQ0jkY/yCe/zDyFVVRjW/+\nIjJO3mHO5tqjt/gv0dLxnmpz/Dp/SOyMld4Tu6ML9/DPGXmDr/W1fn05v+mMrM1MWbvZ+74N\n0vh76FXsS35dh2yy0jJgn0qYpqGvdWyTpYrokpusbhvyC3dzGuvbVmpcoPbvdoOIikazZvps\nRfHjj+EG/0aIMsVvNK7St/F28AdFCHHwZxjmxM/7ZY0nlCPDY+MlVYnVNGxjSXFf4CVrMlHV\nvdzLErpZyCULjb+l4wSuu8b+OzhYdESU2miw+WR2ftNZ7qmhVCj53UeESvyCXYZyp6STXQW7\n8Zd30tAClyHa7PlF+VYo85nKveX9isYTxkvviR3DMLuq9OMeZ3cE9bU/5XpvhYlbqp0zamPa\n5mXlbR++SuYzddfYDdwHfo8Etfnn2wtyKekhXFljx8g13GJc2XGR37i9UgMdFBtdWFg8LCrS\nW7fhnTqdM/g3QpQprCnrGXlqnPdueu5kiLLJUnWdPLf+xEmzDmlkH0cuu6oEyNrNPmnWXpfm\nqwxRfhnb8j8IjUyOSj7yY8hfk/68JNJ14Ec2bgsbqg57WdNJ/AVUfaCy/tl2XuMeLsgtkHee\ne07id1P40R673lqyugehkbo8PtjqOkxjgQ9bfFK+kzoq/Im80w/bHQdur/aZrMs8EYmQ2Bmr\nykjslAplUK9FBy27HjfrKG/wte7jwL5vIvZe4aZodwT1ue9Abxy8xu2I6Iaw0eNLj9hZRyw1\nNDV9VfaRfDQmgq/Jmh23V0Vjt+aVGjlkKaaid7tNREXDxuZOcnJ2xc+LXbseEikM/nUQZYox\nJDN8IYieXH6o8aDaUVVDm7aSWoaV6YkdQyRv8PX5TWdexb58rOknt/bIJJv/HfkO/fgLbHMa\nzP0ikWfv8pdJpmq6nFky74lsv615ZL692mfab50ldeAQ7DJUl21x5WTk7HLop3pcd9S889OI\nJ4RXscarMhK7ckiLT5XXGfuPqHmEsPFW12GqFgmVSpdfRVmpWcEDl8uaTNw+fJXa8vxxxlQ/\nlY4v3qv2Gldjqyi10Fj5N5UcuD2h5JF5UM+F3GI8vfJY49r09XSwpGhE90qaaWV1n5D2vZdR\n8ReyN24kiUQJBv8iiLJGKOnUhqCyQ2MP9rvGbuAvubn26KSniRqvYzI/9VHLVVHSdU9BooNW\n3cpR4GtCb1U5NY4JIWs+Re3r3BHUV1tm/5uWGVrwEzW1oWPVPL70iP+ippAk5RgjIMjtP2rr\nOWTZBYmdEXsfEruigiK1l56RgrqV9/Y2KzVLXmfsC3JWkvChoE75umJ5FfuS3/NcFlmpXjTs\nCtzwTODOXlDuCBscsSilc6M4co3VNOSzKp4J3GUNx13dpX6maeyLMpcstvb7Oacy28G5UnxJ\nMxs2PF9pm0VUKCSS8v9kionJcHFBa2hjjRgq5zAz+o3Nnl8cXbBHXmfsVVHTe4J6f9n1PvXL\noeO89goM0Ra34YymbkevCxszDFOpF7e3iuG/RHUKXN11Sa1qYDrZcfs6YZ1eeYRbFe+OsIEu\nPTnc5fW3p9belu/owj3cETJekcOWfj+X49R+zrv1FJHYkiyR2Bmr9yGxCx6koRdi/s8gfdnm\nNFhtW0G9fyrrSh5deMAvs4JEavloWnwqm+oFOw3hL6+KPDKXNZ9SUp0JVWztvyzYeUgCOeWT\n2RVRs78myRiGKSooSic7/sInzDocX6L+4FBfEUkfaZlvZhb1Ti65iHKEMjMzv3wnjofHJUMX\nHlH+OEAaXiO+D1HSMzZ24NT0xPQ9tr3YX9FFJD4tbZeemJ6VmlXZbyQYojSySyLHBHI6at45\n7I9T7Flw+e16Ly+pKjvYg5rkqGT5J/+V1/ty64BlpbZIZRhGqVDmaeqK79Qvh0r97IPQyINz\ntof+drKkXlG0C+r1k8aXRV5UE4mdsXofErvNNUfxj6q/bHtVxrbS4lP5T9puCj8qx6qekfrQ\nztxqtmr2TNhU6nVk5xdr91t317KA2tiCBSRlR2zT2Hcgo2mQaU0XrzLX/GOIdtDQSr6oIior\nBILMdetul/VoT03Nxet1o46WFF5JP/MqKbZVH6R6AaJUKLkPveS1x5RvnaUOUFZMghyyOGrx\nsVrF5VdU5daR6/tnbOV/JMjtP2W/e2jAf4Fb6hO7itN482WIssnqvW08ISQwBsVVHfgTc63s\nKmNbETsuikmhNrF+8bNyrOrysO+UJFL9WUSSqCkzS1p44LrAzfW+LCIJ+6eCxPxlJPtPBGSd\niNjzz86Raw5af8pf4CPmCfdPKRUql/5BRKPPLZI3mcRfvqXyTqnfwoHSS12Gz4WSyvEpeB8w\njO3Eid7Dh18o06du335Jmg5a9jkSLQAAIABJREFUMBbXqOVI2lpMRnNbHJ6y56ztJ8XKYiIS\nioQeTT3l7Wafl/o9FdYaHS0v3zrvCBtomZtO9o8v3LdkcvO+/E9r5U3urKqUdjdwedrZG/xP\nDXnx1wHr7tf3XS1fkVSutQlQm7LXobejZ/UKrlaL+3/fG/F8m8ZZIXWHKUlZeZuuEENnlkag\n8p7Y5WTkyNrMDLH33+o67MiPIVqWvLQlVK1X9CIS75+xVe9FYhjmRWQc/0fbfYFX+dZ2fPHe\nvbY9L4p9d9v1Obf+RKnLX911Sf7Jf4N6LpTX+5L/I0k1cg7DMPumbeb9hNLQv/ETQa3MlEyG\nYco0anXFQ0Zj3uHWEJURyvDwRN0P9YIChUCQY+gyI8ofzemGxpd973lsHbCMPQK3O6p3SlyO\nKCx5SO40st85eh27LY3D+fwtbaNltLHnVEM1VGu5yZpPYdtDZJPVNqfBld1N2I4Rq/lfJJ/M\nZK2mZ2Vktacm7+cTOyR2paukxC4tPvWGsJHqWFGQSHuduaBei1QVxXLJovIq2DEMc8iyq9qh\nLPOeyF0g8uzda3v+USrK2elXQW6BvOP3u+37bqs+iK0Gx7fv2yD+GbWt+iDuMjLfaapeneLJ\nWeareeiwFKq6udt8/vjNlReFJGlL/OpWuvR/UfyuyogoPby9w3Q/qnNyCpHYGXWcoS6GL0TZ\nY6vL5wzDXNvzj/bFKpizPhF4cqvKaaz2vceu99Mrj19S1ZJWoq9++KPCn6gNg1RxiY8TZW1m\nBrn9R95+tur17sE52/nf4pLYl2GYTS2+ZdAq1nhVUmLHf3NfQFJ+6yGu6Iio7cNXbe76o2pE\nlEryIjJuv3V39rldHpkH1RypyuFOLN1/U/gRW+AYctsxYnVZV56TkXNZ/FYHmBr7AS8qKPpb\n0pq7WBrZ3zgQrrZYVPiTXWM37Ju2+VXsy7ysvOvCxhovKIUkKak7db1HElUfRLv4c2xtb5f2\nUWR171cIBK9zcgp1PLAlkucGLzCiIpFZxpFv3pNgr59b+y/Vvpgu/UlpiWISsJ2DpiemyzvM\n2e44kN8ibfe4PxiG2T3uD7XBJ1ShS58mBnF+05l4TpljyfXKjosMw6QnpvN7BJQ1HM8wDNuN\nMxI7Y8VN7CLP3pU1m7zFbfjmT+eXr32NynnemA0MkfaW2LLWM9iDL5ustlcfWNndGsc/iA/9\n7ST7HpMVHRGlNuBgLlmcXXOsTKuVNZmo9q0VJNL4ljb+Qfy26oOeU41kqnbcrKMub3Ij9l7h\nD4bBxh1hg0q6sAY7D9lr0/OEpMNS+rYJ3RZoy8/eGhK+Ro1/pk27LBBkVE65EHoIG5u7pQ5H\nUVCg8PYOM3hRERWMkoadeH+iQFNydnD2NoZh9k/fouWDpTaJ0CUi9l65d/p2FGcgR1Vbk0yy\nkbWarjojXsW+DHbW0MsB24yXYZiza47tt+5+S9jwlLSd2vCPBsHvwT5M0oqddXD2Nm6eesDq\nU7a7VravLiR2xkqV2O35ZiO3h547gvoV6SWY33kvQxQ8cHlJy2/u9qPawrq0ig3q/dNxs47/\niJrvqDZA++NAXWzuOk/DuVpjeJlWclRTf3VqY84wDJPyLHmXQz/2V2YWWcm9AnV/8xvkPoK/\niZNmHc5I2/Knp5H9A4GXLte1C+IWmz+eq5baPhF4JkclMwzj5HRVxyukSBRnbX23d+/QzMz8\nKlVu6OOCj6jE6N//nJaDLTMzXyJ5bPBCIioea0jDcFgGCf5g8wxRIUn2fLNxc63RqnRKQSJ5\nnbHscZgWnxrD64XgH1HzvTY9D/Kq1pQjEqk6wzBHLNRHDHpG7od+2MFeA7nunrz1+u0O7QpI\nenzJPoZhji/eq1YxZpnbsJCQkPT0dPazSqXy6NGjv/zyy65du7Kz9TASjHYpz5L5raELSJqV\n+u9ruuSo5G1DfpF3/J7bs/EJsw4MEjvjxSZ2qSmp8bzHy+yAzeUjrxuotrYcsuSOx6UmgveS\nsZgEQ3sMGTx48O+//15UpKHCQZDHSO7yr6jKjYPXyl1ghmE21x7NP+EPmJdt3D1+BT6GSN7x\ne7XF/rLrrbaMrMlEjSvk2z5sFX8TshrDGYY5vmTf5tpjnr750RkpqNu/ehexUDxM1GG9eY8d\n9v5aLm1sA5eLm8+dNOvwmqwzyPawxSdnZCf+/vvvW7du6/7gTSh8xZYzNjYTr1/f/xAI7kVG\naj4xk5KSRKL/M3gJEXoJS8q5Qe9u7MGbwoYlzeJ3QVdMguBBK9ij7uDi3Strjfq11qj9P+3i\nHo1HfgxhHyOxa9hRdQD7Y1jtRqA9cjVVxVOQaGv/pQzDvNJUoUXjIwO5V6DaGmQd5rCzQnkP\nNXLJwozMHB0dQ0ND09PTW7ZsqWrf6ebmdufOHfaDmZmZZ86cOXHixKtXr3S8F+hCY3vBIhJr\nb5lxaN7OtdQRiZ2xYhO7o8v28Q/opwLPcq82KzXrothXtapCksg7vZXcHD9+fOTIkX369Jk/\nf356enqGpvofLekj9ujv2rWrUvnWA617p2/zf4Xo3vVdUlLStGnT2rVr16dPn+Dg4GvXrg0b\nNuxLh578MvxIncPCylDHnD/WTSFJ/tl2nrvMq9iX/MI/EtTWcRM5GTlXhd7cz6ZQ1e5NuimV\nyuzs7LFjxwqFwupUzU3sIhKJuI3EO3XopFaxj3th4r77vnbtmlwu79Wr15s1CIjSdL+qnzgR\nzTDMX3/hcZ1RhKJmzTqFhRoq21laWhIlGbp4CL3FMpqpx9Vp7yJY4wuEkmK740ClUhkTE/PH\nH3/Y2Niw1ysLC4v169dzD8j0xPTd4/7Y0ncx94q65lPNvXhqjBvCRrvH/SFrPEHW6Jvddn1C\nJX5/2fX+a87WxYsXjxwxUuNt6NqefxiGUT1vYxgmYu8V/gWcHSeDYZg0suevpBnVJyIXF5dR\no0ap9d3h7e3NMMz+/furVavGTrG2tt64caOOtwNd8HvI446TplFBQYE92SGxM1ZsYndw/k7+\nsRhDbhVZc1FB0Za+i7e6fC6v9yXbbXdsbOyoUaNq167t6OjIPbI9PDyuc5rQslFMAgeyVy0T\nHBzMXfn24RqeWt0V1NOlYMnJyS4uLtwCCAQCIrIgi7v01lvLV1TFjVzatm1bpm993Px/YzIW\nkVjWbLLaMufWn+AXvpAkureE6u3X63fqEE9OaWR/kFo1oNpE9ODBgzFjxmjvAOhw8CH+w1GG\nKEzckl1zXl5enz59NH10v+7X/O++u5STk9OnT1+iVP3dR1SRS3SuElb7IUfjiRPfemD88OFD\n9qQgQktYo4h7uvxPfU479LjJP5tPSSmhiWgG2W4rS+8kf9r2VbspsIRC4bfffqv9Cda0qdMO\n01s1j5UkvCVosN/6U/6GDll2Vfv4kydPqlatym7uCKnXYH5ONZYtW8amXA4ODgsWLCgqKgrq\ntYi/5gviFuwKHwtq8ee60b93HI1f8/Lly1ZWVtwpYrH46tWrOt4OSnX4vztVHSwwRK/JutTx\nZAsKCgivYvWluLg4Kirq9OnT+/bt27dv39mzZ2NjYyt1i2xilxSbyP+dsd/qUz1uKDU11d3d\nvaSE44ca6nVRt1E77gITJkzgru3g7G38k+ei2FeXkkyePLmkYriRSwi1eU3W+WR2hpo3pXpE\nZGlpWVxcXKYvu334qi1uw+X1vjy98gg7JSoqauLEid26dRs7duz5U+f5bbgiBXV1X3/dunU1\nZF7790skkpK+Gksul2ts4r53qpxd84wZM0rcNxT79ofyiPYSZfMv1CJRb4FAIBAIiEaWfDEv\n91vaKCIiitHfHQpRh4g6d+7MHgM//fQT5/8do8MZRXxN5ENUSst0C8rl3uBVkU1WZRqhK5Ns\nQwI3MAyzufsC/twiEq9pN2Pn6HW6r/AX6qTlqlWlSpXr16+XdDEcMGCAmMQTqOMhanWMWkyn\nTuZkvnTp0pCvfudvSNZ4gtrHe/bsqdpQbXLnpqq5ZPG933i1wsybN2/bEA2doZyR/vv7f6vL\n52qzrlFD1cfVEjjWf//7X/7E2bNn635HKNWtI9eDPEbut+6+ueYoXfqdQGKnH2lpad999131\n6hq6mfbw8Fi4cGFubm5lbFfVeGKL/xJutvGCnO+evKXHDS1evFjLqduqVStZs8lsFYcCkv5G\nHa3prRNg5sy32h+kxadqaKf90XhdStK2bVstJSEiAQnEnE72a9WqVcHvfv36dQsLC9UKRSKR\nzLavWuHlb6po6KJv3778Yv/999/avxcRnT9/nmEYed1A1bhqChLJa49Rrbl+/folf9rq449D\nHBy2En1H1JD+7cL+v7xLXAYRdyiRrkRnifLfuo/QNqJF5b2HrSAioh6Vdo/80OIpkaDk//RJ\nhi6eKUVh2T+iJHpd2jIxROb/XrrIk2hFyUvmfeu3jvsbPpLq9KaW9mTXjrxz3u4CXe2nfhGJ\nZY2/kTWeENRzIbcxQW/bDiHUJpw+ukYND1KrZdSpEXndvXuXYZhgl6E6fsk+1LLkI5DozftK\njebNm8df/siRIwzDHDPvzN3KXao75asp8fHxqs8WFxfb2tpyP+hA9rOo01/W3YPcR1zddUnt\n3Q4R2dnZPbr48DVZq30FVcqYmZLJfWlzj7zqkif7WbFY3LlzZ7UVVq1ade7cufyvMHr0aN3v\nCHqHxE4PEhISatWqRUR169b94osvfvzxx+XLly9fvnzu3Lmff/65q6srETVt2jQtLU3vm+Z2\nd3Ju/YmtLp/vs+4uazg+/kF8qZ8tk8GDB2s5b7t06cIudu/07Uuhl8Ri9cGLzpw5o7ZCtXba\n+627s+20S1XCq8YSzZgxo4LfvUOHDmrrrOHoGuQ+IpUcGKJYcpX5TS99LRyhoaFqu2jgwIFF\nRUXc9JHPx8enoODfXRT620mZ7zSZz1S1/lw0vilQSUhIiI2NVdUFISIika3tWc717TWRv6aP\nSok6En1GVI8zcREn4eP2b1zMWdt0opucWfve3MOIqD3RYaIHRKeJThEp3yxznOgw5754gSil\n5HvKa6L9RFmVdiMvqJw16ytSiFpp+R8nEhCtMXQhK++/RuNjY/ZAKmlg3GJeX9yJnBqod4k6\nEbUn6kI0iyiSs4k0ogCiUUTpb6bkE+USvSQKJtpAdI8omSiKKIroGdE5oolEtYnERJ8QHSRK\nIyogekl0gOgGkZKokOgAkTvvv2wPp3gKorVEU9u2XRcdnc4wzIQJE5pSvQHUuspbP8CoJtX4\nnTpcoUZHqeUQauNNdSPo3wYQr6jKwrqa8wx+9Q9nZ2dVc7cRH302nTp9T53XU8f95PcHdWhH\n3r9SJ+7uk4s6az0C/5WSkqKxAImJiWoPRFq3bs0WIC8rT9Z8ymmR3zlqtoA625A1ETk4OERF\nRbGfLS4uVr2H5WKTv9evX2ssSUJCQlDvn7h58AmzDmp3n1MrDv7eYXYvy7bcZwRLliyJjIxU\nVSIkIpFItHv37r179/K3snp1mXtR1SMkdnowduxYiUSye/dujXMVCsX69esFAsGUKfofj6Hy\nhhRTM23aNC0n7YoVK7gLr1ixQpW4iESiuXPnalxnclTytqEr5R2/P7XioO4l2bhxo5aSEJG9\n/f/q9g0ePDg/P78iX1yhUGjMt549e8YwTLm76zty5Ii3t7dIJKpSpcqUKVNev37NMAz/kb6D\ngwMRCQSCXr16xcTElLpa7osJNR999BG7THJy8qxZs3r27Dlq1Ki///6bYZhVq2726RPaqtVG\nImft+5aIeFm7C1FVIjOizkSfETUlIiIbzqpERO2IBhN5a12xC1EHevPjmMiFqA2RKk+1JapH\n1I1oFFEg0SyimUS+b6/Bi2goUU+iT4hmE80hGkjUg6gXkSNRW6J5RF8T1SMyI+pONJ1oLdHv\nRL8S/R/Rr0TfELUk+oao3ZtNWxNNIAomkhGNJZpENIRoAtECom+JdhPtIjpI9JToKdF0IilR\nA6IZRAeJ4olSiV4SXSX6gmgu0R2iDKJXRIlEOUT5RKlEUUSXia4SJRA9IQohSiDKJyp8k1UU\nv0lHioheEZ0gmkE0l2gMcaqxalWTKIgoj0j5Zm1sKDlTFER5RGlE6UQ5RDlEkURRRPlvyplF\n9IpIRtSP6DTRE6LXRLlEcUQbiY4TXSCKJLpEtJRoIdF0olFErYimEo0imkV0iugy0R6i+URf\nEXUi6kb0KVFVokZEo4j8iZoQzSDaSbST6P+Ilrz590Qib6IWRD2IenIODPZgG070G9E4IikR\nEZkRiYn6En1HNIjIjag30QSiz4hcieyIJhEFE/3MOd7ciVw17bpaREOJ+hFV4UysqvOe18Kc\nO3qvRCJhf5W9uXz1IPqJaA5RE3aBTZs2sefvb7/9pnF1b2pVvsWT3BqR17CBw9Sar6m8evWK\n+5jfysrq1KlTqrkBAerjnxJRjRo1OlLTxdR5lXn3P4cuHzRokC7fNjGxxBHwHj58GBAQULVq\nVXd393HjxnHr5GVnZ5ubm6utatCg/43xw996w4YNVXOdnJzU5trY2LC74saBcFnLb+VegbsC\nN5RUsJSUlJkzZ3br1m3o0KFHjx5lJ8bFxX333Xe9evX66quvIiIiGIZRKBTt27fnbqVBgwbv\noCcULZDY6YGzs/OYMWO0LzNkyBB3d3e9b/qdJXaXL1/mP4djDRgwQKFQqC3/4MGD9evXr1mz\n5vZtPQ9EUVxc/PXXX6u27ujo2KhRI9Wfvr6+8fHxERERBw4cePjwoV62+PYjrn/ppU276gkc\nS6FQLFu2zM3NTSAQeHl5yeVyhmHi4+PZtE8Xd+7c0ZiGOjo6armwsk6cOKHx/1fNypUrVVex\nevXqlfpmHAA0atiw4cmTJxcvXrx+/Xr2Zxv7pKpVK/WnsBYWFqrHVK9fv/by8uLOFQqFc+fO\nffDgAfdhEhFVqVJl6dKlpdbiz8/Pl8vl06ZNW758eVxcHHfWypUr1UoiFosfP36clpaWl5fH\nLnPp0iW1ysH8usJ165ahCjLX5cuX+futZs2aqgUSExO5e6Nq1apsssVatGiR2mdnzZpVvpJo\nl5WV9cMPP/j6+jZt2nTy5Mn67fGkHJDY6YFEIlm8eLH2ZebPny+VSsu02ujoaEdHRwetLC0t\niejd/Dj4888/VRUaatSoMWvWrFWrVl24cOEdbJovMjJyy5YtBw8ezMzMLC4uvnDhQlBQUGho\naEk/TCtixIgRalcHPz8/vW+Fi58o6+7x48djx45t3bp1jx49Ro8ePXny5D///FN1FdYiNze3\ncePGajcMtccAfn5+bM8a6enpycn/1tRZu3Yt/+ILYCykUqnGN3qVytLSUu13nYpSqezdu7fq\n1LOystq+fTt3gdjY2OHDhzs5OTk7Ow8aNOjFixfs9IyMjOnTp9evX9/T03PEiBHPn5e/j3pW\nYWFhx44ducVeunQpf7Fjx455e3sLhUJbW9uvv/46IiKC+2PYysqq3LeJe/fu8XedWo29vLy8\noKCgOXPmbNiwITX1rd7dFArFvHnzrK2t2R0+a9YsjR0DmZ73ObETMAxTiSeW/nh6evr5+YWE\nhGhZJiAg4Pbt28+ePdN9tcXFxefPn1coFFqWiYyMnDp1akFBgVQq1X3N5fb69etbt25ZWFh4\ne3vzn5CbqvT09E8//TQiIoL9s06dOseOHatXr572TxmjZ8+ejR8/nn0X4+XltXr1ah8fn/nz\n54eGhkokku7du8+dO5f7plvl7NmzS5YsefDggbu7u7Oz86FDh9QWcHR0HD58uJ2dXURERFZW\nlqen58WLF6Ojo9/J1wLQ5o8//hg2bNi1a9eKiopsbGw2bdoUHBys/cJbVnXr1o2KiiouLmb/\ntLW1jYiI0Ng6XuXx48cXL160tLTs1KkTvxHAO6NUKnfu3Hn58mUbG5uAgIA2bdqUtGR+fr7q\nppCWlrZp06ZHjx55eHiMHTtWS48KpW69Xr16aheKWbNmLV26VPeVFBcXJyUlOTk5qfUMasIK\nCwvNzMwuXbr0Hr5RMZrEburUqWvWrFm+fPmkSZPMzMzU5ubk5CxfvnzhwoVlPRx1cfny5Xbt\n2r2zxO6DVVxcfPr06YcPH3p4ePTs2dO0k9qcnJycnByNTbx1dO3atR07doSFhRUUFDRo0OCr\nr77q3r07f7GYmJjjx49LpdLWrVt37do1KSlJNatp06Yff/zx+fPnMzMzX7x4wf4AFQgE5ubm\neXl57DI+Pj6BgYGTJ09W3YPr1au3YMECtqFSr1692NrTAoHmK0lJ08EYiUQiCwsLOzu7rl27\ntmzZcvfu3bdu3Sqp+rynp2fDhg2JyMXF5YsvvuC3jkpNTZXJZL/++mtKSopqYuPGjTMyMl68\neMH+aW9v36JFCzs7O0tLy4SEhOTkZDZ7u3PnDruAo6Pjtm3bbG1t3d3da9So8fLly/Xr1ycl\nJbVq1Wro0KHsyxYo1bVr1wICAhISEtg/u3XrdujQIdO+AlccEjs9yMjI6NKly40bN2xsbFq1\nauXu7m5tbc0wTHZ29vPnz8PDw3Nzczt06HDs2DH2mbAeIbED0/Do0aNZs2aFhYWZmZn17t17\nyZIl3IrPjx8/TkhIqF+/vqOj4+PHj9PT01u0aMH+iHr69Onu3btTUlKaN28+bNgwbv2ely9f\npqamNmjQ4Pz58zt37rxx40ZBQYGnp2ePHj2GDx8ulUpXrFhx7NgxiUQyZMiQlJSULVu2xMXF\nKZVKoVDo6Ojo4eGhVCodHBwSExPT0tKqVq3at2/flJQUS0vLpk2bXrly5cyZM1lZWRYWFiKR\nKDk5WdWWUOMXZLsGVD2z+WAJBAK2a8mioiKBQODo6Ghvbx8fH89WFK5Wrdrq1atfv37966+/\nJiQkSKXSVq1a/fbbb0ql8sCBA9HR0W5ubi9fvkxKSrp69WpCQoJSqaxZs2ZISIivr1pLGmIY\nJjg4ePv27Xfu3MnMzBSJRO3bt587d663t7daHxlaHD58+PDhw/n5+e3btx8zZoxYLGar8FpZ\nWbVu3Zp/PS8uLj558uT9+/ddXV379OmjVukNyic7O/v48eNJSUlNmjTp1KmToYtjBJDY6Udh\nYeH69eu3bt169+5dpVKpmi6RSHx9fceMGTNmzJjKeA6MxA5Av3JzcyvyNCUnJyc/P9/BwYFh\nGKVSKZVKk5OTHR0dhUK240AqKCgQi8UZGRmPHj1q2rSplZVVenp6YmKivb29SCR6+PBhy5Yt\ni4qKQkND8/Lyqlevfvz4cRsbm8aNG9+8eTMqKqqgoEAkEj169Cg/Pz87OzszM5Nt980viUgk\nUiqVYrGYrXhaUoG1PLkUCoXm5ubu7u4KhYJNZ+3t7Z2dnZs1a2Zra3vjxo369evb2NjExcV1\n7NgxOjra1dXV09OT/WxxcbHqK7N/JiQkODk5ldQLN5vq8d94AEBZIbHTs/z8/Li4uKysLCKy\ntbX18PCo1JQLiR0AAACovM+JnebONd5z5ubm2qvEAgAAAHyAhKUvAgAAAADGAIkdAAAAgIlA\nYgcAAABgIpDYAQAAAJgIJHYAAAAAJgKJHQAAAICJQGIHAAAAYCKQ2AEAAACYCCR2AAAAACYC\niR0AAACAiUBiBwAAAGAikNgBAAAAmAgkdgAAAAAmAokdAAAAgIlAYgcAAABgIpDYAQAAAJgI\nsaELYASkUikRmZmZGbogAAAA8L5g04P3jYBhGEOXwQjcvn1boVDoZVVz587Nzc398ssv9bK2\nD1BgYODEiRObNWtm6IIYpVu3bq1bt+7PP/80dEGM1aZNm4gI52+54fytCJy/FbRp0yZLS8uf\nfvpJL2sTi8VNmzbVy6r0C4nduzZ69Ggi2rx5s6ELYqysra1DQkJ69+5t6IIYpaNHjw4ZMiQ7\nO9vQBTFWOH8rCOdvReD8raAP5PxFHTsAAAAAE4HEDgAAAMBEILEDAAAAMBFI7AAAAABMBBI7\nAAAAABOBxA4AAADARCCxAwAAADARSOwAAAAATAQSOwAAAAATgbFi37X3c2g5IyKVSrEPyw17\nr4Kw9yoIR2BFYO9V0Aey9zCk2LuWnp5ORA4ODoYuiLGKiYnx8PAQCvGwuTyKi4tjY2M9PT0N\nXRBjhfO3gnD+VgTO3wr6QM5fJHYAAAAAJgI/mwAAAABMBBI7AAAAABOBxA4AAADARCCxAwAA\nADARSOwAAAAATAQSOwAAAAATgcQOAAAAwEQgsQMAAAAwEUjsAAAAAEwEEjsAAAAAE4HEDgAA\nAMBEILEDAAAAMBFI7AAAAABMBBI7AAAAABOBxA4AAADARCCxM4Do6OivvvqqTp06ZmZmjo6O\nAQEB4eHhhi6UMUlPT58+fXrNmjXNzMxq1aoVEBBw5coVQxfKmBQVFc2ZM0ckErVo0cLQZTEa\nGRkZU6dO9fT0lEqlrq6ugYGBiYmJhi6UMcFRVxG46FXQB3XbFTAMY+gyfFgePXrUrl27rKys\nwYMH16lT5+nTp7t37yaisLCwNm3aGLp0RiAtLc3X1zcmJqZ3794+Pj7R0dEhISFisTg8PNzb\n29vQpTMCDx48+M9//vPkyZOcnJzmzZtHREQYukRGoLCwsE2bNjdu3Pjss898fHyioqKCg4Pd\n3NyuX7/u4OBg6NIZARx1FYGLXgV9cLddBt6tbt26CQSCsLAw1ZR9+/YR0eDBgw1YKiMyYcIE\nIlq7dq1qyt69e4moV69eBiyVscjMzLSwsGjRosWTJ0/MzMx8fX0NXSLjsHLlSiJatmyZakpI\nSAgRfffddwYslbHAUVdBuOhV0Id228Wr2HfNz89v9uzZHTt2VE3x9/eXSCSPHj0yYKmMiEQi\n6dKly9dff62a0r9/fwsLi8jISAOWylgoFIpvvvnm8uXLXl5ehi6LMdm6dauNjc2UKVNUUwYP\nHuzl5RUcHMzgpUdpcNRVEC56FfSh3XbFhi7AB2fRokVqU5KSkoqKimrVqmWQ8hidVatWqU0p\nLCxUKBRubm4GKY9xqVJ3kqQ+AAAPe0lEQVSlyi+//GLoUhiZ/Pz8u3fvdu7c2czMjDu9ffv2\nQUFBz549q127tqHKZhRw1FUQLnoV9KHddvHEzpByc3NDQ0N79eplY2Pzww8/GLo4xuqPP/4o\nKioaOnSooQsCpikuLk6pVLq7u6tNr1mzJhFFR0cbolDwQcNFr9w+hNsuEjuDsbe3t7Ky+vjj\nj5s0aXLr1i20FCufsLCwGTNmtG/ffty4cYYuC5imrKwsIrKyslKbbm1trZoL8M7golduH8ht\nF69iK0tGRsbs2bNVf3p5eU2fPp27wPjx49PS0u7du7djx46YmJgtW7bghQ5XqTuQiHbu3Dl6\n9OjGjRsfPHhQLMbB/D+67D0oE4FAoDaFrV3Hnw5QeXDRq4gP5bZr6NYbJisuLo67n9u1a1fS\nkufOnbOysmrSpIlSqXyXJXzPad+BxcXF8+bNI6IePXq8fv3aUIV8b+ly+KF9oo6ePHlCRKNG\njVKbPnfuXCI6c+aMIQplrHDUlRsuenpk2rdd5PuVxc3NjdGtuVznzp379eu3Y8eOR48eNWzY\nsLILZiy07ECGYQIDA+Vy+aRJk1atWiUSid5x2d5/uh9+UCoPDw+xWPz8+XO16VFRUURUt25d\nQxQKPiy46OmXad92UcfunYqPj2/atOnIkSPVpufn5xNRTk6OIQplfKZNmyaXy5csWbJmzRpc\n4KCySaVSX1/f8PDw3Nxc1cTi4uKwsDB3d3cPDw8Dlg0+ELjoldsHeNtFYvdO1ahRIy0tLSQk\n5OrVq6qJjx8/PnXqlLW1dePGjQ1YNmOxb9++1atXT5kyZc6cOYYuC3woxo4dm5ubu2LFCtWU\njRs3JiQkBAYGGrBU8IHARa8iPsDbLoYUe9cOHDgwcOBAoVD42Wef1alTJz4+fs+ePTk5OevW\nrWO7FwftvLy8oqKiJk2aZGlpqTZr1qxZGN9Ju7CwsOPHj7P//uWXXxwdHUeNGsX+OWPGjKpV\nqxquaO81pVL58ccfX7hwoV+/fj4+Pg8ePAgJCWncuPGVK1f4xyGowVFXQbjoVdAHd9s1ZAW/\nD9WVK1cCAgIcHR1FIpG9vX3Xrl0PHTpk6EIZDS0H87Nnzwxduvfdzz//XNLee/LkiaFL917L\nyspiR2GXSCQ1atSYMGFCamqqoQtlHHDUVRAuehX3Qd128cQOAAAAwESgjh0AAACAiUBiBwAA\nAGAikNgBAAAAmAgkdgAAAAAmAokdAAAAgIlAYgcAAABgIpDYAQAAAJgIJHYAAAAAJgKJHQAA\nAICJQGIHAAAAYCKQ2AEAAACYCCR2AAAAACYCiR0AAACAiUBiBwAAAGAikNgBAAAAmAgkdgAA\nAAAmAokdAAAAgIlAYgcAAABgIpDYAQAAAJgIJHYAAAAAJgKJHQAAAICJQGIHAAAAYCKQ2AEA\nAACYCCR2AAAAACYCiR0AAACAiUBiBwAAAGAikNgBAAAAmAgkdgAAAAAmAokdAAAAgIlAYgcA\nAABgIpDYAQAAAJgIJHYAAAAAJgKJHQBUlqFDhwoEghcvXhi6IGVQapnFYnHr1q3LutrAwECB\nQPD06dOKlQ4AoBRI7ADAaKSnp0+fPr1mzZpmZma1atUKCAi4cuWKau62bdsEJVu3bl0llYph\nmL/++isgIMDV1dXMzKx69eotWrRYvHhxcnJyJW0RAKAkYkMXAABAJ2lpab6+vjExMb179x41\nalR0dHRISMjJkyfDw8O9vb1Vi/n5+Wl8otasWbPKKFVGRsagQYPOnDljaWnZpUuXmjVrpqam\nhoeHz507d/Xq1Xv37u3QoUNlbBcAQCMkdgBgHObNmxcTE7N27dqJEyeyUwYMGPDZZ5/Nnj37\n6NGjqsV69Ogxf/78d1aq4cOHnzlzpl+/fps2bXJ0dGQnFhcXb9y4ceLEif369Xv48GH16tXf\nWXkA4AOHV7EA8I48f/589OjRNWrUkEql1apV8/f3Dw8P5y5w9OjRVq1aWVpaOjs7T5kyJS8v\nz93d3cfHh50rkUi6dOny9ddfq5bv37+/hYVFZGSkfovBdezYMV9fXwsLi+rVqwcGBmZkZHDn\nnjhx4tixYz4+Pn/99ZcqqyMioVA4bty4hQsX+vj4REVFcacvW7asdu3aZmZmHh4eixYtYhhG\nNTc8PLx///7VqlWTSqWenp4jRoyIiYlRzR02bJhAIMjOzp41a5anp6eZmZm7u/uqVau4a9C+\nA4koOTl5woQJNWvWlEqljo6OAQEB165dK9PeA4D3HJ7YAcC7EBcX16pVq9zc3PHjxzdq1Cg+\nPn7Dhg0dO3Y8c+ZM+/btiej8+fP9+vVzdHScPXt2tWrV9uzZM3To0KysrBo1arBrWLVqldo6\nCwsLFQqFm5ubHovBdfHiRX9/fycnp3nz5jk6OoaFhfn7+wuF//s9vHXrViL64YcfxGIN19Lv\nv//++++/50756aefbt269dVXX4lEorVr186bN8/Ly+vzzz8nouvXr3fq1KlKlSpTpkxxdnaO\njo5ev379qVOn7t+/X7VqVSKSSqVENHDgwFq1au3atau4uHjBggXffvutvb396NGjddmBL1++\n9PPzy8jIGDduXOPGjePi4jZs2NChQ4eTJ0926tRJ930IAO81BgCgcgwZMoSI4uLiGIYZNWoU\nEe3bt0819/79+yKRqHXr1uyf3bp1I6Jr166xfyoUio8//piI/Pz8Slr/6tWriWjt2rXsn8HB\nwUT0448/ailSqcXglrlHjx5EFB4erlr4m2++4Rapdu3aAoEgMzOz1F0xduxYImrfvn1hYSE7\n5fr160Tk7+/P/rlhwwYfH59z586pPrJ27Vrut2PX8Pnnn6sWYJ8F9unTh/2z1B04fvx4sVis\nWoBhmNjYWBsbmxYtWpRafgAwFngVCwCVjmGYAwcOODk5BQQEqCY2bNiwTZs2V65cSU1NJaIL\nFy40aNCgRYsW7FyRSDRr1iwt6wwLC5sxY0b79u3HjRunx2KoFBcXh4WF1alTp2XLlqqJX375\nJXeZ5ORkOzs7W1tbHQvw3XffSSQS9t/NmzcXiUQJCQnsn+PHj79+/Xrnzp2JqKioKD8//6OP\nPiIi7ttYImITU1bt2rUtLS1VPbNo34EMw+zZs6dJkyZubm5Jb0gkkrZt20ZERGRnZ+v4FQDg\nPYfEDgAqXVJSUmZmZqNGjQQCAXd6/fr1iejx48cZGRn5+fleXl7cuW3bti1phTt37uzevXvj\nxo0PHjyo9hp0wYIFGrs7uXXrVqnF4E5MTEzMy8urXbs2d2KDBg24fwqFQqVSqcseYNWtW1f1\nb4FAYG1tnZeXp5oSHBzcqVMnBwcHqVRqYWHRpUsXIlIoFNw1eHh4cP+USCRFRUVEVOoOTElJ\nefXq1Y0bN1zedvLkSSKKjY3V/VsAwPsMdewAoNLl5OQQkZWVldp0CwsLdi77tMzS0pI718bG\nRiQSqX2EYZj58+cvXLiwR48eu3fvtrGxUVugZcuWrVq14pfB0dGx1GJwJ+bm5hKRubk5d6K5\nuTk3KXR1dX306NGrV6+qVaum4WvzmJmZlTTr+++///nnn1u0aLFq1apatWqZmZlFRkYGBgaq\nLaZ64Kem1B2YlZVFRM2aNfv555/5H3d1ddWl/ADw/kNiBwCVztramniZk2qKjY0Nm6/k5+dz\n5+bm5qo9D2MYJjAwUC6XT5o0adWqVfy0j4h69epVUncnSUlJ2ovBnchme2pFys7OZjitUNu2\nbfvo0aPDhw+zzRfUMAxz9+7dJk2aaCwMV35+/v/93/+5u7ufO3eO3VdElJmZWeoHVUrdgapv\nx1YcBABThVexAFDpnJ2dq1Sp8uDBA25WRET3798XCAT169d3dnYWCoXPnz/nzr169araeqZN\nmyaXy5csWbJmzRqNWV0Fi6G2sFQqffbsGXfinTt3uH+y+dzChQvZ52FqNmzY0LRp0/Xr15da\nsKSkpLy8vBYtWqiyOiIKCwvT4Tv9r7Tad6CTk1O1atUePnyo1mPLy5cvdd8KALz/kNgBwLsw\nYMCAxMTEgwcPqqbcunUrPDz8k08+sbe3l0qlLVq0uHPnzsOHD9m5SqVy2bJl3DXs27dv9erV\nU6ZMmTNnTiUVg7ukWCxu27bt06dPuT29qWVpHTp0GDJkSExMTLdu3bj91SkUijVr1kyZMsXF\nxWXYsGGllsrJyUkgEHDbSdy6dYvtS0XtIVxJdNmBgwYNys/PX7FihWrKy5cvmzRp0rdvX102\nAQBGAa9iAeBdWLBgwZEjR0aMGDF58uT69evHxMSsX7/e2tp65cqV7AIzZswYNGhQr169vvnm\nG1tb223btrEd+arWMHPmTCIqLi6ePXu22spnzZrl4OCgl2JwzZw5MywsrE+fPmPGjKlatWpY\nWFhubq6dnR13GblcXlBQcODAgQYNGnTo0KFevXoZGRlXrlx5/vx57dq1T5w4oUvBLCwsevfu\nfeTIkXHjxnXu3Pn+/fvr1q3bvn27v7//0aNHd+7c6e/vX+pKSt2B8+fPP3r06JIlSxITEzt1\n6pSQkPD777+npqZOnjxZhz0HAEbCYB2tAICp4/YJxzBMbGzs6NGjXVxcxGJx9erVhw4dev/+\nfe7yMpmsfv36Uqm0Zs2aP/zwQ2FhoVQqbdu2LTtXy3Xs2bNnjG792JVaDLUy79q1y9vbmx2n\nYcyYMenp6e7u7s2bN1db56FDhwYMGODq6iqRSGxsbPz8/DZs2JCbm6tagO2F7smTJ9xP2dnZ\nNWrUiP13SkrKsGHDHB0d7ezsPvnkkwsXLjAMs2DBAmtra2dn58TExFLXUOoOZBgmMTFx/Pjx\n7u7uYrHY3t7e39//6tWr2ncXABgXAaP1cgkAYCivX7+2s7Pz9/fnvjkF3WEHAnyAUMcOAN4L\nmzdv7ty5MzseAysoKIiI+CN9gUbYgQBARHhiBwDvhatXr7Ld844fP97V1fXmzZsbN250dXW9\nffu2WrMG0Ag7EAAIiR0AvD8uXbq0ePHi69evp6enV69evXv37osWLULfubrDDgQAJHYAAAAA\nJgJ17AAAAABMBBI7AAAAABOBxA4AAADARCCxAwAAADARSOwAAAAATAQSOwAAAAATgcQOAAAA\nwEQgsQMAAAAwEUjsAAAAAEwEEjsAAAAAE4HEDgAAAMBEILEDAAAAMBFI7AAAAABMBBI7AAAA\nABOBxA4AAADARCCxAwAAADARSOwAAAAATAQSOwAAAAATgcQOAAAAwEQgsQMAAAAwEUjsAAAA\nAEwEEjsAAAAAE4HEDgAAAMBEILEDAAAAMBFI7AAAAABMBBI7AAAAABPx/1Whdq1BIbnrAAAA\nAElFTkSuQmCC",
            "text/plain": [
              "Plot with title “Volcano plot”"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 420,
              "width": 420
            }
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "with(mrna_res, plot(log2FoldChange, -log10(pvalue), pch=20, main=\"Volcano plot\", xlim=c(-3,3)))\n",
        "with(subset(mrna_res, padj<0.05 ), points(log2FoldChange, -log10(pvalue), pch=20, col=\"blue\"))\n",
        "with(subset(mrna_res, padj<0.05 & abs(log2FoldChange)>1.5), points(log2FoldChange, -log10(pvalue), pch=20, col=\"red\"))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1XHEhmRXGS_q"
      },
      "outputs": [],
      "source": [
        "library(DESeq2)"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "R_ProstateCancer_DESeq2.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNTyWw9N0hoLoZqF8IBb8fK",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "R",
      "name": "ir"
    },
    "language_info": {
      "name": "R"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}