{
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 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "SQLshare Simple Join"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head -2 /Volumes/Students/diseases/Amanda/seastar_clc_rnaseq_counts.txt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Feature\tHK_CF2\tHK_CF35\tHK_CF70\tV_CF71\tV_CF34\tV_CF26\r\n",
        "seastar_clc_contig_1\t28\t38\t89\t168\t37\t8\r\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head -1 /Volumes/Students/diseases/Canonical_Files/Phel_clc_blastn_nt_nopipes.tab"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Phel_clc_contig_2\tgi\t378345425\tgb\tJN676976.1\t\t81.71\t175\t1e-33\t  154\t7602\tAsterias amurensis\tAsterias amurensis\tstarfish\tEukaryota\tAsterias amurensis microsatellite Aamr32 sequence\r\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!sed 's/seastar/Phel/g' </Volumes/Students/diseases/Amanda/seastar_clc_rnaseq_counts.txt> \\\n",
      "/Volumes/Students/diseases/steven/Phel_clc_RNAseq_count.txt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head /Volumes/Students/diseases/steven/Phel_clc_RNAseq_count.txt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Feature\tHK_CF2\tHK_CF35\tHK_CF70\tV_CF71\tV_CF34\tV_CF26\r\n",
        "Phel_clc_contig_1\t28\t38\t89\t168\t37\t8\r\n",
        "Phel_clc_contig_10\t42\t180\t22\t9518\t2752\t839\r\n",
        "Phel_clc_contig_100\t1235\t6104\t616\t260\t565\t413\r\n",
        "Phel_clc_contig_1000\t8551\t31946\t4311\t2043\t3853\t3070\r\n",
        "Phel_clc_contig_10000\t21\t211\t32\t9\t12\t13\r\n",
        "Phel_clc_contig_10001\t54\t365\t90\t44\t227\t89\r\n",
        "Phel_clc_contig_10002\t478\t1267\t185\t38\t61\t80\r\n",
        "Phel_clc_contig_10003\t29\t186\t17\t9\t29\t20\r\n",
        "Phel_clc_contig_10004\t19\t92\t4\t8\t25\t6\r\n"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Running RNA-seq on CLC"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<img src=\"http://eagle.fish.washington.edu/cnidarian/skitch/greenbird_1978345A.png\" alt=\"greenbird_1978345A.png\"/>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head -4 /Volumes/web/cnidarian/Seaster_clc_rnaseq_tc.txt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Feature ID\tHK_CF2\tHK_CF35\tHK_CF70\tV_CF71\tV_CF34\tV_CF26\r\n",
        "3291_5903_10007_H94MGADXX_V_CF71_ATCACG_R1 (paired) trimmed (paired) contig 1\t28\t38\t89\t168\t37\t8\r\n",
        "3291_5903_10007_H94MGADXX_V_CF71_ATCACG_R1 (paired) trimmed (paired) contig 10\t42\t180\t22\t9518\t2752\t839\r\n",
        "3291_5903_10007_H94MGADXX_V_CF71_ATCACG_R1 (paired) trimmed (paired) contig 100\t1235\t6104\t616\t260\t565\t413\r\n"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!sed 's/3291_5903_10007_H94MGADXX_V_CF71_ATCACG_R1 (paired) trimmed (paired) contig /seastar_clc_contig_/g' </Volumes/web/cnidarian/Seaster_clc_rnaseq_tc.txt> /Volumes/web/cnidarian/Seaster_clc_rnaseq_tcc.txt\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head -4 /Volumes/web/cnidarian/Seaster_clc_rnaseq_tcc.txt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Feature ID\tHK_CF2\tHK_CF35\tHK_CF70\tV_CF71\tV_CF34\tV_CF26\r\n",
        "seastar_clc_contig_1\t28\t38\t89\t168\t37\t8\r\n",
        "seastar_clc_contig_10\t42\t180\t22\t9518\t2752\t839\r\n",
        "seastar_clc_contig_100\t1235\t6104\t616\t260\t565\t413\r\n"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!sed 's/Feature ID/Feature/g' </Volumes/web/cnidarian/Seaster_clc_rnaseq_tcc.txt> /Volumes/web/cnidarian/seastar_clc_rnaseq_counts.txt\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head /Volumes/web/cnidarian/seastar_clc_rnaseq_counts.txt\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Feature\tHK_CF2\tHK_CF35\tHK_CF70\tV_CF71\tV_CF34\tV_CF26\r\n",
        "seastar_clc_contig_1\t28\t38\t89\t168\t37\t8\r\n",
        "seastar_clc_contig_10\t42\t180\t22\t9518\t2752\t839\r\n",
        "seastar_clc_contig_100\t1235\t6104\t616\t260\t565\t413\r\n",
        "seastar_clc_contig_1000\t8551\t31946\t4311\t2043\t3853\t3070\r\n",
        "seastar_clc_contig_10000\t21\t211\t32\t9\t12\t13\r\n",
        "seastar_clc_contig_10001\t54\t365\t90\t44\t227\t89\r\n",
        "seastar_clc_contig_10002\t478\t1267\t185\t38\t61\t80\r\n",
        "seastar_clc_contig_10003\t29\t186\t17\t9\t29\t20\r\n",
        "seastar_clc_contig_10004\t19\t92\t4\t8\t25\t6\r\n"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!grep \"contig_2671\t\" /Users/sr320/Dropbox/Steven/eimd/data/seastar_clc_rnaseq_counts.txt\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "seastar_clc_contig_2671\t22304\t17668\t6133\t1349\t5266\t3297\r\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!grep \"contig_51\t\" /Users/sr320/Dropbox/Steven/eimd/data/seastar_clc_rnaseq_counts.txt\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "seastar_clc_contig_51\t15849\t12626\t4334\t1017\t3858\t2318\r\n"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!wc -l /Volumes/web/cnidarian/seastar_clc_rnaseq_counts.txt\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "   30579 /Volumes/web/cnidarian/seastar_clc_rnaseq_counts.txt\r\n"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      " Version 3 with CLC"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<img src=\"http://eagle.fish.washington.edu/cnidarian/skitch/greenbird_19A511DE.png\" alt=\"greenbird_19A511DE.png\"/>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<img src=\"http://eagle.fish.washington.edu/cnidarian/skitch/greenbird_19A51201.png\" alt=\"greenbird_19A51201.png\"/>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Experiment\n",
      "<img src=\"http://eagle.fish.washington.edu/cnidarian/skitch/greenbird_19C0EA14.png\" alt=\"greenbird_19C0EA14.png\"/>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head /Users/sr320/Dropbox/Steven/eimd/paper/data/Phelv3_counts.txt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Feature ID\tV_CF71 - Total gene reads\tV_CF34 - Total gene reads\tV_CF26 - Total gene reads\tHK_CF70 - Total gene reads\tHK_CF2 - Total gene reads\tHK_CF35 - Total gene reads\r\n",
        "Phel_clc_contig_1\t168\t37\t8\t89\t28\t38\r\n",
        "Phel_clc_contig_10\t9518\t2752\t839\t22\t42\t180\r\n",
        "Phel_clc_contig_100\t260\t565\t413\t616\t1234\t6104\r\n",
        "Phel_clc_contig_1000\t2043\t3842\t3070\t4311\t8527\t31946\r\n",
        "Phel_clc_contig_10000\t9\t12\t13\t32\t21\t211\r\n",
        "Phel_clc_contig_10001\t44\t225\t89\t90\t54\t365\r\n",
        "Phel_clc_contig_10002\t38\t61\t80\t185\t478\t1267\r\n",
        "Phel_clc_contig_10003\t9\t29\t20\t17\t29\t186\r\n",
        "Phel_clc_contig_10004\t8\t25\t6\t4\t19\t92\r\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!wc -l /Users/sr320/Dropbox/Steven/eimd/paper/data/Phelv3_counts.txt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "   29476 /Users/sr320/Dropbox/Steven/eimd/paper/data/Phelv3_counts.txt\r\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "DESeq2"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%load_ext rpy2.ipython\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R \n",
      "source(\"http://bioconductor.org/biocLite.R\")\n",
      "biocLite(\"DESeq2\")\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "name": "stdout",
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "y\n"
       ]
      },
      {
       "name": "stdout",
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "y\n"
       ]
      },
      {
       "name": "stdout",
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "y\n"
       ]
      },
      {
       "name": "stdout",
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "a\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "Bioconductor version 2.13 (BiocInstaller 1.12.1), ?biocLite for help\n",
        "A newer version of Bioconductor is available after installing a new version of\n",
        "  R, ?BiocUpgrade for help\n",
        "BioC_mirror: http://bioconductor.org\n",
        "Using Bioconductor version 2.13 (BiocInstaller 1.12.1), R version 3.0.3.\n",
        "Installing package(s) 'DESeq2'\n",
        "trying URL 'http://bioconductor.org/packages/2.13/bioc/bin/macosx/contrib/3.0/DESeq2_1.2.10.tgz'\n",
        "Content type 'application/x-gzip' length 1647689 bytes (1.6 Mb)\n",
        "opened URL\n",
        "==================================================\n",
        "downloaded 1.6 Mb\n",
        "\n",
        "\n",
        "The downloaded binary packages are in\n",
        "\t/var/folders/28/07h2q2ms7nd609f1ft3mj1240000gn/T//RtmpIk0BZ1/downloaded_packages\n",
        "Old packages: 'RCurl'\n",
        "Update all/some/none? [a/s/n]: Update all/some/none? [a/s/n]: Update all/some/none? [a/s/n]: Update all/some/none? [a/s/n]: trying URL 'http://cran.fhcrc.org/bin/macosx/contrib/3.0/RCurl_1.95-4.3.tgz'\n",
        "Content type 'application/x-gzip' length 711068 bytes (694 Kb)\n",
        "opened URL\n",
        "==================================================\n",
        "downloaded 694 Kb\n",
        "\n",
        "\n",
        "The downloaded binary packages are in\n",
        "\t/var/folders/28/07h2q2ms7nd609f1ft3mj1240000gn/T//RtmpIk0BZ1/downloaded_packages\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "library(\"DESeq2\")\n",
      "packageVersion(\"DESeq2\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "Loading required package: GenomicRanges\n",
        "Loading required package: BiocGenerics\n",
        "Loading required package: parallel\n",
        "\n",
        "Attaching package: \u2018BiocGenerics\u2019\n",
        "\n",
        "The following objects are masked from \u2018package:parallel\u2019:\n",
        "\n",
        "    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,\n",
        "    clusterExport, clusterMap, parApply, parCapply, parLapply,\n",
        "    parLapplyLB, parRapply, parSapply, parSapplyLB\n",
        "\n",
        "The following object is masked from \u2018package:stats\u2019:\n",
        "\n",
        "    xtabs\n",
        "\n",
        "The following objects are masked from \u2018package:base\u2019:\n",
        "\n",
        "    anyDuplicated, append, as.data.frame, as.vector, cbind, colnames,\n",
        "    duplicated, eval, evalq, Filter, Find, get, intersect, is.unsorted,\n",
        "    lapply, Map, mapply, match, mget, order, paste, pmax, pmax.int,\n",
        "    pmin, pmin.int, Position, rank, rbind, Reduce, rep.int, rownames,\n",
        "    sapply, setdiff, sort, table, tapply, union, unique, unlist\n",
        "\n",
        "Loading required package: IRanges\n",
        "Loading required package: XVector\n",
        "Loading required package: Rcpp\n",
        "Loading required package: RcppArmadillo\n",
        "[1] \u20181.2.10\u2019\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!pwd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "/Users/sr320/Dropbox/Steven/eimd/ipynbs\r\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "data <- read.table(\"/Users/sr320/Dropbox/Steven/eimd/data/seastar_clc_rnaseq_counts.txt\", header = T, sep = \"\\t\")\n",
      "rownames(data) <- data$Feature\n",
      "data <- data[,-1]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%R head (data)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>HK_CF2</th>\n",
        "      <th>HK_CF35</th>\n",
        "      <th>HK_CF70</th>\n",
        "      <th>V_CF71</th>\n",
        "      <th>V_CF34</th>\n",
        "      <th>V_CF26</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>   28</td>\n",
        "      <td>    38</td>\n",
        "      <td>   89</td>\n",
        "      <td>  168</td>\n",
        "      <td>   37</td>\n",
        "      <td>    8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>   42</td>\n",
        "      <td>   180</td>\n",
        "      <td>   22</td>\n",
        "      <td> 9518</td>\n",
        "      <td> 2752</td>\n",
        "      <td>  839</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 1235</td>\n",
        "      <td>  6104</td>\n",
        "      <td>  616</td>\n",
        "      <td>  260</td>\n",
        "      <td>  565</td>\n",
        "      <td>  413</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 8551</td>\n",
        "      <td> 31946</td>\n",
        "      <td> 4311</td>\n",
        "      <td> 2043</td>\n",
        "      <td> 3853</td>\n",
        "      <td> 3070</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>   21</td>\n",
        "      <td>   211</td>\n",
        "      <td>   32</td>\n",
        "      <td>    9</td>\n",
        "      <td>   12</td>\n",
        "      <td>   13</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>   54</td>\n",
        "      <td>   365</td>\n",
        "      <td>   90</td>\n",
        "      <td>   44</td>\n",
        "      <td>  227</td>\n",
        "      <td>   89</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "   HK_CF2  HK_CF35  HK_CF70  V_CF71  V_CF34  V_CF26\n",
        "0      28       38       89     168      37       8\n",
        "1      42      180       22    9518    2752     839\n",
        "2    1235     6104      616     260     565     413\n",
        "3    8551    31946     4311    2043    3853    3070\n",
        "4      21      211       32       9      12      13\n",
        "5      54      365       90      44     227      89"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "# Build Objects\n",
      "# Specify which columns are in which groups\n",
      "deseq2.colData <- data.frame(condition=factor(c(rep(\"HK\", 3), rep(\"V\", 3))), \n",
      "                             type=factor(rep(\"single-read\", 6)))\n",
      "rownames(deseq2.colData) <- colnames(data)\n",
      "deseq2.dds <- DESeqDataSetFromMatrix(countData = data,\n",
      "                                     colData = deseq2.colData, \n",
      "                                     design = ~ condition)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "# Run Analysis\n",
      "deseq2.dds <- DESeq(deseq2.dds)\n",
      "deseq2.res <- results(deseq2.dds)\n",
      "deseq2.res <- deseq2.res[order(rownames(deseq2.res)), ]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "estimating size factors\n",
        "estimating dispersions\n",
        "gene-wise dispersion estimates\n",
        "mean-dispersion relationship\n",
        "final dispersion estimates\n",
        "fitting model and testing\n"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "# Count number of hits with adjusted p-value less then 0.05\n",
      "dim(deseq2.res[!is.na(deseq2.res$padj) & deseq2.res$padj <= 0.05, ])\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "[1] 3914    6\n"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "# Output\n",
      "write.csv(deseq2.res, \"/Users/sr320/Dropbox/Steven/eimd/data/deseq2.results.csv\", row.names = T)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head /Users/sr320/Dropbox/Steven/eimd/data/deseq2.results.csv"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\"\",\"baseMean\",\"log2FoldChange\",\"lfcSE\",\"stat\",\"pvalue\",\"padj\"\r\n",
        "\"seastar_clc_contig_1\",115.066144674932,1.2584943899478,0.798269369507704,1.57652847274337,NA,NA\r\n",
        "\"seastar_clc_contig_10\",5559.9807996404,6.21395254235976,0.706071287598319,8.80074385052017,NA,NA\r\n",
        "\"seastar_clc_contig_100\",784.602239929063,0.0240772706127452,0.252625922408093,0.0953079968327662,0.924070191017092,0.963581804834051\r\n",
        "\"seastar_clc_contig_1000\",5399.35140742484,0.220304382495146,0.291639349490296,0.755400061343492,0.450008976442489,0.668550107882446\r\n",
        "\"seastar_clc_contig_10000\",24.759355847272,-0.181484411685002,0.556540344229253,-0.326093900589251,0.744353311654646,0.868919878380582\r\n",
        "\"seastar_clc_contig_10001\",136.27718425946,1.49886855266789,0.550947966456816,2.72052651778936,0.00651780439581695,0.0350101864080016\r\n",
        "\"seastar_clc_contig_10002\",175.868477828981,-0.904068111183539,0.436621462902541,-2.0705993360325,0.0383962542741281,0.130532011415495\r\n",
        "\"seastar_clc_contig_10003\",28.3483004978917,0.703135859400196,0.456126993374581,1.54153529524346,0.12318655962946,0.29495023131509\r\n",
        "\"seastar_clc_contig_10004\",16.5832494690187,1.05100411121411,0.61056831461333,1.72135383717006,0.0851866356198028,0.230797062716078\r\n"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "tmp <- deseq2.res\n",
      "# The main plot\n",
      "plot(tmp$baseMean, tmp$log2FoldChange, pch=20, cex=0.45, ylim=c(-3, 3), log=\"x\", col=\"darkgray\",\n",
      "     main=\"DEG Virus Exposure  (pval <= 0.05)\",\n",
      "     xlab=\"mean of normalized counts\",\n",
      "     ylab=\"Log2 Fold Change\")\n",
      "# Getting the significant points and plotting them again so they're a different color\n",
      "tmp.sig <- deseq2.res[!is.na(deseq2.res$padj) & deseq2.res$padj <= 0.05, ]\n",
      "points(tmp.sig$baseMean, tmp.sig$log2FoldChange, pch=20, cex=0.45, col=\"red\")\n",
      "# 2 FC lines\n",
      "abline(h=c(-1,1), col=\"blue\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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TmmPSuDFCGKO6dZXuQ4cOFSI4bNiwAsPvuPNOWjdrGlFOqkHII7v1Ig+2JHaJ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7lB8B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\nnMvo0slJtd1efVMGXni5vDDsNslVpyWIbHcOhPT7XXjqQPldvZ9rqZoW6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Rd10xL3KtwQ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\n0VBCs9gL/7xYlIblnj17rL7L+nd74cKF552zOnWo6O+yJVaKAZ9Bozy/y5g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      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "write.table(tmp.sig, \"/Users/sr320/Dropbox/Steven/eimd/data/deseq2_sig_results.txt\", row.names = T)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head /Users/sr320/Dropbox/Steven/eimd/data/deseq2_sig_results.txt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\"baseMean\" \"log2FoldChange\" \"lfcSE\" \"stat\" \"pvalue\" \"padj\"\r\n",
        "\"seastar_clc_contig_10001\" 136.27718425946 1.49886855266789 0.550947966456816 2.72052651778936 0.00651780439581695 0.0350101864080016\r\n",
        "\"seastar_clc_contig_10010\" 8.73784349604224 2.43426494953234 0.717338850139719 3.39346593183711 0.000690141423521562 0.00610587057360923\r\n",
        "\"seastar_clc_contig_10013\" 188.603521302622 -1.94923068685006 0.463271107915175 -4.20753777549832 2.58168256856775e-05 0.00041485396609123\r\n",
        "\"seastar_clc_contig_10045\" 50.485024106335 2.87706412205861 0.695003049883772 4.13964244119468 3.47847563039607e-05 0.000526018158180456\r\n",
        "\"seastar_clc_contig_1005\" 3408.98435663456 -1.66691198866687 0.378947946534594 -4.39878881495589 1.08856689786144e-05 0.000199362344222153\r\n",
        "\"seastar_clc_contig_10050\" 276.941589423215 -1.61560402677235 0.323282993601818 -4.9974915437781 5.80808848482353e-07 1.60431884071189e-05\r\n",
        "\"seastar_clc_contig_1006\" 77.8447124150533 -2.01146173192642 0.468218416201358 -4.29599020953798 1.73915258259802e-05 0.000298432523132762\r\n",
        "\"seastar_clc_contig_10064\" 147.578457909919 1.81093710357749 0.683578354090462 2.64920194260252 0.00806821051110654 0.041310905437205\r\n",
        "\"seastar_clc_contig_10065\" 28.5076393455268 2.27188575134493 0.585911374358637 3.87752457243526 0.00010552467251757 0.00131744894528401\r\n"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Using DESeq"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "\n",
      "source(\"http://bioconductor.org/biocLite.R\")\n",
      "biocLite(\"DESeq\")\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "Bioconductor version 2.13 (BiocInstaller 1.12.1), ?biocLite for help\n",
        "A newer version of Bioconductor is available after installing a new version of\n",
        "  R, ?BiocUpgrade for help\n",
        "BioC_mirror: http://bioconductor.org\n",
        "Using Bioconductor version 2.13 (BiocInstaller 1.12.1), R version 3.0.3.\n",
        "Installing package(s) 'DESeq'\n",
        "also installing the dependency \u2018geneplotter\u2019\n",
        "\n",
        "trying URL 'http://bioconductor.org/packages/2.13/bioc/bin/macosx/contrib/3.0/geneplotter_1.40.0.tgz'\n",
        "Content type 'application/x-gzip' length 1461546 bytes (1.4 Mb)\n",
        "opened URL\n",
        "==================================================\n",
        "downloaded 1.4 Mb\n",
        "\n",
        "trying URL 'http://bioconductor.org/packages/2.13/bioc/bin/macosx/contrib/3.0/DESeq_1.14.0.tgz'\n",
        "Content type 'application/x-gzip' length 2340535 bytes (2.2 Mb)\n",
        "opened URL\n",
        "==================================================\n",
        "downloaded 2.2 Mb\n",
        "\n",
        "\n",
        "The downloaded binary packages are in\n",
        "\t/var/folders/28/07h2q2ms7nd609f1ft3mj1240000gn/T//RtmpAtUZwG/downloaded_packages\n"
       ]
      }
     ],
     "prompt_number": 49
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%R library( \"DESeq\" )\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "Loading required package: Biobase\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",
        "Loading required package: locfit\n",
        "locfit 1.5-9.1 \t 2013-03-22\n",
        "\n",
        "Attaching package: \u2018locfit\u2019\n",
        "\n",
        "The following objects are masked from \u2018package:GenomicRanges\u2019:\n",
        "\n",
        "    left, right\n",
        "\n",
        "Loading required package: lattice\n",
        "    Welcome to 'DESeq'. For improved performance, usability and\n",
        "    functionality, please consider migrating to 'DESeq2'.\n",
        "\n",
        "Attaching package: \u2018DESeq\u2019\n",
        "\n",
        "The following objects are masked from \u2018package:DESeq2\u2019:\n",
        "\n",
        "    estimateSizeFactorsForMatrix, getVarianceStabilizedData, plotPCA,\n",
        "    varianceStabilizingTransformation\n",
        "\n"
       ]
      }
     ],
     "prompt_number": 50
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "CountData<- read.table(\"/Users/sr320/Dropbox/Steven/eimd/data/seastar_clc_rnaseq_counts.txt\",row.names=1, header=TRUE,)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 53
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%R head (CountData)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>HK_CF2</th>\n",
        "      <th>HK_CF35</th>\n",
        "      <th>HK_CF70</th>\n",
        "      <th>V_CF71</th>\n",
        "      <th>V_CF34</th>\n",
        "      <th>V_CF26</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>   28</td>\n",
        "      <td>    38</td>\n",
        "      <td>   89</td>\n",
        "      <td>  168</td>\n",
        "      <td>   37</td>\n",
        "      <td>    8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>   42</td>\n",
        "      <td>   180</td>\n",
        "      <td>   22</td>\n",
        "      <td> 9518</td>\n",
        "      <td> 2752</td>\n",
        "      <td>  839</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 1235</td>\n",
        "      <td>  6104</td>\n",
        "      <td>  616</td>\n",
        "      <td>  260</td>\n",
        "      <td>  565</td>\n",
        "      <td>  413</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 8551</td>\n",
        "      <td> 31946</td>\n",
        "      <td> 4311</td>\n",
        "      <td> 2043</td>\n",
        "      <td> 3853</td>\n",
        "      <td> 3070</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>   21</td>\n",
        "      <td>   211</td>\n",
        "      <td>   32</td>\n",
        "      <td>    9</td>\n",
        "      <td>   12</td>\n",
        "      <td>   13</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>   54</td>\n",
        "      <td>   365</td>\n",
        "      <td>   90</td>\n",
        "      <td>   44</td>\n",
        "      <td>  227</td>\n",
        "      <td>   89</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 54,
       "text": [
        "   HK_CF2  HK_CF35  HK_CF70  V_CF71  V_CF34  V_CF26\n",
        "0      28       38       89     168      37       8\n",
        "1      42      180       22    9518    2752     839\n",
        "2    1235     6104      616     260     565     413\n",
        "3    8551    31946     4311    2043    3853    3070\n",
        "4      21      211       32       9      12      13\n",
        "5      54      365       90      44     227      89"
       ]
      }
     ],
     "prompt_number": 54
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "conds <- c(rep(\"HK\",3), rep(\"V\",3))\n",
      "conds\n",
      "cds <- newCountDataSet( CountData, conds )\n",
      "head (counts (cds))\n",
      "LibrarySize <- estimateSizeFactors( cds )\n",
      "sizeFactors( LibrarySize )\n",
      "head( counts( LibrarySize, normalized=TRUE ) )\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "                             HK_CF2     HK_CF35    HK_CF70      V_CF71\n",
        "seastar_clc_contig_1       18.34488    4.768066  109.66656   489.38889\n",
        "seastar_clc_contig_10      27.51731   22.585578   27.10859 27726.21130\n",
        "seastar_clc_contig_100    809.14003  765.902030  759.04044   757.38757\n",
        "seastar_clc_contig_1000  5602.39381 4008.438117 5312.05090  5951.31852\n",
        "seastar_clc_contig_10000   13.75866   26.475316   39.43067    26.21726\n",
        "seastar_clc_contig_10001   35.37940   45.798532  110.89877   128.17328\n",
        "                             V_CF34     V_CF26\n",
        "seastar_clc_contig_1       52.43201   15.79646\n",
        "seastar_clc_contig_10    3899.80803 1656.65399\n",
        "seastar_clc_contig_100    800.65100  815.49237\n",
        "seastar_clc_contig_1000  5460.01466 6061.89243\n",
        "seastar_clc_contig_10000   17.00498   25.66925\n",
        "seastar_clc_contig_10001  321.67748  175.73564\n"
       ]
      }
     ],
     "prompt_number": 55
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "Disp <- estimateDispersions( LibrarySize )\n",
      "str( fitInfo(Disp) )\n",
      "plotDispEsts <- function (Disp)\n",
      "{\n",
      "\tplot(\n",
      "\t\trowMeans( counts(Disp, normalized=TRUE)),\n",
      "\t\tfitInfo(Disp)$perGeneDispEsts,\n",
      "\t\tpch = '.', log=\"xy\")\n",
      "\t\txg <-10^seq(-.5, 5, length.out=300)\n",
      "\t\tlines (xg, fitInfo(Disp)$dispFun(xg), col=\"red\")\n",
      "}\n",
      "plotDispEsts(Disp)\n",
      "head ( fData(Disp))\n",
      "str(fitInfo(Disp))\n",
      "DE <- nbinomTest( Disp, \"HK\", \"V\" )\n",
      "head (DE)\n",
      "plotDE <- function (DE)\n",
      "\tplot(\n",
      "\t\tDE$baseMean, \n",
      "\t\tDE$log2FoldChange,\n",
      "\t\tlog=\"x\", pch=20, cex=.3,\n",
      "\t\tcol = ifelse (DE$padj < .05, \"red\", \"black\"))\n",
      "plotDE(DE)\n",
      "hist(DE$pval, breaks=100, col=\"skyblue\", border=\"slateblue\", main=\"\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "List of 5\n",
        " $ perGeneDispEsts: num [1:30578] 2.732689 3.375718 -0.000427 0.013865 0.100182 ...\n",
        " $ dispFunc       :function (q)  \n",
        "  ..- attr(*, \"coefficients\")= Named num [1:2] 0.379 4.011\n",
        "  .. ..- attr(*, \"names\")= chr [1:2] \"asymptDisp\" \"extraPois\"\n",
        "  ..- attr(*, \"fitType\")= chr \"parametric\"\n",
        " $ fittedDispEsts : num [1:30578] 0.414 0.38 0.384 0.38 0.541 ...\n",
        " $ df             : int 4\n",
        " $ sharingMode    : chr \"maximum\"\n",
        "List of 5\n",
        " $ perGeneDispEsts: num [1:30578] 2.732689 3.375718 -0.000427 0.013865 0.100182 ...\n",
        " $ dispFunc       :function (q)  \n",
        "  ..- attr(*, \"coefficients\")= Named num [1:2] 0.379 4.011\n",
        "  .. ..- attr(*, \"names\")= chr [1:2] \"asymptDisp\" \"extraPois\"\n",
        "  ..- attr(*, \"fitType\")= chr \"parametric\"\n",
        " $ fittedDispEsts : num [1:30578] 0.414 0.38 0.384 0.38 0.541 ...\n",
        " $ df             : int 4\n",
        " $ sharingMode    : chr \"maximum\"\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Hog4eDh+srgIcHtiQK+SwxLZq9MPnk7ub8H1X+DvhWh+/FvrDk415xeTFx2cO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\nuxvx33f5L193bdnavcHMkOu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8sNLSg1icGLcwamp81ZCXH1dfLnJXO457URyvKXI8737c\nKznZ2qrhsQaO78s54NJ3v9bPOc71HuIQR1/xuEWt6/fVDOX1aWRuc06g+gxYo8h3wtqc3xCTXLUO\nnrg4vIT35cmJTw0HGRZt5wiDLytu5CtmwXWMHLYvB6dl+2rp3apdCY42NmppX62cuHHf4sKXVR4O\nOBg4OjH2vZDDKodetJ5zDXw0vA4MDjnFMQcn5lo81/LaiBO3dLw2/ZyAT6B5A853wvIxpV+bAAcP\nuXgAkY+44lZOWspFDhqeA6M/msSycGq5Gua14/xx9fQep+P5Pk3PoY11DXzPeS15t84VDl84OWHg\n4jgu33P4WNf0WvlaaC1FS7HXCo8xWKyFh3VN/JgDr9mo77F84kk0a30S23wTaP4Iei3fCUt/8KU/\n9GqtQw45pBx99NGtdOILMAEdQq0DKOKK/dDC12XUfPhYLpcYCz7ETlODLrW+V3IrtS1Neo7Td558\nLTRjDhxNj+U7Hx00qcG28Jinh2vLjzF1fZY9juuNRovXwlt18OkPby3sPHquxXVt1h7NG/BavhPW\npZdeOvojL73V5V577bXs30LvSZ1rcSZQOwTGHUqqYYmrh7CIw6GHc5wrXoyp9b0Ioxd52Vatc9x3\nDdV67LyV+i1d9tvK03ccj3p41IF7jI8Vp7aYh3JwwOgDTh/yrgfHsT4fraF1tZ59+uNyQ/uO05kk\nP4+ek+wvuZNNYNkN+Gtf+1q5/e1vX3bbbbfygAc8YIea3glrjz32GH04w33uc58d+Cyc17/+9WXb\ntm2jxxvf+MZZSKbGKk6g7xAgFw87cG2LnGOOkxcmDrEsGFYYuGPue174JIv+USPGQzTR6uOO0x2X\nl3acq7BWHVzytT3CiTpwY14xGFa1LGHqF3uCi1ero96t86TnsXiOxZzrrNT3PivV8vrV0vUe6c9v\nAst+B3z44YeXyy+/fLSj//k//2c5/vjjd+xOrwvWzXI11qmnnjp6nfHPfvaz1ZBPzTWYgA4LPbT6\nDjvl4NW2Ra1z8D0H5hqOyRefGqzzWz5c12txh+Ir1WJP4/qpj/fyupYvTeW8zjE0vT5yFdfyNR7a\nsr5U7xqekx+1PF+rq2Fe436ftvNq/iR9avUtbLV0W/0SX9sJLLsBe3vdDL/5zW86tGr+TW5yk3LO\nOeeUG97whuVHP/rRqvVJ4dWbQDwsdKDVDjWwmI/1cafkVYcvjnxiLLXeg76RA9ctXMem8Yf0aunG\n2rinmG/peJ181ekhnwda5NCCH2Nw14GDRZO4Zql3rrRZ7gtznuKYFzbtitp9OrPs29cncxt7Ar03\n4LW6dL3/9POe97zRG3/owx/22Wef0e+C9RnEZ5111lptI/uscAI6lPwQk+8x8o7LVx0HmvvkqPMc\nfHKy9MJ6zn3VOsd9eGBYcGwLj/naPuG0LNrsUzEPr5lGW/Wq81r6kZOln+eEa3mtYjhY8ljHhSnW\no5Z3vegrjgvtiBPToxWDT2rH9Z1UL/mbcwLLfgc8jzE87WlPK5dddln52Mc+Nvr9s/4QS297qc8g\n1mcS64MgTjzxxHlsLXuucAIcuH0yHMZw/dAk59a14GI9h89h6Zzoo0+N58EiB7xma/U1nrCo67Xu\n17hDNeH5LOhLD895L+FwwdHDkkcDvGbVzzWpcY3anuBJE42oH3GvETfGkR/1Ms4JrOYEqs+A9Tvg\n733ve6PPAtazU/l66LXBq7E++clPlre+9a3l0EMPLfpRtP6juNnNblb0++jTTz999ClMq9E3NWc7\ngdbhpn9PPXz5wYeveufJJxdryQmnhv5YapwLBgfrGmCu3eejOa2l95D6yPW9ut/Sol5c+dS4xZcG\nPLgeC+Ph/aiHq5zXE8vCle9LODlqPd/yqWnlHZ9E1+vSzwnMagLVZ8D60a+vAw44YEf4iEc8Yoc/\nK0f9PvWpT5VHPepRyyQ/+tGPlnwZ0rKxrAvAD0P3tXnFtQMQXDl4ssTYUTJ8cT103NZ00IMXJJuh\n8933ghYuDjmsY2j05eBgnSuMWcTrgycLzy34KNl9oZ5YFg49yDkOJlvTcNzrar5jqlMMpnjIintV\nzaQaQ/okJycwyQSW3YD/7d/+bZdvTD0D1h9i3eY2txm9DEkf1DDrdcoppxS97vh1r3tducMd7lD2\n3nvv0bPtr3zlK6NPYfr4xz8+65apt4YT8IOOwxiMgxHLtjwP5lb5WKMYLFrVCmNFfc+5Lz69qJV1\nffcjx2P36YFVzn249K7lvKaWdwzfLdr0Qo/ZOA7XrfOkS+wcNFtajruPlmPyW7hyvgfFvuKePJd+\nTmBeE1h2N+WNMPTOVPr965lnnllucIMbFN2I9UYZq/E63Xve857lC1/4wujjD/WmHPp9sJ716ve+\n973vfasH07wGln1XNoF4gBJj/QYRO0WOYg5d6mKNYjgxB+617sOvYejCwbIn4mjH5Z3f6uuclk+f\naMUHq9V6jv7CWGCK8ZWHA0YePMaOKxeXdMRBbxJ+jYte7BPjobxYl3FOYJoJVH8HLKG3ve1t5Rvf\n+Eb50pe+VK644oqR/cEPflBe+cpXTtNnbI1efnTkkUeWxz/+8eW5z31u+exnP1t0Y+Y/wLECSZjb\nBPg3ksXv2wwcDkpiWWHx4VpwwdBQ7D75lqUXel7b8ltajqMHJi3Xi3l4bp3v+FBf9bEPsefApEtP\nYfjgwiJOrevBF8ZDmC/qaljsK47reF451yKHVd5XC3eO/KG8WLcIsc9jEfaTexg/gWXPgCnRDfDZ\nz3520fswa93lLncpL3rRi0afEwxnNe3ZZ59dXvayl41+HD20jz5C8e///u+rdD3DvtGNblTNJTh+\nAvqPu3U4gWNRa9U4zw8Nx6UR64ll8ekVa6mXVU58X2C1Oq+Jda7hfuShH3GvafnjatCept61XQcc\nTFZLOBgc+oJjHfdaz8v35foxV+M51sd3nnz2PklN1Fj0eCNf26LPftr9NW/A97///cub3vSm0bPQ\nW9ziFqOXAr373e8uRxxxxLS9Vr1Ofzl90EEHVfvw19XVZIJjJzDNf9yq4YD1BmAcip7D9xy9hcVa\nYupkHaOGPHsSDleWHuRHyZ4vQ3lo0w/Jaeupw0Y94Vr0wwqLNZ6Lec+5D08WXLbWl36y+NTAl44W\n+Ygrhz5W2KSrplvTWEmPml5iOYG+CTRvwHodrl6Xq9/F3vWudy16j+irrrqq6D2h3/e+94009WyT\n3xn3NZkmp98368fSkyztU4/auvjii0e/W67lEpvNBGqHV+1g9cOQfNyBc6SrBUYMFvvWNL22lkcT\nO2p4fc+IKVfDqIn5GldYbR+uge/1+NjIQdevN3KIW7ZvXzHnMb1busLhs3/FWsRY8FHy+i+O0Qu+\nKJ73OriOtfyWRosPPkkPatLmBJo34Ic85CHlXve6V++EVvNHui996UvLjW98497+mVwfE+g71GoH\nFxiWqySu6ZGD6xa+OFpY58zDH7IP7b2PRx7r18d1D7029XEd1RGjxV5iDFcWDhaspkXPmp7qtMgt\nRUtfwbDk0COWjRzPzcpfix6z2mvqLM4Emn+EdfDBB5cDDzyw3OMe9xj9Hli/X/33f//30U1ZN2Y9\ntm5tlk91hfpEJP3eV2/IoR+BX3jhhaPPAf7+978/lV4Wre0EpjmEqPHDml2Tk+Uh3jgu9bJoODbO\np5esH+hDtCInxvRu4corR55rJaYeS54YK77nXFMc13Pfa8RTTN5z+K4bMepiP+fRwzGvU761VEMd\nHK+t5eHFunE4+VnYVu+W9qT8lk7iizeB5h1UN9w73/nO5bvf/W551rOeVfT73xe+8IXlHe94x/wj\neeAAAEAASURBVKpdhf7y+qKLLirnnXfeqMdRRx01+p2u8FzrewK1Q4TDUjl8XaX7yvHwHJgsK2LS\n8bxi10YPDIsOujULN+Ziv5inTjz8yHENcjWMnCx6aA7hUz+EGznq45h8ersumHPB4CmOGLloXUe5\nvrqhuq7Zpxf3Mm08aY9J+dPuK+vWfgLNG/B73/ve8va3v73oXbDOPffcor9KFvbBD35w1Xap39Oe\nfPLJo2feaqLPH9ZrkXVTzrX4E+Agk8Vn1xwifTm4WHGpc0y+cB6KvR849fTEer382pIGmtHCFycu\nx7wfPLQUu08e28q5Ptwh1vdS0xiKqZe47M91fR/C4eFT6zw4jtV8+rFP14QPhzha8rEWzciPMfXg\nMQYfZ6etG6eb+fU3geYNWO/7rD/A0k1x//33L3q7yKuvvnqilwVNOg792Fv9fH3kIx8pt7rVrRxK\nf8EnoAONQy0eNrUcHCyXhwZWuNc7z/GajuepE4+HMOrExReuOC6vc47XxRrnea6m73n30Z+kRtwW\nH9x1HcOPewB3y0xkwVWHTx4tehLXLBxp4IsXYzA04GI97/uB79ZrHKcOzPfQqoHrNup4bh7+JHuf\nx/42cs/mH2E9+MEPHj37vO6668rjHve40ScT6S+Tn//856/aPJ7xjGeMfrd8/vnnl+985zujD2PQ\nO2NdcMEFq9YzhSebgP5jbR0gEW9xweFH6zuC69g43/Wox6pWecX4ssTR99jrhBNjhY1b9PEaMK9V\nXquWq+GuNyq0L2jAibFRl/UTl7oaj7znIr/Wjzqs1+N7zn3y9KlZ58gfVw9fVnpDF1zs0LpF4q3n\nvS/SHKfZS/MGrPdm3nfffUefiPTwhz989K5Yb37zm0fvVjVNoyE1+nG3PoLw/e9//+j9p/WaYz12\n2223IeXJWYMJTPIfa41bOwi17YgTtzTipYpHDXpwhPuCJ0vO+3ieOs+DYdEg9r2QA4NDD4/xZalz\nbKV+1Iyx6/t+nccchMHxPBrwiMWhRhh5rOfwycEXjj9yui9wZKmDByfWOB59NMDHxfDcxhrPpZ8T\n8Ak0b8AiPeABD9jB1et/9VjtpTfMOO6441a7TeqvwgT84HHfW3Fgel5+XPCEw8UK48CNvuKoB9dx\n91XDAsc67nsSDgd9uG7JiYtPnnrildhJtbiWWh37dKu9iet8fLTYv+PylUcLHWo8T33LUhPzroEf\nOa04ak4a13SjRo2TWE5AE1h2A/61X/u18upXv7ror6DPOuusZVN60IMeNPqM3mWJBDb9BDh4hhyC\n4sKr1ZGT9QUORq1i11Qca8dx4KPjfPToB1c4izpyWPIxBl8Ly96w2ot8Yt8D+4zWOfK9Fi545MY8\nMRqyLHxxYr6GwW/1RneIbe2LvkM0kpMTGDqBZTdgveTntre97ehjAf0ZMIJ6W8pZr9NOO63o05da\nS+9HffTRR7fSiS/YBDgQ/TCrbREeOY/dj3l0wWXFr+HK1fAaRs9WTngtpx5afbklxq5fW3sGx+5a\ntTPy/da4jrE3rOfcl3qMa5g4jtdqYn5UcP0X6rUffPJg4NiYJx5n0YPnMwCTjTzPxT14Lv2cwLQT\nWHYDPuyww0Zael/lW9/61tX/GKdt1qrTH1q94Q1vGH3cYe2tLfXX2LnW3wSmObTiIdjSAPfD1DH5\nekQ959dyXucThxvrxQGTT8/oK9byfK2ulV+q3vnVeTvRnR55rDLu72TuvPH4fshToxy+csTwZD2v\nGI7wISvyFWt5vfvwa9rUxvpaTL1r9/Hgr7btu77V7p36azOBZTdgtf3yl788+kjAL37xi6M34tCN\n+IEPfODoL6Dlz3q9/vWvL3oXLD1W4/OGZ73f1KtPYBYHRjwEOUjBiX0HyoE7T34tRy25aJUXpsU1\nyXoPfHGohy+r5ZwlZNev9HB0XA3cyGvFwtmfc8Cl5zhc9uY5fHJeSw7MOcLiEl8ceMTOIydsXD5y\nvNY1a35Nu8Zba2ySa1jrvWW/2Uxg2euAP/3pTxf9HljvgqUb49/93d+Nfuerd8S6973vXS6//PLZ\ndA4qp556atEHQPzsZz8LmQzXywTigaGDbdwSp8WLB2OMpa2ejqMFDod9CPccuKzXgovLwvd+5GTJ\nYz1Hnh6K5fsDPvWy+ORqdhzHe1KvGsfx3cp3bfle18qrBzr0izE6wtHBx1IrC98xfPG1xJlmoY3O\nJBrT1Eyin9yNPYFlz4Bf8YpXFH0Qgj4LmKX3g37oQx9a9HKkd73rXaN3qyI3K6u/fj7nnHNmJZc6\n62QC8dDkQBMecxyU4OI6D1yXTg4fW+PQU5yYF8aC5xz59MKKH3E0POeY+/TBeq7mt3hxD8TS8BrH\nlVPMcp58co57DRzy2NiDGvLEsmjI90Vvx1pccSbJuXZfnfeW73Uxl3FOYNwElj0D/upXv1r0Jhy1\ndeSRR5avfOUrtVRiOYFdJjD0EBNPC6sDTQ9iLOJ+4LnvGvI9h49FkzjaqKXYF/XC8GWlI8vDa8h5\njefx2UsrFh45cGPO99biCIcHh/1HnGugPxYN+FjyWPHw3eLTP8bgNetc+mI9p1pw+THn+VpO+bhc\nL+YyzgkMmcCyG/AVV1xRbnnLW1ZrhSufKycQJxAPIz/EYi7WKna+x8L1mEYj1hCjqT7C9KA/sXK+\nyGM9h+86jslXTovefToj4vVf+jSdh08fYll6xpxw9Gv7oQ6LFjWK3e/jUYtVnR6+YqxcxGLs9eqv\nvGxcEUcHK36trqYDNoQPN21OoDaBZT+CFkm/i73BDW6wjH/llVcuwxLICWgCfYfRtDnp+gEZD1Hl\nWeScH/vGWLXCVEM9mCwYeTBZLfSUjwvdiDsXjuvQU3VwsfCjZg2PGLqy6KFDjtht5HoO3zlRi5xf\no3xiadQ4wuG5ptdRC+a8mIMjXIsYKyzWC/M1Lu/c9HMCQyZQvQHrD7Ba6xGPeEQrlXhOYEUT0AGn\n5Ycifjz8IhceG1Aca8hFPNaiLT4+emh4bhymPD1qemDoxJj6iLMncGJ6uR45MNlY5znyaInrGtSK\n5zh1EYePnvJa6C5Fu34dkkMPfdck59iuHZYi+jjfa1r5mlZiOYFJJrDsBvy1r31tx2GBkP4CWj9+\n3n333cuee+4JnDYnsMsEOKh2AQcEHJ7xAFQpmjEXY9qAU+c4GBxy4IrJgdUsdfCdA+YcfOfJn2RF\nvvaJnnTIg0dt8sK5Rvk1HCxqgaOh2LXAZVkx7zWuB1+WGvK+D3JgHqMBRoym9xZGXONTI6sFdynK\nrzmB2Uxg2e+A9U5X++yzT7n5zW9e3vSmN5X73e9+5ZGPfGT5whe+UJ7whCeUq666ajadU2XDTaB1\nkI270L465TiIWzrkseJFTQ5Q2fhwXXLeV5gWNvpwZfHhOkadMF/EWOXcd27Np5csfl+986RHTdQG\ndy33a7Wu7X6NK6ylR2/qxINLjlgcLfClaOmrY5HvvD6/1ruPn7mcwNAJLLsBU6i3pLzooovKeeed\nN4KOOuqoctBBBxXhuXICQybgh984vh+OsU45MGxNr8VTDfqy0SeuacOHQ6z+8r0GH644wsAV15by\nXlPzHZMGmlh04UWcvFvnjKtTXg+vkRYY9Y7hy6oualCrvC+4wtyH4718P447Vxx4WOUjv8aDj401\n9EmbE5hmAs0b8MUXXzx6ve+BBx440t1jjz1Gnw+sm3KunMCQCUxyWHHASVd1xLL45GJv+ohHLZjX\nRC3XobZWB89zwtgXtfDAFccaYfA9J4y66FMj27ekh3Yfr5bzntJhb9hY0+oDHxvrFHvOfXJgsvjq\nFxd78L3Dccx15EetyGUf0cY6ekU7lDeruqiT8fqZQPMGfPDBBxfdhH195CMfKbe61a0cSj8nMJMJ\nxIORg1fiHKAclK0DjhosG3M+Oazn0FcOXxrO8Vi8qCMuGP2x4LJRUxgP+C2LDnliNOMeyIvvPjEY\nVvWuJR4xHFl47ourpVzE4ZN3G33FLLQUuwZ59dHDF5j44xbcITzntLTjXrymz5+2rk8zc4s9gWV/\nhMV2n/GMZ5R73ete5fzzzy/f+c53yuGHH170oQkXXHABlLQ5gV0m4AflLolKUOPWDiBhcGt5DsGY\nowbLFjymFisOOlhyXkcOTaxw8eDikwdXjIbXwAODpzpfxDUemPdCR9ZriVWDP3IqX+AoRQ98t/Lp\nEXHFWuwNHrHnRkT7Aifuo1YDVznnIwcGDwsOr8+qJldOYKUTaN6ADzjggHLJJZeU97///eWb3/xm\nOeKII0aP3XbbbaU9s36DTmCSA2wIl4PRx+WY+3DA0JeNGFzPgWGpIUZPMTlZLXTwZZ1D3q04WjWN\npczSV8/D972gqZz7S9W7fkULlD0Sy6INlxgOuMfj+opLnbjwXZs8um6d5zg+eWnIJybfsvBkqW1x\nI05txBchnvRaFmHPm3UPzRuwBqL3Zz7uuOM262zyuldxAn5IuE9Lx/ywa/nUyVIrq+U1I6D7AqeW\nowaOYvcVa6lWuB6slk+eGqxw9xW7huLagqNaFlgtdp7yzpXPHhyPPMXw5GuhC+52ibH0FRyMOmJZ\n5/g+alyvwx/HQ7PG8961PD3Wg13v+18PM57VHps34B//+MflyU9+8uijCa+55pod/R70oAeVP/mT\nP9kRp7O5J8DhPekU/JBwH52IjetDXnW1g7aFxT70R8/rxvnUSANun69c3K9rUMse0cR63jHXdX3h\nreV90aI29kfD89Qo53znUOe9hBFjhcU6z3mN/HGLWjQVa7FPr4dTyzlvM/vMczPPYFbX3rwBv/rV\nry4/+clPyhlnnDF6JkxDvUY4V06ACcSDal7/cfrByZ58L2C1fTtPeWJZLbTxR+D1eMTIgaMRcY9r\n3Fjne/L9qDZyXbtVxzyoJabWe8DxXvCd5764zkHXcfYWeeC1GjBqiGW9jj2Lp4fnarWqB8cKy7V8\nAjmf5TOZFmnegL/1rW+NngHrE5By5QSGTmDS/zj9YFSPGEcs5omxvk/fSy0vTMt5Xu++OPBdy33x\nidGkDgsnaiumhj5w0IxWeee2esQ6xV6HDv3dwkMbGzXZK7XURW141A/JUzPO0ls89z2OOJq+HzC3\n4/LOHeqvhubQ3slbjAk0X4b0sIc9rLznPe8p3/ve9xZjp7mLDTmBeCDGWBftmPuec1wHG0u+x457\nPbhj0tQDDXy4wiOmuLbYA3nZWKs658GhxvPOE44WNWCyWvCXop0zjdrwZPGpQYceyns9PHDq4WDF\na/nUep6+6A+x9Mb21dCzjxv306c3NLcamkN7J28xJtC8AX/7298uH//4x0ev+73Tne5UDjnkkNHj\npJNOWoyd5y427QT8oHS/byC1w06Y17vvWl6LLy4+XK+Xz8N5rTpqneu6XgeHGvFqvmOxpqYnDjx6\nyzqG79ruOx8uWpEHLkvOa4TV8FqdY/LRwca8x3Cw5OhNjG3h5NPmBIZOoPkj6N/5nd8pv/qrv7pM\nJ38HvGwkmw7QAeSHVYwXaSC+T99XxPuuIR64qhVGDVpYcO+H7xwwLHXog2PJy2pFnsexT6xVPTry\ntWIsDE1Z98m5pYcw/GiVqy3fLz79Ih9N4XAjZxZxS7uFz6JnamyuCTRvwHonLD20LrvssrLvvvuO\nPg1pc40nr7Y2gXgAxbhWMy2mw1ZLPfzgFUaMFabl+4m5JcbOr3BdnxosHMVaisEUg8vvW97D62MN\nes4XR7ge4PjkXIccXM+Btay4yvmKejFPjXjuxx7kZNF0P+rG2Ovlt5ZrtzjT4qupPe2esm59TqD5\nI+ht27aVl73sZeXQQw8t97///cuFF15Yjj766PL9739/fV5p7npVJ8DBu9Im6GB1AHMIj7PqTV3c\nxxBc+uJ5H+ocj33gC5ePjtfGGuXIk6thaCvnvmq00KDnErq0D3LCyKMhzPOKfZGT7atxnurFdT6a\n6HgOn5xs1IsYeXRrVhxp17g1rKaRWE5gLSbQvAHnpyGtxfjXR48hhxaHqV/RkDrny0cHS15aLT3P\nxTrVKw/uGhH3mL4tKz20sPSihp6K5fMgP8RKu7YvtLHOEUYsq+UxmHDnErumsMh3zOud5/3Qla0t\n+imH77bm13TAnA+GJUc8jZ1Gw2czTc+s2ZgTaN6A89OQNuY/+DRXNc2Boz5D6uLBFGP2Ky3XEw9u\nzFGD9Tph1JGXRcNz8r3Wc9S0NFQnvtcQg7k2/dH1WBi1Eff+0fc+qlMsy3JfGD3g0QtLXlxhivHd\njsDui+s4hu8WLhjaxLO2q60f9xtnHfMZb84JNG/A+WlIm/MbYq2vOh5MMW7tR7yhXNeIdX0Hsbjk\nqQMDlxXmy2P8yHNcOR7SkR8X/Igrhu9WfB7gcKOWYjjkFINRJ+t5r1OOpTp4YFjHvUdLS3W+D3Tc\net5950Tf9xFzGecE1moCzT/Cyk9DWqt/gs3VRwdk3+HXyrfwIdOr1TrmftSr7TXeLGI9ca1W+uDw\nvKcwX96LOvJ9OXSo8RhfFg140m5h3rfmC0NbPpoRIyYvrpbHvgfHl5hLX9m/591v9VE1ta6Xfk5g\nrSfQvAHnpyGt9T/F5ujnB2Ttisflqek7QD0nPQ5iarHwvCc+OSw1WHThg8uC0TfGLU1qqYPn9fj0\nI4ZLrWuJA451TFxw6mR9KU8v4S0+urU8mOt4j+gP5cW9oRPrvX/MUZM2J7CWE6j+CFrvAf2FL3xh\n9B7QV199dbn88svLhz70ofLe9753LfeWvTbZBDgga5cdD8wYew25oXrOw0dDVhgP+iiGQw0WjvJw\nHMOXRdctPZ0nH63YR3Gs8Zg89ejGGHycvufRqGHKke/bP33HWe/het5DeOShG/cD3lfjnPRzArOe\nwLIb8D/8wz+U2972tuUDH/jAqNdHP/rR0dtR6qMJn/70p5d//dd/nfUeUm+TTiAelPEg7RuL17rv\nNehhlatxPe8+/BaGlvL40fp+0IsY+ljyHkddxTzQFZ+Ha6AjPj55MOrcoi8MHhaeYl+xppZzbBJf\nPVvL99HHa9XHGtdzv1WfeE5gmgks+xH0U5/61PLKV76ynHDCCTv0jj322KJ3xrryyivLW97ylnLq\nqafuyKWTE1jNCejwi4ej+gkjV8vX9gSfnGuAyToPbazy7sMFUxw5ih2XTzwiX//FsT49ctSqTpjX\nKwfmfLjUeg7MrWvE2thPda7nPrmo4b2i3+LWcHqRw0bNWlzjoie++7X6xHIC005gl2fAevONL37x\ni+Xxj398Ve83f/M3R/lqMsGcwIQT4GDTAdha4rTy1FPb4pGvaUUNcWsYGth4aNPbe4BR47ryeSjv\nOero4Tn34YHJ4kuTell85akTRyvGYHCxI3L4Qj+sp+kLxh6Ix9mapmrAa/smhx3Xw/WGcJOTE5jl\nBHZ5Bqxv2j322GOXt5zU736FaSl/oxvdaJb9x2pdd9115dprry03uMENxnKTsD4n0DosZ3Vgo4Md\nN6XI8xifPcuCua5j7otTqxGH3Mi5niff6+HBIe+xfHqAe4zvVjzXVo4F7nwwWed6TQ0nP4lt9ZiV\n/iR7SW5OYJYT2OUZ8G677VYOO+yw8j/+x//Y0UM33N13X7pPf+ITnyi/8Ru/sSM3K+d//a//VR77\n2MeO/uhLb3v59a9/fYe0fhf9mMc8ZkeczvqYAAf0SnbLAYudVEt78MNbOuwLO0ST/q7Vqoscj+np\nmHRijLZwz7mvPbEv8fEdl0+NLDwwj/GxzhfGin3oQZ464qHW69wfVz8Jd5xW5nMCaz2BXW7Aan7i\niSeW448/vvzVX/1V0Y+ktX7605+WV73qVaOPJ3zkIx85wmb55XWve93oYw8/97nPlcMPP7zc9773\nLV/96ldn2SK11ngCHNRr0bZ1CGsPcR/EWN9fS8c58p0n37XkO9aX69MhF+vV3zHFLHBqhQtjP+SF\nO0cxCw62ViuucDTgoiE7FPMa/FgbY3iyfTnnpZ8TWMQJ7PIjaG3w937v98rWrVvL7/7u75af//zn\n5Zd+6ZdGf/l85zvfuXzqU58q/+E//IeZX4c+d1gve9Kz7VNOOaX88i//cvmt3/qtXZ6Jz7xpCm6Y\nCcRDmJvGpBcYdWr1UTvWcFOq1QoTHw2vdZxaz6PrWOShC451bTjoiUMeXxaefF/gcR/o1fCISQ8d\nbI3jPN9DzUenlkssJ7CoE1h2A9ZGdfPVDfCb3/xm+drXvlbuec97llvf+tardg264erZ733uc59R\nj9///d8v3/72t8uDHvSg8qQnPWnV+qbwfCcw7tCs5WtYvAoO8z6uclpwXaOGObem65jqa/pg3gtd\nz7mW8jGO9eTZNxbc+ezNrfLUwI15x+VLW4s67Ai0L+PwVl4Svn/3TX6H26ezg5ROTmDBJrDsR9Ds\n7/nPf3758Ic/XB7ykIes6s1X/fSSp0c84hG7vLzpmc985ujZuN4SM9fGnEA8NDnUudpaPmJwa9a5\nrs1hTt5zNR0weKrDx6IlrjDFYIrBlAeHK6slHD3F+M4XHhd5+OTRizj5aMVrcT0Hh75RRzGc6Ne4\nYF4jzPXdh9+yUafFG4rPWm9o3+Rt/AlUnwHrsm9zm9uUv/u7vyv6K2T9cdZqrgc84AHlX/7lX8o3\nvvGNXdq8+MUvLkccccQot0sigw05gdYhqwNQuXF5huIHJjVYOG6Vo4dw9yOPmBpir6EXGLG4+DHn\nevhwaz3A3MJHu5YThr7n+3Byke9x7Mle4MS88Ih5Tcyh07KR7zE+tqVRw6epqekklhOoTaB5A9bv\nY/UuWHvvvXfRJyNxE9aPpv/4j/+4prUibK+99ip3v/vdRy85uuKKK8otbnGLkd797ne/okeuzTmB\nIQegH9yaUoyFuU4t75j7XicdX85zHN/zrhP9yPe8csToEVPnHOU8do77aPVxxan18lo0wYbyVUcN\nGm5bvZ3jvmu5Lw4x1uvG+dPUjNPMfE6ACTRvwA984ANHL0mCiL3lLW+JOzN7zTXXlJe85CXlPe95\nT/nWt741+g/mxje+cbnd7W5XnvWsZzXfGGRmG0ihhZqAH+JDD0CvqV0MOuJpEctv1dZwx1zL9aTp\nCx6YuK4zpBaNPq700ZY/roY9uKbXy/ccmo6h4b3AxF/JqvWZVG9We5m0b/JzAkMm0LwB60fQemhd\ndtllZd99993xeuAhwpNwnva0p416fOxjHyu3v/3ti54N66VPl1xySTnppJNGf42tl0fl2hwT8IN3\n6BUPranxapj6RpybDHvyPAf9OMxrqUE31sLFKk8NGNZr4SnneKz1HDrUsCds5Ebc8/JjL9fHH8fx\nPPqODdGhDu5a2tpe17J/9lr8CTT/CEuvAX7Zy15WDj300KI3x7jwwgvL0UcfXb7//e/P/Ko++clP\nlre+9a2jXvrQB33j3uxmNxu9Jvj0008f/THYzJum4IaegL6Hakt4LVfDqCenw7x1oNdwYdSihXU8\n1hLL+oNat64DLow6sD7rGvKpV03UUQw+cipf0MNWKCMILQU1rufRGIrBn6et7XWe+8neizeB5g34\nbW97W7nooovKeeedN9r1UUcdVQ466KAifNbrbne72+g1xjVd/R56v/32q6USywk0J6DDT4d6PNiF\n1w5GsMhXA3LNZo2EtKit6VJW41HnnBqPvFtqY09wuMrXOJEHH0uNePjksMqh0+LAlYXrWJ8/RLOv\nPnM5gUWYQPNH0BdffHE5+eSTy4EHHjjap94PWj8O1kuG9BKlWS69+cYxxxxT9I5Yd7jDHUZ/+KXP\nJP7KV74y+qMsvVFHrpzANBPoO9h1iMd8jIf0rOmoDi3Pc+NQTj6x94GPdS141NdsjQOGde3aHuDJ\nOlcx1xV9xVrkqSNeys7m62pozmZnqZITGD6B5g1Yf/msm7D/BfJHPvKR0VtGDpcfxtQbfeidsD7z\nmc+USy+9dPT7YD3r1e999baU4w6IYV2StdkmMO6QHpfnBsL3n/PJaaaOt2YM37nuqw5On09OliUd\nrwWXpYfyLDDF1GHhwBcXfuTAjXYIbwgn6macE9hoE2jegPUGGPe6173K+eefX77zne+Mfh+rm+MF\nF1ywKjO44Q1vWI488sgd2n/wB39Q9L7THAQ7Ej2OPtRB76BVW7qGq6++upZKbBNPoO9GwI0H62MC\n4/tTsWs57lx816r58FqaqlHO+zg3arqe88Cx1MVYeA0T7ntwXovvHPlrvfz617p39ssJ+ASaN+AD\nDjhg9FfI55xzTvnyl79cHvrQhxZ9HjCvB3aR1fDPPvvs0R+B6XXIQ9c//uM/lr/8y7+s0vVGHze/\n+c2ruQQXfwKrfWj26ddyYK2bjOPiTrpcn3rXlJ7H8IW7H2OvUW7a5T1c0/GWNpxoW/xZ477fcdrs\ncRwv8zmBaSbQvAH/4he/KM95znPKmWeeOfosXtljjz22vPGNb9zx+cDTNFzNGr12WY/a0jN6vZwq\n1/qcwCSH5jRXGPV18LJiDjzaFs9xP9DpoTw41mvc955whTkH3/PiEMtqiQc2Anq+RF6rh+PIgcUY\nHEt+Ehv3NUntEO5K9jZEPzmbewK9fwWtt4b80pe+VPTOVLI/+MEPyitf+co1mZjeG5rPIV6Thtlk\n7hPgxjDJRsbVjMv7Aetc4a2c9ue51n7Rw1KnWA803G9pRdw10YNDDn1wj/GxcFq2xevDlWvl2WOr\n31C8pa/6Vo8WPrRn8nICs5pA8wb82c9+tjz72c8uhxxyyKjXXe5yl/KiF72ofPrTn55V72U6/trj\nL37xi6P3ol6t1x4va57A3CfQd5i2NjdNzSRa6GNjbd9hrhrlY61iMHx0FONj6UksSx059MjJwoeD\ndS4Y1mvcJz/UUoulTrEe7AF8qI16qqthwls9WrhqcuUE1nICzRuw3nzjTW96U/nRj3402o8+G/jd\n73736MMRVmuDa/na49W6htRdvQn4Qet+X8ehh+1QvdjL9aOGYs97beSKB0YNtoYLc9x9+lCPhYOF\n5xauMPedU/OjJrVYahRHjNwk1vvNQm+S3snNCcxqAs0bsN4KUm8NqZcDHXbYYWWfffYZvU5X79es\nZ8V6XHnllbPax0in9dpjvSFIrrWdgB9wq93Ze8n32Hv7Qeu+c1p+SxN+1PN9eK37qnVe1EDbLfU1\nrjDyaMvC9Zww8BbHNZwjX8vrl5DlX73n8uxOZIiW2EP1dirv6tEHu2s2o5zA+ppA84+w9DnAehlS\n39InJs1yreVrj2e5742otZYHXOwV4yHz1cHeV9eXq+m3+BEnrvUn5/qOcTNyzLnRd17sF2NqqSFP\nT/JunaM64hoHDL3Yh3y08CKecU5gM06geQPWzVAPLX0msD6xaNY33DjwtX7tceyf8fwnMOkBzU1i\n0jqulHrimh2iDSfqxdj1VaO8Vo3nmuJ47L5yLHBiLDgW3C25aGscMLge166FfNqcQE5g5wSW/Qha\nn0D0qEc9asd/7Oeee+7os3n333//0ccC6i0iV2vx2mO9A9ZTnvKU8vKXv7z8+7//e7nrXe+6Wi1T\nd51NgBsW2443AHC3scZzffV9ddKo5dEjF+NYRz5a36N85aMmuHLUxzpiamV5kMPCUex+LQ9Ws317\nqenWNKbFVlt/2n1lXU6gNoFdbsD6D0c/ej788MNH/0Hrd7zHH398ede73jV6i8g999yzvOMd76jp\nzAzTpyEdd9xx5aUvfWnRB0Cs1Rt/zOwCUmgmE4gHqWI9+g73VuNpaqRVq/N91fLsIeZiLJ5r1eKo\nVdOAE624rk+tLD49xdPDcfnUYz0f+w2N0UBzaN1QHvpD+cnLCcxzArv8CFofP8hrfvVWkN/73vdG\n/xHqwxD00B9mveY1rxm93eNrX/vaee47e6/zCcQDP14OByk8xbM8tNGNfT0ewnH+JH5Nm2sep1Or\nVY1wLWbVp0cOq7qoSw4rTmt57xYn8ZxATmDXCexyA37qU586eqnRGWecUfTezHoN7ite8YrRhyKo\n7AMf+MDoBv3qV796V5UVRqeddlrRO2+1lv7iWnvJtXEmMORQ19WKx40h1oAzlRiD12zUGsoZUlfT\ncoxrciz6fi3ui+d78By4Y+6rNsbCtFo4OVn05cfVl4tcxZPyaxpDsb5rG6qRvJzAakxglxvwLW5x\ni6J3oLr73e8++r2vfgStlx1t3bq1PP3pTx/573vf+0bxLDejD3l4wxveMHqry7322muZdH4e8LKR\nbCqgdVhHPMazGtKQA3wIx/czbq+ed9815Cvnvd0n7zWRT44eXo9PDu56s+t9/+tt3rnf4RPY5Qas\nMr3VpJ4Jf/7znx+96QYfhqCXJOn3wf9/e2cCv0O1//FvZN9lX0pRqaTlFS65dXFblMpS3RIppFS6\niBaidLVQrivkUhElW0ShsqSVbqm00eKWVChkz+75z+fc/3k6zzwzz/ab53nmmedzXq/nNzNnzvme\nc97n/OYzZ5mZhg0bJm49wZCjR48WvAULP7xrmo4EkiWgxcItXkHO6wt4PBtOaacSx8mOk5+2rfOH\nMOZ+rDhO5+zx49lys2H6I492u+Z57pNAPhOIEmDAqFmzpnoBB77Riy8M4Z3Q9erVU3fahw4dSss7\nmocNGyY333yz7N69W7AQi44EkiEQTyySPa/FLdE8ONl3s+Hmn0haZlwzTfjDmX5O9pzOmzad4sTy\nixfXKT1tL15cHY5bEggqgYhV0Cgk/mGmTZumHv3Bc7l4C9XevXvVIqzrrrtOatWqJZizxXPBXjqI\nLj59SPH1kmowbGlxiVUaexj7cTJxEdZJOEy/ZOzb0zbt2M/h2LSt9/XWKa7bOe3vlIbp52TTPB9r\nP1txY+WJ50ggVwhE9IDxvucOHToI3gO9YsUKqVSpUlQ58G5ovCMajwjhGeEaNWpEhaEHCXhJIJGL\nvD2M/big+YGYaZvmPuyax+a+Dp9s2mY8va+3TrbczsEf+YFzC+NkT/uZZdF+3JIACXhHIEKA8fm/\n6dOnS5kyZVxTwEKtgQMHSt++fdWcrWtAniABDwmkUwxMcXJLxwxj7qOI5rHed7PjIZKYpnT6Oj9O\ngXUY+znt7xZXn7fHsx8nGs4eD8cFietkj34k4EcCEUPQEGC7+GKo+dtvv416TAivpXRasezHQjJP\nuUkAF2Ht3MRAn/dqGysdMz86Pfg5+bvZ0WH1VtuJt9Xh9TZe+HjpIz7CONlzixsvTft5bccpDTOs\n03kd1wzHfRIIGoEIATYLh+dy8TpIzMmeffbZaouXc8R6XteMz30SyBYB84Ju7hckP7DjJArwc/J3\nS0uHxVbnTW/tcUx/M16scGYchLMfazv6nHlst+t2nGyceOHjnXfLB/1JINcJuAowvs2L1c+fffZZ\n+O1YW7duVY8p5Xqhmf/cIJDqhdmMZ+4XpNRe2THzoG3qrXkOwunkbw+DYzOcuW8/h2NTkO1hcT5d\nzkw3XWnQLgnkGgFXAf7ggw+kf//+6ru/KNTJJ58sgwcPlrfeeivXysj8poEAL6juUJNlY4Y3991S\n0GG0gOpjt/Cmv45j+sWKH+uctpFIGJ1uImG1XW5JIOgEXAUYK6Gx2hmrnuGwQnry5Mnq5RxBh8Ly\nxSegL6jxQwYzhJOQaD+w0fuJlN5kqff1NpYdfU6HTSQtpzCx4sc6p20lEiaVsDoOtyQQVAIRq6DN\nQuLDCwsWLFAv5MDnALEQC88D44UceB0l3EcffcSFWCY07ntCAMKiL+rmvifGEzQSL12dP9Oc6Wfu\nm2Hs+1pE4e8UJ5af0zm7/USP45UXdhIJk2h6DEcCJCDiKsD4LCFePxnLYSU0HQl4TcAUFnPfi3Ri\niYh5zut04+U9lfTM/MazH+98rPR1OrHCxLPP8yRAAtEEXAW4du3a6qMLVapUUcPPEydOlGOPPVba\ntWsXbYU+JJAjBNxERIsMimHu62I5+elzeptIGIQ1w7nlR9uMtUVc05Y9rD6HLVyqaaUaz54fHpMA\nCUQScBXg5cuXqzdiff311/Lggw/KypUr1esnf/vtN+nWrVukFR6RgA8IaMEpaFacBCee2CFNp3j2\nvHiRR9NGrDT1OZ13e154TAIkkF0Crouwnn/+eXn66aelatWq6pWTU6ZMEfi9+OKL2c0xUycBFwJa\ncFxOx/ROJK5TGN27hHFz3y0xJxtuYe3+2n4qNlKJo9PX6epjbJ38zPOx9lOJm0qcWHngORLwAwFX\nAd6xY4dagPXOO+8IhqEbNGgg+/fvF/15Qj9knnkggWwTMIXN3E8lX/FExm4/XngzD8mENeNh356u\nm589nluaTvbscc1j2Ek2jhmf+yTgVwKuQ9CXXnqp9O7dWw4fPiw33HCDrF69Wrp06aLeA+3XwjBf\nJBCLQKYv5E7pOfnpPCciMmZ8Hd7007bsWx3W7p/O40TS9Gve08mFtklAE3AV4I4dO6qvIW3fvl2u\nvPJK9VascePGSYsWLXRcbkkgpwgkIggokJMoOPnFK7w9PdOGuW/acfPXYew24e/kp8P7fZvLefc7\nW+bP/wSiBLhJkyYyfPhwwSKsSZMmqRLcd9994ZK0bt1aRo0aFT7mDgnkMgEnwXMSBSe/ZMtt2jD3\nTTtu/mYYp317OXAMl6o9pzToRwIk4C2BKAHGO6Dr1KkjdevWlQsvvDAqNXyOkI4E8omAXdy8KruX\ndu1Caz8uaJ5j5TXWuYKmy/gkEGQCUQJ8xhlnqPKWK1dOatWqpe6g8Q9GRwKZJJDoRT1WuFjndFkS\nEapEwmh79q3Og96a5xO16xTXtJPu/UTSTyRMuvNJ+ySQawQcV0F//vnn0qZNGyXARYsWleOPP156\n9uwpP/30U66Vj/nNUQKJilOscLHOpYoFQhPPmWF0HrA1/ePZMM9rG6Zfqvup5CFe+jgfL0yq+WU8\nEggygSgBxteOMA980kknyejRo+XDDz9Uc76//PKLNGvWTLZs2RJkHixbHhNIRJwSERq3MG7+qSJP\nJL9222YeUomfShx7HnhMAiTwPwJRQ9APP/ywDBkyRH2KUEM688wz5fLLL1eroZ999lnp16+fPsUt\nCQSCAITFFKd0F6qg6RU0fiLlc0ojk4wSySPDkEAuE4jqAX/zzTeCZ4CdHB5BWrNmjdMp+pGArwlA\nTGK5VIUllt1Y51JNT5fBKX6s9HQ8c+tkI5nzZljukwAJJE8gSoB37dolxxxzjKMl+OM8HQnkGgE3\nsUlWtOzldrOLcLHO2e24HSeTv3jpudnS/nrrlhf6kwAJeEsgagga5vEt4GLFikWltGfPnig/epBA\nLhOIJ1rZKBuEUOdLb+35MMPYz7kdu9nS/nprj59KWnYbPCYBEogm4CjAWIDl5q666iq3U/QnARLw\ngICbEJqmzTDpFkgzLTMP3CcBEigYgSgB/vbbb8N3306m8VgSHQnkM4FUBS+VeInEoUDmc2tk2XOZ\nQIQA7927V1atWpXQ+57xlaR69epJ9erVc7n8zDsJJE0gVcFLJp4W3mTiJF0QI4JOz/Dy9W6u5dfX\nMJm5rBGIWISF3u2bb74p7dq1k2nTpgk+SWg6vIhj9uzZct5556nzZcqUMU9znwR8RwAX6lx0mRJe\nzSbZ9BLhmkgYnX6y22Tzm6x9hieBTBCI6AEXLlxYPQO8YcMGuf/++6VXr15y5MgRqVq1qnoLVvny\n5aVp06YyduxYOf300zORP6ZBAgUikMkLtV97ZV7mS9tKhGsiYQpUuYxMAjlOIEKAdVlq1KghTz31\nlPpt2rRJfYoQw81VqlTRQdK+xXeIseq6bNmyaU+LCZBAMgS0CNnjxBMct3h2O14fx8uXPb1Y+UzW\nlt02j0mABP4gEDEE/Yf3H3tFihSRUqVKSenSpf/w9Hjv4MGD8sgjj0jXrl3l448/lunTp6teN3rc\n7du3l/3793ucIs2RQOoETBGCWNmdkx/CmPESjWMPl85jne9Y+Uxn+rRNAvlGwFWA0QO98cYbpVKl\nStKyZUvBfG+HDh3SIob9+/dXc88Y6v7b3/6mhsEx14wV2YcOHZK5c+fmW72wvFkgoAUomaS1WJlx\ntV8qdtzimPbdwhTUP5V8FzRNxieBfCbgKsDjx4+XtWvXyurVq2Xr1q1KDPEPOmzYMM95LVy4UGbN\nmqV6wZ07d5ZWrVrJ+eefr75JPHToUJk6darnadJgbhNwEiQnv2RKWRABKkhcM49uZfDKvpkW90mA\nBLJLwFWA33//ffVBhlNOOUXl8IQTTpDBgwcLvpbktYPtr776Spnt3r27XH/99eEk8GlEzD/TkYBJ\nwEmQnPzMOOncdxPORNI04xa0DKatRNL2Mkw20/ayHAW1RQ4FJZg/8V0FGJ8exLO+psNx5cqVTS9P\n9vv27StXXHGFzJs3T7AArHHjxsrugAED5M4771Rzw54kRCMkkCYCBRHOgsS1F8dLW3bb8Y6zmXa8\nvGXyPDlkknZup+W4ChpFwisn8agRerzNmzeXjz76SL2kIx094AsvvFC+/vprterZxHnZZZfJfffd\nJyVLljS9uU8COUsAvaNcu0DnYp5ztoEw43lFIKIHjGd+sfAKDo8f4aUcnTp1Us8C4xOFX3zxheDb\nwOlweNwIb9XCoqtt27apJPDMMcU3HbRpM1sE/CK+iQ6TUnyz1VKYbj4QiBBgrHx+8cUXZeXKlTJ6\n9Gj59NNP1arke++9V7p06SJ4U5b97VheQDpw4IBguLl27doqjYoVK6pHnxo0aCCTJk3yIgnaIIGs\nEUhU7DKZQfNGIFb+zHCZzB/TIoF8IBAxBI1nfu+44w5p3bq1bN++XSZPniyFCkVotHou97nnnvOU\nDd64hR73ggULBAuy8NwxPomIFdi9e/eWffv2Sc+ePT1Nk8ZIIJ0EzJ6j30XMzJ+Z73TyoW0SIAGR\nSHW1iDz00EOyefNmGTRokCxevFjNy+KNVPrntfiiEhYtWiR47Klhw4bqhR+4CJQrV0699nLUqFF8\nDpgtNSsEYvUM42XIFLV4YWOdL0geYtl1O+dVvt3s058ESOAPAlECrE/hkSMsvsqEw1DzsmXLHJOa\nP39+WlZeOyZGT98RyLQAmQASEaN05y+RPJh55j4JkEDuEIgYgjazjSHoW2+9VfAcLuZotcPw9L/+\n9S996Mn2wQcflI4dO8rIkSPVyzewIAtzzWvWrFGLsvCiDrr8JOBnAYL4+jl/6Wwx+Vz2dHKl7fwi\n4CrAw4cPVyL4xBNPRLwHGgukvHZnnXWWfPLJJ7JixQpZt26dmg/G88aY98WnD9Pdy/C6PLSXHwQS\nEV+/CJXX+Uik7PnRClhKEkidgKsA//zzz6oH3KJFi9StJxGzePHiYqbVo0cPufrqq5MWX7cLg5t/\nEllkUBJImoCX7a4gIuplPpKGwAgkQAKOBFwFGF8hwoKrRo0aZfQzhDqXU6ZMEbwHOpnPEeITitOm\nTdMmIrb4sEOdOnUi/HhAArlEIFERLYhQ5xIP5pUEcp2AqwBv2LBB9EcS8GhQ4cKFVVkvvvhiz+eA\nvYJ40003CX5Ork+fPmpo2+kc/UggHQSyJYSJCnU6ykybJEACiRNwFeA2bdrIOeecE2UpHXPAUYlY\nHnjxB4al6UggVwl4IYTZEvFcZc58k0AuEYgS4HfffVcOHjzoWoZMvRpyyJAhfA2lay0E90S+CU68\n8noh4sFtLSwZCeQ2gSgBvv3228PvYnYqGt4J/eSTTzqdKrAf3kX98MMPy8yZM9XjHY8//riMGzdO\nMLebjq8wFTjDNOA5gVwVnHhC6gYqV8vrVh76kwAJJE4gSoBXrVqlYu/atUuKFSum3s2szeGVkBs3\nbtSHnm8nTJggb7zxhsyZM0fatWsnLVu2lJdfflngP3DgQM/To0ES8IoAhdQrkrRDAvlDIOpNWHjp\nBoQWnwFcunSp2scxfnPnzhX0kNPl8L3hfv36qW8CIw28mxrvgoYo05FAogTQGzWd/dg858f9VPOb\najw/MmCeSCAfCEQJ8MSJE6VEiRKCF3Bccsklah/H+OHZXAxBp8vha0gQYdPNmzdPfabQ9OM+CcQi\nYO+N2o9jxfXDuVTzm2o8P5SZeSCBfCQQNQR9yy23SPfu3ZUAN2vWLLwSGnfX+lGkdIHCo0J47hgf\ngcBQN74HjDdjLVmyJF1J0i4JpIUA/l+yKYjZTj8tUGmUBAJGIEqAUb6jjz5a+vbtm/GiVq1aVX2C\ncMaMGbJ+/Xo5//zz1S/dwp/xgjLBwBPIpvgCrj19CnLgmxwLmIMEogS4SZMmgvdAL1++XCZNmhRV\nJHyMAZ8ITJcrXbq0dOvWLV3maZcEkiYQBPGyC3LSEBiBBEjAcwIRAozHgKpVqyZnnnmm+gpR48aN\npXz58hGJVqhQIeLYi4MRI0bEfPa4fv360rZtWy+Soo0cJpAtIQyKeGWLXw43OWadBNJKIEKADx8+\nrFYc473Js2bNklatWgm+1Wu6dLydCvO8Y8aMUW+/KlWqlJmc2uczwFFI8tIjKEKYrcojv2yRZ7ok\n4EwgQoDx2M8dd9whGGbG94AnT54shQpFLpTWH2lwNpea7+jRowW9b/zGjh2bmhHGIoEsEYjXs4x3\nPkvZZrIkQAJZJhCprlZmHnroIdm8ebMMGjRIrUbes2ePmD98ISkdbtiwYbJz507ZvXt3OszTJglk\njQB7nllDz4RJwNcEInrAZk4HDx5sHqZ9H4uvpk6dmvZ0mAAJeE0gXwWWPXuvWxLt5RuBqB5wvgFg\neUmABFIjkK83HqnRYiwSiCZAAY5mQp+AEEAPjc4fBFgX/qgH5sJfBCjA/qoP5sZDAuyheQizgKZY\nFwUEyOiBJEABDmS1slC5ToA9xlyvQeafBOIToADHZ8QQJJBxAuwxZhw5EySBjBOgAGccORMkARIg\nARIgAREKMFsBCZAACZAACWSBAAU4C9CZZHAIcK42OHXJkpBApglQgDNNnOkFigDnagNVnSwMCWSU\nAAU4o7iZGAmQAAmQAAn8jwAFmC2BBEiABEiABLJAgAKcBehMkgRIgARIgAQowGwDJEACJEACJJAF\nAhTgLEBnkskR4Erj5HgxNAmQQG4QoADnRj3ldS650jivq5+FJ4HAEqAAB7ZqWTAvCLD37QVF2iAB\nEnAiQAF2okI/Evh/Aux9symQAAmkiwAFOF1kaZcESIAESIAEYhCgAMeAw1MkwCFotgESIIF0EaAA\np4ss7QaCAIegA1GNLAQJ+JIABdiX1cJMkQAJkAAJBJ0ABTjoNczykUCSBDjsniQwBieBFAlQgFME\nx2gk4DUBvwgfh929rlnaIwFnAhRgZy70JYGME0i38PlF4DMOlgmSgE8JUIB9WjHMFgl4TSDdAu91\nfmmPBIJOgAIc9Bpm+UiABEiABHxJgALsy2phpkiABEiABIJOgAIc9Bpm+cIEOAcaRsEdEiABHxCg\nAPugEpiFzBDgHGhmODMVEiCBxAj4VoD37dsnO3fuTKwUDEUCJEACJEACOUbAtwI8e/Zs6du3b47h\nZHZJgARIgARIIDECRycWLL2hTjzxRNmyZUtEIgcOHJBDhw4JhLht27YyadKkiPM8IAESIAESIIFc\nJuALAYa4du3aVTp16iRdunRRPOfOnSsrVqyQYcOGSalSpXKZMfNOAiRAAiRAAlEEfDEE3bx5c1m5\ncqWsXbtWDTtDcCtVqiSlS5eW4447Tu1H5ZweJEACJEACJJDDBHzRAwa/smXLypQpU2TmzJly3nnn\nSZMmTaRw4cI5jJZZJwESIAESIAF3Ar7oAZvZu/rqq2XRokVqTrhatWrmKe6TgPBZXjYCEiCBoBDw\nTQ9YA8XCKwxBv/LKK9qLWxIIE+CzvGEU3CEBEshxAr7oAWPF84ABA6R27dpStGhRqVixohLhBg0a\ncPVzjjcwZp8ESIAESMCZgC96wL169ZJNmzbJggUL5IQTTlDii5dwrF69Wnr37i14KUfPnj2dS0Bf\nEiABEiABEshBAr7oAWPOd/z48dKwYUO18hnzfOXKlZOmTZvKqFGjBI8k0ZFAuglwfjndhGmfBEjA\nJOALAcZQ87Jly8x8hffnz58vlStXDh9zhwTSRYDzy+kiS7skQAJOBHwxBP3ggw9Kx44dZeTIkVK3\nbl31SNKOHTtkzZo16m1YCxcudMo7/UiABEiABEggZwn4QoDPOuss+eSTT9Sbr9atW6fmg9Hrxbwv\nngnm0GDOti9mnARIgARIwIWALwQYeStevLi0aNEinM0ePXoIngmm+IaRcIcESIAESCBABHwjwHam\neCvW0KFD1XC0/Zzb8YQJE+SFF15wPI3XXGJ4m44ESIAESIAE/EDAtwKcChz0mvFzcjNmzJBt27Y5\nnaIfCZAACZAACWScgC9WQTuVGl9FwrA0HQmkQoBTF6lQYxwSIIFMEvCtAA8ZMkRKliyZSRZMK0AE\n+EhRgCqTRSGBgBLwlQAfOXJEzfvihRwXXHCBLF26VNq2bSubN28OKH4WiwRIgARIIF8J+EqAsYjq\njTfekDlz5qj6aNmypdSsWVPgT0cCQSfAYfOg1zDLRwKRBHwlwO+8847069dPatSooXJZpEgR9S5o\niDIdCQSdAIfNg17DLB8JRBLwlQDja0gQYdPNmzdPqlevbnpxnwRIIA4B9qbjAOJpEvABAV8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RK8TOEi+tJLL0UUbNasWVK5cuUIv0wcHDlyRB544AG59957M5FcOI3x48fLzz//HD5223n88cel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\nJEAC/iRAAfZnvTBXJEACJEACASfwf7QadPoVxFMkAAAAAElFTkSuQmCC\n"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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MBAPxYzIR4DrgiXjMI7nJGBYyi0ZZWbSOzqJIOl8zBubIvvSlL+Xn8Qec9KuU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\n3XW+il1xT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      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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TIAC7yTAdAQQQQACBLhQgAHchLlkjgAACCCDgJkAAdpNhOgIIIIAAAl0oQADuQlyyRgAB\nBBBAwE2AAOwmw3QEEEAAAQS6UIAA3IW4ZI0AAggggICbAAHYTYbpCCCAAAIIdKEAAbgLcckaAQQQ\nQAABNwECsJsM0xFAAAEEEOhCAQJwF+KSNQIIIIAAAm4CBGA3GaYjgAACCCDQhQIE4C7EJWsEEEAA\nAQTcBAjAbjJMRwABBBBAoAsFCMBdiEvWCCCAAAIIuAn4LgA3NTVJeXm5W3mZjgACCCCAQEoI+CIA\nNzQ0yPTp02XIkCGSnZ0tRUVFUlBQIKNGjZI5c+akBDQbgQACCCCAQLRAZvQLr55PnTpVNm/eLAsW\nLJDhw4c7wbeyslKWL18u06ZNk7q6OpkyZYpXxWO9CCCAAAIIJFzAFy3gRYsWyezZs2XMmDESCAQk\nLS1NevfuLePHj5dZs2bJvHnzEr7hZIgAAggggICXAr4IwNbVvHjx4pgO8+fPl+Li4pjzmIgAAggg\ngECyCviiC3rGjBkyefJkmTlzpowYMUIKCwuloqJCVqxYITYoa+HChcnqS7kRQAABBBCIKeCLADx2\n7FhZunSpLFmyRFavXi3r1q2TcePGOcd9J0yY4HRJxyw9ExFAAAEEEEhSAV8EYBsFba3guXPnSklJ\niQSDQcnPz5dhw4bJjTfeKFdccUWS8lJsBBBAAAEEYgv4IgAzCjp25TAVAQQQQCB1BXwxCItR0Km7\ng7FlCCCAAAKxBXwRgBkFHbtymIoAAgggkLoCvuiCZhR06u5gbBkCCCCAQGwBXwTg6FHQa9euda6K\nZef+2tWv9mQU9NNPPy0vvPBCzC1ds2aNjB49OuY8JiKAAAIIINDdAr4IwLbRubm5MmnSJOe836qq\nKunbt+8eW9j7Dz/88Jjvs3OJbbQ1CQEEEEAAAT8I+CIAW2C87bbbOn0akt3EwR6x0oABA6S0tDTW\nLKYhgAACCCDQ7QK+CMCchtTt9c4KEUAAAQQ8FvDFKGhOQ/J4L2D1CCCAAALdLuCLAMxpSN1e76wQ\nAQQQQMBjAV90QXMaksd7AatHAAEEEOh2AV8E4ESdhtTteqwQAQQQQACBvRTwRQC2sodPQwpvR11d\nnXPaUFpaWngSfxFAAAEEEEgZAV8cA46laRfVuOGGG2LNYhoCCCCAAAJJL+CLFvDIkSNl27ZtbTDt\n3OCmpiaxQHzOOefInDlz2sznBQIIIIAAAsks4IsAbMH1yiuvlJ/85Cdy2WWXOZ7z5s2TJUuWyN13\n3y0FBQXJbEzZEUAAAQQQ6CDgiy7o4447Tj766CP56quvnG5nC7j9+/eXQCAgQ4cOdZ53KDkTEEAA\nAQQQSGIBX7SAza+wsFAeeeQReeKJJ5wbMBx99NGSkZGRxLQUHQEEEEAAAXcBX7SAo4v34x//WOzK\nWHZM2K7fTEIAAQQQQCAVBXzTAo7GHTx4sDz//PPRk3iOAAIIIIBASgn4rgWcUrpsDAIIIIAAAi4C\nBGAXGCYjgAACCCDQlQIE4K7UJW8EEEAAAQRcBAjALjBMRgABBBBAoCsFCMBdqUveCCCAAAIIuAgQ\ngF1gmIwAAggggEBXChCAu1KXvBFAAAEEEHARIAC7wDAZAQQQQACBrhQgAHelLnkjgAACCCDgIkAA\ndoFhMgIIIIAAAl0pQADuSl3yRgABBBBAwEWAAOwCw2QEEEAAAQS6UoAA3JW65I0AAggggICLAAHY\nBYbJCCCAAAIIdKUAAbgrdckbAQQQQAABFwECsAsMkxFAAAEEEOhKAQJwV+qSNwIIIIAAAi4CBGAX\nGCYjgAACCCDQlQIE4K7UJW8EEEAAAQRcBAjALjBMRgABBBBAoCsFCMBdqUveCCCAAAIIuAgQgF1g\nmIwAAggggEBXChCAu1KXvBFAAAEEEHARyHSZLvfdd59UVFTIpZdeKsOGDXNbjOkIIIAAAgggsBcC\nri3gM888U6qqquS4446TiRMnysMPPyzV1dV7sQreggACCCCAAALtBVwD8MiRI+Wee+6RdevWyS9+\n8Qt588035ZBDDpHLL79c3nvvvfb58BoBBBBAAAEE9kDANQCH8ygrK5NVq1Y5j8zMTOnXr59MmzZN\nLrroovAi/EUAAQQQQACBPRRwPQb81ltvyV133SX294c//KHceuutcuKJJ0p6erq0tLTIoEGDZO3a\ntbL//vvv4SpZHAEEEEAAAQRcA7C1es866yx59NFHpXfv3m2kLAjPmTPHCcJtZiTgRVNTk3PsuW/f\nvgnIjSwQQAABBBDwp4BrF/SVV17pBN5PP/3UKfnvf/97J+g2Nzc7r0877TTJyspKyFY1NDTI9OnT\nZciQIZKdnS1FRUVSUFAgo0aNctaZkJWQCQIIIIAAAj4ScA3AzzzzjMycOVMGDBjgFHfChAny2GOP\nyR//+MeEF3/q1KnyxRdfyIIFC6SystLp4t64caM89NBD8uCDD8oDDzyQ8HWSIQIIIIAAAl4KuAbg\nF154Qf7t3/5NDjzwQKd81hq1gPzUU08lvLyLFi2S2bNny5gxYyQQCEhaWprT+h4/frzMmjVL5s2b\nl/B1kiECCCCAAAJeCrgG4KFDh8pLL73UpmxvvPGGFBYWtpmWiBcW3BcvXhwzq/nz50txcXHMeUxE\nAAEEEEAgWQVcB2HZMeCTTjrJ6RY+5phj5LPPPpMtW7aItYwTnWbMmCGTJ092WtgjRoxwgrxdhWvF\nihVig7IWLlyY6FWSHwIIIIAAAp4KuAZgO83ILrjxyiuvyN/+9je56qqrxLqEbQR0otPYsWNl6dKl\nsmTJEufUps2bNzut3ilTpogde7YuaRICCCCAAAKpJOAagG0j7fSj888/v1u2Nzc3VyZNmuS0eO0S\nmJyG1C3srAQBBBBAwCMB1+bsjh07nG7h0aNHy0EHHRR52FWwEp04DSnRouSHAAIIIOB3AdcW8G9+\n8xvnbkj/9V//5YxMDm+InaOb6GSnIVm3s52GNHz4cOccYDsdafny5c5lL+vq6sS6o0kIIIAAAgik\nioBrAC4pKZGf/vSnTrdwV2+snYZkx3/D5xzb+qz7O3wakl0GkwDc1bVA/ggggAAC3Sng2gV93nnn\nydy5c2Xr1q1dXh5OQ+pyYlaAAAIIIOAzAdcWsF2Jyk7/efLJJ51u4YyMDKfodgnK++67L6GbwWlI\nCeUkMwQQQACBJBBwDcB2B6SjjjrK2YRt27ZJnz59xG5H2BXHgBN1GtIf/vAH5+YRsdxLS0vluOOO\nizWLaQgggAACCHS7gGsAtvOA7brPTzzxhASDQbnnnnucazLb9Zm7IiXiNKRrrrlG7BErWUvegjAJ\nAQQQQAABPwi4HgO21uRrr70mdlMGSyeccIJz+0GbnujEaUiJFiU/BBBAAAG/C7gG4Lfeektuuukm\n2W+//ZxtsFsP2jnAFpQTnbgbUqJFyQ8BBBBAwO8CrgHY7s1rQTg6PfvsszJw4MDoSQl5zt2QEsJI\nJggggAACSSTgegz4+uuvl3HjxsnLL78smzZtcs7JXbt2rXNt6ERvX/g0pIsvvrhD1twNqQMJExBA\nAAEEUkDANQDvu+++zpWoHn/8cVm3bp0cf/zxziN8OlIit53TkBKpSV4IIIAAAskg4BqArfCBQED+\n4R/+ocu3I9ZpSP369ZNLL71UTj/9dO6G1OU1wAoQQAABBLpbwDUA33vvvc6VsNoX6JRTThG7TnQi\nU2Njo3MvYLvt4XXXXSd5eXnO37KyMjnnnHPksccek5ycnESukrwQQAABBBDwVMA1AJ977rnyve99\nzymcnQdsV8aaNWuWnHHGGQkv8M9+9jNZsWKFHHHEEfJ3f/d3zgU/nn76aRk8eLDYseh58+Y50xO+\nYjJEAAEEEEDAIwHXAGx3JbJHdLLXdkGOiRMnRk/u9HO75OVHH30khYWFTuvXrj9tx5wt3XHHHfLL\nX/6SANxpZTJAAAEEEPCTgGsAjlXINWvWOLcojDWvM9MssH/55ZdOi/uqq66SDRs2RLJbtmyZHHDA\nAZHXPEEAAQQQQCAVBFwDsLV0H3nkkcg21tbWyvr1653jsZGJCXpyww03yNlnny0PPvig8zd88Y/p\n06fL//7v/3bJqU8JKjrZIIAAAgggsFcCrgH4/PPPd879DedqN2KwlmpxcXF4UsL+2sCulStXys6d\nO9vkedZZZzndz/n5+W2m8wIBBBBAAIFkF3ANwMOGDRN7dFey47/2iE7jx4+PfslzBBBAAAEEUkbA\nNQC7nYYUveXvvvuu0DqNFuE5AggggAAC8Qm4BuBjjz3WOf5qF+L4wQ9+IJ9//rncf//9Yl3TEyZM\ncHLn3Nz4kFkKAQQQQACB9gKuAdgGYP3617+WCy64wHmPXRf6kEMOEbts5C233NI+H14jgAACCCCA\nwB4IuN4NyS5DaacdRaePP/5YCgoKoifxHAEEEEAAAQT2QsC1BWzn45566qnyzDPPOHdFsgtl2E0Z\nXnzxxb1YDW9BAAEEEEAAgWgB1xbwgQceKO+//75cffXVYndAuv32250AbLcOJCGAAAIIIIBA5wRc\nA3BLS4v84Q9/kPvuu8+5EEZTU5Ocd955Ulpa2rk18m4EEEAAAQQQENcAbMH3tddec7qgzemEE06Q\nQYMGOUEZNwQQQAABBBDonIBrAH7rrbfkpptukvBlIbOysmTatGlOUO7cKnk3AggggAACCLgG4CFD\nhogF4ej07LPPysCBA6Mn8RwBBBBAAAEE9kLAdRS03YfXzv19+eWXZdOmTc51odeuXcuNEfYCmbcg\ngAACCCDQXsA1ANt1mZcvXy6PP/64M/rZ7s9rDxsRTUIAAQQQQACBzgm4BmC7FeC+++4rN998c+fW\nwLsRQAABBBBAoIOA6zHgoUOHyrJly6S5ubnDm5iAAAIIIIAAAp0TcG0B5+Xlyfz5851bBNqArHDX\ns10d6z//8z87t1bejQACCCCAQA8XcA3Ap512mhx22GEdePr169dhGhMQQAABBBBAYM8EXAOwdUHb\ng4QAAggggAACiRfocAzYWr5lZWXOmmpra2X9+vWJXys5IoAAAggg0MMFOgRgu+tRY2Ojw/LBBx/I\n5MmTezgRm48AAggggEDiBToE4MSvghwRQAABBBBAoL0AAbi9CK8RQAABBBDoBoGYg7A2bNggdXV1\nsnnzZqmvr5dvvvkmUpSCggLp379/5DVPEEAAAQQQQGDPBWIG4KOOOqpNTvvvv3/k9YUXXihPPPFE\n5DVPEEAAAQQQQGDPBToE4C1btuwyl7S0tF3OZyYCCCCAAAII7F6gQwAOX/Fq929lCQQQQAABBBDY\nWwEGYe2tHO9DAAEEEECgEwIE4E7g8VYEEEAAAQT2VoAAvLdyvA8BBBBAAIFOCBCAO4HHWxFAAAEE\nENhbAd8F4KamJikvL9/b7eF9CCCAAAIIJIWALwJwQ0ODTJ8+Xey+w9nZ2VJUVCR2wY9Ro0bJnDlz\nkgKSQiKAAAIIILAnAh1OQ9qTNydq2alTpzpX3VqwYIEMHz7cCb6VlZWyfPlymTZtmnNVrilTpiRq\ndeSDAAIIIICA5wK+aAEvWrRIZs+eLWPGjJFAICB2sY/evXvL+PHjZdasWTJv3jzPoSgAAggggAAC\niRTwRQC2rubFixfH3K758+dLcXFxzHlMRAABBBBAIFkFfNEFPWPGDOe+wzNnzpQRI0ZIYWGhVFRU\nyIoVK8QGZS1cuDBZfSk3AggggAACMQV8EYDHjh0rS5culSVLlsjatWud48HW6rXjvhMmTHC6pGOW\nnokIIIAAAggkqYAvArDZ5ebmyqRJk5wWb1VVlfTt2zdJSSk2AggggAACuxfwxTFgTkPafUWxBAII\nIIBAagn4ogXMaUiptVOxNQgggAACuxfwRQuY05B2X1EsgQACCCCQWgK+CMCchpRaOxVbgwACCCCw\newFfdEEn6jSk7du3S1lZWcyt3rRpkzQ2Nsacx0QEEEAAAQS6W8AXATj6NKTVq1fLunXrZNy4cXt8\nGtIbb7whL774YkzDr7/+2rm2dMyZTEQAAQQQQKCbBXwRgG0UtLWC586dKyUlJRIMBiU/P1+GDRsm\nN954o1xxxRVxsZx33nlij1jpySeflNLS0lizmIYAAggggEC3C/giADMKutvrnRUigAACCHgs4ItB\nWIyC9ngvYPUIIIAAAt0u4IsAzCjobq93VogAAggg4LGAL7qgEzUK2mNLVo8AAggggEDcAr4IwNGj\noLkZQ9x1x4IIIIAAAkks4IsAbH7hmzG0t2xubnZu0JCTk9N+Fq8RQAABBBBIWgFfHANev369XHrp\npRIIBOTkk0+Wr776KgJqpw9dcsklkdc8QQABBBBAIBUEfBGAZ86cKQMHDpSPPvpIxo8f79wDeNWq\nVangyzYggAACCCAQU8AXXdALFy6UpUuXSl5ennNBjkMPPVROPfVUefvtt2MWmokIIIAAAggku4Av\nWsAWcK31G04XXXSR2MU5Tj/9dLHrO5MQQAABBBBINQFfBOBrr71WLrzwQrn77rsjvjfccIOcf/75\ncv3110em8QQBBBBAAIFUEfBFF/Qpp5widhMGu2FCdLr11lvl+OOPd+ZFT+c5AggggAACyS7giwBs\niAUFBTJ69OgOnhMnThR7kBBAAAEEEEglAV90QacSKNuCAAIIIIBAPAIE4HiUWAYBBBBAAIEECxCA\nEwxKdggggAACCMQjQACOR4llEEAAAQQQSLAAATjBoGSHAAIIIIBAPAIE4HiUWAYBBBBAAIEECxCA\nEwxKdggggAACCMQjQACOR4llEEAAAQQQSLAAATjBoGSHAAIIIIBAPAIE4HiUWAYBBBBAAIEECxCA\nEwxKdggggAACCMQjQACOR4llEEAAAQQQSLAAATjBoGSHAAIIIIBAPAIE4HiUWAYBBBBAAIEECxCA\nEwxKdggggAACCMQjQACOR4llEEAAAQQQSLAAATjBoGSHAAIIIIBAPAIE4HiUWAYBBBBAAIEECxCA\nEwxKdggggAACCMQjQACOR4llEEAAAQQQSLAAATjBoGSHAAIIIIBAPAIE4HiUWAYBBBBAAIEECxCA\nEwxKdggggAACCMQjQACOR4llEEAAAQQQSLAAATjBoGSHAAIIIIBAPAIE4HiUWAYBBBBAAIEECxCA\nEwxKdggggAACCMQjQACOR4llEEAAAQQQSLAAATjBoGSHAAIIIIBAPAK+C8BNTU1SXl4eT9lZBgEE\nEEAAgaQV8EUAbmhokOnTp8uQIUMkOztbioqKpKCgQEaNGiVz5sxJWlwKjgACCCCAgJtAptuM7pw+\ndepU2bx5syxYsECGDx/uBN/KykpZvny5TJs2Terq6mTKlCndWSTWhQACCCCAQJcK+KIFvGjRIpk9\ne7aMGTNGAoGApKWlSe/evWX8+PEya9YsmTdvXpcikDkCCCCAAALdLeCLAGxdzYsXL4657fPnz5fi\n4uKY85iIAAIIIIBAsgr4ogt6xowZMnnyZJk5c6aMGDFCCgsLpaKiQlasWCE2KGvhwoXJ6ku5EUAA\nAQQQiCngiwA8duxYWbp0qSxZskRWr14t69atk3HjxjnHfSdMmOB0SccsPRMRQAABBBBIUgFfBGAb\nBW2t4Llz50pJSYkEg0HJz8+XYcOGyY033ihXXHFFkvJSbAQQQAABBGIL+CIAMwo6duUwFQEEEEAg\ndQV8MQiLUdCpu4OxZQgggAACsQV8EYAZBR27cpiKAAIIIJC6Ar7ogmYUdOruYGwZAggggEBsAV8E\n4OhR0GvXrnWuimXn/trVr/ZkFPR7770nH3/8ccwttekDBgyIOY+JCCCAAAIIdLeALwKwbXRubq5M\nmjTJOe+3qqpK+vbtu8cWdv1ot4t22LnFWVlZe5wnb0AAAQQQQKArBHwRgO00pNtuu63TpyGNHj1a\n7OGWSktL3WYxHQEEEEAAgW4V8EUA5jSkbq1zVoYAAggg4AMBX4yC5jQkH+wJFAEBBBBAoFsFfBGA\nOQ2pW+uclSGAAAII+EDAF13QnIbkgz2BIiCAAAIIdKuALwJwok5D6lY5VoYAAggggEAnBHwRgK38\n4dOQOrEtvBUBBBBAAIGkEfDFMeCk0aKgCCCAAAIIJEjAFy3ge++9VxobG1036eCDD5ZzzjnHdT4z\nEEAAAQQQSDYBXwRgu/zkb3/7W7nsssvErmbVPrld3ar9crxGAAEEEEAgWQR8EYDvv/9+aWlpcR6/\n+93vksWOciKAAAIIILDXAr45Bnz33XdLZWWlVFdX7/XG8EYEEEAAAQSSRcAXLWDDCgQC8qc//SlZ\n3CgnAggggAACnRLwTQu4U1vBmxFAAAEEEEgyAQJwklUYxUUAAQQQSA0BAnBq1CNbgQACCCCQZAIE\n4CSrMIqLAAIIIJAaAgTg1KhHtgIBBBBAIMkECMBJVmEUFwEEEEAgNQQIwKlRj2wFAggggECSCRCA\nk6zCKC4CCCCAQGoIEIBTox7ZCgQQQACBJBMgACdZhVFcBBBAAIHUECAAp0Y9shUIIIAAAkkmQABO\nsgqjuAgggAACqSFAAE6NemQrEEAAAQSSTIAAnGQVRnERQAABBFJDgACcGvXIViCAAAIIJJkAATjJ\nKoziIoAAAgikhgABODXqka1AAAEEEEgygcwkK68nxV2xrELWfFXtrLulReT4k/eRXoVZnpSFlSKA\nAAIIpIYAATiOevzdfV9J8MhekpYm0lzbIjuebpSfXLF/HO9kEQQQQAABBGILEIBju7SZmpWTLlmj\nApKWnia1X9WI/iEhgAACCCDQKQGOAXeKjzcjgAACCCCwdwIE4L1z410IIIAAAgh0SoAu6E7x8WYE\nEEhWgXlPbpCSjXVO8etqmuTcCwfL8AMCybo5lDsJBQjASVhpFBmBVBOorGiUstL6yGbtNyRPsnMy\nIq/jfVKl+ZSsq4ksPmRYgRQEYn/Nvf7qVpGJfUV0TEfjthb5n99/LQePKnTem5eXIedcMEgys+gk\njGDyJOECsffMhK+GDBFAoKsFPv9kh3wdPl2uWeQHJxZLv/45MVdrgaq2RhdqTQ31zdISDL0IaMAq\nKo79vvDybn+X/bVcGhr0XD1NvftkywGH9HJbtM30O6Z/IY29MyQ9O12qSuokV4Pi4P0LnGWCjUH5\npxsOkECv3Z/6N/PulVLa3CJZhZlSX9Yo/fXUhVPPGOjkk62DKY86tl9kvemZ6ZI5MEfSMnRw5eoa\n2a4r/TAjZJL+WZUceVRfGTZy9y3iyh0NsnXTtz8eBu+fL7kawGOlzSW1sm3Lt8seclhvydD17y61\nNAdl+acVkcX675sjAwblRV7zJDkFCMDJWW+UGgHZsqlW/m/ON5LX2sJb+mG55Bzbx2nRtdS1yOoH\nq+TEU/Z1pPJ1mQMPDbXubMLN/+9Tyd0vFGRLl1dLWnaaFB8aCjbVX9XKPQ8cLoHWc90/1Xx3lDU4\n+XylAf7dN7dJ7wGh9warm+WcHw925m1YWyOvvlUqvQ4PBd0d71fIfoPzJNAnS+prm2XH9gYp7Jft\nLFuhQeiwI/tK776hoFqrQTP3hP6SnpshGR/ukPpNjbL5kFCAafmsWizvg0f3dt67q/8y7IyFIwol\nS/NtXLlTVs8vlUc/3e68ZefSKpmqwe6IY4piZpGu780bke/Ma1ob6poOL7hxfY1UlDc6L+10xP77\n5oZnyW9uXyH1vTIkM09/PGyok7qtDVI8IvTjoXJDrdz2m9Ey6DuhfP/1+s8kMDbkU6VnVJz/o/3k\n9LP3c/KqqW4SC9DhZAHW6s3SKy9slsefLpHCA0P5VOu2PPTE0eFF+ZukAgTgJK04it39AnUaRLZs\n/PYL0r6E3bo3rUVZs/PbFmZAW2SZ2uKKlf7y5AYp3RpqFdVpq/SkU/eRon6hAJeub7GLv1iq2dkk\ns+5aJRn6RW9pm365B07sJ9n7hFpb9dry7HNQvqRrt2mlBr9PP6uQ9aF4J2UfVki2Bp9e2iJubmyR\nOn1L4Mz+Tj5ZFvz2y5WMo0IBuqC2NNKK/WZ1tdx37yrJ/74Gdk2Vb5dLn9P7S9bIAgkGg7Lujq/l\niZU7nHlVf62UwCEFkntMaNmML3ZK7TGFUp+fIY0avGrebpDsSdrlq6lm4Vb5a32DZNaFmt0VOxrl\n25Amkp6ZJlnFocLXS1A++6g80nLsU5QV6Z6u1PfNe6ZECjTIW9qg3c95R4R+SGjxJP87WkfjQoE7\nWNUsz/2lRD7SVrqlnRrw3EJ6neb7yJy10kd/MFidrPikQoqODPls+7hS0rS7oP+BofVs07or/uEg\nySjIkKxPKiV9XZ1k/qjYWUdAvcq3NUQCcGCfbMn+QcggS+vx2SdL5P0PypxlN35TK1n9syRXfzw0\nVDZJoElk0kn7OPOWf7ZD8o7pLdnfDa2zSVvoP7/+U+fUyJ1qe+FPhsiEE0LLNup+sD2qO79QbfIL\n4vuq//zjHZEfW3W6D69fr2XSHyaWhuiPiONPDK3DmcB/nRaIr1Y6vRoyQCD5BeY8tEaWraySvP7Z\n0qRfyn20KfRrbd3ESnf9eoVs1y/4TP3y2qktv8O19XbSaQOcRTM0uBT0+vaj99rLWyV9Yiho1eqX\n9Ue3rZDig1u/3FftFPvSztUv0ZrSBmnKT5O+Pw61arOf2iLWassZ3Bq6onsytcuy4OACyWkNnFlf\naT4naLDWZZu17FWPbo5VbGdajXZP/8/sryVPv7TL9Yu81/B8DWqh4FOvrcrolN07SwKt8yzIRhfB\nWoppFkg1oDRXNWmwECdI2fvtnPp07abNP6i1pfhqKAhF5x1+XqkBbVFFk+RW1EmwISjlb5TJwPGh\nIFaqAS+gAbbm4FDLsO5v1eLWMVuvLdNSNSnvGypljQ68cg3AGgDLNODuUN8mLXv62kzJmtAaOLU+\nc/fPk8yxIZO0B9aHi9rhb63W2X13rZQ+2mMQ1B9SO9QoHMKatIs869B8qWrNp0lbvwE9Jp2p+1fj\n1zWy9a1yeXZdlZNn7YYaye8fWp9N0OqV5jP66cWB0qRF95H//d3X8ty8jc6yZfqDICuQofuN/tiq\nb5Feuszt94xx5tkPqn+d9pkU6TF2S0Gdf9f9h0lefqasW7NT7tUu/ILxIZWKd3dI4cQiyUgL/cB7\n/7H1kQBsXeKL5m+SRj08YKmP1vGxk4olfS8ukrBh7U6p0wscWcrJTRc7bt9T0rffAj1lixOwnRu/\nqZE3F21xcupTlC1j9FgRyVsBG3hTuvnbY2tjjuwj6a3H1rZtqWtz/MwCi32BWMrQ75bMrNAXjL1+\n8/WtUl0XarlW6RdkLw0wRa0tsVWrqiTbviD1uKHol7K8VWFviZkatIWUpS1MaxVlLKuSd1/eJn+r\nDnXjbtPWS5Z2tfbRYBjU5SqrGmXAd0JfiDUrdkqvo3tL5rGhfSpjU53knNLP+VLOWr1TGj+ocoJX\nzJUmaGKtttw3DAsdG22QFmnWVpBbUEvQKneZjbWGCzQY5g7NkxYNGDvVM9MGT2nK1iCapt9iWa1d\n221+AbTPVeNuek6a5LZaW/ByTfbjQY9HZ2tdB/XfLvN1zUScH2r5uh+ka9mtx6DlDxvaLG3HnzPD\nP8baFceOhwcOC3VX12uQjU7Ojxt9ry3ToocB8rTnIf2k0PHt9D9tlDz9sZU5JFfS9MdW7XOl8skH\noVb/50t3SK+TiiTnyFCQrX18syx8ZqPT1W2D4Ppoz0b2UaF5dX/Tiw5pKz3vgNCPm83anW+tbkvb\ndJ/IOVTXqT0nltLe2SmV5Q3Sfx/9gdcUlBUrK6Wx9TNm+e7Y3ih99IekpUzlPGZ8qKzWUl8wf7P0\n1rwsVej+/8sZh8r+MUajV+vn5H8eWCM5+aEW+Rb9bGRK6Ieq8+Yk/I8AvIeVVq+nLXz2ZbWs0QEj\nlmqW7JDb/u27MnREcu8Ie8jg+eJfaJfcguc2Sa52b1oX7dK3t0vfcDepfoh/osclTzg91OL8zR1f\nSkV/7QLWVmTdulqp/7pWilq7Acu1/rI0yIaPrW17f4fsc9kg5wt35ydVskO74bb2C9V1pX7Zh9sg\nLdrNt3Zltdxw3SeOxTb9UWZdnv20ZWTJjnf2l1CQsEFE+QcWSOak0LHHLB1kZF26GdqyDOqXlfxh\nvfMev/xnX+5mland5tZK+7Yj3S8lTLJyWDDXHxGiv9m6LIXX4axAX0SlTdq1/fDroR6P7R9USOFx\nod4WW6RS6/e18lpJq0qThlI9xq37eOtRi6gcQk9bNNuWH4YOW2Ro17ptU4FeIdDSVn393IfbJUcH\nh1lPQ4M+ep8cCrKVq+olV/f/pmGhz8aWhzbIGo3bdry/ZkW15OyfG/lsFOjhkRef3xQZYNZXDzcU\n9Q2VyAahrWpu0h9boXyq9JBM6BMWKl8y/k8A3tNa0+/LwCEBCbQeD8otb3K+ePc0m2RY/mvtbtXN\ndZLdfGKfgaFfuzZY5D+1Wy3Y2sJs0F/ZN/7iILHeAEs2345XWirRwDTrP1ZJXx0ZaqlMX9vxqHz9\ncm/QbqfDjugjV1473JnX/r8Xntsoq7XVZ92VlToI6KvlldK79Rf3dv0hVHiGtjBtkIq2ItN0EEy4\nu1UbOfLow9/Ia6+XOlmWaZdq71OLnKCSZi1SLVre90K/8mu0qy/v8ELJ0a5JS+l6HDOzT2aolalx\n11pBOdqSsBTdYgpqAM7oq0H9wlCHYtazWyV3eJ7kaF5OetBfQTVUKP7viQLZ/bIin41s/WEYneyw\nQK4OPLMfW/JFlTTqsW+3ZPu/HfJwUtsY77TE8/Uzla0BOE1bx81v6IDA8Ofmg7TIoQh7b5Z+Zgv0\nsEWGHoJo0V/Pwa3f/jKp3twgn2kX/Oc7dKyF/rAue2Sd7HtcKMyW6bH3gK4jnG8qXBOYABzanRL2\n/3o9jlIe3sl1Jx2jIz33Jtl5kTutm7M12aAea2FZsgAWDoahKfH9b3nep8d4rPvTUlC7iP75ZwfG\nHEhkXVazZq6SIv2xYan6y506Mnas0yW7dXOdbNfQnD4u1D3WpKNUv9FAGQ7AN0/9RLL0g2hpux6T\nC2iXVmZrizPtf0ok235F6y/bDO06K/kodIzLlv1ER9vO0vL11e46S9vW10nfc/fRYChSq4NSs/VX\ndJYOALKUNXej86HP0S5C65Z0mqzOHD2nU3/VZ+vNM+pag2Hz/21qnZP4P9aFSEIAgcQI2Gc9S78b\n7Bi7fa6z9cdwdmuLPdv5Pgw3CRKzPq9zIQB3sgaqdcDDvdoa7KWDEOq1JViq3Yv9xoe6eHZ8XiWn\nHL+PjDw0FKje1BbZFj3mYYNwanVnOkNPPzi5tZu0fTGm62ki4V9627XLW3TH7NeaT5UeD7pr1mF7\nfK7muq93Slme/oo9LNTaa9Lu1+f+vD4SzLOy0iKDKlZ9USn5Opo1s7Wln6nHV5/40zpnYE7Z1jr9\ncRrUD0do5Kn9TFiu56CGfzAENZ/M1q6q7FfTIj8cbBudw272S1pH6jY1NMpq/dV9owZsS6XaOi60\nEbajQ15pv18v2Xr8NV0HZtTr6R17kiwwZmj3tCVnnXvyZpZFAAEEukGAANxJ5Cb9lZang2Qa9Fdb\ns3aTZr6iv9rsXExNGTqi9cU3S+W9HaHgUaYDIPb9h0HSrMGhRUdH/m1VtQbgUAHe0KvyPK7dLQEN\n5DYwp0a7ZgpOCx1DyUrTYGfnGX4/1JoO6Okwq7V72M7NtIEdJdrlU63dvpZ2atfvN3rMJ791YMc+\nekGFCy4eElqJ/u+MStWyWqrQMrzZv07S6zQfPdC3U48PBVpHQNboqMs8PUYZTjt1FOon2drV29Io\nDc3aGtcyhDpmtXWsx1Vf3lgv+dWhQVA7tAX67TvDOXT8a79wM/W0i4zzW7tx523puBBTEEAAgRQV\nIAAnomL1GKUdz2jSv9EdkjbAJvA9Hb3Z2hWasbRSW7KhZes1+Pz13e1yc+tl87bpiL78U/tJ0I6b\naC9Ls3bVuqVybWXPeWqD5GmwrtEWeIMO8slrPbm/5lM9TUbPFcwqDrX+ljyxQd55v8zpxt2hgTJv\ndODbQRZa2JxBuc5pLHZqSq0OOgq0lrVOg3h0sq6h7EE5zojNZr3IQ5MG73Cy1maBnkNqoyWdUb3v\nVYRnxfE3dHwojgVZBAEEEEgpAQKwR9XZrBcFyByqQ/a19eykpzY73czOaQU6EnBXyVqxuXpBg0w9\n9cJOTWn6sEoKWrtt63QEcFrUuaE2iCjzbD0NQrt8s98pl2DNrvPe1XqZhwACCCCQOAECcOIs9zgn\n52IEenzTSRyo3GM/3oAAAggks0Drt38ybwJlRwABBBBAIPkECMDJV2eUGAEEEEAgBQQIwClQiWwC\nAggggEDyCfguADc1NUl5eei6pcnHSYkRQAABBBCIT8AXAbihoUGmT58uQ4YMkezsbCkqKpKCggIZ\nNWqUzJkzJ74tYSkEEEAAAQSSSMAXo6CnTp0qmzdvlgULFsjw4cOd4FtZWSnLly+XadOmSV1dnUyZ\nMmW3rHPnzpVnnnkm5nIlJSUybty4mPN2N9EuGNH84nZnsUy9nVj1lgbJa719VqNeoKJu0XbJsDvm\n6PWBG/T82KaF25xlG9fUSpPeSi13Y+icWTvXtuklvYijniaUoVfC2llSLwXhZfV9tS+XSdbgGue9\ndvu2cD6ZemnL6uV6v9QdocviN+klHOsX6bm9vbX69IIY9XpecHjZBr1iVLNeCD2n9YbiLbpOK3uL\nXRlKL0VZvUnL3noLsaYdTbpOLbteNtIuc2kX3g/nk63zdn5dLnmal6UmvUNOgxnotZTT9XmtnlMc\naC17g95cPfiKln1Va9ltO1vnOV6aR66W2clHt6tODdL1+rSidx2q1/eGl238RsuuJjnrQxf0sLKb\nV7peWStDbw9XZRf7aL0SXaPeXaVGvTLtpvJWdt22cD5ZOq96ZY3kbg9dnMTx0nxEL06SrnnaDRnC\nyzaqR0tZmWTrDRosWR01v6DL6jnSkbrW854tta3roDRu+3adjas1Ty1/pK7VqFH3i3BdV0fXtb6v\nxrwidR3lFa7ripCXna5Wr/mk2VXHYtW17os5ul5LLbpPNmkd2V2g0q2u9bq6+a1XM23Sa5a3qWvd\nj8MG2bZPa/lzW+u6eafux+aldZ0Wq6711oHZf2v10jKF84nUtb7fUpPWWZ3up5G61vKEl23Q/bNp\ng16kXx+WQnWty1pd6z5SaTescOaoe4e6/vazkaWW0XXdrPtZg3lF6vrbz0aj5tmiy2evCXk1W9nV\ny05ACJc9Tz/rluyzUWefDedzrXWtNyoIl92pay1/ru47liyfRvUK6hkN6Vr2Kv0Mfvu5blfXWr5w\nPpm2n27bqbdZDH82dN/UfNL0/H6nrnV/Dy/boJdlbVa/cF036+mEzmcjXNdalvxQNs69l2tf+fZz\nbbeJDOeTrZ/xaq273K2haz432+fara716nfB6Lpu/7nWfS+3ta4bd1HXjWrVHFXXjrt56SmSVtdV\n9tlovYCCU9da9ky75rt9rjXfcNkz9cJGdknc3LLQTm1lrzcvu461XnMhV+/ElGwpTa+k1PqV5l3R\nhw0bJkuWLJEBAwZ0KMR7770nt956q7z00ksd5rWfYIHaHrFSY2Oj5OXlSSCw53ctsttgVeuOEE72\ngXVTi76Benj58N80vaJVMNi6p+nE6Hyin9vyer0Ou8dAzNR+He3fG/2m9ss6Vwppzbf9++xiG3bP\n0lip/bK7yid6nuUV/V67oHv0Ltd2XjtXo4oyaLNsu7K2W7TNOttvT7RtdJ7ty9r+dft1dLCNWlH7\nedHrUQH9Z7mFUvtlw9Ptb/t50flEL2fP28+Lfh393Hlf+42Jyqz9stGvo5/Hyid6/q7q2u4b2xK9\ng7crT3Q+HfYnXXHUbtFmu9u8T5eLruv2+bSZp8tGv7ddcTrUg7Ptrf/tqo7a1/WuPmPt84leR/vn\n0WW1edHlbT+vzUxbVhcOf39FP3fy2cW8XecT/+e6vUGbMkRvSLvt2l35ivQmDtk5oQsQ2bLJkHzR\nArau5sWLF8vFF1/cwWz+/PlSXFzcYXqsCbm5uWKPRKdAL73puD5ICCCAAAIIJErAFy3gpUuXyuTJ\nk6VXr14yYsQIKSwslIqKClmxYoXYoKyFCxfK0KFDE7XN5IMAAggggIDnAr4IwKZgXcfWDb127Vrn\neLC1ekeOHCkTJkzQLhPrlyAhgAACCCCQOgK+CcCpQ8qWIIAAAgggsHsBX5yGtPtisgQCCCCAAAKp\nJUAATq36ZGsQQAABBJJEgACcJBVFMRFAAAEEUkuAAJxa9cnWIIAAAggkiQABOEkqimIigAACCKSW\nAAE4teqTrUEAAQQQSBIBAnCSVBTFRAABBBBILQFfXIrS76R2dS67UxMptoDd6MKuXmZXMiN1FLCL\nzGzZsoWruXWkiUxZuXKlHHTQQZHXPGkrYPtPTk6O9OnTp+0MXjkCdq1/u2DT22+/nVQiBOA4qsuC\n7+uvvx7Hkj1zkV/96ldy8sknyw9+8IOeCbCbrbbgMnPmTHnwwQd3s2TPnT1x4kQ+Y7uoftt/rCHw\nox/9aBdL9dxZW7duFburXrIluqCTrcYoLwIIIIBASggQgFOiGtkIBBBAAIFkEyAAJ1uNUV4EEEAA\ngZQQIACnRDWyEQgggAACySZAAE62GqO8CCCAAAIpIUAATolqZCMQQAABBJJNgPsBx1FjmzZtkoED\nB8axZM9cpLy8XPLy8iQ3N7dnAuxmq+0cxYqKCunfv/9uluy5s/mM7brubf/JysqS/Pz8XS/YQ+e2\ntLTItm3bZJ999kkqAQJwUlUXhUUAAQQQSBUBuqBTpSbZDgQQQACBpBIgACdVdVFYBBBAAIFUESAA\np0pNsh0IIIAAAkklQABOquqisAgggAACqSJAAE6VmmQ7EEAAAQSSSoAAnFTVRWERQAABBFJFgACc\nKjXJdiCAAAIIJJUAATipqovCIoAAAgg0NTVJMBhMeggCcGsVvv7663LcccfJsGHD5NxzzxW7ulOs\nFO9ysd6bzNPM48c//rGMHDlSRo8eLe+++27MzVm+fLlcfPHFcthhh8mJJ54ojz/+eMzlUnHinXfe\nKWPGjHH2IXu+u3TNNdfIP/7jP+5usZSZH+9n5/3335ejjjpKvvvd78oPf/hDWbFiRcoY7GpD4v2M\nbdiwQS655BI5/PDD5fTTT5c33nhjV9mm3Lz169fL0KFD5euvv3bdtj39LLpm1NUz9FdEj0+lpaVB\nvdRk8NNPPw02NDQEr7/++uAVV1zRwSXe5Tq8MQUmXHjhhcHbb789qJd8Cy5evDi47777Bmtqajps\n2cknnxz84x//6EwvKSkJ6qXhgps3b+6wXKpNeOKJJ4LHHntscMeOHUG9rGJQf4AEFy5c6LqZ8+fP\nDxYVFQU1CLsuk0oz4v3s1NXVBYcPHx5csmSJs/mPPfZY8Pzzz08lCtdtifczdtVVVwX//d//3cnn\nww8/dLz0cqeu+abSjP/+7/8OjhgxIqiX5Qx+9dVXMTdtTz+LMTPpponWjO/x6YUXXgiecMIJEQf9\nZRXs3bt35HX4SbzLhZdPpb+9evUKbt++PbJJRx55ZHDRokWR1/akubk5+Je//MX5EROeYR+WXQWi\n8HLJ/vfKK68MPvDAA5HNuOuuu4JXX3115HX0E71mbfCYY44J3nrrrT0mAMf72XnmmWeCp5xyisNl\nP2Z6UornM2YeZ599dvCee+5xaL788sugXh86aD9cUj3V19c7+8bKlSuDxcXFrgF4Tz6LXpvRBa1d\nDOvWrWtzswVt3TkXz9cKb9MBEe9ybd6UAi+sa8wstMUW2ZoBAwbI1q1bI6/tSXp6upxzzjnORePt\n9auvvup05Y8fP95epnRqv2+Yz5YtW2Ju85QpU+S2226TQCAQc34qTmzv4/YZ++abb5z9bMKECaJf\nsqI/4OSLL75IRZI22xTvZ8zedMcdd8hDDz0kF1xwgWiPk/z+97+XnJycNvml4ovs7Gx56aWX5MAD\nD9zl5rXf13b1WdxlRt0wkwCsyNqyk4KCggi33dnHknaxRqbZk3iXa/OmFHjRfrttk8yourradetW\nrVrlHKf67W9/K3369HFdLlVmtDeyu9bs3Lmzw+Y9+uijjt2pp57aYV4qT2jv4/YZ065q0S5Eufba\na53P22mnnSZ33313KtM429bexya6fcbeeecdZwDSIYccIoMGDRI7tm6DkkghgfaWbp9FP3gRgLUW\n7DZxlZWVkfqoqqpybq3Xt2/fyDR7Eu9ybd6UAi/ab7dtknntt99+MbdOu8Vk4sSJ8qtf/coZkBVz\noRSb2N4olo99MUybNk30cIfoMWBncJG1+PR4Z4ppdNyc9j5unzH7sWaDryZPnizaJSs///nP5bnn\nnhMdm9Ex0xSa0t7HNi3WPmSB9l/+5V/kz3/+s+iYDLFgrIeC5O23304hjc5tSnvLWI6dW0Pi3p2Z\nuKySN6fBgwfL2rVrIxtgz4cMGRJ5HX4S73Lh5VPlr30p2q9xG31pBpbM6Dvf+U6HTbSRiSeddMb2\nhDAAAAiLSURBVJLccsstTiumwwIpOsFcLJiGU6x9SI9pygEHHCCzZ892Ftu4caPosTuZO3eupHo3\nfbyfHVvOAm842T1wa2trxe73msop3s+YdVXrWAvnLAPzsMM+Oh5D1qxZ4/zoTWWjeLctns9ivHl1\n+XJeH4T2w/ptAION1n3llVecwQyXXnpp8Oabb3aKVlZWFnz55Zed57tazg/b0ZVlsIENU6dODdpo\ny6eeeip48MEHRwZb2ahoG+Vq6fvf/35Qf6E7A7a0xef8tcETqZ5skJGeghS0kd/6ZRjUQBu0EaqW\n9NSs4LJlyzoQ/Md//EePGYS1q89O9GdMWyvBfv36BfVUJMdLj3cG9XhwB7tUnBDvZ0x/4Aa1BewQ\n2IBR7akLmmFPSu0HYUV/xnb1WfSbEaOgW2vEhq7roJigHlMJTpo0KahdZM4cPcfOGWUYrji35cLz\nU/WvBZVRo0YFtdvZOQ3Agm442SlJCxYsCH7wwQd2ZnyHx8MPPxxeNGX/2ulZduqatmSCOujDGeEc\n3tjrrrsuePnll4dfRv72pABsG+322Wn/GXv22WcdQxtBf9BBBwUtyPSEFM9nzBzsc3bGGWc4P/js\nR5+dmtPTUvsAHP0Z29Vn0W9OaVagLm9mJ8kK7PiKHZtqf+y3ffHjXa79+1LhtQ2SsdGppNgCdrzJ\nRqT2hFGpsQV2PTXez459LenpWj1yX4v3M2b7WmFh4a7Be/DcZPgsEoB78A7KpiOAAAIIeCfAKGjv\n7FkzAggggEAPFiAA9+DKZ9MRQAABBLwTIAB7Z8+aEUAAAQR6sAABuAdXPpuOAAIIIOCdAAHYO3vW\njAACCCDQgwUIwD248tl0BBBAAAHvBAjA3tmzZgQQQACBHixAAO7Blc+mI4AAAgh4J0AA9s6eNSOA\nAAII9GABAnAPrnw2HQEEEEDAOwECsHf2rBkBBBBAoAcLEIB7cOWz6QgggAAC3gkQgL2zZ80IIIAA\nAj1YgADcgyufTUcAAQQQ8E6AAOydPWtGAAEEEOjBAgTgHlz5bDoCCCCAgHcCBGDv7FkzAggggEAP\nFiAA9+DKZ9N7jkB9fb386le/km3btvWcjWZLEfC5AAHY5xVE8Xq2wIMPPiiZmZlSWFjoPPr37y/n\nnXeerFixIgJz+umnS15eXmSZ8LJ33323s8wzzzwjo0ePlj/96U8yadIkmTFjRuS9iXyy3377ycqV\nKxOZJXkhkNICBOCUrl42LhUETjjhBKmsrHQe33zzjRxxxBFiQXfr1q2Rzbvnnnsiy4SX/fnPfy4t\nLS3yi1/8QubPny/HH3+8vPPOO/LBBx9IdXV15L08QQABbwQIwN64s1YE9kqgoKBAfvnLX0rfvn3l\nscce220e6enpUlZWJlu2bHGWtdaxBeNAICDLli2Tiy++WC6//HLZZ5995Oyzz3aCugXnww47THbs\n2BHJ/6c//alYS7qmpkauvfZaGTRokBQVFcmFF14oVVVVkeV4ggAC8QsQgOO3YkkEfCMwduxYWbVq\nVaQ8b7zxhtx///1tHhZ4Ld1yyy1y6qmnyptvvim2XDAYdKbX1dXJn//8Z9l3333lyy+/lAEDBsjV\nV1/tBGfrTn7++eed5SzoWvf1hAkTZNasWbJ69WpZunSpLFmyRD777DN5/PHHneX4DwEE9kyAALxn\nXiyNgC8EBg4c6LRsw4WxY6+vvvpqm0e4m3natGny1ltvibWezzrrLDnnnHMiQdiOL1uL2lqzP/vZ\nz2TBggViA7asZfz000872S9cuFDGjx8vdvx58uTJ8sgjjzgt5tzcXBk5cqRs3rw5XAz+IoDAHghk\n7sGyLIoAAj4RWL9+vQwePDhSmmuuuUb+6Z/+KfK6/ZMjjzxS7PHCCy84f1988UUnoH73u9+VXr16\nOYsfcMABkp+fL3ac2YL0P//zPzvHip966im56KKLnGUyMjKc6daSLi4ulsbGRhk3blz71fEaAQTi\nEKAFHAcSiyDgJ4Ha2lp55ZVX5Pvf//5ui7Vp0yYnmNpgLEvWtXz44YfL9u3bnddr1qyR5uZm5/m6\ndeucY7xDhgxxRlTb4K9nn33WaVWfe+65zjJ2/Nday3b8+PPPP5fvfe97kda0swD/IYBA3AIE4Lip\nWBABbwSslWnHc0tLS+Xjjz+Wyy67TPr06SM/+tGPIgWy47S2TPTDuqDt+K4d+33yySedZUtKSpxR\n0Geeeabz2kZMz5s3zwmiDz/8sBx77LHOKU0201q9du7wcccdJ71793aWt8Btr23Q1oYNG+Tll192\nWsHOTP5DAIE9E9ABGSQEEPCpwAMPPGAjppxHWlpaULt9gxdccEFQu4kjJT7ttNMiy4SXtb8aoJ1l\ntBUb1IAd1JHTQT1mG9TBWs50PR0pqAE6qOcIB7U7Ozhq1KigtoIj+WpQD+po6aAO1IpM0+PCwaFD\nhwaPPvrooLZ+g9oiDupIaGe+HpcO6mCuyLI8QQCBXQuk2ew9C9ksjQACySbQ1NTktGgfffRRyc7O\ndor/4YcfyiWXXOKMgLaWs3Utx5PsK8NawjYoi4QAAnsvQBf03tvxTgSSRsBGO995552R4Nu+4PEG\nX3uftsQJvu0BeY3AXgjQAt4LNN6CQCoI2HWhbTTz+eefnwqbwzYgkHQCBOCkqzIKjAACCCCQCgJ0\nQadCLbINCCCAAAJJJ0AATroqo8AIIIAAAqkgQABOhVpkGxBAAAEEkk6AAJx0VUaBEUAAAQRSQYAA\nnAq1yDYggAACCCSdAAE46aqMAiOAAAIIpIIAATgVapFtQAABBBBIOgECcNJVGQVGAAEEEEgFAQJw\nKtQi24AAAgggkHQCBOCkqzIKjAACCCCQCgIE4FSoRbYBAQQQQCDpBAjASVdlFBgBBBBAIBUECMCp\nUItsAwIIIIBA0gkQgJOuyigwAggggEAqCPx/dOAUJMBTqfEAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 56
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%R write.table(DE, \"HK_V_DESeq.txt\", row.names = FALSE, sep=\"\\t\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Error in is.data.frame(x) : object 'DE' not found\n"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "!DE(head)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "/bin/sh: -c: line 0: syntax error near unexpected token `head'\r\n",
        "/bin/sh: -c: line 0: `DE(head)'\r\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}