{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Attaching package: ‘proxy’\n",
      "\n",
      "The following object is masked from ‘package:Matrix’:\n",
      "\n",
      "    as.matrix\n",
      "\n",
      "The following objects are masked from ‘package:stats’:\n",
      "\n",
      "    as.dist, dist\n",
      "\n",
      "The following object is masked from ‘package:base’:\n",
      "\n",
      "    as.matrix\n",
      "\n"
     ]
    }
   ],
   "source": [
    "library(data.table)\n",
    "library(Matrix)\n",
    "library(proxy)\n",
    "library(Rtsne)\n",
    "library(densityClust)\n",
    "library(data.table)\n",
    "library(irlba)\n",
    "library(umap)\n",
    "library(ggplot2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preprocess"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`bsub < count_reads_peaks_erisone.sh`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "5335"
      ],
      "text/latex": [
       "5335"
      ],
      "text/markdown": [
       "5335"
      ],
      "text/plain": [
       "[1] 5335"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path = './count_reads_peaks_output/'\n",
    "files <- list.files(path,pattern = \"\\\\.txt$\")\n",
    "length(files)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#assuming tab separated values with a header    \n",
    "datalist = lapply(files, function(x)fread(paste0(path,x))$V4) \n",
    "#assuming the same header/columns for all files\n",
    "datafr = do.call(\"cbind\", datalist) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>97998</li>\n",
       "\t<li>5335</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 97998\n",
       "\\item 5335\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 97998\n",
       "2. 5335\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 97998  5335"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dim(datafr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_regions = read.csv(\"../../input/atac_v1_pbmc_5k_peaks.bed\",\n",
    "                      sep = '\\t',header=FALSE,stringsAsFactors=FALSE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>97998</li>\n",
       "\t<li>3</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 97998\n",
       "\\item 3\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 97998\n",
       "2. 3\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 97998     3"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dim(df_regions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "peaknames = paste(df_regions$V1,df_regions$V2,df_regions$V3,sep = \"_\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'chr1_10244_10510'</li>\n",
       "\t<li>'chr1_237575_237942'</li>\n",
       "\t<li>'chr1_565098_565554'</li>\n",
       "\t<li>'chr1_569172_569645'</li>\n",
       "\t<li>'chr1_713421_715095'</li>\n",
       "\t<li>'chr1_752386_753061'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'chr1\\_10244\\_10510'\n",
       "\\item 'chr1\\_237575\\_237942'\n",
       "\\item 'chr1\\_565098\\_565554'\n",
       "\\item 'chr1\\_569172\\_569645'\n",
       "\\item 'chr1\\_713421\\_715095'\n",
       "\\item 'chr1\\_752386\\_753061'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'chr1_10244_10510'\n",
       "2. 'chr1_237575_237942'\n",
       "3. 'chr1_565098_565554'\n",
       "4. 'chr1_569172_569645'\n",
       "5. 'chr1_713421_715095'\n",
       "6. 'chr1_752386_753061'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] \"chr1_10244_10510\"   \"chr1_237575_237942\" \"chr1_565098_565554\"\n",
       "[4] \"chr1_569172_569645\" \"chr1_713421_715095\" \"chr1_752386_753061\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(peaknames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'AAACGAAAGCGCAATG-1'</li>\n",
       "\t<li>'AAACGAAAGGGTATCG-1'</li>\n",
       "\t<li>'AAACGAAAGTAACATG-1'</li>\n",
       "\t<li>'AAACGAAAGTTACACC-1'</li>\n",
       "\t<li>'AAACGAACAGAGATGC-1'</li>\n",
       "\t<li>'AAACGAACATGCTATG-1'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'AAACGAAAGCGCAATG-1'\n",
       "\\item 'AAACGAAAGGGTATCG-1'\n",
       "\\item 'AAACGAAAGTAACATG-1'\n",
       "\\item 'AAACGAAAGTTACACC-1'\n",
       "\\item 'AAACGAACAGAGATGC-1'\n",
       "\\item 'AAACGAACATGCTATG-1'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'AAACGAAAGCGCAATG-1'\n",
       "2. 'AAACGAAAGGGTATCG-1'\n",
       "3. 'AAACGAAAGTAACATG-1'\n",
       "4. 'AAACGAAAGTTACACC-1'\n",
       "5. 'AAACGAACAGAGATGC-1'\n",
       "6. 'AAACGAACATGCTATG-1'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] \"AAACGAAAGCGCAATG-1\" \"AAACGAAAGGGTATCG-1\" \"AAACGAAAGTAACATG-1\"\n",
       "[4] \"AAACGAAAGTTACACC-1\" \"AAACGAACAGAGATGC-1\" \"AAACGAACATGCTATG-1\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(sapply(strsplit(files,'\\\\.'),'[', 2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "colnames(datafr) = sapply(strsplit(files,'\\\\.'),'[', 2)\n",
    "rownames(datafr) = peaknames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>AAACGAAAGCGCAATG-1</th><th scope=col>AAACGAAAGGGTATCG-1</th><th scope=col>AAACGAAAGTAACATG-1</th><th scope=col>AAACGAAAGTTACACC-1</th><th scope=col>AAACGAACAGAGATGC-1</th><th scope=col>AAACGAACATGCTATG-1</th><th scope=col>AAACGAAGTGCATCAT-1</th><th scope=col>AAACGAAGTGGACGAT-1</th><th scope=col>AAACGAAGTGGCCTCA-1</th><th scope=col>AAACGAATCAGTGTAC-1</th><th scope=col>⋯</th><th scope=col>TTTGGTTGTCAGAAAT-1</th><th scope=col>TTTGGTTGTTGTATCG-1</th><th scope=col>TTTGGTTTCAGTGGTT-1</th><th scope=col>TTTGTGTAGGAAACTT-1</th><th scope=col>TTTGTGTCAAGCCTTA-1</th><th scope=col>TTTGTGTCACTCAAGT-1</th><th scope=col>TTTGTGTCACTGGGCT-1</th><th scope=col>TTTGTGTGTACGCAAG-1</th><th scope=col>TTTGTGTGTCTGCGCA-1</th><th scope=col>TTTGTGTTCAACTTGG-1</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>chr1_10244_10510</th><td>1 </td><td>0 </td><td> 1</td><td>6 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>⋯ </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>1 </td><td> 1</td><td>1 </td><td>0 </td></tr>\n",
       "\t<tr><th scope=row>chr1_237575_237942</th><td>0 </td><td>0 </td><td> 0</td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>2 </td><td>0 </td><td>0 </td><td>⋯ </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td> 0</td><td>0 </td><td>0 </td></tr>\n",
       "\t<tr><th scope=row>chr1_565098_565554</th><td>0 </td><td>0 </td><td> 6</td><td>0 </td><td>0 </td><td>2 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>⋯ </td><td>2 </td><td>0 </td><td>0 </td><td>0 </td><td>4 </td><td>0 </td><td>0 </td><td>12</td><td>0 </td><td>0 </td></tr>\n",
       "\t<tr><th scope=row>chr1_569172_569645</th><td>0 </td><td>0 </td><td> 8</td><td>6 </td><td>0 </td><td>4 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>⋯ </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>2 </td><td>0 </td><td>0 </td><td> 0</td><td>0 </td><td>0 </td></tr>\n",
       "\t<tr><th scope=row>chr1_713421_715095</th><td>4 </td><td>4 </td><td>10</td><td>4 </td><td>0 </td><td>2 </td><td>0 </td><td>6 </td><td>0 </td><td>4 </td><td>⋯ </td><td>2 </td><td>4 </td><td>2 </td><td>2 </td><td>2 </td><td>0 </td><td>8 </td><td> 4</td><td>0 </td><td>0 </td></tr>\n",
       "\t<tr><th scope=row>chr1_752386_753061</th><td>4 </td><td>0 </td><td> 0</td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>⋯ </td><td>2 </td><td>2 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td>0 </td><td> 0</td><td>0 </td><td>0 </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll}\n",
       "  & AAACGAAAGCGCAATG-1 & AAACGAAAGGGTATCG-1 & AAACGAAAGTAACATG-1 & AAACGAAAGTTACACC-1 & AAACGAACAGAGATGC-1 & AAACGAACATGCTATG-1 & AAACGAAGTGCATCAT-1 & AAACGAAGTGGACGAT-1 & AAACGAAGTGGCCTCA-1 & AAACGAATCAGTGTAC-1 & ⋯ & TTTGGTTGTCAGAAAT-1 & TTTGGTTGTTGTATCG-1 & TTTGGTTTCAGTGGTT-1 & TTTGTGTAGGAAACTT-1 & TTTGTGTCAAGCCTTA-1 & TTTGTGTCACTCAAGT-1 & TTTGTGTCACTGGGCT-1 & TTTGTGTGTACGCAAG-1 & TTTGTGTGTCTGCGCA-1 & TTTGTGTTCAACTTGG-1\\\\\n",
       "\\hline\n",
       "\tchr1\\_10244\\_10510 & 1  & 0  &  1 & 6  & 0  & 0  & 0  & 0  & 0  & 0  & ⋯  & 0  & 0  & 0  & 0  & 0  & 0  & 1  &  1 & 1  & 0 \\\\\n",
       "\tchr1\\_237575\\_237942 & 0  & 0  &  0 & 0  & 0  & 0  & 0  & 2  & 0  & 0  & ⋯  & 0  & 0  & 0  & 0  & 0  & 0  & 0  &  0 & 0  & 0 \\\\\n",
       "\tchr1\\_565098\\_565554 & 0  & 0  &  6 & 0  & 0  & 2  & 0  & 0  & 0  & 0  & ⋯  & 2  & 0  & 0  & 0  & 4  & 0  & 0  & 12 & 0  & 0 \\\\\n",
       "\tchr1\\_569172\\_569645 & 0  & 0  &  8 & 6  & 0  & 4  & 0  & 0  & 0  & 0  & ⋯  & 0  & 0  & 0  & 0  & 2  & 0  & 0  &  0 & 0  & 0 \\\\\n",
       "\tchr1\\_713421\\_715095 & 4  & 4  & 10 & 4  & 0  & 2  & 0  & 6  & 0  & 4  & ⋯  & 2  & 4  & 2  & 2  & 2  & 0  & 8  &  4 & 0  & 0 \\\\\n",
       "\tchr1\\_752386\\_753061 & 4  & 0  &  0 & 0  & 0  & 0  & 0  & 0  & 0  & 0  & ⋯  & 2  & 2  & 0  & 0  & 0  & 0  & 0  &  0 & 0  & 0 \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | AAACGAAAGCGCAATG-1 | AAACGAAAGGGTATCG-1 | AAACGAAAGTAACATG-1 | AAACGAAAGTTACACC-1 | AAACGAACAGAGATGC-1 | AAACGAACATGCTATG-1 | AAACGAAGTGCATCAT-1 | AAACGAAGTGGACGAT-1 | AAACGAAGTGGCCTCA-1 | AAACGAATCAGTGTAC-1 | ⋯ | TTTGGTTGTCAGAAAT-1 | TTTGGTTGTTGTATCG-1 | TTTGGTTTCAGTGGTT-1 | TTTGTGTAGGAAACTT-1 | TTTGTGTCAAGCCTTA-1 | TTTGTGTCACTCAAGT-1 | TTTGTGTCACTGGGCT-1 | TTTGTGTGTACGCAAG-1 | TTTGTGTGTCTGCGCA-1 | TTTGTGTTCAACTTGG-1 |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| chr1_10244_10510 | 1  | 0  |  1 | 6  | 0  | 0  | 0  | 0  | 0  | 0  | ⋯  | 0  | 0  | 0  | 0  | 0  | 0  | 1  |  1 | 1  | 0  |\n",
       "| chr1_237575_237942 | 0  | 0  |  0 | 0  | 0  | 0  | 0  | 2  | 0  | 0  | ⋯  | 0  | 0  | 0  | 0  | 0  | 0  | 0  |  0 | 0  | 0  |\n",
       "| chr1_565098_565554 | 0  | 0  |  6 | 0  | 0  | 2  | 0  | 0  | 0  | 0  | ⋯  | 2  | 0  | 0  | 0  | 4  | 0  | 0  | 12 | 0  | 0  |\n",
       "| chr1_569172_569645 | 0  | 0  |  8 | 6  | 0  | 4  | 0  | 0  | 0  | 0  | ⋯  | 0  | 0  | 0  | 0  | 2  | 0  | 0  |  0 | 0  | 0  |\n",
       "| chr1_713421_715095 | 4  | 4  | 10 | 4  | 0  | 2  | 0  | 6  | 0  | 4  | ⋯  | 2  | 4  | 2  | 2  | 2  | 0  | 8  |  4 | 0  | 0  |\n",
       "| chr1_752386_753061 | 4  | 0  |  0 | 0  | 0  | 0  | 0  | 0  | 0  | 0  | ⋯  | 2  | 2  | 0  | 0  | 0  | 0  | 0  |  0 | 0  | 0  |\n",
       "\n"
      ],
      "text/plain": [
       "                   AAACGAAAGCGCAATG-1 AAACGAAAGGGTATCG-1 AAACGAAAGTAACATG-1\n",
       "chr1_10244_10510   1                  0                   1                \n",
       "chr1_237575_237942 0                  0                   0                \n",
       "chr1_565098_565554 0                  0                   6                \n",
       "chr1_569172_569645 0                  0                   8                \n",
       "chr1_713421_715095 4                  4                  10                \n",
       "chr1_752386_753061 4                  0                   0                \n",
       "                   AAACGAAAGTTACACC-1 AAACGAACAGAGATGC-1 AAACGAACATGCTATG-1\n",
       "chr1_10244_10510   6                  0                  0                 \n",
       "chr1_237575_237942 0                  0                  0                 \n",
       "chr1_565098_565554 0                  0                  2                 \n",
       "chr1_569172_569645 6                  0                  4                 \n",
       "chr1_713421_715095 4                  0                  2                 \n",
       "chr1_752386_753061 0                  0                  0                 \n",
       "                   AAACGAAGTGCATCAT-1 AAACGAAGTGGACGAT-1 AAACGAAGTGGCCTCA-1\n",
       "chr1_10244_10510   0                  0                  0                 \n",
       "chr1_237575_237942 0                  2                  0                 \n",
       "chr1_565098_565554 0                  0                  0                 \n",
       "chr1_569172_569645 0                  0                  0                 \n",
       "chr1_713421_715095 0                  6                  0                 \n",
       "chr1_752386_753061 0                  0                  0                 \n",
       "                   AAACGAATCAGTGTAC-1 ⋯ TTTGGTTGTCAGAAAT-1 TTTGGTTGTTGTATCG-1\n",
       "chr1_10244_10510   0                  ⋯ 0                  0                 \n",
       "chr1_237575_237942 0                  ⋯ 0                  0                 \n",
       "chr1_565098_565554 0                  ⋯ 2                  0                 \n",
       "chr1_569172_569645 0                  ⋯ 0                  0                 \n",
       "chr1_713421_715095 4                  ⋯ 2                  4                 \n",
       "chr1_752386_753061 0                  ⋯ 2                  2                 \n",
       "                   TTTGGTTTCAGTGGTT-1 TTTGTGTAGGAAACTT-1 TTTGTGTCAAGCCTTA-1\n",
       "chr1_10244_10510   0                  0                  0                 \n",
       "chr1_237575_237942 0                  0                  0                 \n",
       "chr1_565098_565554 0                  0                  4                 \n",
       "chr1_569172_569645 0                  0                  2                 \n",
       "chr1_713421_715095 2                  2                  2                 \n",
       "chr1_752386_753061 0                  0                  0                 \n",
       "                   TTTGTGTCACTCAAGT-1 TTTGTGTCACTGGGCT-1 TTTGTGTGTACGCAAG-1\n",
       "chr1_10244_10510   0                  1                   1                \n",
       "chr1_237575_237942 0                  0                   0                \n",
       "chr1_565098_565554 0                  0                  12                \n",
       "chr1_569172_569645 0                  0                   0                \n",
       "chr1_713421_715095 0                  8                   4                \n",
       "chr1_752386_753061 0                  0                   0                \n",
       "                   TTTGTGTGTCTGCGCA-1 TTTGTGTTCAACTTGG-1\n",
       "chr1_10244_10510   1                  0                 \n",
       "chr1_237575_237942 0                  0                 \n",
       "chr1_565098_565554 0                  0                 \n",
       "chr1_569172_569645 0                  0                 \n",
       "chr1_713421_715095 0                  0                 \n",
       "chr1_752386_753061 0                  0                 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(datafr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>97998</li>\n",
       "\t<li>5335</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 97998\n",
       "\\item 5335\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 97998\n",
       "2. 5335\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 97998  5335"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dim(datafr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# saveRDS(datafr, file = './datafr.rds')\n",
    "# datafr = readRDS('./datafr.rds')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "elbow_plot <- function(mat,num_pcs=50,scale=FALSE,center=FALSE,title='',width=3,height=3){\n",
    "    set.seed(2019) \n",
    "    mat = data.matrix(mat)\n",
    "    SVD = irlba(mat, num_pcs, num_pcs,scale=scale,center=center)\n",
    "    options(repr.plot.width=width, repr.plot.height=height)\n",
    "    df_plot = data.frame(PC=1:num_pcs, SD=SVD$d);\n",
    "#     print(SVD$d[1:num_pcs])\n",
    "    p <- ggplot(df_plot, aes(x = PC, y = SD)) +\n",
    "      geom_point(col=\"#cd5c5c\",size = 1) + \n",
    "      ggtitle(title)\n",
    "    return(p)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Obtain Feature Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "start_time <- Sys.time()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "metadata <- read.table('../../input/metadata.tsv',\n",
    "                         header = TRUE,\n",
    "                         stringsAsFactors=FALSE,quote=\"\",row.names=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "binary_mat = as.matrix((datafr > 0) + 0)\n",
    "binary_mat = Matrix(binary_mat, sparse = TRUE) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3 x 3 sparse Matrix of class \"dgCMatrix\"\n",
       "                   AAACGAAAGCGCAATG-1 AAACGAAAGGGTATCG-1 AAACGAAAGTAACATG-1\n",
       "chr1_10244_10510                    1                  .                  1\n",
       "chr1_237575_237942                  .                  .                  .\n",
       "chr1_565098_565554                  .                  .                  1"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "binary_mat[1:3,1:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Kf4+Hjtz1SiXkCvXLlSDJp2X/AoW4XJ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\nsgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title “Number of Sites Each Cell Uses”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_cells_ncounted = rowSums(binary_mat)\n",
    "ncounts = binary_mat[num_cells_ncounted >= dim(binary_mat)[2]*0.01,]\n",
    "new_counts = colSums(ncounts)\n",
    "# ncounts = ncounts[,new_counts >= quantile(new_counts,probs=0.1)]\n",
    "ncounts = ncounts[rowSums(ncounts) > 0,]\n",
    "\n",
    "options(repr.plot.width=8, repr.plot.height=4)\n",
    "par(mfrow=c(1,2))\n",
    "hist(log10(num_cells_ncounted),main=\"No. of Cells Each Site is Observed In\",breaks=50)\n",
    "abline(v=log10(min(num_cells_ncounted[num_cells_ncounted >= dim(binary_mat)[2]*0.01])),lwd=2,col=\"indianred\")\n",
    "hist(log10(new_counts),main=\"Number of Sites Each Cell Uses\",breaks=50)\n",
    "# abline(v=log10(quantile(new_counts,probs=0.1)),lwd=2,col=\"indianred\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>69319</li>\n",
       "\t<li>5335</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 69319\n",
       "\\item 5335\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 69319\n",
       "2. 5335\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 69319  5335"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dim(ncounts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "sexsites = c(grep(\"chrY\",rownames(ncounts)),grep(\"chrX\",rownames(ncounts)))\n",
    "ncounts.nosex = ncounts[-sexsites,]\n",
    "\n",
    "nfreqs = t(t(ncounts.nosex) / Matrix::colSums(ncounts.nosex))\n",
    "idf = as(log(1 + ncol(ncounts.nosex) / Matrix::rowSums(ncounts.nosex)), \"sparseVector\")\n",
    "tf_idf_counts = as(Diagonal(x=as.vector(idf)), \"sparseMatrix\") %*% nfreqs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>67427</li>\n",
       "\t<li>5335</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 67427\n",
       "\\item 5335\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 67427\n",
       "2. 5335\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 67427  5335"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dim(tf_idf_counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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wQHAGiG4AAAzRAcAKAZggMANENwAIBm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\nYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p_elbow_LSI <- elbow_plot(tf_idf_counts,num_pcs = 200, title = 'PCA on LSI')\n",
    "p_elbow_LSI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>5335</li>\n",
       "\t<li>150</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 5335\n",
       "\\item 150\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 5335\n",
       "2. 150\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 5335  150"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tbody>\n",
       "\t<tr><td>-0.009063687 </td><td>-0.0002460163</td><td>-0.0002805486</td></tr>\n",
       "\t<tr><td>-0.008831733 </td><td>-0.0001022342</td><td>-0.0004277593</td></tr>\n",
       "\t<tr><td>-0.008985058 </td><td>-0.0001010684</td><td> 0.0011672419</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{lll}\n",
       "\t -0.009063687  & -0.0002460163 & -0.0002805486\\\\\n",
       "\t -0.008831733  & -0.0001022342 & -0.0004277593\\\\\n",
       "\t -0.008985058  & -0.0001010684 &  0.0011672419\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| -0.009063687  | -0.0002460163 | -0.0002805486 |\n",
       "| -0.008831733  | -0.0001022342 | -0.0004277593 |\n",
       "| -0.008985058  | -0.0001010684 |  0.0011672419 |\n",
       "\n"
      ],
      "text/plain": [
       "     [,1]         [,2]          [,3]         \n",
       "[1,] -0.009063687 -0.0002460163 -0.0002805486\n",
       "[2,] -0.008831733 -0.0001022342 -0.0004277593\n",
       "[3,] -0.008985058 -0.0001010684  0.0011672419"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "set.seed(2019)\n",
    "num_pcs = 150\n",
    "SVDtsne = irlba(tf_idf_counts, num_pcs, num_pcs)\n",
    "d_diagtsne = matrix(0, nrow=num_pcs, ncol=num_pcs)\n",
    "diag(d_diagtsne) = SVDtsne$d\n",
    "SVDtsne_vd = t(d_diagtsne %*% t(SVDtsne$v))\n",
    "\n",
    "dim(SVDtsne_vd)\n",
    "SVDtsne_vd[1:3,1:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "end_time <- Sys.time()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Time difference of 4.298949 mins"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "end_time - start_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>150</li>\n",
       "\t<li>5335</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 150\n",
       "\\item 5335\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 150\n",
       "2. 5335\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1]  150 5335"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_out = t(SVDtsne_vd)\n",
    "colnames(df_out) = colnames(datafr)\n",
    "rownames(df_out) = paste('PC',1:dim(SVDtsne_vd)[2])\n",
    "dim(df_out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "TRUE"
      ],
      "text/latex": [
       "TRUE"
      ],
      "text/markdown": [
       "TRUE"
      ],
      "text/plain": [
       "[1] TRUE"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "all(colnames(df_out) == rownames(metadata))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "saveRDS(df_out, file = '../../output/feature_matrices/FM_Cusanovich2018_10xpbmc5k.rds')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Downstream Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "set.seed(0)\n",
    "tsnetfidf = Rtsne(SVDtsne_vd,pca=F)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(RColorBrewer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot.tsne <- function(x, labels,\n",
    "         main=\"A tSNE visualization\",n=20,\n",
    "         pad=0.1, cex=0.65, pch=19, add=FALSE, legend.suffix=\"\",\n",
    "         cex.main=1, cex.legend=1) {\n",
    "  qual_col_pals = brewer.pal.info[brewer.pal.info$category == 'qual',]\n",
    "  col_vector = unlist(mapply(brewer.pal, qual_col_pals$maxcolors, rownames(qual_col_pals)))\n",
    "  layout = x\n",
    "  \n",
    "  xylim = range(layout)\n",
    "  xylim = xylim + ((xylim[2]-xylim[1])*pad)*c(-0.5, 0.5)\n",
    "  if (!add) {\n",
    "    par(mar=c(0.2,0.7,1.2,0.7), ps=10)\n",
    "    plot(xylim, xylim, type=\"n\", axes=F, frame=F)\n",
    "    rect(xylim[1], xylim[1], xylim[2], xylim[2], border=\"#aaaaaa\", lwd=0.25)  \n",
    "  }\n",
    "  points(layout[,1], layout[,2], col=col_vector[as.integer(labels)],\n",
    "         cex=cex, pch=pch)\n",
    "  mtext(side=3, main, cex=cex.main)\n",
    "\n",
    "  labels.u = unique(labels)\n",
    "  legend.pos = \"topright\"\n",
    "  legend.text = as.character(labels.u)\n",
    "  if (add) {\n",
    "    legend.pos = \"bottomright\"\n",
    "    legend.text = paste(as.character(labels.u), legend.suffix)\n",
    "  }\n",
    "  legend(legend.pos, legend=legend.text,\n",
    "         col=col_vector[as.integer(labels.u)],\n",
    "         bty=\"n\", pch=pch, cex=cex.legend)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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JXMmPuZax4l6Tf4eqOPW70oQolE/Fuw95X8XWvoqUB1pULeOrB6m3GH0EBACDx8\n2zDRSyFK6bIbs0QvAYAgCMuXL3/vvfccKV9//TUAXH/99f7Xin3hhRf8L8V3HR0dWq02mE9E\nKADsq9qZXgwlEKmK1p7oOR9nAYHvfAQrBaFrH5neTSQVbCDYSGRGr25CKPjSE7ThGvmxkkZe\n6PqyFxeh+p+Vk9LiNeAhTISEhNTV1f3v//4vpZTn+a+++urpp5++6667Hn/8cf+rhCfUIxRo\nnBlMLSBVCkc+BA9buIkjTO/yu2BYZvRi0Cb3vQSEgqWp3XLodP2Fug6lXJKeoJ06IlYq6eyh\n9BQmbDbb22+/vXbt2gsXLsTFxS1btuzZZ5+VyWT+VwYDIUKBRMt306rDnfFMogDOHOwahCYx\nw+8Qn++K0JUg+GECxwgRChhac5xWHupq1QUsCvbm22pbNS3ZHqDnIjQoYCBEKGBow+n+Kbh3\nw4W0uazz/CarAWggd6JC6HcJ1xEiFDiWFpFEQiC4AxBABVpXSCsOgFUPhCGxI0n69SBRBLUO\nCF05sEWIUGDQlnKwuC1gYKXBjoIAQBha+jNY9QCXguLZH4NdB4SuHBgIEQoMen63eyLRXI4t\nQN2mnlLdWbAZL0NNELoSYCBEKCCo2w7dAIRAxIBZ2Gduvdw1QMgvlNJ//vOf2dnZSqVy1KhR\na9asCVTJOEaIUEAQkKnB0tZtYotUTeJG0urcgOz5In6Eve+3Vx0h6dfjWfZogKANRaAroQYd\nsFKijiEJY0ET7/2WV1555fnnn3/hhRemTJnyyy+/PPTQQzzPr1y50v/K4DpChAKDlu+hlQed\nU0jyZDJ0JhgaaekO2haskygAAAgQRmS+qDKCGf8gsAFYgIxQ3wk8Pf09bTrXLZEQMnQWSZoI\nHsKE1WqNjY1dsmTJ+++/b0+5+eabq6qqTp486X+NsGsUocAgqdeShLGX9gAlJH4MSbsOAEAd\nTcYsET+wor9QoDwQ1jXZ1EwbxM9ERSho6IW9rlEQACilZb96ObmMZdmdO3c+9dRTjhSVSmU2\nB2apLnaNIhQghCGZc0jaDDC3gSLUdbmCIqz7eRR+9nT6QHQFoVHXvw9FyDuB87YHb/URCEsR\nvcKy7Pjx4+0/G43GL7/8ctOmTa+99lpAKoWBEKGAkiggRGTFHkkcT4u3Oie45+n/2AigDOs5\nD0L9x9AIvNXTRdpR2+OfwJYtW2677TYAmDVr1ooVKwJSKewaRSgYSOwoknmT9z/aB2QAACAA\nSURBVC1A+z0KSpUkKqe/H4KQN/Y9jzzhbd6uAgDA2LFjjx079sUXXxQXF0+dOjUgvaPYIkQo\nSEjCOJCpoTKXdtRephqwYOnA/bjR5aTw2ifh/SoAACQlJSUlJY0fPz4qKmrOnDnffPPN0qVL\n/awUtggRChJ6ZhMt+l48CkYMBanHY7t9xfQ0HdSqF8784NdJTwj5Sa4BbZKniyRG/MxeANDp\ndB9//HFlZddsmquuugoAnFP6DAMhQsFAm0qdt+R2WbTExAzvPpUGXHL2tMiJkLirgPgQ4Uwt\nwoG3hP1v0aKNYBLbGRWhfsZkzgZWKnJBHUMSJ3i6SxCEVatW/etf/3KkbN++HQBGjx7tf5Ww\naxShoGivcX7lPBxINHHChf2egh259L9ep9JQkGuA9zr64sDbAIDqSqi+nhn/B5DIfboLoUAJ\niWNG3yeUboeOuktJhMQMJxkeAiQAAMTExDz88MNvvfWWUqmcMmXK0aNHX3nllRtuuGHevHn+\n1wgX1CMUDLRiP72wT/QSSbnGZSV+n5DeHVtox8hI0ngyZBow+J0YBZ25jRqbCCsFdbTzciMv\nJ9T/85//XLNmTXl5uX1x/XPPPadQBOBYFQyECAVFe62Q97nYBcKMulM4+W2w6iHSsCQJ40jm\nTcGqAEI9wBPqEfqd0iZAqNhK4chMiMgAuTZY9RBbv3gxv4dJ7Qj9rmEgRChIRGfEkbhRAEBy\n5tFedk4GsieHCng2BRrMMBAiFAg2E7RXg6XDSxYSnQOykG5JqkgSngYAJGwIO/E/yJBpoIry\n/hxH/Avk6nvC+LJ+C6HfKxwhR8g/lNJzv9CLJ+wn0ZPoHJJ9i/gJD1IVc9UioXQHtFcDEBIx\ntNs0ObmGpF5LUq8V8r+AtqpuT3AKe/2x+wxJnADmNmrVE1Wka6hGaBDAyTIooAyNtCqXGpuI\nQksSJ0Bocv8+TuDA0g6KUJGTFoKFVh6k5XucU0jcVST7Fm/3CDwQQhuKoOkcUB5CU0jCeGAu\nvQVDg5C3zst+jAEm14BcA+21AACEIYlXk/Trg/RohMTgZBl0xbIaaOkO4dgaWn8KOi7SxrNC\n/he0sbi/Hkd5eu4XYf+bwpEPhf1v0vI9gR0160VFnJbJd6Y0ngHv3y8Zlpb8RIu30sZiqiul\nZb8KhRu6NnxRxzATVxFtsP4hsHR0RkEAoAKtPkJrjwfp0WjQs7bWc8Z2X3IeO3aMiPnb3/7m\nfzWwaxT1EQVqsBnUUjUBAvo6IX898BbXPKXbSXS/7PJMy/fSmmOdLwSeVh4EiYIkT+qPZ/XA\n/fR53ga8xfUYJmf6OlpX0C2lrYo2nCaxIztfykIgepjzGnwKQLqvfOi/oypoYzFJGN8/ZSME\nAGBt153/6iXdse2csQ0AFNHJCdc/kDx3FWE9hqSUlJS3337bOeX7778/ePDg7Nmz/a8PBkLU\nawIVdlftzK0/bKW8AtipyqRrTBbiFgUBAGxmrvmcJCLDU1EUqM6kM3AGBaOQS+Rh8jDi2z/v\ntK7QLaXgsgRCEhJLW8q7JSnCvEVBANq1oYaTjovgCIQAJCqLXtjn+G5BHP/jyNC36vrC1AKW\nDpBr+u8JaDCzNNWe+Mc8S1PXprvmxqrzX73YXnJkxGNrCSM+zBETE/PYY485Xp44ceLpp59+\n+eWXp0+f7n+VMBCiXttb9cveukP2n83A/2qqkNokE8H119cC9DwrnCvfOl52Z1KIyDa7LZaW\njWUbq/XVFKg9/qkkKiWrJISkalNnJM4IkXqYuCHYwGZ0TbT41MEScCRtBm2tdD4Ft+cxNonY\nafVOR9jT6iP0wn73FnaQWDqEwx+Q5MkkLQD/xCDkovT/nrU01br3aehO/Fy3Z0P8zPt6LEEQ\nhIceemjYsGFPPvlkQKqEgRD12vH6Y64pEmEi1y0Q1jL0a7mtAyjwrXmnPxkZMfKO9DsY0jUm\nTYF+d+67GkMNABAg9lho5IxGzggAOrOuvL181YhVMtHpl4wUlOGue0arowPz9npLE8eMX06r\nDlFjM1FoSeLV3qYI8VZavpe2VgBhup0CQRgSmWn/kdYep2W/9nOle0IFWnkQQmJItMfTABDq\nA1tHc1PeDgAKRKRT4+Ler3wJhGvWrMnLy9u/fz/LBmaWHAZC1Dt6m76Duh6e2Uqo89c7CvC9\n1NbhNHvlVPOpMHnYDck3dN1iabVHQTv3HtEmc1O+Ln9i7ETRapDU6+iZTS4pvXsnAaSOIjm3\n9txX2VYtnPxK5OhRiZxkzIaQWPsrWnPCezHBOMjerrEYMBCigDLWlVGBv9QH5Ha1prTHEgRB\neO2112bOnDl16tRA1QoDIeqdb0q/cU+Mot1+q5sJbWZcp03uv7hfb9PPHzrf/hdgsBkoUBAL\ngQ71pnpPl0jMcGClUH2UmluJKhKSp5AwsQ3MgsCqB1YmvnDQmc0onPxGJAqmTGGSJ3cbU+xp\nk5eALqUnQMHThFvafJ7wNi8HAiDUW8TeLeThl5gwPf92b968uays7L333gtgrTAQol4w8+ZK\nvcgxmLE80TH0AhEaWcpSj8cg5Ovy49Xxk2InAUCUIqrHeTGhslAvV0lkJkRmBqlt5KbV0lpU\nunlES61WoABAJQoiU5PQFJI6TXRNOm0uEx3zI1RwnVmjigB9Q+9r1KeGIiEQnUViriJAhaJv\nXf+78VZac5SkXNP7yiAkTpWQQVgpdf9GCAAA6uSeeyC+/vrrmJiYG2+8MYC1wkCIeqHVIt5Y\nyZcI+RKfFoCXtJbYA+G5c5u85yRADtcdLtQVpoelT4mdEiYfQHuAGTnjlqI1i/QWCe2MPYQz\nA2emxibaXMZcvVxkOoynDk/nqEl56KiDiPQ+BUJPUdBrgBQEaCim+gaIyhb/9tJeK5aKUB9J\nVKExk2+rP7BR9GrCrKXeb+c4btu2bUuWLAnU6GBnrQJYFvrdi1RE2ie29OFeDQUlJWarQW/T\nq/WNp1tK3OaZdkOBGjiDgTPo6nTHGo49kPNAckg/71PjsxONJ9JMJgkVewOWdlqb59qKogLV\ni3XzMhISldX5s75BOPMDGJsAAAgDUiXYTEAYkMjA6jZFthd8aCYam+nFAvFLXteBINQHGfe9\nqL9w0lBT4pIed92imMkLvN9bWFjY0dExY8aMwFYJAyHqBSkjHRcz7niDrzuP2OeCKikstEqH\nCgwAmK0tO4++3aTUmIngKb97Oi/wX5Z8+Z/j/lMQBMkAOELW1lo5nvccxi+152hdIa09DpYO\nogx3Xl9xCSHD7+jc7ZoKwul/g6m58woVwGoAVga8FaxcHw/d7RX35Sh2jjiNUIBINRHj/v5j\nxaZ3Go/+aG6oIBKpOikn8YYH4669W3QqqbO8vDwAGDduXGCrdPn/TUFXlluG3NJqaS1rK/Ml\nMwFCAO61yhKFzt9vBYV5Nsk60t4mFke8jBqaOfOLR14EgFB56JioMRNiJqil6r68AScU6Kmm\nU6WtpQII6dr00VGjnRd4eKSvv7ax0m0ykBO5BuxrAS+tgqBWA7j1UZKINBKZ3vnC0NgVBR05\nu7YbvTy7x5Eh0wgGQtQPWEXI0EV/G7rob4LNSiQS4svfHQAAVFdXE0JSUgI8Mw433UZ9UdhU\nuLl8M9fTaa4UaLTAPGxxnVFZIBE2ScVHy30kY2V3DL0jJ9yv/dv+ff7fBbquLsHssOx7su7x\nNoVH4Gl7NS3f47z5mSvCMGOXgSZOOPA2cGbPD2eYcUtBE29/QVsu0MINvX4DIqVKAnXELgVg\nsm4i8QH+6o1Qj4IfJrBFiPqi1lDbYxQEAAJEtNWmEekW9Uh0lYWVt24s23h3xt0ZYRk+7soG\nAGbevKdmz6nmU1beKpfI27tvRnO29WxJS0l2eLb4zYYGoeh711X8bkhILGjiwKr3GgUBSLfh\nNxISS12W2PcFuRQFA7DUkADQ83sxEKLBAAMh6jWbYDtSf8THzDoi8q9yHWNfvOZhVW13nvLY\nBNuXJV+qJeolOUsSVAk9liNQ4cuzX1bpO4/6s4gtZqg2VIsHQkqF0//uMQoCAFg6hLzPiftO\n3K4FCrS9mijDO19KlST1Olq+u+fyPZHIgHN0pQZob27OBJwFJHKwtNOaY2BsBkUoSRwPyoi+\n1xOhgQePYUK91mJpEdzaLvZ2m5yVa2QaKdO1BNtA6CFJt3kiBqC5Eh68jgj6zsAZPj39qZn3\n2vwCAIDStlJHFPREyYrsAkprjguH3gVjs/slkcxWPbTXUnObD3md3j7lwdDYdUERCh5GQMVH\nMqQK4G2iF/36iFkpSORgaBSOfkyrDtOmUqHmmHD0E2ir9qdUhAYabBGiXguThzGEcYmF4fLw\nmYkzR0WOYghj5s25dbl7a/fa8/wq5XSMcBXHKgBqGbpPwutJzy1Cx9UeG442wZZblzsjcYb3\najeaGr1nAIAjDUdaLC0zEmc4ZuLQi/n03A6vN/Wp0cWwxGlLUlpxgDYUdb00t5HIDGitcF93\n7KF1bAZPuzf6gcSOAgBa9qtj2g4BAMoL535mxv8hoI9C6HLCQIh6TcbIxkaNPd7YtYiCIcz8\ntPlp2jT7SwKkrK2Mp/ylSAb5rJDPujYivYc3x1X7DwQI8TyGVmcUO9ioO+/71Ni1WlqPNhyt\n6KhYMWKFvV1rqznq6Y9E6OxR6cN+LizJuBGsetpYDKyMRAylurMuWWhLufjpvrIQsBp8a/yJ\nLLrwNWgTQpSRVF8HhV/Rdrf2n6ERBBswuPUa+p3AQIj6Ys6QOXKJ/ETDCTNvjlJEXZ98vSMK\nAsD/nf2/Gn2Ne5xTSVQm3tS3icosME+ZmGKWFrG0mHVdk8eLrNJzlRGaESIN0dv0njI4mp4N\npoY1p9cIIHRYO0yCSaGAMTw7i5NInCpuAnBfam4CyJPwLQwNE2Asz6qoWNBRhYHFSM/toEJn\nnSkjAffFkQLvsYEXlQ0tZSLblnZHQhNJ6nShYL1zOHQv8VJo7B4ipSpq1EHXnd2vMlKRCiPU\nG4IgVFVV1dXVyWSypKSk6GifTo9Zt27d66+/XlZWlpSUtHLlysceeywgW8zgbzPqCykjvTH5\nxhuTb7QJNmn3loGFt9ToxVcX2I9YsnPu8BTt/HRJzJaHs6aOETzEUcE9ELaYWwQqeF8FqJQo\nl2Qv+ab0mxaL+JwX555Y5yammUCuhDcSusAqBQAb0ANSIUEgWXy3xzUR+qncZiQUAICFg1L+\nQYssSnALPUa3beoETqStK1ECZxKppVUPumIAIOFpJG6UcGazxzesTQaJvMc1iMTl/zufYhDP\nZX8RmRm0AzDQ71JxcfG6det0Op0jZfjw4UuXLg0PD/dy1/r165cuXbpq1aq33norNzf3qaee\n6ujoeOGFF/yvD64jRAFWZ6xbfWp1AAukQFNCUhZL4hQXCwHgIqEfK0T2NY1Vxq4YuUJCev5u\n12RuqjXU7q3d68uoobO/muRKgB+l3DEJP8smmdb9CMYv5LbzTLd4liowSy0+9x86LwEkBMBL\nT/ClXGGptPWCx6tJE4GV0IqDvlbAR2EpzIiFuPUa6rPS0tJ33nmH41zXX0VHRz/zzDMqlcpT\nmLj++uvb29uPHj1qf/nQQw9t3ry5oaEPG/O6whYhCjD7sRI+7kfa40QYlUR1X/Z90aroY2Xb\nKmU2OZAsnpECuHcL1pvqN5RuuD/r/h4fGqmIjFREdlg7dlR1mwXTY2X2yzgLhRMSPoxCDcPn\ns5Ar4ZsYGiqQCTxbxbjGrUpGsBEqFe0gdUMybgBjE+gbwdJGLW0g9Lym0EsUBABac9RtlNGP\nxRTyMDJkCtHEO85NRKhvvv76a/coCACNjY2//PLL/PnzPd1oNpu1Wq3jZVRUVEtLC8/z/veO\n4vIJFGASRpIRmuFjZu+zRgHg9vTbY1Qxn53+7Ofm/DOskM/y38hsqbz4721Za1m13teZ/aMi\nR3mvjHssP8TyJyQ8AFxnkwwTJJtlXANDeYBmhv4s5dxjM6Eg8fH7ACMhkZlk6CxKOWpq8SUK\n+lCq+7N9i4LKCHDvZLa00oYijILITzqdrqrK4yom+1ainjz22GN79uz59NNP29radu3a9dFH\nH917770BGSPEQIgCb3HW4hERI3zat/MSCtQ5PwESp4p7aPhDmaGZJxpOOJ9lDwDnWDorZoJo\nOeXt5T4+USPTjIv2tm2KaJCOoZIFVskYnj3uNk7JusWdWMr4tFaSMCRjNshCQF/n7xI9whJ1\nDMi1Pef0jEmfAUkTRWJha2UP2+Ug1JOWFm+7UjQ3e1ute/vtt69atWr58uVhYWGzZs0aNWrU\n6tWBGYXBrlEUeAxh7sq4q8HU8OGpD32ZzwkABMik2EkjI0eWt5cTIBmhGS2Wlp8rf26xtLiX\nQIHqCZFL5BbOdXcYAXrRlrol9ZaytrI2qy+L3zulKGNa+PqNLHfRrSOUJxBLST3pjIcsJTke\nWq6uKLWHLurLzjU9FMVTQwMQv74jC6e+93iNs+DoIPKHQuHt98f71XvuuWfbtm0vvfTStGnT\niouLn3/++QULFmzbtk0i8TeQYSBE/SVGGXNr2q2bzm/yZbyQIQwhJFQWOi1+GgAUNRd9e+5b\nL/mPNhy9Ju6aAxcPuKSnalLNvPl4w/EGU4NWph0bPTZC7nE/MJawK0euXFO0ptni064xAHDM\nXOvpj0YJsMIsLWdpM9AwIOk84X0ekKOVB0jEUKKM7NXUNRKeSlsuiBXn05ePXiOMULyFRA8j\nCWNF2osI+SA+Pl6lUhmN4sd+paeni6YDQGFh4caNG19//fUnn3wSAKZPnz5s2LDp06d/9913\n99xzj5+1wt9m1I9SQlLsUbDHWMhT/uDFgx+c/MDePttTs8d7fkppu7XdHjUdrom7JkIR8cHJ\nD36p+qVAV7Cvdt8HhR+cbz/vpRxBEMbFjEvTpinYnhs63t/FJJuEAZLOMxN4NpNnGCC9WHBu\naAIA0MSS8FTfb6LmDqJNAFb0Of2wvIEK0FZFz+2gpT8HvnA0OEgkkhtuuEH0EsMwN910k6cb\nKyoqAGDq1KmOlKlTpzIMU1RU5OmWXtTK/yIQ8kQukdt/6HGozJ7ByBl3Ve+aEDvBl4UNLZaW\nhekLc8JzytrKKNChoUNTQlJ+OP9Du7XrTAmOclvKtzw6+lHREir1lV+e/VJ0921njtmknt5F\nCCUTOfYaTvxrpY3AAQmfwTOJQucKeQGAuEQqpX3XG0KG3w4lP9HGM96r1MnURMWWGgIAMNCb\nTuLeoRfzSfJkAKAX9tK2agAC6kgSN4pEZuFCe9SjuXPnNjY2Hjp0yDlRIpEsWbIkNTXV013Z\n2dkAsG/fvilTpthTcnNzBUFIS0vzdIvv8LcW9SO1RM0Slqe8jwdNAMCF9guFTYW+9KZGK6MB\nICkkKSkkyZHovq12i6VFb9OHSEPcS9h0fpOFt/RYN+9X40G63ExYz3mkFLJ48qncFkVJKk8I\nwBSO1bisqQjpPJgQJAoyfAE9XAPmdteCGKYXs0kF3ztZ+7KmgrZX0/O7utbdW9po83mqCGOu\nWoRnUyDvGIZ54IEHJk2adOLECcfOMlOnTo2JifFyV1ZW1rJly5577jmr1Tpt2rSzZ8++8MIL\nw4cPX7x4sf9VwkCI+pGJM9mnuvi4fTYFauAM9q26vWeWMtJr4q5xT5exrocAEyBSsV0x9TZ9\nk7kJeopz7tuLO9PKtBet7dtk7E1WVg4EujYg7SZBYOIEqGGEegkkC4xrFAQgzd36b0nMSFrp\nthA+KhsafGsp9k6fOlHbq912nwEwtwrFW5mxS/2vE/rdGzZs2LBhw3p1yyeffJKZmbl27doX\nX3wxKSlp0aJFf//735VKkRNjegsDIepHColCKVGaLm0V5ksHKUe5HjITiJJH3ZF+R7Qyuqyt\nrNZQq5KossOz7W2+zNDMi4aLztmHaIbIWbl7MaxvUysFKmSGZZa2ljpSHBE6Shm1KGPRh0Uf\n5gN3VinE8YQnECuQuTaRP6tQytQADwCx7puuAVBrG9QeJ3FjgGEBgKReC1Y9rSvsvCxVkqEz\nSESm0HIBbJ46Q/3Um3ahOsbp7MPu2muAM+PMUtQfJBLJs88+++yzzwa+5ICXiJADAXJ1zNX7\navf14h7q8sqtXUhBZ9a1W9v31Ow529p5aMOOqh13Z9ydHpp+XeJ19cZ6R3q0MnrB0AWiz1FK\nlFHKKJ1JJ3rVWaomdXz0+KLmIptgSw5JTg9N15l1HM+daz/3/fnvQ6QhrZZWE9BylgJAJQND\nKDP80nihI7xwyjBibY6UqG+wEgC3KEKBlu6gtXnM2KXAyoAwJPsWkjYdTC2gCAO5xp6LGX6H\ncHYbmN12Kw0An6NgaBKTPY9ezPcYOXvaGQ6hgQYDIepfMxNnEiCH6w/3OCfFzmV00FO7cN/F\nfc5be1t4y4bSDWmhaUNChtyZcWeDqaHB2BAqDx2iGeLS8qNA8xrzzrWdo9THbeAgQZ2Qpk3L\nCc+xvzTz5jpD3ZYLW5wXONp7UJUS5fTE6ZQS87k9Ct7eJwwAQGKG3ztsPk95puEMLd7i8UmG\nRlp5kKTNgPYa4fwu6KgFVk4i00GTAKyMhA2BsBRm4iowNgGAULABbG6dk/2JpE0ncVeBLAQA\nSOwoUnOsa3NUB1UkSFXBrBVC/sNAiPoXQ5hZSbNmJs1ss7Ttrd2b15jna/zxqtXi2iriBK60\npbS0pfRU06k/DP9Dolpk0952a/u/y/9d3ia++4zoqGSUIiqNUdMzm6ixici1uWr1rqY8q+Da\npFNJVSuHr9TINJ0lhGXT8r20vVpgpB2hCTRpQjhQlrDU3FrBCOcZgQBJF5hkt25S2lZNjE1C\n4VedZ+EKRlp3EupOAgBlpCTrJhI7CtTRAEC08bTpnF/bh/aWIsweBQEA1FFkxEJa+nO35ikr\nY7JuDlJlEAocPH0CBVVZa9m6knX+lxOhiGg2e1wFH6WMmp82Pzmk6wh4nvJbyrfk6/J7+yAJ\nwz5llLFUAIBzjLBe7rqlqCN8/nXsXx3n2tvtrtm9v3a/fdQzRZOyMH1hbvmPh9q6zuC9lpPM\ntHVrsJLwNFBH0+oj4rVhJMyEFaAIg7ZqemEvba3o7dvxRhkOVr3HYw5ZGTPyLpAqQRXRbeca\ncyvVlYCpFeQaEjeqK1Ii1FfBDxPYIkRBlR6WPjxi+Onm0/4UImNlYfIwL4FQZ9J9duazZcOW\npYSk2FP21OyxR0FfZq46Z+AEvh34cCAAUCQRGf3qzEyguK24zdymkWlGRoxUSpSFTYW7a3Y7\nslV2VK4vWV9vrHe+d5+Ey+ZJguA0zzQyHZo9b5cqcLS1AqCSnt3m5S10vZWuNyJyWr0rbxu8\nMcDKhIIvAQDkGpI1l0SkAwDwVrB0EG0iJIzFA+vRlQsDIQq2O9PvPKE9UaArcF/z5yMrbz3f\n5m2/GADgKb+7evfSnM6p/EXNndtPOAc50aDokiIFEnpptYPeSyyhsOV85+DfrupdS3OWOp7o\n4BIF7Sql0gRL51gjiRlOEq+mpjaAMo99npyVXuhh252ut+JcP78IYO3oLNDSQU//m4z/A9U3\n0NLtnbNYZSEk+xYSMdS/pyB0eeAWayjYGMJcHXP1g8MeFF3e18O9vfmNrTd1BR6D2LwSX9b4\nTyQaxyPjxFY+uDNyxh/O/yD6RHfskGl0+O0X4nJ+jU76QS6cbjlzSE6rWI8jf0Sm9th76ZM+\nR0Sn+vA2WpdPizd3reWw6umZTWDV+1ExhC4bDITo8mAIc/OQXk+scDlcwvu8Gwtv2Vm10z5b\nNV4d7yWnQ3JI8i2pt8QoYxjCaGXa7PBsszJ0j4RrIRQApvCs1rdTduuMdVGKKJdE95WLDGGG\nhA79rPHA/7UVHNCXFegKvin9Zn/twWTew1M0cbTFz3HBAM2saa10nTLKmWmLr2dgITSgYNco\numzGRo8NV4RvLNvYYe3wfQ82hx5v4QRu/8X9tYba+3Pun508e+3ptY7V+i60Mu2izEUR8gil\nRAkAE2ImGDnj2tNrz7acBQCQwgEpv8gqTeeZlZqRB9TKav3FGmON+44zzlWaGj+1pLXEyHXt\nsj8jccbxxuOO+a4EyPWJ19caah1dxPbb1eARiR5BK10P3LgsaHutSKpN/EgBhAY4DITockrV\npHICB771Urrw8Zbz7ed31exSMIo5qXNq9DVN5qZwebiESAp0Bfa4OFQ79I70O1w2I91bu1dn\n7lprzwF8r2Jmxl8bpU64UZtm423vFLzjHORcqpSoToxWRv/HyP84cPHARcPFEFnImKgxp5pO\nOa/6oEBbrC0t1haX25sItQK47hRnzxCRRs//KnJBm0DCh1KrARpOdXacEkISJ5LkScKJtWDp\nW48l6VwR6PNqRRLiU7MboYEGAyG6zJRs1x5sveVjO3JvzV77D8khyffn3C9jZAAwO2V2o6kx\nRBoSLg93v6Wqw3Uij4mz/Fi1EwA0Mo2Vt3rZH0Aj1cwfOh8AtDLt3CFzHVX9vsz1wNuzrWdH\nR452eTsCwC9S7ha3fdpI/GhQR4MiFMzdTxJWhjJj7gfCEABIvZa2lANvJaHJoI6itQV9jYIA\nQHu1YJ9E50BYSl+fhdDlhIEQXWY54TkH69w2mPaNlygoGiOr9FW7qnfdlHITAChYhfNCQxcS\nz8cJUUuHReyxKSEpGWEZWpl2WPgw991NBSrYBNdJLhbe4pzoqPBxCd9K6DieVQOEUIgQGIjK\nIqnTAYCkzaBnNnUVQRiSNa/rmFyZmsSOBADoqBWOfgLGnjeQ8xORqiA0ESIySNzonnMjNCDh\nZBl0mc1KmjUsvHeb0PvCcd6FS3pRc5HoFBuu+9SP9FDxk7KncKyZgHvJQzRDRkePTg9NHxM1\nxtMe31HKrukz9tsjFZGH6w87Z2MIc7U2Q0NJGSv8JuVagUbYVxnqSoSjH9GmUhIznIy6m4Sn\ngTKCRGYyY5YQ93aYzSSc2ugSBamHn/0VO5KMuJPEjwESrA1uEAo0bBGidH0ofwAAIABJREFU\ny0zCSBZlLvrv4/9t5s0BL9y9UdhubT9cd3hy3GT7Swr00MVDh+oOddg6QmWh1yZce3XM1QAw\nNX5qtb66pLXE+V4GyLU2yTGJAN2bm4SQio6Kio4KABiqHXpP5j3up0EdbTjqfNowASJn5XGq\nOJezMgQqZMdPukWTw5XvZl2WSXBmWryFTPwPEpEOEelewg5trXBfyUA8/NxXFICAVEmSJgag\nMIQuK2wRogEhXCEyUOcPCvTWobeqJCIbQDufhnHw4sEdVTs6bB0A0GZt23ph64nGEwDAEvaa\n+Gtc4mioAAqAFLe1Dc77FJ5vP/9L1S8uGTpsHT9X/OwyyzQzLNMoNs3SxJlI7ChWdOtqzkLb\nfNiFwOJ2qG/gEQAgQ6Y5TsZA6MqFgRANCGOjxga2QAJkW/k294mdAGDgDAbOkNeY91HRRzur\nd7pctfdVWnjL9+e+d+n/bGOoAHCLTRLmtJrQfWVhXmPe0YajZt7cbu0MSDX6Go5yLqWdbDrp\nOC7KgQJVSVT0Yr7rjBgHczttKqWtFSInPzi4tUf7Ce2Xg4IRCjbsGkUDwoTYCSbOtP/ifptg\nAwIssPZDjtznvMhZuUaqcV7bIIoBjyfLK1hFXmPezirXEGjXYGx4Pe91I2d0349eADjFClfx\nzB/NsjMs30JoFGWKWaGI5Z2zcZTbdmHbtgvbAEDJKq9NuDZaFQ1u/bSiM31CKXOy6WS6VSq+\nxRoBev43+4F/VK5lhi8ArdjexM3nRN9a4Jk8bveK0BUEAyEaEAiQ6YnTpyVMa7W0amVahjD5\nuvwt5Vvco4WFt1h4i4yRuZ+F5BCjjGkwNXi66v2sYArUy+5o22WcYGWv4pmreNZMYLeEq1Ao\nwaZ3vt25zibe9HPVz2nqFDlhLD2dWHs1x4ZRUmRsAHW2+EAeBXDsrWNpF07/m5mwCljXneqo\nvhGCgihCg/MghPoVBkI0gLCEjVRE2n92PvbWnVWwJmuSm0xNLp2fyZrkeUPmyVjZPwv+6ene\nk00nfTwl2J0ZhM0yuh2ImkI7AQFoOCOVMlLHKgjRXbwvGKrGcOxpifvJ9N1whCoo0cq1JGY4\nrT4CgtMnwEhE+kItHaCvg1C3RSByTf+cYu8m7brOH0zNtOoImJpBpiGxwyB8aNeKDoQGPAyE\naAARqFCgK6g11CokipKWEu+ZlaxyVvKsH8t/dGxASgiZEDMhVhULXhuFbdY2QjpP4uzV1m6O\nQT4b0NZLN5k5c2ZoZoW+wvsu262EPmyWfaCwWT0vXlBQUsPQGSRUKPwKBN5xdpJZFckYm0TH\n/ajN7F57ok12nVMjUQAX+Em5nc3WjotC/jpH2KYNp4CVkfTrSfyYfngiQoGH39rQQMEJ3Noz\nazeVbzracHRf7T7nsyNEWXjL1vKtzttwU0q3V2y371NzZ8adolvG2KnYzjmZvdrajQBxz2/i\nTadbTjtHQdF1ihYCWkpus0oYz08Mp8xEdVpsTQFYDZ0lAdgSxrzHNEsdr12q5Lzwn1IwNdPT\nP9Aqtw0K+iUKAr2wHwCE8791a7wCAG+lJdtpc1l/PBShgMNAiAaK3Prcan217/lF58KYOFO1\noRoAYpQxj4x65L7s++wNRBch0hCm9313LGFHRY7q8Sgo0eCaKBAAGM4zyy3SHKHzHAqXfGdY\nIbbFdXUE03DaxJvtwdW9XFqd2/lTR61w9EPhyIe0sXczOf1aXG9oBADoqBO/WnfSn7IRChoM\nhGigcN/e087RwHIOMFfHXO0pktkurUOXMJKM0IxJsZPc81ipNV7Vux2is8Oz49XxJ5tOOvfE\nesqcFJLk/DIUJNM5FgA4gP0SvpihPEAWR1xahxcYvox1je4sZ1VQaPTwKNp+EQCAMwmnvvN6\nxHxndvckvxbX2yfLSFWiJdNgLGdEKABwjBANFJ6297THP5VEdVfGXWbebObMiSGJMcqYHyt+\nrOiocBnkYwjjEoSGRwzfXL7ZpUyjzUjc1v9JiEQAQUIkclZuX2LvrKS1xGVBhfv6CodGU+Oq\nEasKmwr1Nn2sKnaCJlOav84m2H6TcMWX1lqoCcOD64SgC0RI7/71VJAqzcSyUWZbZZG5nmcI\nAKwUODNtqbzUm9pVO7EY5y3qeTwL2HEvAej+lu2jgCQ6m1YdFrlBHe2tPIQGDAyEaKDICM0o\nai5yTtHKtMuHLdeZdCGykFhVrEuX49T4qSebTjqfXEGA3Jh8o0amydfl5zXmGWyGSGXk9ITp\nClbhsn+bVqbVmVxXItrXvAtUcF+YQYB4CXvuLLxFxsrsu3sDAC3fQ3kbA5An4RzhppyITItt\ndmvlskOmTeQajtQfeU9hXWqRRrjEb6teOPQ+RKS6ldSHY628oyDTgjIC2iqBCsDKSMoUkjge\nAEjqdWDpoA2nu2WXyEnKlN7WAaHLAgMhGijGRI+p1FfmNebZX6ql6jvT7wyTh4XJw0Tzh8pC\nVwxfsad2T3l7OQUap4ybnjQ9SZ20p2bPrppd9jw6s+5sy1n7cbvORkeNzq3L1dt8OqIoQhHR\nbO7dynECxHHAoUCFJn01ITSCEgDG0YvYygC4TVvlXfoYY0aQxKtvBkjVpJa0lhzgrTPa2zT6\n7iFcsIGutFfV6yNLOxk6k1y1CKx6kGm6dtlmJGTYfJJ2nVB9HNqrgLeRkDgyZCooxP/DITTQ\nYCBEAwUBMj9t/oSYCbWGWqVEmR6armAV3m+JUETcPvR25xRO4PbW7nXJZuJMBIh9rJEl7KTY\nSVPjp5o58/6L+93r4JIyL3We3qrfXbu7V+8lKyzLfgZFni7vxws/2gQbKIAFENwWa7i8DnG8\nZFiSPJmkdi7UGx4xfHjE8M5LTSXCqY2+VoWVgyqMKCN83g6NeJpAQwGIoRFihoNcK3JZEc5k\n3OBrrRAaSDAQooElQZ2QoE7o8+06s050JT4FqmSVS3OWRigi7CFqZtJMq2A91nDM005sdtsv\nbM+KyBK95GkNYpI66bahtwFAZUfl5vObHZN9eAAgPfSvpvIMAEDsCCZzjqctQ6nYMU9AGBB9\nIwSgo5529LAWxbl4TxcIACjEQiBCVzicNYp+V7Qyj/9SG3kjADgOC2QJm6Lp+UR1HvgafY3o\nJU9rEOtN9fZjJbZVbBNdUyiaCADDeXaE/WiLxhIve2oTdYz74X8kQvwAReD6uIeOQ7eDDMt3\nU92ljQ6setflgwhdmbBFiH5XVBJVVliWyzmCdgSI84oLq2DdUr7Fe3PQzsB52zLGmb2NaBNs\neY15WeFZ9cZ696vQPYISgKECE0FJJsdkCJeqJ9hoey2JzBB5RPk+Wn3IZfYmyLUkZx5pOicU\nb/VlZWBPE0S76ZbTZv7/7L1ndBznmef7f6uqc0Y3ciYyxEyKpChKpCQGSbYky9LIljWWPPbY\nnh3NjO85e3bm3k93vu3O3buzZ+94dmfWlqNsy0q2bJmURGWJOWeQRM5Ad6PRuasrvPdDAY3u\n6uoGQIKkCNbvAw/7rbdCB9S/nud9Ar30BzRup0OHkY6BMKSskzTvRN4qrI7ObYQuhDrLja+s\n+Mrr3a/3RnpV406js9QyF9A/kZhYYMVRE2NKyBrtnPLJKNzJwEmBCoW2ZkOBHkbuoyRqoJMS\nFUHvFzkAmg3f6ZV9dOx0zhBnJpVrSe0WcGaUr2TMbjp4gMYDMDthsCKgXabuunIHZYH2fjCj\nxFSmE+ch8mTl09dzSB2dW4suhDrLDStnfb79+d5I7xs9b2Qqn1k561NNT2VbhCzRyMrjGE7M\n80l2lnSeDZ5NS8UrZueQElPHJo4tfL5MaBehXYxsBkooWQGT3ZG/UErVKghATJHGHXOq6aoh\nq76mvKCBy7SAEF4vqnzK4FWSjsFovyHn0tG58ehCqLM8WeFc8Z/W/af+SP9YYkzxl6qSKMqs\nZQ6DQ5U4v7tud0JIHJ08mukd3+Hp2FO3Jy7GL00tQRPa7D4VmqSAN42ikdBvJCcaDA052woV\njomOwakRXkR8rfA00lDfNV8tFu5ETU3rQqhz+6ILoc4yRJTFE/4Tg9FBm8G20ruyzq4RFMMR\n7qmmp37b/dtMSv5q7+q7y+4mIDuqdwRSgVAqVGIuUdpCLao2tyYMYXbV7mIIs29g37yT01R6\no+eNH6z9AUey/kKFZP5MCsBeBgBUUpZBszYSsuoZjJ5E4AqNjUIsJsCF0ChOY3bRVFg9avVd\nw8F1dL4g6EKos9xIy+kfnvzvEXlGNo5OHH24/uEt5VvyZzY4G/5u9d9dDV9NislqW3V2bTaf\n2eczz93cXcZr7ED75IonI+kIQ5gWd0uZpQxAMBU8OnF03h2jQnQyMZmTSWIry8/xYwiH5JR8\n9T1ERgBCSlaQ5l3I9MslDKlaL/u7FqiCC7L/GAMIAZWz59Lu90nbo3oPQp3bFF0IdZYbr558\nKaOCCu/1v7vGuya/vgwAC2dZ7V2teRxBFgzMTPP31b7VRyeOFuoVXCihkCHMSu9K1WLko/WP\nuoyuT0Y+yS/kpkK9WskaSONDtPeDuRFCyMo/k8++kik0SoNXaSrErP8LzBZupSMnENauZp7P\nQsxemgjkz6UT52DxkPp7F3giHZ0vFLoQ6iw3ppMTyM04lwkdjY80uTSyEfIRZOGj4Y9O+k+m\npJTX7N1Zu7PD01FprXym+Zm9A3vD6TCAMkuZmTVLkEbiI6BQytbka+GqklUqFRRkYSQ+UmYp\ne3H1i1enr77d/3ahyzCxpgprhWqQ1G6CvQxDR8BPw1FFmnfRyQvqctvxAA31z6VeRBbR2ep6\noIHLuhDq3KboQqizrJCpLHIaRcIC410LFMJ9A/tO+k8q/w+mgq91v/bNtm82OhvbPG1tnrZI\nOmJiTUpWPgX99/P/Pp4YR4FFxLWlOS3ah2JDr3e/rkgpx3AP1Ty0p27P/sH92b2FFVjCPtbw\nmFGrsgzxNMDTMPd6NoJGAoIMtVA4KMkJqynQ02PpSS+ocKuOzhcQ3aevs6wgIIyskVFuNWqV\nJcsjLadPB3JSFGQqZy/pOY3OjAq+3v26ooKFeH/o/Uyr4bSUfrX7VUUFAYiy+O7guxXWis0V\nGu0SH6h9YKV3pWpQkAWR5pWbsXgBnGSl/2bm/82U/u/m9C+NQsQ44wSmwe5ZT+Z1soDOG7JA\nez/K6walo3MboFuEOssKQog1TKd8KvuM1pepdUWTaX46v9bMFK/ReqIr1KVqGpXPSHzkV1d+\n9Vcr/8pldI3ER6JpdY/D/UP7/Ql/vlu1P9K/rWJb5uVYYmxv/97h2DAhpNHZ+KWGL5WYSpRN\npKyjZ+iTt8k0gHaJqaZMCnh79KNvlN2Fy3vp+Nm8iyJgjVhYJYGcveZFTNOhw3T8DLP+L+ai\ndXR0bgd0IdRZbuxe9ezLw6+ks9bmVqHEaVtQP3qPycMQRqWFSgaFiqHY/BEoFDQpJs8Gzt5X\ndV92Q0QjJWlCAYzGRzUXF0Op0Gh89OjE0Ug64jK5LocuJ8QEAEppT7jn15d//b2V3zMyRgDg\nzKfdvs3B6HaBNc8eR4xEg5f/WDKuqdNUUwUXVXStGEKS9n9K2h8rtJ0OH6HDRyEkYXKSxh2k\ntH1JTqujcz3oQqiz3Kirbf9L6/N7z78a5HgjZTZ62ze3fXWB+xoYw+byzYfGD2VGWMJurdia\nP1OQ5k9IUBQuxIcAVForAbRL7IMi65PJBJHfMIkBQjUDbdJy+scXf1yoDmogFegN97bbamhk\nFAy3emq8Wcj5Q+YocY0vLv1/aVQQAECjY4WOJl/Zh0xxnGSIXvwdOh8npXct3cl1dK4FXQh1\nliFl3hXf2v5/Xtu+O2t3WjjLSf/JWDpWYat4sObBSlvlUHxoKjlVbi0vt5YroqX0slBhZI35\nldh8Fh8At8n9uGft6tFLDHCMld41ihmVy7cIk2KyeDVw4/g5OfBHpUOFZggQmxeAcz0oK4QL\nFctCBbjFJMbVJeLopT/pQqhzy9GFUEcnB5aw91fdf3/VTEfc3kjvfz35X1NSSrHbvGbvs63P\n+sw+Xqu90dPNTx8aO9QXmatq5jQ61/pmYkfXCaDAJEPfNUrFZSq/3mk2NTKp9/eoG1BcF/N4\nRrO2ze9DJaUF2jdGxjRibqhEhw6R2nsWcJE6OjcKPWpUR6cg4XT4lSuvKMt7it0WTAVfufKK\nTOUSc0n+fJ/J90zzM5vKNzmNTgtn6Szp/Fb7t6ycVdlKkyEAZ1hJXkgQZmHWs26ylCqIa27K\nNMOcCUhI5TpSs0l7V0ajyjkA+LsWfHYdnRuCbhHq6BTk6vTV/Pov/pTfn/RvKN1w0n8y23Rr\ndbd6zB4C8mj9o4/WP5q9i0SlnnCPl8Vhg3iMu5ZmtuWW8pgQYxm2xd2yMs0icSZ3++KDXRiW\nOKppePAaLkYFqd1ESpooHyX2MpgKNkYm9gpKGOS5fKkkLuEKpY7ONaALoY5OQWKCRpI4AYkJ\nsSZX03Otz703+N54YtzIGld6V+6q3ZW92idScSIxkRJTZoP5ze43g6mghyI0+wdXqCqbJl6z\n9/srv5/pIUUnL9AxlRAuXkoMliVRQZhdpPpusAZiL59nJmdC3VYMfK4aJm6Nkug6OjcTXQh1\ndApSbtW4uTOEqbBVAGh0Nn5/5fdFWWQZVqVqo/HR13ten0pNKfOVyJdQ1pRFtbMIpoKHxg9t\nLNuo5PKTsk6Mn6Wh/syEMQNbKSzS0OSXphAMKW0Ha4AsYLYuaxGYhvvkxBT8F+eGDDZSv63w\nHjo6NwNCl3ixYR5GRkaqq6tv5hlvNDKVT/pPDkWHvBbvpvJNZtZ8q69IZ8mQqfzTSz9VpQxu\nr97+QPUD2SO8xH888vHl0GWRivWO+u1V21++8vI0P1384IsyCgE4DI4XOl6Y6YlBZTp+FtMD\nYAzwtfj5aVv3fgu9FS5GZw34MPgoDFZSs4nUbVHMUzrVg5ETlI8QWymp2wpb6dwu4WE6cgwi\nD2c1qdlYMMpU507l5suELoTXRVJM/svZf1GSnQGwDPt8+/P19vpbe1U6S4ggC5+MfnI2cJaX\neJfRta1qm6pbBQV9+fLLPeGezIids8fEBdlbhJISIEgoA1Ij00Fm5oCFBLLOXvftzm+rBunk\nRXrprUW9qRsHadxO6rbS8TP08t65UYZl1r2AeX2nOjoAboVM6K7R6+LlKy9nVBCAJEuvXHnl\nH9b/wy28JJ2lxcAYdtbs3Fmzs9CE4dhwtgoCyFfBjLaVUDJF5h49KaFBgABrRGajxLxkEgql\nVShHGI4PZzeHmtnUvX9xb0nj4EuVUE/p8DFSt5X2fpwzLEu0/1Oy8s+W5iQ6OkuNnj5xXUwk\nJlQjSTGpGWGhs1zxJ/3zzslYeB0inkpzqr86CkQZWikzT6c5rsDyYWaQZlIvqITkFJJTEDRS\n+xfF0nlUCYSE5iXRmPovRUfni4NuEV4XmuU/0lIa88cN6CwTPCZP9kvFdHManZF0RDWTgh40\noEqWpTzn5wSRJ4jcLrH/Mcn81CxOEm3LsNpWrZQYpT3v05HjoBQE+W3r1acFlrSGWlGMdphd\nYFjIucE7JsdNugAdncWjW4TXhcOg/vNmCauZaq0wEh95vef1H1/88Zs9bxbv4KNzu1Brr80O\nLiUgZtb8dNPTmWyH7E0UGGHkfJsvSvAjs/ieQZxgaKCACjo46+ONjwOgAwfp8LGZyjJ03hZJ\nBCDE5IKzWunWq1HdZZ63uLApysnqtoCwpLRDPV6+oO4fOjq3BPYf//Efb+b5otGo01kw5fa2\no9pefdqfUz7xkfpHqu3ay7w94Z6fd/18IjERSUcmkhMn/ScbnY0u053bsGYgOvDZ2GdnAmdC\nfKjCVqFq5n67wBCmxdUSSAWm09MUtMJa8dXmr9Y56vqj/YUCRzXDYSgwzNDTnFY3RaDD5Ht+\n9V87jU4A8UtvGKRiNdjyIZ4GZvXXibeFjp0lsrpc+AKsxQUZlKRxB6ndrJwOyWkorRAZltTe\nQ+r0Imo6C+Xmy4TuGr0u6ux1L65+cV//viAfdBgdD9U81OBoKDT5vaH3sl2pMpX3D+3/Tud3\nbsaFfvE4OnF078BMYOHFqYun/ae/e9d3lTy52w63yf3nbX8uyIJEpUz+TL2jvi/Sp6l5BMQI\nqCvWFIYA1ObLfDhBMWFdrKvTWUXHTtO+T65/QbEgVt+c2rEm0vkVIuwGH4XFA9Z4o06qo7MU\n6EJ4vfjMvm+2fzN/fDwxPhwbthls9Y56A2NgCJMfVTGWGFtsMtnygJf49wbfyx4JpAIHxw4+\nUPNAoV2++BgYgyFrcXhz+eajE0ezg4qzyajgQn4AFOia6uqL9DU6GyPpiJ+Ra+Vi1nOEoZ+z\nkkhQJ5HVEsPYymF20ouqFIulixUFYLQzHY+rBw1WGKxLdgodnRuGLoRLSVJMdoW6YmLsTOCM\nP+nP3OAISJW9iiNcmuaYAXaD/Q5UQQATiQmRqp17w/HhW3IxNwgLZzGz5kJCmNG/hf8ABmOD\njc5GXuLPM/J65Aihn9DSrGx6geI4JwE4zeKcyfvNld/Exd/lHe8af3jEYKViUtX7gtRs0tME\ndW5fdCFcMoZjw7++8uvMjS/7BkdBR2Ij+busLLlDIwjMnEb9nWVWlEemstKSV5NreAAajg3H\nhbjX7J0wmd6i/G7BoFRk6WfkQVYuzerNawJYYIXEOECCydCZqQtrUuFreQ9a0LIOjJxQj0ZH\nl+r4Ojo3H10IlwYK+mbPm4Ue/zVZ4VxxW3sCrwef2ec1e4OpYPZgu6f9Vl3PjYAhjMvkmrfQ\n2sIRpnoOTv3LhtodX65/5I3e35/n0iUUScAA8pepnHydSYZ+nzf65BmtDfR+TuyVNBHUOuri\nCfZoDOaFyOro3EboQrg0hPnwFD+1wMmKW6w30tsX7mt2azYYX+YwhPmz5j97tfvVTFnqeyru\nWeVddauva4nZULrhg+EPNDexYCUULJPNMVx2gycDyLM81yAzAEX3R26z6/stXzsd648JsUpr\n5UZLJXfudczOTxBqoiSjggB8qRhcJmi1QLoWUlrS7mlcgiPr6Nwi9FqjS8Nno58VuuUVgRDy\ncF3n5vIqwAe03Ji0Tj8wDFCgCqi4AcfXYIqf+mTkk9H4qJWzrvGtWVe6TtMTKFJxODacFJOV\n1kq3yX1zru1mQkE/Hvn40PihtJQmIDQ3G48Q9V8fS9iOko413jXnp85fCZzdKjCHODlB6E6B\n2yqyUdATBmmawCNjg6XauT6r6GgqTMdOIRURzM6Xgke+G5cY1QduKWGadtKRozQ6ASm1pN3t\nAYC566vwtS3tMXXuWPSi27cl0/zEu4M/6wnzaVm+hijQ59pKWlxmoBR4HFjaXLqTwPGsl6uB\nLXlzeMAPMEAplqIiTjgd/rfz/5YUk5mRbZXbdtYWrNW57KGgwVTwh2d/qBq3clYLZwmmgoSQ\nOlvd+rL1Ta4mu8EOoCd40XXx9yUy+RdzOkTod3kDAX5uEvlZKTVTfKv9hQpXIyQeQgpmZyb4\npS94sf68doAo8TSQpl3y2d8gvfAqgEXq1mTFnZpdzOa/XvAxdXSKoRfdvh0ZYJn3Hmt0XQ2n\nft8zfQ3BeOeDyRaXGfADZ4F1S3dhwVwVBHAWqAcqs0auAgdmg/ktvLTlxKR/Oj3tNXvX+tbO\nm9UXSAU+Hv54LDFm4SxrfWvXl65nCHNw7GC2CgI4MHbg3sp7LXdqtx0CEuJD+fafzWB7cdWL\nCTFhZI0cmftLDKQC0f6PG2UCYIXMnGAljuJPRokHzTxmpQh+2vWLPdQSlngnSAdjs6zYScpX\nAWj0dkrmj0lOdMxsndJQPz31M0jqhPqi0MI+1ayfeiqM1DTMy9Cs17kTWD5CyEt8TIi5Te7i\nBUokKp2YPDESHzGz5pXelbX22kg6cmDswFhizG6wry9d3+wqtmgnU/n45PELUxd4ia+117aV\nNH449NZonAdQYTVwDDTbBxQ3E2Nz+yxt0TXNo41lCeEU8AmQOXsS+PDwxGQkLQH4fPTz73R+\np4jHMsSHfnzhxykppbwcjg2H+NCu2l0TSXV5ZQo6mZysd9yJ3ako6Bvdb5yfOp+/qc3dBsDK\n5WTaJcTEL7p+8XAyqfjJd6a5CZM8yNBRRkZurGma4A8koXjTP6SRb1z+Y5XRTjyNABhHNS0U\nJro4FQQAMAykhSwu3omJQDrLg+UghCkp9af+P50LngNgYk07qnfcU6Fdz0mUxZ9c+slofCbU\n+8jEkR01O46Oz2U9X5y6+Gj9o5vKNxU6196BvccnZ8ys8cT4Cf+JTLGY8YTAMdp+pOLO0gpr\nxiG5tH5RjZP6kwGfhcaEmD/pL7WMOgyqGxy1sEwEEoCoEH2r/60X2l4odPSDYwdTUipb4w+O\nHWx2NVtZjRxql/EOrSR3NnA2XwUpaLunfUfNjvz5F6cuRtKR+KyBaAL+gjcOMDJLIRL1QTL/\njxP6llH8D+PnZoJWJH4p30N+OTeTA3w0Z8TigfkO/Yp1lgHLQQh/ffnXg7FB5f+8xL87+K7d\nYNcMQTw6cTSjggqfDH+iCmHYP7R/Q9kGTbMyxIcyKqig6j4hytTAkrSkUVU5Q7OruTvcnXnp\nMLBbK22zr2oL7XVNVAJMlsEHAG/1HY+mL0SFqEzlnbXObZX2zCaJ0l90BSeScxZDX7jvpYsv\nRYWox+TZWrG1xd2SfajJ5CTy0iV/3vXz/OtocDYsy1iYefn000/fn3yfqVPHQH254ct3l92t\nuYuSUnKBlTeIM79AAjTITAuxnEdScxeFSUaOJgNOKoEwSKkbXywChgEloAUjWmGvYDoek6+8\ng/DQzIjBwrTnlZXR0bl9uO2F8PD44YwKZjgdOK0phPm1S2ieASfIwmRystJaiTzyuw/m0+Q0\ndYVS2SOtbnN3mJdn14e2Vm5d41tzNnA2KUWqbaltVWYbp9zyWgF1zf7rwwNsBo4oWihT+ulo\nbDiWzpT3Go3PaJ5MaVSQ+6P8SHxOBQmwqdy2qZx3Gi3DsfDHo68/JCX8AAAgAElEQVSG+F3Z\ntrJSALoQmQSAFneL0jPhTuPAgQO/+tWv3Pe7LVAvjqo6N2XjNXsB9DPyXoO4U+CUGp3TBqPN\nUWFODqXEVKEdASA2Ln/2/xJrCVWqXV8bskwcFTSq9quT6k3w1BOjHY5ySAKzYgeNjkNIweQg\npa24UxeAdZYHt7cQUtD3h9/PH1ey0wRZODpxdDA2aCCGjpKOu0ruUnq5zUvXVJemEBa/9SvU\n2I31DuMno7GUKBOQTeXWXbXO94cjJyYTgkzNrLnaVm1iTbM6nQaGgRRQCpQu5NoWySp/0nTc\n/xYD9EXS44mc9aFLU8nusCWQFD8eiaUkmeQasduq7A/VOEVK9w2ET04mKDAY3bd/aP/Omp2b\nKzYDWOtbq7ijNWEJ+71V37Mb7Ko1sDuHDz/8EAA/yltackTCyBqrbQUj4u4queuz0c/C6fBx\nTjrHSeUSkyI0wKTl6FUKyhJWcULkrzqXUsZOCYWMuFoFBeA0J/kJtQNrRNZF51nM0w4SFeIz\nXZzGz9DuD2a8rzYf0/6EroI6tzu3txBO89PZeccZrJxVpOJPL/004wg9P3V+qGKo1d16OnA6\nf76CiSVfaykJpaRj/mM7anbkuzfLreXl1vIidiEFrbYZGp2mLRU2SQbLzHgOd9U6H65zRdNy\nXGw1saar4asDkQEDa2hzt1VYV1zLO18wInUcHo9pumop8KsrU5lIRlUezb2VdgAfDkdPTCZm\nJ1CBCvsG95k58xrfmhVp4fE0t98oajrseIl3Gp1Ksc1PRj7pjfQSkGZX8/3V95tZc1pKXwpd\niqQjpZbSVndrfuu+DHEx/tHwR93hbkrpCteKB2sezO8B+cVkcnISQLInaa41m1fMVI/jGO7x\nhseLBNBaOMs327/57sC7/dF+EGaEiNKs+52AyFS2sKakxGd/oQTwUfIVgYHWsnCC0JdMQojM\nfLsHOOnZtKFBKpqx6qxCnkU4EzgaGaZX3pkLIo0HxPOvcZu+B0ZvRa1zG3N7C6FRq72LzcA8\n2eQl+MW3OxBOl300EjsfTAA4NH7IVG2qslWNxcfyPaIAeIlSig1l1lVey0TidIW1A8ipfhnm\nw3d57grz4UyopAqWkGqbEQAB4ZiccQAOI+Mwdp/wj/2x76oy/snIJ3vq9mwu33xtb38hlFnK\n7AZ7XIhrbi2URGo3MGaWAXAuoCFzB8YO9Ef7t41eWSux1SnyY7OQH4noMXnMrFmk4i+7fjmW\nGFMGJ5OTQ7Ghxxofe/nyy5kG7pW2yhfaX9AsNCpR6VeXf5V5mjnlPzUQGWhyNYXT4anUVISP\nyES2G+w7qnes8a35opUvLy8vHxoaAkXoo5DpsslQZrAYLD/45g+K+EUVfGbfc23PyVQeT47/\n7/P/W7XVY/aKCb9AZz7yEpk8KRiq5YLv/UODlFFBCiqA/NEg/q1U1DUSHtVoMe+uA0D9l1Wp\nFAwfOdWzd13LE8XflI7OF5nbuEKgRKXfXPkNAzRIZK3E1soEAEvIc61enznAEpFj4DVzTze5\nd1Q7ABAQpdyJpgoq8JIMwMiSCusx4BfAj4HfAoeA1JGJI/967l8/HPmwkAoC2F7tMLLz3I6r\nbXMVqmQqvzf43hKWo5Tz8r1Ywl5Dae+4IPOSLFEaFzXi5v1J/yn/KZcoAjjOqdu8Kh/v7rrd\nALqmujIqqDAUG3r16qsZFQQwFh97f0jDvw3g6vRVVXDTFD91bPLYlekrgVQgTdOiLE7z07/v\n/f3no58v9j3eaPbs2ZP5Pz/Kx07HHmp6aF4VzMAQxsxoPByE+FBGBQnwlMCpVFD1hQ2TuV+7\n8qwQIjRavON8bBwVq5DlKyeeBlK5FgDSGk9UVwNnzgc18kN0dG4XbmOL8JT/VCQ68l3eWD67\n5tHHysdLmSqb2kuzvdpxOpCc5udp6s0QVNtVT8oyEAbOSbTv4+FeiUoomhR4b6VtIiGkJFpm\n4Syc9kNGiTknHlWi0lBs6HqCKsPp8EB04EroSl+kLyklyyxlVbbyJleowSGZOYYlVby86M4A\nFDg2mdhWafeZ2cmk+nNTpC5MqJuSs5w6vJCAbK3Y2uHpwGxkqQpVrW0AfZE+zcvI7+BYiI9G\nPrqn4h6O+QL9nu+++25Zlvft2zc5Oenz+Xbu3Hnfffct6gges6fUUqr6ELKfw7wyqZTVP7Mk\naIzQMsoov1HNT4Sbz3omjIls+Db1d0FMw1VNSttn3K6OckxeUE0eZyhCF1d679BWKjrLgC/Q\njWOR0LH42aeM5vK0PETkQZayFM0yszmhIT8E2F5lN7AkLdGuUOrKdAoAQxgWbObhGsAD1Q6X\nUTuTjyWxNaWmuGBY47O8OxD1pzSyki0c89LF4FhcAMAxZEe1Izs5IUMgT1eKrJDNy6ejn34y\n8omUFew+nhifTE6sL/XaDEZAAoYerpP7I+w0XzggXouPhqMSpfdXOV7v0eglREE/5aRtIquZ\nsNZZ0qn8RzN9MN8izzdkFRZuP8lU9qf8ldZKCtoT7plITFg5a7un/daWs9m8efPmzfP4vYOp\nYHe4W5TFBmeDKoiGgDzd9PQrV19R2jlR0BZXS3bujV0r7GWSpb80ClUy82Sa81KyQiajub+v\nGpmZ/0OhImxlxFamGiaV64WRE1xWtv4xTpoi1LmYvis6Ol80blMh9APvPNYoAp53+sKH/TPu\nmv2AVyBfjQv5RuG60pnYxfWl1s9GYx8MR1jC/v36v3+7/+0zgTPNLtO2SkeDs9jCyWqvpcpm\n7AqlNFUQAEMwNpt+IMr0/aGIz8y1e9TerQNjOc4ljuHq7HULe9dqusPdHw5/iDwjVab06ESi\nZta6NbPM3WW2/UMFc8uUxTwl7ChzKInSj4ajADgGWv5RnOEkVsvDZuWs1faZG3qbp+2D4Q+y\nu1M5jA4rZ1UFHHnMnte6X0uKySpb1dbKrZlAU5vRZuEsSe1wnDmUa7ZwFolKv77y657wTJ+g\n/UP7n219tta+tNmZS8kJ/4m9/XszzzFbKrY8XPdw9oRya/mLq148FzznT/kbHA1JMZkthBMs\nlfOWN8YIBTDKyG8Yhe/yxvsFbpShvczMV+ih5HFh/r96OnqS+NqVdcEcWAPW/fnB4z+skqkA\nXGTlM6wEoEgcrI7OF5/bUQjTwLtAEkBPmM+oIAAKBEDfGQx/u8NXZP9tVfZTgYTP3GhgDEra\n1mhcEOcrPq7UfwmktP2rnSWWi1Pq+/WFqWS7xwL4gDQQA1xnAsyFqRxHpdvodhivMQxyMNrV\n7DKF05I/z8oM5l6nz5zzRTOEyRhhLGGfa3vOa/b+5OJPAqlAvtdXUwWVaSc5jW2rvKsuhy6P\nxcdGE6OxdMxmsBGQuBgHUGWr2lC2YTA6GEwFRVlUBMzIGHvDvcq+vZHeM4EzW6u22jn7lekr\nqvQME2vitWqmKBdzYPSAw+jIqCCAhJh4o+eNH6z5wRctjkZhmp/e178v25o/PH642dWcXeRP\nlMU3e9+8OHURwMGxgz6zL/uhJwn6mUHcniVsUdBDs87qcYYGGeqTyZ/zhgFGniTUCdIk5bmP\nNashUSr3fcysez7/so1GJ7fiwV8MvpMZcRld2yq3Lfr96+h8YbgdhXAMmLEw+iIat8XBaPrj\nkej2aodyt+AlesqfrLZztbMWEgHa3J57Kr4MoMxSBiAhyi9fDnpMnM/Mfr21hCX5902WIRIA\nj0nDd7qnvqXKmrw4pc7W75oS/ldSqLIx91ftVrx8B8b+p2pOMBVMS2nN8Nf5+OyBmlEC71A8\n/dIFvypy3purfFNZ66OP1D/S6Gw8PH44kApIVLJxtq5QV6Oz0Wl0BlKLTsSutFZOJCeyfZtH\nJo4cmTiimlbnqHum+Znjk8f/2PfHzKCBGEQqpuV09syoEH134N38EzGEcRqdIT6kmTAD4HTg\ndMYSzTDNT0+lppTHnS8aQ7EhkarfS1+kL1sIPxj+QFFBhewnFQrqAGkSmTeM4kqJWCgZZegB\ngxTPLr0G6gMBUC8zBSu9mlzQLEwaK5gmtKViS6ml9EzgTEJMVNmq7qm4546tqK6zPLgdhXD+\n1YiPR6IxQWIJE06L/ZF0SpIBPNHozjhId9V+iSFOAK3u1jp7nVKbJsSLIV78ycXAc21ea06o\niwmwA0EAzS6zx8SGstbbHEa23VVtMWxhyP+jWusSqDiRmJxITHaFuv5q5V+5jK78mzgFFalo\nxGKF8AJwSbkjXp5KqVSQIWRT+VwauyDTU/4Za5WAnAucs3CWB2se/NGFH4XTYQBXpq8cHDuY\nv3Q3b0up73R+p9Ze+8rVV7pCXcUvdzA6eGX6yscjH2cPClRQjr+Q3lUylSeTk0XmC7KQHYya\nvWPxI98qNKOXVR0qLoUuFdqdgMSAc5wcIPJvjdoVbucPwWI4YvFoV+iWJSSnYCnR3K/J1dTk\napr38Do6twW3oxDOPd03OI2fj2lPGooJE7mFVPYNhlf7LCwhgkwnkpdqbDUAxxDmubbnPh/7\nvDt8lVLBZXLWOipM7CiQva+oqCAAE0uea/P+qT88EE1TSmsdxi/Vu2SkBUlwGp2FEiGSYvJ/\nnPkfpZZSu9GeaWSv3M1LLW4rpxElPx9z0eqh3CgYloHHyI4mhHBa4hiYWfbjkejkbAVRCjoc\nHx7uGa62VysqqCBDXR91XnHaULZBWX4bTyyoaUb24pZC5vhK09pCF5D5T/H5ALJXE5UJDoPD\nZynmJ7+F1NprWcJKuVU9G5wN2S8T8wWhHMuL2s1AQU+x8o68sNI5bKWkaSdCfQj1ax6AXnmH\nrPlG8QvQ0VkG3I5CWAasAHoBNLvMm8ptRyc0cptkeeYZmQDrSq0rvRYzS3iJWjliYEiNbQh4\nHXgAoCa25KGayodqBgAG4IGJXBUEkHOv8Zm5F9q9gkwpqJFhAEylat7oeaN4OqBMZSVCJBP9\nQUCMDPN4Iwe8DjwCLGqlcC6GvtQy8yXaOPbLDc72Esspf+KdgUhaVhr3aKeMqfLz8kWliAoS\nkIfrHy5UNlpFRrHG4gWeWea7AM0r0RxMSalqW/VIfAQzH6/xKyu+8sVcIATgMXl21+1+d/Dd\njM26sWxjq7s1e06Vtao/2n/NpxhlCq58k7JO0vEEpLR8+U+F5tDwMKESivY109FZBtyOQgjg\nQaAcuCDIkfWl1v5oajIxp1UMwc4aZ39U8KdEALvrnPdUaKQxABFAaeTNADRLL9T58hSIpiWb\ngcleOzQwJOOQJKRs4XcrM2veXlXvTw26jOxan9VpZIFp4BPgyws8QleoazAWNRC+3WOutBk6\nS8yfjEQp8NUmd5PLNJEQ/tQfluhME9eCzcXnCw4qAsdyNfaaTNZHvaO+yENARoeUHIAbioW1\nfKfzOxemLownxm0G28qSlQspD3sL2Vy+udHZeGX6iiRLDc6G/JaNe+r2/Ojijxbo3c23km15\n+RVzTeUNVgA0eBV84VYVX9BHCB2dJeY2FUIGWAWsMjDJCqv/r+4aPuU/2hNNiTIqrYZNZTab\ngTFziSvTSYeR3VJhm+9oxe4yB8djn47EUpLMEbKx3Lqz1snlhtLIlD0+eWohq1wK0/z03eWV\nrHr5ZgwQVV/HSHyke7pbolKjs7HR2QiAgr7W/VomeuKzsdiuGsfFUJICbhPX5DIB6AnzEqWY\nrwni9SBIwksXX3qk/hHFKFxgKfPC0KW6467yrWIIs8q7KtN7JCWlPhv9rC/SxxK21d1aKOl+\nip867T8dFaLllvL1peuvKXbpGimzlCkRW5rk97UvQv433pFXUzQzg46eBCgdOZG1Uf1FEFet\nbg7q3AncpkKYwQLUMaRuQ9nAhrKcTqHrSm0TCV8wNXw9enDSn3hvcOZ5WaT08HgcwMN1OUni\nBPTo5IGFn8VlcrEkf12HAlL21/HZ6GcfjXykmAKfjn66sWzjI/WPvNX7VnYMoUzp/uHo5grb\nUExwz5YCSGk1E8/Ol8g78UIlPBuZynv79xqYsdXeVVHhgtfMBlPai1XzHt/KsYnZFA3V5OL7\nqrZW26sfqXske4JIxZ9d+llmCXMoNjQYG/xG6zdUx+wJ9/zm6m8ycUyHJw5/967v2rh5n59u\nBhenLqpiahb4EXHAdpFtVQthltRROVcFoX4cMTlJ6yPQ0bkDuN2FMMMaIKfaJEHTI/UPRtPH\ngZPXdMBWoP+kX51OcNKf3FNXScADsuJNTUmijWOnpYXWbdlUvgnggdwG32CBNwECOIAOf9KR\nUUGnkW33mC3c5XcGh88G1WEpMqU+MwvAn5xJy6tRV4lTphW0ehkwdY46p9FZpKeS5t2Wgv6+\n96Qg93y9xQ3g8Hh83+D0otYaFVb5LMcnEhKlBFjttdY5TLwkd4VSQ7F0oX2V63EanLvrdl+e\nvpyW0iu9K/M7UJ4PnlcF8lydvjoQGVAFpPyh7w/Z0bzT/PSHwx8+1vBY8cu+0aSk1KHxQ9nN\nUoxAtcSwwBhD4ySzBE6yl4FNrOmbaSMvpcpkku8XXZDlbbSTytWweElpm95TQucOYdkIYSeQ\nAM7MBrasALYBcBjXA4PAYtPjGGA7YJ/mh1Qb0pIcF6J2w5y/yMIxL64q++fT40lxfhfW3WV3\n31NxD5AERoHsGB9pVhojwMhgrFyRrla3+elmtxKSA6A/yvkTc7dsRQ8+HI6yhMRF6dOR2PZq\nR4vb1OGxXArNU40l+yAD0YEyS1m1vXokNrLAvTJ8MBTdWGYlIHeXWw+MxaLCgh4IspX1+ETi\nay3u3jBaPeyK2eI+91ba3x2MHBqPae5OQBjClNvKPxj+QFmeHIoNyVRe61ubPU2zYdZ4Yjxb\nCCPpSHb0rMJQVP2932RSUurfz/979qrqCpn5SppTaqqlCd1vkE6wMx915mdXRbkvmeorY0PZ\n1WYK+p0J0Wo+QpiNfwmDnhSoc2dxG3efyGMj8DzwFPA8sBMzmXkMsBMoV2akJLkrlFrAkosM\n8EB7qUVtXdk4NlsFFQwMeaB6QTGfu+p2ERDACjwDbCn0+TMYAMAx5Csr5lQwxIvBPBUEEBdk\nZVHwo5Ho3oHwREJ8tMH1QLXDbWIxWzFgXiaTkyoVbHQ21jlmKmwVsepSkhzmJQAsIU83L7Q0\naPYBJUp/fTXU4DSsyC1xt7PW4SxQ+hWATOXu6e5MkE5STP6h7w9KPmgGzZI9qvAZg5bRozl4\nMzk4djBbBW2UPMUbMpVFjZQ8kuaqc/Mi9gjct1NMZXBAteZdKGy4wG+PUn/BzEUdneXKsrEI\nFQzZWYazOIEngCjAMwi2uA8SdXZEPiyQAtz3V+3pi/w+e8P2as0AVGwos+8dKBx9BwCotddm\nxZVMAOcKxems9JrKraXhtJid1z8cE5TZLCEVVoOFY0bj6URuAbTBaFqVTNLgbNBsATEvlNJC\nNVyyYQnJPBnU2A0sIStczbzED0YHi++YezIkxbTq18gSUmXjIumF+pxlKl8IXsgu3Nrh6fh4\n5OO0NFe5xmF0KGFHGSycpcZeMxzLqQrU4m5ZxMXfAFSpJrUyUdloBGiRmJHZCqKdErtZLPjQ\noPEU46wikkjjWj+M6UFUrV/0Fevo3M4sJ4uwOA7AZ2RLWDKvCgKQgLeARKNz7QvtLzQ6G+0G\nrtpm+GqT5+6sii3ZsATPtpSwTEHLycAYnm19BPgI+C3wW+DdXNdoBgrAwJAqm6HDk3P3O+mf\nya2WKB1LCCtcxv9jTfn60pzrSQg5uug0Ou+ruu/aejxNpaZCqfkTHlZ6Ldzsux6LCxKlDJhv\ntX9rsQVUBVnDbtEsc1qEqJCz8uoxeZ5pfibTAaPKVvb1lq/nFwN7csWTJea5+ilt7rb7qhbX\nL2nJUV2kRWPlFdkzmqXFhDtZvUz7Y6S9wCIoo4eJ6txxLDOLcF4WvljIAyeBVY3OcKPTB2i2\nG5ojxEt7B8KSTPNrhSg+zC81PGDl3gHmsbFoVjvUEC86jaySvHg5lMourCpT+v5QpN1t/lKD\naywhZLpeRAXprhJLdzglU7bBWbqnrtJhOPLdzvt+eHZ/craPnWbkCwNGzjVPY0JMLmCwsoQo\nztjVXsuj9TOeRonSdwYjAPxJP0OYGlvNpXQxJ5vqMrrD/KbynEDNpCgPxdUfe/E40gprhWqk\n2dX8gzV/l5QOW9luQnjgY2Ad0Jk9x2v2/vWqv+4L90WFaJmlrMZeU+Sybw6dJZ1ng2czL0eZ\nuS+in5H7WMpQOsLOPToYFh73W9rBdDwOwgBgVj4tn39dPSG/44SOznJn+QthWk4PRAeUFj8+\n8yKiAGR6BbhY2MabY5qX/tf5ybREATzd/LQkSxPJicvTlycTkwAICEvYlNg9rwoORNP1DiMA\nCrpvIHJsIt4yGywzEE2rJssUg7H0WrO1zW3OCCEFHm1w2jgPRSXBGDAOwGbAf1y39mddw4oD\nMLtuGUtYjuFa3a1llrIPhj/IHLxIukWj07S10mZkiIllAknxUoi3G0iIl46Mx5XWHAREolJM\n1I5zyaDSsyvTqc/HYlsrbAwhAJKi/NLFQH4r5SIq6Da5N5Vvyh9nyFkbl+klGwc+B1igTXl9\n0n/y0PihaX7aa/beV3XfF0EFAdTYa5QycgAo6ATBMVa6W2L3GcRMTbXsj2KIke/KSxnMh5Td\nRdq+hEz/S28LadxO+z/NRM2QkiZSsXpp34uOzhefZS6EI/GRV6++qoQFEpBN5RseqbcoLZzm\nhSHzr5ABEGX67lDYbjCX2KvvrbxXWYJqlVrPBM5k5khUemewt9zqbXSaCh9p1/7BN/7yLiOA\nk5NJZanvynTqh2f9HR5zUKv9kyLSlqx1xBIzZ+NYgCXIWWTimMF1pZXZK2HKbXR37e7NFTOd\nY30W3/HJ45F0pMLqCab6R+Nz0puxwyqthj9vm+vOUWE1/LE/cmIyR/OCfPA/n/jPC1lfVPH+\nUOS0P1HnMPISvRpOKQ8W2bS4TCaWuRRKSXnhjlaOeaal6tLUL3siKQJ3i3vNKu+qWalQd1QH\nzitCeGzy2J/6ZwqMjSfGX+t+LVYfG4mNjMZHLZxljW/N+tL119M2+ZoZiAxk0geVd7HPKF6U\n5YEs0zA7v/A4J3VKTF1eWVGB0DFCGYIyiTGVNJKOx+e2iSl6eS8NXAYAMMRRjtotpLT9Br0j\nHZ0vMstZCCUqvdb9WiY4noIemTheZXtwpXeQJUvWUJtjyNeay4AngbmYyeHYcH4nhK5QqrAQ\n1gGN4TSGY+kau/Hy9FyZt0haOqJVTJVjSL3DBGAkNmMOcoQ81qCsh/kAdeZArW3m1AxBZj2u\nxjFnAHV4Ojo8HQCAt/71nCrycHYVMCH8z3P+Z5o95daZuMod1fYzgZRK9q5BBQmIy+gKpsKB\nVMGvZiCaTs9eOpMVaFRhNXznLu8b3b1dIeVzC54L9lydvvpU01OAkN2uJC3Lh8biA9EpA/Ob\ndk/756Of554B7wy8kxGYodhQiA/tqt212PdynVDQgxMH88ezVVCFDPzcJOxMMxslLuMm7WHl\ntwxijFAAVkoelRMrs89y5Z1ZFQQg0+gYEfQu8zp3KMtZCP1Jf4gP5bngzq3x7Q6kPvOZF32z\nLoAbeDBLBf1A30TyYv68ZMHYj0bgQQCNTttr3YEnm9yaM9f5rKcCM7cqjiFfqne5jGx/JH1+\nKmlmmQ3l1g2l1hITB1QBDflCWGqtfqa5vsHJm1lmMim8PxR1me7SaixOgUCRNsXBlPhad+jF\n1WXKx9oXUavgtUFBp9PFqpYDSGcF1GR/QBKlPdPpWRWc4Vzw3IbSDW6TmyEmp5EHIFL604vB\nsZmeJJcvT19GHqoyLgfHDm6r3HaTm+0FU8GFJ3Rm9ejAcSOt5mmdTABIhB5h5dhs3n2C0Lf4\nocrYiFdp2SiLWSo4e6jhY0SPF9W5I1nOQpiWNEqTxISITD/ymZsEedDALCSCdF52AJlGP+eB\nQwBt94jv5qUPVGvVfAEgyJMS5c2s9eF6088ukZ9dCppYtY/LyDJfbnRtrrD1R/iJhFhhNdgN\nzCl/ojfC2wxMNC21u90lJgowgAXwAVzukqSBYLyzRFDihCushufavIBqRS0FmAECGDmQjaXW\n3mg6mBLyP8NASgymRKXrfV9EvXi5KK6twJsKf1J8s2cuwDVzzFe7X1XaGJVbDU80ukfj6bHc\nzlzznp2CTiYn82th31CU5MgFfjLZcyqyvKMsJV8VuH9jpMjsdgH0cs++rWv+EgCEBPLXgJNT\ndPysvkaocweynNMnyq3l+ZnRA1H+n09PXJg6b2AeBrZmgiaulVVAJmM9ARwGKAX6I+kSU85D\nRqXVsKFUO/XCwMTf7vvX94f2Wzjp+ytLv9ZSsrncmtsZGCucRsBQYW3YUmEXKB1LCPVO47pS\n61NNnr9bXba+1BpJx2cLlvYAh4DtQMYNawbuB3qyD0hAydzi2Rng58AvgJ8CJ4CGbVX2Lze6\nd1Q7Ct2LU7M2q2rxMhPfkd91lmNwd7mNzS1ZriqbqXmuhZBtLGaOmWnmN5EQfnN1aiim1uyF\nKE0m++Km4TP7cE0101VPtWaKTiknFyKR9M/8z+TULB8T7nnver4FHZ3blOVsEZpY0yP1j7zd\n/7YqADImSG/2THtMPVW2bcAwoOEiyyYlUSNjZIgLaAZcQBBIABxQC1QDPKA08hUUj93e/vCx\nyblVPRPLbKu0b6mwzebbGfL6HcJnYT4eOeA01mwqJx0ec4fHvLXSfmQi3h9JA2h1m84HU4fH\nV9xb2Q4kGhyJtaWWTBMMA0O+1ODKTTz3A1bgWcAPEKAU0PQ6KqunF4AjsyMCcAIo7fBYB6Lp\nS1NJTbvEwJByq0Gi9NhEfCQ6917yO+hm83RTSbvH3OIy7RuIhHiRAAxBdkBMkVu/08RIMuKC\nfM0WZDQt8VrlyIvT4Gy4tizM68Ftcq/xrckOtlogDbL6k3Hnlhutlkmm5hpp3EGv7FPNt4vC\naf+pdaW6g1TnzmI5CyGA9aXry63lB8f3XgjmLLpIlJ6fGvfyC1QAACAASURBVK2yAShWAEWm\nmObtVkMrQzoBK4CYEAukqN1Qpzy2A8PAh7MtDAmAQErMVkEAvCQbGKV/IQA70A4cV51ompcA\nnA0Km8pNiktTphiKCkru4EA0zQD3VF4CrgBY47OoWkGxhHhMqq8yDFQCmSVATbNGGcxfzvQb\nWdQ7jPWOkg+Go5+NquqDo9Zu/Ndzk9G0rIreLCJRlVZDu8cMoNVtbnWbY4JkYplPRqKfj82T\nZQGAgkZ4ucpuSAjy9TRschk5lqSzr9lhdNQ76s8Hz2dGTKyJgKSkFIBWd+tjjbem9PZjDY95\nTJ6zwbOhVGiBJlqrxKzNKy4zmdWYd4XMtNkb5ppoVq4V+z5mhZwI6imG9kb6dCHUudNY5kII\noNpW3elZrRJCAJG0co8otsTFEJSYY8BJ4DzF7vcGzx2ZOKLYl43OxqebHrcZPsxq5EsBjMc1\n1h2H46XAOsAK1PmTQyVmjs3KzYgJ8tVpHoA/Of2ji6b1PqbGbjwTjHMMyiyGyaQgUwqCQDIJ\n2IGMphZHZccYgXagK/vNAUoUoVrnstlRbT86EeclmSHEwpF6h3Frhb3CZvhkJHpiMpGYrTNe\nbzd1eKsmEq5T/tOaxxFlKlNkLlypylZqXdDPT9HX0ZhwnQuKzW5Tlc24dyCcMQ15kS+3lgMY\nig5R0EZn447qHS6ja4qfsnG2mxwjkw3HcDuqd2yv3v5fTvwXXpqnmAOAcpl8Lc3lVUngasAk\npLRM6AqJ2UBsTMvu7O3h8o6S4ZzeLEdYSXeN6tyBLH8hBFBubcofrLAq1lK5YmbNR1qQ3js0\n3p953RfpOzT+x5216nb2NXaNBAmnsRxYmRLDB8Z+Op4MyDJ21TkrrAYAYwnhj33TMVEkILzE\nj8T4qRTzteaS3bUzNlwwJZlZYuFIoYZ/WlRk6oxnsRUwA5cBHigBNs2ubrqLFNxhCSmzcEOx\n9M5ax9aKuTqrD9U4G52mX3QFAZSYWLeZ/WCoX7NMmoI/JX4yEn2gZq7umijTifjiwk2VHPN5\ntVBzjoVlorxkNbBWjskIYVpOfzA0V0bAwlk8Jg8An9knUzmcDtsNdvbWdaYlIPWO+ivT8/8+\nY0TpJpG7e+Xa9fXb1o2fQXIKlhJSsUa1Lmhv2P6B/+TdaeqkJEzoQU46wUmPOXJqsero3Anc\nEULoM/vWla475T+VGXGb3BvLNgIA2kT5EsfMX3rNyKZLTNxUVrETf3IUKFFNc5uY73T6PhiK\n9kdnHuQZwnR6OoFelvngoVoKeHmJ/ql/ujeSpqBxQUauU/HReldDVh8Gr3nmRlxqKfJlNQAy\nMAawQCNwt5YLkQM2AZvyOvOsB94r8sYZQtb4rJvKcuqfCTKtshleaPfyEj0bTJwJzJ+Cdtwf\nV4RQkOk7g+FT/qS84N7rGRYbSMkyxGviAkkxKcl/6Fe3W1JxePxwvaNeyS/8bOyztJRmCbux\nbOOuul0cuTV/KY/WPzqeGM/PSVURJ1Su3cwOHpkbMjlI/TYYLKR2S6G9zKy5svWxH/b8HlRU\nftZtnrb1ZbpfVOeOg/3Hf/zHm3m+aDTqdDrnn7fUtLpbLZwlLactnKWzpPPJFU9aOSWGkzCk\n7YPhw0kxbWQYM1csjPbQRCyVFd2RlujWSo1mFC4ju7bUOp4QAinRzDKP1q9v87QBe1kyY4hw\nDGnxmE/7E+G81goEeGKFm1uQ8zOzxxZgK9AMrAPWAPXzPd+oDu4GvEAUEAFrvq+41mHYUDpT\n+SwDSwjHEI+JsxjIW70aApNvlgkyrbYZS8zs73unTweSN8cB5zVzL64qsxmY7jC/kDMyDBMX\n4u8OvqsUjKWgI/ERQRaaXc03+lI1MXPmDaUbXCaXz+xjwOS3TlRocbWsbX4CNh+RJRitpLSD\n6XgMBu0o5WzKLGUrfSvtRmeNvWZb1bbtVduvP5tFR+c6ufkycUdYhAAYwmyp2LKlQvPpmGl2\nPfbrK7/kJfFvVpcp6XH5hNOSEtKSQSzsCQTwZ82e0bhQbjEYWQswoio0yhHS7DYFxtW+QY4h\nC1sCVNJCvMDdQOUC5henAWgAAAwDe1XbfOZizflCBRy2mvfTX10JFr+OJUkrzGYqJYmUbiyz\nNThNl0M0LXd+NvpZoTKqAM4H1E3tAZz0n9xdt/tWKYSRNSrei3cG3xmIDWjOiQpRiUpsaQdK\nOxZ7lSWmknsr773uy9TRuY25U4SwOPWO+r9Z/eL54Gsuo7a2TfPSLy6r3adry4oFU7CE1M5k\n0LOazSvMeVnzAASZTibFCmsR7bEAG4D2G5MDurjeSQC8BZ4brg2l9XwRoVo0lP7z6QmlO5WR\nYTzmLjNrzuQXakwHDSbUas1LfFJMzroQbhnNrubD44c1N40nxs8Hz6/xrbnJl6SjszxYzgn1\ni8Jh8NxT8V0Do5005jaxD9epMxDKLQvsY16blXQ/R6ZGaIaZ8soDkUKmJgUBdgKdN+yLcwFV\ni9rBwjHNLvMSXsEK14olPJqc1aMxLcsTiYkiKqiQHzbpMDhuuQoCaHY13191f6Ei4PmGrI6O\nzgLRLcJsCLAR+EBzW6vb3OQy9YRnbDsKWmk1AEqGchE6ASVmtQW4mhm9FEr1RNRmYrW95NnW\nbzNgGJKm2EsQlSlNSNTKEmWJjhe3mbnrd4QW5yHgtayckHmIpj1TfApIZbcNUoV3mljC57WS\nKEQgEcgc6hq4Hueqsi9DGFVHyQdqHri2AxYkFab9nyPph8VLGu6DeaE5+w/WPLjat/rw+OHj\nkzOpqJGAbai7JJ3i5AbmHl/aadUu46ejo1OEOyVYpihJ4AhwDOgB7EC0kAz4k+LgbJmuNT7r\n3bmBlIAVkGZ1sQJYBWwG3EAvEALuAjwUfkFOizIN81KZhYuk5Ux9bZuB+VqLzWOyG5gagCVg\ngFFCYGQIUVRQ8pi5diWV8EZiAKKAf/6JAGAxsU9uLr93a+VWURaHY8Oq4jJOI7u53G7hGH9y\noZkSoiwaWaNIr7GQdyEVZAgYQmhRpVTGvWbvlvIthBCJSuWW8t11u5fY5RgZkY//BPFx8DHE\nJ+noCeKqWbgWWjlrjb3mTOBMWk6P93uOf7giErTFI+beQeGdo8N77q61qksr6OjcZtx8mSB0\n8SHs18PIyEh1dX7Hg1tIGnijeFJ5hrf6pk/5EwDMLPP362vyGhYS4BtAEnDM1vn8EOie3WoA\nvEqnXAUKSJReCKYCKcFt5O7ymmdXDduA3tkybJmaWJmvqQVYagNFTRR4o3ipgVmqgC9P89Mv\nX345kFKvodY7TM+3e4IpOZgSf3t1SrV1UaYbIcj+nS5qX4+Je7jO2ew2ARiIpt8ZiEwm5y+2\nXmmrfKH9BTM7j9eXgp4Nnj00fiiUClk4S4enY0f1DhNbpOsk5EP/gnRuPR2Dldn6g/nfSRZD\nsaHf9fz+tV9Uiekc2fvKvQ3/8HV9pVDn9ubmy4S+RnhxgSooU7rOZ72nwsYSsqHMqtW2lwIC\n4JtVwctZKghAyFZBAATgCFnjszxU49xQZs2KnbmcVYyUZv2rcHXe4qjXjQN4EmgG3ICnaARN\nPYC3+t5SqaCJZbZW2p9t9YzFRbeJ6fCYd9Y6OWbG4WlkCSGLKCpNgOfbvHvqnJmskvx9nUan\nw6hxnYTgubaSNo+ZJYQlZIXT9M22EqWguaoyuMPoyH45Fh/bP7i/+IXxEv/SxZd+1/O78fg4\nL/HT/PSh8UNv9LxRzK8rpdUqCKUXxMKrJQBArb328YoXVCoI4MJASHO+jo5OEXQvitpSKQRD\nSJ3DWOcwrvVZfdq57SzgBOTZx4uFtpRbPMPX3TRjXlxKi0QAwDTwpir9AwBgAzoFWRiIqmP6\nnUZ2d60TwGRSdBhZoxHbKu0by6z7ByMnAwlekhe1jMcxpNFpanSaamzG3ih/LpAMpNQXY+Ns\nY4mx/H2NhFHlwziMbGeJ+fhkIvsaGp2NA9EB1VX1RnqLX9j7Q+8Px4ZVg5enL48nxiut2ku5\n+V0AZzfQxa5suqxaNYwWGsClo6Mzh24RLjoasNxqUPUSmqUGeAX4MfAboGu+IJrrYemyCxaE\nG3gE8AFkNhmfAHXAEwArUSE/20GQZ0ZcRvbS1MyCayglnfAnKF10g6FMXmWtw7i9yvHXq8o6\nSyyKdajYXgbGMJGc0LTDnEaNX7g3LzOy1lGbP23eLI6r4av5gwQkkCxcqCgvNwMAWAMYboEn\nzeBxmFY1qgsb3b/mRsdS6egsQ3SLsAE4e90HIYAJyBhGUeDTrHaAS84NutnJQB8QBpxAQ+5v\noxL4KiABDKC0gFAEhprZD5XK4NnrdnX2mTCiOoexJ5yaSoklZi5Tc26x3FOREx/EEDzd5P7/\nzk5O8xIBMbCGndU79w3u09RXu1GjUmggL3Kn0dHYY+0ZiecY8Q3OhuIXJsjaa41KwdIcqExH\nT9DJS+A1SsOQmk0AhmPDv+v93VRqimO4dk/7I/WPzJuz8X8/v/7/+vGxqyNhAITgia0NT9+v\nVwrV0Vk0uhAuaIFwPqhWoOk13PcJ4M0rga1ITsZQqAY6F3/keUkCf8xqW+gAvpy3Oshm/avQ\nA4w+1uj6ZddUetYKdBptu2rbFM+wgSG7Z/Mv5Wu1Y+sc6pSAuCAbGYdytQSEMMTCWZJiEkCj\n02RmmZQke4xcSpKvTKcmk0JZlsMwxIsXpnJ6D63xrWl0Nj7e+PjPu36eyTIsMZXsrs3p1ZBP\nrb22K9SlGqy2V1fa1E8q9Mo7dDynv+BcvVezm9RumUxM/uTiT2TIAARZOBc8F0gFvnfX94pb\nz9U+28/+fvvFgdBUlG+qclb7bEUm6+joFOLOEcJLwHkgBriB9UqUBwDgFgYX2AAnkL2yRbXc\nnjLgm+0mUQk0Xk9PvsIcym3eGwU+Ax6dby8/gFq78cXVpaf8iUhaKrUY1pfaTazG+miDywj1\nghpcJvbhOlet3ZiW5ItTqU9HY+k8wcwvZfd6z/RkcuY5Iy2l9/bvVQI1762076rNibo+MBZT\nUjDTMpUp7Yuk3xsMpyQZgMvkanI2NbmaOks6AZRby/929d+eDZ4N82GfxbfKu8rAzLPetqdu\nz1B0KC7OtJ8kICbWNBYb+6cT/9TmadtTt8dusANAalqlgspkEIaUNJKmnWCNb/e/Lc9+9Ypt\nPRYfG4uPVdnmqW/AMGRlnoNUR0dnUdwhQngOODT7fz/wLvAwUAcAWFy2ikRpTJBdWg63RSHI\nNonuMLP5oROawTsBIACwgAlYysIrWeRL11hW4E8hZty/LiO7ozpjPmovjlbbjPdW2g6MzXUt\nNjHM9zpLbQYGAAzMtir73eW2y9PJt/vC6Szx6w7zre65NIZpXhzI87LyEs8Q8mCNOnD03tmq\n6DKlb/SElL6PFHSNd80TK55QtViycJbN5ZuLvt8cPCbP36z+mxP+E4FkwMgazwTPpMQUgLSc\nPhc8F+JDf9HxFyxhaUwjKZP4WobqNgzGhg2RK75p39VDV/k4b/AZLE0WMrsCPRgdnFcIdXR0\nrp87QQhl4Gje4OlZIWwAjgPzdxFSSIjyzy4GH6x1tLrNLANOO2pmHlIi/ulkN8XV/7CyqnwR\nwToScBKw3hjX6LWF9tQBJxcevKNy9G2ptM2o4CwmlnR4LL/PbWdxbCLe6LR2eGbss6hg1Mwj\n9JjYAkFMAGBmmedavYGUOJnwTPP1ETHyZu+bBmJodbcqFuG1YeEs2yq3Afh09FNezJHn4djw\nSGykzvH/s3fegY2VV9p/blGvliVXuY7t8TTPeBrTCzAwEDrDEEJLSAIbAgkpm/Ilu8lu2iZk\nA5vskoTdJCQMhDB0GGBo0/uMp7v3Kku2ZPV2y/eHLFnlSpbLNKPfX9arK90r6fo+9z3vOc8p\nJiSq6C83QPCHaK7O2+RsOCv2ICAHeEAPuGE/YHefd2d/JpugCQiuNWbIkOEC8GkQwsNAYpFW\nJAwoBW4A3gW8CdsIoBJRqwuUr7ePcDxfohJ/YY5+Egc05AuEUhz73J5c+UTTVlsvjBAWAHHV\nArlpJBXrgTXAwXBxhTS1N1unM6ZIX7DDIsvzcX0KeWBnd3BO1l3AECAzyPQU8VRidmXEoycF\nXkb2VkeLjx2biJ8aOrU8d/mNJeMGgcfB6hOYyge5NqAZKh8x28C3DyHIs+CfFzMmjtO2QUdA\n24fq99GxCg03SCT5EsU8heVNi/uMW7lYKSJFlVmVUzyqDBkypMOnQQi7hQajI6I9aapgiKU5\ncqNS1GgrDXK0hzHJ6QknxZwMt7E9MOBakC1Lr+9ShHQnrxNkFWCJSh2SA+vSe2E1UApYABIw\nANsBd7JN43TVllAOCEBKkbly0aAnJg21RFUC5IS8y6UU1uav3dO/J+6FHoYb8jJJSjwByA8O\n6D/oEejecHTwaK2hNlnlX5pkS7PjRlbnK2dpRusriDwQ2XrbcctzVMAOgMRwGQBYS9G+Grd8\nBwEFOleAV5HqJWpvuzeLzLqn6h4yU92UIcNFYeb9p/FAB3AcqAdOAdsAwe7ec8J/cMCJie4j\nTy7aULhgU9H1cvoeYEG4O2CIcb7SAMfXh0vrhn3Mrr7UaauJGhl/wZ0m5MBdwHpgEbAOuHsi\nq6dSoAgoBMTARiCp73OZJqak5MywLyjUaOPmUo2YJCMqqJVoNxVtit5gXeG6WkOtWqSOMzP7\nW9Owl022fCs9b43PWInQ5xKoCJwQiwyLFPRY0qaEIq4xxnyBVjbwe5FwX929X8Oi7WBo3lvv\n8Q/4xX7xHeo7ytUXaDE4Q4YM8cywGSEDvAOYx9uMAroBHpgNOIQCp+NCAKGgqBhYCawE+oE2\ngEvtf8YDb7aPRAfx2u1+CBRzzwfKAS3QCeyNGqeBpRM/2jShp8OwpgDYCnQAjUB88fjafGWX\nIxApKLR4g39vtt5QojHIaI4Hx/OhMnmjUjwvW3LS4gVAE/Q9lfeE0i958CfMJw6ZDll91kj5\nPEEQFEExHEMSZIVmIYXNwNuJuwaUAU5gAhrulXHa4q0yyPIm/bFVItWDcx78oPuDLmeXiBSt\nLphFEmPH0OMO/Pn8cDLrtZFCqMywfWzzd49+M0//59O3k/PWWfOpxfniry4nlJmeEhkyXEBm\nmBDWpaGCAFigA+gA+oCqSe1oSawlTRuwLw2X6kKe73UzMbrrZ3mOR2xwVALUhLtMVANyoB7w\nAFlALZBum4JLhxyYB+QBb8TdZNAk8eAcXetIwOTRK0WDUpo8P+zd0TVSrJQsy5WrRBQAlucP\nm9whFeTBMzzTYGvIlecCOGI68n73+3E743meB//leV/OkeWISBEQEFJBCaA0KkWWKLvtkAQS\nIKQUOSdL9Hr7ts+UPqSTTL4UIUeWc9/s+8KPRoCXI09ta7SmMCClGNh0XEQFQ7zFnF+wY0j5\nynn3s0eZnXcZZhmJSWVmZciQYVxmmBAKuE2mpC0hQ2RcJMDGcMZpCAewR8iKM5EKkjB9tlK3\nu8/ZZPOxPEpV4muK1FEqSAN5wFWxvZaKY3d3pSAHbgCOA0NASJ9YAATISu2KSu0yoA44MScr\npr3DMbP74x5nqM4P4SzTiOHLQdPBuH2oxdT6AlWXM+AJukWKUIBa0O1FBiivMarb7H5HgI1+\ncwVN3VauVYpICcUcHDh4U+lN0/TxNUB2SJLPnHP52VSJPIZm7Fkav/TLkujVB6t7JFSnY+/W\n/2q4K/uLX/xiTo5Ah+cMGTJMkRkmhJNgomUDuQmy1J+eCgJggNVSav/mYk1iv3sgF7h1ggdz\nedICHAE8AAlUAZsBMeAH+oEgkAuEPvtiwBkXSS5UiH0JmtHt6vYyXoqkHIH45V4fwy/JkS/J\nkXuZ80AlQAAKQJGQsJMDlCtFJx9dYDhu9pg9jIRGrlSUJaWNSrGEIgCY3IxSlE44IU0I4FqW\n/+Dl+tYmjz9VE0QOFIPOKgbN8U9Jg2HLOrP4vc7OP/7xjz/4wQ9Icuat62fIcImZYUJoAAYv\n8C6qE0bS6dsXQg0UAflAD+ADGqNSQKVpZ2le5vQAu8J/c0AjEASuASRAtA1myGKsNqrzIgDk\nK6pypITZFyNIfsbfZm+bnz1fKVK6gjE9jHTS0dQYGW0BWoFQvcE6YGdUdaMcWA7IgU1Sat+a\nfBIAx1MkMRa2PWZ2W/1MoTLx7mQSuIETwCAgOjvsafUEkLxdMACeRN9CSDul3uaY1GW1mywc\nGk3C8oo5AL29vf39/UajcToOMkOGDGPMMCGcRNrLhCCEisfTjFYpwmbZmvCUaB6wGzADBFB0\nIU26Lybx3ptAG7A2KpW0DTgB2AEFMB+4CTgGWAAJUEVg4SwtZzbFz8zsATuAFXkrPur5KHp8\nRV60u+ZgWAiLgC1AI+AGdMC88N6NwD2AE6BIgmyw/V0lcvtZ/rzVG+q3XGuonfLH9wFvROaj\ni/QANG+0j6R8CQBIS6WqhSrXGVeoUbbaQ923SytiRuWzvnR0+dBut2eEMMRbfziq29tFsVxP\ntX7Lj67JzJMzTIUZJoRCPW5SoQQSuqSmggc+AfSxpQV5wOw0muVmx37bPLALY+abLcAgcGds\nJcb00g+cAIYBCigAVk6iBVUaCFaDOMJJth3Ax+FBF3AYWBrnaJroWA0glCyzOn81gMOmw66g\nSyuh1+QrFumjP0L016sFViQ5wlEbtmLV1h2dO+qt9QAUIsV1RddNR8VCfVxUdpFevq/fNeQL\nRiaFEjfW8otXbvxMg63h4MBBk8ckpsQLdAs2PbLJbrV3dnZKzf6C75ygTTYAPIEDc93HKz0A\nCIIoKhLIMP4Usv8Lr6174RzBcgDmAvVH+ubsuJ+iMslEGSbJDBNC6fibxDAboIGjE1kp5IBe\nYC7AAE3AMCADFgFFQA/AA0ySBJy4+rZBxFtQO4CWC+MaA6AfeDdqOtsGdAK3AIbp3pFWqHtG\nJNP1bML2Z4DF0Y/n6uYeGjg04BmIrKuVqktDEkWAWJO/Zk3+miDnFJEvJfxqE1vuVdCKrRVb\nA2zAw3g0Es1EuyQmQcBfJldOD/uY0MeROvHF7+n0e28gCGq+bv583fzo5UODwWAwGABg00rX\nJ82vPLutSWKzqkfjHNddd51aPTFr3BnJgZfPzntxVAVDFH3YvuM779/ynzdcwqPKcEUzk4Rw\nJOESPC5lgA6oAo4CVsCZ2iEsjAcIAG9E+bSdBjYB6wEAHyV5VZx7sqC5tuDgRHEDXEIHpURH\nUBbYA2yZjj1GswjoiI1R10SdZokF5QHAC8gij2mCfqD6gfe636u31jMcA2DYN9xqb63SjhW6\niEhCSPbGj0AmIqbEYmoaq/SUiUN2fyhdlqB9WPs/hO61B4iotlDCAiymlJvn3LHqu++//35H\nR4dcLl++fPny5cun7zivYPh9nWSCnV5Z67T872T4lDKThPCTCdqPGYGQqbEsrGEe4KU0UkDN\nwInYyy4HfAxogUASB2oZcB5oAsqAGoASvGImGYzAjPd7DQN7wncDamBdlPoKdpuyAoEURjCT\nQgfcDBwPz5WrY+e4mgQ3O3G0CoYgCbLb2c2E69+dAef21u0Pz3vYIIvMXwUTlCbgk3fBqADO\nRZ8D7KngVV9jBmZD6sCsfZDPLaSK0q0EVavVW7duvTDHeQUjaK1OTs40PkMGADNICN0TmQ6G\n0vqXJxiYyYFrgd3jzQv7hZruMskPgAC84ct0qKHSJqAA0MTOkMTALKGXB4CjQAsQBHTACkAw\nXSIA7Ixa8nQAHwB3hqeGSiGdIC6Mx15O8kaGCwBT7EhN4kbdru4Rf8z0LsgFG2wNUUKoBRIn\nhWkWsVxQ9MA1wP7Qt83sCXi/ZCtp50sOjD4tue9KLAm9vCBWFXN/rIubFPbP0c+7VAeU4cpn\nxuRapV/DAGA1sA6QAE3AJ8BuoC38VDHwWeBGYF3y/rfjdumLI+563QEcAgaBdVFJN1rg+oR4\nZojdQH24xsAKvB9qh5tAf0LiTwDoCP89J35zAMi76HdCZcDV4aRZBbAcEEjUTKwXTBgUnHZP\n6By4cJQB9wHrADHzro9rH4sSEzkKyTdXXcIjmxms+GxN1wM1fFRqzOB15df+x/WX8JAyXOnM\nmBmhFqDSK58ggJCN1s6oxhTNQF+4kk8cnnK5k/hxS4DSNAoWjQnpMBHOAmdj5zRaQNDo0g10\nxo5wQINQkotg+mtksBrwxK4UqsIB4YtMBVCR+mYiV5YrMCiPHiSEZoSXz10dEWrKIf1FHzm7\nKfjCAG8NUMsKJf+ynshLHf3OkBYLn7310LIC5YEeIshZ5+Ws+/66jP1chqkwY4QwfXhgJ7Aw\noT1TI1AdWxRYC5wWCrgtB2YD5qj5liDjRuqir+OdQINQyqhg6wzBrBBBk8zoVhWLgVqgDfAC\nKqAICE58djtdpNqpUWmckzWnwdYQGTHIDIv0i6I2oYA8oD/2dYXTeoRTRwpylvihWeKHLvWB\nXBhaGsynzpgYls3TK9ZsmCUSJ+v7Mf0QBLHq4eV4OJM9lGF6mBlCGAROTKSa3gecEho3xwoh\nL/SeZDjMuAkwA8OAJ8nEUZWwHpaa/igh9AEDQDDJO8StUJqBk4AdkMQ+pUtYdCSACgBAB/AP\nwAWQwCxgZWzlSWjS2QGMAByQBdQAJRP5LFPlzoo7D5sON9maGI4pVZeuLVgrIuMqLNcB70RN\nebOTFw7OcHiOJybW0nIcOJYnx6vJe+vtepmf04spgII7+NLfT23dulCStBlkhgyXNTPgxA0C\nr088dV6wm25c/uRJoRz96NBWTlg4m4Qik8ZwY6Y0ieyrHdibcsXLA3QALYAXEAO9scdJAzwg\nBkqTTLxMwMfhA+OAFsAHhGqwRoDDQG/sYQ8AA8A1SXJ5Lgg0QYdKBpNvoga2Ap2AC9ACxVOc\n2rI8e8R0pN5WH+SCxcri9YXrQ72fLl8C7PD/HG0neLdRTTKcXi2pvLZi3GnZYIfN0jbMk4Su\nVFtQqotT0O7mobZGM1ieI4miSn3VXGHXpEGTQ+Jn0FCqugAAIABJREFUaWrsCzeqpW+903DX\nXQvSOXCe5zOdNDJcVswAITw7uQIygIy93ItiS/2agDqhVwlGIEuBc7EjNFAOEMDB9GoTEd67\nC9g9XljVD3yY/NnQa71AHeACNiRs0JQgzz3h2eHbyYsQjl9MIUwPOjzBnQbeaH/j7PBovf+g\nZ7DV3vrI/Eek1EQtGi4eIz/edW6+npOJALAUNehnAh+0LPxMdQqJqX+jYZAf/emHTpvMzcOL\nrq+KbN/RaOlsGDW3Izm+r8lic/mvWi7gZXP67KCYirvt4F3u8ZOVzh7tsfQ5CfAEQRjLdRU1\nk28AmSHDNHL55BdMmokW0YdQA2uj/MxCzZWiZwBtAi8CkkzUFgOK2JFVAAVUAPcBW5J0e4++\nYomAY8A/gKPTWgbQHLvKOAS8g8Q2BwDgAJpSluJNroPxlYHZaz4zfCZ6xOa31ZkF74QuC3hP\ncKDPwcliwsW2IOvuEiwYBYCRuv6ICo6OeIPmtrF/n5bGeIvX3rZhXqg+L6GcHQAhuGU0Bz5s\nHepzEOAB8Dzf0zbceLJ/nNdkyHBRmAFCODmv6kpgNnAPcD1wI3APUBq7QbLafMFxKbAFWAIU\nA9XALUA10Ae8BfwN+Ch5JDYSyAoCAcAOtE7q46TAHH7/buBtoD+JFVnWeBNrWYJL3Mxh0DOY\n6PAy6L3QnUwmD9dq9eUpEsftf0oq3vbDAjnM9obRUhyO4+mE80IjpvuG3PGjwIJ5OSwXv7VM\nkSq8xPPwu+L/CwY6k8p2hgwXkxkQGi1Lw/A6kRNAD1AOzEtyfc9OYniWLTQIQAIsiXpoAt4L\nRyCThYwE1XHaaQJGgFMpVytnAbIk09YIif2nZg5qscBnFxxMB2ZvF7P9HNdvpVaXSb6+CvFR\nxGmALNNKBwT8zUX7uhMHR18y7EF+vHbSjtGTkCQJN8Mp6ZhDtXiCc4QCrUVGzYGjPTk8ImHV\nTrvv/vtS9e5obLYIhmwz64UZLgdmwIywOLwaN1HMwGHg/SQzpCVC3mN0rNqlILXwXEz6hIxG\n4wgt/lUm6X0RSpSdNfEmxlcMhYrCKNsaAKAJer5u/iTeyv+jj90b/+J/5ljwjTbfP3/knPsL\nrnly0ftUECpJnlJCeYLRg5qTA3Jn0rsrXZ6KcsdsTzKcvmxszdsrjb8jPGfzFGQLzDsBfPaO\n+YoybZcn0OH026XUgw8spulUFxPnsFDUnUdGBTNcDlA//vGPL+b+nE7nNDnou4FhoAXYPbVm\nvE7AENUeIYIEKAcYIAiQgAwoAa4W2jIRDjg05aU+DVA68cZSk2M2oAYkQC5gDTeXzwFWAGWA\nFegF6oEWIDuJ/c2VDUmQ5ZryAfdAyL9GLVbfWn5rqbp0ou/DNQ157nk1+oaBt3Jc4znxvasw\n3Vd86cZy6ePv+bRSJktKeYLZu7uK/rdOck8Nfa1wMynRXAP9833OYg0npQFQnmDZaXPOF8Za\nf1SWZ79+uFvM8xKaHPIEP+keeeD2eblZ8U6wEYz56kU1+bUL86sr9ePqmcPsctnjs8aCwKw5\nabXzZDneH2BFKbU2w4xh+mQiXQh+3DXuaaWvr6+wcIqFz2Zg57Q6LFcAeYAJkALlSRxe0ocF\nXp1sIms0YuBG4M0JzsOkaSepRkMBc4FuwA5IgdnAEoAGfMA/YkO4YmDLeObgVzDOgDPABbIk\nWSQxmWtu4M8nvF9+O25QdA0p/d2j5Gz9dBxgDFzLsPumF9g2WyhThb6mXPHW5yBNut7B27ye\nXx2wtw1DJlLX5isfXY7Ycguex8HzpuY+R7ZKsmGOQfpyPVs3QGTLRJ+roean2YBamO6WobZz\n8TesFbV5RaXJ1hpGGXH5n3r13K6T/UGWK89Xf+PO+UtnT3vvsAyXF9MhExPjihNCK/DqBY7R\nrRB0gk6PAeC99OaC9HibkUBl2sufUoBJ8oaTk8Ya4CrgLaHZ9mog428sTODpvd5vfRI3KL6T\nFj1+P732wjgS+Jngzla+z0nOy6HXTdsueHfAveZP7Jnwr0+T8r/dIbp7MrHiEAEfc/STtqB/\n7BRVaqVL15entgLgeP5rvzt4omUstiwRUX/+53Xl+Zm+jDOZiy+EV1yo4eCFX6k6KpQamo62\nhYoT0oyIskDqRgSGJN3eBZEJ7VcMLAdWp/0m0ZwHPk4Sc05MI3QBHsAF2GfwOmI6ULcsIEYr\nD6O+h3yQ2Z0XapcSWnRLtfgry6ZRBQH4nzwwpoIAGM77T2/DP/lov1hKL1pdotUrCJKgaDLX\nqFm4smRcQ5xOk+tEy1C+3f+NXd3//XrLv73fMb/d9vahpAlBGTJMjisua/QirJlxwGlgBUAA\nHHAKOAf4ABWwGJid/IWnJiIDEuA64IUkMV4RsBpoSrDTFKQqSWkgB9Qk6UQ4LizQnuSp6FiW\nCdgbGwdWAGvH0/gZC1WeJbotJ/immfcSAEBBcj8NBrAcgn8xJJdyeZVjOZvFHfCzSo1EpU26\n8heCPdgTN8I7/MwZM72sQHD7dFBqpLVrSydkCNc/7DaO+J95pUkcYAFUAFe1j3ygleOOyc9N\nM2RI5IoTQnEaVQfZgG1qSZtnAS9wNVAX5S/jBPYAdHKDlQn1yF4A9AJVwJkE+VQANwEaQAw0\nhxswCZIFzANUSYSQ6e7+q89nq6qaxiU9HVAW/tsN7Ez4OdzAR8Dt4abHnzpkf3qYzP4V7+Yg\n4UktEdzDcSaO0PHisrNEcRo9mBgOSVJCzjeY/7GjcdgdKNLKvnDfotwk+ZyCuB3+0we6/L7R\ncymnUDN3WWGKDBdCLpA/PDjkmnq4akK2qCW5qkdOWUIqGOGaVxv5P/HEeG6ocew62r394zZf\nkM3VKX708DKp+Iq79GW4gFxxZ0MFcFJonAYkgAqoAXKB56e8o1bAKTQBPQfogAHADaiAfEAB\nkAAJqNLLkaHCi38Rz5e4jkJu4AhwHSAH5gJtgA8ghBRxGVAKeIV6EoHj8OSTR7///Wms/yOB\nzVHh9K4kNyUM0J52ncmMQ0qLPqfmuhzuBwORX8z3c9b/7C5VxzJBgQnBHu5xb/0H3+8iSJJc\nkqfYcT+hG5u3ffBe07+/18TyPIC6IfcHP/3k/766srwiIQGH47nOEUIjIbLl0cOnD3b6fWOB\nTXOfXaGRlCbPOqE3V/g/aB28rdq2vJCX0ooGi/6j9m6em5wQmiyesy3mIEEsrNQX6ieg30UG\nBZGQa0p5gp5zg4qFE0hq++kfj+xqMnuCHIAGi7v+Xz/8y/c36jSXr39ehovMFSeEy4DB2ICh\nEVgMGGLr4uXJrWHSR3CFbAjYnjBIAqWADogPKCVQBmwCXot1PksMqHYCzcDxKC9vwVkCB3BA\nM6BIdP0+dswaCHBWa7CgYJw4WNpwwFvA7UDoDQU7IIYQsCP5FJFVHvjusbj7Fn4o6Cx/WtXy\nNUIl4IXEtQ671vwpdCLwLMce7XdW/Jd66LsgCQA8z//3rjY2Kq/Ny3C//vOJZ34e04028Ozx\nrh/tGiZRZPNr5hrkr9xNlmoBeN0Bvzd+ea+neSiFEIofXnrS7feUj07r/bkK25pi3s9yHE9O\nZErH8/yHO1toT5AmQAOvnjVlFWvv35xifSEeOkeJvpjFcp4g/Cpx+nJqs3v3NltCKhjC7A58\n73cHn/3h1ekfRoaZzRWXLAPgJuBWYB5QC9wB3AjkJbjDLLtgexf02+SA9gTfbUE6AVd6/qiH\nY5WGEzIN2Au8DxwR1KTduy0A9u8XbGc/aVzA0fDfgv7j4z418yGrNjNnBNSCt7j9Tx4QfInn\nC2/E3Q7xdp//qUOhv4dMriFffDyg3RszYnn53LfebXhgS9U37qi65/Pz/yQmXNc8hyALwGET\nSBtmhAxDI1iHPBEVHD0emhSJqQQV5IEe4CzQKbgYcbauX+QNRkKwCwxKU5v1XMcEVvrZm6vi\nRhxL8pUFE8gafeODNmcg/t92OA2L8AyfHq5EIQSQC6wGlgGCtVm+qIv1xSQdT2oeeC29d0uM\nOiZOHAOAgIFkCINBAuDkyZEXXuhyuxkAHMcHg1P3u4m0SCxL8v1rU6YUfQogSFCJtkQAwAoZ\nfgLgGgXujZi3GkN/yGmSTLgNksUO/Py1c8eLRuUhSBEvLcndoaDZU6EfSyiHK2UJfGeCAbfQ\nSwLAG8B7wCHgA2B74g3ZYI89bmRBrnL38b4Uu45D/9215rvmcuF1U3ttfvDJTeLktZICcAL/\nmBlDmwzRXHGh0XR4c1rL7QFQADepwgBS6DY5zao+aoreNGvX6o8dG+Y47N07tG/fUFaWeNYs\n5Ze+VDb+K6EDbHGft9Xu3z/gtPrYLIl9VX7TbO1sgAI+A9QBvWHZlgIFwOIkVm2fIuiN5cHX\n6hPHiSStawmVhLfGn7RE2FZbYVDMlYvOxk5ilpNjd7EeP3NUHx8A312RdefJAWpZoaFAIFs1\ndYTT5xZI0Qr6GdeIT6mNLK0ddnqG/7Fb0dQj0qm5m1Z4FpTtBW6M2UtCmbKEIj0Or9fP+IOs\nVhkTJXbZ/V1NZr+fyc5VFVdkh9JqJFLa+Kfbuh/p9Z8Z5POV2UsLy8smlod14/qybUd6PMEY\nOcwTClBn+NQy84RwCIi/CZ0yk24/JJ3CUuVUex5VViq//OXyV17pHR4OUBQxd656yxZjei+N\nT39tGfG90Dw66Ai4u5x/v6virnm6eYAEWDnF45yRyLdvtdM/Trx3om+fI7i9+OElvh98HH7E\nAwRAiJ8YyzL9102zv/1uQ1dg9N6oFuQ3Hxv75m1OP5ega1Y5TV1lBECSpEorc47ECG1JSqcb\nWkz6hW7YRoY9ESEccfV//le6QdvoqsRbB2U/uNd60wo2ep1CJKVZX8z9nNUbNNt81/zzDp5H\ncY7yn7fWhJxiOhoGO8PTYvuQp7vJsurG2RRFApApxLM3lmOjsHXcuOTmqW+crX+z3hwMd8wo\nUEn+5cuf1mSuDELMPCGcUA3DtBPtF1MCUMmr8QSJTv5MZwIqA/wpCkUWL85avDjL45FKpRqS\nnLwja5Yk/jzZ1btrni7jL5MK6X9/xvfVHdEj1NIC8eeFWzRIvrc2+G4ze6B3TAW/VEuvHGuK\na7ymfFtV9pG/nhwY8VXmKGoeXkaMzcyQny1XkoQrtjVSpZehwqmVS9aXnT3SYx108jxIkiiq\n1IcyZYJvNfr/fQ/bYCGLNJKvLhd/dXkoPceQr3Y7BFaXo+eRz+2kIioY4lcvqa5fxoqoscEF\nS411+zujF2DOW1wnumzZMnFVtlxEEv/10qmffWVlQZa8MzY4zDDcmYPdtWtLBb+uifKtR1bM\neb9xzzmzj+HyVJJH712o0crHf1mGTw0zTwgnkJydEtmk4qsMUAvogCxAB3RPRAgJwSqIlMwH\nLEBn6m3k8quAdybytvHoZfRNpdp3OseKQ4Z9wyzPUsSM7VA4dST/tIxgOO9P98DiIeQi0YO1\nsqc3p9heufeLzO6O4ItnCblI9IVaKqE8gC7SrP7hBsHXkgTx+NaaX7x0OjIiY7h/+rdrIw8J\nkqhZWQyAYzky3BaKea/Fc/tLob+5lmHvE+/x7oDke2sBlM7JMfXYfZ6YYCxBElrD2P/X6XZZ\nXNwiyGLH4YHbVo953GQZFAuvKjp2uNsfYD0BlqGpY/2OBTnKW2YbqPAyXd3hbmJObuKHctim\nc4Hjxs3VN26eya3EMkyFmSeEuYAoZRF6mkz6m2GjKu6LgdXAkfRW+/gJqiANVALVgDllALYR\n0ALqqfXowGKDfGe3PRJcUolVFMEAxBWbb3UxED92lfixq3irN7oiMAX0hjJ6QzqLuALcsro0\nVyd//ePWIYt7Vr7qgS0LBCv2yKjmiP5fH4x71v/kAcl314AgCAIrNlWcPthls4xWwpAkUVmT\nL1dGJQHx8kQXwKYeGxBj9qYvUN9wx3yO4wHsPN4brOu9pWpMBQFoWH4kYX0UAJ/Q+/fS8scX\nTzX2241Z8ofvWqBSZ2oQZxQzQAj9AA9EzksaKAbapvy2yeKNKoBKWTgfZ+MyD6gGPgSm3SCR\nAQ4C1wFbgXrAChBAW8KRM8B+YKqWVCQBvZQeCDfAqzUA+CtAArOAlVHf/xVA8LlTvl/u521e\nsjxL/uwtZLK+Cjwf+Ntp5u0m3hOkN5SKH7+KkE0mCShNFZw6V83JuSqhqxHXYWNPmQitlF5Z\nFNeYgm2KT1XlR3y8yUXkqwAQJLFoTanH5bdZ3ARB6HKU0lg3gEpjVmNPvBBSSboQh2KqZfmq\nUq2USsjToYW+V2mSxKKLz8Cg6/5f7XaHajC6Rt44a/rpXTXrV5eM97oMVwyXy6k2KazAJ+FF\nQS2wAQhdBaqmQwgF55QEcBMgAnYkcT0lohzIIlBAwQUQQgCdwF8AOVAFrAcoYA7wltCW01BN\n6GEIADRBXJWnWF8Q0nsOaAF8wA1Tf/+Lg+9b7/ufPhKafLMWt7P294p9D9ErihK39D7yduBP\nowZ7zM7W4OsNyj0PxfUtuvS4A+5Xzjcd7WNUkurPLVDXxARU3d/eOXja5DOqRVav7tF3tNvu\npJaMmYVSFTomts09oZIQuTF3cnKlRK4UTrC8/9qqdw53x6WFLixP1VZptlE7u0igo6dIRKs0\nMqc9Zl5Yc9kozeO/PeCOqkRkWO4nr53NCOFM4soVwgDwdlSx3QjwDvBZQA4UAbopZ80ICqEs\n3Jb2TmAHkFgOJU6ySDkLOD7lVr2CBAE7cAxwA2uSByqdwKzY+4OJrkeWfG3hLGegWSUmqfgi\nrB7AAVwJnXE4zv/bIzEfnOM9972mbv163IbsaVNEBUdHjvYFtp0WP7QYlwfssT7v4++yx/sY\ngjCXqJ9Zawz+9sBXKvW3fHd9aAP3cyfPlGp8q0dThQfcwcpH38nf98WIlosfW87s6zpSojle\nomYJLOlxbty6AOkZx3j9zKv7OyQiyhelEOtq8q9dnMqFjSBwy4qSrvODcWdQlkExa35uyxnT\nYI+d43iZQjTvqqJkAnzxMbnii3rdAXagz55fqLkkx5Nh2rlyhbApoeScAc4CVwEAbgE+mdok\nTFAkohfbbwS2J8RIBSYWAAAFkJei+D0JE0rYqQeWAVlJihc9QBsgAmQAAeQAwfGybOLIpYh2\nrSTZfMh5RQghc6gXCStPfJ8jcUu2bkBg8Hg/Lg8h5Hrs7hu3hUoPaZ5f2WHPdQa+fmfVf3ba\nys/0z68pANDZPOSLahbBKkRd9y4wHO+nV42epaKbZz9z06y3ikd/uHfn6Q9zwX9P7wB+/uKp\nj+rGbgRJkvjqrXPv2ViRulDd4/T31JsTVTA7TwWgamF+1cL89PZ/UeGEVittrsDleKwZJsWV\nm+lgEhqM5IOIgc2TbcUXTfT3EzI1jUAA18fO/zQpi+oE8uLGwwfE+0ul5AOgCViYfIMg4AKu\nBRYB/AR//eMpy+SvjF4TZIlG4BZHyKaEMCSk1/MgDNOVkzxVgi+diyvALx/yzjO5AzSx+4PW\n0IizML6O3luk9p8dE/hTTx2MqGCID13+w0Ld/nin3/+zvZ7b/u798lvM7o4huy9aBQFwHN9j\ndocUjuP4V/d1/NPT++/9+a6fv3hqMCr5s7tliE/4/r2ecdzOOI7vbhk6ubfjxO72tvODTHCq\nJbYTRZVwhtAEMTe5U2uGK44rd0YomIAQNzgPYIGjU2jJpAPmAD5ALzTb0wBbgXbACWiBMsAB\n9AJeQATkxlpuVgPnJ9gsngdWAAuBIeBUGp0FB4ABQAwsAjoBJ8AnfHYOOAr0TtwohwNUgMA8\nCZgNXBlVWaRRQ2QpeFtMkq1gS1t6dTGRq+QHozzDxJTo1mnIv+fNbvbcIJElo2pykSS1ZHRL\nk9P7+LvMSROZLXPds6B/cR7LcOosWWm1gWsTiPwXjPhPFapGwi56ROKb8zxdOzZHPNtkgTL+\nCnD6WO+KlTHtJHm7z7Xs2cgeA3+ua/+PaxL33hX+rp569ewreztCf7cPOA6eNz3/vY1ZKgkA\nj0tA83weJnWTwvNHe4bCa5kOm9c66FqyvpycYBumqfC92xf84KVTfNRy6GeXJ4v9ZLgiuXKF\nsBpoSLiaJ9p21AA0sD9hfDHQn2RaGY1H6D2jEYV9Nb3A9tieEgSwAFgRfqgA1gAfjbfHOHYB\nS4BKYDjtFrsB4DywBDACFmBPwgbjtshIBg+sAY4CocsZBSiAqpRz0MsO+c773Fc/B5c/tEpK\nVhsUr342cTMiSyZ/eav3gde4rhEAhEYqfWoztXiqwTD/z/b6frY31OqdWpgn//sWcrbe1D3S\n0zrscwdkKklJld5QoAbA99odlb9lJPTwNWX+PIVkX5dyX2fffTUuu2/Y5FxUKWBr3p0lBVA5\nfzT2oFVL4qpqFD0Oye1jNgiyBJ8EAHJFvEuq/9cH43RX/4sDuDf+/6IkVwnAMuJ7dV9H9Piw\nw//S7rav3DwXgEojtQ8nlPrwvM8blCXsN4Td6hmKzehx2X2DvSP5JRcvCLFxVfH/GmS/fOHU\nkCeokdAP3zB746pMpsyM4soVQj1QG9U1F8BcQNBCrAo4F7uYZwSWAhzQCAyEI36NQq/1ArsA\nBsgF5iX0uIjmjYSaKh44A+QBpeGRFH2LktED9AO3xfaFH5cgcBggptv8uh/YCFQDLkB2hRqK\n0ksKNNbvBf9xjm0epq+riCyYCWy5plhV/xh72sR7GWpxPqGeau5G8PUG379+EnnInjZ57t7u\neHVr05nRGzKnzXvuSM/8q4oMBWr33duDMpqTigzvt3qLNQN3z/XM0lE+hpXSfh9jWVmkK1Rz\nUaub5wqU9fmKCqnojhtGf/SKuxc4t512qkcFRmT3z9lQFu02vWx9mXhfWyBq4kjzWLEh3sks\neCR+bTvb7luTo9xvdoV9cCAWkXesLQXQ1GVLsBdFW/g4jbOyezuscbevJEVIk9el9LYKpGe7\nRny4uEo0r9Lwtx9vuqi7zHARuXKFEMBSoBToBTigMPkiHA3cApwA+gEKKAnPYEhgLjA3vJk8\nVlZD8EALAKADaAVuTaKF5sTK4jC9UUI4uaxRFjgddZzpwwONgHHiSTrJcAN+QHJF5MWkgiJF\nn6tJS8alo3ad00Lw1XgbbvbsoOmTduhjAsuNp/qdNq/YF1TZ/bD7ASiah2f9fH/Lv6z3FatD\nK5oOEkUfP+j77ofM3i4vx50sUr+7xvjZJYVfumehKNyogaLIJQ/UDp81OTusUpVUd+0sn5fx\nugORuVfJPTXfruv/jdPrE5EAJCz/+PLiylmjc83+Dlt3y5DPE5TcOz+X57I/6Yw+yAcq9MZ5\nue8d7XH7mCqj5rHb5lYWanwBNmAVaEVp0I6uWciU4soF+S1nYgLsxvLsFHHRkcQZJCCeVEFn\nhgzJuKKFEIA+SSegOKRpJM4sBdxAU/INhoAGocr0ILAr+auixS9J4fb4WIEcQDrBJcYQeqAU\nOJakm/yEIICzAAWogdKU8+MMAvBDAtf0rL+dcT66lItKx2D8bHejZWFDTLU7wfK5bza1/b81\noYcSmWiAIrofWey7f4FEJppfqd88SyBYShDQ1+Tpa/L6njo48vk3pP0Ot0Y6uGVOwa83i1US\nADc/uXnFKdOp/Z2cXFR7fVVOOL+mr8PafGpUrnxqSdejy8AT2btGY54+o1pUlf31Jcav3zGf\n43hfkP39W/Xf/sMRb4D5xsrSQrWkzzF2spEENswfu0k1ztJJZHR7vdnr8oskdGG5rqQy6b8w\nz/NBf2JqDKHPj88DGhlyW4fdUokoO08lmVCTpgwZrnwhnF5WAY4k+SAhhJq04VjKfhfRBc6T\ndhhRA77JTig5YA4wGJ7aTgU+atKsBm6ePmfX6cHhcCiVSpK8THOhqSUFzIfxVg+6gz2Kdtv5\n322ODlqKLB4yQQBk/Y5QU0KCgMPq6WsfXbfze4MtZwb6Om0yOZ1lUBaW6+JaLJn/Uqf89gej\n7zziy/q/kwM+tuSvd4RGDIvyNsw1dDZauprMPa0WQ4HaOCu7pyU+INm1pTokhL5CVfu3VlTk\nqxmGaz9vHjY57S4fb3GB43keUpK4d37eK/Xm9hEvAIWYurFCXxsrdYYCtaFAzfM8MV5XQMG6\nBbGEUkQ1UQoy3E+fPXKgbdgTZA1y8eYK/dabqkP1GBkypElGCKMRATcDg4AdCAKJzcT7ge1A\nDrAEEAEOQClUVh/BGLtKl05/KALIB/pjB6sB02SF0Az8bTqmg3E4gH1AKhfpi4bX6/2f3z5N\neQZFFNFt9ecVVzz22GNisXDyxSVE8u1VwW1nuN7400Bichn/fLr3i4siI0y2jBNRZGydgD9H\nCQAEeB7OkfjYgMfh8zgwbHJZB101q0qiJYZ/5ljcxupX6oN/uFkkEwFgWa5uT3skn9Nh9TqG\nvb6EkgY2R/Gjry+716DyVOkKq/T6fNWxj9vcTj8ACUkuyddUZimePtqtEFEEQX1pcaEzwHqD\nrF4uFolJsVBWTkQFD583P/NO/bDdl5Ml++aWBQvKxqa29mEPn7DkGPQzXc1DJVV6AL4A++Vf\n7GodGo3Hmt2BbWf6pWLqgc8toujL9H4ow2VI5lxJJBeoAmYLTXc8gA1oAl4C/ga8DjyfJAWm\nALgGuAExjcUFzKUSCPmmVod/GjmwASiegiuNaWoqmOKevX9SzYqnGZ7nt/3PLx5ayH796txH\n1+f85BZjETnw9NNPX+rjEoDIkol/skHwKcNH7bq9XZGHHE0OXRuftOLYUq3WKcb9yq1mV2ej\nhWPHymbo3njHANLH+DtGk5A7GyxxVQ2WAYdIEr8IZ/UyR4JM37L8pZsqKxbkmXsdIRWMoJbS\n15ZlRwRYJaZyFGKSgEhEOWze3rZhU/dI0B9/Gr++r+MbfzjU0mu3Ov2N3SMP/2b/rlNjd4F+\nr4DBEw+0nx+0DroA/OKvJ9pjFxE5Hns7rIk3ChkypCAjhMmggWsTHLQjRDesT/xf1QE3hXtQ\nWAFzWMZ0ya1norEC64CHgPuA+8I19ekshV4M6WyGAAAgAElEQVQIUl93L70Q9nS03rVArJWN\nLliKKOLOWh3l6mOYC2FoN1WIIQ+rFAe18R7lRJAlmJiKz/4HFgzeNpsLZ4Xwi/LmfH+Dy56W\n01Bno/nIR62usBiwJfF3YJyUVlSO5iH3dwikZWYl9Ls/0DMCoMvhV6glAIYHBbLDjGqJb+xT\njJ4bPI8Tu9tbzpgaTvQd/rDVOhhz4/jbN87Hvgf/ixdPRR4okjZ54EM1FQcazVzClHHIE0ic\nR3Y1DR35oPngu01nj3QHfJfjuZHhEpIRwhTkAluBzRM0hREBIbPHIeAV4BXgDeAFoBkAcA0w\nD5ACVPIv3w4MAyQgB/qBj4A3gZ1T+igXhNzL4fxxDjSrpfFpOwuN8v7+fsHtLy2EUdP16FIm\nS2C12GuMycXlRFTffTV994yW/RGnTMG/1EXP81Lj8wTPHe0JyYHye2vG3lZKg0DwoVpCRHEs\n33JmgGEE7mbyirMsAcbuZwCM+IJvNluO9tkBkATR0zJ8an/niEUgO5Th+Z3tEVklABAkET2r\nY4Js/Yk+NvwpRlyBaKvSEE5v0BseVGfJyCTriMEAE2Q5T5BLXGg0yCWq2G/4xO6O9vpBjzvo\n9zND/c5DO5sT56YZPs1k1ghTQwP1E+zkxwFy4CxwNKptqR/YC2iBHGB1OIXVAewQqrvggXeA\nB4FmYPcUP8CUKQdyhNx55MDaS3NEsWSpZIlOA3IxVViYyv35krG6eISGrH1E1hF10DxAQDzk\n9cQa6hEsb9x2NvLQt78btwpY7hEMxwuth3ndAa/LL1dJ5LfN8Tx/p+mV86bryv25CpLjC2Zl\nZwXYUwc6XUIhRJIkNHq5giZ/ubeD5RE95TLwfOu5pDYU9UNun4RWlGglXsbvDSo10oCfscVK\nZtDPuEZ8mmw5AJVcRBBIrDuMzvWhxVRAQLQItU4uosginazbGhMaJQncu2kWHfWFWC1uR6yX\nEMfxDXX9NbEGOhk+zWSEMDXWiTt3s8ALQuMc0AEYokw+1cA9QC/wfoLM+IF+4PBkDnkcQteY\nNEOaxcACQA8YgeOAFWABGWAEFgLT1hwgyHB/39V26PxgkOWWVhnu31SpGC8DnmGYQ4cOdXV1\n6ZV0XoLHyAgrp6jLr7rDxzj+dhrVusEtc2Tddu3R3tDP4TOqpH1OMhg/21M0DRNREybax9A0\nycRGUOXtttmvNJz/13WC4b6An5GrJAD8m8q75VQoYMiRRG+H1Wp2e9zCi8dZuaqupiE5Sd46\nO+eNJnMkc3N9qS43eZ6nJlv+n7evjzzsbbO2nTMJpn1GBimSMBoUPeYYpSzUKySisd/OUKiO\n5MdGkMrFhWU6AN+4q+abfzzCEzxNEizLK8TUlpXF16wqjd64T8iOzmFN0cs6w6eOjBCmJkUD\n3knQDpwDeCAXWAVkA3XAySRWqKZJVQ2OS5oSqANEQDfQHe4tFZnBuIEh4BywZFrM1Xge3/+/\nowfOj067z3fajjSYn/3WWlFyH85AIPDkk092d4/eo3ALszbPG2uI0+fEtfd9c+oHNu14v7qD\nfOEM+fxtHE22f2eVrGNE1uMIZMskw+6S3x5zLhqNwFOugGjYG8hVBHUxtxq8zSs9Y3bNjVkt\n9ucqGu5fIBHTNE15EroFndzXaShQ55dmddSb45bNkqkggNwCdf2JXgCL81VlWdIWqyfIQiuh\n1tXkDZviU8PkKrGL5UdYDioJy/GhprtWi6v1zIDgqUZRpM8TrNvTwbJclkH+X4+ueuCXu13h\n8KlcSv/mKyuit69amD806PK7x9J55ErJsqtHvUZXzMv9v2+tee6dxv5hb4FWdv/mygVV8V7Y\nPDdpq+EMnxYyQpia6a1GikRBB4B3gSXA8eQbGybeMnAa8UTJcCBsLhoNAxwBZBPsjyHAqbah\niAqGaOwZ+ehE3w1JfY35jz/cGVFBAG+etvXYuc/ftJLxe8SGiqLipSCmfzrI8zDZPFqFWNCi\nc/yXm92B506SQO6rDQN3zwPgLdN6y7SknzX+7TQnohi1mPQxxf9bp9vbBR4cTVpuqIycAp5S\nrfyjduaGiri3ZRViViH2OZLeM1n6HZZ+gT5TydDlKt1RgpolFS0v0ABwBdghoRzi3S1Db9SP\n1teW56uf+fpqjULc1TgkeOISJCFTiBrr+kLhYJfdR3WMvPXjaz88bWrqHqkq0ly/1ChNaH28\n6rrKvvbhwV4HRZEFpVpDbBfAuSW6X311VYpPZCjUDA/G63eWIVkeXIZPIxkhTI0eyJ3gGmGa\neIGjyZ9VAwVAyQRbBk4jaU5Gm6cuhC1C7QCbe+0CQhj08m0f85bG65TB2dfnv1pna7WMHmdd\np508PHTjjTdeoKXBX/3j9JsHOkMhPbmUfubx1bOL0ymGGYNtGnWKyXulgdFKrOtKWDFNu4P5\nL52Tt9kASPpdOe+06PaMFlGQDJf7dpO9Nt9TqXNX6XLebeW67GYxKQpyMtGFylEa4fg/fNBc\nm6Ncnq+O0zylmHp9f/ftFfH+NUGGK9JIOY63eIJOu/e/Xz//g/tq/V6BLhOqLFlekbrlTOi/\nafTtWZY7f6Tnlo2zkHLFrrA8u7B8Qna7Y+QVazobzT7PWM4OSZNzllyWS8gZLhEZIUwNAWwC\nDgKdAAfoAB8wXasLydqw5QMbAHva7SYuIZOwEY9HrxFIkTckFBgAPF//Oj/SBYAASrMlj23M\n/dl7/Rbn6AXu+PHjdXV1Dz/8cG1tbYrdpWNoEsc/dre/vr8z8tDjY770m727f3MzlV4z9xBk\n2ALNurbYcv3oxI5Ri3seXiwe8mjqBgpePKs+HX/LJbZ52++awxNEV4/j8M2z2ntH+hoGZ2cr\n7qg2qCY1MU2GREafNrkIhr2hNMsd4Diep2K/JR58x5ATCUJ4VYFmtXHsnoDn0XCiTyqXeN3x\nZUVFs7It/QKeEi67n+eR/m/i9AQ7TM5staRQn5axEUEQy66paDtjspicPA9dtrxqccHF7OKU\n4fInI4TjIgeuBTiABUQADxwCzl2w3a0AaoB+YMek4qLy6dDpCqAtvb0L+FtOlKVVer1aOhQV\n3JNJ6PU1ow2POI5ramqyWq05alG5rTNawyQ0oRSTlqi34jhu27ZtixYtEpQ6k8m0ffv25uZm\niqJqamruvPNOjUaTuFkif/0g3oGWYfk3D3TesbYs3Q8JkAUq0e1zgq83mLbG+6cP3D1PUzeg\nPSJgUSTtdarrTMO1eVk3V90AADg96Hz5vPnv5we/XFs4QUFPSr5WZg2y1VF3JExCKmfLsFcp\nFrhc0LF3AwQBU/eISislCCJ6VVIkpvT5qsEeASHk+XTvTjie//kLJ98/1styPIBlsw0/emBJ\ndhpdQWianL24YHpbsWSYSWSEME3IcKonAawCVgHNgA0IAN2AQE3VZFf4QsbcBya7Ojg5FYwc\nKg3MBZYCCuB01AYSQJpgEUcBSya1uxjUcvEvH17+78/XhTq75mbJvnv3Qre170ibTalUvvba\na729o90zKnOkX92QK6HHrpgOX3wVmsvlMpvNubnxpZ8ul+upp54aGRnNfjpy5IjJZPrOd75D\n0+P/C7i8AgmZdS1DExJCALI/3crnKPy58atT3iI1CAT0CpHNG1dWz6hF9sV5dJRILMxV9dh9\nB3vtI3ZflsC8eTIovv3BwA/WRE/KaILosvuKNRICBIDOEe9rDebrK9INTjpHfCIRxQNskAUB\nnieCAXbfjsYsvUADZ6lSFDJH5Tje3Gt32X1iKZ1XpBXHZg5bRnyPPLVvICrb81iT5Sfb6p5+\ndOUkPnIKWJajUjZMzjDzyAjhpImsjbHAMMAAGsAM+AE1IAbUQCNwLKqacFyMQC4QnO5s1XGJ\niC4DZAE0sBzQAq2AD8gBFgMKwAF0AZ2AB9ABtRPskpiw1/A8YG5J1ov/7+r+YU+Q5dRi5g+/\nfyY6FyZCi9n3+inrZ5dmA2A5/kCby+UXSAiUyQTK1Y8dOxZRwRBdXV3Nzc1z547f30otFw8n\nZKMsq55wLxFCI1U8c5P43aa4wjiJxQMe1lWFvrKs0qePRMZ5iuz5p6WJQcOqbMXBXruV46be\nmpbgkPNus6c8K3EvhSrJJ+22flfA5gs4/OzVZbraiThZB4MsALlSPDDs2dVp67H7ZDS5ME+1\nolTLBsZ+NYIg5i8rAsAE2bq9He5w24rORkvNqhJt9phw/uyFkwMJNQ9HG80OT0AupoM+RioX\ntZucZ9qtUjG1rNqgT+pKk5Qzh7qsg65RFwKNdMmGcjK96DfLcDzP06LLr2InQ3pkhHDqUFH9\nleKmCDVAJdAFHExuFpoN+AESMADl4YZ/1BTMRafIWWB2uKlvXDBJDSwAFkxxBx6P5/XXXz9x\n4oTf7y8vL9+yZUtJSQlJEkaDAsDvfvc7QRUMcb7fO+Ri3j07Utfj8TMCKqhQKFQqgev14KBA\nxtPg4GA6Qvj47fN+/NcT0SNimvrMVem45QlQUJrV2RQd0IX+o3YAYkegf00xoxQbdrSKh9z+\nQrXp9mqfUeCziCmCIJCnlAAgg5xud4d3Vpa7PC5MzQvleMYP8jw3eJNAupMnyJ4zu3kCC3MV\nYko1O1uRLHI54AoQ4EMHI/A+rsCO5qFzltG15PYRry3IfGlT5WC3g+N4dZY0O1/VXj9oGnY7\nXcHsqCkgy3CNJ/pWXFcZeugLsMeaLYnvL6HIxhN97iEPgHdahw72jIRu6iiK/PGDi6+tnUBG\nzNlDPdHFIS6779gn7VddOyv1qzobzR0N4QMjUFadW1p9qdwQM0yejBBeaGRANWCPjTRGIIFr\nASuwF2gD2gAxsBooBtov9pGOMoFU+0nA8/yzzz7b0NAQetjc3Pz000//8Ic/zM7OBsAwTOQp\n4YPzsj/Z0Rdgk8aN3W73kSNHVqxYETeeGCwFkJOT1qzu+qXGviHPn99rDC1NZSnFzzyxhp5s\n9Kx0jsH/WsNgVRYnokgfk/tWc847zQDk7SMAHIvyHIvGWndR7mCib0HXiG+VUaMQUwA4Eanb\n063435MtP1rvmhddQhdxTiASBqMQ+hQ9dt9zpwe8zGgkQ0yRX6gtKEkywep3+g712L+y1EiR\nQu8PGDXSPKVYKaFMrsCJfseeduu3jFmz5uUB6GyyhLoeioHsBAsFrzvg9wYlMhEAr58RrM2/\na25uSAUbLO6D3WMzfpblfvTcicUVep0qXduH4cH4M9/j9HEcn2JSaB92j6kgAB4dDYNZeXKN\nViACnOFyJiOEF4daoDNhjY0G1gAksCtq/hcA9gKFl66IcGJVAROlr68vTuo8Hs/+/ftvvfVW\nAIFAgEtZ/pxCAiM0NTUlCuHSpUvfe+89u33sJygqKpo9O938iYc2Vz20ucobYKQieoopKgRB\nVGwoy7vur4xKQtu8BMsDIKv0mn9dpzk1YHi7VTzs8ReoTLdXuyt1RMK3YfUFZWJqbclYWJTy\nBgmOn/XLAwP3zB/aWMrFKMq4xyowcdzeMBhRQQABlnvprKlSJ9tQqtOFTcBdAdbiCagkdLvN\n0+/y//5E79WlugqdTJygrKuLNJEE1FVGzTPHe9sG7HpNDstwnQ0Ck7xoIhk0WSpJQba8P7bR\nhIQi5xhG23Ec7ItfTeA4fuex3nuuHmdKFyHR6Q2Ay+5XZyUNsZ4/1ps4WH+kb+X1lWnuNMNl\nQkYILw5i4E6gHhgCaEANqIF8QAY0JkRB2Yn7uk0j02AWkwLBEKXJNGpfKZfL9Xq9xTLO9TE1\ngvmHKpXqiSeeePnll1taWiiKWrBgwV133ZVOpkw0MqG0ydSwDGfqGfE6/VKlJK9IE1pGotcU\nK9/6nO9Hu7jTg0ShSvzwUsnXV/j/fnbWT/eHXiXtdahPDLT82/qARpqzp8tyYyUfnpfopKLl\nBTE9knxGtdjisS8rGF5fwk24OXv8dyXWyoY88ZUPYoqoyVOFVJDn8X7r8IFeW2iGFnp9v9O/\n7ezAknz1nXNiJtk8EF2GoZeLrynLNmhkXnegr8Oa2CMiGoVaKpbS3WaX1eEvzVN95+6F3/7j\nESZs2C2iqe/ftQDhSnmnQCN79FgEWmQkRcj2VKlJNaEMJjiGAwj4BVpHZbjMyQjhRYMGaoTG\nk1UTXnyygNpw96gLhWA0MjpuuWzZsnfffXcqu6iurg79MTw8vHfvXqvVmpubu379+oKCgiee\neILjOIIgJlpKODl8rkDXt97XvdmkGPL4C1VN98wv++EGuVIMgL52ljJ2/SnwL59EPyRYrvxX\nBwdvrix84Vz+Kw2+fCUR5Bp/vSlxLx3fWEE7A4xChInUNSbDZHKsKtK2Wb2DUR5sWildkTUa\n7jvSb9/XM1bhGi0dPpbLK9Ja+u1seOKeeEDVOQqpnzn6UY9gqDOCREoXVOu/9J/7zndaAZAk\ncefasue/t+GNA53mEV95vmrLunKNXLT3ncZQRw6DQmR2x/8rzSudQHmPNls2MhQz45QqRKmT\nZWgRHWATbhqmtb4zw8Uh85tdciacfHhhqAbWXYTdGI3G6urqxsbGyIhMJluzZrRPkMPh8HrT\narmXjBUrVixbtgxAe3v7b37zm2Bw9Dr1ySeffP/73zcYDCQ5zZnxI64ATRFKWXwnWwCD392Z\n9391AMBD2uswPnmwl+WqfnV9kOObeuwOd6CqSBNKbuRHfFxCjR3t8Bf+/TwAyhVQtFh9sX2a\nomFU4un6ODqp6KZKPc/jg47hPZ2jglceteh1zpzURWFRibaqNt9u9XgTNClCoV7RckbYjBvA\nJx1WP8vdtLr0quVFjzy9/3zX6AFwHL99T7tWKX7izphcrbJqQ9v5QQAbS3T1Znf0m0rF1MZF\nBdEb25z+lj57nk5enCPgr1a7tuzErnbHyOjpJ1eKl14db2gXR/WSgjMHuuIG5y7PeNZceWSE\n8JKTB1SFuxVeQi7SmUAQxMMPP/zKK68cO3aMYRitVrtlyxa9Xg/g8OHDL774ot+f1Ax6XG78\nzC233vKZ0N8vvvhiRAUBuN3u7du3P/roo1M8/mjONVpOf21H7fEBZZA9W5ZlfPbWohXG6A2U\nL4aNF8LzCuXbzWd7XT+dm9VtdgEQgbiXx+fL9eLP1xJKCZ/gmo0owbCtMsY/O2EEU0kFIAhs\nKstuHfb0Of1FGumKorGVY5dQPBBAbZ5yrkpy7nBPChUEoNFIB53xH9Mb5Drt3pMm5xDDPnLT\nnHXLihyeQEQFI7y8q/2hzTHLusVVerGU7u+0yRTiW+fnvXXeFPrCNErxfz26Sh6enAUZ7qEn\n97SGPVfL8lS/e3x1YiX+ko3lADwuvzxJEmwc2TnKokp9T8uoeR4BFFfrNVlp+d1kuKzICOHl\nwAbACPQAPGAEui9Fyug5wAVcdxH2RNN0Z2dnSKVsNtuf//xngiCKioqef/75qbSV7xQt/Y8P\nmedOfPjgdZU3LM3v64s3amlvn85vddDm7b/thZtaRnM0NOctgQ1/8TY9JgunsfBWL+2Iv+JL\nBlz/tpzrM7vWttluP2PJcQa6tbITTNP8Xx8kjCq+UfgmgCfgWFzgM6qlfU5f4VSM4CfiCUdg\n06xshuXnGuTRLzSqpBZ3sFovz1GIHX7mvMXNg//S4sIilRSANfl8EYAuV5mdpxzsjZn7njO7\n3mi2eAIsAKVMFDKuswg1SnT6AhzPx7XqzSvW5hVrAawAvhHkznVas9XSIoMiOqp5/3/s6ory\n3e4wOb/5+0N//e4GwYNMUwVDVMzPrZif6/MESJIQSwWiAhmuCDJCeJlQAUTiMGWAEmgD/EB2\nGpbfZJJGThOlc1pMtMflvffei24fz7Lstm3bbr311qmooJ3MdxA5AExWzy9fOk1ToCgqLgFV\nKp0eH5YQR3Y0rW+JZCryACEOssMPvmHc/YXQEKGTcRopaY+5oHvUkj6NZHPD8BO7RvOh9K4g\nF8rSSEhRCeH7wiLxrk7NiX7NiX4QGLqmvOeRxfy0rnGes7iGPcH1JfEF+lU6gTKAm6v0K43q\nwnA1xWY/0+sIhFRwXLTZioCfjc6ItnqZ7Q2DwfCaossb/OkLJ2cXaUtyVYnZK2KKIgmC5zHY\nM9LTNWLzBCpLtCWVejKcqioWkYsr48v4BqyeroTuE829dpc3KBjQngRS+bSFpjNcEjJOQpch\nImAFcC/wEHBTGtsvBKarhjfeVPNC0NbWFjfi8XiGhoam8p5+IuaS/fKezvnz58dtU1MjmKw0\nSaij0anzo7IkORtz1yJ5Ir6KY4gEgAeODkQPkjwA8EJCSM7Wy3a0kJ1hxeWh/6jd8H5r3GYE\nj5I/nDD+9Qwl5AY3LrkKcfOQoE2gABKaLIyqKVRJqDmGdMvmLH32jnpzdIZNm80TjCqJ+f/s\nnWdgXFe1ttc+dc70Jo16lyxL7nKviZ3m9E4SCISQwA0BAgTIBe4XQgsXQmgJFxICBEgI6b06\nxXZsx122bEu2ZHWNymh6n9P292M00pQzanacEOb5kVinzZnRaL9n7b3WuwgEvCDvaXNQJGos\nT6/kWb+gAAD27eh5Z2vX6LA/6A7/862Tv/vbATxp3s3eLEUanuDHJ08tx0dMLiL8mEMCcABp\n+SMEAAXAA1AA8wGaAJYAtAHE28J5AVyJh+5sA0TmNePMJN18FmAsPNu67kVhjk/fWh7tLJwY\niSoqKhTPoCjKaDROKZNBlGL2NuAI3nDbDW63u7d3LJehoaHh8ssvP6WbT8VoU5iiTPOoVH9/\nfSQmxn79AYpJEkcRvJTnDBsjojmjMwMAIBWF01bXtIzc7YGMNTnD3iHH5olKNdobrfnJ+1yP\nFwAs73WFSgz+1aWj51fjiQYLUywN5qmZW5tKwoKkno1J2Axi04AvfcIzIkgAgACtLTOsKTXp\nGNIdEeQADwC/vm3Vf/1mR9fQ2MLe/ErTXdcvcjuCnpFAkY4FAI4iV5caWkeDL7138rJNWUv3\nDNp4uJbyIRAIipWMT3P8Z5ITwo8/qwDezdjSCBAG4JL+tpMDoPjQ+ZSSsK0AKAcwAhwAOJCx\n9zR0k8gKxuFrnhKeb5sDMAc0645q3l4cfKspAAD5+flNTU3t7e3btm1LO6mysnL+/PmSJEmS\n9Oqrr2arPJNRyje5zKZFCG3YsKG/v1+tVi9YsCCb0M6aJV9ZHvvBVpR6P+yG8pSDSIL76TnU\nkqLIrS+SvhgA6Gh0fbkpxJCaDHmjL6+XWkaksZgSI7MaFWjlVoVohgzzHe7wSVcEAGos3IYD\nw1yPFyNAGMigoD/u1B930ifd9q8tT5wxLa2KqyDL0XxUnLzC7zRSYlABwPoK4/mJdoMWNQ2C\n9Mu/7N/Z6yk0qW+/tMFqVJXlaxvKTQDQdmI0rWa/IU/75lHHJEK4sMpMUYSYasi3bn4hcUZK\naHL8W5ATwo8/8bXDQwA+AB3AAoB4nVzy82wE4ACAHYAAKAZYmrBqeyP1UnkACxLDYhOADyB5\nko0AWPLhvQ3h+Tbh+TFPmZbK6HsLg069SInAGjS33norQuiGG25oaGh49tlnHQ7H+FkdHR0d\nHR1TXlxK/SafW0/cfffd4fBYWZjD4fjCF75wemsHOQMX+dFZ5P97b2KTUaX+3YWZR9JXNVAb\nKsT3e0GUydWlny3W93T5NH9Psdwjyg2q312INLTw9DHp2ChRrKOvnOuv/I1iLHeiVP/XQ2OL\nrO/3e7ol+RYtbQ2mRJm27b2uK+snqbjIRiwy43pw1YDfsrVn8Ib5eOaFjFVGboFNt7YkfRa0\ngCSG3eFhd7i503n3jUsaEuuXYaW5X3JS2Tbp2Hs+u+SHfzswPge7oMryv7cun+SUHP9pkPfc\nc8+ZfL1AIKDXz/iP8z8eM0ADwBKARqXlQBHgRYB+gBhAFMAB0AKAAeoBTACDiQCxFGAjQPKq\nfiWAPtG5qQDgLAAFQ87ThfDng9LuAQA4VBV5fJM3oJYlEmQCBEFoa2tzOBwIofnz52/cuLGn\npydZC6eDRe6zyAMMIeUXlnz18oZdr/8jFJpY9BocHDQajeXl5ZNcYRLwaCjymWej//Ou8Pxx\nolg33mKXW1dBnVUBUZGwqOlrGzWPX40KFArUAACpaXJuHgDIewawI2S+pQkHBal5GGSMWJK5\ncaFmy+eQmgaSIOfbqE1V5LJipGH43+yGaPq4HzSqfj/H4uNIMREY9ZCo1hGudKfPOgYb8qKl\n02q4mMwRR1DHUPS0+9aSQb7qlx+Ydg0ASQQb8qY+IYPGfE2mMRtDEtsS5RMnBnzXnT1mPhDx\n80Fv+qy+G6E1qSWDaVQV6i9ZVV5dpF9en3/bJQ2fOy9ngfax5szLRC4i/ATQmdG2SQY4AOAD\n2AhQDRAEYFIlcJxagDM1KKjHMvTeXZSewud0Ordu3bp161a9Xm+1WmdR54AA0zhiFdpXFVvq\n82teCKTPCbe1ta1bt24Wdy3ttYfWPDKWjtHtCW3v4X5+LvOtNfG91IYKakNFljPlCUtrGY/e\n+tKjHSOHi3Qkxit/wd9032bDfefJgwGiRA9UugzIgwHvfTui1aaYyioZVJYtXW0Wzq2mO63c\ny/OtEZpYf9KztXZiHtulVfjl8iaFdlRTcmDI3zoa+lTjFI9EJY8eEkwc7Qqbd/THq0TM73UP\nXT13Fq+IlGZuneGJ5dJhdzgUFTUqCgDKasyDPe7kE/p80Ws3T53qbDWoLlpRNovby/GfQE4I\nPwEMZ9neCbAEwAigHKacYajzamI/3Y4BO41ZGzT6/X6//5TaX3zwwQeLFi3K3C5J0+8KmULo\nvL+nJSVGvvs2/eXlSJ0l8z4mRn/2Pv/wAewMkw15qp9uoi6qCz64945IpHvhmLq052uO/eTd\nB568Hlm46PffEZ5rxd4oUWdh71pHLS+OfO01/uUTJC9pADQAkpo+8a1V3w2Ekw3Ht9WkrOZu\nqzZe1uKgkw6IlOojNbPpV3hpXd6WLvc73a5NlVmbTSJJznvtJEr9WGhXBGE8nbqOfn80EJMa\n8iYKzzNtPglAF9Va20ZDXd6IXs2oWQIWvMMAACAASURBVEqWsM8dFnipoank2OEhQpRkjEdF\nefXG6nKlxKVTx+mL6jUMk/GYkuOTR04IPwFks2LBAF0f6rLfjKDWlqnuPSf6g3dNfmI0uxae\nOiRJqlSqaDRlqrCublb1kYKk5PYiy0cdZBYnrch3tvAPjjXXlY6MhK78l+bNz771zsnuspTH\nkQM29d5/NM97uk18LW4qhKXdkfAVTwBHY1FGgpTIcsRkWCh98cSKG+e9n9RmCKfKTUe++r5z\nKr6+a1AdiAFAqM7Se/syeVZ9Ys0c/alGm5gkS5nLlDKJRsxcQaozZ6zUMKUKyhj3eKNvdrps\nGrrOoqYSa4pxFaQYUkzkEBXp2SI9u6bU+G6321ZlDvmjR/eMedYgBOXVlsq5+QSBUPZVyVAg\n1nXMEQnGOA1TXp+nn0l8/Le32v/02vG4Y6pFp3rwa6srZtKUGAD4qDDQ6ZFkuajCqJlekWWO\nj5CcEH4CmOQvXMGe4yOEvaucviZv/VPis91TugTMnqKiohtvvPGvf/3reIV+fX39WWedNYtL\nye6IUgUKQkmVc3K/L/o/70o7eoGj6Yvq+If2pxwryvzvdncq9ZZyvHVSfO1EQmUSA3pESCT1\nTPxXfdJdNpXdyc5a05wvLpMP2GtKDDj/VF2+qCR9SZOasCh3ucOvLbX9vze6k7cfvrR28qpy\nDEAgVGXibluq7BWHlXpsbaw0Lzmr8ujeCec2jKH/pEtrUDFG1ctvdQT9sZgs55cYrt1Uy9Bj\n0ZvbETq8syf+71Ag5hwOzl9RYi2aWHbCGF7e3fPSzr6oIM2vMt98/pw845hcvb1/4I8vT3QK\ncwWiN/1i25ZfXEhPOzRsPzxo7xpb4Bw46TLlaRatrZjmuTk+EnJC+AmgECBbM9uss1sfESeJ\nKvLcu4rxW9Sbb46EQqJaTSIEodBpCxAXLFhgsVgsFktpaenBgwfD4XBlZeXixYtnlzJK2LRA\nEyCkyhhFEBVjWY7YEwlt+KvcOxarxZRqt8V99vwVCqkcxRFRsbABY5wegbFUMDX7n5LxBa3O\nV+fnxWMpkkC3X9ZQRxD+JUUfdt1DICoO+KM7q4z/c0n1Vc2OQj9vNzBPL7EVVxjXTHri8TbH\n3LmTWcxLkrJBkmc4FMkofh8e8HXt6i1jKTBxAMAH+V893vzfNzXF97bt7089HB9vHlybJITf\neWj3jmNjT2Odg/73mgcf/97GuPvoAy+2pr1WTJBe2d1zxdqqSd/fGH53ZFwFx+5/NNTX7iyr\ny3Wu//iSm/7+BFCVJdvTmmTb9jEhBAAIofPPL/jVrxbef//CX/96UVHRbHI6MsFAzFu07POf\nH3M4s9lsmzdvvuqqq5YsWXIqhROqe1M7HyHE/XYzJC7I/+3QuApmvTFneOPnFnOphYPWoFB9\nrvJvJ/NeA/Nti7b2LrQHEGAAIGV8yy77dQI+u9xk4WgdQy6oMKkB+T2n0rhjugJq0zJall5k\n0xnWVzz9pcW3fq7x+5fUHCrWqemUwcS4awAl6Zrlne6l/7d/ttWJCqe5RkOmpIZHDEnUMtSx\nHg8AYIz5WLqmCrwkJR4mPjg2Mq6CcXwh/h9bxqp0vEqm4bun6iE8Tl+HwpH27nQD8RwfK3IR\n4ScAAuAigBYAO0AEAAOoAIoBFgDMZpXow8QCMOEyqtVSGMPQUIwgiMkb0ye7U2ZDNM+/7Ys3\nUxmJ+KcI+81VRLU5+t9v4ZEgKtRxD19KrZlIPlQseE+Hl4oXFf5oa88vnYERPQMAla7Id0vM\nhi8sCT56SNqXbA6OAVCozsKMBGnf2NqkaFKZdvatAlgFIJPE/vl5Or0KrSr9ppZ2JNokNXe5\nm7vc68qMm2sUwg4ZT6dT4QyeFVaW6Ck0VphxTqXlkWZ7WJBqUhfhip84Wvhcm29JIaYJ3VGH\n9tiojOBQRIBsSUZKHBoJNBUbfK5I5hdAktKrFs0c1dXvbawwSaKc8W3BAGjckvSV3QqNrw93\njrkXaViKF9KnKBoyjFizEYsqTG9I4mlxA87xYZETwk8GFMCSj09eTHYWAnQkr1y6XKU//OEN\nkiS1t7e73e5XX31VsQ1TiDBpZM/kWlhrCJ12FYxDXzaHvmyO4i4iww9TAYSIPM3a+y9YsbOv\n782TFEDJ9UvI1aUAoH7mU5HPPCO835cY0pGsovq+uAQA5tz1jpCnBllmHRM5KYQkLzvs+Ptt\nTZ1FWsdgev/C9/u8K4oN5gwj6ddOOkO8yFLEcJA/t8pSnTVtZLpNmqikCNuooq6amy9Iso6l\nAEDGEBJEV1goi4rWoQDXMxEuIwAyUdPa74u+0+NZWaKvt2Rdzux0h19tdy4s1Gd2tFDrWG+I\nhwyLUauRAwCKJpPzbuIvznL0+F1HBQVZ4hLx5afPqX3whaPJuwiErlpXme0+07DYtH53OG2j\nOqPlU46PFTkhzHEmUQNcCXAQwAHAAdRarWPJnPFuukVFRQ8++GDmaV6yWMS0AU+WYtPX29XV\n1VVVNa2FnNMF/al5sV/swMkrWCSCtKQPNKYv9Jqy6qRoEvtjiKM0W28+8Mg+w3PHGXc0WqQd\n3VzDW9UIMGZJdlihpRHCuPTtzpc2V2fuAgC7P2rmaCTJhCBLKor0RZ8fCexOanv0wYC3yqTC\nGJQMxmY5gVxpnFDWPl/k4YN2ANAUqM9Pnar1VxglNQ0AEUF++KBdwrgxT0EFY6LMUkRQkNrd\n4cZ8LcpQu6JyU83CgiMHBz2p7ZycEeHiOWMV/Q1NxUc+6MeJJyeE0LyVpeNHLqgy7zqWXnQ0\nXmX46U3Vx/s9bx+0x8+mSeKnX1g2/T4VFfV5fR3OlBAQwYKkV8/xMSQnhDnOMFqA9dn2KbaP\nx0C4UAlBCAZpMiEUZfzt+59ZunjBTVeuN2rZEXe40KJmZ1VCMH2IGrP6xesjX35VPuEEAOqs\nCnFbT/pBMsZRESUtaMnHnZEvvxI/0l6ojdy+1H9rSjSPZJRqG5YSqxX6eCHLapvREwObDpME\n4eNL/tJs2G3/0acbIGn1LhAT79nWJctQZeIuqrXma2bQP4hxhSk/H66cLAjWMmMf+J9XFTUM\nh0o9Y9G/oGftXxlzNeNoosKo6vRE7P7YsowsIpYiAEBLk5trrD0ZJjIAwHI0AliwpPh9d1hO\ntOwIi/KCFWVc4tUtBbqlG6v6O5zhEK/RqSrq81RJU7JXr698YUf3cJJOL66xXrRy4hnlxzct\n/drl81p7PVqOnl9pZuiZzTSsvaj+0I6egCcCACoNs2htOfUhfw9znCLojLnrxrHb7cXFygVY\nOXIEAoFvf/vbcmra5DBZ6yBrC6SOfGky09EAYe2mlgMAQSCMAWNMk8Snzq6+7dK5s7ZXxq4w\nACBLSpsC7A6L7/dCSCBqLeSyYohnZ9gDjJ6V20aDq/+UHlpRhOalG3BMlE+4iFI9ubEqtPbP\ncqd7fH9UTXf8+nzBwnG9Pu1xp8SStoND3K4ByMILC/Ie3VQejaWvReUF+T890UZqWcD4kW8s\n37CsJBoW3uh0bU94laVNfepZ8valZTSJVFMVBhAhHiEkqWkkY9oV4bP3XcKAf79vYDAQAwBa\nwhs6PSWeaOWcPNX5NZJmQopeP+l8v89LIvRfTSXF2acN49Fh5naEwFygq19cFPRF7YMBTk1X\nVpvJmUyM+8P8397saO50USS6cHnppavLcx7cHx/OvEzkIsIcHwJiFIQwqIyAZvYordPpapZd\ntOXgYL7UpcIBAXEustxJlCHAWnky91EMaJQcS8KUE5NpgiQ/9naHjqM/O0NvSV6Qd7xyfOCv\nB0taHIsH/PSSIu4PF5NNRXKPN/L5F8TtPeNHUmdVOu7d2D8SlCSZosnyPK0hc4JRlEMXPjbx\no0EFqd2IVGGBeKW9GEH+Kx2ZM4FpxCji2YX58zHyyHAy6dPNCwnff7NHJcjgiQCAttNT9ulF\nvSec51aZEcAHA15eSq/K8Mek3+/rb8zXXjJVZr+cCBwxgfg8NREV5Czd2BGgG+YV/OvYyIA/\nqlLTznUVhTYNbdWkiXZYkAFAwvjhgwMrSwyVRq6xxCBFBRmjPXZfhzsMGFebNStL9IyK4jMM\nVzEG11Bgn6dz5Xm15vwJpwKBl4SYyGmYSQrt4+jVzFevaFTcFQ0L0YjAaRhWlRse/1PIRYQ5\nTitCGLe/jp3tAACUClWdjQoVDM+yseWA/e5H96dtRCDnS51WuZfEKXntTqJci100jsYI3QhR\nGyCUR3OzGi4sGzAYDGvWrKmsTEl5iMViNE2nzcfanaE7frfL7hnLd5g7HLr3lU61mdPt+2Lo\nsiekA0NpSufaVNl729LxHyu2dJkfyuxvNSMUklai+Zrub62KVBhDvLh/KHDlLz4oGw3LBPJy\n1KE5FutIqGE4REuyTJOOS+r8i2zuCqO1WD9vRdnz73a82zwky7IowwlXevddAqFNleaVxQZu\nRrN/GPArJ/DFddmiKAyYlzBDKsuRhOG+Xd3+1Ij2H9/Z0L9/8LEjg62jEzdZZ9E8+I01nUdG\nvM4wgMJYZSs1NCwtAYBYVDxx0D48GKBJhEhizsICUc0c63GzNNlUZ9VPr4N8JCL+/onmw70e\nAqF6q+bSleUNS4qm1NQcp51cRJjj3xt8/GXsTlhmi1Hc/jqwOmRWzuzI5NE3T9CSvLrbV+Dn\neyyq/WUGCQEGws/VbyhTHW89AgAEQWCMZQxDVD0GEqZKdvSG5ZaWljl2NvCdNk9YTZebmNuX\nd65VP/X004ODgxRFNTU1rVq8KRqQAYHerPrxiy12z0TE1lag+cvKotu398cePiAdTFdBANAf\nSGk377xsTt4Rh7SrP/24GYAy35Pr3KpIlQkANCp6Q6UZXTUX/fEAKWNLSNh0cHj8jK67VvsX\nFQAAA+D3RN567fiD27okjMvdUVNEhOJ019k1pYazKyYKA9xRwcIxUz8cIyA2VoUlzFHKHzwC\nxGbvX0EiWF9ufrvLFU1klJTbtFXFhuPtzmQVBIB2V+hgj3fD2gpZxkc+6HU70oXcORjAGBCC\nvz/b8mLLsCssqChiebHhzQ7n+30eScYAwLFUXYlBlOT5lZZbL5qjZpUHPVnGt/3q/RPD/sRL\nh0+6I9/n6KrGyUwAcnwyyAlhjtMHH5pQwXGGW2B6QijLONThevjFk4WJErpes+quy2oDGvqu\n6xedv/Rij8fj8/kKCgoikUhXd98df+uNj3STP7GzOFQ7yH7h9bhLtSAddURue6VlZWhwnh8A\n6JC0b/eenpODZy293B9yb3vu1XZxVdolD5TqAEA+7lS8PhkRks2mozFJu/3m0CVPiK+3T+dd\nZyHlBjBF+FKtTZ2bKov/0UKOd7rHIBhV0VJDXAXH0RJoXr7mrCfbNrc6BZK446q6LutEhidN\noLPKU8y7zSp6mlNEWENxs80yBYDVJYZ8jn3m+ND6MnO1RV1ZoncNBY51ujKP3Hd4aMPCQoJA\nGr0qUwglSZZEadfRkb/sHnvyiIry+JponEhMPNzpAoBjPZ6nt3U+8LU1i6sVHJe2Hh4aV8E4\nraPBnUcGFYVw1Bs92DrsdkcbC3VFRXpr4Yfi+p3jjJETwhynj5hC4wgcC0x3vBwOfvOdvnEV\nBIByd/QrOwbq3/18dZEeAEwmk8lkAgCVStVkMjVu87d0ubNeLYEOj5x9KD0S2nCQc6uFC/fq\njEFSJGF/nT9c5fzg+JZgJAh0+v0K8eAmi0CEa8zJZtOq404heoy5YV5CCKdbnJfOWEcGDIAG\nr2+MFuvS9kaLdJqOibcvrC8fXFGEJIxTQ7E1Mby51QkAtCT/5NXOh1cX76s0CCxVZeKK9ezM\nZkRT72C2J45RX6j577yqeC1g2B05urefFBU+4oAv8oO/HSjP1168tBR1utN0WqWmKZp8dMvU\nrZvjSDK+48Fd7/7yYiojYD3er2D+0juaXhEIAA+90vb3tzrkxJ005mtu21jbtGaW3S5zfBzI\nCWGO04faktlQB2mm26xV2tM/byi9cm5ZfyC/SLlF513XLfryb3f4kgyxSISkjIBmZbevciR9\niYjjiRveHSsDoCRY2abuf/jQy4udBIAK+yIopZ/tsl4/YinhmWNJ2xLyxlH9Ny9OPtj2VGu4\neQhoMlFQODHPOaRnHl1ZdKxAywnSBW3ui46NqiYqu1P0EhPotfMqdudrDGG+ssO72JpRb4ex\nKvWzUr90Ys5LJ6LFup6vrQhXT8x2FvRPPJ2YQ8J/b+kBgGO/uSBWovNGZ9iMPiIiGWPNDKxh\nJiG14B0AoMbMqSgimlSBx5BITxHP7B8AgH++3fG1FeW6VOWubrTZnaHjA1O43CUjiPKuYyPr\nFxSkbbco9YiwGtPNB945aH/0zZRY/5gj9Oi2rtJyY37JjNsg5/iYkBPCHKcPkkFlq3HvzqQt\nLCpdOc2zkYomMnImWQwQXwXKoKpQ99Tdm17fOzDoDJn0bFNtHoHgtt/uEJJG0rxw4ItbSDLj\nsjIBRKq7SOlBL9dIRBi5RDraRa2QEn8a+VHpy70BHEtLXESEkaNumMd+c5Xt1hcdF9TyVs60\nc8D6djfX6wUEICQbaiMA8Kuob11R69Iwlx4ZvWnPkDpdBsb0Mlxtci6wPcgRLUYWAEBLQ77m\nSkdgmSRjkgCAEC/JGJfvGiAzfKgBQGUPVN23q/U358sqCgB4UVYdVmhXWXfP1r7bl8Liwiwf\nrTKvD3rNKnqFZpLhXjH8nW5MbGCp6xptz7WN+nkRADQMecWc/D5/FAAKdWy1iTs+GlxWpAcA\nhEBn4qrm2kz5mr++2T7ThL+OAV+mEK6ZV/CHl9tiSeZqaoq84Kx0f4ZtLQqfZ/OI3zUanL4Q\nSpI82O2WJSgoNbAz8ZzL8SGRE8IcpxNUsQ5YAx5uASGMdAWofC1w0zVpJFeWIIoEMUUhyEUF\nkwzVejXzqdSh6qc3L/vlUy0ObwQAls+xfumnbZRSQUKElTWR1FlBDAURdTcTXNAf2ejdf7gg\nv9dM1qu4//nljULezxXudl0Z98BFAGA57DC/1zuxA6X8b5y35lpcGmZVt+/L72crEESSlvGs\nKnljyN9SmLJ095yBOefB/V0XVv/TGxoM8ABQ6o19vVBb7wgDxmkyzzjDmg5XYL6NdoaJp1t7\nAGem7dLeaNV9Hxz/+TmRUn2Al3TMtMq9L6i2TiVoivtnMIlaZ9HcuUo9FIoBhgIt2+uL7Ozz\nnlNlPrvcnPwtwBgiQV5v5gBg0Jm+cAgABEJydnlc2ZCy7BcO8j5XiCGJu29YfN+zLd4gDwBm\nDfPd6xZVlKZrmz+s8PwhyRDIKOvMRut++0j/WAjb1TpitmkXrs5Nq37E5IQwx+kFocKFqHDh\nbM40ceoHLwx/+ZVxD0mkY9VPXjOji6ybX7B2XsGIJ6xR0RpXOHDHFsXDSIUCR7SouGnDC0ca\nelgAuAJ8AoUxAqr2sKDUJw8l7MHoqxv5h9NLPjLpNakA4NzjCouaKE+DnWHBwDo214ivdbx8\njYKvaXcw+mibw6kdix76jew9m6vO7fFW2YPnnEi/ZsUDeyUNyw4GkCTPpVDIpHJd2+BbVizT\npPaYo+QfR2RXuNPKuffaDyP8Zpczj6M/t6BIn5pOmWnVnSFos13+nBSaRGV6FQAIMn7i2HCp\nQbWxwpx5mMBLfk/ElKepVEpU+dFNS3gRv7a3f/+JdFd0tYpqrDABgCzjLQftew4NkhFhjllt\nUTMURfzpS6v8CBMEqi7UKzYgbCgz7mlLL2lVkUS10k1mMmr3jatgHPdIcOCkq6Tm49Yx7T+L\nnBDm+BhB39qk21QVu3e73O8n15Syd65GM/EAi4MQFJjVAAC0FlQUZJRjA4AqDEASkNIAD6/6\nTQfAuMsJpkUEAMK2bmTmsDvd64u+pmHsUr88j3+0GTJWvNJ0osAfAwCrUosfzaufJiqMsd0D\n0tdf/96GMkHJIcVFE+MqGCegIlkJNw5nxkOYdkdpb0ws0lK8HK4y2m9cwNvG0oV8y4u99dYH\n9vYPEwAA1uFAiVXTMxz8y6HBS+vyKk0qAOj1Rl/tcF7XWGCZYtbuwy2wowm0vNBAZS/jkyUZ\nAC5eWfbke12OJDO2uTbtskqL3sRVF+k/9/OtaWddubYSAARRvv13O7WCfE6VibNoJIxdEcHC\n0V1HhlaeW8tkL6W/YVPNK3v6R1O9365bXWYpSE/IUqSrVcEXojcnhB81uX6EOT5eEFUm7pHL\nNG/eqLr7rFmoYAo0yXwuazk/uSh9lSg1MXRs/MV9ftUvzks7jv32Guq8MSMbxNFI2UkyZQQ/\nu8PD8VKPOaPzA0WAmkEWteqiOsIZPmFTcC+rLzUq/qEKvJScZJvyujJmFxb0/PgswaoeV8Gx\n3Xq2OtE0w+mP9o4EAcAR4h9ptt+zteuebV0PH7TbAzFXZIapNB8CtWZ1tnlxggCdiQMAvZr5\n7X+tXFSo07GUmaPXlRmvrc8/urtP4KWaYv2S2hSbBY2KunxNOQA88V4nGRYuqbNyFAkAJEIW\njpYxlkTZ61LIFJ24Akvdf8OitdUWHUupKLLCqrn7+kVfuna6UyCC0gyqrPAUleOMkosIc5wu\n+gGGAWIABoASgOkuDX5I4Iggd7iZr68CkuD/tD+9yzwAub5COjCIEQxZxCArFXgofVhBz6RD\nw9Jeu/rpa4VHD0ldHtHAji4tlButlSGejes0gYi5Vmn/YOa5yRT5Yj96vevpC6rXd3qSkkXB\nwVEw70H66kZySQFktMEDAIYmf3bLsuP7FHI0Kt3RzI3jkaj0akfpez2eNQp9D5K9tpOX0oSk\n5cbdA946S1ZP0dMLw9FqNePNML4xqqgGJlufJiQKMsMCANC8eO3clN7Usaho73ZjGd+6omyH\nRfNqy2AgKs4tN91x5bxiqwYAWjpdSzOykREgSASa2WjdP+Cw+y8sN11YbgIArVHVlOTWPSWc\njhEyZhc47ak98OU4ZXJCmOO08DZAWil9GUAlgAqgCOCM5sW5/LHt33h15ROt6pgIANLqUuPR\nL4dve016t3M8SiPKjarvrh15fPc/VjkG8gQAIGRYd1Rz0d6MUg1J5h/ejx0h9QvXt130WNFb\nJ227BwCg58635MeumruhInzt01OqYJz59uDAitJv+yL/+1KnJhEE5AdiMYqEZ44JzxxjAOYO\nh44WpQRw5zUVF5g445WN8188ciTJ7brCFVl3UrFsYCKGIsMCqzB3CorRnlnqFQh1AOUBAEIg\nAzo8HJiXr5t5k8fMtcMpVhP5iBCP/HhJ7vfHMIZiHctSxF67b3OtsnOeLOOOw0PzVpSSFBEL\nK7yd7sQkZKOaXrCuam5TSV7hxAdLUYSJSx/9EAKEkMGcVf79nojDnlIsG/RGR/q9hdNu29u4\nvGz3GyfS1pwXrssly3zEkPfcc8+ZfL1AIKDXK5eF5fi3pQOgOWOjD6AXoBOgHaAAIGv/1dOL\nIMkP3PHytX9toRPP9USfn/9gQPfapwEh7I4gLUtfWs/9/QqiQPd/3W/0c2M6gRH02gQmxlSM\nKjwdysedA75owT+PjA/o2ojo2dKpanHIz7WmHJp9wEcaxh/h2aHg0v5A8ubkvNaG4dCuSmM4\nkcZZbdP+8Or54oWPCb/dvfakV0IQVjN6PbOhx//N17o0ShFkGrQn6msqFE0TRXJhQXrpxGgs\nI+5RQciMR1hdmZmjr220nV1hKtCy0zfalDH8dl/fgD9aY1GT6ROaU19FEuSIKN+/u3eP3dc8\nHNg76GtxBNpcIY4iSvQqxQnSSIgf6HJJkqzWs87BgMIRCbCMPaOhogrTeJN6f4h3DAWsaR6k\nGEIq6gfPHHnwhWPvHRoy69iKgpRMHNdw0DWc/kIqjrYUTNdZhqIJU77OYfdjGQMARZNLzq7k\n1Lm2vSmceZnImW7nOHVeAlCYuEtCC3DdmVmQ3tPm6L/6X5nJmbqjtxNzU0r7vV7vXXfdlXZY\nBFvzBud8783uzKKLwTpLUXu6B1iUJlXTUKNkMCCUzaUmcc0dVcYRHV3mia4v0FOFutRafiDK\njTgm4pS2vRgIIpFtmxR+YQAEglXdf/Mi/5JCmSDsvsiLJ50DgcyVRSjRq65tsFlnVdYmSHjP\noM+soot0rHF6TRuCvKRNLdvAgH+4rZvPUGgDS22qsizNbmNmMHESxkGv4kTxBHoTV7uwUG/i\nAEDG+NePNy9UM8maHaDIn711gkTIqmZ4SY5J8o++sHRN48RasnMocGR3X9plqxryy+dM1zUi\nx3TImW7n+HckPUM9gyCAG2DyXj8yQAhAc4p62esIWkMKE2XyUCBNCA+0KdXzEeKuSsPJfE19\nRnd4Qknw0MyfIydXQQBQCdI5J8YUF3d6xYxoSI7X7KddVcZAERgAiTIAYBKNXF5v3tbDOCO0\nM1z1i11vNlofOLtMzNLmSUURN84v0GUxpJ4KHJXktaWTNexNwz02N5sihAgQTaCMxBHsi4lG\n5Rsbk3yfJ1JWaw35Y3jSJlZ+T6T5/e6mDVVag4pA6M7PLGk+Ouzo8dAy1mjZ0irLTX/YtdCm\nu7jWqkkodPSEs13A1fNsJEUAgNGqZlVULCkPmSBRXhbnoxz/RuSEMMeskQGOArgBphMSKdQw\nJMAA+wCOAEgAJMB8gGWzTs0vsWrarOqmlLlHwAQi59vSjtzVEZURReCUGwsTBgDYfdvSuT/f\niZNWnpjPLRKCPHSnrMkFVCSlVGI4kwK7qY/MnLOREfrGlTUI0Koe39UHHeO97F3rywavn6c7\nNopiUrDBGivUjZ5XXfv8ceqD/pgkP7yqKE0F1bx0bfMIK+IjRRrP0qLZqiAghKZZku8I8RxN\nEgDd/iiBwcylRJ/OsBDKeNqgSeL8KktNZrYtQPJH5xoKTK6CcWQJ97Y75zYVxyICy9GL5xXA\nvLGAzx2IGWny6ob85BiRQMje7ZYkeW5TMQBQNDlvZVnbfns4GAMARkXVLSxU63ITm//25IQw\nx+zoBXh7ehIIACRA1jIpT+xdzfnvvAAAIABJREFUE9uZ+EkCOARAAjTN7raW1uU9dn7VphNu\nU5KMoa+tHK9/H2fEGxsk6kuko+NbBGAdZA0AmFYUa7Z8Lvq9t6V9dpSnoT+zgP3uurogb3+v\n25xI+ZMItK/csDGjmD3+gkn/VnYdi1EkK8qz0/vjBeoTNi0ANAyHyCSZDJcbBRPnXjuRxChY\nuNh31jrLDbfcvz3zOqwoX3dgBACuOAy99pBrQeEM/NaSmGZUjDEez1ZlEXqlw1ll4gwJ9RUk\n/Nzx9Bq7TZXm2jy1bqwJMAZA2R4c4so0HTyjofdfbpNljAhkztfWzi+IJ20atUxToT5jdRMA\nYKTfW7uwkKIIANCbuOXnVIeDvCxhjZ4lct0KPxHkhDDHLPAAbAGYLMs8FQngZYBLMtNHX+99\nfWVBT9oUGcCJWQshQxM/+Nb6Pxu56seP1I6EsIkr+K+lxV9V8DutKNQd6CjjCa1J6qeBjyDD\nKFkhAmMzcVesqSDVtObdm1KuzNFF7Xc0f2+LdGiYN6s0n1987k/en8aDgLLrGCsqfXrTiCTD\nDPngulIAuOSo8+bdKa0QGaUCOPzfW/q0tH5hnj/dLhXyktxKy1sceEef+0NLXxQxppI0ptzI\nRSX5N3v6lhXpbRrWGxVaRgKLC/QlenYkyJ/0hDGGWrO6yqR6/NBQUJAW2XSlBlVMkI+MBq+a\nm1+oTQ/CJtfiLk+keTggynKlkVtaZCAQBkBYxq7hgGskUFpjqZlXQCA0t8QASmElxhAN8VrD\nWMIRQkijFAViDNtbhg51uhiKWLegcF7FR1xBlGP65IQwxyxon4kKxnEC/BPgouSVwt5A796R\nPeeVFUIMS60i0Iisp4ACgBCAPOvFQpuJ+96318t3rpMxprLn/l9/dvWb+waCEXOQGjPH0muY\njYuKvrB5ji5LwghrUq38wyXjP8rzCkIXPyZ3z6D1wRRMpYIhhrzlhrkeNX1Bm+v27em9f417\n7EPXNsoTuSqYdkb+aGa3VhkgQwUB4Ly2lHDWcMRx2oXw8EjgwGBARvD5hYXjGzGGvXYfAMRE\neUefFwBsGua2paWqhKXZaJjv9UWXFOj7fBEVRQR4qXk40JxI1zzqCGUKoSID/qg7IvT6Yh8k\n2lMcHgkedYQ+v7gwqdMH9He4tHpVQZlx/hxrT9vo2NakXwZCSD1VqR/G8IO/7CtFUKNlJUF+\n49UT+6tNN12g4JaX42NITghzzIKJFThBxgcdIaOKqjGwitNKScQA3gH41PjPfYE+DOB+LsTe\nEcJDEgAQ1RT3FyO11nbqKaYEgYhJhaXYqnnoG+sefrWtrddr1DKbl5devb4yq3CKMow7T2Is\nPHFEfLsLSIK9Z2P0tlewkhFzKjOy5cx6sJqXohSxotd/6y575l52JFR1366+/2ri8zQAwHX7\nXE8f27o0fXEUAEgZ37B/+KJjTgAQCWQ3qigZqw8ruH/NmpEQ/1qHs8MdBgCGJJLb/73b436n\nO0WDV5YYxlUwwEvv93k73ZGtPZ46i/qahoJHmu0WNZ3H0WVGlSci6tlprUcOBaOPHxmOiHJa\nGupJT7hlJLjQlpKD6hwKFJQZS6stw73eaFhI+/xLay3EVNWU7+wbWGPkmMRMaVORzukK9zuC\npfnTsl7L8dGSE8Ics2BszoeX5UeOOR0REQAIhLQ08bl6i2Wy7HkfyD4gxhz9SUQaB4D8XABH\nxuaj5E4xfI1b17IJnZF09KpC3f/esnySA4RnW6PffVvu8YEsAUUSNg19/Xy5wyW8cHzsiL8c\nRCYOIlPNzc1sLTDrwQjgmkOOG/YrF6u8PM96MUvlOSPGH21HImZGQ39fXqh4JEcRnz4wAgB7\ny3S/PbvMpWEAIA+hb8zkLifHpmGsajreOdjMUbyEmTExxLsHfGkH7x30ryg2AIAg4T832x0J\nR9bdA74Bf+zmRYVlhrFkGWeY9yiZx2ZCIkLEOLMYAwD6fdE0IQz6Yn0dTlOetumsqt7joy5H\nUIxJMsYqji6sMJVUT22o7e5256VmDFnVzMED9tLNuaDw34CcEOaYBXMBWgEiHwyH4ioIADLG\nZTpmEhWUmoXot/ziB78DjpbOr1Hde05lfqVrByIjKRqCHbL4rkR/Kttlzhyx+3dGv5PUvEKQ\n5AF/7L54t8WJoA170h2zsnB6ejXccEBZBUe1zO/Xl55cWrK4yrTyR9tZQQIAVqnnOwAEZXxw\nYb5xwH/v+ZXRhFHqKMZhQVIr+6bOhotr85qK9Nt7PZfU5jGJiCom4czUUHcis+noaNCR6ks+\n4I+GkxzprGrGEeI7PGETS23r9Y6EeD1LrSw2jKeVIoLAsgwA+RrmzpXlb3S59mborirjPUZC\nsc6jIwAjZbXW2oWFtQB8TOSjIqdlyOk562gzWt4DADPDGtMcHxU5IcwxC9QAlwLs7QuktB+q\n1mdduZH7pdB5LuyWAQBiEvnkUc+RkeDfLmvgywF60g/OqOE782BfNPr9d7LtnJWkTXEKUWaQ\n+9KHbOUXV6LHolrV7duCwaxnBxfmxaPGJQP+v8sFUkZmo0lFNd+y+Gi3O5rqtbal231Z3WkL\nxhGCIi17XWNB8k2zJKFnSX+q9/R4HYVDqTvHSIivt04k/c6xaP7vQL8rIvKJhKPW0eA1jQVN\nhTpTvqa8Ln/7jm5OkgkErrAwHIwxNMknCRKBYK4lfjWF32Nfh1NvUQ/3epxDAQAgSaKiPq+s\nzgoAsoxH+r1BX4xVUbZSA5ta+8GyJGQ8dlhNZ8isNccpkhPCHLPDAHBuT2B38qZJHp2Fv4XH\nVDCBtnV0+OX20jn1mUKo1BfiTCO1jGT6dCc4bRnzUpmBsXDIpKYvr498+6303dMTXBkBgWFZ\nr29Zr7+lWPszioytKsIAFx5zVY2GrzzseGaRDadeJyTIT7eOZF5qz4CvwaKpM6rir46VGvLN\nipSXP7/amvbqWoaMiTJLESalGQVz6kYCoUBM4lPTbl/rdC1ZWWouNvT7I/e+3UEgIBGKe4gT\nBOjUTCDMAwBNogurrcVjT2zKH27X0eFwIp9WkuTOYyMsR1kKdAe3dYcSjjw9J0YXrCo3Wid0\nrr6hoL1lKO1Scxd+9N/kHNMhJ4Q5Zo+O1nljEzmTfQFhQZZywWArn/lVsz1/3PHghRUrS6Td\nEyYv9KX11PqP3oOYOBONFxDZ55P6fACAuz0KiZ3TUEGRRPGi/qNFuj+sKe7K45AgFlLEOe0e\nU0QAgHNOuA+X6tutYzOHepYUZQhnn7KrfPTw4t12wBgQcp1d3n/rEvn0TZbGWWTTlVWZAiMh\nC0PKGA8EYk+1jvxqd++iAp2KJGkCJTfBMKnoWktKDShCcNeailZn6JV2ZyDxoYWiwnf/vA8h\naCwzrSszzrfpVBTR74u+0+12R4TLVpctrrYc+qCvVK/STlX7Hw6mR6XD/T6/JxpK8qWTRLnt\ngH3V+bXjW4qrzU5H0J3kRFpRn6/VqyDHvwM50+0cs4chmU5/+3g99XBYLNczaW5YYVF+scsb\n2BYtPJpxPgHeqxvLvrMWsRRgIKrNzFeWc784DzICEY8jNDzg27err+uYo+f4aFe7y2TVcLNy\nxZwmyMyJz7Xh0dTWDRgAAVFpAkHKHi9mnJD2o1Kch+M+mdlCwCzbMQCJAQAGjOy3Lq8b1TEA\nCCMUwNCRx517woMAjBFxaa/vlXlWmUAWNX3zoqLtfVnrPRqGQ5/f0j3+UupuLxGT/DMJ0KcV\nxCKkxchAEyxFqCgyX8PkqZkDQ4E+X7TLG0ku5Kswcp9qtGlZkkhNSCYQsmmYCoPq4LA/bTpy\nbaF+Q7lJz1JqmizUsgttukPDgYOd7nmV5joNS0zDfUbxbYUDMTH1Ny4KUlGFiUp6SigoNRSW\nmxiWzCsyNC4vMdty+aKz5MzLRK4xb47Zo6bUooyvqTVpKRIAZIwfbXNttfvDohz/sd0bfejo\naKsnYr1ZYVAQ9Sz3z5bIF16kb5ivefcmzZbPsl9fBakP7JIkN2/vPrSzp6fVQUsyhYAAIGW5\n+f3uwFQmy6cESaj/dQ1Zb01ZlKMI+tJ6zduf1XXcQS5UKEvIQKkJQ1ahwFl3Zdk+vvntOZYo\nnfK3fKxQezJvLArMCwprOn0A4I2KgpISMInR/Jvv9cWv6VtW3H/rkv5bFtPeKKnU5CiNk57w\nE0eG/3hg4E8H7e/3eSY/GAGWxZSQdF6+Nj+1CTNDEV9fUf7FJcU2DVOQxcyz1KAqTg25TCo6\nrcughiFXlxhlGf/2uaNc8XR7RKTfMEXEIgqpqiijXkilpsvn5BVXmcjTNquc40yQmxrNMXt6\nA70A8N5AIJKUpL7VHtxqD3IUIco4PuyqKWJ/IV9QSzIdKcNfuMqc/9gRISxIO/u0zbchq8Js\nZHerQ7FjOAI4uLt3wykULB8+OnJ8a9e8hvzGjdWKBxANedrDX5aah7A7Qs7Lx7Ic+/lO4V9H\nA3MeIBfY5H6/4llKTDO5ZvZLj0MGhXLvQT1b5xj76M4G0NZaKQIJItbQVEhIGdavWlf52p4+\nfyhGSLKMUP+Xm1xnV8Z3jV5Qk/dmp2lHf/edKwWj8kTfgSH/s20TNYg93kiIl9ZXmNVZxEDx\n47CpmfFMGR1LfWNlmSqx5jxJy3grR/f7Jp6HbBqFSQKblgEAUZJ7fNGz1lUOdLoiIT7om8FT\nlFrNhH3pFm4EgZjp9dnI8fEn94vMMXsIRADAaETMfDSOJOUyhEW5N8D/64dw3V0E0z+2nc/T\nWN7rJmISAMiDAf4vB9nvrM18CbcjawapOL16skxc/uiX7nzdriIAgDjuWPGbXT+6dYX2kjqF\nQymCXDbWDiZy7VPCs2OtB6WDQzOx5USTTW6ecuYNRlDqURjWyxIR89DVDfR1jasT279da7m3\nbZTHY7+IMhX1+fPrRtyhbc1DN3+mca6OvXFZSlP70fOrTe/31f54e+v95ym9A/zaSWfaxu19\n3u193hIju6rI2JCnZsmxiNMZ5l9qH62zaDJbVbiiE3HnZXVWVVLmlZjRkGIcW76W84QjiRxU\nr5KBznjdoSRjo1Udz3A5sK3Ln9EpPhsWmzaeRJqMxpBb//vkkBPCHLOnSl+1c2gnKHVIGAcD\nRoAAwFUJDz8mf9NhIodlYgGNLnXj2IRYyq3KvZxk5fYOAACImOXs01e//2ZcBQFARvBBuf6P\nv9z2rXMqgcu66Cjb/eMqOMbMGjBlWfqblcl1+qUR3tzqfml+vl81Mau8otdX6YwAQKxQO3xt\nw/j2mCgPMOQ1jtBbHOnUMggDMxD49XNH3j00FL/HAqUsodAci+3FE2SQl1KdxkZCsW5PJKK0\nXEogNOjjn/aOAABFIDVFrik17Bn0uyNCICavLDZQSUUd/b6oPyYyJMpXM2dVmBsyHNIV6XCH\n3zwypOOYSML8fSTE9/uipUkSJWF8aCQA8aqJYj0AyBJ2OwJB73RNuhFCA10ejY4NpTZxLCyb\nQdupHB9zckKYY/ZUG6pXFKzYPbwbTWaGMrFLYMB1Hlmi5eROEftSRk9UqexQbLSqI0q1ZQBQ\nUD4bU2NRkntlDKmldQeLdbHf72O/tTrbWXKHYpeJU+Q0lWHIKL8h774X2/+8qvhYgUbNS2s7\nvTfuG45fPVRjwYk3e2w09PxxR1iQILF8iBGctHJdeyZsS/ksTx7tPzwrTQUDvLSt17usSI8A\n4fTyRlRt4uL+agAgytjPi290uuIHjYRi/2gZumROnpWjMYY2Z/DFduf18woqjYq9ljLeLoaI\nKHkioj8qLinQNQ8HUGIhF2N44tjwFfX5tWY1APh58ZV2Z3zudGOluUDLBryRll19vFLgmA2M\nccgfBQBOTUfCAgAghEqqzcVVk9nNBH3RzqMjPlc43rCwqtFGT69TVY6PhJwQ5jglNpdtPuE+\n4eVTEhG1tDYoKE9pGhgSAPx388NXN/A2tcoetLzdRSPEfHqB4vFVjTbPaDiaauaJAdMGrmFW\nRVqBiCBnFJj7VZS4b2ASI2eiNm3UOz02MacLVKSrnZf346dacZBPuy+SG/sbd0eEp1qHBSWd\nS34kOemOSBin9OQTJMP+QcOh4bb7zo1rqiBjjIEm0dX1+QSB5ljVx50p6bUbK03jKjhO8gt3\nuMO/+qBXQ5MxSY53SZzKqHaMfXZ/nz92RX2eRk+W6NmmIv3yIsMOV/hIz9iTijcq/vXQ4Noa\ny4VlJmdIyFPTmyrNcyzqEr1quNc3OuiX5azpvgSJWI6OZJRPxBEEefmmGj4manTs5KuDsYhw\naEePwEsAIEkw2OMJB/lFa8szVxByfEzICWGOU+Wiyov+deJfUmJ6Sk2pL6q46MmOJzOPLNYy\nfT6eu5vqv/gseazJHIxcWlf/4D5dnnLdHsNSy8+pHu7zhv0xgiW9vEQAqqsxa9RTdAPIhknL\n6qNS8iwiANSMhulrlZU4DmHT0pfPFV5oS2xAwJAAGPgZdeFIls/TKaVS85AYd6VBAADdFi7E\nEvMGQwCgaRulaFIUpJOesKIKpjESir3cPnp5tQUoEgCImFT6SLPKHgAA1u6PlhoAgB57khi7\n/6vm5j91bCSufCSB1pYaN1WYHSE+vTtGBslea93eSNk0Vt00LHlJnTX5SabUoLqiSHfpmvI3\n9vQPe8L5Zu62C+vxaNg1HKgycVWmhPUaoJGBKfqEyBKOhrKmyIqCRDGkJrt90jjDfV4hdV3T\n6wwFvFG9aVohb44zT04Ic5wSnpjn5e6Xx1WQIZm1RWuHQukWG3HwTp74PT96w8ZxFQQAUc/2\nn1el+9E21f3nK55FkkRx5dSux9Pn+vmFf2p3yInBVCVI1x1zMZ9ZqHzPESH63bf5hw9ATASO\nRjSBoyK5tEh17znCYy38Iwdm8sooy79PCWRR41RvtkpX5K7Lalb0+K887JBHQgMAxRQZnlbh\nIwDAgX7f139/EKpMCGNtm5NOJJXQ/phiqqWGJj6/qMgdEfwx0aZlOIoEgKWFuqOpiU5zzGpf\nTBoOTay0WTmaoojhQAwA3utx11rURRn9lWSMk4sIa8xqwHgoyGsZSpeYbLTQ5PKVZRevLJNE\nebjX09nqkJJytQgSIQBpGg8BMOlqN0kSTJbGF5EQH4uKGi1DsxQA+JTScMKBmKIQDrlC9z9z\nZNgdqSjQ3nrh3PJc9eFHQU4Ic5wSr5181s9PFBLwEv9WX4ZVGEDhUTj3XtC4YHQOGao1pYlA\nqN4q/n5/5lkAEIsIkiRzGuY0Tivd9LVVBffveH17T5gmSrzRi9zRJbtuyZa3Ev32W/wf9o39\nEBFwBNSPX0VfNx8AYj9RaPs+FactEERFOuwMg2KDX4BqZ+Qvq4o2trtjFPG7N0+UWTU1U2Wg\nsKKsjUml3uh1+0fMgwEYTMmTxCSKlGdLD0EAYOZoc1K2UZ1Fc0V9/hsnXRFRQgjm5WvPq7T8\n+XBK96j6PM3qEsNLJ0ZPuMO8hF9oc1zbWGBN9UmwB2JWjuESVZK7+r3vdbvjZTlzrZor6/M1\nDBnyxoZ6vTqj6vCuXj4jlzgj32ryX0H2HlhaJuiN6lLFTOCl1v0D7pEgJNYOa+YXhP0KmTic\nUkfDJ97r/N1zx+LTxp2D/nebh3795ZUr6vOz316OD4WcEOaYPbL7ZF9owh2NA6gXSS2GEQJ3\nkDIGIBHJEEwelxeYo733+6GoIFoLg5dmWonFJMSlfxXDgVjbAbvfEwEARkXNWVRkLZxlQXQm\nF9y59oI7Fao10hEk/q/Nadv4hw/EhZAomsX9zGYIVj46IVRYqczOo6ZFAnXkqU/YNADQ7wz1\npS7jZRKjiEf+2Zbctr49X/34ssIek8ocFlbrVFUaZkYavqxIv7RQ74mKGoZgSeKdbrc3tSx9\nZ793Q5npswuLRBmLMlYp1R1GRXlrv2dzlQUADo0E3+p0je9qc4aePe747IJCAHzioB0jNL1U\n3snfRNa9AV/0wLbu+iVF1iL9wElXwBuhGcrvDYcSJYYY4/6TLpWa5pXqPTKb2nsC/APPpfgt\nYYzvfnT/m/974TTeRY7TSU4Ic8we3LMdJUbvEpm4jqfUCXfnPkJ+nBUFLH1l4Veee2/wqVfa\nZJkFgM4j+evmBM3FKfYfhuYh7ItFv/82/dlFhFEV/dn7wqGhYzctjCYWjfioeGxv/9KzqzRn\n1rxRHg5CZoTRPeacQl8/j//7oeRdiCFx9qK3qZiBysSNtrPhU1HNJToA4Gni+QV5AFBjVmdm\nr2QSZgkIjN1IZ576zitqBZIAgBE90wZwXq9ngU2roojkVk2ChGXACIDJ8FwXMX6sZfDyOfks\nSQCAPZAeJ2EMg8FYrVlNEYjKyGCKc9IV6fWPzTQ2D6WbGJxwhaKirKIIDJMVtDiCfH5qQEbR\nJKumQv7YVI0k024Ytx8e6jk+mi2TGQBG+v0sR4UDKV8DkiJIKn1a9Y19/Zkv7g8J3iBvVAof\nc3x45HyAcsweFHJVymN/3pfzlBqjEOA+UvYhXCYTawUCA36/o/WhV9rkJGevh7pdyD4x7aY9\n7iz+e4t0eDj2vzuCDQ/6K37NP7An4I5EU1MnZBmPDEzfzOX0QBTrUUZyBDF3rFERdV4N99vN\nKDEfiMzcKaigAljxnwABlspUQT4xeTisZ39yfqWXo3Qx6f/WloRYEgC80zAfIGUco8hxOX6i\nySakaBve0ul6+YXWP+3v73CHJYwljE+4Qr/b1/fDbV0DSpOBzUOBdlfkTwcHD48Eg7xEK0md\nZlJH7zZnaOeApzoxG+mPZcxyYvBPVQsRiEmPHR0eTop0EUKiIIV8M1PBOJIoT6KCABCNCLYS\nQ9pGW4khc+p92KNomYS4LCuROT48chFhjlOA1V0QFUaRLCCQAB5QCR40tmRVIBObBBIBOtLt\nllL9LQO81Pxky9VBibdpVYN+betoynjESwDAWxTSCmKRqU0vTzMEYr+/PnpXUnteimC/tz7+\nTxwR+H8ewYm7wkr2LrMmShPfuKJORsgW4llBumtL7/Yao5aXRzX0v5psf3zyuCYmAQAmidEL\nqn3Li0CvOuwKb2139phZkUAAEGBJSAypo2E+beqVREhKDaEkAn3zitrnHmlhRBkAek1pwTfC\nCM466X3IpvnrocF4tcP4FZ477shX04sK9QvyJ3I9mocDAOCJCk8eU24mbFXTNi3jj0n6pKE/\nKspvdzkRIuyBWI83AgBz88auWahlRkIpisuQyDpV/jAvy56I8MC+sdYTOpY6jT0XM1FxZPkc\nKx8VB3vc8Y8nv8RQs0Ch1GdxteWprV1pG806hj3d7T5yTElOCHPMHmSbr+vZ/qUY00pKf1YJ\nfJKgDRPys4wMAFpGg4iIRhcDhEN+FZYRRxNaq4Y71qdvUWiJF4frVWhRq/0oTK3YO1cjo4r/\n4355wE825rP/bwO1tgwAcJCPfneLtGd8iTSjpvwUCDOkR01vbnM9vrSg16IyRMQoTWxs98S1\nbFWP791a0yVHnQDQ+9Vl7rVl8bOqSvVMqf6hI4OgnECTEpKcXWk81OLwcxSf1Fo9vqzYOBQE\ngPyg0J+qhQTGmuhYyCthzFIEiREvyQDgjgjuiHDcFR6tNG9KpPiaVZTKqunxRqJKGT02DXPd\nPBuJ0LY+T62Jq7WoSQSDAf6F446BQAwA9Cy5vNhQa+aKE6mkGyvNrc5gcsn/uVXWLFOqE1g4\nelmRfrfd1+eLAkDpVN8ia6HeNeyPa1jmsiNJEVKWBKU45XV5CKG6RYWVc/PCIV6lZtgsRYdr\n5xeU5mv7k3JrEUIP3LFmiveT40MgJ4Q5Zg/Kq4fhw2TU50OYz9CBKIICoBZU0j2XtnI6HgCi\nIUbTN3+1ropYB0duXGje2V/2xwOE0qwd1+sz7+gbH+IBgNMwRRWzsZI5VRBibmlibmka34D9\nschXXxMeP5z6jk9nrbSal9S8VOyNLrQHvnb1nC/usnOCHKMIVpQBwBwSKt3Rv60o3OwTkj8i\nACixqJcVGXYPTN3pnn6ts44l9pWlT+L9a3H+j4eCAHBem+tAaUo2ULk7ahAkWpKtRu6yOXla\nmny2zdHtTSkVeLfHPceiNqtpjiKvbrABQEiQnjw2fDK1ooAm0ZVzbTYNCwBGFfn3liESIQLB\neHOMC2osa0qNaVX2VjX9lWVl7/W4hoK8jqGWFxsa8zQkS0qxKWakSw2q3faxz6Q4I2klGYal\nXCOBcfFLU0GaIcVJq1DMNq010f6CZikDO9kAS5HEn+9c/9vnj25vGRJFuaJA//MvLcvT52oN\nPwLQJHUzHwZ2u724uPhMvmKODwspJu//C0S9APACI7aQCoNRlYyGAEcIAAAmDKv+BHPeQaog\nGaqz2D+zIFJptL7dVfZH5VI8mSJGL6zxnV0JjfnGPHX5nDxm0mHljBH+zLPCE0dmdeoUeaGI\nIHCG78lvzi7zqOmDJTqRhKrRyG077fMGgyKBrrx1wfwS41Vz01Pt9w/6nzvugElhRPn5R1pI\nGQ+YVHddWu1KaoFU7oo+9GRr/D6fXZT/j+WF0dRkTh1N3L6irNsTeabNISk1dSrWM7cvTZHn\nEC/9ak9vVJSTBxuEYK5VW6BhPFHx8LA/+W0zJHHX6goutbFURJS5LO0sODUTjQo4e6/BPQO+\nF9tHAeD/s3fegXFU1xo/d8r2pl1Ju+pdsiz3gnHBlQ6mE3oIpEAoIQkv5T1CIC+BJC+kQRIC\ngdBLQsd0MK4Yd8tNltXbSquVttep9/2xq9WW2VWxJEiyv39szc7szLb7zbn3nO/olPR3l5ZI\npqeOh9QAkSBQTr464GVIilCZVFs6nYfaHHIZuXpuwZVrKqiUBKIs42HmZeJLMbJk+VcEO9oi\nKggAOThhfC8XiVUcmYfRCVLsoHkAAIzPuw9V7gQADMDrDg+q27ae+M1ZzlWlJY8dRMk33iRw\nAsGLhYPB6vPriOqprKaXRsTCIRsOsOScfGTMdEuOgxz3z+PpHiUKtMisFo8MYhEnqJ5GhrRy\nGA5i6dbw0V1TVRAAyh3e60IoAAAgAElEQVShD+pNkf+356l+ckHVn185afYyAAl5IkgQNU1D\nDkfISia8mQQGIcUK9rLDQ6SIAaDYGf7O1t77LhhtRHVmiyNyMY+tLHpjvkRBW22uWkYQbzYP\nSaogANTkJBcsqmXkmlKji+H2xIWqGEPTkF/Sa71QK09SQQBocQQ+7nBeN9dSkFJ0HwqytIzk\n0mcqnXAE8wyKcxYVrSrSO60JKVdyBT1rcWFvmyNSC5iZ1KhBFLFCJausN5NK6usPbe8c6VDf\n2OY43u36xU1LIn+Gg5zAi0qNjBhzJjfLF0FWCLNMltCoYdVcgdhORWcK6wTyKjb6vWIBL+TJ\neQKhZUG7Eth2XhyI2iOTAS73447+6+aKKpoMsAAYSIKcZ5F9fRF97VzxpAOZlERlzpT0Z8iA\n460mdOUrZGzZiUKKX5wp/0HadRps9YKQZgnOqASdTGi0RYUt7sIRxtTKEu7VJskD04eJGAAN\nJWbSh2nik7qcM9rdHEl0e0KuMJejoOQD/qpfffZSieaVhWZRHH22ZV2eJb2+J08vCI/kXxhC\n3OWN9ssOj+gPgoV9viJ3eECvIDC++MjQFY12AOg2KSRVEACMSpnVxzBp3gQAMKokmnjU56oe\n2Tem51oUSbFACCEEuUrp1Jh0Kihi+KTD0eIIbKg0NiAiSQUBgAlzR3b1nMrEmLXDae1wNjoC\nMRWMsPmg9boN1eUm1Yn9Vo8zCAC0jKyea7Fk21Z8+cgKYZbJohoN1IwiWsORDgLmCkSFOHov\n3yCQ0WCRAjgHqOV08JucOBQNgJR9PgUpaP7vLLHTTa4soc+tibWnJ0+biYkR/4tHqRteTyhO\n4HH4xx8Ts3LpjdItf4nKHKSW4cQEenJ2nux7y0HEoVs2AUCqsOEAy7/ZPPELRAEZubMyedwc\n0Msrh0M37B3450Lz80dtV9ab1zyy7yiJ/rEoITVRxQp3f9qjC/NntLmaLBqCRPV9Pn3KiqxM\nwE++eCIoIwGDaiRgPZnehmYwwJal6dAbodcTXlKQUCeKMTxzZICPRpBj+wb0+xiGF+WJE5gd\nrmCNUUWTE6m2xPiXO7sijqafdrh8jHBhTW5qweKpLQ9FX06XlF9BS6/b3+aINQHmWKH5YL9C\nLTNI9brK8gWSncKeDvwA7QBdAOPtefavCDJVAzU6IK7mqUtZqlog4mfmkqZMkQ7RXxlJDcfA\nWDTVi8tlty5V/Pos+qJZMMN9ajBmbn4DpHI9uVfSTn4CScjvW5uwRU4pn7tcdvMisSuTpzPO\nmGooidWg+Nl5lYO65Bio2MUAwLX7bY+8etLlDD27vVPd4jhQqkvaLSgjT5hVPIGcarrcGTq9\nzZWqgjFUrOBXkH9aU+xTkACgSZ9+0tfrMSCUYZntwIA3KYOmwx2Sj66Wja1kYV58ozlhAbLZ\nEdzX71VNpK6A4UWrj4n5emPAe62eD9uTewinB6X8J9NuOqkFbBVFxFQwehkY23vHTmXKMsNk\nI8IpZy9AzG0EAawAaPgiL2f6IGiQ64GfWPEcWRUdOLCMyL1ubk5R8vA9Y4gdLipNBiC2Z3Ij\nk39/OWFWM4/txwN+cq5Z/pPV5AILABAlyRmYcUx4gvdAifaejdWp2/Uh/vym6Ghe4gpffti+\nuTYHABhK4hQn89V/Xl1i18oKvOzlhwYXWv1F7rSfV76PHdTKH1pf/rP32hsG/Nqw4FMkC4+a\nFe/6uMvi5zcsK/iowynd1AnDk4esSwp0a8pycpQ0AFTlKO9YWrKpdWjMdFaLRhapfD9i9/cH\nmMtm5ZfrlR+1O7b1uDAGq1TZfmqA2eoMvts6bA+wqe/IQZvv/Oq88U2345T/pNsNAcCyIv1n\nve74HsUWo0oT5FLf7i+gHDbLWGQjwqmlL04FAQADfObj+tLu/i8OUk24ngE7ABAQFQb1W9fk\nXDlnOq5qvKQfDsnFhZkPpK+fr9nxdW3bXao3ro7tTG2sQ1M15YVhUa/vmoODD2xqe+SVkys6\n3DIBy3hxWZfnN2+2GuNaBc3p9w/qZE4V3TCQbFNCiPit+Xl2rQwABnSyP60pueXqWW/PyQOA\nfWW6nuR6eQAAU4DbU67r1Sv0Yf7HH3fmBBOG7AVW35MvHPeoqO/rqXdbHZyA1TLpmUoRQ5gX\nc+I8uBGCC2pyM5cTAIAjxF09x3xOlen86tzr5xSU65WtzmBEBQGgxRno9iTEmoKIP+9JCMRt\nfva5IwP2AAtSChbiRDZ9P8JJEX0D1DT5vdPL8kYsAKuLdL/46qKw1G2HJuPEcpYvhGxEOLXs\nSd3kZt58rpm4uPLiIvW/Xd2IZR4MTWzpi1pHaC9pIBZdOU1XNH6ICgOvV1Ce5KEKq2n53Wlb\n1Uf3GQqE79/Kb+4AiqDPq5HfsxoZFEShVv3G1cFvvS02j2P+DWWMNBAggBt390f++ukHnbEz\nJ8U/C/t8N+6x/XFd6T0fdGytNewvGY2wV3V4tlcnrC/yBHp8VVGhj7n3gqqLjg3dtj35Fq3D\npASA/7qs5tr9tprh4Ld29b81N6/ZrEIA862+c5oczWb1H9eUCCPLbIH0iZpGJZ3qZVOmV4QF\nPMuk2tzpjExaRp5JJ6d8jCBgXKxV2PxcvUmlU1AhTtzc6fzc6llebOh0hRhBrDAoihId70gC\n5STm5hwY8PLp6yiMSko++ZKGMVY3NTT5zPdWuThBTpOFJrV7OJBaxUIQqLjKNNkLyDJdZIVw\navGlbjIraXto4KWWl74959tqeoxWOP9aIGMV1J2PO7ZgLjTeuT8CUM40GlxNAIQMm671rH+a\njFu9Y3NVuU13jFFBEeICG54RjkdHOebEEL+nT/Pp14AiyJWl2uN3iL0esccTWP33DOdW/um8\n0OYueD1dHmnaA1M3XXXQdsvV9Xd8ZdZZJx0FHqbZrBnS0BYvS0npAU+gZ5YVAMCHs0xf3TMQ\nvxa4vcrQkq8CAI+SevSM4sTXjBuLtI1FWlrEwvgKALZ3u2fna4oTq9d1cvKKqlyKQIsLdDY/\nQxJILSNVFEmTSBDxnn7PaUV6aiRS18vh5eN+jhc1MvLbS4ojSS6pL6lcr8CAY0m6zowTj2dX\n5SZvQsiYpw6HuHCAFdMq6Hgbg4T9bOWI7YNSLZHgmleso2d4LTzLOCDvv//+mTyfz+fT6b6w\nZaHp5yhAcj4Cj2HngJ8V2XxVvkUlYTn4Lw3SWFDJMkKTj4fHFxpScqL2vPgsmy8QolSvuG0p\np5W7eSG4vCR/37c0Pz4DSWX/jxLmQ5e9zO9OiKVwr4c6vZioid7pI72CKNIyv9wBaQZWan2l\n8g/nkQjY/f0oLiRFZjW1rFjsHKORehIIwGqQ7ynXHyrWteSrnWo6RBMODd0p5dcKAA4VjQAE\nAn1aa2wY8LtVVL9B8ea8vKdOLxLTidyIOInjrmbBAO4wv9Ay6k3DCtgd5iNt6EkC6RWUVk4p\nKIIkEAAQCJXoFETi8y8r1q8rN5YblLHtGCdPabMiHgpwsVwVm5/tTonyCYSqjKqLavNmS2XD\nzlteStFkKMilq8HQ5qjYMD8eLRREkZZRKo0MACia9HvCwTizb4JA9YuKZGkc1yZEZ/PQiX19\nfZ0uiiS1/3ZzrTMvE9mIcGqpS1wjBIBR1ygP+++aLYYgt45YfLN48n3w9Sc8ItcTtediZzu2\nN4HAIl0RqlwPii9RHRUyqbT3rNbes3o8O+NBv/+sZ8XjEr4twjE7dV5N7E+xx5OuZS5Zl6t8\nYmPg7Gf5LZ3RkZVAiCYxw+PBAD/YiQwKnD6lRRJlYtZPXL4jxinD99c/77ca5B/PMg5r6Luu\nqNOwgghAirjEFa61Bz+YLT1xN4mGwt3e0VfBC/j1ZrukDmUg9YypSm31Mu3OYK6KjpRbnF6s\n32P1JLmbYsA3zS+UFHGCIA7t7Ept5xvDZFG7hiQ6zkvisgdc9kBFfX75rDwAqF9c1H58cLDX\nIwqiWqeonmNRaeUCL5KTtbaJsH1Tk8BHR5XmQ9auk8PLz5HIq8oyfrJCOLVI/M5jKd9mpXlG\nr2WGUecTi24ELELQAYwPA0YaC8jUAICMlaj6rC/6+k6ZMB84+zlJFQQAoiwhZRSZNUASkqX3\nwsnhwPkvJKwjihjHecRgd5go0Yv9XpDKyUwFA9pRqQcABHhNq/vcJkdOiGvPVb242NyXkhFz\nw96BrxwaBICV7e77LqzEgMIUccNe21UHbQAACGB9+TZHgCaQN7GCYhK+BiLGrIBlJMIY/rSv\n1x5kczNH26mvbKzTDge5MIHOqxmd8AywApcSiGMMQ0E2X2quEmOcQQUBwDUUTOlxPwoiEU55\ntKt5qKDMIFfSFE3WLSisW1AoCiLHCi2HBw7v6sYYawyK2nkF+kmlVh3a2RVTwQjhINPT7ijN\nLj2eAlkhnDIw4AC3V00DJP58I0lqJZqSWkPtF3JhMwoiQJ0H6rx/PyMp9tlG4Zh0uwyiRE+d\nnXBLjlQ0fWk996p0PeKY2TRinxcpSBwau4kgALQttjjVsgVW35x+//X7og2PypzhFZ3uO66c\n1WeQA4AxwJ3fNLykxzdrMFoZclqP96fvdwZkVIPNXzDSY53JVy8rzVk92wwAzhD/dou9xTF2\nO990YAyf97pXl+W4wpyH5QBgj9WzrEivHe8i2dhfou4gd/Olsw/v6MKA7QE2xIlNQwFJ77fN\nXc5rGiysgLd1O5uGApyIKwzKMyuNYyayZlBBAMAClqtoJjG9FmPccthWt7Bg1B0XocbPuoMj\nrYn97vCRXd1L1ldJriNmxuOQCE+trcNZITwVskI4BWDAuwZ27ejfHhYYEiGCAD1N0gRSUuRF\nFToFRZ1RsGpV4RkEyhar/KsSuvM99tG9kg8hvUL19rUoZZ1G+dcLgRe5N09M5nwYj1MFqQ2V\nVWr6+eeOqxheTPyCKTjxmgO232woA4CVne6YRsYodLNlrtHpepEm23+0Sj7i6GZUUtfNLfjz\nvl57xj60GRBE/GGH44DN6wrzEXEKsMJjB/rOrjSWGZRhXtTJqSQfbR/La2UTGJQW56ldg/7h\nEPfyMVu/jwEAMs0q5tFBP4g2Hyt0jRRgOENchyt052mT9+COkKSCEYYHvD53aOm6SlpOAUBH\n02BMBSPwvDjY64nMoE4MKR+c9Gk+WcZFVgingH2D+z7ujfZuFTAWBBgWIqMY949W4Vtz8jaU\n1AJkav6S5ctM6BtvsU8dkn6MBNWb15DzJCa9UY5S9dpV2OYXmocDG56elitDiN/cQQCoAAAQ\nETdEhmTkS4vN26qiGYzO6JxkwmTj/jKt2c8oRtYXQ9U54UR7GppA883ajzscp3KNjhBvVsts\n/qgMOEPcy8ejgfWGuOaFAsavNg0eGwrMy1ebVLIFFq1RkTCP+kHb8ICfDbD8rUtKRm3SMO5p\nGd7R4+73MXo5VWtSUQTR7Qn1x6kOTRKX1ubVmdTDIfbRAwlZTq4wd2DAu7Jk/IvWE1gqZUJc\nT5ujqsHMc0Jfu8R7mLnTfTrkSiqcIr15X5wxxb8HWSGcDPaQ/cjwkSAfLFAXLMxdeGBIupEQ\nAAwEuR4fU6Z1AJSm2yfLlxmxw8U9nZwAFQEpKOXLV1KryzIcjiwayqIhak1iy+TkRHLkHTH1\nTmOSKSL4xTkV8d0Ed1fohzR0np+LHc4TaHOt0XFZw61HBvGuXiAJcX4BGeAENQ0ABCcoerwi\nReSdcusrjHFMBZMIxuX4kAh5GEEQceOgf325EWHU5gxp5aRZLR8MMO+2DLW5QgAwz6xNNQs9\nq8K4psRgUNDESGi3q9f9Tmt0/pkTxEa7f0GB1u6QEB7JayNJgiQJlk0Nyic25e93hwHA7wlj\nqcQpdcbOiOlYsr5q5zsJGdoEgWrnZ7SAyDIWWSGcMMedx19vf13AAgDAEGzr38bwTHwlUxI7\nBwJlk/rGZ/kywG/ukDRlRlVG9etXk3OkWzTEg10h7JcsbsPU+kr+006ph0bPk3Zj+smwZos6\nqaeugNAvzq38+TvtujAPgMI0+ddVRR25Stw0wGxqoxkeALQvH63a1Hzkf9eaBwOljx+k3WEA\nqCrWHTrNcsIymgU20fTR1B5+MYoTq+MLNPI+L3PdvPzm4dBDn3djwAAgp0iGFwBAJ6NK9PIy\nvcRPSSMjk4xqV5QY2lyh5hEj7F5vCAAMUqKeo6Ahru88Bnx00N/jCcsocm2ZQXZqDQVZhgcA\nipJYEyVIVFA2mfRpmiZXXVi/79NWJsQjQFqDavHa8lO5yCyQFcKJImBhU+emqAoCAICf9UNS\n051EXGEeoHImLi7LNJCukkH9xtVkw9gqCADMA9txf3L3HwBAGjnKnWje4LhkqDtHooKwO0dx\n03WzZ9kDlICbzWqPkgKA+97toOMSVjUBzvi73RVDQWKkok7e530owD78k1Vbe90MK4x5+tQd\n0qlguUE536z1MbwtwKpp0qSUHbJ5dXKy38vGty2MqOCyYv351bn0RJr5VRtVMSGMrESWGpT5\naln8kqeMJOZZtAAQUUERw9ONA32+8OqynDK9IjX0nCh+T9hh8+XkaxQqOmk+s3K2mZ5stE3T\nxIpzpLujZJkcWSGcGEOhobAwgRovhcenkuUD/LtVvP7nINkQiqg2plNB7rnD7GtNiCapDRWy\nmxeBjOT3SJnNEkj55wvYp6QnXdODUrzZJLTJ7JWYA8z3cz058gNxHmwkxvkpoWqVzU8k5kmS\nrvCPzbpPu10wDhFGma3j4nZbXKD9uGN4R487kuehpIgwL4Z5cXdKy8AirXxjTd5EVYmKy5qp\nz1UDAE2g6+cVvNls73CFACBXJbu4Njc3zhB1f7+3xxu+Y2lxrmrCyZzpGLb5TBZtw2klx/f2\nRrQQISiuMpVUZ5M8v0RkhXBi0ET0Z0NgJCKJX3zSHGnx4aN5re3WK81FZ35tZq4wy9RCrSmn\nr53LvXg0tgWZNdojt6XuKXa7/Usew85oUiL3ehP7/BHNp19DKR3VAUD1xtX0hXXCwQF+a9LU\n6FhKkvwgSnwMAcAcm7/UFY631Vaxwi07+35+bnk4rpNRrp8VCCAS3VSw1AW88tIRrkwL42F8\n2YsYw2snEioyQyMl8CEu2d6l1qRKVUE7w1cX6LzOtNUdne7gyOHqsyujhYa5SvobC4vCvMiJ\nOLWKo9sTXF6sn0IVBICBbret260zquqXFIkC5lhBl6OcRNVElmkla7E2MZSU8pjj2Jog20ZJ\n/+LjVZDkhaodu5Q+n+fErrKL75qpa8wyxdCX1pM1JpCRRLlBdvcK9fOXQ2pjPE7w1TyMXYnN\n5/q8hEVD1hj5D9rit5PzzMrfnRsIBF5r2vpSQcdHi3wdhVyBk9KGSNk1c4Xm4XTebGOBPi/X\nFXlYSsSLe33dJoVNJweAMmf4x590L7B617S5h7Ryn4Ja2eme2+/nSOK0bm+SK02LWZWXEiY+\nNid3SCsxdi+uyRtIL0WTQ0mTSd2d6nM1ZfrkOZXN7Q6FQaFJ90ZhrJPROUrq3Orc1aUGMlFI\nKQKlWm8jgjg5HCg1KM1Tq1IYMIZwkBu2esvq8gy5ao7lh/p9fk+YllHURDos/ueQtVj7soMA\nXWFc+EZwM0659ZVH+vCOmCHSYaZ28zaV2wMAAhPk/C5aM+GmRVm+FCBEXzuPvnZehl24fxyT\nXE3k91hVT10iHBxgnzkUCdeIGpPqhSswxo//9bHmjpORWfPWQubx87nvvZFn+KA1nTdbAmkW\n6ygRfruh9NadfYUe5ldvtZ3MV7fmKy48FklYRQVe9qfvdwgEIkf0w6WirAZFrElhR67ywbMr\n7v2gszauI+OOKkNTQZJlEgZA5y4tqfYyaROmJ0udUd007I/3SOv1Jr+x9gB7aNC/p9+rlREN\nedqzKo3JtYAI+nzhjzuce63e1WWG5cXJaSkESWARx6dBIYQbivQOz3jd1CYKz4v9nS6CIrqb\nhyLnJUhUO7+goCw7LHzxZIVwwhwaOmQnklVQi1G5iI6SokYgat58ExOgGRymuOidNUKIUmfo\n2prlXx5+X7/kdqSTA4GUf79EdvcKsdGGLBpqVSnIqe7u7uaWk/F7BuXi3trAWQfHl6aYZsFs\naY/n78sLb7ihoczJhCmi1yhf0ekZEcIoZFwUlRPkGYp49rSCkIy0GuTN+SqvgvrhxVVXNA6d\nd8IxqKG31eS825DSsQEQQuiDfb3jutSJUJGjWFCgPavKuKPbNRjkZASqMqrebR1qHg7Myo2K\nsY8VHj3Qx/AiAHgZ4fM+91CQuWlBYWLCGto/4AEAD8Ozkt2DBREllt6LAl41K29L6ykVTWbG\n3ucJxzXHEAXc0jhgyFVnZ0q/cLJCOGG6OIkMwBsZGiGwI26QwhTDqBzOkQx3BAAY44GtLxau\nu36GLzXLjEHWRnIfkiM1emPUV49syI/Pr7HbJTxLHfq07f3GQ7dR+c4ck1dBhWnypDmSj4pV\nzBjPafGyPInenW1iR4KqME0+v9SyqSHXo0o7PkiWlJwiBTr5LLO2OkcJABfWRi1XBIy3dDmf\nO2JbVKCtzFHyIv6s18MkBs1tzlC/ly3SyQkCYUBYFAHgO6eVucP8B23DnjRWoqkvweMOKXIU\nB22+uXrlhDJUx0k4pUWUKGL3cCArhF84WSGcMARJg5D8hVYAKEXkJgAAuk5b0vD+RwAQPya2\nPvUj4/wNCmPBjF1nlgmT2uNn3FAb69CPP8YJKfJI/o1FSR6kMfLyJLy1TF4KZCSk73abgYPF\nup9eWMknD99oRWe0FKHTpHy/3uTU0OWO0MVHh7Th0bMUuRk2xWYsgwrSJOLGMgTPUctdAek6\neun9FbKN1blliU51GEO7M1hvUjcO+g4MeA8MeAFAsqrhww4HidAVs/NLinTOkXldg4L6SoPl\n5WMDIV5QShXzJZ3rD9s6I9OwmyiizqS+umFKXfLTZEFl9jLNMjNk3S8nho/1KSH5F1UgEiqM\nWkiRdDrnvPNh/Uefxn+1I//HonD89zfN2HVmGT/8zh6v8Vce8mce6mce7QPc80cm8SREqV71\n1jXIoon+raaVf7lQ8djGyF9D7vD7e3vf2tXdY/dHtpSWltbU1MQ/g4JFS8MF8nvOmOCJo6rw\n59VFSSqIMFy333Z6lwcAPq/Q33Fl3dvz8nZWGp5fWnDL1fVO9WjZwOp2NynicWZ8VhqU47ED\ntaTphiiJiiYvrss1qWgEKMQLEccZTsR/O2R9+vDA/gEvL2IFSSwt1N40v3BZocQqQ5szeNIR\n2Gf1OuNWNwGAQDAnX/Ps4YExHVNPDAdii5Esj0+fUtMymYIGLKHfPlbYfMz24ua2pm7XFJ4u\ny0TJRoQTQMBCy+G/XxVinpcRfUR0ckaL0UUsJSi0b/u7F73yBs2wkNgELvY/f/dRLHCInFAn\nmizTCx70B9Y9NZqlGeSCN76uqTKSy4szHgdPvt/8zuc9/jBfmq++/eKGRTW51PpKXc/3xXYX\nkIioyIlKFMbv//Hz/2uxh8lo+9mvn1d383l1BEHccsstr7766qF9BzieL3UrNn6mMdh8zH1b\nAQAINHJJY5WwR8ys5WR/iuu3PsTdsHcg8hSPrCmJ7yzvVNFPLSu8+9PuyJ8yXtzQ4vxo1tiV\nbeUG5TcWFf3j+GDmRvAAkGdQrp5X8PwnrYGMTY4irCjR1470JIqEbgwvbu12dblHU1fCgnh4\nMHDMHpTTBEUgXipfVPKqDErawwjuMCfZhikCJ+KtcVJUrJOXGyYg5HFIf15sWOLCmocD/zg+\nyIz06tq4vOx/rl0wqZNmOVWyEeEEGHS2LAgGZRjdxNBXM/R6jrqEpW9kVZaKDeSSb1U1tdEM\niwEgzfwaFkWRm8BkUZYZIHTX+6m1CqG73s181J2PfPbEeydtrpA/xDV1u29/+LM9zXYAAJIg\nak1ElTEWqFn/8PmvTw5GVBAARIz/9l7zobZhANBqtTfddNMf//zIb9QX3faaocQWd1c6ekmS\nzWSTN8p4kUrpfahn+JCMBIAhrcyZ0ghwZBERAIAU8fc/7Sl0j/3lrDGqAODcapNaupXS6Dt5\nsGV46+H+r50zC6WZbf7KmsqiEWOdefnJRYoCxu0phRmsIIZ4wR3ieBEraImxi5Aaz4q1ih+u\nKKs1qZOuMJ6tve6+kXDQopF9bcGkrTslXqzk6+cE/MqJURUEgE2fd3+4X8p7Icv0kxXCCcB4\nuiPfaQRQKxKreHKeQDiDXlSyjCBlFUEaMt6909ocQj6ZVpxZpg+hMbk5EQCIXZ7UjTH2nRza\n35LcUPDh16VaD2J84PnDTMry2+64WnKEQXz68DivduT6kkdzWsBLe5JzuFZ0eJSsAAA2nSz1\na6lOSaK56pB0t8UYRiW9olgPAHo5dZX0+tnoefxhrqXP8+e3jkk7tSLYccxmHQ4CAAJkVCbr\ntIomMq+UhjnRokmI8AhA5XqJ31fShHH8H4cGfK3OIACUxPXIvXK2ObE51OTW8LDE/+JwMlyI\nS7532dss3fY5y3STFcIJoKIllg0Ef3QA0lmqMh/O+Zz779kgcpPs7pZlOiCrjakbieJM60MH\nUlQQAHqG/Kkbsc3PSE0MsnEjIHaFsHfS8wSjY+x3tvY2DIxew5o217X7oxqf52NTx+Llne6k\nLeta0y5TyUi0ujTn9iUl8hGF+KAtU5lBuUF565Li/11bde/qio21ufKUW4F5FcaBkZa/GHDq\nlGaAwxUpRfRJrC3Lqc6JChiJgCDgg/bh43aJDyKGM8T3ecMCxu4wv7nT+fpJ+8vHbX5WWLGw\nsCJHWWtS6WRkQbIT0OTypzIfhYJSKVEcn02c+WLIrhFOgPzCRYH2T1UoYVKI644WkFlWXzOw\n5XmRz7R2Eug50bPpkfLL7p7Gq8wyEeT3r+Xeb0u4a0dI+dtzMhyikvJK1qXMPQIAylc3eBgC\nYzFxenBBXDNxZFIhswYPJg7f423xMLqTIcQ/9EZrW75qWE0Xu5kSVyj2aIGXVXFCMM7EZEOL\n84rGoaTnssV5x0Sim6oAACAASURBVFQOh+w62j+SFMMKuNkRWFqe4/YxHob/vM/T70sr3vlq\n2U3zC2kSAYCSIpcXG/Ry6oVjtlhkiACOdDjjD9nR47p0VoJ3q5omzqw0tbvCg3GppwQCnZzy\nMYKAMQCU6pXzzNodPa732xwCBsDYy/AvHLNdO8cyJ18DUhwd9H2Y2F4xJOJWL2NxM99cWAQA\nXMoM83RgKdUFOT41+XZRTdaA9Isha7E2ARBBDTRup2mBJkgAEAC3Hjuorz1TX7MEAOQ5Zk3p\nHF/7QT6QaWKND3gKN9w4Q1ecZSyIQh2RpxI+bo/MNyKKUDxwJn19JhMZGU2+tas7aePlqytP\nq0upiCCQptMt7rMeLhpdA9tgVN189fz4vZBGxr/bknAggjBNsBRBC3hII1NhhMSxB2gEYApw\nJW5GH+bjNTIkI19cUoAR1AwFv73T+tV9A+c1OVJ19qUllmazGgBkvPiLdzusBrk1LgEnyAsi\nhV4/Nnh40J85U2ZdhbE8MXMnTy07ZPOF0jvm9PsYL8Pnq2RKmuB4HHFEowi0tEhnUspMSlmx\nXlFhUH5tQdHqspw1ZTkKiuz3MksK9e+02j/r9SaFUb3ecLpeuyeGgj0pPjWeELdg5ILJaSgf\nTEKlky9YWc74GIoVTjoCsYtfPtt85yUN6ZZU/6PIWqx92Snd+KPOl3/uP/4+QZIBl9u8/msl\n594Se9S06GzTorNZ77D9szfaXrxXcnFAYKfAw8nf0zS8/z0h5NfVLslbcsGkq9+yAIDsttNk\nty4VO5yIJtA4/K7qSw3fvmj2Y5tOiJEYB8GK2eZvb6yX3Fnxf2d97UcfL3j7xO5iraCkFq2t\nXH/P2uQLuGUJ0suZP+wWmocRQJAmduUpn11a4FJTZ7S51xToSleUhW57Z9IvcEu1QUTQ0O/7\n0ebufJ+EhiGaHJYRAQUx1+ovc4cvb7QXeBhN4iIixrC73Zl6bCq5KQt+AJCrksXLZ2rEu6/f\nu6/fSyHivjUVsY0kQosKkvNoSAKdUWogCfTYgV6f1ASjLn17oyK9HFL8cBZbxucnPkHSuacH\nvYzT7p+zrDS/WL+oPv9AjxvR5NIG8+p5Bdnf8RcFmg6HiAxYrdaiIom+Nv9aiDzHOPsVpsIM\ntRDuE7uO/N+1Ipd8+2ledUX9rX8a/7mwKITsXQQlV+RGE/oHtjzf8vSPsRBdfDLOXz/37ucQ\nkXXvnVH6hgJ7mocCYW7DwsKiXPUYe7OCOOgninSpCZ+SHG53HN7aseGn2zS2kSlTkoDJzNph\np0rWkaecZ/XLeDEiQH459fTpBduqc0IUkRPkLneyV22sY24dFVqeQAEZcfdldX2GyTSUvrgu\nb1lRcqnfQ593J8WROjlpVMrcYc4dt4yqosmfnFEB4yDACg/slO5pbNHIv3NaieRDGMNvd3c5\nQ6NnXGzRXlSXR59aA96JostRLl6bqUepKIhdzUODVg/PiUoVXVxlspROpovvvygzLxNZIZxG\nwo7+vT9YKbKh2B0wKVctf/ggpR7fdxrjjld+bf3ob0I4AACa8rmVV9/LugebH7sLcMKYWHvz\nbwrX3zANryDLF0bg/Of5D9vSPBgXUCU0gB+7GaCI0I8vqj5SpIl/Er2KemGbldrX71VTD19c\n+7lBLgDolPS8fM0BqzfEJ0ddcprI1SkCjOD2J68UmjWymxcWaxNrG5qG/M8ftcVHgXUm9ZWz\n81U0CQDPHOk/OTxaKfHDFWUGRcL9pc3PJiWIRnhgZ0eAlbg5IBH6wYoyybiw1RlkeNHH8u2u\nEEmgWSb1ArN2GuOwNB8IItDai2enO4jnhL2ftjNJjXwbzGW1qaav/55khfDfjUDfydanfuhp\n3Y8BtBXzZt/2F6V5XDe8GIuHH7zCfWLXeHZW5JdXX3efacFZiMzOdf9bwIse/YMwjlJ0+d0r\niDKDaPOzD+/G/rETkk9Y1N+7rDZ1e5Fe+Uy+/i6b+7hvdA6DIgiFjPBLXQZFIV4qxfFHK8v1\ncQrE8OIhm++9tuHU+vc8FX370lIZiRhB/MPuHg8TPcvsPPX1c0edCDkB/2V/743zC5LUMWKH\nF2CF7T2unb3upGGsVK+8Ya4lVuxo97N9PgYDLtDIC7WTCHPHm7wkTcLNShS9UTVnWYlMIaXW\nRwb6UmahCRKtvrAeTf8S5peBmZeJ7Lg5vaiL6xbc+5bIcwhBhnlUkWNcx7azniF18SzWa/d3\nHwvbe8epggAQtncd+/1N6uJZC/7nNVqXTTz7soCDnNjuJAq1yCRdPyocHGAe3C40DRFFOtlt\nS+lLRxYaRZxaLHigRNtpUhpCwuldHs2IbLCvNSnuXim7Zg7z4PbxXFJvigFNBKsntGNd5fHW\nhKpKXhR1KoWkEEqqoF5OxauggPEvdnYKaVoGDgW5/QPeFcV6OYluX1ry4M7OWpN6XXlOrooe\nCnBBjhcBBgPszh63M8RtanHcMM8Sf3gkjFPLyPOqcwUMu3pHq0EQQI8n9JvPu6uMShVFhjiR\nEcQLa01m9YQlkBNwtzespokCjfwU5FDiHfA4g8f39io0Mr87DACGXHX5rDxaRgKAxyGRRiAK\nOBhg1ZNR8SxjkxXCmYCgaADwth/0NO8maIW6pF6RX6owRW95gv2tRx+6PmRPTkSUJMNvMdDX\n3PrcPbNv/+vUXHSWU4N5YDvzyx04xAEAUahDRVpyaZH8R6tiRYrCgX7/qicjFtviyWH+0w7l\nXy6U3bIEAEBGUqcX89ujXwmORPefX3mgJHqgPszf/25H/WAAAHCXO3Tnu0g33vGxMH3NYv+g\nL3WjYiKdYwOc0OMJl47U/zmDXDoVjDAQrcFAaprcWJu3vDi6sqimSQD6jZP2fdZoke6JYf9T\njf1rynLyVLSSJqhEC5kVxfp4IYyckhXEE0NR39HblhRPVAV5EQ8GmKcPD4Q58ao55gK1fPIp\naRi0RqXfGUp6L9yOIIwUU/o9Yafdv2RdJUkSBClxIoRALpWFlGVKyArhDNH67D3Wj56M30Iq\ntaUX3q4uqj35xN2cf7yWu5GfSDo5dB0bV1iQZbph/34w/NNPY3+K/V7o9wr7rNw/j2kO3EoU\n6/gP20J3vpfUaCL8k82yby2ODLjKv1zoX/c0HgoAwGsL8mMqCAAeBfW79WV/e6kptgV7GSAR\nZOpjEP3KzLIFqhyh9jhHbFLEERvS8jyJlB+V1NxdOngR//VA37rynLMqTcfs/jdbkksVk9DJ\noyqLEMRUkOHFDzocjQM+NrFipNUZbHUGEaCfr0t2rjAqqVFzVinSGMJlAgM8ftDKCXhjXd6c\nPOmqxPHjc46dKx70MbYed1GF0WjWeBzJ9nJ5hToqxZcgy1SRFcKZwNH4SZIKAoAQ8nW+8qvJ\nPWGCCsapIhb4U+kllGWqSNfCAg8HmV/uAF5kn5Bo7Y6dIaFpCADIKiNRn6c9cQf3whGx032E\nECDRtfnCYykaI2CiUCv2x0d1OPXGiRLxg0H4Y9i/z6IWCFQ3GLj1s76dlTnubyycVZN7WpFu\nr3XUqk1GEan2nSk3YckbtnS5LBr5P5sGM4eDJIGWFkrUir3WbD+W3h0GAx4Oskn22QyPM54K\niIn/IkiERBEjQEsKZqygDQe8DACU1eT6nKFh2+hHabJo6xZO2v40y9hkhXAmcB/fGft//LAx\n4TUHyQPixjp93bKsCn4ZSBSkBPhtneIJCZM2AAAC+ef/BTAgJS3/0Sr5vWtkdyzjt3Zyj+6G\n/ASP7PNOpDicYUAmFSScF6X8BwCAsbqNWroeIDfAXnpkqMYerB4KvXNh7eNb2ou1ipwq+pDN\nF+SEQq3ijktn3/tykg8qRoCqCnXt/V7JJ4+w6eRQZhXUyMiLavOS8l8AwMfwGVQwwrZu15Wz\nE5xOO1yZ4i05Rcgk3bgz4mf5BRZdiyMwHR1604Aik5+IQHOXl3qcQZ87RCAir1BLp6+MzDIl\nZN/fmQDHNfKN/1Wl+4WlFcgMP0kE8hxLzVcfnPjVZZl6yLlmsTWNG2eGasAR8cAhLnz/FmRW\ny25eFLrh9bnFmqNxQmgMcrJUlxYEwtExXLMBoNuk+M4Sc8wHfGtNzn3vdS7r9lx8z5bWfNWv\nzyzHpbrKHGWQFVpdwT4fGwwlZcogAsGZi4tMeoXHx5h08jArHEzxHfVz0o7ZWhl1frUpXyOL\nhHTOEJdkt+0Yq7sTAByy+QDgsln5MReYoWDadFmjkr5idr5SqlVFZtQyssMV9HNCmBcVMzIn\nSVJEflwTRL1RpTdmPfpniKwQTjsiG3Yc3jyhQ1L1Lq00YgAEpgVnGhecaVl1Bak41cWMLFOC\n/L61/PutWGpYJxdYxJNSEWFKzRn77GFyRanY77vKHthfqm3Jj67h+WWkSCAiKeSiSUiWH4lv\nzcOrS+O7YYgI/XVV0bJuDwDU2IM/+bDz9ivrrCMJNZ0dzjuaXcXHBjFCB4u1ry7IZykCEeix\nTSfSXPIY+FjezfDzLdogJzx+0FqklSfFdkZl2paB8Ryz+6+oHz2w2qQiOhzx7wcCuHtDjRKB\nMvOcaXowBjfDYwxbupznVacW8J1aQUUKcgU1a1GRMn3HxCzTSlYIp52ed/8cGuxK3jrB31Ha\nfRHkLdvYcMfj2RnRLxXknHz1nm8yD+4QDg7g4QCO5EooKMU9q6kzq7h/HJM4Bsf+iX6UuM8L\nIgbAcl78/eut26sM7XkqQ5Bb2+5OVkECIbMG9yWZ3CZ8JXZWGT6eZTxekJwRM6CX++VUpB6j\n3BEsdYU7TUoAIDC+6He7845GGwPN6fcv6PP998W1QlxKziRE5oN2R6szyArYHmCHgmxDnmb2\nSJKOiOHTTke6prvxcCL2c4J2JAWmUCM/vzr3vTZHzPRuTZlx+wl7tUk56TwXikAKighx4s4e\nT46CPr04yStnan5uepNKqZJZygyGXDUT4tzDQaVGJp9IglKWKSH7jk8l/u5j9s/f4PxubeV8\ny+prolUTLfsgVfjG9ztCJI0FLoNq1n7jt4VrrpVUQdYzFLR1OBs/Edmwvm5Z3tKsJemMQjbk\nq164HAAAY7HDhQcDREMe0isAQPHghvC9W9JYpo1+RsRcM1mfi/I12B4gRXFdq0u6U5JWrnhw\nQ/i774/8LfF12V2u/8U50k4OMl5UcgIAsBTxQb3JOzIKr+j1xVQwwrx+/5Ju957yZPu08RCL\nHVHckh7G8PzRgVm56nK9ghHEpqHAYGC8Tcr29rs3lJtiL3ZFiWFxgc7L8J6wYNLQ+62evf2e\ndRVjO8emgxdxmMMAgAFv7nIutGhTm0mdIlqDYtHqCjbMdxwfPLq7RxiZ7i4oy6lbUPAfUjv/\nJSErhFOGbec/Tz7+PSwKADCw9YX+T59b9NNNhEyBaBlkEL6MoaGuaoGnZV+6HTQV8wrXXpe6\nfWjfO+3P3xd2WGNb+j78W+6icxq+9xRC2QzsGQchosoIVdHGh/xHbexjB9KoYNy3gSDkP1wJ\nNKl65tLgFf/EowqR8o3xMfxbzXG1EylfFwVVP+j//estm+uM787OxYmPr+z0kCIOyMi7Lq/t\ny4mV26O1SKLkoHo4NDkhzBDiNQ8HmocDGY5FAEYlva4ip9URPDzSr2pzh+uILXD9PEueKjqd\nKKeIPEoWCS9XleTs6/dqJl41EYMi0IaKnG097tWlhqWFuilXQZIiFp5RIfDiwe2doUT5H+h2\nyRVUxez8dMdmmXKybZimBoEJHv7FJbFmhBiAc9sJWm6YtZz3u50Z1ggzrgdy3uGIsqZCqw2z\nbnk45sQdw9Oy9+hvb0htBRUcaFdZKjWlaR0Os8wAYosjcOazeCh13I986nHfBoyBx/Sl9USV\nkb5hPlGiwwN+bA9I3jfhQT9wYtq7Kl5U8DjPz53W7VXx+EDJaLOFBf3+H2zulgn42WWFuysS\nFE5t9Z7e5U16zi21xra8GcrgIBGqM6kWWLSX1OefWWHUyam5+drP+7y8iAkEACjACU1DgUUF\n2lTLbJpE3Z6wWSXTnkK+ZXmOck6+ek6+ZspVEACUallJtam/0zWYPKENAMAyfHHVf65F1MzL\nRDY+mBp8XYcFdtSkEQEGgKE9mwCg8Mwb85ZeMIHnGhl2ZPq8DO3s2YC78ecXH/jpucH+BGtm\n27aXYo0pkvCc3DOBy8gyDXCvN0Vju+QQCaVu5F48ErEPJYp18u8up6+ak+5pcYAbfZKMK3eX\nNg7qQzwAEBif1u29/YRTc/MiYmXJifrkfJC9ZTq/nIpXQb+c2ls6ruEJAVTF1QimijMl4jEn\n/s6tNn11fuH6CmOkr5OaJttdQZ2cvGlB4c/WVN23pvKauRYCwdFBPwAEOOHd1uG/Huh7+nD/\nIZsPY1BS5AftaRJ3xwcCiIWbp0jqR2IwqQAgkNIcMQLLSN/+ZpkmskI4NbCepAJnBABcwAUA\nCBENdz1JKSfc84xUqDMMaZFxxNfReOwPXxO5Ud+s8FBKv7URCDprVPgFI/aOlN9J6kDSRhGL\n3aPOYfSNC5CU+ctYz5L8WIUzBAAiQnvLdLeuKzl+Rqlyy01cVfJymkMt+8W55YO6qBLYdPKf\nn1vuVI/L5QsD1MR1Ykr9GvMEGjPRZpYp+cV6GeHmBUU1RhVJIBmJ5uZpbpxf4AqzIV74097e\nz3rdPZ5wiyP4StPgB+3DIU40a2SfW90drtBggGWlbHcwQIAVYn7f0weKK40BAIFAlQ1mAJCr\npN9PbRpL2CzTRHaNcGqQaY0AyVNT8e2WSi64rfPVX0/oOUWWyVAyESPY39b91h9FJkjrTHnL\nLlIV1bqadkrubZy/bkIXkGXysILQ6kAqmig3xOcokXMnsvAjI8lqY+wvolCr/uRG/+LHILkv\nUtwXQk4BJ2RyGwOwx7U0Egj02wO9dNtQl03CAaCxSPv1a2cXucMkSXZraWEi6RtyOUEQSBTF\nSSdYplbvlegVMVe2CGa1vMKo3tXrSRIzhOC6uZbIG48xeFleFmfgGeKEbi9zdNCnkZFaGbVq\nRlr9IYAdPS6aJJxh7jvXLQwFWNcQF/AyCBBOvFVABKpqMKd7nizTQVYIpwZN+XyCliXNZOaf\ndmHkP45DH4fsXeqimrDDJoR9SnM573dxSct4Kes78rwS1j2IsZjwiNQyUPebv4v8p+v1h6qv\n/zmp0AjhmD0HAgBEkCUX3Gact/7UXmWWccG9ejx053vYHgAAcnGh8qlLyIao/tE3zA8/sB2n\n951JgBf9y59QPLCBOq8msoGck4/yVSmHx30hxgpumi3qAX3CdF9/iJOsd4xeAoG6jcrV8yxy\nD3OiezRnFQEQCAnpm7jl65WimGbNUgqaRPPytTkKyhHijtr9vIj7fOG6xKAwXyp+qtQr91kT\nfkoWjezsytzY7QdCoE9cKdza7drREw215+ZpBv2sQUlxgqiRTXg8bBoOFKhlOeOww0YICrXy\nf5wY+u8r5/Yft7f5JNzPKYrIyddUzs5XZbtMzCxZIZwaKKW2+oYHWv7+g9gWTens4gtuA4CO\nfz7Q8/Yjse1yY+HSX23teu03Pe/8OeEpUkYMb+v+SAPe8dddiBzT+vSPFHmlRF4x53VSKp2m\nrEE/63RD/Up1kUQXuixTjnBoIHj967HaduFAf/CilzTHbkNKGgDELg+WavIgjYiFw7bAJS+p\nP76RWl0GAHg4iKUG0OjugIj42AIDyEjCrMauUGQR0bWs+LEKLU6xqs2MSSf//hXzcvWKV7Z1\nvPlZl9PH1BTpv3nBrO5B/69eapQ8pChXffnqiqc/bOFSHXCkyFHQ31pcFJOrDRXGxw/2vdc6\nXK5XxieqSFqGkgRo6IRxrNygzBC7dnvCO0daVSy0aGMV/XKSAAAR4wkZkwqC+LvdPdfNtczK\nHXvWuipHdfeyErkzmOLXE2XxuiqVVAviLNNNVginjML1N2jKGuy7XucCHl3VwoK11xG0PDTY\n2f32I/E/LMbZ3/TILbO/8wQf9PZveQGwiAiSkKuEUMr4iMc1iCQfhHGko1P5Zf9Vftl/Tfrl\nZJkc3MvHkhxexC4X+7dD5Lx8cnZe8Mp/QMKD44iZeJF9eHdECMP3fgq+1PwpDIBEhIik+AwB\nUaTVtn/3n5+0vf7cIaeM9ClIMnObhkTK8jUbV5RdvKKM48Ueu//y1RVXx3V+WFBlytXKf/C3\nvfHNvQmEzlxUdMclDW/s6BLHfaKL63Ljgzajkt5Ym//C0YHf7elZUaRfWaqn0piFBjjh0b19\nGkXCfKnkrpHmuBjj+C6+GyqMSbu5GV5BEqpxN58SAQkYv9489D+rxrN8C3KSYNOoIAD4PaGs\nEH4hZIVwKtFVLdJVLYrf4utoTB3nXMd3EBRde/NvKq/6SXioh9bnNT92p+vYjqm9mJ5Nj5Rd\nfFeGbsBZpgPxYH/qxvD33gMAkJPA8OOzm018zpZo9qOwq2dkG+7NUT6xovBIgUYm4hUd7m/u\nsirZpFRMTMzKa+nzPLypSRjJeRFETCAkjkjB6bPzrcOBXrt0Gd/GFWXnLCn+yVP795ywA4BG\nSd9xScPFK8oij+47OfTbV4/gRPUVMZ5VZvjsuO2xd06M9bKiNwEIQbkhuSSj0qBECHwM3zQc\nWFOeti6+38d4OH5+gabWqN7R42QEDACdnrAgYluAxQAWtYwiEEC0RTxCiBi5XppAOSmu31qa\nemBn5/+sKpellGRI0u4KAoDuFAoW45GnXE+WmSErhNMLqZRINxeYkMhzBEUTtNy6+ZmBrS8C\nFsdp3Dj+VReRY0JDPSpLcvO2LNMKlljdGfnQGAEwmkTuiGj1Cfus5Dxz7PvhVtI/vqjaoaYB\nIATwWaXh2zutyTmnBCH7wcp9KY0gRIy/ef6s+jIDTZHtVk9rv9fmDKXOYepUsjMXFd371P7G\nkSIEf4j71UuNlhxlXYn+nr/vP9gq3UPjeJdr0JncTk8KBAAyQeTSV+nlKOibFmRqP2TzsxfV\n5kXaOa0q1Q/6WYzgmcMD92/riKxfauXU5bPyNDKqcORzicWWST5tEVxhjhVEHyOYVGML4RG7\n/8CAFwAYcTKTN0moNHKtQTn2flmmgawQTi/6miWIJLEgJGT2mQoj7mvtL94/sOX5kX0TLBzT\n5YuOY/1i5EabpBWm5HL7LNMNdeks/q3mxG1I8r9pkPjwsTsUWP4EVlIQjGa17KwyXLvfdnqX\nR8GLRwq0eyp0qf0omsv1y9eWMx+cTD2HSkExnPjfT+xjRmZxS/M1VQW6ln7PwHAAA1QX6X98\n9XwR48aUUrx3d/f++c2m1n6JMvAIJXmaw+Mu4FvU5z1QrOt0B5PyYtpdQYzhjDKDZOeHDleo\nRK8QMT4+5L91cfRLLiMJo4r+097eUNzUtI/hnzk8gAG+taio3KAEAEVcqLev37O+PGF2dF+/\nBwB6vGFTmsKGGK802Q7ZoilpqZHlRJEr6Dmnl0j2ps8yA2TrCKcXSq0vu/RugITBrera+wAA\nY9G285XkA3DSvolI2tCk2algzdXZwsGZBLvDwRteD9/05qk9TZpbIIxjKggAi/p8FxwfNgU4\nNSMs73J//XNr6iHqihwAmFcpYVBSV2J44IVDTJxg9Nj9AHjQGRIxYAzdg742q9cu1eevtd8j\nqYKRbyJJEF9ZW1El0XFX+nWd0+RUcPitk8PuuM7DzhC3qXUYACxS3RiODPqfPNT/x909j+7r\nS0ps+ajdkVoUGLmwgzY/AHhZvsszWsP+aadzW7eLEzEAMIL4cYdjV58HADZ3OsNjpfmE+ehv\nz6Cgr59rybzzmBAUoc5min5xZCPCaaf8ku+rC2u73/wt4xxQmiss62/wdTTad70hN5iFcMra\nTIY7wgxdeaVwHdtu2/6yZfXVk7vsLBMldMsm7tXjCR8TiQBDYnJKprltlKvEw5l6zMYodCfk\njmrDAkciOrFmvO76+QCwpDb34hVlb+3qjm2/dn01QuBPLJnAAFuPDMTW+1hOfOifRx7//hnx\nC4oRVGnWwxCAnCLvu3Fhjkb+jfPqDrQM84IQe7GXrCzbdmTAlZTyiqFfL8MIu8Pc7/f0zM3X\nGBW0I8QetQciDSgkS93fbxvGgJ1hDgBQEB0e9M83R1tMdHukjVoA4OCAxxVirT4mzI9elYjh\nw3bHxx2OxSWG/T2eWD2fM8T9cU/P5fX51ek7Ap5dZarPVWtkZJVJRZ+ynT07jkaMWaYPhNNX\nAk0HVqu1qKhoJs/4pcLf03ToZxcKzHhWUJKQGkDHXDDEUH/7X8wrLpv46bJMDOxjvMZfJSdk\namSyK2ezT0nXGEShCODFuN4Mk6QlX1XrYWDEmotcYCEqDEivpK+YTZ1Xs+v44L6TQySBTp9t\nXlKbe7jdcesfdmZ+QgD40dXzB5zBZz9qhZHvmk4l++pZNX9663jqzpesLLvtogbtyIzisS7X\n0x+2dNl8lhzl5asr1i0o5AXxly81vrcnwfmIwCCmf9E1RlXSGmG7M/hkY0I6EoHQnacVm9Vy\nAPjLvt6+9OUlE+W8mtwzSmai1h4A9EbVojXS7UH+A5l5mchGhDNK2/P3jksFJRROarSIbUun\niAj6Png8K4QzAG53SZQl+Fn2qUZyaZHY7cZpMjMhOgV3qiFFMStqj9/BbToJrjD78lGh0SY0\n2gCAffqQ4r61K366dkWcWUltsV6ron3BMaIQhhNvubC+OFf9/t4+t5+psGg3Li+tLNC98Glb\nfGyHAF25puK7l8+Nj4vmlOc8dMsyAACM7SeHn3uveTDAHm5zJp0igwoCQKsz+Eaz/dyq3EiL\n+RPDgTea7Un7iBhv6XRf2ZBPIlSiU0yVEC4vNsyYCiKEKhuyvSa+SLIR4QyC8Y5vVidNhyKC\nUhZUBa2jGQ3pw7zJNMWmVPpVj0ukS2SZKvgtneEffCQcGUzTWQkAAEhi5NEp6myeUg4ov2e1\n4n/XAwDzx93h73+QdHZt+11ESUJziR1Hbfc9vT/ERiPI+ZXGwx3JKvXUD9fMKjEAQO9Q4H+f\nO3is0wkA1btsWAAAIABJREFUerXsytWV248OtPR5AKDcovnBV+Yvqknt4Q4AwD66b/j+rcOi\naAhx26sMj55Rkln50r1Wo5IOcEKIS/sOkwgpaCLATo1XtVpG/vfK8glV1k+IkmoTJSNddj/H\nCCqtvLQ2V5eTzRcdJRsR/gvDugc7X/0/94nPCEpmWnS2zGCxfvRkeLhXmV9WuvFOy+qrASFK\npUteF0RIV704aG2J5b2cyo8PEWRS2yaZzjR88EN99RJa95/b1WX6EBptgQteyGhshgEQCLEe\nSRP5eEdEE+Wp8FDiRIIokrPzhRPDgAGUlPz20xQ/ixrJCvtSEmcEUdhrTRLCM+ZaXvrJhh1H\nbb4QN6c8Z2ld3q9eaoxfSrz+zJqICvKC+N9P7G3vj9qFewLsUx+efPS7q0ryNAQBuvT9GZh/\nHP3zC41vXFHDE4jAcM6J4VXt7u3VEw6zRAzDYwWvAsYxFaywaAUR99j98TvkqmQrSvQMH2n/\ny0Q8uBUyMswmVXbCihLD6hLD9KkgAPS1OxasKi+vy5u+U2SZEFkhnBqEcODQLy4N2Toifwas\nLTAyjgUH2psf/y4AWFZfnbvoHOsnT8cfiAXOtu3FzE8eGw8T/5QAkclCGLR1HPvdjaRCU3vT\nr80rL5/o68qSGfbx/XEqGPtk4j+i1P+Mm5EjiDyNkCSEgBSPbqSWFYGAQZHwK0ZSsQX78B76\n8uRWlOYc5RWrR9elfnzNgjXzC/adHCIQWt5gXjwS5LX1e2MqGEEQ8Uf7++6+ch4AnOh2P//O\nCWvLcEGAu8qgmnfH6UR5VOqef/34KwujM34igvdn5xqC3KnHxGoFGQhnivzmlBvf35fcg0XE\n4ulFOgC0piwHA/T7mNYwX1WR8+jbTfG70QRaXZ4zFGB1ivGMjZN8LRhDT6vDMA5XtiwzQ7Z8\nYmoY3PVaTAWjJFo69r77FwCovPpemX58t4FxN6RJXeYy/PIEjpUbCxR5pYggERoVTiHsP/nE\n94O29nGdOss4wF5GODoonogvKkennvOSdBIAAJokz69OegDpFeRCC9AkpIzX9EV1qU/E7+zm\nt3aOeb7ls83fuXTOHZc0LI6b6hyWSsUc8oQBYH/L8Dd/u/3TZvtJUdyqJG8Ph7ef/YywP5rM\n8okqOb/UraIjb86GhWNMfKVbsCEJ9OR/rTFIlVXE+PhgH59S4S7EufYigCKt/MxC3ZUrylc3\njFY+kAidVWl6fH/fM4397nBylH9yODAcHPW3wxhjgFZnsHVc7gHJBP1TltST5dTJRoRTQ6Av\nZR0ucTAM2joxFq0fPZHSuTDNXWXK2m38PumTY4BxDsy+47HBbS87jm6JP1DkGNfR7emMZkL2\n7uOPfCNk6yQo2rzyiqpr7kNk9ruRBl4M3f0h+9d9wIspBgenJoEEoi6ahYeDwsEBCLIACKll\nit+fK7txgdg4yH8ych+joJRPXITSiAF1VhW5tlzY2pW0vfnt5jlrpfMSbc5glz1QkqsqkopR\nqiWKAqG2SA8Af3nreHwDChGhvy02L7nrPc1n3wCAofRydaA1+VeQRLr38Yo1lftbht2BtA2r\nAYBG6MyavCKtzM+KB/o9zY4gAJSnmLbwnDBk9dyxobqCQl2esIIk6nPVn3Q6nSEOAF46brtu\nTkGs6xPG8OIxG4/x3DyNRSv3MUKVQbGl22X1MQAwz6w9q9JoVNLj//hVGbU8ywyTHeymBoVp\njDtcpbkMIcK2/Z+pD01i7Mx8SNOfbpHczoe8ktt97Y0H7j8vIr0CQN8Hf3Mc+PC0h3ZltVCS\n8M+3sX/aE/3j1HLN5D9YyW/pFE8MYxGTc/MVvzyLWlsOANgdFvb2YVaglhVHmvGqP7iee6tZ\n2GtFRiV9+WyiIq39JgC4VpfrIkIYvWPCAKjJz6R2uGc58ZY/bG/uiRbI1xTr/vrdM1SJTYss\nRtXlqyte2z4aUJpzlFesqRAxbutP/kZ1GxXM260aTgCarDJrDtv9kt9Vt19CydQKKt+g7LR5\nR2JriUO3HR5YWC2dmBNBJyfvXFqiHil2bMhTv9s61DQUPF8qnScUYGUKqs6kjvnadIx4CPR6\nwr/b3VVuUGpk5OWzzK4wF6m7P2L3H7H7KQKFMbaOZKgeGfQdGfTNNWtumF8gCiCO41tRVJVd\ns/8SkR3ppoa8ZRd1v/UHPiitNABQfO63HI2bQ0PdSdsnvMgw6RUWDPrqJZKPHP/jTUkDemio\nZ2Dbi4XrvzqpM/2bwz1/ONPDE/mAiBK9Zs+3Urcjg4I6O3E6FCH6knr6kvrxPK1rRbGcIuS8\nGJsLDMjJpqrkTgsA8P2/fh5TQQBo7fN+/9Hdf/3uquTdLp9bXajbfNDqC3FzK4xfO6cukiNj\n1MoHE9xnsD7M0yoZUAQA3HrN/Dsf3iVgid68Shkpl1HuuOlBpYz8+w/WvPRpe2e0RbD0m2hz\nBtus7gyvfV2ZUZ1Y8n9ude7ZlUBLuZeptHKVZtTPBeOE3wEr4BZHkCbRZbPMjYnNsy6ZX/BJ\na7KNXKeXWXXhbIRgoNvVesQmSHjTIACs1Mgq6/NNIyYAWb4MZNcIpwZFbvHcu59VFUYbqOrr\nlpVedKc8pwAAFKaimq/9SpFbcvSh67CQvPAwYVGb7NybedUVhtkrJR9i3Mm1WQDgOLR5kmf6\n90bE4oA/eSOBUKwT0FgWB/Eg/bS4alWsLPvtORWekeVDh1r24NkV5QskbMAa25JH86OdztR4\nhiDQJSvLH7lz5dM/XHv3lfNMuuhln70kycwWrWtx0RvrIjPGC6v/v737jo+qTPcA/r6nTJ/J\nTCY9QxohoYSE0EJHUFGqeFexYwddXQu7Xt3r3tUtrq7Xtta1rW1X17YWbCAgAqL03gRCCElI\nb5OZybRz7h+ThMmZM8kQMiHh/L5/+IF33pNziJl58rbnifv7vVOmjkw2h5QWyhkU09h5kWxO\nUVpagmFsTlejvQB7l0lYkk3SbylL6b5amUOcTW6fqFdZkwwuLb+j0n60wSUSkh6jkXQbHKdP\nHhQzPd1ySU58YZJxos28dIyt0Kxze6TvZa9XaKx3+v1Ccrplwqwhqs4Da0rp6GkZ0xYMm3Dh\nkARbDIH+BCPCXhOTO2H84+s9TTUMp+L0MYSQrEUPCl4Pw6sIITsfOe1T7YxKo7EktdaUC4Lc\nO/90Rh4JExd2UZuQsoxkrykhRGXqavJNuRjK5iX4t3VKbsLmxvkjTDMdnH9bx7NhFu3OkFHH\nj/vNlOtTDINrnX6GFlu1g9LMwaUEAzxewR+SBEAQxFaPX6uOqK7QrXOHNja4vtxaJhDCiOT8\nQ3W3aNSapy/u6JCXGfv4kiJBEJ/6aM8nP7RVKJw5KqW4Ulp9c+O+KkLI+aNTNx2sWf6jdOKk\ng17DabusedTiltlQ+s2RmnXH67NjddmxukS9imdocYPrm6N1i5OML3xxYN3uk4FuqWbdoDgd\nqesUNRkNTxnKUlpkiykipwJYToppV0lDcE+bUbVz3TFexeaMSk5IjRk5IW3flrJWp4cQwrLM\n4LzEGGvYhG1wduFAfR/ZeEe+p0lm4NVDnaOgSAivMXpb7V1ERoblMi67L23+3aEvbf/D3ObD\n2ySNBQ+8b8mb3isPe47xrTzimP3P4BY2w+wvCTdfF3Zjk+api9R3T+j1x+uw62jdym3ldqd3\nRIbl0skZKl5m+mf6si88ncsIqzj2+6fndfFlHa2+2qbWlDgd317GobHFXbqhNKnOZR0Wz45O\nDndhY4u7tNqRHKuLi9FMX7ZcUviJUvL9U/N5jiGE7C6uX7ur4uP1JR6fX8MxSXq1KIqlza0M\npQ8tHrPjSO0nG0qCr02J0994Uc5Ln+2vb3EXJBqvCMqhQwgpaXS9sl0mKTkhZFS2VTIm5jlG\n8mAsQ99aWlR6SFpzqt7tf3VHWVP7AUcdzy4dY4vX8YQQhqFjZwzWm9SCX2xpavX7BINZw/dS\nzUIlwIH6c5YmIS00EPb8RBWV/s2QnueoOOS1S5ODdNxJ8PmK33+UUC5t3h2SF/Pvf3/TPeO8\nLR2/3tKUGdcgCobDzcrWr73R88RG/9F6JssiHGvw7w/sgYwg92vQWRj379cwgy38PJnTDr2i\nYLC1oLsdGZdNy3x39ZHglkXnZYXr7Gj1PfHBrhVby0SRaFXsDRfnLr5wCCHEbFCbLx7S7fOY\nDWpz+4LcoHh98clOg8JEiy4QBUWRlNU4Vm4rZwlZUpjasduzrNlddF5WTrp5/ND4rYdqTtS0\njdu0KvZ/ry0cnGz6y792EkJ2VdmtOn5GuoVlKCGkpNH1wf6qcI+0P+TXl9C6jCIhcamm8iP1\n/s6Zg2LV7L0T06t0/LGyZmp3j0k2dtS1FwSx5mSz3hTPsNQUi5QxAwD78MMP9+X97Ha7ySSz\nG/ucx/Dq2q1fBbdQynRbiTfySNlaVyZ4XG0XURpXOCtm6ISWkj3tN2v7Qo0HNiZOupQ3dJr2\nZDhV2rw71dZUUfDHZI8bfterSdOuiOy2CsWkm/mrRqp/Od6//aTv846TM+GOtIT+mRKREK/f\n99Vh/roCGrKs1WfG5yYQQn4ua/L6BYOGv35WztJ5YffjPPrujm+2lAX+7POLWw/VJMXqcnq0\n3KXimPV7KoNbbp07dESGhRDyzreHn/xot8vtm58TPyL+1I4Sk5prbHRlZcdpVOyCSemJFm1y\nrG56QcqvL8/3+oXfvr65vn0P57FG10/lTYfqnN8fb9xworGjoFKSRdvS+XRg6MxwqOHplkUz\nsh12t6NZevKPJWTKWNuoQWa9y8t3rmivN6qtScbglsrSxv1byo7srawqa+I4xhCyGAkd+j5M\nYETYR8zDJ+uSMp2Vx0hg6xiloth9VevTLcrUdpFI3E015rypMlf5ffW716ZeKLM0lTz9quTp\nV3X7SNDBv+Ok5+kfw71KdZzo9BFCqEHFFiT6fuic64QSQkSx2e1fW8Jckx/lJw2LUnLLnKG3\nzBkqdlfz2esTVm2vkDR+ual03oS0Htx3/sR0vyC+vfLwyXpnokV79fnZl0/LIoT4/MLr37SV\nNc6NC1lRc7aFMTXPLpycQQj5bmfFrU+tl1Z3IsTlFUoaXYSQWJPaoOHTEw0zRqVMz0+58P4v\nhQiCXwezQf0/V48ihOhNGkJkqjD6PH7ZkGY0d2o8ebzhYPt3z9nsPrCt3NnizhqeGHohnBUI\nhH3k4Mt3B6IgCQwDwy7NRjoIZHieCILol881ZS/ekTLjGtmXHCf2y7ZDhLyfH/Q8t1kobyZO\nb7j/j/zlI7SvLhD2VBODih0RTyh1XPyOb3Xn3EOBYChX/LbvdZtZs6651ReSVVy2cm+EFk7O\nWDg5w+sXgsdSZTUOj1cIPI+alS5qMpQIgsgwbc9aUml/+O1tnvCZuAkh9c3u+mZ3gkV70Tib\nW64nw5CQLDSEY+mVM7KTY7WzxtoMWp4QEpdkPLa/OnRHhdGi9QeOqQS9wqnYxM6VK0p/lu6l\nOn6oNiElxmDGuLBfwPGJvuBzNjXsWxdZ30gXDbUJGaxKR8LPrpZ8/CTD8qHt9XsifBKQ4Xl9\nu/PSf/vWFAuHaoUTMkMEQkSabNS9dxk1qtlJg9j8RMIy/l2V/OwhbJHM+j9bZAtt7IcSLNpA\nSAiWnXqm81eSGcUEizaQ7VoUyYlmaWo3H0M7oiAhZN2eyq6jYIeth2pWb6/QqtjcQdKJ3PMK\nUmwh+XTyMmLvuGT4f03N7Pgn603qYWNSKNPp7WkbbNUb1eXF9ZI3oc/j9wVtQRJF0SWXCqcs\npNwHnC0IhD3kaao+9Oqy9Tdnrr02ee21yetuTCv9/NlwnZsObyOi2O2K4GlhNYaY3CJCCA3z\nVd1NlZrEjND21toTPaoMDIQQ0vzwJy3xlQIXttwENaiNh+8KHmG13v9ty9iXXb9Z4d9URphO\n7zjVrWPYcQNjEzVDqWT5kOeYm2cP7d276NTcjMK2Srxf/FzbGrR1xSeI4yamB3euD4mUJPx7\nbN/xBkLIrNG24F811Tx7/pjUR28drw9K2apTc4F84hKJg8yTZ+cOyo61xOsTbDF5RYOG5CcR\nQlwOmayhzUFjZUqp5ExhANKN9h+YGu0Jf6tjx58WBmfZFrye4g/+Qllu0NxfSjo3H92+9+nr\nCSHyKUVly+vKzI9Km+xHd4xc9lbL8b3uhkoih4rEmJnvqDgs+UoMxzOczEgRurXljqmqDJKx\n8fxwHWhOnGn/HcFR0PftUfcTP3S8TgSBsJSbm8uYNdzcIfxlI6L8yL3psmmZsUb1f9Yfq2lq\nHZxiuuGinJ7tlOnaA1cWcAxdua2s2uF5cWvZeRmWOB2vU/MzZ2RZEjoN3XJsMhWdaFtxJemS\ngUnLN9jdr319MDhUur3+B1/bMizN/MqyaWt2lJfVOGzx+oVTMuJM8jOWvIrNHik9H8LxMp+i\n9gZXXNBmmdQsS/F+6abx4KQ2cHYhEPZE1YYPXZXFodHq2Md/DQ2ER975nejrpppagLTeRJgX\nO1Ssfnv0H77a8cgvWquOESKNlXxMfO22FaGXWUZOp3JTptAFwe3acPtwweMyOEd59C0qhzQ/\nFjWq+cUFmr9cIFlt862SrAsS4hfFeqf2kyuj+sBRMrMwZWb7iC1KDFr+4evH3H9lQb3dnRSr\nI4JIKGFD1gsJIbPGpn60vvjA8VNHIIanW66eOTgrxbT06fX2oBKGHMtMGZm051iDI6SmBCHk\nQGnjK8v3P7akqGcPbLJo60LyA7R2LqCYnhtfU9Fsbzw1hGUYasuSSXoHZwUCYU84yg4SudAk\neGVWAuzFXaWmjGhJMMwGmrpdq3+8eyzp2H3auQ+rM4SeXFTHJufe9H+R3PPc5/b5D9fTWC2T\nYuy6o+j3/XjPmMDplKphO2uG7M384UJTRcc0naj//GpuTo78hhOvzG4mYWMp6XabZtR46511\nxQ0JIxMZufm6KBFFsmp7+dafayghE4cnTi8Ie+4+QKvmUgOPx4T9LnEs88JdU95bfWT74dpA\nqLt0Skbg+OAfrx/7p39uDxyo0Kq5e3+Rl2OLOV4Vkhuv3aYD1a0uryZkETQSsmUFdSFZ5Qqn\nZh47UF1Z2ujzCoYYzeC8ROyU6T8QCHtCbbURufBE5T/aero02HGDrk5RhN0s4Kk/GdqYNPUK\nlRmbtonnla2tD6wSm1oJIdzMLO0bCxlb2H0f5aveCM5UIHC+4xPX5H26mPoDB6gpNzMrXFRj\np6WTv/0kaRQF4t9dxRbIJP+MKneN4293fP5FnNbLUp3Hf51WfcMzc/vm1g+9te3bbWWBn+nP\nNh6/ZFL6A1eNOvMvq1WxN83OvWm2NCnBhOEJHz10wb6SBp9fHJpmDiQ7HZFhYRkqe3bQ6xcr\nyxozhvSkZHxMrNZk0QYvCnI8m5QmnbZlOSZ7ZFL2yCRREGn46A5nBTbL9ER80XxWYwj9WTYN\nHi1tEsVTC3KnGxB78GYJuoXfI7MU7yg7FJpWVGl8K4+4bv9CbK8361tT7Lzqwy4KKjXu3yj9\nCiq309KWc8tvFUn4kQS/cFigFENnlM3tPrt0r3tmyaefJOq8LCWEOFXsy37fx7/vi9Tqmw5U\nf7stcBK/7Wf6s43Hd0WYnbWntGpubG78hOEJHSm/U6y6MOkCxFST2usMuwGqa5SheRPSElJN\nDEsppTFWXcHkdHX4HwlEwX4IgbAntAnpecve1MQNCvw18AmqiR9U8NuPpF0p1aePbP9z9J+s\nU/VemcFi7bavj73/SPSfo1/zvrtH0uLfeEI42p5hThSrf/z04Mt3Hfj7ryo3fCCKodV3A6jA\neX0al/hUN8fhVVdK6wAyw+JCK8tHm6/OsSJBmu7r82JpCs1o2Ns5OXUXjWfI6xdWbS//xzeH\nVmwtc8tNSl934ZCX7506a1QyGxSN1Cx7SW68ztjzrStqDTdi/KBp84dNWzBs9LRMkwVp1QYY\nTI32kGX4lAnPbHHXVbSU7nNVHzcPnWBID617Sur3ft98dHvfP14Xx/JLv3qRN8WFbupRDqFc\nurWBEFL8/EPm6+bEjZl98NV7Kte9H2is2vBh3baVluGTJenxCCHO2Gp9bQLj48UbdzsbYnW/\nmhHudto3LxUqW/yrjolEJIQyQ62GtTf24j8nQg3fl7hC8j5X9WhV7HRpVTKfM/re/lWg3u6+\n9cl1FXVtR4OSY3Uv3j05KVaaniY/K3Zk5riZ3x5eva+61umJ1fLjUk0JZm1iyBHD00VpmLUR\n6PcQCM+I2pqitobdRCf4vPufWyKTuKK3yaxWdtn76Ht/1NuGxhbMjOpT9VtsfqJvTafNnCIV\nKys+L3v6w7jCWbU7Vga/VLPli8Rpi+JGX1S7bUV7xmya/tOM2JKcQAcqUO+93wsLCpl0md38\nhBBCqX7FYuLw+DaWMYVJTGjmsD4RNzXD/NXBRm2nt3ymXWZ7V6+rt8sc+LPF93Jl2v99Y0tH\nFCSEnKx3PvLuzufunBTak1I6aXpWUryhttIuCqIlXp81IpHjUR1CuRAIo6ji23/4HLLJR7oT\neRkDQkiP5lxrNi9XbCBU/XqS51+7xRoHIcSrcVWO3NpkK/ap3IQQSRQMsB/dmbfsrYa93zcf\n3cEbY32P/hRTktCph0icD31teLPLTK16FXdh2MIOfYDG6xeXtTw75FS0ZgXxhiifhQj4Ya9M\n/YfyWkckZXgjt/OoNFHLjiO1fkFk5dbkeDWXW5gSrcIfMNAgEEZR05GtPbyy28h2xjMwHnt0\ntyr0Z0yK0bB5iftP3zd9vaZ4/HKPTqZ8eTBOZySEWPKmB0pTlS/bGvqrin9X2Fo//ceV7y7S\n3fDxpxqmxqBKa3RfNyyx6P5pfXBfu0tm3Nkkl5Clx6oaXKHZtAVBFMWe1zoD5UAgjCJWdWrN\nPJK3Yxd9ur/8NN/vxsyC0+h9zmHSYrSvLth07ZLue3J8bEHnVDJDTWSP9HvNWgZAcTEaq73k\n82sXtHjEWieTFtPFEb3elRZvqAupYTQ1JEXLmVDLTWzq1BwndxIfQAI/JVEU/AEayUdOF326\nv/x0PtO0iRm2i7uPAec2wR22cgKna9s3wWoMOTc/qU/NCX7V+sQSkZGu+/IX5ZABghpUTIa5\nz6IgIeT6kG9OXoYlM6mbPAanxWxQDUmV7naZW5Qu2xlAAiPCKEqYcEnz4S1lK17rvqtIGF4t\n+MJNFskP9yilslM/XQ8OLXnTR9z1CqftzY+hAUMU63aushfv5Azm1rrycL2KntrUfGQbEQVT\n9hjeKM2DpbGlic9f4L5zDW2PhmyRTX3PhOg99UBXNCzh99eNfvaTvY0tHpahMwpT7r+i9yck\n/nzT2Htf/Kmirm2ie9LwxDsvHd7rd4FzEg2tsBVV5eXlqakDI91+b3GU/1y6/LnqHz7uphIv\npXJnukOCmmw+bpFGPiK0zV6afc0fIu19Dqnfs/7Ai7d52xdHKcPK5hbQJqQXPbWp26/m31vt\n/fcesaGVLUpVXZ0vd2oepGqbWmMMKj5q05Ven7D5YHVtszs7xRSodw8DUd+HCYwIo06fmpN5\n+QOVGz6khHQ1WpP/jSSks2w+7tOZ5VIZrafR+1xx9L0/ln35YvC3OEyGHVr0pDQjmiw2L4H9\nc9gyFCArTq6Yey/iOWZyXl8nroNzAAJhX3CcONAeqs7yBjaGU1lHzzq7z9D3PI3VJ756KYKO\ndPJL+85WLmwAOFswn9MX1LFBG+TOIAX3GeL0MblLntHbIiqm6mmq9beGzdY/sNRs/ZqErAFI\n/sobraMfWh66IggA5zyMCPuCPjXXmJlvP7abkJ6PCc9wnKKxpo59bG0ke2Qq1/37u3ee2Sva\nWhi9kXpnz184ed6iM7v5WcawLJFLvsObrHn3vOEo3c8brZb88xS6gQhA8RAI+wJluRF3vX7w\nlbsbD2wkhBBKA+VG+1IXmySD2Yt3rvrH4+vV49quIpq3l69mzYkTpkyP5tNFl7VwVuheJMpy\nw257LiZnfEzO+LP1YADQH2BqtI9o4geNevA/k17YPf7xDWlzf9mzKBj57KhsT2f5z91eePzT\np/fw0lNfn/0npKrGgKIyJ2QsXBY8JuT0MUVP/hSbr9AkcwAQDCPCPuJzNNXtXOW11xkzCzIv\nf0DwuMtWRnC+sLNuD1KE6dlGE2fr9hbO6uPNjDQQNjg8Pp+P4wbwT0vGL+6zjrm47OuXvS0N\n1vwZqRfdcrafCAD6iwH80TaA1O1avffZW8RWVyBAxY2dM+KuV5uPbG0u3nkGX7WrQaU1/7y6\n3Ws7tYy6IJLa9Ibkwfo6h53pVBnAqOUHdBQMMGaMHHb782f7KQCg38HUaNTZj+7Y+8S1otvV\nEblqt35VvuK1nFueYvhoHatitaahS5/lTVZCCKFMwoRLht72XCQXZl79ULb/hKTxvAsUd+IC\nAJRjwP+a38/5W1t2/XVRaPqe2h3f2mYvjRt9cfWmT8NfLTv5SQkRgtsZTiX4pNn9XdUlSVMX\nJU25vLW+gjdYWHWkNfC08WlX3PeY+Pyje70JPsrxVDxv2uTZc+ZFeDkAwICDQBhddbvW+Jwy\n9dB9LQ2EENOQ0aGBMCj6yUx+modNbNt6GujBsiPufXPPE9eSzvnbdClDCCGEUo31tDMVWYZN\nuv2F5YIgNDc3m0wmhsG0AQCcy/AZF12tVSWy7abs0YSQ5BnX6lKyJS+din4hWz+Tplyef9+7\nafN/pYqJpyxvGlyYf//71oKZtlk3d+5OLcMnn+GTMwxjNpsRBQHgnIek29FVs+XLfX+7WdJI\nOX7KS/tZrZEQ4nM2lS5/vunnza6qEk9jVWA8GBgU8npz5hUPWkedX/PTZ36vO75ogS7pVIlz\nURQobYtS1Rs/3f/ibcG3UFuSxj/5Y3BBRACAAQFJt8811lEXGNKGt5Tu72hhWL7wd8vZ9iQm\nnC4m64oHCSE/3j2akLbxYGBQ6HE2J0xcyGmNtjm3h37ljihICKnf+13gD4EIKhLibqhs/nlz\noKKhrP59AAACwElEQVQ6AAB0ARNf0cXw6vz/fi9pyiLeYOG0RuuoC8Y9udGYPSq0J2WkJbYZ\nQhiWj+Qu/ta2Gmw06L8nvn65x48NAKAcGBFGncqcOPS2Z7vtxvBqSYsYcSYZU/aYms1fSBpb\nAqlNAQCgSxgR9hcyZwpF0VlxOJJrU2YuDq1J6G91dFMKGAAAEAj7D018WmijOoKkaIQQVqM3\nZo+WNBoHFwavIwIAgCx8UPYXydOvkrTEjZnNGywRXj7k+keD94iyGv2QxY/02sMBAJy7cHyi\nHzn53T+L3/+zt6UxkBQt54bHOH1M5Je31pZVrHrDVXVcm5yVeuGNakty99cAAPQzfR8mEAj7\nF1Hwu+vKeVNc5EnRAADOJThHqHSUYWUXCwEAIEqwRggAAIqGQAgAAIqGQAgAAIqGQAgAAIqG\nQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqG\nQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqG\nQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqG\nQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIqGQAgAAIpGRVHsy/vZ\n7fampqa+vCMAAAwgFotFr9f35R37OhACAAD0K5gaBQAARUMgBAAARUMgBAAARUMgBAAARUMg\nBAAARUMgBAAARUMgBAAARUMgBAAARUMgBAAARUMgBAAARUMgBAAARUMgBAAARUMgBAAARUMg\nBAAARUMgBAAARUMgBAAARUMgBAAARUMgBAAARUMgBAAARUMgBAAARUMgBAAARUMgBAAARUMg\nBAAARUMgBAAARft/SkqJjIWGW/gAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(repr.plot.width=5, repr.plot.height=5)\n",
    "plot.tsne(tsnetfidf$Y,as.factor(metadata[,'label']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "R version 3.5.1 (2018-07-02)\n",
       "Platform: x86_64-conda_cos6-linux-gnu (64-bit)\n",
       "Running under: CentOS Linux 7 (Core)\n",
       "\n",
       "Matrix products: default\n",
       "BLAS/LAPACK: /data/pinello/SHARED_SOFTWARE/anaconda3/envs/ATACseq_sciATAC/lib/R/lib/libRblas.so\n",
       "\n",
       "locale:\n",
       " [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              \n",
       " [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    \n",
       " [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   \n",
       " [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 \n",
       " [9] LC_ADDRESS=C               LC_TELEPHONE=C            \n",
       "[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       \n",
       "\n",
       "attached base packages:\n",
       "[1] stats     graphics  grDevices utils     datasets  methods   base     \n",
       "\n",
       "other attached packages:\n",
       "[1] RColorBrewer_1.1-2 ggplot2_3.1.1      umap_0.2.0.0       irlba_2.3.2       \n",
       "[5] densityClust_0.3   Rtsne_0.15         proxy_0.4-22       Matrix_1.2-17     \n",
       "[9] data.table_1.12.2 \n",
       "\n",
       "loaded via a namespace (and not attached):\n",
       " [1] Rcpp_1.0.1       compiler_3.5.1   pillar_1.3.1     plyr_1.8.4      \n",
       " [5] base64enc_0.1-3  tools_3.5.1      digest_0.6.18    uuid_0.1-2      \n",
       " [9] jsonlite_1.6     evaluate_0.13    tibble_2.1.1     gtable_0.3.0    \n",
       "[13] lattice_0.20-38  pkgconfig_2.0.2  rlang_0.3.4      IRdisplay_0.7.0 \n",
       "[17] ggrepel_0.8.0    IRkernel_0.8.15  gridExtra_2.3    withr_2.1.2     \n",
       "[21] repr_0.19.2      dplyr_0.8.0.1    grid_3.5.1       tidyselect_0.2.5\n",
       "[25] reticulate_1.12  glue_1.3.1       R6_2.4.0         pbdZMQ_0.3-3    \n",
       "[29] purrr_0.3.2      magrittr_1.5     scales_1.0.0     htmltools_0.3.6 \n",
       "[33] assertthat_0.2.1 colorspace_1.4-1 labeling_0.3     lazyeval_0.2.2  \n",
       "[37] munsell_0.5.0    crayon_1.3.4     FNN_1.1.3       "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sessionInfo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "save.image(file = 'Cusanovich2018_10xpbmc5k.RData')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R [conda env:ATACseq_sciATAC]",
   "language": "R",
   "name": "conda-env-ATACseq_sciATAC-r"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}