example.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "julian-sherman",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "from communiquer.launchers import CellChatLauncher, CellPhoneDBLauncher\n",
    "from communiquer.drawing import draw_chord_diagram"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "executive-andrews",
   "metadata": {},
   "source": [
    "Provide paths to the data. You have to prepare 2 files. The first one, **counts**, contains normalized (but not scaled!) counts matrix (rows are genes, columns are barcodes). The second file contains **meta information** about cells. It must have 2 columns: the first one with cell IDs (e.g. barcodes), and the second with cells labels (e.g. cell types)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "referenced-colonial",
   "metadata": {},
   "outputs": [],
   "source": [
    "counts_path = Path(\"data/pbmc3k_counts.tsv\")\n",
    "meta_path = Path(\"data/pbmc3k_meta.txt\")\n",
    "\n",
    "cpdb_output_path = Path(\"data/cpdb_output\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "interpreted-embassy",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cell\tcell_type\r\n",
      "AAACATACAACCAC-1\tRPS expressing\r\n",
      "AAACATTGAGCTAC-1\tB\r\n",
      "AAACATTGATCAGC-1\tCD4 T\r\n",
      "AAACCGTGCTTCCG-1\tCD14 Monocytes\r\n",
      "AAACCGTGTATGCG-1\tNK\r\n",
      "AAACGCACTGGTAC-1\tCD4 T\r\n",
      "AAACGCTGACCAGT-1\tCD8 T\r\n",
      "AAACGCTGGTTCTT-1\tCD8 T\r\n",
      "AAACGCTGTAGCCA-1\tCD8 T\r\n"
     ]
    }
   ],
   "source": [
    "!head data/pbmc3k_meta.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "assigned-demand",
   "metadata": {},
   "source": [
    "# Running CellPhoneDB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "eastern-theology",
   "metadata": {},
   "outputs": [],
   "source": [
    "cpdb_launcher = CellPhoneDBLauncher(\n",
    "    meta_file_path=meta_path,\n",
    "    counts_file_path=counts_path,\n",
    "    output_path=cpdb_output_path,  # CellPhoneDB saves its output to the files\n",
    "    project_name=\"pbmc3k\",\n",
    "    counts_data=\"gene_name\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "classical-minute",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running command cellphonedb method statistical_analysis --counts-data=gene_name --project-name=pbmc3k --threshold=0.1 --result-precision=3 --output-path=data/cpdb_output --output-format=txt --means-result-name=means --significant-means-result-name=significant_means --deconvoluted-result-name=deconvoluted --debug-seed=-1 --pvalue=0.05 --pvalues-result-name=pvalues --iterations=1000 --threads=-1 --verbose data/pbmc3k_meta.txt data/pbmc3k_counts.tsv\n",
      "[ ][APP][29/08/21-23:48:04][WARNING] Latest local available version is `v2.0.0`, using it\n",
      "[ ][APP][29/08/21-23:48:04][WARNING] User selected downloaded database `v2.0.0` is available, using it\n",
      "[ ][CORE][29/08/21-23:48:04][INFO] Initializing SqlAlchemy CellPhoneDB Core\n",
      "[ ][CORE][29/08/21-23:48:04][INFO] Using custom database at /home/vladimir/.cpdb/releases/v2.0.0/cellphone.db\n",
      "[ ][APP][29/08/21-23:48:04][INFO] Launching Method cpdb_statistical_analysis_local_method_launcher\n",
      "[ ][APP][29/08/21-23:48:04][INFO] Launching Method _set_paths\n",
      "[ ][APP][29/08/21-23:48:04][WARNING] Output directory (/home/vladimir/PycharmProjects/communiquer/data/cpdb_output/pbmc3k) exist and is not empty. Result can overwrite old results\n",
      "[ ][APP][29/08/21-23:48:04][INFO] Launching Method _load_meta_counts\n",
      "[ ][CORE][29/08/21-23:48:06][INFO] Launching Method cpdb_statistical_analysis_launcher\n",
      "[ ][CORE][29/08/21-23:48:06][INFO] Using Default thread number: 4\n",
      "[ ][CORE][29/08/21-23:48:06][INFO] Launching Method _counts_validations\n",
      "[ ][CORE][29/08/21-23:48:07][INFO] [Cluster Statistical Analysis] Threshold:0.1 Iterations:1000 Debug-seed:-1 Threads:4 Precision:3\n",
      "[ ][CORE][29/08/21-23:48:07][INFO] Running Real Analysis\n",
      "[ ][CORE][29/08/21-23:48:07][INFO] Running Statistical Analysis\n",
      "[ ][CORE][29/08/21-23:48:38][INFO] Building Pvalues result\n",
      "[ ][CORE][29/08/21-23:48:40][INFO] Building results\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vladimir/PycharmProjects/communiquer/communiquer/command_line.py:203: UserWarning: /home/vladimir/anaconda3/lib/python3.7/site-packages/sklearn/utils/deprecation.py:144: FutureWarning: The sklearn.cluster.k_means_ module is  deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.cluster. Anything that cannot be imported from sklearn.cluster is now part of the private API.\n",
      "  warnings.warn(message, FutureWarning)\n",
      "/home/vladimir/.local/lib/python3.7/site-packages/requests/__init__.py:91: RequestsDependencyWarning: urllib3 (1.26.6) or chardet (4.0.0) doesn't match a supported version!\n",
      "  RequestsDependencyWarning)\n",
      "\n",
      "  warnings.warn(command_line_subprocess.stderr.decode())\n"
     ]
    }
   ],
   "source": [
    "cpdb_launcher.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "immediate-being",
   "metadata": {},
   "source": [
    "Read the output and display it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "necessary-spell",
   "metadata": {},
   "outputs": [],
   "source": [
    "cpdb_launcher.read_output(convert_to_cellchat_format=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "classified-praise",
   "metadata": {},
   "outputs": [
    {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id_cp_interaction</th>\n",
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       "      <th>RPS expressing|B</th>\n",
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       "      <th>RPS expressing|CD4 T</th>\n",
       "      <th>RPS expressing|CD8 T</th>\n",
       "      <th>RPS expressing|Dendritic</th>\n",
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       "      <th>RPS expressing|Megakaryocytes</th>\n",
       "      <th>RPS expressing|NK</th>\n",
       "      <th>RPS expressing|RPS expressing</th>\n",
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       "    <tr>\n",
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       "      <td>CPI-SS016EE0084</td>\n",
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       "      <td>CD274</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>curated</td>\n",
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       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CPI-SS0DA033F03</td>\n",
       "      <td>TNFRSF1A_GRN</td>\n",
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       "      <td>simple:P28799</td>\n",
       "      <td>TNFRSF1A</td>\n",
       "      <td>GRN</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>IMEx,InnateDB-All,MINT</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CPI-SS0C4E86714</td>\n",
       "      <td>TNFRSF1B_GRN</td>\n",
       "      <td>simple:P20333</td>\n",
       "      <td>simple:P28799</td>\n",
       "      <td>TNFRSF1B</td>\n",
       "      <td>GRN</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
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       "      <td>IMEx,InnateDB-All,MINT</td>\n",
       "      <td>...</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CPI-SS05D23BCE8</td>\n",
       "      <td>HLA-DPB1_TNFSF13B</td>\n",
       "      <td>simple:HLADPB1</td>\n",
       "      <td>simple:Q9Y275</td>\n",
       "      <td>HLA-DPB1</td>\n",
       "      <td>TNFSF13B</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>InnateDB-All</td>\n",
       "      <td>...</td>\n",
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       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>CPI-SS0E2863F09</td>\n",
       "      <td>TNFRSF17_TNFSF13B</td>\n",
       "      <td>simple:Q02223</td>\n",
       "      <td>simple:Q9Y275</td>\n",
       "      <td>TNFRSF17</td>\n",
       "      <td>TNFSF13B</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>curated</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>CPI-SS09648FAA9</td>\n",
       "      <td>TNFRSF13C_TNFSF13B</td>\n",
       "      <td>simple:Q96RJ3</td>\n",
       "      <td>simple:Q9Y275</td>\n",
       "      <td>TNFRSF13C</td>\n",
       "      <td>TNFSF13B</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>guidetopharmacology.org</td>\n",
       "      <td>...</td>\n",
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       "      <td>1.000</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>CPI-SS0E4B1484B</td>\n",
       "      <td>ICOSLG_ICOS</td>\n",
       "      <td>simple:O75144</td>\n",
       "      <td>simple:Q9Y6W8</td>\n",
       "      <td>ICOSLG</td>\n",
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       "      <td>curated</td>\n",
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       "      <td>1.000</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>CPI-SS040630206</td>\n",
       "      <td>CXCL2_CXCR1</td>\n",
       "      <td>simple:P19875</td>\n",
       "      <td>simple:P25024</td>\n",
       "      <td>CXCL2</td>\n",
       "      <td>CXCR1</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>I2D</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
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       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>CPI-SS07AB1C381</td>\n",
       "      <td>PPBP_CXCR1</td>\n",
       "      <td>simple:P02775</td>\n",
       "      <td>simple:P25024</td>\n",
       "      <td>PPBP</td>\n",
       "      <td>CXCR1</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>curated</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>CPI-SS0D04AE221</td>\n",
       "      <td>CXCL3_CXCR1</td>\n",
       "      <td>simple:P19876</td>\n",
       "      <td>simple:P25024</td>\n",
       "      <td>CXCL3</td>\n",
       "      <td>CXCR1</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>I2D</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
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       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>CPI-SS079DDF890</td>\n",
       "      <td>TNFSF12_TNFRSF25</td>\n",
       "      <td>simple:O43508</td>\n",
       "      <td>simple:Q93038</td>\n",
       "      <td>TNFSF12</td>\n",
       "      <td>TNFRSF25</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>I2D</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>CPI-SS087321EB5</td>\n",
       "      <td>SELL_SELPLG</td>\n",
       "      <td>simple:P14151</td>\n",
       "      <td>simple:Q14242</td>\n",
       "      <td>SELL</td>\n",
       "      <td>SELPLG</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>curated</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.147</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>CPI-SS04C672963</td>\n",
       "      <td>ESAM_ESAM</td>\n",
       "      <td>simple:Q96AP7</td>\n",
       "      <td>simple:Q96AP7</td>\n",
       "      <td>ESAM</td>\n",
       "      <td>ESAM</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>curated</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15 rows × 92 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   id_cp_interaction     interacting_pair       partner_a  \\\n",
       "0    CPI-SC0200AC9E3  THBS1_a2Bb3 complex   simple:P07996   \n",
       "1    CPI-SS0F9D53834            JAM3_JAM3   simple:Q9BX67   \n",
       "2    CPI-SS016EE0084          PDCD1_CD274   simple:Q15116   \n",
       "3    CPI-SS0DA033F03         TNFRSF1A_GRN   simple:P19438   \n",
       "4    CPI-SS0C4E86714         TNFRSF1B_GRN   simple:P20333   \n",
       "5    CPI-SS05D23BCE8    HLA-DPB1_TNFSF13B  simple:HLADPB1   \n",
       "6    CPI-SS0E2863F09    TNFRSF17_TNFSF13B   simple:Q02223   \n",
       "7    CPI-SS09648FAA9   TNFRSF13C_TNFSF13B   simple:Q96RJ3   \n",
       "8    CPI-SS0E4B1484B          ICOSLG_ICOS   simple:O75144   \n",
       "9    CPI-SS040630206          CXCL2_CXCR1   simple:P19875   \n",
       "10   CPI-SS07AB1C381           PPBP_CXCR1   simple:P02775   \n",
       "11   CPI-SS0D04AE221          CXCL3_CXCR1   simple:P19876   \n",
       "12   CPI-SS079DDF890     TNFSF12_TNFRSF25   simple:O43508   \n",
       "13   CPI-SS087321EB5          SELL_SELPLG   simple:P14151   \n",
       "14   CPI-SS04C672963            ESAM_ESAM   simple:Q96AP7   \n",
       "\n",
       "                partner_b     gene_a    gene_b  secreted  receptor_a  \\\n",
       "0   complex:a2Bb3 complex      THBS1       NaN     False       False   \n",
       "1           simple:Q9BX67       JAM3      JAM3      True       False   \n",
       "2           simple:Q9NZQ7      PDCD1     CD274     False        True   \n",
       "3           simple:P28799   TNFRSF1A       GRN      True        True   \n",
       "4           simple:P28799   TNFRSF1B       GRN      True        True   \n",
       "5           simple:Q9Y275   HLA-DPB1  TNFSF13B      True        True   \n",
       "6           simple:Q9Y275   TNFRSF17  TNFSF13B      True        True   \n",
       "7           simple:Q9Y275  TNFRSF13C  TNFSF13B      True        True   \n",
       "8           simple:Q9Y6W8     ICOSLG      ICOS      True       False   \n",
       "9           simple:P25024      CXCL2     CXCR1      True       False   \n",
       "10          simple:P25024       PPBP     CXCR1      True       False   \n",
       "11          simple:P25024      CXCL3     CXCR1      True       False   \n",
       "12          simple:Q93038    TNFSF12  TNFRSF25      True       False   \n",
       "13          simple:Q14242       SELL    SELPLG     False       False   \n",
       "14          simple:Q96AP7       ESAM      ESAM     False       False   \n",
       "\n",
       "    receptor_b      annotation_strategy  ...  NK|RPS expressing  \\\n",
       "0        False                  curated  ...              1.000   \n",
       "1        False                  curated  ...              1.000   \n",
       "2         True                  curated  ...              1.000   \n",
       "3        False   IMEx,InnateDB-All,MINT  ...              1.000   \n",
       "4        False   IMEx,InnateDB-All,MINT  ...              1.000   \n",
       "5        False             InnateDB-All  ...              1.000   \n",
       "6        False                  curated  ...              1.000   \n",
       "7        False  guidetopharmacology.org  ...              1.000   \n",
       "8         True                  curated  ...              1.000   \n",
       "9         True                      I2D  ...              1.000   \n",
       "10        True                  curated  ...              1.000   \n",
       "11        True                      I2D  ...              1.000   \n",
       "12        True                      I2D  ...              1.000   \n",
       "13        True                  curated  ...              0.004   \n",
       "14       False                  curated  ...              1.000   \n",
       "\n",
       "    RPS expressing|B  RPS expressing|CD14 Monocytes  RPS expressing|CD4 T  \\\n",
       "0                1.0                            1.0                   1.0   \n",
       "1                1.0                            1.0                   1.0   \n",
       "2                1.0                            1.0                   1.0   \n",
       "3                1.0                            1.0                   1.0   \n",
       "4                1.0                            1.0                   1.0   \n",
       "5                1.0                            1.0                   1.0   \n",
       "6                1.0                            1.0                   1.0   \n",
       "7                1.0                            1.0                   1.0   \n",
       "8                1.0                            1.0                   1.0   \n",
       "9                1.0                            1.0                   1.0   \n",
       "10               1.0                            1.0                   1.0   \n",
       "11               1.0                            1.0                   1.0   \n",
       "12               1.0                            1.0                   1.0   \n",
       "13               1.0                            0.0                   0.0   \n",
       "14               1.0                            1.0                   1.0   \n",
       "\n",
       "    RPS expressing|CD8 T  RPS expressing|Dendritic  \\\n",
       "0                    1.0                     1.000   \n",
       "1                    1.0                     1.000   \n",
       "2                    1.0                     1.000   \n",
       "3                    1.0                     1.000   \n",
       "4                    1.0                     1.000   \n",
       "5                    1.0                     0.996   \n",
       "6                    1.0                     1.000   \n",
       "7                    1.0                     1.000   \n",
       "8                    1.0                     1.000   \n",
       "9                    1.0                     1.000   \n",
       "10                   1.0                     1.000   \n",
       "11                   1.0                     1.000   \n",
       "12                   1.0                     1.000   \n",
       "13                   0.0                     0.000   \n",
       "14                   1.0                     1.000   \n",
       "\n",
       "    RPS expressing|FCGR3A Monocytes  RPS expressing|Megakaryocytes  \\\n",
       "0                               1.0                          1.000   \n",
       "1                               1.0                          1.000   \n",
       "2                               1.0                          1.000   \n",
       "3                               1.0                          1.000   \n",
       "4                               1.0                          1.000   \n",
       "5                               1.0                          1.000   \n",
       "6                               1.0                          1.000   \n",
       "7                               1.0                          1.000   \n",
       "8                               1.0                          1.000   \n",
       "9                               1.0                          1.000   \n",
       "10                              1.0                          1.000   \n",
       "11                              1.0                          1.000   \n",
       "12                              1.0                          1.000   \n",
       "13                              0.0                          0.147   \n",
       "14                              1.0                          1.000   \n",
       "\n",
       "    RPS expressing|NK  RPS expressing|RPS expressing  \n",
       "0                 1.0                            1.0  \n",
       "1                 1.0                            1.0  \n",
       "2                 1.0                            1.0  \n",
       "3                 1.0                            1.0  \n",
       "4                 1.0                            1.0  \n",
       "5                 1.0                            1.0  \n",
       "6                 1.0                            1.0  \n",
       "7                 1.0                            1.0  \n",
       "8                 1.0                            1.0  \n",
       "9                 1.0                            1.0  \n",
       "10                1.0                            1.0  \n",
       "11                1.0                            1.0  \n",
       "12                1.0                            1.0  \n",
       "13                0.0                            0.0  \n",
       "14                1.0                            1.0  \n",
       "\n",
       "[15 rows x 92 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cpdb_launcher.pvalues_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "detailed-mexican",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id_cp_interaction</th>\n",
       "      <th>interacting_pair</th>\n",
       "      <th>partner_a</th>\n",
       "      <th>partner_b</th>\n",
       "      <th>gene_a</th>\n",
       "      <th>gene_b</th>\n",
       "      <th>secreted</th>\n",
       "      <th>receptor_a</th>\n",
       "      <th>receptor_b</th>\n",
       "      <th>annotation_strategy</th>\n",
       "      <th>...</th>\n",
       "      <th>NK|RPS expressing</th>\n",
       "      <th>RPS expressing|B</th>\n",
       "      <th>RPS expressing|CD14 Monocytes</th>\n",
       "      <th>RPS expressing|CD4 T</th>\n",
       "      <th>RPS expressing|CD8 T</th>\n",
       "      <th>RPS expressing|Dendritic</th>\n",
       "      <th>RPS expressing|FCGR3A Monocytes</th>\n",
       "      <th>RPS expressing|Megakaryocytes</th>\n",
       "      <th>RPS expressing|NK</th>\n",
       "      <th>RPS expressing|RPS expressing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CPI-SC0200AC9E3</td>\n",
       "      <td>THBS1_a2Bb3 complex</td>\n",
       "      <td>simple:P07996</td>\n",
       "      <td>complex:a2Bb3 complex</td>\n",
       "      <td>THBS1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>curated</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.459</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CPI-SS0F9D53834</td>\n",
       "      <td>JAM3_JAM3</td>\n",
       "      <td>simple:Q9BX67</td>\n",
       "      <td>simple:Q9BX67</td>\n",
       "      <td>JAM3</td>\n",
       "      <td>JAM3</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>curated</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CPI-SS016EE0084</td>\n",
       "      <td>PDCD1_CD274</td>\n",
       "      <td>simple:Q15116</td>\n",
       "      <td>simple:Q9NZQ7</td>\n",
       "      <td>PDCD1</td>\n",
       "      <td>CD274</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>curated</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.006</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CPI-SS0DA033F03</td>\n",
       "      <td>TNFRSF1A_GRN</td>\n",
       "      <td>simple:P19438</td>\n",
       "      <td>simple:P28799</td>\n",
       "      <td>TNFRSF1A</td>\n",
       "      <td>GRN</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>IMEx,InnateDB-All,MINT</td>\n",
       "      <td>...</td>\n",
       "      <td>0.197</td>\n",
       "      <td>0.134</td>\n",
       "      <td>0.882</td>\n",
       "      <td>0.080</td>\n",
       "      <td>0.089</td>\n",
       "      <td>0.932</td>\n",
       "      <td>0.487</td>\n",
       "      <td>0.187</td>\n",
       "      <td>0.107</td>\n",
       "      <td>0.092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CPI-SS0C4E86714</td>\n",
       "      <td>TNFRSF1B_GRN</td>\n",
       "      <td>simple:P20333</td>\n",
       "      <td>simple:P28799</td>\n",
       "      <td>TNFRSF1B</td>\n",
       "      <td>GRN</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>IMEx,InnateDB-All,MINT</td>\n",
       "      <td>...</td>\n",
       "      <td>0.206</td>\n",
       "      <td>0.143</td>\n",
       "      <td>0.891</td>\n",
       "      <td>0.089</td>\n",
       "      <td>0.098</td>\n",
       "      <td>0.941</td>\n",
       "      <td>0.496</td>\n",
       "      <td>0.197</td>\n",
       "      <td>0.116</td>\n",
       "      <td>0.101</td>\n",
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       "<p>5 rows × 92 columns</p>\n",
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      "text/plain": [
       "  id_cp_interaction     interacting_pair      partner_a  \\\n",
       "0   CPI-SC0200AC9E3  THBS1_a2Bb3 complex  simple:P07996   \n",
       "1   CPI-SS0F9D53834            JAM3_JAM3  simple:Q9BX67   \n",
       "2   CPI-SS016EE0084          PDCD1_CD274  simple:Q15116   \n",
       "3   CPI-SS0DA033F03         TNFRSF1A_GRN  simple:P19438   \n",
       "4   CPI-SS0C4E86714         TNFRSF1B_GRN  simple:P20333   \n",
       "\n",
       "               partner_b    gene_a gene_b  secreted  receptor_a  receptor_b  \\\n",
       "0  complex:a2Bb3 complex     THBS1    NaN     False       False       False   \n",
       "1          simple:Q9BX67      JAM3   JAM3      True       False       False   \n",
       "2          simple:Q9NZQ7     PDCD1  CD274     False        True        True   \n",
       "3          simple:P28799  TNFRSF1A    GRN      True        True       False   \n",
       "4          simple:P28799  TNFRSF1B    GRN      True        True       False   \n",
       "\n",
       "      annotation_strategy  ...  NK|RPS expressing  RPS expressing|B  \\\n",
       "0                 curated  ...              0.000             0.000   \n",
       "1                 curated  ...              0.000             0.000   \n",
       "2                 curated  ...              0.000             0.006   \n",
       "3  IMEx,InnateDB-All,MINT  ...              0.197             0.134   \n",
       "4  IMEx,InnateDB-All,MINT  ...              0.206             0.143   \n",
       "\n",
       "   RPS expressing|CD14 Monocytes  RPS expressing|CD4 T  RPS expressing|CD8 T  \\\n",
       "0                          0.000                 0.000                 0.000   \n",
       "1                          0.000                 0.000                 0.000   \n",
       "2                          0.005                 0.005                 0.005   \n",
       "3                          0.882                 0.080                 0.089   \n",
       "4                          0.891                 0.089                 0.098   \n",
       "\n",
       "   RPS expressing|Dendritic  RPS expressing|FCGR3A Monocytes  \\\n",
       "0                     0.000                            0.000   \n",
       "1                     0.000                            0.000   \n",
       "2                     0.000                            0.000   \n",
       "3                     0.932                            0.487   \n",
       "4                     0.941                            0.496   \n",
       "\n",
       "   RPS expressing|Megakaryocytes  RPS expressing|NK  \\\n",
       "0                          0.459              0.000   \n",
       "1                          0.000              0.000   \n",
       "2                          0.000              0.000   \n",
       "3                          0.187              0.107   \n",
       "4                          0.197              0.116   \n",
       "\n",
       "   RPS expressing|RPS expressing  \n",
       "0                          0.000  \n",
       "1                          0.000  \n",
       "2                          0.004  \n",
       "3                          0.092  \n",
       "4                          0.101  \n",
       "\n",
       "[5 rows x 92 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cpdb_launcher.means_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "sunrise-contents",
   "metadata": {},
   "outputs": [],
   "source": [
    "cpdb_launcher.count_significant_interactions()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "outer-norwegian",
   "metadata": {},
   "outputs": [
    {
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD14 Monocytes</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NK</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 T</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FCGR3A Monocytes</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dendritic</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Megakaryocytes</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  RPS expressing  B  CD4 T  CD14 Monocytes  NK  CD8 T  \\\n",
       "RPS expressing                 1  0      1               1   1      1   \n",
       "B                              1  0      1               2   1      1   \n",
       "CD4 T                          0  0      1               1   1      1   \n",
       "CD14 Monocytes                 0  0      0               3   0      0   \n",
       "NK                             1  0      1               3   1      1   \n",
       "CD8 T                          0  0      0               1   0      0   \n",
       "FCGR3A Monocytes               0  1      0               3   0      0   \n",
       "Dendritic                      0  0      0               3   0      0   \n",
       "Megakaryocytes                 0  0      0               0   0      0   \n",
       "\n",
       "                  FCGR3A Monocytes  Dendritic  Megakaryocytes  \n",
       "RPS expressing                   1          1               0  \n",
       "B                                2          2               0  \n",
       "CD4 T                            1          1               0  \n",
       "CD14 Monocytes                   3          3               0  \n",
       "NK                               3          3               0  \n",
       "CD8 T                            1          1               0  \n",
       "FCGR3A Monocytes                 3          3               0  \n",
       "Dendritic                        4          3               0  \n",
       "Megakaryocytes                   0          0               1  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cpdb_launcher.counts_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "framed-cause",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YgE5o1Rv8yr/7d8RxzI0/9RJe8Ge/wX+rfpujVGjedwZ7VTfkK37zXzF83aXELZ8v/9h/Yf6Ou/nWr/45z/7q74LWxH7AN17x/zH29KtIYs38HXevuwsmX/A4Jl/wOAD+5bUfoPbNE1z05Mfyzne+czD73GAw7ApG8BgOD5YFk6NwerYbdTgzB0fGJdrT7+dynTSdlYqEQczVimIRBP2e3L2WsAlDeT7HkdfmOlAqLPeowbZ3bVjqnd/4GvOLCwD89i2/x3uHT5BLT1elK6bW/Tu7mOMxb/gJvnLH3TSPn6bx4CzlS8b47utuwz+9xFM++Tq+8XPv3vb2zLFL40sMBsPAMILHcLhwna7o0Vr6rJyehSNjK3qt9AXP7fp3BjFINEngkTNy+5Kj5yY2tJZt7ATg+/LVsqS6KRM2bkVu74MJ8NPT08u3L7n0Uk6r7+CxNdFauGR8+XZQ95n5wr08+P99mid88DUULh7f4C/Xp8020pbZvg5C8ZHtg/1pMBiM4DEcRnKepLdmFlaKnqnx/qa33J4FeANPyI7QGqYX0k7OWvxJxfymf7ZMkkglkh/IY/ihbG/Okzlko9X+R736yOTk5PLtEydOEFwdrzcK6yzaJ2aXb3tTw3zvvZ/Dyjk88sE7eeSDd1L/9sMAPPSezwGsaVxeTbLRbK1sX3d8GXHS7qQl8cBVlxjBYzDsE4zgMRxOigWYUDAzn4qeOBU9YysNx+eC3SMY4j4LnloTFpak1DqMpL/QRUc2XjzjRBbbVjpE03VE4AyV0xlgB8dj9LSnPY2RkREWFha4+eabcd//k+h081snZsgfG8FaQ7zGLZ/v3fJRAMrXHKN85REAkk7I9Ce+ueK+je88Su2bJ7a0PStK4eNEhGS7A4121ygPqZ/Jkfs49uHwdRkMhwQjeAyHl2Je0lvTqeiJU9EzMQKFbURLVtEk4G5muTd3mq9XH+C00yawwaPIEco8gaNcxRjXME6JHaS5OoGYr7OmeK6Tiphg5VgLECHXasvvg1Cq0op5GBteKcgOEklCyXH5w//ydn7u1TfxF3/xF0x8606sH7oIfbLG7Kf/meed+WOsavf0dd/bP7FcpdV5eA67lOMH3/sqAK573y9z3ft+efm+X3rWzczf/t11y9LXohBb8t5p+yJ2Ur86dpoWXC1E43hlF3CDwbDnGMFjONwU8hLVOTOfVgMlcnt0SErZ14uYZFVJPdGg48xxG9/hY9xDgiZyYnL5BE/bKKXQRNzPAp/jARwsLBQv4mpexrVcydjWtjeO4dEzYKtuRCYr155fhAumJOKTiZwwktdYKYkYOmgRhSSR1+AHXd9LGIHr8oqfeikXXXghb3vXO7n9y1+i9f6HKVw4ykW/9OyzqrRO/tU/YBc98sdGuPAXnsljXv8iylcf69tmjgUuPHRaojZe6nvyNojgaM5JVBsMhv6j9AZt+J/4xCfqr33ta7u4OQbDgPADifT0pp7KRRirni16okgiLHEMwxVmR2xu4YvcwQkUMEoBF1uiRr3DQwv5FR19Q2LmaaOBG7iE1/N0xnvHIqxGa3h0Wnwg+VWRoURDsw3VityvVJBITj53sDwiSSKRqo4v/1Jxg+dKpMRz1xz3cBcn+RU+sXKsxC4xS5M/0j/O9XNFeQ9lYyuiSIRoVtVm22nkJ+3k/JiL+m+UNxgMG6KUuktr/cS1fmc+jYbzg5wnPXlm5ruzrxotWXAnRlYuTIt1iCJ0GPFZ/7u8Jf5n2nbMJKWVXo6sz8zyNYOmV/G42ExRJkFzByf4Kid5I8/kOVyeDi1YxfwS1JsrxU6cdCMf2SJ7yTERCzlv/4sdrVcKnCASYZPPidjcYJZVL9cwjoUiJBaxuUuExCgU16gJGPdkn5+cAUeJ4IzjNOLWkdfqOhKZc+yDm1I0GA4pByz+bTCcA44tPXl6R074gSxgzbTPShBCo432A27N/zOvq34FJ4yZ0qWzZzgBK0I660RLLRRTlHGweB2f4VbuQq+u+mm2JXqQ8+Qxg1AEWaMlvy8XoVqWiNLDZ8RPsljf8a4YGNkw1aW6bONDp2ExnW1WHYKLpuQYVCvbEmwlPF7EVczvcj+cedr8BFd3vViVUrdFQBCKuCnkYKgkx8iyuj6fmQU5fkmy8ZMYDIZdwUR4DOcXSklkwXXTIaPpuISZeWgVIY7RScytpe9w69h9TAY5HMdJJ2t7nKV5su7BwEaVywBFXDxsbuUuFHATadQ1jODktEQEMi+LbcvzuU43ihSEEklop9Gd4j4YaZE1MOz43UiOnY70GCpLtKofvqIw4mW1C/lw9Tsktl5HfPaXBI1ONC8LHwNWJK/DUvLaLj0m6cdWR16jSj1XdiqMpkblPdZsS+SuVBBBtMWIlsFg6D9G8BjOP5SSCpqcC7OLkiYCiUq0Ony2ckbETlLA0UhaCSR9cY69axwsJinxJ9zF5Yzw3OQyeOiULJwgi2S5uLKEPNFS+uwH3W21LBEae0EUQbsnTaXU4KrDkkQiWY0WVw5PcIN1GXdwgikGXwE1Q5MbGhM85t55yDe7x95KZ39Zlrw3FmoiTLOfZd2qy0X5F0VSvj6zIH9bLooAMikvg2FXMYLHcP6Sz8Gxia53puMzS4u3jH2TauTiOHa3sitLYWRX+RkrLtY3CfGkOFgMk+Nm7uDxpx3GFhrdyh/LkgUyTB87SkRURFHa28WSX0Rh92eD7q+jdTey1PHl+7wn+69aGcysMq0lHbRYl5TRBZNg27yep/NVTtIipEifx2300CSgiMsbSs+D8mwq7OhGrHQ6AyznyNeWn74vdNd3leE4sp+GyxIF631d5eLBM54bDAcUI3gM5zeWBeMjsuDUmtwy+S+0VcJUkpOhoLYFKu3ho+zuCIm11qet6R1APClnaHDL1Hd4x8izQVksTxknHaq51BAhlqVK8l73fm1fFtYw6qZR1iMb2Bkn3WnnSc+0896f9f5NNmsriNIUmyMRKMeW+zfbXe/TemQl9VbPoNFs6Khldb/20vFFhCqZjaY9lzDRtDoB8y3Nf6z8MG92P4eHjTMAG2JEwhI+b+O5jNkVuNCGh0/LLxttOf45TxyQtt2tMqu35LjlczAytPa+KOTkX7b/FmpyzIfLEvUxwsdgGBhG8BgMqdH2+HDAHZUZJqOe8vI46d7OIj1hJIs/nNMCNUGJ2+2HOV5oruzTE0aS/mi2ZPHPeysNvhoRY2Ek9zlLuKwhZDZoP7FiP8SJzAcLUs+K50Chx4cTR9DnptKoVPgooO0TRzF+qUjDs6gttmhECaGGZiwDHp5TuZyTeolbk68xaVf6KnoiEqZp8mqu57lcIT8sF2GkAosNud3xRYgW8t3xIrl0Hy3WYGJ0c9+SbYnRuZI+3lJD/nao3DU/GwyGvmIEj2FXufPOO3nrW9/Kl770JZrNJhdccAE//uM/zh/8wR/geR4qXdQty6JYLHLkyBGe/vSn87rXvY5rrrlm+XHe8IY38OEPf5h7770XgD/7sz/jF37hF856vu9973tcd911NJtNHve4x/HNb37z7I1qtnnw/vu56hlPBcAZLvDc77wNpyTN7e592ye49/dlXMGFP/tUrnvPq7rRil62Iip6sNLi9A/xHV7PM+Tvm23xFbXa3QnsSkkqJOkRMVHcfb7V3ZdT1GUXAvDAF/6BSy+6WKIRWVQli6xYVjoLKpDncBxZdIv5rfuVNnzZqYhaHVVKhVkSJXTimLDVIfEDFhyXBc9DdyLoRNgolAYfcNBcaCmKp2a4yZ+EkSu5deQ4VfIUrXMv0W8SsITPq7meX+L6lb+cGIV6u9sDKYzEVxVYInys1Lw+MSZVaFtFKfn7Qj6tbmvIv0pJ/h2gcSAGw37HCB7DrvE//sf/4MYbbySOYx73uMfxpCc9iQcffJB3v/vdvOUtb8HzuqmZl7/85ViWxe2338773vc+/uZv/oZPfepTPP3pTwfgy1/+Mpdccglzc3PMzc2t+XxxHHPjjTfi+/6avwdkkVqs04q794mW2pz8269x8b95BjqMeOjPv7Dy/knq0VjdHHAHjFLgo9zDryVPovTQPNQbIjxABEdnnW23FCSIYCkWVqaHVouxY5PSu6eXMOqmpHQiA0XHqrs6Lf1UvcPMYp3hdosEi/rIKNgWebQE1RJNJ05oxAklIEExZSfQ6qDCmJvqV3NFVOHm4W9wRjWZ0EUsy5KIkZWm0pS1dvqxhwTNDE2KuLyN53YjO73YNhwZk+n12bwsx5ZjVW+m7QQ0HB3fuUjJeTIKJQih1pCO2+WiCNB9POjVYDgomMsHw67QarX4lV/5lWUR8vWvf533vOc9fPrTn+buu++mWCyuuP9v/uZv8oEPfIC7776bZz7zmbRaLV71qlct//7//J//w9///d9z4YUXrvucN998M//0T//Eb/zGb6y/YfUmRBH36fnlH7nVIife83kAznz623QeWcCt9mxfGEEYMveZb/Ol5/w+nzz2q3z6iv/A13/u3XROLizf7ePqFXxcvYIH/ujv+dxVv8H/rrySb9z4xyRBt7pq9iNf55+edDOTw+Nc8tQn8iu/+zssLqZT3hPNdx98gBf/x3/HsR+9gcIPXcd1P/NSTtQX+aW3vQX1pO/nlj97jyyS41V++Q3/CVWt8Pv/7ztRxcLyc1x2xRUopfj8Zz8LtQb/v//6Lh73uMdRvvAoV97wNH7//X9KVJGS6QdPnOAFL3gBIyMjFAoFrr76at70pjetv/92SpJQbTYZqTUISgXa4yM4pTxO3kPlc+icR8NxaDsOw0NFKBcYGatQyOagXXoMNVLlufaV3Lb4YzzTP8q01eJM0iCM0tL+TjrgM5sWH0YSYUrEKxUSc4YG0zR5JpfwIf712mIno1yE4Yo8FnQ9OeWiPI/Vp2aDniu+smMT8v3JaUl3mX4+BsM5YQSPYVe48847mZ8XUfHbv/3bciWecsUVV6yI7vRSLBZ5wxveAMA999zD8ePHt/R8X/3qV7n55pt5xzvesSIVdhaNNsQJDzjdJn4X/sxTWfrmQyx89T5OvPd2nEqeIy96/Io/q/3Tw/zjv3oH83ceZ/J530/h4jFO/o9/4MvPfyvJqnLxe9/0IUaediU6inn0g3fyyAe+CMD0//4md73knbT+6VGuf/GPUBke5o8/9Ne8/C1vhGqF040az/jFn+VvP/tpjoxPcONPvhiNZqFe41X/+mcB+IsP3wZJgtaaj3/84wD8zM/8DL/+67++/Py/eOO/4ddfdRMXugX+5D3v4ZW/8VoWGnVe9rKXYTsO//m3f5vf+73fA+TYfOpTn+JJT3oSP/dzP8dFF13El7/85S3t8y2Rpe0enabg2OQvPsKi467IiiWJZsmPSLSmmnexlSLRcNS1xeR7ZFzSPdUKTIwyfvQS3jH0Ev6y/UJe4l9BzY2ZdXxO2W3mrA4NHdBMOjSiNnNhnVPhArPBIrWgyUual/GXjR/jHf6zGdOFdTcbEIEzmfpz4lVGplJBSvJPzWxu5N4qjgOjw9IhPIyk70+9te3UqcFgEExKy7ArTE9PL9++5JJLtvW3vfefnp7myiuv3PD+rVaLG2+8kec973m85jWv4X3ve9/6d3ZtCCz+eai5/KOLX/ksHnzP57nnLf+L2Tvu5pJXPQsrSyko6cFy4n1fQIcxF974NK77k1eShBGfueo3qf/zI8x97jtM/OgPLj/eD7z733Lsp58CGh758y+w9I0HAXjgD/8egAt+68d4ypt+ldfNPoGjR4/yqS/czr3NJT76ub9nbnGR6x57LV/7m7/FimNIEqIwxFEWP3DFlXz7+L18/StfJXFsHn30UZ761Kdy2aWX8s7fv4V3vetdAPzOr/8HLn3s1VDI8ZP/9y8B8OQnP5lqtcoTn/hE7rnnHv77f//vvOlNbyIMJXrx7Gc/mxe84AU89rGPxXX7VP4dRjC3KJGKiVHIe4xrTSvRzLR8Co5NlGhqQUTBsSk6FiiFHycM2VBYWBJRkVtDHCvFlZ0yrx96Fr/m2tzNLMeZ467kJGd0HT8JySUWU2Ge6ztjXBmUuSasUtLZa5sRIZPPSaqykBPBsTq9l3XrfvQM5K20XUEER8ekk3Q56HqwRqv98eC4juwvP0hbKDRgZHhd75bBYFgbI3gMu8Lk5OTy7RMnTnD11Vdv+W9PnDix5uOsx1e/+lXuvfdeRkdHeeELX8gjjzwCwAMPPMALX/jC5UgIIKmDcomZsHvFnr94nKkXPp7TfyuDcy959XN4+M9ul1/aFuQ9Wg9LtKr8WEmpWa5D8bIJgukarROzK7Zn+PEi2Jw0LRY3pMlg+8EZAIYeeyFnaDA+Ps74+DinT5/mxOw0D8ycAeDJT3wiluvIghcn0gwxiXnli36K177z7fzFX/wF5dERAF7x0pdJJKB3oR2vSgQCePDBBwH40Ic+tGIbz5w5Q6PR4M1vfjOPPPIIb3zjG/mt3/otcrkcv/Zrv8bb3/72Tff7uqQ+KepNSQkNdafUK6W4aKhAK4yZ74RorRnyHNx0+7XWJHHCRWEHVS2LX2ktoljSWIU8JRTXc4zrOcbLrR+Q32eZphxQRiI0QZRWpKXpryibQp9GaGxbREU+/ZeJ3kpRXkOjJSIp58rrgnRm27i83pPTsu/7NTU954nYanVEOLoOjA5JWbzBYNgUk9Iy7ApPe9rTGBmRRfnmm28m6fEjnDhxYjmysJpWq8Utt9wCwDXXXLNpdAdkkQT4x3/8Rz7xiU/wrW99C4BarcYnPvGJlXdOfRih23Ml79pc8ivPA2D06Vcz9ITLut4My4KcR/GKKQCax6U/SxJGtB4QAVO8ZGWVjkoXSrUqWlC4VDwarbtP4RMzNzfH7KyIpUuqY1w2LKXqX/3aXSQkUho9WiEq5iHnceOLX0rOy/FXt/1PPnLbh3Ach//rx14oIu7oxHLasHdfX3rppQB89KMfRWu9/O/++++nXC5z+eWXc+edd7K0tMRXvvIVRkdHecc73sHDDz+86X5fk3ZHBFgYiSdluHxW1CRONK5tkSQJJddeFjsAUZww0W6RL+bFvLsezbZUlm3VcJ2JmaGy7K8Lp+TfWFUM3LYtoqjRgtkFeOS0RHXmFkVwZL2boljGSPQ+r2VJKmp8RO6fRbX6gVIiXi+YFBF2alaiPsbfYzBsionwGHaFUqnEH/7hH/JzP/dz/MVf/AXf/va3efKTn8zJkyf59Kc/zZkzZ6hWq8v3f/vb375cpfXwww9TKpV473vfu/z7t771rdx999089NBDALz3ve/l85//PK961at41rOetSx6AN73vvfxi7/4i+uXpcNZE7jHn/N9/NBn3kDhsrUjShff9Gwees/nePjPv0DcCWifmCOYrlH5vgsZe9a1W9onl/7K85j539/ixO9/HOt7Czzrq28iiiKe97Snc1VlhBtf9CLe+u4/4hvf/Ree/NMv5vrv/wHu+udv8963vp3rLnsMY5OX8VPPfwF//bH/xekzZ3jB85/PxLVXLT/+RRddxIkTJ/jVX/1VrrrqKn7v936PX/3VX+U1r3kNN954Iy9+8YtJkoSvfe1rTE5O8vnPf57XvOY13HPPPVxzzTVEUcTs7Cy2bVMub3OUQ5LIQtwJZPEvrh3lqPkhp5s+Y3mPqYLLPQst4kRjp92sc602Y46FGq9uLGaabRGE54LjQMURf9CKGWHpnLAwkn/1JqDk/lYilWBJcnbvnEJOKuTmlsTbMz6ydjpuJ2TjUcoFmK/JANzxqoggg8GwJibCY9g1XvGKV/C5z32OH//xH+ehhx7i/e9/P9/97nf5pV/6pbOqtP7qr/6Kj3zkI+TzeX7hF36Bu+66ix/+4R9e/v0nP/lJ3v/+97OwIFVRd955J+9///v53ve+t6Ntm2Dl8yulGH/O91O6fG3BM3zdpTzl71/HyFOvZPrvvkXrgRmOvfypPPmT/wnL29p1xNS/ejxP+Jt/R/H7jvHwh7/M0sICr37J/8Vfv+0PIE44MjLOFz74P/mp5z2fR0+f5s8/fBtRFDFSLC0vxK965SuXH+9nX/GKFY//tre9jQsvvJBPfvKTvOtd76LdbvPLv/zLvPe97+Wyyy7jtttu4+/+7u8YHx9froB72tOeRqPR4K//+q/5m7/5G66++mo++MEPLkfntkS7I+kcpSSqs4bYSbTmVKPDdCvgwkqBsaJHJe9xyXCBTiQmbKvjM9TxKRyb2FjsZNVX/VzslZJqqaEyTI7BRUfgyIT4dPI5KXW3lKS5puekE3M2wb4TdI3FlgUTI/J30/NpZ+U+mo5tWx5/dFiaVfYzmmQwHDKU3uDD98QnPlF/7Wtf28XNMRj2hr/i2/wBX+Io5xgl2AGnqPMf9dN4ef0yiQQkOu2zo7uN+rLPaTY7y7bg6ktJHIehoSG01pw5c2b7kZh+kiQSbeh0JDW0jnelE8U8Wu+QdyyOlPLL0RyQdORDS23m6y3Ga3UKR8cZH93kmCzWZb+MDffxxWxCb7PGtp/Ozuo5l1qWpJ5KhW7zyCgWQRInEo3x+uy96Y2qjQ33zztkMBwglFJ3aa2fuNbvTErLYACuYmwgc5m2govFlWpMogn5nIieVkeqhbSWvi9+kEYUXBFCQcRtf/p+PvnFO2g2m7z6la+iXChu/mSDou3LYp5P0zhrjEbQWrPoR8w0fSZLOYZzzlm+JjEx5/Gm56gVCxyrbiLgsjL3sWr/XstWsKxuh+QRRMQsp7/8buqrnk5ZL6UT0idGZHtPz55l4O7LNo2PSIRtbgnybYn8mDEVBgNgBI/BAMA1jGOhCInP8vMMkpAYheIaUqOz50r65MwsnJnvTibvHTMQxWDb/NH/+Au+9A//wHOeeQO3/MfXdbsA5zx5nFw61HKQC16SSJqm1dmwIilONKeaHYIo4ZLhArn1OgdrjTW/xPhwkdJwZUX0Z03CKJ1avseVSnZPRAck4tNsy6yzKIaluvxz3a7wWayLOBmvih+oXxTycMyT4/LotIggU8JuMBjBYzCATC9/EVfxEe5mit1LC83T5iU8lhJpNKfty1iBKBHPSK0hC3rvwp/IKIjP3377ygfrnXDuB1JeHYRSvpz1l8nl+jefqeNLz5m8J1VD6wirVhhzst6h7NkcqxaxNopoNFrgh7hHx3G3ItRaHSjswynjXio2qxU5FtkYjzCExbQi0fPk2D5yRkRJP6elW5ZEvYq+VJlVSmtWyBkM5xNG8BgMKS/j+/gwd5OgsTYbwNQHEjQaeJm+Vq70F2uAkjRHtviNVyX9UW9KFMOyJKW11hyvzGjruTLuALopsY4vXXpnFyWakPe6Imi7EaAkgYW6CKqx6roVWFpr5toh852Ao6U8ldwmpxs/kKjHkfGtb1OrI71o9itKdfv4jA6LoG2mvX6CdGZanIqeUl66Kvc12pOTx5xdkP07Xu3P+AuD4QBiBI/BkHIlY9zAJdzBiV2J8szQ5IboQh4zqyGuSVl1YVUvGceW6MliTap8rHQY5lYNr0ql4iYVSL0CqNaAmSwCtEUB1BvVOTa5brQoTBJO1jto4LLh4oreOmsSx/L6sgGmWyGK5F+/Sr0HjVIiDot5SIZFrDXbIoIsSwTp0gMS7Rkqi1jpR0TGsWFqTFJcp2ZgfLQvg28NhoOGETwGQw+v5+l8lZO0CCkyOF9IMwkoRoo3zFwLlYJ0711vcVMqHSVQkHLvKIYtlr6v+VjLAqiSCqC02mgjAaS1LJjNtlQArdfxGGgEEScbHUbyLuMF7yxj8lloLSXV5eK60aI1aXW212xwP2FZ8nrLRRF7rY6k85YacGZObnuu7OdyT6XXTlFKIkz5HMzMi6Dqp2HaYDgAGMFjMPQwTok38kxex2fwsPtfuaU1URiypBu8LbiBsaMXbz19k/fg0mNQa/Yv7dGbcllXANnyfT4nfXXWSYlorZluBdT8kAsreYpbjdQs1GQ7qttsCdDqbNx9+aBg2+KxqZTEzDy/JAIwTiR92EiP91BJBNK5mNCLeXDH5fGzFJep4jKcJ5h3usGwiudwOTdxPdM0iehTEzcNhBFRp8O01eTVzpN5buUHtr/YWJYIg0FdmWcCqFoRL83okKRcHFvSR6fn0l4v/ooGep0o5oGlFkGccFm1tHWx02itHNWwVeJ0dtZhS804jjQ6vOqStMGhEkEURbLfHzkjX6No58/hOjLvy7YkxRWew2MZDAcIE+ExGFahUNzE9QDcyl1Uye88vaWRxTmMaFoRS7mYV1tP4ZfSx9+3LDcR9GXGVC6tIgtCESjzNYgidD7HrO2woBWT5fyavXXWJQhl8T4yvv3KsbYvguCwRidcFy6akkhMkogAbba73qtaU0zOQ+WdeZiUEr9UrSGm+MnRg+OFMhh2iBE8BsMaZKLnCka4mTs4oxtMhB5WrOUKeb0+Mr3ECYQRCQkzuYCileNt/AjP5YrBv4BzIQhlofVcSWFlokIpWRRzHoxApxNwcrGJG3S4LI5xI1+MtoW87KONhE+ciEl5dHhnHYcz/85hxrJEiCzUxNszOSqis9bslrk329JqYKi0Mz/TUFmiSmfmJMp22Pep4bzGCB6DYR0UiudyBddxhLfGt3O7vl+8n1ERNxM8SRr1yCqnVDoSIgwJk5h5L0RbihvUZby69RTGrSI6p7ceBdlNtJYU00JNhMg6fWG01sy2AxY6IZPVskR1tE7HLHRkthSq24hvtaDRWroyF3Ld8vntkKRdjXe7u/JekJmNPVdEyVhVfD4jQxKdabTA92HG37nPp5iXKq7peYjKh8MXZTCsgRE8BsMmjFPiHYtP5XjnUj5UfICPVh5BExOS4CWQ06A06CjCJyZIQlzbQXkOL1Hfx0u5llK9yPGFJqeocbSc59KtlGrvJkki5eZRJP4Od+2oSyeKOdno4FjWynLz3pLrLPXVbMsi3TtXynVkkY4imJjY2ba2fREA+2n/DZpyUfbd9DwEaRPB0WFJdTVaEvXJfD6Ldbn/UHlrkUiQqN2R8VT0xCKo9qMoNxjOATM81GDYiDiBEyclxZOTzrnNqQp3FxocZ4672g9ypjWLb2tyymHKq3J97lKutMa5hnHpoAzct9DgkVqHMEnI2TYTJY/JYo6RvLv30R4/kNdXSJvjbRbVKa49B2tNsqqvZlvSUBqJzlw0tfPhlrML3Unm5xtRLGXlji3RniySo7Xs31pTIj7AcpRtqLR1f06cyOPb1vaN5AbDPsAMDzUYdkIQwskZSfEkMfgalKKUr3A9Q1zPMV4+OyGCyHPh8gt5QHvMzAdMVfKUhrqLTMVzsZRPmGiiJMLpKBINtSDiaCm3/mypQaJ11wC7QW+ddaM6W6G37H0kgYdOi7CaWUjnSuVlUd5q999sYa/u4+7Kg8SxJRIztygVc5MjkspSPSlEP20p0OzILK9mS/b/UOnsxparsS1Jb80uyONPjW6YHmsScDez3MscX+cUp2kQEONhc4QyT+AoVzG2QvwbDHuFETwGw1o0WrKo1JuygGgNthJRoFRaxbTU0/1YEcYJj7Q7xInmgaUWwzmHSjrU0rUtSp5NM4zQwGInBA2J1twfxowXPcYK3sZzpvpJknQrgI6Or9nXZ8dRnfVYqIvAGR+R77MxC4t1EYylguzfjQRVJ9i6afywslxh1YRTs+LpyfcMB815MDEKI5Hcp9HqTnHfis9HKTlG80uSkpwcO+uYHGeO2/gOH+MeEjQRCTkcPGwUEsi7nwU+xwM4WFgoXsTVvIxruZKxQe0Zg2FDjOAxGHrRWk709aYsrs22iAKlZJEt5WWhnluUwY+uDaGIgHCpAfkyfpzgoXik3uFK18axLGwFedvCthRayyzQRhgRJZqyZzPT9Kn5EUfLeYrugBfzIJS0RT4Ho6NrXvEvR3WU2n5UZy1aHTE0H5voPt/ymIWkK34WahKFKBelx87qbWu1d54KO0woJT4ezxHhWq1I48JeHGd9n89SQ1KClXWET2aWXqjBmVmJ+tg2szS5hS9yBydQwCgFXDZ/v4bEfITv8mG+yw1cwut5OuOUNv07g6GfGMFjMGRk/ohO0E0LZB43y5K0SzrNm9Fhufp1bECBbaEaLexckURrgljTiWIerXe4eKiAYylQioJj0wxjXNsiSR+7FkR4lkVZw4NLLUbyLpPFHLY1gGhPqy3m5NHhNSuklqM67ZDJUh+iOiD7dW5RIhFrLa69puY4FuEzvyT7vpKOX7DtbjrriIkQLFPIy/6YnpcGgmuZjS0rFTel1OfTkPf3wpLcHq6sPdpEKXm8xTr69CyfPVLnLfYdtImYpLStAbsuNlOUSdDcwQm+ykneyDN5DpejdmFQr8EAptOywSB0fOk62/FFFDTbaZfbniqkMJJY/QWTctsPU++JRitFkiRUOh1AKtMbQUwzjJlrB9jpYuJaCie9bSmFQlN2bcJEs9AJaIcxC+2A+xeb1P0+dsDNZmHNL8nV+hpiJ+uW3A5jLqsWqfbDUK21+EEqpZVpl/WwbVmcj02IQAojeHRaFvSlhhyHdSrIzltcF45MiIjJhOJaZD6fI+OSpvJcEZjzi7KPG62z/1Yp9EiFW8fu43XWZ3BS4bIdsdOLhWKKMg4Wr+Mz3MpdaNYvnDEY+omJ8BjOb7JGbgu1bnQhSaSvjm1L+gfkd1kpsEYiQZ6TtvgXA3KsLEabLU4Ou9iWRSeK8aOYmVaAlwonpRSuLYuFBmL5KSN5l0YY0Qgj/Nii7Nk8XG9zVOcYOdfxCZlfR2s4evYsrERr5tKozkQpR7UfUZ2MWkO+Dm+zoqq3yWGSyHGZnpf9vVgTwdaveWKHgcxsfGYO5pbEhL7RMNpiXszjrY54qMJQhOlSXQzhaRNDjeZW7uLW/LeZTIVKPyji4mFzK3ehgJtYs6jGYOgr5oxhOH9JEkm1NNsQRHLyV8gVcxhKKiaKJSXgOmmEQsuCG8fysxBQEGmNVhZWklANAtrFAlEC9SDGsSxONzokWiNZKkXBUbQimdPVCmPyjkXRsYkSTZgkNAMYyilaYczIuVhWwhCmF8QPs0bJeSOION30ydsWl1X73BvID0RMHh0/t/Jmy5IIUTP170SRVM/lvLMnrGvd/Zdkt1f9/Kx/6d8ub6JiRQBjxbav8bs0XYllpbet7s92E8vqNhCcWxRj80bbkEV8ivmueTyMUjEvLRg+W3iUW9VdTFLq+yBdB4tJSvwJd3E5I/u/A7nhwGMEj+H8JE5khlAQShrLDyTyUcxBoy0n/jCSKI7W8jsFhLF4YHq6B2sgTjTa0kSWxVSnw4liAdeSlFUtCKnmXFphjK1Ao8k7Dn6sibUm1gmz7QCFwlIw5DnkbAvPthkvnEN0J/PrjAyLR6OHME440/TpxAlHSjnKXp9PBVlUaXR4+5GYTKwkSXdieBxLtMh1ZId7rpig55dElLqO9EmybVnIFSI8FOn3a/3r+R3Icy5vw/J/G3+fiakkSQVW+jXR8vhpBR+WWnk7E0W2LdGZ5a9W9347IRtHMbMgEZut9NJRSoRjqSBpraU6BCGzsyd5y9HPU3XzfRc7GQ4Ww+S4mTt4PEcZYwedtw2GLWIEj+H8pNHqDsIM07RVzoVWWr6bmZRdR6I/WeQj80j0mG91+i9JNIlnkQ8jikFAK5ej5DrUw4hmGBPEybKXR6MoOTbzfkAYi4thJO9S8RxsSzFWOIcyda1l0aq35Iq/p+mc1pr5TshcK2Ck4HKskh9MKfzckkTESqt6+2gtIiaKJVITx91IWhR3RU4mEDIBkEXaMmFQSCe6W5b0SGq0u/O1hso7m8/VT1ZHmpJkjdtJd+p7HMvrjuPu+2stMdT7M8deW8xkomd6XoTPxBYbCColkbRyEepNblFfoW1FTA1YhJTwOEODW/gC7+D5A30uw/mNETyG85O8J4tqMQ+BLSInC+m7bpqe0N1IgJ0uus32WQMWk/QqXwO2stC2xVirTcvzsCxF0bFpRXEaIJI0Vhgn+FFMnIivJ2dLuXrFczhSzi97frZNksiVfazF+Nvj12mFEacaPq6luKRaJDeI0QxZM8NmW3wki3URNpmgiVPh4qQLdiYqC/n0+3UiHPNLIp6qlTWe1IV8Xh673hIfi+uI8Cnk9qZbcG/kaLtdBrTuEUBJ93YYSQVhrziyLYmgOWlvoqxHkeN0Iz3T8+tXyK2z7ceHfO5ghknW2t/9Z4ISt3OC48yZPj2GgWEEj+H8JOfBsUlZnBfr8jMr7bWTpJEGx0rTWenXVnuN9IwmQSI8SmtsC2JsCmFILoqIE5diWoXVDCJsSxHECY309mjepRnG2JYi79pU8+7OxU4YyeKW92Ci69eJkoTpZkAzjJgq5ah4fTAlay1CJkhTf2Eot7MxEtWKLM6OLfu6ZHcX5Z0891aGhdq2PO9wOfWk1GABabRXKmxvoOZeolS6rza5n9Y90bH0ODTbXYEJsk86vkQ0x0ck8uXa3dTfOtzGv0hGbovVWJ+99Ndpn5iVzbctvPEK1adeybV/8ApKl09u+vdWWpz+Ib7D63nGlp7TYNguRvAYzl+ybr1OulAu1sFOPRhZqiVO5KoZ5LaNlKOnJH6ITjRKJ/JhimJirdFJwlC7w0LOW3Z+aAVBnMj3SlJYtqWo5ByiRCaon2n6lD1n+2kmPxCxM9yddq21ZtEPmWkFDOdcLq+Wtt/bJ1tUg7ArbDJ/k22Lx8l1JUJTsWG+JsJku1VZG5Et6ltNU/V6UjpBV9SWiyJ+tjrGYr+jlLw3XQdYVfKfpcyiWI7V3KK8P7JeR0n6vnbd7mN4Ljg2TRXyMe5llLVHjWzE5AsfT/GyCWY+9W3O/O3XiJZaPPX//Oct/e0oBT7KPfwaTzFjKAwDwQgew/lJFEn1kmtLpOfMrPgXgkAEjx+KATWK0yvhtAnb1Jh4U1J/RuvkLFGySFMpNDBbHSaMEjpRRKQsgiAmcjS2UuQsi0An2GkvnqGcy1Qph60U9y00ibQmTKREfKK4hZ41Ga1OalCtLs/Dakcxpxs+SsHFQwXyWxnFkCQibPwwFThhV9hkC2IhD0PpArk6YlJrSPpvqM8ddDu+7PPtikClJKVVyMlrqTWl38x+8fkMEpUZorMIW0F8VWEofaSgK1yDUCJAoXiq7i7Ok4wluNb2heHFr3wWR37qiZz52Nf56k/8AY27T275b11sNJq7meV6jm37uQ2GzTCCx3D+0fHF2zBUkoVvLq30sZQIhkoJpuckauK5sthmKQLNCn9GECcktk2YNmxrKBuVc+jYNpZS5JRiLC9enjjR1III11JcPFTgSLnrBZoo5TjVkKaFc+2QkbyLs5UUTK0pBuXUnBwnmpmWTy2INp5/pXW3eWKQdpYOI3m9nisiYai0trBZizCSKMq5lqCvRceX7TkXXFciT9VK1+fjudJl+Fz7HB0ElBJP1XwtHQo61u1z1EuScG98hkglO3qah/7088z+n39h9tP/DMDRlz55W38fknCcOSN4DAPBCB7D+YPWMiNrqSF+hkJOSpsbze59xqpytZvzUrGTznoKQ1n4cyujAkkUE9sW+XQ+1ljeQVsWSRuZOKEUIwWXoiul5rl0ntZqqjmH+baFHyckWjPbClYIojVfy0JNtv/IONqxWeqETLd8Kp7DFavTV1GcCptQxE2QvR5PXlO5KK93p1Vhc4siHvrdBVlrmbM13CfzbK/Pp9GSyJjryPdb6QR9kFEKRofOmo+1Asvi69YMOXZ2HKc//o3uQ+Vchq+/dFt/72FzF6d4OT+wo+c3GDbCCB7D+UGSdEP6R8ZlkcsaD2YUC3K1P7sg3yslaSIn7bicpQgytKZsQcN1sJMERymmCh5e3sOzffw4Rinpolx0N/6oKaWYLOV4uNYGYKETMlrw1jYwZ+MaogSOjNPRcKbWJtFwUaVAwbHS/kJp5Cab9p6Jm6Fyt2dNP6inIwn6ncoCiRxlXpV+0luC3WhJv6LMy3WYhU/PfKzlSM+qdOdpGnjbLi0TnviRf8/UT17P4lfu40vP+H/41ivfw9gNj6V42ebGZYAcDmdo7Oi5DYbNMILHcPiJ0uol1xWxk6VoFmrdVJVlSci/E3TnCXlud6FdHfoHSDR5xyafz0n0BCDngOdQcEOCRNICQawpbuGCuezaFF2bVhjL9IqWzwWVVcbROJFOuLZFNDnCbDuk5oeMew4jSYxaWJIUkG3Jwl3MywK30+qozchGPRwZQCoLJLpzrumsjTgfhU8mepTqRnp6qg8D4nMa56mUYvj6y3BKOcLFFs37prcseBTgpwNXDIZ+YwSP4XDT9iUaMpxOi84W5bYv6a2MsapEPNqd7s8Km8x0iGP5m97UUdqt1+3xvYTJ1vwQSikmizkeXGoBsORHjBZiCtkVeFp2nuRzzLsu89M1hnTM5VGI00oNusV82t14FyqRtBaBMDxAA3DHX3PQad85H4VPtSKv+/ScTFxXCoIIz9FoR7MT1fPQn36e2c99h9rXHyRcbGEXcwz94EVb/nsN5HYYXTIYNsMIHsPhJBsKWmtI07XeRSuOu2krkFRWMZ/22ukRPMVNBE8Unx05ScVN70yqIN76NOiia1PxHOqBTEqfbvpcMlyEVgd9aoaGbXM6SCjoFpcWPbxSAQrVwUVwNqLREoE31McS9F60lnTc+MhgHn8tVgif9uEUPkmS9k9K58WFIdzzYOrj8jhSzXO/U9vRQ2ceHrdaZPTpV3PV776U3OTwlv/eJ2KKAb2fDOc9RvAYDh+ZNyeMpWqot1mg1lKhFa9KZSkli2sWjbHtzaMWmeDRPYImjfB4PVGfrUZ4MiaLORpBhI5imm2fxvwiXq3BmVKJOJfngqECxXSa9Z4RRZISHFQqCyS96DrdsR67iVIyf6xcONjCJ04k3drbbiBO0v5JaR+eqfFUvCYwNcYT1GV8jlPbeprnPPiuvmxuQMz1HO3LYxkMqzGCx3C46J32fGTs7JLqxbqkSQBQEv3JzLttv3u/rYwkyFJacY/nQJ8d4cnGSWyK1tDxybU6VBttFhKIgQeDiOLUOOMjlf50ST5XtBYD+KB72WT9d/aStYSP58LIACrSzpUk6bYZyAROnIhB3XM39nMVcstT1q8aG8VRe9OV2sUyoyUMA8MIHsPhod3pekp6/ToZrbb0rMmollf6dDo9gmcrC20Uy0KxRoRHJqWLJyFMNInWa3dPThJJo7U7IrhcB4p5hidHODlTQ3cCrEqZC6tlhnL7ZIFttGUh7Wc35bXoBOvMztoDeoVPrQGnZruzvfaic/PqJpFBIFV7nisCp5BP2wQ4Wx8cOjECp+e4ZqmAVVWExLi76KcJiVEormF8157TcH5hBI/h4KO19NapN8/262SEkYihjGxByEgSSWllbFXwOKsiPGn6SimFa1sEy8NCNTknXXiiSEROqyOLVc5bNhsnlsVcO6A1V2MsCGkOl1GOzWw7ZDjn7n10J4phYWmwqSyQYxqEZ/U92nOUkvdNuQiLDencnI3zGNT+yPaF3xO5iVY1iRwub13crIdlwdQopZMzvMi+iI/k72PKHl5pyh8g87R5CY81YyUMA8MIHsPBJklEyMQxHJ1YuzopSUu5My+N40h/nd7Fwe8pR3fdrVU5LVdp9YT/k260x7UUQaqFQj8g1whE5ESxCJxKSRYry0rnXkXMttpU/Q4XEKMumeR7dZ9Ya4I4We7Ns2dkDQaHSoMfyxCEMvZjvw78tG3xfg2VxMv06LREe0qFcxc+mcDp+N1eStmIiJwn4upcxc16BBFozcseGePDlx0nsWKsXVgmEjQaeBnXDvy5DOcvRvAYDi7ZdPCcJ5Gd9UYozC/JAgLd0P3qNMRq/85m6HTAqLNa8HT9Oi7IghWGBA0NQ0UpGc95y9uqtaYRREw3fRwFFycRuSRZFm/jRc2ZpmzbbDoEdNsDQPtFsy2veXh08M/lB2v3PtpvuA5Mjoo4WahJlHFkaHveI53Obuv43UaRti1NMMtFEeeDTpuFkUTu0irFK/NHuaF9hDu8OaYYfFpxhiY3cAmPMf4dwwAxgsdwMAlCmYc0XNm4w+9SQypQMjLBsZrt+nfiRISOUisFTxRJ5+FmC6+ddmfO5wgrBVg1KqIdxUw3faJEM1n0KDeaqCAUs3W6wI3kXRba0sQw0pr5zjYHi/aLOJEFfXJ0d6rD/GDzPkj7iXxO0nzNXmPz0NodorNy+06Qipw0mpXP7Z7AyYgT8bXVmoAGZaUpuhKvbz2LrwYfouUFFK3Bic8mAUVc3sAzBvYcBgMYwWM4iPiBRHZGhyWFsB71pnQBzigX125iF8fdCBBqa8MkM/8OSNl0NnW63pKUWaWEW7WhIUIq7El1daKY2VZAK4qZKHpUPQc1X0vHXqysLLOUYrzocXJ5sGiw9cGi/WSxJmm43Yq6dAKoDu3Oc/ULpeT9VcqMzTNQKsJwSVokLEdwQikLz9JTOW/3S++zuXKL9TQqmW57dWj5fT1eHueNjR/mddbteLaFo+y++3kiEpbweRvPZYxdaDBpOK8xgsdwsMg6J49VN24M2OpI6XRGPid/s1Z0ojedlfe25huJoq5/qNGShcxNK2TS9Jobds3MQZKsEDpjBY9jlTwWdD1IU2uU0QPD6WDRTpyQaJhpBRzdaLBov/FT79GxrY0HOGciabq4K92iB4FSInRAju2jZ6TCazgdWprb4ntsUHQCmF/sivx8TqJRa4jZ55Su5abFGW7Nf5tJSjiFDS4wtklEwjRNXs31PJcr+va4BsN6GMFjODi02iJi1qvEyugEYlImm4nlbZyK2U46KwylLHtuQR6+XIQLJuAkXdOz1qAUni3PFyUJs62IME4YL+ZE6CjVbYKotWzfOotgNlj0oXSw6GJqXs7tRlQg80BVh3YvCuGHK3xOB4IsTdX2pcVAFEtKLptIvliT35eLeyd24hgW6tBIR6o4jgidDZpYqijhpvrV0Gpz6/j9VLVDUZ27Yb1JwBI+r+Z6fonrz/nxDIatYASP4WDQaHU9JBulVYIQpue64sNxYGp9MYHWqyI8awiebOREvSmpq1IBKmUxN2djFWy7G5mIY7AswjihHojQKTg2l1dL3YaESSJiR6kt+WJKrk3JtWn2DBa9cPVg0UGQ+Z/Ku/BcGZ1g/5Wjr0UcdwVO25eIVCF/ljEdgHzazfjMXLd/z24JH627n58kke0aKku0aaNtSBKYnkclmpu8J3FFfZKbq9/kjOMzQQlrB8O2EjQzNCni8jaeayI7hl3FCB7D/qfWFGPl1NjG5dBRLGKndzzE1NjGBtAoWjlmonehDSNZKBotMZ9WSt2r4em5lY/bI3g6fshMO6ITxRQdG8u1UUoRaS2VW1lkx7LOLo9fh2yw6APpYNGaH9HOxxTcAaZ94lg8HrtlVM4IAijtQ/9OVi6eiZwwEoFcyMHIJgNbsxldxbwIj5PT8jeDHhHiBxKhy3pM5XNSTr9Zl+jsPRqG8pmbGOX7GyXe+sgo//Pod7gjdxIFjFLYUnPCkJh52mjgBi7hDTzDeHYMu44RPIb9zWJdBMeR8bUrXjLiWK6eo1S8ZJGTjf4G1o7utNpiPs5SEEfGzl4g/BBGen5mW4SJphXGLNZaVEaGuKCS59F6Z3kQaBgnFGxL0m1KbVnsZBRcm6GcQ81PB4u2fC4eKgyuGeFifXeNytDtIDzoPj9bJUkk5dlKoziWkihOdUj8Xtvd97Ytw1A7vqRnGy2JCG32Pt3Jdi/UJSqJlucd3YbAmq+JqLNtgrEqj9Q7PLTUBsq86dT1nDl6PR/KfY+Pcg8aTUiCh00OBxUmaKXxHU1AjIuFQvESHstLudaMjjDsGUbwGPYnWsuC2+qI2Nno6jlKxU7YU2m1Weoro5Ne+SYaohAeOSPPVSmJV2itkH8cy/al29SOYhp+hOWHFB2bi4o5rLRBoGt3F5cgTsRwrYHJdfoGbcJEMUfdj9BAM4xphjFlbwAf48yofMEuGZUzMrGzl6beLM3ZbMuin82hykY19IN8Do5NdKu5shRTP5oWNtsSRYpjIE1fbSeFVm9CvYFGsVAuc6buM930aUcxwzkHb7jEldN1Xn/kqfya+xTuZpbjzHEXpzhDA193yCU2U84I13OUKxnjGsZNB2XDnmMEz16itSzWfiBfk6RbImql/V0cW9IszoA6q+5HMqOsv7InzZpEEZye6/pnSCMnW+nhkiRi4Gz7sv9LYzA+vHl0wZdFuR0nzLYCOlHMVM6lEnlyiHqaD3rZIqM14WIdLCTNtsNjmbMtqnmXhY6Iu+mmTylNmfWNbDjoyNDuC4+9ajiYiZxWW4ReJnJGhwbXEycbU1EsyPv95Iykm3Y6MDUI5XEyE37Ok8rE7UTLOpICC2PNmUKe2SBmqRPiJwkKKLsOblaBNj1P6eg411vHuJ5jvJwfkJ/7LfB9yI3s7HUYDAPCCJ69IAjFl9KW3irkcyJsbFtOTlqn4ic1yy7WpUGY50IxJyfIfofAd4uZ+W7/kbXQulumvda0817CCM7MdtNY2fTzjXrzgOzbeksqZ5rp4lYuwuTWhIjf9lmKNEu1NmMFjwsqeaxmG1qpwbdnOrprW8uLaag1XHTuM6gmih5LfkiioRMnLPkR1XwfU0CNVlpavYtG5Qw/6JZ0D5p0Oj3Njggd10kNxUO7WxKfdWtudSQCmJWJb1VoJYk02Kw15DVZlviDytsccxHHJNPztPyQOcfjtFaEgUQTPUsRI/PhLIV8XjqBpL7Gqysfx7GgGa/xBAbD3nJAV80DShh1xxxUSt1UzVZOStlwy1YHTs/KSa2Uh3Lp4PQrSRI5QSaJiJSRoZWvXWsRRJoNy7QBSV+dnusajpWCidGNe/NEsSwKjZYYTSslEZUKWWQ2OA5aa5phzHw7wF1qUhwuc8VIqTsBvbdku2eYqKuQRTWOCTaritkijmUxVvCYaUk6bqblM5Rz1p7Gvl0yo/I5RKF2jNayiI5WB/8czXZX5BQLkl5y9vB0mAnMQk72/8mZzXtNgbyG+aVU9Cs5H4zsYIK71rRPzdJqtmlYNg85LnmlyNkQa42FwrYVtqW60cSxYdnOZnulOLbtFaLfYNgvGMGzW9Sbklcfruys6sWyJE1TyMNoOnun2ZJqj0Jexivs99lD2YDOnCuemzjpGnfTElhsa/25WBnZWIl4lUF5vTRWEIrQaXUkepAtbnOLLFfWrrPvEq2p+RHz7QANjBU8hlwLa6i4cht7F5iek73XaKbpsiJhotFa9yX9NJr3WGiHRFoTJpqFTshYPwaLLtRl8doL03AUSyq33wI+65HTTNNVti0XC0cn9l+k1LK65uLZRRE0o8NnC+U4FqHTlN5MeJ4IkB2cA6IkYeHUHMlSk7aG06Uiw3kXhWIh9bgVXYdOFGP3vnet9LM6Pd9Nu4Mcvyhe7kdlMOwX9tmn/ZCyVJcUytHxzctBt4JKxx/kPQm/N5py0nGdbvXIfiQ7OVuWbOPsgpy4x0cksuO6ctLe6CTpByJ2Mp+MslKxs8r3kF3J1xrdiNoFUysjMVmpLpy1UMSpiFjoBORsi8lSTrwySbLCsLzMWhGepTpWy8epFIlQaCBK9Aoj806xLRk5cbpnsGj1XAeL+oGkWXfbqNz7/F4f37u9bQVsSyI5m1X77RcyU3NWwj420n2PN9OoThzL+3+kIu/vHYiLpU7I3NwS+fkaodbUq8NUCh4KWErN8XnbxrYUllJnv7+y9PTMguzbbLacpUT4H5Tos+G84AB88g84jZaInc0qjXaKbaUDNMtyIpyZ7wqh/XZirze7+yATbfNLEmmZGttc7DTbaZVT2lTQSsVOr8kzq1KpNeX2UGntiFqSQNBjdE777/hxwnw7oOZHVDyHi4YK5HuPW1ZFtPrxLEseh9R/lYncI+O4DZ8o9RkFSdJtPniOjORd5jshQZwQa81cO2CytEPD614alTPC6NwjS0kiUZxGq9skcrP+TfsVy5K0Vjvz9niSgu31/o1Vd/w5T7Tm9GKDwvwSYaIJhsvYaQrNj2KCJMFCUfJswjhBKXDW+nwOlSRtu1iX9w/INoWRETyGfcU+WxEPGVEadh6U2OklG1xYzMtif2omHQa4ix1dNyKK0pEBPQuPRk6KSolIWc+oqbUIiMV692eWJQtZFplJElnkaqmoqlbking9AeWHZKMntOvQjhPmGj7tMKaad7l8pIi71n7z1+kRo5SIzziW+yzWJVLi2Hi2op1qqzDW0Ke1VynFRNHj0bosgPMdGSy6I0G1l0bljCwSt12yhoCNlryPct7KJpEHnUJe3s+PnhGRXiqIX61SPKfXZ2nNhZ02LduilnM4bTkUwpi8rWikc+BKno2lFAmsHeGBbk+pkzMiygp5SW+F0dmRV4NhDzGCZ5As1uTEu5tXl5YlJ8dyUZ5/dTh8r2ilV6XZCTpJ293nPBFBbR/uf1QmS0/2NCbLqraare7PXLfbVDCOReTUm/IaJ0a25mPwA7F2xAmLlqbZ8BnJu1JxtZl/aD1R4NjyOjp+Knbk49UrnII+mzmHPIc5x6ITpYNF2wHHtjtYNEn2pqPyaoJ0ivhWiRN5XzRa8n4qF/fefNxv4lgib622RHSKhbRnVHRuHpn0c1VCkx8q4pfLVIOYZhgx7YvYyTs2+VQ869Tbb6/3fFlDxdkFOQZZhMdg2EccojPDPiMLre+VH8JJT0BZOLyY39t0RaMleX3opp1cp+s3yrlyYl9YglxOmrDFsXiTer02hbyIGq3F31BvigDZhgE1TjSteougE2ArRWW0wFS1uDUzcRB0w/arSRLZ36WV5cC9EZcw6a/gyUZOZINFlzoh4wUPbztRnlpTjsNemt6zZo6bVRdl3qxGS/Z1NtZhJ12P9zPZ/La5xXT+lSU9gcrFtNpxCU7NSmRlJ8et1hQRZVnYU2Nc6DpUg4iHa21aYUwYJ+Qdi1iDrST9Za8X4cko5GT7ZhfTsnV//fsaDHuAETyDou3LiWhQTcu2SiEPxyZFSJycERG026ZmrWXCuGN3xY5trfTetP1u76H7H4ZrLhMBFPVcJVZK4ldaanSFzjau6MM4Yb4TstgOONLxGcq5uJbaemogjmX71kpPhpG8xmJeft9zdev1LBJhrLe0rduh7DkrBovOtQOObjXKE6el+kcn+r5d2yKIJHK33nGI4q4B2UrTt4NsCriX9EZ1QD4n49Xu+9y2JaXVbMsFQZa63qrga/tysQDyuOmFQsmV9OtQziVL9y76IQXHJtEa11LrR3gyqhVpm9EJTITHsO8wgmdQ7Kd5QLYlQiczNQ+VxWi4W1fEfpBepTqyDVmJvSItGQ5FwNg25F1JVTxypidio+REmiSSottG3xStNe0oYaET0AhSf045h9tIF8qsm/VWWM+wnM3xGi53r2p7hJrTE1WLdP8FD8B4waMZygK52AkZL3pre5BWs9QQ4bjXBvdwjXRW1hiw1kwbEhYkurfWMTgMbBTVWev1lgppteOiiIzxkc2PYxRLxBfd7fKcstAJ8WNNNedy0VCemVbAQiekEUYEcULesXE2qwJUafPPkzMieJJkf3gIDQaM4BkccSypmf1EqSCpo+kFWbzH1ujvsQZNAu5mlnuZ4+uc4jQNAmI8bI5Q5gkc5aqN5uVk5eittoicQh50An7UXdSypmt+KGKh3pJyW2XJz2sNiZ5sMXUVJ5olP1wewTCSdzlSyktIvt7jB9pOKmQtw3LWPyhbfJYFT7f5YO8iESeDETxF16bg2LQjifLMt0OmNqvYysq29yrt2ksQrjSgZ5V2CqiU159rdljYLKqzHrYt3qt6U0TP6PD6HrOssWccy+NXK8u/CuOE6bSR5VQ5R86xuXCoQDXvcrrRoRHEm6e0MhxHqscefFSO605HZRgMfcYInoGRlijvNxxHRjbMLUmn4smRdU+qx5njNr7Dx7iHBE1EQg4HD3v51d3PAp/jARwsLBQv4mpetnoicr3ZDW/nPLlat5ScnLOfe45c3cbpFWEYdTu42taWhE43mhPSCCLKns3Rco6Cs2rWVK8naDt9X1YblrWWq2XXkcWjR+T0hvMt1X03xFqTaN2frsg9KCV9eR5OvTwLnYCxgrsiunQWi3WJ9u2HtFAQiRBeqIkI81x5fxw2b85aNNtbj+qshVJyHHOe9MPp+LLvVv/9Yl3e+469ormn1prTTZ9EayqeQ6Un0lb2HC4fKbHQDgmSZNnEvCmlghzPmXm48MjhP4aGA4ERPIMia7y1H7EsuXqsNcX4ODGy4ipslia38EXu4AQKGKWAy+aLYkjMR/guH+a73MAlvJ6nMx7mYLEhJ/NCThawkSE5IXZ8OHFK9lWjJYpAa9lvGhEQR8chv7EfZXU0p5p3mSqV1g+/9wqe7fiZeg3L2YDTRMNEVU7ojs2ytInj5XC+UgrHUoRpdCdONFYfmg+upuza5Hsqtubb4fp9efxA9v/YcN+3Y9tkPVzCUBb6g9Ic8FzJRq00mvL9VqM665HzJNU7uyhtKSZGu/ux7Uv6EiWprx6RW/Mj6kGErRRH1ni/WEoxVtyB7290SKLJjbb45AyGPeY8OKvsETlPFvH9ilLiOfFcuSocHUaX8nyW+3kLt9MmYpISFltfmF1spiiToLmDE3yVk7zRfxLPsVzUBVMSBck6TcfJyjx/JnTiWERIqZjOvmqtKXgkmhOn0Zx4/WjOapKkJ/qitu6zWm1YrjVENGTdZaErejL/ThSDJ1fEdo/gibTuVyueFSilGC94PJL25cnGTZyVhsgq3PayR1PmV6k3ZbK250gkoE9NGfc9QSifuzCU983I0I67Ja8gG/dQb4noGR2WC43Mt1OtrLi4CZNkuVv3VCnXt6aYgHxuC7m08tLdP55Gw3mLETyDIu9JmHq/z5Mp5GBqDH1mllut+7m18M9UyTPFNnu59GChmKJMi5DXle/kph94Ajepq1C94unUjIgGZUESiziwbSkxzkLqtiX70HOX/QZRGs1Z7PHmTJXym5spM8KI5VSja299we81LDfbslAfmTj7712nK3h6Ogf3dqgdlI8HoOI55GwLP+2+PN8JmCiuumrv+CIuy3tw1d3bINK2JBVTLqYzrs4DsaO1iJGFJbntul0jdr9QSooS8h5Mz8GZUKKo+ZwYlZc3RXO64RNrTdlzGM71eTnIuXK8q0MiuI5O7O9zoeHQYwTPoLBtifLUW3Ly2cdoz+HWow9xa/INJsMyjuOyjcDOuhRx8bC5VX0dheImnign+VMzYrBUQBgASqpFyiv710hjuTb6/kdoXXsFi2GcRnMcjpbzFBxr+4M4g55S2e3MNcsMyx1fUllTY2tXd/X+rKdSy7bU8kiMKI4hsVLdlYqfZQ2kV1q/equ6em8r1fOv+71SirGCx8lG2n25LVGeZc9Qb3RnNxefMBKRmE2q720QuVDbXsPBg0qciIDPjMnlkqR9BhVl81yJGi1Ni/CYGl9xzGtBN5V1tJTry1DbFag0guo5EDiSvtsPKVTDect5cJbZQ6oVCVufYwv4QfNZ7udW55tMJsM4fgQ6THuinPtjO1hMUuJPuIvLgwrPnR4Ws3QUy+O7jqSvcq4sxlpL6igIiBptlmybRWXDfJ2RkUq30mqnhGH39lavqrWGTgccV8TayLBsfxDKtuq0f1CS9hhqtuVvst48SYITaUh78MSNJissUb3vDbX83xq3e25k+2rFP/n1MIrZGAIgRrHQajHmWPKnQSA9UlwnNY9bEllZ62s/3rNBKGNB2v76nZCD8PB7PDq+nAviuDsja9BjPIJ0xEkxL9PhZyV1TblIlCScbkgqa7Lfqaxecp5cLIxWpaVEubC3DS4N5zVG8AySnCeL6kJNTjT7kFmavIU7qJLHsWzIW3KCCvsreoZjj5vjz/P4+acwFmhZ9FxH9lHWPRdZsxtBSC3SNPJFyjrhaBRSsEAV+nCiDHoET5Z+ipOufyiOe24nImziWAyfliUn7I7fFQuW6k6IdtP+Qp2gW36fllPbfgitAJQiKniw0yGfG5FGgFSiGesEnGr4gGZOKUYqOSyt4XRHTKte2u8oSeR4J+nt7LUnWl7bWWLIXvm9Y8u/1VGKbLH1A0lbjVXXj2Rk77XDyPIcuAag5f2+lX45/XjebNBupSjPmfqGdLvDaS8vqSzXptrvVFYvOU/Gf9gV8SnNLUkhwj6+ADQcXozgGTRjVTg1nc7B2bkvZlDcwhdpEzJFWX6glERb+ix6SrHFGRVyy4XHecfck+XkVy6CbaOBjtYsNTvU5mp42AyVLI5YClsBHRucbV6BJqlYiaL0aypc5pfktk4jLp4ji7htdb+6rhwvJ/3eD0XETI5uLlzDcOXcr8zDEyXLJ/loUB6ebBGxFcPFHLN+RJhoImARi9EwSDsUb0F8a71SBC2LoVQQhWFXEGbROscWxeoHcp/hcldcrbfAxYkch8M4VTuKpGKq4yOht8rupRIXaiJwHKd7vD0Xjo5Tm16gNl/DLhc5Ws73P5XVS67Hy1gqSEqz3hQRbDDsMkbwDBrbgvFR6UehRvZ+iGcPx5njDk4wySqP0QrRE8nV6LmeE22biaTI7ZUZjlcKXOmOEMYJS37Ekh+g2wHD9TqXovHyq672bUtSIqvJKq6iOP3acztJ5GSfRSCyyEQWVbItuPjo1vwTj07LYrHeDK1eHIfl0vRMWK1q2Bb3eZ7WWliplyerwJlr+Yw0Gqhj41t7AKVSAWhvPt1d63RcwZIIw0Je9lcSy8+y/kTLx6LnuMSxmMcP2xV/b2+dbLDmbn32Wx0pCECd1bAxAs64HkQw2WriVnJgD3C7nPTYRrF89kaHxb9XLBxOkWvY1xjBsxvkPTnxzCxIn43C/oj03Ma/oGDt0vNM9GTpmXMNwdsWlp1H6Yi/iL7Dv10q04kShlybo+0WhaUGynNXVupkfXm0lqvC+aU0qhCJqNHIYpkJm5wHJUd+Zq+xiLY73deR87YmdrL5TZdduLVFeUVpupavrruiSmtQ4yVWU827zLYDokQTtn0Wcx4j/U4d+YGkroJQIjrHJs/eT5kvqzfaFsXyt42WRECSNNrmunKMvPTrQRNCSdIdagvyWR+v7l5zxzgWoQXSqXyVX+Z0wyfSUKoUqLpFOScNVwZbWJHPyTHOjmulJPtoYmRwz2kwrIERPLtFPtcVPdsd9jcAmgR8jHsZZW3j5Gcv/XXaJ2bJHa3yI//8VuxKgaV/eYQvPP4/A/BC/UG+9Kybmb/9u1z7327k8tf+GFGzw1de8F+Y/+I9jPzwVTzlk6/DWTXEcljn+YS6l1/OP4mLtIt1cqZb8p1oiIJu6iSLhCiVmoLT5oVOUU6e2zXWBts0LGe9UoqF7V2d9/biCWNw3VURnt0RPJZSjOY9ppsd8EPm8iWqWvcnhdEJxJsShjBUkXTfeo+rlIzctj1YvRszAVouyv4OIxGmSw3Zh5nXq1cM7VchFIbSaK/fvXW2itaSQstGR6xKG9X8kFoQYSklqawsfTs9L9u8VnfmflDMi7CtpKJquCw9uNr+vop4Gw4/RvDsJvlctxPq6dl0UvHemDXvZpYkSXCjRCqGLHvNtJV/apETf3YHl7/muRCtn4qJmh2+8uNvF7Hz1Ct5yv/+T2eJHYC85eBaipP1hzn6kOr2KfKDlcZYz+2agkF+Xyycmw+qtyR9M8ETx90ZWZkxeau4zllDRHv7BEWJRvdLeGzCSN5lbqFO7NgEKGpBxHDuHN5znbRjbxjJwlXeQOhshSgdKZEJmV6ySrcwEjHUbMvXOE2P9EaDcu7ejshoteVznSSD6a2zFepNEYtWOiy4N6rYU5U1VfLwskiq64iJeHaxO2qm3/sxn+um96z0Mz46BPOLa0cEDYYBYQTPbtM77O9UmsuuVnY9n30vc0Q6TStkJ5zM69J7wlOK7/2Xj3PJq5+zclZUD3Er4KsvfAfzd9xN9SlX8ORP/iecyvoltyEJx9U81+eOdst0M3/NeiXnGlnszknw9FZobbAYaZ1GdvKy2Ba2WT7ceyzTrs6WUlhKkWiNRgJWA5gucRY2mtEwYCZ9DbOtgCHP2b7YysY/RKkZeTuznjYiitcfpbDcx8VdWcKdebcyIVRvwmxaNZdzZT5azpPbg15MtZb9slSX70uFjSvSBkUYSZoI0vEUK88np5s+kdaUXJvqasGbdWderHdHUvSzdNy20h5WQffzW0wNzEuNFUNMDYZBYgTPXpAN+ysVxVx4clpOlOXirvWo+DqnyKm0Asuy5MSdeStgucT56MuezKn/+WUe/O+fYfxHvm/Nxzp+89+StAOGn3Q5T/nU63GHNu6p4mFzV7XBy6uXyRV+qyMNGhutbnO9rAtytmBZKo2a7PDkmEULljdig7f+Qk2et1qBR87I1fJ26BVTPc/pWIog7o6XsPtR/rYZ9RajRY852yHRGj9OqAcRQ1uN8oQhLGQencrZzSHPlTCSY70dLCsVND2flez96wfyr9mWbc8EU3Z/Zw1v105JEhHG7Q6gxDMzVN79iIXWPZVQRRETPdT8kJrfk8paa/uyFJznwpm55X49faOQk/3Ue8EyOiyprVLh/JidZthzzLtsL7Gtbp6/0ZKTp6XkRDPgKobTNPCUA3Qribon6q7H5NhPPoH6tx/mvrd/nJEnXd59gB4fStKWHjqX3PQjuMObnyRzOJyhId84jiwSQ2VZQDqBlHXXmlIlBt1U11qVWluld6SE46x/Bd5oiQA7OiELp7vKSL0VesVUEHYrtVaPlxh0UC9JoNbAnhpjNEyYTY/TbDugslmUJ47lir/ZlojOxEj/F/IkHRLbj2iIUt20WLZQJ4nsfz+UY7pQk2OR64kAbdW8vpoglJRnFKURktG986PUm3IxYNuSKuohSvRypd5ksSeVtR6Z+Jiel89Mv7yGhXwqpHpG7TiOvLfmlzb2gBkMfcIInv2AY8uJZbgsC36jJYuNbUv+u5DrllL3iYBYzi+2kj4oK8413W+UbXHVG17I13/+Vh78w09179JTWl268gjN46f59v/9Z7ijZY6+5EkbPrcCfNZIj1mWXAEW8xJVCaPugMlmO+1qvMPZZFsxLPuBnHyPjMu+bu3QVJmVwPf2sXHsVT6ehIErnkZrufnlqJMw3wlINHSihGYoIzrOIklEbNYaIhwumBycNyaL7gxqobMs+fz0DMtcEQVaaogYyir8CjmpqNzs9TZTv45O5L00ObrzCefnShRJBA4kYrJq2880O0SJpLJGVrd7WI+0Xw8zCyJ8VpW274jMaN4zXw6QC53GjHzOB9152nDeYwTPfkIpOekWcrKwB6FENWoNuZ1dxWYlu739ZextVCxpjactNIkM79QhJKo72ykbUwCQJBz9qeupfN8FnPzIXd3H6Ik+XfKa5+KfXuK+t32Mr7/8D7n+tl/nyE9cv/7TA7nNFvte/0a10r1a3+ni2JvOWit8Hsdygh+rdk/I7Y4sZtsl2/bMuBzIorqiUmvQpelay4Kebr9jWVRzLvPp0NXZVkDJ7Zksr9OxGAs1WfSPTgw+zbCRf2dQODY4he7imn3O/DSyOLco98mEUr4nApTNIaul0clSUWZD7eXE+Ux4lQpnCYaaH7LkR1iK7TcYtG2ZFze/JF7DqXMUdUpJlKfVWSl4lJJ9OLsg57292peG8wIjePYrSvX4FCppZ+BYKo3CKD1Bxys74WYjDpYfY9WNLOKg4cioxf05H5JcOkYgfU6s9Hb6p7aFsiyuesNPcNeN/33dzX3sW1+ODiPu/6//m6//9P/LE//23zP5Y9eteV+fqNvZeatkV+s7JdpA8GQm5d5FI4zSadY7/Ij0VmqlZusVvXgGXZreaHW9KyljBY+FTogGWlFMK4opuY4Iu8y3NDEqi/xuEEZ733yu93M2VJZj7ody7GoNmAlTI7QLzY68j5SS1NFulpyvRdbDyLLO6p69MpWV2zyVtRZKyQVArSGiZ/IczczFnESuV5uUM3G5WN+3I3gMhwMjeA4KSqUN9tY5ZFmDvnh16XhPtKZn9tMT1GP4HNMQe91y0bVINNgWR17+NIbe8XfUvnli3U289g9uJIkSHvx/P8XXXvxOnvTR/8DEj/7gWfcLiLmeo5u/5n4S9qTQVi+yS+kVe++JuN2RK86dLmi9V7HpwFJnt3rxZNGdVWZr17ao5l0WsihPrU0pCkR4jAxJKnE3F/AoFjGxn1BKBF8+vdBIEkmpnpmTiwxN1yez3IV8D0RP1FOVNVZdN5VV3E4qaz2GyvL40/Pn1jg1n4Noce3ZaSND0tG8XNz9cn7DeYMRPIeFzHS8xZDwVYzhYPXcPx21nfKc77xNFk7PBddFKXjmN35/xWM87fO/fdbjfv+7fo7vf9fPbfjcLhZXMral7ewbvRGeXtHY8WVBOzqxcuHKpnvvlN6Tdtr/pzelNdBuy812mpY5+2p8rOCx2ArQnQ7NMKY1WqK4V4bRKJIp3vuZVkciD1mH4NFhEWptX7xOWnd9doXc7vQC0lqGcCbJmr2p6kG0nMo61q9ZWaWCpM1nFrpz8LaLUuk8rTaMrB4fY0M1HS56ZMwYmA0DwQie85RrGMdCEaoYNytLVwDpGABUd4BmH2knEZGGyxkdfJVSxuquzVl4P07EOzBWXfk6s2qxc2l97/bM1Epne/WmtAYW4cmmc49Vz/5dkuDVGgw1myw5LgzlmbNdinu1uGSdlPcjq/065aLsU6WkW3Sp0C2F7/gijOaXJHKRGe8H5YFqtrsNBld1R44TzalGBziHVNZ65HPi65me7/Zj2u57p1yUaNla1V+VovioGm25bTD0GeMQO08p4fEirmKedrcPTyZ2smqpAfgrllSH50WPYWYp4oHFFvPtgHDQwzRXR3eU6vYuWat7cyeQVMu5GCizRopAJnrsVd2WB0KzLV2zV/eoabYlZRDFjB8bQ6XpunoQ0VmnoeRAydKve+3hWYskkUW91kj9OtWu2OklKyKolMTfctERqJZF4J6elf29UEtTYX063lEswgpE7KzVYLBfqay18FypYmy1ZTu2+7q8tCN2Z40WE0rJa1qsiV/RYOgzRvCcx7yM75Ouv3YqAOLUpFvIr9/x+BxIkCjSv839IFeOlJgoenSihPsXWpxYarHQCQcT+ehd0LMmd42W/HytCeiZf+dcWdWPZ+Aensy7U+258g4jWbwX6xKxmhghl/Oo9Gxb1p9nV4mitQe87jVRKlbanW6l0tAWzclZJdJ4FS6cEpGktUQRHzkjArvt71z8aC0iI0nkeVZVZUkqK9xZVdZ2cGwRPVEMM/MrWlRsiXKa1lqLnCcXIIv1c99Og2EVRvCcx1zJGDdwCTN2Gh7P+v0M6Dw5Q5MbuITHMIZSirLncKyS58rREiN5l2YQ8b2FJg/X2ix1QpJ+XRWHqyI8Qdid1rzWZO+235+J9r3GzCDEVmp510Za5mn1lVZHhGo+bWuwWJNRAXlPZrj1VLmNF7sRoLof4e92lCeM9193XT+QaqQgNdUeGd95ZWBmfh4dlnlRU2MioBZr8PBp8cI029sTC62ORFYsS0q5V6WyTqeprIlijlw/U1lrYVkS1bIsSVFtJyJTKoigXO+1Vyuyb3ojswZDH9hnZxzDbvN6ns5XrZO0ioqiGlx6oUlAEZc38IyzfmcpxVDOZSjnEieaRhCxFEScbvqUPJthz6Xk2Vg7vWLtPXFmxsvR4bUX3Kwjcz8W41XGZZV2W84My7HWK3w950ytKRU1HV/Mn54rQmcNn0zesal4DvUgQgOz7ZALKruYXor2QUl6L62OvC90IiJnYrR/jT5X95SKYnm+Rtr3J4tqFPPrm56TpJvKGhk665ieafqEiabo2IwOIpW1FlnZ+mJdomKTY1v73GQNVZvt7gT11b+vlCRauZYXzWDYISbCc54zTok38kwWlU/EYLw0EQlL+Pw2z2SMjc2ItqUYzrtcPFTgipESJddmvhNwfL7JyXqHRhBtPzLSG71otM8eRtlLsy2+nn4IkdWl6VoPzsfjB+lE8ZaIndHhTTsAjxW6UZ6aHxKe1dJggMTJ3k4376XelLSfTqSZ4NRYX7uan4VjS5psakxSX6WCiNRHpyVa0midHf1YrEsUJeedVSHVCCIWdyOVtRbZDK6hsogef4vp0XJRXud6DJVMlMfQd4zgMfAcLucmrmeaZt9FT0TCNE1ezfU8lyu29beOpRjJe1wyXOTyapGcYzHTCji+IOKnHkRbS3tlKa0gkhPoqnTAMlrLSbhfQxOzGWAgC1gUr4hS9S2jpXXaJ8aXVMyxiS1NlS+6NqXU06RhuT/PrhDHgxUVWyGrxJpbBLQMRx2v7q6vyLLk/TYx2hU/zbZ4fmYXJL3qBxK9Q51lnu6typoo5sg5e7RPKyXZtjNzW5t5V8iJ6F1PIGVRnsVGXzfTcH5jUloGFIqbkFEQt3IXVfIUOfeweJOAJXxezfX8EuuPmtgKrm0xVvAYK3gEcUIjiJhvB5ysJ5Rcm7LnUPacFcZgIO1EHcvJtePDxUfWr75q+3L13a/GZ2uMmOhdSxP6oHj8QFIx9SZccdG2PScjeZdm2pRxsRMyXvR2njrcDnsd4cnMxM02y0Jir0uhM/FTLkpUsplWQi3VuxVMq96bWSqrsJuprPUo5iWqmI1o2Uh0KyVRnJ7xJ2cxVIZHz0BY3n9+L8OBxLyLDEBX9FzBCDdzB2doMEEJa6sOZk3asVmRKDEoF3F5G8/ddmRnMzzbYrTgMVrwiFLPTyOIONP0yTsWlVT8eLYlC4dGPBPF/MaCoJ/RneWN7RE8YYiluh+5c8poxYkYYFsdEWlTYzsy2FY8B9dShIkm0pqaH1HdjYUzTvYuwhPHML0gETHLEvN6P0zq/cSxpc+Nbcn7Jxt6enJa0m6lAktxspzKOlbO7W4qaz0y/9PMPOjhjQeClouSqss6Vq/GtlIvT/2sruEGw04wgsewjELxXK7gOo7wVr7I7ZxAaRilgNtraNY9/Xqyc2wYEkYh83aA9mxuUJfyBp6xqWfnXHEsRTXvUs27JFrTDGPqfsRsuyW/i2OG2x2ZqLGRmInTBnLj1f5uYO8VuR9iFbrf76hKq3fIZzEv6auTMzs2dyolacPploiy+U7AcM4Z/OK5VymtMILpOfmalZ3v11EGSSLH2bZkO0sF6RHVbBE8Wue0tsBzmaqWyO0nA3jek6jN9Lx8v57osVJBU9vAnLwc5VlHFBkM28C8gwxnMU6Jd/B8jjPHh1pf56O5B9COIiTB0za5Tiw9hB0b35XZWC4JytK8pHkJL40ex5WlC3d9uy2lqHgOFc9Ba007ivFnFvBbPp1CHhUleEFEsXdKeEaznfYf6vMi3Dsryg9Qha7o2naEJ4rFbxLH3UGO2ZDQc1i0q3mX2bZPoqETJbSjhKI7wAU0azq42ymtTiBiJ0lkf02O7a9KsdX0GpVLqZG+kEPnPR61m8TtgKE4ojozL+K3XJAIy36I9OQ8EWln5uR4r3exMVQSs3a1svb7wbZE9Jgoj6EPGMFjWJcrGeP1Cz/Ir00+jbtZ4jhz3BU9zJl4Hp+EnHaZcse4nqNc6Re4Zt6hpNMJ3WtUm+4mSimKjk2x1UZXiniuQ9OxmW4FBHFC2XOoeOL9sUCEw8gAJjU7joiodFK9nXQrxrbcZ6g3qlMpwvBot1t0rXn29OntbqIlbQEWU9PyfCeg6G6QijhX0tTnri7MzbZ4drQWYTsx0n9x20+CsGtUXjU+YroV0I41bt7jaHUEpZP0/VGHZEnERaW491VwnitzsU7PibofWqcEvViQ17pWE1CQv3vkzNpDRw2GbWAEj2F9wgi0puQWuZ4S13OMlydXw+yM/N7zoDght4sxzJ8BdLdEeq9TBUt1QKE8F0fBcDHP8FCRME6oBxGLnZBTDZ8yCSNBhOc5/f9AKCUCsC2VNG4YQZoe3JLeiWMpMw+jblQnww/Srrvn3hV6NN8VPHU/IiwmuINKOe12dKfelH2IhnJp/Sq9/ULWURktKZ+eY94IIubaAQq4oFJI2xzYEgUZKst7ot6UqEkh1/37vXq9WQPHLNIzXD77PsNpSftweW0RaqVRnsXGuc23M5z37ONLHMOe0/HPDpH33tY9JezZlVpGvTn47duIIIR6S6ZxZ5ucLuBuanq+eLjIY0ZKVMOQhudx32KbB5dazLUD/H72pOmZWu4E3dLvTau0mm3x57iOeHV6xQ6kjQa3OPZgs010drFEfTcNy0v1btl5dWj/ix2Q497xuxPEU6Ik4eRyCbq3dtox50nq54IpuT23JO+hWmP7IyD6hetIpKfeXHtkhOt007PrMVSSfRLsYusEw6HDCB7D+mSCp5feK7DVJpTest7GNtvm95Os5Hh1iHyNqIKtoBQETE5WuXK0xHha9n5iqcV9C02mmz7tMD63MRA9QsXuFTzrPWQcS2nvYk2iOiNDZy/SUSTHp49VZb3DJhf7OdpjNbthWM567CzU5PvR6toTuvcbmVEZROyk+0lrzcl6hyjRlFx7RdPINcm8L8cmJCXWCbrzvPZCNDiORHqy1Ozq99ZwWUrU1ztnWFZaxm5mbBl2jhE8hvXxgxXRCWDlUNHVJ6ec182x62T9AYGDZqku4qZUWDnjZ61FttWR7XYcrHS+19FynitHShwtS6nyyUaH7y00OdXYYadnzyULM9lRhEr325qCotWRK3LbgqNrRHUyak0RO330oWQl6sByifpAiBOZ6D4oMrGTpjQZH1nbP7IfWdFRuRsxne+ENMIYRymObaebcmp0ZnJUZnrZtqSXTs1IRGVQonYtHFsiPe3O2aIn58nFVW2DyHClJMLNRHkMO8QIHsPaxLGEIFZXsSjFco5I65UnLaVWRXmau3tChW4qKytz7U1NrSV41um9o5Si6NpMlnJcMVLi4qEinmUx2wq4d77JI7U2Cx1JfW0qgCxruVpLKSU+HlbtmiSRqNT8kvgURofXFzNJItu91hyic0ApxWiPwJ3vBP0fcAqDjfBoLWmcWkPejxMj/e+tNCjCtY3K7TBmuiltA45W8jv3Vjm2RLkunJKIStbReX5p5YDdQWLbMDUuF1PzSys/BNWKHLf1BpEue3lMlMewM4zgMayNH65tdlRqVZRn1YJYLnb/Jgjlimy36E1lObZsW3ZCVdbZAiKK5MS7hTEMOcdirOhxabXIFSNFyp5DK0x4aKnF99JRF0t+SLReSL4nUuOGcoW67OFpd6ShnFJnTTVfk2ZbIm8D6EtSzbvLhzcrUe87yYBMy1rD7KIIbaUkqrFR47v9xkIdMVYXl98vcaJ5tNFBA6MFl4rXh2OulPjtpsYkzQQS8TkzJ+/FQV+kZH2FgnBlpMd1us0I16NS7BZFGAzbxFRpGdbGD9avsrIUyyO3dMIK3Zy1x89My7VGX6qItkRvKgs2T2c12t3+JtvAsSyqeYtq3kVrTRBrmmFEzY843fBxLEXJsym5DkXHlkqadAFTCpz0ajqJE/FUtDsSkdpKt9+sFH10ACX0yPDWgZeoD8K0rLX4nlptEbdTozvqPL1ndPx029VymwGtNaebHYI4Ie9YTBYH8HpcR95L1YqkU+drEsAdKu/os7FlrFT0nJ4VgZP57YbLUmE2tM44id4oz3ojKQyGdTCCx7A2fiAnlrVQFpCKibWct0PlruBpd3anS2qWyjo60T1Jx6uqyHrJBoWeY5mrUoqco8g5HqMFWaQ6UUIzjJlvBzwaJeRti7INw3GCAtwogjBC132o5MRbsVUvjh8C+mxvVR8ZeIl6v1NaSSJip93pLqTreZ/2I5nnCOSzk6aRl/yIJT/CUooLyoXBzjjLLlRKBZkpV2uIqBgq9d0rtuI5p9I+PZnQs9ORGgu1swVNx4elJkxUZfv84GAdZ8OeY1JahrPRWgREboMIT8ZaKRzXWRmtqA144vHqVFbGRhGeTiCvo8+9gpRSFFyb8aJMeb9qtMRE0SOxbGoJLLZDwk6AXqrjF3Loser2FpPMczTAxW/gJer97MOTJHBmXsSObUuK5qAtgu2OLN6Wtdynxo8STqe+nSOlXZyCrpSkeI+My8VAVt21UFvfW3MuZOM9Gq3ueaJSkv2RpcO1hoUlOHES5he7/XxMxZZhmxjBYzibMJKT73qL0kal6Rm90aFGa2W0pd8sNVamsjI2MizvgnAAGXdR8hwmSznGhoqM6BhHixl8IYbj800eqbdZ6IQEmxmgk0TSHqXBm3AHWqKe9CmlFccSHfDTKfdHxve+2eV20Tr17iARDssi0ZpHG20SrRnOOQzn9igQn0tnYh2dkM/So9OSgu23wTmr3qo1JTJsWXLxsrAkPruT03KcXUcuUoIoFUWh8fIYtoURPIaz2Si6AysXq/Wu+vJed/HRWoykgyCK5MpwVft9YGX0qVe8JYlcVe+mobXjQ72JZVtYOZdhBWMFj8uqRcquQyuM0t4/LU421jFAL5fQD75LccVz8FJh29cSda3ZrN/ilohSsRME3R4vB3G4ZKMl1VmOs1x1N93y6UQJnm1xpLSNEvRB4ToyVPeCNPV6akamoft9LEhwHIn0LNZln5QKch669yFJVec9eW6NHHOluoNHDYYtcgDPEIaB4wcyNmI9esVDtI7gUUqiPLML8n2tKd/3++Q9X1vf4LheSqvREkPrbow30FoiUPUmTIyi5hehHeKEEYkWb0zV7jVAi/8nM0C7lkSIiq5Nqd7EWs9X1WdkirrLmX5PUU/0uc/RiiIRO1EkfZ+m9vkQ0PVIkm5FUtpcsh5EzLdDGR1RzqejI/YJti3bOVwWETI9L5+74XJ/hpa6TtfIXGtIUYEfrGwYqZBU1zBSsfXodOoJO4DH37DrGMFjOJsw2rhUez2fzGpKhW7uP46lnLqfPVFaHbkKXM94vFZKK6ty2o2ZPHEsZdJaS1rAtqR7MmAnyVlpPjFA2+Qce9kA3Y4SWmHEYr1Ne6lFq1Ck1PIpuTYFZ42p732kmneZ6fcUdZ2co9iJu2LH86Qa66AudrWmvEc8D4p5wjjhVF1GR0wWcxQGObH+XMi8RkMl+Uz3s7LLsuRzMbMg5wo7J9HYYkGew7bFVA3dcTb11jkP0DWcHxjBYzibKJIQ83r0LjAbeXOysHO6yFNr9q/UNUmkcdlGs5FWNEVMBU+zLYJt0MbWti/RrXJxxRWqynmQmlEdXxr7rSdasuaHRdcG3yeZGKZVzNEMY043fSlXtm3yrkXBEQHkWqpvIsi2FMM5d9m03JcS9UTvvOInjqVXTCZ2jozt74nnGxHH3XTMyBAa6egdaU3ZtRktHAAvklJrV3ZVKzv7nDfbki6LYxFTrY5ceAVS1YjnyEWDH8hnWym535k5EWB7nfoz7HuM4DGsRGsRMRulCJwtpLQyKkWpptBacu9+0J/+KLWGeIQ26l3Ta6i2VJpeqstcpUGhddeHMF49a/tUIYeijkYaEGq6s003fMxmC2tyjLLnUPYcIEeiNe0oph0m1PyIM6mQysRPwbHIZ32AdshIvit4+lKini1U2yVOZGELwzSNNXpwxQ7I5O8kkfdHIcdcy6cZxjiW4lhlH/h2tkNW2VXMi/BZrEsat1qRn23ltSw14NEzImqyi5FiQUz6eU+iPE6p+zmOYkmBea587Xf02HAoMYLHsJIwEkGz0UlqtYdno0XMtqWqKDMt15rnLnjCSB7n2MTG9+ud5q6UXDFa1uB62ERx17N0bGLtVEvPa/eCkCTRWPYmC0LHl9lTqyqQLKUouQ6lZW+4JkpSERQlzLQDOlGCa0mpfCaCcra15QU1K1FvhvFyifpk6RyOX+bh2dbfJDA9J+nLbPL2QU1jgbx/G+kIiZEhWmHMTEsMwMfKeZyDLOQKOfl8dTLhk0Z8CpsIn7wn0eBmG5L0OLu2CKZWRyI7Hb+bas/eC9BtRDjIRomGQ4ERPIaVbJbOgtR0aomg0IksYhst2kOlruBpnWMjQq0llTVc3nw7eyM8SqUn3zUmj/eDdkf8OpXSxuF1z0Xb4lOwkoQkCDfvRN1orRgkuR5KKVxb4doWQ+lDaq3pxAntMKaVNkOMEk3e6abB8q6Fu8EiO5J3aYYSyVvshIwXvZ03wdtuhCfrs+On1VhT4wdb7ICkeLWMkIgdh0cXm2ikaq/cj9ERe41SInDyuTTiU5OIVrUi7/W1jn/OkxlfHV/8O822iJysp1e7k0Z1UnUfhN0qy0JOzgl+ONCGnIaDzyH4dBn6ylbEiFISBQrTCMpmnXOz1FO7A6Sm4bEdjkbITnxbqVbqFTx+AKj+j7noTWFNjGwevVKKOOdht8ScSruz8TbFiSwaO0zDKaWWhU33IbMoUMyCH9JuxFiKniiQTd6xlkVNVqIeJMlyiXo1v0OPSZJsPcKjtVQC+X7aVPCAVmP1EoSymCuFHq5wqtEhTDQFx2ayeMgW6yzVVcjJhc5CDZaUXHSs9Z7PhNJFR7oeuFZbjn0uTWstp7h8GOn5u6ES1BuQN+MmDOtjBI9hJWG8teZttgVZz69oC38zVEoFDyIOqpXtN59LEqkIGatuHiXoneSutXh+hiv9je5kIw20Xj+FtQbRCsHjb3znZlsWhz6OYrAt1eMFkihQkGjaYUwnkpJ4P47J2fZyJKjk2QTtGJQ6txJ1rbsG8s3uNz0vV/xZB+XNInoHgaXUqFwushhrakGErRQXHDTfznZQSqIxxby8n+cWu5Pb17pAyIRSJnxm5qHly4VY1iG9s+pzkw0djSKaTsLdzHIvc3ydU5ymQUCMh80RyjyBo1zFGNcwTolDJjING3IIziCGvhJFUNrCEMutlqZn5HMSjg5DSYPVGt2BgVtlqSFXeluJ0mjNcoe7OJGbW5iKvmXCSBbkvLd208MNiHsrxPwgjXqsIwIaLRgZbMmtUoqcrcjZFiDCNUlngrWjmEYY0Qpi5jshtlK0bEXFdRgteNs3RG/Fw5MNAu2djXUQmwquJoyWozudUpEzTRG9R8o5vH4PU92P9FZ1NdqSAnYdET5rVU1mwufioxLZmVmQi6u2L7/r/dxYFsdHY27ji3yM75GgiUjI4eBho5BTwP0s8DkewMHCQvEiruZlXMuVjO3ijjDsFYfgLGLoK1vx8MDWmg/2opR4WzJTb70p32/VoBmG8jfHJrd2/96S9CCUCEG/rqBbHblKrVaWu+NuB2XbRI6Nkxm+O8HaYiwIRUzuwdRvq7ckPqXo2sy2AsIk4ZF6WwSQJUIpZ1vkUkP0hqbozTw8WstC2Gp3xc5BGxexHkt1QJOUijzaDkk0VHMuwxt1NT+MKCXVm+WCCPrpeensXh1a+1grJYUPxQKMteDBR0UwdXwoFpilyS18kTvKJ1DAKAVcNo+2hsR8hO/yYb7LDVzC63k642z/87wpSSJiN4rldpzI10RLiaZKG3FaSs69bvrvsEb89hAjeAwribc452i7ER6QK7ulunz4k0S8PFtpGKY1zC3Jfbfq4cj8O1Est/sxRiJLjWWNC3coRJRSBJ6HE7UlBtX21xY8uzTva6uMFz1qQYSHhQIuGy6gAT9O8OOEuh8xGyeESYJrrRZBNp6tUHqDCE92nJutgzn1fCPCSBZpFNOOhx8l5GyLI+XdF7P7hqxPV7koFzNn5iRiWh1aO6KX3f/aK+DBk+hWh88WT/IWbqdNxCSl9J25NVxspiiT6IQ7OMFX1UneyDN5DpejtvE4K0gSEWLZnK8wkvOj64iYsSw5v9oWuFZ31ErWDsRvp+IovfAs5OTckPP2zXngIGMEj6FLNrtpKx+s7fTiyVBKfDTL4yYa4u3ZLMrT9uVksJ1oSvZaslLWcx6JkMhiHEZw9Nz9JIHnUmy1023sIL3ye9Ba0h9Hxs/pefrJ6hL1RT9ispQjt0qEJumIDD9O8KOEJT/CjwOiJGG40cbOOVhusCyIXCtdXuaXpJpPKRlaeVjEDqTeHU3TyzEfJTI6opLfebXbYSIbQ1MuysXEqRm5PbyOz8+20Zcd49b4K9zKP1ElzxQ7TFdrjdUOmLI9WjnF6/gMN3E9N3H91kRPknQnu7d9OT/kPXnvlosSsdqszcc620UQSjR5vtZtxljZwvnSsC5G8Bi6ZF1wt/LhtHcQ4QGJtKTmQpIkTW1tEOXRWqo7RrZZTp41J0sSyJ+jdyeKYHqh2wOmDyec0HXR2evpvaLL8INuWe4+ordEfckPmSh6Z6WvLKXIOzZ5x4aeAEaiNWEUEDguLa1Z8EP8ZkysNcOtNqVWG8e20JOjeK6Ls0EX6j0hM8L3XpVv+jMtx3ZugTDRnFQuJD5H8i75TPCierpP9tzufe3Ls6TS1EfWGiKbS7af9tNOsaw0TZwakB89I+eGodKK16fR3Gp9g1utf2KSEs65zMAOo+UUU9HJ49klbuUuFHATT1z7b7QWf1mzLSLHdVMv31D/IjFKyWPlPKlGC0IRzY+cScd6mM7SO2F/nU0Ne8tG5tnVrI7wbLW/ShblmUujPEuNja9aGmk/ju2WkydaREPOO7cKp6wvyFCpbycZDaAUoetk38mJs9LzcWy2xbOwz6h4Do6liBJNmGiaYbzl3jGWUuSUIpd3qfQ0L4wXGyRBQGRbNEaGaGuFv9Qi0eClUaB86g3yHAtHneP4jCx90OunWP119e1M0PR6Ls76t9bvgHqLJNHMWg6hZVG1FVWlpSIyO/6aDW6zsuIw0d3+V0lqyLeUfIZ6hdCK26t+Z1ty0WJb+y9iYNtSiVkpycVOvbliXMVnuZ9buevcxU6ciJDIujcHIU4+x6Qq8SfcxeWM8FyukPtqLeeCZluiLp4r2zM6vDt9oTxX0uhhJP7BVgfGR/bdBdF+x+wtQ5et+ncgPYFa3cUgSbb+wS+nXp7lKE9LrlpWkyTStGxydPtCIwhFiBXz2+/sm1FvypXmWLW/FV4pgedBmJbXtv1uyk5rOaHto3RWhlIyX2uuLZ2BF/1we83yVgvjZht7sYZtK9zxUQo94wHiROPH8XJqrB5E+FGChhUG6Zxj4VkWDhoVJ3Lco1jeXyuETAxxWr2XeSmy93F227XBclf+zO6Jem73fRjF6HqLmrKoDVco5HMcGS70N3K1lghaFkM934cJ6FBux7Hsk1haDSyLn/W+ZmmZ3YwqeK74uDq+pHXqTWYncrzFuYMq+XMTO5q0NxddYZoOOXYcm2Fy3MwdPD6eZKyOnAscW0ROdWjv+kFlE+XrTZkqf9hSvwPGCB5Dl+1EeEBOhplXJt6G4MkqtuYW5ftaQ8LYq5+71uzmw7dLvdkNL+8kfz6/JHn5I2Pd7q59JvBcVCZ4On5XDOzTdFbGcM5ZFjx1PyIu6e2Vp2d37QSpn0vLIrJqFpJtKYqWQ9FleeHWYUQcRYR+SNSKiMKQThjRjmKSRKMcO/3nYHsOluPg5jwcx8ZxbZS9ywt3rUEzCGm4LspzuXBoAL4dpdJO5zsQAJlY6hVA2b8g6PlZKp56hZCT/UurinbiVdkK+Zz45lodblGfp03IFFtoPLoRYbiqCWYqevwA7DylxOFMUuOW9qd5R/Qj+6taMPM82bZUuBnRs2X25xnVsDdsV/A4tpw4YGvNB3vJGoVlJ9dGa2X35Gya9NFN5mWtRRjJYrqTct84lhSWUnKSHUS4P01PxLaNtm0gvQrPWuM3O/synZWRT7sxtyMxLy/5IaOFbZ5ww0jmY2ndHceRRSOCSN5XWSlv9k+BcmwRL7YDxRw4xeWFN1GKUEMYJ4SJGKfDRG6HnYioFeLaYpJ2LUvGcPR+7eOkeQDimPZCnXaU0K4UubBS2HCEx56QiaWtRHazSFkmgKJYjlFm1o1jWYQz8eOk87Cc9Ptzee1KcbzU4g4eZvJcS8ezVJZSrBjdq5S8pnTm3oRT4vbKDMdVzJXsXOw8+OCDXHbZZYA0+ewbpULaxmFBzpP77b21DzGCx9BlOykt2H4vnl6yKM/8knyfeXmyBWexLqJoJ1GOpYY0TwzCze/bSxjK3KZSQTwDg44CKEWSz6VVWogRMudKD5oj+7sR2nDOoR1l5uVoe4InSkWlH8qCqLWUJGfHK5uAnc1RyiIJm5zQLcQjnVvnPZykw1XDOCFIvzbDiNCX21GicSyViiILr0cIZUJpO4LIX6jR9EN8z2N8pLSip9F+59JLL+XEiRMAWJbF5OQkP/IjP8J//a//lampKQB+4Rd+gfe///3Lf1Mul7nqyiv5zde+lpf/1Esgipl55FF+83ffxN/f/nnmFhcYHhrmqsdcyS1v/n94xtOfJsfVdba0WN/GvyBxrHPxb7EylZWRebWy24U8lqVQ+HyI7/B6nrHjpxwaGuLXf/3Xd77NG1EuiuBcqO98XM95hBE8hi7JNgWP03Pf7VRqZVRKIk6yKE+9KVGerCPtBVtsMthLFIlgGC5vT/B0AmlhXx2S9NouofNej+DxZYG3rIGl0frFcM7lTNNHA+1IRlLk1/I1xGkUIOtJslgT7wGA54mw9FxpLOc5W68S3AGWUni2wrOtNWMEWosRO4sQhUlCM4yJkoQwlu+dHvEj0SELL/2ZY6nldFUURtRnl9CAOzrEyAEdavnCF76Qiy66iI985CP85V/+JUmS8Fd/9Vcr7nPddddxww03cPfdd/OpT32Kn/n5n2fs74/yvOc9j1f94s/x0Y9+lCc96Un81It/insffJhvfO3L/OM/f4err76WEVvhZv4/1+mK3exruj+bBHyMexnlHCOfYZhe2KXvsVToJGGMlfMkxZUkcr+cxygFPso9/BpP2fEYitHRUd75znee23Zv+ARD8Og0VMsHf7DugDExMMPO6S2jjqLt/30W5clYanTL0Id3+OGdr4loWnHFuMkC2mpLemWsuqtiB5AIT7bAB4EMQNzKaI89xrYUlVz3+C/5afqp2Zbjd3oWHj4tJ+KFuqSpHFtMw4WcXI1edbFUngyV03lhA/KAbBGlUjHkOVTzLhPFHBdU8lwyXOQxoyWuGStzyXCRiaJHyXVQCtphzGw74KFam3vmGtwz1+D4fIPvPTxDJ4ho2Q7ac5ltBSx0Qup+RCuM8SOJKPU1xTEAXvnKV/LHf/zHvPWtbwXgW9/61ln3ueGGG3jnO9/JJz/5Sb7/+78fgL/7u78D4HOf+xwAn/rUp/jjd7+b//K+D/K5fz7OM1/8Yh7OFfiWk+eBoWHaY9XlJpsPHf8eL//pn+aCo8eoDg/zo896Nh//xudJ0NTuuJeP2zfy6WO/QrjYJJhv8PdT/zefcP4N81+6l9aDM3xcvYKPq1fw0J9+nk9f8Kv8/cQv853/9JfoQIT3Pbd8lI+XXsXXfub/465/827+bupXefS2r4KleOj9X+D2p/4u/3vsl/k/V/4HHvz9j5NEEXczy4MPPsgLXvACRkZGKBQKXH311bzpTW8CYGFhgZ/+6Z9mfHycfD7PZZddxqtf/WpAUlpqVWVh9v0f/dEfcdVVV1GpVLjxxhsJAok+aa35nd/5HSYnJ7ngggv4wAc+sPw33/zmN1ceANuWFHij1bfjflgxER7DKrax4PSmm/xtpo8yysWVUZ65JVn4x6vbf6y2L5GE8aosvFuh1pSKsb3q6mtZYspsdyTcvliHS47t/nZslyShiqbWkaaQS7UGkzaozGQ+XJYoVVbhlBnBkxjstPrmgF2Nqp4I0VqWDq01iYaT9TaW7+PYFsWJYbRlEWlNECbEWhMnmjhNryVaYyuFbck/J7vd89VZ9b203tk9YRgEAXfddRcAP/iDP7ju/e6++25OnjwJwPi4VBgePXqUer3OU57yFJ73vOdx4fc/gWc+97mMjMhUc601C52QuU7AaN5jyIIf+emXcP/99/P85z+fcrHI//rYx/jHH305l3/3P3PRMx/L5b/x49z/9k/wnf/4lyR+SDBd4zG/9ZOMPu0qWg/OLG/P937vb5l8/g9y8m/+kfvf/gkKU8NcdtOzlj10pz/6dYavu4QLf+ap5KaGOfGnn+fb/+4D5C8c5ehPPoGFrz3APf/5bzgatjj+ph/mv/322/jUpz7F8573PC677DLuu+8+vvzlLwPwB3/wB9x222380A/9ENdddx0nTpzgS1/60qb79k1vehMvetGL+Ou//ms++MEP8uxnP5tXvvKVvO997+Mtb3kLuVyOl7/85bz5zW/e+IGK+bSn2aZPeV5jBI9h53guZGP5shLz7RrnLEt63CzUZME/MwcXH9n+42QL6sjQ1v5WaxEXrbSb8V5WRBULInjieOvT6ncTrSUd5Qdpy/wAwoiS6+Bqi9B1iPI5GtUilfWM4ksNOSErJdGdfZ6y2wlKKep+iF9vMaw1w5Ui3sjGXjCtu+KnVwzFaUqtk2Q/kzL9SEtUqFcErRZEdtq52lIqrbjuiiQr3U5ruW3QxsLpxS9+8fLtZz7zmfzRH/3RWfd517vexbve9a7l7y+99FJuuukmAP7kT/6En/mZn+H48eMcP34cgHJliLe9+z0860d/DKUUeddGa82iH/I3H/0I9913H8cuuICrr74agIsvvpj77ruP+m3fhF8+yjU3/1/MfOrbPPynnwdg6LpLuOrNLzlru574kX/P0OMuofK4i/nOaz/AIx+8k8tedQPZRV3xsgl++HNvwEpTsZ9/0u8AUL3+UtxqkerjL6F572lm//sd3PWmU4Rpgcazn/1sXvCCF/DYxz4WN30fZ797ylOews/+7M9y7bXXUihsnn5797vfzU//9E+jtebP//zP+cY3vgHABz/4QQDe8IY38KY3vYlvfOMbPOEJT1j/gXIuzAabPt/5jhE8hp2jlPguMq9MEO5svlSlJJGWtp/2StmBH6jelGhC1i+nN1Ow+pyutZTEh5GInV2ONJyVxCjmYE7J9igkNbRXfT5A9n8nkOPpp19tSzw3OVfSfp4rPXmaPrNpifqSH60teBot8e6goFw6tCW07SjmdLPDULtD2XPwqps3qlRKojrONvR9kgqiaJVAirXGjxOSSCJNWmsSsspznTaCTn+HXu5lmAkjC7VcsR+ls+ie84IfIwpDbv/sZ/jKV77Cl77xT/zQ035YuidEYvL9gcc9jh9++jOpVMo85qqreMlLXkqxWKQdxfzQ05/B8Qce5B//4Ut88Qtf4D1/+v/j5EMneOfNv8vTn/v8Fa/LsRRnHnkYgJOPPrpCRAEE35PojeU5XP7aF/Ctf3srAJf9u+djrXHBUn7sBfL1SjFZd04upOZ3OSbVJ16OVcgttyloPzQHwOn/9fUVjxOeqfFIY4Y3v/nNPPLII7zxjW/kt37rt8jlcvzar/0ab3/723nta1/Lt771Lf74j/+Yd73rXdi2zb/+1/+aD3zgAxsey8c//vGyLdUqAI1GA4BHH30UgMc+9rEAXHvttRs+jvRE29/p0f2AETyGc8Nzz13wWJakQBZq4uWoNUUEbVWIxLFEa1ZMRF/nw58kadk5klbZD6Wcti3l6LW6mHdb7ZUl+oMmSUTgdPx0blmctrV35bh463erHs65y4KnHkRESYLTu0/bfrff0uiQlPyeS5XNPiVKEh6ptbGCiIqOKWSzlAaApRSWrc6hUFrQyyIIklQAZcIo66v0yn/7Sv7VT/wEr7npl/jgn7+f3/lP/5HP3PmPaDRJ+hl78g8/nd++5W3p40BTa+pNH43mH794B0/54Wdw+eOfzOXXPRn36KX89k0/T6PRoO6f7fsbPXohAFf/wOP4w7/9FGXP5SnHqry09ufM6iYA4WKTe37nNpQjFX73vPF/MvVTT8QbWWlFb3z3UYYedwmN754CIH/hmERTU3FkFVf2+CpcOkHjO4/ypI/+BlMv6kZTZh94lKTscfnll3PnnXfSbDb5/7f333GS1XW+P/48oXJ17p6ewDBDGEAEFAbDIg4oIGJeQVcBs4C7ftVN9xpWr67hKnfd38rqdRXjehHURVFERZElCAriKKjADEOagUk9nbvySb8/3udU6DQdqnu6e97Px6NnuruqT506VXU+r/MOr/dDDz3Eq1/9aj772c/y3ve+l1WrVnHzzTdTLpfZvn07b3rTm7j22mt517vexfr166d8DeywDnJ8pG3dunVs27atGhXbtm3btK+lMjNU8Cg1Iuv82VCffpltG3g9hlGbKOz7kgLpnGFCemi0NqhvOjxP2s7jMUmrLIFZNNU9iNnyk2mKKFhIwRMENYFTKktBcSImYrW7XY7PDI9NwjYbPHlG61vUK450vgWBPJ/WbCh4VhZBEPD0WAnHD+iulMnGbHk/LgUxPQ2GEY7HNMAa98GPfkrFLFoTMT718X/mu9d+mwfu/wNbf3Ub559/PqkwCpmN2axrmTx989y3vomWlhae85zn0NnZyY9u+gkALzj7xXRMYmVw3ksv4MsbNrL9Tw/wTxe/hlOfdQqf2LWLX9zx35z007+j/ewO/vQ336D09CCbPvwa/IrLY//nJv787m9w2rX/X8O2fvfaz9F11jPY8717ADji4r+Q93vUfj6Ojf/fS/jz33yDP1z6RVb/5ekEfsDI7x7HWtXCptv/N3/zN3/D9u3bOeGEE3Bdl/7+fizLIpvN8pnPfIYbb7yRk08+mXg8zpNPPglAW9vcimouvfRSbr31Vj71qU/x6KOP8qtf/Wr6P3DcQxsVXiYs7U+ksvRphuAJAjEZ7O2qnWnH8vIhPhjlcEpx+zQDSEHaTPf2S8priYidBvwgFBqIGJlLWm8qgnCu2MiYdE/t2hemmJA2/PW9Eh1rb5nT8MP2ZO09MBwVr3uedL75vlxVd7Q269ksOfbnyxQcj3gQ0BV4crXeMlnj+/Jlw4YNvOlNbwKodmzNhPe973309vby3//933zjG9/AMODid1zB//z4pxru53k+pVKFVtvmJ/91A2947YXs2bmTb/3nt9j+8MM88+IXEzu+hz3fu4c91/2G7Inr2PSRv+S4j19E9hlr2XPdb9jz3d80bPO4f76QA7/4I2YyxtH/8DI2vu8C+YxFqR8/aAgEb3jXOZzy1ctIH9XD3ut/S99P7yfe3ULPO8+klyxnnHEGuVyO7373u3zve9/j+OOP59vf/jYdHR2cdtpp2LbND3/4Q771rW/R29vLv//7v09b5D0db3nLW/jIRz5CNpvl5z//OR/4wAeqtyUSk0TRo7mByrQY07VFnn766cHvfve7Rdwd5ZAyMCyRhtlEF3wfdu0NfzBgw5rZi4lcQeZp9XZK0XJkDJZJS9vyVASBLOAtmYnpg9FczdQwmRDxtMgeO1Oxc6RQnTi+oTVFJmZJ+zbU2vuj4YlzISoyLpVrkRzLkuOQisv/TYw+eH7AjqFcdR05ui1FcmBYHjcRb0w17uuX4bGzHQa7RBkuOezJlTCAo/BI5vIi8FZ1HupdW5L8sW8UIwiIEWA7LqbjYJQdEr5HS8Imk05hJmJS1B63q6aE1/En/pVfs4bpL2wKTx7gv4/6WwBeEXx78jsFSK2gEw49jtmhJcLkd9/LGP/IGbyBk+f+xGeJ53mUSiUyGTkH/OY3v+GMM87Asizy+fxE0ROdBzNL16F9sTAMY2sQBJOOuteUllLDMKYsfZkSM5z55LiATBye1ZVGEITpq7C7qqO1ZkyXL0gH11Tbi1rPp/uQR2MmjlyzIANAm0J07KLp0CCpn9kIniCQSFehJB1fBiJs0klJDS5guNsyDVritnjxAMP9o6wuhyKrZw6DX5cJRUeKlAFWZxIk+wflhtaVFd2ZN55X7e5rHxklFor6omnhxWw6etroaM1gTdMpeRxd8xsWWo+BvDdNqyZ8XFfS6ZMInxgmm1hc5/OxsTFOOukkXv/615NMJquO1ldcccVEsVOq1AYlK9OigkepEU0/ny3xWC39NFvBUyhJ10RU7JxMyBVyIRQzQ6OTTw33fbltqknqAXKSLZXl75fyyaBYhmRShFskeIrlg4/68HwRN4WSPM9YTJ5nW5ecvBdRaLQlYiJ4Kg6jhSK9toHR07li6wpc3+fpsSJ+AB3JGB1eOEsqHju8UwvRTLhKnYVBlK5NxCklE/Qj40LWZFP0ZOKNRe5TcALdmBg4eMRo0ntqMuET1cKEg1AdPAwMTmCSc9ACkkgk2LRpE1//+tepVCps3LiRd7/73fzDP/xD4x19XyLzizEKZwWggkepYRryoZ8t8Vgt2jKbOp7IC6eztfHD2t4SFrcGYedQSUYu1DM8JmmRKaM/BUmNZdNLf9EtlcP9tOX5lCtAIM97fKrOdeXYFEphV1wcUimpSzqERn6ZmEXM93EKJVwMxlqztC7TcQoHo75IOW1brE7HYZ+0NNNy8Fb0FYUbRlBLFXnfup6kohJxEd8drQ1T1GNGntWWRU8mPqtBqhnivJLjuIFt005KT2/smTqVNRUNwscPn5MLlsWgXeK15olzHisxV1KpVNWlekoi77FEbME6AlcaKniUGvOJ8ETMRvCMj+7Uby+bhpy0oTI0KvepjmBwpO5nqllbw2MSIcmmZftL2Z4i6piKapXSyVoNU6EoUR8nnA9WKNVC162ZptfizAfD92krFOgHiMcYsWOs1DLlqEg5Zhqsa01iVMJIhmVBdoXXUNQLnKjjKZkQ4d2aaZh/NRlHtc8h3RcEkC9yUX4NP1j1ML4RzG+A6FQYSETVioMf4LsugeNy0dhaSBflomupiNkggP5hiSpqvdiMUcGj1JiredV4wRMEBz8xBIF0DbW3Tn7f9haJ0gRhXVC+KAImuqppb5kY0ai6J5dEQERFy0tsXlHD3pQrcoUWCZd0SuaBuR4MjEpawDBqtThz6KJacIIADgzRFvj0WxakEuQm8+SB2piJZcpwyWGw5GAA61pSEqUYDYV5OAtqRVEVOGEB/CwFzrypOOFIEp9NnRs4y9jIneycNsrTFEyDA/EyZwXHcmxyjbzG/cPy+cyk5PkfqtfacSWNZRgidpbIRc9yQAWPUmOuER7Lki/Pq3UIHcwTJzKgm6pbx7akW2xkTH4eHpMTTaEktSvjC3qjoaOlMqzukpNz/W1LlVJFFpAo0pMvhEIPWUxa0tLVtJQX0sERKJVJ2BbpTJaCL+Z1I2WXrvFeK8tY8DQUKWeTpGPhez56L6+EVvRpBU524QVOhO/LZz5XkIublgwYBh/gTO5jDwUc0vO2XpyaPBXSxPig8UIRstm0HJt8Sc4znheKn+TiXYT4vnSzjoyJIWjrYZY+bQIqeJQaljE3wQMSpSiE9T8VZ3rBc7DoTkRbVvx4orz6SE5OgF3tjX8XRX0qDvR2S1jaHHf7UiQM1RMk4On9IhozKVjTI88bxBRwKZ/Uxgq1GVmrOmkLDAo5EQXDJYfOZKzRRdZcnoJnQpFy5D2UKwKBROCWeq3YZEQeTYVSzWX7UAic+v0plGBoBBIJSVvXRXK7yfARtvB+fkkcq3mdW3W4+IxQ5krOpYu62hjblnNSW1Yu6vKFMBrriuhJJuQCrtnHzHXlc5YryHl2Tc+hnf23jNGjptQwTYmezIVYDAhddA9Wx1MM73cwLxbTlKu7KDW1f0BONvV/FwQyYd1xGkdF1J9wltqMGc+TK+iyg1EsQFtGijsjkeg4NcETDRVdipPFyxUYHJbvO9shEafVD9hvyCEvez4lz6868gLyuiy11+MgNBQpxyxWZxLRDbIIwfIqGvU8ETfFUOTYtnymZumy3XQcVz7rrgfdHVOOqTmHo7mczVzNVlaRaarocfHpI88VbOZcjpn6jjFbLtjakXNm5Fp+IC8/x+u8hOKxqp/QQQkCef6Rj1YkQjOpQz/keAWgR0+pEdXwzKQGZzyJGRYuBwEM52aepmnJyNVNOTyhtNfl7usL98bPxRofATrU+L5Ec/JFKDiyyMQsyHRMHKERi9W6taIo0GLO1poJngd94diIlkzV0FE8eWKMhI7LIyWHVHac4AnmKKoPEfVFyke0JGsRq4oj4tSyJnYRLiWiNHMUxXGcWjSiY2E9mma8f8NjIvLbWqQ2aJpzg4HB5WwG4Gq20k6yKemtPBVGKHMFm7ks3P6MsEwRJJEfmOvJMa648hkeK8jP0X1NS/43oDrMLAjCSHZ4cWNbcxr1okyPCh6lhmFIysHzZ38SnGnhcrFMNQUw033qaIHHR0VUFcs1B9/+IRFokxXuLYWUVhC2lueKss/JhIiDpA+uLyHxqYatZtK1bq3cEhM8QQB9Q7X0xzjB1p6wa4Kn7LIqE2BG74VlFuEZX6TcUIQ9FkZ3MqmltyBFA2GLoRElhoiy9mxjx+OhpuLI59i2Ye2qGZ93ItFzDB18kjvZT44eMnPq3vIJOECeNDGu5NzpIzszIfLxqW/Yi0SN58tr4/lUhxcahoifyMR1qbw2KxAVPEojMTt0HZ2l4LGsWtFzdKUyWfh1dBbRnQjXl23Fw+0NjNT2byrjwYYIzyJGFIJAOqvyBYnMxGOyIHa110wEh8PuM9eXWonJyKSkjiEIpOX5YHVRi8ngiETcLEu64cYd/3TMIm6aVHwfLwjIVVxaowhgJKiXAbmKy96wHmlNVKQc4fs1c8ylks7y/ZpHU6ks75dUAlZ1Lb2FNJqfN5qXdO4cRKOBwbkcw7NZzWe4izvYiQF0kpqROaGDxyBFAuAsNvBBXthYs9NMjFDYaEfVIUUFj9KIbYtYmS2GISfYUll+rjgTBU+5ImJqNq7HjiODLo9cLSmUyGG5JS3jIqY6SS52DY/n1WaCGYacwNf2yPEch0+YpzcNjKmEpWXKcYoMHXOFmU+PX0hyjUXKk9UWGYZBW9LmQEEiVMPlOsFjmBA0cTDqAlFyPXaPlQiArlS8YUAqIKLC9yXSeCiFqO9L1DNfrEU+xwvspYbjSlTHMGBN96SfkdnQTYbPcj47GOD7PMSNbCcgwMEnjkUCu5o9KuNSwSOGiYHBa3kGF3Lioo+OUA4NKniURmxrZlPKJ6Ne8JQrE2dcjeZn50QbBHBgWK4AU0lJ6+zeL4smyMl+qmLexajhiTpcxgqSNkgnJeJxkJx7EFCd3TNtCD6TrgmefFGOw6G8Sndcia5BzRNoCtoSsargyVdcHN8Xz5pl0KXleD5PjRbxgoC2hM2q9CTP81AWK0dz0/JFed9Vo4iH1m37oERF3kOjDa3mzWITXXyAF/Iensc2+tnBAFvZy35ylPFIYNFLls2sYRNdnED3ojsoK4cWFTxKIzE7rLOZA6mEhKlh4jZcV07OXbOIUgyPyVVqNl27ko3F5AQf+e50TzFNfbzgmUsh9lT4fi2aQwDZjAiAGV5R+1EnRirZUGo0gVSi5m8UddYcqplgobkggS+L60EW+rhlkolZ5B2PABgtuXSl40u+hsfzA3aNFqsdWWuydUXKEVEHTRTJWwyCcMxKPnTcjsfEB6azdWmLnAjXE7M8z5eoTmzhomIZ4mxmLZtZu6gTzpWljwoepRHbBjc/t7+NDLiCQFJR0QRikOhONj3zHHapLKJibU9YJDsoJ/n1q6EvnFuUK8g2Jyv8jXLmUTShGYKn4sjzKBRrxbpzcFz1PV8WfcusFfNORrSgRiIyVzh0gmdoVGqJbHuiD9IUtCVi5MPZbMNlh85U6MmzRCM80n5epOz5JCyT9S2pyV+fXF2x8kLWZFTNKIvynovZ8pjtrYe+s2o25ItS99WSEVuJpVRLpBxWqOBRGonNI6VlmiIEIp+dYhla7FpEZE3PzLbj+9Ju3tUu2+wblBN8V1s4ZqFumvrgiGx3qsLlesEzF6JC0LG8XKW2ZGbVTTKeIAjwo4nMhjF9hAdE0FWjZqWDT1BfCAqlcB8MSdnNcJFvTdjsyxv4QVDz5DGXZoQnCAL25MrkHQ/bNFjfmsKa7MVZDO8dx5XHyBVCM8rklPVgSxrPCw1BXan3OpynyCtLgmX2CVIWHNOU6j7fb1zYIsEw1dVZdHtqvODJyIk7mZi5adbgSM0n5EBY3FgfVehslceI5myN5Sdv264fleEHzKBxo4bjynZzBTlRt2WbMjwwAIKwC840mJguGU98Mk+eRRxh4HpSYApiDzCLRcs0DFriFiNlEdBjZZeUvTR9ePqLFUbKDqYB61tTxKcSlaXQCC6abN8sIofhsby8p7Np8ZZaKp15s6VQkhRWJgVr2rU7SVkSqOBRGjGMWpQnqufJF+VE3JKZejLvwLCke1ozIi5MozZNeTQ/da3NePJFCeOv6ZYoTxBMbD23bWltHx6Vn6M5W+NrGSwTomCV53NQb7L6Rcdxa2MemuhuWq3fScRn7hmSSdU8efKFxRM8QRB6Hfm1ovFZ0hqP1QRPxaUnFsNYYimtoZLDgUKl6rWTmi56Vx/daUZqpuLUojnxmHzG0ktoKvdsibooi2X5zB/MTV1RFhEVPEqNKGJScWDX3jrXZUQwTNcWbRhQKsnCXCyLSEgmaoXHiRlcqbphCLynQ/7O86b22WnLyuLvuLWT7HhRVX9V6U/TCu37Yu43mpN9bcksmJmc73oS5jEPUr9TTyYlzy/qClssT56RnIhWyxLH1zkcj0zcwjRqaa2yb5BcQimtXMVlX642ELQlPs0pMUpvYswvnRW5bucK8p7PplfGfKRSWS5SknFJwWlUR1liLPNPmDJvou6ffNh1FM1xIWi8ii1Vpg/h27ZYpifjtY6qcgXGcnIyn66FHMKZWMPymIVSOAi0a+qTpmGIANs/TQFzfVpiMrM7z6sNv0zEZFGfyvm4SfilSmgrb8xcP0SjCwqL6MlTKovoBDkuc+wEMg2DbNxiNIryOB7JJRLhKboeT4deO92peG0g6FQUwjRqMjH7Gq5q+rVQK3pva5EIyHKN5kREoyFyBamzSy9S55qizBIVPIczfQMy7RckihOzRbDYlpzcoxNxtEBNd/VbLy5itogmL5xyPjwm0YKWDBCIkBlfgBlNRQdZbHu7D36FmEo2FjD3DzdeWZpTCB7XhZG8iLx0clFrJfxypbpYzjjCA6EQXCRPHs8P63YCSWPNc05Ua9yuCp5R16NnrvPamkgl9NrxQ6+dnsm8dsZTCGvTZtMpN8HCID1hAviypmE0RM/KeV7KikQFz+FMJiWCJ2Y3ChbLkhN1tCgFgfxuupNZNAwPaqF5z5eoTyI04hselRP//kE4dn2tJqTihHU44aK+unvmnUidbbVaoUhcRdGP+v31fYk4jeal4Hme3VZzxa84YIu4OmiHVj2L5ckTRdrCOiM6Wue9yWzcJmrOKns+ZcMgcbCI3wLi+QFPjRZx/YBMzGLtZF474/H92kyqmUQwXFfea1HBfldbzbZhpZAvynulow2yS3CemKKMQ5OshzOZtFyVVZxadAVEuFhWLSri+QcPvY+fVB51SFmmLJ6GIRs2kAV7T78IlagwNhGTBaW3a3YLoW01pndG85J+A3nsgNAheLjm5XNEryzki+1l4vv4Fbf6/GYV4Rlvcjc2R6+kg5ELUy6mKTVRTVjETMMgW1efMmaYh2yelj/Oa+eIltTBxQ7UpbPi079vyhU4MAh7DsjPa3qkDm0pDeycL5Hp59CIfF5bmlTArSgLjEZ4DndasyJI9g80muhZlvzetmqCZzosS8RFRBBUa1Wqg0QLRXFYbc/KNnfukUiL68nXmjl6jWRSNZt9wgjF6u7QvDAv+9WWFaFzKE/MFQe/bojjrCI8IMdqNA+EU9ijTrom7h+D4eiIrvambrslbjNaCdNaAXQfAsETBAF7cyXyjkfMNDhyKq+dyZgunRV1943m5H3dkql5SK00Io8sz5fPq6awlGWECh5Foh1R3UYkemyz0YDwYJ4jUQoqCACjsUjZceX3pinCwzTlq1yB3X2yQBy1bu4LrGFIymBPJRzimYfHipBOhAWm9tKYFl2qiOAJmVWEB+Q51PscjeZnN6pjOqqjI8I6kyaPTMjGawMcSxhUHJf4IrcsHyhUGCm7mIYYC8ZmmjadKp3l+7Wid8uUi4fl3FJ+MBxXoqSJuHRSrtTnqaxYVuAliDJrDEM6cTpaawZ39SktOHhbeZTGCpCxEnZYFxR1pyTishjUC6NCSf7G9WTxnk/3jmmKIBgNHZEtU55PzK611R9qyhWCuuLoWQseaPTgyRcaU5HzYWhUXrdYbEE6wCzTIBsVvRsGYxWn6Y8xHUOlCv1F8do5oiVJcjbpzCidlYjXhusOjsDT+2XcRk+HRDsWyMpgSVAsw77+MHrVtnKfp7Ki0QiPIhiG5OM9T65Y43E5yXu+5F5mkmqyrdArJhQ4ldAzJh3OHIrSB0EgV8aeL1OTLVOiS5UytLXOzuMkusoezYko62qXglGAobFa4XV9EfahIPTQ8dNp8GT/Zp3SgppjdeQ/lCvMyRCwgaiYm1D4LlAqpiVuM1ZxwTQYrXh0LcijTGSs4rIvJ8Ns12STNeE1U6J0VtyWCEepLO/R5TjuYbYEgZwPRnIi7BbYtkFRFhKN8Cg1DEOuVNMpESq2JYvhTAsu7bDuxw9FUoAsDOmELMzR4lAsy6LRmqnOlCIRh32D8MiTNVfh6QgCETm7++T+vV2wqkv+j/bVdSFsh65OTD9UOFKs7NeJiRk7LddjGGF7f8hYYX7PKwikJoNAXo8FnHfUEqa1MAyKroezCFG3ouOxe6xIAPSk47QfzGtnPL4vC35kFJiISy1YZ9vhIXYGhsM5eN0qdpRljwoepRHTFJ+QRFz6iB135j4skUCyTYkUre+VmhM/TGsZ1Kz0WzON3jcVR/6m7MATT0/9GNEV5+79IpxWdcpXtK2Y3dhKXQnreuDQprVKZUjEZbREyJyDTfVT5x1Htj1Xhsdqqaz2lrlvZwZYpkEmZoUdfIFEexaQiufz1FgRP4D2RIzu1CzFXLkCT+2vTalfv7pWg7bScT1JYQWBNACsdHGnHBYcBp9cZdZYllzFJuO1+puZ/l25AlZMFof2VhEiUYqp6reTql0tRuMSRnKykLSEs7jGR3miKdW7++Rqu7tTojmT7VtLBhLh9g2jVoPhTTNeYqEpVyDZKHjmVMMDcpwydWm/0Tm2qEfHHWPRuopaIk+mIKh2bS0E7jivnTXZxMzaz0GOy/4BSV9F5osrtetqMsoV2HtALnS6Ow6f562sePSdrExOzIYj14hgic2wwNMLzeqOWlvrZkkloeLW7OcTCbnN98Uvp1yR/9NJKYbMhkNAo46hSOjsOSD/d7fLFWdyGhEWFWEbhqTWvNB08FBFeIKgOpqjfozUnGp4IuqLl4vlxo66me5TfSpruuPZRFriFoYpgqfoeDjNKrquo95rJzkbr51SKHQODMr7dm2P/N6YodngSiBXEKHX1S4RPy1OVlYQGqdUpiYRh5M3kTddtrGHRxjg9+xlHzkqeMSxWE2W01jDcXRxQnc7me52KXiu30a5IguyYUAyJikYM+yiMoD+EUjVeQDFbUlbDQxLiss0oLN1duZtMVsiTFHBaakircVNbreeEVFkybbwg1rkas4RHghb1JM176Gx/Oy6q6qpLHvBU1n12KZJOm6T9wOCIGCs7NI521TTNARBwJ5ciULotbN+Jl470dww15OUVTYcWJsvht1Zc5idtdyIzAQLpUUdtaIoi4kKHmVKdjDA9eZD/Jjt+AS4+CSwiWNVPVUeZ4jbeAIbEzNu8EqO5yJOZFPUg2MatY6ieJjOWNsN2YwIgSeeFhFUnduFLDzlikR1jlk/d2+T1gwMxGvpsYEREQWLHaIvO9Xn3hjhmefVc0um5smTK4hwmclza0hlLX7KoiURIx8WbI9Vmit4+goVRssu1ky8diYInXGOwdGxTa/wYl3Pl6hW1LQwU38iRVlmqOBRJtBPnk9zF3eyEwPoJEWMg1/hOnjcwMP8gIc5iw18gDPpHsiJ2MlmJLrSnpUp0UEATx8Aw6wtuG44IyoIJIXgeVL/M1dhEKW2xkKPH8eV2WHd7XPb3lypONUr5sYannluNxWaKrqhoMwXGzu4JqMhlZVdtFRWPS0Jm/2mQeAHFBwP1/exmyC6BosVBmbitVNxQt8hV96Lk82BCgJ5L8K8h6cuaSqOpLDSyYUdSKsoSwAVPEqVgIBbeZxPcAdFXFaRmVXrdAyLXrL4BNzJTu4LdvMR+yTOOWETxlhB7lQoyeI8PCbfJ+NyhVkqy//JuHQMGYBnyMk4m567hX0yIcIgetxcXn5ezNSW41SLjINmRngMQ6JY0TiI0fzEKMV4DlEqq56YaZKyDAqBT4DJWMWjIzk/wTNadtifr3ntZCbz2nG98H1XFKGzqnPqYxV1DVpWc8d3LCXKFfl8dczS+0pRlikau1QAETtXs5X380vsULjMyScG8ZfpJYttWLx/1e+5uusxgmgBCgKZmt43JAtJsSzpGMuS6EQ8Vpu6Hrk9D47O/YnZ4YIVs0PzQcJp4AvbEt3AQkV4IBQ49S3q03gYHYKurKlojVlE+b2x8vxcl8cqLrvHSgTAqsm8dnxf3nN7+uSgr+uVFNZ0wrA+urMSox6lcq04WcWOcpiggkepip2r2coqMqRpTsFimhirjCxXs5WvtD8aPZjU5jiOpGAiI71knEn1VdyGwWG5/1wwTRFO6WQ4+sKXBfDA8OIYEXqeLOxhesWnXvA0YSE1TUnJRIzlJr/fhK6sQ1uX0hKzqsc/73i4/txei3zFrRoLdqXidNXXA1U9m/okfbWmR2q4ZlKjEtXvLPK8r0WhGIqd7vbJh6EqygpFBY/CrTxeFTt2k98SNiaryPDl1J/4ZXK3pJRGcjWzO8MIIxNOrUW9/qsS1vAU52GuFw0OTSerUQXKZRgZa86TnI6KWy1YDoKg+vAGk+u7OVFft1MoSURpPEsglVVPLG4TybQAyM3Bk6fgeFVjwY5kjFXpuLSfR3Pa9hwQUb2qE3o6Z56a8nwpNMdYeYKnUJIxLqs6V3ZtkqJMwgpNTiszpZ88n+BO2kk2XexE2Ji0GUk+2Xk/pw6dQVdrVhbd1qykGKLBo/XfRx46hjH/lIJtQTn8P1HXtTWck0jHQkY7KqGwgwkdWjM2wjsY8ZgUeReK8nM096h+H5ZIKquKbdNqlAn3mLGKO6uxD0XH46nRmovy6kxoLFiuSEGy50ttSmoWVgYRpTIQyPtiKRyrZpEvSr3Xqs4FHSGiKEuVFfRpVubCp7mLIk7T0lhTkSFOwfL59Nrt0JKuFdy2ZMJ5W0lZYBJxuRK3rZrwmS/1tvjJeJ3ACeRqdyENCZ1a/U592uag3jCzpa1ugGi+WDMijOYhEYSpwyUSsbAtWoKa83Wu4uLNMK1Vcj12jRbxgoC2hC0uyp4nr2XfoIi/tT1ztzNYiemsXEHFjnLYo4LnMGYHA9zJTno4SCtzk+gxW7gjuY8d9kg42HMGQ0KbQX17suc3TgR3PakRWqh6noojdUiAF9SEldXsQthEvC5FEYQRHSBXDMd9WNBx6FNZVWI28dAJGWae1iq7flXstMRt1mYSGCM5SV9ZlsyBa83MXSivxHb0sYJEvaYaxaIohwma0jrMuPvuu/nMZz7Dr3/9a0bzOax1rax52Wmc+K+XYMZtbjIukTuaBlY6QWJ1G51nHs+x738l2RPWVrfT/98Psv1/Xc/Yn58mcD0yx63h2A++irWve96Ex9z+se+z459/UP35uHG3v+Utb+Gb3/zmAjzbkHrB43oS8elqF7M1kIhIMimRp2YSef9MEuGxmx3hAYnyRNGJfEEiOkNhy3pH69JKz4T70hozKYURttGKS9s0aa2K57NrtIDrB2RjFutsA2Nvv7y+a3qa0z6+0trRR3Pytbp7ZTwfRZkH+gk4jPjOd77DpZdeiud5nPysU7Cf04b35CA7v3Qrx3/iIsw675K1b/gLDNNg4I5tPP3NO9n7vXt53s/fT+eZx+PmS9z3yn/FK5TpOGMTdluaAz97gN+/4fO0nbaRzDG9DY/b8fxjOep9LwWg/46HGLt/F8cfeywvfeHZ0JLmuc+bKJKaSn1KK2pHz6SglJEuHpAoTzJWrbdpChWnVjDNIgieRFzGIJRD88a9ffL75CL7Ds0U26bFNAj3krwjaa3J0n2O57NrpIjjB6QtgyPKJcyxCnS0zT11NRkrqR19JCfv714VO4oCKngOGwqFAu9+97vxPI9LL72U9/7np3mP+TN6yJB/bD/WOPv8Y/7Hy2l79ka8Qpl7L/g/DN65jQfe+RVetO2zlPeN4BVkYXjezz+AnU3y8+4rcAZyFHf1TxA8q176LFa99FkAPPi+/8fY/bvYdOoz+Nz/+phMY15oHxDbgmgYhuuLGDAMiXqUKlJnEwTiDbSmu3mRkDr/HVgEwWMYEuXpK0skK1eU9E5n29JcvGMWCV/SWiXPxw8g57i0JRpFp+P77BwtUvE8Up7H+nwJsyUN3auaH7WqCp5lXL8ThCnNfEEiOyt9DpiizJAlFONWFpK7776bwUFJ4Xz4wx/mUXMIF0klZI7pbYju1GOlExz7wVcBkN++l9yOfWSO6WX1X54OwL3nf4Z7L7gSZyBH9znPpPPM46ffkXDdHTXD1ulcYZ7PbAYYRt1JP6gV9JqmdDNFYsBxxKumWfU8dR1aAF7ddptewxORSshjFsNOI9tauoMgbRtcj5ZE7b03Nq6Ox/UDdo0UqZQdkvkiRwYu1pruhZmJ5vthXdkybkcPArEgyBdV7CjKOFTwHCb09fVVv9+wYQO/Zy+JGQb4Uhu6q99X+qQmZN2bziTWlWXo1zs4cPMfsbJJVr/2OZgzDJ0PmHVTzBfD9bh+v5y6x4vHpJ4nolCUmodmUHEXN8IDIt5ittShRJ40C9mFNh9sC1yX1jqxnau4VTdqzw/YNZKnPFYgUShyZGcWa3X3wgm4qB09EV9a9U4zJQjElbxYhtVdcx/HoigrlGX4qVbmwqpVq6rf79y5k33kiM9gIChAcWd/9fv4qjbGHnyarRdehV92Ofvhf+HcPV8g3pnhz+/+Jvt/ev/MtmlFi3AgqZeFpn6RHG/Ml003mvcNjc3P6BDCguVahxYskuDxPClctkypQ4nchpciYYQnYVskwm4tPxDnZc/z2XVghNLgGHHT4Mj1Pdjz6b6aCdFYjkMwUHXeBAEMjEClomJHUaZABc9hwhlnnEFHh5jRffKTn6TsO1Wn38LOA/jO5FEWr1Dm0U/fCED2hLVkN61m7OHdEATEu7JkT1hLck0HqY09AOQe3j2j/fHr1618ceHHPEwV4YnobJOCXwAC6eCaT+TJ9cQ4sW7h8Rp8eBboozc0JseyJVt7zqPhxPqlRsyqHuNsnTAcK5R5enc/xUKJeEuaDWs6iS1G0W15mQqeaGyI60rr+XKMTinKIqBFy4cJmUyGz3/+87z5zW/mmmuuoeNPd5F87ga8PSP03/Jnztv/Rcz22tvhsX/5SbVLq/TUAFYmwSlffScA7acfjZmIUdzZz70XXIndmmLwzm1gGHSeMb7pfHJM05QTs+9LJKTiLKxHyHQRHpDIwaoO8XPxPNmvviG5Wp7LAuK4DfU7QRDg1vnw2AsRqShXpCbKMKT4um9IFkHfFy+WenPCpUA0HDaQNvOBQkBQrrC76JBJx4ll0hzZniY2k9lX88WvGyexnLxqImNJ3xdTQRU7ijIl+uk4jLjkkku47bbbeNnLXkZxVz/7/vNucg/vYf1lL5rQpbXnut+w74bfYSVjHPHWLbxw6yfpfIEUJKc39nD6D/+OjjM2MfSbR+n76QO0nrqRU6/5azr+YtOM9iVFrHFw4dgCFy/HbKoV0643ecTDsmTmUiRGKhVxp51L9MlxG9rh/aA2WsI0mjQpvZ4opUEgIzvi8UaBM5pbnGGps8EII2CuR4oAM19krOxQiNkYiThHtqWIL4bYgVDsBCKMl5NoGBmTWrGejuW134pyCDCCaU6Cp59+evC73/1uEXdHWSyu40/8K79mDYvvvruXMf6RM3hD6TjYF9YHGQYc0buwtQe7+2pT19f0TH0lP5YPxzGEdLaJiJgNA8MissK/q3g+jw5JLU3MNNjU2eRoy2hevIRsC9aG7dpBAE/vl4gVQGe7tKkvJfb1g2kRFEv80Ywx7MucsU2dGVZnF9HpeHhUuptas/J6LwfGCiJ41nRrzY6ihBiGsTUIgtMnu00vCQ5TjqNrwYaFHowYJpsIbe7joegIAlm0F/SB6zK4040xyKYbvYEGR8MOnlnguA2P11iw3OTj7nmyYIMY8UXbj3x5IkbGllYtj+tCrkCQy7G3tQXXtjENg7aEjTPDuVpNIypYXi7prGJJXvPeThU7ijJDVPAcppxANyYGDt7B79xEHDwMDE6ge+KCPJZf2AW5vo7HmaSOJ8IIp4pHYowADgxJKmymuI0pLbfueTW9Q2toVI5bKtmYJgQRbtGC6HkLnzqcCVHn2J4DBMkEg4kkw15AwjZpTdjYlknB8Zgu+tz0/SmH74flULBcCf2iejqa6wyuKCscFTyHKRnivJLjGGQRWsLrGKTIqzieDOHCkk7WTtq+v7At1Afr1KonKmKOoiWeJ51bM1mEI++bOtO3BZuUXnGkrd8wJndUNk1oq0tbjowdWl8e15OJ5mMFgt4uBlIpSsUypgEbW1NkYtGg1YDCbATmfKg4EPjy/ljq0RLXhf0D8lonl6k5oqIcIlTwHMZcxDMJAJ/FuZL2CQiAizix9kvDaKyPGV3AKM/BOrXGY9tSxBwVO5crUptzMNHjuCJ26sRHvctyUzu0hkaBQHyEpmrdbknXok2+3zxjxdkQBNJBtveApI3WdNPvBfS7Prbrsa4lRTYRIxOvCY58ZZEEz3JJZ/k+7B+Uz8tSnI2mKEscFTyHMZvo4iw2cIDFMaY7QJ6z2MCxdDXekE01pl0WyoiwXoR4Xq2YdzpSCZm5FZEryJyi6RiXzoIFMh0sluTLNKdvOY/mhkWM5maXnpsvUXRsNCet0+0tDBQdDhQqBKZJW9yixZJjkonVBE/uYFG4ZlH131nCEZMgkMhYMrH0Cs8VZZmggucw5wOcSYoYBWYQ8ZgHeSqkifFBXjjxxvG1PAvVQm0YjTUPM11QWzONRczDo9PPAHO8CdEWr9kprSAIozvIsTtYKiadbCwQHx6b/z7MhGJJvI1isWpn3GCxwv5CGQNY25IimUpWi8gzMbtqiFly/YbapwUhCGoF6Us1whMZC5omdLYuzUGwirIMUMFzmNNNho+whWFK1WGizcbFZ4QyH2YLXUwxGT2brtXLuK64Ly8E9UNSZ5LWgloRc30EYGB46s4t150wtLHpEZ58UfbfshrHYkzF+ChPrjB94fZ8iQRZ/zB0d8hjGwZDJYd9eTluq7NJ2pIxeU3CfbFMg1RsEdNaTmjMaFlLd9Dm8Ji8p7rbVewoyjxQwaNwDkdzOZvpI99c0ROAWy7RF+S4gs2cyzFT39c0G2t5RhYoyhObZR1PhGFIOib6+yjFMNk2xrWkA7jNrOGpj9B0tM7ccC6VqBNtgYyhWAhcF/YNyLFZ21OdPD5cctiXk6GxqzMJOpLhsYzHGo5jdjHTWvXjJJaimBjLy0BbdVFWlHmjnyAFA4PL2VwVPc1Kb+WNCn1WiSuGj+cy79SD/0FLBozwLek48x/gORn1aYtosZspptnoe+L7InrG1wIdtIZnnh+70bw8Rjw2++LV+ihPoTj7Y3AwCiXY2w/phCzS4bEaLFbYkysRAKvSCTpTda9DLNaQXszUReHyC92eHrWjL8V0VqEkwnaVDgNVlGaggkcBaqLnSs7Fw2c/udl3bwVAEOATVP/+SuslXB6chtE3ePDuK8uUjqKIkbHmR3kSsdqVvOPOrHC5HtuWhdyoS7/VPzffn9CS7gcBfvg8DOY5VsLz5bgAtM+hniMRbxRJQ6PNOcZBIGM4Bkeks62tpbpv/YVKNY3Vm0nQnR4nLuJ22Bou+5G0zGraz/UDSgvZRh9FluJLzM+mXIH+oTCqqCMPFaUZqOBRqhgYnMsxXM/r2cIG+sizn9yMzQkdv8J+Z4Q+8mxhA9/nrzjXOFaiCrFYozCYitZsbREvV5ofgTCMxsWtPIdoViIupm/17er9w7Jgu56IojohMr5+x5hP6iRyS04mqqmiWdPeWtv3Unn+kTTHlaiO60lhcmjeFwQBffkyfWGB8ppskq7UJJEU06zO1AIwDKOhW2vB6niCoFbHtJQEjxOK6O72pRl5UpRlil46KBPoJsNnOZ8dDPB9HuJGthMQ4OATxyKBdNIEQBmXCh4xTAzT4LVjR3Fh8Gw2JdbUNmgY0NUmV6wHwqvWqRZ924JMGnJhq/xIrvntwvF4TUiVKxPdiWdCOikdM4Mj8nOhCEOWLPbTFizP4xrDdWvGjB3z6NaJ2RJJi7Y1PCriaS7byxelgLu9JUxJyjaCIGB/ocxg0ZFurKhAeSqiKE8YzcjEbEbKkubKOS7dLMDC77giemx76dTHeB70DUjnXVq9dhSlmajgUaZkE118gBfyHp7HNvrZwQBb2ct+cpTxSGDRS5bNrGETXZxgdJOxHBguQe+4jRmGdOscGBTh090x9QLblg3bvgNpa644zb0CT8QgqtedTeHyeFqzEpWIjPxGc1CKTRBoTWtJHw5TfJnU/K/821vE7yjw5Rjki42t9wfD92szxnq7GvYnCAL25csMlUTsrGtJ0po4yOsXCwuXw3Rbts6AsOh4eH7QXIdqqL32B9u3xSIIR5ikkrMfVqsoykFRwaMclAxxNrOWzazlDZw8/Z2zMUm7lCsTF2XDkPqO/QMwMCJRn8lET8yGTLLWmj4yFjoeN4nxhctBMPdoSUeriJ5CuK/DOegeF+FpRodW/QiJ9taD3/9gWJb4C0X1QMOjIjZmsn+OA31DIkLX9jRER4IgYE+uxEjZxTTgiJYU2fgMTjPxWIMVgW2aJG2TkiuVZAXHoyXR5NNVlM5cKvOohscm2gcoitI0lkgcV1kxGAa0tkxtbBe1dzvO9AWz9Ve4+dLMTQJngm01dlrNZ9uG0Vhr4fvSRVVXF9OUwaEzGSExW9qydd5H3sym1RdK0nLempHnXSd2/CBg91gkdgzWt85Q7EAtpVVHtu55Lkh7urOEIjzFskQ11WtHURYMFTxK82lJS71JsTT57aYprbalci1NM55EXEL7AAQHH+cwGwyjcZGbT1oLwufTKbUg0XPpG6zWCc3bdLBYntkIidlimpLaihgZm3rkROT9MzAs0ba6eh0QsfP0aJHRiotlGBxZNwh0Rti21K/UicOGuVrNbk8PgqXToeV5tTSvtp8ryoKhgkdpPlHaZboIjmVK7UexLIW/k92vfnHPF0RENYv4PPx4JsOy5PmACInAl9RdxcHx5hHhqR8h0TqDERKzpSXTOK0+eqx6fF8W5GKpoQsrwvMDdo0WyTketmmwoS1FOjbL/YzGftRFctK2hRmKqornU/GbKHhcr+awfChFRjQ2Ipuee9edoigzQgWPsjCkk7LwTzcI1LJgdZfMUZpsCnkiXksV1S/8zWA+BoRTYVtSe2TXpcv2D+DVRZDi1iw/csUSVCq1mptmYxjSbRaRLzSOzHBd2Ncv91vdPaEDLRI7BccjZhpsaE2TnOuIhnFprYnt6U0UvEsluhM5itdH2hRFWRBU8CgLQ1R8OTw6vfdO5F7s+dKhUi96xhdw5otTz6+aLYkYVS+aintwf6CZ4PkSpejtqta2BK5HemAYMzQ4jM2m/TkIpAgaGuttmk0q2dgCHUXcimXx18mmZZbYuNoS1/fZOVqg6HrETZMNbWkS9jz2MR6b4IvUIHicJvrxLAXBUyqLNcB0HYuKojQNFTzKwpGIS4v26EHqb6IaGJhoTphMiC9PxFTpr9limnWDRIP51/GA1GJYljzv0GvIDwJM36d9eJRY4M+utbpYrkV3ZtMyPhfqp3CXHYnqRHUl9WaQIY7ns3OkSMn1SVgmG9pSs49ejScRnxBtyzaMmXCrjtXz5lALHi9ME3a1L92hpYqywlDBoywsHS3h7KeDXJ0bhrgXWybsHyd66k32Kk7o0dME6ut4Sk1Ia3m+7D+IUFvVWfWotjyPjpGxmY+yCIJay3jrAkZ3ImxbxkEESBptYFhej0nqSiqez87RImXPJxmKndh8xQ6I+HAbC5fjllkVUn4gnjzz5lAXLAcBDAxJVG0uppeKoswJFTzKwmLbEp2Yqk29HsOQK954TFqfI3FgW7IYRwyNiriYL/XFt81IlUURnohUklJHW3UiWdzzJoq5qSiVJdphjpsvtpBkUiJ2InPDSYRl2fXZOVKg4vmkbIsNben5D0ONiLrnxkd5GqanN0HweL68VqZ5aKIrY3lwffXbUZRFRgWPsvC0t8hCOpPi4KiINpUQ0RNFhloztQnkft0AzflQ74hcrsy/jsf1YFwNSykeZ6w1SwBYhiEpqoPNFKuv3VmM6A7I89/XL4IzHRoQ5goNr1nJ9dg5WsDxA9IxiyNbU813P54krdUwPb0Zhcv187MWu3amXJFC5R6t21GUxUYFj7LwmKZczQ7MsP4mKlbOpmQRdtzaNiJG8/Ovu7GtWkt2EMxtkGg9nj+hxdnxfcrJJLmWbE0clMoTC7TrKVegXJbnvBCdWePJF0WEdbVLwXWmLs0SvmZFx2PnSBHXD8gulNiBMMIzsXA5eqSS5+PMV5hGre/2IhvN+2FhfmebTkBXlEOAfuqUxSGTkoV1NNeYnpqOthZZ9Pf1y0KcTkpUplQGwjb16QaRzoRkvHbFXyrPzwvF88BqrMmoeCJqSqkkQToOY2HkplgSkTHZ/g8vYu3OaE4iDr1dtXqWjjYpmA4CqFQoDY+x0zfxg4CWuM26lmTVH6fpJOK1yfPhY5iGQTpmVbu08hWP9uQ8jkuUFputV9B8CAIRj8lEdV7YSiBPhW308wgD/J697CNHBY84FqvJchprOI4uTqCbzEIMgFWUWaCCR1kcoonpew5IymSmV7iRo+/+AREHneE2osGixfL8Cj+TidrU8PnW8dQXLYfURyPs9hYwjVo6LhI9PR01YVMqy9dCR3ciX6NiGdZ0N0Y7Yra0wQ+PUfF8RvcPEnR20JaKszabxFjIVIxlyXN33IaC4kzMrgkex6V9usnrByMysFzMKEuuKBHJNd2L95gLyA4GuJ6H+DHb8Qlw8UlgE0eicQHwOEPcxhPYmJgYvJLjuYgT2UTXod595TBFBY+yeNi21PMMDEtEYaYLZzYti2AkDlrSNZEyOCJRmbkuwskERKfosjOpaJkx44qW/SCojpUwCF2WI4O58aJnVac8x2iERktm4aI7QSAt0Z4vZoKTPd/WLKXhHGNlFwNYVSnT2dO6sGInIqrjqRM82bhFX1hDnavImIk578tip7QqDgyNyLFejHqsBaSfPJ/mLu5kJwbQSYoYB4+UOXjcwMP8gIc5iw18gDPpZhHStYpSx/L+9CnLj5aMLLizbS1PJ8UT5sCQ1HlUh166B/f5mQ7LrJurFcw9yhME4aiC2keq4jW2VxuGEY7daGmceF4qSwSrWJIvw2wcntpMvHDkBYjonELcjTgeu2OSgkjZJp2ug9EMr6KZMEnhcsIyq2M5vCBoOLazIgjCQnhjcSI8Ud1OR9uhd3WeBwEBv+QxLuS7/IqdrCJDL9kZiR2AGBa9ZFlFhjvZyYV8j1/yGAEzqOlTlCahgkdZXKLW86HRg3vzjCcl3jYMjTWOhhjJzdzfZjLqu7XmKng8X0RYXdTB8Won81h9gW8keuqLsMsV2LVXzGZaM3OPMk1HNCYiHpvW3Xeo5LBnrEQ5HieelSGgBjTP9PFgTFK4bBgGqboW8oI7R8HjukAgBeuLEa0aHJXjnV2+dTsBAVezlffzS+xQuJjM7diZGPSSxcbk/fySq9mqokdZNFTwKItPPCYRjMnmZx2MRFwiExVHxAFMPfRypjQInjkaEI734AEqdfU7kxrztbVITRKI+CuWpbA7swBmdBWnNiais23KxX6wWGFvrkQArMokaVvTjRGJtXKllkpcSCIDwnFRnPqBpIW5+vFUC5YXIbpTDOuxuqY+3kudSOxczVZWkSFNc6JUaWKsIsPVbOUrbG3KNhXlYKjgUQ4NbVkRCXNxTY7HpB7CoNZNNM4zZlYk6vxYHGf2kSeYvGB5XEprUlqzEvGKIhq2BQeG57YPU1EsSRqrs61xAn0dQRDQly+zLy8RrtWZBN3peFjAPM700WniEM/JmMKAsD7CU5zr8Vms+p0ggMFhOebLuG7nVh6vih27ycuFjckqMnyZrfySx5q6bUWZjOX7SVSWN9EoiaHRufnpxGw4co2IjHxRoj1zTbmYZmOKbC5pLd+fsLBV/ClSWuNJxKVF2jDkeyecZeU2QVjkCtLm3dMxZTu0HwTsyZXoL1YwgLXZJJ2puuPRlq3VnwTB3CJzs2WSOp6UbRIdxspc/XgiwbPQLekjOfF4WsajI/rJ8wnupJ1k08VOhI1JGwk+yZ0M0KSRMYoyBSp4lENHLCZXwAeG5uZybFmwcZ38nytAoSjiZy7Mt47H92GcqJlRhAdkcYzqauqLsfcNzD2aEgTi5zM8JinA5OT+Qp4f8NRokZGyi2kYrG9NTWz5juquorqNUhnGFnhxmkTwGIZBsj7KM5e01mK0pDthIX3n8h4d8WnuoojTtDTWVGSIU8Dh0/xqQR9HUVTwKIeWbFoWt5m6MI8nHgsX9Lh4newfmJt4qjccjNJks8EPGiI8QRA0RCBiU6U1XC8UaQb0dsKqumLiqMjYmWUELPLYKRQl9TdFd1DF83lypEDe8bBNgw1tqYbp5A0k4o3psKHR5kSgpiIRk8jfuNch3VC4PAfBs9AprSCMNLa1LL6TcxPZwQB3spOeRWod7yHDHexkBwOL8njK4YkKHuXQ09k6vyno7S2QSoZuzgXYuXf2giVe1+ruebOPrIyL8Lh+UK2ptg1j6jEMY3kgkEJl2xZTxnr3Zc+TYuOZ1idFC265Ar3dUw7HLLoeT44UKHs+CctkY1u6oUZmUtpb6kZx+HMXqTPBsuRrXLqzvnC56MxS2Prh0FDDWLihoYWSPMZijARpIk8++SSGYVS9ja7nQQyYczfWbDExMIDv89CiPJ5yeKKCRzn0mKZENuZaz2OakhqzLYkY5Qvw1L7ZRXoMozHKUyjNbh/GRXicg3Vogexf1PXUUhc9SSVhVZ0xo+9LpOdg+xTV11TcaT12chW3OhcrE7PY2JaePuUWMT61VSxJVG2hSMYnpBfrRVnJ9fBnI7jqozsL0TXl+yI2O9tntP2NGzdWRcbdd99d/f2vfvWr6u83btzY/P08CHkq/JhH6GRxW+k7SXEj28kzx+aDSTj77LMxDINvfvObTdumsnxRwaMsDar1PAeZJD4VmVTNkTmTEnHw9P7ZCahUXYFpcZaCJ/AbFrlKnQdP3Jpi8csX5bkm4nXmh9G+JBqdeYNAHJmnaguP3JNdT1JjU6TQhkoVnhot4gcBbQl79kNAk/HG6MXQSHM7yupJJSS9WIdlGiRCcRYwyzqeaD8XqmB5aFTeQ8nZz4z6j//4j+r3X/rSl5q5V7NmG/34BDM2FZwKf5ZR0hgWAQHb6J/X4yrKVKjgUZYO2TQkErXhkbOls6129Z6Myzb29c+8kDmVpBq9KFdmt5BPF+GZTHwEgUx8h9q8sPEk4rCmp64WJIzgDI02Hp8gCAu/A4nsTPJ4Udv53lyZAOiez1ys9rr6FN9fuK6tZELa9f1p/Hhm8xpF5pTWAgieckVEdsfsC5U7Ojq4/vrr6e/v58CBA3z/+9+no6Oj4T67du3iDW94A+vWraO9vZ2XvOQl/PnPf67e/tBDD/H85z+fdDrNy1/+ct7znvdgGAavec1rANi7dy9btmyhu7ubWCxGT08Pl156KcPDwxP25xEGyD26j1vWvJubrEt5+lu/wndc7jnv09yy+m/4SfzN3Nx+Gfe96l8pPlWrubnJuISbjEt4/HM/49aj/pbbj/9HHrjsK9xkXMKjn/5R9X5/fNfXuMm4hB3/W343+sdd3PvSK/l59xX8rufvufyVb2T79u3V+w8ODvLe976XY445hmQyydFHH81NN93Et7/9bQzD4Pzzz6/e9zvf+Q6GYfCSl7yEs88+mzvuuAOAt73tbRiGwcc+9jEA7rrrLs4++2w6OjpYu3Ytb3/72xkYkOdSqVS47LLLWL16NYlEgvXr1/OqV71q1q+rsvRQwaMsLbraxNMmmhg+G0wTutupipYgkLbgoZGJImEyLLPx6nw2UZ5xNTz1ow8mTWmVylKMbFnTT8+O2TJwssFZeqwmMnxfIj8w5eT48W3na7JJVmUSc59FVT3OIcXS3LvjDvY4cXtC/VJ6rp1a7gIJnmgSekfrnByy3/KWt1Aul/n617/O17/+dcrlMm9961urtxcKBV784hfzve99j1NOOYXzzjuP22+/nRe96EX09/fjui6vetWruPfeeznxxBNJpVINESOAsbExisUir3zlK7nsssvo6Ojg29/+Nh/4wAcm7M/tTz3AjnM+R7lvhGd/4wqOePMLCfyA8t5hes4/hSMvexHpo1ex/8e/54+XfXXC32/70Pfo2nIC3S85mSPf+SIAnr7m7vBQBfTd9AcA1r3xLyjtHeI3Z32CAz//Ix3PP5bMqUfy+5vu5Oyzz2ZoaAjf93nNa17D5z//ecrlMpdeeilHH300jz/+OBdeeCEdHR3ceuut7N27F4Abb7wRgIsvvpiLLrqIdevWAXDeeefxvve9j+c///n8+c9/5pxzzmHr1q289KUv5bjjjuMb3/gGr3vd6wiCgG9961t89atfpbu7m3e84x1s3ry5IeWoLF+WbxuBsjIxDKnn2dcvNTktsyz+TCYk5RLN18oXJcUznJs4mXwy0sla3UihNPPHHx/hqU9pTZYyiqI7rVNEd+qxLIncHBiqibBcQWpSAkQUdbdPuh3PD3hqrEjB8TANgyNaklN3Ys2GZEKOzfghrs0WE1Faqy7dmKovXHb9mQ8SjURoswuWx/IidqcTrtNw1lln8Ytf/IKrr76aIAg48cQT2bJlC//2b/8GwE9+8hMee+wx1q1bx/HHHw/AkUceyWOPPcb111/PSSedxGOPPUY2m+WOO+4gk8nw6le/urr4Axx33HFcffXV3HLLLfT19fHMZz6THTt28N///d8T9ue6c99P5emhqtgBsBIxNt/wd/T9+PeU9g3TevJ6Rv/wJAO3P0zg+xh17/2T/v3NHPn2s+X9aEDLyesZ+9NTjPz+CQI/oLR7iI6/2ET6qFU8+n9+jDNcoOvsZ/Dcm/4HOSo8cOrH2Xf/E/zXf/0Xp512Gr/61a9IJpPcd999rFmzBgDHcYjFYlxyySV84Qtf4LrrruO9730vP/vZz0gmk7z2ta+ltbWV66+/nt27d3PxxRdXReS73/1uKpUKp556Kr29vfT29nLPPfdw2223sX37dpywK/Lkk0/mkksu4cQTT6S1dXlbDCiCCh5l6WFZUrS7r1++n615W0eriJaorXlwDFZ3SZRn7wHo6Zx6kGM6KYs3yDbqDQVdVxbfyfZpfIRnuqLlihMOCTUgO0NBZZoSwRkYgVw+rNkZlsjPUesmFTsVz+ep0SJlzydmisdOspmLfUerPA/XqxXs9nQ2b/sgwmqwcWxIzDSImQaOH+AFAWXPn9nzqqa0mhjYdj2JRq7unlch9Lve9S7e+973AvD5z3++4bYnn3wSgN27d3PVVVc13Pboo49W01/r168nk5H304knntggeK677jouvvjiCY974MCBCb8be2QPyY3drHrladXfDfxqG/e86FME48Z9+GUHd6xErC1d/V3nc46CclnEuGmw/i0v5KF/vJanv3UXdot8btZdcgYAxSelXif7DInEGED2hDUM3f8EO3furD63I488sip2AGJht+A73/lOvvCFL3DNNdfw7Gc/m+HhYS666KJpBUp0PO+9917uvffehtseffRR3vzmN3P77bfzox/9qJoiO/fcc7nhhhuqx1dZnmhKS1maxGxZPPuHZt+5ZRiNwzErFTH362qH1paw42mKFIxtN7oK54tyBb+vH57uE5HRNzDRnDCoRXj8IMANe9INJnFZjqIi2fTsFl/DkJRfa1a6oyxLjtP+/gnHaLK286aKHZDn29Ve+zk/D+PHqUjERWjWDYc1DKMhyjPjuVoLUcMzNCKRrnlOQn/zm99MOp0mk8nwpje9qeG2qFNr8+bN+L5EtIIgYGhoiH/6p3+qpm2efvppikU5/tu2bWvYxne/+11ABEK5XK7+HEyS5j36zWdTerKf+17xL3gFeZ/v+/59BJ5Pz0tP4YL813nBvR+v/cG4bZi2KRHPZAJiMY649AWYCZs93/0N+35wH4ZtseY1m8H1SG3oAiC3bY9sCshvl/TUhg0bOOqoowCpYdq3b1/1MdzQA+pZz3oWmzdv5g9/+AOf+cxnABqEnRW+1n7dBUh0PP/+7/++eiyDIODxxx/nFa94BbZt893vfpfR0VEefvhhzj33XG655RZ+8IMfTDhWyvJCIzzK0iUZlwV1/0BYvDuLhSoeg/ZWWZBABE8qCS1pqQvpG5SC2PaWiVfmyUQtZVQoSTTH80VUeL5Mvq4vlg0COcGH26l4viz8nkcsEcfwvFqRb/38sLl4tfi+RJm62moix/VEkK3qhGSCsYrL7rEifgCZmMURLbPsxJoNqaQIt+g5DY7I69YsUREVoJcqDSmjtG0xWpZFb0ZztYKg9po1S/gVS/Ieqhd9c6StrY0777yz+n09L3vZyzj66KPZunUrL3jBCzjllFPYtWsXt99+Oz/96U8588wzOfbYY3n00Uc5++yzOfLIIxuiOwC9vb0A/OxnP+Ov//qv+elPfzrlvrz6q/+Dr+/Zz9AvH+Z3F13Fc3709yR6JWIyfO9j/Pk9/8nAHdum/HtAPjtmBZJx4r3trH7N6ez57j2U943Qc/4pJFZJrd4RFz2XRz99IwO3PcR9r/wspUqFkT88QW9vLxdddBHt7e288IUv5Fe/+hXPec5zeOlLX8ru3bu54IILeM973gOIiNu6dSu33HILbW1tvOxlL6vuxvr16wG46qqr+OMf/8jb3vY2Lr/8cr7yla9w1VVX8fjjj9Pd3c3DDz/Mr3/9a3zf57rrruPKK6/k9NNPJ5vN8qc//QmA9vb2g7yKylJHIzzK0iaTEmHQNwcH5dZM3UiFsG07agNf2yPFsPsHJIIQBLKA9Q9JiqJQqqWeRvMSlSlVRLBEk7zLldpX4MvvXRen4soJv1QmPpYTT6D9AyKCRsN0VCpZM/GbKZ4n4yYyKRGAvV1ghB9h34f9A4wMjPD0qIid9kRs9m3nc6GzrSZwPG/uXXZTkUxMKCCfdYQnCOTLMJvjweOHxotNHA66efNmNm/ePOH3mUyGW2+9lTe+8Y3s2rWL//zP/2T79u1ceumlHH/88di2zY9+9COe97zn8ac//YlCocA73vEOABIJef9/9KMf5UUvehEDAwNs3bqVD33oQ1Pux3Ni6znq+5fTcsqRHPjZAzzwtqvZ+P+9hN7XnI5fdhm4cxub/unV0z8Zw5DPVUlcy9eHxcsQprNiNiRiJI9ZzV/c+k/0nHcSg79+hNzWJzn1JWdw2w030plMYxoGP/zhD3nPe95DLBbjW9/6Ftu2bWvwJ7r44otJpyWlduGFF1afM8A//MM/cMopp/DQQw9x1VVXsWPHDp71rGfxy1/+ki1btnDnnXfyne98h7GxsWoB9/HHH093dzc//elP+drXvkY8HufDH/4wr3jFK6Z/zsqSx5gspBlx+umnB7/73e8WcXcUZRIi92DHlSjGbBYY14U9B2piKZupdRhF241uTyUkEhPNQopSIMkkpOIigsqORAgyqVrNjh/IbWEEoh+DPicAz6MTn9VGIH8Tj0l0JmbDulWSmpop9WKnvW56ebkCfYMErkfe8Si6HoV0inRPO93peXRizZZoIntEZ9vsnt90OI5se11vVawEQcD2wXzVeHBTR2Zqg0cQ8bqnLzz2vfPfp2hq/Kom1yzNkZGRkYbI0Pnnn88vfvELPvzhD/OJT3xiVtvayh7ezU/mNlbCDyRdHACEUU/TJEjEuLntMgjgvP1fxM5OXpfXH+T5gvMSNhc65bPiOOI+nklJpG+K9/MFF1zAzTffzK233sqLX/zi2e+3smIwDGNrEASnT3abprSUpY9hyAI6MCypqNmIHtuWv+0fkp9zeUlRpZM1wVNx5KtQEgNA0xQxY1hghkIlHoNCOTStMxpPvp4vi1/Y0l72AN8BDxLJuKTQnHB0RsUB15aOq3xRBFgmOf3z8X3YPyiCrG2ciEjE8Vd3MfLUftwwZdPrOiTHcmFqaZEETyopAifqjhsalcjMPGtbAHkNAySCFg79NAyDlG2SD6M7BdejbTrB08z6HceRiN/aVfPfVpP42Mc+xmOPPcbpp5/O/fffzy9+8QsymQxvf/vbZ72tE+jGxMDBm735YHQBbRrg+mCb7PnBfRz45YN4+TJHXvHiKcWOg4dhGJwQXwPxuAh715XPydCIfM4yofgJbRruuecebr75Zm677TZOOOEEXvSiF026bUUBTWkpy4VorIFtieiZTXork5KrxIiBYeki2RfOqPJ82V7gg+OJ6MmmZaE1w9C850sFcirJhPFCQdBw5VkBudK1TBIGso14vFZkHE13HxyRrrGn9sn3k0VbI7GTiElX1LgrXNcP2FVw2JdtwUkkaEvYJG1TUgl7D8xtVMdc6WiV5wl1ZohzcM0eTzT2Y1xaKz2btFbUXdQMwTM4Gg4HXSDH5jnwrGc9iwcffJBPfepT/OY3v+FlL3sZd955Z7XodzZkiPNKjmOQORSgR+9hw5CvIODJq2/j6Wt/TffZz+CET/3VlH86SJFXcTwZ6jynbFuO9dpVYQrXkPfV3gOQL3Lzz37Gxz/+cY466iiuueaaxYtoKssSTWkpy4toXpTrzS7S43mSuopqcBxXrhLzBYnsBNRO0jFL6mvqp4EnEyIiMmkRS4l4NdqA40qqK5siCGC7J+26mAbHGT52Mi6PmSvI9qNi5VJF6oWiyM0Rq2vbhJqpoG2J2Bt3Mp/Qdt6SJJkvNJo2GqFJ4Bw9YmaN48hxjs4rLZmmFPWSC1+nuhRSruKya1QW5aRtcnT7NCmY4TEYHpUoVGfb1Pc7GKWy1CitW7Uw87iWCDsY4GK+zyoysxsg6rhyEWGGnVq+XxOGvl8Tr+M+tz4BfeS5jgs5lq7pHyMIU8ijefBceY+1ZJpWS6Usb6ZLaek7RFlezDXSY1my8JfD1FKxLIug50t6y0CETpQWCcI0lefJCTaKlFimdH95fm1RD6hGfRzAd6Uw2jYM7Og+5fDv47G6dvmwWNpxZaRGvdiJIiSWOanYKTq1tvNk1HYes2XfejprxcyBL/PJZuI03QyimWgRY/nmtKqnEtUC2OqvbKu6FJddH8+f5vlFKa35RGWCQN4zbZN09q0wNtHFWWzgAFPMbpuK+s+jaQBBXZrLDAeglSd8bg+Q5yw2HFzsgBz7TEocyHs65XP09H55jzcjoqisWFTwKMuPuYieIJATrefVWswdV1JUqWQoREzZZsyW+8TjtWhQJHiik20iVucNU1M8ZT9MfSXjks7yfbnSDd1bScRq+1KpyONm0zIuIkprRWJnvJ9QyFjZZedoAdcPyMYsNrSlGwt2o8XArhNQI2NzH8w6W7LpxohSFJGbD5Ylr025lqKzTIOEXTdIdLrHaEZKqxTOV8su7hTxQ8UHOJMUMQrMIi3q16l/CCM940RQEEg9XPia5KmQJsYHeeHsdzIRF/f0tT3y2uzuq3VCKso4VPAoy5PZiB4vTA2N5Go1OYYhxcQVJyxQNsKCZUMEkG2D70nRsmHUPHgMRBB1dYATPmbdOb7ieJL+siwRPPXRoWiwaaFUc3BuyUj0IhGTTqS+QSmwDgI5kY8TO4PFCk+P1drO10/Vdh6PSet6/QT4Qgn29ouAW0gMAzrbG1MZ0XOaD8kElMbV8dgzrOOZb9FyFN2ZzLdphdJNho+whWFKuMxQKAd+Y42baYgIqr724Ycl8KFSwcVnhDIfZgtdpCfZ4Ayxbfm8rOqULrE9ffJ+V5Q6VPAoy5dI9MRispC7kyzkjgP7DsjJr1iSq/RUUsSOYchCWKrIQuj5UqMTDfSMx2oFyaYpQiFflJ8jA8P6qILvUzbMsEbBkBlafp3gidnikGyEoioZF6EDsv1EXIoxB4bFWLBuYQ2CgP35MvvyMu28Jx1nTfYgbedWOI6ivj3cceQxZjMYdS5YpkSnotWvVBbBOR/SyQmLWONcrZlEeOZ4yovGjCxWLdQS4RyO5nI200f+4KInIDTgrP+lIaInagwIi/lJJnCTMfrIcwWbOZdjmrPDibgUN3e0ScS0f1jTXEoVFTzK8iYat9CSFtFTP1nb88Lf1bWEx2y5b33XVjRzy/PkZN2SlmhCOvT+iISUZUraq39IUlLdHaHgCa9aKw7lbFrEi2GQMIzanCmQfYsGorZmGxffgFqxZ0CtwBoZAPr0WImBcNr52mySnpl67EQt/fWpsajza3hsYUP/yXFt9MNjEyafz4pEXBbOOmHbMDnd9SYdlQDUXoO5mDAehtGdCAODy9lcFT3Tp7eC6l/Jj2HRMmEaKx6Tz1QqQT7m02cUuILNXMZEs8X57bQh4nhtj/y854B8XpXDHhU8ysqgNSvCZ/9ALQrghGLD9WqjBUbzcnvMbvSIcVy5b1Tf09spkZqWMOITmaglYhI1GRyRxdsywwJmn8CwKMdDl1fDIGGGESTfl//jMREAa3okwlKfXimVZSHPpkVkFUuwcy+VUpknRwqMVVwsw+DI1hTtyTl422TTMuCy+piBdC3tH2iYU9V02luqnikwz1b1KDJWF+WJWSbx6gwzKLmTbDsa/QFz6+QpluXvZzvEdoUQiZ4rORcPn/3k8JlEWEbH2Pdrr3E8JsctmQAMfJPq31/JuVzO6Riz6QKbDWbYoRj5cC20wFeWPCp4lJVDOiXh7IFhMcBLxEQIRYXBIBeho/maQV7UzWQa0u1RX6C8qlO2mU6JUDAQcZAKrx6jCE25Ao6H092GH567bdPEjkL5FVdSZe0tIjpMQwRNFJ0oVeRxM+m6eqI4ecfjiV0HKJcrMgC0PU0mPg+v0GikRrJmvU+pHF4BL1CKyzCktqJ+4vzAyNy3N2laq3YamzStFQSIYJ3DWInDOLpTj4HBuRzD9byeLWygjzz7yeEw7ngbhlxMpMIIaTwGlokTM9gfjNEX5NjCBr7PXzUvjXUw0km5yCiUmj/2RFlWqNOysrJIxEVU9A1KRKejVUTP0+Gk5VRcxEVUTBxFfixTBE2+KIKg4sj/qzpDERSmYiKRE00KTyXgwcfADHDiMSjLlW3cDmt+TEO209lWK0KOFuyoGLpSEcflMN0SBDDkBezHJPB8shWHdavamzMTy7JEFA6PhTU1YSpv/6BEnxZiYbdtOVYHBuXnfEGOW3YORaqphFyte141WpWyLUbCQaIFx6NzfJnNfNJZxRJw+EZ3xtNNhs9yPjsY4Ps8xI1sJyDAwSduWSTStvgN4lGmTAWPGCaGafBa9zguLG5iU/vGxd9x24LVXSJ49g3I53qu9VzKskUFj7LyiNkieg4MylcmLVGUjlYRN8WSRF7a0pL2ilrEMWq3lysiVAxDTOZA7re6p/Gx0ik4olfEzYFhshgUMhkSyVjtare7vbHjKh/OGnJc2WY2XW3XDVyfvV7AsCFFzN1tGXra0hjNHABqGHIsknXigUBa10sV6GlvbGlvBpkUFOumqg8M10Z2zHbfkwlpa24RwdTguBzW8TTUN801nVWN7kx0uD7c2UQXH+CFvIfnsY1+djDAVvay38hRxiOBRS9ZNrOGTXRxAt1kEhYM9EHWOzQu1aYpn8PBURlG3NulZoWHGSp4lJWJZcoJbXAEHt1VDa1jmfJ9vigLYSohNTORk28QyKI/khODOZDF7ojawMk8FbbRzyMM8Hv2sm9NjgoenhPQmY9xWq6NZ5TX0rpuHZnuDnFWrl8wc3mJJkUDR00Dyg5uEPC0HaeQTWAm4qxpSdE2l3qdmZJKSIrrwJCktkBcpPcckCLnZkc1OtvC9F8YYTswKKmG2S466aS0HoeCJ2GZWIaBFwS4foDjB8TrZ4hVIzyzfJxCCQidgZVJyRBnM2vZzFrewMnT39lGxP3wWG2A72JjGNDZKoL7wJBEelTMHjao4FFWLtGJzDRrfjvxuIiNTFK6tzrb5H/DkBqPchkIapGIOnYwwPU8xI/Zjk+Ai08Cmzji+OtYAY9lHH6T2Us62I4VwCsTx3ERz2IT3bIRN4ooOWEHmBghFrMZnrbjOKZBzDI5oiXV0HK9YEQprpFcOJIi7KzpG5BU4CTzu+aMaYoz7t7+mpN1/1DoDD2Lx0gnRciGXkbRINFcNEjU8YjXpyuqEZ5ZPEYU3Wnm81ckZbq7T4RvIn7w+y8EkZ3FgUERPt0dh2Y/lEVHBY+ycilX5Couk5QUUqEkAiOVlMXPNGRRW79aFraRMRkoGjkwh/ST59PcxZ3sxAA6SU0+RdqEViOOgYFhgOM53OBt5wfONs4yNvKB2Nl0532JTiQSIr462xiNx9lTrEjAybY4ojVJbDFD7YYhC1EyLgIkKvwdzYUpro7GsRfzIR6Tq/uonqdQErHV3jLzbUSeRcVy1RcnFbPIVVxwPUr5EgReTaiUQodtPxzjYYTPOfKImUzQ5IuhCaVGd5qKacpnbWBE3MAPlZiMXMzDIaSHm7/S4YoKHmVlEgQiXkyjlsrIpmXxyxUkShCz5WQ3VpC0U1e71GuUK5CMExBwK4/zCe6giDujQYpm3Qk8ZsXoNdvxPZc7vSe5r/JtPlI5jXM6ezHW9BAk4hwoOvQXpCC6PRFjdTbRsI1FJZmANatgYKhWWF2pyKLQ1d68RSGTgnK21ik3PCYddalZpNCi9vRI8NiWCKBSmRIBDPp1M8sced2LFRGbBlS9YixTJnGPn2M2MibRP43uNJ9MSj6D0efuUGGG5ph9gyKgD0VdkbKoaMWWsjIZGZPi4/qFzCCs2UmI0Kk4UpzbN1Cr87BMSCcJTIOr2cr7+SV2WIA5q6nRdY9p2ja98Q5sw+L9rfdwdc8TuLbF07ky/aGZYG8mwZpDKXYirDDtVL/Y++EA0gNDNcfi+RIVTQNVf56pRl5E88XqSSfl9Q1/n7TDLjvXo1QsE5TKocgph23/ngjZfFEW2+ExiWZVJjHSyxdlpEhSozsLQmSGOTy6sB5QMyERlwuhodFDux/KoqCCR1l5OI4Y6k3VaRS35SRXcaVmp+JITUhIQMDVbOVqtrKKDGmaUDhsQDqWYlW8jS+n/sy/D9yGNzSKBaxvTdGVis/MOXkxMAyp31k9bgBpvtC8GUWRP09khBiJqvGmhKWyPObuvkZBFA15LZRgNI+9p49Yrgiuhx9AOR4uZC3p2qyyTEoiCpHLtRemF5/aJwLI89V3Z7GIvLGigbmHkrasiOeFnjGnHHJU8Cgrj4orV25+IAXJ5Urtq1SR3/m+LISWJYKnbizFrTxeFTt2kz8itmHRYWT5Wtej/Da+i2MKObKVyqE/6U9GZFRY75fjeRIR65+HY3KEZTV2yUTCMzoWuYII11JFRGyUAgsCESrFknTg7emDYolkLBRBpkmpfpBotL3occJCcWKh8PV9SX8+ugt27ZX7a+3OwtPeIp/VfPHQ7odpihAeGTu0+6EsOFrDo6w8MinIrJPvo9ESnif/u15o9ueC64AftqkXy/DUPvqP7eIT3Ek7yaaLnYikadFFiv+7+s+cU9lE12Do/ByleZZSZCGqc0inpKMlSkHkCuE8sfbZ1d6MJyGF2wwM17Ybs2uRFscTcZNOSs2H7zdGY4JAtmFA0ocx0wDbpOSHr7VtTRQ8pXJtRloUYbLD4bEDw7K9nXulfTmTUq+WhSLyxdnXL8e8WYXxc6ElI1HEaFiwsiJRwaOsbEwT4iZMlZaKFs1wltanuYMiDr1kJ79/M3bJMGizEuwnx6cT9/LZ1S+R1MzgaJhOyshCu5ROvOkkJHokAhNdkXueRGBaMiLW5ioMsmmJruUK8lrs7hMR6vm1Op3hMTkexZSkp6LF0XFlP2yLquyKxSj5ZjisNVUneBCR4weQTkB53PGN5p2lk1KsvbtPUl8drRKNaLYZoyLHu71VargOZdeWFUYHS+X5CXhlSaOXLsrhjWFU25x3pPLcyU56WJzOkR4y3MFOdhiDInDW9sjCmivA7v3Srj1N2qjseuzNldg1Uph8hlSzsSwpaO7pbBQ3Y3kxK4zMC2dL5Itih11z5YqkFwpFibzYtoiVIBABUv/YMbtae5GK7pOIU7Isgih1VZ8tLEoHHm3ZxsU1QFKdiXjNITsZfr9v4NCnXVYyLWl5nQ914XAqqVPVVzgqeBQl5HoexIC5dWPNATOcE/19HpJfGIZEF1Z3i6ioOPD0fomquLWCyoLj8dRokceGCwwWK4xW3Gpr+6KQScm4jXRdm7rrSmoiMgScLW7dZHsnHOLqB/IYkehJJmpu2BGR4AnANiBmALaFH49TScSrdVnVxwgC2U5bGMGLtuWFt9VHcbxwX9atkkJnZWEwDOhqk9d2LH/o9sO2Dn3XmLKgqOBR5s3GjRsxDGPC1/3331+9z86dO3nnO9/J+vXricfjrF27lte//vU8/vjj1fts27aNN73pTRxxxBHE43FWrVrFmWeeyVe+8pVJH8uyLNasWcMll1zC/v37q/f593//d4499lhSqRStra2cfvrpfO9735uw37feemt1W8953nP5MY/QydReM7dufB83GZdwk3EJg3dvr/5+4Ffbqr+/deP7ZnXsOklxI9vJM06wJOJS37BWZncFuw8wtm+AJ/tHeXKkwEjZoeC4DBYdPD/Am0PR89lnn41hGHzzm9+c9d9KtKdD6nvqIy6jOfHtKc1CgJXK8jeuBxgidGxbPJRKlZo/SjIuYqVUqbknRzU44UKVBPm7RJxiLF5NVVaHxaYStfRUfYQncv6NfuW44Po1U8qllF5cidQPtW1GF+BcsC15zZUViyallabxile8gmOOOab6c0+PLNbbtm3jBS94AYODg6xbt46LL76YkZERbrnlFi6++GKOPvpo7rrrLl7ykpdQLBY58sgjeeMb34jjOGzdupUvf/nLXHbZZRMea/369dxwww1ce+21+L7PddddB8ATTzzBSSedxEte8hIefPBB7rzzTt74xjdy2mmnceyxx1a3cc0111S//91v7+OUR15F13FHz+i57vyPW+l8wfHy/ZdundsBA2JYBARso5/NrJ1we2BZjKTTDGBRLpTx8nmKGJQsk8Awqwv0IblyMQypv0kmpNi3GC5UThjtaUkfvLbnwBDs75cFz3HBCCCbqrk9Vypghh1TriePlU3J1OtELKzRCqM8tkUyCBgzJe1VSiagUpbUGMhjJBNScwSSHgsCEU+uV5sdVnHluW1YrV48i0nMlshmNNjzUI2eUFYsGuFRmsY73vEOPve5z1W/1q2TTqm//du/ZXBwkGc84xk8+OCDfPOb3+SGG27gySef5LnPfS4Al112GcVikS1btvDwww/zn//5n1x77bVs376db3zjG5M+1he/+EU+85nPAPDAAw9Ub/u3f/s3fvjDH/LFL36R22+/nba2NnzfZ9euXdX7lEolfvCDHwBw6qmnAnDgmt/M6HnGOjLsvf63VPrHKB8YZd/37yPWMbHup/DkAba+7ipuWfNuft5xGb950ScZuvfR6u2/PvuT3GRcwpMf/D6Xbnkl6XSaF7zgBezcuRM/CBgsVrjprnt5xcsu4PRNG3jBs47niiveyiNPPk7C88g4DqP9/Vz5T/+TFz77JJLJJEcffTQ33XQT3/72tzEMg/PPP7/6eN/5zncwDIOXvOQlnH322dxxxx0AvO1tb8MwDD72sY8BcNddd3H22WfT0dHB2rVrefvb387AwAAAlUqFyy67jNWrV5NIJFi/fj2veu1fSnt5V320J5D0xO6+cDr8JBGosbzUKpUcqVdyXZlsn0k3duyUyiJAXC80j0zKghjZC8RiEr3xA5JGrcumlEzIoumGqbJkvDFaY1m1yE80tb1UkcfeuEbFzqEgGZd6rr7ByU0hFxLPFxGsrFj01VWaxte+9jX+9m//tvoFUCwW+eUvfwnA+973Ptra2qr3b2trY+3atezYsYNt27YB8MEPfpB0Ot2w3ZNPnnwKc6VSYevWrQCccsopDbfdfPPNvOc97+Hss89mZGSEM888kzPPPLN6+49+9CNGR0c55phj+NCHPgTA4DW/ndHzPOItL8QvO+z6+u089fU78MsOR7zlhQ33cfMl7nnxp9h7/W/JHLearhc/k4HbH+aeF/9v8o/tb7jvvv/zC4z1bXR3d/PrX/+av3//B9k+kOOBR5/kkle+lLtvu5UTnr2ZY595Mr+59Rf83cWvxfcrGAmbD1/xVq772tVUyiUuveQSjj76aB5//HEuvPBCOjo6uPXWW9m7dy8AN954IwAXX3wxF110UVWQnnfeebzvfe/j+c9/Pn/+858555xz2Lp1Ky996Us57rjj+MY3vsHrXvc6giDgW9/6Fl/96lfp7u7mHe94B5s3b+buu+8WEdGSlhRcfZeL54mhYN/gRGO3gdBzx6nUOuXyRYnqpBKNi4/jiiAKAkk/dbZJrVM5XBRNExyXpGXVBA8GQToJVjgvK5VqHI9hWyKYKo5EiUoVmbt25GoRUcqhIZMSYbp/oLEGa6FxHB0vscLRlJbSNG666aaGnz/3uc8xODiIF9ZXbNiwYdK/6+vrq36/ceNGAL70pS/x13/919XfP/HEE9XbAP7yL/+y+v2WLVv4whe+0LDNe+65p/q7ZDLJy172MmJ1i1iUznrNa17DBRdcgJWMU36in8G7t1dTVVPRddYzOPCLP7Hr6tsgCMg+Yy1dzz+GJ+qf00/up/DEAdJHr+Ivbv8whmFw31/+G/t/+Due+trtnPC//6p637XvehGn/99384KvDvGuy97J7//wB/bmSlx7zTWMjYxwyvPO4JNf/TZxy+AdL3sxOx78Ez/6wQ849pkn88ff3UsikeQHN/6CU3u6sNNJ/HSceDLJJZdcwhe+8AWuu+463vve9/Kzn/2MZDLJa1/7WlpbW7n++uvZvXs3F198MW9961sBePe7302lUuHUU0+lt7eX3t5e7rnnHm677Ta2b9+O44jAOPnkk7nkkks48cQTaW1trT1x25ZoT6EkBcxREWixBHvK0NYiBcMVp1bcHE2qt8zaNPmodscNh4CahvyN49bqg6J02Z6wfbxSIdbWgm0auH6AHwRUWjIkLAvMADrGdWZZlggmy5Q0VkcLrOpS352lQDYtr3nfoNSKLUa0rVAW7yVlxaKfbKVp3HDDDQRBUP0C6OzsxAoLS3fu3Dnp361atar6/VNPPQVIxOZd73rXlI/1ile8opqu+e1vf8v27dsbbv/Yxz6G4zg88MADrFq1ig996ENce+21AAwMDPDzn/8cgNe8+tVkTJve8ySK9PR//qrWJRR9VdwwvB6mZRyXDW8/i8Jj+yk83seGd549Yf8KTx4AIHP8murIiOwJa+S2nf0N92059UjKeCQyMjG8mM9T9nz2PS0puI2bjsO2DHxg/TFSg7T7qV3sCo/nqnXrMNeu4/FUmkdKHo/vH+XRXX1c8NrXA/CNb/0/fvyLWxkeHualL3s5iUwWf4oi5yeffBKAe++9l6uuuoqrrrqKclladR999FHe/OY38/rXv54f/ehHnHnmmXR1dXHBBReQz9d11xhGrZOrJUu10CgIZH7S7v1y9R7dN5peDyI+IhM6x62lnIJADn80Ay0SUm1ZOKJXvi87ELNlkGhIybIlRdLZLqmyeiwzjBAZItJ6u1XsLCXSKSmKPzAkVg0LSbki7ymtG1rR6KdbWVBSqRTnnHMOAFdddRUjI7WZVblcjn379rFp0yZOOOEEAP7lX/6FSqXCGWecwac//ekpt/uOd7yDm2++mbe97W2USiXe+973Vm8bGxOLeNu2OeWUU6rbfuSRRwCpZYkiFS/csgUjnWTPjyU1tvf7v8XPlxoFjxulU8IHqLgc8brnYqXjWJkER7zxLybsX3qjFGznH9lXFX/57ZJaSm/obryzbZHAojUhAVfDgEzMYs36IwHY+egOHM8nCAKeekxqgHqPWE/v+vUA7N+9m8G+/bJYpxJUUgkqts3Go47jmSedwp8fuJ/PXim1Ti961Wt5bCjPtoEc5TDAMlQoM1RyKDheNQr393//9w3i9fHHH+cVr3gFtm3z3e9+l9HRUR5++GHOPfdcbrnllmo9VAOmKe3Ga7ohXreQRNGfkTE5ptm0FAzbliw4ni9X9K3ZsC098toJRHxGEaCIlgwcuaYqVpJ27bRW9Dy5bePaiZ1WUYRpfa+IIu3EWnqkElKvNTImherzHWcyGUEgHkA6P23FoyktZcH5t3/7N84880wefvhhnvnMZ3LuuedSKBS47bbb+MpXvsJrXvMavvzlL3P++edzyy23cNJJJ7FlyxZGRw9uRPbRj36U//f//h+///3v+fnPf87555/P6tWrOeecc1i3bh07duzg1ltvxTRNzjvvPKCWzjrppJM4Zt0R4Pk8aA/y2G334wzm2X/TH1jzylMbH6h+YnfgE2tN8hc//UewLWJt4yIHwKqXP5vUxh4Kj+3nNy/6FPHuLPtu+B1mKs76t5/VcF8XT6axm3IVG7dM1remueTSS/nuf1zFA/fczUcvfzOu47DjwT/R1bOKV7z6L7HTWU5+zvP503338LaXn8tZ55zH3CQBlQAAH0pJREFUvr17OPPF53LJZe+CeIwL3/xWHvyff8+v77ydlpZWtpyxRdJElknvWqnh+dIXv8DvH3iAv3zjpZz7+kv56le/ylVXXcXDjzxKT083O7Zv457f/KbaCXfllVdy+umnk81m+dOf/gRAe3v71C9SIi6iZ6wAQyNhW7lfm1bvepBMgpsXYZlNy9/Y4XDQRDwcZVGSvyuXJVJUX4+TTcMxR0AsRmB7PGjtZ6c1xOOxA4xRooJHHIvVZDmNNRxHFye0pMkcs17SbMrSJR6DNT1S87W3X1Jc8SbWWI3mpFMvO/FzrKwsVPAoC86JJ57I1q1b+cQnPsEvfvELrr32Wrq6ujj77LOrxcZbtmzht7/9LZ/61Ke47bbb+Na3vkVXVxdbtmzhwgsvZM2aNZNue8OGDbzpTW/iG9/4Bp/5zGc4//zzOe+887jvvvu4+eabaWtr46yzzuIf//EfOfPMM3n88ce55557AIn0PHP9Bhgc4TrzId7zTx9m4Jrfsvu/7mXNq08jtPeteb7UYxq0P/fYWt3JOOxMkuff+iEe/p/XMnTXI4yWHDrPegbP+PRfkTl2dcN9XXw2swZ4DMJH3diWojt1NNfc+DOu/NhHeHDrbwGD57/4PN79T/9MW0cHXgCf+uq3+M7n/5W7fvlzfvjda1m3bh3Pfc+7OaYjg+v7vPOtb+azH/swhUKBl73qNbRn07jFEm4Ab33HFTz8pwd4fPs2Hnnwz5z2vL/g/Fe9hq9efyP/918+za/v/hVOxeGIjRu57H1/z+PDeTqP2Eh7Zxc/+elPyY2NsWbNGj784Q/zile8Yvo3QTQyw3VFvJTC2hzLFCFjWbKIRQNeDUOESGerCCXLlLRXVMQ6iSPujrYK13M/NwbbcVp9nMAjbcVIYkevJI8zxG08gY2JmTV4JcdzESeyia7p9185tJimzG3LFSUdmkpKzZU1zyLjsTyM5kVQaXRnxWME0xiWnX766cHvfve7RdwdRVlkwtlNW4PdvLvzbnqCaFhkIKmVerEThdNjdujpEhrbRYInZs9pAGI/eb7Ayyf34QkCRsouBwplHM+n4gfkKy5uEGBgEBDQk4rTk0nQk568sPOCCy7g5ptv5tZbb+XFL34xBAFBxcEZK1DOFykbJuVEnJJtUwkaJzEcDMswSMes6lfSMqs1SxPwPGlTL1dkkYmKkRufsPzfkhEBtG5VrX08l4e9AxIZWtcrC154/D7NXdzJTgzEzDHGwRdCB49BigTAWWzgA5xJ9yKNFVHmgedLiitXkPdJS2b23VW+L7PryhVY1aFdeSsIwzC2BkFw+mS3aYRHObwxDGhv4YSBTkzDwHFdYthyUq0nmqJsW6HZXawpV4QOHgYGJ9A96e2GYdCejNGasBkqOfQXKsRNg7Lnk3c80WOGMekwjHvuuYebb76Z2267jRNOOIEXvehF1edsJOLEE3HiXW20lCty5ZzP4cdsKqkk5XicUgBlz6fsejiTRbkALwgYq7iMVaTl3DIMUjGLjG2Rilmk7DoBFE05L5ZFGGbT0oI+3pW54kqaob1V0hg9HWHbezYsghYCAm7lcT7BHRRxWUVmVmNBYlj0ksUn4E52ch97+AhbOIejmfyIKksCyxRbgpaMvE/29EnNVyYlFyFTRX2C0GAyV5DITjolqVYtVD9sUMGjKJkUmdE0ryxs4IbE4/S6RqOYMcJ/zHDQqG1PblA2GwEUBOB4DBoFXmueSMaavjvENAy6UnHaEzEGihUGSxXilkk5FGbmJI9988038/GPf5zjjz+ea665ZvLIi2HIYpFMQNCGWSyTzBdIjuZoS8RFlGTTeBiUPY+S64sI8nzKrj9hpIUXBOQqLrlQAJmGQdo2SRuQHi2QqlQwfF8ET/S/ZYnocd2aqKw4UkjqeVK42tIYeQkIuJqtXM1W2knSS5K5YmLQS5YCDu/nl1zOZi5ns4qepU4s7MDraJXuvVxBHL8tC2IWmJZ8Zv0AfE+EdBBIgfyanjlFY5Xljaa0FAVgYJgdfY9y8fq7WOUkMM3wKtEyw1lMyEJsWY0zl8qVWjQoHpt5aL3i4rsOfVaR6/rP4djEGmjLzDi07vg+/YUKwyUHyzDY2J4m3kyXWN+XguFoenkyIcIjmZDnaBgEQUDFDyg4HgXHpeBMHQmiUISyg1mukPY90qUyaUM6qqpizQsdkYnyaoEc02QCjj2yWqhaL3ZWkcFuYrOpi08fea5gM5czaVRcWcpEBpauG6akfblIscILlZittTorHE1pKcpU+L60SI/l2eS1cVa+lzvTffT6KblK9EKxEzn4xmNMeeE/m/OoaXDALHJWaQ3HOq3g5OUKNZ2UaEYyPu2JOWaarMkm6c0kws01+SRumtXoDl5kBliWtJQBJBMYyQSJVIJEMkZHMkYQBDihAMqHIqgqgML//HicnO+RC4zqfqdiFhkzIBMEJIMAo+LUvHc8XwTXgSGp5wFu5fEFETsANiaryPBltnI0HZzLMQf/I2XpEH1Gm9nFpawYVPAohy+lsnh7RKmUZIIP9D+T+zYOUQhc0r4p4XAz7BCKxyYpsq3/YeaiI297pI0UHxx+buPGCkX5itmQzcigzGk6UZoudCbDsmriJ7qCLpVrfjqWBSkRQPFknHgyRntSFpyK50sEKGZSGCtS8XyoAJZ0aflBQN71yMfjYJvECMjGE7QQkC6XMSuOvDZpaUHvJ88nuJN2kk0XOxE2Jm0k+CR3cipr6ELblRVlJaCCRzn8CALpEhoapUGxtLfQ7ab5yMhm3t9+D3HHxI5GHljm/FtgQ1x8RihzpXUuXb1HhF1LOREQEY4rnjXDo7LYt4TeNIc6HF9/Bd1KzQm5WJbncCCcSxWmwOKJOgHUlsHxfPL7Byj4HgXLooIhUTbfBzuGk04yBAwFYLa0kDENsjGblpYkNvBp7qKIQy/Zg+zo/MgQZz85Ps2v+CznH/wPFEVZ8mh5unJ4EQRS2Dg0QlXsmCb0dIqNfWcb51SO4PKR4+mLlXGjwZNTpbLqa+BmoEXqa0TO5Zha0fCqLlgbjmKo7xoJAsgXYF8/7DkQmqQtgNvsXDEMEWLtLTLMc32vdFeBCMpd+8Q3ZWQMyhVipkF7xWGtBcfasMkKWGcbtMVMrFJZhGgQgGXimyZjGOx1PB4ZzHNHbjd3BE/SM4fW8Vs3vo+bjEvY98PpaxLvf+uXuMm4hO0f+z49ZLiDnexgYML9Nm7ciGEY3H777bPeF0VRDg0a4VEOH9xwcnf9BOZEXNqe7fCjEI9hZNNcPvZMMA2ubn+EdjtLesrISr3gmV7x5KkwQpkr2MxlbJ54h3hMRjF0tEC+JL4z9fvqOJJCGhoV47V0+LWU2mrD8RakQk8gz5f0V5g+3Pi8zezc/TSGYZBOpeju6OS5z3o2//DOy3nus0+jUHHIDY+Qa22lbFsNx/QG4yECH0xr4aJcPS85mVh7ho7nH4uJwcA3f81xb7uCs846q0HcvP3tb2dwcJAjjjhiwfZFUZTmooJHOTwoV2TyslfnipxNTz5Dqb0Fo1jm8uIzOSazlk8mfsd+cvSM93mJBlpWmXwh9gk4QJ40Ma7k3IMXwpqmpLBa0rLfuYL45AR+7XGjWh/DEHGRTi098QOSCsykamMgwk6yl285m572Du6+//f8109v4oZf3My1n/0cr3v5K8kAvcNDlNtbybVmybk+/U6JO+JP0GOkpn6seeK7HusufgHrLn5B9XcZxC7AG2fH+L/+1/9asP1QFGVhWGJnR0VZAEpl2DdQJ3YMMS6bamCkbcPaHoy1vZybPZnreT1b2EAfefaTwyHcTjAuujNuUw4e+8nRR54tbOD7/NXsu34ScdnPaMBlfJxfTxBI7U//EDwVpo9yhYnGiYcSP4zy1O3TOy6+hK9/7t958JbbeMPLX4Xrurzrox+mMDDErh2P8oa/ew9HP+uZHLNmFZe99lXs2PsHErZBwrSr6alHP3Mjd576IX6WeTv3vuz/UBmqTWx/8ou38Mv17+EXPe/isX+5acIuRamrP17xNe4579P8JP5mBu/a3pDSeuqbd/Dnt30FgLvuuBPDMNi4cSMwMaVVKBT46Ec/ygknnEAqleKII47gK1/5ysIdU0VRZo1GeJSVTbEkkZ2gvl6nQ1JC02FZ1SLlbjJ8lvPZwQDf5yFuZDsBAQ4ecdMnEVgYpkmAQRmXCh4xTAwMXsszuLAZs5pMs2aj7ziS8ioUpWA4Igjk+RZLgAGJmAimVEL+P1TRn339sp+GURM94ethx2J89O/+nu/85EYGR4a55YHf8Q+f+gSPP7WL8884k2wqzY/u+G/uefHvOfrhf4LuWv3OIx+/gbWvex7FXQMc+NkDPPH/+ynHf+J19N/+EH9+9zfBNFj7hr/g6WvupvjUxDocgF1X/zedZz2DIy49k1hrY/Qoe+IRdJ93Ev23/JnOdat400VvpLOzc9LtXHbZZVx77bV0dHTwxje+kf7+fh555JH5HztFUZqGCh5l5VIoSc1OJHYsC1Z3zXluzia6+AAv5D08j230s6O8h63lXey3C5RNgwQpesmymTVsoosT6K6mRJpKLAbtMSkUdlwRPvmSjGmoEkg6LOoAMwyJDiXrBNBidHxFU9HLjuxTVHBdKIswi8XYsKY2Q2x4cIjHdu1k3Zo1HP+sU8C2OPKJR3nssccYu/5+eFdtiOzx/3whx/yPV7D9o9ez4+M3MPKHJwHYfc3dAKx/6xae9dXLqPSNcMv69xL4E4e8dm45gTNu//Cku97x3GNYd/EZ9N/yZ9LHruZzn/vcpPfr7+/n2muvBeDWW2/l1FNPBcBxnEnvryjKoUEFj7IyKRTFrC4SO7YFvd1NsZPPEGcza9lczvKG4XABbmuBROu8tz1rYrY8dlud+CmUagIjIgigXJavkbGaAIrbtTbzmN38KJBp1oaxFsu118PzxMWZEjt3PVm9e18gIyl2793LVV/8vw2bqjx6oOHn1lM3yiFol6iPm5MJ6qXdgwBkjl8Dnk+8JUm8M0t5/8iEyagdZ2ya0dOopjEn4YknngAgHo9XxQ5ATAdSKsqSQgWPsvKInHmrYseWyI7d5Le7U7cIznZa80JQL348X8RNsSL/V8ZFG+oFUBVD3KXjMYkixWPys2XNTwhZFhhmY82T60EQ4Fom//z1LwPQ2d7OqoxMQN+8eTP33Xdfdf7XXw5/k/4g37BZwzaru11Pcp2knfLb94IBlcEclcFc7XHrMBPTixIjLLL2prECOOqoowCoVCrcf//9PPvZz5aHcl3sZr/nFEWZM/ppVFYWjttYs2Pb4g+zEIKkXkQsNSt7yww7t8K6FM+TAZ1Ri7jjTvJHoYuy4wLFxpvM0HjRtmomjNFsMTP0KjKMxu+jL9uqOVSHwulrP7+JG++9m7v/sJVHdj6Jbdt86cP/zMvO2MLH1x/J1q1becHpz+GU0zez66mn+MXtt3LST/+O9rM7DvrU1118Bk997Xae+uadePkyYw89TeCGgsX3GoXqQUiul9qroa2P8zd/8zeceuqpXHbZZQ336e7u5uKLL+baa6/lnHPO4TWveQ1DQ0Ns2rSJK6+8csaPpSjKwqKCR1k5+H5j67lpQm/Xwogd368TDcbSn7xsWY3t4a4ngq3iSBF0JRI6Uwz/jNyQZ12XYkitTqkskbdQiP7kjttIJZL0dHTw+vPO5x/e+Gae+4yTwPW59d+/zIe+9Hnu/MNW/vDQg6xdu5ZnXnoOseN7ZvSI3S9+Js+86k08duWPOfDzP3LUX5+DO1KkuCssXHacxmjTNHRtOYHui5/L6I//zH/8x3/w8pe/fILgAfjKV77CMcccw3e/+12+/e1v093dzQUXXDCzQ6QoyqKg09KVlUEQiNgphuMZDEPETjKxMI9XrsDesKYkZsO63oV5nMUkEnGVSAA5Iow8b8YCYVJKZanfKVdEfE6W5olmdPm+pL9itkSSNq6DtizX8Sf+lV+zhpaDP140cNRxZbuGIULP9WpF0waQSEycjTYJexnjHzmDN3Dy7J63oiiLjk5LV1Y+Y/ma2AHxrFkosQNLO501V0xTurcSk3j9+H4ofvyaCPK8ai1Ow5cfGjIGARAOX43SWwG17yO8MM0UDQmNCqhXdUobPnAcXTMbFup5UrDt1YmbqP4oHqtFmQKkq20G3WoxzPnbCiiKcshRwaMsfxwnHAQa0poVF+WFpF7wrPRuHMNo8CWaMVFUqBB6IeUKElmJXhvPF5HqG+GYjASYFrRmpOW+rlD6BLoxMXDwiDHFfjievBf8oLE42QwLpqOJ99G4Dj8cfBqPTzkHzcHDwOAEumf33BVFWXKo07KyvAkC6B+uLa7xGHQsQnt4qX4e1woXPHMliuTEbBEUphFGfwI5fmN5ET3ppKScEgkpMO9sm9AVliHOKzmOwfHF1BBGa9ya2IlquKLITf2mLLMxIuf54E5WwC0MUuRVHL8wfkqKoiwqKniU5c1Y3YBNw5CJ5wttqOd6teLdaFq4MjVR0bhpSpopV5C6npgtKat4OG19bY8YI07BRTyTAJlNViUgrDUK63+ieqNIMEVptPoaJNtqLGR33MYZayE+AQFwESfO9ZkrirKEUMGjLF98H0ZytZ/bWhannqZU511zKEc2LBci88GoQNgPah1jyYQInY7WgwrVTXRxFhs4QOjHEwRShxPVFnn+xPqg6NvxRdexWOPrVnEn3OcAec5iA8dq/Y6irAj0TK0sX0bztStzK6z9WAyKdYIntYCF0SuJyLwwHpPXKR6DjjZY0z0rkfoBziRFjEJQCYuT/VqBsmk0ihjDoKp4xjeZGUgqMhJHQVjPE94vT4U0MT7IC+f6jBVFWWKo4FGWJ74vM6IixhW5LhhB0BjhWchOsJVEIi7t6OmkDG5duwrasrNOP3aT4SPuCxh2crh+2DbvB6EZ4jg3Z6NO7EzWVm8YMlojIhRPLj4jlPkwW+higYvfFUVZNFTwKMuTfKnWdhyzF74rK6JcaYwqrZSW9IWmo0XSVj2d4o80D6PGcwa7uHzkePoo4AaeRGuiaE79CIiqx07YHj8ZVmM9j1sp0+fnuILNnMsxc95HRVGWHtqWrixP8oXa99nM4kz+Bim4jUgnF+9xlzuWJVG4JmBYFpePPgOCgKtbttHu2KSjRqvIaBAaX5tI80z2csVs8HzyOIyYZa4YOZnL2k+bslVdUZTliUZ4lOWH49allQzIphbncX1fIksRixVVUhrpbMPoaudy51lcOfI8vJjJ/ngFH79mklhPNZ01eZTHN2B/ooJvBFw59FwuH9mEUV8MryjKikAjPMryozSuaHi2hnhzpVCCIEqjxTSddagwDGjNYrRkOLfczrPz6/mM/RvuiO3GCKDTiRELggmT0RuiP4ip4CBFAuAscyMfrJxKVym0GxjJQSa99GekKYoyY/TTrCw/ynWmf4tVNBwE4vkTkU1pOutQYxiQTNCdXMtnnVez4+mH+H7yMW5sfZrANHHwifuQCCwMwycIoIxPBY8YJgYGr+UZXMiJMjqiJYBcv7S6BwEMjki9kaIoKwIVPMryo1w31mGxXI5LlUaDw4yms5YUrssmo4sPlDp5T+U0trUW2eH2sTXWz34zT5mARJCilzY2s4ZNdHEC3Y0OyoYBXW2wtx8IZOxFoSS1WoqiLHtU8CjLi2iqdsRipJWCAIbHaj9n041Ovcqhp1QTo5lsG5s7NrDZO4435AsiWmIxyLRy0ErkRFxe31wYzRscEfdnNZdUlGWPCh5leRHUtRgbxuIsRKUKlMu1x2zLLvxjKrNjMm8ky5RBsq2zfL06WqBQDCfEu2Jw2aQOM0VRDh162aIsLyYzllvox6ufxJ5Ji4GesnQIgsY05zTzuGaEZTUOoB3NiSmhoijLGhU8yjJjvLfKFIZyzWI0L0WsoNGdpYrjUo362XZzuvayaUmDwURXb0VRliUqeJTlhWmAEb5tA3+i50ozcVwYrovutLVom/JSpFIX3WnW6zNe3I7lF/a9pijKgqOCR1leGEZjwXB9AXMzCQIYGK5FkOIxje4sVRaqiD2Tqgko35don6IoyxYVPMryI1FXo1EoTX2/uRIEMDDS6Obc1a6+O0sVZwEiPBBGeeqKlUdzGuVRlGWMCh5l+VHvi5IvNr+OZyxfa0sG6dpJzLMQVlk4KgtoU5BJ1YrUfV/eb4qiLEtU8CjLj/pxEp7X3FTDaE68VyKy6dm3NSuLx/gREs2usTIMaMnUfq4fHqsoyrJCBY+y/BhfUDoy1li4Ohei9vN6sZOIayprqeP7VDu0THNhXqv6MSLlyvzfa4qiHBJU8CjLk5ZMY0Fp36CYxM0F15O/H6lzU04kYFWXip2lTr0/jrVApzPLglRdGlWjPIqyLFHBoyxPDAN6Omst6q4Lew7I/KOZEvmr7Olr/LtUEno7F24BVZpHfRGxuYDjPrJ1s9MWom5MUZQFR01FlOVLPAY9HRKdIZDFb/+ACJbWjIwYGB+hCQJJSRRLMFaQGqAqhvxdR6tGdpYLixHhgVrdmOfJV8XRQnZFWWao4FGWN+kkrO6CA0M18VIsyZdhiCiyTMCQ2x138tZi24bu9tocJmV50BDhWUCRahjy3siH6axSWQWPoiwzVPAoy59kAtb0iCtyrki1iDUIpMh0OmxLurCyaZ2IvSxZxEhcqk7wFMuNHj2Koix5VPAoKwPbgu4O6d4aK8iC5EzRTWNZIpLSSfnS9NXyZTFfuvroX7ki0SUVyYqybFDBo6wsYjHobJPvXU++olSXZYrYsS0VOSuRha4jti3pDHRciR46rqa1FGUZoYJHWbnYVuPcLWXl0SBcF6FzKhI8oIJHUZYZGo9VFGX5Ui94vEWYc2XXXSPO1fdJUZRDggoeRVGWL/URvPoREwtFrG5Wl6OCR1GWEyp4FEVZvtQLHs9beENAu+6U6av5oKIsJ1TwKIqyfDHNWqdUECxCWqsuhaZuy4qyrFDBoyjK8qZ+QvpCD/ZsqJFWwaMoywkVPIqiLG/qO6VK5UO3H4qiLGlU8CiKsrwZbwi4kDTM7lLLA0VZTqjgURRleZOIU801lZ1xA2GbTH0nmAoeRVlWqOBRFGV5Y5mQiNrFg3Ce2gJR34quppaKsqxQwaMoyvInm659nyssTEFxEDTWCCViU99XUZQlhwoeRVGWP5kUGOHpzHEWpnjZ9WruyoapYyUUZZmhgkdRlOWPaUI2Vft5aLT5UZ5cofZ9Kq4DaBVlmaGCR1GUlUFbSy3KU3EaBcp88X0Yy9d+zqSnvq+iKEsSFTyKoqwMbAvasrWfB0eaZ0Q4PCaiB2SeVjrZnO0qirJoqOBRFGXl0JqpOS8HAfQNzr9NvViG0Vzt57asprMUZRmigkdRlJWDaUJPZy215bqwb6BWbDxbyhU4MFj7OZWUAmlFUZYdKngURVlZxGPQ3U7VjNBxYG8/FEuz206hBPsHaqks05TtanRHUZYl9sHvoiiKssyIojD9Q+EUdU/ESzolKal4bGrhUnFgZAzydQaGpgm9XequrCjLGBU8iqKsTDIpESoHBmtRmkJRvmIxSMZrwicIxEW5XJk4j8uyROzE1WhQUZYzKngURVm5pBKwbpX48tS3qTuOfB2MbBo62mR8haIoyxoVPIqirGwsC7o7oCUjXjr54kFMCQ3IJOX+9ZPYFUVZ1qjgURTl8CARl6/ONihVwihPXfeWZYX3iWmtjqKsQFTwKIpyeGGaoXGgmgcqyuGEJqYVRVEURVnxqOBRFEVRFGXFo4JHURRFUZQVjwoeRVEURVFWPCp4FEVRFEVZ8ajgURRFURRlxaOCR1EURVGUFY8KHkVRFEVRVjwqeBRFURRFWfGo4FEURVEUZcWjgkdRFEVRlBWPCh5FURRFUVY8KngURVEURVnxqOBRFEVRFGXFo4JHURRFUZQVjwoeRVEURVFWPCp4FEVRFEVZ8ajgURRFURRlxaOCR1EURVGUFY8KHkVRFEVRVjwqeBRFURRFWfGo4FEURVEUZcWjgkdRFEVRlBWPCh5FURRFUVY8KngURVEURVnxqOBRFEVRFGXFo4JHURRFUZQVjwoeRVEURVFWPCp4FEVRFEVZ8ajgURRFURRlxaOCR1EURVGUFY8KHkVRFEVRVjwqeBRFURRFWfGo4FEURVEUZcWjgkdRFEVRlBWPCh5FURRFUVY8KngURVEURVnxqOBRFEVRFGXFo4JHURRFUZQVjwoeRVEURVFWPCp4FEVRFEVZ8ajgURRFURRlxaOCR1EURVGUFY8KHkVRFEVRVjwqeBRFURRFWfGo4FEURVEUZcWjgkdRFEVRlBWPCh5FURRFUVY8KngURVEURVnxqOBRFEVRFGXFo4JHURRFUZQVjwoeRVEURVFWPCp4FEVRFEVZ8ajgURRFURRlxaOCR1EURVGUFY8KHkVRFEVRVjwqeBRFURRFWfGo4FEURVEUZcWjgkdRFEVRlBWPCh5FURRFUVY8KngURVEURVnxqOBRFEVRFGXFo4JHURRFUZQVjwoeRVEURVFWPCp4FEVRFEVZ8ajgURRFURRlxaOCR1EURVGUFY8KHkVRFEVRVjxGEART32gYB4Cdi7c7iqIoiqIoc2ZDEAQ9k90wreBRFEVRFEVZCWhKS1EURVGUFY8KHkVRFEVRVjwqeBRFURRFWfGo4FEURVEUZcWjgkdRFEVRlBXP/x+XfT7sJVRqVgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cpdb_launcher.visualise_interactions()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "relative-binding",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Interactions counts'}>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cpdb_launcher.dotplot_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "contemporary-toner",
   "metadata": {},
   "source": [
    "# Running CellChat "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "grateful-luxembourg",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "R[write to console]: Loading required package: dplyr\n",
      "\n",
      "R[write to console]: \n",
      "Attaching package: ‘dplyr’\n",
      "\n",
      "\n",
      "R[write to console]: The following objects are masked from ‘package:stats’:\n",
      "\n",
      "    filter, lag\n",
      "\n",
      "\n",
      "R[write to console]: The following objects are masked from ‘package:base’:\n",
      "\n",
      "    intersect, setdiff, setequal, union\n",
      "\n",
      "\n",
      "R[write to console]: Loading required package: igraph\n",
      "\n",
      "R[write to console]: \n",
      "Attaching package: ‘igraph’\n",
      "\n",
      "\n",
      "R[write to console]: The following objects are masked from ‘package:dplyr’:\n",
      "\n",
      "    as_data_frame, groups, union\n",
      "\n",
      "\n",
      "R[write to console]: The following objects are masked from ‘package:stats’:\n",
      "\n",
      "    decompose, spectrum\n",
      "\n",
      "\n",
      "R[write to console]: The following object is masked from ‘package:base’:\n",
      "\n",
      "    union\n",
      "\n",
      "\n",
      "R[write to console]: Loading required package: ggplot2\n",
      "\n",
      "R[write to console]: Registered S3 methods overwritten by 'ggplot2':\n",
      "  method         from \n",
      "  [.quosures     rlang\n",
      "  c.quosures     rlang\n",
      "  print.quosures rlang\n",
      "\n"
     ]
    }
   ],
   "source": [
    "cellchat_launcher = CellChatLauncher(counts_file_path=counts_path, meta_file_path=meta_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "devoted-recall",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "R[write to console]: Create a CellChat object from a data matrix\n",
      "\n",
      "R[write to console]: Set cell identities for the new CellChat object\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The cell groups used for CellChat analysis are  B CD14 Monocytes CD4 T CD8 T Dendritic FCGR3A Monocytes Megakaryocytes NK RPS expressing \n",
      "  |                                                  | 0 % ~calculating   |+++                                               | 4 % ~00s           |+++++                                             | 8 % ~00s           |+++++++                                           | 12% ~00s           |+++++++++                                         | 17% ~00s           |+++++++++++                                       | 21% ~00s           |+++++++++++++                                     | 25% ~00s           |+++++++++++++++                                   | 29% ~00s           |+++++++++++++++++                                 | 33% ~00s           |+++++++++++++++++++                               | 38% ~00s           |+++++++++++++++++++++                             | 42% ~00s           |+++++++++++++++++++++++                           | 46% ~00s           |+++++++++++++++++++++++++                         | 50% ~00s           |++++++++++++++++++++++++++++                      | 54% ~00s           |++++++++++++++++++++++++++++++                    | 58% ~00s           |++++++++++++++++++++++++++++++++                  | 62% ~00s           |++++++++++++++++++++++++++++++++++                | 67% ~00s           |++++++++++++++++++++++++++++++++++++              | 71% ~00s           |++++++++++++++++++++++++++++++++++++++            | 75% ~00s           |++++++++++++++++++++++++++++++++++++++++          | 79% ~00s           |++++++++++++++++++++++++++++++++++++++++++        | 83% ~00s           |++++++++++++++++++++++++++++++++++++++++++++      | 88% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++    | 92% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++++  | 96% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  \n",
      "  |                                                  | 0 % ~calculating   |++                                                | 3 % ~00s           |++++                                              | 6 % ~00s           |+++++                                             | 9 % ~00s           |+++++++                                           | 12% ~00s           |++++++++                                          | 16% ~00s           |++++++++++                                        | 19% ~00s           |+++++++++++                                       | 22% ~00s           |+++++++++++++                                     | 25% ~00s           |+++++++++++++++                                   | 28% ~00s           |++++++++++++++++                                  | 31% ~00s           |++++++++++++++++++                                | 34% ~00s           |+++++++++++++++++++                               | 38% ~00s           |+++++++++++++++++++++                             | 41% ~00s           |++++++++++++++++++++++                            | 44% ~00s           |++++++++++++++++++++++++                          | 47% ~00s           |+++++++++++++++++++++++++                         | 50% ~00s           |+++++++++++++++++++++++++++                       | 53% ~00s           |+++++++++++++++++++++++++++++                     | 56% ~00s           |++++++++++++++++++++++++++++++                    | 59% ~00s           |++++++++++++++++++++++++++++++++                  | 62% ~00s           |+++++++++++++++++++++++++++++++++                 | 66% ~00s           |+++++++++++++++++++++++++++++++++++               | 69% ~00s           |++++++++++++++++++++++++++++++++++++              | 72% ~00s           |++++++++++++++++++++++++++++++++++++++            | 75% ~00s           |++++++++++++++++++++++++++++++++++++++++          | 78% ~00s           |+++++++++++++++++++++++++++++++++++++++++         | 81% ~00s           |+++++++++++++++++++++++++++++++++++++++++++       | 84% ~00s           |++++++++++++++++++++++++++++++++++++++++++++      | 88% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++    | 91% ~00s           |+++++++++++++++++++++++++++++++++++++++++++++++   | 94% ~00s           |+++++++++++++++++++++++++++++++++++++++++++++++++ | 97% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  \n",
      "  |                                                  | 0 % ~calculating   |+++                                               | 4 % ~00s           |+++++                                             | 9 % ~00s           |+++++++                                           | 13% ~00s           |+++++++++                                         | 17% ~00s           |+++++++++++                                       | 22% ~00s           |++++++++++++++                                    | 26% ~00s           |++++++++++++++++                                  | 30% ~00s           |++++++++++++++++++                                | 35% ~00s           |++++++++++++++++++++                              | 39% ~00s           |++++++++++++++++++++++                            | 43% ~00s           |++++++++++++++++++++++++                          | 48% ~00s           |+++++++++++++++++++++++++++                       | 52% ~00s           |+++++++++++++++++++++++++++++                     | 57% ~00s           |+++++++++++++++++++++++++++++++                   | 61% ~00s           |+++++++++++++++++++++++++++++++++                 | 65% ~00s           |+++++++++++++++++++++++++++++++++++               | 70% ~00s           |+++++++++++++++++++++++++++++++++++++             | 74% ~00s           |++++++++++++++++++++++++++++++++++++++++          | 78% ~00s           |++++++++++++++++++++++++++++++++++++++++++        | 83% ~00s           |++++++++++++++++++++++++++++++++++++++++++++      | 87% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++    | 91% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++++  | 96% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  \n",
      "  |                                                  | 0 % ~calculating   |++                                                | 4 % ~00s           |++++                                              | 7 % ~00s           |++++++                                            | 11% ~00s           |++++++++                                          | 14% ~00s           |+++++++++                                         | 18% ~00s           |+++++++++++                                       | 21% ~00s           |+++++++++++++                                     | 25% ~00s           |+++++++++++++++                                   | 29% ~00s           |+++++++++++++++++                                 | 32% ~00s           |++++++++++++++++++                                | 36% ~00s           |++++++++++++++++++++                              | 39% ~00s           |++++++++++++++++++++++                            | 43% ~00s           |++++++++++++++++++++++++                          | 46% ~00s           |+++++++++++++++++++++++++                         | 50% ~00s           |+++++++++++++++++++++++++++                       | 54% ~00s           |+++++++++++++++++++++++++++++                     | 57% ~00s           |+++++++++++++++++++++++++++++++                   | 61% ~00s           |+++++++++++++++++++++++++++++++++                 | 64% ~00s           |++++++++++++++++++++++++++++++++++                | 68% ~00s           |++++++++++++++++++++++++++++++++++++              | 71% ~00s           |++++++++++++++++++++++++++++++++++++++            | 75% ~00s           |++++++++++++++++++++++++++++++++++++++++          | 79% ~00s           |++++++++++++++++++++++++++++++++++++++++++        | 82% ~00s           |+++++++++++++++++++++++++++++++++++++++++++       | 86% ~00s           |+++++++++++++++++++++++++++++++++++++++++++++     | 89% ~00s           |+++++++++++++++++++++++++++++++++++++++++++++++   | 93% ~00s           |+++++++++++++++++++++++++++++++++++++++++++++++++ | 96% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  |                                                  | 0 % ~calculating   |++                                                | 4 % ~00s           |++++                                              | 7 % ~00s           |++++++                                            | 11% ~00s           |++++++++                                          | 14% ~00s           |+++++++++                                         | 18% ~00s           |+++++++++++                                       | 21% ~00s           |+++++++++++++                                     | 25% ~00s           |+++++++++++++++                                   | 29% ~00s           |+++++++++++++++++                                 | 32% ~00s           |++++++++++++++++++                                | 36% ~00s           |++++++++++++++++++++                              | 39% ~00s           |++++++++++++++++++++++                            | 43% ~00s           |++++++++++++++++++++++++                          | 46% ~00s           |+++++++++++++++++++++++++                         | 50% ~00s           |+++++++++++++++++++++++++++                       | 54% ~00s           |+++++++++++++++++++++++++++++                     | 57% ~00s           |+++++++++++++++++++++++++++++++                   | 61% ~00s           |+++++++++++++++++++++++++++++++++                 | 64% ~00s           |++++++++++++++++++++++++++++++++++                | 68% ~00s           |++++++++++++++++++++++++++++++++++++              | 71% ~00s           |++++++++++++++++++++++++++++++++++++++            | 75% ~00s           |++++++++++++++++++++++++++++++++++++++++          | 79% ~00s           |++++++++++++++++++++++++++++++++++++++++++        | 82% ~00s           |+++++++++++++++++++++++++++++++++++++++++++       | 86% ~00s           |+++++++++++++++++++++++++++++++++++++++++++++     | 89% ~00s           |+++++++++++++++++++++++++++++++++++++++++++++++   | 93% ~00s           |+++++++++++++++++++++++++++++++++++++++++++++++++ | 96% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  \n",
      "  |                                                  | 0 % ~calculating   |+++                                               | 4 % ~00s           |+++++                                             | 8 % ~00s           |+++++++                                           | 12% ~00s           |+++++++++                                         | 17% ~00s           |+++++++++++                                       | 21% ~00s           |+++++++++++++                                     | 25% ~00s           |+++++++++++++++                                   | 29% ~00s           |+++++++++++++++++                                 | 33% ~00s           |+++++++++++++++++++                               | 38% ~00s           |+++++++++++++++++++++                             | 42% ~00s           |+++++++++++++++++++++++                           | 46% ~00s           |+++++++++++++++++++++++++                         | 50% ~00s           |++++++++++++++++++++++++++++                      | 54% ~00s           |++++++++++++++++++++++++++++++                    | 58% ~00s           |++++++++++++++++++++++++++++++++                  | 62% ~00s           |++++++++++++++++++++++++++++++++++                | 67% ~00s           |++++++++++++++++++++++++++++++++++++              | 71% ~00s           |++++++++++++++++++++++++++++++++++++++            | 75% ~00s           |++++++++++++++++++++++++++++++++++++++++          | 79% ~00s           |++++++++++++++++++++++++++++++++++++++++++        | 83% ~00s           |++++++++++++++++++++++++++++++++++++++++++++      | 88% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++    | 92% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++++  | 96% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  \n",
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      "  |                                                  | 0 % ~calculating   |++                                                | 3 % ~00s           |+++                                               | 5 % ~00s           |+++++                                             | 8 % ~00s           |++++++                                            | 11% ~00s           |+++++++                                           | 14% ~00s           |+++++++++                                         | 16% ~00s           |++++++++++                                        | 19% ~00s           |+++++++++++                                       | 22% ~00s           |+++++++++++++                                     | 24% ~00s           |++++++++++++++                                    | 27% ~00s           |+++++++++++++++                                   | 30% ~00s           |+++++++++++++++++                                 | 32% ~00s           |++++++++++++++++++                                | 35% ~00s           |+++++++++++++++++++                               | 38% ~00s           |+++++++++++++++++++++                             | 41% ~00s           |++++++++++++++++++++++                            | 43% ~00s           |+++++++++++++++++++++++                           | 46% ~00s           |+++++++++++++++++++++++++                         | 49% ~00s           |++++++++++++++++++++++++++                        | 51% ~00s           |++++++++++++++++++++++++++++                      | 54% ~00s           |+++++++++++++++++++++++++++++                     | 57% ~00s           |++++++++++++++++++++++++++++++                    | 59% ~00s           |++++++++++++++++++++++++++++++++                  | 62% ~00s           |+++++++++++++++++++++++++++++++++                 | 65% ~00s           |++++++++++++++++++++++++++++++++++                | 68% ~00s           |++++++++++++++++++++++++++++++++++++              | 70% ~00s           |+++++++++++++++++++++++++++++++++++++             | 73% ~00s           |++++++++++++++++++++++++++++++++++++++            | 76% ~00s           |++++++++++++++++++++++++++++++++++++++++          | 78% ~00s           |+++++++++++++++++++++++++++++++++++++++++         | 81% ~00s           |++++++++++++++++++++++++++++++++++++++++++        | 84% ~00s           |++++++++++++++++++++++++++++++++++++++++++++      | 86% ~00s           |+++++++++++++++++++++++++++++++++++++++++++++     | 89% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++    | 92% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++++  | 95% ~00s           |+++++++++++++++++++++++++++++++++++++++++++++++++ | 97% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  |                                                  | 0 % ~calculating   |++++                                              | 7 % ~00s           |++++++++                                          | 14% ~00s           |+++++++++++                                       | 21% ~00s           |+++++++++++++++                                   | 29% ~00s           |++++++++++++++++++                                | 36% ~00s           |++++++++++++++++++++++                            | 43% ~00s           |+++++++++++++++++++++++++                         | 50% ~00s           |+++++++++++++++++++++++++++++                     | 57% ~00s           |+++++++++++++++++++++++++++++++++                 | 64% ~00s           |++++++++++++++++++++++++++++++++++++              | 71% ~00s           |++++++++++++++++++++++++++++++++++++++++          | 79% ~00s           |+++++++++++++++++++++++++++++++++++++++++++       | 86% ~00s           |+++++++++++++++++++++++++++++++++++++++++++++++   | 93% ~00s           |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  \n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  |                                                  | 0 % ~calculating   |+                                                 | 1 % ~01s           |++                                                | 2 % ~01s           |++                                                | 3 % ~01s           |+++                                               | 4 % ~01s           |+++                                               | 5 % ~01s           |++++                                              | 6 % ~01s           |++++                                              | 7 % ~01s           |+++++                                             | 8 % ~01s           |+++++                                             | 9 % ~01s           |++++++                                            | 10% ~00s           |++++++                                            | 11% ~00s           |+++++++                                           | 12% ~00s           |+++++++                                           | 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~00s           |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  |                                                                            \n",
      "  |                                                                      |   0%\n",
      "  |                                                                            \n",
      "  |=====                                                                 |   7%\n",
      "  |                                                                            \n",
      "  |=========                                                             |  13%\n",
      "  |                                                                            \n",
      "  |==============                                                        |  20%\n",
      "  |                                                                            \n",
      "  |===================                                                   |  27%\n",
      "  |                                                                            \n",
      "  |=======================                                               |  33%\n",
      "  |                                                                            \n",
      "  |============================                                          |  40%\n",
      "  |                                                                            \n",
      "  |=================================                                     |  47%\n",
      "  |                                                                            \n",
      "  |=====================================                                 |  53%\n",
      "  |                                                                            \n",
      "  |==========================================                            |  60%\n",
      "  |                                                                            \n",
      "  |===============================================                       |  67%\n",
      "  |                                                                            \n",
      "  |===================================================                   |  73%\n",
      "  |                                                                            \n",
      "  |========================================================              |  80%\n",
      "  |                                                                            \n",
      "  |=============================================================         |  87%\n",
      "  |                                                                            \n",
      "  |=================================================================     |  93%\n",
      "  |                                                                            \n",
      "  |======================================================================| 100%\n",
      "R[write to console]: \n",
      "\n"
     ]
    }
   ],
   "source": [
    "cellchat_launcher.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "computational-familiar",
   "metadata": {},
   "outputs": [],
   "source": [
    "cellchat_launcher.read_output()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "current-porcelain",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015651</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NK</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.014414</td>\n",
       "      <td>0.019459</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RPS expressing</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013504</td>\n",
       "      <td>0.018237</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       "B                 0.0             0.0    0.0    0.0   0.013831   \n",
       "CD14 Monocytes    0.0             0.0    0.0    0.0   0.000000   \n",
       "CD4 T             0.0             0.0    0.0    0.0   0.012438   \n",
       "CD8 T             0.0             0.0    0.0    0.0   0.000000   \n",
       "Dendritic         0.0             0.0    0.0    0.0   0.010088   \n",
       "FCGR3A Monocytes  0.0             0.0    0.0    0.0   0.000000   \n",
       "Megakaryocytes    0.0             0.0    0.0    0.0   0.000000   \n",
       "NK                0.0             0.0    0.0    0.0   0.014414   \n",
       "RPS expressing    0.0             0.0    0.0    0.0   0.013504   \n",
       "\n",
       "                  FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       "B                         0.018676        0.000000  0.0             0.0  \n",
       "CD14 Monocytes            0.004972        0.000000  0.0             0.0  \n",
       "CD4 T                     0.016804        0.000000  0.0             0.0  \n",
       "CD8 T                     0.005722        0.000000  0.0             0.0  \n",
       "Dendritic                 0.013641        0.000000  0.0             0.0  \n",
       "FCGR3A Monocytes          0.003751        0.000000  0.0             0.0  \n",
       "Megakaryocytes            0.000000        0.015651  0.0             0.0  \n",
       "NK                        0.019459        0.000000  0.0             0.0  \n",
       "RPS expressing            0.018237        0.000000  0.0             0.0  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cellchat_launcher.weights_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adapted-american",
   "metadata": {},
   "source": [
    "CellChat has a different output format. Instead of one big table it has a separate table for each interation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "suffering-grounds",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>B</th>\n",
       "      <th>CD14 Monocytes</th>\n",
       "      <th>CD4 T</th>\n",
       "      <th>CD8 T</th>\n",
       "      <th>Dendritic</th>\n",
       "      <th>FCGR3A Monocytes</th>\n",
       "      <th>Megakaryocytes</th>\n",
       "      <th>NK</th>\n",
       "      <th>RPS expressing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013831</td>\n",
       "      <td>0.018676</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD14 Monocytes</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004972</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD4 T</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.012438</td>\n",
       "      <td>0.016804</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 T</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005722</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dendritic</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.010088</td>\n",
       "      <td>0.013641</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FCGR3A Monocytes</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003751</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Megakaryocytes</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015651</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NK</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.014414</td>\n",
       "      <td>0.019459</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RPS expressing</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013504</td>\n",
       "      <td>0.018237</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       "B                 0.0             0.0    0.0    0.0   0.013831   \n",
       "CD14 Monocytes    0.0             0.0    0.0    0.0   0.000000   \n",
       "CD4 T             0.0             0.0    0.0    0.0   0.012438   \n",
       "CD8 T             0.0             0.0    0.0    0.0   0.000000   \n",
       "Dendritic         0.0             0.0    0.0    0.0   0.010088   \n",
       "FCGR3A Monocytes  0.0             0.0    0.0    0.0   0.000000   \n",
       "Megakaryocytes    0.0             0.0    0.0    0.0   0.000000   \n",
       "NK                0.0             0.0    0.0    0.0   0.014414   \n",
       "RPS expressing    0.0             0.0    0.0    0.0   0.013504   \n",
       "\n",
       "                  FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       "B                         0.018676        0.000000  0.0             0.0  \n",
       "CD14 Monocytes            0.004972        0.000000  0.0             0.0  \n",
       "CD4 T                     0.016804        0.000000  0.0             0.0  \n",
       "CD8 T                     0.005722        0.000000  0.0             0.0  \n",
       "Dendritic                 0.013641        0.000000  0.0             0.0  \n",
       "FCGR3A Monocytes          0.003751        0.000000  0.0             0.0  \n",
       "Megakaryocytes            0.000000        0.015651  0.0             0.0  \n",
       "NK                        0.019459        0.000000  0.0             0.0  \n",
       "RPS expressing            0.018237        0.000000  0.0             0.0  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cellchat_launcher.weights_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "advised-output",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'CXCL2_CXCR1':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0        1.0   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " CD4 T             1.0             1.0    1.0    1.0        1.0   \n",
       " CD8 T             1.0             1.0    1.0    1.0        1.0   \n",
       " Dendritic         1.0             1.0    1.0    1.0        1.0   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0    1.0        1.0   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " NK                1.0             1.0    1.0    1.0        1.0   \n",
       " RPS expressing    1.0             1.0    1.0    1.0        1.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              1.0             1.0  1.0             1.0  \n",
       " CD14 Monocytes                 1.0             1.0  1.0             1.0  \n",
       " CD4 T                          1.0             1.0  1.0             1.0  \n",
       " CD8 T                          1.0             1.0  1.0             1.0  \n",
       " Dendritic                      1.0             1.0  1.0             1.0  \n",
       " FCGR3A Monocytes               1.0             1.0  1.0             1.0  \n",
       " Megakaryocytes                 1.0             1.0  1.0             1.0  \n",
       " NK                             1.0             1.0  1.0             1.0  \n",
       " RPS expressing                 1.0             1.0  1.0             1.0  ,\n",
       " 'CXCL3_CXCR1':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0        1.0   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " CD4 T             1.0             1.0    1.0    1.0        1.0   \n",
       " CD8 T             1.0             1.0    1.0    1.0        1.0   \n",
       " Dendritic         1.0             1.0    1.0    1.0        1.0   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0    1.0        1.0   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " NK                1.0             1.0    1.0    1.0        1.0   \n",
       " RPS expressing    1.0             1.0    1.0    1.0        1.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              1.0             1.0  1.0            1.00  \n",
       " CD14 Monocytes                 1.0             1.0  1.0            1.00  \n",
       " CD4 T                          1.0             1.0  1.0            1.00  \n",
       " CD8 T                          1.0             1.0  1.0            1.00  \n",
       " Dendritic                      1.0             1.0  1.0            1.00  \n",
       " FCGR3A Monocytes               1.0             1.0  1.0            1.00  \n",
       " Megakaryocytes                 1.0             1.0  1.0            1.00  \n",
       " NK                             1.0             1.0  1.0            1.00  \n",
       " RPS expressing                 0.0             1.0  1.0            0.01  ,\n",
       " 'TNFSF13B_TNFRSF17':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0        1.0   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " CD4 T             1.0             1.0    1.0    1.0        1.0   \n",
       " CD8 T             1.0             1.0    1.0    1.0        1.0   \n",
       " Dendritic         1.0             1.0    1.0    1.0        1.0   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0    1.0        1.0   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " NK                1.0             1.0    1.0    1.0        1.0   \n",
       " RPS expressing    1.0             1.0    1.0    1.0        1.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              1.0             1.0  1.0             1.0  \n",
       " CD14 Monocytes                 1.0             1.0  1.0             1.0  \n",
       " CD4 T                          1.0             1.0  1.0             1.0  \n",
       " CD8 T                          1.0             1.0  1.0             1.0  \n",
       " Dendritic                      1.0             1.0  1.0             1.0  \n",
       " FCGR3A Monocytes               1.0             1.0  1.0             1.0  \n",
       " Megakaryocytes                 1.0             1.0  1.0             1.0  \n",
       " NK                             1.0             1.0  1.0             1.0  \n",
       " RPS expressing                 0.0             1.0  1.0             0.0  ,\n",
       " 'TNFSF13B_TNFRSF13C':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0        1.0   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " CD4 T             1.0             1.0    1.0    1.0        1.0   \n",
       " CD8 T             1.0             1.0    1.0    1.0        1.0   \n",
       " Dendritic         1.0             1.0    1.0    1.0        1.0   \n",
       " FCGR3A Monocytes  1.0             1.0    0.0    1.0        1.0   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " NK                1.0             1.0    1.0    1.0        1.0   \n",
       " RPS expressing    1.0             1.0    1.0    1.0        1.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              1.0             1.0  1.0             1.0  \n",
       " CD14 Monocytes                 1.0             1.0  1.0             1.0  \n",
       " CD4 T                          1.0             1.0  1.0             1.0  \n",
       " CD8 T                          1.0             1.0  1.0             1.0  \n",
       " Dendritic                      1.0             1.0  1.0             1.0  \n",
       " FCGR3A Monocytes               1.0             1.0  1.0             1.0  \n",
       " Megakaryocytes                 1.0             1.0  1.0             1.0  \n",
       " NK                             1.0             1.0  1.0             1.0  \n",
       " RPS expressing                 1.0             1.0  1.0             1.0  ,\n",
       " 'GZMA_F2R':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0        1.0   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " CD4 T             1.0             1.0    1.0    1.0        1.0   \n",
       " CD8 T             1.0             1.0    1.0    1.0        1.0   \n",
       " Dendritic         1.0             1.0    1.0    1.0        1.0   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0    1.0        1.0   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " NK                1.0             1.0    1.0    1.0        1.0   \n",
       " RPS expressing    1.0             1.0    1.0    1.0        1.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              1.0            1.00  1.0             1.0  \n",
       " CD14 Monocytes                 1.0            1.00  1.0             1.0  \n",
       " CD4 T                          1.0            1.00  1.0             1.0  \n",
       " CD8 T                          1.0            1.00  1.0             1.0  \n",
       " Dendritic                      1.0            1.00  1.0             1.0  \n",
       " FCGR3A Monocytes               1.0            1.00  1.0             1.0  \n",
       " Megakaryocytes                 1.0            1.00  1.0             1.0  \n",
       " NK                             1.0            1.00  1.0             1.0  \n",
       " RPS expressing                 1.0            0.03  1.0             1.0  ,\n",
       " 'THBS1_CD47':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0        1.0   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " CD4 T             1.0             1.0    1.0    1.0        1.0   \n",
       " CD8 T             1.0             1.0    1.0    1.0        1.0   \n",
       " Dendritic         1.0             1.0    1.0    1.0        1.0   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0    1.0        1.0   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " NK                1.0             1.0    1.0    1.0        1.0   \n",
       " RPS expressing    1.0             1.0    1.0    1.0        1.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              1.0             1.0  1.0             1.0  \n",
       " CD14 Monocytes                 1.0             1.0  1.0             1.0  \n",
       " CD4 T                          1.0             1.0  1.0             1.0  \n",
       " CD8 T                          1.0             1.0  1.0             1.0  \n",
       " Dendritic                      1.0             1.0  1.0             1.0  \n",
       " FCGR3A Monocytes               1.0             1.0  1.0             1.0  \n",
       " Megakaryocytes                 1.0             1.0  1.0             1.0  \n",
       " NK                             1.0             1.0  1.0             1.0  \n",
       " RPS expressing                 1.0             0.0  1.0             1.0  ,\n",
       " 'CLEC2B_KLRB1':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0        1.0   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " CD4 T             1.0             1.0    1.0    1.0        1.0   \n",
       " CD8 T             1.0             1.0    1.0    1.0        1.0   \n",
       " Dendritic         1.0             1.0    1.0    1.0        1.0   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0    1.0        1.0   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " NK                1.0             1.0    1.0    1.0        1.0   \n",
       " RPS expressing    1.0             1.0    1.0    1.0        1.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              1.0             1.0  1.0             1.0  \n",
       " CD14 Monocytes                 1.0             1.0  1.0             1.0  \n",
       " CD4 T                          1.0             1.0  1.0             1.0  \n",
       " CD8 T                          1.0             1.0  1.0             1.0  \n",
       " Dendritic                      1.0             1.0  1.0             1.0  \n",
       " FCGR3A Monocytes               1.0             1.0  1.0             1.0  \n",
       " Megakaryocytes                 1.0             1.0  1.0             1.0  \n",
       " NK                             1.0             1.0  1.0             1.0  \n",
       " RPS expressing                 1.0             1.0  1.0             1.0  ,\n",
       " 'CLEC1B_KLRB1':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0       1.00   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0       1.00   \n",
       " CD4 T             1.0             1.0    1.0    1.0       1.00   \n",
       " CD8 T             1.0             1.0    1.0    1.0       1.00   \n",
       " Dendritic         1.0             1.0    1.0    1.0       1.00   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0    1.0       1.00   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0       1.00   \n",
       " NK                1.0             1.0    1.0    1.0       1.00   \n",
       " RPS expressing    1.0             1.0    1.0    1.0       0.08   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              1.0             1.0  1.0             1.0  \n",
       " CD14 Monocytes                 1.0             1.0  1.0             1.0  \n",
       " CD4 T                          1.0             1.0  1.0             1.0  \n",
       " CD8 T                          1.0             1.0  1.0             1.0  \n",
       " Dendritic                      1.0             1.0  1.0             1.0  \n",
       " FCGR3A Monocytes               1.0             1.0  1.0             1.0  \n",
       " Megakaryocytes                 1.0             1.0  1.0             1.0  \n",
       " NK                             1.0             1.0  1.0             1.0  \n",
       " RPS expressing                 1.0             1.0  1.0             1.0  ,\n",
       " 'ESAM_ESAM':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0       1.00   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0       1.00   \n",
       " CD4 T             1.0             1.0    1.0    1.0       1.00   \n",
       " CD8 T             1.0             1.0    1.0    1.0       1.00   \n",
       " Dendritic         1.0             1.0    1.0    1.0       1.00   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0    1.0       1.00   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0       1.00   \n",
       " NK                1.0             1.0    1.0    1.0       1.00   \n",
       " RPS expressing    1.0             1.0    1.0    1.0       0.01   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              1.0             1.0  1.0             1.0  \n",
       " CD14 Monocytes                 1.0             1.0  1.0             1.0  \n",
       " CD4 T                          1.0             1.0  1.0             1.0  \n",
       " CD8 T                          1.0             1.0  1.0             1.0  \n",
       " Dendritic                      1.0             1.0  1.0             1.0  \n",
       " FCGR3A Monocytes               1.0             1.0  1.0             1.0  \n",
       " Megakaryocytes                 1.0             1.0  1.0             1.0  \n",
       " NK                             1.0             1.0  1.0             1.0  \n",
       " RPS expressing                 1.0             1.0  1.0             1.0  ,\n",
       " 'ICOSL_ICOS':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0        1.0   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " CD4 T             1.0             1.0    1.0    1.0        1.0   \n",
       " CD8 T             1.0             1.0    1.0    1.0        1.0   \n",
       " Dendritic         1.0             1.0    1.0    1.0        1.0   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0    1.0        1.0   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " NK                1.0             1.0    1.0    1.0        1.0   \n",
       " RPS expressing    1.0             1.0    1.0    1.0        1.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              1.0             1.0  1.0             1.0  \n",
       " CD14 Monocytes                 1.0             1.0  1.0             1.0  \n",
       " CD4 T                          1.0             1.0  1.0             1.0  \n",
       " CD8 T                          1.0             1.0  1.0             1.0  \n",
       " Dendritic                      1.0             1.0  1.0             1.0  \n",
       " FCGR3A Monocytes               1.0             1.0  1.0             1.0  \n",
       " Megakaryocytes                 1.0             1.0  1.0             1.0  \n",
       " NK                             1.0             1.0  1.0             1.0  \n",
       " RPS expressing                 1.0             1.0  1.0             1.0  ,\n",
       " 'F11R_F11R':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0        1.0   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " CD4 T             1.0             1.0    1.0    1.0        1.0   \n",
       " CD8 T             1.0             1.0    1.0    1.0        1.0   \n",
       " Dendritic         1.0             1.0    1.0    1.0        1.0   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0    1.0        1.0   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " NK                1.0             1.0    1.0    1.0        1.0   \n",
       " RPS expressing    1.0             1.0    1.0    1.0        1.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                             1.00             1.0  1.0             1.0  \n",
       " CD14 Monocytes                1.00             1.0  1.0             1.0  \n",
       " CD4 T                         1.00             1.0  1.0             1.0  \n",
       " CD8 T                         1.00             1.0  1.0             1.0  \n",
       " Dendritic                     1.00             1.0  1.0             1.0  \n",
       " FCGR3A Monocytes              1.00             1.0  1.0             1.0  \n",
       " Megakaryocytes                1.00             1.0  1.0             1.0  \n",
       " NK                            1.00             1.0  1.0             1.0  \n",
       " RPS expressing                0.08             1.0  1.0             0.0  ,\n",
       " 'F11R_JAM3':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0        1.0   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " CD4 T             1.0             1.0    1.0    1.0        1.0   \n",
       " CD8 T             1.0             1.0    1.0    1.0        1.0   \n",
       " Dendritic         1.0             1.0    1.0    1.0        1.0   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0    1.0        1.0   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " NK                1.0             1.0    1.0    1.0        1.0   \n",
       " RPS expressing    1.0             1.0    1.0    1.0        1.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                             1.00             1.0  1.0             1.0  \n",
       " CD14 Monocytes                1.00             1.0  1.0             1.0  \n",
       " CD4 T                         1.00             1.0  1.0             1.0  \n",
       " CD8 T                         1.00             1.0  1.0             1.0  \n",
       " Dendritic                     1.00             1.0  1.0             1.0  \n",
       " FCGR3A Monocytes              1.00             1.0  1.0             1.0  \n",
       " Megakaryocytes                1.00             1.0  1.0             1.0  \n",
       " NK                            1.00             1.0  1.0             1.0  \n",
       " RPS expressing                0.01             1.0  1.0             0.0  ,\n",
       " 'JAM3_F11R':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0        1.0   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " CD4 T             1.0             1.0    1.0    1.0        1.0   \n",
       " CD8 T             1.0             1.0    1.0    1.0        1.0   \n",
       " Dendritic         1.0             1.0    1.0    1.0        1.0   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0    1.0        1.0   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " NK                1.0             1.0    1.0    1.0        1.0   \n",
       " RPS expressing    1.0             1.0    1.0    1.0        1.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              1.0             1.0  1.0             1.0  \n",
       " CD14 Monocytes                 1.0             1.0  1.0             1.0  \n",
       " CD4 T                          1.0             1.0  1.0             1.0  \n",
       " CD8 T                          1.0             1.0  1.0             1.0  \n",
       " Dendritic                      1.0             1.0  1.0             1.0  \n",
       " FCGR3A Monocytes               1.0             1.0  1.0             1.0  \n",
       " Megakaryocytes                 1.0             1.0  1.0             1.0  \n",
       " NK                             1.0             1.0  1.0             1.0  \n",
       " RPS expressing                 1.0             1.0  1.0             1.0  ,\n",
       " 'JAM3_JAM3':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0   1.00        1.0   \n",
       " CD14 Monocytes    1.0             1.0    1.0   1.00        1.0   \n",
       " CD4 T             1.0             1.0    1.0   1.00        1.0   \n",
       " CD8 T             1.0             1.0    1.0   1.00        1.0   \n",
       " Dendritic         1.0             1.0    1.0   1.00        1.0   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0   1.00        1.0   \n",
       " Megakaryocytes    1.0             1.0    1.0   1.00        1.0   \n",
       " NK                1.0             1.0    1.0   1.00        1.0   \n",
       " RPS expressing    1.0             1.0    1.0   0.01        1.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              1.0            1.00  1.0             1.0  \n",
       " CD14 Monocytes                 1.0            1.00  1.0             1.0  \n",
       " CD4 T                          1.0            1.00  1.0             1.0  \n",
       " CD8 T                          1.0            1.00  1.0             1.0  \n",
       " Dendritic                      1.0            1.00  1.0             1.0  \n",
       " FCGR3A Monocytes               1.0            1.00  1.0             1.0  \n",
       " Megakaryocytes                 1.0            1.00  1.0             1.0  \n",
       " NK                             1.0            1.00  1.0             1.0  \n",
       " RPS expressing                 1.0            0.08  1.0             1.0  ,\n",
       " 'SELPLG_SELL':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 1.0             1.0    1.0    1.0        1.0   \n",
       " CD14 Monocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " CD4 T             1.0             1.0    1.0    1.0        1.0   \n",
       " CD8 T             1.0             1.0    1.0    1.0        1.0   \n",
       " Dendritic         1.0             1.0    1.0    1.0        1.0   \n",
       " FCGR3A Monocytes  1.0             1.0    1.0    1.0        1.0   \n",
       " Megakaryocytes    1.0             1.0    1.0    1.0        1.0   \n",
       " NK                1.0             1.0    1.0    1.0        1.0   \n",
       " RPS expressing    1.0             1.0    1.0    0.0        1.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              1.0            1.00  1.0             1.0  \n",
       " CD14 Monocytes                 1.0            1.00  1.0             1.0  \n",
       " CD4 T                          1.0            1.00  1.0             1.0  \n",
       " CD8 T                          1.0            1.00  1.0             1.0  \n",
       " Dendritic                      1.0            1.00  1.0             1.0  \n",
       " FCGR3A Monocytes               1.0            1.00  1.0             1.0  \n",
       " Megakaryocytes                 1.0            1.00  1.0             1.0  \n",
       " NK                             1.0            1.00  1.0             1.0  \n",
       " RPS expressing                 1.0            0.02  1.0             1.0  }"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cellchat_launcher.pvalues_dfs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "computational-parliament",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'CXCL2_CXCR1':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0    0.0        0.0   \n",
       " CD14 Monocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " CD4 T             0.0             0.0    0.0    0.0        0.0   \n",
       " CD8 T             0.0             0.0    0.0    0.0        0.0   \n",
       " Dendritic         0.0             0.0    0.0    0.0        0.0   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0    0.0        0.0   \n",
       " Megakaryocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " NK                0.0             0.0    0.0    0.0        0.0   \n",
       " RPS expressing    0.0             0.0    0.0    0.0        0.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              0.0             0.0  0.0             0.0  \n",
       " CD14 Monocytes                 0.0             0.0  0.0             0.0  \n",
       " CD4 T                          0.0             0.0  0.0             0.0  \n",
       " CD8 T                          0.0             0.0  0.0             0.0  \n",
       " Dendritic                      0.0             0.0  0.0             0.0  \n",
       " FCGR3A Monocytes               0.0             0.0  0.0             0.0  \n",
       " Megakaryocytes                 0.0             0.0  0.0             0.0  \n",
       " NK                             0.0             0.0  0.0             0.0  \n",
       " RPS expressing                 0.0             0.0  0.0             0.0  ,\n",
       " 'CXCL3_CXCR1':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0    0.0        0.0   \n",
       " CD14 Monocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " CD4 T             0.0             0.0    0.0    0.0        0.0   \n",
       " CD8 T             0.0             0.0    0.0    0.0        0.0   \n",
       " Dendritic         0.0             0.0    0.0    0.0        0.0   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0    0.0        0.0   \n",
       " Megakaryocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " NK                0.0             0.0    0.0    0.0        0.0   \n",
       " RPS expressing    0.0             0.0    0.0    0.0        0.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                         0.000000             0.0  0.0        0.000000  \n",
       " CD14 Monocytes            0.000000             0.0  0.0        0.000000  \n",
       " CD4 T                     0.000000             0.0  0.0        0.000000  \n",
       " CD8 T                     0.000000             0.0  0.0        0.000000  \n",
       " Dendritic                 0.000000             0.0  0.0        0.000000  \n",
       " FCGR3A Monocytes          0.000000             0.0  0.0        0.000000  \n",
       " Megakaryocytes            0.000000             0.0  0.0        0.000000  \n",
       " NK                        0.000000             0.0  0.0        0.000000  \n",
       " RPS expressing            0.012438             0.0  0.0        0.014414  ,\n",
       " 'TNFSF13B_TNFRSF17':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0    0.0        0.0   \n",
       " CD14 Monocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " CD4 T             0.0             0.0    0.0    0.0        0.0   \n",
       " CD8 T             0.0             0.0    0.0    0.0        0.0   \n",
       " Dendritic         0.0             0.0    0.0    0.0        0.0   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0    0.0        0.0   \n",
       " Megakaryocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " NK                0.0             0.0    0.0    0.0        0.0   \n",
       " RPS expressing    0.0             0.0    0.0    0.0        0.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                         0.000000             0.0  0.0        0.000000  \n",
       " CD14 Monocytes            0.000000             0.0  0.0        0.000000  \n",
       " CD4 T                     0.000000             0.0  0.0        0.000000  \n",
       " CD8 T                     0.000000             0.0  0.0        0.000000  \n",
       " Dendritic                 0.000000             0.0  0.0        0.000000  \n",
       " FCGR3A Monocytes          0.000000             0.0  0.0        0.000000  \n",
       " Megakaryocytes            0.000000             0.0  0.0        0.000000  \n",
       " NK                        0.000000             0.0  0.0        0.000000  \n",
       " RPS expressing            0.016804             0.0  0.0        0.019459  ,\n",
       " 'TNFSF13B_TNFRSF13C':                     B  CD14 Monocytes     CD4 T  CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0  0.000000    0.0        0.0   \n",
       " CD14 Monocytes    0.0             0.0  0.000000    0.0        0.0   \n",
       " CD4 T             0.0             0.0  0.000000    0.0        0.0   \n",
       " CD8 T             0.0             0.0  0.000000    0.0        0.0   \n",
       " Dendritic         0.0             0.0  0.000000    0.0        0.0   \n",
       " FCGR3A Monocytes  0.0             0.0  0.015651    0.0        0.0   \n",
       " Megakaryocytes    0.0             0.0  0.000000    0.0        0.0   \n",
       " NK                0.0             0.0  0.000000    0.0        0.0   \n",
       " RPS expressing    0.0             0.0  0.000000    0.0        0.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              0.0             0.0  0.0             0.0  \n",
       " CD14 Monocytes                 0.0             0.0  0.0             0.0  \n",
       " CD4 T                          0.0             0.0  0.0             0.0  \n",
       " CD8 T                          0.0             0.0  0.0             0.0  \n",
       " Dendritic                      0.0             0.0  0.0             0.0  \n",
       " FCGR3A Monocytes               0.0             0.0  0.0             0.0  \n",
       " Megakaryocytes                 0.0             0.0  0.0             0.0  \n",
       " NK                             0.0             0.0  0.0             0.0  \n",
       " RPS expressing                 0.0             0.0  0.0             0.0  ,\n",
       " 'GZMA_F2R':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0    0.0        0.0   \n",
       " CD14 Monocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " CD4 T             0.0             0.0    0.0    0.0        0.0   \n",
       " CD8 T             0.0             0.0    0.0    0.0        0.0   \n",
       " Dendritic         0.0             0.0    0.0    0.0        0.0   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0    0.0        0.0   \n",
       " Megakaryocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " NK                0.0             0.0    0.0    0.0        0.0   \n",
       " RPS expressing    0.0             0.0    0.0    0.0        0.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              0.0        0.000000  0.0             0.0  \n",
       " CD14 Monocytes                 0.0        0.000000  0.0             0.0  \n",
       " CD4 T                          0.0        0.000000  0.0             0.0  \n",
       " CD8 T                          0.0        0.000000  0.0             0.0  \n",
       " Dendritic                      0.0        0.000000  0.0             0.0  \n",
       " FCGR3A Monocytes               0.0        0.000000  0.0             0.0  \n",
       " Megakaryocytes                 0.0        0.000000  0.0             0.0  \n",
       " NK                             0.0        0.000000  0.0             0.0  \n",
       " RPS expressing                 0.0        0.010088  0.0             0.0  ,\n",
       " 'THBS1_CD47':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0    0.0        0.0   \n",
       " CD14 Monocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " CD4 T             0.0             0.0    0.0    0.0        0.0   \n",
       " CD8 T             0.0             0.0    0.0    0.0        0.0   \n",
       " Dendritic         0.0             0.0    0.0    0.0        0.0   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0    0.0        0.0   \n",
       " Megakaryocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " NK                0.0             0.0    0.0    0.0        0.0   \n",
       " RPS expressing    0.0             0.0    0.0    0.0        0.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              0.0        0.000000  0.0             0.0  \n",
       " CD14 Monocytes                 0.0        0.000000  0.0             0.0  \n",
       " CD4 T                          0.0        0.000000  0.0             0.0  \n",
       " CD8 T                          0.0        0.000000  0.0             0.0  \n",
       " Dendritic                      0.0        0.000000  0.0             0.0  \n",
       " FCGR3A Monocytes               0.0        0.000000  0.0             0.0  \n",
       " Megakaryocytes                 0.0        0.000000  0.0             0.0  \n",
       " NK                             0.0        0.000000  0.0             0.0  \n",
       " RPS expressing                 0.0        0.013641  0.0             0.0  ,\n",
       " 'CLEC2B_KLRB1':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0    0.0        0.0   \n",
       " CD14 Monocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " CD4 T             0.0             0.0    0.0    0.0        0.0   \n",
       " CD8 T             0.0             0.0    0.0    0.0        0.0   \n",
       " Dendritic         0.0             0.0    0.0    0.0        0.0   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0    0.0        0.0   \n",
       " Megakaryocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " NK                0.0             0.0    0.0    0.0        0.0   \n",
       " RPS expressing    0.0             0.0    0.0    0.0        0.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              0.0             0.0  0.0             0.0  \n",
       " CD14 Monocytes                 0.0             0.0  0.0             0.0  \n",
       " CD4 T                          0.0             0.0  0.0             0.0  \n",
       " CD8 T                          0.0             0.0  0.0             0.0  \n",
       " Dendritic                      0.0             0.0  0.0             0.0  \n",
       " FCGR3A Monocytes               0.0             0.0  0.0             0.0  \n",
       " Megakaryocytes                 0.0             0.0  0.0             0.0  \n",
       " NK                             0.0             0.0  0.0             0.0  \n",
       " RPS expressing                 0.0             0.0  0.0             0.0  ,\n",
       " 'CLEC1B_KLRB1':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0    0.0   0.000000   \n",
       " CD14 Monocytes    0.0             0.0    0.0    0.0   0.000000   \n",
       " CD4 T             0.0             0.0    0.0    0.0   0.000000   \n",
       " CD8 T             0.0             0.0    0.0    0.0   0.000000   \n",
       " Dendritic         0.0             0.0    0.0    0.0   0.000000   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0    0.0   0.000000   \n",
       " Megakaryocytes    0.0             0.0    0.0    0.0   0.000000   \n",
       " NK                0.0             0.0    0.0    0.0   0.000000   \n",
       " RPS expressing    0.0             0.0    0.0    0.0   0.003669   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              0.0             0.0  0.0             0.0  \n",
       " CD14 Monocytes                 0.0             0.0  0.0             0.0  \n",
       " CD4 T                          0.0             0.0  0.0             0.0  \n",
       " CD8 T                          0.0             0.0  0.0             0.0  \n",
       " Dendritic                      0.0             0.0  0.0             0.0  \n",
       " FCGR3A Monocytes               0.0             0.0  0.0             0.0  \n",
       " Megakaryocytes                 0.0             0.0  0.0             0.0  \n",
       " NK                             0.0             0.0  0.0             0.0  \n",
       " RPS expressing                 0.0             0.0  0.0             0.0  ,\n",
       " 'ESAM_ESAM':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0    0.0   0.000000   \n",
       " CD14 Monocytes    0.0             0.0    0.0    0.0   0.000000   \n",
       " CD4 T             0.0             0.0    0.0    0.0   0.000000   \n",
       " CD8 T             0.0             0.0    0.0    0.0   0.000000   \n",
       " Dendritic         0.0             0.0    0.0    0.0   0.000000   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0    0.0   0.000000   \n",
       " Megakaryocytes    0.0             0.0    0.0    0.0   0.000000   \n",
       " NK                0.0             0.0    0.0    0.0   0.000000   \n",
       " RPS expressing    0.0             0.0    0.0    0.0   0.004972   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              0.0             0.0  0.0             0.0  \n",
       " CD14 Monocytes                 0.0             0.0  0.0             0.0  \n",
       " CD4 T                          0.0             0.0  0.0             0.0  \n",
       " CD8 T                          0.0             0.0  0.0             0.0  \n",
       " Dendritic                      0.0             0.0  0.0             0.0  \n",
       " FCGR3A Monocytes               0.0             0.0  0.0             0.0  \n",
       " Megakaryocytes                 0.0             0.0  0.0             0.0  \n",
       " NK                             0.0             0.0  0.0             0.0  \n",
       " RPS expressing                 0.0             0.0  0.0             0.0  ,\n",
       " 'ICOSL_ICOS':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0    0.0        0.0   \n",
       " CD14 Monocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " CD4 T             0.0             0.0    0.0    0.0        0.0   \n",
       " CD8 T             0.0             0.0    0.0    0.0        0.0   \n",
       " Dendritic         0.0             0.0    0.0    0.0        0.0   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0    0.0        0.0   \n",
       " Megakaryocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " NK                0.0             0.0    0.0    0.0        0.0   \n",
       " RPS expressing    0.0             0.0    0.0    0.0        0.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              0.0             0.0  0.0             0.0  \n",
       " CD14 Monocytes                 0.0             0.0  0.0             0.0  \n",
       " CD4 T                          0.0             0.0  0.0             0.0  \n",
       " CD8 T                          0.0             0.0  0.0             0.0  \n",
       " Dendritic                      0.0             0.0  0.0             0.0  \n",
       " FCGR3A Monocytes               0.0             0.0  0.0             0.0  \n",
       " Megakaryocytes                 0.0             0.0  0.0             0.0  \n",
       " NK                             0.0             0.0  0.0             0.0  \n",
       " RPS expressing                 0.0             0.0  0.0             0.0  ,\n",
       " 'F11R_F11R':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0    0.0        0.0   \n",
       " CD14 Monocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " CD4 T             0.0             0.0    0.0    0.0        0.0   \n",
       " CD8 T             0.0             0.0    0.0    0.0        0.0   \n",
       " Dendritic         0.0             0.0    0.0    0.0        0.0   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0    0.0        0.0   \n",
       " Megakaryocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " NK                0.0             0.0    0.0    0.0        0.0   \n",
       " RPS expressing    0.0             0.0    0.0    0.0        0.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                         0.000000             0.0  0.0        0.000000  \n",
       " CD14 Monocytes            0.000000             0.0  0.0        0.000000  \n",
       " CD4 T                     0.000000             0.0  0.0        0.000000  \n",
       " CD8 T                     0.000000             0.0  0.0        0.000000  \n",
       " Dendritic                 0.000000             0.0  0.0        0.000000  \n",
       " FCGR3A Monocytes          0.000000             0.0  0.0        0.000000  \n",
       " Megakaryocytes            0.000000             0.0  0.0        0.000000  \n",
       " NK                        0.000000             0.0  0.0        0.000000  \n",
       " RPS expressing            0.004223             0.0  0.0        0.013504  ,\n",
       " 'F11R_JAM3':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0    0.0        0.0   \n",
       " CD14 Monocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " CD4 T             0.0             0.0    0.0    0.0        0.0   \n",
       " CD8 T             0.0             0.0    0.0    0.0        0.0   \n",
       " Dendritic         0.0             0.0    0.0    0.0        0.0   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0    0.0        0.0   \n",
       " Megakaryocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " NK                0.0             0.0    0.0    0.0        0.0   \n",
       " RPS expressing    0.0             0.0    0.0    0.0        0.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                         0.000000             0.0  0.0        0.000000  \n",
       " CD14 Monocytes            0.000000             0.0  0.0        0.000000  \n",
       " CD4 T                     0.000000             0.0  0.0        0.000000  \n",
       " CD8 T                     0.000000             0.0  0.0        0.000000  \n",
       " Dendritic                 0.000000             0.0  0.0        0.000000  \n",
       " FCGR3A Monocytes          0.000000             0.0  0.0        0.000000  \n",
       " Megakaryocytes            0.000000             0.0  0.0        0.000000  \n",
       " NK                        0.000000             0.0  0.0        0.000000  \n",
       " RPS expressing            0.005722             0.0  0.0        0.018237  ,\n",
       " 'JAM3_F11R':                     B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0    0.0        0.0   \n",
       " CD14 Monocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " CD4 T             0.0             0.0    0.0    0.0        0.0   \n",
       " CD8 T             0.0             0.0    0.0    0.0        0.0   \n",
       " Dendritic         0.0             0.0    0.0    0.0        0.0   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0    0.0        0.0   \n",
       " Megakaryocytes    0.0             0.0    0.0    0.0        0.0   \n",
       " NK                0.0             0.0    0.0    0.0        0.0   \n",
       " RPS expressing    0.0             0.0    0.0    0.0        0.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              0.0             0.0  0.0             0.0  \n",
       " CD14 Monocytes                 0.0             0.0  0.0             0.0  \n",
       " CD4 T                          0.0             0.0  0.0             0.0  \n",
       " CD8 T                          0.0             0.0  0.0             0.0  \n",
       " Dendritic                      0.0             0.0  0.0             0.0  \n",
       " FCGR3A Monocytes               0.0             0.0  0.0             0.0  \n",
       " Megakaryocytes                 0.0             0.0  0.0             0.0  \n",
       " NK                             0.0             0.0  0.0             0.0  \n",
       " RPS expressing                 0.0             0.0  0.0             0.0  ,\n",
       " 'JAM3_JAM3':                     B  CD14 Monocytes  CD4 T     CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0  0.000000        0.0   \n",
       " CD14 Monocytes    0.0             0.0    0.0  0.000000        0.0   \n",
       " CD4 T             0.0             0.0    0.0  0.000000        0.0   \n",
       " CD8 T             0.0             0.0    0.0  0.000000        0.0   \n",
       " Dendritic         0.0             0.0    0.0  0.000000        0.0   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0  0.000000        0.0   \n",
       " Megakaryocytes    0.0             0.0    0.0  0.000000        0.0   \n",
       " NK                0.0             0.0    0.0  0.000000        0.0   \n",
       " RPS expressing    0.0             0.0    0.0  0.013831        0.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              0.0        0.000000  0.0             0.0  \n",
       " CD14 Monocytes                 0.0        0.000000  0.0             0.0  \n",
       " CD4 T                          0.0        0.000000  0.0             0.0  \n",
       " CD8 T                          0.0        0.000000  0.0             0.0  \n",
       " Dendritic                      0.0        0.000000  0.0             0.0  \n",
       " FCGR3A Monocytes               0.0        0.000000  0.0             0.0  \n",
       " Megakaryocytes                 0.0        0.000000  0.0             0.0  \n",
       " NK                             0.0        0.000000  0.0             0.0  \n",
       " RPS expressing                 0.0        0.002767  0.0             0.0  ,\n",
       " 'SELPLG_SELL':                     B  CD14 Monocytes  CD4 T     CD8 T  Dendritic  \\\n",
       " B                 0.0             0.0    0.0  0.000000        0.0   \n",
       " CD14 Monocytes    0.0             0.0    0.0  0.000000        0.0   \n",
       " CD4 T             0.0             0.0    0.0  0.000000        0.0   \n",
       " CD8 T             0.0             0.0    0.0  0.000000        0.0   \n",
       " Dendritic         0.0             0.0    0.0  0.000000        0.0   \n",
       " FCGR3A Monocytes  0.0             0.0    0.0  0.000000        0.0   \n",
       " Megakaryocytes    0.0             0.0    0.0  0.000000        0.0   \n",
       " NK                0.0             0.0    0.0  0.000000        0.0   \n",
       " RPS expressing    0.0             0.0    0.0  0.018676        0.0   \n",
       " \n",
       "                   FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       " B                              0.0        0.000000  0.0             0.0  \n",
       " CD14 Monocytes                 0.0        0.000000  0.0             0.0  \n",
       " CD4 T                          0.0        0.000000  0.0             0.0  \n",
       " CD8 T                          0.0        0.000000  0.0             0.0  \n",
       " Dendritic                      0.0        0.000000  0.0             0.0  \n",
       " FCGR3A Monocytes               0.0        0.000000  0.0             0.0  \n",
       " Megakaryocytes                 0.0        0.000000  0.0             0.0  \n",
       " NK                             0.0        0.000000  0.0             0.0  \n",
       " RPS expressing                 0.0        0.003751  0.0             0.0  }"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cellchat_launcher.probabilities_dfs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "jewish-print",
   "metadata": {},
   "source": [
    "Let's take a look at one of the tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "weekly-prince",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>B</th>\n",
       "      <th>CD14 Monocytes</th>\n",
       "      <th>CD4 T</th>\n",
       "      <th>CD8 T</th>\n",
       "      <th>Dendritic</th>\n",
       "      <th>FCGR3A Monocytes</th>\n",
       "      <th>Megakaryocytes</th>\n",
       "      <th>NK</th>\n",
       "      <th>RPS expressing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD14 Monocytes</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD4 T</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD8 T</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dendritic</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FCGR3A Monocytes</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Megakaryocytes</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NK</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RPS expressing</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       "B                 1.0             1.0    1.0    1.0       1.00   \n",
       "CD14 Monocytes    1.0             1.0    1.0    1.0       1.00   \n",
       "CD4 T             1.0             1.0    1.0    1.0       1.00   \n",
       "CD8 T             1.0             1.0    1.0    1.0       1.00   \n",
       "Dendritic         1.0             1.0    1.0    1.0       1.00   \n",
       "FCGR3A Monocytes  1.0             1.0    1.0    1.0       1.00   \n",
       "Megakaryocytes    1.0             1.0    1.0    1.0       1.00   \n",
       "NK                1.0             1.0    1.0    1.0       1.00   \n",
       "RPS expressing    1.0             1.0    1.0    1.0       0.01   \n",
       "\n",
       "                  FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       "B                              1.0             1.0  1.0             1.0  \n",
       "CD14 Monocytes                 1.0             1.0  1.0             1.0  \n",
       "CD4 T                          1.0             1.0  1.0             1.0  \n",
       "CD8 T                          1.0             1.0  1.0             1.0  \n",
       "Dendritic                      1.0             1.0  1.0             1.0  \n",
       "FCGR3A Monocytes               1.0             1.0  1.0             1.0  \n",
       "Megakaryocytes                 1.0             1.0  1.0             1.0  \n",
       "NK                             1.0             1.0  1.0             1.0  \n",
       "RPS expressing                 1.0             1.0  1.0             1.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cellchat_launcher.pvalues_dfs[\"ESAM_ESAM\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "yellow-green",
   "metadata": {},
   "source": [
    "This format is somehow useful, e.g. when we want to build a chord diagram. That's why we set `convert_to_cellchat_format=True` when running `read_output()` for CellPhoneDB launcher. So you can also get a matrix for every interactions for CellPhoneDB:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "defined-anniversary",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>RPS expressing</th>\n",
       "      <th>B</th>\n",
       "      <th>CD4 T</th>\n",
       "      <th>CD14 Monocytes</th>\n",
       "      <th>NK</th>\n",
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       "      <th>RPS expressing</th>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>CD14 Monocytes</th>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>NK</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <th>FCGR3A Monocytes</th>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>Dendritic</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Megakaryocytes</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 RPS expressing  B CD4 T CD14 Monocytes NK CD8 T  \\\n",
       "RPS expressing                1  1     1              1  1     1   \n",
       "B                             1  1     1              1  1     1   \n",
       "CD4 T                         1  1     1              1  1     1   \n",
       "CD14 Monocytes                1  1     1              1  1     1   \n",
       "NK                            1  1     1              1  1     1   \n",
       "CD8 T                         1  1     1              1  1     1   \n",
       "FCGR3A Monocytes              1  1     1              1  1     1   \n",
       "Dendritic                     1  1     1              1  1     1   \n",
       "Megakaryocytes                1  1     1              1  1     1   \n",
       "\n",
       "                 FCGR3A Monocytes Dendritic Megakaryocytes  \n",
       "RPS expressing                  1         1              1  \n",
       "B                               1         1              1  \n",
       "CD4 T                           1         1              1  \n",
       "CD14 Monocytes                  1         1              1  \n",
       "NK                              1         1              1  \n",
       "CD8 T                           1         1              1  \n",
       "FCGR3A Monocytes                1         1              1  \n",
       "Dendritic                       1         1              1  \n",
       "Megakaryocytes                  1         1              0  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cpdb_launcher.pvalues_dfs[\"ESAM_ESAM\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "productive-integral",
   "metadata": {},
   "source": [
    "As you can see, CellPhoneDB predicts an ESAM-ESAM interaction between megakaryocytes, and CellChat predicts it for RPS expressing cells cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "correct-train",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>B</th>\n",
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       "      <th>CD8 T</th>\n",
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       "      <td>0.0</td>\n",
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       "      <th>Dendritic</th>\n",
       "      <td>0.0</td>\n",
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       "      <th>FCGR3A Monocytes</th>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Megakaryocytes</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NK</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>1.0</td>\n",
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       "      <td>0.0</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "                    B  CD14 Monocytes  CD4 T  CD8 T  Dendritic  \\\n",
       "B                 0.0             0.0    0.0    0.0        1.0   \n",
       "CD14 Monocytes    0.0             0.0    0.0    0.0        0.0   \n",
       "CD4 T             0.0             0.0    0.0    0.0        1.0   \n",
       "CD8 T             0.0             0.0    0.0    0.0        0.0   \n",
       "Dendritic         0.0             0.0    0.0    0.0        1.0   \n",
       "FCGR3A Monocytes  0.0             0.0    0.0    0.0        0.0   \n",
       "Megakaryocytes    0.0             0.0    0.0    0.0        0.0   \n",
       "NK                0.0             0.0    0.0    0.0        1.0   \n",
       "RPS expressing    0.0             0.0    0.0    0.0        1.0   \n",
       "\n",
       "                  FCGR3A Monocytes  Megakaryocytes   NK  RPS expressing  \n",
       "B                              1.0             0.0  0.0             0.0  \n",
       "CD14 Monocytes                 1.0             0.0  0.0             0.0  \n",
       "CD4 T                          1.0             0.0  0.0             0.0  \n",
       "CD8 T                          1.0             0.0  0.0             0.0  \n",
       "Dendritic                      1.0             0.0  0.0             0.0  \n",
       "FCGR3A Monocytes               1.0             0.0  0.0             0.0  \n",
       "Megakaryocytes                 0.0             1.0  0.0             0.0  \n",
       "NK                             1.0             0.0  0.0             0.0  \n",
       "RPS expressing                 1.0             0.0  0.0             0.0  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cellchat_launcher.counts_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "according-cornwall",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cellchat_launcher.visualise_interactions()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "copyrighted-tackle",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Interactions counts'}>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cellchat_launcher.dotplot_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "baking-charm",
   "metadata": {},
   "source": [
    "This tool makes it easier to compare tools. For example, you can clearly see, that CellChat finds less interactions between cells than CellPhoneDB"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}