tasccoda.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# tascCODA - Tree-aggregated compositional analysis\n",
    "\n",
    "This notebook is a tutorial on how to use tascCODA [Ostner et al., 2021](https://www.frontiersin.org/articles/10.3389/fgene.2021.766405/full) for tree-aggregated compositional analysis of high-throughput sequencing (HTS) data.\n",
    "\n",
    "For this example, we use single-cell RNA sequencing data. However, there are no limitations to use tascCODA with other HTS data, such as 16S rRNA sequencing.\n",
    "\n",
    "The particular dataset for this analysis was generated by [Smillie et al., 2019](https://doi.org/10.1016/j.cell.2019.06.029).\n",
    "It contains samples from two different regions in the small intestine of mice - Epithelium and Lamina Propria - and three different inflammation conditions - healthy, non-inflamed and inflamed. In total, we have 365.492 cells from 51 cell types in 133 samples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-30T10:55:10.435711Z",
     "start_time": "2023-11-30T10:55:05.089284Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">ryp2 is not installed. Install with </span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">pip install rpy2 </span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">to run tools with R support.</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1;33mryp2 is not installed. Install with \u001b[0m\u001b[1;32mpip install rpy2 \u001b[0m\u001b[1;33mto run tools with R support.\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pertpy as pt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset\n",
    "\n",
    "First, we read in the per-cell data. In this dataset, samples are specified as \"Subject\", and cell types are denoted as \"Cluster\". Interesting covariates are the samples' location and health status.\n",
    "The columns \"Major_l1\" - \"Major_l4\" and \"Cluster\" describe a lineage tree over the cell types."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-30T10:58:11.272007Z",
     "start_time": "2023-11-30T10:58:08.882042Z"
    },
    "collapsed": false
   },
   "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>Origin</th>\n",
       "      <th>Subject</th>\n",
       "      <th>Sample</th>\n",
       "      <th>Location</th>\n",
       "      <th>Replicate</th>\n",
       "      <th>Health</th>\n",
       "      <th>Cluster</th>\n",
       "      <th>nGene</th>\n",
       "      <th>nUMI</th>\n",
       "      <th>Major_l1</th>\n",
       "      <th>Major_l2</th>\n",
       "      <th>Major_l3</th>\n",
       "      <th>Major_l4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>N7.EpiA.AAGGCTACCCTTTA</th>\n",
       "      <td>Imm</td>\n",
       "      <td>N7</td>\n",
       "      <td>EpiA</td>\n",
       "      <td>Epi</td>\n",
       "      <td>A</td>\n",
       "      <td>Non-inflamed</td>\n",
       "      <td>Plasma</td>\n",
       "      <td>624.0</td>\n",
       "      <td>7433.0</td>\n",
       "      <td>Immune</td>\n",
       "      <td>Lymphoid</td>\n",
       "      <td>B cells</td>\n",
       "      <td>Plasma4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N7.EpiA.AAGGTGCTACGGAG</th>\n",
       "      <td>Imm</td>\n",
       "      <td>N7</td>\n",
       "      <td>EpiA</td>\n",
       "      <td>Epi</td>\n",
       "      <td>A</td>\n",
       "      <td>Non-inflamed</td>\n",
       "      <td>CD8+ IELs</td>\n",
       "      <td>558.0</td>\n",
       "      <td>1904.0</td>\n",
       "      <td>Immune</td>\n",
       "      <td>Lymphoid</td>\n",
       "      <td>T cells</td>\n",
       "      <td>CD8+ T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N7.EpiA.AAGTAACTTGCTTT</th>\n",
       "      <td>Imm</td>\n",
       "      <td>N7</td>\n",
       "      <td>EpiA</td>\n",
       "      <td>Epi</td>\n",
       "      <td>A</td>\n",
       "      <td>Non-inflamed</td>\n",
       "      <td>CD8+ IELs</td>\n",
       "      <td>437.0</td>\n",
       "      <td>1366.0</td>\n",
       "      <td>Immune</td>\n",
       "      <td>Lymphoid</td>\n",
       "      <td>T cells</td>\n",
       "      <td>CD8+ T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N7.EpiA.ACAATAACCCTCAC</th>\n",
       "      <td>Imm</td>\n",
       "      <td>N7</td>\n",
       "      <td>EpiA</td>\n",
       "      <td>Epi</td>\n",
       "      <td>A</td>\n",
       "      <td>Non-inflamed</td>\n",
       "      <td>Plasma</td>\n",
       "      <td>484.0</td>\n",
       "      <td>5161.0</td>\n",
       "      <td>Immune</td>\n",
       "      <td>Lymphoid</td>\n",
       "      <td>B cells</td>\n",
       "      <td>Plasma4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N7.EpiA.ACAGTTCTTCTACT</th>\n",
       "      <td>Imm</td>\n",
       "      <td>N7</td>\n",
       "      <td>EpiA</td>\n",
       "      <td>Epi</td>\n",
       "      <td>A</td>\n",
       "      <td>Non-inflamed</td>\n",
       "      <td>CD8+ IELs</td>\n",
       "      <td>470.0</td>\n",
       "      <td>1408.0</td>\n",
       "      <td>Immune</td>\n",
       "      <td>Lymphoid</td>\n",
       "      <td>T cells</td>\n",
       "      <td>CD8+ T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N110.LPB.TTTGGTTGTGTGGCTC</th>\n",
       "      <td>Epi</td>\n",
       "      <td>N110</td>\n",
       "      <td>LPB</td>\n",
       "      <td>LP</td>\n",
       "      <td>B</td>\n",
       "      <td>Inflamed</td>\n",
       "      <td>Immature Enterocytes 2</td>\n",
       "      <td>2553.0</td>\n",
       "      <td>11705.0</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Absorptive</td>\n",
       "      <td>Immature cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N110.LPB.TTTGGTTTCCTTAATC</th>\n",
       "      <td>Epi</td>\n",
       "      <td>N110</td>\n",
       "      <td>LPB</td>\n",
       "      <td>LP</td>\n",
       "      <td>B</td>\n",
       "      <td>Inflamed</td>\n",
       "      <td>TA 2</td>\n",
       "      <td>3234.0</td>\n",
       "      <td>16164.0</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Absorptive</td>\n",
       "      <td>TA cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N110.LPB.TTTGGTTTCTTACCTA</th>\n",
       "      <td>Epi</td>\n",
       "      <td>N110</td>\n",
       "      <td>LPB</td>\n",
       "      <td>LP</td>\n",
       "      <td>B</td>\n",
       "      <td>Inflamed</td>\n",
       "      <td>Enterocyte Progenitors</td>\n",
       "      <td>258.0</td>\n",
       "      <td>384.0</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Absorptive</td>\n",
       "      <td>Immature cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N110.LPB.TTTGTCAAGGATGGAA</th>\n",
       "      <td>Epi</td>\n",
       "      <td>N110</td>\n",
       "      <td>LPB</td>\n",
       "      <td>LP</td>\n",
       "      <td>B</td>\n",
       "      <td>Inflamed</td>\n",
       "      <td>TA 1</td>\n",
       "      <td>487.0</td>\n",
       "      <td>772.0</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Absorptive</td>\n",
       "      <td>TA cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N110.LPB.TTTGTCAGTTGTTTGG</th>\n",
       "      <td>Epi</td>\n",
       "      <td>N110</td>\n",
       "      <td>LPB</td>\n",
       "      <td>LP</td>\n",
       "      <td>B</td>\n",
       "      <td>Inflamed</td>\n",
       "      <td>TA 1</td>\n",
       "      <td>363.0</td>\n",
       "      <td>747.0</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Absorptive</td>\n",
       "      <td>TA cells</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>365492 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Origin Subject Sample Location Replicate  \\\n",
       "N7.EpiA.AAGGCTACCCTTTA       Imm      N7   EpiA      Epi         A   \n",
       "N7.EpiA.AAGGTGCTACGGAG       Imm      N7   EpiA      Epi         A   \n",
       "N7.EpiA.AAGTAACTTGCTTT       Imm      N7   EpiA      Epi         A   \n",
       "N7.EpiA.ACAATAACCCTCAC       Imm      N7   EpiA      Epi         A   \n",
       "N7.EpiA.ACAGTTCTTCTACT       Imm      N7   EpiA      Epi         A   \n",
       "...                          ...     ...    ...      ...       ...   \n",
       "N110.LPB.TTTGGTTGTGTGGCTC    Epi    N110    LPB       LP         B   \n",
       "N110.LPB.TTTGGTTTCCTTAATC    Epi    N110    LPB       LP         B   \n",
       "N110.LPB.TTTGGTTTCTTACCTA    Epi    N110    LPB       LP         B   \n",
       "N110.LPB.TTTGTCAAGGATGGAA    Epi    N110    LPB       LP         B   \n",
       "N110.LPB.TTTGTCAGTTGTTTGG    Epi    N110    LPB       LP         B   \n",
       "\n",
       "                                 Health                 Cluster   nGene  \\\n",
       "N7.EpiA.AAGGCTACCCTTTA     Non-inflamed                  Plasma   624.0   \n",
       "N7.EpiA.AAGGTGCTACGGAG     Non-inflamed               CD8+ IELs   558.0   \n",
       "N7.EpiA.AAGTAACTTGCTTT     Non-inflamed               CD8+ IELs   437.0   \n",
       "N7.EpiA.ACAATAACCCTCAC     Non-inflamed                  Plasma   484.0   \n",
       "N7.EpiA.ACAGTTCTTCTACT     Non-inflamed               CD8+ IELs   470.0   \n",
       "...                                 ...                     ...     ...   \n",
       "N110.LPB.TTTGGTTGTGTGGCTC      Inflamed  Immature Enterocytes 2  2553.0   \n",
       "N110.LPB.TTTGGTTTCCTTAATC      Inflamed                    TA 2  3234.0   \n",
       "N110.LPB.TTTGGTTTCTTACCTA      Inflamed  Enterocyte Progenitors   258.0   \n",
       "N110.LPB.TTTGTCAAGGATGGAA      Inflamed                    TA 1   487.0   \n",
       "N110.LPB.TTTGTCAGTTGTTTGG      Inflamed                    TA 1   363.0   \n",
       "\n",
       "                              nUMI    Major_l1    Major_l2    Major_l3  \\\n",
       "N7.EpiA.AAGGCTACCCTTTA      7433.0      Immune    Lymphoid     B cells   \n",
       "N7.EpiA.AAGGTGCTACGGAG      1904.0      Immune    Lymphoid     T cells   \n",
       "N7.EpiA.AAGTAACTTGCTTT      1366.0      Immune    Lymphoid     T cells   \n",
       "N7.EpiA.ACAATAACCCTCAC      5161.0      Immune    Lymphoid     B cells   \n",
       "N7.EpiA.ACAGTTCTTCTACT      1408.0      Immune    Lymphoid     T cells   \n",
       "...                            ...         ...         ...         ...   \n",
       "N110.LPB.TTTGGTTGTGTGGCTC  11705.0  Epithelial  Epithelial  Absorptive   \n",
       "N110.LPB.TTTGGTTTCCTTAATC  16164.0  Epithelial  Epithelial  Absorptive   \n",
       "N110.LPB.TTTGGTTTCTTACCTA    384.0  Epithelial  Epithelial  Absorptive   \n",
       "N110.LPB.TTTGTCAAGGATGGAA    772.0  Epithelial  Epithelial  Absorptive   \n",
       "N110.LPB.TTTGTCAGTTGTTTGG    747.0  Epithelial  Epithelial  Absorptive   \n",
       "\n",
       "                                 Major_l4  \n",
       "N7.EpiA.AAGGCTACCCTTTA            Plasma4  \n",
       "N7.EpiA.AAGGTGCTACGGAG             CD8+ T  \n",
       "N7.EpiA.AAGTAACTTGCTTT             CD8+ T  \n",
       "N7.EpiA.ACAATAACCCTCAC            Plasma4  \n",
       "N7.EpiA.ACAGTTCTTCTACT             CD8+ T  \n",
       "...                                   ...  \n",
       "N110.LPB.TTTGGTTGTGTGGCTC  Immature cells  \n",
       "N110.LPB.TTTGGTTTCCTTAATC        TA cells  \n",
       "N110.LPB.TTTGGTTTCTTACCTA  Immature cells  \n",
       "N110.LPB.TTTGTCAAGGATGGAA        TA cells  \n",
       "N110.LPB.TTTGTCAGTTGTTTGG        TA cells  \n",
       "\n",
       "[365492 rows x 13 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smillie_counts = pt.dt.smillie_2019()\n",
    "smillie_counts.obs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-30T10:58:14.103944Z",
     "start_time": "2023-11-30T10:58:14.095410Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 365492 × 18172\n",
       "    obs: 'Origin', 'Subject', 'Sample', 'Location', 'Replicate', 'Health', 'Cluster', 'nGene', 'nUMI', 'Major_l1', 'Major_l2', 'Major_l3', 'Major_l4'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smillie_counts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we convert the data to a (samples x cell types) object.\n",
    "To identify the statistical samples, we need to combine the \"Subject\" and \"Sample\" columns.\n",
    "We also need to extract the tree-structured cell lineage information (Lineages `Major_l1` - `Major_l4`) from the data, generate a Newick string through `tasccoda.tree_utils.df2newick()` and convert it into a [ete3](http://etetoolkit.org/) tree object. This is all done within the `load` function by specifying."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-30T10:58:27.487223Z",
     "start_time": "2023-11-30T10:58:24.440061Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>MuData object with n_obs × n_vars = 365625 × 18223\n",
       "  2 modalities\n",
       "    rna:\t365492 x 18172\n",
       "      obs:\t&#x27;Origin&#x27;, &#x27;Subject&#x27;, &#x27;Sample&#x27;, &#x27;Location&#x27;, &#x27;Replicate&#x27;, &#x27;Health&#x27;, &#x27;Cluster&#x27;, &#x27;nGene&#x27;, &#x27;nUMI&#x27;, &#x27;Major_l1&#x27;, &#x27;Major_l2&#x27;, &#x27;Major_l3&#x27;, &#x27;Major_l4&#x27;, &#x27;scCODA_sample_id&#x27;\n",
       "    coda:\t133 x 51\n",
       "      obs:\t&#x27;Location&#x27;, &#x27;Health&#x27;, &#x27;Subject&#x27;, &#x27;Sample&#x27;\n",
       "      var:\t&#x27;n_cells&#x27;\n",
       "      uns:\t&#x27;tree&#x27;</pre>"
      ],
      "text/plain": [
       "MuData object with n_obs × n_vars = 365625 × 18223\n",
       "  2 modalities\n",
       "    rna:\t365492 x 18172\n",
       "      obs:\t'Origin', 'Subject', 'Sample', 'Location', 'Replicate', 'Health', 'Cluster', 'nGene', 'nUMI', 'Major_l1', 'Major_l2', 'Major_l3', 'Major_l4', 'scCODA_sample_id'\n",
       "    coda:\t133 x 51\n",
       "      obs:\t'Location', 'Health', 'Subject', 'Sample'\n",
       "      var:\t'n_cells'\n",
       "      uns:\t'tree'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tasccoda_model = pt.tl.Tasccoda()\n",
    "smillie_data = tasccoda_model.load(\n",
    "    smillie_counts,\n",
    "    type=\"cell_level\",\n",
    "    cell_type_identifier=\"Cluster\",\n",
    "    sample_identifier=[\"Subject\", \"Sample\"],\n",
    "    covariate_obs=[\"Location\", \"Health\"],\n",
    "    levels_orig=[\"Major_l1\", \"Major_l2\", \"Major_l3\", \"Major_l4\", \"Cluster\"],\n",
    "    add_level_name=True,\n",
    ")\n",
    "smillie_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also visualize the tree:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-30T10:58:29.509324Z",
     "start_time": "2023-11-30T10:58:29.184441Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tasccoda_model.plot_draw_tree(smillie_data[\"coda\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this tutorial, we focus on finding changes between healthy and non-inflamed tissue in the Lamina Propria. Therefore, we subset the data accordingly, and end up with 48 samples:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-30T10:58:33.252642Z",
     "start_time": "2023-11-30T10:58:33.248687Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>MuData object with n_obs × n_vars = 365625 × 18223\n",
       "  3 modalities\n",
       "    rna:\t365492 x 18172\n",
       "      obs:\t&#x27;Origin&#x27;, &#x27;Subject&#x27;, &#x27;Sample&#x27;, &#x27;Location&#x27;, &#x27;Replicate&#x27;, &#x27;Health&#x27;, &#x27;Cluster&#x27;, &#x27;nGene&#x27;, &#x27;nUMI&#x27;, &#x27;Major_l1&#x27;, &#x27;Major_l2&#x27;, &#x27;Major_l3&#x27;, &#x27;Major_l4&#x27;, &#x27;scCODA_sample_id&#x27;\n",
       "    coda:\t133 x 51\n",
       "      obs:\t&#x27;Location&#x27;, &#x27;Health&#x27;, &#x27;Subject&#x27;, &#x27;Sample&#x27;\n",
       "      var:\t&#x27;n_cells&#x27;\n",
       "      uns:\t&#x27;tree&#x27;\n",
       "    coda_LP:\t48 x 51\n",
       "      obs:\t&#x27;Location&#x27;, &#x27;Health&#x27;, &#x27;Subject&#x27;, &#x27;Sample&#x27;\n",
       "      var:\t&#x27;n_cells&#x27;\n",
       "      uns:\t&#x27;tree&#x27;</pre>"
      ],
      "text/plain": [
       "MuData object with n_obs × n_vars = 365625 × 18223\n",
       "  3 modalities\n",
       "    rna:\t365492 x 18172\n",
       "      obs:\t'Origin', 'Subject', 'Sample', 'Location', 'Replicate', 'Health', 'Cluster', 'nGene', 'nUMI', 'Major_l1', 'Major_l2', 'Major_l3', 'Major_l4', 'scCODA_sample_id'\n",
       "    coda:\t133 x 51\n",
       "      obs:\t'Location', 'Health', 'Subject', 'Sample'\n",
       "      var:\t'n_cells'\n",
       "      uns:\t'tree'\n",
       "    coda_LP:\t48 x 51\n",
       "      obs:\t'Location', 'Health', 'Subject', 'Sample'\n",
       "      var:\t'n_cells'\n",
       "      uns:\t'tree'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smillie_data.mod[\"coda_LP\"] = smillie_data[\"coda\"][\n",
    "    (smillie_data[\"coda\"].obs[\"Health\"].isin([\"Healthy\", \"Non-inflamed\"]))\n",
    "    & (smillie_data[\"coda\"].obs[\"Location\"] == \"LP\")\n",
    "]\n",
    "smillie_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A quick plot of the data with the `sccoda.util.data_visualization` module shows us that there are some changes in relative abundance in the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-30T10:58:35.426882Z",
     "start_time": "2023-11-30T10:58:34.983388Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tasccoda_model.plot_boxplots(smillie_data, modality_key=\"coda_LP\", feature_name=\"Health\", figsize=(20, 8))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run tascCODA\n",
    "\n",
    "Inferring credible effects with tascCODA on our data is now simply a matter of running the sampling process. The model creation and inference works analogous to scCODA (see the scCODA quickstart tutorial)\n",
    "\n",
    "As hyperparameters, we have to specify in the `prepare` function:\n",
    "- The reference cell type (which is assumed to be unchanged between the conditions): We use the `automatic` setting here, which chooses a reference that induces minimal compositional effects (here we use the automatic suggestion - NK cells)\n",
    "- The model formula (R-style formula string, just as in scCODA)\n",
    "- The aggregation bias $\\phi$, defined in the [tascCODA paper](https://www.frontiersin.org/articles/10.3389/fgene.2021.766405/full). We go with an unbiased aggregation (`pen_args={\"phi\": 0}`) here.\n",
    "- The key in `.uns` of our MuData modality where the tree is saved.\n",
    "\n",
    "Then, we run No-U-turn sampling via `run_nuts` with the default settings of 11.000 samples, of which 1.000 are discarded as burn-in"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-30T10:58:40.080837Z",
     "start_time": "2023-11-30T10:58:40.049088Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Automatic reference selection! Reference cell type set to NKs</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1;34mAutomatic reference selection! Reference cell type set to NKs\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Zero counts encountered in data! Added a pseudocount of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span>.\n",
       "</pre>\n"
      ],
      "text/plain": [
       "Zero counts encountered in data! Added a pseudocount of \u001b[1;36m0.5\u001b[0m.\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>MuData object with n_obs × n_vars = 365625 × 18223\n",
       "  3 modalities\n",
       "    rna:\t365492 x 18172\n",
       "      obs:\t&#x27;Origin&#x27;, &#x27;Subject&#x27;, &#x27;Sample&#x27;, &#x27;Location&#x27;, &#x27;Replicate&#x27;, &#x27;Health&#x27;, &#x27;Cluster&#x27;, &#x27;nGene&#x27;, &#x27;nUMI&#x27;, &#x27;Major_l1&#x27;, &#x27;Major_l2&#x27;, &#x27;Major_l3&#x27;, &#x27;Major_l4&#x27;, &#x27;scCODA_sample_id&#x27;\n",
       "    coda:\t133 x 51\n",
       "      obs:\t&#x27;Location&#x27;, &#x27;Health&#x27;, &#x27;Subject&#x27;, &#x27;Sample&#x27;\n",
       "      var:\t&#x27;n_cells&#x27;\n",
       "      uns:\t&#x27;tree&#x27;\n",
       "    coda_LP:\t48 x 51\n",
       "      obs:\t&#x27;Location&#x27;, &#x27;Health&#x27;, &#x27;Subject&#x27;, &#x27;Sample&#x27;\n",
       "      var:\t&#x27;n_cells&#x27;\n",
       "      uns:\t&#x27;tree&#x27;, &#x27;scCODA_params&#x27;\n",
       "      obsm:\t&#x27;covariate_matrix&#x27;, &#x27;sample_counts&#x27;</pre>"
      ],
      "text/plain": [
       "MuData object with n_obs × n_vars = 365625 × 18223\n",
       "  3 modalities\n",
       "    rna:\t365492 x 18172\n",
       "      obs:\t'Origin', 'Subject', 'Sample', 'Location', 'Replicate', 'Health', 'Cluster', 'nGene', 'nUMI', 'Major_l1', 'Major_l2', 'Major_l3', 'Major_l4', 'scCODA_sample_id'\n",
       "    coda:\t133 x 51\n",
       "      obs:\t'Location', 'Health', 'Subject', 'Sample'\n",
       "      var:\t'n_cells'\n",
       "      uns:\t'tree'\n",
       "    coda_LP:\t48 x 51\n",
       "      obs:\t'Location', 'Health', 'Subject', 'Sample'\n",
       "      var:\t'n_cells'\n",
       "      uns:\t'tree', 'scCODA_params'\n",
       "      obsm:\t'covariate_matrix', 'sample_counts'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smillie_data = tasccoda_model.prepare(\n",
    "    smillie_data,\n",
    "    modality_key=\"coda_LP\",\n",
    "    tree_key=\"tree\",\n",
    "    reference_cell_type=\"automatic\",\n",
    "    formula=\"Health\",\n",
    "    pen_args={\"phi\": 0},\n",
    ")\n",
    "smillie_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-30T11:02:01.485950Z",
     "start_time": "2023-11-30T10:58:43.135316Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
      "I0000 00:00:1701341923.141712       1 tfrt_cpu_pjrt_client.cc:349] TfrtCpuClient created.\n",
      "sample: 100%|██████████| 11000/11000 [03:12<00:00, 57.14it/s, 63 steps of size 7.98e-02. acc. prob=0.91]\n"
     ]
    }
   ],
   "source": [
    "tasccoda_model.run_nuts(smillie_data, modality_key=\"coda_LP\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Result analysis\n",
    "\n",
    "Calling `summary`, we can see the most relevant information for further analysis:\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-30T11:02:06.911026Z",
     "start_time": "2023-11-30T11:02:06.862672Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                                          Compositional Analysis summary                                           </span>\n",
       "┌────────────────────────────────────────────┬────────────────────────────────────────────────────────────────────┐\n",
       "│<span style=\"font-weight: bold\"> Name                                       </span>│<span style=\"font-weight: bold\"> Value                                                              </span>│\n",
       "├────────────────────────────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> Data                                       </span>│ Data: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">48</span> samples, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">51</span> cell types                                    │\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> Reference cell type                        </span>│ NKs                                                                │\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> Formula                                    </span>│ Health                                                             │\n",
       "└────────────────────────────────────────────┴────────────────────────────────────────────────────────────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[3m                                          Compositional Analysis summary                                           \u001b[0m\n",
       "┌────────────────────────────────────────────┬────────────────────────────────────────────────────────────────────┐\n",
       "│\u001b[1m \u001b[0m\u001b[1mName                                      \u001b[0m\u001b[1m \u001b[0m│\u001b[1m \u001b[0m\u001b[1mValue                                                             \u001b[0m\u001b[1m \u001b[0m│\n",
       "├────────────────────────────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│\u001b[36m \u001b[0m\u001b[36mData                                      \u001b[0m\u001b[36m \u001b[0m│ Data: \u001b[1;36m48\u001b[0m samples, \u001b[1;36m51\u001b[0m cell types                                    │\n",
       "│\u001b[36m \u001b[0m\u001b[36mReference cell type                       \u001b[0m\u001b[36m \u001b[0m│ NKs                                                                │\n",
       "│\u001b[36m \u001b[0m\u001b[36mFormula                                   \u001b[0m\u001b[36m \u001b[0m│ Health                                                             │\n",
       "└────────────────────────────────────────────┴────────────────────────────────────────────────────────────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┌─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐\n",
       "│<span style=\"font-weight: bold\"> Intercepts                                                                                                      </span>│\n",
       "├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤\n",
       "│                           Final Parameter  Expected Sample                                                      │\n",
       "│ Cell Type                                                                                                       │\n",
       "│ Best4+ Enterocytes            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.182</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10.352</span>                                                          │\n",
       "│ CD4+ Activated Fos-hi          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.561</span>           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">160.805</span>                                                          │\n",
       "│ CD4+ Activated Fos-lo          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.609</span>           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">168.712</span>                                                          │\n",
       "│ CD4+ Memory                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.319</span>           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">126.241</span>                                                          │\n",
       "│ CD4+ PD1+                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.933</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13.279</span>                                                          │\n",
       "│ CD8+ IELs                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.112</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30.180</span>                                                          │\n",
       "│ CD8+ IL17+                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.803</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15.123</span>                                                          │\n",
       "│ CD8+ LP                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.602</span>           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">167.535</span>                                                          │\n",
       "│ CD69+ Mast                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.592</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">61.019</span>                                                          │\n",
       "│ CD69- Mast                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.354</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8.716</span>                                                          │\n",
       "│ Cycling B                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.477</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20.951</span>                                                          │\n",
       "│ Cycling Monocytes             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.568</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19.129</span>                                                          │\n",
       "│ Cycling T                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.700</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16.763</span>                                                          │\n",
       "│ Cycling TA                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.090</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36.936</span>                                                          │\n",
       "│ DC1                           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.604</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18.452</span>                                                          │\n",
       "│ DC2                            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.352</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">48.000</span>                                                          │\n",
       "│ Endothelial                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.118</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">37.985</span>                                                          │\n",
       "│ Enterocyte Progenitors        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.904</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13.670</span>                                                          │\n",
       "│ Enterocytes                   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.218</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.986</span>                                                          │\n",
       "│ Enteroendocrine               <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.266</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.518</span>                                                          │\n",
       "│ Follicular                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.828</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">77.261</span>                                                          │\n",
       "│ GC                            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.913</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13.547</span>                                                          │\n",
       "│ Glia                          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.104</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30.423</span>                                                          │\n",
       "│ Goblet                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.220</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.966</span>                                                          │\n",
       "│ ILCs                          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.845</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14.501</span>                                                          │\n",
       "│ Immature Enterocytes <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.067</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11.614</span>                                                          │\n",
       "│ Immature Enterocytes <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.826</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14.779</span>                                                          │\n",
       "│ Immature Goblet               <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.327</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">24.342</span>                                                          │\n",
       "│ Inflammatory Fibroblasts      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.970</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12.797</span>                                                          │\n",
       "│ Inflammatory Monocytes        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.537</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19.731</span>                                                          │\n",
       "│ M cells                       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.398</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8.341</span>                                                          │\n",
       "│ MT-hi                         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.716</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16.497</span>                                                          │\n",
       "│ Macrophages                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.572</span>           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">162.583</span>                                                          │\n",
       "│ Microvascular                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.298</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">25.058</span>                                                          │\n",
       "│ Myofibroblasts                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.014</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33.288</span>                                                          │\n",
       "│ NKs                           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.391</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">22.833</span>                                                          │\n",
       "│ Pericytes                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.682</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17.068</span>                                                          │\n",
       "│ Plasma                         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.580</span>          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1210.987</span>                                                          │\n",
       "│ Post-capillary Venules         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">34.062</span>                                                          │\n",
       "│ RSPO3+                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.617</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18.214</span>                                                          │\n",
       "│ Secretory TA                  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.912</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13.561</span>                                                          │\n",
       "│ Stem                          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.798</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15.198</span>                                                          │\n",
       "│ TA <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>                          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.018</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33.155</span>                                                          │\n",
       "│ TA <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>                          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.174</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">28.366</span>                                                          │\n",
       "│ Tregs                          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.682</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">66.766</span>                                                          │\n",
       "│ Tuft                          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.442</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7.982</span>                                                          │\n",
       "│ WNT2B+ Fos-hi                  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.738</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">70.611</span>                                                          │\n",
       "│ WNT2B+ Fos-lo <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.117</span>           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">103.151</span>                                                          │\n",
       "│ WNT2B+ Fos-lo <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.555</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">58.803</span>                                                          │\n",
       "│ WNT5B+ <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>                       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.384</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">49.560</span>                                                          │\n",
       "│ WNT5B+ <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>                       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.785</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">74.009</span>                                                          │\n",
       "└─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┌─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐\n",
       "│\u001b[1m \u001b[0m\u001b[1mIntercepts                                                                                                     \u001b[0m\u001b[1m \u001b[0m│\n",
       "├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤\n",
       "│                           Final Parameter  Expected Sample                                                      │\n",
       "│ Cell Type                                                                                                       │\n",
       "│ Best4+ Enterocytes            \u001b[1;36m-1.182\u001b[0m            \u001b[1;36m10.352\u001b[0m                                                          │\n",
       "│ CD4+ Activated Fos-hi          \u001b[1;36m1.561\u001b[0m           \u001b[1;36m160.805\u001b[0m                                                          │\n",
       "│ CD4+ Activated Fos-lo          \u001b[1;36m1.609\u001b[0m           \u001b[1;36m168.712\u001b[0m                                                          │\n",
       "│ CD4+ Memory                    \u001b[1;36m1.319\u001b[0m           \u001b[1;36m126.241\u001b[0m                                                          │\n",
       "│ CD4+ PD1+                     \u001b[1;36m-0.933\u001b[0m            \u001b[1;36m13.279\u001b[0m                                                          │\n",
       "│ CD8+ IELs                     \u001b[1;36m-0.112\u001b[0m            \u001b[1;36m30.180\u001b[0m                                                          │\n",
       "│ CD8+ IL17+                    \u001b[1;36m-0.803\u001b[0m            \u001b[1;36m15.123\u001b[0m                                                          │\n",
       "│ CD8+ LP                        \u001b[1;36m1.602\u001b[0m           \u001b[1;36m167.535\u001b[0m                                                          │\n",
       "│ CD69+ Mast                     \u001b[1;36m0.592\u001b[0m            \u001b[1;36m61.019\u001b[0m                                                          │\n",
       "│ CD69- Mast                    \u001b[1;36m-1.354\u001b[0m             \u001b[1;36m8.716\u001b[0m                                                          │\n",
       "│ Cycling B                     \u001b[1;36m-0.477\u001b[0m            \u001b[1;36m20.951\u001b[0m                                                          │\n",
       "│ Cycling Monocytes             \u001b[1;36m-0.568\u001b[0m            \u001b[1;36m19.129\u001b[0m                                                          │\n",
       "│ Cycling T                     \u001b[1;36m-0.700\u001b[0m            \u001b[1;36m16.763\u001b[0m                                                          │\n",
       "│ Cycling TA                     \u001b[1;36m0.090\u001b[0m            \u001b[1;36m36.936\u001b[0m                                                          │\n",
       "│ DC1                           \u001b[1;36m-0.604\u001b[0m            \u001b[1;36m18.452\u001b[0m                                                          │\n",
       "│ DC2                            \u001b[1;36m0.352\u001b[0m            \u001b[1;36m48.000\u001b[0m                                                          │\n",
       "│ Endothelial                    \u001b[1;36m0.118\u001b[0m            \u001b[1;36m37.985\u001b[0m                                                          │\n",
       "│ Enterocyte Progenitors        \u001b[1;36m-0.904\u001b[0m            \u001b[1;36m13.670\u001b[0m                                                          │\n",
       "│ Enterocytes                   \u001b[1;36m-1.218\u001b[0m             \u001b[1;36m9.986\u001b[0m                                                          │\n",
       "│ Enteroendocrine               \u001b[1;36m-1.266\u001b[0m             \u001b[1;36m9.518\u001b[0m                                                          │\n",
       "│ Follicular                     \u001b[1;36m0.828\u001b[0m            \u001b[1;36m77.261\u001b[0m                                                          │\n",
       "│ GC                            \u001b[1;36m-0.913\u001b[0m            \u001b[1;36m13.547\u001b[0m                                                          │\n",
       "│ Glia                          \u001b[1;36m-0.104\u001b[0m            \u001b[1;36m30.423\u001b[0m                                                          │\n",
       "│ Goblet                        \u001b[1;36m-1.220\u001b[0m             \u001b[1;36m9.966\u001b[0m                                                          │\n",
       "│ ILCs                          \u001b[1;36m-0.845\u001b[0m            \u001b[1;36m14.501\u001b[0m                                                          │\n",
       "│ Immature Enterocytes \u001b[1;36m1\u001b[0m        \u001b[1;36m-1.067\u001b[0m            \u001b[1;36m11.614\u001b[0m                                                          │\n",
       "│ Immature Enterocytes \u001b[1;36m2\u001b[0m        \u001b[1;36m-0.826\u001b[0m            \u001b[1;36m14.779\u001b[0m                                                          │\n",
       "│ Immature Goblet               \u001b[1;36m-0.327\u001b[0m            \u001b[1;36m24.342\u001b[0m                                                          │\n",
       "│ Inflammatory Fibroblasts      \u001b[1;36m-0.970\u001b[0m            \u001b[1;36m12.797\u001b[0m                                                          │\n",
       "│ Inflammatory Monocytes        \u001b[1;36m-0.537\u001b[0m            \u001b[1;36m19.731\u001b[0m                                                          │\n",
       "│ M cells                       \u001b[1;36m-1.398\u001b[0m             \u001b[1;36m8.341\u001b[0m                                                          │\n",
       "│ MT-hi                         \u001b[1;36m-0.716\u001b[0m            \u001b[1;36m16.497\u001b[0m                                                          │\n",
       "│ Macrophages                    \u001b[1;36m1.572\u001b[0m           \u001b[1;36m162.583\u001b[0m                                                          │\n",
       "│ Microvascular                 \u001b[1;36m-0.298\u001b[0m            \u001b[1;36m25.058\u001b[0m                                                          │\n",
       "│ Myofibroblasts                \u001b[1;36m-0.014\u001b[0m            \u001b[1;36m33.288\u001b[0m                                                          │\n",
       "│ NKs                           \u001b[1;36m-0.391\u001b[0m            \u001b[1;36m22.833\u001b[0m                                                          │\n",
       "│ Pericytes                     \u001b[1;36m-0.682\u001b[0m            \u001b[1;36m17.068\u001b[0m                                                          │\n",
       "│ Plasma                         \u001b[1;36m3.580\u001b[0m          \u001b[1;36m1210.987\u001b[0m                                                          │\n",
       "│ Post-capillary Venules         \u001b[1;36m0.009\u001b[0m            \u001b[1;36m34.062\u001b[0m                                                          │\n",
       "│ RSPO3+                        \u001b[1;36m-0.617\u001b[0m            \u001b[1;36m18.214\u001b[0m                                                          │\n",
       "│ Secretory TA                  \u001b[1;36m-0.912\u001b[0m            \u001b[1;36m13.561\u001b[0m                                                          │\n",
       "│ Stem                          \u001b[1;36m-0.798\u001b[0m            \u001b[1;36m15.198\u001b[0m                                                          │\n",
       "│ TA \u001b[1;36m1\u001b[0m                          \u001b[1;36m-0.018\u001b[0m            \u001b[1;36m33.155\u001b[0m                                                          │\n",
       "│ TA \u001b[1;36m2\u001b[0m                          \u001b[1;36m-0.174\u001b[0m            \u001b[1;36m28.366\u001b[0m                                                          │\n",
       "│ Tregs                          \u001b[1;36m0.682\u001b[0m            \u001b[1;36m66.766\u001b[0m                                                          │\n",
       "│ Tuft                          \u001b[1;36m-1.442\u001b[0m             \u001b[1;36m7.982\u001b[0m                                                          │\n",
       "│ WNT2B+ Fos-hi                  \u001b[1;36m0.738\u001b[0m            \u001b[1;36m70.611\u001b[0m                                                          │\n",
       "│ WNT2B+ Fos-lo \u001b[1;36m1\u001b[0m                \u001b[1;36m1.117\u001b[0m           \u001b[1;36m103.151\u001b[0m                                                          │\n",
       "│ WNT2B+ Fos-lo \u001b[1;36m2\u001b[0m                \u001b[1;36m0.555\u001b[0m            \u001b[1;36m58.803\u001b[0m                                                          │\n",
       "│ WNT5B+ \u001b[1;36m1\u001b[0m                       \u001b[1;36m0.384\u001b[0m            \u001b[1;36m49.560\u001b[0m                                                          │\n",
       "│ WNT5B+ \u001b[1;36m2\u001b[0m                       \u001b[1;36m0.785\u001b[0m            \u001b[1;36m74.009\u001b[0m                                                          │\n",
       "└─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┌─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐\n",
       "│<span style=\"font-weight: bold\"> Effects                                                                                                         </span>│\n",
       "├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤\n",
       "│                                                Effect  Expected Sample  log2-fold change                        │\n",
       "│ Covariate            Cell Type                                                                                  │\n",
       "│ HealthT.Non-inflamed Best4+ Enterocytes         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19.452</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      CD4+ Activated Fos-hi     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.676</span>     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">153.688</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.065</span>                             │\n",
       "│                      CD4+ Activated Fos-lo     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.031</span>     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">113.061</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.577</span>                             │\n",
       "│                      CD4+ Memory               <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.676</span>     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">120.654</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.065</span>                             │\n",
       "│                      CD4+ PD1+                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.676</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12.691</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.065</span>                             │\n",
       "│                      CD8+ IELs                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.676</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">28.845</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.065</span>                             │\n",
       "│                      CD8+ IL17+                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.676</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14.453</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.065</span>                             │\n",
       "│                      CD8+ LP                   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.676</span>     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">160.120</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.065</span>                             │\n",
       "│                      CD69+ Mast                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.262</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">88.228</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.532</span>                             │\n",
       "│                      CD69- Mast                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.262</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12.603</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.532</span>                             │\n",
       "│                      Cycling B                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.710</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19.355</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.114</span>                             │\n",
       "│                      Cycling Monocytes         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.603</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19.667</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.040</span>                             │\n",
       "│                      Cycling T                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.676</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16.021</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.065</span>                             │\n",
       "│                      Cycling TA                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">69.403</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      DC1                       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.603</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18.971</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.040</span>                             │\n",
       "│                      DC2                       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.603</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">49.349</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.040</span>                             │\n",
       "│                      Endothelial               <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.369</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">49.349</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378</span>                             │\n",
       "│                      Enterocyte Progenitors     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">25.685</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      Enterocytes                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18.764</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      Enteroendocrine            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17.884</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      Follicular                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.710</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">71.373</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.114</span>                             │\n",
       "│                      GC                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.710</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12.515</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.114</span>                             │\n",
       "│                      Glia                      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.369</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">39.525</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378</span>                             │\n",
       "│                      Goblet                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18.726</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      ILCs                       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">27.247</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      Immature Enterocytes <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">21.822</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      Immature Enterocytes <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">27.769</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      Immature Goblet            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">45.738</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      Inflammatory Fibroblasts  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.369</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16.625</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378</span>                             │\n",
       "│                      Inflammatory Monocytes    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.603</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20.286</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.040</span>                             │\n",
       "│                      M cells                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15.673</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      MT-hi                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.676</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15.767</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.065</span>                             │\n",
       "│                      Macrophages               <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.603</span>     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">167.156</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.040</span>                             │\n",
       "│                      Microvascular             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.369</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">32.555</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378</span>                             │\n",
       "│                      Myofibroblasts            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.369</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">43.247</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378</span>                             │\n",
       "│                      NKs                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">42.902</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      Pericytes                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.369</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">22.174</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378</span>                             │\n",
       "│                      Plasma                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.048</span>     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">797.854</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.602</span>                             │\n",
       "│                      Post-capillary Venules    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.369</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">44.253</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378</span>                             │\n",
       "│                      RSPO3+                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.369</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">23.663</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378</span>                             │\n",
       "│                      Secretory TA               <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">25.481</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      Stem                       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">28.558</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      TA <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>                       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.336</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">87.176</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.395</span>                             │\n",
       "│                      TA <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>                       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.336</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">74.584</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.395</span>                             │\n",
       "│                      Tregs                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.676</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">63.811</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.065</span>                             │\n",
       "│                      Tuft                       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.000</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14.998</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.910</span>                             │\n",
       "│                      WNT2B+ Fos-hi             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.369</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">91.737</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378</span>                             │\n",
       "│                      WNT2B+ Fos-lo <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.369</span>     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">134.012</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378</span>                             │\n",
       "│                      WNT2B+ Fos-lo <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.369</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">76.396</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378</span>                             │\n",
       "│                      WNT5B+ <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>                  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.369</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">64.388</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378</span>                             │\n",
       "│                      WNT5B+ <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>                  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.369</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">96.152</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.378</span>                             │\n",
       "└─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┌─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐\n",
       "│\u001b[1m \u001b[0m\u001b[1mEffects                                                                                                        \u001b[0m\u001b[1m \u001b[0m│\n",
       "├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤\n",
       "│                                                Effect  Expected Sample  log2-fold change                        │\n",
       "│ Covariate            Cell Type                                                                                  │\n",
       "│ HealthT.Non-inflamed Best4+ Enterocytes         \u001b[1;36m0.000\u001b[0m      \u001b[1;36m19.452\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      CD4+ Activated Fos-hi     \u001b[1;36m-0.676\u001b[0m     \u001b[1;36m153.688\u001b[0m            \u001b[1;36m-0.065\u001b[0m                             │\n",
       "│                      CD4+ Activated Fos-lo     \u001b[1;36m-1.031\u001b[0m     \u001b[1;36m113.061\u001b[0m            \u001b[1;36m-0.577\u001b[0m                             │\n",
       "│                      CD4+ Memory               \u001b[1;36m-0.676\u001b[0m     \u001b[1;36m120.654\u001b[0m            \u001b[1;36m-0.065\u001b[0m                             │\n",
       "│                      CD4+ PD1+                 \u001b[1;36m-0.676\u001b[0m      \u001b[1;36m12.691\u001b[0m            \u001b[1;36m-0.065\u001b[0m                             │\n",
       "│                      CD8+ IELs                 \u001b[1;36m-0.676\u001b[0m      \u001b[1;36m28.845\u001b[0m            \u001b[1;36m-0.065\u001b[0m                             │\n",
       "│                      CD8+ IL17+                \u001b[1;36m-0.676\u001b[0m      \u001b[1;36m14.453\u001b[0m            \u001b[1;36m-0.065\u001b[0m                             │\n",
       "│                      CD8+ LP                   \u001b[1;36m-0.676\u001b[0m     \u001b[1;36m160.120\u001b[0m            \u001b[1;36m-0.065\u001b[0m                             │\n",
       "│                      CD69+ Mast                \u001b[1;36m-0.262\u001b[0m      \u001b[1;36m88.228\u001b[0m             \u001b[1;36m0.532\u001b[0m                             │\n",
       "│                      CD69- Mast                \u001b[1;36m-0.262\u001b[0m      \u001b[1;36m12.603\u001b[0m             \u001b[1;36m0.532\u001b[0m                             │\n",
       "│                      Cycling B                 \u001b[1;36m-0.710\u001b[0m      \u001b[1;36m19.355\u001b[0m            \u001b[1;36m-0.114\u001b[0m                             │\n",
       "│                      Cycling Monocytes         \u001b[1;36m-0.603\u001b[0m      \u001b[1;36m19.667\u001b[0m             \u001b[1;36m0.040\u001b[0m                             │\n",
       "│                      Cycling T                 \u001b[1;36m-0.676\u001b[0m      \u001b[1;36m16.021\u001b[0m            \u001b[1;36m-0.065\u001b[0m                             │\n",
       "│                      Cycling TA                 \u001b[1;36m0.000\u001b[0m      \u001b[1;36m69.403\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      DC1                       \u001b[1;36m-0.603\u001b[0m      \u001b[1;36m18.971\u001b[0m             \u001b[1;36m0.040\u001b[0m                             │\n",
       "│                      DC2                       \u001b[1;36m-0.603\u001b[0m      \u001b[1;36m49.349\u001b[0m             \u001b[1;36m0.040\u001b[0m                             │\n",
       "│                      Endothelial               \u001b[1;36m-0.369\u001b[0m      \u001b[1;36m49.349\u001b[0m             \u001b[1;36m0.378\u001b[0m                             │\n",
       "│                      Enterocyte Progenitors     \u001b[1;36m0.000\u001b[0m      \u001b[1;36m25.685\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      Enterocytes                \u001b[1;36m0.000\u001b[0m      \u001b[1;36m18.764\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      Enteroendocrine            \u001b[1;36m0.000\u001b[0m      \u001b[1;36m17.884\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      Follicular                \u001b[1;36m-0.710\u001b[0m      \u001b[1;36m71.373\u001b[0m            \u001b[1;36m-0.114\u001b[0m                             │\n",
       "│                      GC                        \u001b[1;36m-0.710\u001b[0m      \u001b[1;36m12.515\u001b[0m            \u001b[1;36m-0.114\u001b[0m                             │\n",
       "│                      Glia                      \u001b[1;36m-0.369\u001b[0m      \u001b[1;36m39.525\u001b[0m             \u001b[1;36m0.378\u001b[0m                             │\n",
       "│                      Goblet                     \u001b[1;36m0.000\u001b[0m      \u001b[1;36m18.726\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      ILCs                       \u001b[1;36m0.000\u001b[0m      \u001b[1;36m27.247\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      Immature Enterocytes \u001b[1;36m1\u001b[0m     \u001b[1;36m0.000\u001b[0m      \u001b[1;36m21.822\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      Immature Enterocytes \u001b[1;36m2\u001b[0m     \u001b[1;36m0.000\u001b[0m      \u001b[1;36m27.769\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      Immature Goblet            \u001b[1;36m0.000\u001b[0m      \u001b[1;36m45.738\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      Inflammatory Fibroblasts  \u001b[1;36m-0.369\u001b[0m      \u001b[1;36m16.625\u001b[0m             \u001b[1;36m0.378\u001b[0m                             │\n",
       "│                      Inflammatory Monocytes    \u001b[1;36m-0.603\u001b[0m      \u001b[1;36m20.286\u001b[0m             \u001b[1;36m0.040\u001b[0m                             │\n",
       "│                      M cells                    \u001b[1;36m0.000\u001b[0m      \u001b[1;36m15.673\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      MT-hi                     \u001b[1;36m-0.676\u001b[0m      \u001b[1;36m15.767\u001b[0m            \u001b[1;36m-0.065\u001b[0m                             │\n",
       "│                      Macrophages               \u001b[1;36m-0.603\u001b[0m     \u001b[1;36m167.156\u001b[0m             \u001b[1;36m0.040\u001b[0m                             │\n",
       "│                      Microvascular             \u001b[1;36m-0.369\u001b[0m      \u001b[1;36m32.555\u001b[0m             \u001b[1;36m0.378\u001b[0m                             │\n",
       "│                      Myofibroblasts            \u001b[1;36m-0.369\u001b[0m      \u001b[1;36m43.247\u001b[0m             \u001b[1;36m0.378\u001b[0m                             │\n",
       "│                      NKs                        \u001b[1;36m0.000\u001b[0m      \u001b[1;36m42.902\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      Pericytes                 \u001b[1;36m-0.369\u001b[0m      \u001b[1;36m22.174\u001b[0m             \u001b[1;36m0.378\u001b[0m                             │\n",
       "│                      Plasma                    \u001b[1;36m-1.048\u001b[0m     \u001b[1;36m797.854\u001b[0m            \u001b[1;36m-0.602\u001b[0m                             │\n",
       "│                      Post-capillary Venules    \u001b[1;36m-0.369\u001b[0m      \u001b[1;36m44.253\u001b[0m             \u001b[1;36m0.378\u001b[0m                             │\n",
       "│                      RSPO3+                    \u001b[1;36m-0.369\u001b[0m      \u001b[1;36m23.663\u001b[0m             \u001b[1;36m0.378\u001b[0m                             │\n",
       "│                      Secretory TA               \u001b[1;36m0.000\u001b[0m      \u001b[1;36m25.481\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      Stem                       \u001b[1;36m0.000\u001b[0m      \u001b[1;36m28.558\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      TA \u001b[1;36m1\u001b[0m                       \u001b[1;36m0.336\u001b[0m      \u001b[1;36m87.176\u001b[0m             \u001b[1;36m1.395\u001b[0m                             │\n",
       "│                      TA \u001b[1;36m2\u001b[0m                       \u001b[1;36m0.336\u001b[0m      \u001b[1;36m74.584\u001b[0m             \u001b[1;36m1.395\u001b[0m                             │\n",
       "│                      Tregs                     \u001b[1;36m-0.676\u001b[0m      \u001b[1;36m63.811\u001b[0m            \u001b[1;36m-0.065\u001b[0m                             │\n",
       "│                      Tuft                       \u001b[1;36m0.000\u001b[0m      \u001b[1;36m14.998\u001b[0m             \u001b[1;36m0.910\u001b[0m                             │\n",
       "│                      WNT2B+ Fos-hi             \u001b[1;36m-0.369\u001b[0m      \u001b[1;36m91.737\u001b[0m             \u001b[1;36m0.378\u001b[0m                             │\n",
       "│                      WNT2B+ Fos-lo \u001b[1;36m1\u001b[0m           \u001b[1;36m-0.369\u001b[0m     \u001b[1;36m134.012\u001b[0m             \u001b[1;36m0.378\u001b[0m                             │\n",
       "│                      WNT2B+ Fos-lo \u001b[1;36m2\u001b[0m           \u001b[1;36m-0.369\u001b[0m      \u001b[1;36m76.396\u001b[0m             \u001b[1;36m0.378\u001b[0m                             │\n",
       "│                      WNT5B+ \u001b[1;36m1\u001b[0m                  \u001b[1;36m-0.369\u001b[0m      \u001b[1;36m64.388\u001b[0m             \u001b[1;36m0.378\u001b[0m                             │\n",
       "│                      WNT5B+ \u001b[1;36m2\u001b[0m                  \u001b[1;36m-0.369\u001b[0m      \u001b[1;36m96.152\u001b[0m             \u001b[1;36m0.378\u001b[0m                             │\n",
       "└─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┌─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐\n",
       "│<span style=\"font-weight: bold\"> Nodes                                                                                                           </span>│\n",
       "├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤\n",
       "│ <span style=\"color: #808000; text-decoration-color: #808000\">Covariate</span>=<span style=\"color: #800080; text-decoration-color: #800080\">Health</span><span style=\"font-weight: bold\">[</span>T.Non-inflamed<span style=\"font-weight: bold\">]</span>_node                                                                           │\n",
       "├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤\n",
       "│                                   Final Parameter  Is credible                                                  │\n",
       "│ Node                                                                                                            │\n",
       "│ Major_l1_Immune                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l2_Stromal                      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.37</span>            <span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>                                                     │\n",
       "│ Major_l2_Epithelial                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l2_Lymphoid                      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l2_Myeloid                      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.26</span>            <span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>                                                     │\n",
       "│ Major_l3_Fibroblasts                   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l4_EndothelialCells              <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Glia                                   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l3_Absorptive                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l3_Secretory                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Cycling TA                             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ M cells                                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Stem                                   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l3_B cells                      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.71</span>            <span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>                                                     │\n",
       "│ Major_l3_T cells                      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.68</span>            <span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>                                                     │\n",
       "│ ILCs                                   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ NKs                                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l3_Monocytes                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.34</span>            <span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>                                                     │\n",
       "│ Major_l3_Mast                          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l4_WNT2B+                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l4_WNT5B+                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Myofibroblasts                         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Inflammatory Fibroblasts               <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Pericytes                              <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Microvascular                          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Endothelial                            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Post-capillary Venules                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l4_TA cells                      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.34</span>            <span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>                                                     │\n",
       "│ Major_l4_Immature cells                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l4_Absorptive Mature cells       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l4_Progenitor cells              <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l4_Secretory Mature cells        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Plasma                                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.34</span>            <span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>                                                     │\n",
       "│ Cycling B                              <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Follicular                             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ GC                                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l4_CD8+ T                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l4_CD4+ T                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Major_l4_DCs                           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Macrophages                            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Cycling Monocytes                      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Inflammatory Monocytes                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ CD69+ Mast                             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ CD69- Mast                             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ WNT2B+ Fos-lo <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ WNT2B+ Fos-hi                          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ WNT2B+ Fos-lo <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ RSPO3+                                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ WNT5B+ <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>                               <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ WNT5B+ <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>                               <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ TA <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>                                   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ TA <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>                                   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Enterocyte Progenitors                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Immature Enterocytes <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Immature Enterocytes <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Best4+ Enterocytes                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Enterocytes                            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Immature Goblet                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Secretory TA                           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Goblet                                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Enteroendocrine                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Tuft                                   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ CD8+ IELs                              <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Cycling T                              <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ CD8+ IL17+                             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ CD8+ LP                                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ Tregs                                  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ CD4+ Activated Fos-hi                  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ CD4+ Activated Fos-lo                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.35</span>            <span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>                                                     │\n",
       "│ CD4+ PD1+                              <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ CD4+ Memory                            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ MT-hi                                  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ DC2                                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "│ DC1                                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00</span>           <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                     │\n",
       "└─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┌─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐\n",
       "│\u001b[1m \u001b[0m\u001b[1mNodes                                                                                                          \u001b[0m\u001b[1m \u001b[0m│\n",
       "├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤\n",
       "│ \u001b[33mCovariate\u001b[0m=\u001b[35mHealth\u001b[0m\u001b[1m[\u001b[0mT.Non-inflamed\u001b[1m]\u001b[0m_node                                                                           │\n",
       "├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤\n",
       "│                                   Final Parameter  Is credible                                                  │\n",
       "│ Node                                                                                                            │\n",
       "│ Major_l1_Immune                        \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l2_Stromal                      \u001b[1;36m-0.37\u001b[0m            \u001b[3;92mTrue\u001b[0m                                                     │\n",
       "│ Major_l2_Epithelial                    \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l2_Lymphoid                      \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l2_Myeloid                      \u001b[1;36m-0.26\u001b[0m            \u001b[3;92mTrue\u001b[0m                                                     │\n",
       "│ Major_l3_Fibroblasts                   \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l4_EndothelialCells              \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Glia                                   \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l3_Absorptive                    \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l3_Secretory                     \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Cycling TA                             \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ M cells                                \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Stem                                   \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l3_B cells                      \u001b[1;36m-0.71\u001b[0m            \u001b[3;92mTrue\u001b[0m                                                     │\n",
       "│ Major_l3_T cells                      \u001b[1;36m-0.68\u001b[0m            \u001b[3;92mTrue\u001b[0m                                                     │\n",
       "│ ILCs                                   \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ NKs                                    \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l3_Monocytes                    \u001b[1;36m-0.34\u001b[0m            \u001b[3;92mTrue\u001b[0m                                                     │\n",
       "│ Major_l3_Mast                          \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l4_WNT2B+                        \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l4_WNT5B+                        \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Myofibroblasts                         \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Inflammatory Fibroblasts               \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Pericytes                              \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Microvascular                          \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Endothelial                            \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Post-capillary Venules                 \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l4_TA cells                      \u001b[1;36m0.34\u001b[0m            \u001b[3;92mTrue\u001b[0m                                                     │\n",
       "│ Major_l4_Immature cells                \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l4_Absorptive Mature cells       \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l4_Progenitor cells              \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l4_Secretory Mature cells        \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Plasma                                \u001b[1;36m-0.34\u001b[0m            \u001b[3;92mTrue\u001b[0m                                                     │\n",
       "│ Cycling B                              \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Follicular                             \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ GC                                     \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l4_CD8+ T                        \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l4_CD4+ T                        \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l4_DCs                           \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Macrophages                            \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Cycling Monocytes                      \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Inflammatory Monocytes                 \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ CD69+ Mast                             \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ CD69- Mast                             \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ WNT2B+ Fos-lo \u001b[1;36m1\u001b[0m                        \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ WNT2B+ Fos-hi                          \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ WNT2B+ Fos-lo \u001b[1;36m2\u001b[0m                        \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ RSPO3+                                 \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ WNT5B+ \u001b[1;36m2\u001b[0m                               \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ WNT5B+ \u001b[1;36m1\u001b[0m                               \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ TA \u001b[1;36m1\u001b[0m                                   \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ TA \u001b[1;36m2\u001b[0m                                   \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Enterocyte Progenitors                 \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Immature Enterocytes \u001b[1;36m2\u001b[0m                 \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Immature Enterocytes \u001b[1;36m1\u001b[0m                 \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Best4+ Enterocytes                     \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Enterocytes                            \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Immature Goblet                        \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Secretory TA                           \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Goblet                                 \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Enteroendocrine                        \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Tuft                                   \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ CD8+ IELs                              \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Cycling T                              \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ CD8+ IL17+                             \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ CD8+ LP                                \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Tregs                                  \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ CD4+ Activated Fos-hi                  \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ CD4+ Activated Fos-lo                 \u001b[1;36m-0.35\u001b[0m            \u001b[3;92mTrue\u001b[0m                                                     │\n",
       "│ CD4+ PD1+                              \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ CD4+ Memory                            \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ MT-hi                                  \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ DC2                                    \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ DC1                                    \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "└─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tasccoda_model.summary(smillie_data, modality_key=\"coda_LP\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Model properties**\n",
    "\n",
    "First, the summary shows an overview over the model properties:\n",
    "* Number of samples/cell types\n",
    "* The reference cell type.\n",
    "* The formula used\n",
    "\n",
    "The model has three types of parameters that are relevant for analysis - intercepts, feature-level effects and node-wise effects.\n",
    "These can be interpreted like in a standard regression model:\n",
    "Intercepts show how the cell types are distributed without any active covariates, effects show how the covariates influence the cell types.\n",
    "\n",
    "**Intercepts**\n",
    "\n",
    "The first column of the intercept summary shows the parameters determined by the MCMC inference.\n",
    "\n",
    "The \"Expected sample\" column gives some context to the numerical values.\n",
    "If we had a new sample (with no active covariates) with a total number of cells equal to the mean sampling depth of the dataset,\n",
    "then this distribution over the cell types would be most likely.\n",
    "\n",
    "**Feature-level Effects**\n",
    "\n",
    "For the feature-level effect summary, the first column again shows the inferred parameters for all combinations of covariates and cell types, as sums over node-level effects on all parent nodes.\n",
    "Most important is the distinction between zero and non-zero entries\n",
    "A value of zero means that no statistically credible effect was detected.\n",
    "For a value other than zero, a credible change was detected. A positive sign indicates an increase, a negative sign a decrease in abundance.\n",
    "\n",
    "Since the numerical values of the \"Effect\" column are not straightforward to interpret, the \"Expected sample\" and \"log2-fold change\" columns give us an idea on the magnitude of the change.\n",
    "The expected sample is calculated for each covariate separately (covariate value = 1, all other covariates = 0), with the same method as for the intercepts.\n",
    "The log-fold change is then calculated between this expected sample and the expected sample with no active covariates from the intercept section.\n",
    "Since the data is compositional, cell types for which no credible change was detected, will still change in abundance as well, as soon as a credible effect is detected on another cell type due to the sum-to-one constraint.\n",
    "If there are no credible effects for a covariate, its expected sample will be identical to the intercept sample, therefore the log2-fold change is 0.\n",
    "\n",
    "**Node-level effects**\n",
    "\n",
    "These parameters are the most important ones. They describe, at which points in the tree a credible change in abundance was detected. The data frame just has two columns:\n",
    "The \"Final Parameter\" column shows the effect values, the \"Is credible\" column simply depicts whether the inferred effect is different from 0, i.e. credible.\n",
    "In a normal tascCODA analysis, we are interested in which subtrees (i.e. nodes) have a nonzero effect, which we can easily extract:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-30T11:02:20.389918Z",
     "start_time": "2023-11-30T11:02:20.386835Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Covariate                    Node               \n",
       "Health[T.Non-inflamed]_node  Major_l1_Immune        False\n",
       "                             Major_l2_Stromal        True\n",
       "                             Major_l2_Epithelial    False\n",
       "                             Major_l2_Lymphoid      False\n",
       "                             Major_l2_Myeloid        True\n",
       "                                                    ...  \n",
       "                             CD4+ PD1+              False\n",
       "                             CD4+ Memory            False\n",
       "                             MT-hi                  False\n",
       "                             DC2                    False\n",
       "                             DC1                    False\n",
       "Name: Final Parameter, Length: 74, dtype: bool"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tasccoda_model.credible_effects(smillie_data, modality_key=\"coda_LP\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "**Interpretation**\n",
    "\n",
    "We see that most credible effects are on intermediate nodes. The only slight increase in abundance is on TA cells, while there are decreases on Stromal and some Immune cell types.\n",
    "The most important decreases (i.e. with the largest effect sizes) can be found on B- and T-cells.\n",
    "Plasma cells have an additional decrease, meaning that they change even stronger in abundance than the rest of the B-cell lineage.\n",
    "\n",
    "We can also easily plot the credible effects as nodes on the tree for better visualization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-30T11:02:25.928197Z",
     "start_time": "2023-11-30T11:02:25.876554Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tasccoda_model.plot_draw_effects(\n",
    "    smillie_data,\n",
    "    modality_key=\"coda_LP\",\n",
    "    tree=smillie_data[\"coda_LP\"].uns[\"tree\"],\n",
    "    covariate=\"Health[T.Non-inflamed]\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To better see the size of aggregated effects on the individual cell types, we can plot them at the side of the tree plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-29T09:48:16.921293Z",
     "start_time": "2023-11-29T09:48:16.906038Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAM9CAYAAABkOBctAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdeViVdf7/8ed9Vjgc9n0HAVHBHRc0tzRzKy3b1MrWaZvKppmmpmn2XzVa820qZ6Z92sc226zUyn3fFVAEFAQBAdk5+zn37w+GMxJqrqDxflwXV3DOfT7nfe6bGe8Xn01RVVVFCCGEEEIIITqBpqsLEEIIIYQQQnQfEkCEEEIIIYQQnUYCiBBCCCGEEKLTSAARQgghhBBCdBoJIEIIIYQQQohOIwFECCGEEEII0WkkgAghhBBCCCE6jQQQIYQQQgghRKeRACKEEEIIIYToNBJAhBBCCCGEEJ1GAogQQghxFlS3u6tLEJ1MrrkQZ0dRVVXt6iKEEEKIi1n1vHk4Cwu7ugzRCfSpqYQ/91xXlyHERU3X1QUIIYQQFztnYSGO3NyuLkMIIS4KMgRLCCGEEEII0WkkgAghhBBCCCE6jQQQIYQQQgghRKeRACKEEEIIIYToNBJAhBBCCCGEEJ1GAogQQgghhBCi00gAEUIIIYQQQnQaCSBCCCGEEEKITiMbEQohhBBnSZ+a2tUliE4i11qIs6eoqqp2dRFCCCHExUp1u1G02q4uQ3QiueZCnB0JIEIIIYQQQohOI3NAhBBCCCGEEJ1GAogQQghxFlS3u6tLEJ1MrrkQZ0eGYAnRzdXX11NSUkJxcTF2u53ExEQGDx6MqqqsX78em82GVqslICCA6Oho4uPj272+urqaHTt24HA4SE5OJikpCT8/vzOqJScnh8rKStxuN3FxccTGxmK1Wtm9e3e748xmM4MGDeLgwYMYDAaio6PP+D2FOBeq583DWVjY1WWITqBPTSX8uee6ugwhLmqyCpYQ3diePXtYu3YtxcXFmM1m3G43mzdvZv/+/UydOpWXXnqJmJgYAgICcDqdAMTGxnLttdcSEhJCZWUlzz33HBEREWg0GjZt2kRaWhpXX301ZrMZAFVVcTgcFBcXk5CQgK+v7wnrqays5MMPP8RgMDBhwgQCAwPZv38/CxcuZNCgQd7jwsPDycjIYNmyZYSEhHDppZdKABFdyllYiCM3t6vLEEKIi4IMwRKim6qtreXrr79m+/btBAcHk5mZyYABA4iLi8PpdOJwOFi7di1ms5nU1FTi4uLweDysXbuWjz/+GGgNMN988w1RUVH06dOHiooK1q5dS3V1dbv3am5u5tNPP6Wuru6kNUVFRVFWVobFYsFoNKLX66msrGTbtm2kp6d7v5KTk9Hr9ezdu5eioiJaWlq8bbQFnqVLl/Lmm2/y1ltvsWbNGqqqqs79SRRCCCHEaZMeECG6qaKiIrZu3Urfvn25//77vT0IqqridDppbGwEYMyYMYwbNw6AsrIy3n//fV544QVuu+02GhoaCAgIwMfHh6ioKGJjY2lsbMThcLR7r+bmZr755huuvPJKYmJiTlhTZmYmMTExpKamkpSUhL+/PwAGg4FevXp5j/Px8UGv1x+3DVVVKS4u5sUXX0RVVRRFYfDgwfj5+REREXHmJ0wIIYQQ54QEENFteTwe7HY7VVVVuC/ACYUajYaAgAACAgLQarU0NjZiMpnQ6/XY7XYcDgf+/v6oqkp9fT1BQUEoinLK7ZeUlODv7098fHy74UuKomAwGI77moiICEaNGsWf//xnmpubGT16NC+88ALz588nOjoajUbDqFGjSE5Oxu12U1NTg8PhoKKiArvdTmVlJWazGR8fH8xm80mHYx2rpqaGP/7xj96fExIS+O1vf3vcY91uN9999x01NTW8/vrraDQaKisrCQgIOOVzI4QQQojzRwKI6LasVivr1q1jzpw5WCyWri6nAx8fH+655x7uvvtuYmJieO+995g0aRLJycns2bOH/fv3M3v2bJxOJ//85z959NFHTyuAOBwOFEVBq9V6ewp+jEajwWg0AmCxWDh06BAul4u5c+eSk5PDzp07KSkpoaamBoPBwEMPPUROTg4Oh4PS0lLuuusufHx8GD58OLNnz2bs2LGnVGtwcDD33nuvt0Y/Pz9v78jxakxMTKSkpISXX36ZkSNHMnz4cKKjo0/txAghhBDivJIAIroti8XC/v37ufbaa1m4cOFp3bx3Fo/Hw5///GceffRR7rnnHu/jWVlZZGVlAa3Dk37zm9+cdtvx8fHU19dTUVGBx+NBoznxlLC2xfLq6+vJyckhLi6O6Ohofve73zFhwgSuvfZa7rnnHl555RXWr1/P999/z6xZs3jhhRdwOp2Ulpby4IMP8te//pW0tDQMBgMmk+mUa/Xz82PixImndKxGo2Hy5Mm88cYbfP755zz22GMMGDCAu+66iwkTJpzyewohhBDi/JAAIsQFTFEUnnjiifMSjrKysoiIiGDVqlXExsYya9Ys3G43O3bsYNWqVdx0003eYz0eD2VlZSxevJg33niDhx9+GIC0tDQ2bNiA1WoFWkOd2+0mODgYjUZDSEgIAHa7HaPRSFhYGJGRkef8sxzL4/GwadMmBg4cyPjx41m+fDlvvvkmJSUl5/V9hRBCCHFqJIAIcQFTFOW89cz4+Phw//3385///Idnn32W3//+92i1WjweD7/4xS+8x91www34+vri5+dHz549+cUvfsH1118PwE033cSmTZu44YYbUFWV0NBQpk6dyvjx4711q6qKXq8nKioKvV5/0s/z5z//mW+++QZVVWlpaeHqq68GoKCggKioKO9x6enpvPPOOwC8/vrrLFy4EJ1Oh1arJS4ujp/97GfMmTOHmJgY3G4306ZNIzs7+5yfQyGEEEKcPtmIUHRb1dXVLFq0iLy8vAt2CNb55nA4qKur4+jRozQ1NWG32wkNDSUqKoqAgAAKCwtxu90oioJGo8HX15egoCCCgoJQVRW3283hw4epq6tDURRMJhOhoaEEBwe3CyAul4uKigoiIyO9c0iOp7KyktraWlRVJSQkhKCgIGw2G6Wlpe2uj9FoJCkpiaqqKhobG72LCCiKgl6vJywsjLKyMqxWK4GBgYSGhhIYGHjS9xbibJRPmyb7gHQThowMYr78sqvLEOKiJj0gQnRjBoOByMhIwsPDcbvduN1u7026oij07t37hK9VFAWdTkdiYiKxsbFA6/yLH84laQsFCQkJP1pPVFRUu54OAF9fX4KDg497fFxc3HEfV1WV4OBgnE4ner3+pPNbhDgX9KmpXV2C6CRyrYU4exJAhBDe4HCivTV+jE53Yf1fSdvQNenxEJ1BdbsJf+65ri5DdCLV7UbRaru6DCEuWvJnQSGEEOIsyI1o9yPXXIizIwFECCGEEEII0WkurHETQohO53a7cblcOJ1OVFVFp9Ph4+MDtG7W2LZJoUajQavVdhim5Xa7sdls3tWuzmbOhcvlwuVyYTAY2rWhqioOhwOXywWAVqvFYDCc11XChDhVMhyn+5FrLsTZkQAiRDfmdrs5cuQIubm55OXlYbPZ6NWrF5dddhkajYbFixdjtVrR6/UEBwfTo0cP0tPTvXM+VFWlpKSEFStW4HA46N27N5mZmYSGhrYLBqqqeoPMyQJDaWkp+/btY+jQoYSGhnoft1qtbNmyhf3796PRaIiKimL48OEEBQWh0WgkhIgupWi1VM+bh7OwsKtLEZ1An5oqc36EOEsSQIToplRV5csvv+S9996jsrKS7OxsFEXh+eefZ/HixTz55JM89thjDB06lPDwcI4cOcLhw4cJDQ3lxRdfJDk5mby8PK666irmzJmDyWTiqaeeIjExkSeffJKwsDDv+1gsFtavX8/QoUMJDAw8YU07duzg9ddfJzY2tl0AaWxs5P3332fnzp1kZWWRl5dHS0sL8+fPZ+TIkRfcJHjR/TgLC2UZXiGEOEXyr7YQ3dTevXt5++23SUtL45///CcBAQFAa2Cw2+3YbDYA7r77bsaOHYuqqhw4cIDXXnuNm2++mTVr1rB69WoiIyO5/vrrSU1NRVEU9u/fT0lJiTeAABw9epS//vWvvPDCCycNICej1+u5/PLL+e1vfwvAuHHjyMnJIS0tjZiYmLM8G0IIIYToLDIJXYhuqqCgAH9/f1JSUggKCkKn03m//Pz8vMdptVp0Op13L4/JkyeTl5dHc3Mz06dPR6vVcscdd3D77beza9cu+vTpQ0ZGRrv3atu08Gy17T1SWFhITU0N/v7+7WoVQgghxIVPekBEt+ZwOFiyZAnbtm3r6lI6MBgMXHfddcyePZuQkBA++OADLrnkEmJjY8nNzaWkpIQpU6bgdDp58803ue22205r8rfFYkGn02E0Gtu97mTzKfR6PUFBQTidTlpaWqirq8PhcDB+/HhKS0spKSkhLi6OlpYWbDYbTz/9NIWFhbS0tJCTk8ODDz5IQEAA/fr1Y/LkyQwZMuSU63U6nXzyySfk5ORw6NAhxo0bx8CBAzGbzafchhBCCCG6ngQQ0a1ptVp69+7NTTfd1NWldKDVaunZsydLly7l2muvZcCAAd7hS1FRUfj6+gKtmwgOGzbstCdiBwcH09LSQn19PR6P55TCi8Vi4fDhw4SEhBAQEMCbb75JZmYmM2bMwOVysXjxYmpra9m5cycjRoxgzJgxZGRkUFNTQ3FxMePHjycmJobo6OgOO57/GEVRSEhIYMKECfj5+dG3b1+Sk5PRyko0QgghxEVFAojo1rRaLT169GD27NkX5EpKqqrS0NCAoiikp6d7Hw8NDfVO0tZqtfTt2/e0205LS0Ov17Nv3z5ycnLo27cvHo+HyspKSkpKSE1N9R7r8XhobGxkx44dfPXVV0yYMAFfX1+OHj2KRqMhNjaWqKgotm3bRmVlJfX19RiNRsaMGYPb7aa0tJTFixczfvx47ypap7vrularpVevXlx99dUEBQWh1+svyGsmhBBCiJOTACLEBUxRFMaNG3de2o6Pj2fQoEFs3bqVDz74gIMHDwJw8OBBPB4PPXr0AGDdunXU19fT0NBAfn4+NTU13H333QBkZWXx3nvvsXLlSkJDQyktLSU0NJSkpCQ0Gg0mkwlVVb1zNfz9/fH39z9pXbW1tXz33XcU/ndJ08DAQIKDg1EUBbPZTHh4uAQPIYQQ4iImAUSIbspgMHDNNddgMplYsmQJK1euRKPRoNfrueeee9Dr9fTp04cvv/ySb775Bj8/P9LT07njjju49NJLUVWVyy+/nI0bN/Lhhx/i8XiIiopi4sSJDBw4sN17+fj4MHDgQEwm00lrCgoKwmg08s4773hDRs+ePbnqqquIjY0lKCjofJ0OIYQQQnQSRVVVtauLEKIrVFdXs2jRIvLy8li4cGG3/qu6y+XCYrFgtVqJiIgATj4Z/Yeam5vRaDQYDAbZk0N0S+XTpsk+IN2EISODmC+/7OoyhLioyZ2COK/adsC+EHOux+O5IOvqCjqdjoCAAO9eIKdLVqISQgghxKmSACLOq4qKCt59910sFktXl9JBS0sL+fn5REZGdnUpQoiLnP6YRRvET5tcayHOngQQcd4UFBTw0Ucf8e233zJq1KiuLqcDVVVRFMU75EgIIc6E6nYT/txzXV2G6ESq240iS4ALccYkgIjzxuPxoNfr6devH/Pmzevqcjo4evQoixcvpqSkpKtLEUJcxORGtPuRay7E2ZEAIs4rjUaD0Wi8IFcvcjqd+Pj44Ha7u7qULlVXV0dxcTFFRUU4HA6SkpIYOnQoWq32tCfmf/vttzQ0NDB27FgcDgdbt27liiuuOOsaXS4XVVVV7Nixo8NzGo2GhIQEMjIyzvp9hBBCCHH+SQARohvbuXMnq1atoqSkhKCgINxuN5s3b2bv3r3MnTv3tFe0ysnJobKykqysLCwWyzkLIG63m5qaGjZt2gRAbm4uQUFBhIWFYTKZ8Hg8EkBEl5HhON2PXHMhzo4EECG6qaNHj/LVV19RXFxM7969SUtLQ1EUDh06hNFoZP369fj5+dGzZ0/8/f2prKzk0KFD+Pr60qdPH/bt28fmzZux2WxEREQwcuRIGhsbqa2txeVyYbfbKSoqQlVV9u/fT2FhIS0tLTQ3NxMcHEyfPn1IT0/H6XSyZ88etmzZgtvtxt/fn4yMDFJSUggMDARaezmCgoLo168fAMuXLycoKIiUlBTCwsKIiYnpylMpujlFq6V63jyc/908U/y06VNTZc6PEGdJAogQ3VRhYSG7du2iX79+3HXXXd5NAlVVxel0snDhQsrKyrj77rsxm83k5OSwbNkyhg0bRnJyMm+99Rb79u1Dq9ViMpm8O6e3cblc3vk1W7du5f333ycwMBCHw4GiKIwaNYrExESOHj3Ka6+9RmFhIX5+fhw5coSZM2cSFBTkDSB6vZ6EhAQSEhIA+M9//sPAgQOZOnUqsbGxnXjWhDg+Z2Gh7AMihBCnSAKI6NZUVaWhoYF9+/Z1dSkdKIpCcHAwoaGhaLVa6urqMJvNGAwGrFYrDoeDwMBAVFWlpqaGsLCw05qzUVpair+/P7Gxse12KFcUBYPBwPDhw3nwwQeZOnUq4eHh7Nu3j8LCQu68804OHz7MO++8w1tvvUW/fv1YunQpwcHB3jZUVcVms1FRUQG0LnlcVVXF3LlzycjI4J133mHz5s1MmTKFvLw8Pv30U9577z369+/Pvffei9PpxOl0nruTKYQQQogLhgQQ0a05HA6WLFnCkiVLurqUDoxGI3fddRd33HEHcXFxfPDBB0yaNImkpCTy8vIoKCjghhtuwOl08tprr/HII4+cVgBpu8HXarXeJYmPNXz4cMxmM3v27KGuro6Kigp69uxJREQEH374IQMHDmTcuHFoNBpuvPHGH32/fv36MWTIEJKSkujRowc1NTXk5uaSm5vL0KFDGT16NIqiEBoaKrupCyGEED9h8q+86NaMRiOzZ89m4cKFp73iU2fweDz85S9/4de//jV333239/HBgwczePBgAAwGA48++uhptx0XF0d9fT3l5eV4PB40Gk2HY2bOnMm2bdv49ttvSUlJYfr06bhcLsrKyry7pp/JbvIajQaNRoOiKPj4+ODn53fGbQkhhBDi4tLxjkMIccFQFIUnnngCg8FwztvOysoiMjKSVatW8f7776OqKi6Xiy1btrBgwQJcLhfXXHMNBw8eZN26dfj6+nLJJZdgNBrJzMzku+++o6SkBFVV2bRpE0ePHj3tGgICAsjOzmbFihV8//33bNiwgW3bttHS0nLOP68QQgghLgzSAyLEBex89sr4+PjwwAMP8P7777NgwQIef/xxdDodHo+HRx55BIDw8HAGDhxIYmIiw4YNQ6fTodPpuPzyy7nyyivJysoiOjoarVbLCy+80K7mU6m9Lcz84he/4JFHHiE4OBir1eqd6yKEEEKInx4JIEJ0U4qi0KNHD+6//35uvPFGmpqasNvthIWFERYWhk6nw2azUVJSQlZWFkOGDPGGCj8/P/7yl7/wwAMP4HQ6CQgIICYmhoyMDJxOJyEhIcTGxrJs2TIArrvuOq688kpCQ0OB1qFdU6dOJSAgAL1ez5QpU5g5cyYWi4W7776bzMxMIiMjT1j7888/j6+vL/7+/uf/RAkhhBDinJIAIkQ3ptfrCQ0NJTg4GLfbjcfj8fY8KIrC6tWrMRgMpKamEh4e7n2dRqMhIiKCsLAw3G43er0eRVHaraYFeJfmDQoKavd4YGCgd4nd+vp6fvvb36IoCiEhIWRlZZGcnIyPj88J65Z9P4QQQoiLlwQQIYR3UvgPJSQkcMstt5Cent5hSJSiKGi1WrRnuRuw0WhkypQpWCwWQkNDSUtLIzo6+rj1CCGEEOLiJwFECHFCvXr1olevXuf1PXx9fbnttttwOp3enhQhLjb61NSuLkF0ErnWQpw9CSBCiBPqrDDQtvmhEBcj1e0m/LnnuroM0YlUtxvlLHt/hejOJIAI0c253W4cDgcOhwNVVTEYDPj6+gKtO5i37c2h1WrR6XQdgoLL5cJqtXpfazAYznj4lM1m826QqNfr0ev1eDweHA6Hd6+QH3I6nXg8Hm99qqridruxWq3tjlMUBb1ej9FoPKPahDgRuRHtfuSaC3F2JIAI0Y25XC4qKyvJzc1l3759WK1W0tPTueyyy9DpdCxevBir1YrBYCAoKIjk5GTvfBBFUVBVlYMHD7J69WocDgfp6elkZmYSHh7ervdEVVXvZocn61XZsmUL+/fvx+1207t3b3r27EljYyNbt25l1qxZ7Y5t27ekqKiI+vp6oqOjSUxMRFVVysvLWbZsmTc8qaqKyWQiPT2dIUOGeB+D1gCm1Wpl6JcQQgjRSSSACNFNqarKkiVLeO+99zhy5AjDhw9HURRefPFFPv/8c/7f//t/PP744wwdOpTw8HCOHDlCeXk5ISEhvPjiiyQnJ5OXl8dVV13FnDlzMJlMzJ8/n4SEBJ588knCwsK872OxWFi/fj1Dhw71rn51PE1NTbz22msEBAQwZ84c4uPj2bJlC3/+8587BJD6+nq++OIL3nnnHXx8fPj5z39OYmKi97mdO3d6Q0Z5eTl1dXWMGzfOG0CgtYdnzZo1jBs37qSrbglxMjIcp/uRay7E2ZEAIkQ3tXfvXt566y169uzJSy+9REBAANAaGGw2m3cI0z333MPYsWMBOHDgAK+++io33ngj69atY9WqVURGRnLDDTeQmpqKoijs37+fkpISbwABqKmp4emnn+bFF188aQCZPHkyn3zyCampqWRlZREREXHCY81mM5MmTaKyspKSkhLv44qi0LdvX55//nlvAPnLX/5CQ0MDo0ePbtfG0aNH+eMf/8jgwYMlgIgzpmi1VM+bh7OwsKtLEZ1An5oqc36EOEsSQITopvbv309gYCCpqakEBAR45220DVdqCyAajca71G5cXBxTpkzh5ZdfpqmpiauvvpoPPviAuXPnkpKSAsDQoUPJzMzs8H4ej+dHa1IUpd3Xyeh0OsLCwggODqaioqJdG8f+d8uWLeTn55Odnc2IESM6tNMWUoQ4G87CQhy5uV1dhhBCXBQkgIhuy9fXl+TkZJ599ln69+/f1eV0YDQamTVrFjfffDOhoaG8//77jB49mri4OHJycjh48CBXXHEFDoeD1157jbvuuuu0Jn9bLBa0Wm2HSeMnu/HX6/UEBATgcrmwWCzU1NTgcDiYPHkyBw8epKioiPj4eJqbm7FYLPz5z39m//79WK1Wdu/ezT333IPZbGbAgAFcccUVDBs27IzPz6mEFY/Hw7///W+Sk5MZPnw4BoOBQ4cO8be//Y3CwkKsViv5+fnceOONGAwGRo0axZQpU+jbt+8Z1yWEEEKIk5MAIrotHx8fhgwZwosvvojD4ejqcjrQarUkJyezZMkSZs+ezbBhwwgODgYgNjbWO2RKp9Mxbty4055EHRoaSnNzM3V1dd4J4j/GYrFQWlpKWFgYgYGBvPbaa/Tv35/p06ejqioff/wx1dXVbNu2jdGjRzN16lSys7OpqqqisrKS6dOnExcXR0REBPHx8ad/Uk7T+vXrKSkpYcyYMaSnp6MoCkFBQUybNo3a2lqqq6spKSnhuuuuIzAwkLi4OKKios57XUIIIUR3JgFEdFs6nY6IiAimTp3a1aWckKqq1NfXo9FovEOcAIKDg71hRKPRnNFmgT179sRoNJKXl8fOnTsZOHAgHo+H8vJyDh482K5Nj8dDQ0MDW7du5csvv2TixIn4+PjQ1NSE2+0mMjKS6OhoNmzYQFlZGU1NTRgMBkaMGIHb7aa0tJRFixYxevRo0tPT0Wq16PX6sz9BJ9C2QtZ7771Heno6vXv3xt/fH2idOzJy5EhcLhelpaW88cYbjB8/nvDwcHQ63XmtSwghhBASQMTpaGmBxsbWL6cT/PwgJAROMqlYnB1FURg1atR5aTsuLo4hQ4awefNmFi1axP79+1FVlZKSEoxGIz179gTgu+++o6KigsbGRg4cOEBLSwt33XUX0Drf46233mLp0qWEhIRQXFxMeHg4KSkpaDQafH19UVUVs9nc7utEtm/fTmlpKXa7nYyMDO+E9cbGRt555x3vcUlJSaSlpbFv3z527NhBaWkpGzduxGQycckllwCQl5fHtm3bePzxx0lISPD2EP2wLn9//x+tSwghhBDnjgQQ8eMOHICjR6GyEoqLobS0NYxER0NaGiQmtgaRlBSQZQkvGnq9nquuugqTycQ333zDtm3bvDuS33HHHej1egYNGsTatWvZuHEjfn5+pKWlcdtttzF69GhUVWXChAls3ryZZcuW4fF4iIqKYvz48fTr16/de/n6+jJkyJATbibYZtOmTWi1Wo4cOUJJSQmpqamEhYWRmJjISy+95D1uwoQJ+Pv7s3z5cg4ePIjT6WT37t2oqtougAwbNoyBAweecOUtX19f79wQIYQQQnQORZUlYMTxqCrY7a3B4ze/gc8/B4sFPJ7/fWm1rV9uN0yZAs880xpKTCbQasnPz2fJkiVUVVXx9NNPd/UnEifRNqncZrMRHh4OnHwy+g81Nzej0WgwGAzodPJ3DdH9lE+bJqtgdROGjAxivvyyq8sQ4qJ26kvmiO6jLXwsWwapqfDuu1BfDw4HuFyt4QNag4fD0frfL76AXr3gxRehrOx/x4iLgk6nIyAggIiIiFNaAveHzGYzJpNJwocQQgghfpTcLYiOGhvh00/h3nvBZjv116kq/OlPrQHk9ttb54gIIYQQQghxDAkgor2aGliyBO6/v3XI1emy2eCNN6C5GS699NzXJ4QQFyB9ampXlyA6iVxrIc6eBBDR3vbt8OtftwaIM2W1wocfwuHDrXNDhBDiJ0x1uwl/7rmuLkN0ItXtRpFFV4Q4YxJAxP9s2gT/+U9rL8jZrk1gtRK2dy99/Pyo6t373NQnzou6ujoOHDhAYWEhdrudHj16MGzYMFRVZdWqVVitVnQ6HYGBgcTGxpKUlHTcdoqLi2lsbCQ4OPiMNxmsqKhg165d9OnTh6ioKAwGA3a7nYqKCvLy8hg6dCihoaGnPUdFiPNJbkS7H7nmQpwdCSDif3JzYeXK1knl50BATQ1xe/eCBJAL1rZt2/j+++85dOgQYWFheDweNm3axJ49e7juuut48cUXSUxMJDAwEJvNhtPpJCYmhltuuYWIiAhvO8XFxSxcuBCr1cqUKVPaBRBVVXE4HOzfv5+UlBRMJtMJ68nPz+e5555jzJgxzJw5k549e3L48GHeeustVq1axYIFCwgNDT2v50QIIYQQ55cEENHKZmvd5+Pw4XPWpM7hwNzQgNlqPWdtinOnurqaJUuWUF5eTr9+/UhNTUVRFMrKyvDz88PlcrFjxw6ys7Pp06cPzc3NHDp0iLy8PN5++20efvhhAI4ePcoHH3xAXl4eBoOBmpqaDu/V2NjIRx99xJ133nnSAFJbW0t5eTlfffUVffr0ITo6mgMHDrBs2TLKyspobGwEoLy8nFWrVlFdXU1oaCgZGRn06tULl8vFJ598QlBQEIWFhZhMJgYOHEh5eTkVFRX4+/szYMAA+vbti8fjYcuWLWzatAm32016ejqDBw8mMDCQgwcPsnPnTmJiYigoKCAlJYWGhgYmTJiA2WympqaGoqIi7HY7o0ePPj8X6AInQ1BEdya//0KcHQkgolVtLdTVnbPeDwAUBb3bTWRDw7lrU5wzRUVF5Obm0r9/f2655RZvMFBVFafT6b3ZHzZsGOPGjQNab/w//PBDXnrpJR544AFcLhdff/01hYWFpKSkcKJthSwWC6tXr+aGG2740bqSkpKorKxk//79BAYGUlhYiI+Pj3d/EoClS5eydu1aHA4HBoOB6upq/Pz88PPz4/nnn2fIkCHU1dVRUVHBvn37cDqdNDQ04PF4KCkpoU+fPtjtdl5//XWOHj2Kqqps374do9FIZmYmO3bs4IUXXmD8+PGUlpbidDr55JNPyMzMJDk5mX379rFq1Sr8/Py6bQBRtFqq583DWVjY1aUI0an0qaky50eIsyQBpJNYLBbKy8tpPpvJ3eeRf34+YYWFBJ7DsfWKqmJ0OIisrz9nbZ5LHo+HlpYWiouLcZ/L4HWOKIpCeHg44eHh6HQ6ampqCAgIwGg00tLSgt1uJyQkBI/HQ1VVFZGRkac1N6KsrAx/f39iYmLa9Uq07YZ+PGFhYQwfPpwnnniC5uZm9u7dy1tvvcVDDz1EZWUle/fuxePxeL9KS0ux2WyUl5fT0tJCUVERAH5+fgQHB+Pv79/hPcxmM+PGjePw4cPk5uYSEhLC9OnTeffddwFwOp28+uqrzJgxg0suuYRNmzaxf/9+QkNDGTt2LEeOHCE1NZVZs2bxzDPPsH79em655RZGjhzJihUrWLx4MT//+c85cuQI33zzDR9++CF+fn785je/Yc+ePURERNDY2Mjhw4cJDQ1lypQpRERE8Le//Y29e/cSEhLC9u3bOXLkCNOnTz+dS/qT4ywslM33hBBCnDYJIJ1kz549/O53v2PTpk3o9fquLqeDsS4Xd9jtTPR4OJfTe3VuN/4X6BAsq9XK+vXrmTt37gUZQHx8fLjjjjuYO3cuCQkJfPrpp0ycOJHExETy8/MpLCzkuuuuw+VyeYdEnU4AcTqdAGg0GlRVPaXXajQa9Ho9iqJgs9mYN28e11xzDbGxsZSUlNDQ0OD98ng8/PGPfyQ3Nxe73c7Bgwd57LHH8PHxYejQoVx//fUn7D2YMmUK7733Ht9//z0TJ05k4sSJ3gBy5MgRCgsLycnJ4dChQ9TW1tLc3ExhYSFjx45Fp9Nx9dVXEx0dzcCBA2lubmbgwIH07duXoqIi9Ho9xcXFbNu2jYEDBzJgwAAMBgPDhg3j6NGjHDhwAKPRSK9evXjooYfa1bRixQqCgoLYv38/Pj4+ZGdnn/L5FkIIIUQrCSCdZNeuXWRnZ/PYY48xduzYri6no5078Tz/PJ433+RcjWpVAadWS53ZfI5aPLcsFgsFBQVcffXVLFy48IJcWcnj8fD//t//49e//jV33nmn9/FBgwYxaNAgAAwGA7/61a9Ou+34+Hjq6+upqKjA7XajPWY88w+HUrX9XFdXR05ODvHx8URGRuJyufjXv/7FP//5T2+vTI8ePXA6nTz00EP87W9/w+FwUFpayoMPPshf//pX0tLSMBgMJ50LEh4ezqhRowgJCWHo0KEYjUbvc/X19QQFBXHZZZcRFRWFoijo9XoiIyM7tKPRaNr9rCgKGo0Gj8dDU1NTu2FnRqORpqYm7Hb7cWuaPXs299xzDy0tLZjNZgYPHnzSzyCEEEKI45MAIlolJaHExp7Tm3BVUbD6+FAWFnbO2uxuNBoNv/3tb89L21lZWURGRrJq1SpiY2OZPXs2brebHTt2sHLlSm6++WbvsW3DqRYvXswbb7zBww8/jEajYdu2bd5jFi9ezKZNm+jTp4/3tcHBwQDY7XaMRiNhYWHHDQrHM2fOHO/3Bw8e9H6fmZlJcHAwvr6+DB48GLPZTHl5OXV1daccCIxGI1OmTGHBggXe+SMbN25k5MiR9O7dm61bt3Z4zdChQ4mMjGTRokXcd999jBo16pTeSwghhBDtaX78ENEtBAaiBAejnGDs/5lQVBWnRkNFUNA5a7M7UhTlvPTOGI1G5s2bx7Bhw/jrX/9KfHw8qampXHPNNQQEBHiPu+qqq4iJiWHChAmsXLmSX//619x0003tajvZF4Beryc6Oto7fOtkn6nt8ZMd97vf/Y4PP/yQyZMnk56ezs0339wuDB37mh+2oSgKWq2W5ORkbrnlFiZMmMDQoUMxmUxkZ2cTHR19wrqmTJnCyJEj6d+/PzExMad6qoUQQghxDEU90bI14px6+eWXKS8vZ+zYsRfmECyAr76C//s/+P578HjOurnmoCB29+7N56NH8/TTT5+DAs+t6upqFi1aRF5e3gU7BOt8c7lcNDc309jYSHNzMzabjbCwMIKDgzGZTFRUVOD57++CRqPBYDB4V5v6IYvFgt1uR6/XYz5m2J2qqrjdburr6wkMDDzpHCiLxYLFYiEgIKDdRHin00lNTQ3BwcEYjUZsNhvNzc3euSYmk4nAwEB8fX2prKwkKioKrVaLxWLBZrNhNpsxGo1YLBaampoICQlBp9PR0NBAXV0dbrebgIAAAgMD0el0WK1WWlpaOvTW/OxnPyMuLo6rrrqKvn37nu3pv+iVT5smk9BFt2PIyCDmyy+7ugwhLmoyBEv8T3Y2lJfD2rWt+4KcpeqkJHLHjTu3S/uKc0qn0xEUFERgYCButxuPx+MNCIqiEBcXd8ptmUym4w6BUhQFnU5H2CkMxTtRG209KG18fX3x9fUlJCTE+x5t8z2OrfmHYemH7QcFBREQEICqqmg0Gm8INZvN7UIUtG62mJuby+TJk0+4G7wQQgghfpwMwRL/ExwMI0bAjTfC2azUpdPB8OE4Lr+cJtm1+qLQFhIMBsN5G/J1Pmi1WrRabYfJ5qdDo9Gg1Wp/9DMHBgby0EMPMWTIkOP2AAkhhBDi1EgAEe0lJsLcuTBpUmuQOF1aLfTvD9dfD5deeu7rE608nnMyTE6cuuDgYGbOnElsbOxZBR4hhBCiu5MhWKI9Pz8YNAgefBAaGmDdulMfQqUokJnZ2oNyxRXgckFOzvmttztpaICSEqipAbu99Xz7+UFcHCQnd3V13cLF0jPUWfSpqV1dghCdTn7vhTh7EkBERyYTjB4NTz0FP/85lJZCXV3rX9yPt2aBokBAAMTGwrx5MHkyREZCfn6nl/6T1dgIq1fDW2/B+vWt18PXFyIi4Jpr4Gc/aw0iZ3CD7HK5sNvt2O12VFXFYDBgNptRVZXm5mY8Ho935Si9Xt9uT45j2e123G63dyjX2bDZbDidTnQ6Hb6+vic91uPxePcp0Wq1qKqK3W7H6XRiNpvPKDS07eSu0WhOu7ejbT8Us9nc7jyoqoqqqjQ2NrY7XqvVYjQaz/qcATQ2NqKqKj4+Pie8TueK6nYT/txz5/U9hLhQqW43ivZc7ZolRPcjAUQcn17fOh9k+3Z45BH4+OPWm2CXC5zO1jCi17cO09JoYPp0+PvfW/8iL84dVW093599Bn/4Q2sPSFuPlNXaGkRefBE2b4aPPgKz+bRCiNPppKKigtzcXPLz87HZbKSlpTFhwgQMBgOLFy/GZrNhMBgICgoiMTGR9PR0fH19292Yu91ucnNzqaurIzY2ll69eh3zEVrDgcvlQqfTnVIg2LNnDwUFBSQlJTFs2LB2myT+kNVqpampCUVRiIyMxOPxkJOTw+HDh5k0adIZ3YjbbDaOHj2K2Wz27mVyqtavX09eXh5TpkwhLS2tQ63vvPNOu7ARERFBZmYmqefgr6pLly7FarUyaNAgMjMzz7q9k5GbL9Gdye+/EGdHAoj4cfPnt35VVLT2ahQWQlMTJCS0zveQ7ujzo623afFiePjh1qFXP+yBUlWor4fvvoPrroNFi8Df/5RCiKqqLFmyhPfff5+qqiqGDx+Ooij885//ZMmSJfzlL3/hiSeeYNiwYYSHh3PkyBHKy8sJDg7mhRdeICUlxdvOzp07+cUvfoHL5eKuu+5qF0CgdXnddevWMWzYMAIDA3+0rmeffZalS5cyffp0IiMjSUlJ8QaZH64cvnv3bpYtW4ZGo+Hxxx9HVVWqq6spLi729mT8MPSoqup97Nj22h7bu3cvL7/8MtnZ2dx8880nPfbYNgEOHz7M3r17ueSSS9o97/F4qK+v5/777+euu+7yhqrExETi4uK8PSTHa/+Hn/lECwWUlJTQ1NREcnLycc/XsXusCCGEEF1FAog4dVFRrV9jxnR1Jd2H2w2/+93xw8cPj9u1C775pnUInL//jzadl5fHW2+9RXp6Oi+//LJ388G2IUwtLS0A3HPPPYwbNw6AoqIiXnnlFW688UY2bNgAQEFBAb/+9a+JjIz0Lov7QzU1NTz99NMsXLjwRwPIjh07aGpqYsyYMQQGBrJixQpv2HG5XDz22GN89NFHuN1uJk+eTElJCdu3bwfgiy++4PrrrychIYHy8nIOHTrEY489xh133MFll12Gqqps376d3/zmN3z00Ue8+eabPPvsszQ2NpKcnMyDDz5IVlYWa9as4YMPPuDzzz9nwYIF/OMf/8BoNPLHP/6RvXv30rt3b2644QZmzJiBwWBg3bp1PPjgg5SWlhIUFMSQIUNO+hn//ve/t+sFcbvdbNq0iWeeeYZVq1YRFhbG/PnzmTx5MkVFRTz55JOsWrUKl8tFdnY2jzzyyI++R0NDA99//z1PPPEEFRUVTJw4kb/97W9ERkaetEdJnD4ZjtP9yDUX4uxIABGnTv5q2rncbtixA6qrTx4+2hw50rqHy+jRpxRACgoKCAoKIi0tjYCAgHZ/Fffx8fEGkGP/2h4XF8fUqVN5+eWXaWxsxGKxcPvtt3PffffR2NhIYWHhCd/vVPc8/fzzz+nfvz8DBgxg586drFmzhltvvRWPx8OKFSv49ttvefXVVwkJCWHv3r1UVlbSu3dvNBoN999/P2azmU8//dS7IaGvry87duwgOTkZo9HI+vXriYqKIjAwkEsuuYSJEycSFhbGG2+8wdatWwkICCArK4tJkyYxaNAgZs6cSVRUFDNnzmTq1KksWLCAtWvXkpubS2BgIJmZmdx///3MnDmT22+/nddff53Dhw+f9DPOnTvXO4Rt9uzZREdHs2bNGhRF4ZtvvmH37t08/PDDTJgwgRdffBF/f39eeeUVYmNjqaioQHcKK9QVFxfzwgsveAPkvHnz+PLLL5k5cyahsjz2OaVotVTPm4fzJL//4qdDn5oq85+EOEsSQES3ZrfbWbx4Md99911Xl9KBQVWZYrfzlKqiACeLfyqweMYMplVVYXA4Tql9i8WCVqv17v3R5mTDc3Q6HQEBAd4d1O+77z7vjfqmTZtwOBzeCe0Wi4Xf//737Nu3D5vNxp49e7jjjjvw8/Nj0KBBTJ8+nezs7HbtO51Oli5dyty5c8nIyKCkpITc3Fy2b99OZmYmS5YsYdq0aQwZMgRfX19SU1PZvn07TU1NaDQa4uPjvZPS2yaRT5gwgU2bNrFv3z6Cg4PZuXMnV155JRqNhuDgYF577TUOHDjA3r17CQ4OZvjw4fj6+uLv709oaCgJCQnU1NSwe/duYmJiOHz4MGVlZdTV1QGtmxs2NDRw//33ExoaSmJiIlVVVSc992PGjPH2QiQkJHDw4EEqKysZP348mZmZ9OjRgz/96U/s27ePgIAANmzYgMFgYPz48fTu3Zvg4GC+/fZbfv/73wMQGxvL//3f/7W7tvX19dTV1TFnzhzMZjMzZsxg3bp1XHbZZRJAzgNnYaHsCi+EEKdIAojo1vR6PUOHDuWee+7p6lI60LjdRBUU4Hz8cU5lfaRhmzahO439W8LCwmhububo0aPem/Uf09LSQklJCWFhYQQHB1NcXExtbS07d+6koqKCo0ePUlRUREBAANOnT+eaa66hrq6Oqqoq/v73vzN79mzi4uIIDw8n+ThLB2/ZsoXKykreeustvvrqKyorK3E6naxYsYLevXtTWFjIlClT8PX1xWAwYDAY8PHx8a5WpdPpcDqd7docO3Ysy5cvZ8eOHURHR1NbW8uYMWNwu938/ve/JyIigiuvvJJ+/fqRn5/v7alp26BQq9VSX1+PwWCgb9++hIWFkZaWhqIohISE4HQ68fPzIzw8HEVR0Ov1PzrHYsqUKd4hWP7+/t4FAMLCwjAajWi1Wnx9famrq+OGG24gIiKCwsJC3nzzTUJDQ7nttttITU3l7rvv9rbRNoQO8AbAtp3uoXWye21tLS6X60evsxBCCHE+SQAR3ZpGoyE2NpbLL7/8wpuY6/GgDhyIe/781hWvTjKESQFim5ogIwN8fE6p+fT0dHx8fMjNzWXbtm1kZWXh8XgoKyujsLCQvn37HlNK6wTqTZs28emnnzJ16lR8fHz45S9/id1uB2D79u0UFRWRkpJCamoqRqORoUOH4na7KS0t5e233yY7O5v09HS0Wu1xhxEtXbqUESNGMGDAAIKCgmhpaSE/P581a9Zw5513EhYWRk5Ojrf3prKyErvdjlarpbm5+bifMzY2loSEBPbs2UNxcTFpaWlERETgdDr57rvv+Pvf/86YMWNYtmwZBw8eBFqDqclkoqmpCWgNa4GBgcTGxtKvXz8MBgPNzc24XC7cbjcul4uysjLi4uKoqKjoEIJ+KDo6usNKWP7+/hQVFeF0OqmqqqKlpYW4uDhcLhfjxo2jf//+rF69mj179rB7925uuukmpk2bBrT+HptMJm97vr6++Pz396CkpIT4+Hjy8vK8w9CEEEKIriQBRIgLlUaDEhWFbvz41mWQrdYTH6sorbvYjxjRuo/LKYiJiSE7O5sNGzbw3nvvsWfPHgBKS0sJDAwkIyMDgK+++oqioiKam5spKytDVVVmz56NoijMmTPH215wcDB+fn5kZGQwePBgoHUuiaqq+Pn54e/vj5+fH37HWapZVVUcDgfffvutd1hXSEgIFouFr7/+mgULFlBcXMzEiRN57bXXePPNN/H398fj8ZCQkEBgYCA7d+5k0aJFJCYmtguTBoOBrKwsdu3aRWNjIzNnzkSj0aAoCikpKeTn59PS0sL27du9w6oCAgKIj49n8+bNBAcHM2rUKEaOHMmBAwewWq243W7ve/fp04devXrx2muvkZCQwI4dO05pjsaxkpKSSE1NZf369bz99tvU1dXRr18/4uLi+OCDD7Db7fj5+aHVagkPDycoKMjbA3Q8Pj4+hIeH06dPH95//32io6PJz89nxowZ7XpKhBBCiK4gAUSIC5miwJ13wsGDrRPSj9cTotNBSAhMnQp9+55yD4her+eKK67A19eX5cuX8/HHHwNgNBq55ZZbMBgMZGdns2fPHvLy8vDz8yM1NZW5c+cyYsSIDu2FhYWRkpJCVFRUh+d8fX0ZMWIEZrP5hPU4nU5CQ0PJysrC/7+T6E0mE2lpaVxyySXU1tYydepUtmzZwtKlS9Hr9fTt25d+/frRu3dvtm7dypIlSxg3bhwxMTH06dPHO89i0KBB3qAxdOhQFEVBp9Nx5513smjRInQ6HSEhISQmJhIVFUVYWBhZWVls2rSJzz77zPu5lyxZwsqVK737nURHRxMYGMitt97KW2+9xbZt2wgLCyMpKcn7Gf53KRUMBgNjx47t0NsWFRVFVlYWJSUlfPnll5jNZu677z6MRqN3CWOXy4W/vz99+vRh9OjRxz2H8fHxWK1WAgMDiYqK4vrrr+fDDz9k8+bN9O/f/0evgRBCCNEZFPVUl6YRZ+Xll1+mvLycsWPHMnbs2K4up1Pk5+ezZMkSqqqqePrpp7u6nA6qq6tZtGgReXl5LFy48MIbgnWsZcvgj3+EvDxobm5dIUtRwGCAmBi49FJ46aXWTSHPgMvlwmq1euchwIW9V0TbcCsfHx9vb4PL5cJisWA2m09r9/KGhgYA/Pz82vVctE1kb2pqIjAw0Hs+WlpavGGi7XhVVbFaraiqislkOuNz53a7sVgs+Pn5tVt97HR2hv8hVVVpamrC39//gr6mF7vyadNkEno3YcjIIObLL7u6DCEuatIDIsTFYOLE1qDx8svw/fet+4L4+EBcHNx0E9x111k1r9Pp8Pf37/BX+wvV8f6K37ZC1+k60b4kiqKg1Wq9k7jbHG8ImaIo7eZgnCmtVnvca+Dj4+Od03G6FEWRYVdCCCEuKBJAhLhYZGbC88+3fu92tw7FOs25BkIIIYQQXU3uXoS4GJ3hUCshhBBCiK4mAUSIi5GM5RfigqJPTe3qEkQnkWstxNmTACJEN1dbW0thYSEFBQXY7XZSUlIYMWIEqqry/fffY7Va0el0BAYGEh8ff9wNBAEOHjxIQ0MDISEhJCQknFEt5eXl7NixA4fDgdFoJDExkR49eqDT6aioqGDbtm0oioKvry8pKSnExsZ2mJTt8XjYtWsXwcHBxMfHe1fCEuJ8Ud1uwp97rqvLEJ1IdbtR5P9bhDhjEkCE6MY2b97M8uXLOXToENHR0Xg8HjZu3MjOnTuZM2cOzz//PMnJyQQFBWGxWLDb7URHR/Ozn/2MyMhIbzsHDhzg73//O1arlSuvvLJdAFFVFbvdTn5+PqmpqcedxN1m37593v009Ho9jY2NJCYmcsMNN5CXl8c//vEPhg8fjt1u54MPPiAuLo4pU6YwaNAgFEXh6NGjrFixgnfffZc777yTmJiYDgHE6XRSU1ODxWKhR48esjKUOGtyI9r9yDUX4uxIABGimzpy5Ih3meShQ4d6b8bLy8sxmUy43W5ycnK49NJLyczMpKWlhZKSEnJycnj99dd57LHHAKipqeH999+nsLAQo9FIbW1th/dqbGzkgw8+4O677z5pAKmvr6e6uprLL7+cmJgYNmzYwN69e9m+fTs2m42qqipGjRqF3W6noqKCzZs38+2336LX6+nXrx9arRaTycShQ4eoq6vD4/F0eA+r1cqePXs4fPgwPXr0OHcnVAghhBCnRAKIEN3UgQMHyM/Pp3///syePds7lElVVZxOJ42NjQAMHjyYcePGAVBRUcHHH3/MwoULefjhh3G5XHz22WccPnyYnj174nK5jvteVquV9evXc+ONN/5oXYGBgWRnZ9OnTx8sFguHDh2ioqKCkJAQQkJCmDBhAhqNBrfbjdPpZOvWrWzbto2BAwcSGBjI0KFDiY2NPWH7drudQ4cOkZ+ff7qnTIjjkuE43Y9ccyHOjgQQ0a15PB6qq6vZuHFjV5fSgUajISoqiujoaPR6PZWVlQQHB+Pj40NzczNWq5Xw8HA8Hg+HDx8mLi7utIYTHT58GLPZTExMTLt5FG2b7B1PaGgoQ4YM4fDhw7S0tLBr1y4++ugj5s2bR3l5OXl5eXg8HjweD263mwMHDmCxWKioqKCpqYm9e/dis9nw9/cnPDz8uHtwWCwW8vPzaWxsJDc3F7fbTY8ePaivr293nFarpX///uzatYvKykoURUGv1xMUFITRaGx3rKqqVFRUcOTIEerr6zl06BBVVVXs3LkTgB49emA2m2W+iDgjilZL9bx5OAsLu7oU0Qn0qaky50eIsyQBRHRrTqeTFStWsH79+q4upQMfHx9uvfVWZs2aRXJyMl9//TXjx48nMTGRwsJCCgsLueaaa3C5XHz44YfMmzfvtAKIy+VCVVWg9Qb9VF6rKAo6nQ6NRoPNZuORRx7hqquuIiwsjIKCAurr66mtraW2thZFUViwYAF5eXnY7XYKCgr485//jK+vL0OGDOGaa65h1KhRHd6juLiYp556CpfLRXh4ODNnzmTEiBF89dVXHY7VarXeHctPxu1289lnn/H222/jdDqpra3FarVSUFAAwIIFCxg4cOA52UxQdE/OwkLZCV0IIU6RBBDRrRmNRq677joWLlx4QU5G9ng8PPnkkzzyyCPcdttt3scHDBjAgAEDADAYDPziF7847bbj4uJoaGigoqICl8uF7r+bGh7vhr4tqNTV1bFnzx7i4+OJjIzE4/Hw+uuv89prr9Hc3IzNZqNHjx6oqsq8efOYP38+DoeDsrIyHnzwQZ5++mnS0tIwGAwnvNlPSkri5z//OcOGDSMkJARfX1/vcLBj6/F4POzduxeDwUBSUtJJP6tOp+PGG2/kqquuora2lq+//pqioiJ+97vfARASEoJerz/tcyiEEEKI0ycBRIgLmEaj4be//e15aTsrK4vIyEhWr15NXFwcs2fPxu12s2PHDlauXMnNN9/sPdbj8VBaWsrixYt54403+MUvfoFGo2Hr1q3eYxYvXszGjRvJyMjwvjYkJMS7CpbBYCAsLIyoqKiT1mUymUhNTT3pPA6LxcLnn3/OSy+9xGWXXeado9IWlI7H398ff39/tFotgYGB+Pn5ERkZeUEGTyGEEOKnTAKIEN2U0WjkF7/4Be+++y5PPfUUv/zlL729IMeGnunTp2MwGPD396dv37489thjXHfddcdt80Q383q93juX5cecqA2Xy8WaNWsICwvDYDCQmprKHXfcweWXX058fDwtLS1s2bKFu+++m7KyMjZt2sS7777LP//5T1JSUrztaLVa/P39CQkJ+dFahBBCCHHuSQARoptSFIXExEQeeugh7rzzTu8QqvDwcPz9/fHx8WHLli14PB4URfFO8vb19T3uZO3Jkyczfvx4b4g5VmRkJAsXLsTf3/+kNU2ZMoWxY8d2OM5sNnPttdcyceJEb0DR6XSYTCaMRqN3c8Ls7GxWr16N2+1Go9F4N1A8VlBQEFdeeSVut1t6P4QQQoguIAFEiG5Mp9Ph7++P2WzG7Xbj8Xi8vRSKorTbbPDH+Pj44OPj0+FxRVHQarUEBwefcRsajQaTyXTSSeIajQaj0UhERMRJ30Oj0XTYPV0IIYQQnUcCiDiv7HY7hYWFfPLJJ11dSgeNjY3s2bNH/grO/1a3EkIIIYQ43+SOQ5w3oaGhZGZmcuDAAXbv3t3V5XRgsVg4cuQIycnJXV2KEEIIIUS3IQFEnDdhYWGMHDkSt9uN3W7v6nI6aGpqoqGh4YSb7gkhhBBCiHNPAog4r0JCQpgxY0ZXl3Fc1dXV2Gw28vLyurqULuVyubBardhsNjweDz4+PgQEBKCqKg0NDd5J6FqtFqPReNw5GgA2mw23241Op+uwE/npslqt3qV7f2xzwLad16F1TouqqlitVpxOJ/7+/mg0mtN+/7Y22z736WhqasJmsxEQENDuPKiqiqqq1NXVtTtep9Ph4+Nz1ucMoL6+Ho/Hg8lkanedVFXF5XLR2NhIYGCgDLc7D/SpqV1dgugkcq2FOHvyr5AQ3Zjdbufw4cPs3buXgoIC70aCEyZMwNfXl8WLF+NwODAYDAQGBpKQkEDPnj0xm83tbsydTid79uyhrq6O+Ph4evfu7X2ubW8Op9Pp3UX9x+zatYuCggKSk5PJzs4+aQiwWCzejQpjYmLweDzk5eVRVlbG5MmTz+jG3mq1Ul1djb+/P6Ghoaf12g0bNpCXl8fUqVNJS0vrUOs777zTLhxERETQt29fUs/BTc3SpUux2WwMHjyYzMzMds/V1tby2WefMWPGjB+dqC9Oj+p2E/7cc11dhuhEqtuNcpp/nBBC/I8EECG6KVVV+eqrr/jPf/5DdXU1w4cPR1EUXn31VZYuXcqf//xn/vCHPzB8+HDCw8Opqqri8OHDBAUF8fzzz3tvmFVVZdeuXfzyl7/E5XJx1113tQsgAC0tLaxbt45hw4YRFBT0o3U999xzLFu2jCuvvJKoqChSU1O9Qcbj8Xi/VxSF3bt3s2zZMjQaDb/5zW9QVZXq6mpKSkpwu93e5XaPXWzA7Xaj1Wq9O6qrqoqiKGg0GhRFYe/evbz88stkZ2dz0003eR93u93eNtoea6u5rZ3Dhw+zb98+Ro0a1e5zeTweGhoamDdvHnfffbc3VCUmJhIfH9+ujR+2/8PPfOxzxyopKaG5uZnk5GRcLle7dqxWK3v37uXyyy8/6fkXp09uRLsfueZCnB0JIEJ0U3l5ebz99tukp6fzyiuvtNt7w2az0dLSAsA999zD2LFjAThw4AAvv/wyN954Ixs3bgSgoKCARx99lKioqBMutXv06FGefvpp/vGPf/xoANmxYwdNTU2MHj2awMBAVq5c6Q07TqeTxx57jI8//hiXy8WUKVMoKSlh27ZtAHzxxRfccMMNJCQkUF5eTmlpKY8++ih33nknl112Gaqqsm3bNn7zm9/w8ccf8+abb/LMM8/Q2NhIcnIyDz74IEOGDGHt2rV88MEHfPHFFyxYsIB//vOfGI1G/vCHP7B371569+7NrFmzmDFjBgaDgXXr1vHAAw9QWlpKUFAQQ4cOPelnfO6559rNPXK73WzatIlnnnmGlStXEhYWxvz585kyZQpFRUU8+eSTrFy5EpfLRXZ2Nr/+9a8ZMmTICa/rqlWrqKioIDAwkEcffZSrr74ajUbDgQMHLsj5WEIIIboXCSBCdFP79+8nODiYtLQ0/P392/0138fHxxtA4H+7k8fGxjJt2jReeuklGhsbsVgs3HrrrTzwwAM0NjZSWFh41nV99tlnDBgwgAEDBrBjxw5Wr17NrbfeisfjYcWKFXz77be88cYbhISEkJubS2VlJRkZGSiKwoMPPojJZGLx4sVUVFQQHR2NyWRi+/btJCcnYzQaWb9+PTExMQQFBTFq1CgmT55MWFgYr732Glu3biUwMJAhQ4YwZcoUBg8ezMyZM4mMjGTGjBlceeWV/N///R+rV68mJyeHgIAAMjMzuffee7n++uv52c9+xquvvkppaelJP+ONN97oHYp24403Eh0dzerVq1EUhW+//ZZdu3bx0EMPcdlll/HCCy8QEBDAG2+8QWxsLOXl5Sedw+FyuRg9ejSTJk1iz549LFiwgKuvvhq73c7BgwclgJwHMhyn+5FrLsTZkQAiujW73c5HH33EkiVLurqUDnx8fJg7dy533nknYWFh/Pvf/2b8+PEkJCSwa9cuCgsLmTlzJg6Hg3/84x888MADpzXh2mq1otFoMBgM7YbznGxfFL1ej7+/P263m+bmZn72s59xxRVXMGjQIDZu3Ijdbsdms2G322lpaeHxxx9n79692Gw29u3bx9y5czGZTAwePJirr76akSNHtmvf4XDw9ddfc/vtt5ORkUFxcTG5ubls3bqVvn378uWXXzJjxgyysrLw8fEhNTWVrVu30tTUhKIoxMbG4na7vRO+FUVh4sSJrF+/nry8PEJCQtixYwfTp09HURSCg4N56aWXKCgoYP/+/YSGhpKdnY2Pjw/+/v6EhIQQFxdHdXU1e/bsISYmhuLiYsrLy6mvr0dVVUwmE83NzcybN4+goCASEhKorKw86bmfMGGCN0QkJSVRVFTEkSNHmDhxIhkZGfTo0YM//OEP5OXlERQUxNq1a9FoNEyYMIHMzEyCg4NZtmwZjz/+OABxcXG88MILAPTu3ZsxY8YwePBgAgMDeeSRR7xDx9qGcYlzS9FqqZ43D+c5CODiwqdPTZU5P0KcJQkgolvT6/WMGjWKBx544ILbkFCj0RAdHc3ixYu59dZbmThxIiEhIQD06NGDqKgooHUVpauuuuq064+IiKCpqYmamho8Hs8phZempiYOHjxIREQEISEhlJWV8cUXX7Bu3Tqqqqqora0lPz8fPz8/rrnmGubOnUt9fT1VVVU888wz3HnnncTHxxMWFkZCQkKH9jdv3kxVVRWvvvoqn3zyCVVVVXg8Hr7//nsyMjIoKiqiV69eGI1G9Ho9er0eo9HonReh1Wq9K2K1GTduHEuXLmXHjh1ER0dTV1fH2LFjcblc/PrXvyY+Pp5Zs2ZRUlJCbm5uh7kWWq2W+vp6fHx8GDRoEGFhYfTt2xeNRkNwcDAulws/Pz/vtdHpdD96LaZNm+bdcd5sNrNv3z5sNhvBwcHo9XoURcHX15eGhgZuvPFGYmJi2Lt3L6+//jrBwcHeeTa/+tWvAPD39/cObTMYDN5VtUwmE06nU4JHJ3AWFuLIze3qMoQQ4qIgAUR0axqNhsjISEaPHn3BBRBo/Yt1fX09Go2G2NhY7+P+/v7eORsajYbExMTTbjs9PR2TycSePXvYtGkTw4cPx+PxcOjQIfLz8xk4cKD3WI/HQ11dHRs2bODjjz/miiuuwGg08sQTT3iH9GzZsoXCwkLS09PJzMzEYDAwYMAAb5tBQUFkZWWRnp6OVqs97jCib775xvvX+5CQEJqbm8nLy2Pt2rXcddddREREsGvXLiwWC1qtlvLycmw2G1qtlqampuN+zujoaJKSksjJyeHgwYP07t2bsLAwHA4Ha9asYeHChYwaNYqlS5eSn58PtAZTk8nkXV0rMjKSgIAAoqKiGDBgAEajkcbGRpxOJx6PB6fTSUlJCQkJCRw+fBin03nScx8eHt5uDkhb+wUFBTgcDqqqqmhubiYhIQGbzcbo0aPp378/q1evZufOnezevZtBgwYxceJEALRaLb6+vh3e59hhdUIIIcSFQgKIEBcwRVEYPHjweWk7KiqKUaNGsXbtWt577z22b9+OoiiUlZURERHBgAEDAFi8eDE5OTlYLBYqKyvx9fVl9uzZKIrCzJkzve35+vpiMBjIyMigf//+QOswMlVV8fPzIyAgAJPJdNx9PVRVxW6389133zFv3jwmTpxIcHAwFouFb775hi1btnDgwAEmT57MSy+9xEsvveTd46NHjx4EBQWxbds23nzzTVJSUtqFSb1eT1ZWFjt37qS5uZlZs2Z5V8Xq3bs3O3bs4MiRI+zZs4fa2loAAgMDSUxMZMOGDZhMJi699FLGjh1LQUEB9fX13hWmUlJSyMzMpF+/frz00kvExcWxffv20176NykpibS0NNasWcOrr75KQ0MDWVlZxMTE8P7779PS0oLJZMJutxMSEkJ4eDh6vf6EE/qPF6YvxIAthBCie5IAIkQ3pdfrmTJlCr6+vnz//fd8//33QGtouOSSSzAajVx66aWUlpZSUVGByWQiOTmZq6+++rirPEVGRtKrV692PTVtTCYTY8aMISAg4IT1uFwuEhISGDx4MGaz2fu69PR0Lr30Upqbm5k0aRLbt29n8+bN6HQ6MjMzGTJkCAaDgT179rB27Vq0Wi0JCQkMGDDA28syaNAgxo0bR0tLC1lZWSiKgk6n48477+Tjjz+moKCA4OBg0tPTiYuLIzQ0lCFDhrBjxw5WrVpF//79uemmm1i6dCnbt2+nvr6emJgYUlJSCAwM5JZbbuG9996joKCA8PBwEhISCAwMbPf5FEXBaDQyZcqUDmEgKiqKrKwsDh8+zNq1azGbzdxzzz0YjUbvMsculwuz2UxGRgaXXHLJcc9hjx49sNvt3tXIfH19mTRpEhqNBpPJxOjRo9utdiaEEEJ0BUWVvvlO8fLLL1NeXs7YsWO9S5qKrlVdXc2iRYvIy8tj4cKF3fovxMfuhh4WFgZc2H8xb25uBlrDUlvIcLlcWCwWzGbzaU3GbxtmZTKZ2g0La9uXo7m5mYCAAO/5aGlpQVEUDAaD9/i23dfbJqWf6blzu91YrVZvG23t2O12HA4HOp3uuEOtRNcrnzZN5oB0E4aMDGK+/LKryxDioiY9IEIIdDpdu3klF7q2HpJj6XS6k/awnMiJXqMoClqttkNPhp+f33GPPd7QstOl1WqP+9mMRuMZ7eguhBBCXIhO/c+EQgghhBBCCHGWJIAIIYQQQgghOo0EECGEEEIIIUSnkTkgQnRTTqeTbdu24XA4SE1NJSYmBlVVcblcfPbZZ6Snp6OqKmVlZVgslnav1Wg0REREMHLkyA4Trjdt2sTGjRu56aabvJvztdm8ebN3larw8PDz/hmF6Cz61NSuLkF0ErnWQpw9CSBCdFM2m40PPviAnJwcpk+fzn333YfT6eS7777jj3/8I7fffjvJycnk5eXR0NBAcXExlZWVDBgwAJPJRFpaGiNHjuzQbllZGevXr+eaa67p8FxpaSl6vd67l4UQPwWq2034c891dRmiE6luN4pW29VlCHHRkgAiRDfldrupqKhg3759pKSkUFRURHh4OO+++653N+6xY8cSHh6O3W7n008/pbCwkJEjRxIeHu7da+KHbDYbBw8e5JNPPqGqqoqwsDBmzpxJdHQ0R48exWg04nA4OvnTCnH+yI1o9yPXXIizIwFEiG5Mr9cTGxuLwWDgq6++4pJLLuHAgQP069cPjUZDYmKiN2jk5eWxb98+RowYcdzNBo/V0tJCXl4eALm5uURERHDVVVdRW1uLyWSSACKEEEJ0YxJARLfm8XiorKxk5cqVXV1KBxqNhri4OOLj49Hr9Rw+fJjQ0FB8fX1pbGzEYrEQFRWFx+OhpKSEpKSkM9oALzMzk9TUVD799FPq6uoYOnQoHo/nR9tSVdU7LMvj8RAUFOQNJiaTiUGDBjF16lRee+01li1bxtSpU2lqasLj8eB0Os/onAhxIZLhON2PXHMhzo4EENGtOZ1O1q1bx86dO7u6lA6MRiM333wz11xzDSkpKXz77bdceumlJCQkcPDgQYqKirj66qtxuVx8/vnn3H///WcUQOLj4+nTpw///ve/ef/99/nPf/7Da6+9dkqv/eSTT/jggw9wOByMGDGCm266CYDQ0FAuv/xyIiMjGTp0KMuXL8flcp12bUJcDBStlup583AWFnZ1KaIT6FNTZc6PEGdJAojo1oxGIzNnzmThwoVndPN+vnk8Hp5++ml++ctfcsstt3gf79+/P/379wfAYDDw4IMPnvF7KIpCWload9xxB1u3biUzM/OUXzt37lyuvPJKVFXFz8+P4OBgioqK2h2j1WpRVfWM6xPiYuAsLMSRm9vVZQghxEVBAogQFzCNRsNvfvOb8/4+CQkJ3HPPPUDr5PRToSgKYWFhhIWFnc/ShBBCCPETIxsRCtHNna+en7Z2j23/QuxlEkIIIUTnUlQZG9EpXn75ZcrLyxk7dixjx47t6nIEUF1dzaJFi8jLy7tgh2CdTx6PB4vFgkajwWQyeR9XVRWLxYKiKPj4+KDRtP6dwmaz4XA4MJvN3seOx263Y7fb8fPzQ6PR4HK5sFgs+Pv7Y7PZgNZhYzqddMCKn47yadNkCFY3YcjIIObLL7u6DCEuanIHIEQ3pdFoMJvNHR5XFAU/P78Oj/v4+ODj4/Oj7RqNRoxGo/dnvV5PYGAgQLugI4QQQojuSYZgCSGEEEIIITqNBBAhhBBCCCFEp5EAIoQQQgghhOg0MgdEiG7I4/FQX19/ws0Bg4OD0el03W5ivhBCCCHOPwkgQnRDbrebFStWUF1djdvt9u79YTAYUBSFGTNmEBER0cVVCnHx0KemdnUJopPItRbi7EkAEaIbcrvdHDhwgNLSUioqKiguLkZRFIYPH46iKFx++eU4HI52u5hrNBoURcHlcqGqKhqNBq1W6+0lcbvdeDweVFVFURQURUGn06Gqqvc1iqJ0eJ0QFzvV7Sb8uee6ugzRiVS3G0Wr7eoyhLhoSQARohvy8fHhV7/6FQAbNmzgq6++QlEU/vSnP3mPueyyy7j00kvZsmULISEhTJo0ieDgYJ5++ml2797NyJEj+e1vf0v//v2pqqpiwYIFfP755zQ3NxMTE0PPnj157733yM3N5Wc/+xn79+8nODiYe+65h2uuuYbExMSu+vhCnFNyI9r9yDUX4uxIABFCHNeBAwcAuOqqq8jIyODIkSMsX76c0aNH8/bbb/Phhx/y1FNP8e9//5snn3ySI0eO8Pvf/56MjAxWrVrFBx98gMvl4k9/+hMjR45k8eLFFBcX43Q6T7qRoRBCCCF+2iSAiG7L19eX1NRUnnzyST799NOuLqcDo9HIbbfdxl133UV4eDivv/46EyZMIDExkR07dlBYWMi1116Lw+HghRde4KGHHjqnN/aqqvLLX/6SIUOGYDab+c9//sOqVatITU1lwYIF1NXV8e233+JwONiyZQvXXXcdY8aMwWw2U1hY6B1yFRsby7fffktMTAwjR46kT58+BAUFnbM6hegsMuxGtJHfBSHOjgQQ0W35+vqSnZ3NF198ccLVoLqSRqMhIiKCjz/+mNtvv52pU6d6b9zT0tKIj48HQKfTccMNN5yXORX+/v74+vqi1+ux2WxotVpGjx5NQEAAHo+HrKwsfHx8UBSFwMBA/Pz80Gq1aP/7D7NWq+XBBx8kLCyM3NxcPv30U2bOnMn06dNJSko65/UKcT4pWi3V8+bhLCzs6lJEF9KnpsqcHyHOkgQQ0W1ptVoCAwMZPHhwV5dyQqqqcskll6DVaomKivI+bjabMZvNQGtQiY2NPe+1REZGkpqail6vZ/To0QDs2bMHnU5Heno6hYWF7NmzBz8/P3Jycryvq6+v55prrqGmpoZXXnmFkpISysrKJICIi5KzsBBHbm5XlyGEEBc1CSBCXMAURaFv375dXQaKopCWlsagQYPIzc3FarXS0tJCQ0MDo0aNYtKkSWzatInPP/8cg8FAaWkpBoMBj8fDd999h9vtJjAwEICoqCjv90IIIYTofiSACNHNhYaG0qdPnw5DuCZNmkRoaKh3OFVCQgIjR47k22+/JTc3l/r6em8vxiWXXILH4/E+bjAYvEPEjEYjmzdvJiAggKioKLKzs+nRo0enfkYhhBBCXDgkgAjRzfXs2ZOePXt2ePwf//hHu5/NZjODBw9m4MCB2Gw2PB4Pfn5+3r1B+vTpQ0ZGBuXl5ezevZuAgAB0Oh0///nPsdlsOJ1O7xwRIYQQQnRfP6kAYrVa8Xg8XV3Gcdnt9gu2NiFOh0ajwWQytXts586dvPjii5SWlhIfH8+oUaOYNWsW0Dp8y9fXF19f364oVwghhBAXmJ9MAPF4PLz++utUV1d3dSnHtW3bNu+QFCF+ambMmMEVV1yB2+1Go9Gg0/1k/q9FCCGEEOfYT2Y3sGeeeYavvvqKmpqari7lhM7HMqlCXCg0Gg16vV6GWAkhhBDipH5Sf6YcPHgw1113Henp6V1dSgevvvoqlZWVXV2GEOeNBGwhhBBCnIqfVABpG/qh1+u7upQOtFqt3KCJC9LRo0fZv38/+/btw2az0bNnT0aPHo1Opzvt39nPPvuMuro6pkyZgsPhYPXq1cyePfuc1OnxeDh8+DAbNmxAVVV0Oh2xsbGkpqYSFhZ2Tt5DCCGEEOffTyqACCFOz9q1a/n6668pLS0lKSkJVVXZsGEDmzZt4le/+tVph/n9+/dTXl7O2LFjaWlpYffu3ecsgLjdbnJycnj++ecZNWoUHo+HoqIi+vfvz5VXXkn//v3PyfsIcTL61NSuLkF0MfkdEOLsSQARopsqLy/niy++oKWlhSuuuILExEQAqqurMRqNfPHFF/j7+5OVlUVwcDDFxcXs3bsXs9lMdnY2mzdv5uuvv6alpYX4+Hiuuuoq7waFHo8Hp9PJgQMHUFWVbdu2sWPHDurr66mvrycyMpIRI0aQlZXl7SlZunQpTqeTkJAQRo4cSf/+/dv1bKiqSnNzMxaLhYkTJ6LX61m0aBFHjhzh8OHDEkDEeae63YQ/91xXlyEuAKrbjSLz3YQ4YxJAhOimioqKOHToEAMHDuSKK67Ax8cHaL3Rd7lcvP7663zzzTfExcURGBhITk4OS5cuZfLkybS0tPDKK6+g1WoJCAggPz+fxsZGb9uqquJwOCgpKQFg7969fPDBB6SlpWEwGNiyZQstLS306tWLyspKXnnlFXx8fAgLC2PFihX4+fmRlJR03KFVTqeTo0ePoigKTU1NxMbGyhAs0SnkhlO0kd8FIc6OBBBxXjmdTmpqati+fXtXl3JcWq2WlJQUUlNTURSFgwcPEhUVha+vL3V1dVgsFmJjY3G73Rw4cMB7XHFxMeHh4fj5+dHQ0EBTUxNxcXHeYUFtx5WUlBASEoK/vz+NjY3U19eTkJCAqqoUFBSQmpqKRqOhtLSUwMBAAgICaG5u5ujRoyQmJqKqKoWFhaSkpKDRaCgrK8NsNhMUFITFYqGqqso7dKqwsJAePXqc8ipUlZWV+Pn5ERkZ6Q0f0DqZXK/XM2zYMF5//XVKSkoICgqisLCQqqoqevfuzcGDB1m9ejXvvPMO6enprFu3jtDQUG8bbQHk6NGjQOsePTabjcmTJ9OnTx/efvtt9u3bx6FDh8jLy2Pr1q385z//IT09nfvuuw+Xy4XL5epQs6qq1NXVsWLFCux2O/v37yc4OBhFUVBVVeZZCSGEEBcBCSDivGpubub7779n3rx5F+RfqU0mE7fffjtBQUGEhYWxevVqLrvsMnx9fSkuLqa8vJzY2FhcLhfLly8n9b9jf9etW8eoUaPw8/OjrKyMgoIC4uLicLvdLFu2jJSUFBRFYePGjWRlZeHv709lZSW7du0iISEBj8fD8uXL6dGjBxqNhs2bN5ORkUFAQADV1dVs3LjRG0CWLVvGnXfeicFgYNu2bfTo0YOgoCCOHj3KmjVrSEpKAmD58uXcdtttpxxAVFXF4/Ggqupxb97bhkDl5ORQVVVFVVUVvXr1IiQkhGXLlpGRkcGwYcPQaDRcccUVP/p+6enp9O3bl6SkJOLi4igvL6ewsJCCggIGDBhAVlYWiqIQFBR0wn1EFEUhNDSUKVOmoNPp2LdvH9988w2LFi0iMzNTNjsU55UMuxFt5HdBiLMjAUScV83NzRQUFPDAAw/wxBNPdHU5x+V2u1mwYAEPP/wwc+fO9T4+cOBABg4cCIDRaOTee+/1Pjdnzhzv9xkZGWRkZACg1+u57777vM9df/313u979uxJz549gdael2OPmzlzpvf75ORkkpOTgdaV3Y49bvr06d7v4+Pjuemmm4DWG/Nj6zsVcXFxNDU1UV5ejt1ux2g0es+H2+3GYDAwffp01q9fT1VVFenp6UyaNAmXy8WRI0fw8fHB4/GgKIp3A8JTpdFovF9+fn4YDAZcLpe3rZMJDg5m7Nix+Pn5MX78eCoqKigvL6e0tNR7foU4HxStlup583AWFnZ1KaIL6VNTZS6QEGdJAojo9rRaLY8++mhXl9HpBg0aRGRkJGvXriU+Pp5Zs2bh8XjYvn07q1ev5qGHHmLGjBm8//777Nq1iwEDBpCdnY3dbicjI4OFCxdSUlJCYmIimzdvJi0t7bRr8Pf3Z9iwYfz1r39l5cqV+Pr6snPnTqKiok76urbemx07dlBYWEhAQMAF2cMmfnqchYU4cnO7ugwhhLioSQARopsyGo08/PDDvPPOOzz55JM89NBD3qFPf/jDHwAIDw9n8ODBpKSkkJ2djU6nQ6fTMWXKFK6++moyMjKIjo7GYDDw0ksvAf/bkPBU5mMYjUb69u3Lo48+ykMPPURISAgWiwWz2YzBYOhwvKqqrFu3zjsvJywsjKuuuoo5c+YQHBx8js6MEEIIIc4nCSBCdFOKopCYmMgjjzzC/fffT0tLC1arlYiICHx8fNDpdFitVgoKCrjkkksYNmyYN1T4+Pjwt7/9jT/96U9YrVYCAwPx8/MjOzsbj8eD0WgkKSmJnTt3AnDLLbdw0003eYd53XjjjcyaNcsbMqZNm8att95KU1MTs2bNYsCAAURHR7erV6/Xc9VVV3lXwFJVtd3mozIBXQghhLg4SAARohvTaDQYjUYMBgP+/v6oquqdxK4oCkuXLsVsNtOzZ892q1wpioKPjw9Go9EbBBRFaTd5XKPRYDabATr0Zhz7c21tLbNnz8blchEVFcXIkSPp0aOHN6wc+556vf60N0cUQgghxIVFAogQAkVRjrt61tChQ+nRowcxMTEdnlcU5Zz0OpjNZp588klvT0pUVBRRUVHSoyGEEEL8REkAEUKcUExMDDExMef1PQwGA2PHjsXlcqHT6SR4CCGEED9xEkCEECfUWWGgbXiVEEIIIX76JICI02OzQUsL2O2gKGA2g79/V1clzoLT6cRqtdLU1ITT6cRoNBISEoLBYPAGkJaWFpqbm7Hb7Wi1Wvz9/QkICOjiyoUQQghxMZIAIn5cSws0NIDDAYcPQ0EBlJeDwQB9+kCvXq3fBwWByQSnsSGd6FpWq5XDhw+Tn59PYWEhzc3NhISEMHToUPr164dOp6Ouro68vDz27dvH0aNHMRgMpKenM2rUKMxmswyZEkIIIcRpkQAiTkxVW3s8Pv8cXngBdu1q7fnQaMDjae0B0Whag0nv3vDwwzBtGoSFwXEmNIsLi8fjYcWKFbz77rsUFRUxaNAg79K5zzzzDCtXriQ4OJj58+ezY8cOoqOj6dGjB4cPH+bDDz/knnvu4cYbb+zqjyFEp9KnpnZ1CaKLye+AEGdPAojoSFVb/+vxwOWXw44drb0gbY+73R1fs3cv3H8/vPQS/O1vMHJk59UrzkhRURH/+Mc/iIuL48MPPyQ+Ph5o3ezP4XCg0+l45ZVX2Lt3L/feey/Tp0/3vlZVVex2e1eVLkSXUN1uwp97rqvLEBcA1e1GkT+0CXHGZKyM6MjjgdLS1uFUa9ZAc/P/wsfJWK2wZQtceik8+WRrb4m4YO3ZswedTkd6ejpxcXHtnjMYDGg0GnJzc8nIyPCGk2P9cJ8OIX7q5IZTtJHfBSHOjgQQ0dH+/TB4cOvQqjPhdMLTT8MjjwDQ3NzMU089RWho6AX3lZCQwDPPPIP634D1r3/9i7KyMgA2b97Mxx9/DIDNZmPBggXe41599VUOHjwIwM6dO/nPf/7z34/uZP78+Xg8HgD+/e9/k5+fD0BeXh5vv/02AG63m/nz5+NyuQB49913ycnJAaCgoIDXX38daB0mNX/+fBz/vRaLFi1i+/btABQXF/Pyyy8DrT0SCxYswGq1nvJlstlsGI1GfH19URSF/Px8Bg4cSHJyMsnJyZSWltLc3IxOp2u3wSD8bw8Qmf8hhBBCiNMlQ7BEe9u3w5/+BDU1Z9dOczN88w04nZjCw7ntttv42c9+dm5qPIc0Gg2hoaH861//4s477+Saa67xru6UkZFBz549gdYegZtvvtn7uhkzZuD/39W/evbsSWJiIgA6nY65c+d6b8yvuOIK/Pz8AEhOTiYqKsr7vnPnzvVu7jd58mR8fX0BSEhI8A53UhSFuXPnegPAxIkTvT0PMTExXH311d6abr755tPqlYiOjqa2tpaDBw/S2NhIXFwc//rXv7DZbEycOBGXy0VMTAxHjhyhvr7+lNsV4qdKht2INvK7IMTZkQAi/qesDFavhvXrz017hw9jWLOG2JEj0cfF0a9fv3PT7jmmqirjxo1Do9EQFhbmfbwtOEBrYIiMjPT+fOxxJpMJk8kEtAaGY48LDQ31fu/r6+sNGT88LiQkxPu90Wj0BokfHhccHOz93mAweOv44XGnok+fPsTFxVFQUMCKFSuYMmUKAwYMwGKxoKoqqqoyevRonn32WdatW0dSUhLx8fFYLBa2bduG0Whk6NCh0gsiug1Fq6V63jychYVdXYroQvrUVJkLJMRZkgAi/icnB5Yuhdrac9Oe1YpfWRl98vKo+sEcgwuJoij06tWrq8vodGFhYVxxxRV89913LF68mJ07d+Ln50dDQwO9evXC19eXgQMHkp2dzb59+/j73/9OSEgIFouF2tpaZs6c2dUfQYhO5ywsxJGb29VlCCHERU0CiPifoiLYvPn4q1ydCVXFp7mZHkVFrDw3LYpzSKvVMm7cOEwmE2vXrqWsrAyj0Yjb7eb2228nICAAPz8/rrvuOr777jvy8/MpLi7G7XYTGxtLUlJSV38EIYQQQlyEJICIVjZba89HXd05bVbrduPf3IzB6Tyn7YpzIzg4mEmTJjFx4kTsdjvNzc2Ehoa2m2CekZFBRkYGdrsdq9Xq3QldCCGEEOJMSADpRE6nk5aWFhobG7u6lA60xcUYysvRa7Xw35WZzqXw6upz3qY4dzQaTbs5Ksdz7NwUIYQQQogzJQGkExUUFHD48GG2bNnS1aV0kFRczLAtW+jl8XCupxTrXC4iq6rOcatCCCGEEOJiJPuACK+2lY+EEEIIIYQ4X6QHpBP17t2b0aNHM3bs2K4upaPiYjTPPw8FBed8CJZTr6fiv/tfCCGEEEKI7k0CSCdSFAWtVuvdfO6CkpgIkZHnZf4HQFVExHlpV5w5p9PJpk2bKC0t9T6m0WiIi4tjxIgRx93fw263U1RUxBtvvMH8+fNZtWoV+fn5XHfddRw8eBCHw0F8fDyxsbGnVYvH42H16tXs27ePOXPmyCR3IYQQ4idMhmCJVjodhIS0hpBzyK3V0hAYiFsjv2oXGqvVynvvvcfbb7/N9u3b2b59Ozt27ODAgQMnfI3b7aampoZVq1YBcOjQIXbt2oXNZqOyspKysrIzXmShpKSEnTt34pQV04QQQoifNOkBEf+TkQGXXgoffQTn4iZQo6ElKIi8Pn3Ovi1xznk8HqqqqoiKiuLaa68FWntAgoKCcLlcvP322+zYsQOtVkt2djYjRowgJCQEl8tFU1MT0NojYrFY8Hg81NXV0dLSgt1up6GhgY0bN7Js2TKam5vp2bMnd999N2+++SZDhgyhX79+2Gw28vPzyc/PZ86cOTgcDqxWKx6Ph40bN7Jy5UoOHDiAXq8nNTWV2bNnExERwfvvv4/RaKSsrAy73c6ll15KVlZWV55K0Y3oU1O7ugTRxeR3QIizJwFE/E/v3jBhAqxdC8cMyzljfn5Ye/Rgf3r62bclzpv6+nqKi4sBMBgM9OzZk/z8fL788ksSEhKw2+2sWLECjUbDlClTTtpOc3MzLS0tHDp0iHfeeYeAgADCw8MpKCjA7XbzzTffEBQURJ8+fbBYLBQUFLBy5UrmzJnTri273Y7BYCAiIoKWlhZ27NhBZGQkN9xwA6tWraKuro64uDj8/f1xn6uNM4X4EarbTfhzz3V1GeICoLrdKBficGohLhISQMT/hIXBiBEwdSq89BKczYpYigIpKTinTKHK5aIoL4+PPvro3NV6juh0OtLT0+nVqxeKolBQUEBsbCwmk4mjR4/S0tJCQkICbreb/Px8evfujaIoFBYWEhUVhdlspq6ujsbGRhITE/F4POzbt8973IEDBwgLCyMgIICGhgZqa2tJTk5GVVX27t1Lr1690Gg0FBcXExQURFBQEE1NTVRVVZGSktLhuJKSEvz9/QkJCaGlpYWKigpSU1NRVZV9+/bRs2fP055jVFpaypo1awDw9fVl+PDhrFq1Cp1Ox5133onNZuPFF19k+/btjBkz5oTtWK1WLBYLtbW1VFZWUlBQwIsvvkhaWhrLly/HYDBQX1+PzWZDVVU8Hg82m+24Q7bi4+NRFAWLxcKhQ4dYunQpK1eu5IYbbqCxsRG73c6YMWNISEggISHh9C66EGdIbjhFG/ldEOLsSAAR7fXqBQ8/DOvWwZ49Z95OTAxceSXcfjv2559n5cqV7N2799zVeY74+vpy6623EhwcTGRkJJs2bWL8+PGYTCbKysooLy8nISEBl8vFmjVr6N27NwBbt25l5MiRmM1mKioqKCwsJDExEbfbzZo1a7yBZvv27QwaNIiAgACqqqrYs2cPycnJ3knXPXv2RKPRsHPnTnr37k1QUBBHjx5l27Zt3gCyZs0a0tLS0Gg07Nmzh6SkJEJCQqirq2PLli2k/nc4wOrVq0lOTj7tAJKamsrUqVMB0Ov1+Pn5sWnTJkaMGEF8fDwBAQHExsZSX19PeXn5j7Z35MgRamtr6dOnj3do1DXXXON9/lSWeq6trWX9+vXk5eVRU1NDdXU1er3e+/y0adMYO3YsgYGBp/VZhRBCCNH1JICIjnr0gK+/hiFDoKamdWWsU+0N0ekgMLA1xNx7L1RV4efnx7333ssTTzxxfus+Q263m7/97W889NBD3Hjjjd7H+/fvT//+/YHWXcDvuusu73M33HCD9/s+ffrQ57/zXPR6fbvjjr3xTktLIy0tDQCtVsvdd9/tfW7GjBne75OSkkhKSgJa52Qc2960adO838fFxTFr1iygdYW1Y487HT169GDSpEnen91uN3a73Rtk3G43Wq0WRVFOaYK4zWajvr4eg8GA2+1Go9HgdDrR6/VoNBo8Hg9utxuPx4PrBKuuPfvss2i1WqZNm0ZycjIbN25kw4YNZ/T5hBBCCHFhkaWJREcaDcTGts4DGT0aAgJaH/sxfn4wbBh8/jk89BAYjee/1nNAq9Xyq1/9Cp1O8ji0hpnJkyfz3XffUVdXx8GDByktLcVsNpN+CvN5QkJCiIiIYP369ZSUlOB2u1m1ahUOh4O4uDgaGxupqqqipqbmuL1iHo/H24MyatQozGYzhw4dOh8fVZwhVebdiG5O/jcgxNmROy5xYlotLF8OX3wBzzwDO3aAzdYaRjye1nkeitK6YlZGBjz+OEyZArKHw0VNURSuvPJK1qxZw/jx41FVlalTpzJjxgxvT8ixx/5QfHw8Q4cOZfv27fTp04eYmBgMBgPr1q1j5syZvPjiizz11FOYzWaio6OJi4tr15ZGo+H666/n1Vdf5ZlnnsHf35/w8HBv79GJ3ld0HkWrpXrePJyFhV1dihCdTp+aKosRCHGWFPVUBmRfBObPn4/FYuGGG26gV69eXV1OBy+//DLl5eWMHTv2wtwJ/WTc7taQ4fHA4cOwd29r74jRCH37tn4pCuj1raHlmJvD0tJSXnvtNbRa7QU7BKu7UlUVh8OBoigYDIZ2j0PrRoUNDQ0YjUaMRiM6nc47hMrhcODj44Pb7cbtdmMwGLzDqTQaDYqi4HA4sFgsWK1WQkJCvMe3tLTgcDjQ6XT4+vp63//Yttxut3eyuV6vx2w2e49zOBzeDT0liHSd8mnTcOTmdnUZQnQ6Q0YGMV9+2dVlCHFRkx4Q8eO02tYvgORkiItrnReiKGAwtH6Ji46iKBiPM0yu7abeYDAQGhrq/bntv1qtFl9fX6B1FbG2oWvHThKH1nkzBoOBwMBAbyjR6XQEBAR4Q47mmKF9x7al0+kICgpCVVUURWl33PFqFkIIIcTFQwKIOD06XeuX6BY0Z7GDvaIox+2hONHj5/K9hRBCCHHhkn/hhRBCCCGEEJ1G/pQtxLGamqCwEI4cAYcDzGaIj4djJkALIYQQQogzJwFEiDZHjsDq1fD997B/P1itrbvDDxoEEybAyJGtx/1EJj63LXdrtVq98zMCAwO98zt2795NcnIyfn5+MhxKCCGEEOeMBBAhVLW15+PTT+Gpp6C8vHXVL2idfL96NXz4ISxe/JPqCXE4HKxatYri4mJMJhMmk4mUlBT69euHv78/Tz31FI899hjp6eky8VsIIYQQ54wEENG9qWrr8sKffgqPPQb19e13fXe7oaEBGhth0iTIyQFf359EL4jNZuP999+noqKC7OxsKioq2LFjB7/97W+ZNWsWW7ZsobGxEafTidvtxuVyoaoqWq3Wuyyvx+PBarXi8XiA1pWz9Ho9Ho8Hu92Ooii4XC7vCldOpxNVVdHpdBgMBjQaDS6XC6vV6l3xysfHx7vkrxBCCCF+euRfeNG9qSocPQp/+EPH8PHD4yorW4+z2zuxwPNv7NixLFiwgL///e/cfffdvPnmm+2ez83N5b777qNnz56kpKQwceJEli1bBkBeXh5XXHEFaWlpDBw4kP/3//4fO3fuZPny5UycOJGbbrqJ5ORkrr/+el566SUmTpzIkCFDeOyxx9i9ezctLS0sXbqUvn37EhcXx6BBg3jvvfeoq6vrilMhhBBCiE4gPSCie3M6Yd06qK09cfhoY7W2DsX63e86p7ZO1tjYyKZNm0hISGj3eGRkJL/61a/4/e9/j6IofPHFFzz++ONMmTKFP/7xjwwePJi33nqL2tpampqaUBSFhoYGDh06xM9//nP+9re/MXXqVD7//HN+//vf09LSwsqVK1myZAmPPPIImZmZfPrpp/Tq1YsvvviC+fPnk5GRQWhoaBedCXEq9KmpXV2CEF1CfveFOHsSQMR5FRAQQJ8+fbjppptYsGBBV5fTgS9wm8vFk243PzaoSgX+Ons2DykKRlVl0Qcf0KNHD4YMGUJJSQlLlizh3nvvRVVV5s+fz/3334/JZOKTTz4hKiqKESNGUF5ezscff8z9998PwIIFC7j77rvx9/fnyy+/xGw2M3bsWKqrq3n33XeZN28eAM8++yy33XYbwcHB3t6HiRMnUldXx+uvv87DDz8MQHl5OeHh4R02BTyZN998k6+//prGxkbi4+N59dVX2z0fEBDA9u3b+eabb8jPz6e8vByLxQJAYmIiy5cvJyAggLFjx9K7d2+0Wi0HDhwgNjaWa6+9Fq1Wy4ABAxgyZAgDBgzA4/GwdetWSktL0Wq1mEwmXnvtNbZs2cKhQ4eoqKjA2TYHR1yQVLeb8Oee6+oyhOgyqtuN0rZBrxDitEkAEeeV2Wxm8uTJ7N69u6tLOS7F4SBo1Socv/wlBvjREHLHkiXoH3sMgMmTJ3tv9GNiYpg1a9b/jrvjDnx8fAC47LLL0P73H6rw8HDmzJnjPe62227DZDIBMGbMGO+8h+DgYG6++WbvcbfccgsBAQEAjBgxwvt4QEAAt9xyi/fn8PBw727ip2rUqFHccccdBAQEEBUVRVRUVLvn33//fbZt20ZsbCzXXHMNVVVV/OpXvwLgl7/8JXFxceTk5PDII49w6aWXcsUVVwCtGwnq9XpUVUWv13vndWi1WhRFwePxcOTIEV544QXy8/OZN28eRqOR22+//bTqF51PbrxEdyf/GxDi7EgAEeeVVqvF39+f9PT0ri7l+NxuVF9fPE8+CRUVJz1UMRoJGzCgdWUsRfEGAgC9Xk9wcHDrcYrSbviQv79/u+NCQkK8P5/oOJ1Od8LjzGaz93utVtvuudPp+WgTFxfHsGHDMBgMGAyGDs8XFxdjNpvJysoiIyOD2tpa73OlpaVMnz6d8ePH8/bbb9PQ0EBRUZE3fJ1I207oVquVwsJCBg4cSHZ2Njk5OaddvxBCCCEuLhJARPem0aDExqK9/np4+WX479CiDhQFQkPhzjvhDG7yL2QGg6FdqPmh9PR0NmzYwKeffsrGjRspLy/3Bohvv/2WxsZGAgICqKqqIjU1lbi4OGpqak7YnnLMCmImk4nMzEw2b97Ms88+S319vXd4lxBCCCF+miSAiO5NUcDHB26+GcrKYPny1j1B/rusLIoCBgMEBcHtt8OIET+JJXihNXhMnDiRyMjI4z4/e/ZsoqKiCA8Px+VysXfvXlwuF6mpqURHRwMQGxtLTU0Nzc3NpKenM2LECDIyMigtLeXqq6/2tjVu3DgSExPx9fVFURSGDh1KY2MjQUFBTJ48mbq6Ourr64mMjGTOnDknrEkIIYQQFz9FVX9s6Z+Lw/z587FYLNxwww306tWrq8vp4OWXX6a8vJyxY8cyduzYri5HHM+GDfB//9e610d9PbhcYDJBbCz06wcvvggazU8mgJwOl8uFzWZDVdV2Q8WgdT8Rl8vl3b/jdKmqisPhoKWlheDg4HY9JEIIIYT46ZEeECHaZGdDSgosXQq7d0NLC0RFwfDhMHFiV1fXpXQ63QmHaf3YfI8foygKRqNRdlsXQgghugkJIEIcKyICbrqpq6sQQgghhPjJkp3QhRBCCCGEEJ1GAogQQgghhBCi08gQLCG6KYfDwaZNm2hoaCA1NZVevXrhcrkoLCykqamJQYMGeVe+iouLIywsDLvdTnl5OZs3b2bq1Kn4+fnJpHEhhBBCnBbpARGim7LZbLzzzjs8/PDD/Otf/6K5uRmXy8WaNWv47LPPcLvdfPfdd3z11VeUlZVhs9nYuHEjv/71r6mursbX17erP4IQQgghLkLSAyJEN+XxeGhubkZVVRoaGli+fDmTJk2iubmZ+vp6ABobG2lubqaxsZGVK1fy+eefk56ezuTJk9FoNGzYsIFFixZRV1dHcHAwU6dOZdSoURJOhBBCCHFCpxxAqqurWbRoER6P54IccrFu3TrS09O7ugwhLiparZZ+/fqRmJjI559/zsiRIzsc43A4WLFiBVarlZCQEGbOnElKSgqqqvKPf/yDkJAQevbsSXNzMw6HA6fTKQFECCGEECd0ygFk27ZtfP755yQkJFyQ6/VXV1eTmpra1WWcVElJCUuXLuXQoUNdXUoH8fHx9OrVi+joaKxWK0VFRWRmZgKwZ88eevbsidFo5PDhw0DrDth2u539+/fTt29fAHJyckhJScHX15eKigqcTicJCQk4nU727t1Lv379AMjNzSU5ORmTycSRI0ewWq0kJSXhcrnIy8ujb9++KIrC3r17iY+Px2w2U11dTVNTEz169MDtdpOTk0O/fv1QFIV9+/YRExNDQEAAR48epa6ujtTUVDweD3v27PEet3//fiIiIggKCqK+vp6qqip69uyJqqrs3r2bvn37otFoKCwsJDg4mNDQUBobGykvL6dXr17e4zIzM9FqtRw4cAB/f3/Cw8Npbm6mtLSU3r17o6oqe/bsoU+fPuh0OoqLi/H19SUyMhKLxcLBgwfJyMgAYPfu3fTu3Ru9Xs+hQ4fQ6/VndQ0sFgs+Pj5oNKc+ujI1NZW+ffuyadMmNm3a1OH5AwcOUFpaSnx8PNdffz0DBgwAWjcQXLt2LXfccQcTJkzA7XYTERGBXq8/3V8/IYQQQnQjpxxANm3aRK9evbjxxhsJCgo6jyWdmVdfffWCDEbHOnDgAJs3b2blypVdXUoHY8aMQVVV9Ho9Go2GnTt3em9+t2/fTmJiIkajkZKSEuB/N7/bt2/33vz+f/buOzyKcn34+He2ZzfJpvdCekILEHrvVVEQEGwgdsXe2/HgERQ7olg5ehTFDoqIFEGlJZRQJNQESEIS0rMpm2yd94/8Mi+RgCBCQJ7Pde3l7MyzM/fM5nCee5+2Y8cOwsLC8PDw4OjRo9TX1xMVFYXdbiczM1NJQHbu3ElQUBBGo5GioiLKy8uVBGTr1q3K+Xbt2oXZbMbT05OSkhLy8/OVBGTr1q3K+Xbv3o3RaMTb25uysjIOHjyoJCBN55MkiT179qDRaPDx8aGiooI9e/YoCcjWrVtp164dKpWKffv2kZCQgL+/P1VVVezevZvk5GQAtm7dSkpKCmq1mgMHDhAZGUlgYCDV1dVKMtFULjExEY1GQ05ODv7+/gQHB1NXV8fOnTuVBCQzM5O4uDi0Wq2SqDQlIH/lO6irq0On051RAmIymWjXrh1paWl88skndO7cudnxw4cPA41dtvLy8qioqMDPzw9Jkujfvz+ZmZnY7XY6dOhASEiISEAEQRAEQTglSZZl+XQKzpw5E1mWmTFjBgEBAec6rjP24osvYrVamTx5slJZvJC89957FBYWMnDgQAYOHNja4bRo8+bNFBUVccUVV7R2KMJ5UFVVxT333ENCQgKPPPIImzdv5rrrrmPgwIF4enry2muvMWfOHAoLCxk0aBCHDh3ip59+Ytq0aUyZMgWdTkdxcTHffvst6enppKenc/3113PHHXdckP9GCIIgCIJwYRCzYAmK7t27i+TjEqXX64mPj2fChAl8+umnzY55e3vTpk0bpkyZwqhRo5gzZw7p6em4XC7S09OZOnUqH3zwAYMHD6a6ulrpIiYIgiAIgtASkYAIwiWuaVKJwMBA7rrrLsxmc4vloqOjmTx5MpMnT+aGG27g8OHDPPzww6SkpNCxY0cOHz5M7969lW5jgiAIgiAILRHT8ArCJcpsNvPf//5XSUDUajUxMTEUFRWhUqlQq9U88cQTyLKsjCmJioriqaee4vHHH0er1ZKVlUVlZSV6vR4PDw+0Wu0FOUueIAiCIAgXDpGACMIlSpIkNBpNs/cAOp1O2adWq0/4jFqtVvbrdDoCAwOVYyL5EARBEAThz4gERBCEs3ImM24JgiAIgiCImoMgCIIgCIIgCOeNSEAEQRAEQRAEQThvRBcsQbhEWa1WLBYLNpsNjUaDp6cnXl5eHDt2DH9/f/R6/QljOhwOBzU1NVRUVOB0OvH29iYoKAi1Wi3GfwiCIAiCcFpEAiIIl6iSkhLS09M5evQoPj4+dOnShZSUFL7//ntGjRpFVFRUs6TCarWSn5/P7t27yc3NxWq1EhoaSr9+/WjTpk2zweuCIAiCIAgnI7pgCcIlyu12s2/fPpYvX8769etxOp00NDTw9ttvc/jwYWRZVsq6XC4yMzN57bXXmDdvHrW1tWg0GpYtW8bcuXMpLS1VWkbKy8uxWCw4HI5WvDtBEARBEC5UogVEEC5RsbGx9OzZE6vVSlhYGN27d6eysrLFsnl5eSxbtozCwkIWL16Mr6+vcqyhoYHDhw/z73//m7Vr12Kz2UhLS+Pxxx+nR48e5+t2BEEQBEG4SIgERBCEP5WXl4fD4aB9+/b4+Pg0O6bX65k/fz46nY733nuPhIQEjhw50myNEUEQBEEQhCaiC9Z50rlzZzZs2MDIkSMxGo0X3Ovqq69m7dq1QOPYgFdffVWJ/aWXXlJ+GV+xYgUrVqwAoLKykpdeekkp9+qrr1JSUgLA2rVrWbp0KQA1NTXMmTNHKTd37lwKCwsB2LBhA9988w3QOMbg+eefV7r+vPXWW+Tm5gKwZcsWPv/8cwBsNhuzZ8/G7XYD8O6773Lw4EEAduzYwccffww0DpieNWsWLpcLgAULFrBnzx4A9uzZw4IFC4DG7kWzZs1Sugx9/PHH7NixA4CDBw/y7rvvAiDLMrNnz8ZmswHw+eefs2XLFgByc3N56623lHLPP/88VqsVgG+++YYNGzYAUFhYyNy5c5VnMWfOHGpqagBYunTpWX8HhYWF56Trk91ux+12tzgwXZIkIiIi2L17NwsXLiQjI4PIyEg6d+78t8chCIIgCMLFT5KP7+h9CjNnzkSWZWbMmEFAQMC5juuMvfjii1itViZPnkxycnJrh3MCm81GVVUVDQ0NrR1Kizw8PNi/fz+VlZWMGTOG2tpazGYzABaLBU9PT9RqNfX19Up5l8t1ynKyLGM0GnG73dTU1CjlqqurMRqNaDQaGhoacLlcmEwm3G431dXVmM1mJElqVs5ms+FwOPD09ESWZSwWi1KupqYGg8GAVqv903J6vR6dTofdbsdms+Hl5XVCudraWrRaLXq9HofDQUNDw5+WczqdWK1WvL29lXLe3t6oVCrq6upQq9UYDIZm5ZqemZeXFyqVCqvViiRJp/VsT/YdOJ3OM5qR6qeffmLNmjWEhYVx3333UVlZyYABA5g7dy79+/dXVjzfvn07CxcupLKykvfff/+EFdIrKipYtWoV6enp7N69G5VKxZNPPkn//v3/8t+kIAiCIAj/TKKPxHmi1+sJDg5u7TBOSa/XY7PZUKvVSoUWaLbt4eGhbJ9uOZVK1exYU+UbwGAwNCt3fPee48vp9Xr0ej3Q+Iv78eW8vLzOuJxOp1NmbfpjOU9PT2Vbq9Wi1Wr/tJxGo1Hi/WM5k8nUYjlo/syMRqOy/Ve/g3PV7SkmJoaIiAgyMzP56quvmDRpEpIksX//fnbu3EloaChdunQhLS2NjRs3smrVKjIzM0UCIgiCIAjCCUQCIiiOr8gK/3z79u3j559/Zv369URFRdGpUydSU1Nxu9289tprfPHFF0iShJeXF+PGjaNPnz4UFxfz9ddfs2nTJjQaDSUlJXTp0oWDBw9SVVWFVqtVWpo6dOjQ2rcoCIIgCMIFSCQggnCJUqvVJCQkoNPp8PPzU7qTXX/99ZSWlirduEwmE3q9noSEBCZMmMDatWspLS3F5XLRpk0b0tLSKC4u5sCBA9hsNiIjI4mKiiItLa2V71AQhAuR7HIh/aEb58Xmn3APgtCaRAIiCJeohIQEEhISTtj/6KOPnvQzXbt2pUuXLjQ0NFBfX4+fnx/Q2O3MbrfjcDiU8S6CIAgtkdRqSu+7D0d2dmuH8pdo4+MJfP311g5DEC5qIgERBOGMqFQqZfa04x0/rkYQBOFUHNnZ2LOyWjsMQRBaiZiGVxAEQRAEQRCE80YkIIIgCIIgCIIgnDciAREEQRAEQRAE4bwRY0AE4RJXWlrK3r172bNnD/X19aSkpDBkyBDcbjfLli2jrq4OjUaDn58fMTExJCYmnnCOrKwsdu7cSUVFBW3btmXw4MEAuN1uMjIyWL9+PWlpaXTv3r3Z+ilnwuFw8NNPP2Eymejfv7+y5smePXvIzc0lICCAbt26nfF5a2traWhowGw2K2u+CIIgCIJw7ogERBAuYT///DNLliyhoKCAtm3bIssyH3zwAb/88gv3338/s2bNon379vj5+VFVVUVlZSWBgYH861//IjIyEoC5c+fy888/ExYWRlBQENHR0ciyTElJCQ899BCSJNG+fXtmz57NmDFjGDduHG3atFFisNvtrFu3jgEDBpxyFXebzcbLL79Mfn4+v/76K2FhYZSXl/P++++zdu1aLrvssr+UgKxYsYL09HTuvPNOYmJi/tJzFARBEATh9IkERBAuUbm5uSxevBiNRsM999xDaGgokiRRVVWlJAKlpaUMHjyYrl27YrfbOXLkCKtWreK5557jnXfeYfv27axYsYLp06eTkJCAh4cHPj4+1NfXc+DAAdavX89nn31GSEgI/v7+LF++nE6dOjVLQOrq6njttdfo0aNHs1Xj/8jtdlNeXo6vry/ffvstU6dOZc2aNRQWFqLX66mpqaGuro4ff/yRb7/9lvr6eiIjI7nxxhtJSUmhuLiYX375hbVr11JfX09UVBRPPfUU8+fPJz8/n9zcXPr27cugQYPEIoqCIAiCcA6JBEQQLlGHDh2iqqqKtLQ0evfurUyhK8syLpeLqqoqAKKiomjXrp2yXVdXx1NPPUVDQwObN28mPz+fdevWsWXLFoKDg+nZsycdOnTAbrdTVVVFUlISvr6+9OzZkw8++EA5bxOXy8W+fftwuVynFfe4ceNYsmQJvXv3Zv369RiNRtq3bw80rkei0+no1KkTBoOBzZs3s3r1asxmMxkZGfzyyy9ERkbi7+9PSUmJsnBiXV0dKSkpxMbG4u3t/fc8YEEQBEEQWiQSEOG0OJ1ONm3axKFDh7Bara0dzgmCgoIIDQ0lOjoab29vDh8+TMeOHZFlmczMTDp27IhWqyUnJwcPDw/CwsKoq6vj4MGDdOrUCYBt27bRvn179Ho9R44cQa1WExkZSX19Pfv27aNz584AZGZm0rZtWwwGA3l5eciyTHR0NDabjaysLLp06QLAjh07SExMxGg0UlBQgM1mIzY2FofDwa5du5SVwnfu3ElcXByenp4UFRVRV1dHfHw8TqeTHTt2kJaWhiRJ/P7778r9lZSUUFlZSVJSEi6Xi+3btyvlTldpaSkGgwE/P79m63dIkqSMr/gjb29vkpKSqKiooK6ujgMHDuDj44PD4cBut3Po0CEqKyvx8fEhODiYqKgoPv30U9q0acPBgwcpLy/H5XJx7NgxDhw4wNGjR6mtraW2tpavv/4aDw8PgoODSUtLw8fH54TrS5JEnz59+Omnn/jqq6+orKwkISEBt9uNxWJBo9EQGxuL0+nE4XBgtVrZtm0bAwcOpKCggKNHj9KtWzd69epFXV0dHh4e9OjRA4fDwRVXXEFycrJYy0QQBEEQzjGRgAinxW6387///Y89e/ag1+tbO5wTJCUlERkZSffu3enYsSMHDhygY8eOQOMA6bZt26LVajl69Chms5mwsDAaGhrYv3+/koDs3buXpKQk9Ho9hYWFaLVaIiMjsdlszRKQffv2ERcXh8Fg4NixY7hcLqKjo3E4HOzdu1dJQPbt20dUVBRGo5Hi4mJqa2uVyvGePXvo0qULkiRx4MABQkND8fT0pKysjNLSUuLj43G5XOzZs0dJVA4ePIi/vz/e3t5UVFSQl5dHUlISbrdbSXzOJAFRqVS4XC5cLheyLJ/WZ91uNw6HA51OhyzL1NfXk5SUxEMPPYSvry8LFixg+/btbN++ncsuu4xJkybxww8/EBkZyY4dO3A6nej1ekpLS8nIyGDr1q3YbDZqa2v54Ycf0Ol0tG3blsTExBYTEAAfHx8uu+wyPvzwQyZNmkTbtm3Zs2cP0JgoHzhwgFWrVlFfX09ZWRmenp44HA7i4uIIDQ0lIyODmpoaOnTogF6vx8PDA51Oh6en5wmLKwqCcG5o4+NbO4S/7GKOXRAuFCIBEU6LzWajuLiY6dOnc/PNN7d2OC1at24dNpuN4OBgJkyYADT+Yn7DDTcoZQYMGKBs+/v7c/XVVyvvr7vuOmW7d+/eyraPjw9TpkxR3l9zzTXKdvfu3ZVtT09Prr32WuX95MmTle2mpATAw8OD66+/Xnk/ceJEZfv4sQd6vb5Z7OPHj1e2k5OTSU5OBkCr1TJ16lTOVFRUFFarlaNHj1JTU4OXlxfQmGzW19c3KyvLMk6nk6KiIjIzM0lISCAgIICQkBCKi4sxGAyYzWbatGlDXl4e1dXVeHt78/jjjzN+/HjKy8tZvnw5e/fuVVpRoqKimDZtGhUVFYwcOZKXX34ZLy8vJRk4lcmTJ5OZmcmwYcMwGo1KAlJRUcGTTz7Jtddey5QpU9i4cSMrV64EYOjQoYSHh7NmzRo2b97M66+/zqZNm1Cr1UoSJgjCuSe7XAS+/nprh3FWZJcLSa1u7TAE4aIlEhDhH6Nfv36tHcJFpWPHjoSGhrJ582a++eYbJk6ciNvtZseOHaSnpyvJT0NDA7W1tRQUFPDDDz+waNEi7rvvPgC6du3KU089RVFREQaDgYMHD2K325XZqBwOB9HR0RQXF7Ny5UquvfZaYmJi0Ol0SlcnSZLQarUEBgbi5eV1Wi0xkZGRfPnll0BjFzZoTJIcDgcWi4UxY8YQGhrKkSNHsNlsyLJMXl4ebrebe++9l/LycsaMGcOePXsIDg6msrJSmY5Xq9WiFhULQThn/gkV93/CPQhCaxIJiCBcogwGA/feey+ffvopL774Ig899BAajQZJkpg5cybQmBxcddVVaLVavL296dSpE48++iiTJk0CYMyYMfzwww9cffXV2Gw22rVrx7XXXktaWhoWi4XZs2fz2WefUVdXxz333MPkyZMJCQlpFodarSYiIgKV6vTWRW0pQZEkCZVKhY+PD9OnT2fgwIEYjUYCAwMJDw8H4KeffmL+/PnIsoy3tzcpKSkMHz4cp9PJSy+9xNVXX02PHj2YNm0aw4YNO5tHKwiCIAjCKUjyafY7mDlzJrIsM2PGDAICAs51XGfsxRdfxGq1MnnyZKVrivD3qays5IYbbuCKK664YLtgCWdOlmWl5aCuro76+nqCgoKUaXj/ODOVJElKZb+Jy+XCYrGgVqsxGAxotVokSUKWZWpra6mqqiIsLAyVSqV8/o8xuN1u5ZwnawE5Wbmme2ja53a7qaioQKVS4e3tjUqlQqVSIcsyDQ0NWK1WPDw8MBgMyrncbjfV1dXodDo8PDxOOxkSBOHM/RO6L/0T7kEQWpNoARGES1hTQqDT6dBqtfj4+CgV+1PNhnU8tVp9wueaeHl5YTKZlOTjZDGcTpenk5X7Y1KjUqnw9/c/4ZgkSUri8cfPqNVqzGbzGQ3iFwThr5HUakrvuw9HdnZrh/KXaOPjL/oxLILQ2kQCcgHZsmULe/fupa6urrVDOUHTYGUxUPefqaWWiTPRUotB0/nO93iKU93LqY6JVg9BOH8c2dnYs7JaOwxBEFqJSEAuEDU1Nbz88suEhYVhNptbO5wTNDQ0kJCQcEL/fUEQBEEQBEE4EyIBuUDY7XZ+//13Bg0apKw6fSGpqakhPz8fu93e2qEIgiAIgiAIFzGRgFxA1Go1qamp9OrVq7VDOUFlZSVvv/02lZWVrR2K8DdraGigqqqKyspKXC4XPj4+hIWFIcsy+fn5OJ1OJElCr9fj5eXVYgtdZWUlFRUV2Gw25fPQOEC8pKSE4uJiAgICCAwMRKvVnlZcNTU1VFdXo1arlZY3WZYpLy+nqqqKqKiov7RqucvloqGhQQw2FwRBEIRWIhIQQbiEVVRUkJ2dzf79+ykuLsZmsxEUFES/fv2IiIjgyy+/VGa3aprWNi4ujpiYGAwGAwD5+fls27aNvLw8GhoalPVFHA4HBw4cICsri5ycHAIDA+nfvz9RUVF4eHj8aWw5OTls2bIFrVbL+PHj8fLyQpZlVqxYwb59+7jnnnsICAg447ErNTU1bN26lZ49e2IymcTAc0EQBEE4z0QCIgiXKIfDwYoVK1i6dCkNDQ107doVlUrF6tWrycrK4tFHH+XNN99k0KBBhIWFUVpaSkFBAVqtlmeeeYYuXbpgs9mYN28eu3btIikpSZlu1+12U1hYyO23305sbCy9e/dm4cKFZGdnM3XqVNq2bfun8WVlZfHJJ58oSdGoUaOora1l5syZZGdnc8011+Dv709NTQ1Wq1WZotdkMuHp6Yksy1RVVWG325FlGb1ej06nY8+ePdx777188MEHxMbGEhgYeNaD8AVBEARBOH0iARGES9T+/fv56quvSE5O5rHHHsPb2xto7OZks9mora0FYNq0aQwaNAiAQ4cO8f7773PnnXeSnp7Or7/+yi+//MKHH35IXFwcKpUKtVqN1WolKyuLffv2sWrVKgwGA506deLJJ5+kX79+p5WAQOOK50VFRXz00UcMHjyYxYsXExcXx6FDh4DG7mNz587lo48+oqamhoCAAK655hqefPJJqqurufvuu0lPT8fpdNK/f3969OhBfn4+OTk5TJ06FYPBwLp165R7FwRBEATh3BMJiHDGLvSpeJsWwTt+obrjt5vKtHSstcv92TlOp9zpOnDgAL6+viQmJjargEuShMFgUBKQ44WHhzN27FjeeustqqurWbduHVVVVYwYMYLa2lqSk5OZPn06U6ZMwdvbG4fDgcViwWAwEBISQkVFBVartcW/oZbib9OmDcHBwezatYtly5bxyiuv8Prrr/Pbb78BoNVqmTBhAuPGjSMsLIxdu3YxadIkpk6dynfffUdxcTGLFy/Gx8eHI0eOoFar6dy5Mz/88APvvfcesbGxeHt7i9YPQRAEQTiPxAhM4bR4eHgQFRXFv//9b/R6/QX36t27N48++ii//voreXl5zJs3D2ismD///PPK2iqLFy9WKq9FRUW89tpryj3OmTMHi8UCwLJly1i9ejUAZWVlvPzyy0q5l156ifLycgBWrlzJjz/+CEBVVRVz5sxRyr366qscO3YMgF9++YUlS5YAUFtby/PPP69Uwt944w3y8/MB2LBhA1999RUA9fX1zJ49Wyk3f/58Dh8+DDSuGfPpp58CjTOozZo1C7fbfUbfaX19PSqV6rQWG2yi0WgwGo3KKufHjh2jR48erFy5kqysLIYPH86qVatYtWoVKSkpjBkzhq5duzJq1Cj69eundOH69NNP6dOnD9HR0bRv356lS5eeNCmJi4tj1KhR3H333URFRdGxY0dl8LhGo6GqqopFixYxceJEbr/9durr6ykpKSE6OpoDBw4wf/580tPTiYqKolevXhiNRjQaDYGBgWJaaUEQBEFoBaIFRDgter2e2bNn869//QuXy9Xa4ZxAp9OxadMmampqCA8PZ/r06cqxu+++Wxn0PGrUKKXyGhQUxK233qqUu+uuuzCZTAAMHTpU+VXcz8+PO+64Qyl35513YjQaARgwYICy39vbmxkzZijvb7vtNuW6vXv3VhIEo9HI3XffrZz/pptuUsp169aNLl26AGAwGLjnnnuU802bNg29Xg9AamqqMl2zVqvl3nvvPeNf8cPDw6mqqqK4uFgZP/FnLBYLe/fuJSwsjODgYPz9/bHb7fj5+REYGEjHjh2pqKjg6NGj+Pn58eabb7Jz504aGhpYv349GRkZeHp60qtXL1JSUrDZbKjVauLi4k56zZCQEJKSkvj888+55557mt3npk2b+Oijj3A6nTz66KPodDruvvtuoPE7fO2119i4cSNz584lLCyMKVOmEBsb2+z8ovVDEM4/bXx8a4fwl13MsQvChUIkIMJpkSQJs9l8QS6S2KR///643W7UajWenp5AY9xeXl5KmeNnXzq+HNCsXNMMT9C4Qvbx5Y7fPt1yTYlDU7njr3V8ueOnlf1j7E3JUVO5prJ/LHe62rdvj6+vL5s3b2bFihWMGDECt9vN/v37yczMZPjw4UpZt9tNcXExq1evZuHChUydOhW1Wk3Hjh155513sFgs+Pr6UlhYiMPhoF27dkiShI+PDz169GDnzp1kZGTQu3dvoqKiCAgIwMfHR+k6dqqpeTUaDfHx8Xz00UdERUXhcDiUY8eOHUOtVpOcnEzXrl3JycnBarUCcPDgQbp06aK81qxZw549e0hMTMTX15fy8nISEhLO+LkJgnB2ZJeLwNdfb+0wzorsciGp1a0dhiBctEQCIvxjXMjJ0YXI19eXK6+8khUrVrBgwQIWL16MSqWisrKSvn37Kl2iXnrpJRYuXIgsy6hUKnr06MHVV18NNLYALV68mDlz5mAwGKirq6Njx46kpqZitVr57rvv2LhxI4WFhbRp04ZRo0YRERGBRqM5o65fBoOBdu3aIctys7VoEhISWL9+PatXryY7O5uamhoaGhoA2LdvHytWrMDHx4eqqiq8vLzo0KEDZrOZrl278uqrrxIcHMycOXMwGo2iJUQQzpN/QsX9n3APgtCaRAIiCJcotVqtjInYvn07VVVVuFwu2rRpQ8+ePfH09OSee+6hrq4OtVqNXq8nNDSUTp06KV2mIiIiuOGGG9izZw8ul4uwsDA6d+6Mv78/DQ0NeHl54efnR2hoKL169aJDhw7NWnJOpX379gQHBxMREdFsv8Fg4JFHHiEgIACj0ciIESMICAjAbrcTFxdH+/btCQ0NRZZl4v+vq0RkZCTJycl07NgRs9nMuHHj+PXXX0+765kgCIIgCH8fST7NKY1mzpyJLMvMmDGDgICAcx3XGXvxxRexWq1MnjyZ5OTk1g7njJWXlzNw4EDee++9C3IldOGfzeVyYbPZlJXM4czGRlitVqUrVVPLRtN0vnV1dfj5+Z2zFgZZlmloaMBut+Pl5dUsoXA6nVitVgwGQ7PubbIs43A4cLlcGAwG0fohnHeiC8/FTXx/gnB2RAuIIAio1WqMRqMyuP5MtfS5pul8jx8ncy5IkoSHh0eLq6trNJoW1/iQJKlZQiII55ukVlN63304srNbOxThDGnj4y/6MSyC0NpEAiIIgiAIrcCRnY09K6u1wxAEQTjvROdnQRAEQRAEQRDOG5GACIIgCIIgCIJw3oguWIJwibLb7WzcuJHc3FzUajUmk4k2bdrQuXPnE8ru37+fnTt3UlBQgNFoJC0tjbS0NGpra1m5ciU5OTmEhISQlpZGXFzcOR/3IQiCIAjCxUskIIJwiaqvr+d///sfeXl5dOrUiZqaGgoLC5FlmbfeeouoqCjcbjevvvoqmzdvxtvbm4iICA4dOsRXX33Frbfeiq+vLz/88AMRERHk5OTw9ddf079/fx544AExva0gCIIgCC0SCYggXKJkWaampobk5GTuuOMOnE4nVVVVLFq0iEcffZSPP/6Y5cuXs337dgYPHsygQYPw8PDA4XBQXV1NYGAgJpOJiIgIZRHC119/nd9//51jx44RFhbW2rcoCIIgCMIFSCQggnCJ8/HxURbsczgc1NfXM2HCBOrq6ti2bRs+Pj506NCBlJQU5TOyLONyuVCr1fj7+wON3bTcbjc6na7FKXEFQRAEQRBAJCDCJai6upo9e/aQnp6O2+1u7XBO4OvrS6dOnejYsSMqlYr09HS6d++OWq1mz549+Pn5ERISgsVi4dChQ3Tu3BlZlsnIyCAtLQ2tVvuXr61Wq+nQoQMVFRXU1dVRXFxMUFAQXl5ezcpJkqQsOAhQWVnJDz/8gMvlokePHi2uvSEIgiAIggAiATn/3G6oqoL8fKirA5UKoqJALIp23hQVFbFq1Sq++uorIiMjWzucE4SHh+Pl5YWHhwdJSUkcPnyYrl27olarKSoqQqPREBISQn19Pfn5+cqg8cOHD7c4gPxMyLKsrBzelGTY7XacTudJP1NbW8vPP/9MRkYGnTp1YujQoajFCsGCIAiCIJyESEDOJ7cbjh2DX3+FL7+E3NzGxGPKFKSRIxuPC+dcaWkpADfffDP33HNPK0fTsvLychYvXkxycjLXXHONsn/IkCHKdkhICGPHjgUaWySmTJnyl68nyzJutxuLxcKaNWtISUnB39+fpKQktmzZQkFBAR06dECn0+F2u6mtrUWlUqHRaEhPT+f9999n4MCBjB8/nri4uL9+44JwCdH+X9dH4eIivjdBOHsiATlfZBnKy+H11+GNN8Bm+//H9u9HX1SEtrZWLMwiAODv78/NN998Xq5ls9mwWCzU1NSwceNGnnvuOZ588km0Wi0jR45kyZIlrFq1ipCQEJKTk6murmb16tX4+fkRFBTEbbfdxk033cS4ceMICQmhtrYWnU6HTrTqCcJJyS4Xga+/3tphCH+R7HIhiZZeQfjL/pH1XVmWL7yX2438+OPw5pvNkw+AqiqM8+czsqICf1lunYcmXJIkSeLNN98kOjqarl278uqrr/L4448zbdo0NBoNSUlJPP300xw7doyrrrqKpKQkUlNTmTdvHkFBQSxbtoyioiJmz55Nt27diIiIYMSIESxatKi1b00QLmii8npxE9+fIJydf1QLSNM6BhfiDDyGDRsw79+P4WTdrGpquF6tJlR0wxLOE7PZzJdffon8h6RXkiQkSVLeDxo0iEGDBlFfX09dXR1qtRofHx8kSaJnz548++yzJ5z7+M8LgiAIgiAc7x+TgAwfPpwZM2awdOnSZrPzXChG19QwraKCtnZ7i81OEqAWrR/CedSUJPxZstB03MPDQxmcfvxnRLIhCGdOdOG5uInvTxDOzoVXU/+LUlJS+Oyzz3A4HBdkhci0dSs+776LtGkT1Ne3WKZUpSLoPMd1rqSnp5OZmXlBTnObk5NDaWkp3bt3b+1QLip/TDwEQfjrJLWa0vvuw5Gd3dqhCGdIGx8vxu8Iwln6xyQger2eqKio1g7j5Hx9G2e/2rmzxQRE1un4WqcjQKXC5/xH97dav349y5cv59ixYxfkNLcWiwWn03lBtpQJgnDpcGRnY8/Kau0wBEEQzjtRAztffH1hyhSwWuHHH6G6GhoaQKMBvZ76W29l69dfU/0P+IW5uLiY+vp64uLiGDx4cGuHc4Jdu3axZ8+eE8Y+CIIgCIIgCOeeSEDOp759G6fj9feHvXuhpAQ8PaFdO2zTplH100+cfLm3i4uXlxfx8fH07NmztUM5gdPppLi4GJfL1dqhtCqXy8WxY8eorq5W1vTw9vYmMDDwhLKVlZWUlZVRV1eHRqMhMDCQ4OBg5XhtbS11dXWYTCY8PT3P520IgiAIgnCREQnI+davHyQmwo4dUFQEZjMMHNg4VkIMaBPOI7vdzpo1azhy5Ag+Pj5otVrMZjPx8fG0b98eg8GALMscPnyYrKwscnNzqa2tRa1WExoaytChQwkJCaGoqIisrCyqqqro0KEDycnJrX1rgiAIgiBcwEQC0hqCg2HEiOb7ystbJxbhkmWz2fjuu+8oLS1l4MCBVFdXk5ubS2lpKS+88AI9e/bEYrHw9ttvk52dTVRUFG3atKG8vJzffvsNvV7PxIkTWbt2LZ999hmenp54e3uLBEQQBEEQhFMSCYggXOL69u3LzJkzAbBarcydO5dbb72VLVu28Pnnn5OTk8P06dMZO3as8hlZlrH934KaQ4YMoaysjAMHDrRK/IIgCIIgXFz+kSuhC8LpOier3v+Nr+NjPNV2S+//CoPBwNSpU9m7dy/V1dVkZWXRtm3bE2YzkyRJWRMkJCQEX19ftFrtWV1bEARBEIRLg0hAhEtO03TNDz/8MFqt9oJ7tWvXjjfffBO73Y7b7ea5557DbrcDsHDhQrZu3QrA4cOHefPNN4HG5GPWrFk0NDSc1bORJAkvLy9kWVYGlqvVatRifJIgCIIgCH8T0QVLuOSEh4fz4IMPcuedd7Z2KC1SqVTU1tby7rvvcvfdd/Pggw+i0+kAmDRpkpIMREdHc/PNNyufe+CBBzAYDGd1bafTyebNmwkPDyckJISYmBjy8/MpF2OUBEEQBEH4m4gERLjkqNVqjEYjRqOxtUM5KS8vLyZPnowkSc3i1Ov1yrZarcbDwwPghHJnyu12U1tby5YtW3jyySe57bbb0Ol0jBgxgscff5yff/6ZyMhI4uLiqK2tZd26dRgMBgYNGiRWRxeEv0gbH9/aIQh/gfjeBOHsiQREEC5AGo2GoKCg83KtJUuWcOjQISRJQqVS0bdvX6677jo0Gg3t2rXjqquuYtOmTTz++OOYTCbq6+uRZVlpQXriiSfIyMigtLSU7OxsCgoKuPrqqzGZTOclfkG4GMkuF4Gvv97aYQh/kexyIYmuqYLwl4kERBAuUQaDgWuuuYaDBw+iVqvRaDT4+PjQqVMn2rRpo4wHueyyywgNDSU3N1cZYxIcHExCQgIAKSkpBAcH43Q60Wq1REVFiTEjgvAnROX14ia+P0E4OyIBEYRLlMFgYPz48X9ark2bNrRp0wa73Y7NZkOlUjVr3bj++uvPZZiCIAiCIPzDiAREEITTotPplMHwgiCcHdGF5+Imvj9BODsiAREEQRCE80xSqym97z4c2dmtHYpwhrTx8WL8jiCcJZGACIIgCEIrcGRnY8/Kau0wBEEQzjuRgAjCJeqPq6Y3Tad7/P4LYYrdpnguhFgEQRAEQTh7YiV0QbhEORwOfvnlF1auXMnRo0eBxsq+w+Hgf//7H5mZmdhstlaNcfny5cyZM4eKiopWjUMQBEEQhL+PSEAE4RJVX1/Phx9+yP3338+HH34IgN1u5+uvv+a+++7jhx9+oL6+vlVjzM/PZ8eOHcr0v4IgCIIgXPxEFyzhr6mthf374dChxu24OOjZE7Ta1o5MOE2yLON2u7FareTl5bFjxw6io6P54IMPSEhIwG63I8syP//8M9999x179+5Fo9HQvn177rnnHiIiIqisrOS1115jx44daDQaBg0aRGpqKuXl5ezduxeArKws5s6dy2+//cb3339PWVkZycnJjBkzhr59+3LkyBGef/55AgMD2b59O7Gxsdx5552kpKTgcrnIycnhlVdeYf/+/URERPDQQw8RFxfHjz/+yOLFizly5AhGo5Fu3bpx0003ERYWRnFxMc899xx79uzBz88PHx8frrrqKkaMGEFRURGffPIJv/32G6GhoUyZMoV+/fpRVlbGl19+yfr167FarcTFxXHrrbfSsWPHVv6mBEEQBOGfRbSACGdu1y54/XWYM6fxv/PmwfPPw913Nx4Tv1ZfNFQqFUlJSQQGBrJo0SIyMzNRqVS0bdtWGXPh5eVFjx49mDx5MsOHD6e8vJwlS5YA8P3333Pw4EEGDhxI//798fb2pri4mKysLL7//nscDgcdOnTAZrPxv//9j/DwcAYOHEh1dTWrVq2ivLycqqoqVq1ahb+/PyNHjuTQoUNs3ryZkpISAFwuF2q1mjFjxlBfX8+yZctwOp2YzWb69+/PddddR69evSgoKGD58uU4HA7ee+89CgoKuPLKK+natStHjx4lLy8Pi8XCjh072LFjB1dddRXdu3fnzTffpLq6muXLl5OTk0PHjh2ZOHEiKSkprd4CJAiCIAj/RKIFRDgz27bBF1/Ad9/BsWNgtYLbDTodaBr/nHRBQRQdOcKBAwfYv39/Kwd8oqioKNLS0pRf2DMyMujbty+SJJGRkUFycjJms5mjR49SVVVF+/btcTqdbNy4kX79+iFJElu2bCEuLg4/Pz+KioooKSkhNTUVl8vFhg0blHLbtm0jKiqKwMBASkpKKCgooHPnzrjdbtavX0/fvn1RqVTs2LGDkJAQQkJCKCsr48iRI3Tt2hVZllm3bh19+vRBrVaza9cu/P39CQ8Pp7KykoMHD9K9e3elXK9evdCeYStUUlISiYmJvPfee5SVlTFq1Chyc3OVBCQ4OJiKigqKioqorq7m6NGjysDwJUuW0Lt3b6666iq0Wi1Wq5X8/Hz27t2L2Wxm+PDhBAYGcvjwYaqqqhg6dCgJCQl8++237Nmzh7179+Lh4YHT6WT06NEEBARQUFDAwYMH6dy5MwB+fn4MHDiQbt264XK5+O2337j11lsJCwujoqKCsrIyqqqqyM3NRafT4XK5+Prrr5k+fTpTpkzh6NGjbNu2DbvdTnFxMZs3b6aqqgqj0UhtbS0ZGRnk5eWRn59PSUkJYWFhJCcnYzQaCQgI+Hv/+ARBEARBEAmIcAby82HJEvjmGzhypDHxaNLU6vHZZ4R17oxOlsl1OnE4HK0R6SnZ7XYCAwPR6XRERUVx7Ngx5VhpaSmxsbEA1NXVUVlZCYDb7aa4uFgpV1ZWRkREBABWq1UpJ8syx44dQ5ZlJEmivLyc4OBgoHHMRXl5uXKOpnIA5eXl+Pj4AGCz2U4o53a7UavVVFZW4uHhodxHWVmZUq64uBj38d/JaQoICCAxMRGz2czOnTt57LHHmDdvnnJ8//79ZGRkUFxcjNVqRZZl6urqcLvdbN26lYceeoiQkBAMBgMATqcTo9FIu3bt6N27N7Is89tvvxEREUGbNm2IjIwkJiaG3NxcDh48SGpqKiaTifbt2yNJEu3atSM9PZ3q6moAzGYzqamp+Pr6kpiYyBdffIEsy+zevZuMjAyqqqqwWCxKdzK3201eXh79+/fH19cXq9WqLKBYWVlJTk4OXl5eHDx4EIBOnTphs9no0KEDZWVlZGdn43Q6iYmJYdiwYWf8PAVBEARBODWRgAin78cfYdUqKChonnwcr7aWtlu3MrpnT4bccQfjrrnm/MZ4mrKzs9m5cyeJiYlMnDhR2X/ZZZcp20lJSSQlJQGNq4AfX27UqFHKdlxcHHFxcQBoNBomTZqkHBs+fLiyHR0dTXR0NNDY9en4ckOGDFG2w8PDCQ8PBxqnnj2+3IABA5Tt4OBgRo8erZQ7Pr4zIUkSsbGxTJ06ld27dysJWJOPPvoIrVbLFVdcQVRUFOvWrWPTpk3IskxtbS0NDQ243W5cLhdOpxO73X7CNTQaDU6ns9nL7Xaj+b9Ws6ZEzOl0YrFYcLlcLcaqVquRZRlZlpk3bx7JyclceeWVGI1G1q1bR3Z2NpIk4e/vr8RmsViUmCRJwmg0EhUVxbBhw5AkiX79+hEbG0tycjKhoaFs27aNTZs28f3332MwGP7ycxUEQRAEoWUiAblASJKESqWirq6Oqqqq1g7nBBJgXL0aTVYW0p9MzapxOvGvqMB+AU+dGh8fT3x8fGuHccFoGowNNKv8N7UqpKamkpKSQm1tLUeOHAEak6guXbqwdOlSwsPD8fT0pKqqSpnS93iDBg3ijTfeICcnB41Gw759+7BarXTv3p26ujocDgdlZWVYLBZ+/fVXOnToQFBQ0Em78Lndburq6khJSSE2Npbc3Fzlumq1mkGDBrFw4UKlW11TK1d4eDjdunVj3bp1xMbGotFo+P3333G73Wzfvp2goCCmTJlCly5dWLhw4QXZhVD459CKf4MuSuJ7E4SzJxKQC4RGoyE4OJhnn332jPvwnw8Gl4tnDh2ii8Pxp380aqcT79pa7LW15yU24a9Tq9Wo1eoT9qtUKuU1fvx4PvjgA+bPn4+npydBQUHExcUhSRIvvvgiN910E4sXL8bhcDB69GhlXEtT64YkSURFRTFlyhT+9a9/UVZWRtu2bZkyZQoJCQlkZmZy7NgxunXrRmVlJV27duXKK68kKSmJDRs2oNFolPEoKpVKifm6667jgw8+4Nlnn8XLy4ugoCDat2+PVqvlkUceYdasWdx+++3ExcXhdrvR6/WEhoYyYMAAMjMzGTFiBNXV1bhcLr799lt+/fVXfvjhBywWC76+vsTHx/PEE0+c1+9DuHTILheBr7/e2mEIf5HsciG18G+nIAinR5L/uBzyScycORNZlpkxY4YYmHkOyLLMkSNHKCoqavXF306m3WOP4b91K+o/GWfg1GjISkzEftNNdHvggfMUnXCmTrXi+R//WbBardjtdrRaLSaTSflMU7nKykr0ej0GgwGV6v9Prnf8eZsWOXS5XGg0GjQaDTabjR07dnDNNdewd+9eGhoa8PLyOu1Vz2tra3E6nej1emVsDDSO5fH29kav1/PFF1+wb98++vXrx+DBg5UyLpeLiooKAgMDlX02mw2bzYZKpcLT07PFZyMIgiAIwtkRLSAXCEmSiI6OJioqqrVDOSnV8OFQUtI4AP0UbHo95T4+uLy9z09gwl9yqor1H48ZjUaMRuMJx5q2fX19//S8kiSh1WqVFr7jy6lUKnQ6nTJY/HQr/U1JwvGfcTgcfPfddzz++OP4+vrStm1bpk6dSmpqqlJGlmXUarWSfDTt1+v16PX6M4pBEARBEIQzIxKQC8jxvxxfkKZPh9xcOHoUnM6Wy2g0lIeEUBQWhv64yqFwcfuzyvjpVtb/WE6v19O5c2fWrl17Ruc51XU1Gg2TJ09myJAhyqBzLy8vJbE41XVE0iGcL6ILz8VNfH+CcHZEAiKcvogIuPPOxvU+PvnkxCTEwwO6dWNvcjL5ZjOxF3pCJbQ6SZLQ6XTKlMZ/1zk9PT3x9PRUpkMWiYVwoZHUakrvuw9HdnZrhyKcIW18vBi/IwhnSSQgwunTaqFjR7jlFggMbJyWNyencb/BAEOHwoQJ1JaWUl9Q0NrRCheJc5EcNJ1TJB7ChcyRnY09K6u1wxAEQTjvRAIinBmjEdLSICgI4uPh8GFQqxv39+oF3brBTz81rhUiXNCqq6spLS2lvr4enU6Hr69vswHZLamtrSU7O5sjR44QHh5OWVkZvXv3xsvL64LpQijLMjU1NXh6ep7T1g+3201tbS0FBQUEBQXh7++v7M/JycFgMODn56cM2m8tTeum1NbW4unpecF8T4IgCMKlSyQgwpnT6SAurvEly+ByNSYh4tfmi0pFRQUbN27k8OHD+Pn50atXr1MmIHa7nUOHDvHll19SV1dH586d+fLLL4mLi8NoNF4wFVuXy8WPP/7IyJEj8fb2PmcJiMvl4siRI3z66aekpaUpC0YWFBTw+eefExkZSb9+/ZRFKltTXV0dP/74I1deeaWyYr0gCIIgtBaRgAhnR5Iax4QIFx1JksjLy2PDhg1ERkbSp08fXC4XR48eRafTUVtbi1arVX7FLyoqYtWqVSxfvpzHH3+c5ORknnrqKaxWKy6Xi7KyMmpra5FlGa1Wi9lsxtfXF4fDQWFhIRqNhvr6erRarTJlbk1NjTIblclkorS0FKfTqayubjAYMBgMWK1WbDYbJpOJ0NBQAIqLi6mrq8PpdKLRaPD29sbX15eSkhIeeOAB/Pz8iImJITIyEgCLxUJNTQ0AJpOJ4OBgVCoVubm5eHp6YrVaUavVygrtQUFBSJKEy+UiLy+PqKgo1Gq1ktA4nU6ys7OZN28eXbt2ZfTo0ZhMJr7//ns+/PBDevbsSWxsLDExMdTX11NaWorNZlPWI9HpdFRWVmKz2bDb7cp9+Pn5KeNXiouLqa2tRZIkvL29MZvN6PV6XC4X1dXVVFRU4HK58PDwQKfTodFoMJlMGAwGHA4HFosFWZbJycnh/vvvJz4+nuDgYPz9/VGpVMozUalUeHt74+/vj9vtpri4GKvViizLeHh4YDab8fLyaoW/UkEQBOGfSNQcBeESFR0dTVpaGhaLhbCwMDp37kxVVRXXXnstKSkp/PrrrwQFBTFjxgyGDBnCL7/8wrx587BarcydO5fZs2cr52poaOC5555j5cqV2O12wsLCGDduHA8++CBHjx5lypQpREVFsXv3bvz8/OjWrRuSJLF69WrMZjMPP/wwY8eO5ZVXXuHYsWPs37+fyspKOnToQLt27di2bRt79+6ld+/evPvuu3h4ePDyyy+zevVqysvLCQwMZNSoUcyYMYNvvvmGsrIy7r//fgwGAx9++CE2m43PPvuMFStWIMsyffv25cUXX8THx4dp06YxdOhQtm/fjtlsprq6mqCgIF544QUlKZowYQLLly8nMDCwWYuKWq3G09MTtVrNypUrGT16NJ9++inR0dH4+fkBjd3WNm3axPPPP092djaxsbG8/vrrdOjQgY8//pisrCzy8/MpKioiICCA2267jYkTJ2K1WnnmmWf49ddfUalUXHHFFVx99dV06tSJ6upqPvnkExYsWIDFYiE1NZXExER8fX0ZOnQo3bp1o7CwkI8++giTycSuXbsoLy/n5ptvJjExkQceeAC1Ws2iRYtYvXo1RqORMWPG8MQTT1BVVcWTTz7J5s2bsdvtdO3alWuvvZbLLrvsvP+NCoIgCP9MF0afCeEfSZZl3G73Bflq6hff9Do+5qb3LW2f6lhrlmvp/V/hdrs5dOgQfn5+LF++nCFDhrBhwwb2799P586dmTZtGmPGjOHbb7+le/fuyue0Wi0333wzP/74I5s3b+bee+9lwYIFFBYWYrfb2bNnD0OGDOGbb76hQ4cObNq0Cb1ez3//+18mTZrEW2+9BUBRURHl5eU888wzzJkzB5VKxfLly5k2bRpLly5l+/btbNmyBZfLxcSJE1m8eDHbt2/ngQceYN++fWzcuJHJkycTGBjI22+/zffff09KSgqLFi2itraWF154gfnz51NYWMiSJUsAOHToEL/88gsjRoxg+vTpdOvWjYqKCn7++WfsdjtffPEFsbGxeHt7t9jNzGw2c9ttt/Hiiy+yePFioqOjSU5OVloM9u7dy9KlS+ncuTMbN24kLS2N1157jbq6OsrKyigpKWHYsGG8++67XHnllcybNw9Zllm5ciVZWVl89NFHvPzyy+Tk5LBkyRKcTieHDx/mhRde4D//+Q+bN2+mT58+9O3bl4yMDHbu3InL5SI/P59vvvmGESNGcN999xEQEMCnn37K/PnzSUpKYtWqVRQVFfHZZ5/xwQcf8PXXX7N7924+//xzCgsLWbBgAWvXrmXGjBnN1nkRBEEQhLMlEhDhnFi/fj3XXnutsuL1hfQaPHgwX3zxBQ6Hg7q6Op577jml4j537lzy8vIASE9P5/PPPwcaV8j+z3/+o9zfW2+9RU5ODgCZmZl8/PHHQOMieM8++6xyvvfee4+9e/cCsHv3bhYsWAA0VvSfffZZXC4XAB9++CE7d+4E4MCBA7zzzjtAY1Lxn//8B7vdDsDChQvZsmULAIcPH+bNN99Uyj333HM0NDSc9XcnSRK33XYbMTExDB48mIqKCsrLy9HpdHh5eeHp6UlQUFCzdTW0Wi0lJSW88cYbXHXVVTz++OPU1dVRUlICQGBgIFdddRUpKSm0a9eOIUOGMHToUDp27EifPn3YvXu3cq7Ro0fTuXNnevXqRYcOHUhOTuaqq64iOjqarl27snv3biWJnDdvHhMmTOCZZ57h4MGDVFRUYDKZlG5dwcHBlJaWkp+fT3JyMpdddhnt27dn7Nix/PDDD8o1n3vuOa677jp69+7NyJEjSUpK4ttvv8Vms/Hhhx9y2223KQso/pHJZGLMmDFYLBbuvvtubrnllmZjaY4ePUp2djY33XQTERER3HfffaxatUrp4tS9e3cGDhxIt27d6NGjB3v37sXhcLB06VLGjx9P27ZtGT16NImJiZSXl7Np0ybS09Pp3bs3l19+OYGBgTz88MNcfvnlBAQEcPDgQVauXElmZiYJCQm0a9cOs9mMWq1WBsvv2bOHQ4cOkZuby7x583j11VdxOp389NNPREZGkpOTw7vvvsuvv/5KcHAwvXv3Puu/K0EQBEFoIrpgCedEr169uOGGGxg3blxrh3ICtVpNTk4On376KdOmTeORRx5Rjt15551o/m9MS7du3ejatSvQuGDeo48+qpS79dZblXKdOnWiQ4cOQGNF/LHHHlO66dx4442o/2+xqrZt25KUlAQ0Ljr52GOPKceuu+46ZTs+Pp6YmBigMRl49NFHlRXCJ0+erPwK36ZNG2677TYlpkceeUQp93dpusc/tqxIktRs38qVK/nggw9ITEzkxRdfpKKigueff/6Ez0iShEqlUrYlSUKtVrfYcqNSqZR7/WPZoqIi7rrrLoYNG8YzzzxDcXEx69evP+EckiQpYyg0Go1yDg8PD2U8yPHnlySJpKQk2rdvz9dff82XX36J3W5nwIAByvfT0jUMBgMPPvggS5YsoUuXLqSnp+NwOJBlGbvdTkNDAyaTCUmSMJlMWK1W5fjxUwY3XUOWZSwWCyaTSXleOp0OSZKoqKigqKioxQH2Q4YMYePGjUrXq8mTJ5/0mZhMJrp3786IESMAGD9+PPHx8cTGxqLT6Vi7di1vvfUWn3zyCddccw033HBDi/cvCIIgCGdKJCDCOdFUyfP29m7tUFqUlJREVFQUkiQ1+yX/+Ap8U+UbOGU5tVqtVBzPdbnjf4VXqVTK5/5Y7nwrLCzE19eXrl27kpyczMaNG6mrqztp+bOdmaq4uBhZlunduzddunRhzZo1VFRUKOcOCgqitLSU+Ph42rRpg4+PD8XFxRw5cgS32016ejoDBgxo8dw6nY6YmBiSkpKYM2cO119//UlbP5poNBomTpzIqFGjmiUGkiQREhJCTEwMv/zyCzfccAM//fQTPXr0OGFK3OOfiSRJDBo0iHXr1jF27FgsFguFhYWYzWZSU1M5duwY33zzDQUFBYSFhbFlyxbat29P//792bhxI7/99hs9e/Zk6NChSJKEn58f9fX12Gw23G43HTt2ZNOmTRQVFZGamoqXlxfl5eXU1NSwe/duUlJSSE1NpV+/fixfvrxZC5UgCIIgnC2RgAiXJL1e36oV9gvBjh07WLJkCRs2bCA6Opr4+Hilq83xFeg/VoyP13S8S5curF+/ngULFrBkyRJldqfTWRDwZOc8VdmYmBji4uJ47733+OSTT7BYLMpxtVrNmDFjeP755/Hx8eHZZ59l6NCh/Pbbbzz22GOoVCo8PDwYPXr0Sa8RGhpKv379WL9+PVddddVJ7+H4+zObzZjN5hPKxMXF0adPH5YvX87KlStxOp3ccMMNGI3GUz6DYcOGsWXLFh566CHcbjf+/v707duXsLAw+vTpw4oVK5g6dSoRERFUV1fzxhtvEBwcTExMDO3btyctLU2Jx8vLiz59+vDggw8SGRnJlClT6Nq1KytWrGDmzJnY7XYqKiq46667KC8vZ8mSJZhMJhoaGvDz8xNdsM4RbXx8a4cg/AXiexOEsycSEEG4RPn7+zNq1Cg6deqEt7c3UVFRGI1Gnn32Wfz8/JAkiZiYGK6//nri4+Px8/Nj4MCBdOnSBWisJM+cOZOwsDAMBgPXXHMN2dnZyLKMyWRCo9EQERGBVqvl6aefVhbk69u3L3V1dURGRqJWqwkPD1fG11x33XWEhITg5eWFJEkMHz6cbt26AY2tP00DzP38/Lj11ls5cOAATqcTo9GIr68vycnJSmtEaGgobrdbqXwHBARw5MgRXC4XMTExJCYmIkkSzzzzDNHR0c1avJxOJwBdunQh/iSVDa1WS/v27Xn44YdPODZ06FDsdjtt2rTB39+fwYMHYzabOXbsGMHBwfTp0wedTseYMWOU5wQQGRnJ7NmzUavVtGnThhtuuIGcnBw0Gg1xcXEkJyej1+uJi4vjrrvu4vfff0en0+Hp6akMerfb7YSHhzN48GClhUWtVnPPPfdw8OBBzGYzQUFBhIWF4e3tTV5eHhaLBbVaTVxcHGFhYdTV1eFwOPDw8CA6OpqUlJSz/nsTmpNdLgJff721wxD+ItnlQjpJt0xBEP6cJJ/mtDkzZ85ElmVmzJhBQEDAuY5LuIh988037Nq1i3bt2imLswn/fLIsU19fjyzLGI3Gc7YA4PHq6uqU7mfHj9GQZRmn04nb7Uar1SoVcafTidPpPOVifLIss3XrVt5++23S0tK46667/pZY3W43DQ0NzVo+TkdDQwMajabZGiRNcTqdTmV9FEmSyM7O5p133kGlUvHkk0+e0CLT0NCgdPFreiYulwur1aqco2ntk/r6enQ63d8+rkgQBEEQRAuIIAh/C0mSzrhyfbaaWlVaiqWlcRtNM6GdiizLuFwuDAYDw4cP/1vihMYxO3/l+ZwsWWq6x+Pvs7S0lMjISCIiIlrsDtbSudRq9QmLDDatbyIIgiAI54JIQARBEI6jUqno0aMH3bt3b3HdjwtZz5496dmzZ2uHIZwG0YXn4ia+P0E4OyIBEQRB+INTDYS/kF2MMV+qJLWa0vvuw5Gd3dqhCGdIGx8vxu8IwlkSCYggXOJONQzsTCu0LZ3r76oUn+zcLa1R0tqOj+lCiEe4MDmys7FnZbV2GIIgCOedSEAE4RJXVlZGVlYWv//+Ow0NDbRt25Zhw4b96doXLfn8888pLy9nwoQJNDQ0sGrVKm655Za/JU5ZlsnNzeWXX35h9OjRBAQEoFarqaqqYt++fZSUlNCrVy+CgoL+luudDavVSkNDAwaD4aTjVARBEAThUiUSEEG4hC1fvpyvvvqKoqIiOnfuDMD8+fNZvnw5r7766hnPgJSTk0NhYSFWq5Xa2lqy/sZfd10uF9u3b+eee+5h//79PPTQQwQEBLBq1Sree+89rFYrr7766gWRgKxdu5b169czYMAARo0a1drhCIIgCMIFRSQggnCJysnJ4auvvsLX15f77ruPwMBAJEnCarUiyzLvvvsuZrOZ4cOHExISwu7du0lPT8fX15exY8fy448/smDBAqqqqkhOTuaee+7B7XYra2i4XC4OHTqELMusXLmSn3/+mdLSUkpKSoiOjuaKK65gxIgRNDQ08PXXX/Phhx9is9kIDQ3liiuuYNCgQYSHhyvxNs1OFR8fz+LFi5k8eTJOp5Pff/+do0eP0qZNG9xuNy6Xi23btvHCCy9QWlpKx44dufHGG0lNTWXr1q189NFH+Pv7k56eTmRkJI8++igJCQlYLBa++OILVq1aRV1dHampqdxzzz1ERkZSUVHBnDlzyMzMRKfTMWLECDw8PCgsLOTqq68mJSUFWZa5//77mTBhAm+//TZ79+5lzZo1/Pjjj4wcOZI+ffrw9ttvs2rVKsLCwrj66qvp378/ubm5LF26lF9//RWHw0FSUhKzZ8/G19dXdN8SBEEQ/pEurileBEH42+Tk5OB0OomJiSElJYXQ0FBCQkKIiYmhTZs2BAYG8u2333Ls2DFcLhe7d+/mt99+Izg4mKqqKl599VV69OjBbbfdpiQvTWRZpqGhgdzcXAAKCwvZsGEDMTExjB07FpfLxapVqygvL2fPnj289dZbDBo0iBkzZlBXV0dRURFWq7XFuENCQmjbti2//PILX331FQDt27fHw8MDaFzr44033iAuLo6pU6dSUVFBeno6eXl5lJaWsm3bNmU1ckmSWLZsGQ0NDaxdu5b9+/fTrl07Ro4cSXV1NV999RWyLPPtt9+Sm5vL+PHjueyyy/D396ehoYGKigpWrlyJ2+3myJEjrF69mqCgILp27UpycjKDBg3i8ssvJzIykh07drB582ZuuukmhgwZwoIFCygsLOT777/n0KFDXH755dx8883ExcUpSZwgCIIg/BOJFhDhbxcUFERVVRVffPEFO3bsaO1wTtCmTRt69OhB+/btcblcrF+/nkGDBiFJEhs2bKBdu3b4+PiQm5tLVVUVqampOBwOfvvtNwYPHowkSWzatInExET8/f0pKCiguLiYLl264HK5+OWXX5RyGRkZxMTEEBQUxLFjx8jPz6dbt2643W7Wrl3LoEGDUKlUbN26lfDwcEJDQyktLSUnJ4eePXsiyzJr1qxhwIABaDQaMjMzCQwMVH6V37dvH71790aWZdauXUu/fv1Oe+xGZWUlOp0Ob2/vZp+RJAm1Wk2PHj2YO3cu2dnZ6HQ6cnNzUavVxMTEsHv3biwWCxMmTCA8PJykpCRCQ0OVczS1VtTV1QHgcDgwm80MHDiQxMREZdxGTk4Oe/bswWazMXnyZMLDw1m5ciXQuHBfS/R6PRMmTOCrr76iurqaMWPG0K1bNzIyMnC73ZSXl7N+/Xq++uor4uLiqKys5MiRIxw+fBin04lGo6F///706dMHq9XK2rVrmT59Ohs2bMDb25tRo0YREhLCypUr+eabb7j33nv57rvvGDJkCGPHjkWlUlFfX09JSQlOp5Off/6Z6dOn8/PPPxMbG0twcDApKSmUlJSQlpZG3759KSsrY+nSpVRWVuJ2u7HZbOzcuZPDhw+Tn59PcXExsiwTExNDcnKyGDciCIIg/KOJBET428XFxdGuXTssFgtHjx5t7XBOYDKZKCoqQqfTERMTQ01NjXKstrZW+fXZbrc3+xX+VOWaKtqyLFNdXY0sy0iSRF1dHQ6HA2ishDeVA5RyQLNyTqfzhHJNrFZrs3K1tbUtnu906PV6HA4HNptNifd4bdq0IT4+nj179pCXl0dlZSUdO3bEZDKxe/duYmJiSEhIQKVS0bVr1z+9XlhYGFFRUYSEhBAQEIBWq+XYsWMUFxcTFxdHXFwckiRhMpn+dP2NAQMGsGjRIlwuF9HR0TidTjIyMnC5XJSVlWG1WunUqRMajYZ27dqRnZ1NWVkZOp0Oo9FIx44dMZvNxMfH88UXX+ByuTh8+DADBw4kLi4Os9lMSkoK2dnZOBwOtm3bxpNPPklgYCB6vR6A0NBQKioq+PLLL/n9999ZsmQJEydOxGAwoNPp0Gq1GAwGjEYjdrudffv2ERAQQH5+PgBpaWmo1Wq6dOmCWq3m999/p7y8nLi4OFJSUk77exQEQRCEi41IQIS/XVhYGLfeeiu33npra4dyUocOHWLXrl2kpKRwxRVXKPtHjBihbCckJJCQkACAVqvlyiuvVI4NGzZM2Y6JiSEmJgZoXGl73LhxyrHBgwcr25GRkURGRgKNi90dX27AgAHKdmhoqNKaIElSs3J9+/ZVtoOCgpSVuiVJahbf6YiOjsZut5Obm0tpaSmBgYFAYzJksVgIDQ1lzJgxLF26lIKCArp06UK/fv1wu91YrVbsdjs2mw2DwUBtbe1JV+xuiSRJqFQqNBoNfn5+2Gw2qqurUalU1NXVnbT1o4mfnx9jx45FrVbTvn17fv/992bn1uv11NbWYjabqa+vV671R2q1GlmWkWUZvV6P0+nEbrfjcrmUWayatpvicrlc2O121Go10dHRJCUl8dlnn7Fnzx6GDx+urE7eVLYpJqPRSFBQEEOGDEGlUtG7d2/i4uJo3749ycnJbNu2ja1bt/Lpp5/Sq1cv4uPjT/t5CoIgCMLFRIwBES5JsbGxZ1xh/6dJSUkhKiqK3bt3880331BYWMjRo0dZt24dn332GS6Xi6FDh1JaWsqBAwfw8vKiU6dO6PV62rVrx+7du9m5cydFRUWsW7eOsrKyM47BZDLRpUsX9u/fz+rVq1m/fj179+6loaHhTwdg33rrrdx0000kJycr+7RaLfHx8fj6+rJ+/Xry8vJIT08nLCxMSRJbOq9KpaJ79+6Ul5eTmZnJ3r172bZtG/3798fDw4OuXbvy/fffk5OTw5EjR9i3bx+FhYWEhITQr18/PvzwQ3r16kVwcDAqlYqgoCDsdjvFxcVKy8vAgQPJzc0lPDycyMhI3G43DoeDvXv3otFouOaaa5gxYwYBAQEcPnz4jJ+lIAiCIFwsRAuIIFyiDAYDd9xxB4sWLeLtt99m5syZaDQaVCoVTz/9NAD+/v507NiR6OhounfvjkajQaPRMHToUMaOHcvw4cMJDg5Gr9fz1ltvodFo0Gq1yjiSpml81Wq1sv/49x4eHqSkpHDvvffy3HPP4evrS0NDA15eXi1OAaxSqU66v+n8Wq2WZ555hmeeeYaqqio6dOjAXXfdRVJSEvn5+c3iOP58V155JR9++CHPPfccdXV1dOzYkYcffhiVSsXzzz/PTTfdxPfff4/D4WDs2LHceOONREdH07dvX4xGI9OmTVPOm5qaislk4q233mLJkiVcddVVjB07lvT0dMaOHUt1dTVut5u33nqLpUuXsnr1aiRJwsfHhw4dOjRrORP+ubSileuiJL43QTh7knyancZnzpyJLMvKL3SCIPxzNI07sVqthISEAChT8l599dUMHDiQadOm4e/vr3xGlmVsNht1dXWYzeYWuzidDpfLRWFhIREREVRXV3PllVfy73//m169ep3xOiR/ZLFYMJlMZxRbQ0MDTqcTT0/PE46Vl5fj4eGBXq9XFkFcu3YtzzzzDDt37gSat7BYrVZcLpcyrqVpcH5lZSX+/v7KWJemLm0Gg+GMurIJFy/Z5UJSq1s7DOEvEt+fIJwd0QIiCAJqtRpvb2+8vb2b7f/222/x9fUlJSUFPz+/Ez6n1+uVQdl/VWVlJf369aO+vp6oqCiuuOIK4uLi/tJK7H/0x/s5Hae6pz8+g/z8fBYvXsyNN97YYvmmqYGPp1arT/gRx8PDo8Wywj+XqLxe3MT3JwhnR7SACIJwUlarFZvNhoeHxzn7Zd7tdlNaWorVasXT01OZOUp9EfwfvMPhoKamBr1eL6bOFQRBEITTJFpABEE4qfPxy3zToG23241KpbqoVv/WaDRixXJBEARBOEMiAREE4aTOV8W6adD6xUYkHoIgCIJw5kQCIgiXKJfLRV5eHhaLpdl+Dw8PEhMTT1q5lmUZu92O0+nEaDS2aiXc7XbT0NAAgNFoPKPPyrJMQUGBMn2w0WgkJCQELy+vVk8sZFlm27ZtJCcn4+HhQX19PVqt9qzH2wiCIAjChUAkIIJwibLb7axevZojR44og6slSSIgIIDExMRTfi47O5vCwkKGDh16vsJtUUNDA9u2bUOtVtO7d+8z+qzb7WbDhg1kZWXh7e2NVqslPDycjh07Eh8f/6ersZ9LsiyzatUqgoODcTqdrF+/noSEBJKSklotJkEQBEH4u4gERBAuUTabjRUrVlBeXq6s7C5JEg6HA4DCwkKcTif19fW43W6MRiP+/v7YbDa+/vprtmzZQnh4OP7+/vj5+WGxWKiqqsLhcODh4YGfnx9eXl5UVVVRW1sLQH19PYGBgWg0GqqqqqiurkaSJPz8/AgODkaSJKqqqigrK8Nms6FWq/H09MRoNFJbW0tUVBQANTU1VFZWUlJSwn//+19UKhX+/v6YTCbCw8OpqKiguLgYSZLw9vbG39//hEH0siyzbt06Dhw4QJ8+fSgtLeX7779n+PDhTJ8+HYfDgSRJ1NfXI8sybdq0obi4GIvFgtvtxsvLC39/f4xGI263m4KCAiwWCyqVCrVarbSmOJ1OKisrqaioUO41KCgIh8NBYWEhbrcbp9OJy+XC29tbmQZ5//792Gw2CgoKePXVVxkxYgTjx49X7qe8vJyysjJkWcbf35/AwEBkWaaiooKGhgY0Go3yvOvq6qisrESWZYxGI8HBwWLQvCAIgtBqRAIiCJe4tLQ07rzzTuV901iMuXPnUlxczKFDh6itrSU1NZVrrrmG2NhYPvroI6qrq5k+fTqTJk1i8uTJLF68mO+//57y8nKSkpIYP348V1xxBT/99BM//fQTHh4eHDhwgDvvvBOTycTixYtZt24dWq2Wyy+/nGeffRZJkvjuu+/4/PPPyc3NxcfHh27dutGtWzdWrVqlJBvr169n8eLF2Gw2MjMzKS8v58iRI3Tp0oVZs2axaNEi/vvf/6JWq+nbty/Tp0+nXbt2LbZq9OrVi/vvvx+TycR9991Hbm4uv/76K5s2bUKj0ZCTk4Pb7ebdd9/llVde4ZdffqG+vp6ePXty3XXXMWDAAMrLy3n66af59ddf8fb2xu12869//YuRI0dSUFDAokWLWLp0KTqdjhEjRvDkk09y7NgxHn30Uerr66mpqaG6upr+/fvz9NNPYzabycnJQZZlvvjiCw4cOKDENXToUG644QbeeecdvvjiC1wuF5dffjkPPfQQsiyzYMECfv/9dyIiIti3bx+33347a9asYcWKFbhcLlJTU3nwwQfp0aPHefsbEwRBEITjiQREABp/DXa73bjd7tYOpUWSJKFSqZTF3I6fMcntdiNJEpIkIcsysiy3ajloHF9xfDlAOcdfKXf8tU5VrmlW7TMZw/D111+TmZkJNCYfMTExvPvuuxw7dozy8nIefvhhjEYjy5cv5+uvv+b555/nzjvvZOPGjcyfPx9PT08yMzPJzMxk/PjxDBo0iE2bNvH8888zZswYLBYLS5cu5YEHHmDUqFHExcWxaNEiSktLWbBgAfX19dx4443ceOON+Pv789JLL3HjjTcycuRIjh07RlFREcnJyTzyyCMcPnyYuLg4PvnkEzp37kxaWhp6vR6tVsu//vUvNBoNFRUVvPDCCyxZsoSgoCDuvvtu0tPTCQoKIjg4+IT7d7vduFwuDh48qCyIaDKZyMnJIS8vj4ceeoiwsDDWrVvH7t27efrpp/H29mbJkiW8//77dO7cmf/+97/s2rWLJUuW4Ovry6RJk6irq6Ouro7NmzezYcMGPvroI7y8vBg7dixjx47F09OTw4cP06NHDyZOnEhpaSkLFy5k/fr1jB49mkOHDmG325k6dSq7d+/miiuuYNKkSahUKg4dOsSCBQtYtGgRer2ea665hlGjRhEZGcnhw4fZu3cv7du3595778Vut7NgwQJ27tyJ0Wjkt99+E1OpC4IgCK2q9To5CxeU/fv3c+edd6LT6S7IV9++ffnss8+AxjEIzz33nFLZfvvttzl48CAA27dv53//+x/QuLr3c889p1TYP/jgA7KysgDIysrigw8+ABoroM899xxOpxOA//3vf2zfvh2AgwcP8vbbbyvP6bnnnsNutwPw2WefsXnzZgCOHDnCvHnzgMYkYPbs2dTX1wONFfz169cDjd2aXnvtNeV8zz//PDU1NQB8//33rFmzBoDS0lJefvllpdycOXOorKwEUFoUoHERvzlz5ijlCgsLlS5Up6tnz548/PDDPPzwwzz44INMnTpVOTZ69Gi6du1K//79CQ0N5ciRI8iyjNlsxsPDg+DgYDw9Pfn5558pKChg5cqVvPLKK3z33XdYLBblOV5++eXcfffdjB07lvLyclwuF3369KFXr15069aNoUOHsnTpUpYuXUpKSgojRoygbdu2DB48mGuvvZawsDBGjBjBRx99xLFjx/jtt98YOnQoCQkJGAwGTCYTQUFB6PV6fvrpJ/R6Pe+99x6zZs2isLCQ7du3k5OT0+L9L1iwgO7du9OrVy+MRiMTJkwgMDCQwMBAHnzwQaZMmcKAAQNYuXIlgwcPpkuXLgwaNIiuXbtitVrJzMxk06ZNXH/99XTs2JGoqCiMRiMqlYr9+/eze/duKisrmT9/Ps8//zxut5uVK1dis9nw8fFhyJAh9OvXj8TERJKTk9m9e3ez+Ly8vNDpdJjNZgIDA7HZbGzevJk+ffrQu3dv0tLSGDZsGJs3b6a4uBiz2czIkSN56qmnGDJkCJ07d8bhcPCf//yHVatWMXDgQGJiYs7ob0QQBEEQ/k6iBUQAGhOQkJAQPvroIyZOnNja4ZxApVKRl5fHO++8w2233cYTTzyh/Mp/6623Kt2GOnXqRMeOHYHGNRqeeOIJpXVg+vTpynbbtm1JTk5Wzv3EE0+g0TT+z+H6669XysXHxzerrB1fbvLkyUoM0dHRzboxPfbYY0q58ePHK+VCQ0O55557lHKPPvqoUu6yyy5TygUGBnL//fcr5R566CGl3IgRI5T9vr6+PPTQQ8r70NDQM57BKTY2luHDh5+yjFqtPumgbEmSsFgsJCQk0LFjRyIjI5FlGY1GQ2xsLDt37lRikiQJq9WK2+1Gr9crrTpGo5Hq6mpqa2vx8PBAo9E0uw8fHx8mTZrE7bffjqenJyNHjlTGShwfh9vtpqqqiuTkZMaNG4ckSVxxxRWEhIQQHR3dYvxjxoxh6tSpxMXFYTab0ev1SuLUdF4Ai8WCwWBArVYjSRJarRaNRkNdXZ2SBB1fHhoXclSr1XTu3Jlx48YBMG7cOGJjY5uVa2rhU6vVSmJ9smftdDqpq6vDZDIp5zAajdTX1zdLPpvOGRISQkZGBp988gmvv/46b775Js8991yrTyAgCIIgXLpEAiIAjb/aS5KETqc74+lMz5eYmBiuueYapfLX5Pjtpm5awAnlmirwF0q5P8Z+fLlT3ePx62X8sdxfmbnpTNfgUKvVBAQEUFpaquwbMGAAq1atwmw207dvX2w2G7m5uS1+vkOHDsrsU5WVlVRXV7Np0ybmzp1LaWkpX3/9NTk5OURGRlJVVYXFYiE5OZlu3bphNBp59dVX+eSTTzCbzbjdbtRqNfX19djtdjw8PBg2bBjz58+nbdu2BAYGUllZSU1NDS6Xq8V4goODSUlJURYUPFkCN2jQIDZs2ED//v1Rq9Xk5eXhdrvp1q0bBw8e5Ntvv6Vv374cPXqUY8eO4XQ6SUpKIi8vj3379tGxY0d8fX0pKSmhurq62fd2Kr6+vrjdbiXB8Pf3p3PnzixcuJCKigo0Gg2bNm3ivvvuO6FrlcvloqCgAJVKxeOPP87UqVO59tprKSgooKGh4Zytbi8IgiAIpyISEOGiodVqT7vSJpy+Tz/9lE2bNgHNx4CcjMFgoFOnTlRWVjJ58mSGDBnCwIEDycnJYfny5Xz33XfU19ej1+t54YUXTvh8UFAQaWlpLFmyhBtvvBGVSkWnTp1ITU3FbrfTs2dPXnnlFd555x20Wi2pqak888wzmEwmhg8fzpo1a+jUqRMGgwFZlklJSWHZsmVMnTqVdu3acd999zF27FhmzpyJ3W6nvLyc0aNHM3r0aIKCgk6IR61Wo9VqW0zejk9GhgwZws6dO5k1axYulws/Pz+uuOIK/P39GTVqFNnZ2Tz22GNERERQW1uLXq8nICCATp06sW/fPp588knsdjvFxcU88MADREdHn5Ds/LFVBBpbN7p06cKPP/7Ihg0b6N27N6NGjaJnz55Mnz4dSZKIi4ujU6dOSstR02fdbjdlZWU88sgjhIaG4nQ66dKlC4mJieh0ulP9WQiCIAjCOSMSEEG4RHl4eHDbbbcxYsQIpcKqUqnw9fUF4MYbbyQoKAiz2YwkSQwdOpSkpCS0Wi1hYWE8/vjjVFZW0r59e8LDwxk9ejTt2rVTpoH18/PDz8+PAQMGKAvqAeh0Onr06IHZbObo0aOoVCoSEhLw9PREkiRuvvlm9u7dq/xC39QFTpZlqqqqGDNmDGazWUkYBg8eTGhoKJWVlYSFhWE0Gpk6dSo5OTlUVFQAja0u/v7+ze5fpVIxZcoUDAbDCS0B0dHRXH/99YSFhSn7IiIiuO666zh06BBut5uwsDCSkpLQaDSEhYUxadIkiouLsdls7N69W5kWOCkpiWuvvZa8vDwqKytRq9WkpKTg4+PDvffeS9u2bQEICwvjiiuuULq7zZkzh7CwMHQ6HZMmTeLAgQM4HA5iY2MJCgrilltuYd++fbjdbhISEggPD8ftdjNx4kTl+1Sr1URERDB16lTsdjuenp5ER0eTlJTUquucCIIgCJc2ST5Vh+PjzJw5E1mWmTFjhphB5R9oyZIl7Nixg6SkJKZMmdLa4QgXAVmWqa+vx2AwNJsNzOFw4HK5lITjZJpmnwJOaNlyOp04HA7UajU6nQ6n08nRo0cZN24c8+fPp3v37s26jTWto6HRaJrtr62tbTZu4+9gs9lQqVRKa4PT6aSgoIDPP/8cs9mMw+Hg6NGjXH/99bRv377Z/VqtVmX1+DONx+FwIMsyarVaGSvicrmU8TanWrkeGtdOMZlMyqxrgiAIgtBaRAuIIAh/SdPg8T/uO92uPX8cD3M8jUbTbEyMLMs0NDSQkpJCly5dTvjcH8s38fT0PK1YzoRer2/2vim2jIwMdDod0dHRjBw5koiIiGblVCrVWcXzxyRNkqQW7/mPmpINb2/vv3xtQRAEQfg7iQREEIQLnlarJSkpiYULF/6l1oNzSavVkpiYyDfffIPNZlNm9xIEQRAEoWUiAREE4aJwoSUex2uKS8wqJQiCIAh/TiQggnCJamn41/mu4B8fw7m+9p8Nd/uzMRR/Vu58OBfP62TP5UJN9gRBEISLn0hABOESlZ+fz86dOyktLcXLy4vExERSU1PPawxut5u6ujoaGhoIDAw8p5Xeqqoq9u/fz549e5rtT0lJIS0t7ZRjV0pLSzEYDMpMXa3F4XBgtVpxuVwnzOr1V1mtVnbt2sWmTZtwOp2MGDGClJQUMU2vIAiCcM6IeRgF4RJlt9vZsmULn376KcuWLaOuru68x1BVVcWXX37JE088cc6vVVhYyA8//MC8efPIzMxUXnl5eSddpBAaWwiefPJJvvzyS2pra895nKeSk5PDRx99xMsvv/y3nbOkpIQ333yTo0ePUl1dzcSJE1m4cCFlZWV/2zUEQRAE4XiiBUQQLlFRUVF07tyZqqoqwsLC6Ny5MzU1Ndx+++1ERUXx22+/4ePjw5VXXsnhw4fZsWMH3t7eTJgwgfHjx1NQUMCDDz5IUFAQu3btIjw8nLS0NOrq6li/fj0BAQHcdddd9OnTh8zMTP79739TWFiIyWRiyJAhXHXVVUiSxGuvvUZlZSWjR49m3Lhx+Pv7U15eTp8+fWjXrh27d+/myy+/ZMqUKZhMJp544gl69erFpk2bGDZsGMnJyWRlZfHtt99SX1/P4MGDufPOO/Hx8WnWWiHLMnq9no4dO/L0008r+z08PKioqOD111/HYrEoK6cPGDCAu+66i0OHDimLAH7xxRfcfPPNJCQkkJmZyZIlS2hoaGDw4MHccccd+Pj4cNttt9GpUycOHDiAwWCgV69eBAcH88Ybb3DgwAHi4+P5z3/+Q0xMDLW1tXzxxResWLGC0tJSYmNjmTJlCp9//jn33nsvqampqFQqXn/9dfz8/MjPz+fjjz9W1hoZN24c119/PW+88QYrV67EYDDQv39/Ro4cSWhoKKtXr+b999+nqqqK2NhY5syZQ0RERLPZs8LDw3nppZfQaDSoVCpqa2vZsGEDffv2FVOuC4IgCOeEaAERhEuUTqfDw8NDWYjPw8MDh8NBRkYGdrudu+66C7PZzOLFi3G73YwbN06ZiaqpK9Bvv/1GWFgYt9xyC06nkzVr1tDQ0MDEiROJjo5m4cKFQON0uJMmTeJf//oXV199NYWFhSxbtgwvLy/69+9PYmIid9xxB3369KGiooJDhw5RXV0NgMViYffu3VgsFurr6/npp584ePAgXbp0ISYmhs2bN7Nr1y5GjBjB7bffzuHDh1m9enWLYxusVis7d+7klVdeUV4///wzFouFzMxM7HY7w4YNY9CgQezcuZOdO3cSHh5OYmIi/fv356abbqJLly5s3bqVrKwsRowYwS233KJcE2Dbtm2sWbMGX19fOnbsSENDA6tWrcJgMPDggw/i4eHBwoULqa+v5+eff2bXrl20bduWW265hX79+lFTU4PRaOSbb77B6XSSn5/Pxo0bsdvtpKam0qtXL1JTU7ntttvo2bMnO3bsID09nUmTJnH11VeTl5fH8uXLyc3N5YMPPmDkyJE888wzdOrUSVmr5Y9/B2FhYQQGBmI2mzl48CCBgYEnTDcsCIIgCH8X0QJynuTn5/Pdd99x8ODB1g6lRTk5OZSVlZGRkUF6enprh3OC6Oho+vfvT9euXXE6naxevVpZwXvdunUkJSURFBREfn4+hYWF9OjRA5fLxapVqxg+fDgqlYqNGzcSExNDaGgoRUVFHD58mN69e+N2u1m5ciXDhg1DrVaTkZFBWFgYkZGRlJSUsH//fvr164csy6xYsYKhQ4ei0WjYunUrAQEBtGnThvLycn7//XcGDhyILMusXLmSQYMGodPp2L59O97e3sTFxVFVVUVmZiaDBw8GYOXKlfTv3x+DwcCuXbvQ6/UkJSVRU1PD5s2bGTJkCACrVq2iT58+GI1GZQxD27ZtsVqtbNiwgWHDhgGNXZq8vLyaLcZ3purr6xk4cCD9+vXj2LFjrFu3jnbt2jF06FAyMjL46aefKC0txe12I8syw4cPJzY2lqysLIqKimjfvj39+/dn69atzJw5E4CAgADUajW5ubkcPHiQXbt2IcsyHh4eJCcnU1lZyZAhQ9BqtUpl2+12A43jRBoaGnC73co1R44cSXx8PHq9nu+++449e/YQHh5OeXk5paWl/Pzzz4wfP/6Ee2tap+T4NTE8PDyQZRlZlklNTWX06NHk5uZy6NAhsrKy6NWrF6GhoSQnJzNw4EAMBgMHDx5k7969hIWFUVFRQUlJCWvWrOGqq67CarWSlpbGkCFDCA8PZ9OmTezevZvx48czatQojEYjs2bNYsaMGfz666/4+PgwYsQI2rVrh9VqxWq1otVq+fe//82DDz7Ir7/+ipeXFxEREYSGhpKQkEBxcTGDBg1Cq9Xy+uuvU15ejsViwWazcejQIWpra0lKSuLYsWOUlJTQtWtXhg8fjq+v70n/NmRZ5vPPP6esrIzBgwfj5+f3l/+GBEEQBOFURAJynmRlZbFp0yZqa2sJCwtr7XBO0LSStNPpxG63t3Y4J3A4HFRWVvL777+TnJzcrM9+02rQgLI6dBOn0/m3ljv+2B/LNVWYm441aao4H//+ZOVO57rHf/6P5f4u7dq1w9vbm7CwMEJDQ5X/+vr6otVqsVgsqFQqPDw8SExMxNvbm4CAAHQ6HREREQQGBhIWFkZ5eTkAO3bsYNOmTRgMBmXRQLvdjiRJ6PV6tFptsxXCmxKClnh5edGnTx+8vLwoKiqivr4ep9OJ2+2msrKShIQE5Vx/pNfriYmJYdy4cco+Pz8/ampq0Ov1REZGEhERQXV1tdIVrGnVc71ej4eHB3V1dVRXV7d4zSbdunWjXbt2GI1G3G435eXldOrUCS8vL7p160ZOTg4NDQ3s379fSab8/Pzw8/PD7Xbj7e1NbW0tu3btYtmyZXTr1o34+HhsNhtarRatVovJZEKWZbKysggICKCmpgaHw0GbNm0IDw/Hx8eHsWPHkpeXxw8//EBERATR0dEtPle73U5GRgZfffUVI0eOJC0t7Zws4igIgiAIIBKQ8yYvL4+EhAQGDhzIwIEDWzucEyxZsoQdO3aQnJzM5MmTWzucFhUUFLB582Y6dOjAmDFjlP3HP8+oqCiioqIAUKvVXHbZZcqxfv36KdthYWFKIqhSqZqV6927t7IdHBxMcHAw0Pjr+fHX7dGjh7IdEBCgtGpIksTo0aOVY2lpacq2j48PQ4cOVd6PGjVK2e7UqZOy7e3tzfDhw5X3I0eOVLbbt2+vbJtMpmbHfHx8+DupVKoTKvInmwXq+NXJj08kAD777DPsdjs333wzgYGByLJMVVUVkiSh1Wqx2WzKZw0GA3a7HafTidPppKGhAYfDcdIYPTw8iIqKomfPnkql3O12txinRqPB19eXdu3aNdtvtVpPuEeVSqXEr9frlcS8aQX46OhoevXqhdFo/NNr6nQ6ampqkGUZi8WixOlwOKitrVVaeJxOJzabjcDAQPr27cuXX37J77//ztSpUwkPDyc3Nxe1Wt3sRwKTyYTZbKZPnz74+Phgt9sxmUyEhIQQGBhIRkYG27dvZ/bs2XTv3p3OnTsrrSBNq7jv2bOHjz76CH9/f+6++258fX3FNLyCIAjCOSPGgAjN/NlaCa0pPDy82S/Xwtmpr6+nurqampoaamtrlTEXp/JXK6X19fXEx8djNpspLCyktLQUaBx/EBwcTGlpKUePHqWiooLIyEgsFgt5eXns37+fffv2YbFYWjxvaGgo0dHReHl54Xa7CQoKwsvLi4qKihb/ll0uFzU1NRw+fFh5lZeXN2tVaklUVBRHjx4lLy8Po9FIeHg4np6eza5ZWVl5wuckSSI8PJykpCRWr15Nbm4uP/zwAwMHDsTb25sOHTqQk5PDhg0bOHToEPv27WPv3r1IksSkSZP45JNPSExMJCoqCg8PDzw9PfH29qakpIT8/Hxl8H5xcTGenp4EBgai0WhoaGigoqKCnTt3MmjQIB566CHCwsI4duzYCS2chYWFzJo1i99//5377ruPmpoa8vLyaGhouKD/PRAEQRAuXqIFRBAuURkZGSxatIiMjAzatGlDUFAQEyZMwGg0Kr+Qq9Vq9Hq98r6p25VKpUKlUmEymZTzabVadDpds882dUuaOnUq999/P//73//w9fWlvr6efv36YTKZ6NKlC/X19QwfPpyrr76a22+/HZPJxJw5c3A6najVanx9fZVr/rF71fDhw3E6ncyePZuSkhLKy8u56aabGDFiRLP7ValU1NTU8N1337Fs2TJl/80338x1112ndA9rKtvUNUySJC677DKmT5/OsmXLuPPOO5X1UmbNmkVxcTGVlZXcdNNNDB8+HA8PDzQajRJjYmIiQ4YM4Y033uD999+nTZs2/Oc//8FoNHLHHXfw8ssv8+yzz+JwOAgKCuLhhx+mW7duDB48GIPBwIQJEwgJCQEgJCSExMRE3n//fcaMGcOkSZN44IEH2LRpE48++ihlZWU4HA5GjhzJiBEj+M9//oPD4cDT05Pk5GT69++Pl5eXcu+yLFNZWcnKlSvRaDTKWCJJkli8eDE9e/YULSGCIAjC306ST/MnrpkzZyLLMjNmzBBTM/4F7733HoWFhRd8F6ykpCSmTJnS2uEI/0ANDQ3U1NTg6emJh4dHs2NNFWGz2ax0+2pqkfHy8jqtSrDD4aCurg4PD49zMoOT2+2muroak8mEVqs942u63W4sFgu+vr4nHKurq8Nut+Pp6YlWq0WWZTZu3Mgtt9zCihUriIiIaPYMXC4XFotFmWpYkiSldUen0ymJn8vloqqqCqPRiMFgEMmEIAiCcEEQLSCCIJwXer3+lJX0P1bMj/+l/nRoNBrMZvNfiu10SJJ0wvnP5JqSJJ10jI7RaGw2iN3tdjN37lxuuOGGZjN2NVGpVCc8L5VKdUIsKpVKzGYlCIIgXHBEAiIIwnlxql/fWzp2pr/Wn+tf9882xjO5f5VKxfvvv49Op0Ov15/WRAB/xzMUBEEQhPNBJCCCIAgXoKaWD5FECIIgCP80IgERBEG4wIikQxAEQfgnEwmIIFyiqqqqKCoqoq6uDr1eT0BAAKGhoec1Brfbraz5YTKZzmnFu76+ntLSUkpKSprtDwwMJDw8XJkB649kWaaurk5ZjLA1kwOXy4XdbkeW5WZjRv4Osiyze/duEhISWv0+BUEQhH82kYAIwiWqsrKSTZs2kZ2dTUBAAAMGDDjvCYjNZuPAgQMUFBQ0W5TxXKioqCAjI4P09HRlcUmAzp07ExwcfNIEBOC3334jPDyc5OTkczLD1umqrKzk8OHD1NXV/W2z6TmdTuW8n3zyCU8//TT+/v7KdMqCIAiC8HcTCYggXKI0Gg2lpaXs3LmTyMhIhg0bhtPpZP/+/ej1eqqqqtBoNAQGBipT6Go0GoKCgggMDMRms3Hw4EF0Oh21tbXo9Xq8vLyUKWK1Wi0RERGYzWZl8T+bzaas6xEUFER1dTVffvklO3bsICwsjMDAQLRaLQ6HA7PZjKenJ7W1tZSUlBAcHIxarSYnJwez2YzFYsHPzw+j0UhdXR2lpaW4XC78/PyUFo3jf8WvrKxkx44dbNiwgauuuqrZs7Db7eTn5yurrzudTnx9fYmIiMBqtTJ//nw6duzI6NGjSUhIwGg0Ul1dTVlZ2QnX3LdvH15eXlitVmVmKp1OR35+PlarFaPRSGxsLB4eHjidTmXtEofDgcFgICQkhOLiYiIjI/H09ESSJPLy8tBqtezfv58lS5ZQXl6Or68vgYGBhISEkJ+fT0VFhTI7lp+fH3q9noqKCgoLC3E4HHh4eBAfH3/CdLxOp5OioiLWrl3Lu+++yz333CNmzhIEQRDOKZGACMIlKjIyktTUVMrLywkLC6NDhw5UVVVxyy230LZtWzIyMtBqtVx++eUUFRWxe/dujEYjY8eO5a677qKgoIBp06aRmJjInj178PHxoUuXLjidTtLT0zGbzdxxxx2MHz+erKwsHn30UYqLi9HpdPTr14/Jkyfj5+fHF198gcVi4e6772bSpEmYTCaOHTvGiBEjSEtLY+/evbz77rvceeedmM1mbr75ZoYPH87WrVu57LLLiI2NZfv27SxduhSHw0HPnj156KGHiIyMPOGeDQYDycnJTJs2Tdnn4eFBWVkZ//rXv6irq6O+vh6LxULPnj158sknOXr0KJs3b2bv3r2sXbuWO++8k4iICDZt2sSyZctwOp307NmTBx98kMjISO6//366du1Kbm4uXl5e9O7dG19fX1555RWOHj1KWFgYL7zwAmlpaRQXF/Pf//6X1atXU1VVRUxMDNdffz0LFizggQceYPDgwbjdbt566y0iIiIoLy9nyZIlOBwOCgoKmDhxItdffz1vvPEGGzZswMPDgx49enDZZZcRFxfHokWL+PTTT7FarYSHh/POO+8QHR2trGMCjQtIxsbGcs011zBr1qzz8acnCIIgXOJUrR2AcGGQJAlZlnE4HNhstgvuZbfbcblcQGNfdafTSdMami6XC7fbDTSOKWiNck3HzqQc8JfKud3uk5aTZZnTXFu0RW63myNHjhASEsJ3331Hv379+OGHH4iMjOS1115j0qRJfPTRR8p3sn//foYOHcqXX35JTEwMGRkZBAQE8Oabb3L55Zfz/vvvAxAREcHcuXPZsGED8+bNw26388033xAYGMgtt9xC//79+eqrr5g2bRpOp5OysjIaGhqAxgUMCwsLaWhowG63s3nzZioqKrjlllsYOHAg6enpZGdn8/TTT/PZZ59hsVj49ttvW3wOFouFVatWMWXKFOX13//+F4vFwpEjR4iMjOTpp5/miSeeIDc3l/T0dNq3b0///v255ZZb+Pjjjxk3bhybN2/myJEj/Otf/2LhwoVUVVUp12z6XI8ePZgyZQp6vZ4ff/yRzp078/PPP9O1a1fefPNN6urqWLx4MUeOHOG6667jyy+/5IEHHkClUpGWlsbHH3+M0+nkwIED7Nq1C29vby677DKuv/56Lr/8chYtWsR1113HunXr2L17N6+//jpz587FYrHwzTffkJOTw9tvv82///1vMjIyuPnmmzEYDCc8E7VajaenJyEhIaLblSAIgnBeiAREACApKYmioiKmTp2KwWC44F79+/dn0aJFyLKM3W5n1qxZSgXznXfeITs7G4AdO3bw8ccfA42V9lmzZimV9QULFrBnzx4A9uzZw4IFC4DGSvesWbOUivzHH3/Mjh07AMjOzuadd95RntOsWbOw2+0ALFq0iC1btgBw5MgR3nzzTaXc7Nmzqa+vB+Cbb75h/fr1ABQWFjJ37lyl3AsvvEBNTQ0AS5cuZc2aNQCUlJTw6quvKuVeeuklKisrAfjpp5/46aefgMZuRS+99JJSrqm7zdmQJInp06fTpk0bevbsSY8ePejduzc9evQgKSkJDw8Pjhw5AkBAQAATJ04kKSmJ9u3bM2TIEAYOHEhqaio9evQgKysLAH9/f5YtW8b111/PXXfdxdKlS7FYLKjVasxmM0ajkeDgYLy8vFCpTv3PUmRkJLNnz+bKK68kMDCQoqIitmzZwuLFi5k9ezZHjx5lxYoVLSYgJpOJTp068dBDDymvoUOHotfr8fHxYdCgQfTv35/ExETatm3L7t270Wq1GI1GzGYzQUFBNDQ0kJOTw5YtW/j22295/vnnlWs2eeyxx7jxxhvp27cvkiSRnZ3N9OnTiYiI4O6772bVqlVYrVbWrl1Lhw4dGD16NMnJyQwYMIArrriCG264gcWLF1NRUcHnn39Oamoqbdu2xcPDAy8vL0wmE8HBwXh6erJkyRLq6+t55513eOutt8jMzKSoqIjc3Fx8fHyYN28eX3zxBYMHDyYsLKxZ64cgCIIgtAbRBUsAGhOQ+fPnN6tEX0gkSeLIkSO8/fbb3HHHHTz11FNKP/bbb79dqbR26tSJ1NRUoHGMw1NPPaUcu+mmm5TPtG3blpSUFKBx0bfjy91www1KuYSEBOLi4pQ4ji83ZcoUpVybNm24++67lXJPPvmkUm7ChAnK/rCwMO677z7l/eOPP66UGzt2rLI/KCiIBx98UHn/yCOPKOVGjhyp7Pf19eWRRx5pdv6/k1qtbnGRPFmWW9zftE+SJKUcNFbIDx8+zO23305sbCwffvghFRUVJ72u2+0+rZacpnEpHTp04KqrrlI+4+Pj02Iio9PpiIyMZPjw4co+SZI4dOhQs3KSJKFWq1uMoemaHTt2POGaf3wmTQmzzWZTZq0ymUzU19fT0NBAUVERsiw3a5lQqVTExsbSs2dPPvvsM7744guef/55kpOTycvLOyGe8vJyevXqRc+ePTGZTIwbN46AgAAlgfzkk09YtGgRTzzxBGvXriUxMRGdTvenz1YQBEEQzhXRAiIAjRUujUaDTqe7IF9arZaYmBimTp2qVA6bKnvHb6tUKqUbSUvlmiqlp1uu6djZlFOpVC2Wayn2sy0nSdIFOX1qbm4uffv2pWvXrgBKq49Wq8Xf35/i4mKlbNNYh+rqaqqrqzl69OhJk5XIyEhCQ0Px9PQkKCiIAQMG0KNHD2w22ynjaXqGxydNpxIcHKwMcj/+msHBwQwYMIDu3bu3eE1JkggPDyc+Pp7Vq1fjdrv54Ycf6NOnD2azmbi4OPbu3cuuXbuw2+2UlZWRlZWFSqXihhtu4JVXXiEyMpLY2FhMJhNGoxGTyURZWZlyjbFjx3L48GHatm1Lv379SE5OxmQyUV1dTX5+Pg8++OD/Y+++w6uo08b/v+f0kpPeK4EkhIQOoSO9C1hQwS5rW8HVdXVdfXYfF/dxdbGXtaMooKAiSBek9957CSUhIb2X0+b3R76ZHzEBYRcJkvt1Xbl2zpzPmblnEpe5z6fcfPPNN4SEhHDgwAGtZ04IIYRoLNIDIn4zDAbDRZdKFZdn69atzJo1i/Xr1xMXF0d0dDT9+/cHLlwI7+cJzsUe3s9/76abbuKjjz7ip59+0oZwdezYEZvNRtu2bSkoKODmm29myJAhDBkyBJ1Ox6uvvsp7771HSUlJvWFltcc2GAz069ePn376iddff53KykoKCgoYMmSINvzpfIWFhcyZM4e9e/dq+26++WYGDRp0wfgVRWHw4MH8/e9/Z+vWrdx1112kpKTg9Xp57bXXqKyspLCwkMGDB9OrV68690lRFBISEujduzdz5sxhzpw5GAwGxo8fj91u54EHHuCLL77g73//O1arFT8/P+68805SU1MZOnQof/zjH7nxxhuJiIhAp9MRFhZGfHw8X375JWPGjGHQoEGMHDmSbdu2MWnSJCorK6moqKBbt2706tWLV155RUtcmjVrRufOnbHb7XWus6ioiKVLlzJz5kzKysqYOHEiQ4cOZezYsVd9WWYhhBBNgzzNCdFExcTEcO+99zJ8+HDsdjsJCQnY7Xbee+89QkJCUBSFrl27Eh8fr60olZyczN/+9jeioqJQFIW33noLq9UKwLBhw3C5XFpNjebNm/Puu+8CMHjwYBwOB2VlZfj5+aEoitYuJiaGSZMmUVRUREpKChERETz66KOcOnUKVVWxWq2YzWYSExMxmUy89dZbdWpxpKam4ufnx5kzZygqKkJVVVq1alUv+YiOjmbs2LF06NChzvCsxMREYmJi+POf/6wNt4uMjGTMmDFa71LHjh159tlnKSsro02bNgQEBGhDooqLi+ucc/LkyaSmpmrDnIKDgxkwYAARERGcO3eOsLAw2rdvj8lkonPnzlitVs6cOYPT6cTPz4+2bdsCNXVL/P396d27NwEBAUDNKl4dO3bkr3/9K2VlZbRq1YrQ0FDuv/9+zp07R1FRETqdjvj4eCIjI3n88ccpLS3FbrcTHBxMVFRUvYnmVquVdu3aYbFYuPXWW7Hb7cTExOBwOK7MH5oQQgjxM4p6iUvmTJo0CVVVmThxIsHBwb92XNedjz/+mLNnz9K3b98rVkBMiN8St9tNdXW1NqTufKqqUllZqdWoUBSFqqoqFEXBZDJd0jCp2irhRqPxV+kpU1WVqqoqTCaT9hB/Oees/Xxtwna+2lXeao/t9Xp5++232bJlC2+//baWENbyer1UV1drFcsVRdH2GQwG7f56vV6qqqq0+K7F4XlCCCGaHukBEUJcFRcbQqcoijZJu1ZDS8ZejF6vb/Dh/kpRFKXe8S/nnA19vlZDk8I9Hg933HGHVozwfDqdrt6xLrTv5/dVCCGEaGySgAghxDVGURSeeuqpa3ZRASGEEOK/IQmIEEJcYyTxEEIIcT2TBESIJuiXKqaf//Bb2+5SHorPP6Y8QAshhBCiIZKACNEEud1uFi1aRH5+fr33FEVhxIgRhISEUFVVxfLly7HZbLRq1eoXl2U9efIkBQUFhIaGaitnCSHE9cbjUdHrm96XLE31usWVJwmIEE2Qx+Ph0KFDnD59mpycHE6fPo2iKHTq1AmdTke/fv1QVZWffvqJF154AYPBwKOPPsr48eMbPF5hYSFLlizh66+/Rq/X8/vf/14SECHEdUuvV3jyyVyOHXP9cuPrREKCkbfeCmnsMMR1QhIQIZogs9nMo48+itvtZtu2bSxbtgxFUfjLX/6Coij4+vqiKAoLFy6kb9++bN26lb1791JaWtpgfQi73U7Pnj05ceIEp0+fvujwLiGEuB4cO+Zi/35nY4chxG+S7pebCCGuN4qi4OfnR1BQEL6+vlitVqxWK0FBQQQGBmIwGCgoKGDXrl306NGDPn364HQ62blzZ4PHMxgMREREEBoaetnL5wohhBCiaZEeEHFZvF4vO3fuZMGCBWRmZjZ2OPX4+/uTkJBAcnIyPXv2ZNGiRYwYMQKdTseaNWto0aIFUVFRZGZmcvz4cW644Qa8Xi8LFy5k+PDh6PV61q9fT0xMDLGxsZw7d44DBw5oQ5IWLFjA0KFDMRqNbNq0idDQUJo3b05eXh67du1i4MCBqKrKwoULGTx4MCaTiW3btuHn50diYiKFhYVs3bqVwYMHA7Bw4UL69++P1Wpl586dWCwWWrVqRUlJCRs2bGDo0KEALF68mBtuuAG73c7evXsBaNOmDeXl5axZs4Zhw4YBNUOhHA7HFSnEt2HDBi1JSU1NZf369WzatIkbbrihXludTodOp8NgMNSpMi6EEEII8XOSgIgLUlXIyQGHAywW0Olq5g7s3buXpUuX0rVr18YOsR673Y7L5WLv3r307NmzToE3o9GoPRzrdLo61bgvp13t6k5Go1GriK3T6eoc4/xtg8Fw0Xa1xzu/XW0F8PNjOr9dLUVR6sSn0+mu2OpTixYtory8nMWLF1NdXc3BgwcpKCiguLgYPz+/K3IOIYQQQjQ9koCIeior4eBByMqCjAzw84PwcGjeHPz8vJSWlhIQEMAbb7zR2KE2KCcnhw0bNqDX6xkyZIi2v3v37tp2RESEtqKTTqer065Lly7adkhICCEhNZPuFEWp065Tp07admBgoNYzoCiK1sMB0L59e23bz8+Pvn37aq8HDRqkbbdp00bbdjgc9O/fX3s9cOBAbbtVq1bats1mq/PelUgMVFWltLSUjRs30rx5czIyMlAUBa/XS3FxMQcPHqRbt27/9XmEEEII0TRdNwmIy+Xi3LlzeDyexg6lQfn5+bhc1/ZqGaoKFRWwaxf83//BkiUQGgolJRATA/feC8OGgfMan3MXGhrKTTfd1Nhh/Kbt2bMHp9PJW2+9RUxMDIqisHLlSr777jt++umnegmI0+kkNzeX3NxcioqKyM7OJjMzk6ioqEa6AiGEEEJcq66bBOT06dM8//zz5OfnX5Hx71famTNnSEtLa+wwLsrphJUr4Q9/gNrpHTk5Nf979Cj8859w9qwOVdUBsg749UKv12OxWLShW6qqsmzZMoYNG4aPj4+2v3nz5iQlJbF8+fJ6x8jIyOCll15i9erVVFdXs2PHDtatW8cnn3xyVa9FCCGEENe+a+9JUpsxIQABAABJREFU/T80e/ZsfH19GTFiBLGxsY0dTj0LFiy4pifnqip8+y28/DKcPFnz+ucqK2HKFAMGQyB9+oRf9RjFr6NLly51hp3pdDomTZpUr11cXBxPPPEETzzxRL33mjdvzpQpU37VOIUQQghxfbhuEhCAqKgounTpQsuWLRs7lHoOHz5MVlZWY4dxQSdOwO7dcPZsw8lHLacTXK4ueDzRVy84IYQQQghx3biuEpBaV2oVoCtJURQOHz7M2bNn2bhxY2OHU8/Jk3Fs2dKJyspfSt4UVDUcr1dWQRJCCNF0JSQYf7nRdaSpXa/4dV2XCci1yuPx4HQ6qa6ubuxQ6qmuduJyuXG7PYD+F1orl9BGCCGEuD55PCpvvRXS2GFcdR6Pil5/7X3JK357JAG5imJjY+nQocM1WT/jxAkriuLLqVM6ysou3lZRClCUXCDgqsQmhBBCXEua6kN4U71uceVJAnIV+fj4EBUVRUJCQmOHUk9ISE3tj1WruGgCoter6PWH0et3Ah2uVnjiCvN4PBw4cIDy8vJ67ymKQmpqKna7HbfbzZEjRzCZTISFheHr69vg8YqLizl58iR5eXlYLBZiY2OJjIzUCisKIYQQQtSSBEQANcUGu3evSUJmzaqp/eH11m2j10Pbtl50ulPo9dsbJ1BxRXg8HrZv3052djaVlZWUlpYCNTVUdDodMTEx2Gw20tPTmTlzJhaLhQEDBlywAOG+ffvYsWMHhYWFKIpCQEAAnTp1qlP8UQghrhdNdShSU71uceVJAiI0aWlgNEJhIaxbV7MilskEbjdYrdCiBdx1l4e8vAr27i1t7HDFf8lkMmGxWMjOzubAgQMoikJsbCyKomg/q1evZt26dZSWlmKz2ejcuXODdXZyc3Pxer2EhISQn5/P6tWr2bdvnyQgQojrkl6v8OSTuRw7dm0XGL6SEhKMTXLei/h1SAIiNIoCHTrAW2/VFB1ctAj8/aG0FBISYPx46NZNZc4clb17Gzta8d8wmUzceeedAGzcuJFFixahKApPPvmk1sbtdrN8+XIGDBjA+vXrOXbsGPn5+YSFhdU73vmV50+ePInVauWbb775tS9DCCEazbFjLvbvdzZ2GEL8JkkCIuqJiIB334V33oG9eyE6umaIll4P1dU1cwRUVW1w/kBjUxQFnU6HXq/HYDDgcrkwGo0oioLL5UKv16PT6fB6vXg8HoxGI6qq1mtXe4yLtXO73SiK8h+3A3A6nQ22qz2GyWRqsB2AwWCo187r9Wq9F/+t7Oxs9u/fz4MPPoivry+HDx9m48aNdZKNn/N4PJw6dYr9+/fTqVOn/zoGIYQQQlx/rt3S3KLRKQq0bQuBgTXJB9Q89IaFhXHmzBl8fHyuuZ+kpCTuu+8+Pv/8c9xuNy+//DLe/zeZ5fPPP+fAgQMAHDhwgM8//xyoeWh/+eWXtQf76dOns3v3bgCOHTvGxx9/rN2Tl19+Gaez5huvmTNnsm3bNgBOnTrF+++/r7X717/+RWVlJQDff/8969evByArK4t33nlHa/fqq69q8y8WLFjAypUrgZohTW+99ZbW7vXXX6ewsBCApUuXsnTpUgAKCwt5/fXXtXZZWVm4XFdmSMDs2bNp06YNRqORhIQEFEVh5cqVqBeoVKmqKjt27GDmzJmcPn2av/zlL1ckDiGEEEJcXxT1Qk8TPzNp0iRUVWXixIkEBwf/2nFdtsmTJ1NRUcHYsWNJTk5u7HDq+fjjjzl79ix9+/alb9++jR3Of0xV1To/16IzZ87www8/8MQTT6CqqtYjcH7vQG38Op1O275S7aBuT8SVbld73xtqd/57l+r8IVgvvviitr979+6cPHlSO15lZSXt27fn888/p1mzZvWOs379et5//310Oh3PPfccrVq1uiaLggohxJVw441nm9QQrNRUEwsWRDZ2GOI6IUOwxGW5UsN7fk2xsbE88sgj9WKtfUiHutdxpdv9/L0r3e78/T9vdyV+N6qqcvDgQbKysliyZAnR0dEoisKKFStYvHgxixYt4rHHHqvzmfnz5/PRRx/Rvn177rnnHq3HRAghhBDi52QIlrju6PV6rFZrY4fxm6WqKj/88AO9e/cmIiKCwMBAAgMDad26NfHx8SxbtqzeZxYtWsSuXbv44osvGDduHD169GDo0KFs3y7LNQshhBCiLukBEaKJa9myJX5+fnV6ekaNGsXw4cPx9/fX9sfExHDHHXc0OIRw/Pjx3HjjjXg8Hq29yWQiLi7uql2HEEIIIX4bJAERoomr7eGoVVsJ/efsdjuJiYkkJibWey8tLe1XjVEIIYQQ1w8ZgiWEEEIIIYS4aqQHRAghhBDiMiUkGBs7hKuqqV2v+HVJAiKEEEIIcRk8HpW33gpp7DCuOo9HRa+XFQ7Ff08SECGaqIbqufx82eHLPd75x2nofa/Xi06n+4+W6K09fm1hyfMpilJnqeLLje1q+XntHFmqWIjfpqb6EN5Ur1tceZKACNFEuVwu1q1bR3p6OoqiYDabiYqKolevXuj1+ss+ntfrpaioCICgoKA676mqyunTp9m/fz9t2rQhJiam3ucvpYhidXU1X331VZ0HeZvNRnJyMh06dLjg56qqqqisrESv1+Pn53c5l3XFud1uzp49S3R09H90n4UQQojfOklAhGiiKioq+PDDDzlz5gzdunWjpKSEgwcPkpiYyNSpUy/7eLm5ubz++usoisLkyZO1/aqqkpuby+23305xcTFvvPFGvQTE6/Uyf/58hg4dislkumAPSklJCY888gj3338/JpMJAD8/P/z9/S8a26ZNm1ixYgWRkZH8/ve/v+xru5LOnDnDoEGD2LhxI6GhoY0aixBCCNEYJAERognzer306tWLv/71rxQXF7Nw4UJmzpypvT9//ny+/PJLMjMzSUpK4qabbmLUqFEUFBTwzDPPsHnzZqxWK+PGjePcuXP89NNP5Obmsnv3bjp06MDLL79MRUUF48ePp0ePHqxbt67eMKTaOP73f/+Xnj17EhgYeNFeEI/HwwsvvIDD4QBqekxMJhPp6elMnTqVgoICduzYAcATTzzB4MGDmT17Nj/88AMmk4mlS5cyevRoxo0bx0svvcSCBQsIDw9nzJgxDB48mJMnT7J69WoADh8+jNfrZdq0aUydOpUvv/ySwsJCunTpwtixY+nfvz9lZWX88MMPfPDBBxQWFtKhQwdGjBjB0aNH6datG4MHD6akpIQNGzbw3XffoSgKmZmZjBo1iqSkJCZMmICPjw9z5sxh4cKFWK1Wbr75ZiZOnEh5eTkvvPAC69evp6qqig4dOjB27FiGDBlyJf8MhBBCiKtKEhAhmrj169fzz3/+k8LCQnbv3s19990HQHl5OZ9++il9+vQhOTmZ3bt3s2zZMlq0aMGOHTs4deoUH330EUVFRZSXl5OQkEBWVhZOp5OJEyfi7+9PdXU1zz//PB06dKB79+7s2bOnwRhqezcamt/RkBdeeKFOD8gNN9xAfHw8x48fp7y8nGeeeYb09HSmTZtGp06d6NKlC4WFhQQHB3P77bcTGhrK1q1b2bZtGy+99BJVVVXMmDGD0NBQVFVlx44dVFZWMmzYMIKDgykuLubDDz9k3LhxBAcHs3z5clasWEFqaipFRUW89dZb3HfffSQnJ7Nq1SqSk5OZN28eRqORtLQ0CgsLmT9/Pi1atKBNmzb88MMPPPvss0RFRREdHc38+fM5fPgwf/7znzEYDLz55psMHTqUHTt2cPToUSZMmEBoaChlZWXadQshhBC/VZKACADOnj3L4sWLWbFiRWOH0qCEhAQGDx5Mz549cblczJ8/n5tvvhlFUVi2bBmtW7cmIiKCkydPcurUKfr06YPH4+GHH37gpptuQqfTsWLFChITE4mJieHMmTMcPXqU/v374/V6mTt3LqNHj0av17N69Wri4uJo1qwZWVlZ7Nu3j0GDBqGqKnPmzGHkyJEYjUbWr19PWFgYCQkJ5Obmsn37doYOHYqqqsydO5fhw4djNpvZtGkT/v7+JCcnU1BQwMaNGxkxYgQAc+fOZciQIVitVrZt24bFYqF169YUFxezZs0aRo4cCcC8efPo378/Pj4+7Nq1C4D27dtTVlbGihUrGDVqFAAFBQX4+vpiMFz6f9p2u53Q0FB8fHyoqKhgwYIFjBo1ihMnTpCZmcmZM2fQ6/Wkp6dz9uxZ7fzp6emcOnWKFi1akJqaisfjYeXKlUBNYcKqqiq+/fZbsrKyuPvuu3E6nUDNPA6Xy0Vubi5r1qxh69ateL1eCgoKeOGFF7BarcTFxTFkyBCSk5MbjLl58+ZYLBYAfHx8CAgIwOv1oigKnTt3pl+/frRp04a3336bsrIywsLCiIqKIiIigk6dOlFVVcVXX31FaWkpR44cweVyceTIEY4dO4avry++vr507tyZkSNHYrFY2Lp1K1arlf79+xMZGcm5c+fIyMhg48aNuFwubDYbN910E8HBwURGRhITE0Pz5s3Jy8tjx44dmEwmduzYwUMPPYTFYsFsNtOpUydCQ0M5duwYR44c4ezZs6Snp+PxeMjJyWHjxo2YTCbOnDnDqVOnCAsLo2XLljJsSwghxG+eJCACgBMnTnDgwAEqKysbrILd2CIjI3E6nWzdupUOHToQEBCgvefr64vRWLM+uclk0obmAHXmBjgcDu3b40ttZzQa8fX11d4LCAjQhgf5+PhgNpsBMBgMdSY3+/v712lX+7BsMBjqnMvf319bvclut2vn1ev19drVTli22Wza/p+3MxgMl72yUvPmzRk2bJg2Ofqvf/0r27dvJy8vD39/fywWC6qqEh0dTUxMDMHBwURFRdGvXz+2bt3K5s2b6d+/PwkJCej1ehRFwWq1UllZyZYtW8jKymL58uVkZ2dz+vRplixZQmRkJPHx8djtdi150Ol0+Pv7Y7PZ6vxOGzJs2DDt91c7sTw7OxuDwUBMTAy+vr7YbDbKyspwuVzo9XoMBgNGoxGLxUJVVRVHjx4lJiYGj8eDwWCgb9++xMbGUlRUhMPhIDk5mWbNmuH1ejlx4gQRERGEhoZqSUZ2djZHjx5FVVWtJwMgJSUFgG7durF06VIWL15My5YtCQkJITk5mczMTBRFwWKxYLFYyM3NpaqqioCAAO1vYfDgwfj5+ZGUlETfvn3Jzs5mwYIFxMfH06dPH0lChBBC/KZJAiIAyMvLw+FwcNtttzFu3LjGDqdBWVlZ7Nq1C4PBQL9+/bT9Xbt21bYjIyOJjIwEah5M+/fvr72XlpambYeFhREWFgaATqer065jx47adnBwMMHBwUDNXIPzz9uuXTttOyAggO7duzfYrnXr1tq2r68vPXv21F737dtX227VqpW27ePjQ+/evbXXN9xwg7adlJSkbVut1jrvnZ8sXarg4GBSUlLweDwEBwfj7+9PZmYmYWFhWCwW2rZtS3JysjZ3w9fXFz8/Px5++GF27tzJ/Pnzyc/PZ/z48SiKgsfjwePxYDQaadWqFdXV1aSnp5Ofn09lZSXnzp2jqKiI4OBgBgwYQK9evfB4PEyZMoXx48cTFBSkJQoXkpCQUO9as7Oz67w+f1ne2sTO5XJp7wUFBeHxeOjTpw8Gg4G0tDTCw8PZsmVLneMoikJAQAAlJSVUVVXhdDopKyvD4/HgcDgoLCykpKSE8vJybDYbeXl5BAQE0KFDB9atW8fKlSspLi5myJAhmM1mzGazdo9UVcXHxweHw4GiKPTq1Quj0Uh1dTV+fn4EBQVx9913c/DgQdasWcPq1atxu911/kaFEEKI3xpJQMRvRkREBBEREY0dxnUnNzeXPXv24HK5OHnyJIWFhSQlJdGmTRs+//xz3G43Op0Ol8tFRUUFLpeL06dPa4mgqqqsXLkSk8mEj48PGRkZ7Nu3D39/fx577DHtPLt37+aZZ57h4YcfZujQoUBNb47NZsPtdmM2m/H396/TK3Qhe/fuxcfHB6jp9Tl/2d+GeoCCgoIwGAxkZGRw+PBhbDYbQ4YMYcqUKeh0OgwGg9bz0dAk+Z49e/Laa6+xa9cusrOzOXz4MGazmR49enD06FFmzJjB2rVriY2NZceOHYwYMYLo6Gji4+NZuHAhBw8e5C9/+QtQk6xaLBYOHDhASUmJ1nuye/duVFXFYDBQUFCgTVbX6/W0a9cOm83GunXrKCkpufxfshBCCHENkQREiCZKURR8fX1ZuHAhy5YtAyAwMJDbb7+dAQMGoCgK48aNY9GiRXz88ccUFxcTFxfHI488QlZWFi+//DKRkZHodDoeffRRWrVqRWFhIQcOHOChhx6iU6dOfPDBB9r5aoepXWgSdXJy8kWHXUFNz0VwcDBjxozREo2wsDDuueceRowYgcPhqNNzUpt4tGjRgsjISKZNm8auXbsYPXo048ePZ82aNTz55JOUlJTg8Xh46qmnsFqtdYbNKYpCVFQU48aN47XXXqO0tJS2bdtyxx130LZtWyIjIxk0aBDjx48nPDwck8lE9+7dCQgIICEhgd69e6PT6WjRogWANl/kmWeeITIykmeffZYePXqQk5PDX/7yF0pKSiguLubtt98mLy+PN998E4PBgMVioUuXLtx0003/8e9cCCGEuBYoakNf9zVg0qRJqKrKxIkTtSEp15LJkydTUVHB2LFjLzhxtTF9/PHHnD17lr59+9YZdnOtmDt3Lrt27aJly5bX7BAs0XhKS0tRVRW73Y5er0dVVVwuF4WFhYSEhNTpsXA6nTidTkwm0zW3YlN1dTVVVVU4HA4tZo/HQ1FR0S/OO4Gaa6sdXnb+RH9VVamurqa8vFyby6GqKlOmTGHbtm2MHj2aYcOG1TlWaWkpRqMRo9Goze9xuVwUFRURGBioVYx3uVyUlJRgtVrrzP8RQgghfqukB0QI8Ytqhzudz2g0NjgZuvah+lrUUFKk0+kIDAy8pM9f7Npq53fUOn36NHv27EFRlDpzjGo1dE8NBkOdOUe1+y41PiGEEOK3QBKQq+jQoUNkZGSwfv36xg6lnoMHD6LX62nZsmVjhyKuQT+fV3GxlbYudxWuq6mh2C4n3gu1bWh/TEwMr776KkCDPUGXGsu1fD+FEEKI/4QkIFfJuHHjMJvNHD16VFuJ51pSO9FYHnaEuDJ0Op2WeMh/V0IIIcT/TxKQq8ThcDB8+HDKy8sbO5QGLV26lBMnTjS4ApAQ4j8jiYcQQghRnyQgV1FISAghISGNHUaDQkNDOXv2bGOHIa4it9vNsWPHyMvL0/YpioLNZqN9+/YXfHj2er1aNfPa+hWNxev1UlFRATQ8p0IIIYQQ1x5JQIRooqqrq1m8eDHp6emEh4cDNcOGQkJCaN++/QU/53Q62bdvH+np6dx2221XKdqGlZeXs3r1agwGg1ZbRAghhBDXNklAhGiiXC4X69evp6ysTFt8QKfT4XA4gJpFE5xOJyUlJbjdbgICAoiJicHj8TBr1ix27dpFaGgo0dHRxMTEcO7cOc6ePUtVVRW+vr5ER0cTEhJCVlYW+fn5AJSUlBAfH4/JZCIrK4ucnBx0Oh3R0dEkJCSgKApZWVmcPn2asrIyjEYjgYGB+Pv7U1BQQNu2bQHIz88nMzOT3NxcvvrqK62iuL+/PykpKWRmZnL8+HGgpk5ITEwMNpuN/Px8jh8/TmlpKXq9nubNmxMXFydDpYQQQoirSBIQIZq4xMREbrzxRu117cTpKVOmcO7cOXJycqioqCAhIYFbbrmF1NRUFi1aREFBAS+//DI33XQTN954I3PmzGH58uWUl5cTGxtLv379uPPOO1m1ahXz5s0jMDCQ06dP87vf/Q69Xs+8efPYu3cver2e7t278/LLL6PX65k7dy5LliwhJycHHx8f2rVrR6dOnZg3bx5ffPEFRqORNWvWsHTpUrxeL4cOHaKgoICqqiratWvHc889x1dffcWiRYswGo2kpKRw//33ExcXx9q1a/n4448pLCzEbDYzduxYHn744To1PYQQQgjx65J/dQWAVjitoqKCoqKixg6nHoPBoNVwqC36ZjabURSF6upqDAYDer0ej8eDx+O5pHZutxuz2VyvndPpRK/XX1I7nU6HwWDA6/Xicrkuqx1AVVWV1s7lcqEoygXbmUwmdDqdtoqa0WjE6/XidDq1qt1erxdFUS7rG/1FixZx5MgRFEVBp9MRHx/Pe++9R05ODsXFxTz++OPY7XYWLlzIvHnz6NGjB+PHj2fDhg28//77+Pj4sGXLFnbv3s3QoUPp06cPmzdv5u2332bMmDGUlJSwYsUK/vSnPzFixAji4uL4+uuvKSws5J133qGiooLx48fz8MMPExgYyAcffMD48eMZMmQI586dIzs7m8TERNatW8eJEydISkpi5syZdO3alQ4dOqCqKkajkRdeeAGDwUBeXh7vvvsu3333HcHBwTz11FNs3bqV06dPs3HjRiIiIpg2bRp5eXkcPnxYej+EEEKIq0z3y01EU5CUlMS5c+d46KGHCAwMvOZ+Bg0axLfffouqqjidTiZPnqyt2DVlyhRtuM3u3buZMWMGUDPJevLkyXi9XgC++OILDh48CNTUPfniiy+Amof2yZMn43a7AZgxYwa7d+8G4Pjx40yZMkW7T5MnT8bpdALw7bffsn37dqCm6NyHH36otXv11VeprKwE4IcffmDjxo0AZGVl8d5772ntXn/9dUpLSwFYuHAhq1evBiAvL4+3335ba/fmm29qieGyZctYtmwZAEVFRbz55ptau6ysLO06LlVaWhpPPvkkTz75JE888QR33XWX9t6QIUPo2LEjPXv2JDw8nFOnTqGqKr6+vlgsFkJDQ/Hx8WHVqlWcPXuWFStW8M4777Bw4UJKS0u1+zh8+HAeffRRRowYQX5+Ph6Ph+7du9O1a1c6depEv379WLhwIYsXL6Zly5YMHDiQVq1a0bdvX8aOHUtERASDBg1i+vTpZGdns2HDBvr3709CQgIWiwW73U5oaCgmk4lly5ZhNpv57LPPePXVV8nOzmb37t0UFhZiNBrZuHEj//73vzl37hyjRo2qU8VdCCGEEL8+6QERALRs2ZIPPviA999/v7FDuaATJ07w73//mwkTJvC3v/1N2//73/9e2+7QoQMdOnQAanpNzm/30EMPadupqamkpqYCNb0/57e7//77te3ExEQSExO11+e3u/POO7XtuLg4/vCHPwA1K0n99a9/1d4bM2aMth0ZGclTTz2lvX7++ee17dGjR2vbISEhPPPMM9rrv/zlL9r2sGHDtO2AgIA670VGRnK5WrRoUW8C9897BfR6vfag3tBSzUVFRSQlJdG+fXtiYmKAmqFcLVq00JKQWhUVFXi9Xq3XRlEU7HY7paWllJWVYbVa6w2J8vf3Z+zYsYwfPx6LxcLw4cMJDw+vF4vX66WoqIhWrVpx6623otPpGDNmDKGhocTExFBZWUlqaipLlizho48+4q677uLll1++Ziu3CyGEENcjSUAE8P8/cF7Lw1GaN2/Oww8/fNGq3BfavprtrpWYLsflfM5gMBAaGsq5c+e0fYMGDWLRokU4HA569+5NVVUV6enpDSYr7du3Z/369ezevZuCggJKSkpYvXo1n3zyCTk5OcyaNYsjR44QHR1NYWEhRUVFtG7dmrS0NHx9ffnXv/7F/Pnz8fPzw+v1otfrqaiooLq6GpvNxvDhw3n33XdJTU0lNDSUwsJCCgsLSU9Px2w2M2TIEIYPH86cOXP44IMPpPaNEEIIcZVJAiJ+M86vLC2unI8//pi5c+cCNT0diYmJfPfddxdsb7FY6NSpE4WFhQwcOJDhw4dz8803c+zYMWbPns2nn35KZWUlPj4+fPDBB/U+HxISQvfu3Zk1axajR4/GYDDQq1cv2rVrh9vtZuDAgbz44ov885//xGq10rVrV1555RUsFgsjR45k6dKltG3bVpsf07ZtW2bPns2NN95Ihw4dmDRpEnfffTePP/44lZWV5Ofnc9ttt9GsWTN27NjBihUrCA0NpaKiggkTJqDX63+V+yqEEEKIhkkCIkQTZbfb+Z//+Z86Q9MURdGW4X366afx8/MjMDAQRVG4+eab6d27NyaTibCwMN59910KCwtp0aIFkZGR3HrrrfTq1Yvi4mKqq6sJCAggJCSEESNG0LNnT+x2O1DTg9KtWzeioqLIzc1FURRiYmIwm81YLBYmTJjAyJEjtYn3UVFRQM3wqlOnTnHrrbdit9u1IWFDhw4lOTmZ0tJSgoODMZvNPPDAA9ryv0ajkfj4eHx8fEhJSaFPnz6oqoqfnx+JiYkyB0QIIYS4yhT1EscfTJo0CVVVmThxIsHBwb92XJdt8uTJVFRUMHbsWJKTkxs7HCGue7WrfZlMJm3lLVVVcbvdeL1erYfiQrxer7ZAwM/nfNSuPqbT6TAajbjdbtLT07npppv46quvaN26dZ2ei9rVz2pXL6tVWVmprR5WG5/H48HpdGKz2a7g3RBCCCHEpZIeECHEf0RRFG0i+fn7LnVCt06nu2Dvw88TCVVV0ev1DB8+nFatWtX73M/b17JarfXiMxgMUvdDCCGEaETyr7AQ4ppXO4zqX//612XXORFCCCHEtUUSECHEb4IkHkIIIcT1QRIQIZqo2jkYqqpqD/dXe0Wo86egXa3kQlXVOteu0+m0675YDLWV6vV6fZ12tfNKVFXFYDBc8Bg/n24nyZQQQoimShIQIZqojIwMdu/eTU5ODg6HQyskeDV5vV7Kysqorq4mJCTkV30or00AysrK2LVrFzt37qS0tJSkpCT69++Pv7//RROwd999l6SkJLp3705QUJC2v7KyklWrVnHgwAGeeuqpC16D1+slLy8Pq9WqrTQmhBBCNEWy/qQQTVR1dTWbN2/myy+/ZP78+VRUVFz1GAoLC5k5cyZPP/30r34uVVXZuHEj48eP57HHHuP48eOoqsrMmTMZPXo0+/fvv+jn9+7dy6lTp6iurq6z3+12c/r0afbs2XPRz5eUlPCXv/yFWbNmaat/CSGEEE2R9IAI0UQ1b96crl27UlFRQWRkJGlpaZSUlHDnnXcSHx/P8uXL8ff354477uD48eNs3boVf39/7rrrLu68805Onz7NI488Qnh4ONu3byc2NpauXbtSXl6uFft7+umn6devH5s3b+aZZ54hIyMDu93O8OHDufPOO9Hr9bzyyiuUlpbSvXt3xo0bR3BwMHl5efTr14+2bduya9cuvvzySx544AEcDgd/+MMf6N27N2vWrGHEiBG0adOGXbt28fXXX1NRUcHQoUP505/+pNUvqbVjxw5mzZpFWVkZq1evxmw2oygKHo+H8vJyAgMDKSgo4IcffmDatGlkZmbSpk0bXnnlFVq0aAHATz/9xIwZMygtLaVjx47cf//9dOrUCfj/e1jy8vJ45ZVXWLNmDQ6HgyFDhjB06FCys7NZsGABq1atYsqUKUyaNIkePXpIb4gQQogm57J6QKZMmUJRUdGvFIoQ4mrS6/UYjUZtWdraehv79u3DYrHw1ltv0bJlS+bOnYuvry9PPfUUffr04YsvvsDpdFJVVcW2bdto164dkydPxtfXl7Vr12I0Gnn22Wfp0qULn3/+OVBT/fzZZ5/l66+/5vnnn6e4uJi5c+cSGBjImDFj6NSpE6+//jqjR4+moqKCzMxMysrKgJohU8ePH6esrIyqqipWrlzJmTNnGDlyJB07dmTTpk0cPHiQhx56iNdee43s7GwWLlxYb87F6dOnKSoqonPnzgQEBGC327HZbDgcDkJDQzEajaxdu5Y9e/bQvXt3/vWvfxEcHMxHH32kHcPr9fLAAw/w2GOPoShKgxXjZ82ahdvt5tlnn+Whhx6ipKSEhQsXkpSUROfOnbntttt47bXX6NSpU71lgoUQQoim4LJ6QHr37i3Fu65TGRkZzJ8/n6VLlzZ2KA1KSkpi+PDh9OnTB5fLxffff8/tt9+OoigsWrSI9u3bExkZyYkTJ0hPT2fAgAF4PB6+/fZbbr/9dnQ6HUuXLiU5OZnY2FhOnz7NoUOHGDx4MF6vl2+++YbbbrsNvV7P8uXLiY+Pp3nz5pw9e5Zdu3YxfPhwVFXlm2++4ZZbbsFoNLJ69WoiIiJISkri3LlzbNmyhZEjR6KqKt9++y2jR4/GbDazfv16AgICSElJIT8/n3Xr1jF69GgAvv32W0aMGIHNZmPz5s1YLBbatWtHUVERK1eu5OabbwZg9uzZDB48GIfDwfbt2wHo1KkTpaWlLF26lFtvvRWA/Px8/Pz8/qs6Fy6Xi2HDhtGlSxeOHj1KZWUlbdu2ZcCAAVitVubOnUt2djaqqmI2mxk6dCgxMTFs3LgRf39/OnToQO/evbHb7Xz77bcABAUFkZ2dzZYtWzh+/Dj79+8nLS0Nk8lEbGwsmZmZdOrUSYvb7XZrCYSqqrhcLlRVRVVVrFYrd955J7GxsaiqypkzZ9i3bx8hISGcO3eOnJwcVqxYwV133VXnuiorK/F6vYSEhOD1ejlz5gzPP/88AGFhYTzxxBPs2bMHVVUZNmwYrVq1Qq/X89xzz/HKK6+gqirt27enZ8+eBAQEUFpaytq1a8nNza1zniVLluDj48OBAwfweDza0K4HH3yQoKAg4uLi6NixI2azWaqwCyGEaJIu6yklKSkJk8n0a8UiGlF6ejrHjx/HbDbTtm3bxg6nnqioKAA2btxIWloakZGR2nthYWFaQTybzUZwcHC9z0HNt/C13zhbrVZCQkIabBccHKwl2haLhbCwMO29yMhIbVhPUFAQdrsdALPZTHh4eJ12tQ+XgYGBWjuTyVSvXe3E54CAAK2In9ForNMuIiJCezj39/fX9hsMBiIiIrTXtVXJ/1vNmjXT7mVgYCBBQUEEBgbicDgwGAyUl5ej0+kwmUxER0fjcDjw9/dHURRCQkLw8/MjKCiIkpISAJYvX86WLVuIiorSErHaVaWMRiN6vV4bElVbsfznPRi1bDYbqampOBwOMjMzcTqdmM1mAgMD8Xq9dOnSBbvdXu8+WK1WvF4vp0+f1oooJicnk5mZyZo1a7j33nvJy8tDr9cTFxeHr68viYmJZGRk4Ha7AQgNDcXf35/w8HACAgKoqqqq0yusqirp6ekMGjQIu92OXq+nXbt2WCwWbbUto9GI2Wy+6iuOCSGEENcKmQMigJpvzn18fBg9ejTjxo1r7HAadO7cOfbs2YPBYKB3797a/tox+ADh4eHag7ter6/TrkOHDtp2SEiIloDodLo67dq1a6dtBwYGEhgYCNQsm3p+u9atW2vb/v7+pKWlae169eqlvdeqVStt2+Fw0LVrV+11z549te2kpCRt22630717d+11jx49tO3a+QhQ81B9/ntXej5BQ7U3LpTgnL///EQCYN68eRiNRoYMGYLD4eDcuXOUlJSg0+kwm81UVlZqn7Xb7VRWVuJ0OnE6nZSXl9eb+F3LZDLh4+NDVFQUHTp0wN/fH4/HQ2VlZb04o6OjCQgIYPfu3Zw6dYrY2Fj++Mc/snHjRnbu3InX68XhcFBeXk5BQQHBwcGcO3eO4OBg7Vi111NcXExRUVG9yu+qqhIaGqrNqQkICKCyslJb7tdqtTbKZH8hhBDiWiIJiPjNCAsLY9CgQY0dxnWjuLiYrKwscnJyMBqNZGdn/2IP5+UUAzy/ncFgICgoiLKyMjIzMzl79iw+Pj6YTCaioqLIzc1l586dBAcHExsbS1lZGQcOHMBgMGjL5TYkJCSEFi1a4HQ6yc/Px2azaQlEbX2TWomJiXTu3Jm9e/fy3Xff0bdvXwwGA+np6TgcDoxGI23btmXHjh2sXr2agoIC1qxZw+DBgzEajSiKQkZGBnv37qW4uJhjx44RGxtbp6dKp9MxbNgwSkpKKC0txW63U1hYSHV1Na1atSI+Pp6jR4+yc+dOmjVrhr+//381XE4IIYT4LZJ/+YRoovbu3cuKFSvYtm0bsbGx/Pjjj4waNYqIiAjtW32r1Yq/vz9msxmo6XEICQnBYDCg1+uJiIjQHvJ9fHzwer3aUKrzh5vdddddPP/88yxZskQbutS9e3dsNhtt27bFZDLx6KOPcssttzB+/HhCQkKYPn06brcbg8FAYGAgJpMJg8FAeHh4nbkT/fv3x+12M3XqVHJycigsLOTee+9l5MiRda43ICCAIUOGoCgKn3zyCVOnTsXhcFBZWcno0aMJDAykZ8+eFBUVMXfuXKZNm0aLFi145plngJperuXLl7N8+XIqKiro0KEDjzzyCFarFbvdTkBAAAC33XYbU6ZM4YMPPiA7Oxuj0UifPn0YOnQoAwcO5LHHHmPbtm38z//8D3379sXX1/fX/UULIYQQ1xhFvdBA65+ZNGkSqqoyceLEOmPsrxWTJ0+moqKCsWPHkpyc3Njh/ObMnTuXXbt20bJly2t2CJb4bauqqqK0tBQfH596qz+pqkphYSF+fn7odDoURaGkpARFUfDx8bmkXheXy0V5eTlWq1VLmC6ktgBiZWUloaGh9Y5fu8rXz5MDVVXJy8vDYDBgt9sv2mNUVVWFy+XCYDBo11s7t6WoqAh/f3+ZhC6EEKJJkh6Qq+gScz0hrksWi0VbLODnFEXR5trUutyeAaPRWGeC/sXodDp8fX0veA6TydRgclE7yf5SNHS9tUPYfn6tQgghRFMiCchVNGfOnF+sttxYDh48iNFopGXLlo0dihBCCCGEuI5JAnKVTJ8+naVLl2I0GomJiWnscOrxer31Ju0KIYQQQghxpUkCcpVUVFQQERFB586d6yyveq348ccfOXbsmAwTE0IIIYQQvypJQK6i2uJ30dHRjR1KPUFBQZw5c6axwxBXmcfjIS8vj5MnT3Lu3DkcDgcJCQlER0f/6r1h1dXVVFRU4Ovr+6sV5fN4POzcuZOysrJ67ymKQocOHXA4HLhcLvbu3YvNZiMyMhI/P79fJR4hhBBCSAIiRJNVVVXF8uXLOXz4sFb0z+VysXz5cv7+97+j1+t/1STk6NGjrF27lttvv52goKBf5Rwej4cdO3aQk5NDWVkZxcXF6HQ6IiIi0Ol0JCQk4HA4OHz4MF9++SU+Pj6MGDGiTnFHIYQQQlxZkoAI0USdO3eO7777jtLSUvr3709AQAC5ubkcPHhQG4qXkZHBiRMntJ6KmJgYYmJi8Hq9nD59Wkte/P39SUhIoLi4mJKSEsxmM8XFxSQmJmI2m9m1axeVlZWEhIQQHx8PwLp16/joo4+wWq1ERUXRv39/CgoK2L9/P2VlZfj4+NCsWTNiYmKoqqpi+/btREREkJmZib+/P4WFhaSmphIcHIyqquTn53PkyBG6du2q1TE5f8Wp4uJiTp06hcFgoF27duh0Oq3dqlWr2L9/P8XFxYSHh5OWllanwrkQQgghrhxJQIRoovLz8yktLaV58+YMHToUHx8fbDYbPj4+QE3vwQ8//MDKlSspLS0lJCSE3r17c9999+H1epkxYwY//fQTLpeL8PBwxo8fz5YtW9izZw8tWrQgIyOD3/3udxQXF/PZZ59RUVFBXFwct956Kw6Hg0OHDpGRkcEXX3yBr68vvXv3ZtmyZcyYMYOCggL8/f258cYbueOOOygtLeW5555j2LBh7Ny5kzZt2rBixQqeeeYZ+vXrh9frZfPmzXzyySd8/fXXWvJgNBoZM2YMAGvXrsVsNmMymXj44Ye1++ByuVixYgWDBw9m1apVpKenk5ubS2Rk5NX/pQghhBBNgCQgAgC9Xo/X66W0tJTc3NzGDqee2mJuFosFVVWpqKjAZrOhKAqVlZUYjUYMBgMulwuPx/OL7dxuNy6XC6vVWq9dVVUVer0eo9F4ye08Hg9Op7PBdtXV1dq37R6Ph+rqamw2G1CzOIHFYkGn01FdXa1VEPd6vVRVVTXYzul0AjTYzuPxaIX8fklqaioxMTEsW7aMo0ePkpaWRps2bejduzd+fn4UFhbyxRdf8PDDD9O1a1eWL1/OqlWr6Nq1K35+frzzzjt8/vnndOrUifnz5+Pj40NGRgYnT56ke/fujBw5ksjISMaNG8eECRPo168f77//Pps2bWLQoEH06NGD7du388orrxAfH4/RaOT111/nvvvuo1+/fsybN4+DBw+yZcsWEhMTOXXqFHv27OHBBx8kKiqKQ4cOsW3bNuLi4vB6vWzdupUWLVpgt9sv628rMzOTI0eO8Mc//hGDwUB6ejpbtmzhpptuuqzjCCGEEOLSSBleAUBSUhK5ublMmDCByMjIa+7nxhtvZPbs2Xi9XpxOJ2+88YY2TGjq1KmcOHECgH379jFz5kwA3G43b7zxBl6vF6hZCvnw4cMAHD58mOnTpwM1SxC/8cYbuN1uAGbOnMm+ffsAOHHiBFOnTtXu0xtvvKElAN9//z07duwA4MyZM3zyySdauzfffJPKykoA5s2bx6ZNmwDIzs7mww8/1Nq99dZb2gTpJUuWsHbtWgDy8vL497//rbV79913KSoqAmD58uUsX74cgKKiIt59912tXXZ2tnYdv8RsNvPSSy/xxhtvkJCQwLJly3jggQcYNWoUHo+H5cuX4/F4WLp0Kf/+979ZsWIF+fn5rFixghUrVpCWlsbQoUMJCwvjwQcfpHnz5vj6+jJw4ECeeeYZevTogaIo7N+/nw0bNvDyyy+zb98+duzYQWZmJhaLBZPJRHBwMCEhIZw+fZqsrCxuvvlmWrduTb9+/fD392f79u1AzSIO//rXvxg6dCht27bljjvu4NChQxw8eJAjR46wd+9ebrvttku69vN9//33tGnTBkVRaNGiBU6nk3Xr1smKcEIIIcSvRFEv8V/ZSZMmoaoqEydOJDg4+NeO67JNnjyZiooKxo4dS3JycmOHU8/HH3/M2bNn6du3L3379m3scOr5LTxsHT9+nCVLljBhwgQA7Vv+2tgVRbng9sXaXYljXIvtLsX5v3ePx8PJkydJS0tjwYIF7Nq1i1WrVjF8+HBt5TabzYbNZmPu3LkcPXqU6dOno9PVfI+RkZHBG2+8gcFgYPLkyTidTvbs2cMtt9zCJ598orWz2+3ExcWxfft23n77bT7++GOaN2/Onj17uPnmm1m7di2RkZHs2LGDOXPm4PF4GD9+PMOHD2fp0qU0a9ZM69G688478ff3x+FwUFhYyJdffnnBa1+7di0//vgjJpOJ//3f/9X2d+nShVOnTmn3rbKykq5du/Lxxx/TrFmzS7qPQgghhLh00gMigJoHr2v9p3nz5jzyyCPa65/HfrHt//S933K7X7JmzRpmzJjB1q1btSFkp0+fpqqqCn9/f0aNGkVmZiZhYWF0796dbt26ERUVhdfrJTU1lZUrV3L69Glt/kV+fn6d4xuNRlJTU/H19cVsNtO7d2969eqlLXtrtVrx8/MjJycHgDZt2mA0Gtm5cydFRUXs3LmTiooKOnfu3GD8FouFfv36sXfvXnbv3s2NN954Sdddy+v1sm/fPrKysli/fj3p6emkp6fz2WefERcXx6JFiy7reEIIIYS4NDIHRPxm6HQ67Vt08d+zWq2sWrWKV155BVVVsVgsVFdX85e//IXExER0Oh133HEH06ZN480336SkpITIyEgef/xxBg4cyODBg+nXrx+RkZGoqsoTTzxRLzkymUz8z//8D//+97956aWXyMnJIS0tjXvuuYfY2FhatWrFo48+it1uZ/ny5fz5z3/mvffe4//+7/8IDAxk2LBh9OjRQxum9vNkq1evXqxbtw673U6/fv0ua9lgVVX5/vvvGTBgAIGBgVitVhRFISUlhQMHDrBs2TIee+yxK3vThRBCCCEJiBBNVXJyMk8//TQ5OTmUl5cD4OfnR1xcHEajEUVRuOOOOxgwYAAFBQW43W4CAgJo1qwZfn5+/PWvf9V6QBwOB/Hx8XTu3LlOEqDT6RgyZAipqakUFBSgqiohISFERUVhsVh46KGHGDx4MKqqYjKZGDVqFB07dqS4uBgfHx8iIyMJDg7G39+fGTNmEB4eXucaMjMzCQ0NpWXLltpyuxfStm1boqOjtSRWp9Nx99134/F48PX11eJu1qwZ9913n0xCF0IIIX4lkoAI0UQ5HA6Sk5NJTEzE5XJpvSDnJxDh4eGEh4drE+9rExOAhIQE4uPjcbvdmEwmdDodYWFhdc6hKDV1OAIDA6murkav19cpcBgXF0d0dDSqqqLT6QgJCSEkJASXy4VOp9MqpBuNRrp06VLn2B6Ph/Xr1+NwOOjcuTMGw8X/78zPz69OhfPaYX0/Z7VaiY2NvdTbKIQQQojLJAmIEE1cbVJwMSaTqd4+RVEwGAy/+OBfy2w2X/AYP3epRQBTUlIICQmhZcuWl9ReCCGEEI1PEhAhxG+SXq/n7rvvvqyJ90IIIYRofJeVgBQWFpKenq7VI7iW5OXlNfgNqxDi+iWLEgghhBC/PZeVgMyePZulS5f+4nCNxpCXl8eYMWPweDyXXIjtavJ4PL+JWhui6VBVFY/HoxVqrFU7LOpCvQq1f8eqql6TvQ+qquJ2u/F6vZhMpv86PlVVtWOePwdGCCGEEP+Zy0pAbrvtNu69914CAgJ+rXj+Yx999BE5OTls376d3Nzcxg6nnmPHjsm3teKa4nK5WLt2LSdPntT2KYpCQEDARVeA8nq9lJWVUVVVRWho6K8f6GXyer389NNPHDhwgMceewyr1fpfHzM3N5cffviBO+64o85EdiGEEEJcvstKQHx9fYmJiSEoKOjXiuc/5u/vz5IlS9i7dy82m62xw6knKyuL7t27N3YYQmgqKir44IMPOHnypLbClE6nIyoq6qKfKysrY9asWaxevZpp06Zdcz0CXq+XM2fOsGfPnivWG1pZWcm+ffu4+eabr8jxhBBCiKbsshKQ8wuMXWsURWH48OGMGTOGpKSkxg6nns8+++ya7JkRYsCAAfz9738H6lZS//vf/05OTg779++npKSErl27cs899xAeHs5LL71EaWkpXbp0YezYsdx3330sWLCAb7/9lqysLNq0acM999xD//79mTt3LqtXrwZg//79PPbYYwQFBTF37lyWLFmCyWTi7rvv5plnnkFRFL7//ns+/fRTzp49S0pKCmPGjGHkyJEcPXqUCRMmEBsby7p16+jUqRNPP/007du3p7CwkB9//JE333yTc+fOYbfb6datGwDZ2dm8//77LFy4kMrKSnr27Mlzzz1HfHw8ubm5PP3002zatAmr1crYsWNp3bo1Z8+eZd++fXg8Hnbt2sV7773H0aNHcTqdrF27lqVLl7Jv3z5yc3MpLy9n7NixPPvsswB88803fPTRR+Tn59OhQwduv/12hg0bdvV/sUIIIcQ16rpaBctoNGK1WrHb7Y0dSj1ms1mGYIlr0qJFizh79ixQs7JUdHQ0//jHPzhz5gy5ubncf//9mEwmtm3bxty5c3n22We566672L59O//4xz8IDw/n+PHjbN++nQEDBtC5c2cOHDjA66+/Tp8+fSgoKGDu3Lncf//93HXXXcTHx7N48WIyMjL4v//7P6qrq3nllVcYN24c/v7+fPjhh9x0002kpqayceNGli1bRmpqKpWVlezatYsxY8bwu9/9jrfffputW7cSFBTE9u3bmTZtGiNHjmTYsGF89dVXFBcXAzB37lztOgICAtiwYQNTp07lhRde4PPPP6eyspK3336b6upqvF4vpaWlHD16lNWrV3PXXXfRo0cPDAYDp06dwu12U1JSwvHjx/H39+fee++loqKCf/7znzz00EOYTCbeffddxo8fT0JCAkuXLmXFihWkpKQQFxfXmL9mIYQQ4ppxXSUg4j935swZvv/+exYvXtzYoTQoOTmZUaNG0b9/f1wuF9988w133nkniqIwf/58OnToQHR0NMeOHePEiRMMHjwYt9vNzJkzufPOO9HpdCxatIiUlBSaNWvGyZMnOXDgAMOHD8fr9fLVV18xduxYDAYDS5cupXnz5iQkJJCRkcHOnTsZOXIkqqry1Vdfcfvtt2M0GlmxYgWRkZEkJyeTnZ3Npk2buOmmm1BVla+//ppbbrkFi8XCmjVrCAwMpHXr1uTl5bF69WpuvfVWAL7++mtGjx6NzWZjw4YNWK1WOnToQFFREcuWLeO2224DYNasWQwfPhyHw8HWrVsBSEtLo7S0lEWLFnHHHXcANYsx+Pv7X3JtDoCoqChteKBOp9Mqirvdbjp16kT37t0JCAjg1KlTbNmyBZ1OR3R0NCdOnKBNmzYYjUbmzJlDRkYGLpcLl8vFqVOnOHXqFEePHsXj8dC6dWvGjBlDWFgYJ06coKysjJYtWzJgwADKysr45ptvWLNmDSEhIeTn53Pw4EFKSko4ePAg+fn5bN++nZYtW2K1Whk9ejRBQUGkpKSQm5vLkSNHSE9PR1VV7rvvPiIiItiyZQvbt28HYN26dbRp04YBAwbg5+eHx+Phk08+4X/+53+YN28eEyZMoFu3biiKgsvl4tChQxw5coTOnTtzxx13YLfbyc/Px+12axPSg4KCSEhIoG/fvuTk5GCz2Th69CglJSUUFhayb98+zp07x5EjR/B6vezZs0cSECGEEOL/kQREAHDixAkyMjIICwujY8eOjR1OPeHh4ZhMJtasWUPPnj1JSEjQ3ouNjdV6vXx9fYmOjgZqHqYTExO1IUUxMTE4HA6gpgp4TEwMUDPsKDExUeuhio6OxtfXFwC73V6nKnZCQoLWLjIyEn9/fwBsNludB8wWLVpoq8WFh4dr8VksFuLj4+u0q00WwsLCtAJ8JpOpTrvmzZtr74WEhGj7jUZjnWreP69kfikSEhIYPny4di/OLwIYEhKCn58fwcHBWCwWKisrUVUVg8GATqfTevYyMjLw9fUlLCwMPz8/EhMTCQkJ0QoYhoaGEhcXh5+fH3v27MHr9RIWFkZAQAB6vZ6IiAhOnz5NeXk5QUFBBAcH4+fnR+vWrdHr9VqFdZPJRGRkpJYo5eXlUVpaisvlwtfXl/j4eDweDxaLBahZwSo7O5vevXsTGhqK3W4nPDycrKwsnE4nBw8epGXLlvj4+GjXnZGRgdlsJjw8nGbNmqGqar2lx202GwEBAQQEBFBeXo6Pjw8lJSWcPHmSkJAQLf6OHTtis9nq/M6EEEKIpk4SEAHU1Hix2+0MHTqUcePGNXY4DcrJyeHAgQPo9Xq6du2q7W/Xrp22HRoaqq3MpNPp6rRr06aNth0UFKQtpqAoSp12KSkp2nbtQ2ZD7ZKTk7VtX19fOnTo0GC78+ck+fj41Enwaid/Q00yUstms9G5c2ftdVpamrbdrFkzbdtisdR5z8fHh8vl5+dX55gNOX9uiKIoWK1WKioqtPfDwsKorKwkKSmJjh074na7KS8vb3DFqICAAHQ6HUVFRVRVVVFdXU1OTg7dunUjODgYvV5PSkoKrVq10pYKtlgslJeX14sJapJEh8OB2+2moKAAX19f8vPztXbBwcGUlZVpQ7IKCgoIDQ1FURTMZjOnTp2iVatWAJSXl9c7zy9RFAWdToeqqlpy1LZtW5o1a6Ytv12bqAohhBBCEhDxG3J+ciGunNOnT7Nq1Sqg5mHabrfTqVOnC7Y3Go3ExMSQn5/Ppk2bCAsLo0uXLmRnZ1NYWEhRURGVlZXk5uY2OOyoRYsWBAcHs2/fPlatWkVVVRW5ubn06NGDwMBApkyZQmlpKUVFRTidTpxOJ8HBwRfs2fH39ycqKgpVVVm4cCExMTHs378fnU6Hoij06tWLM2fOsGbNGhwOB/v376dfv35YLBb69+/PwoULsdvt6HQ69Hq91ttxuT1JtYmnyWSiuLhYuw9er/eyhsQJIYQQ1zv5V1GIJkqn0xEaGsrSpUvZvHkzUDMJPSkpiblz5xISEoKvr682lMzPz4/w8HAsFgtt27bF4XDwzDPPMGrUKO69917atWvHihUrmDNnDpWVlQQHB9OzZ098fX0JCQnRhq4FBATQo0cPMjMz+cc//oHRaGT48OHacLmxY8fy448/MnPmTEpKSoiPj+eRRx4hODi4znA4Pz8/3G63Fk+3bt148803URSFsLAwUlJS0Ol0DB8+nBkzZjBz5kyqq6tp27YtDz30EDqdjj//+c/88Y9/5G9/+xtut5uRI0eSmpqKv79/naFoRqOR6OhoDAYDNpuNwMBAbThf7RAyq9VKUFAQd999N4sXLyY7O5uSkhJat27NI488crV+rUIIIcQ1T1EvsTz3pEmTUFWViRMnEhwc/GvHddkmT55MRUUFY8eOrTM05lrx8ccfc/bsWfr27Uvfvn0bO5x65s6dy65du2jZsuU1OwRLXFtUVaWwsBA/Pz+tt8Hr9VJVVYXT6fzFYUcejweXywWgzdk4X2lpKVAzHK02Cfql41VVVaGqaoND0Wp7IxpaJa+goACLxYLZbL6kc12K4uJi9Ho9NptNVsATQgghziM9IEKI/4iiKNqKWbV0Oh02m+2SioHq9fqLPuzX9jBcKr1ef9EluC9WEf3n13ElSMV0IYQQomHytZwQQgghhBDiqpEERAghhBBCCHHVSAIihBBCCCGEuGokARGiiSsrK+PIkSMsWbKEb7/9lhUrVlBYWMjF1qdQVZW8vDzeffddqqur672fmZnJJ598QmFh4QWPUVsrpKSk5IpchxBCCCF+GyQBEaIJO3bsGLNnz+bzzz9n3bp1HDlyhFWrVvHaa69RXFyM1+tt8HOqqlJcXMx3332H0+ms935eXh7z58/XVrJqSFFREZs3b2bhwoVX7HqEEEIIce2TVbCEaKJKSkpYtGgRO3bsIDAwkNTUVEJCQjh37hy7du3C7Xbj8Xg4cOAAJ0+epKqqisDAQFJSUggJCcHpdHLs2DFWr15NVVUVVquV5ORk4uLiqKqq4syZM7jdblRV5cSJE+zfvx+Px0N4eDjNmzcnIyODGTNmkJmZic1mIyEhgVatWsmStUIIIcR1ThIQIZqo9PR0li1bRkJCAs8++yxhYWFATe+Gy+XCYDCQn5/PrFmz2LZtG1VVVYSHhzNs2DDuuusuoKa2xqxZs8jMzMTr9XLHHXdw66231jmPx+Ph66+/ZsuWLVqRwJEjR6KqKlu3bqW0tJRp06YxevRoWrZsKQmIEEIIcZ2TBOQqMRqNVFdXk5ubS2ZmZmOHU09+fj6lpaUUFBRck/EZjUZ8fHyw2WyoqkppaSkOhwNFUSgrK8NisWAwGHA6nbhcLux2e7125eXlmEwmjEYjLpcLp9N5wXZGoxGTyYTb7aaqqgofH5967SoqKjAYDBds5+Pjg06no6KiAr1ej9lsxuPxUFFRodW4KCkp0dpVVlaiKAoWi6Veu9LSUux2OzqdjqqqKqCmeJ/X66W8vFxr5/F4tKKAv+TYsWMYDAaaNWtGWFgYLpeL/Px8bdhVaGgoGzZs4NixY9x+++20bt2a5cuXM2XKFO644w6gZh7H8OHDSUlJ4dNPP+Xw4cMcOHBAq7mhqir5+fl8+umnvP/++8TGxvLuu++yadMmevbsye23387Ro0d59dVXsdvtV6wIoBBCCCGuXZKAXCXt2rVj1qxZvPHGG40dSoO8Xi+qqqIoCk899VRjh1NPly5d+P3vf88dd9yB2+3m3Xff5bnnnkNRFKZPn86AAQNITExk//797Nmzh/vuuw+3280777zDc889h16v5+uvv6Z79+6kpqZy5MgRNm7cyIMPPojX6+Wdd97h2WefxWg08t1339G2bVs6dOhAeno6y5cv59FHHwXg3Xff5emnn8ZsNvPDDz/QokULunTpQkZGBvPnz+fxxx8H4L333uPJJ5/EZrOxaNEiwsPD6dWrF9nZ2Xz77bc8+eSTALz//vs89thj+Pr6smzZMnx8fOjfvz/5+flMmzaNP/3pTwB88MEHPPjggwQGBrJq1SoAhg4dSlFREZ9++il//vOfAcjOziY0NBSj0fiL99TpdGIymTCbzaiqyrFjx7jpppvIz8/H6XSyZ88eVq1aRWpqKp07d6ZNmzZUVFSwYMECDhw4gMViITAwkBEjRuDr68ugQYNYs2YNx44do02bNkDN39VPP/2EyWRi9uzZmEwmjh49Snl5OaGhofj4+GC1WgkNDb2Sfy5CCCGEuIYp6sWWujnPpEmTUFWViRMnEhwc/GvHddkmT55MRUUFY8eOJTk5ubHD+c2ZO3cuu3fvpmXLlowdO7axw2nQsWPHWLJkCRMnTmzsUK4L69at429/+xvt2rXjhRdewOFwUFxcjMvlIjY2loMHD/LPf/6TxMRERo8eTXJyMuvXr+eFF17ghRdeICQkhGHDhrFnzx4cDgfz589n6dKlJCUl0bVrVx599FFmzZrFkiVL+Omnn3jwwQe1Cun+/v64XC42b97MoUOH+PDDDxv5bgghhBDiapHB1kKjqupFl15tbC1atOD3v/99Y4dx3UhLS6Nt27bs37+fmTNnoqoqAQEB2O12rc2AAQM4cuQIJ06cIC8vj+PHj1NWVkaXLl2A/7/nrLKyko0bN+J0OomPj9c+r9frueWWWzh48CCJiYnccMMNdOzYEX9/f3Q6Hf7+/uTk5Fz1axdCCCFE45EhWOI3Q1EUmSNwBZlMJiZMmMDs2bOZNm0a77zzDgEBARQWFjJw4EB8fX3p378/hw8f5vXXX6ekpITo6GgmTJigDfHKy8tjwIABVFRUYLfbefDBB+nduzeHDx9GURQURSEiIoLx48fz5z//meLiYgoLC+nbty933303qampvPPOO3Tr1o1bbrmFp556CoNB/m9JCCGEuJ7Jv/RCNFGKotCsWTMeeOABRowYQWlpKVVVVfj5+eHn50dAQAAADz/8MKNHj8blcuHr60tYWBg6nY5mzZqxevVq3G43ZWVlBAYGEhsbi6+vL6mpqXz55ZdERkai0+l44IEHGD16NAUFBej1ekJDQwkLC0NRFKZOnUpxcTFxcXGSYAohhBBNgCQgQjRhJpOJ8PBwwsLC8Hg8OJ1ObQWr2pW0oqKitCV69Xq9tt9qtZKWlobb7cblcmEymbQEwsfHh9atW2vnCQ8PJzw8nOrqavR6fZ3jtGnTRpsQL4QQQojrnyQgQggURcFgMFxw+NPFhkVd7HM/ZzabGzx3Q/uFEEIIcX2SSehCCCGEEEKIq0YSECGEEEIIIcRVI0OwhGiCVFXF6XRecNllk8mkrWLV0GdVVaWqqkqbM/LzeR1CCCGEEBciCYgQTZDb7WbJkiXk5eXVSUJqk44bb7yRkJCQBj+rqiqFhYV8+OGHrFq1igkTJtCyZUtiY2Pr1BARQgghhGiIJCBCNEEej4eDBw9y+vRpsrOzOXXqFIqi0KVLFxRFoV+/fgQHBzfYo1FSUsKMGTNYu3YtL774IgD33nsv//znPxk0aNDVvhQhhBBC/MZIAiJEE2Q2m/nTn/6Eqqps3ryZxYsXoygKL7zwAlCzstXgwYN59913SUhI4OTJk6xatYrc3FzatWvHP/7xDwwGA4888ggtW7bk+PHjPProoyQmJjJmzBgefPDBRr5CIYQQQlyrJAERoglSFEWrZm4wGLT5G+fX4jh8+DCVlZWoqkplZSU5OTmUlZWRnJzMDTfcQEJCAuPGjaOoqIgjR47w+9//nhtuuIGgoKDGuiwhhBBC/AZIAiIAiI2NZfny5bz44ot88MEHjR1OPSkpKdxyyy0MHjwYp9PJV199xX333YeiKMyZM4fOnTsTExPDkSNHOHbsGMOHD8ftdjNt2jTuu+8+dDod8+bNo02bNsTHx5Oens7evXsZNWoUXq+XL774gnvuuQeDwcCiRYtISEggKSmJM2fOsG3bNm6++WZUVeWLL77gzjvvxGQysXTpUqKjo0lJSSErK4t169Zx2223oaoqX375JXfccQcWi4WVK1cSGBhIu3btyM3NZfny5YwdOxaAL7/8kltvvRW73c7atWuxWq107tyZwsJCFi9ezJ133gnA9OnTGTVqFL6+vmzatAmAbt26UVJSwrx587j77rsByM3NJSAg4JLrclyMy+XS5oeoqorX6wXAZrMREBBAeHg4rVq14syZM1itVuLi4khISJBq5kIIIYS4KElABADNmzfn9ttvp02bNo0dSoNCQ0Px8fFhxYoV9OnTp06cSUlJ+Pr6AhAYGEiLFi0A0Ol0tG3bVpvHkJiYiJ+fHwB+fn4kJiYCNb0Bbdu2RaerWZW6RYsWBAYGAuDr60tSUpJ2rjZt2mgP2PHx8drxfHx8SE5OrtOuNgmIi4vTqovbbDZSUlLqtKvtiYiJidG2LRYLqampWrvWrVtrxfoiIyO1/WazuU7FcZvNpl3HlVC74tX5FEVBr9djMBgwmUwYDAatkKFUMxdCCCHEL5EERADg7+9P79696d27d2OHckF5eXkcOnQIvV5Pp06dtP3nP6gHBwcTHBwM1CQg57dr1aqVth0YGKglGYqi1GnXsmVLbdvPz09LMn7erjaBAXA4HFpSpCgKHTt21N5r3ry5tm2322nbtq32ukOHDtp2s2bNtG2r1Uq7du201+3bt9e2Y2NjtW2z2VznvSu5CpW/vz8lJSW4XC5KSkooKSlpsGfFYrHg8Xhwu914vd4rmgAJIYQQ4vojCYj4zQgODqZXr16NHUaT0b59ezZu3EhxcTFHjhzhzJkzxMfH12vn5+dHYGAg+/fvx2azERsb22A7IYQQQgiQBESIJs9qtRISElJvyd077riDDz/8kHnz5hEUFERgYCAhISEYDAYiIiIICAjQPj9s2DBWrlzJhg0bGDVqlCQgQgghhLggRb1QKeSfmTRpEqqqMnHiRG2Iy7Vk8uTJVFRUMHbs2Dpj8YUQ/7mKigq8Xi9ms1mbn3KxtoA2L0QIIYQQoiHylCCEuCCbzfartBVCCCFE0yWzRYUQQgghhBBXjSQgQgghhBBCiKtGEhAhhBBCCCHEVSNzQIRo4oqKijh16hQnT56kurqauLg4OnXqhF6vr7cy1i9ZuXIlJSUl9O7dG5fLxY4dOxg2bNh/HaPb7SY3N5c9e/bUe09RFGJiYmjVqhVut5vs7Gz2799Pt27dcDgcUpdECCGEuMZIAiJEE7Z3717WrVvHyZMn8fHxwePxsGXLFo4cOcK4ceMuezWrPXv2kJ2dTYcOHaioqGDz5s1XJAHxeDzk5eWxceNGAA4dOoSvry/BwcFYLBbcbjetWrWisrKSH374gXnz5vGHP/yBQYMGSXV2IYQQ4hojCYgQTVRBQQGLFy/m6NGjtGjRgpYtW6IoCidPnsTlcrFlyxbsdjstWrTAx8eHnJwcMjIysFqtJCUlcfToUXbu3El1dTVBQUF07dqV4uJi8vPzcblcVFVVcfz4cVRV5cSJE5w4cYKKigrKy8vx8/OjZcuWJCQk4Ha7OXDgALt27cLtduNwOGjZsiXNmjXD19cXqKlqX7sfYPHixbRq1YqoqCiCgoIIDQ1FVVVKSkqYPXs2LpeL+fPn06dPH0lAhBBCiGuMJCBCNFHHjx9n27ZttGnThscffxy73Q6Aqqq4XC7effddcnJyeOihh2jRogX79u1j6dKldOzYkdjYWKZPn86OHTuAmmro0dHRdY7vdrs5deoUAJs3b+brr7/GbrdTWVmJyWSiX79+xMTEUFBQwGeffcbu3buxWCwUFRVx2223cdNNN2kJiNFopFmzZjRr1gyA2bNn07lzZ2666SaioqIAqK6u5uzZs5w+fZp//vOfvPjiixQXF2O1WtHr9VfjlgohhBDiElxXCUhJSQkZGRnX5Deevr6++Pr6YjKZcDqdVFVV4evri6qqFBUV4e/vj6IolJaWYjKZMJvNuFwuKisrG2xXVlaGwWDAYrHgcrmoqKjAz89Pa+fn54dOp6vTzu12a98+Q83Yf19fX3Q6HeXl5eh0OqxWKx6Ph9LSUvz9/bV2DocDvV6vFZuz2WwXbVdZWYnX68Vut+P1eikpKdHaFRcXY7fbMRgMVFVV4Xa78fHxwev1UlxcrF1jcXExNpsNo9FYp93P70VJSQlWqxWj0Uh1dTVOpxOHw9FgO4vFcl3/Dtxu9yXP3Th16hQOh4OYmBgt+YCaORUmk4lu3brxxz/+kWHDhhEWFsbBgwc5fPgw48eP5+zZs3z22WdMnTqV9u3bs3jxYi0GqEliqqqqOHv2LABlZWVkZ2fz9NNP07p1a6ZPn87GjRsZOnQoBw8eZNasWXz11Ve0b9+eCRMm4HK5cLlcl/XfWEFBAZs3b6Zdu3aMHDmSZ555hgMHDuDv71/n+oQQQgjRuK6r2ZmzZs1i1KhRtGnT5pr7efHFFzl06BAej4djx47x3XffAeD1evnggw9wu90AzJ07l4MHDwJw8uRJvv76a+36PvzwQ5xOJwALFixg7969AJw9e5bp06dr7T766COqqqoAWLp0Kdu3bwcgJyeHqVOn1mlXXl4OwIoVK9i0aRMA+fn5fP7551q7Tz/9lJKSEgDWrl3L2rVrgZqE79NPP9Xaff755+Tn5wOwadMmVqxYAUB5eTkfffSR1m7q1Knk5OQAsH37dpYuXQpAVVVVnXbTp0/XHmD37t3LggULAHA6nXz44YeoqgrA119/zcmTJwE4ePAgc+fOBWoexj/44AO8Xi8A3333HceOHQO4bn8HOTk52nX8EqfTiaIo6PV67V6er0ePHtjtdvbs2cOyZcvIysoiMTGRsLAwVq9eTceOHRk4cCChoaHcd999xMfHX/R87dq1o2vXrqSmptKiRQusViv79u1j9+7ddOvWjb59+xIQEEBQUNBlzz1RVZWcnByWL19Ot27dyMrKomfPnixatIiioqIGr08IIYQQjUNRL/Ff5kmTJqGqKhMnTiQ4OPjXjuuyTZ48mYqKCsaOHUtycnJjh9Og7777juDgYPr27dvYoQjB2rVrefvtt+nSpQt/+tOfGlwt6v3332f79u3k5ubSokULRo8eTdu2bXnnnXc4evQo06dPr9Pb8o9//IOMjAz+/Oc/k52dzf3338/Ro0f55JNP2LJlC3/9619p1qwZn332GVu2bGHEiBEcO3aM7du3M23aNAD+8Ic/0KxZM2688UZtzsfPjRkzhr59+3LzzTcTFRVFZWUlS5cu5c4778ThcAA1iaXJZGLx4sW0bt36slf0EkIIIcSv47rqAbnW3XLLLfTp06exwxACgM6dOxMaGsrq1auZOXMmqqridrvZunUrr732Gm63m1tvvZX09HTWr1+P1WqlZ8+emM1mWrduzYoVKzh16hSqqrJ582at9+tyOBwOunfvzsqVK1mxYgUbN25kx44dWq/QpTp+/Dh79uzh7rvvJiMjg4yMDDIzMwkKCmLbtm3k5uZedmxCCCGE+HVcV3NArnVSj0BcSywWC48//jgzZ87k9ddf54UXXkCv1+P1ennqqacACA0NpX379sTExNClSxeMRiNGo5EhQ4YwYsQIunXrRkREBDqdjrfffhtA62m4lB4Hi8VCamoqTz75JM899xwBAQFUVFTg4+NzWXO5jh8/zr59+xg7diwGg0EbcjVs2DC2bNlCu3btCA0NvdxbJIQQQohfgQzBEqIJczqdFBYWkp+fT2lpqbakbnh4OIGBgVRXV3P33XfTsWNH7rnnHmJiYoCa4U1ZWVlkZ2drS+fGxsZSXl6Oy+UiJCQEt9vNmTNnaNmyJQUFBVRWVhIaGorJZNJeBwQEYDKZOHz4MEajkcrKSh5//HGef/55evfufcHJ46dOncJut+Pn54fRaKS4uJiioiICAgK0lbMALb7AwEBsNttVuadCCCGEuDjpARGiCTOZTISFhRESEoLH48Hj8WA2m4GaHox169ZhNBpJSEggLCxM+5xOpyMyMpLw8HA8Hg9GoxFFUfDx8dHamM1m7cuAoKCgOucNDAzUtouLi3nppZfQ6XQEBATQsWNHmjdvjtVqvWDccXFxdV77+flpK4udLzw8/DLuhhBCCCGuBklAhBDodDp0Oh1Go7HO/rCwMMaNG0dqamq9IVG1K2j9tzU2jEYj3bt3p6KiguDgYJKTk7VhXUIIIYS4/kgCIoS4oNatW9O6detf9Rw2m42JEyfidDoxmUyyWpUQQghxnZMERAhxQVcrGVAURRv6JYQQQojrmyQgQjRhqqri8XhwuVy43W50Oh0mk0krBOj1etHpdNIrIYQQQogrRhIQIZooVVWprq7m1KlT7Nq1i/T0dAICAkhLS6NDhw643W4yMjIICwuTFaSEEEIIccXILE8hmqji4mKeeuopHnjgAZYuXUp5eTnr1q3jlltuwel0kpGRwa233srOnTtRVVWrrVG7fbF9F/oRQgghhJAeECGaqP3795OVlcWNN97In//8Z22/1+vFaDTy4osvcvz4ce69914SExMZN24cAwcO5JtvvuGjjz5Cr9dzzz338OSTT7Jq1SoWLlzIkSNHyMrKQqfTMWLECKqrq5k5cyapqan861//olWrVjLXQwghhGjiJAERoolq27YtgYGBzJw5k8OHD9O9e3fatWtH9+7dAfjd737H5s2bef755+nSpQsOh4O9e/cyd+5cPvzwQwIDA3nooYcYOHAgeXl5HD9+nHbt2vHkk09y9OhRXnnlFe69915++OEH3nnnHRYvXkxERESdeiJCCCGEaHquqyFYs2fP5vbbb6dr167X3M8rr7zC8ePHATh+/Dhz5swBar5t/uSTT3C73QDMnz+fQ4cOAXD69Gm+/fZboGaIy6efforT6QRgyZIl7Nu3D4CzZ88yc+ZMrd2UKVOoqqoC4KeffmLnzp0A5OTkMGPGDO1+ffbZZ5SXlwOwevVqtmzZAkBBQQHTpk3T2k2dOpWSkhIANmzYwIYNGwAoKSlh6tSpWrtp06ZRUFAAwJYtW1i9ejUA5eXlfPbZZ1q7GTNmkJOTA8DOnTv56aefAKiqqmLKlCnaUJ2ZM2dy9uxZAPbt28eSJUuAmurdn376qdbu22+/5fTp0wAcOnSI+fPnA+B2u/nkk0/wer0AzJkz57r/HeTk5GjX8UvsdjtPP/00TzzxBD4+PixevJgnnniCRx55BK/XS3h4OGazmZiYGOLj46moqGDPnj0UFRWxfPly5syZQ1lZGevXr6esrIyYmBg6d+5Mr169aNu2Lf7+/owaNYrWrVuTlpbG8ePHqaysvKTYhBBCCHH9uq56QNq0aUPHjh2JiIho7FDqSUhI4Pjx4zidTiIiIrTaCoqi0LVrV63oWkpKCgEBAQD4+/vTrl077Rhdu3bVir61bNkSh8MBgK+vL+3bt9fadenSRVvFKDExUaso7ePjQ8eOHeu0qy0u17x5c60Inc1mo1OnTlq7tLQ0bdjM+RWozWYzaWlp2utOnTppk5VjY2NxuVxATbXtLl26aO06duyoVcyOiorSqmIbDIY67dq3b4+vry9QU9HabrcDoNfr6dq1q9auXbt2+Pv7AxAaGqpdh06no2vXrtoKTq1bt9YqcgcFBV2XvwMfH59LLuCn0+lITEwkICCADh06kJuby9GjR3n99dc5evQoBoMBRVEwGAwYjUYqKiq0RKNZs2YA3HPPPaSkpJCRkYHVasXhcOBwOLDZbFitVkJCQjCZTPj5+VFVVaUlg0IIIYRouhT1EmeGTpo0CVVVmThxIsHBwb92XJdt8uTJVFRUMHbsWJKTkxs7nAbt378fm81GfHx8Y4ciBCdPnqS4uJigoCAiIyNxuVzs27ePvn37smrVKiIjIxk6dCjvvPMOvXv3JiMjgwULFrBkyRJeeuklbDYbZWVlmEwmtm3bxvbt2xkyZAjDhg1jy5YtPPbYY3z99dckJCQwY8YMFi9ezD/+8Q+aN2/e2JcuhBBCiEZ0XfWAXOtSU1MbOwQhNBkZGWzYsAGDwaD1aBw+fJjk5GTCwsLw8/MjJCSEbdu24XQ6iYqKolWrVqxcuZJjx45hs9nIzs6mRYsWeDyei55L6ogIIYQQopYkIEI0UUFBQRQVFbFx40YqKysxm80YDAaeeuopoqKiUBSFkSNHsmbNGrZt28bNN99Mr169GDhwIN999x1FRUWUlJTw/PPP4+fnR1RUlDZkzmaz0bJlS23YWEBAAHFxcdpwMyGEEEI0XTIES4gmrrq6moqKCjweD4GBgfXmkFRUVKAoCkajsU6F9Pz8fK299HAIIYQQ4lJJD4gQTZzZbL5obY6GqqDrdDpCQkJ+zbCEEEIIcZ26rpbhFUIIIYQQQlzbJAERQgghhBBCXDWSgAghhBBCCCGuGklAhGiiXC4XO3bsYPPmzZw7dw6oqeLucrlYuHAhhw4d0opJ/jdUVeWf//wnZ86cIS8vj5kzZ7JmzZr/+rhCCCGE+G2SBESIJqq6upq5c+fy5ptv8uOPPwLgdrvZuHEjkydPZvXq1VRVVV2Rc82bN4+CggJKS0vZtGkThw8fviLHFUIIIcRvj6yCJUQT5Xa7OXLkCOvXryc4OJgBAwbg6+vLzJkzSU9P59SpU7jd7nqfq66u5vDhw2zfvp2qqirCw8MZOHAgLpeL/fv3c/z4cRRFoUWLFnTq1AmLxUJWVhZOpxO3260lItXV1WRmZrJx40aKioqw2+3079+fyMhIbblfIYQQQlx/5F95IZowk8lESEgIXq+Xn376iS5durBt2zY6duxYrx4I1NT/KCgoYNq0aRw5cgS9Xo/dbqdr167s37+fZcuWcfLkSYxGI+Hh4fj5+dG6desGz52Tk8NPP/3E3Llzsdls6HQ64uLiCA0NlQRECCGEuI5dN//KW61WsrKyOHHiBJdYW/Gq8vf3JzAwELPZrBV+CwgIQFVV8vLyCA4ORlEUioqKsFgsWCwWqqurKS8vJzAwUGsXFBSETqejuLgYk8mE1WrF6XRSVlamtTu/QFxJSQkGgwGbzYbL5aKkpISgoCAA8vLyCAgIQK/XU1paik6nw26343a7KS4ubrBdWVkZAD4+Png8HgoLC7XClPn5+fj5+WEwGCgvL8fr9eJwOBps5+vri9FopKKiArfbja+vr/ZwGxQUhKIoFBQU4OPjg8lkorKyEqfTiZ+fn1YEr/aeFRQUYLfbMZvNVFVVUVVVhb+/f717W1hYiM1mu65/By6XC4PBcFmFAdu3b09iYiIzZswgPz+fdu3aYbFYGjyG0+kkPT2d77//nk8++YR27doxZ84cjEYj8+bNQ1VV7r//fsxmM1988QWLFy++YAJy5swZVq9eTWpqKk899RQnTpzQEhEhhBBCXL+um3/p09LSWLFiBXfeeSfdu3e/5n7+9a9/cfjwYdxuN8ePH+eHH34Aar5RnjJlijbUZcGCBdr4+DNnzjB79mztGj/77DNtUvCPP/7I/v37AcjKymLWrFl12tWO3V++fDm7du0CIDc3l6+++kpr9/nnn1NRUQHAmjVr2Lp1KwCFhYVMmzZNa/fll19SUlICwIYNG9iwYQMAJSUlfPnll1q7adOmUVhYCMDWrVu1icYVFRV8/vnnWruvvvqK3NxcAHbt2sXy5csBqKqq4rPPPtPazZo1i6ysLAD279+vzVNwuVx89tlnWqI5e/Zszpw5A8Dhw4dZsGABUDPEaMqUKXi9XgB++OEHjh8/DnDd/g5yc3MbHDZ1Mc2aNaN169ZkZmby/vvv8+ijj14wgcnPz2fHjh107NiR/v37ExQUxIMPPojH4+HEiRPs27ePRYsW8dVXX5GXl8e2bdsueF4fHx8CAgJYtWoV06ZNw2QykZKSgtFovKz4hRBCCPHboqiX2F0wadIkVFVl4sSJ2ret4vLMnj2boKAg+vbt29ihCEFRURF/+MMfSExM5N5772X+/Pls3ryZqVOn8sc//hE/Pz+eeuopAgICtM8cO3aMqVOncvbsWaZMmaLtP3r0KM899xzx8fEMHToUqKmW7ufnR8eOHWnWrBnfffcd/v7+/OMf/6B9+/Y8+eST5OTkMHv2bFasWMGSJUuYOnUqI0aMaLD6uhBCCCGuD9dND8hvwS233EKfPn0aOwwh6omNjWXChAl1elMa4uvrS7NmzVi5ciWnT58GanpuoqKiCA8Px263ExcXR79+/ejUqZPWu9OQc+fOcezYMR566CFmzZrFPffcw8aNG6murr6i1yaEEEKIa8t1Mwfkt+ByxuULcbUoinLJf5vBwcEMGzaM9evX06FDB6KiotDpdMyZM4d77rmHuXPn8sgjj5Cfn09lZSV33303vXr10s5x/nnOnDnDO++8w9atWwkPD0en0/HRRx/h4+Pza12qEEIIIa4BMgRLiCbK4/GQk5ODyWTSJrtDTeHA3NxcdDqdNvH9fG63m7y8PHJzc3G5XPj7+xMdHY3X66W0tJTi4mIqKiowmUwEBwcTFBREeno6kZGR6HQ68vPzMZvNWK1W8vLytHlDfn5+REREYDQaJVkXQgghrmPSAyJEE6XX64mIiKi3X1EUQkNDL/g5g8FAWFgYISEheDyeOgmDxWIhKCgIj8eDXq/XVrRq3ry59vnzzxkdHU1ERASqql726l1CCCGE+G2SBEQIcdkURUGv19frHYGayeeXupSuoihS80MIIYRoYmQSuhBCCCGEEOKqkQRECCGEEEIIcdXI2Achmiin04nX68VgMGAwGPB6vTidTgDMZjOKomhL4hoMBtxuNy6XC6PRiNlsRlVVXC6XVujR4/Fo2+fT6/UYjUaqq6s5f80LvV6PxWIBoLy8vM5+s9mMTqf7j+aEqKqKx+OhoqICj8eD2WzGZDKh1+tljokQQghxDZAERIgm6tChQ5SUlBATE0NcXBzl5eVs3rwZi8VCz549Adi+fTsmk4no6GjOnj3Lnj17SEhI0N4/fPgwxcXF6PV6Tp8+TUlJCaqq4vV6tQf+6OhoEhMTWb16NR6PRzt/TEwMPXr0wOPxMHPmTIxGIzqdjuDgYDp16kRoaGidqui1x21oSd/zqarKqVOn+PHHH8nLy6NNmzZ06tRJW2FLCCGEEI1LEhAhmqhjx46xaNEievXqxX333UdmZiZPP/00YWFhLFmyBFVVmTx5MoMGDcJqtbJkyRL+/ve/07ZtW5YtW4a/vz/Lly/nxIkTdO7cmWPHjpGXl8ehQ4c4ePAgAwcOxNfXl6qqKkpKSnj11Vfp2LEj/v7+ALhcLjp06EBBQQETJ07kiSeewOVysX37dkJDQ/nDH/5A//79tXg9Hg9btmwhJiaGqKioCyYgbreb6dOnc/r0aWJiYnjvvfcICQnhvvvuY9iwYVfj1gohhBDiIiQBEaKJSktLY+bMmaSnp2tJQnV1Nfv378fpdOJ0Ojlw4ACPPPIIERERmEwmYmNjSUlJ4a233uLvf/+7dqxBgwZx9913o6oqX375JZ999hkvvfSSlih8//33JCUl8b//+78kJCQANStgeTweCgoK0Ol0vPrqqyiKwsKFC/niiy8oKyurE6/T6eTTTz/lpptu0goXNsRoNPK3v/0NVVVRFIVNmzbx0ksvcejQIUlAhBBCiGuAJCBCNFGRkZGEhYVRXFzM1q1byczMpEePHmRmZrJz507KysqIj48nJCREG7rUvHlzxo4dy4QJE3jkkUe0YymKoiUEtT0TOp0OvV6vzfvYsWMHt99+O5GRkQwcOJBRo0YRHx8P1PRuPPjgg1RXV7Nx40bGjx9PSkpKvZhVVeWXaqf+fHjW+vXr8fHxITIy8r+4W0IIIYS4UiQBEZetqqqKHTt28Oqrr3L8+PHGDqeegIAAbrjhBvr160e/fv34+OOPueeee7DZbNrQobS0NHJzc1m4cCH3338/AJ988gljx47F4XCwatUqTCYTPXr0oLCwkDlz5jB+/HgApkyZwq233oq/vz/r1q3D4/HQp08fSkpKmDVrFg899BAAn3/+OSNHjiQ4OJjNmzdTWlrKwIEDqaioYPr06Tz00EMoisKXX37J4MGDCQ8PZ+fOnWRnZzNs2DCqqqqYOnUqjzzyCIqi8NVXX3HDDTcQHR3Nvn37SE9PZ+TIkTidTqZMmcIjjzxyyfU3oGayd1JSEunp6WzcuBGn00m3bt04c+YMmzZtoqSkhNTUVPz8/LQHervdTmpqKj169OD999+vU0H9Ytq3b8/bb7+N0Wjk0KFDrF+/nqysLF588UWgJmno3bs3Xq+XuLg4li5dSkhICE6nk927dzNjxgw8Hg979+5l7969fPzxx5jNZv72t7/RoUOHC5538eLFzJ8/n1tuuYUePXpc8r0RQgghxK9HEhBx2aqqqsjKyqKgoIBJkyY1djj1mM1mHA4HO3fupF+/fvTp0weTyQRASkoKZrMZAIfDoU2mBrjhhhu0VZlatmypFdmz2Wz06tVLa9e7d2+sVisAiYmJ2jfyFouFG264QWvXq1cvfHx8gJqeA5fLBYDJZKJPnz7aQ32PHj3w9fUFIDY2lpCQEKBmKFHfvn2143Xt2pWAgAAAoqKitM8YDAb69ev3H63wlJSUpCUcfn5+jBw5kvDwcL766itKSkq49dZb8fPz09rrdDpCQkK45557eOqppxgxYkSDK1/9XHR0NMHBwSiKQps2bcjKyuLUqVPk5eVpxx06dCgAFRUV5ObmkpGRQV5eHu3atcNgMFBdXc2UKVNIS0ujY8eOGI3GC/ZqqKrKpk2b+Pe//82gQYMYNGgQYWFhl31/hBBCCHHlSQIiLpvH48HlcmGz2bj55psbO5wGVVVVacu4Jicna/ujoqK0bYvFQmJiova6ZcuW2nZERIS2bTabSUpK0l6fv33+Q63JZKpzjPOPXZtUQE3CcH672jkRQJ0eBb1eXyf2Fi1aaNsBAQFaMqLT6eq0uxwJCQmsXr2a/fv3k5qaSvPmzfH392fPnj1UVFTw/PPP43A46qxeZbFY6NSpEzExMaxYsYK0tLRfPM+5c+cIDQ3FbDZTXV2tJXfnV0GPiIhAURQKCwtRVRWn04nJZCIhIYHY2FgqKyv58ccf6dSpE0OGDMFgMGgJ4/k8Hg87d+7kk08+ISUlhdGjR9O8eXMtCRVCCCFE45IERFyXzl9KVlxYZGQkDocDt9uNv78/DocDi8WC2+0GahI2s9lMRUWF9hmdToe/vz/33HMPDz30EB07dvzF82zatIny8nJ8fX3JzMwkLy+PlJQU/Pz8KC4uRlVVZs6ciaqqFBUVUVJSQseOHYmKisJkMmEymdDpdPj4+Gg/5ycv5/N4PMyePZt58+YxYcIEduzYwb59+2jevDnJycnaKlxCiEunejwo/++LAyH3Q4j/liQgQjRhVquVlJQUhg4dSseOHVEUBb1ez7Bhw/B4PDgcDnQ6HTqdjsjISK3nxmAwMGrUKKZPn06LFi3q1NcICQmhdevWdXocCgoKmD17NmazGbfbTZcuXbjpppswm81YrVbS0tKYMmUKHo9HG/I2YMAAYmJitGPo9Xpat25NaGjoRYebqapKfn4+LVu2ZM2aNaxduxaAoUOHEhYWJgmIEP8BRa8n98kncR071tihNDpjQgIhb73V2GEI8ZumqL+0pMz/M2nSJFRVZeLEiQQHB//acYlrWH5+PsuWLeOLL75g8eLFjR2O+I2oqKiguLgYh8OBzWa7rAnzQojGd/bGG3Hu39/YYTQ6U2oqkQsWNHYYQvymSQ/INcrr9V7SkqONwePxXNLEYyHOZ7PZsNlsjR2GEEIIIRqZJCDXIFVVOXr0KOvXr+f06dONHU49lZWVnDp1CqfT2dihCCGEEEKI3xgZA3ENysrK4ttvv+Wzzz5r7FAuKDAwUCZ5CyGEEEKIyyY9INcgVVUxGAykpKTwpz/9qbHDqaewsJBVq1bx3XffNXYoQgghhBDiN0YSkGuY0WjE4XA0dhj11NZnqC2sJ36bjh8/TmVlJSEhIYSFhVFRUcHhw4cxmUykpKSgKAoHDhxAr9cTEhJCfn4+6enpREVFkZqaiqqqnDx5krKyMnQ6HdnZ2ZSXl9c5h6IohISEEBsby+7du+v8zYSFhdG6dWtUVWXFihVAzUpXgYGBtGrVCl9f3/96ovr+/fuxWq2Eh4fL/BMhhBDiGiEJiBBN1IkTJ9i+fTvt27dn6NCh5OXl8e9//5uAgAAmT54MwIwZM2jbti2dOnViw4YNfPbZZ6SkpPDaa69hs9nYsmULmZmZNG/enOPHj1NYWMjZs2c5e/YsrVu3xmq1kpCQQHl5OVOmTCEuLk5LBJKSkmjRogVlZWW88sorDBkyBK/XS3Z2Ns2aNWPUqFGkpqZq8Xo8Hk6cOEFgYCCBgYEXXIpXVVVKS0tZtWoVs2bNYtiwYQwcOFASECGEEOIaIXNAhGiiHA4H+/fv5+DBg7hcLgoLC9m8eTPLly/H4/FQXV3NqlWrcLvdmEwmsrOzOXDgACdPntRqa2RlZXHy5EmCg4Np3749Xbt2xdfXl9OnT5OamkqXLl1o2bIlBQUFZGdnk5SURJcuXejSpQtJSUmYTCYqKyvZsmULXbp0IS0tDT8/P7Zu3cqZM2fqxOt2u1m6dCknTpz4xVXYauuZHD9+nHPnzlFdXf2r3UchhBBCXB7pARGiiUpMTERRFHJycjh37hz5+fkEBASQn59PXl4elZWVVFRUEBERga+vL3q9nqioKNLS0pgxYwY33HCDdqyEhATCw8OBmjox27dvZ9CgQURHR6OqKhkZGSiKgtFoxMfHh/DwcKKjo7FardoxAgICtEKEgYGBdd6Dmh6Qbdu2ER0dTfv27dFfpAqx1Wrl/2PvvuOjKtPG/3/O9JIy6T2BkISQQOgdlBqqiI1iL6joIlj3cXfdZxd/7lp2LTxr74IKilgAqYIKSGiBUEIChEBIQnqbTDJ9zu+PbM6XGFAQNWju9+vFyzMzd8655p4I55q7XEOHDiU+Pr5NkURBEARBEDqeSECEC6ZSqVCr1bhcLnJycjo6nHY0Gg0BAQEEBAQQGBhIRUUFYWFhqNVq6uvr0Wg0+Pn5Kd/6h4eHA1BeXq60a2hoQJIkAgIC8Hg81NTUEBERAUBFRQUhISFoNBqsViuyLBMYGIjX66W6ulppV1lZSVBQEFqtlsbGRrxeLxaLBa/XS1VVlXLDXllZicViQafTYbPZcLvdBAUF4fP5qKysJCIiAkmSqKqqIiAgAL1eT1NTE06nk+Dg4HbtzldISAhRUVHY7Xb27t1LVVUVgwYNori4mJycHBobG0lMTCQ4OBiNpuWvipiYGCZOnMgdd9zB4cOHz/taZrMZn8/H+++/j9lspmfPnkycOJGhQ4cCLXVv3nrrLVwuF9nZ2UyePJmAgACam5tpampSEqL6+npKSkrIz89Hq9USGxuLn59fm2tJkoRGoyE4OBiDwXBBfSIIwrlpk5I6OoRLgugHQbh4IgERLpjBYCA0NBSn08n48eM7Opx2QkJCGDduHKNGjeKaa67hgw8+YO7cuZjNZrZu3apsIVxTU8OKFSv4wx/+AMDSpUu54447CAgIICsrC71ez+jRo2loaOCjjz5i/vz5ACxbtoybbrqJ4OBgdu/ejdfrJTMzE5vNxocffsgDDzwAwMcff8yMGTMIDw8nJyeHhoYGpk6dit1u54MPPuDBBx9EkiRWrFjBtGnTiImJITc3l9OnT3PVVVfhdDp5//33lZ3QPv/8czIzM0lISODIkSMUFBQwY8YMPB4PS5Ys4aGHHrrgm+3u3buTm5vL9u3bkSSJwYMHExUVRVZWFo2NjfTs2ZPAwEClvcFgICkpicmTJ/Of//yHXr16ndd1+vXrxyuvvIJGo2Hfvn0sXbqUkpIS+vXrB7QktdOnT0eWZYYOHcqbb76pjIjk5OTw2muv4fP5KCoq4uDBg7zzzjsYDAaeffZZBg8efEHvWRCECyd7vYS98EJHh3HJkL1epB8YhRUE4YdJ8nmW2l64cCGyLDNv3jxCQ0N/6bg6tdLSUpYsWUJxcTEvvfRSR4fzm9TQ0MDLL7/Mn/70p44O5ZKWlZXF559/znfffUdERASLFi2iuLiYv/71r1itVh599FFGjx6NVqvl1VdfJSsri48++oiTJ08ycOBAZsyYgUaj4a9//asyovPuu+/y1ltvsXTpUmJjY4GWheFn+uc//8mePXt46qmn8Pl8ZGRk4HK5kCQJWZb561//isvlYsKECQwePBibzYbdbudPf/oTEydOZNy4cWi1WiwWC3q9/pzv7+abb2bgwIFMmzaNhISEX64jBUEQBEE4b2IRuvC7FBAQwKOPPtrRYVzy0tLS0Gq15Obm4vF4iImJoW/fvuTk5JCXl0evXr3ajIBAy1a5sbGxzJ07lzfffBOXy/WD15Blme3bt1NXV4fP5yM/P5+ioiIMBoOStJypqKiInJwcZFkmLCwMs9lMREQEERERGI1GgoKCiIiIIDw8HJ1O97P2hyAIgiAIvzyRgAi/S5Ikibn/5yEgIID4+Hh69epF7969gZb6M3379mXgwIH4+fkp/djap5IkodPpeOCBB7BYLOfVz2vXrqVXr16kpaUxYcIEGhsbmTNnjrI1rsfjISoqitDQUC6//HIiIyO59tpr6dmzZ5vrtiYkZz73fT6fj8OHD9O7d29WrlzJP//5T2688UY++uijn7HnBKFzkb3ejg7hkiL6QxAujpiCdQkSU7CEX1NjYyNNTU0YDAYsFguyLFNZWQlAaGgoarUan8+HzWbD6XQSFhaGLMv4fD5Onz6NyWTCYrEou1LZbDZsNhuhoaFoNBpkWaa+vp7KykoaGxvx8/MjKCiIwMBA9Ho9Ho+H06dPt0l0TCYTfn5+baZX+Xw+GhoaMBgMP7i4XJZl3G43VVVVeL1eZVF6QEAAZrP5F+5NQfj9qrr/ftwFBR0dRofTJiWJ9TCCcJHEInRB6OT8/f3x9/dXHkuSpOzk1UqlUhEQENCmjVqtJi4urt35/Pz82uxMJUkSQUFByo5iarUatVqtJBBarfa81meoVCqCgoJ+tF3rCE1MTMyPthUE4fy5Cwpw5eZ2dBiCIPwOiAREEIRfRWviIQiCIAhC5ybWgAiCIAiCIAiC8KsRCYggCIIgCIIgCL8aMQVLEDoph8OBLMtoNBq0Wi0+nw+Hw4EkScoib7vdrizi9ng8OJ1OdDodRqMRWZZxuVz4fD4A3G63cnwmjUajVG/3eDzodDoMBgNarRZoWVze2NjYpr3BYGizTuRCyLKM3W5vtz2wXq9Hr9ejUl3c9y4ej4fGxkZUKlW7LYoB6uvrMZlMaDSai76WIAiCIPweiQREEDqpI0eOYLVaiY2NpWvXrthsNrKysjAajYwcORKA7Oxs9Ho9cXFxlJaWsn//frp168Zll12mnKO+vh6tVktRURFWqxWfz4fP50Oj0SBJErGxsSQlJfHNN99QWVlJQkICffv2JTExEb1ej9Vq5YMPPlCSg5CQEPr3709ERESbOh+yLOP1elGpVD+4zbLP52P37t3k5eW1SQB69uxJRkZGmwXyP0VdXR0ff/wxfn5+3HLLLe1eX758OaNGjSI+Pv4HiyQKgiAIQmclEhBB6KQKCwtZvXo1I0aMoEuXLpw+fZr/+Z//ISIignXr1iHLMv/617/IzMzEbDazfv16/v73v5ORkcHGjRuxWCxs3ryZwsJCBg4cyLFjx6ipqSEvL4+8vDzGjx9PQEAATqeT3bt3U1JSQkREBJ988gnLly9n2rRp3HLLLZSXl7NgwQIWLFiAx+MhOzubsLAw5s+fz5gxY5R4vV4vu3btIi4ujpiYmHMmIF6vl48//pjdu3fTp08fZaTFYrHQo0cPZFluU5n9zPN8//mzXcPhcJCfn4/FYmkz4tPaNi8vjz59+ohduARBEAThHEQCIgid1MCBA1m6dCknT57E4XBgtVpxOp3k5ubicrlwuVzk5eUxd+5cIiMj0el0xMfHk5aWxvPPP8/ChQuVc40bN44bb7wRgHfffZe3336bf/zjH8TGxra77oEDB3j55ZfZsWOHMoKgUql49tlnAfjyyy959913sdlsbX7O5XLx5ptvcuWVVxIZGfmD05skSWLSpEn88Y9/VIodAlRUVPDee+/x9NNPU1lZSWZmJi+//DKBgYG88cYbfPDBBxw9epSwsDCuuOIK/vnPf571/E6nk1WrVrFz507y8vIYM2YML774In5+fhw7dgy32y0KYQqCIAjCOYgERBA6qejoaCIjI2loaGDXrl2UlpYyYsQISkpK2Lt3L42NjXTt2pWwsDBlFKFbt25cf/313H333dx9993Kuc4cLfh+5fTv27dvH83NzfTq1Ut5zuv1csstt+BwOMjKyuLuu+8mPT293c+eZ91UZFnm008/JS8vD41GQ0pKClOmTKGmpoaPP/6YBQsWMGzYMB544AE+//xz+vTpw4cffsjVV1/NFVdcQXV1NSdOnDjn+d1uN5GRkdx5552Eh4fzt7/9jU2bNnHllVdy8uRJmpqazroeRhAEQRAEkYAIP4HD4WDPnj08+eSTFFyCVXGDgoIYPXo0Y8aMYdy4cbzyyivceuutmEwm1q9fT1BQEIMGDaKyspJVq1Zxxx13APDKK69w44034u/vz+bNm9HpdIwYMYLa2lo++eQT7rrrLgBee+01ZsyYQVBQEFu2bMHr9TJ69GisVisffvghc+fOBVC+rQ8LC2PHjh1YrVYyMzNpamrivffe45577kGSJN555x0mTpxIVFQU2dnZlJeXM2XKFBwOB2+99Rb33nsvkiSxZMkSRo0aRVxcHAcOHKCwsJDp06fjcrl4/fXXuffeey9o0bNKpSIlJYXCwkK2b9+O2+1myJAhnDp1iqysLBobG+nZsycWi0VJJEwmE2lpaVx22WW8+OKLhIeHX9Bn8/XXX/PFF1/QrVs3rrrqKuV5SZIYO3YsPp+PlJQU1q5dS3BwMJdffjn79u1j8eLF+Hw+Dh8+zL59+3jxxRfR6/UsXLiQ/v37n/VaCQkJXHbZZeh0OmUEp7i4GLfbzaxZszAYDEyfPp1NmzYxbNgwvF4vmzdvRqPR0LdvXyZMmIDNZmPevHkcO3YMgPnz55OamorJZKJXr15Km4yMDA4ePMi0adNE4iH8bmmTkjo6hEuC6AdBuHgiAREumMPhoKKigqamJhYtWtTR4bSj0+kwmUzs3LmTcePGkZmZqSxm7t27t3IcEBDQZo1BZmYmBoMBaFmw3Hoz7+fnx7hx45R248ePx2w2AyhrCgCMRiPjx49X2o0dO1apHp6cnIzH4wFadmOaMGGCclM/evRoLBYLAImJiURHRwMtFcInTJignO+yyy4jJCQEaLm5bj3WaDRMnDjxJ035SUlJ4dSpU+zYsQOLxcL06dOJjIxk8eLFWK1WZsyY0aYCukqlIiwsjFtuuYU//OEPXHHFFed9w71jxw5ee+01UlNTmTZtGvHx8W3OO3HiRGRZxuFwUFVVRWlpKTU1NQwcOBB/f3+cTievvfYagwcPZsCAAeh0urNWYoeWhKZ79+5MnjwZo9GIVqulqakJu92OVqslMDAQn89HeHg4VVVVBAQE8Oijj5Kdnc3u3bvZsmULvXv35pFHHuG6666jtrYWgIyMDNRqNSqVCoPBgJ+fH06nE7PZjMPhuOD+F4TfCtnrJeyFFzo6jEuG7PUiicKqgvCTiQREuGBerxe3243RaGTixIkdHc5ZOZ1OZbekpDO+rYqMjFSODQYDXbt2VR5369ZNOT7zm32dTkdiYqLy+MzjsLAw5Vir1bY5x5nnbk0WoCVhOLNdly5dlOOgoCDlWK1Wt4k9ISFBOQ4MDFS2gFWpVG3aXYjk5GS++eYbcnNz6dWrF127diUoKIgDBw7Q3NxMamoq/v7+eL1e5Wf0ej19+vQhKSmJjRs3MnTo0B+8hizL7Nq1izfeeIMuXbowdepUevXqhV6vV5IyaOlzSZKoqanB5XLhdrvR6/UkJiYSGxuL3W5n1apV9OnTh7Fjxyrb9Z6Ln58fkZGRyhoQo9GIxWLB6/VSXFxMZGQkhw8fJiUlBYfDQffu3QkPD6ekpIRvvvmG9evX88ADDzBy5Ejl/RuNRioqKtpdS5Kk854eJgi/ReJmuy3RH4JwcUQCIvwu6fV6Bg0a1NFhXPIiIyOVRCY4OBg/Pz9l61iNRkNUVBR6vZ7m5mblZ1rrX9x8883ceuut59XPn332GWvXrmX69OlkZ2eTl5dHVFQU/fr1A1q2zn377beVmiBNTU0MGTKE2NhYtFotWq0WSZLw9/fHz88Ps9mMRnNhf32ZzWYSExOJiYlh6dKlhIWFcfToUWbOnInNZuO7775DrVaj0+nw9/cnKioKSZLajAC1vv/vEwmIIAiCIJw/kYAIQidmNBpJT09n6tSp9OnTB0mSUKvVXHHFFXi9XgICAlCpVKjVauLj45WCgRqNhsmTJ5OZmUlqamqbeh2RkZH069evTQ0Mu91Oz549KSwsVBZ3Z2Rk0LVrV8xmM5dddhmfffYZXq8Xo9HIsGHDGDVqVJutbNVqNX369CEiIuIHp5tJkkRycjKBgYHtkoXk5GQmT57MqlWraGxspHfv3gwbNgyr1UpeXh5lZWXodDoiIiK44YYbMBqN7c6v1+tJTk7G398faBn56tq1q5KADBo0iKCgIFGEUPhdEVOO2hL9IQgXR5LP82u7hQsXIssy8+bNIzQ09JeOq1MrLS1lyZIlFBcX89JLL3V0OO3U1NSwceNG3nvvPdauXdvR4QjCBfP5fNhsNvz9/ZVkRpZlpcK5yWQSCYQgfE/V/ffjvgQ3Hvm1aZOSxHoYQbhIYgREEIROR6VStZtadbbpVoIg/D/uggJcubkdHYYgCL8D4is+QRAEQRAEQRB+NSIBEQRBEARBEAThVyMSEEEQBEEQBEEQfjViDYggdFLHjh3D4XAQFhZGZGQkzc3N5OXlodPp6NmzJ5IkcejQIdRqNeHh4VRXV1NYWEhcXBw9e/ZElmUKCwux2WyoVCrKyspoampqcw1JkggPD6dLly7s3LmT6upq4uPjSU9PV7a5bWpq4quvvgJa1maEhITQs2dPZQeuC+Xz+Th48CCFhYVtnk9MTCQ5OVmpC/JT1dfXs379eoxGI9OmTbvgn5dlma+++opBgwbh7+8vFrsLgiAInY5IQAShkzpx4gQ7d+6kX79+TJkyhaqqKhYtWkRwcDDPP/88AIsXL6Zv374MHDiQbdu28cYbb5Cens6iRYswm83s3LmTkpISkpKSKCwspLa2ltLSUoqLi+nduzcmk4mkpCSOHDlCfn4+BoOBnJwctmzZwqhRoxg9ejTV1dU88cQTTJ06FZ/PR2lpKQkJCVx11VVkZGQo8Xq9XgoKCggJCSE4OPicN+5er5e1a9eyd+9eunbtivq/W2VqNJo2RR9/Krvdzv79+wkICLigBMTj8VBUVMSWLVt44403eOutt0hKShIJiCAIgtDpiAREEDopi8XCkSNHMJvNZGZmUl9fz969e9FqtXi9XrxeL9u2baNv377odDplBCQ4OJhvvvmGKVOmUFlZSUlJCSNHjiQ0NJTm5mY2btxIdnY2/fv3JywsjJCQEOx2OxEREZjNZg4ePMiOHTv47rvvGD16NA6Hg/379/P000/j8/n45ptv2L9/P4MHD26TgHg8HtatW8eQIUPaVIz/PlmWKS4uRqfTMWzYMKUeSUJCAi6Xi+zsbL799luamppITk7myiuvxGAwsGvXLnJycqipqcFkMtGjRw8mTJjQ7vxerxer1YpKpUKWZaxWKxs2bCA/Px+TycT48eNJSUk5a5V2jUZDYGAgBw8exG634/P5foZPUhAEQRB+W0QCIgidVFJSEmq1mqqqKsrKyqiqqiI0NJSamhoqKyux2+04nU4iIyMJCAhArVYTGxvL4MGD+eCDDxg9erRyrq5duxIZGQlAeXk5u3btYtSoUcTGxra7rs/nY9++fUpRw1atiQ9AaGhou6lSXq+XnJwcunTpgs/nU0Y2zkWtVqPX69Hr9QQGBhIaGkpVVRVffPEFubm5GI1GsrOzSU1NJTY2lhUrVlBWVoZer0ej0eB2u8+agJzJbrdz5MgRli5dislkwul0Ul1dzf33398uAVGr1URERDBq1Kg2RRoFQRAEobMRCYjwk/h8PqxWK1lZWR0dSjsajYagoCCCg4MJCgqitLSUqKgo1Go1NTU1yrfQLpeL6upqoqOjASgpKSEyMhKNRkNtbS0qlQqLxYLb7aayslKpyl1aWkp4eDharZa6ujoAgoKC8Hg8lJeXKzfdpaWlhIWFodPpaGhowOPxEBISgtfrpaysTGl3+vRpQkJC0Ov1WK1WXC4XoaGhSruYmBgkSaKsrIygoCAMBgM2mw273U5YWJgybSk2NvYHK4R/X3BwMNHR0djtdvbu3UtVVRWDBg2iuLiYnJwcGhsb6dq1K8HBwWg0LX9VREVFkZmZyfLlyzl48OAFfzZ1dXXs2rULoM3ohs/nY+nSpbhcLvbu3cvYsWMxmUzYbDZsNhtlZWU4HA5qa2spLCxk//79SgXyc9XuOHjwIJIkodFoSEpKYuzYsZSUlJCVlcWCBQvo06cPDz30EBs2bCAzM5PvvvuOCRMmMH36dDweD3V1dXi9Xo4cOUJzczMAcXFxeDwe5Rr19fXs2LEDWZZ58sknyc/PZ8GCBcyYMYOQkBCl36BlPYzBYECv16NSqS7osxIEQRCE3xORgAg/idvtJj8/n2uvvbajQ2knJCSEMWPGMHz4cK699lo++eQT7rrrLkwmEzt27CA4OJihQ4dSV1fHypUrmTt3LgCffvopt956KwEBAezZswe9Xs/ll1+O1Wrl888/5w9/+AMAn332Gddffz3BwcHk5OTg9XoZN24cTU1NfPbZZ9x3330ArFy5kmuuuYbw8HAOHTpEQ0MDkydPxuFwsGLFCubPn48kSaxevZqpU6cSHR1Nfn4+ZWVlXHnllbhcLpYvX879998PwNq1axk7diwJCQkUFBRQUFDAtddei8fjUdpd6E1t9+7dOXjwIFlZWUiSxKBBg4iKimLHjh1YrVZ69uxJYGCg0t5gMJCUlMSkSZN46aWXyMjIQJbl87qW3W5n7dq1bN26lSFDhjBlyhTlNZVKxZVXXoksywwdOpQ33niD0NBQZFnm4MGDvPnmm/h8Po4fP86RI0f4+OOP0ev1PPPMMwwaNOis10tJSWHy5Mno9XqCg4MxmUyUlZUBMGXKFHw+H1OnTmXFihVcc801hISEsHPnTrxeLwMGDGDw4ME0Nzfzt7/9jfz8fAD++Mc/tkmc6urqOHToEOPHjycuLo64uDgMBgMnT56ka9euWCyWC/o8BOFSpk1K6ugQLgmiHwTh4okERPhJ9Ho9gwYNYu3atR0dylk1NDTwyiuvIEmScgMPtLnpjYiIUJIPgPnz5yvHmZmZynFISIiSfADMmzdPOT5zGlJgYKCSfADcc889yvHw4cOVY7PZzIIFC5THd911l3J85s200WjkgQceUB7ffvvtynGfPn3o06cPADqdjgcffJCfIjU1lby8PL777jsiIiKYN28esbGx/OUvf6GxsZE//elPbRIQaBntmTt3LgMHDsRoNKLVan/0Ol6vl3Xr1rFo0SJmz57NjBkzCA0NVUYTJEli4sSJSJKELMsUFRVRV1dHY2MjM2bMYPLkydjtdv70pz8xadIkxo4di1arPecNviRJdO/enalTpypTucrLy3G73ej1eiVp0uv1NDc3ExAQwEsvvcT69etZv349n3/+Od27d2fp0qX8+9//xul0AhAWFobVam3zvpqbmzEYDMiyjCzLGI1GnE6nMp1MEH4PZK+XsBde6OgwLhmy14v0I9NABUE4N7H9ivC7FBgYyKOPPtrRYVzyevTogVarJTc3F4/HQ0xMDH369GH//v3k5eW1GwGBliluMTEx3H333bz11lu4XK4fvIYsyyxevJhHH32UP/7xj9xyyy1ERUWddeSkNfnIyclBlmVCQ0Px8/MjMjKSiIgIjEYjFouFiIgIIiIiLmgtRWRkJAkJCdjtdrKzs3G73axcuZLMzEwqKytpbGzkmmuu4d133+XBBx8kNzcXm81GQkICKSkppKSkEBQU1GbtSWhoKIMHD2bt2rW4XC6OHDnC6dOnSU9PP+tC+fMdLRKES4242W5L9IcgXByRgAhCJxYQEEB8fDy9evVSRlS0Wi39+vVj4MCB+Pv7K9O6JElSjvV6PQ899BAWi+W8pn299957FBUVcdttt5GYmEhwcDBXXnkl2dnZQMsOV2FhYQQFBTFixAgiIyO57rrr6Nmzp3KO1poiZrP5J6+f6NOnD1OmTOH222+nR48euFwurrvuOtxuN/PmzWPw4MEMGTKEDz74gD/84Q9nXV9yZj+EhYWRmZmJVqslNTWVa665hoceekhZt3OmpqYm3nrrLdLT06mpqeHqq6/moYce4sCBAz/pvQiCIAjCb5Ukn+dXcgsXLkSWZebNm0doaOgvHVenVlpaypIlSyguLuall17q6HDaqampYePGjbz33nuX7BQs4fw1Nzdjt9vR6XT4+/sjyzK1tbVAy1a9arUan89Hc3MzbreboKAgZbpRZWUlBoMBf39/ZWSgubmZ5uZmZbRAlmVqampwu91trqvX6/Hz80OlUlFZWalsa6tSqdDr9ZhMJnQ6ndJelmUaGxvR6/XodLpzJiGtW+OqVCr8/PzatPN6vdjtdpqamrBarYSGhhIQEIDP56OhoYH6+npUKhUBAQEYjUbMZnO783u9XqX4op+fH16vl8bGRmpqavDz88Pf3x+j0diuvofP58PhcGCz2fB6vahUKgwGAyaT6bymsQlCRxJTjtoS/SEIF0esARGETs5kMrXZ8laSJEJCQtq0ab3ZPrONJEnK1rs/dr4f+9KidSeyHyJJ0jl3vPp+u+9PG2ulVqvx8/PDbDa32aVKrVYTEhKijOj80C5VarW6zfk1Gg0Wi6VNEna2n1WpVO36RhB+KyS1mqr778ddUNDRoXQ4bVKSWA8jCBdJJCCXqNaqyZ9++mlHh9JOY2MjBw8ebLMdqSD8lrRuz/tjz13M+QTh98ZdUIArN7ejwxAE4XdA/It5ifL5fNTW1l6S88Ptdjs1NTVnLTInCIIgCIIgCD9EJCCXqNYieD169OjoUNqx2WwYDAalCJ8gCIIgCIIgnK9Om4C4XC48Hg8+n6+jQ2mnubkZWZbp0qULM2fO7Ohw2jlzEbrw2+Xz+WhqalK20VWr1RgMBgwGg9JGlmXsdjt2ux2v14tWq8VoNCq1NFqT0DOrfLeug2hduN7U1IQkSfj5+WEwGJTF5i6XS7m+JElYLJYfXFwuCIIgCMLvQ6dMQLxeL0VFRZSUlGC32zs6nHZqa2spLS0Vc8qFX5Tb7WbLli2cPHkSnU6HyWQiKSmJjIwMpbBebW0thw8f5vDhw1itVsLDw+nVqxf9+vXD6XTywQcfoNfr0Wq1JCUlkZSURFhYGCqVivr6enbu3ElOTg4ajYb+/fvTu3dvLBYLHo+HwsJCvvvuO0pLS9FqtWRmZtK3b1/UarWShPh8PuVLAvH/gyAIgiD8PnTKf9ErKir4z3/+w+7duy/JHWmcTif+/v5tqnELws/NbrfzzjvvUFJSwuDBg6msrGTv3r08+OCD3HXXXdTU1DB9+nQCAgKUgoU7duzgvffeY926dTQ2NnL//fdz77334nQ6WbRoEUOHDuX2228nJCSEf//732zcuJGpU6dit9t59dVXmTFjBrfddht6vZ5t27bxzTffkJaWRkVFBRMmTCA7O5v4+HhlFMVqtVJWVobH46FXr14d3GOCIAiCIPwcOmUC4nA4cDqdzJo1i/nz53d0OO2cPn2aJUuWUCC2OxR+BWPHjuWJJ56gtraWjz76iE8++YS77rqLPXv2YLVaeeaZZxg2bFibnzmzfNATTzxBYGAg69evZ+XKlXzyySckJSWxbds29u7di7+/PwCnTp3i6quvJj4+nuuvv54777yTO++8E5/PR1lZGW+99ZZSX6RVaWkpmzdvpqmpSSQggiAIgvA70SkTkFZnVjQWhM7M7XZz6tQpNmzYwIgRIwAYOXIkWq2W++67j0GDBjFo0CD69etHnz59+H79Up/Px6FDh2hqasLPz4+qqir69u3bppJ6XFwcXbp0ob6+nqqqKiwWC8XFxTz55JOsWrWKP//5z8TGxiqjH4IgCIIg/D516gRE+OmcTie7d+8mISGho0NpJzg4mLFjxzJ+/HgyMzP5z3/+w5w5czCZTKxZs4bg4GCGDBlCRUUFX3zxBXfddRcAL774IjfffDMBAQFs3LgRvV7PZZddpowM3HPPPQC8/PLLzJ49m6CgIL755hu8Xi9jx47FarWyePFi5s2bB8Brr73G1VdfTVhYGNu3b8dqtTJx4kSampp4++23mTdvHpIk8eabbzJ58mSio6PZvXs3ZWVlTJs2DYfDwWuvvcb8+fORJIl33nmHsWPHEh8fz/79+ykoKOCaa67B5XLx8ssvM3/+/HbVt8/HK6+8wtKlS9FoNAwYMIB7770XaCko+NFHH7Fu3Tr27dvHO++8w//93/8xcuRIXjijCNc111xDQ0MDkiQxa9Ys0tPT2bZtG263u02Cr1KpcLlcOBwOpYZMQEAAmZmZ+Pv7895773HDDTcQGRnJww8/rCQ09fX1eL1e1q1bhyRJvPTSS3Tv3l0kKoIgCILwGyUSEOEn0Wq1pKSk8NRTT3V0KO1otVr0ej3ffvstmZmZXHnllej1egAGDhyIVqsFwGKxMGnSJOXnpk2bpqwJ6tevn3Iz7+/vz9SpU5V2U6dOVaqCZ2RkKKMBJpOJadOmKe0mT56sVMxOS0tTbroNBgPTpk1Tbs4nTpxIcHAwACkpKUpSp9VqmT59unK+zMxMpV1iYqJShVyj0XDVVVf95NG8qVOncuWVV/LNN9+wZcsWZWMGlUpF165dmTFjBpmZmdTW1rJt2zY+/vhj8vLyCA8PB+DGG28kODiYsLAwEhISsNls7Nmzh8OHD2O32zEajQCUlZVRVlbG0KFDlf4zm81cfvnl9O7dm82bN5Odnc3EiRO56aabqKuro6ioiJycHJxOJzNmzECSJGJiYn5SoiUIwsXRJiV1dAiXBNEPgnDxRAIi/CQqlYrAwEAuu+yyjg7lrFq3dpUkqc0oTVhYmHKs1+uJi4tTHsfHxyvHISEhyrFWqz1nu9aEAFoSgTNfO/NnLBaLcqxWq9vEdGZBx9aE5WztYmJilGN/f39lbYVKpbqokai4uDgmTJhAWFgYJSUlPPfcc/zzn//k6NGjNDY2kpaWRnJyMg0NDeTn52O1WvF6vcrPX3755YSHh2MwGNBoNDQ0NJCSkkJzczObN29m8uTJyLLM+vXrlVjVajWlpaX4+/sTGBiIz+ejvr4eaJka2bt3b3w+H3l5edhsNpqbm5XftTO3CRYE4dche72EnTHy2dnJXi+SGIUVhJ9MJCDC75JOp6Nv374dHcZvhp+fH71792bWrFk8//zzfPbZZ1gsFjZs2EBYWBhBQUE0NzdTWFjIwIEDldEXaEnCWkc0Ws/Vq1cvRo8ezccff0xxcTE+n4+tW7dy2WWX0atXL5qamti1axfFxcWEhIRQUVFBRESEsttW6yiVyWTCz88PlUp1Se5YJwidhbjZbkv0hyBcHJGACEInpdFo6NevnzICExAQwJQpU8jNzSU/P5+rrroKtVrN3r17gZYRmaioKG677TbCw8NpaGhg8uTJ7epztI7c3Hnnnbz55pts2rQJWZaJiYnh+uuvJykpibKyMhoaGti1axd6vR6Hw8ENN9xASkpKm/MFBASQlJSE0+n89TpGEARBEIRflEhABKGT8vPz489//rPyuLVa+eOPP648169fP6USukajUUYjoGVa2erVq896bpPJxMCBAxkwYAD19fWo1eo2P9utWzfmzp3LbbfdRkNDAwEBARiNxnbrWGJiYtpMPRMEoWOIKUdtif4QhIsjEhBBEH6Q0WhUFpJfKEmSCAoKOutrKpXqos4tCMKvR1Krqbr/ftyiPhXapCSxHkYQLpJIQARBEARB+FHuggJcubkdHYYgCL8DYi9LQRAEQRAEQRB+NSIBEQRBEARBEAThVyOmYAlCJ3X06FHsdjsRERFERkbS3NxMbm4uOp2OjIwMJEni4MGDqNVqIiIiqKqq4vjx48TFxSkFGI8fP47NZkOSJE6fPk1TU1Oba0iSREREBF27dmXHjh1UVVWRkJBAz549iY6ORpIkmpqaWL9+PdCyg1ZISAi9evUiMDDwJxUc9Pl87N+/n8LCQqVIJEBSUhIpKSkXvZ1vXV0d69atw2g0tikU+WPcbjf5+fns2bMHj8fD0KFDSUpKEnVNBEEQhE5HJCCC0EmdOHGCrKws+vfvzxVXXEFlZSXPPfccISEh/Oc//wHgnXfeoX///gwaNIitW7fy6quvkp6ezssvv4zZbGbHjh0UFxeTkpLC8ePHqa2tpbi4mOLiYvr27YvJZCI5OZn8/HyOHDmCyWQiJyeHb775htGjRzNu3Diqqqp4/PHHmT59Ol6vl1OnTpGQkMC1115Lnz59lHi9Xi9Hjx4lNDSUkJCQcyYnXq+XNWvWsHfvXhITE1H/d6canU5Hly5dLjoBcTgc7N+/n8DAwAtKQJqbm1m8eDEajQadTsf//u//MnPmTEaPHq1UlRcEQRCEzkAkIILQSYWGhlJQUIC/vz8ul4v6+nplxMPr9eLxeNi+fTuDBg3CaDRSW1tLSUkJUVFRbNy4kenTp1NdXU1ZWRljx44lOjoah8PBunXrOHDgAMOHDycsLIzg4GAcDgddu3bFZDJx4MABtm3bxnfffce4ceNwOp0cPnyYF198EZ/PxzfffMOBAwcoKytrk4C43W7WrFnDsGHDCAoKOmcCIssyp0+fxs/PjzFjxigjDDExMbjdbnbu3MlXX32FzWYjNTWV6667DqPRyPbt29mzZw9VVVWYzWZ69uzJFVdc0e78Xq8Xm82GRqPB5/NhtVpZvXo1ubm5mM1mJk+eTFpaWruRDb1ez6hRo/D390ej0XD8+HF27NhB9+7dRQIiCIIgdCoiARGETioxMRGNRkNVVRWnT5+msrKSiIgIqqurKS8vp7m5GY/HQ2RkJH5+fqjVamJjYxk6dCgffvgh48ePV84VHx+vVEcvKipi+/btDBs2TClyeKbWKugOh6PN8w6HA4/HQ2NjI+Hh4fj7+7d53efzcejQIZKSktpMrToXr9eLy+VStgIODAykoqKCL774gsLCQvz9/fn000/p2bMncXFxrFixgrq6OsxmM42Njeh0uh+9hsPhIC8vjxUrVhAaGsqpU6eor6/n4YcfblMtHsBgMDBlyhQltg8++ACHw4Hb7f7R6wiCIAjC74lIQIQLplar0Wg0OBwOvv76644Opx2tVktISAihoaGEhoZSVFREXFwcarWayspKtFotQUFBOJ1OKioqiI+PB+DkyZPExsai0Wiorq5GpVIRHByMy+WirKyMhIQEoOUGOzo6Gq1WS01NDbIsExoaitvt5vTp00q7U6dOERERgV6vp66uDo/HQ1hYGB6Ph5KSErp06QJAcXExYWFhGAwG6uvrcTqdRERE4PV6KS4uJiEhAUmSKCkpISQkBKPRiNVqpbm5mcjISHw+H0VFRXTp0qVdIb8fEhQURHR0NM3Nzezdu5fq6moGDhxIcXExOTk5NDY2kpiYSHBwsFKdPCoqirFjx/LRRx+Rk5NzwZ9NdXU1u3btQpIkevfurTzv8/n44osvcLlc7Nu3jxEjRqDVamlsbKShoYGSkhIcDgdVVVXKNCytVkv37t0JDAw867Xy8vJYuXIlGo2Gbt26oVKpKC4uZvfu3Tz44INkZGTwyCOPsHHjRiZOnMjOnTsZP348V155JbIsY7Va8Xg8HDp0SFnb0rVr1zYJQ11dHTt37kStVvP3v/+dI0eOMG/ePK6//npCQ0PbVYmHlhGavLw8Dh8+zPTp08XohyAIgtDpiAREuGAGg4GIiAi0Wi133HFHR4fTTlBQEKNGjWLw4MFcd911rFq1ijvuuAOTyUR2djZBQUEMGTKEhoYG1q9fz5133gnAl19+yc0334y/vz85OTno9XpGjhyJzWZj7dq1zJ07F4A1a9Ywa9YsgoKCOHToEB6Ph7Fjx2K321m9ejV/+MMfAFi3bh1XXXUVYWFh5OXlYbVamThxIk6nU2knSRIbNmxg0qRJREdHU1BQQFlZGVdccQVut5uVK1dy3333AfDVV18xZswY4uPjOXHiBMePH+fqq6/G4/Eo7S4kAQHo3r07Bw4cICsrC5VKxeDBg4mMjGTHjh00NjaSnp5OQECA0l6v19OtWzcmT57Myy+/TJ8+fc5rNAJa1kCsXbuWrKwshg0bxsSJE5XXVCoV06ZNQ5ZlhgwZwhtvvEF4eDgqlYrc3FzeeecdvF4vx44d48SJE6xatQq9Xs8///lPBg4ceNbrpaSkMGnSJPR6PcHBwZjNZsrLy5EkiYkTJ+Lz+Zg0aRKffPIJM2bMICIiguzsbHw+H/369WPQoEE4HA6eeuopjhw5AsDDDz9Mz549lWvU19eTm5vLmDFjlKrtRqORoqIiEhMTsVgsbWKSZZna2lr+9a9/ERAQwPjx44mLizvfj0sQBEEQfhdEAiJcMIPBwMiRI9mwYUNHh3JODQ0NvPbaa0iSpNzAA0yaNEk5Dg8PV5IPQEkcAMaNG6ccBwcHK8kHwD333KMcX3755cpxQEBAm3PcddddyvGwYcOUY7PZzLx585THZyZxAwYMUI4NBgPz589XHt96663Kce/evZURBJ1Ox4IFC/gpUlNTOXz4MNu2bSMyMpL77ruPmJgY/vznP2O1Wvnzn//c7iY6KCiIO++8k8GDB2MymdDr9T96Hbfbzdq1a3n55ZeZPXs21113HaGhoXg8HqBlt6zMzEwkScLn81FYWEh9fT2NjY1cd911TJo0CbvdzqOPPsqkSZMYN24cGo2mXWytJEkiJSWFyZMnK4vOy8vL8Xg8aLVafD6f0ncOhwM/Pz9eeOEFvvrqK9avX8+qVatISkpi2bJlPPPMM8p0sfDwcBoaGpTreL1eHA4Her0eWZaRZRm9Xo/L5cLr9SrtWpO05uZmHn/8cY4dO8bixYvp0qXLT9rpSxA6gjYpqaNDuCSIfhCEiycSEOF3KTAwkD/+8Y8dHcYlLzU1Fa1Wy+HDhwkNDSUmJobQ0FD279+P0+mkZ8+eBAQE0NzcrPyMRqMhJiaGO++8k2eeeYbbb7/9B68hyzLvv/8+Tz31FP/4xz8YO3YsFotFuWH/ftuioiL2799PWloaoaGhmM1mzGYzzc3NGI1GLBYL4eHhaLXaC3qvkZGRxMfH43A4yM7OplevXqxcuZLx48dTVVUFwFVXXcWMGTNYsWIFzzzzDDabTZmi18pmsynHoaGhDBo0iHXr1nHjjTdy/PhxysvLSUtLIygoqM3P1dXV8eCDD3L06FE+//xzZSev1j640NErQfg1yV4vYS+80NFhXDJkrxfpvzvsCYJw4UQCIgidWEBAAPHx8WRkZCg7Tmm1Wvr164fX68Xf31+5MZYkSTnW6/U8/PDDvP766+d14/zuu+9SVFTErbfeqmyLO3LkSP76178SEBCAx+MhJCQEj8eDn58fU6ZM4brrrqNXr17KOSRJIjw8HLPZ/JNv1vv27cuUKVO47bbbsNlsDB48mBkzZlBbW8sDDzxAcXExer2emJgY5s2b12b62ZlxtF4/LCyMCRMmkJWVRUpKCkajkYceeoiYmJg2MbauKWndhjcpKUk5z2uvvcZ1110nEhDhkiZuttsS/SEIF0eSz3MC98KFC5FlmXnz5hEaGvpLx/WLKiws5OmnnyY9Pb3NFJdLRWlpKUuWLKG4uJiXXnqpo8MRfuccDgdOpxOtVovJZEKWZRobGwHw8/NTvqVv3aXK399fGb2or69Hp9NhMpmUqUSt52vdOevMBd1n0mq1GI1GJEmioaEBSZKQZRlJktDpdBgMhjaLuGVZprm5Ga1Wi1arPecNe2s7SZKU87dq3RnLbrdjtVoJCQlR3rPNZqOhoQGVSoW/vz8Gg+GsRQJ9Ph92u105v8/no7m5mdraWvz8/DCbzeh0ujZTq2RZxufzUV9f3+58fn5+6HQ6kYAIgiAInYYYARGETu77N9qSJLX75r/1ZvvMx5IkERwcfF7nO9dOVa1CQkJ+NE5JkjCbzRfVTq1WYzQaMRgMBAYGKqMx0DJtr3XrX5VKdc6EQKVStTm/Wq3Gz8+vTRL2/Z+VJEmp8i4Iv0ViylFboj8E4eKIBEQQhE6nNSH4secu5nyC8HsiqdVU3X8/7oKCjg6lw2mTksR6GEG4SCIBEQRBEAThR7kLCnDl5nZ0GIIg/A6I/R8FQRAEQRAEQfjViBEQQeiknE4nTU1NeDwe1Go1BoPhR9dYuFwuamtrqa+vx9/fn+bmZuLi4tDr9ZfMImpZlnG5XOh0OuCX29629Tpn1gWBltoiGo0Gj8ej1AexWq2YTKaz7qp1vjweDw0NDTidTqKjo9u9XlRUhMViURb//5T38kv3mSAIgiCASEAEodMqLy9nz549nD59msDAQHr16kXfvn3P2d7n81FSUsKKFSvYt28fQ4YMYdu2bTz55JPEx8dfcF2OX4rP5+PQoUOkpaWddRern4vX6+XUqVOsWrVKKXYIkJCQQFBQEPX19SQmJmK329m8eTN9+vRh9OjRP/l6jY2NbNiwgZMnT/KnP/2p3esvvPACkydPZujQofj5+V3QuT0eD7m5uaSlpZ1XYUlBEARBuBgiARGETsrtdpOTk8PWrVuJj48nOTkZWZZxu91KRfLWxdUqlYra2lq+/fZbli9fzpNPPklkZCTPPPMMjY2Nys+1VhiXJAmVSqV8E//9c7buFtXaXqPRoFKp8Hg8yha/siwru1H5fD7lcevWvF6vV3n+zOvZ7XamT5/Ol19+SXJysnJD7fP5lOrkreeRJAmXy9WmIGBr/GeOIrjdbiXBah0dcLvdHDhwgMcff5ybb75Zadv6PioqKggJCaG5uZkjR44QERGB0+ls835bt+c989oajQav16vEqlarUavVOJ1OioqKyM3NxeVyKe+7Na69e/fSr18/PB4PXq+3zbbHrec4W7+p1Wpqa2u5+uqrWb16NUlJSej1eqW/zuzfM7dFFgRBEISfSvxrIgidVFJSEsOHD1em9AwdOpT6+nqmTZtGSkoKa9euJS4ujocffpjRo0ezcuVKHnvsMRwOBw8//DDPPvuscq7m5mYeeeQRvvzySxwOBwkJCdxyyy3Mnz+fkydPcuONNxIREUF2djYxMTEMGzYMr9fLqlWrCA0NZeHChUyYMIHHHnuM8vJy9u/fT01NDYMGDaJ3795s3bqVAwcOMHHiRF5//XW0Wi0PPfQQa9asoaqqiujoaK655hrmz5/PkiVLKC8v58orr0Sv17Ns2TIkSeK9997js88+Q5ZlJkyYwLPPPovZbGbSpElkZmaSlZWFv78/TU1NxMTE8Mwzz6DX66mtrWXcuHGsW7eO8PDwdtOTQkNDWbRoUZvnNm7cSFVVFTabDZVKRU1NDe+88w5/+ctfcDgcPPHEE8yePZvvvvuOLVu2UF5eTm1tLT6fj0WLFvHJJ5/w/PPP4/F4uOGGG5g3bx4GgwGXy0VWVhZTpkxREo5ly5a1qbrudDpZvXo1//u//0tNTQ3+/v7cdddd/OUvf8Fut/PYY4+xdu1aGhoayMjI4IorrsBms1FaWsoVV1yBXq9nzZo1rF+/nqVLl3LkyBFCQ0OZOnUqTz/99C/7SykIgiB0CmIRuiAICp/Px/HjxwkODmbz5s2MHz+erVu3kp+fT79+/ZgzZw5XXHEFq1atYsiQIcrPabVa5s6dy6ZNmzh48CCPPPIIr732GqdPn8btdnPo0CHGjRvHqlWr6NWrF9999x0Gg4H333+f2bNnKzfwZWVlVFdX8/jjj/Pcc8+hUqn48ssvueOOO9iwYQPZ2dns3LkTr9fLrFmzWLNmDfn5+Tz66KPk5eWxbds2brjhBsLCwnjrrbdYt24daWlpvP/++zQ2NvLss8/yxhtvUFJSwqeffgrA8ePH2bRpExMnTuTOO+9k0KBBVFdXs3HjRlwuF0uXLqVbt24EBgaedW1EeXk5M2bMUP4UFBRQW1tLRUUFNpsNaBk1iYiI4PPPP+fPf/4zTz75JDabDZvNxrZt2ygrK2PChAncd999WK1W/vWvf7F48WI+/fRTNm3aRHZ2No2NjXi9XkJCQrj77rtZuXIlVquVlStXthvtGDlyJB988AHHjx9n5cqVPPfccxQXF7Ns2TJOnDjBv/71L3bt2sXChQtJSUlh5syZREZG8u6777Jhwwaam5tZunQpV111FXv27GHJkiX069fvl/zVEwRBEDoRkYBcomw2Gx999BHR0dGX3J9hw4bx2GOP8fXXX+NyuXj22WeVqTTvvfceBf/dJz43N5cPP/wQaJlj/uyzzyrTSj744APy8vIAOHr0KIsXLwZaboCfffZZ3G43AB9//DH79+8H4MSJE7z99ttAy6LZ5557DofDAcBnn33Gnj17ACgpKeH1119X2j3//PM0NTUBsHr1arZv3w5ARUUFr7zyitLnixYtwmq1ArBhwwa+/fZbAGpqanjxxReVdv/5z3+ora0F4Ouvv2bjxo0ANDQ08H//939Ku5dffpnKykoAtm3bxpo1awBoamrihRdeUKbdvPbaa5SWlgKwa9cuPv/8cwDsdjvPPfec0u6tt96iqKgIgH379rF8+XKAdp/Bz+Hmm28mMTGRyy67jNraWmpra9Hr9QQEBODn50dUVFSb9RUajYba2lreffdd7r77bp566ilsNhtVVVXIskxwcDDTpk0jLS2NHj16MHz4cC677DIyMjIYMmQIuf/d2lOWZcaOHUvfvn0ZPHgwPXr0IDExkWnTptGlSxcyMjLIy8tTpnK99957zJ07l2effZbjx48r1cg1Gg0RERFER0dTW1tLcXExSUlJTJo0iZ49ezJhwgTWrVunXPOPf/wjM2fOZMiQIYwdO5akpCRWr16N0+nkgw8+4JZbbjln9XWTycTkyZOVPxaLpU0VdACLxcL48eNJS0vj9ttvx2azUVxcjNPppFevXsycOZMbb7yR9PR09uzZQ//+/Rk2bBj9+/dn5MiRHD16lOLiYgwGA0lJSUydOpU+ffowffp0vvvuu3YJiMPhYPv27cydO5c//OEPNDc3U1VVRUREBKWlpaxYsYItW7bg7+/PqFGj8Pf3R6PREB4eTnR0NJGRkQCsX7+ejz/+mObmZiZPnvyz/X4JgiAInZuYgnWJMplMjBkzhoceeqijQ2nHYDDQ1NTEoUOHuPzyy5k1a5ZyYzZx4kRlp58uXboQHh4OtNwUzZo1S7kxGz9+vLJQNi4uDovFArR8Uzxr1ixlvvro0aOVBb5RUVFMmTJFiWPmzJnKrj2XXXaZchwWFsa0adOUdjNmzFBulocNG6bMYw8KCmL69OlKu2uvvVa51sCBA5VYAwICuPrqq5V211xzjVIxu2/fvkqCYDabufbaa5V2V111lfK+MjIylJtEg8HAddddp/TZtGnTlIriPXr0oFu3bgDo9XpmzpypnG/KlCnK+ZKTk4mLiwNabv7P/Ax+DiaTSaka3roWoLX6eetaizMTnqysLD788ENCQkK4/fbbqamp4Y033lDaqFQqjEYjWq0WnU6HwWBAr9ej1WoxGAxKwtn6vlvXSLTuKGU0GpFlGb1ej8vloqqqiieeeIL09HSuv/56ysvL2bdvn5KYtF5TrVZjs9nw+XxKhXadTkdAQICSRELLZ2w0GtHpdHTv3p3U1FTWrl3LunXrsFqtXHbZZefcWcpsNrf5fQsMDGyXgKhUKgwGAxqNRvn9a2howOPxoNVqMRqNmEwmmpqaqKurIzAwEJ1Op1SRb25uxuFwIEkSGo1GmY5lMpmoqalps4bk2LFjfP311+zevZurr76asLAw7r77bnw+H0OHDuXBBx/kwIEDrFixgtWrV3PllVcyfvx4JU6VSoXFYuHxxx9nx44d7Nu3j6+//pqePXvy1FNP/aTfJ0EQBEE4k0hALlEqlYqwsDAGDx7c0aGclc1mIyQkBJVKRUxMjPJ8RESEcmw2m5VtXSVJatOuNTEBMBqNGI3Gs7YLCwtTjltvIM/WLiQkRDnW6/XKN7jfb9d6ow8t26VGRUUpj89sd+aceq1W22bb0zOPWxMCaEkEznztzHOfuf2qWq1uc60z27UmNkC7vm19TwB+fn5KAvf9dj+n801qTpw4gdvtJi0tjSFDhpCTk6OMdv3U856tTetzlZWVlJaWMmvWLEaOHMmOHTvIzs5W2rTuQuXz+QgPD8fPz4+6ujrKyspwu93k5+fTq1evs17Xz8+PLl26EBYWxiuvvMKYMWMIDAw8Z5xqtbrN79+5tC78PnDgAB6Ph9DQUKqqqtq0MRqN9OjRgw8++IDGxkY0Gg1Hjx7lsssuIyQkRFmc7/P5aG5uZu/evcTHx7dJeCorK5XRjtGjR2O325XPoqamhv79+5OamkpOTg5ZWVls376dzMxMLBYL9fX1ANTX1xMTE8OkSZPo378/mzdvZvPmzTQ3N7fZ8UsQBEEQfgqRgAg/iZ+fH927d+/oMISLcOLECXbt2sW+ffuorq5mz549JCYmAm1v/s913PpYkiRiY2PRarXs2bOHmpoaTp48qUyP+zHnOucPsVgsREVFKdsIFxYWUl1dDbQkZEOHDmXZsmVs376d66+/nv79+3P06FHeeOMNJEmisrKS2bNnn/XcKpWK6OhoBg0axMsvv8zf/va3s8Z5IRoaGli3bh3V1dXs3buXsWPHEhkZybFjx9q0MxgMpKWlERkZyUsvvYRarcbr9ZKWlkZYWBgej4cjR47wn//8h4aGBmVL3jN3pwoODiY4OJjdu3ezdOlSbDYbzc3NSJLE0aNHOXz4MHq9nsbGRoxGIwkJCWi1WgYPHsyHH37I9u3bGT58OFu2bMHn86HX6/F4PHTv3r3dyI7QuWiTkjo6hEuC6AdBuHgiARGETspms6FWq4mKiiI4OJjq6mq6d+/OlClTMJvNSJJEaGgoAwcOJDo6Gn9/f5KTk5XRHEmSmDx5MoGBgURHR3P48GFycnKUG9yxY8cSFBSEXq9n0qRJyhS5bt26ERwcTFhYGCqVisDAQGVq3cCBA0lMTESv16NSqUhNTVWup1arGTBgAF26dCEuLk7ZCerAgQMYjUb69+9P165d0Wg0XHPNNSxbtoxDhw7R1NTEmDFj0Gg07N+/H1mWGTBgAAMHDgRg0qRJBAcHt5liZTAYiI6OpkuXLkq772sdyZowYUK712JjY+nduzdRUVGYTCbS09MpKChg37592Gw27r33XiwWC7GxsWRkZBAbGwugrF258cYb2bx5Mz6fj/Hjx5OamorRaCQ5OZmUlBQOHjyIzWZjxIgRjBw5Eo1Gw+WXX058fDxJSUk0NjZy8uRJ9u7dS2BgIJMnTyYoKEjZ7cput2M0GunWrRvjx4/HYDBw9dVXs2zZMg4cOMDw4cNpaGigrKwMnU5HeHg4N9xwwy9aV0W4tMleL2EvvNDRYVwyZK8X6QILfgqC8P9I8pmTh3/AwoULkWWZefPmERoa+kvH9YsqLCzk6aefJj09nfnz53d0OO2UlpayZMkSiouLeemllzo6HEE4L7IsKzVB/P39f5VvyxsaGpT1JWeOArRW9vZ6vRgMBiUWt9uNy+X6wYrvsixz6NAh3nnnHfz9/Vm4cOFFxynLMl6vl5qaGgIDA3+0cvyZdVW+39br9WK323E4HOf8u7j1/VutVmWqZCuPx0NzczMajabNdKrv95kkSdhsNiRJwmQyidEPQRAE4WcjRkAEQfhZSJLUZq3Lr+FcazMkSTprRW+tVvujFdt9Ph/l5eUcPnyYf/3rXz9LnK2Lx89cI/Vj7VtHjL5PrVa3WQN0rp/X6/Vt1lC10mg0Z/2cztZnZ65JEgRBEISfi0hABEEQzqBWqxk3bhxjx44V3/oLwn+JKUdtif4QhIsjEhBBEISz+Dm3NRaE3zpJrabq/vtx/7fOU2emTUoS62EE4SKJBEQQBOF7RPIhCO25Cwpw/bdoqCAIwsUQCYggdFJut5vdu3fjcrlITk4mJiYGWZbxeDx89tlnpKamkpqaes61CD+kdcH1Rx99RFZWFrNmzaKxsZGJEydSXl5Ofn4+QUFBjBkz5qLew6uvvkp8fDwjR45ss15BlmXeeOMNkpOTGThw4A+ulzgbl8uFzWZDr9f/4IJ1QRAEQRAunJjgLAidlN1uZ9myZfz973/nk08+AVqSkvXr1/PXv/6VjRs3nnctj++rq6tj/fr1ZGVlMW3aNAICAsjNzcVut1NdXU1+fj4nTpy46PeQnZ3NsWPHcLlc7V7bu3cvJ0+ePOtrP6awsJDXX3+db7755qJjFARBEAShLTECIgidlM/no7q6msLCQvLy8jh27Bjh4eG8//77qFQqampqqK2tZfny5fTs2ZP+/fsjSRJlZWW8//77LFiwgObmZj788ENOnjxJQEAAI0aMoEePHuTl5fHOO+9QVVVFQEAAd999N0VFRTidTtxuNxUVFeTm5lJSUkJjYyMDBgxg5syZ1NTU8PHHHxMeHk5VVRUWi4VevXrR3NzM6tWrsVqtpKWlMXv2bMxmMzabjZ07d9LQ0IDNZiM0NJTZs2cTGxtLU1MTDocDWZbZsGEDu3btoqqqSin2d/3116PRaFi5ciU7d+7E6XQSHR1N7969qa6uZvny5WRlZbFr1y5uuOEGGhsbWb9+PdXV1fj5+TF48GBGjx4tKoMLgiAIwgUSIyCC0IlpNBri4uIwGo2sWrWKY8eOUVJSQq9evVCpVEiSxPbt29mxYwfl5eVYrVays7P59ttvAdiyZQvbtm2jubmZo0eP8u2335Kbm4vb7cZqtRIbG0t4eDgGg4GSkhJlNKKpqYnq6mrq6uooKyvjnXfeoaGhgYaGBpYsWcLGjRspKCigvr6ewsJCPvvsMwoLC/F6vaxevZqDBw8q56qurqaiooKamhq2bt3Kpk2b2r3PxsZG7HY7Go0Gq9XKqlWryM/Pp7q6mrfeeoumpiYkSaKiokKpqC7LsvIH4J133qGwsBBZlmloaKCysvInja4IgiAIQmcnRkAuQRqNBq1WS1VVFV9++WVHh9OO2WwmLCyM8PBwQkJCOH78OElJSUiSRFFRESEhIfj5+WG1WmloaCAuLg6fz0dBQQHJyclIksSpU6ewWCwEBATQ2NhIbW0tCQkJyLJMQUEB3bp1Q6VSUVJSgr+/P4GBgTQ1NVFVVUWXLl2UdomJiajVakpLSzGZTAQFBWG32ykvL6dr165Ku9YK2a2VnUNCQnA4HJw+fZrExEQACgoKSEhIQKvVUlFRgUqlIiwsDJfLRXFxMd26dVPaxcfHo9PpqKysRJZlIiIicLvdFBUVkZSUBMDx48eJjY1Fr9dTXV2Nx+MhMjISj8fDiRMnSE5OBlqm+0RFRWE0GqmtrcXhcBAdHY3X66WwsFDp25MnTxIeHo7JZKK+vh6bzUZsbCw+n6/NZ3ChevbsSVJSEp988gl1dXUMHToUp9Op1PVISEjg5MmTHDp0iC5durB161b69u2LwWDg448/pkePHtx4443s37+fr776ioMHDzJx4kQyMjLo0aMHd9xxhzKa4vF4gJZ6HKmpqdx5551UV1dz9913c+zYMfz9/amoqMBisTBmzBji4uI4ePAg27Zt47HHHqNPnz488sgjbN68me7duwMtVcenTZtGaGgon376KStXruSWW25p8x67d+9OSEgIXq+XgoIC3nrrLXbv3s3w4cPZtm0bt9xyC8nJydTX1xMWFobVaiUjI4NBgwYxe/Zs/Pz82LBhAzfeeCPjx48HaFf8UBAEQRCE8yP+9bwE+fn5ERMTQ319PQ8//HBHh9NOQkICgwcPpn///kycOJENGzbQrVs35dvyIUOG4Ofnx+nTpzl06JCSgGzcuJFu3bqhVqvZuXMnvXv3JiAggMrKSvbs2aMkIBs2bOCuu+5CpVKxZ88ekpOTCQwMpKamhu+++44uXboAsHHjRu644w7UajU5OTlER0cTFBREXV0dW7ZsoWvXrgB89dVX3HLLLWg0Gg4cOEBQUBAhISFYrVa++eYbJQH56quvuOGGG9BqteTm5iqF3Gw2G5s3b1YSkM2bN3Pdddeh0+k4cuQIXq+XiIgI7HY7mzZtUhKQb775hmnTphEWFkZBQQGNjY1ERkbidDr56quvlIRhy5YtTJgwAaPRyIkTJ6ioqCA6Ohq3283GjRuV823dupVRo0ZhMpkoLi6msLCQ2NhYPB5Pm8/gQsXExJCWlkZTUxMrVqxg2bJlvPnmm8rro0aNYsmSJezduxdJkti3bx9PPvkksiyTlZXFfffdR2xsLBaLha1bt3LixAlUKhUGgwGz2UxQUBA1NTVtrhkaGkp0dDTp6enU19eTlpZGTk4Ow4cPJzg4mGuuuYZBgwZRX1/P7t278Xg8ZGZmApCZmcmKFSuw2+1AS3LRv39/DAYDl19+OR999FGba3k8Hqqqqvj22285cuQIFRUV1NfX09DQQEREBPHx8axatYr09HQGDRpEWFgYzc3NbeIHGDBgAHv27MHlctG/f3969+6NwWC44P4WBEEQhM5OJCCXILPZzKxZs5g1a1ZHh3JOJ0+eZN26deh0Ov7whz8oz8+ePVs5bt1FCVpGdc5sd9111ynH3bp1U27uVSpVm3bTp09XjuPj47nhhhuAlm1S7733XuW1KVOmKMfR0dHKN+CSJHHPPfcor02YMEE5Dg8P5/bbb1cez507Vzk+c3em4OBg7rzzTuXxXXfdpRyPHDlSOW5d69DqjjvuUI6HDBmiHJvN5jYx3Xrrrcpx//79lWODwdDmPd50003Kca9evejVqxdAu8/gQkmSRFJSEnfccQfZ2dmkp6e3eX3QoEF8+umnZGVlYbVaMRqNDBw4EK/Xi8vlQqvVIkkSarUaWZZxu914vd4fvGbrtCZZlvH5fHi9Xpqamtq183g8eDwe9Ho9Xq8XtVqNRqPB6XQq52jl8/lwu93tzlNdXc3//d//4efnx5w5czCbzbzzzjtAS6Xv5cuXs3z5ctavX8/SpUu55ZZbGDFiBJIk4fP5lOssWrSIFStWsG3bNlasWMGoUaNYuHAh4eHhF9bhgiAIgtDJiTUgwk/SpUuXNjfswm9bXFwcd999N6+//nq71wwGA4MHD6axsZEvv/yS6667Tkk4JkyYwPr167FarWzfvh1omdL1Y1v3+nw+PB6PMr0tKyuL/v37t6s8HhoaSpcuXXC73crow+rVqxk9erSyPa7X61UWtm/atIl+/fq1OUd1dTUqlYq+ffsyYsQI9Ho9JSUlyLLMyZMnsdvtPPTQQyxbtoyUlBSKiorw+XxYLBZlip3P52P37t3ccMMNLF68mNmzZ+NyuTh+/PjFdLsgCIIgdEpiBEQQOrnzmbY1aNAgsrOzOXz4cJtRqQULFvDYY4/x5ptvEhQUxIwZM5g4cSKyLLc57/evcfToUd566y2ee+456urquPnmmxkxYgTHjh1r17ZHjx7ccMMN3H777VitVoYOHcq1115LQEAAAC+99BKvvPIKsiwTHh7Ou+++2+aaPXv2pHfv3rz11ls8+eST6HQ6QkNDkSSJhoYGrrjiCvz9/VGpVAwePJgpU6Yo9UMefPBB3njjDRYtWsQf//hHbDYbRqOR6OhoZs6cycCBA39KlwvCb5L2v9NBOzvRD4Jw8ST5+/MYzmHhwoXIssy8efMIDQ39peP6RRUWFvL000+Tnp7O/PnzOzocQegQsizjcDhQqVTo9fo2z7cuQtfpdEiSxPr169m0aROhoaE88sgjSJKkjAw4nU7q6+sxmUwYjUa0Wi3QUsxPpVKh1WqRZZnm5maMRiOyLONyuWhubsZms6HRaAgNDUWv1+Pz+XA4HBgMBtRqNfD/RkucTicNDQ0EBwdjMBiQJAmHw6EUDXQ4HISFhWE2m1GpVDgcDtRqNVqtFpfLRV1dHU6nEz8/P/R6PVqtFo1GQ1NTEzU1NQQEBGA0GtHpdKjVajweD83NzVitVmXtTn19PVqtFqPRiMFgUKafCcLvnez1Iv33/0lB9IcgXCwxAiIInZQkSRiNxrM+f+biao/Hw3fffUdjYyOzZ89Wbrhbp2GZTCb0er2ybW+rM88hSVKbauQajQaDwYDFYlHOA6BWq9tVHlepVOh0OrRaLSaTqc11WhMBPz8/ZFlGrVa3ea2VXq8nPDwcWZbbxenv79/mvK2vaTQaAgIC8PPzUxIpo9GotBGJh9CZiJvttkR/CMLF+f0mIEVF8O23cOQI+HzQrRuMGgX/3UFJEITzo1KpmD17Nl6vV9lZ7PvUP+EfY5VK1W7Nxw85M1E5n+fPdr1znfds2+m2JhhnnvunvE9BEARBENr6/SUgDQ2wYQN8+WVL8nH6NMgyhIXBrl0wfTpER3d0lILwm6FSqZTdzMS3/oLQOYkpR22J/hCEi/P7SkAaG2HdOnj99ZbRD1luGf0AKC6GY8egshLdlCmoGxs7NlZB+A0RiYcgdG6SWk3V/ffjLijo6FA6nDYpibAXXujoMAThN+33k4DIMmRlwSuvwI4dcLY6BI2NsHYt/i4X/g0NaAcP/vXjFIRLhM/no6GhAYfDAbSsefD39/9JxfUqKiowm80YjcYLnqbUuui9dcG7SHYE4dLkLijAlZvb0WEIgvA78PtJQJxOeO452L275fhcXC78tmwhITCQMLf714tPEC4xbrebb7/9lpMnT2I0GjGbzaSkpJCeno7JZLqgRGD9+vX06tWLlJSUdovIf4zH42H//v1kZGSIyuKCIAiC0AlcUALSWvnY+UM3+B1EtXs3mtOnkVyuH22rbmqiH2D+7ze/gtAZ2e123n//fUpLSxkyZAjl5eU88cQT/O1vf2PWrFlKgT+fz4dKpUKj0aBSqZRtdNVqNV6vF61WS0FBAdHR0Xi9XmXbXI/Ho+xMpdFolLYqlUqpfu7z+aitrWXmzJl88cUXJCUlKbtXtVZUb11k3rq9r9PpbPO8RqMRi8MFQRAE4TfkvBMQi8XC8uXLOX78eJuaAZeKkUePclVJCRafj/P53jbK7Ubn8fzicQnCpW7MmDE88cQT1NTUsHTpUt555x1mzZpFdnY2jz32GEeOHCEtLY3Zs2eTmZlJYWEhjz32GGPHjuWzzz7jT3/6E4cOHWLAgAEAFBQU8NFHH7F48WIaGhoYOnQoN910E2vWrOGvf/0rXbp04cSJE2zcuJEdO3bQvXt3SktLueqqq9Dr9Xz55Zc0NTXxxhtvsH79ekwmE9OmTeO+++5Dq9Vyyy23sH37dnQ6HTNmzODmm2+mT58+HduJgiAIgiCct/NOQO677z6Cg4PxXKI37V11OqSCgpYKzOfRXv7vH0EQWlitVnbs2EF8fDwAjz76KDNmzGD8+PFs3LiRgwcPotFoCA4OZvv27WRkZPD444+TmprKc889R0NDA83NzXzzzTesWbOGRYsWkZGRwdtvv83o0aN5+OGHueaaawgLC2PPnj3s37+f8ePHM2zYMF5++WXeffddEhMTiYyM5L777iMkJIR3330Xr9fL4sWLWbp0KQC1tbUcOHCAxsZGCgoKLnjKlyAIgiAIHeu8ExCVSsWMGTM4z8Lpvzp1ejrq7Gyk+nr4kWlYsiRRqNfjr9NxKW7Ia7PZWL58OS+++CInT57s6HDaSUxMZOzYsYwfP56RI0fywgsv8PDDD6NSqXj77bcZOXIkycnJHDp0iJycHG688UY8Hg/PPfccDz30EGq1miVLltC/f3/S0tI4cuQIWVlZ3Hrrrfh8Pv7973/zwAMPoNVqWbZsGampqfTp04cTJ06wadMm5syZgyzL/Pvf/+a+++7DYDCwYsUK4uLiGDRoECUlJaxevZq5c+ciyzLPPvss99xzD2azmZUrVxISEsLw4cMpLy/nk08+Yd68eQA899xzzJkzh4CAANatW4der2f06NHU1NTw/vvvs2DBAgBeeOEFbr75ZoKDg9m0aRMej4cJEybQ0NDA22+/zQMPPADAf/7zH2bMmEFERARbt26loaGBqVOnYrPZeO2113jwwQeRJImXX36ZK6+8kpiYGHbs2MHp06e5+uqrsdvtvPjiizz88MNIksTrr79OZmYmXbp0Ye/evRw7doyZM2ficrnafAYXasmSJWzcuJHGxkYiIyN57bXXKCsr49ChQ8TFxZGXl0dZWRmN/905bsKECXTp0oV//OMfaLVaZRoUQH5+PuXl5QwZMoRx48ah0Wh4+OGHMRgMTJw4ke3btxMUFMThw4dpampi0qRJeL1eNBoN4eHhREZGUlNTQ35+PlqtFqvVSnNzM6dOnaK2tpYbb7yRvLw8XnrpJYYPH07//v0JCQn5OX6tBUEQBEH4lUjypZpRXCi7He64A9avh9raH2wqA09ERRH5xz9y5/33/yrhXYjy8nKWLFnCwYMHefjhhzs6nHb0ej0NDQ3s27ePO++8k6qqKsLDw5EkiZqaGvz8/NDr9djtdux2O8HBwciyTGVlpdKutrYWo9GI0WjE4XDQ1NRESEhIu3Z1dXXo9XpMJhNOp5PGxkZCQ0OVdmFhYahUKurr69FqtZjNZlwuF1ar9aztGhoaUKvV+Pn54Xa7qa+vJywsDIDKykpCQkJQq9VYrVYkScLf3x+Px0NtbS3h4eFKu+DgYDQaDY2NjciyTEBAAF6vl5qaGqVdVVUVFosFrVaLzWbD6/USGBiI1+ulurqaiIgIpV1gYCA6nY6mpibcbjcWiwWfz9emb6urqwkICECn09Hc3IzT6SQoKKhdu/NVX1/PnDlzUKvV3Hbbbfj7+xMZGUlcXBwFBQVMnTqVRx99lODgYLxeL2q1muDgYHw+HwsWLCD3jN1wLr/8cubMmYPZbGb79u2YzWYWLlzY5nobNmzg2WefJT09HY1GQ3R0NPfddx91dXUMHDiQdevWkZyczPHjx5k3bx49e/Zk6NCh+Hw+fD4fFouFoUOH8tFHH7F//37279/PkCFDuP766+nXr99F/U4LgvDjTk+dKnbBAnTp6USvXt3RYQjCb9rvZxcsoxEeeghsNvj665b/nqNd7YwZVJ0+TeBP+Lb41+D1evF6vfj7+5ORkdHR4ZxVa8KgUqmUG2mgzbfRrQkGtNSROLNdcHCwcmwwGJTdj77fLigoSDnW6/XK+qPvt7NYLMqxTqcjNDT0rO0CAwOVY61WqyQfgJI4AAQEBCjHrd/On62dv7+/cqxWq9u8dua5/fz82rQ7M6Yz2505nej7fdv6ngBMJhMmk+ms7S5UXFwcw4cPR6fTodfrkWWZmJgYAgICCA0NpV+/fuj1eurq6rDZbFit1nOey2KxIEkSR44coaamhqCgIA4dOkSvXr0YOHAgOp2O9evXM3bsWIYNG4ZarUaSJIKCgqirqwMgMjKSoKAggoODSU1NJTQ0FLvdzunTpykrK2P06NFKwrJ3716KiopEAiIIgiAIvyG/nwQEoF8/uOceMJtbChG2TseSZdBqW5KU66/HlpmJ+/PPOzra3zSz2Uy3bt06OgzhZ6DX69skUpIkERgYyJQpU9i/fz/Hjx9X6nQkJia2SQrP/BmA+Ph40tPTycvL4x//+AeRkZGUlJTw/PPPExQUREZGBuXl5URERNC9e3egJWEcOnQo7733Hps3b+buu+9m5MiRlJWVsWrVKtRqNQ6Hg+joaIKDg9m1axeRkZGUlZURFxfXJoETBEEQBOHS9/tKQCQJJk4EvR5iY6GwECorW5KQyEjo2hXuuguvJOHT6To6WkHoUDqdjssvv5yoqKizvj579mw2b95MaWkpVquVqKgoLBYLkZGRTJs2rU3bzMxMEhMTiY6OZtiwYcoUPZfL1WZUx2Kx0Lt3b9LS0pTRKL1ezzXXXMOKFSsoKSnB7XaTmZnJrl27OHLkCPX19UiSRFpaGhaLhdraWpxOJ2azmcsvv1xJZARB+GVpk5I6OoRLgugHQbh4v581IN9XX9+SgBQVgcMBycnQty+oVBSeOMHTTz9Neno68+fP7+hI2yktLWXJkiUUFxfz0ksvdXQ4QifX3NyMJElotVplsfmP8fl8Ss2g1kTDbrdzzz33kJ6ezpVXXklKSorSvrW2iNfrxWAwKIvpXS4XbrcbnU6HVqtFlmW8Xi9Wq5XAwEBR/0MQfiWy14sk/n9TiP4QhIvz+xoBOZPF0jIlS8wNF4SL0rrW5EKoVKo2a3ugJbGuq6sjNTWVxMTENu0lSTprfSGdTofujNFKSZKUrYAFQfj1iJvttkR/CMLF+f0mIIIgXFKSkpL47LPPkCTpgnbrEgRBEATh9+XS3AZKEITfJZVKJZIPQfgNkr3ejg7hkiL6QxAujhgBEQRBEAThB0lqNVX334+7oKCjQ+lw2qQkwl54oaPDEITfNJGACEIn5Xa72blzJ263m5SUFGJiYpBlGY/HwyeffEJaWho9evRg//79+Hw+4uLiiI6O7uiwL1pFRQVffPEFqampjBw5UozICMJ5chcUiEKEgiD8LMQULEHopOx2Ox9++CGPPfYYH330EdCSlKxZs4a//OUvrF+/XikAWFpaiu1cxT1/Y5qbm9m/fz/FxcUdHYogCIIgdEpiBEQQOimfz0d9fT0lJSUcOXKE/Px8oqKiWLx4MSaTifr6enw+H7W1tfh8PpxOJ83NzeTn5/PZZ59RXl5OdHQ0c+bMITs7G7fbTX19PfX19URFRTF16lSWLVvGvn378PPz45prrqFPnz6sX78eSZIYMmQIkZGRNDc388YbbzB+/HhUKhVLliyhsrISvV5P7969GT16NAkJCZw6dYr33nuPsrIyLBYL1157Lenp6VRUVLB9+3ays7PxeDwkJydz7bXXsnTpUu69915MJhN79uyhurqauLg4DAYDzc3NuFwuAF566SUOHz6M0+kkNjaWMWPGMGzYMGpra3nzzTfp168fu3btIjU1lcmTJ7epai8IgiAIwoUTIyCC0IlpNBoSEhIwm8188cUX5OfnU1lZSc+ePZVaHPX19dTV1eF0Ojl9+jSfffYZp06dIjw8nNraWurq6ti5cyefffYZ2dnZNDQ0YLVaOXToEGvWrCEgIACr1cqSJUuorq6mpKSEXbt2cejQITweD+Xl5Xz44YdotVpcLhdarZbIyEjUajXZ2dl89dVXNDY2smrVKvLz84mNjUWWZerq6mhubmbLli1s3rwZWZYJCAjg2LFj1NTU8PnnnytJRkFBAfv27ePUqVPt+sDhcBASEkJkZCRHjx5l27ZtnDp1ioaGBj7++GPWrFmDzWbD5XLxey2bJAiCIAi/JjECconyeDycPHmSTz75pKNDacfPz4/IyEgiIyMJDw8nPz+fHj16IEkSx48fJzw8HH9/f+XGtWvXrvh8vjbtTpw4QXBwMIGBgVitVqqrq0lMTESWZfLy8khNTUWlUlFUVERAQABBQUHYbDbKy8tJSkpS2nXv3h21Ws2pU6cwm82EhITQ3NxMaWkpycnJyLJMfn4+ycnJaDQaSkpK0Ov1hIWFYbfbKS4uVgri5efn061bN7RaLadPn0atVhMREYHT6eTkyZNKxe38/Hy6du2KXq+nvLwcWZaJiorC5XJRWFhIamoqAEeOHCEhIQGDwUBlZSVut5uYmBg8Hg/Hjh2jR48eABw7doyYmBhMJhPV1dXY7Xbi4uLwer0cPXqU1NRUJEmioKCAqKgozGYztbW1NDY2kpCQ0K5vL1RaWhrJycl89NFH1NXVMWLECJqampRzNTU14fP5sNvtNDQ08O233/LAAw8wduxY9u/fT2BgIM3NzdjtdgYMGMDw4cPxeDzs2LEDk8nEgw8+SGFhIXPnzqWkpISuXbty/Phx9uzZw8CBAzl48CBer5cuXbpQW1vLsGHDlH756quv2LFjB1dccQXZ2dno9XquvfZabDYbAQEB1NbWcvDgQXQ6HXfddRehoaFs27YNj8dDXV2dkjA4HA6amppwOp3t3v+AAQNwuVw4HA5OnjzJkSNHOH78OLGxsdTV1eHv78/06dMJCQlpU9dEEARBEISfRiQglyiXy8X+/ft54oknOjqUduLj4xkwYAC9e/dm8uTJbN26VblJzs7OZtCgQfj7+1NRUcHhw4eVBGTLli1KwrBv3z569epFYGAg1dXV7N27V0lAtm7dSnJyMiqViv3795OUlERQUBB1dXXs2bOHpKQkALZu3Uq3bt1Qq9Xk5uYSHR1NSEgIDQ0N7Ny5k+TkZKVdQkICGo2G/Px8LBYLYWFh2Gw2srKylARk27ZtxMTEoNVqOXbsGDqdjoiICJqbm9m+fbuSgGzfvp3IyEj0ej3Hjx/H6/USFRWF0+lk27ZtSgKSlZWl3LSePHmSxsZGYmJicLlcSjtJktixYwfjx4/HZDJRXFxMRUUFcXFxuN1utmzZopxv9+7djBw5ErPZzOnTpzl58iQJCQl4vd42n8GFio6OpkePHjidTlavXs2yZct4/fXX27VramqiqqoKu93OFVdcgUajYeTIkUDLSMrQoUPJzMykZ8+eHDlyhLy8PEaOHElUVBRRUVGYTCZKS0vp1asXO3bs4MiRI5w8eZLNmzczbdo0NBoNjY2NbN26laKiImprazlx4gRpaWkYDAbS09P58ssv+eSTT8jIyCA+Pp7s7Gy8Xi8ZGRmkp6cDcNVVV5GTk3Ne793tdlNYWMiuXbuorq6moKCArl270tTUBIDBYGDOnDl06dJFLFYXBEEQhJ+JSEAuUSaTiSuvvJKXXnqpo0M5q6KiIjZs2IBWq+Xuu+9Wnp8xY4Zy3L17d+WmXaPRMHfuXOW1q6++WjlOTExUKmOrVKo255s2bZpyHBcXx6xZs4CWithntps0aZJyHBUVxY033qi0u+uuu5TXxo0bpxyHhYVxyy23KI/nzJmjHF9++eXKcVBQELfddpvy+Pbbb1eOhw8frhz7+/u3Ocett96qHA8aNEg5NplM3Hnnncrjm266STnu27evcmwwGNq8x9mzZyvHPXv2pGfPngDtPoMLJUkSSUlJ3HHHHWRnZysjM9/X3NxMQ0MDWq0Wn8+HLMv4fL6ztvX5fLhcLjQaDbIs4/V60el0eDweQkNDSUpK4vTp06xZs4Zt27axePFiAJ577jnKysq47bbbSEpKYunSpeTn5xMUFMQ999xDdHQ033zzDS+99BL/+7//i8fjweVyoVar8fl8SJKkPPZ4PMiyrMT5/VhlWaasrIwHH3yQp59+mhEjRrBp0yaxOF0QBEEQfmFiDYjwkyQkJLS5iRZ+22JjY5kzZw6vvPLKOdsEBQURFRVFZWUlmzZtwuv1cuzYMUpKSnC73W3aBgcHM2TIEGUnrfz8fCoqKujevTvBwcFkZGQQGBjIm2++SWhoKOnp6UiSxOnTpxk+fDh9+/bF6/VSW1sLtCQ/O3bs4LrrruP111/n+uuvp7CwkJCQEBobG9m3bx9lZWU0NTWxbds24uLiqK2tpb6+noaGBk6cOEF1dXW791ReXk5AQAATJkwgPj4eq9VKfX39z9q3giAIgiC0JUZABKGT+7GpRa2vGwwGBg8ezJw5c5g5cyZhYWE0NTXx+eeftxtdCA4OZsKECXz33XekpKRgMplYsGABCQkJSJJEeno6/fr1Y82aNcqoFsDdd9/NggULePbZZ7FYLDidTvr374/VauW9997j+uuvV9bLPPfcc/Tp0we9Xs+rr75Kjx49CAsLw9/fn3379nH11VczcuRI3G43gYGBDBw4sM17kiSJQYMG0bNnTwYNGoQsy5hMJgYNGtSmT8TUK0EQBEH4eUlyJ9zWpbCwkKeffpr09HTmz5/f0eG0U1paypIlSyguLr5kp2AJv32yLONyuVCpVGi12jbPu91uJElCo9Hg8XiAlulxkiTh9Xqx2+3U19cra1y8Xi+SJKFWq1GpVMrUJ7fbrSzk1ul0aDQaJElSpmW53W60Wi0aTct3IV6vl8bGRhobGzGbzRiNRlQqFTqdDpfLRWNjI263G4vFgk6nQ6VS4fV6cTqd2O123G43QUFB6PV63G431dXVGI1G9Ho9arVaic/tdqNWq9FoNDidTsrLyzGZTBiNRiUeSZJwOp3o9XolYRGEzkxUQm8hKqELwsUTIyCC0ElJkoRerz/r8zqdTnl8ZnLS+rq/vz9ms1nZqletVrdr03qe8PBw5eb9zP9qNBol8WilVqsJDAzE398fSZKU8wPodDqCg4ORZVlJhqBlfZFarcZoNCLLshJL6yYCrec4M4E4833r9XpiY2OVmM9sZzQaf7APBaGzkL1ecdN9BtnrRfre33uCIJy/TpuAuFwu9uzZwzvvvNPRobRTX1/PgQMH8Pf37+hQBKGd1hv07ycd52p7oSMHrSMpF3Kuc712PjFeSDtB6KzEzXZboj8E4eJ02gTE6/VSV1dHUVFRR4fSTmNjIxqNhri4uI4ORRAEQRAEQRB+Vp02AdFoNMTHxzNkyJCODqWd2tpaDhw40NFhCIIgCAIgphx9n+gPQbg4nTYB0Wq1dO/enYkTJ3Z0KO2UlpZy6tQpUY9A+EX5fD5qa2ux2+1tntdqtURERFzQ1Kn8/HxCQ0OxWCzt1nWceb3W2iAajUZZcF5aWqoUETxfBw4coEuXLuj1eqxWKyqVipCQkHO2t1qtWK1WZU2KIAgXRlKrxSL0/xKL0AXh4nXaBEQQOjuXy8W3337LiRMnlMXWKpWK4ODgNgUlz8fLL7/M1KlTGTZsGH5+fmdt43Q6OXToEAkJCYSHh+N0OsnLy+Ott97izTffvKDrPf300zz88MNERkayd+9e9Hp9myKT33f06FH27dtHWFgY06dPv6BrCYLQwl1QgCs3t6PDEAThd0AkIILQSTkcDpYuXUpxcbFS0V2lUtHc3Ky83lpBvHV3KZ1OpyzYbt32VpIksrOzGThwIB6PB6/Xi8vlUooT6nQ69Ho9p06d4qGHHuLee+9l6tSpOBwOampqyM7OpqmpCa/Xq+xm1bpV75nn0Wg0ypa4e/bsob6+HovFQmlpqbIDlsfjwW63I8sykiRhMBjQarXU1dVx4sSJdgUTBUEQBEH49YkERBA6uXHjxvH//X//X5vnJEli4cKFVFRUcPDgQaxWK0OGDOGOO+5g5MiRNDY28vDDD7NixQoCAgKorKxUbu4PHz7Me++9x0cffQTAnDlzeOyxx3juuec4fPgwjzzyCK+++ipjx44lIyODsrIybrvtNjZv3syoUaP497//TWxsLEVFRSxbtoylS5ficrmYOnUqf/rTnwgNDW0TZ3V1NXq9noaGBjZv3swDDzxAbW0tERERPP7440yZMuXX60xBEARBEH6U6sebCILwe/bBBx8wbtw4xo0bR2ZmJnPnzkWWZU6fPk1FRQWPPfYYL774ImFhYXz44YfU19fz1ltvsX37dr788ks2b95MamoqarWapqYmtm3bxq5du1i6dCnLli3jtdde4/jx49x9992kpKTw+OOP89FHH3H77bcrBQunTp3K3r17qa6u5uuvv6a+vp6PP/6Y06dPs2jRIlavXk1dXR3Lli1rE7vb7aaiooKqqioMBgN9+/bliy++oLKykn/84x889dRTlJaWdlDPCoIgCIJwNiIBuUTZbDbef/99AgICLrk/ffr04ZFHHuGrr77C5XLx1FNP4fP5AHjzzTc5evQoAAcPHmTx4sUAeDwennzySbxeLwDvvfceuf+dS5yfn8/bb78NtCxUfvLJJ5Vv0z/88EP27dsHtFSwf+2114CWat1PPfUUDocDgOXLl7Nz506ANhXkZVnm6aefpqmpCYAvvviCrVu3AlBeXs7//d//KX3+r3/9i4aGBgDWrFnDpk2bAKiurub5559X2j333HPU1NQAsHHjRtatWwe01G/597//rbRbtGgRFRUVAHz77besXLlS+WyfeeYZZFkG4MUXX6SkpASArKwsPvnkE6BlitPTTz+ttHv11Vc5efIkANnZ2SxduhSg3WdwoQYOHMiCBQtYsGAB8+fP5/rrr1demzBhAv3792fkyJFERkZSVFREY2Mj27dvZ9asWQwYMICEhASlKOGRI0eoqqpiyJAhDBkyhH79+jFu3DjWrVuHwWBAp9MRFBREWFgYfn5+aDQaoqOjmT17NrGxsQwbNozCwkKKioo4evQou3fv5tNPP+XZZ5+luLiYjRs3nvN9aLVa9Ho9n3zyCdOnT+fvf/87p06dUiq5C4IgCIJwaRBTsC5RJpOJK664gr/+9a8dHUo7rXPqd+/ezdixY5kzZ46yY9K1116LyWQCIDk5mfj4eKCl0Nudd96pVKW+8sorlYXPXbt2JTIyEmiZUnPnnXcqOylNmTJFqVodGxvbZnH0nXfeqVTsnjBhglKxOzIyss1N9Jw5c5RrjRkzRlnDEBoayo033qi0u/3225UF1JdddpnyniwWC7fccovS7pZbbsFisQAwbNgwJUHw9/fntttuU9rddNNNBAQEAC03+a3Jl8lk4o477lDOf/311ytFJ/v06aPsCKXX65kzZ45yvpkzZ2I2mwFIS0sjKSlJ+TzO/AwuVNeuXdss4D6z+nhrlXGtVotarVbWg3i9XiIjI1Gr1W2u27ouxGw2o9FokGUZf39/6uvrlTatFc7PrIre+tnpdDrcbjeNjY2oVCq6d+/OuHHjlPUdrf15NkVFRcpoywMPPIBer+eGG274SX0iCIIgCMIvRyQglyiVSkVgYCDdu3fv6FDOqrm5mdDQUCRJajMnv/XGHMBgMGAwGAB+sJ1er1eSjO+3CwwMVI51Op2ScEiS1Gbb1TNvTLVaLUFBQWdtd2Z1eY1GQ3BwsPL4zHZn7uT0Q+1aEwJoSbLOfO3Mn2lNyoB2W8ae2c5oNLbZkerMdq3v6fvtvt9nF0qr1bZ5H2dzZpKh0+no0aMH2dnZ3HTTTdTU1NDU1ITP5yMuLo68vDz27duH1WrF4/GQk5PDX/7yF4KDg/F6vTidznOOSrReJzw8nNDQUJqbm0lISCAuLg6n06mMAJ1NU1MTJ0+epG/fvgwdOpSDBw/+5KRMEARBEIRfjkhAhJ/EZDKRkJDQ0WEIP4OvvvpKqQWiUqmIjIzkoYceOmd7k8nEyJEjWbRoEX/+859RqVRUVlbi8/kIDw8nNTWVnJwc/vGPfyBJEhEREfTt2xeLxUL37t3ZuHEjhYWFJCcnK7tane0aQ4YMYc+ePXz++edotVqsVitJSUnKjl3fFxAQQPfu3dm5cydOp5P6+npcLhfQktiIZEQQBEEQLg0iARGETkqn05GZmUlOTo5yo65SqZT1N2PGjKFLly7K6E1GRoayTW7fvn3JzMzkyJEjhIeHc+2119K9e3cCAgLIyMigoaGBAwcOAC1TzCIiIlCpVFx11VXs3bsXp9OJJEkkJCRw7bXXKjENGDAAj8eDv78/gwcPRq/Xc+jQIWpra5VpXwCzZ88mJiaGwMBAhg8fjlarJSQkhEmTJmG1WqmvrycyMpKbbrqJkJAQdDodgwYNajPyJgiCIAhCx5Dk1gnsnUhhYSFPP/006enpzJ8/v6PDaae0tJQlS5a0WUwtCJcaWZapq6vDYrG0G2Hw+Xx4PB5kWVam17VyOp3IsqysK/kxHo8Hh8OBXq9X1or8UEwul4umpiaCgoLEqIcg/IxEJfQWohK6IFw8MQIiCMJPIklSm/UrZ1KpVMp6ne/7fkLyYzQazTmrq58tpjPXFAmC8POQvV5x030G2etFOo8vUARBODuxDa8gCIIgCD9I3Gy3JfpDEC6OSEAEQRAEQRAEQfjViAREEARBEIQfJP+3jpHQQvSHIFwcsQZEEDopl8vFzp07OXXqlFJ3pnfv3sTExPyk8zU0NCDLcpv6L7+0DRs2YLFY6NKlC4WFhaxevZqFCxfy7bffkpeXx+23367US/k5FRYWUlVVRXBwMMnJyUDLAvjGxkY2bNjAuHHjfvYdt77++mvKyspIT0+nd+/eP+u5BeHHSGq1WIT+X2IRuiBcPJGACEIn5XA4eP/99zl16hTp6enU1dXx/PPP88c//pFx48Zd8A5Sn376KY2NjQwdOpSBAwf+QlG3VVhYSFRUFOHh4ZSVlZGVlYUsy5w6dYr9+/cr1ed/bpWVlaxduxaAhQsXKs+vW7eOzz///BfZ8re4uJiCggLCw8N/1vMKwvlyFxTgys3t6DAEQfgdEAmIIHRSPp+Pmpoa4uLiuOmmm6iqqmL16tUsX76ccePGkZubywcffMDp06eJiopizJgxXH755TgcDj799FO+/fZbfD4fGRkZjBkzhs2bN5Ofn8/XX3/NgAEDuO6660hJSWlzTa/Xy5YtW9iyZQunTp0iICCAUaNGMW7cOP7nf/6H2tpadDodQ4YMITMzk4iICPbv38/KlSvx9/cnLy+PxMREFixYQFBQEKdPn8ZoNCLLMm63m+bmZmUrXrvdjizLfPvtt2zYsIGioiL0ej3p6elcf/31hIWFsWTJEgwGA0VFRbhcLjweDz169GDEiBHExsZit9tZtGgRU6ZMIS0tTdk2OCEhAa1Wy86dO6msrFSSgpUrV5KSkoLBYODAgQNs3ryZI0eOYLFYGDFiBJMnT6ayspLnn3+e4OBgjh8/TmhoKOPGjWPYsGFUV1fz2muv8cgjj+Dn58fhw4fJyspi4sSJuN1upYq8y+Xi6NGjvPvuu9TU1DBw4ECmTZtGREQEBw4cYNOmTeTl5aHRaMjIyOC+++771X+/BEEQBOFcxBoQQejkwsLCyMjIoEePHmi1Wurr6wF4//33qa6uJiIigrKyMrZv387hw4cpKCjg/fffp1u3bqSkpFBfX49Go8FkMmGxWIiKiiImJuasU5+Ki4vZvHkzp06dIjIykqCgIEpLS5FlGbPZTM+ePUlISGDDhg3k5ORgtVo5fvw4a9aswel0EhUVxddff83evXtxOBxUVFTQ0NCAz+c75/vz+XyEhYWRmppKcHAwubm5bNq0CVmW+e677/j444+pqalBkiTq6urYu3cv+/btw+12U1JSwooVKzCbzW1GhEJDQ+nSpQtqtZo9e/YgyzL19fXs2rWLUaNGodfrWb9+PcePHycqKgqdTscXX3xBeXk5VquV5cuXU1VVRVRUFEVFRezcuZPS0lIaGhpYuXIlDocDgLKyMrZt26Z8Jq2sVivLli1TEqacnBx27drFyZMn+frrr9m/fz/dunUjISGB2trai/8lEQRBEISfkRgBuQRptVp0Oh2lpaUsXry4o8Npx9/fn5iYGGJiYoiMjOTQoUNkZGQgSRJHjhwhMjKSwMBAamtrqampITk5GZ/Px8GDB+nVqxcqlYpjx44RGhpKUFAQ9fX1VFZWkpKSgizLHDhwQGl3/PhxLBYLISEhWK1WTp8+TWpqqtKuZ8+eqNVqTpw4gZ+fH2FhYdhsNk6dOkVaWhqyLHPw4EHl5rr1W/DIyEiam5s5ceIE6enpABw4cIDU1FR0Oh3FxcWo1Wqio6NxOBwUFBTQs2dPAA4ePEhycjIGg0G5eY6NjcXlcnHkyBF69eoFQG5uLomJiRiNRsrKynC5XCQkJOB2u8nLyyMjIwOAw4cPk5CQgNlsprKykqamJrp27YrH4yE3N1fp27y8PGJjY/H396e6upqGhga6deuG1+tt8xlcqGPHjvH5559TVlbGsWPHGDt2LE1NTaxevZq//vWvDBo0iI0bN3L48GF27dpFYmIi+/fv58EHHyQuLo6qqioSEhLo2rUrgYGBjBo1ihEjRuDxeFi+fLlynfHjx7N7926qqqoYMGAAU6dOxePxcOrUKXQ6HcOGDUOj0VBWVsaKFSuUPne5XEiSxNSpU4mIiKC4uJisrCz69euHzWZTRjrOJS4uDp/Ph81mo6CggGPHjrF9+3ZmzpyJzWZDkiTGjRtHVFSUcgOflZXFsGHD2LVrFyaTifj4+DZ9q9VqSUxMJCEhga+//lqpKK/VaunRowdVVVXs2bOHoKAgevXqRUVFBRs3bmT//v106dKFxsZGLrvsMvr166ckesePHyciIoK6ujoloXK5XFitVjwej3Jtn89HZWUlX3zxBXfccQe9e/cmJyeHrVu3EhgYyPHjx5WpcCEhIdTV1V3w74QgCIIg/JJEAnIJ8vPzo0uXLmzfvp1XXnmlo8NpJzY2lr59+5KWlsaUKVPYs2cPvXr1QpIkcnNzMRgMBAYGUlNTQ35+PsnJyciyzJ49e5Sb+Ly8PNLS0ggKCqKuro7c3FwlAdmzZw/p6emoVCqOHDlCYmKikoAcOnSI1NRUALKzs0lNTUWtVnPs2DGioqKUBOTAgQOkpaUp7ZKTk9FqtRQWFhIYGKgkIDk5OUoCsnfvXhITE9HpdJw8eRKdTqckIPv27VNi37dvH/Hx8RgMBk6dOoXX6yU2Nhan08nevXuVBGTfvn1ERkZiNBopLS3FZrMpCUh2drbSZ/v37yckJASz2UxZWRmVlZVKApKdna0kKgcPHiQgIAB/f38qKyspKiqiW7du+Hy+Np/BhTpw4AB2ux23201iYiIzZ86kvLyc+vp6Bg8eTHx8PBkZGRQXF3Py5EmGDx9OcnIyX3zxBSkpKYwcORKdTodOp8NgMGA2mzGbzRQXF/Pqq68q1+nfvz/Z2dn8/+3deVRV5foH8O/hTBxmBBPH1ABRBA6JHFHRMIeLECla1grT0rJrgzdblbZsMJdTi7TShpt5MxdamdogKmldh7qKQyLpQkAwxZEAB4bDmd/fH/7YiyODkHAOxPezFmvts9/37P3sh12+D3u/e/v7+0Or1aJnz54Abt7OVFpaiqysLBQVFaGyshLl5eUwGAwwGAxQKBTw8/NDdHQ0hBCIiYnB4cOHYTQam3R8V65cwa+//oo//vgDZWVlKCsrg6enp9QeHx+PYcOGwd3dHT169MDvv/+OrKwsnDp1ChkZGXjooYcgl8vr5Pbuu+9GSEgIvvzyS9y4cQPp6ekYPXo0PDw8cOjQIRiNRpSVleHw4cPQ6/Xo2rUrLl68iN69e8PT0xM6nQ533XUXevfujRs3bqCkpARdunQBgEYLKpPJhJKSEly+fBnFxcXYtWsXlEolKioq4Obmhr59++LcuXPYtm0bgoKCMGzYsCafC0RERI7AAqQNcnNzQ3JyMpKTk50dSoPOnTuHn3/+GUqlEjNmzJDW1445KChIekKQXC6365eUlCQt9+nTB3369AFw8w3atfuNHz9eWu7RowcmT54M4OYbr5988kmpbezYsdJyQEAAHnnkEanfE088IbXFxcVJy/7+/njsscekz9OnT5eWY2NjpWUfHx9MnTpV+vz4449LyzExMdKyp6cnpk2bJn1OSUmRlqOioqRlNzc3u5geffRRabn2041cXV3tjvHhhx+WlgcMGCAVWLf+Dppr5MiRePnll+Hr6ws/Pz8IIVBaWgqVSgWr1SoNhm02G2QyGfr27Ys1a9Zgy5Yt+O6777B+/Xps3bpVGqALIeDi4oJu3brh008/lfbTo0cPVFRUSG81r/krf0VFBTIyMvDVV1/ho48+QnBwMObOnQs3Nze7OIUQsNls0Ov1MJvNTT6+d955B507d8aECRNw11134cCBA8jOzq63r6+vL0JCQpCfn49Nmzbh6NGjWL58eb19u3btiv79+6OqqgoHDx7Ezp07sXr1aqhUKpjNZnTq1AnBwcGIiYmBTCaDTCZDQEBAnYnxLi4ucHG5eTesTCaDXC6Xjs9kMtXZr9Vqhclkgp+fH+6//36o1WoIIaBWqxEYGIi+ffsiLCwMu3btwsaNG7Fu3TocOnRIioGIiMjZOAeE/pK7777bbnBM7Ze/vz8CAwPh5+cH4OYgeMCAAdBoNMjKysKff/6J48ePQ6/XIzQ0FBcuXIDFYsG8efOwceNGXLhwAWVlZfDy8oLNZsPVq1dhNpuhUChwzz33SD8qlQohISE4c+YMsrOzUV5ejrKyMmRmZuLKlSsICwtDdHQ0rFYrbty4IQ2+ayaYV1dXo7i4GDt27EBERESTHvVrtVpx9epVREREIDo6GiqVChcuXGj0OwMHDkT37t2xceNGREdHo1u3bvUO3F1cXNC1a1dERUVh6dKlKC8vx/Dhw6FQKDBixAjYbDa4uLggNDQU9957L3r06AG9Xt/ovtVqNXr16oXc3FwYjUZkZWXVudLj7u6OoKAg+Pr6QqFQIDo6GlqtFjabDZcvX0ZpaSn69euHt99+GytWrEBubi7Ky8tvmysiIiJHYQFCRPWqGcDqdDps2LAB99xzD4YOHYpTp05hzJgxiIiIwNixYzF79mz07dsXI0eORHl5OebOnYuEhATs37+/zjanTp2KoKAgrFy5En379kVsbKx0m9OxY8cQFBSEUaNGISsrS7pCYjQaceTIEemKmkajwdNPPw0fHx+7wqC+ZblcjpSUFHzxxRcICwvD5MmT8b///a/B7wFAYGAgdDodOnfubHdFqz4BAQEYO3Ysjhw5gilTpkChUEAmk6Fz585ITk5GTk4ORo8eLT0p7Ny5cw3GCgB+fn6YOHEiHn30UfTo0QM7duyQJqTXvoLRuXNnzJ8/H4sWLUJkZCR69uyJL774AufOncOqVasQGxuLwYMHY/bs2Xjttdfq5IqIiMiZZKKxm43/ps6cOYPly5cjNDQUL7zwgrPDIXIKIQQsFgtkMhkUirp3Y9psNlitVlRWVkrzO1xcXKTH3JaUlKBz585QKBTS42ktFguqq6thsVjg4+Mj3VpUe59WqxUGgwFGoxFyuRweHh6Qy+UwmUy4dOkS7rrrLiiVSsjlcly/fh3p6en4/PPPkZ6eDoPBAG9vbyleq9UKmUwmxWW1WqFQKGCz2SCEgFwuh81mQ0VFBUwmE1QqlfREK7lcbvf9mgH6xYsX8e2332L79u1IT0+Xjq2hHNbk0cXFxW6uiM1mg81mQ3V1NfR6Pby9vaFSqSCTyWA2m6FUKiGTyaR+NXFYrVZUVFTAZrPB09NTirVmXzWx1hzvtWvX4OrqCo1GIx1TVVUVDAaDdJWksWMgaqpLiYl8DwgAVWgouqWnOzsMonaNc0CIOiiZTAalUtlge83cBG9v7zrzB9RqNbp162Y3dwEAFAoFPD09pYFyfftUKBRwd3eX5njUFA8qlQq9evWy22btKxk136m9vnbhVDOAr+lfQy6Xw8vLy+64atRXeGVlZSEnJwdJSUn1HsOtxyOTyaBSqRrMn4eHh1T01MRdu3/tOSA18Xp7e9fJQUP79vf3l/rUrPP29oaXlxfnfVCLUgYGOjuENoF5ILpzLECIqFG3DsJrFwW3qj0QbsytA+OGtunl5YXx48dj8ODBdzSYvl0hUdvQoUMxYMAA6erDnWpu3M3pX1/fpv4OiJpDWK3o/N57zg6jzRBWK2S8skj0l7EAIaI2S6FQwN/fH/7+/g7bp6+vL3x9fTmAJ6qFg217zAfRnWEBQkRtmqMLARYeRERErYsFCFEHZzKZUFlZievXr8NoNEKj0SAgIABqtRqlpaUoLy+Hn58flEolKisrodFo7OZUENHfH285ssd8EN0ZFiBEHVhFRQXOnj2LvLw8FBUVobq6Gt7e3ggLC8OQIUOQnZ2NEydOYMSIEfDy8kJeXp70ZnQi6jhkcjlK/vUvmAsKnB2K0ykDAzkfhugOsQAh6qCsViv27NmDTZs24fz584iMjESvXr2Ql5eHTz75BBkZGSguLkZhYSEiIiIgk8lw8eJFeHl5QQghPdoWuPk2djc3N+k9GET092MuKOBjeImoRbAAIeqgCgsL8emnn6Jnz57YsGEDevToAQDSez4UCoXd06P0ej1KS0tRXV0Ng8GAp556Cnv27IHFYoFOp8Prr7+OwYMHN/poXyIiIiK+CZ2ogzp58iQUCgX69euH7t27S+tr3mtx66NrKysrceXKFZSXl0OpVOKf//wncnJyUFBQAA8PD/z88884ffq0ow+DiIiI2pkOWYD4+PjAw8MDqampcHNza3M/sbGxePvtt3Hw4EGUlpbi3XfflWJPTU1FWVkZAGDXrl3YuXMnAOD69et45513pH4rV65EcXExAGDv3r34/vvvAdwcRC5btgxCCADABx98gAsXLgAADhw4gG+++QYAUF1djaVLl0r9PvroI/zxxx8AgKNHj2Ljxo0Abk5gXrJkCWw2GwBgzZo1yM/PBwD8/vvvWLduHYCbb8hevHgxrFYrAODzzz/HyZMnAQC5ubn47LPPANx8e/SSJUtgNpsBAGlpaTh27BiAm3+x/+STTwDc/Cv9kiVLYDAYAACbNm1CZmYmAKCoqAirV6+W+i1btgxVVVUAgG+//Rb79+8HAFy+fBnv1bqPd/ny5bhx4wYAYPv27fjpp58AoN39DprKYDBArVZDo9FAJpMhNzcX/fv3R0BAALp27YqioiLp91Ufm82GF154AQkJCdi7dy8uXrwIvV7frBiIiIio45GJmtFNB2K1WnHjxg3o9fpGB1jOolKpkJOTg7KyMkyaNAmVlZXSm5Fv3LgBDw8PyOVyVFdXQwgBNzc32Gw2VFRU1NvPYDDAZrNJ/crLy+Hj4wMAKC8vl+7dNxgMsFqtcHd3l/rVvAW7vLwcGo0GSqUSRqMRZrMZHh4eEELgxo0bUr+Kigq4urpCqVTCZDLBZDI12E+tVkOlUsFkMsFoNEpv0K7dr7KyEkqlEmq1GmazGdXV1dIchNr9qqqqoFAooFarYbFYoNfr7fp5eXnBxcUFVVVVkMvlcHV1hcViQVVVlV3OPD094eLiAr1eD5lMBo1GA6vV2q5+B021b98+LFq0CJGRkViwYAHUajUKCwthNBoRExODU6dO4cCBA8jMzERycjJMJhO2b9+OYcOGISoqCqNHj8b8+fOh1WqRlpYGX19fJCUlISoqqiX+MyCiNuZSYiLngABQhYaiW3q6s8Mgatc65BwQuVyOTp06oVOnTs4OpUHu7u4wGAyQy+XSgBaA3bJGo5GWXVxcGuzn6upq169m4AvA7nGqTe2nVquhVqsB3Lxdp3Y/T09PaVmlUkGlUt1RPw8PD2lZqVRK8wtu7efu7i4tKxQKKd7b9WsoZ25ubtJye/sdNNXAgQPRp08f5OfnY9euXZgwYQKCg4NRVVUFIQQa+tuExWJBcXExqqurkZiYCA8PD5hMJumqFREREVFjOmQB0h54eXnxXQvUqnx8fJCcnIxdu3Zhy5Yt+OWXX+Dp6Ynr168jLCwMbm5udeaBADcLt+7du6Nnz55Yvnw5XFxccPLkSeh0OiccBREREbU3LECIOii5XI6hQ4fCzc0NR44cQUlJCYCbhclzzz0HLy8vhISEwNXVFT179oTVasWoUaPQt29fdOvWDTNnzkReXh40Gg3i4+MRGhqKLl26OPmoiIiIqK3rkHNAiMiezWaDyWRCVVUVfH19IZPJbjufRAiBa9euwd3dHSqViu//IPqb4xyQmzgHhOjO8QoIEcHFxQWurq52c1BuRyaTtel5VETUspSBgc4OoU1gHojuHK+AEBERUaOE1QqZXO7sMNoM5oPozrAAISIiIiIih+mQLyIkIiIiIiLnYAFCREREjRJt8KW9zsR8EN0Z3oJFREREt1Xyr3/BXFDg7DCcThkYiM7vvefsMIjaNT4Fi4iIiG7LXFDAx/ASUYvgLVhEREREROQwLECIiIiIiMhhWIAQEREREZHDsAAhIiIiIiKHYQFCREREREQOwwKEiIiIiIgchgUIERERERE5DAsQIiIiIiJyGL6IkIiIiG5LGRjo7BDaBOaB6M7JhBDC2UEQERFR2yWsVsjkcmeH0WYwH0R3hldAiIioyYQQqKqqcnYYRETUBri7u0MmkzX7eyxAiIioyaqqqjBo0CBnh0FERG3Ab7/9Bg8Pj2Z/j7dgERFRk93uCkhlZSVGjhyJffv2/aV/lJylvcYNtN/YGbfjtdfYGbfjNTV2XgEhIqJWJ5PJmvQPqYeHR7v7Bxdov3ED7Td2xu147TV2xu14rRU7H8NLREREREQOwwKEiIiIiIgchgUIERG1GJVKheeeew4qlcrZoTRLe40baL+xM27Ha6+xM27Ha+3YOQmdiIiIiIgchldAiIiIiIjIYViAEBERERGRw7AAISIiIiIih2EBQkREzVZdXY0pU6Zg69atjfbLzs7GQw89hMjISIwaNQrffPONXfu3336LMWPGQKvVIjk5GVlZWa0Sr16vx/z586HT6TBo0CC88sorDb5Q8Y033kBkZKTdT//+/TFjxgypT3x8PCIiIuz6FBYWOj12AHjzzTcxcOBAu9i+/vprqb0t5hwAfvzxRzz44IO49957MWrUKKxevRo2m01qb82cl5WVYfbs2YiKioJOp8PixYthsVjq7btv3z488MAD0Gq1iI+Px549e+za16xZgxEjRkCr1WLq1Kk4c+ZMi8TYErF/+eWXGDduHCIjIzFu3Dhs2LBBarPZbIiMjIRWq7XLsV6vd3rcM2fORFhYmF1c+/fvl9odmfOmxj1z5sw6/x/p168f3njjDQCOz3dtV69exZgxY3Do0KEG+7T6eS6IiIiaIT8/X0ycOFEEBweLLVu2NNjv+vXrIjo6WqSlpQmz2SwOHDggIiMjRXZ2thBCiMzMTBEZGSmOHj0qTCaT+Pzzz4VOpxN6vb7FY543b56YNm2auHbtmigtLRUpKSnirbfeatJ3f/nlFxEdHS3y8/OFEEJUVFSIfv36iQsXLrR4nPVpbuwTJ04UW7durbetreb8xIkTIjw8XPz3v/8VVqtVFBQUiLi4OLF27VohROvnPCUlRbz00ktCr9eLoqIikZCQINasWVOn3x9//CHCwsLE7t27hdlsFtu3bxfh4eHiypUrQgghtm7dKmJjY0V+fr4wGAxi6dKlIiEhQdhstlaJuzmx7969W0RFRYmsrCxhs9nEsWPHRFRUlMjIyBBCCJGXlydCQ0OF0WhstVj/StxCCKHT6cShQ4fqbXN0zpsTd23ffPONGDlypCguLhZCOD7fNY4ePSpGjx4tgoODRWZmZr19HHGeswAhIqImO3DggIiJiRHr168X9913X6MFyKZNm8TYsWPt1r3xxhvilVdeEUII8dJLL4kFCxbYtf/jH/8QmzdvbtGY9Xq9CA0NFb/99pu07vjx4yI8PPy2A++ysjKh0+nE999/L607ePCg0Ol0LRpjQ5obu9FoFKGhoVKxdKu2mvOMjAyxZMkSu3VLliwRzzzzjBCidXN+9uxZERwcLA2uhBBi+/bt4r777qvTd8WKFeKJJ56wWzdjxgzx/vvvCyGEeOSRR8THH38stZlMJhEZGSkOHjzo9NjT0tLEv//9b7t1zz77rFi0aJEQQojNmzeL5OTkVonzVs2Ju6ioSISEhIiKiop6t+XInDcn7toKCwtFeHi4OHLkiLTOkfmusXXrVnHfffeJ7du3N1qAOOI85y1YREQkMRgMOHfuXL0/er0eISEh2LNnD6ZOnQqZTOsJc+AAAApTSURBVNbotk6fPo3g4GC7dYGBgcjNzQUAFBQUNNreUnGfO3cOZrPZbl/33HMPDAYDzp492+h2U1NTMXDgQCQlJUnrTpw4AY1Gg5SUFOh0OiQnJ9e5PcFZsefm5sJiseCDDz7A0KFDMW7cOHz66afSrUxtNefjxo3D/Pnz7ba9d+9ehIaGAmj5nNd2+vRp+Pj4oEuXLnaxXrp0CeXl5XZ9b5e/W9uVSiV69+79l/Lb0rE/9thjePrpp6XPZWVlOHLkCAYOHAjgZo6NRiMmTZqEIUOG4LHHHsOxY8ecHveJEyfg7u6OF198EUOGDEFiYiI2b94stTsy582Ju7aFCxdiwoQJiIqKktY5Mt81hg8fjt27d2P8+PGN9nPEea5oRtxERPQ3l52djccff7zetg8//BCjR49u8raqqqqg0Wjs1rm6ukr3ON+uvTkai3vOnDkAADc3N2ldzX4bm5Nw/vx5/PDDD3XmrchkMoSFhWHu3Lno1q0bMjIy8PzzzyMtLQ1ardapsVdUVCA6OhpTp07FihUrcOrUKTz77LNwcXHBzJkz23zOAaCyshJz5syBq6srpk+fDqDlc15bfTmp+azX6+Hl5dVo39Y6p5uiObHXVlJSglmzZmHgwIFITEyU4gwPD8ecOXPg7e2NDRs2YMaMGfjhhx/Qs2dPp8VtMpmg1Wrx4osvIigoCIcOHcLzzz8Pd3d3xMfHOzTnfyXfR48eRXZ2NlJTU+vE6Kh81+jcuXOT+jniPGcBQkREEp1Oh7y8vBbZlkajQUVFhd06g8EAd3d3qd1gMNRp9/X1bfa+Gos7JycH77//Pqqrq6V9V1dXAwA8PDwa3OaWLVukCei1zZw50+5zUlIS0tPT8eOPP/6lwXBLxj5s2DAMGzZM+hweHo5p06Zhx44dmDlzZpvP+ZkzZ/DCCy/Az88P69evl/q2dM5rc3Nzk2KrUfO5JvYaDeXvduf0rdtpKc2Jvcbx48cxZ84cREVFYenSpVAobg4F582bZ9dvxowZ2Lp1K/bt24eUlBSnxT1hwgRMmDBB+jx8+HBMmDABO3fuRHx8vENz/lfy/fXXXyM+Pr7O4N+R+W4uR5znvAWLiIhaRXBwME6fPm23rqCgAEFBQQCAoKCgRttbSp8+faBUKlFQUCCtKywslG4baMiuXbvw4IMP1lm/du1aHDx40G6dyWSCWq1usZhrNDf2n376CV999VWd2FxdXQG07Zzv27cPDz30EGJjY7F27Vp4e3tLba2Z86CgIFy/fh2lpaV2sQYEBMDT09Oub3PPabPZjLNnz9a5naWlNCd2ANi8eTOmT5+OadOm4d1334VKpZLaVq5ciZycHLv+rXVeNyfuzZs3Y+fOnQ3G5cicNzffFosFP//8s90tnDUcme/mcsR5zgKEiIhaxZgxY1BaWop169bBbDYjMzMT27Ztw6RJkwAAkydPxrZt25CZmQmz2Yx169ahrKwMY8aMadE4NBoN4uPjkZqaiqtXr+Lq1atITU1FYmKiNDC/1bVr11BYWIjBgwfXabt8+TIWLlyI8+fPw2KxYPPmzcjKysLEiRNbNO6/ErsQAkuXLsXBgwchhEBWVhbWr1+PKVOmAGi7OT9+/DieffZZzJ8/H6+++qr0V/karZnz3r17Y9CgQViyZAkqKytx/vx5fPTRR5g8eXKdvklJSTh8+DB27NgBi8WCHTt24PDhw1KhOmnSJKSlpSE3NxdGoxHvvvsu/P397e79b0nNif3HH3/EW2+9hVWrVuHJJ5+s056fn4/FixejpKQEJpMJq1evRmVlZYufG82Nu7KyEosWLUJOTg5sNhv27t2L9PR06Zx2ZM6bEzcA5OXlwWg04t57763T5sh8N5dDzvNmT6EnIiISQsTFxdV5Ctb48ePtno7y+++/iylTpojIyEhx//331+n/3XffiXHjxgmtVismT54sjh8/3iqxVlRUiAULFoihQ4eKwYMHi3nz5omqqqpG4w4ODhbV1dV1tmU0GsXixYvF8OHDRUREhJg0aVKDT5NxRuxffvmlGDt2rIiIiBD333+/SEtLs9teW8z5rFmzRL9+/YRWq7X7mTFjhhCi9XNeUlIinn/+eREdHS2GDBkili1bJiwWixBCCK1Wa/cUtP3794ukpCSh1WpFQkKC2Lt3r9Rms9nE2rVrxahRo4RWqxVTp04VZ86cabE47yT2xMREERISUifHr7/+uhBCiGvXrol58+aJmJgYKfZTp045PW6bzSY+/PBDERcXJ8LDw0VCQoLYuXOntB1H57w558rOnTtFTExMvdtxdL5vdetTsBx9nsuEEKKVCigiIiIiIiI7vAWLiIiIiIgchgUIERERERE5DAsQIiIiIiJyGBYgRERERETkMCxAiIiIiIjIYViAEBERERGRw7AAISIiInKQs2fPOjsEIqdT3L4LERER0d/HqFGjUFJSUueN6wCwZs0a+Pj44LnnnkNxcTFSUlLQv39/LFq0CCaTCampqYiLi/tL+83JycHDDz+MkydP3ukhELVrLECIiIiow1m4cCGSk5Prbfv444/h6uqKo0ePQi6X44knnkBCQgIWLFhwR/usqKiA2Wy+o20Q/R3wFiwiIiKi/7ds2TJ8+OGHyMvLQ1RUFKKjo5GZmYmvvvoKo0ePBgAUFRXhmWeegU6nQ1xcHFauXAmTySRtY9u2bUhMTERkZCTi4+OxY8cOnD9/Hk899RQAIDIyEllZWU45PqK2gAUIERER0f+bN28eZs2ahaioKGRlZeHw4cOIiorCrFmz8NNPP0Gv12P69OkICgrC/v37sXHjRhw4cACrVq0CABw6dAivvfYaXn75Zfz222+YP38+XnnlFRiNRqxZswYAkJWVhcjISGceJpFTsQAhIiKiDmfhwoWIioqy+3nggQdu+729e/fCZDJh7ty5UKvV6Nq1K+bMmYMNGzYAAL777juMHTsWI0eOhIuLC0aMGIGNGzeiS5curX1IRO0G54AQERFRh/Pmm282OAekMRcvXsTVq1cxePBgaZ0QAmazGWVlZfjzzz8xYMAAu++Eh4ffcbxEfycsQIiIiIiaKCAgAL169UJGRoa0rrKyEmVlZejUqRO6du2KS5cu2X3nP//5D7RarYMjJWq7eAsWERERURPFxcWhqqoKn332GUwmE8rLy/Hqq6/ixRdfhEwmw8SJE7F79278+uuvsNls+OWXX7Bq1Sp4enpCrVYDuPk0LKKOjFdAiIiIqMN58803sWjRojrrZ8+e3ej3PDw8sG7dOixbtgyfffYZbDYbdDodPv74YwDAoEGDsHz5cixfvhwXL15E9+7dsWLFCgQFBUGv12PQoEGIjY3F+++/j5EjR7bKsRG1dTIhhHB2EERERERE1DHwFiwiIiIiInIYFiBEREREROQwLECIiIiIiMhhWIAQEREREZHDsAAhIiIiIiKHYQFCREREREQOwwKEiIiIiIgchgUIERERERE5DAsQIiIiIiJyGBYgRERERETkMCxAiIiIiIjIYViAEBERERGRw/wfF//UIY71pvIAAAAASUVORK5CYII=",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tasccoda_model.plot_draw_effects(\n",
    "    smillie_data,\n",
    "    modality_key=\"coda_LP\",\n",
    "    tree=smillie_data[\"coda_LP\"].uns[\"tree\"],\n",
    "    covariate=\"Health[T.Non-inflamed]\",\n",
    "    show_legend=False,\n",
    "    show_leaf_effects=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## References"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Ostner, J., Carcy, S., Müller, C.L. tascCODA: Bayesian Tree-Aggregated Analysis of Compositional Amplicon and Single-Cell Data. Front. Genet. 12, (2021). https://doi.org/10.3389/fgene.2021.766405\n",
    "2. Smillie, C.S., Biton, M., Ordovas-Montanes, J. et al. Intra- and Inter-cellular Rewiring of the Human Colon during Ulcerative Colitis. Cell 178, 714–730.e22 (2019). https://doi.org/10.1016/j.cell.2019.06.029"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.1.-1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}