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). 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.\n",
    "\n",
    "This tutorial is designed to be executed on a standard computer (any operating system) in a Python environment with tascCODA, Jupyter notebook and all their dependencies installed. Running the tutorial takes about 8 minutes on a 2020 Apple MacBook Pro (16GB RAM)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": 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: #808000; text-decoration-color: #808000; font-weight: bold\">Installed version </span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">0.4</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">0</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> of pertpy is newer than the latest release </span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">0.3</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">0</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">! You are running a nightly version and </span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">features may break!</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1;33mInstalled version \u001b[0m\u001b[1;33m0.4\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m0\u001b[0m\u001b[1;33m of pertpy is newer than the latest release \u001b[0m\u001b[1;33m0.3\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m0\u001b[0m\u001b[1;33m! You are running a nightly version and \u001b[0m\n",
       "\u001b[1;33mfeatures may break!\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import anndata as ad\n",
    "\n",
    "import pertpy as pt\n",
    "\n",
    "import importlib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data setup\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": 2,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": 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>NAME</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>0</th>\n",
       "      <td>N10.EpiA.AAACATACAACCAC</td>\n",
       "      <td>N10</td>\n",
       "      <td>EpiA</td>\n",
       "      <td>Epi</td>\n",
       "      <td>A</td>\n",
       "      <td>Healthy</td>\n",
       "      <td>Enterocyte Progenitors</td>\n",
       "      <td>425</td>\n",
       "      <td>968</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Absorptive</td>\n",
       "      <td>Immature cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>N10.EpiA.AAACATACAGGCGA</td>\n",
       "      <td>N10</td>\n",
       "      <td>EpiA</td>\n",
       "      <td>Epi</td>\n",
       "      <td>A</td>\n",
       "      <td>Healthy</td>\n",
       "      <td>Cycling TA</td>\n",
       "      <td>1695</td>\n",
       "      <td>7273</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Cycling TA3</td>\n",
       "      <td>Cycling TA4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>N10.EpiA.AAACATACCACTAG</td>\n",
       "      <td>N10</td>\n",
       "      <td>EpiA</td>\n",
       "      <td>Epi</td>\n",
       "      <td>A</td>\n",
       "      <td>Healthy</td>\n",
       "      <td>Immature Goblet</td>\n",
       "      <td>391</td>\n",
       "      <td>1190</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Secretory</td>\n",
       "      <td>Progenitor cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>N10.EpiA.AAACATACCCTTTA</td>\n",
       "      <td>N10</td>\n",
       "      <td>EpiA</td>\n",
       "      <td>Epi</td>\n",
       "      <td>A</td>\n",
       "      <td>Healthy</td>\n",
       "      <td>Secretory TA</td>\n",
       "      <td>1327</td>\n",
       "      <td>5620</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Secretory</td>\n",
       "      <td>Progenitor cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>N10.EpiA.AAACATACTGCAAC</td>\n",
       "      <td>N10</td>\n",
       "      <td>EpiA</td>\n",
       "      <td>Epi</td>\n",
       "      <td>A</td>\n",
       "      <td>Healthy</td>\n",
       "      <td>Immature Enterocytes 2</td>\n",
       "      <td>1383</td>\n",
       "      <td>4676</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Absorptive</td>\n",
       "      <td>Immature cells</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>365487</th>\n",
       "      <td>N9.LPB.TTTATCCTAACGAA</td>\n",
       "      <td>N9</td>\n",
       "      <td>LPB</td>\n",
       "      <td>LP</td>\n",
       "      <td>B</td>\n",
       "      <td>Inflamed</td>\n",
       "      <td>Enterocytes</td>\n",
       "      <td>2768</td>\n",
       "      <td>18811</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Epithelial</td>\n",
       "      <td>Absorptive</td>\n",
       "      <td>Absorptive Mature cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365488</th>\n",
       "      <td>N9.LPB.TTTATCCTGTAAAG</td>\n",
       "      <td>N9</td>\n",
       "      <td>LPB</td>\n",
       "      <td>LP</td>\n",
       "      <td>B</td>\n",
       "      <td>Inflamed</td>\n",
       "      <td>Plasma</td>\n",
       "      <td>1392</td>\n",
       "      <td>27685</td>\n",
       "      <td>Immune</td>\n",
       "      <td>Lymphoid</td>\n",
       "      <td>B cells</td>\n",
       "      <td>Plasma4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365489</th>\n",
       "      <td>N9.LPB.TTTATCCTGTCGTA</td>\n",
       "      <td>N9</td>\n",
       "      <td>LPB</td>\n",
       "      <td>LP</td>\n",
       "      <td>B</td>\n",
       "      <td>Inflamed</td>\n",
       "      <td>Plasma</td>\n",
       "      <td>574</td>\n",
       "      <td>5478</td>\n",
       "      <td>Immune</td>\n",
       "      <td>Lymphoid</td>\n",
       "      <td>B cells</td>\n",
       "      <td>Plasma4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365490</th>\n",
       "      <td>N9.LPB.TTTCAGTGGCGTTA</td>\n",
       "      <td>N9</td>\n",
       "      <td>LPB</td>\n",
       "      <td>LP</td>\n",
       "      <td>B</td>\n",
       "      <td>Inflamed</td>\n",
       "      <td>Macrophages</td>\n",
       "      <td>1437</td>\n",
       "      <td>5698</td>\n",
       "      <td>Immune</td>\n",
       "      <td>Myeloid</td>\n",
       "      <td>Monocytes</td>\n",
       "      <td>Macrophages4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365491</th>\n",
       "      <td>N9.LPB.TTTGCATGGATACC</td>\n",
       "      <td>N9</td>\n",
       "      <td>LPB</td>\n",
       "      <td>LP</td>\n",
       "      <td>B</td>\n",
       "      <td>Inflamed</td>\n",
       "      <td>CD8+ LP</td>\n",
       "      <td>544</td>\n",
       "      <td>1348</td>\n",
       "      <td>Immune</td>\n",
       "      <td>Lymphoid</td>\n",
       "      <td>T cells</td>\n",
       "      <td>CD8+ T</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>365492 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           NAME Subject Sample Location Replicate    Health  \\\n",
       "0       N10.EpiA.AAACATACAACCAC     N10   EpiA      Epi         A   Healthy   \n",
       "1       N10.EpiA.AAACATACAGGCGA     N10   EpiA      Epi         A   Healthy   \n",
       "2       N10.EpiA.AAACATACCACTAG     N10   EpiA      Epi         A   Healthy   \n",
       "3       N10.EpiA.AAACATACCCTTTA     N10   EpiA      Epi         A   Healthy   \n",
       "4       N10.EpiA.AAACATACTGCAAC     N10   EpiA      Epi         A   Healthy   \n",
       "...                         ...     ...    ...      ...       ...       ...   \n",
       "365487    N9.LPB.TTTATCCTAACGAA      N9    LPB       LP         B  Inflamed   \n",
       "365488    N9.LPB.TTTATCCTGTAAAG      N9    LPB       LP         B  Inflamed   \n",
       "365489    N9.LPB.TTTATCCTGTCGTA      N9    LPB       LP         B  Inflamed   \n",
       "365490    N9.LPB.TTTCAGTGGCGTTA      N9    LPB       LP         B  Inflamed   \n",
       "365491    N9.LPB.TTTGCATGGATACC      N9    LPB       LP         B  Inflamed   \n",
       "\n",
       "                       Cluster  nGene   nUMI    Major_l1    Major_l2  \\\n",
       "0       Enterocyte Progenitors    425    968  Epithelial  Epithelial   \n",
       "1                   Cycling TA   1695   7273  Epithelial  Epithelial   \n",
       "2              Immature Goblet    391   1190  Epithelial  Epithelial   \n",
       "3                 Secretory TA   1327   5620  Epithelial  Epithelial   \n",
       "4       Immature Enterocytes 2   1383   4676  Epithelial  Epithelial   \n",
       "...                        ...    ...    ...         ...         ...   \n",
       "365487             Enterocytes   2768  18811  Epithelial  Epithelial   \n",
       "365488                  Plasma   1392  27685      Immune    Lymphoid   \n",
       "365489                  Plasma    574   5478      Immune    Lymphoid   \n",
       "365490             Macrophages   1437   5698      Immune     Myeloid   \n",
       "365491                 CD8+ LP    544   1348      Immune    Lymphoid   \n",
       "\n",
       "           Major_l3                 Major_l4  \n",
       "0        Absorptive           Immature cells  \n",
       "1       Cycling TA3              Cycling TA4  \n",
       "2         Secretory         Progenitor cells  \n",
       "3         Secretory         Progenitor cells  \n",
       "4        Absorptive           Immature cells  \n",
       "...             ...                      ...  \n",
       "365487   Absorptive  Absorptive Mature cells  \n",
       "365488      B cells                  Plasma4  \n",
       "365489      B cells                  Plasma4  \n",
       "365490    Monocytes             Macrophages4  \n",
       "365491      T cells                   CD8+ T  \n",
       "\n",
       "[365492 rows x 13 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smillie_counts = ad.read_h5ad(\"data/smillie_data.h5ad\")\n",
    "smillie_counts.obs"
   ]
  },
  {
   "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": 3,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>MuData object with n_obs × n_vars = 365625 × 51\n",
       "  2 modalities\n",
       "    rna:\t365492 x 0\n",
       "      obs:\t&#x27;NAME&#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 × 51\n",
       "  2 modalities\n",
       "    rna:\t365492 x 0\n",
       "      obs:\t'NAME', '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": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tasccoda_model = pt.tl.Tasccoda()\n",
    "smillie_data = tasccoda_model.load(smillie_counts, type=\"cell_level\", cell_type_identifier=\"Cluster\", sample_identifier=[\"Subject\", \"Sample\"], covariate_obs=[\"Location\", \"Health\"], levels_orig=[\"Major_l1\", \"Major_l2\", \"Major_l3\", \"Major_l4\", \"Cluster\"], add_level_name=True)\n",
    "smillie_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also visualize the tree:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt.pl.coda.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": 5,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>MuData object with n_obs × n_vars = 365625 × 51\n",
       "  3 modalities\n",
       "    rna:\t365492 x 0\n",
       "      obs:\t&#x27;NAME&#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 × 51\n",
       "  3 modalities\n",
       "    rna:\t365492 x 0\n",
       "      obs:\t'NAME', '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": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smillie_data.mod[\"coda_LP\"] = smillie_data[\"coda\"][(smillie_data[\"coda\"].obs[\"Health\"].isin([\"Healthy\", \"Non-inflamed\"])) & (smillie_data[\"coda\"].obs[\"Location\"] == \"LP\")]\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": 6,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAB8YAAAMWCAYAAACDduxsAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzde5xcdX0//vfsZi8JFyOGi9UgPhClkYoxwfWCUAitVQHXLIIlCqFfEM3PC0IjoLZAQBKjQA2UilIMlCBUNo1gEa0gF9syCGIVjAQpIgUVCSBskt2dJPP7A3fZ3cxuZmdn5pw5+3w+HnlkZ/bszHtmzsyc83l9LrlisVgMAAAAAAAAAMiopqQLAAAAAAAAAIBaEowDAAAAAAAAkGmCcQAAAAAAAAAyTTAOAAAAAAAAQKYJxgEAAAAAAADINME4AAAAAAAAAJkmGAcAAAAAAAAg0wTjAAAAAAAAAGTalKQLqLWtW7fGk08+GTvssEPkcrmkywEAAAAAAABGUSwWY8OGDbHbbrtFU5MxvlRP5oPxJ598Mg4++OCkywAAAAAAAADKdPvtt8cee+yRdBlkSGLB+Pr16+Pv/u7v4u67747m5uY48sgj4/TTT48pU7Yt6e67744vfvGL8ctf/jJ23nnnOPbYY+Pkk08u63522GGHiHjhzbPjjjtW9TEAAAAAAAAA1dPT0xMHH3zwYMYH1ZJYMH7KKafE7rvvHnfeeWc89dRT8dGPfjRWrlwZJ5544rDtHn744fjwhz8cZ511VnR2dsaDDz4Yxx9/fLzqVa+Kv/qrv9ru/QxMn77jjjsKxgEAAAAAAKABWCKZaktkYv5HH3007r777li8eHFMnTo1Zs6cGYsWLYpVq1Zts+0111wT8+bNi/e9732Ry+Vi3333jWuvvTbmzJmTQOUAAAAAAAAANJpEgvGHHnoopk+fHrvvvvvgdXvvvXc88cQT8dxzzw3b9qc//Wm88pWvjFNPPTU6OjriXe96V9x9992x66671rtsAAAAAAAAABpQIsH4hg0bYurUqcOuG7i8cePGYdf/4Q9/iKuuuiqOPPLI+M///M9YsmRJfOELX4ibb7655G339/dHT0/PsH8AAAAAAAAATF6JrDE+bdq02LRp07DrBi7vsMMOw65vbW2NefPmxZ//+Z9HRMQBBxwQ733ve+M73/lOyTXGL7vssrjkkktqUzgAAAAAAACQuC1btkShUEi6DBLU0tISzc3NZW+fSDC+zz77xLPPPhtPPfVUzJgxIyIiHn744dhjjz1ip512Grbt3nvvHf39/cOu27JlSxSLxZK3ffLJJ8cJJ5wweLmnpycOPvjgKj8CAAAAAAAAoN6KxWL89re/jWeffTbpUkiB6dOnxx577BG5XG672yYSjO+1114xZ86cOP/882PJkiXxzDPPxKWXXhpHHXXUNtt+4AMfiBNPPDG+9a1vxZFHHhn33HNP3HjjjfGlL32p5G23trZGa2trrR8CAAAAAAAAUGcDofhuu+0W06ZNKysQJXuKxWJs3LgxnnzyyYiIePnLX77dv0kkGI+IWLFiRSxZsiTmzZsXTU1N0dnZGYsWLYqIiNmzZ8c555wTRx55ZLz1rW+NSy+9NFasWBHnnHNO7LLLLnH66afHvHnzkiodAAAAAAAAqLMtW7YMhuIve9nLki6HhE2dOjUiIp588snYbbfdtjutemLB+IwZM2LFihUlf3ffffcNu3zwwQebDh0AAAAAAAAmsYE1xadNm5ZwJaTFwL5QKBS2G4w31aMgAAAAAAAAgGowfToDxrMvCMYBAAAAAAAAMuhXv/pV0iWkhmAcAAAAAAAAoA4OPfTQWL169TbXr169Og499NAJ3/4ZZ5wRZ5xxRkRE/PznP4/DDz+85O8mI8E4AAAAAAAAQMY8//zzg+uyIxgHAAAAAAAASI1f//rX8ZGPfCQ6OjrikEMOiYsuuij6+/sjIqJYLMZXv/rVOOKII2Lu3LlxwAEHxGmnnRa9vb3DbuOxxx6Lk046KSIiZs+eHffdd19ERKxfvz4+8YlPREdHRxx44IFx9dVX1/fBJUgwDgAAAAAAAFAn55xzTsydO3fYv3POOSciIjZu3BgLFy6MffbZJ+6444645ppr4r/+67/i4osvjoiI73znO3HVVVfFxRdfHPfcc09ce+218cMf/jBuvPHGYfcxc+bM+NrXvhYREffdd1/Mnj07IiLuuuuu+MAHPhB33XVXnHbaaXHeeefF7373uzo++uQIxgEAAAAAAADq5Kyzzop77rln2L+zzjorIiJuu+226O/vj1NPPTXa2tri5S9/eXzyk5+MVatWRUTEQQcdFNdff33stdde8fTTT8czzzwT06dPLzvcfvvb3x5ve9vbIpfLxXve854oFovx2GOP1eyxpsmUpAsAAAAAAAAAIOLxxx+Pp59+Og444IDB64rFYhQKhVi/fn20trbGRRddFD/4wQ9il112iT/90z+NQqEQxWKxrNufPn364M+tra0REbFly5aqPoa0EowDAAAAAAAApMAee+wRe+65Z9x8882D1/X09MT69etjl112ibPPPjueeOKJuPXWW2PHHXeMiIgjjjgiqXIbiqnUAQAAAAAAAFLgkEMOiQ0bNsTll18e/f398dxzz8Xpp58en/rUpyKXy0VPT0+0tbVFc3Nz9PX1xRVXXBHr1q2LQqGwzW21tbVFRMTzzz9f74eRSoJxAAAAAAAAgBTYcccdY+XKlZHP5+Oggw6Kww47LJqamuKf/umfIiLilFNOid7e3njb294Whx56aPzkJz+J9773vbFu3bptbuu1r31tzJkzJ97xjnfE7bffXu+Hkjq5YrkTzjeonp6emDNnTtx7772D0wkAAAAAAAAA6TNWttfb2xuPPPJIvPrVr4729vaEKiRNxrNPGDEOAAAAAAAAQKYJxgEAAAAAAADItClJFwAAAAAAkCbFYjH6+voGf46IyOVyg79va2sbdhkAgPQTjAMAAAAA/FGxWIzFixfH2rVrR91m1qxZsXz5cuE4AEADMZU6AAAAAMAQAm8AgOwxYhwAAAAA4I9yuVwsX748+vr6ore3NxYsWBAREatWrYr29vaIMJU6AEAjEowDAAAAAAyRy+UGQ/AB7e3t21wHAEDjEIwDAAAAAAAADW3Lli1RLBbrcl+5XC6am5vrcl9Uj2AcAAAAAAAAaFhbtmyJhQtPiKefXl+X+9tll5fFypVfT3U4/qtf/Sr22muvpMtIFcE4AAAAAAAA0LCKxWI8/fT6OPHvL4ymGofVW7dsicuXnDru0emHHnpofOxjH4v58+cPu3716tVxySWXxK233jqhus4444yIiFi2bFn8/Oc/j6OPPjruv//+bX43mQnGAQAAAAAAgIbX1Nyc6lHc9fL8889HoVBIuozUaUq6AAAAAAAAAIDJ7te//nV85CMfiY6OjjjkkEPioosuiv7+/oh4YVT8V7/61TjiiCNi7ty5ccABB8Rpp50Wvb29w27jsccei5NOOikiImbPnh333XdfRESsX78+PvGJT0RHR0cceOCBcfXVV0dExL//+7/HnDlzoq+vb/A2br755jjkkEPqtmZ7vQjGAQAAAAAAAGrsnHPOiblz5w77d84550RExMaNG2PhwoWxzz77xB133BHXXHNN/Nd//VdcfPHFERHxne98J6666qq4+OKL45577olrr702fvjDH8aNN9447D5mzpwZX/va1yIi4r777ovZs2dHRMRdd90VH/jAB+Kuu+6K0047Lc4777z43e9+F3/xF38Rzc3Nccsttwzexpo1a+J973tf5HK5ejwtdSMYBwAAAAAAAKixs846K+65555h/84666yIiLjtttuiv78/Tj311Ghra4uXv/zl8clPfjJWrVoVEREHHXRQXH/99bHXXnvF008/Hc8880xMnz49fve735V1329/+9vjbW97W+RyuXjPe94TxWIxHnvssWhtbY3DDz88vvWtb0XECyPLf/jDH8b73ve+2jwJCbLGOAAAAAAAAECCHn/88Xj66afjgAMOGLyuWCxGoVCI9evXR2tra1x00UXxgx/8IHbZZZf40z/90ygUCmVPdz59+vTBn1tbWyMiYsuWLRERMX/+/DjmmGNi/fr1ccMNN8Sb3vSmmDlzZvUeXEoIxgEAAAAAAAAStMcee8See+4ZN9988+B1PT09sX79+thll13i7LPPjieeeCJuvfXW2HHHHSMi4ogjjqjKfe+3337xmte8Jr773e/Gv//7v8eHPvShqtxu2phKHQAAAAAAACBBhxxySGzYsCEuv/zy6O/vj+eeey5OP/30+NSnPhW5XC56enqira0tmpubo6+vL6644opYt25dFAqFbW6rra0tIiKef/75su9//vz58a//+q/xq1/9Kv7yL/+yao8rTQTjAAAAAAAAQMPbumVLbKnxv61/nH682nbcccdYuXJl5PP5OOigg+Kwww6Lpqam+Kd/+qeIiDjllFOit7c33va2t8Whhx4aP/nJT+K9731vrFu3bpvbeu1rXxtz5syJd7zjHXH77beXdf9HHHFE/PKXv4x3v/vdMXXq1Ko+trTIFcudeL5B9fT0xJw5c+Lee+8dnFYAAAAAAGB7ent7o6urKyIiuru7o729PeGKACD7xsr2ent745FHHolXv/rVw76Xt2zZEgsXnhBPP72+LjXussvLYuXKr0dzc3Nd7q8etmzZEgceeGB85Stfif333z/pcso22j5RijXGAQAAAAAAgIbV3NwcK1d+Peo1HjiXy2UqFH/ooYfiO9/5Tuyxxx4NFYqPl2AcAAAAAAAAaGhZCqrr7eSTT46IiBUrViRcSW0JxgEAAAAAAAAmqVtvvTXpEuqiKekCAAAAAAAAAKCWBOMAAAAAAAAAZJpgHAAAAAAAAIBME4wDAAAAAAAAkGmCcQAAAAAAAAAybUrSBQAAAAAAAABMxJYtW6JYLNblvnK5XDQ3N9flvqgewTgAAAAAAADQsLZs2RIfOm5h/OHZp+tyfy+Zvkv8y1UrheMNRjAOAAAAAAAANKxisRh/ePbp2NpxQkSuxitJF7fGH/JfH/fo9Ne97nVx8MEHx2WXXRa5XG7w+tWrV8cll1wSt956a7UrjYiI2bNnx9e+9rWYO3fudre96aab4txzz43+/v741Kc+Feeee27ccsst8cpXvrImtZWrWs+RNcYBAAAAAACAxpdrimiq8b8JBO+33357XH755VV8wNt33333lRWKR0R885vfjPe85z1x7733xp//+Z/XtrAECMYBAAAAAAAAauxDH/pQfPnLX44f//jHo27z4IMPxkknnRRvfvOb46CDDoqzzz47nn/++Yh4YeT0X//1X8d5550Xb3nLW+Ktb31rfPazn41CoTDq7b3uda+LfD4fERGHHnpoXHbZZdHZ2RmzZ8+Ozs7OuOuuuyIi4qijjoq77rorrr322jjssMO2uZ0f//jHcdxxx8WBBx4Yf/Znfxbz58+Pn/zkJxERkc/n49BDD43LL7883v72t8ecOXPiwgsvjFtuuSXe+c53xuzZs+PjH/949Pf3R0REf39/fPnLX4558+bFm9/85jjppJPi0UcfHbyvhx9+OD70oQ/F7Nmz44gjjoif//zn43uiRyEYBwAAAAAAAKixv/iLv4hjjjkmTj311Hj22We3+f0zzzwTxx13XLzmNa+JO+64I7q7u+ORRx6JT3/604Pb/PjHP46Xvexlceedd8Zll10WN910U3zve98ru4bu7u748pe/HP/1X/8V++67b5x99tkREXH99dfH3Llz4+STT47vf//7w/6mt7c3PvrRj8Y73/nOuOOOOyKfz8eee+4Zy5cvH9zm8ccfj9///vdx2223xYUXXhiXXXZZrFq1Kv71X/81brjhhsjn83HTTTdFRMRFF10Ut912W6xcuTLuvPPO2H///eNv/uZvoq+vLwqFQpx88smxzz77xF133RUXXnjhNvVUSjAOAAAAAAAAUAenn3567LLLLnHGGWdss075LbfcEi0tLfG3f/u30d7eHrvuumv83d/9Xdx6663x+9//PiIi2tvb4yMf+Ui0tLTEG97whnjd614XjzzySNn3f9RRR8WrXvWqmDp1ahxxxBHxq1/9art/09LSEtddd10ce+yx0d/fH48//nhMnz49fve73w3b7uSTT46WlpY48MADIyLir//6r+MlL3lJzJw5M/bZZ5/4v//7vygWi3HttdfGqaeeGjNnzoy2trb4//6//y8KhULcdtttcd9998VvfvOb+PSnPx1tbW2xzz77xAknnFD24xvLlKrcCgAAAAAAAABjam1tjX/4h3+I973vfXHFFVfES1/60sHfrV+/Pv7kT/4kmpubB6975StfGREvjMiOiHjZy14WuVxu8PctLS2DAfvs2bMHr58zZ07J9cxnzJgx+POUKVO2CedLaW5ujnw+HyeddFJs3LgxXvOa15T824HHMlD/zjvvPPi7pqamKBaL8fTTT8fGjRvjk5/8ZDQ1vTiGu1AoxOOPPx79/f3x0pe+NNrb2wd/t+eee263xnIIxgEAAAAAAADqZM8994xzzz03Pv3pT8f8+fMHr3/FK14RTzzxRGzZsmUwXP71r38dERG77rpr/O///u+Yt3vffffVpN7/+Z//iXPPPTeuvfba2G+//SIi4oorrthmpPrQwH40L33pS6OtrS2uuOKKeOMb3zh4/f/+7//G7rvvHmvXro2nn346NmzYEDvssENERPz2t7+tyuMwlToAAAAAAABAHb373e+Orq6uuO666wavO/jggyMi4ktf+lL09vbG73//+/j85z8fb3nLW+IVr3hFUqXG888/H01NTYOjuH/yk5/EVVddFf39/eO+raampjjqqKPiggsuiN/+9rexdevW+Ld/+7c4/PDD49FHH43Zs2fHq1/96jjvvPNi06ZN8eijj8YVV1xRlcchGAcAAAAAAAAaX3FrxNYa/yturVq5n/nMZ+JP//RPBy/vtNNO8fWvfz3WrVsXBx98cBx++OHxile8Ir785S9X7T4r8fa3vz2OPfbYWLBgQRxwwAFxzjnnxIc+9KF4+umn46mnnhr37Z1++umx//77x7HHHhtz586NlStXxooVK2LWrFnR3NwcX/3qV+PJJ5+Mt73tbXHiiSfGvHnzqvI4csVyJo5vYD09PTFnzpy49957Y8cdd0y6HAAAAACgQfT29kZXV1dERHR3dw9b6xIAqI2xsr3e3t545JFH4tWvfvWw7+UtW7bEh45bGH949um61PiS6bvEv1y1ctha4CRjtH2iFGuMAwAAAAAAAA2rubk5/uWqlVGv8cC5XE4o3oBMpQ4AAAAAAERERD6fj87Ozsjn80mXAjAuzc3NMWXKlLr8E4o3JsE4AAAAAAAQES8sG1AoFGL16tVJlwIAVSUYBwAAAAAAIiKiq6srWlpaYv78+UmXAgBVZY1xAAAAAAAgIiI6OjpizZo1SZcBAFVnxDgAAAAAAADQMLZu3Zp0CaTEePYFI8YBAAAAAACA1GttbY2mpqZ44oknYtddd43W1tbI5XJJl0UCisVi9Pf3x+9///toamqK1tbW7f6NYBwAAAAAAABIvaampnj1q18dv/nNb+KJJ55IuhxSYNq0abHnnntGU9P2J0oXjAMAAAAAAAANobW1Nfbcc8/YvHlzbNmyJelySFBzc3NMmTKl7FkDBOMAAAAAAABAw8jlctHS0hItLS1Jl0ID2f6YcgAAAAAAAABoYIJxAAAAAAAAADJNMA4AAAAAAABApgnGAQAAAAAAAMg0wTgAAAAAAAAAmSYYBwAAAAAAACDTBOMAAAAAAAAAZJpgHAAAAAAAAIBME4wDAAAAAAAAkGmCcQAAAAAAAAAyTTAOAAAAAAAAQKYJxgEAAAAAAADINME4AAAAAAAAAJkmGAcAAAAAAAAg0wTjAAAAAAAAAGSaYBwAAAAAAACATBOMAwAAAAAAAJBpgnEAAAAAAAAAMk0wDgAAAAAAAECmCcYBAAAAAAAAyDTBOAAAAAAAAACZJhgHAAAAAAAAINMSC8bXr18fixYtirlz50ZHR0d8/vOfj82bN5fc9sQTT4w/+7M/i9mzZw/+u+OOO+pcMQAAAAAAAACNaEpSd3zKKafE7rvvHnfeeWc89dRT8dGPfjRWrlwZJ5544jbb3n///fHP//zP8eY3vzmBSgEAAAAAAABoZImMGH/00Ufj7rvvjsWLF8fUqVNj5syZsWjRoli1atU22z722GPxhz/8IWbNmpVApQAAAAAAAAA0ukSC8YceeiimT58eu+++++B1e++9dzzxxBPx3HPPDdv2Zz/7Weywww7xqU99Kt7ylrfE4YcfHtdff329SwYAAAAAAACgQSUylfqGDRti6tSpw64buLxx48bYeeedB6/v7++PN77xjfGpT30q9tlnn8jn8/Hxj388dthhh3jXu961zW339/dHf3//4OWenp4aPQoAAAAAAAAAGkEiwfi0adNi06ZNw64buLzDDjsMu76zszM6OzsHLx944IHR2dkZ3/nOd0oG45dddllccskl1S8aAAAAAAAAgIaUSDC+zz77xLPPPhtPPfVUzJgxIyIiHn744dhjjz1ip512Grbt9ddfv83o8P7+/mhrayt52yeffHKccMIJg5d7enri4IMPrsGjAAAAAAAAAKARJLLG+F577RVz5syJ888/P3p6euKxxx6LSy+9NI466qhttu3p6Ylzzz03fv7zn8fWrVvjtttui29/+9txzDHHlLzt1tbW2HHHHYf9AwAAAAAAAGDySmTEeETEihUrYsmSJTFv3rxoamqKzs7OWLRoUUREzJ49O84555w48sgj4/jjj4+NGzfGxz72sVi/fn3MnDkzvvCFL8TcuXOTKh0AAAAAAACABpJYMD5jxoxYsWJFyd/dd999gz/ncrlYtGjRYGgOAAAAAAAAAOORyFTqAAAAAAAAAFAvgnEAAAAAAAAAMk0wDgAAAAAAAECmCcYBAAAAAAAAyDTBOAAAAAAAAACZJhgHAAAAAAAAINME4wAAAAAAAABkmmAcAAAAAKDK8vl8dHZ2Rj6fT7oUAABCMA4AAAAAUHXd3d1RKBRi9erVSZcCAEAIxgEAAAAAqq6rqytaWlpi/vz5SZcCAEBETEm6AAAAAACArOno6Ig1a9YkXQYAAH9kxDgAAAAAAAAAmSYYBwAAAAAAACDTBOMAAAAAAAAAZJpgHAAAAAAAAIBME4wDAAAAAAAAkGmCcQAAAAAAAAAyTTAOAAAAAAAAQKYJxgEAAAAAAADINME4AAAAAAAAAJkmGAcAAAAAAAAg0wTjAAAAAAAAAGSaYBwAAAAAAACATBOMAwAAAAAAAJBpgnEAAAAAAAAAMk0wDgAAAAAAAECmTUm6AAAAAACApBSLxejr6yv5u97e3pI/j9TW1ha5XK7qtQEAUD2CcQAAAABg0urr64uurq7tbrdgwYJRf9fd3R3t7e3VLAsAgCozlToAAAAAAAAAmWbEOAAAAABARBx/xtJoaW0ddl2xWIyI2Gaq9EJ/f1y57My61QYAwMQIxgEAAAAAIqKltTVaWtuSLgMAgBowlToAAAAAAAAAmSYYBwAAAAAAACDTTKUOAAAAAFAFxWIx+vr6Bn+OGL42eVtb2zZrlQMAUB+CcQAAAACACSoWi7F48eJYu3btqNvMmjUrli9fLhwHAEiAqdQBAAAAAKpA4A0AkF5GjAMAAAAATFAul4vly5dHX19f9Pb2xoIFCyIiYtWqVdHe3h4RplIHAEiSYBwAAAAAoApyudxgCD6gvb19m+sAAKg/U6kDAAAAAAAAkGmCcQAAAAAAAAAyTTAOAAAAAAAAQKYJxgEAAAAAAADINME4AAAAAAAAAJkmGAcAAAAAAAAg0wTjAAAAAAAAAGSaYBwAAAAAAACATBOMAwAAAAAAAJBpgnEAAAAAAAAAMk0wDgAAAAAAAECmCcYBAAAAAAAAyDTBOAAAAAAAAACZJhgHAAAAAAAAINME4wAAAAAAAABkmmAcAAAAAAAAgEwTjAMAAAAAAACQaYJxAAAAAAAAADJNMA4AAAAAAABApgnGAQAAAAAAAMg0wTgAAAAAAAAAmSYYBwAAAAAAACDTBOMAAAAAAAAAZJpgHAAAAAAAAIBME4wDAAAAAAAAkGmCcQAAAAAAAAAyTTAOAAAAAAAAQKYJxgEAAAAAAADINME4AAAAAAAAAJkmGAcAAAAAAAAg0wTjAAAAAAAAAGSaYBwAAAAAAACATBOMAwAAAAAAAJBpgnEAAAAAAAAAMk0wDgAAAAAAAECmCcYBAAAAAAAAyDTBOAAAAAAAAACZJhgHAAAAAAAAINME4wAAAAAAAABkmmAcAAAAAAAAgEwTjAMAAAAAAACQaYJxAAAAAAAAADJNMA4AAAAAAABApgnGAQAAAAAAAMg0wTgAAAAAAAAAmZZYML5+/fpYtGhRzJ07Nzo6OuLzn/98bN68ecy/WbduXey///6Rz+frVCUAAAAAAAAAjS6xYPyUU06JadOmxZ133hnXX399/Pd//3esXLly1O03bdoUp512WvT29tavSAAAAAAAAAAaXiLB+KOPPhp33313LF68OKZOnRozZ86MRYsWxapVq0b9m3POOScOO+ywOlYJAAAAAAAAQBYkEow/9NBDMX369Nh9990Hr9t7773jiSeeiOeee26b7desWROPPvpofOxjH6tnmQAAAAAAAABkwJQk7nTDhg0xderUYdcNXN64cWPsvPPOg9c//PDDcdFFF8U3vvGNaG5u3u5t9/f3R39//+Dlnp6eKlUNAAAAAAAAQCNKJBifNm1abNq0adh1A5d32GGHwev6+vriU5/6VHzmM5+JP/mTPynrti+77LK45JJLqlcsAAAAAAAAAA0tkanU99lnn3j22WfjqaeeGrzu4Ycfjj322CN22mmnwet+9rOfxa9+9av47Gc/G3Pnzo25c+dGRMRHPvKROPvss0ve9sknnxz33nvv4L/bb7+9po8FAAAAAAAAgHRLZMT4XnvtFXPmzInzzz8/lixZEs8880xceumlcdRRRw3bbu7cufHTn/502HWve93r4itf+Up0dHSUvO3W1tZobW2tWe0AAAAAAAAANJZERoxHRKxYsSI2b94c8+bNi6OPPjre8Y53xKJFiyIiYvbs2XHDDTckVRoAAAAAAAAAGZLIiPGIiBkzZsSKFStK/u6+++4b9e8efPDBWpUEAAAAAAAAQAYlNmIcAAAAAAAAAOpBMA4AAAAAAABApgnGAQAAAAAAAMg0wTgAAAAAAAAAmSYYBwAAAAAAACDTBOMAAMCo8vl8dHZ2Rj6fT7oUAAAAAKiYYBwAABhVd3d3FAqFWL16ddKlAAAAAEDFpiRdAAAAkF5dXV2xbt26mD9/ftKlAADUXKG/rybbAgCQPME4AAAwqo6OjlizZk3SZQAA1EyxWBz8+cpln5nwbQAAkE6mUgcAAAAAAAAg04wYBwAAAAAmrVwuN/jz8WecHy2tbWX9XaG/b3CE+dDbAAAgnQTjAAAAAAAR0dLaVnYwDgBAYzGVOgAAAAAAAACZJhgHAAAAAAAAINME4wAAAAAAAABkmmAcAAAAAAAAgEwTjAMAAAAAAACQaYJxAAAAAAAAADJNMA4AAAAAAABApgnGAQAAAAAAAMg0wTgAAAAAAAAAmSYYBwAAAAAAACDTBOMAAAAAAAAAZJpgHAAAAAAAAIBME4wDAAAAAAAAkGmCcQAAAAAAAAAyTTBOw8jn89HZ2Rn5fD7pUgAAAAAAAIAGIhinYXR3d0ehUIjVq1cnXQoAAAAAAADQQATjNIyurq5oaWmJ+fPnJ10KAAAAAAAA0ECmJF0AlKujoyPWrFmTdBkAAAAAAABAgzFiHAAAAAAAAIBME4wDAAAAAAAAkGmCcQAAAAAAAAAyTTAOAAAAAAAAQKYJxgEAAAAAAADINME4AAAAAAAAAJkmGAcAAAAAAAAg0wTjAAAAAAAAAGSaYBwAAAAAAACATBOMAwAAAAAAAJBpgnEAAAAAAAAAMk0wDgAAAAAAAECmCcYBAAAAAAAAyDTBOAAAAAAAAACZJhgHAAAAAAAAINME4wAAAAAAAABkmmAcAAAAAAAAgEwTjAMAAAAAAACQaYJxAAAAAAAAADJNMA4AAAAAAABApgnGAQAAAAAAAMg0wTgAAAAAAAAAmSYYBwAAAAAAACDTBOMAAAAAAAAAZJpgHAAAAAAAAIBME4wDAAAAAAAAkGmCcQAAAAAAAAAyTTAOAAAAAAAAQKYJxgEAAAAAAADINME4AAAAAAAAAJk2JekCAAAAAADSoNDfv811xWIxIiJyudx2twUAIL0E4wAAAAAAEXHlsjOTLgEAgBoxlToAAAAAAAAAmWbEOAAAAAAwabW1tUV3d3fJ3/X29saCBQsiImLVqlXR3t4+6m0AAJBugnEAAAAAYNLK5XKjBt5Dtbe3l7UdAADpZCp1AAAAAAAAADJNMA4AAAAAAABApgnGAQAAAAAAAMg0wTgAAAAAAAAAmTal0j988skn49e//nUUi8Vh1x9wwAETLgoAAAAAAAAAqqWiYPxf/uVfYtmyZbFly5Zh1+dyuVi7dm1VCgMAAAAAAACAaqgoGL/yyivj7//+76OrqyumTKl40DkAAAAAAAAA1FxFqfbTTz8d73//+6OpyRLlAAAAAAAAAKRbRcn2m9/85sjn89WuBQAAAAAAAACqrqIR47vvvnucfPLJ0dHRETNmzBj2u6VLl1alMAAAAAAAAACohoqC8f7+/njPe95T7VoAAAAAAAAAoOoqCsaNCgcAAAAAAACgUVS0xnhExJVXXhnvfve7Y//994/DDjssvvKVr0SxWKxmbQAAAAAAAAAwYRWNGL/yyivj61//enz4wx+OV77ylfHrX/86Lr/88mhqaooPf/jD1a4RAAAAAAAAACpWUTB+7bXXxqWXXhqzZs0avO5Nb3pTfPzjHxeMAwAAAAAAAJAqFU2l/uSTT8a+++477Lp99903nn322WrUBAAAAAAAAABVU1Ew/qpXvSr+4z/+Y9h1//Ef/xGvetWrqlIUAAAAAAAAAFRLRVOpL1q0KE455ZS4+eabY+bMmfHrX/86brnlllixYkW16wMAAAAAAACACaloxPhhhx0Wl19+ebS2tsYDDzwQO++8c6xatSoOOeSQsm9j/fr1sWjRopg7d250dHTE5z//+di8efM2223dujUuvvjiOPjgg2P27NlxxBFHxE033VRJ2QAAAAAAAABMQhWNGI+IeMtb3hJvectbKr7jU045JXbfffe4884746mnnoqPfvSjsXLlyjjxxBOHbbdq1apYs2ZN/Mu//Evsueee8YMf/CAWLVoU++23X+y5554V3z8AAAAAAAAAk8O4gvEPf/jD8dWvfjU+9KEPRS6XK7nNVVddtd3befTRR+Puu++OO+64I6ZOnRozZ86MRYsWxRe/+MVtgvEFCxZEV1dXTJs2Lfr7++Ppp5+OqVOnRnt7+3hKBwAAAAAAAGCSGlcwPmfOnIiI6OjomNCdPvTQQzF9+vTYfffdB6/be++944knnojnnnsudt5558Hrm5qaYtq0afHDH/4wTjrppCgWi3HmmWfGbrvtNqEaAAAAAAAAAJgcxhWMn3zyyRHxQoj9rne9a5vfX3fddWXdzoYNG2Lq1KnDrhu4vHHjxmHB+IA3v/nN8bOf/Sx+9KMfxaJFi2LXXXeNd7/73dts19/fH/39/YOXe3p6yqoJAAAAAAAAgGwqOxjftGlTPPPMMxER8ZnPfCbe+MY3RrFYHPz9888/H8uWLYtjjjlmu7c1bdq02LRp0za3HxGxww47lPyb1tbWiIh461vfGu9973vjxhtvLBmMX3bZZXHJJZeU96AAAAAAAAAAyLyyg/Genp54z3veE729vVEsFuOQQw4ZXGe8WCxGLpeLww47rKzb2meffeLZZ5+Np556KmbMmBEREQ8//HDssccesdNOOw3bdtmyZRERccYZZwxe19/fH9OnTy952yeffHKccMIJw+o++OCDy32YAAAAAAAAAGRM2cH4rrvuGt///vdj06ZNccQRR8S3v/3tYb9va2sbDLm3Z6+99oo5c+bE+eefH0uWLIlnnnkmLr300jjqqKO22Xbu3Lnxt3/7tzFv3ryYM2dO3HbbbXHTTTfFFVdcUfK2W1tbB0eXAwAAAAAAAMC41hh/2cteFhERHR0d8ZKXvCR23HHHiu94xYoVsWTJkpg3b140NTVFZ2dnLFq0KCIiZs+eHeecc04ceeSRcdhhh8XnPve5+NznPhdPPfVU7LXXXnHxxRfHm970porvGwAAAAAAAIDJY1zB+ICf/OQnEx6VPWPGjFixYkXJ3913333DLh911FElR5MDAAAAACShWCxGX19fyd/19vaW/Hmktra2weUqAQCorYqC8cMPPzw+8YlPxBFHHBG77rrrsIO3Aw44oGrFAQAAAACkUV9fX3R1dW13uwULFoz6u+7u7mhvb69mWQAAjKKiYPzqq6+OiIjbbrtt2PW5XC7Wrl074aIAAAAAAAAAoFoqCsZ/8YtfVLsOAAAAAICGtHXuByOaRzS1Fosv/D9yqvQtm6PpnqvrUxgAAIMqCsYjIn7729/GjTfeGI8//njstttucfjhh8eee+5ZzdoAAAAAANKveUpEc0vSVQAAMIamSv7oZz/7WbznPe+J733ve/GHP/whbrnlljjyyCPj3nvvrXZ9AAAAAAAAADAhFY0Y/+IXvxif/OQn47jjjhu87sorr4wvfelL8Y1vfKNqxQEAAAAAAADARFU0YvzBBx+MY489dth1xx57bKxbt64qRQEAAAAAAABAtVQUjE+dOjV+85vfDLvuN7/5TbzkJS+pSlEAAAAAAAAAUC0VBePvfve74+Mf/3jceeed8cgjj8Ttt98en/jEJ+Ld7353tesDAAAAAAAAgAmpaI3xT37yk/H000/HokWLolAoRFtbW3R1dcXHP/7xatcHAAAAAAAAABNSUTDe1tYWy5YtiyVLlsQf/vCHmDFjRuRyuWrXBgAAAAAAAAATVlEwHhHR3d0d3/rWt+L3v/99/Mmf/Em8//3vj7/6q7+qZm0AAAAAAAAAMGEVBeP/9E//FFdeeWUcc8wx8fKXvzwee+yxOOuss+LZZ5+ND3zgA9WuEQAAAAAAAAAqVlEwfs0118Tll18e++233+B173znO+PUU08VjAMAAAAAAACQKk2V/NHGjRvjta997bDrZs2aFT09PVUpCgAAAAAAAACqpaJg/D3veU9cdNFFsWXLlsHrrrjiivjLv/zLqhUGAAAAAAAAANVQ0VTqDz74YPzP//xPrFmzJl7xilfEk08+GU8++WTstttuMW/evMHtbrnllqoVCgAAAAAAAACVqCgY/8AHPmAtcQAAaCD5fD6WLl0aZ555ZnR0dCRdDgAAAADUVUXB+Pve976IiFi/fn08/vjjseuuu8bLX/7yqhYGAABUT3d3dxQKhVi9erVgHAAAAIBJp6JgvKenJ04//fS49dZbo1gsRi6Xi7e+9a3xD//wD7HzzjtXu0YAAGCCurq6Yt26dTF//vykSwEAAACAumuq5I8uuOCC2LBhQ3z729+O//mf/4lvfetbsXXr1vjiF79Y7foAAIAq6OjoiDVr1hgtDgAAAMCkVFEw/oMf/CAuuOCC2HvvvaOtrS1e+9rXxhe/+MX4/ve/X+36AAAAAAAAAGBCKgrGN23aFDvttNOw63beeefYunVrVYoCAAAAAAAAgGqpKBjff//948tf/nIUi8WIiCgWi/HlL385/uzP/qyqxQEAAAAAAADARE2p5I9OO+20OO644+KGG26IV7ziFfH4449HLpeLr3/969WuDwAAAAAAAAAmpKJgfObMmfHd7343brnllli/fn284hWviIMPPjh23HHHatcHAAAAAAAAABNSUTB++OGHxw033BBdXV3VrgcAAAAAAAAAqqqiNcYjIjZt2lTNOgAAAAAAAACgJioaMd7R0RHvf//746CDDorddttt2O8+9rGPVaUwAAAAAAAAAKiGioLx//u//4uZM2fGI488Eo888sjg9blcrmqFAQAAAAAAAEA1jDsYv+SSS2LHHXeMAw88MBYsWFCLmgAAAAAAAACgasa1xvjy5cvjmmuuiZaWllixYkV89atfrVVdAAAAAAAAAFAV4wrGv/3tb8eVV14ZK1asiBUrVsSNN95Yq7oAAAAAAAAAoCrGFYw///zzsc8++0RExJw5c+J3v/tdTYoCAAAAAAAAgGoZVzDe1PTi5lOmjHt5cgAAAAAAAACou3EF48VisVZ1AAAAAAAAAEBNjGvY9+bNm2PNmjWDlwuFwrDLERGdnZ1VKAsAAAAAAAAAqmNcwfiMGTNixYoVg5df+tKXDrucy+UE4wAAAAAAAACkyriC8VtvvbVWdQAAAAAAAABATYxrjXEAAGByyefz0dnZGfl8PulSAAAAAKBignEAAGBU3d3dUSgUYvXq1UmXAgAAAAAVE4wDAACj6urqipaWlpg/f37SpQAAAABAxca1xjgAADC5dHR0xJo1a5IuAwAAAAAmxIhxAAAAAAAAADJNMA4AAAAAAABApgnGAQAAAAAAAMg0wTgAAAAAAAAAmSYYBwAAAAAAACDTBOMAAAAAAAAAZJpgHAAAAAAAAIBME4wDAAAAAAAAkGmCcQAAAAAAAAAyTTAOAAAAAAAAQKYJxgEAAAAAAADINME4AAAAAAAAAJkmGAcAAAAAAAAg0wTjAAAAAAAAAGSaYBwAAAAAAACATJuSdAEAAAAAAA1tS6E22wIAUDWCcQAAAACAcSoWi4M/N92zasK3AQBAbZlKHQAAAAAAAIBMM2IcAAAAAGCccrnc4M9b5y6IaG4p7w+3FAZHmA+9DQAAakswDgAAAAAwEc0t5QfjAAAkwlTqZF4+n4/Ozs7I5/NJlwIAAAAAAAAkQDBO5nV3d0ehUIjVq1cnXQoAAAAAAACQAME4mdfV1RUtLS0xf/78pEsBAAAAAAAAEmCNcTKvo6Mj1qxZk3QZAAAAAAAAQEKMGCfzrDEOAAAAAAAAk5tgnMyzxjgAAAAAAABMboJxMs8a4wAAAAAAADC5WWOczLPGOAAAAAAAAExuRowDAAAAAAAAkGmCcQAAAAAAAAAyTTAOAAAAAAAAQKYJxgEAAAAAAADINME4AAAAAAAAAJkmGAcAAAAAAAAg0wTjAAAAAAAAAGSaYBwAAAAAAACATBOMAwAAAAAAAJBpgnEAAAAAACAiIvL5fHR2dkY+n0+6FACoKsE4AAAAAAAQERHd3d1RKBRi9erVSZcCAFUlGAcAAAAAACIioqurK1paWmL+/PlJlwIAVZVYML5+/fpYtGhRzJ07Nzo6OuLzn/98bN68ueS23/jGN+Kd73xnzJ49O975znfGqlWr6lwtAAAAAABkX0dHR6xZsyY6OjqSLgUAqiqxYPyUU06JadOmxZ133hnXX399/Pd//3esXLlym+2+//3vx4UXXhhf+MIX4sc//nEsW7Ys/uEf/iG++93v1r9oAAAAAAAAABpOIsH4o48+GnfffXcsXrw4pk6dGjNnzoxFixaVHAn+u9/9Lk466aR44xvfGLlcLmbPnh0dHR3xox/9KIHKAQAAAKhEPp+Pzs7OyOfzSZcCAABMQokE4w899FBMnz49dt9998Hr9t5773jiiSfiueeeG7btggUL4sMf/vDg5fXr18ePfvSj2G+//epWLwAAAAAT093dHYVCIVavXp10KQAAwCSUSDC+YcOGmDp16rDrBi5v3Lhx1L/7/e9/HyeddFLst99+cfjhh5fcpr+/P3p6eob9AwAAACBZXV1d0dLSEvPnz0+6FAAAYBKaksSdTps2LTZt2jTsuoHLO+ywQ8m/+clPfhKf/OQnY+7cubF06dKYMqV06Zdddllccskl1S0YAAAAgAnp6OiINWvWJF0GAAAwSSUSjO+zzz7x7LPPxlNPPRUzZsyIiIiHH3449thjj9hpp5222f7666+P8847Lz7xiU/E3/zN34x52yeffHKccMIJg5d7enri4IMPru4DAAAAAAAAAKBhJDKV+l577RVz5syJ888/P3p6euKxxx6LSy+9NI466qhttv3ud78bZ599dlx88cXbDcUjIlpbW2PHHXcc9g8AAAAAAACAySuRYDwiYsWKFbF58+aYN29eHH300fGOd7wjFi1aFBERs2fPjhtuuCEiIi655JLYsmVLfOITn4jZs2cP/vv7v//7pEoHAAAAAAAAoIEkMpV6RMSMGTNixYoVJX933333Df5844031qskAAAAAAAAADIosRHjAAAAAAAAAFAPgnEAAAAAAAAAMk0wDgAAAAAAAECmCcYBAAAAAAAAyDTBOAAAAAAAAACZJhgHAAAAAAAAINME4wAAAAAAAABkmmAcAAAAAAAAgEwTjAMAAAAAAACQaYJxAAAAAAAAADJNMA4AAAAAAABApgnGAQAAAAAAAMg0wTgAAAAAAAAAmSYYBwAAAAAAACDTBOMAAAAAAAAAZJpgHAAAAAAAAIBME4wDAAAAAAAAkGmCcQAAAAAAAAAyTTAOAAAAAAAAQKYJxgEAAAAAgNTJ5/PR2dkZ+Xw+6VIAyADBOGNy4AEAAAAAQBK6u7ujUCjE6tWrky4FgAwQjDMmBx4AAAAAACShq6srWlpaYv78+UmXAkAGCMYZUxYOPIx6BwAAAABoDMViMXp7e6O3tzfe8IY3xDe+8Y3Yf//9o7e3N4rFYtLlAdDApiRdAOnW0dERa9asSbqMCRk66r2joyPpcgAAAAAAKKFYLMbixYtj7dq1JX8/a9asWL58eeRyuTpXBkAWGDFO5mVh1DsAAAAAwGQg9AagVowYJ/OyMOodAAAAgBTbsnnb6wamfB4Z8pXaFoiIF0Lx5cuXR19fX/T29saCBQsiImLVqlXR3t4ebW1tgnMAKiYYBwAAAACYgKZ7rk66BMiMXC4X7e3tw65rb2/f5joAGC9TqQMAAAAAAACQaUaMAwAAAACMU1tbW3R3d5f8XakpoEe7DQAA6kMwDgAAAAAwTqWmey7FFNAAAOlgKnUAAAAAAAAAMs2IcQAAAACAIYrFYvT19UVvb+/gdUN/bmtri1wul0RpAABUSDAOAAAAAPBHxWIxFi9eHGvXrh12/cCa4RERs2bNiuXLlwvHAQAaiKnUAQAAAACGEHgDAGSPEeMAAAAAAH+Uy+Vi+fLl0dfXFxEvjCAfuH6AqdQBABqPYBwAAAAAYIhcLhft7e1JlwEAQBWZSh0AAAAAAACATBOMAwAAAAAAAJBpgnEAAAAAAAAAMk0wDgAAAAAAAECmCcYBAAAAAAAAyDTBOAAAAAAAAACZJhgHAAAAAAAAINME4wAAAAAAAABkmmAcAAAAAAAAgEwTjAMAAAAAAACQaYJxAAAAAAAAADJNMJ4h+Xw+Ojs7I5/PJ10KAAAAAAAAQGoIxjOku7s7CoVCrF69OulSAAAAAAAASJhBlfAiwXiGdHV1RUtLS8yfPz/pUgAAAAAAAEiYQZXwoilJF0D1dHR0xJo1a5IuAwAAAAAAgBTo6uqKdevWGVQJIRgHAAAAAACATDKoEl5kKnUAAAAAAAAAMk0wDgAAAAAAAECmCcZTKp/PR2dnZ+Tz+aRLAQAAAAAAAGhogvGU6u7ujkKhEKtXr066FAAAAAAAMqxYLEZvb2/09vbGpk2bYtOmTYOXi8Vi0uUBQFVMSboASuvq6op169bF/Pnzky4FAAAAAICMKhaLsXjx4li7dm3J38+aNSuWL18euVyuzpUBQHUJxlOqo6Mj1qxZk3QZAAAAAABknNAbgMlAMA4AAAAAAJNULpeL5cuXR19fX/T29saCBQsiImLVqlXR3t4ebW1tgnMAMkEwDgAAAAAAk1gul4v29vZh17W3t29zHQA0sqakCwAAAAAAAACAWhKMAwAAAJBa+Xw+Ojs7I5/PJ10KAADQwATjAAAAAKTWypUro1AoxMqVK5MuBQAAaGDWGAcAAAAAAKChFIvF6OvrG3Y5IiKXy0VERFtb2+DPABGCcQAAAABSbOHChbF06dJYuHBh0qUAAClRLBZj8eLFsXbt2lG3mTVrVixfvlw4DgwSjAMAAACQWh0dHbFmzZqkywAAUkbgDYyXYBwAqKp8Ph9Lly6NM888Mzo6OpIuBwAAAICMyeVysXz58sGp1Ht7e2PBggUREbFq1apob283lTqwjaakCwAAsqW7uzsKhUKsXr066VIAAEiRfD4fnZ2dkc/nky4FAMiAXC4X7e3tg/8GDFwWigMjCcYBgKrq6uqKlpaWmD9/ftKlAACQIjpQAgAASTKVOgBQVdaABACglK6urli3bp0OlAAAQCIE48CkVywWB9eiKRaLERHDptmxFg0AAMDE6UAJAAAkSTBOJgk6KVexWIzFixfH2rVrR91m1qxZsXz5cvsMAAAAAABAgxKMkzmCTsbLfgAAAFB7+Xw+li5dGmeeeWZ0dHQkXQ4AADDJCMbJJEEn5crlcrF8+fLo6+uL3t7eWLBgQURErFq1Ktrb2yPCDAMAAADV0N3dHYVCIVavXr3dYNxMcAAAQLUJxskcQSfjlcvlBveNAe3t7dtcBwAAQOW6urpi3bp1MX/+/DG3MxMcAABQC01JF8ALisVi9Pb2Dv7btGlTbNq0afDyQO/oySyfz0dnZ2fk8/ntbjsQdA4NNgcut7e3O3EGAACAOuvo6Ig1a9aUNY2683YAAKDajBhPAT2hyzOeKdcAAACAxmQmOAAAoBaMGE8JJ3Pb19XVFS0tLdudcg0AAABobGaCAwAAqs2I8RQY2hM6Ikr2htYT+sUp1wAAAAAAAADGQzCeEgM9oUca2TsaAAAAAAAAgPExlXqG5PP56OzsjHw+n3QpAAAAAAAAAKkhGM+Q7u7uKBQKsXr16qRLAQAAAAAAAEgNwXiG7LfffhER8frXvz7hSgAAAAAAAADSI7FgfP369bFo0aKYO3dudHR0xOc///nYvHnzmH/z3e9+N+bNm1enChvP/fffHxERDzzwQMKVAAAAAAAAAKRHYsH4KaecEtOmTYs777wzrr/++vjv//7vWLlyZcltC4VCfO1rX4tTTz01isVifQttIF1dXdHS0hLz589PuhQAAAAAAACA1EgkGH/00Ufj7rvvjsWLF8fUqVNj5syZsWjRoli1alXJ7f/mb/4m8vl8nHTSSXWutLF0dHTEmjVroqOjI+lSAAAAAAAAAFIjkWD8oYceiunTp8fuu+8+eN3ee+8dTzzxRDz33HPbbP/FL34xLr/88thzzz23e9v9/f3R09Mz7B8w+eTz+ejs7Ix8Pp90KQAAAAAAACRsShJ3umHDhpg6deqw6wYub9y4MXbeeedhv9tjjz3Kvu3LLrssLrnkkokXCTS07u7uKBQKsXr1arMoAAAAAAAATHKJBOPTpk2LTZs2Dbtu4PIOO+wwods++eST44QTThi83NPTEwcffPCEbhNoPF1dXbFu3bqYP39+0qUAAAAAAACQsESC8X322SeeffbZeOqpp2LGjBkREfHwww/HHnvsETvttNOEbru1tTVaW1urUeakVSwWo6+vb/DniIhcLjf4+7a2tmGXIY06OjpizZo1SZcBAAAAAABACiQSjO+1114xZ86cOP/882PJkiXxzDPPxKWXXhpHHXVUEuUwRLFYjMWLF8fatWtH3WbWrFmxfPly4Tipls/nY+nSpXHmmWeaSh0AAACoi4EBJ729vYPXDf3ZgBMAgOQ0JXXHK1asiM2bN8e8efPi6KOPjne84x2xaNGiiIiYPXt23HDDDUmVNuk5OCcLhq4xDtResViM3t7e6O3tjU2bNsWmTZsGLw/MPgIAAJBlAwNOurq6YsGCBYPXL1iwILq6uqKrqys+/elPO0cC2I58Ph+dnZ2Rz+eTLgXImERGjEdEzJgxI1asWFHyd/fdd1/J6+fPn2+94BrL5XKxfPnywZ6tAwfxq1ativb29ojQs5XGYI1xqJ/tzTZiphEAAGCycN4DMHFDBz2ZDRSopsSCcaqvWlNH53K5wRB8QHt7+zbXQZpZYxzqS+MPAAAw2Q0dcBIRgyPDh54vGXACsH0GPQG1IhjPEL2oAEjC9mYb0fADAABMFqUGnAAAkA6JrTFO9XV1dUVLS4teVADU3UDjz9AGoIHLQnEAAAAAyjV0ECBANQnGM2Rg6mijxQEAAKovn89HZ2dn5PP5pEsBAIDMMggQqBVTqVM1xWLRGkoAAEBmWb4KAABqb2AQIEC1CcYbXFrC6GKxGIsXL461a9eOus2sWbNi+fLlwnEAAKAhdXV1xbp164xcAQAAgAYkGG9gaQujBd4AAECWGbkCAAAAjUsw3uDSEkbncrlYvnx59PX1RW9vbyxYsCAiIlatWhXt7e0RYSp1ai8tMygAQBrl8/lYunRpnHnmmaaABgAAAGDSEYw3sLSF0blcbvB+B7S3t29zHdRC2mZQAIC0sTYyAAAAUA0639OoBOMNThgNLxJ4A8DorI0MAABEDJ91caTe3t6SP49kZkaY3HS+p1EJxoFMSNsMCgCQNtZGBgAAIiL6+vqiq6tru9sNtK+V0t3dbXAWTGI639OoBONAZphBAQAmbuTokWKxGBEvzsyioxkAAABMbjrf06gE4wAAQES8EIIvXrw41q5dO+o2s2bNiuXLlwvHAQAgA7bO/WBE84iY4I+dY2PkMf+WzdF0z9X1KQwAakAwDgAADBJ4AwDAJNI8JaK5JekqAKAuBOMAAEBEvBCKL1++fHAq9d7e3sF1BVetWhXt7e2mUgdgXIYu0TFyeY4IS3QAAAD1IxgnE0auhTmgt7e35M8jOREHgOzI5/OxdOnSOPPMM6OjoyPpchpOLpeL9vb2ba5vb28veT0AjMYSHQAAQJoIxsmEvr6+6OrqGnObgdFOpXR3d2voBYCM6O7ujkKhEKtXrxaMA0DCBN4AAEBaCMYx2hoAyJSurq5Yt25dzJ8/P+lSAGBSG7pER6nlOSK0KQAAAPUjGCdzo623zv1gRPOQXfuPa5jFyBPtLZuj6Z6r61cYAFAXHR0dsWbNmqTLSB1TzAOQhFJLdFieAwAASIJgnOxpnhLR3JJ0FQAAqWKKeQAAIG1Gm800woymAFSfYJxhjj9jabS0tg5eLv5xtPXIA4tCf39cuezMutYGAEDlTDEPyTFjAwBAaeXMZhrRWDOaAqNzbkTSBOMJmWhPuFr1gmtpbY2W1raq3y4AAMkyxTwkx4wNAAAAzo1InmA8IRPtCacXHAAAQGNIcsaGkZ2yR84KZupRACAtts794AvLZA71x2OXGHm8smVzNN1zdX0KA6rGbHYkTTAOAAAANZTUjA3FYjEWL14ca9euHXWbWbNmxfLly4XjAEDymqdENLckXQVQQ2azI2mC8RQYua53ROm1vSfjut5DRzeUek6MbgAAABid8yUAANLOLEdAvQjGU8C63qWNZ3QDAAAAw+VyuVi+fPlgI2Nvb+/gcl2rVq2K9vZ2jYwAACTKLEdAPTUlXQCMxRcdAADQ6PL5fHR2dkY+n6/7fedyuWhvbx/8N2DgsnMuAACS5pi08SR5jgMTYcQ4qTV0dEOpkQ0RplABAADSr7u7OwqFQqxevTo6OjqSLgcAAFLDLEeNyTkOjUowzjCF/r7tbzSO7SZqYHTDUCNHOjA5jVx3Zqje3t6SP4+UxgOqoY9r5Fo6EemsGQCAsXV1dcW6deti/vz5SZcCAACpUyoHiNg2C8hqm3Ajco5DoxKMMxi+RURcuewzE/p7qJe+vr7o6ura7nYDvQtLGTr7QETyB0/W0wEAyKaOjo5Ys2ZN0mUAAMCgkSHzyEE6aQyQq9Em3N3d3bAD7/L5fCxdujTOPPPMxEdpO8ehUQnGgUlrrAOkpA6e0nawCQAAUA+jjQBLugMzAGSRATqNyfTlMHGCcYZ9sR1/xvnR0tq23b8p9PcNji73xUjSjj9jabS0tg67rtQ05BERG3t64poLz6pbbeMxdD2dUmvpRGjsAQAAsqmcEWBZHf0FAEmotI0xLSPNt879YETziIhrYHbbkfe/ZXM03XN1zWuqNdOXw8QJxhmmpbWtrGAc0qSltbXs/bal9cWDtjQePJVaT2fkWjoAAAAAAJUaOkAnIkoO0ikVcKdqpHnzlIjmltreR8qYvhwmTjAOTF6T8OAJAAAg7bbpxJzx0V8AkIRSA3Qitj9Ix2yW9ZOW0flpqwUmQjAOAAAAQHroxAwAqVTpSHPGL02j89NUC0xUU9IFAADplM/no7OzM/L5fNKlQF3Y5wFg4orFYvT29pb8N2B7vwcA0mtgpPnIkeUDlwWj1ZOm5zJNtcBEGDEOAJTU3d0dhUIhVq9eHR0dHUmXAzVnn4d0yufzsXTp0jjzzDO9N6EB9PX1RVdX15jbDIwsA2DycEwH45Om0flpqgUmyohxoOEV+vvG8a8/6XKhYXR1dUVLS0vMnz8/6VKgLuzzkE5DO60AANCYGvGYbuQsKJs2bYpNmzYNXh5YYxlqJU2j89NUC0yEEeNAQxp64Hnlss9UeiNVqgayqaOjI9asWZN0GVA39nlIp66urli3bp1OK9CAjj9jabS0tg5eHjiPG9lwWujvjyuXnVnX2gCor0Y7prOmMkA2CcZToNDfV9XtAAAAskKnFWhcLa2t0dLalnQZAJNWmqYvb8RjOoE3QPYIxhMy0dGupmlhsht6YHr8GeeX3diysef5uObCswdupAaVAQBQTZU26KapIRgAIAkrV66MQqEQK1eudDw0TtZUZryKxeLg/jJwOeLFduzJur94XkgbwXiD6u3tHfZh0dvbW/LnkXzIkEUtrW1lB+MtrWZeAIChRp6kDuUYkzQYuh7leBp0K/07AACIeHFN5ZFGrrEMpt4vzfNCGgnGE1LJaNdCf9/g6PIPfvCDo2430HOtlO7ubl/aAAAM6uvri66uru1u5xiTpFS6HuV+++0XDzzwQLz+9a+vUWUAAOm2cOHCWLp0aSxcuDDpUiDzBLuleV5IG8F4CoxntGsajRw9ZGQRQLYZXQpAPVW6HuX9998fEREPPPBAlSsCAGgMjbiuNzQiU++X5nkhjQTjDWzr3A9GNA95CQfWHR/5IbJlczTdc3XN6hhr9JCRRQCNa7S1WY0uheza5vgyIrFjTJioSkeaAwAAjJep90vzvJA2TUkXwAQ0T4lobnnx35TWF/4Nva65ZdvGTQAow9C1WYFJYuTxpWNMGtjACCnriwMAk1U+n4/Ozs7I5/NJlwIkyGcBvEhrFlVRrdHro03Pu72pecearheAypSzNqvRpUzUaDMTAAAAMDFDO7w73yJNS+NVWoscoDI+C+BFgnGqY2B00QSVMz3vWFPzAlA9Za3NWqXPfyYvJ2e1M7KhofjHTisDjRjW8QKg1gr9pRu8K90OqJwOqZNTmpaWsQ8mL01L41WjFsqXps8CSJpgnOzZUqjudqReob9/m+tGNv6/uG19XvehYUSpWoQRNAIHzdSD/aw2isViLF68ONauXTvqNrNmzYrly5fXsSqgHiY6EshxKhM1cP4TEXHlss9UdiPO66HqdEidnAaWlkmDlStXRqFQiJUrV9oHoc7S9FkASROMV4HebrVx/BlLo6W1dfDy6EFnf1y57MzBy033rBr3fQ09cafxDH3902A8YYRGR9LMQTP1YD+rHd8x5XEsT9ZMdPRNtUYBwUQ4r4fq0yEVGGpk23tE+e3vSdaysacnrrnwrJrVAmSfYLwK9LisjZbW1mhpbUu6DLJsPKMLxjkSQRgBQJJyuVwsX758cNRob2/vYAi2atWqaG9vNyr0jxzLA1TX0O+W4884v6zz+kJ/X+WjyycZs5NRKR1SSdrChQtj6dKlsXDhwqRLIdLV9j6eWlpaLb8CTIxgvAr0uEyXrXMXlLfe7ZbCYC90J42Np62tLbq7u0v+rlTj/4BNmzbFBz/4wYiobBRCxPZHIgwNI0arRWMFALWWy+VKjvpsb283GnQIx/Jk2da5H4xoHnHaP3AsO/RYdMvmaLrn6voVxqTR0tpWUaO78/rSzE4GNDKdMxrX0LbQkcvxlLNUT4S2UCA9BONV4Es9ZZpbyjuBpqGN1tg/0sjG/3pNr1eqPkEEjcb0wsBk4FieekjsO7V5inMjElXo7x92eawpWodxXj8qoQIA9ba58OL39GjL8Wzvd5brAdJCMN7Iyp3aeZxTQEOWDW1EKHsUQsSkG4kAEaYXhkYzdGrVkcbqxT9Wr36gOnynMlnVcj3SycjsZAAAMDGC8QZWyTTQ9RotCw3BKAQYk+mF08+ofobq6+uLrq6u7W43Vi9+oDZ8pwLVYnYyAJJU9lI9EZbrAVJJMM4wFU9zVpNaSo94qnQ7SJtKR/YNZTQAtWR64fSrdARikoH6yM++kccaPteALPKdymTS1tYW3d3d21w/2gjnUr8HIBuGnv/96Ec/igsuuCBOO+20OOCAA5z7NSpL9TSkStqBtF2TVYLxFCgVMpcKpEduV/Y00OOYAjrpac6Gjmi/ctlnEqwEaq8aI/uszwOT23777RcPPPBAvP71rx/X3yU1pW+xWIzFixfH2rVrR91m1qxZsXz5cidOE3T8GUujpbV12HWjdXjc2NMT11x4Vt1qAyDbSo1oHskIZ4D6SLpTdKnzv2XLlkXEi+d+QO1V0g6k7ZqsEoynQMVhtGmgAWBSu//++yMi4oEHHhjX3yU5pa/Auz5aWlujpbWtzG3NvgMATIwlfiCdkuoUPSBN539DR7+auYzJxtJO8CLBOKma5mzoAcjxZ5xfVoNuob/P6HIanvV5gEpUemKT1JS+uVwuli9fPtgYUepYQ4MEAEDjSTp8g/GYTAFp0p2iB87/kj73297sZWYuYyxZ6Pw10Xag8cxKV+jvT3xmYhiLYDwho4XREWMH0rUKo9M4zVlLa1vZI52g4VmfBxrGVVddFdddd10cc8wxcdxxxyVaSyOuWTvacUcaplTNwsku4+d1B4CJMxKNRjHZAtKkzxlLnf8lde6XldeU+hut89dkWoN7PLPSQdoJxhNSThgdkY5GYgDgRTfeeOPg/0kH4wK96jLSaXJauXJlFAqFWLlypdcdACqUdPgG49EIIRTVVe7o9ckUdKZJob/85b0K/f01rKS0/fbbLx544IF4/etfP+z6WqzBnYV9cGAkecS2dY7nMUCtCMaBzBg4cBjtC9YXKlANRxxxRFx33XVxxBFHJF1KxUFuLUa9ZyGkN9IJqJaRDVpZn6YVABpFmqb3To0thdpsmzLljF6vRdBJaUPD04qXSR1yG7V0//33R0TEAw88UPP7ysI+uLnwYueFserc3mOAWhGMA5kw2lRYQ79gZ82aFUuWLKl3aZBtk+QEemjA8f73vz/e//73Ry6Xi97e3kQbTioNcmsx6j0Lo62NdJqcFi5cGEuXLo2FCxcmXQoZsb0pWiOyN00rAOmXhY6s1ZKm6b2TMjSUbLpn1YRvAxKxpRBR7vH0BNqkyml72Tr3gy8slTnUwHtkZI1bNkfTPVdXXA8wMYJxIDM0LMLEDQ2ARxvdNtlOoLO4Bl0tRr2PNrUYpF0WOkRo6E6fRvpOqCcj6QGSk4WOrFBPgs7aGnrMd/wZ55e9fvWG55+Lb1x0TkRENN17TUX3XZM2qeYpEc0tVb3J489YGi2trcOuG3n8PKDQ3x9XLjuzqvdfDd5HpJFgnOoot8dVA48WJN2GToUVUfogoa2tbdQ1WoDyA+DJKK2N9JU2bh133HFVXx+9nlOLAcNp6E6Xkcelpml9QZpH0utcAkwGlg1Kv3p+Hw39rt06d0H5gd6WwmAH+cwfy9Qg6KS0lta2soPxkUFxLYzszPnNb34zCoVCXH/99bH//vvX7Vi+pbW17OdlpNR0SPU+IoUE41RsoiMGG2m0II2h1FRY9TDyQGOo0dY73+byJJmOmvQr56B4sp1AT2QNunJG4E9EmkZpp6kWmGw0dKfPaMel1ZymtRHD3LR+/+tcUlsDx0OjnRtNxo4ikIQszJKTdYl9HzW3pCe40j6Wfgm/RrVukxqrM+fPf/7z6OrqSv3AkTR3SIU0EIw3si2bh18eYwqKScXzQrlK7QMV7C99fX3R1dW13bsbut75SJNhOmrSr6IAOE0n0DVUyRp09ZiCPU2jtNNUC9TDVVddFdddd10cc8wxVZ+BYbw0dE9OjRbmpnkkvc4ltTPa8dDQc6OkGpcbsXMJkG2T9ftosi3X1ohq/RoV+vtH3X7bKcOHhO01apPKQlhc7cdQ6C9/FtZSryekiWC8gSW93kJFvbPGMVpw5AfoWOtnDJX080LjsK/AtioJgBldrU+m0tRwkqZaoBZGzhBzww03RETEjTfeGEcffXSiIx6FO/WTpue6ET936zGSvhI6l9RWRZ+Ndejw3midS4Ds831UPVWZ3THj0hR0pmlt7DR35ixXtR7D0M4MVy77TGXF6LRCCgnGqY4a9M5K0xcilOv4M5Zus9bNaJ06Nvb0xDUXnhURk2M66pHS1LAMtTCRKdjLVWnDSS3efxpxyLKxZoDYuHHjsOn0JvK+rvS9mfVwJ03HDGl6rn3u0ghGNsyWOjcqdUxUj07MjdC5pNJgZ6i0N94D1VfrJb2qrRZTY1djdsekpwyvhWoEnVvnHBsxpcx1vhu0DTOtnTnHIwuPAWpFMN5g2traoru7e5vrSzW4j/b3WTbysXteGGm091BEdfaXltbWaGktb39qaR3SwDFJpqMeKk0Ny1AraR2B7/2XfWnq/Z82I0OGchsL69GQU+l7sxHCnYlI02dWks91pfsu25emzhdZNFrDbNIaoXNJNYKd7u7uVD7/jM/Q74Af/ehHccEFF8Rpp50WBxxwQET4DuBF5S7plVopah8zrfsoqvQaVdpGO/R31NbQ75Xjzzi/7DbvjT3PxzUXnj1wIzWoDCZGMN5gyjmhTEODe6WqEfyPdiLQyM8L1VNuo4z9pfay3ogPaVaL959QIXmmOdu+7TUURkTJkd/1mk6v0vdmI4Q7E+GYYXz7LuOXps4Xk1k9BgKMNYpy4Da291lerWOecmqhMlk7Lh3tO2DZsmWDP1dj5hqyw34w3Hhmd9zw/PPxjYvOrldpdZemoDNNbbSm3t++lta2ygaDQQoJxkmVrAf/ZJ8ReuXLeiM+pFkt3n9ZCBWy1ohKaZU2FNZjKjrfjaWl6XlZuXJlFAqFWLlyZd0/Jypbp7nMaT0bZPrPWtH5Ih1q3R5QaeeokapxzFNuLUuWLBm8vHXuByOaRzTjjbH2ej2mo0+rLByXjlSNoNOx7uRQjyW9Gs14ZndsbXuxXS/ryx4KOl9Ulan3gYYhGIdJyglR9RihB9liLcfKjBYqNNLz2eiNqGnq/Z9W9Rr5TXZt3Lhx2P8DJvpZt739bjz77tBj00qmAM389J8lpKnzBbVVjc/3anWkGHctzVNSM71w2mWts8v2gs6I8o6Xa3Gsq21p4mqxHnhal/RKSsWDWFI0rTs0rPF0wJ3knXWpH8E4TFKN3vgPTJypokrL6lqOtWhwGWq0UKGRns8sNaLq/T+6eoz8prrS1Og+bdq0Yf8PmOhnXTmfc42479a6w0AWpWl/z5pqhYvV6EhRbi2jvX/SKE37bhY7u1QadA79HN53333jgQceiNe97nWDn7sT/ZxthLalNHfULXc98LHuO03n9WmrZYBBLIzHsaeeEy2twztEjDb1/qYNG+JfL/583Woby9B9fqz3WD0+6ybaUXfkbUC1CcaHSNNBPNRalhr/k2aEHo3KVFHZNbJBolgsxmc/+9l48MEHS26/7777xnnnnTfuNTazJouNqKS7MZTypKnRfeHChbF06dJYuHBhonWMZei+WvYUoDWa/rMeHQayJsnp+ieDNI2iTFMt1Vh7PU2f1bxgtNC1u7s7uru7I2Lia5M3QttS2jvqTvR7N03n9Wmqhe0rtcTjaAFwoT/bI3mHhrDXXHhWpTdSpWoqs7nw4us51nssDYMSIGmC8SEcxDOZaPyvDSP0IFvG01O4v68/vnHR2RFRvd65pQK9sUK+gb8fOvKoHL/4xS/iqKOOGnbdeE+IyulgaG3MBpDBac7S3hjK9qWp0b2cY+iyP+vq8TlnCtCGM9p0/UkweGBymMja60OPS4844ohYt25dHH744VUbjVwp++6Lav38a1uaGOuB187Q563iEcAZf+6vXHZm0iWwHRUvA1AD4+lIsbmwefDnsjvqRtSssy6MJBgfIk0NLg1ny+bhl8do5GbiqtGbm5Qp9d7wPqKOjj9jabS0tg67brQD3I09PZX3oG0A1egpXK3eueUGemlQVgdDa2PWzXhOWvv7XtzWNGekUcM1uvusKylVHQZSbLTp+pNg8MDkUUn7wWiB+rJlywZ/nuho5ErZd19QreUDxtJonRDS2FG3mrNHVHxeX4M2qTS1MWS5/YLqqMr31NbNEVvKvJ0xOplXYxmArXMWREwZcT4ywc+6ijtS6KhLCgnGhyi3waXU9KQR1V2ns9FM5oaL8ajGCcNEenNTe5VOQzQZ30OVvh9qceLdaCfztdDS2mq2g4zaOvsDEc3Nw68c9YRoSzTdd21F96ODYbqkvfd/Up+742mg6+/ri6u+8EJDRNJrtFGZRv9+T9M6nVWRsg4Dae1snKbp+pP+bh94jUbb37f3GqVpKY00vZ9L1bJkyZLB5/r//b//FxER//zP/zzqeudtbS+cN6T1O26//faLBx54IF7/+tcnXUpFKt1fhv5dufvuyPsZ7z6fpk4IZX3v1+m76KqrrorrrrsujjnmmDjuuOMGr6/151Kl5/W1aJPSxpBObW1tg0spjDRaB5qRv6O0VHUyT9lxN6SNYHycahVKDj0wKnUgpFEtG6p1wmBfSK+0BxFpUun7oRYn3mk6mW84GZztYOhn7PFnnF/2yfzGnufjmgvPjojajEQYCPSKxeKwtaOGmtLSGrlcLjY8//zgtO6VBt3jPTlruBGdKZOWjpf1muYsqc/d8TTQDZ22zhptjanRv9+t01k7ae5snKbv0yRrGe01Grq/b+81quZSGhPtSJGm93O5tQwE5KUMPC+1Ho1cqfvvvz8iIh544IG633c11Hp/qeaxS9IdaIZauXJlFAqFWLlyZeLf+zfeeOPg/0ODcUv81I8AuLRSMxSUUumsBY2q0v1l06ZN8cEPfrCqtVSjTapaywB4H5FVgvEKVPugfqyT8oEPkDSOAB7tg3GsD8WRfz/ZVHrCMLKxvJLe3LlcLrWjIhj7ACKr76PxvB9qsXbd0Nvcd99944EHHojXve51OiSNU/ZnO9h2HxhtdOnwbUuEyqPuT+UF0EMDvda2sU9QW1pTOlqQkqoV0FTlpLVO05xVOpKr0UcAN5LRRjptT5peozQ11pM+jvPSLy2vUWo6Uowx7eqEtp2Aak4BXU0+/+tnPB1oat0mtXHjxoh4IahKwtDH9653vSu6u7vjXe96V/T29qayfWFKy4uzKGWxTaoqAXAGBwKkWUUDB6v0GlVjf6lNJ/NK26Sqw/uIrBKMD1FOI87Q9XkiSh8oVHKwk7aDo3KU88E40ROiiU6dljaV9rgvp0fpWL25V61aFW1tbfHZz342HnzwwVG323fffeO8886reHRamqbGrqdKg4iRtzHac52GhoVqGXqQ+4Y3vCG+8Y1vRC6XG/MgtxZr1412m93d3YOvZTm32ej7btqN1XBSr8//SmeBqMUUWkNHr27P5sLEG0Mb6fs1C6rxfDdS7/9KR3JNdATweN5HQ5dHqdeSBGkycMy6Zs2acQXj1RitNbJT6I9+9KO44IIL4rTTTosDDjig7O+ANI28nahylwEo9PdPuhmMKgla6rHubtIavVP0yLaXiT6GY089J1pahzdWj7Xk1cj1aKv5XI2nlo09PfHNS86PiOodX1ZjytaRwWMalhip5FyzEVS6v1SqnP2jks+XenQwmTZtWkRETJ06taK/n4jttTEMPLahkl7vfOjzPNb5Qd3PHVIUomV/IECFavAajWfg4FDpeo1KfHaN9ryUGWJn4bg+Xa8RvEAwPkS5DW2jNTpWeqAw8oQvwrrlEdWZOo0XlDt1yS9+8Ys46qijBi+Pd3qmShur0zTdVSUaKYhI0kROhCf6Hi81RfH2Tvi3bt0avb29Y34ON/oUrZWqR8/y7e0vk+Xzf+h+euWyzyRYCdU22mwwEVFyRpiRs8FE1Oj4sE4NUZWO5Krk76rxPqrXkgTldriqxdT7I29zxx13jL6+vthpp53GNdJpoqO1xvr8H+gUV+53QCUd2Eo9t6OtBRrx4nNd63W9x7MMwDDlvqcbdHTGRI8v0zjStRqqFUAl3Qm03POs0Qz9DB4ZdJdr4LOs0lnbqllLmow1bWw1p4Aez/diKkb1V0ma9pdS34uVDLqIqE3H26H1HXvssXHBBRfEscceO6xDRL2M+/FZA7ikWoZoYw3Amoxt75Wq1WvU6M//ZAiALQdMVgjGhxitoW2sxpByesWW84FQ6Qlf1kZUj5TW2iudWrJS1ejRXQ+mK3tR1t+b5ag0jN60aVP0/3GU3sDzNNGGqHLX8RqqnI4ilU4FPFI1RvRM9HNpfKORXxxFWa2e5ePdX0Z2XIgovWxEJaMMS80CMfQ9XSqwHAhFBhoCKx1dWovPhauvvnrYqIksTItXLUmu613N9T2rqVYn8yOf65EjuSbjCOBSyulwVa3G/5HfPaM1cj/11FPR1dW1TSN3xIufE0Nf24F9sr29veKpQyt9343cz775zW9GoVCI66+/Pvbff/+yaqnkmGEb5U5hXIepjrPYQDdy3y23s2PEC6/vyP0gDSNdh6r0mK7S52Xkd97Q2/nHf/zHKBQKcemll8b+++8/bLvJYqwAuN7f0VvfeEzElHJHl45+fJn212/oPnjFFVdEoVCIr3/968P2wYio6Fxzex2f2Xb/qOa5dLVn6ih3drklS5aMq/5KbG8mktJTQFd/eYTxzY5U/raVqHSmplrZ3gCsgePnas0KyfiMZ+BgPV6jJAPgqiyRVoPPl/GM6q/Wa7R5c2N23iX9EgvG169fH3/3d38Xd999dzQ3N8eRRx4Zp59+ekwZeZAfEbfffnt86Utfisceeyxe/vKXx6c//ek45JBD6lZruQeBo/WKrcUJUUT2R1RXe+q0iRr6hXjDDTdERMSNN94YRx99dN1rqZfxTqFV6XRlCxcujKVLl8bChQsnXPOA8YxuqHaIPZH3ZloD9UpGi1R6Av3+97+/rG3r3RA1YOg+/9Of/jQiIn72s5+Vvc9Xq8f9yIbLf/u3fxv8v9zPpWqMoqxWx53x7i8jG1siXnjd29raxmwcKed7cWRntdHe0wP7YMnpvKo0jXI13u9Tp06tWeeFNIyiLGW0UKHcIHDAaEFgo3zfp6U3dzVHcVXyfVSNx1ib9eK2VU5H3Uoa/yMm3mms1Ofu1VdfHeeee27J99Fjjz02ZqA+ciTlRGZQGGjYGm0/+/nPfx5dXV11OzeqZLrjRukImwbV2HdHU82RrpW68cYbB/8fTzA+0edlrOOogQ4yEY3VxjC0xvFMR71pw4b414s/n7pamn5yXVVrSsL2PutGO2YY+E6JeDHoLPd9PWCiM+TVUzXeX2laM7rc84HtzY40kZngBlUpLNreudBIA9sOnVGnFssjJH1eX41aBjp2l9M5fahy9t1y3ltpnhUyyY7d9Qijy33ua/0aJREAD1WqTaqctpeh779aLO83UFs50vw+gogEg/FTTjkldt9997jzzjvjqaeeio9+9KOxcuXKOPHEE4dt96tf/So+/vGPx4UXXhh//ud/Ht/73vfilFNOie9973ux++67V7WmRpzOuRFORidiolOnTUQ5jecbN24cPDmb6PrcY0nL61wsFqO3t3fY83LOOefEQw89NOrfvPa1r42///u/H+zR197evk2gV4v1v8qd4rpWHUwqqT3NnV0qmTI8TQ281VpHb7TPgoEG94jtfxZUo8f9qlWroq2trWQt/f39dflcqrZqvkaVjjQfS1qft3qq6yjK8W47wmihQrU6YFR9BFgN1q9O+mS+FkFuRJLH69VfL66UW2+9NQqFQtx6663DHl9a992xRlKOp5aJzqAw8L1Y7dGCx5+xNKa0tAybKWWkKS2tsblQqPn6f+WOuhq63cB7dmQnme01LpfTsDyyga6sGVqqNJI+TceYtfCmN70pfvjDH8ab3vSmcf3dRJ+Xco6jIhp31G2l01HX4js66amxK/3e37RpU1mf++NRqo1hy5YtY/7N5s2b45lnnqnKfWfZQNhQbqAymmo8T2N1OhpPh6RKz6WH7rfVCosmOoiK0Q0cm5TTOX287XRjDcBK+/dZ0ktGTLags9IAeKKfuSON57y+1sYzqh/SLpFg/NFHH42777477rjjjpg6dWrMnDkzFi1aFF/84he3Ccb/7d/+LebOnRuHHXZYRES8+93vjtWrV8d1110Xn/jEJ8Z938ViMf7whz9ExAsndM8///zg7wam7u3v749HH300dtppp2hqaqp4fbyh91kLtRpRXemI1TSNdK1GLRNtgBxoaBq6n11++eXx4x//ON70pjcN7usD+1lExEte8pKSdY08cR2r1+TA9n19fRM+AB9ZS29v77h7Za9bt27YScjll18e7e3t4wrUR3texjKead2rvV9O5L1ZjVqGfs5FbPtZN9LAPjiyzqF/9453vCN+8YtfxIEHHhiPPvrosL+LGH3fnaitb5gf0dz6QuPT1i0DDzD+WOiLGzY1RxQ3R9P/lG7gqYZyG4G2NxKh1g0L46mlGq/ZwG2M9blbr8//agU0I5V7Al3qs3qsEcljTUs89HK1bjMNr1E1ey2PdUx30EEHxc033xwHHXTQsGO6Wo1eH6uWn/70p/G1r30tTjrppHjDG95Q8viyVutXJ3kyX40g95//+Z+jtbV12PM58PPzzz8/7LUdUOr7aLTjqIixQ8Kh4UA1p6Mea3/54Q9/OPh/rffdJAOBat93tb4XRyr090exuDU2F8YeMba5MHyKv62zPxDR1PTisUspTc0RW7eOuZTGREddtbW1jdqwHDH+xuWBfXeszrEDM7QMHMsP3XcbfST9aLWM9Z4eaehn1s477xzPPffcNn/329/+dvD/eh53V+tYN2tq9R1diZGdXcZqDxjr+LJUuFHOd381VKuN4aSTTqpKPWk13nOAiNKdotPc+b4cafoOSJORr1WazutLzY7xwrFS6WOpKS0tkcvlotBfGOw0NHAbSYa7Q1VrFq5KjxeGvg/K6Tj07LPPDtZTzjFDpY8vLbOT1aKWUgHw5z73uVi7dm3MmjUrzj333JK3OZ4QuxaDr6r5WTDW7yeyHHBE8vsLRCQUjD/00EMxffr0YSO+995773jiiSfiueeei5133nnw+l/+8pfx2te+dtjfv+Y1r4lf/OIXJW+7v79/MOCOiOjp6Rn8uZyeVREvnIAuWrRoXI8pKdUeUV3pQXOaDrarVctED8DHmub5xz/+ccl9bLS6hr7O25vSd+B2vvCFL1TlRKraRnZ+Gc3QQL2SfafcNUhr1cGkkvdmNWop93OuUl/5yldKXl/qNarGe73pp6sr+ruR798kD67SdDI/spZqha7b+9wtd/rypJTzGpXzni4VLjaPHGE0RFNT0+AsGrW+zWq8Rmnbl8v5rLv55pvj5ptvrvp9V1LLaJ+ftVJpb+5qncxXY38Z61jqmWeeKftYqpzjqKH3V8se9+P5nq72+Uia3sMjJVXbaJ1uBlQ6qrNay2lUS7U6Xo7nGHNk59hqSlOj2USOvadOnTpmJ/xf/vKX4z5nTEKaP1sqDRc/+9nPxoc+9KFU1FLq/Lyc9oDxnD+X24ZSj3Wa6ylNnyUjjfccIKL0eUCxWJzw40zT85Tk502pY+asqcY541ATmR0jLaO7q3luVMu2ugEjj7+2V1ulj69WAXAlahlGD/0cfv/73x9Lly6No446arsDK6ppPOf1Q481KjnOGLitakvT/gIDEgnGN2zYEFOnTh123cDljRs3DgvGS23b3t4eGzduLHnbl112WVxyySWj3ncSb65Ge0NXWm+aHmeaaqmFch5ftU6kxnu/jajaHUwmohq1pOV1KtX487nPfW7Ujk0R9W2ISqqWtLw+EdUNXdP0uNKiFifzE7nNRn6NStWepseTVC216s2dpue2Fsp9fCMbFsr53iinYSEtz297e3tcf/310dfXF8ViMZYsWRLr1q0bdfuBEcB9fX1jdlooR1qeg7SrRphRaSeZWtRTiVL3Wel7c6IzaqX9+7XS56W3t7dmnRiSVuk58cg2qErvuxq11CLoLKWc26z0nGqszvfVeCwDy2lMtJY0q7QT/ci/GznicbS/S4ta1HX11VdHe3v7mPtLvcKiatUy3vfmWLeZpn0hLW111XpO0vTcDiUHKE85A7Cqedw98nbHu/Z6NXKAakrT/gIREbliAl3c/uM//iM+97nPRT6fH7zuwQcfjCOPPDLuueee2GmnnQav/+hHPxp77bVXnH766YPXLVu2LB577LH4x3/8x21uu9SI8YMPPjjuvffe2HHHHSuatqRYLA77kBjv9JJpPsgsZejjG8+I1Ur/rhaqUUuxuO1aV+W+7q2trdHX1xe5XG7YfnbDDTfEzTffHH/1V38VRx55ZERUNi1eUq9Rqeeg3Odl4L039HK5tdRqusCsGvo5FzH8s+6CCy6Ihx9+OPbee+847bTTIqK8qdRLqdW+GxHD3nsj/66UofvL0LXs01hLpe+jobWUeh9VUkspYz0vY31GVPp3pf5+rOtGPrahn9XlPC+lvqPrdSKQtGq8RpV8Lw5sN/BcR8S4p+kebWTzaMd0I79vh37O9fb2Dr7mlRzTjdY5pJJa+vr6Bj8/x1vLaNdVw8ha6rm/DP3bgeliy3k+B4x3usDxPL5qPC8Df1fJ+Ugt9t1KHl+p7Sa6707k82UgJKrW9+JEaomICb1GpWqZyHNd7c+IofvuePaXWp9Ll3teUavnc7T39PaW0RptKvVSannOOJHP60Y8jir3HKDS897RLldaS73aXhqxjWHk5TS1SaVVPp+PpUuXxplnnhkdHR1l/c1Ezl8Htqnk/LXU5ZGfV+XWUuozq9rnRturZaxjs4nWMlp9jXRev73rklSPc4CxznGG3t94a2mEc6NqSFMtaZKm56XSWnp6emLOnDmD2R5USyLB+K9+9at45zvfGf/5n/8ZM2bMiIiIm266Kb7whS/E7bffPmzbiy66KB544IG4/PLLB6878cQTY7/99otTTjllu/flzQMAAAAAAACNQbZHrTRtf5Pq22uvvWLOnDlx/vnnR09PTzz22GNx6aWXxlFHHbXNtkceeWTcfffdcdNNN8XmzZvjpptuirvvvjve+973JlA5AAAAAAAAAI0mkWA8ImLFihWxefPmmDdvXhx99NHxjne8IxYtWhQREbNnz44bbrghIiL23nvv+Md//Me47LLL4oADDohLL700Lr744nj1q1+dVOkAAAAAAAAANJBEplKvJ9MtAAAAAAAAQGOQ7VEriY0YBwAAAAAAAIB6EIwDAAAAAAAAkGmCcQAAAAAAAAAyTTAOAAAAAAAAQKYJxgEAAAAAAADINME4AAAAAAAAAJkmGAcAAAAAAAAg0wTjAAAAAAAAAGSaYBwAAAAAAACATBOMAwAAAAAAAJBpgnEAAAAAAAAAMk0wDgAAAAAAAECmCcYBAAAAAAAAyDTBOAD/P3vnHRXVtb/9Z6SJQGiCihBL1FiRjh3EhgoqxS42ENCIih0bTexYEBsKig1R6YKoiF1BhCAiGluUpnRUQKSd9w/WzGUoyv29l31Owv6slRVmn1nZT87M7LP3t1IoFAqFQqFQKBQKhUKhUCgUCoVCofyroY5xCoVCoVAoFAqFQqFQKBQKhUKhUCgUCoVCofyroY5xCoVCoVAoFAqFQqFQKBQKhUKhUCgUCoVCofyroY5xCoVCoVAoFAqFQqFQKBQKhUKhUCgUCoVCofyroY5xCoVCoVAoFAqFQqFQKBQKhUKhUCgUCoVCofyroY5xCoVCoVAoFAqFQqFQKBQKhUKhUCgUCoVCofyroY5xCoVCoVAoFAqFQqFQKBQKhUKhUCgUCoVCofyrEWVbQEvDMAwAoKSkhGUlFAqFQqFQKBQKhUKhUCgUCoVCoVAoFArlR/B9enwfH4Xyv+Jf7xgvLS0FABgYGLCshEKhUCgUCoVCoVAoFAqFQqFQKBQKhUKhNIfS0lLIyMiwLYPyL4LH/MvDLWpqapCbmwspKSnweLz/83+npKQEBgYGuHPnDqSlpf+HCv+5Wriig2qhWqgWqoVqoVqoFqqFaqFaqBaqhWqhWv4JOqgWqoVqoVqoFqqFaqFaqBaqhWr5OQzDoLS0FMrKymjThnaFpvzv+NdnjLdp0wYdO3b8n/33pKWlWV9U+HBFC1d0AFRLU1AtjUO1NA7V0jhUS+NQLY1DtTQO1dI4VEvjUC2NQ7U0DtXSOFQLd3UAVEtTUC2NQ7U0DtXSOFRL41AtjUO1NA7V0jhUS+NQLY3z/6uFZopTWgIaZkGhUCgUCoVCoVAoFAqFQqFQKBQKhUKhUCiUfzXUMU6hUCgUCoVCoVAoFAqFQqFQKBQKhUKhUCiUfzXUMd5MxMXFsXTpUoiLi7MthTNauKKDaqFaqBaqhWqhWqgWqoVqoVqoFqqFbagWbmvhig6qhWqhWqgWqoVqoVqoFqqFaqFaKBT24DEMw7AtgkKhUCgUCoVCoVAoFAqFQqFQKBQKhUKhUCiUloJmjFMoFAqFQqFQKBQKhUKhUCgUCoVCoVAoFArlXw11jFMoFAqFQqFQKBQKhUKhUCgUCoVCoVAoFArlXw11jFMoFAqFQqFQKBQKhUKhUCgUCoVCoVAoFArlXw11jFMoFApFiJKSErYlUP5BVFVVsS2BQqFQKJRWT15eXqPjr1+/JqyEQqFQKBQKhUKhUCgU7kId4z+gurpa8PedO3eQkpLCohpuUFNTg5SUFERFReHJkyeoqalhRYeVlRVCQ0Px7ds3Vuavj5ubG9sSANQaxLZt2wYAePLkCQYPHoyJEyfizZs3rOhJSkpiZd66vH//Hjdu3GjSWEgaX1/fRsf3799PVggAPT29RscNDQ3JCmmEwsJCtiUIePv2LXJycojO6eLiQnS+/wtfv36Fj48PRo4cybYUyj+AkpISVFRUsC2DQqFQ/mfcuHED27ZtQ3h4eIMzERvP8XHjxjUYq66uxvTp04lrAYDU1FQAwJcvX7B79274+vqyEkxXWlqKU6dOAQDevHmDqVOnwtbWlvjeDuDOPaFQKP8+qP2yeSQnJ2PZsmVsy6BQOM+nT58AANnZ2U3+Q6HUhWtnIwrlZ/AYhmHYFsFFYmNjsWnTJjx8+BCHDx/G0aNHwePxsHHjRkybNo2IBlNTU0RERMDIyAg8Hq/R99y8eZOIFqDW6Wpvb4+XL19CTk4ORUVF6Nq1K/z8/NCxY0diOoBa52JoaCiys7NhbGwMCwsLaGlpEdVQFz09PTx+/Ji1+fk4ODigrKwMJ06cENwTSUlJpKSkwN/fn7getu/LvXv3sGTJElRWVkJaWhpHjx6Fjo4OcR2FhYV4+/YtAGDRokU4ceIE6i69X79+xapVq/Dnn3+2uJYPHz5gy5YtYBgGT548aXA/SkpKUFxcjNjY2BbXwickJASpqakYM2YM+vfvj/nz5+P58+fo0aMHjh49is6dOxPTAtQGdLi5uSE0NBQXLlyAi4sLREVFsX//fowePZqIBi0tLU4EljRGZmYmTp06heDgYEhISMDMzAxr165lWxaFY7x9+xZ79+7FoUOHcOPGDTg6OkJKSgqHDx+GtrY22/IoHKS6uhoiIiKC1zk5OejQoQOLioSpqqqCqKgo0TkXL16MI0eONBifM2cOzp49S1QLRZjz589j//790NfXR0JCAgYMGIDDhw9DTEwMALnn+IcPH2BtbQ2GYZCdnQ0VFRWh6+Xl5VBQUEBERESLa6nLkSNHcOLECSQmJmLt2rVITU1FmzZtMHjwYGzcuJGolvXr1+PFixcICwvDnDlzoKioCAkJCXz9+rXR31dLwaV7wkXy8/PRvn17VFRU4PLly5CXl8f48eOJ63B3d4ejoyOkpaWJz/0z3r59C2lpadaejVz5jCgN4YL9kuvcuHEDfn5++PPPPzFgwABcunSJuIbKykpERUUhKyurgdNo6dKlxPWwSXl5Ofbs2YMnT56gf//+WL58OZSUlATX+fZw0nBlnbt69Wqj8wYGBhILeOTvZXv37t3AJ8EwDHg8Hl68eEFEC5coKiqCk5MTEhMT0a9fP2zatAk9evQQXOeyLa8l4crZiEL5byBr3fkHceTIEaxYsQI1NTU4e/YsDh48CEVFRTg6OhLbWNra2gKodXZygZ07d6Jr1644ffo0pKSk8PXrV7i4uGD79u04cOAAUS3W1tawtrbG8+fPERISgmXLlkFaWhoWFhaYPHkylJWVierhCs+ePUNUVBTy8vLw4sUL+Pr6QkZGBvr6+qzoYTvuZu/evVixYgVmzpyJY8eO4fDhw/Dz8yOuQ1xcHMuWLUNRURGAWoN2/eukNrddunTB2LFjUVRUhKSkpAZZ4+Li4jAyMiKiBQAOHjyIs2fPQl9fH2vXrkXPnj0FzrOLFy9i9+7dxLPpPT09YWhoCIZhcOzYMezYsQNycnLw9PQk5hhn+7fTGCkpKfD19UVMTAwYhoGrqyumTJki2Oi2VsrLy/H+/Xt069YNEhISQtcSExNbrRN427ZtUFZWBsMw2Lt3L5YtWwYpKSns2LGDFUNUaWkpLl26hPnz5+PNmzdwcnKCvLw83N3dWTEwV1RU4M6dO8jKysL06dPx4cMH9O7dm7gOrjgA9uzZg4KCAmzfvh1AbUCZkZER5s+fjzVr1hDVkp6ejkOHDiEnJ0dgtKysrMTff/+NuLi4Fp8/MzMToaGhAID79+/D29tb6HpJSQn++uuvFtfRGGz/jkaPHv3T5yOpoOHTp0/Dx8cHGhoaKCgowKJFi7Bhwwbs3r0bALnneJcuXbBx40YUFRXBxcWlgWFdQkICurq6RLTU5cqVKzh37hwqKipw7do1BAYGQklJCZMmTSLuBH78+DGCg4Px+fNnJCUl4datW5CTk8OwYcOI6uDKPbG1tYWPjw+srKyaDL4/ffo0MT0AcOnSJXh4eCA5ORm7d+9GVFQUeDwe/v77byxZsoSoloiICDg5ORGdsym4EKzLh0ufEVBbyfDmzZsYM2YMcnJysH37digoKGDlypXE9zRxcXHIyckRrPuVlZX466+/sGnTJmIauGC/rI+bmxu2bNnCytx8vn//jsuXL+PUqVPIzMyEmZkZtmzZgj59+rCiZ9WqVYiPj0fPnj2F1t+m1uL/Nc3J8K0fYNdS7NmzB8nJybCwsMD169cxffp0BAQECPaTmZmZRHTUhe117tu3bwKb4YYNG6ChodEgoWbHjh3EbIeRkZEAyCbkNUVCQsJP30Nqv7tjxw4wDIOdO3ciOjoas2fPxrlz5wTOcZK2PHo2olD+/6CO8SZIT0/HtGnTkJaWhm/fvmHo0KEQFRVFfn4+MQ2mpqYAADMzM2Jz/oi4uDhER0dDSkoKACAjIwMXFxeMGjWKNU39+vVD7969MXz4cBw4cACenp7w9vaGgYEB1q9f3+KbOn42f0lJidB9YGvj8O3bN7Rt2xY3btxAr169IC8vj5KSEuIZTnwjbkVFhZBBl3QU7IcPH7Bw4ULweDwsWrQIY8eOJTo/H2lpaTx69AgAYGxsjOjoaFZ08Jk9ezYAQFVVFVOmTGFVS0hICPz8/NCvXz+8fPkSZmZmiI2NRadOnTBw4EBMmDCBuKZ3797h7NmzePfuHfLz8zFhwgSIi4vD0dGRmIaamho8efLkh5tHUhv/mJgY+Pr64uXLl5g8eTLCw8Mxe/ZsjBgxotU7xV++fAkbGxvk5+ejXbt2cHFxwaRJkwTXFy1aRCwqtrFI7vqQjOj+66+/cPToUWRlZSE9PR2zZs2ClJQUPD09iWmoi7u7O168eIH58+fDxcUFKioqkJCQgIuLC9GMQaB2j7lw4UJUVlbiy5cvMDAwgIWFBby9vYm3JuCCAyAwMBDh4eHYsWOHYExeXh5eXl7YvHkzunbtiqlTpxLTs3HjRjAMA3l5eRQUFKBv374IDQ3F/PnzicyvoqKC169fo7CwENXV1YiPjxe6LiEhAWdnZyJa6sP272jNmjVYtWoVbG1toaam1uLz/Yi8vDxoaGgAABQVFXHs2DFMnToVp06dIvZd4cNfN1RVVZtsk0Oa3Nxc9O7dG48ePYKMjIwg8IeNNlilpaWQk5NDdHQ01NTU0KFDB1RUVBBzRPDhyj3hB+yxFTjdGGfPnsWhQ4dQXV2N4OBgHD9+HEpKSrCysiLudLWwsICbmxvMzc2hpKQk9D0h5TDiw4VgXT5c+oyAWsfEtWvXMGbMGDg7Owuqnrm7u2Pnzp3EdGzduhUXLlwQ2Miqq6tRWlqK4cOHE9MAcMN+WZ8rV66w5hgvKCjA6dOnceHCBSgpKcHa2hp79+7F8uXLWa1GdP/+fYSHh0NVVZWV+c3MzPDly5dGr5HOAI6JiUFgYCA6dOiAOXPmwMnJCfb29ggMDIS4uDjxZzTA/jpXUlKCiRMnory8HAzDCCWs8D8fkmt/p06dAIB4BcfG2LhxIzIyMpq0j5H87j548ACRkZGQlZWFkZER9u3bBzs7OwQHB0NWVpbod5eejSiU/z+oY7wJJCUlUVBQgNjYWGhra0NUVBQvX76EvLw8cS25ubk4dOgQMjIyGvQgIxnNXVNT02CB5/F4rDlGUlJSEB4ejqioKAC1gQTbt29Hhw4d4OnpCXt7e4SHh7eoBn6kmL29vSDLiU3U1dXh4uKCxMREjB8/Hvn5+XBzcyOeKZKVlQWg9mDI/5sNeDye4DsrLS3NiR5+0dHRQuVi79y5AwUFBQwYMIC4ljFjxgg2KfzMLwUFBbi5uRE7MBYVFaFfv34Aah17YmJigg24goICKisrieioi4iICEpLS3H37l1oaGhAXFwcWVlZRLMPvn//3qCyQF1IbvyXLl2KmTNn4vjx46xnlQJokD3ZGKSCcHbu3Ilp06Zh4cKFiI6OhrOzM8TFxWFsbAyAbFQs6eyun1FVVQWGYfDgwQP069cP0tLSKCwsbJBVTwquZAwCgIeHB8zNzbF48WLo6emhW7du2Lp1K7y8vIg7xrngALhw4QI8PT2F9io8Hg+jRo2CiIgIvLy8iDrGU1NTcfv2bWRnZ2P//v3YtGkTRowYgWPHjhFZW9q0aSOoxLRp0yZs3bq1xedsLmz/jsaNG4f09HQkJCSw3h9USUkJKSkpUFdXF7zev38/FixY0CATjBR6enp48OABzp49i5ycHBw7dgx+fn5YtWoV8SDZDh06ICEhAaGhoRg8eDCAWicJG0a7nj174vDhw7h79y5GjhyJkpIS7N+/X7D/JAVX7omdnR0AbpXt/fjxI4YOHYqkpCSIiooKWqQ15cBpSU6ePAkAuHjxouB3zFbJWC4E6/Lh0mcE1J6hAwICUFpaivv37yMyMhKKiorEkzauXr2Ks2fP4tu3bwgPD8e2bduwc+dOlJWVEdXBJfslFzAyMsKIESOwb98+DBkyBACIV6FrDCUlJcjJybE2/8WLFzFr1iysXLkSgwYNYk0HUBu0xq/0yePxsHXrVsybNw+bN2/Gzp07WckuZXudU1JSQkxMDL59+wZTU1NcuXJF6LqEhATat29PREtdEhISsGXLFmRkZKC6ulroGqnn4oULFzBjxgw4Ojqy3sKD36qTj6OjI969e4eVK1fC19eX6HeXno0olP8/qGO8CSwsLDBlyhR8+fIFXl5eSE1NhY2NDRYuXEhcy7p16/D582cMHz6c1ew8fX19uLi4wNXVFe3atUNpaSlcXFxYyUwwNjZGZmYmhg0bBhcXFxgZGQkZfObOnYuZM2e2uA7+/7uYmBgnMjQ8PDywd+9e6OjowN7eHs+fP0dFRQVxoyo/SODmzZusBgxwsVQLl/p/sZ35BTQsG9a2bVuh12x8hqNHj8acOXOQlZWFTZs24c2bN/jjjz9gYmJCTIOkpCSRnvPNYcGCBQgODkZSUhLmzJkjlBHNBi9fvsTNmzehqakp1I+YD8kNd1paGo4fPw5RUVFYWlpCXl4ea9asQdeuXZuVwf2/5GfPoMLCQkJKahk8eDAcHBzw8uVLWFtbIyMjA2vXroWhoSFRHXy4kjEIAMnJyTh48KBQ8NbkyZPh4eFBXAsXHACZmZlNBvANGzYMq1evJqKDj6SkJGRlZSEqKopXr14BAEaMGIF169YR1QHUZqJxpew+wI3f0YIFC3Dv3j3We9DPmzcPixYtwqJFi2BjYwMA0NDQwMaNG2Fvb9+gdygJIiIisH37dkydOhWPHz8GULvv5PF4WLt2LVEtDg4OsLGxQdu2bREQEIBHjx7ByckJBw8eJKoDgOD8Ki0tjaVLlyItLQ3x8fHw8vIiqoNL9wSo/T2fO3eu0eB70uc3WVlZfPjwAdeuXRPsZ+Li4oT6zZKCCyVj+XAhWJcPlz4joDa4WkVFBbdv34aysjK6dOmC6urqBk6blubbt2/Q0NBAXl4enj9/Dh6Ph6VLlxKvesYl+yUXqir27NkTf/75Jzp27AgVFRV07dqV2Nw/Yt26dVi+fDlmzZqFX375RegaiWSWLl26wM3NDfv374eFhUWLz/cjfvvtNwQFBcHS0hIAICoqin379sHc3FxwTiINF9a5iRMnIi4uDmPGjOFEpjZQ2xZBR0cHmzZtYs0noaCggO3bt2PNmjUYN24c2rRpw4oOoLZy7ZEjR/DHH38Ivqfbt2+HpaUlNmzYQFwPPRtRKP93qGO8CRwcHKCnpwcJCQloaGjg48ePcHNzY6UUc3JyMu7evQsZGRnic9dlzZo1WLBgAfT09CAnJ4fi4mL06NEDx44dI65lypQpsLCwaHKD0qVLF9y+fZuYHq44YJWVlYVKkQ4cOBCHDh1Ceno6K5GFXLkvXOLw4cOc6f/FduYXV9m8eTPCwsLQtm1bTJgwAe/fv8eMGTMwd+5cYhq4FE25bt06rFixAuHh4Th//jz27NmDsrIyvH//npWNt5eXFxYtWgRNTU3Ws53ExMRQVlYmMGyMGjUKNjY2cHBwQFBQECtrYEpKCnbt2tWgP3JhYSFSU1OJ6di6dSv8/Pygra2NuXPn4uXLl+jXrx9WrVpFTENduJIxCNS2osnPzxfKyM7Ly4OsrCxxLVxwAIiKiqKiogLi4uINrtXU1DQaANOS/Prrr7hz5w4MDAxQU1ODjIwMiIuLs1J1hktl9wFu/I5ERUU5USFj5syZUFJSQm5urtC4paUlZGRkcOjQIeKafHx8cPjwYWhoaOD8+fNQUlLCsWPHMHfuXOKO8XHjxgkCoSQkJKCsrIybN2+iXbt2RHUAQI8ePXDmzBnBa11dXURERBDX0dQ94WfMkcbJyQlPnz6Fjo5Oo+svSRYsWCBoI3fmzBkkJibCzs6OlbYRjTkiqqqq8OrVK+JOCi4E6/Lh0mcEAGpqaggNDUV0dDSGDRuGmpoa+Pn5CXq8kqJjx44oKCiAkpISPn36hMrKSrRt2xYlJSVEdXDJfsmFqoqXL19GSkoKzp49iylTpkBPTw/fv39n3T719OlTPHjwAA8ePBAaJxmQOmrUKLx48QK5ubmsPX+A2izbxYsXIz4+XtCDWFlZGYcPH4a1tTUrrVe4sM5VVFQgJiYG169fx7Rp0xr9zpKuCJqdnY2wsDBWndFAbSuYZcuWoaioCIqKiqzpWLt2LRYtWoSUlBT4+PgAqK1Q6uPjg3nz5qG8vJyoHno2olD+7/AYtncGHCctLQ2ZmZkwNDTE169fWVl8J0yYgEuXLgn6FrFJVVUVEhISUFhYiM6dO2PAgAHEDZYAMGTIEFy/fp0TZX25Tk5ODgwNDYmXfgNqywOycXDnUz9jk58FVxfS90VfXx/x8fFIS0vD7NmzkZCQAFFRUWhqahLPEOZriY6Oxr59+3Dt2jVUVFRg2LBhgkyjlqZPnz5CzqHs7Gyh1x8/fkRaWhoRLfX5/PkzMjIy0LdvX1RVVRE1GrLxfWguT548wdmzZxETE4OePXvC3NwcVlZWRDVkZ2fD3NwcMTExrD4H1q9fj+LiYqxYsUIog9Pe3h65ubl4+/Ytnj59SlSTpaUl1NTUICcnh4yMDAwdOhSnT5/G3LlzsWDBAmI6Fi9ejN27d3PmOf3mzRu4urpCQkIC+/fvR1paGtzd3eHl5YVu3boR1XLgwAHcuXMHq1atwvLly+Hn54fdu3dDU1MTK1euJKqlMfgOgL59+xKZz9bWFlOmTGk0uyoyMhLnzp3D+fPniWgBajNsHR0dceXKFURERODcuXMQERHBkCFDhIIPSWBnZ4eBAwcKyu4nJCQgJCQEp0+fRkhICFEtALd+R5SG6Orq4vHjx+DxeNDT08Pjx4/BMAx0dXXx5MkTolr489dHR0eHuBYArJaYT0hI+Ol7SBu5gdq95rVr11h1jNQlIyMDoqKi6NSpEwoLC5GdnY3+/fsT13H79m24uroiJydHyCEhKiqKZ8+eEdVSXV3dIFj31q1bmDdvHisOisY+o379+rES0JuQkIB169ahbdu2OHXqFN68eYOVK1fi6NGjgh6nJNi5cyfu378Pf39/bN68Ge3atYOEhATS0tIQHBxMTAcfLtgv+TT1HCBNYWEhLly4gMDAQFRWVmLSpEkwMzPD77//TlyLrq4uPD09MWzYMNadjFwgJycHGRkZ0NHRERrPyMiAv78/Nm3aRFwT28+inTt34syZM6iurm7UKc5GW48ZM2Zgz549UFVVJTovl/n+/Tuys7MbnH++fPmC4OBg2lObQvmHQB3jTVBQUIA//vgDqampEBMTw+XLl2FpaQk/Pz9oamoS0ZCdnQ0ACA8PR1paGhYvXtwgm4hE/0e+jh9Bqg8lnwkTJuDgwYP47bffiM77TyQnJwcGBgZ4+fIlkfny8vJYK6lWn+YcxEiXwDc0NERQUBACAgKQnJyMEydO4OXLl1iyZAliY2OJapkzZw6GDBkiKM+3dOlS7N+/H2/fvhWU121pmmPYNzMzI6DkP5SWlmLLli2IjIxE27ZtERwcjAULFuDkyZPo3r07EQ1PnjxpcEBkCxcXF7i4uDQYz83NRUBAAC5fvox79+4R1/X+/XsoKyuzkn3Gp7i4GBs2bICIiIhQKdTy8nKsWLECd+7cIX5wHThwIOLj45GZmQkPDw+cPHkSycnJcHNzI2qgGzRoEO7evct6FlpTNBYoRYrKykrs3bsXFy5cwLdv3yAhIQFLS0usW7eO+P3iggPg/v37WLVqFdzc3DB69GiIiIigqqoKN2/ehLOzM7Zs2UK8JGlOTg4UFBQgJiaGqKgolJSUYMqUKcQ/H319fdy7dw/i4uICA3NNTQ309PRYcS5SuM3UqVNhZ2eH0aNHC74vDx48wN69exEUFNTi83/48AFbtmwBwzCN7mNKSkpQXFxMfL8bERGBbdu2Ydq0aTh79iyio6MxZ84cjBo1ikgm/c9aH7Bh5AaAsWPHIjIyktVWbXXhStsIExMTDB06FL/88gv++usvmJiY4NChQ7C0tCQeCLp169ZGHUNr167Frl27iGjg93VtjM+fP8PR0RF+fn5EtPyIiooKACD+nK6srIS/vz+mT5+OsrIybNy4ESUlJdi8eTPRaipcsF/WR1dXt1mBQS1BYwka1dXVuH79Os6dO4fExERW1t1hw4bhzp07rCQXUX5OU99XMTExKCgo4NdffyWmhQuJEqGhoQCA1NRUPHjwANOnT4ecnJzQe6ZMmUJcF4VCofyvoI7xJli1ahWkpKTg5OSEESNGICEhAUeOHMHdu3cREBBARAM/27X+R8QfI3WIrpt1y5+3/r9JbyqXL1+O+/fvQ0NDo0GUO5s9rbkI6YzxPn36YMWKFbCzsyMy3/+V6upqpKenE89wOnjwIC5evCjo/6WoqCjo/2Vra0tUC838ahxnZ2fk5uZi7dq1mDZtGh4+fAgPDw9kZGTA19eXbXnE0dLSQlJSUpPXq6qqiGRc/RNJS0sjlnXLZ/jw4bh37x6+f/+OUaNG4f79+wD+UyGCFFu3bkVmZiZMTU2hpKQk5IRmIzMOYDdjsCkKCwshLy/PmpOeKw6AU6dOYc+ePRAVFYWsrCyKi4tRXV2NZcuWEX82conRo0fj9OnTUFFRETg6c3JyMGvWLOJl8FNTU/Hq1SuYm5sDqHUGLF68GMuXL8eAAQOIaqE0zsOHD7FkyRKMGjUKMTExMDMzw5UrV+Dp6QkDAwMiGs6dO4eioiIcPXoU9vb2QtfExcVhZGREvNSxqakp3N3doaGhIXDUvH//HnPnzsXdu3eJauESfn5+yM7OxrJlyxr0uiVN/bYRwcHBMDExYaVtxMCBA5GYmIjMzExs3rwZZ86cwZs3b+Do6EikBH9OTg4ePXoEoPZM4urqKnT969ev2Lt3LzGHibq6Og4ePNhgDXn9+jWWLFmC6upq4sEufN6+fYuAgAB8+vQJ7u7uiIyMxJw5c1jRwjZcsF9yiZ+dX//66y9WMsZ9fX2Rn58Pe3t7VlooUX7MqFGjkJ2djTZt2kBeXh5FRUWoqalBmzZtUF1dje7du+PYsWNQU1NrcS3FxcUNnNCkMTIy+uF1Ho/HibZcFAqF8n+FWrKbIC4uDjExMZCUlBQYK21sbIhGw3LlAcMVHXVp164dK/2S6mJlZfVTQzYX+nyQRlRUFBEREXj8+DE8PDzQsWNHtiU1Sn5+PiZMmEA8qINL/b/q91zU09Njpeci17h16xYiIiIgKysLHo8HMTExrF+/HiNGjGBbGiv8LH6ODadiaWkp3rx5g4EDBwrGfHx8MGPGDOLG3aa0zJw5k7hTHAC6d++OgIAAzJw5E+3atcOLFy8gLi5O3PF69uxZALUZyXVhKzOubsYgv5pIbGwseDwe8d67QG0v+L///rvB74t01H1GRgbWrFmDzMxMxMXFYezYsejevTscHR2JOsbnz5+PCRMm4O7duygsLISysjJGjBgBBQUFYhr4RtT6bVjqQvq7a2pqiqVLl2LVqlWoqalBSkoKdu/ejYkTJxLVkZaWBisrK8yaNUsw9u3bN7Rt2xbz5s3D+fPnWcnspAgzZMgQQblYfX19Qc9ddXV1Yhpmz54NAFBVVeVMFtGnT58Ez2j+b7tLly4oKysjMj/Xqq/VD74/d+5cg/eQXus8PDxgbm4uaBvRrVs3bN26FV5eXsQd4woKCmjTpg1UVFTw9u1bALVnpk+fPhGZX15eHmfPnkVhYSEqKirg5eUldF1CQgJLly4logWodc47Ojri7Nmzgn1tTEwM1q5dCw0NDXh6ehLTUpcHDx7AwcEBI0eOxMOHD1FeXo5Dhw6hrKyMaEBdRkYGjh49iqysLNTU1AhdI2kL4oL9ks+3b98gKioKMTEx/Pnnn7h69SpkZWUxadIkIg5F4OfnVzac4kDtepudnY1Tp041uMbG+YgizKRJk5CdnY0tW7ZASkoKZWVl2L59O1RUVDB37lwcOHAAHh4eOHr0aItrWbZsWZPXSK0tbAU9USgUCimoY7wJxMTEUF5eDklJScGmqrS0lGif786dOzcYa6qkbWvQURcuZIUbGRlh586dmDVrFlHDbWP8qERVYWEhQSW1v53AwEC4u7vD2NgYM2fOxNy5c9GpUyeiOpoDWwUz9PX1BX936tQJSkpKrGSWVlRUICIiAjk5OYKDfGVlJV69eoUjR44Q1cIlampqBGX4+N+RumOtjZqaGjx58uSHvxeSGcAFBQWYNWsWevfujQMHDgCoXef4PXfPnTtHbE0uKCjAzJkz0adPH9a18Fm+fDkWL16MoUOHwtraGtOmTYOIiAhmzpxJVAep9h3NxcfHB0eOHIGGhgbOnz8PJSUlHDt2DHPnziXuGN+7dy+OHz8OJSUlocASHo9H3JHEtgOAz71791BRUQFLS0sYGxujsrISBw8eRIcOHeDv70+k1K+Pjw8AwN/fn7UM/vosWbIE5eXlWLp0Kb59+wYrKytYWloSdYoAwKFDh2BnZyeUAfzLL7/A29sbnp6e8Pb2hre3N1FNdXn79i2kpaXRoUMH1jRwRUvv3r3h7OzMytx1GTNmDE6dOoX58+fjzZs3cHJygoKCAtzc3Ijfm65du+LmzZsYPXq0YOzhw4fo0qULkfmNjIw4UQWODxcDt5OTk3Hw4EHweDzB+jt58mR4eHgQ1/L777/jwIED+OOPP6CoqIg7d+6gbdu2kJCQIDK/uLg4Ll++DACwtrZmvVqVhYUFCgoKYGtri8DAQAQFBeHo0aOwtbXF8uXLWXte7t27F/v27YOBgQF0dXXRqVMn+Pj4YMWKFUQd4ytXroSYmBgGDRrEas9oLtgvgVoHPb8F5IYNG7Bq1SoMHjwYFRUVOHnyJPz9/YmUmOfKPq4+O3bsYFtCk3z69An+/v5Yt24d21JY0xIaGoqoqChISkoCqE3I2rBhA8aPH4/Fixdj1apVGD58OBEt9Vs+FhUVITo6GtOnTycyf1OYmprSZBoKhfKvgTrGm8DIyAhr1qzBpk2bwOPxUFBQgK1bt7KeMRgeHs6qQ5pLOvz9/REYGIisrCwoKSnB0tISdnZ2xDbBCxYsQE5ODvLz87FlyxYiczbFz7K6SB8MpKSksGPHDlhaWsLb2xujR4+GlpYWdHR00KFDhyb7lJGGjQMTF/q58tmwYQPu3bsHeXl5VFZWol27dnj9+jVnMnzYYtCgQXBzc8OWLVsE35H9+/cT70fPFb5///7DsoSkDboHDx5Enz59hHorKigoIDY2Fg4ODjh06BA2b95MTEvfvn2b1OLt7U38+aClpYW7d+9CTEwM06dPR58+ffD161cMHTqUqA6g1qgRERGBrKwsKCsrw8TEhGhvtvpa2MwYrEt4eDiOHj1KrLTxj2DbAQDUOqiWLVsmcObl5uZi8+bNYBgG3t7eCAoKIrJv4PdDrhu8xjZiYmJYt24d1q1bx2rZ/adPn2LPnj2NXrO2tm7Qx7OlSUpKgpubG0JDQ3HhwgW4uLhAVFQU+/fvF3J+thYtXKxi5e7ujhcvXmD+/PlwcXGBiooKJCQk4OLiQjz40tHRUVBi/vv373BxcRGUmCcB16qvNbaf9fHxYbVthYyMDPLz84Uy5/Py8lgpNbxmzRosW7YM06ZNw7Jly7BkyRLU1NSwUl2GX3a5ffv2qKiowOXLl6GgoABjY2OiOmxtbZGbmwsTExOIi4vjyJEjrO9hPnz4ILDN8de/AQMG4PPnz0R1vHnzBo8ePULbtm2JzlufpuyXpD+n/fv3Y82aNSgqKsLq1auxc+dOTJgwAQBw6dIl7Ny5k8jzqKysDH369Pnhe9jI0Oavv58/f0ZGRgb69u2LqqoqVgPw09LS4Ofnh+joaCgoKLDqGGdbS1lZGb58+SJwjAO17StKSkoEr0ntwxsLgjU3NxeyO7BBZmYmq/MDwjYGJSUlmJiYEAt25LIWftstLsAlLRTKj6CO8SZYtWoVnJycBIeOYcOGwcDAoEGPJwo7+Pv74+TJk7C1tYWqqirS09Nx4sQJtGnThuihfvny5Zg8eTJycnJYzVLhWmYeHx0dHZw6dQrp6em4fv06EhMTERMTwxnHOBvs2bMHY8eObbSfK2nu3buHgIAAFBYWIiAgAJ6envDz80NKSgpxLVzCyckJixcvhq6uLqqrq6GpqYmuXbsSKZlVH36WUX3ExMSgoKCAkSNHwtraukUzFCQlJYn1MWwO/F559Q0I4uLicHJywsKFC4k5xpujhZRj/NOnT+jYsWODkq3t27dH+/btkZ2dTbRU67NnzzB//nx0794dqqqqePbsGXx8fODr6wttbW1iOviwnTFYl9LSUtYDLflwwQFw8uRJuLq6YtKkSQBqA8XMzMwAAG3atMHly5eJ7BuaWm/rQsrBFRoa+tP3kAxi42ehNYacnBzKy8uJaQEAT09PGBoagmEYHDt2DDt27ICcnBw8PT2JO8a5oIVLwRx8Hj9+jODgYHz+/BlJSUm4desW5OTkMGzYMOJa2C4xX7/6WlpaGjIzM2FoaIivX79CUVGRiI4fwc8AZguutI0AgN9++w2RkZEAaj+7W7duobS0FN26dSOu5dKlS/Dw8EBycjJ2796NqKgo8Hg8vHv3DkuWLCGqZdOmTSgsLERubi4rwZb1UVFRQVJSktCe8tmzZ8Sr1PXu3RufPn1C165dic5bn6bsl25ubkR1vH79GrNmzUJZWRm8vb0xbtw4wTVzc/Mmg+z+10hISOD48eNE5vpvKC0txZYtWxAZGYm2bdsiODgYCxYswMmTJ9G9e3eiWu7cuQNfX18kJCRgyJAh2Ldv3097Sv/btRgbG+OPP/7AypUroaKiguzsbHh5eWHs2LEoKSnB1q1bBYG0bNCvXz+kpqayNj/AfjWGxmwMx48fZ8XGwCUtAHsVURuDS1oolB9BHeNNICUlBS8vLxQUFCArKwsdO3aEsrKyUKQYG3BlcWFbx4ULF3D48GGh0tNaWlpwcHAgeqiXlJTE9evXic33f+Xp06dC/W9bksa+G7/++itsbGxgY2NDRAMfLpWY58OVfq5AbYns7t27Q05OThAxPXv2bFZ6kXHBAcxHUVERgYGBePbsmWD9V1dXh4iISIvPXZ9p06bh4sWLsLGxgZqaGrKysuDn54chQ4age/fuOH/+PMrLy+Hg4NBiGtg+/NTn8+fPTQYide3aFcXFxa1Sy4QJE5CUlNTob4mNUq27d+/G8uXLMXfuXMGYv78/9uzZg4CAAGI6+LCdMVgXQ0NDRERECBzBbMIFB0BKSorQ51B3HzFmzBhipXRbch39b6nfU7Y+pMvuq6io4OXLl432Ef/rr7+IO/bevXuHs2fP4t27d8jPz8eECRMgLi4OR0dHojq4ooV0af3mUFpaCjk5OURHR0NNTQ0dOnRARUUFK3sKX19fWFtbNygxv3//fqxYsYKYjoKCAvzxxx9ITU2FmJgYLl++DEtLS/j5+UFTU5OYDi7ChbYRPzo3AkB+fj7R1kEAcPbsWRw6dAjV1dUIDg4WtGGxsrIi5hive18sLCywefNmrFu3TihgjfR9AQA7OzssXrwYM2fORGVlJY4fP44zZ85g5cqVRHVs2rQJ8+fPFwS+14Xk95dvvywsLERmZqbAfkkaSUlJFBYWQkFBAa6urqiurhacod++fUustLuIiAgnq73t2rULZWVluHr1KqZNmwY1NTWMHDkSHh4eRNomVFRUICwsDCdPnkRhYSGmTp2KFy9eYNu2bcQTfbikhc+GDRvg4eGBP/74A9++fUPbtm1haWmJVatW4fnz5/jy5Quxyqn1g90rKysRGRnJeotKkoH2jcElGwNXtPCf09XV1UItENl4NnNJC4XSHKhjvAn4ZR8UFRWFjD2GhoZ48uQJa7qioqJYm7subOvIzc1tYJzr3bs3UScEl9DS0kJSUpLgNb8MNJ8FCxYIXW9JuBSZy7US8wB3+rkCQMeOHZGRkQE1NTUUFBSgrKwMbdq0QWlpKXEtXHAA85kyZQpCQ0Ohrq4ulE1kZGSE2NjYFp+/LteuXcOxY8fQs2dPwZienh5Wr16NLVu2wNDQEFZWVi16X9gOhKqPnJxck1U6cnJyIC0t3Sq18J2bXCnZ+tdffzUIspk1a9ZPHX4tBdsZg3X5/v071q9fj6NHj6J9+/ZC10iVO+aSA6CiogIyMjKC13W/I1JSUqipqSGiw8zMTNDrfNSoUYJe5wAEvc5JQfpZ8zMmTpwIDw8P+Pj4CGWOl5WVYdu2bcSztEVERFBaWoq7d+9CQ0MD4uLiyMrKIrrmclFLVVUVjh8/jrCwMOTk5EBVVRUzZszA7NmziWvp2bMnDh8+jLt372LkyJEoKSnB/v37ifSWBWoDYPn77IMHD2LgwIFC+5mvX7/C39+fqGN827Zt6NWrF06ePIkRI0bgt99+g62tLXbt2sVKwFhd2N7rcaFtRHPOjaRLL3/8+BFDhw5FUlISREVFoaWlBQD48uULMQ2N3Zfs7GzBvpON+wLUPpekpaVx7tw5qKioIC4uDhs3bhTKUCbBwYMHUVZWhufPnwsFcJP6/ja1n/vw4QM+fPgAgKxDYty4cbC3t8eZM2cwbdo0wfipU6dw4sQJzJs3j4gOtte0prh16xYiIiIgKysLHo8HMTExrF+/nlglKSMjI3To0AELFiyAqakp2rZti0uXLhGZm8ta+EhISAhsqcXFxVBUVBT8lnV0dIhkiycmJkJbW7tBsDvDMJCVlcXWrVtbXMOPuHLlCkpKSiAuLs5KCwAu2Ri4ooXfcuDbt2+Cqm88Ho8VuxCXtFAozYE6xuvw4cMHbNmyBQzDoKSkRCjqBwBKSkoaRIGSoLS0FJcuXcL8+fNRWlqKqVOnQl5eHu7u7kQj6biiA6jtC3rjxg2hg8+NGzeIl0StqqpCSEgI4uLiUFxcDAUFBQwdOhSmpqZEs0vrb/yvXLki5BgneTBgs7RQfbhYYp4L/Vz5mJqaYtasWbh8+TIMDQ2xePFiSEhIoH///sS1sO0ATk9PF/S8fPPmDZycnISul5SUEC8VC9Q+l+qX5lNTU8Pff/8NAFBVVW1x4xiXgl0AwMDAAMeOHWu0RPnx48cxaNCgVqmFHz1ev2QrW0hKSuLjx49QU1MTjH38+JGVfqEAdzIGAaBXr17o1asX0TnrwyUHgIKCAt6/fy/IUh88eLDg2vv37xsED7QUXOl1Xp+MjAxcvXpV4Og0NTUldk/4LFiwADdv3sSYMWNgaGiI9u3bIy8vD3fu3IGSkhL++OMPonpGjx6NOXPmICsrC5s2bcKbN2/wxx9/EO91zjUt+/fvx/Xr12FjY4NOnTohPT0dfn5+KC0tJV4m28XFBa6urpCWlsbSpUuRlpaG+Ph4YsZCcXFxLFu2DEVFRQCAOXPmNLg+ffp0Ilr4xMXFISYmBpKSkgJjt42NDfFKTba2tvDx8REaY3uv5+3t3ei4uLg45OXlMWTIkBbf33Dx3CgrK4sPHz7g2rVrguzXuLg4KCkpEdPAxfsCAFevXsX48eMb9NAODAwk+tuOj4/HjRs3iD+X+XBpPwfUOkX27dvXwGH29OlT2NraNrCxthT29vZE5vlvqampEdwbvo2u7lhL06ZNG4iKiqK0tBRVVVVE5vwnaKnL27dvERAQgE+fPsHd3R2RkZEN9hAtyaJFi5CUlNTAkSgiIgJFRUWIiYkR08Ln7du32Lt3Lw4dOoQbN27A0dERUlJSOHz4MPGS4VyyMXBFCz+gWk9Pj/Xgai5poVCaA3WM16FLly4YO3YsioqKkJSU1KD0jri4OCt9Ttzd3fHixQvMnz8fLi4uUFFRgYSEBFxcXASOnNakA6gtt7ZixQpBeb709HTcvHmTaGTW58+fMW/ePHz48AFaWlqQl5dHQUEBXF1dceHCBZw8ebLJfoz/axorm/uj6xT24EI/Vz62trZQU1ODjIwMNm/ejN27d6OkpIRYf+a6sO0A/vXXXyEvLy8woNZHQUEB+/bta7H5m6J37944duyYUCk+Pz8/9OjRA0Btj+uWNhRyKdgFABYvXgxTU1NkZWVh4sSJUFJSQm5uLq5evYrExERcvny5VWrp3bv3T9d6koaxCRMmwMHBAatWrYKqqirS09Oxb98+TJgwgZgGLmYMAtwoe8wlQ/fw4cPh6+vbaAaEn58fDA0NiejgSq/zuty7dw9LlixBv379oKKigpSUFHh7e8PPz49Yixyg9gx09uxZnD59Grdu3UJiYiKUlJRgY2ODWbNmEc8Y2bx5M8LCwtC2bVtMmDAB79+/x4wZM4gZ3Lmq5cqVKzhz5oyQgW7QoEFYtGgRccd4jx49cObMGcFrPT09REREEJtfWloajx49AlDbMzQ6OprY3E0hJiaG8vJySEpKCp5FpaWlxEoL82ms+h3be71Xr17h+vXrGDBgANTU1JCdnY3k5GQMGDAA1dXV8PDwwJEjR4QCp1qK+uVr60K6hCw/kxIAzpw5g8TERNjZ2TUI8mstfPv2TXBW27BhAzQ0NBrs63bs2EHUMa6srMxKgDsfLu3ngNr9Aj9jsC6kz9F2dnZE52sugwYNEmQk889t+/fvJ1b2/datW7h27RrOnTuHAwcOYMqUKaisrGTFXsglLXwePHgABwcHjBw5Eg8fPkR5eTkOHTqEsrIyYvso/prGlWB3oLbijbKyMhiGgaenJ5YtWwYpKSns2LGDeJY/F2wMXNQCcKtSBpe0UCg/gsfQb2ujhIaGEu3d9yOMjIwQHBwMHo+HwYMH49atW5CTk8OwYcN+Wgrz36iDT1xcHEJCQpCfn4/OnTvD0tKSaElUFxcXvH37FocOHRKqJFBUVIRly5ZBU1OTWI+r+qXU+a0AmrrektTPtG2M7du3E1DyzyA3N5d4P1cuMmvWLAwZMkTIYXTs2DHExMTg0qVLuHv3Lvbs2YPw8PAW13LkyBEsXry4xedpDmlpaVi0aBFERUXRqVMnfPz4ETU1NThy5AgqKiowb948HDhwgJWgLTb58OEDPDw8cP/+fdTU1EBUVBTDhw/H2rVrif+WuKKl7prfFCR77X3//h3Ozs6IjIxEZWUlJCQkYGFhgXXr1hEzIJaUlGDMmDFNBrzwMwY3btxIRI+LiwtcXFx++Jwk/XzkggPg48ePmDRpEoYPH44ZM2agQ4cOyMnJEaz9kZGRRDKx9PX1cePGDcGeTldXV7C/LS0thaGhIfH9rrm5OebOnSt0Jrl48SIuX76MixcvEtXCRT5//oyMjAz07dsXVVVVrJR05JIWQ0NDREdHo23btoKxb9++wcDAoFnPiP8lFRUViIiIQE5OjqAdQmVlJV69ekU8oNrLywsWFhasG5nd3NyQnp6OTZs2Ydq0abh69Sq2bt2KX375Ba6ursR0kDwXNpeVK1dCR0cHs2bNEowFBQUhPj4eu3btQlRUFE6ePEnEAM8PNOSbyeo6adgoGZ6RkSE4BxQWFiI7O5toda/65Xzrw+PxEBMTQ0RLXl4exo4di/LycjAMI/ic6v579OjROHjwIBE9QO0zOSIiAnPnzhWUx+ZDsoQ5F/ZzfBiGQWBgIKKjo5GbmwslJSWMGzcO06dPJ1pVkYsUFBRg8eLFSEtLQ3V1Ndq2bYuuXbvi6NGjxKtwvnz5EmfPnsWVK1fQpUsXWFpawsTEBPLy8kR1cEmLhYUFli1bBgMDA8E54NmzZ1ixYgWxUtBcfEYPGzYMt27dQk5ODsaNG4f4+HhISUlBW1ubuNambAxr164V2v+2Ni0A4OrqypnAOS5poVB+BHWMN4GmpiaMjY1hYWHBegS1vr4+4uPjER0djX379uHatWuoqKjAsGHDiBo5uKKDKxgaGsLPzw/du3dvcO2vv/7C8uXLiWUncMkxvnXrVpw9exbjxo1Du3btGn1Pa3SMN8eYTurw3JwsJlJ9bvlwyQFsZGQEc3NzmJubEzckNEZJSQliY2Px6dMndO7cGUZGRpCUlERxcTGqq6uhqKjItkRWKC0tRXx8PMrKyqCoqIiBAwc2uea0Ji182HbS5OXlQUlJCRUVFfj8+TPat28PHo+H169fC7VMIAUXMgadnZ3h6urKKcc4VxwAr169wpYtW5CcnCzQM2DAAGzbto3Y90VTUxNJSUmCe/Do0SOh7ERtbW0kJiYS0cJHT08PcXFxQn1Lq6qqoKuriz///JOolqbIy8uDmZkZ7t+/T2zO0tJSbNmyBZGRkWjbti2Cg4OxYMECnDx5stF9eWvRcvz4cbx+/RpbtmyBtLQ0ysvLsWPHDsjKysLR0ZGoltWrV+PevXuQl5dHZWUl2rVrh9evX2PKlCnYsWMHUS329va4f/8+tLW1YW5uDmNjY1YyPEtLS+Hk5ITr168DqF1vDQwMsHv3bsjIyBDToa6uDjc3tx++h3SCwKBBg/DgwQMhp1l1dTWGDBmC+Ph4MAwDHR0dImtwVlaW0OvCwkKcOHECo0aNElQUIcm3b9/w+fPnBgEmY8aMITJ/SEhIo+PJyckIDAxE3759ERwcTEQLUOtY/PbtG0xNTXHlyhWhaxISEsRLmvfu3bvRcdIlzLmyn6upqcGiRYuQkpICIyMjKCsrIzMzE/fu3cOAAQPg6+srtKdpjTAMg2fPniErKwsdO3aEuro6sYABfv/qunz+/BmXLl1CQEAAcnNz8ezZs1anhY+Ojg4SEhLA4/GEbKo6OjqNVltpCfr06fNTGxTpfs2DBg3C3bt3ERISgqCgIFy8eBGFhYWYOHGioDoPaerbGNiES1ooFMp/By2l3gSnT59GWFgYli5dil9++QXm5uYwMzMjHsUHAD179sThw4dx9+5djBw5EiUlJdi/fz/69evXKnUAwLNnz+Dp6YmsrCzBIZEPqU1CcXFxkwav33//HQUFBUR0ALWb648fPwr1Kar7mmT8y6ZNm1BcXAw5OTls2rSJ2Lxcx8rKSrBJauzzIHl4fvz4MWRkZGBsbMzKmtYYffv2xbVr15p0AN++fZuYA3jt2rUIDQ3F0aNHoaOjAwsLC4wdO5a1MnnS0tKNGuLk5OTIi+EIJ06cgLe3N75//y7IEGnXrh1WrlyJ2bNnt1otAHecNOPGjUNSUhLExcUFvTCrq6sxffp0VqLgJ0yYgKysLFYzBvkZgb/99htmzpxJvHxuY9TfM9V1AJCkV69euHDhAnJycvDp0ycoKSkRD0ziSq/zuujo6CA2NhajR48WjD18+JBotuDPqKmpIbrnBYBdu3ahrKwMV69exbRp06CmpoaRI0fCw8MDvr6+rU5LfYfIlStXICMjI+jbKS8vT9wxfu/ePQQEBKCwsBABAQHw9PSEn58fUlJSiOoAgKNHj6KgoADh4eHw8/ODu7s7JkyYQLzamJSUFLy8vFBYWIjMzEx06NCBlX14ZWXlD9uP8Xg84o7xdu3aITU1VahFRFpamiCor6CggFiLsvr7hM6dO2Pr1q0wMzMj7hgPCgqCu7s7vn//LjSuqKhIzDHObylSFz8/PwQFBWHmzJnNqhb3v4R/Hty4cSMUFRVZycqrC1dKmXNlP3f27Fnk5uYiOjpa6Oyek5MDGxsbnD17lmirkYyMDKH2ImwzZcoUhIaGQl1dXej5Y2RkRKQfL79/dV1kZWVhY2MDa2tr3Lp1q8U1cFELHxUVFSQlJQk57J89e4ZOnToR0yAmJsaJtlt1GTJkCBwcHPDy5UtYW1sjIyMDa9euJdbuCqit6vszSO1duKQFqF3n0tLSoKenBzk5OezevRt3796Frq4unJyciCZIcEkLhdIcaMb4T6iqqkJsbCyioqLw6NEjqKurw8LCAqNGjYKYmBgRDW/evIGrqyskJCSwf/9+pKWlwd3dHV5eXkTLtHJFBwCYmJigZ8+eGDZsWIOI08YOby3Bz7KwSWZp1+8ty3fO1P2bZKRwUVERxo8fj6ioKCgoKBCb90dERkZi4sSJrM1vb2+PP//8E8bGxrC0tMSAAQNY0/LixQtcunQJV69eFaxpRkZGEBWlsVJ14RtRo6Ki8OHDB0yYMAEWFhZEP7v4+Hi4urri/fv3DQIqSJdzbKqUopiYGBQUFDBy5EhYW1u3eBbApUuXsHPnTqxbtw6GhoaQl5dHQUEBYmNjsW/fPri7u2PcuHEtqoGLWvg4OzsjNzcXa9euxbRp0/Dw4UN4eHggIyOjxZ00Hz58gLW1NRiGQXZ2dgPHZnl5ORQUFIj2meXDlYxBoDYL+NGjR5wtJ/n161eYmZkRK43KFVxcXFBVVdVor/MtW7ZAUlKSmAOAP09hYSEePHiAkSNHQlVVFbm5ubh58yZGjRoFT09PIlp+Rk5ODgwNDYk+k0aMGIGIiAjIysoKMnrKy8sxYsQI4lWsuKCFa600gP+0IigsLMScOXMQFRWF79+/Y9SoUUSrCzRGcnIy3Nzc8OLFC3Tv3h2zZs3C9OnTW3wfnJ2djZUrV2Lz5s3o168fdu7cieTkZHh5eQkCyEjAxTKtp0+fxqFDhzBjxgx07twZWVlZuHTpEqytrTF+/HjY29tj8ODBxJ2wfL5+/YpRo0YRX1/GjBmD2bNnQ0pKCgkJCZg3bx52796NoUOHYtGiRUS1AMCXL1+wbt06PHnyBG5ubhg/fjxxDXxMTU2RlZUlqPJYP/OUJKmpqejfvz++fv2Ko0ePQkFBAfPmzWP9bM3Gfs7c3BwbNmxotOpmXFwcdu3aRbTCQP/+/aGpqQlLS0uMGzeOlUCK9PR0QQuRiIgImJqaCl0vKSlBYmIiHj582OJaNDU1OVNxiEta+ERGRsLV1RUzZ87E6dOnsWTJEpw5cwYrV64k5ujk4jO6tLQUfn5+kJCQgK2tLV6+fInLly9j1apVxILWflY5ksfjEUuS45KW69evY+XKlZCSkoKIiAgsLCxw5coVGBsbIyYmBqNGjcL69etbnRYKpblQx3gzePnyJa5cuYIbN26gtLQUysrKyMvLw7Zt2zB8+HC25bVKNDU18fjxY2LBCY3BJcd4/ZJvjUE6S66srAwSEhKcMfzXLy/PBgUFBQgJCUFwcDBEREQwdepUTJ48GbKysqzoqaioQExMDC5fvoxXr17B1NQUFhYW6NGjB3EtXHIA16WwsBDXrl3DxYsX8ebNG8jIyKBjx47w8PBAnz59Wnx+MzMz9O7dG6ampg2MK6SN3EePHsXFixdhY2MDNTU1ZGVlwc/PD8OGDUP37t1x/vx5jB8/Hg4ODi2qw8zMDEuWLGk0UyYqKgrnz5/H2bNnW1QDF7XwYdtJc+vWLRQVFcHFxaVBz1QJCQno6uoSdQDUhR/sEhoaiqysLFYyBgFg1apV6NmzJ8zNzaGsrEx07ubAlgOAbbjS6xxAs5w/XGlLw4ZjfNiwYbhx4wYkJSUFDtiysjKMHTuWuNOVS1qA2gz+1NRUZGZmQllZGVpaWqyUrTU1NcXhw4ehpqYGfX193Lp1C23atMHgwYNZMYRXVlbi1q1bCAsLw927d9GjRw+Ym5ujc+fOOHLkCDp06ABvb+8W1WBnZwdFRUVs2LAB0tLSKCwsxL59+/D58+cfZnD/r+Gi0R2odUgEBQXh48ePUFFRwfTp0zF27Fi8fPkScXFxsLKyInKurP89qKysxL1799C+fXv4+Pi0+Px10dDQwJ9//omsrCysXr0aFy5cQHZ2NubPny8oyU+K5ORkODo6Ql5eHgcOHOBEFm5qaipCQ0MRGRkpqPI4ZcoUopUYjhw5ghMnTiAxMRFr165FamqqYK3buHEjMR2NwcZ+TldXF48fP240mLqiogJDhgwhVpIaqN37h4WFITQ0FNnZ2Rg/fjzMzc2hqalJTANQW12mqKioUce4uLg4JkyYAH19/RbXwaX1n0ta6nLnzh2cO3dOUOp+2rRpRAPduRgwwKegoABZWVlQUlIimkVPaZpJkyZh4cKFmDJlCqKjo+Ho6IiAgABoaGjg7du3sLa2xu3bt1udFgqluVDHeBPk5OQgIiICYWFh+Pvvv2FgYABzc3MYGhpCREQEFy5cwMGDB/HgwQMievz9/REYGCh4CFlaWsLOzo54/wqu6LC1tcXSpUuJG7Pr0rdv3x/2n09MTMTz588JKqL8CL6xkiskJiYiODgYMTExGDx4MCwtLTFs2DDW9Hz8+BHBwcEICQlB+/btceHCBaLzc8kBXFFRgZs3byIsLAz3799Hz549YWZmBlNTU8jKysLb2xthYWFEokA1NTURFxfHWmZrXczMzLBr1y6hfr/v3r3D6tWrERwcjMzMTFhZWbV42TNNTU0kJCQ0moVRUVEBQ0NDIhH3XNPChytOmsePHxP/7f43sJUxCACGhob49OlTo5VeSAcCcckBwAW40Ov8nwYbjvHVq1dDTEwMW7ZsgYGBAR4/foxt27YhPz8fe/fuJaaDa1ry8vJgb2+Ply9fQk5ODkVFRejatSv8/PzQsWNHolp8fHxw5swZXL58GXv37sWnT58gISGBb9++4cyZM0S1bNmyBdeuXQMAQRBo3eDGFy9eYObMmUhOTm5RHXp6enjw4IFQYPf3798xYsQIxMfHt+jcdeGy0Z0LWFlZCb0WERHBb7/9Bjs7O+LBbKNGjcLVq1chIiIi6LcOANra2kT6rfM5ceIEDhw4gOnTp2Pt2rWcK4VaVVWF+/fvw8vLC3/99ReGDh2KWbNmESnzO3HiRHh6eqJ79+7Q1dVFYGAglJSUMGnSJGK2QoA7+zltbW3cuXMH0tLSDa6VlJRg1KhRRNe7uqSlpSEyMhIxMTFo06YNLCwsYG5uTqzCYXV1NY4dO4YlS5YAAB49eoSXL1/CwMCAWLsrLvWv5pIWPu7u7nB0dGz0+0sKZ2fnBsHlbFNSUoJ169YhNjZWcGYdPHgw9u/fj19++YU1XaampqxUomsMtrTU3dNVV1dj4MCBSE1NFVwnuV/gkhYKpbnQurlNMHLkSHTv3h3m5uaYPHlyg962gwYNQmRkJBEt/v7+OHnyJGxtbaGqqor09HScOHECbdq0ga2tLRENXNIBACtWrMDcuXOhr6/f4EFMKoOGv6FtCpIOgeZkOHChT01eXh7MzMyIOmf4WVfl5eVCGVhsZ1ppa2tDW1sbVlZWWLNmDRYtWsRqZvT79+/x/v17FBQUsNK7+v3797hw4QInHMBDhgyBiIgITExMEBgYiH79+gldnzBhQrP6Cv0v6Nq1K3JzczmRlfHhwwd07dpVaExNTQ1///03AEBVVRVfvnxpcR08Hq9J56W4uDjKy8tbXAMXtfAZNGgQ3NzcsGXLFoHjdf/+/cSeST4+PrC1tcXjx4+bzFBh63nUWMbghg0bBBmDjx49avGMQaA2a4Qr1DdOioiIQFNTE3Z2diwpYhcu9DqvDxeCUuu37KlL3fY9pHBycsLixYuhq6uL6upqaGpqomvXrjh69ChRHVzTsnPnTnTt2hWnT5+GlJQUvn79ChcXF2zfvh0HDhwgqsXW1hZqamqQkZHB5s2bsXv3bpSUlGDz5s1EdQC1JcxdXFwwatSoRh16nTp1IrL2i4qKorCwUCib9fPnz8RL+0ZFRRGdrzkUFRXhzJkzyMnJQU1NDYDaZ/arV68QHh5OVMuZM2fAMAxqamogIiKCvLw8KCgosFIFTV1dHVu2bMHmzZvRtWtXBAQEoG3btkTPavb29rhz5w7mzJmDsWPH4unTpw3eo6urS0xPfZ4/f46wsDBERUWhpqYGVlZWgr7wt2/fhouLS4vOn5ubi969e+PRo0eQkZFB7969AQDfvn1r0Xnrw5X9XJ8+fRATE9No2emYmBjB/SFNVVUVsrOzkZ2djYKCAvz66694+vQpjh49io0bN7Z4O8acnBwsXLhQkNgTERGBdevWoXfv3jh06BBOnjxJpF0bl/pXc0kLn4iICNZadvDhmlMcADw9PVFaWoorV65AVVUVHz58wLZt27B79264u7uzpiszM5O1uevDlpa6ZzARERG0a9dO6DrJXFguaaFQmgt1jDdBQEAA1NXVBQei/Px8yMvLCw5EXbt2JRbtfuHCBRw+fBh9+/YVjGlpacHBwYGoQ5orOgDAw8MDioqKkJKSIjpvXbi0iftZ1C1pg2VT1NTUoKCggOic/BLyPB6PeDn5pigpKcHVq1cREhKC1NRUGBoaYtWqVcR1fPjwAcHBwQgLC0NlZSVMTU0RGBiIXr16EdfCJQewm5sbxowZI8joqaioEDKk9ujRA7GxsUS0jB8/HjY2NrC0tGxQfppUnys+vXv3xrFjx4TWPj8/P0Hp/bt373LmN9aaYdtJk5CQAFtb2yafS2w9j+pnDF68eFEoY7BTp06YOXMmES16enq4ePEiDAwM0KFDB4SFhaGiogJTp04lMn9duOQA4BIdOnQgWoq1KbgSlHr69GliczUHRUVFBAYG4tmzZ4JSl+rq6qx8b7mkJS4uDtHR0YLzkYyMjMAhzAZ1+w+zaeg9ceIELl68iKKiokbXXDk5OSJVm4yNjbFs2TKsWLECnTp1wsePH+Hl5UW0RCsABAUF/fQ9pM+5Tk5OeP/+PRQUFFBSUgIVFRXcv38fs2fPJqoDqG2jt3jxYhw4cADq6uo4ceIEYmJicOLECXTr1o2oFicnJ2zatAmlpaVYs2YN7O3tUV5eTjTAm1/29MyZM43av9iodgPUBmKGhYXhw4cPGDZsGFxcXGBoaCgIWB04cCDmzZvX4o7xDh06ICEhAaGhoRg8eDAA4MqVK8TPtKQrcTTFnDlz4Obmhi5dugiVK79//z527tyJrVu3EtWTnJyMsLAwXL16FTweD6ampjh79qzAQX/jxg0ijvF9+/bh999/x+rVqwEABw8exKJFi+Do6Ijw8HAcPHiQSGa/qKhoi/+/NhcuaeFjYWEBNzc3mJmZQVlZWejcynagLJvcunULQUFBgoTBXr16Yffu3Zg0aRKrjnGu2LkBbmmhUCjNhzrGm0BCQgJGRkaCA9Hx48dZOxDxo1Dr0rt3bxQXF7dKHUBtZPCDBw9YdYwDtZnaz58/x7Bhw1g5uPPhykGIi/ANO6dPn2Y9mOHBgwcIDg7GzZs30a1bN5ibm+Pw4cPEM7QvXryI4OBgPH/+HAYGBti8ebOgTQRbcMkBrKGhASsrK2zevBn9+vXDvn37kJycDC8vL+K9kfkl7QMCAoTGeTwe8fuyadMmLFq0CJcuXRIYdGtqanDkyBEkJSXhjz/+IJKRVlVV9cOM/erq6hbXwEUtfNh20hw/fhwA955LXMkYBAAvLy+EhIQIsvilpaWxbds2fP78GTY2NkQ08OGSA4DSEK4EpTanPynJSklTpkxBaGgo1NXVhdoqGRkZEQtc46KWmpqaBoY5Ho8nVLq7pbGysvqpcZB0oMXBgwcRHBzM+pq7Zs0auLq6ws7OThB0OWXKFDg6OhLTANSeX2VkZNCnT59Gs3fYMO4mJCQgKioKOTk58PHxEbQtunLlCnEtHh4eMDMzE6y7a9asgYyMDNzd3eHn50dUi7KyssBZpqysjLi4OFRWVkJSUpKYhpcvXxKb678hNDRU0FO8ffv2Da6rqKhgw4YNLa7DwcEBNjY2aNu2LQICAvDo0SM4OTnh4MGDLT53fVJSUvD33383+F2TPDMaGxvj+fPnmDVrFlRVVdG+fXtkZ2cjLy8PS5YsIR6oNXv2bAwbNgyurq4wMjJq8Dzs06cPjIyMWlzHgwcPEBYWBgUFBWRnZyM9PR2TJk0CUNsygVTAAJcyNrmkJTExEdra2jh58iSAWnsZ/1nIVrsrLvHt2zfIyMgIjf3yyy+CCi9swaVgBba0VFRUCFU5KCsrE3pdUVHRKrVQKM2F9hhvAisrK+jq6mLJkiUQFRVFVVUVjh49iqSkJOIHInNzc9jZ2QlFk1+7dg3Hjh1DcHBwq9MBAJMnT8bx48eJ9/mqy65duxAaGgodHR3Ex8fD2tqaeOb8Pw02+lDyYbvHuKGhISoqKmBqagpzc3P8/vvvrGnp3bs3FBQUMH78eMjLyzf6HtJBBE0dSHk8HvHeUnZ2dlBUVMSGDRsgLS2NwsJC7Nu3D58/f4aXlxdRLVyjpKQEsbGx+PTpEzp37gwjIyNISkqiuLgY1dXVDdqOtATNMV6QckZwSUtdqqurkZ+f38AxT/rAxgUDXV24kqU9YsQInDt3TiibKD09HfPmzcOtW7eIauHSfpfSEG1tbSQkJKBNmzaCsZqaGujq6hLt0Va/5259eDxeizs709PTceTIEQC1pS5NTU2FrpeUlCAxMREPHz5sUR1c01IXR0dHiIqKwtXVFe3atUNpaSmcnZ1RXV2Nffv2EdHAxfZOXFpzgdoS4Z8/f4aioiIrTuiTJ08iODgYlZWVmDp1KqZMmUJk//Yj9PX1ER8fjy9fvsDCwgI3btxAVVUVDAwMiPZpBgAdHR0kJCQIfTbV1dUYNGgQsbNkc1o2sbWX4hIPHjxA3759IS8vjzt37kBMTAxDhgwhruP79+8AapNrSkpKUFZWRtxOtXfvXhw/fhxKSkpCbZ7YOEsDwIsXLxATE4O8vDwoKSlh7NixrNg/vL29sWDBAtYTaur23r169SqcnZ0FQYdVVVXQ1dUVXG9JuNS/mktatLS0kJSUhKysrCbf05or49na2qJnz55YvXo1eDweGIbB7t278erVK5w4cYJVbSUlJRAXF2808L01aFm/fv1P95KkqsxwSQuF0lxoxngTvHjxAqdPnxb8qEVFRbF48WIMGjSIuJYlS5ZgxYoViI6OhpqaGtLT03Hz5k3iDhqu6AAAMzMzLFy4EBYWFpCTkxNafEkdEq9cuQJ/f3/07NkT8fHx2Lp1K3WMcxg2ej3W5dOnTwBqy6I2ZTwmFTDA7wP36tWrRq+zYaRjw3nYFH/++ScePHggiChXUFDApk2bMGLECGIa+FHLTRngeDwedHR0iOnhIy0tLYhurwvJqgdc+q5wSQufa9euwcnJSai3IRuR7j8y0LFhzOVKxiBQe2ju1KmT0FinTp1QVlZGVAfArf0upSFdunTBjRs3hIJSb9y4gS5duhDVwYUKEL/++ivk5eVRVFTU6HUFBQVizl8uaanLmjVrsGDBAujp6UFOTg7FxcXo0aMHjh07RkwD29WZGoNLay5Q21e1sQxXUixYsAALFixASkoKgoKCYGJiAi0tLUydOhUjRowQCsQhRefOnZGamor+/fujtLQUhYWFEBUVRXl5OXEt0tLS+Pvvv9G9e3fBWEZGBn755RdiGn5mX2FrL8Ulzp07h3379uH8+fOQl5dHQUEBduzYgQ0bNhC/N7m5ucjJyREEglZWViIqKgrz588npiE8PBxHjx6FgYEBsTmbgmEYqKiowMHBgW0pOH36NJYsWcK2DMjKyqKwsBAKCgp4/PgxtLS0BNfevXvXZLLC/xquOKIBbmnh/3Zbs/P7R6xevRpWVlYIDw9H586dkZWVBR6PJ8iwJ8nbt2+xd+9eHDp0CDdu3ICjoyOkpKRw+PBhaGtrtzotO3bsIDJPc+CSFgqluVDHeBNw4UDEZ/To0Thx4gRCQkLw/PlzdO7cGefOnRMq19eadAD/KcFX31BH8pD49etX9OzZE0BtRk9OTg6ReblO7969m3Ss8p0zbMDfmLx+/RpiYmLo2rUr0fm51J+TCwZuPlx0AIuKiqKwsFCov+znz5/Rtm1bYhoWLVqEpKSkJrP02CjnFR8fD1dXV7x//75BBnBrLi3GNfbs2QMbGxtMmDCBaPnc+nDJQAcAly5dEsoYHDVqFHr27Il58+YRd4z369cPPj4+QoY6Pz+/Bu1qSMCl/S6lIfWDUj98+IDY2NhWW71k7dq1AGod04sXL6Za6qGiooLIyEg8efIEBQUF6Ny5MwYMGMBKq5yqqiocP34cYWFhyMnJgaqqKmbMmMFK6ykurblcgl/+38nJCdHR0Th58iScnZ0xefJkrFy5kqiWWbNmwcrKCpGRkTAxMcG8efMgKioqCOYliZmZGRYvXgwbGxuoqKggOzsbvr6+MDc3J6aBi4GXXOPkyZPw9/dHr169ANRWN+zVqxdWrVpF1DF+7Ngx7Nu3r0HZ5T59+hB1jJeWlhIN4m6KjIwMLFy4EJmZmejXrx+8vb3RsWNH1vQMHz4cPj4+MDc3Z7Xa5MiRI+Hu7o4xY8YgIiICzs7OAIAvX77gwIEDGD58OGvaKLQ/9M/o1asXrl27hpiYGBQWFqJz584wMDCAtLQ0cS3btm2DsrIyGIaBp6cnli1bBikpKezYsQOXLl1qdVru37+PYcOGCV5fu3YNUVFRaNu2LaZPny4UhNOatFAozYWWUm+CAwcOICoqqsGByNTUFH/88QcRDZmZmVBVVSUy1z9BB9fQ1tYWKmOpp6fXrB6M/3bi4+N/urEk1Yfy48eP2LBhAyQlJeHu7o7ly5fjyZMn4PF4GDhwILy9vVnN2KD8p2xVU8ZJNhzAbm5ueP78OVasWCHope3l5YUBAwYQ6VXHVczMzNC7d2+YmpoKZQADZHvLUn4MV55Furq6ePz4MWcMDVpaWnj8+LHQd7eyshLDhg1DfHw8US3Pnz/HwoULISkpiY4dO+LTp0+oqqrCiRMniDtquLDfpfyYuLg4hISECBydFhYWrASlcgkjIyOYm5vD3Nyc9f6CXNLCd8g8efJEEMAmKysrcByRZM+ePbh+/TpsbGzQqVMnpKenw8/PD9OnTydeYYtLay5XKS0tRVRUFPz9/ZGeno6UlBTiGlJSUgQB1idPnkRpaSkWLlwIWVlZojqqq6tx+PBhhIaGIi8vD506dYK5uTlsbGxYCTLJyMjA1atXBQEmpqam9PyK2tLUiYmJDVqN6Onp4cmTJ8R0GBgYYOPGjRAXF0dsbCxWrlwJd3d3dOrUCatXryamY82aNRg+fHijlb1IYm1tDWlpaZiZmSEgIADS0tLw9PRkTY+hoSE+ffrU6HmEpI3hy5cvWLFiBZKSkjBx4kR4eHgAqP0eKykp4fz58/R3zSJ9+vT56R6OjZYEbBMaGsq56iTDhg3DrVu3kJOTg3HjxiE+Ph5SUlLQ1tZGUlJSq9PCt6cCQFBQEDw8PDBlyhRUVFQgMjISu3btwpgxY1qdFgqluVDHeBNw4UBUd1EBarOd2OiFyRUd9SksLER4eDiys7OxbNkyJCQkYOTIkcTmr39fuOKMiIyMxMSJE9mWwQmWLl0KcXFx8Hg8PH/+HN27d4ezszNERUWxbds2AGD1oEbhJt++fYOrqyuioqJQUVEBcXFxTJkyBU5OTpCUlCSiITs7+6fvIW2A19TURFxcHCQkJIjOS/nvsLa2xpo1a1g39nPFQMfHysoKgwcPFsoYPHbsGB4+fAh/f3/iej5//oxbt24hNzcXnTp1gqGhIWRkZIjr4MJ+l9I49+7dQ0VFBUaNGgVjY2NUVFQAADp27Ah/f39WK0KwTXR0NEJDQ3H//n3o6OjAwsICY8eOZeX5xAUtlZWVWL9+PdTU1LBixQqoq6sLvi8SEhKIjIwkHuRsaGiIM2fOCPX1fvv2LRYtWsRKNixX1lyu8fDhQwQFBSE2NhbdunWDubk5TExMiLbIoTTNvXv3sGTJEvTr1w8qKirIyMjAu3fv4Ofnh4EDB7Itj1WmTp2KWbNmwczMTDAWFhaGc+fO4eLFi8R08HtHf/r0CUuWLEFwcDAKCwthaWlJdK1btmwZYmJi0LVr1wYOVpKV63R0dHD37l20a9cO2dnZmD17Nm7dukVs/vr8yD7HhcDu+/fvQ1dXl56vWUZdXf2npd3rrjWthfo2bycnJ9Z7RA8aNAh3795FSEgIgoKCcPHiRRQWFmLixIl49OhRq9PCfwYBgKmpKdavX4+hQ4cCAG7fvg1PT09ERES0Oi0USnOhpdSbQEREBA4ODqz2xakfs7B7925WHNJc0VGX58+fY8GCBejevTv++usvWFlZYfny5XB2doaFhQURDVVVVQgNDRW8rqysFHoNkOt3XhdXV1dWHePe3t4/fQ+p/oNPnjzB7du3UV1dDR0dHQQEBAj6N7m6usLY2JiIDkrTcNEBLCkpiR07dsDd3R2fP3+GoqIi8axXIyMj8Hi8BusvHzYy6bt27Yrc3FwhIzeFO/DXXgUFBVhbW2P8+PENDNske79+//4d69evx9GjR1k10PFZv349Fi5ciIsXLzbIGGQDUVFRQeBWdXV1k7/1loYL+11KQx4+fIhly5YJSm3m5uZiy5YtqKmpgbe3N4KCgjBjxgyWVbKHsbExjI2NUVBQgPDwcJw+fRru7u6YMGECLCwsMGDAgFalxc/PD+np6Vi2bBmAWmc4P+PX3t4ep0+fZqXijZKSktBrFRUVlJSUENcBsLvmculsBADv379HSEgIwsLCUFlZCRMTE1y4cAG///47MQ31efPmDXbs2IGMjAxUVVUJXSOdpZeXl4fjx49jw4YNSExMhIODAxQUFLB//3706NGDqJZ9+/bB3d1dyKZw8eJFeHh4EHX+cpEVK1Zg8eLFuHjxIlRUVPDx40ekpaXBx8eHqA5lZWWUlJSgQ4cOyMzMBMMwUFBQwOfPn4nq6NWrFyvVQepTU1ODdu3aAWB3zeejp6eHmpoapKamIjMzE8rKytDS0hKqNMAmdcsOU9hDVFS0VTq+f0b9vRIXsuaHDBkCBwcHvHz5EtbW1sjIyMDatWthaGjYKrXUtVPm5+dj0KBBgtcGBgZwdHRslVoolOZCHeNNwDAMTp8+jcDAQGRlZUFJSQmWlpaws7Mj5iCpPw9bRlOu6KjL9u3bsX79epibm0NXVxdqamo4dOgQtm/fTswx3r59e6Eej/Ly8kKvSfY7rwvbn8/PStKSdjDyeDzBP3Wzq/iGMQq7cNEBDAAxMTEN1n9TU1Ni83Ph0FGf8ePHw8bGBpaWlg2M3VwrsdUaqbv28oPG6kJ67eWKgY5Pv379cP36dU5kDH748AHz589HZWWloHz5rl274O/vj549exLR4OPjA1tb2x86bEg6aijCnDx5Eq6uroKKC6KiooJ1tk2bNrh8+XKrdozzUVRUxOTJk9G2bVtcvHgRQUFBuH79Ojp27AgPDw/06dOnVWiJiorCtm3b0KVLFwDC6/3ixYuxfv36Fpu7KWbPno0tW7Zgy5YtkJaWRnl5OXbu3ImZM2cS18L2muvt7Q0ZGRn06dOn0f0u6efz+PHjIS8vD1NTUxgaGkJUVBRfvnxBQkKC4D2ke3s7OTlBXl4e1tbWrFfDcHNzQ1lZGRiGwdatWzFhwgRBWy7SFWYyMzMbVN4xNzdnPWOPCwwdOhRhYWGIjIxEXl4eRowYgZ07dxIP4NXV1cWyZcuwf/9+9O3bF3v37oWEhAQ6dOhAVAdX92xst1TKy8uDvb09Xr58CTk5ORQVFaFr167w8/Njtfc5hVuwbUPlKlz0Bbi7u8PPzw/a2tqYO3cuXr58iX79+mHVqlWtUktVVRWePHmCvn37YsCAAXj9+rWgcuDLly8FiWGtTQuF0lyoY7wJTp8+jZMnT8LW1haqqqpIT0/HiRMn0KZNG+J90fiwvankwwUdr169wuTJkwH8R8/w4cOxYsUKYhrYKAP4I5ycnAAA5eXlgr8BED84nzlzhuh8P2LIkCHYtGkTampqICEhgUOHDmHRokX4/v07PDw8oK2tzYquT58+ce4gVr9MEim46ACOiIiAq6srpk+fDiMjI6Snp8PFxQXl5eXEqmV07twZQG0lCm9vb1haWkJNTQ3+/v4oKioSZIWR5MKFCwCAgIAAoXG2goAowvDX3ry8vAaBCwDw+vVronq4aKDjSpb29u3bYWxsjDVr1qBNmzaoqanB7t27sWPHDvj6+hLRkJCQAFtb2yaD2biw12vNpKSkCLV6qftdHTNmjKA3ZWuloqICN2/eRFhYGO7fv4+ePXvCzMwMpqamkJWVhbe3N5YuXUpkj8EFLRkZGULZvgoKCoK/1dXV8enTpxabuz78HtH87+yVK1cgIyOD0tJSVFVVQV5ennjGCNtr7rp16xAcHIzc3FxMnToVU6ZMgaKiYovP2xQMw6CwsBD+/v6NOnrZCEp98+YN4uPjIS4uTnTexnj27BmioqKQl5eHly9fws/PDzIyMtDX1yeuRUdHB7GxsRg9erRg7OHDh+jfvz9xLVykW7durO83169fD09PT1RVVWHDhg1YsWIFvn79ykrwwsWLF3HmzBnk5uYiJCQEO3bswPbt2yElJUVcC1fYuXMnunbtitOnT0NKSgpfv36Fi4sLtm/fjgMHDrAtj8IRuNL6i+tw4XwoJSUFBwcHFBQUICUlBUpKSti0aVOr1aKnpwcHBwd8+fIF7dq1w969e+Hj44Po6Ghs3boVc+bMaZVaKJTmQh3jTXDhwgUcPnwYffv2FYxpaWnBwcGBNcc45T8oKCjg3bt3QlH+7969a1CutTXBd6TxeDzB362dTZs2wc3NDe/evYOHhwcYhsGIESNQXV0NNTU1Yg6I+kyaNIkT/ejrwpaDiIsO4OPHj8Pb27tB6R83NzfibSS2bduG5ORkTJ8+HUBt1uuOHTtQUVGBtWvXEtXCtWAgSuOMGzeuQZBLdXU1pk+fTjz4hUsGOrYzBuvy9OlTeHl5Cco4tmnTBsuXLydaTvH48eMAuBXMRvkPFRUVQtUM6lYkkpKSQk1NDRuyOMOQIUMgIiICExMTBAYGol+/fkLXJ0yY0KC90b9Zi4iICCoqKiAqWnu0j46OFlyrqqoi6mxko1XGz2B7zV2wYAEWLFiAlJQUBAUFwcTEBFpaWpg6dSpGjBhBvKTvy5cvic7XHLp06YKSkhKhoA62+PbtG9q2bYsbN26gV69ekJeXR0lJieD3RQJ+kHt1dTVWrFiBkSNHQlVVFbm5ubh58yZGjRpFTAvXMDU1RUREhKDqWGOQDLyWlpYWtD1RUFBAVFQUsbnrcurUKQQEBMDa2hq7du2ClJQUcnJysH37dmzdupWYjvLycsydO1fwurS0VOg1QPY5ERcXh+joaMHZQ0ZGBi4uLq36N0RpyM/6i1O4Q0lJCdatW4fY2FgwDAMej4fBgwdj//79+OWXX1qdFn5buMzMTDx79gwVFRUAatdeGxsbzJ8/n4gOrmmhUJoLdYw3QW5urqDkA5/evXujuLiYmAaubCq5oqMus2bNgp2dHezt7VFVVYWoqCgcOXJE4DxqjfCjpU+fPs165DRX4PeDq4u+vj7y8vLQo0cP1kr1caEEEdfgkgM4Ozu7QVaInp4e0YwrPtevX0dERITAUKijo4OjR49iypQpxO5LYmIitLW1hUps1oXH40FHR4eIFkrjfPjwAdbW1mAYBt++fWtg7CkvLyceMMUVAx0ftjMG6yIiItLAAVBSUgJJSUliGprjqKOVINhDQUEB79+/R7du3QAAgwcPFlx7//59qw4EBWpLHY8ZM0awj6uoqBBy/vbo0YNYMBcXtHTt2hXJyckYMmRIg2vx8fH47bffWnT+uujp6Qn+5kpfVy6suUBt9r66ujqcnJwQHR2NkydPwtnZGZMnT8bKlSuJauEK/L2lgYEBli5dioULF0JWVlboPaTLuqurq8PFxQWJiYkYP3488vPz4ebmJvTdJoWCgoKglVNxcTHExcUxfvx44jq4BD9JxcHBgVUdP2pFw4ekTSYgIACHDx/Gb7/9hj179kBWVhYHDx4k3jd5yZIlQq/Z+N3UpaampkEARf0WexQKpXHKysqEWgExDNOgNRDpCjOenp4oLS3FlStXoKqqig8fPmDbtm3YvXs33N3dW52WK1euwMTEBKqqqlBVVRWMk2oxy1UtFEpzoY7xJujSpQtu3LiBcePGCcZu3Lgh6N1GAq5sKrmioy5z586FiIgI/P39UVNTgwMHDmD69Ok0AgnU6doY79+/R3x8PIqLi6GoqIhBgwaxchjiOyKqqqqEnBJccD6w7djkggOYT8eOHZGQkCC01iUkJEBFRYWoDgD4/v072rVrJzQmLS2NqqoqYhoWLVqEpKQkWFlZNXqdrT7wlP/QpUsXbNy4EUVFRXBxcWlgiJOQkCBuWOaKgY4P2xmDdRk5ciRWrVqFzZs3Q1VVFRkZGdi6dStGjhxJTEPdDOTGoC0S2GX48OHw9fVtNIjEz88PhoaG5EVxCA0NDVhZWWHz5s3o168f9u3bh+TkZHh5eTXaSuLfrsXU1BTbtm3DqVOnhIImCgsLsXPnzgYBzSTgUl9XLqy5dWnbti3GjBmDyspK+Pv749SpU63WMV5/b1m/sg0be0wPDw/s3bsXOjo6sLOzQ1paGioqKoga3GkP8abhBwpcv34du3fvhrS0NCs6+K1o6raOqAvpksNFRUWCYDq+HkVFRaJnRoB7rZT09fXh4uICV1dXtGvXDqWlpXBxceGETZNC4TpcrAJ069YtBAUFCVrS9OrVC7t378akSZOIO8a5oGXLli0wMTEhMtfP4JIWCqW58BjqRWuUmJgYrFixAmPGjIGamhrS09Nx8+ZNeHl5sXaIplCaAz+7k1J7KHRzc8OFCxcgLi4OWVlZfPnyBRUVFZg3bx7WrVtHVA/f+JOUlAQtLS0AtYdmNjecX79+RXl5OX755RdISEiwpkNHRwf3799H27ZtBWPl5eUwNDREXFwcUS2XLl3Crl27MH36dMH6HxgYCCcnJ+LRjvb29ujQoQM2btwIcXFxfP/+HTt37sSnT59w+PBholoo/wweP37MCWOPnp4e4uLi0KZNG+jq6iIhIQHV1dUYMmRIk32tW5Jhw4YhPDxcKGMwPz8fZmZmuHfvHlEtxcXFcHBwQEJCgsBwOmLECOzevZt4CTgKN/n48SMmTZqE4cOHY8aMGejQoQNycnJw6dIl3L17F5GRka06a9zOzg6KiorYsGEDpKWlUVhYiH379uHz588/Dfr4N2qpqanBokWL8OzZMxgZGaFDhw7Izc1FbGwsBg4cCB8fHyI66rJ69WrBPrxuX9eqqirifV25tOY+fPgQQUFBiI2NRbdu3WBubg4TExPIyckR1UH55+Dv74/AwEBkZWVBSUkJlpaWsLOz40SvVzYZNGgQ7t69y1pfeoZh4O3tjbS0NAwbNgyzZ89mRQefuXPnYvz48Zg5cyb09PTw+PFjREREIDAwEGfPniWqpaSkBHl5eQJHfVBQEF68eIExY8Y0qMrW0mRnZ2PBggXIysqCnJwciouL0aNHDxw9epR4kBaFQvn/R19fH/fu3RNa+79//44RI0YQtzFwQYumpib+/PNPInP9DC5poVCaC3WM/4C4uDiEhIQgPz8fnTt3hqWlJdTV1dmW1arhWskqPpGRkZg4cSLxeX/E69evISYmhq5du7Kmge37cvz4cZw7dw7btm0TlJesrq7GgwcP4OzsDHt7e1bK7/MPq2zBMAwOHz6MgIAAFBQUCMZ79OiBefPmwdLSkrgmrjmAg4ODERwcLFj/p06dCmNjY+I6MjIyYG1tjezsbMjLywuyAY4ePUqsNHZ2dvZP38NGNj2lcRiGwenTp1k3onLJQAcAmzdvRmZmZoOMQTU1Nbi5uRHXA9T+vgsKCtC5c2fiWa5NtUbgQ1sksM+rV6+wZcsWJCcnCzLSBgwYgG3btqFnz55sy2MVPT09PHjwQKj6D1tGMa5oqampweXLl3H16lV8+vQJSkpKGDduHGbMmAERERFiOvgMGzYM0dHRQtmcX79+xahRo1jbA7O15r5//x4hISEICwtDZWUlTExMYG5ujt9//52Yhn8Cf//9NyIjI5GXl4fOnTvDxMSElf1lUVERzpw5g5ycHNTU1AAAKisr8erVK4SHhxPV4u/vj5MnT8LW1haqqqpIT0/HiRMnMGvWLEFJ8dbK1q1bkZmZCVNTUygpKQntcUlUSdq9ezdCQkKgo6OD+Ph4WFtbs/qZPH/+HPPnz8dvv/2G1NRUDB48GMnJyThx4gQGDhxITMfbt28xZ84cGBkZwcPDA6dOncLevXthaGiI+Ph4eHp6Eq/WVFVVhYSEBBQWFqJz584YMGAAK89FCoXy/4+trS169uyJ1atXC85Hu3fvxqtXrwQ9rluTFi0trQbVdtiCS1oolOZCHeNNsHjxYlZLM1Eap3fv3pCRkUGfPn2aLFnFRvYt247Ojx8/YsOGDZCUlIS7uzuWL1+OJ0+egMfjYeDAgfD29mYls4jt+zJx4kRs3rwZgwYNanDt7t278PLywuXLl4nr4mdPssXRo0cRFRUFe3t78Hg8+Pn5YcqUKeDxeDh27BhsbW2JR71zwQHMVaqrq5GYmIj8/Hx07NgR6urqEBUl1wmld+/eTZYJBGgpda7BFSMqVwx0fBrLGDQwMMCuXbuIZQw2Z90nVfK+d+/eP7xOf9fcIScnR+DopEFItQwZMgQhISHo0KGDYCw3NxdTp07FnTt3Wq0WLjFkyBDcuHEDUlJSgrGSkhKMGzcODx48IK4nNzcX6enpDfYyJNbcPn36QF5eHqampjA0NGx0D0e63QnX4Ffr69+/P1RUVJCZmYnXr1/j+PHjxIO07O3t8f79eygoKKC0tBSdOnXC/fv3MXv2bDg5ORHVMn78eHh6eqJv376CsbS0NDg4OODmzZtEtXCNpvYxpPYvI0aMgK+vL3r27In4+Hhs3boVERERLT5vfW7evIlRo0YBqN0vREREICsrCx07doSpqSnxfcOyZcvQsWNHrFu3DiIiIhgxYgTmz5+PhQsX4s6dOzhx4gTOnDlDTM+UKVOEWtjxMTIyQmxsLDEdFArlf8OrV69gZWUFcXFxdO7cGVlZWeDxeDh58iR+++23VqeFb6v7EaTO9FzSQqE0F+oYbwK2SzNRGufkyZMIDg5GZWUlpk6diilTpgj6ebAJ247OpUuXQlxcHDweD8+fP0f37t3h7OwMUVFRbNu2DQDg6elJXBfb90VTUxNJSUmNPpzZLOnr4+PDakS5kZERzp07h06dOgEAsrKysHLlSgQGBiI1NRUrV67E9evXieti2wHMp7S0FOfPn8f79+8FmSJ8SPf8s7KygoWFBcaNGwdJSUmic/PJysr66Xtae/ACl+CSETUnJwfh4eHIzs5mzUDH58mTJ9DU1ER2djZrWdp8I27dZ5KsrCy+fv2KmpoayMnJ4dGjR0Q1USj/RNzc3PD8+XOsWLECnTp1wsePH+Hl5YUBAwZgw4YNrVYLl3B0dISoqKhQX1dnZ2dUV1dj3759RLWcOXMGO3bsQHV1tdA4KQcaDUT6ORMnTsSiRYswZcoUwdjly5cREBCAoKAgolq0tbURFRWFnJwc+Pj4wNvbG2FhYbhy5QqOHz9OXEtCQgLatGkjGKupqYGuri4SExOJaqEIU7dkbFVVFYYMGcJKQoCmpibat2+POXPmwMLCgvXEniFDhuD69euQlpbG+/fvMX78eFy/fh1qamooLy/HsGHD8OTJkxbVkJ6ejiNHjgAAIiIiBH3p+ZSUlCAxMREPHz5sUR0UCqVlKC4uRkxMjKAKhIGBAWtrH9taBg4c+NO9Cak2e1zSQqE0F/Ieh38IJiYmWLZsGWulmSiNs2DBAixYsAApKSkICgqCiYkJtLS0MHXqVIwYMULo0EgCftR4eXm5UAQ5aefZkydPcPv2bVRXV0NHRwcBAQGQl5cHALi6uhIvAc2V+8Lj8ZqMWBMREUFlZSVRPXxmzpyJvLw81vp6f/36VajPrqKiIt6/fw8A6N+/v1B5dVJwwQHMx8nJCX/++Sf09fWFSqOygaGhIXx9feHu7g5jY2NYWFgI+tOTgu/0rqyshLe3NywtLaGmpgZ/f38UFRVh2bJlRPVQfkxubm4DI3zv3r1RXFxMXEuHDh2waNEi4vM2xh9//IHbt29DTU0NampqrGh4+fIlAMDX1xevXr3Cpk2bICMjg7KyMuzYsQOysrKs6Pr06ZMgw0hZWRkmJib49ddfWdFCoTSHNWvWwNXVFXZ2dqioqIC4uDimTJkCR0fHVq2FS6xZswYLFiyAnp6eUF/XY8eOEdfi7++PLVu2wMLCgpWAS/7aT2ma7OxsTJo0SWjMzMyM+NkRAERFRdGhQwdISkrir7/+AlDruN+1axdxLV26dMGNGzcwbtw4wdiNGzfQpUsX4lq4SEVFBe7cuYOsrCxMnz4dHz58+Gkgyv+KunYnNtYVPvfu3UNwcDACAwNx4MABmJubY86cOay10ysvLxc4hZ4+fQoFBQXBvrtNmzYNApRagl9//VVQga4xFBQUiAdoUSiU/z9CQ0MFwXNycnKstH/kohYRERHOOJu5pIVCaS7UMd4E/P6Xt2/fFhonGdHNlX7aXNFRF3V1dairq8PJyQnR0dE4efIknJ2dMXnyZKxcuZKYDr7DiMfjsZ4xyXcC83g8IWcej8cjcgCpC5fuC1fgUl9vdXV1eHh4wNnZGSIiIjh8+LDAiHD58mVWjC1ccADziY+Px+XLl1lzntXF2toa1tbWeP78OUJCQrBs2TJIS0vDwsICkydPhrKyMjEt27ZtQ3JyMqZPnw4A6NevH3bs2IGKigqsXbuWmA7Kj+GKEbWpUlqioqJQUFDAyJEjsX79erRt25aIHjU1NTx79owThzVfX1/ExsYK/t/btWuHjRs3YsSIEVi1ahVRLc+ePcP8+fPRvXt3qKqq4tmzZ/Dx8YGvry+0tbWJaqFQmoukpCR27NgBd3d3fP78GYqKij8t3dcatHCJ6upqREZGcqKva2FhIaZOnUo8gJrSfNTV1XH9+nWhYO7Hjx9DQ0ODuJbOnTsjNTUV/fv3R2lpKQoLCyEqKory8nLiWpYsWYIVK1YgOjoaampqSE9Px82bN+Hl5UVcC9dIT0/HwoULUVlZiS9fvsDAwAAWFhbw9vbGyJEjW3x+rhTelJaWxty5czF37lzExcXhwoULMDU1xaBBgzB37lwMHz6cqB5FRUV8/PgRnTp1QlxcnFBS0cuXL4mdXflnUzU1NSxZsoTInBTKvxm222S6ubkJVZVxcnJiJXiOa1q48iwCuKWFQmkutJQ6h7GysgJQG3X57Nkz9O3bF6qqqsjJycHTp08xdOhQ+Pr6thodTVFaWoqoqCj4+/sjPT0dKSkpxDWwvUlYuXIlREREUFNTg9jYWMyYMQOLFi3C9+/f4eHhAaB5AQ7/a9i+L/3794e9vX2T148dO4Znz54R0cKlvt7v3r2DjY0NCgsLISYmBgkJCZw4cQKVlZWwtrbG4cOHiffz48N3AEdHR7PmAB4xYgRiYmI410qjuroa9+/fx4EDB5CWlgYJCQkYGBhg/fr1RMpTDx06FBEREULVBvLz8zFlyhTcv3+/xeenNA9+n84xY8Y0MKKSMBTyOXXqFMLCwrBixQqoqakhKysLBw8ehJ6eHrS1teHn54fff/8dmzZtIqLH2toacXFxUFVVhbKyspDj6vTp00Q08Bk0aBCCgoKEAsfevn0LKysr4mUd586di9GjR2Pu3LmCMX9/f0RHRyMgIICoFgrlvyEmJgaBgYHIysqCkpISLC0tG5RLbY1auELdcrpsY29vj3nz5mHw4MFsS6E0wcaNGxEaGgpDQ0N06dIFOTk5iImJgY6OjtAZgITh+fLly/Dw8EBkZCROnTqFR48eCbLIjx492uLz1ycuLg4hISHIz89H586dYWlpCXV1deI6uIadnR0GDhyIxYsXQ09PDwkJCQgJCcHp06cREhLS4vOrq6vDzc1N8NrV1RXOzs5C76nrOCFJXl4egoKCEB4eDgCIiooiNrenpyeSk5MxfPhweHt7w8vLC4aGhnjz5g22bNkCTU1NrFmzhpgeoDY4it/aadmyZUhISCB6JqJQ/g1woU0mv30FwK6tmUtajh07Bjs7O1bmrg+XtFAozYU6xn8Am6WZ6rJ+/XoMHDgQM2fOFIyFhITg+vXrgt45rUkHn4cPHyIoKAixsbHo1q0bzM3NYWJiAjk5OeJa2N4kFBYWws3NDe/evYO9vT0YhsG6detQXV0NNTU1+Pr6spL9yvZ94Qd1/IgzZ84QUMK9vt5lZWVITExETU0NtLS0ICMjg8rKSjAMw7pDmG0H8NGjR5Gbm4ulS5cKOYHZIiUlBeHh4QKjhqmpKczNzdGhQwd4enri6dOnAsNHS6Kjo4P79+8LZfiWl5fD0NAQcXFxLT4/pflwwYg6YcIE+Pr6CtY8oLbn+IIFCxAVFYWCggJMnjyZWFDFj4LDSFe92b59O+7cuQMbGxt06tQJGRkZOHHiBCZNmkS8NYG+vj4ePHggVAa0srISgwYNov1LKZwlIiICrq6umD59OlRVVZGeno6LFy9i/fr1mDp1aqvVAgAPHjzAmTNnkJubi2PHjsHPzw+rVq0iXup3woQJOHjwIH777Tei8zaGs7MzQkJCoK+vj/bt2wtdYyvDhyJM3dZbP4LU55WSkiKofHPy5EmUlpZi4cKFxFueLF68GLt37+ZEgAnX0NfXx7179yAuLi5wStTU1EBPT6/Fe1gDtWf7H8Hj8XDz5s0W19EYJSUlCAsLQ3h4OLKysogGMFdUVMDd3R1JSUmYOHGiIFtbXV0d/fv3h4+PD9Hv8/Pnz7FgwQJ0794df/31F8LDwzFx4kQ4OzvDwsKCmA4K5Z8K355rZ2cHHx8fQVYw6RazWlpaSEpKErxm09bMJS0UCuX/D1pKvQnYLs1Ul+vXr2Pbtm1CY5MmTRKKUG0tOt6/f4+QkBCEhYWhsrISJiYmuHDhAn7//XdiGhqDjejxuigoKGD//v1CY/r6+sjLy0OPHj1Y65PM9n0h5fRuDlzr6y0mJobBgwdDVFQUJSUluHv3LhiGYTWbpjEH8Pbt2wUOYHt7eyIO4IsXLyI7O7vRbElSrTT4GBsbIzMzE8OGDYOLiwuMjIyEjNtz584VClZqSXR0dLB9+3Zs3LgR4uLi+P79O3bt2sVayXtK0wwaNAiDBg1iVUNOTk6DwBJZWVl8/PgRQO1zi2RZUtLO7x+xZs0atGvXDkeOHEFOTg46deqEadOmsdKPXVJSEh8/fhQKnvv48SNr/c4plOZw/PhxeHt7C61zBgYGcHNzI+6M5pKWiIgIbN++HVOnThUY6GJjY8Hj8Yi3POnZsyemTZsGDQ2NBlV/SDujKyoqMHHiRKJzUv47uBSgwK/qxQ8UtrW1ZU3Ln3/+yXrAMleRkZFBfn6+UNB0Xl4esf1LbGwskXn+GxITE3Hp0iVcu3YNvXr1wuzZszF+/HiiGsTFxeHu7o7i4mKhhJWQkBCoqqpi165d2Lx5MzE927dvx/r162Fubg5dXV2oqanh0KFD2L59O3WMUyjNYN26dQCAb9++CfaSbAb+8OFS2yI2tTTVvo4Pj8dDWlpaq9NCoTQX6hhvAg8PD5ibmwtKM3Xr1g1bt24lXooUqDUeJyQkQF9fXzB2//59oqWFuaJj/PjxkJeXh6mpKQwNDSEqKoovX74IRWeRjlwDINSHMykpiTVH0fv37xEfH4/i4mIoKipi0KBBrDnFgf/cl9evX0NMTAxdu3YlroFhGGRkZODXX38VjEVFRWHcuHFE+xxyqa93cnIy7O3t4evrC3FxcVhbW6OkpAQMw0BWVha+vr7EM3y45ADesWMHkXmag7m5OczMzKCkpNTo9S5duuD27dtEtGzcuBHW1tbQ0tKCvLw8ioqK0K1bN9YDYCi1WFlZ/fRQRrJkuKamJtzd3bF582ZISEjg+/fv2LlzJzQ0NMAwDAIDA4mvMxcvXhRkUoaEhGDHjh3Yvn07pKSkiOoQFRXF8uXLsXz5cqLzNsaECRPg4OCAVatWCbJd9+3bhwkTJrAtjUJpkuzsbKHzCFBbxvDTp0+tWouPjw8OHz4MDQ0NnD9/HkpKSjh27Bjmzp1L3DHerl07jB07luicTcElpyulafz9/Ru0JLCzsyNucI6Ojsa+fftgaGiIqVOnYvjw4awZvU1MTLBs2TKYmppCSUlJSAcbNg8uYWpqiqVLl2LVqlWoqalBSkoKdu/e3eqCYIqLixEaGopLly4hIyMD48aNg7+/P2vl9l+8eIGlS5ciOzsb6urq8PHxgaysLKqqqmBhYYGcnByijvFXr15h8uTJAP7jvBo+fDhWrFhBTAOF8k+GHwSkp6fHyYCg1k5T9p1r167h3LlzGD58eKvUQqE0F+oYb4Lk5GQcPHgQPB5PsIGaPHmyoF8zSezs7LBo0SKMGzcOKioqyMjIQExMDHbu3NnqdDAMg8LCQvj7+8Pf37/BdR6PRzyjsz729vbE+4swDAM3NzdcuHAB4uLikJWVxZcvX1BRUYF58+YJovxI8PHjR2zYsAGSkpJwd3fH8uXL8eTJE/B4PAwcOBDe3t4Nyhi2FGVlZVi4cCHat28vKKNbUFCA9evX4+zZszhx4gTatWtHRMvGjRthY2MDbW1tob7ez549w65du3D48GEiOoBaA6G1tTX69OkDGxsbTJ48GStXrkRNTQ327NkDNze3Rn9fLQmXHMB6enqoqalBamoqMjMzoaysDC0tLbRp04bI/HwYhoGxsbHQPakf1CEuLk4sk0RNTQ1Xr15FYmIi8vPz0bFjR6irqxMvz0ppHL5jJjMzEzExMbCwsMCvv/6KT58+4eLFizA2Niaqx9XVFba2ttDW1hYEUvTo0QNeXl6Ij4/Hvn37iLZhOXXqFAICAmBtbY1du3ZBSkoKOTk52L59O7Zu3UpMB1DbLuLatWt4//49ampqhK6Rzmxfvnw5CgsLsWTJElRWVkJCQgIWFhZwcHAgqoNC+W/o2LEjEhISoKenJxhLSEgg0m6Fy1o+ffqEgQMHAviPA6BLly4oKysjroVrzmiuOF0pjePv74+TJ0/C1tZWEKR14sQJtGnThnjG9sWLF/H27VsEBwdj06ZNaNOmDczMzGBhYQFVVVWiWs6ePQsADc5AXLB5sM2SJUvw/ft3LF26FN++fcPcuXNhaWnJqQpBJBg+fDjk5eUxbdo0zJgxg5idpSk8PDzQq1cvbN68GWfOnMHRo0dhYGCAJUuW4PfffyceUK2goIB3796hZ8+egrF3796xfp8olH8abHfhLSsrQ58+fQSvGYYReg2Qq+7IJS11zx9AbUu0HTt2IDAwEKtXr4aNjQ0RHVzTQqE0F9pjvAlGjx6N06dPQ0VFRdCzKCcnB7NmzWKlZMijR48QHh6O3NxcdOzYERYWFqxkJXNFBxcwMjJq1JiSnZ0tMIaR+q4cP34c586dw7Zt2zBkyBAAtYb3Bw8ewNnZGfb29pg+fToRLUuXLoW4uDh4PB6eP3+O7t27w9nZGaKiooJS/J6enkS0eHp6Ijk5Gfv374eioqJgvKCgAIsXL8bgwYPh6OhIRAvAnb7e2tragmCFwYMH486dO4L5KyoqMHjwYKK9ZbmS1c8nLy8P9vb2ePnyJeTk5FBUVISuXbvCz88PHTt2JKKhqaCOkSNHon///kSDOvhYWVnBwsIC48aNg6SkJNG5Kc1n1qxZWL16tdCzOTU1FZs3b0ZISAhRLTU1NUhOTsanT5+goqKCgQMHgsfj4fv37xATEyMabDJu3DgcPnwYv/32m2Bfl5ubCzMzMzx48ICYDgDYtGkTIiMj0bt3b6HAEh6PRyyr39raGr6+voLX3759Q0lJCdq3b08dRRTOc+nSJezatQvTp0+Hmpoa0tPTERgYCCcnJ+KlUbmkZerUqbCzs8Po0aMF69yDBw+wd+9eBAUFEdUCAOHh4QgLC0Nubi46d+6MmTNnwsDAgLiOppyus2bNYrVMNuU/jB8/Hp6enujbt69gLC0tDQ4ODqyWa62pqcGtW7fg4eGBT58+0RKgHMHb2xvPnz/HsGHDMHv2bBQWFkJeXr5V7l+uXLkCY2NjzgQqa2tr48aNG1BQUMCnT58wZ84cfPnyBTNmzMCKFSuIB5qfPn0ap06dgr29PXbs2IGtW7fiyJEjMDMzw8KFC4lqoVD+ybi6usLZ2Zm1+ZuTfFbfMdtScElLXTIyMrB8+XIUFxfD09MTmpqaxDVwUQuF8kMYSqPs37+fMTMzY+7fv89oa2szT58+ZebMmcN4enqyqqugoIDV+flwRQeb7N27l+nXrx+za9cuJjg4mAkODmaCgoIYDQ0NwWtSTJgwgXn06FGj1+7cucNYWFgQ06Kvr898+/aNKSkpYXr37s0UFhYKrn39+pUZOnQoMS1jxoxh3r9/3+i1tLQ0ZuzYscS0MAzDVFRUMJWVlQzD1N6LO3fuMLdv32a+f/9OVIeBgQHz4cMHhmEYxszMjPn48aPgWmZmJmNkZERMS2lpKTN9+nTmjz/+EIzl5+czAwYMYGbOnMmUlpYS08Jn1apVzMqVK5mSkhKGYRjmy5cvzMqVK5lly5YR07Bnzx5mzpw5TH5+vtB4fn4+M3XqVGbv3r3EtPA5ceIEY2JiwmhpaTEbNmxgEhMTiWug/BwNDQ2mqqpKaKyiooLR0NAgruXjx4+Mj48P4+zszHh7ewvWHTbQ1dVlqqurGYZhGB0dHYZhGKaqqorR09MjrmXIkCFMSkoK8XnroqmpKfRaV1eXJSUUyv+NoKAgZvbs2cy4ceOYhQsXMlevXm31Wh48eMAMHDiQWblyJaOurs44Ozsz2trazO3bt4lrOXHiBKOvr8/s3buXCQgIYHbu3Mno6uoyly9fJq7F2NiYef78udDY8+fPie53KT9GS0tL8IzmU11dzWhpabGkiGEePXrErF+/ntHU1GQsLCyYwMBAVnR8/fqVuXLlCuPr68tcu3aN+fbtGys6uMLOnTuZwYMHMw4ODoyenh5z7NgxtiVR6lD/vNGvXz/G19eXJTW1nD17lpkwYQIzcOBAZty4cYyvr2+D9YZCoVD+yVy9epXR1tZm7OzsmOLiYqqFQmkm1DHeBBUVFcyOHTsYDQ0N5vfff2cGDhzIuLu7E3dg8bXs3buX0dLSYgYOHMikp6cz5ubmTE5OTqvUwSUePnzIjBo1irl48aJgjA3jsoaGBlNTU9PoNdKGf319faa8vJwpLS1l+vTpw3z9+lVwraSkhBk0aBAxLT8zptR3DLQkf/75J6Ovr8+kpqYyr169YoYPH85oamoyGhoajIGBAfPmzRtiWg4ePMiMHz+eefjwIXP16lVm9uzZzKNHj5jbt28zxsbGRJ2uXHQADx06VOh7yzC1znGSv22uBXXUJTU1lXF3d2eGDh3KjBs3jvHx8WnVzwGuYWFhwZw4cUJozMvLi5kxYwZRHSkpKYyWlhZjaWnJrFixgjE3N2cGDhzIPHnyhKgOPlZWVsz58+cZhvnPczo8PJyZPXs2cS2DBg1qELxAmvrPP36wAIXyT8DNza3Bc5otuKSFYRjmxYsXjIuLC7No0SJm8+bNzNOnT1nRMWbMGCY1NVVoLCkpiZX9CxedrhRhzMzMmOjoaKGx6OhoxszMjLiWvXv3MiNHjmR0dXUZNzc35sWLF8Q18ElJSWH09PSYESNGMNOmTWOGDh3KjBw5knn79i1rmthm+PDhzKtXrxiGYZi4uDjGxMSEZUWUutTfX2poaDAVFRUsqWGY48ePsxJoT6H8W0hPT2eio6OZwsJCpqamhtm5cyczceJExsXFhRX/CEWYiooKxsXFhenfvz9z8uRJqoVC+S+hpdSbIC8vT9DXtW5pptevXwv1pyHBvn37EBcXBwcHBzg6OuLOnTtYs2YNREVFceDAgVang2vk5+djzZo1+OWXX7B161aMGjWKeI9xLS0tJCUl/Z+v/y9ZuXIlREREUFNTg9jYWMyYMQOLFi3C9+/f4eHhAQCC0tAtjYGBAUJDQyEvL9/gWnFxMSZOnEishO706dMxevRoWFtbw8bGBv369RPq652WlkasrzfDMDh06BBOnz6NL1++CMZFRUVhYmICd3d3iImJEdEyduxYHD9+HF26dGlw7cWLF1ixYgWuXbtGRAufIUOG4MaNG5CSkhKMlZSUYNy4ccS+L9ra2j8sZ0/yN90Y1dXVuH//Pg4cOIC0tDRISEjAwMAA69evZ6WvKuU/JCUlwd7eHu3atUPHjh2RnZ2Nmpoa+Pr64vfffyemY+7cuRg9ejTmzp0rGPP390d0dDQCAgKI6eDz/PlzzJ8/H7/99htSU1MxePBgJCcn48SJE4KevKTw8PCAkpISqyV8668h/LLLFMo/AT09PTx69IiVditc1rJ48WLs3r0b0tLSbEvB0KFDcfv2baH9ZEVFBQYNGkR8/2Jubg47OzuMGzdOMHbt2jUcO3YMwcHBRLVQGicmJgYrVqzAmDFjBC0Jbt68CS8vL4wcOZKoljlz5mDq1KkwNjaGhIQE0bnrM2vWLIwYMQL29vYAas9wXl5e+PPPP3Hq1ClWtbGFpqYm/vzzTwBAVVUVhgwZQvcvHIJr+0suPaMplH8a169fx8qVKyElJQURERFYWFgI2jfExMRg1KhRWL9+PdsyWzVmZmZ4+fIlZsyY0aRNY8qUKa1OC4XSXKhjvAkaczpUV1dDV1eX+GHeyMgIAQEB6NChg2Bj+eXLF4wZMwbx8fGtTgcXYRgGhw8fRkhICAoLC4l/R7jkGC8sLISbmxvevXsHe3t7MAyDdevWobq6GmpqavD19YWamhoRLevXr4eqqiqWLl3a4Nrhw4fx/PlzHDp0iIgWrvX1Bmr75v3999/4/PkzxMXF0bVrV+LGVC46gB0dHSEqKgpXV1e0a9cOpaWlcHZ2RnV1Nfbt20dEA5eCOuqSkpKC8PBwREVFAQBMTU1hbm6ODh06wNPTE0+fPkV4eDhxXRRhiouLcevWLeTm5qJjx44wMjKCjIwMUQ36+vp48OCBUM/DyspKDBo0iPhaxyc3Nxfh4eHIyspCx44dYWpqykogx6xZs5CUlARJSUkoKCgIXSPVS5VrhksK5b9h586dKC0thZmZGZSVlYX6ypL+TXNJy6BBg3D37l3B/pJNdu7cCTExMTg6OgruydGjR5GZmYmtW7cS1cIlpyulaeLi4hASEoL8/Hx07twZlpaWUFdXZ0VLTU0NUlNTkZmZCWVlZWhpaRHvjQw07tSrrKzE4MGD8eTJE+J6uED9syPdv9SSkZFBzMbyI9TV1eHm5iZ43VhfYpKOkVWrVqFnz54wNzeHsrIysXkplH8DkyZNwsKFCzFlyhRER0fD0dERAQEB0NDQwNu3b2FtbY3bt2+zLbNVY2Rk9MPrPB6PmH2BS1oolOYi+vO3tB4+fPgAa2trMAyDb9++YdSoUULXy8vL0blzZ+K6ysrKBIZTfhxD27ZtiR/OuKKDT2RkJCZOnMjK3PXh8Xj4448/oK+vz4pTqKKi4odZ2JWVlcS0KCgoYP/+/UJj+vr6yMvLQ48ePYhlIgOAnZ0dzM3NUVRUhAkTJkBJSQm5ubm4evUqgoKCcPbsWWJaZGRkkJGRgV9//RWdOnVCYWEhOnbsCKC2QoWcnBwxLXzS09Px5MkTFBcXQ0FBAfLy8sQd49LS0igqKmrSASwpKUlUDwCsWbMGCxYsgJ6eHuTk5FBcXIwePXrg2LFjxDQMHjwY586dazSo4/z589DQ0CCmhY+xsTEyMzMxbNgwuLi4wMjISMjpOXfuXMycOZO4rv/X3p3H1Zj//QN/naIGWStUGtswGVmKsjXa7AotxmAQIcuYydiHJLKPL5oGaTHWMEWJMIphRIUY+/Cbb9GC0oKydKrz+2PuztdRMWO5rqvO6/l43I+H6/qc+75e92HOOdf1/nzeHyqrXr16cHJyEjVDjRo1cO/ePZWHdPfu3UPdunVFyePr64sFCxZg/PjxKudnz56NVatWCZpl6NChGDp0qKDXfFVRUREiIiKUx3K5XOUY4Ixukq4tW7YAAPbu3Qvg79/hCoUCMpkMN27cUNssDg4O+Oabb+Do6Ah9fX2VIr2FhYUgGezs7CCTyVBUVIQHDx4gLCwMjRs3RlZWFrKysmBiYiJIjpf16tULQUFB2L9/P65duwYjIyPs3LlTtKIrlVXa7aBr165iR8HDhw/h4eGBmzdvol69esjNzUWzp1JlJQAAW/NJREFUZs0QEhKivHcTyqeffopLly6hU6dOynM3btyQRAFULFzXU77+/fvDzMwMrq6u6Nu3Lz766CNRcujp6cHPz095XL9+fZVjmUwm6O/LCxcu4NChQyodLsX6jiaqbFJTU5X/vfbu3RuamprK51AtW7bEkydPxAtHAIDjx4+LHUFJSlmI/ikWxl/StGlTzJ8/H7m5uVi0aFGZgoS2trZgDxVe1rFjR/j7+6vMuN++fTvatWunljlK+fj4SKIwnpKSgoSEBGVxUYzWqGZmZq9dtS9GEe3l90VXVxddu3YVtCgOAM2bN0dwcDC8vb2xc+dO5cPK1q1bIzAwEKampoJlcXV1xaRJk+Dl5YWJEydi5syZ+Prrr/HixQusWLECDg4OgmVRKBRYvHgxdu/eDS0tLdStWxePHz9GYWEhxowZgzlz5giWRYoFYENDQxw6dAjnzp1DTk4OjIyM0K5dO0FbsElpUkcpZ2dnODk5KbcZeVXTpk05Y1gCEhIS4OPjg5SUlDIPD4V8ADRgwABMmzYNM2bMQJMmTXD37l2sXbsWAwYMECzDgwcPcPbsWQDAL7/8UuYz/8mTJzh27JhgeUq9PGkhJyenzKpxIUjtwSXRvyGl1QZSylL62+DV72IhCwBff/21SkFeKrp27SqJoiuV7+LFi5LodAAAK1asQLNmzbBt2zbUqlULT548waJFi7B8+XLBto8rnfBuYGAADw8PuLq6okmTJsjMzERYWBj69OkjSA4p4sS+8p08eRKRkZEIDg7GkiVL0L9/fzg7O8PMzEzQHFIrjAg9+ZWoKnn595ympiZq1qypMi7WRCUpdQoRO4urqyvs7OxgZ2cnyuRTqWYh+qfYSr0CiYmJsLS0FDsGgL9Xdbq5uaGoqAjZ2dlo2rQpCgoKsGXLFrRo0ULtcpSysLDAuXPnBL9uKSkVF6VEqu9LamoqcnJyoK+vL0rrXCnt6x0YGIidO3di2bJl6N69O4C/t4qIi4uDt7c3Jk2ahGHDhgmSJTk5Gc7OznB2dq6wACzUBIaMjIw3vkbIfztJSUnw9vbG7du3VSZ1eHl5CT5JS6FQKDselIqOjkbfvn25Z5vEODk5wcTEBI6Ojior+gEI+rvmxYsX8Pb2xqFDhyCXy6GtrQ0XFxfMmTNHsD07CwsLMWLECOTk5ODevXswMDBQGdfW1oarqyvc3d0FyVOqqKgIP/74I3bs2IHi4mJERUXB09MTmzZtqnDiCRGVdf36daSlpcHGxgZPnjyBrq4us5DS6NGj3/iabdu2CZCE3sTX1xdpaWmidjsoZWVlhSNHjqh00Xry5Ans7e0Fe/g9atSo147LZDK1/bfLVq1vdv36dRw6dAgxMTHQ0NCAi4sLnJ2dRZmIKQV79+6FtbU1GjVqhMjISBQWForeuYmoMnjT1ltibHsIiF8LeJnYWdatW4f4+HhcuXIF+vr6sLW1ha2tLbp27Sr4hEMpZSH6p1gYr0BxcTGOHj2KlJQUlJSUqIyVt7LxQ3v27BlOnDiBjIwMNG7cGDY2NoK3PJZKjnnz5gEADh48qLLKdvny5YLmkFJxEZBO4Upq74vUSGFf74EDB8LLy6vclTOnTp2Cn58fwsLCBMsjlQKwiYmJ8kFc6Vfjy8ditVwTe1LH06dPMW7cOOjp6SlXsGRnZ8PW1hampqYICgoqM3uYxGNmZob4+HjBis8VOXToEHr16gWZTIZHjx5BT09P1FWE7u7uCA4OFu36L1u7di3i4+Mxbdo0TJ8+HSdPnsSsWbNQrVo1wVajEVVm2dnZmDp1Kq5evYrq1asjLCwMrq6uCAkJEXx1nJSyvG6Cn1C/HyZOnIjNmzdj1KhRFX7mC1XQMzExQe3atdGvXz80atSo3NeIcV9PZVW0skiM397du3fHsWPHUKtWLeW5/Px89O3bF3FxcYJmIfq3ioqK8Ntvv+HQoUP4/fff8fHHH8PIyAhnz57F/PnzRd9qSWh+fn7Yv38/tmzZgmbNmiE2NhbLli3D8OHDy2yvRESqTE1N4ejoqDyOiooqc3z16lXB8pQWoD08PLB582blMzsxOvtKKQvw9++U+Ph4nD17FnFxccjMzESPHj1gZ2cn+Oe+lLIQvQkL4xVYsGABDh06BBMTE5UVV2LMzp08eTI2btxY5vxXX30laDtdqeQoLcxs3rxZpW250A82pFRclFLhSkrvixS92nq/e/fuMDIyEjSDmZkZkpKSyn1gWVxcjO7du7+2Nf+HInYBeNCgQcjIyMDAgQMrbBku9N+VFKxZswaXLl3CunXrVFbAZWdnY/LkyejWrRumT58uYkJ6mZOTE/z8/ETff9LS0hJxcXGCb6FRGdjZ2SE0NBSNGjVSzrx//PgxevfuLcpnL1FlM2PGDNSqVQvz5s1Dz549ce7cOWzcuBGnTp1CaGio2mYpneD36uQ+QLitNAICAuDh4aG8HymPUPdsN27cwC+//ILDhw+jffv2cHFxgZ2dXZluKkQvmz59OqpVqwYfHx/UrFkTBQUF8Pb2RnFxMdauXStIhtIFAK+2CH+ZOrYLp4pdunQJkZGROHz4MGQyGRwdHeHs7KycdHLs2DHMnz9fMu2HhdKzZ0/s3LlT5b7o7t27GDNmDE6cOCFiMiLpK12U9jpCLlAr7Rjycic4sbqESCnLq/Ly8hAZGYmtW7fi3r17oizukWIWovKwMF6B7t27IyAgQLT9s9PS0pQ3QqUPGF6Wn5+P8PDwD96yQyo5yiP2Xh5SKi5KqXAlpfdFSqTUYv5NLY/EaokkBVevXkV4eDiOHDmCDh06YOjQobCxsVHrduF9+vRBYGAgmjZtWmbsxo0b8PT0xNGjR0VIRuXZvHkzwsPD4erqWmZyh5APUd3d3TFo0CAMHjxYsGu+TmJiIhYtWiT63uvA33vd/v7776hevbqy/VphYSGsra2Ve6ITUcV69OiBmJgY1KhRQ3k/IJfL0b17d8HvSaSUJT09XeU4JycHQUFBsLe3x6BBgwTJUNphR0oKCwsRExODsLAw3Lp1C46OjnBxccEnn3widjT6P6X7eE+ZMgUtW7bE+vXrkZaWhkWLFqms3BZCRkYGxo4di/T0dNSrVw95eXn45JNPEBAQUGHngffN0dERUVFRFbYNl8rDd5KOtm3bwsrKCs7OzrCzsyszMTUtLQ3+/v5YsWKFSAnFYW5ujsTERJUJUXK5HFZWVmr5TIqoKhC7FvAyqWRJTk5GTEwMYmNjcfXqVbRq1Qq2trawt7dH27Zt1TYL0ZtwunQFFAoFPvvsM9Gub2hoiNu3byMnJwfFxcVlfrRpa2vD29tbbXKUR+w5HTKZrMIHP5qampDL5YJlOXr0KAIDA8vsZ6irqwsfHx94enoKVhiX0vsiJUFBQThx4gSCg4PLbTHfrFkztW4xLxWmpqYwNTXFvHnzcPToUWzfvh2LFi3CoEGD4OLighYtWogdUXDZ2dnlFsUBoE2bNsjKyhI4Eb3O7t27AaDMSkWZTCZoYTwvLw9z5syBl5dXmTbqYjzMXb58OTp06IAFCxaIvlqwY8eO8Pf3x/Tp05Xvy/bt20WbjElU2VSvXh3Pnz9HjRo1lPcDBQUFghfQpJbl1a42RkZG8PX1hZOTk2CF8U6dOqlMroyLi0OPHj0EuXZFtLS0MGDAAAwYMAD37t3Dvn37MGnSJOjp6Sm/M0lc3t7eePz4MerVqwcAcHBwwOrVq7Fs2TIsXbpU0CzFxcU4dOgQzp07h5ycHBgZGaFdu3aCTpItLYiHhISgWbNmgl2XKq/Jkydj7NixFX73NGnSRO2K4sDfEwY2b96MKVOmKM+FhIRUuH0DEak6duwYzp07B1NTUzg4OEBDQ0M5tmjRIixatEjwTGLXAl4mdpa1a9fi2LFjSE1NhYWFBRwcHPCf//xHlA6cUspC9E+xMF4BBwcHBAcHq7TqFpKGhoZyn8kFCxbA19dXrXOUZ9OmTWJHkAwWrqQvIiICK1asUGkxr6mpiZ49e8LHxwd+fn6CFcYLCwtf2+JSXScvvExLSwuOjo5wdHTEn3/+iZkzZyIkJEQtW//o6OggNzcX9evXLzOWl5eHGjVqiJCKXnXhwgV06tQJx48fL3c8KChI0DxfffWVoNd7k5SUFOzevVv0vdcBYP78+RgzZgz279+PgoICDBgwAAUFBdiyZYvY0YgqBTs7O8yaNQsLFiyATCZDdnY2fH190bNnT7XOUpHHjx8Ldq1XHxBOnz5dEitpSqWkpCAlJQXZ2dnKIiyJ78yZM4iNjVUW9Vq2bIkffvgBvXv3FjzLsGHD8Ouvv6Jbt26CX7vU9u3b4enpCWdnZ7Xt4kX/zrZt21SKv/S3uXPnYty4cdi7dy8aN26M+/fvo6ioSPD7IqLKaNeuXVi3bh26dOmCAwcOICoqChs2bFB2pDhw4IAohXEHBwfBr1kRsbMEBATA3NwcK1asQPv27ZmF6F9iYbwC165dQ1JSEjZu3IgGDRqojAm90snX1xfPnj3Do0ePUFJSAuDvwtWtW7cEvVmUSo5SnTp1Uv45KSkJ5ubmgl5fSsVFKRWupPS+SElGRga6dOlS7liPHj0wa9YswbKYmZm9tnVYx44dBcsiZWfOnMH+/fsRExOD5s2bY8GCBWJHEkW3bt2wc+fOcvcE3bVrF/+9SMSECRNUHp4OHjwYkZGRyuMNGzZg/PjxgmRRKBSws7ND3bp1BbneP9GsWTNkZmaKvvc6ABgbG+PQoUP47bffkJ6ejsaNG8PGxgY6OjpiRyOqFGbMmIF58+ahX79+AAArKytYW1vDx8dHrbO8+vtbLpfj999/F/R7+tWuUWKvpAGAO3fuYN++fYiMjIRcLoejoyP27NmD1q1bix2N/k9JSQmKi4tVzikUClG2MqpXrx4ePHgg6ndyo0aN4OLigufPn2P06NHlvmbbtm0CpyIp+/zzz7F582Y4OzujYcOGYseRjLZt2+LXX3/FiRMnkJmZCQMDA9jY2KB27dpiRyOSvG3btmHz5s3o2LEjsrOzMWHCBHz//fdYvXo1APF+44nVtbY8YmdZuXIlYmNj4ebmhkaNGsHe3h729vYwMzNT6yxE/xQL4xUYOnQohg4dKnYMAMC+ffuwePFivHjxQuW8rq6uoAVpqeQoz6RJkwRfjSCl4qKUCldSel+kREot5rdv3y7YtSqblJQU7N+/H5GRkSgsLMSgQYPU/uGph4cHnJ2dkZubiwEDBkBfXx+ZmZk4fPgwwsPDsWPHDrEjEsremGZkZLx2/ENJTU3FuHHjkJaWhrZt28Lf3x+NGzcW5Nqv079/f4wfP170vddLlZSUQKFQQKFQoKioSDnhkIjerFatWvDz80N2drZycknDhg2Rn5+v1lle/f2tqakJMzMzeHh4CJ6llJj7je/duxf79u3DtWvXYG1tDS8vL9jY2IhSbKXX69mzJ+bMmYN58+bBwMAA9+7dw6pVq2BlZSV4llatWuGLL75Ax44dyxQYly9fLkgGf39//Prrr7h16xYsLS0FuSZVbhcuXMChQ4eU3R5fpo4dz15Wt25dtG7dGjVr1oSNjQ2ePHkidiSiSiErK0v5/FZXVxcBAQEYOnQofv75Z7i5uQmeJzU1FdevX4elpSXq1auH1atX49SpU7CwsMC8efOgpaWldlkGDx6MwYMHo7CwEHFxcYiNjVXWBUr39ba1tVW7LET/lEwhhWnc9Fq9e/fGyJEjUatWLZw7dw5jxozB6tWr0aNHD0yYMEGtctjZ2ZX7gCUjI0O5b4UYe5eKLTk5Gc7OznB2dq6wcGVqaip2TLVmbm7+2lZ4bxp/3xQKBVJTU/Hxxx8rz0VHR6Nv375q+8Dwyy+/VD48dXJy4sPTlyQlJcHb2xu3b9+GTCaDQqFA69at4eXlBQsLC7HjEcp+hlhaWqpMGBPqM8bd3R06OjpwcnJCaGgodHR0sGbNmg9+3Tcp3a/zVTKZTPDfDXfu3IGbmxvkcjkMDQ2RkZGBkpISbN26Fa1atRI0C1Fl9OrnW6nOnTvj/PnzapslKyurzMQfALh9+7Zgny1v+i4SkomJCRo0aID+/fuX21ULQLmTikl4OTk5+Pbbb3Hu3DnlvX737t2xevXqMt37PrR58+ZVOCZUYbzUypUrMWfOHEGvSZXT6z5n1XlyRXZ2NqZOnYqrV6+ievXqCAsLg6urK0JCQriKkegN+vXrh1WrVqm0xb506RLGjh0Lf39/TJs2TbBnmL/++iu+++471KpVC5qamnBxccHBgwfRr18/xMTEwN7eHnPnzlW7LOUpLi5GREQENm3ahLS0NFEnR0kpC1F5WBh/xcSJE7F582bl8aFDhzBw4EDlsRg39x07dsTFixeRnp6OmTNnYvfu3cjIyICbmxt+/fVXtcqxdu1aBAcHY8yYMfjkk08A/F3gW7JkCRYuXAgAcHJyEiRL6bWlUlyUUuFKSu+LVJiammLSpEkVjgcEBODKlSuCZHn69CnGjRsHPT09ZdvN7Oxs2NrawtTUFEFBQahZs6YgWaTExMQEtWvXRu3atStc4aSOE29elpqaipycHOjr6ysnI5E0SKUw3rlzZ5w6dQo1a9ZERkYGRo4ciRMnTnzw61akdO/1igQFBQnWYr7UpEmT0Lx5c8yaNQsaGhooKSnB6tWrcevWLQQHBwuahaiyuHPnDhYuXAiFQoHz58+jc+fOKuP5+fnIy8vD8ePH1SrLy8r7nC8uLoaFhYVgDy5NTU3h6OioPI6KilI5BoQrLo4aNeq14zKZjO2oJSYjIwNZWVlo3LgxGjVqJFqOx48fQ1tbG9ra2vjrr7/QoEGDCidXfGhXr15FWFgY0tPToa+vD2dn5zKfOUQVycnJEXxyiZTMmDEDtWrVwrx589CzZ0+cO3cOGzduxKlTpxAaGip2PCJJCw0Nxbp16zBhwgSV++WwsDD4+PigpKQE165dEyTLoEGDMG7cOAwZMgRHjhzB9OnTERoaio4dO+Kvv/6Cu7s7fvvtN7XLUio5ORnx8fGIj49HYmIiNDQ08Pnnn8Pa2hr9+/dX2yxEb8JW6q94dWa/j4+PSmFcjP2RdXV1IZfLYWBggOTkZACAoaEhsrOz1S7H9OnT0bVrV3h5eaFZs2bKdvcrVqwQtCAOVFxcnDt3Lnbs2CF4cdHc3BxRUVGiF66k9r5IhZRazG/cuBHVq1dX2f9SV1cXJ06cwOTJkxEQEIDp06cLlkcqhF4FUhkZGxtLYo9mkq6SkhLlZ7yhoaEo7YRfJqW910v98ccf8PPzg4aGBgBAQ0MD3377rSgtY4kqi6ZNm6JPnz7Izc1FUlJSmRVwWlpaFXaGqMpZ7ty5A3d3dygUCjx79gz29vYq48+fP4eRkZEgWQCUKYK/eiwkbh1UuaSmpuLBgwdQKBS4e/cu/vrrL9y6dUvwdq3x8fGYPHkytmzZgo4dOyIqKgq7du1CUFCQyqo5IZw+fRpTpkyBnZ0dPv30U9y9exdjx47F2rVr0atXL0GzkLRdvnwZq1atwoMHD5Tb88jlcuTk5ODq1asipxNPfHw8YmJiUKNGDeXE9/HjxyMkJETkZETSN3z4cGU30pe5urqidu3a+OmnnwTLkpqaqtz+rHfv3tDU1FQ+Q23ZsqWgWyRIKcusWbOQmJiIrKwsmJiYwMbGBu7u7mjXrp3g2xlJKQvRP8XC+Bu8uqBejP+Y27dvj4ULFyqLwaGhofjoo49Qr149tczRrVs37N69G7NmzcLp06fh6+sr6PVLSbW4KHbhSqrvi9ik9HDu6NGjCAwMhK6ursp5XV1d+Pj4wNPTUy3/joSeXEP0PhUVFSEiIkJ5LJfLVY6Li4uFDwVx95cFpLP3+ss0NTWRn5+vsoInPz8fNWrUEDwLUWUycuRIAECTJk2UD6TUPUvTpk0xf/585ObmYtGiRWVag2trawvaOYqTDOltBAQEYO3atcrfDAqFAjKZDG3atBG8ML569Wp8//33yofcnp6eMDY2xrJly7B7925Bs/j5+WHlypUqK6wOHz6MDRs2sDBOKhYvXgxjY2O0atUKqamp6NGjB7Zt24YZM2aIHU1U1atXx/Pnz1GjRg3lb/6CggLUqlVL5GRE0nfw4EE4ODiUO9a3b1/07dtXsCwvP1PQ1NQss9hKyHt6KWV59uwZpk2bBmtr63K3UxKSlLIQ/VMsjL+B2A90AWDu3Lnw8vJCQUEBZs2ahUmTJuH58+eCP3iQSg4A0NPTQ0hICDZs2AAnJycUFRUJnoHFxfLxfamYVFrMZ2dno2nTpuWOtWnTBllZWYJlIaL3Q09PD35+fsrj+vXrqxy/+pmsLl79HfemYyHY2tpixowZ8PLyQpMmTZCamgpfX1/Y2toKnoWoMhoyZAguX76M5OTkMg+fhC5SSyFL6WdHkyZN1HovWaq8du3aBT8/P2hpaeH48eP47rvvsGTJEhgYGAieJSUlRdmVrpSzs7MozzySk5PLFB769u2L+fPnC56FpO327dvYsWMH0tLSsHTpUowdOxZmZmZYvHgxxo4dK3Y80djZ2WHWrFlYsGABZDIZsrOz4evrC2tra7GjEUnewoULKyyMkzSUdmmVAillIfqnWBivBBo0aKDc97xhw4aIj4+HXC4XfGWRVHKUkslkmDp1Krp06YIDBw4Ifn0WF8vH96V8Umoxr6Ojg9zc3HL3ysvLy+OqRaJKSOi9bCvy/PlzjB49WnlcUFCgcgxA7fd0nTFjBqZNm4YBAwYoC/PW1taYOXOmyMmIKof//Oc/CAwMhL6+PqpV+9/trEwmE7wwLqUsHTt2RHh4eJlWurdu3cLGjRsFzUL0bzx+/Bh9+vTB/fv34efnh3r16mH+/PlwdXUV/LtRV1cXly9fVmmbfvXqVejp6QmaAwDq1auHW7duwcTERHnu5s2bXIlFZdSpUwcfffQRjI2Ncfv2bQB/fyekp6eLnExcM2bMwLx589CvXz8AgJWVFaytrbF48WKRkxFJnxid1SpSWFiIefPmKY+fPn2qclxYWKiWWYjo3bAwXglYWVlh8ODBcHV1RevWrVGtWjWVBy/qlgP4eyZ3QkIC8vLy0KBBA0ycOFHwDCwulo/vS/mk1GK+W7du2LlzZ5l2m8DfKzaE3O+ciKqWKVOmqBxz9WJZ/+///T/8/PPPyMjIQHZ2NoyMjPiQm+hfiIyMxKZNmySx4ktKWb7//nv8/vvvqF+/PuRyOWrWrInbt2+L3nZebE+fPhVs8im9nYYNGyI/Px+NGjVCWloaFAoFGjRogEePHgmeZeTIkZg4cSKGDRsGIyMjZGRkYO/eveXeN31oQ4cOxeTJk+Hh4YEmTZrg7t27CAwMxIgRIwTPQtLWokULhIaGYvjw4ahZsyZu3LgBLS0tSXTAFFOtWrXg5+eHnJwcpKWloXHjxmjYsKHYsYgqBSl9fjg6Ov6rY3XJQkTvhoXxVzx79gz29vbK4ydPnqgcP3/+XPBMq1atQkREBIYOHYrWrVvD1dUVDg4Ogu+LI4UcCoUCixcvxu7du6GlpYW6devi8ePHKCwsxJgxYzBnzhzBsrC4WD6+L+WTUot5Dw8PODs7Izc3FwMGDIC+vj4yMzNx+PBhhIeHY8eOHYLkIKKqR4wHx68jxb3Xp06dit9++w3GxsYwNjYW/PpEld3Tp0/Rs2dPsWMAkFaW33//HaGhocjJyUFoaCjWrFmDkJAQXL58WfAsUipG9+jRA/369YOLiws6d+4sdhwqh4WFBb755husW7cOn332Gf7zn/9AW1sbjRo1EjzLmDFjULt2bURERODXX3+FgYEBvv/+e1HayU6YMAEvXrxAQEAAHj58CCMjI3z11Vdq3Rqbyvftt99i8uTJ6NGjB9zd3fHFF19AU1MTw4cPFzuaaEpKSvDo0SPUr18fDRo0wK1bt3Do0CHY2NigefPmYscjkrynT5+iTZs2r33NjRs3BMkixnYmFZFSFiJ6NzKFlHpjSMD+/fvf+BonJycBkpT1+PFjHDx4EAcOHMCtW7fQt29fUT6QxcwRGBiInTt3YtmyZejevTuAvx9qx8XFwdvbG5MmTcKwYcMEyZKcnAxnZ2c4OztXWFw0NTUVJIuU8H0pX6dOnXDhwoUKx83NzZGUlCRYnqSkJHh7e+P27duQyWRQKBRo3bo1vLy8YGFhIVgOKbKzsyt3dmz16tXRoEED2Nrawt3dHRoaGiKkI6J/w87O7o2vEboNvaurK2bPns3V9ERvadasWfj8888xaNAgsaNIKouFhQXOnTuHnJwcfPXVV4iOjsaLFy9gb2+P06dPC5rFzMxMMsXoK1euIDIyEgcPHkSdOnXg7OwMJycnUYquVL78/HysWbMG06ZNw8OHD+Hp6YknT55g+fLlsLKyEjueaFJTUzmBjv6xFy9eoHr16tDQ0MDly5fx5MkT9OjRQ+xYonjw4AHGjRuH9u3bY/ny5YiKisKcOXNgYmKCu3fvYsuWLWjXrp3YMYkkrUOHDggMDHzta4S8nz127BjOnTsHU1NTODg4qDyPW7RoERYtWqSWWYjo7bEwXsmkpaXh4MGD2Lt3LxQKBU6cOKFWOQYOHAgvLy907dq1zNipU6fg5+eHsLAwQbIALC5WhO9LWdbW1oiIiKiwxfzAgQMRFxcneK7U1FTk5ORAX18fhoaGgl9fijZt2oS9e/di/PjxMDY2Rnp6OkJCQmBlZYUWLVpg165d6N+/P6ZNmyZ2VCKqhNzd3REfH48mTZqgYcOGKhNx1H3/daJ/4ptvvkFMTAyaNWtWZt9fof8bklIWR0dHbNiwAcbGxujSpQtOnDgBDQ0NdOvWDRcvXhQ0ixSL0UVFRTh+/Diio6Nx9uxZtG/fHi4uLrC3t0f16tVFy0XSUPog++V9Ql8l9KIEU1NTmJmZwdXVFf369YO2trag1yfpy8jIeONr1PEef+7cuSgsLMT8+fOhq6uLPn36oH///pg+fToOHDiAgwcPYvPmzWLHJJI0oRfvvM6uXbuwbt06dOnSBefOnUO7du2wYcMG5e83IbNKKQsRvRu2Uq8E8vPzcfjwYURERODy5cuwtraGt7c3Pv/8c7XLkZGRgS5dupQ71qNHD8yaNUuwLMDfX3hRUVEsLr6C70tZUm0xz1a+ZR09ehQBAQFo1aqV8pylpSVmzpyJhQsXwsbGBqNGjWJhnIjeipmZGczMzMSOQVRptW7dGq1btxY7BgBpZXF0dMSIESMQFhYGGxsbTJ48Gdra2qJ0amrXrh3atWuHuXPnKovRgwYNErUYXa1aNXz88cdo0qQJ6tWrhxs3bmDz5s1YunQpli1bJvi9NQH+/v5vfI1QW7SUrhdRKBSS2Vf15MmTiIyMRHBwMJYsWYL+/fvD2dmZvyFI6eVOZ6/+2y09FqrVsZTExcUhMjISDRo0QEZGBu7evavs7GJvbw9fX1+RExJJn5TWUW7btg2bN29Gx44dkZ2djQkTJuD777/H6tWrAQibVUpZiOjdcMV4JdChQwc0btwYLi4ucHZ2LrMaQZ1yvGnmFWdmkVSxxXzlYW5ujoSEBJUHtnK5HJaWlsoVV29qjU9EREQktMOHD8Pa2holJSVYvXo18vPz4enpKeokyJs3b+LgwYM4duwYCgoK0LBhQ2RlZQlWjH7w4AGioqIQGRmJ5ORkWFtbw9nZGTY2NtDU1MTu3bvx448/itK5Sd2ZmJigdu3aaNOmTbkPkmUyGTup/J/r16/j0KFDiImJgYaGhvKZTIMGDcSORiJKT09/42uMjIwESCItZmZmyvv2w4cPw9vbG4mJiQD+7h5iYWEheCcVosomICAAHh4eYscAUPb5W1ZWFoYOHQo3Nze4ubmp/DevTlmI6N1wxXglEBAQUG7rcHXNQVQZNW/eHMHBwfD29sbOnTtVWswHBgayKC4hJiYmCAgIUFmhEhISgk8++QTA39s2qOMDBqJ/Ky4uDtu3b0dmZiYCAgIQEhKCGTNmoFo1/vzcu3ev8r3Zv38/VqxYgeXLl6NWrVpiRyOSrFf37EtKSoK5ubnyeMiQIYiIiFC7LC/r37+/8s8+Pj6CX79UecXo2bNnqxSj586dK0gx2tbWFi1btoSTkxMGDx4MXV1dlfGuXbvi0KFDHzwHlTVnzhzs27cPmZmZGDp0KIYMGVLm70coUlq9/qqioiJkZGQgIyMD2dnZ+Pjjj/HHH39g06ZNmD9/PpycnETJReLjPWn56tati5ycHDRo0ACJiYkq38///e9/y93ejohUSaUoDgD6+vq4fPky2rdvrzxet24dxo4di1atWgna6UVKWYjo3XDFuIQdPHgQDg4Or32oMmTIELXJAfy9z9akSZMqHA8ICMCVK1cEyUL0tthiXtquX7+OCRMmoFq1ajAwMMC9e/dQUlKCjRs3orCwEGPGjMH69ethZ2cndlQiyYqKisLy5csxdOhQ7NixA0eOHMFXX30Fe3t7zJ49W+x4ovr5558RGhoKd3d3rFq1CrGxsZg4cSJatWrF1o5Er/FqZyhLS0vlCjAAgq7QkFKWUleuXMGaNWuQnp6OkpISlbHY2FhBs3z22WevLUanpKTAy8sL27dv/+BZAgIC4Obmxv2ZJezy5csIDw/Hr7/+CnNzcwwdOhQ9e/aEhoaGYBmkuHr90qVLiIyMxOHDhyGTyeDo6AhnZ2eYmJgAAI4dO4b58+erfPaQejExMXljEUYdW6n7+PggLy8PvXv3xsKFC+Ht7Q1HR0c8fvwY8+bNg56enqiTx4gqgzd9vshkMly/fl2QLKGhoVi3bh0mTJiA8ePHK8+HhYXBx8cHJSUluHbtmtplIaJ3w8L4awwePBiRkZGiXd/BwQEHDx6ssPgik8kEecghlRwAMGrUqDe+RogHLERUteXn5+P48eO4f/8+jIyMYGdnhxo1aiAvLw/FxcWirWYhqiwcHR2xZMkSdOzYERYWFjh37hxSUlIwevRonDp1Sux4ourbty82bNiAli1bKotpmZmZcHJyYitfotd4tdhc+tlSSsgtlaSUpZSDgwNatWoFKyurMgVFoVeUSqkYbWlpibi4OMH3NKd/7/nz5zhy5Aj279+PlJQUDB48GN99950g196yZQv27dsHuVwu+ur1Um3btkWPHj3g4uICOzu7Mv+G09LS4O/vjxUrVoiUkMSWkJDwxsK4paWlQGmk4/Hjx/D09ERSUhIGDhyIpUuXAvj7u1tfXx+7du0SbYtKosqioklXR48exc6dO9GzZ09s3rxZsDwxMTHIzMzEiBEjyuT56aefcODAAbXMQkRvj4Xx13j1AYfUPHnyBLVr1xY7hmRyEBERkTRYWFggMTERMplMWfxVKBSwsLDA+fPnxY4nKktLS8THx0NDQ0P5W7O4uBjdu3dHQkKC2PGIJOtNq7SFLEZLKUspMzMzJCYmSqIALKVitLu7OwYNGoTBgweLHYX+gYKCAkRHR2Pr1q24e/cuLl++LOj1pbB6vVRmZiYaNmwo+HWJqqrTp0/DwsJCEpO2iCobuVyOFStWYM+ePfD09FRZLf2hlXaylQIpZSGid8NNHsuRkZEBAFAoFLh3756ylZZYLY9ffdBSytbWVtCHy1LJoVAokJqaio8//lh5Ljo6Gn379oWmpqZgOYioakpISICPjw9SUlLKtFJUx1Z0RG+jWbNmiI2NRa9evZTnzpw5g6ZNm4qYShpMTEywZ88eDB8+XLnKJzo6Gq1atRI5GRFVZhYWFrhx44Zyz0MxtWvXDtHR0ZIoRufl5WHOnDnw8vKCnp6eyupKoVvMU8XOnDmD8PBwHD9+HM2bN8eXX34pyoPn9u3bo3379pg3bx6OHDmCLVu2wNvbW9DV61Le75ykxdHREVFRUbCzs6tw5Tg/5/7HyspK7AhElVJqaiq+/fZb5OXlYfv27TAzMxP0+gsXLpRMMVpKWYjo3bAwXo7SH5UKhQK2trYA/m4XLmRB5M6dO1i4cCEUCgXy8/MxevRolfH8/HzUqVNHbXKUevr0KcaNGwc9PT3lDWN2djbmzp2LHTt2ICgoCDVr1hQsDxFVPStWrECHDh2wYMECVKvGr0mitzF9+nRMmTIF9vb2ePHiBRYtWoSDBw9izZo1YkcT3Zw5c+Dm5obIyEg8ffoUEyZMwKVLlxAUFCR2NCKqxDw9PTF69Gh06dKlzP3Z8uXLBc0ipWL0V199Jej16J9LSUnB/v37ERkZCblcDgcHB+zevRuffvqp2NHw0UcfoXfv3pDL5di6dSt+/vlnQQvjb9rvnAgAJk6cCACYNm2ayEmIqKo6cuQIFixYgM6dO2PLli2oW7eu4Bmk1OxYSlmI6N3wiX85bt68CaDiFdJCaNq0Kfr06YPc3FwkJSWV2RdIS0urwj2/q2KOUhs3bkT16tXh4+OjPKerq4sTJ05g8uTJCAgIwPTp0wXLQ0RVT0pKCnbv3s0Wa0TvoHv37ti9ezf27NmDLl26oKSkBCEhIZJYySi2tm3b4tChQzhw4ADatGmDxo0bw8fHR7TORESVxfPnz1Um6RYUFKgcv3jxQi2zlFq6dCl0dXVRq1Ytwa/9KikVo0v3V8/OzkZ6ejr09fVhYGAgcioCgP79+6N+/fpwdHSEjY0NqlWrhsePH6tsZ2dhYSF4LrFXr8+ZMwf79u1DZmamZPY7J2lydHQE8L/PuYyMDGRlZcHAwIBt+InoncjlcixbtgxhYWGYMWMG3NzcRMsipQlhUspCRO+Ge4y/hlT2GI+IiMDgwYNRUlICTU1NPHz4EPXr1xe8bbgUcvTp0weBgYHltmK9ceMGPD09cfToUcHyEFHV4+TkBD8/PxgbG4sdhajSCg4Ohru7e5nz69atg6enp/CBJMTX1xcLFiwoc3727NlYtWqVCImIKgcptReWUpZSHTt2RFxcnCQK46WkUIzOz8/HnDlzcPz4cSgUCshkMnTr1g3r1q0TtPMZlWViYvLacSG79pW3et3Z2VnU1etS2u+cpC0rKwvTp0/HhQsXlJ9zPXv2xOrVq/k5R0RvxcnJCTdv3sSXX36JDh06lPuaIUOGCJLFxMTkjQVpoX4vSCkLEb0brhh/jU6dOokdAcDfH7p2dnZYv3492rdvj8DAQMTExCAoKAjNmzdXqxzZ2dkV7k/apk0bZGVlCZKDiKqu/v37Y/z48XB1dYW+vr7KmFA//Ikqo5ycHPz1118AgB9//BEdOnRQaTX25MkTbN26VS0L4w8ePMDZs2cBAL/88gtMTU1Vxp88eYJjx46JEY2o0pDSnrpSylKqadOmKCgokERhXErF6DVr1qCgoAAHDx5EkyZNcOfOHSxbtgyrV6/GkiVLBM1Cqko79UmBFFevS2G/c6ocvLy8UKdOHRw+fBiGhoZITU3FqlWrsHTpUqxcuVLseERUCT169AgGBgY4efIkTp48WWZcJpMJ9nxMW1sbgYGBglzrTaSUhYjeDVeMVwKjRo2ChYUFpkyZgmrVqqGoqAibNm1CUlISQkJC1CqHtbU1IiIiUL9+/TJjeXl5GDhwIOLi4gTJQkRVU0XbQ8hkMsH3xSSqTPLz89G7d2/k5uaWO66lpYVhw4Zh/vz5AicTX2FhIUaMGIGcnBzcu3evzMpJbW1tuLq6lrvKnojon/j5558RFhYGFxcX1KtXT2U1i9AT+3x8fJCcnAwvLy+VYrSxsbHgxWgbGxuEh4ertKLOysrCoEGDlBOWiKS0er08BQUFiI6OxtatW3H37l1cvnxZtCwkPZ06dcLJkyeho6OjPPf48WP06tVLtO0hiYjeF3NzcyQlJYkdA4C0shDRu+GK8X9o0qRJ2LRpkyjXvnHjBrZt26Z8uFGtWjVMnjwZXbt2Vbsc3bp1w86dO8tdpbFr1y507NhRsCxEVDUdP35c7AhElZKOjo6yyNCvXz8cOXJE5ETSoaWlhbCwMACAu7s7goODRU5ERFXNtm3bAADbt29XOS/kip5SJ06cUClGt27dGqtXr8agQYMEL4w/e/YMtWvXVjlXp04dlJSUCJqDpE1Kq9dfJvZ+51Q51KlTB48fP1YpjBcWFqJevXrihSKiSs3V1RV2dnaws7N74+SxD01KazqllIWI3g0L46+IiIgo93xCQoJyTOgHCzo6OkhOTkaLFi2U51JTUwVvQyeFHB4eHnB2dkZubi4GDBgAfX19ZGZm4vDhwwgPD8eOHTsEy0JEVcuFCxfQqVMnlZaJL5PJZOjcubPAqYgqpwEDBiA9PR1GRkZiR5EcFsWJ6EOQ0sQ+KRWjO3TogPXr12PmzJmQyWRQKBRYv3492rVrJ3gWon+ivP3Od+/eLep+5yRtX331FTw8PODp6YmmTZviwYMH8Pf3R8+ePUXdDoCIKi8rKyucOnUKP/30E/T19WFrawtbW1t07doVWlpagmaZNGmSoNd7HSllIaJ3w1bqr+jRowfy8vLQuHFjlVlApW0vxWilu379ekRHR2P8+PEwNDRERkYGgoOD4ejoiKlTp6pdjqSkJHh7e+P27dvKhxutW7eGl5cXf+gT0VsrbYlU0WxYsVsoElUmkyZNwunTp9GpUyc4OzujX79+0NbWFjuWJCQmJmLRokVISUkpM+OcnzFE9C7Onz+P9PT0Mp8tQk/snjhxIlq1aqVSjF69ejVu3bqFoKAgQbP8+eefGD16NLS0tGBkZIT09HTIZDJs2bIFLVu2FDQL0T/Rpk2bMvudv4rPPehl/2Q1J+9lieht5OfnIz4+HmfPnkVcXBwyMzPRo0cP2NnZwcnJSex4RERvjYXxV2RmZmLmzJkwNDSEt7c3atSoAeDvG4+KVhF+aMXFxdiwYQMiIiKQlZUFAwMDODs7Y8KECdDQ0FC7HKVSU1ORk5MDfX19GBoaCn59IiIiqlh2djYOHDiAiIgIpKenY8CAAXB1dUX79u3FjiYqJycnmJiYwNHRsczDbktLS5FSEVUucXFx2L59OzIzMxEQEICQkBDMmDGj3AKSumTx9vZGWFgYGjZsqLK/uBgTu6VWjM7Ly0NMTAxycnJgZGQEa2trlZbDRFIi9f3OiYhIPeXl5SEyMhJbt27FvXv3BPsuMjExUflt+yqZTIbr16+rXRYiejcsjJdDoVDgp59+QnR0NNasWYM2bdrA0tISiYmJYkdTceLECdja2oodQzI5iIjeRUZGxhtfw0k4RG/n0qVLWLx4MW7cuIEWLVpgxIgRGDZsmChFLLGZmZkhPj6eK+iJ3lJUVBSWL1+OoUOHYseOHThy5Ai++uor2NvbY/bs2WqbxcLCAlu2bIGpqamg162IVIrRkydPxsaNG8uc/+qrr7gNFxFVGc+ePcOjR4+UW1bI5XLcunULvXv3FjkZEVVmycnJiImJQWxsLK5evYpWrVrB1tYW9vb2aNu2rSAZKqrHHD16FDt37kTPnj2xefNmtctCRO+GhfHXiI+Px/fff4/Ro0djw4YNkiiMFxYWIjIyElu2bEFycrJoM4WlkoOI6H0pnflZ0dciV2cQ/TtyuRwnTpxAZGQkTp06hU8++QTOzs4wMjLCxo0b0ahRI/j7+4sdU3BOTk7w8/ODsbGx2FGIKiVHR0csWbIEHTt2VHb1SklJwejRo3Hq1Cm1zWJnZ4cjR44Ivu9jecQuRqelpSEiIgIAEBAQAA8PD5Xx/Px8hIeHi9YRjojofQoPD8eSJUvw4sULlfO6uro4ffq0SKmIqDJbu3Ytjh07htTUVFhYWMDOzg52dnaSWCwil8uxYsUK7NmzB56enhg/fjyzENG/pn7LdP6Frl274pdffsHs2bPL/MAUWm5uLnbt2oVdu3ZBLpdj0KBB8PPzU9scRETvm9BtRomqsoULF+Lo0aMA/i4c7d27F23atFGOGxgYYPjw4WLFE1X//v0xfvx4uLq6Ql9fX2VM6H2AiSqj+/fvo0OHDgCgbGXYtGlTPH36VK2zTJ48GfPnz4e7uzvq1KmjMibEQ8yXi9GnT58uM/EpPz8ff/755wfPAfz9/+/t27eRk5OD4uJiJCQkqIxra2vD29tbkCxERB/apk2b4OnpiVq1auHcuXMYM2YMVq9ejR49eogdjYgqqYCAAJibm2PFihWS2gotNTUV3377LfLy8rB9+3aYmZkxCxG9FRbGKxAcHAx3d3fo6uoiODgY9+7dAwCsW7cOnp6eguW4c+cOQkJCcODAAbRu3RpPnz7FwYMHYWRkJFgGKeUgIvpQSj/P5HI5/P394erqCmNjY2zduhW5ubn45ptvRE5IVHlkZGRg0aJFsLe3L3f1ooGBgVquFgeA3bt3AwBCQ0NVzstkMhbGif6BZs2aITY2Fr169VKeO3PmDJo2barWWV68eIHo6GgcPHhQeU6hUAjW8UZKxWgNDQ2sX78eALBgwQL4+voKcl0iIjFkZWVhzJgxSE9PR3h4ONq2bYtly5bBzc0NEyZMEDseEVVCK1euRGxsLNzc3NCoUSPY29vD3t5e1OLvkSNHsGDBAnTu3BlbtmxB3bp1mYWI3hpbqb8kJycHf/31FwBgwoQJCAoKUmmp++TJE8yYMQMXL14UJM/UqVMRFxeHXr16YdSoUejQoQO6du2KyMhINGrUSJAMUspBRCQEHx8fXLp0CT/99BMMDQ1x/vx5rFixApaWloLvF0pUme3duxfW1tZo1KgRIiMjUVhYiKFDh4odSzQXLlxAp06dKhwPCgpi6zWif+DMmTOYMmUK7O3tERMTAycnJxw8eBBr1qyBtbW12mbp3r07pk2bBisrK2hoaKiMCT2ZWWrFaO69S0RVmb29PQ4fPgxNTU10795dOTGpU6dOuHDhgsjpiKgyKywsRFxcHGJjY3HixAkAUO4xbmtrK0gGuVyOZcuWISwsDDNmzICbm5sg15V6FiJ6NyyMvyQ/Px+9e/dGbm5uueNaWloYNmwY5s+fL0ieNm3awMXFBSNHjlS2HxWjIC2VHEREQujRoweioqLQoEED5bmHDx9iyJAh3KON6B/68ccfsW/fPmzZskW5onLZsmUYPny42hZ/zc3NkZSUpDwePHgwIiMjKxwnoordvHkTe/bsQXp6Oho3bgxXV1fR2jxKJUuXLl3KrNIWk1SK0fv27cPixYu59y4RVVnTp0+HtrY2vLy8MG7cOAwZMgQfffQR/P39uV0YEb03xcXFiIiIwKZNm5CWliZIRyIAcHJyws2bN/Hll18qtzB6lVCd16SUhYjeDVupv0RHRwdnz54FAPTr1w9HjhwRNU9UVBR27NiBkSNHonXr1hgzZgzEmMcglRxEREJ48eIFatasqXJOR0cHRUVFIiUiqnx++eUX7Ny5E8bGxgD+XsnSqlUrjBkzRm0L46/+dsrIyHjtOBGVb/LkyVi9erUk9oiWUhZnZ2ds27YNo0ePFjvKa4vRQhfGN27cyL13iahKmzdvHhYsWICCggLMmjULkyZNwvPnz7F8+XKxoxFRJZecnIz4+HjEx8cjMTERGhoa+Pzzz/Hdd98JluHRo0cwMDDAyZMncfLkyTLjQm5JJqUsRPRuuGL8NYqLi6GpqQkAOHnyJBo0aIB27doJniM/Px9hYWEIDQ3FnTt3MGzYMIwYMQKffvqpWuYgIvqQJk2ahEaNGmH+/PnQ0tLCixcvsHLlSty/fx8bNmwQOx5RpWBubo7ExERUq/a/OZhyuRxWVlaSWtEopFdXhFtaWiIxMbHCcSIqX9euXXHq1CloaWmJHUVSWUaOHIkLFy6gVq1aqFu3LmQymXJM6BWDvXv3xsiRI8stRgu9323Hjh1x8eJFpKenY+bMmdi9ezcyMjLg5uaGX3/9VdAsREQfikKhgEKhgIaGBu7fvw8dHR3o6OiIHYuIKqlZs2YhMTERWVlZMDExgY2NDWxsbNCuXTuV35hERJUVV4xX4Pjx41iwYAHOnDmDDRs2YNOmTZDJZJg/fz6++OILQbPo6OjAzc0Nbm5uOHnyJHbt2oUhQ4agTZs22Ldvn9rlICL6kObPnw93d3eYm5ujfv36yM3NRfPmzbFp0yaxoxFVGm3btsXmzZsxZcoU5bmQkBCYmJiImIqIqgIHBwd88803cHR0hL6+vsrDOQsLC7XN4urqCldXV0GvWZGsrCyMGTMG6enpCA8PR9u2bbFs2TK4ubkJXhjX1dWFXC6HgYEBkpOTAQCGhobIzs4WNAcR0Ydy8+ZNTJ48GevXr0f79u2xZcsWxMTEICgoCM2bNxc7HhFVQs+ePcO0adNgbW0NfX19UbO4urrCzs4OdnZ2oj9PkFIWIno3XDFeAVdXV3zxxRdwdXWFlZUVli9fDl1dXUyfPh3Hjh0TOx7u3r2LXbt2Ye7cucxBRPSeFRcX48KFC3j48CEaN26M9u3bq6x8JaLXu3btGsaNG4caNWqgcePGuH//PoqKihAUFKS2N5BcMU70flT0GSKTyQTb61CKWaTE3t4ehw8fhqamJrp3767sFNKpUydcuHBB0Czce5eIqrpRo0bBwsICU6ZMQbVq1VBUVIRNmzYhKSkJISEhYscjInon69atQ3x8PK5cuQJ9fX3Y2trC1tYWXbt2Fbxrk5SyENG7YWG8Al26dEFCQgKuX7+OkSNH4ty5c6hWrRrMzMxw8eJFseMREdEHMmrUKLi4uKBv376oUaOG2HGIKq1Hjx7hxIkTyMzMhIGBAWxsbFC7dm2xY4mmffv2WLx4sfLYx8dHZV9ib29v/PHHH2JEI6JKzN/f/42v+frrrwVI8j9SKkZnZmZiwYIF8PX1xd27d1X23nV0dBQ0CxHRh9C5c2ecO3dOpWtJcXExunbtinPnzomYjIjo/cnPz0d8fDzOnj2LuLg4ZGZmokePHrCzs4OTk5PaZiGit8PlbxWoUaMGsrOzcfz4cXTq1AnVqlXDzZs3Ub9+fbGjERHRB2RjY4Pg4GAsWbIE/fr1g4uLC8zNzcWORVTpVKtWDVpaWpDJZCguLoa6z8XU09ODn5+f8rh+/foqx7q6umLEIqp0MjIyKhwzNDQUMIk0spSuxq6IGPtAzps3DwsWLEBBQQFmzZqlUowWWsOGDbF582bln+Pj4yGXyzn5kYiqDB0dHSQnJ6NFixbKc6mpqahTp46IqYiI3i8dHR306tULvXr1Ql5eHiIjI7F161bExMQIXoyWUhYiejtcMV6BH3/8EXv37sXjx4/h5+cHXV1djB8/HuPGjcPEiRPFjkdERB/YtWvXsH//fhw5cgQ6OjpwcXHB4MGD0bBhQ7GjEUnenTt34ObmBrlcDkNDQ2RkZKCkpARbt25Fq1atxI5HRJWYiYkJZDKZcrLNy4VfMVqpSyWLlBUVFYlWjJbL5YiOjkZ6ejpKSkpUxoReSU9E9CGsX78e0dHRGD9+vPJ3d3BwMBwdHTF16lSx4xERvRfJycmIiYlBbGwsrl69ilatWsHW1hb29vZo27at2mYhorfDwvhrJCQkQFtbGx07dsS9e/dw5coV9OnTR5Qshw4dwsCBA0W5thRzEBEJobi4GKdPn8b69etx/fp1aGtrw9raGnPnzhV8VRpRZTJp0iQ0b94cs2bNgoaGBkpKSrB69WrcunULwcHBYscjokosPT1d5TgnJwdBQUGwt7fHoEGD1DaLlEipGP3NN98gISEBrVq1Upm4IJPJsG3bNkGzEBF9CMXFxdiwYQMiIiKQlZUFAwMDODs7Y/z48dDU1BQ7HhHRO1m7di2OHTuG1NRUWFhYwM7ODnZ2dqI8k5NSFiJ6NyyMv8H169eRlpYGGxsbPHnyRLQ2l5aWlkhMTBTl2lLMQUT0IV2+fBkHDhxAdHQ0AMDR0RHOzs5o1KgR1qxZgz/++AMHDhwQOSWRdHXr1g0nT56ElpaW8tzz589hZWWF8+fPi5iMiKqiJ0+ewMnJCTExMWJHkVQWsUipGG1ubo4DBw6gSZMmgl6XiEgM9+7dg4GBgdgxiIjeGxMTE5ibm2Pu3Llo3749sxDRe8E9xiuQnZ2NqVOn4urVq6hevTrCwsLg6uqKkJAQmJmZCZ5HKvMXpJKDiOhD6devH9LS0mBlZYVFixbBzs4O1ar97+ty9OjRGD58uIgJiaRPU1MT+fn5aNCggfJcfn4+93Qlog/m8ePHYkdQklIWMZw+fVoyxWh9fX3Uq1dP7BhERIIYOHAgkpKSxI5BRPTerFy5ErGxsXBzc0OjRo1gb28Pe3t7UeozUspCRO+GK8YrMGPGDNSqVQvz5s1Dz549ce7cOWzcuBGnTp1CaGioYDnmzZsHADh48CAcHByU55cvXy5YBinlICL60DZv3gwnJyfo6+uXO15YWIjCwkLo6OgInIyo8vDy8kJaWhq8vLzQpEkTpKamwtfXF8bGxli8eLHY8YioEvP391c5lsvl+P3336Gnp4fNmzerbRYp6du3L8LDwyXxW+n48ePYuXMnRowYgTp16qiMWVhYiJSKiOjDMDMzw8WLF8WOQUT03hUWFiIuLg6xsbE4ceIEACj39ba1tVXbLET0drhivALx8fGIiYlBjRo1lO3fxo8fj5CQEEFzGBkZAfi77Vzpn8UglRxERB+SQqFAv379VIri0dHR6Nu3r3J/Ni0tLZX20ERU1owZMzBt2jQMGDBA+TvK2toaM2fOFDkZEVV2CQkJKseampowMzODh4eHWmeRkjlz5uDbb7+VRDH6jz/+QFxcHOLi4lTOy2Qy3LhxQ9AsRERERPR2tLS0YGtrC1tbWxQXFyMiIgKbNm1CeHi44L/ppJSFiN4OV4xXwMbGBvv370f9+vVhYWGBc+fOIS8vD0OGDMFvv/0meB6p7O0tlRxERO/b06dPMW7cOOjp6SlXgGVnZ8PW1hampqYICgpCzZo1RU5JVDmcP38eZmZmyMjIQHZ2NoyMjCrswkBE9G9kZWWV+3ly+/ZttGrVSm2zSMnatWsREBBQ5rwYxWgLCwusWbMGVlZW0NDQEPTaRERC8/b2ho+Pj9gxiIjeu+TkZMTHxyM+Ph6JiYnQ0NDA559/Dmtra/Tv319tsxDR2+GdYQXs7Owwa9YspKSkQCaTITs7Gz4+PrC2thYlj1TmL0glBxHR+7Zx40ZUr15d5UGCrq4uTpw4gaKionIf8BJR+aZOnYrCwkIYGxujY8eOLIoT0XvTt2/fMueKi4sxbNgwtc4iJbt27cLmzZtx/fp13Lx5U/k/Yqyg0dbWRo8ePVgUJ6Iqy9fXV/nnl+9lZ8+eLUYcIqL3atasWbC2tsbAgQPxyy+/oGXLlggICMDp06exYsUKQQvRUspCRO+GrdQrMGPGDMybNw/9+vUDAFhZWcHa2lq0fTE3bdokynVfJZUcRETv29GjRxEYGAhdXV2V87q6uvDx8YGnpyemT58uUjqiysXY2BhXrlyBpaWl2FGIqAq4c+cO3N3doVAo8OzZM9jb26uMP3/+XLDtnqSURaqkVIweO3YsfvjhB0yaNAl169YVOw4R0Xvx4MEDnD17FgDwyy+/wNTUVGX8yZMnOHbsmBjRiIjeq2fPnmHatGmwtrYWfcK9lLIQ0bthK/U3yMnJQVpaGho3boyGDRuKHQcAkJSUBHNzc7FjSCYHEdH70KlTJ1y4cKHCcXNzcyQlJQmYiKjycnd3R3x8PJo0aYKGDRsq9xkHgG3btomYjIgqqxMnTiA3NxeLFi0q0yZWW1sbFhYWgj2gklIWKQoODsbDhw8lUYy2s7NDRkaGyvdQKe4BSUSVVWFhIUaMGIGcnBzcu3cPBgYGKuPa2tpwdXWFu7u7SAmJiIiIpIuF8X/gxo0bOHPmDDp37owOHTqIHUcy+3xLJQcR0ftgbW2NiIgI1K9fv8xYXl4eBg4ciLi4OBGSEVU+/v7+FY59/fXXAiYhoqomMTFRMt0opJRFSqRUjH7d/Sr/7oioKnB3d0dwcLDYMYiIiIgqDRbGX3H//n3MmjULV69eRb9+/fDFF19g1KhRqFWrFvLz87F27Vr06dNHkCx2dnblPkzIyMiAoaEhACA2NlZtchARfUhz585FkyZNyi3abdiwAdeuXcNPP/0kQjIiIiIqVVhYiKioKDx48AAlJSUAALlcjlu3bmHjxo1qm0VKWIwmIhLWw4cPoaenh8LCQoSFhaFBgwbKrSGJiIiISBX3GH/F4sWLoaOjg//85z84ePAgPDw88N1332HcuHEIDw/H5s2bBSuMOzo6Ijg4GGPGjMEnn3wCAFAoFFiyZImgq62kkoOI6EPy8PCAs7MzcnNzMWDAAOjr6yMzMxOHDx9GeHg4duzYIXZEokpl79692L59OzIzM7F//36sWLECy5cvR61atcSORkSV2Pfff4/ff/8d9evXh1wuR82aNXH79m0MGTJErbNIiZSK3ydPnoSvry/S09Px6poAtlInoqrgl19+wdKlS3Hp0iWsXr0a0dHRkMlk+O9//4spU6aIHY+IiIhIcrhi/BVdunTB8ePHUatWLTx69AhdunTB5cuXoaWlheLiYnTp0gXnz58XLM/Zs2fh5eUFDw8PDB06FIA4LcylkoOI6ENKSkqCt7c3bt++DZlMBoVCgdatW8PLywsWFhZixyOqNH7++WeEhobC3d0dq1atQmxsLCZOnIhWrVrB19dX7HhEVIl16dIFoaGhyMnJQWhoKNasWYOQkBBcvnwZ69atU9ssUiKlYrS9vT369OkDa2traGhoqIxJqYBPRPS2Bg8ejNmzZ6Nr166wtLREYGAg9PX1MWrUKPz2229ixyMiIiKSHK4Yf0VhYaFyJVPdunWho6MDLS0tAICmpmaZG/sPrVu3bti9ezdmzZqF06dPi/YwWSo5iIg+JHNzc0RFRSE1NRU5OTnQ19dXbhlBRP9caGgoNmzYgJYtW+KHH35A3bp18eOPP8LJyUnsaERUyZWUlKBFixaoV6+essg6cuRIhISEqHUWKVm8eHGFxWih5eXlYebMmdDU1BQ1BxHRh3Lv3j306NEDSUlJqFatGszNzQEAjx8/FjkZERERkTSxMP6KV/fSfvVGXowF9np6eggJCcGGDRvg5OSEoqIiwTNIKQcR0YdmbGwMY2NjsWMQVVq5ublo3rw5gP/9dtLV1eVvByJ6Z40bN0ZqaiqMjY2RnZ2Np0+fQkNDAwUFBWqdRUqkVIy2tbXFyZMnYWdnJ3YUIqIPom7durhz5w6OHj2q7IQRHx8PfX19kZMRERERSRML468oKSnB+fPnlQ9xi4qKVI5LSkpEySWTyTB16lR06dIFBw4cECWDlHIQERGRdJmYmGDPnj0YPny4ctJhdHQ0WrVqJXIyIqrsHB0dMWLECISFhcHGxgaTJ0+GtrY2TE1N1TqLlEipGD169GiMGDECn3zyCerUqaMytm3bNpFSERG9P2PHjoWjoyMAYPv27bhw4QI8PDzg7e0tcjIiIiIiaeIe468wMTF57bhMJhN8X7SUlBQkJCQgLy8PDRo0QLdu3dCkSRNBM0gpBxEREUnbtWvX4ObmhpYtW+Lq1avo1q0bLl26hKCgIHTo0EHseERUyR0+fBjW1tYoKSnB6tWrkZ+fD09PT1G6vUgpi1RcvnxZMsXoIUOGoHbt2ujcuXOZFexff/21oFmIiD6U1NRUVKtWDQYGBsjJyUFGRobaT9IiIiIiqggL4xKmUCiwePFi7N69G1paWqhbty4eP36MwsJCjBkzBnPmzFGrHERERFR5ZGZm4sCBA0hPT0fjxo3h6OgIQ0NDsWMREdEHJqVitJmZGRITE1G9enVBr0tEJKT79+8jKioK6enp0NfXh4ODA5o2bSp2LCIiIiJJYit1CQsKCsKJEycQHByM7t27AwCKi4sRFxcHb29vNGvWDMOGDVObHERERFQ5+Pr6YsGCBRg/frzK+dmzZ2PVqlUipSKiquDKlStYs2YN0tPTy2xzFRsbq7ZZpOTOnTuSKUa3adMGqampaNGihdhRiIg+iCtXrsDNzQ0tWrRAkyZNcOXKFQQGBiI4OBidOnUSOx4RERGR5LAwLmERERFYsWIFunbtqjynqamJnj17wsfHB35+foIUpKWSg4iIiKTrwYMHOHv2LADgl19+KdO+8cmTJzh27JgY0YioCpk3bx5atWoFR0dHaGhoMIsESakY3a1bN4wePRr9+vVDvXr1VMbYSp2IqoLVq1fj22+/xejRo5Xntm7dih9++AGhoaEiJiMiIiKSJrZSlzAzMzMkJSVBJpOVGSsuLkb37t2RkJCgNjmIiIhIugoLCzFixAjk5OTg3r17MDAwUBnX1taGq6sr3N3dRUpIRFWBlFpjSymLlPz444/Ys2ePJIrRo0aNKve8TCYTfL9zIqIPoUuXLoiLi0O1av9b+ySXy9G1a1dcuHBBxGRERERE0sQV4xImk8nKLUYDf6/YlsvlapWDiIiIpEtLSwthYWEAAHd3dwQHB4uciIiqIgsLC9y4cQPt27cXO4qkskhJYmIimjdvjj///FPlfEX3lB/S9u3bBb8mEZGQatSogXv37sHY2Fh57t69e6hbt66IqYiIiIiki4VxIiIiInqvWBQnog/F09MTo0ePRpcuXVCnTh2VseXLl6ttFimRWjE6Pj4eDx48QGmzPLlcjj///BMLFiwQORkR0bsbMGAApk2bhhkzZqBJkya4e/cu1q5diwEDBogdjYiIiEiSWBiXsMLCQvj7+1c4LtRKbankICIiosohMTERixYtQkpKCl7dtefGjRsipSKiqmDp0qXQ1dVFrVq1xI4iqSxSI5VitK+vL3bv3q38OyouLkZBQQE+//xzQXMQEX0o3377LXJycjBlyhTI5XJoa2vDxcUF06ZNEzsaERERkSSxMC5hZmZmr927u2PHjmqVg4iIiCqH5cuXo0OHDliwYIHKfodERO/q2rVriIuLk0QxWkpZpERKxejDhw9jx44dePbsGQ4cOIBly5Zh5cqVePr0qeBZiIg+BG1tbaxYsQKLFy/Go0ePoKenJ8rWFURERESVBZ9USphUWtBJJQcRERFVDikpKdi9eze0tbXFjkJEVUzTpk1RUFAgiWK0lLJIiZSK0c+ePUPHjh2RlZWFa9euQSaT4euvv2aLYSKqEvz9/XHt2jVYWVlh5MiR0NfXFzsSERERkeSxMC5xCoUCqamp+Pjjj5XnoqOj0bdvX2hqaqpdDiIiIpK+Zs2aITMzE8bGxmJHIaIqxsnJCePGjYOLiwvq1aunsipuyJAhaptFSqRUjG7cuDGys7Ohr6+P+/fvQy6X46OPPkJ+fr7gWYiI3qdVq1YhIiICnTt3hp+fHwoKCjBx4kSxYxERERFJnkzx6saPJBlPnz7FuHHjoKenp9zjOzs7G7a2tjA1NUVQUBBq1qypNjmIiIiocti8eTPCw8Ph6upaZuWKOheLiOjd2dnZlXteJpMhNjZWbbNIyYABA7B9+3bo6urC0tIScXFxkMlksLS0RFJSkqBZVq5cidOnT2Pr1q3w8vJCzZo1oa2tjevXr2Pfvn2CZiEiep969uyJ4OBgtGrVCgkJCfD19UVUVJTYsYiIiIgkj4VxCVuzZg0uXbqEdevWQVdXV3k+OzsbkydPRrdu3TB9+nS1yUFERESVA4tFRETqS0rFaLlcjq1bt2LYsGF4+vQp5s+fj/z8fHh5eaFt27aCZiEiep/MzMxw8eJFAEBRURG6d++OxMREkVMRERERSR8L4xLWp08fBAYGomnTpmXGbty4AU9PTxw9elRtchAREREREZ0/fx7p6el49VZWjI4UUsoiFSxGExF9eJ06dcKFCxeUx5aWliyMExEREf0D3GNcwrKzs8stRgNAmzZtkJWVpVY5iIiISNouXLiATp06VTgeHBwMd3d3ARMRUVXj7e2NsLAwNGzYUGVPb5lMJngxWkpZpKR69eoYP348AKB27doICgoSPMO8efPe+Jrly5cLkISI6MPgOiciIiKit8PCuITp6OggNzcX9evXLzOWl5eHGjVqqFUOIiIikrYJEyao7B87ePBgREZGKo9/+uknFsaJ6J1ER0djz549MDU1FTuKpLJIAYvRRETCKSoqQkREhPJYLperHAPq3b2EiIiIqCIsjEtYt27dsHPnTnz99ddlxnbt2oWOHTuqVQ4iIiKStldXrmRkZLx2nIjo36pduzZat24tdgwA0spCqtLS0rB9+3aEh4fDxcVF7DhERO+dnp4e/Pz8lMf169dXOVb37iVEREREFWFhXMI8PDzg7OyM3NxcDBgwAPr6+sjMzMThw4cRHh6OHTt2qFUOIiIikraXWwn/k2Mion9r8uTJmD9/Ptzd3VGnTh2VMUNDQ7XNIgVSKkZfvXoVjx8/xtKlS0XPQkT0IRw/flzsCERERESVEgvjEta8eXMEBwfD29sbO3fuhEwmg0KhQOvWrREYGChYyz6p5CAiIiIiIvX24sULREdH4+DBg8pzCoUCMpkMN27cUNssUiClYrS5uTm6dOkCAGjTpk25r1HHvyMiIiIiIiJ1J1Owp2WlkJqaipycHOjr64u6+kAqOYiIiEh6zM3NVfYYt7S0RGJiYoXjRET/Vvfu3TFt2jRYWVlBQ0NDZczIyEhts0iBu7s7zpw589rXCFWMfvbsGa5fv45x48YhMDCw3NdYWloKkoWIiIiIiIikgyvGKwljY2MYGxuLHUMyOYiIiEh6ioqKEBERoTyWy+Uqx8XFxcKHIqIqpbi4GMOHDxc7BgBpZZECf3//NxajhVKjRg106tQJa9asYQGciIiIiIiIlLhinIiIiIjeCzs7uze+hvshEtG7WLlyJQwMDDB69Gixo0gqi5TExMSgV69eYscA8PfkhaNHjyIlJQUlJSUqY19//bVIqYiIiIiIiEgsLIwTERERERFRpTBy5EhcuHABtWrVQt26dSGTyZRjsbGxaptFSqRUjF6wYAEOHToEExMTVKv2v4Z5MpkM27ZtEzQLERERERERiY+t1ImIiIiIiKhScHV1haurq9gxAEgri5R4e3tXWIwW2vHjx7Ft2za0a9dO8GsTERERERGR9HDFOBERERERERG9F927d0dAQIAkitHdunXD6dOnoampKXYUIiIiIiIikgCuGCciIiIiIiJJ8/f3f+NrhGrTLaUsUqRQKPDZZ5+JHQMA4ODggODgYEycOFHsKERERERERCQBLIwTERERERGRpCUkJLx2XMg23VLKIkVSKkZfu3YNSUlJ2LhxIxo0aKAyps77wBMREREREakrtlInIiIiIiIiovdixIgRSEpKQo0aNUQvRu/fv7/CMScnJwGTEBERERERkRSwME5ERERERERE7wWL0URERERERCRVLIwTERERERERUZXBfeCJiIiIiIioPNxjnIiIiIiIiIjeiZSK0dwHnoiIiIiIiMrDwjgRERERERERvRMpFaO3b98u2LWIiIiIiIio8mArdSIiIiIiIiIiIiIiIiIiqtI0xA5ARERERERERERERERERET0IbEwTkREREREREREREREREREVRoL40REREREREREREREREREVKWxME5ERERERERERERERERERFUaC+NERERERERUqb148QL3798XOwYRERERERERSRgL40RERERERPTeJScnY86cOejZsyfMzMzQq1cv/PDDDygoKPhH//sJCQn49NNPAQBpaWn49NNPkZaWVu5rR4wYgTNnzry37ERERERERERU9bAwTkRERERERO9VUlISnJycYGRkhIiICFy8eBGBgYH4448/MG7cOBQXF7/X6+Xm5r7X/3tEREREREREVPWwME5ERERERETv1cKFCzFkyBB88803aNCgAQCgefPmWLt2LXR1dZGamgoAePjwIWbOnIkePXrAysoKCxcuRH5+/r+61rhx45CRkQFvb28sXrwY7u7u8PLyUnmNh4cH1q9fj4SEBPTs2RPr169Hly5d0KVLFyxduhSFhYUAAIVCgW3btqFv377o3LkzRowYgatXr76Hd4SIiIiIiIiIxMbCOBEREREREb03d+/exe3bt+Hg4FBmTE9PDxs2bECzZs1QUlKCKVOmQENDA0ePHkVUVBQyMzOxcOHCf3W9kJAQGBoawsfHBwsXLoSLiwuOHDmiLHY/fPgQcXFxcHZ2BgA8ePAAycnJiI2NxZ49e/Dbb79hw4YNAIBdu3Zhy5YtWL9+Pc6ePQtnZ2eMHTsWDx8+fMd3hYiIiIiIiIjExsI4ERERERERvTc5OTkA/i6Cv87Vq1dx7do1eHt7Q0dHB/Xr18ecOXNw6NChd2qN3qtXL2hoaOD48eMAgKioKJiZmcHY2BgAIJPJlNds1qwZxo8fjwMHDgAAdu7cCQ8PD5iYmKB69epwdXVFy5YtleNEREREREREVHlVEzsAERERERERVR36+voAgKysLDRr1qzM+MOHD6Gnp4e0tDQUFxfD2tpaZVxLS0vZav1taGlpwcHBAZGRkejXrx/279+PcePGKcfr1q2L+vXrK48NDAyQmZkJAEhPT8fKlSvxww8/KMeLiopgamr61nmIiIiIiIiISBpYGCciIiIiIqL3xsjICK1bt0Z0dDQsLCxUxrKzs2Fra4vly5fD0NAQH330ERISEqCpqQkAKCwsRGpqKpo2bYoLFy68dQYXFxd88cUXuHjxItLS0tC3b1/l2JMnT/Ds2TPUqFEDAJCWlgZDQ0MAQOPGjfHNN99g4MCBytffvXsX9erVe+ssRERERERERCQNbKVORERERERE75WXlxfCw8Ph7++P3NxcKBQK3LhxA5MmTULbtm3Rt29ftG/fHk2bNsWKFStQUFCA58+fY9myZXBzc0NxcfG/up6WlhaePHmiPP7ss8/wySefYPHixRgwYICyCA4AxcXFWLlyJV68eIH//ve/CA4OhqurKwDgiy++wMaNG/HXX38BAH7//XcMHDgQ586dew/vChERERERERGJiSvGiYiIiIiI6L2ytLTEjh07sGnTJgwcOBDPnj2Dnp4e+vXrBw8PD1SvXh0AEBAQgJUrV6JPnz548eIF2rdvjy1btkBbW/tfXc/V1RVr167FlStXlG3QnZ2dsXTpUixcuLDM6+vWrQt7e3sAwJdffonx48cDANzc3KBQKDBlyhRkZmaiUaNGWLhwofK1RERERERERFR5yRQKhULsEERERERERETvU2xsLH744QccPnxYeS4hIQGjR4/Gn3/+KWIyIiIiIiIiIhIDV4wTERERERFRlZGbm4v79+9j48aNGD58uNhxiIiIiIiIiEgiuMc4ERERERERVRlXr17Fl19+CX19fXz55ZdixyEiIiIiIiIiiWArdSIiIiIiIiIiIiIiIiIiqtK4YpyIiIiIiIiIiIiIiIiIiKo0FsaJiIiIiIiIiIiIiIiIiKhKY2GciIiIiIiIiIiIiIiIiIiqNBbGiYiIiIiIiIiIiIiIiIioSmNhnIiIiIiIiIiIiIiIiIiIqjQWxomIiIiIiIiIiIiIiIiIqEpjYZyIiIiIiIiIiIiIiIiIiKo0FsaJiIiIiIiIiIiIiIiIiKhKY2GciIiIiIiIiIiIiIiIiIiqtP8PNUvnyvNRoy0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pt.pl.coda.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": 7,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": 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 × 51\n",
       "  3 modalities\n",
       "    rna:\t365492 x 0\n",
       "      obs:\t&#x27;NAME&#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 × 51\n",
       "  3 modalities\n",
       "    rna:\t365492 x 0\n",
       "      obs:\t'NAME', '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": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smillie_data = tasccoda_model.prepare(smillie_data, modality_key=\"coda_LP\", tree_key=\"tree\", reference_cell_type=\"automatic\", formula=\"Health\", pen_args={\"phi\": 0})\n",
    "smillie_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "sample: 100%|██████████| 11000/11000 [05:37<00:00, 32.64it/s, 63 steps of size 7.53e-02. acc. prob=0.93]\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": 9,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": 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\">-1.183</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10.338</span>                                                          │\n",
       "│ CD4+ Activated Fos-hi          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.562</span>           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">160.905</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\">168.648</span>                                                          │\n",
       "│ CD4+ Memory                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.320</span>           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">126.319</span>                                                          │\n",
       "│ CD4+ PD1+                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.932</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13.287</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\">30.169</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\">15.117</span>                                                          │\n",
       "│ CD8+ LP                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.604</span>           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">167.807</span>                                                          │\n",
       "│ CD69+ Mast                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.593</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">61.057</span>                                                          │\n",
       "│ CD69- Mast                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.353</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8.722</span>                                                          │\n",
       "│ Cycling B                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.480</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20.880</span>                                                          │\n",
       "│ Cycling Monocytes             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.565</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19.179</span>                                                          │\n",
       "│ Cycling T                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.699</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16.774</span>                                                          │\n",
       "│ Cycling TA                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.092</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36.996</span>                                                          │\n",
       "│ DC1                           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.605</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18.427</span>                                                          │\n",
       "│ DC2                            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.353</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">48.029</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\">37.971</span>                                                          │\n",
       "│ Enterocyte Progenitors        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.903</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13.678</span>                                                          │\n",
       "│ Enterocytes                   <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.217</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.992</span>                                                          │\n",
       "│ Enteroendocrine               <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.265</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.524</span>                                                          │\n",
       "│ Follicular                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.829</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">77.309</span>                                                          │\n",
       "│ GC                            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.914</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13.529</span>                                                          │\n",
       "│ Glia                          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.105</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">30.381</span>                                                          │\n",
       "│ Goblet                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.217</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.992</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\">14.495</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\">11.609</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\">-0.823</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14.818</span>                                                          │\n",
       "│ Immature Goblet               <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.329</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">24.284</span>                                                          │\n",
       "│ Inflammatory Fibroblasts      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.972</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12.766</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\">19.724</span>                                                          │\n",
       "│ M cells                       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.399</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8.330</span>                                                          │\n",
       "│ MT-hi                         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.714</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16.524</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\">162.522</span>                                                          │\n",
       "│ Microvascular                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.300</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">24.998</span>                                                          │\n",
       "│ Myofibroblasts                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.013</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33.308</span>                                                          │\n",
       "│ NKs                           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.392</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">22.801</span>                                                          │\n",
       "│ Pericytes                     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.683</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17.044</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\">1210.528</span>                                                          │\n",
       "│ Post-capillary Venules         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.008</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">34.015</span>                                                          │\n",
       "│ RSPO3+                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.616</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18.225</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\">13.556</span>                                                          │\n",
       "│ Stem                          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.799</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15.177</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\">-0.014</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33.275</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\">28.355</span>                                                          │\n",
       "│ Tregs                          <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.683</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">66.807</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\">7.979</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\">70.585</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\">1.118</span>           <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">103.215</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\">0.556</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">58.839</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\">49.542</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\">0.786</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">74.055</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-1.183\u001b[0m            \u001b[1;36m10.338\u001b[0m                                                          │\n",
       "│ CD4+ Activated Fos-hi          \u001b[1;36m1.562\u001b[0m           \u001b[1;36m160.905\u001b[0m                                                          │\n",
       "│ CD4+ Activated Fos-lo          \u001b[1;36m1.609\u001b[0m           \u001b[1;36m168.648\u001b[0m                                                          │\n",
       "│ CD4+ Memory                    \u001b[1;36m1.320\u001b[0m           \u001b[1;36m126.319\u001b[0m                                                          │\n",
       "│ CD4+ PD1+                     \u001b[1;36m-0.932\u001b[0m            \u001b[1;36m13.287\u001b[0m                                                          │\n",
       "│ CD8+ IELs                     \u001b[1;36m-0.112\u001b[0m            \u001b[1;36m30.169\u001b[0m                                                          │\n",
       "│ CD8+ IL17+                    \u001b[1;36m-0.803\u001b[0m            \u001b[1;36m15.117\u001b[0m                                                          │\n",
       "│ CD8+ LP                        \u001b[1;36m1.604\u001b[0m           \u001b[1;36m167.807\u001b[0m                                                          │\n",
       "│ CD69+ Mast                     \u001b[1;36m0.593\u001b[0m            \u001b[1;36m61.057\u001b[0m                                                          │\n",
       "│ CD69- Mast                    \u001b[1;36m-1.353\u001b[0m             \u001b[1;36m8.722\u001b[0m                                                          │\n",
       "│ Cycling B                     \u001b[1;36m-0.480\u001b[0m            \u001b[1;36m20.880\u001b[0m                                                          │\n",
       "│ Cycling Monocytes             \u001b[1;36m-0.565\u001b[0m            \u001b[1;36m19.179\u001b[0m                                                          │\n",
       "│ Cycling T                     \u001b[1;36m-0.699\u001b[0m            \u001b[1;36m16.774\u001b[0m                                                          │\n",
       "│ Cycling TA                     \u001b[1;36m0.092\u001b[0m            \u001b[1;36m36.996\u001b[0m                                                          │\n",
       "│ DC1                           \u001b[1;36m-0.605\u001b[0m            \u001b[1;36m18.427\u001b[0m                                                          │\n",
       "│ DC2                            \u001b[1;36m0.353\u001b[0m            \u001b[1;36m48.029\u001b[0m                                                          │\n",
       "│ Endothelial                    \u001b[1;36m0.118\u001b[0m            \u001b[1;36m37.971\u001b[0m                                                          │\n",
       "│ Enterocyte Progenitors        \u001b[1;36m-0.903\u001b[0m            \u001b[1;36m13.678\u001b[0m                                                          │\n",
       "│ Enterocytes                   \u001b[1;36m-1.217\u001b[0m             \u001b[1;36m9.992\u001b[0m                                                          │\n",
       "│ Enteroendocrine               \u001b[1;36m-1.265\u001b[0m             \u001b[1;36m9.524\u001b[0m                                                          │\n",
       "│ Follicular                     \u001b[1;36m0.829\u001b[0m            \u001b[1;36m77.309\u001b[0m                                                          │\n",
       "│ GC                            \u001b[1;36m-0.914\u001b[0m            \u001b[1;36m13.529\u001b[0m                                                          │\n",
       "│ Glia                          \u001b[1;36m-0.105\u001b[0m            \u001b[1;36m30.381\u001b[0m                                                          │\n",
       "│ Goblet                        \u001b[1;36m-1.217\u001b[0m             \u001b[1;36m9.992\u001b[0m                                                          │\n",
       "│ ILCs                          \u001b[1;36m-0.845\u001b[0m            \u001b[1;36m14.495\u001b[0m                                                          │\n",
       "│ Immature Enterocytes \u001b[1;36m1\u001b[0m        \u001b[1;36m-1.067\u001b[0m            \u001b[1;36m11.609\u001b[0m                                                          │\n",
       "│ Immature Enterocytes \u001b[1;36m2\u001b[0m        \u001b[1;36m-0.823\u001b[0m            \u001b[1;36m14.818\u001b[0m                                                          │\n",
       "│ Immature Goblet               \u001b[1;36m-0.329\u001b[0m            \u001b[1;36m24.284\u001b[0m                                                          │\n",
       "│ Inflammatory Fibroblasts      \u001b[1;36m-0.972\u001b[0m            \u001b[1;36m12.766\u001b[0m                                                          │\n",
       "│ Inflammatory Monocytes        \u001b[1;36m-0.537\u001b[0m            \u001b[1;36m19.724\u001b[0m                                                          │\n",
       "│ M cells                       \u001b[1;36m-1.399\u001b[0m             \u001b[1;36m8.330\u001b[0m                                                          │\n",
       "│ MT-hi                         \u001b[1;36m-0.714\u001b[0m            \u001b[1;36m16.524\u001b[0m                                                          │\n",
       "│ Macrophages                    \u001b[1;36m1.572\u001b[0m           \u001b[1;36m162.522\u001b[0m                                                          │\n",
       "│ Microvascular                 \u001b[1;36m-0.300\u001b[0m            \u001b[1;36m24.998\u001b[0m                                                          │\n",
       "│ Myofibroblasts                \u001b[1;36m-0.013\u001b[0m            \u001b[1;36m33.308\u001b[0m                                                          │\n",
       "│ NKs                           \u001b[1;36m-0.392\u001b[0m            \u001b[1;36m22.801\u001b[0m                                                          │\n",
       "│ Pericytes                     \u001b[1;36m-0.683\u001b[0m            \u001b[1;36m17.044\u001b[0m                                                          │\n",
       "│ Plasma                         \u001b[1;36m3.580\u001b[0m          \u001b[1;36m1210.528\u001b[0m                                                          │\n",
       "│ Post-capillary Venules         \u001b[1;36m0.008\u001b[0m            \u001b[1;36m34.015\u001b[0m                                                          │\n",
       "│ RSPO3+                        \u001b[1;36m-0.616\u001b[0m            \u001b[1;36m18.225\u001b[0m                                                          │\n",
       "│ Secretory TA                  \u001b[1;36m-0.912\u001b[0m            \u001b[1;36m13.556\u001b[0m                                                          │\n",
       "│ Stem                          \u001b[1;36m-0.799\u001b[0m            \u001b[1;36m15.177\u001b[0m                                                          │\n",
       "│ TA \u001b[1;36m1\u001b[0m                          \u001b[1;36m-0.014\u001b[0m            \u001b[1;36m33.275\u001b[0m                                                          │\n",
       "│ TA \u001b[1;36m2\u001b[0m                          \u001b[1;36m-0.174\u001b[0m            \u001b[1;36m28.355\u001b[0m                                                          │\n",
       "│ Tregs                          \u001b[1;36m0.683\u001b[0m            \u001b[1;36m66.807\u001b[0m                                                          │\n",
       "│ Tuft                          \u001b[1;36m-1.442\u001b[0m             \u001b[1;36m7.979\u001b[0m                                                          │\n",
       "│ WNT2B+ Fos-hi                  \u001b[1;36m0.738\u001b[0m            \u001b[1;36m70.585\u001b[0m                                                          │\n",
       "│ WNT2B+ Fos-lo \u001b[1;36m1\u001b[0m                \u001b[1;36m1.118\u001b[0m           \u001b[1;36m103.215\u001b[0m                                                          │\n",
       "│ WNT2B+ Fos-lo \u001b[1;36m2\u001b[0m                \u001b[1;36m0.556\u001b[0m            \u001b[1;36m58.839\u001b[0m                                                          │\n",
       "│ WNT5B+ \u001b[1;36m1\u001b[0m                       \u001b[1;36m0.384\u001b[0m            \u001b[1;36m49.542\u001b[0m                                                          │\n",
       "│ WNT5B+ \u001b[1;36m2\u001b[0m                       \u001b[1;36m0.786\u001b[0m            \u001b[1;36m74.055\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\">19.399</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</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\">153.578</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.067</span>                             │\n",
       "│                      CD4+ Activated Fos-lo     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.035</span>     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">112.416</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.585</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\">120.567</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.067</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\">12.682</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.067</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\">28.795</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.067</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\">14.429</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.067</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\">160.165</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.067</span>                             │\n",
       "│                      CD69+ Mast                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.263</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">88.077</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.529</span>                             │\n",
       "│                      CD69- Mast                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.263</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12.581</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.529</span>                             │\n",
       "│                      Cycling B                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.708</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19.302</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.113</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\">19.692</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.038</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\">16.010</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.067</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\">69.422</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</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\">18.920</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.038</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\">49.314</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.038</span>                             │\n",
       "│                      Endothelial               <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.366</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">49.413</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.380</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\">25.667</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</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\">18.750</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</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\">17.871</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</span>                             │\n",
       "│                      Follicular                <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.708</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">71.465</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.113</span>                             │\n",
       "│                      GC                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.708</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12.506</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.113</span>                             │\n",
       "│                      Glia                      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.366</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">39.536</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.380</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\">18.750</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</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\">27.200</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</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\">21.785</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</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\">27.805</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</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\">45.568</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</span>                             │\n",
       "│                      Inflammatory Fibroblasts  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.366</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16.613</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.380</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\">20.251</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.038</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\">15.630</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</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\">15.772</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.067</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\">166.868</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.038</span>                             │\n",
       "│                      Microvascular             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.366</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">32.531</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.380</span>                             │\n",
       "│                      Myofibroblasts            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.366</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">43.346</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.380</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\">42.786</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</span>                             │\n",
       "│                      Pericytes                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.366</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">22.180</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.380</span>                             │\n",
       "│                      Plasma                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-1.045</span>     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">798.876</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.600</span>                             │\n",
       "│                      Post-capillary Venules    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.366</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">44.266</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.380</span>                             │\n",
       "│                      RSPO3+                    <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.366</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">23.717</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.380</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\">25.437</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</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\">28.480</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</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\">0.335</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">87.287</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.391</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\">0.335</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">74.381</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.391</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\">63.765</span>            <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.067</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\">14.972</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.908</span>                             │\n",
       "│                      WNT2B+ Fos-hi             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.366</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">91.855</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.380</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\">-0.366</span>     <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">134.317</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.380</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\">-0.366</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">76.570</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.380</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\">-0.366</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">64.470</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.380</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\">-0.366</span>      <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">96.371</span>             <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.380</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;36m19.399\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      CD4+ Activated Fos-hi     \u001b[1;36m-0.676\u001b[0m     \u001b[1;36m153.578\u001b[0m            \u001b[1;36m-0.067\u001b[0m                             │\n",
       "│                      CD4+ Activated Fos-lo     \u001b[1;36m-1.035\u001b[0m     \u001b[1;36m112.416\u001b[0m            \u001b[1;36m-0.585\u001b[0m                             │\n",
       "│                      CD4+ Memory               \u001b[1;36m-0.676\u001b[0m     \u001b[1;36m120.567\u001b[0m            \u001b[1;36m-0.067\u001b[0m                             │\n",
       "│                      CD4+ PD1+                 \u001b[1;36m-0.676\u001b[0m      \u001b[1;36m12.682\u001b[0m            \u001b[1;36m-0.067\u001b[0m                             │\n",
       "│                      CD8+ IELs                 \u001b[1;36m-0.676\u001b[0m      \u001b[1;36m28.795\u001b[0m            \u001b[1;36m-0.067\u001b[0m                             │\n",
       "│                      CD8+ IL17+                \u001b[1;36m-0.676\u001b[0m      \u001b[1;36m14.429\u001b[0m            \u001b[1;36m-0.067\u001b[0m                             │\n",
       "│                      CD8+ LP                   \u001b[1;36m-0.676\u001b[0m     \u001b[1;36m160.165\u001b[0m            \u001b[1;36m-0.067\u001b[0m                             │\n",
       "│                      CD69+ Mast                \u001b[1;36m-0.263\u001b[0m      \u001b[1;36m88.077\u001b[0m             \u001b[1;36m0.529\u001b[0m                             │\n",
       "│                      CD69- Mast                \u001b[1;36m-0.263\u001b[0m      \u001b[1;36m12.581\u001b[0m             \u001b[1;36m0.529\u001b[0m                             │\n",
       "│                      Cycling B                 \u001b[1;36m-0.708\u001b[0m      \u001b[1;36m19.302\u001b[0m            \u001b[1;36m-0.113\u001b[0m                             │\n",
       "│                      Cycling Monocytes         \u001b[1;36m-0.603\u001b[0m      \u001b[1;36m19.692\u001b[0m             \u001b[1;36m0.038\u001b[0m                             │\n",
       "│                      Cycling T                 \u001b[1;36m-0.676\u001b[0m      \u001b[1;36m16.010\u001b[0m            \u001b[1;36m-0.067\u001b[0m                             │\n",
       "│                      Cycling TA                 \u001b[1;36m0.000\u001b[0m      \u001b[1;36m69.422\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      DC1                       \u001b[1;36m-0.603\u001b[0m      \u001b[1;36m18.920\u001b[0m             \u001b[1;36m0.038\u001b[0m                             │\n",
       "│                      DC2                       \u001b[1;36m-0.603\u001b[0m      \u001b[1;36m49.314\u001b[0m             \u001b[1;36m0.038\u001b[0m                             │\n",
       "│                      Endothelial               \u001b[1;36m-0.366\u001b[0m      \u001b[1;36m49.413\u001b[0m             \u001b[1;36m0.380\u001b[0m                             │\n",
       "│                      Enterocyte Progenitors     \u001b[1;36m0.000\u001b[0m      \u001b[1;36m25.667\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      Enterocytes                \u001b[1;36m0.000\u001b[0m      \u001b[1;36m18.750\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      Enteroendocrine            \u001b[1;36m0.000\u001b[0m      \u001b[1;36m17.871\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      Follicular                \u001b[1;36m-0.708\u001b[0m      \u001b[1;36m71.465\u001b[0m            \u001b[1;36m-0.113\u001b[0m                             │\n",
       "│                      GC                        \u001b[1;36m-0.708\u001b[0m      \u001b[1;36m12.506\u001b[0m            \u001b[1;36m-0.113\u001b[0m                             │\n",
       "│                      Glia                      \u001b[1;36m-0.366\u001b[0m      \u001b[1;36m39.536\u001b[0m             \u001b[1;36m0.380\u001b[0m                             │\n",
       "│                      Goblet                     \u001b[1;36m0.000\u001b[0m      \u001b[1;36m18.750\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      ILCs                       \u001b[1;36m0.000\u001b[0m      \u001b[1;36m27.200\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      Immature Enterocytes \u001b[1;36m1\u001b[0m     \u001b[1;36m0.000\u001b[0m      \u001b[1;36m21.785\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      Immature Enterocytes \u001b[1;36m2\u001b[0m     \u001b[1;36m0.000\u001b[0m      \u001b[1;36m27.805\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      Immature Goblet            \u001b[1;36m0.000\u001b[0m      \u001b[1;36m45.568\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      Inflammatory Fibroblasts  \u001b[1;36m-0.366\u001b[0m      \u001b[1;36m16.613\u001b[0m             \u001b[1;36m0.380\u001b[0m                             │\n",
       "│                      Inflammatory Monocytes    \u001b[1;36m-0.603\u001b[0m      \u001b[1;36m20.251\u001b[0m             \u001b[1;36m0.038\u001b[0m                             │\n",
       "│                      M cells                    \u001b[1;36m0.000\u001b[0m      \u001b[1;36m15.630\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      MT-hi                     \u001b[1;36m-0.676\u001b[0m      \u001b[1;36m15.772\u001b[0m            \u001b[1;36m-0.067\u001b[0m                             │\n",
       "│                      Macrophages               \u001b[1;36m-0.603\u001b[0m     \u001b[1;36m166.868\u001b[0m             \u001b[1;36m0.038\u001b[0m                             │\n",
       "│                      Microvascular             \u001b[1;36m-0.366\u001b[0m      \u001b[1;36m32.531\u001b[0m             \u001b[1;36m0.380\u001b[0m                             │\n",
       "│                      Myofibroblasts            \u001b[1;36m-0.366\u001b[0m      \u001b[1;36m43.346\u001b[0m             \u001b[1;36m0.380\u001b[0m                             │\n",
       "│                      NKs                        \u001b[1;36m0.000\u001b[0m      \u001b[1;36m42.786\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      Pericytes                 \u001b[1;36m-0.366\u001b[0m      \u001b[1;36m22.180\u001b[0m             \u001b[1;36m0.380\u001b[0m                             │\n",
       "│                      Plasma                    \u001b[1;36m-1.045\u001b[0m     \u001b[1;36m798.876\u001b[0m            \u001b[1;36m-0.600\u001b[0m                             │\n",
       "│                      Post-capillary Venules    \u001b[1;36m-0.366\u001b[0m      \u001b[1;36m44.266\u001b[0m             \u001b[1;36m0.380\u001b[0m                             │\n",
       "│                      RSPO3+                    \u001b[1;36m-0.366\u001b[0m      \u001b[1;36m23.717\u001b[0m             \u001b[1;36m0.380\u001b[0m                             │\n",
       "│                      Secretory TA               \u001b[1;36m0.000\u001b[0m      \u001b[1;36m25.437\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      Stem                       \u001b[1;36m0.000\u001b[0m      \u001b[1;36m28.480\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      TA \u001b[1;36m1\u001b[0m                       \u001b[1;36m0.335\u001b[0m      \u001b[1;36m87.287\u001b[0m             \u001b[1;36m1.391\u001b[0m                             │\n",
       "│                      TA \u001b[1;36m2\u001b[0m                       \u001b[1;36m0.335\u001b[0m      \u001b[1;36m74.381\u001b[0m             \u001b[1;36m1.391\u001b[0m                             │\n",
       "│                      Tregs                     \u001b[1;36m-0.676\u001b[0m      \u001b[1;36m63.765\u001b[0m            \u001b[1;36m-0.067\u001b[0m                             │\n",
       "│                      Tuft                       \u001b[1;36m0.000\u001b[0m      \u001b[1;36m14.972\u001b[0m             \u001b[1;36m0.908\u001b[0m                             │\n",
       "│                      WNT2B+ Fos-hi             \u001b[1;36m-0.366\u001b[0m      \u001b[1;36m91.855\u001b[0m             \u001b[1;36m0.380\u001b[0m                             │\n",
       "│                      WNT2B+ Fos-lo \u001b[1;36m1\u001b[0m           \u001b[1;36m-0.366\u001b[0m     \u001b[1;36m134.317\u001b[0m             \u001b[1;36m0.380\u001b[0m                             │\n",
       "│                      WNT2B+ Fos-lo \u001b[1;36m2\u001b[0m           \u001b[1;36m-0.366\u001b[0m      \u001b[1;36m76.570\u001b[0m             \u001b[1;36m0.380\u001b[0m                             │\n",
       "│                      WNT5B+ \u001b[1;36m1\u001b[0m                  \u001b[1;36m-0.366\u001b[0m      \u001b[1;36m64.470\u001b[0m             \u001b[1;36m0.380\u001b[0m                             │\n",
       "│                      WNT5B+ \u001b[1;36m2\u001b[0m                  \u001b[1;36m-0.366\u001b[0m      \u001b[1;36m96.371\u001b[0m             \u001b[1;36m0.380\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_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_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_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_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",
       "│ 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",
       "│ 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",
       "│ 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_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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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_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_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_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_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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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_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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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\">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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ CD4+ Activated Fos-lo                 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">-0.36</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+ 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",
       "│ 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",
       "│ 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",
       "│ 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_Epithelial                    \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_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_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",
       "│ Stem                                   \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",
       "│ 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_T cells                      \u001b[1;36m-0.68\u001b[0m            \u001b[3;92mTrue\u001b[0m                                                     │\n",
       "│ Major_l3_B cells                      \u001b[1;36m-0.71\u001b[0m            \u001b[3;92mTrue\u001b[0m                                                     │\n",
       "│ NKs                                    \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ ILCs                                   \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ Major_l3_Mast                          \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_l4_Immature cells                \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_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",
       "│ Major_l4_WNT5B+                        \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",
       "│ Inflammatory Fibroblasts               \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",
       "│ 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_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",
       "│ Cycling B                              \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",
       "│ Follicular                             \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",
       "│ 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",
       "│ 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",
       "│ Inflammatory Monocytes                 \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",
       "│ 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",
       "│ 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",
       "│ 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",
       "│ Enteroendocrine                        \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",
       "│ Tuft                                   \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",
       "│ WNT2B+ Fos-hi                          \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",
       "│ RSPO3+                                 \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",
       "│ CD8+ IELs                              \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",
       "│ 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",
       "│ CD4+ Memory                            \u001b[1;36m0.00\u001b[0m           \u001b[3;91mFalse\u001b[0m                                                     │\n",
       "│ CD4+ Activated Fos-lo                 \u001b[1;36m-0.36\u001b[0m            \u001b[3;92mTrue\u001b[0m                                                     │\n",
       "│ CD4+ PD1+                              \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",
       "│ MT-hi                                  \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",
       "│ 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": 10,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Covariate                    Node                 \n",
       "Health[T.Non-inflamed]_node  Major_l1_Immune          False\n",
       "                             Major_l2_Epithelial      False\n",
       "                             Major_l2_Stromal          True\n",
       "                             Major_l2_Lymphoid        False\n",
       "                             Major_l2_Myeloid          True\n",
       "                                                      ...  \n",
       "                             CD4+ Activated Fos-hi    False\n",
       "                             MT-hi                    False\n",
       "                             Tregs                    False\n",
       "                             DC2                      False\n",
       "                             DC1                      False\n",
       "Name: Final Parameter, Length: 74, dtype: bool"
      ]
     },
     "execution_count": 10,
     "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": 11,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt.pl.coda.draw_effects(smillie_data, modality_key=\"coda_LP\", tree=smillie_data[\"coda_LP\"].uns[\"tree\"], covariate=\"Health[T.Non-inflamed]\")"
   ]
  },
  {
   "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": 12,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pt.pl.coda.draw_effects(smillie_data, modality_key=\"coda_LP\", tree=smillie_data[\"coda_LP\"].uns[\"tree\"], covariate=\"Health[T.Non-inflamed]\", show_legend=False, show_leaf_effects=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}