research_amp/cc/notebooks/Master_model_prediction_analyzer.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "641dfabd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-24T21:11:47.079441Z",
     "start_time": "2023-08-24T21:11:45.400486Z"
    }
   },
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "421d3567",
   "metadata": {},
   "source": [
    "# Descriptions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1775aed",
   "metadata": {},
   "source": [
    "Compute model performance metrics."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd2460ef",
   "metadata": {},
   "source": [
    "# Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c891ef5b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-24T21:11:58.091653Z",
     "start_time": "2023-08-24T21:11:47.084877Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/app/amp/core/signal_processing/decorrelation.py:12: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n",
      "  from tqdm.autonotebook import tqdm\n"
     ]
    }
   ],
   "source": [
    "import datetime\n",
    "import logging\n",
    "\n",
    "import core.config as cconfig\n",
    "import dataflow.core as dtfcore\n",
    "import dataflow.model as dtfmod\n",
    "import helpers.hdataframe as hdatafr\n",
    "import helpers.hdbg as hdbg\n",
    "import helpers.henv as henv\n",
    "import helpers.hpandas as hpandas\n",
    "import helpers.hprint as hprint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "09f1ee19",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-24T21:11:58.426546Z",
     "start_time": "2023-08-24T21:11:58.094924Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0m\u001b[36mINFO\u001b[0m: > cmd='/venv/lib/python3.8/site-packages/ipykernel_launcher.py -f /home/.local/share/jupyter/runtime/kernel-2362db0d-4090-41a5-ab85-9866ab52ad81.json'\n",
      "WARNING: Running in Jupyter\n",
      "INFO  # Git\n",
      "  branch_name='CmTask5051_Port_Cx_ProdSystem_to_the_new_style'\n",
      "  hash='31bf2944a'\n",
      "  # Last commits:\n",
      "    * 31bf2944a Nina Lee checkpoint                                                        (   4 hours ago) Thu Aug 24 16:59:26 2023  (HEAD -> CmTask5051_Port_Cx_ProdSystem_to_the_new_style, origin/CmTask5051_Port_Cx_ProdSystem_to_the_new_style)\n",
      "    * caac00b99 Nina Lee checkpoint                                                        (   4 hours ago) Thu Aug 24 16:42:38 2023           \n",
      "    *   65f9a7ba3 Nina Lee Merge branch 'master' into CmTask5051_Port_Cx_ProdSystem_to_the_new_style (   5 hours ago) Thu Aug 24 16:23:23 2023           \n",
      "    |\\  \n",
      "# Machine info\n",
      "  system=Linux\n",
      "  node name=c24ced58c9eb\n",
      "  release=5.15.0-1039-aws\n",
      "  version=#44~20.04.1-Ubuntu SMP Thu Jun 22 12:21:12 UTC 2023\n",
      "  machine=x86_64\n",
      "  processor=x86_64\n",
      "  cpu count=8\n",
      "  cpu freq=scpufreq(current=2499.9959999999996, min=0.0, max=0.0)\n",
      "  memory=svmem(total=33280286720, available=18857377792, percent=43.3, used=13942001664, free=2452606976, active=1823141888, inactive=26039767040, buffers=440303616, cached=16445374464, shared=3567616, slab=2537598976)\n",
      "  disk usage=sdiskusage(total=156052275200, used=79818858496, free=76216639488, percent=51.2)\n",
      "# Packages\n",
      "  python: 3.8.10\n",
      "  cvxopt: 1.3.2\n",
      "  cvxpy: 1.3.2\n",
      "  gluonnlp: ?\n",
      "  gluonts: 0.6.7\n",
      "  joblib: 1.3.2\n",
      "  mxnet: 1.9.1\n",
      "  numpy: 1.20.3\n",
      "  pandas: 1.5.1\n",
      "  pyarrow: 10.0.0\n",
      "  scipy: 1.10.1\n",
      "  seaborn: 0.12.2\n",
      "  sklearn: 1.3.0\n",
      "  statsmodels: 0.14.0\n"
     ]
    }
   ],
   "source": [
    "hdbg.init_logger(verbosity=logging.INFO)\n",
    "\n",
    "_LOG = logging.getLogger(__name__)\n",
    "\n",
    "_LOG.info(\"%s\", henv.get_system_signature()[0])\n",
    "\n",
    "hprint.config_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7dcf7a98",
   "metadata": {},
   "source": [
    "# Config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "08bf1b13",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-24T21:11:58.594459Z",
     "start_time": "2023-08-24T21:11:58.432580Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dir_name: /shared_data/model/historical/build_tile_configs.C1b.ccxt_v7_1-all.5T.2019-10-01_2023-02-13.ins/tiled_results/\n",
      "asset_id_col: asset_id\n",
      "dag_builder_name: C1b\n",
      "dag_builder_ctor_as_str: dataflow_orange.pipelines.C1.C1b_pipeline.C1b_DagBuilder\n",
      "backtest_config: ccxt_v7_1-all.5T.2019-10-01_2023-02-13\n",
      "start_date: 2019-10-01\n",
      "end_date: 2023-02-13\n",
      "metrics: \n",
      "  calculate_hit_rate_kwargs: \n",
      "    alpha: None\n",
      "    method: None\n",
      "    threshold: None\n",
      "    prefix: None\n",
      "  n_quantiles: 10\n",
      "  column_names: \n",
      "    hit: hit\n",
      "    bar_pnl: bar_pnl\n",
      "  time_scaling: 105156.125\n",
      "column_names: \n",
      "  price: vwap\n",
      "  volatility: vwap.ret_0.vol\n",
      "  target_variable: vwap.ret_0.vol_adj.shift_-2\n",
      "  prediction: vwap.ret_0.vol_adj.shift_-2_hat\n"
     ]
    }
   ],
   "source": [
    "config = {\n",
    "    \"dir_name\": \"/shared_data/model/historical/build_tile_configs.C1b.ccxt_v7_1-all.5T.2019-10-01_2023-02-13.ins/tiled_results/\",\n",
    "    \"asset_id_col\": \"asset_id\",\n",
    "    \"dag_builder_name\": \"C1b\",\n",
    "    \"dag_builder_ctor_as_str\": \"dataflow_orange.pipelines.C1.C1b_pipeline.C1b_DagBuilder\",\n",
    "    \"backtest_config\": \"ccxt_v7_1-all.5T.2019-10-01_2023-02-13\",\n",
    "    \"start_date\": datetime.date(2019, 10, 1),\n",
    "    \"end_date\": datetime.date(2023, 2, 13),\n",
    "    \"metrics\": {\n",
    "        \"calculate_hit_rate_kwargs\": {\n",
    "            \"alpha\": None,\n",
    "            \"method\": None,\n",
    "            \"threshold\": None,\n",
    "            \"prefix\": None,\n",
    "        },\n",
    "        \"n_quantiles\": 10,\n",
    "        \"column_names\": {\n",
    "            \"hit\": \"hit\",\n",
    "            \"bar_pnl\": \"bar_pnl\",\n",
    "        },\n",
    "    },\n",
    "}\n",
    "# Add `Daguilder` column names to the config.\n",
    "dag_builder = dtfcore.get_DagBuilder_from_string(\n",
    "    config[\"dag_builder_ctor_as_str\"]\n",
    ")\n",
    "dag_config = dag_builder.get_config_template()\n",
    "column_tags = [\"price\", \"volatility\", \"target_variable\", \"prediction\"]\n",
    "config[\"column_names\"] = dag_builder.get_column_names_dict(column_tags)\n",
    "# Add `vol_adj_returns` column if needed.\n",
    "# config[\"column_names\"][\"vol_adj_returns\"] = \"target_vwap_ret_0.vol_adj\"\n",
    "# Add start and end dates to the config.\n",
    "if \"start_date\" in config:\n",
    "    hdbg.dassert_in(\"end_date\", config)\n",
    "else:\n",
    "    # Extract start and end datetimes from the backtest config.\n",
    "    hdbg.dassert_in(\"backtest_config\", config)\n",
    "    backtest_config = config[\"backtest_config\"]\n",
    "    _, _, time_interval_str = cconfig.parse_backtest_config(backtest_config)\n",
    "    start_ts, end_ts = cconfig.get_period(time_interval_str)\n",
    "    config[\"start_date\"] = start_ts.date()\n",
    "    config[\"end_date\"] = end_ts.date()\n",
    "# Add time scaling to the metrics config.\n",
    "freq = dag_config[\"resample\"][\"transformer_kwargs\"][\"rule\"]\n",
    "time_scaling = hdatafr.compute_points_per_year_for_given_freq(freq)\n",
    "config[\"metrics\"][\"time_scaling\"] = time_scaling\n",
    "#\n",
    "config = cconfig.Config().from_dict(config)\n",
    "print(config)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29bf070b",
   "metadata": {},
   "source": [
    "# Load results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5a1eb695",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-18T11:34:52.645161Z",
     "start_time": "2023-08-18T11:34:52.640732Z"
    }
   },
   "outputs": [],
   "source": [
    "# Get data column names to request.\n",
    "data_cols = list(config[\"column_names\"].to_dict().values())\n",
    "if config[\"dag_builder_name\"] in [\"C3a\", \"C8b\"]:\n",
    "    # Remove target variable column name for models that do not compute it.\n",
    "    data_cols.remove(config[\"column_names\"][\"target_variable\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f8a505c5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-18T11:35:53.121992Z",
     "start_time": "2023-08-18T11:34:53.692354Z"
    }
   },
   "outputs": [
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     "output_type": "display_data"
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-10-01 00:05:00+00:00</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-10-01 00:10:00+00:00</th>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-10-01 00:15:00+00:00</th>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-10-01 00:20:00+00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8235.761381</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.002071</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                vwap              vwap.ret_0.vol            vwap.ret_0.vol_adj.shift_-2            vwap.ret_0.vol_adj.shift_-2_hat                  vwap                                                                                                                                                                                                                                                   vwap.ret_0.vol                                                                                                                                                                                                                                                   vwap.ret_0.vol_adj.shift_-2                                                                                                                                                                                                                                                   vwap.ret_0.vol_adj.shift_-2_hat                        \\\n",
       "asset_id                  1464553467   1467591036     1464553467 1467591036                  1464553467 1467591036                      1464553467 1467591036 1030828978 1528092593 1776791608 1891737434 1966583502 2099673105 2237530510 2384892553 2425308589 2476706208 2484635488 2540896331 2601760471 2683705052 3065029174 3401245610 4516629366 5115052901 5118394986 6051632686 8717633868 8968126878 9872743573     1030828978 1528092593 1776791608 1891737434 1966583502 2099673105 2237530510 2384892553 2425308589 2476706208 2484635488 2540896331 2601760471 2683705052 3065029174 3401245610 4516629366 5115052901 5118394986 6051632686 8717633868 8968126878 9872743573                  1030828978 1528092593 1776791608 1891737434 1966583502 2099673105 2237530510 2384892553 2425308589 2476706208 2484635488 2540896331 2601760471 2683705052 3065029174 3401245610 4516629366 5115052901 5118394986 6051632686 8717633868 8968126878 9872743573                      1030828978 1528092593 1776791608   \n",
       "end_ts                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            \n",
       "2019-10-01 00:00:00+00:00        NaN  8282.824049            NaN   0.001509                         NaN  -0.756972                             NaN  -0.022196        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN            NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN                         NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN                             NaN        NaN        NaN   \n",
       "2019-10-01 00:05:00+00:00        NaN  8245.537329            NaN   0.003570                         NaN  -0.270427                             NaN   0.035918        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN            NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN                         NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN                             NaN        NaN        NaN   \n",
       "2019-10-01 00:10:00+00:00        NaN  8236.123917            NaN   0.002732                         NaN   0.337224                             NaN   0.029619        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN            NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN                         NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN                             NaN        NaN        NaN   \n",
       "2019-10-01 00:15:00+00:00        NaN  8228.176188            NaN   0.000890                         NaN  -2.306540                             NaN  -0.007338        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN            NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN                         NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN                             NaN        NaN        NaN   \n",
       "2019-10-01 00:20:00+00:00        NaN  8235.761381            NaN   0.002071                         NaN   0.250014                             NaN  -0.020015        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN            NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN                         NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN                             NaN        NaN        NaN   \n",
       "\n",
       "                                                                                                                                                                                                                                                       \n",
       "asset_id                  1891737434 1966583502 2099673105 2237530510 2384892553 2425308589 2476706208 2484635488 2540896331 2601760471 2683705052 3065029174 3401245610 4516629366 5115052901 5118394986 6051632686 8717633868 8968126878 9872743573  \n",
       "end_ts                                                                                                                                                                                                                                                 \n",
       "2019-10-01 00:00:00+00:00        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN  \n",
       "2019-10-01 00:05:00+00:00        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN  \n",
       "2019-10-01 00:10:00+00:00        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN  \n",
       "2019-10-01 00:15:00+00:00        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN  \n",
       "2019-10-01 00:20:00+00:00        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN        NaN  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iter_ = dtfmod.yield_processed_parquet_tiles_by_year(\n",
    "    config[\"dir_name\"],\n",
    "    config[\"start_date\"],\n",
    "    config[\"end_date\"],\n",
    "    config[\"asset_id_col\"],\n",
    "    data_cols,\n",
    "    asset_ids=None,\n",
    ")\n",
    "df_res = hpandas.get_df_from_iterator(iter_)\n",
    "df_res.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b57c102",
   "metadata": {},
   "source": [
    "# Compute metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "37cc731a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-18T11:36:36.565758Z",
     "start_time": "2023-08-18T11:36:36.561091Z"
    }
   },
   "outputs": [],
   "source": [
    "metric_modes = [\"hit_rate\", \"pnl\", \"sharpe_ratio\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f1fa096",
   "metadata": {},
   "source": [
    "## Overall"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "38a61fa9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-18T11:36:44.457544Z",
     "start_time": "2023-08-18T11:36:37.415372Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO  removed rows with nans: 7367 / 6039243 = 0.12%\n"
     ]
    },
    {
     "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>hit_rate_point_est_(%)</th>\n",
       "      <th>hit_rate_97.50%CI_lower_bound_(%)</th>\n",
       "      <th>hit_rate_97.50%CI_upper_bound_(%)</th>\n",
       "      <th>total_pnl</th>\n",
       "      <th>SR</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>all</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>all</th>\n",
       "      <td>51.865224</td>\n",
       "      <td>51.825349</td>\n",
       "      <td>51.905097</td>\n",
       "      <td>8888.756355</td>\n",
       "      <td>9.150719</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     hit_rate_point_est_(%)  hit_rate_97.50%CI_lower_bound_(%)  hit_rate_97.50%CI_upper_bound_(%)    total_pnl        SR\n",
       "all                                                                                                                     \n",
       "all               51.865224                          51.825349                          51.905097  8888.756355  9.150719"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tag_mode = \"all\"\n",
    "stats_all = dtfmod.cross_val_apply_metrics(\n",
    "    [df_res], tag_mode, metric_modes, config\n",
    ")\n",
    "stats_all"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77baa7d3",
   "metadata": {},
   "source": [
    "## Per asset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "eb74c6ee",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-18T11:36:58.853473Z",
     "start_time": "2023-08-18T11:36:48.922806Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO  removed rows with nans: 7367 / 6039243 = 0.12%\n",
      "INFO  backtest_config='ccxt_v7_1-all.5T.2019-10-01_2023-02-13'\n",
      "INFO  universe_str='ccxt_v7_1-all', trading_period_str='5T', time_interval_str='2019-10-01_2023-02-13'\n"
     ]
    }
   ],
   "source": [
    "tag_mode = \"full_symbol\"\n",
    "stats_by_symbol = dtfmod.cross_val_apply_metrics(\n",
    "    [df_res], tag_mode, metric_modes, config\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "37465948",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-18T11:36:59.689487Z",
     "start_time": "2023-08-18T11:36:58.857339Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='full_symbol'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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SpUol+XuX2Zk6rpmaN+PaFaaMa5n9/JxCyL9KlCiRpCL7ww8/KC4uTtWrV0/SLi4uTtmyZbM6PK8pW7asNm3alPh63bp1crlcql27dpJ2x48fV6FChawOz2tuu+027dq1K/H11q1b5Xa7VaNGjSTtzp8/r9y5c1sdnteYup+b2t8c31eY0t933313kjvgV69eLZfLpbp16yZpd+TIEcesFyGZm7ep47mfn1+SAscvv/yiixcv6sEHH0zSzuVyycfHOae5lSpV0uzZsxN/XH/xxRdyuVxq2LBhknZ//vmnihUrZkeIXmFq3qaOawEBAVq0aFHi67CwMLlcrmTTLxw4cCBJITizM7W/TT1PNTVvU4/v0qVL66effkp8vXHjRklKdoNWVFRUkhu5MjtTxzVT82Zcu8KUcS2zn59nsTuAW0W9evU0efJklStXTn5+fpowYYKyZcuWrCN37typ22+/3aYoM16HDh00cOBARUdHq0iRIvriiy9UunRpPfTQQ0nabdy4Uffcc49NUWa8Zs2aafLkySpUqJD8/Pw0duxY5cmTJ9m6Ajt27Ej2qFtmZup+bmp/c3yb1d9du3ZV9+7ddeTIEfn5+enrr79WhQoVkt2Js27dOlWoUMGmKDOeqXmbOp5Xr15d06ZNU82aNVWwYEHNmDFDvr6+atSoUZJ2u3btUokSJWyKMuO99NJLateunWrVqqU8efIoMjJSQUFByaZfWL58ebK7sTIzU/M2dVx74YUX9Mwzz6hp06YqXLiwfvjhB9WuXfua011WqlTJpigznqn9bep5qql5m3p8t23bVmPGjJEkFSlSRJMmTVLhwoX18MMPJ2m3ZcsW3XnnnXaE6BWmjmum5s24Zta4ltnPzymE/KtXr176/vvv9cwzz0i6cifh4MGDVbhw4cQ2brdbS5Ys0aOPPmpXmBmuZcuWioyM1Jw5cxQdHa0KFSpo+PDhypLl/3eNkydPat26derdu7eNkWasrl276ueff9aAAQMkSbly5dLbb7+tvHnzJraJjY3V4sWL1b59e7vCzHCm7uem9jfHt1n9Xa9ePY0dO1Zz5szRrl271KxZM73yyitJ2pw8eVIHDhxQt27dbIoy45mat6njecKJd/369eXj4yO3262uXbsmmadWkpYuXZrs6ZjMrFy5clq6dKkWLlyos2fPqkKFCmrdunWSNidPnlRAQECyRVkzM1PzNnVce+CBBxQSEqJ58+YpOjpavXr1UpcuXZK0OXnypHx9fdWqVSt7gvQCU/vb1PNUU/M29fh++umntXfvXk2YMEFxcXEqWbKkxo4dm2y6rKVLl+r555+3MdKMZeq4ZmrejGtmjWuZ/fzc5fF4PHYHcatwu93asmWLoqOjFRAQkOxO4TNnzuj7779XpUqVksxPjczrn3/+0ZkzZ1S2bFnlyZMnyXsxMTHav3+/7rjjjiQXUDM7k/dzE/vbZPQ3nM7U8fzs2bNauXJl4g+t/86zferUKYWGhqpevXrJ7kwCAACw2sWLF3X+/PlrTgsUFxens2fPKk+ePMqaNasN0QGAOSiEAAAAAAAAAAAAx2JqrH9t27YtxfeyZMmiwoULq3Tp0hZGZI3Bgwen+F7WrFlVqFAhVa9ePdncfpldaGhoiu8l9Pd9992X7C7yzM7U/dzU/ub4Ts7J/d2xY8cU37u6v1u2bKns2bNbGJl3mZq3qeP51Qul/1eWLFlUoEABRy0On8Df318ul+ua7/n6+qpw4cKqVq2aunfvrrvvvtvi6LzH1LxNHdcaNmyYYn8njGvVqlVThw4dHLXIrKn9bep5qql5m3p8f/LJJym+l9DfDz74oMqWLWthVN5n6rhmat6Ma8k5eVzL7OfnPBHyr4SOTOk/h8vlkp+fn1566SU9/vjjFkfnPdebp87tduv48eOKiopStWrVNGXKFOXKlcu64LzI398/1TY5cuRQ586d1adPHwsisoap+7mp/c3xnTIn9nevXr1SPCFxu906duyYdu/erTvuuEOzZ89OspZEZmZq3iaP5yn1tyT5+PjovvvuU58+fRz1Y2vWrFkp5h0fH69jx45p3bp1ioiI0Oeff657773X4gi9w9S8TR3X3n777VT7e8uWLcqSJUviQqxOYGp/m3qeamreph7f/10k+2put1vnz5+Xy+VSy5Yt9c4778jX19fC6LzH1HHN1LwZ15Jz8riW2c/PKYT8648//kjxvYQBa/Xq1VqyZInGjBmj5s2bWxidvbZv364XXnhBbdq00cCBA+0OJ0OcPXs2xfeu7u+JEydqyJAhCg4OtjA67zF1Pze1v9OC49us/j506JA6duyohx56SG+99Zbd4VjGiXmbOp5/8803Kb6XcOK9evVqbd++XdOmTVOtWrUsjM5ecXFx6tSpk3Lnzq0pU6bYHY5lTM3bieNaWpw7d05PP/207rrrLo0dO9bucCxjan878Tw1LUzN28TjOyYmRqtXr9aIESP0/PPPq1evXnaHZBlTxzVT82ZcM2dck27x83MP0mXo0KGetm3b2h2G5UJCQjwNGjSwOwzLjR492hMYGGh3GJYzdT83tb85vs0yf/58T506dewOw3Km5m3qeP7CCy94nnnmGbvDsNzy5cs91apVszsMy5mat6njWmhoqKdmzZp2h2E5U/vb1PNUU/M29fieOHGip0mTJnaHYTlTxzVT82ZcM8uten7uY3chJrNp3Lix/vrrL7vDsNw999yjY8eO2R2G5WrVqqW///7b7jAsZ+p+bmp/c3ybpVSpUjp9+rTdYVjO1LxNHc9btWql3377ze4wLFewYEFduHDB7jAsZ2repo5rxYoVu+7Tn05lan+bep5qat6mHt8PPPDAdddBcypTxzVT82ZcM8uten5OIQRpcuzYMeXNm9fuMCwXGxurLFmy2B0GLGJqf3N8m+XgwYMqWLCg3WFYztS8TZU9e3a53W67w7Dczz//rJIlS9odhuVMzdvUce3PP/9U0aJF7Q7Dcqb2t6nnqabmberxHRUVpZw5c9odhuVMHddMzZtxzSy36vk5hZB0WrNmzS256r03nTt3TtOmTVPNmjXtDsVyS5cuVYUKFewOw3Im7ueSmf3N8W1Wfx8+fFiTJk1SvXr17A7FUqbmLZk7nn///fe644477A7DMufOndPSpUs1ZcoUtWzZ0u5wLGNq3pK549r27ds1ceJENWnSxO5QLGVqf5t6nmpq3qYe3/Hx8fr8889VuXJlu0OxlKnjmql5M66ZM67d6ufn5t0Km4LrTZ/gdrt14sQJrVmzRosXL9aYMWMsjMy7rrc4U0LeW7dula+vrz755BMLI/OuVatWpfje1f29bds2TZs2zcLIvMvU/dzU/ub4Ts7J/d2jR48U34uPj9eJEye0e/dulSpVSn379rUwMu8yNW9Tx/OoqKgU34uPj9fx48e1Zs0ahYSEaPDgwdYF5mWVK1eWy+W65nvx8fGKjY2Vx+NRYGDgdY+JzMbUvE0d14KCglJ8LyHv6OhoVa1aVX369LEwMu8ytb9NPU81NW9Tj++ZM2em+F5Cf3/77beKiIjQ3LlzLYzMu0wd10zNm3EtOSePa5n9/Nzl8Xg8dgdxK/D390+xIyXJ4/HIz89Pffr0Ubt27SyMzLsaNmyY4ntZsmRRoUKFVK1aNXXs2FF+fn4WRuZd/v7+133fx8dH9913n3r37q06depYFJX3mbqfm9rfHN/X5tT+7tChQ4rvXd3fjz32mKMevTc1b5PH8+vlLUlZs2bVc88956gfmOPHj08xb19fXxUqVEgPPvigypUrZ3Fk3mVq3qaOa4MGDUq1v6tVq6Y6deqkOg5kJqb2t6nnqabmberxfb3fJb6+vipYsKCqV6+u7t27q3z58hZG5l2mjmum5s24lpyTx7XMfn5OIeRfW7duTfG9hI4sU6aMo3Zekx0+fDjF97JkyaICBQooe/bsFkZkDVP3c1P721T0N0xg6ni+ePHiVE+8K1WqZOT8wynZtm2bKlSooFy5ctkdiqVMzdtUR44cUdGiRY1c+wtwOo5vAE5j6rh2S5yfe3BT4uPjPePHj/ccO3bM7lAs5Xa7PQ0bNvTs2bPH7lAsFR8f7xk0aJDn8OHDdodiKVP3c1P7m+PbrP6Oi4vz+Pv7e3799Ve7Q7GUqXmbOp57PB7PkiVLPFFRUXaHYSlT93PyJm8TmJq3qeeppuZt8n7eoUMHz/79++0OxVKm9repeTOumdXft0reLJZ+k+Lj4zVhwgQdO3bM7lAs5fF4dPjwYV26dMnuUCwVHx+v0NBQnT592u5QLGXqfm5qf3N8m9Xf0pU+N5GJeZs6nrvdbg0ePFiHDh2yOxTLmbifS+RtGvI2h6nnqabmLZm7n2/dulUxMTF2h2I5E/tbMjNvxjXz3Ap5UwjJALdCR8I6pvY3ecME9DdMYOp+bmreAAAAAAAKIQAAAAAAAAAAwMEohAAAAAAAAAAAAMeiEAIAAAAAAAAAAByLQghumMvlsjsEAF7C8Q0AAIBbkannqabmDcC5GNdgNQohuGEsOgo4F8e3OVwul0qWLKls2bLZHYqlTM0bZvHx8VHr1q1VsGBBu0OxlEl5Hzx4MPH/mzquuVwuVatWTblz57Y7FEuZ2t+SueepJuZt6vFtqsw+rm3btk0xMTHp/lxmz/tmMK6Z41Y5P3d5TNzrMtiSJUvUsGFD5c+f3+5QYIGtW7eqYsWKypUrl92hWCoz7+cbNmxQ3bp1U213+fJlDRgwQB9++GHiNhP6e/Xq1erbt69+/fVXu0Ox3LZt21StWrXE107t7z179mjv3r3y8/NT1apVjbrz5tSpU8qTJ4+RPyxSkpnH88WLF6tJkybKkydPuj7n8Xg0YcIEPfnkk/Lz8/NSdN4zd+5cBQcHp9ru+PHjGjVqlMaOHWtBVPa5ePGiFi5cmDiutW7dWiVKlLA7rAwzZMgQvfPOO6m2++OPP9S1a1dt3LjRgqi8b+fOnbr77ruVM2fO67Y7ffq0Nm7cqKCgIIsi864//vhD/v7+aWo7b948tW/f3ssR3Vri4uJ08uRJFStWzO5QkEEOHDign376SSdOnJDL5VKRIkVUuXJllS5d2u7QMlxAQIC+/PJL3X///en+7OHDh1W0aFFlzZrVC5F5319//aV58+bp0KFDKlq0qB599FE99NBDdoflVTfT3yZgPHeGY8eOaeTIkXriiSdSvM62YcMGzZ8/XyNGjFDhwoUtjvD6KIT8a8SIEerWrZtuu+22xG1hYWGqV6+e8uXLl7ht7969evvttzVjxgw7wsxwb731VprbZsuWTbfddpsaNGigkiVLejEq7wsNDU1X+1atWnklDqv99ttv6WpfoUIFL0VirUqVKmn8+PF6+OGHU2xz8eJFvfDCC9qyZYtxBYGvv/5aL7/8snbt2mV3KJb55ptvNG3aNP3888+OyXvZsmXauHGj3nvvvSTbBw4cqGXLliW+rlixombOnJnuC8m3sh9//FFr1qxRXFycmjRpoipVqig0NFTvvfeeTp8+rSxZsqhNmzZ67bXXlCVLFrvDzRC//vqrunTpovfee0/16tW7Zpv169drwIABCgkJSfNFtludv7+/smfPrvr16ysoKEj16tXLtBcI0qNChQqqWLGi3njjjWv2pcfj0ezZs/XRRx8pT548Wr9+vQ1RZrwPP/xQa9euVVhYWOK2CxcuqG3bttq3b1/iXYT58+fXwoULVapUKbtCzVAVK1ZUUFCQ3nnnnRQL1zt27FCPHj3k5+enFStWWByhd/z3AlJ8fLzuv/9+zZ8/X/fee29iu59//lnt27d3zN/vChUq6Nlnn1Xv3r1TLALt2rVLr7/+un7//fd0n8/fqipVqqQ5c+bovvvuk3RlHOvSpYuGDx+uO+64I7Gd0/p78ODBaW7rcrnSVBTNLCIjIzVkyBBt2rQp2V3gLpdLdevW1dtvv50pb1hIib+/v+bPn2/chfHt27frueeeU1xcnAoVKqSoqCjFx8fr9ddf11NPPWV3eF5jan+bOp6n54YMl8uV5Dd5ZjZ69Ght3rxZS5YsSfE81ePxqE2bNqpdu7b69etncYTX54yrARngyy+/VJs2bRILIW63WwMGDNDChQuTXAw+d+6cNm/ebFeYGW7t2rVpbhsbG6uoqCiNHj1aU6ZMUa1atbwYmXcNGjQo8YBNrRbocrkcUwh5/PHH03QnuMfjkcvlcswfqAYNGujFF1/Uxx9/rPr16yd7/8yZM+revbt+//13jRs3zvL4kLHi4+M1ffp0LV68WEePHtXtt9+uF198UY8++qg2btyo0aNH66+//tJtt92mN9980+5wM8ySJUuSFalDQ0O1dOlS1a1bV08//bT279+vjz/+WLNmzdKLL75oU6QZa82aNerdu7fy58+vHDlyaPbs2Ro0aJBGjRqlevXqqVy5ctqzZ4/mz5+vsmXLqlOnTnaHnCFCQkJUuXLlFIsgklSvXj1VrVpVM2fO1OjRoy2MznuWLl2q5cuXa8WKFfr666+VL18+NW3aVEFBQapevbrd4XnNl19+qddff11t27ZVhw4d1Lt378Qn13bu3KkRI0Zo9+7deuaZZ9SnTx+bo8043333nRo0aJBkW0hIiPbu3atevXqpS5cu2r9/v/r06aPJkyfr7bfftinSjDV27Fi98sorcrvdGj16dLJzt2+//VYvv/yyypUrp08//dSmKDPef8/JPR6P4uLiHD9tRv/+/fXxxx9r5cqVeu2115Ls8+fOndO4ceP0xRdfyN/fX/PmzbMx0owVGxubpG/j4+O1adMmnTt3zsaovC8tv68uX76svXv3OqoQcuHCBXXs2FHHjh1T586dVadOHRUvXlwej0eRkZH63//+p3nz5qlTp05atGiRcuTIYXfIuAnjx4/XnXfeqcmTJ6tEiRI6d+6cBg8erHHjxjm6EGIqU8fzChUqJDlH83g8Cg0NVf369W2f/smb1q1bp06dOl332qLL5dKTTz6pkJAQCiG3qmudYDv9pFtKXyFEunLB+LXXXtP777+vxYsXeykq78uWLZuyZMmiRx55RIGBgXrggQfsDskSn332md0h2GLs2LHq37+/evfurXHjxqlRo0aJ7x07dkxdunTRkSNH9Omnn6pGjRo2RoqMMGfOHI0ZM0Z33nmnGjRooCNHjuiVV17Rrl27NHXqVPn5+enNN99U69atHfN0gCT9+eefatOmTZJtYWFhypcvnz7++GPlzJlTDRo00Pnz5/X11187phAydepUNWnSRGPGjJGvr68mTZqk0aNH67nnnlP//v0T273zzjtatGiRYwohW7du1cCBA1NtFxgY6JgiiCSVL19e5cuX1yuvvKIff/xR4eHh+vrrr7Vw4UIVLVpULVq0UFBQkAICAuwONUNVrFhRCxcu1GeffZZ4wbRfv37asmWLFixYoEqVKmnRokWOefInwcGDBxPvLkywatUqlSxZMrHgU7FiRXXt2lWzZs2yIULvaNKkiT766CO9/PLLcrvdev/99+Xjc2Vpx2XLlmnIkCGqWrWqJk6caNz80k7UqVMnPfroo3rzzTfVs2dPPfLIIxo6dKh27NihUaNGKTY2VkOGDNHTTz9t1NSWTnW9mQliY2P15Zdfatq0afL19VWLFi2sC8zL5s+fr2PHjiUW9a525513qlatWmrZsqWefvppLVy4UM8884xNkWa8c+fOKSoqKk1tCxQo4NVYrLJnzx698cYbidNW5smTRwMHDlTjxo119OhRR01n+V9btmxRREREmto2adLEy9HAm959990kr+Pi4hQaGqrevXs7ZnaVazl8+LDuuuuuVNuVK1dOhw8ftiCi9HHOFSB43blz55Q/f3499dRT6tGjh93h3JTNmzdr9erVWr58uXr27KnixYsrMDBQgYGBaTqgMysn3y17PT4+Pvrggw80aNAgvfTSS/rwww/1yCOP6O+//1bnzp114cIFffbZZ47+Y2WSBQsWKDAwUO+//37iBYPp06fr/fff14MPPqipU6c6bg0QSYqOjlbx4sUTX7vdbu3YsUMPP/xwkqk2qlSpopkzZ9oRolfs3btXvXv3lq+vrySpffv2+uijj5I9KVG/fn0tWLDAjhC94uTJkypatGiq7YoWLaqTJ09aEJH1KleurMqVK2vo0KHavHmzwsPDtWDBAs2cOVN33nmngoKCMv35ytV8fHwSL5gGBwerX79+crlcjp5mIjY2NskUtefPn9fu3buTPal79913KzIy0uLovKtRo0b65JNP1Lt3b7366qsaM2aMZs+erXfffVeNGzfWmDFjWPvIQYoXL66JEyfqm2++0RtvvKHGjRvL7XYrMDBQAwcOVJEiRewOEV508eJFffHFF5o+fbrOnDmjli1bqnv37o5aM2PNmjVq27btdQv2AQEBatu2rVatWuWoQkiXLl3S3NYpMzKcPn06ye8SSYnFj9OnTzu6EDJ27Ng03VTtpBk4cIUpNytkz549TU/7nD9//pY8V6UQglSdPHlSISEh+uKLL7Rt2zZVrlxZX375pd1h3ZTcuXOrVatWatWqlU6dOqWvvvpKK1as0JQpU3T33XcrMDBQQUFBjvsDvWrVKtWsWTPJRQVTuFwuvfvuu/Lx8VHfvn3Vu3dvhYSEKEeOHJo7d67Kli1rd4gZLq1rAP3zzz9ejsRahw4dSjL9nXRlWrj3339fzz//vCOLIJLk5+enI0eOJL7+5ZdfdPHiRT344INJ2rlcrsQ7i53g3LlzSca0hP//37ukc+fOrYsXL1oamzfly5dPx44dS7XdsWPHlDdvXgsiso+Pj49q166t2rVra8SIEXr//fc1d+5cffTRR44qhEhXFpgdMWKEDh8+rJo1a2r79u36/PPPdc8996hq1ap2h5fhbrvtNu3atSvxac2tW7fK7XYne3rz/Pnzjnwyol69epowYYJefPFFtWzZUnv37lWbNm00cuRIR43jqTHlwsLly5e1e/dunTlzRtmyZdOFCxeUM2dOZc+e3e7Q4CXnz5/XnDlzNGvWLJ09e1Zt2rRR9+7dM/16nNfy119/qWPHjqm2q1mzppYvX25BRNbp0aOHo4pauL7x48c77slk4Grly5fX2rVrrznt/NXWrFmj8uXLWxNUOlAIucrVjyy63e5k2yTp7NmzNkTmXT/99JOWLFmio0ePqlSpUurQoYPKlCmjEydOaMKECVq8eLHi4uLUvHlzSVKOHDkcNfVCoUKFFBwcrODgYEVERGjWrFn66KOPtHPnTn3yySd2h5ehXnrppWSLUDZr1kwTJkxw9JMwCVwul0aNGqWsWbNq3LhxKleunKZPn65ixYrZHZpXpGfqOycV/S5cuJDswm/C68KFC9sRkiWqV6+uadOmqWbNmipYsKBmzJghX1/fJFPBSVfuNHNSf6fE6RfOHnjgAS1cuDDxb3NKFi1apCpVqlgUlX1+++03hYeHa8WKFYqMjFSRIkXUrFkzu8PKMJcvX9aUKVM0depU3XbbbQoJCVGNGjX0119/acSIEerQoYNat26t/v37O2ZaDUlq1qyZJk+erEKFCsnPz09jx45Vnjx5kq0bsmPHjiSLcWZ2Vy+GXahQIb344osaM2ZM4npP/72D1ElPtI4ePTrZ3/B33nlHefLkSXztxN9jW7du1fDhw3X48GE9//zz6tatm5YtW6YPPvhAa9as0YABA/TYY4/ZHWaGCw8P144dOyRd+V3icrkUFhamrVu3Jra5+iYPpzh37pxmz56tkJAQXbhwQe3atVO3bt0c+5tEuvLkclrOwwsVKqTo6GgLIrJOgwYNjFs8W5KeffbZa56PBwcHJ9nucrkSxwEnKFq0aOLawyYxdTw3Udu2bTVs2DBVrlxZrVu3vmab0NBQLV68OM0351qJQshVrvXI4n/nEk9YRNop1q9fr549e8rj8ahQoULatGmTwsPD9d5772ngwIGKjo5WixYt1KtXL0feMZ/g7NmzWrVqlZYvX64tW7bo9ttvT/Yj2wmutQjl33//rdjYWJsiskZQUFCybR6PR+fPn1fXrl2TbHe5XFq2bJlVoXlVetcAcpJ9+/YlTpUk/X9xe9++fcnaOuUC0ksvvaR27dqpfv368vHxkdvtVteuXZOdiC9dutRx0+SZeOGsc+fO6tChgwYPHqyBAwcmu/gdHR2t0aNHa/PmzZo9e7Y9QXrZ/v37FR4ervDwcP3zzz/KlSuXmjRposDAQNWqVctRd8wHBgYqIiJCPXr0ULdu3ZQ1a1ZJ0l133aU5c+Zo0aJFev/997V27Vr1798/2XpBmVXXrl31888/a8CAAZKkXLly6e23305yvMfGxmrx4sVq3769XWFmuMcff/yavzc2bNigjRs3Jr5O+F3ilKk1qlWrJkmKiYm57jYfH59kTztmZgMHDtSyZctUs2ZNTZo0SWXKlJEktWvXTo0aNdLo0aM1cOBALV68WCNGjHDUb7JrrV94rfV+nPT7e/z48Zo9e7bi4uLUvn17denSxdE36iSIi4tLcm6ekoRzWGRuTlmLEGln4nieEqfn2Lp1a23YsEGDBw/WnDlzVLduXZUsWVIul0tHjhzRxo0b9euvv6p58+bJprO9Fbg8JqwIngZLlixJV/uUql6ZzdNPP63Y2FhNnDhRxYoVU0xMjIYNG6bVq1fLz89P48ePV8WKFe0O0ysuXryotWvXKjw8XBs2bFDhwoXVrFkzBQYGOubC6H/5+/tr/vz5iXekuN1uVahQQYsWLXJszpKSTZOUmlGjRnkxGnibv7//Nfs74c9dwntOu4AkXbnYv3LlSkVHR6tChQqqWbNmkvdPnTql0NBQ1atXT+XKlbMpyozVoUOHdLV3UlFg7ty5GjVqlHx8fFSxYkWVKFFCLpdLR48e1a+//iq32524wK5TREZGavny5QoPD9euXbuUJUsW1atXT4GBgWrYsOEtOQ9tRujatauGDx+uUqVKpdgmKipKo0eP1tKlS/X7779bGJ33/fPPPzpz5ozKli2bpMApXblAvn//ft1xxx2OmQbu6rsn08JpxW3T1KlTRwMHDrzmjTsJtmzZkjgt3s6dOy2MDhkt4Tz1/vvvV8GCBa/b1uVyadKkSRZF5l3+/v569NFHU13v5sSJE/r6668dc37+39/fcDb62yzX+rv9559/6o477kj2m8RJN9wmmDt3rmbNmqWDBw8m2V66dGl16tTplv0NSiHEcDVq1NDbb7+txo0bJ247cuSIGjZsqA8++ECBgYE2Ruc9r776qtauXaucOXOqadOmatGihaPuLEuJqYUQ0126dEkrV67U9u3bFRERIenKopzVqlVT06ZNHXfhkAtIMMkff/yhzz77TNu3b09cLLpYsWKqXr26OnTocEvOy3ozAgIC5HK5VK1aNQUGBurRRx91zMXvjLJ9+3Yjzmn+69KlS477e2aaXbt2pXle9YSnJJzg7NmzaRrHLl++rE8//VS9evWyICp4i6k3cDRs2DBd7Z3yZPuSJUtUv379VItepnK73QoLC7sl7xq/EYcPH1bRokUTn9yFs5l6w23Hjh01fPjwxBsrIyMjk/wOvdWneaQQYrhrVawTLo4vWLBA9913n43ReY+/v79y586tKlWqpPqIrtPuxOnYsWPi+gDx8fH64IMP9OyzzyYbrFwuV7Kp4TKrRo0aacKECY5a2yattm/frn79+ikyMlIejydxIemEuXdLliyp999/35GL7KZFwkKkTrBixQrVrl1b+fPnT9yWsFbC1eNcZGSklixZ4rhFpGGGmTNnqnnz5qmeYJ85c0azZ882amqG6OhorVy5UmFhYY65cPbSSy9p2LBh8vPzu2679evXa+TIkfrmm28sigzeUKNGDc2cOVP33ntvim08Ho+GDBmi0NBQx9wxbrL58+dr9uzZOnTokIoWLapmzZqpV69eFDXhOKbdmHa1U6dOqWDBgkkuGF+8eFFffvmlQkJCdPToUceM56Ghoelq75QCUEquXvNMurLesFNmJTBZZn/yiTVC/jV48OA0t3W5XHrnnXe8GM2tIS1zeGZWCfMNX7x40eZIrJeeuRudUgg5fPiwLl26ZHcYltu7d6+6deumkiVL6r333lODBg0SpxSJiYnRunXrNHnyZHXr1k0LFy7UnXfeaXPE1nC73dqwYYPCwsK0du1a/fjjj3aHlCFeffVVffnll0me+Kpfv74WLlyY5ImviIgIffTRR44phGzbti1d7RPGf2ROzz33nKQrU2ccOXJEt912W5K51SMjIzV9+nQtWLBAly9fdnwh5NKlS1qzZo3CwsK0YcMGXb58+boXkTObn376Sc2aNVPfvn319NNPJ7vrLiIiQm+99Za++eYbR63t1rFjxzS3dblcCgkJ8WI01rnrrrvUqVMnTZ8+/Zo3Y126dEmvvPKK1qxZoyFDhtgQoXcdOnRICxYs0E8//aQTJ07I5XKpSJEiqlKlitq2bauSJUvaHWKGWrRokV5//XXdcccdql+/vg4dOqTJkycrOjpar7/+ut3hARnmejemzZ8/Xx9++KHjbkyLjY3VqFGjtHTpUl28eFG5c+dWr1691LlzZ82fP1/jxo3TqVOnVLVqVb399tt2h5thrn5CILV7zl0ul2MKIXv27FGXLl3Up08ftWvXTtKV36JXr3nm8Xjk6+ur0NBQ3X333XaGm2FMvuE2M6MQ8q+0VKAvX76svXv3Oq4Q8uyzz17zca7g4OAk210ul3bs2GFlaF7jlDsl0+uPP/6wOwRYaOLEiSpTpoy++OIL5ciRI8l7uXPnVmBgoBo1aqTg4GBNmDBBY8aMsSlSa+zYsUPh4eFauXKloqKiVKhQIT3xxBN2h5VhrnWybcJDnx06dJDL5bpurgl/y1wul2PWTnjrrbfS1X7YsGFeisRaZ86cUf/+/bVhwwZJVxZVbd++vYYOHaqPPvpIM2fOlNvtVvPmzR07fYzH49GmTZsUFham1atXKyYmJvHHdKdOnRw1HdpXX32lDz/8UO+8845CQ0P15ptvKiAgQG63WzNnztTEiRNVoEABTZgwQY0aNbI73AyTJ0+eVKdaOHnypH766SdHLcg5bdo0Pf/88+rcubOmT5+e5E7DmJgY9ezZUz/88IPee++9666nkRmFhYVp6NChunTpkooVK6YSJUrI4/Fo//79+v777zV9+nSNGjVKzZs3tzvUDDNnzhw9+uijGjt2rHx8fCRJkydP1ieffKIhQ4YoSxbnXqo4cOCAcubMmeTpxpkzZyZpkzt3bkedpx45ciRd7Z1S+DP1xrSpU6dq3rx5ql27tgICAnT48GGNHTtWv/32m5YvX657771XY8aMUa1atewONUNly5ZNWbJk0SOPPKLAwEA98MADdodkiblz56pIkSKJRZCrjRgxQmXLlpXH49HUqVM1Z84cvfHGGzZEmfFMveE2s3Pu2UU6Xe8RttjYWH355ZeaNm2afH191aJFC+sC8zKn3ymZkv/OaQc40ffff6/BgwcnK4JcLWfOnOrcubNj5qv8rz///FPh4eEKCwvT0aNHlTVrVl2+fFmDBw9WcHCwo598M0Vqj6AfP35c06dP1/fff6/cuXNbE5QF0jN3tsvlckwhZPz48dq0aZPatWuX+MN63rx52r17t7Zv364GDRpowIABKlu2rN2hZridO3cqLCxMX331lU6ePKk8efKoadOmql+/vvr06aM2bdo4qggiSbly5dLQoUP12GOP6fXXX1fbtm31+OOP68cff9T+/fv13HPP6YUXXrju37nMaOLEiSm+d/z4cU2bNk3fffed8ubNq2eeecbCyLwrZ86cmjZtmnr06KHOnTvr008/VeXKlXXq1Cl17dpV+/bt04QJE1SvXj27Q81Qe/fu1ZAhQ1S1alW99tpryX6f/Pnnnxo5cqQGDRqkgIAAx4xvf//9t1599dXEIogktW/fXuPGjdPhw4d1xx132Bid96xfv149evTQlClTEgshbrdbo0ePTtLO5XKpePHievjhh+0IM8M1bNgwzYVbJ924YuqNaStWrFDHjh2TPL0XGhqqQYMGqXHjxvr444+THPtOsXnzZq1evVrLly9Xz549Vbx4cQUGBiowMFB33XWX3eF5zffff5/i06wVK1ZMnJ3g+PHj+uSTT6wMDV7Sr18/Zc+ePdV2t+Ii8RRCruPixYv64osvNH36dJ05c0YtW7ZU9+7dVbp0abtDyzCmFkK2bt2qmJgYu8OAhVJ68um/nPTkU3R0tIoXL55qu+LFiyeuGeIEERERicWPPXv2yNfXVzVr1lSfPn1Uo0YNNWjQQAEBARRBHCKlR5GPHTumadOmacGCBcqaNatefPHFdE03c6tzyiKi6fW///1PPXr0SHL+UrVqVfXs2VNPPPGE3nzzTRuj856mTZvqn3/+Ufbs2fXwww8rKChI9erVU7Zs2XT27Fm7w/O6ihUratq0aWrXrp3mz58vHx8fTZgwwVHTYaUmMjJSn376qRYuXKgcOXLo+eefV8eOHRPvLHaK7Nmza8qUKerZs6e6du2qN954Q+PHj9fp06c1ffp0R00dk+Dzzz9XqVKlNHXq1GuuE3D33Xdr2rRpatWqlebOneuYwvb58+cTpwhKkLBo/Llz5+wIyRKLFi1SvXr1rlngWLRoUeIFwxEjRmjhwoWOKYSkdvHz0qVLmj9/vr7//ntHnaObemPa4cOH1bBhwyTbGjduLOnKzCNOLIJIV4pbrVq1UqtWrXTq1Cl99dVXWrFihaZMmaK7775bgYGBCgoKSlyz1SmOHj2abLorHx8f1a9fP8k4X6xYMR09etTq8OAFZcuWVaFChewO44ZQCLmG8+fPa86cOZo1a5bOnj2rNm3aqHv37o55PPN64uPjFRUVJUkqUKCAY/9Amcrf39/IO3EkqUWLFmkqCjhJ8eLFtWvXLj344IPXbff777876r9NwoWxChUqaNiwYWrWrFniH2kTLhj+l5OmTUmLiIgITZ06VYsWLVLOnDnVo0cPBQcHO+5i4eDBg9WrVy+VKlXK7lAsdeTIEdWoUSPJtpo1a0qSWrZsaUdIlvj7778lXSkINGnSRHXr1nX0wqr/FRoaqvfee0/x8fHq06ePQkND1bdvX/Xo0UNdu3Z19BQ6R48e1eTJk7VkyRLlyZNHvXr1UnBwsKOecPuvbNmyadKkSerTp4/69++vIkWKaM6cObrnnnvsDs0rtm7dqieeeOK6x3S2bNn0xBNPaPHixRZG5n379u1LctHb7XYnbv+vq9c7y8x++ukn9e/fP9V2derU0ciRIy2IyBoJF8H/KzY2VvPmzdP06dN16tQptW7dWt27d7c4Ou8x9ca0S5cuKVeuXEm25cyZU5KSFUCdqlChQgoODlZwcLAiIiI0a9YsffTRR9q5c6fjnorw9fXV5cuXk2xzuVyaPHlykm2xsbGOu8Zo4g23kvTCCy+wWLoTnDt3TrNnz1ZISIguXLigdu3aqVu3bknm7nSqb7/9ViEhIfrxxx8VGxsr6codWVWqVNGzzz7ruEfQTXX14l0pWbdunb7//nuLIrLOE088kWkH6hvVuHFjTZo0SXXr1lWZMmWu2ebvv//W1KlT9dhjj1kbnBfly5dPZ86c0cGDB7V7927dc889mfZuhfS61iOqffv2TXJxJWGMd5rDhw9rypQpWrJkifLnz68+ffroqaeeSvYjzCmWLFmip556yrhCSFxcXLJ9PGH/TviB7URLlizRsmXL9NVXX6lfv37KmTOnGjVqpKCgoGsuKu0U+/fv1/Dhw7Vt2za1atVKAwYMUMGCBdW1a1dNnDhREyZMUFhYmEaMGKFq1arZHW6GOnjwoKZMmaLQ0FAVKFBAr7zyitq3b++4acCu1qNHjySvL1++LI/HoyJFimjs2LFJ3nO5XJo0aZKV4XnN0aNH0zStXfny5XX48GELIrLO4MGDr7m9f//+SRbYdblcaVrTMzM4depUsrvBfX19NWDAgCTbCxQooFOnTlkdnmUuXLigzz//XDNnztSZM2fUunVrPf/887r99tvtDi1DmXpjmiRt2bJFERERia/j4+Plcrm0ZcuWZGNZkyZNrA7PEmfPntWqVau0fPlybdmyRbfffrsjn2YtU6aMduzYodq1a1+33fbt21O8LpFZmXjDbWZHIeRf48eP1+zZsxUXF6f27durS5cuKly4sN1hWeKtt97SnDlzlD9/fj388MOJJ2BHjx7Vli1b1KNHDz3zzDMaOnSozZFmrMw8p92N6tSpU4rvffPNN5o4caJ+//13VatWzbGLzJqkZ8+eWrt2rR577DG1atVKDRo0SHJ8f/vttwoNDVXx4sWTXXzIzL777jtt3LhRYWFhCgsL04IFC1SsWDE1b97c0UXdVq1aJSt0VqxY8ZptnTS1yD///KNJkyYpLCxMhQoVUv/+/fXkk0+maXxH5hQeHp7kjqqEH9ZhYWHaunVr4naXy3Xdv3uZSUBAgAICAjRgwABt3bo1caH05cuXK2/evHK5XDpw4IDjigEtW7bUHXfcodmzZye5iJQtWza9/PLLatmypYYPH66OHTvqscce07vvvmtjtBln0KBBCg8Pl5+fnwYPHqx27doZ8QTQtaatTdinnTylbUxMTJqe8MmVK5fOnz9vQUTW+Oyzz+wOwRa5c+dOnIHhap07d07yOioqypE3c8TExCTOvhETE6O2bduqW7dujpsqKIGpN6ZJSnG9k/feey/JaycVOqUrU+yvXbtW4eHh2rBhgwoXLqxmzZrp1VdfdcyTbf/VtGlTTZ8+XS1atEhxHd69e/fq888/V5cuXSyOzrtMvOE2s3N5PB6P3UHcChKmDLr//vtVsGDB67Z10h1IS5cu1aBBg9SrVy916dIl2cnWhQsXNH36dE2cOFGjR49WUFCQTZFmLH9/f9WrVy/Nd4k7ab7O/1q5cqUmTZqkPXv26KGHHlLPnj1TvWMls/H399f8+fON/AN14sQJjRgxQmvWrLnm+40bN9bw4cNVpEgRiyOzxoULF7R69WqFh4dr06ZNiVMuPPXUU+rcubPj7jozUYUKFRQfH68aNWqobdu2qV4sdModZ6aOaymtCXMtTvth/V+XL1/W+vXrFRYWpvXr1ys2NlYlS5ZUq1at1Lt3b7vDyxBTp05V586dU536KmHqrE2bNlkUmXcl7Od33HFHqmOak27YMVVax/Off/5Z7du3d/S4lpILFy445qm/Z599Vrfffrvefvvt67YbMmSIDh065JiC0blz5zRr1izNnj1bsbGxevLJJ9WlSxcVLVrU7tC8Kjo6Wu3atVNERESqN6YtWLAgcZ2czC69T6/ddtttXorEWq+++qrWrl2rnDlzqmnTpmrRooXjrq1cy4ULF/TEE0/o8OHDCg4O1kMPPaQSJUrI5XIpIiJC3333nebOnavbb79d8+bNc8x4burvscw+RTOFkH916NAhXe1nz57tpUis1b59e91zzz2pLi76+uuva8+ePZo3b55FkXmXqQNWAo/Ho+XLl2vy5Mn666+/VK9ePfXq1UuVKlWyOzSv+OSTT9SuXTsjprlLyZEjR7Rt2zZFRkZKurJQWbVq1YxY+yjB6dOntWLFCi1fvlw//vijXC6Xqlat6pjxfNCgQWrZsqVq1apl1Logpl4Y9/f3V9WqVdP0g9lJN3CYavHixWrSpEmKa93ExMRo9erVCgsL05YtW/Trr79aHKH9IiIiHDM1QVqmMr2ak2/YuZYDBw4oLCzMMQU/f39/5cyZM9U+93g8unjxomP+jqXG7XZrw4YNCgsL09q1a/Xjjz/aHVKGWLZsmQYPHqy3335brVq1umabpUuXasiQIXr33XcdcyNitWrVdO7cOdWoUUOdO3dOdfYNJ905b/qNaSbx9/dX7ty5VaVKlSTrH12L087PT58+reHDh2v16tXXfL9JkyYaMWJEqjeeZyamX1e8lujoaB04cEAFCxa8ZQslFEIMV7lyZX3yySepzuX33XffqXfv3vrhhx8sisy7TB2w4uPjtWzZMk2ePFl///23GjVqpJ49ezrqRPNajh07ppEjR+qJJ55Q3bp1r9lmw4YNmj9/vkaMGGHMtHgmO3LkiMLCwhQeHq6wsDC7w8kQDz30kE6fPq3ChQurefPmCgwMNGKMM/WOM39/f917771pXjDZKQU/U/n7+yt79uyqX7++goKCVK9ePWXNmvWabU+dOmXMukhOvVCK5I4fP67ly5crLCxMv/32m7JmzapffvnF7rAyxPjx49NV+HrxxRe9GI39duzYofDwcK1cuVJRUVEqVKiQAgMDU1xPJDN69dVXtXz5ct1///2qXbt2sjunf/75Z7Vo0UIffPCB3aFmmKtvXLne/u60NWGuduTIEW3dulXHjh2T5Owb09avX5+mKYkvXryoCRMm6NVXX7UgKu8z9QbrqyXs58ePH5ckFS1a1LH7uck33K5YsUKrV69WXFycHn30UbVo0UITJ07U5MmTdfnyZUlS7dq19fHHH99y0zxSCDFclSpV9PHHH6tOnTrXbUchxBkeeeQRHTp0SDVq1FCvXr10zz33XLd9gQIFrAnMy0aPHq3NmzdryZIlKZ54ezwetWnTRrVr11a/fv0sjtA7Ll++rNjY2GR3EB8/flwzZszQ3r175efnp/bt2zt6sV1TxMfHa9OmTQoPD9c333yjmJgYlS5dWkFBQQoMDHTcwnSmM/XvmKmF7d27d2v58uVasWKFDh06pHz58qlp06YKCgpS9erV7Q7PciZcKMWVqXRWrVqVuP5PfHy8ypcvr8cff1yBgYGOuqvUdH/++WfizSlHjx5V1qxZdfnyZQ0ePFjBwcGp3lmdGc2dO1ezZs3SwYMHk2wvVaqUOnXqpODgYJsi846r1/BKCxP/tjmJv7+/mjZtqqFDh6Y4/dmaNWv09ttvKyoqyjHXmWCWFStWqHbt2sqfP3/itsjISBUpUiTJ363IyEgtWbLEMeuyLly4UMOGDVNAQIBy586tH3/8Uc8++6xmz56tJ598UuXKldOePXu0YMECdevWTS+99JLdISdBIeRfoaGhKb6XJUsWFS5cWPfdd1+KUxJkVmmdGuu1117TX3/9pS+++MKiyLwrs89pd6PSeidOAqfcifPoo4+qU6dOat++/XXbzZs3TyEhIfrqq68sisy7Ro4cqY0bN+rrr79O3Hb69GkFBQXpxIkTyp8/v86dOydfX199+eWXCggIsDHajNOtWzcNGTJEZcuWTdw2efJktW3bNskj53/88YdeeumlJP99nOLSpUtat26dli9frvXr1+vSpUu699571bJlSzVv3lx+fn52h2iJzPBo7o0ytRBiamH7aj/++KPCw8P19ddf6+TJkypatKhatGihoKAgx4zj12LShdJVq1alq71T1j6S/n/tm2XLliWufVOqVCk1atRIISEh+uyzzxIXUHeKF198Ua+//rrj10r4r4iIiMRjes+ePfL19VXNmjUVGBioGjVqqEGDBpo9e7bj+vu/IiIiEp8QKFq0qGOm+LsZTloTJkFMTIxWrFihH3/8USdOnJDL5VKRIkVUpUoVNW/e3HH5fvPNN3rrrbd07tw5vfzyywoODk48bzty5IhGjhypdevWqXHjxho6dGjiuinI3C5duqSVK1dq+/btioiIkCQVL15c1apVU9OmTVNd9yyzCQgI0Jdffpn4e8ztdqtixYpauHBhkllXnLbG12OPPaaqVavq9ddfl3SlMPLaa6/p5ZdfVvfu3RPbffLJJ4k3Lt1Krr/yoEEGDRqUapscOXKoc+fO6tOnjwURWePpp5/WwIEDVaxYMXXu3DnZH+CLFy9qxowZWrRokd577z2bosx4p0+fTlw0OcEPP/yggIAAx52EXM20OaQTHD58WHfddVeq7cqVK5fuaXZuZdu3b9djjz2WZNvMmTN14sQJjRw5Uu3atdPJkyfVqVMnTZkyRePGjbMn0Ay2YcMGnT17NvG12+3WRx99pLp16yYphMTGxuqff/6xI0Svy5Ytm5o2baqmTZsqJiZGq1at0vLly/X+++/rvffeU40aNTRjxgy7w8wwmfnRXCscPHjQMYWgdevWqVOnTtct5rtcLj355JMKCQlxZCGkcuXKqly5soYOHarNmzcrPDxcCxYs0MyZM3XnnXcqKCjIMXecpXShtE+fPokXSgMCAhxVBJGUrt8aTppCZtiwYVq9erWio6NVuHBhtWvXTkFBQapUqZLOnj2rWbNm2R2iV/z+++9q1qyZXn75ZT3zzDPGrPPVoEEDSVfWghg2bJiaNWuWOK3f1edxTle8eHGKH3L2VIebN29W3759FRUVpSxZsiTOuhAVFaVFixZp7NixGjdunKOKfo0bN9ZDDz2kDz/8UKNGjVJoaKiGDRumrVu3auLEiSpSpIgmT56s+vXr2x1qhjtw4IBy5syZZLqkmTNnJmmTO3duPfHEE1aH5lXbt29Xv379Egsg+fLlk3TlxrT58+frww8/1Pvvv6+qVavaGWaGutZzBSY8a/DPP/8kuYbetGlTDRs2LFnfVqtWTVOnTrU6vFRRCPnXtm3bUnzP7Xbr2LFjWr16tSZOnKjChQs75lHVli1b6ueff9b48eP12WefqUaNGolz9yXM7XfmzBkFBwcrMDDQ5mgzzvr169WrV6/E1263W8HBwckqt07TunVru0OwRfbs2XXu3LlU250/f95RdykcPXo02d3Ba9asUdmyZdWuXTtJUuHChdW5c2eNHz/ejhAtY8IJSUpy586t1q1b64EHHlBISIi+/PJLbd682e6wMsx/H80dMGCAfvvtt2s+mvvpp5/eco/m3qhq1apdd32QU6dO6auvvlJYWJh+/vlnx1woNbWwfS0+Pj6qXbu2ateurREjRuj999/X3Llz9dFHHzmmEGLqhdKUFtR1uoULF8rlcumhhx7Sm2++6Zg1nVKzYsUKffLJJxo9erSWLl2qkSNHOvrprgT58uXTmTNndPDgQe3evVv33HOPMesbSVeeTJ4zZ462bdumyMhISVfWjKhevbqCg4OTPMnvZNea6tBJF4gjIiLUu3dvlShRQqNHj1atWrUSf29eunRJmzZt0gcffKBevXopPDzcUWsN5MqVS0OHDlWrVq3Up08fPfXUU3K5XHr++efVs2dPZc+e3e4QM9z69evVo0cPTZkyJbEv3W63Ro8enaSdy+VS8eLF9fDDD9sRZobbu3evunXrppIlS+r9999XgwYNEmfTiYmJ0bp16zR58mR169ZNCxcu1J133mlzxLgZFy5cSPI7NOFGw//eVJ4jR47EmxJvJRRC/pU3b97rvl+gQAHdc889iomJ0bx58xxTCJGuTHv10EMPKSQkRN9++60uXbok6codxZUrV9azzz6rhg0b2hxlxjK1cmuq8uXLa+3atanecbJmzRqVL1/emqAscPnyZeXIkSPxdXR0tPbt25dsirBSpUrp5MmTVocHC0RGRmrFihUKCwvTrl27lC1bNj3yyCNq2bKl3aFlmNmzZ+vpp59O9dHcwoULKzw83DGFkGstrnjhwgWtXr1a4eHh2rRpk9xutwICAhy1boKphe2U/PbbbwoPD9eKFSsS5yRu1qyZ3WFlGFMvlKa1AHDmzBnt3bvXMQWDQYMGKSwsTN99950eeeQRPfjggwoKClLTpk0d/ZREjhw51K9fP7Vq1UojRoxQu3bt9Mwzz6hLly7KmjVrsvZOWcPvu+++08aNGxUWFqawsDAtWLBAxYoVU/PmzdO0yHJmNmvWrMSF0O+5557E9TqPHDmiJUuWaMmSJerXr586depkY5TeY9JUh3PmzFGePHk0d+7cxDvkE2TLlk3169dX5cqV9dhjj2nu3Ll65ZVXbIrUO6KiojR37lwdPnxYpUuX1j///KNffvlFx44dc8zTyldbtGiR6tWrd80Cx6JFixJvuh0xYoQWLlzomELIxIkTVaZMGX3xxRdJrj9IV27KCwwMVKNGjRQcHKwJEyZozJgxNkUKb8os52oUQtKpVq1amjNnjt1hZLhGjRqpUaNGcrvdOn36tCSpYMGCjjoJgdSxY8cU38uaNasKFSqk6tWrq2XLlo66Q6Nt27YaNmyYKleunOJTMaGhoVq8eLHeeusti6PzntKlS+unn35SrVq1JEkbN26UpMTXCaKiopKdmCPzOnPmjFauXKnw8HDt2LFDLpdLNWrU0DvvvKNHHnnEcWtdZfZHc2/Wf6eSuHjxoooUKSK3260xY8aoefPmdoeYoUwtbF9t//79Cg8PV3h4uP755x/lypVLTZo0UWBgoGrVqiUfHx+7Q8wwJl8oTYvvv/9eL7/8smOe+OrUqZM6deqkAwcOKCwsTOHh4Xrttdf05ptvqnr16nK5XIqPj7c7TK+56667NGfOHH3yySf65JNPFBIScs12TunvLFmyqH79+qpfv36SQv5nn32mmTNnyuVy6auvvlKJEiV0++232x1uhlm/fr3efffdxLvkE2ZjSHD06FF9/PHHGj16tMqVK6e6devaFGnGMnWqw82bN6t9+/bX/a2VP39+tW/fXqtWrXJUIWTJkiWJ06u/8847atOmjTZt2qQ33nhDgYGB6t69u7p163bNgm9m9dNPP6l///6ptqtTp45GjhxpQUTW+P777zV48OBkRZCr5cyZU507dzZiuvbMUhC4Gf369Ut2zbBv375JbkSLjY21Oqw0oRCSTrGxscqSxTn/2f67uI+vr2+SOfRN4/QBK0+ePCnm6Ha7tXfvXq1YsUIzZ87U7NmzVbhwYYsj9I7WrVtrw4YNGjx4sObMmaO6deuqZMmScrlcOnLkiDZu3Khff/1VzZs3V6tWrewON8O0bds28W6LIkWKaNKkSSpcuHCyO0+2bNniuMdT9+3bl/hDKmE9oH379iVr4yRhYWFavny5vvvuO12+fFn33XefBg0apObNmzt6XM/sj+beqKunkjh9+rQKFCigli1bKigoSHfffbdq1KghPz8/u8PMcKYWtiMjI7V8+XKFh4dr165dypIli+rVq6e+ffuqYcOGjn36xdQLpaYrU6aMevfurd69e2vnzp2JTz15PB717NlTTZs2VatWrVSjRg27Q81QbrdbM2bM0PTp03XnnXeqU6dOjrpAeD05c+ZUy5Yt1bJlS50+fVorVqzQ8uXL9cUXX2jevHmqWrXqNZ+EzIxmzpypJk2a6N13373m+yVKlNCoUaMUExOj6dOnO6YQYupUhwcPHlTFihVTbVexYkVHrd/XoUMHbd++XW3atFH//v0Tn2R76KGHFBYWpsmTJ2vy5MkKDw/X8OHDHTOenzp1KtnC776+vhowYECS7QUKFNCpU6esDs9roqOj07TWUfHixRUdHW1BRNbJzAWBG3Wt32ApjXO34powzrmib5GlS5c6ag0Jk6eDSsuAJV0pjixbtszK0Lxm4sSJqbY5dOiQOnbsqA8//NBRF5HGjh2rqlWratasWZo8eXKS90qXLq3XXntNTz/9tE3RecfTTz+tvXv3asKECYqLi1PJkiU1duzYZNNlLV26VM8//7yNkWa8a00F1L9//ySFQI/H46jiZ//+/VW2bFn16NFDQUFBKl26dIptt2zZ4pgfHClxUt9eS3BwcOLTPs8995xq166deKOGky8omFrYrl+/vlwul6pVq6Y333xTjz76aIrTul64cCFZIdAJTLpQiv93//336/7779fgwYP1/fffa9myZfrmm28UGhrqmCcjpCvF7REjRujvv/9W9+7d9fzzzxtTBPmvggULKjg4WMHBwTpy5Eji00FO8euvvyZOi3U9jz/+uPr162dBRNYwdarDc+fOpToNu3Rlqva0TP2ZWURFRWnOnDnXvAiaLVs29enTR0FBQRoxYoQ6derkmPE8d+7cioqKSra9c+fOSV5HRUUl3rzlBMWLF9euXbv04IMPXrfd77//nqaCSWaR2QsCNyqzP9VDIeRfq1atSvE9t9utEydOaM2aNdq2bZumTZtmYWTwhvQMWKa5/fbb1bNnT3388cd2h5LhEn5URUZGJlmU0EmL0l3N19dXI0aM0KBBg3T+/Plr/tjIlSuXvv76a0dNl/TZZ5/ZHYItrp539lp27dqlZcuWacWKFTp27JhjfnBIZt6Jc88992jPnj3atm2bfH19dfr0aTVu3NhRx3JKTCxsDxgwQM2bN0/x79V/p0j78ccfLY7QWk6/UIrkXC6XatWqpVq1aumNN97Qt99+a3dIGWbo0KFasmSJqlWrpvHjx6tMmTJ2h3TLKFmypLp3755kza/MLi4u7rrTxyTInj274uLiLIjIGqZOdRgfH5/mm3OcdJPqkiVLUp1JpWzZsgoJCdHSpUstisr7/P39tW7dOjVu3Pi67dauXft/7d17XFVlugfw3xYMUxTFkdJCabAk70iYOBXJNNaoiDoyUlreO1pZaZeBDmZeCC0lEbpMllJpZaYVIGUTTqVp0kWxi51RSyWFVDTAywFEzh/EPhvYqNXee7nW7/f9fOYzufdOn5WL93n387zvuyx1hOtNN92EZ599Ftdff32jOWzfvn14/vnnERMT49ng3MjsDQFWtmorjba/Q0hIyFnfb9KkCXr06IFp06bZH2ZmBSEhIVi2bBm6du16Xp+3ysP55Ow+/fRTTJo0CV9//bXRoYjI71BQUGB/lsD3339vP2Zm2LBh+POf/2x0eC7xax8EbqUJ6+7du5GZmYl169bhwIEDaNasGSIjIzFgwAAkJCTg5ZdfRnh4uNFhuhVLY7sxjkek/fzzz/D398eQIUN+9c+FmNP69est9YyQsyktLcXevXvRpk0byz1gt1+/fvjHP/7R6HF/LA4ePAibzdbgWJnCwkJUV1c3eJaGWY0YMQIRERHnfI7AE088gU8//RRr1671UGSe43jU4ebNm+3H2N56662YMGGCpY46DAkJQceOHc/5/M3y8nIUFBRQjOdWlpmZiYSEBCQlJTW6M/mdd97BI488gvnz5yM6OtqzAbpJaWkpYmNjUVRUhGHDhmHAgAH2sbywsBAffvgh3n77bVx66aVYvXr1ee2SEvMwW/5WI+QXBw4caPQ9b29vtG7d2lIPj64VEhLyq44PUWLmsHr1aixZsgQbN240OhS3MNtA7Sqs183m6NGjePfdd5GVlYX8/HwANTvevv76a7z44ovo37+/wRGKO9QWxNevX4+jR4/CZrPhpptuwh133GH5ZgibXbt22R84W1hYiKZNm6KyshIJCQkYPXq05R4064glj51vYeT48eMoKiqy1Pw8JycH//rXv3D69GnccsstGDx4MJ555hk899xz9uc8/elPf8KSJUssc6zIsWPH0KZNG5w4cQI5OTnYtm0bjhw5ApvNhj/84Q/o06cPBg0aZMkj7xyFhITA29u7wUKsbt26obq6Gt9++61BkbnWihUrsGDBAsydO7fRQunbb7+NmTNnIj4+HqNHj/ZsgB7meNThtm3bYLPZLHXUIfOCHUcs+RsAHnjgAaxbtw49e/bEn/70J7Rv3x42mw1FRUX45JNPkJ+fj8GDB5/XEXlmcuTIETz22GPIzc11+v5NN92EWbNmWfrZlUz3uSOz5W81Qn4DK50rHxISgqlTp571LHlHVl2pxDpgOXPgwAHcfvvt6N+/v6WeEeLIbAO1q7Bc9x133HHen7XZbHjppZfcGI3nZGZm2lfWnT59GldddRWGDBmCIUOGwNfXF3379sUrr7yiorjFVVVVYdOmTcjOzkZubi5OnTqFDh06NPqlxOxY8ndRUZG9+fGf//wHXl5e6NevH4YMGYJrr70WAwYMoPj5Zslj8fHxv+q7hlUKZ2+++SYSExNx9dVXo0WLFti2bRvGjh2LV155BaNGjUJwcDD+85//YPXq1Zg8eTLuu+8+o0N2mS1btmD69On4+eef7YvwgJpz5E+fPo22bdti8eLFlv4ZT0tLQ5MmTXD33XfXeT09PR0AcM899xgRlsudOXMG99xzDzZs2IA//vGPiIyMtOeqgwcPYuPGjdizZw+ioqKQnp5umbrD+XA86jArK8vocMSFWPJ3rZUrVyIjIwMFBQV1Xg8MDMS4ceMs3eA8ePAg8vLycOjQIQA1O7bDw8MtMyc/G7b7vJbZ8reeEfIrVFRU4K233sKyZcuwfv16o8NxmQEDBqBnz55Gh2GoqKgopwPWTTfdZKkBa8qUKY2+d+bMGRw5cgT/8z//g8DAQEyfPt2DkXnW3XffjSZNmjR4ferUqQZE4zks1+3r63vOL43FxcXYvn27pb5cPvzww7DZbOjfvz/i4+Nx5ZVX2t+z8sOz62MpjDfGy8sLkZGRiIyMxP/+7//igw8+sPSzE1jy94ABAwDUfJFKTEzEX//6V/tzn5h+vlny2Pz5840OwRCvvPIKbrvtNjz66KMAahojM2fOxP3331/nGRFt27ZFdna2ZRohRUVFmDZtGtq3b48FCxYgIiLC/oyriooKbN68GQsXLsRdd92F7Oxsyx4BOG3aNKevX2gFlN+rSZMmePrpp/HKK6/g5ZdfxvLly+u8f/nll+ORRx7BmDFjLDVPPR9WfCaM1GDJ37Vqn2NWVFRkbwgEBARY6kHhjenQoUOju92sju0+r2W2/K0dIQ5+/PFH5OTkoLCwEIGBgRg+fDjatGmD8vJyvPLKK8jIyMCRI0cQFhaGlStXGh2uS4SEhOCNN96gb4SYrYP5W91+++2Nvuft7Q1/f3+Eh4cjJibG8tvvhdPhw4fxwgsvYNWqVWjatCnGjBljmULK1KlTsWnTJlRWVqJTp06Ijo7GkCFDEBQUhLKyMoSHh2vFuIUK41KDJX9fe+21KCkpgZ+fH26++WZER0fbf5aZfr7F2kJDQ/HMM88gIiICwP/f2ytWrMA111xj/9zWrVsxefJk7Nixw6hQXWrhwoXIzs5GZmYmWrVq5fQzJSUliImJwdChQzFjxgwPRyjuVFRUVOdZV1YtlFZWVqK8vBy+vr51Xj98+DCWLVuGPXv2oF27drj11lvRvXt3g6J0P/YFO2Jt7Ec8ijloR8gvtm/fjvHjx+PUqVP211599VWkpaXh/vvvx759+9CnTx88+eST9sm5WIfZOpi/lVXOWhX5tX766ScsXboUb775Jpo1a4Y777wTd9xxR4MvY2b27LPPoqSkBO+99x6ys7Px9NNP4+mnn0a3bt0QFRVFs6qQZSVObaH/fNhstgaNAqtgyd+ffPIJNm3ahKysLGRlZWH16tW45JJLMGjQIERGRhodnrgZS+Hs1KlTaNGihf3Xtc8AqV84adasmf15IVawZcsWxMXFNdoEAQA/Pz/ExcXh/fffVyPEYi699FLLNj8czZ8/H5s2bapzssaxY8cwfPhwHDlyBH5+fjh+/DiysrKwatUqXH311QZG6z4sO1mlBkv+Bs5+xOOaNWuQkpJi+SMexRzUCPlFWloa2rVrhwULFqBr16748ccfMXv2bNx2223w9vZGWloa/vKXvxgdpsslJycjMDDQ6DBERNyisLAQzz33HN566y34+vrirrvuwujRo+sUWqzEz88Po0aNwqhRo/DTTz8hKysL69atw5IlSwAAixYtQlxcHAYOHGiZh8zWx1IYT09Ph4+PD3x8fHCuzb1WboSw8Pb2xo033ogbb7wRp06dwr/+9S9kZ2fbj1Wx2Wx499130b59e1x++eVGhysuxl44s3ojv6Cg4LxWwHfv3h3Lli3zQETGYN3RyVIo/fzzzxETE1PnteXLl+PIkSOYO3cuYmNjUVxcjHHjxuGf//wnFi9ebEygbsayYEdqsORvHfHIzWz5W42QX3z33XdISEhAaGgoACA4OBizZ8/GX//6V8ydO9eSTRAAGDJkCMrLyxu8Xn+LalxcHHr06GFAhOJOLBPv+sw2ULsK03UXFBTgn//8J95++220bt0aM2bMQFxcHJo1a2Z0aB5zySWXYNKkSZg0aRL27NmDzMxM5OTkID4+HnPmzMGXX35pdIjyO1xyySUoLi5GWFgYoqOjERUVRXV/M7v44osxdOhQDB06FMeOHUNOTg7WrVuH1157Da+//jrCwsIsuwOUKY85YiqcPfjgg/Dx8anz2vTp0+0FFQBOv7uY2fHjx9GyZctzfq5ly5Y4fvy4ByIyxrBhw+Dl5dXg9ZiYmHM2/M2MpVBaWFjYYJdHbm4urrjiCsTGxgKoef7PhAkTkJaWZkSIHsGyYKc+5e+6rJa/V6xYAV9fX6xcubLB7saLLroIN954I0JDQxETE4OVK1dadmcj631utvytRsgviouLG+yMqP11ly5djAjJI7RFtQbrgMUy8a7PbAO1q7Bcd3x8PLKzs9GuXTskJCQgNja2TgHFqt577z2EhYWhXbt2Dd4LDg7G9OnTMX36dGzbtg3r1q0zIEJxpY8++giff/45srOzMXfuXCQmJuLPf/4zhgwZguuuu87pz7oVsebvWm3atLE/kPPgwYPIyspCdna20WG5DUseq4+lcDZ8+PAGrzW2UyIsLMzd4XjMmTNnznvXi5Xv8/nz5zt9/fHHH/dwJJ7FUiitrKyss2CjtLQU33//PeLi4up8LjAwEMXFxZ4OT9xM+bsuq+VvHfFYg/U+N1v+1sPSf+HsoeFVVVXo1q0b1q5di65duxoYnfvExMTg5ptvxl133WV/LSUlBc8//3yDLarBwcGW3aIaHx8PLy8vJCUl1Xn9kUceQXV1NZKTkw2KzL1YHjIrXEJCQgAAnTp1OmcDxGazITMz0xNhuV1ISAhsNhsuv/xy9OnTB2FhYQgLC0NwcLDRoXkUY2G8qqoKmzZtwrp165Cbm4umTZvi5ptvRmxsrKUfOArw5m8RsY6QkBB07NixwU6Y+srLy1FQUICdO3d6KDIR14mJicEtt9xib/Dk5OTggQceQGpqKgYOHGj/3AcffIDZs2dj48aNRoUqIr9S3759kZKSguuuu+6sn9u0aRNmzJiBvLw8D0Um0pB2hDhwthUbaLgd20qFM21RrWG2DqarsKxQEC7Dhg2z/Hnizrz11lv44osvsG3bNuTl5eGdd96BzWZDq1atEBoairCwMPTp0wc9evSw9A4ZxpU4Xl5eiIyMRGRkJMrLy5GamoqMjAwUFxf/qoeqmxFr/mY92lLEipzthGmMlXbC1FdZWYk333wTX331FYqKivDoo48iKCgIOTk56NKlC93CDqsZOXIkFi1aBAD4wx/+gGeffRZt27bFDTfcUOdzW7duxR//+EcjQvQIxgU7Yn064pGb2fK3GiG/aGwCavWVlNqiKozMNlC7Cst1N1YYtbqrr74aV199NcaMGQOg5qF1X375pf1/ixcvxpkzZ9C0aVP06NEDK1euNDhi92AtjO/Zswfr1q3DunXr8OOPPyIiIgIjR440OixxE9ajLVnyWH2shTOWhp92rtU8223cuHE4duwYunbtii+++AInTpwAAHz22WfYuHGj/juZ3G233YY9e/bg6aefxunTp9GhQwekpKQ0qEW88847uPPOOw2M1L0YF+wAyt9Wz9864rEG431uxvytRsgvLrS/GE/p2LEjtm/fjoiICAA1W9UA2H9d6+effz7reX9mxzhgsTLjQO0KrNfN7NJLL8WgQYMwaNAgVFVV4bPPPkNGRgY++ugjPSjdIg4cOIB169YhOzsbu3btQu/evXHHHXfglltuQdu2bY0OzyNY8zfLmfKOmPMYa+GMteHHaN68efD398fq1avRqlWrOosRw8PDkZKSYmB07sVSKPXy8sJjjz2G+Ph4nDx5Ev7+/g0+07x5c6xfvx6+vr4GROgZjAt2lL858ndjJ+w4Ki8v91A0nsd6n5sxf6sRQk5bVHkHLIBn4u3IjAO1K7BeN8CzotRRaWkptm3bZt8N8vXXX6OyshJdunTB6NGjERoaanSIbsNSGI+Li0N+fj5CQkIwdOhQDB48uME9bnXM+ZvxaEvmPMZYOAM4G34A57wlLy8PixYtgr+/P6qqquq8165dOxw+fNigyNyPqVAKAM2aNauzC8SRt7c32rRp4+GIxN2UvxuyWv7WEY+897kZ87caIY1gmYBqiyrvgAXwTbwBcw7UrsB63QDPitK33nrL3vzYs2cPWrdujd69e+P666/Hvffeix49ejT6xdMqmArj27dvR/PmzXH69Gm88847eOeddxr9rJWebeaIOX8zYs5jrBgbfgDPvMWRl5dXo989jhw5gubNm3s4Is9hKZTWx1JvqY9lwY4j5W/rs8r3q9+D9T43Y/5WI6QRLBNQbVHlHbAAzom3GQdqV2C9boBnRWlCQgIuvvhijBgxAqmpqZb8InUuTIXxYcOGnfdZvFbFnL8ZMecxxsIZM5Z5i6Pw8HAsX74cN9xwg/3abTYbqqur8cYbbzQ4tlnMj6Xe4ohpwY4j5W/lbwas97kZ87caIY1gm4Ayb1FlHbBYmXGgdgXW6wZ4VpSOGzcO27Ztw6pVq7B27Vp0794doaGh6NOnD3r37o3WrVsbHaLbMRXGG2tkM2HO34xHW7LmMdbCGTOWeYujBx98ELfeeisGDx6MqKgo2Gw2rFy5Ert27cK+ffuwevVqo0N0G9ZCKVu9BeBasONI+ZsvfzPu+GK9z82Yv9UIaQTjBBTQgMU0YAGcE28zDtSuwHrdTOLj4wHUPIRux44d9mOyVq1ahdLSUnTq1MneGAkNDUXnzp0Njtj1mAvjjJjzN+PRlqx5jLVwBnA2/FgFBwdjzZo1SE9PR3Z2Nry8vPDhhx8iIiICCxcuRMeOHY0O0S2YC6WM9RamBTuOlL/58jfjji/W+9yM+VuNEKlDAxbPgMU68TbjQO0KrNfNyMfHB+Hh4QgPD7e/tmfPHnz55ZfIzc3FrFmzAMCS4zlzYZxxIQNr/gY4j7ZkzWOshTOAs+HHLDAwEAsWLDA6DI9iLpQyYl2wo/zNl78Zd3yx3ueA+fK3GiFShwYsngGLeeJttoHaVVivm3lFaW0DpPZ/+/btAwC0atXK4Mjcg7kwzriQgTV/M2PMY6yFM4Cz4QdwzluOHz+OkydPIiAgoMF7hw4dQosWLdCiRQsDInMv5kIpI+YFO8rfdVk9fzPu+AI473Mz5m81QhrBOAEFNGAxYZ14m3GgdgXW6wZ4VpRWVFRgx44d9qbHtm3bUFpaat8N0KdPH4wbNw59+vTBVVddZXS4bsFcGGdcyABw5m+A82hL1jzGXDhjxTJvcZSYmIgWLVogKSmpwXtpaWk4efIkFi1aZEBk7sVcKGWst7Au2FH+Vv5mwHqfmzF/qxHSCMYJKCvWAYt14m3GgdoVWK8b4FlR2qdPH1RVVaFJkya46qqrMGTIEISFhSEsLAyXXHKJ0eF5DGthnHEhA2v+Zj3akjWPsRbOAM6GH8Azb3H0+eef24/urC8yMhKzZ8/2cESewVwoZay3sC7YUf7my9+MWO9zM+ZvNUIawTgBZcU6YLFOvM04ULsC63UzufPOO9GnTx/07t0bvr6+RodjCNbCOCvW/M16tCVrHmMtnLE2/FiVlJQ0mp8vvvhi/Pzzz54NyEOYC6Ws9RbGBTvK31z5G+Dc8cV6n5sxf6sRInVowKrLygMW68TbjAO1K7BeN8CzovTee+81OgTDsRbGWbHmb9ajLZnzGGPhjLXhB/DMWxwFBgZi8+bN6N+/f4P3tmzZgssuu8yAqNyPuVDKiHXBjvI3V/4GOHd8sd7nZszfDQ+TFgA1E9DXXnsNjzzyCCZMmIC9e/cCAHJycrBnzx5jg3OjYcOGISYmpsHrMTExTl+3AtYBq3biHRoaWmfi3bFjR6xevdqyE+/agdqZC3WgdgXW6y4oKMAtt9yCJ598Evv378eWLVvqrCh94YUXDI7QfQ4ePIjCwsIGrxcWFuLgwYMGROR+n3/+OW688Uan70VGRiIvL8+zAXlQSEhInUJhrW7duqFr164GROR+rPmb9WhL1jx2/PhxHDp0yOl7hw4dsuc0q8nLy8PUqVPh7+8Pm81W5z0rN/xY5y2xsbHIyMjA0qVLcfToUQDA0aNH8cILLyAjIwN///vfDY7QfWoLpZs2bcLXX3+NTz75hKIJwlhvSUxMRGpqqtP30tLS8Oijj3o4Is9Q/m7IyvkbqNnx5Wxh2uOPP27Z3Zys97kZ87d2hDjBvBWbcYuqGTuYrsK4QiE2NhaLFi2Cn58f/va3v8Hf3x9Hjx7F2rVrkZGRgRkzZhgdoluwXjfzitKoqCinO/xuuukmy+7wYy2MA5wrr1jzN+vRlqx5jHWnG2vDj3XeMm7cOOzfvx8pKSlISUmBl5eXfcdbXFwcJkyYYHCE7sG6Q4C13sK6k1X5myt/s2K9z82Yv9UIcYJ1AsqKdcBinXibcaB2BdbrZj1CBgDuvvtue5HU0dSpUw2IxjNYC+MA50IG1vzNerQlax5jLZyxNvxY5y02mw2zZs3C2LFjsWXLFpSUlKB169bo168fgoKCjA7PbVgLpaz1FtYFO8rfDVk5fwOcRzyy3udmzN9qhDjBOgEFNGAxDVisE28zDtSuwHrdrCtKAWDatGlOX7/nnns8HInnsBbGWbHmb9Yz5VnzGGvhjLXhxzxvAYCgoCBL/zzXx1ooZa23sC7YUf5uyMr5m3XHF+t9XstM+VuNECdYJ6AasLgGLNaJdy0zDdSuxHbdrCtKWbEWxgHOhQys+RvgPNqyFlseYy2csTb8mOctVVVVyM/PR1FRESoqKhq8P2zYMM8H5WashVLWegv7gh3l7/9n5fzNuuOrFtt9Dpgvf6sR4gTrBFQDFteAxTrxBsw3ULsK43WzrihlxVoYZ13IUIstf7MebQlw5jHmwhljw4913vLNN99g2rRpKCwsdFogt9lslvz5Zi2UstZbmBfsKH/z5G/WHV8A531uxvytRogTrBNQDVhcAxbrxNuMA7UrsF4364pSAAgJCXH6sPRu3bpZ9mHptdgK48wLGRjzN+vRlqx5jLVwxtrwY523PPbYY/D19cVLL72Ezp07o2nTpkaH5BGshVLWegvrgh3lb678zbrji/U+N2P+ViPECdYJqAYsrgGLdeJtxoHaFVivG+BcUQrUFIC9vLwavB4TE9PoWG8FjIVx1oUMrPmb9WhL1jzGWjhjbfgBnPOW3bt3Y/Hixejbt6/RoXgUa6GUtd5Si23BjvI3V/5m3fHFep+bMX+rEdIIxgmoBiyuAYt14m3GgdoVWK+bdUUpAMyfP9/p648//riHI/Ec1sI460IG1vzNerQlax6rxVY4Y234sc5bgoKC7Ec6MmEtlAKc9RaAc8GO8jdX/mbd8cV6n5sxf6sR4gTrBFQDFteAxTrxNuNA7Qqs1828opQRa2GcdSEDa/5mPdqSNY8BnIUz1oYf67wlISEBSUlJ6NKlC4KDg40Ox+PYCqWs9RbWBTvK31z5m3XHF+t9bsb8rUaIE6wTUA1YnNgm3mYcqF2B9bpZV5QCQGVlJd5880189dVXKCoqwqOPPoqgoCDk5ORY9j5gLYyzLmRgzd+sR1uy5jHWwhlrw4913jJ37lwcPnwY0dHRCAgIQMuWLeu8b7PZkJmZaVB07sVYKGWtt7Au2FH+5srfAOeOL9b73Iz5W40QJ1gnoIAGLKYBC+CceJtxoHYF1utmXVFaUFCAcePG4dixY+jatSu++OILe8H4s88+w8aNG5GcnGxwlK7HWhhnXcjAmr9Zj7ZkzWOshTPWhh/rvKVbt26w2WxGh+FxrIVS1noL64Id5W+u/M2644v1Pjdj/lYjxAnWCagGLK4Bi3XibcaB2hVYr5t1Rem8efPg7++P1atXo1WrVujevbv9vfDwcKSkpBgYnfuwFsYBzoUMrPmb9WhL1jzGWjhjbfixzlsae66Z1bEWSlnrLawLdpS/ufI3644v1vvcjPlbjRAnWCegGrC4sE68zThQuwLrdbOuKM3Ly8OiRYvg7+9vLxzVateuHQ4fPmxQZO7FWhhnXcjAmr9rsR1tyZrHWAtnrA0/1nkLK9ZCKWu9hXXBjvI3F9YdX6z3uRmpEeIE6wRUAxYX1om3cGFdUerl5eV0pxcAHDlyBM2bN/dwRJ7BWhhnXcjAmr8BzqMtWbEWzmqxNfxY5y0AUFpaivXr1+OHH35wOq4lJiYaEJV7sRZKWestrAt2WLHmb9YdX8zMlr/VCHGCdQKqAYsL68QbMN9A7SqM1826ojQ8PBzLly/HDTfcgCZNmgCo+W9RXV2NN954AxEREQZH6B6shXHWhQysWI+2BDjzGHPhjLHhxzpv2bt3L+Li4lBRUYFTp07B398fJSUlOH36NPz8/ODr62vJn2/WQilrvYV1wQ6g/M2Uv1l3fAGc97kZ87caIU6wTkA1YHENWKwTbzMO1K7Aet212FaUPvjgg7j11lsxePBgREVFwWazYeXKldi1axf27duH1atXGx2iuBDzQgbG/M16tCVrHmMtnDE3/AC+ecv8+fPRq1cvpKamonfv3nj++ecREhKCnJwcPPXUU0hNTTU6RLdgLZSy1ltYF+wof3Nh3fHFep+bMX+rEXIWbBNQDVhcAxbrxNuMA7UrsF43wLmiNDg4GGvWrEF6ejqys7Ph5eWFDz/8EBEREVi4cCE6duxodIhuw1gYZ13IwJq/WY+2ZM1jrIUz1oYfwDlv2bFjB5KSknDRRRcBACorK+Hl5YXo6GgcO3YM8+bNw+uvv25wlK7HWiitxVZvYaX8zYV1xxfrfW7G/K1GSCMYJ6AasLgGLNaJtxkHaldgvW7mFaWBgYFYsGCB0WF4FGthnHUhA2v+Zj3akjWPsWJt+LHOWyoqKuDr64smTZrAz88Phw4dsr935ZVX4rvvvjMwOvdhLZQCnPUWgHPBjvI3F9YdX6z3uRnztxohTrBOQDVgcQ1YrBNvMw7UrsB63awrSo8fP46TJ08iICCgwXuHDh1CixYtGj1KycxYC+OsCxlY8zfr0ZaseQzgLJyxNvxY5y1BQUE4cOAAwsPD0bVrV7z66qvo378/vL29sWrVKqfzGTEv1noL64Id5W+u/F2LbccX631uxvytRogTrBPQWhqwOAYsVmYcqF2B9bpZV5QmJiaiRYsWSEpKavBeWloaTp48iUWLFhkQmXuxFsZZFzKw5m/Woy1Z8xhr4Yy14cc6bxk8eLB9zL7vvvswceJE9O3bFzabDdXV1ZZewMVYKGWtt7Au2FH+5srfAOeOL9b73Iz5W40QJ1gnoIAGLKYBC+CceJtxoHYF1utmXVH6+eefY9asWU7fi4yMxOzZsz0ckWewFsZrsS1kYM3frEdbsuYx1sIZc8OPcd4yfvx4+z/37t0b2dnZ+Pjjj1FeXo5+/frhqquuMjA692EtlLLWW1gX7Ch/c+Vv1h1frPe5GfO3GiFOsE5ANWBxDVisE28zDtSuwHrdrCtKS0pKGj366uKLL8bPP//s2YA8hLUwDnAuZGDN31a9rnNhzWOshTPWhh/rvKW+9u3bY9SoUUaH4XashVLWegvrgh3lb678zbrji/U+r88M+VuNECdYJ6AasLgGLNaJd31mGKjdgeW6WVeUBgYGYvPmzejfv3+D97Zs2YLLLrvMgKjcj7UwzrqQgTV/Sw2WPMZaOLPqeH0urPMWgLOhz1ooZa23MC/YcaT8be38zbrjqz6W+xwwX/5WI8QJ1gmoBqwaLAMW68QbMN9A7SqM1826ojQ2NhaLFi2Cn58f/va3v8Hf3x9Hjx7F2rVrkZGRgRkzZhgdoluwFsZZFzLUx5K/Ac6jLQHOPKbCGRfWeQtrQ5+1UMpab2FdsAMofzPlb9YdXwDnfW7G/K1GiBOsE1ANWFwDFuvE24wDtSuwXreVv1Cczbhx47B//36kpKQgJSUFXl5eqKqqAgDExcVhwoQJBkfoGSyFceaFDIz5m/VoS9Y8xlw4Y2z4Wfnv82xYG/qshVLWegvrgh3lb678zbrji/U+N2P+tlU7+xsSSnl5eUhKSkJKSooGLAc2mw07d+40IDL3GjlyJMaMGYNhw4Zh/PjxqK6uRnp6Ory9vREfH49vv/0W77//vtFhulxsbCzKy8uRmJjY6EBdf1WSFbBeN7u9e/diy5YtKCkpQevWrdGvXz/LP0ybsTA+fPhwTJ48GYMGDTI6FI9izd9TpkxBdXW1/WjLNWvW1DnacsmSJejevbvRYbqc8liNwsJCisLZ+TT8cnNzjQ5TXCQ0NBSLFy9GZGSk0aF41PLly/HTTz8hPj4e27dvx8SJE3Hq1Kk6hdKhQ4caHabI76L8XYMlf0dHR+Pw4cMoLS2l2vHFep+bMX9rR4jYsW5RNWMH0xVYVyiwrpxmvW6Ac0VpraCgIMs3PhyxrsRhXXnFmr9Zj7ZkzmOOWHa6MT/LjnHewnoyAesOAWaMC3aUv2uw5G/WHV+s97kZ87caIY1gnIBqwOIasFgn3mYcqF2B9bpZj5ABOL9osRbGWRcysOZv1qMtWfMYwDmeszb8WOctrA39+lgKpQBnvYV1wY7yN1f+tuqC2nNhvc/NmL/VCHGCdQKqAYsby8TbjAO1K7BeN+uKUtYvWqyFcdaFDKz5m/VMedY8xjqeszb8WOctrA19gLNQylpvYV2wo/zNlb9Zsd7nZszfaoQ4wToBZcU6YAGcE28zDtSuwHrdrCtKWb9osRbGWRcysOZv1qMtWfMY83jO2PBjnbewNvRZC6Ws9RbWBTvK31z5G+Dc8cV6n5sxf6sR4gTrBBTQgMU0YLFOvM04ULsC63Wzrihl/aLFWhhnxZq/WY+2ZM1jrOM5a8OPdd5i1b/Pc2EtlLLWW1gX7Ch/c+Vv1h1frPe5GfO3GiFOsE5ANWBxYZ14m3GgdgXW62ZdUcr6RYu1MA5wLmRgzd/1sRxtyZzHGMdz1oYf67yFFWuhlLXewrpgR/mbC+uOL9b73IzUCHGCdQKqAYsL68RbuLCuKGX9osVaGGddyGDVn9/zwXi0JSvW8bw+loYf07xl3rx5mDBhAjp06IB58+ad8/NWzGOshVLWegvzgh1GrPmbdccXE7PnbzVCnGCagDrSgMWFaeJt9oH6t2K9bkesK0pZv2hZNT+fC+tCBlZMR1sqj/GO5wBnw49p3rJhwwaMHDkSHTp0wIYNG876WZvNZsmfb9ZCKWu9hWnBjvI3b/5m2vHFep+bPX+rEeIE0wTUkQasxl1oP7iuwDTxNvtA/VuxXvfZsKwoZfqiJVwLGZS/uY62VB7jHc+ZGn5nY+V5i+PP9Ll+vq2KtVDKWm+xaoPHGeVv3vzNtOOL9T43e/62VTubWQqlkSNHYsyYMRg2bBjGjx+P6upqpKenw9vbG/Hx8fj222/x/vvvGx2mS0RFReGZZ55BSEgIoqKizvpZm82G3NxcD0XmOdHR0Th8+DBKS0upJt7Ch3FFKRMVxoFrrrkGzz77LMLDw3Httddi7ty5GDhwIABgy5YtmDp1KrZv325skC6i/A2EhoZi8eLFiIyMNDoUEbeJjY1FeXk5EhMTG2341Z+7WgXrvOXo0aN46aWXkJ+fj8OHD6Ndu3bo1asXxo4dC39/f6PDc4v4+PhzFkqTk5M9FI2IyO+3fPly/PTTT4iPj8f27dsxceJEnDp1qs6Or6FDhxodpriQ2fK3GiGNYJyAasDiwjzxNttA7SqM130+K0p37txpQGTiKiqMcy1kEGD48OGYPHkyBg0aZHQoHseYx1ixNvxY5y35+fmYNGkSzpw5g/79+6Nt27YoLi7G5s2bAQDLli1Dr169DI5SXIml3qIFOzWUv3kVFhZS7PgCOO9zM+ZvNUKcYJ2A1qcBy9oDFiszDtSuwHrdzCtKS0tLsX79evzwww9Ov2Ba9YsWI+aFDIz5Oy8vD0lJSUhJSbH80ZaOmPKYCme8DT/WecuIESPg4+ODpUuXwtfX1/56WVkZJk+ejMrKSqxZs8bACMWVmOotWrCj/H02VszfrJjuc0dmzN9qhDjBOgFlxTpgsTLjQO0KrNfNuqJ07969iIuLQ0VFBU6dOgV/f3+UlJTg9OnT8PPzg6+vryW/aAGchfH6WBYysOZv1qMtmfKYCme8DT/WeUvPnj2RmpqKAQMGNHgvNzcX06dPx44dOwyIzPVUKFW9hY3yt3NWzd8Az44vR0z3uSMz5m89LN2J3bt3Y/Hixejbt6/RoXgc44A1e/ZsdO7cudEBa86cOZYZsDTxrvn5Tk1NrfN3DdRMtidPnozp06cbFJl7sV53UFAQTpw4YXQYHjd//nz06tULqamp6N27N55//nmEhIQgJycHTz31FFJTU40O0S3qF8aDgoJQXFyMFStWYMWKFZYtjNdn5YfrOmLK345YH77JlMfM/hBKV2B9iDTrvKVTp04oLS11+l5ZWRkCAwM9HJH7sD5c1xFzvYVxwY7yN5fz2fFlxboi033uyIz5W40QJ1gnoBqwrD9gaeJtzoHaFVivOyEhAUlJSejSpQvVitIdO3YgKSkJF110EQCgsrISXl5eiI6OxrFjxzBv3jy8/vrrBkfpeqyFcYBzIQNT/nY0f/58o0MwBGseAzgLZ6wNP9Z5y0MPPYQ5c+agffv2dYrjW7duRXp6OmbOnGlgdK6lQilvvYV1wY7yN1f+fuyxx+Dr64uXXnqp0R1fVsR6n5sxf6sR4gTrBFQDVkNWG7A08TbnQO0KrNfNuqK0oqICvr6+aNKkCfz8/HDo0CH7e1deeSW+++47A6NzH9bCOOtCBqb8Lbx5jLVwxtrwY5q3REdH1/l1WVkZxo4di5YtW6JNmzY4duwYysrK0KpVKyxcuNCyx4UxFkpZ6y2sC3aUv7nyN+uOL6b73Oz5W40QJ5gmoI40YFl/wKqPZeJt9oH6t2K9bkesK0qDgoJw4MABhIeHo2vXrnj11VfRv39/eHt7Y9WqVQgICDA6RLdgLYyzLmRgyt+sR1sqj/EWzlgxzVuYrrUxrIVS5noLy4Id5W/e/M2044v1Pjd7/lYjxAmz/6X+VhqwrD9gOWKaeLP+TLNetyPWFaWDBw+27/q47777MHHiRPTt2xc2mw3V1dWW/e/CVBh3xLSQgTV/sx5tqTzGVThjbfg5smp+dobpWhvDWihlHduZFuyw/h07Ysrfjph2fLHe52bP32qEOGH2v9TfSgMWF6aJN+vPNOt1CzB+/Hj7P/fu3RvZ2dn4+OOPUV5ejn79+uGqq64yMDrXYi2MO2JayMCav1mPtlQe4yqcsTb8hBdroZR1bGdasMP6d+yIKX87YtrxpfvcnNQIETsNWFxYJ95ifVpR2lD79u0xatQoo8NwC9bCuCOmhQzK3zVYjrYUrsIZa8NP8xZerIVSJlqww4spfzvSdzO50KkR8gtNQDVgsdHEW6xKK0prVFVVIT8/H0VFRaioqGjwvlUenq3CONdCBuE62pKVCmc1WBp+mrfwYiqUstZbVGPhovyt72Zy4bNVV1dXGx3EhSAqKgrPPPMMQkJCEBUVddbP2mw25ObmeigyEff4+OOPMWfOHDz++OMNJt7//d//jZkzZ1oyMYsw+OabbzBt2jQUFhbCWZq32WzYuXOnAZGJO8THx5/zS3ZycrKHohF3GzFiBHx8fBo92rKystIyR1uyOp+faUdW/Pmu3/Br27YtiouLsXnzZgBQw09Mq36h9NChQygtLXVaKA0ICEBWVpZBkbqW6i3CQPlb5MKnRogIEdaJt3BjWVHqKDY2FuXl5UhMTETnzp3RtGnTBp+pv2tARMyhZ8+eSE1NxYABAxq8l5ubi+nTp2PHjh0GRCbiOswNP8Z5CxMVSkXEalh3fIk56WisRrBMQDVgcdHWXGHDeoTM7t27sXjx4jq7vUTEGnS0pTBgfZYd67yFiY6NqcFSbxFhoCMexUy0I8QJpq3Y2qIqIlbGuqJ0+PDhmDx5MgYNGmR0KOImWsjAS0dbCoPo6GhMmjQJMTExDd57++23sXTpUqxbt86AyNyLdd4iXJjqLSIicmFRI8QJTUBFRKyB9QiZvLw8JCUlISUlBcHBwUaHI26ghQxcdLSlsGFt+LHOW4SL6i0i1qYdX3Ih09FYTrBuxQY0YImItbAeITN37lwcPnwY0dHRCAgIaPA8EJvNhszMTIOiE1dw3HZ+ri3oYn462lIY1G/4lZWVYezYsU4bfgsXLrRkI4R13iJcmOstIlanIx7lQqdGiBOsE1ANWCJiNQ899BDmzJmD9u3bN1hRmp6ejpkzZxoYnfuoaMpHCxmsTWfKCwPlLt55i3BhrbeIMJg9ezY6d+7c6I6vOXPmaMeXGEpHYznBuhVbW1RFxAp0hIyw0VnbIiLmpXmLsGGtt4gw0BGPcqHTjpBfaCu2tqiKiDVoRamw0corERHz0rxFGKjeIsJBO77kQqdGyC80AdWAJSLWwHqEzLx58zBhwgR06NAB8+bNO+fnExMTPRCVeIIWMoiImBfrvEW4qN4iwkFHPMqFTo2QX2gCqgFLRMTMNmzYgJEjR6JDhw7nfHi2zWZTI8RCtJBBRERELmSqt4hYl3Z8iZmoEUJOA5aIiDU4Nj/O1QgRa9FCBhERERERMYJ2fImZ6GHp5OLj43/VgJWcnOzGaERExFWOHj2Kl156Cfn5+Th8+DDatWuHXr16YezYsfD39zc6PPmd9HBdERERERERkfOnRoiIiIjF5OfnY9KkSThz5gz69++Ptm3bori4GJs3bwYALFu2DL169TI4Svk9tJBBRERERERE5PypESIiImIxI0aMgI+PD5YuXVrnAdplZWWYPHkyKisrsWbNGgMjFBERERERERHxnCZGByAiIiKutXv3btx55511miAA0LJlS0yePBm7du0yKDIREREREREREc9TI0RERMRiOnXqhNLSUqfvlZWVITAw0MMRiYiIiIiIiIgYR40QERERi3nooYeQlpaGvLy8Oq9v3boV6enpePjhhw2KTERERERERETE8/SMEBEREQuIjo6u8+tDhw6htLQULVu2RJs2bXDs2DGUlZWhVatWCAgIQFZWlkGRioiIiIiIiIh4lrfRAYiIiMjv161bN9hsNqPDEBERERERERG54GhHiIiIiIiIiIiIiIiIWJaeESIiIiIiIiIiIiIiIpalRoiIiIiIiIiIiIiIiFiWGiEiIiIiIiIiIiIiImJZaoSIiIiIiIiIiIiIiIhlqREiIiIiIkJux44diIuLQ+/evdGlSxfs3LnzvP/dLl26IC0tzf7rtWvXokuXLvjxxx/dEarbxcfHIzQ01KW/Z1RUFOLj4136e4qIiIiIyPnzNjoAERERERExTmVlJe6//35cdNFFSEhIQLNmzdChQwejwxIREREREXEZNUJERERERIjt378fBw4cwLx58xAbG2t0OCIiIiIiIi6no7FERERERIgdPXoUANCyZUuDIxEREREREXEPNUJEREREREjFx8djzJgxAID77rsPXbp0we23327/n7PPR0VFuTyO48ePIykpCVFRUejevTsiIiIwfvx4fPPNNwCAJUuWoFu3bvamjaOZM2fimmuuQXl5OYCa53H813/9F7Zu3YoRI0agZ8+eiI6OxtatWwEA77//PqKjo9GjRw+MGDEC3377rdOYCgoKMHHiRPTu3RvXXXcd0tPTUV1dXeczJ0+exPz58xEZGYnu3bvj5ptvxosvvtjgcyIiIiIiYiw1QkRERERESI0aNQpTpkwBANx+++144okn7L/2pFmzZuG1117DwIEDMWvWLEyYMAE+Pj7Ys2cPACAmJganT59GTk5OnX+voqIC69evx8CBA+Hj42N/fd++fXjggQcQFRWFGTNmoKSkBFOmTEFmZiaSk5MRHR2NadOmYf/+/bj//vtx5syZOr9vVVUVJk2ahLZt2+Khhx5C9+7dkZaWhiVLltg/U11djalTpyIjIwPXX389EhIScMUVV+CJJ55AcnKyG/9riYiIiIjIr6VnhIiIiIiIkAoNDUVFRQWee+45XHPNNbjlllsAAM8995xH4/joo4/w97//HfHx8fbXJk+ebP/nTp06ITQ0FJmZmfYdLLX/XklJCWJiYur8fj/88ANef/11hIaGAgA6d+6MiRMnYubMmXj33XftD4P38/PDo48+is8++wzXXnut/d8vLy/H9ddfj8TERADAbbfdhilTpmDp0qW4/fbb4e/vj9zcXHz66ae4//77MXXqVADA6NGjce+99+Lll1/GmDFj0LFjRxf/lxIRERERkd9CO0JERERERMRQrVq1Qn5+Pn766adGPxMTE4P8/Hzs37/f/lpWVhbat2+Pvn371vls586d7U0QAOjVqxcAoF+/fvYmiOPrBQUFDf680aNH2//ZZrNh9OjRqKysxJYtWwAAH3/8Mby8vBocITZhwgRUV1fj448/Pud1i4iIiIiIZ6gRIiIiIiIihnrwwQexa9cu3HjjjRg5ciTS0tIaNCcGDRqEiy66CJmZmQCAsrIy/Pvf/0Z0dDRsNludz7Zv377Or2sfBH/ppZfWed3X1xcAUFpaWuf1Jk2aIDAwsM5rV1xxBQDgwIED9v8PCAiw/x61goOD63xORERERESMp0aIiIiIiIicl6qqKrf8voMGDcIHH3yAxMREBAQE4MUXX8TgwYPx0Ucf2T/j5+eHAQMGICsrCwDw3nvvoaKiAkOHDm3w+3l5eTn9cxp7XQ83FxERERGxNjVCRERERESkDj8/vwa7JADg4MGDbvszAwICMHr0aDzzzDPIzc1F69atGzyrJCYmBnv37sWOHTuQlZWFrl274sorr3R5LGfOnGmwI+WHH34AAFx22WX2/z906BCOHz9e53Pff/99nc+JiIiIiIjx1AgREREREZE6AgMD8f333+Po0aP217777jt8+eWXLv+zqqqqUFZWVue1tm3bIiAgABUVFXVev+GGG9CmTRu88MIL+Oyzz5zuBnGVlStX2v+5uroaK1euRNOmTREREWGPpaqqqs7nACAjIwM2mw033HCD22ITEREREZFfx9voAERERERE5MIycuRIZGRkYOLEiRg5ciSKi4vx+uuvo3Pnzjhx4oRL/6wTJ04gMjISN998M0JCQtC8eXNs3rwZX331FeLj4+t8tmnTphg8eDBWrFgBLy8vDB482KWx1PLx8cHGjRvxj3/8Az179sTGjRvx4YcfYsqUKfD39wcAREVF4dprr8VTTz2FAwcOoEuXLvjkk0+Qm5uLsWPHomPHjm6JTUREREREfj3tCBERERERkTqCg4OxYMEClJWVITk5GRs2bMATTzyBbt26ufzPatasGW699Vbs3LkTS5YsQXJyMn744QfMmjUL48ePb/D5mJgYAEBERAQCAgJcHg9Q8yyRF154AUeOHMGTTz6Jr776Cvfccw/uu+8++2eaNGmCZ599FmPHjsW///1vJCcnY8+ePXj44YeRkJDglrhEREREROS3sVXryYAiIiIiImIS3333HWJiYrBgwQIMGzbM6HBERERERMQEtCNERERERERM44033kDz5s0xcOBAo0MRERERERGT0DNCRERERETELU6cOIGTJ0+e9TP+/v7w8vI65++1YcMG7N69G2+88QZGjx6N5s2buypMERERERGxOB2NJSIiIiIibpGWlob09PSzfiY3NxeXX375OX+vqKgoHDlyBNdddx2eeOIJ+Pr6uipMERERERGxODVCRERERETELQoKClBQUHDWz4SFhcHHx8dDEYmIiIiICCM1QkRERERERERERERExLL0sHQREREREREREREREbEsNUJERERERERERERERMSy1AgRERERERERERERERHLUiNEREREREREREREREQsS40QERERERERERERERGxLDVCRERERERERERERETEstQIERERERERERERERERy1IjRERERERERERERERELOv/AAsracWe44LgAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "stats_by_symbol[\"hit_rate_point_est_(%)\"].sort_values().plot(\n",
    "    kind=\"bar\", ylim=(45, 55)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "aa16d7d9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-18T11:37:02.104707Z",
     "start_time": "2023-08-18T11:37:01.021849Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='full_symbol'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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xxTGRkZFq1aqVVqxYYWNl/mXqem5qblO3b1Pnqdn9/Zumih/s379f5cuXz3Bc+fLldeDAARsqsoepuWNiYlS5cuUMx1WuXFl79+61oSJ7mJp727ZtatasWYbjoqKi9Msvv9hQkT1M3b7j4uIsnVpbqlQpxcXF2VCRPXbs2KGGDRtmOK5hw4basWOHDRXZY9euXbrvvvsyHHfffffpt99+s6Eie5ia29T1/PDhwypbtmyG48qWLauDBw/aUJE9TM1t6nyN/drVBdp+zdT5mqnzc1P3a3/88YeqV6+e4bgaNWrojz/+sKEie5i6npua29Tt29R5anZ//6ap4genTp1S3rx5MxyXN29enTp1yoaK7GFybivXccyXLx+5A8Dx48dVsmTJDMeVLFlSx48ft6Eie5i6fZ85c8bSDWxvuOEGnT171oaK7HHixAndeOONGY678cYbdeLECRsqskd8fLyKFCmS4bjw8HDFx8f7vyCbmJrb1PX89OnTyp07d4bjcuXKpTNnzthQkT1MzW3qfI392tUF2n7N1PmaqfNzU/driYmJKlSoUIbjChYsqMTERBsqsofJ67mpuU3cvk2dp2b39+9gpwsIRKmpqXK5XJbGejweP1djH1Nzp6SkWLq5pcvlUmpqqg0V2cPU3GfPnlXOnDkzHBcSEqJz587ZUJE9TN2+pUsTu4y+cElKSrKnGJucP3/+qqcep8mRI4cuXLhgQ0X2uHjxooKDM54aBQcHKzk52YaK7GFqblPX80DbR1tlam5T52vs164u0PZrkpnzNVPn56bu15KTky97+el/crvdSklJsaEie5i6npua29TtO5D+Da9Vdn7/pqniJ717987wi9fz58/bVI19TM09bNiwDI8iuF53Av+GqbljYmIynNDGxMTYVI19TN2+O3XqlOEYj8djedKbXWzYsEGxsbFXHbNv3z57irHRkiVLtHnz5quOOXTokE3V2MfU3Kau50899VSG+6xA/HBnam5T52vs164sEPdrps7XTJ2fm7pf++ijj1S4cOGrjjl27JhN1djH1PXc1Nymbt+mzlOz8/s3TRU/eOihhyyPrVKlih8rsZepuatWrSrp0ul6V+N2u3XPPffYUZItTM0tSf369ctwzPW6088sU7fvoUOHOl2CY4YPH25pXCCt55L0ySefWBpH7sBg4nrevXt3p0twhKm5TZ6vsV+7ukDKbep8zdT5uan7teLFi2vbtm2Wxlq5DGB2Yep6bmpuU7dvU+ep2f392+UJxDYXAPjJxo0br2l8tWrV/FQJ4D/XevO7m266yU+VAP7Deg4g0LBfAwAAsAdNFQAAMiExMVH79u1TeHh4QB0NBsBsJ06cUN68eZUjRw6nS7GVqbmBQMd8DQCQ3Zk4T80O798Z3/0H1+zPP//UqlWr0i1fu3atHn74YVWsWFENGzbUzJkzHajOf0zNfeLECf3222/plv/222/q2bOnmjVrpqeeeuqyfzfZmam5r2b37t368ssvtWnTpoC71qWp2/eaNWsuexmN0aNH695779Vjjz2m+vXrq2fPngF3w9crWb16taZMmaKFCxdmeFp2oDh37pxmzpypN998U2PHjtXhw4edLskWpuaWAns937Ztm2bNmpVu+bx581SjRg3VqlVL99xzj4YNGxZQ72Wm5ma+5ov9WmDu10ydr5k6Pzd1v3bx4kWdOnUq3fKjR49q2LBheuaZZ/Tqq6/qf//7nwPV+Y+p67mpuU3dvk2dp2b392/OVPGDl19+WYcOHfLZIHbt2qVWrVopJCREtWrV0r59+/T7779r9OjRatiwoYPVZh1Tc7/22mv69ddftWDBAu+ygwcPqkWLFjp37pzKli2r2NhYxcfHa/r06d5rRGZ3puZevHix1q1bp3fffddneZ8+fbR48WLvz+XLl9e0adOUJ08eu0v0C1O3765du+qGG27QyJEjvctWrVqlbt266c4779TDDz+svXv36rPPPlOfPn301FNPOVdsFpo+fbq+/fZbTZs2zbssJSVFTz/9tH766SfvRO6mm27S559/nuENM7OLDz74QKtWrVJ0dLR32dmzZ9WqVSvFxMR4c+fLl0/z5s1TyZIlnSo1S5ma29T1vGfPnjp37pwmTZrkXbZp0ya1a9dOxYoV0wMPPKC9e/fqu+++05AhQ67pmt7XM1NzmzpfY79m1n7N1PmaqfNzU/drgwYN0rp16/TVV195l508eVLNmzfXsWPHlC9fPp06dUpBQUH6/PPPFRkZ6WC1WcfU9dzU3KZu36bOU7P7+zdnqvjBL7/8oiZNmvgsmzlzplJTUzVr1iyNGjVKixYtUt26dTV9+nSHqsx6pub++eef1bx5c59lH3/8sc6cOaOJEydq/vz5WrVqle6++25NnjzZoSqznqm5FyxYkO6Uy4ULF2rRokWqXbu2xo0bp5dfflm///67Pv74Y2eK9ANTt++dO3eqbt26Psu++OILhYaGaurUqXryySf1+uuvq127dlq4cKEzRfrBV199pTJlyvgs++yzz7Rx40Y99NBDWrx4sT788EOdPn06oLbv77//XvXq1fNZNn36dO3Zs0fPPfecNm/erHnz5il37tyaMGGCQ1VmPVNzm7qeb9++Pd0H79mzZys4OFgzZ85Unz59NGHCBD344IOaPXu2Q1VmPVNzmzpfY7/2f0zYr5k6XzN1fm7qfm3Tpk168MEHfZZNmzZNx44d06BBg7RhwwatWbNGt9xyiyZOnOhQlVnP1PXc1Nymbt+mzlOz+/s3TRU/OHr0aLrJ7Lfffqu77rpLERERkiSXy6VWrVpp7969TpToF6bmjouL0+233+6zbPXq1YqMjFTt2rUlSTfccIOefPJJ7dq1y4kS/cLU3L///rtq1Kjhsyw6OlphYWEaNWqU6tWrp44dO6pz584+RxFld6Zu3ydPnvS5iavH49GPP/6o6tWrq0CBAt7ltWvXvuabw17P9u3bp8qVK/ss+/LLL1W4cGENGjRId9xxhxo3bqxnnnlGa9ascajKrLd//35VqFDBZ9mKFStUvHhx9ezZU7lz51b58uXVuXNn/fTTTw5VmfVMzW3qen78+HHdcsstPsvWrl2re+65x2d/98ADD+ivv/6yuzy/MTW3qfM19mv/x4T9mqnzNVPn56bu1w4fPpzu7JOVK1eqVKlSat26tSSpUKFC6tixo7Zt2+ZEiX5h6npuam5Tt29T56nZ/f2bpoof5MyZ0+dabwcPHtTRo0fTnZaWP39+JSUl2V2e35ia2+VyyeVyeX8+duyYDhw4kC530aJFdfLkSbvL8xtTcycmJqpYsWLen1NSUrR582bVqFFDoaGh3uWVK1fWoUOHnCjRL0zdvgsUKKDjx497f961a5dOnz6tKlWq+IzLmTOnUlJS7C7Pb06dOqXw8HDvzxcuXNAvv/yimjVrKigoyLv8zjvvVGxsrBMl+sX58+cVFhbm/fnMmTPatWuXatas6TPu9ttvV1xcnN3l+Y2puU1dz/PmzetzTfaYmBglJCSk26/lyZNH586ds7s8vzE1t6nzNfZrl5iyXzN1vmbq/NzU/drFixd1ww03eH9OTExUTExMugP+SpYs6bM9ZHemruem5jZ1+zZ1nprd379pqvjB7bff7nOE+tdffy2Xy6X77rvPZ9yhQ4cC5jq2krm5S5UqpR9++MH78+rVq+VyuVSrVi2fcUePHlXBggXtLs9vTM0dHh7u0yz53//+p3Pnzumee+7xGedyueR2B84u1tTt++6779aMGTO8E9rPPvtMLpdL9evX9xn3+++/q2jRok6U6Bc33nijzxFPP//8s5KTk1WtWjWfccnJyQoJCbG7PL+56aabtHPnTu/PGzduVEpKiqpXr+4z7syZM8qdO7fd5fmNqblNXc8jIyP1xRdfeH+Ojo6Wy+VKd+r9vn37fL6cze5MzW3qfI392iWm7NdMna+ZOj83db928803a+vWrd6f161bJ0npmsXx8fE+TeXsztT13NTcpm7fps5Ts/v7d7DTBQSizp0769lnn9WhQ4cUHh6ur776SuXKlUvXWV29erXKlSvnUJVZz9Tc7dq1U58+fZSYmKjChQvrs88+080336x7773XZ9y6det0xx13OFRl1jM1d7Vq1TRlyhTVqFFDBQoU0EcffaSgoCA1aNDAZ9zOnTt14403OlRl1jN1+37hhRfUunVr1axZU3ny5FFcXJyaN2+e7lTspUuXpjuaIjurW7euJkyYoDJlyig8PFxjx45VSEhIusnNtm3bVKJECYeqzHpNmjTRhAkTVLBgQYWHh2vEiBHKkydPuuvyb968Od3p2dmZqblNXc+ff/55Pfnkk2rcuLEKFSqkn3/+WbVq1brspZLuvvtuh6rMeqbmNnW+xn7NrP2aqfM1U+fnpu7XWrVqpeHDh0uSChcurPHjx6tQoUKqU6eOz7gNGzaodOnSTpToF6au56bmNnX7NnWemt3fv2mq+EHdunU1YsQIzZw5Uzt37lSTJk303//+12fM8ePHtW/fPnXp0sWhKrOeqblbtGihuLg4zZw5U4mJiSpXrpzeeOMNBQf/3+Z1/PhxrV69Wj169HCw0qxlau60nf79998vt9utlJQUde7c2ec6kJK0aNGidEcFZmembt9lypTRokWLNG/ePCUlJalcuXJ66KGHfMYcP35ckZGR6W4cmZ1169ZNP/74o5588klJl8686tevnwoVKuQdk5KSogULFuiBBx5wqsws17lzZ/3yyy965ZVXJEm5cuXS4MGDlTdvXu+Y8+fPa/78+WrTpo1TZWY5U3Obup5XrFhR06dP1+zZs5WYmKhu3bqpU6dOPmOOHz+uoKAgtWzZ0pki/cDU3KbO19ivmbVfM3W+Zur83NT92hNPPKE9e/Zo7NixSk5OVvHixTVixIh0lwRbtGiRnnnmGQcrzVqmruem5jZ1+zZ1nprd379dHo/H43QRAJCdJCUlafny5d43+X9ex/bEiRNauHCh6tatm67DDmQXKSkp2rBhgxITExUZGZnuSN6EhAT9+OOPuvvuu33uMxQI/vrrLyUkJKhUqVLKkyePz2OnT5/W3r17dcstt/h8ORcITMxt8noOmID9Gvs1INCcO3dOZ86cueylj5KTk5WUlKQ8efIoR44cDlQHAOagqQIAAAAAAAAAAGABl//yg/bt21/xsRw5cqhgwYKqVq2aWrRooZw5c9pYmX+Zmrtfv35XfOzvuf95DcjsztTcf79J/T8FBwcrf/78AXXjzzSmbt8RERFyuVyXfSwoKEiFChVS1apV9eyzz+r222+3uTr/+emnn674WHBwsAoVKqSbb77ZxorssXDhwis+lpa7QoUK6Y52zu5MzW3qel6/fv0r7tfScletWlXt2rULqBufmprb1Pka+7X0Anm/Zup8zdT5uan7tTFjxlzxsbTc99xzj0qVKmVjVf5n6npuam5Tt29T56nZ/f2bM1X8oFu3bldcKVJSUnTkyBHt2rVLt9xyi2bMmOFzjdvszNTcV7ueYUpKio4ePar4+HhVrVpVEydOVK5cuewrzo9MzX21nb4kud1uVahQQT179gyoN3pTt++PP/74irlTU1N15MgRrV69WrGxsfr0009155132lyhf6St51eaIrhcLoWHh+uFF17QI488YnN1/hMREZHhmBtuuEEdO3ZUz549bajIHibnNnE9Hzx4cIb7tQ0bNig4ONh7c9BAYGpuk+drGWG/Fjj7NVPna6bOz03dr/3zBuV/l5KSojNnzsjlcqlFixYaMmSIgoKCbKzOf0xdz03Nber2beo8Nbu/f9NUcciBAwfUvn173XvvvXr77bedLsc2pubetGmTnn/+eT388MPq06eP0+XYJhBzf/PNN1d8LG2n//XXX2vTpk2aMmWKatasaWN1zjJ1+05OTlaHDh2UO3duTZw40elyssRvv/12xcfSJvFff/21FixYoOHDh6tp06Y2Vuc/SUlJV3zs77nHjRun/v37q23btjZW5z+m5jZ1Pbfi1KlTeuKJJ3TbbbdpxIgRTpdjG1NzB+J8jf1aeqbv1wJxvmaFqfPzQNyvZeT06dP6+uuvNXDgQD3zzDPq1q2b0yXZxtT13NTcJm7fkrnz1Ov6/dsDx8yZM8dTu3Ztp8uwnam5p0+f7qlXr57TZdjO1NzPP/+858knn3S6DNuZun0vXbrUU7VqVafLsN2rr77qadWqldNl2G7YsGGeqKgop8uwnam5TV3PFy5c6KlRo4bTZdjO1NymztfYr5nF1PmaqfNzU/dr48aN8zRq1MjpMmxn6npuam5Tt29T56nX6/u32+mmjslKliypkydPOl2G7UzNfccdd+jIkSNOl2E7U3O3bNlSv/76q9Nl2M7U7btAgQI6e/as02XYrmHDhvrjjz+cLsN2NWvW1J9//ul0GbYzNbep63nRokWverR/oDI1t6nzNfZrZjF1vmbq/NzU/VrFihWveh/QQGXqem5qblO3b1Pnqdfr+zdNFQft379fBQoUcLoM25ma+8iRI8qbN6/TZdjO1Nw5c+ZUSkqK02XYztTt+5dfflHx4sWdLgM2OX/+vIKDg50uw3am5jbV77//riJFijhdhu1MzW3qfI39mllMna+ZOj83db8WHx+v0NBQp8uwnanruam5Td2+TZ2nXq/v3zRVHHLw4EGNHz9edevWdboUW5ma+9SpU5oyZYpq1KjhdCm2MjW3JP3444+65ZZbnC7DViZu36dOndKiRYs0ceJEtWjRwulybLdy5UrdfvvtTpdhu0WLFqlcuXJOl2E7U3ObuJ5v2rRJ48aNU6NGjZwuxVam5jZ5vsZ+zQwmz9dMnJ9L5u7XUlNT9emnn6pSpUpOl2IrU9dzU3Obun2bOE+93t+/OSzHD7p27XrFx1JTU3Xs2DHt2rVLJUuW1IsvvmhjZf5lau6r3RAsJSVFx44d08aNGxUUFKQxY8bYWJl/mZo7Pj7+io+lpqbq6NGjWrlypaZPn65+/frZV5ifmbp9V6pUSS6X67KPpaam6vz58/J4PIqKirrq31F2c7VL16Vt3ytXrtT8+fM1fPhwGyvzrxUrVlzxsb/n/umnnzRlyhQbK/MvU3Obup43b978io+l7c8TExNVpUoV9ezZ08bK/MvU3KbO19ivpRfI+zVT52umzs9N3a9Nmzbtio+l5f72228VGxurWbNm2ViZf5m6npua29Tt29R5anZ//3Z5PB6P00UEmnbt2l3xseDgYBUsWFBVq1bVgw8+GFCnZZqau379+ld87O+527dvr/DwcBsr8y9Tc0dERFxxp58mR44cevrppwNqcmPq9j169Ogr/nsHBQWpYMGCuueee1SmTBmbK/OvjNZzj8ej8PBw9ezZU61bt7axMv+KiIi46uNut1sVKlRQjx49VLt2bZuq8j+Tc5u4nvft2zfD/VrVqlVVu3btDN/vshNTc5s8X7sa9muBtV8zdb5m6vyc/Vp6QUFBKlCggKpVq6Znn31WZcuWtbEy/zJ1PTc1t6nbt6nz1Oz+/k1TBQCuwfz58zPc6d99991GXt8Tvn766SeVK1dOuXLlcrqUa7Zx48YrPpa2nt96660BNaGTLp1CfyXBwcHKnz+/cubMaWNF9jA1t6nr+b9x6NAhFSlSxLh7UJiaOztjv5Ye+7XLy87zNQAATJ2nXhfv3x5cN5KTkz0RERGe7du3O12KrUzNnZKS4qlfv75n9+7dTpdiK1Nzezwez4IFCzzx8fFOl2ErU7dvU3OnpqZ6Ro8e7Tly5IjTpdgqNTXV07dvX8/BgwedLsVWJuc2cT03db9mam5T52vs19ivmcDU3Kbu11JSUjzt2rXz7N271+lSbGXqem5qblO3b1P/va+X3Nyo/jrjMfTEIRNzezweHTx4UBcuXHC6FFuZmjslJUX9+vXTgQMHnC7FdiZu35KZuVNTUzV27FgdOXLE6VJslZqaqoULF+rkyZNOl2Irk3ObuJ5LZu7XJDNzmzpfY7/Gfs0UJuY2db/m8Xi0ceNGnT592ulSbGfiei6ZmdvU7Vsy899buj5y01QBAJtcDzt9wN9MXc/JbRZTcwMmMHX7NjU3AABAZtBUAQAAAAAAAAAAsICmCgAAAAAAAAAAgAU0VQAAAAAAAAAAACygqQI4yOVyOV2CI0zNDQAAkF0wXwMQaNivAYGL7Rt2o6lyHXG5XCpevLhCQkKcLiVTfvrpJ50+ffqan5fdc/8bpt4Q0tTcJjJ1+3a73XrooYdUoEABp0sBgCzhcrlUtWpV5c6d2+lSbGVqbon5GgKfqfM1U+fnEvu1QLd//37v/5u6npuaWzJz+zZ1nnq9vH+7PCaudX7222+/KSIiwtLY2bNnq02bNn6uyB6RkZH6/PPPdddddzldynUpOTlZx48fV9GiRZ0uBf/C/Pnz1ahRI+XJk+eanufxeDR27Fg99thjCg8P91N1zti9e7f27Nmj8PBwValSxYgjRM6dO6d58+Z5cz/00EO68cYbnS7rurBgwQLVr19f+fLlc7oUW23cuFHly5dXrly5nC7Fr3766SdVrVrV+7Mpuf8pO6/n27Zt0+23367Q0NCrjjt58qTWrVun5s2b21SZffbt26etW7fq2LFjcrlcKly4sCpVqqSbb77Z6dIc8/XXX+vFF1/U9u3bnS4lS6xdu1b33XdfhuMuXryoV155RR988IF3Gfu17LdfmzVrltq2bZvhuKNHj2ro0KEaMWKEDVXZ448//tDs2bN14MABFSlSRA888IDuvfdep8uCH/yb71sOHjyoIkWKKEeOHH6ozL/69++vIUOGZDjut99+U+fOnbVu3TobqnLeiRMnlCdPHiObJxLfrwWKI0eOaNCgQXr00UevOG9bu3at5syZo4EDB6pQoUI2V3h1NFX8oFy5cnrqqafUo0ePK35g3blzpwYMGKAdO3bo119/tblC/4iIiNCcOXOMa6rcfffdmjlzpipUqCDp0pfnnTp10htvvKFbbrnFO+6XX35RmzZttHPnTqdKzVJvv/225bEhISG66aabVK9ePRUvXtyPVflfRESEcubMqfvvv1/NmzdX3bp1s+Xk9FotXrxY69at07vvvuuzvE+fPlq8eLH35/Lly2vatGnX3HS6Xn3wwQdatWqVoqOjvcvOnj2rVq1aKSYmxns0TL58+TRv3jyVLFnSqVKz1MCBA9WlSxfddNNN3mXR0dGqW7euwsLCvMv27NmjwYMH66OPPnKizCy3cOHCaxrfsmVLv9RxPfrmm280ZcoU/fLLLwHzPnat869y5cr5qRJ7/fNLmdTUVN11112aM2eO7rzzTu+4QJu3SFJcXJz69++vH374Id3RjC6XS/fdd58GDx4ccAc/WPHVV1+pV69eAfPvfffdd2v06NGqU6fOFcecO3dOzz//vDZs2BAwzaTt27erU6dOevfdd1W3bt3Ljvnuu+/0yiuvaPr06ZYPBLzelStXTuXLl9ebb7552Uwej0czZszQhx9+qDx58ui7775zoMqst2nTJj399NNKTk5WwYIFFR8fr9TUVA0YMECPP/640+X5Tb9+/SyPdblclr6Qzw5M/b6lfPnyat68uYYMGXLFg/c2b96srl27Kjw8XMuWLbO5Qv/ZsmWLVq5cqeTkZDVq1EiVK1fWwoUL9e677+rkyZMKDg7Www8/rNdff13BwcFOl5slTP1+7VoOYnK5XD7fwWRnw4YN0/r167VgwYIrbt8ej0cPP/ywatWqpd69e9tc4dUFxlZ3nXn55Zc1atQoLV++XK+//rrq1avnfezUqVMaOXKkPvvsM0VERGj27NkOVoqscP78eZ8P5qmpqfrhhx906tQpB6vyv1WrVlkee/78ecXHx2vYsGGaOHGiatas6cfK/GvRokVaunSpli1bpq+++kphYWFq3LixmjdvrmrVqjldnt8sWLAgXUNs4cKFWrRoke677z498cQT2rt3r0aNGqWPP/5Y3bt3d6jSrPX999/77MMlafr06dqzZ4+6deumTp06ae/everZs6cmTJigwYMHO1Rp1vr888/18MMPe5sqKSkpeuWVVzRv3jyfL5ZPnTql9evXO1Vmluvbt693MpfRMSculytgmiqpqamaOnWq5s+fr8OHD6tEiRLq3r27HnjgAa1bt07Dhg3TH3/8oZtuuklvvfWW0+VmmUceecTSmXUej0culytgPrT9c932eDxKTk4O+EsmnD17Vu3bt9eRI0fUsWNH1a5dW8WKFZPH41FcXJzWrFmj2bNnq0OHDvriiy90ww03OF0y/oV69eqpe/fuGjVqlO6///50jyckJOjZZ5/Vjh07NHLkSNvr85fp06erUqVKV2yoSFLdunVVpUoVTZs2TcOGDbOxOv/5/PPPNWDAALVq1Urt2rVTjx49vGcabdu2TQMHDtSuXbv05JNPqmfPng5Xm3VGjx6t0qVLa8KECbrxxht16tQp9evXTyNHjgzopoqV9+OLFy9qz549AdVUMdWIESP03//+VykpKRo2bFi6udu3336rXr16qUyZMpo8ebJDVWa9lStXqkePHsqXL59uuOEGzZgxQ3379tXQoUNVt25dlSlTRrt379acOXNUqlQpdejQwemSs4Sp36+VK1fOZ932eDxauHCh7r//fscvceVPq1evVocOHa76mczlcumxxx7T9OnTaaqYoEOHDnrggQf01ltv6bnnntN//vMfvfrqq9q8ebOGDh2q8+fPq3///nriiScC7jI5GzZsUGxsrKWxjRo18nM18KdraapIlz68vv7663rvvfc0f/58P1Xlf2XLllXZsmX13//+V1u2bNGSJUv01Vdfad68eSpSpIiaNWum5s2bKzIy0ulSs9Tvv/+uhx9+2GdZdHS0wsLCNGrUKIWGhqpevXo6c+aMvvrqq4Bpquzfv997lEyaFStWqHjx4t4P5eXLl1fnzp318ccfO1Chf1zuy9VA/8JVunRWXXBwsP7zn/8oKipKFStWdLokW8ycOVPDhw9X6dKlVa9ePR06dEj//e9/tXPnTk2aNEnh4eF666239NBDDwXMUXCS9MknnzhdAmw0Z84cHTlyxHtg09+VLl1aNWvWVIsWLfTEE09o3rx5evLJJx2qFFlhxIgRevnll9WjRw+NHDlSDRo08D525MgRderUSYcOHdLkyZNVvXp1ByvNWhs3blSfPn0yHBcVFRUwDRXp0lxs3rx5+uSTT7wHN/bu3VsbNmzQ3Llzdffdd+uLL74ImDNz0uzevVtvvvmm9xK0efLkUZ8+fdSwYUMdPnw4YC9Ne7Uzi8+fP6/PP/9cU6ZMUVBQkJo1a2ZfYTY4deqU4uPjLY3Nnz+/X2uxS6NGjfThhx+qV69eSklJ0XvvvSe3+9LtoRcvXqz+/furSpUqGjduXEDdV2LSpElq1KiRhg8frqCgII0fP17Dhg3T008/rZdfftk7bsiQIfriiy8Cpqliqnfeecfn5+TkZC1cuFA9evQImLPlL+fgwYO67bbbMhxXpkwZHTx40IaKrk3gfDK+zhQrVkzjxo3TN998ozfffFMNGzZUSkqKoqKi1KdPHxUuXNjpEv1ixIgRlr54C6QjPpGxU6dOKV++fHr88cfVtWtXp8vJMpUqVVKlSpX06quvav369VqyZInmzp2radOmqXTp0mrevHnA5E1MTFSxYsW8P6ekpGjz5s2qU6eOz2UOK1eurGnTpjlRol+cP3/e53JXZ86c0a5du9KdoXD77bcrLi7O5uqQ1davX6+vv/5aS5cu1XPPPadixYopKipKUVFRliZ72dXcuXMVFRWl9957z3uwx9SpU/Xee+/pnnvu0aRJkwLy3gKBfHYh0lu5cqVatWp11S9VIyMj1apVK61YsYKmSjbndrv1/vvvq2/fvnrhhRf0wQcf6D//+Y/+/PNPdezYUWfPntUnn3wScF9UHD9+XEWKFMlwXJEiRXT8+HEbKrKP2+32HtzYtm1b9e7dWy6XK6AvhXXy5Emf+bkkbyPl5MmTAdtUuZxz587ps88+09SpU5WQkKAWLVro2WefDbh7ZXXq1Mny2ED6vqVBgwYaM2aMevTooZdeeknDhw/XjBkz9M4776hhw4YaPnx4wN1bZM+ePerRo4eCgoIkSW3atNGHH36Y7kzE+++/X3PnznWiRPhRoB2AfyU5c+a0dBbSmTNnrsttnKaKH128eFG7du1SQkKCQkJCdPbsWYWGhipnzpxOl+Y3o0ePDrgj9JF5x48f1/Tp0/XZZ5/pp59+UqVKlfT55587XVaWc7vdqlWrlmrVqqWBAwfqvffe06xZs/Thhx8GTFMlPDxchw4d8v78v//9T+fOndM999zjM87lcnmPHAoEN910k3bu3Ok9inXjxo1KSUlJd1TrmTNnAurIKFPlzp1bLVu2VMuWLXXixAl9+eWXWrZsmSZOnKjbb79dUVFRat68ecB9SXHgwAGfS59Jly6N9d577+mZZ54JyIaKdOmssxo1avg0Tk0W6B/e/vjjD7Vv3z7DcTVq1NDSpUttqMgeVu+B99dff/m5Evu5XC698847crvdevHFF9WjRw9Nnz5dN9xwg2bNmqVSpUo5XWKWCwsL05EjRzIcd+TIEeXNm9eGiuy1b98+DRw4UAcPHlSNGjW0adMmffrpp7rjjjtUpUoVp8uDH5w5c0YzZ87Uxx9/rKSkJD388MN69tlns/19PK+ka9euAdcosqpu3boaO3asunfvrhYtWmjPnj16+OGHNWjQoID6/Jnm1KlTPnPUtP//52fO3Llz69y5c7bWBmSVsmXLatWqVZe9VOvfrVy5UmXLlrWnqGtAU8VPNm7cqDfeeEMHDx7UM888oy5dumjx4sV6//33tXLlSr3yyit68MEHnS4zyxUpUsTnxsamWLJkiTZv3izp0jUfXS6XoqOjtXHjRu+Yv38hHSi2bt2qBQsW6PDhwypZsqTatWunW2+9VceOHdPYsWM1f/58JScnq2nTppKkG264IeBOu0/z66+/asmSJVq2bJni4uJUuHBhNWnSxOmysky1atU0ZcoU1ahRQwUKFNBHH32koKAgn8tpSJeOiAqkL5ybNGmiCRMmqGDBggoPD9eIESOUJ0+edPdZ2bx5s8+N8wLB3y8vkJKSkm6ZJCUlJTlQmT0KFiyotm3bqm3btoqNjdXHH3+sDz/8UNu2bdOYMWOcLi9LnT17Nt2Xa2k/FypUyImSbPHCCy+ku2F7kyZNNHbs2IA+M0m6dFPIf/6bDxkyRHny5PH+HGjbd2JioqX1uWDBgkpMTLShIntcy+VaA+n9O43L5dLQoUOVI0cOjRw5UmXKlNHUqVNVtGhRp0vzi4oVK2revHneufeVfPHFF6pcubJNVfnfxYsXNXHiRE2aNEk33XSTpk+frurVq+uPP/7QwIED1a5dOz300EN6+eWXA+aSSGmeeuqpyzbF27Zt67Pc5XJ5P68GglOnTmnGjBmaPn26zp49q9atW6tLly4Bu22nqVevnnE3qv/111+9/1+wYEF1795dw4cP997X859n5ATaGYj/FOgHwUjmfr9molatWum1115TpUqV9NBDD112zMKFCzV//nzLBwrZiaaKH/Tp00eLFy9WjRo1NH78eN16662SpNatW6tBgwYaNmyY+vTpo/nz52vgwIEBeZSUaS53XfbL3V8hkN4Av/vuOz333HPyeDwqWLCgfvjhBy1ZskTvvvuu+vTpo8TERDVr1kzdunUL2HV87969WrJkiZYsWaK//vpLuXLlUqNGjRQVFaWaNWsG1BEzL7zwglq3bq37779fbrdbKSkp6ty5c7om6qJFiwLqkjqdO3fWL7/8oldeeUWSlCtXLg0ePNjny8jz589r/vz5atOmjVNl+sXlLi/wz2v1pt3AO1AlJSVpxYoVWrp0qTZs2KASJUqka6gFipiYGO/lBaT/a6TFxMSkGxsoH1Yvd8P2P//8U+fPn3eoIntUrVpVknT69OmrLnO73enORszOkpOTfdbxK0l7jwsU13oPvEDRvHnzdMs8Ho/OnDmjzp07+yx3uVxavHixXaX5VceOHdWuXTv169dPffr0SddASExM1LBhw7R+/XrNmDHDmSL9ICoqSrGxseratau6dOmiHDlySJJuu+02zZw5U1988YXee+89rVq1Si+//HK6+wRmV4FyD8NrNXr0aM2YMUPJyclq06aNOnXqFNAHgZjukUceueznjbVr12rdunXen9M+lwTSZc9MPAhGMvP7tSsJ9IwPPfSQ1q5dq379+mnmzJm67777VLx4cblcLh06dEjr1q3T9u3b1bRp03SXYL8euDwm3HnWZrVr11afPn0uO5lPs2HDBu+pydu2bbOxOv+JiIjQnDlzjDtywlRPPPGEzp8/r3Hjxqlo0aI6ffq0XnvtNX399dcKDw/X6NGjVb58eafLzHJxcXFaunSplixZop07dyo4OFh169ZVVFSU6tevf11e5zGrJCUlafny5UpMTFS5cuVUo0YNn8dPnDihhQsXqm7duipTpoxDVfrHX3/9pYSEBJUqVcpnEitd+hJy7969uuWWWwLmUhoLFiy4pvFXOqokOzp37pxWrVqlJUuWaO3atSpUqJCaNGmiqKiogGkm/FNERMRlJ+xpU8S0xwLtw+o/5y0pKSkqV66cvvjii4D9tzZZRESEHnjggQzva3js2DF99dVXAbOem+qflzTMyNChQ/1Yjb1mzZqloUOHyu12q3z58rrxxhvlcrl0+PBhbd++XSkpKerfv7+eeOIJp0vNMp07d9Ybb7yhkiVLXnFMfHy8hg0bpkWLFmnHjh02VoesljZvueuuu1SgQIGrjnW5XBo/frxNlfmXqd+3/P3sBCsC5QC/du3aXdP4QGqUm+hy3x///vvvuuWWW9J9xxRIB4OkmTVrlj7++GPt37/fZ/nNN9+sDh06XLdzFpoqfpCUlGTpi7WLFy9q8uTJ6tatmw1V+d/BgwdVpEgR75FBCGzVq1fX4MGD1bBhQ++yQ4cOqX79+nr//fcVFRXlYHX+ExkZKZfLpapVqyoqKkoPPPBAwHyRjn/nwoULAd1UM8FLL72kVatWKTQ0VI0bN1azZs0C6kj9KzH1w6qpTZWdO3davv9d2tnVgaB+/frXND7QzvC4cOGCli9frk2bNik2NlaSVKxYMVWtWlWNGzfm/SvA/Pbbb/rkk0+0adMmxcXFSZKKFi2qatWqqV27dtfldcntsmnTJiPe2/8uJSVF0dHR1+VRvplh6pfNCxYs0P33359hIwlA9mPqwSDt27fXG2+84T0oNy4uzmfecr1f0pGmCrLMwoULr2l8oEzqJGnOnDmaMWOGDhw4oCJFiqhJkybq1q1bQH9AvdyRMmlfSM2dO1cVKlRwsDr/mTZtmpo2bZrhzj0hIUEzZswImNPyly1bplq1ailfvnzeZWn3jvn75VTi4uK0YMECde3a1Ykys9wLL7yg1157TeHh4Vcd991332nQoEH65ptvbKoM/hAREaHcuXOrcuXKGV4mKJCOfLwWZ8+eVWhoqNNlZImIiAi1b9/eex+J1NRUvf/++3rqqafS7eNdLle6y99lV9WrV9e0adN05513XnGMx+NR//79tXDhQs7YCACbNm1S7969FRcXJ4/H473Zbdq9Y4oXL6733nsvoG7k3aBBA40dOzZg7+WHa5eYmKjly5crOjo6YL5k/7sTJ06oQIECPl/KnTt3Tp9//rmmT5+uw4cPsz8PEDTJYaK/31tHunS/3kC7OoaJsvsZeNxTxY8OHDiguXPnauvWrTp27JhcLpcKFy6sypUrq1WrVipevLjTJWapv3dWM+rVuVyugGmqfPHFFxowYIBuueUW3X///Tpw4IAmTJigxMREDRgwwOnyHGHlmuXZ1dNPPy3p0uVBDh06pJtuusnnGr5xcXGaOnWq5s6dq4sXLwZMU+Wll17yuaFzSkqK7r//fs2bN8/niO7Y2Fh9+OGHAdNU2bp1q5o0aaIXX3xRTzzxRLqjR2JjY/X222/rm2++Cah7bfTr18/yWJfLpSFDhvixGvuk3Vfi3LlzDldyfUlJSdHatWsVHR2tVatWacuWLU6XlGWu5ZrNgdJUue2229ShQwdNnTr1sgdAXLhwQf/973+1cuVK9e/f34EKkZX27NmjLl26qHjx4nr33XdVr14972UsT58+rdWrV2vChAnq0qWL5s2bp9KlSztccdY4ePCgLly44HQZcNiFCxe0cuVKRUdHa+3atbp48eJVG8rZzfnz5zV06FAtWrRI586dU+7cudWtWzd17NhRc+bM0ciRI3XixAlVqVJFgwcPdrpcZIGrNcnnzJmjDz74IOCa5O3bt7c81uVyafr06X6sxj4//fTTNY1P+xyT3e3evVudOnVSz5491bp1a0mXPov8/d46Ho9HQUFBWrhwoW6//XYny80yHAySPdFU8ZPo6Gi9+uqrunDhgooWLaobb7xRHo9He/fu1Y8//qipU6dq6NChatq0qdOlZpmQkBAFBwfrP//5j6KiolSxYkWnS7LFzJkz9cADD2jEiBHeG5NPmDBBY8aMUf/+/RUcHLib2VNPPXXZUxTbtm3rs9zlcmnz5s12luY3CQkJevnll7V27VpJl25o26ZNG7366qv68MMPNW3aNKWkpKhp06YBc2k/6fKNUhNOdPzyyy/1wQcfaMiQIVq4cKHeeustRUZGKiUlRdOmTdO4ceOUP39+jR07Vg0aNHC63Cxj5UjGixcvas+ePQHVVAnEI1f/jc2bN2vJkiVavny54uPjVbBgQT366KNOl5VlfvvtN6dLcMSUKVP0zDPPqGPHjpo6darPkWGnT5/Wc889p59//lnvvvvuVe8PmN0cOnTomsYHysFP48aN06233qrPPvtMN9xwg89juXPnVlRUlBo0aKC2bdtq7NixGj58uEOVIiu8/fbb1zT+tdde81MlzvF4PPrhhx8UHR2tr7/+WqdPn/Ye0NehQ4eAuvTZpEmTNHv2bNWqVUuRkZE6ePCgRowYoV9//VVLly7VnXfeqeHDh6tmzZpOl5rl9u3bp9DQUJ8zS6dNm+YzJnfu3AE1bzG1SZ4nT54ML4t0/Phxbd26NaBu6t2uXTu5XK6rfuZOy+tyuQLmXlGzZs1S4cKFvQ2Vvxs4cKBKlSolj8ejSZMmaebMmXrzzTcdqDLrcTBI9hS43/Y6aM+ePerfv7+qVKmi119/Pd0pab///rsGDRqkvn37KjIyUqVKlXKo0qy1fv16ff3111q6dKmee+45FStWTFFRUYqKitJtt93mdHl+8+eff+qll17yNlQkqU2bNho5cqQOHjyoW265xcHq/CdQzsC4VqNHj9YPP/yg1q1bez+8zJ49W7t27dKmTZtUr149vfLKKwGzXZsuV65cevXVV/Xggw9qwIABatWqlR555BFt2bJFe/fu1dNPP63nn38+3RdV2d3VLud4/vx5ff7555oyZYqCgoLUrFkz+wrzs39e09VEv//+u5YsWaLo6GgdPnxYOXLk0MWLF9WvXz+1bds2oM9ENEVoaKimTJmirl27qmPHjpo8ebIqVaqkEydOqHPnzoqJidHYsWNVt25dp0vNUvXr17f8ZUsgfTnx448/ql+/fld9nwoNDVXHjh0D5vrcJruWewG5XK6Aaqps27ZN0dHR+vLLL3X8+HHlyZNHjRs31v3336+ePXvq4YcfDqiGinTp8rzt27f3Oatw4cKF6tu3rxo2bKhRo0b5fEYNFN999526du2qiRMnepsqKSkpGjZsmM84l8ulYsWKqU6dOk6UmeVMbZKPGzfuio8dPXpUU6ZM0ffff6+8efPqySeftLEy/8ro8vpHjx7V1KlT9eOPPyp37tz2FGWDH3/88YpnJ5UvX957lYyjR49qzJgxdpYGP+ndu7dy5syZ4TiXy6XFixfbUJF1NFX84NNPP1XJkiU1adKky17P8vbbb9eUKVPUsmVLzZo1K2Ams7lz51bLli3VsmVLnThxQl9++aWWLVumiRMn6vbbb1dUVJSaN2/uvXZ5oDhz5oz3tNs0aTcuP3XqlBMl2cLUpsqaNWvUtWtXn/xVqlTRc889p0cffVRvvfWWg9XBX8qXL68pU6aodevWmjNnjtxut8aOHRtQl/zKyLlz5/TZZ59p6tSpSkhIUIsWLfTss8/q5ptvdrq0LLNx40adPn3a6TJsFxsb622k7N69W0FBQapRo4Z69uyp6tWrq169eoqMjKShEkBy5sypiRMn6rnnnlPnzp315ptvavTo0Tp58qSmTp0aUJcNSZPRB+8LFy5ozpw5+vHHHwNqXU9MTFSxYsUyHFesWDHvPVYCxZXOqP6nQDqj+lqaKoGkcePG+uuvv5QzZ07VqVNHzZs3V926dRUSEqKkpCSny/ObgwcPqn79+j7LGjZsKOnSlQMCsaEiXbr8dt26dS/bLPniiy+8X7oOHDhQ8+bNC5imCk3y/xMXF6fJkydr3rx5uuGGG/TMM8+offv23jN3AsGVLgN15MgRTZkyRXPnzlWOHDnUvXv3a7pE2vXu8OHD6S7p5Xa7df/99/t871a0aFEdPnzY7vLgB6VKlVLBggWdLiNTaKr4wcaNG/Xoo49e9QZhISEhevTRRzV//nwbK7NPwYIF1bZtW7Vt21axsbH6+OOP9eGHH2rbtm0B2U2OiYnx+QCekpLiXf5Pf7//RCBJTU1VfHy8JCl//vwBO4k/dOiQqlev7rOsRo0akqQWLVo4UZKjAukU66tZuHCh3n33XaWmpqpnz55auHChXnzxRXXt2lWdO3cO6Mv8nTlzRjNnztTHH3+spKQkPfzww3r22WcD5tI4kLc5WK5cOb322mtq0qSJd2IbyF9GRUREGHnmQpqQkBCNHz9ePXv21Msvv6zChQtr5syZuuOOO5wuzS/Svmj8p/Pnz2v27NmaOnWqTpw4oYceekjPPvuszdX5T7FixbRz507dc889Vx23Y8cOS82X7KRZs2YBlykj/fr1U7du3VSyZEmnS7HVn3/+KenSQTCNGjXSfffdZ8TNui9cuKBcuXL5LAsNDZWkdAf9BZKtW7fq5ZdfznBc7dq1NWjQIBsqsofJTfI0hw8f1oQJE7RgwQLlyZNH3bp1U9u2bQPqTI0riY2N1aRJk/TFF18oNDRUXbt2Vdu2bQOqkSRduj/vxYsXfZa5XC5NmDDBZ9n58+cD7jsnEw8GkaTnn3+eG9Xj/xw+fNjSqcVly5bVwYMHbajIGUlJSVqxYoWWLl2qDRs2qESJEgF7VPeVbur88ssv+9xMy+VyWbpXQXby7bffavr06dqyZYvOnz8v6dIRsJUrV9ZTTz0VcJcPSU5OTndqYtqHtrQPMYHqcqdlvvjiiz4fWtPWgUCxd+9evfHGG/rpp5/UsmVLvfLKKypQoIA6d+6scePGaezYsYqOjtbAgQMD5uaAaU6dOqUZM2Zo+vTpOnv2rFq3bq0uXbr4XLsagSEsLEwJCQnav3+/du3apTvuuCPbHi10Lfr27ZvhB5fVq1frxx9/tKkie3Tt2tXn54sXL8rj8ahw4cIaMWKEz2Mul0vjx4+3szzbnD17Vp9++qmmTZumhIQEPfTQQ3rmmWdUokQJp0vLUg0bNtT48eN133336dZbb73smD///FOTJk3Sgw8+aG9xfvboo49m2w/pmbVgwQI9/vjjxjVVFixYoMWLF+vLL79U7969FRoaqgYNGqh58+aqUKGC0+X51YYNGxQbG+v9OTU1VS6XSxs2bEj3XUOjRo3sLs8vTpw4ke7qF0FBQXrllVd8lufPn18nTpywuzy/MblJvn//fk2cOFELFy5U/vz59d///ldt2rQJuEswX87Bgwc1ceJELViwQPny5VPPnj31+OOPp2uoBopbb71VmzdvVq1ata46btOmTVec12RXJh4Mkt3RVPGD06dPW+qU58qVS2fOnLGhIvucO3dOq1at0pIlS7R27VoVKlRITZo00UsvvRSwZ2h88sknTpfgmLffflszZ85Uvnz5VKdOHe8k9vDhw9qwYYO6du2qJ598Uq+++qrDlWatJUuW+BwZkPbhJTo6Whs3bvQud7lc6tChgwMVZr2WLVum+/KxfPnylx0bSJeNadGihW655RbNmDHD5wNMSEiIevXqpRYtWuiNN95Q+/bt9eCDD+qdd95xsNqsM3r0aM2YMUPJyclq06aNOnXqpEKFCjldli2y8zVdM+v777/XunXrFB0drejoaM2dO1dFixZV06ZNA64x/ndX2z9/8803GjdunHbs2KGqVauqW7du9hXmZ5e7xF1aU9iEy9+dPn3ae/bd6dOn1apVK3Xp0iXgLk+b5rnnntOqVav04IMPqmXLlqpXr57PfO3bb7/VwoULVaxYsXQNNyC7iIyMVGRkpF555RVt3LjRe5P6pUuXKm/evHK5XNq3b1/AHQAj6Yr3zXj33Xd9fg6kg/ty587tvULC33Xs2NHn5/j4+ID64tnUJnnfvn21ZMkShYeHq1+/fmrdurURZ6L99ddfGj9+vKKjo1WwYEG9/PLLeuyxxyx9TsnOGjdurKlTp6pZs2ZXvM/lnj179Omnn6pTp042V+dfJh4Mkt25PB6Px+kiAk1ERITmzJmT4cbwyy+/qE2bNgEzuXnppZe0atUqhYaGqnHjxmrWrFmGR1GY5uzZswFzNsOiRYvUt29fdevWTZ06dUo3YT179qymTp2qcePGadiwYWrevLlDlWatK13b9HIC6cOLqSZNmqSOHTtmeHmvtMuD/fDDDzZV5l9pl0W66667VKBAgauODaQj2SMiIlS3bl3LZ2kE4vWqz549q6+//lpLlizRDz/84L2c5eOPP66OHTsG3FH8/7R8+XKNHz9eu3fv1r333qvnnnuOuUyAOHXqlD7++GPNmDFD58+f12OPPaZOnTqpSJEiTpfmd8eOHdPAgQO1cuXKyz7esGFDvfHGGypcuLDNlfmP1c9jgcbU3Jdz8eJFfffdd4qOjtZ3332n8+fPq3jx4mrZsqV69OjhdHlZ4lqvenHTTTf5qRJ7PfXUUypRooQGDx581XH9+/fXgQMHAuYgyMTERLVu3VqxsbEZNsnnzp3rvc9rdpf2+fuWW27JsJkSSAc9lStXTqmpqapevbpatWqVYfZAORPt7NmzevTRR3Xw4EG1bdtW9957r2688Ua5XC7Fxsbq+++/16xZs1SiRAnNnj07YL5fM/X9O7tftpSmih9EREQoNDQ0w0tKeDwenTt3LmC+dI2IiFDu3LlVuXLlDG/wGUhfwmUkJSVFa9euVXR0tFatWqUtW7Y4XVKWaNOmje64444Mb8w+YMAA7d69W7Nnz7apMvhD37591aJFC9WsWdOY+6hcq9jY2IA5Xbddu3bXNH7GjBl+qsRepk5mr+TkyZNatmyZli5dqi1btsjlcqlKlSoB8++dxuPxaOnSpZowYYL++OMP1a1bV926ddPdd9/tdGmO2rdvn6KjowPmy8eqVavq1KlTql69ujp27Jjh2XeBeIb1oUOH9NNPPykuLk7SpZu8Vq1aNSDvkTVmzBi1bt3auEtWRkREqEqVKpa+TA2kz2Pz589Xo0aNrnhvgdOnT+vrr79WdHS0NmzYoO3bt9tcIbLS4sWL1a9fPw0ePFgtW7a87JhFixapf//+eueddwLm4D7JzCa5lcu1/l2gHPRk8sGcJ0+e1BtvvKGvv/76so83atRIAwcOzPDgv+yEz6HpJSYmat++fSpQoMB123ShqeIHo0ePvqadfvfu3f1YjX1M/RLuSjZv3qwlS5Zo+fLlio+PV8GCBRUVFXXF+69kN5UqVdKYMWMyvNbl999/rx49eujnn3+2qTL4w7333quTJ0+qUKFCatq0qaKionjDV+A2TU3FZPbKDh06pOjoaC1ZskTR0dFOl5MlUlNTtXjxYk2YMEF//vmnGjRooOeeey4gv0y36ujRo1q6dKmio6P166+/KkeOHPrf//7ndFlZ4u9fTlxtnh6o98AzzZEjRzRo0CA9+uijuu+++y47Zu3atZozZ44GDhwYMJe4jIiI0J133mn5ps2B8nksIiJCOXPm1P3336/mzZurbt26ypEjx2XHnjhxImDuG/bdd99ZukznuXPnNHbsWL300ks2VGWPl156SUuXLtVdd92lWrVqpTuS/ZdfflGzZs30/vvvO12qXxw6dEgbN27UkSNHJAV2k9xUpp6J9ndp6/nRo0clSUWKFAnY9dzUg0EkadmyZfr666+VnJysBx54QM2aNdO4ceM0YcIEXbx4UZJUq1YtjRo16rq7pCNNFSAL/f77794vnA4fPqwcOXLo4sWL6tevn9q2bZvhGTzZSeXKlTVq1CjVrl37quMCrali6of01NRU/fDDD1qyZIm++eYbnT59WjfffLOaN2+uqKiogLtJXEYCvWlqKpoqZvnPf/6jAwcOqHr16urWrZvuuOOOq47Pnz+/PYXZ7NSpU1qxYoX3vmCpqakqW7asHnnkEUVFRQXMUYB/v+eZFdWqVfNTJfa6ePGizp8/n+4I/qNHj+qjjz7Snj17FB4erjZt2gTUDb2HDRum9evXa8GCBVdsonk8Hj388MOqVauWevfubXOF/mHq+9iuXbu0dOlSLVu2TAcOHFBYWJgaN26s5s2bB8y2fDkRERFq3LixXn311SteynDlypUaPHiw4uPjA+bzWJpZs2bp448/1v79+32WlyxZUh06dFDbtm0dqgwArs2yZctUq1Yt5cuXz7ssLi5OhQsX9vkeMS4uTgsWLAiY++DNmzdPr732miIjI5U7d25t2bJFTz31lGbMmKHHHntMZcqU0e7duzV37lx16dJFL7zwgtMl+6Cp4gfdu3fXgAEDjLhGMy5d8ietkbJ7924FBQWpRo0aioqKUvXq1VWvXj3NmDEj4G6MaPXyX6+//rr++OMPffbZZzZV5l+mfkj/uwsXLmj16tVaunSpvvvuO124cEF33nmnWrRooaZNmyo8PNzpEv3CpKbpwoULr/hYcHCwChUqpAoVKlzxMhvZVXa/pmtmdenSRf3791epUqW8yyZMmKBWrVr5XD7it99+0wsvvKCvvvrKiTKznNUzF9IE0pkLafcaWLx4sfdeAyVLllSDBg00ffp0ffLJJwE3b7kWgXQPvEGDBmndunU+2+3JkyfVvHlzHTt2TPny5dOpU6cUFBSkzz//XJGRkQ5Wm3UeeOABdejQQW3atLnquNmzZ2v69On68ssvbarMv0xtqvzdli1btGTJEn311Vc6fvy4ihQpombNmql58+YBs36n+eabb/T222/r1KlT6tWrl9q2bet9Pzt06JAGDRqk1atXq2HDhnr11Ve9998INLGxsd4zNooUKRIwl+O9ktOnT2vZsmXasmWLjh07JpfLpcKFC6ty5cpq2rRpwLx/pVmxYsU1jQ+Ue4tcTXa4LNK/deHCBS1fvlybNm1SbGysJKlYsWKqWrWqGjdunOE9ZrKbyMhIff75597375SUFJUvX17z5s3zOYs+0O7N/eCD/6+9O4+rqtz+B/45gGKKopAk3DBKU5xFQoUylEwLZdArSWKJKKaVpl7tQmHO4UgiZJalmHpzHphKC8scyKEcGux7E1NJURwQcLiAyO8PXpwfo6KdfbZ7r8/79bqvG+ecbG3Z+1n7rGc9zw6Au7s73nvvPQClkyxTpkzB+PHj8dprrxk/Fx8fb2xqfZDc+cm7dF9+++03vPjiixg/fjyGDh0q6vkDp06dwkMPPVRhydqKFSsqfKZBgwZ46aWXzB2aYnr16gWgdO/tqKgovPjii8Yl5fn5+WqGpqghQ4bg3//+Nx555BGEhYVVuXn73//+h+XLl2PTpk2YN2+eSlGa3rfffovQ0NA7XtcGgwGDBw/GypUrdTmpUrduXfTt2xd9+/bF9evXsWPHDqSkpGD+/PmYN28eunXrhuXLl6sdpknUNGk6btw446RpmzZtdDWhApTuXXw39erVQ1hYGMaNG2eGiMwjJyfH+GD2Mj/99BPatGmjuy+o5e3evbtCviouLkZsbCx69OhRYVKloKAAZ86cUSNERehlz+17FRUVha+//hp5eXmwt7dHUFAQ/Pz80KlTJ+Tn5yMhIUHtEFWh1+0cDx06hICAgAqvrVixApcuXcLMmTMRFBSEy5cvIzQ0FB9//DEWLVqkTqAmdvbsWbRs2fKun2vRosU9b7GiF5mZmbosxrm5ucHNzQ3vvvsu0tPTkZycjA0bNmDFihV44okn4Ofnp5sO3969e8PLywsffPABoqOjsXXrVkRFReHAgQNYsmQJHn74YSxduhQ9e/ZUO1RFNWvWTPcTKWXS09MxYcIEXL16FVZWVsZVtFevXsWmTZsQExODRYsW6aox4l6+a+ht+04tb4v0dxw6dAiTJk0yTqY0atQIQOlk0vr16/HBBx9g/vz5cHd3VzNMk6puvYOENRBnzpypUHvo27cvoqKiqvxuPTw88Mknn5g7vLvipIoCUlNTER8fj7lz52Lbtm2YOXOm7rpiqrNr1y6MHj0aH3/8sXFSpbi4GHPnzq3wOYPBgGbNmuHZZ59VI0yTa9SoEXJzc5GZmYn/+7//Q6tWrXSzT++d+Pv74+jRo4iLi8Pnn3+Obt26Gfe2LNv7Mjc3FyEhIejfv7/K0ZoOv6RX1KBBAwwYMACdO3fGypUrsW7dOqSnp6sdlslInTQ9ePBgje8VFxcjOzsbX3/9NZYsWQJ7e3vdbK+wa9cuvP7668afi4uLERISUqVDSAIJN/EDBgxQOwRVbNy4EQaDAV5eXpgxY4Yu9+C+F9Vt56in5p+srKwq30PS0tLw+OOPIygoCABgb2+PsLAwxMXFqRGiIqytrXHt2rW7fu7GjRu66nb18PC44/NUrly5gi+//BJJSUk4evSoroqPlVlYWODpp5/G008/jWnTpmH+/PlYs2YNYmNjdTOpAgD169fHu+++i8DAQIwbNw4vv/wyDAYDRo0ahTFjxsDa2lrtEBXz+++/Y/Xq1Th48CAuXLgAoPTZIl27dkVISMg9PehbC86fP4+xY8fC0dERc+fOhaenp3H8KiwsxL59+7BgwQK8/vrrSE5O1s2zGdLS0tQOQRWVt0V6++238euvv1a7LdKyZcseuG2R7ldGRgbCw8Ph5OSE+fPno1evXsbdEa5fv45vv/0WS5cuRXh4ODZu3IgnnnhC5Yjp77h582aF+5ayycHKDY316tUzTiQ+SDipooB69eph0qRJCAwMxLRp0xAUFIShQ4dixIgR1T4wTy97dG/atAne3t7VTpZs2rTJWJCaNm0aNm7cqJtJlb1792LPnj1ISkpCUlISNmzYgEceeQS+vr61enCglk2ZMgVeXl5YuXIlvvvuOxQWFgIoXcng5uaGYcOGwcfHR+UoTUvql/TqXLhwAampqUhKSsLx48dRt25dPP/88/D391c7NJOROmnasGHDO77fuHFjtGrVCtevX8fatWt1M6kitUOIZImIiEBSUhL27t2L559/Hk899RT8/PzQt29fMaurJW3nWFRUhHr16hl/zsvLw8mTJ6tsi+Xs7IzLly+bOzzFtG7dGjt37rxrh35aWhpat25tnqDMoLoHz9+8eRNff/01kpOTsW/fPhQXF6NNmzYingP366+/Ijk5Gampqca96V988UW1wzK5q1evYs2aNTh79iyaN2+OM2fO4Oeff0Z2drYuVyMBQEJCgvEh9K1atTI+5/PcuXPYsmULtmzZgkmTJiE0NFTFKE1r9erVsLGxwZo1a4yd+2Xq1q2Lnj17ws3NDQEBAVizZg0mTpyoUqSmVdvmj9zcXGRkZOimWWTVqlUYMmTIXbdFsre3R3Jysm4mVZYsWQIXFxd88cUXFe5fgNKGzv79++O5555DSEgIPvzwQyxcuFClSElJWvlOwkkVBbVs2RKrV69GfHw84uPjsXLlymo/p5cOoSNHjmDy5Ml3/dwzzzyDmTNnmiEi87CyskLPnj3Rs2fPCl9aPv/8c6xYsQIGgwFffvklHB0d8eijj6odrsk999xzeO6551BcXIycnBwAQJMmTXRVkChP6pf0Mrm5ufjqq6+QnJyMH3/8EQaDAd26dcP777+P559/XnfP2JA8aVobnp6eWL16tdphEN2XV199tcb36tSpAzs7O3Tt2hX+/v666vQNDQ1FaGgoTp06haSkJCQnJ2PKlCmYMWMGunbtCoPBgNu3b6sdpslJ3c6xefPmOHLkCDw9PQEAe/bsAQDjz2WuXr1apUinZYMGDUJUVBTc3NxqXJW2detWbN68GbNmzTJzdMqrvJ3d//73Pzz88MMoLi7GwoUL4evrq3aIivnzzz+RnJyM5ORknDlzBvXr10efPn3Qv39/eHp6wsLCQu0QTWrLli3GrZbff/99DBw4EPv27cP06dPRv39/vPbaawgPD6+2uVOrdu3ahTlz5hhX55TtllAmKysLixcvxty5c9GiRQv06NFDpUhNKz09HcHBwXccq21tbREcHIwdO3boZlKltn744QeMHz9eN/U1rW+LdL9++OEHREZGVplQKe+hhx5CWFiYiK18tTK58HdMmjSpynetCRMmVGhSLigoMHdYtcJJFQUVFxdj+fLl+Oyzz/DEE08gNDRUVzczlV25cqXKw+8sLS3x9ttvV3i9cePGuHLlirnDM4uHHnoI/v7+8Pf3R05ODlJTU5GSkoIvvvgCa9euhbu7e7UdZFpU+UFalpaWFfbe1yupX9KTkpKQkpKCvXv3oqioCB06dEBERAR8fX11/XuXPml6NwUFBbCy0v+thISb2ZMnTxqLyWXPlTl58mSVz+iJjY1Njb/b4uJiZGRkIDU1FStWrMCqVatgb29v5giV5eLigrFjx2Ls2LE4duyYsZu7pKQEY8aMQd++fREYGIhu3bqpHapJSN3OcdCgQcYuzocffhgfffQR7O3tq6wY379/v6620BgwYAB2796NyMhIrF69Gj169ICTkxMMBgPOnTuHPXv24JdffoGvry8CAwPVDtdkym9nl5OTg8aNG8Pf3x9+fn548skn0a1bNzRt2lTtME3uwoULSElJQXJyMo4fPw4rKyt4e3tjwoQJ8PHx0e3q8VdeeQWHDh3CwIEDMXnyZOMOGF5eXkhKSsLSpUuxdOlSJCcnY+rUqboZz1esWIE+ffpgzpw51b7v6OiI6OhoXL9+HZ999pluJlUyMzPRvn37u36uffv2unm+pWRa3xbpfuXl5dXqGUnNmjVDXl6eGSIyHy1PLtyv6mpqNY1zD+IzdPRfCVHJjz/+iGnTpuH06dN47bXXMGrUKF1PqAClS/GuXr1a5fWwsLAKP1+9elVXD9GqSZMmTRASEoKQkBCcO3fO2A2qF1K3xJH6JX3y5Ml4/PHHMXr0aPj5+aF58+Y1fnb//v26+dJWnqRJ09ratm2b7p41UpubWaB0oiUxMdGcoSmqum1gJk+eXGHSoaSkRFcTTEuWLLnrZ/766y+8+uqr+OCDD3Q1UV5Zx44d0bFjR0RGRuKHH35AYmIivvnmG2zdulU3HZ9St3McMmQIMjIy8OGHH+LWrVtwcnJCTExMlS3Btm3bhlGjRqkYqenFxMTA3d0dCQkJWLp0aYX3mjdvjilTpmDIkCEqRaeMkJAQ4yri4cOH4+mnnzY2P+h58rBnz54wGAzw8PDAjBkz8MILL9S4lenNmzerFCW16urVq1i9enW1haa6deti3Lhx8PPzw7Rp0xAaGqqb8fyXX34xbv11J//85z8xadIkM0RkHteuXbvrFr1A6Ta+tdmumrRJT/fi1WnWrBmOHz+Op5566o6f++2332o1+aIVWp9cuF9aX23ESRUFvPvuu9iyZQs8PDwQFxcHFxcXtUMyC1dXV3z77bfo3bv3HT+3c+dOXW6LdCdOTk547bXXKux9Sdol8Ut6+eciVef48eNITExEamoqsrOzdfOlrSZ6nzTdsWNHje8VFxfj0qVLSEtLw8GDB/Hpp5+aMTJl3cvNrJ58/vnnaofwwHr00UcxZswYLF68WO1QzMJgMMDT0xOenp6YPn06vvvuO7VDMhmp2zlaWlpi2rRpiIiIwI0bN6qdSKpfvz62b9+uuy08ARhz9YULFyo8yFovD3CurFWrVvjvf/+LgwcPwtLSEjk5Oejdu7cuf7flvf322/D19a3x91p5O7TDhw+bOUJlbNmy5a4rhh9//HGsXLkS27ZtM1NUyrt169YdtwYqY21tjVu3bpkhIvO4fft2rQvqUhsg9UbiyoXevXvjo48+Qo8ePWqspZ4+fRqffPIJAgICzBucgrQ+uSCVoYSjrcl1794d//73v2vcGkivEhMTERkZidmzZ9fYob9t2za88847mDNnDvz8/MwboJmcO3cOBoOhylZoWVlZKCkpqbLnq1a5urpi+fLlaNu2ba0+X7YcXW+kfEmvTmZmpnHP6pMnTxq3ygoMDMRzzz2ndnj0N7i6ut7xfQsLC3To0AFjx441PhiUSK9++OEHjBw5Er/88ovaoSguLy8Pp06dQpMmTXT7cGOg+gd3A8DLL7+MsLAwkds5kn6cOHECiYmJSElJwdmzZ1GvXj14e3ujV69eiIyMxOeffw4PDw+1wzSL8tuhXb16FXZ2dujfv3+1qzNJOwYOHAhPT8+7Ps913rx5+OGHH7B582YzRaYsV1dXNG/e/K7PeSsoKEBmZqbum9wq2759u66eqXKv45ReivJ5eXkICgrC+fPnERgYiF69ehlra1lZWfjuu++wdetWNGvWDBs2bKjV6i3SDq3VUzmpooCcnBw0adIE169fR2pqKg4fPoxLly7BYDDg4YcfRpcuXeDr66ubZcfl/etf/0JKSgo6duyIp59+Go6OjjAYDDh//jz27t2Lo0ePol+/frVarqtVrq6usLKyqlJ8adeuHUpKSvDbb7+pFJlpubq63tPSU73c3Eh35coVfPnll0hKSsLRo0cBlHby//LLL/jss8/g5eWlcoTK0lqSv19nz56t8T0rKys0btxYVw/uJrqTDRs2YPHixdi9e7faoZhMamoqvv76a9y6dQsvvPAC+vXrhyVLlmDp0qXGfbmffvppLF68WPdbtpbfzvHw4cMwGAy63s5RSh6rTOpxl00qbN++HVeuXIHBYEDv3r3x6quv6nZi5Y8//kBycjKSkpKQlZWFOnXqoKioCJGRkQgJCTE+P0yPpJznq1evxty5czFz5swamzm3bt2KKVOmICIiAiEhIeYNUCFSi+y1bca9du0azp8/z7qDDly6dAnTpk1DWlpate/37t0bU6dO1fWzXaWM55VprZ7KSRWFpKenY8KECbh69aqxAAWU7nt669Yt2NvbY9GiRbq8mV2zZg0SEhKQmZlZ4XVnZ2eEhobq5qamJnFxcbCwsMAbb7xR4fX4+HgAwJtvvqlGWCbn6uqKMWPG3PHZGuXpdeWWlGSXmJho7Oi9desWWrVqhf79+6N///6wsbFB165dsWrVKl2OaeVpLcmbg96es1GelOv71VdfrfVnDQYDVq5cqWA0D5azZ8/ilVdegZeXl26eqbJx40ZERUWhTZs2aNCgAQ4fPoxhw4Zh1apVGDx4MFq0aIH//ve/2LBhA8LDw/HWW2+pHbLZlN/OMSkpSe1wFCE1j0k97jLFxcXYs2cPkpOTkZaWhps3b8LJyanGgpXWnD9/3njd/ve//4WlpSW6d++O/v37o1u3bujVqxfvU3V0nt++fRtvvvkmdu7ciSeeeALe3t7Ge7Jz585h9+7dyMjIgI+PD+Lj43V7nypFRETEPf0O9TKZRKXX84EDB5CdnQ2gdGcQDw8P3XwHuxMp43llWqun8pkqCjh//jzGjh0LR0dHzJ07F56ensY9DwsLC7Fv3z4sWLAAr7/+OpKTk3W3XVDZ3sXnz583Dn4ODg66eojUnYwdO7ba1x+0i98UevXqhY4dO6odhqp8fHyqTXa9e/fWVbJ7++23YTAY4OXlhYiICDz55JPG9/T84NPK3njjDVhYWFR5fcyYMSpEo67CwkJs2bIFy5cvx/bt29UORxFSrm8bG5u7flm9fPkyjhw5oqvCxOjRo2t87/bt27h06RL+7//+D87OzpgwYYIZI1PWqlWrMGTIELz33nsASidZpkyZgvHjx1d49pu9vT2Sk5NFTapIeAae1Dwm9bjLWFpawtvbG97e3vjf//6Hb775RlfPguvVqxeA0mJTVFQUXnzxRePzg3ifqr/z3MLCAh9++CFWrVqFzz//HCtWrKjw/qOPPop33nkHQ4cO1dV9i1Rz5sxRO4QHgpRmr/KcnJxqXI2md1LG88q0Vk/lShUFLFiwAMnJyUhMTESjRo2q/Uxubi4CAgLg7++PiRMnmjlCor/P1dUV69evFz+porWZ9Ps1ZswY7NmzB0VFRXjsscfg5+eH/v37w8XFBfn5+fDw8BDRASjJX3/9hdTUVGRlZcHZ2RkDBgxAkyZNUFBQgFWrViEhIQGXLl2Cu7s71qxZo3a4ipByfd/JxYsX8emnn2LdunWoU6cOhg4dqpsi+yuvvFLje1ZWVrCzs4OHhwcCAgJ0tWWrm5sblixZAk9PTwAwjuGrV6/GU089Zfzc/v37ER4ejmPHjqkVqkkVFRWhoKCgygO7L168iOXLlyMjIwNNmzbFyy+/jPbt26sUJRHdj27duiE3Nxe2trbo27cv/Pz8jPekvE/Vv/Pnz1d4xqWUZk6JRXbJpK1ckPg4BdIerlRRQHp6OoKDg2ucUAEAW1tbBAcHY8eOHbqdVGGSJwm0NpN+vz766CPk5ubiq6++QnJyMj788EN8+OGHaNeuHXx8fNgFpjNHjhzB8OHDcfPmTeNr//nPfxAXF4fx48fj9OnT6NKlC+bPn28szOqRlOu7OhcuXMCyZcuwceNG1KtXD6NGjcKrr75apSCtZXp9Zsbd3Lx5Ew0aNDD+XPbMlMpfTuvVq2d8vooezJkzB3v27Kmwsi4nJwcDBgzApUuXYGtri2vXriEpKQnr1q1DmzZtVIyW6P6UTfrXhsFgqNI0oFV79+7Fnj17kJSUhKSkJGzYsAGPPPIIfH194e3trXZ4pLBmzZqJmUgpT8qK6sqk1pkkrVy40+MUNm3ahJiYGN0+ToG0hZMqCsjMzKxVh1v79u2xfPlyM0SkDqlJXkoHQXR0NJydndUOg8zI1tYWgwcPxuDBg3HhwgUkJSUhJSUFixcvBgAsXLgQwcHB6NOnj+4fbKx3cXFxaNq0KebOnYu2bdvir7/+wvTp0zFkyBBYWVkhLi4Ozz//vNphkgKysrKwdOlSbNmyBTY2Nnj99dcREhJSoQhP+qT3yfFDhw4hICCgwmsrVqzApUuXMHPmTAQFBeHy5csIDQ3Fxx9/jEWLFqkTKNHfEB8fD2tra1hbW+NuG1LoaVLFysoKPXv2RM+ePXHz5k18/fXXSE5ONm4NZTAY8OWXX8LR0RGPPvqo2uGSibHIXpEei+zlSa0zSWn2kv44Bem0Vk/lpIoCrl27hoYNG971cw0bNsS1a9fMEJE6pCb5wMBAWFpaVnk9ICDgrl9utKR///4oKCio8nrlbTSCg4PRoUMHFSIkJT3yyCMYOXIkRo4ciYyMDCQmJiI1NRURERGYMWMGfvrpJ7VDVITWkvz9+v333xEZGQk3NzcAQIsWLTB9+nS8+OKLmDlzJidUdCgzMxMff/wxtm7disaNG2PixIkIDg5GvXr11A7NbCQVZSZNmgRra+sKr02YMMH4pRVAtTley7KysqqsPklLS8Pjjz+OoKAgAKXPkQkLC0NcXJwaIZqFlDxWmZTjfuSRR3D58mW4u7vDz88PPj4+osZxoHTVnb+/P/z9/ZGTk4PU1FSkpKTgiy++wNq1a+Hu7q7blYpSzvPKWGSvSG9F9sqk1pmkWL16NWxsbLBmzZoqu//UrVsXPXv2hJubGwICArBmzRrd7vwjdTzXWj2VkyoKuH37dq27/R7Ek8JUpCb5mh6k9v7775s5EmVxG41SUpLdV199BXd3dzRt2rTKey1atMCECRMwYcIEHD58GCkpKSpEaB5aS/L36/Lly1VWopX93Lp1azVCUoWU6zsiIgLJyclo2rQpIiMjERQUVKG4LoWUosyAAQOqvFbTCmt3d3elwzGboqKiCsXlvLw8nDx5EsHBwRU+5+zsjMuXL5s7PLORkscqk3Lcu3btwqFDh5CcnIyZM2ciKioKzz33HPr3749nnnmm2r8DPWvSpAlCQkIQEhKCc+fOISkpCcnJyWqHpRgp53llLLLLIrXOJAUfp1BK6niutXoqH1SvAFdXVzRv3rxKB2BlBQUFyMzMxPHjx80UGZHpBAQEoG/fvnj99deNr8XExOCTTz6pso1GixYtdLuNRkREBCwtLTF79uwKr7/zzjsoKSlBdHS0SpGZlqurKwwGAx599FF06dIF7u7ucHd3R4sWLdQOjRTg6uqK9evXo2PHjsbXiouL0a5dO2zevBlt27ZVMTrzkXR9A8Bjjz1218kUg8GAxMREc4RldnFxcbCwsKiyHU7ZMwr4ZV3bAgIC8MILLxiLbKmpqfjXv/6F2NhY9OnTx/i5b775BtOnT8fu3bvVCpXIJIqLi7Fnzx6kpKQgLS0NderUQd++fREUFFSrraqJiOjBIaXZq2vXroiJicEzzzxzx8/t2bMHEydOxIEDB8wUGVFVXKmigOo6AGuipw5AKlVUVISNGzfi559/xvnz5/Hee+/BxcUFqampaN26tW6K0NxGo5TWZtLv15YtW/Djjz/i8OHDOHDgALZt2waDwYBGjRrBzc0N7u7u6NKlCzp06CCyw12PqtseCKi6RZCei+xSru/AwEDdP0+jNtj5qG+DBg3CwoULAQAPP/wwPvroI9jb2+PZZ5+t8Ln9+/fjiSeeUCNEIpOytLSEt7c3vL29UVBQgNjYWCQkJODy5cv39EB7LZK0nSPJJaXITqWkrFzg4xRk01o9lZMqCtBL5+rfJTHJZ2ZmIjQ0FDk5OWjbti1+/PFHXL9+HQBw8OBB7N69WzfnB7fRkKVNmzZo06YNhg4dCqD0AXI//fST8X+LFi3C7du3UadOHXTo0AFr1qxROWJlaC3J36+amgPY2apPNU0ekQxSio9DhgxBRkYGPvzwQ9y6dQtOTk6IiYmpci+zbds2jBo1SsVIlSUlj1Um9bgzMjKQkpKClJQU/PXXX/D09MSgQYPUDktxUrZzrEzqeS6VlCJ7ZRLrTICcZi8+TqGUxPFci/VUTqqQYiQm+VmzZsHOzg4bNmxAo0aNKhQgPTw8EBMTo2J0ptW8eXMcOXIEnp6eAEqXXwIw/lzm6tWrd9wPU+skJjsAaNasGXx9feHr64vi4mIcPHgQCQkJ2LVrl24fUq/FJH+/9HIcf5fU65tkkVJ8tLS0xLRp0xAREYEbN27Azs6uymfq16+P7du3w8bGRoUIlScpj5Un7bjPnj2LlJQUJCcn448//kDnzp3x6quv4oUXXoC9vb3a4ZmFxGdsSDvPy2ORvSK9Fdkrk1hnkqamHRPKKygoMFM05id1PNdiPZWTKmYgpQOwMolJ/sCBA1i4cCHs7OxQXFxc4b2mTZvi4sWLKkVmetxGQ26yy8vLw+HDh42rVH755RcUFRWhdevWCAkJgZubm9ohKkKLSZ7un9TrG5B73yK1KCOt+FivXr0Kq1PKs7KyQpMmTcwckflIzWOSjjs4OBhHjx6Fq6sr/P390a9fvypjuQQSt3OUdJ5XxiK7LBLrTICcZi8+TkHueK7FeionVcxASgcglXZB1nTjdunSJdSvX9/MESmH22jISnZbtmwxTqRkZGSgcePG6Ny5M3r06IFx48ahQ4cONRap9EKLSd5UJBbZJV3flUm9b5FalJFYfARkjmtS85ik4z5y5Ajq16+PW7duYdu2bdi2bVuNn9XzM9EkknSeV8Yiu76L7CSr2Usvx/F3SB3PtVhP5aSKGUjrACwjMcl7eHhgxYoVePbZZ42/c4PBgJKSEqxfv77K1lhaxm00ZCW7yMhIPPTQQxg4cCBiY2N1ef3ejRaTvKlILLJLur4rk3rfIrUoI5XEcU1qHpN03IGBgbXei570RdJ5TrKK7JVJrDNJbvaSSOp4rsV6KidVzEBiB6DUJD9p0iS8/PLL6NevH3x8fGAwGLBmzRr88ccfOH36NDZs2KB2iCYneRsNSckuNDQUhw8fxrp167B582a0b98ebm5u6NKlCzp37ozGjRurHaLitJjkTUVikV3S9V2ZxPsWkkfiuCY1j0k67pomh6WRuJ2jpPO8MhbZ5RTZpdaZJDd7SVxZLHU812I9lZMqpAipSb5FixbYtGkT4uPjkZycDEtLS3z33Xfw9PTEggUL0Lx5c7VDVAyTnb6TXUREBIDSB8IdO3bMuBXYunXrkJeXh8cee8w4yeLm5oaWLVuqHLHpaTHJm4rEIruk65tKSSzKADKLj4DMcU1qHpN63JJJ3M5R6nnOIrusIrvUOpPkZi+JK4uljudarKdyUoUUITXJA4CzszPmzp2rdhhmx2QnI9lZW1vDw8MDHh4extcyMjLw008/IS0tDVOnTgUAXf6+tZjk6f5JvL4lk1qUAWQWH6WSmsekHjcgs+kJkLmdo9TznEX2qvRcZJdaZ5Lc7CVxZbHU8RzQXj2VkypmILEDUGqSv3btGm7cuAEHB4cq72VnZ6NBgwZo0KCBCpEpj8lOVrID/v9kStn/Tp8+DQBo1KiRypEpR2tJnu6f5Otb4n2L1KIMILP4KJnUPCb1uCU2PUkm8TxnkV1WkV1qnUlys5fElcWAzPFci/VUTqqYgcQOQKlJPioqCg0aNMDs2bOrvBcXF4cbN25g4cKFKkSmPCY7fSssLMSxY8eMEyiHDx9GXl6escuxS5cuCA0NRZcuXdCqVSu1w1WEFpO8qUgssgNyru/KJN63SC3KSCZxXJOax6QeNyCz6QmQuZ2j1POcRXZZRXapdSbJzV4SSR3PtVhP5aSKGUjsAJSa5A8dOmTc/qgyb29vTJ8+3cwRkZIkJbsuXbqguLgYFhYWaNWqFfr37w93d3e4u7vjkUceUTs8s9BikjcViUV2Sdd3ZRLvW6QWZQCZxUdA5rgmNY9JPW5AZtOT1O0cpZ7nLLLLKrJLrTMBcpu9JJI6nmuxnspJFVKE1CSfm5tbY5HtoYcewtWrV80bEClKUrIbNWoUunTpgs6dO8PGxkbtcFShxSRvKhKL7JKub5JblJFafARkjmtS85jU45ZK6naOUs9zFtllFdml1pkkN3tJXFksdTzXYj2VkypmILUDUGKSd3Z2xr59++Dl5VXlvfT0dPzjH/9QISrzYLKrSG/Jbty4cWqHoDotJnm6f5Ku78ok3rdILcpILT5KJTWPST1uqaRu5yj1PGeRXV6RXWKdSXKzl8SVxVLHcy3WU6tusEomlZmZiRdeeAHz58/HmTNnkJ6eXqED8NNPP1U5QmVcu3YN2dnZ1b6XnZ1t/DvQm6CgICQkJGDZsmW4cuUKAODKlSv49NNPkZCQgJdeeknlCJUTGBiIgICAKq8HBARU+7oeSE12AHDu3DlkZWVVeT0rKwvnzp1TISLllSX56jyoSd5UioqK8MUXX+Cdd95BWFgYTp06BQBITU1FRkaGusEpROr1LfW+pawo4+bmVqEo07x5c2zYsEG3RZkDBw5gzJgxsLOzg8FgqPCenouPgMxxTWoek3rcQGnTU/nJ0jLt2rVD27ZtVYhIeVK3c5R8npcV2ffs2YNffvkFe/fu1fWEClBaZI+Nja32vbi4OLz33ntmjsg8pNaZDh06hJ49e1b7nre3Nw4cOGDegMxozpw51U4mvf/++7pdTS11PNdiPZUrVRQmtQNQ6kx6aGgozpw5g5iYGMTExMDS0tLYIRUcHIywsDCVI1SOxG00tDiTbio+Pj7Vrkzq3bu3blcmBQUFYeHChbC1tcU///lP2NnZ4cqVK9i8eTMSEhIwceJEtUNUhNTtgaRe31LvWwCZnY9Si49SxzWpeUzqcQMyO3ylbuco9TyXumJD6opqqXUmqc1eUkkdz7VYT+WkisKkLj+WmuQNBgOmTp2KYcOGIT09Hbm5uWjcuDG6d+8OFxcXtcMjE5Oa7ADgjTfeMH5RLW/MmDEqRGMeWkzypiC1yC71+pZ63yK1KCO1+Ch1XJOax6QeNyCz6Unqdo5Sz3MW2avSc5Fdap1JarMXIHNbYqnjuRbrqZxUUZjUDkCpSb6Mi4vLA3vRK4XJTk6yA4CxY8dW+/qbb75p5kjMR4tJ3hSkFtmlXt9S71ukFmWkFh+ljmtS85jU45ZK6jM2pJ7nLLLLKrJLrTNJbfaSurJY6nheRkv1VE6qKExqB6DUJA8AxcXFOHr0KM6fP4/CwsIq7wcGBpo/KIUx2clMdlJpKcmbgtQiu9TrW+p9i9SijNTio9RxrYy0PFZG4nFLbHoCZG7nWEbaec4iu6wiu9Q6k9RmL6kri8tIG88B7dVTOamiMKkdgFKT/K+//oqxY8ciKyur2i/rBoPhgRsETIHJTl6yk0prSd4UpBbZy0i7vqXet0gtygAyi4+SxzWJeQyQedxSm56kbucIyDzPWWSXVWSXWmeS2uwldWUxIHM812I9lZMqCpPaASg1yU+bNg02NjZYuXIlWrZsiTp16qgdklkw2clKdgDg6upa7YPq27Vrp9sH1WsxyZuC1CI7IPP6lnrfIrUoI7X4KHVck5rHpB631KYnqds5Sj3PWWSXVWSXWmcqI63ZS+rKYqnjuRbrqZxUMQOJHYBSk/yJEyewaNEidO3aVe1QzIrJTlayA0qLyZaWllVeDwgIqPFc0DotJnlTkFpkl3x9S7xvkVqUkVp8lDquSc1jUo9batOT1O0cpZ7nLLLLKrJLrTMBMpu9pK4sljqea7GeykkVhUntACwjLcm7uLgYl9VLwmQnK9kBwJw5c6p9/f333zdzJOajxSRvKhKL7FKvb6n3LVKLMlKLj4DMcU1qHpN63FKbnqRu5yj1PGeRXVaRvYy0OpPUZi+pK4uljudarKdyUkVhUjsAAZlJPjIyErNnz9b1gx+rw2QnK9lJpcUkbwpSi+xSr2+p9y1SizJSi49SxzWpeUzqcUttepK6naPU87wMi+wV6bXIDsisM0lt9pK6sljqeK7FeionVRQmtQNQapKfOXMmLl68CD8/Pzg4OKBhw4YV3jcYDEhMTFQpOuUw2clTVFSEjRs34ueff8b58+fx3nvvwcXFBampqZpKgvdCi0neFKQW2aVe31LvW8pIK8pILT5KHdek5jGpxy216Unqdo5Sz3OARXZJRXapdSapzV6AzJXFUsdzLdZTOamiMKkdgFKTfLt27WAwGNQOQxVMdnKSXWZmJkJDQ5GTk4O2bdvixx9/NBafDx48iN27dyM6OlrlKE1Pi0neFKQW2aVe31LvWwCZRRmpxUep45rUPCb1uKU2PUndzlHqec4iu6wiu9Q6k9RmL6kri6WO51qsp3JSRWFSOwClJvmanjOhd0x2spLdrFmzYGdnhw0bNqBRo0Zo37698T0PDw/ExMSoGJ1ytJjkTUFqkV3q9S31vkVqUUZq8VHquCY1j0k9bkBm05PU7Rylnucssssitc4ktdlL6spiqeO5FuupnFRRmNQOQKlJXiomO1kOHDiAhQsXws7Ozlh8K9O0aVNcvHhRpciUpcUkbwpSi+xSr2+p9y1SizJSi49SxzWpeUzqcUtteiojbTtHqec5i+yyiuxS60xSm72kriyWOp5rESdVFCa1A1BqkgeAvLw8bN++HX/++We124dERUWpEJWymOxksbS0rLaTGwAuXbqE+vXrmzkiUpLUIrvU61vqfYvUokwZacVHqeMaySK16QmQuZ2jVCyyyyqyS60zSW32krqyWDKt1VM5qaIwqR2AUpP8qVOnEBwcjMLCQty8eRN2dnbIzc3FrVu3YGtrCxsbmwduEDAFJjtZPDw8sGLFCjz77LOwsLAAUHpNl5SUYP369fD09FQ5QuVoLcmbgtQiu1RS71ukFmUAmcVHyeOaxDwGyDxuqU1PUrdzBGSe5yyyyyK1ziS12UvqymJA5niuxXoqJ1XMRFoHoNQkP2fOHHTq1AmxsbHo3LkzPvnkE7i6uiI1NRUffPABYmNj1Q5REUx2spLdpEmT8PLLL6Nfv37w8fGBwWDAmjVr8Mcff+D06dPYsGGD2iEqQotJ3hSkFtkBmdd3GWn3LVKLMlKLj1LHNal5TOpxS216krqdo9TznEV2WaTWmaSSurJY6niuxXoqJ1XMQGIHoNQkf+zYMcyePRt169YFABQVFcHS0hJ+fn7IycnBrFmzsHbtWpWjND0mO1nJrkWLFti0aRPi4+ORnJwMS0tLfPfdd/D09MSCBQvQvHlztUNUhBaTvClJK7JLvb4BmfctUosyUouPZaSNa1LzmNTjltr0JHU7R6nnOYvsskitMwEym72kriyWOp5rsZ7KSRWFSe0AlKqwsBA2NjawsLCAra0tsrOzje89+eST+P3331WMTjlMdrKSHVD6RX3u3Llqh2FWWkzypiKxyC71+pZ63yK1KCO1+AjIHNek5jGpxy216Unqdo5Sz3MW2WUV2aWS2uwldWWx1PFci/VUTqooTHIHoMQk7+LigrNnz8LDwwNt27bFf/7zH3h5ecHKygrr1q2Dg4OD2iEqgslOVrK7du0abty4Ue35nJ2djQYNGtS43YSWaTHJm4LUIrvU61vqfYvUoozU4qPUcU1qHpN63FKbnqRu5yj1PJdKapEdkFlnktrsVUbaymKp47kW66mcVFGY1A5AqUm+X79+xgHurbfewogRI9C1a1fjQ7z1XrRhspOR7KKiotCgQQPMnj27yntxcXG4ceMGFi5cqEJkytJikjcFqUV2qde31PsWqaQWH6WOa1LzmNTjltr0JHU7R6nnOcAiu6Qiu9Q6k9RmL0DmymKp47kW66mcVFGY1A5AqUl++PDhxn/u3LkzkpOT8f3336OgoADdu3dHq1atVIxOWUx2cpLdoUOHMHXq1Grf8/b2xvTp080ckXloMcmbgtQiu9TrW+p9CyCzKCO1+Ch1XJOax6QedxlpTU9St3OUep6zyC6ryC61ziS12UvqymKp47kW66mcVFGY1A5AqUm+MkdHRwwePFjtMBTHZCcr2eXm5ta4vddDDz2Eq1evmjcgM9FikjcFqUV2qde31PsWqUUZqcVHqeOa1Dwm9bgBmU1Pes3PdyP1PGeRXVaRXWqdSWqzl9SVxVLH88q0UE/lpIrCpHYASk3ygMwvL0x2spKds7Mz9u3bBy8vryrvpaen4x//+IcKUZmfFpK8KUgtsku9vqXet0gtykgtPkod1yqTkscqk3LcUpueqJSU85xFdllFdql1JqnNXlJXFlcmZTwHtFdP5aSKwiR3AEpM8lK/vDDZlZKS7IKCgrBw4ULY2trin//8J+zs7HDlyhVs3rwZCQkJmDhxotohKkZrSd4UpBbZK5NyfUu9b5FalJFK8rgmMY8BMo9batMTIHM7R0Dmec4iu6wiu9Q6k9RmL6kriwGZ47kW66mcVFGYXpPZ3UhN8lK/vDDZyUp2oaGhOHPmDGJiYhATEwNLS0sUFxcDAIKDgxEWFqZyhMrQYpI3BalFdkDm9a3X/Hw3UosygMzio9RxTWoek3rcUpuepG7nKPU8Z5FdVpFdap2pMinNXlJXFksdz7VYTzWUVPcbIjKxrKwsEUnezc0NixYtgre3t9qhmNWBAwcwe/ZsxMTEMNmVYzAYcPz4cRUiM49Tp04hPT0dubm5aNy4Mbp3767rB6EGBQWhoKAAUVFRNSb5yt3OpF3Sr29pBg0ahKFDhyIwMBDDhw9HSUkJ4uPjYWVlhYiICPz222/YsWOH2mGaXG2Kj2lpaWqHSSYiNY9JPe4BAwYgPDwcvr6+aodiVqNHj0ZJSYlxO8dNmzZV2M5x8eLFaN++vdphmpzU83zFihW4cOECIiIicOTIEYwYMQI3b96sUGT39/dXO0xSiJQ6EyCz2cvPzw8XL15EXl6eqJXFUsdzLdZTuVLFDCR2AFYmZSZd6ooNqdtoaHEm3ZRcXFx0PYlSmdSOT6kkX98S71ukdj5KfZaMVFLzmNTjltrhK3U7R6nnudQVG4DMIntlUupMUlcuSF1ZLHU812I9lZMqCpO6/BiQmeSlfnlhspOV7ACZ17cWk7ypSCyyS72+pd63SC3KSC0+AjLHNal5TOpxS216krqdo9TzvDIW2UvptcgOyPweKrXZS69NTXcjdTzXYj2VkyoKk9oBKDXJS/3ywmQni9TrW4tJ3hSkFtmlXt9S71sqk1KUkVp8lDquSc1jUo9batOT1GdsSD3PARbZJRXZpX4PldrsJZXU8VyL9VROqihMageg1CQv9cuLVFKTndTrW4tJ3hSkFtmlXt9S71sAmUUZqcVHqeOa1Dwm9bilNj1J3c5R6nnOIrusIrvU76FSm70AmSuLpY7nWqynclJFYVI7AKUmeb3epNcGk52cZCf1+tZikjcFqUV2qde31PsWqUUZqcVHqeOa1Dwm9bilkrqdo9TznEV2WaR+D5Xa7CV1ZbHU8VyL3zs4qaIwqR2AUpO8VEx2ski9vrWY5E1BapFd8vUt8b5FalFGavFR6rgmNY9JPW5AZtNTZVK2c5R6nrPILqvILvV7qNRmL6kri6WO51rESRWFSe0AlJTkZ82ahbCwMDg5OWHWrFl3/bwev7ww2cki6fomuUV2qde31PsWqUWZyqQUH6WOaySL1KYnQOZ2jlKxyC6ryC71e6jUZi+pK4sl0Xo9lZMqCpPaASgpye/cuRODBg2Ck5MTdu7cecfPGgyGB24QMAUmO1kkXd9aT/KmILXILpXU+xapRRlAZvFR0rgmNY9JPe7ypDY9SdrOkec5i+zSSPoeWp6e7kvuhaSVxVLHc63XUzmpYmZSOgAlJfnyF/7dBgG9YrKr2YM26JuCtOtby0neFCQV2Xl9VyXlvkVqUUZS8bE8SeOa1Dwm9bjLk9r0JGk7R57nLLJLI+l7KMlaWSx1PNd6PdVQUt03KDIpiR2Akl25cgUrV67E0aNHcfHiRTRt2hSdOnXCsGHDYGdnp3Z4ihg0aBCGDh2KwMBADB8+HCUlJYiPj4eVlRUiIiLw22+/YceOHWqHaRI+Pj5YsmQJXF1d4ePjc8fPGgwGpKWlmSkyIvq7eH2Xknjf4ufnh4sXLyIvL09UUSYoKAgFBQWIioqqsfhY+e+CiLThqaeewkcffQQPDw9069YNM2fORJ8+fQAA6enpGDNmDI4cOaJukApwc3PDokWL4O3trXYoZAYRERF3LbJHR0ebKRoi02GzF7BixQpcuHABEREROHLkCEaMGIGbN29WWFns7++vdphkQlqrp3JSRWG16QA8fvy4CpGREo4ePYqRI0fi9u3b8PLygr29PS5fvox9+/YBAJYvX45OnTqpHKXpMdmRFFpL8qYiscguldT7FqlFGcnFR6njmtQ8JvG4JTU9lTdgwACEh4fD19dX7VDMTuJ5LgmL7LKw2auqrKws3a4srkzieK7FeionVRQmqQOQSR4YOHAgrK2tsWzZMtjY2Bhfz8/PR3h4OIqKirBp0yYVIzQPJjt9JzsAyMvLw/bt2/Hnn39WW4zS4/WtxSRvClKL7IDM61vSfQvJLT5KHdek5jGpxy216enAgQOYPXs2YmJiRG3nKPU8l0RqkZ11JpJG6niuxXoqJ1UUJqkDUGqSL69jx46IjY1Fr169qryXlpaGCRMm4NixYypERkqQmuxOnTqF4OBgFBYW4ubNm7Czs0Nubi5u3boFW1tb2NjY6PL61mKSNwWpRXap17ek+xaSW3yUOq5JzWNSj7syKU1PUrdzlHSes8guC+tMpSQ2ewEyVxZLGs/L02I9lQ+qV5iLiwuuX7+udhhmofUHDJnCY489hry8vGrfy8/Ph7Ozs5kjMh+JyW769Olo2bJljcluxowZukx2c+bMQadOnRAbG4vOnTvjk08+gaurK1JTU/HBBx8gNjZW7RAVceLECcTGxlb4XQOlhbfw8HBMmDBBpciUdeLECSxatAhdu3ZVOxSzknp9S7pvYVFG7gN+pY5rkvOYxOOuzNHREYMHD1Y7DMVJfZC1pPNc6gOdK5NSZGedqWqzl4uLCy5fvozVq1dj9erVum32qs3KYj3WmSSN5+VpsZ7KSRWFRUZGYvbs2WjdurWoDkBATpIvb/LkyZgxYwYcHR0rfFHfv38/4uPjMWXKFBWjUw6Tnaxkd+zYMcyePRt169YFABQVFcHS0hJ+fn7IycnBrFmzsHbtWpWjND0tJnlTkFRkL0/q9S3pvoVFGbnFR6njmtQ8JvW4AZlNT3PmzFE7BFVIOs9ZZJdbZAdk1pmkNntNmzYNNjY2WLlyZY0ri/VI0nhenhbrqZxUUZjUDkBJSd7Pz6/Cz/n5+Rg2bBgaNmyIJk2aICcnB/n5+WjUqBEWLFigyy1VmOyq0nOyKywshI2NDSwsLGBra4vs7Gzje08++SR+//13FaNTjhaTvClIKrKXJ/X6lnTfwqKM3OKj1HFNah6TetxSm56kknqeAyyySyqyS6ozlSe12UvqymJJ47nW66mcVFGY1A5ASUle6u+4PCY7/Se78lxcXHD27Fl4eHigbdu2+M9//gMvLy9YWVlh3bp1cHBwUDtEk9F6kjcFSUX28qRe35JzmsSijFSSxjWpeUzqcZcnqelJ6naOPM9ZZJdWZJdUZypParOXpJXFUsdzrX/35KSKwqR2AEpK8lJ/x+Ux2ek/2ZXXr18/42qUt956CyNGjEDXrl1hMBhQUlKiq2tC60neFCT9HfD6lpvTJBVlpBYfy5M0rkk61vKkHnd5kpqepG7nyPOcRfbq6LnILqnOVJ7UZi9JK4uljuda/+7JSRVShNQkLxWTnSzDhw83/nPnzp2RnJyM77//HgUFBejevTtatWqlYnSmpfUkbwqS/g54fcslqSgjtfhYnqRxTdKxlif1uMuT1PQkdTtHnucssksrskuqM7HZS9bKYo7n2sRJFQWwA1BukpeKyU42R0dHDB48WO0wiP42qdc371tkFWWkFh+JpJHU9FQZt3OUg0V2WUV2SXUmNnvx74AefJxUUYDUDkAmebmY7OQpLi7G0aNHcf78eRQWFlZ5nw8+1TYW2WWRet9SnqSiTGVSio8c10gaSU1P5UnazpFYZJdAap1JarNXefw7oAedoaSkpETtIEgfIiIi7inJR0dHKxgNESnl119/xdixY5GVlYXqUojBYMDx48dViIxMxcfHB0uWLIGrqyt8fHzu+FmDwYC0tDQzRUakjO+//x4zZszA+++/X6Uo8+6772LKlCm6+ZJeXuXio729PS5fvox9+/YBgK6KjxzXSJrafDfT4/exgQMHwtrausbtHIuKinSznaNUlYvs2dnZyMvLq7bI7uDggKSkJJUiJVNgnYmIHlScVDEDKR2ARCRDUFAQCgoKEBUVhZYtW6JOnTpVPlO5G5KItEPKfQuLMiw+EpH+dOzYEbGxsejVq1eV99LS0jBhwgQcO3ZMhcjIVFhkJ9IvriwmLeH2Xwrj8mPSKyY7uU6cOIFFixZV6OYmfZNSZCdZ9y1St9EoT9KzZCrjuEakT5K3c5SCWwIR6Re3JSYt4UoVhbEDkPSK22jINWDAAISHh8PX11ftUMgMJG0PRLxvkcbPzw8jR45EQEBAlfe2bt2KZcuWISUlRYXIlMVxjfSKTU9yt3MkIiIi8+KkisK4/JiI9ObAgQOYPXs2YmJi0KJFC7XDIYWxyC4L71tkkVp85LhGeiW16YnbORIR6RNXFtODjNt/KYzLj0kKJjs5Zs6ciYsXL8LPzw8ODg5Vnp9iMBiQmJioUnRkapK3B5KI9y36V7n4mJ+fj2HDhlVbfFywYIEuJ1U4rpFeld8q5W7bpugJt3MkItIfSdsSkzZxUkVhkydPxowZM+Do6FilAzA+Ph5TpkxRMToi02Cyk4VfXGVhkV0W3rfoH8dwjmskh5SmJz5jg4hIf6ZPn46WLVvWuLJ4xowZXFlMquL2Xwrg8mOShttoEOmX1O2BJOF9C0nDcY0k4LODiIhIy7gtMT3ouFJFAewAJGm4jQaRvnB7IFl430IScFwjadjhS0REWsaVxfSg46SKArj8mKRhstO/WbNmISwsDE5OTpg1a9ZdPx8VFWWGqEgpLLLLwvsWkoDjGknDpiciItIybktMDzpOqhDR38Zkp387d+7EoEGD4OTkdNcHnxoMBk6qaByL7ESkNxzXSBo2PRERkdZwZTFpCSdViOi+MNnJUn4i5W6TKkRERESkLjY9ERGR1nBlMWkJH1RPRPclIiLinpJddHS0gtGQuV25cgUrV67E0aNHcfHiRTRt2hSdOnXCsGHDYGdnp3Z4REREROJUbnrKzs5GXl5etU1PDg4OSEpKUilSIiIiIm3jpAoREd2To0ePYuTIkbh9+za8vLxgb2+Py5cvY9++fQCA5cuXo1OnTipHSURERCQLm56IiIiIzIOTKkREdE8GDhwIa2trLFu2rMLDT/Pz8xEeHo6ioiJs2rRJxQiJiIiIiIiIiIiUYaF2AEREpC0nTpzAqFGjKkyoAEDDhg0RHh6OP/74Q6XIiIiIiIiIiIiIlMVJFSIiuiePPfYY8vLyqn0vPz8fzs7OZo6IiIiIiIiIiIjIPDipQkRE92Ty5MmIi4vDgQMHKry+f/9+xMfH4+2331YpMiIiIiIiIiIiImXxmSpERHRXfn5+FX7Ozs5GXl4eGjZsiCZNmiAnJwf5+flo1KgRHBwckJSUpFKkREREREREREREyrFSOwAiInrwtWvXDgaDQe0wiIiIiIiIiIiIVMWVKkRERERERERERERERLXAZ6oQERERERERERERERHVAidViIiIiIiIiIiIiIiIaoGTKkRERERERERERERERLXASRUiIiIiIiIiIiIiIqJa4KQKERERERGZzLFjxxAcHIzOnTujdevWOH78eK3/3datWyMuLs748+bNm9G6dWv89ddfSoSquIiICLi5uZn0z/Tx8UFERIRJ/0wiIiIiIqo9K7UDICIiIiIifSgqKsL48eNRt25dREZGol69enByclI7LCIiIiIiIpPhpAoREREREZnEmTNncPbsWcyaNQtBQUFqh0NERERERGRy3P6LiIiIiIhM4sqVKwCAhg0bqhwJERERERGRMjipQkREREREf1tERASGDh0KAHjrrbfQunVrvPLKK8b/Vfd5Hx8fk8dx7do1zJ49Gz4+Pmjfvj08PT0xfPhw/PrrrwCAxYsXo127dsYJoPKmTJmCp556CgUFBQBKn1/y2muvYf/+/Rg4cCA6duwIPz8/7N+/HwCwY8cO+Pn5oUOHDhg4cCB+++23amPKzMzEiBEj0LlzZzzzzDOIj49HSUlJhc/cuHEDc+bMgbe3N9q3b4++ffvis88+q/I5IiIiIiJSFydViIiIiIjobxs8eDBGjx4NAHjllVcwb94848/mNHXqVHzxxRfo06cPpk6dirCwMFhbWyMjIwMAEBAQgFu3biE1NbXCv1dYWIjt27ejT58+sLa2Nr5++vRp/Otf/4KPjw8mTpyI3NxcjB49GomJiYiOjoafnx/Gjh2LM2fOYPz48bh9+3aFP7e4uBgjR46Evb09Jk+ejPbt2yMuLg6LFy82fqakpARjxoxBQkICevTogcjISDz++OOYN28eoqOjFfzbIiIiIiKie8VnqhARERER0d/m5uaGwsJCLF26FE899RReeOEFAMDSpUvNGseuXbvw0ksvISIiwvhaeHi48Z8fe+wxuLm5ITEx0biypuzfy83NRUBAQIU/788//8TatWvh5uYGAGjZsiVGjBiBKVOm4Msvv4STkxMAwNbWFu+99x4OHjyIbt26Gf/9goIC9OjRA1FRUQCAIUOGYPTo0Vi2bBleeeUV2NnZIS0tDT/88APGjx+PMWPGAABCQkIwbtw4fP755xg6dCiaN29u4r8pIiIiIiK6H1ypQkREREREutGoUSMcPXoUFy5cqPEzAQEBOHr0KM6cOWN8LSkpCY6OjujatWuFz7Zs2dI4oQIAnTp1AgB0797dOKFS/vXMzMwq/72QkBDjPxsMBoSEhKCoqAjp6ekAgO+//x6WlpZVtkkLCwtDSUkJvv/++7seNxERERERmQcnVYiIiIiISDcmTZqEP/74Az179sSgQYMQFxdXZaLD19cXdevWRWJiIgAgPz8f3377Lfz8/GAwGCp81tHRscLPDRs2BAA0a9aswus2NjYAgLy8vAqvW1hYwNnZucJrjz/+OADg7Nmzxv93cHAw/hllWrRoUeFzRERERESkPk6qEBERERGR2RUXFyvy5/r6+uKbb75BVFQUHBwc8Nlnn6Ffv37YtWuX8TO2trbo1asXkpKSAABfffUVCgsL4e/vX+XPs7S0rPa/U9PrfLA8EREREZG+cVKFiIiIiIgUY2trW2X1BgCcO3dOsf+mg4MDQkJCsGTJEqSlpaFx48ZVnu0SEBCAU6dO4dixY0hKSkLbtm3x5JNPmjyW27dvV1kp8+effwIA/vGPfxj/Pzs7G9euXavwuZMnT1b4HBERERERqY+TKkREREREpBhnZ2ecPHkSV65cMb72+++/46effjL5f6u4uBj5+fkVXrO3t4eDgwMKCwsrvP7ss8+iSZMm+PTTT3Hw4MFqV6mYypo1a4z/XFJSgjVr1qBOnTrw9PQ0xlJcXFzhcwCQkJAAg8GAZ599VrHYiIiIiIjo3lipHQAREREREenXoEGDkJCQgBEjRmDQoEG4fPky1q5di5YtW+L69esm/W9dv34d3t7e6Nu3L1xdXVG/fn3s27cPP//8MyIiIip8tk6dOujXrx9Wr14NS0tL9OvXz6SxlLG2tsbu3bvx73//Gx07dsTu3bvx3XffYfTo0bCzswMA+Pj4oFu3bvjggw9w9uxZtG7dGnv37kVaWhqGDRuG5s2bKxIbERERERHdO65UISIiIiIixbRo0QJz585Ffn4+oqOjsXPnTsybNw/t2rUz+X+rXr16ePnll3H8+HEsXrwY0dHR+PPPPzF16lQMHz68yucDAgIAAJ6ennBwcDB5PEDps1c+/fRTXLp0CfPnz8fPP/+MN998E2+99ZbxMxYWFvjoo48wbNgwfPvtt4iOjkZGRgbefvttREZGKhIXERERERHdH0MJn6RIREREREQC/f777wgICMDcuXMRGBiodjhERERERKQBXKlCREREREQirV+/HvXr10efPn3UDoWIiIiIiDSCz1QhIiIiIqIH3vXr13Hjxo07fsbOzg6WlpZ3/bN27tyJEydOYP369QgJCUH9+vVNFSYREREREekct/8iIiIiIqIHXlxcHOLj4+/4mbS0NDz66KN3/bN8fHxw6dIlPPPMM5g3bx5sbGxMFSYREREREekcJ1WIiIiIiOiBl5mZiczMzDt+xt3dHdbW1maKiIiIiIiIJOKkChERERERERERERERUS3wQfVERERERERERERERES1wEkVIiIiIiIiIiIiIiKiWuCkChERERERERERERERUS1wUoWIiIiIiIiIiIiIiKgWOKlCRERERERERERERERUC5xUISIiIiIiIiIiIiIiqgVOqhAREREREREREREREdUCJ1WIiIiIiIiIiIiIiIhq4f8BzeKn05cEhqcAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "stats_by_symbol[\"total_pnl\"].sort_values().plot(kind=\"bar\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "055f3168",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-18T11:37:04.961953Z",
     "start_time": "2023-08-18T11:37:04.237777Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='full_symbol'>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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vff755ypUqJBGjBih2267TU2aNFGPHj30zTff2BSl/508eTLJAqo+n0/fffedatasqfz58ye+fu+996Z5YdaMzNTzmKn9+/jx47rxxhuTvLZ+/XrdfffdST7/Dz74oP766y+rwwsYjmuXmHJcM3XcYmrepvZvU9vb1POYqeO1Q4cOJXvKY/Xq1SpTpozat28vSSpYsKC6dOmiHTt22BFiQJja3vTv/2dCe2f2cSqFkH9ky5YtydxlUVFROnr0aLJHl/Lly6fTp09bHV7AmJq3y+WSy+VK/PnYsWM6cOBAsryLFi2qkydPWh1ewMTGxqpYsWKJP3s8Hm3btk21atVSjhw5El+vWrWqDh48aEeIAREfH6+QkJDEn8+ePavdu3erdu3aSba79dZbFR0dbXV4AWNq/za1vePi4lS4cOHEny9cuKDt27erdu3aCgoKSnz99ttv1+HDh+0IMSDy58+v48ePJ/68e/dunTlzRtWqVUuyXbZs2eTxeKwOL2BMPY+Z2r/z5MmTZK7tvXv36tSpU8k+57lz59b58+etDi9gOK5dYspxzdRxi6l5m9q/TW1vU89jpo7XLl68qOzZsyf+HBsbq7179ya7KbNUqVJJzneZnantTf++xJT2zuzjVAoh/7j11luT3AG/atUquVwu3XfffUm2O3jwoGPmJ5XMzbtMmTLauHFj4s9r166Vy+VSnTp1kmx39OhRFShQwOrwAqZw4cJJChz/+9//dP78ed19991JtnO5XHK7nXN4uOGGG7Rr167En7ds2SKPx6OaNWsm2e7s2bPKlSuX1eEFjKn929T2Ll68eJI7B3/44QclJCSoRo0aSbZLSEhQ1qxZrQ4vYO666y7Nnj078aLCp59+KpfLpQYNGiTZ7vfff1fRokXtCDEgTD2Pmdq/K1SooEWLFiX+HBERIZfLleyx9P379ye5sJjZcVwz67hm6rjF1LxN7d+mtrep5zFTx2ulS5fWTz/9lPjzhg0bJCnZjSsxMTFJbnDJ7Extb/r3Jaa0d2YfpwbbHUBG0a1bN/Xs2VMHDx5U4cKF9cUXX6hixYrJKnlr165VxYoVbYrS/0zNu2PHjho0aJBiY2NVqFAhffrppypdurTuueeeJNtt2LBBt912m01R+l+NGjU0depU1apVS/nz59fHH3+soKAgNWzYMMl2u3btUvHixW2K0v+aNm2qSZMmqUCBAipcuLDGjBmj3LlzJ5tnftu2bcke6czMTO3fprZ33bp1NWnSJJUtW1aFCxfW+PHjlTVr1mQDkh07dqhkyZI2Rel/zz77rNq3b6/atWsrd+7cio6OVosWLZJNO7F8+fJkd6lkZqaex0zt308//bQef/xxNWnSRAULFtQPP/ygOnXqXHGasLvuusumKP2P45pZxzVTxy2m5m1q/za1vU09j5k6XmvXrp1Gjx4tSSpUqJAmTpyoggUL6v7770+y3ebNm3XzzTfbEWJAmNre9G+z2juzj1MphPyjbt26GjNmjObMmaNdu3apadOmev7555Nsc/z4ce3fv1/du3e3KUr/MzXvli1bKjo6WnPmzFFsbKwqVqyoV155RcHB/98ljh8/rrVr16pPnz42Rupflw9Y9erVk9vtlsfjUbdu3ZLM7ydJS5cuTXY3VmbWrVs3bd++XQMHDpQk5cyZU2+88Yby5MmTuE18fLwWL16sDh062BWm35nav01t7969e+u7777T448/LunSk11DhgxRwYIFE7fxeDxasmSJHnzwQbvC9LuyZctq6dKlWrhwoU6fPq2KFSuqTZs2SbY5fvy4KlSokGzRxszM1POYqf27cuXKmjlzpubNm6fY2Fj17t1bXbt2TbLN8ePHFRQUpNatW9sTZABwXDPruGbquMXUvE3t36a2t6nnMVPHa4899pj27Nmj8ePHKyEhQSVKlNCYMWOSTZe1dOlS9ejRw8ZI/cvU9qZ/m9XemX2c6vL5fD67gwBgndOnT2vlypWJB+r/ztN54sQJhYeHq27duskqupndX3/9pVOnTqlMmTLKnTt3kvfOnDmjffv26cYbb0xyQQ2Zl4nt7fF4tHnzZsXGxqpChQrJ7og/deqUvvvuO911111J1gsCMhsT+7epOK4BzkX/Bpzt/PnzOnv27BWnBUpISNDp06eVO3duZcmSxYboAJiIQggAAAAAAAAAAHAspsb6R6dOna76XpYsWVSgQAHVqFFDLVu2VLZs2SyMLLBMzXvIkCFXfe/fef93br/M7t8Lpf9XcHCw8uXL56jFCC8LDw+/6nvBwcEqWLCg7rjjjmR3FWd2pvZvU9v7+++/v+p7l/MuXbq0hRFZo3z58nK5XFd8LygoSAULFlT16tXVs2dP3XrrrRZHFzimnsdM7d8NGjS46uf8ct7Vq1dXx44dHbW4Lse15Jx8XDN13GJq3qb2b1Pb29TzmKnjtXHjxl31vct533333SpTpoyFUQWeqe1N/07Oye2d2cepPBHyj969e1+1IT0ej44cOaLdu3frxhtv1OzZs5PMXZqZmZr3teYl9Hg8Onr0qGJiYlS9enVNnjxZOXPmtC64ALrWAUuS3G637rjjDvXt29dRB+vy5cunuE327NnVpUsX9e3b14KIrGFq/za1vS/376ud1l0ulwoXLqxnn31WDz30kMXRBc6MGTOu+jn3er06cuSI1q5dq8OHD+uTTz7R7bffbnGEgWHyeSwlTuzfb7zxRoqf882bNys4ODhxoUYn4LiWnJOPa6aOW0zN29T+bWp7m3oeM3W8Vr169au+5/F4dPbsWblcLrVs2VJvvvmmgoKCLIwucExtb/p3ck5u78w+TqUQkgYHDhxQp06ddM899+j111+3OxzLmJr31q1b9fTTT6tt27YaNGiQ3eH4xVdffXXV9y4fsFatWqWtW7dq6tSpql27toXRBc7p06ev+t7lLxyrVq3ShAkTNHToUIWFhVkYnb2c2L9Nbe9ff/31qu/9O+8lS5Zo9OjRatasmYXR2SshIUGdO3dWrly5NHnyZLvDsYwTz2Om9u/UiIuL02OPPaZbbrlFY8aMsTscv+C4dnWmHtecOG5JDSfmTf++Oie2d2o48TyWGk4cr6XkzJkzWrVqlYYPH64ePXqod+/edodkGRPbW6J/m9beGXqc6kOazJ8/33fvvffaHYblTM175syZvvr169sdhuWefvpp3+OPP253GJYbOXKkLzQ01O4wLGdq/za1vYcNG+Zr166d3WFYbvny5b7q1avbHYblTD2Pmdq/w8PDfbVq1bI7DMtxXDOLqeMWU/M2tX+b2t6mnsdMHa9NmDDB17hxY7vDsJyp7U3/NktGHae67S7EZDalSpXSyZMn7Q7Dcqbmfdttt+nIkSN2h2G51q1b6+eff7Y7DMvVrl1bf/75p91hWM7U/m1qezdq1Eh//PGH3WFYLn/+/Dp37pzdYVjO1POYqf27aNGi13xqxqk4rpnF1HGLqXmb2r9NbW9Tz2OmjtcqV658zXVMncrU9qZ/myWjjlMphKTR33//rfz589sdhuVMzfvIkSPKkyeP3WFYLlu2bPJ4PHaHYbn4+HgFBwfbHYblTO3fpra3qbZv364SJUrYHYblTD2Pmdq/f//9dxUpUsTuMGARU49rpo5bTM3bVKa2t6nnMVPHazExMcqRI4fdYVjO1Pamf5slo45TKYSkQVRUlCZOnKi6devaHYqlTM07Li5OU6dOVa1atewOxXLfffedbrzxRrvDsNzSpUtVsWJFu8OwlKn9WzKzvSVp9erVuvXWW+0OwzJxcXFaunSpJk+erJYtW9odjqVMPo+Z2L+3bt2qCRMmqHHjxnaHYjmOa+Ywddxiat6Sef1bMre9TT2PmTpe83q9+uSTT1SlShW7Q7GUqe1N/zanvTP6ONW8W+WuolevXld9z+v16tixY9q9e7dKlSqlfv36WRhZYJma97UWnfN4PDp27Ji2bNmioKAgjRs3zsLIAismJuaq73m9Xh09elSrV6/WzJkzNWTIEOsCC7Avv/zyqu9dbu/Vq1fr+++/19SpUy2MLLBM7d+mtve1prP7d96LFy/W6NGjLYwssKpUqSKXy3XF97xer+Lj4+Xz+RQaGnrNPpHZmHoeM7V/t2jR4qrvXT6ex8bGqlq1aurbt6+FkQUWx7XknHxcM3XcYmrepvZvU9vb1POYqeO16dOnX/W9y3l//fXXOnz4sObOnWthZIFlanvTv5Nzcntn9nGqy+fz+ewOIiPo2LHjVd8LDg5WgQIFVL16dbVq1cpRj+6ZmneDBg2u+t6/8+7UqZMKFy5sYWSBVb58+asesC7LkiWLnnzySUcNvMuXL3/N991ut+644w716dNH9957r0VRBZ6p/dvU9k6pf/t8PhUuXFh9+/ZV+/btLYwssMaOHXvVvIOCglSgQAHdfffdKlu2rMWRBZbJ57FrcWr/Hjx4cIqf8+rVq+vee+9N8TyfmXBcS87JxzVTxy2m5m1q/za1vU09jzFeSy4oKEj58+dXjRo11LNnT5UrV87CyALL1Pamfyfn5PbO7ONUCiGAQRYvXpziAeuuu+5y3PyFUVFRV30vODhY+fLlU7Zs2SyMCIFkantv2bLlqu9d7t833XSTowaf1+v7779XxYoVlTNnTrtDQSqZ2r+vx8GDB1WkSJFMuWYKx7W047iGzIL+jdTKzOcxANdG/zZLhhin+nBdEhISfOXLl/ft3LnT7lAsZWreHo/H16BBA99vv/1mdyiWW7JkiS8mJsbuMCzl9Xp9gwcP9kVFRdkdiqVM7d+mtrfX6/WNHTvWd+TIEbtDsZSpn3NTz2Om9m9TP+cc18xqb/I2K2/6t1ntbWrepo7XPB6Pr2PHjr59+/bZHYqlTG1v+jftbQcWS/cDn6EP1ZiYt8/nU1RUlC5cuGB3KJbyeDwaMmSIDhw4YHcolvJ6vQoPD9fJkyftDsVyJvZvU9vb6/Vq/PjxOnLkiN2hWM7Ez7mp5zFT+7dk5uec45p5yNsc9G/zmJi3qeM1n8+nLVu26MyZM3aHYilT21uif5smI7Q3hRAAqZIRDlh2MDVvU5na3qbmDbPwOTcL7Q04F/0bAACkB4UQAAAAAAAAAADgWBRCAAAAAAAAAACAY1EIAQAAAAAAAAAAjkUhBEgjl8tldwgAAKQb5zEAAICMjfGaWWhvs9De9qEQcp1cLpdKlCihrFmz2h2KpUzNW2JxPjifyf0b5nC73WrTpo3y589vdyiW4zxmDpfLperVqytXrlx2hwILmHRc+/vvvxP/O7OPW77//nudOXMmzb+X2fNG2pja3iafxxivmcXE9qZ/myWjjFNdPhP/71/Br7/+qvLly6dq23nz5qlDhw4Bjsh+v/32m/bs2aPChQurWrVqVCwdYPHixWrcuLFy586dpt/z+XwaP368HnnkERUuXDhA0WUM33//vapXr57485YtW1SpUiXlzJnTxqjS748//tC8efN04MABFSlSRA8++KDuueceu8PKsDJ7e6fXkiVL1KBBA+XNm9fuUPzm/PnzWrhwYeJ5rE2bNipevLjdYVlu1apV6tevn3bu3Gl3KH6xfv163XfffSlud/HiRQ0cOFDvvfde4mtO6d/79+/XTz/9pGPHjsnlcqlQoUKqUqWKSpcubXdoGUpmPq7NnTtXYWFhKW539OhRvfXWWxozZowFUQXe0KFD9eabb6a43a+//qpu3bppw4YNFkQVeBUqVNBnn32mO++80+5QMo3M3L9TcuLECeXOndtxBY8dO3bo1ltvVY4cOa653cmTJ7Vhwwa1aNHCosgyhoSEBB0/flxFixa1OxS/uJ7jWlRUlIoUKaIsWbIEILKMwWntDbMcOXJEI0aM0MMPP3zV72Xr16/X/PnzNXz4cBUsWNDiCK+NQsg/KlasqCeeeEJ9+vS56sl5165devnll/XLL7/o559/tjjCwFi2bJk2bNigd955J8nrgwYN0rJlyxJ/rlSpkqZPn57mC+gZ1euvv57qbbNmzaobbrhB9evXV4kSJQIYVeCVL19e2bJlU7169dSiRQvVrVvX0QOMtPjqq680depUbd++Xbt27bI7HL/YunWrnnzySSUkJKhAgQKKiYmR1+vVyy+/rEcffdTu8AImPDw8Tdu3bt06IHFYbfjw4erevbtuuOGGxNciIiJUt25dhYSEJL62Z88evfHGG/r444/tCNPv3nvvPa1Zs0YRERGJr507d07t2rXT3r17E++2yZs3rxYuXKhSpUrZFaotvvjiCz333HOOOa7dddddGjt2rO6///6rbnP+/Hk9/fTT2rx5s2MKQJIUHR2toUOHauPGjcnuInO5XLrvvvv0xhtvOOqGhbSOtytWrBigSKxVsWJFVapUSa+++uoVb9Ty+XyaPXu2PvjgA+XOnVvr1q2zIUr/q1Spklq0aKE333zzqjdgbdu2Tb169VLhwoW1YsUKiyMMjPLly2v+/PnGFUJ27typrl276p133lHdunWvuM26des0cOBAzZw5M9U3LWYGP/74o1avXq2EhAQ1btxYVatWVXh4uN555x2dPHlSwcHBatu2rV566SUFBwfbHa5f/PfCuNfr1Z133qn58+fr9ttvT9xu+/bt6tChg6PGLXPmzNEdd9wh6dLxu2vXrnrllVd04403Jm7ntLxNPa6Z2t5pKVy6XK4k1xozsyFDhqR6W5fLlaqbPTKDkSNHatOmTVqyZMlVx2s+n09t27ZVnTp11L9/f4sjvDZnnFX9YMCAAfrwww+1cuVKvfTSS6pfv37ie3FxcXr//ff16aefqnz58po3b56NkfrXkiVLkl3cDw8P19KlS3Xffffpscce0759+/Thhx9qxowZeuaZZ2yK1L/WrFmT6m3j4+MVExOjkSNHavLkyapdu3YAIwuspUuXavny5VqxYoW++OILhYSEqEmTJmrRooVq1Khhd3gB4/V6NW3aNC1evFiHDh1SyZIl9cwzz+jBBx/Uhg0bNHLkSP3xxx+64YYb9Nprr9kdrt+MHTtWN998syZNmqTixYsrLi5OQ4YM0fvvv+/oQsjgwYMTT8gp1fpdLpdjCiGfffaZ2rZtm1gI8Xg8GjhwoBYuXJjk4mBcXJw2bdpkV5h+9+233yY5Z0vSzJkztWfPHvXu3Vtdu3bVvn371LdvX02aNElvvPGGTZHCH+rXr69nnnlGH374oerVq5fs/VOnTqlnz5765Zdf9P7771seX6CcO3dOnTp10pEjR9SlSxfde++9KlasmHw+n6Kjo/XNN99o3rx56ty5sxYtWqTs2bPbHbJfPPTQQ6l6Itnn88nlcjnmgsJnn32ml19+We3atVPHjh3Vp0+fxCeZduzYoeHDh2v37t16/PHH1bdvX5uj9Z8xY8bo+eefl8fj0ciRI5O1/ddff63nnntOZcuW1UcffWRTlPCXmTNnqkqVKlctgkhS3bp1Va1aNU2fPl0jR460MLrAWb16tfr06aO8efMqe/bsmj17tgYPHqy33npLdevWVdmyZfXbb79p/vz5KlOmjDp37mx3yH7x3zG5z+dTQkKC46eHiY+PT5Kj1+vVxo0bFRcXZ2NUCBRT27tixYpJztk+n0/h4eGqV6+e7dMgBVJqxp0XL17Unj17HFUIWbt2rTp37nzNMbrL5dIjjzyimTNnUgjJqDp37qwHH3xQr732mp566ik98MADGjZsmLZt26a33npL8fHxGjp0qB577DFHTRH1+++/q23btklei4iIUEhIiD788EPlyJFD9evX19mzZ/XFF18YWQiRLl1YeemllzRq1CgtXrw4QFEFXrly5VSuXDk9//zz+vHHHxUZGakvvvhCCxcuVJEiRdS8eXO1aNFCFSpUsDtUv5ozZ45Gjx6tm2++WfXr19fBgwf1/PPPa9euXZoyZYoKFy6s1157TW3atHHMXVfSpentXn311cTpgHLnzq1BgwapUaNGOnTokGOnCcqaNauCg4P1wAMPKDQ0VJUrV7Y7JEtc6Yuk079cSpfmib9819VlX375pUqUKJF4gbBSpUrq1q2bZsyYYUOE8KcxY8ZowIAB6tOnj95//301bNgw8b0jR46oa9euOnjwoD766CPVrFnTxkj9a/78+Tpy5EjiTTn/dvPNN6t27dpq2bKlHnvsMS1cuFCPP/64TZH616xZs+wOwRaVKlXSwoULNWvWrMQbtfr376/NmzdrwYIFuuuuu7Ro0SJH3SEvSY0bN9YHH3yg5557Th6PR6NGjZLbfWlJy2XLlmno0KGqVq2aJkyY4Lj5xDdv3qzDhw+natvGjRsHOBprbNmyRYMGDUpxu9DQUMcUQSRpypQpaty4sUaPHq2goCBNnDhRI0eO1JNPPqkBAwYkbvfmm29q0aJFjimEwDxxcXGKiYlJ1bb58uULaCwIrLfffjvJzwkJCQoPD1efPn0c87TulVxrJor4+Hh99tlnmjp1qoKCgtS8eXPrAguwqKgo3XLLLSluV7ZsWUVFRVkQUdo454qfHxQrVkwTJkzQV199pVdffVWNGjWSx+NRaGioBg0apEKFCtkdot/FxsaqWLFiiT97PB5t27ZN999/f5IpwqpWrarp06fbEaLt4uLilDdvXj366KPq1auX3eH4TZUqVVSlShUNGzZMmzZtUmRkpBYsWKDp06fr5ptvVosWLRyT74IFCxQaGqpRo0YlFjKnTZumUaNG6e6779aUKVMy/ZzxV3Ly5Mkk/VtSYvHj5MmTji2EbNq0SatWrdLy5cv11FNPqVixYgoNDVVoaGiqTtjIXOLj45NM/XX27Fnt3r072ZM+t956q6Kjoy2ODv7mdrv17rvvavDgwXr22Wf13nvv6YEHHtCff/6pLl266Ny5c5o1a5bjvnStXr1a7dq1u+aF7woVKqhdu3b68ssvHVMIcfLTqilxu92JN2qFhYWpf//+crlcjp/esmHDhho3bpz69OmjF154QaNHj9bs2bP19ttvq1GjRho9erTj1k6QLhV5U3PzgpOefDp+/LiKFCmS4nZFihTR8ePHLYjIGnv27FGfPn0UFBQkSerQoYM++OCDZE/G1KtXTwsWLLAjRMAvunbtmuptnXJcwyVOunk8rc6fP69PP/1U06ZN06lTp9SyZUv17NnTUWv5ZcuWLVVPOZ09ezZDjtkohPzHxYsXtXv3bp06dUpZs2bVuXPnlCNHDmXLls3u0AKicOHCOnjwYOLP//vf/3T+/HndfffdSbZzuVyJd2SZ4vjx45o5c6Y+/fRTff/996pSpYo+++wzu8PyO7fbrTp16qhOnToaPny4Ro0apblz5+qDDz5wTCHkwIEDSaZLki5NtzFq1Cj16NHDkUUQk+XKlUutW7dW69atdeLECX3++edasWKFJk+erFtvvVWhoaFq0aKFYwtBprnhhhu0a9euxLv/t2zZIo/Hk+xpgLNnzzrqDuLUrnX1119/BTgS67lcLr399ttyu93q16+f+vTpo5kzZyp79uyaO3euypQpY3eIfvfHH3+oU6dOKW5Xq1YtLV++3IKIrPHll1+qVq1aSYqdJtm/f7+GDx+uqKgo1apVS1u3btUnn3yi2267TdWqVbM7vICpW7euxo8fr2eeeUYtW7bUnj171LZtW40YMcKx30fGjh3ruCeyUxISEqIjR46kuN2RI0eUJ08eCyKyRlxcXJJj2uX//u8YJVeuXDp//rylsdnB5AumTterVy9HXfwFruXs2bOaM2eOZsyYodOnT6tt27bq2bNnpl9n+ErKlSunNWvWXHGa4n9bvXq1ypUrZ01QaUAh5F+2bNmiV155RVFRUerRo4e6d++uZcuW6d1339Xq1as1cOBAtWrVyu4w/apGjRqaOnWqatWqpfz58+vjjz9WUFBQkqkmpEsVeqddNPzpp5+0ZMkSHTp0SKVKlVLHjh1100036dixYxo/frwWL16shIQENWvWTJKUPXt2x01BcNnPP/+syMhIrVixQtHR0SpUqJCaNm1qd1h+c+7cuWRfoC7/XLBgQTtCsswTTzxxxS8YYWFhSV53uVzatm2blaFZokCBAgoLC1NYWJgOHz6sGTNm6IMPPtCOHTs0btw4u8Pzu38/gu7xeJK9JkmnT5+2IbLAadq0qSZNmqQCBQqocOHCGjNmjHLnzp1s3ZBt27YlWaQws0vLFI9OO39Ll45Zb731lrJkyaL3339fZcuW1bRp01S0aFG7QwuI2NjYVJ2vChQooNjYWAsissazzz6bbHHdpk2bavz48Y5+wu/ixYuaPHmypkyZohtuuEEzZ85UzZo19ccff2j48OHq2LGj2rRpowEDBjhqOpGff/458b8LFCigZ555RqNHj05ct/C/dww76cmvIkWKJK7xZYrKlStr4cKFid+1rmbRokWqWrWqRVHZx4SCwMiRI5N9J3vzzTeVO3fuxJ+dNk6VpMjIyMTvWV6vVy6XSxEREdqyZUviNv++OdUp6tevb9xi6ZK57W2quLg4zZ49WzNnztS5c+fUvn17de/e3bHfSSSpXbt2evHFF1WlShW1adPmituEh4dr8eLFqb55z0oUQv4xaNAgLVu2TLVq1dLEiRN10003SZLat2+vhg0bauTIkRo0aJAWL16s4cOHO+Zuw2effVbt27dXvXr15Ha75fF41K1bt2QD8aVLlzpqeoJ169bpqaeeks/nU4ECBbRx40ZFRkbqnXfe0aBBgxQbG6vmzZurd+/ejmnr/9q3b58iIyMVGRmpv/76Szlz5lTjxo0VGhqq2rVrO+6Ou7179yY+gi79/0XivXv3JtvWKV+snbKmz/U6ffq0vvzySy1fvlybN29WyZIlk10kd4orPYL+37mlLy8q7BTdunXT9u3bNXDgQElSzpw59cYbbyT5oh0fH6/FixerQ4cOdoXpd2ld68opWrRokew1n8+ns2fPqlu3bkled7lcWrZsmVWhBVRCQkKSc9jVXB7LOcWVFtf9888/FR8fb1NE1ggNDdXhw4fVq1cvde/eXVmyZJEk3XLLLZozZ44WLVqkUaNGac2aNRowYECy9f4yq4ceeuiK56f169drw4YNiT9fPo8xlUrm1qVLF3Xs2FFDhgzRoEGDkhX1YmNjNXLkSG3atEmzZ8+2J8gAMbEgUL16dUnSmTNnrvma2+1ONjtFZnel9a6utG6dk8bnJqO9/5/Tcxw7dqxmz56thIQEdejQQV27dnX8jbaS1KZNG61fv15DhgzRnDlzdN9996lEiRJyuVw6ePCgNmzYoJ07d6pZs2bJpqvOCFw+E1ZSTYV7771XgwYNuuIX7Ms2b96c+Hj6jh07LIwusE6fPq2VK1cqNjZWFStWVK1atZK8f+LECYWHh6tu3boqW7asTVH612OPPab4+HhNmDBBRYsW1ZkzZ/Tiiy9q1apVKly4sMaOHatKlSrZHabfRUdHa/ny5YqMjNSuXbsUHBysunXrKjQ0VA0aNMiQ8/f5Q/ny5a94Er58+Lv8Hl+sneP8+fNas2aNIiMjtX79ehUsWFBNmzZVaGioYwpd/7VkyZI0bX+1uzcyq7/++kunTp1SmTJlklxIkC59wd63b59uvPFGR02vYaL/TnOYkrfeeiuA0VinfPnyevDBB1Ncr+7YsWP64osvHHMeK1++vObPn594R6nH41HFihW1aNEixx7LpUsF3ldeeUWlSpW66jYxMTEaOXKkli5dql9++cXC6ALn33fLpoZTbtL67+fcJHPnztVbb70lt9utSpUqqXjx4nK5XDp06JB27twpj8ejoUOH6rHHHrM7VL/p2LFjmrZ3WhEIZjD5uGaiK11H/f3333XjjTcmu8bkpBuVLl9nuvPOO5U/f/5rbutyuTRx4kSLIrPG3LlzNWPGDP39999JXi9durQ6d+6cYc/dFEL+cfr06VRdHLl48aI++ugj9e7d24KoECg1a9bUG2+8oUaNGiW+dvDgQTVo0EDvvvuuQkNDbYwucCpUqCCXy6Xq1asrNDRUDz74oBEXBU39Yp1aHo9HERERGbJanx4vvPCC1qxZoxw5cqhJkyZq3ry54+4sQ/pcuHDBcQXfCxcuaOXKldq6dasOHz4sSSpWrJiqV6+uJk2aOC5fUzVo0CBN2zvliSFTCyFpsXXrVs5xmVxUVJSKFCmS+OSPaX799VfNmjVLW7duVXR0tCSpaNGiqlGjhjp27Jgh5xdH2u3atSvV6+Bcno0DmdeSJUtUr169FC8OwxlMvVHJ1MJ2p06d9MorryTeKB8dHZ3k/J3RpwWjEGK4FStWqE6dOsqbN2/ia5fXiPj3FAzR0dFasmSJYxbPvtIdCpe/XC9YsEB33HGHjdEFzvTp09WsWbMUD0ynTp3S7NmzjZxa6dy5c8qRI4fdYfjdiRMnlD9//iQDlPPnz+uzzz7TzJkzdejQIUfdQZwrVy5VrVo1xalknHhnhmmeffZZvfjiiypcuPA1t1u3bp1GjBihr776yqLIAm/r1q3q37+/oqOj5fP5EhdcvbxGRIkSJTRq1ChHLarcsGFDjR8/3rFrdiGp8uXLq1OnTonr3Hi9Xr377rt64oknko1lXC5XsqkAnSw2NlYrV65URESEY75Ymyo8PDxN2zvlxhWYpWbNmpo+fbpuv/32q27j8/k0dOhQhYeHO+Z7ydX8e00k6dJ6pE6ZfePfTLxhZ/78+Zo9e7YOHDigIkWKqGnTpurdu7cjc4WZMvsTX6wR8h8HDhzQggUL9NNPP+nYsWNyuVwqVKiQqlatqnbt2qlEiRJ2h+hXL7zwQpJFKD0ej+rVq6eFCxcmudPu8OHD+uCDDxxTCLmW1MzBnVk9+eSTki5NnXHw4EHdcMMNSeYwjI6O1rRp07RgwQJdvHjRmEKIx+PR+vXrFRERoTVr1ujHH3+0OyS/iI+P11tvvaWlS5fq/PnzypUrl3r37q0uXbpo/vz5ev/993XixAlVq1ZNb7zxht3h+s3l+YbPnz9vcyTWGjJkSKq3dblcevPNNwMYjXV++uknNW3aVP369dNjjz2W7G6kw4cP6/XXX9dXX33lqLVh9uzZo+7du6tEiRJ65513VL9+/cQpwc6cOaO1a9dq0qRJ6t69uxYuXKibb77Z5oj9IyoqShcuXLA7DFgoLXNtO70QcuHCBa1evVoRERFav369Ll68eM2LiplNp06dUr2ty+XSzJkzAxiNdf59J21K9yi6XC4KIZnc999/n6btL49rM7tbbrlFnTt31rRp06540+GFCxf0/PPPa/Xq1Ro6dKgNEQbGb7/9pq5du6pv375q3769pEvfPf+9JpLP51NQUJDCw8N166232hmuX13rhp358+frvffec9wNO4sWLdLLL7+sG2+8UfXq1dOBAwc0adIkxcbG6uWXX7Y7vIDhRiVkJhRC/iUiIkLDhg3ThQsXVLRoURUvXlw+n0/79u3Td999p2nTpumtt95Ss2bN7A7Vb6402DblIaEnnnjiio/vhYWFJXnd5XJp27ZtVoYWMKdOndKAAQO0fv16SZcWo+vQoYOGDRumDz74QNOnT5fH41GzZs2MmP5t27ZtioyM1MqVKxUTE6MCBQro4Ycftjssv5kyZYrmzZunOnXqqEKFCoqKitKYMWP0888/a/ny5br99ts1evRo1a5d2+5Q/crUO2NTc+fcxYsXtWfPHkcVQj7//HO99957evPNNxUeHq7XXntNFSpUkMfj0fTp0zVhwgTly5dP48ePV8OGDe0O128mTJigm266SZ9++qmyZ8+e5L1cuXIpNDRUDRs2VFhYmMaPH6/Ro0fbFCn84eDBg2na3ik37vz66692h2A7n8+njRs3KiIiQqtWrdKZM2cSL4Z37tzZUdMG5c6dO8WpNY4fP66ffvrJUQuwZs2aVcHBwXrggQcUGhqqypUr2x2SJV5//fU0bf/iiy8GKBJrdezYUS6X65rfuS9/vl0ul2PWAJo6dap69OihLl26aNq0aUnuJD5z5oyeeuop/fDDD3rnnXeuuW5rZjN37lwVKlQosQjyb8OHD1eZMmXk8/k0ZcoUzZkzR6+++qoNUfqfqTfszJkzRw8++KDGjBkjt9stSZo0aZLGjRunoUOHKjjYmZdgTb5Raf/+/cqRI0eSJ5WnT5+eZJtcuXI56jpTZufMXpgOe/bs0dChQ1WtWjW99NJLyR5L/P333zVixAgNHjxYFSpUUJkyZWyKFP5gypMO/zV27Fht3LhR7du3T7wwPm/ePO3evVtbt25V/fr1NXDgQEd/vn///XdFRkYqIiJChw4dUpYsWXTx4kUNGTJEYWFhjnoiaMWKFerUqVOSu6rCw8M1ePBgNWrUSB9++GHiAM1J/jtnpSmuNbVGfHy8PvvsM02dOlVBQUFq3ry5dYEFWM6cOTVs2DC1atVKL7/8stq1a6eHHnpIP/74o/bt26cnn3xSTz/9dLJiQWb33XffaciQIdfMK0eOHOrSpYtj5uE1WYMGDVJ94ddJF85MtmPHDkVEROjzzz/X8ePHlTt3bjVp0kT16tVT37591bZtW0cVQaRLBd6rOXr0qKZOnapvv/1WefLk0eOPP25hZIG1adMmrVq1SsuXL9dTTz2lYsWKKTQ0VKGhobrlllvsDi9g0rKWkcvlckwhJKWp0I4ePapp06bpu+++U65cuawJygI5cuTQ1KlT1atXL3Xp0kUfffSRqlSpohMnTqhbt27au3evxo8fr7p169odql999913V33arVKlSomzcBw9elTjxo2zMrSAMvWGnT///FMvvPBCku/YHTp00Pvvv6+oqCjdeOONNkYHf1u3bp169eqlyZMnJxZCPB6PRo4cmWQ7l8ulYsWK6f7777cjzIDo37+/smXLluJ2LpdLy5YtsyCi1KMQ8o9PPvlEpUqV0pQpU644d9+tt96qqVOnqnXr1po7d65jBmKmMrUQ8s0336hXr15J8q9WrZqeeuopPfzww3rttddsjC5wDh8+nFj8+O233xQUFKRatWqpb9++qlmzpurXr68KFSo4qggiXboz478L7DZq1EjSpSefnFgEkaQtW7bozJkzdoeRIZw/f16ffvqppk2bplOnTqlly5bq2bOnSpcubXdoflepUiVNnTpV7du31/z58+V2uzV+/HhHTYf1b7GxsSpWrFiK2xUrVixxzRCnuNoTnf/lpCc6U7o4cuHCBc2fP1/fffed485lJmrSpIn++usvZcuWTffff79atGihunXrKmvWrDp9+rTd4VkqOjpaH330kRYuXKjs2bOrR48e6tSpU+KdxU6QK1cutW7dWq1bt9aJEyf0+eefa8WKFZo8ebJuvfVWhYaGqkWLFolr5ThFWgohTnK1qWOOHDmiqVOnasGCBcqSJYueeeaZNE0Xlxlky5ZNkydP1lNPPaVu3brp1Vdf1dixY3Xy5ElNmzbNUVMkXXbo0KFk01253W7Vq1cvcaoo6dICw4cOHbI6vIAx9Yads2fPJmlXScqTJ48kKS4uzo6QEECLFi1S3bp1r1jgWLRoUWKhc/jw4Vq4cKGjCiFlypRRgQIF7A4jXSiE/GPLli16+OGHr7mAUdasWfXwww9r8eLFFkZmDyc9bp4aXq9XMTExkqR8+fI59gLxwYMHVbNmzSSv1apVS5LUsmVLO0KyxOULoRUrVtSLL76opk2bJh60nXxB4cKFC8qZM2eS1y4vBP/fARqc5ezZs5ozZ45mzJih06dPq23bturZs6djpsu5kvDwcL3zzjvyer3q27evwsPD1a9fP/Xq1UvdunVz3KPoxYoV065du3T33Xdfc7tffvklVQWTzKR58+aOyykll4vY/xUfH6958+Zp2rRpOnHihNq0aaOePXtaHF3glC9f3sgnYf78809Jlwq8jRs31n333WfcIquHDh3SpEmTtGTJEuXOnVu9e/dWWFiYo+6Qv5ICBQooLCxMYWFhOnz4sGbMmKEPPvhAO3bscNTd4tKltc169+6tUqVK2R2KrQ4fPqwpU6Zo0aJFypEjh3r16qWwsDBHFfv+LWvWrJo4caL69u2rAQMGqFChQpozZ45uu+02u0MLiKCgIF28eDHJay6XS5MmTUryWnx8vKOuQZh8w87evXuT3JTi8XgSX/+vf6/Lm9mZeKPSTz/9pAEDBqS43b333qsRI0ZYEJF1nn76aRZLz+wOHTqUqsfLy5Urp6ioKAsiss6VHmnq169fki9c8fHxVodlia+//lozZ87Ujz/+mJhjtmzZVLVqVT3xxBOOezQ3ISEhWVtfbufLF8idKCQkRKdOndLff/+t3bt367bbbsu01eu02rx5sw4fPpz4s9frlcvl0ubNm5Mdyxo3bmx1ePCzuLg4zZ49WzNnztS5c+fUvn17de/ePcmcpU6zb98+vfLKK/r+++/VunVrDRw4UPnz51e3bt00YcIEjR8/XhERERo+fLhjFhyVLl0Ynzhxou677z7ddNNNV9zmzz//1JQpU9SqVStrgwuwhx9+ONMOvP3l3Llz+uSTTzR9+nSdOnVKbdq0UY8ePVSyZEm7Q/Orfy8ifTVr167Vd999Z1FE1liyZImWLVumzz//XP3791eOHDnUsGFDtWjR4oqLDDvJ33//rcmTJys8PFz58uXT888/rw4dOjhuesNrOX36tL788kstX75cmzdvVsmSJR35dOOSJUv06KOPGlsIiYqK0uTJk7VkyRLlzZtXffv21aOPPprsJian6NWrV5KfL168KJ/Pp0KFCmnMmDFJ3nO5XJo4caKV4QXMTTfdpG3btqlOnTrX3G7r1q1XHc9lRibfsDNkyJArvj5gwIDEMY3P55PL5UrVGo+ZhYk3Kp04cSLZ05pBQUEaOHBgktfz5cunEydOWB0eroJCyD/OnDmTqjuMcubMqbNnz1oQkTVat26d7AtmpUqVrrit0x5Vff311zVnzhzlzZtX999/f+KB6tChQ9q8ebN69eqlxx9/XMOGDbM5Uv+KjIxMUoG/fGE8IiJCW7ZsSXzd5XKpc+fONkTof99++602bNigiIgIRUREaMGCBSpatKiaNWvmuGLXf11tvtV33nknyc9OG4hl5jkr02vs2LGaPXu2EhIS1KFDB3Xt2lUFCxa0O6yAa9mypW688UbNnj07yZetrFmz6rnnnlPLli31yiuvqFOnTmrVqpXefvttG6P1n6eeekpr1qxRq1at1Lp1a9WvXz/Jeezrr79WeHi4ihUrluziAzKvM2fOJD7tdebMGbVr107du3d33JQ5l11rHPLVV19pwoQJ+uWXX1S9enX17t3busACrEKFCqpQoYIGDhyoLVu2JC6Uvnz5cuXJk0cul0v79+93VHFXulT4ioyMVOHChTVkyBC1b9/emCdhzp8/rzVr1igyMlLr169XwYIF1bRpU73wwguOumMY0l9//aWJEycqIiJCBQoU0IABA/TII4+katyamV1p2trLxzAnT2nbpEkTTZs2Tc2bN7/q+oV79uzRJ598oq5du1ocXeCYesPOrFmz7A7BNibeqJQrV67EmWX+rUuXLkl+jomJcWyROzNy+Xw+n91BZATly5fX/PnzU+y427dvV4cOHRx1wdBES5cu1eDBg9W7d2917do12UHp3LlzmjZtmiZMmKCRI0eqRYsWNkXqX1ebk/ZKnHZh/LJz585p1apVioyM1MaNGxMfVX300UfVpUsXR91Nm9an12644YYARWKt8uXLq27duql+6scp89JenkLmzjvvVP78+a+5rZPutJsyZYq6dOmS4tRXl6fO2rhxo0WRBd6xY8c0fPhwrV69+orvN2rUSK+88ooKFSpkcWSBk9rxmtPExcVpxowZmj17tuLj4/XII4+oa9euKlKkiN2hWW7lypWaOHGifvvtN91zzz166qmnUrzj1AkuXryodevWKSIiQuvWrVN8fLxKlCih1q1bq0+fPnaH5xeXx6k33nhjigUQJ93I8MILL2jNmjXKkSOHmjRpoubNmxvxmTb1eF6xYkV5vV7VrFlT7dq1S/GzzhPbmdu5c+f08MMPKyoqSmFhYbrnnntUvHhxuVwuHT58WN9++63mzp2rkiVLat68eY6ZpSE2Nlbt27fX4cOHU7xhZ8GCBYnraJjk3LlzjmlvU4/nTzzxhEqWLKk33njjmtsNHTpUBw4ccEyhLLNPbUkh5B/ly5dXjhw5Unz83ufz6fz58465QDx48GC1bNlStWvXNmpdkA4dOui2225LcXHwl19+Wb/99pvmzZtnUWSw0smTJ7VixQotX75cP/74o1wul6pVq6bZs2fbHRqug6kDsY4dO6ZpexM/54cPH3bkI9sHDx7U999/r+joaEmXFtysXr26I9eEGTdunNq3b+/o6d6upHr16oqLi1PNmjXVpUuXFJ/2ctod5D6fT8uXL9ekSZP0xx9/qG7duurdu7fuuusuu0MLiMWLF6tx48ZXXSPgzJkzWrVqlSIiIrR582bt3LnT4ggDIzVTof2bk25kyJUrl6pWrZpkXvkrcdKNDOXLl1e1atVSdQHUaXmnllNvTLuW/fv3KyIiwjEFXunSd85XXnlFq1atuuL7jRs31vDhw1O8kSmzMfGGnZR4PB6tX79eERERWrNmjX788Ue7Q/ILU79/L1u2TEOGDNEbb7yh1q1bX3GbpUuXaujQoXr77bcdc4P1tcTGxmr//v3Knz9/hi2UUAj5x9ixY9M08H7mmWcCGI117rnnHp08eVIFCxZUs2bNFBoaasTBq0qVKho3blyKc3V+++236tOnj3744QeLIoNdDh48qIiICEVGRioiIsLucPxi3bp1qZr66/z58xo/frxeeOEFC6IKPFMHYrgyp37hMNWRI0c0YsQIPfzww7rvvvuuuM369es1f/58DR8+3DHTw/37wtm1xqtOm3Pa6/Vq2bJlmjRpkv788081bNhQTz31lOMKPf9Vvnx5ZcuWTfXq1VOLFi1Ut25dZcmS5Yrbnjhxwph1z5zK1BsZypcvr9tvvz1V01NLzsnb1Ce2r+Xo0aNavny5IiIi9PPPPytLliz63//+Z3dYfnfw4EFt2bJFR48elSQVKVLEsTeu/NvlvI8cOSLJ2TfsXM22bdsUGRmplStXKiYmRgUKFFBoaOhV1xPJbEy9UUm69FTn8uXLdeedd6pOnTrJnvjavn27mjdvrnfffdfuUP1qxYoVWrVqlRISEvTggw+qefPmmjBhgiZNmqSLFy9KkurUqaMPP/www00LRiHEcF6vVxs3blRkZKS++uornTlzRqVLl1aLFi0UGhrqqAW7/q1q1ar68MMPde+9915zO6cVQky9gGSq8uXLq0mTJho2bNhVp09ZvXq13njjDcXExDjmc04hBJLzv3BcvHhR8fHxye4YP3r0qD7++GPt2bNHhQsXVocOHRy1uPLIkSO1adMmLVmy5KoFAZ/Pp7Zt26pOnTrq37+/xREGxr/X8EqNGjVqBCgSaz3wwAM6cOCAatasqd69e+u222675vb58uWzJrAA2717t5YvX64VK1bowIEDCgkJUZMmTdSiRQvHtC3AeM1scXFx+vLLLxPXqfR6vSpXrpweeughhYaGOu7pCJjn999/T7zJ8tChQ8qSJYsuXryoIUOGKCwsLMUnADOTFStWqE6dOsqbN2/ia9HR0SpUqFCSPKOjo7VkyRLHrV84d+5czZgxQ3///XeS10uVKqXOnTsrLCzMpsgCY+HChXrxxRdVoUIF5cqVSz/++KOeeOIJzZ49W4888ojKli2r3377TQsWLFD37t317LPP2h1yEhRC/vHMM8/o5ZdfNnKu5csuXLigtWvXavny5Vq3bp0uXLig22+/XS1btlSzZs1UuHBhu0P0m9ROjfXSSy/pjz/+0KeffmpRZIFl6gWk7t27a+jQoSpTpkzia5MmTVK7du2SPIr766+/6tlnn9UXX3xhR5h+99VXX+n1119XXFycnnvuOYWFhSW2+8GDBzVixAitXbtWjRo10rBhwxyz2G5mn7MyvcLDw6/6XnBwsAoWLKg77rjjqlOtOIFJXzhGjBihDRs2JDlenTx5Ui1atNCxY8eUN29excXFKSgoSJ999pkqVKhgY7T+8+CDD6pz587q0KHDNbebN2+eZs6cqc8//9yiyDIOp805fVlqntx2ypMw//bjjz8qMjJSX3zxhY4fP64iRYqoefPmatGihWP69WVffvllmrZn7YTMjUJIcplhSpHrcXmto2XLliWudVSqVCk1bNhQM2fO1KxZsxIXUHeaCxcuaOXKldq6dasOHz4sSSpWrJiqV6+uJk2apLhWTGZ15swZrVixQj/++KOOHTsml8ulQoUKqWrVqmrWrJljxiuXHT58OPG7yG+//aagoCDVqlVLoaGhqlmzpurXr6/Zs2c77nNeoUIFffbZZ4nHc4/Ho0qVKmnhwoVJnuJ1+prLhw8fTnzyqUiRIo6cklmSWrVqpWrVqunll1+WdKkw8tJLL+m5555Tz549E7cbN25c4o2JGcm1VxY1yC+//KKmTZvqueee0+OPP27UehmXZc2aVU2aNFGTJk105swZffnll1q+fLlGjRqld955RzVr1tTHH39sd5h+8dhjj2nQoEEqWrSounTpkuwEfP78eX388cdatGiR3nnnHZui9L+1a9eqc+fO1/x8u1wuPfLII5o5c6ZjCiHr16/X6dOnE3/2eDz64IMPdN999yUphMTHx+uvv/6yI8SAaNSoke655x699957euuttxQeHq4XX3xRW7Zs0YQJE1SoUCFNmjRJ9erVsztUvzp58qQ8Hk+S13744QdVqFDBcYPtfxs8eHCK22TPnl1dunRR3759LYjIGlf7wtG3b9/ELxwVKlRwVBFEkrZu3apWrVoleW369Ok6duyYRowYofbt2+v48ePq3LmzJk+erPfff9+eQP0sKipKt9xyS4rblS1bNs3Tj2RmTp0CzilrQFyPKlWqqEqVKho2bJg2bdqkyMhILViwQNOnT9fNN9+sFi1aOObOyrScm5w0BZx0aV2EHDlyJJlWZPr06Um2yZUrlx5++GGrQ8sQ/v77b0cVBjLzlCLp9eKLL2rVqlWKjY1VwYIF1b59e7Vo0UJ33XWXTp8+rRkzZtgdYsBs3bpV/fv3TyyAhISESLpU+Jo/f77ee+89jRo1StWqVbMzTL/btGmT+vXrp5iYGAUHByc+tRkTE6NFixZpzJgxev/99x1VFKhfv76kS2u1vfjii2ratGni9JX/vh7hNFe6v97Ee+6LFSvm2OLHv/31119Jrj00adJEL774YrJjWPXq1TVlyhSrw0sRhZB/rFixQuPGjdPIkSO1dOlSjRgxwnF3WaVFrly51KZNG1WuXFkzZ87UZ599pk2bNtkdlt+0bNlS27dv19ixYzVr1izVrFkzcY7Ky3NYnjp1SmFhYQoNDbU5Wv/hAtL/M+XEnDNnTg0bNkytW7dW37599eijj8rlcqlHjx566qmnlC1bNrtD9Lt169apd+/eiT97PB6FhYUluyPFab7//vurvufxeHTkyBGtWrVKEyZMUMGCBR3ziK6pXzgOHTqUbJyyevVqlSlTRu3bt5ckFSxYUF26dNHYsWPtCDEgsmXLpri4uBS3O3v2rGPvrvy3K00B56QLpW3atLE7hAzD7XarTp06qlOnjoYPH65Ro0Zp7ty5+uCDDxxTCLnagrpOt27dOvXq1UuTJ09OLIR4PB6NHDkyyXYul0vFihXT/fffb0eYfle9evVrrg9y4sQJff7554qIiND27dsdU/j675QiAwcO1M8//3zFKUU++uijDDelSHotXLhQLpdL99xzj1577TUj1j6RpD179qh79+4qUaKERo0apfr16yc+nX3mzBmtXbtWkyZNUvfu3bVw4ULdfPPNNkfsH4cPH1afPn1UvHhxjRw5UrVr104cl124cEEbN27Uu+++q969eysyMtIxa0uEhITo1KlT+vvvv7V7927ddtttrONlgF9//VVz5szR999/r+joaEmX1sKpUaOGwsLCkjzh7ATnzp1Lcv6+XLD/702n2bNnTyzuZyQUQv6RPXt29e/fX61bt9bw4cPVvn17Pf744+ratesVFyd0yhzEVxIdHa0VK1YoIiJCu3btUtasWfXAAw+oZcuWdofmVy+99JLuuecezZw5U19//bUuXLgg6dKTMVWqVNETTzyhBg0a2Bylf3EByUwxMTGaO3euoqKiVLp0af3111/63//+pyNHjjjq7rrLTL0jJU+ePNd8P1++fLrtttt05swZzZs3zzGFEFO/cFy8eFHZs2dP/Dk2NlZ79+5NNmVUqVKldPz4cavDC5hy5cppzZo1KT7Jtnr1apUrV86aoCxm0hRwSOrnn39WZGSkVqxYkTj3dtOmTe0Oy29Se2H01KlT2rNnj2MupC5atEh169a9YoFj0aJFiTdxDB8+XAsXLnRMIeRKi5+fO3dOq1atUmRkpDZu3CiPx6MKFSo4Zn0v6VLejz32WIpTihQsWFCRkZGOKYQMHjxYERER+vbbb/XAAw/o7rvvVosWLdSkSRNHz8YxYcIE3XTTTfr000+TjNukSzefhoaGqmHDhgoLC9P48eM1evRomyL1rzlz5ih37tyaO3du4hMwl2XNmlX16tVTlSpV1KpVK82dO1fPP/+8TZH617fffqsNGzYoIiJCERERWrBggYoWLapmzZqpbt26doeHAJgxY0biQui33XZb4jrEBw8e1JIlS7RkyRL1799fnTt3tjFKa2SWYzmFkP+45ZZbNGfOHI0bN07jxo3TzJkzr7idU+5IuezUqVNauXKlIiMjtW3bNrlcLtWsWVNvvvmmHnjgAcfOKd+wYUM1bNhQHo9HJ0+elCTlz5/fsRcRuIBkniVLliRO7/bmm2+qbdu22rhxo1599VWFhoaqZ8+e6t69+xULvnCm2rVra86cOXaH4TemfuEoXbq0fvrpJ9WuXVuStGHDBklK/PmymJiYZF9AM7N27drpxRdfVJUqVa76tEB4eLgWL16s119/3eLoAsfUKeA6dep01feyZMmiAgUKqEaNGmrZsqUjn3CUpH379ikyMlKRkZH666+/lDNnTjVu3FihoaGqXbu23G633SFa7rvvvtNzzz3nmO9jP/30kwYMGJDidvfee69GjBhhQUTW+u/UfufPn1ehQoXk8Xg0evRoNWvWzO4Q/SqzTymSXp07d1bnzp21f/9+RUREKDIyUi+99JJee+011ahRQy6XS16v1+4w/e67777TkCFDkhVB/i1Hjhzq0qWLo6aD3LRpkzp06HDNMWjevHnVoUMHffnll44phAQHB6tevXqqV69eksLurFmzNH36dLlcLn3++ecqXry4SpYsaXe4AZdZLoyn17p16/T2228nzr5xeZaZyw4dOqQPP/xQI0eOVNmyZXXffffZFKn/9e/fP9nYu1+/fkluqI6Pj7c6rFShEPIfHo9HH3/8saZNm6abb75ZnTt3dvQFwoiICC1fvlzffvutLl68qDvuuEODBw9Ws2bNkqyd4DT/XcwpKCjI0fleZuoFJEnau3dv4gWiy+tH7N27N9k2TtKxY0dt3bpVbdu21YABAxKfZLvnnnsUERGhSZMmadKkSYqMjNQrr7yimjVr2htwgDl9IJZa8fHxCg52zunf1C8c7dq1S7xrsFChQpo4caIKFiyY7E7hzZs3O2aaBenSVEnr16/XkCFDNGfOHN13330qUaKEXC6XDh48qA0bNmjnzp1q1qyZWrdubXe4fmPqFHC5c+e+6rHb4/Foz549WrFihaZPn67Zs2erYMGCFkcYGNHR0Vq+fLkiIyO1a9cuBQcHq27duurXr58aNGjAU7sOc+LECRUvXjzJa0FBQRo4cGCS1/Ply6cTJ05YHV7A/Htqv5MnTypfvnxq2bKlWrRooVtvvVU1a9ZU4cKF7Q7T7zL7lCLX66abblKfPn3Up08f7dixI/EpN5/Pp6eeekpNmjRR69atHfO9JDY2NlVrBhQrVkyxsbEWRGSNv//+W5UqVUpxu0qVKjlmHdr/ypEjh1q2bKmWLVvq5MmTWrFihZYvX65PP/1U8+bNU7Vq1a74ZFxmlZkvjKfX9OnT1bhxY7399ttXfL948eJ66623dObMGU2bNs0xhZArXUu8Wn/PiGsfOedKiB9s27ZNw4cP159//qmePXuqR48eji6CSNKAAQNUpkwZ9erVSy1atFDp0qWvuu3mzZsdMyAxYZqcKzH1ApKkKz5SP2DAgCQXWHw+n6MulsfExGjOnDlXPPlkzZpVffv2VYsWLTR8+HB17tzZMXdWSqkbiEmXiiPLli2zMjTbLV261LFrpZj0heOxxx7Tnj17NH78eCUkJKhEiRIaM2ZMsumyli5dqh49etgYqf+NGTNG1apV04wZMzRp0qQk75UuXVovvfSSHnvsMZuiCwxTp4CbMGFCitscOHBAnTp10nvvveeYmzjq1asnl8ul6tWr67XXXtODDz541ekPz507l+wCKjKXXLlyKSYmJtnrXbp0SfJzTEyMYxbOlqSwsLDEWQiefPJJ1alTJ/FGDScXeK/GSd9BUuvOO+/UnXfeqSFDhui7777TsmXL9NVXXyk8PNwx30uKFSumXbt26e67777mdr/88oujFlmOi4tLcdpe6dLUvqmZujuzy58/v8LCwhQWFqaDBw8mPhXlFJn9wnh67dy5M3FarGt56KGH1L9/fwsiskZmf3qNQsg/hg0bpiVLlqh69eoaO3asbrrpJrtDssS/5529kl27dmnZsmVasWKFjhw54pgBiclMvIA0a9Ysu0OwxZIlS/6vvXsPq6pa9wf+XaBhiqK4pbRQ2piSdyRM3BXJ9lhbRdQtW0rLe1srK+2yoYOZF1JLSYQuO81LaaWmJSBlO+yiaWKl2MVOaqmkIKIGeDmAyO8PY/24LLx01lqzOb/fz/P0JGst8R0yhmPM+b5jzEtW/t9www1Yvnw51q9f76aoXO9KFmJW8uGHH9b5Xnl5OQoKCpCZmYkdO3Zg8eLFbozMGFa/4PD09MQzzzyD2NhYnDlzxuFN8YYNG2Ljxo2WPN6y8md79OjRag8ltMrDNmtiPQLuclx//fWYOHEiFi5caHQoTvPkk0+iX79+dfbnmkcJ7dy5080RijMFBQXh448/Rp8+fS76uU2bNlnq6Np27drhxx9/xI4dO+Dp6YmTJ0+iT58+lpyzamKsnL4Ym82GsLAwhIWFYfr06fjkk0+MDslp+vTpg5dffhm33XZbnfeYDh48iFdffRVRUVHuDc6Fzp8/f9nJPbYi1VatWuGf//xntWcCmZ3Zb4z/XufOnbvosXeVvLy8cO7cOTdEJJfDVsH2r04devbsiX/96191HhfEJCcnx34W8U8//WQ/dmTQoEH461//anR4ThEUFIQlS5agQ4cOl/X5yiOFrIblBpIIg6CgoIu+7+Hhgc6dO2PSpEn2h7iJiPk4epgwANx9990YM2aMpY6Au1xffPEFxo0bh2+//dboUFyq6lFCv/76K3x9fTFgwABLPUj6cmzcuNFSzwhJTU1FXFwcEhIS6tyRvX79ejz11FOYM2cOIiMj3RugC+3btw+pqanYsGEDDh8+jAYNGiA8PBy9e/dGXFwcXn/9dYSGhhodplNd6XhluMFYVFSEAwcOoFmzZvD39zc6HKcqKipCdHQ08vLyMGjQIPTu3dt+5F1ubi4++eQTvPfee7j22muxZs2ay9pFYQZBQUFo3br1JZ/fVVJSgpycHMv8e17TkSNHYLPZah1/mJubi4qKilrPlBBzGTJkCMLCwi75nK/nnnsOX3zxBdatW+emyNzLbP1ciZDfnDx5Es2aNcPp06eRkZGBnTt3oqCgADabDX/605/QvXt39OvXz7Jbz0+cOIH3338faWlpyM7OBnChgvrbb7/Fa6+9hl69ehkcoXMFBQVd0fZjq07MwsVsE5RcmcOHD9f5Xr169dC0aVPLPky4KtZ+rnZztbtS1SPgdu7cCZvNZqkj4C7XmjVrsHDhQmzevNnoUJxu7969SE9PR1paGnJzc1G/fn2UlZUhLi4Ow4cPtz//zAou9wb/qVOnkJeXZ6n1+WOPPYYNGzagS5cu+Mtf/oKWLVvCZrMhLy8Pn3/+ObKzs9G/f//LOoLDrCoTfRs3bsSJEydgs9nQp08f3HfffZZLhrDKyMjAf/7zH5w7dw533XUX+vfvj5deegmvvPKK/Xkof/nLX7Bw4UJLHQNXUFCAZ555BpmZmQ7f79OnD6ZNm2apZ5Yq4XdBUFAQ6tWrV6tQo2PHjqioqMD3339vUGSuxbI+X7FiBebOnYuZM2fWWcjw3nvvYerUqYiNjcXw4cPdG6CbmK2fKxFSxbZt2zB58mT8+uuv9ptGwIXzWM+dO4fmzZtjwYIFllqIpaam2isKz507h3bt2mHAgAEYMGAAvL290aNHD7zxxhuWajNwYaBOnDjxos9EqcqqO4VYJqj77rvvsj9rs9mwfPlyF0ZjHLNNUM7C0s+vhNWeh1MVaz9Xu7na7UjVI+DS0tKMDsdtDh8+jHvvvRe9evWyzDNC8vLy7D/HH3/8EZ6enujZsycGDBiAW265Bb1797bk+jw2NvaK5iar3ThbuXIlli1bhpycnGqv+/v7Y9SoUZa9gVJTeXk5tmzZgvT0dGRmZuLs2bNo1apVnTeRxRzeeecdxMfH46abbkKjRo2wc+dOjBw5Em+88QaGDRuGwMBA/Pjjj1izZg3Gjx+PRx55xOiQne7IkSPIyspCfn4+gAsnMoSGhlJei7BITk6Gh4cHHnzwwWqvp6SkAAAeeughI8JyOZb1+fnz5/HQQw9h06ZN+POf/4zw8HD7eD5y5Ag2b96M/fv3IyIiAikpKZa9/jZbP9czQn6Tl5eHSZMmoWXLlpg7dy7CwsLsZ3SWlpZi69atmDdvHh544AGkp6db5gihJ598EjabDb169UJsbCxuvPFG+3tWf0hd79690aVLF6PDMFRERITDCapPnz6WmqC8vb0vOekcP34cu3btsuzkBAAPPvggPDw8ar0+ceJEA6JxH5Z+fjlKS0vx7rvvYsmSJdi4caPR4bgEaz9Xu6uzersdseKZ0xMmTKjzvfPnz6OgoAD/8z//A39/f0yePNmNkblW7969AVy4YRAfH4+//e1v9ucAWXl9PmfOHKNDMFTls4/y8vLsN0r9/Pws9QDly+Hp6Ynw8HCEh4fjf//3f/HRRx9Z6hlfNbEU7Lzxxhu455578PTTTwO4kBiZOnUqHn300WrzVvPmzZGenm7JREirVq3qrBoXa5o0aZLD1/9oN4adjWV97uHhgRdffBFvvPEGXn/9dSxdurTa+9dffz2eeuopjBgxwtL3mczWz7Uj5Dfz5s1Deno6UlNT0aRJE4efKSwsRFRUFAYOHIgpU6a4OULXmDhxIrZs2YKysjK0adMGkZGRGDBgAAICAlBcXIzQ0FBLVpwFBQVh9erV9IkQs2VuXeHYsWNYvHgxVq1ahfr162PEiBGWXHgzY+rnv/zyCzIyMpCbmwt/f38MHjwYzZo1Q0lJCd544w0sW7YMBQUFCAkJwcqVK40OV0QuU1lZGUpKSmo9RPjYsWNYsmQJ9u/fjxYtWuDuu+9Gp06dDIrS+e69994636tXrx58fX0RGhqKqKgoSx1fe8stt6CwsBA+Pj648847ERkZaV+LW3l9LsKIpXI6ODgYL730EsLCwgD8/3/LVqxYgZtvvtn+ue3bt2P8+PHYvXu3UaG6BOsR7JVYEn7CLS8vr9ozeNkKGcxCO0J+s23bNsTExNSZBAEAHx8fxMTE4MMPP7RMIuTll19GYWEhPvjgA6Snp+PFF1/Eiy++iI4dOyIiIsLSWUsxX+bWmY4ePYpFixbhnXfeQYMGDXD//ffjvvvuq3WTScyPpZ/v2rULo0ePxtmzZ+2vvfnmm0hOTsajjz6KgwcPonv37nj++eftF6EiYg5z5szBli1bqu3kOnnyJAYPHoyCggL4+Pjg1KlTSEtLw6pVq3DTTTcZGK3zsD3rpNLnn3+OLVu2IC0tDWlpaVizZg2uueYa9OvXD+Hh4UaH5zasN85Y2l1ZkHI5bDZbrYIWq2CpnD579iwaNWpk/7ryGSA1EwANGjSwPy/EKi52BPvatWuRmJhouSPYa9IOfWFw7bXXKvlhAkqE/CYnJ+eyKug6deqEJUuWuCEi9/Hx8cGwYcMwbNgwHD16FGlpadiwYQMWLlwIAJg/fz5iYmLQt29fyzy0bPbs2fD39zc6DDFAbm4uXnnlFbz77rvw9vbGAw88gOHDh1dbmIuYUXJyMlq0aIG5c+eiQ4cO+OWXXzB9+nTcc889qFevHpKTk/Ff//VfRocpIr/Dl19+iaioqGqvLV26FAUFBZg5cyaio6Nx/PhxjBo1Cv/+97+xYMECYwIVp6hXrx7uuOMO3HHHHTh79iz+85//ID093X7sgs1mw/vvv4+WLVvi+uuvNzpcl2G9ccbS7pSUFHh5ecHLywuXOqTCyokQloKduli98JL1CPaaWBJ+NbHs+JILWAoZajJbP1ci5DenTp1C48aNL/m5xo0b49SpU26IyBjXXHMNxo0bh3HjxmH//v1ITU1FRkYGYmNjMWPGDHz99ddGh+gUAwYMQElJSa3Xax4xERMTg86dOxsQoThbTk4O/v3vf+O9995D06ZNMWXKFMTExKBBgwZGh+Y2Zpug5Mr88MMPiIuLQ3BwMAAgMDAQ06dPx9/+9jfMnDmTJgnC2s/Vbmu3Ozc3t9Yuj8zMTNxwww2Ijo4GcOFc9TFjxiA5OdmIEN2C8QLz6quvxsCBAzFw4ECcPHkSGRkZ2LBhA9566y28/fbbCAkJsezOGdYbZyztvuaaa3D8+HGEhIQgMjISERERVOtyRo8//ji8vLyqvTZ58mR7YgCAw2t0M1uxYgW8vb2xcuXKWqePXHXVVbjjjjsQHByMqKgorFy50jInj9TEmvAbNGgQPD09a70eFRV1yQSwmbGsz2tiKWSoyWz9XImQ35w/f/6yqxH+iD/I3+uDDz5ASEgIWrRoUeu9wMBATJ48GZMnT8bOnTuxYcMGAyJ0DdYjJmpimaBiY2ORnp6OFi1aIC4uDtHR0dUW3CzMNkE5C0s/P378eK2dbpVft2/f3oiQDMHaz9Xu6qzW7rKysmo3CIuKivDTTz8hJiam2uf8/f1x/Phxd4fnNqwXmJWaNWtmf6D2kSNHkJaWZumHSLPeOGNp96effoovv/wS6enpmDlzJuLj4/HXv/4VAwYMwK233urw33Yxr8GDB9d6ra4TOUJCQlwdjtuwHsEuF8yZM8fh688++6ybI3EvlvV5TSyFDDWZrZ/rYem/CQoKQuvWrWtVKNRUUlKCnJwc7Nmzx02RuVZQUBBsNhuuv/56dO/eHSEhIQgJCUFgYKDRoblUVFQU7rzzTjzwwAP21xITE/Hqq6/WOmIiMDDQskdMxMbGwtPTEwkJCdVef+qpp1BRUYHZs2cbFJlzBQUFAQDatGlzyQSIzWZDamqqO8ISN2Hq56tXr0aXLl3sr5WXl6Njx45Yt24dOnToYGB0IvJ/ERUVhbvuust+IZWRkYHHHnsMSUlJ6Nu3r/1zH330EaZPn47NmzcbFapLJScnw8PDo9YROZXPGrDajWIRFuXl5diyZQs2bNiAzMxM1K9fH3feeSeio6Mv6/hqM2Mp2GHVo0cPJCYm4tZbb73o57Zs2YIpU6YgKyvLTZGJiHDSjpDfOKpQqIuVKhTeffddfPXVV9i5cyeysrKwfv162Gw2NGnSBMHBwQgJCUH37t3RuXNnS1XQ64iJC8yWuf29Bg0aZPnzZ6VuLP0ccHzkAFD72AEl/ETMZejQoZg/fz4A4E9/+hNefvllNG/eHLfffnu1z23fvh1//vOfjQjRLVgq5WtiPBJMuHh6eiI8PBzh4eEoKSlBUlISli1bhuPHj1/RQ9XNiLVymoWOYL+ANeFXVlaGd955B9988w3y8vLw9NNPIyAgABkZGWjfvr3lC5CFg9n6uRIhv7FKRfCVuummm3DTTTdhxIgRAC48zOvrr7+2/7dgwQKcP38e9evXR+fOnbFy5UqDI3YOHTHBpa4b4WzMNkHJlakroW/1SsqaWPu52m3tdt9zzz3Yv38/XnzxRZw7dw6tWrVCYmJirbXM+vXrcf/99xsYqbgC65FgrDfOWNu9f/9+bNiwARs2bMAvv/yCsLAwDB061OiwXI6pYKcqlgQv6xHsNTEm/HJycjBq1CicPHkSHTp0wFdffYXTp08DAHbs2IHNmzdb9j4ky/pczNnPlQiRaq699lr069cP/fr1Q3l5OXbs2IFly5bh008/tcyD0gGgdevW2LVrF8LCwgBc2IoKwP51pV9//fWi53manSYoHmacoJyFpZ9b9ed3JVj7udpt/XZ7enrimWeeQWxsLM6cOQNfX99an2nYsCE2btwIb29vAyIUV2I9c5rxxhnA1e7Dhw9jw4YNSE9Px969e9GtWzfcd999uOuuu9C8eXOjwxMXYkrw1rVjuyqrPSS+JsaE36xZs+Dr64s1a9agSZMm1YrTQkNDkZiYaGB0rsO0Pq+JsZDBjP1ciZA6sFQoVFVUVISdO3fad4N8++23KCsrQ/v27TF8+HAEBwcbHaLT6IgJ7gmKcXybcYJyBuZ+zoi1n6vdPO1u0KBBtV0gVdWrVw/NmjVzc0TuxXiBCfAeCcZ44wzgaXdMTAyys7MRFBSEgQMHon///rXW5gxYCnZqYknwsh7BLkBWVhbmz58PX19flJeXV3uvRYsWOHbsmEGRuRbj+rwSUyFDJTP2cyVC6sBSofDuu+/akx/79+9H06ZN0a1bN9x22214+OGH0blz5zovuM1MR0xwT1As47sqM05QzsDczxkTfqz9XO3majfAOb4BzgtMEavatWsXGjZsiHPnzmH9+vVYv359nZ+16rPNmAt2WBK8Vv35XSnGhJ+np2eda5OCggI0bNjQzRG5B/P6nKWQoSoz9nMlQurAUqEQFxeHq6++GkOGDEFSUpIlJyBHdMQE9wTFMr6rMuME5QzM/Zwx4cfaz9Xu2qzcboBzfAOcF5jMGG+cATztHjRo0GU/O8GqmAt2hAdrwi80NBRLly7F7bffbr/3YLPZUFFRgdWrV9c6lt0qmNfnjMzYz5UIqQNLhcKoUaOwc+dOrFq1CuvWrUOnTp0QHByM7t27o1u3bmjatKnRIboU8xETzBMUy/iuyowTlDMw93PGhB9rP1e7udoNcI5vZoxHgrHeOGNqd12JTSbMBTusGHd0sib8Hn/8cdx9993o378/IiIiYLPZsHLlSuzduxcHDx7EmjVrjA7RJZjX5yyFDFWZsZ8rEUIuNjYWwIWHc+3evdt+TNaqVatQVFSENm3a2BMjwcHBaNu2rcERuwbjgoR5gmJkxgnKGZj7OWPCj7Wfq91c7QY4xzfAeYEJcB4JxnrjjLXdrJgLdhgTvADnjk7WhF9gYCDWrl2LlJQUpKenw9PTE5988gnCwsIwb948tG7d2ugQXYJ1fc5UyFCVGfu5EiECAPDy8kJoaChCQ0Ptr+3fvx9ff/01MjMzMW3aNACw5MQMcC5IWCcoVmacoJxB/ZwLaz9Xu7nazYr1AhPgPBKM9cYZa7sBFaaxFewwJngBzh2dzAk/f39/zJ071+gw3Ip1fc5cyGC2fq5ESB1YKxSA/58Aqfzv4MGDAIAmTZoYHJnrMC5IWCcogHd8m22Ccgbmfs6KsZ8DardYH/MFJiPWG2es7QZUmMZWsMOY4AU4d3SyJvxOnTqFM2fOwM/Pr9Z7+fn5aNSoERo1amRAZK7HuD5nLWQwYz9XIqQOLBUKpaWl2L17tz3psXPnThQVFdmrbrp3745Ro0ahe/fuaNeundHhugzjggTgnKAAnvFdlRknKGdh7eeMCT/Wfq52c7Ub4BzfrBeYAOeRYKw3zljbDagwTQU7YlWsCb/4+Hg0atQICQkJtd5LTk7GmTNnMH/+fAMicy3W9TlrIYMZ+7kSIXVgqVDo3r07ysvL4eHhgXbt2mHAgAEICQlBSEgIrrnmGqPDExdinaAAnvFdlRknKGdg7ueMCT/Wfq52c7Ub4BzfrBeYrEeCsd44Y203oMI0NowJXlasCb8vv/zSfsR8TeHh4Zg+fbqbI3IP1vU5ayGDGfu5EiHk7r//fnTv3h3dunWDt7e30eGIG7FOUKzMOEE5A3M/Z0z4sfZztbs2K7cb4BzfrBeYrEeCsd44Y203K9aCHdYEL8C5oxPgTPgVFhbWOX6vvvpq/Prrr+4NyE1Y1+eshQxm7OdKhNSBpULh4YcfNjqEPwTGBQnrBAXwjO+qzDhBOQNzP2fE2s/V7tqs3G5WrBeYzEeCMd44A3jbzYi1YIc1wQtw7uhkTfj5+/tj69at6NWrV633tm3bhuuuu86AqFyPdX3OWshgxn5e+xBOQU5ODu666y48//zzOHToELZt21atQmHx4sUGR+g6R44cQW5ubq3Xc3NzceTIEQMico9BgwYhKiqq1utRUVEOX7cC1gmKdXxXTlCO/FEnKGdg7efAhYTfW2+9haeeegpjxozBgQMHAAAZGRnYv3+/scG5CGs/V7trs3K7Ac7xXXmBGRwcXO0Cs3Xr1lizZo1lLzBZjwQ7deoU8vPzHb6Xn59vX7tZDWu7gQuFaVVviFfq2LEjOnToYEBErvfll1/ijjvucPheeHg4srKy3BuQm2RlZWHixInw9fWFzWar9p7VE7xz5sxxmPh69tlnLbsLJj4+HklJSQ7fS05OxtNPP+3miNwjOjoay5Ytw6JFi3DixAkAwIkTJ7B48WIsW7YM//jHPwyO0DWY1+eVhQxbtmzBt99+i88//9zSSRDAnP1cO0IcYK5QiIiIcLgzok+fPpbdGQFwHjFhxsytM7CO7+joaMyfPx8+Pj74+9//Dl9fX5w4cQLr1q3DsmXLMGXKFKNDdAnWfs565ABrP1e7udrNOr4Bzkp51iPBWCvlWdsNcFbKsxbssCZ4WbHu0B81ahQOHTqExMREJCYmwtPT076zMyYmBmPGjDE4QtdgXZ+z7nwyYz9XIsQB5i3oDz74oP0iq6qJEycaEI24EusExTq+zThBOQNrP2dN+LH2c7Wbq92s45v1ApP1SDDWG2es7QZUmFaTlQt2WBO8gI5orsnKCT+bzYZp06Zh5MiR2LZtGwoLC9G0aVP07NkTAQEBRofnMqzrc9ZCBjP2cyVCHGCuUJg0aZLD1x966CE3R+JejAsS1gmKdXybcYJyBtZ+zprwY+3najdXu1nHN+sFJuuZ06w3zljbzYq1YIc1wcu6o5M14VcpICDA0uvSmljX58yFDIC5+rkSIQ4wVygwYl2QsE5Q7OPbTBOUM7D2c9aEXyW2fl5J7ebAOr6ZLzAZjwRjvXHG2m5AhWlMBTusCV7WHZ2sCT8AKC8vR3Z2NvLy8lBaWlrr/UGDBrk/KDdhW58zFzKYrZ8rEeIAa4UCK9YFSSW2CYp5fJttgnImtn7OnPBj7edqN0+7Wcc36wUm65FgrDfOWNutwjSugh2AM8HLuqOTNeH33XffYdKkScjNzXVYwGKz2Sy5TgU41+eshQxm7OdKhDjAWqEAAEFBQQ4flt6xY0fLPiyddUECcE5QrOPbjBOUszD2c9aEH2s/V7u52s06vlkvMFmPBGO9ccbabhWmcRXssCZ4WXd0sib8nnnmGXh7e2P58uVo27Yt6tevb3RIbsG6PmctZDBjP1cipA6MFQrAhRuCnp6etV6Pioqqc9I2O9YFCesEBXCObzNOUM7A2s9ZE36s/Vzt5mo36/hmvcBkPRKM9cYZa7tVmMZVsMOa4GXd0VmJLeG3b98+LFiwAD169DA6FLdiXZ+zFjKYsZ8rEeIAa4UCAMyZM8fh688++6ybI3Ef1gUJ6wTFOr7NOEE5A2s/BzgTfqz9XO3majfAOb5ZLzBZjwSrxHbjrBJbu1WYxlWww5rgZd3RCXAm/AICAuxH/DFhXZ+zFjKYsZ8rEeIAa4UCK9YFCesExTq+zThBOQNrP2dN+LH2c7WbC+v4Zr3AZD0SDOC8cQZwtluFaVwFO6wJXtYdnawJv7i4OCQkJKB9+/YIDAw0Ohy3YV2fV2IrZDBjP1cixAHWCgUAKCsrwzvvvINvvvkGeXl5ePrppxEQEICMjAxTdewrwbogYZ2gWMe3GScoZ2Dt56wJP9Z+rnZztZt1fFdiu8BkPRKM9cYZa7tVmMZVsMOc4GXc0cma8Js5cyaOHTuGyMhI+Pn5oXHjxtXet9lsSE1NNSg612FdnwOchQxm7OdKhDjAWqGQk5ODUaNG4eTJk+jQoQO++uor+w3EHTt2YPPmzZg9e7bBUboG44KEdYJiHd9mnKCcgbWfsyb8WPu52s3VbtbxDXBeYLIeCcZ644y13SpM48Ka4GXd0cma8OvYsSNsNpvRYbgd6/qctZDBjP1ciRAHWCsUZs2aBV9fX6xZswZNmjRBp06d7O+FhoYiMTHRwOhch3VBwjpBsY5vM05QzsDaz1kTfqz9XO3mwjq+WS8wWY8EY71xxtpuQIVpTAU7rAle1h2drAm/up6/a3Ws63PWQgYz9nMlQhxgrVDIysrC/Pnz4evra1+IVGrRogWOHTtmUGSuxbogYZ2gWMe3GScoZ2Dt56wJP9Z+rnZzYR3frBeYldiOBGO9ccbabhWmcRXssCZ4WXd0sib8WLGuz5kLGcxGiRAHWCsUPD09HVbYAUBBQQEaNmzo5ojcg3VBwjpBsY5vVqz9nDXhJ8KAdXwzX2AyHgnGeuOMtd0qTOPEluBl3dHJmvADgKKiImzcuBE///yzw/k7Pj7egKjEFVgLGQDz9XMlQhxgrVAIDQ3F0qVLcfvtt8PDwwPAhb+LiooKrF69GmFhYQZH6BqsCxJWrOMbMN8EJb8fc8KPtZ+r3TztZh3frBeYrEeCsd44Y223CtP4MCZ4WXd0sib8Dhw4gJiYGJSWluLs2bPw9fVFYWEhzp07Bx8fH3h7e1tynQpwrs9ZCxnM2M+VCLkItgqFxx9/HHfffTf69++PiIgI2Gw2rFy5Env37sXBgwexZs0ao0N0CdYFCcA5QVViG99mnKCchbGfsyb8WPu52s3VbtbxzXqByXokGOuNM9Z2qzCNC2uCl3VHJ2vCb86cOejatSuSkpLQrVs3vPrqqwgKCkJGRgZeeOEFJCUlGR2iS7Cuz1kLGczYz5UIqQNjhUJgYCDWrl2LlJQUpKenw9PTE5988gnCwsIwb948tG7d2ugQXYJ1QcI6QQGc49uME5QzMPdzgC/hx9rP1W6udldiG9+sF5isR4Ix3zhjpMI0roId1gQv645OVrt370ZCQgKuuuoqAEBZWRk8PT0RGRmJkydPYtasWXj77bcNjtL5WNfnrIUMZuznSoQ4wFqhAFxYhM6dO9foMNyKdUHCOkGxjm8zTlDOwNrPAc6EH2s/V7u52g1wjm/WC0zWI8GEiwrTuAp2WBO8rDs6Ac6EX2lpKby9veHh4QEfHx/k5+fb37vxxhvxww8/GBid67Cuz1kLGczYz5UIcYC1QuHUqVM4c+YM/Pz8ar2Xn5+PRo0a1bll2cxYFySsExTr+DbjBOUMrP2cNeHH2s/Vbq52s45v1gtM1iPBAM4bZwBnu1WYxlWww57gZdvRyZrwCwgIwOHDhxEaGooOHTrgzTffRK9evVCvXj2sWrXK4X03K2Bdn7MyYz9XIsQB1gqF+Ph4NGrUCAkJCbXeS05OxpkzZzB//nwDInMPtgUJ6wTFOr7NOEE5A2s/Z034sfZztZur3azjmxXrkWCsN85Y263CNK6CHeYEL+OOTtaEX//+/e3Xmo888gjGjh2LHj16wGazoaKiwrIFHqzrc4CzkMGM/VyJEAdYKxS+/PJLTJs2zeF74eHhmD59upsjch/GBQnrBMU6vs04QTkDaz9nTfix9nO1m6vdrOMb4LzAZD0SjPXGGWu7K6kwjaNghzXBy7qjkzXhN3r0aPuvu3XrhvT0dHz22WcoKSlBz5490a5dOwOjcx3W9TlrIYMZ+7kSIQ6wVigUFhbWefTV1VdfjV9//dW9AbkJ64KEdYJiHd9mnKCcgbWfsyb8WPu52s3VbtbxzXqBadV56lJYb5yxthtQYRpTwQ5rgpd1Rydrwq+mli1bYtiwYUaH4XKs63P2QoZKZujnSoQ4wFqh4O/vj61bt6JXr1613tu2bRuuu+46A6JyPdYFCesExTq+azLDBOUMrP2cNeFXE0s/r0nttjbW8a0LTC6sN85Y263CNK6CHau261JYd3SyJvwAzgRvTSzrcxUymKefKxHiAGuFQnR0NObPnw8fHx/8/e9/h6+vL06cOIF169Zh2bJlmDJlitEhugTrgqQmlgmKdXwD5pugXIGlnzMn/Fj7udrN027W8c18gcl4JBjrjTPWdqswjatghxXrjk7WhB9rghfgXJ+rkME8/VyJEAes+g/xpYwaNQqHDh1CYmIiEhMT4enpifLycgBATEwMxowZY3CErsG6IAE4JyjW8W3GCcpZGPs5a8KPtZ+r3VztZh3frBeYrEeCsd44Y223CtMuYCnYATgTvKw7OlkTfqwJXtb1uQoZzNPPbRWOeqZQO3DgALZt24bCwkI0bdoUPXv2tPRD67KyspCQkIDExESqBcnlTFB79uwxIDJxhejoaJSUlCA+Pr7OCapmVbEVqJ9zYe3najdXu1kNHToUI0aMwKBBgzB69GhUVFQgJSUF9erVQ2xsLL7//nt8+OGHRofpdBMmTEBFRYX9SLC1a9dWOxJs4cKF6NSpk9Fhulxubi7FjbOaWNo9ePBgjB8/Hv369TM6FLdjLNi5nARvZmam0WE6XWRkJI4dO4aioiKqHZ2sgoODsWDBAoSHhxsdiluxrs+XLl2Ko0ePIjY2Frt27cLYsWNx9uzZaoUMAwcONDpMpzNjP9eOkDowVihUCggIsHTioybWIybMmLl1FsbxzVppx9zPGbH2c7Wbq92sWCvlmY8Eq4qpUr4qlnazVsqzVk6zPvOJdUcnwJnwYz15hHV9zrrzyYz9XIkQB1i3oAOcExTrgoR1gmId32acoJyBtZ8DnAk/1n6udvNhHN+sF5isR4IBnNclAGe7VZjGVbDDmuC1asL+UlgTfqwJXub1eVUqZPjjUiLEAdYKBdYJinVBwjpBsY5vM05QzsDaz1kTfqz9XO3majfr+K6J5QKT9cxp1usS1narMI2rYIc5wcuINeHHmuBlXZ8DKmQwSz9XIsQB1goF1gmKFesExTq+zThBOQNrP2dN+LH2c7Wbq92s4xvgvMBkPRKM9bqEtd1W7ceXwlqww5rgBTh3dLIm/FgTvKzrcxUymIcSIQ6wViiwTlAA54KEdYJiHd9mnKCcgbWfsyb8WPu52s2FdXyzXmCyHgnGel3C2m5WrAU7rAle1h2drAk/q/bjS2Fdn6uQwTyUCHGAtUKBdYJiXZCwTlCs49uME5QzsPZz1oQfaz9Xu7mwjm/WC8yamI4EY7wuYW03oMI0poId1gQv645O1oQfK9b1uQoZzEOJEAdYKxRYJyjWBYlV+/GlsI5vVqw/T9aEnwgD1vHNfIHJeCQY63UJa7tVmMaNJcHLuqOTKeE3a9YsjBkzBq1atcKsWbMu+Xkr/rvGiqmQwez9XIkQB1grFJgmqKpYFySsmMa32Sco+f2YEn6s/Vzt5mp3VUzjuyqmC8yqWI8EY70uYW23CtP4MCZ4WXd0MiX8Nm3ahKFDh6JVq1bYtGnTRT9rs9kss07V+pyrkMHs/VyJkMvAUqHANEFVxbQg0QRVm5XHt9knqN9L/Zwr4cfaz9VurnZXxTS+q2K6wKyK9Ugw1usS1narMI0La4KXdUcnU8Kv6tr0UutUK9H6nKuQwez93FbhaOYRygoFVkOHDsWIESMwaNAgjB49GhUVFUhJSUG9evUQGxuL77//Hh9++KHRYTpFREQEXnrpJQQFBSEiIuKin7XZbMjMzHRTZO6l8W1t6uciItYTGRmJY8eOoaioyPIXmFUFBwdjwYIFCA8PNzoUEZe5+eab8fLLLyM0NBS33HILZs6cib59+wIAtm3bhokTJ2LXrl3GBukkKtgBoqOjUVJSgvj4+DoTvDX/jbeCpUuX4ujRo4iNjcWuXbswduxYnD17ttqOzoEDBxodpjjRiRMnsHz5cmRnZ+PYsWNo0aIFunbtipEjR8LX19fo8MSJYmNjL1nIMHv2bDdF415m6+dKhDhwORUKe/bsMSAycQUtSLgwj2+zTVDyf8Oa8GPt52o3V7sZxzfrBebgwYMxfvx49OvXz+hQRFxGhWmOWbVgRwneC3Jzcy27o1MJPyA7Oxvjxo3D+fPn0atXLzRv3hzHjx/H1q1bAQBLlixB165dDY7SNVjX54zM2M+VCHGAtUIBAIqKirBx40b8/PPPDi+srThB1WTlBUlNjBMU6/g24wTlLIz9nDXhx9rP1W6udrOOb1ZZWVlISEhAYmKi5Y8EY71xxtruqlSYxkUJXutTwg8YMmQIvLy8sGjRInh7e9tfLy4uxvjx41FWVoa1a9caGKFrsK7PWZmxnysR4gBrhcKBAwcQExOD0tJSnD17Fr6+vigsLMS5c+fg4+MDb29vS05QrFgnKNbxbcYJyhlY+zlrwo+1n6vdXO1mHd+smI4EY71xxtrui1FhmrULdpgSvDUx7uhk1aVLFyQlJaF379613svMzMTkyZOxe/duAyJzLab1uQoZzNnP9bB0BwICAnD69Gmjw3C7OXPmoGvXrkhKSkK3bt3w6quvIigoCBkZGXjhhReQlJRkdIguw7ggmT59Otq2bVvnBDVjxgzLTFBVsY7vffv2ISkpqdrPGrhws2z8+PGYPHmyQZG5Fms/37dvHxYsWIAePXoYHYpbsfZztZuv3SzjWxeYXA/PNvvDN38v1nZfTMuWLTFs2DCjw3C5mgU7AQEBOH78OFasWIEVK1ZYtmCH6aHCVbE+JB7gTPi1adMGRUVFDt8rLi6Gv7+/myNyD6b1uR4Sb85+rkSIA3FxcUhISED79u2pKhR2796NhIQEXHXVVQCAsrIyeHp6IjIyEidPnsSsWbPw9ttvGxyl87EuSJgmqKpYx7cZJyhnYO3nrAk/1n6udtdm5XYzjW9dYF4oVGLFeOMM4G23CtN4CnaYErxVPfPMM/D29sby5cvr3NFpRawJvyeeeAIzZsxAy5YtqxWvbN++HSkpKZg6daqB0bkO0/pchQzm7OdKhDjAWqFQWloKb29veHh4wMfHB/n5+fb3brzxRvzwww8GRuc6rAsSpgmqKtbxbcYJyhlY+zlrwo+1n6vdXO1mGt+6wOTFeuOMtd0qTOMq2GFN8DLt6KyKKeEXGRlZ7evi4mKMHDkSjRs3RrNmzXDy5EkUFxejSZMmmDdvniWP62ZdnwM8hQxm7+dKhDjAWqEQEBCAw4cPIzQ0FB06dMCbb76JXr16oV69eli1ahX8/PyMDtElWBckrBMU0/g2+wTlDKz9nCnhx9rP1e4LWNpdFdP4ronlAlNHgnHdOKuKtd0qTKvNygU7rJh2dFbFlPBjutdQldbnXIUMZu/nSoQ4wFqh0L9/f/uuj0ceeQRjx45Fjx49YLPZUFFRYdm/F6YFiSYorvFt9gnq91I/5/rZM7W1KrWbF+vfAdMFpo4E47pxVhVzu1WYZu2CHSV4uXZ0VsWU8GO611AV69q0KqZCBrP3cyVCxG706NH2X3fr1g3p6en47LPPUFJSgp49e6Jdu3YGRuc6TAsSTVBczD5B/V7q51w/e6a2VqV282L9O2C6wNSRYFw3zqpibbcK06xfsKMEL++OTqaEHyvWtWlVrIUMZqREyG9UoVBby5YtMWzYMKPDcDmmBQnrBKXxzYW1n4uIWBnzBSbLkWBVsd44Y223CtOsTwlerp89a8JPeLEWMpiREiG/UYXCBeXl5cjOzkZeXh5KS0trvW/Fh9QxLUhYaXwLAyX8RKxL45v3ApPpSDDWG2es7a5KhWl8GBO8TD973WMRNqyFDGZkq6ioqDA6CPlj+O677zBp0iTk5ubCUbew2WzYs2ePAZGJiMilRERE4KWXXkJQUBAiIiIu+lmbzYbMzEw3RSYi/1ca38Bnn32GGTNm4Nlnn611gfnf//3fmDp1qiVvEA8ZMgReXl51HglWVlZmmSPBYmNjr+jG2ezZs10Yjfuwtruqy/k7sGK7WdVM8DZv3hzHjx/H1q1bAcBSCV4Rsa6ahQz5+fkoKipyWMjg5+eHtLQ0gyKVqpQIqQNjhUJ0dDRKSkoQHx+Ptm3bon79+rU+U7M6R8SMGMe3iIiI2egCE+jSpQuSkpLQu3fvWu9lZmZi8uTJ2L17twGRiYj8PkwJXu3oFLEuFTKYk47GcoBpC3pV+/btw4IFC6pV2VmVFiS8WMe38FHCT8S6WMa3jtbgPRJMRKyL6ZlPOqJZxLqYjruzEu0IcYCpQqGqwYMHY/z48ejXr5/RobicjpjgxTq+hYuOHBCxLo1vLqxHgon1qTCNV2RkJMaNG4eoqKha77333ntYtGgRNmzYYEBkIiJidUqEOMC6BT0rKwsJCQlITExEYGCg0eGIuATr+BYuSviJWJfGt/XpSDBhoMI0XswJXpYdnSIif1Q6GssB1i3oM2fOxLFjxxAZGQk/P79azwOx2WxITU01KDrX0oKEB+v4Fi5MRw6IsNH4tj4dCSYMqh4TdKkjg8T8aiZ4i4uLMXLkSIcJ3nnz5lkyEaIjmkVEjKdEiANPPPEEZsyYgZYtW9aqUEhJScHUqVMNjM51WC+6tCDhwjq+hYsSfiLWpfFtfTpzWhipMM3aWO81VDV9+nS0bdu2zh2dM2bM0I5OEREX09FYv9EWdF46YsL6NL6FDfORAyJWp/EtIlajZx8JAx3RLCJiPO0I+Y0qFHjpiAnr0/gWBjpyQMS6NL5FxMpUKS8MtKNTRMR4SoT8hnUL+qxZszBmzBi0atUKs2bNuuTn4+Pj3RCVe2lBYn2s41u4KOEnYl0a3yJiZSpMEwY6ollExHhKhJDbtGkThg4dilatWl3yIXU2m82SiRAtSETECpTwE7EujW8RsTIVpolVaUeniMgfixIh5KomPy6VCLESLUhERERERESMp8I0sSrt6BQR+WPRw9KlmhMnTmD58uXIzs7GsWPH0KJFC3Tt2hUjR46Er6+v0eE5TWxs7BUtSGbPnu3CaERERERERHjULEzLz89HUVGRw8I0Pz8/pKWlGRSpiIiIWIUSIWKXnZ2NcePG4fz58+jVqxeaN2+O48ePY+vWrQCAJUuWoGvXrgZHKSIiIiIiImamwjQRERFxNyVCxG7IkCHw8vLCokWLqj2orri4GOPHj0dZWRnWrl1rYIQiIiIiIiIiIiIiIlfGw+gA5I9j3759uP/++6slQQCgcePGGD9+PPbu3WtQZCIiIiIiIiIiIiIiv48SIWLXpk0bFBUVOXyvuLgY/v7+bo5IREREREREREREROT/RokQsXviiSeQnJyMrKysaq9v374dKSkpePLJJw2KTERERERERERERETk99EzQshFRkZW+zo/Px9FRUVo3LgxmjVrhpMnT6K4uBhNmjSBn58f0tLSDIpUREREREREREREROTK1TM6ADFWx44dYbPZjA5DRERERERERERERMQltCNEREREREREREREREQsS88IERERERERERERERERy1IiRERERERERERERERELEuJEBERERERERERERERsSwlQkRERERERERERERExLKUCBERERERIbd7927ExMSgW7duaN++Pfbs2XPZv7d9+/ZITk62f71u3Tq0b98ev/zyiytCdbnY2FgEBwc79XtGREQgNjbWqd9TREREREQuXz2jAxAREREREeOUlZXh0UcfxVVXXYW4uDg0aNAArVq1MjosERERERERp1EiRERERESE2KFDh3D48GHMmjUL0dHRRocjIiIiIiLidDoaS0RERESE2IkTJwAAjRs3NjgSERERERER11AiRERERESEVGxsLEaMGAEAeOSRR9C+fXvce++99v8cfT4iIsLpcZw6dQoJCQmIiIhAp06dEBYWhtGjR+O7774DACxcuBAdO3a0J22qmjp1Km6++WaUlJQAuPA8jn/+85/Yvn07hgwZgi5duiAyMhLbt28HAHz44YeIjIxE586dMWTIEHz//fcOY8rJycHYsWPRrVs33HrrrUhJSUFFRUW1z5w5cwZz5sxBeHg4OnXqhDvvvBOvvfZarc+JiIiIiIixlAgRERERESE1bNgwTJgwAQBw77334rnnnrN/7U7Tpk3DW2+9hb59+2LatGkYM2YMvLy8sH//fgBAVFQUzp07h4yMjGq/r7S0FBs3bkTfvn3h5eVlf/3gwYN47LHHEBERgSlTpqCwsBATJkxAamoqZs+ejcjISEyaNAmHDh3Co48+ivPnz1f7vuXl5Rg3bhyaN2+OJ554Ap06dUJycjIWLlxo/0xFRQUmTpyIZcuW4bbbbkNcXBxuuOEGPPfcc5g9e7YL/7ZERERERORK6RkhIiIiIiKkgoODUVpaildeeQU333wz7rrrLgDAK6+84tY4Pv30U/zjH/9AbGys/bXx48fbf92mTRsEBwcjNTXVvoOl8vcVFhYiKiqq2vf7+eef8fbbbyM4OBgA0LZtW4wdOxZTp07F+++/b38YvI+PD55++mns2LEDt9xyi/33l5SU4LbbbkN8fDwA4J577sGECROwaNEi3HvvvfD19UVmZia++OILPProo5g4cSIAYPjw4Xj44Yfx+uuvY8SIEWjdurWT/6ZEREREROT30I4QERERERExVJMmTZCdnY2jR4/W+ZmoqChkZ2fj0KFD9tfS0tLQsmVL9OjRo9pn27Zta0+CAEDXrl0BAD179rQnQaq+npOTU+vPGz58uP3XNpsNw4cPR1lZGbZt2wYA+Oyzz+Dp6VnrCLExY8agoqICn3322SXbLSIiIiIi7qFEiIiIiIiIGOrxxx/H3r17cccdd2Do0KFITk6ulZzo168frrrqKqSmpgIAiouL8fHHHyMyMhI2m63aZ1u2bFnt68oHwV977bXVXvf29gYAFBUVVXvdw8MD/v7+1V674YYbAACHDx+2/9/Pz8/+PSoFBgZW+5yIiIiIiBhPiRAREREREbks5eXlLvm+/fr1w0cffYT4+Hj4+fnhtddeQ//+/fHpp5/aP+Pj44PevXsjLS0NAPDBBx+gtLQUAwcOrPX9PD09Hf45db2uh5uLiIiIiFibEiEiIiIiIlKNj49PrV0SAHDkyBGX/Zl+fn4YPnw4XnrpJWRmZqJp06a1nlUSFRWFAwcOYPfu3UhLS0OHDh1w4403Oj2W8+fP19qR8vPPPwMArrvuOvv/8/PzcerUqWqf++mnn6p9TkREREREjKdEiIiIiIiIVOPv74+ffvoJJ06csL/2ww8/4Ouvv3b6n1VeXo7i4uJqrzVv3hx+fn4oLS2t9vrtt9+OZs2aYfHixdixY4fD3SDOsnLlSvuvKyoqsHLlStSvXx9hYWH2WMrLy6t9DgCWLVsGm82G22+/3WWxiYiIiIjIlalndAAiIiIiIvLHMnToUCxbtgxjx47F0KFDcfz4cbz99tto27YtTp8+7dQ/6/Tp0wgPD8edd96JoKAgNGzYEFu3bsU333yD2NjYap+tX78++vfvjxUrVsDT0xP9+/d3aiyVvLy8sHnzZvzrX/9Cly5dsHnzZnzyySeYMGECfH19AQARERG45ZZb8MILL+Dw4cNo3749Pv/8c2RmZmLkyJFo3bq1S2ITEREREZErpx0hIiIiIiJSTWBgIObOnYvi4mLMnj0bmzZtwnPPPYeOHTs6/c9q0KAB7r77buzZswcLFy7E7Nmz8fPPP2PatGkYPXp0rc9HRUUBAMLCwuDn5+f0eIALzxJZvHgxCgoK8Pzzz+Obb77BQw89hEceecT+GQ8PD7z88ssYOXIkPv74Y8yePRv79+/Hk08+ibi4OJfEJSIiIiIiv4+tQk8GFBERERERk/jhhx8QFRWFuXPnYtCgQUaHIyIiIiIiJqAdISIiIiIiYhqrV69Gw4YN0bdvX6NDERERERERk9AzQkRERERExCVOnz6NM2fOXPQzvr6+8PT0vOT32rRpE/bt24fVq1dj+PDhaNiwobPCFBERERERi9PRWCIiIiIi4hLJyclISUm56GcyMzNx/fXXX/J7RUREoKCgALfeeiuee+45eHt7OytMERERERGxOCVCRERERETEJXJycpCTk3PRz4SEhMDLy8tNEYmIiIiICCMlQkRERERERERERERExLL0sHQREREREREREREREbEsJUJERERERERERERERMSylAgRERERERERERERERHLUiJEREREREREREREREQsS4kQERERERERERERERGxLCVCRERERERERERERETEspQIERERERERERERERERy1IiRERERERERERERERELOv/AQfAuFPjHoa9AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# TODO(Grisha): Seems too big for some assets.\n",
    "stats_by_symbol[\"SR\"].sort_values().plot(kind=\"bar\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79ccc47c",
   "metadata": {},
   "source": [
    "## Per prediction quantile rank"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "9d873df2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-18T11:37:17.077691Z",
     "start_time": "2023-08-18T11:37:07.988813Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO  removed rows with nans: 7367 / 6039243 = 0.12%\n"
     ]
    }
   ],
   "source": [
    "tag_mode = \"prediction_magnitude_quantile_rank\"\n",
    "stats_by_pred_magnitude = dtfmod.cross_val_apply_metrics(\n",
    "    [df_res], tag_mode, metric_modes, config\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "37219b86",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-18T11:37:17.534556Z",
     "start_time": "2023-08-18T11:37:17.091002Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='prediction_magnitude_quantile_rank'>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "stats_by_pred_magnitude[\"hit_rate_point_est_(%)\"].plot(kind=\"bar\", ylim=(45, 55))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "cbe61754",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-18T11:37:17.923083Z",
     "start_time": "2023-08-18T11:37:17.537463Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='prediction_magnitude_quantile_rank'>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "stats_by_pred_magnitude[\"total_pnl\"].plot(kind=\"bar\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7ce0501e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-18T11:37:18.272224Z",
     "start_time": "2023-08-18T11:37:17.925761Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='prediction_magnitude_quantile_rank'>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "stats_by_pred_magnitude[\"SR\"].plot(kind=\"bar\")"
   ]
  }
 ],
 "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": "3.8.10"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}