{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c000",
   "metadata": {},
   "source": [
    "# Concentration response\n",
    "\n",
    "[Hits, effects and cell loss](hits.ipynb) asked whether a treatment did anything. This page asks how much\n",
    "of it was needed, and what the cell did on the way there.\n",
    "\n",
    "The dataset is [the OASIS pilot](../../datasets/oasis_pilot.ipynb). OASIS is a liver toxicity screen: its main cell\n",
    "line is HepaRG, a hepatic progenitor line that differentiates into hepatocyte-like cells and keeps much of the\n",
    "drug-metabolising machinery a real liver has. That is the point of using it: a compound that only becomes toxic\n",
    "after the liver metabolises it will not show up in a cell line that cannot metabolise it. Most of its thirty-six\n",
    "compounds were dosed over ten concentrations, a three-fold ladder from 15 nM to 300 uM, with eight replicate wells\n",
    "at each concentration spread over eight plates; a few, such as berberine, over a different range.\n",
    "\n",
    "Three things make a dose series harder than a single-concentration screen:\n",
    "\n",
    "- Most compounds never plateau inside the tested range, so a four-parameter logistic has no EC50 to find.\n",
    "- Distance from the controls grows when a compound kills cells, which is a different finding from a phenotype.\n",
    "- Most of the ladder is usually empty. You screen four decades because you do not know where the compound's\n",
    "  effective range is, so the concentrations below it and, sometimes, above it carry nothing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c001",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:00:43.324022Z",
     "iopub.status.busy": "2026-10-21T01:00:43.323644Z",
     "iopub.status.idle": "2026-10-21T01:00:49.129225Z",
     "shell.execute_reply": "2026-10-21T01:00:49.127817Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 2831 × 99\n",
       "    obs: 'Metadata_plate_map_name', 'Metadata_Plate', 'Metadata_Well', 'Metadata_Site_Count', 'Metadata_Count_Cells', 'Metadata_Count_CellsIncludingEdges', 'Metadata_Count_Cytoplasm', 'Metadata_Count_Nuclei', 'Metadata_Count_NucleiIncludingEdges', 'Metadata_Object_Count', 'Metadata_Row', 'Metadata_Col', 'Metadata_CellCount', 'Metadata_SiteCount', 'Metadata_Compound', 'Metadata_Concentration', 'Metadata_ConcentrationUnit', 'Metadata_ConcentrationRecorded', 'Metadata_CellLine', 'Metadata_Control', 'Metadata_Control_Type', 'Metadata_Perturbation', 'Metadata_Perturbation_Type'\n",
       "    var: 'object', 'feature_group', 'feature', 'channel', 'scale', 'angle', 'gray_levels', 'radial_bin', 'params', 'is_feature', 'feature_kind'\n",
       "    uns: 'mantispy'\n",
       "    layers: None (.X)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scanpy as sc\n",
    "\n",
    "import mantispy as mt\n",
    "\n",
    "adata = mt.ds.oasis_pilot()\n",
    "# EMPTY wells hold no compound and no vehicle, so they are neither treatment nor control.\n",
    "adata = adata[adata.obs[\"Metadata_Compound\"].astype(str) != \"EMPTY\"].copy()\n",
    "heparg = adata[adata.obs[\"Metadata_CellLine\"] == \"HepaRG\"].copy()\n",
    "heparg"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c002",
   "metadata": {},
   "source": [
    "## The usual preparation\n",
    "\n",
    "Nothing here is specific to dose response: normalize each plate against its own controls, then select features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c003",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:00:49.135293Z",
     "iopub.status.busy": "2026-10-21T01:00:49.135123Z",
     "iopub.status.idle": "2026-10-21T01:00:49.457602Z",
     "shell.execute_reply": "2026-10-21T01:00:49.456856Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2831 wells, 99 features kept\n"
     ]
    }
   ],
   "source": [
    "mt.pp.normalize(heparg, by=\"Metadata_Plate\", reference=\"negcon\")\n",
    "mt.pp.feature_select(heparg, na_cutoff=0.0)\n",
    "heparg = mt.pp.subset_features(heparg)\n",
    "print(f\"{heparg.n_obs} wells, {heparg.n_vars} features kept\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c004",
   "metadata": {},
   "source": [
    "## A mantispy object is an AnnData object\n",
    "\n",
    "scanpy works on it directly. The PCA, the neighbour graph and the UMAP below come from scanpy; the colours come\n",
    "from the columns `mt.ds.oasis_pilot` attached."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c005",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:00:49.459357Z",
     "iopub.status.busy": "2026-10-21T01:00:49.459118Z",
     "iopub.status.idle": "2026-10-21T01:01:12.815364Z",
     "shell.execute_reply": "2026-10-21T01:01:12.814503Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<path>:7: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n",
      "  plt.tight_layout()\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABKwAAAGuCAYAAAC9V57lAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjExLjIsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvgI3uAAAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs3Xd4VFX6wPHv1MxMeu+EFHrvRZqAgg0FG4qi6Np7W3V3XXtd15+uvYMdOyqoCFKk917SIL33ZDL9/v6YZJIhhVCD+H6eh0fvnTP3nhlC5sx73vMelaIoCkIIIYQQQgghhBBCnCLUnd0BIYQQQgghhBBCCCGak4CVEEIIIYQQQgghhDilSMBKCCGEEEIIIYQQQpxSJGAlhBBCCCGEEEIIIU4pErASQgghhBBCCCGEEKcUCVgJIYQQQgghhBBCiFOKBKyEEEIIIYQQQgghxClFAlZCCCGEEEIIIYQQ4pQiASsh/gJ++uknFi9e3Nnd+EsrKChg7ty5FBYWdnZXhBBCiFPad999x/Llyzu7G+JPSn5+hDh9qBRFUTq7E0Kc6r777juqqqqIjY3lrLPOavG4zWbjs88+A2Dw4MH079//iO/x2WefkZiYyKhRo45Ln5sbOnQoQUFBLFmy5JTqV1vy8vLYtm0b1dXVREVFkZKSQnx8/Am/74l8rUuWLOGss85i2bJlTJgw4bhfXwghhDhd9OzZk759+/L111+flPsVFxezdOlSrFYrV155JXq9vs22WVlZbNy4EY1Gw6hRo4iKijopffyz+frrrwkPD2f8+PEn/fon++dHCHHiSIaVEB3w8MMPM2fOHC655BLq6+tbPL5gwQLmzJnDnDlz+OGHH47qHrfeeivz5s07Dr09vk5mv3bv3s3EiRNJTk7mxRdf5Mcff+Txxx8nKSmJ8ePHs3nz5hN6/1P170AIIYQQx99vv/3G5MmTGThwIA899BBz5szBbDa32f6+++6je/fuzJs3j7feeouuXbvywgsvnNQ+/1ncf//9vPnmm51y/enTp3PmmWeesHsLIU4eCVgJ0UEJCQnU1dXx7bfftnjsww8/JCUlpVP6dbrYvHkzI0aMACAzM5Nly5bx2WefsXz5cjIzMzEYDPzxxx+d3U0hhBBCnCbq6+t5+OGHycnJaTWDvrk33niDl156iQULFvDjjz/y66+/8s477/Dggw8e9WSlODGeffZZbrvtts7uhhDiONB2dgeE+LOIioqid+/ezJ07l1mzZnnO5+fns3jxYh577DEeeeSRNp+/e/dudu/ejUajYfjw4Z4lbo3LCW02G/v372fu3Lme+02dOhWAH374gfLycgC0Wi2RkZGMHDkSf3//Fvepr69nxYoV1NbWMnLkSOLi4lrtz+Guebz71R6Xy8XVV19NUFAQ33//PQEBAV6Px8fHs3DhQvbu3et13ul0smHDBg4ePEhAQACjR48mODjYq83HH39Mjx49GD58OHv37mX79u3ExMQwZswY1Gp1h19ra9fp06cP/fr1A6CiooI1a9ZQXV1N165dGT58OBqN5ojeByGEEEK0zeVysWnTJjIyMvDz82PUqFGEhYW1aGe1WlmxYgWVlZUMGzaMxMREFi9ejM1m4/zzz/e0mzZtWofv/eKLLzJmzBjPuABg9uzZPPXUU7zwwgsdvlZGRgbbt29Hq9UydOhQYmJijvg1zp8/n9jYWMaMGUNaWhpbtmwhPDyccePGodW2/vXucPcFSE1NZfv27dBQTiIxMfGo7jt37lxqa2s5cOCAZ0wVEhLieY+aXyc9PZ3NmzeTkpLCkCFD+OWXXzz1PjUaDeHh4YwcOZKgoKAOX/+7774jODi4RQmGE/XeCiFOHPlXJ8QRmDNnDjNnziQnJ8cTcProo4/w9/fnoosuajVglZ+fz5VXXsmWLVs444wzcDqdXHXVVdx22228+OKLOBwOli9fjsPhID8/31MksmfPnp5B0aZNm8jOzoaGgNT27dvJz89n3rx5TJ8+3XOvTZs2ceGFFwIwYsQIHn/8ce6+++5WX8vhrnk8+3U4K1euZO/evfz73/9uEaxqpNVqPcEhgF27dnHJJZdQUVHB6NGjyczMJD09nRdeeMFrVu2GG27g5ptv5ssvv2Tt2rWEhoaydOlSBg8ezNKlS9Hr9R16rY3XmTdvHlu2bMFoNDJlyhT69evHa6+9xoMPPkhKSgpJSUmsWbOG4OBgvv76a/r27dvh90EIIYQQrUtPT+fiiy8mNzeXMWPGkJ+fz86dO3nsscd46KGHPO127tzJ+eefj81mY+TIkTz33HNcffXVLFy4kMrKSq+AVUcdOHCAAwcOcMUVV7R4bPz48XzwwQeYzWZMJlOb1ygpKeHaa6/l999/Z8SIEQQHB3PXXXcxa9YsnnrqqSN6jXfddRdTp05l2bJl/PTTT0RHR7Ns2TJSUlJYsWIFfn5+R3Tf0tJSZs+ezYoVKzwTetdccw2zZ8/m9ddf90zAdfS+y5cvx2KxUFxc7BlTdenSxRNQarzOwoULWbp0KUFBQQwdOpQhQ4awbds29u3bBw2Bx507d5KZmclbb73F7NmzO3T9hx9+mL59+3oFrE7EeyuEOAkUIcRh9ejRQxkxYoRisViUkJAQ5amnnvI81rNnT+WWW25R0tLSFEB58sknPY85HA5lwIABSrdu3ZScnBzP+ZUrVyoajUZ56623POcCAwOVm266qcN9uvfee5WAgAClrKxMURRFqaurU2JiYpRRo0Yp1dXViqIoitPpVG688UYlKipKmTRp0hFf83j0qyOeffZZBVAWLlzYofZms1mJj49X+vfvr5SWlnrOP/TQQwqgLFq0yHPOx8dHSUxMVObOnes5t2LFCgVQ3nzzTa/rtvdafXx8lISEBOWdd97xnDt48KDy888/K4Dy4IMPes6XlpYqAwYMUOLj45W6ujpFURTlt99+UwBl2bJlHXqNQgghxF9Vjx49lIsvvthzbLfblZ49eyopKSlKfn6+5/xzzz2nAMrnn3+uKIqi2Gw2JTk5WRk4cKBSXl7uaff3v/9diY2NVYYMGdLmPa+//noFUCoqKlo8tnjxYgXwGrc1evLJJxVA2bVrV5vXdrlcyqhRo5SYmBhl9+7dXq/rm2++OaLXqCiKEhkZqSQmJiovv/yy59zWrVsVlUqlPPvss0d0X0VRlDFjxiixsbFKRkaG59yWLVsUHx8f5bnnnjvi+yqKoiQkJCiXX355q+9HZGSkkpCQoLzwwguecwcPHmzz/Xv88ccVo9HoNZZu7/pH+/NzpK9RCHHiSQ0rIY6Aj48PM2fO9BTmXrt2Lfv27ePaa69ttf1PP/3E9u3befrpp72W5o0dO5Zp06bx2muvdfje5eXl/PLLL3zyySfMnTsXPz8/qqur2bp1KwDff/89+fn5PPHEE54leWq1mieffJLS0tKjuubx6FdHlJWVARAaGtqh9t999x05OTk8/vjjXs957LHHCA8P55VXXvFqHxQUxDXXXOM5HjduHN27d+e3337rcB8BTCYTN9xwg+c4ISGB//3vf4SFhfHYY495zoeGhvLkk0+Sk5PTas0zIYQQQnTc4sWL2bdvH//85z+Jjo72nL///vtJTEzk5Zdf9rTLyMjgkUce8SoR8Mgjj1BVVXXU96+trQXAaDS2eKwxq6qmpqbN5y9btoy1a9fy73//m969e3vOa7VaZsyYcUSvsZFarebOO+/0HA8cOJBhw4Z5jW06ct8VK1awatUqHn30UZKSkjxtBg0axJVXXtlirNqR+3aE0+nk3nvv9RwnJCR4/r+qqorFixd7xpY+Pj7U19ezfv36I7pHoxPx3gohTg5ZEijEEbr22mt54403WL16NfPmzaN3794MHz6c9PT0Fm0bP1hzc3P55JNPUBQFRVGgoW7S3r17URQFlUrV7j0fffRRnn32Wfr06UP37t0xGo1UVlYCeNb5N9YcGDx4sNdzIyIiWq1j1ZFrHs7xuAbgSa+uq6vrUPsdO3YAMGzYMK/zPj4+9O/f3/NeNBo4cGCLa8TFxZGbm9vhPtIweGutL3379sVgMHidb+zb9u3bueqqq47oPkIIIYRo0tbnvkajYfDgwSxcuNCr3aGf+35+fse0OU7jZ7zdbm/xmM1m82rTmo0bNwIwevToNtt09DU26t+/f4vxY1xcHLt27Tqi+zaOVYuLi1uMVWtra8nNzaW6utpTsqEj9+2I/v37t1rr88UXX+SRRx4hOTmZXr164evr69m58UjGls2diPdWCHFySMBKiCM0bNgw+vTpw5tvvsmPP/7Iv/71rzbbWq1WaKj1pNPpvB4LCwvjqquuwuFwtHisuWXLlvHEE0/w6quvcvvtt3vOr1ixggULFngGFQ6HAxqCNoc69FxHr9me43GNRo21qXbt2sXEiRMP275xwNjaazUYDC0GlK3VxdLpdJ6/n44KDw9vtS9t9YM2BrdCCCGE6LjDfe43joHaGwu1Nj7oqMaJv9YCJgUFBdCwQczh+t9eUKujr7FRR8Y2HblvY/tt27aRlpbm9ZjJZOKaa67xGtOdyDHVli1beOCBB3jyySe9xtfbt2/nq6++OqKxZXMn4r0VQpwcErAS4ihcc801/P3vf0ej0XD11Ve32a579+4A3HPPPQwdOrTda7aVZdU483X55Zd7nW+cLWrUmMadlpbmNbNotVrJzs72yrLq6DWPR786YsqUKYSGhvLRRx9xxx13tHnP8vJyQkJCPK81NTW1xe4u+/fvJzk5+Yj7QDuvtT1JSUktBniN/QCOui9CCCGEcGv+uX9optT+/fs9jzf+Nz09ndjYWE8bl8tFZmZmu0Gl9vTq1YugoCA2bdrU4rGNGzfSrVu3dssa9OjRAxp2jO7WrdsxvcYj0ZH7No5Vb7rpJiZPnnzE92jL0YypNmzYAMc4Pm3NiXhvhRAnh9SwEuIoXH311VxzzTU8/vjjREVFtdnusssuIyQkhMcffxyXy+X1mKIopKameo7Dw8OpqKhocY3GQFPzoEhVVRXvvfeeV7vp06fj4+PTon7TW2+91Wpac0eueTz61RG+vr689NJLbN68mX/+858tZtBcLhdPPvkkH3/8MQAzZszAYDDw0ksvebX97rvvSE9PZ9asWUfcB9p5re258soryczM9KpVpSgK//nPfzAYDJ4aEUIIIYQ4Oueddx4BAQG8/PLLOJ1Oz/lly5axadMmz+f+ueeei5+fH6+++qrX8+fPn9/hsgOt0Wq1XHvttfz8888cOHDAc37z5s2sW7eOm2666bD9j4mJ4emnn6a+vt7rsaysrCN6jUeiI/e94IILiI2N5cknn2w1A61xAu5IHc2YqrWxZV1dHW+++eYxXf9EvLdCiJNDMqyEOApRUVHMnTv3sO2Cg4NZsGABF198MQMHDuSSSy4hPDyczMxMfv31V8455xyef/55aBhkvf/++zz77LNER0cTFRXF1KlTmTFjBk8//TSXX345d9xxBw6Hg6+++oqbb76ZW2+91XOvmJgYXn31VW666SYqKiqYNGmSZ619r169vPrV0Wsej3511OzZs3G5XNx9990sWrSIGTNmEB0dTX5+PvPnzycnJ8cTsIqOjua9995jzpw5TJ06lXPPPZcDBw7w5ptvMn36dG677bYjvn97r7U9t956K8uWLeOKK67glltuISkpiYULF7Js2TI+/PBDrxleIYQQQhy5oKAgPv74Yy6//HImTpzI9OnTyc/P5/XXX+ess87iwQcfhIZx13vvvcesWbM499xzmTp1KhkZGZSVlTFy5MgWhdcPHDjAihUroFmQ5LPPPsNkMhEWFsb555/vafv444+zevVqzjzzTO644w5sNhsvv/wyU6ZM8SrQ3RqTycR3333HBRdcwKBBg7jiiisICgpi3bp1VFdXs3Dhwg6/xiPRkfuaTCZ++OEHLrzwQvr27csVV1xBZGQkWVlZ/PbbbwwbNoy33nrriO997rnn8txzz/Hkk08SHx9PSEgI06ZNa/c5U6ZMYejQocyZM4c777wTrVbLV199xY033sjatWuP+von4r0VQpwcErASogOmT5/u2QWmLQEBAVxzzTUMGDDA6/yYMWNIT0/n66+/ZuvWrRQVFZGUlMSXX35Jz549Pe2ef/55evfuzbZt20hNTaVHjx5MnToVk8nEpk2beP/999m3bx/h4eF8+eWXmEwm1q9f77Xk7IYbbmDw4MHMnz+fffv2MX78eGbOnMmTTz7p1f8juebx6FdHXXvttcyYMYMffviBbdu2kZubS3R0NP/4xz+48MILPbsfAsyaNYuRI0fyxRdfsHv3bgICAliwYEGLANPVV1/N8OHDW9zrrLPOajFwbeu1tncdjUbDt99+yy+//MKSJUvYtWsX48aN44033vB6D2JiYrjmmmvazcgTQgghhHvcdeiGMdOmTWP//v18/vnn7N27F19fXz7//HMuuOACr0zyyy+/nN69e/PZZ5+xb98+Ro4cyaxZsxg+fHiL2kTFxcUsX74cgMTERBITEz3L0hITE70CVgEBAaxevZrPP/+c9evXo9FoeP3115kxYwZq9eEXrQwfPpzU1FTmz5/P9u3bqamp4eKLL/bKxD6S19hY/7O58ePHt3jfOnLfwYMHs3//fr799ls2bdpEcXExiYmJfPjhh/Tv3/+o7vuvf/2Lrl27snHjRs9yzMaAUlvX0el0/PHHH3z44Yfs2rWL4OBg5s2bR0xMDGvWrPGagG3v+sf689PR1yiEOPFUytFWrxNCCCGEEEKIU5zD4SAiIoKLL76Yd999t7O7I4QQooOkhpUQQgghhBDitFBYWNiibug777xDRUUFl1xySaf1SwghxJGTJYFCiBPm999/Jzs7u90206dPJzAw8KT1SQghhBCnr82bN/PII49w/vnnEx4ezsaNG/nkk0+44YYbmDJlSmd3TwghxBGQgJUQ4oTZtWsXW7ZsabfNlClTJGAlhBBCiOPivPPOIyEhgZ9++ondu3cTExPD0qVLOfPMMzu7a0IIIY6Q1LASQgghhBBCCCGEEKcUqWElhBBCCCGEEEIIIU4pErASQgghhBBCCCGEEKeUk17DyuVykZ+fj7+/PyqV6mTfXgghhBAdpCgKNTU1xMTEoFbLHNfpTMZnQgghxJ9DW+Mzi8WCzWY7omvp9XoMBsMJ6OXxcdIDVvn5+cTHx5/s2wohhBDiKOXk5BAXF9fZ3RAnkIzPhBBCiD+X5uMzi8VCYoIfhcXOI7pGVFQUBw4cOGWDVic9YOXv7w8Nb25AQMDJvr0QQgghOqi6upr4+HjPZ7c4fcn4TAghhPhzaG18ZrPZKCx2cmBzAgH+HcuKr65xkTgkC5vNJgGrRo1p5gEBATIgEkIIIf4EZInY6U/GZ0IIIcSfS2vjswB/dYcDVn8GJz1gJYQQQgghhBBCCCGOL6fiwql0vO2pTgJWQgghhBBCCCGEEH9yLhRcdCxi1dF2nen0yRUTQgghhBBCCCGEEKcFybASQgghhBBCCCGE+JNz4aKjC/063rLzSMBKCCGEEEIIIYQQ4k/OqSg4lY4t9etou84kSwKFEEIIIYQQQgghxClFMqyEEEIIIYQQQggh/uROt6LrErASQgghhBBCCCGE+JNzoeA8jQJWsiRQCCGEEEIIIYQQQpxSJMNKCCGEEEIIIYQQ4k9OlgQKIYQQQgghhBBCiFPK6bZLoASsxEmVUVLL2owyukf6MzwxpLO7I4QQQgjxl7e9Ip2c+mIGBXUj1hTe2d0RQghxlFwNfzra9lQnAStxUpTVWll/oJx752/D4nD/03jh4v5cNiy+s7smhBBCCPGXVFBfxu9Fm5l78GcATBofXh50F4l+0Z3dNSGEEEICVuLE+2VXAXd8vhW70zvl8MtNORKwEkIIIYToBG+kfcd3eSu9zpmdVlaUbJOAlRBC/Ek5j2CXwI6260wSsBInlMPp4u7521oEqwAiAw2d0ichhBBCiL+yvVUHWwSrGoX5BJ70/gghhDg+nIr7T0fbnurUnd0BcXpbmVaCxd5ydaxeo+bR83t3Sp+EEEIIIf7Kfi5c3+r5eGME50SPPOn9EUIIIVojGVbihLI5Wi/lZtRriAiQDCshhBBCiJPNpbQ+PuvqF41GJfPZQgjxZyVF14U4Anvyq1s9f8PYxJPeFyGEEEIIAVl1hS3O6VRapsWc0Sn9EUIIcXy4UOFE1eG2pzoJWIkTqsJs9zruHR3Akxf1YUhCSKf1SQghhBDir6zOafE6nhQxmKu6TiXOFN5pfRJCCCEOJTm/4oS6bGg8Jr0GAI0Kbp2QLMEqIYQQQohOdFHsWM//B+h8mZ14jgSrhBDiNOBSjuzPqU4CVuKE6hcXyNc3jyIhxIRTgX8t2MWW7IrO7pYQQgghxF/WtNgxPNDjSnw1BqrtdTy+60Oq7XWd3S0hhBDHyNmwJLCjf051ErASJ9wfaaVklZsBqDTbeWbh3s7ukhBCCCHEX9ryki2epYGZdfl8l7uys7skhBDiGJ1uASupYSVOiKJqCwt3FBDsq8Pm9N5/wP5nyD0UQgghhDjN7K/OZmdVJil+sThcTq/HHIqzzecJIYT4a3M6nXzxxRfMnz+frKwsunbtym233cbZZ599Qu8rAStx3JXVWpn22iqKqq0ATOsfTVKYL5mldRh0au49q3tnd1EIIYQQ4i9lW0UaD+14C6finki8sstZ7K/Jxuy0EmUI4cLYMZ3dRSGEEMfIpahwKR3cJbCD7QCeeuop0tPTueGGG+jSpQuLFy/mnHPO4csvv+Tiiy8+hh63TwJW4rjIrTBTUGWhT0wAazPLPMEqgF92F7H90bNJK64hKtBAhL+hU/sqhBBCCPFXkFqTj9PlpGdAHMuLt3qCVQBptTnMG/EviizldDFFYtT6dGpfhRBCHLsjWep3JEsC//GPf6DT6TzHAwYMYMOGDbz99tsSsBKntkU7C7jri63YnQpJ4b48dkEfr8djg40Y9Rr6xwV1Wh+FEEIIIf5KXt7/A19lrwZgUmR/egZGeD0eaQghSO9HkN6vk3oohBDiz6J5sKqRoiioVCe2DpYErMQxe+m3/did7rpUmSV1XD9vIwEGLSa9FpeikBBi4vd9RUzsGdnZXRVCCCGEOO1V2Go9wSpftY0Zfi+RpLfRPymUeSVDuDw0m/6BG1AcQ1Bpkzq7u0IIIY4TJ2qcHdxbr7FyYXV1tdd5Hx8ffHzaz7rdtGkTCxYs4O233z7qvnaE7BIojklhlYWsMrPXObtTodrioKzOSnGNleWpJfxt3ia2ZFd0Wj+FEEIIIf4qNhTnoDTscfNs11X0N9Xgp7LSW5/PM7GLGWzYjta6AKV8NoqrtrO7K4QQ4jhRGmpYdeSP0lDDKj4+nsDAQM+fZ599tt17HDx4kIsuuohLLrmE66677oS+HsmwEsdk3tqDnuyqQzU/71JgS1YFg7sEn8TeCSGEEEL89by9Zz01ZgP+Jgtxeu+JRQ1NdUZxFYMzG9S9T34nhRBCnBJycnIICAjwHLeXXZWdnc3EiRMZPnw4H3300QnvmwSsxDHRqdtes2rQqrE43MU91SoY1EVqWAkhhBBCnGgatRqzxYd6i56V5TFcHJkFDfVG7JjQq+rdDdVhoOnSuZ0VQghx3BxN0fWAgACvgFVbcnJyOPPMM+nfvz/z589vta7V8SZLAsUxmXNGIj2j/AEI89Nz96QUIgN80KhVnmBV75gA3rxqCEMSQjq5t0IIIYQQp7+HB04kUG9AQcVnRVdQopnJzto4njkwkHPWn8OCou5UqM5CFfIRKrUUXRdCiNOFU1Ef0Z+OysvL8wSrvvrqq5MSrEIyrMSxCvbV89MdYyiqsRLqq+eD1QcoqrZ6tSmpsTKlT1Sn9VEIIYQQ4q9kcFgcq6fdQYXVTKTRn2t//JbVFSZUBvdk4v17RzPN3If/i0zp7K4KIYT4E3jmmWfIyMjA4XDQq1cvz/m4uDiWL19+wu4rAStxzLQaNbFBRgC2ZVe2eNzfID9mQgghhBAnk1Grw6gNBGB7UQEcMhnur2t/ByghhBB/Pi5UuDq4kM5F67WoW/PYY49xzz33tDh/ojOtJJIgjqsRSaEs3lPkOfbz0fDCxf07tU9CCCGEEH9lw2PiWJqVAVo7Kp1Ct4Aw7uw7prO7JYQQ4jg7mhpWHREeHk54ePgx9OzoSMBKdIjLpfDzrkLqrA6m9ovCqNPw/dY86u1Opg2IIcikB+C6M7qi16jYmlPJ4C7BXDUyobO7LoQQQghxWqpz1LG5YjMmjYkhwUMorTezMG0/gQYD07r1RKN2z7K/cvZ5vL5pPSXmOi7s0Ysx8TI+E0KI09GR1KZyKh3PsOosErASHXLvl9v4fls+AO/+kUlciJFl+0oAmLvmIAtuPQN/ow6VSsXVo7py9ajDX3N3fhWbsyroExMgBdmFEEIIIY5AvbOep/Y+RaGlEIDhwSP5dLWavJpqAFZmHeSls85BpVLhq9fz99FjO3RdxbocnHmgH4dKG39CX4MQQgjRHglYicOy2J2eYBVAWnEtacW1nuPMkjoGPLGYS4bE8dyM/qjVh08tXJdZxtXvr8fuVFCp4NUrBnF+/5gT9hqEEEIIIU4nqTWpnmAVwMaK9eTX9oaGJR7f79/L6sXpPDTjTGaM7tehayq1b6LU/p/7QBUIod+g0nY5MS9ACCHEceeuYdWxpX4dbdeZOr6PofjL8tGqCTY1FVNTqSDgkELqLgW+3JTLol0FHbrmgm152J3uFERFgW825x7nXgshhBBCnL6CdEFex0a1LyhNXz5UDrDanDz15VJKq+s6dE2l/ptmB1VgXXL8OiyEEOKEc6HG2cE/HS3O3plO/R6KTqdSqXjrqiEkhfkS7u/D49P68OGcYfSKDkBzSDbVEz/u4eUlqYe9ZlSA0es4OsjYZlshhBBCCOEtwTeBK+KvIFAXSJQhiru738kT4ycR4+uP2gKmfBUuLdT7KVz78df8vj/j8BdVR7V/LIQQQpxEKkU5uZW2qqurCQwMpKqqioCAgJN5a3ECfLDqAE/8tKfF+f9dMYhpA9pe4mexO3nwmx2sySijX2wg/3fZQAJNJ3ZLTCGEEEdGPrP/OuTv+vShKAr3vP8jv+/IwBbcND2t12j49Y45RAf6t/1cRzZK1d/BmQuG81EHPHTyOi6EEKJDWvvMbjz3xbbemPw1HbqOucbJzIF7TunPfqlhJY7JdWMSGZIQzC2fbCa/yuI5n1Xafuq5QafhlZmDTkIPhRBCCCH+OlQqFf+97nwWb0vjnh8Xec7bnE4KqmvaDViptF1QhX5xknoqhBDieHMdwVI/F6f+LoGyJFAcswHxQVw2rGkXGR+tmom9IgDYeLCcVWmlOJyuTuyhEEIIIcRfh0atZuqg7gxLiPOcSwgJomdkOBaHnRVZB9lRVNjuNYQQQojOJhlWwsumg+VsOFjOgLggzkgJ6/Dz7p7cnaRwP7JK65jYK4I+MYE89M0OvtiYA8DYbmHMnTO8Rc0rIYQQQgjRvh+zdpNvruas2O4kBYR26DkqlYp3Zl3EV5t3YnU4uXhQH8DFzG8/ZXtxBQD3jjiDO4aNPMG9F0IIcbI4FRVOpWPfuTvarjNJwEp4LNtfzPVzN+JqyAx8ZeZALhwY2+HnN9asyqus58wXl3Og2bLAP9JK2ZZTyZCE4OPfcSGEEEKI09QL25fx9t61ALyxZw3fnz2HRP+QDj3XqNMxe+RgAKrqV7Cz4FYeHlHH0qy+vLvjTN7YvF4CVkIIcRpp3AGwY21lSaD4E1m4o8ATrAL4cXvBUV3nP7/s8wpWNfI3SHxUCCGEEOJI/Ji12/P/tXYry/PTj+o6B8ofQK2qQ62Cs7ruYkB4Fn56/XHsqRBCCHF8ScBKoCgKX23KIbfC7HW+S4jpqK5Xa3V6HauA+87qTvfItot8CiGEEEKIJjZnHVvKvmBkVBYGjc1zvovf0WWrO13ek4khRoUXJ51zzP0UQghx6nAp6iP6c6qTlBfBsz/v452VmQBoVBAVaGRo12DuO7v7UV3vb2MTWZVegsXuIsCg5fMbRtInNvA491oI0aks1WCpgsA4UJ3669+FEOLPxKU4+T7nfoot+0kIgGt7BfFb9kSmJQxkUmy3o7pmTMBt5Fa9AIBR14d3znsereboJieFEKcmh8MBgFYrX/P/qk63JYHykyz4ZVfTLjFOBa4d3ZUbxiUd9fVGJoWy5N7xpBfX0jsmgAh/w3HqqRCiM9kcLu75YgtL9hTSjSze0r1EXLdBcMXnoNF1dveEEOK0Uesoodiy33Ns1Fby6cQphBuOLlgFEB14KwHGcTicFfj7DEOtlvGZEKeDwvpyHt/9AVl1RfTVxXOl/3hiIqOJiIjo7K6JTuA6gmLqrhPem2MnAau/qLUZZbz6exp6rZpwfx+yy5uWAyaG+R7z9eOCTcQFy6ydEKeTj1fuZuGuIkDFLrrymH0276W/xFMvPEvY6FncPD65s7sohBB/anO3b2FheiqJQSZS4v2wuWoB0KoM+Go7vntzW3z1fY9DL4UQp5L/7f+K9No8ALbaDhBkUVGZnYNPkQ8zu8ykT2Cfzu6iEEdNAlZ/QcU1Fq6ftxGzzV1rKsxPz1m9I8irsHDhwBgm947s7C4KITqB06WwPbcSPx9tqzXnytM2AFGe4zLFvdS3rMbMez/vo3d0AOO6h5/UPgshxOlicWY6j/+xDIBNBXCx+jxGJe3GpTgZET4Hk1Z2Whbir6jGbmVfRRHxfsFEmVqOz0rNlZ7/V+MiXdmGggss8Fr6a/x3wH8xaSWR4K/ChRpXB5cEdrRdZ5KA1V9QTnm9J1gFUFpr4+np/Tpt6V6l2caegmoSw3yJDjSe0HvllJupsTjoGeWPWi11d4Ro5HQpXDd3IytSSwC4Z3J37prsvfRkelQ5Hx/wpxpf1Lg4U72Vxc4hLHKNACDnkI0bhBBCdNz+slKv4+35el4883+d1p/84ioKS6vp0TUCX5PPCbuPoijsLyvFqNOREBh0wu4jxJ9Rgbmay5Z8RL65GoNGy9tjL2VMVKJXm/F+fTlYXogCGFVaFFXTQi+Ly0K1o1oCVn8hTkWNs4PF1DvarjNJwOovqHukH7FBRvIq6wHoFxtImO+JG4i0J6usjkveWktJjRWDTs0H1wxjdMqxp7y3Zu7qAzz+0x4UBcZ3D+f9a4ai1Rz7P9JdeVW4FIV+sYGopPi0+JNaf6DME6wCeGVpKjdPSMJHq/GcS5l0DT9nzmRVmR/vui7gJedl7sJ3qAg06hjXTbKrhBDiaI3tksD/Nq7FpThwKWrGJyR24FknxrL1qfz71YU4nC5iIgJ59/ErCAk69pIRh3IpCrf98iO/ZKQBcP/IMdw2dMQxX9fqcLCruJgQo5HEYMlME39en6dvJd9cDYDF6eC13ataBKwuTBpPqOLH3rICFn2fj+EsM8YoCwBJvkmE+8j4TPx5ScDqL2BNRikfrDpIgEHLA1N7EBVgYGjXYPK21eOjVXP7mSmdlm308dosSmqsAFjsLt5ckXFCAlaKovDsz/tQGjZCWJFawh/ppZzZ49iKET66YBfz1mYBcOHAGP5zyQC+2JhNjcXB9EGxxASd2IwxIY6X5oEpAJ1GjaYhALs9p5JP1mURaNRxx/ULUDbuIf23xkwAd7Dqh9vPID5EZu+EEKKjimo+oqp+GUZdd2KD7iUl1J8Zo8sptufiqwrl5n79Oq1vH363DofTnaWRX1zFTyt2MfvCYw8kHWpLYb4nWAXw33WruH7gYAzao9/Iw2y3c8XXX7KzqAi1SsWTEydxdlQiixdtx2jSc+60weh95CuQ+HPw0Xj/rBqaHa8s2cC2yj109Y3nnD7j+OO1n6ktUTB/lUhg30r6pETzwIU3oFFpWrmyOF25UOGio0XXT/1kC/lt/SemKMphM3pyys1cN3cjFrt70LGnoJoHz+nJgm35AFgdLh79YTdT+ka1e52OWJdZxnt/ZGLUa/jHub06tLzPqPf+BWrUHf0vVIvdyevL0smrrOfCgbF0i/DjnZWZANwwNhGtWoW1WXvtMQbpiqstnmAVwIJt+RRXW1mbWQbA3NUH+fWecYT46o/pPkKcDEMSgrlmVALz1mah16h5dkY/tBo1uRVmrnx3HXUNy4h35FZx2bB4oGnpSoivnoTQ4z/zLoQQf0YdGZ+V1S0gu+LfAFRZlqFgY21tT4rtuQDUKWV8l/ctNyTdcMz9+XjPVtbl7SYpKIrbB09o8QW4NQYf74CR0efoA0hWRw4F1W8CClH+N7M7S8PCTfuICvZnUJ9Yr7YatfqYs9UXp6exs6gIGjK4Xly9mgW/LSPXZkbthPWr0nj2lVnHdA8hTpbZ3YeyLD+drWV5RBj8eGjgJADWlG7hlbS5AKwo2UC9ox4fvfvfqcuuoWJrKGEhPTFoZDfQvxpZEiiOO5dLaTXD6UBpHVX1dvrGBHgtXauzOrj5k82sTi+lV3QA710ztM3gUGpRjSdYBbCvsIZKs82rTa3VcUz935NfzZqMUp77eR8OlzuF6Y+0Urb9++zDPvdvY5NYmVbK9pxK4oKNPHROz6Pux9+/3sEP292BuAXb8gn101Nc7Q5RLd1XxL8v6M2/vt+F3akwbUAMYw7J5NqcVcFD3+ygxuLglgnJXDO6K+nFNeSU1zMwPojgQwJPOo0atQoaXjKAJ1gFUFJrZU1GKef3jznq1yTEyfT4hX259+we+GjVGBqCxztyqjzBKoCNB8v56LrhLNiWxx9ppZj0Gh69oHcn9loIIU4MRXGhUnkP5l0uhb25RRh0OpKjQ70eK7MeYFHuv6m2F5DiP56zYv6Buo3MhjrbjkOOd1LvTPA6V++sP6b+ry5O4/ecdLrY3uLVfnuxOtUs3H0NM/o/fNjn3nvNRO574VvKq8wM69uFaRP7H1UfXIqFfUVXYHO6A3GltUu58+3LqbO639dzi3oys3c/vtizE41KxaNjz2wRUPti3XbeXr4BXx89j0+fzJCusWzKzsXqcDKiazxatfffkV7r/Xy1C1JDHDiN7i/uv5fkUV9vw2iUCUVx6vPX+fDV5NmUW80E6o2en/ddVfu92m0u28udF9/A1r25FJZWExcVxDUXHf+sSCFONglYdaKccjN/m7eJtOIaxnYL562rhngyjp76aQ/vrToAwKikUOZdNxy91v0L6u2VmfyR5s5u2J1fzXM/7+OVmYNavUff2EACDFqqLe6g1JCEYM7uHUXv6APsKXCvh759YspRv4bFuwu55dMtOJtHbYBKs521GaWMSvYOCrlcCnsKqjHqNSSH+xFo1LHgtjOoqrcTYNAe06zaxoPlnv93uhRPsIqGQvNDEoLZ9K+zqLc5iQpsOdtw08ebKa11P+exH3dTa3Xw38X7cSkQHWjg21tHewUGg3313H5mCv/7PR2Aq0cm8PG6LK9rVtfbj/r1CNEZAo1Ns+jzN2bzyPe7vB5XgOWpxXx03XAKqy0EGHT4ytIKIcRpJKt2Pb8VPIvNaWZw6OWMDL8eAJfTzusLXmPNvmL2FEZw45QR3HbeaM/zlhf+H1V299byaTXLiK8aQu+gc1u9R4BhNEU173uO/X1GMcl/EhvLN2J2mtGr9UyJmnLUr+HFPT/zceYaBviV8M+eewHw0bg4J/RjFOXvqA4JpFmcFvLq8wjRhxCsD6ZnUiQ/vnEzZosNv2MouG5zFHiCVQAKxQT6l1NndY8PN6bmsGT2jdw9fDQ+Wg1BBu8J2NTCUp788XdPSYc7P/mRSQNTmL91JwBnJHXh3Sumo2kWtJqSnMJdgyFG9zsVVn+qa6/m431NX+4toTo02lM/q0CIRiqVilCDO5NdURQWFbxCmXUxAwLUZNRFUOs0sDW1BlWimi//7zrKKusIC/JFq5WlgH9FTtQ4O7j7X0fbdSb5ltGJnl64l/1FNdBQU+mD1Qe47cwUXv09zROsoiFr54+0Eib1igSg6pAMqUpz20GRyAAD828axcfrsvA3aLl1fAq+Plq+uWU0Gw+WE+Krp29sYLv9LKu18sP2fPx8tEwfFOuV7fXp+uwWwapGTpf38e68Km78eBN5le4igD5aNS9fPpBz+kV7fUk+UiU1Vl77PQ11s2CXWgV+Pk2BujA/PdGBRnx9tK3ey+ZwUVbXFOBSFHhrRYYne6qgysLXm3K5Y1LTrmkWu5Nvt+Z5jpfsLfIKDgIMSQjxus+qtFJWpZfSJyaACwZI5pU4dZXX2fjnd7s8WZPNPbNoL5+uz+bK4V04p190p/RPCCFOlMX5T2N11QKwqexTuvqNItLQg5rCa7lt9EZuGw3z1g3g5V9hzuRhmBqWy1mdNV7XsTir27xHkHESyWFveWpYRfrPQaVS83Tfp8k2ZxNjjCHMp/2anmk1+WwqSyfJL5IRYT28Hpt/cAMAPirvwZhO7QJcQNMX2azSLF7OfplKZyUAwbpgHujxANHG6GMKVu1OLeCH33Yw7qwg9Ab3tVFCKK8O8LTpFe+uJRrp59fqNUpq6jzBKoBycz3zt+7EFWAHHxerCjPZmV/EwLimzyK1cz93dH8fcI+PaxR/Plnci8bLBPka0OuavgIpisJPS3aSV1jJuBHd6N1dPtfEqSu1Zi07KhdDw7/nLj7lLN/Zl6KsQG60fE+X4CDuGT2aKG3AYa8lTk8uRYVL6WANqw6260wSsDpJssvM7MyrondMAIlh7gh51SHZN1X1dhRF4dWGjJ3m9M1mgmYO78K3W/KosTrQaVRcO7pru/fuFR3AM9O9C3ca9RrGdT/8jhHVFjvT31hDdrl7u/pl+4t5Y9YQAPIr69lfWNPq80YmhTAyqSlYU1BVz6Vvr8XcbGmR1eHini+3MbFXRIuCz0fi6vfXs6+hH3qNmjNSQrl8WDwJob68ssRdyPOuyd3azQLRa9VMHxTLt1vcAaiEEBNZDa+50W97irwCVvmV9eRWNKXrF1RZeOmyAbyxPINai4PbJqbQI8rf8/iyfcVcN2+jZ+BVVmvl2jM6bwcgIdpjtjlaDVYBZJfXk11ez+r0UhbcNoaDZXU89/M+VCp49II+nNU78qT3VwghjsaOvEIKqmoYkRhPkNGAS3Fic3l//ludNWDfir9mo+fcNSO38/7q4WialXQYEHIJywpfAhRM2lC6B0xq994hpqmEmKZ6nQvSBxGkDzpsv/dU5XDbprewudyTZPf3vIjp8aMAqK2txV+tp8zlYHNNOGurIhkV6K7ppPa7HZWqaeKuurqaRTmLPMEqgAp7BZ9kf8IDPR44bD/aUlBcxd2Pf0m9xc6Gnedx+aW7GDYggZiA23n8SoWfNuwlIsiPu6eNafc6A7tEkxQeQmaJO4t+cs+uLK5JQwl3T94qwQ721RYykGZBJvs2T7AKwF+zg4cuuZX3f9uIn1HPY1ec5XWPNz9ayeffu/9uv/xhM28+dyU9kuVzTJyaGoPpjVQuKMoMxh4Ee6pL2FNdwoa8XNbccCMfPfE9v3+9noi4EP7+5nXEys+1+BOSgNVJsCW7glnvrqfe7kSvVTN3zjBGJ4cx54yubDxYjsOlEGjUcdnQOFQqFUadBpujaUZsbLcwr3pLvaID+PWecWzLqaR7pD8pEa3PSh0Pm7MqPMEqgEU7C7E6nPhoNdz9xTYKqy2ex/rE+PPMjP44nAoD44O8BnHbc6q8glWNLHYXNofrqANWVfV2T7AKwOZ0ccPYJM9Og29dPaTD13rxkgFM7BlBjcXBmT3CGfXs7zT/ut5Y++unHflsyaqkf1wgkQE+FDUsPdRp1CSH+7Hk3vGtXn/J3iKvWcKl+4o9Aav04hr2FtQwIC6ILqGy05rofHHBJqYNiPHUhYsNMmLUqUkvqfO0cSmwbF8Rry5Lx+50/3Df8fkW1v9j8jFlTQohxMnw0botPPPrCgBiAgP48m8zCfPzZUDwxWyr+AqAcEN3Yk0DwZnh9VyrQ8N90yfh0yxTp0/QeYQbulFtKyTW1B+j9vCBp6P1e9EOT7AKYHHhNqbHj8LpdJKdnc1tYSNZVPc9WnUNO5X7GR3SBVR+qHTdvK5TW1uLhpZjMLPD3OLckUjNLKLe4g4alZQE8/qbY1nx5X2o1SqmDoapg3sc9hoAvj56Pr35chbvSsPPR88ZiTHsWJxNnrNhtYEK0uqLsdudfP/lBsrLajnn3Cji/DSAe9y5ryyG84b3Yua4ga3eY9WGpoliu8PJxm0HPQGrLXtyqKypZ3i/hGPKNhPieOnuP5p1+m8os+UAUF82mLAwPwqUpkBWub2eRd+v59s3lwBQWVLDS3d+xH8XHn0QWvx5uI5gSaBLlgQKgM/WZ1Nvd39o2hwuPl6bxejkMPYW1BDu74O/QctzM/qTEuHOxnnx0gHc9cVWzDYnlw6J4z+XDmhxzZggIzFBh9+F71jFBhm9CotH+Pt4gksHyuq82u7OryGtqIZLhsS3uE6PKH/0WrVXIA7giuFd8Dcc/RfbAIOW5HBfMhq+RPv7aDscwLPYnRRWWYgKNGDQaVCrVV4F0q8elcBHzXYBHNAlmC835fD3r5sKpd4yIYl3VhzAqSjYnS5u/mQzqx6c6BWsa9TtkH4lh7uPl+8v5oaPNmF3Kpj0Gj6/YSQD4k/cIFeIjnpl5kBmDovHpcDo5FAOlNUx6b8rvNqEBfh4glU0BKGr6+0SsBJCnPLmrtvi+f/8qmoW703n8iEpRGt2Y/KrRavtQY/w59GqfUDdG8X3Jqh7BwUdqoAnmD56cItrRhi6E2HofsL7Hm0M9jqONLjHDXa7HZfLRWLAIm6OWACAirVY1YsxaFuOz4xGI4O1g0l1plKmlDW0V3F21OE3zmlPStcI9HotNps7qNYzJarVDYZaU22vp9pWT4wpCLVKTaDRwKXD3CsFFEVhWHgseYX7PO27BYTz0jM/svQXd12rn77Tce9/7sFq+4YSsy//2zicCT1+5z8zzmn1fl3jQ8nJr/AcJ8S5i+m/PX8Vc79f7z4XE8J7T14pQSvR6QwaP65J/D9yzLvw04YQ1TuF98M389Sq5Z42Wo0aV6n3pg3lRVWd0FvRGVyKGlcHd//raLvOJAGrkyDokC9uQSY9S/YU8X9LUgEoqILr5m6kT2wAt05I4azekex49GzsTsVThL2zdI/057mL+/PGsnT8DFqevqhpaeHUPlEtioz/e8Fuzu4TxYr9JQSb9Izp5s50Sgzz5d3ZQ5m7+gA6jZpx3cNJDvdjVHJoi3t2RGGVhW+25GLSa3jvmqG8sSwDs93JDWOTiAg4/Pat2WVmrnh3HXmV9cQEGvjshpF0bViq2eiJC/sSE2jg191FJEf48cj5vfnHtzu92mzLqcLZLG2qoMpCjcVOkKnlzjOzR3WlqNrKgm15GPUahiS4B5ufrMvyfOE325x8sTFHAlbilKBSqTzZigBJYb6c1SuS3/a6l5ackRLKZUPi+WZzHpuz3IP9MSlhxJ6EYLoQQhyrQKOB/KqmLO0go4G8qv9Sbv4JAKetmI9Sb+OAbQp3dj+fKP/7UPxuQ4UGg6pzg/IXxY3kYF0xa0v2keQXxd09pgGg1+sxGAzU677DqFIRplbjxEZW6f10D/sP2LeDtjsqnTvDKTg4mK7OrtxWcxsVmgocvg5ijDHEmeKOql9bCwtYmX2AlJBQ/vuvi/n25634+xn428wzOvT85YV7+fuWL7G6HAwPTeL14Vejb7ZroEql4snRF2LYaiS1uoRxUclcnjSIS9b87mljtdj5blMYi4uallumFZe1uFejB2+dgsoHthoyiY4LJKqXe0Jx/s9NAc2s/HLWbT/A5FFHv5u1EMeLj8ZEiv9wz/H0Hr34cPsW8mrcdfPuH3kGYyKS+fLlX6guc2denX3l6DavJ04vTlQ46dgEQUfbdSYJWJ0Ed0zsxq78KjYerGBAXCD3nd2dHxuW2TSqrLezOr2MzVkVLLt/AtGBRk7mxg5ltVZqrQ66hJha7NR32dB4Lhvaclbu8Wl9WJVewoHSprRxs83JtFdXcbDMfe7GcUn849xeAIzvHs74DtTNOpwqs50Zb6wmv8q9HHHZ/nA+um74YZ/X3OvL0smrdM885FdZeG1ZOi+2ksl284QUbp7QtItijyh/Fu4s8BwPTQjmQEmdZ2nkgPigVoNVAGq1Cr1W7en3HZ9vxaTXEHxI+2CTZKaIzlVYZcHkoyHgkOxHlUrF21cPYW1mGSqVewdTlUrFp38bwU87CtCo4bx+MR2eRRdCiM701LSzuOvLnyiqruXCAb2Z2qc7GaU5Xm1sjlxWFO8iz1zGvFF3o1IdflLseCq2lKFTawnWe2+Qo1Gpua/nRXBI/EStVpOYmEhdno4eWhWahjFdPXtRyqaBYnYP/4NeQ2WYCEBYWBhhYWEkcmx1NTcX5DHzuy9xuNzZ9A+OHsuT9087omu8sOdnrA1LHTeUZfJrwS4uiPNeymfU6nhq2Hle5xKTI9ix1T2JqlLBhJ5JLC3O9kwqjk1JaPOegQFGCkeWUFhRTiHl/G3de3w97k4C/Y3UW5tqYQX6y2SM6DwOp4vSilpCAk1emwYAhBhNLJo5m80FeUT6+dE7zL2ZwatL/sGm33cTGRfCkIl9OqnnQhwbCVh1wJqMUvIrLYzrFtZu9s6yfcW8viwdo17DP8/rRc+oAOptTvwNWr64cRSKovDK0jQufnMNISY9fj5aaq0Or2tY7C6yysxEB568D8VvNufy4Dc7cLgUJveK5O2rh7S6pO1QarWKly4dwPQ313qdbwxWAby7MpO4YCOzR7VfGP5wVqWVUlVvZ3yPcHbkVXqCPgArU0sw2xyY9B3/cXYp3sWkXW0Ulz6UWu3OmHMpCucPiOGuSd24fFg8H6/LwqjTcN2Y9gd7q9NLvY7XZJTxwNQeZJTUsjOvipFJodwyIbnDr0OI48nlUrjji60s3FGAXqPmv5cN8NrNsqjawsdrs9BqVMwZnegJbht0Gi4ZcnSz8UIIcTQUxQ7WJaC4wHAWKlXrk0UAr29az+LMdJKDQ3hs3JkE+Bios9noEx3Jkruup85u4fm933D56heYGh5Jf6MKUHAqKrZUdwHgQF0RiqK0mNQ7kd5M/5QlxatRoeKqhIu4KPasDjwLNBoNXfwuQmP7xnPOgIWmwpwOtmW+hD2gO8Pjjv53t81lY3vldnzUPvQL7MeSAxmeYBXALxlp3Dz4yCYUlUPHZ4qrzbaNLFY7hm7BuGor8VWpueXSMUydMJC4rmEs3Z9BYmgwlw/p1+bz7S4HWyuaVgzUOCzsrcrnsdvO4dHXFlFRXc+lUwYyrG/bQS8hTqSyyjpuf+pLDuaVExbsx6v/vISusU2rVDJqM9hcsZkwUxg9Qyd4zkfEhXDu7LGd1GvRWWRJ4F/MHZ9t4ccd7oyaUF89P905ptVgUm6FmZs+2eyp0XTtBxsZ2jWYn3YUEGzS8fbVQ6k023i5Yde6rDIzA+ICuWBADJ+sy/IEeSL8fegVdXK3IX3sx92e3cCW7C1i4Y58zu0XjVZz+B/ggV2CiQ0yerKVfLRqrM3qVCkNywTjQ0yc2SPiqPr3xI97+GD1AQB6RPrzf5cPQKOCxrI5UQEGjLojS0e7ZUIyS/YWUWG2o1bRobpXy/cX8+KvqZ7jtKIatBo1ccEmHj6nV4fu2zc2kE1ZFc2OA4jwN/DtrR1LlRfiRFqRWsLCht93NqeLf3630xOwqrM6uOStNeSUu/+t/7aniB9uH4Pd6aLG4iDcX+p6CCFODrvDTt7BK+ji11BTsn4kBH+IStVyLLBg/15eXLcKgB3FhdTbbeRlVZNaXErPyHDevWo6n+YuZWmR+1ofZMMdyQ8wNMjBc/v2sc/sri86PLT7SQ1WZdRms6R4NQAKCp9kfcf48AEE6cI71I+ggBtwlS5AhXtiVKUKA6Vp0iyjCp5Y/j3L51xPiPHIJ0ntLjvP73uezLpMAMaEjSExyDs4lRgU3Maz23ZPryn8Y+vX2BUnPY0RjAtOOexz3vt6DUs3uMdndUBOvbuu6fCucQzveviAnE6tJcUvkvRa93J3H7WWJP8I4iJD+P61G4/4NQhxvH3600YO5rl3yiytqOXtL1fz7D3u7MWDdQd5bt9zOBT3v/UiSxFXdLmCOkc9igJ+OskM/KtxHsFSv5Zbop16JGDVhs1Z5Ty9cC9bspu2+S2rszF/Yw7Xju7aYtlXdpnZq6B4YbWFnxq++FWY7Tz07Q5mjfCemSmttfG3sUlcNiye9/84gMXu5KqRCQSe7CVhhyQX3fnFNh74egfDE0MY3z2cjJI6uoaauH5MYosglkql4rMbRvDCL/uptzu5aVwSq9JLee33dK/LphbWHFXAyuVS+GjtQc/x/qIacsrr6REVwJ4C9zrtyb0jOzR4q7HYcSkQaNTRJcSEsyFI51Lgv7+lck6/aBIPqWPVXPPdEmkIOnZUdpmZB7/ZQWG1hRGJIfjoNEzoHs70Qa0PpLLLzKQW1dAvLpDIDtTkEuJ4cBySaehsdpxWXOsJVgHszq/m510FPPzNTmqsDsZ1D+e92UPRa0/9mRohxJ+XYv6S7NxPSAxoKrqNbR3V9esxGYagU3sHz9MqvGsXbcjNo67YvbvvvqIS3lixjrqYcq82mfXhzEy6lH/2L2Jh/kb8dSYu7zLmRL6sFpRmoyij2spA/xw+zZyJzRWO2Tmd+NwECg/WMHxgAmeOarnjnkqbhDr4TZS6j0EdCH63Yyl/Emxr2V0RxgvbR1Jrs5FXXX1UAauM2gxPsApgVekqXul7KVsTU1hXXEi8rx/3Dx7RoWs5HA7UajVqtZoxQUm8Enc+NU4r0Tp/ivMKCO7R/kRuXrF3Mem8Iyguvao4lVf2LsahKAwLScJHo2NW4mjiTCGttt+RX0i5uZ4RCXEYdVLCQZwcTqd3pqHD0RRm2F292xOsAtheuR01EbyfuRAFhdldp3J11ykntb9CHE8SsGpFQVU9s9/fQJ2tZczx5SVpvLwkjXB/Hz66bji9ogOottj572+pXu3C/PSU1to8x3VWB5N6RvDyklRqLA7PuZs+3sRzM/pzz1knfkeZtjxyQW8e/nan15dTq8PFH2ml/JHWNBuXV1nPExf2bfH8hFBfXp/VtFPOiKRQaiwO5q5xB5r0GjVnNCvcfCTUahVBJp3Xe1lQXe8JVgF8tj6Lf5/fu90vyu/9kckzi/biUuCuSd24bkwi1ZamX+5Ol8JbKzJYlVZKuL8PL146oEXW1fju4fgbtJ6/v+ZLpQ7nzi+2si3HHfw8UFrHJ9eP8BSkByiusfDDtnysdif+Bh1PL9qL1eEiwKBl/k2j6BV9crPuxF/ThB7hnJESyur0MtQqeOjcpszBuGAjvnqN5/dimJ8PLy9Jo6ZhWfPK1BK+35bXar07IYQ4HhTLryjV/yLxkI9Ep6JiXtZjlDsM1DrG83i/2/DVGqivrydZpUGjUuFUXESFVBJvsrG7WIfT6c7GqrPZODt6IGtK96FT2xkRcpAIfTari8sZHX4jt3c/v1Nea4pfAhPCR7K8ZB3JphIMGvfvWr26hL1VC/muPBHjkgB+XLKDp+5XMWFUy3Gkymc8Kp/xnmOfsPeY9tmn7C0tAaBLYCDJIa0HZg7HT+s9RjKoDdRW1TIrIZlZCe7SBvUVFRDa9uY6iqKQk5NDdXU1arWa+Ph4XC4XgRoDgRr3ZF2NxcKdS39kY2EegyNjeGH8VHx13pPGk0b2YMXGNBQF1CoVk0Z2bExdYavjvk1fYHG561QV1lexePID+OuaJgr3V+exoTQVH4uR9GwLc7dsBaBnRDifz74MX33bS1GFOF4uP2cIyzekUVxei7+vD3NmjPI8FmuM9Wob4RPpCVYBfHTwF86OGkak4ej+rYs/H1kS+BeQVlTbarCquZIaKw9+s4Mfbh/DOysyPTtkNSqttaFWubN3VCp34fWuYb78cPsYXvx1Hwt3FlJZb+fX3UX4aHfzvysGtbhHaa2VWz/Zwo68SkYlhfLalYPx9Tn+f2WXDY1nQo9w3l2Zybt/HGiz3aH1l9rzwJQe7M6v4kBpHSOSQugR5d9u+z351VSYbQxJCMZwyPK+/10xiHvnb6eq3s4N45LoF+u9g55LgW+35jJzWJdWr11Wa+XpRXtpLIvwytI0Lh4cx+RekSxp2O0sJsjA/I3uQqt5lfWc978/+OrmUfSPa7pXQqgvC247g193FxETZGDaEQSsciu8s7GaZ2tVme1Mf32NZ1llc9UWB5+sy+Lp6W3XXhDieNFp1Hx03Qj2FVZTU+8go7SWNRmljE4OI8zPh/evHcbLS1LRadQ8OLUnt322xev5zbNMhRDieFPsO7yO7U41ZqeGlbYQ6hQtPhoH5baNzDvwO7d2O5f8/Hy6+frzzMBhrFUW4vJ11ynyD/Zl7R89MWmNzB4xmL5RkYTo/dlU+go2VwUWJ2wtn0+QPo4+Qee16Ed6bTpvZ7xNraOWSZGTuCTukhPyeu/oNpuL46aypvg5Cuu3ec5rVC6UYBeK3oXKpmbzruxWA1aH0qjVfDZjNKWFD2FUV+EbOBtTO1lCTpeLjQV5+Gi0DIqK9noszhTH5fGXsyBvAXq1nusSr0Nr8x6jWiwWLBYLBkPrmeLV1dVUV7snIF0uF/n5+SQnJ6PT6bDb3UGkBaW5/JDhzqZbmLmftO0FfPm3qwkKNHmuM3lUD4L8jezJKKB/j1gG9uxYXa4ya60nWAVgdtqosNV5Ala7KrO4bdPbOBT3d4Ka7ADAfd99xSWszDjIOb06b8JZ/HXERATy2YtzyM4vxz84E0W7nDrbcHz1SQwMGsisLrNYX76ecJ9wzoo4l58L/uv1fLvL0ea1xenHqahxdjAQ1dF2nUkCVq3oGe1PoFFHVb37QyzAqGV8t3BPLatGZQ1ZPzUWe6vXcSkwbUA0t0/sRvdId8AmMcyXLqHey86yyltfWvb8z/vYcNCdpr5sfwlvLs/g/ikt076Phwh/AzePT+a3PUVeRdObK6yycOlbaxiSEMy0AbH0jmk76+e1ZelsPOgO4i3cUUjv6ExuO7P1OgRvrcjguZ/dg5H+cYHMv3EURn1T0Gp0chjr/jHJ6zl9YgLYnd+UZfXVprYDVnanwiE1PLE6nLx51WA+WZdFYZWFUF89z/y8r9njLm7+eDNrHva+b1K4H7dMOHy9q0a1VgfrMsoYkRjCwp2FgHtJ4thm2VVbsitaDVY1Kqu1kV1mpkuoqc02QhwvGrUKH62amR9t8mRPPT6tD9eM7srIpFC+uLFpVu++s3tw7/xtOFwKPaP8mTaw40FcIYQ4Uir9MJS6dz3HqwrGk+7TlXLNH01tUKiyuWsYuRoKgHcL8GW1o6motl9AHU9cMpCxsSOJ9Hd/pg8OSSaj2kFR054uVNm8d3Ru9FbGW5TZ3EsNFxYspHdAb3oH9D7eLxeAGGMEo8Kv4cecfTgUCxanlmK7P/oaF5xdTY/IUs5LWY655DN2Wy8nLngU0b5tj8/86x/E39QQ+LM+iWLrg0rfctLUpSjcuHABv2e5l/3N7jeQx8d7j4mmRk1latRUz7HT6aSkpMSrcHpVVVWbASuXy3uSQ1EUtFotycnJ5JTtxaW2UV3s3Sa3qoo3313Gw/d7BxKH9u3C0L6tjwNbk19XRWpFGUl+EWTWFgPQNyiOGGPTROXy4p2eYBWAIbQeS6l7LObrX0+F6iBmRxwmrYzPxInna9QTGLGO3aX/ABTUKgNDoz8m0KcvkyMnMzlysqftBTFn8GO+uwbelKjhxJmOro6wEKeCUz+kdhJUmm3Mfn89Ax5fzJwPNxBo1PHFjSOZOSye685IZNl9E3j+4v6E+nmn/TYGHWaNTCDQ6J6hOnRzvcFdgj3BqkZT+kShb1YL6vx+3rNWjcrrbF7HZYccH2+hfj4svHMsU/tGtfp4nc3JxoMVvLUik/P+94dXbalDZRTXtnvc3KtL0zz/vyO3imX7iw/b14sHe8+eRbRT8Dkq0MA1o5rqh80YHEu3SH82HiznP7/u5+2VmXyw+iB+h2SvFdVYO7x7YGtqLHamv76av320iYU7CzmvXzQPndOTBbedQXxI0+AmNrjt2hEq4JfdhZz98grWZZa12U6I4+mnHQWeYBXgyT481Dl9o7hgQAyxQQa6R/qjUanILjNTXG1ptb0QQhyJYksqn2Vex3tp01lb8gEqnwmogl4F4wxUfg8wccjrTIi+HKvV/Tlqc2k4WBvDlIiBAISFucdpGrT40BQ0UaFidEIPT7CqUYp/0+5aapWOJP/W61bVOGq8j+01rbY7XmJNA5iVNJdSRz/2maMINFjpnlCKX5daXuz/B90DUjE4V5HgeoBpP73J9tKCti/myGx2oICj9cz6HcWFnmAVwEc7t1FpaXtyjYbdCf38vN9TrbbtufHAwECMzepnRUS4v1Rvq/qShRV38XPZAwyKW4K6MQCmKPjlKJSUHtv7vbO8gHN+fpc71nzP/hIzl8aP4ME+5/HuyGvRqpsmTKMMQfT2z2dcWCq9/fMJ09bSrXsOKT1zGTgijd9qPuexPY9Rba9u935CHC95td94ig+7FAuFtQtbbXd5xFQSDgzBuK07QdnJ2J1OMkvLqbFYT3KPRWdQUOHq4B+lg8XZO9NfIsPK5VJ46NsdfL8tn7hgI2/OGuK1RO2phXtY2VCradn+Ev42bxMfXz+C5y7u72nzzsoMT0ZVo68353LN6K70ig7gt3vGsTOvCn+Dlud+3kdacS1n9YrkqpEtt8AdGB/EN7eMZmVaCSkRfkzp03qAaNbILqxILcHhUjDqNFw29MRvG+/royWt6PADAQV4fVk6s0d1bfXxs3pHsnhPkddxW4x6rdcSTJP+8Dv+XT0qgV35Vfy+r5juEf48Nq1Pu+0fv7Avlw/rgktR6BsbCMArS9IwN9y3sNrCFcPi+Xl3IZVmd8bc9EGxqA+JQNbbnCzeU4iPVsPZvSNbPN7c7/uKSWsWqFuRWkzf2EDmrjnIhQNjSAr3o7TWSpXZhqpl7Xtods5idzFvzUFGJrVdC0KI4yXqkEL/UYFNxz9sz2f+xmwi/A3EBBn4bmseAHmV+ezOryajpBaVCv55bi/+NjbppPddCPHn4XA4yMrKwmKx4OvrS3x8PBpN0xhgYe4j1Dnc9ZY2l32CURPGwJBpqAxNBYRfWrSdtRmjCAivwaLSMD2+H77lLlyhLoKDgzEajdjtdq513s1Xee9jdVmYGjWDGGPLenuDQi8jQB9NhTWbLn7DiDC0vtxrcsRkFhUuAiDSJ5J+gSd+2b5T0ZNVXw243x+Nxk6coZZAbVOWf5jegq+mkrn7NvF/Yy5o/UI+k8CywP3/Kn/QD2+12aF1onRqNXrN4b82REdH43Q6sVqt+Pv7E9JOjSy1Wk1iYiIWiwWtVoter8epOFhf8oGnTa1rJ08NGctLHx1AW6pgrIAps1rWU62xF5Nr3kqQLpZoU8vHm/ssfQu1DveY3up0klFRi7rWn1fy1/G3gUNxqlzYXA66mnIYEOT+jIs1VhFhrKHM4f7+YHOpUVBTYi1hU8UmJkZMPOx7I8Sx8tF4Z0oZtO7vV06Xi1fWrWVzfj4Do6NJ3VrIxlT3787/HVjNZ3t3klddjb+PD2/NvJChXWJbvb44PciSwD+hBdvz+HJTLgCZJXU89O0Ovrv1DM/je/K9AzRrMlpmshRVt4xIO1wKu/Kq6BUdQESAgUkNX/K+bXZtu7P1mi794gLpFxfYbr8n9ozkpzvHsK+ghoHxQXRtZwe74yk53I+MkjrPcVvBFH9D23UPLh0aT5BJz7acCoZ1DWFCOzsEvnhpf+74bCs1Vgczh8Uzvnv4Yfuo06h56bKBHXg1TbqEmjhQUkeV2U6gSdeiSHt0kJGl947n512FBBp1nHdI5pvN4eKKd9d5iqef1y/aq9j8oQKM3u+P0wXP/+Jedvjpuix0WjVmm5PoQEOr72+L67XzfgtxrHLKzTz+4x4qzDauGtmFWSO68MuuQhLDfHnyIvfgf2t2BXd9sdWzxPbQzMaMEneAVlHgmUV7uWpkAjani7SiWhJCTYT5tZ0JKYT46yksLKS+3p21U1tbS2lpKZGRTRNcZof3eGxH5S8MDJnmda64ug6HU0N5oXsplz1Ug91ux+FwoNfrMRgMGAwGejOAR4P+53meS7GjVrX8XE32Hwvtl93k0vhL6RPYhxp7Df0C+52UJWF+Wj/8tf6e7C4VGrIs/uRafYnzcY/ZMuoCyav3Y5yu7d+1qsBnQTcAxVWGyngeKm3rk6HdQkK5Z/hoXt6wBp1aw9NnTm633lUjvV5PUlLHJyvUajW1uCiurqBbcCg6tQq1SotTaZokPrN3T0beM55tO7NJToxgQD/vYGOlLY+vDt6G1eXOdBofeRf9gi9s854Beu9Jmc35+Swvdwemvj64gypNDQpwU59smm/cbdTYoSH5WK1ScDZ8Fpo0siRQnDgbdmbx4bfr0Os03HzFDYQYyqmxpRJmGkt8wCwA3t28idc2rAdgbW4O4Zamn3GnAfIaasXVWK389/dVfH7t5ZRYKimxVpLkF4NBI5sHiFPXaRuwsjqcLNtXzI7cKjYc8B7wVDRbWudwuugd7e+165xvKxk+Fw6M4dP1WVjsTQEovVbNwPigFm0br3vX/G0s2llAVICBd2cPpU9MAFtzKtFr1J4sn8PpGRVAz6iTu0Pccxf3R6/dRXa5mfP6RdM/LogNB8rIr6xnU1YFmSV1hPjqeW5G+zOKZ/WObDezqtGEHhFse/RsbA6XV+2q48Vsc7C/sIZbP91CQZWFIJOOT64fwcPn9GJf4QZKaqz0jwvkmtFdCTTquGpkAoqi8PbKTFanl9InJpB7z+rOzrwqT7AKYOHOAp6qsxHs2/ov+TN7RDB7VAKfrs8m2KTD5nDRUBYNu0vB3pDdVVBladjBqO2wVXSggfvOlsKe4sS55dPN7Mpz/x7cml3BD7ePaVHsf19hjVc9uDqbw7O5RGtyK8zMem89RdVW/H20zL1uOEMSgk/o6xBCnNoUZzEu2zrSatPJqLcQSB+CcO8q53A0LUWusVvx0XTB4nSXH3Ap4KtrmZF+ydC+PP3TMgBMOi2jukSi1+vRtRFcsTkKSC2ZQ719H34+w+gW/h6gpca6B4M2BqOuY5kHJ6pmVVu0ai33dr+X+TnzsbvsXBhzIXlmOxus49CrN/NHXjbP7+9Kz5BY7ux/RpvXUam04HtVhxaB3Dl8FDcNHoZapUKnOf7js3KrmT9yDvLAil+wOZ30Do1g/gUzmRB1D8sK/osLB32CzndnTCVCUmI4TlcNB8v/idWRTahpGmF+l5JevcwTrALYVfljuwGrW3uPZltpHptLc0n2DyP1YLVnerZCXeN5b9YWqpjULDZW52wKBCqKu9XAoIEMD2k9S02IY1VaUcuD//0eS0OZhvTsEha89h5arfe/xz0lJV7HgaFGLPnuZAutVo2Dpu+viqKwumQnT++Zh11x0sUUyf8NuoMA3clJjBAnnktR4VI6ttSvo+0602kZsLI7XVz9/gY2HChv9XGXovDwtzv5+5QeXPbOWtKKmpZt6TUqXAoMe3oJT17Y11PPqX9cED/dMZY/0krYnlOFRq3isqFxdItsfRru2615LGwo0l5QZeGf3+0kJsjIz7vchbfnnNGVRy9ofxlbW1wuhZJaK4FGXYsd9Y6HEF89r13pnTk0KrlpKZrV4cRHe3zvq1GrjilY9en6LL7ZnEt0kJHHLuhDeEPmx6KdBdwzfxvWZruXVZrtvPDrPu6e3J0l94zH6nAS5ufjtbzvsw3ZnkLwf6SVolLB5UPjvb6cm/Saw/b5iQv78ugFfdCoVVz9/nr+SGt9p8XLh8XjUhQiAwz46NS8szLTszRRpXLvlBgR0HrRUiGOh+a/B12KO1vq0MD6sK4hGHRqT+B+Ys9Irh6ZwIYDZfSNCWTB9ny+25qHSgUPndOTT9dne7JTa6wOXl+WzgfXDjvJr0wIcapQHLko5ZeicpXRTYF8TRDbNcvo67iTn6uLqKizMs7el9Eh/Zi+6EOsmgQuSSkn0MeMoz6ED97x4Xv9Rzx11/kkxLiXms0aOZBuEaGkF5XQPciXmEB/wsPDUalaH4TnVr5Avd39+V5r3Uhe5cvk1K2h3pGNCh39Il4k0vfso3p9doeTimozoUG+aNTHf5lFV9+uPNjzQc9xvyCAwcB0Lo2AC/o7MHRg2d6R8GmnBtXh2JxO/rN4JTvyChmaEMs9k8agbXhfnt66hA/2byBAX8/47lloVApbcxL4aN9Kzk/uyfXdvsel2DBqvSeGD5Q/RIXZXben2vIHOk0kRq33RIhJ0/7ESKDeyPzJs3G6XNTZ7Yz/6D0qrRZQ4RXI21EWz829x6FV5xDm05Md1cWsKVuN3eXChRo/jR83Jt2IWnXqL6kRf075JVWeYBVAeZWZqloLoUHewaVxCV35KXW/5/i6kUMIGKQnv7yaId1i+fevS0ktKcPPR899E8fw7sHPsDdsKJBtLmJx4UYuiZ+AOD04UePsYKnyjrbrTKdlwGp3fnWrwarYIAN5lRayy+vJ3pDNjtxKry9p6oYd5WxOB7VWB3d9sZUtj5yFb0Mx7pQIP4prLKQW1RIbZGBgl9azqwCq6713DiyttbE9t8pz/OHqg9wxsRshzbJzVqWV8vmGbEL99Nx7VneCTC0zd8w2B7Pf38CmrAoCjTo+uHYoQxLarg/QnKIobQ7gtmZXUG9zMiwxBJ2m/R/c4x2sOlar00v553e73AfZlVTX2/n4+hEA/OO7nV7BqkZ/pJayMrWUlAg/vr55VItaVM13IATYlVfFg1N78uRFfXnx1/34aDU8M6NvhwKGmoZrv3z5QJ5ZtI+iagsD4wOZuyaLWquDXlH+3D25m1dAatbwBJ7/dR8FlfVMHxzHsK4d+zsW4mhN6hXBooadLAMMWoa28jOXEuHH/BtH8d3WPCICfLh+TCI+Wg3DE91tJ/SM4M5J3TDo1EQHGnn2571ez9cf5neLEOI0Z1kILnfWu0oF/Xxq2WPzYy2r+cPsng3aVZ3NZzXbqMEKTh2f7R9OX7Waip/AbtdSTgnPvbuYNx+d6bns8KR4hkWtQbHvQKUfgUo3rc0uOFzen+/Vth3UO7IBULCTWfF6i4BVWVkZdXV1GI1GwsLCWh1LZeaUctez31BaUUtKl3Be/eclBAUcfqlYe2Mzm8PB5ux8/A0+9I05fMb68Q5WHas3Vqzj4w3bANieV0iQ0cgNY4axt6KID/ZvQIXCOUm78Ne7JzZigyrYaslm0x4NI0JGcFPSTS2uabbt9j6276ZX4I0U1u8ho2YlgboYJkTd3aH+adRqAnx8+OjCS3h5/RpQQZdIPz7O2IgCTE/ox6So89A2fHYNCIEJEVP4If8HXIqLC2MvxKhpe+McIY5Vcnw40eEBFJS4f2/1To4iJLDl75VL+vTBR6thU34eg6NjuLBnL6/Hv7lhFtnllUT4+xJgMPBhiff3F5361PrdIY6NZFj9CQSbdKhUcOgKqwh/d8CqUX6l924nh4Y1rA4XtVaHJ2D19ooMnm3IugE4WGbmxUsHtNqHCwfG8uHqg+RV1qNWwcxhcfz3tzSvNs//vJdnZvRHo1aRVlTDdXM3YmuoeZVRUsunfxvZ4rqfb8hhU1YFAFX1dp78aS/f39Z26jfA7/uKuO/L7dTZnNw2IYW7Jnfzevypn/bw3ir3LjGjk0P56Lrhng/njlIUhd/2FFFvdzK5V6TnPTsZUg8pEt/82N5KsIpmNbnSi2v5alMuN4zzrrdwRnIYn63PbjpOadgRckQCs0a0LKTfEaF+Pvz3sqaflxvGJvPt1hye/3k/w59Z6pV1F2jS8cwhy7EcThfz1mZRUFnPBQNiGNDGclQhjsb/XT6QwV2yKK+zMWNwLLFBrQ/CB8QHtfuzl9is1t6NY5NYsb+EfYU1RAcauH9KjxPSdyHEn4TaO/PF0lDstcCqA5rKNdTYaxv28lO4o/tSRodlYhusZd7nU9i5J4nyarPXdaoK/4c/rwGg1H8FuFAZL2q1C1EB11FtXYWiWNGo/PH1GQX1ezyPZ9SVU5q3gQti3cu8ysvLKShwZ8xXV1ejKIpnN7vm3vziD0or3JOg6dklfL5oM7fMHNvu2/Hmj2uY9+smTAY9T147hTP6JnoeszoczJ73Ndtz3fe+bfxI7pgwqt3rtUZx1YD1d1AFoDKcecTPPxZpxWUoKO5vG05IK3EHK+0ud2aHj8bhCVYBaNUudConTkXD+vL1nBN1Dgm+3mOuAMMZlNQ27lKtwd9nJGqVhknRDzAp+oGj6me/iEjev2C65/jGPiN469e1LPhiD2d8/TqPzzqbqYPdn1/xpnhuS7nN6/llNWY+X7EVBbhy3EBCA2RplTg+fI163n7sCr5dsh0fnYZLpgxqM8B9QY+eXNCjZ6uP6TUaUsKbVsvcmjKdf+96nxqHmf6ByUyNkmWt4tR1WgasEkJ9uXtyN17/PQMFha6hvoxOCaXO6mRbTqUnWHFmj3C+3Zrf5nVGJYXw/C/78NFqmDO6Ky/8ut/r8VVtLO8CCPf3YdGdY9mUVU5ssJGeUQHYnAqv/p7uaTN/Uy794oK4amQCO/OqPMEqgC1Zla1e13FIEfe2iro3crkU7vp8m2eL+v9bksrEnhGegu/1NqcnWEVDwflNWRWe3eh+3V3I2owyBsQHMn1Q27sU3vfVdr7d4i5Y2ScmgG9uGX1Cliu2pk+Md42vGktT6uyD5/Tk0R92twheNuejaxmcO69/NDCY1Rml9I0J5MoRXY5vp4EAo5b/Lk7D0hBU+3D1Qc7tF+2VTbW3oBqdRkVKhD///G4X8zflAPDxuix+vGMM3dtYkir+PCx2J1X1diL8fdochBytgqp6tmRVkhzhe9haeD5azXHf1S/Uz/17sKTWSoiv/rDZm0KI05xxBvX1v+FjX0Wty8R+1xBGhI1BrdpPpa2YjLpwVKgZre3Jt+WpDOxykNFhmQDo9Q4un7GMnXuS6DYqhjt//YmuQcFc06MPWts6aJaUrtjWtRmwCjCcQd/o37DYUjHp+6JRB1Nu2U2FZR11Tj0/FPWiIPtb+gd1JcE3ArPZOzjWWCT+UC3GZw5nq+0a7TpQyLsL3UWSbbX1/OODn1n+31s8nwNrM7M9wSqAd/7YwG3jR6JWqXAqTpYWLaXUVsqw4GF08+/W6j0UVy1K2WXgzHAfG69EHfhYu/06noZ1ieLXuj0ovi5wgX/Dx1C/kGjOje/Jopy9lNX7Emp0F413uNTYXE1fTXTqlnXIugQ/ho+2C1ZHNiGmc/HzGXTc+11WYub7Ze4gpsXu4NFPFzN5QDfPZK7DZaXMegBfbRg+qmCu/99XHChyr+z4bVsaXz94FXrdafkV6y+lps6Cy6UQ6H/8s+j25RaTXVLJoKQYwgP92m0bHuLHTZe1n5xwpPoGJfHFqMeocZgJ0Qcc9/Gn6Fwu1Lg6uNSvo+0602n527S01srHa7M9AaDkCF82HazwLPMKNOp4YEp3Zo1I4NfdRdTZWg4q7p6Uwtw1WazNdH8ArU4vwXlIZeHk8PZnUAJNOib1akrhvu/sHizfX8LOvKalgY1ZXv3jgtBr1dgaghdDu7a+/v6yofF8uSmHjJI6fLTqwxbitrtc1NocXufmrTnA+gPlxAQZeWZ6X3y0aq9lc34N2VELdxRw22dbPOer6x1cM7pri3uYbQ5PsIqG5XRbsioY3ZCVdKLlVHgPHs02JwdKa0kM82P2qK5M6B5BWZ2V9QfKyS43kxTmy6u/p1NVb2dEYgiXDY1HURS+3JRDVpmZs3pHMqhLMOf1j24IXLmV1lox6TSkFtfiq9e0Wb+so1yKO1jRXF2zder3zt/Gt1vd7+tN45NYtr/Y85jV4WJtRlm7AatVaaVsOFDGwC5BTOx5+KUE4uTbcKCcv83bSLXFgVGnJsCo4/YzU7hqZIJn8LBsXzErUkvoGeXPzOHtB06Lqi38kVZKfLCRUD89M95YQ7XFgUat4rUrBnHOITtfngxqtYpIqb8mhAByzTv4oeQACu7fRcPDxrC1/CtcSh3DQmBoiB+jI+6ih080wZ9qcZZWeD3fz1fFLbeP59GtK8C9gpn8igoe6J6Ev36Tp51K236NUIO2CwZt0+/TPhFvc8HyB7G6tA2Dd4USSzUJvhGYTCYqK5smEU2m1pf5zZkxkp2p+dTV24gM9eeyqW3vIgxQZXZn/CuAooZaq4Wnd85nd3UOfYK6MMHknfFg1OtQN3wufJr1KctK3IXmlxUv45Hej9DF1Mrng22DJ1gFQP18lIBHUKlOzoSi02h1B6tw191YUpPGI0xFpVLxv9HTublyNCj1FNl/x6HYsbpCOZD3M6BwbtS5xBhjqHfWs7RoKQ7FwYTwCQTpg4gOaFoq6HS5KLea0ak1pJeXE+cfQJTfsY3PzFbvsh5WhwOny4VWo8birOHbrLsotx1Eo9IxyHSvJ1gFkFVcQW5ZFUlRoa1c2V1H95sDO8ivq2JqfE96BLW9i7boPJ//vJlXP11BypADDJ+UQ7BfMBOj7iPK2AeVSoVLUfh843YOllUwqWcKIxPj273evqoC9lcXMCC4Czv3FPPvTxfjUhSCfY18fO9M4sNP/qoJvUZHqKZjm4CJPxenosLZwaV+HW3XmU7LgNWmgxWU1jalGP+6q4jmoaaqejuDu4TgUmi1vtH5/aMZlRzGy0ubsqGyy+sZkRjC+obaWBH+PvzvyiOf1blsaJwnYGXUaTinbzRvLs9gZ14lV49MoLzORpifnjsmtT5bFuyrZ+GdY9nfsMTmcIW4fbQarhqRwMfrsqBhD5SvG4JLORX13P7ZVl68dAAPfL0dq8PFrROSPYWWV6QWe11rRWpJqwErH60Gf4PWk9mkUrkzK46FzeEiu7yOyAAD/gb3DJuiKDzx0x6+35pHfIiJV2YOIjHMl9jAljMf2mbFTruEmugSamJQl6Yg4NWjEqiqtxPu585qee7nfby1wj2oe3N5BjOHx/P0Rf1Qq1XYnS5u+ngzv+8rRqNWeQKX90zu3mJ55ZHQqFXcemYK/1vqXio6rGswo5PdQb69BdWeYBXA2ysyGZEYQnFN0891e8GqX3YVcsunmz2ZZS9eOoBLhrSdISc6xxM/7aa64d9Nvd1Fvd3KIwt28+TCPfhoNMwa2YW3V2Z6/h7L6mzcdmZKq9fKrTBz4WurKWvYBXVUUqjn2k6XwodrDnoCVvU2JzUWO+FtZHU5XQp/pJWgUqkYmxLWosabEEIcjcyaVSjNCjCkVy/B5appqCIKBnUOQ0JSqK2t5bzRySjEY3PsxKXdC6hJDH2IdcU2r2vuKCuhwnYFoGDUpoN+OP6mq46oX0aNnhFhg1le7K6H2cUUToJvCJ9kfUKNo4YhwUOIdkVjNBoJDW09ENG/eyxfvXw9+cVVdI0NxdfY/jbxQ7rFkdwljF31pShaCEqo5+eirQBk15cSnODH1cMH8smGbRj1Op67aErTa67a4fl/h+Jgb/Xe1gNW6kP6qg4+5mCVw1WN3VmMj7YLapX7NVaY67n/25/ZlV/EyMR4nr9oKgadFvUhNU+dzUbjKpWKPsHujY36cL3n/OTI83EqTvy0fiiKwov7XySzzp1l9/3BxVwSdBvn93EHJPPqqrh62Wdk1VagcWmwV2owqHW8fe6FjOvScrzaUYOSYxjWLZ6Nae6s9jmThuHTkDG1r+oXym3uJYlOxU66bT6BpmGeAGSAyYeIdjJmntzyGx+luYOr7+1fz/dnzyE54ORM8IqOqa6z8OqnKwiIqGLY1N2gggpbNfMPPMRryycSHxDIiOBYvt/srtP52cbtfHTtpQzp0voOo8sK93Lf5i9wKi4Mah1RGTG4GgZ2FXX1LNy0j5vPcZeBqbSZUQGB+tYD49W1FrbuzSEixJ9eyS13TRXidHRaBqy6hJja3WrdV69Bq1axJ7+a68ck8vZK9wdh90g/npnejyEJwZTX2Qg06qhqKJ6eFObLvDnD+XVPIYoC5/SLOqri41eP6kpimB/pxTWM6RbGop2FvPRbqufxFy7pz2VD24/SG3SaFjVkimssPPHjHoqrrVw+LJ6LmwUnhnYN9gSsDn1LMkvruGBADOf2i8bhcnm9pkOXEPWMaj1AolGreGPWYB76Zid1Ngd3TepGjzbadkR5nY2Z76wltaiWAIOWD+cMY0hCCD/uKODD1e5BQoW5ige/3sGXN49iZHIoE3uG8/s+95au0wfFEB/SfqHToioruZVmDDoNAQYdS/YWeR5TGmqFdY/0Z84Zify0I5/f97mDd82z7F5ZmsrNE5KOugj99pxK9uRXMTo5lIsGxXDRwDj0WjX7C2tYm+G93FStgmdn9OOVpWkUVFm4ZHCc186Nh1rc8HPa6NfdhRKwOgXZ7K0v6bU5FGwOB+80C1YBrNhf0mbA6uedhZ5gFcC+Qu/CwsEmd+D32UV7+WD1AexOhTN7hPPO7KFeS/UUReGWTzazeI/738SUPpG8ddUQT2Br48Fy3l6RgUGn4YEpPUgIlVodQoiOCdI3faFL0tVzlnEjGpOTXVZfVtYHE+wTT2Z1GXanE5PJhNkMevOz+AeXEBXRDYOuK4OiDnpdc2hMHMnJ3amtvR+VVou//9GNPx7vdyVLi7ZjdtiYFNWfNzNeZV+Nu27pFtUWnujzBGHG9gMLwQEmgg8ptL41J59Xl69FpVJxz8QzPMXTDXotKb0j2Lnd/Xnv0NloPprIri3h+XOu5f6zxqLTaDzZVTTUUSqzlXmO44ytf76r9APA7z6UuvdA7Y8q8PmjeGea1Fg3kVY8B6dSg1HXnZ4R89Fqgnlp6SpWZ7jHmb/uSSMlPJQ7Jozisp5D+Tp7F/tqStGq1Dw0aNJh75FeVo3FYWdwlIlaZ40nWOV+PfU8ufR7kkPD6RUVwf92/UFWrTsLz6l2ojIqWOpUvLpx3TEFrBYc3IOlp4Nh3eK5sftwhie5g4GbyzPIrvUen+nUOt64ZTqvL1yDAtx67ij8jG1P2i7ObSovYnbY+aPwgASsTjFOpwtF7cTkV0/zOT2N2gw4OFhVSXFVXVN7RWFNZnabAatvsjfhVNzjPYvLTn1YLTQraxzoa8DssHH3hvmsL09FBdzRczLXp4z3uk5FtZm/PfIZ+cXuxId7rjnTK5Pzx7zVrCndRZwpnOuSzsOoObbkAfHnJUXX/wTsThe9YwJIL6rF4nB5BWmiAw1cObwL57+6CpvThUmv4ZYJSQzvGsqo5FBP3aVQPx8+u2EE767MxEer4a7J3TDoNVw4sPVfRkdiTLcwxnRzfzgt3bfd67HNBysOG7A6VHpxDffM3+7J3NqYVU7XMJNn98DWssga9Yp2B6U0ahUaddNQyeVSCDHpCfPTU2NxMCg+iLsndyezpJZXf09HURRuOzPFsyxubLdwVj808Yj63ZaP12aR2rB7Y7XFwX9+3c8XN46iuNri1a6opun4g2uHk1pUgwoOu1Tvl12F3PH5FuxOhdggI9/dOpqUcD/Si2u92u0tcH/ht7YRVNCqVeSUm0mJOPLBcaXZxtXvr/dkwGzJrmBctwg2Z1Vw5xdbcboUz1JNtQr+cW4vksL9eGVm+1l9OeVmVqSWeA1sAZIOs3xVnHzfbM4ls7Su3TaHBt17Rrf9sxbm7z2bnxTuR7BJx/L9JXSL9OeR83vz4q/7PQF6gGX7S1i0s4ALB8aiKAoltVbK62yeYBXAr7uLyCqtoevGJ3GkLqG8IpwN1uupxo8duVWseGCC1D4QQnSITm3CXxeFxV7DRGMhGpV7WXxfnzpqNcP4o3QiT215hYSQMqKMAdydOJsupkR8fQd6rjGuS1denXIev2Sk0TUomDuGjkSn1RIc3HophY7SqjVMiW768pda0/SN0qE4OGg+SLSx48uqnYqTPeVp3P7tIsoq3b8j9xQUs/Su6zHpdQ1tmsYX1jIDPuEWdyo8MD6sNwA+Wu+huuKq5YyKUPIOGCnVa5kYP54+gX1YeiCDb/btIdLXl3tGnEGAj/vLqsrvJlR+LXfbOxp5lS/gVNwb29TbUymu/ZiYwDsprvH+LCuucY+nfHV6vpt6Pfurigk3+BFlan+89NSq5by/bTMAZyYk8ta5FxCgDaDa4R6POR0qzGYd6cVl9IqKwOr0LnnR+N45XS5Ka+sI8zvysc+q/IPcv3qh5zinopKfu17P/6Uu4NuctWhUTs6NCsNPW4qP2o8xkbcSa4rizVtntHvdrTn57CssIcoQQGF90+ZASf5tTz6KzvFD+Vf0vGMPig1qqoz4B7pLj+wtjMWpuL8rabVqnDSV9egR2XbQMcTHO+PuzB7d2HiwjKyiCs7sn8yM0X2Z+fs8Mhsy9xTg1X1LmBY3mHCDPw6Xk0p7HSvWZ3iCVQCf/bSJ6ZP6kZeXx4aqfbxb8SsAmyr2YXHauK/nTMRfk6KocSkdq02ldLBdZzrtAlZltVauen+9V+Ht5s7pG8WPO/I99a3MNidvLs/k7FujWhQJ7xMTyMuHCRAczuasclbsL6FHVIBXPSSAPfnV7Myt8jrXVu2qtrz0W6pnSVkjRYHUolpPwOr8/tF8si6LHblVqFXuJXz1dicJISY+vq7lrhCKonDLp5v5dXfTl9Z1B8pZn1nGA1/voLAhcLQ6o4zl90847jsCKi3ywNym9Ini9WXpVJjdWW8zh3mnv3e0APnry9KxO933yKus56vNuTw7ox+5FWZ25TdlpYzrHg7A+QNi+GhtFnsKqj27T6pVYHMqTH5pJWckhzIiKZRpA2LoGtaxwVFOeb0nWAVgsbu476vt1Nscniwuq8PF9WckcsekFIJM7S8tADhYWse011Z5rjskIRizzcnA+EDumdx+rTNxcpltDh76dgeOZhGpv0/pQaBJxw/b8lh/wD1jfNHAGHpEBbB8fzE9o/x5+NxebV7zwgGxbDpYwQ/b8okLMfHCJf1JDvfz2jJ90c6CFs+zOVxYHU6un7uJVeml+PlovDJUNWoVvrs/hw3voAWmqDKp1Bp50HEj2eVmNh2sYFhiSIvrCiFEc1m1G/m98D8NR4onWNWoT+AM5qzZyLAueeg0LmyYeS3nDV4a8GKLa53frSfnd2t9N6yOWle2jgJLAQMCB5Dk573hxMdpmygz6wk2ub+oqtGQ6JvYxpVacrgcvJT6Entr9tJtFOj2RlN4MJwKcz2ltXV0CXFnyV8/ehgr0w5SWW/Btz6Qqwz9qNHXMCA0iSldWhmfOctwlFzK4C659I9R8fz/jeGbHRn0/CCXmxYtwNmQkptTXcV7509v8fwT5ZJBffkj/SAuRUGv0XDRgN6ex/QaDf1CDh/oq7FZPcEqgGVZB9hdUsK93e/liU2vU2mpIzc9Er3iy6D4GABu7DWKPwoPUGmrR4Mae70GHWp27S9k4v73mdIzhT7RkVw6tB++PocfRwHsLi/yOk6rLuWT3zfyrbIWAKei4ceCrvxn4AMMD+2PVn34LJZFu/Zz3zeLUACtXsWwIfGYFRvTu/ZjXPTx3exEHJudVTtZXrIcAJUeCtRdmRZ1Dmabhk/WZgF1qIB7R40mPbuMg2WVnN0rhbN7tV0i5K6eZ5FnrmBvVT7DQxO5e8BZGAfrPeOzQnMNOysK8G32FUIBHIqTXHMpd21+j0JLBeHqIDBqoN79fdXf10B+fj61tbUctHj/3O6sOEBeZTWxQe1vuCPEn8FpE7Ay2xysTi+jsMrSZrAKQK1SoVG3jCTuL6zxqnF0PKzPLOPK99Z7AhD5lb24YVzTB9PWnAqvDApfvYZLm2VXbc2u4MFvdlBd7+Dm8Ulce4b3YKne5uTV372DVTTUxiqpsfLg1zsYnhjCxUPi+OrmUewtqCHUV0+4vw+VZveuZK3VptmdX+0VrPKcL6j2BKsASmqs5FbUH9Pyv0Yul4JLUdBq1Mwe1ZWFOwpIK3YvCXxgSsNWwiEmFt45lpWpJcQFmzxZakfKqPcOTBp1GoJ99fx051i+2ZzLzrwqRiaFMLWve4Dl56Pl21tHszu/mgh/H6rr7Zz36irP81dnlLE6o4wPVx9g0V1jiW6lptahEsN9CTBovYJW2WV1pER4z8IU11h4fVk647tHHPb1/rq70Ot6FWYbv983oQPvyOnNYnfyf0tSSS2sYWKvSK4emdCBZ51YNofLEzRtNDoljIHxQVw2NJ6VqSXoNGrGdgtDpVJxy4Tkw15TrVbx9PR+PD29H9SVwYHFYIlDFd/0pSch1OSV1WXUaegZHcC3W/JYle5e5lBrdRIV4ENVvftn6dELehNettLrXiaafg9c+vZaLh4cx38vG3AM74gQ4nRlcxRQa9tOsXlvs7MqNtSHMMrkXtaWag2gXheJQetAp2nKOjI7a6myVxGhOb6FqX/I/4Hv8r4DYGHBQh7u+TDJfk2/ZzcU57C3KJouweXoNE66GvsTZWiqF7O4cBVf5y7CoPHh5uRZ9A7wXqq9q3oXe2vcr1elgoQehRQeDKNbZDCra1bwS0UtEyJG0SMyiV/umMOB0nISw0Lw1+tQFAWtto3hueV7NOQCoNUqXHnpTv5Y05XNObmeYBXAtqKWkxNHy+5yolWpUalUxAb93WtJYITf1QCc1SuF+dfPZG9hCYPio+kWceTjM51ajU6txu5q+vs3anUk+Mbw+uhnmLtuC+XJZmYM7ENcsLvWau/gSH477yYyq8tI9g9lwfa9PPvLClSosOHkx137WbhtP7/tTuOTGy7vUDbwiKh4VAo0rpLRVak5WFCJMVZPvbNx2b2KP7ZXsN6ygYtH9KPLYQpmf7d9j2cq1mFT6GWP4dHzDr888nSnOAtQal4CpRaV73Wo9MM6u0tYnN6rOWw46RN0PgALZ5rZmJ9HfEAAfcIjoYPDnlAfP94fdR0AVquV+hozaqOCT0MWZLCPkQCdCYvdQYR/LX56KzGGSIL0Bp7b/S2FFvckZomrkqRz4sj63k5YsB8P33g2Nps7W6+bLpol9ds8P2d70+s5+7cPeOKCyVw8qO/xenvEn4QTFU46WHS9g+0602kRsKq3ObnkzbXsaVjCZdRrqG/Y+U91SN2mnHIzZc0KsgP4aFWeDAGL3cmzi/ayp6Casd3CuWNiylEvd1myt8ir5tGvuwu9Alb9YgO9ingPPyRL4aaPN3uKbD/24x6Gdg3xFESnYRCkUalwNBukXDQwlgh/vacu1vxNObgUhUuHxjOwWd2rqMC26y4dmmkGEOKr59y+UXy8Nou8hp0Ng0w6nvt5Lwmhvtw/pYdnd8Ej9cP2fB78egc2p4u7JnXjzknd+OnOMfy6q5Bd+VVkl5s92WJqlYofd+RzsNTMlD5RPHJ+ryP++3n0gt7M+XAjxTVWzkgJ5coRTZlaFw+J86r/1cig0zAkwR3QbHz9h6ow21mXWcb0QYevFeXno+XlmQP527xNnqDlxJ4RzDkjkdyKTWSW1pEYauLHHe5B53urDjBvznBP1ldrogK9C/BHyc5s0FCzad5ad22NZftLCDbpOL9/TKf2Kcik5+qRTZshTOgRTr+Gf9s6jdprd9EjVlME706EaveXGs5+GkbfDsDzl/Tn3vnbPcGperuTmz/ezN/GegfDTXotax92D6ZVKhVkTYON74LLQZXiy7+Um73af7MllxvHJR2X4LUQ4vRhtu1nX9ElDcvItASrw6lwuSd1ltZG80t1PCa1gwyrP7cb1rF25AK0qnp2WYJ4tbQXMYZYQvTuz3+bzUZhYSFOp5PQ0FACAo4+c2BzRVMmj1NxsqNqh1fAakBoDIty9pJZ5v7MvXhgP89j2eZ83sn83JMN/sK+t/lg2POoVU2ToTqVzut+WrWWW8aOpDZyC9/nrwdgZck6XhjwT2KMUZ6MocNSeX+uW6xaBgxOYExKItpta3E0BHtCVUbuev17hvXowlWT29+tsD2PbVjCR/u34KfT87+x05gQO5T+savZXPYbqRYnenMJ3f3dYyNbvYP5i7fykX0jN58zivOHtZ0R3BqDVsezZ57NP5b9hs3l5NYhI+gZ5n7/DTotN49tmXEGEOJjIiTcXTcswMeAqpUvX1uzCyipqSMioO1i6I0GhsVwfcQwPt65GbVFhaFAw5izkpgYF8fTu7/C4rQRVBrFJ+t3A/D9ht1888DVhPm3nWEf6e/X7vFflVJxPTjcG1wptjUQ9jMqTeeOz/oH9qerqSsHze7leRfEXOB5LNRoYmry0W+2VFtbS1ZWliezKjExEZPJhI9Gy7vjLuPZHV+iMbq3P61y5vJ+5ufYFO/vZAP7xvHxxRd5Eg6Ki9UUFxfTTR/DudbRfJuzHTM6avP8AYX/LlklAau/IJfS8dpUbdX8PpWcFgGrVemlnmAVgN3hYtaIeAw6LbHBRp74cY/nsT0F1V47rUX463nvmmEkh7s/PJ7/ZZ/ny+3GgxWE+umZNeLoMjLigr0zbRIblouV1Vq558vt7C2oZmRiCCYfLdGBBu47u4enrcPp8trpEOC2T7fw4ZxhlNXZ8NVr6R0TwJMX9eWR73fhcClcO7orj03rww0fbfJ63ouL9/PykjTO7BnO49P6ojnMjl8pEX7cPbkbLy9pyt7qGxNAXLCJL24cyRvL0ymssrJsfzHL9pcAJZTWWnntyiMfFFnsTu7/aju2hjpbL/2WypQ+UZhtDu77arsnCyW7rJ67JnfjX9/vZHW6e0b2g9UH6Bnt71Xzy2xzoCi0u0yxT0wg6x6eRK3NQYBBR0mNlfu+2k5+ZT0zBscdNgMnNsjIbWcm8/qyDK/zKhV0PYIC1BN7RvL1LaP5ZVch8cFGrhyRgEat4rd7x6MoCpe/vQ5K3NkwigLL9he3G7CaNiCG7TlV/Lgjn/hgI89f3L/DfTmd7cjzXna7M7eq0wNW4N64IcxPT6/oACb1imzx77Le5uTxH3ezI9ddmL9bpB9rMsroExPA38Yktb1z394fmoJVAOvf8gSsIvwN3D4xxROwoiEAO7FnBF9syGF/UQ06jYr7zu7hHQhOGA3XL4YDK9nl7E3Vzy2zWHWa1vtTVmulwmwnMcz3sL97hBCnl9K6Lzw1j8BBH79wylXjCNTHsLmyhrXl6wAwqA30U15HpXZnsAw0VnBndCDJkQ+iVbs/z7OysrBa3eOiuro6UlJSMBiObmImzhBEiSWdepd7mVikj3uSYHdVNs/t+YZaez3TkhMwW3wYEhbHdT2agiUVtmqv0gU1jjoysw4QHhpNenYpsZFB9A7tzejQ0awpW4NWpeVvSdczInQE12740vM8u2JnVcY6Bup7ExYWRkhIB5ZWGy8Fy1KwrcJs8WN/3izu+efZxERE8uEFM/h23x7yCyrZv7aAEqWSP3YewOij5eKxRz4eWFOQxdx97sBetc3KfasXsvmyO/itaDVf5v4EwMLCX3mgxwMk+3bjrnd/oKbe/ffz709/ZWBiNHFhTROltY5aDGqD5++zNRf36sP53XvgcikYdTryzPtYUTwXBRgfcTVxpj7t9vn8vj1YsH0v6w/mgAKNq06DTAaCTB3/WfnXOZMYGhbL3qxihk6PY2w/92TzzxMexeZwMOTvr3raltfWsyu7kAl92s6Evm/yGIpqatlTUMyopC5cN3pIh/tyulIUiydY5T5R7z7u5ICVCi1DuIQkQz5nJHYjya9l8X7FkY1S/Ti4KnAYr2BeQSD59eVMjOzH2Ii2f0bLy8tRGpIMFEWhvLwck8kdbB0SFsdl3brxTW7TRlxZ5lyu63otW8ozqHVYCNX7c3mXMV7jv4iICAwGA1arFe32Uuo2BFMX2yx4rmk7QSGnugoVKuKOIfgvxMlwWgSsAo3eM1kBRh1PT2/6cI4JNLIlu4KhCcH887tdXm31Wg3949wfqFaHk/2FNV6PH3rcUWsySvnPL+6dQEx6DZN6RvDIBe41/U8t3MvKVPeOdiU1Vv51Xi/+NtZ7DbtWo2b6oDi+2dL0xTOr3MzFb67x1HC6c2IK957dgwsGxGBzuAjxdQ+8+scG8luzoslF1e4BxCfrsukW4c81ow+/c8otE5J5ZUmaZ0i2Mq2UjQfLGZEUyrMz+vPOygyW7S/2tN+eW3lU75Pd6fIEqxrVWOysTC3xWjK1eE8hd03uRl6ld6pufrNsp/f+yOSZRXtRgPvP7tHmbmo0LJ8KMLh/bi5+cw3Z5WYAtmZXkhjqe9jldw9M6cnsUV3JLjPzv9/TKK21MXtUwhEvKx3cJZjBzZ6TW2Hml12FhPv70C3Sjw0Hyz2P9ThMjS6VSsW/L+jNvy/o3W67RpuzKqg02xidHNZimeTpZGRSKFuzK72OLXYnBVUWogMNrWYUnmgvL0n1BIRjg4wMSQgm1M+7DsZ/F+/ni43uLbWbB+QXbMun3ubirsktZ/kW7y5k//oK7mh+0uT9JahXVAChvnrPjoI9Iv1JCPVlwe1nsKegmsgAA7FBrSxrjR0CsUPoUm5G/9sKr3+3N49PIim85Yzxop0F3D1/GzaHixGJIXx0/fCj3lVTCPHno1EHeh376eMZGHY/AAOCHXT1TaTKXsXIkCGoapZ6tR3gZ0KtC0BRnCiKyxOsamS1Wo8qYFVQ/RYDdf9jYLhCurUvRtPfGB02GoCHt31EWcMSmxLrTj4YcQfdA7w32+nu35U4YxS59e5MiD7aZPLzy7nn+cWUVprR67Q8d+80bhh4A5fHX46P2gefht26En27sKfa/YVUjYoQZyA2m438/HxMJtNhX49Kpf9/9s47PIo6/+Ov2Z5sspvee0IIvfeOUmyogIhi7733O9udnqenp6e/s3esoKhYAEF6752QkN572d1sn/n9MWGTTTYhieB5Xl7Pw/Mw2ZnZ2Tbznff3/Xl/MKv/RVHZUURJR/pgJXV1NURHRzIxPpGJ8Ync+do3ZLWaWT+aX8G8Sd1+mzA5vd9vk0Ne3lu/1/M3EZH99fuJViZ5xCqaOypXNpiJCwtClERez3mdPXV78FP6cXvq7QwwdnxTr1WqQAn1jno+ynsEQZCvVV8WPsltfT7AT9nxWEijUvHBVfMoqW/gcHEF72/ajVqp5OFzp6DpqMyyA2aPymD2qJactCMNeRxpyKdvYDxJ4cHkV8llWiqlgsTwzsd+wf5+vLOoa5liTtHF7toT6BQahoX8cfOtBEGHpB4MzoPNfzCCqh+S2AhiPShjEYTfdrzgFkVu+vQbtufJY69p6U28vjCxXSWHVH8nuOSSX2Xjn9lWPoXj1mBWl+/n/0bexNBg789NkiR+KPuB/XX7CRVDmaCagFJQtiv9HWzsx8byJaT6ldHo8iPZcBb9jPF8MeFBSppqSNRHEKhuPz476TbtkxiJ2gRqk4QzUECJwJPn+W6I9ddN63j/gPxbvm3EaB4c14OTRC+/W8RuhK53db22ZGdno1arSUrqeUfWrvKHEKxGJ4dw69RU3tuUR6BOLrVqzeyBUcweKGcPbMiq4tMdhZ7HLhoWw8Hiem74aDeVJjsZbUpaJvfp2NHSGX/94Rjm5rLEJoeb0SmhHoGktE1JWVmDtwjTYHXy6Y4CksP8ObtfBGuOtQhDJ8UqgNfWnuBQSQNuCe4+K40QvXxjetu0NNySxP6ierIrzF4lbG2fuyMUgoBKKXiJRqpWDoqRSSFe5Yxjk3vW5SRQp/YqjRqfGsrQ+KB2ZXcnb4bnDovl2eabd3+N0vO5VppsPPvTMU5WR/5j1XEuGBJNQkiL48nlFvlgSz55NRZm9o9kat8I1h+v9IhVJ8muNHUpHyvSoCPSoGPx9WN69Npb4xYlnlp+hM93FnqCuBeOiuOy0QkcL29kSnoEl45qcZJ9f6CUz3YUEhao5fHz+hHRzfK/l34+zmtr5ZmtATEGlt4yDn/NH+J00I4HZvYlVK8hq8JEiF7DJzsKuPuLfTTaXEQZdFwxLoH86iaGxAdxxZiE36Tj3YdbW9qyl9Rb+SWzsl130Jwqs48tZXa1EjJPcqyskds+3YtL7E+oajrzVZvQhMTDnP/zWk+lkEXhk+RWmTHbXAToVF7iaUfEh/jz1hUj+Pe6E6iVCu6d0YfRbX7/TrfIvsJ6nlp+xCNs7cir5ceDZcwdfuqS2V566eWPQVTgTZjte2i0bcFP3Zf4oMc8j6kUKmZGzfQsi02J4C5oXhLAfyFV5i8oqH0CEPEPuAnRfC4ASqXS40zoDi53HcX1z3vCItK0hxkYIZf7uUQ3tY6W866ERJW9kXRaBKsyaxH763dwcewoSiqsKFwCA1SpfLchh+p6eSzhcLp4/qd16PN3E+bnz58mTiFCLwtW96bfyGeF39LgaCDNlkCUsmWM6XQ6uyTACYKAKHXs5h6RHseWIy3XmOHpPTvnTo5JZlBoFIdqZGHutkFjAYjWRXPC3OKMifaLxqjXMal/MpuO5gGQEhVCv3jZtbardpenBNPqtvJ+3oe8NPQfXs9V77Dwaf4G7KKT+fHjSdCH83HeTx6xCsAhNmF21nQqWNE8fo0PDiI+OIhzBvXtdN2u4HK5WHFiC/8qW46EhIDArZfMY/2GKhqtdq6eOoLkCHn87RZF/rVrGztLihkSGcUDYyd26nBp91yim3v3vse+Ormb70VxY3mw328Xnv9bIwS/i2R+CyQz4IdUfzc4DwBOUI1E0o4CsRJBdz6CdsIZP54TVbXsLM1DFSjisqhZl5VLaYOpfXC5q6XbsiBIxGvMHLcGIyFxsL6gnWC1tnIty0qWAZBLLgoUzAqaRXi49z2mxtrAwpBtaNWyi/144SpIvoRgTQDBmlOXkc6a2I+y6kY27T5BRKiBe6+YRkSQ93aNjVa2HMrxiFUAr+/ZyZWDhhIV0Bvr8EdBREDsYjZVV9ej+Xz4zjvv8MYbb3DixAnGjx/PmjVrfsWRdo0/zB3qw7MzeHBm347LZJp59uJBRAfp2J5by9kZkVwzIYkLXtvsKRPMLDdx6cg49Fo1E/uEMj2jZ1kybtHbNeRytyzPHxHHjjz5hlOrUnDBENn+6nCJ5FaZuPvLAx5nV0qYHqOfmgars10el9ScyQOwr6CODQ9NI0SvQakQuKe5K9ynOwo8rjKNSsG5g7rWklmtVPD0nIE8/t1h3KLEwlHxnhwpmp1B718zih8OlBIX7M8tU3s+C/TXiwYyZ2gMNqebsSmhqJQKLhwaS0FNE6uOlJMaHsBfLpRn426cnEJaZAB5VRYmp4d7QsodLhGpTQ3ug18d5LMbxqJUCFgdbp747jBL98iOtS92FvLZjWPbiYUAE9Lai1X7Cuu4+4v9VJvtXDkukUfP6V42w6l4e2OuR7Q7yY+Hyjn01Kx26x4srufuL/Z5ao7L6q18dev4Lj+XJEm8tbHlYnuktJFN2dXMGhDV6Xb/rSgVAjdMSmFHbg0L397u9Rsqb7Tx4ip5tvurPcXYne52bsfTTWZ5I41Wp9ffQvXtuxfNHBDl+X23ZXhC+4DXrApTs9gp8JjrBp7iJrLuOqfdejvyanG0EqKdosTOQ0eZPqrrJSPTMiKYluE7BNnhErnivR3szGsvqv0GWmAvvfTyO0Kp8KdvxGIkSUQQOp/FFcKWIzX8FcQK0N+MqEykoHYeEvLNm0XxBrFhM1EQRVBQEGq1utP9+ULel/dgQZLk/asUSmZFD2NlmXwjF+sXypAgeebY5LRzvCGHJSX/wC7K44aRgZMYYpsMgK7VhI9TDwcC66BYduCUmk0snSe3lzeoA7klVQ4qLywspLFRnoDTaDRdFuD0ej1Go5GGhgYEQSAmJsZrouXqmSPRadQcK6xgVN94zhvTs/GKn0rN0lmXs6OiiCCtH0PC5PHjZQmX4ZbcFFuLGWwczOQw+T14+YYL+HF3Jnani3NG9MVPI38+DtHhtd+ypnrePLyDWwbKk311pibuOPAW+Va5MmBtxUE+G38/NXYRh6TFoJbH56JkIFjTvlystraW8vJyz3thNBrbrfNrKC4uZkvtYU8ZqITEIdtxXrv+2nbrvn9gL6/tkstcd5QWo1WpuG9M14WWIw2FHrEK4Nvi7dzW5xz0qj9mJqmgCEIwPIxoegUsr3s/6Not/wMk63cQugRBfWazmPaajxM0vBpBAJdFRdOxcAJ8dZfUnQ22HwFoEv04YJHvGwQEBhgT2q1e0OQ9vm/SN5Gc3L7r6InKnwg2tkQuhBl34XK5Om7C4INrLhrDNRf5nkgvK6njnls/osJugQu8v1O+st96+e/FLQm4u5hh1dX1ABoaGjh48CCffPIJ//znPykuLu7CVr+eP4xgRXOZV1e4Y1of7pjWsmyxe+ex9I0ycN3ErrUvrjTZ8Neo2gWO3z+zL3d+vg+HSyQjKtDjKlhxqIx/rztBjFHH2f0juWJsIumRgTQ0Obn07W1ktilBzK228OkNo6k02UkK1fP9gTLe35KHuo37yWR3UVzX5CkLPMmiMYkkhPiTVWFmQlooGVFdr1O+fEwC5w2KxuZyE2nQ8fORcl5Zk41WreCJ8/szJT2cKZ1kKnWHUUntsxvuag5gb8u0vhFMazNpFhfsz8JRcXyxq+WHsyO3lo3ZVcQY/bjivR1UtcouEyXYllPDZaMTCNWrqbHIAsLc4bGk+yi9u+fL/R4n1lsbcpmQGtZpnlR3yapoX3oaH+x78Hq83OQVkNf2O3MqBEEgUKuixtUyiDzp/vsj8+rabE6VK7gjr/aMC1bvbsrz+vxSwvU+Q9YvG51AiF7D4ZIGxqaEklttYUt2NQNjDdw6tX256/CEYPQaJZZmZ+dEH8IrQEZ023OARMYPc1mTdQtPlwwn2uDHPy4ZTGI38thaszWn2qdYNTYlpMuCeS+99PLH4lRilbyOH0LQ3zzLLle5R6ySkQgK0eGvOfXkiiS5cborUSlDUQgt4yK1MpyowJspN70FQJj+Evw18oDiHwfWsTK/glB9PBcnD+Di+NEEqP3YX1PCdRu+JMi/hEGRLZNcx60HmZ92LXa7nRsvTeJEqZmDx0vxi9CC0DLeyKz2PfEQHx9PfX09oihiNBpRdtGJIwgC8fHxREVFoVAoUCqVVFRU0NjYiEajITY2loXThnZhT6dGp1IzJdb7muin9OPGlBvbratWKblobPtSv5EhI1le8hPVznIkCfKqwties4FrMobzy54TPP3FCtTntsRY1DnM5JrLmRU9kscPHiBeX4VCELgq6XZUCu8x7slyypMUFxcTEBDQ5feyK9hsNkLauLqidL6rCo61+aw7+uw7om25l0ahQt1J5tcfAUmSoOnTU6zlAsdeOMOC1dLSjZ6JNZXexcKzUjD6tRcLBeMLoB6BJNai0pzDzLhsSppqOCtqCCNC2meZDTAMYFP1Jq9lX4QH9PU64zVawjicdZTl7j1kmYsYGJTCvekL0Cp9iGhd4Ptv9lBbY0YNBGU6qc+Qx/63jxxDZEBvI4BeTk1oaChvvPHGb/68f+yzYBe5ZUoqjyw7iChBfIgfc4aeOvBPFCXu/nI/3x8oRaNS8M8FQ7yCnGcNiGLzQ9OoNNlJiwhAp1ZS2Wjj7i/242h2W321p5iHZsv18Z/uLPApPARoVQyMCcLoL59UhiUEc9/MdAQk5r3RInCFB2g8wfFtmdQnnEk9LG00+qsxoqa03sodn+3zHPv1H+1mx2NnoVb2rO71TPDc3MF8u78Um7PFzaYUBF76+biXWHWSgbFGoow6frhrEmuOVRIZqGVmBy6jWrP3DGGNpf3+fg3TMiL4Zl+JZzkp1J/XLh/mWf7+QClZFSampIczOjkEf42SpmZhoiei4cuXDuWuL/Zhsrm4dnwS41J7VtL530R+dVO7vwVoVZhbCdZD4k7PzKwoSnyyo4DcKgsz+kd6ufa0Ku/fzMjEjsvwZg2I8jjfJqSFddoQID7Eny9vHsfS3UWE6LXcNNm38BYT5MdfLhzACz8eBpeVh1RfECNUocp6jSL76xTVWrnny/18c1vP7Pd+bTLB9Boly++YQFJYQG/oei+99NJlNKooQvVzqbHIpTRBfjPwU5+6xMvpruJ45SKszizUymj6RizGT90i8scHP0pYwAIkyeURq1YUHePNY9sAKLdCoKKUa1Nl0f7lgxtpcNhQqbxzBiO00fj5+eHnJ4sMbz11GY1mG9XOJi5Y8glNbgeoRIbF+B5XCIJAcHD3ci9bc9JhVl9fT1WVLIzY7XZKSkpITOxZs6AzgZ/Sj0uib+bGjR/gcKmwOjUoBdly+/wX63BZQWlRotC7m9fXEOcfRpjWwP+NvJsjDYUMMMbTzxjfbt9ut9trWZIkRFE8rYJVYGAgM5yDqXObyXFWMDA4mauTZfe73eli6eaDmG0OLho7gCkJSXxzvKXR05TErk1+nyQlIIqb0mbxfs4aNAoVjw6Yj+YPLlghVoPU0P7vgrHV3xWg7jxwv6tYXBZWla/CITqYHjGdCF2LW7ztez0yvv13DkAQ1KC/AgHQAbf16bxz4JjQMSgEBccaj5GkT2Jy+GSf6w1LXsDaI8ewu3/EYg0hWnkfP5p2sckqV8pUVOwhUhvCtSnn9uCVg7bV5HTYPhfTDAnc/+j5xAb2hq7/0fgtMqx+S/7gZ8GusWBUPEMTgsirtlDWYGXN0QouHBrbaRD1huwqvj8gz+o4XCJ/+uZwu85jEQadV7ZQldnuEXxozraqb3K0c2chpzeAADMHRHrEqpOcXP+9q0cy5/+2UGNxUGV28NraEzxyTka7fZ0OyhqsXsdea3HQaHW2C4r+TyIIAn+9cCCPLjuES5Q4b1A0E9PC+HibtxVX7vKXxoz+sqsl2uh3ys6AV49P4v/WyZkNiaH+TOvruxyqNW5R4pt9JdQ3ObhgSAyRneRMzRkSg06lYFd+LUPjg5mYFkZZoxWb081HW/N5bkUmAK+vz+GzG8aw5OZxLNtbQpC/mkark9s+3cOcITHMHtg1B8vk9HD2PzETtyj9z4gIGVGBXtlo989M55rxSXy+s5CdebUMiQvi1qlpNDlcvzrP6/lVmby1Qbb1f7wtny9uGsfoZNlFeNdZfdiRV8uJSjMpYXqGJwQz+5WNaFUKHj+/PyN9uA3bklneyIpD5cQG+XHJyDhPOcjAWCMDY08tul01LomrAvfCVzd4/maXWs4zJXVdy7rzxZiUUBaNSeDTHYXo1ApevGQIqRG9uQi99NJL90kOeYlw/aU43BU43TXUW1cR7D+7023KG9/B6pRLvZ3uMkrqXyIt3HtG2E/t7YIotTR6Lzd5LwPUNAVwuCKaQaFWEjThXBx2Tbt1DAE6DOh4fsYMHti1HKfkZoclh3WlJ5gW03EjmF+Dw+HodPn3wOjIJGbFjmHJiUMoBIEnRp2FTqlq7pgm4NgUjGqgmYEpEdw95DzCtPINdD9jHP2MHWdw6XQ6/P39aWqSJ6QMBkOXSkUlsQ6sy0HQgd/FCELHjpWYmBh0Oh13O+diNBqpd7sobTSTEqTh3ne/Z8sxOS/sq60H+eqRK3l99gXsLC0mwc9I3uYynlpfwpUXjiY1/tTZqABXJ0/niqSpKBB+k0zN/zgKYxtxSglB74G6H1heA3cZgt+FoB6CJNkRhF933/FS1kvkWeSstR21O3hm4DPoVbI4/WC/i3nswGLMLhsTw/tzpMDCP9Z+QKIhiOemzyBCf2oX0obDuRwuKGdkWhxj+raUB44KGcWokFGn3H76gCcpKbmBujq5pLiu8ZjX4xW29g72rjJ/4Rh2bjtBVmYZkVFG7r15Vq9Y9QdFREDsYqnfyQyrkyXqJ9FqtWi1v4/7/F7BqpnU8AD+/M1hT1e2JbuLWHLzOFQdOIicbTrbOd2iz/Va0ycikMFxRg4WyyflcSmhxBjlmblFoxNZvr+UzHJTS1aVBMv2lrBoTCIjfLgwjpQ2ejp9Aby/OY+HZ/c9Ixe4ftEGksP05FVboLm8pytiVZ3FQbXZTlKY/oy7seqbHOzOr2NkUjAz+kdy/UTZYXL3WX3YXVBLfZOT2CA/ltwyzncXtE54YFZfxqeGUmW2MzU9op2I6HObpQc8rqn3Nufx412T2pVstmbmgChmDohid34tE19Yi8nmIiVcj76VcOoWJX7JrOSxc/sRotdw5Xs7yKmSP5MVh8v54saxjEnxdkudqDRxx2f7KK6zcvGwWP5y4QDPd+R/RawCeG7eIB75+hAFNRbOGxTNndPlGbGbJqdy0+RUTlSamfD3XyhvtBMbpOPrW8cTZeze9+Qkv7Tq0ilKsPlEtUewijToWH3vZOqanNicbqa+uN4TTH7SudhZ58ITlWbmvr7V47A7Vt7Ikxf0YOax3xzIOB8yf0BU63nO1VLicdGw2E437Yyi2iY2Zsuz/RGBWgbHt8/bastnOwrZnV/LsMTgU4rHvfTSy/8OgiCgUcVzovpWXKI8Posy3EJ80CMdbiNK3oKNhLPDdU9ydmw6/3dkC41OueRvblJL6dG9gydzaEMZDQ4bLmsS89UTCFJqMZVbkIIln2OuvfVFOCX5HO2SRD7K2nXGBKvAwECqqqqaxR+6nOFUba/GLbmJ1PUsq7U7WK1Wbo8dwCWhScRERhIbJI9T7p03mec+/wW3RcUo81BemXhhh+NuXwiCQFJSEiaTSY47CDz15IgkWpBqFoJbFi2wrUYIebfT5wgNlY/3/f17eGbzeiRgdkofthzL82T/VDVYOFxQzjn904kIUvDwN19iqXfDIX92Hsrny39eR6Dee+Jy0/I9vPHol4iixA1PzePsS+Vge2UXSmj/KAiCBoLfQjI9C5IDIeAuBF1zLqvhCQAk2wqkiqGAA0kzASH4vS6VGbfF7DJTZj2OUeXC4tZS76ynqKmIDIM82T8iJI0fpjyO1e1gY34Rd27+AYCculoeXbua9y7oPAB/+Y4jPP7pzwC88/MOXr5+DtMGty8RPBURERFYLBYcDgej9X056ChAQkKBwLTIYV3Yg28O78mn+EARCpuT5MHxxMR2Pj6zOp28tWkn5Y1mLhzcj3Ep7fO5evnjEN/GUfjkk0/y1FNP/ceOpzW9glUzhbVNHrEKYG9hPfk1FtI6cAZM7RvBuJRQtuXWoBDokrNJo1Lw+Y1j+W5/KSqFwJyhMZ7cLaO/muV3TCSv2sK5/9qEu1WCeH2TPPhyixJvbsjhSGkD41LDSI/wVvrdksRl72znifMH0D/m9Crm/hoVX90yjqV7itGpFCwcfeqT1vrjldz6yV6sTjeDYo18ftNYn26yX0tDk5NHvznIuswqrE55gLgjr5YBMUbGpoQyKM7IxoemUVJnJSlU36lzzhebs6v5x8/HUQjw2Ln9uiRWSZLE8gMtuQplDTbWHC1nwahTv28v/ZyFySaXqeVWWegX7f0dTAnTY3O6Wfj2dq8Oh5IE+4rq2wlWD3510FM6unh7AaOSQ5gz5NRlr380IgJ1vH9Nx7NbTy4/THmjXOpZUm/jote3su2R6d0WgHOqzO06T/Zv8xkKgkCIXsO+wjqPWEVzh9BGq7OdYLX1RDV/Xym77AbHGT1iFcCqw+U9E6yUKlj4KViqUWgCeKRRZPjRcqKNfpwzsOcB/K/+kk1RrezQKqy18n9rs3lubseB7p9sL+DP38p292X7SnC7Ra6Z0L0yil566eWPS4N1rUesAqgxf92pYBVpuI4660qc7nKUQiDRhttP+RyJgcF8N+ta1pWeIE4fxFmxLSU+Q0Nj2XDB7eTXVOCqrEOtkM/PoigiSbJgVWe18vLOrdTZrFw+YDBGtbcwcTingofzf+JPC6Zj8D+9Adp+fn6kpKRgMpnQarVdEqy+KfmG5aXLAZgaPpWrk64+rcd0EqvVSklJCTabLAT6AY1llUQFBqFUKpk7aRATByZjstpIjgrtchbtSd7au4tvjx8jNjCQZ6fOwNCV67XzcItYBeDYiMtVh0rVeXmm0+3mua0bPVmYK3OzSYgIoL5Svt6rFAriwoLINpVy3/73cSW5USSBZHRRt1GguLyefqkt11ZTvYV/3PYBzuZYglfu+ZhhUzIIjTr1JM8fDUEzHCH0a5+PSZIbqf4hoFmIdmxBangYIegfPtfvjBLLdvr7lyEI4BQV5NgS2gm26ubcsMKGeq+/FzTW44uvitazqnwnYRojDUdaPjtJgrWHTvRIsFKr1fTp0weXy8UA1QD6N6RzzFTAAEMyGYE9n9T79zPfY29u4rVrYxabfj7C1HM7Hp89+u0qVh7NBuDHQ5ksufEy+kWdusKkl/88Uje6BErN6xUVFWEwtOgHvxd3Ff/rglVxXRNPf3+UWouD+SNi0akVnvwjrUpBiL7jD0qjUrD4+tEcKzNh9FOTECoHZEuShMMtolX5FkX0WhWXj/EtWmhUCvpGBXLNhCTe2yxfTPtFGzz5Qq+tzeaVNfKJ46dD5bwwfzC3TEnlvU25OEUJtyixPbeWaz/cybZHzur2hf9UhAZouWVK10+8f1+R6RGQDpU0sHR3EdeegRvRZ348yk+Hyr3+JklwtLSRsc3ijUGnxhDd/WDxGrOdmxbv9ggE13+4i22PnoX+FMKbIAhEG3QUtypBe21dDvNGxJ/S1dR2vDUlPZyMKAP7iupIDQtgRv9Iimqb2okiCgGfTrxqs3feVrWPPK+u4BYlvthVSHmDjfMGR3crwP8/ia35O9iZa4nmz7o15Q026pqcHbriimqb+GJXIf4aFdeMT/J8J5bsLvLqwhdj1HUY0N8v2kBaRAAnKuVW6qOTQwgP9D7vNFid3Pjxbk+YelabrLuUDrLrusrzG6t5d/NO9BoVz148iHc353LH53sZmRjMO1eNpNbiYMuJapLDApjY59QlDS7RO9re4eo86n5Hm4D2nfm1vYJVL738jyPZtyCZXwdBg04zzesxjarzCRedKoFB0auxOnPQqhJQK2V3q1tyIyCg6MCZkRAQzNXpvic1AtVaBkTEkWdxYrXK1/Xg4GAUCnlft6xYzs5SuenLz7kn+Hr+ZeyrKWFzeR6CWcCe6Wal4zgKQeC5q9t3b/21tM7SOhUmp8kjVgGsr1rPWRFnEeffceldTyksLMTpdLLiRCG7yqqIDdSzaGAfnE6nJ2cqIjiAiODuX8fW5ufy960bAcisqcL+y0oWXzj/1Bsqo5q9KvJ4v8GlZnHuz9yVfukpN207ert7zgRWbMik3tzE+cP7Ehdi4NvSY7ikVtlaMU5CjP7ER3uPz5oarR6xCsDtEmmstfRIsJLEemj6XF7wvwxB8d8hekmiGQQdgtDZmNoNtBm3OvZ0ut/tJUWszc+lT3Aol/RvcUseqPvaM8ZWK0QmBqURqPIt8E5PSuG13duxueTP6Ly09Hbr7Kk9zls53wGQbykjOCEU9rc0rEkK73lGnYSdI1U343BuQaVKo1/jM/z1zu+oq7Vw7pxh3Hn/bPYdKya3uJoR/RNIjjt1Fq3b5Z355nK6O1wXYFdBS7auUxTZX1TWK1j9lyBK3SgJbF7PYDB4CVa/J/6nBatbPtnD4RK5XnNfYR1/Pq8/i7cXIEmSp+SqM1RKBYNahTRvy6nhtk/3UG91Mn94HC/MH9yj8rzHz+/PWRkRNNqcTE4P9+Tp7C30Vvf3FtTx93mDmZgWyhXv7fT8vaLRjtnh+o93fmv72hVnqBa/oLZ9mDbA6ORgRFHqknBXabLx8dYCFAqBa8cnEdz82Vc02r3cLI02FzVmxykFK4D7Z6Vz75cHPMtFtU1UmexEGTufXX1wVl+u+WAnDVYX6REB3Dw5lTc25JBf3UR+dROj//YLH10zmlC9xlMSqlEqeGnBEE+3RbcoUdFok8sGxybyt59kd05YgJZzBvXMPfPEd4f5dEchNJc4fn/nxA6D/k8iSRIbsqqwOUWm9g0/pWh0OtiWU8O645X0iQjA6nTz9PdHkSSJB2b15TYf3fVOcuOkFO5fetCzHB6gxejn+zdUZ3Ew742tVDaLfxuzqvjy5nHgo+NiaYONKf9Yz6c3jGnXgVKnVsrOxd3FqJUCl45KaPe7qTbbPWIVgM0lcsuUFDZmVRMT5MezF/e8a87645W8sSEHgHqrk7u+2Ie7WXDalV/H098f5ecj5Z7nf/KC/qcUnW+ZksqGrCpqLQ7CAjTcMiWF+iYHz/2USVmjjfkj4rwcfkPjgzx5gABD4v47Btq99NLLmUFyVyDV3waSLAwFuLKICbyD6qZlqJWRJIe+eMp9KBWBBGhbOuWtKFvB1yVfIyBwZeKVHYYed4ZCoSA5ORmz2YxCoSCgVVetfeUt5zCH201uXS0fTr2M177fzLtbd3key6voef7MmeRMRElIkoTT6WRrcQXvHTgOwMHKWlwSvDJooMeddioOFpSx+kA20cEGLp0wGGWzSJhXX+e1XtvljhBUiWx3Xk2suAS7pOTf5QMxCTmn3E6tVPLEpGk8uXEtoiRxYXoGFw3sj66qiRcXb+PNg5tZtfoIdz8wEQEBqdmLFSEF88rjCwjwlyejbG4XNVYLkbHBjJ4xiJ2rDwEweEI6CX2730lXkhxItVeAS85tw/YThH7daS4XgNVt5XDDYQJUAfQz9Ov283b/OCWwLkNy54BmMli/BNuPIARC0GsI2vE+txMEDZJ2BthXt/xRPaTD59lRUswV3y71VKqUmU3cNVoen2kV3mPWJYdK+Wrvlyy+cD5+bbLPMsLC+Wb+5azNzyXBGMT5fdo3fCi1Vnsfq5+TeeMHcrigghFpsVx11oiuvDU+2Vn6T5TuDQgCuN2Z7Ct9hOqqqdDc7c9tULNknXyPoVGreOPJS+mf2vn4/tp7ZvHyE8twu0QyBsczceYATphKWJy/EkEQuDJpFqkBLZEQg2OjWJcl57EqBIEBMWe+fLiX3z/Hjx/H6XRSX1+PxWLh8OHDCILAgAGnpzGCL/6nBausCrPn/6IEoQEa1j0wtcf7e+jrA9Q1yVkJS/cUM6N/ZIdd507FeB8t6UclBrMxq6VF7klxYnB8ELFBfp5A6XEpof9xsQrgsXMzuGXxHiwON0Pjg5g/wnv2Lq/awtd7ignyV3PluMQOXWkA3+wrZsmuYiINWv50Xn8vF8oFQ2LYmdd+EHj9R7upNjuYOyyW5+cN7lC4sjrcLHhzG/k1svD185Fyvr9zImqlgtQIPemRAZ7vyuA4I7HBXZvFnJIegUGnorG5vC/GqCM0oP0A4mBxPbUWR3P3PxVhAVoCtGoarC6anG5MNifvbsr1rO8WJZ5beYzF14/hlTXyAOWes9M9ZaCNNidXvruDA8UNBPur+eDa0Xxx01hK661MTAvzagTQHX5ulcvU5HCz9UT1KQWrB5Ye5Ou98qzziMRgPr9xLBrVmctm2JZTw6J3t3PS5OPJgwNeWHmcgc1lor6OYd6IeBSCgnc25RIaoOGJ8/t36IY7XNrgEatodglZ7C70WhXXTUhmZ14tG1r9VqtMdl5Ylcm7V3nP3jtcIh9uzSenysLM/pE+y1UTQvwZGGvwiOsDYgzcP7Mvj5zTj+PlJvYX1TMiMZiwHjRAWH/cu+W2u407KrOs0UssW7q7+JSCVd+oQNbdP5W8GgvJYXqMfmqu+WCn57k2ZVcRG6RjRKJ8/rpuQhJuUWRXfh3DE4K5cZJ3d0NJkthbWI9aKTC4V8zqpZc/Pu4Sj1gFgFhFjOFqYoMf6NHuquxVLC1e6hEQPi74mBHBIzxBy91BoVD4nIEeGR3LtpIiALRKFYMi5LHflIGpfLh2D67mnNPpQ85MjlV3CFQHcnHsxXxT8g0AZ0WcRayfd25hg20zjbYt6NUDCNGf3+G+3JKbLwp/INOUQ0ZgKgsTzkcpyNcxQRAwGAzk1Wd7bXPQWc2QZf8E4PHhM7g0dajPfQMcL6ni2n8vxdHsDMmtrOXP86YDMCUhiX+q1TQ55XH37NTOO7W1Rqu/mBsPVnqWp0W07wbnEkW2lxShVigZEyuPX+MFAyH5KmxuFw6lA9NYC5/8dBBrs1Mqr6SOrJ31PDV6IStK9xCuM3Jbn3MxqOUqjMM15Vz9yxJqbE0MCIlk8bvXcGRNJpIoMfacISh7kvXqLmwRqwBcx8FdBKqOKyKsbivPHH2GUpsstJ4TdQ4L4hd0/7m7g+X/kMyvNf//fWh2uCGZcDX8iYqAJcT5+3ajK4L/jdj4HNi3gHogguFPHT7N+oJcr1iVX/JzPYLV5Mg7+bHkz9TZS8ipiuBAcSKiVMqyzKMsGuQtglU2mPnql4PYnE6mTfE97hkR0hd/pY4mt1zyOjliCLdPmAHAtvICNpflMyE6CU0PulYer8+mf6s5TkWQxevxHUdaGko5nC7WbM08pWB19oXDGDwqmYY6C0l9InEqXDy6903qnfI9zpGGPD4e82f8mjuivnDxbF5Zu5VKk5mLhvRncKz3/q0uO1mmIiJ0QUT7da2pQC+/DWeyS+Dtt99OeXlLZdPChQtRqVTs37+/28fZVf6nBauzMiJYcVh+wwN1qi515+oMi93bWmluZfU9Hdw+LQ2dWsmhkgbGp4Yyr1kAMujULLttPF/uKsJfo2TRmN9HaPGkPuFsffQsai0O4oP9sNjdVJvthAVoqWi0Mff1LR6Bb2deLW9fNdLnfvYU1HLfkgOcvP5Umux8duNYz+NXjk3EqFPxyLJDHjeUTq2gojmPaOmeYqb0DW/XxfEkudVmj1gFkFluorzBRnyIP1qVkiU3j+PznUUoFXDZ6IQuB5WH6DUsvn4M/7fuBBqlgvtmprcLnv/3uhP8Y5U885gRFcjXt47ntbXZHvGxuM7Ka2tPoFAIiK3KzCRJon+Mwed79sn2Ag40B/vXNTl57qdjHvdPV3G6RR5YeoANWVVEBGp556qRpIbrqWol0pyqFK3B6vSIVQB7Cuo4WFz/q39nnbE+q5LWmkvbYrSr3t/JgBgDX9w0lkAfou7Fw2O5ePipA8eTQvVoVApP/lRskJ/HdeenUfLRdaOZ89pmDpa0tGrOLDO128+zPx7lo+Yult8fKCVAp2rXgVKtlLPvvtxVhCTBpaPjUSsVfLe/hPuWHMAtSoQFaPnmtvHEh/if8thbMyIxmA+35nuWtSoFTreIKIGfWsHUvuEca1WCGBPUNbHT6K9mqH+LuHRSbKNVue5JwUoQhObg+/b7kSSJ2z7d6zlPXz0ukacv7LmjrJdeevkvQJUOilgQm8tR1INA0fObIZvb5hGraBZZHKIDPd0XrDrijXPm8OqubdTarFw2YDDJQXIp0ODkaD64ewGbjuSREhXCOSPOTCfn7jInZg6TwibhltyEacOotjfip9SiV2mpt64ju+o6zxXUKVYTGdi+IyLAtyWrWVayCoCjjSfQKjXMj2speYyPj2daPxPfHs9HAiSlRIl/LScr5h7fvYLpMWmE+/keT2zPLvSIVQCbj7VkT6WFhPL1vMv4OfcEsYEG5mb07/LrHxmSwQN9L2ND1T6idWFcn3Ke1+NuUeSGH75hQ6F8fby0/yD+Pn0mf/9qHQ67GwUCW47ls+HoXjL6HkLQKMnNj0XUSFglJ2dHjebsqPZC3PN711Njk8ebR2orWJy9j7vnTOzycQM4nU6++W47O/cUkhAfxs3XjUYtBIDUPAkvBIKi87KtIw1HPGIVwOqK1WdcsJJs61oteTeqanBUc+3Ov3FO9Fju6+u7NFNheLRLz5Me6n2uSA9pKZUL1iZwRcrHDHj1FZoULd+rw3ll0EawuuX1ZeSU1QCw/lAu3/3pakIN3ueMGL8wXht+D5uqDxKhDeLsSHlM/tj2lXyWJd+8j46M59MZCz3Zd12l2jkFi2sLepUDtySwo2E4lXNFdEUCGeUhxCaGU1DZUnkTEdq1bswRMUFExMjjs1JLtUesAqh3mqmy15Ogkp1UgTotj587zed+Ghxm7t73KiXWKpSCgkf7XcGUiJ4HwvdyeulJSWBXWbNmTQ+Pquf8TwtWrywcyvCtBdQ2OZg3PLbbnePactvUVJ75UW4/2jcykBn9T691UqEQuHFyis/HIg067jqr67NLvxVGPzVGPzUfbsnjLz8cRZTgugnJjEgM9ohVAGszKzu0h2eWm2g1WeIJEG/NnKGxDIw18vG2Avw1Sr7eW4zN2SKuHC5p6FCwig3yI1CrwtQsMIboNV5ulSB/DbdO7X5oIsCQ+CDe6UCIA3hjfYsNPbPcxNrMSlxub5llQ1ZVu78dLTNx6yd7+Pflwz3OMbco0Wh1tlu3baZQV/jHqky+2y8PZuqbnFz47y38dOcknvr+COXNZV0Tml2ANqebI6WNRBl1Xr8hnVrhlQsnCBDUhcD6X0N6myYJrTtbnuRIaSNf7irihkm+f0tdIT7En7euGMEb63Pw1yr583nt7fTJ4XovwSraRyno7gLvEoY9+XXtBCuAQJ263fG+tznP44iqNttZtreEu8/u3jnggiExbM+tYenuYvRapddvcmhCMOcOiqbB6mLNsQqSw/T89aKeiUUT00L5tvn7pFEqGJXcNdHyaFmjR6wC+GhbAXdM79Mu56uXXnr54yAoAiD0c6Smz+UW9v5X/qqStTi/OIYFDWNf/T4AJoZNJFjT82wZXxh1Oh6f5PvGbnBSNIOTul/qdaYJ1gQjSiKPH/yEtRWH0ChUPD7wUlLUa7yme+qtv3QoWOVbir2WCywlXsuCIDBzyADe8vdnXVYuRqOW14o3eh53SxIljQ0dClZ9or3Fh9Qo75yejLBwMsJ8u3JOxazo0cyKHu3zsSNVlR6xCuDLo4d4cNxEj1MOwKg3ExF5H+fMruEcYOneMXwnDuBl91q0J1RcnTbGs67d5cLuduMUvYUal3jqDuNtWbFqF6+/uxWA3fuKsTQ5eOSut5BMsmtNCLwfQSGPheprLZQWVJOQGkGAoWV8FqDyfr/bLp8RVH3AdbhlWREDYimiBJ9Wy2OXFWXbuTB2oldZWne5uG9/ykwmfsnPIS04lD9Pal85E9XgT67RBApQWiC1zfmgscnmEasATFY7J8pr2glWAAn6SBbpZ7Ss67B7xCqAnRVF7K8qZVRkexdfZ1zf71Ie3WHB5tyPXYhiT6MaksGWLDE4MYOpwRlYbA5yi6oZOzSZ+bO6LxZF60KJ1oVSZpNfa4wujChd18Znqyt2U2KVnfNuSWRx/qpewaqXM8b/tGClVSk7FIB6wg2TUhiXGkq12cGopGBP9tT/Oma7yyNWAby/JY+RicEoFYLnhjs1PMAzILXYXXy5qwhRkrhkZDxjkkO9hI8prQKsj5ebeHtjDmUNNmb2j+TRczPQqpQ43SLvbGqZiVu2p4RHzvEWFSx2F3VNDmKMfnxw7Sj+uToLpULgoVkZ3e4k2FP8NUovJ15+jYVbp6ayMbuKarODYH+1V+lZa1YcLmfNsQpmDogiq8LEVe/tpLzRxsBYA4kh/hTUNuGvUXLv2e2DIn1xsLgetygxND6IQ8WNXo/VNznRqBXtHF0NVieXvLmVrAozaqXAK5cO47zB8sBcq1Lyr4XDeOTrg9icIvfPTO+w6+bpYt6IOMobbaw5VkGfiACeuGAAJyrN3PflfnJbCVenI09tWkYE0zI6nsW8enwSq46UY3OKKBUC109sf64ZnhDMkdKW99pXaH5HtC37NehUVJvtBPtrOnUBLtldxKu/ZKPXqHhpwRCevXgQz148iHc25vLsT8c8623LqeGC/9tCRlQgq++b0mGeV1d4fv5g0iICKGuwcdGw2C4H9vu1yTxTKoQzWlLaSy+9/D4QlFEIgfeenn0JAnek3cFx03GUgpL0wK5dE/8X2FZ9nLUVcoaSQ3Tx4rFv+GCE98SHrlVpWYWtgt11uzGqjYwPHc+woAFsrdnreXxYUEuGyYbKw6wq2o+7TuCC0DE8ed5ZSJLEquXHyGq+0RVMCj7bcpChc70FirrGJkRRYnzfRP48bzo/7s0kOtjAIxf1PLajO+g13vENggSmBhv3XjiJxz9ZhUsUmTO2CqWyRdSYNuAw3x0agIjE3w/+zMUJQzBodCzPOsaDv6zC4XYzo08KepUGi8tBQkAQV/YdfspjsTtdHC4oJ9SgJykimKwTlV6PH80sQ9BcgBD6udffjx8s4rGbPsRishEcFsCLH99IbKIsAGYYMjgv+jx+Lv8ZvUrPzSk3/8p37NQIhseRBAW4chG000F/NU3WHdy1/xMKHS2CmaKLnc0647aRY7ht5JgOH79u7EheXLYeSQUhaj/OHentfAz005ISGUJuc+ZcoJ+2nVjaEVqlCp1SLhs9ib9STX1jE0GGjl3wblHkH9+tIbt8J+GGeB65aAFvTJY7nN605TPghGfdt/ft5J2Sg1w8tD/fP9aFRgMdoFGqeWnoHXxVvA4BgfnxU9EouzbW0yq819MpeycSf0+I3egS2NX1/pP0KiqnmQExp24n3FVOVJrIrbIwLCH4v9pR4BYl2pp84kL8ePnSoXywJY9gfw1PXtDfs+4V7+1gX3PA/Fd7ivnujgksuXkc3+4rJdKg9WTo1FocLHx7m8cVsjWnhp+PlvPJ9WMZlRTiJVjVNDlwi5LnRn5rTjU3f7wHk93FqKRgPr5ujFeZ4W/FjP6RniBzgBWHyrlzeh/WPjCVguom9BolM1/Z2KFL6khpIzMHRPHsj8cob5Rr6A+XNHLn9DRm9o8iOkjXpWyjx745xGfNxzFnSAznDIpiW27LQCwiUEuIf/v8rW/3lXjyvZxuiWd+POoRrABmDYhiVg9z3HrK7dPSuH1aS07I0PggnrloIDct3oPZ7mJInJEFozqf6TLbXfirlb+q0+bwhGB+vGsSe3LK6B/hx8CU9u/Dn8/vR7C/Ws6wGhDZqQDWlqfmDOCmj3eTX2NhYp8wPtlRwNM/HCUp1J9PbhhDXHD7gdHxchMPf3XQM3e+4K1tHP3LbGjuUKhSCO2+a5nlJr7aU8z1E+Xf3eJt+ewtrGdkUnCXy4+1KiV3TO++AzQlPIB7z07nlV+yUAoCT80Z8KuEs1566eV/E4WgOK3B0rsKimlyOBmXHI9G9d87lPbqZgc4RTcRAVfhdFfSYNuMXjOAuKCHAaix1/DXo3/F4pYnf3LNuVyVdBVapZrMxlwyDClMCJMntXbVZPOnA4s915pNG7O5IW8W180dxwR1KjlZsvtYaFJQqfV2QX+yfCevf7EJSYLLzx/JnYumcOmEjkO2zwSpwSEMcIRwRFULEhhyYPmag9x1xVRGpMVRZ24ixLidgrqWbouNLtnBJCChUrrINZczKCiBR9b+jMMtv8+rs3N594KLCNf7k2YMxV/deTB6k93Btf9aSmZxJQpB4LEF0xnYP5YfVx33VB4MGuC7u+OX723EbLZhTtHRoHbz0YfreezJFnFjftx85sf1XOzoLoIiAMH4nNff9P5TOCvWwYd5K5CQuCBmAskBHXcBlSQJq9uGv+rXVcQsmjGcjIQIiqvqGN0vgehQ73s3QRB48/Z5vLVyG1a7i6umDyfMh7vKFxqlkpcnns9DW1dgd7u4JGog9zz8FeYmOxOGp/D3e+eg8pHZu3TrdtLi/8RZI6pwuRV8srmYO2bJWV1jI5LZUNEiWGGRt/9m/1GuGTucvpHhWBwO/r17BxUWM/P7DWBcnO+O9G0J1wVxa9rFXVq3NbOix7C1+jC76zIxqvXc3mdut/fRy5njTJYE/if4773K/sFZcaiMOz/fh0uUCAvQ8PWt40kMPX15C78lRj81d0xL4//WySfbC4bEMCjWyOC4IOYMiWFPQR1LdheREhbA6OQQj1hF881yTqWFwXFB7QKXsytMXiVMAFtzaimuszI2NZSkUH9PNtX84XFerpNnfjjmKQHclV/HV3uKuHJc0hl9H1ojihIVJhsJbTKHTh6jQaf2dKB8ft5gnvnxKIIgMKN/JEt3F3kEwH/9kk1Fow1bm9a0LlEiyF/NU8uP0ORwc8OkZMan+s4AKWuwesQqgOUHSrljehpPnN+fL3YVEmXQ8cL8IT7Fm7Zul7IGG5uyq5jUp2cW/TPF+LQwtj46nRqznKem6iDY1OZ0c+PHu9mUXU1EoJb3rxnFwNiWgcxbG3L4eFsBYYFa/jFvIOlZb7PuUCGfWMcRnNCPh8/xbgiQeuJjUn/+E0giTH4IpnsHhWpVSu6b2b7zTFdIiwhg7QNTcYsSTy0/wsYsuVtNfk0Tr6zJ5sVL2g/w9xTUeuV6NTnc5NdYSArVMyQ+iI+uG80PB0v55Vill7NP1fzZf7Alj6e/PwrAN/tKkCS4YuyZzcy7++w+3Dg5GYUg/CZdJnvppZdeOuPZFetYvFMu+RkeH8OHV8/vUajy74HxYRkMC05hX10uCgRu63MugqAgLugh4niIFXsyWV66hwn9krAYcz1iFcDO2p1clXQVE8JGeoSqkxysz/fOkIxy8v26w1w3dxxzhvRn6b7D2F1uBGDu0BZXVn1jk0esAvjsh91cMHUgSbFdc7ecDuwOFw0mKxkuI9W7ZIeN0MqZHRkUQGRQAJJ0AVbnLqotX6NRxpBlnYtCqMTob0OpkLhzz5s80n++R6w6iVahwiaYeOLwSgJUOm5Jm02Un2939S8HTpBZLDuqREni9Z+2sfaZm3C5BLbuzCU5MZyrF03yua1araJ6dCDWGHlM8rWrlJvMFsICfl/3EpcnzmBm1GjckpvITsrRSq0V/O3Yq1TZa0gPSOHRfnd6hCub08WT365mV34Jg2Ij+cuFZ2Gqq+XTwoMcaaplaEQ8dw6c6MmRkiSJcD8RbZBAXUUJARoFgYHeFQCRQQE8sXCGz2M5FeckZnBOYgaiJHHZAx9gbpLHU1v25rJ623HOmdQ+b83NKlIjZOehSinSN34ZII8Zr+szDn+lhr3VRSzfmgUNLRN3J7tm3rv6J1bnyTEjP2Qf57sFi3pcLtsVNAoVzw25GbPTip9Ki1Lodb//nugVrHr5TXhnU67H6VBtdrB0dzEPzOrZje3vgQdm9eXi4bHYnaKnmx3A3sI6Ln1rm+e13jY11StPSq0U+HBrHumRgVwzPslLaEgJDyBAq/IqqdMoBYz+agw6Nd/cNoFVR8ox+qmZPdDb3dI2N6AnOU9krYK1fwWFCmb9DRJ9t+RtS9sufn0iAsiuNBOoVfHoue0DWeeNiPME7ANMz4jg5sV7PMtf7CrijUXDOVBcj80pEm3UccXYRK58bwe5VfLgcmtONWvum+LTdaNVKVEIeLngdCol101M5rqJnXeEmzs8lmd/PIq5VcOB1UcrTilYvb85j5fXZOGnVvL8vMHdchb1FINOfcrumZ/vLGRTtiz8VJrsPP39EZbeIn+u23NreG5FJgAl9VZ++fBpaFrJTY7ncKKC6lLyaqx8fWvz96CpFk6KVQAbX4AhCyG0Z3loHaFUCNhd3gPitgLmSYbGt++y599KBJqQFsaEtDC25dRw08e7MdldjEgM5pKR8vevbTfOnXm1Z1ywAnrLq3vppZffBTanyyNWAewtKmVvYSljk7uXT/N7Qa1Q8crwG8gxl2NQ+xHt1yIYfPjLbl7+bhMAH6zZzZM3e5evDQ+op6D2CQy6CQT7z/J6rJ+hzftRpSIsWBZKBsdG8fVNi9hdUEx6RBjDE1rKAUUJr8xSfHSv7QqVlZU0NDSgVquJjY1Fre6aM/d4XgX3/n0ZdY1NJMWGEBToR4PJSkJMMJed5y3KCYJAYshfSQz5KwCDYkDvt5yvi7fIrwWJJYWbuWvUOF7eKWdOTYhPID7Yn2t2vI1DlMeuOeZyFo/zXf6qU6vaLQuCwPnnjuT8czvORwW44o7pLH5nsWfZKrnZV1DKjAEdu52dopsHt3/P6pIsUgJD+ffEuSQEnN68N1+EaU9dnfJpwTKq7LLzP8ucyw9la1gQfwEA72zcyfcH5PFZeYMJP0EiNFbB26UHAdhSLU/K3jd4CgCNjY00NspxDKIoUlJSQkbG6W+IoBAEHA7v8Zjd4bshV7+4GFqv6a/1zj1dmDKChSkj6OvczYtrNiEBV48dTlq4LObuLG3Jj3OIbvZXlJ1RweokAepf53brpZeu0HsX8DulbQczg99/30dltrt4a0MODVYnl41OoF90+9ya9ZmVXmLR+uNV/G3uIJ747jB2l4jN6WbJbjnUs6i2yatDWHigls9uHMNTy49wrKwRo5+av1w40FMyFKzXsHC0b0vsg7MyuP2zvThcIv2iDV6CUJcwVcCSq8All+Hx+UK4LxM0p+7Stnibdxe/PhEBbHhwKiF6jc/OdW1JbdOdT6NSMLVvBOsemEphTRMZ0QbUSsEjVgHYnCJf7iqivslJ/xgDl7V6X+qbHNw8JZW3N+YiShL3z0gnIbRr3eaK66yezownSQlrP3uXVWHilTVZiCJcNDSGv/54FEkCk83FHZ/tZf+TM9t1UPy1VDTa+OVYJVFGLdMzutYAoe1raXK42ZBVxeGSBq+wVYBYazbHpERZrGpmT0Edl7+znQCtioX9tUyX2gSqnvy+nGZumJTCmmOV1FocGHQqbpniWxRLiwgkUKfCZJMHTAFapae7YWvGpYay/bGzPBlvJ911Q+ODvELQfQlgvwaz3cXDXx/kYHE9Y5NDeebigWh9WOd76aWXXv4TqJQK/NVqmpwt7m6D7r8vsqHOUcShum9RCVqGhy6kr6F9yPW6Qy1NYURJ4sRxiXkj5rGxeiOD9fn01e2k0ryZSvPHpIa9SYj/bM/648MzeHzApby/dz1V+VYSK+J5/LaWx9PCQz032q0JMfpz5ZxRLF6+C4DzpgwgNb57HSIbGxuprJRdSXa7nZKSEpKSuuag//dnG6lrlJ35+SW1XHvxWM6Z3J+oMAPqLlyLkgO8BYIAlY67Ro1jVmofzA47QyKj2V6T6RGrAHLN5by/aReldSbOHpDG2FR5fOYSRaLiA5k4LInN+/IJ0Gl4YuHZXX4fDhRUoHCC2Fx1KAAJoe2v2T8fy+brfUeICNQTnxLI94Wyi/pofQVP7lnFB1MWdvk5u4rkPALOg6AegqDuWndHu+id52p12fhx7SEaGm3kW70b2JTVN1Jh8B7Prchdw8igJQTpdIQrFwEt5ZhSW5X0NHLTggk8++ZK3KJEWkI4M8b5Nh8kRE1lf9m/MCqbcEsCTRrfJczXTxjJxUP74xJFIgJb7geGRkZ5GgWoFAoGRZzexl+55TU8/flqas1WFk4awqKpp85f6+U/R6/DqhcvNmdXszWnmkGxRs4ZdPq6wDx5QX9u+Gg3eTUWpqaHc9VvWK52urhl8R42n5DdKt/sLWHVvZOJadOJMTXCW3xJDdfz0s/H25X6AR7nS2sGxwWx7LYJ3T62Gf0j2fzwNCob7fSJDOj+TbGpzFt8sDWAtbZLgpWvLn7dKfdMiwjg4dkZ/HP1cdRKBc/NHYSfRomfxo9oY8v7OywhyFNeqVEpeG1tS/17fZOTW6em8vcVmby5QR6UXjwshmcuGuRTwOiI3fm1Xs4sjVJo9121OtwsencHVc0lZltyqr1mUC0ONzan+7QKVuUNNs5/bTPVZvk575iW1iWH4iUj4vhsRyEl9VbUSoE+kQFc/f5OaB7sGf1UNFjlgeYSxTkkOY+jw46NlhuWrTnyDOCaY7Bt2LVEHv1AfmDQAogc4OtpfVJncfDCqkwqGu0sGBnH7IG+zy9Ot0iUUccv903hRJWZlDA9oR3kllU02jxiFYDZ7iav2uJV9ngSvVbV7rtw46QUpGZhbnRSCNdOOL3npRdXHefHg2UAFNUWkxDiz52/w+6nvfTSy+8bSZLA+hWSuwhBNxNB3bMOp21RKRQ8f/FsHv1uFTani1smjaZ/9Jl3CJ9OrO4GlhXcg9Ut3+QXNe3l0qQ3262XHBHC/txSz3J8qIFkUxhJmiTs6j/Tejqm0bbJS7ACmB0znNkx3b+pve2yyZw/dSAul0hKN8UqAIfD0elyZ7SdmJKA+KiuO4zOjx3FzppsNlUdJUoXxH0ZFwLQN7TldfQNjCVQ5YfJZQUgyBXEiys2A/DlzoMsvmkB/WIjuHL1l+ysLEapEnjqlrNZ2HcI6m6Unu48XIBfpYQtFCQFDA2NpG+Ut6B2sKSce5b+iNg8KIs16aHVUKzW1tTl5+sqkn0DUt2tgEu+DQ1+G0E78ZTbzYmZxXFTDg7RiVFtYOs3FnbkrUZSgE5QojQocIsifjobgTE7qXPa0ShicYgq1AoXN2X8iN1tpcICdYodxPi9iV3+CIiM7J64c7Sskjc27UAhCNwxZSx9Inx/T602J9PG9GFwegzV9Rb6Jkeg0/iemK605ZBpj0QtuHFLCtSKSp/rAYTo299rvDrrPF7cvoUqi4VL+g9kQPjpFawe+OBHT+fEF5ZtoH9CJMNSet7NsZczS69g1YuHtZkVXP/Rbs/N918vGsiVp6k8JiVczqdxucUO83b+U9ic8k1uTJBfhwHIoiixJadFYDLZXRwsrvcSrFYfreDtjblEG3XoNUoGxhq5a3ofpv9zg8999ovpWmexrhIRqKPR6uTq93fSYHVx/cRk5nfVaRWeAeH9oKq5q1r8GAjsOCiyNZePSeCbfcXk1zThp1Zy74yOOxZVNNoQJclLiAK4dWoqN01OQSHQYbvvp84fwPy3tuJ0Szhc3oOwDVmVLBgZ5xGrAL7ZV8rNU1K73MENICPK4FVOODwxuF3WVXmjzSNWgeyq6hsZyPEKEwBzh8V2yVnWHX7JrPCIVQBf7i7qkmAVYdCx4p5JHC5uIDbYj3lvbPU8JgFRRh33np3Al7uL2FyWyGYSUeMkngqK8B4ciBL8FHs3106+AUQnxHSv3e9dX+zziLTrj1fyzW0TGNLG0bQxq4rbPt2L2e7i/MHRvLpwWKdB8eGBWqIMOk9Af4heQ3xI19x0AAqF0KF7y+Z0s3hbASa7iwUj43yWn56KolrvwXFR3ekfLPfSSy9/fCTT89D0vvx/y/sQuhRBfXpC12f0S2NGvzTcoujJj/m94HK5cLlcaDQaFB0cW40txyNWAVTZsrC7zWiVLROIO6s/Im3Meq5M0XBo52hGp/Zj5qAkSkrksiOFOwVR1VIa6d9Fl0xXSYgOIce0iS/zFqNS6JgUeQcRuq51dwwICEChUCA2Rz8YjV1vhnT9vHE8+I9vsdqdxEQYmTfDd9i7KEkUW+oxanQYNS3jM7VCxXNDr8IlulEpfItL4Tojz6VfxtL8zfgJGtZtacQvtQal3omzWseO3GIK3fXsrJSrC9ySxMuHNnNl/+6Jf+mJEfy8NRN9uTxAmz6+fafio2WVHrEKoLHCiTFRR4PDhgBc2WdEt56zK0jWZc1iFYALyfpNlwSrwUH9eHno05TZKonXxjD1w3eRVPJ4x4bIJX0HkJQcSF3Aiyg18vc7paGCz46Nwai2E6S1evblEGuIjNWgEuNQKpVotV13SZpsdq5b/DX1VnkctbewlNV3XdeufPPDb7bz9tItKASBu6+axiWzOh8DhunSEFDibBYPIvy6V6Jo0Or4y5SzfD5W0tjIV4cPo9douGLIEHRdLJH12kdNg9dyaU1jr2DVy29Gr2D1K1h9tNLLKbL6aMVpE6xOciqxyuZ089rabIpqrcwZEsPZ/U+vot6W8gYbC97aRmFtE0Y/NR9dN9pnWZBCIdA/2sCRUrlGXKNU0CeyJdCwtN7qKcmj+cb5hflDUCkEUsP15DSXs/lrlAyMMZIaoefRc09fh5+T3PTxHnKr5ed66KsD9IsO7FqnR7UOrlsB+z4BhRqGXwldHLiGB2r56e5JZFeYiQ7SERGo87neK2uyeGVNtnyck1N4rM3rV56ig93eojqcbt825/omJwpBQBC88yJUPl7DkdIGKk12RiWFENDKcVPeYOPZH4/hp1YSoFUxLjWUP5/fftAaE6QjMdSfguYA/NggP764aSxbcqrx1yiZ1vf0z05HGXSdLneGQadmfJo8W9bW9aVTKdlTWM+xMpPnb07U7cQqmoPKRyQGQ1TnOWAdcbikZXAgSnC0TP4tvbMpF3+NLHQ+9s0hT4bbDwfLOH9wdIdOLACdWsknN4zhX79k4xZF7pjWp/Oue7nroewgJE2EWN+D5bWZFewrrGfd8SrPMX++s5BV90wmRN95B6S2zBkaw9rj8nlVqRA4f3DXROBeeumlFy/sv7RacIB9M5wmweokpxKrHA4HVVVVcsBzeHi3bop7gtlsprCwEFEU0el0JCcno/ThyAnSxKMWdDgl+YbboI5Go2hxeWc3rmNn9UcA6ILg0rkRnBt3PXa7HUEQkCQJlf1K1GoVKr8iDLqJhAdcflpfS6OjjFUlf0VsFjZ+KHqUa9KWoBBO7TDS6XSkpKRgMplQq9UEBXW9dH3EgAS+euV6yqobSY4LxV/X/hrmcLu5ceMSNlfkoVWqeHnchcyK854Q60isOkmIS8flxjGU2MysT1mHziCPQ9WhDhyGBtQK73Gor/1JkojJvh0QCNSO9Zq8NJvNjEwzcOHkPuSXmxnWL4Gr5oxpt4/hCTFolEpPMPyEuEQemjWZXVWFJAeGMDj0DFyDFW3GS8qu37eEaUMI0zbnrCm9x8ABAVo2lO5i2MAWMTbS2EiIU6C2yUB1UwBh/nJXa50yGr0mHqWi+/lLpQ2NHrEKoMpsodJk5siRUjbsOUFiTAjnTOjHW0vkLDO3JPHKR+uYOT4DY2DHzxehS+fc2Kc52rACf1Uo48Kv73BdSZKor6/H7XZjNBp9ZrS5RJElufspNNXz9e5Mak3yMW8uKODDefO6/brPG5nB11sPAxAa6M+Yvl3rQtjLfwYJEOmac+rMFcSePnoFq19Barh3GVdam2yh34LHlh1i2T55xuuHg6UsuXkcI5M67rLxa/lgSx6FzS6IBquTV9Zk8eG1o32u++7VI/n7ikwarE6uHp/klb1U1mD1cv3UWhzkVZvxU6v49IaxvLY2G7tL5MZJKfSNCmy3741ZVTzz41FECR6encGMHgh1kiRR0MrRIUqyw6NLghWAXzCMv7Pbz0tziHRbt0xrKk02j1gF8PbGXC4fnUCSj3yojkjqpMxQqRAI1mt4eHYGz6/MRJJkUUyvVfLI1wexOt3cMDGFXfm1/OUHOc8gNVzPXWf1YXtuDWkRgezIrWFnvhzCbXG4qTE78PPRxU2rUvLFTWN5a4OckXXjpBSC9ZozKkac1S+S26el8uWuYqKMWv65oP0sqcXuYl9hPVFGLWkR7b9jAE9fOIBbFu9BlOQGAH2jAj2Zaq1ZMCKOEUnBVJrs1JodNNpcXDQspl1ny+4wLjWUnw7JeVEalYKkUH+ueHeHpyHB3sL6duHqbTO4fJEWEcBrl3XB7bX/M/j2Vvn/ChVc+S0ke3cjWra3mPuWHGi3aZXJzoGi+u6F6TuauNC8hIhhEocMkxjVP41hCWc+7LWXXnr5A6JKAXdBq+XT2+ziVIiiSF5eHs7mrCuz2UyfPn18Ckini/Lyco+ryGazUVdXR1hY+1KlAHU458c/x96aL1ArdIwLv8FL7Kh3eF/j6h0lFDfV4qfUkJSURF1dHUqlkoiI53y+nh/LfmRD1QaC1EFcl3wdUbqoduucikZnhUesAmhy1+EUrV4usM7Q6XTodF2fqGpNSJCekKCOx08rizLZXJEHgN3t4q97V7cTrE6FRqNhV0Mlz+buITjERGtZTAhwMCO+D2fHpbGm+ARapYq/jJnB3pxivtx0EKO/jlvOGUuN7V7qravkY/a/AJNiCrX2ApICxmIvDsHtdnPBBNlVFR4e7nMCPD0ijPevnMt3B48RERjAjRNGoVOruFB/ekpofSEE3IXkLgLHXtCMQNDf1m6d6rI6CjLLSO4fS0ik7zH5wglD+HyrPP6IDAxga20p2bVNDMhQolHJYyGrTcPT4y+g2N6EJA0nWr8ZhUIgyXh9j8QqgPjgIKINgZQ1yhOXiSFB5ORW8fSbKzzrlFTUe20jShJ2p++w9dYkB04gOfDUMSclJSXU18vPUV1dTVpaGiqV9y39Y7t+4us8OXQePdCkAbeCTQUF2F0utKquSwAOh4MbpgwkPcKIAwUzh/UlzPD76jbZize9JYG9eLh2QjJVZjtbT9QwMNbAg/+BLn67Clq6domSnC1zJgWrtuVnig7K0Sx2F09+d4Rd+bUMSwiWnSat6BdtIDlMT16zuykp1J9zX92MW5Q4f3A0r102rMNSN5PNyS2f7PHcnN/x2V62PDKdsA5yezp7LbMHRPHjITkzJyxAe0bfu67gcIm8vyWPE5Wmdo+5uxkKOS0jginp4WzIqmr32PhUOez0limpLBgZj0sUCQ/QcvY/N3jcbWszK9EoFQwWcnhS/TFH6xK554trkZoV+0iD9/u96UQ1d3+xj3evHuX199fXn+CzHYVEGnS8MH9wt0rQfg0PzsrgwVktlur1xyt5/LvDOFwit01N4+Nt+Z7XatCpeOvKEYxL9R7cz+wfxfoHppFVYWJgrJEXVmV6PR6gVXLb1FRum3b6c5b+uWAofSJyqDTZmDs8DodL9IhVACcqzQT7t8yqDYw1tOuG+as4uKTl/6ILjnzTTrBadaS8/XbN7rLELgb3e/hyEeSsZRwwzj8MJm7v0WH/Xqkx29E2uxF76aWXM4tgfA6p8WlwFyPozkPQTf9Nn9/lcnnEqpPLDocDP78z11GrozFTW/LNFfzl8AYqbH6cFzuS2Rrvsp6kgHHsrvkUtyRnPxU0hTFn/T9RIPBg//O4NGlsh/s+0nCEr4q/AqDKXsVbOW/x5IAnu/1aInR9MKijaXTK47M4/2FdFqvOFJVWM+8d30F2g3eeqti2uUoXiIyM5MfdP+OSROwONRpNy2TT8OBUVAoF70ybS3mTiQC1lvoGK/P/tRhbs+hRaTrMohmrPNvUNn3PPut+HJKaow0/MVi8hRBaHIVVVVUolUovAdNmd/K3t3/mUFYJA/vEcMNNU9uVtZ0JBEUAQvAbXn/78JvtLFm5j6BAP66cOoi37/iY2sQgXOF64mNDef3phe1ExEcWTOf8sf2pNTUxMi2e2W9/iNWu5YdtoxnT7ziRAQYuiLuTjLDW2aEzfvXx+2vULL72Ej7YuheFADdMGMWylfu91tlRWUJTPzVOmwt9mcQlE4cQEeJ7YrS7nHRXncTlcmGxWNqVvv5cfLxlQQFoRLAqiDMYuiVWuVwucnNzcblcDIzwR6/XExV8el7L7wFREql3NmJQBaBS9I7Pfq/0fjK/AqVC4NFzTn+ZWncYnhBMUa1cly0IdNuR4BYl6pschOg1XRrsXD8xmdVHy8mpshCq13D/TN+ZAq+uzebnoxXQLHz85fujvHjJEErrrWSWN5IRZeCrW8axZHcxaqXAC6uOe1oX/3CwjMtHJ3jKstpSZ3F6OUnsLpFqs73bghXAKwuHMi41lAarkwuHxvRoH6eTP31ziKV75NnN1tlQE9NCvcKyu8rZ/SO9BKvwAC03Tk7m+oktWQYny7YampweAYfmrKkYg5r3Nf8gTGhktXuER6zCR7kcwI7cWq/lzdnVvLBSvmgW11m554v9fH/nqbMKTjc2p5vbP92Lpfl78/T3R7zC4httLq58byeZf53dbhYyIdTf0zXxoqGxLN9fikuUUAjw4iVDT69I1Apdm3yzKpMdo5+aBqt8E6QQ8GpOsGhMIv6a03hKD24pb94hZpBVP4hxlSYvN1pKeABQ4VlODPUn2F/DLVNSmh+Tv1d3fL6Xvc1i+muXD8PQNrPM5YCctS3LTdVQsgf6eof4/rfy8FcH+XJ3ERqlgufnD+LiYd3sStpLL710C0ERghD0r//Y86tUKtRqtUe0UiqVaDTdK5G2u1zYXC6MXXQKRUVFUVBQgCiK+Pn5ERzsezz41yNLOGEuQiGIfJq/gVR9DLNihmK1WnG5XIT4JzM/8f/IN2+jzqHhkf2HABCReOnYCuYljOqw5K3aUd3pclfRKPXMT3yNYw0rUQk6BgSd16P9nC7sbheXr/2EPJM8xtEqlNhFN/4aNxelJlBurSXKr+sTngqFggiDEerKaTT54XYrGBYZxo19pzA+XJ5oEwSBaL2cKbqjpNAjVgEczGtgEQpojr6XJBClk2MXiSZdISFW7/uTpibvTMj3l21n9VZ5Eq68+jiRoYHcsWhKj96fX8P+zGJP+VxdYxMvfrYBd6QeR3NubUFlPXc8s5TPXrym3bYDE1rGXxcP6s8bW3dSXBWG2RzHN9ctItZ4erNvTxIXZOTxc6d5loekt4i+Li0UqZrkOiutgC1FyVXz25dj9hRBENBoNDgcDkRJYkduBYeq7Zw7agBGfcu5IiUwlAO1LU0T+hjDiIww8uepUz1/O1JVwd0//0SlxcxlAwbz6IT2n//J88JJLBYLoih2mJH334TZaeGZY/8iz1JIsNrIY/3uIkH/x8jl6nVY9fK74u9zBxNl1FFca+WCIdGMTu76BTOnysyV7+6gtMHGwFgDn1w/hiD/zgdU4YFaVtw9mdJ6KxEGbYc3yMfLvR1Cy/YWkx4ZwL/WZGNxuAnQqvjkhjHcOjWVjVlVuNtkLZ1c+nxnISsOl5MSpueh2X3x16iIDfZjVFIwu/LlOvXBcUZSwno286ZWKrjiNOeO/Rpad0IUJbhybALf7S9l84katuRs4e9zB3HpqK7XjV86Mp4t2dWsOlpOXLAf7141ymeJJYDBT0WfiACyK+Uaf4NOxTPnJBL2nZydNEiRB60qzianhzM03sgjXx/yiD9tyxyL24Rml9RbkSSpyzPBpwuL3eURqwAvseokLlGiymxvF3Dfmsnp4Sy7bTy78moZEh/UJUdeUW0T723OQ6kQuHlyChHdyNNqjSDAWRnhHChuICMqkB8PebubnvzuCLMGRHU7N6pDzn4ammpYmqPiwcZL4DDojm9myc3jPKWOd5/Vhwark/2F9YxODuFP5/VrJ2S+vCbL873ekFXFq2uy22edqTQQkgq1zU0AFGoITTs9r+M/zPbcGr7cXQSAwy3y2LLDXDgkttNw/F566eW/G4VCQXJyMpWVlZ4Mq+6UA/544jj3r16J3e1iQb+BPH/WrFNuo9fr6du3ryd0vUOXuquIFEM1ggAmh5a/7PuJWDEI6uVrv1arJSUlhdDQRPZWfsSYoFz2NiTglFSAhAS4RQfbqz+g2p5Don40Q0PmAzDQMJAAVQBml7yvcaHjuvya2+KvCmFE6OnNxuoppZYGj1gFYBfd3Dl4MD9UrGNV1UY21+7kleF3kBLQ9aiDx0ZMI6ehhuP11Qw19OWtsXPRq31fvzPiwtGpVR7RKiEsnXDdg1RZXwIE6uzDcdEyOZkSNhx/U5CXE6etu6+8urHd8n9ifFZdZ/ZatksSQpC3Q7ussoFTce/UCQyOiaK4oZ6z0/t0SazaW5fFxsr9ROpCmB8/FXUPHTaGcD8GT02ipsZCSkQI3xe1RHo43SJ3LP6Or+64okf79kVCQgIlJSX8a+UeNhyXY2E+23SQzx+4nAA/eeL9tQkX88TulVTZLFyWOozL0tpHQdy3egU5dfL3+u19uxkbG8+0JO9w/pPnEqm5ykOtVv8hxCqAn8rXkmcpBKDO2cBnhd/wSL87/tOHdVroFax6+V3hp1H22OX1/IpMShvkEL7DJY28synXq4SqIzQqxSmzlGrM3m2ERQleX5/jEQ3MdhcfbsmjX7SB51Z4l1nNHhDFuJRQ1hyt4NFl8szexqwqTDYXLy0YglIh8PF1Y1i2rxhRlJg7PA6NqnsnzyOlDdicbobGB58yvPxUNNqcbDheRYhew4QOXGGtKam3cqLSTL/owHaB6wNiDJ4OboIgZxI1NjurJAkWby/olmClUSl488oRXeo2KQgCn9wwhld/ycbqcHP9pGQ5z+vAJMjfxHnKHdT6LWd1xNX0iQriwVl90amVhAVoeWV1Nia7kxGJwbhFyfOeTukbTqheQ41F/j5EBGrp86cVRARq+fei4UQb/Sipb6JvlOGMlkqFBmiZ2T/S4/obFGskUKdia06NZx2tSuFTrNp6opp3NuUSoFPz0Ky+LNldxGc7CjH6qfn35cM7dALSLJQteGsbZc2/s3XHK1l1z2Sf7rTOEEWJRe/s8HRWNNlcTE4PY2NWi8DpcIss3V3EzR108es2fkFw6ScsfWsbNMoDGptTZPn+Uo9gpVMr+dvFgzrdTVWrbo2AV/dGLxYthZWPgr1RzoYL+2MIVm07dLpEEVGSUHQxDLOXXnr570Sj0RAX1zM35aNrf8bulq/9S44dZk56BhPiTz25plQqOxXGREkkQFPjmRQM1NjJd5v5JGs3V0TI4z+73U5DQwPVrvuQ7Ou5Lg6mhGTxUu4s7smYjVqhZFPFmxyo+xqAIstudEoDGcaZhGpDebL/k+yt20uQJohRwaM6PBZfuEQXuZZc9Co9sX6/3unQ4Cih3JpJmC6FUO2pG6BU2U5gczcQ7TcQlaLFcR/pH0iI1p9auzwJF6TxI8ea2yzfgcVtY3X5bm5Om9PlY4sLMLJqzvW4RNFnwxuvdcOCePP2uSzdfBBDc4ZVgFaN9cRkXC4XUbgRdatxamtJChhHunEakkFCpdHw/r59lFqtnK/RMDs83LPPmRMy+GXbcfl6pJPIHZTN5DWPMsCYwN+HXo1WKMUtNqHXDEIQzpxAMWpgItHhBsqqZAHt3En92fndPiokSR4IA0nRvt2Cn23Yx4bDuaRFh3Hd7KFsd3/BCU6QUxTPvX73EqzpuOrkeGMhjx18C3dzSWeptZr7MxZ2+/gLa+q5+r2vsDpkN2VIdAChen9qLM0TthJkllZRVtlAdETXO1Z2hk6nIyEpiY1Zy1uOo6qefbmlTBogf89j9Ubem3Jpp/upbuO6a7tMs4AdHx9PdXU1CoWC6OiOG/v8t+ESvStXnKKzw3V7+c/SK1j9D2NvcyNlc3a/Dr8jgvzbd6zQtLlJD9Sp+Xxnodffbp6SwiOzMxAEgcOl3jMqazMreH39Ca6bkIyfRsmiMT1zRj2/MpM31stOjml9w3n36lE9Fq0abU4u+vcWcptL6W6ektKpgLgjt4ZrPtiF1enG6Kdmyc3jvBxPLy0Ywt9+OkZpvY25w2Ox2F18vbfE83iovmclix2JVZIkUd5ow6BTo9eqiDToeLatALFoKez5CFxWrhx6BVcGhHs97BbhYHN3uH/9ko3DLfLwbHngG23047s7JvDzkQrKG228vTEXgNIGG7d/tpdaiwObUyQ+xI+vbxnfY/dRaw6XNFBc18To5FAvt9Hri4az4nA5dpfIuYOi8Neo+HRHAf+3Nht/jYpXLm0/+1RU28R1H+3y/DZ259dQ1iALLnVNTu5feoBtj/puIwyQV23xiFUAuVUWyhts3c7xqjbbPWIVQKXJzquXDWNXXi3WVr/bfYX1Heyh+6zLrKS43opB532ZiDJ27zNaOCqen4+U43RLaJQKFoyK971iaCosWuL7sf8i7C43/1ydxfFyE9P6RrBoTAKT08PZ2Fyae//Mvl6/xx8OlvLVnmKijToenp1xSpdrL7308sdGkiTsbu8GGjZX9yMBOkIpKHC1yl2SJAVapfd5XhSqaLCt9yyn+lfzzaQ5xAXKpU1Vtmyv9VccXscJTTznj+pHmDaMmVEzu31cTtHJi8dfJMucBcD8uPmcF93zUsAKaybfFt6HU7KhQMk5cX8hOaBjx9femi/YWvU2AOHaPsxNfAV1czC3v0rDx1Mv4+VDG5GQuGvgJL4uXeW1fZCmZ07/jsQql+iiwdmAUW1EpVAxLCWWYSneIl5qSh8aGhpQKpUMDn7Iyx0lCALvHDnCh0eOALAyN5cP5s5lUlISABOHp/LmUws5nF3K4dAs1pvkAPNDDQWsKbqPRLX8+oy6s+gT/s6vFq0kSWLnoQJcLpExQ5I810FjoB/vPbOIzXtyCAr0Y9LINKRbZ/P311ey/VABcZFB/P2hi9rtb8WeTJ7/Wv6Obj9eSFngTuqCTgBQZC3iq+KvuDHlxg6P52B9jkesAthfn93hup1xoKjMI1YB7M4rZvGNl3LJG5+BIAtWqkaRHfvzuWhm+wZA3cXhcvHjYVloDArwo87UEgsTbuxeEPoVg4bw6i45LzQmILCdu+okBoMBg+HMlFf+lpQ3mnj5ly2Y7HauGjOcmTFT2FK9i2pHLTqFlnlxLecbSXKD5XUkx34EzQjQ33JGhdvTTa/Dqpc/DLdNTWVXfi1NDjcRgVquHpd02vZ934x0DhTVe9xBIXoN/1wwhL+vzORwSSODYo3cdVYfjleYyK9pUfT7Rxs8F9yxKaEohGxP+VZdk5MXVh5nf2E9b181skfH1eRwecQqgHXHq9hX2POg+k1Z1R6xCuCjrfmdClbvbs7D2tzZrcHq5KNt+V4OlSB/DS/Mb7mgudwiewvrWXWknOQwPX+98PR1bnG4RG74eDcbs6rwUyt5fdFw313d1H4w9hZozlF684ejOFwi109MJilMz47cGq/Vd+Z551jFBftz3cRkluwq8vp7ZaMdV/OHW1Rr5dMdhV6ZTT3hsx2F/OnbQ0gSRBt1fHv7BCKbRTCVUsEFQ2S7fpPDxac7ChAQWPfANHQ+uhsCnKgyewm5J8Wqk5wqVyw+2J8gfzX1zVlTkQYt4YHdFx1D9Bpig/woqZcHJoFaFWkRAVwxJpF3Nud51ksM636gfWWjjSeXH6G80cb8EXEsGpPIa79k89Jq+aZBpYDBsUbKGm1MSQ/n6vHyeaKkzsrdX+yjxuJgwch4bp3q29k1qU84P9w5iYPF9QyND6JP5B8nrNMXz684zvtb5M9k/fEqgvzVfHDNKI6UNlDRaOPVX06weFsBFw6NweZ08/6WfM+25Q02Puig62ovvfTyv4EgCNw7ZjzPb90EwJiYOCYlnJ7xmUJQsDB+IZ8WfoqERJVZT5J/KrcOmUxdWQVut5ugoCCCDEYUZh2i1Oz4RkWEX4u7O04/nFLrQc/y2h0iH+avpLHJxuVTutCF1gdHGo94xCqAb0u+5dyoc3tconasYQXO5uMXcXO47vtOBatdNZ94/l9lzybfvIM+hpa8n37Bkbw9+RLPcqT/hVTb68mzlDM6pB8Xx03u0XH6ospexQuZL1DtqCZcG85DfR8iTNveza3RaAhvdk01NTVRV1eHSqUiLCwMpVLJzuKWjo8SsKukxCNYAQxKj2FQegxPHzoBzXNiasFFgupnzzoNtl8w23cRqPt1OUxPvvYjq7fJmaZjBify0sNzUTaLdcEGfy6YJo+FHQ4HjY2N3H7lBB41nNPh/o4VVXot11gbUbRKpbC6rZ0eT1qgt/uxT2AHk2mnoG9UOCqFAldzh87+MREMjI1kpBjCkdpqFC7Q1knE9MBdtbeolFfWyvle90yfwNC4aG7+bBmlul0Ygi1Ejg0h6FAKFqub62aMIiNOHsNvrDjOv47+DKKKe/rPYlK0byHq3jETGBUTR6XFwpTEJEL9fpumSP8pbvr0W7Iq5cqErTmF/HDbVbw49AmKmkqJYTf+tlsRq9TkKW6lwbKdoRrZRSo5NiEIWtBf/x9+BV1HkgSkLgpRXV3vP0mvYPU/zJiUUNY/MJX8mib6RgZi9OGK6inDEoLZ/Mh0Khps6LVKIg1+KBUCP/QJx+Z0ewSCF+YN5u4v9lFUZ2XOkBjmDGmp/x+bEsr714zi7Y25XqVbvrredRWlQkCjVOBwt4gQHYkVXSFY7/2ehZzCHaHXeD9XYAdlcFaHm0abk4hALS9fOrTHx2d3uXl9XQ6FtU3MHhjFrAEtAZU/Hir1uD6sTjdPLj/iW7Bqpr7JwYx/bqC+OfR75ZFy1tw3haEJ3rlVQ+KCfG4/o38kUau1lDfKok+AVuXZF4BW/etnLt7dnMvJZoplDTa+P1DKDZO8L9ROt8hl7+zgQJHsRnp5TRZr7puC0a/9939gjNFLcEoK80elUHCiOeerI5HmJEZ/NYuvG8Nra7NRKQXum5He4fftl2MVbD5RzYAYI/NHeA+kVEoFi68fzUs/Z2F3ubltWhphAVrun9WXOquTXfm1jEgI5p6zui/43fPlfs/va19hPSlhASze3tIO3iVCfZOTXX862/M3i93F7Fc2eroWPr8yk5ggHRcO9V3C0TcqsMPstD8ah0q8XW4Hixu4cGgsg+OCmP7Seo/A/Xor4bxl28Z2f+ull17+97hl+GjOTkql0W5nUEQk6m7kX52KsyLPYnjwcJpcVnSCgVA/2RkUaQxGkiRPPk1q2L8pqH0CCRdxQY+gUbWUAo0KvRKd0sCqwxvZvFtFYb48tth6rKDHgpVGoWm3/GvylHRKb4HAT9m5YKBW+OEUWyZQNQrfN+/1NiuSBBF+wfzfiHt6fHzlTSZeP7oFh9vNdRmjSTe2uNeXly73BNZX2av4vvR7rk2+tsN9NTY2UljYUrFgtVpJSkpiSHQ0R6taxsxDonw3ibk4fixryw7iEtyILgWgBFom5ATh1zUkqqo1e8QqgB0HC8gtqqZPoveY0+FwcCwzi6VrjlFcaWbskERuucx3h88x6Ql8tHYPAKIKgux9cSpqsIpWNAoNMyM7d/kNC+7DwxmLWFu5lyhdCNen+HbzuSWR70u2UGarZlLYEAYGeY8p06PC+Nfl5/PlzkOE6P24d6bcWOjvd13I82+soqrWzHnnDWT00O6JziabnZs//RaTXR4z3/LZt3xyzSUUKveSkHwyDqKEGen9uKHvIs92WY0lPHrgAxDkwfBduxbz/fS7iQvwPTaf2IVS4z8CDrfbI1bR7FrNrqohLjiFPv46pKqnPN/5cPtj5JkjoJWXQXIe+a8KchARELt4xF1d7z9Jr2D1P06EQXdayrB8oVMp+efqLFYfrSA5TM/bV40kOUzvdcP+3f5SbE6REYnB3D4tDUEQEEWJQyUNaNUKpvaNIDRAw4X/t8XjtMqI7rktVatS8re5g3h02UGcbombJ6cwMLbnNeXjU8O4bWoqH27NJ9hfw78Wdi4uPTg7g8OljZyoNDMkPsin4LEpu4pbFu/B4nAzOT2cd68a2e2MrpM8tfwIn++UnU3f7i/hsxvGMi41FABnm6D7uiYHl761jX7RBh45J6OdsHLn5/u8BKYqk52cKjPnD47BZHOxNrOSvpGB3HVWH5/HEqzXeIWd11udnq53wxKCuOo0OPzaik4GHyJUXrXFI1adfB0PLj3g07XX5HAxPCGIg8UNVJsd5Fc3YfRT8exFAxkUZ/RkOXXGoDgj98/sy7J9xazLrCI+xB+tyvu9XX20ghs/3u1Zrm9ytBPaUsIDuHlKCk8tP8Jjyw5x5/Q+nDc4mhcv+XUW86wK78DTE5Um/NsIqzUWb2fZgeJ6j1h1kv1F9R0KVr9nRFFOIfm1WXYnGZcS6mkIAfBLZgWXjU4gLSKAsnpbp9uOb/5t9tJLL72khZy584GtQcEjL64hr7iacUOTeebuC9BqVB6ByGy38+wKB5nlNzM+NZGHZkwCQBIt4DoOymgGB1/EQVcC+XkbPPvtE3PqHM+O6G/oz+SwyWys3ohGoeHapI4Fmq4wPPQyqmzZFDftJVyXzviIjsvDAM6OfoiVJX/BITbR33guiQHt3a6v7drOyzu2IAH3jh7PXaN7FirvFkWuXPcpuc1B7r+UZrP63JsJ0soliG7JuyTUZDGRl5eHwWAgNNT7e+F2uylu5aSiuZMbwONTp2LQasmprWVGWhpnpfqeZDNYAnF8bYQQF2KNiq8HnsUlF61FwklEwDUEaHs+cQrgp1OjUipwNU8WKwSBAP/2IpjJZGLJ6mOs3S2Lb8cLaomPieS8KQParRuXUMV9txSSWdrEyt3JrDpaxRDLKB64YDBJAQmEa8PbbdOWs6NGclZQI5JjJ4JzHajObbfO2znfsax4IwDflWzmX8Pupq/BO0t2WkYqg+L2Um56g+qm9wjQPkNsVDqvPt15hlRnVJjMHrEKoNFmx+F2E2jwzgg2Sd5VDmvKD3jEKgC12k6uqbZDwer3jCg5UQinx0yhUSoZHh/D3iK5c6IgwVdrDzAqIRa9ospLoA1QOTlkCWF6SEski6DpeQOJXn49vYJVL6eV8gYbhbVNZEQH8vWeYlYcljuZZVeaeXL5ET6+rmUA8MPBUl5eI9u/j1eYkCR4+8oR3PrpHlYdkcOxLxkRx4asKkRJ7lo3Pi2MJy/o38Gzd435I+I4f3A0LlE6LUHfD83O4KHZpw6rB4gN8mPNfVOwOtz4adrPmK46Us5tn+7F3azsbMyqYvmB0naOm67SujxPkmBPQa1HsJqcHk5YgIZqs0PuFmRzsSOvlh3N2zw1x3uAcLjEO1NMp1KQ2JzFdNnoBC4b3XkY/Gu/ZFFp8hY+nps7iNHJIYTqf91M6kn+dvEgbl68h5J6K+cPjmbe8PbvW6heg1IheN5jmkUsgPxqC4ve3U5JvQ2FIAteJ91VJ2mwuiisbWJRF7tLFtU2Mf+NrR6BZ39xPf++fLjXOuuPV7ZZrmonWImixI0fbOdu+1tMVBzi6FfJFIZ9REJM17sS+WJG/wiPqKlRKsittnDpqHj+seq4R2A8Z5B3yGaM0e9kNIOHaX07duf5QpIkluwuoqCmiZkDohga/9sPpj7bUchT3x8BCR4/vx9XdiKaHi5p4L4l+6k2O7hibCL3dVC+es/Z6ewrrGfTCXkmL7+6iYv+bzPbHzuLeSNi+WR7YbtttCoFUQYdY1J6VprcSy+99HIqcspqsNgcDEiM5JWP13GiUHbebN6by9KVe7liTsv47B+rN/H9IbkhTnZVDbHGQK4clYBUuxDchYAGs+pvDAlPYe7wFLKrTAxNi+e2c3/dTd21yddyafylqBVq1Ipfd6OqUfhxQfxzXV4/QT+KG/t8h1tyoVK0d8uvLnkdh9+3XDNOy0+Hh/Lyzq3M6zeA2MDuT6LW2Js8YhVArb2JXFMNw7XymGWQYjw7nHsR1Xb88GeIOASLxYLFYkGtVnvlCTmdTkTRO4NWq5XFIK1KxUOTJnV6LHa3i8e2/EDMWUVYzH7UVESxcVs6f77+7/jpBFTKX39tDvDX8udbZvPC+2twu0Vuv3wy0eHtJ4vVajVFFd5dxrMLKoEB/JKXw4O7luLysxDn5+a8uF1ICjexcXCOtpplaydyoKAeW10o4aGnFqsAJNtKpPq75P8DSI0I/t7B6ztrjnn+75ZE9tZltROsmhxHyat9GJA/h8zy6xiWsLnrb5APEoKNpIWHcKJK/p5EBgawMTOfyVFjOMRKz3pjwrwnWxP03q9diZoBwZHdem6T1c6Xmw7gdLmZP2EQ4cae5bP1FEkSOVL9J8rM36FRhjIk4lWCdB07N3/aeIQ3Pt+ESqXg/mvPYuJw38Lsm5dfyEV//YByyYrCIbAxK5873/qW9++6CFT9wCV/1lsaoviwoj91Lh1zwiQSddPRcx7/TQWTvRlWvfxP09DkpLbJQUKIPy5RZOXhcgRBYPaAKHbl13J9c0B1gFZFYJuw5sMlDUx/cT0DY438be4g8qstXo/nV5v54WCpR6wCWLqnZdao0eZiVFKIz05u3cXjHrLWw9c3QPEuSJwAc98G7Zk/MfsSqyx2F3d/sc9LSKG5hK2nDEsIJqdVxtbQ+JaOKY8tO0R1czdHyfspOVrWvjRpdHKI57MRgL/NHURoQNds4pnljby02jvQMjHUn4l9wjDoTl8par9oAxsfmoYoSig6cMyEBmi5f0Y6L6xqsadP7Stf4B/95hAlzS4YUaKdWHUSX86tjtiVX+vlRlqXWdlunbauQV/lc2aHiwtt33K5ei0ACVRxYNXz1M94mowoQ49deM9cNIh+0Qa25dSw8nA5HzRnKj04qy8Wu4tIg45FY7wHZ0lhel6+dAjP/pSJKErcNi2VyeldGyCe5O8rM3lrgxzC/+6mPL6+dTyD4k5PB52uUGWy8/h3hz2/tyeXH2HmgChP5llrDhU3cO2HOz2/l1d/yWZ0UggT+7R3EygUAjaX9+y42eFm4TvbWXLTOMalhFFjsVNSZ+WHg2VYHC7qm5wU1Dbxp28OkxDiz6Q+3Xsve+mll14kd7lc3KGMobLWxI4D+USGGRg9KJG3V+3g3z9uRVJJGIdosQXZcca78StSIirgi12HWHrwKOeMyOCWc8aSX1Pnte+82hrqG1djdJ8U3B0obG8g8A/mjZRvDtPS0lCrfn3por9Kvi20Wq0UFxfjcrkICQkhMrJ7N909QRAUqIT2YlWhZTfHTV+hVYFW5eLcgfv5YNtUT25RdwnR+pMQEEyhWX6fgzR+JAfKExYWm4MnXttCvT0NrcGOnzuQwMuCqDFZUasU2Gw2L8FKrVajUqlwNQfzC4JAQkLXu0l/cXgHc/u/SqJBdup8HTYaTf5VBOo77rDXE2ZN7Mesif2QJKnDCUqDwcCoQQlkF7V8/0YPSsTudnH3hmUowywIgFZVi0TLdTYypGVC1aDrevmiZF/fbrmtYJUcEEOxtaWsMlnfvkue3VXoEasAXFIpB8syMRiMJPlYvytoVCoWX7OAT3fuZ0t2Afvzyvi/NdvQazU8c811NCjKSAtIY3iw9wToeTEjyTKVsap0H34Kf54afimhuq6HsYuixC2vL+NwgWw4+H7XUb565Er8tb9dQ5gKyyrKzN8C4HBXc7T6ccbH/eBz3RP5pfztrVWesdzjr/7Aj2/eir+u/fEadDpsBU0oI1rGy7vzSnj1i+3cdemnYPsBu6jkp1IHkbpSKu3TwDqSCrsKhSmf9PR0VKr/DumkN8Oql/9Z1mVWctune7E63QyLN6JUKNhdIF9UJvUJw+FyewKqzXYX5lY36QJQa3FQa3GQW20hyF9NcZ13IKJblLjri/2dHkOTvWedco6UNvDZjkIMfmpunZraIpKsexZOrJb/f/xH2PgPmPF0++d1uPBTKzu8yDbanLy7KQ+rw8WiMYkkhXWvUwfN71nbTo2p4XqvXK/u8sxFAwkN0FBY08Q5g6K9brBbl8W1pb7J4SX6NNqcBGhVxBh1hAdqeWBW327dVJfWtw+//NN5/cirsvD8ykxESeK+GX0Zndwzh4koSuRWmwnUqYk06DoUqwBw2bltUgKD44JYfbScpDC9p+FAjdne4WYnHUWT08O5bsKp22OfJC0iAIWAx62U7iN0/IoxCdRZHGzOrqZ/jIEHZ/X1ejyrwkRlo50hxiZojtj4zj2e+4+fjev4FgbHGfniprH4a7p/SlcqBK4al8T+onovx9SBoubmBqIIO96A0n2QPBmGXwXARcPiuGhYz5x/NJdBnsThFtmYXfWbClZNDpeXOCxKcLS0kaOljQxLCPJ069uUXcW1H+zyNAg4SaWp4/K+cSlhXmWBAIdLGvl6b7GXi+vRc/sx5R/rvITRI6WNvYJVL7300i1E07/A8m8ALMIVXPNEOHWN8sXipksm8OZGuROYLc2BRWsDLTAclFYBhaimqEGepHpjxTZSooIZER7Mjnx5wlCnc1EbuZIV5YdY2ErDkCTviZu2Lp+usq7iIDtqskgNiGZe/DgUzZ24iouLsTeXRFVVVeHv709gYPvrp8XhQK/p+Gb6REM1X+bux6DWcX3GaPxV3b/xtrq8z+d6rZ3LBwwm0dgz95FKoWDx1Mt49chm7G4XN/cbR7BWFupKqxupNTUBSqzV/lhx8/73h9hztAJBgNsuncAVF7Y4mp1Op8dR5efnR3R0NJpO3o+2KNnpEasALhi0j3Hnf8k32w7zzbbDhBn1PDxvGpFBPZvMtbsdVNiqCdMG46/y69RNL4oity+aTnxMBDmFVYwZksT4YSk02m04JBcnp6urbAE4RQVqhfydK6sOQ6VQcMOEkQyJ67pAJKj6eI17ULWPtLg3fQH+Si2l1hqmRgxlbFhL9YEkSeDcTYBCiyCFIAmyG6rUls7/5b0FwJyYidyZPq/Lx9SaYH8/7pg6jmU7DntShix2B1UlAVwxfgFut5uysjLcbjfBwcHo9XoEQeC+jDnclzGnR89ZbbJ4xCqAkppGTpTVMDipZ8JbT3CJpnbLFosFSZI8rxGgoqKC49l5XmM5m92FucnuU7AC6BcTzk5ntdxWEVA64dOVe7hwyiCSYhaiA54bLuepZWW1NIEQRRGn0/lfI1j90eh913vpMs/8eNTT4W5fkXd52KbsakZ30GlvUKyB2CB/Vh5pOQFmV5jZ1qa7XF6rboEASgEWjk5g6e5iHG6RQJ0KlVIu5epO3kxZg5WFb233uFz2FtTx5c3NtnVTmffK5gqvRbvLzS2L97DueBWRBi3vXT3KZ+bVtR/sYk+zePfNvhJ+vncKIfruDYoiDTpm9o/k5+Yb+X7RgSy9ZRz6X1G2qFMrefQceUbr6e+P8udvDhET5Mdrlw1jdHKIp2RTrRQQBAGHS774Z1WY2ZhdxdTmMq/Hlh3ih4Pye1XaYOu262tkYgiC4O3kijb6ceV7Ozw369d9uIvND0/zCAVdxeUWufHj3aw7XoVSIfDsRQNZ2FF54pZ/wZqnQRCYeM7zTLzwBq+Hr5uQzCPLDvncdEh8EF/fOr7bWUeD44L454KhfLK9gCB/NSAw8fm1RARqMdlcBPmreeaiQdx1Vh+f+V8fb8vnyeVHkCRID76MifyCETMvOC/FhTywP1jcwA8HylgwqmddbgCSQr1F1sTQZvPzlpfhl7/I/z+0FBQqGHp5j5/nJH0iArw6bKaG/7aW88RQPecNjubH5u/14Dgj13+0C1GCKIOOb24fT7TRj2/3lbYTq2KMOqZ04ii75+w+ON1u3t2c55UV13Y/ABPTwiiokV0LSgHSIwN4bsUxBASum5hEROCZyRjspZde/hhI7kqPWAXgL32Cv2Yhdchjle/WHUStUeIWXbgDvM9Bsy7oz76t5ZTWtriqc0oqmZ4UhUGlJK/BhCY2hxNiLRssUQz3qyVd1wiKEKwqOXB8r6mSHJeJqXVapvn7zrDsiI2VR/jzwU89yyanletS5QYfTqe3w/mkg+gkBQ31XLP8a/Ib6hkRFcP7F8zFoPV211RYTSz45WMaHPIEw66qQj6e1v3rV0LAaALVUZic8pipb+B5nD9wRrf305q4gCBeGHM+9XYrd239hgO1ZYyNSOBvw88lMjiAijo5XzLcqGf30Qp50kyCN5dsZf45I9Bp1EiSRH5+vue9sVgsntD8rjIurj+1rQoelAoD+/NKefqL1Z4xW53Zygd3L+j2a6y21/L44ZeptNcQqNLzRP87SQloPz6TJInCwkJMJhNKpZKZ49LwP2uw53GDVseMmP5saNqLUi1icvmxcv1w+gVVYG/SMDp8EX/78xQU3Y2W8L8GxDpw7AJlAjh24q46m22WAbxfEUVqQCz39L2EBzIu83nMUv3dYF+JEsjQTie7MQqzW8nrFS3h3stLN3NJ/DSi/Hpe8p8QEkR5Q0veaHyoLJQWFhZ68soaGhpIS0vziJc9JchfR0igf7NoCjqNiujg37ZpTqR+JgUN79PkkhsABXMJeXly92W9Xk9SUhKCIFBfX09sRCCpsUHkNDe8GT8shfDgjseTrzy+gMdf/4H1hYUIIqiabz3dbQR3tVqNVqtFdBYioURQRnsEQrVaTWho6GmJMjlT/NFKAn99W65efjPsLjd51RasDncX1j49mO0uMssbsdhdtL/VakGrUvDg7HQiAtuLDRP7hHHp6HivHgTj00LQKDv++ulUCg48OZNnLx7E4utH46dWYLK5eH7lcR5ddrDD7XxxsLjBqyRrZ36tJ/iRYVfJN+AASo3XjfhPh8q4+r2drDsuW4ErGu08tfxIu/2b7S6PWAVQbXZwpFQW9BqanNz26R6mv7SeZ344iujjhrU1b1wxgjevGM6rlw3jm9smEKD1XXrWaHOyPbfGp3PJFz8dKv1booAAAQAASURBVOfDrfk02lxklpt48KuDvLRgCHdMS2P+iDg+um40qjZCjNhKXWpbIniszHv2Q2pbU9gGg5+afy4Yik6lQKUQ+Mv0UMIaj2Jtahklme0uSk8RSu2LDVlVns/ILUr89YejvlesL4TVT4LkBtEFPz0EFm/RdOHoBJbdOp6Lh8UyNrnlO6oQ4PqJyT0O5r5oWCxf3Tqe5DA9a45VUFxnZW9hPdmVZnbl13Hz4t0dbvvqL9meQWNWncjqiV/CjL+i8vcWTtWqX3fBuWVKKpePkcPB5w2P474ZzS6vgm3eKxZs+VXPc5K/zx3MBUNiGBJn5LFzM5g90Hf3ojPJawuH8dkNY/jk+jG43KLHBVfeaGNZczlyTJC3YDQhNZTld07stBxWoRB4+Jx+vLFoBNrmUs1+0Qbm+ciiG5YQxMmvVb8YA08vP8JbG3J5c0MOC9/ajt31253ve+mll55hstoprKpvd9NzJqmyWMiqqUYU258jpFaVeeHBATyx8GwUGgVCU6txlwSLRo1gyshE/CbUoJ9dgf/wRsZlyOepkTHhzM9IJr/5RtkhKXm+aiBvma5GCN9EePR0snUuni7YziclR7hh01K+yz/crdewp/aE1/LeupbuqSEhLTf4arXa465yut28u2c3V38ni1UAe8pLeXd/++vowZoyj1gFsKUi31PGd6yugkvWfMw5K97h21Mct5/SyIKkN5gR/Shz4p/n/MS7O1y3wlbPvtpczM6ujc9eOrSeLRX5mJ121pRk88GJXbz9wCXMmzyI+VMG88il07zGz6IkeQIkXS6Xl5AniiIOh3co96nGZ6mhszD4XYkkKRAIok/IS2QVV3hNMOaU1XS2iw75vnQtlXZ5W5PLwpKin3yuV19fj8kkjyvdbjelpaXt1nlt5hyeG3QpsyPTmOYfgTXLyI7vB5OzfShnjxnSfbEKEAQlisAHUIR+Ca5scO5DcBcyXreCEOEo66v28U7O9743dp0Ae0uWlD9rSYu4nFDDZYhtbq9V3RQR2/LcJbOZmJ5EakQI98+eyJS+ssu/qallol+SJKzWrn3nOkOjVvH6LRcxOj2eoSkx/OvGOb95hpVaGcSY2K8YGvkGo6KWIjRO9TxmsVg8r1OtlsP871s0kuvnDOLRG6bz/P0XdiokBQbqeOXh+dw4ZRTqJrl64oLJA0iN8454EASBlPCP6RNyK+khN5EYtoKCggJqamooLy+npKSkw+f4PXCyJLCr/37v9DqsfidkljciIHTY+r2swcplb28nv6aJ8EAtn94wxmdp0ekku8LE5e/uoMpkJ9Kg5a7pffjzt4e9hCuFIDuDnrygP6OSQvn53ikM/ctqr/0U1Fj5eOter+0OFTfyj0sG89iyQzhFyetmEeCGSSkENJft5ddYsLYqlfv5aAUvdON19I0MRKNSeNxD/aIMqE6KZekz4ca1ULof4kZCpGz1/XZfCfd82b480eyjJDFAqyIhxJ/CWvnCoVUpSG4uCfzLD0f56ZA8I5dblUdimJ4rOwnrVioEZg/s3HZb1mBl3utbKW2woVUpeOvKER4nVEdUtSlfyqu2MPf1rUQadDx78UDigv3503n9ePzbw4gSTOsbzuRWZUmT+4R73DAqheAJbgd44rvDfL6zkFC9ln8vGsaIRN+zSBcPi+WioTFImT+h+GoObLWzwj+JC5v+jAl/UsL0pIR3v5Sy7XWpw0GLo8k7Jlxyg8tKZnkjO/NqyYgyMDo5BKVC4MeDZTiaRc3ZA6O4bWpqlzoCdoQkSSzdU8wvx9rnVwEU1Vk7zHWQy/xaBqD6yFRwF/K085/cxj00oWNKvIrzB/+68PWcKjPHy+UB46ik4JactbhRLWWzAHFyMG+lyUaVyU5aREC7roddIViv4bXLetb+vC02pyzmRxl0BHfD2ahQCIxPkwcpgW2y1AK2vwTDHuX2aWkU1DSxM6+WIfFGXrxkSLt1O+Ls/pFsfng6VSY7qRF6n+/T337K9Jz7Dpd4C8O51RaK66y/ufusl156kbG7XByvriZMryfGRzkawLbMAu5993usDidDk6N58/Z5/D97bx3expl+f39GbNmSmSGm2GFmZmjSpE2ZmWlLW97dtrvdwha33G6ZIW0KaZOGmdmOE8fMbItx5v1jFMkyBQq739/rc13tlbFGo9Fo4H7Oc+5zQjS/nTdjV/ju6GHuWfUzblFkbFIKH868FqX9bQA+2TmYY2IkBqOSzMgIHrphLunJ0ShClPzp6x8QXQKoJdRWNS9/uoWDEQdRxspqJiHZxjFNDRP06TQ3N5Pf3MbWfToGjtWiNzjxuNTMT7oEwZfctb6+NGi/fqk6yuL0QSf9PfoZg0n8XEMgaTYhIYHQ0FA8Hg8Gg8HfivPwmlV8mZeHpJCCpt2tHYgagCxjNGqFArePpOobHuMnD67b+CU1Nvme++ft3zMwMp6+4d0rZ0OU4eSG96yq2tpYwIP7P8QleojXRfDG6JuJ1fXc6t5gD0zcCYJIkXMDr9etIntSNpekXYJKUDFnYj9WbpZN8G+8YBI632SmSqVCp9PhcDj8y8cVNuY2G4/+6RPy95WTMyiFv71wMRHRXT9LcmMfR5L+Rl1dAzVljcSobISoVdjdcs07dVBml+87EQSEjn/oEh3bSY8vb6gpptzSwqSEDNINUQj6Wo7VbwcdxJ+vYJ5nMQsGjCUh5vTTw60eB99XbWKxpgRtu/2LV8ukSLW9ses3CiHtzCIAlIQZYzBabMwNGc4K+14E4LI+84jR/jrj+jxHEdacYuKVGsb3C0zuhYSE+EkrQRDQ6eQJthJzM15RJDv89FI7+6fG89at5/6qfT6OVqedGpuJDEMUOtXJ3xdVijBi9dMQRRFBOBxEvNbW1pKenk5ycjJVVVWoXC7OnDH0lHzubjl/MoumDsLjFclI6pzIKrmPIDg+9y+r3a8hMBYJ+TlgsVg6vacXvx96Cav/ATyw9IA/pevy8X14bHHww35PeQt3f7GfUl/LXIPZyfO/HOW1S0f+rvv16roiGnypbnUmJwcq23jynMHc93WgZUqU4PPrx5Pmax+K0Gu4ZGwaH2+XW1yyYkJZfrCm07YbLE4WD0tm8bBk7C4PA/66Iuj1qbmBoiGzw2At8xT9odJjQnnnitG8t6UEo07dOdEvcaj8XztsONpAR6gUArdMz+7yM96/egz/XH4Ym8vLDVMzSYmUj0d5c7CxfHmTtcv3H8eKvFqW7qkkMTyEu+fkdDkw/mR7OdVtcnHi9Ii8svbYCQmruYMSsK9+khmeTZRL8Txgv5YCezgFtWbu+GwfX980gUvG9mFGvzjMDg/ZsWFBPlCPLBzgJ+XmDkxgRJpsZLH6cB0fbJUlu7UmB/d8eYC190zrdj8EQUBY8zh45fMqUyzl3wMK2JN4AZeP7xMwwz8FTM2JY/aAeH7Jr0OlEPjros7xxwDE5sKAsyBfNnJk2KXsbg3lorc24/KICAI8e95QShqtfrIKoLLF9qvIKoCnVxzhtXVF3b4+MTuGzceaGJUe2ekYPHnOYG76aA9tdjdnDUti7sAE+OhzpikPsEtxE2ZCiOtzHoJybrfbb7O5MTncpER27x9x/Ye7qGiWC7QHvjnI4JRwBiaFw5R7QKmSPazSp8DIK/glv45bPtmDyyMyINHI5zeMO2kS57dGs9XF+W9s5Vi9hVCNkreuGMWErFMv0h5dPJBrXvuFKqeOGYo9XOj8EtaK6Ja8yUunS6yVbiL24JfEGlMg7nbgxOe3XqPE5lPRRoVqSOjCBL4XvejF7w+Ly8XFX3xBXn09aoWCf82fz8LcYH/Brw4f4h8r1mEzONE2CewrqeH77fmcP3lot9v9LfDE5g1+EmZ7dSXLa8/EWZXLe+v2UdUqD97DEvR88Ojl/vdMy81gYEI8+bXyxEm/qBi2FJQRMskddGdqdplJSksiMTGRpmOleFwqDmzqizbEDR4taRMCk26ZxuCB3nHj8JPF/KSRmD12tjceJduQyLVZwYRQV55VG8vkmgPJ958A0SEhXDKo8zHPNEbz6sRzePfoToxqLQ8MmwmAy+v1k1UAXkmi0trWLWElSiI/1f5EsaWYvoa+zI2f2+Wz9P3iNbhEmeSpc7SyrGo712bN6fEYnJsxhDXVhXgliYzIVhxCE1V2qLJXEa4O5+zks3n01gVcdfY4tBo1ibEBckYQBNLT02lqakIURaKjo1Eq5V/zkzfXcWiPfKwKDlTwwatruP2R7n2NvF6JxkaZnEkI1/OXRaM43OwkISqcCyad3vm8KHkmO1sOUOtoIFxt4MLUhV2uFx4eTlNTk18dFhsby9sF2/nnvtUAhKm1LJ19BVua9vjfIyKiSjP/KrJKkiQeOPA6h01laOPjWBwpH69Wj4bdVvlcyApLJr+tlAHhwSnCgioFDH9GMv9LpuaMD4MQSWtrNfNCRzApZAAC0C+q5zbZulYLKoVAtLHrsU2lrZHHDn2OV5Kv93v3vsv3Ux9GIShIS0ujvr7eH0yg0+l4at8a3iyQPevOzxzGP8eccdrH59diV0MF12z4AovbSbohis9mXEpsyKlNwCkUCpKTk6msDIRw2Ww22traiIyMJDPz9MjU5uZmFB47EfrTy/47Tg7+r0I6hZbAXoVVL06I0karn6wC+GBrGddPCRAe1a12Lnt7O9YObYDiCSS+vwU6KVcUMjnQ3kBaIcCxBgvrjtYzsk8kmTFhjM2MJjFcR78EI4X1Zp76+Uin7V7czmMoRKPijpl9eWGVnCI3e0A8I9MCzp6j06P4x9mD+HRHOXEGHY8tDiYkdpU2Y3N5GZcZ3W1S2qS+MV0menWHfokG2BtYPmtYErfP7NuJPDuOjJhQ2aC6HRxuLyHtyAe1UpDJhm6wt7yFmz7a7T+21a123rx8FHUmBxsLG0mNDGFsZnQnQuNkSJ7EyhXcJH4GCsilEpC4zn0P+M5B/3rhISR2MRmoVAhcPamz0XjHFL1WW+cZzs4bC77tlDY7eLOwiD1lLbxyyQjCTyGB7/i+vXnZSCqa7YRqld23agkCnPcelG8FQQlpY/n+uzy/8k6S4KvdlSwZETzj2yf61FVfHbEqP9gbbVJ2DHMGxGNyuMmrNvHToVo2HG1gULKRL2+YEJQiqdeomJEbi16j5K45uTKRGC57VekFJ3qcENm9d9UPB6q564v9uDwiM/vF8cZlIwMKQx9EUaKqXQiCJEFli10mrBRKmHx30PpP/1zgP275NSaW7qniignBxdwfhU+2l3GsXp7psrq8PLvyKBNuiqGg1sQ3e6uIDdNy+fj0E6Yo9kswsnnUBpy7PkIr+JSUbluP7+kKHq/IfzaVUFRWwcxjTzBXsV1+ofEorfNf4ZFleRQ3WJg3MIHbZvblkYX9+fNXB3B7JSb3jeHOWX15ac0xBODuObm/ysOuF73oxenj+4IC8uplcsctijy7aVMQYfXTsaPcu3qFXElHA4KErlH4Q+qzjt3pCkEg1JBDszOfyCgTrS1hhIVoWbejkOY2G1NHZ+PRubnyjL60tmYyKDyN/yzfQRGNuMtCUES4EQQIVWmZlSCTE4IgMCEzjQmZaWwpLsdp0/LnOVOCVMw39p9As9PG7oZKhsckc+vASf7XnG4PuworMei1PRo2n582ifPTJnX7ekfkxsRQa7EgSAKSV+KBKVM4p/9AokO6HnjOSO7LjORg0qDRaiVFE0mlS7ZzSNQbGR6d3OX7AX6q/YmvKr8CYE/rHlSCilnxs8ivrye/oYERSUlkRkaiVQbXL1rFieuZAYow/pU5hWJHG8263VQQaL+rcwRqh/TkzioQfKqqrpQlZpOjw/KpPc8kj8SWrcU0tVmpq2zjrku6n4zsDlGaCF4Y9jANzmaiNBHolF3XZyqViqysLOx2u9876Ktt+/2vW9xOfq44QqIuliPmYv/fE3W/LqCk1W3hsEkmqV6tG0i+LZKr0oZiVg9kUWoIWxry+KpyHV9VruPMpIncnhOsOlplHsKe5j/TJzSJ83SzUAoCarUat9tNmEImNHoywH/663V8vH4vggB3nDmJq2aN7rROnaPVT1bJ+2zF7nURqtKhUqlISgqo6xvsFj9ZBfBF8T6uzh3do3Lw98QLBzdgccsT1KXmZj4s3M1dQ6ayq3k/BaZjZBvSGRd9YvFFREQE9fX1Qe2upxPy0Oy08Xr+FpotZmaExJOmM9LSIt8D6qxunvl2PQ6Xh+vnjmXqwFykkAvB/hkAirA7SNT2o7W1FbVaTULCH29jcSqQukiA72nd/3X0VsL/JdSbHFS02NhZEpw8IgigbjeYPFJr7kRWRerVXZoz/9a4bUZfthU1Ud3mICUyhJunZWNxutFrVP7WuPmDErnWZ1SsVgqkReop8hEgZw1L4q7Zuby+vpg2u9u3fgLXTcn0K3SO40+zclg4JAm7y8vAJGOnlLdLxvbhkrGdW+n+9l0e722RJeljM6L46NqxQcfvdDEoKZzRfSJpsbuZ2T+Oe+bknvJ2H/zmIBsK5dkqwZfYN6obY3p8xvXt2yL3lLdQ2WJj8cubabLKN+lHFg7gignprCmoZ3dZC/FGLQ+e0b/bbeZXm/jXyiPMb1nPee3+niEEDPB7Mo8GeP6Xo7yzuYToUA3PXTAs6Leb1T+ezJhQin2/+bWTT2KmY+4T8Nkl4DRRFjqUJ2tH4kBk07FGXlxVyF/OHHDibXSAIAh+lR8AXjeUbeGNPIFN9VoGJoVz1+wcmbToM8G/WkJ48AxJYngI54xIprTRyoq8WrJiw3h88cm3N7SH2eHm850yGd0nWk9hfUA+fKi6jU3HGkkK19HSjvQ7VGViTUE9C4bIxX11q51L3trmvwccqjGz7JaJMOdxsDVD7QHImg7jbu52P/7WjpRbXVDPqsN1ndpOFQqBBUOS+H6/7BuRYNQxJCUct1fs8rzv6OV1ut5evwU6znIrBChvsnHua1v996kDlW0np5IaexPaw9+DrQk0BpjQvU9Jd3jq5wLe2iibg37JbbyvtjFFeRBKNvDwt4f84QV51SbSovWcPTyFyX1jMdndpEeHolAIvHfVmFP+3F70ohe/DcqsDdTaTOxpLQetF5zyBIJaGTw5tKc22GfHGwIDUuM4c8ypP8NOFX+ZPIM7Vv6Iy+tlcmof5mX1pci8jkuuWI2gEGmoi8WVfyEPPP8dAP/5ZSOeeQ1YvA4EBP4cuYTFYwey5XAZngo9CpuGqxYP46zckSS1M4dWK5W8dcnZ5NfWY9BqSY8Ort00SiV/G9lZ3etwebj6pS/IK5cJl+vmjOHWhRN/9feWJInpuenUeNvQeFRcPmgE5w7sRlXdDVxeL5d8+SWVbTbQqwjVavhg/sVEaEO6fc+u2mCPqyJLEZIlnZt/+B6vJKFTqfj4nHO5NWcBd+95hyaXmSER6ZyTOqHbbX537DCfFRwgRJS4MqUvsyLDOeKxU+EOEDIjI7sfzNsdLh57fjm7D5SRmxXPY/cuIjI8UActOG80G1cewulwo9GqWHj+2B6Py3Hiq65O/s3eW3mYijrZj/WzlXsYPSCVycOzetxGV1Ar1CSFBAg1j8dDY3Mb7y3bTW2jiVnj+7Fw2iCUSiVhYYFJ4YQQI4VtgXa8RL2ROann4RLdlNtqGBk5kFnxp3dOlVU3s3ZHIVEReiLVBlrcZkCgRVJRbX8fCRf91CP4wJLiV0Z/X72ZKzPmY1TLk5gbG/bzdMEnvi0ewOp1c03mQtLS0qiursbj8RATE0NISNfn1bGaRj5eL8+MSxK8+P0mlowfTHhocF3az5hKSkg0lXaZyBwXnYvCo0RSdraRUAhCUJMigEr479lVd7ToUAgCWxp38WKh3L5MDVyfaWdm/IkJ67i4OL/KSqvVEhFx6p0PV677jLwWefyzSlnEy32nE6HS0mYyc8t/fqLRR+re8+4PfPfQlSRGPoYUei0IGgRlApFAZGTkCT6lF78Hegmr/wJ+PlTDbZ/sxd3BgFsQ4J45ucS3awHpGx+GUiH4IzsTjDp+uWvKH9J+kxETypp7plHT5iAxXIdOreTOz/cF+TitKaj3kyxur+QnqwC+3VfNo4sH8cNtk9hQ2EBqpJ4pPZAj2XGnJhO1uTx+sgpge0kzu8taGJfZ9SzUyWJTYSOXv7Pd/70uGZt2WiTYztJm/78lwGTv7H/VHnsrgslLg07NTwdr/WQVwEfbyrhmUgZf3zSBFqsLY4i6W7KgrMnKOa9twe72Ui3ksFCrIcTnhbRcDAyIFw3t3vtoW3ETL66WlW9mh4cbPtzFyj9N9fsEhevVfHvrRLYWNRETpmVkn0gkScLk8HSvlMqYAncXgL2FZ3+sw9EUIM8aLc4ej9FJweOCD8/ikyIt//RcC5jZWNhIYb2Ze+bk0j8xIB+/emIGR+vk1/snGnloQX8EQeCeubncMze3x4/pcRe8Ipe8vZ0DlXKxlxMfxsIhiVQ02xAlOFgl/726zYFOHXxuFTeYmf3cUbyixLxBCUGE9f6KVlweEU1IJFz0CScDb4f7TFcBjx9uK0MpwJLhyfRPNNJsdTHxyTUoFQKPL+6cuvjIwgHc8OFuLE4PY9KjOGdEZzPxPwqXjuvD8oM15FWbCA9Rc/+8XLaVNAXdp9YWdO0d1glx/eCWnVCfDzF9wXDqM2jbittf9wq2iQNkwippGEUNwS3Bx33hYsK0xPRg4t6LXvTij8G/j/zAZ+UbAbA5NBAdAiaJMJeev06fHrRu34jgWmN2bjYvLVjYidj6PTAvqy87rrqRNqeDFGM4CkFga+PrCAr5Bh8b38AB03K0aWk4y/U0Rzej8MqKGwmJbyu38c6420mIMFBQVc/wzGT6JnWtQlcqFAxOOrV74faj5X6yCuDd1bu4+YwJnSYjTxXP7tvIywe3AKBRKMlNOPV6r85iobytTZ5KtKmw2kTsXfiTtse+fQ4i2s1dCeZoPi09iNcnYXB4PHyVn88/Zs7imykPYvU4MKq7bzVaun0/d+9f6ScW6mxWnhw0llxVLlpBS7VYTbIimVGRo7rdxiff7GTTDtm0fldhJY+/8zNP3rYIjc/rq/+QVN74+jaOFVSTmZNAUlo0btGL0+shTN318yY2NtY/IDfbNgW91tR26orjjnC5XBQXF/Pql7vZmS/XfpuPlnHM2sLFU4YTZwiMA54YPZ+7tn1HmbmFean9ODt9EIIgcHfutT18wolRVdfKtY98gsUm15tzFg7DNrAWl+jmgtjNSJJcJ3s9exgcJrDPItc/SkHBt5Ub+aVuJ1EaI8khwdfLwVaZaAwJCSEr68TEXscQJtlLP/hvdo+Tz8pXMTgygXExWaSFJLL5yxpmPPMSUeF6/nXv2fTPClyb0bpQ7h4yjWcPrEMCrus3jgzjrxsT/RrcM3Q6+es+o8VlJyc8lsv7juSTii+C1tnbcvCkCKuIiAhCQkLweDyEhIScchqm2e30k1UAZq+LUoeJYWGxiAqln6wCcHm8VDebSIw0Iqi6SR3/H4eI0NlDrod1/9fRS1j9F/D0iiOdyCqAH26dxMDk4H6svGpT0IDT5fH+oV4xOrXSbyBOF22Cdnf3CVY6tQKPKJIapWdK31h2lDRzoLL1V/sBHYdaqUCnVuBoZ8hu0J3cKb2xsIFNPpLirOHBMvBVh+uClE4r8+q4amLndrgTYVhqpN8TSBBgaGrP31vbocgdmRZBTIfUxZiwwPJx0mjZvioOVrYxITuaGf3kWSyr08OFb27z/z4FUhpLnI/y3oQm3s6XeKtFnrXTa5TkdGP0TxcEUoPZxfR/reO1S0cw3ucTZNSp/a2OFc02LvvPdkqbbAxMMvLhNWOJ6sIEu9Wj5l9rW6gxOVEpBDyihEal4MIx3be2dcTSPZX8kl9HVmwYt83M9hta79rwPa7iFt7yXB20/urD9aw70sArF4/wJ9JpVAqeO3/YSX/myaK82eYnqwCO1ll45eIR9I03cPcX+/2EFcCoPlHsKm3G4VNBPb+q0H/+vbWxmBC10v87Dk4OP2FrG4DbK/KvlUfYXNhIapQek70NrwQTsqKZPSC4deC9zSX87ftAsuKd0XpeWy/7bYleiYe/PcT8wYlBBOTE7Bi2PziTFpuLpPAQFAqBZquLNQX1xIRpTuip1hU+21HOrrIWRqRFcvHYky8QwkPULLtlIlVNJpLX/gnVBxcx0NCHNxQ3UiTK13ZOqAXWPgFDL4KoE1zLodGQMfmU9/84BqeEB/2+Q5IMkHYlzPobczY1cNiXuKlWCkzvFzhOFqeHpXsqaLK4WTgkkb6+UI2KZhsFtWYGJhlJiuheAdCLXvTi16HB0eYnqwD0OhdWu4b4BCMr599AiDq49jpa0YjKLCBqJASvgNal+kPIquMI1+kIb+ejInRIJlMm2ok6s4bGr5JxOzooHVDhEUWGZCQiGkUOmWoItapJCu3ZIPxkEaYLfu6HajUnRVZJksTSrYcob2hl+uAshmUGT6itrDjq/7dL9LKuqojB0adGpsX5DPSrfal0USEhpIWfwBi9IAaT1UVorA1LXSjnTxzEMX1Z0DoxPi8cpaDAqNbj9Hj4cNc+mm02lgweSHasTBwcKazlyfdXIrUrPcrsFqKjo2lubiZdmU66Mh2dTtdj2llLqzzAtkcLWFIElpvKKH7zU96+eAkxEXLdnpASSUKKTECtrT7GHVu+xepxsSR9ME+PXdjl9t1uN42NjcwZncFnq+Vk7IRoA1NGnJy6yu3x8tbK7RyraWLqoEwWj5UVcKIo8eqqzfxcdoxKlQVlAijtYEsQeH3XLr7Iz+OLay8iJVL+LZJCw/ls5mUn9Zmngu0HyvxkFcCujXX8eImsUt9f9Tntm1omxwxhn0VOovRKIh+WyX67tY5mml3BISkDw0/OFsHtrae8+XG0yiKeuKgPj3yWjVdScP3csUSEBj/jnyr4mM2Nsm+wWlByjudMtu6WJ+qb22z8693V/OfvlwS956YBEzg/cyheSSLO5xdV2NbAvqZqBkYmMCDy5I3JARxeF5+Vr6bJ2cas+FEMjezay7crDIlKZMOiW6g2teJpbKX6WAlhBH/HKCJobGwkKirqhCSUVqv1hwqcKgxqLRmGKErM8qSiXqkmNyqeuIgYYmNjGZmVzO4iOfkvKdJIbnJAYFFf10ZDxQqSk92Ex89HUMgq1APVtTRZbYxOSyFMe/KBP38ETiX9r9fDqhddQtnFA0KnVpAa3Xk2xuPtoI74jRtND1W1cfcX+2m0OLlsfB/+NCunx/Xbtwm2h0apYM7AeIalRvDcL0exubw43CILX9rE0+cO4eaP9mB2ehCAJSOSGZsZzdnDk39V+55aKZMN9365H4dH5Jbp2bLnzgmw7kg9V72309/b22B2ct2UQCtbVoekutNJrgN4cslg4g1aKlvsLBqWxJiMns1Ir52cwYbCBmwuL+Ehaq6ZnEluvIFdpS0s3VNFeIiau2YHfh+3V+SWj/ew0ueP9PamEt64bCRzByZwtM5MTYffqNWYi2HuVK6a7KZp5REsDg/XTcnscRA8uW8s6dF6v+E/QKvdzUVvbeecEcmMyYhict9Y/zb+tfKIf928ahOvrTvGQws6t0fc8skeNh+T5c0qhcA9c3KYNyiB7LiTS75clV/HXV8E/A1MDjePLR7E9uIm/vpLHcXSfbjoTOx6RYkPtpb6CavThcXpIawHb6EYg5YwbaB1Vq9REmvQIkkSkiT5feBiwjQ8tngg57+xFYdFntVrT5a6vRL/XDKI9UcbMOhU3DkrB4fby57yFmLCtN0mhb66tog31gfaCkI1St68fBTjMqP9ijy7y8uH20p5duXRoPfuKW8NWvaIEk6PFzocz1Ctyu+v1Gx1cea/N1HVKhO0N0zN5IH53beqdsRH28p4+Fu55eKr3ZV4RJHLx3dT/EkSFK2R/aWyZ4NaR1WrnR9W/EzMkRbOVXrRtRXxadKX3Kx8lNjW/fzF+jSsb4ad/4GbtoDh1Aq29jA53Bi0qm4HEn9ZOIAwrYqieguzBsQzb8wC/2t3zo4kPUZPSYOV6f3iGOYjsU0ON/Oe3+C/r7689hgfXTMWpULg8ne243CLhGlVfHLd2N+M8O9FL3oRDEU3rTOJemMnsgqfklbpElC65HvB6Xiq9ITNjZv5qvIrlIKSy/pcxtCIno2vJ8ffysrqf+CVXDS79TS4DAgKiMySOCt1FpWJ5ayq3Y/NBWuLWrjS/AVnZvbjoZ3LkYAwlYbL4sYwJjGVKX1PfZKuPUZmp3DZ9BF8vG4voToN/7hs3km974XvNvHe6l0AfLRuD+/96QIG9wk8r7OM0RxtDbSJdTR9PxloVSo+PPdc/r1tG15R5KYxYzCcYBB83dxxPPftBhqPQr+UOKYOymK0N40KczNVnkIyI6O4ekSAgWp0WLjou48paWlFaFXx+d5D/HDdZSQaDezaXYK6XkTwCEgq+dyZmppJYmIiBoOBpqYmlErlCRPP5s8cxM/r8mhMFP2zyQUNjSz685tcPG806anRzBraF51Gfk7fv+NHrB65zlhaepAz0vozPSmYfPB6vZSWluL1epkzIpnMBAPa0AjGD8kgwnByEyYvfLeRj9bJrW6r9x8jVKdh1tC+vL5uO6/u3Ys7XAIDYAB1K0SqnExNK6PFoePHQ0e4YfLpt8R7JRG36EGn7J48SIkPHickx8vP1FaTjdXrZjF+/MeoVF5CNWMYEnYVlD7f5XasHgd3517IjubDZIQmclHaLNrcbVTaKkkKSSJS03XrWFHjbUR5dhGjVJKacYwp99fSpnqblNjAuexyt/LAui3sU+Sh8HHgbslLhSc4xMrucHfcPPiUVsexs76cy9d9ikv0ohIUvD753E6/e094puATNjTI9faqul28PPJOssK69nvzer1YLJag9s68kjrW7c0n2ahjSEo0I6QBuCM8lHmqiHFHMNI9gNraWkwm02kbqOMju0VR9IcOdIX3p13EcwfWY/W4uLbfWEbFBibJX77+bL7ccgCHy83Z4wYRppPvCUcPV7Nn7Z84f4mcHO+seQ1t4ne8vb2IZ9bKKsTsmCg+v/xCDLr/HaW8KAkIJ0lEnaw5+38TvYTVHwyXRwzq6VUIsm/O3xYNxNiFcmrWgDjGZUaxrbgZQZDbtzxesZNp8uni9s/2+ttSXlhVyJj0KH/Me1c43ib45oZinvslMNC9ZXo2d8ySfbXWFNSzpUgmI2raHDy78ihm38BdAr7eU8XXe6pYmVfL21cEDAabLE5CNEr0mpM/Lc8YnMj8QQl4Remkj8nagvogI7rVBXVBhNUlY/tQ3eZgw9EG+icae/SI6gmhWhUPLzx5L4tR6VGsvnsqhXUW+iUaiDPIM6d6jaywsbu93PbpXn64bTIJ4Tr+sizPT1Ydx7oj9cwdmEBKpD4obSxEreSz68eh16jQa1QnrSoKD1Hz7S0Tufb9XewqC25ZPP47RurVfHfrJFKj9P7PO46Oy8exvyKgQPGIEgnhISdNVuHz9+pqeU95KwVSsNeZUpDwtrsZ59eY5La6k1AqdURFs43L39lBSaOVoakRfHDVGML1na9bo07Nm5eP5J/LC5CQuG9ePyL0GpbuqWTp3ir/erkJxm6N/AGGpISzaGgS546UW+5sLg/nvr6FQ1UmBAEeWTCgSzP8gtrgmT+ry0tedRsTfdf2E8sP8+aG4k7vA5jSNwaNSsEvvnPr4rFpxBl0FDVYuPuL/dSZHPSNC6PR4iIpIoR/nD2ItzcW+8kqfEmWp0JYbStuClreXtzcPWH1/e2w5wP53ymjqT7raxa/up1WmwG4nt1SX55Wv0Wc0sZXN4yDxxeA4BtI2hqhYjsM6D4pqTu02dxc/s529le2kRoVwodXjyW9i8RSnVoZfM+wNUNLCcTkgNbA2cM7t0+uOFQbNAngFSW+2FWBw+31K0gtTg8fbi3jmfMChNXmY41UNNuYnBNLcq/6qhe9+FUwCFrODh/Bt217kACvM5SBESk81Y50bo+rJ4xkzdEiXJ46xqTXcv2k06sVukKTs4l3S9/FK8nP0FeLXuWlYS+h7ca0GiDLMJmrsr/klcL/sN98RE4uQ+CfV1zIAGM2XnEs7+8tw+MzcN5UU0qNs9XfhGTxuHjjwDbeXrubB+ZO5YpxI8CXkGdymwhThaFSnHx9ds/ZU7lj0SRUCkWPSqH22JAXeC55vCJbDpcGEVb/GDcXpUJBqamZ+X36sSC9Xzdb6hnpkZE8O3/+Sa9/xYyRjM9No8ViZ2hGEjqNCo2oIDOnDNFSjZ1qXjj2Go8MuBOvJHHJuo8ooREiQQrzYCoX2F1RzcKBuaT3iUFtgYQNEpY0yI6P4dnp8r6EhYUF+Tj1hIE5ibzz3OWc98FntLkCiiGLTuKtdTsB+HLTft6+/TzUSiUOTzC5Yfd0JjucTideb6Buy04ykpOT3aNxeEfsLwkmVQ6U1DBraF/2llcjakQElYgkCiAqiI5089nsr0g1ymq3o2YlcHqE1famPJ7I/xCb18mCxPH8Kff8LtcbMySd2y+dyg/rDhEbFcZ918rJlC9/soEf14fz09orCQ11cO7MM5k0s/uOllnxo5iXOJZ5ibI3WIWtgqcKnsLqtaJT6Lg7926ywzoTQy73YWJUAVIlVMgjLKIWiEYSrUgt16Ny7+SurFD+XDSeet81r0DBwiEjORRnoaq+DaVC4Iqz5c9ee7CI55ZtQAJSoow0mWyM6pvCXWdN4e9bVuMS5d/UI4l8UbzvlAirA62BhGuP5CW/rbRLwkoURUpKSnA45FomOjqaI002/vSf7/xjrpunDWJidiILI2ZiMBgoLQ3YuthsNrxeb4+EU3ew2+1+ojUsLIy0tLQu1VrJoeE8Oz5Q/7lcLrxeLzqdDr1WzRXTO3vG/bhsPdecl+df1ijrwbGWN7cGxl/HGptZc6yYxYPkZ4Bb9LKi6jAeSWRuUn9CVP+dFO3/l9BLWP3B2FHSzJE6s39ZlGDNPVP97Uz41CNf76kkIVzHXbNzeO/K0Zz7+lYOVZv4cFsZ1a123r5iFIIgcKzezH82laBVKbl5epaf5DhZ1HVQ4dSZHd2uexw6tZLbZ/YlTKtia3ETQ5LDuXl6NssP1PCP5Yc7tZEZulGirDpc71cr3P3lfpbuqUKlEJg3KIEbp2YxKPnkpOmCIKBSnjw73LEFrqNKRaEQuG9eP+6bd3qF0K+BnNIXPPD8ek+A4Gi0uFh3pJ4Lx6Sx4WhDp/cf/y6xLXtZn/kRe+sllkVcxk0Lxp922l2EXsPzFwzj/De2dlJtAbTY3Px4oJobp2Vzw5RMthxrxOryEhWq4aqJXZMOo9MjWXtE3n+NSsGw1MBvva+ilS92VRAdquGmaVldEpij06OAog7LMDyts/okLTqUksZ2CjGbm/wak1/dcip48ucCSnw+bfsrWpn+7DoWD0vioTP6dyJMJ2TF8P1twX35HY9fvS/F5+EFA7j3q/24vRJKhYBWKbBoWDKPLBwQRKz9kl/HoSqZjJIkeHF1YZeE1dScWH46VBv0N4vD49/v7siq++f34+pJGVw1MYOdpc2olApG9pFnCe/8fJ+/zfH498ivMWF1ujupsrpqAw0+EAfg0FdgSITR1zIsNcJvRo6PqOsSTnOArAKo3MnW3buD0ip/8o7lafXbshG9QgHR2dDoI9cFJUQHtzV4RYm95S3o1Moe7zlvbixiv+/7VzTbeernAl679ATpNpW74MMl4GwDYwpctRwigwlVty9VsCNcHm+nhEBju7bMNzcU8cTyAgAi9Gq+u2VScPBAL3rRi1NCc3Mz8/QDmaDNRAISDdFBM/6iJLKidgXHLMfIMeQwJ34Oy26cw7HGs4EW7J4fqTU9TIJR9tiRHKuRHCsRVOkQei2CcPKDFpPH5CerAFyiC5vX1iNhBaBTGri5741Elf9AvbOJyTGjGWDM5pODX6GQPuD2/lY+Lx1FlU2+r0doOtSMXrmW+u7AYa4YNwKz28wzR56h0l5Oms7LtNjJjIk5F72qZ8X4cZxqi2R2QjTFtQEfwKzEYAVVlE7Py1MWn9I2fyvkJAd7sFbbazlmCQy4802FNDibcHpUFJkCKjDUEkqNRFaMfMz650ZzyQUj2Lm7grToWG67bhZa5ekNx9KSo3jqnHnc/vn3uEQRTZsI7VpD95XUUFTTRL+UOO4YPIV/7F0FwNCoJGZ0QVpotVpUKhUej1wvaDQa1O3UhU3WZZgcWwnVDiEu7OIu92lEVjIHy2qDlgEGpcSzXpWPUi8iSeBt1XBdjtNPVgH0Na4+reMA8EzBp9i88vjjx5qtrN7RyJWDpnLO8M6m/BctGMVFC4L9weqa5P2wWPVYrHrqmqykhyayIHE8P9ZsQaf0oFOCQRXGwqS5LEkJ9rRbVbcKq1euDx2igxW1K8jO7nyMw7STED2/+MULku9/AoDtI3DLZGOi3sr1cYe559hE4gxaHhmxhFExfXn/n2nkFdWSEGMgLTGKZouNP7//Iy6PfL+oaGgFCY5WN2L2uDhc3wDtTt1YXc+EqMlkwmazERISQnh4OLmGNLY3y7YRCgRyDF1bd1gsFj9Zhe9++su+iiCBwI6SOibnJBMZGYnCR2RLvhVUKlUnksnr9WK329FoND2SptXV1X6i1WKx0NLSQnR0z+rLpqYmamrkujM0NJT09PROxLrTU8mYs55CGeIMuq6qSr0YdFraHIHxrtGn0pQkiVu2fs76Otlf7tOonXw05UrUij+uXZzjnmgnmxL4fyAmsJew+oMR1sFjSa9R4nB5ufmjPewobSY7Loz95a0cF5YfrGzjscWDOFQdUEysLqinus2BXq3kgje2+U25txQ18vMdU7r0CXB7RVbm1eGVJOYOjMftlbjmvZ1Bhs5J4Tqm9O1sir61qImtxU0MSjIyx+dVZHd5GZMRxVnDk4kK1XCs3swtn+7pdNIPTQnn+QuH8dfv8lh9uC7IbypSr8bh8vLY93ks9ZEyHlHihwM1rMyr44sbx58WqXAiXDwmjXqTkw2FsoLqVJQg/w0khutobme8frz9rn+iMUjVctawJK4Ynw4tpfDh2cS6bcwB5kTWQnL3RUCb3c1flh3iaJ2F2f3juHN2TqebdmqUns33zWDOC+s5Vm/ttI2KFnk/RqVHseaeaRTVW8hNMBAdpsXtFVEKQtB5+e+LR/DymmM0WpycNzLFr64qbbRyUTvvrbxqE29fPop3NpeQV21ifFY0549KZXq/OF6+eDi/5NeRHRvGjdNkEqJvF8b9JY02lIh4fQ8bhQDRJyBUulNg2TsoxpqtLt7dXEqCUccNU0/s7zBvUAKvryvyKw7PGyWrbc4ankxmbCiLX96MV5SwiRJL91bx0ILgc7MjeafXdP0AvHBMGvk1Jj7YGvDY+GZvFXfNye1W9XbeyBRu9H0HQYCxHcILqlu7JrOLG6w4PcGtMPfO6cGwvqkI3pkHbt95VLOfqxe/htsrsau0mZHpkVzXXdqkSgfq0MB7gT6xEUDgOtCrFXiuXYcqxacivPBT+OnP4GiVSaz4QPHqFSWueX8n63zk6Q1TMnmgG0XlyaoHg7DhGZmsAjBVwvbXYd4/g1bZVtxEQa2501t/PFjLsJQIBiYZyas2MSItglunB4rfT3dU+P/danPzc14N10859QSnXvSiFzKOz+wblfIzVqFQUHqkhqdu+4DGmjYG3heFdcBu5hiqkMwCG2kjR28CAorfestHJBivRXJuQ2q9Gb+NsliPYPxrl5/r8Xgwm82o1WrCwsIoaGrg6h9/JiE1hPAw+d42NHwoEergekiSJJYW5FNhamNOZjYDYmVPPKfJyyTXRNIyYtBq1Xyet5V43cMYtQ6ygNzwWm7bfhHnZo/i5kHjuGXzUo62NuBuA0WrfAySIozkNdTxXvGnNCoqyA6pJ1zl4FDrZ5Rb13Nh+ptolKc3CdYTHrlwFhq1ioqGVmYN68usob9/Ivbpwqg2oBZUuCX5ea5VaDCowghXqYjWhtLklJ9TSknB3+fMoX98LK2trVRXVzN+dCLjRycSExNDuLF7deyx8gZeeH8tNoeLyxePZdqYzsdjWk4m626/jiU3v4HbKWFJkORCB3lWXPIF/lydO4ZJCRm0OG0Mi05Gq1Th9HjQqgJ1hVKpJCMjg8bGRgRBIDY21l8PNlm/pbjpTwA0Wj9DFG2ESRfz6b9/wdRsYd5F4xk4OpPbz5yEUa+jqKaJKYMymDZYfi5l5YYjmORaQRBAZXCxaYeJK9t9JUHRfYfHcbhFb5eDf4fXFbRc2dbCw9+tJCc++qRCAxZMGcjuvHIkCTRqJXMmyrXAn3LPp09oJB+Vf4MItHlM7G7Z04mw6kgmaxRd15npMc9jbzyXEO8R+TsD2D8GzRNIkj1oXb3SQ1NNJA8MnM+4GLljI1SvZczgwMRXi8XuJ6v8G/SNxUoaWlA2qJC0ImKoiNal5q7BU7s9Bq2trf4kPnyqqfv7X8o7JT/S5GxjTsIYco1de4x2VEYpFArSYoPvWWmxkWRnBxR7qampNDQ0oFAoSExMDBp7uN1uiouLcbvdCIJAamoqRqORrtCxHftk2rNrawOkqtVqxWw2d9p+veUjNPpWSrwCGYKAUlSw7IM03ntuDdPumMryMDetdgfnDR3EtGx58rjObvaTVQD7mqs42lbPwMjgdO7fG70eVr34VRiWGsHVE9N5Z3MpAjAyLZJ/rznGal+K1d4OSoVdZS1UtFiDkgI1KgUmu5uqFntQgtzROgstNhfRYVpEUfITBJIkcf0Hu/yKlrEZUYzPjGZ7SWAWKzxEzTtXjia6Q1LV2iP1XN3O7+mJswcza0Ac572+lbImG2FaFS9dOIz1Rxs6kVUPL+jPNZMyEASBVy6WpeXf7K3kxVWFhGhUPLKwPxe+tc3fktgeLq/Iqvy634WwEgSBO2fncOfsYL8ul0fkSK2Z6DCNnxQSRYkvd1dQ2+bkjMEJfiPkPxIvXjice77cT73JwYVj0vxJi//KPcI/mu1UKRJZPGEwF4z2PURqD8n+Pj5IVbu59/M95NVamZITw31z+wWRR49+l8eyfXI89+EaE6lRes4b1XkGRaEQ+OiacZz96uZOSqH2yqZ4o86fdPnsyiO8svYYWpWSZ84bwsIhsoFqmFbF/fM7K9j2VrQEGflvKWrktfVFPLNCfrB/s1dW4S0ZkcLCIUksTLbDoaWwLxaGX4ZSISAInWcLRAQSacSlCuPeRaNJjepaidJgdnL1ezs5WNXGkJRw3u1wTVw3OZOtRU2dwgZKGjufw10hKzaM72+bxMbCBtKiQ5naLjVTIQhB+TAuj4jV6aXF6kYQZNJwVv84loxIZumeKgxaFU+dM6Tbz5qQFR1EWNW0OZAkidHpkUzKjmHTMXkGeGpOLOePSmW+z9frWL2ZZfuqiQnTcnG7hMxzRiYH+WIdx/zBieRVt7GzVB60DUuNYG5PHmElG4IIJ46uQKEQuGlaFtAz4SIpVLyW8zYb9x9hgFDKvbOzGDViBJqvl+PyGfzVuXVMeL8Ru3sFV03MkH3fLlva5fb2VbT4ySqANzYUc5tPPdoRl49P5/v91TRaXISolX5yr0d0bJ/pop1Gp+5+1m1fZSsfXD2G8VnRnfz+4gzaoPOufbpsL3rRi1NHdHQ0eU2lvFW7Frvk5sLQKWy8czulBfIsfGlbLc/EHSRaJdddrd6nEYX7g7ahQI/b24zKvTM4XN4lqyaOqwmOD8w8Hg9FRUW43bJKNDY2lr9tXUe1xUpdSSpx0SZyIuK4YfjNnSaSntq6kTf2yNt9Y+9Ovjn3YuxlFv5y3xc47G5SUqN45KVF7Khcx4X9A8/sKK2VzWdfQGyozBQsm3s1oiTx1Ir1/GIrIjMmkkvGD+Pcrz8jOamSPoki4arA+03uGuodR0gJHfFbHn4AjHpdl35XJreNKlsTKfoYDGq5Pmtz2fmsSPaVuShrOMaOarHfGREaI7f1vYZPypcioOCK9PPQq0IQRZHnBs/jjeIdKFRK/jR4OsOiZZWRzRactFdcVMvz/1yN2ezg3AvHMmNOIIpQkiTufmop9c0WAB556Qc++deVpCZ09kaKCtfzz7sW8+Azywhp8eIIVyB4JQzFNmKMAWIxJ1yuORweN5cv+4qNFWWkGIy8c+YS+kbJk1RarZbk5M4tXybH5g7LW3jxDhf7NssK5o0/7OPVlX8mKT2Wa+eMwWKxYLPZMJvNGAyGziSTV2B3WQpf7Z3E2UP3gSIaVcSz3R7vXQ0V3Lzpa5qdNs7JGMKTYxYEXROX9pnDf0p+BMBp0uBo0SEB5c1tJ0VYzZs8gIRYI8fKGxjWL4XstEB91tF72OQ24/GKVNS0EBWuJ9wQwsLEhRwxH6HcVk6iLpElyUu6/ByFoCVEOxJsR9odC7kGF/TnI9m/BrEOEQ1m9ZV8vmQuo5Pkyc2t+0rYV1DJwOxEpoySJ7D6xEYyND2R/aU+lbrvtiMA54weROnqVlrK5f2/atJIIrTdE6Rms7nTclpkJLfnnHvC4ycqVbx/sJiyxhYm9knkmhkTuDA5hSMlFRTUtpAVG44mGsZ98BZapYq/T5vFzIysbkmolpYW/31RkiQaGhq6XTcuLo6KCnkST61W+5Mue0J7dRft7sntoRDkY2WXJPLdbo5uiuWj5+Tab/u/N7Cx4t8IKgWqdsowg0ZHiFKN3Svvu0pQEKXtVb//WvQSVv8FHJ+Zl4CNxxppsbl6XP/Jnwp4cslg/vlTATaXB4dbZP6LG7lucgYGnQqzr9WnT7Se0iYrC/+9iQazk/NGpfLE2YOobLH7ySqA7SXNpEQF37Da7G7u/epApxamlXl1QYP/N9YX8eaGIsp8xtoWp4drP9hFF6GHTMmJ7XQDOHt4it/D5VBVW5dk1XH8ke0tNpeHi97cxv7KNlQKgX+dN5Szhifzt+/z/IP+tzYW8/1tk4JSE/8IZMeF8e0tE4P/uOVlSn9+h1rPeShoJMfmBXyEVcLgIBVKhX4AX+2VH2SHa0ysyq/j21sm+tMmizqQLUU9/CYJ4TrW3D2Nj7aV8cyKI7i8ImMzojhzaFKndQ9VtfHvNfIsg93t5Z4v9zN3YELQwLvO5KDJ4qJvfBhqpYL+iUZ/aiC+VLz2xCrAztJmloxIgbZKeHsm2FvYK2bx1moPuvRR3Dg1k9fXFQeRP0k0sll3B0Smw5j9dIcXVh31J7wdqGzjxdWFPLY4UECOz4pm1d1TeWdTMf/ZJLcCCAL+lMSTQXpMaJfeR/0SDIzPjGarz89p3sAEXl9fxHtb5M+5ZXoW987tx3PnD+PxxYPQqZV+A/WuMDYjmgi92t8uF2fQIkmgUip476rR7C5rIVSrCmqDq2i2cfarW/z3lH0VrTx/gaxUemB+f0akRVLRbOPdzaV+dZ/L4+XDa8byyY5ythU10Tc+jBabq/v25Lj+wVOAcSfv8/bZzgqe3i0BOWwlB0wZPAJoVUpc3kAseb1Zlmm/tLqQ8ZnRjM/qWhrekSxSKwVU3RzTjJhQfrlzKodrTGTEhnZq3d1e3MSzK48iCHJr5fC0SJjxCFTtBnMNxPaDCbd12u7o9CguH9+HD7aWyao+SfKTb/i88LoKp3jqnCHc8dleKlrsLBqaxKIursFe9KIXJw+FQsErjWuodsvPnJeO/Uhiu3aoyHqXn6wCiFCaaLJmEBt2CY2WbwEPdk8+B6onkht+M0EVjHoInxzbwxN7VyMI8NcRczk3cwhms9k/KMPXRmNxuxA0XtBL1NsN1NvtvHhoE/cPmxG0vz8dC/iIOjwe/rFuHUcLanD1hahD0JpRzOOlj6CK9tDm1hGudvjWTSBaH9yarBAEHpg3jQfmTQPgrb27cHg8VNVGExfdiltUolbItasCJQb16QdXnCqKLbXctutNWt1WItShvDzqBpJDYrhkzcccbpUne78vy+ObOVf94W03Y6OHMzZ6eNDfKioqqDLvJSuqAIPCQEq7xMTQ0FCamwM1zWsvbKSq0YwjRs3e//zMgsIKHr5F9rNyOD1+sgqfp1d1fVuXhBXA+JGZfPPmDbzx/ArWLN2DAFxwzRRi4zu3un94cD8bK+TattJs4rGNa/lwcTApYXcfQ0CBTi0rnvWawWD9MvBdNIM4tCNgzeB0uDl6oIKk9FhMJhPl5eUArD9STV6diaykGKbG92V9XSF4QV0oTwZuLJrLgNS7iIyMJFndtZk3PtN4By0Y9F6+KdvLjKRs5qYGJj4v7DOL0dH9eXr1WtbvrwdJIFIfwqg+3W+zI4b1S2FYv84+kxNiRrCsehWtbrnbZVbMZG7822fkHatBq1Hx9zsWMmlEFo8OfBS7106IsmdPSUG3AMn2GRzvpxHkdlFBmQQxP4A7D6UyjRkJgX1Zu/0oD77wvX/5oRvmsnDaIFRKBW/cfA4/7S6gqbaNL19YiVUroGt2EjXLxRc3XcwPBTsx64oZmuTEI3q69aLrmMCn0508CfzostUsz5PPh0N1zQzNyWZsn0Su9nn71dht3Lh9o7+D6PaVP7L7mpvQdePv1LE9sKcEwfDwcHQ6HW63m5CQkE5qr2VvrWXNl9uIS4nm5icvJDLOSFJSElVVVUiSRHh4eJfecfGGq2izr8Pq2ovgjWXFC4HuAY1Og1Kl6LRfoSoNz485h8f3/4RbFLln0EwS9b9N+uqpoFdh1YtfjcqWYMlnYkQIR+ssuLwiaqVApF7jH3ABlDbaOHdkCoNTwpn3QiBy+a2NJXx0zRg+2VGOVqXkrtk5XPnuDr/65dMd5UzNiWV8VjQalQKXr21HpRA4e1gyKw/V+VuTAA5Vt+EVpaBBsLrD4K2sOXh2iA6pZsdhDFHhcPfcMpMYrgsyBg/VKBiWGkmd2cnsAfGcN7LzQ+P3wg8Havz+NB5R4umfCzhreDI/t/MBsjg9bCps+MMJqyCIXtj8AuYt73CF6y+0Id9gD/7iZtNYt0xCRfaBy5fBzrdAF87fy2ZBc+B3Lmqw8sraIr/Cae7AePZXyMo+lUJgVv+4HnchRKPkuimZnDMyhRabi/To0C6JE0u7cwvA4RZxe0X/4HvZviru/mI/HlFiRFoEn1w3jn4JRt64bCQfbSsjOkzLffP68dG2siC/rmGpEdSZHGxft5V0awQJgsTlrgcwN+uhuYqMmFB2PjSTZfuq+WzLUYxth3lc9Y785j4diD+A6n3QcAT6jKewzhL00tG6zq1ayREhPLJwIOMzYzhY1ca4doSIJEknNpdtKoK8byAsHoZdIvssIRNJ7189hjUFddS0Ovhgayk/5wXOv1fWFnHF+HTijLpO3kYHKlvZV9HKkJQIvyoxMlSDxxuQRVe3OVh7pJ6Z/eNRKRWdWv7wkdnHySp8nlntMXdgAmsL6oNaUT/dUcFfzxzIsr1V7K9sY2V+HT8cqOGnOyZ3HaCQNg4WvyJ7URkSYP5TPR+vdsivDjaTP1wjL/9t0UDuX3oAtzeQwHgcHT312mNgUjg3Ts3i9fVFqJUC/1wypEfFU2SopstQihari2ve3+U/5696bydb7p+BPq4f3LEfLPWyX1c3PiWPLR7EvXNz0agUrDlcz11f7Mfh8XLNxAz6Jxp4YOlBCuvMTO8Xxy2+tsD0mFCW3ToJl0fkqZ8LOOe1LYxOj+Leubm/WShHL3rx/ydIkkSdI6Byl5AYvCiHrXt3A2Bak4Lj+kPolHId5PZGYnWFkp7wD3SqLCpaHwNAlOyUWn9kYMTTSI4VoEynXnkVf939H0TfDOBDO5czIzkbtSr4nqBUKrl26Aju3lod9PcDTcHLABpn8LNmU1U5QpgAuWoklUTq4iYQwCOp+KltMBNCi9CoPLiUA3CJzh6T1LIi5QG0w6Vhx4EcInNzmJJRgoib0dGXEq45eRLg1+Kj0nW0+ibgWt1WPi5dz0VpM/xkFcDh1nrKLS1kGU/cUvZ7wePxUF9fT0FbHms8PwFQ44X3y97k7gEPgW9gLYoiFosFjUZLfa0JR7wGyWdB8OOmfGZP7s/YIemE6NSMGdyHHQdlYikuKoz+mT1PjkUY9dz317O54tppKBQCcYlddylYXM4Oy8ET56XND9Fg+RiAeMO1pEU+TFzYZYiSDZNjC6GaoSSF306/4a9yaIesvFZrVWQNSKbkcDV7tuYR1yeMEoeDN9fLhtWbCypYMmEQqxbO4/0Vu9kqlpKYEcKl4+VuB72+8yS12WxGFEXCwsJwKWuIj5Sf+ZGhNmrszZ3WzwpL5pUzL+ar5IO02BwsGJRLvEGuk0+mPjuuCtPr9UEERow2in8NfYA8UyHFBWZeeSwPs1U+hk6Xh1c+2cCkEbLypiNZJTlWg1gH2ukISl9bmBAaIKsAnMuRxMcRFKEIinDQTui0bxt3F3VYPsbCafKEaohGzZLxg3nr78tQlJkJC9WBILDs/Y08NDeNA9ql2Dw28sq3UGwp5oasG7r8/rGxsYiiiNVqRa/XExvb2SamOxTUNnRantYvk8jISFpaWmhzudp/Y2xuN1a3u1vCKioqCrPZjNVqRaVSkZDQ87mv1Wo7EW4Au1bn8fqDnwNwdG8ZDquTxz+/jYiICAwGA6IoBvm0tYdKYWRAwjd4vK0oFUamnPENS19dhSZEzd0vX0FFYxvPfrsBq8PF5TNGMnWQTO5OT8xhemIODY42XjzyPT/XbebM5DGckXQC39PfEL0pgb341Vg0LMnfjqNWClw7KYN75uSyv6KVQcnhuL0iZ7+62T/oGpISjiAIQemC+JQdedVt6NRKxmZEkRqlp80eTBKY7G7CQ9S8eMEw/rLskG9AJXDpf3aQGqXH5RX9/jOj06M6EQ8z+sfxwbYyukN7NUzw53p45NtDLLt1UpfvA4gO0/LW5aN4duURVAoF95/RjxFpJ5Zx/lZYf7SB/RWtjEqPRN3BtF3tKx7SY0KDyMOMmJNLb/ndsP5pWP8kdWKSn6wCaPOoqTM5/KopUkfL/wETNpewsiw/aDPN1sB3unlaNimReo7VW5iaE+s32T4RokI1PZpr7ytvJVSrwuobxF89MSOIwHjypwL/ubOnvJUfD9RwzsgUZvaPZ2b/eCRJ4uU1x9hS1MjwtAiiQzVM7hvL+MwY5r+4kWarHoHHuU7xI+Z2c9kljVbUSiXXTM7kmsmZcFQBeRMh4mKYdGfwTh78CpZeB5IIWiMZ4c+wg0Dbp7crNtaHWQPimTVAnmV2erzc9sleVhfUkxUbyluXj+ra5L61At6aIfspIZuGs+gl/8salYJ5gxKZ9dx6Spo6k8N08UxZd6Sea97fhVeUyZqnzxnCOSNTfIVZ8Bu+3l1JfrWJKyamd5lKmhkbGtRSmdWFJ1h0WPBvLgF7K1r9hC9AWZONo3WW7lt6h18i/3cqqNrNFA7xIYEByWSf5945I1OY3i8Oq9PD+1tKeNunfusTre/Sl6897p/fj9tmZKNSCkHhF6eCmjZHEEHbanPTaHaRFq0ClRYiujYpbY/j1+78wYnMGZiA2yuiUyt5YOlBPt0hz1TvKmsh3qjzp0YCvLz2mN+0fU95K8YQtZ/U6kUvenHyEASB2QnD+LlmDwBx2nBuv2wJZ+aMobG2lZFT++NWLsFleRkJBQ22CzBGRvje24EklqDSeQSPGEZMyHTMTsFPVuFL67K5XaQYIoiJiaG5uZkiVwOv1q/F5LUzPiuZrZVm/z18XHywIgpgjj6diup9eHXgVQHt6hhHlBKhnZI1XG2nRooAN+AuZU/Tp0yIu77bYzEjPZOHJk5l2dHDpBjC+du4mcTq/5jJOq8o8v3WfBrbrMwZlYtK6KCEVSiJ1YURptJg8chES5hae0Iz6d8b5eXl2Gw2mqTGoL/XuYNT8yIjI/0tS+Mn5bCiOLjGbjUFJoSeumcx3646gM3hYuHUQRjDTk7xkpDcfR0niiJTomL5WKujyelArVBww4hAYrfDXeInqwDqzG+TYLgGjSqRROONJBpvxCO2Udr8IFe8UEz+ulQKNw3hjEsnUna0ln/e8j6iV0SnV5N5Q3DbaF5ZHalhkTx8ziykJRJNTU04HA5CQ0M7tXFVVVXR0iJbDeh0Oox6J04f46FUSoRouu5OUSkUXDhqqH+5sq6V+/71LWXVzUwckcnjty9Eo+48/G2vCgNISUkhIiJQw0RqwskRcrn/9bdxI+IOB6UDVE5811oXx9r8LFjfAEASXsRq/BhjSDbQcUJfRLK8AKpsCDm/S2KtT1JUh+XOk46GCD3e2HDw1dolrXbyWwuweQP15N7WvV3uK7574ImIoa5gMpkYmRJPcYNMIioVAuOz5K6P5ORkYmNjyZQkPqkuZ2+dfD2ckZ1DdEj3nTQKhYKMjAy8Xq/foP10UFEYfP2Vt1tWKpUnlUqoUsrnwbV/O4fL71+EUq1EqVSw8LF3qGiUa9/9JTUsffDyIN+uvxz8hAOtcj16sLWMNH0MgyI638t7cWL0Elb/BZw/KpWk8BAO15gYlxnNYF8iVm679LoPrxnL+1tKCQ9Rc+9cWYKYE2/gygnpvLelFEGA6blx/PMnuQd66Z4qXB6RS8am8uJquQ0rPVrPbN+Aev7gRA5UtfHaugBDX9FsY2a/OOKMWowham6e1nmQMzE7hnGZUWwr7jyTEW/Q8u+Lh3P9h3JKV0fvoI4Km64wMTuGiV0oFn5vfLu3ij99LnsfCAK8evEIpuXGsu5IA3qNkkcXycbML144jIe/OUR1m4PzR6Uwqe+p7+vaI/UsP1BDapSeG6ZmnvagGICK7QCkCvVkCVUUSfIsZ1ZsaLe+TFdOzKDR6uLVtccQJdCpFQG/Kx9+63aiFXm1PPlzgX95bEYkfzkzuPWrIwHbMenx4+3lPPtLoOVBAKxOD602l9+EXkLBOsUYIgUHLV65kMuND8PQPtwgZ478X1fY+R+ZrAJwmjhLsYHPCUSYH642YXa4A0RgN/hwaxkrfWqko3UWHv0+n3euHN15xZL1AbIKIH8ZZM0AjwP6nwkaeUBQ22bv9NbbZ/btss3um71VfmJNlOCerw7w9Z4q3r1qNA8t6M/D3x7CK0poVQqWH6pl+aFaVhXU8+3NE4IKgKIGC+9sKmFQUjgOt5e0KD2PLh5Is9XFv9cUYnF4uGJCOkNSIgjVKrE6AwVXXnUb0aEav6deiFpJUsRv6CdydCV8eiGzJS9vaUaxKetuBgwYxNyBCTyx/DBmh5tLx/VhYFI4Dy8cyOScOJqtTqbnxhGuP3EyV0fF2okQNFPrNJMZYiEzNtTf4tw/0XjC71/SaEWnVnRqLcRX7Cl9rS1HaoNVZR1Vf0c7GLZ3pQrsRS96cXJ4cOB5jIrKxuS2MTNhKBGaUIZPbh8iMYYmnsdisRAepSMuTlYkx4SeR5P1W6yufSiEMBQKPbWm18CXrJYT9xlzk5NZUSUHzMxP7UdyqFz7JSQkYLVa+ahuKyavfO8vsVdx7cBJtNoE+kXEcUVO5+fJpXNGsWFTIXVWK625Ap52fNK8Ef05M30kH1d8jISI5FBDu1uhW+z8jOmIa4eP4trho0643m+Nf3y8mm83HwLg49V7ePGehextKaba3kxySDRXZMzAqNHxxuTzeObAWgQE7h067ZQ9rCRJ4quKLRw1VzEqKpu5ib/Ok+u4P1WKkIYKFR7kGnhQ+NBu3/Pgo2djeuIbth6RiZKUhAjGDwsk/+o0ai4847dVZdTW1qJ1unhx5HgKzW0MSevDiIx2QSdCFzVqh7+VNj9Ii+1HIgSBxTP3I81ciUVn55kbRUSfstthcyOWmdsbAPgTA/GRIzExXdfUoij6ySoAh8NBvDqCcmdA9b1yawkXpE874fd9/v21FFfKVgsbdhXx9cp9nRICAdra2jotS5KEUqn0eye1mGy4lCJNg0HUySKp2CIFt13ajZG5PeCfKUgt/OfInwk3XsPVmQuQdIvA8Z3vVQXY3pePk7ccwXBv0Ga2rTxE0bL95BrCECN1DM5J5ppzxpNXU8cnO/YTqtVw05SxjJ47hP98ut3/PqvDg9KkR0A4Hv9Aou63Nf+ura2lsbGRc/omE6aQcCg1zBmUQ25sJFVVVSgUCmJjY9GrVHxy9nn8UlyERqlkdubJTaydDKHUHu3rM4/Hw5BJuWh0alwOufV67JzuvV8BXG4PFY1txIaHYtR3vqdofOMBp2+943B7vZQ3tAQRViWWwPkqIVFirfvDCKvelMBe/CaY1DemR/KjOyLnb4sGcv2UTFRKgYe+ORT82vf5eEWJ8VnRXD6uDxOyYwhvF4O+u6yl0/bUSgX/XNL9xatWKvjwmrHsKWth3ZF6XvOZLodpVXxy3Viy4gxsvm8GDWYnOrWC89/YRnmzDaVC4NYZ/7uz/MsPBhh2SYJfDtfx7pWjqTc7MehUfiVQYngI/+mKeDhJ7C5r5pr3dvrVclUtdp46t+ebZY9IGwfFa9EKHj7XPM772S8ixQ3kyonpPRJh98zJZfHQJPJrTAxJifjd2xqP1Qe31jVYOs+EPbpoILd+ugeHW2RKTizzBwU/RI+3ex2HBGwtbiavQ1tYXPpAXj5zAJ+sP8DY8rfxtNRx5V93MuuMc7l8fHrPOxoaPEPVPzsLAinVWFxeCmrNjE7vOcL7uE/UcRypNeNwezu3l0VmBC16JAXvffoZWtycl/wGumt/ArWOGf3i+W5/cAvI9VMCBWVxg4VbPtlLeZO1S6Jya3ETX++p5JKxfZiWG8uWoibu/iLg3bW/opUmq4sYn6G80+Plkre2U2uS24kj9Gq+unEC4Xo1i1/e5FdP/Xyoll/umsqQ5Ai/1xZA/wQj7101hieWH8bh9pIUoePJnwo4f1Qq47poPTxlHPgMfBHvsxW7mK3/EkafwZJXN7PHF1Txw4EafrlzKgnhuiAz+1OF2yuytqAetVLB1JzYoICCvOo2bvhwNzVtDhYPTeJf/Y+hWHYzOq+Tn/ov4bUh96NUKLh8fHq3bXmSJHHn5/v4dl81ggAPzu/Pdb7fttnq4pu9VejUCs4dmYJWpWRGvzj/dxQEOinGJIIrjQnd+HX1ohe9ODGUgoL5J2jbiI6O7hSZrlSE0j/+a5yeStTKKPZVjfe/JuHiSP0Sruqj4OKMGxCV5zEpIcM/qJIkCbvdjkMKfo7kRERzzuDOrUHHkRgbzkfPXMHRknre2r+HdWUliGroGxXNMwvno1YqGR09CpfowuGp5IfKB/FIDnRKI4MjF5/mEfr9sWp3YKKqzeqgrNTEpxPuocllJlpjQOUj88fF9+Hr2Vee9ud8ULqWN4+tAGB59W4EBOYkDj/h+7qDXq/HZrMRpYjhHM2l1BuqiQmJY1rcrG7fo9GoeO5v57E7r5wWk40xg9NPWkV1unA6ZYV9uEbDqOhYorTBn6dTpZFovJka06sAJIffhUYZbBVhdx1GAWSoVL7JRzcRjhdouXAhHrOA6pD8XBqXncGZUzL4Zc8RDpsa+CB/Pz/86ygvXXAmI1K7nygVBAGlUonXG5gYm8wk3m3+HqXOi60sjD3FJrjoxN/XZJHJWUWsC2Wag0PuQqAzYXU8ue448qtr2b3rIAlhIZwxuD9JSUlkpcZg6B9Gg85X4yogdlx0EMnYYltJWcvDSJKbgZqIoIF2o1vH8vJVzEkYQ0rEv5A8NyLZPgfb+4GVnOugHWF17FAlj9/wjp8IHDYxh3ufmkWdycIV73+FxSnX13srqnnvoiWEhmmx+qwQQsO0DEscwNWRV7O2fi0ahQajysgHpR+wIHEB0dpfXy8cJxYVCoH5fVNJSkrCYDBQWFjoT+uz2WxkZWWhU6k5M6dz4NLJoslsY1dhBcnR4QzqE6wEW74hj2ffXY0oSdx68VTGD4rz+8X95ZPrObi+iLjUKOZd1n3nT6vVztUvfUlRTRNhOg0vXb+Ykdmyol1yF4BzI6gyEHSz0KpVjO6bys5C2ew9MiyE/qkBbz9RFBmqT8Ut/ExWSANVzniGR3aTgP07QCasTtbD6nffnV+NXsLq/yCiQjVUttgZkGgM8pg5rrLYWtTEFeP7BJFVAKP6RLKjnYG1RqXgmsnBA+iuoPb53YzNjOaMwUlUt9kZmxFFhF6+uYdqVX6Fwg+3T+JARRuJETqyYv9YebYkSby2voitRU0MTg7nztk5XZoV4zNQbo/06FAEQSDeqKPF6uJgZROZsWHEGjr3Q58KdpS0BPnpbC9p6mn1E2PKn0EdAjX7icmYyt0ju04h6Qp94w1/WMrh1JxYXlxViMv3gJ3dv7NB66wB8ex8aBYmh4ekcB2CICdhfrStjOpWO326UYyZfB5LKoVAVmwYj581iIyYUB6yPY3asg4UMEfazpnfG9hZMpo+0aHcNC2raxXNvCehrQoaCiB7FmGTbyZ+x2bqTPLDPkStJK2b/WiPc0am8NG2Mlrt8oCjqtXO1e/t5JPrxoGPwPslv46kiHQWz38Gdr+LVxfJFYVT2CwNBmBFxUE+qt4LfcZz49SsIMJKo1QEmYE/+M1BP6FXUGtmSEo4edWmoBZGt6/VNzE8hEnZMejUChxu+W9xBi0R7e4P9Sann6zCR8BVtNjQqsOCWv3MTg+Ha0y8cKHcYlzT5uC8kSl+X6dPrx/HVe/u4MeDsvfWDwdqWH77JLLjfuV5Z+zglxKejMsj+okcALPDw6GqNhLCA8X3psJG7v1qPxanh1unZ3PDCZL9vKLEle/uYPMx+TpdMDiRVy4JzLo/sPSg34Nw6d4qniz8ExqvfK6485czde5FpAye2qOqa095K9/6UjklCf7502EuG98Hryhx7mtbKPaFIKzIq+ODq8dw64y+aJQKfjpUy7isaP9EhyhKbC5qZEVesM/YqsP1nRSUvehFL35/CIISlZCMx+0lVDMUs3NzhzVEtOIbDE+8IUhhLAgCISEhnBE2mA/btiEhkRISzaz47pU5xxEeFsLowX0YOSiNzUVlSJLExKw+KH3eiEa1L1VLG8Mlme/S4ionRpuNXvXH2S8AeL1eamtrcbvdhIeH95jilRoXweHygD9VamwEKoWSeF0ElU1t1Lea6Z8aT4jmxOrZnrCvpbjT8q8hrNLS0mhoaMDj8ZARlUFo6MlPDI4c+Mfds41GI1ZrIFzHYOj8fE6J+DPxhisBBWql/Mwxua18U7kBCYkJhvF4PMVB57FCAFVCC/bb4gj/u5cx/fpx1rVTUamVlNdX8o0vTbDRauOWZd8xeUA6Q+ISuHTQsE6fLwgCqampVFZWIooisbGxjI+M54Wvd/nrnP7JJ9fxcMH8ERSYvkF7Zj2CEnawg4/LYrikz2wA9jQf4Yi5gkHGDKIiI7HZbJS1Wbhv9TZ/DVtttvHIOYmoVErOmzWcp7YF/IQN7XyTvKKN4qbbESW5nipwtJGr60+rs4KVbSnssMq1sEeS61hBlQ2aUUjtCStV8GR/UV6ln6wCKDwoq/GO1DX4ySqAg9V1qHQq/v70BbzzxlokCa65cTqhYTomhU1iRMQIHjj4AAUeufshz5THPwb9o1sD9pOFWq0OIhbVajUOh8NPVgHY7XZEUQwyKH89fwuvHd6KQa3l6bELmRDf8wRzXYuZS577lIY2+dx96LwZnD9Zvke2Wez8882Vft/W595bwz9vnUyUUVawO4x2Rt86lExDUo/m7V9uOkBRjVz/WRwu/v3DZt770wVI7nykpgsAn51K2L0IYdfx0vWL+Grb56i0+xiVvohogzxekCSJ+vp6Lghvxqvf6dt6KWrv98BVp3aAewG9hNX/PVS12rnwza1UNNuJCdNw5YR0KlvsbClq9JuX45up31naTHp0qJ90mT0gngaLk2aLk4yYMK6elEFSRM9JFh0xOCXc38LYFYw6dZByrKLZxg8HaogO03DuiJQgtcJvjY+2lfH0z3KL5MbCRhSCwD1zc7tc987ZObTYXOyraGVMRpQ/ov5YvYUL3thKk9WFQavig2vGyGlfp4mhHY7VkJRuPH1OFgoFTLzj123jBNhd1syyfdXEG3VcOznjtFoYByWH88WN41mRV0ufKD0XjO7aw8egUwe12/31u0N8tE1+GGtVCv62aABvrC/2Bwm0x8Vj0/wJfm02N2GVO/yvaQUPgyhm6QF5ZqSg1sTbV3ShlAtPgevX+hdVwPtXj+GJ5QU43V5um9GXeKNMgDRZnNz71QGO1JqZ0S+OB+b3I6/GRGyYFoNOxVUTM3h+VWBmeEtRE212N00WJ2e9stnfIps/dTIP3Hw9e47VsfnoLv/6m8TBtCijiQQGJBm5ZXoWr64rQq1Q8OQ5g4PUWo0dFGvzByVy87Qsbv90Hy6vSL8EA0tGpvD5znIOVrUxMSuGty8fzUtrCtGqFDx4Rn9USgXLD9aw+nA92XGhZMSEUuIjSxKMOtJjQtGpleTEh3HUZ0av1yjJSTAQb9TxxmVdt4q0J8VdHpF9FW2/nrCaeh+0lkH5dkgdA1PvR6NS0C/BQIGvJU6nVgS1VYuixM0f7/YTnP/8qYBJfWMYmNT9/aug1uQnqwB+PFjDI20OPwnWZm+vgJAQRHm5RoriXOdfqfrOjf7ntfznitHdJhN2tGE4rrI4WNXmJ6sANhxtoM3upsXq4ukVR/CIEnsrWsmraqOyxU5pk5UBiZ0jnrcX/0pSvBe96MVpwWw2U15ejiRJaEPuJiaiD05PKWbnlnZriVQ3N9FkttIvJY4QjRqP6KXB4CZHSuVfURm49QpGxPUlVHXyShuFIDA5u+cBn0EdH5Tut7u8il1lVQxKimdi1u/bplJVVYXJJE+yWCwW1Gp1l6lcAE9dt4AnPllNo8nGeVOGMCxbnrD4aXcBD3+4Ao8okpkQxft/uqDLlp2TRT9jCjuaCtstn9hrsCeoVCoSE3/bdquOKGhbSa09n8SQQeSGd6/c6gnR0dGoVCrsdjthYWHd/g7qdqoqj+jl7n2vUGqVuxPWh0Tz934PU2l+hRSV/NwqcBgpsEUgqeDP31zJ1Di5PquobqDJEmhB9WhFahQWvig4xBcFh3B6vVwztLOqMSwsjH79AmqcWODJS+fz6cZ9RISG8OezAm14+xtreHDbCixuJzcPGseijD40u8qI0vSh39Bopqvj2WoJkKCbGvZzSZ/ZrK7bzZOHPwJAgcDjg69jTHJ/fvhlg5+sAthSVed/Vl85bDibKsvYXFlOfGgYf5ky3b+eKFn8ZBWAExF3+BN8U1HK143rAJgdP5o4TQwv7thCi8PB+f2H099wvy+gIQ3B+DCi5GVv8xe0uMqJGD4AjVaNyynXG0PG9wUgOy6asFABj8aG26omOzIBrUrFoKFpPPfqFZ2OZ62jFrOnjREhzWgEL3vtXtrcbb9aZXWcWHS73URGRmIwGHC5XAiCgOST7mi12iCi6GBzDc8ckI+Hxe3k9s3fsGvJnd1+BsCKvUf9ZBXAR+v3+gkru8MdFDIkShJ2hweMcNhVyX/aVuNu9pIcEsuLI24lUtN1TdrRJ8uvgnX8EiCrAMnxI0LYdTQ4vyE3/S8oBIlW51KK6v6Os2m4/AzQakEd3Alldmwn3vDHEFa9KYG9+K/irQ3FVDTLN/5Gi4v3t5QyNTeW++bl8uj3+YgS9E808OzKo37S5W+LBrAir87vsTM0NYJXLsntMQ3rVGB1evh+fzUqpYJFQ5PkaHagts3B4lc2+/2Gdpe2/Lp2uBOgY6vYoeq2btfVqZU8fW7n2ct3N5f4fXjMTg+vry/qdmB+MpiQHcOLFw7j+/01pEaFcM+crgm0/xUcqTVz0Vvb/YmShXVmXrjw9GYch6VGBJlubylq5NW1RejUCu6b169Ltdeaw4GCwukR8Yqw/t7p3P/1ATYVNlLfLvFtkk/V859NJfzjx3zeU2UxRXlQfq+k4qAUkN5uLTq5QbzD7eWXvDoyY0I5d2QKg5ID5MZjP+SzpkDevw+3lfFLfh21JgcCoG2nXjqOWIMWg1bF17srg/zcfthfwwPz+5MYbUCtgONvi9CIhCUGZtbunduPW6f3pcHi4Ktdlbyy9hhXTkgnVKvisnF9+Ot3cvJOVKiGhUMSSY3Ss+HPkdSZHOQmGPhwaxn/WH4YgI+2lfPqJSP44oZAm8qq/Dpu/niPf/ny8X2YmhOLV5S4dnIGYVoVJofbr9QCuGhMGsknILljDFqs7QzjS5usmB1ufjpUi16jZP6gxC5TJdvD7RX5YGsZ9SYHi4YlySTT+R90Wu+9q8bwzIojmB1urpqYQWS7EACXV/STVcdx/F7UHcJD1EEpgxqlglBt4D557eRM/rLsEJIESeEhOCY8gnrtw3zomU0VcquezeXlpdWF3RJWI9IiOWdECl/vqUQhwINn9EenVpIUHhIUYhGpV6MU4K4v9gUFW2woDBj6Hqo2EaJWYm+XyDq0O6P7XvSiF78ramtrkSSJ/PpmXtx6CKsrgSsnLeDM4XE0274FwG4/m7Of+8FPujx+fTqfVK5kc6MTj6TkvLSJ/Clp0W+2Tw5POW32dWhVqUSEBAbW6wtLuOnTZX4j+GfOnseZQ/r/Zp/bEXZ7sGeWw+HolihJiY3g1TvO6fT3137ahsen2iiubebHXQVcNKWzOudkcU3mbJSCgqOmakZGZbEoZcxpb+uPwKGW71lX97z879bv8EpuBkTMP61thYeHEx4eqG++qdzApoYDJOtjuSFrcSeytM7R7CerACrtTTiVVxMZexa/1D5DsbmM7xvjcIoawlQ6+htT8IoiD7/4A+t2FKLUKIjqp6HZ5ULskNWztaq8S8KqI+oczZSGFTD5DD3npU4nXBM4f65bu5R6uzyx9tz+L2kR9+ORrCgIYU1jGm2e4O+TEiKTcevr9/n/JiKxoWEfY6L7kxUf3HqfHhN4nutUaj466zzMLidltiq2Nu+gwh3HnITRqJVxRIbMo8X+MwBh2lHoNQO4MXso8xPH4pVEMsOSuPr7pawtk8NSvj6cx08XXUFK9NX+z9hU9yr7W77yLa3kns//xJ7PrETGGTn/5pkAmIVWEkbX4JRcKCQl9/U/s8fjF6+L58boIkbp5bFgmasGj2inzNLMtoYSMg0xjI45MXHd1GJl6c97UQgC5y4YQbghhKysYPW6RqMhPT2dxsZGlEolsbExuEU7aoVcPzY5gkOF2twO3KIXtaL7cWlEaPBvGNGOrE6IMTJzXA6rt8mTxuOHppObmYTFYuYn617cPpP7KnsDy6u3cUn67C4/4/xJQ1ix5whHqxsxhGi5/Uw5WVxQpgabLyiTqTWZKaj/N1Ea+RVBkKiyvkWU+DL47nEKTQ5e9Xr/20I1v98YuCOkdt5xJ7Pu/zp6Cav/Y7C7gpMlJGDdkQaGpkSw7p7pNFmdfLmrkk98qVJmp4e7vzwQ9J79Fa1sKmz0J5ydKrYca6Sg1sy4zGiy48K46K1tHPC1DS3bV8UHV49BEAS2FDUGDRC/P1D9uxJWE7Jj+GxnhX95YtapG6R3VBP9FqTe4mHJLB72x0VA/xrsKG32k1WAP83y16LO5OCa93b5B9b51SY23jejE3GRk2Cgup2aKic+DI1KwXMXDEOSJD7cVsa6Iw0MSg5nVv942uxu/vGjTNTe6r6NO6WvmZEqcDR5CcWbA8VMT6rA9rjjs73+FqsvdlXw0x2T/Wl/x1vBjuN4C50EQWRVpF5N3zgDfzlzAAqF0Kml8PhySqSeFy8awQurjuLyiIxKj2TTsUam5wZmNd2iyIVvbPMfk7UF9Xx10wSumJDOwCQj5c02JmTF+BVACeE6/783FAZHDG8sbOSMwYHZ347tqYeq2lh688Sgv/18qDYorfC7/dU8sjDYPL8jbB3CFr7cWc6q/Dq/EmrhkFpevrhnc9v7vj7A0j2yOfGH28r44bZJZLZrMa4zObjri32UNFiZMzCBB8/ox1Xv7eRAZRuZsaF8cPUYUiL1XDg61X9PGJBoZFQf2YvM7HDz3uZSHB4vF4/tg9cr8fmuckK1Kh5aMIDnVh5BpVTw+FmDghSAl43rw7CUCKpa5bZoQ+hMGLwA9bpy2BHwbTueMtodnj1/KHfM7ItOrSDOp+BLi9bz3AXDeGl1ISFqJddOTmf28xs6qQuFDsXFZePSsDi9HKpuY1ByOH/uRlXai1704vdFvqWRp4u3U+ewoQhToWpQ8+b6HUzKvocBydcioOKip7fhEWXPl4S+61nX+D5JOpgdF8Iv9f35snwz12fNRa86dTsCryjyXWEBZqeTM7JzCVPXkV+7GK8kT+Ylh99LUvgtAPycfzQotXB53tHflbAKCwsLMtHW60/cat8RHeszbRdJb6cClULJtVndBLL8D6LCtjt42brrtAmr9tjUcIBXj30DwIG2IlxeN/cPuDRonSitEaMqFJNHVriEKnXEaiMwqPXM7fMUVo8TsXgV5bZa5iaOIE4XwfqdhazbISvYvC4RQ4nEnVdO5Kjbwlt5gcmyIXEnTqWzeRzcufffNDhlG4AdzYd5bdQ9KAUFTq/HT1YBjEwowSPJ+yliJyu0nj1tcstlnDaCfsY+3JYjE6KJIcH+pIk6mZhaNKQ/xxqaWJFfSIiopL8UQUlFIxmp7TpI7DXcs/8VvL7gnhpHE1dmzCcr5hVa7b8gSm4i9bNRCHIN0Sc08D03VQSSIS1uF/vqqkkxBhTT1bYAkQYS6tR67nj6mqB9/aZqA05JHmOJgpf1zTuZkNC9P5ReIfnJKoA+GgvfVH/I3/MEbL60zUeHLeDCzO7JQ6fTzS2PfEZljXwtr99eyDvPXIaq3bW5o7KSv6xejdPj4bbx45mQIfBR+R3YvS1khE1kXvJfGROXSr+IOApa5UngCzKH+cmqFmc5h9t+Rqc0MiRyCfvya9m2v4T0lGgWjRnAT7uPkBRt5JELgxWGj922kIXTyhBFkTFD0lEqBJkYzw8FU6AeVvVAihn1Oj6592KqGtuIMYYSFuK7D4ecDZ5CcK4CVTprj13KPSve408LRKLazU16xeD7Wmr0jbS69LiFAxhDRpFgvLHbz/6t0auw6sV/FSaHu8u/t9hcpEXrSYvW88OBmi7XaY8w3en99F/srODPX8sEmEap4O9nD/KTVfgGxXUmJwnhum4H6r8XFg1NQvAZTg9ODueiMQFPgMI6M6VNVlYdrmfdkXoyYkJ5/oJhnRK6bp6exZYimZBLi9Jz9+z/fw3+BiQagtIeB/TQPnUqKG20BqlAqtscNFtdxBq0iKLkbxV99ryhPPjNQQpqzLi9Ivd/fZDzRqXwp1k5AGwrbmJNQT1rCuo5Umvin2cP9qthTITxqOcKRi+cxOzkcN7MquPTHeXEhGn9SZvd4WBlGxISG44GCDqby8vushaZsHKaWTIswR9coFQIQX5R7XHW8GT+euZA//KsAfHcMyeHpXurSI4I4alzAqTtGYMTcXtF7vhsH6VNNr7aXcW/LxrOmb7UxvxqUxCBt6ushVabiwi9hlHpUYzymcFLkkRhvQWtSuEn2AYmhbOxnRpnQFJw+1hHJU5X7aphHXy/DCeRpmcMUQeZ7AuCwk9W4fO1euocT4/JfGsLAko7m8vLtuLmIMLqoW8O+Vv33ttSSnGDxX8fKm6wMvWZdYzPjObFC4cxZ2A8FqeXmf3iCNHIhcoV7+zw+199uasSjyjSbJXvrZOyY8h7bF63+9apLToqg6vnpbC6ahuHqkzEGrTcP+/EpqJp0Z3vh4uGJrFoaBJ1Jgezn1vfSSEmAOeNTOGrPZWIEsSEablsfHq3CaG96EUv/jg8XbaTWrcNlOCN96CwKlDYlLTY7IRq5PYorXqXTDirRfoPDCR8RGjsxGnNNLpielQZ9IS7V/3MsqOyqvatvbv4YKHTT1YBNFm/9hNWaZHB9/u0yN/mWd8dkpKS0Gg0uN1ujEZjEGG1vaqSBrOF71fnUVTTxKQBGTx0wQzUHdLBHjhvBne8tQyTzcnE/umcOfr3I9j+FxGrzabIvCGwrOv7m2y32BIc8JLXKpMpx9u5BEEgRKnliSHX88rRZTS2WbBtCuXabz/jtkumMmlEFl7Jw46WfVTbG9nTeog2txmjt8OkuChw3oQxSJJEjDGM7dWVDI1L4JYRY7vdN6fXRaG5kmaX2U9WAZRYa2hxmYjRRqBCYEGfXH4sky1BdMrgut7bbjB+S99zmBAzyL98ZfoZtLmsHDGXMyQii/PTZvhfu2vmJFxHrPyw7iBfUs+PPx/k3X9dTnKCfO3sbD7sJ6sAtjYe4sqM+QiCkkh9oIZwed2U2+qJ0YYT4VOF9Y+J40C97PWpUijIiQqeYI8L6U+D81hgWde5ptArgxVH+hO1EAs6HKIGncJHcklw1OLB5gnUsl+V7e2RsKqoafWTVQDF5Y3UNZr9x8Tt9XLjsmW0+Yz971+xgofPPIRSbGBKiBmF93t2HDXQx3Apn824lLU1RRjUWqYnyd0FFncDX5XdhlOUa8b8uh289kSKn1y/8YJJ7Hr+9i73TaEQGDc0uC06JCSEm/uexYMH3qLNbWWAMZ1FSRO7fP9xqJVK0uODiUxBEBCM9wH3sXlPMfe+9w32OAXvbprJn+d9Q6TGhkOKIFnzF1y+kl2v1xMVFUW00HOrYy9ODr2E1f8ovt5dyRsbijDo1Dy+eJB/sGnroLDCN6g8f1Sg9/6mabJhc4PZ2WldgCsnpPeY3OX2iryw6igHKtuYkBXDjVMz/X28S/dW+tdzeUV2l7agVgq4vfLNJFSjxBgin1aj0qN4dNFAPtxWRnSohn8uGXzax+NkcebQJP9g/zi+21/NnZ/vCyIY6kxOHv7mUKcEwJgwLT/dMZkWm5uIEPXv6rnVE47VWzhWb2F4WoTfQ+mPwMg+UbxwwTC+2l1JglHHA2f8NgVhv0QjCUZdkLH3LR/vprrNQXWrnQVDknj+/KFYnV52l7XS2K7174VVhfRPNJATZ2C5z8wbnyn1ffP6cdO0LF5bVwTAWcOS/G18M/vHM7Oj2XtLKSy/F6wNMPo6GH4J9399wK/CiQ7V+Ik1pUIgN1YPn18Gh7/jEl0Egxa+yk6pP+Myo3nqpwI2+hRox9vIcuMN3Dwt0NZX1WrH5RG5dUZfbp0RXFyWNVlxekRWdjDNXplf5z+HU6P0aFUKnJ6AWXp7xQ++ovL2z/bxvc+k/e7ZOdw2sy93zc5BkiQOVcvX8aVjg01dFw5Jos3uZm1BPTnxBu6Y1bn4nTcwgbOGJfHtvmoi9eqTuoZfv3QkZ726GavTi1al4OEF/bnts71+EtSoU51Qudg33uD3whIEWWnXHtWtwWq3wg6plF5RYtOxRp7++UgnVWeL1RVk1l7f4T656VgjTo/3lLzbwvVqvrtlEg0WJ5F6jb8t+nSxs7S5E1mlVSlYf+80EsJDuGpSBmVNVkb2ifrVwRC96EUvTh6SJLKp/jXKrNuJ1mYyPeFudEq5vb3ZFXxfklSyz8yE7ECbzZ+XTOXqD5fiUoLTpSFE52q3bR0PDTwfdQ8myE1OM68WLqfVZWVJ6ngmxsrPaI8o8n1hgX+9SrOJcrMRfbtbkVoZUHhcM3EU1W0mdpZVMTgpnttndJ9G+FtAEARiYzuntz6ybhUfHZITbJU20JsEvtl2iKzEaC6bHqzEHZGVzJp/3IDV4SIi9NT8V39L7CmqxGRzMi63DzrNHzeMGhF9EV7JTY09j8SQQQyLOu+32W5UDh+X/YKIXGccLXLyTejzpEW9jYSHlPD7SDBeTVmVk9XLvXglHbg9hNe38PCLP/DNv69giyWfantgguyL8jW8P/phhvVLZu+RShQKgVsumgy+c+GG4WO4YXhwC6bZbKa+vh5BEEhMTERUC9y1998UW6tRoEAjqHD5zMqjNeHo0VJYWIjT6eS2xP5MTczA5vUwM/UiVtbci93bgEtUYhNDAIlpcSMYFy0rxEVJpNLWQKhK10lN5pVEyqy1hKlC2LgjQBrZ7C72HCr3kzNp+uD6sr2C6jjaXBb+tPcVym116BQaHht8NSOjcnjjjEU8uWUDzXY7lw0ZRk50MGE1Oe5mNAo9ra4KMsImkmnoTLJc2mcO+aZSiixVZIYmcVmfuT3+zoKgwhz6BBbzX1ALbtbZRpOonwGs9q8Tp+vZbzQuOoxQvQarTb5vhRtCiIoIkM82t9tPVsnHUqLR1MyV8Y1EKOXfzqn+hJKWqej1ehb1GRi0/Vp7np+sAmgR9iNKSb7pOti8t5grzuqe4OwK/YxpfDbhr5jcVqI0BhTCr6vPNu0pQvBpR2qbo7j3sysZkxnB2xdfiVJQYbFYEEWRsLCwTp5Yfyj+H+sJ7CWs/kvweEWeWXGEXWUtjOoTyZjMKB74+iAWp4cRaRFsKWryK0eu+2AXm++XWf+Lx6ax6VgjXlFCq1Jw24xsFg9LDpphj9JraO3g1aJRKZieG8sz5w7BGKLB5RFZe6QelUJgem5cEDHz0upCXlkrEwAbCxsJ0yq5bLzMWnc0ae8bH8Zz5w/j6RUFqBUK/rpoIPp2D/ArJqRzxYSejUB/b7y5oahLNUxXRt74HqZRocFN9l5R4p1NJRTWm5nVP545A08sYT5d/JJfx80f78btlYjQq/nqxglkx/1xiYu/RwtjeIiav505gBvbeSbtKA3M0ny/v5qxGVFUttiDyKrjuOHDPUTpg/2FFIJM1p4xKJEvdlbQZHVhcXpxecQgwuCLXRUU1pmZlhvHxNWXQ41cHLPsFuq06Xy2M0BeNFldzOofh9MjcvGYNAa2rIbD38kvOloZuu9Rht4qm7snRwauBVGCM4cm8uIFw/3X0qvrjvlDAM4dmcK/zgt4pr2w6igvrJKl8h3JmKzYQLJQckQIr182kpfXHCNEreShBf07tVHuq2j1k1UAz606ytWTMgjVqk5IOF4SU8Ql4rPQqIPmv0Nc8PoKhcALFw7nyXOGoFUpTurh2zfeQN6j82ixujDoVKiUClrtbl5aXYheo+SJJYNP6GH174uG89j3+dSZHFwwOtWvJDuOc0amkP9DHho8KFTabq/lenPnvxtD1EHkqValwCuKHO+E7ROtP62gAYVC+M3I5YyY0KBzXaUQ+PdFw0nwKUL7Jxrp34Xhei960YtfjyanmRePfEej08yC5FHEaQ6zp/kzopUeEkP6kG8qwI2KVlclakUIsxLvA+DSviN554j8fEjUGbln7nRm9+tLqLZdPaERcCnlm83PW0Yya+w+ogwCwyIv4ObcS1AICppMVnYeqyQpysiQ9GAT74f2f8jBNlkBs7O5kHfH3k6WIRGVQkGcPpRaq0zeC0C0/kyM6jqabT+gVaWSEf1UYDeUSh4/s2sflz8KJqfTT1YBePXg1YHKAXWt5i7fo1YqO5FVLU4br+VvxeZxcXnOKHLCOxNjvxWe+3YD76+RW/MGpsXzzu3n/2GklUJQMjb2tzdsHhSeyTim8HPVbjx2Fd5GNQmT/43oUw+Vtz5OpH42b2zcgff4zJNaQJVp4Y7533Gs9XmihSxCFblYRXkCJUwVgkatYuYVWezIO4woSTT2aQ36XK/XS1NTE6IoYjAY/IEFAKWlpZQYWym2yrWNiIhepWeoIRW1oOTqzAW0NDbj9JEjHpebSVGxJCXJk31VrnhaXCAioFZ6eGTAQqbEyS1kXtHLXw79hx3Nh1Gg4M7c85mXKJMgHtHLQwffZE/LURQIRI/pQ1uAzyE1MRDCND1+BHWOZjY1HiRFH8st2Z1Tu3+s2Ua5TZ6UdIgu3i1ZzsioHBLCDLwwZ0G3v4lKoSVXcQ4mlwmNRYPX4EXZQXEYpTXy+qh7sHudhChPbuIqPnwRXuNCrB4bZ6vD8EoihaZmVtccIcsQw1+G9txiajSE8MxD5/D2p5tQKBTceMlkQnSB+1u4TsfMzExWF8sJnHFaPUd3JhCxOM+/jlZhQ6OsxuPpnNocoUlDQIHkI081nkQ/WQWQmXJ6BvEahYoY7W+jIu2TFIXaDNpmCZcRIvVh/GXeOSgF+T7QnTffH45TaAmktyWwF93htXVFvLFBvqB3l7Xw7uZSfyLFpmPB3jLVbXb/IHzuwAS+u3UiBTVmRvSJJCOmc2yuQiGgVStxt/OSee/K0f7oeY9X5Ip3drC1uOvo9kNVwWblh6oCkvJHFgyg1ebmcI2JqTmxXDkhHZVS0UnV9FugvMlGUaOFwcnhxISdvorAoO06+vickSknvY2nVxTwxnr59/pydyXvXTWGqTm/T1H0zqYSv2Kt1ebmi10VPPgbKZ3+W6g3O3j0h/we13l17TEW9XAeNdvcxBm0/qS2RxYOIM6o4/oPd/uN8lcdruPrPZX+dtB/ry7k2V9kE8b/bCrhQ52SwDyVhM5UgiBE+tU/AhBv0HHWiGRGp0fBbmvwTrjk5dJGK6224PZctULhJ6ssTo+frAL4ancll4/vw5CUCMwOt5+sAjhaZ+GMwQmUNtoYnR4ZpNACmJ4bx/TcOERRYmV+LQW1JuYOTPATwyvza4PWVwjCCQkhANqq4NOLweNTBdTlw52HoIt2lBMponaUNHOoqo0xGVF+hdtxA3STw828QQlcOu7kU6jijbqge1JHXJNSxeXht6JytlKSvIgZRecHFTX4lrpKp1QqBD64ZgxPLD+MzeXl1unZOD0ib/oUrQ8v+P2vtSO1Zv7+Yz52l5dbpmczvV9c0OsDk8J59vyh/GdjCRUtNtrsHp5fVcjglPBObcy96EUvflv87eCn7GmRJ+0qbYeYE59PirqZZHUreI4wKETJIUcybkmFyRWYLHho+CwmJWTQ6rQzPSkbo6Yzga1VBcruqoYYPvlpLrsfuAWNbzBa22Lmkmc/odEkewc+eN4MLpgcmOw4Yq7y/9sriRRZaskyyKTWG2cs5oG1KzE5nVw/YjSD4hKAh0mLfPg3P0Zl1iLsXivZYf1RKbqusU4ErVKJRqnE5Q10DggiaNVK5o44eTuGq9Z/zsFm2Qrjp4oCVpxxHTG6337Q6PGKfLQuMOmWV17HrmMVTBqQ8Zt/1h+JrSXlfLW5BI8okzERIRZUikCrm4DEJ6XLcHmCJ0kWT9xOSpKsqlJKRVyRHMvrFUlEaAzcmXsBZreDf+b9gMdHfL1U8AuzEweSFiqTDuXl5Vitck3V0tLiJ6vwkVkqIVB3aAQPY4zHODs5mmTj+YSoEqhorgjaH1EUcYteSszNuEUvIoGJS60ycI7uaD7Mjma5dVZE5NVj3/gJqx3N+expOep7TcI8qIaJbWNpbLFw5szBDBsYXFNc2GcWF/aZhdltY1tTHgaVnnExAdXQior8dvIVAaVwcpNhbW1t1NbKtZ3NZkOSJFJTu06x7ImskiQJHMtBbAbdXARlHEpBgVEtXx8Obyt/HTaDf4zs2bC9PYb0S+alRy/o9vXHJkxgUEgITlHE0Sjw/WYLNdO2kRgu/9Ye0YCXFIzGzpNuMbpM5iY9wv6WpeiURllpdl4ZW/YVk5kSw+2XTTvp/Txd/JR/lPe378Go0/HQ3Gn0iQpunz5v3nAaWyxs2lNEXYUFp8vKOx9v5q+3nIFK+evUW73oHr2E1X8JBXXBs0ft41M7Yu6AhCDFyMCkcAYmhfPh1lKufX8n0aFanlgyOEiF8+Q5g7nri/24PCIXjEr1k1UABbVmP1mFL7r9LyaHXx0wMTuGtUcCBnUTsgOMdmSohnc6tNH9Hlh/tIHrPtiFyyMSHarhq5smdEnOnQweXTyQa97fSUWznfGZUcweEE/feAOT+wYIJ7dXRKUQulWQbGuXMidJspfS1JxYNhU28vcf8zHZ3cwdlMDtM/oGJZWdDo63VB5HeMjpFYP/S/huX3WQCkYhyH493+4LFPvVbQ5G9onsZCrdHkqFwOHH5uHyiH5yyNrB5NvSrpVqTTsvJFGC9eGLmdjqKzh1EYT3m8oDLhdP/lSAKMmf+/GOcj7bWc5FY9OIEPpzW2QO2pajIChg6p/523d5vLdF9h45ntAWE6bhxmmB2aKWLtLo3F4Rh9vLv1Yc6fTazdOygxIJu8KfPt/Hdz4l1cCkEr6+aQLrjzbw2rrioPXOG5lycmEBLSUBsgrAXA2ONtBH9fSuTvhufzV3+Fr+1EqBD64eS7xRy66yFsqbbLy+vgiPKHHx2DSeODu4pfBIrRmtSkH6KV7b9q9vIsQpK/Qyq5ZxVdRA3m2WfSniDFpm9Y/jwjFpsi/Xhmdg2+ugj4azX4PkkeTEG3jvquB2hNmnGELx1e5K1hTUkRNv4Jbp2ahPslARRYkr393hvx5u+Gg3a+6eSkpksA/V2cNTKKg1+4nywzUmnllxhOfOP/1UrF70ohcnRrElMAmgVcgTE3GqQM2mEbxEKGw0eI1kG6cHvXdqYhYur5fH9qxka30ZgyMT+Pvo+YSp5UHl4OQELh87nA+270WtUPDowpl+sgpfdPtxsgrgk/V7gwirUVHZbGmUW/9ClBoGhAdavYfEJ/DjhZf/xkejM5bXfMmK2qUApIf25bbsR06LtNKqVDw7ax73rVmJy+vl3MwBDB0Sz6i+KWQnBmpWl9cbdIzaw+p2+ckqgFaXnYLWBiYlhNHQ0EBtfSO7yuqJj41l7sh+KBWnP6BUKgT0Wg1me0AFbgz54ywbfi+8t31PUBKtV4zC5J2AUbkFgApHJF/VlHLp6Mt4dPka/3phuuDaa2hEEssznsEledAq1LS4bH6y6jisHvnYiaJIk6mNMquFMLWSRF0oGrUGj0feZkhICDMS+rG56SBbmg5xQfweErXNlLTto9L0DQU7HkD06BidG0mIVolCoSAk3MgFqz5kf3M1fcINDEloQ8JLH302wyPH+ffhQH2wDYPD95k19lY+KNoS9JpaoeSpB87u8fhZPXZu3/MClXZ53HRm0kRuzzmXJ/M+o9pTgsLnC+sR4ZK0ntv2/PvkCFaHO51dW7ycCJLpr2D/zLejb0LMMnY1mym3NKNR/kCZdS0KVMxMvJfc8IDi0unyUFrVRGxkGFERJ1+fOZ1OGuvrmZEsd2lUhJhZqdZx0ztncd30nQzJiCE8+iYyMoeiUqn8pKVOpyM1NRWVSkW2cSrZxqn+bV61JJGrlozr4VODIYoiDQ0NOJ1OjEYjEREnn5x8tL6Ru5cu9ysJK1vbWH7TFUHrKBUKbr1kKnvyK3A45efDqq1HGDc0gwVTB3a53f8GJCngR3wy6/6vo5ew+i9hRm4cP7YzRx/VJ4JdZa2d1huUbOTfFw+nzebmH8vzqWyxc9bwZLLjwnhkmSyxLGqwcvPHu1l5Z+ACXzgkiVn943G6RcL1wYVEp+h2lQK9Jji6PVSr4kBlG+OzontUvfxeeHNDkT+trsnq4pPtZTy0oOd0su6QE29g459ndGoVO46Hvz3IJ9vLMYaoefmiEUzq2zldcHBKOPvbmcsPSQ7H4vRww4e7sPp8xd7dXMqKvDqW3z6JCP3pk1YPLxhASaOVwnoLk/vGcvXE/9uzd0Ang+3suLBOCiWAlCg9T54zmIe+PYTHK3HNpAzWFtRT3GhFEODm6dm8s7mEf/5UgAA8vKA/N0/P4p4vD+AVJVKjQjhruPygFF12rmn+FwM1eeyTsnnQfQ2tSVNhwr/AUg9DzoeIVK6fApeO68NZL2/mqM8LySvBR9vkpM13hfuZaazk7MkjSe8znPe+XOffX7vby3tXjmZEeiTGdt5SXX23eKOOJ38q4P2tZUF/P3t4En3jw4LM5zui2er0k1UAedUm9lW08sraY53WbU/E9oS28H5IYdlEWHzbSB51ymQVwDd7Kv0PO7dX4t3NJWwobAhKTgT4ZHs5v+TV8fS5Q5iWG8sdnwUIuDtm9uXO2Tkn9Xlf7qpguqmVkHaH6rxBRgbFD6XR6mRQkpExGdEygVS2Bdb8XV7J1ghfXgV/OtDttk8WPx+q4Z4v5VaW5QdrsTo9J31/Mjs9QeStyyNS3mzrRFgBmDv4WJnsnk7r9KIXvfhtMT6mHz/VyG1fbe4o9MpkXFIlaiGgBMorSKdv3BKG9DuLRkcR2xrfQZJExsRcztKSFj4t2gtAqbmZSK2ev44MpNE9OG8at04bh1qpJEQdXJ9FdoxuDwtWVD425BI+Ll1Hq8vKgqTRpOhPr0XmdCFKIr/ULvMvl1oLOWI+xMDw4ae1vYV9+3FGdi6iJKHqQCa1ORxcvXwpu2ur6RcVw7sLzyExLNhjJ1StIdMQRbFZ9jzUq9RkGaOxWCxUVdfw2Hc7KWqQuwR+2V/E89eevJKkIwRB4Mkr5vPgBz9jdbq4cuYohmQknsQ7/7cRqgmuV6eMCufbpqHMjThAvMZCqq6Fs2MPcWH/IRysrmXpvnz0ajUDEm9BIdyPKNlQCgZiQi/jH/kfsLHxAOHqUP426GqWpI5kaYV8LU2L70euUbbTqDWZuH33ZlxRNWj/P/bOOjyOcm3jv1nfTXbj7mlSd3cvpU6hhUJxKG7lwEEOB/0O7hzcrcVKhUKpG3X3pE2axn2TbNZtvj8m3c1G2rTI4XByX1euKzPzjuzs7LzPe7/3cz9BLrSoeKHn1SQI4ZItR3g4cpmcJ3rcQLW9mL2l/opwLrGCjfvXcCovjq+Xy+gYFsLf509mZXkOB4xSTJFfZ0DFAD4YNYM4baIvXQtAtAVjNmkINtgRveCuka7pjp2fk1NfjkEjR6OQFF5Xp05EFEVEkVbjs435B31kFcCK0u3ckDaFtZU7fOsEAcqrQskMblkl1RRuNThFN6pfm2ZmW+z/31vOpoLPuGmviURdDTNTpRjGi5ufCp7nidUVPH/1FPRqNbc+8TV5xdWoVQqevXdGMzPz1lBWVobd7eHlHQc5WF5Naqiel++aTnFZHdFhVxKdHI9WK73TKioqMJmk36bFYqG8vJyEhF9vR1JWVobRKL0PTCYTcrkcvf7M3lyncaq6xp/2CuRV1+AVRWQtiBnqrYEkotl6fqTi74X2KoHt+E1wSb9EdCq5z8PqeHl9i4SV2e5m7bFyPticx+6GCmVbc6u5bXRg7m+B0dpsX41S3qLSIilcx5MzuvNsw6A/KULH3V/t594JHX0qj8sHJnP5wGa7/mFoWp3sTBXF2oqWyKoN2RU+YqLW6uK+bw+w/eFxzdo9MqUrOpWCnAoz47pEM6lHHIVGq4+sOo2SWhubT1T9qhTJpHAdq+aPwuMV25ba9WdE1QnJKyq+D0R0YFa/RNZnVbDqaDlRejXFNTaOl5ub7VZaZ+OyAcnM6J2AVxTRqRTMn9CR3aeMxBg0hOqUDH12nY8geXL5UbZfE8HKrqsoESPpPekGDA0m1GU/Ps1UzzqQQRrlVIihvLD/Sp646HpftbjT0KkUdIk3+AirxrCIGpbVZbBseR39Dx1otr1LvCGArKKBkEuN0HGqWvpddos3EBei5WiJKaCdQiaweF8JKw6V4XB76Rij54Nr+gd40lWZHfz9u+bnjQxWo23y+04O1zG+a3Sztk3x3qZcnlmRhSg+yV1pxdzbuRYGnVu5XaPFySNLDrGvMPC9VVFvb0ZWnUal2cHtC/by6fUDAwi419ae4MYRac0M5ZvB62H17mMcdc/gMeXnAGR7E7l1TwKTB5h95vuD0sL54sZBKOubVEw1l7d01HPG6WqRp7G7yfJpVJsdqJXygPdZiFbJwNRwdp6SAqpYg4ZurVTjvHJQCj8cKKHe7katkHH9sP+sH2A72vG/gAe7XkKGPo4qh4kJsb15ZukGNqs0XNR1N0EqO5sPdWPppmFM6R/GCuUhCoMexSlKE1pltiMUmgNn5AstzWM7g6ZlZc6UAV3YlVPEz3uy0aYqqO9o4/7tP/Bwn3GEqXVo5Spu7HBBi/v+EZAJMtRyNTaPP+ZsWpXt3I8ptDggfGvvDvaUSf1ElrGKF7Zv5uXxk5u1+2T05bx0cAMWt4sbOw0kTmfAaDRyqrreR1YBrDuYg7HeSrj+/KuqDu+axqZnbz3jBNOfHRaLBbfbTXBwMHK5nL+NHU5WeSW5VUa6Zeg4JNtDuruSGJU/HuoVnIUoOnh6xkQevnA0aoUCpVyOw90fmysbnbIzG6uK2FwlTQjVuSy8dvw7ns+Yx2BVAjKlnLHpvXyG1+/v2IpJZSQkSJrcs+HkvYI1vD3g1mbXG66ORS2PweGR+m+XS47RKBEQHrkL/YD1fF+ynIiYHggoERtSAb2ihkRd8z5zVEo6r+yMpqrMidcjcE33fri8HnLqKwABq0PN7LBjpOnq2VhSztu7VlOxMZwxPTJ47prJKBt5XB43FfPJ1k3QiIdSe9QoZQqUghyX6B8jXJLemzDNmX8rHq+HJ498wtbqw2hkKm6Pm8bAiK6EhYWdcb+mOFZXxBvHl/NIrJZYpZ9IWVpcBaiQCYGSGplM5EhBOU99u5bhCUnkFUtZJQ6nm3e//qVNhJXH46G+vp4fTpxib5mUKppTY+Krg4e5vU9nrFYrubm5REVFERMTg8sVOLHbdPl8YbVamy03Jay8XhGj0UxIiA5lozi6d2IcoVoNtTZpUnFURmqL7yaAq6YN4NkPViOKEBdlYMKQ/62q8n802gmr/yAm9YhjUg9pdmb5odIW29TZ3Nzyxd5m65UKGZHBKqoaysdP7RlIkHy7u5BvGyq9/XNq12aVpK4cnMK0XvGMfH49R0tMHC0xcaCwls0PjAkwTf9P4eHJXcguq+dUtZWBaeHcOCL9dzmPuUk6Wb295RemRilv5iOVEKplQGoYu04FDlZ/q6pd/7Vk1cmN8OVs8DhAoYWrl6BMHsx7V/fH4fZwvMzMtH//0uKuIVpppu+0wffJSjM3f76HU9UWJnaL5c6xGQHSVa8I9m9vIsOTTwbA92vhpvUAyGoDlUxJQiVur4jT40VLcyL3yRndUchknKwyU1pnp6wFI+/d+TUkhGopbqhSd9e4zBaNtrUqOd/eMpTPt+ejlAlcPTQVuUxgWEakj6gAfDJ8e4OaMLu8nn/9eIx3rpLKCpsdbi55eyv51YEdcHK4jozoYB6b1o3rPtlJuclBz4QQvrxx0FkNw6vMjgaySlp+PS+BS2bNJUVzbml5/1h8iBWH/akzoTolYztHkximZX9hXav7WZ0eXO5AQksm0GpQ4EPZYfhyFu/Vl7JL3pGZjsfRCzZ2ezvh8ih4p4GsAtiRZ2THSSPDE/qBPl5KdwTod+05fcbW0C8lnPc35/mWB6Q2V6b9Y/EhvtxRgFIu8K+ZPbi0fxJHSuqoMjt5c24fvt1ThM3p4fKBya2m/XaNN7B6/igOF9fRMUZPcsT5D7Ta0Y52tA0KmZw5KSN8y9ll9dRYu5JdmsjQnsdQhnuIT6hi7cEcNmXvZc5V/vedw2tmVHwE3+UJvpn6KUn+2MEjulle8jWnLCdIC+rElPhLA3xt5DIZT82dyOTxnbhy/QKKa2s5UFtCrdPG+yMv/cPuwZkwN+VWPj/1Jk6vg5FRF9IhuPPvcp56Z2BqvcnZsoIhISiEl4fMCFin1+sJDdIgCP50F61KiU796ywbTuO/layqqKigokKySlCpVKSnp5MQauCnW6/B4XaztGQT75/MwuYN7JNkQhCCIK0LUqkQBIEtlYd4OftrnF4X16QJqJukhVpcVoqLi0lACx6orKgkNlZSM9XZ7QiyQNLE4Wk5/hYEOX1j3+O48QUcLgsffBGPqU5SHPUak036YMnXzS5uZkZaP5bkhaGVK3m49/gWj9clMopvLr6clbknSDSEMKdbD2SCQJ+wFPbV5PNA0l5mRUvxxMTQAuZ7FdTEq1l7IIdFWw8xZ6SUlp9lKuLWXW/jjHWj8MhRerxgljHEOQCVXMk9nS7l1exvcIkeJsYM5b4u08/6/fxSdZCt1Yelz+N18kXVOi7MHH7W/RrD7fVw376PqHVZeNDel4cS95Gh06AIvoZKjxzIp9ASSr45jJTgGkQRDu/pwLD0AlQyEYU80G9U0Yaqx7W1tRQXS9+DyRH4PVbXmwNIpMrKSqKjo9Hr9dTW1vq8y86VlGsNOp0uIKVSpwuMm8wWO/c/8DXZ2aWEhQXx7NOzyegQTbH1ADK5nK+vm8Pig0cJ0WiYO6BXC2eQMH1sT7p2iKOs2kTPjgkYgv9k6cGi0HYz9XaFVTvaiqYpgqdRY23uhSM0pKTNvn0YPx4sJTxIxcV9/QbiO05Wc/93/rQXo8XJFzc2LwNaUmvzGVjTkHpXYXKQGvmffyxSIoLYcP8Y7C6PTyXm9Yr8eKgUi8PNpO5xzVIdzwdjOkXTJc7AsVJpFu62MRln3ec0ZDLJr+e1tcf5bk8Rbo/ItcNSGZz+x0r0/3TY/aFEVoHkkbTnE0iW8s/VCjnpUUEBpI9cEJDJ4OaRHeiXEsab63N4fe0JNEo58SEaTjSonpYfLGVQWjhTe8axvOG3MjMdkksaEVMle8HjYmteHZ+f7MS/ZQJyQcQrCvzoGcy8EWmtkgMhWiUvXSp1TiW1Nv7vx6NsyamirkkaliDA1gfHIhMEYkOkDiq7rJ5dp4x0iTPQL0XqdKP0au5tkuY2MO3sHXLj3+ShorpmZJUA3DlWek67xhvY9uA4zE53M5VXa3B7xGb56q4zeOi1hpOVgYb01w9L465xmdhdEin5S04V3eINzB/fkUeWHCKnUfvv9hRxzZAUPt2Wj0yQDPTPqqJc9Q9oUEwNkB1niDybt9xSekf3WD1HSkwB5mcxNXvguxvBYQJDAkx4Anq0UgbcamTbii/526FE6rwabhmVwZ3jMlu9lAu7x/LKZb1Yl1VJp5hgbhkVqHjdk1/Dlzsk5abLI/LI4sPUWpw8vULynukUo+e7W4ecXVEGxIZofM9ZO9rRjj8eozumseTAYaaP3EGwThoIxU3dxcLPx2C2aKgxBhMWLvVTOiGS0bEDWDgug10VBXQPj2N4rD+tf1XZEtZVLAfgpCUbrVzLhNiLmp0zq7YiYPlYk+X/JHqE9OfZnh/iFT0+76pau40VuSfQq1RMzuh09gmINuDK7r1YnpuFyeFAo1BwQ69+bd5XqVQytE8P7jU5+WjdfjQqJf+4dNwfVtHvz4rqar8fq9PppL6+3kcUqBUKeoVmIBdklDpDWWXsyviw4yjlwaSHv4hLFHn6yEdsqzpCgi6SMpsRlyjFR+/lLuPVPneSpI2m0FaBDIFpYYOhURLCadLizd07WFyYh0yuQRdiQ6HyIhdkXJvePLvhNIJVHekb+750nZcU8p5nC1nZpYSEBKriJyVFcWfXGwlX63xFDw7XHabSUUmPkB5EqiXLj14xsfSKCaz23UWWyfbaMgZ28yuxFYJIT101u2XSpLmpkX/Z5oqjOL3S53d75bgrVIR8H8WlL0ulfS6IHciY6L64RU+bq/idPt5pnL6/54J6t41alxRv5dpDuDFnNG8PuJWeQak81bea+TsWUWCpQSu7huGGeJ7+6keen/QDyWEmvKKAW5fA2u1xHMkpRR+k4Y65o854PlEUKS4u9hFPY1MT2JBfgs3tQaES8abU8ETZakYGpzEmOAOZTEZVVRXl5dJ91mq1xMf7UwWbwm6389VrP7HsnY1ogzTMf+1q+o9r3SsqNjYWhUKBw+FAr9c3U1ctWbKX7GwplqypsfDue+sYc9dR8sySf1nnkInMH/NAm+51RkoUGSm/X1XSX4Pf28Nq586d/PLLLwQHBzN9+nQfGf174X/7zf0nwiX9EglSy3no+0PUtOB/0xgisHBnAR9cM4CbGwZK3+wu5IWV2ajkMsY2qTiVVdZyeeC0yCBSInS+AXGHqCDiQ/9cFagapzTe+81+n0n3e5tPsuyO4c1SB88VQWoF3986lB151YQHqSST5law6XglKw6XkhSuY96IdJRyGVqVnAcndeHBSYHqK6fbS06FmWiD+ldVOPyz4pvdhTzz0zHkMoEnpndnSs9GPg5NPTWaLAepFXxzyxA++iUPhVxg3oh0IoKkGbusMslYGsDh9mJqonirsbp44/I+XD0kFZkA/ULq4a0gcFmoEg3khI8m0+bltbXH2eHqzaXCo/SXHUeTMoBbp8w6q7H5acSHanlrbj8cbg9vrc/lzfU5PjVUiFbJp9tOMW9EOjUWJ7d9uZftJ6sRG5RCr1/ep5ni8TQq6s+c466QCVzXKO0rIVSLQib4zh2kkvPRdQMYlOa/pzKZ4COrDhfX8d2eIqL0am4YntZiSnBsiIZrh6b6jONHd4riSImJEK2qVXWg2+Pl9bUn2F9Ux6C0cG4b3YGJ3WPJbigeoZLLGNNJeu+U1dnpGm9geGYkcwYkoZDLePmy3kz/9xbf8b7fV8zWB8f6zMrbVKjAFah4u2dUAj1i+7I+q4Jv9hT51mtw8I8+DjL3vS2RVQCmYlzGAlqkh7we+Gw6d5y6jWpUgJeXVh9neGYkfZJbJxhn9klkZp+WK402JQDdXi9vb/QrwLLL61l9tDxgoqEd7WjHnxNPTh1Px1gNFt2PvnUyuRu9wYLVquHHpUO5YFQZfVMjSfSOor7WRr/IRPpFJuIVRR5fvpYVR4+TEh7KyBGBlc1K7IUtnBEGR6egkslxeqUR/4jY30dlfr6QCTJfepfZ6eTi7xaSVyupzdeeOskrE5qn7p0rukZGs3rOdRypLCczPIIkQ8vxmSiKGI1G7HY7wcHBhIRI/bxKpeLqCUO4esKQgPYmq50So4nkqNDfTHH1Z4HXK/LCR2tY+csx4qJD+NfdU0lN8McLcrkcT6OqjApFYAzdyZDMc71uZVPFAWK10+kXPwKFXGrzfdFGtlQdAqDQGkigioh4Efl3v/lkmfKJUIcS6tZQWCg93yUOM16Fm1iXk1d2SLGA1yOnMj+c+4f346LM3sRp2+ah2bdrEu88PofKqnp+OKjEyvcNWwT2GlUU244xN20w2aZiXsp+FxfSNQTJg/hn138So2m5wEqNzYGjVsvh6miSE/1EWHZFJPYiHRF6HVP6+9WECU1i285R8Tz577kkxPvjBqVMgbJhqJ1j2kCx9SAx2s50Dmk5rXdEVC+WFf9CVn0BMmQMVg9g9eETjOqcjqoV9byxzspbCzdhrLMyY2wPRvbPoGdoKgdrpRgvXhtORrAUo6coT7BooB1BORBBIxWMeO+qvRg8UqwkE0RUzg9594mVVBrNhOq1aFqptH4akseXn/FIC9XzzXWzOWE08VXNBg7XS/c/11hNnNLAiMRulJeX4/F6OVRbg0ouIy6uZS84p9PJltU7+frFVQDYzA6emfc+35x4GXkrhW5kMhnR0a1bY7hcTSahDVU+sgogq24lgyOvJ1j55ySi/gx47LHHeOWVV7j00kspKiri/vvvZ9WqVQwa1Fwc81uhnbD6E+HC7nHsK6z1VYVSyARm9k1g2f4S5DIBayO/pMIaG/d9ewCZABf3SeSh7w/haRjUfrunEI1S5vORGd0pCpfHy1vrc8mtNDOhawzTesWjUcr55maJOJDJBK4fltaiz9OfAXaXJ6Ci3MlKC3vyaxjV8de9UOpsLt7ekEu93cXcQSmtttuTb+S6T3b57nFxjY1/Nal4dhpmh5s5723jcLEJtULGm1f0Zfw5ViD7M6O0zhbwvM3/Zj/DMyP9yqUxj0BFFhTtgpQhMPL+ZsdICNXyz6nNTarrmpC1ooivaqBMkJRPgiAwMO10YBMOVy/h8PqvmXt8BHWlSgwvbsDRkHK2R+zEHk8n7krLbDNZ1RgyQWBPfo2PMNIoZRwpMXGkxMS6YxVkRAcHVNz0ivDt7qJWCatRHaNICtdSaJTUZWFaBeO6xnLj8DROVVvJiA4iI9o/G5QcoeOiPgl810DIDEqPCCCrGuNUlYVL393me08cKanjrbktz0g/Pr0blw9MZtHeQt7blMeG7Eqi9WqW3TG8RTXPm+tzeX2dZM6+6XglWqWceyd0JD0yiLwqC+O6RNMjMYTSOhsXvbXFZzq/J7+GVy7rTXiQKiA1Qy4T0Crl51ZRc+R98NVcSb1nSEQ18HomhcQFpCUasLBC/zQJx/Ka7b5gRz6XDvFI/mVeL5w2+DUV4yk9TC2BpqbV5ubq1rZiQGp4QLrwvRM68vXuwoDJiF9LtrejHe34Y6CUy7l24Ei+ze9EhV2aUAmSR9I5ugfVFWXEBkczLnw8EV7p3Vnv3EBd1UZU8nh251/AV3skxfvB4jJCj8vQNuKpuxp6I3oqEc1vgmhFCLoWQdmVLmExfDF2Lj8WHCVeF8I1Hfv/Zz58G7C7tNhHVgEszT7Gc2MntlrZr604UVHFgl0H0KmU9BnWui9oY7VGTY10HadJq6bIKqrg5jcXUWuxExum56O7ZpMQce6xwZ8Vq7dmsWSt9LydLKzi6fdW8d4Tl/u2JyYmUlhYiNvtJjw8vEUz6l6hGfQKbZ5tYHbZApYNyiBMDUoeebWO4iM2ug/V0Dfc7+Xj9Xr5KmcfL+fuwItI6onteERvg1YcRK+MPhGZbSarGsOhEvmgQIm2oj/JEXVUyDQU2aqBnymwVLOz5gAGdQmnLUstHgt7a/YyKW5Si8eb1aUbi7OP8tDukdQ61AyPk6ELm8q8zlOZElVP77Q4Igx+64SJsb35LG8dhVbJr2li594BZFVjZNetYXXp0wAcqgWX10aPsBnN2mnkKl7ucyc59UW8+uMO3j+cA+QwuEMS7193cYtVLh957Qf2HZNixJ0HT/Hh/83l5b43sKRwO06vm2kJA9Ap1Ij29Yi1tzTQi4DhaQTdLEKCIxEbuzgIwchlMmIjDW36HmQyGVFRUVRWSsbzwcHBpMTFkhkfxytrFge0LXaZqKysxOP18vihveyvkeLn/XYrT4+TKiiKouir2G6xWKivaeJJVW/H5XAjP8/iVpMm92LxLwcxVlswuBXMnDKEvSz11SeXIUch+wuo2sUzlFxvqW0bceTIEZ566imWLVvG1KlTAZgzZw4333wz+/fvP79rbQPaI+Y/GR6Y2JnkcB2nqixM6BrLwLRwXpjVi5yKema+tdVXNaq01kZ2g3JqfVaFjzwAsLu8fHrdQH7JqSTGoOGaoan868djPkXFsgMlBKsVjOkcTYxBw0NNvJn+jFArZEQEqai2SINIQZDK1/9azPt0t89TaNmBElbNH0lcSHOV2faTxoB7vC23ulmb01i8t4jDxdJshcPt5dmfs/5ShFWNxRVwL5xuL2aH209YBUXA9SvO69h9ksPolxLmM7W+fGAyWaUm9hXW4hXhq12FDM2IDKxcmTSQV0WBOrc042dqUllNLsAVg5I5V2zNreK5FVkB1SEbm4mfqDDjbUFHG9uCp9VphOpU3D02k/saUnZrbG76JofROc5A57jmwYHd5WHxvmLf8rqsCh5Zcois0no6xup5ZEoXn+fc7vyaAFJ70/GqM36+TrF6Vh7xS98r6h38dKiU64c3r0p5uKSuxeXTFRlPY8dJY0CFxBWHS3nlst4khun4+8TOvLgyC7GBuKu2OFolrOqsLnadMhIfqqVrfMN9yZwAd+6B2nyI7QEaaZAxrku0z8B9unwrCS4/WeUVBWSCyDFvMi8Zh5G2Zycjd98JxlzoOAlmf0yBI5gnvA8RjolKpGAzNUxN32RpNv98zHXf2ZjrI6s6xgRzw/B0+qWEc9uXe6i1uZjVN5EJf6F3Qjva8VeHIAjMSHqBAzXf4/Y66BE2g+syoxFFMcC/RVQcp8r9d6mGPaBTHwL6I5d58XjllBRG8dTwu8mzHKdDcGd6hQ7EWzUN3BIRJjrWQeQKBHmUT6X1Z0d0UJBvYgkgXKv71WRVldnClZ98S12D+fHOU0V8O++KFtuazYFpYRaLpVXC6r2VO6i1SMcsq6nn03V7eHj22F91rX8mGE2Bg3tjXeCyTqejU6fzM4ceH9ufH0q2UOsyI0PGvJTpvPDOehweF54CDf8nrKJPp2SiI/wkWFhYGFvqfmZiXCHHTHGcsoBcVOBBDgLEq/QMij/3Z/y7gq18cWILFq2F0qpoipwhaML9KuztlSeo9ZrRKWWo5P64KFTVehZF/7gEZgZ3ZPnhLF44Noq33Ao+e3gGXRIj6ZLYvL/ebczxkVUA7+asoMhWRKGtgqGRPZidNMa3rcCyK2DfAsvuFgkrGlRZIWI4mw/7J+m35xaSW2GkY2zzKubZef44zuMVySmoolNaDJenjgxoJzpWBzATomMVgm4WaKbjsK5G7VqL2W1gVcVsLtA7MKhbHmM5nU7sdjtarRZlQ5XTmJgYQkJC8Hq9aLVaH+E0MqYTixuqRKoFBV3UkvLpeH2dj6wCWHjsMHf06kdtRQWiKBIVFUV0dDROYScJw15n3kc1LH06nfKTIQyb0Q9VQ1aB1+tF1gKJ1xo8Xi+P/riWnGgXRKsY3bsrQ/sMQFN9E9srP0AQZIyKuRuNvG1VBf/M+L2qBH7//ffExMQwZcoU37p58+Yxfvx4cnJyyMhou7XOuaCdsPqTQSYTWlT6ZETrWXH3CHbmGZEJAvd87WcxK81OZIKk7gAY0ymKUQ1/p7E73xhwvF2njIzpfPZqYn8WCILAu1f148HvD2G2u7l9TAe6tDDAPxe4Pd4AA+x6u5vDxaYWCaseTdQ5Z1LrCE28G+S/gZfDnwkdY4IZnB7O9pPSvRvfOYr4Q+9ATR50nQ4ZLRtdNoXL46W4xkakXu1Tm6gUMhbMG8Sm41XoVHKGZUQy9qUNAfvtza/hSEkd8SFa5g5KprDGxsbjla2cBTwiXP7edr69ZUhAeuaJ8nqe+zkbl8fLHWMzAoyzi8vKKfn0Jv5JCavl/XjX07wUdrRezYXdY3lzvT/Vq09yKA9OOrMB7fY8/zOXKRSRuPkzqE6GEfexPM9DWZ2did1ifZUCxSak2OmqlrvzJbPMZy6WlH6dYvQB74EucWfvcMN0qgCPrIjglgmkYR0iWH20vNFy86AJIDUyKEBJlRYpqZasTjc/HCjB07B+XVYFu/KM/HjXiGZG4lVmBxe9uYWiGhuCAP+6qIefcAxNkv4aYUbvBIJUCnadMjLV2xF2+7edEuKZ57iHAjEGFwp6HPwXVJ+QNmb/CLs/Yt62bmS7ujfsIaJVCJyqcTD9zS1kxgSzMbuS5HAd713dn44xbQti/t2gRgM4Xm5mQ3YFk3rEsfefE3B6vGc1xm9HO9rx54NaHszAyKsD1gmCQFhYGGq1GofDgZWtlNT7JzZ0mv28e+VuNAona471Iin0MfqE9aVPmOTrKHrrfWSVtMIE7hMg/+9JR+kaGc3jI8fy9p6d6NVqnhkz4VcfM6u8ykdWARwqKcfidBKkat5HabVaLBa/R6KmlQqMtBCP/dcWt2kFYwdl8sWynT6iaua4HpSWliKKIhEREahbISGawupwUllnIT7CgLKBfIzXRvJu//s5YsojQRtFsFOPNXezbyjpxsuqov3UVpvoFZrGiOiuVFuWcmfmN8gEcHtlPH10MtklKcjrBRCgWrRw17fLeW321ADfs5WFWXyZs5dwtY6H+owjRuvve38q2MUr2UsBCA6XJrDNpsDvvEtoAjZvEEdMHmKFOtRykbHRIxkcPviMn/vQkRLUNdJ12OVuVm49gGFUD4LDDawtl4iXCbED0MhVzUQpguBkRdkOAA7X5RGlDmV0dB8AItUdyGa1r22kugNnQrBahVIux9WQvimXCRi0LX93/bunsGm3FHOoVQp6dGw5vU6QpwZes1yyn8izVHHrwWicnuk4PHKMJaf49Ng3LJ49F0UTMshsNpOfn48oishkMtLS0nzeUy397h7qNp1MfRwV9jp6y2MId0jPik4eSD+o5HLKS0pQNpyvoqICTZCZQtOdoHSS1Atu+byaZ2+bw6YjpdTe+TnWChP5ORX0HtSBf748B63u7M/24eJyfjnh9739fv9R7p82ir4Rl9Er/BIEBGTCXyg+O0dvKpMpsJK5Wq1u9s7IysoiIyMjYKzbsWPHgG2/B9oJq/8iJIbpSAzTYXa4idarA/xwGgle6BzbfFDVNznMp/oBfMbQ54WSfbD9HVAHw6gHIPiPIb76p4az5t4zm/+dCxRyWYDhuloho2NMcIttR3aM4sXZvVh+sITkcB1/v7B1UuKSvoks3V/MrlM1BKnkLaa+/TdDIZfx6fUDWXO0ArlMYELe8whrP5Q27vscrlvhM1lvDXVWF5e/v52jpSYMGgUfXTuA/g2EkVohD1CfXNI30edrpVPKWbizwJfyl1VmIi0yCJfH/wNQygSm947n+73Fvnd1XpWFL7bnc8946aXq8ni56sOdlJkaZm/zjCy6dQhGiwulXCBl8wPMkklEWX/ZcUrFCFYIw7hjbAYHCutQyATum9iJjjF6MqP1nKyyMCIjkhqrk1PVljOmumVGS89YGCa+Uj1FhLkedsK/9ql5v17y2nhzfQ4/3DmcxDAdD07q7KvqlxEVFGBefrzc70/XIzGE1y/vw8KdBUQGq/lHK8rJarMDo8VJWmQQz8/qyW1f7qWoxsrMPglMayWV8dphaWhVcvYXSh5WTZVVp9E7KZRnL+7Bp1vziQhW8X8XSUTQ5hNVHC0N7AjrHW625FaRHBGofvvhQAlFNVLqgSjCu5tyz6qQG981RlIxejKgbgOcWAmaEOqGPUflWhUeh5trh6QSVhZoFC9aa8mpbDw7L3DaY7+oxua7jlPVVh5Zcphvbg70QmkNQWoFNpd/VjdYI3W1giC0k1XtaMdfEDqdDp1Oh9LRn5J6GSD1UXLBjkYp/X9B1wN0ig5MqxJkekRFBrgbSG4hGBTnH/DX1tZSX1+PWq0mKiqq2QTa74Wre/bh6p59frPjdYgMR6tUYGvwm0mLCGuRrKJB3UGDOXNwcDDh4a2nl906eQj78kqorLOQHBXKteMG/GbX/GdATISBT5+5it2HC4iNNBCksPmM1k0mE5mZmcjPon47nF/GbW8vps5qJyMugg/vmk1okERKhKsNjIiSitOIosjAHinsPCQRALFDlLzdUFBgYf4mnuhxOcmyxZzmBBUyL7OSK/m5bDj76kt9g+nVx3LYW1BM/xRJaXWsppw7ty7GI4oIgpec+jI+H3Mp1Y5cDMoo9pRkB1yvUuMi0hLHNemD2W86RYIujPldJqKQyVhSuB2H18XwiM6UO8updFQRrWmdDE6Pi6C4zoStmxN3pJd3PHuIzJOz7uROTtolo+415bt5uc+dDIjIZHhUV36pPIpckBGtDaLS4U+NPWUpBaTfRO/wWTi9VkpsB4nRdKZ/5JUtnt/ZUBnToNXw7OyJ/N+y9Xi8Xu6fPJLYkJYnzJ64YzJf/LALY52VKaO6kRzXyvMfdD14K8G5HZQ9EPTzAVhatAOz2w7IEWQQFGbjcFEFxfUmUkICFWnV1dW+SVSv14vRaCQhoeV4kNMVV1MH+z7bqVOncDqddIyI5O7+g/n3nh2o5HKeHj0epTuQXbG78hHxWzMoVE5m376OT5+/kIP7C5DZXAhekb3bclj02RauvOXsSsmm7xClXI66wcdNLrRTIklJgRPCjz32GI8//njAOrPZ3EzBGhoa6tv2e6H92/kvRLBawcKbBjP/6/0cLGpePn7tsQquG5ZGdKPUpH9M6UKoVklOg4fVuC7nmY5iKoVPp/vNjAt3wC2/nPdn+U/jo2v78+yKLMrq7Fw1JIWUiKBW287ql8isfmeXLmtVcr66aQgltTbCglR/Sa8atULuN1rfsNm/QfTCqV8geTD1dheHiuqID9WSGhl4X7/Yke8jMEx2N8/9nMXUnvEcXPc144Rd9OzVj8RJ94Ncwe1jMugSp6eg2kqN1cVra0/4jrP2WAWPTgskBPunhvHSpb0pqrGyI88fPCgbGTTWWJw+sgrA5vIw+XX/c7wp5EjAMYcZKnhm/gUtVrK7qE8CxbU2Lnh5I5aGlLzpveJ4/fK+Ld672f2TeGn1cTI9xUQIfsJpcb2fYKqxuth4vJK5g1K4aWQHpvWKx+b0UFJr56qPdvgUTI093A4X1/HxllNYnR6uGJgS8Ps/jdVHy7ljwV4cbi99kkNZcOPgNpPAlw1I5rI2xPZSu0CCqbXKjOmNnotyk513N54MIOEA9Jpz+P3IlTD3G7AaQa1HXW5jYQeRzGi95M936Hb4/iYQPRAUhdB7DoNzy9lyhhTf0zDZzlwMozHun9iRR5YcxuURuaRvIiMy/3vUEu1oRzvOH8HqvmRGvse64lc5bnEzMvQ4AOEyGSGCgML6NaJ6AILgHzgJYR8hmt8A0YYQdB2C/PwmAU0mE0VF/gIUHo+nVTPjPzviQvS8P3cm7/2yCxH4+4QRrbYVBKHNFarSYyNY/s/rqTKZiQnVo/wLTiBEhgVz4YiuuFwusrP95I7b7cbhcKDT6SivNlFQWkNmchShhkCV8xvLt1BnleKjnNJqvli/l/J6MxuPnCQl0sCTs8eRlhCLIAi8cP9FrNqShcvtYVv4Piqq/RYGWyqzyEgInASbkDSSy7vMpt/T/8bl9SsRFY1ItON1lXhEEaXCRUiwDVFTxmvZK1DLXQjIiFWPh0ZhwqyUvtw75SKfEqwxLk8dybqyQ/zz6JNoFE5EUeCGtBsYETWsxXt30ajurDXl4I6Urs2Km/fK9yIz+Ku4HzWdotRWTaIuimd7XU2BtYoghZofin9hQYGkopIho1+YP/Wy2rKYIPdXdFEbSAm9pUVypKysjKoqKcUwIiKCST07Mann2dM3NWolN84aetZ2gqBAMPyj2Xq9MjCrxOsRMKjVRGr9z8XewhKW7D+KRvQwMSUWdcO9Phv52RgqlYrMzEw8Hg8ymZu7Uyzc3ncWcmUSMkGgpKQEo1HKQNDpdIQG96GoPgRPI4OtxIyWsynMJnuL65siIyaCGX26sHSfVDTq8YvGoVH+9cZonGdKYGFhIQaDP3upJUVmUFBQQD8DUFdX59v2e+Gv+S39D6BDVDBPzujOJW9vDfATAjheYebKD3ewar5/IKpWyLn3gvPLWw9AxRE/WQVQdgicFlD9fg/p7wmDRklelYWDRXXsK6xFIZNxYfdfX5pTLhN8KV1/ecT1hqrj/uX43pSZbFzy1jaKa20oZIJUJa6R71TTNDezw83K5d/whfIZZIIIu1eDwgQXPgPA2M4Swbo1twrW+vfrGKNnas94jpSYWLa/hMQwLS/Mlmb/Hp7clWs/3kmN1UWPhBCuGuJPtY0MVgeo6/wQkeFlsaU7dyukz+RFzpSZVxGkVuB0e3n8hyPszDPSOymUp2Z0R6uS8/zPWT6yCmDZgVIemGQjoVHVTVEU+WhLHj8cKMXp9nKSeEyiDoMgSffjFfVUuf2zWYlh0vNjsrt4d+NJyurszOqXyGfXD2R9VgUdY/TMGSgRQ16vyHWf7KKyQXV591f76BZvaEYUPvPTMZ86bV9BLYv3FZ+Xv9e5YnB6BDeNTOfDX/KQCRAfouXaQfEMSpKuz+n2ctGbWyitk4IOrVKO3e0hRq/h6Zk9+HJ7PlllJqb2jGdQeiPT+SNLYN3/gVwFk55jnaMjDyw6hN3lITM6mL0FtQDMHZQsFUnoMQuiu4LxJCQNhOBo3pqbwIjn1/u8z06nNMYaNLg8XqotUsp1S95eLcFkd/HSquM+1d+h4lo8XvEvl3rSjna0o2WE6sZjUyr5ofInnF4Fc6KOkHa6GpvzZ8T6CATDY772gjwWIeRfv/q8Vqv1jMv/bdBr1BwqKafGauN4eRWfXzub5PDWPYjaCo1KQWLkrz/Onx0KhQKlUonLJU22yGQyVCoV2w7m8eCrS3HaPIQZtLz92BxS4v2qnKbenIcKy9h6QrIiqCmw88z363jxmqkYDAZUSgVTR0tK6qqccrZUH/PtlxYcQ2LoA7g8VVidh9FrhhBruBGZIOcfk8bw1E/r8Igil/btQe9EP7HaNzKRIIUKdVA9MUFmEnU1qOXSZxDx4tQc5Naw2RyyF5GoDufmrtNQyuVU2Gt49fg3VNpruSB2ILOTJQ+pd3O+Qac+7X8r8lXhN80IK4vTyWvbN7C76AToAn1QLXYPESEKnKK0Xi1TEqqUlPInK428s2E3ggA3jxpEdMdQCi1lDI7sQY9QKe3P6jxGnvF+n+ryRNU8esZvDDiHy+XykVU0KJnCw8PbnML5a3B5yigO1eazx5iD3KMhRUjh7xeORdfgT5VTWc3Vn3yLu4FgzK2uYf6A7uh0OoLCDHx6cg12j5MZiUOI1fqzd8rKyqirq0OlUpGYmIjRaKS6uhql3EFa2KPIvNnIUSCEPAfaacTHx2MwGBBFkaCgIGQyGemRr3Ki8gbfvSvKkcYCGZkxFBwqxgME6TVcOLPlAkNNsS+/hOUHsqDB7+tQURkz+3X7ze/pnwLnYbpuMBgCCKuW0KlTJzZu3Bhgjn/ixAnftt8L7YTVfzF6J4Xy/tX9WLyvBLPdxfpsP/N8vNzM2Bc38PmNgwIGzb8a0V1BpQdnw/RGdLdfRVbZXR5eWX2c3EozF3SN5dIBSW3Y67fDkv3FPpWa0+3luZ+zfhPC6s+GKrODe785QHaZibGdo3lqRncUrZSEPWdMfQW0oWDMg24zOaIbwKwXN2BzSh2M2yvyxtrjAYTVFQOTSdr2KBOca6kgnJ3pL1FaeUwiqxrgzdtE0ysc2iGSZy7uwXd7iogN0fBYg7rqgQs780CTNM1eSaFse2gc1RYnsQZNAGEgkwksuHEQE1/dFJBaCwK3ypdxQExnrOIzNNh5Ymw0AzpJ5pVvb8hlwQ4pcMupMBMRpOKhyV0wWppXlFPKAwmKtzfm8vzP/tnOKkKY63yYmxU/oNLomHfBEO5aVuTrX4ob0tHu/foAa45J/lGrj5Vz97hMvt5ViMsrYna4uXFEOlaXx0dWnb7nl7y9FZVCxsOTuzDt9L1vwpn8kfZqD0/uwgMXdmZdVgUbv3qJK9Z9iHe9F2HMQ6wwzPWRVTQo3pbdPoyeSaHc/dU+ljZUCP18ewGf3TCA42VmHNWF3HbwRgRvQyD71RXca3uTWqc043earAL4ckcBt4zqQGKYlneOqdmTH0OfMhO3jIzktbU5yGUywoOU9EsO446xmehUcpLCdVgcbnadqiEpXEu3+LZVksqtMAc8U8fLzVSZHcScwYy/He1ox18LV6SMRC7IOFrXE0G2GvCXTbeYP6fMUUKHyH8jE85cMv5coNPpzrh8rii3G/kkbwV2j5PZSWPoGpL6K6/w3PDO5p3UWKV+sLzezIdbd/PE1LZ5ZP43wezYxynjQ3i89cQZbiVa33K62LlCEARSU1MpLy/3GVkvO5rNA2tX4B3jAkHEeszNolX7ufdafzrVzRMHcji/FKvDTXxYsFRF0S9sp8bqwGKxNBvYXps+FqvHwZG6AnqFpnFFykgUMjmZUe81u7Y5/XsyqVtHHG430fpAK46k4FC+GncVN+96BaXci0cMjATtuDkpX0NESARz0i9CpZTUis8d+5KDdZKn6Hsnl5EaFEv/8M54CIzPZDRXBd2zZgG20M2EZHrpnazgYH4iNrkSRJio6khQdDyryyWDTK8oUuGoQfDKue6j76gyS8TwzpOFPHG1BZn3Bw5WG4hWP0a8rg8Od6GPcAGwuwq4dMs/CFOF8mCXK0kLbsVz6g8K0IIUal7rNw+P6OXTvBUsLFjDk7lHmF0xjEs7TuCNJb/4yCqAg+XVdOvWDUEQuGnbq2RZJVXdipJdfDToGqz2RTgcHqxVIxEIxuVyUVBQgM0m/Za1yvXIvKdjYTei+RUE7TTqLXbe/3I7lUYzk8Z0o1ffeJ46dhKPezxjwkvoGdaPtBG3Mqq3koSkcIrzq8jPraBTj0SiYtoWn+3KKwoQeezILfxN7+X/AmbOnMkTTzzBqlWrmDhRquz40Ucf0a1bN5+X1e+BdsLqvxxjO8cwtnMM5SY741/aSL3DPzNwssrC8z9n8dqc385XAEM8XL0Utr8leViNfqht+1XnQu46iMiADv7KGU8uP+ojANYcqyBUp+SCbn8cYfRXN+A8jaeWH2VTgzH5wp2FdIzRc92wtilGmqLO5sKgUfg7U3UwTH7Bt/1f72/3kVWnYWmyHF7wMzNcP4EAqZSSVPgMjwVPg0aqXll8y8/t5QOTuXxg21RBbq/IqSoLDpeH9KjAoCgsSMUjU7tw18LAMqxxQjXvuqfhNiuAYG5c7WL3IC/51Ra+3RPYuZ2qtvD62hNsPhFYke/64alE6wMJiuUHSmiKQ2I6fxPns+T6YXyzuzBgMmTpfkn9tL/QT7x4vCKvrTmBp2EG9F8/HWN8lxhSI4MYkRkZcB2nK2r+7ZsDDE6PIEqv5pEpXbj9y33YXB4GpIYxsxUvqt8LeVVmHvtmGxuFD1AKDYq09f8it3PgDJdCJpDSoA5bcag0YNv93x6k3OSgt5DD7Wp/mp7gMKF0moDm/nyCIBn6f/hLHs/9LM2urTlWQXZZva/CIA2+Wr2S/DPvGqX8nAnslIgg9BqFr6KrXq3guZ+zmNknoT01sB3t+B+BIAjMSZHS2ER7LGKtn7AyiyK1tpVUW74nKviy3+ycBoOBhISEAA+rtsBisWC32wkKCvIZJ4uiyIMH3qHIJsUNe2uy+XDgQ0Sq2zYw/C0gaxaf/UaTbH8y5FTehMsr3ef8mn8SrO6HTnXu1bu9oojZ6Qyo7qZWq0lOluIlp8fDIyvW4E10cpqzMffwUC8GEjrxQQpenTOcaoudWIOOelHBst1HcbilPntUZrzPaLsxlDIFd3dqXqCmNThsLk4VG1EkywgPCSRXu4bFMCa2FwdMv1DtDCZEYSNUaUWOlhM2Lw6vEaPbyIKSBdydeTebtx7nWH0hNBIkFVorWFz8C3VuB0q5Ao3CjSjKuSHtumbXUq04QEiD15xa7SaFOso2RdNJNPDgy5O4+/CrvrYu0c2WqkMM1vbzkVUAmuCTZJm2AWDz1LC+9BnmdviGYHU/lPIYXB5p4vGIJY4al5Ual5Xnsr7knf73oVQqiYqKorJSeg4iIyNRteLZ9nvA6XCxIyeLhZVrAPDg5Zv6XxhQlMmpE5WgE30znBFKqQqg0VrnI6sAzJ5aciovQxClzykErUJteRkBmU/lByDSlKSXPuf/vfoTW3efBGDr7lyG3BfNdvNxIIxddWHcKBvBdemx0CAGTEqLIint3GKqrvGN0q1VHuTpZp4+vIyr0oaRFBRxpl3/CyE0n6U+Y9u2oWfPntx///1cdtllXHnllRQVFbFmzRp+/vnn877StqCdsPovRqHRikIuEBeiJcagYcG8wdz11V7yqvwvULPdfcZjnBcS+8GsD9veviILPhjvV2Vd+BwMvgWAA40G4wAHi+oCCCuLw01WWT2JYdrfRaFwUZ8EFu8rZkeeEd1f0CD9NEpqbWdcbgtMdhfXfLSTfQW1JIRq+fyGgc1IIMCXctYYQ9ObdATWQM8gc00Zt/VXYdkbg0J0ouo2FWHS8+d8jY1RY3FyydtbOVllQS4TeGFWTy7um4jD7eHnxZ+TUfgtA6MTuKTbVSw6IqUGynCjxIO70auxzuZiy4kq/r7oYBM1lhQgvrz6eMC6qT3jeHRqc4lxSkQQR0v9xgvhQSr+ObUL/VPCSQrXkRQWGLCFB6nYklNFn+RQX4U+uUwImB0SRel7AXj/6v7c9+0BVh0tx9noO3B6vNRYnUTp1YztHMP2h8ZhtDpJDte1iaB1ur0cLTUREaTypbl6vSIvrc5mW241PRJCeGhyFzTK1r0MRFHk7q/2s+xACeHYUGo8AdvTDUKAdnlcl2iOlNTx2NIjAYb6AFX1UnB9TEzmmDeJLrIGEjFtFENVXVl6QCK4Yg0ayuslBvS+CzoRY9BwoInnX1O/rHJT4Pd7PggPUvH5DYN4c30OR0tMFNfa+H5vMUv3l7Do1qH0Tvrrp6K0ox3/yxBFN3gKQBaBIAtB0IyDkBeprf0nFk89pQ1qBY+3/qzHOleEhYURFtb2ojo1NTUUF0uDTkEQSEtLQ6fTYXHbfWQVgNXjoNBaEUBYVTlMlNlqSAuOJUjx26cu3T5qMHsKiikzmUkJD2XesL+WQTqAV3Ti8jae8BJxesrQcW6E1eGKcq5fvphKq4VhScl8OGWmz0zady6viNvroanAaMjgwMlLt9tNkFpJkcnCx3uyiQnV8+KcMRzIKyEpXM/IHh19JsvniwPZxcx/ZhE2h4uQYA1vPXoZ6UmRlFea+PirzTidTmZdOIBTihxq3eVkm2PQeoMZFZyGw7vDd5ycsnx21Z3ksf9bAmMUyAdI8YFWrmZFyQHyrHkIgkCVIwiZU+SejnPoHdaj2fWEqHWAfzwyIDmZkdHjGTw0E61WRawmgjyLf/IsVGFFoSkg1qCjzCSNueLCAu+3o+H3rZRH0DlqEd/9/DQHqOOgwV9ludrhj0liYmIIDw9HFMU2k1V2Tz21zkJCVYlo5JLircZs4/lFGygx1jGpX2fmjOx9xmPU1Vi4//oPyfeUwb3+9V5EXB4PHaMiKDpehyMUZG64eVR/Pti7h0/27UGWqACFNM5MVNf7yCoAUZ4DQg2IEYSGhmIymXA6ndQ5hhMZvAO1sBOEYATDPwE4dqLMf26vSFF9dQCPUmlvauFx7hjeMZV/XXIBPx3KIisqiyKhlu8KythUkcX3I+9G9zu8x/5jOI+UwLbiueeeY8qUKWzevJnMzEzeeOONZobtvzXOmbCy2WwUFhbSoUOHZmZrhYWFOJ1OOnQ4c7nOdvx6PLr0MJ9tkypz3DM+k3vGd6RHYgjvXNmfS9/dRp3NhUYp44YR56ei+U1xdImfrALY/4WPsBqcHsHRklpmyLYSLqtneMzNvmYVJjuXvLOVQqMNjVLGe1f1Z2TH31ahoFHKWThvMMV/YYN0Girt7TolGZCrFTKmtlINriVklZlYl1XBvoJa9jWkWRXX2nhy+VE+uW5gs/Z3js3gxk93424gVoLUcm4alR7YqPNUxE0vIpikQPlHW3eu2NaoEkXVCVCdfzqDy+Nl3me7OVklVYXzeEVeX3uCi/sm8vqCJdyTe6+k8DHBFcJhFiEZUXpRcFKMI0NTR47dH5jf8sUe7E2IuH/N7M5jS4/QFJnRLVdyefnSXhwtMZFvtKJWyHjzij4M6eAPXK4ZmkpelYWNxysJD1Kx+mgZKw6XEWtQc82QFOodbi7uk8jifcUs2isZHg7PiPSlqp2qtrD8YGmz86rkMmjkSRGiUxKia1sais3pYc772zlQWItcJvDsxT2Y3T+Jj7ee4s31kvR+b0EtGqWch1qpSii1qfEpmYwY+MI9jisVkhmZJ3MS0yZOZL87i00nKukSZ+DxaV0Z+2KgYhQgxqAmKljN4RITDlTMcT3GitElxEcYoPcVvCJTMa1XAna3h/FdYnC4vCD4Td8Hp4fzQyNF1cRusZTW2alrMFS/tH/LHa7D7eHb3UXYXR5m9kkgIvjMQY2Urt2fYc+u863zeEV2nzK2E1bt+N1gNBoxmUykpjZP3Tp06BDx8fFERPzVZpH/XBC9FsSaa8B1EAQthP4bQT0CQTsdj8dJqfHvAKjlSUQEXfSfvlxqavyFSURRpK6uDp1OR7BSS3pQPCct0vsyWK4lRetXJ+yqPsED+z/F4XURpwnj7QG3EaU5s/fJuSI9MpyVd15HZb2FaEMwqnMweP5vgUxQEa6bhtG6DAC1IpVgddv8eADWF+VytKaCJUeOodOcYmxSOdWWU3x5JJ3rewUeR6NUcPvQwbxxfDOiXpo06hwazYikwPgsPDycrKIynly3B5dHinuOl1fz9wbiw+MJnHA6V1Taa3ky6yOEGSaUJ3TUHoBvV+5j/jVjuOMfCymrlMYLu44VYL/SCA2KHCtOdGI4SkGJS5T67OLVAs8f+QGvV4S1esQyJboYGbdeOYn/O/IdGsVpzkPAKwokaVsuOPWP3jfxbNbzeGRWQuSRzB98HSFKfwx4d8dZuLPdFFkrGRJeR775DfLNcPMlvTl6aCIg59rh3dhVX0SNMw+AXmFzfPsv+/IE/8rpgBAsEtu3DLlauofu8hDsLrfP+FupbHuKcLUjjyUFf8PmqUUjN3BR0ktEajrw2IJVbDwsKZX255WSGBnC8K6tjwV//HYXBScrQZDBITn0kK5ttLY7KbGJPDgvE/H9VRSV1TJmSEeSOkbwt2++BkBxMpSYRAuZIXpmR41BJmzFK0oEnkIWSWx0R9TqIAwGA1FRUdTX1yOXy9Hqv0D0VIEsGEGQxAh9uiexbouUKqhQyJgU2493yn/Ei4hSkDMxruWsi8rSWjYu24s+RMf4WQOQn6WQwsx+3ejfOZYZG/f51lXYTRRZjXQ0/HcWqfhPYOTIkYwcOfIPO985jc4//fRTbr75ZhwOB+Hh4bz66qtcddVVvu1ff/01ZWVlvPjii7/HtbajATkV9T6yCuDVNSe4ekgq4UEqOsXqWX3vSI6UmMiICv7djL/LTXb2FdSQER1MRisDdB8MTcgRgz8N6aFJnZlV9BxdypZIK9augYzNEBzFlzsKKDRKSiC7y8vra0/85oQVDX5Gf3WD9DkDk0mO0HG8rJ6hGZF0jDnLd9aAY6UmZr61BburuWpqZ56xxX1Gd4pm8wNjWHesAhGRUR2jA+6vw+3hniWF7DM+xkDvQUrFcDJlxcB6/0Gqc9r82bxekQU7CyiptTG5RxzdE0J4b9NJdufXBLQrqrFxtLQOW8E+fzoa0NkbeK704Zdy28jhDHt+A+YGwsTu9hKslmN2SPslhGq5uE8iL6zMptbqlzoPTQ/n5qbkXAO0KgUb7h9NRb2DEK0yQJFUb3exYEcB/bwHeVz5DJaqWl4VZvARkygzOQgPUvPEDMnYdFhGBJf0TcDh8TIiIxK5TGDBjgLe3tDyPXN6vLy0+jiPTut2zn52Kw6X+lSQHq/ICyuzmd0/iRNNlEk/Hiplf2EtIzIjuX1MRjPvhabLj7hvYJFnJHP6xnDZJZeBTMbj0/2qtMp6RzOyakr3OP45rSseUeTJH45QZXZy1eDexDdKa5QB47v6A9Kmqq+5g1JQyAR25tXQLyWMKwYlM6tfIptOVJIUpmv1/TLvsz2+lNovtuez/K4RbSK3eyWFUNygZhQE6JnYTla147eHKIrcdtttvPPOOwB06dKFzz77jP79+/vaPPTQQ9xyyy1MnTr1P3il/wOwLZbIKgDRhlj/PIJaSg2MDJ5FkLoXTncJQereKGS/T3pdbn4lRWW19OwcT1jImT1Gmw6QGy8/0+Nm3j20CKvbwUhtV0xlNYSnStf88cm1OBr8A0vtNSwp2s68jAt+88+iVihIDPvj0hD/E0iPeIVQ7Tg8XhPhuqkoZG0j/r48vo9/bF8JQLK+mtmd9/h8KWssy4DmxNfdo4YysXMmm8tPEqnXcUFiJ7QK/3deXFHLA2/8QHZNNS6Df6LrSJk/3nM6m3t2toY6i52vNu9HFEUuHd6LcL2OF7IW4AorI1TwYApzY9Kp+Lk6j4uKe/nIKoBKi4sgmwyZVoo/ZcgYkT6UbsZu/Oujj3FXKrEdCcKlt4BGiWD3Ih7RMiC8Ex30UlzgcCtQyT3IBLguZRLdQ1uOzzJCUnhnwGvUu+sJUYYgE/zpp/mWStaW7aeLqgOXKQaw2Xuf/xpd+7n5guuI10mqrcTwtyi27kMrDyVG2w2318Mnp75jfexuYoPklGVHUbY3Fm24Da9VTnGlnMVJW7moT0+0inOLD/YZv8HmkeIzu8fEXuPXXBD/MDmlfsVerKGeePmjeI0yBN3VktqzCWQNSntRJsO6PgpyPagEBSPnjiAyUppUffH+mb72y7KyfP+7HUoqcsP5e8owLhjWD4srlJK61xAEFUmhD6JT+QkguVweoMwT5P4JW4CH77yQpPgwqoxmLhjVlb49kulVm8yJ+lJ6hqbQQd+cTKqtNjN/+itUl0tKtX2/ZPPgv685672L1hiI1hioaFBthamCiNO2XZn6X4HfUWH1n0CbCavi4mJuvfVWHn/8cUaOHMn333/PddddR2FhIQ8//PDve5XtCIDYwoPVuOpatF5DdKeW0+eKaqzc89V+TlVbmNwjjsendfO9rNqKnAozs97ZSq3VhUIm8Obcvkw8k+9U7yuh9CAc+0HysJrysm+TQi6jS+UKf9v6Uji1CbpfIpWhb4Smy+04NwztEMnQDpFtaOnHmqPlLZJVAFanh9fXnuCucZnNtmmVcuYMTMbidPPsiiwKjVYu6p3AJf0S+WTLKVYcLgOCWYZUirfMG0Y9WvQ0pCp2nX7Wa1t+sIQXV2ZTY3X5FDIfbclj2R3D2V9Q26y92ysy/Y0tTI7rib1KiUaQ9tnh9SuDksK0XHrhGARBoFdSCFty/KmLZoeHuBANoztFcdvoDLQqOa9c1pubPtvtS1vbetLI1Nc388WNg4kNaf4bFAShWWqrxyty5Yc7OVhoZJ/6PuSCBQPwqPJztnq7kSUmo1PJA44xNMP/Pe7JN/Lw4kNnvFerjpSz8kg5U3rE8cblfXy/ebvLw1PLj3KgqJbBaRE8OKlzgBm/sokxv1Iuo87qIiM6MBW0qMZGUY2NHXlGssrq+fcVfXF7vL5j9U0OY3a/RL7d4y+Fu0/MZP9emDLdS7A68DxRejUjO0b5SCKAHw+XcrTMxPI7h/PuVf1913+0tA6Lw0PvpNBm19sSLhuQzGUD/B5oSeE65g5KabV9nc0VcB2nqq0cKqpjSIezK1Weu6Qn0XoNxbU2ZvSOZ2Ba+Fn3aUc7zhXff/893333HQsWLCAmJoZXXnmFUaNGsXTpUsaP/+uZVP+5cebIX6vMRKts3mcCiI4tiKbHQXQgBN+DoLv4nM++atNR/u+NFXi9IuGhOt59Zi5x0a0TPnFxcXg8Hux2O8HBwQEKPLVHzjStPw3PbDbjdrul6nOywMkAleyvqU7/IyAIciKCZpzzfstP+SvypYRUBxRRMVkPsSeniH4ZiQH7eEUv8eFBzIsZxMmSah77aCVuj5d5kwfRLTWW5z9bx/GCSrxKQO+vzJIe4SfRzlZFTBRFXlyzmR8PZ1Nf78BldCF4YcWebL554ErCZVt4OGUrckFkT30yH2jGUVpt4fpvvyc0XEtdjQ2nQcCtFWBNJNrBNQhKkZG6gaSHJRKjjIQ9sdjq7dR21ODSS89ir9BIRnVIYe5lQ9BolFyZMoYvTq3H5pRTW6Ln6ZUH2dfFztNzJ6FSNH9eFTIFYapA0qLMVsPNO9+k3i3FpkO0qaRFyBEbTXoqZZpG/+tIDfZXIFxSsooVZRshBMJDwOOSU5ETiaUkGMEFY4YcoFr/Ax/lyBgefRu9wv2/eZOzjI3lr2Pz1NAjdAZdQi8MuDZ5k4INckFBqcVE9y6xFP1Sh4DAq7N/JjWkCpzgsu8giw/oGT8cUXQhNOw/5dKBbF51mCNVNXjVCihXYAc+WbKLEf2bm2gPTU4mJiiIcouUwaDNdfD6tys5crCYBx+7CINGiuu9XgsWiwWZTNai51lTqNVKbrxieMC67qEpdA9tPT47sjPXR1YBbP7xAA+8IZ7VsF4tV/LOwOt478R6PHi5ocNo9Mq/WGEcUZD+2tr2T4429zAbN25k/PjxPPjggwAMHTqUsWPHMmvWLLxeL4888sjveZ3taITMGD1XD0kJSAk8W4rKaTy8+LBPefLZtnx6JIQwu5U0mNbwze5Cn6rE7RX5eEvemQkrmQymvCj9tYTQpEBFTYg0mLx6SAqrj5azv7CWyGA1D58h5agdvw+SI86sPPtoS14AYWVzerj2453syDMSGaymY0wwW3Ml0mfziSpiQzTNKuqFB6nomtqT0j4/oq9eC/o46D03oE25yc6jSw9TWmdnVr9EJnSNYf7X+5v5Gxlc1SxavYnskpZl1W6vyDFXDI+GPE1f449UY+Attz9QnNE7wdfRvXJZbx5ZfJhVR/05+aV1dqb3SiApXIfN6UGvUjS7hpxKC6NeWM/tozuQW2UhJSKI28d0QN2KTLnMZOdAYS1q3IQKloBtEUIdQ9MjuHJwYIddY3FisrtIDtcFeNbR4HMVrlNSY3X50jJPX+GPh0q5dEASoxqURK+sPs6XDUUPDhebcLg93Dk2k+gGUm1S91jGd4lhzbFydCo51w1LZcTz6zDZ3UTp1VzQNYZdp4wcLzf7zi+lJe5lxeEygtUKXpvTm9Gdonlhdi8mdY/l+k93+9rKBKFZ4YPT+ODq/izYkc/jPxz1rcursnC4uI6BaeHc/91BvmtEgA1KC+fzGwb95sR2sFpBRJDKZ2IPcOsXe3hhdi8mdG05veA09BplgHKsHe34PbBy5UoeeughLr/8cgDGjh3L448/zvTp01m6dCkTJkz4T1/i/w60F4N9CbgOgaBF0N/fpt1E0YlYeweIUh8gmv4BqgEIinOLz776YY+UHgUYa62s3HiUa2cPabW9QqFoMYWUFtRXcrkcWYPx+e2Zk/nbvo8wOs10NSRxSVLr52jH74Pk4FC2IfXfFdZA1Xx1pYGFJ/YHEFZ55nLu3fshFY46uuiTKFgmp8oo+Tzuzylm6VPXU1MvETNyF2iMEJceSr/MROYN641aEKV00eDACavDdSf56OSPiIhcnzaF/EIXH27d49suBIGqHgqM1fyQu5IxIdt9FaH76QtYKa/hGAaqrTaGX9iZrYfyMHslP0mnXY1neSwCcOEDgwAICtbwfy9cxvPvrqRS5ldkHTEZ+fiquchlMkxmO4r6SEqOn1ZNCwixsPxUDoff+IyJgzpxqr6WkcmpXNKl9T56T02uj6wC2G8v5kLvFWTLFiIKbvqGX06UJpCALrXVohBkRGkMlNjKA7bFBonY9SpqXQ5iNTV0zZS+PxEvv1S8RbfQqShkkn/VipLHqbRLHqlry16g3qOgZ+hwNHIpPusfcSVFlv3UuYoIUcZTWNeHeWvexiuKdBkZzXhFOh2j3/WdWyHzsnDPQrqo3kXu3oGoyEAIfQ+9IZHXF9zCe1/9wmc/+uMzeSsTgJE6HUsun8u/f9rMmkX7CSqSyLuN647ywKMzQKxBNN4A7iMI7iTyTf8kLKILMTFnjpfOBzGJ4QiCgFcQKZkSjqWjjkkLP+PtydNJCz2zYio1OIqn+1z6m19TO34ftJmwMpvNxMUFyvEmT57MTz/9xJQpUxBFsU0Majt+Gzw5ozs3Dk9HIReIP4c0n/JGpeNpIALOFaf9YFpbPmdc+jksuxNsRux95/HQViVZZZsZ0ymK728dQpXFSahW1a6w+g9gRu8ETpSb+fFQKSabK2DQDmDQBH73X+7IZ0dDqmCV2UG93RWw/UhJHRf3TWTBjgLqHW5kAjw2rSsOl5dFBWbGdr6BQXEycFlA7Q/A5n+930d8HWwwzm5KFF0o20k4Jt49PB5wIcOLl+bPjAhstKfzjfsm37qHQlZysWwzEZXpUPcahCQSrdfw5ty+dHtsZYCJuUYp46dDpcz/en+LBvM0GM+/vMZfB7rK7ODpmc2NPgHCdSpCdUpqrfCdZySz5Juk64zuyjtX3YpeHzg7vuxACfd9cwCnx4tBq2B4hwiC1Qpf+qJOJafS7P+eFDJofJler8iRkjr2F9ayr0nRg8+3F/DdnmI+vKY/QzMiUchlfHBNfyrq7ejVSm7+Yg+mhkIOlfUO9Bols/ol8vRPWQHHOe2lVWdzMf/r/ex7VEoVGdslhqsGp/D59nxkAjw6tStaVSCRV2t1ctuXe9lXUEv/1DDCGsg3AJkgEe1HS00BZBXAjjwjW3KrGNMpmvNBUY2knOocZyAt0p9GI5cJfHjtAB5cdJCsMik4rrW5uGvhPg48dkH7e6kd/3G0FJ89/vjj6HQ6pk+fzrJly/5j1/a/BkEWBOFfgye/wXS9jWk+otlHVknwgLcKODfCSh+kPuPyuUClUpGUlER5eTkymQx3qJwHD76DxWPn0qQxLB7xMHUuK+Gq4LMqGtrx2+Ph/mMxu5wcrCqlrFzLRouH9NhyTBV6dm7rwvQBgd/9myd+oqLB5PtYfSGu6GAwSuSTyeqgpLqO2eN68X8frUIUIVyu4ZXLprB990lWrM5i2oSeaDQavF6vj7i0uO08cvB9LB5pLPHIoQ+4gCZpx3IQ5F46TcxlRf1B5mmbxE1Ofx/qlYlUe/3FT7wagU7p4YzplkRCqMJ37m49krjz7gu54Y1vfW1VSjkyQeC1zzfw1U97sMULkNb8ucxx1ZC9dzsAy05koVbImZrZucV7nKwLzEqIURiIFQfQST+W2PiYAHUVwLNHfuCbfMkUPtwVzZDoaAQExIZpwzJzENU4QAmykMDYQWzI4dpyKI/yWjM10QUBWz8/9RGCsIEnu99PqCoEvTKauekfY3XXoJGH0m3hq3gbsm2OWSt4aPwYLLKBBIvSZzU5VXTQlyF3Nyjy3TmI5hcQQl9DrpBz9SVD2J1VxNHcMvRBGu6cO6rZ/Si3ZbOq5F9YPUYG9hjDjtc9vgnRyKhgysrKiNZ9gOCW/F01ikKidF9RWnkHUVFRvufmXHGksIyyGjP9OyQSEuS/5xk9krjr2Ut5be1m6rtIsWS2sYpHN67l8xmzzutcfxWIYssZWa21/bOjzYRVv379eP/995utHz16tI+0SkpKYsqUKb/1NbajFZxN/dISLh2QxFPLJcWCXq1gUo9zN5i7flgaO/OMbDpRScdoPY9M+ZWV9WK6wjzJgPmx7w6yeJ9U9etYqYnEMB1XDEo+ywHa8XvivomduG9iJ2jwWnr6p2N8s7uIMJ2SF2f3CmhrcwaacQapFTjcEnmikAkMSougU6yen+4ewZ58yQNt9dFyXlsrkTsfbM5lofJJBspzYNJzMHAeALmV5oDjujxeusUbOFIi5Z9HBqt4yLuIMdZnfG1Ok1WnfZuKa22oFDL+PrETb67P8VWEGy3bx82OT6Wdck7C4lvg2uXQkAL33CU9eOC7Qzg9Xq4blopWJeeOBXvxnsMLflcrfl8AWpWcj64dwDM/HeML9wN06Xo53SJkCJ2noFc39xp7YtkRnA1GqCabm58Ol/vur9srUt+kMuiwjCg2n6jEK8KYTlHIBLjozS24PCItZQPbXB5eX3ciIO0wWi8FCE3bywS4aWQH1mZVsOOk9Bm1Sjk2l/85MDvceL2iLw3xqYu6c+fYDJRyGWFBzSvhvLgqO0CVN6N3PHmVZrLKzDg9Xn48VMr67IoW76WuiWdVbqWZJ344isnm4uaR6a2+7w4W1XL5e9uxOD2oFDI+vnYAwxp9/t5JoTx1UXdmv7Mt4D7Z3Z52wup/EG63G6fTiU735/A+7NevH3v37vUprE7j73//O3K5nBkzZhAdfX5EbjvOHYKgAMW5FR8SZOGI6nHgkGIhFF1Bee6x1b03juPB55ZQXFbL8AEZTJ/Qqw17tY6QkBBCQqRJk6u2P0WZXXrPP3PsC97r/3eSg3571UQ72oYQlYY3R0nG/aIoUlxTxz8+/Zn9eaV0TYrm9ilDA9o7PIETiCEhak6bHsSG6UmJDqNLcgwdEiMpKKuhT+dEnnrpRw4clSaHlq8+wD9uH4pBryUlJQWdTofRafKRVQBWj51eGZEEq1WYHVLslxRkIDy+TvJtQsZ2czpDg3MRBHC5h1FYnQa4idEHc83gfqw+lIPTLcUQSrmM26b2wKBWYTQaUSgUvndZ/8xEZg3rwXdbDqFWynn88gl8sH4n72bthXQBbaWIsh5cesALCqsUg3ibjHx3lRS3Slj1CE3l710uZmnRDkJVQdwUP5Z4XQR6vb4ZSZtTX+4jqwCqFRV8uc9BiBBHhGDHc1JFcaxfYFBoNBAmH0SNR9pnSNQNfLB8D+8vl5YnTI8mMUMirVxeGXUuLQ6xirUVv3BJojTWlglygpWReEWRpuGcDAF1xL/5bOffcLmNfHeqM7d1LQhs5PVX3gvSqnjvycupqDYTZtCiUTcXI6wufZo6l/Q85As/Mu/xG/j5IxMKJcya24vq6mp0nnL0je6xXLAiCEKz+7V17VG++XATuiA1Nz0wmdSMlt8lC3/Zz9PfSx63cWF6FtxzOZF6/6TihZcP4XgHyNq51beu1n7uldD/cvhf9bDq168fKpWKbdu2MWRIoPR31KhRrFixgsmTJ/8e19iO3xA3DE+jc6yeU9UWRmREnRfppVXJ+fT6gQGD0N8KJ6sCiYmmREU7/rPQa5Q8c3FPrhycwlPLj/LU8qPcPCrdV3XwsgFJfL27kKIaGyq5jKdndudUtZVCo5UpPePo1VAhLSlc5zNif/D7g77je0SBjZ5eDJRlw4oHoOdloDEwoWsMX2yXOlqtUs6ojtFc2j+JpftLUMllzOgTj/rdYEKtZoz4/RVemt2LyT3ikMngRLmZaL2aaIOG9Khg5n+9n9I6G3MTPOCvYYBozAvo+Gf2SWRUZhRKhQy9RsmElzc2I6syooLIqQxM52uMfimtS5OLaqxkldZzw4g0OsXo+dePGoxZDq4RTczo3Zywaq1fcbfCoBk0Cn55YCxmh5uMqGDu/cafSukVISVCh8vtpaSR+rK19MX7LujEoaI6qi1OMqKDuX64VHlm4Y2D+W5PEeUmO+O6RPPAokMcKpZmcm8amd7sPRFtaNkrwO7ykFMR+JuXywQ+vX4QfZ5a7VtndXpIidCRX+1Ph7xycDKD0iNwur0+EumGT3ZxqqHNnQv38XOMPsB/K7/awtM/HWN/QS2WBrLV6fby2bZTAYQVQK/EUPomh7K3wR/t4r4JzRSGdTYXL67MprTOxsV9E5l8HhMC7fhjYDY371vkcnmblOIffPABL774Ijk5bS8O8Xviuuuuo2/fvjz22GPN0nX+9re/IZPJuPfee1vdvx1/Dgihb4D9ZxDtoJmEIJy7OiolMYKFb9zwm8dnLq/bR1YBeEQvJbaqdsLqTwJBEEgMD+XT+XP4aXcWn6/fwwOf/MSDs8aQGS/1ZVenjeFIXQEOr4tItYFnpsxlpT4Xt9fL3LF90GmkCaSu6bF0TY/FbHH4yCqAGpOdwtJ6OutUlJaW0qFDB2I14aQFxZFnkVTVqbpYBsV34Lt50WzKOUVSWAgj0pPZdHQTnzskZc8BazIlziQe6/p3dKourJnvoKimjtSIMILVKl6YPYnnVmxCFEWuH9AVg1qF3eXB4fYQ2sTw/ZFLx3HzhYMJ1Wmottq497UVeFXSc2+JhdBDIvZkOW68vvUqEzgade/94lqvmn00rwxHucC9aTMwWeD/VuxApZBz/4QRdIkNnAQQm8hUTvMz9SYdNpuO8DwvSp2Iy9BQt9AjEFx3FZN63IxC0GBQxfLw5vd8+6/+qTuTZqUjhOVS6JTjEKV4Qyk0J5JkgsCTAyfw8PaVuEUvU1O7MCwuBUEQmNn3DRYePcisHjLGddaB6RoQ6wAlQtC1AceRy2TERbXsUVZbb8PsDJx87T4gkgsGTKWwsNC3rqJ+Ivrw7SCa8Hg1GO0zSEiQ7DZE0YkgqCjJr+bpe7/C3UBMPnrLZ3y2JjB9emNuHh/t2MOBvFJEGQheKK2pZ9X+E1wxondA2xmduvDJwb3U2O0IwNU9mlcUPFFexdvrdyAictuYwWTGnJun738d/lc9rACWLVvW7Ad5GiNGjODw4cPtsuD/AgzLiGw2GDsf/NZkFQ1l5nedkjy25DKB8V3ag6E/I276bI+v+tk9X+2nS5yBDlHBRBs0rLh7BEdKTCSGaUkMOzsh2jFGz+Fi/yxPR1lDgCR6wCuphZ6Y3p0ucQZKa+1M7hHnIx0CvJ0mPcu/v3iK+6xXYyKIW0O2cYnlKKikTrB7gj+1LiM6mB/ubDB3rErD++57yFzSAHaRvR8j6+1E6zWY7C6u/3gXu/NrSInQ8el1AyltklabHhnEfRM7cceCfbi9InKZQGKoBoNWRY3VSZc4A49P7+YbQFgcblYdLUOrVJAYqmXWO1uxN+TsqeQyn3pqf+F+OkQFB1w3wCNTunD/twfxtFHD+8PBUm4dnUHXeCkIaWr6fpr0ERrIsGi9mocmtzzb2CXOwG1jMsitNDO7byKRDd55MpnApQP8qSvf3jKEbbnVGLRKH1n3za5CVh0tJzMmmHvGZ/pIMY9XZMm+YirrHSzZX0RWmZ9IUClkXNY/iVCdkvTIIE5WSaSgXqPgixsGkV9txaBVkBYZhAhc+s42dp4ykhkdzPtX9/eRVTQQevnVlgDC6tqPd5FX1ZxobCnNWaWQsWDeYNZnVaBRyRndQkXBv31zgDXHJMXbuqwKvr1l6BnJynb8Z1BbW0tYWBgajQa53E/O9u3bl02bNv1Hr+18EB4ezubNm1tNt5g/fz7jx48nKenc0sva8cdCEBSg/W2qOP7W8ZlSpmBQeFd2GCWFfrjKQBdD62bI7fjPIK/cyCNf/IynYQLrrveWsuLxGwAYEJHJwmH3UWI10kEfi0Gpo+ushFaPFaRTER2pp6JKSoVXKGREhUuE/umxoFKm4MXet/NDyVYQRaYlDEMpU5AaEUZqhL/v6xHXg5FFI9nu3o5KUDFeMw2vMwlBLRCq1RCq9cclE7plMqGb5AtVW1vL4s17eXPdIVweL2N7pPHSDQnIZALHyiq4ecESKuotjMxI5dYRAwPjIrnAZZN7g0HBJxv2IHeCVqaggzYEq9dLvdzF9O5dmN6xiy8+K7MZ2V97giRdNMf31vPK0W9RdzPDMbCWGKgukCZd532xmPXzb0TZqP/INMQyM6k/iwslHyibUYPokSFrJGwz5IqY0gQQQFkPLy/ayIz+t/q2R4UGUVVnQUTElCLw5dEgdLqOdMksRa5w01GfzgWxI1v8vi5OT6FfuBRDZkQM843HQzQabuk70NdOVC0H12FQdEBQpOJ0uflgyXZOFlczok86M0b57StMdVbWrTpCrcPBF1sPktY3nl7DpYwIvTKW1KDByDyaBjJKuvdydTeEyBXgzkYmpJEaG4fgycJbMR28ZYjqCZQU3uEjqwAqSmux25xotBJpWlBTy23f/YDL4wEBBAOoGhwsDLrmRH5KSCgr5lzDzpIiUkPD6BEdOHa0Ol3c8PEiqsxSTLj7VDE/z7+OIHVzlX87/pw4J8JKJpPx0ksvkZWVRWpqKvfeey/x8X5mOiWlvfNqx6/DjSPSiQvRkl1mYkTHKAaktlfVOhcs3V/M8z9no5ALPD6923n7+TSFKIqYHW70GiV2l8dHVtFABDyw6CAnKy30SAjh9Tl9GJzurzRkavCxaqpGOY0npndDLgjkVJiZ4N3EjOoGWe/QO0Enff9ymXDGSm4ApI9m6IMD2LpgjlRp0gGsAyI7nbnqYGQG/4r/N5qcnygRI1hsH86163N5fHo3Ptic5ytSkF9tZf7X+1HK/QOB8CAVC+YNIjZEy4q7gzlebqZ3cijf7i7k1QYPq6IaG5e8vZVjpSY6RElkyYkGFVFaRJCPrAJ8ZBUN6qfcSnMAYVVnc9E3OYwtD45lzbFyVh0pY0tuNR6vSP+UMCL1alxuL2uzAlPmHI0Cg7vGZZJXZWHXKSMOtxdrg7JIBG4b3YH5Ezq2Wm3viR+O+Io9LNpTxLI7htMptrkKTKOUM6az/9n7+XApf18kKenWHCvH4nDz5IzuANz7zX6W7i9pdgyDVsH3tw7zEUyf3ziIV1Yfx+bycPPI9ACVHsCLK7PZecrou78vrspmdKcoNmRLFf4ig9X0TvL7ydhdnmZklQD0TAzxpcC29LnOlEZ9qNjvCeYV4XBxXTth1UZ4vCI784xUNJDFA9PCkf8OkyKNsXDhQi666KLA6/B4sNmk95tarW5mPH0mnA7YW5u4O11h7feAyWTiueeeo7y8nP79+3PPPfegVvsD+x49WvbQa0c72opHu13L8tKtWNx2JsYOJEQV3Ia92kHDu0Gsfwbsy0GeiBDyIoLit7G7cHu8uFwetBolRVV1PrIKwOktYHvRLOyeUuKCp9Ep4kFiNP5+sMZZT5Bcg0re/D0nCAIvPnoJb368AZvdxdjBiUSE6RAEISDF2KAMYm7KmQs7REVFMTdkLoNyBuH1esEDBQUFdOzY8Yzv2NDQUD7Zmo2rITZaeziPjUdOMqZHB/5vxXoqzWZkgsimnFMojR50ThlWldS2X0I8986Vqj6P7JqGyepgSKdk/vbsYk5tkyZGl+3ay7avsiirqKP/yDhy+x7ypThqTsRJZFUDdPEmaguC8TgUVFms1NrsRAX7U9Mqa8zcFD+Oq9KGs/xENj9V5ZBjqkbmEZjRsROiyo5V4WFzkV+15pAF2mg8df2FPPLhzxSb6qgJkvohq1XD3gOpfDZzBsPiM1rsX7yii6yKOdhckp9oVvkqusX9hExooVq1PAbkfkLnta828e2a/QBs2peLIUjDmP6ZWC0O7rr5E4oLjVijVbgMCg5s7kR5QQSD+0Rww/Qb0cpDQCGN/41GI3K5nJiYGAS5AuRRnKbzvDVPgLes4UOvpmvnQURE66mukMjQ3oM7+MgqgNxqo0RWNUBUSPW7pvbtwuQ+LU+oxgQHM61jy9vK6up9ZBVAtdlKaV09GdFnr/b83wpBlP7a2vbPjjZHTh6Ph+HDh1NcXEzXrl3ZsGEDCxcu5Pjx4wQFBbXhCO1oR9swpWccU3q2p9KcK0rrbNz37QFfutftX+5l1z/GE6T+dQOkQqOVqz/aSV6VREh9dv1AxnSKYn0DERCkkrO7QRW38XglTy4/QmaMHq1STq3VyasN/lT3XdCJ28dkNDu+XqPkhdm9yC6rp7Q2A4t6HEG6YMnbDGnQv2RfMTEGDdcMTT2zZ5AqCOqbkB/GkwGLJ8rr2XyiiozoYEY2qGQK5Ums8vgHrhXbv2abSY5V7B+w7/7CWl9KnlYpZ9ntw4gNkWYcM2P0ZMZI5M32k9UB+5322jrRJN0tr7r1NEJBgH+vyyEqWE1FvYOSWhv/Xp+D1emhX0oYX9wwiCsHp1BldlBnc5EWEeSbVX9mxTHe3Sh97gu6xtAr0R+gBqkVvHe19Lnmfbab1Y2qIPZMDG2VrKKBbDoNh9vLLzlVLRJWTbG/sC5g+ZcTVdAQaP9woDlZBRCqVQWooRJCtc080xqjqcF/vd3Nu1f14/Nt+dTbXczunxRQTVWjlDMwLZydeX7vrdtGd2DeyHQ0ypZTIs+GwekRPvJNKRfayao24ufDpTzxw9EA9WJciIbHpnXlwu5/bF+wYsUK5syZA4DL5SI1NZWnnnqKSy9tvZpQdnY2N998M9u3b0er1TJhwgRee+01nxH6Dz/8wEMPPUR2djZ6vZ6ZM2fy8ssv+7yBfi1OnjzJgAEDiIiIIDExkeXLl7N161aWLl36mxy/He0AUMmVXJzY3Ii5HW2A/UewfiL9761CNP0DIfzzX33YLXtP8ugby7HaXUwb051brxhBdEgwFXVSrDHvoh3Uu6RJpgLTp5htaew6mUpShIFtnl/YYTyKTq7hsW7X0je8+URNWlIkL/zzEg7W5eL1eklVx6NSqlCpJHJhc+UBDtedpKshlVHRzdOwGkMQBImsaoAoirjd7gDCanNJHifqqhgel0rHUCk+c3u8iIArBDxauGfFT7wgjiU45Bg3DfgFuUxk15GO7FjhJrjMiyJSRkZaNB9fN8tH7gzIkNSlXq/IgWw/YWRzuCiqr0Xmhb32LBSN/Lg88YFFaaQPIaJINaMO9fLk0e95tOs0FC6Rr9Yc5uPluwC4fGJf5l8xmjv6DKPAWItKISfWIMVJTpebm95cxL6TJQgC3NHEZywtLoIvH5mLw+Nm2CfvUX168kShpFNofKuTIU53sY+sArC7T2J35aFTnb26+pHc0oDlHYfzGdM/k6yjxRQXNqQANiI0yvIjEVO7S2RVA4KDg5ulowdArA9Y1GqdvPzlzaz6fg/aIDVT5wwK2N4jNoYwrZaahs/fJy6Gd26bTFhoG4tYNEFCqIGEUAPFtVIsHt+w/JfG/6qH1Zo1azCbzeTm5hIREUF9fT3Dhg3ju+++45prrvl9r7Idf2nkVVnYk19D51h9s/SndrQd1WZnQOU8q9ODye6ist7BgaJausUbyIg+O7nQFM+vzPYpUQ4V1/HOxlzevrIfC3cWYLa72V9YG6Do+fFQKfa9xc2O88LKbC7um0BcSHOPmAU7CvjHkkOIIqRG6Fh8W2/CGp6NS9/d5lMBHS6p47U5fagw2Xno+0MUGK1M7RnP3eMblRXuOgM2vyT9r9BC5gW+TYeL66QUPJcUND0+rSvXDkvj9jEZbM2twuzw8LbyZSbJd0MO9BB0/Cw8TZEozSY2fqfbXC0YblfnwvJ76FXZk+0EBiItIVglJzUyiMMNhFafpFB6JIbw2bZ8RFEiuK76aGfAjCnAnvwaFu0t4srBKUQGq32peafx0KQuXNQ7AbvLQ6/E0FbTQ569uAcquYx8o4VpPeO5sHtsq9dqcbiptwUaumdGt22GvUN04KRGYY0Vm9ODViUnLkQboNijgQSd1D2WDdkVjD6DSnDBjgJ2nTLSKzGEKwYls2hvMWaHG6Vc4MYRaWiUcuaNTG91/4+uHcCb63L4fPspzA4PL60+zq78Gj67fmCr+5wJz13Sk9SIIErrbFzUO6H9fdYG/Hy4lFu/2NssXiqrs3PrF3t5+8q+vxtpZbfbA7ysNBoNU6dO9a1zu90sWbKEq6++mm7dutGtW8vlz2+55RZSU1P58ccfkclkrFixghUrVnD99dezfv16rrrqKhYsWMAFF1xAdXU1V155JbfccgsLFy78TT7H+++/zwUXXMB3332HQqHg2LFj9OvXj/z8/Hblezt+FQ7XnqTUXk2fsEwi1ec3WGwH4C0PXPZIy6JzL3hKQT0EQXbuGQX/encl1obJmh/WH2bMwI58ce8clu48SrBGRWT4koAKYB9tW8Xao93RRVuI6CJNrFk9dt44sYiPBz3c4jmePfYF6yr2AjAiqhf/7CqN+VaX7eL5rAUAfM8mrB4Hk+IGsy+vmBeWbsLl8XDHhUMZ1U3qgxUKBTqdDqtVUrqo1eoAFejn2Xv5545V0ja5gu8uvJIeEbHcPW04T/2wDk9D6Ghzu3l6wwZmTdgiGRsBg3pkU7MyArNXj67Ci0LtRCUPnHiqr6+nvLyc1LhQ8kokMkpopC4RLYHxXOeYRI4frMPRQYpvp8WMZH9vM3tcx3EDmyqO8y/bYmZrevrIKoCFK/dy8dhepMSGkRwe+JtRKRW8f+csjhaUE6LTkBrT8neuliv4aOrFPL1lIy6vh7sHDiXqDOIQl8fYyNgBZAShkret3wzTB1p3HD0uEVhR0SHI5AJej4imxoUYpMCtgKSYUGaN7oLNZmvV89HhcbC8dDlGp5HBEYPpHjQPb91DCHgRZXEImunEBIVx1R3jW9w/MjiIr66+jC937cVptTAtPZnioiLcLhdRUc3tGM4GtVLBpzfO5qPNuxGB64f3Q6v6lRXu2/GHos2EVW5uLpMnTyYiQpLP6fV6LrnkEnJzc3/P62vHXxwHCmuZ8952bC4PcpnAm1f0PeOguR2to2OMnl5JoRwolDriEZmRFNfYuPLDHdhdXlRyGR9e258Rmef2src5A0kKi9ONRinnumGS4fYNn+wM2H6aDGoJTnfL297acMIXVJ2qtrL8YAlXDUllx8lqH1lFg4IL4IFFB30Kr1fWHCczJthncP1zzE1ou0fQO7iWkN4zfEotgBWHSwOub/G+Yq4dlkavpFC+umkIf/v3Ai6U7fZtDxatjJXt4zPPRGhIATRaJNPPQWnhROmb5NJ/ey2UHeQ+cQsqeTlHEy+lc3oKX2zPp87mQiETuKRfAj8fLkenkvP8rJ6MyIzCZHdRZ3WREKplxeEyX9odDalSLaE1P8HT6BLX+uyR1yvy3Z4iKs0O7p/YidTIs6tkl+wvpt7hfxYiglQ+hdrZkNmEKHV5ROrtLrQqOe9e1Y9/LD5Enc3FTSM7MKRDOFd9uIN3N53k3U0nuWlkOg9Pbj5LuHBnAQ8vlkxcF+8rZla/BF+VSpVc1ozEawnBagXDMiJ5e6O/H9t0vBKLw31eykSNUs78CR3Peb//VXi8Ik/8cLTFyT2xIfx+4oejTOga+7ukB1533XUBHlYffvghl112mf/6PB4uvPBCBg8ezPLly1slrEpKSpg9e7ZPbX7xxRf7tj377LPccMMNjB07FpfLhV6v59FHH2X06NF8/PHHaDQtFyA4F+Tm5nL55Zf70g27dOnCoEGDyM3NbSes2nHeWFK0iTdzFgMQogzi333vJVbbbtNwXlBPAPM7DWbXIGgvQbR8hFj/rLRdFgsRixDk5xaf2R2BymKbw0VMmJ6bJkqKlRcOxdE7WCJcrB4lx+ql4wuywLeu0xsY551Gqa3aR1bRoKgqtFaQHBTDLmNWQNtdxizGRPTnjg+WYrJJVZjv/XQ5K/5xPdEhwdjdbrZbTZgtFi5MTiM+KjrAd+/73MO+/x0eNz+eyqJHRCyXjuhFnczJCxt/8W13iS4QAtPp9Do4Pf0wdlRgzOByuSgoKEAURW6b1ZslG08gV2pIiw1n4fe78Ioi+sIo+oaksN+cTZIuhge6zSFmQDhVDuk7i1SH8H/uZexpVKSnzGlit+wUQqQTscqf0iaeoYy0Ui6nV1rrRu8ml4WfS3cgF2R8PP0itIqzxzLl5g8DplQN2qEo5G0jmHulx7F170nJK8oLzoY4LyklgvsemsaXn/6CVqvi9nsnEhalw1hVistaR25uHcnJyRgMzWPNj099zA6jVO1wh3EHvUIGcaquP1EKO1ZZZx6OMHC2ni8tIowbe3ejqqrKf29MpvMirGhQVT0ybex57ftfif9V03Wr1dos9S8oKIiysrLf47ra8T+C7/YUYXNJnY7HK7JgZ0E7YXWeUClkLJw3iOUHSlHIBab2jOfhxYd8BI3T4+XL7QXnTFjdNLIDW3Ml4ihMp+SaIakB20N0gaaFgoCPfFIrZDgaSKo5A5JIiWiZGDE7AgOPJ5cfZc2xCm4ckRZwvI4NKXeNq8M1Xn5hZRZvrs8FUgnVKflhYDqNbYbjQwNngxovd08I4coOdoSigCaUIil8Yg0aPrl+AL+cqEKlkHFp/6Tm8mxjHgBKwYNc8FBcZ0ddZeabmweTV2UlRq/mkaWHqbO5cDbyjzJolD6Pr6EdIkgIba46aoxeiSFc3Dex1e1nwz+WHGLhTqmqy7sbc1lxz0gSQs9cHU3W5LOG6to+O9UlTk/3BIPPXH9Uxygf2dc9IYSldwz3tV26v5iiGr8s/4vt+S0SVrvyAqvVrDtW6TNctTg9fLu7iEennb0sfGKYFoVM8FVZjDGo0anOLyWwHeeGnXnGZkUMGkMESuvs7MwzMqTDb+810ZKHVU1NDfPnz2fZsmWYTCY0Gg12u52uXVt/lubPn8/8+fNZs2YN48aNY8qUKaSmSu/Jffv2sXHjRt59992AfbRaLcXFxXTo0OFXf47W4rPTSoZ2tON8sKxki+//OpeFjZX7uCx53H/0mv5bISiSIWIxODdLHlbqEXgrRvsbeMvAvhKCrjyn415/yRDeXCAViujaIZahfdICtu8zd+G4RYlBYSPPFkmdU3pPWCt1xKc7sSvNyAUZ16ZNavH4apnSN3sQorDSL7SAn4qup0fYdNKCOrC+Udu0oFjqrHYfWQXgdHuoqDMToddx1Q/fsbtMUt+vKDrFtzMvDzhXfJCBfVV+i4CEID8Rcnn/niw6cIiTtXUIwEXpnYj3jqBEthmAJF0//m/+nWzfmUdCXCijRwZ6Gbndbt8kn1olx4lIZXUdSUkRvP/CVZRV1KFNFnn25KdYPQ6q6+qRuSUyLVLtV0pPju/J4oK9uEUPMkGknHJWeE4SMd1L7fYI3EcNzB7Xi9T48yN2nR4X9+17HSUHEYBNlXt4uc985MIZrDAAgcDtKnnbx1FjB3fky+W7MVul723qKP/EzIRJPZkwqadvubi4OKCKdk1NTYuE1fH6477/PaKHHcZduLzBFLmCgSqOmI7TL6xns/2aorECD/ClorajDfhfTQkE2Lp1K48//njAstlsDlg3dOhQLrjgglaO0I52BKKpCiIyuP1l9GugUykCqrVFBAXez7Cg5vfX6fby1a4C6qwuLu6X2Iy4GJgWztq/jeJkpYXOsfoAHyCAm0amsz6rghqrizCdkttGZ7BobxFapZykcB1ZZSY6xeh5YkbL6gQaCJtaq3+m0OUR2Xi8ko4xwbx8aS8W7iwkWq8mVKdk7EsbAvbVKuWMbTD4XrTHzzbVWl189Esej033n/fyAckcL6tn9dFyOkQHN7umq2bPxv3vF1C4GrylIjJ4cM49XGG00icpFINGSVpkkK/CXTN0uwj2fc5Sz1Bedc+CWsiqlUj9t+b24831OT4/K5vLw+1f7uWG4Wks2V+MVinnjrEZzOqXxJLbh/HzkTKq6h281uABdhpPz+zO7P5JKOUyHG4PBwrrCA9SYdAo2JJbRXK4jn4pZw6Wvm+Usmmyu1lxqJQbR7SeOgcws08Ci/cVszPPiEImMLpTIPG5+5SRb3YXcrzcjEImMDwzkrvHZSIIAmqFnK9uGsLyAyUo5TKm9WrdiyGqyfOl17TcTTUlH6MNaoxWf8nr8KDWCbXPt+ez+Xgl3eJDuH1MB16/vA9vrs8hSKXgseld26vd/kGoqG+drDqfdr8F5s+fT05ODjt37qRDhw4IgsDkyZNxu1tWINCQEjhlyhRWrFjB6tWrue+++3jllVe45ZZbAHjqqae4//77W93/t8CCBQvYvduvDj1+/HizdVdccQUdO7YrANvRNoQp9RTiT/cPU527pUA7/BAUiaBoRNLIwsHbyMNR1tzz0O6uoNS8GLmgJUF/KXJZoC7lymkDGNwrFZPZTreMONSqwP7y2rRJvJT1NV68ZAYnMiSzPxs8p4iLCAaliyq3kUmJ3ZgQO6Dli3YqMO0PQ9+zhr4RBegVDtwi7DN+zeT4/8PqGcfhupP0MEQxSPc95dbnuWNKIm/+2BsRgfSYcDJiIykw1bG3soAOSRVEhpixOfM5WDWYvtF+wv7xgRMwu5ycqK1iXFIGV3Ts7dsWrFbz6WUzWHvwMKFqNcmGYMJCeiILm41bdJCg643bC6kpUchbqJZ6Ov3Q4XDw1fpsth+T0t5yi6uJjTAwa1wv7t//Fia3RPJXyWq444t36bEnjEPbc4nqmchtj15M306pfDn8ZvYa88mpL2C/aT0haql/ih7t4KGrbqRTvDSZaHKZKbQWk6CNpazayfGySnolx5MS0bryKd9SSr/gn0jXSqqiPFshlfZriNWeubJ7fMjd1Dt24vKUY/dGUuWdRGNt7c+lO9hdcZyCA1ZU+WFcckFvxgyS+oLkuHA+fvpKdhw4RUJMKIN7pbZ6nqZFQ1qLlULcMdQgedsKCGhkOlxefz+uV7RsJ+H1eqmoqMDpdGIwGAgNDcXpdGIymVCr1T5fyHb876HNhFVISAglJSV88sknzbY1XqdSqdoJq3a0CJPdxTe7ChEEgcsGJBGsVnDTyHSOlNTxS04V3eNDeGjS2Q0CzwVWp5tqs5O4EA2KM5hJ/xVhc3rwiCJRejU1Fid9kkO574Lmg5U7F+5l5RHJT+Gz7fksu2MYFoeHGIMafYPqJy5E26L3FEDnWAPr7xtNbqWF9MggwoJUdIzVc9Nnu9nXkJ54vNxMSkRQQPW1CpOdR5YcprjWRpgaClo4dpXZycw+iczsk8jXuwp4YNEh37Y+yaGM6xzN+K4xdIrVk1dlodrsDNj/q12F/P3CzmgbFDMymcATM7pz86gOvLz6OE8sO8qNI9Lok9wQKIYkopi3FvZ9IVUoHHwbHZRaOkQFsz67grujVWzFAAEAAElEQVQW7qPe7mZgahgvzu5NcoSOzScq+X5vMbEhGu6c+BK6pEGc3OeFRjzTyUqJAPPWBXp7ub0i727ym8Lf9+1BduYZeX5WL64anEL5xg+Yp/4HAE+4r+Zbz2g+/CWPKwalYHN6uOy9bRwskuTqQWo5lgal2hPTu3HN0NaDDm+TdMLSM6i5TkOjlHP32Eyu+mgHbq/Ih7+cIkSr4q5xmRwvr+eKD3YEpHzuzq/B4xX52wXSdx6sVjBn4NmrIg3NiOSWkem8t/kkXhHKTQ5eWpXtOw4N3mYfbvan8SlkAnePy+CdjSc5VlrPyI6RrRJwi/YU8c8lUurBqqPluDxe7pvYyZdS2o4/DtH6tqXDtbXdb4Hdu3dzyy23kJEhFYiw2+3s27eP5OQzP7tJSUncdNNN3HTTTTzxxBO88cYb3HLLLQwYMIAff/zxdyWsYmJiWLt2LVu3bg1Yv3Xr1oB1I0eObCes2tEi8i3lbK06RLQmjLHRfREEgfmdLuWpI59Saq9mdHQfxsf0b8OR2o56Vz0u0UW46n8vzdDmKqJETCSBfJQ4ELQzQTM5oI3LW8+u0suxuyVSq9K6ge7Rr2N1V2NQxSMXpPgsI7l11fwFsQPpGZJBjaueDsEJqGQKghIEXju6AbEavB4Zh6q20D00mWGxfnVWqfUwWyvfwyt66aiO4+CyJFTXHoVG80B2bx03pE8FILfqboxWyX+qb+ZJnr6yG1V145g5sDsalYLjlbl061JApFYihHRaJ6uqF9E3+u++40Vpg/h0/KVsLyzk8/37eWTNGv42bBiRDerRmIgIpvbrg8ViQaPREBYWBiQA8OqBX3j94BbkgsDFKT14dNA4dEol36/Yx+HjpfTsnMC08d2pra3FaNkfcI8KyiRixWINjINKrRay1EoYFcPJeid7H/+KR269kMkju9HJEMvHh4ycVPlJGEHmYpPtFzoxh0JrCU8ceYl6twUlKrJ/icNSo0GrVPDJvNn0SGxZARWsqPeRVQBp2mqUQhVwZsJKq8xgj/2fLC1cQa1bC/zA6/1i6R2Wzo8lW3n1+LcAKFPcdFLV8MPOn0mI+ScdU6XvPDEmlMQLep/xHDRUe7RYLD71rslkor6+Hr3eT2av/OUYqz4ViZodhDLYhcodze1dL+bz/K+xuK1Mi59AR33L8VlJSQm1tbW+YysUCmJiYoiJiWmxfTvOgP9VhdW8efOYN2/e73s17fjLwun2ctm72zlWKqlLlh0oYdEtQ9Cq5L6KZb819hXUcN0nu6i1uugWb2DBvMGEaP93TPb+vuigrwKbQibwz6ldm6mjPF4xoEpcZb2DmW9tpazOTohWySfXDfCTOU1RVwTb3gQEQofeQb8Uf07+fd8e8KUCnsbx8sAqIX/79gCbT/g75omynZSLYRwSO+BBhkoh47JGarGmaYAer8gdY/1m6/9el4OriW+AzeWh1uZEq/KTbaIocsX72znVcLwN2RWsv2800YaGQXF0F5j4r2Yf975vDlBvl1QWO0/VcOFrm3j1st7c9uVeXzpZfrWFt+ZexbjoWt4+uQ1nQynmSd3jwFTC3MM3sUT4G7liAloc2GjuTfDN7iLundCJWLmJmI0PgCCd8xnFB2zw9Ca3EvYW1FBUY/ORVYCPrAL4dNupMxJWaZFBHC/3m033T/UPGHIrzdzz1X6Kaqxc1DuBf07tyoGiWnQqBZtOVNL4Fq/LquCucZnsya9p0Z/s7Q25zOyTQHrUuZU/75EYGnCeDzbnBRBWv5yoxOb2N3B7RZ77OZsN948567H3FdaccbkdfxwGpoUTF6KhrM7eYrwkALEhGgam/XED2h49erBgwQIuvPBCAB555JGzWh+MHTuWu+66i4EDB2I2m9mwYQNdukiTL4899hgjRozgzjvv5M4770Sj0bBt2zYWLlzIkiVLfpNr/vDDD3+T47TjfxNF1gru2vsKVo+UEpRrLuamDtNJ1EXz7oDfh2hdV7GOL/K/QERkROQIrk+7/nc5z58RHq+d3WXXYHeXcBJQy2MZFv1Qs7R7k+Owj6wCMNq3sfDkLBxeG+GqdKYlv4ZG3rJXpcVioa6uDoVCQXRkpM97LMdUyWtHJZW6IIBM7sXjFcgxVfkIK6fXxvKih3F4pRhhyJgcQoXLqC3qTmzmPgD0imjSgof4zudw5wecv1e6SFKoP7b/tOBHFPLAGKHWFZjWD5BfW8u13y/CgQfBC9lVVXx/xRW+7QaDoVkKWnZNJa8ekPytvKLI1ycPcLSkist1nXnrk40ArN58DICZF/bmgsFdOXJSUg7KZQKj+nbAZDIxSujGCUcxqEW8NXJMpQZo8E50GkBeJfLpkh1MHtkNk8lEPyGRzaISBH92wNLiPdyYfhk/la6l3i1NVLpwEpFejWVPAjaXm8V7jrRKWEWo4xuG5qcVvQr0Sj8huerkCZ7cvAGP6OHBoSO5oEMahdZCItWRbKk8SbXrdKzlZXvVcXqHpbO/Nkf6vhGZHb2bxGSJEMp33k6GuASZ0PbMFplMhkajCUg3NxqNAYTVxl0noJsNo1wLNi1gZ0vl/7N31tFVXGsb/80ct7h7SIIEd7cibaFAW0rdC3V399vb9va77a0LtIVSb4EKtBSKu0NwEuLuJ8dtvj8mnOREkHuhmmetrJWZs2dmz5w5M+9+9vM+bw7v9H/xhPtvmcZus9mOX32wA+3j70pYnSzq6+tPW6nmDvx1cLTK4ieraDRbL66zt+tpdDrw4k8H/Wlm+0rMzN+Uz21j08/Y8f5o2JJb7f/f45PYkV9Lr4RAKbJCFEgK0/vJG6GxOhdAvd3NK78c4tOZQ1rv3G2HjydDbZ68fGgJ3LoJVDLpY3G0Tp8Z3y1whuSY6ugYBokHuUH5M4ekZLKmLKZPUkhAVcOJ3WOYvTbXTwKd1ytQESO18cQdlBJGdAt1RpnZ4T9fGv2OsissTYRVIwprbHy6uQCdSsF1w5OxOAPPyeby8u2OIj9ZBbAlVyY/eiWE8M0tQ/n1QAWdIg1M6xMPR5YR5iljsfpRcqUYYoRahjrfwNGCtFKIAlqVCPYGaGaEqhR8GAU7lVIIPp+EtmWFwmY4keH465f15fbPdlJW72B6v/gA37j7v95NVrFMhH20IY/FWaVUNMgDmfHdAiv2RZk0nPV/qyhvx4fI45NYeaiyFWGVX23lkQVZZBXX4/NJDE+P4N+X9MHYaHTe0h+rJdHcFgFWb3e3WtcWBqWGM39Tk55vYMrfb3b/jwKFKPDUlExumb+jWX0jGceGbk9NyTzthuuCIGAwGFqlNwC8+uqr3HrrrQwfPhytVsu0adOYPn16gDm6SqUK8Ix6+eWXeeGFF7jtttvQaDSMHz+ef/7znwAMGjSIdevW8eyzzzJy5Ej0ej3Dhg3zf/5bwev1YrfbO4L/DrTClpoDfrIKYHXFLm5Mm3rGjufxefis4DP/O3tt1VpGR44mzfi/+7n9GeDwlAYQUU5vGXZPMUZ1RkA7nTIeARUS8rvNhxqnzwYI1LiOsr/uO/qFX9Vq/3a7nby8PL9nk8vlIiFBTlOzepwBbQVBrkg3LLppgsvuqfGTVQA+wcUVI+MwMhC76iyCItQkGQahUzaN9cL052F1ycolARWhutaZNg6PCp/KcYwDYnD44FZtlh3NxqH0QKN36a6KUnyS1IrM25xXyMpDR+kUEUanFnEtAmRVlpPoCIyDdh8o4oJz+nDZ2f2IDjOSXVTF4O7J9O4cT1lZGd1NCVxeOIHv1+7DYVXiTvLgSXAh2kRUpbJKX6+VyR2v14tCEBmqGMsqz6+IgkS9S4fDq0RCQiMGkkA+b1O8Fm4MrMrXHGpFKD0iX+Rw9T+RkOgS/jBqhezfWO9wcMfSxXhMNhRqHw/v/JpfzDXYJDMqQUW0rheHms0Lm/PdnPfCW/h61EF/CFLaSdDWNTVQ5WJ152JSdwnoQ75lM2srPqDEXsthSxIjoiZwbWqT+k/Rovpiy+WkuDCEmsB43OI5sYqfRu9Fl8sVsNyBDnC6CKu6ujo+/fRTZs+ezbhx43jllVdOx2478CfD+2ty+GlvGakRBp6a0j1gkBll0qJTKfwG6yaNkrA2/JROJ1qmPXm8fwIK+b9EtcXJobIGOkUaiQmWB1Z9E0P5eZ+sDBAF6JXYdt787GsG8OR3+6i3y1XqfmmmuJIkObXQ6vIEkiC1+U1kFUBtLtQXQoQccN1+Vjr/WnoIGn3JnjgvUyZtmmFi92g+Wi/vQ4eD0eIeALqECXQZkEhL9EkMYcGtw1h9uJK0SGMrc/7bxqazPruKcrMTk1bJ9cNTuHl0OmKLwe7BsgZaomWVvHqbm4ve3UC5WQ7uVh+u4Lax6fx72eGAdj3jg1l+oMJfya9vUtM17pUQEkgQRmWC2oTW1UA3oRB3ZA+kUh00UyYpRXhmWndC9GrQdYIuk2QyEFju7UeuFMN5vWLpnxyKJMG0PnF8t6sEvUqkf0oYO/JrSQzT88IFPVud4zF8v7uEb7YX0S8phEfO7eb3NXN5fCzbX052hSWg/TGyCmD5gQruGJvG+pxqOkeb2JJbw9GqJuKxZ3wQRyutWJtVdkwMbZ1KeuunO/xeXjSm5v1n+WEemywbWw9Pj2DWyFTmbsgnWK/itUsDperD0yN46JwuvLrsiJ/AnDXq+B5cxzC1dxxuj4912VVkxgZxw4jUk9iqA2cK5/SI5Z0r+/HMD/sDDNhjgrU8NSWTc3qc/lTN4OBgLBZLm5/FxMSwYMGC425/ww03cMMNN/iXBwwYcNxtBg4cyA8//PA/9Pi/x9GjR/nwww/5+OOPeffddznvvPN+l3504PeD3evk3exFHLWUMii8K1cmnx3gPROnDUw3itOd/gIHzSEh4ZMC1TZeydtu+z87JE8eeMtA1RNBNKBVxqBRROH0yioftSICrbJ11Ti9KomeUa+QW/ceCkFHqVsB5AW0MbutKAQFBmUToW6z2QKqCDd/1vUIjWNEVBrrKuSU+q5Bsfyj3xQygptUPCZVDJGaDCqdsq+BXopB31h8Jk7bh/jgwFgOICZoJhplEnb3EYJ1ozCoA2OQm9Km8dKB+VTYTXQyBnFlynkMDW89GZpTX9M0WyGAQa9qRVZtLyjm+nnf+ous3DhiIMOik9lQ3qjycomoRQW9OsWxZ2PT5FT3zk3X+KyBnTlrYFN6tF4vk0gDMxMZmJnIPp+FR/evaPzUi4CPcFcQ918vFx0ICgqisrKSIVJ3dtkr2OsqQkTgri5TEAWR8+PPZZ/5MAW2YqLUESgtGVSrzAxJS+L6kW1nlXi9Xj555msObD5Cj2F3ccUT0/1VFKvMVr7ftR/JaCUqsgFRlAhR2bBJ8nfrltyY7QWcFzeQfGslfQxpfP70Xjk23aBG4w0hZWwibu8mVAqZEBIFDRpF4G/f6qlmSfFTeCUXegV0M5n5PN9Ht6AUBofL8VlERAQ2mw2r1YpOp2uVrnfdBUPI+7KUjZ5tSEofGlHFBQnD2jznloiNjUWlUvk9rDoIq/8Bf9cqgS0hSRKrVq1izpw5fPvttyQkJDBt2jSuv/7vI+vtQBOWZJXywhK5xO3Ogjrc1fm8ce1okHygDyPMoObdq/rz8s8HEQWBRyZ19fsjnSncO6ELM+duxery0inSwJVDTuyf82fEkfIGLn5vI7U2Nwa1grnXD2JAShivXNybuF90lNTZuaBfPP3aSe1LjzLx2Sw5cKi2OMmptJBTaSVYp2JU50j6PvcLDrePyT1jeeOyvjIBFBwP+nCwNaq4DJEQ1BQM3DY2ndGdIxEOLaaz0Ykqo2+r4z4xOZNuMUEU1dk5V9hE+gED6AbCea+1e6494oPpEd+2gjPCoOGRc7siCAJndYni2R/3M/iF5agUIlFBWiZ0i+KeCZ2JMgXOugXplMQGB6qr9pXU+8kqgB0FdXx03SC6xQbxr6UHqbe7mdo7Ho1SwZDUMOxuL70TQ7h3wnH8YYLj4ervYPM7oDayJWEWzi8Dg88vbxxK55hGVZkgwCXzcR1axmeb8/m8OoMLE8K4cVQqRbV2EsP0/OfSvjx3fg90KgWqk/Bo255fw11f7PRXXSw3O5l7/SB8Pokb5m4NSNFsDwatigW3Dgegz7O/BHx2uNziTwWNDtJw+aBkJnZvLX3PrbK2WldmDpz5fWxyJo9O6tauqectY9K5ckgyG3OqiTRp2k9dbYZqi5OKBifn9Y5lev//vspiB04vzukRy4TMGLbk1lDR4CDKJKcBnm5l1d8FDoeDBQsWMGfOHFavXs2AAQO4/fbbGTKkDbVsB/7yeD/ne5aUbgLgYEM+JnRMjh+GQqFAFEWGRHTn+tTJ/Fq+jShtKHd3vviM9kclqrgo4SK+KfoGCYmBoQPJMGacxJZ/Pkj275DqHwa8oEiF8C9QiKH0j/mYo3XvABKpITejFNsemEcbJhJtkNVKpbbd/Fz8CC6flTB1J3bUaXko63FEBG5OP58LEkYBBKhBaaxIegwKQeS9YZexqeIoHruTPqHxrbJiREHB+Un/x966H/BJXiIcA3HbBLRaLTEx7VefC9VPJJS2PYyTdUlcn3Q5CUYTnUwR/PPAJ/xz3yKUdcEYjyZz5egBTOzbmbTQQMXzkITWk5drs/P8ZBXAuux8vpp1Ge/v2cL8rN0o1QpuHzKYwiM1dBoYT5BHwcjenbhoUus49BiCgoKIj4+noaEBrVbL98WBaeAZfSN5aeYU0sLk/imVStLS0iioKyBV6SLEo2FY2BDOigzF7a0hRB3Gy70ex+qxYVDqEfqf+F325Uvf8enz3wKwY9keNHo1Fz8wjYp6C5f/32dUmC0EjbUhivK5C2ILL9JaG7cljyazexRH8iqY7zvm+SpQU6nlp+1ujujGcHHXHSRGB9Et6n6/eusYLO4KvFKTwkkjelGLXqqdTfYTCoWC1NRUJElqMz7TqJW8eNUMSu3jONJQTJoxlnj98T24AEpLanG5vCSnRJ2wbQdODEGS/0627R8dp0xYlZSUMHfuXObMmUNFRQVJSUlcf/31vPXWW2emhx34U+BQC9XKkYISpJdSEJBYFnEVkdOeZ3TnSEZ3bt8c8nRjaFo4ax86i9J6O2mRRrSqv2ap+o835FHbmPpodXl5b81RBqSEYdQoeXJK+6XY20K4UcOSu0ZSWGMjOkjLuP9bjcMtExCLs0qZ1ieO7vHBzN9UjCZjLtdbZxOk9MCYR0AdGHD12P08bHlfXtjwb7hxtWxk3ghRFJpVNOwM46/+r69BtcXJ+W+vp7BGlh3HBGkpMzepNaqtLg6UmokM0nLl4CQen9yNd1blYNIqeWl6r1Yv3eQIAxql6Cdf4oK1mDRKJmRGMyFTnk166eeD/GPJAf82t5+VfmISNqE/JMwGIKnGhlZV4L++SlFg+rsbCTeomT9zMA63lzu/2ElpnQ+PLwGwc6iymAU7ZeP2+yd25vazMgg6BeJ3f2kDzYWHx1ROudXWkyKrAKzNUiOvGpLMGyuO+SMQ4Fsm+WDtkUq25tXw6KRuZMY1+U5M6BbNd7ubUiIUAlzYr/Ws7Ymq9Zm0qjYJsbaw5nAlN32yHbvbS5doE1/dNJRg/d/H0+6PDoUoMDTtzCo7/urYvXs3c+bMYf78+RiNRnw+H59//jkzZsz4vbvWgd8R+dbAwXdW2RF0dbDGvo/woFCuyziPy5LHc1ny+N+sT5NiJzEobBBOn5M4bftVY//skCxvy2QVgDcX7D+A4WoM6lR6Rr18SvuK1ffm8k5fYvNUU+9WMWubnM3iQ+Ld7EVMiB5I7o4SNv2SRWiMkf7j01Cr1a0UMCIQYwGHQ6LIWkR9fT3JyckBbTQKI/3DL+N0YEtFAdeu/gKn14NJDSmRFqzexhSxoApKRBcPz62gU0wYl3fvzb6qClbkH6VLWATPj57Qan+dowLJj4yocJSiyK19hnBrH5mUv+L/Pmdvvnzfm3Qanho16YT3WGhoaKORO/S0Byp795dUMXn/J/SKjmb+jBksW3WAd+evIeKSg6iibGgENyrnQvaVWREFPRmRHxCkHY5RdfIKoexduW0ur8zKodJsRUBA4RCgMaOwzqlDjxuDzoXLqSTvYBzmrvLEX2piBH0yE9i1vwhnpA9zf/ke3Es0hzdNYpAtBY+6jKTIn3jkorEE6WWSM0yTikkRR4NXjs9qXHp0ilAGhbcuiHWi6xmrCyNWd3KWC598uIZ5c9YAMOGcnjz4xLST2q4Dx8Hf1cNq165dPPnkkyxZsoQ+ffrw4IMPcvnll/Puu++e0JC0A399jO4SyVsrDuGRZJXHWeJOhMZfwISqT7jpg3ieuOcuEkLbz90+nfB4fTz4zR6W7isjLcrIW5f3IzHstzn26cT8Tfl8t6uYhFA9T5yX2WYapV6tOO7yqUKjVPi9o1r6AhXX2njq+33+1J2ViTey6NZh/hfXp5vz+Mfig7g8PvoQxxyVgWDBCnUFcHQV9Ljwf+pbe1i6r9xPVtHoU9UWlu8v46WfDuJwe7n9rHTuHt+GIqpsL/Gr/sn6FCevOC+gwtCZRyd1bZVauOlodYvlGs7qGo3PJzF3Yx55VVYmZMYwIqMpuJq3MY9vtxXJabNTu/PRtYOYsy6XIxVm8qvl/ldbXby5Ipus4vqAc2qJ/1t2mOuGp2LQHP8x/v6aHN5amYNRo+TOcemolaLfIH1EukwQBOtUqBQC7hOkzYYb1FzUTJl038QuDEoNY09RHf9aGpguWWlxUmGRg6drP9rCmgfHsnhPKRaXm7zqJoVV74Rgnj+/Jz0TTs77cENOFa8uO9yo1OxGn3ZSXVviX0sP+VOSD5U38OW2Am4c9ffwTOnAXxvffvstL774Ijt37mTSpEnMmzePSZMmMXXq1AB1RQf+nhgcnklWvVyNVgCSlZG8Vb8Eu+SCSjhkKzpj5uptQfKWIdXdSZjnCGhGg/Zl4MxaRJxu+CQnRXUvYnVlYdIMJT74HgShDZWzoDv+8ilCozChUZiodhUF9geJ/buO8sylc/A1psmbq8Zx/SNTAJAkLwcqHqG84WdKLKHsL76Wy5IHAtDQ0IDH42nT0+90YH72dpxeDyARGlyD1RuYDipqvXh9Eq+uWM+qnFwMGjVvXDiZURmt0/Xr6+vJNGq4aVBvtpZW0CkinIfPHhXQxuHy+MkqgAa7k0PFlUQGGzHX2/n28404nR6mTh9AXIJMqLh8Ht45sojDDYUMDOvC1annUO9ysLIkmx35ZZjr5Im6PeXlzN28gy8+WI/PJxEdLMeamboSwpSN1aAlG0V1/yIzZvhxr4vL6+XhRUtZdfgoGVERTBnTjbXfbPJ/3m9cLwDCTU1jF9chE8qBtaCU8HkVFDuDEZ0SDXlBZAan0S9JznRQKkT+/eRFrN2SzUpLDp/X7vbvwx0ssStHvj5788vw+nw8MnkU63/ejdcrseybzgT3VyFFSGRkns3bI84lQnNycdaS0l9ZW7mFKG0416deSrCq7aIAzWG1OPjkwzX+5WU/Z3HBxYPI6NJRubkDTTjpp9Py5ctZsmQJL730Evfee+9fdjakA/8d+iWF8sXwCpZt3EKqUMYlilUBnz8nvMPuoqt+M8Lq8y0FfiXKnqJ6nvxuLx9dNwiACrODo1VWusaYZK+gduDx+lCeRJrVmcLqw5U8vmgvAFvzamlwuJl9zcBW7W4Zk87Go9XsLTaTGmHg/old2tjbqWNrXk2rSn/5NbYAn5ndhXWsPlzJmC5RZFdYeGzhPv9n2+jMC+7LeUn9gbzCFIvb6+PDdbkU1dqZ3CuWIZ1OTlHRnvT4GFqadLeHjTk1fs+j15YfYUJmNN3jmhElTgt8cj5YK4kAXtTvgBt24VC0vm97xQezs6DJwLLc7GBeI1H1YaM317yN+VwxOAmFKGDQKHh7lTxo2F1cT6XFyaezhlBnc3H7ZxUB+xZFgRqri+NBgFbeDi2xt7jen6pbb3fzwpIDXDU4iYNlDQxJC+fGRt+nCKOGV2b05tGFWQHVBlsaYT8/rUdAoQSvT2JkRiQDU8L4ZntxQKpf8+0qGpzcOG8ba9pQce0uqic96uSMoGusLmbN3eb3yLruoy1seHgcupMgaVsSju1dO6fHy8qDlaiVAmM6R7XargMd+KPho48+Ijc3l59//pnx4387lUwH/hy4JGkcUoObXEsJXVQJSEgyWdWIo9YSbB4HeqX2uPs5XZDM/wC3bNCNYwmoeoJB9oQrsZdg9VhJNaSiFNsfokiSF0H4/VTzxXX/przhIwAszm0oxRBigm5o1U4Iegqp9maQakEzFnTnn5bjLz2ahccnohTleMa1z8CW+iP4vD4EvYR+spMNitVc4BpBqDqUCstnWJ1fYVRD5zAztc5PWF2ewOjoWERRRBRFJG8lku0jkDwIhmsRFK19tVriRLEZQEhjlWZBkFpVCvR5wVloQG9U82u2HB+ZHU4eWPgzmx+8JaCtzWajsLAQgAmJUVzQrRMpKSk4vYETq1q1kk4xYRwtk6sQqpUKthwuxO50s+j1NRw5WArAr7/uZegFvVGpleSlZ7PHLsfbhy0FGJQ6rswYS+VuK2uKi0HTdI4ulwdfo2+p5YiJoB71rQQqAie+N+dv3sWSvbLX6+6iUgwpKoY/OwNHfhUTxvRk3BUjARjfO4PLR/Xhy3V78FarsSyPRBPvRNWzHhDwIWBKsTFn9PmoGw3QfZIPlVLBuOFdSawP59ule3H55LhJXxc47skuruLuqf+morgWSasGnYaqQnliUtO7gYhxJ0dW7azNYm7e1wActebj9Lp4uNvtJ95QEBAEIcB37Zh3V0u43W5sNhsqlcrvO9aBvwdOmrCaMmUK+/bt46mnnuLdd99l5syZXHfddWe2dx34U2HApOsYoC+DvHywpEFNjv+zKKGezFD5RVVSZ0etFE9Yyex/QaUlcLBf1bi8Na+Gaz/cgtXlJcKo4eubh5LawnA7v9rK9R9v5WiVlRHpEbx/1YCTGhCfbhxukWZ5qLy1WThAmEHNj3eMxOxwY9IoTxuZ/PmWglbr0qOMaFWiP40N4Ia521h06zC+21XSqn2BKgWM0TD4JkgeypML9vD5lkL//hfcOqxV5cKKBgdPLtpHSb2dHnFBLN1XjsXp4fax6dwxrm2fi3N7xHDZoCS+2V6ITqXA3FilUCHA9P4JhBrUDEgOZda87QHbnf/Weq4YnMzTU7vLKxpKwVrp/9xmtTDrw22sL7CTFKbno+sGktZYoe7Ryd3QqZUcKK1nT1E93+0qkQ3Qm90rEjB/s3wdW34ru4vqqLG6eOCbPQF+DKF6FXeNyyApTMdbK+XfUKRJw/l94siutLDyYCWiAI9PzjzhfVllCfSFqrd7mNNIpoUa1GiUTdtP6xPPsv3l/LintN39hTf6f607UsUdn+/A7PBw3bAUHj8vk69vHspH6/OwONzMGJjITfO2U1wnK8R6JwS3SVbRqAhUt1PxUJIkFuwopqjWzsTu0Xh9UoChe63NTZXFeVLqyUfP7crMedtocHjonRjCpYNae9q5vT6umr2FLXlyoDuldxxvXNa+70UHOvBHwF133YXH4+Hss89m2LBh3HjjjVx00UW/d7c68AfCRV3GU1ZWhtPppMJWg0ZQ4ZTkgX6sMhS9UovX56XCWUuwynhmyStf4LtA8lUjAD+X/cyXhV8CkGHM4IEuD6ASAyejJMdKpPoHQLIhGWYimu49c/08Duzuw8ddPgZB3ReiNoBkRxBPX4XOX2p34PIqcDdWn5OqtXTqHgeCRNjTFlRpPrw4eXrPc7zU9wUO1X1Lc21XpK6BQ7VO1Go1sbGxCIIXqfpq8Moxh+T4BSIWI7Tw1so6XMLbn6/BJ0nEdArjp92H0GvU/OPKcxiemUJbuLvnKA7WVbCruhiVZMItyLGsSalnpHc0ysEGoqJMPPXTrwAYYi0YOxVywbpHuSNjOmdF94fG6ofNkWMu5f61X1DqqGVgWAYv9bkGjUK+X9655ULeXLyekhozu3NLmbtCjv2MdU4MjbFZsdrL17/IxKl4ZSX6Zqe6ofIwMa4E5m3ajNYnYosTQIT+cXHMHD6QIyuL2H2giPLF8SRqUkgeNQGVOA+35yAKIYiE0EdO+B1WWwO9PLccKmBvsRwLDo4LVJw/dOFYftp2iFqLHdwibrOC5r8MpSiiVslrfiz5kUUli1AJKq5PvZ6BYQP5cvzVfJ+7F5OkYWi/FG55ZyGexsnbdIOJrGK5wjUtilUZg9pXBNq9DpaXr8Un+TgrajhF9sBsq2L7yWVfGQwaZt02jvffXI4kwZQL+5OWEd2qncvlIicnB69XjgHj4uIIC+uo8twehFPwpvozTMueNGHVpUsXPvroI15//XU+//xzZs+ezRNPPEFCQgKjRo06o3LSDvzBYS6B7F8hJBHOekxe56jH93p/RJs8+LeG9SA+PpFHFmTx+ZYCREE2VT5TFbqm9Ynj4/W5mB0eBAG/4frbK7P9A94qi5O5G/KayIpGPPfjAXIq5RfJ2iNVfLg+l9vGpp+Rfh4Pw9LDUStEvyJIp1LwyII93DgqrRXJBpySl9HJIKyF+iwt0sAVg5NJjTBy3UdbcDWmj3l9Ei/9fAh3C5k3wEVTz8fZ+xY2ZFejP1rNuuymQNXjk3hrxRGeG2UkKjIKDLLa6po5WzjQSNYdLSrlFdV79FbksHVVF/amzaVHSusXmSAI/PPCnrxwQQ8EQeD73SVkV1gYlhaG2e7BqFUyLC2Ca4el8PGGJqNzt1fi4w15ZEQbmd4vAW1wIoSmylUPgbmqi1lfIAdJBTU2nv9xv1+pp1EqePjcrmzIruLy2Zv9+7S52q521PK9EaxTM/KlFQEEDMDz5/cgPcrIA2d3ZXhaBFVWF6MzIv1+SyV1djRKkfAWhG9BtY13Vst+UjePTiM53MCg1DC6xpjarIy4OKuU//N4A0irvkmhAYSVslmaYK/4YAalysHB3V/u8vumzV6Xy7hu0QxNC+eBs5vUfd/eMozPthSgVYlcNiiJ0S+v9BOJx5RbCkHgznEZ7Zprv/jTQd5bI8+6vrs6h69uHkKnCIO/MmGP+CDiQk4uxWJwp3A2PTKOGquLuBBdm8fcV2L2k1UAP+wu4ekpma2udQc68EfChAkTmDBhAgUFBXz00Uc88cQT3HnnnahUKs4///QoOjrw54Tdbsdut6PX60lIkFUTMdYYbvGcy2p7FmpBxWXx47B67Dyw622OWIowKLQ833MWPUJOrvLqqULQX4ZUv0N+CwgGBK3sV7OweKG/zRHLEbLqs+gX2s+/TpIkpPr7oLEyGtZ3kTTjENS9z0g/j4dg3VjqHSv9yw5PHoV1LxIXdAeKFiSPIChAOH1kFUCo1kiV24zUONScNrwPk8YNos5SybK0b/ztzFItq/bvoERdTaZWQNE4gj1Yl8SVg4cSZlCTZc4jCS9x3qZJZnwlHK79ggT9xeg0BkRRxGxzcO28r7CqPajMIG6TCQmn286DHy9m3Uu3tjlhGqbR89X4q5EkCZfPzeKSjdi9TgaGZVJsryHZEEWcJoKvd+/lQFUxoRk1CAJYPHZePvgZyfo4UozRGAyGACXO1w3bKXXIRMvWmiMsKNzIZSlyemBMqInnrzyHN39cz/bsYn9fvNEaKHMjKQUkVdNEmdWmRm9omuCzuOD2g/NgDChK1Jh26UEhMOeWCzBqNbz61EWs35aDSqlgWP80RFFAki7G6S1BJYa3ugeqbesptX6PRhFNp5CbUYh6pvbK5IttWVhdLgRAVd8UJS5Zv58LxvYK2EevlFhW75XjIVTg9oqoFD4kCWYkjkQhiBTbi/m2WDZu90pePjj6AX1C+tArLJZeYU0pdh/eOYNVWUdJjgqli1rPvf9uTMlzutGeLyH0d6Kx67hidGC6pf/2kHw8v/81si1yPL26ciO3pV2HSlDhbiTCB4T1anPbtnDRpUMYd3ZPPG4vkVFtpxHW19f7ySqA6urqDsLqb4RTZphMJhM33ngjN954I1lZWcyePZv58+cTFRXF5MmTuf322xk8ePCZ6W0H/nioK4T3x4CtkYgY/zSMuAe0wYizfoWtH4BSh2HorWQVm/2qHZ8E/1i8n8sGJaJXn36iMy3SyJK7RrL5aA2pkQZ/hbyWxuttGbGbHe7jLv9W6B4XzBc3DeHH3SUs2lnC4XILh8strDhYwa/3jcF4Au+iU0WF2cGyA+VEGjVM7B7DHeMyOFjWwJa8GvomhvDulf0RBIHh6RHEhujIr7b5ty2ttzMwJYzNuU2D/SsGJTKldxyXf7CJbflyUJHUQgmzdH8Fu/Yf5Hv9M0Rf9H+sVw/3k1UA9yq/4RzFVgCmKjaSv/U/kPICDreXd1fnUG52ckHfeD+RcixYmto7DofbyyXvbWR3kVzd5NphKTw9tTuTesZy3UdbAoiixxbu5eWfD/HmZX3ZmfQaPfmEzlFGLIYrYUNTup6lmeG4w+1lQ04VNqcXpSjgaZSIhxnUnNM9hrxqK5UWJ0fKm0pK69UKbC4vJq2SUJ3Sr0A6hkGpYUzIbDIRH5beurJKWwSNw1LLo+8uZFtDCA40rD5Uya/3jUGvVvLNLcP49UA5dTYXT/+w3z+BFmHUBJBVANcPT8Hnk9iaV4PXJ/HrwaZzP/Y7kCSp1W+ipdcZQEywNqBq4ntXDeCJ7/Zic3qotDhxeyW8ksR7q3O4dlhKm7/Fn/c1zdDZ3V425lTz1c1D+XRTAUqFwJVDkk+pkpxBozyu51eIToUgNE0yapTiGXk+daADZwJJSUk89dRTPPHEEyxbtow5c+Zw22238cILLzBt2jTuv/9+4uNbFzfowF8TZrOZgoJGha8gkJKSgsFgwGAwMDpjIP0auqJWqwkLC+PrwpUcsci+SFavgw+O/sB/+t11Rvol6KaCMgU8OaDqj6CUJxRVggoXTep4tdjSssEDki1wlWQ+I308EaJNV6MUg6m3r6ba9j0W52Yszs043NlkRM4+7cfLt+aTY80hRZ9CJ2MnHu0+gyf3fEqFo55Jcf25r+tkAGZcNZFl678DrfxO9rlEjh61YhyQxF6HRLDCjt2rZmrXR9BpJW7c+jJ1bgtaUeLrziGokW0O7D6RpRVfkCKuJpPrSUwZyiub1lEd50EhejGmWvHla/FWyPGI1emirt5MaEgwxXVmPtq4HQG4YfgAYoJkT1RBENAo1FyYOJp8ayU3b30bs9uGQhB5pudlzL/2Yn44spP3Kz7zn7dX8nHZ+v+QakjgiZ7n8YO0HY/LwwVRI/C1KDZs9TbZVVjcVVQ4DhETHagyH9AjmYhgDza7i52WWix2+X7T7g6joq8ClcpFoi6WbZYmkkuKcyHmarh+8DBMOnnySq1SMnZooP2GICjRKlsrt2usu9lRcZPffN/uKaRX1Kt0iY5g0c1XsL2ghKM5lXzxXVMGQHS4qdV+/nHVOby9ZAMVdRZKUkrYb7fg8khIQJVDPk+bJ/D34ZbcuH3uVkrF3qlx9E5tSvm88cnzWTRnNcpBEnUXyHGfGwsLnIt5lFtbn5Orzk9W0aimEgSBZ3vcz5aanURqwhkbdXwPr5YIDT2+Qb1CERgjdohkTgBJkP9Otu0fHP/Tt92zZ0/+85//8PLLL7Nw4UJmz57Nt99+20FY/V2w4Q3Y8GYTWQWw7SOZsAIITYaJz/s/8kl1AZtLrdWnpxUJoXoS+gcSJA+e05Ws4nqKau10jwviplGtZxBnjkhlZ0Etbq9EqF7FJQNal9X9rdAvKZRIo8bviQRQbnaSV2WlR/zJmVSfDCoaHEx5cx3lZvmlN2tkKo9NzmT+zLZ/y9cPT+Wp75v8qgZ3Cuehc7rS4PCwv9TMyIwInjwvky25NX6yikaV0oz+CSzYWYy3keApJ4z17i6MXfgAO4cuDjhOnBBobJ4gysv3fb2bxY1KoG+3F/HDHSPoEhP4gt+SW+Mnq2ispvjIpK4MSg1jbJdIfswKlCvX293c9tmORhXQhagqBN6/KpmIPfVUWZyoFILfpNvh9jLj3Y1kFcv7n5AZTWGNDb1awTNTe/gNxGutLm77bAdZxfXEBGn554U90aoUpEQYuP7jrQHHv2JwEk9P7Y6qmW+a1yfxwNe7+TGrlOQwPe9c2b+131PpHvhwKvPdtRSqI7nE9QQl9REU19lIjzJh1CiZ1kcepKqVCt5elY1Jo+KFC3u2+l4FQWDWqE7MGtWJ73YVBxBWUSatv83NozrxemN1wMRQHWaHC5vLc1xyZ2haOMvvHc2eojqmvrnev77W5qao1uY3+m+OlHBDADGaEm4gwqjhrvFnpgR6SoSBp6d0519LD6FSyKq93yMduAMd+F8giiJnn302Z599NlVVVXzyySfMmTOHcePGdRBWfwP4fD5KSkowm5vIHEmSqKurw2CQB4VGoxGjseld4muhAfZJrRXTpxOCqheoAhUY16dez3tH38PlczEiYgTdgwLV74KgQtJfC7YP5RWqXqAedEb7eTyEG6bhkxxU2xb41zU4tpz24+yr38erR17FK3kREbkj4w76hPThi+GtjfJVoorEQ6M5ZNqIoJCoWRdF1xmJ9Ip/jlXlr+L0WugfcRHdQwbw0dEl1LnlCTWHT+DVinO4Ky6PItsetthDuMRUSqQyH0naSl3VQxwx69Ao3Uzru51Qgw1PH5H1S3tRWhDJhMxEkHzYXG6u+vhrSurle2/1kVx+vPVq1C3IhSUl2zC75Xe7V/IxL2c1Y6N7cWG3/nxTu4Qatzxe8PgEREEiu6GUh/e8i9Mnx6iHXcVckzyV5/Z9iUfyEq42cV6c7PFa48zn2/w7cfoaEE1Kbjj/ElZuVJISHcaTl44n1CiTbIdyy7n3px8oUTfQNz6Oh4dcgReJZGMII375R8AA5R/XTWJS5x4B51BZ1cBTzywgJ6eC/v1SeOKxaeh0gSRrbW0tn+2fR5e4pgnSKltT7JcYGkJiaAjenj5cZjfrd+eSlhDOfVeMbfXdmnQaHpour39m9yL2Fxb5FXaRGjl+SjWk0sXUhUMNsjdWuiGTrPpcBod3b7W/5rhg5hgumDmGRcW/8En+Iv/6Qktrqw8Ak9KIQaHH6pW/Q42oJlwTQrAqiE7G5Da3+V8RGhqK1WrFbDajVquJizuxx9rfGn/XKoHHg0aj4dJLL+XSSy/F5Tq+UXAH/iI4shx+ebz1elP7JeZ7JQRzfp84FjV6Hd0/scsJK5ydbqRGGFjzwFjq7W5C9Ko25csTu8fw012jyK2y0jsx2D9Q/70QFaQhLlhLSaPZebhBTVL46TUbXH2o0k9WAXy1rYjHJme22/6aYSnYXF5WHqygc4yRRyd1Q69W8tYV/QLamVqkKerVCl6c3ovdRXUcbqY8iqEGm8tDUljgDMtC7wgmiNtQCBKSqETR+2IANuY0EVkur49t+TWtCKu2jNjnbchn1qhO3HZWBkv2luFr8ZBurqByeyXKzQ6W3j2SPUX1pEQY/KmYH67L9ZNVACsPVnDo+XNbqX0sTg/b8mpxeX00OCzc/tlONjx8FqIo8PC5Xbn+463U2dx0jwviwXO6BpBVAN9sL/QXDzhSYeGxhVl8edPQgDaOX/+J1i2TgoliJbOUi3nGcw0frM3lpemBA4LLBiVxWRveTW1hau84dhbU8d2uYhLD9Lx0UdO+7p3YhdFdonj554Nszq3hwW+y+GRjAV/fPLRNpVRzZESZiDZpKG9out/eWpnDq5f0adX2Xxf14rFFeymssTGtTzwTu7f/fDlduGZYCtcMa9uLowMd+LMhIiKCe+65h3vuuacjPvuboKKigrq6ulbrj6dImBQ7hF/LtpFnK0Mrqrmu0+Qz3MvW6Bfajzf7vonb50avbDvGEYMeRtKOB18DaIYhCL9vurZe3R0BJRJy7GDQtH6P/a/YUL0BryQTHj58rK9aT5+Q9o/z8BUzePOjSAqKa7jgrHTOGt4VgIuS3whoZ2jhU2YhAU/wnSysuJ5emmoilfLzQhC8mMSPGBj3AlbFekINMkmhVPgYN66EpIpz6J0chdFo5GhNvZ+sAiioraekvoGU8NCAYwWpApXi+4uq2FVUSp+EWC5MOIu3jnyPBPgkAZ8kIgo+P1kFUOaooXtIPJ8MvYdiezXdghIJURtwON0sP/IZTmVD4/XykJR+gIVnvdLqOh2QqthnlCfcV1QeJWivjtdGylUVH+o+iRf3LsaHxAWJ/VuRVQDvf7CSg40G7ps25/D1N1u4+qoRAW1+zN7ARqmWDEkm3gB25puwNhxkSs+u/nYKUeTha0++YMZd3SZSYq/jQH0JgyI6cV26bNCuFJXc3/l+dtTu5J3s71lVUcKqitmcHz+S2zJOXKW7T0gmXxT8iFuS7+cMIYna2lpCQwO/P41CzUPdbmN+3rd4JC+XJk07qYqA/wsEQSAx8fcTEHTg98VJswVbtmxhxYoVJ2w3ePBgxo5tzQx34C+G4m0tVggQ0xOmvdXuJoIg8Nqlfbn9rHQ0SsVJGSWfCYiiQKjh+CWU06OMJ1257HSjwuzgpZ8PUW93c+2wFEZkRPDprCE8+d1eaq0ubhmTftr9qmKDA4OHmCA5kCmus/POqmy8PqmVd9YtY9K4ZUzacffbMyGYu8Zl8NbKbHQqBa9c3BuFKPD6ZX2Z+fFWyusa6CIUkiRU8LznKp5JC+OJyZk8t3g/AEt9A7nY/RSfTlIjJA3Bqgwl7KeH+Ye+gietZ1FJKKJAYKW/RvRKCGFkRgRrm5l9f76lgFmjOtEtNog3LuvHnHVHOVTWgNXlRasS6RxtYk+jKkulEOiVEEK4UcPYrlH+fTy2MItPNwca0hu1ylZkldnhZk9Rnd+DDKDM7KDB6SZYp6ZfUigbHx5HlcVJbLC2zYqU1S0qBdbZmlLvHG4vuwrrCK+101xvdGzG7cuthdxxVrq/Mqfb62tFiB0PgiDw9NTurTzejiEj2hiQAppVXM/uwjoGdwpn4c4iPt9cSIRJzZPndScmuCkw1qkVnN833u9NBbC/pO20jqggLR9cPeCk+9yBDvwd8c0335CdnX3CdjNmzCAt7fjP7A78+WFtYeYsCAImk4nIyMh2twlSGXhrwH0U2SoIVwcRrP594h+VqGqVvtQSgvr3eyc0OLdTZn4PUdCREHI/BnUP0iLeo7T+dQRRS1Lo06f9mKHqQLIgRCUXqimy7uJg/VL0yjAGRFyJWpTjOL1OzYO3TjzhfqfFj2BXXTbbag4Sr4vglvQLCFJFMCX+PvKrng9oq1AYuGvAUMS927HT9KwJM5oYn9QdrVGBxV6LYLcRrNVQ35iiFmnUEx3U+l66KHE48/ZupEFdh9empOGokUX6/fRJiGVG0nAaPHZWl+8j11KNxycRowtGrzJT75bv7WhNKOGaENSikiSDfF/bHW5ufuYL1En59G42DNUoWh+/2tnA/tpAlf2O0qY0wEtSBnN2XE+cXjfRurazGerqAtPvzOYmi4cqh5Uj9ZVsdBymzBPCgoq+9DAWU2M2sXD9CCKNGwIIq1OtSh6i1vPekGvb/EwpKnH5NBTZmyaFfyzZwK3pF+DzScx74Tv2bjxC1wGduPbx81E1U8anGBK4NewydjUcIFQ00UfVFYfD0eZxupjSeK7ngyfd5w78xvi7KqzWrFnD448/TkzM8We4PR5PB2H1d0BRYDoT8f1g1okJTaDN1J8ONGHmvG1+0mTNkUqW3j2KPUV1rMuuQpLgni93EWnS+H2bjoctuTUs3FlEdJCWm0entat+GZERwT3jO/Pp5nwiTRr+fXEfXB4fl72/iYIa+aX833pn3TOhcytjbbVCpMLiwo2KvVInxrhe5cFJ3YkyablhZCql9XZmr8tFFOC8yeezJdLIrXO2Y3GWMVHU8rZqIQOCtvBIzHtcOLATfRLlAG5PUR0bc6rpFhvEqM6RXNgvPoCwijA1zcZO7hXL5F6xONxejpRbiA7WUGVxMntNLtVWJxanl38vO8TtZ2X49292uFuTVRolr7VQBy3cWcSD3+zB7ZVQCEJAFcCf95ZxyUBZ5aRTH5+4ndo7jg/X5VJlcSEI+JU/FqeHGe9u5ECpmS7COcxX7yBSqCfXF817nvNArhSMWiFSb3Nzw9ytbMuvJSlMz7Q+cZzbI5bMuP9tNkynUmDUKP2qNEGAcKOGnQW13PvVbr+avsLs5JtbhgVsO65bNB+sPepXuHWOMTL59bVYnB5uHZPmvz4d6MDpxrx583j//feP2+azzz4jKenPcw9+/PHHrFy5stUseEsMHDiwg7D6G8DpDPTtiYyMJCoqqt32x6AWlXQydqTZtAeXp5zDFVfjk2TSxOraQ8/YFdTbl2N17wbgcMVVdI/5EaXi+L9FAMn2DZJ7B4KqP4J+ervtpsROodxRzuGGw3QyduLChAupdubyfdFD+BoNrmtdBUxOeO6UzkejUPNCrxvx+rwoxKbYsNol8m1NHLGimV66WlySFk3wUwiiyK09buTL/AKK7PvRikbOjr+ZXNtPbMr9CCRI803j8eED+S67EL1ex+1jhqJrrF637EA2BbV1jM5IJT0ynP7e/izYuNdfoyzCKMdCoiAyM20iM9MmUuuyUmqrI1Efxu6ifH41b6Le5sS818izOcu5Z9oowk3ydpuz8jicV4GiOJWopBpiOlURrklheOTNAef98v4FfFe8GREBvU6HzS7HhZVHLeRX1JIcJX93IerjT6qfP60fu3YX4PX60OvVnHO2rELfX1vOFSs+xex2EB1kR6eDbHs02fZoGgpNONxq1I1+TIdyynj0n99RUdNA6qA4xo3uynm9uhJu+N8m9EPVgeOsYJURQRD49q1f+Or1pXI/tx5Fo1dz9cNTA9p2DU0jzN20/fLcIj75+ieMGg1PnzeOXvFnXunegf8dgnQKVQL/SoRVRkYGJpOJ8PBwbrjhBq688soOd/4ONCGuf+Cy2w5r/w11BdBjOnQ+8WxPB8DnkwJSzVweH59vyedgmcVPALi8Pr7bVXxCwupgmZkrZ2/2K3yyKyy8eXm/NttWmB3Y3V4u6BfPDcNTiQrSkldl9ZNVNHpn5Vdb21QznQhWl4d/LjlAfrWN83rFEapX4fI0KY98goJZI5v8xB4/L5Obx6ShEkWC9SpGvbwSi1OWxP/iG8gS32CmujYy+/w4aKx8svloNVfM3uw3P39pek8uHpDI9vxafthdSmKYrilFbt1rsO1DMEajnfYWPRM689ryw7y2/AgAWpWIwy33b0tuDasfGEuoQY1aIaJWigF9n9I7lg/X53GwrAGHy8vyA+UcKGvwe3R5Wxi15VW3MI09DhJC9f7iAUlhenonhuDx+nj6+30cKJVVSYekRM6W3iBZWU+JGE65SyaPHjy7K1FBWv655IDfR6ygxsYbK7J5f3U2n984hH7J4a2O2eBwk1NpJTlMf1wlokoh8ublfXl0QRZ2t5d7JnQmPcrIV9sKA7zpDpW3rlA4KDWMj68bxC/7y0gJN/De6hwqLbKa7JEFWfRJDG2V4tmBDpwOjB07lk6dmp41l156KWPGjOHmm5sGNcdTovwR0bdvX5YvX06PHj244YYbmDZtGmr18VXEHfhrQpIkfxW1Y9BqA1O/XC4XVVVVSJJEREQEGk1HFdSTgcOT4yerAJyeXKyuPVRZv/Wvc3mLMTs3EKY/fkqlZPsMySyrsST7N4AHQX9Jm23V3oPcElWLENsT9FcjCGoO12f5ySqAEtue//q8at3FrKr4GK/kYXjEpeTZ8vAi8p+qTIyimxRjD+6Llf1M1aKWK1NexuKpQaswYffUsqiq0VNMgBzxO4aFDOCBob3p0qXJlPydNZv5z8oNALy1ahNfzLyU+8ePoLjOzP7SCoZ0SmTm8IH4fD6Ki4ux2WzodDri4+MxGWO4+98L2bKvAEEp4DIK+CQbUEFJtZkP75KtIoyNhuhet5IV8wcTEqVk+KxYnt33E+dE9WfZlhL2mwupiZMVYj4kQoJseHN1iDYRdY2Ckhqzn7A6EYYP68x771xLXl4Vmd3iiIkJodph5eEtizG7ZVVSRYOGngYtPsGOu15DSb4eo0bNE5NkYce/3llGRXUD5mSBLc5ytvxSzrwtO1l40xUEaVvbkZTZGqiwN9AlJAqNov0hfPfgVK5NOZdvi1ZjUup5oNtlAOQfDPSkarlM4/tPoVDgdDopd7j554Ll+BqfKbd98R1r77vppK5PBzpwOnHShNW0adMoLS3l22+/Zfbs2Tz00ENMmzaNG264gXHjxiGKJy9l7MCfG5IksdhwIROFNaglF5IuFGHgDYGNfrwHdn8u/5/1FVy/FBJ/P3PMPwtEUaBnfLBfYQUwd0Oe3zT7GNqqFNcSx7yTjqG571NzOD1eLnl/E7lVciD2y75yvr99OI8uzApoF25Q/9dpnA9/u4cljSbnG3Kq+ddFvTCoFf5KfYNTw1v5iUUYm4LollXonJIKjNEBnmmLs0r9ZBXA97tLuGRgEs+f35Pnz29mMJ67BpY/Jf9fl4/v6+touG6Vn6wC/GQVgNnhYWteDZ2jTaREGPi/Gb154OvduLw+esYH8/mWQgDWHK484XVQKQTGd4s+iSvWhCiTlim9m2a97/1qN9/vDgwyTKYgFj4glwavt7sRBPxpoy0r+iVQwXLlAyg+FvBNeonF6nOwOD1M6hFLrc3FJe9vpNzsJFinYv4Ng+mZEExWUT2VFgeDUsMDFHZjukSx4ZFxAfsfnBoW8N2Oyojkzs93sj67isy4IP5zaV/CDGpGdY5kVOdInB4vzy8+4N/eJ0FJvb2DsPq7weeF/A1gKZd/28nDQDz9hveJiYkBPhharZaEhARGjJC9R/bv38+ECRN4++23efXVV8nNzeWVV17B5XLxxBNP8Ouvv/q3LS4u5pJLLuGbb77xq8/tdjtvvvkmK1euRK1WM2rUKO644w5UqtObxt0czz33HHfeeSdz587lySef5JZbbuHKK6/khhtuoGfP1sUVOvDXhc3rYLFnByXWKgZo0hkakhloru7zkZubi9stvxcaGhrIyMhoVYGrA62hU3VBFHT4pKbUr+L6/0OtjMHpaVJeqxWxJ9yX5NrcYnlTm4SV5D6CVHMl4JSzdtxHqNY9wJdFPxOrkienAKJ13f6rc3J5nXye/xgWjxwfFtv2Mzjido7lS1h8KjJMgX6mgiBiUskVjKs8LUr1CRI+POh0gTHqj1kH/f/b3G5WHDrKzSMHMfeaiwLalZeXs+9wEVk5lUSF6pk4QsXBYgtb9snX1yNIAd6jB4oqOFxfSZhGx4AeSVx8Tj9+OrwaXZCIcbCen0rlynubKg9Rmx2GoJAIbgynzgnJ5+aYfbhTlby4dCSHpV50Tzq1+KxTahSdUmX1otXtYsbyeeRbmgoNSZJIN10fXhg0CYDqs2wYNWo0jX5yFqsTSQBnSFP8W1xn5vsNW5iY2Z3t646iN2gYeXYPlhUf5u6N3+HyeekaEsUXZ12JQaXmgPkAoiDS1dQ1II6+ImUiV6QEigUGju/Biq+b7r0+58bzdd7tmN2lpJtGMyr6DgRBIDxcnszMPpLrJ6sAKi02nB6Pv/8d+APj75oSSGNgd8UVV3DFFVeQnZ3NnDlzuOaaa1CpVLz66qtceOGJDd068CfCnq/g1+dAoYQpb0CqHNDP3ZDH05tDSBReIl0oYeSQcVwf1TVw2/wNTf9LPijc/IclrBxu2Txcq1Iwpktkm0bsvyXuGZ/BdR83eYQ5PRJ3jcug2uJib0k9w9MimDky9YT76R4XhCjgf7kfq1zXEoU1Nj9ZBZBbZeXb7UVsySmnk1BBpRSCXTTw6azBp+ydtfZIJXd9sYuaFl5MFQ1OPr9xCJ9vKSBIp+K2sent7uPfyw4HEFbdNFVM6hzG0b7zef/7I+jUCm4bm05iaCCZFmFoe9bYWZ1H809slXkIghz4tVW10qBRcOMnctBj1Ci5ZUwaLq8Pn0SAGu5k8PjkTFQKgZlzt6EUBe6d2JnO0SdHzFRZnOhUChbvCSSrdCoFL1zQNCgN1gV+R1cOSebHPaU0ODyAxCTFJtb6ejJB2ME9i46w0CsHaB+sPcqglDC/+X693c2bK48wIDmMfyyRCaX0KCMLbh123PsgOdzA1zcPY9GuYiKNGmwuL68uPwzA2iNVvLDkAK/M6O1vX29zB9ynAtCtg6z6e2H/9/DzQ2Budm8HxcE5L0Hm1ONtedphNptZv34906ZN45FHHuH6668nIyODtWvXsn79+oC2drud9evX+z0+XC4X48ePJygoiJtuuglBEHj55ZdZuXIlP/zwwxntd2RkJPfffz/3338/69atY/bs2QwZMoTu3bszd+5cunX77wa0Hfhj4lgVQJVKRXJyst9Q/V8HP2d9rTzZtN9VSO9OmQETyh6Px09WHVt2uVytCIY/CiRvObi2gjIZQfX7kq8qRTjhhouotHziX+f11ZMW8TZ51Q/h8dURbboOo6ZtJXtzCMruSPzUtKxqbeoNgGsz0CzF07WOn+t7Uuq0Y/VEEqGyEqKOYWLcY6d8Ph/8spmPV6/ivCuaJjOdPhsp+hhu6nQT+8z7SNInMS5qXJvbS5LE47tXYFRGkmGSJ+zixVHEhqax21PPG5t+IC0onJldhxAXbOKQtQqfCkQPxLbhawVwOK+Cf368ya9ir7F46Ne7KT4UvI2DawEkQcLT18V1m/6FTu0mQRfDqFHRxGfmy5fKq0B0h+JDRBIkFHoPriotzmoNiTG1PJSwE6UggcrJK9NXUK9/HIv3Z7LLFqNVxpMRdh8q8cSxiE/yUe+u51BtHWXOCkJNLnySQINVS7Ixgjt7jPS3bZnqd/kFg3jl3V8Q3eBrFMUKgEESuP/q2VQUy0r6TasOsnxUDS6fPBF4sK6CBblZ1Ikb2FW3C4Ch4UO5sdONx+3rmAsHotaq2Lcpmy79Uqjp9wXlNtkzNqtuEdG6rnQNbiK56uvs4AUa+ewIta6DrPqz4O9MWDVHeno6t99+OzqdjhdeeIHNmzd3EFZ/JZQfgAWzmpY/mQb3HwF9mF/9UyhFUyhFo6xQcX3L7RMGQF1+44IAcSd+gf/WcLi9PPxtFkuySv1KpAv7xfPvi09/lZdTwfD0SAamhLI1T56luWJwEvGheuZcO/CU9tM3KZQ3L+/HN9tlD6uHzunSZruYYB2hehW1jYbeOpWCSJWD79VPkCnmY5Z03C0+TNeYSad0/M+3FPDIgqxW65WiwLC0cHolhNArIeSE+1m6N9AYc/ywIdiGXcqFr672m5BvPlrDc9O6IzR77hbWtp16d1A/EMmXylzPObhQMVHcyvjN7/Ds2EE8ubIaSYIZ/RMINaips7n4aluRf1uL08Prvx7xkystqww2P/7lkXlQn883rqG4kCMRhQhXzdniJ+B2FNSy5sGxx62sJ0kS9361m4U7i1ErxVbvlbev6Mfw9Ih2t+8eF8wv94xi5f5y/rl4D+97pvK+Fy73LmeRr8lb6millbTIwCqNKoXI26uaDFazKyws21fO9P4J7fb14w15ZBXLxOr0/gk8+d3egDarDlXwyi+HmNE/geRwAxUNzoDrKAHeP8HLswOnCfu/h6+ubh0xmUvl9RfP+81JK4BXXnmF6dPb95VpC/PmzaOiooJVq1b5FVUjR44kOjqaHTt20K/fb/MeHDFiBAaDAUmSmDdvHnl5eR2E1V8IFRUV1NTIBS88Hg85OTn+9KtD5ialj4REtrWYnqFNvmVKpRKVSuUnrRQKxR8yfVTyFCDV3QuevYBPfrsGvXBcr6ffArFBN1Jr+wmPrwpQEG2aiUHdg+6xi09tR4YbEPAgubbLJvL669pup2oRt4mReD0yaWH26jF79fTX9kGrOPlJHkmSuPPLH1h2KAdBraK22khouGzQbVJGEKFJIl7flSHhQ467nzqXjZ21+UAG++tjkYB/9buWHKeTOzYu8rercdromhbF8rpcALwqyHW0rmIJsPdoDQ0GH7ZYEN2wZl8BV04ZwMg+nVi76ygaUcHNZw+mwmajVFPPRsVW9Br5Xi52lLKu6pB/X2qFF53KjdWtQYmCYK2N2EHFuF1KrgzugVJY6m+rFF0oVdvYVfGIf53bW0vv6P8c9xqY3WZeOfQKhfZCDAoTUcEq3JI8tNYo4acJs1AdR704dWIvMjvH8sP6LD7avQuvKGEq9nJIUeInqwBWLd6DYnSgr6JTqvOTVQAbqzdyUcJFhKnbtguxeux8lr+c+k4WJg0fSmZwCp8eDSyU9dWmdXQLimFcz3TCjHpqGuyozBI+DQg+gWDjmVMKd+D04m/rYXUMbrebH374gTlz5vDrr78yceJEvvjiC84777wz08MO/Kb4ZnsR/1p6kOm+Xwio/eDzQNURSBrMkE7hLNjZVE1jSKfWPjhMeR2MMTJp1XMGpAz/Tfp/Knh7VQ6LdhUHrFuwo5inp3Y/7VX4TgVqpcj8mYNZn12FTqVkaFob1/ckMalnLJN6Hl+ebtQouXt8Z576fh8AdrcX3Z55ZIoy4Rgk2HkldCFwt3+b9dlVfLerGK1KwbQ+8fRPDsz5tzg9PLFoLy0xIj2c28Zm0C02iOI6OzFB2lbV9VoiNcIQ4IOUEWPiUFlDQMW8/aVm9pWYA4a8RyostIWw2GTGup7Fg4J/Kd9lmnIjrNzIVaZYzr17OS5NuD/lstzsCCCsaKzm0hL9k0O5YnAS/1h8AJe1hseUn3FpwyoQYYRqJ7e67yY+REdqhDFALVbR4KSywUlimB5Jkqi0OAnSqgIIrLVHqljY+Htr7p11DBuPVgdUMWwLsaUrmLHiJmYobLzNVF71zOBr3xjCFC6qvbJPgiDAtcNSOFppJafSSlywlnsndCaruN5PZgKYtIGvDV8j2ySKAu+szuHln+WAccGOYkQRpvWJ54uthf6+V1lcvLkimzdXZPPwOV1IizIGKKwGpoQSG6Qlp9JCXpWVPolypcYO/AXh88rKqjan9xqn0X9+GLpOPiPpgcfDsRTBU8HKlSupq6tjwoQJAV5Coiiyf//+M05Y1dbW8tlnnzFnzhxycnK45JJL2LRpE4MHDz6jx+3AmYdP8vHmkQWsrthFmGjkCsMoIhRy4YzmiqneIen8WiErghWCSI/gQDW2KIqkpKRQUVEBzfxq/miQ6h8ET3NfJgnJNv93J6w0ykR6xP6ExbkDrTIVnbrzf7UfQVCA8VZOpOcX1AORNGPBuVJe4TnASMWF7BJCqJPqMGBglG6Uv73H5+P7vfvZ2rCflMhgLkgaTJQ2cGJw9ZFclh3KgcaqwkvX9KdXcj4Xj+rBqJjpqAUPkrccQXH89DijSkuo2kCty0q1y4haVBKrC+HXwl0B7TZXFJAqBBp1H6quoi3oI/XUZgKNosA8t4PysjJuP7839105FoNOTbBRjs8W5e1ly/4tza8WAkokmn4PXp/IWdG9mBCTwedhbyI1vmv2STmc7e6CXtVIcGnOot5dGtCXBtd+//8+yYvNU49eGYwoNP1elpYtpdAu20JYvQ1E6DSU2UyoFV5QeDhiKSQzOOX411HrpS67nIidTZkIh9W1Aar/oFA9d/WbyC3rv8XidjIkKpnJST3ZtE/wn5NCUKARA2Mln+T19/fZfR+zo1ZWu6+u2MV7Ax8gM/hc1le+C4DTqWLJNjVfST/z0moV714ygzxtLQ193SCBrkDBpP7yxEepbS9uyU68vg8KoYPE6sCZx0kTVvn5+bz++ut88sknhISEcP311zN79mxiY0+cq92BPweKam089O0evD6JxUJn7lcLiMdoV1EJERkAXDwwEUGQzah7J4Zw5ZDk1jvTGOGcF37jMzg1FNW0VuDoVAq0yt8/eNMoFZzVNZo6mwuH23tcBc7pQGl9YNnaoppAXwJVM1Jp9tqjAZ5Dn27K56ubh9I/uWlWx+3xBfhJASSG6Xjnyv7kV9sY/uIKqq0uusUG8fmswYTo25/hfeHCnogi5FbZOLdHDFN7x/HLvjKUouA/RnyIjlGdI9GrFdgavZNGd27bOFmvUuBp1DdPUzRL8WkoJaJyC/RoUopGB2m5cWQq76/N9a+7SviZL6Wx2JslFp7bI4bh6RFUW11cKO7gUuUq/2cTNXv517RenNU1Cq1KQXyIjuI62QMjLdJATLAWp8fLzLnbWHukCpNGyXtX92dYWgRfbSvk4/VNx24L7685yujOke2rrHxeWHAjKrcFBLhLuZBl3v5U69N488oRPLxwLw0OD7eNTWN4eiRL7x5FpcVJuEGDWiny8vRe3PrpDmptLi4ekMiEzKYg9ostBTz1/T4k4PHJ3dh8tCbg0P9ZfoRPbhjMj3eM4Nb528muDLyvXvz5EFEmTYDC6voRqfyyv4zbP9uJxycRYdSw8NZh/7V/Wgf+wMjfEJgG2AoSmIvldqkjj9Pu9MNgMJxEq0A0NDTQq1cvnnnmmVafZWRknKaetcaGDRt48803WbRoEQMGDOCuu+5ixowZ6PUdv5m/Cn4t384PJfL7yoyVr6T13Bp8LkCAP9q9XS4hXh9BhaOOsdH9yDAlttqXRqMJ8HH7Q8Jb3HqdeGJF9m8BlSKSEN1EPL5qJMmDIJzhFClfc3JHIlRxmHMU0/jVsQM1GhQ0mXPf8eUPbFduQxXiYk0+/FS2nXlD7yZI1fQscLg9Abt3utQkSVOZknSOXLmw5knAg6S7EDH4xXa7pRIVvDHgal45sASXz8ON6WOJ0YXg3VvvTyED6KKPYFhUKt8dboobRya1TeKEJ5ugye6KBrXcV6vVSmJioj/1FeDcxK58nptKlXQAUQARgd4MYbN3PQpBotapx+FVcVXqWGpduX5iB6BCqiS//mmigncTERED2omEug4g1CqRkI8ZppUVZjWuEr7If5R6dwXh6kQuT/4najGYf29eT5ZzL+pm2Y2iIKFVehq9xSQey3qfeYMfx6Rq+1lss9moqqoiKCjQYD0tLZYLxvfhyw9WozdouOuZC+gek8ymaXdS73IQrZOr/l2aeClfFX2FiMhVyVdhUMrvLUnysaLsFQ7W/4JOEcK5Cc+QVZfj37/D5+L1n5by9OSLidCm8dD8+eSWRuDp5CY4Vp4gfnz7lxy0eeTUAQFcKT6untCfteVvsrt2AQBxul5MS3oFxZn+DXTg1CEJ8t/Jtv2D46TvsK+//prXXnuNs88+m1GjZDZ/7ty5rdoNHjyYsWPHnt5eduC/Rlm9A7fXd1KDvWqLy1/ZLF+KZZbrHt6L+U5+QUx5HfRNhMSMAYnMGPAHD3hOgCl94vhud4n/nJWiwMwRqaiVv38BAUmSeOCbPXyzvQiNUuTfF/dhcq8zRw73jA/0t8pLvYTCw2tIdOfSIOm4pew8nixvoHO0ia9bKI68Eqw4WBFAWIUa1Fw3PIWP1ucB0C8phKendOfaj7ayr6Teb2p+oNTMR+vzuGdC+7OUYQY1b1/RVIUyu8LC7Z/vDCDEyurt1NhcfHXTUBbtLCbSpOHa4W0HRGEGNV2iTRwqb6BIiqST0CzlMKQ1+fro5Ewu6p/Inm9fJLZsJcMV+xjh3cutnntwSQo6RxuZ0T8Ro1ZJ1xgTh8oT8UoCikayVxnTw/9bWZ9dhValIESnYlCnMJ4/vwcqhciXWwtYe0QOShucHp75fj+PTu7Gg9+cXOWfg2UN7RNWXje4AomiLsE+rrh8KP2SQll27+iAz5QKkdjgJj+TwZ3C2f7EBNxeHyqFSF6VlYNlZuJCdDy2aK//9/P09/u4ZlgKq5uZz+dV27h89iZW3DeG83rHBRjbH4PsrdUEj1fiw/W5/u+3yuLkq22F3Dex7ZTWDvyJYSk/ve3OIPR6PW63G4/H4x80lZcH9istLY0ff/yRYcOG/aaFaF544QVWr17NpZdeSufOnSktLeX1119v1W7GjBmkpaW1uY8O/LbwST5K7NWYlDqC1W37+TRHtcscsGwVnKhUKlQqVQD5pFaouCrlnDPS598Uuqlg/aBpWTCCvpX5xO8Cj7eWQxVXYHPvR62Io3PUPHSq9n04/2coe4C7yV5BMPTkvdxfaPDJE1/5RTV8FPco9XYnK7OzCR/SpNSpdNZz2FzCgPCm/o3p3Ine8THsLi5DAC4f0JsR0Qlc+uAcPr7zFdRKedIP+wIk3XQEdft2FJkh8Xw4tMk+ZOn89ay65yciz43G2kWNulai6OtcJsydyNvnTGFraTF9o2OZ0rlrm/vrFRWDTqnE7pHjgh7BsnpfoVC0UgJqFEo+HzOLbVU57MrfQ6oyglhlGHVmJUutcsbA2bF96WyKo9Ipq4+cPtkPLFFMQUKDTz0ZQSdPwn2138n6wun0i81mROJAukbcCsDaivnUu2VFYrWrkI3VX7HjaCbv7diK1qiibxclGqUHj1ekoDoUk6nJc8zisVPprGuXsPI0nudZYzpRUmLm0OEqOmfEcust4wkNNTDlssC0TJ1ShU7ZRFBPjJnI+OjxAIiCyJ7cUqoarETF5XGg/mcAbN4aVpS+QmdTX/aZ5QlQyQtrlhXyUtlynrr1XLSOHKzkYYptes40BFcgOkLw+eR3mRcJm8fmJ6sASux7KLVlkWDo2+b5deB3xN/Vwyo4OJjExET279/P/v37223n8/n+NoSVw+1lY041QTplwGD9j4LXfz3Cv5fJ8s+rhybz7LR2TB0b0S02iN6JIewulHPLha6TUF7z1G/S198DY7tE8fXNQ3li0V72lZjx+CTeWpXNmK5RrVLcfmusz67mm+0yMeT0+Hh4wZ4zSlhN7hVLjbU7yw9UkB5l5IGzuzDk+X8Q4SqiQgrBjJHdhXV0jjYRFaQJSNED6BRhpLLByb1f7eJIuYXxmVE8M7UH0/sl4PR46ZsYyuTX13KgrGm788SN/EM1B90GLxT0pmrww9RGDiI1woBS0TTYszo97CsxExusJTFMz5KsklapcV4JVh2q5N4JnekR37a5/DEIgsC7V/bjye/28pbjKZ4T3kfvrYcht0JC/1btnR4vChEmRDcQXCkHQeMVO1jbbwtlA+6nS4zJr4D7dOZgPlgbxYJKiSmun9CGxMDEf0BjmuRNn2zH4pQDlDWHKxEbDf5bno/L62N/iZmTgSDAsOOljW5+J/BtFNub/7vhFlCemm+JSiGyMaeaaz/agtPjQ6sS/WQVjX5elw5MxOHy8vnWQv/6who7lQ1O7jgrA61Kwcs/HwxQVE3uFcM32+XZ9J7xwfRODG7lDdYyDbEt+Hwy0bWvxMzw9Aim9YlDpWhNGny2uYCteTX0SwrhqqHHl+p34AzDeJIVmU623RlEt27dEEWRH374gQsuuACn08nLL78c0GbmzJm8/fbbPP300zzzzDMIgoDL5eKdd97h6quvJjT0zLxXoqOjCQ8PZ8WKFaxYsaLddoMGDfrbEFbVznoONRSSpI8iQX/8lOnfGh6fl8ezPmB77SFUgoIHul7O2Ojjp4uOjOjFVwUraPDIyvCpiSPokvjXJfFF0wP4lF3B/CxI9SBZwPwwknopgnhigu9MoqzhA2xueRzk8pZQVPcyGZHvn7HjCUGPIAka8OQgaMZS7h1Kg29TU38cNdS4zARrTBiUGrxOEYVGjimUgoJYXSjbS0p4YvlyrC4Xtw0ezCfXzmBPcRmheh3BSg2XP/wmCXHFiEJgLJKfl42ojcYXrESj1hCrC4w1HJ4K7O58jOoMVIoQluzaR30PE4Y8JUFHGm0AMJNzuJxz+3Xm3PTjp1AmBYfw5jnjeXvbHoJUKu5I74ZWoyE2NrbNgkgNbgex+mB0xi4IHjlwuDCoH9PTRqDR60g3yXFzpCaaezs/xobqNYhOkT7iQIINIURGykr8DUUFvLB+NWBidUFffs0N57uLZWLIKwVWWvZKbvZWygSWw65ha34SBo0Lh0eFy6VArfai0chxnkEwEq9rezJRkiSqq2XDe5VKwXXX9Cc8PPyUM5dEQY5z5vyyhdd/lFWYwwZV0X1AUxunz8LTPa7nkVUfcbCoFPd+A1Kdir1HZIXzqzOn8vySn9nARv82AjAmLo0VRTLJdVWXvthqPYio8dFEiqoVJ1Yjmx0O3tyymVqHg0t79KB3dGxAnA/g9jnYVv0pFnclXYMnkGhoHY934O+LkyasZs2axaxZs06i5V8HVRYnczfkIUlwzbAUIk1NKUAOt5cZ7270Vwm7dUwaD57T9ozB74Eaq8tPVgHM25jPVUOSyThORTK1UuSLWUNYklWKSikyqUdMu21PO2pyYd9CMEZB78vhN5qd7pcUGuCF5JNgZ0Ht705YORtNNY/B5fEhSdIZrWB41dCUgAF8z6QI1jYKYtQKkd6Jshz/nxf25PbPdnKopIZMZQnTe8nm2rd9usOvEpq/qYAuMUFc1Zgu6vVJHG7mKWXAzv+p3kUjyLnxUsEWLs4+ylHJwaCUMObdMAitSkGN1cX0dzaQW2WVq+uN7MR7q3NoC+lRJxfEPvXdXuZuPFYQIJicxH/w1a1DA5R1G7KruP+b3VgcHhocHiRA5GxeDLFzseMriO5B9IQ7iTYGpiiEGzU8fG5XoCtwBwBHKy18ueQAPknyk1UADrePygYnEUYN0/rG8+nmAg6WNaBSCNw7oTMJoToUohBACrWFW8ek0fV4VfV2fBK4nHn+KZNVx/DJpjycjeSaw+1DpRBwNzqkj+0SSedoEw9P6sayA+VUWeSAJiVcj0Gj4Lkf95NTaaFbbBD7S81IEozrGsU/L+hFpEnDoTIL/ZJCOPe1tVhdXhSCgFeSGNU5kqtPglh6a2U2/9f4zFu4s5j7v97NqM6RvH9Vfz+hOH9TPo83eqst3FmMxydx3fATV9zswBlC8jC5GqC5tJ0pPkH+PHlYG5/9toiNjeXZZ5/l0ksvJTMzk7KyMqZMmRLQpnv37ixYsICbb76Z9957j9jYWPLz87nuuuv+qxTDk8WcOXPO2L7/qDhkLmBVxU4iNSFMjR+BspnHWb61nHt2vk6Dx4ZKUPBUj+sZHJ75u/a3OdZXZbG9VvbOcUte3sledELCKl4fyTsD7mN7zWHidOH0CT1zKaYtYbVasVqt6PV6jMbfjiwSVL2RpGaVeH2V4C0A8ff9Ln2SM2BZarF8uiEIWoSgR/3L8W47ISojdW45porRhhGmDkIpKnj94ik8tXwJ9shyooK03JF5LnG6MM6f+y41dlmR9djy5fSLi2NAslw8ZX/uXu679VPCQhso8SlIEBWIAjQ4B2BxdWdBzVLWHpUJuksSz2Jmmvzcq3VsY2fZTXglG2pFBDuLb6NoeBZJozwcPmQi9AcBhRtUagUxcSdO5/T4zOwvuwaTuJNrugfzj01TWVIbwWMjxgS0e3/JGj7etxNnhAtDQjkalRetoOH2kEnEK8IIDg4mISqhVbycbEgl2RD4vt++/gjb1h2hOD6QqCs0N913QyNmkG/djcNnwaAIZWDYBeQnlrKuMB+8Ip4GDRarEp9KwGdTUOwIJyTEikoUeWHYtajFtj2ePB4PVmug+j0k5L9Pe/14RVN18c25BuJ76gnRyAR3v7BLCFEbuSnpAm77+Ct8jeZYvbvEk9dQw//tWU1DpIMQTyR1kqySvzVjEpMiBvFy2QrcLg/R2Rouf20eid16MPyCLJQqLwPCryBKe2Ift1t+/IGNRfJE5oKsfcTshOsmDWLm5U1ekb+WvkR2w2oAjph/ZUbK20Rqf7vn3F8Nf3vT9b8LXB4fl7y3kZxGz5W5G/PY8PBZmBrNuNdnVwWUtP9g7VHun9gF8QQG0s2xPruKOpub0V0iMWrO/FdxMvejTq1otwJYezA73GzLqyEmSEdmXNCpd6y+CD44C+yN/jeFW2Bq63SGM4V+yaF+TyFRgD6Jv79PwsiMSIZ0CmPT0RoEAe6f2OWMklU0krBFtXZig7UYNErevLwfry0/TJXFxSUDEuncSHYmhOr55qw6xC+vRsSHtFeEHgaK6wJJk5LGawqwp6gugHjR45DJqkYIAugaZ2y25NWwJKuUC/sl8O32InKr5N+g2ysxZ21ugPpGKQpEmjRcPiiJqb3jTniOm45WNyOrZOwqrONweYNfmeXy+Ljqwy2tiCIf8FjDBUx/9GUUhtaEZoPDzcs/H6Kw1sa0PnFc0DeBygYnF727kRqrfG4mrdKfAtc9Loi0SDn4D9KqWHTbcA6UmokK0hLfaPr+yfWD+L9fDrG9oO2KOv+4oAdrD1eR8dhPdIo08P5VA0iJaDEwDoqDmmYkX0hgpRmP18dnWwqobHAytXfccUntYF1g4OVuVs6ve1wQgiAQrFPxxY1DeG/1UVRKkdvHpvPsDwf4dkdRq/0NT4/g1eWHeWfVUUBOLT0GryRxzbBknpl6fGXoMWzJq2m1bs3hSj7ekMfNo2VVyZbcwDZbcms6CKvfE6ICznmpsUqg0OIt1fi8O+fFM2q4/uWXXxIR0TQD3r17d9auXdum/9MjjzzCzJkzKS4uJiMjA4VCwdVXXx0wIz558mTy8/M5dOgQLpeLLl26oNVqW+2rA/898q3l3LvzDVyS/CxdWbGDN/rf4//8p9KNfiWSW/KyoGj1KRFWLq+bzTX70YhqBoZ1PQPvXqnF0smNFqK1YUyKO37ltpYos9eQZy2lkzGOKO2pT8SZzWYKCpoqDyYkJPxPg+pTgiIGxDjwNfrciRGgSDrRVmcc0aZrqbH9iNtbjigYiA267YwfU/LVg68aFEkYVTr+1edWvixYgVJQcHnyBD9hOzwtmdfEs/ls7x4UToGgaoGGELufrALwSRJlFgvp4bJayhSykjCFrH6vlLxkm03Ee5/B60ul0mthraMpq+bLwhWcnzCSCE0IeXUf4JXk35nLW4XJ+BZju8kxQu/EfJZWjiLWHMadV48lKub4yneAcvNsnJ6dAMQY6rmy2wY+yIoOIKzWbD/IP49sAZNEeGQdGpU8ueuQnKyQ9vFCtxvbLCKQY67itaw1uH0+bus+nJ5hsWxbd4Qnbp6LJEm4DSL6qyOwNfpXTcloEiDE6jpzU/oH1LhKCNckoFOYuKlfAkEaDR/8sonagw34FArMGfJby+sVcNRG8MbY83n936vJLV7EsD6pPHfneWjUTWM9URQRRRGfr4ksa+7RBVBba2Xxoh0oFCJTL+yPwdj+uyRIp8Vsk8lTczJ8emgQ8cZarG4N/UNluVWfrgm8eO9Uft10mLjoYK6cOpBzf/mAImvTeFYUTIiCQJ/grtz38kL25chm9GsbPy88EMsXB2J46f4pDO56cirPrSVNnnSSAhx6H3O/3sSIQel0TZfFESW2JgsMH17K7Ps7CKv/BX/XlMDPPvusTU8EURRJSEhg5MiR3HLLLa1+bH9WFNTY/GQVjT4rd32+k1Kzg8IaOwmhgQ8Ng0Z5SmTVPxbv54NGI+eMKCMLbxv+X5NWkiTx72WHWXOkisxYE0+cl0moXsXYrlGsbBwAXjE4yU84tMTBMjMvLDmIw+3ljrPSGZnRtll1W6i1urjg7fXkVdsQBHh2avdTT7M5urqJrALYt+g3Jaxemt6TuGAtRXV2pvaOY0DK75/eqVaKzL9hMFnF9QTpVH5i42Sw5nAl763JQa9W8si5Xel0EtuW1Tu45P2N5FfbiDCq+eSGwXSLDeKpKd3bbL9nyQf0Q37JCpIP6/bPmd7/WXY1ppNqVSKTm1UnbHlvVxLKnpBx9Kr7FYBt3gwOSk0+HMfGB1pVoNLOKwU+VT0+idJ6B2uzq7hj3IlfbFanp9U6pQgRzarQZVc0tKtq8vlA0rYdeD28IIvFe+QX+6pDlSzZU4pPkvxkFY3PkaemZBJmPsh5Rx9C8Vo1DL4JRt6LVqWgb1LggGJYegT9U0K547OdrDhYgV6twNxIeE3MjMbp9vLzPtmD63C5hae+38ebl/dl9eFKQnRqRmREwNQ3YMGNcsXOHtPlv2Z48Ns9LNghBxMfr89jyV2yufXdX+6ioMbG1N5xPD65G4IgcO+ELuwvbWBPUR1BWlVAxUNzMy+q9CgT/5rR27+8r6SetvDq8sPEB7cfgBnUJ/9M7Bpj8iv8msPcrI99EkP4fndJwHIHfmdkToWL58nVApsbsAfFyWRV5tQzevj+/QPTDkwm03ErBEZGRvrTSGinmqAoinTr1u0097R93H///axbt67VerVaTadOnZg+fXorNdifGbvrjvjJKoCDDQX859DXbKk5gN3rIFob+A43KHVt7KVtuHwe7t/9FgfM8sTGxJhBPND1sv+6r2a3lbeOLKDEXs2oyN7MSBpL75B0YrRhlDlqUCByS/r57W6/qmIni4rWEqQycEv6+a1Sso6HvXVHeWTPezh8LvQKDS/3vpUuQadG+JjN5lbLvxVhJQhqCJuHZH0bJA+C8ebfPR0Qf6XAX7C7j6BVJqFSnHzK6c7qr8i1bCBUk8zwqJtRiye+NyXneqS620CygaoXhM4lxRDLQ92uaNXW5nZz44qllNplImlTVQWfx8VzbkYGPx05DAKkhoTRpxnJrlYGTjRXSSoqnTp6qsR2qhjKa0WhxThIa8fulQkrk85B2Dl5ZFdZyPJVMogTx2deKVBtpFO5iDEEft8b9xwGhdCmJMQjedskq5xeD1ev/JwyewOi4CPPuoWrEvvy8ze1NKSZUDa40ZTbGblbS79b+mFAoL/eyOHDh4mLi8NoNKJXBqNXBsZ+l3XvxciIJB7+v+84Wl6NJClpENwIksB9A0awaOFOsgtktdLa7Tl8vXQn4wZksP9AMampkXRKjSIxMZHS0lIkSSI6OjqggILT6ebeW+ZSVCiPj9auOsgbH1yHxbWG/NqnkSQ3CSEPEm6YBsBzV57Ngx8tptZiR1QLuHxKcs3yu8rsaiqsNHJAOiMHyJ5m1Q5rAFkF4JNEfBI898535OYE2n80QUCrPvmJmG4RkeypkGNVwQeqxoQLi61JnRit60auZUPj3sWTUm514O+Dkx4NRERE0KNH65lun89HWVkZjzzyCN9//z3Lli073X38XRATrA1IdwFYcajJTPhgmYWkMD0ldXYMGiWvXdLH/5nT46XO5ibSqGmTxJIkibkbmlQeRyosrM+u4uzu/10K3icb83ljRTYAuwvrsDm9pEYa/GQVwPhubXuAeLw+rvlwC+Vm+aExa942Vt0/lpjjDCKbY3FWKXnVtsbzgndW5Zw6YRXWQuEQ9tv6yujVSh6ZFDi4OFBqxuOV6Jlw4lmhMwWlQmxFYJwIhTU2Zs3b5k/bOlTWwJoHT+wp98Hao+Q3fo9VFhevLjvM+1cPaLf9LrORfs1u7SJvGOO6RvFWkJYys4NIoyaABMqINpERZeRIs7TARZ2epVf6NbBzPtV1CShLRLxeGJ4ezuSeslpqxoBEftlfztojVYQZ1HSNMbEhp7pVf7bk1mBzedC3Q3CsOFjOWytz0ChFIo1qKi1NJNLMkZ2ICdZytNLCzLnbyK22ttJ6HMP9Z3dulXd/DHuLA1/6yw5UtGrTKdIgK3pen96kevr1GUgcDCnD29yvRqnwfxeSJLHxaDU+n+xb9dqvgSbm1aW5XPi23X+dZ41M5bHJmTCz/efysv1NxtENTg+bjlazYEcx2/NrAZizLpdeCcFM6xNPpEnDd7cNx+eTWJtdxax523B5fGiUIkcrrby9KpubRqWhaPHcG5oWzsGy1oFPg8NDnTqQRAzVqai1u8mMDWLWyE7t9nvdkSo+2ZRHmEHN2d1j+LLRN0shgrdxwjLcoOaSgU1E6HXDU/D6JNnDKjn0uPvvwG+IzKnQdbJcDdBSLntWJQ87o8qqvxKSk5Opq2utwnS5XBw9epRp06bx3HPP8dhjj/0u/TvdSDa0jpV+LN3g/7/BUky8NoJiRxUp+hhu7NREelo9dtw+LyHtGJ0fMuf7ySqAX8q2cGv6+adEejXHywc+ZXONXB3tYEM+YZogFpdspMwhD0K1Sg29Q9o27M6xFPPP/fPxNU4OlTtqeG/gAyd97IXFa3D45Hedzevku+J1PBh0+Sn1X61WH3f5TENQJiE0q1TnldxUOo6gUwQTrI7/TfvSHEoxGJOm/RipLRw2/8r6yneh0axakrycFXv/CbeTGl6SySoA9x6wfwuGq9tse6Sm2k9WAWQ3mKl1u7iofyYr7Adw+jx0ijWgayYuiDReyrKiD+hiKKLOrePbir7c0SWOGEUMhgYDZ/v6s7R+OwBXJk8kQiPHxelhd2N27cPhKcak7ka+ywfIBKdPErAJahShbr6sXskNtJ/W/fa+9fxSfJheITGcFWHAoLTi8ir4oaQPT46W49elRYd4aPOP2HQuRKeAz62kvk6HUetApfShFJRck3pum/uvclgpszcAEoMS8ojQW9niKkQ7SYfvk2449TpEl5ceiTFc26M3hw8f9puhFxQU0LVr13aLaCREhzD/5WsAsLhcbC0pIspgoHtkNDctPBzQ9sjRUj7/YC12uwuFQuTpJy9g+LAMTKa2xQQFeVUU1lbhPscFSji0qYjKinKKPbfia7wfcqvvx6QZhFoZS7+0eJY/fyM+n8R/9q3hzX2yn1W4oOfnZYdQ9FcwvncgcRim0dMtJIoDdS3iVQ+UrKsgND6UWptMdqmUCgQfuD1eJo/uzsAe7ZPfu2sWUGTbQaS2MwdKMtlbW45C7SU5th51nQtnaBBdk9Pp3a0po2d87MNsrvq40cNqItG6327S5y+JU0gJ/EsprCZOnMjEiRPb/by8vJz+/fuzbNkyJkyYcLr697vBqFFyz/jOvLz0EN2EfGYoVlMtBTHbOwkn8gtbqxJ56/J+dIo0+NNodhfWcd3HW6mxuuibFMInNwxupS4RBIFgvYrKhiZmef6mfCKMmv/KO+nzLQUByysPVbRKz/pmexG9EoIJb0YiANTb3X6yikZfmoIa20kTVi3NkI+lTJ4SkofBuf+CbXNkD6vzXjv1fZxGPPvDfj5cL6vfpvWJ4z+X/nmqX+RVW/1kFY1KQavTg+EE6r0WwqUTPrt+jriWyIpK+olH2O7rTMrwB5iz/DBlZvnFVlhr540VR/jHBT3927x1RT+u+GAzlRYnqREGbhqTDkE9IHMaZwNbbG7q7C4SQ/V+olerUvDJDYOptbowaZXsKqpjwzsb2+xTg6Ntwqqo1sbN83f4jc1VikAy5Rgp/fQP+zla1TTDFx2kwahVcs2QZPRqJVaXh083F/DjnlKemtKdQalhzfbhI+gE975Jq+Sja+VqO1JDaeDMZUNp6w0slbLXVDNFlyAIDEtrSl+anmli/q9maghCxMdA21o+amgK2uZuyOfRSd2Om9KiUYo0p5Lsbi/lZkdAmwU7ihEFAZfHx+KsUpLD9TxwdheW3j2KD9fl8smmfNZlV7EuuwqPV+LOFmq3xyZ1IzZYy+7CepZklQbcX2FGNZN6xpJdaWFc1yiuGJxEnd1NuEHdbr+zKyxc//FWXI3M1OI9pX6Fl7eZFcVd49NJDm9KkRQEgVmjOjFrVAdR9YeDqIDUkb93L/6UuOOOO477+erVq5k8eTJ33HEHQUH/Rdr+Hwy9Q9LpHZLO7rrsdtt0D05lZtoUMoNSCNPI57y4ZAOvH/4WHz7Ojx/JbRkXttouSBWYUq0QRN7P+Z6rU84hXHNqE1gOr4tdLfq4pGQjWfVNKdpWj53l5ds4P34kGkUgGVRoq/CTVQAFtlOrltmSZDMoTz01NSIiArfbjc1mQ6fTERX1+xnYe3xOFhbcS7njAAIio2PupkfIeb9bf04VVY6jgcvOtv04W+PkR5NxJhN6pQqbR1YWh2o0JEVEMvOn93D65Hfkr6XZLC06xKQkmRAQBQ1RIW/w6P7PsfkERkV2Z3hUJgpBJCIigvtJ5WrHZERBIELTpK4zqFIZkfALbl89KjGEg9t+otj+ERq9k4OOaBo8jfefxttWVwH4Pn8f/5cl+xZl1cCivAtJ0dVQag+m0hGEQ3Lj9nm5b+P32L2NaukQiYzDItG1kVw2cBpKk4+9dYU8uet7EgxhPNXzAiK1Tc85hVcgWNThEMxE6JtiPH2kHX2EHWuZgZTeCcx84Fw8Hg/1NidHq8zEhxiICtLj8/kCCCtJkvB4PCgUioD1RrWasSlNscV5o7uy94istNdrldgqzNjtMoHs9fr4/ocdDB/WvvIsPNKE61oH3gj5+vm6ecBgwVfXREhKuFlRvpAU43iWra3kUFElQ7slc8/o0YyOTeM/P61j5/YSVviOsnL3UT68cwb90ppIIkEQmDvmMt4/uImssjI25xUhCCA0KLFFe5jaJYU6rYTN7ubyyQPonh6D0+Uh2Ng+gb+/bglrK94EINeygS0lnfFJGXRJLyM4yAYxoOzq4JEeM1GpmialNAojo6Jvb3e/HThF/F1TAk+E6OhoLrnkEnbv3v2XIKzcXh+xIVruHajhpn3PofHJD4g+Yg6z3PdBIxlw0/ztiAK8dmlfpvaO4x9LDvhTgHYW1HHPl7vQqRToNQo8Xom0SCOzRqbyxmV9ufuLXZQ3OJAkWHukiu35tSy9exSJYW2XP23Zv5I6O3PW5QZUXqNRmdM9LohtjQoJGpVQa45UMv+GwX7zbIAwg5o+iSH+VK64YC1dY49j4NwCU3rFsepQJYt2FRNh1PDi9J4nsVUbGHyj/Pc7o8ri9JNVAN/tKuHm0Wl0i/1zBPnd44KJMKr9htcDkkNPSFYBzByZyvID5RTU2AgzqLl7/PHl2y9fPpTbPn2cBoebm0an0atTHM4tgcH0l1sL+XlvGS9O78WEzGg6R5tY+9BYys0OYoN1ASbnAMF6FcH6tkmfUIMcyAvtCNQHpYQSZdK0+VlBjS2gCl9z1SSNKYAOtzcgdQzgkoFJ3DtBliSX1NkZ869VfoJk5tytbHlsPLsL61hxqIJ9xfUBnnZt4YYRqSSHG3C4vSxXjOM89w8AmNXRBHVqoYL78V6ZwBWVMPn/oP+1be4zOUTNT5qH2ebrQqpQigUdH3mbCKsQveqE/isGjdJ/vwDU29xcNCCBl38+5F+3+nAlqw9XBmxXb3Pz70v6tKpwuL3Zc+cYlAqRG0el8eOeEhZnBZJzFw9I4NphgSrLCGPb3+Ux7C81+78LGsnKNtuVtCdn70AH/j4YPXo0Xbp04fDhwwwYcGqqkD8ial0NjIroTYwyBKfFwXrHAdw0DYpFRJaXb+OX8q0EKfX8p99dRGlCeePIt34CaFHxWiweOz6fD61SjdvnZXB4JqOj+nBT2jQ+zv0Jp8+FV/KxpHQTB8z5vD/wwZPqn83joNJZz8sHPsXpC3yvBKsMJOujyW9GPs0++iPLy7fzap87MKqaBoLdg1IxKfV+P65BYaemOLgm5RyONBSSbSmmqymZK5Pbn3RuD6IoEh//+ymZmuOoZT3lDlmtJuFjU+XsPxVhlWQYwM6aL5Ea78Fkw6CT2k4wPYhUdztIdlD2AF1rovUYIvUG/jXmbP61cR1alZKXJ56DRqnE6Q18R969cRFv7FvH2yOmk2oKY2JsX4ZEdMHqcRCjDW0VN7TnfyYIImqF/JnDHs7ClcMQNR6Ce1UjquRY6/L09lOss+sD0/jdkok9tTJpLCCwr7SCoTFJTWRVI567eTqDo+SiPktL9jA/T66aWGCr5rmsRbw+8Gq+27qP7NIqluRlY7FIEKbGnSKiUsrX3+cRcFlUiILA7bdNRKtTk1Nq5qFvNtLgcKNSiDx2/lB6NFOjeb1e8vLysNvtKBQKUlJS0OnaJm9G9e+ECgdl1VbS4kPYvKkw4PPg4OOP9SSD5CerAHwGiQqvkiDtKMyONQBUuE0sKN+MT9rGkT0pNJSZWLs/F6NWzbTB3ak8akXwyd+lJEFWXlkAYQUQrjXwSJ9xPPnTcrbVyEorCQlnjIrJ5/eja3pg1UKt+viTs2X2AwHLMUHy+NJkbPJR8+CmwFlEounMVT/vwF8Lp9VwSq/XY29m7Pdnxs2fbOfXgxVMFTegUTex2SMF2RROIQo43I0PPQneXZXN1N5xuL2Bg7fm6TbHUNng5Mkpmax/+CzSH1viX29zedlXYj4hYVXZ4OTS9zcGeGw1x93jM7h4QCJKhcjiPaV+1UuDw8Pji7L44Y6mWWxBEPjkhkF8vD4Ph8fLFYOTT6gUaQ5RFHj1kj68fFGvNkvI/9mgFAVEgQBjb43yz3NeYQY1394yjE83F6BXK7hhxMkZSseF6PjlnlEU1tiIDdGxMaeau7/YhUIUeOK8TIanN6l6JEniiUV72VciS7+/2lbEjP6JzBrZiVWHKv2+Rh6fRLXVxZ2f72T3UxNRK0W0KkWA4uVU0ScxhJEZEX6vouFp4Vw8MJFJPdsueUwjiRcXrKWkXv4d9E8KxaBRsKZxH6sPV/HCkgPMHJnKXV/swuuTiDCquahf00u9zOwIIEjMDg+PLtzDwp0lrdRpNHpwqRUi47pGkRppoFOE0V/MYH12FbfXXcoPYjrhgpkV7gFs0IVRWmfnnVXZ+BoquenIDySLgM8Di++XK2e2VdnPEE70iGuZvL5RldjrUu4wpjNnXS4hOhWvNktVbg8DksP86aAAvRJDGN05kszYID7dXNDmMwxgTyNBNyAllC+3NQViA1PaV4n2ig9Bp1JgdzcFYS8sPki0Scu5PU8+cOmdEBywn16JwRTV2Klu5hcGBJDzbaHO5uLhb7M4XN7AWV2jeHRSt1PyIuxAB/4s+KvEZ/UuC7dvf5UKp0yMpyqjWpBVQoAqyeyx8VPpJq5MOdtfGesYlpdvC1heVr4VtajkosQxdDLE8tCed/2f5VpLsXocJ1Qp7a7L5smsOdi8jlafqUUllySNI0RtZHbOj2ys3usntPKspXySvzTAzypSG8Krfe9keflWgpQGpsW3P/BvC+GaYN4ZcD9unweV+Of3l1UIqhbLv2164v+KBENfpia+RJ5lI6GaFLoHTz6p7QTNSIhcDb4qUCQz5+hKlpbuJE4XxiOZFxGja3rnVput/PvT1dTUy+ODpYaD9Lwgmrt7juKJbT/7fwNeSeJwfSVPb1vK3LGyR1uQSk+Q6sQT5u3hgj7d+WL7HsrMFixZkVw2NoOJaZkMCG875RVgTFwa7x3YiEeSf7OXpfdhWc5RChvqwaHgtfWb6BwayZXp/ZifvQOAAREJ9A1vis+KbIHFVHJqK7j139+wtqgQSQB3SONkZ6WWHVs60yu9AJNeRU/FRLqPj2JwrxT6NqamLdi4jwaH/Jt0e338vLeQC0YPYndtNr+Ub0XnUTJUSkcjqPB6vZSVlZGa2nacbTKZ6JwSTVyEFUmSuPzSYdTUeti+PY+M9GhumnV8u45glZ44XRgljR6/JqWOREMkwarZ1Nh+5OfSH1ld68GHCIJESFI9DWWy4GBfQTnTBnenb6d4iqvlWF0UBHqlth9nDUxK4IudWUiChFcLFj1ct/J7Pgu/mNTQk8/+idf3Zn/9Yv9yt5CBKEURq02DySg/F5WCkmT98Ynwg0UVvPDVCixOF9ePH8h5AztSBE8JHQqrtuHz+Vi6dCn33Xff6drl74Yaq4tfG/2fDksJeCQRpSA/TN/zyrM5LU2Zj5FXd4/vzE2fbMPh9rXrg7M5V/bgUYgCvROa1E06lYLuJ1Flb/a6o+2SVc9O6+4vAf/EeZn4JImP1uf5P88qNjPj3Q2MSI/khpGpGDVKTFrVSRlWHw9/BbIKIESv5vHJmTy/eD8+Ce44K/2kTMt/L6w5XMmLPx1EEODRSd0Ynh5BcriBRyed+oNdq1KQEW2iosHBrZ9u9yuRbvpkO5sfHedXapXWOwLMrXc3q7K34r7R/LinhKe+b6oqY3d7cXi85FRaWJJVSmywjksHJv5XxIBCFPjo2oFsya1Bo1KcVAptsE7Ft7cO4/MthehUCq4emsx/fj3iJ6wAsg5l82zQfjpfMYlcYuiXFEqkSYPXJ1Fnc9EtJtCDSyEKLNhR0u4xZ189gHHt+MbJ11FgqU9ODwzRq3D7fFz2/iYKamTiaCVPsFxzPwbBKZNWjcHcz3vLeOaHfXh9Eo9N7sa0iDL2FVXznPc56jwq4sz9uaRLMGd1iaLMbGf14UoGpIT5PaW+313C/I35hBpUTO0Tz4oDFYTolVw9JJmSegeTesYwurNs0jmmSxRWp7ddwmpoJ9n8d8aARDw+iQ051fSKDz4uSRoVpGF6/3h+2VdORWNKtMvr44WfDvgJK69P4tEFWf7Uw7cu79eq8mFyuIFPZw3m880FhBnU3HZWOipRpKTOxne7StlfWs/QtAguG3R8g+Fnf9jvN60/ui6X5AgDVw1JPu42HejAnw0lJSXs3r2bjIw/f8WlXXVH/GQVQIEnUPnpayPq8vh86BQarkqZyLy8pcfd/566HIZG9CDZEINeofUTTyn6mJNKqXs/5/s2ySqVoODtfveRbJT9tx7rfjU3bn2ZXGuT4nRB0WqqnHX0D+3CubFDEASBZEM0N3T631REfwWyCiDVOIw00yhyGtagErSMibnnJLb6/bC9+jMO1v+CURnJWbH3Y1JFk2joT6Kh/0lsHQhBDAExhFXle/n46HIEQaLEXs0/93/Df/rP8rdbfyCPyvqm8cGiTfu4/4LRXJrWlyFRyby3fwNf5TZVY6t1yST2pqV7OLQ9l+6D0xkwru1iOydCdJCR726+ij3FZSSEBpMafuL4rF9EAp+Nu5KVxdmkBoUxPbUX2w7Np7ihaRJtS24ut/fpz9nxXXBKXoZFp6BWKPBJDnySkzHR3fgwZw12rzxhVbPORkllPuhEkEAdb0UZ5UByi7iKQvnH8NeJNLY9cWpoMWFv0mk4ainhkT3v4pZkYjxXXcJ1QeOgcQL3GF7ZvYrPc3YSpTPy6tBpREsqNmwv5MOvd+D1+rji8oGMuDkVX1UNLp+ZXZ5DjEO+F3ySxKsbNrCpsJCe0dF0VYWxO7eUsxKHURFThMvn4cqUsYQ2eu9FGC7Ep7TgYaX/+E5LkzJ9UIbs3fnEJeOJCTVRXF3POf260LdT+yTRsPRIrj5Hw7aSUvbnmfB4lJRbrby3bSsvTpDVmZVWK7f+/AMHqioYmZTCaxMmoWlRbK1L8HgkfBRadxClzaBX6IWcn+qgzF7LmtpfafBYmRA9igT98St73/n+d5TXyTH3k58upVtCFGmxJ1904u8O4RQ8rE7a6+p3xEm/xQ4cOMD27dtbrT9mur5gwQKqqqqYNm3a6e7jbw6DRoFJo2Sa5yfuUC6kmmAEYwzbGkKZJ7RdaeeSgTI7P7pzJGseGMtdX+5iYxvm0AC9Eppm/edcM4DXlh+h3u7m6qHJJ5UO6GtBlulUCjQqkWuHpfjJqmO4ZUwaC3YUUW9vkgNvzatla14t3+0q5s5xGUzqGdsqPevvjOtHpHLxwES8Polg3X/hyfUbodbq4qZPtvtVJjfO28bGR8edkkKuLezIrw1Im7M4PdTaXH7CKkinQq9WYHPJx1UpBH8KV7hRw2WDkvluVwk7CmQi9sJ+8VSYnUx/Z4N/mwOlZm4c1QmfJB1XceX1SQiNSr5jUCpEhjVTfJ0MYoN1/vQ+Gk3A31/T5CdxuMbDPcvM/NMwjc43/QqmGLIrLFw9ZzMl9Q56xgcz55qBLD9Qzs7CWn7Y3YbnVCMEATKPQzwP6RTO9cNT+XhDLkpRYEByKDvyav1kFUAp4RRIUXQTCmHsY6DSUm93c9cXO/0eZfd9uYtO+hd42jqd7aQBcPBgJSsONg3gtuXXYdQquXVMOnuL67nr853+4dzSfU1E1NgukXx03SCe/3E/jy78iXCDhjcu78vkXrEcLs/gxz0lJIXpmdonjk05NSSF67mxmQ9Ut9ggciosiKKAT5Jor7bQvV/tYklWWav1imbquG+3F/kVW/tKzDy6MIvPZrUu5d4vKZR+LYoSpEWZuHeiCa9Prs7o9UmtDOCbI7/ZNQcoqG57IqAtHCprYEdBLT3jg+kR//sVZ+hAB1atWkVRUVGr9S6Xi/z8fD766CMmT55MTMx/V9jlj4SWPlKhopHOugS22A6jEMRWKXgAU+LkghZXpZzDmKh+3L791TZJJcBfRS9cE8zLvW9hQdFqtAo1V6Wcc1L980mBKnutqMak0nNX5xl+suoYbsu4kAd2vY3UjGRbU7mbNZW72VS9n6nxwxkQ1vWkjvt3gCgoODf+aeyeOlSiDqV4/NTx3xN5lk1srJwNQK2rgGUlL3Jh8qv/837XV+1Bq3QjCLKxebEtMKUuOiTQ0iMqpGnCNcUUxs2Zw1lWfIRalx0BuDqjP8u/3MT/3f6xv93Ds2cSNyaZMI2ecG378Znb5+X/2TvrKDnKrI3/ql2nx90lk0zc3YkRkqABggZZXBdnkUV3WXxxlwAJFgIEAkmIu3smk3F3abeq74+adE9nJiHLst+yMM85c85Ud1X121XV9d567nOfqz6uMYZFr2Ns9r/WOGlwdDKDo4OKqVEpqeyvqwOVCBYvi5v3IhxwcEFSb7KyslAoFDQ5llLUeDuS5CbaeD4fjvoz6+rz2fDdUY5srcObIOHTgyLagype/q0LWpGEPPGEZBXApRMHs72ggm0llRgjtEQmmNjTXBggqwAKfe3d7gQh4Om2quoorx6SGz+0eJzcsuFz7o4dwFuLtuP3S0gGP+8L36PNd6NUyL/3/a1FJOqj6RWWxns7d/LK3g1g9LOztARVhQpdnRK2we1njuOs0X24ftnXbKuspF9cPK+dPpvzUs7D4XdQ6iglz5yH0CuPgrBGRvZM47QBcnJCp1ExbZybWmcxSYYwaI8Vj4fL7+LJw0/S6G8kIg76m3Ts2J0NCCHx2eMb1rC9Wu4qvaywgDdjtnPjkM7xWU/LVHpagiXIEXo9EXo9vSIvweP34vC7O23TEW6vL0BW0f4sUNXUdsqE1Y6mfOrczQyN7Bniu9aN/12cMmG1dOlS7ryz6+4k0dHRjBs3jk8++QSd7l83dfytQatS8sEsE/2/fQ/FsUDCD6c/tJHMOhvTn18Xsv6orCiuGhu8CcSG6TAf5xuUHmUgK8ZIdqyZ2zo8OEeZtDx6ZufuiyfDxSPS+H5/DRXNTix6NR9cMeyEpS96tRKNUim3fDgORQ12bl20my92VvD+/GHdpTAdcLxRPu2ePauP1BFt0oaUyP23UG9zh5RW2T1+Gm2ef5uwWnlcd7tIg4ZES7BG36RV8fJFg/jr1wfw+iXuntEzxKRfo1Lw8dUjWHW4Dp1GyYQeMXywqTRAVgF8ubOCDzfLnZguH5XObaf1oN7mJi3KgChJrD3SwHd7q1iyuyqgHrtybCZU7oDSTZDQ/98yaJ6YG8sdU3vw9I9yFxc7ehaLY8lw1nBz0SqIzuapZYcDZYT7Klv5dHs5d0zLZflB/UkJK0mSS80S2o+ZJEmIEiHEyf0ze7GuoI6COjsrDtWxr7KVWLM2oDoK06lIvvxDMJkhWpbTtzm9IYb6Pglm2e9Di6fTGDoiv93j7lB12wlVv1uLm1idX8db62X/tsoWJ7cu3M3auyZy25QeIfesswaG+h8crmlj7uubAl5WR+usPHl2vy4/p2Pn0mPQq5U8OCsvsFxvCw1kGmxujtZZeWdDCXq1kusnZAWaRxTX27G5vfTtkAQob3Jw8dtbKG10kBVj5KOrRpywicQZ/RICnltqpcD0Pqf2QL+5qJFL396Kxy+iVAi8fvFgTsvrWlHXjW78p/H000+zdOnSTq8LgkBKSgrnnXcef/3rX/8rY/u10ceSyUXxk/m2bhNGQceF5rHkRWby19Q/8Wbh13xavipk/euzzyLZGBNYTjF0Ng3PC0snTG1keFQeE2KDTVZyw1K5N++Sf2l8l6RP58mDH+ISPWQaE3lmwI0hvlQdoVeemHDZ1LifTY37mZ9xOvPS/vd9YX9N6FWd493ilmb21NbQKzqG3Kj/fnzW6glVYLd5T6zI/ldwoK2AY/yBQpDINseEvD88N5XrTx/JZxv2EmU28tjF00LeTzNHsHTGVWytKyPdHEnfyAQefSRY+iqq4C+1P1H9gwe1QsnTw+cwKCoZr+gn1RRBs8fK7uajvFuwiYNtFRiUev459HL6R6bQ1taGx+PBbDaj1f5yMvHO0WM4WtvIKudhUEu0iR7eqzlIT30EqampaLVaShrvQZLkWKHBvohc4xwuyxxLubWJI9RhrJXjTSlaREBEp/Ti8GtxSqHxhV/0o+xAupn0Wh66ZCpzXvuQFq+bD7buYrQ9BkW0IlBqnGlOJDMzE41Gg6pdXVTvDJIrJp0Lv6GAJ+0FKCbp8S+PgBw3mEUUHaQsEhIl9mp6haWxuaYUwn3IuT4JX7IX6uRx7TxaQZXWxoZyucHW9upK/r5hLU+dNp1rs64NfpkueML9zd+wulYmSvc0f8HUxL/QI2xSp/WqnFU0eoIiC5PRhVbjJVYXw3VDg15rDc7QpF6Dw0G9YxV19hUY1RmkWi5HIajwiyKHGuoI0+hIDQ/+Xrc0HuSxA+/jEj2Mie7HX3pfhlLoLJjQqlVM7JvFqn1yY4KECDP9T1LO2BEfly7n3WLZbidcbeLlwbef0IOtG/87OGXC6rbbbuPGGzu79ysUiv/3Nrf/HxgY4Q4t6HM2g89FTqwZo0aJvf3hWxDg4dm9O2Xxb56cw9aSJlocXhItOj68cvgpqad+Dvct3scnW8swapQ8NqcPs/onntCoGmDtkYZOD4DHY11BA5Utzl9lfL9XtDg8nPnyBkravX6un5DFXdP/O5nPBpube77YR1GDLcRgvX+yhZSIX9Z6uyO06tDJY2xOdCcyc2JuLBPvPHG3IJ1aGeJJlHVcWaW9A3n13sYSFm4rw+UV6Z1oRqtSBtRZIP8MH116iDlhBUQvmSeXyCHA2W9Cv/N+8fc8vlkBQJUUBe1+C67jzMRL2jsIDkjpPPF19FPSKAVm/XMD5wxKZlyPaO7+Yh8ur5+bJuVwS7uZfZ3VRUFdcOKvbXNz1sAkFu+SM1dWl48d7iQmpAePcXKEnvE9YjqZn7vRICAi0bVKcmSW3M0wO/bEpa39U8IDzSKOoazJwZXvbeO1SwaftOR3U2FjiPH66vz6E66rVipweoPrzh2czF9m5bHxaCNj/v4TkgTXjMskwqCm2SErJeItOua8vAG7Wz6+Gwsb+f6Wsdy2aHfgeCVH6Fl9xwRUSgUvrCwIeHIV1tsD3SqL6m3ct3gfFc1OZvZN4N7TezF/dAYpEQbya62MzYkOUb+eDJ/vqAh4mvlFiU+3l3cTVt34r2Hx4sX4/Z07calUqsAD1e8J08OHMMQXfDrzeuV7xbiYASGEVYTaxFnJ4zptf03WHF448hkiIoMievB43z+hOk4p8q+izWvn/r1vcthaSpI+hhuzz6ZfRDaak5TjfV+9OURddaJ1ugmrk2NndRUXLfkMl8+HWqHgjZlnMiHt1Pw7f23Y3Lsoa34YRDsxKh/1Pvn8Z4dN+FX2r1OEPm9NjOucHLpm+giumd5Z9XIMcXozs9KCZX8p2cFEjW2ggdpwORbwin7u37YUq0f+fZ2VkUupbzctXhuSBCadAlHyctuOd/mk3zXU18tzf11dHVlZWb+YtFIqFBworoWk0N9Gg8+NSqVCkkTE44inamsDYToY1juVlcv24U5VoLN66VVcw+y569Ep3eTb4nj7wGn0ef1FHhg7kRZNEV9WrMWo0nFPr4sZFiVbaewqr8LlDSb5dx1pYWR6EkdssvK71F6DU+nFoAo+M01KyiZ+v5kaZxvRFmuAVFTmOfEfMuJ3yy/4O1jM6BQaepnk+1hyVBgh7ZrVwe/eJy2eI87QZjbfrt1P39YILjln+EmPZal9a+iybWuXhFWEJhJREgKEmk9U8PKcMxgd15M3lm1h8ab9xIWbmDqhJ5sqyhElibgIF9mJm9lduyDwvOz2N5AefgfTP3qXYlcLiHBuXB5PnyX7tb145HNconx9rW/Yy4b6vYyLHcCmdfm8/fZq7GES8y8cx9SRefxj/kyWbDmAzeVh5pCehBlOTRCztCrYSbzFa2Njwz7O7GIe+N3jd+Zhdcp1YEqlEp1O1+nv90hWAZAyHGI6EBJ9zgWNAaVC4I1Lh5ASqSfKqOHhWb3pEde5q16fJAtr7pzI0pvHsPz28b8KGbTmSD0fbylDksDm9vPiTwUnJatoN+EOWTaoGZIWEVKwo1UpCNOr8flFHvnmINOfX8sdn+3B4em689YfEWuO1AfIKoAPNpVS1eJk7uubGPLYCu5fvK9TqeZ/Cvcv3seKQ7UU1dtpsHk4c0ASD83K46OrR6D6FbzEbpiYTWa7Z1ByhJ4/T839t/c5Jieav87uTd8kS8AjqSOOecAdqLKGklUdsO3bt9rJKuS7677PAu+VNTqY+eI6ej2wjFsX7sJ3XPODrhAeKPeUz5sCP7NH9oUs2Qjz+glZIYb7S/dV88WOCmLMWtKjgr9nhUCI0s3jl/CJEou2l3Prot3Y3D58osRzK45wsN2oPsqoJT4sOPkatUoK64MZOqkLNZIgCLx12RBevHAgqZGhxORwSxvvXZBDWodxCQLo1Aru+WI/N3+yi0SLjkhj8H4Ra9ZyWq9YLhqeysvzBjGpZ2zI9wJYebguQAqdCLnH3f9y40/cZTT1uPtgvEWH3y9x88JdVDQ7qWxx8uDXB7C5vIzvEY1eo2TtkYYAWUW7Uqyo3hYyropmJ6+ukTNx7uOIxoZ21dr1H+1kc1ETFc1OXl9bRK8Hvqf3g8vYU9HCDROzT5msAogLCw3EY8N+u6Up3fj9Q61Wdxmf/R7JKoDw8PCQdvIR7YbAuWGpXJ05C4vaSKI+mgf7zO9y+9MTR7BgxAO8MeQunuh3zb9NVgEsKvuJw1ZZNVzprGdF7faTklUAFnVoEiHHlESqIZT4jtTI5eVN7jYe3v8O12z7BwvLVv7b4/09YdGhfbh8cmzgFUU+3r+HTRVlTFrwDqPee51PD+77fxmHKHkpqL8Su2cPHt9RMjXVjIg6lykJ9zM65tpT2MPP48acszG0K/MGR+QyKW7Qv73PeXfMZOb8cWT3S2XwxLyQ92zeIDG0qm4nLV45ThEEULYTLy7JxtNbNwbWE0URqzXIvmzeWsg5815m5jnP88VXoY0OTgSLToeirYPySdBwRq+BKJVKBEFBUvjtgff2NyRx/uIijjY1MnhUFq2zlNTNhOpzFYy7aTc6pfwdck219NGXYvd6eXTLN3xesRoREavPwd8PfRTYX25cdEgZXGaEhQJbsOS6zefgUFtpyHijdSaWTJvPk0NPD9kWYPbZvXnk9LPRbXbj8SjwtgD7VVSviOKcBxaxcO1uJmcmEWexE260IyDR15jAxL5Z3HTGaK6YMpQLe/dDp2y/n4gSxkp4Y8E6qutO3p06Sptx0uVj0CsNVNjCsXs12LwaKmzhhOv1bD5cxls/bqXR6uBgeR3/fHctqUc0XNQ7il49Cql3/xTCdjS7tvL5gX0yWQWodT6+btxLXbN83XjaS7bVgo8otQ2Hr4mGujYefuQL1vZoY3MPO3cWfcrMNXdz8da/kpSr4PLJQ4ixnLqXcJQ21JLj2D30j4ZjHlan+vdbx+8zmvk1oDHClT/CwSWgMUFesHPL6Oxo1t3VmaE+Hha9Gov+1/M2sR3Xut3m/nlCaWRWFNdPyOKdDcVEGjQ8f8FAhmVE8vWeKp5YegilQuDBWXlY9GreWFvIOxvkkqDDNVZMWhUPz/5l5ov/6yhvcvD40kO0Or1cPjq9E/Fn1ql44Kv9bC2Wu3d8tKWMvkkWLvgZk+dfAx07ugFkRBuZP/rXyyYmWOSOgQ02D1EmDSUNdoob7GRE//LufgCXjUrnslFyNunZH/N58aejAITrVbQ4f/5a3u8IZ0ZHfjY8JfDvA0uCXQu/2l3F4LQILmn3c/OLEh9uKqGk0cHUvLiA/9X5Q1L4aEsZ7RpsVEo1A6ZeHNjniMwozhqYxMJtclZNAj7bUc7Zg5Koagl22zoZT9nRCwwIdJ/RqBQsuGoY//ghnyO1Noob7OytCA08crogwtVKBbP7J/L9vmrKmjq0CI5IZ8KAHlR/Xhh4TZKCRODXe6rYXtpEk13+fJNWxaJrRpARHRoELLlhDKc9u5p6W1Bt5fR0Vm50xKjsaP52dl++3FlJYriOB87IO+G614zP4tZFcifGSKOGcwYn0+L0hii0ALyi3L2xK6RHGQjTdZ663ttQzGWj0rlmXCZr8utoa79f/nCwlrfWFVFynD/VMaXXP386yujsaEZknrqZ5w0TszlaZ2NLcRP9k8O5c2q3z0w3uvH/BZ1OR1ZWFna7Ha1Wi9EYnJvmpk5iburPx2cxunBi+PW8TY73xLKfwCOrI85PmcQRazm7m4+QbU7m4d5XEKkN47WjX7Gidjux2gju6Cl3cHs6fyHbmuR28UVFVaQaYhkV3fdXG///EiT3BiT7GyDoEcx3EqU7lgiRQCmhVSu55ruvsXpkouLeVcsZmphMRvh/tizIL1rxiR071nnJNQ/FrBv6q33GoMhcFo16BLvPiUlh4GhdEzEmI9En8WX6OWh0am58ah4Abr+PlnUL2VhXgkahJFbfQHZUPU6/mhr78c8zcuzkdan5sryYi9OyULYTyWq1HKz5fH7++uTXOJ1yTPHS6ysZMiidtFQ5Dmvz2vmifA0e0cvspDEk6OV5+PQeOby8sQnBrkRAoo8+iZTIYLIzIexa7vrJRq29hqKWWPySn+8LCxiVkUxrcoe4SxXqaadWtpcKKkJjDoffhSiJKAQFveJjef68M1i4fQ9lWwppevp7lC9HQaocdygFRZelxdE6E3OzBvLW/uVIYdUIAtitOrTxccR5VSgeqkSvANGope7SQTLrh8g/li0ngQaMeg9GoF9MJG8MuzTEH2xQQiIfTj+ba/6+CLUV1O2PAS53Z8++jhgafQk+0U2t6zCJhn4MiDy3y/V0Sg0zEsayuGIzAH0tafQNT+OrQwdD1hMFCVedm6P1hehNEo2+0OsuTNM7kDC2RNkwhcn3wecKv+LJIRczP+N03ir8kFGRR9EpfZRan8Hiu4PmJAFvmAK1xktMYiseCZo8Hp44+CFfjH4MjfLUrU7uyL2QJw99SJ2rhSnxQxgX+/Pdsrvx20c3YXUy6Cww6NL/9igCmNgzhj5JYeyvlB/Mb5p0ah1/7pres1P52uz+iczuH9qhobjBftLlPxKu/mA7h9tLxraVNPH9LWO5dnwWb68vwuuXqG51hXgyAdS0/XyA+mvgjH4JgbFpVQom9zpxaV6by8sDX+0nv8bKpJ6x/HlKDz7bUUFli5PpfeLpndg1oapSKoi36Ljzsz18tkPOLN0wMYs7p/06D+a3T81l3vA0ihpsXPp2qGR5ZGYku8pbUCoEHG5/IHfzpn8mV/YWiKzbBAkDYPKDgW2OL2drsHlAFEGh4G/fH+LNdTIR++HmUhb9aQRD0iM7KWA9fhGb24dBE7wtZsaETsaxJi23LNzVqUtoV0gK1zM6O4pPt8vHb3hGJIM6dDXMjjXz2Jl9Gfr4ipDteiWYmdIrjouGn5j87Jcczvf7g+blaZEy8TQgOZytJU1dblPVErw+bW4f6wsaEKXQck2LQc09p/fkjs/2IkmQFK7jzAEnbz0McMGw1FMia2f1T6RHnJniBhuD0iKINevwixIjMiPZXNT1uI8h3KBmXE4MSeE6nl9ZwJD0CLaXBGXyjXYvS3ZVcsnIdB44I487Pw92QnrmxyNMyo3lu/2dDd9pL7P9V2DQqHj9kiH/0jbd6EY3fj1otdp/yyfn18bsxDGsqduN1edAp9BwbsrPl4DpVVqe6PenTq9fm30m12afGfJapSO01LrCceLS698zJH8NUvN1gDyfSd7DXD94GQfqa9nQVoik9rOseT8+QQnID/yiJFHvsP/HCSu1MhKzdhRWt6w20qoyMGhOnMA5UtfAY9+vwub2cNWoIUzplUCFdSESIsnm89Eoux6vTqnB4xWZ+/ZC8msb0KqUPH/eGUzskdnl+v8KtEoV742/iDJbM7XuLfxU909oT4BZdC7C1UPZ2VyOTqGnptWHx6OmpSYMk1qN2WTC6/USHh6OxSLHlm63L0BWHdtPc4uDtFTZ3/OePa8F1Eur6nbx1tC7Man1GFUaNFYByapEAGxxnb06VcpMCpo7NOTxwXPvroRgLpNvKvoxP2sDKoVEjSOcLRWy5cPwqJ7ozWUcscoJybkpk1B08FKa0isb5e4annxvCUpTGDxmRXNdGDnjszk7eRxpxhP7XcaTyaYCCYVCxONSk5hjISkqHlO4EVuLHUmlgA4qLFWEG7cY/H51nlr2txaRZownUhNMXA7JSOHMvr35/OgBHAqYkZRNRsrJ/dqUgpoxcdeddJ1juKPXWUyM64fT72ZYVA/UChXjemcSad5EU3vXRmV7GOlsVKHPgEpPJJutmQwJU5OoG8p3e4bj8rYSp9SiCgsmHdc276PUXsfpiSNBWkeR9TAAXslJvelHoi2J1ONBqRQ7HhpcogeX6PmXCKtUYxyvDrnjlNf/XeN/QDl1qugmrP6HYNCo+PzaUWwraSLCoPnVO1NN7R3Pwm3lHOvSOuMUDYh/b5AkiYK6YHmWT5Q4Wmfjlsk5vLE2qGBpdQYzGyatipl9T80Q8N/FjZNyyIwxUdxgZ2Ju7Ek70j3yzUGW7JbNPg/XWNlV1sKmItlY8c11RXx94xh6xJmps7pQCkLAzJp2M+1jZBXAy6sKuWJ0Bq1OL+uPNpAZbWJMzi83N4236PhyVwW+48ifML2aw4/OAODHAzX8+bM9OD1+rp2YR+SUM7vc1yUj0rj7S5lksWjhzB2XwaYCDvT+Mwv3BiXzflFi/dEGhqRHkpcYxpC0CLa3m27P6BNPrDm0Rn7+6AyO1NpYc6SenvFm9le1UXQckWvSKrG1l6z1TQrjkTl9qG1zMSIzinCDhnMHp+Dw+BiVFd3JC6re2pnkfGneoBASqaLZgVqpIK5DCeGVYzIoqLOyrqCBvIQw7p8pey+8evEgnll+hCabh7gwLR9sLkWSoEesiVaXl9o2mZhRCPDAkgMoBLhnRk9GZUWTHWtCp1aSX2ML3ANqrW7Kmhz0NQTvNXVWF59sKUetErhkRBrmnzH531nWzAsrClApBP48NZe8xDC5bFAUwdWKUmfhvfnD+G5fNZ9tL2dTO3E1ICWc0/JiWbyzksRwPU+e3ZdXVxfy6hq5u6NKIRBr0lDXQQ2mVckPKDHm0AdZnVrBP+cNQvx4Jz+0k1bHrrrMaCNjczqXqXajG93oxqkiw5TAW0PvptBWSaoxjjhd5K+6/zExfQP+XFqFmqGRvX7V/f/PwFcaIKsAEKswqt1cPnQA69fKTVRESUJtFvG65fmgZ1QM/WL/fzwGe8S+Q73tU0TJRbTxXJSKEyufrv14CVWtcgL6nq++w2hehUcsAKDG9i3DE79AENQ0eZowqUzolMEY4KvdB8mvlQkBt8/Pcys3MLFHJjubCimy1TI4MosM0y/7zgpBIN0cyaam9YHXBAHMKheT4vrweN9bEASBf2xaxxu7tmNWq3luyulkpncmzIxGLVMm9Wb5TwcAyMqMBqmFgwdttFoOEaFaRx+zhkO2eBo9rZTYq+kTnsm0AT14f/UOmu2ykvz8Uf077fvxCadx2/LvKWlpZkJKBu8u3IxbklCjwpss+5ntrM+mqDmWcK2DqSkzeHlGDpIkMS41HZ/kY09LISaVnjxLZ8fyopJG6J2NoBCQJAntyw08f9vNgfd9fpGquhYiwgyYjcFz88TEqdy2/DvKWls4vV8PzsrthSAI/H35A3z6jyWotCoqcpJYVyCbqI9OzeUAmwOm7j7Rzx27X8Wk0vPnjItJ0MSQExuNKElsj2mkTZIZnU1hDdg9HowdrHn2NlWzvCKfVFME52b0QxBO3kzri837+G5nPomRYdwxaxyDI+UGYqIoIooiceEmFt55ET/tKWDRtzuprZdL/Saap2GKKqHQXkiyaRwTkudx3hsLOVovl9/GReg6tfo6ViJtUYc+u2pUOj58aD6XfPYph1xNeJ061Hr5Nz4hdiBh6n+vuuMPi9+Zh1U3YfU/Bp1a+Yserj7cVMLm4iYGpoRz5ZiMLm9iE3Nj+fiqEWwuaqRvkuUPayIsCALjcqJZ1W4ebdGrGZjadabrkTm9EQSBsdnRpP+bJXP/Ck4/RXKs5DhyZV9lsOzM5RVZV9DAFzsreH1NEYIAd0zN5YaJcgZKdZzRuiDIqrvL3tkaME1/eFYel5+kHNHh8XHnZ3vZUtzEwNRwnp3bP4TgSArvbBI/vkdQMTa1dzx78+I6ddk7HnOHptAj3kxJg51hP5xJousITaKRedsysR43bfZKCEMUJdYeqeeyUelcNDwVvUbFlC6ud7VSwdPn9Q98l7wHfwh9XwG3TM7B7vGjVSm5ZGQaJq0KSZJYsruK8iYHU3rHMSyj64eXY2rJY9CqFCFk1V++2seCzWWdzo2mcgvPqt8nP0XDP1xz+Nv3h7j/9DyiTFqeOCtYJnLRiDTqrW4GpoZT1eLkHz/kU9roCCj0RAme+E7OdOXGmfn0mpGsOFQb2N7nl1hbUE/fZEvgGJz32qZAWeoP+2tYfP3oTqb8VpeXZ348QkmjnS1FTQGPrz0Vray/eyK6hv3w0Xlgq4WM8ejmLeLsQcmcPSiZDUcbsLt9jOsRg06t5MaJQSXp+qPBjJ1PlJicF8+3e6uwuuT1zxwoq8HG94jh3MHJfL6jAr1ayd/O6YdSIfDaxYNxef0IgtwZscnuYUJuLBb9v9dZsxvd6EY3IrVhRGr/Nb8Up9/NgpIfqHO3cFrcYIZHdW3DcFXmLNKNCdS4GhkV3ZcM0/9Pguw3B3VPUMSC2O7xqO6PoLAgEFpCrlWpeHrq6Ti8Xmbm5KJT/f/c4xWCjjjzz1dmeHy+AFkFEKZvC5BVAHZvIa2eAt4o+ZZ8az46hY4bs2+kt0W+PpSK0OSXSqHgm8qt/O3gF9BOar485Fp6WUK7+nZEUXMTt6/4nmqrlXN79ebOkaGdly3q0GcNv6Smp7ln4PnhzpFjuX346E5jOR733TmTieN7YrM6iI6SUCkV1PgOcrDtVRJ0Uvt4fRyw5pCgj6LN7WJ3Uw33XDQJv81HcpSFgRmdld6J5jAWnX0+AKv3FbJMksvXtOVqNBUq8g54uPDxaRRo2kgzh3NuVl8EQcDh8vDJT7vxiyJnju6Dxdi1mXedw4fQHtsIgkDyyKBazu70cNPjn3GosAaDTs3f/jyHoX3SADD4fPx9yEg+OHyYgtpGXtqyhRuHD6fH4Cz+slD23pIkiV1FVSgEgQGZiWyo78m3VRupcNZT5WwEBGw+J3ev/4jm/Cjm9OvF7VPGsLcuGJ+Vt7VypKmRgfHyveBgcy3nr/gAjyjHW4VtjdwzoHN5dJm9lgWlP1LfZmP19234rDLh1eZw8cIVs2lubqaqqgpJkoiJiSEuLo4Lxw/kzOF92LqvBLNRx6C8lJB9VrW2cbQ+qJKvbXZxddxYvqpdjwRcmXUaCXo5Dh4UeQHl9h00uI8Spk5gRMxVhGtMfHfNFVg9btRKgS2NB1Ar1IyIOrFCsRv/O6ivr+fdd9/liy++YODAgbz22munsFUougmrPwA+2lLKA0vk7MbSvdVUNjt56ATeVCOzohiZdepeLr9XvHLRYN7ZUEyLw8PcISnEW+QJ7f6ZeTy29CCSBHOHJHPpyC76yP6GMK13fEBBpFQIZMYYQ7ySTFolj34rK1YkCZ7+MZ/zh6YQbdKSHWvmqjEZvLW+GEGAe6b3ZG1BQ0iHv893VnD56Ax2lTVT2eJkRGYU0R1UWk8tO8zSfdUALD9Yy7PLj/DQrOC1N7t/Igeq2vhsezlalZJrx2cy77hSOEEQUJ48SQTtipwByRb4tpS9YgZzPQ/gIjQQue20HKb1jueSt7ewrkAOcPskhhEbpuPzHRXcelrOCZWLBo2KcIOaFkdQWecV4cnvD/PjbePIjg1Kt5/6IZ9XV8tqvFdWF7LkxtFdNmc4dl0l0EB/RSHaDr5ch2vaWLBZzsAdOzcXD0/D4iiBD88En4tc4FL/Ti4tupcWh5c3Lg0tU+sRZw58bm2bm8m94vD4RP7y1f5OY8mvtfLp9nJyYk0U1QeJzpz27oJVLU4W76oM8VDbU9FKndUd+B7HcNfne0NKFo+hweZm1j/X87rhNTJt7YFX8RrY8R6MkGXro7NDVXsfbi7lw00lRBm1zDIcZFTbAuzoedw3jxl9hvHw7DysLl/IdScIAk+f158HzshDp1YElFe0k/7Ar6aqsrq8PLUsn8oWJ2cOTOpUat2NbnSjGyfCM4cXsqZ+NwBr6nbxeN8/MTSqs3pKEASmxP96Xkj/qxAUFoj8BMn5CYKgB8PlAIxLyGRqcg9+rDiCSlDw0KCpzM787arQNCoV43MyWFMg2xVoVVEohTD8kkxiKQUDu1uLybfmA+ASXXxS/gmPWR4D4KwBvVm6P5+d5VWYtBrunjaO96q+DezfLXpZWbuH3LBENjfk45dERkb3DGkw8MzmNzgvZzEapZ/P8oexvDiBKRnZgfcnxl2J3ddCqeMgGkUc56TcSLIhlAD7ObKK9mt31PBs7HY7xcXFLKs9wkHldwyKD8o64nU+Lsy4GpWk5bSP36PeIccgL42X6G85iNgah2C+C0HRdfI4PVZuJnVsjyq7SEu9nU/v/5GPVtwVWE8UJa574Uv2Fctx6TebDvDRfRehVXd+HI5LCPW4yx2YFvj/29X7OdpYijpMwNEGL320lvefvCRA9nxYUMDnxfK53VReTphWy2UDB4Yck0FZMgnnFX14RC9T4oeyo/kIVc4g8SOJcvC7ZO8h5g3tT5TeQKNTjsEMajXJYTJBfqC6lrfztwTIKoAVlUc6EVZuv4e797xKg0d+DogYpaBlXSwZI8ppiTzAPwtKGesei6qdHqivr8disaDT6dDr1IwfGkwg+kQfH5d9zGHrYdIM6SFdy8N0Wq7Insy1eachShJmdTA5rVdZOD/9dVxiGzqFGaFDKaZZI8dx42ODx+rfQUlFI28v3IAkSVx27khyMk5sofJ7w79ipv6fNF1vbGxk4MCBXHjhhYSHh3P06NFftJ9uwuoPgB0loe1QP9hcyhVjMn6VzoW/V+g1yoCapSOuHJPB7P6J5Ne08fb6Yua+volrx2cyqedvU4129bhMEsP15Ne0YXX5sLp8aJQK3D6RswYmhRATtBMjHbsd/uWMPP40LhOlQi4XXLi1LGT9+DA9H2wq4cF2QjTWrGXJjaNJsMiT0w8HakPW31najMvrp6LZSVK4Hr1GyX2n9+K+039ZYCmKEkfq5AYByREGEATcI27i3JV98BBqlJ8RbeT6idlsLW4MkFUA+6vaoN2wfcPRBsINahweP7P6J/DI7D4h6qHPrx3J1R/sCPF3EyWobnWFEFbft5N0IHcQXJ1f1yVhNa5HDI+NhLN23YURF5JNgD1h0P/8Tl0CJQm5BXrlTvAFSyKGKuSA9mC1/B0abW6+3FmJTq3gvCEpuH0i89/dGui+GGXUMLFnDKsOd/ZAUSoE/nZ2P3TqA5Q2OjijXwJTe8dzqLqNua9twnpco4dIo4YIY+fM9Z7yrjs9AhTU2bhHN45P+S74oqdrv7z1R+t5oJ1cSxEKeV/7EBqlTBiOMNdh7nEVAFpT112+TlU51erw8si3BylttDOjbwJXjjn1JgZ3fraXZQdkcm5Vfh2xZu2/ZODejW5044+Lfa0dGmUAz+Qv5JORD/9sKc8fGYIqBcF8V8hrCkHgldHnUG5vYd+BKr79cB+bDYXccskEUuL/s95VvxQvzj2DRTv20epuw5xYQYNwDknqHagFJRnhN/HUkVUh64tS0CjcoFGzYP5cqluthBt0GDUavreGEiyxOgsP7P2I1XXyHDokMptnB12JUlAgSh7OzXkfk0Yuubt18DJK7WfRYk+ixe4iJdqCXmnmvNSHf/H3c/k9lDnqiddFEKY2YDAYqHQ5+NK7lWiVHlGS7QkA+oaPpX94NvevWh4gqwZH1TAtegm0V/0fLTvMLc9ORuuS+NP8CcyYGlSTp8dF8uRF03jqw5XYmxyEFcqkTnOjDZ/Xj6o9UVXbYg2QVQBF1U0UVTfSK7VzDD/v8rEUF9VycG8F6VmRjByfiNvtRqvVcsC4mqwrZEVcw5YYpAo5AWa3y2Mv7tAlEeBQnRzPlTnK2Nuyl3hdPEMih1DrKua1o0/S6G6jxBFFhrEHKfpYyp11eO0q2kqDik2dWs37s8/myY1r8fpFbhk2khiDkS927ecvXy/Hb/JDByFaVlhny44Gd2uArAJQakWSB1UTFiePe2fLTrQqLaPUowLriGLXXbeXVC6gzv4x8SofNY59zBw9gUP74vGLIvOH9SfC0LmC4hgEQUCvPDVbm8P19fx93To8fj83DB/OqNRTa27ldnu59a+f0dAkW7zsOlDBopevwmT87Xgf/kfxGykJtFgsFBYWotVqufzyy6moqDiFrTqjm7D6A2BQWjhfdmgB7xcl9la0hhBWyw/W8syP+aiUAg+e0ZuMaCNtLi8ZUcZO5T5/dMSYtZz1yj4qmuWJfnd5CytuG09q1G+TAJzZL4Hd5c28u7EE2v2LPr56BFFGDVOeWxuy7lVjMogNC1XLdFyeOySFA1Vt/HCghqwYE4+d2YcL39wceL/O6mbp3mquGpvZ/lmh106MWcukp1dT1eoiPkzHx1cPJzOmi3a1fp+svFGqIX1siEFlYBVR4poPt7PiUB2CAA+ekcf80Rm8q5mHh8Mh62pVCt66bAhqpYK9FScmU5xeP85WOUO1YHMZcWE6RmZGMTA1AqVCIDvWzKo7JnD9Rzv4bp9MUmRGGzuVjKZH6hncvIwooZWl/hGkRQ0+4WderN/MCn8eX/lHkyQ0cMu2BRj6n8977efrGGb0iSfcoIGE/qDUgF+O4naLMrE6NieGNqeXc1/bFCDUfjxYi0IQAmQVQKPdw4QesZQ2OEL8uCIMapxeP3VWNy9cEJrdWrStPISsMutU9Ig1YTFouPL97WiUCpodHoalR3LntFxGZEYF7jlKQS7D3F8VLH9o0KSATw2iFyypMPBiusIHm4KtozOFGjQE1W1mRzl4HKD593939321j6V75SB2e2kzyRF6pvUOevi1Or3c+PFOtpc0MzgtgpfnDcJikMmwjmW2kgT7K1u7CatudKMbp4RkQyxNnuDDbaOnDavPEeLb8kHxMlbX7SJeH8ntuRfg9ntQK1TE6n6bRMx/C4IgILVJ/O2fPwY6lZXXNLPomSv+20PrElqVikuHD+ThAw+zs1me68JU8Tze93FW1u5mT0sdMTolGqUfEDg3ObTDm0IQSAoPEhq35M6ixWOnyFbDyOiejInO44X8bwLvb286SpGthhxzIn6xLUBWAaiVIkZvE1MffBO318+Q7GReue6sLpVHPp8Ph8OBRqNBp+u6nK7B3cqNO16hytmESaXjqQFX0seSzoJ9BxGSJRo9JtY29CBV34TOl8Z1PW4B4EhTY2AfvcIb6Pj4YdEXUaMdh9rt56nnv0dr1pCaFEl2qkwWzRiex9heGdx04atUu+TzP3563wBZBRBu0mPWa7E6ZT9PrVpFbHgXMSigN2i49E9D+WatmeKqVjbsqyQpOR4xTKRcvy+wXvTwei4ZK8dMBoOBlpYWBkZFsaMhmBgdnZZGia2EJw4/gVeS45izXLMobPsUjaKNBD2EaxxsblTxVM9buPwfi/EqBUSDgCRI5KXFsammjDk9erFgznkh43xv804kQGFTItWpiE3Sk2OKRrtV4padn2Pt58IheDg/YzAzU3qToIui2iUfZ4vSTFy0DwfBOMav9dNup4XZbEav75p4qnV8j04px4VRajsOfSF3jZwmH7sTbPOvwuv3M//LL6lrJwL3VFfz0xVXEGsKnrOD9XXc9MO31NptnJ/XlwfGTgSgodkeIKsAWq1OqutbyTH+cVRWvwWoVCpUqn+fbuomrP4AuHhEOq+uLqKyRZ6cNEoF2bEmXl51lH0VraRGGXh3QzFev0yxXvrOFnx+CZ8oMTE3hjcvHYJK+fOy3z8KHB5fgKwC8PhEShrtv0nCqrLFycGqNn7qoKYRJdh4tIGxPTqXRN182sk7TyoUAo+e2YdHz+wTeC3cEKpiiTAElU1zh6Tw3ArZCFWjVKAQBKpaZXVQTZuLl1Yd5dm5x7WcFf3wyflwtL173oCL4MxXAm8frmnjmR+PUG91s7tdySNJ8MTSQxysamPNkc7KIbdP5O31xTxxVl96J4ZmIVUKoZPx+zE886M89rE50bw3f1jAR+vFCwYyJa8Km8vHrP6JmLSht9JXLe+j13wMwK2GHzCkTj/hMd3hSeVP3tsRkX9jVY1l/BMQCCXpph9rghDbE+Ytgu3vUiuGsUYzjyu1ESzbX8PCbWUBw3SAdQUNmLWdb/MxZi3jesSEEFbNDi//+CGff/5UwOWj0vnpcB3R7Z5Yx5/jCbmxNNrc/HScCmxXWQthejVPnN2XlEgDlS1OZvdPJCPayJyXNwS6Oc4bmwd9tkNLmUzA6dozbY4mKN8KEWkQ24swbfBz94kZNGEhsj2w8qeMYn2JnSij92cbULy4soD3NpagVym5e0Yus4/rfHikxtppuSNh9cKKgoAqb/3RBp5bcYSH28uqR2RG8cVOOWOkUggBv7L9la1UtjgZlh5JhDFU7deNbnSjGwC39zifq7b9HZ8kJ0ridZGIksiLRz6nxWMlUmNhSdU6AMqdddy047mAQuKKjJlcmHbaf3X8vzWUVTcHyCqAsqpmfD4/KlXXKtz/JvKLa6loqqdUDCZm2nxtVDgqaPPakRCoc5lQK/yk6ZMYFDHopPuL0Jh4fvBVgWWb14laUOJtv7YUCJhVMpGgUkRh1o7A6t7cvpzG29814W73m9x+tIIfduYze3iofYjX66WoqAivVyZdkpKSiIgIEqc/7Mzny037sSXXUGWSS9tsPhcv5y/FXZvAblsLJrcChVak2mWhzBZJY6uJ0YlHmZmax8jkFLZXy8murfUJeEUVaoVMimwtlC0TvCYFbg/c/6JcAnnN3NFcftYIAExhep778BrWLd+Pyaxj3LS+IePXqpTcMWcwH6w6gF8UuXhCHyLNJ47dl20q4vOVchy441AtUVERTJrSWYE9OE9W/URGRiJJEvPMZuIjIylxODBHOXit7j0MTVZM6mDSbWfzRrRCMJGnV/owKiVSwqPJiYnlSFUDSjf4UhTsttWwe10N7+/bxbCceHY1VtA/MpFHhkzHog+ShspmNdcMGc2CdzaRb3fRNsGJr1n+PexuqiDdFMnTA25gYdlKRElkbuokql2lvHL0FURENAoNU1OnkqhMRBRFDAZDQO3pdrtxu93o9XrUajVahQJnh2bpMYpgbO1WqFhTUEx2TFQIqXo8XH4PTx3+mF1NBcQqo7mr50VkRQYJpVaXK0BWATh9Psrb2kIIqz+vWEZRi1xJ9M6enQxPSmFqZjaxUWaS48OpqJGfE2Kj5WVJklhfWYpPFBmbnI7qFMpa/xfxS0oC29qO89X9DXXj7Sas/iBYfP0o/rbsMK0OL5eMTGPZ/poAkXA8XN7gZL8qv55V+fVdGlL/UWHQqBieEcmWYnkyjjFr6XuKHRtFUaKi2YlFrw4oNH4tLNtfw0Nf78fnl7j39F5kx5qY9+ZmHB4/x+uTeidZ6J8czuC0CHa0e1ydNziZsBN0fKtqccpd2cI6Z9Om94lnT3kLoiT7HZ01MIkjtW18sLEUk07FX2f3xub2MTE3lvc2Fodu3NXNtGZfkKwC2P0RTH4IzHE4PX4ufGMzzR18pI7BL0khXQ2PR1G9nGkZmRXFE2f15bMd5cSH6bhxUjaf76hgwebSAGl7PNYVNLD2k6eYOGU2xPZCpVRw1sATm5nq878K/G/wNvH8m2+xUj2B26bkhJaPVu1mV3EdIkHfox1+uUvLg7PyuHXRbjw+kTHZ0czo08FkN2sSZE0iDrgHmPPyhgAh3RGRRg39ky2BBgIAE3rEcHrfBKbmxZEYrqOk0cHGow2UtHtTubwir7V34jtSa+OGj3ey4Kph7CprYf3RBnolmLnv9J5MO06ddwxHaq3o1Epum9Ij5PWlN49hfUEDKZGGoAIpooMHXGsl6165jvetQwgT1nDXrEHMHzOV7/ZX4/D4aRUsHJzxGWNav8GjNHHhvoHseGcrAHdP78l1E7K6HM+mwkaeXR681928cDd2j58LhwVl5RN7xgY6g6oUQicyt9HuDllusAWXnzi7D+lRMjl3Rr9E+iWH8/GWMu7/ah+SBIkWHV/dMLrL3043utGNPzaSDDE8PeAGFpX9hFahZn7m6Tx64H32digV7IiO5TzvFn/H7KQxGFXd95Zj6J0VT0SYnuY2eT4c3i/tlMkqUXLh8dWgUcajUPy6x3Rj3ZscaPkGgyqSKYn3sWa1jacWrcIRJzFghgaNQU7maBVa4nRxnBYXzZLKdbR67fhFNWenTO5yv35RpNzeQpTWgFkTOmaTWk8/XTY77LJtwJywEcTrI1hXeZgdrTvIDLuYwZbTUAh+oo3n4fEuRsIJGgm8QpfhWWtra4CsAmhoaAgQVvtKa7j7/e+QJNAKbehyg9vtr6ujotQFAjjLIzDF2pBUYHfJD8NFbXI8feOQEdg8HnZUVzE0cTCKyLOpr1vEwrU1fLxJboAj+EFSy1GthMSby9YzZlgCGfHJKJVKwiONzDp/eJfHy+VykRFt5KHzhgGw3lHAZZueJ0Jr4s5eZ5FsCJbRtbS0kF8SauZfWNHCPF08U+Om8mPtj/JxTZwT0vkuKiqKqKgo5qelYfM6OWfDg/gkP0oBTB1C7ChNEpJUjd0nx+BOn4bL0uYSpQvj9RvO4b2V27F6PLxXtyewTYm7gbJi2WqjsK2RCK2Bh04fy02f/kBFcytT83IYEpfAq3Y5Mey3BJ/nJOCotYGBUSnc3COo1kvUR/NA3gOUO8rJNmWToO/c0MFqtfLPnavYba0jwxDO/SNmMDzmIlbXPAdIaBRhnJ5yNaJTR7nVzo2fLqXN5UavVvHGRWcxNK3reHlh2QrW1cvfz+YvY/7yl3l9/A30ipdJqyiDgb5xceyrlb9zotlMj6hQBfsxT69jaHDIy2q1kn8+cj4ffbUNURS5YPYQ9DoNN6/8lq8LDwEwPiWDd6ef06ka5HeBX1ASmJISaqb/0EMP8fDDoWXB5eXlzJo166S7mz17No888si/Nt6fQTdh9QdBbJguRMlyfLlRRygVAv4TKE7+yHB5/TzzYz75tTYm94plXI8YbG4f84alnpKCwuMTufL9bawraECrUvDCBQOY3ufX6fRjdXm5ZeEu3D55crrni71MyYvD0W6QLgECMDgtgjkDkwLqkY+uGs6aI/Xo1UrG5kRT0+ritkW7KWqwMa13PA/P6s0j3x7kvY0lnTrVAdjWvcrK7+2IkuxBVVBn4+/LDvPG2qLAfTLKqOHH28YRZdJy3YRsvtlTHegalxPXhRRba24fbfseFGpoN2z8fn91l2SVUoBEk0C5NXjdDki2sKeiNTCO6b3j2V/ZyuNLD+H2+bl5cg4Tc+VJsXeihck94/jzZ7upbXN32j9AZP5CXEUvortpE4T/TA29JRkagiTJ2noj+6RWrluwkzV3TiTeouNQURlvvfs5Nr8SBWJAYTUkQyZLTu+bwKisKFocXlIjDSctzW1zhh6TGJOWxAg9D8/KIyvGyNinVtPavs6OsmbqrC5izTr+NE4mea5bsCNAWB2Pw9VWBj6ygpRIPctuGUNOnJwtG5MTHSiLBFAgcpVyKZfY7bBvDmLvcyhvdmDRqwk3aEiw6DlvSEqXnwFQvOkLrmydH/Aey/+uhqWPWPjh1nHsLm+hZ7yZnDgzMJwf9lSxo2ZXYNtXVh09IWFVZ3V1eu31NYU02tzsqWhleEYkd0/LJS3KQGmjI0DkvbehmAijhln9Ejl/aArf76/B4xPRKBUhZJdWpeSmyaHKxDfXFQWUblWtLr7ZW/0v+WJ1oxvd+OOgtyWDR/peGVg+1FZ60vU74nf4mPWLIPkrkazPEi7ZePev5/LFKh0mg4a500+uSjoGt6+cw7UX4PFXolYm0DP2Y3TqX+eeXWrbys6mT+TP8dhYXvUkHy0dTnNPkNQKdh9Ip1dWA6PSk5iZOJMIjUwAvT7kTva3FpOkjybbnMyWulIe3L4Mp8/HLX3HMj25J5eu/pjdjVWYVBpeGXMOo+PlMYuiyOcHNrC+rQiQWZIv9+yiya7mkPo7NBo/m1phr6UXf8mTy/Gumz2Cu/d/hWjyo/YrycgK7/RdFMepUTouf/jeqsC85ykyok1yI5i8WFRG8quDZJrfryRbmc0up5xg1CiUTEzMZnHRft47tIMInZ4XZ5xOmlk+DnGpQ7DEbEMjbkRsc2Eos+JJiUBSSHgn2/DE+7h47zvcVj+Buf0nnNT/Ta0OMkbFngYWtG6WY0Q73L9nAe+PvBWAXbXL2dewitRhKnYdMSOJ8vfsnyursy9MvZCpcVNRCIrA+eoKTr87oJ60+zSoPCKZJhMphmQuS59PcctUXtj7PD5RYldpOvstZZyZCpFmA7efOQ6/KPL1O0docskErEIZjHFjdW30Mj5Iib2Jx88ZSf/Yl1ApDThdXuKjzdQ0WFFXK/GkyZ+vV6hJ9WlxOp0olGrqGq3ERJnQadSkG9NJN564idRHh7bydrXshbbDVod6p4bHxswmRptDm7eaJEN/DKoICIdXt6+gzSXH0U6vj/c37zwhYdXoDlX0iEovi3ZuZvygQpy+ZnqHn8EH55zD+7t24fb7uah/f2o99SyvKyTLlET/iGwu7TeAZzZvACDBZGJKZjAWjIkyc+uVQeP5aps1QFYBrCkvJr+pnl5Rv8MywV9AWJWXlxMWFlTEdaWuiouL47333jvp7iIju+6M/u+gm7D6g2JoeiSr8zuXTunVCh6c1ZsHvtqPT5SY1DOWibm/Tjet/3U88d2hgKfO2iP1XDs+i3tm9Dzl7b/fXx0oK3L7RP76zcFfkbDyBcgqAJ8ooTqutZ4EzB+dwcx+wc/UqZUhpU9/+Wo/m4rk2vYPNpUSZdQEyM1jneouGp4qeynlf8+6H79gh3RzyOd8saM85B7ZaPewu7yFyTkR1FvdAbIK4PkVBVwzLiuUjInKgimPwMpHQKGCM54DnXwD/eG4znMGjZJ5w1J5f2MRNVZvIDBTCnDfTLkd7vqjDeQlmJncK46RT/4UUMdc++EOVt85IWAQPyYnmqfP688lb2897qgJXKVcSn9FEfih6fBaIkd07bkUgD54sxYlAR9yhtftE6lscaJWCsx9dx9W70gAEqlnsKKApBHncPP0oIQ93KCRj3V7G+TV+fU4vX4m9YwNdLsD+NO4TO5b3EHRc+NoYs1ygNjq8AbIKtqvlTX59SHk0SNz+uD0+imstzEyM4ofD9TQ4pRl+P72CLS8yckj3x7iwyvlzOWzcwfQs/EZ6mqrSBAaGSAcZbTyIJSDp2wpV/6kY121gEal4Jnz+jPrZ7rn5TsjQozyD3riEEWJlEhDpwYRJp3qpMvPrzjCm2uLsOjV/HVOb8L1alo6HAOX18/T7eWeyw/WolUruWSE3AGo2e5h5ovrAqWr6wsa+Md5/fnu5jHsKW+lX7KlnTg7McKOM3s/VfP3bnSjG93oG57JzubOCvg8czpppni+r96MgMAVmTMxdKurAJCargK/rEqLYjVXnr0ArfbUuypWtb6Mxy+Xonn91VS1/ZPMqGd/lbE5/KGNjxy+JpRhyoBKyOXSsutAEm+Ou46IDt4/UVoL42PlRLNX9HPtui9o88rz0r1bl1JqbWZ3YxUANp+Hv+3+iW+my8RnbW0tG1t+Ii+yGo+opNIajjtczXdVO8jNCcZg+1oP4fK50So1lOkbEE3ye16lnxcOr+btMReFjD0iIgKbzUZbWxtqtZrExOC8nr/0AAyNAKUCyaMkfX8uYVP8bG4oxBIv4W1x4/OoMApRvDX9PFbXFFJqbWJSUg5I8OcNSxHb441rVn/JsllBEvfyaUPRVB3ioPJzpGyBw+4EGmrC8ViUgIBH8vNu3RbO9o0JIaWOh0KhQKFQIIoi9X5rSKxa5pCfiQpat7Gs8TmZDU6DOVf0oXrzQMYN68XsSf06nJ+g0sfqcbOmvJhwrY4xyUHiJ0YXzuS4Qays3QkI5JoG8ni/q1C0d8arbFWz6pD8HCEIIkdtxTS4mojWyTGkUqHgzZln8uDaldg9Xib3SOO94i1IwLmp2zGpZWVak2sT5daPyAi/Gr1OzasPXcDLC5YDEoowcCl9jA1LxugS2brzAM99spPaRivRkUZevn8uqYknJxiOOkK9X/Nt8nNCnD6XOH1uyHsmbWgC39hh2S86KWq8mVbXWgzqPE6LvYcfqrciCRKSBPYaI5FjvuJAi/zcUWLbzPkZr3PTSDlW3tdSyF17Xg2QgHf1nMeNQ0YwJD6JGruNsalpROlPXOJpUKtRKxR4243kFYIQ6EzYDQgLCwshrLqCRqNhwIABJ13nP4FuwuoPiuvGZ6FTK3ls6cEQzxunV+TcwclMyYvD5vKRFmXo7lbTju0lTSHLb68v4rYpOWhPUW4uHcd0/5oqtgSLjsk9Y1nZ7ik0LD2SB2bmsfJQXUBlpVYI5Maf/EG7ujW0rKzOGqo2kiTZAwugvvQQt3hvxE/o9+/K7+za9zczUChgfnwRMDPwul+UECUJxfF54tE3w8gb5PxxhwxepCl0YrkuuYzCjWswiv1pwYwKH5cofsQR3oOBqTNQKxUBT6FGmzuklMvtE6lodpJg0VNQa+WDTaWsORLqyQQC36vvppeyXB6vJPDUdhFv2W4emt37hCWUNOQH/lUIEnmKUvb6s0iw6OiVYOaBr/Zj7SCKqiKGpXHvEnHGoyHftyP+/NkevtwpB9QDUsJZdM2IwLV34bBU+iVbWHukgVizJoTMCtOryI0zk18b9Gm68/O9HK6x8sAZMqkXY9by3vxhSJKEIAjM6BPPtQt2hpCgAG2uoPG6Tq3k5tRSaFrQaazfi8NYVy2fU49P5KZPdrFgcylvXjbkhMes39g5mLetxCrKwc3wZP0JVWUTc2O5cFgqC7eVEaZT849z+wfe217SxPMr5O49do+f+xbvZ9ltY7nmgx3srWwlIUxHUoSemg5Kuj3lLQHCanNRY4CsAvhqdyVPnduP7FhzSCfIk+HJs/py5ftbqWlzMzwjkrMGJp3CVt3oRje6AQ/2vpyXjnzBirodIa/Xupt4YfAtXJg6GbVCRbS2swLmjwhJcgXIKgAFEtUtj5AS981JtwtF6FwnSV13RvslSDcOx6yKxeqT44s+EbPpdeFE5n//FWL7VJ1qsWA5gYE5gMPnCZBVtCeSrN7Q+EzsQL/sat1Fq64EdbuhekpYC+VSBN46A6IohxkqwU+kxsX9+64iW9GXRmdoGf8x76uOEASB1NTUQKzQEdE6Hbb1tThSjChdfrKnJLKkQTYnT42sJSxeHu+4iAzCdXrOTA96oX5TfChAVgEUtQbj7fX1B9lQvwfTyE+JR1aCR4oOVih64XHrcfvkmEKvquOT8idJMmYzKfbCLp9dPB5PoOtdjiYOg0KBX3AjITAqqjd+UeSdFV8S1qFxtTG+kbvmjw8h5zrC5vFw9pKPKGiWSZyr+w3h/hETA+/f2+siTosbzKG2cnLMoUqjvrFx6FUqPJKbXrkVGPQebt71ALf0uIrhUbKR+6CERL49/5LAMTc4Vby1dSvGtNCuzT4xGOPFR4dx8Yw+IeWbx7B0/VFqGq044gUak61M+eYt5vUdwIMjp5zweW9CWi6La4Jx7dikrhXtAH8aO4wd5VXsqagmJyaKWyeODrxXa32TFudyAOyeXUSqPuaJvJt4eNU3lFa66R+ZiUa/Hl/7pSDio95VQJRWVg6uqtsVIKsAVtRuZ0r8UEYkn1i93xEWrY6/j5vOfet+xCeKXJM7hGTzqVm6/K/hl3hY/ZbRTVj9QaFQCFw5JgOdSsH97W3jAYwaJWqlgs1Fjaw70kDvpDAuGZHWTVohdzo7WB2cELx+CYfb34mw+m5fNfcv3ofXL3H3jJ6BB+EZfeP5eGskW4ubUCsF7p/Zq9Nn/FIIgsDrlwzmx4O1+ESJab3j0KqUrL5zAn///jCtTh+XjkwjO7brbijHcO7gZA5UHYR29dKlI9MRJYlPtsqEzXmDk/nHD/nEmLVMiRqGp0NnkWNQK2CG/iCrnJl4BB2iBF5UbJV6kVFbxcSoFlY1yoH2HdNysbl97K1oJT3KGGpcr+hMBN4xtQdH66zsLm/h6civmFO1CDRQJsYw2/MYLZi5Vf0ld7Vcw8bCRsZ38CKKNGpCPLuSI/T0Sgij3upm7uubuiw1BHjReyaXsRylIPKhbypfV0RBRSXrjtSxdewecDTCwIsgvoO5Z8Y4OLgEADdqdohyIGh1+XB7RZYfqg35jBSNlfDLP+mSrNpc1Mg/fypgw9Fg95zd5S3srWhlaHokhfU2PD6RNUfqeWqZHFCkrjzKuYOT0KtVnD8shQ+vGsY1H+xgV3kwS/b2+mKuGZ8ZUGK9urqQ51ccQadWMjgtvBNZpRRgVFYU9VY3EhIv/XQUh/0irggrIa9tvawqc8pBpkTn77GluInL3t7K4htGd3oPIDE6jNP6Z/D1nioMGiU3TOtHaaOdglobfZMtxLV7QL2zvphlB2rIijGy4/7TiDBqQu5Pje3G7sfQ4vAQa9Kx5MYx+PwiKqWCN9YWsq0kmPU+RmoCJIaHdreJt+j+5fufTq3A5vYjSbC5qInX1xZy/YTsU9iyG93oxh8dRpWeu/Mups7dEuJllWqIwyf6WVO3mypXI2Nj+jM08tRV3r9XCIIOtyIejSgrsH2ShE3q7OkIUNb8OHW2D1ArosmKfhGTVu7gmxB2Ha2uNXj9tagVMSRabvzVxqdXhTM3/TVK7VsxqCJINQ6FGPg08gJe37YNvVrN7aNHn9RHx6LRc1pSDisq5WRMD0sM1+WNYkdDOQeaa9Er1UxLi+fZ/EX0CkvDow6dB1UKPyhhZFYcu8s89EkrIUrvwi0J+BA4LO5imDaRRF0YVa42DCoNN/QcR6WjkQpnI73CkglTB+OzrubEO56/mL/d+D4t+TZGz+qNNxJoBaPaQ5gmSK6ta17BxeJ5qBXB5NXQuGTCNTpaPDIpd1qKPF9uacjnnt0fYFY5mJkQtC3QKvzoFV4Uigiq8ROna2VoXCGVLqh0babaUcpk3eUoFAqioqICXcq0Wi1qtRqv14tVtCMo3Sjba6cc/haKyhs4uAtGdAjPIxVZxMcHKxE6Yl/zErbW/UBqlIOS1ly8oor39+/ivuET8IsShWX1mIxaPqvawJZGOT4bHpnDgIh0YnThTIkbykdnnsf9G9/DoJfPmR8/H5UsDhBWXp+fe9/+jjV7CkmJjcCnFFHXq1i7pT9pZ6xApRQRhHCqnMNJ9fs4UlbP52v2olMrmNQzBqNWFVCV0Z549hrBlSziT5Lj3g/KthNlMXBj7zFdfs8pqenc563A4S9AJaRwWdZ1HGorpc1rp394NjqlBqfXyxMb15Df2MDEARl8cNm5aI/rDuf1hyb+fWIjQ+Ky+faC2/CJIiqFgq/Ld1JmlysdlIKGOF3wHnd8Z9RY7b/eKdVYryBipRyffbN2F1Njs+jf88SetP+z+AUlgf8pTJs2jdraWsrKyvB6vQwYMACVSsX27dtPeR/dhNUfHBeNSKOi2cGHm8swaVW8cvEgvttXzY0ft/vDbJf9cW6cdPLucb9XlDc5WHGolvgwHY+d2YeNhY1Ut6svZvSJ7+RdZXf7AkbZAA8t2c+EHjGkRBrQqpR8cvUICutthBvUAaLg14JKqeD0vqElhrFmHc8c34XvJJg/OoPsWBNF9XbG5ESTFWPiybP7cfXYTCpbnFz1/vYAkXE4L47BcTZ21IZm4RIch0nzH8VFXqebYAtm3u61kwMDHsSkU6FWCkx7fi21bW40SgWvXjyIyb1ObPAfYdDw2bWj5IUnrwm8nqqoZ7xiDwbBwxqxPz+Kg7lCFUqaCILA+1cM48NNpbh9fuYNS8WkVbGjtPmEZJUCkVGqg1zgfbDTe3U2L60/PYdFsMOuBXDdBrm7HcBZr0NsHraGci7fkUmBJE+GNrfcYfIc7Xau8L+LHwV/9V3KzDmXIVg6Z+9qWl1c8d62gEou9FioefqHfF5adRTauzAeQ1mTg2eXy4Htkj2VLL5+NAZNZwLwWHeU/Borf192GNqVZ2uOKxfuEWeiuMHOq6sLWbi1jHCDmuIGOXhcrr+FFde/TUxkBKx9GuoOMiPjNN7fEc6uslAZ+Z6KFvxvnIa3tYqa7AtJnfOXgIpqdX4di3fJCjKry8cdn+2h2eHF4xMJ06n49NqRFNfbeeRbmVDdWtyE2yvy7Pmh13ffJAtxYdqAF9nFI9ICn3FM/Xf12Ey0KiV7KloYkRHF3A7lkf1Twnl4Vh5vbygmXK/hb+eEdhk6FfxwoBZrBzXa5zsqgoSVzw2qbgl6N7rRjZPj7/2v4/59b3CorZQUQyz35l3CK0cX802V7NfyQ/UWnhl4I30smf/tof5XYHXvwO7ejUk7EJXln9Q2XICAh3pRJDb80k7rtzrXUmt9EwCPv5Kixtvolyg3D9GpM+ib8BNuXxlaVQpKxcmTe/8q9Kpwelqmhrw2MDGR1+bMOeV9vDz6HL4pPYDT72VWah5mjY7PT7ucYmsj+9oO83rRYgC+r97M/IypGBVG7KLcYa3VLSdi0hRa+vWrpVWQ53ivqKDRawIEVAovHw+/iDrBTZIhnENtZVy08Q28kp9obRivD72eeP2JCYLcAWm8v/EhnE4nhYWFNPjsrLQV4JFCyTOloAyUxB1DvMHM4tMvZXHRfiK0Bi7qIZM1O5oLkZCw+bRYvVrManlet/k0eDxGRjr68cn+IpJHVNCRQztq3U5cw2QS9AasVitZWVkIgoBCoSAjI4OGhgYOtFUhtXZQddmrCUvT0VAcw47FvUnIrcfRbOS6C2/q5N0FUGhdy5raF9rPJUSZrRxoTsJhS8TnF7n1yS/YebAcRaQP5dmyHYiAxK6WQ+xuPdQ+zkquzzkLd7MPc4fw3d2h+dUX6/by066jSEBRQxPGdpuIA0XpPP3BuYw+Tc3XdW6svjX0CjtE049OXO3xR0FVIm/efi6iKFJXV4ff7+equWPZ+tJXtBlsId9nfVUhY5XhHPVUkx2XRv+4oOJue+NHOMXDCAL4KWFBySN8JodrZJmSeG7gTTyxcR0L9skG6tuqKokxGDm3V5+Qz/B5pyOKi1AonICSWFPQXuNYPDo98UG2Ny7A4W8mz3I6EdqgZ+g5yeOpdNSzozmfbFMyf8qa3em8/By+X3sAJLkPt9fn58eNh+nfMxmpXeHXLdD49fHcc8/h8YTeB/7V49xNWHWDu2f04u4ZwXTCX77aF/L+pqLGPyRhVdniZPZL6wNkxjXjMln55/Es21/TyfvJ5fXT4vACUoCsArl8rtXp5djjsFIh0ONn/G/+P9Bs96DXKENKxzYXNbKuoJ6e8WFcNirUfDEzxsT2kuYQ1c3moka23j+Fr3ZX8vn2CvZVtpJq8PKE62Xm+e/v9JkavMzTb0Ex9Fn6xskS3Kd/yA8QCx6/yMuf/4B71gTiI80MSg0GRg02N1e9v509FS0MTo3gzUuHEGGMgQ6GjWP79+CJfWF84p3EvOGpDM+M6jQGk1YVYs5d2minsM6GWil02SFQi5sSbU/CBJE2b2jAkkAj5nZ5Oh4rVGwLElZqPUy4B51fxFq+HtrL8ZLC9aRrrdzvfg6VQr6uXtf9E03vm7o8T8UN9i7JKoD1RxsDZNWx49cV9le2Ud7koF9KOBsKgyqtCbkxRLYTrm2uUMLOL0F6lIHSJge5cWbMOlXg+DQ7vCEEX6vTS0GbiphYLUy6v/24wedDJea/u5W1BcEuO+nKRm4tGU6U0Matu1/lhbpYbv3TnxAEgWZH6GTWYPMEymbbXD4+3lIW8PM6hkM1ViqaHby4sgCX18/U3nE88+ORwDU1rXccD80KbctN+0R5/DXeEZePzuDy0UHD3Vanl/sW7+NIjZUJuTHcO6PXSU3wE8NDyehEix6pZh98fD5CWyX0mAFz3+8mrrrRjW6cECqFkr/3vy7ktd3NBYH/RST2thT+IQmrZsePHG24tr2UT0lOzJtExv1Im2sT6ao0zLpgl7g2hwufX0RSHKfuOM5bSqkwYtD8esr3XwJRlGixO7EYdSg7kCQNts9x+UqYkjgZkzZoJK9RKskNj2Vx1Y8h+ymw1vBwn4fZ2LiVryt2YfM6GGRKZowxgfVCWWA9tUJEJYhopXBy9f2Ji4giof1zF+xdFSgLbHC38enRJZyemkqMPheLJljmvvdIJfc//y3NrXZmT+rHLRePBSBaZeSx+OkUehpptZSyo3UTKkHF/PT5KIXOCbSMsEhuHzAusLyrvApb+ykSUbCyvic9DLUolCJHGuJpXh9NQYQbyaGi1WqEDiKoJpeGW3Zs5KmBw0kH/H5/QGWl0WhITExkTLiaBXUrcYly7DEkMhePZKffuXoOFlloXZnEFdMHE27qOmZvcIV28ow22IjFijKikO92bWPnQbkyQXQLKEVAAYIghRBr6+r3cH3OWUR7srDVt2CKceD3KJiZeHpgnVa7C1EB7iiQVODBS4LRSFOTgwHpQ/i05iDedlP4Q211GIwa1C75+O4tqkYQFKjVSpKSgufsi4cvY/bC96ntWCVR5eRe1wLcJg80wnXuOZybOh4Alz+0mqLMXiobfAGFtkq2N+VzuCE00Xm4oYGNFWUsPLAXk0rD6IgUHvl4Gyb9+eQk1XDBmLOISJ3W6bhqlAZGxf6py2OuVqj4c88LQl4rslXxUsEX2H0u5qZOYnLc4C63PYbYqNDzGRtppqm5kcqqSgRJQWxsLLGxvwMT9t+QwiovL+/f3kc3YdWNTuiXFA4EJ7Q+Sb/P+t6fw6rDdSEP5l/uquTe03tx9qBQ6eiO0iaueG87rU4vQ9IimNYnjh/2yyVfIzIj6fkzvlH/nxBFiZsX7uLbvdUYNEpemjeQST3j2HC0gUve3hLwp6ptc3HV2NAguFdCWEgHyb7JFnRqJecPSSE53IBPFBkrbqPqEy8NhJr2XT00krnJreTkvQfmYFRh0IYGLY0OLzcu3IOIgnMGJQXUYc8tP8Lu9nK27aXNPLs8n0fPeRO+uBrs9TD0Ks49bT5nnO3H7RNlk2uPHVrK5I5+GmOnY7GvopXz39iEw+NHKQgd+xIG4ETP2/bRPHlWXxZuK6Ok0REwML9P/RGKY4XfChXEdC7NUCkVfHz1cN5eX4zHL3LlmAze/vYHbpWC15VGdOG2NvLMT1Ucqm5jXE4MV4/LbD/mZqJN2hDvrWM4UNmKQgh6igGYtEqcHj+CIOBrf8OkVRFt1nLL5BxaHB62lTQxLCOSv84OZr76J4fTI87Ekdpgxq2y2Un+ozPQqBRctyDUSyXCoA78NsxaVZelpkqFwAdXDuftdUV8t7+aSKOWnw76KEJWyG3w5xFf2siRWiu58WFMzI0NdOoDyIoxhozHrFMxNieal1cdDVyDY7KjmffmFsqa5G2+3lMdMoYfD9byxHeHuO20Hui7UJidKh799iBL98r7LqizkRplDJT6doXZ/RPZV9HKN3urSIs0csnIVHa9fhaDpPaU5JHvYecHMOzqXzymbnSjG3889DCnUO4Mei3mmE/Nu+X3hkbHkg6+U34a7UvIin6BGFPo8fh4zS7+8eUaREli/mm5TBqSgdtXDECcef5/YeQnRkObnT+9/AWF1Y2kRFt47YZzSI6yUNnyLFVtLwJQ0/Y6PeM+w6QNVRbnmJNZ2cHzLMecTLQ2mklRkzFZc4lOMhKjkPjq0E480Uo0qvZEmKRiduxl9NAPIM6SEKIk0iuDCZVEXQtnWJ4jzeGk1aamLuw5Ys2yYuzx136gvsWKJ1pi0a5djOyfTu/MRGpra4lUmeiT0YOwsGk4fBejUqjQKDT4fD58Ph9arbZLpcXH2/bwyHc/ARCWGoE/wo4bNXv87edXBcpedoq2NPGXiyaycFs4VTEewkwN2DxaftrXG6ffz5q6arLDI1AqO8//SYYYnh14I8trthOuNjEneQxXbXqJMlMD9IOYQQr6JURR3Wrl6RXrsLrcXDJ8IGOz5WRXsnEQ2xs/Qmq/Dtv8sorNj48WoYMfql2JusiIoocDQVAhEUzOJeqjAXj2gln89SsdjZWtzB08kNk5AwPrnDEijzc3bcel8qKPdqJQiSSb4vnxwqtQKhSs/vIoLZ5gCawWZeCXkZce12VyLTrMxMr5f+LJrT+Rb68jvEVJ/sHDKKcHx/ZRyYoAYZVnOZ2CtlX4JDcKQU2dJ9SX06jSMT4tg+3VchMAAciKiGT+11/iEeVr7VP7PoweBS6PhYZWC0cLimiZsJMzZ51aJ88T4YF9b1HnlpnNpw59TLYpmTTjiSs1bpg3jsYWB0eKaxnaN43+Y6r5pOYBUIhkinOgbiJhYWHoTuIp97+Abg+rbvzuMXdoCm0ub3t3tTBuPa3HKWz1+0PScV42xy8fw4NLDgRIjO2lzTwwsxfnD0nB45O7LHZlQv7fwvJDtXzb/uDt8Pi598t9bLkvjhWHakOIjx8P1nYirPomW3jlokEs2lZOjNTE3YNbwOfhls8O8PUeeZKakBvDrPRrEI8EgwO1UuD+c0YGlp0eP4dq2ki06Ll8VDprVy9nsyuVGJoplYJk1pc7K3nq3P4oFUJIlzuAJburuGfGZIw37wx5XaduV43VH4H3Z1HaJpKvH0DfCx8lIT2UUPp0e3lAveQ/3hG/AwxqBaVNdlKjjFwxJoNmu4eHvznIY96LkRDINrrJm3M7xPfpcvsokxaHx8+Hm0v5alcl+DSME7MZpJDVUdWRw3h7s4O3NsgdKNcVNGDRq5k7NIVwg4bPrx3JB5tKOVDVypbiYIZ4VHYUvRLCeGzpQURJDhBsbj9qpcCdU3P5dl81AnDPjF6E6dQcrGpj5aE66qxuwvUaPD4Rdfu1qVEpuO/0Xlz+7rbA/r2ixMGqVgakRnDvjF7k11opqrfTJymMx8/sw/sbS9hU1ITL6+fBJQd4em5/lu2v4WBVG2NzopnYU85QXTk2kyvHZrJgUynLDwa9uwpIpUBM5b7F+1n0pxGEGzR8fcMY1hbUE23Skhpl4Ip3t5Ffa2VYeiTXjM8iTKfmwyuHsfxgLZkxJiblxvDmuqITnjtJgjfWFtFo8/DM3P4nXO/nUNpoD11usJ9wXdoVXH85I4+/tJvan/7COp72Owix9jqunXM3utGNbvwcbulxHma1gSpnA+NiBvxhPaw0ytASeq2qc2MLu8vDh6sXkxbnpqQ2lndX5DNj8DskRx1ApYwmTDfi/3HEP4+3ftxKYbWsgi5vaOWVpRt54tIZNDuD6ikJL62u1Z0Iq7OSx+ERfexrKSRTl8AZUSNoc7k4/62FFDfKD/O3TRrF3mYn+yr6MaJHAYIg4baOZXzvYCOcZo+NSkcjGaY4bsw+nVu3v0mz6OCquKOka2RSJFzppcH2JLQTVm12Jy0jvHhj5Tjq9cotLBhyUafW9gaV7IHV2tpKRUUFrVIxCp2PgelT0KpCk4oLtu4O/N9WpsVfp0GfbENrDMaCgkYkNTGCo41N9EpO4JL0x/jn7k38WBRUPsWbw0hPTz9h+VGcOoaNG7zsKN3PwtQyGpODivBqXytug8B1nyzhcK2sHtpUXM7X111CRlQESYb+zEp5kmLrRna05FPplhNnGoWGqb2GkT9cYNWWI+hHtqHIlef7aG040+Mnsq5hLzHacG7tcR4Ah9YXUv3yPrxePy0Xx8OwIGGVFG3h7DF9+aZlBaYEOfao8+7FJc7BqNDz9IhZ3LppCXavmzlpvTl/0EA+2rCJ8qTDuI0tvF/8PXOTT+OdPTtpdbs4P68PWRFR6NVqHhktK5zuuHchPqUmpIVSg93N81s2cuvwUSQY+nBBxpvUufKJ1mYzzO7kiYMfYvc5mZ00hkERPRg0BGIMRvIbGxifmk6D09FOVkmgAP9xj1CtDXaef3k5er2Gaad1HT//HLyiL0BWAYiI1LgaT0pYWUx6nrnrLACcvhbeOXoukiBTfIWKr4jxDwj4fXXjt4NuwqobXeKqsZmdCIs/Gib2jOX2KT34dHs58WE6/nFe5wfejUcbOFgV+uDpEyUm9TzxzfK/hf2VrXy1uzLktWMlflkxoQqZ45ePYVrveKYdfVT2bCqF6i3T+bow6BWxOr+esy6Yh6Jgd4AA650YVOg12z2c89pGiurtaFQKXpk3iIWzTdiXXMEeMZN53r8E1pUAr19EqZDN348RbbSXiK3Or2dmv1DPrgDWPcPG1kjme+/C7dFgfvMwn1yfEKIWVCt/vn461qxlWEYkr62RSZFv9lTx2sWDOGdQMssPqngv9gFemjcIOpCZDo8PASGg6FlzpJ73NsotehtsHrQqBfN89zNLuQlRUnDu9JvZv7os5HMPVLVCeyFperSRB2flIYoS72wo5kBVG6OyojgruhoURZxz60hu/a6GVe2+U16/xOFaK1/fGGqe+djSg4Guj9tLm/lgU2lIeeT4HjFEGTUhpuVf76lmQGoEqVEG3rx0CBe8von9lW1c9cEOJvWMDfi5LTtQQ9O7Hra2d9J8Z0Mxb182JMSPLMzQ9XSzo7SZHaXNJIbriTRqmNU/+CDyw23j8PqDxBrAqKxoRmXJWUmfXyTapKHBFlpOeLzybFd5aOnH8XB5/awvaMCoVTEyq3Mp6Yw+CQGTdpVCYGrvrg1YTwSb28drvlk8q34FlSBi18Zh7H/hv7SPbnSjG93Qq7TckHP2f3sY/3UkWW7F66/G5t6JSTuUhLDOZfV1tld4ZP4HABwoSeWFL+bg9xuINJ7xXxjxybFhzWEO7C8Pec3jkxNqOnUWTu/hwOs6VecObQpBwdzkiQzxpOF2uykrKWVHkzVAVgG8u2knV04eyg/ryvhyszzPXTc0qG7Z21LCn3e+g8PvJkYbxqtDr+PVHldQ19yAQZ0f8nkaIWhVMH56D464g8muTc5Smt0OIrQGukJ1dTUlLKNYtRR8cLTkK+ZmvIJGGVxffZzHldIl4CszIIY7UWhEkKCnN4uGMD8fb5d9k1bmF/Lu5efQ5HRypKmRyelZ3DxuIuoO6iqr14FBqUXZ3tTnlXWbOOTOxxAHBVV+YpNU+ATZ/8mo1JIVn0Z+7fdoY50IKhFPo56jdY1kRMmWFanGoaQahzI02sHXVV9j89kYHzMeo8/A3fPHcesl4/nTwb9hbz9c9e4W4vWRvDn0rsCYvF4fLzzyNV6vvNLiBZuYMKMfuX2C1RxXjx3Mqm1LAss+tZO9LYWMjO7DxMRsnhg6gz9v/oavSg9Qbm8lum8DVlsLeGFB6Y98f6iSLUVyWd+nB/ez7MJLie9Q6qixaPHv0eEuMaBJc+D3KaivCufVkq1cM3gwLV4rMdoEwsPkMUVq4csxj+MX/YFjCXB+XtDzs6CpEQUghfkQNCKI4GvQoGlRonCI6Bvk73vwcNVJCasGd2u7j18M6cbQmF+tUDEyqg+bGuXmYTHacHqFnVj9fjy8kiugkANZaqQ1KNHruxYo/E/hN1QS+Gugm7DqRjdOgpsn53Dz5BP7d/3zp6Mhv/NwgzrEwPm3gv2VrZzz6sYQDyqFAH+emgvARcNTqW51suZIPblxYSfuYOhshl0LECWBb8QR1JYqUAkEWtAqBBicFsGzcwfw0ZZSooxaHpwVrF3+dHs5RfVyhsjjE3l2+RFOu+USpPBcBjUVEvEtNLd3bp7UMzbgsTUsI5JIo5omezC7dqi67cSElSDwjn86bmTPI6tfzUdbynjy7OBkuragvutt20s5txQ3UW9zB7oKHsOushaemduf9zaE8eHmUm5btJsnz+5LZoyJl34q4JnlR1AIAn+Z2YszByRxy8Jdxw1NokdyLNucpzN/dAYWkxmbK7Q98fFeTbR39gyQyNvfgbdvwycpaNNmkpj5Ysi6xzrq0U7qqJQKXN5QL6xjy+sLGlhxqJasWBNjsqNZ0q6Wk/cjlwQUN9h55JuD1LcTQ/VWNxuPNoTsr7A+1MBzzZH6EMJqQm4s4QZ1u9dbKB5Ysp8jtTbMOhVvXzY0pGtfR7KKtU/D5lfkjoRnvYYqeQjzhqXy4k9HQ/Y3s28C3+6tDvw2h6WHZno7wu3zc8EbmwMlp5eNTOOvc0KDpyvGZJAUoedIjZXROdEh/mqngusnZHHfYgcHPGkMDmvj3qsvwRj22yO1u9GNbnTjfwFKhZGs6JdO+L4k+Wh0BN/vnV7GxZOgV8pvz5vm68+38dIzy/DpBBQ9DYhqAbNey/zThgCQHvE4Agpc3mIiDDOIMs7qcj82mw23243N42VDeQ3VdkfI+xa9jisGDqLZ6WRrZQX94uK5eXhQZfZ+0UocfjmpVe9u4/OyjdyQczpKvR61cA8u9xXoFD5ECbTmIEF47qQBfPjjBtx+FQmWVgwqkVp3JRHaE8fOZYoVgf9bfGWU2reQEzYRgKqGVmoONyOEgaSUySuvICJ6lLgOxNJvtIKjjioqEkqoqTe0u2aCze2hxebioznn8eh3q9h6uIL7rD/y1zNOQ60SeHj/O2xtOoRZZeCRvlciIPCT6lsic+W42NCsJbEhFyGyEY1Wxe0Dz2R3dS2x/Vz4THJi2pDkIDmms8WEQWXgglTZW6m8vJyy1jK8khe/ViJSY8buDJbsRWnkxKlfFFEIAqJfwndcfOZx+5Akie+W7KK0uJ5hI7OJ1IbR5AkmyCM1svXG4bZS/r73O7ztpXc7Giroow2Nxw63VAHyuFvdLnbX1jC9A2F1wdnDWL23CMeWCCrt4e1FfRATJnHplsdo8dpIM8Tx9IAbCdcEE9rHyCpRFKmoqMBms6HX60lJSSEnMoo8UyQHNe3JZgV4s3xMb8xi609HULR/5X69T9yhr8JRxy07X6TNZ0eBgvvyLmF8bKi68IHel/F99WbsPhdT4ocQpu58fk6EMHU8uWGnkd8mX49p+pH0ThnxuzBe7y4J7EY3uhGAVh2aBbp4eFqnzoG/Baw6XBdCVqVE6PngyuFkRMs3dkEQuHNaT+6c9jPlBSodKFQ0+E1E08Y//OcTplPg9MmKlntn9CQ5wkByhIEzB3aW6GuO69ynVgpc+s5W1h6pJ9IYjc3jDVD9Fc3BYOueL/aGkFUAL606SmqUoWuCcOwdhO3+CDpYP4Xpg7c7l9fP0brQsq5rx2Xi8onkxpu5b/E+jlUJHlMRHcOgtAi2lTTx8Ddyt7rCejs3fLyLNy4ZzNM/HoH2EsNHvz3I/srWTgSNWqlkb4Wc6Xr46wMIx6mBaPcQOym2vkWrZGSe5z4OuDPQ7mkgxmzA5RUZmRnFjROzWXuknpsX7sLq8nH5qHRumpzDtR/uwO0TSQrX4/GJjH1qFeVNweM8f3Qao7KiOFTdxvgeMcwfncGn28u554u9ncaYFmWkqtWFX5RQCJASqQ9RZ+Ue591mc/kYkBLO4eo2Ykxajtbb8fhFRmdFBYzZrS4fT3x3iK9uGN35O5dugp8elf93NMJnl8Nt+5nVP7ETYfXNXrkccmh6BKOyorl+opyRrmpxcsvCXRTW25maF8fjZ/VlW3FzgKwC+GBzKffN7IVWFep5Ma13fEijhX8FFwxLZVBaBFUtTganRWDWqU9hq250oxvd6MYvgwJBUCNJwWTQ1dPG/iYfRNetltVTKpdE1D47I0/vza03TSfKLCuOVMpwsqL/+bP7USgUuHx+7l+9jUqrHN8khYdR02ol0qjnyTlTUSoU3DVmbJfbqxWhj4QOr4+JC96hrK2V6T3sDEmLIU7poVVUkaKoYZwJnH4r6xof5eLeR3H7VVS7LXgkFc8VPM1DeQ+RqO/c/TghIQFVlR5/hwBN06ErY1F1Ez6XH0N7GCQhcsPFo2h2OIlPE3ir4jt5fH43YT38VJcoULgFwlx6esRG8+aG7Xy2S1bclDa1EGk0MKCflq1Ncmc+q8/BSwVfYvU6AqVgALoIN42fV0DvNqQRPu7a/gqlZeFEJLVy7KoR1CIV3lp60XWy1Ofz0draSpW/lo+d3+CyOYlUK8g2amjyGDg9cRyDI3N5b/Fm3v5iExqNivv+NJULrhrHJ2+uAWDAuCzeaT3Ahje/xXPASsw2H0s+28o1z0zlW8NabF4nc1MnkRuWylOHPmZ57Ta0JohRaKlvk0msXGMOu9r2AhLZegU6pYnW9thapVCQFRGaxNPEW5l8u4PmFhfN9RlsbmrDpNEwONfPUadMfpU6avmiYg1XZs7s9L0bGhpoa5PJNLvdTk1NDcnJyUzrk8PBo8HqCBGRFSUl6HoYmBCVyMRhPZg8UU5qb6wt4S/bvsfp83JTnzHMyx7EDzXbaPPZA9surljbibBSK1TMTgqtKPhXcFrCveSFz0SSRJIM/RGE346NSzeC6CasutGNfwP3zujFoeo2atvc9E+2BMyyf2tIjw7NOPRKCCMj2si3e6t48rtDaBUif5nd7+dLGcs2gegjVmghVtnCC8LLnOP8K69fPIgpefEn7Jy2o7SJRdvKCdOpGZwWwY7SZsLVPq53vcmeag1rmUOTPbSs60itDbfPz47SZhZuK+9yv6sO13VNWEVnc9dNN7Prra0Ut/iINGqY3S8YOOnUSgamhrOrTCYqwnQq5o/JIC5MR2WLkxNZWo2NsjKqfhE/7lQHOqQAFNXbQkgP2jtENh5XqkY7KXMMUrvP0vFIjepaSh+AMZoP/DkckOROdm5JRb3Vg1opcPvUHhi1Km5btDtAlr29vpjTesWx6o4JlDc5qG51cuuiPZ12u62kmW9vCg1mn19+pBNZBXBGvwTump7LK6uO8sOBWnaXyyScWilw+ch05g1LDVn/2gU7AkRdvc3DNzeOpkecmbfWF4d0EhRPdPBttZ2W/aJEuEHDRcNS+Ghr6DUiAVqVktumBD34HlxyIFDat3BbOb0TwwKG7YFDq1Gh7qKF9b+DI7VW8musDEwN7yarutGNbnTjPwxBUJAe+TeKG+9EwkOMaR5humH/7WF1icTkCPbskG0DFH4YnJNMlNnAk7tX8nXJXhKNETw7Yg5p5pMre+12O0ebWgNkFUBlSxtb7roOi/7EBtKfH9rP5soKUiLTiNFWUO9uI00bzd58K2Vt8pztlEpxSkpKfHKplNYlJ+e2Ni6mxiUnjLRKH9EaK1XuCDyih8PWw10SVhaLhanCfXxb8VdEwYHXOoTYDp5cuSkxmA1arA6Z0OqXmcC14+Suj0srt4Xsy6/wI5pERBNMSUmnpL6aLRVlSEgICIgqiU3VZSRmhyabXH4Pdp8z5DVBFEBjRxrla9+3l9ikZpxeNWqtLAcSEEg0nFixrVAoEASBle6NOCUnURobaoVMivUxxHFh2mQKyxt4/dMNAPicHh55ZRnL376BsVP74HJ6+MSaz8KD7R5evVWo7RIRB/w0bHfyzk33Bs+to57ltcHjYTa4abb7kdwabs4+izL3INJ8fyNB2IEnWcF9W8ezqrYfT542hZzIoPVBi6eF5wuexy25wQJx0U4O9PkbWqWa+/a+AR0Okyh17e3k8/k6LYuSi8v6ZvNjfT4HWmtBAk2ZHP+4fD56DE1h+hS56sEvityw/kvavDJL+eD2ZfSxxLOjqDqEqTCrf/1SvU2V5bS69YxLTf99kVXdJYHd6EY3jiE33syGuyfR6vQSadT8JrN3ALP6J1JUb+f7/dWkRRl4/Ky+1La5+Osnq2mWjOhxs33Bgwy99znMxpOQJc0lIYupQh2CAInhhhOSVUX1Nua9uSWg8JrQI4atEw5g2fR3tDYfQ1VmPKgpl2JYIQ7F357LGpwWgValDFGGHY8ecSfpwKjWU+uQ78JNdg83fLyTVXdMCJyj9y4fxgsrCzhaZ2Vmv4RAGV1SuJ4Lh6XwyXEESIpQy0u2+zGvdnAOUKOazT98sgTc7RO5ZeEuBqeFs6NUJq6m5sVRE6KUkjjXcoTlrUm00rVHmEWvZlb/BK7+Of+4M57D98abENppGK9fYt2RBnLjzFjdoQHEzQt38talQxmeGcWrq0PbMR9Dz/iwTq/pTtBd73CNlTkDklh+qC5krvP6JaLMnTv/HK62Bv73ixJH6+30SghDFCXMOhVWlw+9Wskd7WWqnZA5Hp8lHVWrfA3a+lzMGc+spqTRQVaMkY+vHs6PB2oDfmEAzQ4PpY120qJkwrbOGqpc+25fNZuKgkb2Bo2SFy4YcMJr+Zdg+cFarluwA58oYdKqWHTNCHonWnh9TaHc2CIxjD9Pye2kPuxGN7rRjW78ckQZ5xCun4okuVEpw//bwzkh/nTTFNwuL0UFtQwensXsc4aytGwXUcLDPD+wnGqnhUe3NvDW5DtOuh+Px0OkXouiQ//EcL0Ok/bEqv8vDh3gzpU/BJbvHnkaw+INqNzwcHmw62BZUxRD0ooDy8kG2RTcL4UqyDtO+4m6zmTVMeRXWvjnZ5MQBBFJUtBcu5pHZ00BICbcxJt3nMd7P22nVeHmqolBonFCXD8+K99IgVW2LmizBgmMJfmH+OxAPhIghIPCJeE3wj5bHRWrm+mdF02NuwGloKCnOYcdjUcBOSZQIDC+bgCrVQdDxqlQijSXWrDEWUkJN3Fp5gR6W0KTcSHrKxSkpKQg5YNSkAJkFUCDp5Y6VyU2u0zaSAK4zQIOjZ9rXv6CZ6+aTYRJT8l3W0L26QmTD2pmTmg5q1apRkBAao/AJAm0fj/WVgUHGxqYktSC1CyfQ41S5OHB6/l2QU+SjKFxXp27DrcYVLs1e5vxSC5UkpfZsRUkKg+w2xqPR8jhrOSu1Xnh4eHs31NMfZ2NzJxoIuNL2VVxOqLk4OnB03AqH+DZT9ezu162ahDVkN/QgN3twajV4PR7A2QV7fzJg8tWkF/SSlSeDl2kiyRdDNdln3XCY/9L8PiG1by5ZzsAuZHRfHnOPBQKP5+Vf0a9u56hkUMZFzPuV/3M/zd0E1bd6EY3OkKlVBBlkmvo1xXUU93iYnxuTIiP0DHsKG3ipo930WD3cMmINB44I6+LPf5ncMtpOdxyWtBTYMnuSuoluZbeior3fVO4cvsHMP7aE+8kaxLoLOCSmZLVqjE8PK03fZMtJ9xkT0VLCOm0ubiRWN0OEHyIksA8z30clmS1UoTCwdRBuUSaNFw7Xi7jqm5xYtGraHXKBMzwjEh8osSgKB83Fl0HLzTCyBtg2NUhn1tYbwt0AQQoaXRgdfsIa1e4aFQKtpY0sr+yjbUFDRyts3H/TPl8PHl2P+YNS6O4wc6ti3YhSjBZsQuLEFTjnKncwHPihfja5UeiBHq1ki+vH4XN5eOGj3YGSCMLVhapH6Wnu4KirNlMLrwgZH5QK2Qz8avHZZIbHxbq29Su0PH4RHonhslEUFQWF9/4V955enUnYio71oQgCFw7LjOkVK7e6uHWRbtZdccEJvaM4YWVR3B55fOSYNExIiuKe2d0Lgn9y8w8rnxvW6f5LClcj4TUpSLKrOs8tYzrEcOKQ7JKyqxVMSg1nLfXF/PUD0Ez19um5DCuR0ynbQHe2dHCy/X3MVHYQRsm7A1TKWmUOyoV1tv5bl81D5yRR6Pdww8HavD4RA5UtTH7pQ0svXkMyREGzh+aElB5mbQqPP7Qsc8ZkBTiu/Vr4INNJYFrxOb28dn2CvbGt/Lk93IZyLqCBpDg3tNP4BvXjW50oxvd+EVQKvSAHr/kpdC6FoAs01iUis4kzkdbd/PMyvWoFQoemjmZ0/ucIHnyK8No1HLPw6EP4j73ZwyMkJNmSYZWxsQsxe2+Ca1We8L9WCwWEtvauG5wbz47VIRZr+OR2VNQnkQxvKUqNDG3rbqKsboeSILE5IgEdjc0IimhtDqOQtdkZs/QE6lJp1/EmYiSRFObmxSVjWZRhUuyEKcbjEGlYJBhEIoaBUfrjpKYmIjBEJoIPVBVB4AkyWM7UF0XOjCDgm/dhbS53fywpJiXp89iamY2RpWW14dez+G2CjZUVfBU9YbAJu4OsYikBIVRgb+dumt2ehmmnsD4XvEUW5t4cM/XAKiVOnJ1UdwcNQF9pAb/fgW7vBvpEVuDJAnsLEpHLxk4I2wI56TkkR0bHTJMUfLi8BxApYhAp5bj2LCwMC7rMZdHDj6HKAko2g2CVIKGcE0U8dlGBuWlsLm0AlErk1E7i6p4aekGHjj/NGZk9GBdhZx4EyToo45iys3ZTJwW6q0ZrQ1nRvxollavB8ArKjFHOdHqfWSER4AUem6F9nGYj7uGkvXJRKgjaPbK6vN0QzpmlZndtddjc62mpxF6GmsYFH83UdrOxK8kSTz16FI2rM0HSSIi3MA9r32OiBwvt7p+ICt6Do+fN5073/uOA411iILEt/vzKW9tY8E1czGptZye0ovvyuWyzZ7hsRRsb0ISFTTsjwUkbj9nJon66E6f/0shSRLv7Qt2Gs9vamBDRRlF4gq2NMmk4f62/URoIuhr6XuSPf02IQScyE5t3d86ugmrbnTjV8KLKwt4drkskw7Xq1l26zjiLaGk1W2L9lDV7on09vpixuZEMyH3v2MCGl6zEQgGEQ60GCT3SbchIh2uXgX7PgNnC+f1OQdS0jutJopyzkepEMhLsKBWCnjbyYH+yeGQOQGOLKOBsABZBdAsGphb+SSDL3oE9Goe+eYA72wIKmbSTSKLrhkpLzzfD1pK5f+/uwOSBkNSsONNz3gzkUZNoNSwb5IlQFYBbCpqYH9l0MDy3Q0l3D29J6p2sqhvsoW+yRZWHqplyZ4qKqRQIqVSig4QEccQZdLi9Ym0ODwhRFIrZiIUsg9ApqoJs05FW4fSwHG5sRyutnLx21sxapS8fflQRmTKku0nvz/E6+1dCmf1T+TFCwYgCAIxZi1Lbx7LZe9upbjBjkGj5PoJWUzsKV9Pt0/NRRDghZVB0qqhvUtgz/gwvrxuNMsP1pIUoeP7fTUs3lnJ8gO1vHLRIEZkRuEXJfQaJSkR+i6TL5FGDQaNijun5fLUsiDpNK13XJdlmi/NG8jb64tptns4d0gyyREGtpU0haxzfMfNYzhc08aj3x5EwsTnjAcgpjbUVNTlFdGqlPzzwoEMfORHPO0kaavTy7qCBi4clspFw9PIjjFRWG9ndHYUn++oCDHVH5ByYuL1lyLiOAP9r/dUkV4RGrzvrzpOKteNbnSjG934VSBKfr4tvwuzbwMaQaKwZRjTUl5EIQTVwxXNrTy+bHUgAXPPVz8wLifjpOqk/yQSlKGJqAStbGx9MlgsFpRKJedGRXH+sAGEh4ej0XQe/7FGLAD9YuP57NCBwHv9Y+MxmUxYrVZ0bQLRO8GnB7UdtksGbpt8DsmxyQiCgsc2/5npiV8A4JcEasUbmZPxZ9xuNwUFBXiQY6/S0lJ69uwZoroekZHCG+u3BmKLEemhMcOig/toc8vxik8UeX/vLqZmZkO7sqh/RAb9IzJY/NMhCOGv4QABAABJREFUSr0tKG0CboOA1CHk9rnFY37sAETotYiSSJk9GHd4/Soa3SJGhbzhJTeMRKpbhFotJzvHZBQQr5/N+5/v5RvvXlJjw3n7rvOJDDMgSi7y6y7B5t4GKEiLeIRY88UA9LbkcnvODbxY8C56VSORGjNXZVyHSSWrm56/9xxufvUrNhYEO0Q3WmWCZ16v/sTojRxorKVnTDgfVX3Fh87D/LRlC08PuBazYEKlUqBWKknQJdHs1KNT+wK0g8bgxWJQgnYsaMeDew1+UeCZbaO5c+IY0iNDS0sNKgP39bqPn+p+Qq1QMzVuKoIg0OLe0WEtLy7fYaB3p+vp6y93yGQVssSuucWB22NH1eHSEyUXydHhPHzRFM7654LA63vKq6lsbiM1KpznR85hekouTp+XaSk9ubpyMbsrZP8rtVJFz/iuk5m/FIIgYNHqaHAGE9FP/7iOvCGhnqil9tL/ScLq94Zuwqob3fiV8Na6osD/LU4vb60r4i/HKaiaHaGeRl11TPv/woi6zxgkjGSnJHv8XKb+Cf2gu0JXcttg70J5Iux/AWiMoI+AvYugqQi2vApTHoHRtwQ2WbK7knu+2IfXL3LblB7cMDGbNy4dwsdbyog2abhlcg/ynX1ImqYlonwjibuaqJJkTwATDlKb1sOSG2g4/5uQ8i6AEpuCZStXMH3SZGirDB1ra3kIYRVl0vLpNSN5f2MJBq2Sa8eFtoK2+ENJApNOFQjicNvA2QRhyTw0uzeHatpYUTuY1ziPM1hDhRjFnd4/QTsppwB6xYdRUGvj/Dc2I7SrjI75VfUUyok+Vr/Xby5S6NfC7vJR2SIbBdg9fl5cWcCIzCia7Z4AWQXwzZ4qrhmXSW68meoWF7FhWlbdMYEluyv5aHMZ+yvbqGxxkhSup6rFSX6NDZ1aEVBSXToqSA7mJYaRlxjGV7sqWXlYzm7a3D5u/3Q3bS4fHp/INeMyuW1KD9KjDJQ0hno9JUfIUvzrJ2Rzep8ECutt9E2yENuFspB237AbJsoBJz43tFYwKCWMHw4EvakGnqD73pFaWyfSLDfBjKdCDJTjdiyjTI0y0uwIeoqlRQYJouGZUQxvJwNvmZyDUiGwv7KN0dlRnD/0xFL/X4r7Tu9FSaOdfRWy5WmT3dPJr21U1q+XNexGN7rRjW4E0eqtojcryWx38baKP9HmOkS4PqhYaXW5QtTCHr8fp9f7XyOs9K4pOAzfo1BYkSQlyapL0OlC51aPx0NbWxtqtRqLRU62KBQKmpqakCSJ+vp60tPTMRqDHqbPvLuSL5fvwWTU8uhNM7mob39cPh+bKsvpHxfPZb0GUNdgxRKuJjvNj8a3H2WrfFxSk8y0tbVRX1/PAa+NZMOmwH6VgkSDazHNzivQiKHHzO/3I4oiSmWQIByZmcorF85hVX4RmdGRXDI81EjbcJyXUFgHVdAxvySVSsU/ZszklleWYHW4SU8xcVRrxSdIqGyg8PsRYmSdydTkdBY3f8X79Xa0Cg1apQq3vz05qY8LHDulwRsgqwA0Wh9b8w/j9sqfWVbXwuJ1+7hy5nBanCvbySoAkYqWvxNrvhi7y0Oz3cmQyN58OOIZXli9kS0l5XxaU8ddk3PRqFTsrKiiWe/FHyagsEmoBQXnjgqSIlPSs5mSns0/Di+kyikrySud9dyx8n32fyOh06h4bP4MBmelo1aokSR/oBzTqNISpjYgCCoIfx2H8zA1VrhzZjbGE1zP0dpo5qbMDZwvr9eLRdufRqes3vo/9s47PI7y6tv3zPaqVe9dlrvcey9guum9Q+gt9EAIpEEoAUINvYNpBozBBeOGe5GLbFmWVazey65W23fm+2PklVaSKXmT90vy7n1dvi6P9nlmZmdHmrO/55zfEVBj1Q4UqwAqypoG/MzVcDHWzFcBCaO2gGjDSQDEW0zoNWo8PdfTpNMSY1JiSZUocmpG73emFy88g2fXbqbT7eHCCQXkxB3fO+wf5bkTTuP275bT4nKhcglUuzrRVYnE9einIiLDrD/RjOrflUhJYIQIEQbD3a8tbVmLc8CYa2Zm8+yaIwDkxJlC2TD/29R2uFCp4/hQ+2e2SCMxCR6mzDkVrH06nwQD8O5iqFPqu9m3BK5aASXfKGLVMba8EBKs3L4g93y2P5Td8uSqwywamci8oQnMG5qAw+Pngle2cajBgUGTwt8ve4x3J3bx1Cdr8DqauUX9JfGCA7oaqW53DWr23VK2BxYshFHn9ohpgDUNMgd2CclLMPPHM0cN3Imvmwnfncstqsm8GjwNs+jjmfN7avPL18HHl4LPCVmziLnkM765bRaNdg9x5pNosLu55oVNdMvK5x2UZIJAVUd3qGzxmJn61TOy0agFrstPQdX8Z0gcCTlzOfXo/pCRvEmrYmiShW2Vvat+x0oCVSoBsV8XQafHz6JnN1LR0k20UYNBowpl7QHU290su2Um17yzi0MNSsaSShT4y9mjOW+QzCdf+Q9ArxdYax+j+Fc2VrBwRAIfXz+Np1YdZuORFlSiwFXTs0OiT7c3wO0f72VfTSd6jcjLl0wI3dcd3T6+KWrAatBw2uhkxRuq8QC8fzY4m7gucRS6hc+xtUFmcnYsl0/LHHB+9PiZmXVqnD1Za2admsfPKUCvFqlo7SYv3hzWnfO5C8fym6VFNDk8XDQ5g+l54YKQLMsIgsAPR1rJijVxzczsf5kZelKUnmW3zGTyn9fQ3NWbwXjBpDREQWRkipVLpvzzhbIIESJEiABa9GRrep+RFjGIX64EemODoYnxTM1OZ1ul8lw+ZWQ+8WbToPv7V1Pc3Mxhu5nc4AuImlIEKZWszDlhGUo+n4/y8nKCQSUOcbvdJCUl0dbWhiwf8zSSaW9vDwlWO/Yf5bPVipm3w+nhDy+vZPnLN3DtuIlcO24ih8obOf/Xb+JwekhJiOLl313AIzdr+GTFbox6FefOV0okA4EAhzqa8fjCr0+XpKO5q5m82Dy0Wi0+nxJLWCyWMLHqGPPyc5iXP9Cv0+12M8diY3NMHHvbW8m22nhwxlwAmpubaW5WFtji4uIYm5fKysd+RXuXi6QYC98UlvDARyuRjDLeEYFQrVOdqizUbc4r+ZiWmEaiJos0Uwynx40i6PNjNptRa0XidBm0epXMpwRdLuWBKKB3wU7T00FYIFz8EQQdO0pruOO1ZXR7faRFW3F6PDSaleuwp7YBnUrNpZPGcsOHX+L2B0ADsakG3r7kXIakDIxT7M7wrPOKplYgFrcvwEPvrWL9kzfwypRreLN8LWXOGqI1Jn49fDF6lXJupc1tXP3eD7R1u0i1beXdK84j1aZkeZXaW9jWVMVQWzxTEpTYq6Ojg/r6emRZJjbqLgyWDHzBNlIt52DRDS7cTJySy7fL9oS2c4ckMWfa1QTkiwhIrRi1oxAFRXCMMRt59uLTeGb1ZkRB4N6TZ2PWh5coyrKMx+Nn/+YKTrFlMPW0/H+ZP/D0tAw+Pv1CTnnxndDPjhxI4oKCKQTVTiZGTyTPnPcvOfa/GkFW/v3csf/uRASrCBH+SQT7qStJg2Sa3LEwn+m5cbQ6vcwcEhdWovavRJJkmru82Iwatle2c927u9AG5vGMvpxZUbXohsyFOfeHT2or6xWrAGp3KKbrhvAadr8+hoY2FwlWHb6AFBKrjtG39O2TnTUhEcXtD/LEyhK+uW0Wf7/hJHh1Hrh6usVNuJIhCWaSrToaHL1f8uOwszCr55qd+RLkzoPuVqUcsCf/uMHu5oW1ZfiDEtfNziEvYRBj9rZy6Kzibk0Vd6k/VVamEnu65q38jSJWARz9AfYvQTPhStJ7snRy4s18dfNMluyo5vVNvSakx8SqY5h1an53ep8Mu9xxof/++azRjE6Losnh5fSCZBIsenZXd3CgzkG8Rcf9PV5SVr2G3502gj8sL0aS4fo5Oaw51ExFixJ4dbj8dBCepXe4sYugJFPS2BvoBCUZq2GQey0Y4NTiu3lXuJ8DcjaK40N4YHnJa9t55fKJPHb2aG7+sJBVB5v4+4ZyxmdGMyEzmqV76tjX0yHR45d49NtDzBumiJNnvrSZqp7MrPUlzTx9wVhY80io45/QdIArh67kysseHHhuPciyzCsbyhEEiDNrWTw2hXsWDUOvUc7zmH9cX/bWdBJt1DIuw8alU3tFMH9Q4tcf72XlgUaMWlXo3hySYOa6OTmsOtBIWrSRuxcNxaz7eY/HbRVteAMS03NjB3iP9eXUgmTe6ilvFQWINemYmRfHmHTbv22zhggRIkT4T6fR58AmaYhWKc9KSQZJDF8cUYsir15yFj8cOYpGJTIzb6DVwb+KoOzHHejEqI7hb9u28/z2bYiCxORkHfcXzCQ1MSMsSwqgq6srJFYBdHZ2kpSUNEAY8koSNXY7KRYLTnd4Zm+3O9wC4vXPt+JwKsJefbOdJSt2c9ulc5k8Ko3qakXAEQQBm83GdK3Ald/NJNlkJ0lvp8YXQ4dnGqmmVFQqFTk5OdjtdmRZxmQyIUkSoihyuOswG1s2YlFbOCPlDIzqgU1+uru70Ykivy+YgCzLaLVa0qxWAoFASKwCaG1tJTo6GoNOR6pOyTA7Y+II4q0m3indyXfO0tDYNo8bTZ9QIcUQw33DTx/087gk8wn2dHyLKIiMiz6Fqec6ue25L+l0uinISebcOQUA2AwLiDaeSofrG0RBT1bMn7n+gw10e5XrXNvhwG+UwxyCjrS0UdnWrohVx87N5SY5dmCc2t3dzSz1UPYJlbhkL3pZi/2whYAGfNHgVvk45cV3eOeKc7k/52xufPkLipraeTJtGy/flEK02cCLG7bR1q3EYHWdDt7cspuHTpnHvrZ6Llr7Pt6gch6PTz6Vc7ILQmIVQJc9QFb0rzGbB28SBOAPtpMw/I/8+f19dDTmQ+f9LDpZMclXkxnWTRsgIAXoMO9n4cl2RkeNZkp87yJqQ7uD219bRllDK1aviGa/HUGCBaeMxnRuNAc66pkan82VQ6Ye93z64vb72VZXg01vYFxS8nHHpUdHMSI5gTp/OWl5zRjUOmJ1s0jQJTPCmvqzjhXhX09EsIoQ4Z9ElEFDR58Sv0WjkgYdNzn7n5/W+mO4fAGueHMHO492EGXQkBZtwBuQ8GLkWs9t4IH7Jw3jBnW/VGFzAqgNcKz1r8YIpliIPQ0mXAV73qPZkMdFrt9T/uQ64i063rtmMhdPyeDD7UpwMzMvjoLUXl+g/l/MQ5u2DLh+I5R/D1HpkDsPC/DpjdN594dSGoq3MD64j1PyzSQueEyZI6pgyInw9mmw+kHQRxG48BMu/sxDZasi6Kwtaeb7O+cSZewVawJBiY9K1bTKF3OmvJZssRFMCWDuMduWwoWnAds9mVt3nTiUb4oaaOjJbkqJ0jMxK4Zl++oxaVU8ds7xa95VosAlU8If5Mtunkmr04vNqA3rGHfljGxOHJmEJMmkxRj5/dcHB9ljL3OHxqMSBablxLKlXEklt+jVFPQxxt9f28lDXx3E7fVzs7+Az7UPsz44mp3SMGpU6azy96bn+4Iyjyw7yC3z8kLle23dPq57dxf5iRZiTOFCWE2Hi11H27G7/SGxCuDLvXU8cW4BailcYPP7vRCU+LaoAV9A4tSCZIza3kfTsn31vLtV8SrrAorqHCGxajDWH27m9iV7Q9sdLj+PnqV8Fh/vrGH5fsUToa+QeqTZyb2f7g9lRbc4vbx48Xh+it8sLeKjHcq9PiMvlneumtxbVtqP3502gpUHGmmwe5BkeGl9OS+tLycn3sTSG6djM/7/KT2JECFChP9mtKKWZ1tGcml0OUYxyKqudC5LGGiorlWpWDAsd9B9/Kto81ayrOZeugNtxGizeXPPELRqgfMmbSMxys4mVnCG/s9AbNg8jSb8uXvMqyohIQGPx4PL5aLU1c0jG9fj9PkYn5zMK6csZkhmPEeqWgC47IzJYfvo3xz3WLxmtVrJzc3F7XZjNBrR6/WMM5l4Zf5VfF0xkYNyLeOj4rkpcwZmkyJuqNVqDAYDVVVVNDY2otPp0CfreerwUwRk5dlb567jrqF3hR3T7rezwbkBh9/BGPUYtII2VAopD9LgZTCm5WdiitOy7rsyArKygDrCPIKgtpqK7npSDfFckXXycecb1VZmxF8Y2h6ZZWbF49di7/YQazWFuggLgkhe3Is0d92PVWdDr7Ugye+FX1OfQLCP1jg7L4thifFEGw10uJTYenRKIuY+JY/LNxzg/eU7MRk0nDs3l9/GncMez1Fq/O1sTu6kuVkGlXIONR12Xt64HakzSGWTkqV/sKGJCz9aQmKsBcnb01gnu4X41A4ade10+saxvLo4JFYBLK0s4pzsgrBz9waC+ANBOnxOfmguJlprYlZCeFlgbefjOLybEVQQk1pIyogtQPh91ZeldUtZ0bgCgF0du9Cr9EyOUcY//eVGDtcp92aHJogpUYO5wc/n9v3YFS921jUeQa/ScGHOhOMeA8Dl93Pe5x9R3Krs79eTp3Pb5GmDjtWoVPztogU8cmgdkhAEunmv5lW2lOVwetYInp+9+EeP9W9LpCQwQoQIg/HkuWO4bckeXL4g509MY26/bmfNXR5eXl+OPyhxzcwcsuN+frr5W5sreWfLUaJNWh4/p4D8xEGyho7Dkh017DyqGEvb3f5Bu7o9vrKES6ZkhJdFGWPg/Hdg9W9BUMGJf1L8qwBOfxZOfZrXVx6mfKNSHtjS5eXp1aW8OjfIYlUdR8UMLJkZOL2B0JfxCyals2xvHftq7agEAVEQKK5Xsopu/qiaA/UJzMiz8Fx6EINWRVq0kQfOGAtnjB1wzgDsfAOaewQcj53W1X+lsvXK0MutTh8VrU7GZUTjC0gs21fP+1uPsrfWDpzG26oTWJG9jJST7wJNT3vkhQ/DJ1eCHACNCZIGF54MWhVLrpvKy+uV7J8b5+SREWvkz2eNQq9R/Wi2TV8O1Nl5ctVhJFnmzhPyB3hAPf/9EZ5eU4oA3H/yMK6Zmc2KokYaHZ4B+1KLArurOvhoRzWXTM2krNmJLMMDpw4jOUp5f5Ikc/Xbu2h1Kqurdwo3EVAJ3Bu4nlPE7cySd7OK8OvtD0gDSl7bun1srVAEsaQoHY12ZX8ev8TVb+/krasmhY236NQcaXaSOf1ujLW7wddFrRzHuevy0OxdT02HEry9u7WKz26chq4n7b7ZEb4K3NL1440BCqs7w7f7mKr3/X9/+v5W7K/tPO64Y9hd/pBYBbC5rI39dXbGH8eHSxCEQc+9oqWbr/fVc9m0/70V/QgRIkT4v0K6MZ2xcRfwl4blqAQVl2dejk4Vnpnr9BbS6vwUtSqGZOtNqMSfF59Jso+q9t/S5dmKUTua7NjHUYk/Pz7b1vIG3QHlOdruq2RSjoYuj4rEKMXzUsLD1pbXOM/0Utg8q9VKfHw8nZ2daDQa0tLSoEcoysnJQZZlHvjoA5w9ZXmFDQ0sLz/Mk3edSmFxNe5oB9npVoKyhKrHL+q682dwsKyRutguyBYoTW/H7nNT7WriDwc+xuF3cUHGTK7OPQGAqUkZTE06fjl7U1NTKAvM6/VS1nSEgOwPZRyV9smAarE7Wb2/hG36D3GiPKfLKee6uOtISU6BHpEuNjaWtp7uwBqNBrV68K+xBTHJvDb7fL46eoBko5WbR87AoNbQ5XdhVht+dlbzmsZdrGjYRqwuihvzzgyJVfT4nN346TJ+qDiKVa/jpXPO4LbTZ3Dn61/jDypCkSoAQjv4omVEm4p3ivcyKi2Rk6bk8+XhYmxaA4+fflJon0eqW3j0tdWhOL25rYs5l5tY5VZK7sQCAVOjia4jvQvf/qCEz9e7ENidIVGpr6c+6CcgaUhNF8gYrizUuajl9crXSTbODnufetRUVrUSFxdPS0szbxWWsKK0Br1BIGlaF/agUnVwXvoM7hh2Rp9jh/tX+YP9uj32o8wZbmhe7ixncsxkPAE/JcFm/HEB1G0qBFlAVivXOpAqAr2VG0Ud9VzIjwtWG6oqQ2IVwMuFO44rWAG4cfSIVQo6TQCNKsjXRw9x+5iZ5EXFHnfuvzX/AULUzyUiWEWI8E9i4YhE9j18It6ANKCcKCjJXPzadsqalT/6qw82seauOT+rJHB3VQe//7oYgKNtLm58fzff3zX3Z59XoF9nmQSzDr1G9ZNf/HG2wNo/QWspxA+HxHADeURxQBlksKsZ3rqEKbLEJFng5i238WfrXL68eQbxFh2iAC9ePI6Fz2zE45fYX2vn8jd3MCsvjh1H28kUGkk8vJJvlx3inHMv+xnvrvf4+6Qcrj163oARhdUdjE23ce27u9hY2hL2mj2oY/vYP3FWUlroZ7WqNFKRlZDK3w2fXQO/PhA2r8vj57PdtQjAldOzONzUFRJ0fokXkssX4PI3d4RMuPfVdPLDffOJ6infq+1w8deezpMy8NiKEs4al8aT5xVw2Rs7BuwvIMm0On08sLQIjVoMlWf+7quDHG7oYniKlYXDE0NiFT3dfR5R3UIwIOHEwDSxGAMe3CjCmQDce9Iw5uTH8/bmo1T0ZK/1pa3fveTwBEiw6MlPNFPa083P7glw8t9+IMGiY8klm7j3jeUU+5NxoYcesQqgqM5Ocb0Dq0HDI8sO0tLlxaRT0e1Vru/Fk48fILc6vcSbwzOVJmUpgd1fVpSwdE+4UX+0UUNQkjl9TApLdtaE7ucp2T8dnOg0Ito+1xjAqlfztzVHWLKzmgSLjr+ePyasJHXB8IQwk/lj9M0oixAhQoQI/1zOSTuH05JPQxRENGL4M9rjr+Rw88VIsrII5PIdIj/hzZ+130bHa7R2fwKA112DpjOWzJg//uzzkuTwDO55WRmsKG0I+5k8yLfO7u5u2tvbCQaDGAyGARlXgiAMiP067HZa1A1sNazloLMcDsGE6FHcP+wGREEkKSmKW+6fy63bvwDg2/pDSDskGuTDNHkUAe2NijWMMmcwOXFghtqPUSLtYYtjFRZVEK+kxierae/Wsr+1gVRdFBc/9RFOTTPDTu5dVKoL1GFJtIREKVmWcAj1dNOFiTj8fj8NDQ0hse4YFR3trK4sI9Vs5abRI2n1tuKTXRiIwqIZWIJ4PA7aK3mi5MPQ9e/wdfHk2JtCr399oIQfKpQyf4fHy+9XreWb6y7n4jnjeWdtr52GrJLxWwEpSHlHO1d//QXtASX7vMPv4fYfljEvO5u5Kbk4W8LN/1s6nKx2HQlVFapEGUOCB2eZhCyLmLVarp0xka4uD1sOVdHt86JO8hAb26VkzNncpOnD33OTp4mrh47iqZ0b8Qg+CApsLKzhqqfepGBEGudfO5UVpYqXW9DsColVAMvrd3LHsDP4rrKMF3dtpyAundNzVUAQQdARZzrnuNfT469ihMnCkT72vkPMQ/BLQS5b/xHFlkawQKAjSFSpgViXSFSilWmjc1ji6PXImhQ/uNdpXyy6cEHaqtXhCvi4b/tydrfWMi42lSemnI5Jo8SLaYY0YrWxtPkUMdTu0uMPqhEAgyoSn/07EPkUIkT4J6JRiYNm1rQ6vSGxCqC5y0t5s/O4XdH6Utvh6rftPu7YwThvQjqf7KqlrNmJTi3ywKnDmT8sgTs/2csXe+oRBLj7xKEDhZaNT0LjfuX/LYdg3Z9h8YthQ66emc3KA43UdbqJMmi4zbIGWpQgSRRkzlBtYUXnFL7ZX09ps5MPt1ejU4t4+3zJb3V6aXC4yRNq+UL7MBbBDQfegjQnTL3xx9/cxGvgwOfQUsJvAtfRIg1cFX3s2xIWDk8cIFbRU5KYHddbn3/bR3voKvqGt7R9sonsNRDwKR5ZkkTw23vwFn7BEH8Sd/pv4g9CNJKsZDe9ctkEFgxXSgvbu308+EURla3dnDI6mdsWDBlw/CaHN6xjnMMToMHuDglW3n5+YLIMvqDE6NQo4szakEF6306A9IhbfYWULk+Av/dkwt130jDmDY1n3eHe69HVkza+ThrLImknn2p/z1fMQzP0BC48aR4Zscp1XXbrTPbVdHL5GzsI9gmq/BJkx5lCpZgFaVGk2Aw0dA7MAmvu8vLC9k52B7IHXfwRBWiwe7j1wz3U9nROVAkCdy7MZ2J29HE76m0obeH693bh8UskR+kZk25jaKIl1Jlwyc7qsPG3LxjCr0/ID22fODKJ5fvqSYs2csPcgUaw/dFrVDx13hju/3x/qCNmXaeHZ9YoAmOD3cPtS/byzW2zQnOeu2gc722torjewZpDTTg8AU4ckcjisSk/ebwIESJEiPCP0z+r6hhO396QWAXQ5d066LjB8AZq+m3X/qJzmhh7KQ3ug/ikbszqBBZnXs1ZOQaW1d5Nu68cjWhgWvyvBsyrr68PZS85HA7sdjs2W7i/6D0zZnLzN8vxBAIMi4tjZkwsnVIXBwPloTG7Ow5Q0lnNgyu3sK+pEVusGvqEgqX2FgL68EWqkppyRlnSMRp/XPxJSEigqqoKV9DJpuBKZCQEAXRigOq2aI40JfKH7u+5Km4CzXYnaoMGKSAgqpXIwKw2Y1Yr8Zk74OGVsntwS+UgCIyQTyGXOSFjd3rM4LcfLuG6jd/jCgZISWwj366If1GaKB4a/hCxOmUxSvYXITseBdmLYL4VQT9vwPlXdjeEiYWV3fVhr3sD4WLjsRK7WSOzeHfdLmRBxjjEQVSSmpoOEbdTWQR0+DzQ8zVB0AcpdtdTXFzPK4e28trU84iPNtPSoXxfEH0g+UDoc+uqZRWnpWQxJCuVC2eOxarXQzx89eAV7Kyp5YHKj8LKO9sCQVJFLT5JuVYToidQ5+jC3SkAyo6DBgjqJYoO1pJX1HtPy75w+4U4nYmNjbu56/s1dHnU7GuycajtMl5cNAyLfiIGzeAG5XWdz1Dv+BupwFVJkyj2LaAgqoCJMRM51NFEYWvv700wWuK1e85lbIriHyXLMvkVSRzoqGdKfBZnZhQMeoy+zEzP5MqCcbxXtBerTsdfTziZ5w9s4tuaEgBW1h4m1WTjgXELADCqjTww/AHWN6+nqK2ZD0rbEQWB+8bNJdUc9RNH+/ckYroeIUKEX0yMSUuqzUBdzxdwq15NZuzPSzmfnhtHgkUX6jB25thfZgIYbdKy/NaZHG7sIilKT2JPydkzF4zj9gX5aNUiKTbDwIm+fl0OvQO7HqbaDHx352wqWrpJjzYStW0H9GkgWCsrZZGNDk/I18obUIKWY3rHyBQrV0zPoqT6dUWsOsae9wcIVpIks+ZQE96AxAkjEtGbYhXvq/YKnG/VQ8dAgSQgyeg1KgwaVVhZW6JVx10nDGVsuhLk/W1NKcv21RPFEOrlGFKEnq59Q08JGbqz5z1Uu14nDpipauOPvMX1/jtDx3l/WxULesSxWz8qDBmxlzR2kR1n4vQx4cJEqs1AXoI5JGZmxRrJ6rkv9tV08uSqw2Gf/SVTMkjt+ayWXDeNh748wNaKtjCxCmB4koUub2BQcXPVwUY+vn4qk/60JszHyaxT4fQGeUi+nrtnZ/Dg/BEghouvZp2aGXlxTMmJCfljARg0IpdOzeCzXbUkRel55oKxHGpwDLoyTI+we9PcXF5cpwTOI5ItOL1BvP4gcRYdN31QGDY+KMvkJ1nYUNrCde/uJs6s5bmLxlGQ1hugP7XqcOg6NNg9XDndxvVzev1IEi16Ovt4zI3PDBeL5+THM6dfGe/xKKzuYGt5GyNSrBz8/SIkWfElW7IjXBRrsHt4ZUM5r2+qJMqg4a4T8okz67h+Ti5PnjcGtz/4s83dI0SIECHCPx+jZjgCamSU56FJe3z/yf7Emk6nrfuznrkCsaZf5neTbBzFZTnv4fA3EK3NRKtSRKALsl/C7qvHqI5BrxpYYij1y57qvw0wLzuHjVdfS7PTSW5MDHXV1bQ6vYiISD0lViICS4tL2dfUCECn3YcYJ4Se3XNT8rAYU/m4ehMAiSorw7VJ2O32AYKV0+Fm56ZSLFFGJs4YgslkYujQoTS7GpDLes9PEKC2PYaApMIT9JMUrby/gFtD+fosUgqaGJ6ayBV5l4ay4X6z9xkSjT1CmyBziJXkyLOwWq2h/TY0NLChpgpXj3CUltgbo9j9dnZ27OSkpJN45/ttnJF3PVE6JT6SO2+F+O8QVOHG3AVRuehEDd4e382JMb1d8r6p28m6wA5SRrhoKNWhkjTcMXs6AJOGpPO3Xy3mleqltBjtBIHkGKgrTcTr1nJybj4rq0rxSxKCtve6BGSJHZ01PHXnGdz9+TPo4ry4is24v4lCd3YXQYIYRBOPjL+K8ScM9FpLjLZwojWf3x/VA71Z79mWdPLMI6l0HWF01BAuSD+f5Z9tQ+OR8esVZUvlklH1hM9DY+OYmJXKrqN1BOxaCoTh1GpqiNbqiDU08lbNC4wbLVBclobbq2N/mx45eCoP/HU1e0u+YWRuMn++43SiLEqsGpAc1Dv+Fjofg7yTy9J/F/o9i9Eb0Ygi/p57WK9SkxvfuzApCAKX5IZbTPwYq/eUUtPaycUjC3hw5lzUPXHsZzV7wsbVdXdyx5Yv2dxUyXBbIjfETiGqdSi3jlvEfaN0oXP5jyXiYRUhQoRfikYl8v61U/jr6sP4gxI3z8sjxvTzTJbjLTq+umUG3xY1EmPSsHjML+9aodeoGJNuG/DzrB/z0ZpyPRxaDl47aM0w7ZZBh724rowVBxrJijXx+OJbibfX4qvYxPruLP4WPJezxqUyNj1cHNCIAtfOykGjErl6RjZRRg0F86fAxs96B1kHZp3c8fFelu1TVrnGptv4+Pqp6NQ6SBjOjfNMPPBFEbJMmDh13ewcEq16ZufHhZVjZceZOH9Sb4eSb4uUgM2OmbO8f+Bs1SYunD2SzAU39J6APXz1NEVoDdu2e/yc8PQGjjQPFPcqByml06pFllw3lbc2VxKU4OoZWeg1Krq9Aa54a0dIYDFqVbx11aSwUrW8BDNp0eFC46gUK2eNS+XLvfUhcbQ/ufFmtpS1hYlVRq2K7349B5NejUWnpqSxi+oODxmxg6+gvn7FRG58v5DtlW3EGLWcMyGNPy5XXDEPNXbx5uajfLmnDqe3VyAUBaU7U6rNwC3z80iPMXLyqGSc3gATM6NRNxTSvuFlvjzkpI6z6CQ8SH97cwXbKpVyAac3wB0f72Vtn9JYVT/HWJUo4PQGuO2jPeysbGdIopn8RAvt3V4unpzxs8Wp/mwpb+WyN3aEygcfPWs0F0/JYEVRA58V1oRlEM4aEsdjK5QVvZYuLzd9UIgMaFRKNt78YYn/0DlEiBAhQoR/DkbtMPLiX6XF+SFqMZY02z0/e65VP4NhiZ/h9O7EqB2JVT/9Fx/foLZhUIfHZypBQ4zu+KVP8fHx1NcrsZBWqyUqamAWiCvQzddNr1HvrmaYbwynpl4AdXAWC/i6ez0IcEXm2ew43EfsCogUaNOZmJ1MptnGRXnjEQWBbCmaZmc7o3VpGETtgBLE7i4Pt1/6CnVVikh09mXTue7uk1GpVCRb0pgQPYPdHZsB6OyOo8urQyuquK1gBhMy0kgWDDT6XXRXmanZa+SUc2eQM1bJdO7wdVNsbySxTzgiCCIZaRlERfVeN7/fT5K+NybyB9SAklUkIjNKWE5T2V+xaTQhsUrBB8F66CdYZZgS+evYW1jXXEisNooz05Rs6b0dlTxa3BOrmmDajDT+NPJy0my9n8GcUTm82uUK6UaCAOeOzyJRncGH1buQrB5UXSrwCGDuVQtyrLHsUW0gbq6SAW8Z5cCydTxPzngASZAQgiJH69rp0LiItg6Mz7QqFZ/OvYE7d79Le6CNPEsSMToTn1Qri4C7WveQ7hnC3+/9lNRcEel6AZVZQioxIYkmJo3JYsHs4SyYO5y91Q2Y9VqGJyfQ0dHBt43fssapxHmiKDM0pw4/GpAFnt/wGdv2KYu8u4trePWTzdxzzULlvSOipJT1ES1RUWpv4fYtX9LgcjA9IYvD9hbUoshD40/Aohk8G/Kn+PuKrby8YhsAr67czvt3XURuUgwfvrqe9ooGhHEgC0rWvkGt4Yujit3H5qaj7P3hKHE/iMTEmHj5hSuIj7f+xNEi/G8SEawiRPhfIjvOxAs/o/PYYCRHGbhmZvY//Zz60uzw8MjXB2m0ezh/YjoXTh4Dt+yApoOQMHxQAenLPXWhLJmKlm4eEAVeu/zvaIETgX2SjEoU8PiDjM+whQyxb1+YHyrVOkbq3GvBfRgOfQ0xuXDaM2Gvd7p8IbEKYG9NJ0W1dib2eBRdNDmDcRk2Gjo9jMuwUdnYisVdT16eIkpNyooJE6xSbeEP+8xYI4ebugBoIoY9mVdx3yKlfa7D42f30Q4yExaSo3lR8bYCfjCdyJiEKA41dpEda2RPVedxFyrmD0sY9OdxZh33LFJW7iRJxhsI0uTwhGUDuXxBogfpIjc6LYpPd/eKaAuGJ1JY3UlRnX3A2HizlplD4nn4jBH8fX152GuZMUaSbQYkSea693bzXbFyne4/eRg3zBm4kmfUqnnn6t5OMA99Ge7xtbOyjQZ7uGB2zO7s5FFJpMco137UsQ6SndXwzhnE+Lu5Wg0FYgXn+h4Jm39MrDpGmzO8RfcDpwzn2nd24vAEGJtu48LJGTz//RHWligmoIXVnVw+LZM/LB414P38ElYeaAzzbvumqJ4x6VHc8tGe0M9TbHruO2kYOrWKr/b23rPHZvmDMh9sq44IVhEiRIjwb4DNMB+bYf4/NNesG4tZd5zGMP8kijqP8krZKgQEbhhyEiNjMjAajQQCAQwGAyrVwM65X9a9z97O7QA0tzQQr0tkds5J5JDDRfKZ0JO9kq/v4OvDJbS53RjUau6dNIep6elh+zp5yFRqamrwer2YzWZiY8N9Hgu3lYXEKoCvP97BdXf3duK7LPNmpsXOR0IiWZfLwZwmEnRGcmKUhaOCxAScu3vT8xP7iAVmtZ6AlEhlVzvZljYkWWBm/DUhsaq2u5Mj9haS9TomxyVwWfYQ1jXVY3COJz72CJ3+dq5NlEmRV4MZTs+HZr+eBI2SUtQWsBGn7s2e6stQawZDrYpvpl8KEJQlKp3hPpStgc4wseoY+ZZ0mr1K3CIgcO6QiVy77mvavW5Fv4kKIlZrkaUgmclRLM4eydnZo/lj8Zdh+5m+OAGdRkNbZzfXP7KEuqZOjHoNT95zFuNHpA84bpY1hqXz7ghtX7zlqdD/ZWT2tpYjBSXU50oQ35NhNa4Lb6uWM8+eiKanC/OkbMUbzG63U1dXRzAQ3nhHVMkQVDLeKqP3Ar3+oh2OXisTlWgm3fYANZ2PAhIJ5iswakdwz7o3KbUrwtyGxgpemnE2i9IH/xx+LqsKe438Pf4AGw5UcHDdEd5/eR0AafsFhp6Xw3VnzOfr6kNhc491c2xv72b9xhLOO+f43Q7/E4iUBEaIEOE/ml1H23lpfTlalcjdi4aSl6B4BNy2ZA/bKpQVksLqTrLjTEzJSQJL0nH3VdXm6rfdTZPDQ7RRi1YthrJe6jrd3Do/D0mGFJuB4cmDrFyIIpz6Vzj1rzg8fu79dD9FdaXMzIvjj2eOwqBVYdSqcPmUh6YgMCBLbViSlWFJVuioYtxXpyr+U6YEuPwrrpw+jPIWJxtLWxmWZOG3pw5HkuRQ15c/nzUaSZYpa3Yyb1gCD5+utO9t7/Zx1kubqWpzIQjw3MIPOd18GOKGcFPufI5ZcH62u5a7P9036HXKjDGExJmSRgf7a+yKx1JSbxbR2pImbv9oL05fgEumZIYZlufEmciIGbiadtnUTFy+IFvL2xiTbuPW+XmDmrFHGTR8+KupODwBGu2eAd5pk7MV0W97ZTvbi8uxINKFkSdXHebqGdlo1UpKdavTy8oDjUQbtZwyOinUaWd8po33tlWF9lfR2o1GJeIPhgc4AEv31PHb0/oZ+DfsD4mAAOOFI2hFGZ8UnjWVZNWHuiNePi2T5i4Pf1x+iCa7h/MnpbPtgQW0OX2k2AyoRIEW5y/rMHg8tle08d62KmxGDQmW8C6OGTEmSpu6wkSs+k4Pd3y8lxvn5JIZaxzwewID790IESJEiPB/m4+K9rPiyBEybTbumzkLs1ZLl9/N3XvewhlQnn13Fb7J57N+g0mv/9F9tfnChZUmTyMtHgexOjOi0Fvun2Cs4MsLR1FpTyMnOo4Uy8ASRLVaTXa2smh6xNHIFVteodPv4uKsaVyYNY3oWHPYeFtMePa+IAgMsSjPfYfDgbWjG7fspKKzi+zsbO65/gT+/MJKaurbmTstn0Wzh4fmakQVz068jKeKv6Go3cmVOfOYlaB0idvRUsU1G5fgDvoxa3S8Pvkcbk+ewQMmE/o+10fqvBf6OEZUeKwsbc9GJ0qIhvO4qqcr5Pa2Ulq9DqbHDSNa2/ue3q5cyQdHv0Mjqrki+2T0ogZPT6ngtLjBDejvHnYh0RUWmjztLEicwChrDnZfuG2FIMIYIZ2/L1hMeVc7ja4ucs25VHT3indDrMri7uer91DXpCz6ujx+Xv9sCy/97oLQuEMdTexsqWFEdCIT43uFrFFRmVR1N6NVBREFmUPaCrqf06Ex+wgzfTAFWLmpmJkTwhcpHU4H2/3baZVaiRPiaJVbMagMtHv7ZOnrdGg1Knz+IGqVyBnzC9jTWsezRRsRBLiz4FTGpp6NLPvQqpXvFK2e8KqDFs/AKoSfw+cb9rP9UBVD0xNIibVS0dQeei0tLoriTUrTKlmQ0SxyU5G7j9+XlHBx2mnoVGrFe0wGc2lvvGmL+vnm/P+2REoCI0SI8J9KS5eXK9/aibPnQbO/tpON985DrRLDTOEBjjQ7mZLTs4rWUQXLboHOGhhzIcy9H4ATRiTy0vqyUAlUp9vPlEe/J96i492rJzM82coXe2q5+9P9BCWZjBgjX9z00ynzf1lRwsqDSonex7tqyIwzctPcPF64eBy/WVqExy9x94n55MSbB9/B5r8pYhVAdzNsfBL1eW/x2NmKWePW8jZOeGYjdrePy6dl8dBpI4i36Hj9iknY3X6+2lvHkh3VnDU+leX760OCgyzD47skTr/v+tChgpLMhzuqKWlwhAlq9Ihq4zOiefJc5bg/HGnh6rd34g8qXQhFUWBcuo0zx6Xw5KrDdPV8Lu9vq+KVyyZwsM6ODFw+TSkV7I8gCNwwJ5cb5uQSCErc+ck+tlX09ZZScfO8XM4Yk8IDXxxgU5lSwnjXCfk8ff4YvituIi/BzC3zlYAoc9/T7Ne/QFAWeDRwCe9yKl1eP7FqHR3dPha/sDlUanjR5AweO1vxIDhrXBpFtQ7e3FwJPWbyx+OYh9oxnN4AD20I8KisxSAoWVONpmHs//XJvLaxItQl8ZRRSWjVIrIM50xIY3Z+PBe9uo2tPe93Z1U7kiTj8gUYnRbFhMwYzpuQzvJ9DfiCEmpRCCsBbe7yYNVrBr2uzQ4PjQ4P+YkWGu0eLn9zR+gen5Bh48rpWWw80sKIZCu/OWUYdpcfk1ZFd5/PXpbhpfXlfH3LDIobHOg1Kr4orGVrRTujU6O496T/2UpihAgRIkT47+H7igoe/H4NAJuqq3D6vDxz0im0eO0hsQqgK+CmzevApFayk5xOJw0Nirl4YmJiyNdpnG0aZcdKuBBZcrSEZ0v+zKioDJ4efy0mtY7Ktvtp7V6izDUsItn89588z3sKP6LapTx3nyj+hpG2NEaPz+KSG+bxxftbsEYZuffRc487v7GxEbnHxNTtdtPZ2Ul8bAzPPqx0ed7T9gmvHDkFlaBhftJd5FnnUhCdzrszbqCisY3Nh6pY31bO3NG5vFO6E3dQEY6cfi+f1R/kL5NODx3L7nPxcdU2MlXxnNBHg9hwOIMNcgbz8kZzW7Zyrq+Vrebtyu8xqb18UutEJ6rI00wlWpXHkpbVAHglP29VfsvfJtzMhuaDxOksnJM+eExrUhu4LV/Zd3N7F1c/+AFai4A7R3nvqfoo7jhxLmMykjj923docHWhV6l5Ze6ZnJFioN5dzxjbGCZET0CSJLq6HH32LqM1uQlIXtSijp3N1Vy+/iN8UhABeGbaYk7PVBZd7xp2JnXuBkqdSnxW62lEtIgEe9zMAGSPQOCogfhZ4WJlVX07j257A19G74LkJbGXMCdrDk8c+jv7HQfRiVpyg1MxnqwhVWfhnEmjiE80M+frl3D4lfv2QHsjf5s1h66AnfHRahL0cVycN56nizYAkKA3szBVaYITlIM4/A6sGisqYWB81uBuICAHSDems3xrMY9+8D0A3xeWcfHCcQgjBWpb7ZwwdggnjR+KscXH6q8KoSAI45QYzR30srxxLV+deCM7W2qweXR8+v1WGnWdLJg3ggXzRx73/v1PIZJhFSFChP9Yqtq6Q2IVQL3dQ7vLR4JFz/xhCXyySykvM2hUTMvtk/L95U1QpZhusv4xSCqAYacwIsXKJ9dP49k1pdR2uLG17OJu9QZa3FE8842GV6+dwwtry0LZJ9XtLr7YU8e1swZ2YatoceIJBDFo1NS0D94Zcf6wRLY/8ONlVJIkc7DeQZhtqhCeqfPr9zfT6lYehG9sqmTe0AQK0qP4Zn8Dz39/hHq78pD9pqiBs8eHe4b176b4yLKDoewirVrgjDEp1Ha4yIw1cfO8XPISegOAj3fW4A8q10LuEbt2VXWwqyq83A3g26IGRqZYuWRKJp8X1vLprloSrXr+dOYokqIGrqz+7fsjYSWTmbFG3r9mCukxRjYdaQ2JVQDPfn+Ekj+exNnj+7SDbisnZf8LAKgEmQfUH/C5dxaT/rSGB04ZTpJVH+aL9emumpBgBZAdf3w/tBEpVuo73KRGG3jmgvDSiT9+XcwXRzXUCvdzhXo1DtnI98ZruepoB6/2dDYcmWLl2wONoTlJNj2z8+NDJZz0CET3L92PJCt+WS9cPJ5TRiez/LaZ7K3pZHRqFMOTrQSCEje8v5s1h5oxaVW8eMl45g7tLddcU9zEzR8W4g1I5Cea+dWsnLBujXtr7Xx24/RQdhmAVa/hkxum8c6Wo6HfoWPoNCoumKSkyi/+hQ0TIkSIECHC/w2KW5rDtg82K9uphlgyTfFUdSvlU9mmRJINSpZ0MBikuro6ZLpeU1PD0KFDUavVzIw/AdlrZEPZbg7K7TQGlOf3AXs1X9Zu47z04SGxCqDTvQq3/xBGbXgGdEAK0OhpxBtQYVCZaPB0hr3e4O5ktC2dy26cz2U3/nhZpTvYRWHwE1xCB2nyBFII7/jW5qlic4simgVlH981/IVM81TafZ1sqd3F858eoK1B8Te67fQZmKPCM5Utmt7YyC8F+dX2NyjrUjLNdiScxlVRRrbsMGLrmsJnl83AbOod/2XtNkAm2eRAFGT8cpBDvo3sPXyUmD6Pbr8UYG1jCTmWZE5MGM1f31vPgfIGxuSncMeFc1Crw0UWXyDAw++spLihGctRDdpGidnT8/jzqadi0mh5onADDS4llvEEA7x8YAdLFl0Uto/Ozk5mFiSzo6iW2tZOFl62i/jMVt4qW8opaX/k0/IafJIixsjAkrK9IcFKp9KQaLBS2mdNWhDAF1QjyRI5TRk07ZaYNTSTa8+ZFnbcOx9fivbEJvpGnA6tg1cLC3ljmxeNJptxtnTeLlFiYAGYVpBFwCWFxCoAvaGR58peBeCTmq95rOA33DxyBmNjU2h0dzE7KYd4g5k2bxtPHH6CZm8zCboE7h16b6izI8BntZ/xTcM3AEyPnU5LRfh3ifK6Nl769TlhP5u9aDSiSmR55RZ2Uxz6uVfyMyQqniFRivB7yuv/+SLVfzMRwSpChP9DDEm0hHWdG5ZkIc6kPPwfPWs0I5KtNDq8nD4mmdy+2Uud4d3P6OxdbXlq9WF+ONJKnlDL+9rH0AnKateu6sOwdjEm3ZywqaZBuqLd/ek+PuvjxZTZx+xbABaNPL5Itaa4iVd/qMCqV/PgqSP4ck8tn1XMZIl2PeliC93aOEyz7+2dcHgFdrcf6A0qmhwezn7p4IAssx+OtPLUeWM4fUwKy/fXE2fWhYk0AGsO9abd+wIy4zJsPHfRuAHn6Q9KA3ydjodWLfLV3nq+2lvPp7tqQybuRXV2nF4/S64LDyr+tLyY1zdVhv3smHCnUYnoNOHd/lSCgKqfiEfA22+MjIYAkgyPfnuIW+cP3q74GLOHxGHRqUNZYsfIiTOx5LqpWPsJfcc4JjrtlIex069kHV2Tlc3vvjoQ2tfBekfYnG09HQqn5MSwoqhXyDpWlSfJsLSwllNGJ5OfaCE/sVc0/KaogTWHlC8C3b4gv/vqIBvv7RWsnlp9OCRQlTY5qWztRq8RQx0IJ2RG09zl5YGlRdR2uDlrfCo3zMllZEoUT5w7Bq1a5P1tyu/LGWNSwo4dIUKECBEiDMa09HSe2yYQ7Mk+mpmhmK7rVBpenHgDn9dsQUTgnPTpaEQljgoGg2EdAmVZJhAIoFar6XC6+eNzB2h1BNHNDSD2WYOsb2qg25bbEwf1bY4SvvDUHejm8ZLHqXHXEJQEDjamkGOzIWiOoBaCeAJxTIoZuAB5jK/rv2a/fT+phlQuSLuQT6seo07eCwI0UUK0LgmbrVcga2wJjzWDso+q7jKeL3sWr+RlyAkg/JBFa2UM3+wq4aXbz+RgRyMl9mbGxKRy0/AZobkN7o6QWAXwRbORi4beyvmXDIwn5WArtyTvxxVwsNMXTVPA2Oc1EZdTh9GsxEj+gJa3K34AYKl/LwfWKguOh6uaibYYuWbx1NBcbyDA5e98xj5HA2SL6FskDC0i2kaR3cU1TBqWga5fJ7p+kZlyDrKMyaDhwaunUeZbT71ZWYD0Sk5+aHqRo02zw8a3dISX182OH8MPLb2WFUFJiQnnJYzj9wsvhksGHtPj9VPfbCep0YA+oVd8ilYlc9e2TYCAz69me0sDWlFAkARkYMfRWm7Jnkqi3kKTR4nv4ky9sXV30MWujv2cmryAGUnh3rzL6pfR7FXis2ZvM8vql3FV9lUAOAPOkFgFsKVtCyfkDYENvfPH5qVQWF7L01/+gCTL3HLqDKYPz2TmwpFMCOZx154XOOKsRUTgyuyT+a8mUhIYIUKE/1SiDBo+vWEab285ilYtcv3s3JCHk1olcuWM4xi7jz4XNj2t/F8XBUNOBMDjD/LDEeXBOU4sC4lVAGOFI7DxCf64aDLXdOpodXpZODyBc/pm9QBFtfYwsYp+3lgysK/Gzpz8gablla3d3PjB7lDW0s6jHT1iVDwLfU+SKrSSkpDL+wl9yq8aD/Ar1SGeCyqrMPnqZvRa1QCxCsCqV2Mzanj+onH89bwxIS+nvgxJtNBg732YH/ME688fvi5md1XnoK8d43enjQBk/rC81wyyf8fB8pbwQMTlCwwQqwDqO93c8P5uTFoVk7KjQ1366Fldc3j82PoauSeOgIILYP/HALwZOIkWlFVcSWaA6btBq+KZ75TMujPGpjAnP54vbp7BygMNJFr12AwaHJ4AC4cnHlesoseMfm9N73U5c2wK9500jG/3Nxx3zug0xQ9sZm5cmGDVl+Qow6A/9wWkH93WqMI/4wSLjvevmcKH26uJMmq4fcEQbvqgkC09otlfVpQwJMHMguFKEPynM0dz4aQMApLMmLSBRqwRIkSIECFCfyampPLmmWezuryMTJuNq8b2LnxFa81cm3vigDkajQaj0YjLpcRMer0erVZ5Vh+obKC1x/zaf8iMdmoHghoSVBZm6HOpr7OTkf57ajp/j0yQtKi70WvCOxNubNlIjVuxV1CJMtkxrQhCCyaNUr6vUzfR4qsjWpc/4Nw2tmxkad1SAMqcZaw7XEFW4kH0x0IJQcZlbUcUe5+5en8yNimPTrEMgAzNLPZ27scrKWKRIEBCfiutlTGkxFhJMlpZvug6vMHAAOEnTmfBqjHg8CsLhWa1jgT9QP9UWZaQO65gUdQRAOYF6nmocRwuWY29y4DDacTjiuKJsxeyubWUT6oKQ3OPyPVAb6xxtKE9bN+by6vYV9sby3hiBYwege+LK/i+uILUcRqSx2gwG9w43XqQBLocfvpjs9lob2/H6/ViMobHKJLsJ1OOpdBeh2wKInhE0qw2fr/3W4KyzDVDpjE3YRwWtZFDjiryzKl0+rzoVVpmJ4wYcKzQZ6HTMH5EOnvWSQQ9KsyJAa6ccjq5xuEgbu4RRAbKa6NSEtGp1IzWpdPYfhgAr0eDTtMrjMZpowfMAwjIgeNui4gICMh91JU5BUMwXxHPtkNVDEtP4KzZozj1z6/iCrjxuzT8+o1lrHj4GmIsRgwqHc+Ou43SrhpsWgtpxn+sU/R/DBHBKkKECP/JZMaaQobiYTgaQFSDeZA/4gsfhuQxii/U0FMgVjFl1GtUpNoM1HW6OShl4ZdVaATloaQWFCFgjL6ZnQ9ejNsfxKjt+ZMjSbDmYShdRYYllyjOxM5x/KhgQIngMSpanCGxCugRqxS8aKmQUxDc/USm7NncqX2M2cEimiQbpuELcPd75qoERYj6/Rkj0alVBCWZL/fU0e7ycfqYFFJtvQHKX88bwyPLDlLX6WZufhx6jQqPPzjAG2lrH28pgMumZpAZa+LjnTV0uHycPzGdq2dm02j38JcVJfh63pfNoMEXCOLqyfDpn22mFkW0ajFMeBmaaOZwj2F7ty/I+sOtYXO8AYkGuydcsAI4+1WYdjOIag5s8ENhHQDXzszm7AlpvLm5kup2JfjLijXxt++VAO/LvXV8dsM0xmVEc8v8IYN+VsfjtgVDSIrSc6Spi3lDE5ieF8cnO2to6uqTTq4RuXRqJuXNToYkWrjzBCU4TrGFi1JWvRq9RsWYdBv3nDS4EeqpBcl8tWU/k5o/QxQge+4dYa8/dNqIULfBSVnRXDApA4NWFepGWdbsZHtFeFBa2RouIoa6H0aIECFChAg/k1mZmczKDBeNZFnG7/ejUqkGdAMUBIGsrCw6OpQsH5vNFhKA0uNtqEWRgCQhNekwbU7ntrNHkqK2oRM1yLJMtP584tMvACREQcm2DwQC1NfX4/V66ZK7ws8F0GnCBZVWbyv5loGCVZ27LmzbSRutHhNpWmWBKigLlHUFmdNnLdJqiaLAdRPtcgken4DWX4BdUxK2H3XQwNShGTx0wUIAOpxulu0oRqdWcebUUeh74kyjWsfzky7n+cOrkWWJG3LTUcnlQL9OwVIbBI6ENm1qH3flnMl3DVreK64j2Szy8Kx5zEocglciTLDKMMZyhN74dM748Ex0ky48xjLqtAS1AUSdH2L8tOU10tYNUTYQJXC0mGkIDFw8ValU5Obm4vF4yBRSaGsspN1biShomBJ/NaOnDGHl+0dwdwbQyyJlyXVsrlA+u/UNpXx7wk1MiBnKhJjB46Lj8eQ9Z/LJyj243F4WzyogNdHGfTuWoYrzIMsgd2nIdEYzf1wetQ4H8/JzWDRCiQEzLDbkcuWzqDyayLRR3eh1AWbFTWFK7OAd009OOpn9nftxBp2YRBMnJZ7Ue+3URi5Iv4CPaz5GRmZR4iJSDamkzkjljBnKd5oVVevJPm0vokqms9pKxcZMWhzdxFiUjDmtSsMo2/EzAiP8+xIRrCJE+DdBlmWK6uyIgvC/8oV3d1UHf1lxiKAk80LsZ6QcelNJRl7wO5h1Jy+uK+PtLUeJMWr56/ljGDXyzEH389ZVk/jD18U4vTb257/IhENPQnu58qIlBYacgCAIvWIVQOE7sOU5AKJaD/N2UpCzGq8IvZwVZ+JojwigEgVOG5My6LHHpNuINWlp6/Yd930OyHjKmAKXLWVY0QoeOjiVQ0VaxAOFnDwqie2V7Vj1ap44d0yocx7APZ/uY+keJfh6/YdKvr19ZqhbXLxFx4uXjOfl9WU8vvIwz35fRopNz5o752DUqgkEJdQqkYLUqLAsrrlDE2h0eDhrfCozcmMJSEq2VHOXB4NWjc/tx2bQ8PoVE7HoNXyzv55Ys469NZ0s+Ot6pubEMi03li/31DMpK5qdle34JZmb5uby1d569Hi5Vf0FqUIrXwRmsEHuXa3NjTeRHTfQc8oflLj/B1h/uJ6ceBP3LspneHIU84YlcKDOTmOfTLLq9l6RJijJ7C6pHNB9cDBqO1zc+tEeypudnDgyib+cPZrzJ/aaoUuSzENfHaBP0z08fomv9tbzxhUTGZpkQdfjETFvWAK3zMtjyc5qEix6nrlgbFjnxcEwihLvir9HVCsrf+wugkmboMf7YnJ2DNsfWEiHy0eSVY8oCuyt6aTN6WVqTizPrikNlWwAqEWBuUP/y1fqIkSIEOH/MH7JQ4vnCGZ1PFbt8Tsn/7M40PE1BzuXY1THkuM7C9ltQBRFMjIy0Bh0/OngJxS2lzPMmsrDoy8iNjZ2wD6ykmJ49JqTefe73ZgMWq5dOAaD4AuVEJrNZjQaTZgfI0BDQwMOh1KGnyvnkqZLo9ZbSyAoUtkWx6w0Aw5ZyYCyqq2MsA6epVMQVcB3Td+FMmI6WqzUOaPoph69yk+dK5orstPD5sTFxaFSqeis1fDw8vV0eVcSZdRw3uJx1PpLSTWkce3JtxClsQHg8vq58tmPOdqsCHZr9pXx+q29hu+jbem8OuUadh39FZL7zxS7QZTOZkLW0z3G7zKI0aBKg2BPpr9gwaqZjKqzkRuHpzNpaByIMrIs09ou4eswojJ6ybUm8MLMyziY0ERRWQNpuQZWCd/x8Y4vOD11JtVNInuaGxg1NJEDhxsxarX88cx5PFP6HkKUFykg4EOFJCsCo1YfQEBgQfbggopfaqSq63Y8/grGGGfSbLibodYRpBizeO/oXpxGRUj0aYI0eXvjsyZPF1VdbYyMGTyO7sumxkoe2PEt7qCf20fN4tIhE7jyzCmh13e1VPP50f3KZRJAMPtxr3XQprVz54UzGRrTGwvdPnk6VfZOdjfUMz45l6cnnoxFq/vR48er4rlCewXtUjvRQjRChwB9QtVFSYuYETcDSZawahRP0h0l1ahVIpOGprOifSmiqmexN8PB0NEyWQk/HZf+NxIxXY8QIcK/hDs+3stXexXT7MunZfKHxeGrQL6ARHmLkwSLjljzj//R/ym6vQGufnsndrefXKGOlOY3e16R4fs/sCPubJ5cpXyhb+nycsuHhay/Z96g+8pPtPD+tcceaDPghIvg8EpwNrFWHs+mdS1oxDaSow3MzY8nK84E7RVh+xhn7mDTffNw+QKIgkBWrImdRzsoqutkYlYM448jhMSZdXx+43SW7KzBoldT3+nmg+29HgiZsUZ+c/LwgRNz5rKyI49DW5WafkmGXVUdFD50wqDHWd6nPK3V6WVbRTtn9BPRnu7pZgdQ3+nhka8PsqWsjbpONyeNTOIv54wmyqihqs1FXryJ3yzdT3NXuNCWE2fCqFWFMsU63X5Km5xcPCWDoUlD+cPrH/NFmSLAlbd08+H26lAm77yh8bx86QQO1Nl5cV05z2pe4wxxK+ulMVygWk9rwEojsSxQFXLryAz0mrlhxy5t6uLS17eH/M3aun3sPNqBWhR47qJxlDQ4QllfALLUpxsiEqOLn4ITPxz0+h3DH5S44JWt1HUqwtdnu2vJijVy49w8VD2lqTIgyQOfni1dXs54YTOjUq0suW4a5h4vtLsXDeXuRb9g1bCzCrH1cO922xHoqISE3vvEoFVh0CrZWy+tL+OJlcr4IQlmsmLD2x2fNCopzFg/QoQIESL89+AJdvF51W10+KoQUXFCygMMsYbHQ66Ai1ZfK4m6RHSq/1l8Vu/az/qmZ5QN7xE65CbG82skSaKxsZENQiVrmxTRYFtbKX8/soJ7R5wz6L4WTshn4YTe7CdJkrDb7fjkADvdh1lXuQlDg5kYRzYzZg3FZNbj9fb6WeoEHTfG34jKpqLLK6MdpSPNFMX29u04/A4mRk/EprUNeuyRUSO5K/8uiuxFxGuTeWVfPQcbajislxG1ElNj8zkjbXLYHEEQiImJ4du1O+jyKvGR3eWn4eBwnj7/zgHHOFzXHBKrAHYeqaGty0Wspfc53eIoQha/670G4lKcHaMx+v4Gsh/BcidC9FvIzmdB9rGsZSp/Wvc+HoeEyeDF2mOIPi12NB/90ElA0kGHjj11HuwTfMwcm8OMMdlcs/UxanyKMf7zRz6jpjoOj0fJsLp/8Rx+VTCRj6rXIEQp11dUy2ilAD5JjSSLpIrRzE3N5v6J4R6lAEcc66lpvwOLqGSnBbxfsbqlipfKR/O38bezrLTXRsLvl4kStLhl5fpZVTp0rgDEDNhtGPXOdn694228kky3V8cju1cx3JDAhLReUTEgSwPm2fMkvlSX8eVnZVw8fAyPzlJKV81aLa+eOvhC9/FwOp3o0ZMiKvF1V1fXgDFmtRIDByWJO176ii0HjwJw2tThSAXh53fLqdPQaf6PSh2RksAIESL8sylt6gqJVQDvbq3i5nl5JFqVrA+Hx88Fr2zjUIMDvUbk5UsnMG/oQE+nn0ub0xcSRVT0fwDJNDrCDbgbHR5+EUNP4rFvD/HKxnBhyqBR8dmN0xg57DTY9jJIPanlI88kLTpcCJiWGxveqfA4ZMWZuP/kXo+qa2ZmIwgCiVZdeFZXPwz9SvaM2oHtc4+REWsMZUcJAmTEGAeMCUrhf/G/3d8Y6si44kAjs4bE8/DpI/l4ZzX3fV4EQJrQQoFQTomcQYWcQkVrN3Hm8BTy7mMm5nW7qaooBXpTqfsesajOgU4thjzFJoql3O6/ma8lpeVyMi10YeST4Hy2bWjiswktJMT3rIZ11vC3D9fT3BU9wPIzIMnc/ek+4vqJpJPjA6Q3rKZWjmexajNTHIX8FKc/vykkVh3jqdWlvL6pkvnDErh9wRAyY03cd9Iw/vTNoUH3caDOwbK99Vw8JYNPdtaw5lAT+YkWblswZFCPsQFYksAQDW4lyO0STNy+tJbfnJXGkEEM0l9eXx76/5FmJ2eOS2FXVQcdLj/JUXruXTRswJwIESJEiPDfwWH7d3T4lEYzEkG2t74dJlhVdlfy18N/pTvYTZw2jvuH3R/W2eyX0uGrCdt20ds9UJZlWn3hTUhavOHbP4YoilijrPx673O4gnsxqX1gBHuJlU+uH8fzr11NVFQUHo/ynBYEAZvVhlFvJLFPq7hpsQNFlcEYGTWSkVFKudbsq4JUtLYTYzRgMWrRq7THnafvJzIcL5ZLslnQqFT4g8oCms2kx2oIj1XancHwSZKAzvMkCEpsJXc9gaBbgGh7hps3f8qWzn0IVtBZZazG3nK/rW1FqLQJBDy9593tV0Sh1tZWmnzh3Z41mkBIsCpua8YV8LO3qT5sjCiCXgxg8too2SNwWK6itf0b3rz6IkRBQJZlOl1NfFf/GCP04dYYUWoPnX4nNy15jXZ7TJ9v9AJn2wqoDjQRlCXOiR2GOjBQaOqL3efkmq2PY7Mq78fh8tPqsHDNM0tIjY1l4cR8rp87hcnxmSxMyWdNfSnIYDispiutN2b88NA+riuYRIrJwktrt1PR3M684TmcNeHndeDT65WbTJJkPtxeysH6DkZlHeXB8+dj7ve5lta2hMQqgOXbDvGn+Yv5vGkJEhLDLMOYnjh5wDEi/GcSEawiRPj/iMsXwKhVo+v3RVsUws2fP91Vy6EGJSjx+CWeWHn4fyRYpdj0jEq1cqDOQamczreaEzjF37MCNesuZo3KJnVdHXWdil/RBRPTf3yHg/B5Ye2An7n9Qb7aW8/IU6bANaugbC0kDIPhp4fGPLLsIB/tqCbBquOFi8YzJr139a62w0VJQxfeQBCbUcvUnNhQZs4xcuKP74XVl5NGJXHq6GS+KWrAolfz6Fmj8QclXt1YQWVrNyeNTGLhCMUv6u+XjueBLw7Q0e3jyhlZjE0fuKI4a0g8G0pbQtvOft3yHB5FnHt7s/KAHSVUsET7J8yCB6+s5lr/3fwgFTBrSDzL9tUTlGTSYwycOa6nn3JnNaeqtvG9pAhWAhKiqAoJZVOyo3noqwOhDnUbgqNDYhVAA72p2tVyIh/tbuD2k+Jh+6uw8j5elCUmqBfxh8DlPaKVzFihjCFiHct9U6luD6ISFfP10alRPLYonvh3bgGvXdnpkFN+9HovLaylpHHgahlAp8vP0sI6NhxuIcqoweuX+M0pwxidEsXBegevbCyn1dmbjaZRCaw80MC9nyurzKuLm3B6Azxyxs8IinQWuORznCseZn9NO0/5z6PwqI+Kd3cNmkVo1Wvo8vR+liOSo1h/zzxq2l1kx5kG7XoZIUKECBH+cwlIQYKyhE6lQS2GCytqIXx7Wf0yuoNKCVarr5XVTau5KOOif/jYacZxaEUTPknZZ5I4DoKKeJSYmMii4HhW1O/GLwcRETglZeIv2n+Nu5lKZzk5lt5natR4B6WfN1C0r5rJ0/LQarV4vV4sFgsGg5Jt7PC7eHDf+xR1HmVkVAaPjrmMKG1vvVZxdRN1nQ4kq0SqJYpRseGlkxqViqGJP698/qZ5U9ldVUd5czs58THcNH8adr+d5fXL8ct+Tkw8kRRDCskxVh6/8hReXrEVrVrFfefMRaMOX3zMjh/F8yvnMbNgHcgC32yZyoT5u/uMkEHuwun38n3jIYyG0E+RZWWR8hgn5eTzVbESw52QncuIOCUO9/v9jNVls8OreGFp0OJy6ZS9CDAxMYULln5MaUczqTlqtLrw+LBLZQdZMYTfVtvEnpp6xqenUFNTQ4OjFEntpzlgIVureKF6JTVFTiU2bG/14N3vJG6MDkO8jvnZudxaMJ662t4Y3Gz+8bj46cOfEND03g8Wg4eOWiteg0ily85rG3dS6N5PMKEFi87IyzNPR+swclDfxBNNW8P2pVGpeOLbjXy4TalgWFNchtWgZ8GI3J/41MFkMpGamsp7a3exokiJZavbSjDoNPzuwoXhY/U6BEH5jOhpHDU7fjZTkybQHegm1ZCKKPyMRcz/UgRZRhikWuF4Y//diUTaESL8f6C8xckVb+6gtsPNlOwY3rxyEncsHMKza44gCvDbU0cQY+oNivppMmHb7249yvaKdsakR3HtzJxQ178fQ60S+eDaqXywvQpJkpk25UNwVSqm67G5RAPLbpnBd8VNRJu0LBr5yz0bkqMMYSLDMeKPZeqkTlD+9WFNcRNvb1GCgZp2N3d9uo81d84BYNfRdi57Ywduf+9q2byh8bxxxaRB3/O6kmYeX1mCIAg8eMpwZg6JC3tdJQq8eMl4bmvs4sV1R3hr81He2XKU1cVKG+TPC2v54NopTM+NIy/BwifX//iK4ptXTuLZNaU8v7ZswGtJVj1njlWCiwSrnkONXVysWotZUFYxdUKAy1Wr8WbO5Y+LRxFl0FBY3cHc/HhiTVq6PH42dI8gziDyDn+hSM4mLsaGOOtuHl5WjNsfpLC6k6Y+HlN/DFyGVgjik48Fb3JY9pTOYFKe9N89BD1p3lerV7EiOIVD2lHcp/6Iy4JfAHCJuIaz/H8gKIm0On1Y9BriU7IV0XHvh2CMgSk3HvfaBIISD35R9KPXj54yxGN+ZE+sPMz3d85hel4cw5It3Ph+IU5vgFlD4lg8NpW/fnc4bO6xToMef5CX1pdT3+nmjDEpzM4fJEBOm8Dm6a9z/Xu9QWt1uwtJkgfcS389fww3f1BIh8vHxVMymDdMCVCjIsbqESJEiPBfx7qmIv504GO8UoALMmZy05ATKevaSE33LnSihdmJt4WNF/plJR/7kuyX3OxofRenv5l86wKyLdP5OURpUzg383mOONZjUscwzHoyfl8AjUaDWq1mLFbemHIrRfYq8i2pjIj6ZQuKNo0FAU2YGCP5BSSvSEysImxERQ18vr1V8T2FHUrG8d7OSl6v+I67hiklX++s3c1fl23AOcyPZFTiiQfGz+O6UVMHPYf3jq7mu8bdJOpt3D3sAhL14fVqCVYzy269nMMdOyjrXsa+rr+xqbqTGreSQV7YUcijox/FrDazYEweC8bkDXocAK1GzdXzXuKPS5bxw6EqfH4N42KdLB7TE0NoZ4B6BHpZQIcWWfb1XBcBj9uA0ehBRub89Hmcm7YQl+pb2rzdnDN8OIIg0ORp5WCwnOHaZCr8TfhkP+clz2Wvzs/Smr1IyHywfwel7d2AipqyRCy2bhJSe7sjS4FwYUWrVuFyuXA4HBhJwCbl0Rwowy1pidfGsawhj2Y/BBu0+IvMiAGwHpJ45qRppKSkEG2zoRJFuru7MRgM2GyDl20CHLRXsqUtPD6TZTAdFvEalPPSWL00RlWDF1q8nbxbvYz3pj7EnGFDkApV/HXXJmTgjgnTSTVb2V8T3r15f00DC0bk0tDu4M01O5FkmSvnTyQ9fuB5RUdH45LVCCoJUSUR9KmpaR3YYTsjwcavz5nNc19sQq0SeeDiBT1ZWDpitD9R//h/gUhJYIQIEf6n/PmbQ9R2KNlL2yvbeWtzJXcszOeamdmIgjAga+P8iel8tbeevTWdmHVqHjxV8dv5YHsVv/vqIADfFDUQlODGuT+9igEQZdBw09w+D3lTuA9QrFnHhZMz/uH3+OyFY7nhvd2UNzuRAK1K5OTRSZwxNoXl++tJsupDndeO0d7PPL2jZ7uk0cGtH+0JE6sA1h1uYcORlgHZZm1OL9e9tyvUQfD693ax7YEFWPSa3kE90dotHxZy5Fi5H+Ev76hsZ3puuNDVH6c3wJMrS6hqdzFvaEJYxz61KPD4OQXMG5YQEiD/dOYoxT+sPXzFa1ZBPgvPncrLG8pDot3+WjsOj5/NZW0953gDI4VKhgo1/LV5JkM3Hw1dkwZ7eKmdBz13Lsznrc2V+IMyWbFGihscSDKMTo3i0qk9nYiE8NXI+XlW3M3dXOb9IvQzg+BDpjegWravnlvn5zEkcTic+Mewz+uJVYdp6fJywaR0TujJUPMHZdz+gSnpahGOl6kelGSaHB6y4kxMy4nlutk5HGpwcFpBMlq1yOSsGF7Z0Ftyeswk/4GlRSGD/C/31PH5jdPDsvSOEWPU9OSRKczJjx9U+JyaE8vuh04ImecfY21JE58X1pESpef2hfkhT60IESJEiPCfiSRL/PngJ0SrW8g0tPFDUzvzEkezOP0J3AE7WpUJlRD+t/6s1LMod5bjCDhI0idxUpLS2ez7hicp61oPQFnXBs7JfJ4kwyCemoMQo8tiSvyVoW21QRP2eq4lmVxL8j/0Hm1aM/cNv5q3j76NXtUIPoHOL7L41a8WEZ0ZoNi+gSR9HjG61LB5nb7wbrj2nu2120t5ftkm/DYJ2SwhqmQEAZ46sJ6rR0xGLYaLMRub9/N25UoA6twtPH7oI54ed/OA8+zyN7K+5RECsmJRYRE0QI+3UaCLenf9oN0J+1LpaOPpoo34pSBTCrL5fr9SkvfIN/PY1ziZhy+cA9rpCIIKtQDPTT+P+3YuxSs4ydBGcVfiTIyimsTkJNLjU7hi3UdsaqoE4JYtS/njpNl83fwZHskLMrhkNQFZxTsNq2loj0bqiTDK1a2g0kJQhSwLBBw2zp48hm8atmBRm3BUxgPK+7xk8lhGpyThciklgAIiBdKNtMqFjI3dhCVYxoyUJnbWXMmjqw6BX8nWirHoeW7JbkYPqeXWK07CarVitVpD16Ksq44Pq79DJYhclrmIDJMSnzkD4aWGsgzeoAqtSsLbEyer9OGxd6vXjizLCILApaNG4zfW4Q56OD0zC4AJWakcqGsKjZ+QlYrPH+Da5z+jtk3Jyv/hYCVfPngFRt3A0tDkfA9DksqUbn8VVhZmDO6he+nCCVw0fxyiIISaB8iyzJKqHzhor2ZMdDbnZcz40Xvkv5WI6XqECBH+x3S4woWZ7w81c8v8IeGCSh9MOjWf3zid2g4XMSZtaNzuo+E187urOgad/2O4fUGeX3uE+k43i8el/nSpod8NGsNP7jc33sx3PdlRx2hzeln84uaQWHffScPCBLaFIxJJX2egpl15/crpWTi9AS59ffug2VoAy/bWDTjnj3ZUh8QqgG5fkI5uv3LdGvbBx5eBox7PqIs40tzbNrf/3+wxaf2EDo8DvA6wpoaWJh/8oijkP7b+cAu3zMvj0901yLLy/vqKVQDpMUblunjGwcd2OLoJUsaiP+n3IAgU1drDDvn2lqqw7YNyNgflbICwUrX+CD1ZR1/ePIPtFe2h8jmABIu2V2A59SlYditIATpzz+CJ4mS0sh+nTh/KADMKA6/9X1cf5venj6BmxzKi3NXEj5jNpSv8HKxXSlfXHW7mq5tnkGoz8HlhLVOyY9he2R6arxYFXr18Am5fkBVFDYgdFUzpXssaeyrrpHEMTbRQ0HP9n1h1mFd7/NBWHGjEqFWzYHgiz180jrUlzeQlmLl+ttJZZ1tFW+gYAUlmV1XHoILVX1YeDvu8+wt+/ekrVu2r6eRX7+4OlWPWdrh5+dIJPzI7QoQIESL8uyPJMunaWq5L24BalAjKAt3e2UAmBvXgWbXpxnSeKHiCTn8nsdpY1KLybG1wHwiNkZFochf/bMHqGC3eFpbXL0dG5pTkU0jS/3i2uyRJiOJPl0HNiB/NjPi/9v5gKlR3F/FmxS0EZB9qQcuFGX8i3dTb/Gdx2hTWNxfhkwJoRTWL06ay73Adv/3b1wSiBYQgCD1iFUAQie/rSlmUHu7z+M7mrdDnkVzb3Rr6f0dHBw0NSpObYHRdSKwCMKj8CMjICBhUBhL1iWH79fv9CIKAWq1cf78U5LL1H9HgUmKS7Zpqzp83hlXbS0mwmTlz5gW4pHhMfQTIOcm5bDvjHjweD9XV1fh8Pmw2G6lxijhY1NHbgEeSZV46tIz46J5zFECrChIIqAjIQWTBH/Y121QHbhsgSxhaJbq2mPn0gj/zu2/X8HV1SWhcRrRynxmNRqKjo+no6EBEw+R4N8bgZgAsuibGp1m4/4qr2F3SREVtBwcq2qCpi6LyVtLSkikYk0JlewNJejMqtNxf+SIuWYlzDnRW8M6UB6mu66R4r52kqHgaZcXSIiCJJOhj+MsdV7G9tI4ddXUYtRJHVYW0BxVbh4WJE0MC0QP7X+GIUyk/3NlRzBuT7ueuk2ZhMxmobGln7rAcZg/NprqlMyRWATR1OqlttZOfGp4FL8syq7q+6e32l+PAJTVzPFT97vePqjby4pFvAVjXXIRKEDk7/ed5rkX49yUiWEWI8P+B8enR7KnuTXEta3H+5ByVKJAZawr72YSs6FA2CcDErF/evvW+z/ezbJ8iuHy9v4HPb5w+wKPJ4fFzqLoZw+eXUeDdTbsmGes1S1EnDd7O+HisLm4KiVUAb22uDBOsYkxavr5lJj8caSXBomNydgz7ajuPK1YBmHWKeFfT7uLZNUfwBoKhsrJjRBs1pEYbWFfSzLMf7UDnu5zfat6nYP+72LSL6PT1ZtZMyoomyqDhpFHJofIvAA59DZ9fCwEP5J8EF3wAKjVFdeECk0GrYvsDC/muuInberLCTitI5rkLx4Vn8OitcMWyASYJ03NjWXEgPJ16MLQqkevn5PDYtyUDMs/oEd/WljSzt6aTS6aEZ8rV19cgL/8YoeA8GHux8n78LjZXicgH9+BFy03+2/mD5m0yrSrSFzzEgn0JfH+oN2hYf7iFKQfXARZgJKattXTTK2QGJZk91R3cvmQP5S3KSuzIFCsTs6JRiQInj0pmUk+G3aktr8MRJXi+WCuwbuLfmbjwRAw9Rvjb+4hQ9GQlzhuWwOljUji9X7fGMek26u3K9RMEKEgb/EtGmzO8sUC93T3ouI2lLdz96T6c3gC3zM/jprl57K3pDDPZ/0eE4ggRIkSI8O+FWlRxQaoLtaik/qoEmSjxB+DSH52nU+lIVIULKMmGUaEMKwGRRMMvi5f8kp/HSx6nzac8/4rsRTw2+jH0Kn3YuFavne2VFTy7ciduf5ALRw/lphPn/izhqi+FHd8S6OksF5B97OlcESZYjY3O5p2pd3DYUUe+NZVUQywfby1ElkHbJSMJAoIEDNK/ZktzBUsqdhOtM1Ja7EI9SUDUKM/QDEmJT96vXMWa2h3Eqayca56ButWAP6hBo1f8P9vqohidOAGtXuTkpJOJ0vQ+2xsbG2ltVYSvxMRE4uPjafe6QmIVgMPv4dQThvHgWQt46aMfuPG3S1CJArdfPo/zFo0LO1+9Xk9+fn4oi+gY0xIy+a6+GKvZjSjIvQZKPciyMjZJH8NpeTN5vlgRmDRNIsYqkeg4B0arhzZ/FO8c2E9Lm5OGmPB4tbS+gYaGBuLi4khNTSUhIQFBEAh0fBo2TqtqJTstlplTCrjjL0tDPw9q4fc71tNV5wKtjBqB6BIZy9zeRblWn53CyqPc/8dv8foCoNKy6MJpGHMEorQWzkybSqLeRn5KEtPLbbjdbrqkVA74q8lNyWJekuKl6g54Q2IVgDPgpqK7nokxw7h+brjheUKUmYQoM8125ftOjMVISoyV/sjIBAmPaY/UNA0YB/B1/dd80/ANBpWBa7OvZWTUSIrs4Yu8RZ1V/zcFq0hJYIQIEY6xtqSJ1zZWYtErZXr9BaXjMWdoPG9srgxtJ1n1Pzr+eFwyJRNJktle2c7YdBtXz8j+xfvYebQ36yUoyRRWdYQJVoXVHVz55g7O93/FbzWK50+Mv4G6T35N6m2rjr9jRz18fCk0HoC8BXDum0Qbw1N/+28D2IxaTh+TwuHGLmb8ZS31dk9YmV2iRYc/KNHu8hNr0nLp1AyCksylb2ynqk1Jbe5vYp8Tb+KFtUd4cV0ZvmAKkMJVvnvZpruFdKOfTl/veYzPiMZm1PL1vnqq2rpZPDaF+z8v4uWm24in54FfuhJKlsPIM5mWE0tFjyAjCjA1p6c07Ysi3P4gw4RqRhV/xI6P8pl6wf2g7vee+wRD72w5ytubj6JVCfiC4U8QvUYk2qjlgknpqASBOUPjKUizsWhkEoXVHXy2q4bdVZ109nR/PEZ7t4+8eDMmrYpunxIEnOv6hB07jnLX5tE4tB3cOC+fq2dm8doP20LzNkpjWJd2M1clVYCvm5vm5LD2UHPouebpV8s3TiyjXoqloidlX6sWMevVIbEK4GC9g3evnkxsv46DlK/rvRzIzNcdgj7ZhmPSotjXJ/NsbMrxf8+ePG8MiVY9dZ1uzhqXGhLF+nP5tEz+sLy3E6FaEHlrcyVX9fkdkiSZmz8sDGWyPbHyMLOHxDMuw4ZKFEKi1T8iFEeIECFChH8de9rep7p7OzG6HKbG34hG/Hlx1kjbWBq7toe2dapf7uEJsCD5HqyaJLoCiofVL82uavO1hcQqgE5/Jy3eFtKNvZ5VX9Vt4qUjS5GQcaUaaCuO48Xt+5iYlcbUYccvl3M6ndTW1iJJEnFxcSQkJGBUhYsHBtVAMSHDFE+GKZ7lRSWcsewjfIEg+gQRfbOEqQ3GdGewI6qWgCxRYElmXkoe5Y4WrtvyEX5JiT8s2QaC6xPRJbtJtnQyfXo7y2rf4Z2qvQDUBduRnXCJfi5rXp9C3pRq/B41hzbm8shtJ7F9exUvtO5l0QwvepuOp7/cgM/n5+KpQxiXEU9TUxPR0dHE6UwMscZxxKEIWQl6M7mWWCpr23hv2Q5klUxXZoA/bf6OEcNjGZkx0ALjmFjl8vh4afVaatVHSIjuRu6JhAIyuFxGokw+Mo2pjIkaiyioODFpMjE6K6ekj2JvcRVr95bQMmEfqXMUcScQENnx/QjWHz3K/fMWsqtKWXhOG9pCRdIRHqz+Bk1tELPGzNXZV2PrTOKVRx08+KCIRqvEXpL2NIyikWAwyPTxQyg6oog67ngBj9kL2p5zRKYzWcbULSKalLkphjiK9jcpYhVAUODIRjcfnHZF2PsPBoO43cpinkU0ME03lExzZui6GNQ6MoyJVLuUY+tFLZnGwX9f9Fo1r91yDn9fuY2gJHPdoikDOv/R4wGX5xjHkahCBAFcXVqORNnZ3lrBlLic0LjK7kqW1ilCnVfy8nL5yzw/7nkKorLY2HwwNK7Aljno+fy3EykJjBAhAkt2VPPEqhLau3vFgbIWJ2vvmvuz5s/Oj+eWeXl8sL2KeIuOZy4Y+w+fy2XTsrhsWtY/PH98RjTfFClpzqLAgPKpp1eX4vAEsKj7ZaB4B+/4FmLVg1C3m11SPrfvW0T7gTVcOTOPy6Zm8smuGhKtep46b8xxp/9h+UHqe8q0fAGJ8Zk2RiZHccPcXD7fXcvT35XS1u3juvd2c+Oc3JBYBeANSJw6OokjzU4qW7vZXdXJ7qpw08Y2orBbh3DuuDyKVivdSLRqERl4fKWSnr2htIVPd9XS6PAg6ALhJleS8qB/5IyRpEUbqW7v5uRRyUzIVAQSjy+AGRcBRMrkFK4ofZ7OJeXYLn1n0Pf77JpSnl1zZNDXhiaZWXXHnEFf8/olHvryAK1OX1g3m77EmXUsu3Umaw81k/DdTSxWbWWC52XaiAKvxOMrS1CLQsi4HEAjyFxZ+zvoSeCbML+Tt666ghVFjTR1eVh/uLcjooVu3tc+hkvW8WJgMV8EZzI0dziTs2PRqIRQeaZGJYRlJoVIHgP1haHNGssYqstayUsw89rGCsrLDjNdKMMkeFkgFnJSy3gCwYd45OuDrD/cQlq0kb+cPYqsODNmnZqHTx/BM2uO8MrGCn440sJDp40Y0Bb76pk56DUqnllTSkuXj3aXj99/XUycWRfK2vJL0oBujx0uH7OGxPP6FRP5orCOZJue2+YPGfzCR4gQIUKE/zVkOYjseISAezmJAR8HPdE0uvcDMrMS7/xZ+0iJuhVPoJwu707M2rGk2n7evP5oRAPTE677h+YCxGhjiNZE0+FXMnijNFHE6Xo9NYOyxCtlX4Z8kozxbpw2L95OPc1d3cfdL0BNTQ3BYJCDwZ3srFuPtlHH2WmXkGE8Sq3rEGnGEcyMv3jQub5gkAe+Wo0vqAhQ7hiYl5fLiOQELjltEre+8yXby6sp93Tw69ZlZI+LColVAF6jj4U5o8C8j9yx+6iX9oETMgxpVLtjAWgOdhITE8WYzPFsXKYIZ6lJNpZvPMCmQsUeYOv+SgKJGnwBZd/Pfbef5y+ZjblnsUslirw//2JeObQNvxTkqvzJWLR66v12zFYnp1z1A9GWbra15nDdTi0f6y8iLSFxwPsFuPPxpRycWIhGH0AL+IJqZBTfpPnxC7lnzEmDzmva2czb931NMCCR/Vhv6aNaLZGY0kFtvZFzxo0i1RbFD/W72SUeRkZCFv34gHZ/Oy+Wv0jB96eyY5uZO25fSMHYZgT1EGYungR00NHRwbkLR2IyaCk92kxhoIX9wfrwEwmINNbaMKe7QBa4NHU+SX4bsgA+s4Ckhm5tcEBGmUqlQqvV4vMpWWCCIFDZ4sDfZCcnTcWO9jeYH9VImRCLwx/DXMMoDAE1zXYnD3+wmoqONiaMTON3py1Er9aQlRjDw5fO4rvGv7PFu4b21plMiTtnwHX7/YnX8vLy1XwmbqFTkIAmbtvxPl/Ou41kg/IdxRkIr0xxBV0E5SAXZs5CJYoc7FQ8rM76v5hd9V9IRLCKEOEXUtnazQNfFNH/e3dFSze+gIRW/fPSsO9eNJQpOTHc9cleFr+wGbNezYy8OP5y9ujjeln9K3ji3AJSbHrqOz0sHpvChMz+2SLKG30ucBY/BEfxvPYFEmknRhuE+j2QMm7Q/eJSVgZv991MHfEQhJc3VPDhtVP445mjBp/TB6c3PCV49pB47liorBi+1Sc7rarNxf1LwzucRBs1VLR2U9oU/kDr2wJ3YrxM7A3fcoUplozURMqanMwcEsebmyrD5rT2lI495r+YxzWvohYkgunT+EtFHuW7d3LyqKRBje6n5MSy5lCQMtlIWTCNaLq4vfwrluyoDpnZByWZF9aWsauqncONgwuAAkrXyOOxZGd1qGRysM60Jp2KFqeX6XmxRE9IY993LgKySAeWsHGeQPj11tBPAKvYwNzZ9zB3aAKdLh/n/n0rZT1m9Zeq1gBgFLzco/mEHLGBuw7fiMPt55IpGSEfLn9Q5vfLi3nx4vHhJ7noUVDroaWEtVFnccNyA77AdoxaFS5fEDAAo3lG/SJnqTZDs563txzl/W2K0Fjb4Wb+Uxt486qJzB2ayIc7qnnue0X821fTiVoUB73nLp6SyZKdNbR09abkFzc4QoKVTq3ioskZfLhdOc6oVGsoY2ve0ISf9nuLECFChAj/e7g/A/fHqIEkNcw02FnliqHdW/EzJiuoRDND4l9nd9uHrG19n1XtF9Lqz2JszImclXrWv/T0+6IVtdw77F6+rv8aGZnTkk/DoAr3Dx34yJdJMRvJs1kIBAIhP6ewEbJMMBjELrezRVoNgD/oY0n1mzxa8BpacWDme18CQSkkVh3j4jMmMjEzjdK6FnYerEVExJ3lY4W2BKFYDkssn51kYNTId3AHwxcRk3XOkGA1M76AzMxM/nBXOqs2FtPt8nHCrOFc/dsPQuMlgZBYBeALSjg8PnR6M394eRU+f4DLzpjMg+MWhh0nPyuBa67ZSWy8shp3TkYhDS4bDy9fw02z5zAhLw2Azm43z361icYOB4VtR7Ea/YiChFqUEAUJd0CLTWPm6mHHN/X+4KNN1E3RI2kFkjpUaPv45EtegUkzBSqcFUzNziFoamBXOQMWHt1BNxqjSHeKhvUjc1gn55DXoWVmnzEulytU1rinpp5rP1yK3e1ENkiYBA2mTpHmXBmPQ4n7XjiwjZ1n/Zo31u/icLMipFU67Hy2pYjzZhSEHT8rK4vGxkYkSeKz3ZW8t0G5Zy67fDN6s1KhEW/WcErwNxiIw+Px8IfPN7GxqQKxoItObQWbVu3iiwW/JlZvZlXDCxxy/ABAvfswUdpEhllnhh1TrRK5+tR5vL5yc6gdkkfyc9TZGhKs8s35ZBgzqHYp8dm8hHkh/7jzM2bCP94z6r+DSElghAj/Peyu6uAvKw4RlGTuPnEo0/N+vCMcQEuXd4BYRY/30M8Vq+gJGm75cA/2nhKuTpefb/Y3YDNo+PNZo3/ZG/kfYNKpefBHBJGJWTFsKmsjiIpd8jDu8V/P+9rHMHSUwPvnwK8PKibswQCo+vxJmXQtHN1Eez9hpN3lo77T3ZMZY2B2fvzAgwI3zc3llg8L8Qdlkqx6zp/YmwYfZdDQ4fIPmBOlVzMqNQqtSmRdacuA10cmW1k0MgmdRuSSKZkIOjVBSaaly0tQlrH0iIaf7u6tyQ/0fNifS7PZ5h/F0iuH8tQeFZ9uVYKdtSXNvLGpkjevnESKrTeYtPUrd6yUkzgUTOX+pUX4ghKXT8vitR8qeGZN6XGvfaJFx4LhiQxJsBx3zK5+xvs2gwadWkSjFul0+XB6g9zx8V52VbXzpzNH8/3wP9Jc/DRzxb2slRThaEiCmatnZPPRjmrqO5WstrFCv2yv5N5sOJtR8Ro71OjAqFGRs3cL9FZQUCUpq5QqUcDaT3w92jrIyq/WCCf/BYAXXtqML6AEsi5feFB8QMpWBKu8hdQ0hHe2kYBbPtzLgd8v4kg/obK06fjZgLOGxLG/p9xQEGBmv78Bj541minZMWwobWF8RjQa1S/zBYkQIUKECL8c2bUE2fUxqBIQrA8jqFJ+elI/c2ajqDxD0k1TftGxmz2lbG15HXq+Lkerj7Cs3k2aIY1JMZN+0b7+JyTpk/hVzq8GfU0liORb0il2HA39bNbQaC5JmIzk9VBXV0dmplIO1TdzRhAEYmNjaWqpC9ufX/bhkzyUdzVxuKuO0VGZg3YiNGo1XDl1PG9vU7Kip+dkMDZd+WzMBh2iIBAQJQJJwR7xRSDgVzEkKppsXRyTYlfh7CdWAUyNm8mQqOGkGOI4IUm5xh7cqEfUEyuoMVnUTBiZzjcblHIvlSQg+mQkrfK+Ek0mpo4dxZUPfEiLrQHtNDs7yzcys3U6D0xcjK5HvBMEgZQkF33XRBN0DrYVN7KvaCkf3n0R+anx/OadFWwpURbbNHEyWlWAOH03KkEmIAno3eOZoB+HRXX8JkQ78r04dErZ2872XM5wtCLYXATssSSPaSQgtPKnQ/u5IfcGxsWMJqUukXpPI5IsKB5ZwIzYGZx76Ryebi5B7gk/yix+Sts6yY9VxBuDofccxqWnsPqWq6lq6yDaasDT3MIPaVU8XrMrNEboEYEMZi30+ZWpbhn4uWi1WjIyMvD5A3z0wmcY47z4neqQWAUgCX66hUaMxGMymahrsyPmO0mMcfTcAx5+t/99Xpx8Ay3e6rD9t/bbPoZJraPAls7+zhoAorUmhlp770edSscDwx5g+dGNVDQ5yA5MPO7n8H+RSElghAj/Jbh8Aa5+e2dIMLr23V1sum9+WEe3wRidaiU7zkRlzxfvrFgj54xP4+qZv8w/yh+UcXgGii4/HGllf21nqEPa/w/au33c/EEh+2s7Seznr9Us9zkvVxt0VsOqB6BsDcQOgYs/hthcGHEGXL+BK1eX83KxMjxH52B0x3ec9lUK7T3G6PcsGsrN8/KUAX4PtJSANYVFI5NYc+ccqtpcFKRFhQlAT503hhvfL6Sln3G2JyCxuTzcoBsgyqBmcnYsvz9jZJioBHD/5/tDAtVrGyv49vZZ/O3CsWwtb0MGPt5ZExrbRAyJ+ZPZu3xD2D5KGrs46dmNfHfnnND1OmlkEp/vrg0tXKQIbdziuw2AreVtXD4ta4BhuygQJoY2dXn5cEc16w43s+L2WQNEMPxujAE7I4VKXtL8jSShncKok5l2+3usPNjEDe/vDg1dsqOGPy4ehWiK5b7AdYpp++xMhidHsWB4AiadmvRoY0iw2iKNYk36rSzUHoTEUTD/t2GHNmhVjM/oycaLfRC8HbSXbmFFVw4vB8/gqhlZ5CdaWDA8kb9vqMAXlELX5Xh4/MFQ1tZgzBiRCaNfh4LzOKWijXe3VoUtDDm9AdYUNzF/WALvbD0ayjhbOHzwNH+Au04YSoJFT1mzk/nDE5jRT7Bq7/bxlxUlNNg9LC2sY9fRdp698DhZhREiRIgQ4X+M7NuF7PidshE4iNzZiRD78U/Ok7TzgdcRUCwMutQzmJN0JsOiTv1Fx3cHwp/NegKcYqnF6n0fOZiNoPrpxc1/FU3uQ6yufxR3sJN4bTrQ6wOUYFNj0SqLRB6PB6/XS1VVFT6fD4vFQnp6OqIokpycjNFsYG/tJqo9ZQAM141la0MZfyj5BAkZjaDi2QnXMjZa8Q0KBAL4/X50Oh33L5rDKaOG4vL5mZiZirrH4D0lxsq958zlyW/Wh5+0LFBT7qa6oY6U01uI7tMLxaxOINs8nZkJN6Dqk93lDXp57NBj1HuU8rZdHbu495q7SEuKprHVQWtzF1sLK/AbFPFleJyNQAAauzswntmB0CPubHJt4vLlXj5afBGicEzcWkS1423lOAE1ZXszEX0ifoLsragnPzWeQ/WNmAva0SZ5kNwqrCovsZpuUrSdyAjsbdHy7AY/eypaeOXiMwd8Th6fjw5dr6WAO6hjgvkSzh0znver3uf7ZkUwlJHZ2LKRYaYxVFfkUukWidaauG3qWDIssYy1jSUgSUhq8NsCyBoJ0aVCZTBiNpuxWq1YLOGLmrEmI7Emo/L+DCY0ajXrHHXssDegFVU8POFEABYU5LG3Qrm+alFk7qgcjkeTr4kRiw+j1gcIeFU0NdtITFAELo1gIsNWQFJ0FgaDgZMnDOO17tKwbLEj3WW0eOwMMU+m1asIgSJqcszH77D84pTLeLd8M66gj/MzJxOjC/cv3V/bwsMfFhOQJN6gmj+dfgLnjv/pCo4I/3lEBKsI/2dpc/pCYhU92RwNdvegglVpUxeHG7sYm27jsRWHQmLViSMSefnSCajE45gH/QhatcjFkzP4YHv46kJ1u4tz/76VpTdOZ1Tq4B3O/tU8sbKErT2d2Spau9GIAv4eJeUsczEcu2xJo6HkG0WsAmg7AqsewHf+R3y2u5Zur4mrzzqZWaonaS/ZyGz2Y13nZpzvLr5HeUgt2VnNzfPy8Dha+fNzL7CvO4ap6iPce+kZZA49YVAje7c/OGhnPG8/I3AAo1bF61dMOq759vL9x9oUy1zlfQ/dG79lceZYFp/6JDUuNcv31YfMymfkKdlg03JjOdJPWHF4Aryz5Sj3nqS0cF44IpEPfzWVHZXt1He6eXfXotBYly/IygMN+Pud72CZewANdg97qjvDuxaWfAOfXcPbATd2rZEoQck4mtb5NRR/Sbwl3E8tzqxj59EO3t2qBAq+oMQH22soemR4aOV1VGoU2yt7V81WNphZODQKZtwB6oHmmCG0RjjzJWK2vsgJ+1Yz37aO5IWzoadr32c3TmNtSTO58eYBXf36srq4CYenN8BTiwL3nzyMitZu5ubHM39k75eOKTmxPHvhWG5fsjdsH3/6ppj198zj/WumsPFICyOSrSwem3rcY4qiwBXTj+8Bt6OyjQZ7b3edr/c38PT5Y8M7PkaIECFChH8egcof3+5DbXchnqCTFEMu5a23IgXsWEUtcVG/Jtdy4z90+BTjaOJ0ebR6ywCZU8ztpGk8QDVyezHEfoUgGv+hff9PWVX/Jxx+JW6xqUuI0+bQ6rOgFlSM0/cKDlarlYaGhpD/UFdXF+3t7WiiVOxu34xeZeCW/AdYW7oK2S+THszj5aPrQ55YfjnIivpCxkbnUFndxBNvrMbu9LJgchaXnz2HgtTBF598zR4M5QGciSKBZEkRLbwCwUYQgV1FQ1g4Yy+CIBOlSePczOcxqAfGurXu2pBYBVDSVcLByiJOmZ5NQkIC328uYdvuCrQu5XynFGRhsxpJz7TSLjaE5okiFDbVUFTfyJhUJUMnP+ZeLNqheAINvLZcpP2oEj+lZ7RgStpOk1uHbUYr3YaeOM8cQK8Okq1v4dijf2JWOXv35LHhSCXeQCCUwUWfroXDomyU2BVRx6hSEydLBAIBbJrwBekoTRRv7dtNYUMLYKYDWF7k5LVTlXJGjUpF1rAoDrmVdCjJGKBdcqDXpxAd/eNNX3Q6HTlZ2Typ1XHU0UZSVAy5KUrZ4+XzJ5ASY6WsoZVpwzIZk338+GxN82rUeiU+U+uCdLtHMiE2C1/QyajoM4jV9S7aX7doCrWbqtka2NJ7X0gyb1Ws4Z7hV2LTJtPha2CIZQophqHHPaZVY+CWYQuP+/qKg6UEpN44+tuDhyOC1TEiJYERIvx3kBylZ3RqVCjLJTfexOeFtdz72X5Gp0bx8OkjMWhVfFfcxI3v7yYgyX08dRRWFzfR7QsMKHv6ufz5rNGcODKJrWWtvLapMmRI7QtIbDzS8v9NsGrtl7k0KjWK08ekkBVnZH7qRNiZCKIaplwHm/8WPtlj56YPdrPmkPJgfWfrUTZErUal2hcaMl48wveSIlglWpSMpGc/Wcl7TiUNfL8/l5gvV3HDfScMen4PfXlggBl2fxJ7zOxz4s0kRR2/O1BGjJHDTV1cpFrLLeqvwA7sLwG1lvQznufj66exZEc1KpXITXMUr6qHThtBeYuTzWXh2Vyv/VDBBZPSQyLbtNxYpuXGIkkyGbFG1h9uZk91JxtKW9hQ2kLyIOclDPLsUIkC6TH90s6/vh0CyiryMbEqhKudCSOjufekobzxQyVRBg2/PiE/ZCZ/DI8/SLc3CAIEg/IAH63qbjUc/EIxmL/g/eNeQwCKl8GqB0gAaFwPKjs1C16kwe5hVKp10IxBjz+IXtPbA1vTTwSKNWu5dtbxV/wWj03lUL2Dv2/s9Sfx+CU+213LO1uOEmPScvLIJNy+IAbtIL22fwZp0cYw77NUmyEiVkWIECHCvxLtVBDMIPcIBrqZSB23QrAWwXAagukaADY1v8ze9k8ByNWLxInKs6BV8uFyfsPIf1Cw0oh6zsn8G1XO7TT+P/beOkyOctv+/1R793T3uPtkLO7uQkISAgQI7u7OAS4cXM9BDn6Qg3sIIZCQhLjLxGWSTMbdpXvapX5/VKd7eiSEc+/9fe+99HoeeFI1b71VXVXdtWvttdc2ryZFviTwR08FuE+Cqu+mMf+dsLmDbQAWRoxBYchjSEQ2SfJITCYTKpWKyMhISkuDvbs6XSY+OfEa7S4pdinsOMg4z2yJSQLCZcFxRoxaMjz/61srKKmW9vuvnw6Sk5HAlLE9iYH6JhMffrMVgKgCBY4oLyhAdMtxRko7OVmewuC4Udw6M584TR4qee/EX6QqEoWgwC1KsZ4GDYJDoLGxEZVKxcyJUnKw4GAFifFGFp0zEplM4J27ruC2nf+gXSsl3ywmDW6HnL9+uppl/3ENgiCZpScZJFXUoxfa0Sq34tDuJDFvJ2WenZRXLEZjzMDi0vuPx+ER6ProVyk8qJVuwtXhQWSV3W6nuVnyhfrrsOEsLivF4nYzLyWVGI0Gj8fDnIQ5VForKTQVkqpLJaNlDC/t2A1dwhSby4XJZUUrV1HVaqLNG9z4qMjUwujmZpRKJdHR0b2eQ/91qa+nvb2dCOTY2zpo04bR1OHC7fEyc2g2s4YFN47xil5EvMiFwOc65Q91CvkpqYyPvaHPfT4zaRG37K7hZGclXlHA5ZVj97h49afN7C5qZkBaMrkL4vF4Pchl/2Z8FhH8jpQc3rOz5Z8Z/xtK/c4UIcIqhD8tFHIZX900li93VuD1inhFkdfWSL49R2tN7Cpr5YqxaWw80eT3MeruqSOXCSj+ky+vU3Nj+b6gqkf3tH6x+l7He7wiH28to7S5k9kDEoJVNz443V68ohhEBvwRXDYmjXXHGv3EyYGqdp45bxCDU3wPhxmPBQYPvwr2fS6VB8oUOEffxtqvAkXx1W026tKGk1IfIKzicsdxTdl2dHo9iy64HYDizmAFz0l3HG+sPcmP+6tJCtfyt4uGkBrlkzj3oqSK0auZPTCeH/ZUY9AouH5SJgOTwgnX9U0mvrtRksJHh6kYLjRBVw6sWboXdCo5m082U9lq5Yc9VfzzqpFMzonlqxvHsbigkoeWBAzfXR6RIzWmHqowmUzgwhEpLNlb7b+XACzdSDe5TGBWfhyrC6UWwTIBtEo50/PjyIzpdj+4g0lFP8JTof+5ANw+LZvbR0fSUvA9zyxexz73GPyRKZAZE8bQZ37D4xWJ0CpptwWXqE6QHw06F92xdH81q47UkxETxoPqo3Q907+UC9z3ykbcXpGs2DCW3DqBSJ968WSDmWs/KaCm3caU3Fg+uGokGqWc2QMTmDMwntVHG5AJoFHKWVvYwKwBfZf03Tkzh00nmzlWZ0IAcuL1PLg4cK9tKmpCq5Tz5mXDOes08/SFQcnhPH/+YD7aWkq4VskL/z/6y4UQQggh/BkhKFIh+ntE2woEeRyifT04pVJ80XxUWg67nkOtS/3bWNytxHQRyMuE06iCzwBKmZZs4zQ6TffhEkWUPiWyiLpPPy2zy8zK+pU4vA5mxc0iUdvTA8rqcKFWypHL/j0/xFzdPI5afgTA0qhh2TvtfPLFRFS+Trg6XYAAiomJoapKsjVQKBS0q5r9ZBXAEdMeJuvn4fLFIhdEjMKmFjlhrmFoeAZXZUpK7ZrGQDJLBMqrW9n2+WcUHaxk8Lh+3Pn8xajUClxdlO+CFzStUgw6pH8yrhQFBeXVZERGMjVxBAmaHBR9eEJ2uhy8vH877dZcYgx1RMo0TJVPReEjUBwOKf4R4x1sdO3DvE1k+dZC3nn8YuKiDXw951Ge2PojK4pPYGnTomuSUWFto8NqJyIsmJQz6jRcOj+N5VXvdPmMHrLD7LS0B+IuhZBMhNJNu0uqiqjriEGRquGqIcHEpejLbpkcTt47to/G8ArCDSrk2hgMhmRUKhWCIHB79u3Y7XZ+WbWPv6xeh1sHQiqoDE6MRgey2ErmbnwatUxJx3Ej7V4BfCG4DBhiiAk6F13h9nr4quI3yix1jIrKZ4A9WA331tdbWbVNiutmjc/jmbvm+5X2+9p28E3l+7i8TmYnLGRe4iIAzkk8h0JTIVrxMAN1TSSpXVhcZxGm7NsO5YH+F3P3ng8we2yoRRUNBSJbD+xDpvHQ1P8g2/asJEETxctDbyNJ+8fLbK8eN5yqtna2lVSQnxDLQ7Mn/+E5QvjfgRBhFcKfGkaNktunSf5Jj/54KOhvZc0WnltxjPyE4NrwkWkR7K1sRy4TeOrcgehUv/81qmm38fqaIuwuDzdPyeqhNmkyBz9wxmZGMacPr58Xfz3GR75Odt8WVPHVDWODzOK/L6ji8Z+O4PJ6uXdmLvfMyul1ntNhZv94NEq5v+xOBI7XmwKEVVdE94Pbd0L1HojORhmTQ5xhHY2+zySXCTimPwXJKdBUBDmzWLTtLRaJh8EMbD5BxYx3SEzNhPoG/7Sx2SP9huQVLVYeXHyQ726R2tM+MDuPh5ccwuMVCdcqiDNomDMogVumZNFosrP2WCMvrjzO31af4MOrRjKjFw+jnw/W8rdVJ/zL9TnToXoFiL6AK/8cGkx2zn17q79jocXp4dnlhfx231QAFo1O4/u91RT4jM81ShmDkqUMT2GtiY1FjWTFhKGUy7j5i709SMnhqRHEGjVsK24m3qjmkbn92VnSQqPZgYjIgaoOLE4Pyw/V4XR7yUswMKt/PENTI2DGXxFX/gUBkT3eXP7uuphowcQ1s69mrN5nZG9rh49mEN1WzhsKmMQUXnRfhhMlneiCyhq7klVRmLhHtYyrhZXSirx5Pc7fhhON3PddgBgyDszgDplCUmMB/7DN85NzpU0Wlu6v8fu8Pf1LITXtUrZwc1ETX+6s4MbJWchlAu9cPoIxz6+l1eqiosXK7V/vY8OD00iO6N3YVK9WsPT2Cdz0+R62nGxmy8nmHmNsLg+PLT1MYriGF1cew+n2cteMnD4N/7vj8rFpXD420HLG6nTTbnWRYNSE1FYhhBBCCP8NEBTZCIZ7ABAt/wr+o6sA2veSosyg0vfoanQbydEl4HQXopBFkhr5eC+z9oTJvp1G85co5BEkhz+AUh5Qq3hFFy5vO8UipMjlCICgvxWDvPdnxytFr/i7lhW0FvDC4BfQKyTSQxRFnvpmDT/tPEqYWsXfr5vPxAF9l6P3haTOC/jw9RLUBhcNh6NxWZy0t1qIS+gZn4WHh6NWq3E6neh0OhpddQgIiL50ZLgyin6Z2TQ2NuL1ekk1GLi5RoVXIyUFrR2dFMvM5E41cmhTMzhl6DQKGvbUsfmX/QDUV7YQnxLFFfeeTWpSJPNnDGLF+iOIchH1VDUR8WFcOGI4uapY7n9nGScaWrhr+QoiV2pYfv81ROt72j68sH8dP5T5YvKGGB7Jm0SyXLJ1EAQBg8HA7pZjvFj5OQwRUQ+GuvUevvylgPuvnYFSpuDB4eewZUUzgk2KRbPiowjXSar29TUnOdHRxMSETE5at7O8bjnpak8Q4TkrYQZ2rFRbG8kzpnNl+ln8WrsJj3iUJoucJeVqPHIrfyv8DY+mmIQwPVNjp2LUGDEajbz02wZq044hV3lpA97r+I1vBo7zE0NWq5WysjJ++u0wXqWAzAWRHQ4ihzQiyKDO1YFCJsfhBVV6G4q9sQhuiI7QcnvuAAYbpPu0u38VwMdlK1hctQGAbc2HuTPlfPohjW83O/xkFcDaHSe45vyxZKfF4hHdfF3xHi5R+lKtrv+RIeGjSdFlEKmK5OGcyymouwQQ6XTu5WDDXUxIWd7nvZprSOJfI+7mzte+orHYxi5NLYTJ0OV2oDBKsWK9vZXPy1bRP2woXxTvIVKl44nhs0nVn77UEZ/v1pPzZwata7fY8Hi8RBt73ld/Kohi763D+xr7PxwhwiqEEHw4a0A83xZU9fjeRuqUDEkJ51idiUnZMbxzxQgcLi8KuYDhDEoBvV6RKz/a5fe92lzUxLoHphFrCGT/LhubSkFFK6IIYSo5Ty4Y2Od827uYiosi7CxtYUJ2DHsr2mi3OvmPpYf9RMHra4uYPySR7Lje1VqncKSmg4+2lKJVyblnZi4J4Rqm58dSe2QrU2SHKJOlMypjWt8T6OMgXyI1BODja0fz12VH6LS7uWN6Nv0SIiHhIWls2RZoCKiSOLqUCw4toMWlQS2Hc/KNnDM8g7J2N+wv9A+rbgvIoS8amcLYzCjeWn+S7/dU02Hr5OT6YlYdqQ8y7fZ4RR5YfJD9T8zuccjF3TrHrezM5u5rl0PJBojrD4MuYNu+aj9ZdQrubqTTB1eN4h9ri2izurhyXDqbipp4Z8MOGk0Ov0ItWq/qQVZF6pT8fdFQ4rqY2j+57Aif+TymuuO3wgZ+K2zg/U2lLLltAoPH3sxrZSlsPVjEETETFwoQYVSbAn8/pJL10BboILRQvhUZHh5w39HrPk5BboglZsQVLD8eiTymH7Om3kd3Z7cDlcHdZH5pSeaOa1dgPbqS5ZZ87MVRYA1cs65qP621ho+UbxIjdPCVZxZme4BUNdvdtHbpAOl0e6lps/VJWAGo5LKg70VvcLi9XPtJgb/c9eYv9rDpoek9mgqIoojT40Wt6F2duLO0hZs+34PZ7mZUeiSf3zDmjEjrEEIIIYQQ/k2oZ4H1424rvUyOmsDSlsM4PZ0Mi7qIITHX4/Y2IZeFn5HCyu4qpajxWkQknyebq4j+8T/4/y4TlMSEXUyz5TuK3G60ylz666/tdS6L2+InqwDMbjPV1moydP0oqK2horaNn3ZKqmWLw8mTX//G2udu/t1jXH7wOOuOFZMVE8Ut08aQlh6D0JxJ9VETAGkZ0UTH9N1JWKPRoNFIz7kkRSqXp93CusZf0Mh1XJxyAwqFgqQkSTHW0NCAt4sn0BelG/i+bTekQuQVema1jGPh5OF8/uRPQftoqAp4Xz56x9lcOHc4Dx5bzlFzA9V2M3ftWEr8ET2tdhcevUTYtIkOnl62jjevOLfHMRebmlHLXUTqrDjcCppwkpKSgsPhwGAwoNPp2FhxwF/zJAgg7ycRFacQbdDx4Z0X8fmGvWhVCm6cNYZ/PLmUFW1FlE2Uxr17bD2j0koAqHZEIhe8aOVOYtUDmRJ/NdMSpDhAFEVuLvgb5dZ637IMBA2IIgOTatjRXgLtsLV5K88MfIbU1FQa3FbkqsDxOHHS4uzAqJKIlLa2NkRRJFqvRrBYEOUC6gS73yweQC54cSMHuYiAgMKkYFxKBsV2F2vqjzC3Xw6DeiGsjpuC48gasZWpKUOpMDVwUqhDluzEWxOI6tS+GMbtdfvJqlOwdylFtLurg0wrrK7eO/x1RUNlJ01HHAjIUCDi0okI3cKrJoeZj4/+jNf3AtZgM/Pz7Bt7zOXyeBAEwW/y3x2frd/L68s2I4qSP9cD50/53eP7v4pQl8AQQvg/ihn58Xx5w1g+2lLKhhNN/vUTs2O4c0awSulUs7bD1R2sOlpHaqSOi0el9qq26LC5/GQVPnPu0qZOYg1qrE43d369n63FzfSL0TNvcAIXjEgmSt93oDUo2UhhnanLcjiP/3SYL3f2/uCwOk/v9dRotnPZhzsx+8yud5S08Pn1Y3l9vB1F8dPITymOTsZAzO2nnavrMS29fWLvf9THgyAD0ZfBk4XRbpeIP4cHvCoD0welktls4fW1Rf7jitGrmPHqRtKidLziKw9sMjuQ4+EC+RYM2FjeNB4IVq/1Zs4OMDknhrfWF/sfvZ12N97UycjSJ/jHpET29Fa4fVq/oOXIMBVPnyd5ORyqbueJZUd7bNNpD74GAvDUuQODyCrAr9Q6HZweLxtPNDI4JZzhw0by1oHAk0YuE7A43dz25V5yIuDOY48HEU0dhDFSVowCN+5uP/8KmYDHKxJnULNoVCp3bCgGzoEGuGVNEY/O6x80fkxmVJC305CUcB7fJ2f5oYm0W12ADYVcwO0RmZIby4UjA8bnfxdfI0IukZZDZB/SnHIekOs/n2Myo9jtM39Pi9IxIKl3X4KPt5bx9e5KYvVqYvVq6k12//ldNDKFHWUtVLXakAlw27QsXloZUNTZXV6q26zEGzW0Wpz8crCWmnYb3xVUYbK7uGRUKi9eMNifDT2FR5Yc8t+TeyraWLyn+rSm7SGEEEIIIfznIBgeBkU2ouVj8BT71sqICJvP9ZFPBI1VyiWbhFbrKqzOQxjU4wnX9l4qZHUd85NVABbHAURRRBAE2hyVrKx5kg5XLTm6WeQZp5Gkn09fhXw6uY5YdSxNDil+1Mg0GBXRLFryLUeaJJsEdaSAus2nsHH07BLdHZtOlPGXxT6lMyJ19mYemj2dx587hx+/24VMLmPG7BwcTjs6xZmZwI+JnsqY6Km9/k2pDE7CrjIFkosdQid5UyLITI5h2nkj2LX2KKIooogB80UVPHTwMfIMg7kuYxG5WfEU7w0kkdyil1bBhtjNB8ni7v0cTE5MRKnfjEouxW/GsFoiIoJjuwRNFCBy6gmtivRw6bjgjnP9U+N48eq5ACz+eAurl+yl7moNp8yiXF3IOQ8ySu2xaGQarsx6GFkXVqXTbfOTVQCC4EWpcCPzyAjXBJqyNDmaqLJWkWPIYUZWf1ZbylCGSZ8xRhnBinUlVNbtZWxeMvlxUpx/6fmDaPy8gBK7FaFJgC4e5KLvf65yI3IEBibF49GLfHnsCADb6mpIjoxiWnpwWd7g8H4c7gj4l0UooniscDVHrIckT7A5ICvQIx7RccOFE0hNkNRMclHBINlojngLAEiSZZCuzfbPE6kZiVIWhcsrxWdxYb0boru8Lr6o+IKTnSdJEFJQqETcTgGFHWJtSmbGTWSXsBmLaEOv0NI/rD/LxK3+7YtNgXcw0XUcnDv49biXv6wwI/epqi4cHpzYb++08fpPm/0x/efr93L+2IH0Szy9v9f/WYRM10MI4X8vWi1O7v/+AMfqTEzLjeO5hYNQdqmhn5gdw8TsGL7YUc6awgYGJoX7Swa7Y/XRem77cq+/s9vJxk7+es6AHuOMGgVROqVfNRKhVZATL2VE3t9UyvrjUiBT3NTJm+uL+WhrGVanh8HJ4Xx+/Ri/788pPH3uIPRqJRtPNNJuc/HOhmIOVnf02C/ArP5xDEo6vXF7cUOn/wUcoLzFypS/b+CKpHqeF7uQPYXLYPyZEVYA24ubWX+8kZx4PRePSg28+MfmwvxXYeNLoNTxoudGPNZAYBCulQKmjJgwfr5zEmsLGygob+U3n69TaZOFOf/Ywua/TGdCvxguKP0rC+Q7AbhZWMUc2/N0EFCUXT+x9/p6o1YV9Btd1Wajpt3m98kCSI3SBpEyALtKWslPMPLN7krCtUpum9bPr7SrbbfTG6LCVHTYXFidHtKidLx0weCgMs5TGJEeEURGXjchg4pWK4er22nqDATV/XyKuRn58Xxy7Wg+2lKKSiFjbGYUL/nKHFcCZvkMbpKvIEowo1Kr+Sb8fm5pfI63lG/xtvt8VLjZL/ZDhsyvHGu3uWjpZrp/sLqdnaUt3PfdATpsLm6anMV9Z+XyzytHsvpIPZkxYaw93sDBquD70O0RWXPfFP/9fgoRloDqS4ZInCOYbP3sujF8tasCh9vLxaNSUcoFHllyiILyVoanRfLc+YMkX7XlkgKvuLGT7Fg9Q1MjMNlc3Dg5k0UjU3l7fTH7K9uYOSCOa8ZnsOpIAweqJGVYSqSWvAQjZruLhe9uo6Il2Lj+24IqZg+MZ0Z+oJz0l4O1lHcb5/L09FMLIYQQQgjhj0F0HULseAy8ZgT9TQi6K/x/EwQBdBeBZh5i5z/wuE8iaM5DoRrZ61ztbY/jtX6DDDhpeo/smA+J0PV8uVbLU33khRTr6NWj/LHKhvpXaXVKSpXjllIqzFVcHfUyAg5E7UUIxueDEhqCIPBg7oMsrvqBQ3U1VBTHcN+xtRxpD3h6umJA7ctL3TJ33O+ekwOVvi55gkj00CYK9FVcvmMzV0XO4LxFAT9Fs9kc5F11OoiiyPelBykxNTMtKZsJ8YGES2RkJDabDZPJhEyhwO4Qg94UjUppH1PPHUFkrIGiQ1UUjFhDOUXghKbmWqqsbTw96DbGxaaxqV4iTVSCHINDjdXqwaOVskpyQeC6SaN6Pca8aJF91kD8WWE73GNMTHMqOGQIvvJFIpycFEopbZSzt+0EWWFJnJc8yX+NmuqkZ7+y3YszU0CrcYIA4bL+dHiPATDAMIBrM68lVh1c8qlXaEnTxVNpleLQMLmGK7PGc6y2CZmnFq9cipmUgpIYtRTbPXzWVJL3hLHdvI+M6AhcJ4x8snYPAOv2FXPXvCGEKRSolXKeuX8mD176FXaZDXFSYL9Rcj0l6wy4HQpkHhGtUaCoLVhNfqixnhZZBZ+Xr0ItU/FA/iVcnXk2eoWWUkstufoMnt69E6/chCEsEOunTdHy0X13EaYNvGO4XC7Gy2eTJQzAhZMkIR3RI/rN4NWKOMYkfUt95y8o5ZEkGy6ipt3EE8vXUt9h5oJhA7lh4iiW1y1nS/MWAOqpZ+5dozn4jQaNRsn9N80kIdaI9yeRNtq5fMp4EhIjea9wDx1OKYaemSQlMEXXIcSWywEnc5OhoP9kvi0cxFPL1zJnQDZ6dSC5//YnG3vwLl07CIbwvxshwiqEPxWeW17IRp966rs9VeytbGVsZjR3zcjxd5ITRZHd5W1sPtnMluJmInRKbpkarKrpsLm477sDdK3y+u1ofa+E1Sfby4NKnIanRXKgqo3JObG0Wpw9xp8ydj9c08E/N5fw6NxgZYtWJeesAfF8vE3yseptjrcvG06cUcOo9Mjf9djJiTdg1CgwdVMBfVWbwFWqVPJlkmEn0f16n6AXbC9p5sp/7fKfn7oOO/fOyg0MGHU9jLqe4sZOvnhtk3+1ANw0OUAwZcaEcdOULNYdbwiav8XipLDOxI0TU2H9Lv/6BLGJ+/Na2UAm2bFhzOgfz4R+vRs5RoYpUcoFXB7pIDVKGUZtcHaxps3Wo0S0otXCZR/sxOwzKd1f2c43N0uB57isKJIjtH5/plOo67Dz/MJBTOwXQ2qUDnkf1+Sv5wwgUqeipEky1M9PNLDwne1+lVicQc21EzOYNzhg5Do9P85vvP/iymNB8/3qGcsnHim7OELeSFr0cO6raeVOxU88q/yEJ13XAjK6PtIdbm8PRdO4rGju/Hq/v5zujXUnmZwTw5yBCcwZmIDb4+XVNUW9fqaXVh7nnStGBDcAyJ8Hh76T/q0Oh4xJQdtoVfKg7oCvryni2wLpPixpshCtFntkzcpaLOz+j5lE+9SJXcsrtxQ3kxEdxhc3jOHzHRIRdsXYNPRqBRtPNPYgq06hsNYURFitOlIf9HeDRsGiUam9bhtCCCGEEMKZQ2y7A7zSs95repq6zl8RVKNIDL/dX97nFu0c71yP3V2MzFJAjiwBoyaY+BGdBRgc3yPIpWeOEmi3reuVsKrp+IefrAIIU4/A7NiLQT0Smyc4AbMovBL5qbG2H0AzF9TByq04TRye6mFs2iw9K73KOujyOI0O0/H2nfOJ1GvJSfp9k+nh6VKpnibWhibG7jsHHha3b2VI1OX+cSpV96L9vvHmkS28eVRSs3xSVMAX0y5nXHw6+Ei35ORkkpOT+abgIE2FOvR5TmRKLwZrDJNiAzHukPE5DBmfw8qCr/zrBAEOtUuJpJeGzea1veswuZ3MjExDGSNjc3ErdtHD8AHJTO2fRXZs7+qXSFWwf1GEqmeX4ZpGk1Sa1yWC2dtWxG/1u/3LFreNKzIkS4gpZw9m5eICYtY4EcYKnGqAt6PRwqcTniBOYyRa3fvxCILAS0Nu5YuK1dg9Ti5Kncax3W38/MUR1HEpxE+tJys9ksuzL/Yfu0wQuHr0aK5G6n591fKvg+b8dv0JOpqkWPH8GQMIjwzDrgyOHd1uL3alAlSSCqa8o4MpI/pxsrXFv4/0aA1vl3wPgNXj4PnCL1g68XkWpU0HYGt9GWaXA003tXjtzip+2vQLVzx2oX+dWq1GpVIR70wBQKvV9lDd6ZSpZEUGktcPL13KnsoaAP6+dgu5cdE0yhqDtmnUlfPVmy8jCAKiKHLlXz6jtFr6DIe2reDbV65l8Yzr+KniEJFqHVf0k4hM0b4Kuiggz8kp4svyAbhFL3VmMzldCKudBaWoZF6cRkmEMDwlkbzkM/Mp/b8IwSv9d6Zj/6cjRFiF8KdCeYslaLm40UJxo4WdpS2suW8qMpnAhuON/HJQymqJIry86jjXTMgIeuEub7b06BjYVZnTFV0VMwAbTjSx4UQTE/pF85c5eSzZV91jrlOw9bG+OyGiUUikg9vj5b5ZuZwztPcONr0h1qDm65vG8d7GYlYcDn4hZ/gVULtM8nSa84J/tSiKfL+niooWK2cNiGd4WnBwsamoKYjMW3+8kavHZ+DxeikobyMtSseg5PAe5YoioO3FD2hKTiw7SwMeCQqZQGK4BkGuBGMymKp9fxG4Zu5krkno2W65O+IMGl6/ZBgvrDiGTCbw5IKBfnXXKfRPNBJvVNNgcvhmh9EZUezuUrq3s6wFr1dEJhOI0Kn46Y6J/Hq4jg82lwZdpwNV7TSZHWTH6TlnSO/XR62Qc8/MHP6++gRf7KxAJgSXNBq1yiDFX6PZzssrT9BmdXLVuHRGp0fxPgEZeFOX8sh91jiuzI3h67Z5zKsc778+E/pFB/k/yWUCV4xNJ0KnYnNRE/0TjVw9Lp13NhTTFa0WJxtONPL40iM43B60Shk2V8+n3rrjjXyyrZzbupZSnvcOJI8CSyMMXgQRaT2264qKbt/byr2ruO7my1ErZP6OkR6vyOtri3ju/MGsPFzH4r3VQdu8+tsJvr9lAndMl85fp8PNOxuKqWqzIvShiH5nQwlzByf6O3amRwd/x68al97jngkhhBBCCOGPQRTd4A285AqA0b2LE/ZtuLxNZERJ8Udtx5vY3dKzyCt2UtPxCkbND8GTOffT9dU8TCbDo+w94WZ1BSd56k3vUm96l6TwexkSuZBNDW8A4PLKUHY3ehF7T3TUdARiPplLIE1jpMregV6l5u8zz2ZM+pknOabkZvLKxfP4sXQ7FQQaishkMoxGIw6HA6PRSGRkIAazmKz8/M5qXA4X8285i+jE4PhsQ12J/99eUWRjTTGDdPF0KFqotdWSFZZFtDoai9OJu1NF+944QCQmLrZHiTxARlgWpZZT1wQiVVICLVwbxpXxgYSr3CBnwYwJvc7RHaOjRjOncw47WnYQrY7mhswbeoyZOCiTz5cakQ+TYkONV9PjSX6g/SRXIBFWg0Zm8Po3t1Kwp4i/q9b6x7hEDxuPVSG0KZnQP4MhGT07OwLEaiK4Jv4c/vH5Bl5r3UZHpxTfORq1VC7OZPTsYQweGVC9HT1Ry5c/7kalknPT5ZMYlp1EYUUg+drWavOXl/60vpB3XriQ1577gcb6RsQEL3JBRrQlEwTf/SSAPlLDE5OmkxhmoKKjnTn9coiO8EIXkbrN48DhdfFj5Tp+rN6ETq5FI/didyqx2DxoVE40lVaUn7bwaeG3jJo9lLzRUlwkk8nIysqitbUVQRCIior63etV0RrsZ3qwtIwJY0azs1WqfBBFqLO3sat1H2OjRvD3fRvYm1GHPEpAtCho1dh5e+dOnjh7JvcPlki28sY2ft51lFFJLsYF3CSoceglhR5wx2/LWXHJVSh9xHRyYgQdRXUoLR4Q4J6bJ/CnRqgkMIQQ/vdiYnYM+7qZReNTbbRanQjAX5Yc6vH3Sz/YQafDwy1Tslg0KpWMmDBi9CqafWVaOpWcVxcN7bEdwNTcWH7cV9Nj/faSFmQygVX3TOGNdUUs8Y2RC+ARITpMxdXje/fGmZwTE7T/RaNSeXLBALwiqBRn1irZ7fGyqUhSm03Li+OdK0aSt+4kr/mUMleMTSN/4Xzg0R7bvrzqBP/cJAU9H20p44fbxgd1PszrVgJW3NjJiGfXoJAJuL0iggAvXTCYRSNTmZ4X6/cM659oYO4bm0mO0PL6JcNIj5bMKW+fno3Z7mbx3io0Sjl/PWdAwF/qsq9h+X1g74AJd8MZkFWncM6QpF7Jo0+2lbGmsIF+sXq+v2U8n20vp6XTyfWTMjFoFHy4tQynjygZmGQMUrHFGtRcMyEDk83lVx3JZbB0X42/7K6y1eonnhrNdqpabeQnGAhTK3hvYwnvby7tcUwA6VE6TtSbqWixMCI9klu+2Mt+3/285WQTv949mTcuHca6Y43kxOn5YHMJZp9p/BjhGONKNnLB2CFw65UcqulAJgi0WZ1BhJVBrWD54ToWDElkQRfi86pxGX5VX268nlEZUUx+eT2WPkjVrmi1dGu7LFfC2C5ms43HoWQdROdAbrBBvtXpxuH2IuBFRIaAl3neDSRU6JmaO85fKgrQbnVxot7Mnd/s72Fyf7jGxAPfH+DdK6USkus+2d2rZ5jc5+WFz/+soKzVT1jdPTOHVouTvRVtjMqI+rc6cIYQQgghhBAMQVAgKvqDO9BoReF7Ue50SGVUJvtOGju/CNrO7WnlcN1ZyIUw0qOeJUw1GFTDfZSX9DvulWcTb7iu1/2Ga6bSbPm2x/p600eMTD1CjDqbJdVfUNhZyzKZwMURPjNr5VBQ996IZv7APJYfOo5HlPyVHh0/hel5WSjlcmRnQNYA2Dwd1Fj2E6aMZd6QgcwelM3jhz9kb9sJFIKcO3IWkhbfM9Hj9Xp5ZM5zHN8ldYFb88UmPjj4Clp9oGlJbngsh1vr/MvL39vNNmEtsTc0IMpEtHItj+Y/yrlD+vN1wSFqO0zIZTIUMhmTX/2AMRkpPH/ubDRK6RXyobwHeOvkhxw3lxGuTOD+3GvAp9ZJTk6mqakJmUxGUlLSGZFVp3Bp2qVcmnZp0Dq7x8l7J1dS2tnAxNj+vL/wJn48uhttuMD1o6exq6WQ3+oL/ONzDMHkYHb/JLL7J7FhVwl7WqR4xoiOf35fAG4ZH67ezb/uXsSwLCn2KW1uxeJ0MjAxHpkg8ORbK9hbWNXr8SbHR7D3aCUOp5t+qTE88MwPWKxSjH6sqI4v3rqOcL2W0roWchKi+eCrgGeTSiknLkXLP7+5A4VWRXFnNTGqCL7aVsh2Ap/HoFZxqKyO20f5W+vg9LrJN6Rx3CyxVmfFj6a4s4bPyiXvM7PbSpxBTlVlLJb2MOITbEQMdiG+b8TyTxsdzcENiBQKBXFxcf7lzs5O7HY7er3eb95/CtXN7UQq1DQhJRV1CgX54Xr6a/qjEiLpdJvwIsMryuh0W/mqeB/vn9wJ0eCKFlG67YRr7fxs3sjAohguzB1KU0cn17z+Le0WO58IGh6ZMoDJORWU1UfwTHnAG/dkawt1nWbSwqV3jyfvn88r/1xLS1snC84awvBBp0+EhvC/CyHCKoQ/FW6fls3iPdV+c+ZTyIwJI1KnYun+Gj8JdAoGjZIDPm+eh5ccYkhKBHkJBr65aRzvbSpBKZNx54xsEvvoYnbesGSUchnbipv5tqDK/zIsCGDUKEmL1vHqxcO4f3YeZrsLo1pJeYuF/EQjUWG9y7wNGgVLb5/I6qP1xBrUnDv0jwUCXq/ILV/sZZ3PP2tmfhwfXTOKu2fmcNHIFNwekbTovv0Q1hQGlFhOj5fNRU1BhNUFI1KoN9lZf6yRug67X2l0irARRfh4azmXjE7jmfMGcfH7O6jrsHOsTnpwNpgczH9zCxePSuORufmoFDIenpvPw3Pz8XhFjtWZqGixSIRW4lC4af0Zf3aA7wuq+GxHOVFhKp49bxAZMYH2t0v3VfP0L1LQvL2kBafby8sXDQna/qOrR/HZ9nLCtUr+cnZ+j/lPNpiJM6p5aE4uTrdIdZuNJfsCip+Vh+sYlGRk6b5alh+uxeURSYnUsuS2CRzv1r0wO06PVxRJj9IxNS+WuW9sxitCjF5NuzVwr7o8IsfqzZw3LJnzhkkpqf6JRu75dj8D3Ef5VvUCsqMeOAq0VzJkxmP+bW+ZmsVn28txuUXabS7u/mY/O0qaefGCwOd+YsEApufH0mFzMTU3FrdHPCOyCgjyieuB+sPwr9ng8mWrZz8PE+70//nBxQdZeaSe5xSf0I6e4UIxE+VHQX05t0zNYsvJZmwuD2qFjCvHpVPS1NmDrDqF1UfraTDZ0arkfRrcK+VC0Hc0LyFAvmqUcl66cEiv24UQQgghhPCfgPF5aL3IX6LX7vOfCVONAKDZ8n1Q+R4osLvL/SVhJ5tuYGjSLgTVaIh4G9H+K8hTCNPfgdC9LZkP6VHPolVmY3bspt32W2BmmeT9magbyB05L1Jjq0EtVyPI2kBsB+UwBKH3+GxEejJfXX8J+yprGZwcz+j0lD90GqzuNhaX34bZLcVnE2NvZXj0xbww5GZqbc2EKbREqnrvCtjW0OEnqwDqyxopO1zJgPEBJ+8nRpyFXJBRYmqmemUt2kI3+ls7EGW+RI3HxuamzVyRfgWPTZzEEx+vwqT1UOhTwK04coKitSe4bdJY5l0xAY1cw0P5dwFgsTkpr2mhLc5KpFFHZGRkkPrr9+ARPXxavoSjHSfpp0/jxsxLUMsD5/mVYz+xsm4vAPvaSnhy0KU8Pi/QZfDsxLFY3Da/h9U1mXN77GNXUSWzPCMZkZGJQiVjzYpK2txS0s7t9bJmfxFVje38eOQoO2qkuG1qTibvXnouJVXNQXPlZcZjszsZMzidsupm3vxiIwC56bF0+pLgAHWNJqw2FzfODxBNDouLz5ftQqmQc+05A2lva6W9rZWMjAwGhUuWCLdMHsOx+kZ2lVXhcXopLKznhsLFvHj1XOaOlGJPlUzBK8PuYFdLIWq5ijFR/dncdCDoOOUqL4o6FWGRViLipU7aggzCbtWSnJfe5/VobW2ltlaqOBEEgczMTL9Xms3p4oa3fqCuzYxCBTqtgidmjCRBr0Mmk7EgaR5fVEjqx1h1NGOihvH3qgBJJ5d5SUpsRS6X7rtv6n7mwtyhHCyvo90ivaN5RRkvbJxM7KrBiCqwDAjzf9+jtTpidYHYPSk+gteevKjPz/JnQ6hLYAgh/C+GViXnl7sm8dWuClo7nTR1OjBoFNwzKxe5TCDWENydLy1KS1VboKzLK0J1m5W8BAMpkTrCVApO1JtZfqguuOSpG+YNTmTe4ETGZUXz6JJD2N1eLhiRElRGmByhBSTSKymyd/LL4xW5+5v9rDhcR6ROyQdXj2J0RtQfPg/lLRY/WYWvbKu8xUpmTBhJfRBvdR02bvliL8frzITrgsugsuN6Bk+3T8vm9mnZXP3x7h4ljIB/jjfWnaSuo6dZeafDw8fbytCp5Dw4Rwq23B4vN3y2h01FTQgCPDavf5DXUV9oMNn5YW81WqWcQclGHv7xkN+b6tpPdjNvcCIZ0WGMyojk8WVHgrbtXtIJMCU3lim5vdfGF5S3csVHu3C6vchlAu9fOZLkSG0QYVXU0MnVHxcEbVfdZuOrnRXMyItjxaFA9vPWqf24aKQU8J7z1hZ/KV9zp4P0aJ3ff0mnkjMsJdjnYdaAeA4/NQfvut3ItnUJ9ItWQRfC6tG5/RmUFM5d3+z3r/txX00QYQUwOSf4M88bnMCvvjLSQUlGJmbHUG+ys+xAbdC4dzeW8F1BFW9fPoLx/QIeEWsKG2hf8S6LXF1KKw59F0RYneoW+K1nOh+pXiVBaIP8c2DY5YyUK1l97xQO13QwMMlIRkwY9R12wrVKOmw9uw95RDha28G03DgSwzW93ndeL5zVP45Oh4dLx6T2KHcNIYQQQgjhvx4y1UDE6O8R7WuwuFuwulpJDMskKfxuAJSy4OePUT0Jk2Ojf9nlacQr2pELWkyyAWzr3IzTW8sw4QAZ+t4NzmWCkgTjjSRwI5VtT9No/gKZoCPBeIt/jCAIpOhOkU59e+LUd5q55uclFLW2MCAmlk/PvTDohfpMUWre4ierAA62LWF49MXIBBkpurhet9nbWswzR76j02VDeUsCnvel57JGpyY+I3gbvVLNi2PmIYoi859/CRcgc+JTpEkUi14hqYrf/nwT3nY3hAUnROs6Onnr0e9JTI9h+CTJn7ShxcStT31LfbMZnVbFa39ZyND83yfrDrbUsqmuhCxjNC5ZNb/WSde0wlpDvcmGwd6fSWnpmEUrv1QdQNHlzfWkuY7ZicOD5rswdRoXpvaufvt4TQFv/CKRJlEGHV8/cBmlkTaOE1CZf/fbfpxqcEb5TwebTpaxp7KGCcOz+HWz1Alao1bw9J3zSE+KotPq4Kwb3vbPUVTRRIRRTafPTqJfRiwRxuDY+tZLJnH9BeOoKC/H4QjEIp2dnej10vnXq1V8dOUFPPPtWpZsl4znRWBFwXE/YQWglquYEjfMvzwiMo8kTQy1dolgOytuDJ3Do7EomqghoBATgZnvfsqA+Hjeu/w84g2BhkWflq5jffUBEmRGLjaOQiNT0tHR4Sesalo6qG8zIwByJzicblSCnPj4eNRqNeckzSLP0I9WZxsDjXnolWFMS8zm62IpzlQpXH6yCqBDbMXhcZIRFxmkdA8f24yQYkcAhns0KC25KAQ5D46bhFYZsmToE6JIDxPe0439H44QYRXCnw6xBnWwAXgXTM2N5bZp/fh6VyUxehVvXDqcdzYUs9JntmzUKPyeOc//WsiXOyUJ7u7yVmINaj+x0BfmD05k8d5qNhc18f2eKlotDj68etQZq6N+OVjLisMSmdFmdfEfPx5mzf29tyc+HQwapb88D58nlEEj/Ry0WZz8ddkRypotzB2UwJ0zpLKn51Yc45CvG2GT2UF+ggG1Us78wQmcPSihz31lROvY0qVEWhAgMzqM58+XSvfsrtOrdE50URxtK2nxlzGKIvxt1Qmun5jpL8mrarXy0ZZSZDKBW6f2I96oobSxk7lvbvFft9x4fdBvc3mLlXc3SuWNefEGLI7g45mc8/vGqF3xw55qf7mgxyvybUEVH149ksb6WsKOfIHdLfJu5zQc9FSwqRQyLhyZgk4lZ29FGyPTI5nbxWC9u19SfryBSdkxiMAlo1I5VNPOq2tOkBUTxu3Ts1HKZchkArKEbs0A4oKN/IEeRGVyH8SlHw4zby1I4ZwhSTjcHs4emIhWJWWxK1qs/m58p9BicXLPt/u5/6xc8hONRGiV3P7VXs5Hz6KuH6ubn9WwZANrT7RwRMxiovMdlt4yiiEZASP0tGhdkBowIVzDktvGs3hvNRFaFV/sKKfWR0ypFQI5cQZkMoHPrh/D8yuO0WZ1cKg6QEo6PV5GZUT1aLQQQgghhBDCfy8E5WAE5WAMQPc0WFL4XdhcJ+l0FBCmHkZ61HOcaLgUp0dKBmkUuTjdVWhVufxS/R+0O6UX81rbES7P/JgIVXIvewwgwXgbLZaVuL31VLY9gSg6STDeeMbH/vqu7RT5zLALm5t4u2AnT0+d+YfPgUZu7HP5SHMDz+7YgMPj5u4R45mRJj2nnjj0Ne0uqSzLfoGOIZYBqMs8XPXEoh4eVqdgtzrJy4hEO2sDSSOb8HhllNrjSAsbydkJZwMSCQGgMom49L4AziOiL5FUOpVFdX7CavGq/dT7ysusNicf/7iTN/4joHjZVlXBLydPkGoM56bho1DJ5Xxz9ACPH/rVTwzNyw5OGu9oKKKkxMw/9+0mOkmOU65ArwjEaKOje+/i3Rd+2B6w/Gg1W1l/qJhHLpqOw+mipL6F5jozFtwBpqoLVHI5j950FjnpsTS1dTJ7Qj7pSVLCWKWUo1IqcLrcklwlw8FZ8/NxHZURptRw6bmj+GzZbkqrmpkwLJOzJw/wbadAp9MGEVZqtbrHvhMjg78NCZG9K+xOQSuo+MewuyhoP064Moyx0QNhkOQ/e+7PR9DFtSJ6ofZ4HIgChfWN/PWnNZydncO4vDT224v4sERSHJbQiABcFTE+yNw/KcpItEFHi1lKOMaGhzFp9HB06sCYHEMmEGikNDM5h39NuYTtDWWk6MP4umYJHp9qMk0Xj1quIjsxhpevmceXm/ZjFS20pwQMuprlzbwz/WpyDaFmN//b4PV6aWlpISYm5g9VBJ1CiLAK4U+DRrOdJ346SnW7lfOHJfepzHn47Hwe7lLm9eZlw3lr3Une21SCye7m9q/28dSCARyvCy7dOt6LEqc7Spo62ewjXADWHmukus3Wp2F7VzSZHXzQzduoL7P23tBhdbGjtBm1QoZeo+Txc/rz6mrJY+mJBQOI8XVXe/ynI35S7GitifToMBYMTaK1W6nkxOyYXrsidsU3uyv53Nep7RREER6em0+cQaqFv2VKPzYXNWGyuzFqFIzLig7yJVLKBSa+tB6z3cX8IcFmmAq5wKnfPYvD7S8tBNh0oonV903hkR8P+ckqfOqmCK2S9l4UOLUdwUqwYakRPDg7r8e406G7Si/WoEZwO7iz4m6wHwdgkmor5zufxUOgTGFoSjhXT5A8y+bm6pnb+BGUN0PU1ZAs+S49fe5AbvxsD+U+VdXqwgZ0Kjk/3DqBBpOdO78OKKTe2VDC+1eNlDoIDr4IOqrg+K8QkwNnv9jjuEemR/L4/P58ul0qlXz5dKVvB7+DZXcg97oYnnURJ8a+GOSd9sFVI7np8z0U1pn8XRgBGs0OHvnxMDIBbpqchcsjspip5AtVzJEXkNhvMPL5rwb24/Xymut5XpNnUC9GcWF0BUNSenZ66o7sOIO/u+Z5w5L4++oTmO0urp+U6f+u5cYb+Oz6Maw6Us+tX+4N2r5rKa7V6cbh8hLZR3luCCGEEEII/zmIzgOI5r8BHgT9PQjqnobJcpme3LiPg9YNSFhKRetfabOtwu4u4mjDAvLivvWTVQBe0UW7s+p3Cas2q0RWnUKD+dMzJqxE5wFuSH+di+ItvHZ0NDubkrG6esYYfaG8vY3C5iYyIt1EamPoHz6PE6Y16BUxzEh8CHzlateu/IFmm/T8v3XNMjZeciPxYXrM7uDY5cpXL2VibM/EVFe88fC3mDw76DdSiknlMi/DDALDjZcj+F4Pb7xoIq98shaVGTJdkYTj5fCJchqnh6O0i+xNtfLEt2+gV6qYLAsmERSKQHxzoKGOa3/5EbevzLPS1M6L02fzwtb1EB7YprTVi1YvIPpSnO3tkkJNBOxuN1anGo9XQKHwcnXWJMZE95587gsxhjBqWgKxerQxDJUMrh/fD1HM4v5/bMDmKzpTWMAdJnFXl44cwvBUyddq4cxBtLS0IAhe3G43CoUClVLBE7efzQsf/IZjXDNipp0l1s1kDIrjo7F38dG3O/h6ueTFtmb7cd7/agvvPH0JSfERJCRICV+73Y7BYOi1hPKaGSOpbGpn98kq+qfGcfeCiT3GnEJNTQ1tbW1Y7S5cZhWGtGjwCdsFQeDJYbfz6K8/09hhw+EIxG1bj5Wzq6Acg1bNvMvig+as85iIiooiKipQ0aEQ4NF5I1iypxhBgGunB5NVfWFaUj+mJUlE69DYWH6o2kiYXMP1WfP9Y84anstZw3N5dskaNrmPICh8caQI4cqAarHNakOtUKBThZRW3fE/pSSwtLSUZ599liVLlqBWq7Hb7dx+++288MILyOW9l2r3hhBhFcKfBn/54RAbfebeR2pMZMWGBbWs7wuddjeL91YHvXj/uL+Gs/rHs6dC8sERBHotEbM43Kw91oBBo2B6XhzhWmWQ1FUpF9Crz+xr+ODigz3K066bmIHHKyKXnZ6tbul0cP6726hqDQQ1MXoVP9050W8ofQolTZ29Ll8zIZ3d5a14vCIGtYJFo4LVZC2dDl5aeZxGs4PLxqRy9qBEthUH1/ufwi1f7CU6TMW3N49jcEo46x+cRkljJznxBnQqOaOfX4vZLmX2fu3SufCb3VXMyI9j/fFGlHKB584f5Gfqy5otQSVepc0W6jvsdHbrRKhTyVk4PIkjNSZSo7T8uD9QvjY8NYLj9WYazQ7ijWpeu3goHlHkUFUHEVplkNdVX7h9ej+KGszsLG1haGoEf5mTBy1F0HTcP2awrJwkoZk6IYER6RE8Pn8Ag5LCA+bt318jmZADHFoMt22DqEyy4wxsfGg657+zza9gsjo9LD9U2+M4nB4v93y7n/UPTOWb3VXI5Qu48so7MWr6frDfODkriMj9fk8VB6vaGZcVzbS8WN7bWEK7xcFzx+5B5pWC8cTSH7jveD5f5U/ng6tGIggCcUYNy+6chNnu4sL3tlPUEHxPeUXYV9lGjF5Nc6eDZ91XsT7jXr66ulvZRkcVxtrNPKXcLC2bgab7IfHMfaQUMoFJ2TGkRGoZm9WzZfWARCMqhYDTLX0no8JUxBrUzHx1Ix02F+1WF26vyOVj03hh4eBe9hBCCCGEEMK/C9FrRWy7WfKGAsT22yF2PYLs9+0OWp0t1Fi2ovO9d4uig3brKpJ1w6ixSj4+Gnk4cZqexIbZVUed9SCR6gxiNfkouu1PIT+zcnDp+G8iW98Benh/wmoWrLuWC3MGntH2u2qquebnJfRPLGZG3lEEARK0A7g55xcUsgABYHLa/WQVgNPjodpsIklv5ILU8Syu3AZAtj6REVHBCuEjtQ28t3kXMpnAPdMnkB0bzYHmMnSjg4+l3tLGwtVfMyw+kW8WLuKCs4YyalAqbR1W8rMSONrUwEVLv0UErDKRz+skxVKH086vymKGpMVQUtlMdEQYt106yT/v7ppqP1kFsKO6CofbjcPqCSKsNK448pzpeDQd2B0a9rUESiPnJw1gWe1hbA6BMcZU7sifSafZTmVFM4nJkURG/n589vQVs3nks5XUtZqYPzqfOcNzaWlpQfTJ7i+akctnK45iF0R0ciWzcnO5c/4E4sMlRZPH46GsrAy3W4orOzs7yc7ORhAEZo7LY+LoTGau/6t/f+WWRo62V3LweHDjpYZWM29/tolrFo1jY0ExibFGFkwb1KfyRKVU8OyVc/zLdpuTr/65gfZWC7PPH448TsvnO/cjR2RGQhQyL7z4yU6afHYc91w1jUvnSYnPUekprLntdo7WNXD1pz+gULUxYWghatwc2t+Pmqo43A0qZDKp1Q3AzLThJCUFNyiyWCwkhmu5c6YUF3Ut7ztTRKnUzEnMp19YP+I0Pb9vI9JT+HldNIYhbQgykWHiMJZvKWbx1kN0qtw0u20o5XKeWzCL84aePoH+p8P/kC6B69atY9q0abzzzjvodDr27dvHzJkzMRgMPP7442c8T4iwCuFPgx5ETKOFGT39snugN4+lpHAtd87IJtag5kSDmWl5cT0IK5vTw0X/3MExH8l06ehUXrpwCE+dO4AXfz2OQibw9HkDT6vc2HqymZdXHUcQoLabD1R0mIrnVhzj0+3lfHnD2NOSKauPNgSRVQDNnU4+3lrG891ewmcPiOd4vaQeU8llzMiX/A/OHpTI8rvCONnYyYi0iECXPh/u/Ho/O0olOfzW4mbeu0JgfRefrO5osTj5cEspf7toKDF6tV/hVdtu85NVveGq8em8dOFgtEo5hi7kS2qkjgidknarRKTEG9VE6ZRcMTadx5ZKvlQyATRKGZ9sl1Rfx+rNPDg7lzXHGsmI1vH0uQNRymVUt9lIidSikAtc8eEudpe3Igjw1IKBXDOhZ+fGJXur+ce6IjQKOc+eP4gPrh4VPEBIApUenNI9aJMb6BDCMWoU3D0j129Y73B7qGq10q9sc0CQ7rJAzV6ICsiqE4zBnVoSwjUkhfcs4TPb3Zz79jZqO+zkCZXU7XXz1B3XIdfoe4ztjk+2lfnN57/aVUluvJ6ihk5keHla7aQrR6rEzZrCBsqaLWR1IUANGiVLb5/IbV/uZfPJYPIyOULLq4uG8d2eSvRqJdf2cl7RRYPayEmbgXIxnuHKKmIMfZefdkddh40Fb22juVPykXhsXn9umpJFp8PNj/uqEYALR6bwxfVj+XxnBeFaJbdOyWLuG1t6GMp/vauShcOT/y3PuBBCCCGEEPqAt9VPVgEgWsFTD2dAWK2r/ztRougnrABUimTmp9zLwdYfcHg7GRhxDjpF8FytjlKWVd6J02tBQMb0xP8g23AOFvt6TNYViPJkMqNePu2+97V8x/GO1cQqw5ip7PCv1ytdZLRauOXVHxiXl8ZbN5+HStn369aXRw7g8LiZ2O+EXzFebyukvHM72caAF1OURsfohGQK6iXyI9UQzoBoKT67N+9cJsb0p9NtY2x0HtouRuUdNjs3fLGEDrv0HDxQVcdfLxtD1fU2FLJYMh3NRKpteEXYXipZQBxoqGNVSTHn5/UnLTGKtETp/JWZ2gPvtt1kGWaXgw+eu4xOk4MIozboMw+KC04O50fHolEomJ/Sn+UNhXgNHsJENUcaWtknl4itYVE6LhkwmGPNTUxOS+eBsRN50DGVNoeVLEM09bXt3H/757S2dKILU/PS65fTf2Cwis7r9fLB0z+xbdUhkjNjefAfV/DdX64IGtO1BG9kdiz7a1o5ebiafumx3HX/ZcT5yCqz1U5VfQtOhxOFr5GMw+HA4/Gg8BlrqWQKjEodJp8vp4BAtNrAoJxEjhYHvElFAfYXVbP1iW9wuaVY42RZPQ9cf1af90lXvPzoYnZskJKgq1bup+mcGNrt0nvKtnA9uXoDJ5JtyOLAUA5fr9jjJ6xOYWBiPMtvv5pf6m7CiRSrJyS0svib6Qw2ZjI/bwA7m0+QpY9nbtLIHseg9PlHFVW24nB6GJ5/egVjdxxsP8hbxW/hET0oBSUP5T1EjiGHGmsT21uOEKeOYP6o4VgdC9hxooLcpFiGZCRw27tL8SrA5SM6XR4PTyxfyzmD85HLzqxLegj//+Gmm24KWh4xYgQLFy5k1apVIcIqhBB6w+wBCfxrq9TGVqOU9Wma3R3dzZtj9CqeOW8ggiBw6Zi+26buLm/1k1UA3+2p4poJ6by1rhir00OcQc2QlAjcHi9NnQ5i9OqgbmrtVic3f7HHX/anlAcYArlMInzwmXX//bcTvHP5iD6PJULXu6pGregpx7x/dh4ZMWGUNVuY2T8+qPtf/0Qj/RONPbYBycz6FDxekWUHaoNKFg1qOSPTo9jYpSSyaxnZKcQbNQxMMnK0Vjp3YWq531cqL97A2MwodKrgny6n28vra4uIN2iI0CqRCVDabGX4s2sxaBTIZTAkOYK7Z2Rz3Wd7/Nt1OtzoVAqW3REsrz7VGW7VkXp2l0um35Jn1vEehFVFi4W/LDnkV83d/Pke9v71rODOeLoouPRrWHororkOp9vDME6w2TqUe7/bz57Hz6LRZOeSD3ZS1mxhmSaToUjlml6ZEndMf7rSmk+fN5B2m5Pixk5m9Y/nirHpyGUCL184mOdXHMPkI/xEoLbDzjXy1Typ+ByZWcT14ZfIb1oDmt6v4yls7UYwnfSppLzI+Jv7Eh5VfoMMkY2eoWz3DkQm0KtaMEytoKMbAZkUruGx+QOINah5aM5pWGO1nhWjP+OetZ24kRMjhx8detJ+n28DYOXhej9ZBfDFzgqunZjB5R/u9Pux/bi/hsW3jPerr2rbbX12P3S4vL2uDyGEEEII4d+EPBEUg8Dta3gizwTF7zdTAXB4TJS7Y5ALXrSCE516PHH6KxAEOaNjrupzuyLTbzi9kueTiJfC9mVkK12kuH4DJaBMRFD2w+O14fGaUMrjgtQvFZ272d70PgBtTpGRRiMRMilmqWmPobBKSiDuPFHJst2FLJrYtyo4Qi0loDxeORB4Vsp76UL42dyL+LLwAHaPm0vzh6Dv4ik0Ojqn1/lr2k1+sgqgqdPCL9UFIIBblLOmaQCTVJHsrVFTFPAeR9VLuc6Y5BT0ShWdLid4BIwKNSa3NPei7MHolCp00cHHXd9h5tvNB8mRRyI3yGl32VlTVsyID95Ff9BNjEzF9PF5GJN0vH80EJ8daKnnkwsuIEITSMbFaMKI0Ujndun3u2ltkeISq8XBN59v45mXLw7a95rFu1n2iaTQbq5r5+3/WMxTHwe/QBsMBuLj42lqamL9J9so3nwCAShts/Dhw1/y2Nf3svt4JQ+88zNWh4v0WAOPXDCStg47coWCgV3Ok0yQ8eLQq3i58EdsHgfXZs0kUx/PHZfH4HZ7+WnNQTyiF2SCvxPeKWzac5JLZvcnJeX3jer37Sjx/9us9PrJKoDSTjNFChOiL3T3qCGnXdPbNMQYFDjrAollhcLLORNiOW/sQGQygZFRfXt56vV6lm2pYPlmiTgbklvP23/th7KX94resLFpIx5RirVcooutzVsJU0Ryx97XsHikz1NkruamiQv8359lu472Opfb48Uripx5gdn/ffxPKQnsDSdPnuyh2Ps9hAirEP40eGxef3Lj9VS22pg7KCGoXf0peL1ioCzLhyvHpbHqSD02lweNUsY7l48gztj7j39XRHdTThk1Sj7aUkajWXq4N5odvPpbEcfrTJQ2W0iO0PL1TWNJj5Yexk1mRxDh4/KIPDg7F4fbS1mzheVdOsk5fse4fO6gBC4bk8riPVWISCWJefGGPjsbXjDij7VhxudpdcqcXi5AuDb456V/UjjPnj+IKz7aRWWrlazYMO6Y3tMwUy4T+PCqUTy69BB7K9qJ0au4a0YaCUYNM/vH9SCrvF6Ri9/fzoGqjh5zOT1eP7G3v6qdOlPPrnCnzOZ7g7obodYbwdZgcvjJKgCT3Y3F4SZC1y3YVOrAXIsAhAtW3lS+zTDHh5hsbkRR5ONt5ZQ1SwH0jfZ7ecH4I3J7K587Z9K0uJXvbnH7CaF4o4Zvbx7f41guGZ3GgCQjC97aFrT+TsVSZL4nkrLlOBxfDsMu7/NzAwxMMgZ1kkyK0Pq7PX4qLuA3xygMWCkUM/Ai49pxGb35lIKvmcHBLibsV45L7+H11Rc+PKHGjbTfZjv8sLeK+8/QVyym2z4MGgVlzRY/WQWwv7KdLSebGZURiUGjJDFcw8TsaLYVtwRtOyU3lnFZIXVVCCGEEMJ/JQRBDlGfIVq+kjyswi5DEIJjLFH0Igg9n7/Doi5mW+N7nHAkYlQmsij2HWm+34G2W7mfRh6BaH4Z8CUoXXuwmt/geMfneMVOjJrJ5MR+hEyQnikdrkCJl4jAr9Y0rkiYDXh57CsBpycQazicfSvGAe4dO4FjzU2sOz6Y+YMPIJe5yTHO6LWzoU6p4uahY37383VFenQEiUYDDZZ2EjOaiTIoidVGge8x6BFlZCePZlZaP+5avRyry8XsrGzmZPWMz1KN4Xw091y+rv0Km7yG9LBUslUziFZHMTOlZzxpc3fwweF7ic9pwlYdz6bjA3D5Qu92lx1rEkQdhc2/HuPqOyYFbyyA9zTdy5TdYkGVqmcs11wb3Pylqbat17lEUcTr9WIzB8eInW0SIfb2j1uxOqR7o6LJzJvLDlHiS+rtOdHGIzfN9m8zLDKLbyY+GHysCjkPXj+T6IgwPlgcHJ+dQkJUGO3t7cTFxQWZm/eGfvmJFB6QzMhVNhGtQoHNV6YYZdTSQKB01K2H2y8Yj8VtJ0wR/L1SyrQkagdTZ5M6EAqinnmjZ/Z4D+oNNrvLT1YBHCqq5XBRLSMGnJkhergyPGhZK4Sxu6XQT1YBrGvYy+yEMSRpo1HKFEzITyfGqKPJZEVwgug7TXdNn4DyD/gh/Snwb3QJNJmCbWfUanWPJgBut5vq6mpOB71eT0xM7w2rPv74Y3bs2MGmTZvO7Nh8CBFWIfxpUFhn4s11xdR12KhqtfL6JcP83k/rjjVw33cHsLk83DYtm3tn5tBhcxGhUzIyPYrV907hSG0HA5OMfkLp9zAoOZz7Z+Xy/uYSDBolr148lKX7g+vYT9RLZBVATbuN19cU8Y9LpRa9GTFhDEg0+n2rBieHc8vUfijlMsqaLewsbaW504FereiTeDoFQRB48YIhvLBwMF4R2qxOonSqM3oonSlev2QYHbYCtpe04BHhm4Iq5g1OYE95GymRWv5+0RBKmy3MH5xARkwYF41M7dV76x9ri/jH2pP+5U6Hmw82l7L38Vm91vd/v6eqV7KqNxyt6UAmSB5K+MrSwrUKHv3xEP1i9Vw3MTPomKbmxnLu0CR+PliLWiHjxQt6ehgNTg4nL97g72Y4q39cT7IKwBYcKBmwIsfDDZP7IQgBk1GAJiK4y3Yj9lOKnloTS/ZWkZdgxKhRMiCpb3VUTpyBtCgdla1SwJJg1OBx68AbeBAtLezgyx3bGZYawcNn5/dKxN01Mwe3V+RQdQdjM6O4eFQqf//tBO1WF1eMTePvq09wxHdvGjUKPt1Rzqc7yrlxUiaPdzPjv29WDjqVjDd96sK/rT6B3eU5I+LJ2K0zYvfl02HBkES+2lnBrjJJJVfRYqXT7kajlPnPrQBc92kBEToln18/hiEpEXx87WiW7a/F5fUyJDkcjyhd59/zigshhBBCCOHfgGMNWN8D0QMyA4Rd7f+T1/w6WD5CFHQI4X9DVE/EK9pRyIwMj1pEonYQFnczybphaOSn7552CoMiL6DDvodW6x5Q5jAx7m5o2xo0pqVzKV5RIixM9i20WJYRq5cUPGlhY1DKdLi80nM23TADQX8rAFfOKOLo5ytxe7xkxEWyYMzpvXWitTp+uOgyRPFSPKILl9eGVhF+2m3+CMJUKr64bhEvHH0Jm0pqaNPoamd89GCKzI2MiOrH5elTOGZez5vnGkjWjCY/clCPeZwuN/d8+DMnxb2kjpF8M4stJ4hUGbkk9fZe97258S2iYiQLhqH9y2hxhLG/Od3/d9HHMbgR6Sg2oWoHp08ZdGFmf34+fpyilhamZWQyOzuYQLv4ivHs2VVCeWkTcfFGrr2pZ8fsSfOGsuSDDdgsUqJ41kW9k30ej5T0zV8wmA1HyqGyA43Fzfl3zpWOs9t7f1F5s1/Ns2z9Yc49eyC2MBvJ2mgStH17n00e2Y9Plu70lwHmZ8Zhs9mJidBy+Zz+dLgdPFSwgnqbmYWZg7m03/Be53n81Uv51+uraW+1MO+i0ehyI/jX9j2oFQouHjOYG35disXlAkSGDHDwVP17qBqVPNL/CibHDg2aa0HKCywr/4hVJYfZX53KG/af+dc5C5mc1otNQxcoFTI0agV2R4CQ1evOLBEJcGHyhewoLsSmbcFWFcbqn61cd0dE0Jg2p4kbC16inz6ZV4beQWy4nq8fuJz1h0uI0mtJiDNi0KjJigklE7vj31FYpaYGk41PPvkkTz31VNC6mpoapk2bxulw0UUX8corr/RY/+uvv3LbbbfxxhtvMHFi340Dej9G8Uzpt/8amEwmwsPD6ejowGg8fUlKCCH8V+K8t7dysIuy4pVFQ7loZAper8iQp3+js8uPboJRQ73JzoBEI1/eODaoa9iZ4ni9ics/3EWrT+EjEyAnXk+7xUWD2UFSuIYR6REsPxQwFZ8/OJF3rgiU9pnsLr4vkLrdXDI6Ncizqd3qpKihk4wYnb/j3n8LStZDxXZsccPZrx1LnEFDdlzvNVkXvredvRUBYuYUedFqcfJdQSUvrzrh/9vfLhzCxaODfxzLmy1Me2Vjr3Pnxut56tyBTOgXzNr/ffVx3tlQErSuK4F0Cl2JqlMYkGjgWL3ZH4zcNDmTx+YPALsJKneCMRESBtPS6UCnUqBV9Z7BMdld/HKwFo1CzrnDkoLLAU/BacXz8dnI6w8C8C/3XIpH/AcvXiBJnbuWBEbqlISpFVS3BXzHuhNt2XF67jsrl2GpET12Vd9h519bSxEEgRsnZRLXUoD43ZUI9nbWq6Zzg+kGRKRjHJsZxec3jAkuDzXV0fLDPWCqQzn6KowTb+6xj3ark4+2lNHpcPPZ9vIgz8Zf757ElpPNUsnigHjmDEzg292VPPLjYf+YGL2KPY/37dfgdHt5+pejbDnZTKvFQafDg1IuY0xGJG9cNtzvefZ7mP/mFn95KcB9s3IZkhLOiyuP0dzp9H8/AablxfLpdX8se/1/HaFn9p8HoWsdwv8LiN4OxMbxXcrhBITYDQjyJETnQcTWRYGxaDjgcuIV7USHXUhm1Cv/Vot00bYUb8d/IODBKcrwokCpGo7cdQBwgGo8R+1l2N2V/m3SI58jznClf7nVUUGpeSt6ZSx5xrOCjqOmpYPGjk7ykuPQqf97OpiJokhbWxsulwuHSk6VvZOciBjitD3jM5fXxc17g5/j9+bcy9CIoVR2tLO15V9U2KVGLwpBzXVZbxCjDra8+GHbIZ79bh2Jo2tJzA9YBtidYSicE3h5zDkkhQX/biwuv5MGe6F/+dDxXA60DKXJZkUmgvE4eBVgzpZ8ncKqQdsg+RkMmJrKlo6AkuOj885nRmYWTqcTu92ORqNBoVDS3mYhPFyHvJfEG0B1SQN7N58gJSuWkVN775xot9tZt+8Af91YgNXlRikIvDBtKgumSIRR15LA7KRoKoua/EbVytEdqEdIcaTboyBziYa8zlhuefUaIuN6Eo8HT9SwZvtxEqINXDJvJB3tbRTXVPF9UxHbzXU0OQLqqDvjJnLfjGAirsNsYnX5ThBgTsY4wvU9f6sLmxtZcuwoDmUru+wBIjZCqeeD0Y/wSclmrG4Hl2aMJ9sQzz2rV/DzyYBaakFOHm/OOafXcwXQ4mjhs4rPqGqvo7RARREGlNEKFmYP4smRc5CdwXfS1Glnzk3vBK3755OXcFhTyJqGAtqdZqyeQCnrzVnnsiht+u/O+2dCb8/sU+vGz30GhfLM3g3dLjs7Vj5BVVVV0LO/N4XVv4tVq1axcOFCXnzxRe69994/vH1IYRXCnwbdvahMvmWX14ulm2S73lc6Vlhn4v1NJTw67/TtgXvDPzeWBL0Me0U4Ud/JnIHxPHx2vr/EaldZG01mBxE6ZQ+l1Jc7K1h9pJ7MmDAWjUzlZIOZR388TKvVybUTMrh6/OkzIP9pHF8B316BWdQw3fEqzewC4NG5+dwytaeqKy/BEERY5SUYOFjVzlX/2uX3VQKREcJJSvY1w6irocuDze7uu7SxqKGTGz/bw97Hzwoijs4emMiHW8pwuiXFzCWjUnh+4WB2l7cSplIgAg98f4CSJkuPObsrZreXtIC1Ff51FrQUS/qbeX8nesxNPbbtCqNGMnc/LVQ6Vo/5hJ9++AIzOnZ4BxJ2oNZPWMUZNay8ZzLVbVYSwrUcqGzn1i/30ulwo5ALuLt0qaxpt1HTbmNfZRvbHpnRo/Nfgs8jKnCAk3l3zBre+u0Idnvww2dXWSuPLT3CK4ukrJvd5eG39x4hz3KUPFk1rHmI1vB+rLRks6WomQFJRm6f1o8InYoH5+TRZnHy6fbyoDlfWnmMzSelkrrFe6tZODyZOQODTVfDf0cp9f6mEr7aVRm0zuXxsq2kheeWF/qViL+H7qWHsQY10/PjmJ4fx0srj/PPTQGyM6SfCiGEEEL4/xmiNci7CUTwmkEOiKZuY+14RSmuarEsIVq3gHDt6bP9ve7S/CoCUryhEryAE1y7wPAwgvoskKeQZF1BWcv9iLjQKQcQHXa+f3ur28H7xbsp7mxlfEwseUbY07qHn2p/QiEouDztcoZn9exM+F+J+vp6WlpaOG5t5jPzMjQqKxa7kZeG38eQmGB/GKVMSbw6ngaHpLBSCAoSNAl8efAgT21czyWTtqL3WUW5RQdF7buJiQ8mrBwuNx6dl1qtjjivgFzmJVnVjlrVSJ2llcf3uPh46jVB2+QaZ/gJK1GUc9Poa8iJHsbhxgZSDOGUlzRx067l/i59lhTwykFfDdXu4EZJO6uqGBefQHl5OV6vF5lMRkZGBlHRpze1TOkXT0q/03cE12g07Gw2YXVJ96FLFFlZW8kCpDhjTH4aK166kRaTlZTYcL5evof3v98KRhfqEVJyVBBAIXdzYrqLk2/W03TFG7y65oke+xqal8zQvIBBeUxMDPceWs2O5ooeY/+1dTd5ujjmjZPeQUz2Jp4/9hpHbWbsXhUbOg7x8og7+HDbHipa2zl7QC7zBuUxICaOAZPj2NR4gF2FXQgreSf/OPQia5pdiDLY0LSTO3PnE6sLQ67woAu34fXKiNKenuj4qOwjjpuPgwBRYyCsLok2axhfFu9jUFQii7KGnnZ7AK1GiU6jxGqX3sVkgkBkuI4rE2dzZcZs7tz7OifMXWLAUID2x/BvdAk0Go3/Lcmq3377jYULF/L888//W2QVIcIqhD8Tbp7Sj8d+OowoSgqVc4Ymgs94/LoJmXy8TTJkN2oUXcgVsPXhD7Wvso3X1xQhlwk8ODuPQcnBmRRFbyoboNHk8HdS6xerZ+39UylrtpARrQsqJfvlYC1/8ymSDlZ34BHhWJ2J4kbpIf7EsqMMTg5neFpAflzXYUMllxF9huqT38XxFYDI39yX0ExAyfPamqJeCavH5/dHJkBRfSdT82JZNCqVmz/fE3Q+J8qO8JXqRagDftwCF37k/1t+gpFJ2dFs7eYfdApWp4fFe6r49Ugd8UYNj83vz+CUcH66fSJbTjbRL1bPrAFSYNJVidWbMkoAFgxN4lh9QPU1KCkcjv3sI6sARFybXkH5O4TV76G82cJffjhEWYuFJm+gj3RXxRzF69BseJ5smQJmP8eknDEUPDYLk93FjFc24vb0vA/NdjcPLT6ITqXA6fEyMi2S6yZm9Jpx3lXejp3e74sdJS0gilhdHi55fyeH2y4GLuZxxRfcqFjJR1uKebdCInFXHa3H6fby4BypnC8yTMUd0/v5VW4apcxPVp3C0v01yGUCKZFav2qs0eyg1eIMVi+aanHt/4bNFXaW1Xfrt90Fpwhl6g7CiZUQlcXByNm0WZ2My4pGowxc72fPG8Sd3+yntKmTswcmcIlP1ef1ipwzJIFVR+oob7ESFabigTP0xgohhBBCCOG/BoI8EVGzAOy/SCvU00DhMxBXjQHlEHAdAqDJGxxXecSevpQAovV7RNsykCcjGB9FkHUv0+rj9cfbgaCQiJrosAUY1KNwehrRqfL9/lUAbxctZ3mtZBB+3FSNXiFjbdO3fhPpN0++yevDXkcpU/qO00OLowWj0ohG/l+jiD/lN7PcupYYo+TVpNc0897J73gv5r4e4+/LvY/vqr7D5rFxdsLZxGvi+du2xXhFkXZLGHptQM1ib5LRqmwlKipQanXO6AG8XbiNRreafdVpjIovJ8EgHUOk2kZZxxb+vqMfe+pqGJGQyAPjJjE06gLCVUm0OspJDRtJrEa6rqfKzaIH6/DsDH6rdusEvLkqJmVnUHbwgH/9wLg4WlpacLs9HK5tod3mZKKgZFj/3s3mzxTb9pTw3hebqdbZoMulMXRRljQ1NdHR0YFSqUTAyDXnj+X8WUMotdTyl2Nv+8cJAiDK8GRGciijgVcKv6WjRIOrVcWC0QOYOKD3JPOe5qqeKz2gaJOx50QVc8fm0+os54eKe0gzdpKol7G9tR9FzloeX72C3w5K2685VkykTsv4LOkeHh8ziCHh/TjUUcIEfSOPJ+9HLri5PjaMByrH0+FR827xj9yUeT7JNhNuQSKP6tXFwKygw7FarZS11rCqvYASe3CSUqtwcSpVXW+VCDyTyYTNZkMbpuO4ow6VTMmwyEC3a6VCzvP3nsvLH/2G3eHmpkUT/N0onS43F8bM4HXrN9g8DnL0KcxL7OnbGkLf+J9iur5hwwbOO+88brnlFi644ALKy6V7R6FQnFGDgVMIEVYh/Glw+dg0hqaGU9tuZ3RGZBA59MSCAcwZGE+nw41WKeemz/dgcXqI0at6dIUD6LC6uObj3Zh9RMzh6g62PjwjiBi5Z2YOO0qaqWkPDqguGhX8BQ3XKoPKujpsLl5fU8SWHl3azFS1WoPWfVtQyZ1f70evVpAapWXtsUZkAjxxzgCunZjJH4Xd5UEllwW8raIlz4AOMdi3qy8jTJ1KwXPnB/s8KbvJtPOFLg/mw4uh4ZhE75/1NOScxQsLBzP9lY14+vgBffKXo35VVH2Hne9uGc+AJGOfvk4er8hdM3K486t9uLrUBIo+BdjzCwfx29EG+sXqeWhOHi37jxLdZfsys5ydO8qZ2T+e5Ahtr/v4Pdzz3YEg03EBCNdJvmYAdDbCd1eCrxUyny2Ah0rQqvVoVXIenJPH078U9jr36qMN/n+v8BnxXz+p57UfnhrB5i4dGrtikLoBnotnLZM5bLnev/4N9wVcJl/PCSFLykD7sK8y2I/roTn5XDgihbc3FPPjvmCftlPYXtJMbZfvgtnu5tvdldx+ynjf2gofzUJpqmEm4PWM5CYe8I9XyATcXhFBgEUjU6H+MPxrNrilOTe7z+dV98UMSjay+JYJ/u9iapSuRxdIq9PNNR/vpqC8Db1azusXD2X2wATCfKb2awobaO50MKt//Bmbw4cQQgghhPDvQQh/BbQXSm/pqgl+g3VBUEPUV+DYDjI92A9C+3MAhKlGENGLukp0bEM0+dqluwoQRRNC5D+D92d8Em/73QgESBovKuSauUHjVIpEVIpE/3KLo4y9LV/j9BSjVxjpdEsMR2lntZ+sArB6zJS1PILVuQWVIpulLSkUW5oIk4dxb+69ZOt7Gpr/HhweB2p54HmkUqlwuVzIlPYgIYVMZu11+3hNPHfn3B38+XxG1RuPDGRi/+OkGUQSXMOJM+T6FVxyuZyUlBTCwzTcc9YkHtu7EptLhbxbHBittvHuVkmFv7u2Gq1Cyd1jxpOhH9ergTxAmErJTcNH8eF+ifyTOUFwQycu7hs3Ho1CTlFzC9MzMzkvvz8/b9rDMz9uxSGX9v3tviLevMNNbkwqYYozbB/cBe0mK3999RecTjdeOaiy5Di1kBcfw30zpbjBZDLR0CDFWXa7nbKyMnJycgjXaxkWlsX4xkHsaJE6XLqcMsTtBjQzWyHDw+rGXYhagdbjCazZf5IvH7iU/qk91V5Do5LY0+wrf/SIKBsUqGsUyC0y4g1Kjh49SrHye1w+TzWlzEuOvpE9bf04WReIx0TgYHWdn7BSyRT8behtlFnqSLPfitwjvbOkqi3MDq9mcauUeN7bftxPVgEcNpVR22kiyVduaLFYOFF6kpfaltDm7SRcJWLw5VvlKGmz6QDQK1TMTc2npaWFuro6PKKXt1rXccwpWZ8sTBnHg/0X+vczbmgGS98KLlUtrWrmnheX0NzWSUZGDi/cexb5sckoZHJsTherDhehkMs4e3BuyGj9fwHWrl1LfHw8P/30Ez/99JN/fUpKClu3bj3ttl0RIqxC+FNhYFI4A5N6N7M81dYeYMOD0yhttpAXbyCyF/+q6narn6wCaLE4aTI7SIuWfrRbLU4e+fEQJrubCf2iGZkWSbPFwZwB8fywr4ZXVp9gQJKRh+fk89hPRyht6mTOwAT+dtEQ7v12PxtO9CQWzhoQT12HnR/2Sg+1SJ2S7woC9f2nPJu8Ijy74hiXjkkLUprgI6TeWHfSv7+u3QAf/+kwX+6sxKBW8Oblw5meFwcT7obORm4pOs4vdRMQfZrc3Hg9NqenT0+nrrh9aj82nmjE4vCgVcDNsl/8fxMBodHXyvrri+Gew6RFp/D6pcP5h0+91mi202GTznV+goHj9QFvqq7/7o4Om4ubPt9DQXkr/RMMfHfLeJ5dXsh+H3EUa1AzLDWCaL06qJzvsbI8JnomsVC2jRaMPOK6iX3LjvLEsqM8fHb+7xrc94aatuAA8pnzBnJV13JOU22ArAKJhNn2Bsx4DIDrJmYyKTuGfZVtPL+iEJO979LJvRVtfsKqosXCbV/uo7zFwuyBCdw/K4fd5a09FGw3t74Ccgc6T2u32QQ+7/8B5+YNYF15INM5KqOnwWVWrJ7E8L4zx/0TjbRbXUGdLwvKu+yvugBMAbLrLPlelC43k/OTuHZCBonhGnaWtZKfYGB0RhRs/tZPVgHMle3mVS7mSI2JTUWNnD0o8JLRHd8XVFFQLgV5nQ4PH28rZ6Hvu/Dc8kI+2iqpLd8MP8kvd006Y7+sEEIIIYQQ/jgEQQD1hD7+pgaN5F2ToBpNuHYabk8bYeqhyIRe/EXdJ7otFwUtNtiOsabuU1zuTPobxxOvUBOl8GLQjkM0/RXRXQXaeVQJZ7O+4VXcXgdjY68l3zibnyofxOZpI0IJM2JVLK8bDMiZHjcWS/1Jau2SGfmsSC8dtiUAuDyNZCriKGYgFo+FxVWLebT/oz0Ou9XZzPLapTi9DmbFzyMjLAsAi9vC60WvU2IpIUGTwAO5DxCjjiElJYXa2lrGuYayw70efDYHg7W/X451CndPHMuze9ZgEwW2HxjGzjIpymsYXcZ5wzNxOCRCr7S0lPz8fC7JHkaZpZXVVSfQyQcDNYBkx2C35gfNfayl9wQZQLG5miePfEyzo42pccP5+ryLuO+HX2kz2xAQmJCVRoRWy6OTg/2b3l6xF4cgItO6iR7dSHpiE+/X7EJdp+H27PvIM5ze4L47WtutOH2WIDIPGE96+OKNa8lMCSj0nU5n0DYOh0NSDmm1CILAU4Ouo9BUzu7Ccj76aB94BOTJASJUUIgoo5zYq5Qcrqj3E1Zb95Xw8odrcLjcXH7BKHKzYzl2oorG944iCnrckRoMnW4m5PiOxaOALvlfQVTxYN7FbDF3UOaLowVgeFpwOahcJifbkILXqYMuoaNTDEw20JjBloZSv0OH2yljY3k5lw+SLCtMJhOtHjNtXokw63BqcHnlXJQyiZnxUylLdVBubmVSQhbphkjKyqQYqtzV4ierAJZW7+SW7LMxKPtO/r7//Taafd0Zy8vb2bi2jEFXpOF0e7j2ox84XC3Nt/zAcf55zfn/lofdnwJesadx7+nG/jfh+eef5/nnn/9PzxMirEIIoRfEGTXEGft++c6K0Qd1YsuN15MYERj/8srjbPORAttLWhiVEcWLFwzhnQ3FLPepYLYVt3Bz415/edOP+2sYkhrB/srgNrzTcmOZPySRi0amIIowLiuaVouD6DAVDyw+1Ovx9aWAemZ5IV/7fIFWH20gQqdkRn48W0428eVOab3ZIZWZ7Xn8LJArYO5LOAa2Ib673T/P0Voz5769lbcvH052nOG03dP+ubkUi0N6StrcsIAXeFHxIVPlh5AhIpzSoopeOPQtTHmQc4cmce5Q6aFb3Wblx301GDUKxveL4fx3tvnLNKfmxva53/c2lrDb1x2usM7Mfd8fYNU9k/lqVyVmu5tFo1J6LZ3sdHp5wHU7j3Azrm4/kS+vOs7+yja2l7QwIMnIO5ePOCMFzvS8OBZ3IRpn9O+WYYvNA2UYuLr4bJmC28bmxBvIiTcwOSeWjSea2FXWwrIDtT32NSI9UPrw+E9H/F0mf9pfw4i0CFIidYRrlX5PN6MKsgXpnpwp28eFss0s8U5Br1bw9hXT/OfY6fGytbiZAYlGbpyc1evnvGlyFhtPNHG01oRGIcPu8xUD0CjlzBkYz9L9gWNOjdIFNo5IB0EOoodW0UC7GIZHUHDnjGxG+Mpec+K7dICKDs5Ql4kBgqprqaXJ7uLRJYcpbe7kwhEp3Dg5C3e3h7PLEzjO7/YEFIB1HXY2FzUFEbshhBBCCCH8v4NWmQ2ns0BUjUMa4FOMqCYF/Xl17XOYXNIzb0/7GhamvU64bije1mv8pYdYv6LYthaLW9rR5oa30cgisHkCapYwhZPL00cwNmYMI6L6MTjyUbY3b0chU9BPsZ3Gzi3+sXpZgMDoqsQ6BVEUeaPobzQ4pOM6ajrMUwNfJlwZwa91v1JikUru6+31/FD9A7f2uxWlUkl6ejquplwOnyhGH2aj3aRnS/MJSsu9/MfZU4hQ9WzKcgoOj5sPSrfj1XhQKdyoY8zIo+Q4jxn49XAF5w0PKLXdbjdutxuFQsGjw2by6LCZANRaZ1Nl2UeMJosDRPMFq/zbTD1Nl7l/FC1GIytmblwtcJhqr5ml11/Nkv1HCFOruGxU76Sb3elGECF8SCvRcSbUCulcOrx2vi/7huJvcqlpaGfW+Dz+csNZv9sJOy0pkpHjZVQ3NtBUHs3A7BR/Wdop6PU9lVsOhwOtViJdZIKMQeFZDBqfxbi4ARwvbWCNfh3FDimWEL3g6lCikMkYnJ4AvpK3J95cgc0h3aPvf7mNccMyyRdi6Sx1I7ik94f80QGLhzTvWZjkpZjESiJUqVzT728YlPFMm+cm1hBGVVsHcwbkMDYjtcfxAgiGxxDbbgaxjf2tqfxY2w+5Vop9otQGdOZUOpR1eL0yTI16ovIDpJJKpSJSrscgaDGLNkBAI4vmotQL0MrVJGlhYkLgflGr1VgsFrRC8BdVJVOgkgXi6uKmFn47/Ak6RSfjcq8kPyEbd5d4DPAvFzc0+8kqgC1F5TSaLMSH/3Fl3Z8C/4aH1f9khAirEEI4Q/x6uI73N5UQplbw1LkDWXzreD7dXo5cELhuYkZQZ7imTkfQtj/sqWLRyBQaTMHlgZ2OYCP4Z7qUu+Erg3K4JaJgXFY0qVE6LhopvTyb7S4yN5RQ1iyRHDF6Fc2dUibowdl5HK838+zyQhxuD/fOzGXWgHgOdCPDDlS2MyM/3k8oBY4r2IS+3RqcYQI42djJnH9sYVhqBF/eOBa9uvefk/3dyscaieQG90Oo3G6O6W4Cb5e5I3sGOCmROu6eGfAo+P6W8SzdX0OcUc11E/sOiLqb7Fe0WFl/vMlPthyoauen/TXkxBuYMzDBP+6mKVlsOdmEzdXz8wjAb4WSNHx3WSsv/nqM1y4Z1ucx4Csv++mApBwKU8v555Uje5YWKrUw7S+w5snAupw5vc6XFKFlSEo4qVFaUiK0HKk1oZAJyGWSaaXX66XD6iJcp6SlM/i67atsZ19lOxE6JRP6RSMTBO6bkUH4uv5QswdBgFcnunn2rDmoFXLkMgGn24tKIWPRqFQWjeolEOpshF/ugbZyIgYuZPldD9FicWJUKxj6zBo/ubjiUB3vXTGCRrODgvI2RqRFcN+sHJrMDoxaBeq4fFzn/ZNbfqplvSMHpSAyKiOKf20po2KAhYXDu5FGA8+Hlsfh6E80K5N4ofpiZG64enwGE7MD2dFrPt7tJ4GfW3EMtVLGopGpfL+niqKGTlQKWZB3VaROFaSejD8NcR1CCCGEEML/W4iiSEnbGzTbNhOmzCY/5q8oor5EtK9EkCeD7oqg8VZ3sJJ4T/OXxKfkI/M0Bq3XYCPAjIn8VvesLwqQgjSd3ECCZh8Odytu743oFXpmJ8wGwOKMpdnyJV6fx1aNS0qwaGQaLki5gM1Nm1nbsBaD0sBV6VdhUOj9ZBWAzWOl3l5HuDIChzc4nrR5bEHLbXYbLe1GWtql8q2U5BYaE45w38GlzIibwVXpV/V63hptndRZTcgEL5EGCzIZkORGHuEm4mBPFXVvSNINIUknqXD65YNGoWBPbQ0jEpJYkJvf53Y2TxtDjdWc4pMabD8SnnwZd06TfIparb/Sai0lXDuNMNUg/3Y3nzOOV5dsRqbpSfrVNHRQVC5dw2XrDzM4N4n5Uwf1GNcVu1o/Iuec5eQAKnsWV+Tfibyb/6xGoyEsLAyLRYq1ZTIZOp2u1/lyM+Mwy11cJTuP7dbdtNhNeKrDsSeqiG+2U7mukLyrY7E5XDg9dobPKEIfYaX0SAo7DvrmuHQk8cVtRCeEc+1fz6OtsxmPx4MKA+clvIFWr0AlD0MURdweLyqFgrun965OtFqt1NXVIYoi8fFZ6OO2gmhGULYhbwx4b719cgmvTLqf+35bRb2lk8v6D2JmRhZNtk6iNWFERUVRY2nB06zGLTrQyVRk61P5x4nvuSBlKnnGYIP++Ph4vF4vapuay2QT+L5pJ0pBziMDLkItl75TdpebXUfv4tYBUjlolflXzMblXLdwLIdO1NBpdRAXpeeSuVLn9Ci9Dl2snbB+bSAK2Etj0Gv+eAf3EP53IkRYhRDCGaC0qZO7v9nvV2YsfGcbi0alcuvUfiT0UgZ1yehUNp5o9Kssazvs3PbVXp45bxDf7q7E6RGRCXDu0GS+Kaj0k1RdhR/TcmPZWdbCjlIp03KouoP1D0z1Z1sMGiVLb5/A8yuOsWRfNc2dTnLi9Lx9+XAyY/SMe3Gdv0vh7V/vY9ND0xiTGeVX3NCltGtqbixDUsI5VN0BwF0zgk0sx2fFMDDJyNHabh17fMTP59vLmT0wgeQIbY8ywTGZUVS3dfc1EjhvZCby/Pdg6a3gdUkEzcCF/B4Gp4QzOKX3ss6uuGJsGt/urgxKHJwisfaUt3LpBzv91/OJcwb4y+hGZ0Sx/sFprC1s4NkVx/zdBwEyYnSUNQdK97oTk73hg80luHyGXBaHh01FTUHlp35MvBeMKVCzDzInQ95catpteL1ikBLp9TVFvLHupO9YI/nyxrEoZTIu+WAHBeVtrDrawOK91fx85yQiw3pPQ7dbXfzHvP7+RgHW+J/RVW0EtQEyp6ADypotXP9pAWXNFibnxPDBVaMw2V0crzeTn2AIEDk/3wVFvqxqYyFCTC4xA89HFEXEbmkblULGVzdKXhZ2l4cbPitgW3EL4Vol/7pmFN8U5bLeLvmluUTBr5BbcbgOg1rpN9T3Y8pDMOUhYoD1oojbKwYRxwCF3e7ZH/fVcNW4DH6+cxJFDWYSuqkpVd22V/XRKjuEEEIIIYT/96jp/IGyjvcBsDmPcNi1hwT9+SQYH5DKCbthYMQ5HGxb4l+usu5lV/MnjNctgs6XpJVCOF71THDs7ra1iEqmI0GbT521gCrrbqqsu3F5bUxJeNA/Kkw1mAEJv7Cm5nV2tddS6zIyOnI0V6VfRZOjiU/LP5WejzZ4p/gdnhn4DEmaFGrtkrI6TK4nSSN1kpseN51drbvodHeikqk4O+HsoCO6uP8gvjt6mE6XE5ngpV9Wnb+0a33jeoYZxhImxJIeHo5cFniexWsNpIVFUOdopstqZDoPj1w2lQithvZ2KdkTHx+PQvH7r4zzs/OYn/37zUsWJI6i2tLVv0bE6bWhA+o63qW6428A1Ha8Sf/4HwhTS6TYlbNGMrZ/OisbdrDCtBa9woFa7sEjCpiPBie1Wjt69/I6BY/Xyf7W7/3LTk0prZ5jhDGyx9j09HRaWlrweDxEREQgVygob2jFqNMQZZDiM7fXy41f/sjOMklZddPEUbw4azJNMS3cdv1DHGs2sxEo3H6Cu9+9mXmXnSC6n9TgJ3NQLb9+MpGmmihqzVY+/1ny7/SIXgzOMNx2F2q1Go1GilU27ynm6XdX4nC4uPLcMdx6ySTKOutodZoYEJ6BVq7G6/VSUVGBx9ewp7KyktzcXJTKKNSKjqDP5xVF8mJi2HDVDQCUmVqYseI9aq0m8sJj+WzqZTx1ZAXNSiugQCY42N0q+arubCnk4zGPEK0OxOWnfM8AcsjhVu85yAQBmRC40RrMnZzXL2A1kWpop9a8jkE5l7H49eupbTKRnhRFmFYipVQakZjhLXh8dY3GES3IQyxGnxD+gJn6/4aiytClDuH/FLacbOLXw/VkROu4YVJmn536/igqWq1BZUQWp4dPt5ezuaiJ1fdN6fGSPGdgAvedlcurvwW8E47Xmbn24904feTFgqFJvHDBYC4alcLe8jae//VY0BzzBiewsYtJdlmzBZPdTbg2QEJE6FRsL2nxE10nGzvZX9lOtF7tJ6sAnG4vte12Hpvfnxi9ipImC7MHxDMlN5ZGsx21XM73t4xnb0Ub4Vplj46HWpWcxbeO58PNZby/uSTIhwhf+d3fVp8gMVzDNzeNIyMmYNL+wsLBpERo+a6gigazRPBolXLumJ4NMUMhbx44O0Ef90cvy2kxKEbOvWP1vL5LqoVPjdJy9iBJSfVbYUPQ9fz1cF2QUXliuJarxmewp7yNZQcDJWzhWhVapQOby4NcJnDZmOCsUm/orjzTa07zszv4Ihh8ES6Pl+s+2sXWYsl4/9oJGTx17kA8XpF3NhT7hxeUS+WJefEGvycTQFFDJ/9YW+QvS+2OWIMas93FnV/vY3NREya7mzEZUUzOjWb7mp3kJRg42Wj2q/e2nGzmxZXHWLqvBrPDjUGt4MsbxzI0NQJaS4Pm/sfiVVjKc3ls/gAePjufZ5YXIoowKTuGKV1KOH/YW+0/vg6bi5u/2EubpaeS7xT2Vrb1JKy6QBAElPLgx26bxYlaIcPRhXTsF6OnwWQnzqBmSErPconuKsiKFqvkmRVCCCGEEMK/BVEUaer8EquzEKN2MlG6ef9lc1tdUtcpOR7CZE48nlJqOl7D4a4hM/rlHuMnx99Bq6OcKuteAARE3Pbv2GevRS+4UAtKIiPuY1LYpaQYdlDWuYvCjuX+7RWCmgSNRFidQpP9RI/9mD3hLG2yAVJJe0FbAYtSF9HkaApK5jTYGxAEgXtyH2Zl3c84vQ5mxp9NmEJPi6OFWHUszw16jkprJYmaRGLUMUH7yY2OYfXl1/Da5m2sPHyU7pY+1/60hDaTmvEpqXx8/kLUPuJJJZfz1YwrePPoJnaaduMSpYReZlg8E7OzkAkyEhISEAQB+X+xufX8hLksqdpIs1MiLLL0EwlXSjYQrdZf/eNEnLTb1voJK4Cc5BhykheweeshSkwKFIKIyytnfP9kKnZJJWPheg0zxuae9hgEQY5SUOPq0mlSJetdOSWTyYiNleKXuhYT1z//JbUdZpRyGc9ddTZnj8hjb2WNn6wC+GjbHu6YOp796w7T0RzwW9343XY642MJO7u6y/wicaltNNVEMTQ3md/q9rOqbjfHzMV4RA/nJE6k9WQEZS1tzMzrx0f/2kynyo0M+OynXQh5Jpa0r0VEJF0Xzxsj7kElKvxk1d4Vh1n2ymoUCgV3vHE9kxeNY1LMELY2SyWwV2XMRtvF0P+1w5uos7cjV3opttZx44bvqeloRx0rXRVZFybE6rFTYakPIqy6QyHref9Y5SaUHjU6ZUDRrtPE0+60EGEMI8IYfC2anR1+sgrALjowuSxo5CGVVa8QRejDHqbXsf/DESKsQvg/gz3lrVz7SQEeHxFR2Wrl+YXBHeu8XpGnfjnKmkKpK9xrFw89rVfVKQxLiSDeqKbBFKyoKW220GCykxLZ8yF34YgUPtxcislXXuT2iv5/Ayw7UMvdM3MYkRbJiLRIjtWZ+HG/pESaOyiBGflxROqUtFmlIGJgkjGIrDqF7goQpVxGdJiKMRlR7PaZWmfGhNE/0YBSLuPOLuqpx5Ye5qtdlchlAk+fO5Arx6UHzbWnvJW/LjuKw+Xhnlk53DMrhzum9+O3ow08sPggNpcHg0bhL6Gq67DzzoZi/r4o4D+gUcq5f3YeN0/tx3sbi2m1OLl4VGqA1FLppP/+K9FaCp/M5x5zLdOMI6ib+jfGDx9GuE46f8puvganzPK7Iz/RGERY5cUbeP2SYewpbyU/wXhGSq/HzxlASVMBla1WJmZHc20vXSe744HvD/jJKoBPt5dz1fh0smLC0CrlmLuUbIapFETqVBg1Cv/9JRNg7bHGHvMOTgonN8HAecOSuOGzPUHE4+7yVv/9sqO0hW7cDztKWvz7NTvcfLytjDcuHQ79z4UtrwBgF5Wsdg7h2JYyxmRGc93ETGbmx2Oyu+ifaAzyOutKIuFrVHA6jM7o3pa8dxQ1mKluszIyLYrrPysI+s5lRoex+mgdP+yrZmxmFJ9dP6ZHY4L5QxL5tkAKOk+VToYQQgghhPDvo870LjUdfweg2fINRL9DVNj8oDGipxmx42HJJF09A8H4BILw+0RJrHYalR2foRBcQWSN2bGzz20GR57nJ6wSFB3oaEUEzCKYRSft7f9guP5yMg0TSdINpd52mFZnBSAwKuZKolSp7G/90l8emKQb3mMf8l6OXSEoyDXkolfo6XRLybSRkZKiJ1wZwaVpVwNgdVt57thzlFnK0Cv03JdzH4PDg+PZL0/u5V8ndhOh0vDimPm8Mn8uz5w1ixX1v/Brg9TcxtwWQ5tJeqHfUV3FypNFnN8/YEyeFBbOS2POpdIynu8rt6KUKbgqY5pfCXMmqqo/CpPJRFVVFQPFa7GoS0lISCBdPwZBEPCIbkQhOK5SK3pPDKbq4qmzmfwdpWcNGcDlT06lpqGd0YPSiYs29LrdKcgEObOSHmFt3cu4vQ6GR11CvLb/abdxutxc99xXNKe2oM5w42lS8cqPmzh7RB46VXB8rlYoUMhlJPWTEm3uKCUd8+JwxxrZsPsYE3LCCYvxkWWiQGbkUIbMzaPf5DCePvINWkXgfv6lbisNJ+NxmtTsKq9CiBcRfA7smiYvqzu2+0nQCmsDW5oOMSdhDDqdjoaqRr756094fDHXy1e/xfCZg3li4LWUdNaikStJ0QUnjNucNmRyr3//RY4ahDodykgHMgV4vQIymbS/MLmGjLC+m9x0xc76StxeL7mR4Tx66D1SlUN5OOkA4XIXJ1yzuO/wb3hZzZUZ07gtJ7hjZ4YugQxdAuVWiZQcYMwg5jQkWQj/txAirEL4P4OdpS1+sgrgq12VnKg34xFFsmL0PLFgACsO1fH5jgrwkStPLDvKP6/qKf/tjsgwFUtvn8gXOyr4dHu535cnKVzTp+l2UoSWH2+fyLIDNdR32P2m213x8dYyzhmSxNe7K4nSKfn4mlHo1ArGZEQhkwl8f8t4PttRjlYp57ZpvbdBfvrcgdz25V4sTg8T+kVz7rAkBEHgs+vH8PXuShxuD5eMSkWnCv66H6hq5yufAbvHK/LUz0dZNCoFtUIKstweLzd+vod2H2H2wPcHGZ4aSVq0jnlDEhmTFUV9h51/bS1j6f5AyV9fPL1ereD/Y++tw+So0vb/T1XrtI27WzKRibsTIYIlOAQJwV0XWGRxdpcFdmFxCywSCMEhCQTi7jJJJpPMZNy1p7unter3R026p0dC2N33/e2+376vK9eVqjp1qupU9dRT97mf+/nd7L49Df6t2PwStCtE01D3HoZWvwYTlwDwwk9HeXWdYmAaphGZ2j+Wx84e1Gs3107KpLjBxqZjjQxOtvD7eXlEGLRkdlGQ/RqyY01suP8MnB5fD3KkL2w41tjrekEQ+MtFQ7nr071+Q/PX1h3nzStH8s7Vo7nhH7to7fAgyUoaa1fMHBDHW1eOQhQFvt1f3UMl1x2+bjcyN1LNsS4cmF85NuNRiM3jja9/5tuOIRyRFdKzoVNN1xcZeMGIZJ7+/nDQ85ITZ+J4vXLe0/rFMjwtkuMNNoakhLP5eBN7y1u5fkoWFn3vqY7Ld1dy//L9SLLy26xuC1ZL+WSJ9k6/tu0nmvl8V0VwtcZOReCI9Ega2l2cPSSRpO5+YyGEEEIIIfwmWJ2bAUhSqUgQReT2e5GcnwEdCLqpYLwVuf1pcHcalXcsBXUuGK/41b4jw0YzKvEf1LR/gq1juX+9UTukz32yzJM4J+XPVHfsxyhtweVaE7S9w9dEuW0bVk89lY695FimE6/vh1EdS4xe8cGcnfwMZbbNRGjTyI+8qMcxonXRLEhewNdVSin3s+POJVKrTLw8OuBRtjdvx6Q2MSV2So991zas5YRdqbRm89pYVrmMB/Me9G8/0FTNY7t/BKAcuHnTF6w9+2YMWg0XpZ3PlLiJeCQPly5dCQTUPX3FZ2nGWO4b8OuWDP8O1NbWIssK4WJy5WDxJCEIIj7Zy7cV91PnqCRTayBSYyTJfBHRxgt67eeBARfw9KFlVDmamJEwlFkJwxASBYblnX6RlGzzFLJMk5DwoRJO5eSvoKbBSktyA7p8RX2uSevAU6B8A+QnJXDdhFG8u2WXIm5p9LJk5Q6uP2scN7y0iMdVu3FGqWkDdAMEdn44kI4WPYYYJ2eNuZJxV5wDwJ4cI/QAAMYbSURBVJ8Pf9HrsUV1YJJPFgWEzkV1rA6zVk+7K1C0J0ylQxAEMjIyaK+1+8kqAI/bS3uLDUu0mRxzcq/HOjt9ADtbiv3LEjLRgoWWPWpUYV4unzAOX1QDHT4X6apcXtq2k5yoaBYOHorYR9W++zb/wPLigwCMT47CrnJS6IvkmhKlAqjTo0XqfEI/Kl3HvKSRpBsDRJpWpeGF4bfxY80OVKLI3MRxQSmGIQRDkH9DSuB/vsAqRFiF8H8H3dPYAHaVKWlSe8tb8UoSqd2UUNVtHT326QtJEWE8MDePs4Yk8tq646hEkbtn5voJnt6QE2fi3jP702J3s6W4iarW4ON9vL2cz3dV4u6sglFUZ2PpDeP823PjzTw9P79Hv10xpV8sT543mN9/eZAtxU08+MVBnr9oCGFaFdd2SXPrDp8UrHDxyTJdV9lcXj9ZRadCrKatw09AxJh0xJh03D49hy3FjdRZXSRY9NwyLTvQyc9PwO4lYEqAC96GhFNfy78N3V9inXJkm9PDK2sCKXUdHomrxmX4lVfdoVWLPH/R6ZeI7g2tDjff7a/GoFVz3rCk00pTjTRogsbeqFWRHatUQpkzOIF+8SYOVCneTOuONrB8dyULx6aj6aK2k2TIjjVSZ3WRFKHnkbMGIrpa4cDnjHXIGFUJ2H2BV0BXhRZB1rIQoVfxh/o7aREuZJBYjkUncukZzwZOeMhFuOqHcfhnJQU2waJn5sBTp3hGGLRcMzGD9zaX+q/51ctHcKLRhkYlkpdg9hOLr645RmuHcm6bjjfy1S0Te+3zjXXHgnzjYs06P3EWplGhFoPH/tv91T0IK1EUuLg3c/kQQgghhBD+KRi1+XjdW0nsTC0TkMCjKKBkz34EMR58NUH7yFLNaXurROhHEKEfQZN9Ms2O79CqUkiJuO+U+6SbRpNuGk27cwhH6zcid1YVlGWo8kRwou6vtHg6bRna1zM25hpGx4z1759hmkiGqfd30Umcm3QuR3/R8PWaAxR5TqBefIBzpw8hTh/HOUnn9Llf90qCXim4EE6VI9iDqMbRppBAnWRBvF5R9Tw0ZSr3rFqJ2+djbHIK83KVNDmfz0dlZSV2ux2DwUBqauq/Pe3vt+Jw62aqHPsAFcfcCYhuFTel3Ou/pu5ICIvklVE3/kvH7HAX0ebcRJgmh/CwnsRhd8RGmdAleul6d/KHB9TfN04czadf7cInKTHU699tZfao/gy/aizOlfv97VwmGUu/WI5siiA/P4VhF87B6XRis9lI10YDAl5JRKNSgvIIKZqKFiUbRCCYeRyVm8xsfX/ec/+CQ3Yx3jKQybEKWSuKIoPHDmTY9MHsW1OgtJ89lMSsvu0VAM7PGMqy0t0ctVZi0LoZEJ7Mc7MWsrushpQIC6LJwQ81FTicMo9sXY9PUmKrWpuN342f1KO/+g6bn6wC2FnbQP9UDW5J+c2lGuI42taKSvAxwFyLXuXhUMtO0rupMC0aIxelnfGr9ymEUJXAEEL4j8W0/nH86fx8fv/lwV5/e0V1Nm6YksW7m074FVIXdCtX7/VJPLPiCJuPNzIoKZyn5g/u4UE0ODmc1xb+uiqrKyKNWr6+dSLvbTrB6+sDsxaCgJ+sAthV1uw3Cp8/LLmHgXlfePzbQ/5+vthTyYLhyUzKjTnlPiPSIpk7OIGVBYq89t5Z/YKOF2HQMq1/LOuOKgFbVowRURAoa7KzbFcF1g4vC8elkZdgYen143hrQwmRRi3Rxk7F2bGfYdOLyv87Wqh49wo8N2ymxeFmZ2kLQ1LCmZCtnKMsy3x/oIaGdhezByf0rKL3WzHpHiheAy2ltGvj+FZ/Kec4PTz+7aEez8bpjPGOE828taGYMK2a+2f3DzJB745VBTW8/MtxwrQq7p/dn99/eZCSTi+o1YfrghR9Hp9EQ7uLOLMuiMi698z+3PbJXv/ymV2qGNJJtAUtd6qljFoVDV3Wt9g92FxeiupsLH57Az+E/YGw1iLigfUpk3jQ8Dhalcjc/EQm5sSwv6KVdUfr6Z9gQaMSeGXtcQxaNU8PKCNhyzGW6v6odCwBKxrg8s/8x7pzZi6jMiKpbXMypV8sZr2aWz7ezYaiRnLjjOg0Kppsbi4elcL1UxRS85GzBrK+qIHiBjstDg83f7SbH+6YjFYtMv2FdZQ19TRN3Vveis3l7VmV0lqNqbUQCKQPXD85k2N1NtqdXhZPymRbSRMvrg74yu0sbWHZrooQQRVCCCGE8D+I5Ih70cq14F7Z63bZewwhbD6y5+R7T4egD04J8vjqKW1+CJe3gijD2SSF396jn2jjeUQbz/tN52bWj2FgwtccaX6dkvYttEtheFCjVwVbQFQ69qBrMWFUx5BtnnxafR8pruXLFYc7P7ck/vLeL8yZPBCt5tSfX9Nip7GlcQt1rjp0oo4FycHqp7Fx6SSEmantUNRTZ6bkUtRejdAksmJFAYYwLZddNJZ5uf2IsPjY2HCA/hGJfr/VhoYGrFYrG70bKXWUkmZP47q86/i5pIzqdiuzsnLIjFCIGJvHxTelBYiCyIKMwejVv65EOhUSExMpLy/nRFUrB0uaGZDrY+40M38vWsWQLvPOKkHrT3s7FT7dvp81R0rIio3kzlkTCdP2fX7bGt6jpH0TEdpUxkXP5UTjIn8lx7TIJ4k3X+Vv6/C6cPicQWlnBr2WWf3yWdW6y79ubm5gItbt9SFJwSbWHW4PiREWNLIKj6DEampJpKbFCZLM5v2lPP3yCnL6mymsbCY7IZxF/ady1F1HrM7E9Ph8hkRks9x0iJLGFs7ol8X6whLWHCkmOy6Km8YNRvS4eCpqIV58aAU1zU3NxMQo8bVKpeLZFQ+x+asdCILAxAVjqHa28IcDH1PZ0ci8+CimRKxHJUhkRj6ART8BrajipXHzuXnXC7gkFzWeYj6o/I4HBi+kwlHPjTvfwCMrJGpChoaqEoUA21RR2ith5e1wohYEvJ1eST6firtzF7K5aQ8GtZ5rMudy/+5PidGvJs2gCA2Ot/+NFlc+kbpf94oNoScEWUY4TW+q0233/ydChFUI/6dw6Zg0atqc/ipqXTEjL45BSeF8d/tEXvipiIZ2FzaXF58k+7113t9SypJOxUdRnQ2TTs1T809dFvd0EWvW8cDcPJxeH0s2l6ISBW6dls2bG0r8fj56jYoHv1RmIT7fVcGyG8f/qiJHluUg0gug0eaiod3VZ7oinellry0cwZGadgxaVZBR+km8deUovtpbSZ3VydLtFVz05lZUgoCv84/bN/uq+Oa2iVz13g4qWxT12IaiBr67bRKirTaoL6O7kXlvb6O+3YUkK2TdS5cO59yhSTzx3WHe36KM+2vrjvP97ZN7rb7YG5weH3/9uYjSRjtzBycyf3gyRKTScf1Wrv371+xuCcO10cVnJ7ZT2y1FbHx2NMPTTu2NVNPWwaIlO/wpdAVVbTx/0VCe+O4QLo/EXTNzmZuv5O9XNDu4felef1XA6/+xG6szoJRadagWh9uLTq1i+e5KnvuxkCabm8wYIx9fN9affub1yRh1atxeH+Ozonm62zN4+4xc7vlsH15JJiPawILhiqy7tcMT1K7ZEfCFimg7wmaHCYHhTBP3EVO3iXd+lwlGJahxuL1M7RfLGXkBZdRFo1IprLXyp+Xt9PNcxkOapYHOi1aB2w7awHMzMSdAkr669jgrDirPwN6KwGzwMysKibeEce6wJOrbXRQ3BGTsJY12iuraSQzX90pWAaRFGXqSVQDbXuNp4Vuu5z5qiWS2pYJrJs4NKohgd3l77Lb5WEOIsAohhBBC+B+EKGiJi3wBuaUF3N29pUQE3VQE3URkMQHsS0BQga8aNIF334mmB2lzKql7VW1H0WtyiDLM5d8Bg3YQQ+Keo8J1Hx7nIfSqcPpbzmZX8yf+NnUdhVQ5FJXMiKhLmRB3w6/26/YGK6V8ko9GZzORopkwVd8TcxaNhScGPUG1s5pobTQWjSVoe5TOwJdnLmJF+RFaPC18X7eRxdt3oGpRI6w2IThF9h4o464np/FU4bt4ZR8/N0KNs5Gbcxbg8XjY69vLTq9iHN/gaKB4p52vdynv1ld2befbixeSZLZw+ZqPOdSivMu/KzvER9MX9pn21R1VTW28sXIbLq+XRdNHMTAtHrPZjCosmr98tBq3x8e364soqK/gUIyEXoyjn7keryQwIuaGPtVVJ/FTwTGe/EZ5JjYVldLh9tI/P4oPinYSoQ3j6dFzyQ1XzNIL235iV9NHADS7SzHKezF0MVxvsn9BvPkqrA4nHxZs4kvbL3hkLxNjBvJU/lWoRRWyLBOx0UhYux4xVWD+0LGclTza30e0xchFU4bw+QbFzHz68Bz6pcRSVN+EXKZGiO4kBpo0eASZk9TappITfGP1ILgE1AdUXCfl8/yF1/j77fB1sHDMMP/ypJx0Hj77DH7cc5Q/f7udMJXAFRP6EWNSnqm2tjY/YQWg0WqYdklADfiXA19ytL0KrehhuGEpPq8HH1BYfzVDk9ajUydRaC3FJQVI282NyrfJobYTfrIKQB/mQRAlZEkkLyZQWKcrHM2t3J42hFfLD+KTZW7LG83MxKHMTAxkMPQ3Z6EWA1WdRcFHTcehEGEVAoQIqxD+L+LuWf2YNTCetg7FsHD90QayYo3+j9KdpS1+VdGushYkSeb2GYoR+cmqaCdR2mTv5Qj/Gh47ZxC3nZGDWiUSHqZhQk4MS3eUIwpCkBfUnvJWSpvs5MT1NI7cXtJEYW07Y7OiyEuw8LvZ/XlmxRFkGdKjDdz1mVJ55YYpWTw0r28TSUEQGJhk6XO7Vi1yyeg0/rjyCDWd1dN8XZh4q9PL6sN1frIK4FC1lfp2Fwm5Z9IRlkBYhzLWn/hmUGd1+RVOsgzf7a/m3KFJQdfdaHOz4VgDZ+Un8ub6YvZVtDI0NYJrJ2USYQhUA2nr8HDlu9sprGn3E3Y/Hqoj0qhlar9YjjW72dISmBk7UNnG2Mwo6tsDL+C7Z566igxAcb09yO/pRKOdxe/vpK2THLrj072sTQknJdJAZUuHn6xSxseDKOBPU4syatGpRG7+aDc/Ha4L6vOVtcd5dkE+jTYXv1u+39/P5uImiuttDEkNVLQ7d2gSQ5LDqW7rYEhKhJ/AiTXpglIJu+KomMl1HiVFYqa4i+fVbxKhsyBJMouW7GDDsUZ0apE3rxzJtP4KaeXxSVz17g7q22XKhFHcL3+G+qRxgjEONH0rzRraXX1u23isgXOHJRFh0AQVFtBrRBIj9EQZtKhEIciTLj3awIAECw/O7emDJssyh6rbGSyWsVV/O25ZhTZjFvurL6e0yc7YzGgSwvVMzIkhJTIs6HnN76VSYAghhBBCCP9eCIIaIt8D904QDOA7gewtQtBORtCNVxo5vw2kCrq3QtRHCNpRALi8pUH9dV/+V6ERDZyX9goObxM6lQW1qMOkTaDKvhef7KHEtsnftrDtp14JK1mWwLkSZCvoZ5Ofm8SUUdls2FUMgsy4G9t5uPABNIKGG7JuYFTUqD7PR6fSkWns29YhPszMNf3HsHjby7g6U6t8kV7EfBeqnWEcKaxhe8MRvF3SC3c0HeHmnAVERkbS0tgS1F9VRw2gxMntbhdry04wJi3JT1YBbG8op8ZhxeOReO/ANjyaSmZl5DEtYWKQn9DuiiruXrGS2vZ2VK0yWqvAliNlfPvIIqLMBnYVlOP2BM5r7+4aws82sLs1nf1tKZjURq7vN+eU9wvgUFVd0PLO+nI+3rXDH2feuvlLfpqnpA22uauC2tp9Hgxd5oO1qmRabB0s/OsnWIcXIYYpsc7mxsNsbCjgjPihbFpXyHef70ZEjS/Rx+aSQq4cMg2zJkA+/v7yGZw7YRAer48hWYqnbESYHo1HjVDdeUAZOqJkxAYJRJnGCQ68OuV4umNaDpZ3VlD2tPHEzqdp0TQS7onmsVEP+33QCivrefCDlUidMXlDewdPnz8WQRDQak9dOa/ZrXiFZoQ1YRADMaOAB5e3FJ06iRRDHAKC38w9JUwho6K1FuTOSeeTGJkcQ15EKr+fMLXHsWTJRqR2CVektzIvbiYObzZJCYlsazyES/IwLnogOpWWy7NG81ZRBPFhJ6tbi8Tos3v0F8JpQur8d7pt/8MRcisL4b8ax+vb+f2XB3jsmwJqOv2oDldbKW6wkRFjZEJ2DL+fN4BLRqf5Z2r2lge/pPd0WZ4zOIGuBeTm5Z9e5YvfimiTzl/xb1xWNC9dOpzHzhmIXhP4SerUIlHGngqpL3ZXcunb23js20Oc+8pmdpe1cOX4dJYsGs3bV40MUqa8taGE4/XtPfr4rVCLvc9yadUiYzKiMHZJq4s164g0asAUh+3q1Twu3MLV7gd43nsJWbHBKq6USOUl3z0FMCUijJs/3sPLa46z4Vgjf19znLP/von2Lmql81/bzIHKth7qsn3lrdDpOWbocl5RRi1/u2QY549IZkJ2NC9cNJQxmVGnvO46q5NGuzOoOmOkQeMnqwA8Ptmv3MpPCSetS7rgxJxo/nTBENKiDOQlmHn7qlFUtnYEkVUn4e28jrYOTxDp5ZNkLnxzC9tLmoLan3y+u6qN/nrJMGJMwYGKWhRIiwrDLgXW/yyN4vGIp0Ct5YMtpX6Td5dX4uaP9vjb1bc7/QTfCTmRezw3UyQl02AZrKQDnmL284IRKYT1YTI/sbPynl6jYsk1YxidEcnQ1AjevHIUcWY9apXImQMDHgsqAV65bARvXDmyVyXga+uKuaZwDMWS8nuVdeEsi7uT+a9t5s5P9zH3pQ2UNtrRqkV+vmcqF41MYWR6JPed2Y/FE/v+IAghhBBCCOGfQ6vjZ0qa7qW67WV8kvKOtDq30uJrRlLnIITNRzTfHyCrADz7u/QgBS1HGub5/y8KesL1/34vG0EQMWpiUYtK7DU44mxmJz/KwIh5Qe3Mmt49GmXrQ8htdyNbH0NuuhABK0/deQbvPDOJPzw5jBaDUujGI3v4qPyjf8s5q0UVIKNVedGpPIhRnb5AyVH0Cw+2vThZzc1kMjE5ZTJCl+Q1jScpqG2qJZw4vQmtGHiPG9VakOCSrz+mkG+oVW/hw8r3eKvkLX+bDpeHK5Ytp7LDilct44oBr06mvcNFab0Sb6cnB1ffzYqP4cUR1zI+Jo/R0YN4YcT1GNV9ZwgAHG1qRGdRQ2e1Om+4D1uEK8j2ocLWGrh203jELsbqscbLiTNdhVaVhEU/hfSoJ1hz8DhVTVa6m6d5Okm/1hZlEtsz1o3z5g5Kp9ayePvLtLiDi9wMykhgWE4yYmfsHG8x8dQ5M5WxlEBtUyaMxSQ9lgkmP1kF4E71MDhLUc2/suldWjRKfNamaeLljYFxPlJR7yerAEobrDx270pqqxwkJp7622VBiuKV2+7TYfMFxtktqTFolEnuAZZ07up3MTmmZEZH5fHooKsBGBaZS7Q2QjGWlyFaG8E/zr6cp6bOxKDpmY4pt95GpPZzIvWryYx4jAhjO+80rOLRgnd4+vAH3LfvNdySl1RjJLfl/Z0Y3SQS9COYm/wH4vS/PqkcQu84mRJ4uv/+0xFSWIXwX4s2h4dL39pGo01Je/pgaxl6tYjbJyHJYNareeGioWTHmfyG1UAQ+QAwugtpMTk3ls9uHM+W400MTrYwY0CwMWG91cnNH+/hcLWVybkxvHzZ8NOu/Abw5Z5KiupsnNE/lrFZwS/sCIOWVy8fwTM/HEEGHpo3gChjz1mSL/ZUcvJvi9srsWxnBfcvb6a4wY5F3/Mn7ele7q0LvD6J0iY7UUZdr8c6iWsnZbF0RwXN9kCKWb84E4+eM5BhaZG8u2g0L/9yDI1K5IE5eX4j+tiENBbf9ihf7q1kWpiGi0am8OT3h9l+opmhKRHcd2Z/Kpod3DEjh7c2nKDR5uKyMWmMz47mine3B51DZUsHO0ubmZ6n3JOShp7qN0GA0RnK7FOMScc7V43imRWHqbe6GZ0ZiUol8OLFw3rs1xsOV1u55K2ttDu9aNUCozMi2VXa4lcDnURWrNGvUjPp1Hxx8wSW764kTCNy6Zg09BpVUMpZk82FWhTwdlEPRRm03NDp65QZbWRybgwbu1QKdHtl/rG1LPDMOJrBWg3ROaAJpE4OTg7nyfMGc8vHAdLJK8mUN/csLnDjpRcCcKTWGrTe2Tnr+e3+an73+f6gbd9KE/nWPRGxAbaYBhLsrBWM/JRwVtw5mU93lPPmhpKgbTO6kFHDUiP4/KYJlDXZeeK7w7z0cxGLJ2Xyt0uHMXjjCSpbOjh3aBL5KeF4fVKvKbLbSppoIII57j+TLDQwdfAQdh12+X8nLQ4P3+yr5s6Zueg1Kv7yLxrphxBCCCGE0Deszm0ca7ze7+Zb1fYiKsGCT1beNwZNHnlRzyCqUxFUCvkjy15cQiw6TlZUFkEzwt9nSsR9hGlycXnLiQibiUEbrLaV3TuRW+8HuQ3BeC2C6dbTPl+P5ORgy9e4JQcDI+Zh0QS/3TJM4xgTczVHWldi1MQwM/HBHn3IsgQd3wRW+Cpx2D7iaNsb+NTtRIvp6IRUXLISg3Y3Vu8On2TH7a1Cq05FJfadPnh7v7O4Z+8rnCwbpx7awTBhEHdfOo/EmAhuzTmf9Q17SdRHc1POfP9+I2JHcL/ufg5bD5NmSCNB3Y8HHT9S1d7OgrwBzMjIAu9R3powhif3H0UlijwyfBYVVisesQljWEBFvb15O4szF6MVtRytqMclBF+brIFIdRhZCUq8PXlkNndcOY1Pt+6jwyCTNCyWbGMizw+/htPBZ4cP8tDa1UiyTEyGgQSjgYOeWspdbYiawFzavLRAhkF8WB4Xpv+dMtt2IrWp5FimAZDOk/424QaF4HIesRA2tBVBhEHh6UyNVXyqJkzpzydLNlExMaA6q+5oZl1dAQtSFRLI7XYjSRJ6fbCtxYJhgzhcVMuyTQf862xeD63NHdCF/zQKWm44RyFx65uaIfD5QkOLcn4vvr+Gz1bvRYgSkTuvVdfmw9buYumSXcycPeaU43d+6niyTQksq1jD983NTAgvBhn226cwMSNgkzEvaRzzksaxrrqYuzavIEyt4ffDZvDqqLtYVr4WSZa4KG0aYSodPsmHSuzle8i9w/9fUXASG1fPml2BGLWwvYwiazmDI7KID0vg0swne/YRwv/zCBFWIfzX4niDzU9WnYSzS+nWdqeXGz7cDcDI9EjanR5EQaCwVlEcqUSBxRMzuGlKNq+uPc47G0sID9PwwsVDuXNmbq/HfGbFEXZ3Vh786XAdb28o8acT/hpeXXucv/x4FIC3N5bw8XVjGdeNtJoxIL4HSdYdieHBgUtFi8PvA2R1eoNSni4cmcKAxN5T/hxuLwvf2c7e8lb0GpFXLx/R57GjjFoGJ1n8ShyAEemRTM6NxenxMS4ruse1nERatIG7uqTePXdhgCz4YEspj393CFlWqh0uu3Gcn5AYlBTOwaqA95HQqQA6iTiLjjprIGAakhzOrdNzmNDFR6lfgpnKFidtHR5WHKylsKadNfdN6/U8T8Lu8mJ3e/loexntnVXz3F6ZmjZn0MxdnFnHDVOyuGBECgZt4E9prFnHzdP6ljFHm3T88fx8nvjuMJIss3hiJtdPyfITqaIo8N6i0dzwj92sPVrv388S1nmM0s2w9FJwWSE6Fy79GKKyQaVsnzMogfNHJPPV3iq6T5po8AIyHjRUtzkZkBTOBSNTWLar0t8mI8aI1ydx//L9QePdFZIMdndPP6juyIwxcssZOXy3v5rqThXa2MwozPqes3DX/2MXRXXKLOX+T/fxwx2TuPWMHADanR4ufWsr20qayUsw8+6i0SRHhNHh9vHMisPsKlV+kx7UlMqJ3JSWQElbcMWpKNOpJfIhhBBCCCH8e2Bz7exReuokWSUC6fJxhJbLkNBSLw6m0deELLlx+8pIVKkIE82ER/wJQTMQqeUOcG8G9QCiIv6GoOrdVF1uvRsk5Z0p214C7QQE7fDTOt8fKh+h0qF8RB9uW8llme8QpgquPD0m5mrGxFzdZx+CICKLcSAF3j11ju/xyUrMKUhlTImIZ3WLBhGRi1Mu7rMvh/soR+sX4pUa0aqSyYv/FJ26d6/F/IgM1CJ4O4dbFmXmXpZHYnwELo+X+SmTmZ/Su0l8niWPPEuA+Pto/kVKH7KM3HonuFYxUQ0/Tb0bwaSkQNbZbIiyPigtTC8aaHE6iTdoiY8yo28XcIYrJyT4YF5eP26aNY4IYyB+TekXTeHONmS9j9cLttLmcfL4vJl9jglAc0cHakHgjd07/eqiRqcD0XQyVhGQPCKjE5K5JGcICzKCK1PH6fudUrUzY0gOF07I5+vthzB4o7nz/PGcmTO4U8UG0TFmXvvgOq7d9XfqCKi3TqYENjY2UlurkFkWi4XExETUarU/w+OmOeMoKKvlcEUgtlM1qlDXqvHGehGdAtqDIvJlyrUN9Y1mvaMa0SAjdQgMdo1gf2Eln/+4FxHQtUjIBhF1gwtjnTKZ6rAHfxf1haGRmajF6dy77zAH2pVn6+qMnp5w1fY2bt60HLekkJDH1n/GxnNv45ZchfwstlVx79YnqXe1Mil2CA8PuBKVqKLR1cD7Jz5kfpiJLN3JsdKg1g5CL27DKbk775iARdNTOR/Cv4j/Y1UCQymBIfzXIjPG2EMt1Rd2l7VQVGfzk1V0plrp1Cr2VrTylx+P0uLwUNrk4NaP9/bZT1M3gqzpNF8MdFaI63rsrmTEb8HDZw1gWv9Y4i06LhyZwtDUYA+ezBgjv9w7lR/vmsLzFw1ld1kLt368hweWH6DOGjCY/GpvFXs70+ecHqU64qnQverg6Mworn1/J3mPrmLCH3/hSI21z317gyzL/HHlET+psqGogd9/ecBf8e7tq0YxOTeGMK0KlaD8Pb3l4z18uK0MgI+vG0degpkYk5abpmbx7e2TmN21mp7bTs2BNZidAd+CkkY7Bypa6QurCmoY8dRqxjzzC9u6peCdTDntinOHJRF5CmVaV1S2OLjtkz1c/d4O4i16Cp6YzeEn53Df7P49nmONSuTFi4cyKj0SQYChKeHcM6u/snHtMwpZBdB0DF4dg/TiAFyVihpKFBUVWdHTc4NSTAEGCSfwdNp83vv5fqpaOxibGc1Llw5jaEo4swfFs/ym8fhkuQdZNSE7QEieNSQxSLV4KoSHafjilgncOSOXh+blseSa0T3ayLLM8fqApN4nyUEKujfXl7CtpBmAwtp2/ryyEICbPtrFR9vK/VU/BeDWM7K5dEwaT88fzIBEC3qNyHnDkrhsdMhYPYQQQgjhfwNGbd8q1mhRxCAq7yYBNxbfbpyeY7h8ZchAtc9HsacVu2AB+3vgWgVyO3h2ILf/udc+ZVkGqTl4pdTYa9vu8EhOP1kF4PA2Ud9RdMp9+oIQ+Qqo80BMQjA/gpPgCcapsVN5fODjPDfkOSbHTuZw60pWVD7Ktob38MkB9Xa19WW8nefv9lVRY33zlMcdHhkgYcJUOsK9kZz79PuMuffvLH5pGbaOvj0le4VnrzLunZDa/8aPm5TYON5k4rVZCxGs+cg+HU6Plp014cz7+XUOtlSTGGXh5XPOJrPDTKbHzFtzzuX5q84mJzEQQ3o8HrYVl+JLduNL9OBL9LC8ZR8uX98TYX/cuJ5Rb77OiDdf79GuodmBIEhERbQTH9tGjMXNgsx8VOLpfeYeth7mxaIXeb34dW46byi7nr+DHx+8iXn9hvrJqpOIjDLxzNgriNOFIyIwN3Ek0+PzkSTJT1YBWK1WCgsL2XP0MC6Pcm+jLUaW/m4hyx+4wt9OQEB7XId+jwGx3IA1XGTxh1/ilSQWXXQO04ovJGrVECYXnc/1l15AR5fiMaIPtHbI05kROgnEy6/pWaWvLwwKz+SFYbdxedosHshbyBUZZ/ZoU25r9ZNVALUd7bR7At8SLxctp87VgozMxob9/Fi7E7vXxh+PPMZx+17eas5koy2OvY5UhMg30Gr78dDAK4nUmDGo9NyUcx5pxlNP1IfwT+Bkzubp/vsPR0hhFcJ/LaKMWt66ciRvbyxhX0WrX20VZdTS7vScMhXuJBIj9D3MoZvsLmRZ7rU6ycKxaWwtacInyRi0Ki4YkUJtm5O7P9vHiUY7cwYn8IezB/rz1iVJZm9FK1qVSE6ciX1dyJLcXszUT/e6379mDHaXl/e3lNJkc5EWZaC82UF4mIZ7ZvXzkwnVrR1c+e52v2n4/spW3r5qFD5JDvIugB4p+z1ww5RsTDoNB6vamJAdTYvDzS+FCulW3ebksW8Oseym8b/SS5fjCQJqUQxy+/t8dxU1bS4+um4sCeF6Prx2LF/sruTeztQ0WYaXfi7iynHp5MSZWHXXFP++To8PSZYVtZOjGd6bTX5jEWu1Ku723ML3knJuG483BBmYd8XDXxX4iZqSBjvZsUaKG+wkhuup6VZhsL7dxcNfFfD2VT1NU9/eUMLao/X0TzDzwJw89BoV1yzZSXG9ldniTr454SPj1rtIS+i9ogpApFHL8psn+KtYVrV2cLjayoAedw5Eez2737qF2vM+42B1GxuKGhiYFM75w1P4ZIfimSHio0YOkE6tDg+rCmq5dlIm5w1L5rxhyUF93joth1fWHgdgUJKFcZlRzBwQz8AkC1EGDfsrWslPDvc/632hrMnO2xtLUIsil49Nw6BVs7O0mZ+P1JEVoxRD8Lo6iDRoaLIrQZ1Bq2JkekCW3rXS4sllSZLZUBT8QSIDU3KVMU2PNrLyztMrPR5CCCGEEMK/D+FhU0iLfIoWxypsrj3IdAAiKsEEgitoSl/u9WNJRKOKR3Y3BK/ug4QSBAHZcDk4/qGsUGWDdjxW51bKmh9Fkp0kR9xDjPF8/z42t5uChjqSTGbM6njavcqkoihoiNAm9XqcX4OgyUeI+ZZWdyVH2lahFUchCkeRZDthmjzizVegFhXl1nHrBtbU/gWAEttm3D47gyPPRa8y9xKfnfo9++jAq/msYg1Wj505iWN5Y9k+yjr9onYXV/HRuj3cNPf04zOE4M9DnyTw7Js/Udvo5ur5YxmTlMKYpHt4cNc3fFV+0jrAxZJjW3lxzAXMHJHLzBGB7IN2pwu9Ro1GpcLhcFBaWkoYLmRTIP7rULkpbK1naHTPsT/a2Mjbu5WMCUmWqW+zEWc20uCwkxoWTk1VG8bYDsLClFjhQHsRX1Zs5aK0iUH92F1uXvxpEycampk1KJfLxg6l0dXI34r+hqeTMCyzl/Hnob0ToycxIDyVr6Y8hE+WUAkiJ8obUamC75Hd5+Gx0q0c62gl9oiBt6fMo6pjCW2eKrLNZ5CTGM3xGmViVKMSsHeZA9xVXkVxQxP942O5ZvE8IOChNnJQKsMHpLD3SCUyMGFcFrkZ8STrw+iXEYcn3k2Fo55UQ+8+a11RYttDqX0D/czxjIuZBcDq2p2U2msYGZXHiMh+WNTaoOrgAyPiCdcGiFibN3gy1+7toMJRht2nCASskpalbZmU2WJYkamQaeNjBjM+5t9TgT2E/zcQIqxC+K/Fq2uP8/xPSordvbP6MTDJQphGzfhOJcifVhbyxvpi6DSe7uoZBDB/WBKXjU7D5vaSFWOkpLNC4KVdDNq7Y25+It9EGSiqa2dkeiTp0UaufX8nWzvVOO9vKWVgkoWLR6UiyzK3fLyHVYeUGZfLx6Rx4cgUjtW1M2NAPBeOTOnRf0FVG7cv3Uttm5NLRqfy+LmD+rz+a5bsZEepMqMYZ9by1c0TyIk3BaVbHa1rD6pwV1jbzuTn1gJwySjFeHp3WQthGhWPnDXwV8f88rGB8rKvdpIZJ9Hu+vUUse54ev5g7vt8f9C92XS8EafH5/cGM2jgbvVyRgpH2S335yvNwh79fLStjMe/PYRPlrljei53m9dAozJDqhF83KX+gu/dSrDWPaWyK7obuN93Zn+mD4ijqNbGea9uotsjREWzg+74YnelX622pbiJBquTv146nGP1Nt7QvMQclVJGum3ZBrjlF1CfWqGlEgU+2V7OI18fRJLh6tSLeFxfgOAMVoppcXPf8v3+cyxusHPZmFT+fEE+x3evYXrVGzzvvZg6OeDZFt6L55nL6+PN9SXUWZ08ce4g2hxuXvz5GIeqrQgCzBucwA8HlWd65oA43rpyVJ+kVbvTw8VvbvWnbm4oauBPF+Rz+dvb/fe8YtdK8quX0eS5J+ia4y0B/4eFY9P5em8VVqcXrVpk8cRMRFEgN97kTyMEiDfryIk7PeVXCCGEEEII/35IsofjDTfQ5lyLSjCTFfMiAiI6dQYGbX9k2YncfC14diKhpdLX3Y9STUbUs4RpspGZj+xYDjgBEcHQdxqdaHkEWTcFJCvopiILWo433OhPRTzR9DtM2pHoNek0dTi4cPlSStta0Ygif551I5HGlbglByOjLiVcm9yj/02Nm/i0/FMAFqYvZHx07wSQ3dvE8rLbcfoUS4NMw1ymJ96ETp2GKATe93XOw0H7FVp/5EDrV4iomRZ3JRpxOx6pAa0qhQTLjacc8zC1jkWZgXQuu3NH0Hab8/SzAQAEzRDksMugYylen8Bfv5yA26tm055irp4/1t9O1019ZOgWz0iyzP3freLbgkKMWg1/W3AWGWoRSZIYn5jAqy0i7s5JS7UgEqPvPTXMI/m69Qs/Xn41Bo2Wj7bv47nKDWiE4PituqOb4g545vu1fL1XGfdtJRVoBZF+/fGTVQD17nrKqspIT07/1XESEXjyrz+weoMS811yzjCmjVGU/t81lXCsQ4nTGlwOVtf+DqNaWd7d9D5P3vAwm3f2o7ahkVHp0TywfgceSbkGlShg1vQ0nW9wtvFh6TrSL1AzX5rN2q1l/LiniJ8PlWAxahl6qY/DVScAuCHrXC5K67swQZWjkGXlf0DuHP82Tz1W72DeLfkegOUV67gj7jx+rKwOqg6eZAi2Gbk4dTovHv0UCZlYXQRnxI9AwINa0ODtHFePJDLc1Pf3TAj/fgiy8u902/6nI0RYhfBfierWDr8fFMALq4t4+ZLhPPjFQdqdXm6Zls2Dc/O4dlImKlHgie8L+GZvsKfN/OFKBQ+LXsNXt0zk5yN1hIdpmDnw1NLUwcnhDE4OeBtUd1Pe1LQqy4eqrX6yCuCTHeXsfmQm0aa+K5/c9/l+TnQSZ+9vKaW2zYlPlpk1MN5v3G11elh9qNZPVgHUt7txeHx+sqqi2cHeilZijFrMOnWvZNJnuypZeedk9BoVUQYt4YbgtLQdJ5r54UA1qVEGFk3I6GF2fcGIFD7aVkZNmxOVKJzSt6kvzB+eTE6cifmvbvYTGCmRYUFG9rNbPmWu+ksAJnGIudmZQMDnwOr08Ni3h/B17v/SL8dYOCfIwxJRG0asTsdZ+YksGB4ciJY32Xl1rVJyeuHYNN7aUIIkw5jMKKYPiEOnVpGfEs6LFw/jzfXFHK1r95NC5wztORN4qDo4NfKHg7VcMKqR+ak25jTs9K8Pbz4AtQchZWSf42N3eflufzVPfnfIf8wPKmKZfNkaZkY24Pz0GvSOapyyhr97F/Qg1IrqbPzx/CEwehFUDOTPVQ3cttXIsQYHPknmD98UEGfRM6VfQOn16NcFfk+rL/dWMbZLUQJZxk9WAfx8pJ5tJxSy1qzTkJ8S7PlR2ugI8hkrabSz4mBNEEH5S7mX/G5vIlU3Aqx/gpmf7p7Kwao2cuNM/kqB71w1mie+O8Shmjaa2t3Utbu44PUtLLtxPHGWYMPTEEIIIYQQ/ufRbP+WNqcyMeaT26lqfZ5o4/mUNN2NSjCSGf0XLFEfglSLKJhx1swEX9fKuV6ijYo/jqAZAjFfg3sPaPojaPL7OKoCQRdQXft8LX6yqnMNHl89ek06XxYeprRNIQ88ksSbO8tYdXnfqpo2Txvvl77vN0r/tOxVoqVPEQUvCebFmHTKe1z21bOp+mM/WQVQ6tiHXp2FICgxlM21D5e3ggSdMgFoFF3Eqqx4UVEjReDDy9amr1mUvR63rwadOhlRCH6fLT9SwIH6OiakpDEnu6eP6lXTR7KnuAq310ekMYwLJ5x63HqDGP4Eqw/M4C9LNtHeocStGd2q+03XpPCduwC71o3Fp2NxenDK/9pjJXxboKTw290eHlnxM5/MnwOdZNdD6WN4p/4wkgD3DplGsjE4hjhQXcxh6zckWIycNyCFb44osclNo0YToVcmH68eN5wWRwdrGvfS2mnYrxZUnBHf85qP1ARbcfzl83V88rsLMIgGHJIyAZkoJmJvs0NPzjIIFS2tfL7lAN/vPcLJqP6z7/ZxxQU3I0tuPHUBm41kUwt6VVvQ/i7quGHOmciyjM1m4xmziT//vIU2qwPLEScP3fIRf3n5CmLjFILIK/m4ffdbVDgUleEWXSHW4oASvcPSxmF7QJG45MQPzLKM5vjROpJTo0hMigw6foWjwE9WAZTZ93O0PRB7ScjstR4DgklEjSqYpJydOIZ+5hRqnc0MCs/0+1HdnH0X31V/RZW1jcN7DOw6YsWx5ztevPacX1Xmh/BvwG9J9QulBIYQwv8MPN2UMLIMD3190G+S/cLqIqb0i/X7O+06EaxGMWhVQaRTuEHDBb0onugkRAwaVa/VyQAuGJHM0z8oQZFRq2JufgJWp4clm08EtVOJAttONLGrtIUBiZagynEn0dzNE+sk4bX6sEKmRRm1XLNkJ7ZuBJRahLQoAwCHqtu45M1t2Fxe1KLA1RMyeH/zCXrLkNSoBDJjes5oFVS1sfCdbf60ypJGO4snZvD6uhJUItw+PRedWuR3s/vj9PgYkxn9TytbBieH89rCEby5oQSjTs0fzh6A3eVla3ETUSYtMYXbSevS3l62J2h/j1fyk1Un0VBxjLjsGVD8Cz59JI6pf+SX4VOxdDP7LqhqY8Frm/3XqVEJvH/NGCIMGgYkWtB0uefzhyczf3gyR2vbWXu0nswYo98zS5JkVh+pw+H2EtvN3FvuVF39zfQpdM1uEEQw9m5UT2cFyMve3saByrYe2wStCdKyUd+2lafeX84P5Vpq6dnXkORw/rSyEBmZxROHkJOq5zpNJfd1plg6PBKPf3soyIh++4kAEeqT5B7pGqJAEDH29A9HONxJ0t12Rg73ze7v35YWZSDCoKG1s7JiYri+8zdZ5m/TT6gim2qGC0XslfuhUQk8fk7PmbiEcD0J4cFBe1q0gXcXjeacv2+itk0hxkqbHLy/pZT75+T16COEEEIIIYT/WcgExzE+2UZVm5L6JskOihtvZ3jKfgRVEi5PGZ4gsgoMmiFBSiRBnQXqrJ7HkWVcUjs60dyrKl6tiiRcP4M25y8AhGn6Y9AO5nhzEyuPB3tUGTQqZMfHyN4yBP1MBG1wlTWH1xFU1W9exB7aOhSCo61jHfmJv6BxrURq/xOztDIpsoG1HcpkT4Q2xU9W1bd/TFnLI4CMWoxhiGU6Ws9yVJ3qIJPootCViICASjQQJvacCFyyfw9PblQIwQ8P7uPvs88mOcbBtuZtxGhjODfpXDIyNDxz53Boj2RkWibRln/O1HrW5CmU12vYvLeErJRo7rpyGrKvBjwFoO7Pp2sL8R3XoVNrcXsFtkaVkTUj4CXa4QmOVW1OJzqdDo1Gg8fjIV4Vzl+GnMvI9JQeflNLd+3mmO8JosJtNFphWHYyi4f9kTBNGDlRgXhHJYrcO3MS9zKJbY1HKbbVMDIqhzyLEtNbnU7WHi3BrNcxYKATbV4RHreK0v3JeOp17Cto4NK4S9nr3otW0DJKPQqV6tTVv8uaW7no7U+wOl2QrcJQLWGslxFFAa1WgyHMyK2jprNpbQ21ThsWjQ+3rCZMUGIhWQZvYy5/+3oNsdEmLj5rJOcOz6fw+xJWrzkIQBXNfPLBJu78nZIO2Oiy+smqk8spyQm0dcY+si/4N6ASVNx0xds0N9nQaFU89qeLGTM+x789ISwnqH1iWD9cUgKHrIFvlwR1JJmRRvY6yql2+ojVG7l9UE+PrExTEpmm4AncQeFDyDEOZPQfX8Yr+VALsPZgMTuPVTC2f1qPPkII4VQIEVYh/FciPdrIJaNS+WxXBQCXjE7l887/n0SLIxA0pUSGUdUayLN+eN4AYk6hdKLzY/22T/awsqAWlSiQHmXgzpm5Pbx+rpucRW68mRMNNqb0iyUr1sSiJTtYdzTATqhEgYVj07jtk71+IrvR5uKWacEvjKsnZPiVYxqVEOTDta+ilZ0nmnuQVQD94i2kdhJWy3ZW+Nt4JZkPt5X1SlbNGZxATh8+WluLm4KOvf5oAz8dqqPRprwY1xc14PJKtDo8aFQCr14+4l9KxTpzUAJndpI/NpeXM/+6wX+/HozL4yZ+8rfdLOfTte5PtEnH1ePT+WCrQoJkUs3Fh8YTa5nBdVMe4dk1VTi+8ZK0bgNf3DIhKCXww61lQdfp8cmUNNhYNDGzz3Ptn2Cmf0LwuN37+X6+2quYu3dXBwHEW/Sojx0LWnckajpHTqg5v3PSa3dZC812NxOyozHq1BTVtfdKVs0ZlMDI9EgOVraRHmPkoZuuJXZjCS/8dDToWnLjTKwvavCnuv5YUMuqu6bg7Ub2dk+DHJISQVmTEogLAtw4NZuUSAO7y1oYlRHJ0JQIHv/uEB6fzJkD4/mpSzGB19YdJyvWSFmTgxkD4hjCcbZGPUmrqo0fo69k8gW3kB1ros7q4sdDtWRGhzG0yseZ9c8hIZJl6GDJrXNJjz794PrN9cVB1ST7ugchhBBCCCH8zyPKcDZ17f+gw3MEATXRhgXUtr/h3+6Tbci4EdCjUUUhCkYkWXlPCajJiXn1V49h8zTwTcX94DtMmtZBlK4fmVFPYdAGWxvkxL5Bs/1bJNlJlPEc7B6RS79aRlNHIJ0/Sq/ntclFyFYl3U92fAhRnwRVGIzXxzPYMpgCawEawUuUOrC/JNvpcB9C3f5nhE5vrgE6B4fcRup9OjJNgQ/8Otv7fv8ur9SI3b2CMHXgHWwWFa+v0TFX9XntG8pLg5Z/qd5JW+sa5M5+j9mOUWwrRkLCorYwQvdoD5XMb8G1F4zn2guU9EfJfQBfw0JEXMhoiTNfCIQjeJV3bp012M9oRr8sBsfHUVBXj1rtY+K4Oh4ue5gcUw7UjmDJ5gIAJmWn8+bl84NIq0/3bmDW5EDKf7u3iqQID9G63ieXAcbF9GdcTGDSzOZyc+m7n1HS2Iwx3MGQCccxdIYH/UaUUVLYjwiznkhUTNdOB+Cg5yhOnQfJKjLAkovX62PHwTK0GjWjBitEy8+FxxWyqhPOGAFzI9y6aBrtHjelra3kxkWzat4N/GXJKrZ+upemuyxExNsQkUhVzeDBx7bh7qy2XFLeyKN3zOsRn3m9AZI0SmcmXh9OnVOJd8I1Bp64aB5/+2wzDa125k8aRF3CMX6s3YFGUDOifDBbm5RnxeP2sfSTTZQkVePyeTk7eTQWVxqjxSupZC/xpjSmJy5GklVIyJTaaxgR3o+i+lJ2uo6hj4BLLAN5ZMjVPdI++4Isy9y8+QvsuUrWibfNh/6Qtk/LlRD+vRAk5d/ptv1PR4iwCuG/Fn++cAhXjk9HEGBQUjh6tegnLQYmWhibGZiBefGSYTyw/ADVrR2cPyKZheN+PTd9xcEaVhYoCiefJFPSaOeeZfvJS7D0ICym9ovF5fHxwZZSBiWHs7u0JWj7k+cN4lidLUh1uf5oQw/C6tYzchidEUWt1cmOkiY+2l7u3zYmI4qdJ3rm5ANEd1H1RBmDiTi3t/e/RGsK6zleb+uVaBqQGJyjnhoV5q/SBgSleXl8Mu9uOuEnnE4FWZbZUtyELCtV547WtfPYN4dod3m5aWoW5w1L5o8rjgSRiy80jueY6GU4R9kp9Wfg6EUAHKmxIgoC/RPMPHHeYC7cfx3b3Bk8470SALtV5qk1dbi8SgBU3ebk0x0V3D0rUE3H3IuHU1ackY+3l9Hq8HDesCRSIhUi8MWfjrKyoJb0aCN/uiDfT3g63F4/WUXns9IVozMiuWtmLsgzYfcSAFyyhrurZ1K4bD+VLR34JJmXflEIrbwEM8tvnkCMSddDzXThiCRumpbDzBc30GhzEW3UsvSGcSzbVRFEVl02OpWrJ2Qw56WN/nWlTQ7Kmx2cMzSJj7aXUVBlRaMS+F0XRRTAn87PJ8akpaK5g3OGJjKtfxzT+gebdy4YkYzbK1HcYAsirFSiwD3LFPXWm+uOcdB8O2HOJsKARfV/BvECwMRNU7O5aaoyczzhjy1IKAFNiSOMP64o5LkLh2A5zQqgJ6tGnkSsWcs1pyAcQwghhBBC+J+DSjQzMOErHO5DaFRxaMRYrM5NODwKORFrusyf4qYSzeTGvkVFyzPISKREPIBO8+sVXXc2fYjDc5wh+jpEARzu3RQ1XMPQpG1BH8SioCHKOJ8DLV9R2PABgjc/iKwC+OqihcR5rgD/XKAP3JuhC2ElCiJ35t7J/rb9SlU3ZxMdHsULSSVYMGj70R0nz0KvCsRYGjGSriYSHZIaSVaUywAOSQdI7GtezqCIsxCFnkqfgTGxrCsLqGCizE5au7z/T9hPIHWmelm9VjY3bua85PN+dUw7fB0cbT9KhCaCDGMGq2v28VHpOoxqPffknUeOOZGWlvuIxNV5fW6umXiQr/cqhJxaJTJzWH/cPg8l9mqiteHE6iN476Jz+XHvPk7od3NUVOKFQlshta0NnMy721Rcxp6KakanB8gojRCB06VBr1NUSaIchtNj5PWC7ejVGi4blI9ercHmcPHnd1ZzvLyBsUMyuP2KqX7ia0dpBSWNSuyqN7iDqgvpw90sOmcMZ4zqx/Hjx3G5XGx27WaNeys44aemDTyUdydvvrKf3YeVCfGzpw3m4Rtnk2gJ/gaQBYEHH5iLL0xg5kvv4pEkhiYn8MK8OWz9RwGgYdczQ4ga1Mrdd1xARZEZt/tn//479inE0iULJ7B7RwnWtg4io4xceFnAJ00rqnlpxA28W7Iar+Tjqqzp9DMn8sZdF3Y5k1HckH0uWlHDF//YzlYC5GbRxAp2FClpit9WbufBiNkkiPkkkI/GrkGnUmLde/pfAkCVo4GPK1b7999pPcQXpVu5PHsSql6ey+6otLexvqbYv+wLl5g0KoPRuX0TjiH8GxFKCQwhhP8cDE4Ox+uTWHGwhhHpkUzpF4vLKzGtfyxh2sAf1OSIMD66buwp+6LTcLrF7iHOrKPD4+ux3SfJlDbZexBWqwpquOmjQKpaVqyR9gYl+tGoBEamR6LqNquQl2Bm5cEaDlS1MT4r2u8jNKbTM2je4ASSIsM4Xm9jRl48Z+TFYXd52V/RikeSETrn6Uw6NXfNDARL10/JZH9lK5uONTIgyUKsScvPR4Lz9ukkslYV1HDbdMX/oNHm4tkVR2hod3HZmDSeu2AIX++rIiUyjDtm5DL/1S1+hZVFr8bqDCi92jo8/mp2p8JtS/fywwHFS+zMgfEcrGylppP8umfZfgYlhbO7LJjs06hErrzhAdYfbWB2vIl5+Yk8sPyAX123aEIGj587iPxZV3F0xcoe96sruj4TALdNz2FHaTMHKtswaFXcNSOXz3dV8d3+agCWbD7ByjunsKW4kZfXKCbzx+ptXPmug8fPGcTYrGh0ahVmvdqfjtoVGdEG3r9mDEadGuY9D7H92bn/AM+W9qdQVmbqVh+u41h9u3+fwtp2NhQ1MC8/kdEZUUEpesv3VPPT4Xr/2DfZ3by+rrjHszUkNYLUKANRRq0/zTTCoCEhXI9Rp+aLmydQWNNOrFlHUkRAcdZkc/HsikLq251cPCo1yKPreH07R2rayUswc6CyDbUoMCw1gkUTMnh/SylhGhVRRq2fbNT4HGicTYGTkrzs3H+Aj+utJEXoWTwpixiTDn23e7LqUC2rD9fxxpUjmfUrfnIAMSYdlS1d1ZMDiTKe3gxgCCGEEEII/36Igh6TbiSy1AyuleRF3EWb7EYlmAgPmxLU1qKfyKDEFb/ap09qR5JdaFQxeCUnOsFL15DD46tDkm2ohOD4bGPdqxxs/RoAgW/pFzuVogblvZdqCSfBZIb2fuANpAnKqizqrO/hlZqJNi4gTJONWlQzMnJk57H+QXXbK0iyg3jzIjTqVE5wLanyO4iCTKHLSJ1PR6Q2nYERgQpv6VHPcrzhJlzeciLC5lDoaaLIVUyCug296MGHQKTKTounkibXCWL1yqSmzbWP6ra/IwgiNwy/G680ioP1dYxLSWVOTjR/OrrFr7Ayqo20edqIUtswqNxIUvWvjq3da+fpI09T61QmaefEn8OrRTvxyQrxdf++JXw5+SHc3gro8sqOjdLzl2vOoqS2mUkDM8hMjuD2PX+jxF6NWlDx4IArmBI7lHEZaZQ3bYMuYbVOFxxj6zXBn6SPzZ3Lo6vq6Je9l1iTgQU5d7Lwq+8o6/QeW11ynE8WXMzLH63j561KZkJxfTO1HXZuWjCRjLhIYkwBZZm1yYjXrUGtVQiw8bFjuXGcQrZlZmbS1NRESVUgU0NC4peybew+HEjD+35dAbctnMK8wf15fPlqrJIHlc6LOb+FZ9o+QKgw4JFNgMD+qlrWFJf49/U61NTvjCFROwhNugNBCPAEORlK/J+dG8+ST2+hurKZlNRoTOaADcKhijpe/3ErgmDgtrkT6GcOeI/uOVxBa3sH6YmRHDpeQ1yEkYnjs9i9o5iCfRXEZFgoiw48B7WuVio8LfTTKTGW1dnBB3t3UljcwKDoBC6dMgydSoOAgIyMKEjE6m2saXmfLbu/5InBDxOnP3UVQotWh1ZU4e40zFcJIo9fdGZIYfW/BTmoGOuvt/0PR4iwCuG/GrIsc9NHu/2EzOiMSJZeP65Pv6lToaCqjUVLdtBoczM0JZw3rxxJXoKZwtoAmRBj0jEsJZziBhvRRi0RBuXDeMOx4FLL8RY9U/vF0mhzc/GoFEWVFW+m0eZiQ1EjeYlm0qON3PyxQnK9sb6Yt64cFfSBrlaJfgWW2yvx7sYSXvrlGJ5OEiYxQs8rl40gK9boPw8Ag1bNe4sCxpden8RXe6v4/kAN64uCS0T/7edjjMqIYlxWNLd9ssevotp8vJGvb53IJ6PH+dt+esNYXltXjFoUuH5yFg98cYA95UrgUFjbzlPfH/ZXNVx5sIY95S2MzojyK6/Kmxx+sgoIUubQSS5VtDhoaHcFrZ+YG82w1AiGdfqRFTfY/GQVneb0N07NInH8LcxImU7qhyeosCpB1sWjUvmlsI46q4thKRFoRIFVBTXMGZwIQIRBy7e3TcLjk9CoRGRZJvfhAOnVaHOzs7SZ0sbgGdkjNe1c8tY2/nh+PpeNSeONK0bywBcHcLh93Dw1G5Uo4PJKXDwqRSGrAFRqGHczFdpK9p7Y7+8rJ85EfbsTpydw3eGd6qLrJ2exo7Q5aPLD2o0YU4kCj549kJs+2o3D7WNMZhQLhiej16j4x+IxvLi6CEmWuWdWP7+Hl06t8vu7dcWdn+5j0/FG/zOQHBnGiLRI1h6t54Z/7MLjk3uovqKMWj6/aRzDUyO5+aM9fsKqHQO18VNIqNsAQJ0mhUU/+bBT3Xn/61lxx2SemZ/P4vd3BhHEPlnmka8PnhZh9ZcLh3DbJ3upau1gwfBkzhv2z5UjDyGEEEII4d8HWWpGbrwApCoEIMJ4I6L53n+qrwbbZ5Q1P4yMl1jTFQyLupoK22ZcUj06UXl3mHUTEFEhe4tBlYzQqeIqt+8KnBM+7pmQwI+FyWhEkdtGj0OrUiFbnkAW9OAtQ9DPptj+Ay2OHwCot33I4IRVaNWJ/n40qhjSox4HwO2rZ1/tn3mv6AD7mhagEmFk/FAeGDaaSG0aajEQn4VpcshPCihrkiNbOWr9Ga/jdWSpGD1eLKKTJp+RHyoe4pLMt9EIMkX1V/kN5O2ufTwwYWOQEfttObexvXk7MdoYxkSN4R8n/kCkWpkwqrJ/TnH7YLLNk/HJXg62fIXd20x/y0xi9IrSeVfLLj9ZBbChcS0+2eBfrnO24fbUECMG3tOSDD7DIs4cHpgw/a5qMyV25R3vlX0sObGCqXHDSEtLY7ZhNsfKjuGRPagFNWelzqJ4/3E8Ph/XTklEDttGbUc/EsKUtM785AS+vvZBvJKEWhTZXlXpJ6sAtlZV0OrsoLJWWefVg9sssvLQMdYdK+Ufd1/CkOQE7ps5iXc278KiD2dx0jzsulJMahOTYyf7+1Kr1cTHx5PenkppQ2Xg/oQlAoH4XqtRodMqMd3FQ/P5cO0e9GOtqMw+hR+w2NEniDhrFKIsItzA1ddN5YN31iv7LBxPckoUyUTx8G1zWbnuEDFRJm67OuAjarGEYRkYbD3S3uHixje/pM2h6PMOltey8uHFhGk1vPHZJj74ejsAoiAgdQaM2j2lDDKH8fF3vycqIZxz1j1Nm1dJvdUIKuJ0io+vzefmvuObqPHYQAbdFg0ldU384dJZXJd1Nm+XfIdZ7UQjKnG1U7bydfXX3JB1A6dCuDaMF8adyxN7fkKSJX4/bCZxYaEqziH8cwgRViH8V6PW6gxSD+0sbeFoXTuDksJxeX0UVLURY9KdlifOsyuO0GhT1Cj7K9v4Yk8VX986kV2lzWwraUKtEjk7P5FbP9nLrrIWdGqRVy8fwcyB8QzoprgakhzO7+cNCFonCAK3Tc/1K5oWLQmUHZZlWFNY1+cH+h1L9wZVHASobnViCdMEkVV0Ej8Ot9dfMVCtErloVCqruxFEdHpcfbmnksPV1iBlkyQrKXdDUgKkRk6cmRcvHuZfnjUwwU9Y0elrBbBsVwX3Lz8AwNsbTzB/eDJ/u2QYRp0KlSj4VU8CMCDRzOEahRCMMWn5Zm8VrY5gw9bZ3VINNd2MOQVBuebbl+5lW0kTAxKiuGVmAunRRoakRPD0/MGUNtq57J1tPPWDIoe+ZmIGj3Ux9j5pri4IAunRBoob7P6+06IMpEcbeG3dcVzd0is/21nBjLw4PtpWRrRJx8V5cYxIj1BSVDW9S6bPH5HC8XobH24rw+uTkGWZv1w4lLs/20dbh4erxmcwMScGgJkD4/nkunE88d2hIOL0JGmUEhnGHdNzSYs2sP2hGbQ6PCRHhPkrsAxODue9RaNpdbhPi8Q9VB3wgjr5DIxIiwzy+upeibDZ7ubFn47x7Pn57C5XniGhM20w4fwvYP8nNLe2Mmd1PHYCaq7j9TaqWzsYnx3N0uvHMv+1LUH99pXK2h258WZ+vHvKabQMIYQQQgjhfw2u9SAF0uVxfAqdhJXH14zTU4xek41GFdV3H4AkeyhrfhS5M2evwfYRMcbzuTTrQxoce5B9u9CrYojVj0NunAVSA4jJEPUhgjqFGH0WbZ4ACZEXOYTZs4JN1QXRjBD+rH+5telp//99Uhvtrp1Eq8/tcW5eycqR2gV4fFVcmQFDI5J59vBZOGsb/OqooCHxKeoenUqJz8LUEQyLupDd9sf9IgdBgBi1HauvhCr7elLlrSSIdhp84AY8UgMeXwM6dSB1ckTkCEZEjvAvDwmPp8IemNgrt+8i2zyZNTXPcdSqEGY7G75gmPlZpqWNwqAKkFMAPlkgWmumya3EHf30abz1yzfcEggBEQUw64YE7dc9VUwjqGhzV/FT9R9p99ZxYdI4TNrxpBlSSdRHc/XgMym17eLn2kfZUOdDQGRu8uNkmQO+X+rOmC/ZbAlS7ESHGTBpdcwY15+9Ryrx6gPKnQ63h1V7juI02tmn28PIMwQWZmSTY9YSpz+7x305iUUZF9Nqc3CgthhPlQUpLYZbL5/CW8s2o9Go+P31Z6LXKvfu3vlT6JcUw9/rv8DRpdCAYJKQNDKT0zKYM6gf2iEDOOu84fh8MjGxgW+FOdMGMXvqQJrddkyaU6vCq1usfrIKoKndQX2bjfTYSD5dsdu/Xuoyu+nNjuPYqgP89O4aohYMpnJPGPp0N1qtyO+GzWdsYj5tbW18W31UIatQgjd3ipfNRxSrhYvTptPcruer6mWYtYFr9Eo9Mwp6w7y0AcxLG3AaLUP4d0OQZYTTTPU73Xb/fyJEWIXwXw2TTo1OLfqJBJUoEGnQYnd5ufStbRysakMA/nh+PpeOOXVVCrc3WJ687mg9t56Rw6TcWCblKtLbT3eUs6uT2HF5JZ5ZcYSZA+O5Ylw6rQ4Pm4sbGZwUzj1n9vQz6I6cWFOQMXt2bO8zDz5J5qfDtT3WK+lcwVXTtpU0ceOHu2nr8DBnUAKvXD7cT1RMzInpoWoCKKqzsWxXZdA6vUZkVMapg8i8biRdv3jl/Nd0Sz/8em8VF49MYUJODE/PH8yjXxfglRTx+uGadhaOTSPCoOGjbeV8vS9Yum7RqxmfHRO0Li3awB3Tc3h5zXEEAe6f3Z/Pd1X60/ga2l3EWfR8tK2cQ9VWcsLhsmFRQb5by3dVcuOUbN7bfAKnx8f1k7P8pvVvXjmKR9/7hharlcXGbQyWYiF1DF/eMoEXfipiTWHg+hIseu76bB9bipWZzP0Vrby4WhmbZTeN71GV8CQa2l3+FMKv91UzINHC7kdn9ZpWOT67Z/W/k6TRLdOySYtWztus1/hJyq7444ojvLmhBKGzr1cXZBJpMYFWIXE73F6O1LaTGK5nUm6sfxxVokCiRXm+Igyn9pPyShIfbSvzpx/KndeIWgsjF+G1Omn7+Zcg2XFEmIZYs+IDNiwtkmcXDOapH47Q4fYhQKjKXwghhBDCfzPEmG7LyrvM4T5CYf1l+KRWRMHCgPhPe5ilB0Pyk1Un0e7cQWL4CNItM4GZSqvWexSyCkCqQra/jRD+BNMT7kMnmmjzVJNrmU66aUxvBwlCmCYHR6dHFYjoNT2rFCrXUoDbFyDlhkRUoRfdDIlO7NH207INvFqkpD7e2u8sLk0PKHws+om0dvwY1F4rekh1vYJGKiVBpSJKFDnk8aBV56BRndozNFqXSUUXZVm0LgOAEttW/zq1ysur+5YyMiGfkZEjmRQziU2Nm/BKIuXtalR4uCJjKrZ2ife/LuKA6OXsDAtpEYrSC81QEGODjjszYRTr6vewt/UYBpWeW3LP55ea56hzKmNZZP2BmXHhNDTfRo3UjEkzkwpfJlJnrqCMRGHbjzTbMvn26BEiDGHcMnwMeo2GFIuFl86cywtbNqJB4PbBw0CSuODMYcRFm/nbD5s43hiwUAi3aPnd3iXYvE5GRZayp2kZe5ogzzKbmUkP9DpuBnUY2z/UUNOoKLVfYB3vP34568660z8ReBKCIDBjaC5PvqRBO0wp/OzzCVidWlTx8OC8KWg7qw1GRvWM7zt8bm7f+Q/2tZQQphaZnzya23LnolVr/GlzjQ475W1tpFgsJEdZqGxpwxfjI8pswNzpoxpu0lPfbOvRv9ChxGNej5c3Nu7AbVPjPqT8BqujfGjSNMTExBBrD/4uEHyQmxj47V4/YByVjlrKfatQqTwYVAbmJc4jhP9whDysQgjhPwdmvYaXLxvOH74pwOuTeXBuHkkRYSzfXemvHCYDD311kNGZUX2SQgBnDkxgV1lAMbSrtAWX14dO/evmgoIgcPuMXG6fkXva537f7P44PIoKbHx2dJ9G0SpRIDXK4K/cBjA5N4ZHzx6IQRv8E374q4O0dSgzeKsO1fLC6iKO1rYTHqbh/jn9abS5eGXNcT9vMDQlHGtn+5MYlhrO4+cO7nWs2hwenllxmIrmDuYPT+Kp+YP5bn81qZEGHj1bmUXpl2DuoQYra3YwAbhsTBrf769mc3FT0PbJubG8urY4aN11kzIZlRHJrtJmxMyooOp+95zZnxHpETyw/CB/XX2M9Ojg2cHtJU1UdPoaHW+D9RvXAkP92+PDdVz85lbKm5Ux/XBrGW9fNZJJubFkt25mqfMW0AIe4Mv9cOc+BiWF89aVI3n4qwJ+KawjO9bEE+cN4py/b+oxToW17Xyzr5orO839G20u3tt0AkmGxRMzqG4LrqRT3ZlG15cHmFbduzpqS3ETl4/tu4BAYa2VNzcoHgoysK24Ac3fzwOVj8bpz3PJ9gy/mkyjEnjx4mE0211sPt7kV619c9tEHpyTR0mDnUPVbWTGGGlsd2F1evFKMkatirtn9WNrt3tq7Hw2a9o6+NPKQrJiTZQ0KIUHsmJNnaq7wPN7+dh0LhqVyqFqK9FGrZ9ADCGEEEII4b8Pgm4ysvFGcCwFMQYh4gUAatvfxicpsZYkWzlafxVDkzYhivpe+xEFHSbdGGyubf51LR2rSQy/6VfOQIl0dCoT0xPv+03nnhP7JmXNj+GVmokzX41RO7jXdlpVMgIaZJQ4yu41c0HWGO4bMj2oXYOzjVeKVvh9pl4p+oGzwg9hlHaCJo+sqOc43uTE6lRSx3yySIb5QjTSh4FjCQIpxgVERTyEKPScRGp0FrOt4V1kJEZEXY4k+2hwHiPFMJz8CMV03Sim0ioVKqMjQ1VbGM0dHZi1OhZnLOaD4mP4/B+vTvpbUjhUbkOWBDokDVd+uYCbx5Zy2dhR7OoYg62+gPExeehVikJIK6r589CbWVr+M0vLfuaJgveYG18VdJ7tjndBUoglm+dnRNeMoO1ur5nLv1uGW+8GFbx3bCc/nreYKH0YQ40W/joiYFVRV1dHcnIyk0dm0y87nof+sZKSumamDspi0vA03truxKBykWsKTA4XWn9kZPRlROqUSewDjTV8feIQCQYzV/cfSX1ze9D51DW1MzCzd4JQkmU8VXp81mic/d24PBokn4gPH7vqqsiNiul1P4Avy3exr6UEndqHhI8vq7Zga23lkqixlPrg96t/plXlAgHijSZeueos7t72DdVSG7W0ccW6j/nqzGt4/LazeOyVH2i1dpCRHEVNXSvOmla0u06QlJPAubfMZtUPq4KObehUiR1qO8YB+zrGp3nYXS0gu7VM1mTz1MWz/W1VosjTo8/H4Z1DjbOGOF0cZk3vFcZDCOF/CiHCKoT/eswelNAjbUzX7QNfkuG5VYW8eeWoPvsZkxWsZNGqRb8U+STOG5bMsl0V7ClvRacWeWjePyd1Lapr5+NtZUQZtHx03Vgseg0+SabF7iayF8Pod64axR++OURbh4frp2SyYHjvVTY63MEqsbc3lODtlOMcrW1nxZ2TOWdoEluLm+gXb2Z8djS3L91LSaPdv8/t03PJSzDj9ko9iJLfLd/vV2ltLWnio2vHsuzG8UFtbjsjh9WHaznSmepn1qmYlBN4afdPsAQRVv0TzGTHmoKMyzNjjAxKtnDLx3uQZMXT6YubJwRVNHzs28PUdfpdHau3oRJkfLKAKEBqlMFPWAGYcPK78DV8KM8jxqzl1jNyuLmLSb4M3PrJHlxemasMW3kyaFADqZJqlcifLwyWwM8cGM8nXao5nsTJZ9Dtlbj0rW0cr1dmwFYW1HDT1Gw2H1fGQKsS6Z9g5nef7yfCoOG2M3IJ76ZouvfM/tz04e4ehQAGJYX3OG7gomTcq58BAulyEiI+VCA5Cf/5PkqcSwDlPD0+mXuW7UPfhaC1u32sPlzPzdOy+frWiUHdd7h9/HKkDqfXR794M4OTw9l0vJG95a2kRRl4cK6ikLrug10cqlZmZDWiwPd3TqJ/QnAVypPQqES/V1kIIYQQQgj/3RDN9/rTAP3rhOBKxl6pkQb7Z8Sbr+6znwj9lCDCSiX2tHkQjDcju7d3pgQmIRiv/6fOeduq/ez85RAZeVdx9uKpCIKAJDuRZQ8qMfhDXa9JJyvmZWraXkEUDQxMeIxpWT3JLZfk8ZNVALMjSjE6v1QW3BsRZC/94z6grWMjTm8J4frJ6NSpyA0/gVR38gKJi3gYSdAjy3KQebVXcvFtxf04fEq8UttxmCuzP0KvCn7XnpX6GM/vfRAJKweq0ojVDSDZrLQRBIFMYwLHbYrXqEoQSTfEokoJxF1NDgNH2y/mL+VWvqn6FIA8SwqvjbrJn+ZY52zhgxMrkTqvt6BNR//OYdOJFjSCk67TpFFSNinqeJo5Rrw+j7qmibg1m/3m7jafk7N+fId2j5M8UzQPp4zGolbiZJ8vEBPFR5h4946L/MseyUumMZ6ajkpkWUm1PAlVp6/Y8bYmLv7xY5w+JfY80lLPnAkD+GGToghLjLFQKzl44KtVDEiI46pxwxG7dGQO03HTnHG8sWob7kYRyaRcsygI5EUHq8+6wuv1UttQhygEK1uOuutwud08sGo97RqlqqFG60EdV8LjxW9g0wvgUCZvj7Y1cLS1nuEDUvj21RuD+mltaOOngkIsSREYY8w8MvcMbvrkaxpsDiZlp3PRiME0uVp49shrOCUljp6WGc2rwx9BFHufIDWoDWSbsvu8phD+wyADp+esETJdDyGE/78wd3AC6VEGypoDqiSn59S/3GGpEVw/OZO3N55AqxZ57sIhPRQvYVoVy24cT2mTg2ijtldy6ddQb3Vy0Rtb/UqoHSeaeXL+IK5+bwd1Vhcj0yP5YPEYTF3UJ7nxZpbeMO4UvSq4c2Yuv//yIJIMSeF6qtsCOe+Ha6y8/EsRt0/PpV98IOh6ZsFgTDoVZU0O5uUnsq+ilev+sQuNSuSPC/K5YGSAHDtSaw063pEaK5Nyg2eQtGqRH26fzBd7KqlvdzElNwaPT8Ljk1CLApFGDSmRYfgkmQtHpHDluHQEQeDj68by5voS9BoVd8/K5Y6le/2pb20dHr7aW8nvZgfSxFrswV5Xd6s+wzL0PAaPnYFereLS19dj9YgY6WCxagUZUcnccN0ZaFQiVqcHg1aFowvB5/IqB/vakc+NhiSST1bWGXfLKcf8qfMGKyl9pc2sPlyH3e1jWv9Y5g9TTDOrWjv8ZBVAWZOD4WkRLL1+HEdqrKRHG7h96V7/uRyobOOzG8fT5vBg0qnYV9lKtFHLxgfOoKbVycqD1eyrbGNURhQ3TOk9TQGAExvIP/4G80QdKySlQuaNqm8JFxRyUsTXWf8lAI9PxuMLTr1IiQyjN/x4qJZ7lu1DkpX01K9umcBXt0zE5vL6n11JkjlcE3hmPJLMpmONfRJWIYQQQggh/N9GkuUOGm1fIHfx/ZFk5yn3iTNfTatzHTbXDjSqRNIiHunRRtDkQsxPINV0mq73/u46FXasPsgTV77uX25ramfurT5ONN2PjJs40yK/2fpJRBnmEmWYe8p+UwwxzE4czo81ewE4MyY4dqywrqLJN5sRkZMJJ5AqSNQS5PYXQHaD4VqKmu7G6tyIRhVPv9gl/lRKh7fFT1YBuCQb7Z66HoRVpC6eB4a/zmeHC8jJFpiVnEV9YztJceFYnU6SWnJpkF1YTGpuzJtFtjmR7P7wpwtms/rwcTJiIrlu6ijmbQyMQaG1koOtZYyK7qxo6HX4ySqAQnscc/VnkpRoJit8Ai7XBkqbHwQkBF8KomcqA4yJ9EvORBAEtlEBbPbvL6hk2j3K81Foa+KLxmNckzAIQRCIiurbukIjqnl11I18WbkVjy8Kj28dMjLjYq7BolEmubfXlfvJKoD1VSXsuvYOxg5Op93uQrIIPLZyDQDfHDiCw+3mhklj6HB7EAQ4UtnAueMGcvboAdTZbSwtPUC93cbFeUMYHtd3AZimpiYm6NJYJRbgIBAfpmui8UoyHV4vdM5bJqQ1o9N7cOEmxgIujxqXR4NWVBEX1rvS6c8Ht/Pp4YNwCMYeSuHD8y5kwz034PB4MGqVZ6/aXu8nqwDqXU2U2mvJMocK1/xfQMjDKoQQ/gugVol8eO1Yzn99M402N0atilum/frMwMNnDeTuWf1weyW/KXRSRHDQo1aJQUqf34qDVW1+sgpgR2kzT3132O+xtLushfc2nSDKqMXjk7hibBqa00hLBLhkdBqjMqKoszpJsOg579XNftUSwIurjxFp0HLl+Az/Ootewx/PV1RDR2qszH1pI3Qqg37/5UHOGpLoNxCfnBvrVxNpVEKv/koAoihw0ahUdpY2c/k727nI8x0L9ZsQw1P4uPpialH2e2/LCWYPTmBwcjhDUiJ4dWHANDSqGxkY2c1c/rrJWby4WilDnSVUc6XqF8JjB0HahTz/41F8ooY4dTt/4C2eZTF7TqQT88c1vH/NaAYnh/P+pbnc+vFuWn1aPAQUTVZM3KB/jh/OlsAYB+nBCrIjNVYe+bqAtg4PN0zO4uLRqVw5Lp0rx6Xj9krYXN6gc4+36Igyav3+TuFhGhLDw8hLsDA+O5oVB2uCiLMdJ5qZ/bcNHK1tDyLVrpucySNnDSQ/5RSqqq6QlIDqVc1LFMiZiEgI5njoFNMVDbgN9ql6nVmJM+vQa1ScPSSRmQPie/XWentjiZ9QbGh38eS3h9h6ohmfJHPXjFxumJqNKApMyI72q8kAnvrhCIdqrLx48TCW7argxZ+K0GlEnp4/mMm5fc9IhhBCCCGE8N8PrTqRrOiXKGm6AxkPOnUmMcYLT7mPSjQyIH4ZXsmK0+emxVODqLKhUwXHYoJoBLGn2fnpYt+Gwm7Lh8i7bImfXKu3vU+Ufip4S1Cp0zAYZp12338YfCnnpyjxxCD9MeTWgGJst13NitrXeGzgY6QaAmbqgjoHIVIh0Gqt72J1KvGZx1dHecsT5MV/BoBRE0OUNp1mt2KWbdYkEKHtXYlv0em5fvgolq7YzaXPvYcsw5QRadTFSOysLyM2vxGP7OXjEz8yOioXkyaMc4cP5NzhCjnmkyWMah12b5fKxtpACn+mKYlh4TnsazsOwHBtJmnCSDLDMlGJKj6sraDGPpZklYEk97m82fozbTUOBlan8rcR1zEuJZW7h0zgb4c3I4s9P6Y1JgOpqano9Xp0umC13ndlh3j18GYMKi2PjzyTIdFJXJOl+Jy5ffcAMlpVQJ2XFxGL0EVgkhcZhygKzBmvZE888cMvQf2vKSxm6co9tDlc6MLUOD1e1CqR5686ixn5OYzK6H3Mu0OWZcwqHX9KOIfv2g9QJbWSqonkbGM+OlHNhfkD+PzQYbwqGY0meBIxzWxE8pq5N38q4bqen/FWl1MhqzqxvbqSO9/7hn0HKjFqtDx/4zkM7Z9MuiEZi9qE1asQZh6fyKLtf+f+AeczL2kkrxz7ko0N+0kKi+GhgVcSrz+1r20IIfxPQpDl/11azWq1Eh4eTltbGxZLaJY9hP9ZtDk8HK1rJyPaQJyld3+E7mi0ubjg9S2UNTnQdlYC7Kt63z+D8iYHs/663m8UnxtnItKgZUdpwCwyIkxDayepFWvWse3B6ahOo8pbdxyutnLtBzup6aK0umxMqp+g6o7dZS1c8HpwtbaDj5/pN/P2+iTe31JKZUsHZw1JZPSvGLNf+PoWwirW86H2T/51W30DucwTmB0dkRbBl7dM7LFvRbODGz/czfEGGzPy4njp0uE9UhR3ffsGjTuXM0EswKIBrlvNFlsil7+z3d8mXK+izRkghCZkR/PJuRZ4fx50tGCVDSx0P8RBWVEriQL86YIhXDwqld4w+bk1VDQr6YaCAD/cPpmBSb38LWs+AcsXQ3MJzRlzudexCB8id8/MZXhapL9ZSYONOS9t9FfFizRoaHF4evYH7P3DrB7EXZ/weWHpJXD8Z0DgudRX+aQylvgwmb+elcjAQUM4UmOl9sQhavas4KHKcf7rf3fRaKb1i+XBLw7y2a4KzDo1f798ONP6x/m7v/ztbX6z+d7w891TyIk30+708Lefi3h3U2nQ9vcWjeK6D3b5SS+TTs3uR2eelmdcCP97CL2z/99B6F6H8L8Jl7cSt7cGg3Zgryl+vaHSvo8fKh/CIzsxqmO4IO1lLNpTG5D/Fqz5fDt/uWWJf/nc6ycx6qY/+HNr1EB/jQm9oBBYtap5JMX+7Z86luz8kQ2Vz1LmCWOtLQEQuCnrJsZGj+21fXXbK1S1Pe9fNmjzGZTwnX/Z4W1hX/NyZHwMjbwAk6bvCSCn28OMRX8Pqirnydeiy63BEBuwU7g8bRbXZPU02N7WeJRnD32Ow+diUeYMrsicFrTdK/n4oXA9bqeb/ppkwvR6srOz+bbmC1bVfutvJ8gJHGgJxHU3ZM/m3MjhHCsu5faXf8FrAlkjYR3tRVZDuFbPJ9OvIC8iju440d7MnBVv4ZWVexWtM7Bt/p1BKXwn0d7eTnV1NbIss9Pdxg81xcQbTDwyagaxYYFn8ct9h3jom5/8y2adBrvDhcomdNZDVhBnMfLL4zf0Od7d4Xa7OXHiBB6PB5dX4r2tx9hfWsfg1DievWoOURYTW06UU9/ayjb3FnZ3HAUgQmPi9VH3oVepeOHoC5Q6SknQJ3Bvv3uJ0SnZDi6vl6Fvv4qri3LMWCqgcivna5bUbHrldgCqOup4q3g52xqPYfdokRGI0Bi5vf9sXjj6qX//0VF5PDvkRkL4z0Jv7+yT66YPexC1SverfQB4fS7W7PvTf/S7P6SwCuH/NMINGsZk/rZZgWW7KvwG526vxEu/FAURVnaXlx8P1RKmUTF7UEKPyiG/hrRoA+9ePZp3NpVg1mt4YE5/jtfb2P9hKy6vRIxRQ6M9QFg0tLv4/kAN5w1P/k3HARiYZOHaSZk8/cMR/7pTqViGpUYwrX+sv3rhtZMygyrPqVUi100+RRpaN8hAplATtC5TDF52dPPdOonUKAMr7pzcY32TzcXO0hbSogyMOvcm6JcGTcchZybED6RhXzeDT1dw/812F2x91e9NZREc3KD+nts9d7B4YgaXj00jJ653mbVPkqnq4o0ly1DZ4uidsPr+LqhWfLKiCpey5NyJMOLKHs2yYk28v2g0H24rQ5JlfulWZbEr9pe3Mi0vEKjJskyjzY0lTO0nej7ZXs6BylbGZkWx4PJlSLUHufb7VtYeswMeWjvg7p9a+XEQDIjVMWDpdWCtJF3zCwfU+Yy57BFG9otjbWE9n+2q6BxDL/cvP8COh2f6j/3keYO47v2dlDfbGSYWs0cKLjhwvMFOTrwZs17D7dNzeW9zaVAhknan109WAdhcXhyuUxc5+GhbGQcqWxmXFc35I05vJjOEEEIIIYT/POjUKejUv+3v+O6mj/F0pg/avY0cbP2aiXEB83WXtwKrcyt6dSZm/ejffE7TLxpLW5ONnb8UkJGXxKKH59PgrKfa+jIAMZpU9EKgqprR8yOyLCEIv31CUdDPZq90hP22/QDoRf0pPYJijBfRYFuK21eFgIZEy61B2w3qSCbE/XO+XQBZZjPVquBKzR0+V69tx8X059upPdMySxqbOd7QxNDkRM7Jm0ZrayuSJBEREYEoirR72oLa27xWIKLLcgf19fXotCpMKg2OFi+gInadinvvnsnUrGxiw3rPcKi2t/nJKpBpcjlweN2YNMEf7ZIkUVFRgSQpbYeLRi4540K02p6TgecPG0SH28OWknJcRg8/Nx8HAQQXGI5pEL1K/N/QZscnSai6+D95fD5aO5xEGw2IgoDD6+aNw1tpctm5KGso+Tk51NuauXP72zRkNYFJz9bdTt5evZMHLjiD4QmxFNutZKkn0l8Vj1sjMb//GcTowvm0/FNKHcokYK2zli8qv+DGbIVQ0qnVvDhrLg/88iMur5dMj5Fad8Cn1i55/OeaHBbPtNgp/FwT8GFVCSJNruD71OQKtgPpDp9kp8b6Gl5fMzGmizHphp+yfQj/CwhVCQwhhP/b6P7B3HXZ6fFxyVtbKahS/nifNSSRVy8f0aOPX8Ok3Jgg76eUSANr75tGebODCIOGOX/bGNTerP/nf6rXTc7CEqahoKqNCdnRzBncs9zySahEgXevHs2u0mb0GhVD/0UD7N/N7s9THwzHJn9GnRzJamkkUnQ/DC1KqptaFLj1jBxWFdRQ0mhnWr+43smfTlS3djD/1c3Ut7sQBXjuwqFcODJ49m9avzjSowNVFc16TVAK5oDEcNAEq+0ETRhXj0rnkbMGnpKAVIkCc/MT+eGAQroJgvJM9ApbN+LJVtd7O2BCTgwTcmL4/ZcH/Cb5vcHSxYy9w+1j0ZIdbD/RTIRBw7tXj2ZveYufnPx0Z0XnOyiGtSXBJF5du5MTjXaS5Dq8bQ187DsLDyoulX4g2nwLkNqDSOy+nBNnZt2YHfjW/olWTIx1vYq385WiUQlMzlXSPn88VMtj3xwiTBNIb7xxahazByUwKMniN2Q/c2D8KT3h3tlY4r+2ZbsqofP398uRetSiwMwB8b+ZPA4hhBBCCOG/ByfNsv3LQmC5w1PMkdr5+GSl4Et65DPEmRf+5mMsuGkGC24KVK5L1t9DpGEePtmOs2MrOF8OHFNS86/oEW7Ovpkf636k3dPO5NjJfpVMb9Cq4xmUuAKHuwCtKgW9pu8Kwb8GvVbDzZdN5rWlG5BlOOMMmXHjm9jZlMAOuRxJkIjQmJibOIY19WtwS24mRk88ZXW4tUUl3PHZd3gkCYtex8fXXExuXPD1TIiZwo7mrXhkNyIiDc7gWCw/PB3RKqISRW69aAQfrzqMT4LrL5rIWYN6r9R4EkOik0g3hWMyHSHKYEeQTXRIVkwET9JKkuQnq07C6/X2SlgBLBwzjIVjhjH1qzf9oipZB95wCW2TYqugE9VBSq7ixmYWf/wFtVYbefGxLLniAh7Y9R1rqpU0ya9LC/h+znV8Xv0zTZpGRECX0oHXaqW61Up5WytGr49qh5319TVEaPTMSU71p+W5pWAPV5cUTCzOy+lHnqjGZrez+0Q9fys54N+WERPpJ9beLfmB76s3E6UTaHH50Io67huwgExTLJ9XrMXuU8jhOYm9q/4C13sbbc61ADQ5vmZQwgrsUhT7Wo+TqI9mYHjGKfcPIYRfQ4iwCiGEbrh8TBo/Hqplx4lmoo1a/nD2QP+2A5VtfrIK4IcDNTy7wEN4WM8Sw78VSRFhWJ0eShvtnJWfwA8HawEYnRHJ9AG/npLY6nDz4uoimuxuLhudFkSIXTwqtc8Ut+5QiQJjs3r3pgLA7YDVj0JtAWRPh6n3B5df6YJxWdF88sAV7DuQx03fN2DzqqAOrpmYyoy8eJIjw1hZUMNzqxS580s/H+OLmycwOLl3n6av9lZR31kZUJIVEuPCTlP4JpuLWz/Zw8HKNkamR3Lz1CySIgws3VHOyoJafx8zB8RD5u+gdBM0FEJUNmdf9XfOjji98bluYqafsJJlePirAs4ZmuSv2OP2SlS1dhA3dDHG1Z2ltPURMGhBn30erray/UQTNmewV8Gw1HAOVVvx+GSuHp/OiC6phJ/tLGf7CSWNtNXh4cnvDxPTjfDZUtxEdmzP2Ui3V+KM59eRGaEmQnqcvV4l8P1Cns4PpnTCgOl5ceQnh3OwSplpu2NGL74g9gZUgkw07Xyl+QNPqO9AiB/AswvyMeo0tDs93LF0rz/9VS0KfHPbRH91w2U3jueHgzXoNSrmDT51Wkf39MPNxxv5dEeFP5V2Xr5SLbS00cGMAXF9PkMhhBBCCCH8d2JC7PU0Oo9j8zYQq+/HsKhAVbhmx3d+sgqgwfbJP0VY9QaDNo/NtSfo8M4iR1xFonCMdkmNzXAHCaehrnK4D1NjfRNR0JAUfic6tRJv6FQ6zk0697TPQy2GY9H3tFA4CbfbTU1NDT6fj5iYmFOm91xxzmjOnJDHoaaVHJLeoBxISBB5Lu5BvKSSbUrmnRNvcMh6CIB19et4fNDj6FW922t8uH0vnk4iyOp0sXxPAb+fo6QK7q+s4f6vVtFs7+DCceczJd9Ckj6VW3d9CJ2m41pRzYDwVMKMKsrLy+mXFsmL984hLS0tqCJiXzBrdNw8NJkVtbuUFYKNpeVLuSP3Dn8bu9NNo9WOwWjCYVeOGxYWhl7ft2XI1sZCKh1NmLTB5zAqLYWDdTVo1SJPXj4r6BxfXLOJWqvSf2FdA0u27mZrc5l/u9PnZV9jVQ/lkmCRWGEt4dsPjzMuKZmCujpsnal9xR123hiskHYz4mewo3kHdp8dnahjTsKcHuft8/kQBYHRWfFcP2kgG4pqSYuL4ulFStudzYV8Wv6zv32OJZbXRt6LQa0o0l4fdS97WopICotleGRuj/67ot211f9/Se6g2r6JBw4V0epRxuDm7PMwadx4ZA+TYyZj0fxnpp39n4IUlLX6623/wxEirEIIoRtOVgJssrmwhGnQdPGOijZpEYSAetKkU2PQ/ns8d77ZV8XdnylV16KNWr65ZSJRJi2pUYbT2Btu+XiP/6P+p4JazhueTLRJy3WTsogwaBAFoYdx9j+Fnx+Hne8o/6/YBqZYGLW4z+bhBg1F3gRs3oBH10+H6njsnEEAfL8/kCLo8kr8dLiuT7KhOzHYdfm2T/ayrUQ5xoZjjQxJieDSMekMTg5HFAXKmuzMHZzIWUM6FWa3bFPSAvUR0EcZ397Q7gomlWwuL/ct28/Fo1PJiTNx6VvbOFZvI8KQzgfzvmWopgIyp0BEWq/97S5r5rK3tuP2KW+MrFgjJxrtmHVqEiPCePHiYUSbdD2u/WR7/7JXIj8lnF8KA8qu/ORwzugfx+vrjmPtJMPSosIo7/TgOtHqBQKztCW+OI62wjCz8jv4/Kbx7ClrIdKoZUBiLwHGsIWwbyl47ORrKll+cQLkTQiMldPrJ6uAHuoxo0592kRqfnI4a7pcW6xZxxd7AsqxFQdrWdFJ8r685hjXTcrk3jP79/A9CyGEEEII4b8TUboMrsr+BKfPSpgqIogk0IjBShqN6t9XxOPhnSv4tHgfAKNiLua1STMwqk3EqH99YsTra+Vo/UK8kmJD0Ni+hfXrHicxJpJL5oxApfIiCKfnNfNrKCsrw+VSJvXKy8vJyck5JRkTF21mR8f+k5wRMhINrt3MTJyJ3Wv3k1UAda46Su2l5Fnyeu3Log++BkuYclxZ9rD7yKPcPLSWtWUZLFnvYmr6BaRHp/HC8MX8veh7XJKHxVkzidUr4zlgwAB8Ph9q9W/9TA32/zxWUs6rn3/PxYsnU2G3ccdb39De4aJ/ciwvXn0mJr0Wi8WC2EcM+HHpel47tgIAvV5LsiWWWruDeKOR/Iw4Xpp/NiadHr02+DzdPl+P5fyoBHY0KDYLakFkQGQ8lrAx7G4pQkZGjQqPFO5Pa9xWHayM31QXSNdMDkvmmfxnqHRUkqBPIFrXc5I5KiqKmholvp6Rn8YN888IUpG1uIPJMqvH7ierABLDYjgrrG/FX1cYtEOwuXYAIKBhn1Xyk1UA39UsA0GJO7+vXsX5SdcwK/G3Z6eEcPoIVQkMIYT/RxBt6hlAZMeaeOq8wfx1dRF6jYo/np8fRGidDk7WORAEAavTw6c7lNzxb/ZV+z19muxu1hbVc9fMfqfd757yQEljjySzfLeSNvX5rkpaHW40KpE/XZDPguH/ovdP/eFuy0eCFmvaOlhVUEuMScfZQxIRBMGv0jmJ1KhA5cW0KAOHawIvzvRTEHSXjE5lS3EjqwpqSYsy8NR8ZbZp9eE6tpYEK3AabUrQFmXU9p62KQhgCPib7TjRzHubTmDSq7nvzP4khPce5I3JjGJoSjj7K5VrkoEv9lbx3YEaLhyVwrF65SXd6vDw/MFwPrz2ij6vh87705V88vlktKKA1ell5cFaiutt/HT31B77XTQylU93VlDSYEerErlrZi4z8uKQZBQPq8xorhyXxl2f7cfq9CIA5wxNoqA6+F7o1KKfVBIFKG20MawzFVSvUTEhp/eARZZlaowDMC9ej7l+N8QPgoT8oDZNNldQAYHRGZH0j+87pWB9UQN//+UYOo3IQ/MG+JVYALdPVxReJz2s5g5O4K0NgUqFXSv9+CSZNzeUUNxg552rR51y/EMIIYQQQvjvgSioMKgje6yPNV2K3b2fFscq9Jos0qOe+s19d/Uhkr3HwfkTTjmKz4qL/XKFXY2VlFh9jI47PRWv01viJ6uUC6hm9ZatdDjCGJ3yR3ISCpDFRITINxE0vZNBpwNZlv1k1Um43e4gwqquo5CajgLi9P1JMuTjlXwcaG3B0uVrMFyTBIBepcekNmHrrCKnElS9EiMncf+ZUzjR1MKx+ibGZaayaLwSd8ntf2FR/gYAzu1XxI0r5tFkV8iL/pZkXhnV08xbEIQgsqqg5TtK7duI1mUxJuYqVELvWQ2TYiaxvmE9dp8d2QcVn8oc27OdXVuO4ZueSHuHMj5Hqxr48WAp184ac8rx/K5ip3/ZKbnpFxVGrdNGnbOdtwu34fR5eHzk7B773jhxDLvLq7G73cSZjVwxehhhYaN4fv86Gl12LsseTlyYibu27KTKYSFcL3J5zgg+atqLXhZx2np+f2hdApV1raTEK/FZuCac8PDen0FJdmMKd5ChT8HrAaPRiEYTPGaNzSrwaUGlpBeelTSh175O4q0j21hZcYQMcxSPjTiTCF0gjs+JeY3K1ufwSs3Emi6nsdUIKASviOQnq5RxtPGnIx/S6ungorS+1YIh/IsIeViFEML/DRyra+dwjZXhqZGkRZ+eignginHpXDEuoEopbbRTVNfOkJSIPkmOk/hoWxlP/3AYAYFHzx7Ax9vL/R4+xm5Krd+aZjg6I4qNxxp7rG+2Ky8jl1figeUHmTMokbB/RRWWeyaUnvTYEiAnUNa5vt3Jua9spqEzbW/HiWbuO7M/X3czQr9lWsBY9OkFg/FKEiUNdmYPTuD8EX2by2tUIq8tHIkkyUF+RTu7VFikk4u66DSVO7VtTj7cWspbG0vw+JQ/2gVVbay6a0qPtkdr29l4rIFbpuUgCHD3Z/uwd/oyuX0Sta0dQe2lX3kJPP/jUT7dWRG0rqzZEbRcVGejw+3rcc8ijVq+v30SR2raSQzXkxShBA/3zAqQnNtLmvh2vzIrJ4P//yeRFK7nD+cM5I5P9+H2Skgy3P/FQUamR51S2ef1Sdzw4W7WFNajU4u8fNk0ZicEp/RJksziD3b5ySqVAM8uyEfdB8Fb2+bkxg934fQo5NmiJTvZ8uB0PyGsVoncPSuYwH1q/mD+vLIQrVokJTKMfRXBZNwvhXV4fVKfxwwhhBBCCOE/D0esR2j3tjPYMhiD+vTiM0FQkRn9HJnRz/nX1XYcxumzkmwYhkbsOz6TZJnf/byKr4uOEG80smTuKHK5DmQ7OuDxfgN5rChAbli0p1d1GkCvyUYtRuOVlEm1uoYIbHYD88cfJiehoPMEapCtTyFEf3za/XaHIAiYTCZstk6CSaUiLCxAKpTbd/Jdxe+RO3OF5iT9gWpnFD/X6xkZEUWU1k6bJ5Kboy5R9hdU3JV7F5+Uf4JLcnFe0nnE6vpWrSWFW/jmpiuRZDm4Mp97Z1C7aRktTMo+Pf+tElsJO5u+oqHjBwBKbVvxSk4mx9/ao+32xqOU2Oq4NuN2qqrKeeP+X/BWK3F0TUUzkZ7gcz9VeOZye7n3ua8oT2pD6BJK7qiqASHw6XywuabX/UelJfPTrYsob2kjNzYac6f67E9jz/K3eengBo5ZGwEN7W43n1VsQBMOUeHQUmNmRHh/xsQk8cqmbQhuUBW7ua/sKz594ZpTjpnLW8XR+stxecvQqpLpH/cxGk2wH+2RxgYeXbsexGiMZicxunCunXZWn32urDjCn/evAeBAcw1eycffJ57v365RxQT97mbpJQraSlhXv5eEsGj0Kh92n2L8LsnglVSsqzsYIqxCOG2ECKsQ/p/E2qP13PCPXXh8MgatiqXXj/unDMY3FDVw3T924fZKmHUqPr95AnkJgdSpr/dWUdHsYNageCINWv7wTYFfEfLI1wVBVdLsbh+pkWFUtXYwa2A8C8ee3gt947EGfj5cx+TcGPrFmai1ulhXVI/d1dMM3O2TcHl7kh+/CRPvAGMs1BVA1v/X3n3HR1GnDxz/zGxJ2fReSCEh9N6LdAHBgtgQQUXxxILl1LOenuf9PL07vbOXE+wCCiiiIggiItJ7SygJCSGF9L7ZOr8/NmyyKRA8kPa8Xy9eL2Z2ZnZ2s8l895nn+zwjIaW+c9xbPx1yB6uoqzn1yNgOTQ4R7l8/2Avz82L2rafWzUdVXdlp/1yWRk6pmcQwz5bYk3rF0ieh6R3YxoqrLEx8cy3HKjzvSqblV2Kxe3as25NTznXvrHMHVJ6+ojN9EkNYc8DVUVGnKtx2SVsyi2vIKKomwFvPQ2OavvbjjhTX8MZPh056jj3iglr8efka9fRJCGb1/gI+XJdJ5+gArm5lN8kAHz0rHx7OO6vTsTaYtme1OzlcVH3CgNXyvcfc0/MsdidPL97DJ+uz2JBRTJfYQN67uQ8+Rp3HZ8GhuTpeprSQYZVdWuN+b6nrjlluthHWTKbjcVMHJLh/T4qrLDwwfwdrD9UHbdsE+0iwSgghziMLjy7kuzxXgCLKO4qnOz3d6qBVQxsLP2Rz8ccAhHm149qEVzGorgCOw1lNYdU8NByEm27gu0P5fLnflT2eV1XFyv0fk9K+vrPatdH5vHzYm1qHjQe6DqVDUEQLz1pP0zT2ln1DsSWTNv5Poto3UFRq4c33QnE6VUzetkY7VLV0qFaLj4+nuLgYh8NBcHCwO6vG4XSyJGs+qPVd9PZXrMTPeAN2TcfG0rYABBp8PQrbJ/sl83Tnp0/pHFRFwWw9QE75K4CTeH0cenv91MKJfW/Ez+fkAb/UilRePvAy0cZCIhuU5zxWm9Zk2y+z1/Ny2mKoq4X1UufbMJkDKcd1AzAsIoB7rxzCwx8spdpiJTk6lOuHdG/xuZev3cfWvUcg0x/nyAoIclBb4U1tiTeE1peFGBjR8jg9zM9EiMmX+enbOVJVxtg27ekd1vwMBy+jZ6mJsZ1ieL7n5fxnx9v07XGQ6iMmClKjycotwW53oD9BN+W8irew2F31sqyOHA4Wv8jsvHAKLSUMCevH3cm3kF1R5rqh6tBRWWaiWnE0DTQ2cKjc82a4K9DWMp2i8kjHKTzScQrUBR7fOPRf8szFFNeasGs64kytm24ofiPJsBLi/Pfp+ix3Nk2N1cHnW7J/U8Dq1R8Pur/sV1oc3PPpNlY8NBydqvCPZWm8vTodgLdWp/PalF4eASqnBr7G+s5pJqOOb+8bir+3vtXdztanF3Pr+5vcx71nRDJvTu3NzuwyXv3xIKoCJTU2tmW50tGnDYwnyLflTmyt1nNKk1VbMkv4cF2Wx7rYIB8CfQ08dGl7Xl5xAIAp/eOar4d0iv60YCfL97o67ykHCpk5LInM4mraR/pz36gTF4g8buPhkibBKoCecUFNukUu35vvEVBZvD2HT2b051/L91NQaeGGvnEMTQln6QNDySquISrQ+4RZcjbniascjukcSWKoL/eMaKbYeQM/ph5jxkdb3MvF1VZmXOIafPZvG8Ll3V1dDVUF7lSX8KB+Ecuc/fg88inWHCjktVWeQbMwP6+TFiy3Nzr3wiqLuxj+zuwy/rFsPy/f0IMh7UL59ZDrrnJskA9d27R83E7RAcQEeZNb5upK0ys+iFCTkc2ZJWzNKqVnXBADT9AMINTPi0/vGMDXO3L475oMArwN/HVilxO+DiGEEOeWFcdWuP+fX5vPnoo99A9peepWS7YU12crFVkO8UXWZ0xtewea5mR/wTSqrdtdj1UtoNL6vMe+hyo8m5V4GZPZfu1DaJrWqgLgAJuKPnIHzHaXKVwV9yL92vVj1pQ9LF+bit0Qh1M5gqrlAzoU0x9O+TU2pqoq4eFNs6DeSV3PhsIyBjZIhPY3RDI4rDP9Q9qzqeQAOkVlVkrrC8C3xOmsZX/hNGwO102tKjWYbgG3oThyULxH4eczvlXH2VyyGYfmoNLhTST1xfRjfXs02faHvO3u/1uddjZUHuCF/97G/Pd+RtUpTL1rJHGJ4Xz/7AwKyqtICA/CaGj5K7D9eJmGah2OlcGUdFXcBay9KwxM6N6ODkER3Nb+xDdbX9zxI3P2u2o7fXhgE19ceivdQ1x1VKel9OG77FTSK4rRaUaP+lvdQ+L5MncR6ezBKxS8Qi3YK4wkW3qfMFgFoGmewa+duXvIt7jKZ6wp3EDXwI70jupOuK+JwhpXUHZs23YtBqsAhkUl8XbqL1gcGqBwaUx7NE3jp4LtFFvKGRzWlVjflrPvkvySeKnH33n74DI2FR8gyS+K+9pfccLXIf5HErAS4vwX0qibWrDvqXf5O3isku0N6kYBZBRVs2RnDpN6teH73fWpwmabg/SCSi7tFMnKVFeQZXzXKG4emMA/lu8HTeORcR0IbOY8iqssFFVZSQo3NamXtfZQoUcQbM3BQh69rCM94oJ4f7rrQppbXsP9c7dTUm0jKaxpx7jTZddRz+lYBp3CGzf1AuC+0Slc26cNNoeThFBTC0c4NQ27NWoamLx0vHuzZ72itQeL+GFfPm3DTNw6KLFJIDAu2LdJEf0b+8Vx78imQaLYIB+P5TbBPgT5GnlyQieyimtoU1eXy0uvNvuzaiw53I8p/eOYt8k1JfDybtHszS2n3GzjjqFJ3DYkkdm/HOa1VQe5oW/LQb6GhcgBfkorcAesFEXhzZt68/CYKkzfzCTyyLcAXK1bx6gue5hXHO2xb6CPgS/vHtzk96OxcV2i6JcYzOZM1+e/8bUuLb+CJTtzeXtqHxZuPYrZ5uD6Pm0I8G759+yl5fvJLatFVeCyLlH88/oerEwtYOYnW3Bqrmmeb97Umwndols8BsDEnrFM7Nm6LDMhhBDnFn+9P8XW+pqUfvpTH7fsK1uKhmeW+ZfZ2xgTXUagvsYdrAKotR9iZIJKG/8AjlZWoAC94q9D8U9BMy8CNRIC/gp119SGNPsRQEPRN820OVK9peGWZFdvJd7Uj8uHd+Xy4a4AQn5NAgeLXqUaL7o62/A/Vhht0c7iXDYdSyTQaCbWrxQdcQwMux29quOfPWeQXVOEv96HEK+Wa0y2ltVxzB2sArA5S6n1uhKTV1f3Ok3TwPw5mj0NxTgcxXtkk+Mcn35YbvclwxxGe79A+odcSs+Q65psG+UTzO7y+hum0T7BJMVFMevv4ym3lRPt7cq49/fVEeAbetKg47hLOvP1qt0cyCzAx65janJnvs9Lx8dg4O9jxtDWO5BFP+xg9s513Hh5HwL9fJo9zqrc+huCNqeTX/MPuwNWod4mvhk3g8yKEkqzc1hWtYtD1gKSjeFMjhnMu9nveByrR98Qnh549QnPGyAq4E7KzauwOQupKjWyNj8R6iYc+KoWampXovhpfHndTSw+sI9AL28md+7W4vFq7LW8f2QhseGFeCleXBE5jpkdhvNu+hIWHV0NwNwjK3irz8NE+7R8U1FVVO5tP4F7mXDS1yBEYxKwEhelRy/rSEZRNbuPljMwOZS7G2Wx/LS/gGPltYzqGEFEQPOpy+vSi3E2E5Qur3HdJUkINZFZXF+PqG24H38YlszaQ0WoCgxJDkNVFb5KCuXRRbuY/sFmIvy9eGdaH3e21w9787lv3nYsdic94oKY94cB+DboRtI4iNEpqmlQ47GFu9mSVQbAc9/uIyncxIgOJ09nP1V9EoLRqQqOujfl8m7R7ulfVruTmCAfNE3jzZ8OsS69iK6xgTw8pgO1dge1NgcR/q2vCQEwMCmURduOupfnbTrCjEuSMHm53p9Nh0u45f2N7p9RXnktT07o5HGMbm0C+b+ruzJn7WGCfY38fVI3OkQ1P2C7oW8cB45VsSI1n6QwP56b2JUjxTVM/u968sprCTEZuXdkMv9ZcZAaq527hidz36gUjHq1vjujrZYjn93PF4cU/P39+Mtts5g+eBg6FSICvCmpshIX4uuaXvjBJn7a75puuHDLUZb9cViToBnQ5Hzzys3MmruNu4YnuzOlksL9wHrEY7sARzkjO0XwysqDmG2ugf3UAfHodAqv/XgQf289Nw2Ib5JpRl0x9nl/GMgD83fw3W7PGg4KsDe3gvvnbWdoShgf3db/pBmD24+U8uG6TKjLPFxZVxvr2131jQg0Db7dlXvSgJUQQojz18ykmbyb8S6V9kpGR4ymc0Bn92N2p5X0yp8BhXYBw1ssvp1ZtcFjudzmTb7Fnyp7LaHGYHRKAA7NddNLVbyJMCXw7eRubMo7SrTJn64RkUAvKoyTePXgq2SmP02yXzIPpDzgDqA5K/8F1e8BoPlOQw14xuM5w7yTOVZb36QmzCvZ43Gr08w3R5/H4nRNBcyqfYpbkufio2tdMfdT0S8ijh9zD7LsiCto9GL/yzHqjk+ztJNgisDiqGJV3stU2vJJCRhF56DxFFsq8VL1+BmaD8g0x6iPxqiLw+qor8+ZV/E27cLfrN+o+m20qlcA0GrmQvB/UbxGeBxnTOQYCi2F7K3YS4JvArckTm9xaugDHa6kxm4hoyqfQeEdmdhmANtKt/F2+tvYNTuJvoncGq2nsGoOquJLUui/MehH4Nega57FYmHFFz+x5+c0kron8O6zk8nMKSUkyBedycl9Wn/CvYOoqKpl6p8+pKjMlZ20YWcm7z8/tdkgWPvAcA5XumqsGg12tlXs5F+px/hD8liCjCa8dHraBYSSqhZwXUCf+h2dGn2D+7K7fDcACgo39RrPgawCNu3KJDk+nFEDmm/K5GNIplvMKp66/S/s31SLY7CKzww7JrWWSWHb0ds3sC3/M9oFP8isZgreN/Z1zlr2VbjGZxbNwmFLGooykp8Ktrq3qbKb2VKSxpWxUpPqnOF094lo3bbnOAlYiYtSuL8Xi+6u74ixIaOY1LwKBrQN5fs9ebxeN00qwt+LxfcMZvm+YxRWWpjYM5aEUF82Hi5pNn02NsiHy7u7Oqz867ruPPnVbrJLzFzVM4ZxXVy52MPbu+4aaZrGoYIqNmQUuzv65ZXX8tiiXe6C3y9+n+bu4LYzu4yvtucwdUACxVUWUvMq6RUfzDNXdGbFvmMkhvnSNTaQL7Zkc1WPGLwNrkBDRmG1xzmmF1YzouXSSr/Z8ayur3fkEBvkw70j21FrczDzk638fKCQuBAfru4Z635vfz1UTP6Rgyw9DDZ0XB9dyL8emM6WzBKyS2sY0i7shEGsR8d18AhY5ZVb2JdXQb/EkLrjF3lmnx0obBKwolEdpBNRVYVnruzMM1d2xmx18NbqQyzdnUdeuWsKW0m1lb8vTXMH7N5anc5bq9MxGXW8NqUXoztFUrTmPa5JG0ERgVAK699byYdP/YFfDhZy1Ru/UmN10CchmBcmdXPXxgKotNh566dDPD+p6V2wkR0iuLRTIZnF1eSXW0gvrCa9sJpfDhbx0yMj6rOlBsyEr2e5yq/7hEC362gf6s9X9w7mx9QC2gT7MCwlnMteXeOeJrlsTz6fzxzU7Puh16lc37dNk4BVwxjuLweLOFpqPmlTg+xGheZtDicOp0ZcsOd+ccG+rEo7xjc782gT7PqMHf+cCyGEOP+l+KfwUo+XANA0JwcqfsTiqKKt32B+yH2eXPMuAFLLlzEi6ilWF/6MqqiMjhiNr2IG225ijMFkNDjm4eowBod1JNEUgaqopES8T3bp/6FpdmKDHsagiyBQB2Paum5eWhw2cszFrCr4jsPVhwE4VHWIb3K/YUr8FDRHvjtYBUDNp2i+t6DoEymzHqXSVkC/0FtQUSmxZhHt0xWb08zhyl9p6+/6Um+2l7iDVQA2p5lqW9EZCVjd0WEAXqqenSW5DAiP5/qkHlTbDrM9/y7M9iOEeA+mwBFNetU6ALJrtvJV1m6WFhSjQ+G+thO4NvkSdpTtwKE56BnUE4PafLBQVYxEB9xFVulT7nVl5h88ttEsvzRaXtckYKVX9dySeEurXl+w0Y9/9pruOveqMv669QfytKXYcU2PM9t2Uli1DQCnVsXeY/dxy3d/ICEwmI+uupb4wCB+XPAzr932PppT40d+paaslunPTOGzzB/4cNf3AFzbZjiRhcnkm6upjdeobqNRaMtjXVYWQxITm5zXzC6dUfW55FRrFDnz2FeZyb7KTLKqC9zdEXU6HUFBQZSVuW4s+/j44OPjwzDTMAINgWTVZNHRvyNV2T7c//zn2BQNuwnuzB/IzInNB4h0qj/tO4xk56of4QdwHFJIHncY7xut7m2OVn5B26CTB6wyqz3HeBaH66Z8lHcoJdb6qZoR3sEsyl7Nwcqj9AxO4bLoASc9tjhzFE1DaeVUv9ZudzZJwEpc9L7cdpSHF+xE08CoU/Ex1k/lKqi0cO+87Ww/4rqQfLQ+k7gQX9LyXH+kR3eKoMJsw8eg46qeMVzaKZIgXyNOp0ZeeS2PXtaR9nVZRl/vyOHLbTnEBPnw2LgO/GnRLlbsO9YkAF5hrp/HXma2ejymKgoZhVVc/856iquteBtU3r+1H9MHJzJ19kb39LLPN2fz+Z0D0etUBieHsqAuIGZQFYalnLlCh8Pbh7sDcgCzf8ng57rAS3aJmQVbPDvifX/YiQ3XoGdBXjjxH8/n5X2u9yvMz4sls4a4u98dZ7U7MepVQvyMhJiM7i6IRp1KdIMujZ1jPLPNGi//Lx5esIOlu/ObrHc0k3JXbXXwyIKdbH9mLDuO2VzBqjqrK2OwOZz837ep7lpmW7NKGffKGhofad6mI8wcluwR/EkvrGLSm79SUWunsXKzjcNF1fUBq17TIKITFGdA4hAIcAVWO0YFuBsF/JRW4FHTa+PhEt5efahJBuJxIzpE8MaUXsyat73Zx416lQCfk19mXm9UR2vagAS8DTpmjWpHXnktW7JK6B0fzPD24UybU581l1tWy8s3NK1nIYQQ4vy3Kv8lUsuXAbC56FNqHPVTBY/WbONfaX8l1+IqR5BZ/hP3hvyKopXRDSP64MtJq60B2nB76BUMCOuEqqjUOmrJtwYSHfIBwcZg7E4H/z20nNSKbHoFJzM+ujeztrzLUXMxcaYqGpairLbXdTpzOppJXlA5WPETK3L/jhMHAYZorkt4Hafm4IvMu6hxuKbQ9w65kcERd+JviCLOKwR/XFk0ZVongoyt6258qhRF4Zb2niUTDhT/A7PdlXldUrsOs9NzKv1h8x4gGgcabxxeSo5zGzvLdwLQ0b8jj3R4BJ1Sf8PIqblurqqKismre116h+ti7dV4yqShE9jqM3QUQ8fT8jpr7FamrPqUvJoK+sRZOD78MSqe00MNqhVVcZJZXsY/1v/Cm5ddyc5V+9AajOG2fL+TiY9fwYeZ37vXLTr6M3mbDmBtr8ca5nq9Ti94Yv0PrEm80+M51hev572M99B0GmGBBsrK/bA6XR+mveWeGe+xsbEEBgbidDrx9/dHVV3fQ3oE9aBHkGuM89q21ViMGiXdwGmEf2VtpFduAv1jmp9IetvjV1CeX8Kyj9ZgX2+mwqTBjfWPe+lO/l0g31zCL4W7PNZNTXB1Bn+801T+vf9zCi3ljIvqT3pVDh8cXgrAjwVb0SkqY6JOraGSEC2RgJW46H25Lcddg8fqcGJSPDM29ufX30GotjjcwSqAXw4Ukfa3yzymPDmdGjM/3cqKfa5aVfeNaseQdmE8+PkO9/Psz69gW10QrHFg4g/DkqBumlRJdX3wyqBTmNQrln8sS6O4LkhTa3PyzpoMYoN9WJ9RP5DbmlVKRpGrAPnRUrN7vc2pkV9R26RT25Kdubyx6iA+Rj3PXdXlNxWgb87x83S/Br1nXScnnsv7s7IBV/p/UZWFpbvzuGNoEntyytmbW84/l+2npMbKNb3a8K/ruvP+9H48981eam1OHrg0hQh/b8pqrAT5GhnXJYq/TezC93tcNayeaCa76rfakFHSZF1kgBfDUsLdwcGGjgejEnuPQb/rMHZcn7G2/hoGnerq1tJAc/c6nJqruHnDgNU3O3M9glVGvepuAhBqMtIu3DV1YcnOXHZmlzGgbSxju/dp5ugucSG+qAoemWmvrDzIXcOTW6z5MKFbNP3WZ7rrWUUGeOHUQFXgL1d2OWmRf7vDycECz+5IQ+uCqt4GnUdA6t2f0z3ObdmePAlYCSHEBUjTNPaX1xdgr3EUo6Bz16ZSFQPHLCVQdz1tr9+GornGVQpWOhsK6Rr5vscxy23lPJ/6PIWWQgyKgVntZrGl+BgfHV4FwKbig2wtOcRRs2s8VVRrJM5QCzjxVr0ZGeGqtbS94mcctf7083aNB7O0rrTVx7Ol+DmcdedXYcsjrfwHvHR+7mAVQGr5cgZH3IlTq6aNPg2n5rpJFKgcBMxA/TVT0zSOlr1ImXkF3oYkEkP+gUHXcp2gU6FzFtLH6MCoQI5DIZtwcm3H6h5VOWapHyeqisMdrAJIq0wjx5xDlFc0B6uOkla5k+/zv0VBYWr8VEZEjCAx5EWOVX6AXg0iIeT/qLZaURQFX4MBxf9RNHRg34/iNRzF55rT8pqyq8rIq3FN9cwoCqNzVB46VcPX2K+uyZEry+qbQ71waK7PTY3NNc5u170tq/jVfay23ZrPvLcH2V3l0VXA6RoXFdRUN9nu58Kf0epGc3bNRrCXlWNmV8CqR5CrzqjVbufjLTsorq7h6m6d6RDRchApLiqYmmhXsArAoWq8vXVTiwErRVG4+dEr+HXez5RX2Nj/fQCFG3sQPSgTb300ncP+ftL3M8dciK1REfcuga5zj/YJ418973Wvf2zH2x7bLcncIgGrs0mKrgtxYWmYlQPQLsKPwkoLlbV2JveLY+NhV5cyPO4Xufh66dzBqt1Hy0nNr8DHoLqDVdRlj/ga9R5/D7KKPadAqQqYvPTEBfsytm7q4PGua8fZnRqvrjxQXw+pjsmoI8jXiLdBdXex0ylQXRfIyCjyDAZkFFYzNKU+CyqzqJqHPt+BvS4SMOOjzWx68tJWdyo8kdJGAasu0YE8Mb6Tq4ZVTCAVu7/nhYMxaKiMMqZSFdwZGlz3Q/2MPLZwF583ysxatO0ol3aKYHy3aL68x5USvfZgEX3+toJKi53LukTx5tTe3DwokZsHNU3T/l/1aBPori+lUxXevKkXIzpE4G3QMWVAPCXVVl7+YT+pdcHN+0e7uha269iN1yepvPdLBgF+vjxzrStl+vHxHbl37jZqbc4mAaPjusYG0KVRlliYn5fHcp/4INpF+GO1O7ljaFuW78vnvTUZ7oDQnLWHeeOmXlxRN221sXYRftw9PJk367pbUldE/kQFSlVV4aPb+/P55mxsDic39I07pU6UWt3v4PGplYE+Bnq2EDCNDfbMtqu2OkgvrCI5/Mw1ExBCCPH7UxQFP30osephvBQHdk0hya8/mypzqNa86RN6O7urvsLhdF07nDSaeq7UXxd+yj1EmcWMXX+QQovr2m3TbHyd+zWVFs+sphJL/ZjJC41HwzNJ8i7HaRyCt8m1bbWtiN21gey1+JGoN9PWuxKt+hP0iuc12aD64Kd3jbdCdVY6GavRqXo0Zw02RyFOrf65nFo1NkcBerU+C7uoegH5le8CUGvPIKv0GdqFvcnp0FFfhr6udk2KqhHnfwMhvlYqbfkk+g0ltXg9JXW1LyeG9GOvcwX2uuCFioqKnvu2vUJWzVGifCo4Pkz4JOsTegf3JtxvMuF+kwF4c8tGXt7wNYqi8OSQ4czo2Qcl4KkWzuy3izUFEurlS7GlhlKziYxj3Zg3+kZifSMBG5W1G8mvdrIufwNBPtXU2gK5s5cr8+y6B66iorCKLT/sJKl7Avf8ezo+Rh+mxF/KvCMrASgv9aXWW+cauWiAFdAUbujQtFxDgN5zvHZFzCByawwEGU1MjR/BW/PWMP/wPvJx3VSev303S+6YRlxQ81NCrx7dnc8z97Kxtn6KnrfuxF/jw2JDeX3DC/z8xTqCIgIZc/1wdLrWl1EINgSgV/Tun3uXgLb46psv1aHYPBsq7ciugIGtfipxujk1UFoZiGruS8c5RgJW4qJVa3NQWmNtUrR6c2YpqgLv3tyXMZ0jySs385ev91JYZWFK/3jS8ir5cN1hTF56/l2X3bF0dx6z5m7Dqbm+4Ddk0CkMaBuCQadgc7j+KIzoEI7Z5mDp7nyUugBFZa2dfXkV/Pmr3XxwW386RPoTajK6s5Q0Dd7+OYM+8UH0jAtiR3YZCaG+PD6+I4E+Bl6f0ot7P9uG1aHh0ODOT7ey8o/DGdclio/Xu7qn+Bp1XNJoSmBumdkdrAIoqrJSbbXjf4KObq1VUWvzWPY2qEzoFl1fOLv/TMZtW0FleQmd+91KRo03eZ9tJ7u0hok9Y+jZJog/fr6z2WNXNpoG9+RXu6m0uNYt25vP0t15XNmj+cBMa/2UVkBpjZXRHSM9Oji+MrkXL/2wn/yKWq7r08Zdnwygd3wwX+/I4eAx10C0S0yAu2sfwPgBXRg/oIvH84zuFMmvj42iqMrKnxfvdmcrURccmzYwgQndot31msrNNuaszSC9oIoBbUPYl1tBUriJf17Xg7gQ16B99f4CHl3omcrtWl/YYsAK4JFxHThWaWHh1qN46VX+cW33k75Pn2/OZvGOXNoE+3BN71Prc/TeLxnuYBXAyA7hLTY66N82pMm6xr9vQgghzm+asxI0C9cF++Nta9CN2bmCNn5BKGFfo+iieSAlnsW5i1FR6RT1EFhfBNtm0LVF8f8TAM9uXc4nB13Tz7pH1hLU4P6GQTXQLzSFX4tS3esmthnAoux1HKkp5OHYfXTwrrthZv0earqDaQbeWj/QviPSYGaEqQwoQ6v8G5cFTWVB4TFqHCUkmPrTOXA8OtXIkJCJdHK8jVFxAtVoZffhFfwOPoZOmG2u5/YxdGwydc5iP3LC5f+FXqv0WPZRHPQOnexefnVgd3bmH8JX70XHiES2lLbl06xPcWgOboi7gV1lWWRU56JXNBre03LixOpsUCupopyXNqyFuoyx59eu5qr2HQn3/e0doy0OC9vKtmFQDPQO7o2quMYBfgYvPhl5E2/s/RVVUbivyyXEmY6Peb0I9BnG9vL/cE0fV02tFL+rGdQmHuoCpDOen8qM56d6PNftSZczPnogDs3J2C8/AerGtQpc3b4T4xM6Mi4xxb19VkEpH2zeitkYQ3RkAmX2AroFduOWxMnoVdfX7jfnruHTbzZT3Flx3WEGqq1WtmbntBiwUhSFt6dO4uYlC9lbWECMvz+PDLrkhO9Trd3GWyXb2NO7jIERgYw5SXfExl478B2VVgW9qqKhcEX00Ba3HRTQlx8y0vHytmKu9ibIcebKj4iLjwSsxEVp99Fypn+wieJqK35eTX8NnHUdycZ0jiQ60If/3uI59/+JCR3RqwqbM0t5YWkqq9IK3AFqi91Jxyh/0vIr0asKf5vYld4JwXwyYwBLduYSG+TDH4YmYdApZJeY+Wj9YeaszXQfe3t2GaXVVqbO3thkSh3AtuwyDj0/AbPN4XHufRJCsDrqA0+FlRbS8it49soudI4OIK+8lgndoptko3SPCyIh1Ned9TW8ffhpCVYBXNUjhu/35KPVTRFrHEBavb+A/ZVJDGnfH9UvkHZ+sPyPw9yP55WbUZSm2arJ4SbGdY1i25FSft5fSIcof2ptnjUKdh0to7LWzrD2YbSpK96taRrr0otxODWGtAtrkq3W0LNL9ro717UNM7H43iEE1hWzCPQ18Leru7a479+XprqDgHtzK/h+Tx6TejUfyDlcVM3LP+zHandy94hkJvaM9QhYXd0rluv71t8BrrbYufy1Xzymet7Qtw1mm5P3fz3Mg5e2J9DHwN7cimafr0Nk810Qc8vMfL0jlyBfAy9e042nL++Ml0E9aVHzn9IK+Os3rk5IO7PLMFsdvD+9Pg1819EybA4nveKCm83ayyryzDZsrh7XcRH+3jw5oSMvfp+GBjw8pr37ZyuEEOL8p9V8gVbxLGDHu7k2V1oZWNaC7/V0DOjI4wGPN3jwMzTNiqIY0cxf4ayZS0ZRLj66YNoGFFFpNtAuOJYiWw4B+gBujLuRRFMi3joDqeXZ9AxOYmx0Lya26U+euZSYmj9Ag6GFZtnAlvJx3LJ4I37eg/lLr7Vgqi/HYHIc5LZ2C7BptRjV+ozgnv7t0MobtOKyrkdVDHSMnE9h1VzQNML9bkJVPLOTg33HkV/xXzRcY8EQ3ytOz5sM4HMl1Hzi+r8SDF71wQ9Ns1Nq/pJY/0pCTVehKAr9QvrRL6T+2r4ifzMAdk3FbDfgo3cFcgaGDCTMKwzN/B04MtBsPT2eVqc4UC3foikG8B6PorjeJ81ZBdbNoAtDMTTNWDrO5rTxYtqLZNa4xmf9Q/pzd/Ld7sc7BEXw+pBJze5bajnCnrJv3MsHqxYzxHYTfobmgyurjqTz2b6dBHv78Fj/YYyMS+K7rP0AGFSVP3TrT5eQSPf2aUcLuP79uVSF1E1bPRDAzEsGkllRxrzMDUxtOxhVUUk77JqFobeAvW4IoyoKyWFNb8oB7CnLYmtJOin+MXxzwzRKas0EeXmjU098w+7fu39m7iFXjdFdJXmEeZuY0dGV2e/Uaqmy7MCgC8XHkNLs/jnmYjQUbE7Xd40ia2Wz2wFcntKR7w71YsXhdPwMRp4bP/qE5ybOMJkSKMT57+9LU93BoCpL81+QG3coa8igU9mSWcKU9zY0W2i7otbG5qdG42vUY6oLKg1MCmVgkmftgfhQX9qGed5lKq+x8cvBInLKzDSnU1QAOlVpEmgL9DEQG+Tj3s9k1NE2zISqKtzYP77F1+LnpefLuwfz5bYcfIw6ru97ahkyJ3JZ12g+v3MQO7JL6ZMQTJ+E+ovxpxuy+PPiPVBXMH3enQM8HgeIDvThT+M68K/lrgHCLYMSGNEhgn6JIaTmVTDlvxvcgaEJ3aJYticfp+bq7vjeL4fd78uSWUNICDXxwPwdLNmZC8DojhG8d0vfZoMomqYxd2P9nczDRdWsTy/isq7RrXrdukZ3sZrrKEld/aZpsze6f2brM4pZ/cgIdKrC5kxXofFpAz3vuG7JKvUIVgEs2HLUPVU1vbCaj2/vz8CkEHSq4v58hvt5cUO/NtzeINvruKIqCxPf/JXCummo69OLeW1Kr1a91oMFngOYQw3qUT3z9R53dt9lXaJ4e1rvJtMLx3eLYsHWbHfA151914I7hyVz04AEnJpGwGkKrAohhDj7NM2KVvFX4Pi4rIUvUrqWxymKYkSreget6t8AzOmu8HlZNGV1WTgx3pczOvZPmHQmd8bLlbH9uTK2v/sYBlVPvCkcpyXUI2CFo5CvD6RhdTooqfFjzdG2XBGdVf+4oQuKomBUPKevo29f95Wr7nXpXUXG9Wog0QF30xKTsRudo76i3Pwz3oZkgn3HtbjtqVL8/wyGXuAsAK+xKLr6TPH04gcorfkOgGOV79MleqnHVEWAkRG9WVO4gw3F+zDbQ7gpfjTt/ePo4N8BrepttKr/ABCLgft73strO8yAxpKx6wi2zEazADXzIOQz0GrRiq8Hh2vchv9jKKYZzZ734erD7mAVwKaSTdyacCu++pPfvFKUpjfgFKX5oM/+kkLuXL4Ye10x+czyUj65/HraBoSQX1PJpKQuHsEqgO+37sfsU/+B0fvVMj/HlV22Im8PDk1jevJQ+nWNZ8ueI/hladTEQHxCKPcMH0C36Cga21J8iIe2z8FRdx6PdbqWq9r0b7Jdcw5VFDe77HCaSSuYTI11F6AQH/wMkf63Ndl/VGR3Ps1cDYCPzsjA0JZbjOtVlf9efjUl5hpMRiNeJ5muKM60UwhYtfR39hwinyZxUbI7nR7L7SP9sNqdqIqCzemkf2Ios0Y13xntuNX7C5sNVlHXvexYhYWusc1PbWqoW6xnvZ4Qk5HYYM/9wv296B4bSKCPgT9d1vwFQ6cqfDyjP/9atp9au4N7RrRrcWpVY6F+Xu5i76db/7YhzU7lWrIj1/1/q8PJ0t35TQJWAPeMaMfNdUGbhplfK/cd85jKmF9ey6qHR1BYZeGRBfXTCMvNNpbvzefy7jHuYBXAj2kFHCyoajIllLrU61A/o8dUtcb1ok7k2au6cP/87dTanAxvH+4OwjicGkdKagjxNRLoa6Ck2uoRmKystZNZXMOU/vFMaSHIGN7MeTT8FG7NdBWE75MQwoe39eP7PfkkhPgy45K26HXND8w2HS5xB6uom+L66o09T1i76rihKeEY9Qfcxd5HdYwAoLjK4g5WUTdNc29uBV1jPQe9IzpEMP/OQWw6XEzX2EBGdIg46XM2lxUphBDifKfhGSECdB2A2roqoqD4TkbxGnTio1h+qt9d0ejsU8G6WtdYq9j6M4GGh1t1NopxIJr1l/oVhgQiTfVZ6ouyOjAsLpQr4gvA0BHF74Hmj2NIgaA30Go+AzUQxf/RVj0/gK+xC77GLq3Y8tQoigI+TTO2nJqN0pql7mWrI4cqy1aCfEZ5bKdXdfyt2x8os1bhq/fGqNZfl521PzTY0sYDPSyMSpmKkUI6aP9t8NBOsB8E2/76YBWgVb/XYsDKX++PguIuaO6temNUW1c3M8gYS++QG9lWMh+AAWG3YdK7xp21FhsFJZVEhgbgZdSTWlzoDlYB7C46ho/ewCO9hrV4/PAAE6oVHHXxSr235w3xnaVZwFBuvqo/fr7eHMgqoH+3BEYNaN/iMVcX7HYHqwBWHdvV6oDV6Jh2/JxXX5N0ZEwyAGXmlXXBKgCNnLL/NBuwujtlPMl+UeTVljI0vDOJfpFNtmksxEey3s8JkmElxPnvwUvbc8dHWzDbHCSE+vLpHQOI8G9dcOe4lEjPqXUNi2XrVIVgU+suoD3ignj0sg68szodf28DL13fgz4JITwxviPv/3qYYF8j/7quB93aND+vvaHkcD/eubnlLnDnkjbBPmyqv0lGXKOC2g01N0UxsVFmWtswPxLDTCSGmYgO9PYobB8Z4I3JqEOvKu4gl6qAn3fLfwLfuKk3D3+xgzKzjRlD2tI3sflU7cbKa2wMTA5l01OXUmG2ERvkg6Io1Noc3DJnE5syS/A2qLw9tQ/D24fTIdKf/cdcWUrh/l60izhxAfHOMQH85YpO/HP5AexOp3v/4/XRGp7n0JRwhqaEY7E7OFhQRWSANyHNfC7jQ3w9pl66lltX60BVFKICvMgvr6VPQgjPXOHq8mjQqx4ZXgA+xuanF7YU1BRCCHHxUBQv8HvAnZ2D12iUoDdbzIJpkb4d2La7F0uc9WMIX/0pXGtMt4J9D1jWgL49iv8T3NkrjPTSYn49eoSu4ZEM63gPqnfL4xf3a/MeheI96qTbnW2qYsCgi8TmyD++BqOu5bqXQcZmxiz6RLDvdS8q+kR6REahOf3RCn1BOz4+04MaCmqjG4eKZ8HyhqJ9opmWMI2vcr7CqBqZnjjdnSl3IpqmgbOIQeHT6RFyLQqK+7OQmVPMfc8vpKi0iujwAN58ejK9IqPx0Rsw211THQfHtDxT4bjJw3qwMzuPpfkHUXxUegcnsMd+0P14zxDXzVdFUbhmjKsGblV5DRl7jhKTFIF3Mw1r2vh6zsyI9W19l8joAJXOMdXYnQ4ujxrO2DauG966RhmAqtpykGlsdOuy7YU4kxRN+33DahUVFQQGBlJeXk5AQMt/kIQ40worLeSWmUmJ9MPX+Ntit2+vTueHffkkhfkxNCWMF79Pw+508thlHT3qDh2XW17D55uySQrzY2KvWI/Hvt6Rw8bDJfSKC2p2XwCnU+PHtALMNgdjOkW2GAA4H5RWW3l00S7251cyokM4f7myywlrSjWmaRr/XL6fn9IKaB/pz9+u7uquMZVVXM0D83dwtLSGK3vE8MwVnVEUhS+2ZPPM13twavDk+I5MH9J0etz/4uUf9vP6qkOoCjw5oRN3DK3PWpu/6QiPf7nbvZwUZmLVIyMorLTw7s/pWOxObr+kbZMpoq2x7lARH67L5FBBFRH+Xtx2SVt3Ifhys43J764nLb8SH4OOd252Bcqoew9fX3WInw8UYtApFFVZCTEZSQozse1IKSkR/vx9UjePgvONXfn6WnbnlLuX35nWGy+9jsIqC6XVVv61fD8OTeOB0Sk8eGnLdxHFuUmu2RcP+VmLc4Vmz3QFNfQdTz1YVVcPSav8O9gPoXgNZ6PZm92lS/DVBzMm5kkivJtei3YWZ7G5OJX+4R3pHlzfXdjisPP+/k3k1VRwVUIX+oY3Pz7TnJVgWe3KoPJqOQvnfFBt3UNWyVM4nJVEBdxFuN8Np7S/5ixDq/gL2DPA61JU//rMM82yGq3iOdDsKP6PoPhchaZpaBVPg3khqCEoQa+jGE/fzVdNs6CV3gnW9aAEoAS/jWKsr8f1zOvfsWJdmnt50qU9eHTGpewoyOOL/bsJ9fblrp79MRla3wH5uC+yNvLTsT2UWstI9AvjrnaXuTOV9m/P5M83vEZVWQ1RCWH8c8nDhMcEA1BZXcvrH/zEkfxS1EuqKfUvp61vFOYdfmTlVzCyWzKzLh/c4s3FcmsVk9f9FZvmyljUKzo+Gfg4WTX7UNER5PyCkprFqIqJdmFvEugz4pRfmzi7mrtmH193acIs9GrrZobYnRZWZr1xTl/7JWAlxO/kSHE1o//9szsTZlTHCHdx6tdXHeTlHw64t/3bxC7cPCixyTH++PkOvtqeA3Xd4764axBe+vM3aHU2OI9nWJ1CcKw1DhdVM/Kl1e5lVYGtfx7jzrSbt+kITzQIWLUNM/HTI6dvgDDxzV/ZmV0GgF5V+Oa+S+gUHcB7azJ4fml9B6SusQF8e9/QZs/plkEJdIkJ4LFF9esm9YrlP5M9i6Y2NOiFHz2mTg5NCeOXg0UAxAR6s/DuQQT5Gn9zUFicXXLNvnjIz1pcrL45spV5Oe/gpbfjcCrcEHsbV7RxXSef3vIaByt2k10VQkltCF+OmU6nYM+pUZqzCq34OnBkuFb43ooa8NTZeCnnNU2zoyinf6yg1cxHq3imfoW+E2rY1+7FZ177lhXr97uXrx7dncfuGHNanrvYUsnkX/+J2eGqmxvhFciCSx5Dr+p4ZsobbF65x73ttfeO4Y5nrwXgL//+lh9/rQ+iPf+nq1i2P52lW+vX/fWmsVw9sPnpokdrCrl14wsN1miMjfIht9Y19bJzQC9mJN6FqvqgKlIP9Hx0woBV/D2nFrA68tY5fe2XfuBCnEEWu4PKWlc68dur093BKoBVaQUs3ZVLal4Fr6w46LHf8S/8DVXU2tzBKoCdR8vZmV3eZLsLWXphFTf+dz3j/rOGzzZmtWKPplRVOe3BKgCbw7MumlPzXDexZwy94l01NPSqgkGncM9nW8krb764/qlKbdAV0O7UOHCsknKzja935HhsZ7PXn9P+fM+C6fvzKzncqGtfRlH1CZ+3YVH4CH8vth2p73CYW17L+vQSCVYJIYQ4p1TZLFgcrhpDXx39Di+96/86VWN+9udkVOWzp/QbIv0Wc0lMOjekbCHCt5BNhUeaHsy6rj5YBVAzl985H+CsK635gb15E9iXfzVVlq2/6RhnIlgFgNao47Zm8VicPmkgIYG+KIrG9Vdt57Jxb3Ok9G84G233W+SYi93BKoACSzkVthqKajMIuPkXBr2fS9h1RhzRoTgafGYyjhR6HOdwdjFZhaUe67IKPJcbivEJpW9wfc3bnkEx7mAVwL6K7VQ5bBKsEucF+RYhxBmybE8+D37uKrw9uW8cYf5NU4nvnbudmwbEe1ykgCaFqQF8DDpMRh3VVld6r6LQbD2iC9k9n25z13v68+I9dI4OoFd88Nk+LQDaR/ozqVesO6h425BEj6L3vkY9C2YOYsW+Y8yau50Dx6o4cKyKnLJavr53yEmPv2LfMf68eDdWu5NHL+vYpCj7sPZhrEwtgLqi5L3jg3l2yV72NAhkAR5tkEd0COej9Znu2lUjO7o6MM5Zm+EOrk7o2rRrTUP3jmxHr/gg8strGZoSzpT3Nnh0CowIaH2xeiGEEOJMe2HHj8xO24hBVfm/vhPw1XvT8NaMRbPx4NbZ3JpY32VNp2ikBBbQJbiZa6Ia1mg5uNV1IC8EFnsu6UWz0HAFZg4UzqBn7EZU5Ry5/vtMBPPnrgLvGFD8H/R4OCkujC/+M4PMwnepYS1WDY5VbkNRjMQFPXbSw3959EtWFqzEX+/PzKSZJPnVl4NIMkUS7hVAocU1FkvxjyHQ4MvHGY/jnVSEN9D3nr2syh2IGl7fhGlQnyQOZ7s+fzqdSt8eCWjBevYeOQaAXqcysltyi+ekKirPd7+DX4v2ABqdA6L5e+pOnHVNDQyKEW+dFEi/YJ1DRdc1TWPdunXs27eP0NBQRo8eTWDgyesyNyQBKyHOkEcX7qTW5spm+XxLNp/c3p9le/JJL6wfFml12TANtQ3z5Z4RTS9CBp3KG1N788Si3dRY7Tw0pv1JC3RfaDKLG7x3GhwpqTkjASunU+PX9CIUFAYnh7Y6I+s/k3vWdeNT6BjVNK1Wr1Ox2J0eAcr9+RVNtmvMbHVw/7ztmG2ugcZTX+3mknZhxIXUDzZen9Kb2b9kUFxt5fq+bYgL8SW9sKrJsawNsr5GdIjgw9v688uBQjpFB3BtH1er8AV3Debn/YWkRPq5OxyeyODk+sH6K5N78tAXOyiqsjJ1QDxDU8JPur8QQgjxe9hTks/stI0A2JxO/rxlKd9ddit/3fs8On01NqdKkdkPq7MSY6NA1Ijo/s3WsFKMvcHvfrTq90ENQgn85+/2es4FNkeeO1gF4HCW4XBWoOpO//Xf7iynqnYzBn0UJmPXVu2jqIEQughsaaCLRNE1HdeYfIz4mrKpaRC5NFv3N9musX0V+/gm7xvX9g4z72a8yz+6/8P9uJ/Bh7f63c2iI+swqHqmJAzFoVmottfPpNAZNEzhZmot9V0F75o6jJjIII7mlTK0Xzu6to+ha/sY2oQGkp5fwiWdE+macOIbinpVx/CIHu7lmxJmsiRnLjpFz7Vxt+KtO3mzAHGecmqNeoifbNszIzMzk2uvvZaAgADat29Pamoq06dPZ8GCBYwbN67Vx5GAlRBngKZpWOyeU8Qsdic/PjyCOz7a7M6EMepVZlzSlgh/L5buziMx1MQL13ZDr2t+tu7IDhFseHL07/IazkWXd4/my22uDKZQk5FBSa3vltJamqZxz2fbWLbX1SFnfNco3prau9V3S5vLjmuoT0Iw/l56KusGJscLoJ9IlcXuDlZRd20pqbZ6BKx8jDruG53isd/YzpHsOuo5bXTaAM/MrOHtw5ucQ8+4IHrGBfFbdI0N5Ic/Dv9N+wohhBBnUq3D5rFsczqJ8gnlnX4vc/P6f5JfWwkoxPmGMTLqTtYWOCiypBNv6sslEXe3eFzFbxaK36zf4RWce3wMnfDWJ1Frd02L9PcagL5x1tlpYHOUkHpsEha7qyREfPBfifS/tVX7Koo3GFuuxwkQ6DOCouovGiyffCxTYas44TJAjE8I93W4wmNdG99eHK1xdbI0l3hhzg9h7MPd3Y+rqsLVY3s0OdaYXu35rdW1+oUMpV/I0N+4txCnTlEU5s+fT0pK/feTadOm8fjjj0vASoizTVEU/jimPS9+7yqO2C8xmKHtXRfvN27qzTs/p3OswsI1vWNpH+nPw2M78PDYDic56sXH6dTILK4m0MdAqJ8X/7quBwPahlBcbeXK7jEeU+5Ol8NF1e5gFcD3e/LJKq4h8Td072tOXIgvC+4exKKtRwkxeXHbkKbF9RsL9/difNcovt/jOq/e8UF0ij55YcRZo1JoE+zLjuwy/Lz0DO8QTr/EU2jpLYQQQlxAeoXGMjKmHT/lHgJgZqdB7u5vb/S9l/lZv6AoClMThuNnCOSy2GdOcsSLk9NZi8VxFKMuBp3qS8fIhRRVL0BVvAgzTT4jUyJLa5a6g1UA+RXvtjpg1RohvhNQwt6j0rIek7E7oaarT7pP18CuhHuFU2hx1ZwaGTGyVc91eZvn2VO6hGNFhdgrujLl7W60iZPxmThNzpEpgQkJCU3WhYSc+udcugQKcQYdOFZJhdlGj7ggDC1kTYnm2RxOZny0hTUHCjHoFF66vgcTe8ae8ectqKhl0IurcNSlyOpUhQ1PjCbc/+zWYnA4NVbsO4bV4WRs50i8Da3vDrkju4znvtmLxe7kwUvbM6ZzZCv2EkKu2RcT+VmLi4XD6WRHSS6+OkOTjn/i5Cz2o6Qdm4zVkYNBDadD5Fx8DCmt2PN/U1y9hIzi+93LPoaOdI1edsaf92Sq7FXsKtuFv8GfboHdTmnfz9N38NGBzYR4+fK3vpfRNuD0zxwQF6YTdgmMnolebV2dY7vTysq8d8nOzva49nt5eeHldXq++8ybN4/c3Fz27dvH+vXref/99xk4cGCr95cMKyHOoPaR/mf7FM5bK/cdY80B1x0rm0PjuW/2/S4Bq4gAb56b2IXnvtkHwF+u7HLWg1XUBc4uO0kB9OZY7U5u/3AzJdWu+hL3zt3G6kdGEBMktQuEEEJcfHSqSp+wNmf7NM5b+RXvYnW4yjPYnIXklr9KctgbZ/x5Q3yvoLx2NcXVizHowkkMefGMP2dr+On9GBw2+JT321Wcy1Obl7orDd396yKWjb/ztJ+fEK0RF+dZn+8vf/kLzz77rMe68vJyPvjggxMep3PnzowdO9ZjXV5eHunp6ezbtw+dTnfKXVQlYCWEOC/8nqmgUwckMKWfq9ZTawuun6sqam3uYBV1Aay8crMErIQQQgjxP9N+pxGaoqgkhf6btiH/RFHO/6+wWVWlHu9cVmXpWTwbcUH5DVMCm8uwasxms5GZmXnCw0VERDRZ99BDD7n//8c//pFrr72WI0eOoNe37vf4/P9tF0JckC7tHMnQlDB+OViEQafwlys7/0/Hczg1dKcQfDrfA1XHhZqMDGgbwsbDJQC0DTO1qv6VEEIIIURjUQF3UmZe5Z4SGBvwwP90PE1zoCitL3NwIQSrAAZEJBDi5UuJpQaA8XEdz/YpiQuF0wk4W7Hh8W0hICDgpOUAwsLCeOWVV/6nU7v88st55ZVXyMnJabbGVXMujN94IcQFx6BT+ei2/hyuK7oe5ndq0/LmrD3M26sP4WvUE+5vZNuRMtqGmph9a1+Swv3O2HmfaxRF4cPb+jNv0xEsdic39G2Dr1H+9AshhBDi1Hnp4+gW/WNd0fVodGrrm9I4NSuZxY9RVruKAH0ibXU1KI4jaMahKMFvuLr5XSQifPz4csx0vsnaS7CXL9cnNe0KKMRvco4UXT9w4ADt2rVDVevrOP/000/4+/sTFdX6MifyrUUIcc5SVYXk3xBc2ptbzt++3Ve3ZOVIievuVUZRNc9+s4+Pb+9/ms/03OZj1HH7JW3P9mkIIYQQ4gKgqt74qO1Oeb+Cyo8prvkKgBDnXhTqvsha10DNp2C643Sf6jktzi+Ie7oMOdunIcQZsXr1aqZOncqIESMICgpiy5Yt/PDDD7zzzjunVNBd2pYJIS443+3Ka/GxCrPtdz0XIYQQQoiLnaZp+FiW0Umvp61O1yRrQnOWn6UzE+ICczzDqrX/zpA777yTuXPnEhsbi9lsZvz48WRkZHDzzTef0nEkw0oIcUHJKKzi3Z/TPdZ56VUsdieqAtf0jsXp1C6YGlVCCCGEEOc880L8HbtAVfEFKh1ONFQUnKAEgXHU2T5DIS4MTq317aqcZ7ZpQkpKCg8++OD/dAzJsBJCXFCyS804Gv3tXfHHYcwamYxBp/LM13u55f1NWOwO9+NrDxbx2cYssuumDgohhBBCiNNHc3h2F/M1tkcN+xa8LgOtDEon46x8tX57zYZmXoJW8yWaU8ZnQlysJGAlhLig9GwTRHRgfdHO4e3DiQ818c2uPCx2VyeMtYeK+Hana9rgf9ekM23ORp76ag9XvL6WzKLqs3buQgghhBAXIsVrlMfkHr3vNaD4gGVZ/UbVb6I58tE0Da3sHrTyR9AqHkcrvRlNs56dExfiPKNpzlP6d66TKYFCiAtKoK+Br+4ZwoIt2fh565nSPx4Ae6O0K0ddCuz8zdnudeVmG8v25nPX8OTf+ayFEEIIIS5cirEPhMxFs6xBMaSgeI9Hsx9pZksHOAvA8nP9KttusO8HQ7ff85SFOD9pWuun+p3BGlani2RYCSEuOFGB3tw3OoXbhrTF26AD4PHxHTHqXH/yesUHcWWPGNe2AZ4tlCMDWt+1QgghhBBCtI5i7Inqfz+K93jXsj4efKfVb+A7HUUXC4o/KL4N9tSDGvr7n7AQ4qyTDCshxEXhyh4xDGgbQlGVlZRIPwx1wasXr+nOA59v50hxDVf2iOHqnrFn+1SFEEIIIS4KasAzaL7TAAVF3xYARfWFoFfRKp4DzYbi/zCKLuZsn6oQ5wftFIqunwcZVhKwEkJcNCICvIlolFEVH+rLV/cMOWvnJIQQQghxMVP0SU3XeQ1HCf/xrJyPEOc1pxOUVtamOg9qWMmUQCGEEEIIIYQQQghxTpEMKyGEEEIIIYQQQojznUwJFEIIIYQQQgghhBDnEs3pRGvllEDtPJgSKAErIYQQQgghhBBCiPPdBZZhJTWshBBCCCGEEEIIIcQ5RTKshBBCCCGEEEIIIc53Tg2UCyfDSgJWQgghhBBCCCGEEOc7TQNaWZvqPAhYyZRAIYQQQgghhBBCCHFOkQwrIYQQQgghhBBCiPOc5tTQWjklUDsPMqwkYCWEEEIIIYQQQghxvtOcpzAlsJXbnUUyJVAIIYQQQgghhBBCnFMkw0oIIYQQQgghhBDiPCdTAoUQQgghhBBCCCHEueUCmxL4uwesjkfxKioqfu+nFkIIIcQpOH6tPh/uwIn/jYzPhBBCiPPDicZndmzQymGbHdvpPrXT7ncPWFVWVgIQFxf3ez+1EEIIIX6DyspKAgMDz/ZpiDNIxmdCCCHE+aXh+MxoNBIVFcXa/KWndIyoqCiMRuMZOsP/naL9zrdNnU4nubm5+Pv7oyjK7/nUQgghhDgFmqZRWVlJTEwMqip9Wi5kMj4TQgghzg8tjc9qa2uxWq2ndCyj0Yi3t/cZOMvT43cPWAkhhBBCCCGEEEIIcSJyu1QIIYQQQgghhBBCnFMkYCWEEEIIIYQQQgghzim/e9F1IcTZk5qaSlpaGpMmTfJYb7fbWbhwIYMHDyY+Pp6cnBx++eUXgoODGTdunMe2tbW1LF68GIAbbrihSV2bVatWUVJSwnXXXdfk+Y8fF0BRFCIjI+nevTshISEe25WVlfHjjz8SFRXFkCFDTtvrF0IIIYQ416xevRovLy8GDRrksf74uOmaa67BaDSybds2Dhw4QMeOHenZs6fHtpmZmWzYsIHw8HBGjx7t8ZjT6WTBggXExsZyySWXNHn+48cF0Ov1tGnThl69euHl5eWxXXp6Olu2bKFv374kJyefxndACCGaJzWshLiIvPjii7z00ksUFRV5rK+qqsLf35958+Zx4403snjxYiZNmoTBYCA7O5vIyEj3tp988gm33HILAGaz2aNIX0VFBdHR0dTU1LBhwwYGDBjg8TzHj3vNNddgMBhIT08nNTWV1157jdtvv53y8nIefvhhli5disPhYOjQoSxcuPCMvy9CCCGEEGfLpZdeSlhYGPPnz/dYf3zcVFhYSFhYGLNmzeLNN9+kV69ebNu2zWPbW2+9lY8//pghQ4awdu1aj8eWLVvG+PHjCQ0NJScnp0kgatasWcydO5exY8dit9vZtm0bTqeTr776il69erFr1y4effRRDh06RFZWFq+//jp33XXXGXxHhBDCRaYECiFaNGjQID7++GOPdXPmzGH48OHNbj937lxiYmKYNGkSs2fPbvG4c+bMYf78+WzevJn77ruPe+65h+LiYmpqahg4cCAHDx5scpdRCCGEEOJi17NnTw4dOsT27dvd6yoqKli4cCHDhg1rdp/Zs2czffp0VFV1Z8k3lpSUxPz581m4cCFpaWnExsZyzz33AFBeXs4DDzzAgQMHmgS7hBDiTJKAlRCiRTNmzOD99993Lx86dIiNGzcyderUZrefPXs2d9xxBzNnzmT+/PlUVVWd9DmuvvpqLBYLaWlpREdHc8cdd2AymU7r6xBCCCGEuBCYTCZuvPFG5syZ4143d+5cevbsSadOnZpsX1hYyJIlS5g1axa33nrrCW8oHmc0GpkwYQI7duwAYOjQoYwfP75JGQghhDjT5K+OEKJFV199NYWFhaxbtw7qAlKTJk0iODi4yba7du1i165dTJ8+nbFjxxIeHs4XX3xx0uc4ePAgANHR0WfgFQghhBBCXFhmzJjB3Llzqa2thbrx2YwZM5rd9uOPP6Zr16706dOHO++8k1WrVpGZmXnS5zh48KCMzYQQZ50ErIQQLTIajUybNo05c+Zgt9v56KOPWhwQvffee1x11VVERkaiKAozZsxo8S7el19+yfz583nhhRd48MEHufbaa0lKSjrDr0YIIYQQ4vw3YMAAYmJi+Oqrr9i5cyf79+/nhhtuaHbbOXPmcOeddwKQkpLCsGHDPLLnjystLWX+/Pl89tln3H///XzyySc89thjZ/y1CCHEiUiXQCEuIoqi0FyfhePrFEVp8tiMGTMYPHgwI0eOxNvbm1GjRrFo0SKPbSwWC5999hnTpk1zFww1mUysX7+e1NTUJinq3333HUajkfDwcF5//XUmT558ml+pEEIIIcT54beOz95//306dOjA5MmT8fPza7LNunXrSE1NRVVV9/gsKSmJDz74gGeffdZjil9paSmLFy9Gr9cTExPDL7/8wuDBg0/zKxVCiFMjASshLiJRUVGUlZVht9vR6+t//QsKCqCFaXndunWjU6dOzJo1i4cffrjZQdOiRYvQ6/UUFBR4FPPs2LEjs2fP5uWXX/bYfs6cOQQFBZ3mVyeEEEIIcf6JiooiJyenyfqCggK8vb2bLcVw880388QTT7Bx40aWL1/e7HFnz55N165dWbVqlcf66upqli9fzvjx493rjhddF0KIc4kErIS4iPTr1w9N0/jhhx+YMGGCe/3y5cvx8fGha9euze731FNPMW/ePG677bZmH589eza33HILL730ksf6BQsWcO+99/LCCy9gNBpP86sRQgghhDj/9e/fnyeffJKSkhJCQkLc65cvX06fPn2aLXYeFhbG008/TXZ2drOdlSsrK/niiy9YuHAhl112mcdjM2fOZPbs2R4BKyGEOBdJwEqIi0jnzp156KGHmDp1Kvfffz+JiYns27ePt956ixdffNFjkNTQxIkTmThxYrOPZWRksHr1ap577rkmj40fP56KigqWLFnCdddd16pzXLRoETabjZycHHQ6HfPnz8fLy4tJkyad4qsVQgghhDj3zZw5k08++YShQ4dyxx134Ofnx8qVK/nxxx9ZsWJFi/s99dRTLT42f/58dDodo0aNavLY1VdfzcSJEykoKCAiIuKk51dcXOw+D7vdzpYtW5g/fz4JCQnNBsuEEOJ0kYCVEBeZl156iQkTJrBy5UrWrFlDfHw8a9asoU+fPu5t2rRpw+TJk9HpdM0eIy4uzv14amoqN998c7N1Dvz8/HjiiSfIy8vzOO6Jsq2++eYbamtrSU5OBmDx4sUEBARIwEoIIYQQFySj0cj69ev57LPP2LZtG9XV1fTp04dXX32VqKgo93Z9+vQhLCysxeP069fPvX1xcTFPPvlks2Ou0aNHc/3117Nv3z4iIiLo06cPgYGBLR73eH0r6oJdVVVVLF68mMGDB0vASghxRilacxX+hBBCCCGEEEIIIYQ4S5pOiBZCCCGEEEIIIYQQ4iySgJUQQgghhBBCCCGEOKdIwEoIIYQQQgghhBBCnFMkYCWEEEIIIYQQQgghzikSsBJCCCGEEEIIIYQQ5xQJWAkhhBBCCCGEEEKIc4oErIQQQgghhBBCCCHEOUUCVkIIIYQQQgghhBDinCIBKyGEEEIIIYQQQghxTpGAlRBCCCGEEEIIIYQ4p0jASgghhBBCCCGEEEKcUyRgJYQQQgghhBBCCCHOKf8PFzq53iGu3wUAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1455.6x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pp.pca(heparg, n_comps=20)\n",
    "sc.pp.neighbors(heparg)\n",
    "sc.tl.umap(heparg)\n",
    "\n",
    "heparg.obs[\"log10 concentration\"] = np.log10(heparg.obs[\"Metadata_Concentration\"].replace(0, np.nan))\n",
    "sc.pl.umap(heparg, color=[\"Metadata_Control\", \"log10 concentration\"], size=40, ncols=2, show=False)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c006",
   "metadata": {},
   "source": [
    "The highest concentrations collect at the edges of the map, away from the bulk of the wells where the controls\n",
    "are spread.\n",
    "\n",
    "## From profiles to a response per well\n",
    "\n",
    "{func}`~mantispy.tl.hit_calling` writes two columns. `hits_distance` is the group's statistic repeated over its\n",
    "rows; `hits_row_distance` is each well's own distance from the control centroid. The curve fit needs the second:\n",
    "a column that is constant within a group carries no dose information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c007",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:12.827345Z",
     "iopub.status.busy": "2026-10-21T01:01:12.827076Z",
     "iopub.status.idle": "2026-10-21T01:01:13.473818Z",
     "shell.execute_reply": "2026-10-21T01:01:13.472856Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script>\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        </script>\n",
       "        <script type=\"module\">import \"https://cdn.plot.ly/plotly-4.1.1.min\"</script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"height:525px; width:100%;\">            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/3.2.2/es5/tex-svg.min.js\"></script><script>if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script>window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
       "        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-4.1.1.min.js\" integrity=\"sha256-O24V1F27f8pb0glCkelh3cVHLNiHAJ5gCaVtq2aNch8=\" crossorigin=\"anonymous\"></script>                <div id=\"cc52bf79-5417-44b6-9974-727180b0d2c0\" class=\"plotly-graph-div\" style=\"height:100%; width:100%;\"></div>            <script>                window.PLOTLYENV=window.PLOTLYENV || {};                                if (document.getElementById(\"cc52bf79-5417-44b6-9974-727180b0d2c0\")) {                    Plotly.newPlot(                        \"cc52bf79-5417-44b6-9974-727180b0d2c0\",                        [{\"customdata\":[[\"5,6-benzoflavone@0.0152\"],[\"5,6-benzoflavone@0.0457\"],[\"5,6-benzoflavone@0.13717421\"],[\"5,6-benzoflavone@0.411522631\"],[\"5,6-benzoflavone@1.234567904\"],[\"5,6-benzoflavone@3.703703701\"],[\"5,8,11-Eicosatriynoic acid@0.137174212\"],[\"5,8,11-Eicosatriynoic acid@0.411522637\"],[\"Aminodarone Hydrochloride@0.00191\"],[\"Aminodarone Hydrochloride@0.00572\"],[\"Aminodarone Hydrochloride@0.0171\"],[\"Aminodarone Hydrochloride@1.388888888\"],[\"Aminodarone Hydrochloride@12.5\"],[\"Aminodarone Hydrochloride@4.166666668\"],[\"Amperozide@0.0152\"],[\"Amperozide@0.411522634\"],[\"Amperozide@1.234567901\"],[\"Amperozide@11.11111111\"],[\"Amperozide@3.703703704\"],[\"Berberine chloride@0.00381\"],[\"Berberine chloride@0.0114\"],[\"Berberine chloride@0.0343\"],[\"Berberine chloride@0.102880656\"],[\"Berberine chloride@0.308641975\"],[\"Berberine chloride@0.925925924\"],[\"Berberine chloride@2.77777778\"],[\"Berberine chloride@25.0\"],[\"Berberine chloride@8.333333332\"],[\"Bevirimat@0.0152\"],[\"Bevirimat@0.0457\"],[\"Bevirimat@0.137174212\"],[\"Bevirimat@0.411522632\"],[\"Bevirimat@1.234567901\"],[\"Bevirimat@33.33333333\"],[\"CLIOQUINOL@0.0152\"],[\"CLIOQUINOL@0.0457\"],[\"CLIOQUINOL@0.137174209\"],[\"CLIOQUINOL@1.234567905\"],[\"Calcipotriol (hydrate)@0.0457\"],[\"Calcipotriol (hydrate)@0.411522631\"],[\"Calcipotriol (hydrate)@3.703703706\"],[\"Cladribine@0.13717421\"],[\"Cladribine@0.411522629\"],[\"Cladribine@100.0\"],[\"Colistin Methanesulfonate (sodium salt)@0.0152\"],[\"Colistin Methanesulfonate (sodium salt)@0.137174211\"],[\"Colistin Methanesulfonate (sodium salt)@1.234567901\"],[\"Colistin Methanesulfonate (sodium salt)@11.11111111\"],[\"Colistin Methanesulfonate (sodium salt)@33.33333333\"],[\"Cucurbitacin I@0.0152\"],[\"Cycloheximide@0.0152\"],[\"Cycloheximide@0.0457\"],[\"Cycloheximide@0.137174213\"],[\"DMSO\"],[\"Ethoxyquin@0.0457\"],[\"Ethoxyquin@0.13717421\"],[\"Ethoxyquin@0.411522631\"],[\"Ethoxyquin@1.234567907\"],[\"Ethoxyquin@11.11111111\"],[\"FCCP@0.0152\"],[\"FCCP@0.137174213\"],[\"FCCP@0.411522638\"],[\"FCCP@1.234567903\"],[\"FCCP@3.703703709\"],[\"Fluazinam@0.0152\"],[\"Fluazinam@0.0457\"],[\"Fluazinam@0.137174211\"],[\"Fluazinam@0.411522634\"],[\"Fluazinam@1.234567903\"],[\"Fluazinam@3.703703703\"],[\"IOPANOIC ACID@0.0152\"],[\"IOPANOIC ACID@0.0457\"],[\"IOPANOIC ACID@0.137174212\"],[\"IOPANOIC ACID@1.234567902\"],[\"IOPANOIC ACID@11.11111111\"],[\"IOPANOIC ACID@3.703703705\"],[\"Imiquimod@0.000762\"],[\"Imiquimod@0.00229\"],[\"Imiquimod@0.00686\"],[\"Imiquimod@0.0206\"],[\"Imiquimod@0.18518519\"],[\"Imiquimod@0.555555557\"],[\"Imiquimod@15.0\"],[\"Imiquimod@5.000000004\"],[\"Lys05@0.000762\"],[\"Lys05@0.00229\"],[\"Lys05@0.00686\"],[\"Lys05@0.0206\"],[\"Lys05@0.0617\"],[\"Lys05@0.555555558\"],[\"Lys05@1.666666668\"],[\"Lys05@5.0\"],[\"MILTEFOSINE@0.0\"],[\"MILTEFOSINE@0.000381\"],[\"MILTEFOSINE@0.00114\"],[\"MILTEFOSINE@0.00343\"],[\"MILTEFOSINE@0.0103\"],[\"MILTEFOSINE@0.0309\"],[\"MILTEFOSINE@0.0926\"],[\"MILTEFOSINE@0.277777776\"],[\"MILTEFOSINE@0.833333335\"],[\"MILTEFOSINE@2.499999998\"],[\"MUPIROCIN@0.0152\"],[\"MUPIROCIN@0.0457\"],[\"MUPIROCIN@0.137174209\"],[\"MUPIROCIN@0.411522633\"],[\"MUPIROCIN@1.234567904\"],[\"MUPIROCIN@3.703703705\"],[\"Natamycin@0.0\"],[\"Natamycin@0.000381\"],[\"Natamycin@0.00114\"],[\"Natamycin@0.00343\"],[\"Natamycin@0.0103\"],[\"Natamycin@0.0309\"],[\"Natamycin@0.0926\"],[\"Natamycin@0.277777776\"],[\"Natamycin@0.833333332\"],[\"Natamycin@7.5\"],[\"Nedocromil (sodium salt)@0.00381\"],[\"Nedocromil (sodium salt)@0.0114\"],[\"Nedocromil (sodium salt)@0.0343\"],[\"Nedocromil (sodium salt)@0.308641974\"],[\"Nedocromil (sodium salt)@0.925925929\"],[\"Nedocromil (sodium salt)@2.77777778\"],[\"Nedocromil (sodium salt)@25.0\"],[\"Nedocromil (sodium salt)@8.333333333\"],[\"PEMIROLAST POTASSIUM@0.00381\"],[\"PEMIROLAST POTASSIUM@0.0114\"],[\"PEMIROLAST POTASSIUM@0.0343\"],[\"PEMIROLAST POTASSIUM@0.102880654\"],[\"PEMIROLAST POTASSIUM@0.308641974\"],[\"PEMIROLAST POTASSIUM@0.925925921\"],[\"PEMIROLAST POTASSIUM@2.777777774\"],[\"PEMIROLAST POTASSIUM@8.333333332\"],[\"Rifampicin@0.0457\"],[\"Rifampicin@100.0\"],[\"Rifampicin@11.11111111\"],[\"Rifampicin@33.33333333\"],[\"Staurosporine@0.0152\"],[\"Staurosporine@0.0457\"],[\"Treprostinil@0.0152\"],[\"Treprostinil@0.0457\"],[\"Treprostinil@0.137174209\"],[\"Treprostinil@0.411522634\"],[\"Treprostinil@1.234567902\"],[\"Treprostinil@33.33333333\"],[\"Triamcinolone acetonide@0.0152\"],[\"Triamcinolone acetonide@0.41152263\"],[\"Triamcinolone acetonide@100.0\"],[\"Triamcinolone acetonide@11.11111111\"],[\"Triamcinolone acetonide@3.703703701\"]],\"hovertemplate\":\"called=not called\\u003cbr\\u003edistance from the controls=%{x}\\u003cbr\\u003e-log10 q=%{y}\\u003cbr\\u003egroup=%{customdata[0]}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"not called\",\"marker\":{\"color\":\"#636efa\",\"symbol\":\"circle\"},\"mode\":\"markers\",\"name\":\"not called\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"\\u002fNd7L5VpFUBYXZST0VUUQMYTLWiCgRRADS9FYlFzFEA6l2aYdwoTQFLN5zqVOhJAG42TQ0shFEBaY7RhfyQUQCxcUZPjpRJAsGl0gVHLEECCyajKIjIWQK\\u002f+4dRntBFAYrO+e\\u002fCeFUCwGoegpbQSQIjm8Ne6mRNAiZo625eFD0DZ1mxgy64QQJ4N1mMwDhJAcN9l5RN+EkDMBVTYcwMVQMDPgwovMBJAmn12cAdyEEBkrFmVtsAVQHc0f6jzoRNAU7q13ISFFUBu1MhUtfYOQLyfOuXWxBZAVpFF5kpiFEAI6kljJuYOQMw8kiygLRRA6aJTllkqFEAyq\\u002fejqnITQE2YuhU82RRAJlkVF1F4FUBxzejX2BYSQJUit1y4VBVAosxoMQKvEUCy7HPXne4RQCiux2FnwhVABKmfsHwlFEB8AhqpX58TQFjKdfKQ0RNAwjTUmWBtFUDm\\u002fchKixQUQBK6qKRnygxAcpx8M0LtFEDsMT0MdYkTQGD\\u002fRRn\\u002fnRZAbL+MGEkwFEDswwTKZ3oVQB9cCbmsGhFAktwhh5y2FkA0VlobtZEVQOkwPcwhCRBA1iLo2ixUFUDwDIJvvh4UQCIW2UutpRNALnP+jhi5E0D30AAHYh0UQNoMX717rBFABVRN6s0CEkBj5IluGXkTQD4Ye1FzFxJAAqvL6NsPEUCzCz9dtFQSQJQI1LvUyhJA1goaLLrSEEC004B7NYcUQLPGH4IorRRARPncjQNJFEAEiQd+\\u002fCcVQIR7AEjNnhBAIsSe2yk+EkDy96KzVl8SQIbUFVvEjhRAkMPqmzTwEUB4JMcd2Y4VQB+3bmf6hhFAaHQBIPQlEkAOvTmm+wIQQEr+rw6b9BVAH1Qv75iXE0Aeny6gCegRQOw11j+pNRRAoBCEqTXqFEBRYkWgnmAQQDTZ6xd+qBNAcNESArA5EUAqucub844SQG4TIonKJhNAWJX1fxabEEDEE7PYqBsVQB+NCkAtDBxAB6omgkgtEEDGkjZKevoOQF+iit64nhBAvltiejgwEkDMz\\u002fnLgJcSQBhP2nKH7RVAqMJhoNWnFkB15DiF2akRQCi3tcshvxJAiSF1NxeaEEBgmi2qtpESQKWg8Xr1IRNA4kQzmtpJFED+sXi4\\u002fOkVQFS6CR43QBJAGqf3hnaCEkAnGUKMS\\u002fYRQOsgZM1zVhNA4JEpLtF3EUCe5oXhllARQOJNwzJ+eRBA1ionoZ+CE0Bd7ot7EecSQNDtKNyLcRRA17J3kRjOE0DINkk8rCoRQBCff4wCERNA2kuV51BhEkCeK3J0wW0VQPxG+EJo8RNAAhpfkhrpFUB05pcwq44UQHQpDU8gnxRAOcfzoRHqEkCysiTzbMITQJjcLyZ9txBADJy633oRFUA\\u002f90gqfvwQQLwo\\u002frau4RNA1MeOSnCeEkCIsU38SmwQQHrPqHQNPxNAkuUxAp0sFkDzVeOOPVYRQDPhuTqA0hRAJGNswsg3FUCC9VBgtkMUQCiV2CPnlhNAEVz2b7udEkCidJ417VsVQDynLzN7KBZA\\u002frViBx1eEkA6BWjSUlMWQKEJCVlk\\u002fBFAGpZSvJPKEUBoNvwfRYgUQMr3BaDqrhVAP0JXGofaEkA=\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"kfT7U8tW8j9iySolvzzsP6F5J2grZOs\\u002fREzdKk+n7D\\u002fJVrOgSnXiP36Szzm6pNo\\u002fk1t9ukKH6D+TW326QofoP3DNKMAcvuA\\u002f7bKRFpus0T+yp0XqVXz0P9yvbt7uEdU\\u002fkfT7U8tW8j8yGfxKb5\\u002fiP6Oq0pKmI+Q\\u002ffRVPOdKCwz9i\\u002foXFpibLP6X0WPSWgdk\\u002fIvI+jc4L4D8+W2gUXLnuP\\u002f3iyf\\u002fWJNw\\u002fddapai50zD+R9PtTy1byP\\u002fDpqg2yH+c\\u002fkfT7U8tW8j9ObMgp3hi\\u002fP7KnRepVfPQ\\u002fptIhTVLD6j9h1gbLchnAP6F5J2grZOs\\u002fynj04olk6T8EN7SbOJzkP4Mb8ClrR+8\\u002fetNI74jz8T\\u002fsPOgVEAzbP7KnRepVfPQ\\u002fpcjzdEkB2D9IWb627mTYP3rTSO+I8\\u002fE\\u002fNFB3sCkM6T9yCNHijGPlPzXOrZy6+uk\\u002fetNI74jz8T\\u002f9v58LnennP8QNvGg7bJs\\u002fetNI74jz8T9yCNHijGPlP7KnRepVfPQ\\u002fk1t9ukKH6D8G0B3eYMXyPy7N5SG17tE\\u002fSaPSQuvl8z9ceQ26Z1jzP57p+6voJrU\\u002fXHkNumdY8z\\u002fKePTiiWTpPwoa5EAUruk\\u002fMkmjNd3a5j9Gh+1qbgjrP92UueLMidg\\u002fAlqslexm2z8Te0W4go3lPy4P757Es9o\\u002fLs3lIbXu0T\\u002fsPOgVEAzbP2P\\u002fRu12yuI\\u002f6JJeFaLH0D8NHXXvPo7tP5DhbodjxOs\\u002fREzdKk+n7D9q1Oq44d7vP\\u002fLDTTyWN84\\u002fXm\\u002f80jRb3j8\\u002fkKJcH1bcP2HrdRjrA+0\\u002f0L+CPSav2D8G0B3eYMXyP9yvbt7uEdU\\u002fiCApxUv02z\\u002fL6SltTSHIP0mj0kLr5fM\\u002fEf79lSJB4z\\u002fI8OlW\\u002fdTYP6bSIU1Sw+o\\u002fptIhTVLD6j+Hib9\\u002f5FTMP1+a9qFaROc\\u002fLs3lIbXu0T9eb\\u002fzSNFveP\\u002fDpqg2yH+c\\u002fpCIYHjcqzz8PlkdSzkrwPyGNxtTPmfE\\u002fwmLXuLm6yj\\u002faXlCHk5XDPyD\\u002f7+howtE\\u002ffpLPObqk2j8GdJHvEZDhP0mj0kLr5fM\\u002fsqdF6lV89D\\u002fSPsk1nofVP5AJztCR4OA\\u002fc1l4xuQ1zD\\u002foeZWMHX\\u002ffP4TE7vD5E+I\\u002fk1t9ukKH6D+yp0XqVXz0Py3Yrit5xNs\\u002fmy7R7NUT1T+l9Fj0loHZPwpePB74BuY\\u002fb\\u002faA76xp1T+NpUyD37HTPw0PlK71Wc4\\u002fjS8sZVIT4z9j\\u002f0btdsriPwoa5EAUruk\\u002fE3tFuIKN5T8g\\u002f+\\u002foaMLRP337h5oRtuE\\u002fIvI+jc4L4D8hjcbUz5nxPzXOrZy6+uk\\u002fsqdF6lV89D9iySolvzzsPz5baBRcue4\\u002fgAcZ1Ckc4D\\u002fw6aoNsh\\u002fnPwanNbkOWdA\\u002fIY3G1M+Z8T\\u002fZxBbcxzjRP\\u002f2\\u002fnwud6ec\\u002f\\u002foQJ195r4D\\u002fL6SltTSHIP2LFrWsTsOM\\u002fSaPSQuvl8z8PjCx93mTSP3FecxPSH+4\\u002fgxvwKWtH7z9ETN0qT6fsP\\u002f5X3F74l+Y\\u002fkAnO0JHg4D9ceQ26Z1jzP1x5DbpnWPM\\u002fGQWmTV7P3T9Jo9JC6+XzP8z3Whaa39o\\u002frbOR2FqV2z9Gh+1qbgjrPyGNxtTPmfE\\u002fY\\u002f9G7XbK4j8=\"},\"yaxis\":\"y\",\"type\":\"scatter\"},{\"customdata\":[[\"5,6-benzoflavone@100.0\"],[\"5,6-benzoflavone@11.11111112\"],[\"5,6-benzoflavone@300.0\"],[\"5,6-benzoflavone@33.33333333\"],[\"5,8,11-Eicosatriynoic acid@0.0152\"],[\"5,8,11-Eicosatriynoic acid@0.0457\"],[\"5,8,11-Eicosatriynoic acid@1.234567902\"],[\"5,8,11-Eicosatriynoic acid@11.11111111\"],[\"5,8,11-Eicosatriynoic acid@3.703703706\"],[\"5,8,11-Eicosatriynoic acid@300.0\"],[\"5,8,11-Eicosatriynoic acid@33.33333333\"],[\"5,8,11-Eicosatriynoic acid@99.99999997\"],[\"AMG 900@5.1\"],[\"Actinomycin D@0.0152\"],[\"Actinomycin D@0.0457\"],[\"Actinomycin D@0.13717421\"],[\"Actinomycin D@0.411522633\"],[\"Actinomycin D@1.234567901\"],[\"Actinomycin D@11.11111111\"],[\"Actinomycin D@3.703703704\"],[\"Actinomycin D@300.0\"],[\"Actinomycin D@33.33333333\"],[\"Actinomycin D@99.99999999\"],[\"Aloxistatin@5.1\"],[\"Aminodarone Hydrochloride@0.0514\"],[\"Aminodarone Hydrochloride@0.154320986\"],[\"Aminodarone Hydrochloride@0.462962964\"],[\"Aminodarone Hydrochloride@37.5\"],[\"Amperozide@0.0457\"],[\"Amperozide@0.13717421\"],[\"Amperozide@100.0\"],[\"Amperozide@300.0\"],[\"Amperozide@33.33333333\"],[\"Berberine chloride@75.0\"],[\"Bevirimat@100.0\"],[\"Bevirimat@11.11111111\"],[\"Bevirimat@3.703703703\"],[\"Bevirimat@300.0\"],[\"CLIOQUINOL@0.411522638\"],[\"CLIOQUINOL@11.11111111\"],[\"CLIOQUINOL@3.703703705\"],[\"CLIOQUINOL@300.0\"],[\"CLIOQUINOL@33.33333333\"],[\"CLIOQUINOL@99.99999997\"],[\"Calcipotriol (hydrate)@0.0152\"],[\"Calcipotriol (hydrate)@0.137174213\"],[\"Calcipotriol (hydrate)@1.2345679\"],[\"Calcipotriol (hydrate)@100.0\"],[\"Calcipotriol (hydrate)@11.11111111\"],[\"Calcipotriol (hydrate)@300.0\"],[\"Calcipotriol (hydrate)@33.33333334\"],[\"Cladribine@0.0152\"],[\"Cladribine@0.0457\"],[\"Cladribine@1.234567899\"],[\"Cladribine@11.11111111\"],[\"Cladribine@3.703703707\"],[\"Cladribine@300.0\"],[\"Cladribine@33.33333333\"],[\"Colistin Methanesulfonate (sodium salt)@0.0457\"],[\"Colistin Methanesulfonate (sodium salt)@0.411522634\"],[\"Colistin Methanesulfonate (sodium salt)@100.0\"],[\"Colistin Methanesulfonate (sodium salt)@3.703703704\"],[\"Colistin Methanesulfonate (sodium salt)@300.0\"],[\"Cucurbitacin I@0.0457\"],[\"Cucurbitacin I@0.137174209\"],[\"Cucurbitacin I@0.411522631\"],[\"Cucurbitacin I@1.2345679\"],[\"Cucurbitacin I@100.0\"],[\"Cucurbitacin I@11.11111111\"],[\"Cucurbitacin I@3.703703701\"],[\"Cucurbitacin I@300.0\"],[\"Cucurbitacin I@33.33333333\"],[\"Cycloheximide@0.411522635\"],[\"Cycloheximide@1.234567901\"],[\"Cycloheximide@100.0\"],[\"Cycloheximide@11.11111111\"],[\"Cycloheximide@3.703703704\"],[\"Cycloheximide@300.0\"],[\"Cycloheximide@33.33333333\"],[\"Dexamethasone (DHAP)@5.1\"],[\"Ethoxyquin@0.0152\"],[\"Ethoxyquin@100.0\"],[\"Ethoxyquin@3.703703707\"],[\"Ethoxyquin@300.0\"],[\"Ethoxyquin@33.33333334\"],[\"FCCP@0.0457\"],[\"FCCP@100.0\"],[\"FCCP@11.11111111\"],[\"FCCP@300.0\"],[\"FCCP@33.33333333\"],[\"FK-866@5.1\"],[\"Fluazinam@100.0\"],[\"Fluazinam@11.11111111\"],[\"Fluazinam@300.0\"],[\"Fluazinam@33.33333334\"],[\"IOPANOIC ACID@0.411522632\"],[\"IOPANOIC ACID@100.0\"],[\"IOPANOIC ACID@300.0\"],[\"IOPANOIC ACID@33.33333333\"],[\"Imiquimod@0.0617\"],[\"Imiquimod@1.666666672\"],[\"LY2109761@5.1\"],[\"Lys05@0.185185184\"],[\"Lys05@15.0\"],[\"MILTEFOSINE@7.5\"],[\"MUPIROCIN@11.11111111\"],[\"MUPIROCIN@300.0\"],[\"MUPIROCIN@33.33333333\"],[\"MUPIROCIN@99.99999998\"],[\"NVS-PAK1-1@5.1\"],[\"Natamycin@2.5\"],[\"Nedocromil (sodium salt)@0.10288066\"],[\"Nedocromil (sodium salt)@75.0\"],[\"PEMIROLAST POTASSIUM@25.0\"],[\"PEMIROLAST POTASSIUM@75.0\"],[\"Quinidine@5.1\"],[\"Rifampicin@0.0152\"],[\"Rifampicin@0.137174213\"],[\"Rifampicin@0.411522635\"],[\"Rifampicin@1.234567901\"],[\"Rifampicin@3.703703704\"],[\"Rifampicin@300.0\"],[\"Staurosporine@0.137174214\"],[\"Staurosporine@0.411522636\"],[\"Staurosporine@1.234567901\"],[\"Staurosporine@100.0\"],[\"Staurosporine@11.11111111\"],[\"Staurosporine@3.703703702\"],[\"Staurosporine@300.0\"],[\"Staurosporine@33.33333333\"],[\"TC-S 7004@5.1\"],[\"Treprostinil@11.11111111\"],[\"Treprostinil@3.703703705\"],[\"Treprostinil@300.0\"],[\"Treprostinil@99.99999997\"],[\"Triamcinolone acetonide@0.0457\"],[\"Triamcinolone acetonide@0.13717421\"],[\"Triamcinolone acetonide@1.234567898\"],[\"Triamcinolone acetonide@300.0\"],[\"Triamcinolone acetonide@33.33333333\"],[\"UNTREATED@0.0\"]],\"hovertemplate\":\"called=hit\\u003cbr\\u003edistance from the controls=%{x}\\u003cbr\\u003e-log10 q=%{y}\\u003cbr\\u003egroup=%{customdata[0]}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"hit\",\"marker\":{\"color\":\"#EF553B\",\"symbol\":\"circle\"},\"mode\":\"markers\",\"name\":\"hit\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"eoaSymZsM0DccNj3V58YQJgUPbaZly1AhtpZ19AzF0A0kPx+pWUcQOlW8p0owBhAWtQSNYYdFkCafCHkMM8YQK1AVEZoFRlA401+BmnAPEBDWkNmFWslQIHF20QqpidA9AyhtS0qGEB4g3y1QQwjQAZRPuzwlh9AM+mbXprWIEB5FnJtWP8iQEg0UBhfRiRA6mBMpHshJUB\\u002fgLYIIJwiQCqsLqjKwj9Ax8uJ7VUVLUBUiiiuyJQzQNwRAHEVZRlAlp1ddKfBFkB6VHib6q0aQPHV8yfwfxVAH\\u002f8BecQ0LECO\\u002fbS\\u002f1+AVQJ73AJumoxZAEfNzYPn3K0Ch5ponRXsqQHUZPoGRaRpAMrO5EpzHIUAA7rUqUU0dQEYSxEy68xtAIrTbrgNeG0CohfbmQpQwQA\\u002f7\\u002f5\\u002fZXxVAC9d9gVuzG0Cgo1dWd6YWQIGU6gjxOy5ANkCC6xCJIkAExf8zVSEqQBgCm3PGGBpAgpXJetgwFkBgbstl3gEWQG5JROpECCZA5kk7QPvGG0C02nytQzMpQL7KpNH44SFAOJlPr+TLFkAYx8vz6+kXQPnWsoDBmRpA4KS9faI0F0Awmsedv0cYQOQNO\\u002fQH1R1AquWEp\\u002fbAGECG\\u002fwiCbT4XQPwzOlDc2BdAl34qnsVFGUBIg5Jv0N8bQCTncxpxXixAhHoS9aNdG0CcE5DNs\\u002fwcQJm0VGgQvR1AxPUKj\\u002f7aG0CBZBXVwistQJ6Qc73IxCZAVteMrrcbI0CY01rhVPcuQE9w\\u002f83Z7iVAzA2ZED0JGkB6AKDEoBgaQP4E\\u002f8q3tRtA8Rdvz1nHIkDmwJ0rKGgeQIsUsmUr1CVAmTyOrZfSGUA2nOn4bigZQADF6YDVdhhARxPgIa1qKUC2dnZzkEsYQDmU0CxgVy5AauCbu58FG0AmbYI8THEXQKwqGq7JUSZAttYMHz0QHUA6QLlesRs8QHyyn4+87iNAAm3DLfgHGECMTV0oEBkyQBRAwxOCmB5AZZsAeklDLUDW\\u002fbCW1yMiQEz\\u002f+6lDRRpANyi50cQgIkBcyVvClVQkQH5RrpoffRhA3g6ghSsfFkC0gaJ9oTYaQDrp8RiqZRZAFnuEwGcLGEAwciOMbQMcQIZZS5031CJA1G2z8QiVFkCOuK0DQ9EgQP0Gst1cKBtAA2yP9CSSFkBMoXOCddQcQNzIDaz4mRxApZWb2i+WGUDxKsGT4D0fQAT2RFWt\\u002fxVA0HShrtsXFkAqtTyym74WQJJyTPphvhdAPg2CcHVLF0Ao3GfOOxkYQMuLg\\u002fuazBtA6VKA+B0IF0Di8Oy6CqAhQNgjlDJDlhpAnOdCjPghJUAr6J\\u002fftBEnQMR1d\\u002fBAlCtA5jHtZY8lKEBetZf0QWMlQOjtnRtauTJARoWe7N97KEAGoZ0+peAYQFZwcIukCBpAKBLRomyRHEB0uGLyT50yQL7f6+L7xx1AntIobyeZFkCiia5D370WQJ6nZ+IOwxZAceLVFObDH0AecIjnfCsWQFEHqLOn0RtA\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"MNxy1qyh\\u002fz8yhm2+Wk35PzDcctasof8\\u002fMRsb80nY9z8w3HLWrKH\\u002fPzDcctasof8\\u002fMoZtvlpN+T8w3HLWrKH\\u002fPzEbG\\u002fNJ2Pc\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fr29XHK4T9T8w3HLWrKH\\u002fP0dblTuz8vU\\u002fMNxy1qyh\\u002fz9HW5U7s\\u002fL1P69vVxyuE\\u002fU\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzKGbb5aTfk\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fP69vVxyuE\\u002fU\\u002fMNxy1qyh\\u002fz9HW5U7s\\u002fL1PzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fP4\\u002fCoweQmfs\\u002fr29XHK4T9T8HXNr4MrD2PzDcctasof8\\u002fMoZtvlpN+T8w3HLWrKH\\u002fPzDcctasof8\\u002fR1uVO7Py9T8xGxvzSdj3P4\\u002fCoweQmfs\\u002fB1za+DKw9j8xGxvzSdj3PzDcctasof8\\u002fj8KjB5CZ+z8HXNr4MrD2Pwdc2vgysPY\\u002fj8KjB5CZ+z8w3HLWrKH\\u002fPzDcctasof8\\u002fj8KjB5CZ+z8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8yhm2+Wk35PzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fMRsb80nY9z8w3HLWrKH\\u002fP4\\u002fCoweQmfs\\u002fMNxy1qyh\\u002fz8yhm2+Wk35PzDcctasof8\\u002fj8KjB5CZ+z8HXNr4MrD2PzDcctasof8\\u002fj8KjB5CZ+z8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fR1uVO7Py9T+PwqMHkJn7PzDcctasof8\\u002fMRsb80nY9z8w3HLWrKH\\u002fPzDcctasof8\\u002fR1uVO7Py9T8w3HLWrKH\\u002fPzDcctasof8\\u002fMRsb80nY9z8w3HLWrKH\\u002fPzDcctasof8\\u002fMoZtvlpN+T8w3HLWrKH\\u002fP0dblTuz8vU\\u002fj8KjB5CZ+z8w3HLWrKH\\u002fP0dblTuz8vU\\u002fMRsb80nY9z9HW5U7s\\u002fL1P4\\u002fCoweQmfs\\u002fMRsb80nY9z8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fMNxy1qyh\\u002fz8w3HLWrKH\\u002fPzDcctasof8\\u002fB1za+DKw9j8HXNr4MrD2PzKGbb5aTfk\\u002fMNxy1qyh\\u002fz9HW5U7s\\u002fL1PzDcctasof8\\u002f\"},\"yaxis\":\"y\",\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermap\":[{\"type\":\"scattermap\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"distance from the controls\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"-log10 q\"}},\"legend\":{\"title\":{\"text\":\"called\"},\"tracegroupgap\":0},\"title\":{\"text\":\"hits\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('cc52bf79-5417-44b6-9974-727180b0d2c0');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mt.tl.hit_calling(heparg, groupby=\"Metadata_Perturbation\", use_rep=\"X_pca\", n_permutations=300)\n",
    "mt.pl.hits(heparg, label_top=6);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c008",
   "metadata": {},
   "source": [
    "Which column names the groups matters. HepaRG carries eight\n",
    "wells at each concentration, but only because `Metadata_Concentration` is the dose each well was *meant* to get:\n",
    "two of this accession's twelve plate maps write the dose to three decimals and the rest to four, so\n",
    "`Metadata_ConcentrationRecorded`, which keeps what was written, splits a treatment's replicates across two\n",
    "spellings. U2OS is two plates rather than eight, and there most groups really do hold one or two wells.\n",
    "\n",
    "## Fitting the concentration response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c009",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:13.477627Z",
     "iopub.status.busy": "2026-10-21T01:01:13.477442Z",
     "iopub.status.idle": "2026-10-21T01:01:18.420777Z",
     "shell.execute_reply": "2026-10-21T01:01:18.419629Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>n_doses</th>\n",
       "      <th>spearman</th>\n",
       "      <th>qvalue</th>\n",
       "      <th>ec50</th>\n",
       "      <th>r_squared</th>\n",
       "      <th>fit_ok</th>\n",
       "      <th>hitcall</th>\n",
       "      <th>hitcall_model</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>Staurosporine</th>\n",
       "      <td>10</td>\n",
       "      <td>0.591008</td>\n",
       "      <td>7.335594e-08</td>\n",
       "      <td>2.218850e-01</td>\n",
       "      <td>0.142390</td>\n",
       "      <td>False</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>linear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Actinomycin D</th>\n",
       "      <td>10</td>\n",
       "      <td>0.452491</td>\n",
       "      <td>5.404548e-05</td>\n",
       "      <td>1.003418e+02</td>\n",
       "      <td>0.112453</td>\n",
       "      <td>False</td>\n",
       "      <td>0.999999</td>\n",
       "      <td>logistic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fluazinam</th>\n",
       "      <td>10</td>\n",
       "      <td>0.556897</td>\n",
       "      <td>4.543326e-07</td>\n",
       "      <td>1.883942e+01</td>\n",
       "      <td>0.365059</td>\n",
       "      <td>False</td>\n",
       "      <td>0.999987</td>\n",
       "      <td>logistic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5,6-benzoflavone</th>\n",
       "      <td>10</td>\n",
       "      <td>0.497156</td>\n",
       "      <td>6.916195e-06</td>\n",
       "      <td>3.853868e+01</td>\n",
       "      <td>0.629746</td>\n",
       "      <td>False</td>\n",
       "      <td>0.999986</td>\n",
       "      <td>logistic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cucurbitacin I</th>\n",
       "      <td>10</td>\n",
       "      <td>0.529948</td>\n",
       "      <td>1.337576e-06</td>\n",
       "      <td>7.164990e+01</td>\n",
       "      <td>0.180595</td>\n",
       "      <td>False</td>\n",
       "      <td>0.999985</td>\n",
       "      <td>linear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CLIOQUINOL</th>\n",
       "      <td>10</td>\n",
       "      <td>0.609101</td>\n",
       "      <td>2.847418e-08</td>\n",
       "      <td>6.905675e+01</td>\n",
       "      <td>0.568431</td>\n",
       "      <td>False</td>\n",
       "      <td>0.999982</td>\n",
       "      <td>logistic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5,8,11-Eicosatriynoic acid</th>\n",
       "      <td>10</td>\n",
       "      <td>0.370323</td>\n",
       "      <td>1.122650e-03</td>\n",
       "      <td>6.805594e+06</td>\n",
       "      <td>0.496050</td>\n",
       "      <td>False</td>\n",
       "      <td>0.999975</td>\n",
       "      <td>linear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FCCP</th>\n",
       "      <td>10</td>\n",
       "      <td>0.664696</td>\n",
       "      <td>4.972740e-10</td>\n",
       "      <td>2.828735e+08</td>\n",
       "      <td>0.621083</td>\n",
       "      <td>False</td>\n",
       "      <td>0.999972</td>\n",
       "      <td>linear</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            n_doses  spearman        qvalue          ec50  \\\n",
       "group                                                                       \n",
       "Staurosporine                    10  0.591008  7.335594e-08  2.218850e-01   \n",
       "Actinomycin D                    10  0.452491  5.404548e-05  1.003418e+02   \n",
       "Fluazinam                        10  0.556897  4.543326e-07  1.883942e+01   \n",
       "5,6-benzoflavone                 10  0.497156  6.916195e-06  3.853868e+01   \n",
       "Cucurbitacin I                   10  0.529948  1.337576e-06  7.164990e+01   \n",
       "CLIOQUINOL                       10  0.609101  2.847418e-08  6.905675e+01   \n",
       "5,8,11-Eicosatriynoic acid       10  0.370323  1.122650e-03  6.805594e+06   \n",
       "FCCP                             10  0.664696  4.972740e-10  2.828735e+08   \n",
       "\n",
       "                            r_squared  fit_ok   hitcall hitcall_model  \n",
       "group                                                                  \n",
       "Staurosporine                0.142390   False  1.000000        linear  \n",
       "Actinomycin D                0.112453   False  0.999999      logistic  \n",
       "Fluazinam                    0.365059   False  0.999987      logistic  \n",
       "5,6-benzoflavone             0.629746   False  0.999986      logistic  \n",
       "Cucurbitacin I               0.180595   False  0.999985        linear  \n",
       "CLIOQUINOL                   0.568431   False  0.999982      logistic  \n",
       "5,8,11-Eicosatriynoic acid   0.496050   False  0.999975        linear  \n",
       "FCCP                         0.621083   False  0.999972        linear  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt.tl.dose_response(heparg, compound_key=\"Metadata_Compound\", min_doses=4)\n",
    "curves = heparg.uns[\"mantispy\"][\"dose_response\"].set_index(\"group\")\n",
    "curves = curves[curves.index.astype(str) != \"DMSO\"]\n",
    "curves.sort_values(\"hitcall\", ascending=False).head(8)[\n",
    "    [\"n_doses\", \"spearman\", \"qvalue\", \"ec50\", \"r_squared\", \"fit_ok\", \"hitcall\", \"hitcall_model\"]\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c010",
   "metadata": {},
   "source": [
    "Three columns answer three different questions.\n",
    "\n",
    "`spearman` with its `qvalue` asks whether the response rises with dose at all. It assumes no shape and works with\n",
    "three points.\n",
    "\n",
    "`fit_ok` asks whether the logistic converged on something curve-shaped, with an EC50 inside the tested range and\n",
    "an $R^2$ of at least 0.8. It is `False` for every compound in the table: most have an EC50 inside the range, but\n",
    "the curve explains too little of the scatter between wells, so no potency should be quoted for them.\n",
    "\n",
    "`hitcall` asks whether the response is large next to the noise the controls carry. It is the product of three\n",
    "confidences from the ToxCast pipeline: that the curve beats a flat fit, that some concentration's median clears\n",
    "the cutoff, and that the fitted top clears it. The first weighs the curve against a flat fit over\n",
    "mantispy's two shapes, the logistic and the line, where the ToxCast pipeline weighs it over ten, so it is not\n",
    "the number `tcplfit2` reports. The cutoff is three times the controls' MAD unless you pass one, and without\n",
    "marked controls or a `cutoff=` there is no scale to read activity on, so `hitcall` is `NaN`.\n",
    "`hitcall_model` names the shape that won: `logistic` where the curve plateaus, `linear` where it is still\n",
    "climbing. Note that it saturates at 1.0 for the strongest compounds, so it separates active from inactive but\n",
    "does not rank the actives against each other."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c011",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:18.424727Z",
     "iopub.status.busy": "2026-10-21T01:01:18.424563Z",
     "iopub.status.idle": "2026-10-21T01:01:18.886927Z",
     "shell.execute_reply": "2026-10-21T01:01:18.885783Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script>\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        </script>\n",
       "        <script type=\"module\">import \"https://cdn.plot.ly/plotly-4.1.1.min\"</script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"height:525px; width:100%;\">            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/3.2.2/es5/tex-svg.min.js\"></script><script>if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script>window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
       "        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-4.1.1.min.js\" integrity=\"sha256-O24V1F27f8pb0glCkelh3cVHLNiHAJ5gCaVtq2aNch8=\" crossorigin=\"anonymous\"></script>                <div id=\"7c9f8ec1-da3e-4ce1-87ca-bc2a011290d5\" class=\"plotly-graph-div\" style=\"height:100%; width:100%;\"></div>            <script>                window.PLOTLYENV=window.PLOTLYENV || {};                                if (document.getElementById(\"7c9f8ec1-da3e-4ce1-87ca-bc2a011290d5\")) {                    Plotly.newPlot(                        \"7c9f8ec1-da3e-4ce1-87ca-bc2a011290d5\",                        [{\"hovertemplate\":\"Concentration=%{x}\\u003cbr\\u003ehits_row_distance=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"\",\"marker\":{\"color\":\"#636efa\",\"symbol\":\"circle\"},\"mode\":\"markers\",\"name\":\"\",\"orientation\":\"v\",\"showlegend\":false,\"x\":{\"dtype\":\"f8\",\"bdata\":\"xY8xdy0hjz8mgqOqqqpAQEUEfrXsjsE\\u002fI1ARaC+hDUAAAAAAAMByQDJYL47jOCZAJ8h3RcrA8z\\u002f1udqK\\u002fWWnP\\u002fHBywljVto\\u002fAAAAAAAAWUDFjzF3LSGPPyaCo6qqqkBARQR+teyOwT8jUBFoL6ENQAAAAAAAwHJAMlgvjuM4JkAnyHdFysDzP\\u002fW52or9Zac\\u002f8cHLCWNW2j8AAAAAAABZQMWPMXctIY8\\u002fJoKjqqqqQEBFBH617I7BPyNQEWgvoQ1AAAAAAADAckAyWC+O4zgmQCfId0XKwPM\\u002f9bnaiv1lpz\\u002fxwcsJY1baPwAAAAAAAFlAAAAAAAAAWUD1udqK\\u002fWWnPzJYL47jOCZAxY8xdy0hjz8AAAAAAMByQEUEfrXsjsE\\u002fJ8h3RcrA8z8mgqOqqqpAQPHBywljVto\\u002fI1ARaC+hDUAAAAAAAABZQPW52or9Zac\\u002fMlgvjuM4JkDFjzF3LSGPPwAAAAAAwHJARQR+teyOwT8nyHdFysDzPyaCo6qqqkBA8cHLCWNW2j8jUBFoL6ENQAAAAAAAAFlA9bnaiv1lpz8yWC+O4zgmQMWPMXctIY8\\u002fAAAAAADAckBFBH617I7BPyfId0XKwPM\\u002fJoKjqqqqQEDxwcsJY1baPyNQEWgvoQ1AxY8xdy0hjz8mgqOqqqpAQEUEfrXsjsE\\u002fI1ARaC+hDUAAAAAAAMByQDJYL47jOCZAJ8h3RcrA8z\\u002f1udqK\\u002fWWnP\\u002fHBywljVto\\u002fAAAAAAAAWUAAAAAAAABZQPW52or9Zac\\u002fMlgvjuM4JkDFjzF3LSGPPwAAAAAAwHJARQR+teyOwT8nyHdFysDzPyaCo6qqqkBA8cHLCWNW2j8jUBFoL6ENQA==\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"gu2MjDNhFECymCzuYPYtQE9LXBn7nBNANaYd08lxJEDvvfraXX8+QMW7+iG8OyVAEOUNroduIUBxnM5DGbITQMUtxMox5CRA6el2t6UMKED2XnozAsYVQLoq+uH1kylAXWHMvp2GEkDmFg3WsA8lQHTzxGagoj1AfK2Sx+MKI0ATwwMNZIAkQFKyC0CTgw9Ai54Aw2quIEAbAPVWFMchQFJnXlGPqRRAlLUs42JvKEBRYhESzgAcQJSyTnWbNyNAwYmQ9XmBLUBUeweGItslQKncxYZl4iZAENLEjj7RGUAX2LeyfSwhQN4qOmu8fCVAbMy5RDwZLkCTTtN8U9UUQNHvEEwqeCdAR7r2zmZyEEAfYTKGM18wQEvrpVSxsBtAZvbwHOeMKUCr+9zCEWMjQK3dAsAA4yVAXHBLzqk+KkAbHzWcRQ8pQGV5kCviExFA\\u002fHPJf\\u002fTSKECQXCfyIogSQCGefNCHkDVAZlyCENV7GUDC1JZWyjMkQGWvHhrL3yVA0TwGjOGkIkCyUOuuQpglQABNTBgE3C5Ash4kIotkEUD+NOkW6\\u002fItQBzKufWaOxlAsnoJsYATNUDbXulDXbwSQK3zeTgEQSdAZHyXcBoCJUByocFNv18lQC539HpzoCVATTY9lBOxKECkEPDltbk2QP979L4WbjBA3kES135SN0A9JVCocWoZQMxmiRyJP1VA5njNe8drRECIS9YCK2glQPR10pTMBD5A0HpQ9+p3MkDhKqFJ9kwxQM5Cc0WCHidA9yrFKbgNLUBz1KUjPlQeQKKx4hcrABFAyc5ii6p8IkDF1JszIR0qQPhUEPZciChAxeIWhgX8PkALGkQ6QS4lQA==\"},\"yaxis\":\"y\",\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermap\":[{\"type\":\"scattermap\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Concentration\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"hits_row_distance\"}},\"legend\":{\"tracegroupgap\":0},\"title\":{\"text\":\"Staurosporine\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('7c9f8ec1-da3e-4ce1-87ca-bc2a011290d5');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "        <script>\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        </script>\n",
       "        <script type=\"module\">import \"https://cdn.plot.ly/plotly-4.1.1.min\"</script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"height:525px; width:100%;\">            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/3.2.2/es5/tex-svg.min.js\"></script><script>if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script>window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
       "        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-4.1.1.min.js\" integrity=\"sha256-O24V1F27f8pb0glCkelh3cVHLNiHAJ5gCaVtq2aNch8=\" crossorigin=\"anonymous\"></script>                <div id=\"ef2c5fb5-e6fc-4160-9dee-43cdaf37d6d0\" class=\"plotly-graph-div\" style=\"height:100%; width:100%;\"></div>            <script>                window.PLOTLYENV=window.PLOTLYENV || {};                                if (document.getElementById(\"ef2c5fb5-e6fc-4160-9dee-43cdaf37d6d0\")) {                    Plotly.newPlot(                        \"ef2c5fb5-e6fc-4160-9dee-43cdaf37d6d0\",                        [{\"hovertemplate\":\"Concentration=%{x}\\u003cbr\\u003ehits_row_distance=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"\",\"marker\":{\"color\":\"#636efa\",\"symbol\":\"circle\"},\"mode\":\"markers\",\"name\":\"\",\"orientation\":\"v\",\"showlegend\":false,\"x\":{\"dtype\":\"f8\",\"bdata\":\"bj6FjuM4BkD4DzNFysDTPwAAAAAAADlALnO6LCY2bz8AAAAAAMBSQABvgQTFj6E\\u002flCdDZy+h7T+jNp+qqqogQAM56fxiVro\\u002f1CtlGeJYhz9uPoWO4zgGQPgPM0XKwNM\\u002fAAAAAAAAOUAuc7osJjZvPwAAAAAAwFJAAG+BBMWPoT+UJ0NnL6HtP6M2n6qqqiBAAznp\\u002fGJWuj\\u002fUK2UZ4liHP24+hY7jOAZA+A8zRcrA0z8AAAAAAAA5QC5zuiwmNm8\\u002fAAAAAADAUkAAb4EExY+hP5QnQ2cvoe0\\u002fozafqqqqIEADOen8Yla6P9QrZRniWIc\\u002fozafqqqqIEAAAAAAAMBSQPgPM0XKwNM\\u002fAAAAAAAAOUADOen8Yla6PwBvgQTFj6E\\u002fbj6FjuM4BkDUK2UZ4liHPy5zuiwmNm8\\u002flCdDZy+h7T+jNp+qqqogQAAAAAAAwFJA+A8zRcrA0z8AAAAAAAA5QAM56fxiVro\\u002fAG+BBMWPoT9uPoWO4zgGQNQrZRniWIc\\u002fLnO6LCY2bz+UJ0NnL6HtP6M2n6qqqiBAAAAAAADAUkD4DzNFysDTPwAAAAAAADlAAznp\\u002fGJWuj8Ab4EExY+hP24+hY7jOAZA1CtlGeJYhz8uc7osJjZvP5QnQ2cvoe0\\u002fbj6FjuM4BkD4DzNFysDTPwAAAAAAADlALnO6LCY2bz8AAAAAAMBSQABvgQTFj6E\\u002flCdDZy+h7T+jNp+qqqogQAM56fxiVro\\u002f1CtlGeJYhz+jNp+qqqogQAAAAAAAwFJA+A8zRcrA0z8AAAAAAAA5QAM56fxiVro\\u002fAG+BBMWPoT9uPoWO4zgGQNQrZRniWIc\\u002fLnO6LCY2bz+UJ0NnL6HtPw==\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"VG\\u002fA6CX6EkAm4RyvRoUTQAfbAKevWBdAtkZ1+ybcF0DEQ5MPCzQZQK4adUB\\u002fww1A2fVDHB+XFEA73HrLYtQSQChGqN2jSx5AiK9BhcTwHEB+DpKRN6AYQJsxrjA8DBRA0RELJueWEUD+I1ZB3PMUQAP7CFBvjzBANSjLQZTtDEAV4kWF5c4TQHc+p8PmrxNA7deiFcuyGEBTbF49W2QVQKTBwoWq3whAP4RrevnwEkDkvWJA8l0TQBC43YFVihRAE2DbHoFXHEAIbTQ5eKYRQASzqB6Bwx1AuYKM0E78EUDPdOdJWy0XQDYEHfFDBxdA8euSNlWpFUDUgdLA3VIdQLIEdupvXQtALNxrTuAlFEDoy1Ca46ARQIO0a5x56xBAiP6Djk+ICUBYZlKvBfgNQEgARk7XqxdAYFHQBXIuHEBirrx\\u002f1twUQLP08jinryJAyIfhoaC+E0AnH03gk7scQCBR\\u002f00lRhNAYY0CiSrxD0DhYO5ZS7cNQNbAW0VVfQtAxYH8sOeSEkCkq4eHGLgUQNZSY\\u002fozNxxAsXGA7JDfIEAULuxhveYbQHJkdCP+MBZAh+4ERe4LE0CKfmCP8xARQJ+Pr9oXzBNAo54u0D7UCECpDyMD9G8aQBK31W296g5A\\u002fqPRpw8bEEAmmQ4Nv74XQLBeQWeCqTJAmudRbwsTFUBAYY7j0hRIQAEzq7S9OSBAAsnjMfFSFkBEyaJmjYwgQPxiJ+gAqRtA514zJCg7GkBJdM5Mv+cTQMm+27UUjEBAqp2afTiKDUAScAXwhgAvQPnjy+ARVBRAkoxG0vdGB0DJiLs24UYDQAZvaTiylARAl\\u002fpahl2nBUAKBxhUGpkZQA==\"},\"yaxis\":\"y\",\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermap\":[{\"type\":\"scattermap\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Concentration\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"hits_row_distance\"}},\"legend\":{\"tracegroupgap\":0},\"title\":{\"text\":\"Berberine chloride\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('ef2c5fb5-e6fc-4160-9dee-43cdaf37d6d0');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "        <script>\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        </script>\n",
       "        <script type=\"module\">import \"https://cdn.plot.ly/plotly-4.1.1.min\"</script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"height:525px; width:100%;\">            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/3.2.2/es5/tex-svg.min.js\"></script><script>if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script>window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
       "        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-4.1.1.min.js\" integrity=\"sha256-O24V1F27f8pb0glCkelh3cVHLNiHAJ5gCaVtq2aNch8=\" crossorigin=\"anonymous\"></script>                <div id=\"c719516f-fc1b-4b4e-b797-36b91ff7500f\" class=\"plotly-graph-div\" style=\"height:100%; width:100%;\"></div>            <script>                window.PLOTLYENV=window.PLOTLYENV || {};                                if (document.getElementById(\"c719516f-fc1b-4b4e-b797-36b91ff7500f\")) {                    Plotly.newPlot(                        \"c719516f-fc1b-4b4e-b797-36b91ff7500f\",                        [{\"hovertemplate\":\"Concentration=%{x}\\u003cbr\\u003ehits_row_distance=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"\",\"marker\":{\"color\":\"#636efa\",\"symbol\":\"circle\"},\"mode\":\"markers\",\"name\":\"\",\"orientation\":\"v\",\"showlegend\":false,\"x\":{\"dtype\":\"f8\",\"bdata\":\"cYbq\\u002f\\u002f\\u002f\\u002fWEDFjzF3LSGPP\\u002fW52or9Zac\\u002fa2R4aC+hDUC28EVGysDzPzJYL47jOCZA1DzBquyOwT8mgqOqqqpAQLYfkwZjVto\\u002fAAAAAADAckBxhur\\u002f\\u002f\\u002f9YQMWPMXctIY8\\u002f9bnaiv1lpz9rZHhoL6ENQLbwRUbKwPM\\u002fMlgvjuM4JkDUPMGq7I7BPyaCo6qqqkBAth+TBmNW2j8AAAAAAMByQHGG6v\\u002f\\u002f\\u002f1hAxY8xdy0hjz\\u002f1udqK\\u002fWWnP2tkeGgvoQ1AtvBFRsrA8z8yWC+O4zgmQNQ8warsjsE\\u002fJoKjqqqqQEC2H5MGY1baPwAAAAAAwHJAJoKjqqqqQEBrZHhoL6ENQNQ8warsjsE\\u002ftvBFRsrA8z8AAAAAAMByQPW52or9Zac\\u002fxY8xdy0hjz8yWC+O4zgmQHGG6v\\u002f\\u002f\\u002f1hAth+TBmNW2j8mgqOqqqpAQGtkeGgvoQ1A1DzBquyOwT+28EVGysDzPwAAAAAAwHJA9bnaiv1lpz\\u002fFjzF3LSGPPzJYL47jOCZAcYbq\\u002f\\u002f\\u002f\\u002fWEC2H5MGY1baPyaCo6qqqkBAa2R4aC+hDUDUPMGq7I7BP7bwRUbKwPM\\u002fAAAAAADAckD1udqK\\u002fWWnP8WPMXctIY8\\u002fMlgvjuM4JkBxhur\\u002f\\u002f\\u002f9YQLYfkwZjVto\\u002fcYbq\\u002f\\u002f\\u002f\\u002fWEDFjzF3LSGPP\\u002fW52or9Zac\\u002fa2R4aC+hDUC28EVGysDzPzJYL47jOCZA1DzBquyOwT8mgqOqqqpAQLYfkwZjVto\\u002fAAAAAADAckAmgqOqqqpAQGtkeGgvoQ1A1DzBquyOwT+28EVGysDzPwAAAAAAwHJA9bnaiv1lpz\\u002fFjzF3LSGPPzJYL47jOCZAcYbq\\u002f\\u002f\\u002f\\u002fWEC2H5MGY1baPw==\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"YTd3OwlUEkD\\u002fFrJPdt4MQCnISuAjexNApvgxncyAE0Bt9aQo3K0aQBsZYMcL3xVAdjrXoYHOFkDjPOms5MgZQKDDaaBsTBlAXo2QDVkYJEAsd\\u002fMtO44WQNHXI52LBhFAmGwQdEmoEUCX4uOuf\\u002fgTQHcMXJkIyRNAdhPGElf3F0C4WD+LdpgUQL0DJbmefxNAFBNx228EFEB6\\u002fH8kI5UdQPBoBWwGSRhAQWvG0aItEEDxN8DgoP0PQK4SoqV26A5ArtbT7Rz9E0COwgYcBksXQHpthAgyPg1A2n\\u002flMxP9JEAPUe3eHo8MQN9yG3X01yJASRU5QXiAEUABfOGeof8QQEA1slc1chlAn10qRF16EUD+oKQ3xnoUQG7qapeBNhRAxlB7qpTyGUAJGuttooERQF6tc\\u002f3PrxpAsHb1WEWPFEDvXnIZ0QBiQDuEMlSMIA1AQEAJzdoOB0CIvJ9\\u002fwdQQQFrvHf8Q6xZAPRjbxq2nC0DehHKtXy4MQN3Lggw9jRBA9N6yuyRpD0A3IEAwg0MQQAC7eC3\\u002fzRBATQLZ734wC0BFC8JsA54NQG9vBmgO0xhAQOJryiIdG0A\\u002fVdtuQEIHQL3nSkmwWxVAFbmOWrTHDkDUFsysBPoaQBWGnPQTFhlA2mAruw6WFkDUD4KJXmsRQOY\\u002fTIO\\u002fKxdA2Je\\u002ftJvcKEBOjR2D3NYXQKZIoK5cwihAkuijanSrEUAX0XoO1YccQHcbHlnbkhJANyrP+OY+MEDH+0KGY8YhQO7stxCqcyZA++SSHCfUJkCcykFN3wIjQLhMJIirIihAj9xJe9K8FkAgxujg+QsFQD\\u002fCaL5+gCRADm2Zr7uJE0AgHyCsQSwdQA==\"},\"yaxis\":\"y\",\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermap\":[{\"type\":\"scattermap\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Concentration\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"hits_row_distance\"}},\"legend\":{\"tracegroupgap\":0},\"title\":{\"text\":\"MUPIROCIN\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('c719516f-fc1b-4b4e-b797-36b91ff7500f');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for compound in [\"Staurosporine\", \"Berberine chloride\", \"MUPIROCIN\"]:\n",
    "    mt.pl.dose_response(heparg, compound=compound)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c012",
   "metadata": {},
   "source": [
    "Staurosporine is a broad-spectrum kinase inhibitor and a common positive control in Cell Painting, and it is\n",
    "called at 1.00. Mupirocin inhibits bacterial isoleucyl-tRNA synthetase and has no target in a human cell, and is\n",
    "not called; berberine is not called in this cell line either."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c013",
   "metadata": {},
   "source": [
    "## Which features move, and at what concentration\n",
    "\n",
    "The distance plotted above is one number per well, its distance from the controls. That number says a compound did\n",
    "something; it does not say what. {func}`~mantispy.tl.dose_features` asks the same question of every feature and\n",
    "reports the lowest concentration at which each one's median response reaches three times the spread the controls\n",
    "show on it.\n",
    "\n",
    "That is a benchmark dose rather than an EC50. An EC50 needs a plateau, and most compounds here never reach one.\n",
    "A benchmark dose only needs the response to cross a line the controls set, so it is defined for a feature that is\n",
    "still climbing at the top concentration. The ToxCast pipeline reads its `3 * bmad` the same way."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c014",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:18.890188Z",
     "iopub.status.busy": "2026-10-21T01:01:18.890031Z",
     "iopub.status.idle": "2026-10-21T01:01:18.972581Z",
     "shell.execute_reply": "2026-10-21T01:01:18.971518Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30 of 99 features respond to staurosporine\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>feature</th>\n",
       "      <th>bmd</th>\n",
       "      <th>max_z</th>\n",
       "      <th>direction</th>\n",
       "      <th>spearman</th>\n",
       "      <th>qvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2504</th>\n",
       "      <td>Cytoplasm_AreaShape_Zernike_1_1</td>\n",
       "      <td>0.336326</td>\n",
       "      <td>3.445138</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.066715</td>\n",
       "      <td>0.655931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2510</th>\n",
       "      <td>Cytoplasm_AreaShape_Zernike_6_2</td>\n",
       "      <td>0.362425</td>\n",
       "      <td>4.209308</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.313785</td>\n",
       "      <td>0.012627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2547</th>\n",
       "      <td>Nuclei_Correlation_Overlap_AGP_DNA</td>\n",
       "      <td>0.368587</td>\n",
       "      <td>3.983743</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-0.218047</td>\n",
       "      <td>0.099024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2507</th>\n",
       "      <td>Cytoplasm_AreaShape_Zernike_5_1</td>\n",
       "      <td>0.397131</td>\n",
       "      <td>4.653107</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.313973</td>\n",
       "      <td>0.012627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2477</th>\n",
       "      <td>Cells_AreaShape_Zernike_2_0</td>\n",
       "      <td>0.452530</td>\n",
       "      <td>3.777016</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.300500</td>\n",
       "      <td>0.017164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2555</th>\n",
       "      <td>Nuclei_RadialDistribution_FracAtD_DNA_3of4</td>\n",
       "      <td>0.467579</td>\n",
       "      <td>5.298065</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.518075</td>\n",
       "      <td>0.000017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2509</th>\n",
       "      <td>Cytoplasm_AreaShape_Zernike_6_0</td>\n",
       "      <td>0.760266</td>\n",
       "      <td>3.965238</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.296635</td>\n",
       "      <td>0.018215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2531</th>\n",
       "      <td>Cytoplasm_RadialDistribution_MeanFrac_Brightfi...</td>\n",
       "      <td>0.788061</td>\n",
       "      <td>3.821740</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-0.559913</td>\n",
       "      <td>0.000002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                feature       bmd     max_z  \\\n",
       "2504                    Cytoplasm_AreaShape_Zernike_1_1  0.336326  3.445138   \n",
       "2510                    Cytoplasm_AreaShape_Zernike_6_2  0.362425  4.209308   \n",
       "2547                 Nuclei_Correlation_Overlap_AGP_DNA  0.368587  3.983743   \n",
       "2507                    Cytoplasm_AreaShape_Zernike_5_1  0.397131  4.653107   \n",
       "2477                        Cells_AreaShape_Zernike_2_0  0.452530  3.777016   \n",
       "2555         Nuclei_RadialDistribution_FracAtD_DNA_3of4  0.467579  5.298065   \n",
       "2509                    Cytoplasm_AreaShape_Zernike_6_0  0.760266  3.965238   \n",
       "2531  Cytoplasm_RadialDistribution_MeanFrac_Brightfi...  0.788061  3.821740   \n",
       "\n",
       "      direction  spearman    qvalue  \n",
       "2504        1.0  0.066715  0.655931  \n",
       "2510        1.0  0.313785  0.012627  \n",
       "2547       -1.0 -0.218047  0.099024  \n",
       "2507        1.0  0.313973  0.012627  \n",
       "2477        1.0  0.300500  0.017164  \n",
       "2555        1.0  0.518075  0.000017  \n",
       "2509        1.0  0.296635  0.018215  \n",
       "2531       -1.0 -0.559913  0.000002  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt.tl.dose_features(heparg)\n",
    "features = heparg.uns[\"mantispy\"][\"dose_features\"]\n",
    "# bmd is NaN for a feature that never crosses the cutoff, so dropna leaves the ones that responded.\n",
    "active = features[features[\"group\"] == \"Staurosporine\"].dropna(subset=[\"bmd\"])\n",
    "print(f\"{len(active)} of {features['feature'].nunique()} features respond to staurosporine\")\n",
    "active.sort_values(\"bmd\").head(8)[[\"feature\", \"bmd\", \"max_z\", \"direction\", \"spearman\", \"qvalue\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c015",
   "metadata": {},
   "source": [
    "The features that move first are shape and spatial-distribution measurements, with one channel correlation among\n",
    "them, not intensity ones.\n",
    "\n",
    "`Cytoplasm_AreaShape_Zernike_*` and `Cells_AreaShape_Zernike_*` are Zernike moments: an orthogonal decomposition of the cytoplasm or whole-cell outline, so a\n",
    "change means the cells are changing shape rather than getting brighter. `Nuclei_RadialDistribution_FracAtD_DNA_3of4`\n",
    "is the fraction of the DNA signal falling in the third of four concentric rings measured out from the nucleus\n",
    "centre, so a rise means the DNA signal has shifted toward that ring.\n",
    "\n",
    "`spearman` and `bmd` disagree in the first row. A monotone trend across the whole range and a threshold crossing\n",
    "are different questions: a feature that steps up early and then flattens has a low Spearman and a low benchmark\n",
    "dose. A crossing with no trend behind it is the weakest evidence in the table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c016",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:18.975712Z",
     "iopub.status.busy": "2026-10-21T01:01:18.975562Z",
     "iopub.status.idle": "2026-10-21T01:01:19.250293Z",
     "shell.execute_reply": "2026-10-21T01:01:19.249059Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 760x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "shown = [\"MUPIROCIN\", \"Amperozide\", \"CLIOQUINOL\", \"Fluazinam\", \"Staurosporine\"]\n",
    "jitter = np.random.default_rng(0)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(7.6, 3.0))\n",
    "for row, compound in enumerate(shown):\n",
    "    block = features[features[\"group\"] == compound].dropna(subset=[\"bmd\"])\n",
    "    if block.empty:\n",
    "        ax.text(0.25, row, \"no feature reaches the cutoff\", fontsize=8, va=\"center\", color=\"#999999\")\n",
    "        continue\n",
    "    ax.scatter(\n",
    "        block[\"bmd\"],\n",
    "        row + jitter.uniform(-0.18, 0.18, len(block)),\n",
    "        s=4 * block[\"max_z\"],\n",
    "        color=\"#3a7ca5\",\n",
    "        alpha=0.7,\n",
    "        edgecolor=\"none\",\n",
    "    )\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_xlim(0.2, 500)\n",
    "ax.set_ylim(-0.6, len(shown) - 0.4)\n",
    "ax.set_xlabel(\"benchmark dose (uM)\")\n",
    "ax.set_yticks(range(len(shown)), shown, fontsize=9)\n",
    "ax.set_title(\"Where each feature first passes three control MADs, point size its largest response\", fontsize=10)\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c017",
   "metadata": {},
   "source": [
    "The potencies span a wide range: staurosporine moves a feature at 0.34 uM, while fluazinam, clioquinol and\n",
    "amperozide each need a higher concentration before any feature responds. Mupirocin moves none of the 99, which\n",
    "is what a compound with no mammalian target should do and is the check that the cutoff is set sensibly."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c018",
   "metadata": {},
   "source": [
    "## The same phenotype, or a different one?\n",
    "\n",
    "A distance from the controls grows for two reasons that mean different things: the same phenotype gets stronger,\n",
    "or a different one takes over. Distance cannot separate them, because it discards the direction.\n",
    "\n",
    "{func}`~mantispy.tl.dose_direction` keeps the direction. Each concentration gets `amplitude`, how far its median\n",
    "profile sits from the controls in MADs per feature; `split_half_cosine`, the cosine between the directions the\n",
    "two halves of its replicate plates point in; and `cosine_to_top`, the cosine against the highest concentration's\n",
    "profile. `amplitude_null` is what control wells spread over the same plates in the same numbers reach.\n",
    "\n",
    "Read together: a concentration whose plate halves disagree has no direction at all, however large its amplitude.\n",
    "One whose halves agree but which points away from the top concentration is a real phenotype, and a different one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c019",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:19.253887Z",
     "iopub.status.busy": "2026-10-21T01:01:19.253729Z",
     "iopub.status.idle": "2026-10-21T01:01:19.976209Z",
     "shell.execute_reply": "2026-10-21T01:01:19.975094Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x330 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mt.tl.dose_direction(heparg)\n",
    "direction = heparg.uns[\"mantispy\"][\"dose_direction\"]\n",
    "\n",
    "fig, axes = plt.subplots(1, 3, figsize=(12, 3.3), sharex=True)\n",
    "for compound in shown[::-1]:\n",
    "    block = direction[direction[\"group\"] == compound].sort_values(\"dose\")\n",
    "    for ax, column in zip(axes, [\"amplitude\", \"split_half_cosine\", \"cosine_to_top\"], strict=True):\n",
    "        ax.plot(block[\"dose\"], block[column], marker=\"o\", ms=4, lw=1.4, label=compound)\n",
    "\n",
    "axes[0].axhline(direction[\"amplitude_null\"].median(), ls=\"--\", lw=1, color=\"0.4\", label=\"control wells\")\n",
    "axes[1].axhline(0.5, ls=\"--\", lw=1, color=\"0.4\")\n",
    "titles = [\"amplitude (MADs per feature)\", \"split-half cosine\", \"cosine to the top concentration\"]\n",
    "for ax, title in zip(axes, titles, strict=True):\n",
    "    ax.set_xscale(\"log\")\n",
    "    ax.set_xlabel(\"concentration (uM)\")\n",
    "    ax.set_title(title, fontsize=10)\n",
    "axes[0].legend(fontsize=7, frameon=False)\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c020",
   "metadata": {},
   "source": [
    "Amperozide and clioquinol are the simple case. Nothing happens at the low concentrations, and then the\n",
    "amplitude climbs while `cosine_to_top` rises alongside it. One phenotype, arriving late and getting stronger.\n",
    "A single number per concentration loses nothing for these two.\n",
    "\n",
    "Staurosporine is the case a single number hides. Its amplitude rises early and then stops climbing, so as a\n",
    "distance it saturates well below the top of the range. But its plate halves agree from the low concentrations\n",
    "on, so each of those has a direction that reproduces, while `cosine_to_top` stays low throughout. The cell is\n",
    "doing something different at the bottom of the range than at the top. The next section shows what.\n",
    "\n",
    "Fluazinam is an uncoupler of mitochondrial oxidative phosphorylation. Its halves agree across much of the\n",
    "range, `cosine_to_top` stays low throughout, and its amplitude falls back at the top of the range. Its top\n",
    "concentration is doing something this page does not resolve.\n",
    "\n",
    "Mupirocin sits on the floor: its amplitude barely clears the control null, and no concentration has halves\n",
    "that agree. Its strongest concentration reaches a little above the null with no reproducible direction, which\n",
    "is why amplitude alone is not enough to call a response."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c021",
   "metadata": {},
   "source": [
    "### What staurosporine's two phenotypes are\n",
    "\n",
    "`cosine_to_top` says the direction turns. It does not say into what. Each column of `heparg.X` is already scaled\n",
    "against its own plate's controls, so the median of a concentration's wells reads directly in control MADs and the\n",
    "features can be plotted against dose.\n",
    "\n",
    "Group on `Metadata_Concentration`, the dose each well was meant to get. Grouping on\n",
    "`Metadata_ConcentrationRecorded` would alternate between the two batches' spellings at every step of the\n",
    "ladder."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c022",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:19.981769Z",
     "iopub.status.busy": "2026-10-21T01:01:19.981610Z",
     "iopub.status.idle": "2026-10-21T01:01:20.457068Z",
     "shell.execute_reply": "2026-10-21T01:01:20.455560Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1100x340 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "early = [\n",
    "    \"Cells_AreaShape_Zernike_2_0\",\n",
    "    \"Nuclei_RadialDistribution_FracAtD_DNA_3of4\",\n",
    "    \"Nuclei_RadialDistribution_MeanFrac_RNA_3of4\",\n",
    "]\n",
    "late = [\n",
    "    \"Nuclei_Correlation_Correlation_AGP_Mito\",\n",
    "    \"Nuclei_Correlation_Correlation_Mito_RNA\",\n",
    "    \"Nuclei_Correlation_Overlap_AGP_ER\",\n",
    "]\n",
    "\n",
    "stauro = heparg[heparg.obs[\"Metadata_Compound\"] == \"Staurosporine\"]\n",
    "traces = pd.DataFrame(np.asarray(stauro[:, early + late].X), columns=early + late)\n",
    "traces[\"dose\"] = stauro.obs[\"Metadata_Concentration\"].to_numpy(dtype=float)\n",
    "traces = traces.groupby(\"dose\").median()\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(11, 3.4), sharey=True)\n",
    "for ax, group, title in zip(\n",
    "    axes, [early, late], [\"moves at 0.4 uM: shape and chromatin\", \"moves at 300 uM: channels collapsing\"], strict=True\n",
    "):\n",
    "    for feature in group:\n",
    "        ax.plot(traces.index, traces[feature], marker=\"o\", ms=4, lw=1.5, label=feature.replace(\"_\", \" \"))\n",
    "    ax.axhline(0, color=\"0.6\", lw=1)\n",
    "    ax.set_xscale(\"log\")\n",
    "    ax.set_xlabel(\"concentration (uM)\")\n",
    "    ax.set_title(title, fontsize=10)\n",
    "    ax.legend(fontsize=6.5, frameon=False)\n",
    "axes[0].set_ylabel(\"MADs from the controls\")\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c023",
   "metadata": {},
   "source": [
    "Two different things, at two different concentrations.\n",
    "\n",
    "At 0.4 uM the cells change shape and their DNA and RNA signal redistributes radially: a Zernike moment of the cell outline,\n",
    "the fraction of DNA signal in the third of four rings out from the nucleus centre, the same for RNA. That is the morphology of a cell\n",
    "that has changed shape and redistributed its nuclear signal.\n",
    "These three then stay elevated across the remaining two and a half decades, and fall back at the very top\n",
    "concentration.\n",
    "\n",
    "At 300 uM a different set takes over, and all of them are channel-to-channel correlations inside the nucleus\n",
    "region: AGP against Mito, Mito against RNA, AGP against ER. AGP is the actin, Golgi and plasma-membrane stain.\n",
    "Channels agreeing this much inside the nucleus region are not a phenotype in the usual sense: they are consistent with what\n",
    "the image looks like when the cell has lost its internal organisation, though these three features alone do not show that.\n",
    "`Nuclei_Correlation_Correlation_AGP_Mito` is the strongest of these at the top concentration.\n",
    "\n",
    "So the distance saturating from about 1 uM while the direction keeps turning is a sequence of two profiles: the\n",
    "shape and radial-distribution profile arrives first and stops, and the channel-correlation profile takes over later. Two of the\n",
    "plotted features change sign at the top: the RNA radial fraction falls below zero and the AGP-Mito correlation\n",
    "rises from below it. A curve fitted to distance\n",
    "alone reports one EC50 for both and describes neither."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c024",
   "metadata": {},
   "source": [
    "## Where on the ladder is anything happening?\n",
    "\n",
    "Every column so far describes a single concentration. None says which stretch of the ladder is worth reading.\n",
    "\n",
    "`dose_direction` labels each concentration with a `phase`:\n",
    "\n",
    "- `silent`: no reproducible response.\n",
    "- `responding`: still moving. The step from the concentration below, `step_amplitude`, beats the noise two\n",
    "  independent groups of wells carry.\n",
    "- `saturated`: reproducible, but it has stopped changing.\n",
    "- `cytotoxic`: more than half the cells are gone, so the profile is the morphology of dying cells whatever else\n",
    "  is true of it. The US EPA's phenotypic pipeline drops these before fitting anything.\n",
    "\n",
    "The window is a run, not a scatter: `split_half_cosine` over eight wells is itself noisy, and a response that\n",
    "has started does not stop, so the window is the run of concentrations reaching the highest one that is not\n",
    "cytotoxic."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c025",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:20.463061Z",
     "iopub.status.busy": "2026-10-21T01:01:20.462892Z",
     "iopub.status.idle": "2026-10-21T01:01:20.475823Z",
     "shell.execute_reply": "2026-10-21T01:01:20.474682Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dose</th>\n",
       "      <th>amplitude</th>\n",
       "      <th>amplitude_null</th>\n",
       "      <th>step_amplitude</th>\n",
       "      <th>split_half_cosine</th>\n",
       "      <th>viability</th>\n",
       "      <th>phase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.02</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.18</td>\n",
       "      <td>1.01</td>\n",
       "      <td>silent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>0.05</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.20</td>\n",
       "      <td>1.02</td>\n",
       "      <td>silent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>0.14</td>\n",
       "      <td>0.54</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.92</td>\n",
       "      <td>silent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>0.41</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.91</td>\n",
       "      <td>silent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>1.23</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.59</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.98</td>\n",
       "      <td>silent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>3.70</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.94</td>\n",
       "      <td>silent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>11.11</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.97</td>\n",
       "      <td>silent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>33.33</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.69</td>\n",
       "      <td>1.05</td>\n",
       "      <td>responding</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>100.00</td>\n",
       "      <td>1.65</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1.17</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.85</td>\n",
       "      <td>responding</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>300.00</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1.22</td>\n",
       "      <td>0.89</td>\n",
       "      <td>0.77</td>\n",
       "      <td>responding</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      dose  amplitude  amplitude_null  step_amplitude  split_half_cosine  \\\n",
       "40    0.02       0.45             0.4            0.45               0.18   \n",
       "41    0.05       0.52             0.4            0.65               0.20   \n",
       "42    0.14       0.54             0.4            0.57               0.16   \n",
       "43    0.41       0.57             0.4            0.82               0.45   \n",
       "44    1.23       0.49             0.4            0.59               0.18   \n",
       "45    3.70       0.55             0.4            0.60               0.66   \n",
       "46   11.11       0.48             0.4            0.60               0.35   \n",
       "47   33.33       0.92             0.4            0.86               0.69   \n",
       "48  100.00       1.65             0.4            1.17               0.72   \n",
       "49  300.00       2.30             0.4            1.22               0.89   \n",
       "\n",
       "    viability       phase  \n",
       "40       1.01      silent  \n",
       "41       1.02      silent  \n",
       "42       0.92      silent  \n",
       "43       0.91      silent  \n",
       "44       0.98      silent  \n",
       "45       0.94      silent  \n",
       "46       0.97      silent  \n",
       "47       1.05  responding  \n",
       "48       0.85  responding  \n",
       "49       0.77  responding  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "direction[direction[\"group\"] == \"Amperozide\"][\n",
    "    [\"dose\", \"amplitude\", \"amplitude_null\", \"step_amplitude\", \"split_half_cosine\", \"viability\", \"phase\"]\n",
    "].round(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c026",
   "metadata": {},
   "source": [
    "{func}`~mantispy.pl.dose_direction` draws that reading. The solid line is how far the profile sits from the\n",
    "controls and the dashed line is how far it moved from the concentration below, which is the one that says where\n",
    "the action is. The background is banded by phase."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c027",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:20.479461Z",
     "iopub.status.busy": "2026-10-21T01:01:20.479318Z",
     "iopub.status.idle": "2026-10-21T01:01:20.898699Z",
     "shell.execute_reply": "2026-10-21T01:01:20.897426Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script>\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        </script>\n",
       "        <script type=\"module\">import \"https://cdn.plot.ly/plotly-4.1.1.min\"</script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"height:525px; width:100%;\">            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/3.2.2/es5/tex-svg.min.js\"></script><script>if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script>window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
       "        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-4.1.1.min.js\" integrity=\"sha256-O24V1F27f8pb0glCkelh3cVHLNiHAJ5gCaVtq2aNch8=\" crossorigin=\"anonymous\"></script>                <div id=\"9e21e1f3-b980-457a-a673-2bff0994984c\" class=\"plotly-graph-div\" style=\"height:100%; width:100%;\"></div>            <script>                window.PLOTLYENV=window.PLOTLYENV || {};                                if (document.getElementById(\"9e21e1f3-b980-457a-a673-2bff0994984c\")) {                    Plotly.newPlot(                        \"9e21e1f3-b980-457a-a673-2bff0994984c\",                        [{\"hovertemplate\":\"series=distance from controls\\u003cbr\\u003econcentration=%{x}\\u003cbr\\u003eMADs per feature=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"distance from controls\",\"line\":{\"color\":\"#636efa\",\"dash\":\"solid\"},\"marker\":{\"symbol\":\"circle\"},\"mode\":\"lines+markers\",\"name\":\"distance from controls\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"xY8xdy0hjz\\u002f1udqK\\u002fWWnP0UEfrXsjsE\\u002f8cHLCWNW2j8nyHdFysDzPyNQEWgvoQ1AMlgvjuM4JkAmgqOqqqpAQAAAAAAAAFlAAAAAAADAckA=\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"0CIKGBVJ5T\\u002fxWSoKYz7pP5hy1ijaDOc\\u002fncpkAGcY+D+rWN34tqr9PwFwTzfWR\\u002fs\\u002fOo0Qy4H8\\u002fj81uvPaSpwAQFcPeTkPLf0\\u002fj7OgAjcmAEA=\"},\"yaxis\":\"y\",\"type\":\"scatter\"},{\"hovertemplate\":\"series=moved since the last\\u003cbr\\u003econcentration=%{x}\\u003cbr\\u003eMADs per feature=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"moved since the last\",\"line\":{\"color\":\"#EF553B\",\"dash\":\"solid\"},\"marker\":{\"symbol\":\"circle\"},\"mode\":\"lines+markers\",\"name\":\"moved since the last\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"xY8xdy0hjz\\u002f1udqK\\u002fWWnP0UEfrXsjsE\\u002f8cHLCWNW2j8nyHdFysDzPyNQEWgvoQ1AMlgvjuM4JkAmgqOqqqpAQAAAAAAAAFlAAAAAAADAckA=\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"0CIKGBVJ5T96rMNbbp\\u002fhP3Ffkp8nTOM\\u002fXP9uoDIc9T+zQ9uCIXHtPxDG0FWNy+U\\u002fLZoOxYuV6D\\u002fCr1M5mRTnPyoNR4g+KvA\\u002fxmbv+wnsA0A=\"},\"yaxis\":\"y\",\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermap\":[{\"type\":\"scattermap\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"concentration\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"MADs per feature\"}},\"legend\":{\"title\":{\"text\":\"series\"},\"tracegroupgap\":0},\"title\":{\"text\":\"Staurosporine\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('9e21e1f3-b980-457a-a673-2bff0994984c');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "        <script>\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        </script>\n",
       "        <script type=\"module\">import \"https://cdn.plot.ly/plotly-4.1.1.min\"</script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"height:525px; width:100%;\">            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/3.2.2/es5/tex-svg.min.js\"></script><script>if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script>window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
       "        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-4.1.1.min.js\" integrity=\"sha256-O24V1F27f8pb0glCkelh3cVHLNiHAJ5gCaVtq2aNch8=\" crossorigin=\"anonymous\"></script>                <div id=\"d2839630-0f94-48c2-af03-d801e8c73efb\" class=\"plotly-graph-div\" style=\"height:100%; width:100%;\"></div>            <script>                window.PLOTLYENV=window.PLOTLYENV || {};                                if (document.getElementById(\"d2839630-0f94-48c2-af03-d801e8c73efb\")) {                    Plotly.newPlot(                        \"d2839630-0f94-48c2-af03-d801e8c73efb\",                        [{\"hovertemplate\":\"series=distance from controls\\u003cbr\\u003econcentration=%{x}\\u003cbr\\u003eMADs per feature=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"distance from controls\",\"line\":{\"color\":\"#636efa\",\"dash\":\"solid\"},\"marker\":{\"symbol\":\"circle\"},\"mode\":\"lines+markers\",\"name\":\"distance from controls\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"xY8xdy0hjz\\u002f1udqK\\u002fWWnP1H+5qzsjsE\\u002fth+TBmNW2j8nyHdFysDzP1MIVmgvoQ1AMlgvjuM4JkAmgqOqqqpAQDlD9f\\u002f\\u002f\\u002f1hAAAAAAADAckA=\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"98ynlRe68z8uvSVZ\\u002fF3xPxtnxqVoqPM\\u002faMZe+dio8T+\\u002f\\u002fOrTxIT1Px4XdUzfmfI\\u002fkxzMdeMU8z\\u002fIbyy8mFb3PwfUQmkIeAJA7TcsUuPiEEA=\"},\"yaxis\":\"y\",\"type\":\"scatter\"},{\"hovertemplate\":\"series=moved since the last\\u003cbr\\u003econcentration=%{x}\\u003cbr\\u003eMADs per feature=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"moved since the last\",\"line\":{\"color\":\"#EF553B\",\"dash\":\"solid\"},\"marker\":{\"symbol\":\"circle\"},\"mode\":\"lines+markers\",\"name\":\"moved since the last\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"xY8xdy0hjz\\u002f1udqK\\u002fWWnP1H+5qzsjsE\\u002fth+TBmNW2j8nyHdFysDzP1MIVmgvoQ1AMlgvjuM4JkAmgqOqqqpAQDlD9f\\u002f\\u002f\\u002f1hAAAAAAADAckA=\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"98ynlRe68z9KaDeR9SPrP\\u002fjlS3xLwOw\\u002fvx3AXu+C5z8mBhfdjLrwPxRcdL+Mbu8\\u002f\\u002f4jeYFLa7j9plhbemyPvP3J3vH0JmvQ\\u002fIIylfjcACEA=\"},\"yaxis\":\"y\",\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermap\":[{\"type\":\"scattermap\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"concentration\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"MADs per feature\"}},\"legend\":{\"title\":{\"text\":\"series\"},\"tracegroupgap\":0},\"title\":{\"text\":\"Actinomycin D\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('d2839630-0f94-48c2-af03-d801e8c73efb');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "        <script>\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        </script>\n",
       "        <script type=\"module\">import \"https://cdn.plot.ly/plotly-4.1.1.min\"</script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"height:525px; width:100%;\">            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/3.2.2/es5/tex-svg.min.js\"></script><script>if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script>window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
       "        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-4.1.1.min.js\" integrity=\"sha256-O24V1F27f8pb0glCkelh3cVHLNiHAJ5gCaVtq2aNch8=\" crossorigin=\"anonymous\"></script>                <div id=\"f803110c-dfb4-444e-96b6-3b40ed8bba64\" class=\"plotly-graph-div\" style=\"height:100%; width:100%;\"></div>            <script>                window.PLOTLYENV=window.PLOTLYENV || {};                                if (document.getElementById(\"f803110c-dfb4-444e-96b6-3b40ed8bba64\")) {                    Plotly.newPlot(                        \"f803110c-dfb4-444e-96b6-3b40ed8bba64\",                        [{\"hovertemplate\":\"series=distance from controls\\u003cbr\\u003econcentration=%{x}\\u003cbr\\u003eMADs per feature=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"distance from controls\",\"line\":{\"color\":\"#636efa\",\"dash\":\"solid\"},\"marker\":{\"symbol\":\"circle\"},\"mode\":\"lines+markers\",\"name\":\"distance from controls\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"xY8xdy0hjz\\u002f1udqK\\u002fWWnP86\\u002fDK\\u002fsjsE\\u002fdACmB2NW2j+HOAFGysDzPzusM2gvoQ1AMlgvjuM4JkC1+7iqqqpAQAAAAAAAAFlAAAAAAADAckA=\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"o0K0Av2v4T94zohuD6feP7ISvyJ9fd0\\u002fnHc3E4\\u002f04z\\u002f6zt4X3z3iP1sEGn2mDeY\\u002f4ktt1Sde8D8bpge8GEr2P9a3Uu9FJQZACu3LQifZ+j8=\"},\"yaxis\":\"y\",\"type\":\"scatter\"},{\"hovertemplate\":\"series=moved since the last\\u003cbr\\u003econcentration=%{x}\\u003cbr\\u003eMADs per feature=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"moved since the last\",\"line\":{\"color\":\"#EF553B\",\"dash\":\"solid\"},\"marker\":{\"symbol\":\"circle\"},\"mode\":\"lines+markers\",\"name\":\"moved since the last\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"xY8xdy0hjz\\u002f1udqK\\u002fWWnP86\\u002fDK\\u002fsjsE\\u002fdACmB2NW2j+HOAFGysDzPzusM2gvoQ1AMlgvjuM4JkC1+7iqqqpAQAAAAAAAAFlAAAAAAADAckA=\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"o0K0Av2v4T+H3SBokkLjPx14UC\\u002fTguI\\u002fTQBDTRvZ4j+z444sdNzkP\\u002fvX5D4ESeM\\u002f4tnnUQEH6j8cDV3ZZkjmPx9JKvoVbvo\\u002fXrX9fVlJBUA=\"},\"yaxis\":\"y\",\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermap\":[{\"type\":\"scattermap\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"concentration\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"MADs per feature\"}},\"legend\":{\"title\":{\"text\":\"series\"},\"tracegroupgap\":0},\"title\":{\"text\":\"Fluazinam\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('f803110c-dfb4-444e-96b6-3b40ed8bba64');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "        <script>\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        </script>\n",
       "        <script type=\"module\">import \"https://cdn.plot.ly/plotly-4.1.1.min\"</script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"height:525px; width:100%;\">            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/3.2.2/es5/tex-svg.min.js\"></script><script>if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script>window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
       "        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-4.1.1.min.js\" integrity=\"sha256-O24V1F27f8pb0glCkelh3cVHLNiHAJ5gCaVtq2aNch8=\" crossorigin=\"anonymous\"></script>                <div id=\"7a6a6cb1-2e10-4dc2-9f7c-4ad2d918f7d6\" class=\"plotly-graph-div\" style=\"height:100%; width:100%;\"></div>            <script>                window.PLOTLYENV=window.PLOTLYENV || {};                                if (document.getElementById(\"7a6a6cb1-2e10-4dc2-9f7c-4ad2d918f7d6\")) {                    Plotly.newPlot(                        \"7a6a6cb1-2e10-4dc2-9f7c-4ad2d918f7d6\",                        [{\"hovertemplate\":\"series=distance from controls\\u003cbr\\u003econcentration=%{x}\\u003cbr\\u003eMADs per feature=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"distance from controls\",\"line\":{\"color\":\"#636efa\",\"dash\":\"solid\"},\"marker\":{\"symbol\":\"circle\"},\"mode\":\"lines+markers\",\"name\":\"distance from controls\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"xY8xdy0hjz\\u002f1udqK\\u002fWWnP1H+5qzsjsE\\u002fdACmB2NW2j8nyHdFysDzP1MIVmgvoQ1AMlgvjuM4JkAmgqOqqqpAQAAAAAAAAFlAAAAAAADAckA=\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"Z6L1Fc2B3D8aU5bDuIjgP8BHp9NrH+E\\u002fPhqtbGwt4j\\u002fH\\u002fg0bLHbfP64BdoH4fOE\\u002fUvhfsFO13j+5U9clY1rtP8V0VlElYPo\\u002faCBHi2BpAkA=\"},\"yaxis\":\"y\",\"type\":\"scatter\"},{\"hovertemplate\":\"series=moved since the last\\u003cbr\\u003econcentration=%{x}\\u003cbr\\u003eMADs per feature=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"moved since the last\",\"line\":{\"color\":\"#EF553B\",\"dash\":\"solid\"},\"marker\":{\"symbol\":\"circle\"},\"mode\":\"lines+markers\",\"name\":\"moved since the last\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"xY8xdy0hjz\\u002f1udqK\\u002fWWnP1H+5qzsjsE\\u002fdACmB2NW2j8nyHdFysDzP1MIVmgvoQ1AMlgvjuM4JkAmgqOqqqpAQAAAAAAAAFlAAAAAAADAckA=\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"Z6L1Fc2B3D+r74yqQvHkP5gb8vLUWOI\\u002fcEaJDTFi6j8vK\\u002fShD\\u002ffiP2OOA4kaGuM\\u002fv0hsYH8f4z+N94sFSYnrP4FES0TbrPI\\u002fhJ3Ebf2C8z8=\"},\"yaxis\":\"y\",\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermap\":[{\"type\":\"scattermap\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"concentration\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"MADs per feature\"}},\"legend\":{\"title\":{\"text\":\"series\"},\"tracegroupgap\":0},\"title\":{\"text\":\"Amperozide\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('7a6a6cb1-2e10-4dc2-9f7c-4ad2d918f7d6');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "        <script>\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        </script>\n",
       "        <script type=\"module\">import \"https://cdn.plot.ly/plotly-4.1.1.min\"</script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"height:525px; width:100%;\">            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/3.2.2/es5/tex-svg.min.js\"></script><script>if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script>window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
       "        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-4.1.1.min.js\" integrity=\"sha256-O24V1F27f8pb0glCkelh3cVHLNiHAJ5gCaVtq2aNch8=\" crossorigin=\"anonymous\"></script>                <div id=\"07e2c929-b53a-40ef-9752-f1572f076e2b\" class=\"plotly-graph-div\" style=\"height:100%; width:100%;\"></div>            <script>                window.PLOTLYENV=window.PLOTLYENV || {};                                if (document.getElementById(\"07e2c929-b53a-40ef-9752-f1572f076e2b\")) {                    Plotly.newPlot(                        \"07e2c929-b53a-40ef-9752-f1572f076e2b\",                        [{\"hovertemplate\":\"series=distance from controls\\u003cbr\\u003econcentration=%{x}\\u003cbr\\u003eMADs per feature=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"distance from controls\",\"line\":{\"color\":\"#636efa\",\"dash\":\"solid\"},\"marker\":{\"symbol\":\"circle\"},\"mode\":\"lines+markers\",\"name\":\"distance from controls\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"xY8xdy0hjz\\u002f1udqK\\u002fWWnP8hCWLPsjsE\\u002fM+G4CGNW2j8nyHdFysDzP1MIVmgvoQ1AMlgvjuM4JkAmgqOqqqpAQAAAAAAAAFlAAAAAAADAckA=\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"pYT1H1my2z9OcmDLVY7mP51rp58kOOU\\u002fGdYxynXr5T\\u002fo8WTUhBTmP1R4myR1guY\\u002frpwuzJNa6j\\u002ffPNSMiBfpP7ry29lYje0\\u002fcKJBuOJ5\\u002fD8=\"},\"yaxis\":\"y\",\"type\":\"scatter\"},{\"hovertemplate\":\"series=moved since the last\\u003cbr\\u003econcentration=%{x}\\u003cbr\\u003eMADs per feature=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"moved since the last\",\"line\":{\"color\":\"#EF553B\",\"dash\":\"solid\"},\"marker\":{\"symbol\":\"circle\"},\"mode\":\"lines+markers\",\"name\":\"moved since the last\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"xY8xdy0hjz\\u002f1udqK\\u002fWWnP8hCWLPsjsE\\u002fM+G4CGNW2j8nyHdFysDzP1MIVmgvoQ1AMlgvjuM4JkAmgqOqqqpAQAAAAAAAAFlAAAAAAADAckA=\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"pYT1H1my2z97VGZJbBHnP4Sput3RWec\\u002fAsU\\u002f\\u002fehc6z\\u002ferBfT2ZfrP43tVgsPq+o\\u002fJhI7ON0X6j+1dFIVKCzwPz3Jawzusuk\\u002fvw+8oXFs9D8=\"},\"yaxis\":\"y\",\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermap\":[{\"type\":\"scattermap\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"concentration\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"MADs per feature\"}},\"legend\":{\"title\":{\"text\":\"series\"},\"tracegroupgap\":0},\"title\":{\"text\":\"Cycloheximide\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('07e2c929-b53a-40ef-9752-f1572f076e2b');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "        <script>\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        </script>\n",
       "        <script type=\"module\">import \"https://cdn.plot.ly/plotly-4.1.1.min\"</script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"height:525px; width:100%;\">            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/3.2.2/es5/tex-svg.min.js\"></script><script>if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script>window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
       "        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-4.1.1.min.js\" integrity=\"sha256-O24V1F27f8pb0glCkelh3cVHLNiHAJ5gCaVtq2aNch8=\" crossorigin=\"anonymous\"></script>                <div id=\"c7ef745e-1395-4c36-bd42-5be102df7381\" class=\"plotly-graph-div\" style=\"height:100%; width:100%;\"></div>            <script>                window.PLOTLYENV=window.PLOTLYENV || {};                                if (document.getElementById(\"c7ef745e-1395-4c36-bd42-5be102df7381\")) {                    Plotly.newPlot(                        \"c7ef745e-1395-4c36-bd42-5be102df7381\",                        [{\"hovertemplate\":\"series=distance from controls\\u003cbr\\u003econcentration=%{x}\\u003cbr\\u003eMADs per feature=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"distance from controls\",\"line\":{\"color\":\"#636efa\",\"dash\":\"solid\"},\"marker\":{\"symbol\":\"circle\"},\"mode\":\"lines+markers\",\"name\":\"distance from controls\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"xY8xdy0hjz\\u002f1udqK\\u002fWWnP9Q8warsjsE\\u002fth+TBmNW2j+28EVGysDzP2tkeGgvoQ1AMlgvjuM4JkAmgqOqqqpAQHGG6v\\u002f\\u002f\\u002f1hAAAAAAADAckA=\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"QDFlHM982T\\u002fc\\u002fX5Cw7vgPz6QHfyHA+A\\u002fG\\u002fVqewp14T9E9vCl+1riP1XZ61VYh+M\\u002fVl8py37H4D84TwHXFw\\u002fqP9yHdIdnWeQ\\u002fsaq1NSTt6D8=\"},\"yaxis\":\"y\",\"type\":\"scatter\"},{\"hovertemplate\":\"series=moved since the last\\u003cbr\\u003econcentration=%{x}\\u003cbr\\u003eMADs per feature=%{y}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"moved since the last\",\"line\":{\"color\":\"#EF553B\",\"dash\":\"solid\"},\"marker\":{\"symbol\":\"circle\"},\"mode\":\"lines+markers\",\"name\":\"moved since the last\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"xY8xdy0hjz\\u002f1udqK\\u002fWWnP9Q8warsjsE\\u002fth+TBmNW2j+28EVGysDzP2tkeGgvoQ1AMlgvjuM4JkAmgqOqqqpAQHGG6v\\u002f\\u002f\\u002f1hAAAAAAADAckA=\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"QDFlHM982T8Gm74D6mziPziMQ31BUts\\u002fRm6zGQGi5j+qfbj2cavkP9iEhXh\\u002frOY\\u002fBRZaY\\u002fpN5T+K7J8bkwLoP78rHGLasfE\\u002fs913WAzq6j8=\"},\"yaxis\":\"y\",\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermap\":[{\"type\":\"scattermap\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"concentration\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"MADs per feature\"}},\"legend\":{\"title\":{\"text\":\"series\"},\"tracegroupgap\":0},\"title\":{\"text\":\"MUPIROCIN\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('c7ef745e-1395-4c36-bd42-5be102df7381');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for compound in [\"Staurosporine\", \"Actinomycin D\", \"Fluazinam\", \"Amperozide\", \"Cycloheximide\", \"MUPIROCIN\"]:\n",
    "    mt.pl.dose_direction(heparg, compound=compound)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c028",
   "metadata": {},
   "source": [
    "Mupirocin is grey the whole way. Amperozide and cycloheximide are grey until about 30 uM and then respond to the\n",
    "top, so seven of their ten concentrations sit below their effective range, which is the expected result of\n",
    "covering four decades to find a window you cannot predict, not a wasted experiment.\n",
    "\n",
    "Staurosporine responds from 0.14 uM to the top without settling, which is the turning direction above seen from\n",
    "another side: a compound whose step never falls back to the noise has not finished changing.\n",
    "\n",
    "Actinomycin D is responding at the lowest concentration tested. It intercalates DNA and blocks RNA polymerase at\n",
    "nanomolar concentrations, so 15 nM is already well inside its range and its onset lies below this ladder, and the\n",
    "screen cannot say where. Where a concentration\n",
    "falls below half the cells, the band turns red. Both edges of a dose series can fall outside it."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c029",
   "metadata": {},
   "source": [
    "### Check the cell counts before trusting a cytotoxic call\n",
    "\n",
    "`viability` is each well's cell count per field against **its own plate's** controls. That matters here: the eight\n",
    "plates range from 484 to 708 control cells per field, so scoring against the whole screen's median would mark the\n",
    "sparser plates as dying and hide real losses on the denser ones.\n",
    "\n",
    "Per-plate normalisation is necessary but not sufficient. The pilot's HepaRG wells come from two batches, and they\n",
    "do not agree about cell loss."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c030",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:20.902303Z",
     "iopub.status.busy": "2026-10-21T01:01:20.902100Z",
     "iopub.status.idle": "2026-10-21T01:01:21.012902Z",
     "shell.execute_reply": "2026-10-21T01:01:21.011429Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "control cells per field, by plate:\n",
      "Metadata_Plate\n",
      "BR00145690    587.0\n",
      "BR00145691    572.0\n",
      "BR00145692    524.0\n",
      "BR00145693    652.0\n",
      "BR00145694    597.0\n",
      "BR00145695    484.0\n",
      "BR00147878    696.0\n",
      "BR00147879    708.0\n",
      "\n",
      "viability of treated wells, by batch:\n",
      "            count   25%   50%   75%\n",
      "batch                              \n",
      "HepaRG_AD  1871.0  0.90  0.98  1.05\n",
      "Ptx_AD2     704.0  0.66  0.82  0.96\n",
      "\n",
      "viability below 0.2 uM, by batch:\n",
      "batch\n",
      "HepaRG_AD    0.99\n",
      "Ptx_AD2      0.87\n"
     ]
    }
   ],
   "source": [
    "heparg.obs[\"batch\"] = np.where(\n",
    "    heparg.obs[\"Metadata_Plate\"].astype(str).str.startswith(\"BR001478\"), \"Ptx_AD2\", \"HepaRG_AD\"\n",
    ")\n",
    "control = heparg.obs[\"Metadata_Control\"].to_numpy(dtype=bool)\n",
    "per_field = heparg.obs[\"Metadata_CellCount\"] / heparg.obs[\"Metadata_SiteCount\"]\n",
    "\n",
    "print(\"control cells per field, by plate:\")\n",
    "print(per_field[control].groupby(heparg.obs[\"Metadata_Plate\"][control], observed=True).median().round(0).to_string())\n",
    "\n",
    "# Each well against its own plate's controls, which is what dose_direction's viability column is.\n",
    "reference = per_field[control].groupby(heparg.obs[\"Metadata_Plate\"][control], observed=True).median()\n",
    "viability = per_field / heparg.obs[\"Metadata_Plate\"].map(reference).astype(float)\n",
    "print(\"\\nviability of treated wells, by batch:\")\n",
    "print(\n",
    "    viability[~control]\n",
    "    .groupby(heparg.obs[\"batch\"][~control])\n",
    "    .describe()[[\"count\", \"25%\", \"50%\", \"75%\"]]\n",
    "    .round(2)\n",
    "    .to_string()\n",
    ")\n",
    "\n",
    "# At the bottom of the ladder nothing should have happened yet, so any gap there is not the compound.\n",
    "low = ~control & (heparg.obs[\"Metadata_Concentration\"].to_numpy(dtype=float) < 0.2)\n",
    "print(\"\\nviability below 0.2 uM, by batch:\")\n",
    "print(viability[low].groupby(heparg.obs[\"batch\"][low]).median().round(2).to_string())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c031",
   "metadata": {},
   "source": [
    "Against its own plate's controls, the median treated well in the `HepaRG_AD` batch sits at 0.98 of control and\n",
    "the median treated well in `Ptx_AD2` at 0.82. The gap is not dose-driven: below 0.2 uM, where almost nothing\n",
    "should have happened yet, the two sit at 0.99 and 0.87.\n",
    "\n",
    "A cytotoxicity call is a claim about cell counts, and cell counts are the most batch-sensitive number in\n",
    "a screen: check them against the plate layout before believing one."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c032",
   "metadata": {},
   "source": [
    "### The point of departure\n",
    "\n",
    "Toxicology has a name for the concentration at which a response leaves the baseline: the point of departure,\n",
    "which is what a benchmark dose estimates. This page has now arrived at one twice by different routes.\n",
    "{func}`~mantispy.tl.dose_features` crosses each feature against the spread the controls show on it and reports\n",
    "where that happens. {func}`~mantispy.tl.dose_direction` asks when the whole profile starts moving in a direction\n",
    "that reproduces across plates, and the onset of the responding window is its answer.\n",
    "\n",
    "They are not the same construction, so whether they agree is worth checking rather than assuming."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c033",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:21.016367Z",
     "iopub.status.busy": "2026-10-21T01:01:21.016216Z",
     "iopub.status.idle": "2026-10-21T01:01:21.034839Z",
     "shell.execute_reply": "2026-10-21T01:01:21.033693Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20 compounds with both | rank correlation 0.79 | 16 within one step\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>window_onset</th>\n",
       "      <th>feature_bmd_5th</th>\n",
       "      <th>steps_apart</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Actinomycin D</th>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Staurosporine</th>\n",
       "      <td>0.14</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fluazinam</th>\n",
       "      <td>3.70</td>\n",
       "      <td>13.53</td>\n",
       "      <td>1.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5,8,11-Eicosatriynoic acid</th>\n",
       "      <td>3.70</td>\n",
       "      <td>17.96</td>\n",
       "      <td>1.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lys05</th>\n",
       "      <td>5.00</td>\n",
       "      <td>12.15</td>\n",
       "      <td>0.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Calcipotriol (hydrate)</th>\n",
       "      <td>11.11</td>\n",
       "      <td>13.34</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FCCP</th>\n",
       "      <td>11.11</td>\n",
       "      <td>26.52</td>\n",
       "      <td>0.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Berberine chloride</th>\n",
       "      <td>25.00</td>\n",
       "      <td>45.35</td>\n",
       "      <td>0.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IOPANOIC ACID</th>\n",
       "      <td>33.33</td>\n",
       "      <td>82.39</td>\n",
       "      <td>0.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cycloheximide</th>\n",
       "      <td>33.33</td>\n",
       "      <td>108.08</td>\n",
       "      <td>1.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cucurbitacin I</th>\n",
       "      <td>33.33</td>\n",
       "      <td>3.84</td>\n",
       "      <td>-1.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Amperozide</th>\n",
       "      <td>33.33</td>\n",
       "      <td>48.44</td>\n",
       "      <td>0.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CLIOQUINOL</th>\n",
       "      <td>33.33</td>\n",
       "      <td>31.23</td>\n",
       "      <td>-0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ethoxyquin</th>\n",
       "      <td>33.33</td>\n",
       "      <td>58.23</td>\n",
       "      <td>0.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aminodarone Hydrochloride</th>\n",
       "      <td>37.50</td>\n",
       "      <td>23.53</td>\n",
       "      <td>-0.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Treprostinil</th>\n",
       "      <td>100.00</td>\n",
       "      <td>36.93</td>\n",
       "      <td>-0.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colistin Methanesulfonate (sodium salt)</th>\n",
       "      <td>100.00</td>\n",
       "      <td>139.49</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bevirimat</th>\n",
       "      <td>100.00</td>\n",
       "      <td>129.33</td>\n",
       "      <td>0.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5,6-benzoflavone</th>\n",
       "      <td>100.00</td>\n",
       "      <td>48.05</td>\n",
       "      <td>-0.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rifampicin</th>\n",
       "      <td>300.00</td>\n",
       "      <td>265.41</td>\n",
       "      <td>-0.11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         window_onset  feature_bmd_5th  \\\n",
       "group                                                                    \n",
       "Actinomycin D                                    0.02             0.02   \n",
       "Staurosporine                                    0.14             0.37   \n",
       "Fluazinam                                        3.70            13.53   \n",
       "5,8,11-Eicosatriynoic acid                       3.70            17.96   \n",
       "Lys05                                            5.00            12.15   \n",
       "Calcipotriol (hydrate)                          11.11            13.34   \n",
       "FCCP                                            11.11            26.52   \n",
       "Berberine chloride                              25.00            45.35   \n",
       "IOPANOIC ACID                                   33.33            82.39   \n",
       "Cycloheximide                                   33.33           108.08   \n",
       "Cucurbitacin I                                  33.33             3.84   \n",
       "Amperozide                                      33.33            48.44   \n",
       "CLIOQUINOL                                      33.33            31.23   \n",
       "Ethoxyquin                                      33.33            58.23   \n",
       "Aminodarone Hydrochloride                       37.50            23.53   \n",
       "Treprostinil                                   100.00            36.93   \n",
       "Colistin Methanesulfonate (sodium salt)        100.00           139.49   \n",
       "Bevirimat                                      100.00           129.33   \n",
       "5,6-benzoflavone                               100.00            48.05   \n",
       "Rifampicin                                     300.00           265.41   \n",
       "\n",
       "                                         steps_apart  \n",
       "group                                                 \n",
       "Actinomycin D                                   0.00  \n",
       "Staurosporine                                   0.89  \n",
       "Fluazinam                                       1.18  \n",
       "5,8,11-Eicosatriynoic acid                      1.44  \n",
       "Lys05                                           0.81  \n",
       "Calcipotriol (hydrate)                          0.17  \n",
       "FCCP                                            0.79  \n",
       "Berberine chloride                              0.54  \n",
       "IOPANOIC ACID                                   0.82  \n",
       "Cycloheximide                                   1.07  \n",
       "Cucurbitacin I                                 -1.97  \n",
       "Amperozide                                      0.34  \n",
       "CLIOQUINOL                                     -0.06  \n",
       "Ethoxyquin                                      0.51  \n",
       "Aminodarone Hydrochloride                      -0.42  \n",
       "Treprostinil                                   -0.91  \n",
       "Colistin Methanesulfonate (sodium salt)         0.30  \n",
       "Bevirimat                                       0.23  \n",
       "5,6-benzoflavone                               -0.67  \n",
       "Rifampicin                                     -0.11  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "onset = direction[direction[\"phase\"] == \"responding\"].groupby(\"group\")[\"dose\"].min()\n",
    "crossings = features.dropna(subset=[\"bmd\"]).groupby(\"group\")[\"bmd\"].quantile(0.05)\n",
    "departure = pd.DataFrame({\"window_onset\": onset, \"feature_bmd_5th\": crossings}).dropna()\n",
    "# How far apart the two answers are, counted in steps of the three-fold ladder that was dosed.\n",
    "departure[\"steps_apart\"] = np.log10(departure[\"feature_bmd_5th\"] / departure[\"window_onset\"]) / np.log10(3.0)\n",
    "\n",
    "print(\n",
    "    f\"{len(departure)} compounds with both | rank correlation \"\n",
    "    f\"{departure['window_onset'].corr(departure['feature_bmd_5th'], method='spearman'):.2f} | \"\n",
    "    f\"{int((departure['steps_apart'].abs() <= 1).sum())} within one step\"\n",
    ")\n",
    "departure.sort_values(\"window_onset\").round(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c034",
   "metadata": {},
   "source": [
    "They agree: the two rank together at 0.79, and sixteen of twenty compounds land within one three-fold step of\n",
    "each other, which is all the resolution this ladder has.\n",
    "\n",
    "Cucurbitacin I is the largest exception and the informative one. Its early feature crossings, the 5th percentile\n",
    "of its benchmark doses, sit two steps below the\n",
    "concentration at which the profile as a whole starts to reproduce. A few early features passing a\n",
    "three-MAD line is a weaker claim than a whole direction holding across replicate plates, and where the two\n",
    "disagree the aggregate is the one to believe. Read the per-feature points of departure as the order in which\n",
    "things engage, and the window onset as where the compound engages."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c035",
   "metadata": {},
   "source": [
    "The phase is on `obs`, so the window is an ordinary subset and the rest of the package applies to it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c036",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:21.039382Z",
     "iopub.status.busy": "2026-10-21T01:01:21.039241Z",
     "iopub.status.idle": "2026-10-21T01:01:21.104890Z",
     "shell.execute_reply": "2026-10-21T01:01:21.103585Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "592 of 2831 wells are inside some compound's responding window\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "group\n",
       "Staurosporine                 30\n",
       "FCCP                          27\n",
       "Fluazinam                     26\n",
       "Calcipotriol (hydrate)        24\n",
       "5,8,11-Eicosatriynoic acid    21\n",
       "CLIOQUINOL                    17\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The controls are in no phase, so they have to be kept deliberately: every statistic here is read against them.\n",
    "responding = heparg.obs[\"dose_direction_phase\"] == \"responding\"\n",
    "window = heparg[responding | heparg.obs[\"Metadata_Control\"].to_numpy(dtype=bool)].copy()\n",
    "print(f\"{int(responding.sum())} of {heparg.n_obs} wells are inside some compound's responding window\")\n",
    "\n",
    "# Two doses is enough here: the question is which features move inside the window, not where they cross.\n",
    "mt.tl.dose_features(window, min_doses=2)\n",
    "inside = window.uns[\"mantispy\"][\"dose_features\"].dropna(subset=[\"bmd\"])\n",
    "inside.groupby(\"group\").size().sort_values(ascending=False).head(6)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c037",
   "metadata": {},
   "source": [
    "## Comparing compounds on what they do, not on when they do it\n",
    "\n",
    "Two compounds compared at the same concentration are usually compared at different points of their own ranges:\n",
    "at 11 uM amperozide has not started and staurosporine started two decades earlier. Comparing them at their\n",
    "strongest concentration instead throws away everything on the way there, which for a compound whose phenotype\n",
    "turns along its window is most of what it did.\n",
    "\n",
    "{func}`~mantispy.tl.dose_trajectory` reads each compound's window onto the same relative axis: position 0 is\n",
    "where it starts responding, position 1 is the top of its window, and the profile is interpolated in log\n",
    "concentration between them. The result is an ordinary object of compounds by features-and-positions, so\n",
    "{func}`~mantispy.tl.similarity` and anything else works on it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c038",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:21.108807Z",
     "iopub.status.busy": "2026-10-21T01:01:21.108672Z",
     "iopub.status.idle": "2026-10-21T01:01:21.138552Z",
     "shell.execute_reply": "2026-10-21T01:01:21.137187Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20 compounds with a window of two or more concentrations, 297 columns (99 features x 3 positions)\n",
      "Actinomycin D    -> Cycloheximide +0.46, Calcipotriol (hydrate) +0.33, FCCP +0.25\n",
      "Staurosporine    -> Fluazinam +0.46, Calcipotriol (hydrate) +0.43, Triamcinolone acetonide +0.34\n",
      "Fluazinam        -> CLIOQUINOL +0.61, Amperozide +0.56, 5,8,11-Eicosatriynoic acid +0.47\n"
     ]
    }
   ],
   "source": [
    "paths = mt.tl.dose_trajectory(heparg, n_positions=3)\n",
    "mt.tl.similarity(paths, metric=\"pearson\")\n",
    "\n",
    "compounds = list(paths.obs[\"Metadata_Compound\"])\n",
    "similarity = pd.DataFrame(np.asarray(paths.obsp[\"similarity\"]), index=compounds, columns=compounds)\n",
    "print(\n",
    "    f\"{paths.n_obs} compounds with a window of two or more concentrations, \"\n",
    "    f\"{paths.n_vars} columns ({paths.var['feature'].nunique()} features x 3 positions)\"\n",
    ")\n",
    "for name in [\"Actinomycin D\", \"Staurosporine\", \"Fluazinam\"]:\n",
    "    neighbours = similarity.loc[name].drop(name).sort_values(ascending=False).head(3)\n",
    "    print(f\"{name:16s} -> \" + \", \".join(f\"{other} {value:+.2f}\" for other, value in neighbours.items()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c039",
   "metadata": {},
   "source": [
    "Actinomycin D's nearest neighbour is cycloheximide. One blocks transcription and the other translation, and their\n",
    "profiles are the most similar pair for actinomycin D (+0.46). Nothing in the input encodes that, and their windows start three decades apart.\n",
    "\n",
    "The window also tells you what to run next. A range-finding ladder buys the location of the window; the way to\n",
    "resolve it is a second ladder spaced across the concentrations this one marked `responding`, not another four\n",
    "decades at the same spacing."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c040",
   "metadata": {},
   "source": [
    "## Distance is not the same as phenotype\n",
    "\n",
    "A compound that kills cells also moves away from the controls, and the curve cannot tell the two apart.\n",
    "{func}`~mantispy.tl.cytotoxicity` compares each group's cells per field against the controls', so the calls can\n",
    "be read beside it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c041",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:21.142055Z",
     "iopub.status.busy": "2026-10-21T01:01:21.141920Z",
     "iopub.status.idle": "2026-10-21T01:01:21.230357Z",
     "shell.execute_reply": "2026-10-21T01:01:21.229002Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script>\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        </script>\n",
       "        <script type=\"module\">import \"https://cdn.plot.ly/plotly-4.1.1.min\"</script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"height:525px; width:100%;\">            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/3.2.2/es5/tex-svg.min.js\"></script><script>if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script>window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
       "        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-4.1.1.min.js\" integrity=\"sha256-O24V1F27f8pb0glCkelh3cVHLNiHAJ5gCaVtq2aNch8=\" crossorigin=\"anonymous\"></script>                <div id=\"d531633f-b259-4026-8534-4b0355f47989\" class=\"plotly-graph-div\" style=\"height:100%; width:100%;\"></div>            <script>                window.PLOTLYENV=window.PLOTLYENV || {};                                if (document.getElementById(\"d531633f-b259-4026-8534-4b0355f47989\")) {                    Plotly.newPlot(                        \"d531633f-b259-4026-8534-4b0355f47989\",                        [{\"customdata\":[[\"5,6-benzoflavone@0.0152\"],[\"5,6-benzoflavone@0.0457\"],[\"5,6-benzoflavone@0.13717421\"],[\"5,6-benzoflavone@0.411522631\"],[\"5,6-benzoflavone@1.234567904\"],[\"5,6-benzoflavone@100.0\"],[\"5,6-benzoflavone@11.11111112\"],[\"5,6-benzoflavone@3.703703701\"],[\"5,6-benzoflavone@300.0\"],[\"5,6-benzoflavone@33.33333333\"],[\"5,8,11-Eicosatriynoic acid@0.0152\"],[\"5,8,11-Eicosatriynoic acid@0.0457\"],[\"5,8,11-Eicosatriynoic acid@0.137174212\"],[\"5,8,11-Eicosatriynoic acid@0.411522637\"],[\"5,8,11-Eicosatriynoic acid@1.234567902\"],[\"5,8,11-Eicosatriynoic acid@11.11111111\"],[\"5,8,11-Eicosatriynoic acid@3.703703706\"],[\"5,8,11-Eicosatriynoic acid@300.0\"],[\"5,8,11-Eicosatriynoic acid@33.33333333\"],[\"5,8,11-Eicosatriynoic acid@99.99999997\"],[\"AMG 900@5.1\"],[\"Actinomycin D@0.0152\"],[\"Actinomycin D@0.0457\"],[\"Actinomycin D@3.703703704\"],[\"Aloxistatin@5.1\"],[\"Aminodarone Hydrochloride@0.00191\"],[\"Aminodarone Hydrochloride@0.00572\"],[\"Aminodarone Hydrochloride@0.0171\"],[\"Aminodarone Hydrochloride@0.0514\"],[\"Aminodarone Hydrochloride@0.154320986\"],[\"Aminodarone Hydrochloride@0.462962964\"],[\"Aminodarone Hydrochloride@1.388888888\"],[\"Aminodarone Hydrochloride@12.5\"],[\"Aminodarone Hydrochloride@37.5\"],[\"Aminodarone Hydrochloride@4.166666668\"],[\"Amperozide@0.0152\"],[\"Amperozide@0.0457\"],[\"Amperozide@0.13717421\"],[\"Amperozide@0.411522634\"],[\"Amperozide@1.234567901\"],[\"Amperozide@100.0\"],[\"Amperozide@11.11111111\"],[\"Amperozide@3.703703704\"],[\"Amperozide@300.0\"],[\"Amperozide@33.33333333\"],[\"Berberine chloride@0.00381\"],[\"Berberine chloride@0.0114\"],[\"Berberine chloride@0.0343\"],[\"Berberine chloride@0.102880656\"],[\"Berberine chloride@0.308641975\"],[\"Berberine chloride@0.925925924\"],[\"Berberine chloride@2.77777778\"],[\"Berberine chloride@25.0\"],[\"Berberine chloride@75.0\"],[\"Berberine chloride@8.333333332\"],[\"Bevirimat@0.0152\"],[\"Bevirimat@0.0457\"],[\"Bevirimat@0.137174212\"],[\"Bevirimat@0.411522632\"],[\"Bevirimat@1.234567901\"],[\"Bevirimat@100.0\"],[\"Bevirimat@11.11111111\"],[\"Bevirimat@3.703703703\"],[\"Bevirimat@300.0\"],[\"Bevirimat@33.33333333\"],[\"CLIOQUINOL@0.0152\"],[\"CLIOQUINOL@0.0457\"],[\"CLIOQUINOL@0.137174209\"],[\"CLIOQUINOL@0.411522638\"],[\"CLIOQUINOL@1.234567905\"],[\"CLIOQUINOL@11.11111111\"],[\"CLIOQUINOL@3.703703705\"],[\"CLIOQUINOL@300.0\"],[\"CLIOQUINOL@33.33333333\"],[\"CLIOQUINOL@99.99999997\"],[\"Calcipotriol (hydrate)@0.0152\"],[\"Calcipotriol (hydrate)@0.0457\"],[\"Calcipotriol (hydrate)@0.137174213\"],[\"Calcipotriol (hydrate)@0.411522631\"],[\"Calcipotriol (hydrate)@1.2345679\"],[\"Calcipotriol (hydrate)@100.0\"],[\"Calcipotriol (hydrate)@11.11111111\"],[\"Calcipotriol (hydrate)@3.703703706\"],[\"Calcipotriol (hydrate)@300.0\"],[\"Calcipotriol (hydrate)@33.33333334\"],[\"Cladribine@0.0152\"],[\"Cladribine@0.0457\"],[\"Cladribine@0.13717421\"],[\"Cladribine@0.411522629\"],[\"Cladribine@1.234567899\"],[\"Cladribine@100.0\"],[\"Cladribine@11.11111111\"],[\"Cladribine@3.703703707\"],[\"Cladribine@300.0\"],[\"Cladribine@33.33333333\"],[\"Colistin Methanesulfonate (sodium salt)@0.0152\"],[\"Colistin Methanesulfonate (sodium salt)@0.0457\"],[\"Colistin Methanesulfonate (sodium salt)@0.137174211\"],[\"Colistin Methanesulfonate (sodium salt)@0.411522634\"],[\"Colistin Methanesulfonate (sodium salt)@1.234567901\"],[\"Colistin Methanesulfonate (sodium salt)@100.0\"],[\"Colistin Methanesulfonate (sodium salt)@11.11111111\"],[\"Colistin Methanesulfonate (sodium salt)@3.703703704\"],[\"Colistin Methanesulfonate (sodium salt)@300.0\"],[\"Colistin Methanesulfonate (sodium salt)@33.33333333\"],[\"Cucurbitacin I@0.0152\"],[\"Cucurbitacin I@0.0457\"],[\"Cucurbitacin I@0.137174209\"],[\"Cucurbitacin I@0.411522631\"],[\"Cucurbitacin I@1.2345679\"],[\"Cucurbitacin I@11.11111111\"],[\"Cucurbitacin I@3.703703701\"],[\"Cucurbitacin I@300.0\"],[\"Cucurbitacin I@33.33333333\"],[\"Cycloheximide@0.0152\"],[\"Cycloheximide@0.0457\"],[\"Cycloheximide@0.137174213\"],[\"Cycloheximide@0.411522635\"],[\"Cycloheximide@1.234567901\"],[\"Cycloheximide@100.0\"],[\"Cycloheximide@11.11111111\"],[\"Cycloheximide@3.703703704\"],[\"Cycloheximide@300.0\"],[\"Cycloheximide@33.33333333\"],[\"DMSO\"],[\"Dexamethasone (DHAP)@5.1\"],[\"Ethoxyquin@0.0152\"],[\"Ethoxyquin@0.0457\"],[\"Ethoxyquin@0.13717421\"],[\"Ethoxyquin@0.411522631\"],[\"Ethoxyquin@1.234567907\"],[\"Ethoxyquin@100.0\"],[\"Ethoxyquin@11.11111111\"],[\"Ethoxyquin@3.703703707\"],[\"Ethoxyquin@33.33333334\"],[\"FCCP@0.0152\"],[\"FCCP@0.0457\"],[\"FCCP@0.137174213\"],[\"FCCP@0.411522638\"],[\"FCCP@1.234567903\"],[\"FCCP@100.0\"],[\"FCCP@11.11111111\"],[\"FCCP@3.703703709\"],[\"FCCP@33.33333333\"],[\"FK-866@5.1\"],[\"Fluazinam@0.0152\"],[\"Fluazinam@0.0457\"],[\"Fluazinam@0.137174211\"],[\"Fluazinam@0.411522634\"],[\"Fluazinam@1.234567903\"],[\"Fluazinam@100.0\"],[\"Fluazinam@11.11111111\"],[\"Fluazinam@3.703703703\"],[\"Fluazinam@300.0\"],[\"Fluazinam@33.33333334\"],[\"IOPANOIC ACID@0.0152\"],[\"IOPANOIC ACID@0.0457\"],[\"IOPANOIC ACID@0.137174212\"],[\"IOPANOIC ACID@0.411522632\"],[\"IOPANOIC ACID@1.234567902\"],[\"IOPANOIC ACID@100.0\"],[\"IOPANOIC ACID@11.11111111\"],[\"IOPANOIC ACID@3.703703705\"],[\"IOPANOIC ACID@300.0\"],[\"IOPANOIC ACID@33.33333333\"],[\"Imiquimod@0.000762\"],[\"Imiquimod@0.00229\"],[\"Imiquimod@0.00686\"],[\"Imiquimod@0.0206\"],[\"Imiquimod@0.0617\"],[\"Imiquimod@0.18518519\"],[\"Imiquimod@0.555555557\"],[\"Imiquimod@1.666666672\"],[\"Imiquimod@15.0\"],[\"Imiquimod@5.000000004\"],[\"LY2109761@5.1\"],[\"Lys05@0.000762\"],[\"Lys05@0.00229\"],[\"Lys05@0.00686\"],[\"Lys05@0.0206\"],[\"Lys05@0.0617\"],[\"Lys05@0.185185184\"],[\"Lys05@0.555555558\"],[\"Lys05@1.666666668\"],[\"Lys05@15.0\"],[\"Lys05@5.0\"],[\"MILTEFOSINE@0.0\"],[\"MILTEFOSINE@0.000381\"],[\"MILTEFOSINE@0.00114\"],[\"MILTEFOSINE@0.00343\"],[\"MILTEFOSINE@0.0103\"],[\"MILTEFOSINE@0.0309\"],[\"MILTEFOSINE@0.0926\"],[\"MILTEFOSINE@0.277777776\"],[\"MILTEFOSINE@0.833333335\"],[\"MILTEFOSINE@2.499999998\"],[\"MILTEFOSINE@7.5\"],[\"MUPIROCIN@0.0152\"],[\"MUPIROCIN@0.0457\"],[\"MUPIROCIN@0.137174209\"],[\"MUPIROCIN@0.411522633\"],[\"MUPIROCIN@1.234567904\"],[\"MUPIROCIN@11.11111111\"],[\"MUPIROCIN@3.703703705\"],[\"MUPIROCIN@300.0\"],[\"MUPIROCIN@33.33333333\"],[\"MUPIROCIN@99.99999998\"],[\"NVS-PAK1-1@5.1\"],[\"Natamycin@0.0\"],[\"Natamycin@0.000381\"],[\"Natamycin@0.00114\"],[\"Natamycin@0.00343\"],[\"Natamycin@0.0103\"],[\"Natamycin@0.0309\"],[\"Natamycin@0.0926\"],[\"Natamycin@0.277777776\"],[\"Natamycin@0.833333332\"],[\"Natamycin@2.5\"],[\"Natamycin@7.5\"],[\"Nedocromil (sodium salt)@0.00381\"],[\"Nedocromil (sodium salt)@0.0114\"],[\"Nedocromil (sodium salt)@0.0343\"],[\"Nedocromil (sodium salt)@0.10288066\"],[\"Nedocromil (sodium salt)@0.308641974\"],[\"Nedocromil (sodium salt)@0.925925929\"],[\"Nedocromil (sodium salt)@2.77777778\"],[\"Nedocromil (sodium salt)@25.0\"],[\"Nedocromil (sodium salt)@75.0\"],[\"Nedocromil (sodium salt)@8.333333333\"],[\"PEMIROLAST POTASSIUM@0.00381\"],[\"PEMIROLAST POTASSIUM@0.0114\"],[\"PEMIROLAST POTASSIUM@0.0343\"],[\"PEMIROLAST POTASSIUM@0.102880654\"],[\"PEMIROLAST POTASSIUM@0.308641974\"],[\"PEMIROLAST POTASSIUM@0.925925921\"],[\"PEMIROLAST POTASSIUM@2.777777774\"],[\"PEMIROLAST POTASSIUM@25.0\"],[\"PEMIROLAST POTASSIUM@75.0\"],[\"PEMIROLAST POTASSIUM@8.333333332\"],[\"Quinidine@5.1\"],[\"Rifampicin@0.0152\"],[\"Rifampicin@0.0457\"],[\"Rifampicin@0.137174213\"],[\"Rifampicin@0.411522635\"],[\"Rifampicin@1.234567901\"],[\"Rifampicin@100.0\"],[\"Rifampicin@11.11111111\"],[\"Rifampicin@3.703703704\"],[\"Rifampicin@300.0\"],[\"Rifampicin@33.33333333\"],[\"Staurosporine@0.0152\"],[\"Staurosporine@0.0457\"],[\"Staurosporine@0.137174214\"],[\"Staurosporine@0.411522636\"],[\"Staurosporine@1.234567901\"],[\"Staurosporine@11.11111111\"],[\"Staurosporine@3.703703702\"],[\"Staurosporine@300.0\"],[\"Staurosporine@33.33333333\"],[\"TC-S 7004@5.1\"],[\"Treprostinil@0.0152\"],[\"Treprostinil@0.0457\"],[\"Treprostinil@0.137174209\"],[\"Treprostinil@0.411522634\"],[\"Treprostinil@1.234567902\"],[\"Treprostinil@11.11111111\"],[\"Treprostinil@3.703703705\"],[\"Treprostinil@300.0\"],[\"Treprostinil@33.33333333\"],[\"Treprostinil@99.99999997\"],[\"Triamcinolone acetonide@0.0152\"],[\"Triamcinolone acetonide@0.0457\"],[\"Triamcinolone acetonide@0.13717421\"],[\"Triamcinolone acetonide@0.41152263\"],[\"Triamcinolone acetonide@1.234567898\"],[\"Triamcinolone acetonide@100.0\"],[\"Triamcinolone acetonide@11.11111111\"],[\"Triamcinolone acetonide@3.703703701\"],[\"Triamcinolone acetonide@300.0\"],[\"Triamcinolone acetonide@33.33333333\"],[\"UNTREATED@0.0\"]],\"hovertemplate\":\"status=ok\\u003cbr\\u003eviability, relative to the controls=%{x}\\u003cbr\\u003edistance from the controls=%{y}\\u003cbr\\u003egroup=%{customdata[0]}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"ok\",\"marker\":{\"color\":\"#636efa\",\"symbol\":\"circle\"},\"mode\":\"markers\",\"name\":\"ok\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"1V5MurLn7z\\u002f41GZRntvuP4JVr4xIJe8\\u002fq7WTkDxY7j\\u002f8wviaavzsP3q2HTSkM\\u002fA\\u002fj94KUvVV7j8mIXmwfD7tP\\u002ffOxVtXVew\\u002f7ADTd41d7j\\u002fE2bjRyZjuP3Q6q3uXO+s\\u002fj1oI4GCa7T+semVEKvnvP9EwHSb+WfA\\u002fqnTETuNy7T+fnsyG8APuPx5fyLdAU+w\\u002fGBZ\\u002fZx1D7D\\u002f2qnTETuPyPwOrXhmRSu4\\u002fnJTuiUTo5z\\u002fPmQXcI5PoPwPeh4F6Mus\\u002fefFLgLaS7j+tcPxxH5HvP\\u002fPqnOSVnO4\\u002fLBNIAa707j\\u002f53Gs1x1LwP4JFpcT2Nuw\\u002f3Hs\\u002fj6QO7T9UfZXXrI\\u002fuP9eXFhjjVe8\\u002f4+enf18Y7z9SCs8k2zrwP+pFapaqJO0\\u002flsjUvv2U7j9ieulGnI3rPzK0PUg01+w\\u002fGgwWlRLb6z+XNMiEF+vqP4BXE3sqFu4\\u002fuAPBCdcp7z9fud9vcs7nP\\u002fH0BbegBO8\\u002fhgavmyD27z++rLs0hoPuP1h5zfrorfA\\u002fSqedD7og7z9CvdOiseHuP\\u002fgXmoHZse4\\u002fuQvG7f+g8D9UvmQZBnXvP3Y+6IL80O4\\u002f28wYmU\\u002fi8D+myWU1UijvP\\u002fvC+Jpq\\u002fOw\\u002f0eYWCQuF7j9XrPZi0pXtP\\u002foNMa\\u002fOSe4\\u002f3InlaBQM8T8I0FbSq+jsP\\u002fNelY7Yaew\\u002fjTFISoIa8T93f7fEVbbvPyxWezHpyu4\\u002f2kp6FZ0X7z+RUJ8NVjLtP7jC8cd9RO4\\u002flUzXMJJQ7z9k\\u002fIfKTljtP+g\\u002fyaBjnuo\\u002fJba34dNg8D+UVNwUu8fwP+Lnp39fGO8\\u002f+ErD6cKZ6z\\u002fHEB9BGBbvP8eUIbOs0e8\\u002fq7WTkDxY7j9QBWAmBS3tP6LPkQD4+us\\u002fILOs0d9D7D\\u002f4DTGvzknuP34uU+VLlvE\\u002fOhihVMZp7T+HMdMf4WbrP2jgsEEQEes\\u002fIDevQ3T\\u002f7D9eEr5dRhntP37dedugwu0\\u002fDvVOi8aG6z\\u002f\\u002f8VkmkALsPzSq1HUpb+w\\u002flLSN70YR6D\\u002fklGqH0lPsP+83Oefb2u4\\u002fZMFZfjz57j9ab2Qo3kXwP9TUqFLXpew\\u002fWqguhg607z+s5lgKRE\\u002fsP4GI2PQxDew\\u002fqgDMpKCl7z8VupVpVdvyP+61mmMpEO0\\u002fKFpDDq2s7D9op+bj36LrPwaR63409Oo\\u002fuO95OiCm6D\\u002fMq3OSV3LqPzoEWoUP5uY\\u002fRGz6mAYO6z+y\\u002farp7u\\u002fmP8yrc5JXcuo\\u002fIzweQkoN8D\\u002fU1KhS16XsP2\\u002fKeq4YUOs\\u002fGU9JxU2x6z\\u002fwGYlFGu\\u002fnP7xnr+vHCOo\\u002fqLFWidfC6j8V3xj4zsXrPxxLgeiJz+0\\u002ftBHyuKVz7T\\u002f\\u002f\\u002f\\u002f\\u002f\\u002f\\u002f\\u002f\\u002fvPwJylLtg3O4\\u002f10Y9DjiC6z+QF9WvJcTtPwExxXkH9+0\\u002f7rs7WXCW7z+0nMcX8i3wPy5\\u002fO8fHSus\\u002f2BGwt2yp7z826T\\u002fJoGPuPzK8QixdTu4\\u002fVIRoxGSO8D9BQzoDKI7uP55lAinAle4\\u002f2v9BATnK7T\\u002fcQBFDkq\\u002fuP0QrK1etKOo\\u002fZiVIYC3Y6T+inGiYDhPvPxB37Q55Ue0\\u002f+lc3zMEe8D9UPMaVU6rtPxwQU5x3cO8\\u002fmXMz2I7f7D8OeVH9WkLsP7n7uyWusu0\\u002fPgTPr7CZ7D\\u002fe7dNKBevrP850gk2qqO8\\u002fAP\\u002fNCI+H8D9YnOyagKfqP2WGKzIqmvA\\u002fcFwj+hwJ8D\\u002fo0XHsZ1fvP+LhBooYkuw\\u002f+wvNwOxY7z8UrO+P5d3uPyZkrOC3FO0\\u002f50kyc24G6z\\u002fIBrZuDa7uPx4G6slsCO8\\u002fQY1AIBtj8D\\u002fOr7CZvAfuP8DlhZK28e0\\u002fNvFErcna7z9q3kxTLiDsP86vsJm8B+4\\u002fWOXAwAIE7T8aDBaVEtvrPy4J3y6jjO4\\u002fQI1AIBtj8D9qqyPrRDjvPzrdcgi0Cu8\\u002fTKU5Idgv8D+DlUzXMJLwP5zraIk2Qu4\\u002fM3kP\\u002fCF47j8wg3jOLODuP8RVtl813e0\\u002fBGgr6VV07j9A0aVHx7HvPxACw23FC\\u002fA\\u002f3DgMX2k47T\\u002fMNRf6MrTtP8YYJCVBjfA\\u002fnC6cuXEY7j+iUTCEqsXtPywTSAGu9O4\\u002fV7T7RvsM7z+Cyac2i\\u002fLsP\\u002fZazbEUiO4\\u002fRmqWqiQd7D8V1xMUpk7qP8FvKfqRM\\u002fE\\u002ffiZOASMf8D8gw7aZMTLvP12WwM\\u002fa1O0\\u002fMXtz6gNp7T8ITrhO+R3rPxTnHdz3PO0\\u002fs0wgBbjS6z9Oi8aGe9nsP\\u002fBwA0UMSe4\\u002f7ErZlIAy8D\\u002fnbYMKd3j0Px5HuQvG7e8\\u002fO6N2sxIk8D\\u002f0n2TQMU\\u002ftP26XUUYvaO4\\u002ftCDKiYbp8D8bGrxugtjvP8aOgL1lS+0\\u002fBh3z1PEm7T9dFCJMKArsPzgiCifR0e0\\u002fmnnUzdVl7z+KJQZf9A3sPzhdOHPjMOw\\u002fJ9CfptFq6T8MiVvFrDDvP07O+ba2r+w\\u002faWpUqetS7j\\u002fxcANFDEnuP3qmE2xSRe0\\u002f6JCiqg5y7j8+0wk2qaLuP4GQ3dhahO0\\u002fXhK+XUYZ7T+uqyq+MfDtP47eClL1Ve4\\u002fuAPBCdcp7z8Y00s34mzsP8JReVjQR+o\\u002fGuHxEFJq8D++7+5kwVnuP26fVipY3+8\\u002fYABQpxI66z9wTBkyyxrtP7MLUcNe7eo\\u002fNLLZWVLm7T8y32HM9EfoPyRsscTgi+4\\u002frqMl2gh57D\\u002fiKtuvmu7uP3pdP0bQ6Oo\\u002fghJ8XA1P7z9s3OhkTC\\u002ftP2in5uPfous\\u002f4Gdt6o4+7D8m4KluI1nsP5a4yvarpus\\u002fwgCgTiV05j\\u002fEBN1VignqP4fDe2vlH\\u002fA\\u002fWFsdWSfC6T91\\u002fRhBo+vtP8rKVSuK1vA\\u002fuH++l0Ju7j\\u002fuOZ3VvcvtP4ofZWmth+k\\u002f+JOXD0X27T9J4stbzH\\u002ftP83y48n33e0\\u002fAHUqobNF6T+4RvQ5EgDvP17XjxE0uu4\\u002fo5L\\u002fxQOr7j\\u002fC4yGk1ADvPyjeRYBBaO0\\u002fvH1aqWB97z\\u002fePXtdP0bwP8LNduY7jOk\\u002fAnKUu2Dc7j8eSR36p97uP3VO8kpOv\\u002fE\\u002fhr3adZ6Z7T9KbaG6GDrwPw==\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"\\u002fNd7L5VpFUBYXZST0VUUQMYTLWiCgRRADS9FYlFzFEA6l2aYdwoTQHqGkspmbDNA3HDY91efGEBSzec6lToSQJgUPbaZly1AhtpZ19AzF0A0kPx+pWUcQOlW8p0owBhAG42TQ0shFEBaY7RhfyQUQFrUEjWGHRZAmnwh5DDPGECtQFRGaBUZQONNfgZpwDxAQ1pDZhVrJUCBxdtEKqYnQPQMobUtKhhAeIN8tUEMI0AGUT7s8JYfQH+AtgggnCJA3BEAcRVlGUAsXFGT46USQLBpdIFRyxBAgsmoyiIyFkCWnV10p8EWQHpUeJvqrRpA8dXzJ\\u002fB\\u002fFUCv\\u002fuHUZ7QRQGKzvnvwnhVAH\\u002f8BecQ0LECwGoegpbQSQIjm8Ne6mRNAjv20v9fgFUCe9wCbpqMWQImaOtuXhQ9A2dZsYMuuEEAR83Ng+fcrQJ4N1mMwDhJAcN9l5RN+EkCh5ponRXsqQHUZPoGRaRpAzAVU2HMDFUDAz4MKLzASQJp9dnAHchBAZKxZlbbAFUB3NH+o86ETQFO6tdyEhRVAbtTIVLX2DkC8nzrl1sQWQDKzuRKcxyFAVpFF5kpiFEAI6kljJuYOQMw8kiygLRRA6aJTllkqFEAyq\\u002fejqnITQE2YuhU82RRAAO61KlFNHUBGEsRMuvMbQCK0264DXhtAqIX25kKUMEAmWRUXUXgVQHHN6NfYFhJAlSK3XLhUFUCizGgxAq8RQA\\u002f7\\u002f5\\u002fZXxVAsuxz153uEUAL132BW7MbQKCjV1Z3phZAgZTqCPE7LkA2QILrEIkiQATF\\u002fzNVISpAGAKbc8YYGkAorsdhZ8IVQIKVyXrYMBZABKmfsHwlFEBgbstl3gEWQG5JROpECCZA5kk7QPvGG0B8AhqpX58TQLTafK1DMylAvsqk0fjhIUA4mU+v5MsWQBjHy\\u002fPr6RdAWMp18pDRE0DCNNSZYG0VQPnWsoDBmRpA5v3ISosUFEDgpL19ojQXQDCax52\\u002fRxhA5A079AfVHUCq5YSn9sAYQBK6qKRnygxAhv8Igm0+F0BynHwzQu0UQPwzOlDc2BdA7DE9DHWJE0CXfiqexUUZQGD\\u002fRRn\\u002fnRZASIOSb9DfG0Ak53MacV4sQGy\\u002fjBhJMBRA7MMEymd6FUCEehL1o10bQJwTkM2z\\u002fBxAmbRUaBC9HUDE9QqP\\u002ftobQJ6Qc73IxCZAVteMrrcbI0CY01rhVPcuQE9w\\u002f83Z7iVAH1wJuawaEUCS3CGHnLYWQDRWWhu1kRVAzA2ZED0JGkB6AKDEoBgaQP4E\\u002f8q3tRtA8Rdvz1nHIkDmwJ0rKGgeQIsUsmUr1CVAmTyOrZfSGUBUAEmrDk4QQDac6fhuKBlAAMXpgNV2GEDWIujaLFQVQPAMgm++HhRAIhbZS62lE0Auc\\u002f6OGLkTQEcT4CGtailA99AAB2IdFEC2dnZzkEsYQGrgm7ufBRtA2gxfvXusEUAmbYI8THEXQAVUTerNAhJAY+SJbhl5E0A+GHtRcxcSQKwqGq7JUSZAttYMHz0QHUACq8vo2w8RQHyyn4+87iNAAm3DLfgHGECzCz9dtFQSQJQI1LvUyhJA1goaLLrSEEC004B7NYcUQLPGH4IorRRAjE1dKBAZMkAUQMMTgpgeQET53I0DSRRAZZsAeklDLUDW\\u002fbCW1yMiQASJB378JxVAhHsASM2eEEAixJ7bKT4SQEz\\u002f+6lDRRpA8veis1ZfEkA3KLnRxCAiQIbUFVvEjhRAkMPqmzTwEUBcyVvClVQkQH5RrpoffRhAeCTHHdmOFUAft25n+oYRQGh0ASD0JRJADr05pvsCEEDeDqCFKx8WQEr+rw6b9BVAH1Qv75iXE0C0gaJ9oTYaQB6fLqAJ6BFA7DXWP6k1FEA66fEYqmUWQKAQhKk16hRAUWJFoJ5gEEA02esXfqgTQHDREgKwORFAKrnLm\\u002fOOEkAWe4TAZwsYQG4TIonKJhNAWJX1fxabEEAwciOMbQMcQMQTs9ioGxVAH40KQC0MHEAHqiaCSC0QQMaSNkp6+g5AX6KK3rieEEC+W2J6ODASQMzP+cuAlxJAGE\\u002facoftFUCowmGg1acWQHXkOIXZqRFAKLe1yyG\\u002fEkCGWUudN9QiQIkhdTcXmhBAYJotqraREkCloPF69SETQOJEM5raSRRA\\u002frF4uPzpFUDUbbPxCJUWQFS6CR43QBJAjritA0PRIED9BrLdXCgbQANsj\\u002fQkkhZATKFzgnXUHEAap\\u002feGdoISQCcZQoxL9hFA6yBkzXNWE0DgkSku0XcRQJ7mheGWUBFA4k3DMn55EEDWKiehn4ITQF3ui3sR5xJA0O0o3ItxFEDcyA2s+JkcQNeyd5EYzhNAyDZJPKwqEUAQn3+MAhETQNpLledQYRJApZWb2i+WGUCeK3J0wW0VQPxG+EJo8RNAAhpfkhrpFUB05pcwq44UQPEqwZPgPR9AdCkNTyCfFEA5x\\u002fOhEeoSQLKyJPNswhNAmNwvJn23EEAMnLrfehEVQD\\u002f3SCp+\\u002fBBAvCj+tq7hE0DUx45KcJ4SQAT2RFWt\\u002fxVA0HShrtsXFkCIsU38SmwQQCq1PLKbvhZAknJM+mG+F0B6z6h0DT8TQD4NgnB1SxdAKNxnzjsZGEDLi4P7mswbQJLlMQKdLBZA81Xjjj1WEUDpUoD4HQgXQOLw7LoKoCFAM+G5OoDSFEAkY2zCyDcVQIL1UGC2QxRA2COUMkOWGkCc50KM+CElQCvon9+0ESdA5jHtZY8lKEBetZf0QWMlQOjtnRtauTJARoWe7N97KEAGoZ0+peAYQCiV2CPnlhNAEVz2b7udEkCidJ417VsVQDynLzN7KBZA\\u002frViBx1eEkBWcHCLpAgaQCgS0aJskRxAdLhi8k+dMkA6BWjSUlMWQL7f6+L7xx1AoQkJWWT8EUCe0ihvJ5kWQKKJrkPfvRZAGpZSvJPKEUCep2fiDsMWQGg2\\u002fB9FiBRAyvcFoOquFUA\\u002fQlcah9oSQHHi1RTmwx9AHnCI53wrFkBRB6izp9EbQA==\"},\"yaxis\":\"y\",\"type\":\"scatter\"},{\"customdata\":[[\"Actinomycin D@0.13717421\"],[\"Actinomycin D@0.411522633\"],[\"Actinomycin D@1.234567901\"],[\"Actinomycin D@11.11111111\"],[\"Actinomycin D@300.0\"],[\"Actinomycin D@33.33333333\"],[\"Actinomycin D@99.99999999\"],[\"Cucurbitacin I@100.0\"],[\"Ethoxyquin@300.0\"],[\"FCCP@300.0\"],[\"Staurosporine@100.0\"]],\"hovertemplate\":\"status=suspect\\u003cbr\\u003eviability, relative to the controls=%{x}\\u003cbr\\u003edistance from the controls=%{y}\\u003cbr\\u003egroup=%{customdata[0]}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"suspect\",\"marker\":{\"color\":\"#EF553B\",\"symbol\":\"circle\"},\"mode\":\"markers\",\"name\":\"suspect\",\"orientation\":\"v\",\"showlegend\":true,\"x\":{\"dtype\":\"f8\",\"bdata\":\"9XmvSkfs5D8YdMxTx5vkP9ugwh0e+eU\\u002fhSWRNFNa5j8EJ1yn\\u002fI7dP5Om5xXXE+Q\\u002fQoQJRYFz3z89NWVU1+vhP1nPFQNqj98\\u002fItAqfDC34z+\\u002f\\u002fGJHwN7iPw==\"},\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"M+mbXprWIEB5FnJtWP8iQEg0UBhfRiRA6mBMpHshJUAqrC6oysI\\u002fQMfLie1VFS1AVIoorsiUM0CBZBXVwistQDmU0CxgVy5AOkC5XrEbPEDEdXfwQJQrQA==\"},\"yaxis\":\"y\",\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermap\":[{\"type\":\"scattermap\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"viability, relative to the controls\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"distance from the controls\"}},\"legend\":{\"title\":{\"text\":\"status\"},\"tracegroupgap\":0},\"title\":{\"text\":\"cytotoxicity\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('d531633f-b259-4026-8534-4b0355f47989');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mt.tl.cytotoxicity(heparg, groupby=\"Metadata_Perturbation\")\n",
    "mt.pl.cytotoxicity(heparg);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c042",
   "metadata": {},
   "source": [
    "A high call with viability near one is a change in the shape of living cells. A high call with viability\n",
    "collapsed is the morphology of dying cells, which most mechanisms share. The US EPA's phenotypic profiling\n",
    "pipeline drops any concentration that loses more than half the cells before it fits anything, and that is a\n",
    "reasonable habit here.\n",
    "\n",
    "## Does the call survive a second cell line?\n",
    "\n",
    "The same compounds were dosed in U2OS. The two lines were normalized and feature-selected apart, so their\n",
    "distances are not on one scale, but their calls can still be compared."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c043",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T01:01:21.234514Z",
     "iopub.status.busy": "2026-10-21T01:01:21.234355Z",
     "iopub.status.idle": "2026-10-21T01:01:25.709260Z",
     "shell.execute_reply": "2026-10-21T01:01:25.708164Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<path>:6: UserWarning: 280 of 289 groups have fewer than three rows, so their statistic is the median of one or two wells. Aggregate more replicates, or score activity with mt.tl.map(mode='activity'), which ranks replicate pairs and is built for screens with little replication.\n",
      "  mt.tl.hit_calling(u2os, groupby=\"Metadata_Perturbation\", use_rep=\"X_pca\", n_permutations=300)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "28 shared compounds, 57% called the same way in both\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x460 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "u2os = adata[adata.obs[\"Metadata_CellLine\"] == \"U2OS\"].copy()\n",
    "mt.pp.normalize(u2os, by=\"Metadata_Plate\", reference=\"negcon\")\n",
    "mt.pp.feature_select(u2os, na_cutoff=0.0)\n",
    "u2os = mt.pp.subset_features(u2os)\n",
    "sc.pp.pca(u2os, n_comps=20)\n",
    "mt.tl.hit_calling(u2os, groupby=\"Metadata_Perturbation\", use_rep=\"X_pca\", n_permutations=300)\n",
    "mt.tl.dose_response(u2os, compound_key=\"Metadata_Compound\", min_doses=4)\n",
    "\n",
    "other = u2os.uns[\"mantispy\"][\"dose_response\"].set_index(\"group\")\n",
    "both = pd.DataFrame({\"U2OS\": other[\"hitcall\"], \"HepaRG\": curves[\"hitcall\"]}).dropna()\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(5, 4.6))\n",
    "ax.scatter(both[\"U2OS\"], both[\"HepaRG\"], s=30, color=\"#3a7ca5\", zorder=3)\n",
    "for compound in [\"Staurosporine\", \"Actinomycin D\", \"Cycloheximide\", \"MUPIROCIN\", \"Rifampicin\", \"Berberine chloride\"]:\n",
    "    if compound in both.index:\n",
    "        ax.annotate(\n",
    "            compound,\n",
    "            (both.loc[compound, \"U2OS\"], both.loc[compound, \"HepaRG\"]),\n",
    "            fontsize=8,\n",
    "            xytext=(4, 4),\n",
    "            textcoords=\"offset points\",\n",
    "        )\n",
    "ax.axvline(0.9, color=\"0.8\", lw=0.8, zorder=0)\n",
    "ax.axhline(0.9, color=\"0.8\", lw=0.8, zorder=0)\n",
    "ax.set(xlabel=\"hit call in U2OS\", ylabel=\"hit call in HepaRG\", xlim=(-0.05, 1.15), ylim=(-0.05, 1.15))\n",
    "print(\n",
    "    f\"{len(both)} shared compounds, \"\n",
    "    f\"{((both['U2OS'] >= 0.9) == (both['HepaRG'] >= 0.9)).mean():.0%} called the same way in both\"\n",
    ")\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c044",
   "metadata": {},
   "source": [
    "The corners carry the biology. Staurosporine, actinomycin D and cycloheximide inhibit kinases, transcription and\n",
    "translation, and are called in both lines. Mupirocin, an antibacterial with no mammalian target, is called in neither; rifampicin is not called either and scores low in\n",
    "HepaRG. Berberine sits off the diagonal, called in U2OS and not in HepaRG, which may be\n",
    "a difference between two cell types rather than a failure of the fit. Read the U2OS calls with\n",
    "care: almost every group there had only a row or two, as the warning above notes, so each call rests on the\n",
    "median of one or two wells.\n",
    "\n",
    "## Summary\n",
    "\n",
    "- Use `hits_row_distance` as the response, not `hits_distance`, which is one number repeated over a group.\n",
    "- Quote an EC50 only when `fit_ok` is `True`. Use `hitcall` to decide whether anything happened, not to rank\n",
    "  what did.\n",
    "- Find the window before reading anything in it: `phase` marks where a compound is silent, responding,\n",
    "  saturated or cytotoxic.\n",
    "- Read the direction and the features, not only the distance. A distance that plateaus does not mean the\n",
    "  phenotype stopped changing, and {func}`~mantispy.tl.dose_features` gives each feature a benchmark dose even\n",
    "  where no EC50 exists.\n",
    "- Score viability against each plate's own controls, and check the batches agree before calling anything\n",
    "  cytotoxic.\n",
    "- Compare compounds on their own relative dose axis with {func}`~mantispy.tl.dose_trajectory`, and check a call\n",
    "  in a second cell line."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}