{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5092964b-0ec6-43a2-a854-d352b027d6ee",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "# Analyzing Pixel Classification \"As a Whole\"\n",
    "\n",
    "This notebook depends on the SupervisedClassifier notebook having been run first!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8cd4af3c-bfe4-421d-be6b-a144281a3f8f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The PalmettoBUG package is copyrighted 2024-2025 by the Medical University of South Carolina and licensed under the GPL-3 license.\n",
      "It is free & open source software, can  be redistributed in compliance with the GPL3 license, and comes with absolutely no warranty.\n",
      "In python, use palmettobug.print_license() to see the license, or use palmettobug.print_3rd_party_license_info() to print information\n",
      "about the licenses and copyright of 3rd party software used in PalmettoBUG itself or in the creation of PalmettoBUG.\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import palmettobug as pbug"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c91bdee7-ffc6-4c3a-9bc4-ae8059454a0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.2.11'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pbug.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc9e6031-a3e8-4718-95a4-ef1cfd3e7993",
   "metadata": {},
   "source": [
    "### CHANGE The following directory to match an existing directory on your computer if you are testing this tutorial on your own machine!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b527dbf5-646e-4276-b71a-24ef1a546ff9",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_computer_path =  \"C:/Users/Default/Desktop\"  ## CHANGE This DIRECTORY to match an existing directory on your computer if you testing this tutorial on your own machine!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d2c51f1-9dc4-4bd7-8b68-586394d1e8a6",
   "metadata": {},
   "source": [
    "## Setting up for a Whole-Class Analysis\n",
    "\n",
    "This requires:\n",
    "\n",
    "    1). a pixel classification to have been run (usually a supervised classifier, but sometimes a merged / annotated unsupervised classifier could be used)\n",
    "\n",
    "    2). Region measurements must be taken from the classifier's predictions (treating them as if they are segmentation masks)\n",
    "\n",
    "    3). The set-up of Analysis_panel.csv and metadata.csv files, just like for standard single-cell / CATALYST-like analyses\n",
    "\n",
    "In this case, requirements #1 and #3 will depend on other notebooks where those steps have already been done, but requirement #2 we \n",
    "do within this notebook, then load for whole-class analysis. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b5a80f08-6c0d-42e8-87e9-b37021e4a6fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "''' Gather directories from which we'll read pixel class region properties '''\n",
    "\n",
    "project_directory = f'{my_computer_path}/Example_IMC'\n",
    "\n",
    "pixel_classifier_output = f'{project_directory}/Pixel_Classification/lumen_epithelia_laminapropria/classification_maps'\n",
    "\n",
    "whole_class_directory = f'{project_directory}/Pixel_Classification/lumen_epithelia_laminapropria/Whole_class_analysis'\n",
    "if not os.path.exists(whole_class_directory):\n",
    "    os.mkdir(whole_class_directory)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6b837e3c-47b6-41f9-958d-004c9b8a0c92",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CRC_1_ROI_001.ome intensities csv has been written!\n",
      "CRC_1_ROI_002.ome intensities csv has been written!\n",
      "CRC_2_ROI_001.ome intensities csv has been written!\n",
      "CRC_2_ROI_002.ome intensities csv has been written!\n",
      "CRC_2_ROI_003.ome intensities csv has been written!\n",
      "CRC_2_ROI_004.ome intensities csv has been written!\n",
      "CRC_3_ROI_001.ome intensities csv has been written!\n",
      "CRC_3_ROI_002.ome intensities csv has been written!\n",
      "CRC_3_ROI_003.ome intensities csv has been written!\n",
      "CRC_3_ROI_004.ome intensities csv has been written!\n",
      "CRC_1_ROI_001.ome regions csv has been written!\n",
      "CRC_1_ROI_002.ome regions csv has been written!\n",
      "CRC_2_ROI_001.ome regions csv has been written!\n",
      "CRC_2_ROI_002.ome regions csv has been written!\n",
      "CRC_2_ROI_003.ome regions csv has been written!\n",
      "CRC_2_ROI_004.ome regions csv has been written!\n",
      "CRC_3_ROI_001.ome regions csv has been written!\n",
      "CRC_3_ROI_002.ome regions csv has been written!\n",
      "CRC_3_ROI_003.ome regions csv has been written!\n",
      "CRC_3_ROI_004.ome regions csv has been written!\n"
     ]
    }
   ],
   "source": [
    "''' Make region measurements from pixel classifications '''\n",
    "\n",
    "experiment = pbug.imc_entrypoint(project_directory, resolutions =  [1.0, 1.0], from_mcds = False) \n",
    "analysis_folder_name = \"Whole_class_analysis\"\n",
    "input_img_folder = experiment.directory_object.img_dir + \"/img\"\n",
    "experiment.make_segmentation_measurements(input_img_folder, \n",
    "                                          pixel_classifier_output, \n",
    "                                          output_intensities_folder = whole_class_directory + \"/intensities\", \n",
    "                                          output_regions_folder  = whole_class_directory + \"/regionprops\", \n",
    "                                          statistic = 'mean',\n",
    "                                          re_do = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a9016df0-0c8b-4d75-a631-1a9029ece777",
   "metadata": {},
   "outputs": [],
   "source": [
    "class_dict = {1: \"lumen\", 2: \"epithelia\", 3: \"lamina_propria\"}\n",
    "\n",
    "seed_df = pd.DataFrame()\n",
    "seed_df['class'] = [i for i in class_dict]\n",
    "seed_df['labels'] = [class_dict[i] for i in class_dict]\n",
    "zip_dict = {}\n",
    "for i,ii in enumerate(seed_df['labels'].unique()):\n",
    "    zip_dict[ii] = i\n",
    "\n",
    "seed_df['merging'] = seed_df['labels'].replace(zip_dict)\n",
    "seed_df\n",
    "\n",
    "\n",
    "## Each of these dataframes has been created previously -- so in this case I will just retrieve them from the disc\n",
    "classifier_df = seed_df\n",
    "metadata = pd.read_csv(project_directory +  \"/Analyses/metadata.csv\")\n",
    "panel = pd.read_csv(project_directory +  \"/Analyses/Analysis_panel.csv\")\n",
    "\n",
    "metadata.to_csv(whole_class_directory + \"/metadata.csv\", index = False)\n",
    "panel.to_csv(whole_class_directory + \"/Analysis_panel.csv\", index = False)\n",
    "\n",
    "whole_class_analysis = pbug.WholeClassAnalysis(directory = whole_class_directory, classifier_df = classifier_df, metadata = metadata, \n",
    "                             Analysis_panel = panel)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22b87b63-89d9-48b1-b5c3-3ea4280546fd",
   "metadata": {},
   "source": [
    "## Now we can make plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "febb7dbc-b057-40c0-a187-564da095d29d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''Compare area of each pixel class between conditions:'''\n",
    "fig = whole_class_analysis.plot_percent_areas()\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c7055f7e-67aa-488c-b309-d2a141b38202",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LCwv069dPlqNG/1PSMyUGK/Ob2tnZffKcdAySG2VlMa/XmfnzsbGxMFRYLj9C50hzUG6gz9H3pww0jw4aNChPcxzDKMJS4TuMxpLN6IZ2+PBhUeHC0tISnTp1EjclZaDJLjuomkZiYqKYlKUTKR1TStGiRcU+aLKlm2FmaJJVFemiLytokUjKRFZ8/vnnGDBgAPbs2SMmaqrMsWbNmizH0oQ5adIk/PbbbwgMDMwwgdL10Hf666+/Yvv27Z98lhaMN2/exLNnz7B582bxWlJSkkjko0Q/qoaj77DcZOTly5cZntO5UpU0UjoyL7DoOJS8SRvJDlVoW7x4MUaOHCmu5cqVK1kWPMgMfQdUoWbo0KGfvEe/A+3r6dOnInFU1e9fX2G5ywglqlNlrevXr2Pfvn3CoKIO3N3dVZJFY5Gv3MJy+R8tW7bEli1bhKKgCqmpqeLe26ZNG6XGU9VKSo6XVtCKiooSfwdkAKLiMgyTF0xrBtMDaKFEE2aBAgXEZEbWnKNHjyr9ebKskXUlODg4y/dpkqTFNVlwyfr75MkTUYZP3lJDk/bw4cNlViSy5OzatStP16Roy+7GThMbWZRIEXnw4AGWLFkie4+qZ40bNw4PHz4UZXjJekiKCCkhWd2saWFJ3yMtNLPyilSpUkXsixQT2uh45FGh9wwBlpuMnDx5EgcOHBA31OXLlwvPGFVfywrq5fH48WNhySQPHHnHaPFC3yMpFlTiUmp9DgsLEzf2rPjmm29EFZkbN27ILNp0g6byqeRtGzJkiNgXKST0PlVakipN9P2TMmxosNxlhKzCVHHos88+Q8WKFUW1P3WgqixmJn/+/GIfhihjuYHl8j8mT54s7mkkP6Qw0fdCnloyviiSH7oXkjJHCsWoUaNkr5ORjpQw2kdKSop4LC2DT1Xj7ty5I7uHVq9eXXhL/vrrr1xfM8NIYWVEy5QtWxa//PILmjZtKqxhNFl06NBB6c9TKVuygNB+aCF//vz5T8Zs3LgRz58/FxNuz5490adPnwyhBOR9kLqVaXFG1mRaYGkbmsTmzp0rLEI0kdK5SqHwBHIhk9WG6qKTi5y8GFSSl5SXzJCSQiFftNCUhyZTcudTaA7dQOQ36kNCJQ71IRQmJ1huMkIhd6SE0Pn8+eefwsLn6uqa5VhSDlq1aiVq7NP1UyjfsGHDxHszZswQz+l7pfep1KWiRQ0pujNnzhRKBx2LQjT++OMPoeQQdPMnBZfkkL4fWrBKQwpJ1khxofM1pN4iLHefQtdDlm9VLdE5oYosZsbW1hYTJ04Uoaz0XdF3asywXGb0mpCHju51tWrVEudCckT3z0aNGsnGjRkzRtZnpEuXLuIeSJ4N+dBB+l5IlkipobBWekylfgkaTyV/pRt9F7Qv+VA2hsktZpQ4kutPMwYB3eTIknzs2DFdnwpjQOir3FBzL1oEcMMt40Rf5Y4xbVguGUZzsGfECKH8CHLDkp5JlpoFCxYIKy3DZAfLDaMLWO4YfYTlkmG0ByewGyEUL0phT9RZlWJqKaxE3SEFjPHBcsPoApY7Rh9huWQY7cFhWgzDMAzDMAzD6AQO02IYhmEYhmEYRiewMsIwDMMwDMMwjE5gZYRhGIZhGIZhGJ1gEgns1KX19OnTonZ25cqV8eOPPyocS43MqH8BVdKgXhfU3bRbt25aPV9Gf6Eme2vXrpXVpafa8tQ8ysLCItdjk5OTRbMz6neiqAM9Y5qoIm85zXM8tzHamttWrVolel+QzNnY2Ii+F9Sng5qNMgzDmKRnhBqUUZMfakiWEzSJUsfTxYsXi86mJ06cwJkzZ7Rynoz+s3PnTlHukbrB00ad3BV13VV2LDXsog7KDJMXectpnuO5jdHW3NaiRQvMnz9fKCxz5szBy5cvRWNShmEYk1VGqCtpzZo1RffR7EhKSsLFixdFt1Xq8u3l5SU62lKjI4YhTp06ha5du4qFn3Txp0g+lBlLHX5v376Njh07aukKGGOVt+zmOZ7bGG3ObdShmzwiUszMzBAUFKSV62AYxvBgn6kc7969E+5nHx8f2Wv0WJF1iEhJSRGbPFZWVmJjjAuyKoeFhX0iH6GhoSIcwc7OTqWxaWlp+Ouvv0TtemUqbLOsmRaqyJu65zaWNdNC3XMbsXv3buzYsUMowqQg9+7dW+HxWd4YxrRhZUSOxMREWFtbZ4iRpYk1ISFB4WfoZr59+3bZc19fX8yaNUvj58roRj4I+RszWZkJkhH515UZu3fvXnETL1u2LO7du5fj8VnWTAtV5E3dcxvLmmmh7rmN6NSpk9jevHkjcktcXFwUHp/ljWFMG1ZG5CC3MiUTk8VaetMmS4+tra3Cz3Tu3Bnt2rXL4I6Wdm8lSyRj2Hh6esoeS8MOSCacnJxkj4nMMpLT2Pfv3+PYsWOYPXu20ufCsmb85Fbe1D23sawZP5qa2zJDIVve3t4iV2n8+PFZngvLm+nIGsNkBSsjclAcNd2oKdmuePHi4rUXL16gWLFiCj+TnSuZm9sbFw4ODnB3dxcyUahQIfEaPabXMlupcxp79epVREVFYcSIEeI9uuGSxZFCtn766SeULFnyk+OzrJkWqsibuuc2ljXTQp1zW1aQEpxdzgjLG8OYNiaRwE4TIVkF09PTxcRGj7OytlAYQ926dUV1I7L00ORJ5TKbNm2qk/Nm9I/GjRuLkILIyEix0WNF1YuyG0ulLv/880/hGaFt6NChwuJIjylEgWFUlbfs5jme2xhtzW1kVKEE97i4OCGHVGqackcqVaqk5StiGMZQMJOYgNlh69atGeJRCYrTnzRpEqZPn47SpUuLaiAE3aiXLVsmq8XfqlWrXNXiJ/dy5oQ8xvAgi7I8tLijXiAXLlz4pL4+yQ3x5Zdf5jg2M5QzQiUwc9NnhGXNeMiLvGU3z6lrbmNZMx40NbeRMkJzWWBgoJAVZ2dnUemte/fuQilWBZY345Q1hjFJZUQX8CRqHBjCJMqyZjzou7yxrBkP+i5rBMubcWAIssboFpMI02IYhmEYhmEYRv9gZYRhGIZhGIZhGJ3AygjDMAzDMAzDMDqBlRGGYRiGYRiGYXQCKyMMwzAMwzAMw+gEVkYYhmEYhmEYhtEJ3IGdYRiGYTQINaJ89+6d7Lmbm5vCbuUMwzCmBisjDMMwDKNBtu/YiWvXb8HeyVl0JU9JiMW0qZNhbs7BCQzDMKyMMAzDMIyGII/I+QsX0Wf4FOSzthGvHdr2F44dO46WLVvo+vQYhmF0DptlGIZhGEYDxMfH4/c//kSzTgNkigjRpG0fHDx8FI8fP9bp+TEMw+gDrIwwDJNnXrx4gX///RfJycm6PhWG0RtFZMbM2ShXMwDF/MpkeM/Gzh7tew3HwsVL8fz5c52dI8MwjD7AygjDMHlOzp3y6wzMXbwSN2/e1PXpMIzOCQkJweQpU1GiYj1UqtkkyzEehYqg3efD8cefC/nvhlErKSkpiIuLE1tqaqquT4dhcoRzRhiGyRNBQUEwt3dFhL0PHjx+itq1a+v6lBhGZ1y/fh1/r9uAxu37onipitmOLeBVDF0H/ohNGxfi8eMn6NatKywt+bbM5J7IyEiMGz8BNrb2wlBknc8SkydNRL58+XR9agyjEPaMMAyTJx4+fIQ4aw+kORbEv/ce6Pp0GEYnxMbGYsnSv7Bzz0F0HTQmR0VEipOrB3p89QveRyRi/MRJePXqlcbPlTFOIiIiMH3GLDRs8zn6fDsVX4z4Fb5lamDO3N+QmJio69NjGIWwCYZhmDxx6fpNJNgVhMTaEVHR0SI0wN7eXtenxTBagUr1XrhwAVu37UDlus3xWesBMFOxZK+lpRUat+uN14GPMP+PhahWtTK6de0CG5v/kt41DYXzrF27FufPnxfPGzRogH79+sHCwkKlsRQitHLlSpFDFhMTI3qqdOjQAU2bNtXatZgit27dwpq161C/VQ+ULFdN9nrNxu1w80I+jBs/EV8P+wrFixfX6XkyTFawMsIwTK6hhUfg8+dI8/9oBU5y9BI3xfr16+v61BhGK4UbVq/5G1a2Tvhs8M9wdHHL0/6K+pZC7+GTce3sQYz5aSw+69YF9erVg5mZGTTNzp078fDhQ/z222/i+fTp07Fr1y5069ZNpbFpaWlwdXXF+PHjUbBgQTx58gQzZsyAu7s7KlWqpPHrMDU+fPiAdes3IiIqFp36fw9X94KfjKlarwU8i/lh4ZJlKFvaH5916wpnZ2ednC/DZAUrI0YKWa7I3U9Ntby9vbVyM2NMj3/++Qepjp7A/1uCYx2K4viZ86yMMEYfl79py1Y8e/ZChMRkrpaVF8hLUqdpR5SrWh9nDm3B4SPH0L9fX5QoUQKa5NSpU8K7QYoE0aVLF6xbty5LZSS7seTN6dGjh2ysv78/ypUrJ5QXRcoIGTVok0L3K1tbW9lj5lPev3+PXbv34NHjJ6jVtDMCKtTI9rvyLOqH3t9Mwp0rpzF+wiTUqlUT7dq2gYuLi1bPm2GygpURI2X7zl04dPIcJKnJ+GbIANSqVUvXp8QYIYdPnEaUo7fseZpDQbx6fFmEZzg6Our03BhG3VDp6oMHD+HkqdOo3rAterXqr7Eu6k4u7mj7+dd4++IJlq1ciyJehdC7V0/hYdBEvktYWBh8fHxkr9Hj0NBQUaLYzs4uV2Ol39nTp0+zNVCQV2X79u2y576+vpg1axby58+vxqs0Du7du4eNm7Yg8MVLVKnXCn1b9oN5FqF0WWFhYYkqdZuhfPUGuHPtNCZOmoJq1arh857dUaxYMY2fO8MogpURI4QqaJw5dwERxZvBPDEaB4+dZGWEUTu0KAkMfIE0fzlrp5kZEpx9cO78BbRp3UqXp8cwaoXCD9et3wAf/8roPXwKrG0+Wu41TWGfkvh86Hjcu3URk6dMQ9MmjdGuXVu1Vt2SJjfLKxLSvK+EhIQMr6sylvJpli5dCk9PT9SsWVPh8Tt37ox27drJnkst/FQimUvTfox0uHLlCg4cPAwzS2uhhNRtO1Dl3CQpVvmsUa1eS1SuFYCHd67gp18mws3FCW3btELFihXVrmDT788w2cHKiBFy48YNJFg5Q2JlhzRLW7x+dh1v375F4cKFdX1qjBFx/vwFJDh7CwVEnjiX4jhy4hQrI4xREB0djZWr1yA0PBpte4+Ae/7cLazSUlMRGRECF9f8sFBRkaBFZ/lq9VGyfDVcOrYTY38Zhy+HDFZb6JY0UZ48G05OTrLHhDRcStWxpIisWLFClP6m/JHsFrhWVlZiywrajynL3rHjx3HmzFkULV4WjTsORP5CRdQma/Reuar1ULZKXbx58Rj7Dh8VZalbNA9Ao0aNtFpAgTFtuLSvkSGqnGzcjAiP8h9fMDNDhHsFrPp7va5PjTEyjpw8jViXTyuzSGycEJssEQowwxgyVBGK4uvdi5RDt0Fjcq2IELQ4XDl3jPg/t1hb24qqW006DcTipcuxc+cu4QnPKw4ODiL8ixLypdBjei1z2JUyY0mBoIpaFJ71yy+/fLIPJnvevXuHv5Ytx7gJkxAaZ4bPv56E5l2UU0RyI2vkiaLiCe16fYuOX4zCo5ehGP3jT9iwcZMoF8wwmsYkPCOqlCxctGiRGCfvAierDiXhGQK79uxFpKUH0m0/JhYSqS7F8PzFE1y9dg01a9TQ6fkZOlz+ErLwiej4JEg8s67IEmVfVIQK9urZHfpqcTx46DCCgt7LXitfviwaNWyoN83B1CVrxjCv6YLDR47g2InTCisUqcLCqcORnPQxvGnD4qn4buLiPO3Ps0hxfP71RJzcsxa/zf8D3337TZ7ltnHjxiJ3o3Tp0uI5PQ4ICMjVWJrbHj16hAkTJgjlhVGON2/eiBLRb9+9R9X6rdCvRV+R56FNqO9Nw9Y9ULtpR/x7/SwmTp6KihXKo0vnTuI+xTCawCSUEVVKFhItW7ZE//79YWiQderQ8dOI8mud8Q0zM4R51cKK1X/Dv2RJrp6RB7j85Ueu3biBWHvFYX/JLsVw+Zr+KCNkqaVwkfv37+P6zdvC8liheiOUqtFSRJmlp6Xj338vY8+e0ShTpgyqVqkk/tfl34q6ZM3Q5zVdcOzYcZw5fwXdvxwrvBF5JSU5CakpyeKx9P+8YmWVDy26DsbF47vw+x8L8MP3I/MU69+1a1dhGBk5cqRMoaVcDmLZsmXi/y+//DLHsWSoOHr0qAi7+vrrr2X7pzHSzzOf5t9t3LQZDx89Qe2AzmjStVquq4ipS/HNZ22DavVaoHKtprh74xwmTZmG+vXqolPHDnpjsGGMB5NQRlQpWWioUMzu7N/+QJhXHcDi09hbakgX5l4Bc+b/gakTs4/fZfSz/KU+cf3mHSQ6KA4ZkOSzR1xCok4aIJKXgMpevn79Gi9evMTzwBdC+XBxyw8vn1KoWLcdWhYt/knyJyUKN2zVAy+fPcDl2/9ix+59SElKFFVmivv6oFixouIxKYza+PtRl6wZGzTX0W9MXh5NhP+QdfrAoSMiaVwdiogmoQVr3WadcXTnShw6fBht27TJ9b7o+xw8eLDYMpNZichuLFXA2rp1K4wBCjPbsnMPCnsWQv++vTVyDDJELVq8BBVrN0Of4X2VroylLcWX8koq1Woi8koun9ormieS4lugQIE875thTEYZUbUMIXHmzBmx0Y29SZMmaNu2rcLFhz7UR6eY4bm/L0Coox/SHRSXQkx2K46X70Lw9/qNGNCvr1bOzZjQdflLfZA1KW/fvkF68Y+NDhWRbucuet2ULVtWI+dA3iWp0vH69Ru8ev0Gb9+9RVJSMtw8CsK9YBF4FCqGms1rw72A1yd/w2RBpBu3tLrM8PELYWmVD36lK4mNSElJRsi7V/jw7iWeX7qF0F37EB0ZBicnZxQuUgTeRQujaNGiYiMlRV2/gyZkzdDmtay4c+cO5s7/A1b2zkiNi8KEcWPh5+en1mPs3XcAdZt3gbWtYeQ50O/RqPXn2LBoItq0bs2GJjWybfc+3Agzx5OnF9CudUt4eHiodf/krV2waAna9/5O6XwQXUFzZIOWn+GFbxnMnDUb06ZO4VwgRm0YvTKiShlConXr1ujbt6+Ic6XF4fz588VkL192UN/qo/+1YiWehScjwatqjmOjClXH2esnULPmAzQzkPwEfUHX5S/1Qdakym8aJc2aZz99JFraiwWtuso60oL7+vXruP3Pv8KDRHkfbvkLwa1AYbh6eKFUjbKoV6Cw0otIUkSkykh2oTBe3iXEJv97xcVGIezDWwR/eIvH568j7MMeREeGo5CnJ8qVKY0qVSqjcuXKub5Zq1vWDHFey8pjseivFYgo2RoSG2eYx4Vi3h8LsWzxArWe17NnT1GjRR8YEjZ29nB1LyBkk8uoqgdS5OlvJaVkR8SbAafOnMVnXbuo9RjHjp9AzcYd9F4RkcfHvzxeP6+Gy5cvG0yOI6P/6EQZIWvApUuXEB4eLty8VHWH3O7UKVzdqFKykChevHiG0JlOnTrh7NmzCm/auq6Pfv3GTew8cBzhxZt/UmI1S8wtEFqkPub9sQhODg7CossoRv7Gruvyl7qWNSm0wJXkoIgQSRJLcV205QW6tj8XLMKr16/hW6oyvLz90bpqCzg4qi+fQ5XyofS907Fp8y5R7r99pKcjMjwE714/w7a9RzHvt9/FzbpL544qy5u6Zc3Q5rXMkPJJikdwoVpCESHS7T0QlFIeg4d+g59+GJnBM5QXSBTUUaFK26SmpgiFPasCB1nBSkv2HD12AgnOvoC5ORLdSuDYiaPo1KG9whLEucHW1gYRcdFQJ61btUKrVi1lf7cp1vZ4ExKn1mMkxEXD1lY9f28MoxNlhCybCxcuRNWqVUU/DFJGKK6cYkzHjRun9uPJlyEsVKhQtiULsyKnkARd1kf/8OEDlixfiTDvZjlaqTOcl5UdQr3qYMac3zBnxjR2tWpAlpQZK1/+khSRnH4HvarFr8TxzCAR55XXcyPL/6NHD1GhRmOUqlAT7gULqyVUSN03bcpBcfUoCGdXDzg5uyE1JUWEFXXu1EHnsmZI85o8SUlJ2LxtB85cvIqwIg0zVAkkUlyK4Z2lLSbPnIfWzZqgc8f2eW4GWKpUKQQ+uoPSlWoZzAIxIT4WsTGR4jc35b4c6jS4HDh8BLG+H3slSaxsEe/ghSPHjqNdm0wFYvJAq5YtRRd09/xe8CtTWS37pNyhvXv3iMcUdjpq2gqok5sXjyE24j1q1Bik1v0ypo3WlZFNmzbh559/FhP+gAEDZCEA8jXL1Y0qJQsvXrwowivIovj8+XPs2bNHVKHRNyjHgJSJ0II1ILHOonRiehrMkmI/vmf+qaUs3aEAghN8MX/BIoz98QedxoEbElz+knodWEOSlpLzOKSpJXmd9jF3zmycO3cOFw6tR0hoKLyKFoendykU8S0FjwJeuepErK6bNlmk378JxNsXj/Du5WOEvn8rPBGN6tTMNuxOm7JmKPOaFPJMnD13Dpu27kC0QzHE+rVSaHChPLkQv9bYfeUfEUrTt1cP1KpZM9e5E61btcAfC5bAv3z1PCcTa2uBeO3MAQQ0bcL5Impi645diHEuDonVf03/oj3KY/e+A2jcsIHa5mtHR0f8MvYnzP1tPt69fIQ6AZ2FfOgjpPCe2rce5mnx+GnM6Dwr/Qwjj9aliUKzSBGRh9zKmnSLq1Ky8MiRI+I1So6lmtotWrRQGMqgS8gj8t6yANKcsy6vSoqIw90diC3fFRLbrHtBJHqUxqM357Fn/wF0aq9/16iPcPnLj5ZdS1qkibwRxYsf6/QEtdWlp5s/5T3QJk32f/DgIS4f2SiS2D2LFoe3fyWUKFsFtnaaV+wiw4Lx5N4NvHpyBxFhwfAtXhxlS/ujZYMeouKWOhaF6pI1Q5rX6PwuXLiALTt2I8bSBZFFm2ZtbMmMhRWiPasjJjEKS7cewuZtO/F5966ir5KqvwX9fuXLlRaVg6hSlb7z7uVTIYdD+0/V9akYBTSfnL1wCXEl2mZ4nbwj0a7++HvDZnz91adVxHILebOmTJqIHTt2iiIEDdv0gq9/hTwlmpN3jCppqUOxofDTe7cu4uqpPWjXtg2aN2/GxktG7ZhJtOzTHTt2LPr06SMq7JBnZPXq1bh37x42b96MqVONZzKlxaZ8NRp1cuzECWzYexxh3k0V5omYJUTlqIwI0lKQ//lh/DD8K41VPTJkvLy8YMqypogx4ybigX0l0W1dEQVfHMXM8T+qvQJNZiiHgcpj3rhxE1evX4dXsRKoE9AFzm75larHTzdtGzsHperxvwl8hEsndiEtJQF1atdC1SpVUKRIEbXdnPVd3jQlaxSOdfzkKew7cAhxNvkR5V42W9nKCfOECLiE3Yd9aiS6dGiPRg0bqBTrTwrvhImTUTOgK4qXyr5qnDLMHz9EVixBnZ6RuJgobF0+Hd+PHCGUKGOSNV3NbZN/nYnbSfmR6ppFDqskHfmfHcSkMaNU/r6VLdKwavVaSCys0bD15yLsMzeEhQSJDuyDfpgF9/y5zw0Kev0Mp/dvQGHPAujbp7esdLiqGIKsMSbmGenZsyfmzJkjSkvSImLjxo04ffo0RowYoe1TMUgokXPT9j0IK95SuYT1nLCwQmiRhpi/cAl+nTSea4czSie/PgqJRlo2C8b0xFitdOylcAFqUEhbr16fi+IYW1fPQfWG7VC+egOFigKV8pXetHt/PT7HUKxzh7ci9O1T9PuiL3cuVxOUaL//0GEcO34S8Y5FEVM0AJJ8OeSw5RCCKobYuiK8SD1EJMVgzeHLIuyGSrO2aN5MlvCfHdTU7ftR/8O0X2fA0Vk/y66ScrNn3R/4vMdnGlkYm+r99eWHcKT6VMt6gJk5wvNXxqq/N2DSuJ/VfnwybIwfNxbXrl3D5vXzUaxkRdRu0lFUS9Mm0RGhOH90O2IjPmBgvz6fRLMwjLrReoBpxYoVMWnSJGHtoCZvlLxO3hJ6zORsNZn7xyKEFm0EWFqrbb/kOQkpUB1Tps8U5VIZJicKFyoA86RYxQPS02Blaan1GHY6Xr169TB1yiS8f34bu9bOQ3DQq1zvjxzHTx/cwsZFk+DpaoMpkyexIqIGyPOwfecufDdqNHZeC8T74q0R7VktZ0VELgSV/s8JavYa5VUT731aYPP5+/h25A/Yf/CQUhXBqFzwt8O/xv6NCxATFQ59gsKaD21dijq1qqF27dq6Ph2jYdO2nQh3r5CtoS/NqTBevQ8V92NNQMYTyjWbNXMG/Iq4YcPiibhx4QjStFDFLikxAeePbMPO1bNRv2ZFTJs6mRURRivoJAOJSvgOGsSVGFSByh9PmTELIV51sg+7yiWUexKUnozxk6dh6sRxshKhDJMVLk6OME9XHD5hlpYMaxvdda8m+aUuwbdu3cL2nathYWWLCjWbioo1Fhb/TXsurvlFKAP9L09SQjzu376If6+eQmGvQhg5YjiXwVYTt//5B0tXrEa0nRdi/NoClppP2KV4/5hCVRHrXgabT93G4aPHMXzoEFnCvyJKlCiBPr16Ysu6P9B9yM/IZ52zV0UbnD24CYU8nNGpo+qV2pisIUPcm3fvkVayRvYDzcwQ5eyHYydOabR5MIUVtm/XDo0bNcL2HbuwbsE41GrSCaUr1sxVwY6cPL//XDmF25eOomnjxvhy1kzhHWQYo1VGqAOwIho1aqTVczEUKFl31m9/INizjqiCpSmSXX1Btp6xEyZj4i8/6bTBGaPfpKSkQgLF1kOJmTnS0rTfjyKzhZFKiFepUkX8DR09dhznDm1Gmcp1UalOM9g7OMHC0jJDTHXo+ze4dfEoXj27L3JCfvrxew5dVBPkZdq4ZSuOn7+KsMINZP1CVMH+1kaY/b8SbPdgP+Kq9lbtHKxsEeVVAzHx4Zj951J0at0cHdpnTFTOTI0aNRAcEoKDW5agY58RuVoIqjOp+Pblk4gLf4dvf/qRE4nVyP3795Hk6KVU+HOKcxHc+uc8PtYD1SxUcWtA/y9EKf/NW7fhxvlDqNe8K3z8Kyj8/RUZWbLysD24fQlXT+9D5UoV8evUKWyIZExDGTlw4ECG55GRkaIKDMW8sjLyKRcvXcbKvzeIvI50u9wlj6mskJjnwy8Tp2D0yO9QsmRJjR+TMTwCX79BurWj4gEW+ZAQHy9udrouN0o3bJJj2mJjY3Hy1Gls+WsqSleqg1qNOwiFJC42Gqf3r0dM+AexOB35zUAuXalm9uw7gKOX7yDct4XCXI+cMEtPhVl62sfHktwru+l2bggp3hI7j56Co5MDmuRw72nTujVev36DC8d3on6LbiofT5X8pOx4HfgId68ex+RJE5Vubsgox/MXLxFn5ax0r67YuFihYGpLISxYsCBGfDtctEHYuGkLrp87gPotu8OzqN8nYzMbWTJD5/380R1cPLodxX2LYdzYMWx8ZHSK1u+2s2fP/uQ1qnlPJR2Z/6BFHFkRT1y4hjCf5krFUqszZOuDlR1m/LYAvbt3RkCTJlo7NmMYsnnnzr9I9WmheJCZGSSOBfDgwQO9ygejEsEd2rdDyxbNsWXrNqyY8z1sbO2E4tSzx2fCIMLWZs0kqu87eBjhVC41l4qI2rGwQnjRBti4eRsa1KuXrfJJMjFo4ABMnjINT+7fRMmyVaFtYqMjcWznSowZ/b1a+vcwGfkQEgaJlfLfq5mVtTBukOdCm/j4+GDsz2OEJ2f9xvWwd86PBq16wMnFXanPhwS9xukDG+Bglw//++5rDj9l9AK9MP21b98eX331Fbp06aLrU9ELKKl/zvw/8SwyFZF5sCLmBfLChBRvgXW7juDxk2cYMrA/W4oZwblz55Fo4w5YZh8/H+FUAhu2bMOvk8vq3QKfGjd+0bcPevboLqyEZGVm+dZslaIUR0+hAOgTFLaVZueGwMDAHL3AFMM/8n/fCYUkf6GicMmhdLQ6SU9LE2FivXp2R+HCWfeWyiuU1L927VqcP39e1qumX79+WXpgchp7+PBhUSXz1atXotnmjz/+CH0nKiYGEkvlq/+ZWdnoRBmRQqX4p02ZLBqabls5CxVrB6BqneYKwwhTUpJx6dhOvHr6L/p90QcVKuS+lwnDqBu9aNf6+PFjXZ+C3vDu3Tv8OHY87iU4IbJwnVwpIhRXbX9/tyyuOtdY2iDMpynOPQ0TYVtcaYuhuv/rN29DRIHKOY5Nc/LE25h0HDx0BPoKJWmSYsKKiGaJiIhAgrn2vLuqkGxpL5rxKtugjuL3D25aJJJ+tcXFE7vg51NUo5Wzdu7cKZTG3377TWzk1dy1a1euxlI/CjIuBgQEwFAIDwuDJJ/ynpE0SzuEhYVBl1AIbP369TFj+jQkR77BjtVzEB8X88m4iNAP2Lx0Kgq6WmPmjF9ZEWH0Dq3fgclCIm8lpWZXlJhFjRBNHZrQ5/25GKGetZDmWCjX+1FXXPXHHZgjxrManoU/w0/jJmDC2J9QqFDuzy3HZLoHD5CYmCibaCnEh6t66AeU30UNwUILVlP6ph3uVRs79h+Gq6sL6tbhEqSmSnBoOFIt1FeOXJ0kmeVDRESk0uOpIMLDR49x5sAmBHT8Aprm2cN/8O75PUyeNEGjxzl16pTwbkgb25EysW7dOnTr1k3lsbVq1RL/U36DrhfsyoYRxsXFQ5KDt1eeaEsX/HvvAcqXLw9dY2dnh2FDv8LpM2ewbcVMdB04Gg6OLrKwrH0bF+DLwQP14lwZRi+UkTZt2mR4Tg2oKAZSUwtcQ+HOv//ij8XLEFKsca6qzGiaJDc/vLO0w4Spv2LSLz+rraMqufufP3+OW7f/wZUrV+Dq4QVHFzdZzXPqRktu/urVqoh658o0LGPUD9XU/3XWXHxwq4BUZxUawFnmQ6hPAJav3yKsz23btNa7kC1G89y8fQfpjnnvZK4JUmw9cPXWP2jVqqXSn+n+WTdMnzELd6+fE401NUV46HucPbAB4375WaUO8qpC4UakNNC9WAo9Dg0NFQt1WuzmZqyyUN8x+U7rNEfY2n4sDa6N+eLIseNIcPZWqZFwiqsPTp89hq6dOwrvqj7QpHFj2NrYYOua31Ctfith4Lt6ai9GfPeNKFPNMPqK1pWRxo0ba/uQBrHQ+2PxXwgp1hSSbDpa6xoKuwk2q4WpM2Zj9vSpKsfKkseDrvX169cIfPESgYEvEB4RjkKFfVDUrzy6DPpJZs2RkpyUiGcPb+PwyYtYuXotbKyt4evrC1+fYqJfDcVPcylCzUH5FKdOn8GGrTsQ6pW70tIUlx/q2xzbjl3E/YeP8c3QIZyAa0Jcv3EDoXEpSC+g+WqAuYG80C+e3RJhRzn1HZFCuRH/G/EtJk6aAmf3Aijqq/7GcAnxsdi3/k8MGTxQ45WOpN5oeUVC+jeakJCQ4XVVxioLhXht375d9pzm+FmzZmmlwhOFiR84cgIxlJ+p4rwW7eSL1X+vx6Txv+iNkaVz586wtbXDi5cvAQuIfku1a3/0VDGMSSsjBw8ezJXXxBQgy8W8PxYizLO2Xisi8jfukKSSWLp8FUaPGpHl4pVyS6hJI22v377D2zdvERwcLMoNehQoDNcChZHfszSaVW0JJ1ePDJP4wqnDkZKcJPaTL58Nhk9YiDKVaouNiI+Nxoe3L/Aq6DVu3zuB0A9vkRAfJ2K5yVtTtGhhFPbyEkoKvabrsrKGDHkyFi5dhmchsYjwbSFuvrnGIh/CizXCtdCHGPXjz/hq8ABUrVJFnafL6CE0B1CDwzBv9eQOkGetXZvW4rGEchfuRWL31ad526mZGcK86mD+gsWYPmWimDeUgYwxo38YhZmz5qB97+/gUSh7j6GyvR8ImgP3rPsdHdu30UpojdTjTJ4NqXGHHhNSD0VuxqqygG7Xrp3sufSeQDlq5D3XFI8ePcKc3xcgpHB9wFJ170Zs/vK4cP8CfpkwCcO+HKw3uWeVKlUUm5SgoCCdno+np+IywwxDaOUv59q1a0qNM0Vl5M6dO4hIt85TjohWbthyJLn74+GzA0LBIPc0lRh8/OSp8HaEBAfDzt4R7gW94OLhBbeCpVC3fGO4eBTM0Pk6u5swbYqwc3CCb6mKYpMiSU9HdGSYqOMfFPwOD55eQ1jwbvGas4sLfLy9UbKEH8qUKWPy4YDKQGW2Dxw6jD37DyEif0WkFK2mUviCQszMkJi/DIIcC2PB6s0oeewkvhrUX+nFH2NYREVFYdrMOQj1rANJdj1pVODAwUM4uH+feCwxt0BstX5qqx4Y7FEFk3+dgZnTpiht3adF1vBvhmHBoj/Rud/3cPUoqHBsTr0fpFBi/L4NC1C7RlWtRRJQyWv6O6QcD+kcSY/ptczfhSpjlYVC0BSFoZFhShNz3O69+3Hg6AmEFW2IdNtceu3MzBBRpC4uBd7Cy3ETMeq7b3jhzTD6qoxMnDhRG4cxSK7f+gdRtuot1aipG7YMMzPE2RTA3HnzkZqWjmJ+ZVGoaAk0rNAErm4FctWhOE+nY24OZ7f8Yisur6RIJIiNjkDwu1e49/wZjhw/g/TUJAweNAD+/v5aPUdD4e7du/hr5RpEWLoiyq91rqyFOUEewFCfZogKf45n4yaiVbMAdGzflgsVGBl/LvkLwc6lkeaoeIGuT6S6FMX7lBisWP03vvtmqNKfo5LAXw0ZhGUrfhMKiYu76qGMUtJSU7F/40KUK+2HTh07QJuQ4kPhUtJQNXqsqBpWTmNpsU8bef5pHk5OThZean3wHJA3ZMnyVQg1c/o4x+W13LSZOaI9qyEu6g3GTZmOgMYN0LWT/uSRMIwhoPuZwcSJT0iExMLwFmFpKUmITohB884D4FOinLD6qYPWrVrJEknJVZ9ibY83IXG52hd93tHZTWzFS1dC0OvnOHd4C27cvMXKSCYoHGLZqrV4+uYDwgvVQLqdhr0V9Nu6+yHYpRh2XbmDk6fPYGC/PqherZrexF4zuYeqJAYGvkRyqU4wJBI8SuP2PztV/hxV/Rs8sD9WrCKFZFSuFBKhiGxaiFJ+xUSCvLbp2rUrYmJiMHLkSFnvEAqfIpYtWyb+//LLL3McS+zYsSNDDghVy6S+GJMmTYIuQwbXbtiEJ6/eI7xgNaQ7qDcfJc25CIIdCmL/zXs4c3Y0unftjMaNGmbZp4VhmIyYSTThA80GqsSxceNG3Lt3T0xm8odfvXo1jGlxJ18dRBFHjhzFmpN3EFso574NyuJw429R3ldjnhEAHq/PomfLeqIhIiV+FiryMQndp2T5PFkG548fIgvTsrTKh1HTVuR6X5Rf8vLpfdHk6XXgI3h5eaJJo4ai7KSyuSTqqhqmD7KWFRSPvXP3Xhw5cQoRHhWQ4uqrnpAsFTFLjILbhxso5maPb74ajIIFDcOarm70Xd6UlTWyiH8zYhTeFaqLdDvlG8npem6ziHkPn+h/8fvcWbn2LC5fuVplDwkpIlR+tbRfMfTo0V0rCrm+y1pe5zYp1Dpg/eatuPfoGSLcyyPVVbmqWdSv66OsSSAxt0JclV5KH9MsOQ7OIf/CMTkMn3fvinp165p0/qIhyBpjYp6RlStXigZYZClZsGABvv32W+zdu1ejzZz0mbp162Drrr2I9SgryqAaAmYJUbBNi0Hz5s3RsmVL4Y5/9uwZbv9zB8d2/CU6yPuWqgT/CrVQqIivVi3dkWHBeHjnMp4/uIm0lGRUqFAeLZvUQZmvB7LbPBNUUpmSdsOt8iPar41Ou2NTOeuwYk0QFfkKYydNQ/s2LdGhbRuTvoEbMvS7/fC/bzHrt98R4eyPRHf/XDVwzYzEnG5ZEtFHSWKmxttXWirsQh/ALe4lRv80Ote7oWTzIYMGYPnK39B1wA+iQIcy3dUPbF4sPCLaUkRMASo/vGHzNty+ex+R7uWQUqKNCKlSrV9X7pLnqQ9TZOHaiEqMxvJdJ7Fl+y706dkdtWrV5N+XYfRBGSHL0bx580QVDrph1ahRQ5Txmzt3Ltq2bQtTgyqydG7fBltPXEFEkfo6sUqrRHoq3N9ewFdfDZAtFMkNTWFPtFF4AXm8bty4gfOndiAiMgoVawWgbNV6sLLKWdmyymctvGWpKcnCM6IMlMBOjcFuXzqKlMQ4NKhfD11HjdBKWUhDhL7fPfv2Y+/h46KKW17DFfJiQcyAmZmwWgY7eWLH6Ru4dv0mxnz/Py7dbKD4+flh3szp2LB5K67d2IdYFz8kuPlBYpX7TuxCttLTYJYUC4m1Q57PkfZjH/EUdlEv0KBebXTv+lWuk7DlFZIB/fpg7drf8NmQn0VBj+z+Fo/uXAnvwvnRkxURtUClh7ds34mzFy4h0q0skku2U0kJUXd+HCW4RyVEYunWA9i2a48o2sFhwgyjY2WErOhUjYMgSzXVJacqHLouPadLqPrVoyfPcPPtdUR7Vs+zQqIx62F6GtxenUWbpvVRqWLFbBUsSnCkjVzkhw4fwd+/j4V/xVooX61hthVnho9fKKpirZw7Br2/Hp9jGNb92xdx99oZeBcriv59enBjJyXCZxYvW4Grj14jongrtXhD8mJBzBKLfIgsUgcJYU/x8/hJmDx+LDw8crYwM/oHzQVDhwxCrx7ROHrsBE6cPokkS3tE2BdDqkux3MmfuQUktnloDJuahHyRL+ES+wo2ZiloGdAETZsMld2X1AE1ao2JjcXedb+j2+CfYGmZ9XVeOrEbdlbp6NunNysiauCfO3ewZNlKRDoUQ1yJtoC4F+qedFsXUbUrIjYYM/9cimrlS2NQ/y+4iS/D6CpnZMKECejdu7fopj179myhiFBtcrKkk8fEWFA11pWUtPl/LsI/ryOEezevIQ0USuVwdwdiy3fN241bSmoi3F+dRcsGNdDzs24q3zipDv258+dx+vRZpEmAEuVqoGT56nB1L5hl/HRkRIiox585MZ4UkKf3b+HpvWuIjghBvXp10LRJE42VhzWEWFdVZG3z1u04cPkuIovUVZu1UJNx/JaRr1E05j7mzvzVJKpt6bu85TWGn243T58+xYkz53Dz5k2k2rghwq5w7hUTZUlNglXkK7jEv4FVcgxq1ayBpo0aiMapmlQCNm/egrehsQjo+OnfBHlzb57ZjYkTxutEtvVd1lSVt1179mHv0VMIK1JPhH3q7bwmSYd98F0USn2PSePGwsUlY6NfY8QQZI0xMWWE6pFTeE+xYsXw/v17LF++XHhHvvjiC6W73xoCublpk9V645ZtOHHhKsKK1M9TbX51KiPmsSFwf3cRfbp3RdMmea97T96Sy1eu4OrV60hMTkGJstVQunKdLBUTIj4uBo/uXMGTu1eRGBeDatWqok7tWiK8T9PWREOYRJWVNer7MOqncQhWs8VQ00nFjkE30bNBWXRo/19TNGNF3+VNHQnF8vMddb8+de4Cbt26hRQbV0QKj0lR9chnWgosI17CNf61UEBq1qiORvXrivAxbXkh6BonTZmKyvXbZyg7nhAXg01LpmD8uLE6CyfVd1lTRd6uXL2KJeu2fWyuqUQ/K32Y16zCA+GX+hKzfp1i9LlxhiBrjG7Rug/zjz/+QMOGDWFvby8aJo0fn30ojilBE1Kfz3ugXJlSwtUc7lYWSW4ldJdHkp4O+5C78Eh8ix/GfA8fHx+17JYqJXXs0EFs1OX78uUrOLx5EaztHFE7oAu8ivmJcVHhIbh0YheCXj0Vif5ffzkQRYpk3+WYUQwt/JIdvfQmdEFZ4py9cf32HZNQRkxtviMDFG20aKf+D8dPncU/d/Yh2dETUc4lkG6vYnieRAKL2GA4Rz9FvrgQYbho1niAVhWQzNc47KsvMWvOPHj7lZV5ei8c24E2rVtxXpua2EUNWgvVUJsioo3mwSluvgh/9QIvX74UhjWGMWW0vir57LPPcPbsWVGDnEK1SDGhSlqajJ2k8qVr167F+fPnZTXR+/Xrl2X9b1XGaooqlSuLsJSFS5fh8cuTCPesqbYOxspiHhcK96ArqF21Ivr3Ha6xMAI3Nze0adMarVu3woMHD/D3ur+RkJgIMzNzpKWmoEf3bqj7v6F6YzlSpyxpW9bIAGCZlqj2/Wr6pm2WkgAHZ/XF8xsKhixrqkJ/32XKlBEbWcKvXb+OPQcOI+RDHMLdyokeDtkaZSQSWEa8gGvEAxTO74YOPdqgSpUqetFkjzpyVyhfDvduXkDFmo0QHRmGdy8eYuTXA3R9akaDdb58MEtLNqzmwRIJJKnJJhF+yjB6F6YlHzJy4cIFnDt3Dm/evEHNmjVFmV9NsHXrVly7dg1jx44Vz6dPny56TXTr1i1PY7ODEvKp62xmyDonf4PMzgVNY2/cuIlVf69HpKMvkvKXobt2lmPpR0zHf+9ZpKfALCkOEmv7LPNP0uTHIl3ujWQ4Bf8Ll9RwDBsyUHQXlj9fWtRkJzJWVlZ5GksWUnoszsvCQrZYUmW/dL5SK6i0C3Bux1JMuaZkSduyRlVmRv/8C966V0e6vXv28iMvE5nIPNbxn80wI3lLT0O6hTXiK/dQTtayQH6sOdLFPt1fnsTIL/sJ44U6ZU0dY9Upa5nlzZBlLad5Tdmxr169woYt2xH4PgzhhWrCzPbTymrmcWFwC76Bkt5F0KfnZyhcuHCOv13mc9C0/AQHB2PipMnwLOKNiLBgtG3dCs2aNdMbWTP0MC3y+s6cvxCh3k3VUmVN42FaEgkcPvyDih7m+Hn0KBg7HKbF5ITOzEbOzs5o06aNcNFv3rxZWOw0pYycOnVKWAFdXV3F8y5dumDdunVZ3ohVGUvQRCk/WdINgBLyqXcK5cRkpmjRomjd+qMVmVi/fr1s8Z2VRa19+/aoWLEC1m3cjNSkQFhZZf2TRaTlw7mEjzdhoonDe9g50X4jPhkbnWaF0wn/hTs1sH0HJwu5Cd+ZQiM8xG9y+/Zt9Or1X6nW/fv3ixtEVpB3i3J/pBw+fFhhlTS6WQ4cOFD2/Pjx43j9+jUUIe38S5w+fRqBgYEKxw4YMEB2k6droBuVIvr27St+L+Ly5cu4f/9+hvcnTpyoMVnStqxt2rQJFcuWRkXEUvvRDGND02xwMcFT9ryZ/WtYm6UrJWu16tSDnbm8DL9UXtbkiE+3xPH4orLn9WyD4GqRDFTwx6VLl8RmzLKWWd4MWdaUmdek0PxPinJWUBjTxF9+wp07d7Bw6XLR6dzWKpNBhtaeBUuJa5MP49y9e7foaZUVVDlL2/MaJc0TxbwKCAPcmjVr9EbWDB0qlfvtlwOxaNkKhHtUVEvzVk1VpaSGiG5BV1G2aH7879uv1bZfhjFkdKKMUJ4AeUQoXIsek4VOUxMjdXyn5kfy+Q70ODQ0VFR4kq8pr8pYKbt27RIhZ1Io9nPWLMXde+nGRjdjKdnFMZP7Vjp20vhfMHPmTCQlfexOrk7MJIotbOSZkD9feUteVqEW8mOzcz/TdcuPzSlMT36s9CarCMpFkh47p7GUv0LhS0RO/QXUKUtkqdQnWdM3zJJiYGUeDdhlLRcsa4Yra/LzGpFdCCbNNzSWNupJtXDRItFXSJEiIL/f7EK0eF4zPqpUqYxZ0yZj6fJVeBp4FBH5KyHNsVCeetpIC8HEl1FDvlpqEhxC78Mx9hX6ft4D9evVM6g5mWGMKkxrypQpIlGxQoUKIl+kevXqGo2ZpBvu119/jRUrVsiap0VHR2Pw4MFYsmRJhpKwqozNyYJIlrOs3Mt5DWeghcXJU6exc+9+0VU22cVHWIBUCbORhcNI0mEXch9usS8woG8vVK1aNcdz0FU4jK7CGajqmyZkic5fl7IWGRmJPxcvxeuoVEQWrIJ0K9tch2mpEnqV41iJGWxCH8E18hGGDOyPKpUrmYysycubMcmaOseqK/TK1Oe1zHObsVVvozXG2g2b8T4yDuGuZXLOOVKEfIPNXJbbN0uOh0P4Q9hFv0LLZgFo37a1yfUX4TAtRu88I9WqVcOIESNEmJY2kP7RkwVQeiOmx1lZl1QZK38zycqqRjcDRTcW+ddzSrDMamyrli2Ey3/BkmV49uocIrxqQWJlq3ABmBVmiVFwf3sRNSqUxoAvZmRraZM/h5wSXvVhrPx4smrmlPyu7Fh1ypJ0caArWaMmgpPH/4KTJ09j0/YdiHb1R4J7aVlOUk7yI4+6xprHBiP/hxuoUKo4Bv88XTTMyw6WNcOQNXWONYT5x9BkzRih/LLpUyaKnjabt+/C86e3EeXqj2Q3P9WqCeahwaZ5fBhcwh/CNikc7dq0RLOm35mcEsIwequMtG3bVqvHo9hgsvxRfxNycxP0mF7L7L5WZayuofjo8T//iFOnz2DD1h0I86yltEs6X8RzeITdxTdDh6BihQoaP1djQd2ypGtZI8tpQEAT1KpVA39v2Izr/xxAOIU2OBfVajlpsjy6htyGu0UShn73lYj/NnWMTdYYRheUKFEC434aLQoI7N53AFeu7UOCsy9i3f0hsdKA7FNp6cjXcIt6BHc7K3Tt3h41a9QwOWWQYVRF93UPtUDjxo1FDLS0qSI9DggIyPNYXUOLSWpCWMq/JKbPmYfgZH8kupdQ/AGJBI4fbqOYVSx+nj5Va94pY0KdsqQvskaL2a+/Goy3b99i2eq1ePXiEcILVP2k4pbaSU2GY+hdOMW9Ra/u3VC/fj2+aRu5rDGMLihQoAC+HDRA9PE6fuIkDhw+igTb/Ih0L6uWbu0UzpUv/BlcIh6hpJ8vuvf/CsWLF1fHqTOMSaCz0r7ahGJxqXIJlRLOXGN/2bJl4jVpVZPsxuqqU7EyUBLrlOmz8NKsIOI9suhkL5HAOegqKnraY9R3w/Wi/r4hxrqqU5b0Vdbu3r2LFWvWIVxij8gClSHJp2YLoiQdNmFP4BT2AK1bBKBDu7Zcaz8LeTMFWWP0a27Tt742mpI3yqO5eOkStuzYhRhzR0R4VITE5tOy0TmSng7r8CdwDnuA6lWroFvnDtzIMgs4Z4TJCZNQRnSBLm7aVB7zl4lTEGhdHCmuGbul23+4g8oewI+j/sfWZyObRDUha5RncOrUGWzesRPRzn6I9yirsMeNKljEfIDbh+uoXLYU+vX5nL1zBiZvrIwYr6yZYl8bmueuXruGLdt2Isq6AKILVBC9kpQpuGEe/RYuH26jeqXy+Lx7N5HjxgUTlOvXxTCZYfO4EUHJcZRH8uPY8Xhv5yFr/mQR8x6FUj9g1HdTWRFhlILkhPJJ6tSpJXrcXLl5UOQlpTvk0uqXmgyXDzeR3zwOw7//lkMYGEbPMOW+NpXKlxH/x8Y9xZkoN6Q5fSy53MTubaYeSv+RnC8FnYeMkTXZ3LZtm171tdHnfl0MkxlWRowMFxcX9O/bC8u2HUJY0YYiJMbt/XWM+mkUh8IwKkMJzl8NHohmz57h94VLEBpbCLEFKwJmyiu1pAy7B11BhzYt0b5tG1aIGUbP4L42/3+e3sXw5vI1vE2ORJzHRwVFEV5enqI1gRTua2NafW0Y9cLKiBFSp3ZtbNm+C+nvrkKSmoRSfj4GUVOe0V/8/Pwwb9Z0rFi9FlfvnURY0QaA5X/hDFkikcAu9AEKJLzCmF/GZOiOzTCM/iD1FMgvJKWLy4SEhAyv5zRWGvqjzL6kdO7cGe3atftEuejQoYPCvjby3oI+ffoovLbMY3v06JHt2DZt2mDazDl4EnwPpwqUydAvxOPVSXw9ZCAqlC//yX7J+5JdmJb82FatWmUbIiU/lgpNKDuWcnPq16+v1NjatWuL0DlFkPIo/R1I6cqqD5mUqKgo0buIqFSpkugjxzCqwMqIEUITCJUzfPXqlXjOpVIZdUBWsq+/GgL/EyexcccehHo3hSTfx0XGJ0gkcAq6jlKuZvhxwjSur88wegz3tcnoxaD750/jJiIw2hVpTl4iwsDj9Xl82f8LVKlc2WB71XBfG0ZfYWXESKGKHlzVg9EEzQKawtnJEUtWr0eIb3PA8lNFw+nDLVTytMX3I75VuYIOwzDahfvaZMTa2ho//O9bjJ80RTQ+TE9PQ40aNVCjxn9hWQzDqA9WRhiGURm6McfExuHvXYcR5hOQoUmidfgz+NgkYNR3o1gRYRgDgfvaZIQS01ct/0vXp8EwJgErIwzD5ApquHnn7n3cub8X5hb/TSUW6an4ccY07mXDMAZE165dERMTg5EjR8ryDyiXg8jc1ya7scq8zzAMIw/3GdEQXI/fOND3vg+6ljWKD89cJlNR/Ddj+PLG85rxoO+yRrC8GQeGIGuMbmHTJcMwuYYSFQ0lDpxhGIZhGP2DSx4wDMMwDMMwDKMTWBlhGIZhGIZhGEYnsDLCMAzDMAzDMIxOYGWEYRiGYRiGYRidwMoIwzAMwzAMwzA6gZURhmEYhmEYhmF0AisjDMMwDMMwDMPoBFZGGIZhGIZhGIbRCayMMAzDMAzDMAyjE1gZYRiGYRiGYRhGJ7AywjAMwzAMwzCMTmBlhGEYhmEYhmEYnWAJI+fhw4dYuXIlgoKC4OnpiSFDhsDf3z/LscHBwRg+fDisra1lr5UrVw4//fSTFs+YMQZZymn8zZs3sWfPHrx69QoWFhYoU6YM+vfvD3d3dy1eEWMKssbzGqNNeYuIiMCyZcvw/Plz8Xj27Nnw8fHR4tUwDGNoGLVnJDY2FrNmzULLli2xevVq8f/MmTMRFxeX7eeWLl2KdevWiY1v2ExuZCmn8fHx8ejYsSOWLFmChQsXwtbWFvPnz9fyVTGmIGtSeF5jtCFvZmZmqFy5MkaPHq3lK2EYxlAxamXk6tWrcHNzQ7NmzWBlZSX+d3FxEa8zjCZlKafx9evXR9WqVWFjYyO2tm3b4smTJ0hLS9PylTHGLmsMo015o8ekoJQoUULLV8IwjKFi1GFaL1++hLe3d4bXyF1Mr2fH999/LxaFNJn26dMHhQsXVjg2JSVFbFLIKkRWbktLo/5qTQ5VZUnV8ffv30eRIkVEyJYiWNZMA03JGs9rjC7mNmVgeWMY08Zg/9LJLUxx94qg0JfExETY29tneN3Ozk68nhVOTk6YPn26mFiTkpKwY8cOTJs2DfPmzROfy4pdu3Zh+/btsuf16tXDiBEj4OrqmutrYwxfllQZHxgYiC1btmDUqFHZnifLmuGjC1njec100fXcpiwsbwxj2hisMvLdd98hNTVV4fsODg4i/IXiW+WhWH26OWcFjZe6lski07dvX5w7dw6PHz8WMbBZ0blzZ7Rr1y7Da2ThIfe1MZOQkIBJkyaJjSxYhoymZEmZ8ZTATgvFgQMHomLFitmeJ8say1pW5DSe5zXTlDVdz22qYIryZmyyxjAmmTNClhia/BRt5ubmwpX84sWLDJ8jV3KxYsWUOga5imnLDpos6VzkN2OeQKVIJBJh0af/DR1NyJIy40kRmTp1Knr16oWGDRvmeJ4sayxrWaHqeJ7XTEPW9EXelMEU5c3YZI1hTFIZUYaaNWsiPDwcJ0+eFNYh+p9KDdLrWUEJxG/evEF6erpwOa9fv17ctLMrcciYBqrKUk7jX79+LRSRHj16oEmTJlq+GsaUZI3nNUab8kYkJyeLjaAx9Jjkj2EYJivMJEaullM99BUrVoh66F5eXhg8eDBKlSol3gsNDcXIkSNFSVUPDw+cP39exO5HRkYiX758KFmypLBa58XiY6yQW576YqxZs0Zh3Lkpy1JO4xcvXowzZ84IOZNH/vPMR1jW8iZrPK8pjynKmrrljejevfsnx5g4caLob8OYtqwxjEkqI4xmoHheSjqkWF9jd6czuoVljdEWLGuMtmBZY5j/YGWEYRiGYRiGYRidYNQ5IwzDMAzDMAzD6C+sjDAMwzAMwzAMoxNYGWEYhmEYhmEYRiewMsIwDMMwDMMwjE5gZYRhGIZhGIZhGJ3AygjDMAzDMAzDMDqBlRGGYRiGYRiGYXQCKyMMwzAMwzAMw+gEVkYYhmEYhmEYhtEJrIwwDMMwDMMwDKMTWBkxAjZs2IC6devq+jQYE4HljckOlg/DYPr06fj8889hqrCc5o1JkyahU6dOuj4NxkhgZcTAOH36NFxcXDK81rt3b1y8eBGGyKtXr9C/f394eXnB0dERJUqUwLfffougoCDxfuPGjWFtbS3ec3Z2Rvny5fH9998jJCREto83b96Im4q7u7sYU7lyZezatUv2Pu2rQ4cO4hhmZma4ffu2Tq7VEGF5+1TekpOT0a1bN/j4+Ah52r179yfHiYyMxODBg+Hh4QEnJydUr14d8fHxMDaMST5ocWVpaQkHBwfxm1WoUAGbNm3SyLHWrFkj5ikpaWlpGDhwIMqWLSvmM00fjxg7dqzGrk/fMCY51dY8xvdNRpuwMsLodEKtUaMGrKysxE0hOjoaFy5cgKenJ86cOSMbN2vWLMTExIgF3tatW/H27VtUq1YNHz58EO+7urqKmy1NtFFRUVi8eDH69OmDwMBA8b65uTlatWqV5aKRMR3UJW9E/fr1sW7dOhQpUuST46Snp6Ndu3biOI8fPxb7Wb58uXjO6Df0u8XGxorfbPz48ejbty8ePnyo0WMmJSWJReHdu3dx7ty5LGUqO1JSUjR2bozpzmN832S0ioTROvPmzZOUKFFC4uDgIClevLhkwYIFsvcCAwMl9LP8/fffEj8/P4mzs7OkX79+kuTkZEloaKjExsZGvG9vby+2s2fPSlavXi2pVKmSbB+vX7+WNGvWTOLo6CipWrWq5Ndff5V4e3vL3o+JiZF88803kqJFi0ry588v6du3ryQyMjLH46ub/v37SwICArId06hRI8n8+fMzvJaSkiIpV66cZPTo0Z+MT09Pl1y6dElibW0tOXny5Cfv07XdunVLYkqwvGlO3ug6d+3aleG1/fv3i2ulzxkCLB8fmThxoqRjx44ZXnN3d5ds375dcuTIEUm1atUkTk5OkkKFCkmGDRsmiY+Pl42j65k1a5akVq1a4nts2LCh5NWrVwqPJf2O6NqbNm0qadKkiSQ6Olr2/ocPHyS9evUSx/L09JSMGDFCkpiYKN47deqU+B4WL14svrPq1auL13v37i3GSr9n6fx38+ZNMR+am5vLfqeXL19+cr30PS9ZskTIOu2jffv2st9BH2A51e48ltN9k+Snbdu2koEDB4rvjH6bnTt3qnw9DEOwZ0QHeHt74+TJk8KisWLFCowePVpYNuQ5dOgQbt26hfv37+PEiRMivpXCkOh1cruS9Y62Bg0afLL/Xr16iWOQBYTc8CtXrszwPoUDhIeH486dO8J7QJa14cOH53h8RZD7W9FWsWJFhZ87cuRIrmKWKZSCYlXlrUAEHYtc03Xq1EG9evWy/G5MEZY3zcibImgchU2QVZ2+w3LlymHt2rXQV1g+PoXCpjZv3iy+E/qMra2t8G7RedJ3c+rUKfz2228ZPrN+/XpxfeShtbe3F56V7CCrddOmTUUoDV0f/U/Q2o/CYwoVKoRnz57h33//xT///INp06Zl+Cy9Rl4bqVwGBATgwYMHCAsLQ8+ePYW3hcZVqVIFS5cuFWFn0t+pWLFiWZ4TWdBJFsj6TuFi8+fPh77AcqrdeUwZDh8+jJo1a4rvhf4e6LxIZhlGZVgn0z1knZo2bVoGC8uDBw9k7w8ePFgyfPjwDFYxeeQtPGSNo8+HhITI3p89e7bMwhMcHCwsZOHh4bL3Hz9+LLGyspKkpqbmeHx1YmlpKTl06JDKFh6CrIJkiclMUlKSZN++fZI5c+YIL0lmTNEzkhmWN/XJW1YWxUGDBolrIsstyeP58+eFNffMmTMSQ8BU5YMsvSQjdD3kESGPA3lFsoJkhKzoUuh6yKsgZf369ZLy5csrPBZ9R2Shp2vfvXt3hveuXr0qcXNzk6SlpcleO3r0qPAGSL9z+k4iIiKyvR4XFxche9LjyXsBpNeb2TMi//dBMtCuXTuJvmKqcqqteUwZz0iZMmUyvNaqVSvJ1KlTlbgKhsmIperqC5NXyFoyb948vHjxQsSXU2Krr69vhjFkFZNCVjaK+1SGd+/ewcbGRiTOSpG3gkmPmfl4FB/6/v37PB9fFegcKY41N9Dn3NzcPnk9X758Iu57yZIl4hood8TUYXnTnLxlBSVAUwy21GpKXjqySO7fvx8NGzaEvsHy8R9t27bNMkb+2rVr+Pnnn4WXIiEhAampqShVqlSGMZnPkbwS0qpVtBFkkSfrOUHeM0oqJmsyeSRo3pJ+J3R98vJG60Hy1kghL4p8QjZ9h+SJof2QZZ++P/IghIaGqnT9iq5BH2A51e48pgzkScr8PLfnxpg2HKalZcj93a9fP8yePRvBwcFismrTpo242SgDTX7ZQZUvEhMTM9yE6JhSihYtKvZBky8dW7rRZwoXLpyra6LFl6KNQlQU0bJlS2zZskXl49FCYM+ePaJiiCLIhf7kyROYOixv2pE3eSpVqgRDgeVDOUhhaNKkCZ4/fy4W+aRcKPsdUdUqaXiQVBGRQqF8FP7VvXt37N27V/adFChQIMP3QYU56POKvveNGzeK7cCBA2IsfYbCkqTnmNPvpO+wnGp/HlOGly9fZnhO31luvw/GtDHsGcoAoRsKTaB0s6HJ7eDBgzh69KjSny9YsKCwVtGEnBU0aZIllm6AZMGjBfmyZcsyWG7ISktWW+nES5Yd+VK4ubkmRdu9e/cUfm7y5MmiXODQoUPFJEbfC8VbUxUQRZMtxUjTTYluuKNGjRKvUQzspUuXRKlC2qiyFsV0N2/eXPY5umnQRtAYekyWLmOH5U398iatgEQyRPsgxZceSy3XnTt3Fs8pTp9eu3LlilgEUB6AvsHyoRykgJAngqzdlJdBnld1QSVmV61aJfI8yCtDlZLoexs3bpz4bun3oUVfZkUm8/mRV5is5jS/TZkyJYNXg34nKtVKv4EhwnKq/XlMmfsmVQskZZoUHVKEKaenR48euf5OGNOFlREtQ3Xkf/nlF5G4SIl1NHmoskih0IBBgwaJ/dDN8fz585+MIQsZWfBoAqYbHIUqUWK3FFqs02fppkf19Cl04MaNG9A25NKl8Aea4GrVqiXOhZLPyc3bqFEj2bgxY8bI6qV36dJF3BiuX78uro+Ii4vDV199Jb5Peo0WCpR8SmULpVACKm0EHYsenz17FsYOy5v65U36vZAM0WKArNr0mEpkEnStdGOmBFg6xhdffIFFixZlkEd9geVDOf766y/MnTtXWK1pEUjXoU5of/Q9UBI1KSQU0kdyWaZMGSGHFD729OlThZ+nhSZZ00nGixcvLuRRvlwr/b61a9cWVmv6ruWt/oYAy6n25zFl7ptU+vfy5csi9GvEiBGiiEPJkiW19l0wxoMZJY7o+iQYzTJjxgxhsTh27JiuT4UxAVjemOxg+WAMAZZThtEe7BkxQm7evCncsqRnkuVmwYIF+Oyzz3R9WoyRwvLGZAfLB2MIsJwyjO7galpGCMWPUigBVVWhGNshQ4YIFzXDaAKWNyY7WD4YQ4DllGF0B4dpMQzDMAzDMAyjEzhMi2EYhmEYhmEYncDKCMMwDMMwDMMwOoGVEYZhGIZhGIZhdIJRJLBTw521a9fKaodT/W+qu25hYaHSWGr6Q70B/v33X9EgiWpnUy1zqm3OMATLGqMvHD58GKdPnxY9AipXrowff/xR4dhJkyaJBmXycvrHH38IuWMYdc5tBDVxpF4Y8fHxsLGxEX0wqG+HpaVRLDkYhlEzRjEz7Ny5U5Tk++2338Tz6dOni86o3bp1U2ksdR51dXXF+PHjRWMg6sJKtcapyVKlSpW0fl2M/sGyxugLJD/UzIwU2rCwMKU6fVPzPIbR5NxGtGjRQjRwJEWEusPPnz8fe/bsQdeuXbV8VQzDGAJGEaZ16tQpMcnRzVl6g6ZmRaqOpYmzR48eolOpmZkZ/P39RVdbmnQZhmBZY/QF6ohcs2ZN0WWZYfRlbiOo+zvNcVJojgsKCtLKdTAMY3gYvGckNjZWWAV9fHxkr9Hj0NBQ4SK2s7PL1VgiOTkZT58+Rf369RUen8JtaJPHyspKbIxxwbLGGDJkzd6+fTvy588vPCSNGjVSOJZlzbTQxNy2e/du7NixA0lJSUJhJs+cIljeGMa0MXhlJDExUfwvP1na29uL/xMSEjK8rspYar+ydOlSeHp6CuujIsg1TTd4Kb6+vpg1a5aaro7RJ1jWGEOFQmbIWp0vXz7cvXtXhM3Y2toqlDeWNdNCE3Nbp06dxPbmzRuRW+Li4qLw+CxvDGPaGLwyInUFk0XGyclJ9pigm21uxtLicMWKFcKtTDH95uaKo9k6d+6Mdu3aZXBHS7u5UpIfY9iQgiCFZY3RprypEwoDlELJ7s2bN8fFixcVKiMsa8aPpuc2KaQEe3t7Y/HixWKOywqWN+NGU/MaYzwYvDLi4OAgkn5fvHgh4u8JekyvZQ6FUWYsLQ6pyhGFzNDEmXkfmcnOlczN7Y0LljXGWJAu9hTBsmZaqHtuywwV7MguZ4TljWFMG6NIYG/cuLFw80ZGRoqNHgcEBORqLC0OHz16hHHjxolJl2HkYVlj9AVa4FGuUXp6uliw0eOsrMhxcXG4efOmiN2nsVR969ixYyIBnmHUPbdRGBcluJPckVxS6WnKHeEqgQzDKMJMYgRmB7oBr1mzBhcuXPik5vmyZcvEa19++WWOY8kl/M033wgLjXy4DI2Rfl5ZaF+ZE/IYw8PLyyvDc5Y1Rpvylh1bt27NEGdPlC1bVvQUoVKrpUuXFlWOqLTqzJkz8fbtWzGGEtjbtGmTq542LGvGg6bmNlJG5syZg8DAQCErzs7OQvHt3r07rK2tVTpHljfTm9cY08QolBF9hCdR48AQJlGWtdxBce5UjjQtPR1Ojo7C2ptT+JKpyxvLmvGg77JGsLwZB4Yga4xuMficEYZhGFUhG8yqVWsQm2KBQkV8cenqWaRLJAjIhbeAYRiGYZjcw8oIwzAmp4hs3LQZEbFJaPf5NzAzN0epijWxddl04SGpUaOGrk+RYRiGYUwGo0hgZxiGUQZK4l64aDFevAlBmx7DhCJC2No5oMvA0di8bSf2HzjIFXwYhmEYRkuwMsIwjElAzdfGT5iIfE5eaNNzGCwsMzqGHZ1c0ePLX3D77mPM+22+6DTNMAzDMIxmYWWEYRijhrwcR44cxZx589GwbV/UatJeYaJ6PmsbtP38G+T3roBx4yfg/v37Wj9fhmEYhjElOGeEYRijhcqMLl7yF+KS0vH5sAmwsbXP8TOkqFSq1QRFfPyxcs1S1K9bC506dtR5pS2GYRiGMUbYM8IwjFFC/TWmTP0VjgV80a7X8CwVkbTUVISFBIn/M+NesDB6fjUO9x6/xJKly0TDQIZhGIZh1AsrIwzDGKVHZOasOShXsxlqNGyj0KsRGRGClXPHiP+zwiqfNdr2GIb4VAusWLmKE9sZhmEYRs2wMsIwjFFBCsOSpX/Bt2wNlKtaL8/7o4pbTTt8gXfBEThy9KhazpFhGIZhmI+wMsIwjFGxc9cuxCeboXqD1mrbp7m5OVp3H4qjx07i33//Vdt+GYZhGMbUYWWEYRijgHI6tm3bjhu376FFt8FqTzi3trFFhz4jsGLVGty4cUOt+2YYhmEYU8VMwkHQGiEkJAQpKSm6Pg2DIyYmBoGBgeJxwYIFxaZLvLy8oO+wrAFBQUFYvmIVrB3cENCxHyyt8uX4mYVThyM5KRGpKcmwsXPAdxMXK3Ws6Mgw7N+4CP4lfNCzR3c4ODjAVOSNZc140HdZI1jejANDkDVGt3BpX0ZvePv2LX6b/wfye3nD0jIfXj67h0ED+qNy5cq6PjVGTwkNDcWu3Xtw7/5DNGjVA35llJeVlOQkoYgQ0v+VwcnFHT2/+gU3Lx7Dz7+MQ7OmTdGiRXPY2trm6hoYhmEYxpRhZYTROfHx8di3/wAuXrqMZp0GoGjx0uL1yPAQbNq6FOcvXMLnPbvD3d1d16fK6AmvX7/G3n378eTpM1St1xp9v+sNCwvtTWfmFhao3qAVyldrgBsXDuPHMT+jXt06aN26FZydnbV2HgzDMAxj6HCYloZg93LOxMXF4fCRIzh95izKVm2A6vVbiVKq8kjS03Hv1gVcO7Mf5cuVQ6eO7ZE/f36tnaMhuJdNSdaeP3+Obdt3IjQ8EtUatIF/+eoiuTw3zB8/RHhHCArrGjVtRa7PKykpAXeunsadKydRuVJFdO7UEW5ubhqVt8OHD+P06dN49eqV8B7++OOP2Sr8y5cvx82bN5EvXz60bNkS3bp1U/n8TEnWjJ3Mspaamoq1a9fi/Pnz4nmDBg3Qr18/WFhYfPLZ7MaSfKxcuVIUeqCwW/o76NChA5o2baryObK8GQeGcB9ldAt7Rhid9IDYf+AgzpASUq0B+nwzBda2dgrLqpL1uUzlOrh38wJ+nTELZUqXQvfPusHV1VXr587oBlpMr1m7Di9evUadZl3RomR5veqIbm1tixoNWqNqnea4e+McJk2ZhmZNm6Bdu7a5VpZyguS/S5cuYtEXFhaW7dhVq1YhNjYWixcvRlRUFKZOnSqU+kaNGmnk3BjDY+fOnXj48CF+++038Xz69OnYtWtXlkprdmPT0tKEbI4fP17k/D158gQzZswQnu1KlSpp/boYhtF/WBlhtAotnFauWgP/CrXQ57upYhGXGeqGTU3oXFzzw8Lyo4hSCE7FGo1Qvmp93L15HhMnTUH7dm3QrFkzvVqUMpqpkjVj5ix4l66Oz4cOEAqqOmjdqhVatWopHpMMpVjb401IXJ72SfJaqVYToTwf27UaUdGb0LdPb2iCWrVqif9fvHiRrTKSlJSEixcvCgXE3t5ebK1bt8bJkycVKiNkjZa3SNP3I82J4b834+TUqVPCuyE18pCiu27duiyVkezG2tjYoEePHrKx/v7+KFeunFBeFCkjLG8MY9qwMsJojSNHjuLoiVPo0Pd/cMvvqXCctCv2oB9mwT3TOIrVJ6XEv1x1HNmxHM8DX2DwoIFZhhIwxgEttOMTk1Gtfiu1LkwOHT6MvXv3qCVMKzP5rG3QrGM/rF84XmPKiLK8e/dOhNX4+PjIXqPHZMlWBL23fft22XNfX1/MmjVLqyGSjPYgrxn9nWWWESoQQV5JOzu7XI0lkpOT8fTpU9SvX1/h8VneGMa0YWWE0UpY1oaNmxD4Kgjdh4wV/Rryio2dPTr0/g6nD24SVvNhQ7/iBHcjxcPDA4U9C+HwtmVo2Lon7B31P0E8+N0rHN+9Bm3aqK/xYl7+/qytrTMo7LRgTEhIUPiZzp07o127drLnUiWQYvhJsWEMH09PzwwyQsgrEuRBI0hO5F9XZSylpC5dulQcq2bNmgrPheVNfdB3vnDRYgS+eCFyLuvUroPu3VXPD9OUrDFMVrAywmiM8PBwkRdy6vRplK3WEF369xKeDWV6PxAbFk/NtvcDhes0adcbD/65jMlTfxWJwy2aN0ORIkXUfi2M7qCFyf9GfIsTJ05i67Jf4eVdEuWqNURhH/88eUqkxRLo5p0vn02ezzM1NQXPHtzGveunkZIYhy9690T58uWhayhshqzTFMsvVUjIgp1dKWIrKyuxZYWua57cv38fzwMDUbpUKZQoUUKn52IskIxI5cLJyUn2mMgsJ8qOJTlZsWKF6AFE+SPZ5U7ps7wZGpSPGRGbjB5fTUB6Whp2rJ4DPz9fVK1aVdenxjAKYWWEUSt047lx4yauXb+BmNg4lK5UB58Pmwhbe0eN9X4oU6k2Spatige3L2PRXyuRmpSA6tWroVrVKihevLjGEogZ7UG/YfPmzdCkSWPR/fz0mUM4unMlfEtVQomy1YRiourvPHz8wjyfV3JyEl48voNn92/g7YsnKF++HPr07IqSJUvqTaw7VbIhJeTly5fi70GaZ1KsWDEYIsvXrMPrFAeUuXEbUyf8ouvTMQqocSd5lkkuChUqJF6jx/Ra5rArZcaSAkEVtSg8ixSRzPtgNMPJk6dw5txFdBs8RoSKEu17Dcfa1XOEslehQgVdnyLDGK8yoq6ShKqWy2Q+Jhc/evQIV65ewz//3IGNvSN8/CuhYbt+cC9YWGvnQTH/FWo0FFtMdASe3b+F9Vt2IvTDW5QuVRo1a1QTvyeVNc0LLGu6xdLSUiRu00aloalU7ZVrx3Bk+zIU8S0FH//K8C1VUS2hgIqIiQzH0we38OLxbYQHB6FChfJo06wBypUbKs5PW5Cngzb6G6TFH3k/SCHLfA4UolW3bl1s2bIFI0aMENW0SPbkk4wNBQoRioqORpJ/E7x7tFtcOxsb1EPjxo1F7kbp0h/7PNHjgICAXI0lRYTuCxMmTBDKC6NZaB7YvGUr7t5/jK4DRmcoDOPk6oHO/b7HqjW/o02rFmjWLEBvDCUMY1R9RrZu3Ypr165h7NixsjKDtFjJqgpITmOvXLki/lCl5TJzu0A09vrotAg4cvQoDh8+Co9CReFXthqKl6okcjnygjp7P0i9K6+ePcCzBzfw8sk91KpVE5916yoLNVC1PjrLmn5C10/hO9du3MSdO3fg7FoAxctWg3+5amrJMQn78BaP713H8/s3YW4mQbVqVVC9WjWRuKvOxbAq9fhJvuSTfomyZcti0qRJQtZooUhVjqRhNMuWLZP1GWnVqpVB9hmh8/9j0wGEe9VB/tdn8POwL4QXilFPn5E1a9bgwoULnxhPSHaIL7/8MsexJCPffPONsMTL/23QGOnnDUXeDAH6jhYsWgyX/EXRqE0vWQXKzCTGx+Hw9mVwcbAWRV+0qSRynxHGJJSRYcOGiYmwdu3a4vmlS5dEmUGqqZ/bsXSjJ9czLxCzhr633fsOo2PfEbBz+Bg3rA4eXtiRqdxqgTyXW5WSkpKMk3vXw9PdFl/07ZurSZRlTf+hKY1Cki5fuYqrV6/BztEFZarUh3+FGrCyUt4zFhcThXs3z+PRP5dgZ2eDurVroUaNGiKh3lRv2rqWtXl/LMS5cDukuRSDVegTtC1pj0H9v9DZ+Rgy+i5r+iBv+j7PUR7d3v0H0LDN5yhRpopSn/nnyincunAYX/TtjWrVqmnlXA1B1hjdYvBhWposSagMplofvUyZMjh4+AgOblmCEuVrwte/ApxdPfSy3GpCXAxePr2P5w9uICToFbq2G5qr34ZlzTCg74JKg9LWs0d3oeidOnUGf/++C6Uq1kLV+q1gl00OE4X2XTuzDx/eBKJRowbo9vOPXKlND6B+KfcfPEBayQ7ieYpLMVy5eggDvujDoVqMSUFK2tK/lsPc2gGfDx2vdE4mzY2VazeFT8ny2LFzJS5dvooB/b+QVUNjGF1h8MqIpkoSKoup1kenUn0rlv0luuuePnMWJ3cuQ2RUFDyL+MLD0wcFi/iioJe3LIlOWxWOqGFiyIc3eP8mEKHvAhH0+jkszM1QtWoV9O/dDVWqVMl1TxKWNcOErHKUM0FK4N59+7Dlr6moXLs5KtcOyNBAMSkpAReObEPwm2cYOKCfCCvh/jX6AzVuTHIsQs2GPr5gaY0k2/y4deuW1iy8DKNrzp47h+3bd6J+qx7wL189V/twcS+AzwaNwa3LJ/DLuPEibEsfKv8xpoulpioqUUgKlXYdPHgw3r59K2JMvb29DaIkoSqYen10R0dHtG/XVmxkuQwMDBQVVJ7cOokTu15Q/V2hlHh4+QhFpWBhH5nCkdcKR2lpqQh9/wZBbwIR8i4QwW9fIjEhDoWLFEHJEsVRpVEtlCjRO0NsbHBwcK7ro7OsGT6NGjYUuR4rVq3GpqUX4OTyn8cjOOg1mjVtgv8N6y+UEFVlRR1wPf6sIePEngOHEeNWI8Prkc4lsHPfQVZGGKOH7q8rVq7Ch9Ao9Bg6HvbZhEeTUY6aB7u45leYQ0KGmKp1m8O7ZHmsXbcU1atVFvmU7GVkjEIZuX79OhYuXChqWlMJTlJGqOoNxcWPGzdO70sSqgrXR/8PSowtVaqU2KTQApzi9589e4YnN0/g2M4XsLK2Eb0iiviWRjG/srCxtVc6Gf3Ni8d48/wB3r18jOjIcJniUalBDRQv3gPOzs4a+x1Y1owD+v6//eZrvH79OoMSR79ZgQIFxGP+PvUL8sBGp5oj3dYlw+vpDgXw/vkNYfAqXFh71fsYRpuQwWneb7/Dt0x1dG47KINHNytIEVk5dwwG/TAL7vmzN3DQ+z2GjsOpfesxc/YcjPh2OIdtMYavjGzatAk///yzWJAOGDBAFk5CCzFDKEmobLlMRvmFH+WX0CYlMjJSlH389+49bDm2A3aOzvCvWEf0C8kc1kVNm549vI2Hty/iw7sX8C/pj4oVyqFbuyYoWLCg1nMlWNY+hfJjvh89BolJiRg0cAAa1q8PfYfkxlD7bJgiO/ceQLiz/6dvmJkh0rkk9h44jGFfDtLFqTGMRqF75eIlf6FR294oXrqSRo5haWmF5p0H4J8rJzFx0hT88P1ImRGNYbSB2lc9FJolbxknKOSBFlyaomvXroiJicHIkSPFc4r1ppAWInNJwuzGEjt27MgQl9+nTx9ZuUxGPbi4uMh6RdAinCzUZ86ew7oF41CqUl1ZcnEqlWu9eQ5+xX3RrWMrIVe6diGzrH3Knv0HEOXsh3gXX2zash11atVS6MFhGFWJjo7Gk2fPZInrmUl288X1m/uQlNRH9FRhGGPh1KlT2LPvIDr0GaGVvl2VajWFi0chTJ85G4MH9kfFihU1fkyG0UhpX+qpIF1UkWdk9erVuHfvHjZv3oypU6eazLfOJQlzZ2GnBoHkLZBC4X66jKM3hJKEupS1N2/eYMKvsxDi1wawsIJT0A20qlwMfXt9rpPzMXT0Xd50IWsHDx3GutN3EVuossIxzu+uYminRqhfr55Wz82Q0XdZM+X7KOWHrFqzFu/eh6FNz2GwtVO+J8jCqcORnJQowppt7Bzw3cRPy87nRGRYMPZvXIjataqjS+dOeTYCGoKsMUbmGenZsyfmzJmDJk2aiHjsjRs3ii7T1PmXYbKDYvapGRtjGFAu2My58xHuWUsoIkR0wUo4eeEoypYujWpVc657zzA5cebCZcQ7l8t2TKxDUTGOlRHG0Hn+/LkIyypRvha69O+fY35IZqhpMCkihPT/3FTbojyS0/s3YPKUaRj+zTCu2shoFLXHvJBbj8JMyJpRrlw5sWAhbwk9ZhjGOCBDw4zZ8/DB3g9pjnKxxeaWCCvaEIuXrxSFCxgmL9B9JCQkGOk2GRPXM5PmUBCBz55x4QHGoOfU7dt3YMGipQjoPBC1m3ZQWRFRJ9QglvJIKtRpjam/zhAhY/z3xWgKjWTKUgnfQYM4mZBhjBG6IS1augzPE22QWOjTpGKJtQNCC9fHjDm/YcbUSXB1ddXJeTKGz7t372Bm7yYS1bOFFm357BAREQE3NzdtnR7DqC0c7fc/F8Ddszh6fTNJKAL6QomyVeDlXQLHd63G9Ru3MGzolxnK5TOMXiojZ86cUfheo0aN1H04hmG0zJFjx3Hz6VvEFGuscEy6vQeC3Spgxpx5mDF1MjcPZHJFaGgoUiyVKzOabu0oxrMywhgSjx8/xsJFS9CoXR/4aahaVl6hojLte3+LO1dPiWpbP47+XlSzZBi9VUYOHDiQ4TmVcaWKQlRGk5URhjFswsLCsG3XHoQXb52jtTrF1Qfv3n3A3v0H0blje62dI2M8UJ+iFDPlblNp5layxqIMYygeEVJEOvb9n9qqZbVu1QqtWrWUlTBPsbbHm5C4PO+X9kXVtpzdCmD2nHn4ddoUWXNfhtE7ZWT27NmfvLZnz54MFZIYhjFM/t6wGZHu5QFL5UqoRhWojAOHDqJFs6bcSItRmY8x6sr2EjLjmHbGoDh67DiqNWij1rK9hw4fxt69e8RjS6t8GDVtBdSJT8nyeOFXDlevXkXDhg3Vum/GdNFKd7X27dvjq6++QpcuXbRxOIZhNMCHDx9w9+FjJJdoq/yHLK0R61Ice/cfwOc9umvy9Ewy4XXt2rWiHLa0j02/fv2yDIlbtGiRGCffUHP8+PHw98+ikaAeQedrBuV6VNE4Q2sYaqjylNPYw4cPiyqar169QuXKlfHjjz9q+WoMAyqZa4iG2rR0wztnRr8x11ZMJMMwhgs1LV3013JEeFQAzFSbNuI8yuL46XMICgrS2PmZIjt37sTDhw/x22+/ie3BgwfYtWuXwvEtW7bEunXrZJu+KyIEKRcWUM7bYSZJY2VES/KU01gqWkHGx4CAAC1egeHRulVL3Ll8DM8e3IYhQJ7HW5eOI/Tdc9SuXVvXp8MYEWqfuckCQrGF8s17yKJKjRAZhjHM8qoLl/yFwGggpbCP6juwsEKYZy1MmT4L434ajcKFNd9J2BSgUptkjZZWK6PFHykZ3bp10/WpMUYuTzmNrVWrlvj/xYsXIs+MyRoXFxf8MvYnLFi4CI//vYy6zbrC2S1v/Tys8lkLpYF6jFCYlrr48O4lzh3aDFcne4wb+zPy5dOfil+M4aN2ZaRNmzYZnlOCk4+PDwoVkutFwDCMQfDvv/9i2ao1CLP2RIzXxwVGbqBeJEGojgnTZqBVswB0bN+Wb2Z5IDY2VizyaG6VQo+pmhQlcdvZ2WVZ6ZA2WkBSU9q2bdsq7KxMCqh852syMNna2soeawu6lmSolsCuzfMzRXnKjezlhL7IW2buP3iAcxcuw8nRAT0+65rnTuRZUaBAAUyeNBEXLlzAzr/noUBhX1Sp2xIFc2P4ATB8/EKEhQRh5dwx6P31+DydGyk1r57dx80LR5CSEIOePT5DpUr6WfGLMWzUrow0bqy43CfDMPoPxTDfuHED23btRWh8GsIL1ES6nXve9+tYCMF2bbDr6l0cPT4KzQOaomXzADg7O6vlvE2JxMRE8b/8wk9aICAhIeGTBWHr1q3Rt29f0R/g6dOnmD9/vljktWvXLsv9U8jN9u3bZc99fX0xa9YsrXdhDgoORbKVo1Jj48wdEBYeAU9PT42flynLk6qypwz6Im/ykGK1YPFfCHIoCcfYR/D18UbnTh01drzu3buja9euOHfuHLZu24a4hESUqdIQpSvVQj5r1apWubjmx6AfZon/c0N8bDTu37qI+zfPwbtYUXw9pJ/I/WFFn9FrZeTgwYO58powmoMsGnTToMmDy+8xyjaYO3byNC5cvIQku/yIdCmP9AIe6j2IRT7EFKqKGI9y2HH9MQ4f/wXFfX3QpnlTYXHjfiTKIf2bpgWTk5OT7DEhtSjLU7x4cdljyhXp1KkTzp49q1AZ6dy5c4b3pIsQKkVKycvaylM6e+480ooql3eQ4uiFw8dPomWL5ho/N2NAXmlTRZ5UlT1l0Ad5y2yQmT57LsIciyPVwx+RLsWwbPXf8HB3Q4kSJTR67FKlSmH8uLF48+YNTpw8hXV/jkPR4qVRtlpDFPYuqZRCYGFpCff8qinl6WlpCHz8L+7fPIuwD2/RoEE9jBs7Bu7uHw1R79+/z/U1sYGA0Yoycu3aNaXGsTKiHejGsGjpctx/+AiS9DQ0bdIIvXp05+RO5hMo5OL8hYs4cuIUohNSEOXogyTfVkqX7s01ltaIL1gB8QXKIzz6HZ5u2Aer5atQs2YNtAxoIvoSMYohDwctEigmXxoCS4/pNWUs0zktaKysrMSWFdoqn3v5yhUkWDlBYqXcAldi64yID+kitLB8+fIaPz9Tlae8yp6+ypsUUn7m/r4AD8PSEO9Z+uM5WNkgtEgDzJj7O8aM+g4lS5bU+HlQbt0Xffug1+c9cfPmTZw8dQDHdwWjXLUGKFe1PuwcPiqCeSUqPAT/Xj+DR/9cFtfVpX1LlClTRhaSxuWyGW2gltXpxIkT1bEbRg1KCHXHPnj4KKJdSyK+dGdAkoaj/9zG5Suj0a1zB9SvV49j9RmxeNi+ex8ePHyIBGdvxLpUh8Qzd+FS9rc2wiydrJcSSMytEFell/IfNjNDmnNhhDkXBtJScPhpIC7fWggnGwt0btcadevWZSU6m5BYCm8pXfrjgokeK6pedPHiRRFmQZbr58+fi95PVF1LX4mIiMDqvzcgvFhTlT4XXqAqFv21AnNn/sp9bTQoTzmNJc8CbeTdosVscnKyWNzq+98y3UOnz5qL54k2iPGsnqGxa7qdG0KKNsTM3/7EsMH9Ub1aNa2cE31nNWvWFBv9XZw6fRpbl01DwSJ+qFKvJQrlIreEfpOXT+/h9sWjiIsOR7OAJhjQk/9mGN1hJmG1VyOQe1k+IU+TUC33vQcO49Y//yDe2Rdx7qWFJUces8RoOIU/hG3sO9SvVxdtWjbXaTyuoeDl5QVjkjW6mS3+awWevX2PCJcySHUtpnKp3sw43Pj7/5URQGJugdhq/ZBXzBMi4BT+CA5JoRgysB+qVqkCU0AVeSML7po1a0Tia+ZeD8uWLROvffnllzKD0cuXL8UC0c3NDU2bNhX9n1RNyNXGvEbeunGTpuKVnT9SXL1V/rxN2BP4SYIwafxYDlFVQdZUkafsxhJbt27NkANClC1bFpMmTdLb+yjNjZN/nYG31sWQ6PFRycoKs6RYeLw6jZ6d26NFc92ULiYlj/L69u47IEJf6zTrCq9ifjl+jpZ7zx7expWTu+Hh5ooO7dsKhVLTuSCGcB9ljEwZoRvJxo0bce/ePcTExGRw8a1evRqmgqYnUboZXLt+Hbv2HURodAIinUsgxdUHMM8h5j4tGdbhz+Ac+RTeRbzQuX0blCtXTiNVQowBQ5hElZU1+tsc/fM4fHAuixQ33wxWP31TRuSVaPc35zGodzfUr1sXxo6+y5um57Xg4GBMnTkbQfYlkOSW+9h8u5AHKJIWhPE//yjKpzKGJ2vaVEZIERk3eSqCnMoppwCnJsHj5Sl0bROAdm1aQ5fQWmvjpi2wdymAxm17KQzfCg99j5O718DR3gaf9+yu1VBYQ5A1xsiUkT/++EP8YVPZyAULFuDbb7/F3r17RYMces1U0MQkSq5uajR17uIV3Lp9G8kOhRDlUhLp9rlIMpZIYBH9Dq7RT5EvOQp1atZE3do14efnx0nEBjaJKitrFHf8x8b9CC+s3kV9j4IhshsyTSY770Vi99Wnatu/RXQQqloFYcJY4+/irO/ypsnF4fUbN/DXijUIKVhdhO7lFauIF8gfdgcjvhkqrPK6gsrg3r59+5PYe1oM6rLxpL7LmraUkbi4OPw8fhLeOJZGiosKnri0FHi8OI5+n3VE40YNoUtItih8a/eefWjRZRCK+JbK8P6Dfy7j8vGd6N+vL6rowMtsCLLG6Ba1B3DevXsX8+bNE1U2yNpeo0YNUaZv7ty5JqWMqGNyobrtgYGBuPfgEe49fITw8HCkOxZElK0XUku0E83kso/hJ0u1ZdYx/P8fqx9KN/3UROx9+Apn/1kPs9hQFCxUCOXLlEaZUiVFFR4uvWoc0ILMKW0j4kMeItGjlNo8I/sPH8OBg4dylzOSA+bx4XD7cB3thwxQ2z4Z/YLKwa5c8zdu3HuCMO8ASKwd1LJf8hS/t3HBnEXLUb9GFfTt1VNr+XKUe0AKyIWLl/H23Tv4V6gFS8v/ji2BBGcubEdKUhwa1q8n7pMcNqt9qOLklOkzEWTnq5oiQlhYIdS7Cf7esgOODg6oVq0qdAWFWTVt0gSl/P0xd958NOnYH8WKfww1u3vjHO5fO4kpkyfyvZwxHWWEYpKp2gZhbW0tbjRUZSMoKEjdhzIq6Ob16NEj3L3/EA8eP8GH9+9hZm2PJBs3xOZzQ5pTVUjyOyq1gCRFRKqMKIWlDVLy+yME/sJjEpoQiYd3guF48wks48NgnpYMryJFUL6UP8qWKSUqbnASvOFB8fMzpk7CspVrcPfxQUS4l0OqS95zRtSpfEgxS4iCS/g9OKdF4ZvvhskSZRnjguLel61ei0jH4ogv3iLPspiZdFsXhBZvhRMP/8XN0WPw9ZeDRViqJqzr1L/l/oOHuHfvPqJjYuBTsjxK12iBZj7+MMsiDLZW43aICP2AR3eu4MxvfyIlORGlS5dC2TKlRXlXDw8P7uugQcjYN2POb3hj4YlEj1x6qCxtEFqsCRatWIue4eFo3ixAp78ZVeD6cfT3mDx5CqyoN4lEAktLC0ydMlm2LmMYkwjTmjBhAnr37i0m09mzZwtFhCq40E2HPCamgrLu5bdv32LJitUIev8eqQ6FEG3lhnSH/Ei3cc71jVntMfzpaSKh2DIuBE4p4TCPCYa/f0kMHTzA6C0txhrKQEUPNm/fhYdPniLWpQQSKD5f0+V8c0KSDouot3CLfgoHs2RZ9TdTymfSd3lTV9gMhS4tXbEaT9+GIsyzJiQ26ilTmqOXLegqKvj7YHD/L2Q9MlSFrp+KATx79gxPnj4X1cnoJupZtAQ8vf1R1LcUXNwLqLzfxPg4vH7xCO9ePELQq6eIjYlE0SJFUbKkH0r4+QkvtToXlPoua5oMdz546Aj2Hz4iqq+lkEEmr6Qmwf3dZRR1scaQAV/ovDQ5JbhLIeVI10qtIcgaY2TKCJUMpcUD/TFSk5zly5cL78gXX3xhUtZNZSfRjZu34uDJc4gtXBNpDgVyTkDXdQx/Wgoso9/B4fVlfP3lQNSpUwfGjLHfsCm/69CRYzh99iyS7Aog0rmkUIa1iVlKImwjnsIh8hlKFPcVRRXImKHrG6gu0Hd5y+vikBZJ+w8ewp79hxDhUVGthRSUQiKBddhjuIQ/QI9undGsadMc5Sw6Olrk6pHX4/GTJ4iOjkEBz6IoULg4ChXxhWeR4rC2zb6/xsKpw5GSnCQeW+WzxvDxC3M81bTUVIS8f42g188R/PY53r8JpG8QfsX9UKa0vwi7pD4fuf070XdZU7cyQnMdlb4/ceoM4h2LIjp/ebUbYCwiX8Mt9F8U88yPrh3bcXEYA5I1xsiUkZEjR6Jhw4Zik3buNEWUnUTp5kxNI0+cuYDnz5+JeOkEG3ckUGiWvQck+exVvlmrzTMikcAsKRoWcaFwSA5HvoRQWKQli4ZILZo20ki4g75hKjdsqs5G3kuqzhYcGYtIl1JIcfNRe9hMZku1c8RD2CaEIqBJY7RsHmD0njZDl7e8yBp1lJ6/YBGC0+wRWbBKrhaCeeppI4dZSgJc3t9AYXvgf8OHoWDBghnej4yMxOnTZ3Dl6jUkJiWLDthe3qXg5V0CTi6q39fmjx+SQRkZOXV5rs47KTEBQa+e4e3Lx3gb+EB4TypXqoSmTRrDx8fHqGRNHXMbffbWrVs4cPQE3rwLQoxzcSS4ldSsF5iKw8QEwTXqKayTo9CoQT0xvxUooLq3zFgwBFljjEwZoeZaZ8+eFV1wybpJSglV0tJkvXdaSK1duxbnz5/Psua5KmNV2Ze6J1H6KcibRLHHdx8+xuMnzxAVFQkzezfEWLkh2S4/0shqbW6pmRt2ajIsYj/ANjEUdknhQEIk3D0KoIx/CZQrU0pU2jI1BTOrWvzGIGvZ8fr1a+zYsw//3nuAKLfSH0usqsFjJ8U8Nhhu4ffgYpWO7l06omaNGlzBzUBu2rmd1w4cOiwU3bBCNZHm5Jnr46s7BNUy8hXcgm+ib8/usopIdP/avnM3yldvhFIVa8HZNRfVCrNRRiyt8mHUtBVQB6ScPHtwC3eunEDRwp4YNvRLpS3x+i5reZnbKHTu0NET/1910hPRTj5IcyiokmFPHYovKb3WEYFwinkBN0d7tGreFPXq1jG5/jeGIGuMkTY9jIqKEg2Rzp07Jyxi1D2UyvxqAmqwRN6FsWPHiufTp09HrVq10K1bN5XHqrKv7KCEfYpNzQy51OW70GY30Urd77Q4fPT4MW7duY8XLwKRbmWHWNsCSLL3Qrqdq5hg6UdMx383IQv8FzOaFWk0lmL0Y4PhEP8OtvHByIc0+JUsiUrlSosYZQoBoEWi/PnSAjo7kbGystL5WDpf6Xcn7QKc27He3t4mI2uZx1JYw47de3HznzuIdC//sdpMbmVN9AyJgkfIbXjYAL26dxVhJvIhJpnPwdRkLSt5M/TFIX1/fyxagjsvghHuVQeQqyilLz1taMHo9uYC6lT0x5CB/fHD6B/Roe+oXOV9aFsZkUIyuvaPsfj5xx8+8fIY8gJRFXmj7+DKlavYsmMXopKBCEdfpFLPkByMd9qSNfP4CDhEPYNN9GvUrlUTn3XuaDI9cAxB1hgjq6YlhcIt2rRpI/JENm/eLKy/mlJGTp06JSzKrq6u4nmXLl2wbt26LBd1OY1VZV8ETZTykyUtNihhn3qrkJcjM0WLFkXr1v81SVq/fr24YWeFp6en6JJMiYu0hQQHw8NFPoEx5v83IDLZDGeTPi4WiSZ2b2FnnvV+Y1KAf54HwTLmPXx8fVHMuyCSkz9eL/H82TOxEZQw2avXfxah/fv3ixtEVpC1h3KDpBw+fFhhFTVamA0cOFD2/Pjx40LpUoS08y9x+vRpUfJYEQMGDJAtKEnuHj9+rHBs3759xe9FXL58Gffv38/wPnWuNiVZk0J/s1T20tIMqFm5wv+/+kr8G5GWD+cS/usDkZ2sRadZ4XRcITgG34FLQhDq1Kgq9ktKGG3ymLqsZSVvhgwpW7Pn/Y67YWmIKdpQu7khKiCxskWYT1Oce3AFSUuXoWPHDti7YQFa9xgKj4J573dCtG7VCq1atZT93aZY2+NNSJzavCMn9/4NX+9iJhsKRMbPmXN+w7t4CSI9qiHd9r/7mb5AhsNou+qILlAZR548wZWfx+GLz3uiYcP6uj41hjFOZYT6YZBHhNzd9JisvZq6yVJXaarMIh8vS4+pbB+Vy7Wzs1N6LN08ld2XlF27dmH79u2y59RTZdasWQrPlxZRtPCTkl3yIZXPlR+bnfvdwSIVBZ/uQ7yTN2IpJjYb7C2Bqd/1R9WqVcUxFi9erHDRR54R+XOQtxpnhs5Pfmx25X/puuXH5uS2lh8rXdApgjw60mPnNJasiPb29uJxVr+vPCxrH7FITRRx0UqVmZakoeDzw2jXshkGDZiFlStXCmUky/2yrBkVlKj+IDgeMYXr6K0iIsPMHFGFa+PG49OoVL4cBg3oixUrF6BkxTqo2bAtLOQ8drnh0OHD2Lt3j9o9I88e3MaZgxvRonkztGndyiSLPhAL/1qOx5JCSC6a/b1PFdq2aa2ZQjAWlkjKXwbBLr5Ys2kr/P1LiHmEYUwZtSsjU6ZMEf0yKlSogK5du6J69eoa7UkhXdjI39ylN3yq4iX/ek5jpeEYyuxLSufOndGuXTvZc+nNoEOHDlm6l+l9eQtunz59FF5b5rE9evTIdixd34mTp3Dg8FFcdfJGXP5yoiyv84dbcE6LRKd2bYRiSIsxshbTYpggi7iiUJTM59CqVatsw1bkxwYEBCg9lvIl6tevr9RYykGi61AELeilvwPJHyld2VnUqFoOUalSJSG3imBZ+3huy1evhfvLUwgrUk8kgp6Kz8J6LJHAJvwJPGID8csPI4RnjwwTLGvKyZqhQ7/F/oOHEenbSq2KiMYWiISZGSIK1cC2XXuwcP5cTP91GrZs3YZNS6ageddBKOilPyF0CfGxOL1/A5LjIjD2px9NfjGblpaO9FyGYymCGrke3L9PrSGB8tA+SQmmkE2GMXXUroxUq1YNI0aM0FpVHKmVk6zJ0rrx9DgrS2VOY6Ux3MrsS956m5UFlxb7ihZH8q/Lx8jndSwtZju0b4eWLZpjxeq/ce36TrEobN+2LTp36pDB2i2/35yShw1trPx4uuacEjqVHcuyBjg6OmLUd8Nx+OgxbN29H6HeTZFGFd8y7gjOQTdQwhn4cexUoVhJ920I8qMPsmbokDIucoXUXLVI4wtEawfZ3yH9Dff7oq8IvVu2/C94+1dGrSYdkI+ayekIkp8H/1zG5RO70LZ1KzRv3syo5UhZvvlyEKZMn4WQpHDE5K+Q59wkjULVtqLficIJXdu3Fo0KGcbUUbsy0rZtW2gTijOnCk/U30RqHaLH9Fpm67IyY5Xdlz5jbW2Nb4YOAUAboy5Y1v6jVYvmyO/ujkUr1iDUt7mIu5fiHHQdVYs4YMTwr7lKlolCC3lR2CA1SffNNFXALCn2k78/f39/4SXZu28/1i0Yh4q1AlCxRmNY22QflicPlfMlRSI1JVmEaakKGS+oata1M/vgWTA/Jo7/xeQqG2YHfRdzZ/6KPfsO4PCxg/8frlwKkny5n0slwtMigVl6GiRmalgqSdJhGfkarhEPUdjDGUN++l7nzREZxugT2LVJ48aNRTy9tKkiPaawjdyMVWVfjOnBsvYf1apVRf+EeKzeslcoJBTmYh32BH5O6ayImDgUutamdUvsOH0DkWrMGVH7AjHDziVwfX8N3Tp3+OQtCjXu1rWLyM04eOgw1i8Yj2J+ZVGman0ULlYCZjl4J6jJYVhIEFbOHYPeX49X+pQiw0Pw4NYFPPznEor7+uDrrwar3E/EVCCvcbcundC2dUscP3kKBw8fRaKVEyKcSyDN0VNlGaRSvmYJUXC4uwPxZf4Lj1UVs+T4j01do56jVMmS+GzA1yLfj2EYLZT21SZUIWjNmjWilHDmfg3Lli3LUCEnu7HKvK+r3g+M/vQZYVnLyG9/LsTFDxZIcimGgs8P4bdZ02WhZ4zmSmCqs+eNJmSNrPlU4eheWBqiC1VVm0IiXSDGlu8Kia2awoEl6XB5exk1/Arg22Ff5ZgITt8BNQk9ffY83r17B78yVeBfoSYKFSmu8LPUUT0yIgQurvmzTYiPjgjF47vX8eTuVVEAokH9eqhfv57aQ5+NvYcSyR/1O9t78AhevHqNWGp46Oqnkrck17JGZfOj3sI1+jlsUmPQPKCJaHxoqk1dubQvYxLKiD6i6wUiYzqTqK5ljZK4v/9hNCRmFujcqSM6d/yvRDCjOXlTZ88bTfW0oUXpXytW45/n7xDhVROwtFGpT01WY80SomF/fzfiynaCxNYpy542Oe1XfixZrj3eXUSdSqXxRe/Ps8zByK73TFxcHG7evInLV6/hw4dgFC9dGaUr10UBz2KQkAcnm1usheXH/cZGR+LB7Ut4dv86kJ6KmjWqo0aN6hkS0zXd08aYeyhRdcOTp8/g2IlTSM7nhEgnX6Q5en2iIGeWN8uESIWylpW8CS9I5DPYR72EX3FftGkRIJo/c78u/Sn+wOgnrIwY6QKRUQ+sjCgHHZ9uQBTOYqrlRbUtb8OGDRPWZqr4RVy6dEn0qaFS3XkZm11Pm7/++kupnjarVq1S2NMmNM0GFxP+K5/c0v4lrM2yXuhk7mnTzO519j1tEorInje2fQMni6z/LuLTLXE8rgjyRTyHa+hdNKpXC4kJCUr1tNm3b5/Cnja06KTKcWfOXUB0TCzKlCkHSWrW+yU8ilfHP5eOIToiBJUqls9y4Z1VTxvqf6NsTxvyTijT00ad8qRP8ibfQ4mWO6tXr1Y49lN5ewU787Ts5Y0S0mPeo4l7NOyss84HytxDiUJyle2hlJ28Ze6hdOjQIaV7KB07dkzpHkp5lTdj6p/EaAajyBlhGEa3ZNcThFE/6ux5o+2eNlaJkTBLcoDE2hE6Q5KO/K9OoqyPF36ZvQw7d+7EOwXKiCo9bWgsLTppowUkLXyzMxO8vHce33w1ABUrVhTfd1ZKgzZ62phSDyV6rkgZ+ZTsDStW4c/hFvkIvkW8UMDdS3w3WcE9lBgme1gZYRiGMTDU2fNGmz1tyDJ99do1PNm4GTH2xRCTvxyOxxVVeJ2Z3fZZ9rRRwLmELLxMqUlwDL0H56QQfNu/L6pWqSK8EZrqaUMW48jISKxe8zciY+Lg5OKO1JQUhAe/xaCB/VG2bFkxjqz/uuxpY8o9lOj3P3fhAvbuO4gYmwIw83CHxOrjol5RDyXLqFdwCb2N+qVKoOew70V53uzCnriHEsNkDysjDMMwBoY6e95ou6dNvbp1Ub1aNezcsxfHTx1ApHt5JLv5KZXgLh+jr9JYSTpswp7AOfwB2rZqifZtW2e4Fk32qaGys6NGjsCTJ09kDe7IUyDff0eZ/Wqyp40p91Ci5y2bN0dAkyY4cvQ4du3bj0iPCkhy8/tE3syS4+D27jKKF3TGkHFjZJ4G2r8h9EXSF3ljmMywMsIwDGPiPW900Qvp8+6foUVAU6xaux4Pnh9GWMHqSHfIr/ZjWUQHwe3DDVSpUAb9xuim0hstziiRWV/hHkoflZK2bVqhfr06okLgs3ehiPKsIbqkE+axwcj/7hIGftELdevU0fXpMoxRweorwzCMASLtU0NhQLQp0/NGmbHahBaoo0eNwJhvv4Rv9G1RXlc0SlQDZinxcHt9Dv5JjzHhx/+Jkr1cclo78qSv8qYMVH534i8/o6aPG5zf3xSvmSdEokDQJUz6ZQwrIgyjAbialhFXOGLyDlfTYvS5z4i6et7og6xReM/Bw0ewa+8BRBSojBTXXDb3k0hgHf4MLmF30at7NzRp3IgrvGUB91DKHgqp++mXCQiPT0ZqXCRGjxyB8uXL6+RcDB1DuI8yuoWVEQ3BC0TjwBAmUZY140Hf5U0bskaJs/MXLMbrWCCCwmQsVKjUlpokYvpLFHDEd19/ZbJN5oxB1vRhbktKShKeHaoq5erqqrPzMHQMQdYY3cJhWgzDMIze4OHhgakTx6Fj/UrI//wIzJJilPqceUKEGP9564YY99NoVkQYteQ2UdlaVkQYRrNwAjvDMAyjV1DCd9fOHVHCzxd/LlmG0CINkW7npnh8zAcUeH8Zo0d+C39/f62eK8MwDJM32DPCMAzD6CWVKlbE2B9GIv+bczBLjMpyjHlcKAq+v4xJv/zEigjDMIwBwsoIwzAMo7f4+flh1LfD4PH6LJCWMX/ALCURHm8vYOyPHxvPMQzDMIYHKyMMwzCMXkOdyts0awzn4NsZXnf9cB09u3YSTQQZhmEYw4SVEYZhGEbv6dShPZyTQmThWuaxIfCwSkazgKa6PjWGYRgmD7AywjAMw+g91CH7s84d4PTuGqze34Pz+xvo3b0b9xBhGIYxcLiaFsMwDGMQ1KtXTzSjo94TNjaVULlyZV2fEsMwDJNHWBlhGIZhDAIrKysEBATo+jQYhmEYNcJhWgzDMAzDMAzD6ARWRhiGYRiGYRiG0QmsjDAMwzAMwzAMoxNYGWEYhmEYhmEYRicYfAL7w4cPsXLlSgQFBcHT0xNDhgyBv79/rsZHRERg2bJleP78uXg8e/ZsbqbFyGBZYwxRFoODgzF8+HBYW1vLXitXrhx++uknLZ4xo8/w3MYwjC4xaM9IbGwsZs2ahZYtW2L16tXi/5kzZyIuLi5X46lePZWKHD16tJavhNF3WNYYQ5VFKUuXLsW6devExooII4XnNoZhdI1BKyNXr16Fm5sbmjVrJko+0v8uLi7i9dyMp8c0sZYoUULLV8LoOyxrjKHKIsNkB89tDMPoGoMO03r58iW8vb0zvEbuYHpdHeOVgZpv0SaFrEK2traiWzBjPLCsMfpCbmXr+++/Fw0DaZHYp08fFC5cWOFYljXTgec2hmF0jd7+pZPb9+bNmwrfX7hwIRITE2Fvb5/hdTs7O/F6Vqg6Xhl27dqF7du3Z+gQPGLECLi6uuZ6n4x2YVljjFkWnZycMH36dLFgTEpKwo4dOzBt2jTMmzdPfC4rWNaMA57bGIYxBPRWGfnuu++Qmpqq8H0HBwfY2NiI+FV54uPjxc03K1QdrwydO3dGu3btMrxGFh5yXxszCQkJmDRpktjIgmXIsKzpN8Yka7qSRWnIDFma+/bti3PnzuHx48citj8rWNaMQ9Z4btNfjE3WGMYoc0bI0kKTm6LN3NxcuIpfvHiR4XPkKi5WrFiW+1R1vDLQZEnnKr8Z8wQqRSKRIDAwUPxv6LCs6TfGJGu6kMXMUAgMbdnBsmYcssZzm/5ibLLGMEapjChDzZo1ER4ejpMnTwrrD/1PpQTp9dyOT05OFhtBY+hxenq61q6J0U9Y1hhDlcUnT57gzZs3QrYolGb9+vVCGcmudCtjOvDcxjCMrjGTGLhaTvXOV6xYIeqde3l5YfDgwShVqpR4LzQ0FCNHjsT8+fPh4eGR43iie/funxxj4sSJoi4/k9Et379/f6xZs0Zh3LmxwbKmG0xR1tQpi+fPn8eWLVsQGRmJfPnyoWTJkujVq1eeLNnGiqnKGs9t2sdUZY1hjFIZYXQDxfNS0iHF+hq7O53RLSxrjLZgWWO0Bcsaw/wHKyMMwzAMwzAMw+gEg84ZYRiGYRiGYRjGcGFlhGEYhmEYhmEYncDKCMMwDMMwDMMwOoGVEYZhGIZhGIZhdAIrIwzDMAzDMAzD6ARWRhiGYRiGYRiG0QmsjDAMwzAMwzAMoxNYGWEYhmEYhmEYRiewMsIwDMMwDMMwjE5gZYRhGIZhGIZhGJ3AyogBsmHDBtStW1fXp8GYKCx/jKZg2WJ0Ccsfw+gGVkb0nNOnT8PFxSXDa71798bFixdhiLx69Qr9+/eHl5cXHB0dUaJECXz77bcICgoS7zdu3BjW1tbiPWdnZ5QvXx7ff/89QkJCZPtITk5Gt27d4OPjAzMzM+zevfuT40RGRmLw4MHw8PCAk5MTqlevjvj4ePHeoUOHUKFCBbi6usLNzQ3NmzfHv//+q8VvwXBg+ftU/uQ5evSokMH//e9/stdevHghXnNwcJBt7du319o1GgosW5/K1uXLl9GyZUsxb9HcRI/v37+f4TgXLlxApUqVYGdnh8qVK+PSpUtKz32M6cofcf78ebRu3Vrc++jaSY5mz54t7qkEzVu3b9/+ZN+PHz9G586dUahQIfG5evXqCTlkGHXBygij1cmyRo0asLKyEhN+dHS0mNA8PT1x5swZ2bhZs2YhJiZG3FS3bt2Kt2/folq1avjw4YNsTP369bFu3ToUKVLkk+Okp6ejXbt24jg0idJ+li9fLp4TdAOnRWRERASCg4PRtm1bMdEyxo065Y+Ii4vDd999p9CS+ubNG8TGxopt3759Gr8+xvBli+akAQMG4OnTp3j//j1q1qyJVq1aIS0tTbwfHh4u5rbhw4eLsd988414TvtTZu5jTFf+9u/fLxQRUnCfPHkiZGPLli1C2ZVXWLKCxtJnyWgXFhYmlJ42bdogNDRUS1fIGD0SRuPMmzdPUqJECYmDg4OkePHikgULFsjeCwwMlNDP8Pfff0v8/Pwkzs7Okn79+kmSk5MloaGhEhsbG/G+vb292M6ePStZvXq1pFKlSrJ9vH79WtKsWTOJo6OjpGrVqpJff/1V4u3tLXs/JiZG8s0330iKFi0qyZ8/v6Rv376SyMjIHI+vbvr37y8JCAjIdkyjRo0k8+fPz/BaSkqKpFy5cpLRo0d/Mp6uc9euXRle279/v7hW+lxO0HX++eefEgsLC41csz7A8qcZ+RsxYoRk8uTJ4nzpsRTpNUVEREiMHZYtzc1tRFRUlLiGZ8+eiecrVqwQ4+UpW7asZNWqVSrPfcYAy59y8peeni7x9fWVTJ06Ndv90PneunVLqWO6urpKTpw4ofK5MkxWsGdEC3h7e+PkyZPCWrFixQqMHj36ExcnhQ7dunVLWClOnDghYlfd3d3F6+TSl1pYGzRo8Mn+e/XqJY5B1rVNmzZh5cqVGd4fOHCgsKjduXMHgYGBSElJEZa1nI6vCHLTKtoqVqyo8HNHjhzB559/DlWxtLREp06dMlgYs4PGkYu6b9++4jssV64c1q5d+4klic7XxsYGI0aMwM8//2y01kOWP/XL35UrV3D8+HH89NNPCj9HYTgU1tChQwc8fPgQxgjLlmbnNnqdjl2sWDHxnK6TPLvy0HN6Xdm5z5hg+VNO/sgTQueXGxnNCvKQkIevbNmyatkfw7BnRAd07NhRMm3atAzWkwcPHsjeHzx4sGT48OHi8alTp4RFRR55682rV6/E50NCQmTvz549W2a9CQ4Olpibm0vCw8Nl7z9+/FhiZWUlSU1NzfH46sTS0lJy6NAhla2HxOLFi4UFTBnPyKBBg8Q1kZUsKSlJcv78eWE5O3PmzCefj46OFuN2794tMRVY/vImf2TZrFChgkyeMntGyFp65coVMY68I6NGjZIUKVJEWLmNHZYt9c1tL1++lHh6ekpWrlwpe23gwIHCEi/P119/LeY8Vec+Y4TlL2tIDuhcEhIS8uwZoTmNvHETJkzI9fkyTGbYM6IFyBJStWpVkZBIFo6DBw9+EmtJFlQp9vb2wuqgDO/evRPWfUpWlCK1okmTaSmO2NfXV2ZhodhSc3NzEZOc1+OrAp0jxUjnBvocfX/KQAnDlEtCFqp8+fKJZDuyPlLMbGYo0e/rr78WcdpkOTJGWP7UK38U90+x/A0bNlQof/Q+edroeufOnSsspoaaGJsdLFuamdso3yggIEDMYWR9l5etqKioDGPpOc1jqs59xgDLn3LyJ72G3MqovKxRzgnlbE6aNClP+2IYeSwzPGPUDoUD9evXD4cPHxbVVKRu+Y9GiJyhiS07qHJGYmKimIClEw4dU0rRokXFPmhipeormaEJVVXohqcIcmnfu3cvy/doEqOEuUGDBql0vNTUVOzZs0ckzCkDVQjZsWOH0vun34K+Q/ou6MZiTLD8qV/+KDyLwi6kVdwoxIOq0JCycfXq1U8+T+/RZmywbGlmbiNFpEmTJujTpw/Gjh2bYTyF6vz+++8ZXqPqR6NGjcrV3GfIsPwpL3/+/v6i+uTmzZvxyy+/IC+KCIX+LV261CjntNzSb9AQhIaFa+VYHu5uWLtyOYwN9oxoGFqo0ORYoEABMXGR5YYqOSlLwYIFhSWFqj5lBU2IZP2im1ZCQoKIDV22bFkGqwxN0GQpk1qMyGqza9euPF2Tok3RZElMnjxZ3DiHDh0qJnX6XqisJVmaaSLNCoq1pxsOTYTSGy6RlJQkbhS0D7I602NpxRmqjEXPacKk1yi+n274FLtP0IRM1WrIqkVVQihnhCxWZGEzNlj+1C9/27ZtE8ehfdFGckUlQffu3SveJ3l78OCBkD06pzFjxogbd506dWBMsGypX7ZoYUuKSI8ePTBx4sRPPkNzGykrlLtA5Vjpf6qEJK0GmNPcZ0yw/CkvfzT/LFiwADNnzhT/U0UsgiqukQLz8uVL2b5IrkiGpBvdXyknh6q6kVJDuTmsiGSEFJH3JTtqZQvNhdJDsjBs2DDh2aPy4iS7pFhK86v++ecfMUfQ3xJ5A0lxpTkoq7+NGTNmwMLCAnPmzIE6YWVEw1CCF1kimjZtKpLmaGJQ5cZQqlQpMVnQfsgNTHXCM7Nx40Y8f/5cTK49e/YUFjUSOClr1qyRuZCp7jwl6t24cQPahiw7165dExNcrVq1xLnQAo1cx40aNZKNo8WbtBZ/ly5dxB/O9evXxfXJfy+2trZi4u3evbt4TKV+CbrWAwcOiBs1HeOLL77AokWLhGtZarGi3iJ0DJpc6fmxY8fE8YwNlj/1y1/+/PlFKIx0I6soWTSl4Rj0XVB5Vdo/edpoEUGLJGOTL5Yt9csWleElQwl5P+T71Jw7d068T+FIVCb6jz/+EPv4888/xXPqG6HM3GdMsPypJn80J1EyPcmHn5+fOG/q11W6dGlRAlgKfZ7up9JtyJAhQsGiHjjkdaN9S+Uyu2R8Rn/o2rWr8OZTMQtSQMlwRt5EUkpJUaGQUJpbqBACGdJWr14tPINUvj4zq1atwo8//ij+VydmlDii1j0yOoc0V6owQgtshtE2LH+MpmDZYnQJyx+TFW07dRVeC21Q6MkeHNitfCgmRX+QsYKafMobRqRQuPFnn30mvH8U6pgdVK2PogAov5a8JxQloKjPlqqwZ8QIuHnzpnD5k15JVhlyw5JwMYw2YPljNAXLFqNLWP4YQ8fh/71YpHRQeHtmyDtLuWvk/crJN0EeVyoPTcVZ6P/Mpa7zAisjRgC52ag7KuU9kDuO3KqqJlIyTG5h+WM0BcsWo0tY/hhDx9LSUoQTUogWheZJ86CkvYlq164tnlNPHSrUQPJO+SDUW0ceyhvavn27CFUk6P+tW7eKfCZ1wGFaDMMwDMMwDGNkYVpSKJ+Ics8o94dyh6jyIxUj6N+/v3if8kcoBJGKXpCXhJp5nj17FhUqVBDv//XXX1i4cKFoeCnf2HfkyJFqUdBZGWEYhmEYhmEYI1VGMjN48GCR+yRfSU2+olqVKlVQvXp14VEhqHcWFduQL4lNFUmpUIK0Klde4D4jDMMwDMMwDGMilC1bVtYrKzPUMJUqrkmraZE3hBQRSoKXb9BK3hOqykV5VVSVLS+wMsIwDMMwDMMwRkZYWJgoujBw4EDRNJVKi5NiMXv2bHTs2BH79+8XvdeodDW1OqBgKSoXTn17qMQvQYnq5Blp2LDhJ/unstb0fl77jhiEMkKZ/uQqktYBp1re1CyKGq+oOpa6tZJ2R/0pKleuLOolyxMfHy9qvVMVDdIOqTEM1eJmGHXKKjWSoj9gsjhQ4y2yNlCNfKqZz5gO6pzblNkX3YSoHwM1Z6P+KJSU26JFCy1dLWMKsshzG2NqUFd0PNmjvWOpAFXSot4x8+fPx7Nnz8TfJzX0pGIMlLhOTVPpXvD999/j9evXoo9OyZIlRT5J3759RcjW+vXrRY+krKB7yLx58zB9+nRRZSvXSAyALVu2SH744QdJeHi42Ojxtm3bcjX28uXLkitXrkhWrFghmTVr1iefX7BggWTatGmS2NhYydu3byVDhw6VnD59WqPXxxgPyspqQkKCZPPmzZKgoCBJenq65NGjR5L+/ftLbt++rZPzZgx/bsvp/Vu3bkm++uoryd27dyVpaWmSmJgYyZs3b7RynYzpyCLPbQzDqIpBlPY9deqU0L6ocQtt1LmWsv5zM5Y0RHI3kasqM1SD+eLFi8JdRaX8qAMllTlTdCyGya2s2tjYoEePHqLGt5mZmXCPlitXTsReMqaDOue2nN4njwh5eUnOKAmRLGaFCxfWynUypiOLPLcxDGN0YVpUw5hi3qjboxR6HBoaKkKqyL2Um7FZ8e7dO+F+zvx5KnOmCHJ50SbP/7F3FuBNXl0c/9fdKVKkuLsOl+LuztAxxtjYYMMdBoMhY2y4u7sOd3d3p1B3b/M95/IlS0vTJmk85/c879PkfW/e3CSn995zj5GpKkvmKsYoyYr8kSn02bNnqFWrlsI2LGumhSbHNspqktF1Uj5evHghMqQMHTpUnCtRogT69u0rFpNpYVkzL7Q5z/LYxjCM0SsjlBuZkB/gyGpBUPl6+fOqtFX0XuQvJ+8jS6+h1yqCFBUqBCOlQIECmDlzpkqfkTEN1JU/ChhbvHgxcuXKJax2imBZMy00ObZJM7Qruk5Qm6tXr2LcuHHCMrx06VJRUXrChAlf9I1lzbzQ1jzLYxvDMCahjJDJl6AdF1dXV9ljwsHBQe22it6LdnGSk5NlCgm9PqPXtmvXDi1btpQ9J7O0tHIrWVkY44YmUWVRR/5osqZAMQoiGz9+fKoc3mlhWTMtpLJBed6p8q38b6rq2EaWkYyuS5UVcjv19vYWjzt37iysJLS4lN5fCsuaeY1t2phneWxj1JlHGfPE4JUR8mv28vLCq1evhA8qQY/pXNqdZlXapgfFiJASQouDggULyl6fL18+ha/JyJTM9STNC1Xlj+SDss6QCwNN1pnJKMuaaUELN3d3d7x7907ICEFjj7pjW2bXpQqPMrCsmReanmd5bGMYRhWMIoCdiqqQGTcsLEwc9NjPz0+ttmT1IOsH7STSIEePpTsv5KJVo0YNEehJOz20o0OpgDklIaMNWaXJ+vHjx8JthiZ4xvwg1xWqghsRESGOrIxtmV1v2LAhDh06JApV0bhHbjGlS5f+wirCmCeanGd5bGMYRhUsKKUWDBxSFlavXi0rOS+f05z8nomBAwdm2pbYunVrKt9UaSXKSZMmicekhNA9pXVGmjZtqladETIvpw3IY4wPspZpQ1ZJPr7//nuxGyjvvkDtpbKsLCxrxgttjtBC7vr16+J53bp11R7bMrtOGzCUL/706dPiOWU4okJYZJ1RFpY10x3bNDXP8tjGZHUeZcwPo1BGjBEeRE0DYxhEWdZMB0OXN5Y108HQZY1geTMNjEHWGP1iFG5aDMMwDMMwDMOYHgYfwM4wDMMwDMMwhsi3g75DcHCITt7Ly8sTSxYvUrq9NDOdIiZOnCgLUyhevDhevnwpEqlIk1PoClZGGIZhGIZhGEYNSBHp98sfOnmvlbN/Vak9JWKSQsmZqK4UJZeQIk0wce7cOVEniGKk16xZg5EjR0KXsDLCMAzDMAzDMCZGTjkLh5ubm7CUpGf1oAx43bt3F0lUqP4UKyMMwzAMwzAMw2idyMhIbNu2DZcvXxauWuHh4Th79qzIgKcrOICdYRiGYbRMcHAwXrx4gbdv33IhP4ZhDIbNmzejSJEiIt07pefu2rWrsJToEraMMAxjllBNoUuXLomFIVVDr169eqbBfgyjDlFRURg9ZizyFSwG/7cv0ad3L1SpUkXf3WIYhsHKlSvRs2dP2XN6TO5aCxYsgIuLi076wJYRhmHMkqPHjuHs5dt49iESO3bvw/Pnz/XdJcZE2bJ1O6rWbYmW3X9A+z7DsXnrNiQkJOi7WwzDmDkPHjwQm3IjRoyAtbW1OL766iuxWUcWE13BygjDMGYHWUPOnbuAei26oVq9lqhYsylOnzmn724xJsiNGzfw+OkLVKzRSDz3ypEbBUtUxtp16/XdNYZhzJwVK1agTp06uH37Nm7duiU7hg0bplNXLVZGGIYxOx49egRHFw+4eWQTz4uWqYKbN2+K3SCG0RSUr3/12vVo0W0wLK2sZOer+7XFm/cBOHT4sF77x5juZktKSoo4OD6JUURiYiLWrVuHbt26oXTp0qmOAQMGiID2+/fvQxewMsIwjFlBk/PW7TtQuU4L2TkbG1uUqlQbBw8d0mvfGNPh/fv3mDtvPpp3+U6m9EqxtLREi+7f48Spczh1+rTe+siYJiR3330/BN98MxDbtu/Qd3cYA2Xv3r0isUa7du2+uFaiRAlx6Mo6wgHsjMFN4E+ePBGPKRc2/TMwjCYhC0gyrJG3YPFU5yvWaoINCybAr0EDeHh46K1/jPFDhcZm/TEHjTt8g5x5CqTbxs7OAe37/oIdK/8QykkdHabRZEzbGuf/KRCDRs9HYkI81i0Yh6ZNGsPV1VXfXTNZqCq6qsUIs/Je6tKnTx9xSOnQoQOSk5MzjCfRFayMMAYBmZOPnziBffsPoni56rC0tMKBw8dQvmwpdOzQHvb29vruImMCxMXFYd36jWjVc2i6i8Oq9dtg5ao1GD7sJ730jzF+AgMDMXPWbDRs3x+58xfJsK2DozM69P0F21fMgp2tLapVq6azfjKmOY8uX7EStZt2EZkBbe3sUalWM6xfvxGDBw/Sd/dMliWLF+m7C0YPKyOMXomPj8e58+dx8OBh5MhbCF2/HQdH5887OJXrNMPV0wcwYuQo1K1bB40aNuTdHSZLrFu/AcUr1ISnd650r5eqWBNP7lzChQsXUKNGDa33h3aldu3ahevXr4vFAwUS9u7dW+R6T0tSUhLWrFmDc+c+B9pTQSr5tpldl0JZnIYPHy4KXa1evVrrn9GcoJgjsojUbdEDeQsUU+o1Dk4uaNd3ODYt/11Y5IoWLar1fjKmCblkuWfPB9/CJWXnylWtj+0rr4p5tlbNmnrtH8MogmNGGL25Y61avRbDfxmBO4/folWvn9G4fX+ZIkJYW9uIQM/ugycjONoS4yZMwvy/FojgYw7KY1TlypUrePn6ParIxYqkhRSCxh0GYPOWbfj06ZPW+/Tvv/+KQnijRo3CyJEj8fDhQ6GcpMfOnTuF7M+dO1ccadtmdl3Kli1b4O3trdXPZa6sWLkaxSvWRoFiZVV6nbOLO1p0G4KFi5ZwEgVGLc5fuIAbt+6ibvNuqc5bWFqiedfB2LZ9p8wFmmEMDVZGGJ1BCsS9e/cw7bcZ+HPBIli75kHvn6ajfssecPf8b3GUnJSE4EB/8Zewd3RC1Xot0efn35GneHVs2rYHo0aPwdmzZ4VZmmGU8eFfv3EzmnUZJPzzM8LZ1R31W3+NeX/+pfVaEJStpHHjxnBzcxNH+/btceLEiXTbnjx5Uvj40u45HWnbZnadIMWH0ja2adNGq5/LHHn8+DHefwxAxRqN1Xq9d848KFGxFnbt3qPxvjGmzZ07d7B9xy607vUTrG1sv7ju5OyKVt1/wD8LF+Pdu3d66SPDZAQrI4xO+PDhA6ZNn4EtO/aifO3W6D54IspUqQMbW7sv2oaFBmLF7JHirzy0iCxUojza9RmOJp0H48L1+xg5aoxQcBhGEbTTTNllGrbtCxc35YL/ChQtg/zFK2HJ0mVas8JRv8LCwpA7d27Zufz58yMoKOiL3XGq4E1ZT+h6em0zuy51CVuyZAn69+8vCltllvKRXic9YmNjU1mP+Pjy2LN3P6r7tROP1YUUmUuXLgv3VW33lzENyBq6fOVqtP16mFA6FJEtZx406TgQs+fM1YnVl2FUgWNGGK1Ck+revftw7sIlYT4uWLxchu3/njoECfFx4vGGhVPx48SF6bYjn/8mHQYg8OM7rN+0Gnl8zqJnj25wd3fXyudgjBOynC34eyFKVKqDfIVUy8xWrX4r7N/0D/bu24c2rVtr5X+DcHBwkJ1zcnISf2nx7+jomCrwnpA/J99WqjApuk7nKY0jKSglS5bMNHc8uXdt375d9rxAgQKYOXMmu3cpICQkBP4fP6JRof989dWBNmcKlagorCxNmzbVWP8Y0+TVq1dYuHgp2nz9M9zkvAsU4eNbGPXb9MHMWX9g/LixnDWQMRhYGWG0QmhoKE6eOoVTp06jaNmv0HPI5HStIGmhVIRJiZ9dY6R/M3Nt6DJwDO5eO4PxEyejQvlyaNyoIfLkyaORz8EYN5s2b4GlvRsqVP9c/VoVaPe4ScdvsG3pdOTJnRuVKlXSaN/s7Oxkioazs7N4LLViyCsohDSbHF2XJnGQbyt1V1R0/ePHjzh69ChmzZqlVN8o73zLli1lz6U76ZQpigLlmdTs2rUbxcpW14jFoWTFWti2fS3Kli2rVQtGrlzpJ3FgjAOyepIraYuug+GlICFHevgWKonqjTrh91l/YPLECZypkjEIWBlhNAa5iVy7fh2XLl1BWHg4SpSviW7fTRTZYrQJBeiVrVoPJSvUwMNbl/DP4uVISYpH1apVULVKFaGYsFuC+XHmzBncf/QMHfr9qvbvb2trh1Y9f8TaFTORPXt25M2bV2P9I2sFWfIomUO2bNlkO51eXl6pLBwEKSt0nq5T/Z302mZ0nYL3w8PDMXTo55TGpFCQEkQuWxQ8X6RI6hS0NjY24kgPTh7x5cbL8ZMn0X3wJI3cL7tPPljaOojfrGrVqhq5J2NakBvlnHl/ok7z7siR+z/XTGUpUqoSwkMCsGjxEvw09EeeHxm9w8oIkyVop/TcufO4fPUqkpIlKFi8Aqo37Q7vnHl1PsBR4B7FodARERqEpw9uYPHy1YiOCEPFihVQq2YN4W7CA6/p8/TpU+zcvU9YzayssjbMubp7CV/reX/Ox+RJE+HiojnlmhabZLEguZS6R/n5+aXbtl69euJ68eLF022b0fXq1aujTJkysraUVWfx4sXCUkKB84x6UKzOH7PnolaTLqJmiKbwa9MH61fMFMoqp/pl0kvh65O/pIihTA9K/kIxl+4e3rBSEB9WqVZT7F3/l0gEQynFGUafWEiMYJtL2fz5yrTN7Po///wjrskHeI4fP17lCYEW6bR7YaqQC8iSpcvx7v0HFC9fE8XKVIGrx+fd3azw6PwONG3aRDwmpSHRLjveBUZn6Z5xMdF49vAGHt26AKQk4PvvBintouDj46M1WT18+DBOnTqFN2/eoHz58hgxYgTUwdRlTZ2d6klTpqJl9x+FG5+muH/9HF7cO48xo0el+3tmtc4IUbduXZm8LF26VJwbOHCgTLaoLsj58+cVjm0ZXU/1We7fxx9//KFynRGWtdQK76LFS1GpTktRn0bTBH18h30b/0bL5k3QsGFDjW+ipB3bNDnP8tim3cyAM/+Yi54/TBHp79ODslFSEpj+v8zM0IUrKjIMW5f8ht9n/PaFNVaTqDqPMuaHUSgjW7duxdWrVzFmzBjxfPr06aJSbceOHVVum9l1UkYo8LNPnz5Z6rOpD6LkArP/0DHhAmNnn9q/PSvMG/+NiBuRWjqGTVuusXsnJyfh2O51yOZqjf79+mplEFVFVimtKy0w7t69K1zceMLOOrRImjxlKspUb4qipato/P4n962Hl4sVvu7VC+Y4abOsQbi7bd22HY+ePBO1kZRxk6HEHNJxjWLnhoz/W6n3io2JEjIXFxWMPl/3QsGCBaEtWdPkPMtjm/agOJHcxapkOL4pq4wQF0/sgZejBJ07ffk7m8u4xugfo0jtq0z+fGXbqnIvRjFUnbpyhTJYv2A89qydh2tnD8P/7XMkJRnOxEFBvUGf3uPOldM4tHUxVs4ZATcHCTp2aK+191RFvmjyJjcdTbr9mDur16xF9nzFtaKIEHWad8XDJy9EhXbGvIiIiMDGTZsxfsIk2LjmQY/Bk5T21ydFRP5QFnL9at5lECrX74DFy1Zh9px5wtpg6PMsj23a4e3bt3j/4SOKlKqssXtWrNkYZ8+eEy6HDKMvDD5mJLP8+fKmxcza0uJUmXudPn1aHDTI1q9fHy1atFBYKI12beR3bmg3SJoJx5RjEyi4tUuXzujUqSNevnwp3D7uXjiAt2/ewM7BETly+cIrVz5458qH7DnzinNK3ff/GbfIYGdrq3yWD8q8RYpHgP8bBH98i0D/1wgPDULOXLlQrEgRtGpSD8WKfQtb2y8LQulDVtXBXGVNWU6fOYNXb/3Rvu+vWnsPij9p0e17bFk6Hb6+vpy1zUwsIfv27RdxcWWr+qHXj9OUygyoCHWcEfIVLI5u303A84e3sGDhUnh7eaBTx/ayWCNDmmfVGed4bFNObtat34DqjTpo9Duxs3NA2Wp+2LFzF/r0/lpj92UYk1JGMsuvr+lc/M2aNUOvXr1E9ppnz55h3rx54h9fPs2lPJyPH6JoW61atVL57JM/9ZMnT/H44XmcOfACiQmJ8M6VF1458yGHT37kzFsw3YBPZdwXaGfx0/tX+PjuJYI/vUHAhzdISU5EPt/8KFa0CGo0roUiRfqKrEK6nMhUkVV1YFlTzPPnz7Fr1150+mZ0phXWs4qzizsadRiAvxb8jcWLFsp+Y8a0oIX1nr37cPHiJZSr3hBfD50Om3SqW+sKGssKl6wggpZfPL6DRUtXwjubB3p275blNL2anGfVGecMcWyjzcsbN27I6gFRxjnKqKcv9h84gCTYomCxshq/d8UajbBp8RQEBASgXLmMa4ExjMEoIxRAdfHiRVHoacCAASI1Jflq006hpsksv74mc/ET8j65FLTetm1bER+hSBnhfPzpQylQ6fDzayCeJyQkCPcCsqI8eXYN545sRkqKBHkKFEe+ImWQv0hphRM9/W7vXz3Bqyd38O7FQ8TGRomduKJFCqNmhfrIly+frE6DPFRbIauoMsmrIqvqwLKWPtHR0Rg3fiIadxwAxwwqEGuSPPmLolj52pgwcTKGD/tJY0ov134wDO7cuYOVq1ajePlaWbaEaBqStULFy4lF6bMHNzDzjzmoU7sm2rZpo7Yirsl51lTGtj379mPHoeOQOGen9FRwSQzG7N+nazXQOyN5XLtuo8gOqI0NNsq41azzIEz7bQZG/Dpc4xZfHtcYjSsj165dw99//42KFSuKDDCkjNBigALaxo0bB02jTH59Vdoqey8pmf3jcz5+5aDvqFChQuJo2PA/c/+DBw9w4+YtnD6wAfkLl0aJirVE4Lr0+3vx4AYe3roA3/y+qFyxArq1ayyryWBo37UqsqoOLGvpK6pkoShXvTFy5S2k0/euUKMRDm19gd179qJtG81XaGf0AwVmb9q6A216D4eHVw4YKjQ3Ub0I2sg5vmcNVqxchW8G9DeIedbYx7YzZ85h16FjCCnQCLD6PB/FBj/G5N9+x4QxI3WqkJw7fx7bd+xG297DlKrZRckSEuI/W682LJyKHycuVOp9vLL7iBTms/6Yg0HffoMSJUpkue8MozVlZNOmTRg9ejSKFSuGvn37ykyqNBhpi8zy66vSNrPrFJhKqQhph+fFixfYs2cPmjT5nGqW0Sw0qVGQIx20+0Xf/eXLh2n2kbUh60fvGb8ZjSuMKrJKaV3poAU1TbhkPaKdTfm00kzGbN26DZb27ihXrb5eFoON2vUV8SP5ffOJcYMxfrZu24G2vX7SSKpyKc2aNk2TstwpyynLpZDVpkmHAVj/90QRt5HeZo2u51ljHduoz5u2bsPx81cR7NtApogQcV7F8CJIgpHjJmDU8J+Fe7I2IfcwihF58fq9cD91UtLqS27MFENJSP8qi49vYbTu9ROWrfgHdWrVQOvWrbTu9sowhMojA7lmkSIiD+UWl7pAaQPK2hEZGYmff/5ZltOczLpE2lz8GbVV5vqRI0fEPWlQ8vT0ROPGjRW6aDGagyYpKrxk7MWXVJHVHTt2pPKT7tmzJ0qWLIlJkzRTydnUuXjpEm7dfYCOA0bprQ+0EGzV4wesXDETo0Zm5xSWJgC5HgUHfNCoMnLo8GHs3btHKynLpSmAExJiZS5U+p5njXFso0xVf/69CJ9SnBFOFhHLL5dHsdmK422EGyZM+x2tmjVGqxbNNVZzSB7yGFixcjUKl6mGjv16wFIL75GRhaTrdxNw+sBGTJw0Gd8O/IYTdTCGV2eE8opLBxayjKxatUpkUtq8eTOmTp2qvZ4aGZwf3TQwhsWlOcoaWWLnzV8gdgwpoFzfvH3xCKf3rxUV2rNixTN0eTMHWfv06RNmzvoDJSrWFYG9iipYq4LUdYZ2qu0dnZV2nVGGV0/u4eT+9ejSuQNqVK9uMrKmK3kjd+GNW7bh0vVbCMlRGcmuSsQ3JCXALeAmPJPDMLBfb5QuXVpjfVm/YSNevHqLRu36iaQv+qzV9frZfZzctw41vqqGdu3aKnSlMwVZY4xMGaFAKsowRSlvjx49KrJPUaXVoUOHolSpUtrrqZFhDpO2OWAMg6i5yRqlWp04aQqadvkOOZWs86ALbl8+gffPbmLUiF/Vdm0wdHkzF1mjgOwtW7fh1u27qFC9EUpWqgXbLAaxJyclISw0EO4e3llWcCQpKXj19B6unT0IextL9O3ztcq714Yua9qWN3INPnTkX+zZfxCR7kUQk604YKmaBcIyOhieAddRIKcXBvTplaXvlGJw167bgLJfNUSF6g3VHkM0XTg4MTEBl47vwpund/HdoIFqFd40BlljjLAC++vXr3Hs2DExUFDQWqNGjVLlHGfMZ9I2dYxhEDUnWSP3yam/TUfRCvVQsrzyu8CarIqdEUd3rULe7K7o2rWLScqbOckaQfU0Dh46jCtXrqJAsbIoVbkucvhoPmukskRFhuHhjfO4f+Mc8ubxQauWLUTWR1OUNW3K242bN7Fi9VqE22ZHhHcZSGzUd2+jGEfrsDfwCLqNryqVR4+uXVSyjtKYtn79Rjx8+hxNO30Ld8+spTPWtDIixf/dC/y7fTkaNawvYqBUyeplDLLG6Be1tmcohW///upl7WAYhlGXrdu2w9UrT5YVEULVatjKUL9VT2xdOh3FixfjgHYTgDbbevXsgS6dO+Hy5cs4cWQTIqKiUbx8DZQoX10nLoLk2vXswU08unUOEaGBqF2rFiaOHyOK8jKqERYWhr8XL8Vz/1CE5KiJFAcN/H4WFkjy8EWgWx4cf/YIV38dhb69eqBG9a8yfSntBf+zcDESYIfOA0brNDZEVXLlKYiu343HwU0LERsTiw4d2uu7S4w5KyNUmVwRdevWzWp/GIZh0uXx48e4fuO2mBA1jabSh1pb26B5l++wavVs/DatcLr1bxjjw9bWVgRp00G79WfOnsXOFTPh4pENJSrUFsUI6bfXpDz6v3mO+zfO4vXTeyhbtgy6d24nCu9xRXL1uHP3LhYsWooQr9JI8K0glIhMSUmGRXwUJHbOmbtwWVohJnspxLrnx9LNu3H52nV8/+03QnYUQQpuWFQ8WvUYqLHfVZuZ26haOyXs2Lx4GqpUqSxqfDGMXpSRAwcOfLHTQFk1SChZGWEYRhuQKwNll2nUvr9GF33awN0rO8pVb4RNm7eoXfeBMVyoKniH9u3Rvl07PH36FCdPnsbqw1tQpFRllP2qQZZqk8THxeL+9bO4d+00PD3d0bBBfQwd1DvDBS2TOZcuX8bS1RsRlK8+JPbKF0YlRcT53g5Ele4AiYObUq+R2Doh2NcPV97dRjDVJRk7SuHvd/feA5SsWFujCqa2M7fRPYuUqSYyfrEywuhNGZk1a9YX56gWBy0WGIZhtMHFixfhlTMfchhQwHpGlK/WAOsWjBO76LR4ZUwPWkBSvAYdcXFxojjdwY0L4OLhjar1WiNnngJK3ys6MhzXzx7C0/vXhHvP6JG/sNxoiHfv3mHZ6vUIKtAIEhvlixU63dwIi5TP8SqOD/cjumIP5d/UwgJROcvj+cdbWLJiFX747tt0mxUuVACXb10TljVjISU5GS8f30T9at313RXGhNBIBaJWrVrh22+/Rfv27EPIMIzmOXr8BGo16wVjgXy/y1Spj5MnT6Fz504K29EmDhWMo0w6tLilOju9e/dOt3YBZf9Zs2YNzp07J56Ty5B824yuUxDwihUrcPfuXWHJphpKrVu3RoMGDbT2HZgTVN+joZ8f/Bo0wK1bt7B9xzrYu3igTrNucMugXgllKrp6ej8e3bqI5s2a4Ns+M2Fnl7WsXUxqFi5dgeCcVVRSRAiLlCRYpHzeZLWQJKn13lE5yuLm/SN49uwZChcu/MV18ia5eu06TuxbjzrNumjE6kvJOMjNj2KNyIqhSeJio3Fk2zKULFZY7cQJDKM1ZeTJkyeauA3DMMwXUPXmkOAQtXLu68u3mihUsiKObluUoTLy77//4sWLFxg16nPhxpUrVwrlpGPHjl+03blzJx49eoS5c+eK59OnT0/VNqPrpPRQwPP48eORI0cO4V40Y8YMEaBdrlw5jX1mc4fkqEKFCiJ5waVLl7B55SxUqdcKpSvV/qJtgP8bHNqyGNWqVMKsmTOyVLCQUbw2+Rgei+T8esrmZGGJkGxlsX7zNkwaN/qLy5S+d/iwn7F5y1Zs/GeSUF7zF81azRLKCiifRloTUCrpB7cv4fKJ3WjRrCkaN26kkfsyjNrKyIgRI1L5N8bHx4siUVQIkWEY8+P0mbNYtWYtLC2tkL9AAYwZMRzWGigUJyU0NDTD3WVD9a12dfcSMXUZQQGsbdu2hZvbZ390si6vW7cuXWXk5MmTwtIhzaKUtm1G12mh26XLf+mGaVeT6kKR8sLKiOahObJ69eriO57/1wKRBatGw/88B948f4jje1bhh+8Hp7tjzmQdsg6s2bAZIZ76rX+W7OqDNy/uiE2H9Gp0kOWyR/duqF2rJtat34grp/ehar1W8C1cSu1YEqpj4+WtRPFGJVyyHt+7imun9yO/b15MGDcG2bJpfixmGJVXDM2bN0/1nCY5qjGSM2dOTfaLYRgDh9yCduzag8OnziGkWGtIbBwQ9/Emxk+eiuFDf9DYpEVVf8nlwNigiTw9dyv5wnqkrOTOnVt2jsbSoKAgcc3R0TFVZWaqeSFfz0m+bUpKSobX5e8ltTaR60itWrXS7Ru5dcnXd6BFkYODg+wxoxykZI4ZPQpz583HspnDYGFpIZPpsaNHCSsVox1OnT6D9xEJSM6X9UV5lrCwQEj2ivhr4RLMmj5VYTA7BYOPHTNKWHN27d6Lc4e3onyNRihe7iudJ+2Ij43B3etncPfKSRQrWhTDfvoh1TjFMHpXRurVq6fxTjAMYzzQwvfKlSvC9SDMJhvCCzQGrD5PlpE5K+Bx6CuMHDcJdWvXRNtWLeDqqnz2mvRwd3dHZEQYkpISDT6Tljwf379E7gyqYpNVmZAu8glpsbTY2NhUCgQFSBPy5+TbSlMTK7ouf57aLl68GLly5ULVqlXT7Ru5d23fvl32vECBApg5c6beg6qp7wEBAeIvubhQf4xBOZo3d7a+u2BW3L9/H+u27EBIAcNwJ0p2yYFPMTkw588FGDH8pww3KchqOXLEL/D39xcFN9fM24Pi5aujbLUGcHHVbm2Z4EB/3LpwFK+e3EHNmjUwacI4rmfDGI4ycvDgQbWsJgzDmA4U+Hzy9BkcOnIUMbYeCMtePd2iYYke+RHgmhsH7j3G6bOjUa5sGbRu3jTVrr0q0KKzbNmyeHLvmkaKHeoi0JN4cOMcanyV/mKfkAYqk6IhrUdCVoy0CgohjSeg61LlTr4tKYgZXZdCn3f58uVioUPxI/Tdpke7du3QsmVL2XPpgp+yg5FFTB/QZ1y4dDmu3boLKztHJMdGon6dWvi6RzejUEgMDVJGTZHrN25i4bKVn9P42qT+P9InUdnL4J7/dfz+x1z8Omxopuma6ffp368voqOjRX03qmvjncsXFWo1EQUINQWNCa+e3sPN80eQEBeJZk0a44eBPTmdNGN4ysjVq1eVuhkrIwxjWtDC886dOzh87CSevXiJWLf8iM5TX+TSz7A4mJUNYrKXRky2Ejj14RVuz1sEZ2sJGvvVQ62aNWUxEsrSulULzJo9F0VLV9aYdYQCPWkncMXskegxWLOFFEMC/eH/+jG+GtxXYRuyVpDV5/379zKXtlevXomg8rRuVaSs0Hm6LnWJTds2s+u06KCMWuSeRYpI2veQh9yI6NBmgUhVIBe0P/9ehFeRQFiRliIwmGTu+PULePd+tigup6pMMabH8ZMnsWHbHgT5+n0eiwwJCwtE5KqEu4F3hSvr+NEjlSqKShZOWls1bdoUN27cwL4Dm5GYbIGqdVvBt4j6cSWk3D++cwXXzx5Ajuze6N65LYoVK8aKPWO4ysjEiRO13xOGYQwCmqRowXrs5BncuHkTSc7ZEeacH8lFy3xeBKpSHMzSColehRDgVQiBcRFYf/oBdu47hFw5c6Bxg7qoUrnyF1YARbuEVSpXwoV/d6BO864wZJKTk/DvjhX4ulfPTAP5yU3q6NGjwg1K6h7l5+en0EWWrhcvXjzdtpldJ0WEqthPmDDBaCrDh4eHY9eefTh74RJCs5dDYm652h2WVgjJUws3Qp5h+KixaFi/Llo2b2Y0n43RLAcPH8G2/UdFPRFYG2h6ZAsLRGcvixfBTzFu0lRMmzReaXklK2blypXFQdnwtu/chUsnd6N20y7I7VtE6S7QZsKzBzdw8dhOFCqYX8SD+PjoKdsYw/wfC4k+trnMAHJnkA8AZYwTYxikNSFrNAy8fv0aJ06fxeUrV5Fo64pQp7xIcs8niwfJCIvYcOUrFZO/f3QQXCJewTbyHQoWKIBG9WqLlKgZuQaQlWbylKkoVbUxiperBk0gtYz0/2WmRrLP0Pd4ct86ZHO1FcpIZsjXGZHWHZDWBlm6dKk4N3DgQNnnX716Nc6fP6+wzoii6yQj33//vbB2yLtmURvp/Q1lXKPvkBZb+w4ewYNHjxHpWRSxXkUBywwUu+QEOAY9gnPY8yy7BZoLpjS2UVa4WX8tRmBBil/TjHtRlxyBQrklaJG0834Ydl95Bk1hH/QYZZyiMGHMSLXvQcHua9dtgLNHdtRt3h0OTi4Ztg8LDsCx3avh6mSLnj2660wGjEHWGCNTRiiry8aNG0WAGPmQy7981apV2uijUcLKiGlgDINoVmSNgoFPnDqNM+cuIN7SHmFOeZHg7qvSzqK0UjEVCEuxslOtUrEkBVaRn+Aa9Ro2kf4oUbw4mvjVEylR04tnoJ1yUkjqtvoavoVKwtCUkSun9iPkw1P8+suwDINUjVXetDmukSsWxSSdOH0GcRYOCHUt+FkZVmCNS5eUZFiHvoJH5As4W6UIa0md2rWEOxxjXLKmirxNnDoDtyV5keyiuayeztfXisKHhMTSClGVemvs3p9vKkH2V/9iysifspSpiizZx4+fwL4DB9G4fX/kKVAs3XYPb1/CpWM78XWvHqhUqRJ0iTHIGmNk2bTI1E95/6muyIIFC/DDDz9g7969+Oqrr7TTQ4ZhNApNXteuX8fOvQcQGBqBCJf8iM/TQO1gzyxVKrawRLJrLoS65hILyeDQ97i/ejts45bBr349NGvSCC4u/+32UVzAyBG/YsbvM9GgbT/kK/jZJckQuHb2MPxf3sWokSPUUkTMEQqyv3T5sohJCg6LQKRLfsT51PsyJklZLK2QRC6BXoUQFB+JDecfY8+hf5Eze3Y0a1gPVapU4QrnJkhMbCxSXAwnWF0pLCwgsbaXJZpQF9q0adSoIUqWLIE5c/9E9UYdUaRUamXj6plDePP4OqZMnsixVYxpKCP37t3DnDlzRMYW+iegwZ38nWfPno0WLVpop5cMw2gEKrw1/5/FCJM4IsyjGFIK6TdVayosrZDsng9B7vlgkRiHHdee4six0WjVoinatGwhC6yk2gykkMycNRt1WvRAwWJl9dptsg5fOrEHQe8ei37xYjfz74tiV/Yd+hePHj9GnGs+RLmVQko2L+VukDZZgqL3sXNBTI5yiMleFkHRQXi99wxWrd+EsmVKo1WzJukWoGOMkxZNGiJg5yGE5KuXoUwYEtZhb+FqGY9ChQpp5H5kXRk/bgymTvsNrx7fgsX/LcsJ8fGIiwzGuLGjeWxiTEcZIR9nacAVCTblsKeMLZQqkmEYw3Z5mP7HPAT61ECKswEpIekgsbFHTI4yiMlWDDtPXERyUjI6tGuTKqCdJtffZ/6B2OhIlKpYU29WplP71yM5NkwoIpwOM+O5g+JZtu/ehyiJLUJcCiG5aBvV3LAySpag8AUWQt7DSeZzJOPUx9e4PX8p3O0t0bl9G1StUkVhimPGOKhbpzb8P33Cv2f+RYhP+inHVUUiYpQkwuorsVB5qaSYlBQ4Bt5D9vgPGDd2lEZlj2qCjB83Fm/fvk11vnDhwqyIMAaNyv9hefLkEcGFlAKONHqKH6FsOJqqtsxkDYrjoZSeN27dwZPnL8VucvnSJVC6VEn4+voqlbmIMU3evXuHRMdsGldEWjRvpr1ATytbRLgXwcPHT7+4RGPOhPFj8cfsOYgMC0a1+q10mpYyMSEeB7cshk92d/T/7ide0GbA9Rs3sHLNOkTYeCLc+ytI7NVzFZHGJxGOD/erFp8kdePyLIhAz4IIjgnBoi2HsHHrdnzbr4+IU2KME/q/79a5E0oWL4bFy1Yiwj4HIr1LZ6nOSHSF7rLEHDEl/qu5ozYSCazD3sAj6A6qVSyH3j0Hy+oHaRJSSLhQIWPyAey00KVJN1++fPj48SOWLVsmrCNff/21LKUko/0AdiqU9uHDB7x58wZPnr/Cy9evERQYgBRLG8SGB39OLEALMwtrJOapAJfEEFhGh8DaEsieIycKF8yPIgXzI2/evKIugaKaAuaOMQTeKStrlG1p3MQpeJXigWjv0p/lw8ADPSnrVrb35zHml58UujMkJCTg738WItHCHg3b9oGVlfJ7LMlJSQgLDYS7hzesMknDK09UZBj2rpuPmtWroHUrzSlBhi5vqo5rVGX+70VLcffFe4TkrKKcJUPHsmYZEwxP/6uoWrYEvunXO9N0zKaCocuauvMotT9y9Bj27j+IGCcfRHgVFy576qBSlkBFpKTAJvQl3EMfokj+vPi6e9csBawbI8Yga4yRKSM///wz6tSpIw5yz2I0M4jSz0CVVsmyIX9EREQiJDwcIaERCA0LQ3h4GGKioj6bkB3cEGPjijhbd6Q4eCDF3lW4PKSesK0RVenr/94oJQmWceGwjAmFY2I47BMjgNhwWFpI4OTsIrLOeIjDDZ7ubnBzdRFueRRETAfFCpmTdcUYBlFVZI0Wh/8sXoY7z98iJFc1SEhmDFEZSUmGU+A9eMW+x68//5hpmlZyl9q4aTMePnmBVj1+gL2DmgHQShD08R32bfwb3bp01HjiDkOXN1VlbcKUaXid7IHo7FSjxsJwFV9JClw+3kARlxSMHz3CLBQSQ5e1rG7q0SbF6bNnsXvfQURbOiHMvSiSnXOoJIdZUUYo7s0h5KlIN122TCl0atfGKL5zbWCun5vRojJy4cIFnDlzBnfv3hWuWqSU0ISsDXOj/I7umjVrcO7cuXTz66vSNqvXNT2Inj5zFksWLxKPKeDM1s0bFg7uSLK0RYKFDRIsbEXGDYm1nTA5S2wcxeOMBlS18qNLUsTgaZEYA4sk+hsHy6R42CIBtpJEWCXHQxITivjwINlLqIpziRIlYMqoOohqUla1OWFfvXoNK8htxikvIr1LZik3v0YXiBIJrMLewjPwFmpWq4ye3bqo5Ot8/PhxHDj0L9r0+glunpqPi3n19B5O7l2L7wcPQtGiRc1u0lZF1hYtXYHTL8IQnaOc0aRbdf1wFS0qFUL3rp1h6qSVNV3Os7quoXTnzh1s37Mf7z8FIdy9CBI8C2Zct0bFZAlpLW1uoY9hHxOIhn710bRRQ7GJZ84Y+rjGGHHRQ8r3T8GIZ8+eFb7oVEmY0vxqg61bt+Lq1asYM2aMeD59+nRUq1YNHTt2VLltVq8rCwX0085MWsidQ37Xjb67s+cv4GNAEIJDQhAREYH4uFgkJ0sAaxvA2h4p1vZItLQTR5I1KST2kNg4IcXWQbaIpB8xBZayCdsKKZ/PW1ohusKXftXJ1JZ++uQEWCdEwTIpBhYJsbBOjoOdJB42KQmwTIqDJCEWyUkJsLK0hKOTE9zd3JEtmxd8cnijfr26qdKuEvLuXjQhZSRe2mpL36/UbYaCZmnXXN22FGejL1nVtKylndRp53r/wcOizki0qy8iPYvJfKyl8pMe8rJGuNzenKrOSEz5Ll/K2v9ReF+qNxL2Fm4hj1Agdw70+7qHyJqljkzQRsmadRvQpOM3yOHz+fezov+l/5OSnLH8KGr74NYF3Ll4FD8N/QHZs2fXuKypI2+G7BI48PsfEVisrcoB6nqt/ZCciJzP92PZon9gbgtEXc6z2h7bFLUl13Jy37p64yZiXX0R7VkkVVxJ2rEto3Ew1dgmkcAm4g08Q5/A08kWbVo2Q8UKFWTvm7a/+pobjWUeZcwPtW3RlKu6efPmIk5k8+bNYgdEW8rIyZMnxa6KNCirffv2WLduXboDW2Zts3o9LTQIyg+E9A9JbkxUe4UGvrRQjEazZp+tFsTRo0fFoOBsbwNnnxwAHf+HFjw0gJPiRwctsj7/k9P7hf3/+ExUbDxuvotEtKWjmPyrVq0CB5m16nWqPsTEJeDOg0di14cUjOKFC8LWhkTB5v/HfwqGk5MTevT4T5mhatG0IAkJDsKOHTtS3ZesYxQ7JOXw4cMKs6zR4NWvXz/Z82PHjn2RAUQe+SrRp06dwsuXLxW27du3r2zQJbmkKrWK6NWrl8zt7NKlS3jw4EGq6xMnToS+ZFXTsrZ+/Xoha2mpUqGs+L4uXTuGeFs3hDn7wi83YGeZ/uQTmmyLs7H/+TxXq14Tjpby9/1P3iKSbXAqNo/seW2HD3C1Sn/hkOIkQbMBQ2UTl1TW0iMzWStdsjjePzgrDksra1Rq1Et27dmtkwgPfJfufcX30bSv7PGLO2cR+umV7HnRIoVw8OBBrciaOvJmqHwep2hxYmE8yRIIC6sMF12mjC7nWV2NbdLMe61atZI9drCzQdUK0nTgARmObfUd36cZ25B6bIvxgU3IS3iEPkTlMsVhnbuwuPbg/n1xSCFX5+7du8ue79+/X+2xzRzmUcb8UEsZCQkJERYRcteix7Rg1pawUcV3qswr7zNOj4OCgkSxIEdHR6Xb0iSTlevy7yWFFkzbt2+XPaeaKzNnzlT4eWigoQFRSkaBr/TPXbFiRdlzymKmqECSbx4ftG1VAa9ev8Hdhw6w/H/GmfTwyZkdUyZNkLm/LFy4UOHASIOdfH8zCnSnxAbybTNKc0qfW75tZm5+8m0zi1mhgHzpe2fWlnbfSeEi0vt99SWrupY12iXdvX0Ubt26JYohIilBOTcGDeLh4Z4qBkNTspby/4KM6iExSFkzdOg7KVa0CCKDHiPOW3OJTQ4cPISD+/dpzTLiFHgXlXVcndoQ0OU8q+uxjWRRvm2GWe9UcBQha3COF4dRoXQJfDdlrlCcFM2j5J7G8yjDKEbl1caUKVNEwaoyZcqgQ4cOqFy5slZz61PWqLQCLhV6yuIlfz6ztlKTpLrX0/sna9euHVq2bPnFoNi6det0Tcd0XX6XgyrZKyJt2y5dumTYlhQHKuTVoH498d5S83ba34fakhIphXaNFJlr0/ahadOmGZp25dv6+fkp3ZZ8imvVqqVUW1qwkgKsCJr0pL8Dyae8QpcWsjiRaxxRrlw5IdeGIKv6kLVPnz6Jyer7bweIPtDu1pkLl8XfZEcvhDv4IMktNyRWqSfSkzGZZIaRSGAZHQjnyLd4GPUO2b2zo06NqqhSuXKqasDakDX6fWf9MRvOOS+hRLnPik7h8vUzvO9/3Zbgzbv3sEyMxaBvB6Yb1KwvWTMGhgz6BuMnT8P7gETEaDB7m1YQAey3kN8uBv16D4G5oct51hDnUXqPg4eP4PLR47DOloIkj3wKxzaKp3T/dB0+LlaYNGqYsNIQPI+az9jGGIAyUqlSJQwdOjTVIkKbSDV92lGRBoFJrQNptfXM2krN7+peTw/a4Uhvl4MWLooGEPnzmWVtyUrbjNrLt80sqNDY2sq3p12mzOo/qNJWV7Kqb1mj/tHkQwf9X9AGxMkz53Hz1iFRqyTMtRCSXXKKBaZ8TIg8FPjpFPoMjhGv4ZMrJ/ya10LlypVkRVN1IROU8W/smNGY9tt0WFvboEipSsJtSxnOHt4Ky8RI/DDk+wz7og9ZMwZoATp9ykQsXLocd58dRXDOallO7asNKODYy/8KqpUvhX69e5llmnNdzrOGOI/SuQ7t2qJOrZqY/ecCvPMPRETOCkhOE+9Eqca93p9H145t0bBBA7FYl97bGOZGY5hHGfNEZWWkRYsW0CW0cKEFBdU3IbMhQY/pXNodFmXaZvU6w+hKVg0FmlgoaxodFJxImWn2HDyCN89vICRbGSS75U21601KiEfgbTglhqFZk0aoW3ugXrPJ0HuPHjUSU6b+BkcnV+TOXyTT11w/fwRRIe8w4pfhKmcAYlIvXIf9OAQ3b97EslVrEW6fExFkJaGMgHquim2RGAu3wDtwTwrFd4P7o2TJkjBXdD3PGire3t5Cgf5n8VJcfXEJYbmry8Y2y6hA5PC/gDEjh2eaapxhGNUwimTq9erVEz6l0qKK9JhMl+q0zep1htGVrBoitDCvUKGCON6/f48lK1bh1bvXCPWpJoJ/7cJewTPkHr7u1gU1atQwmB0yCqQdPuwnzJo9F536j4KLu6fCti8f38GTW+cwedJErdabIMWOfvPr16+LHVayOg8ePNigU5arC8nL/NKlRfa2A4cPIdKtEGKyFQfSuPzppCp2Ujycgx7CJfI12rdthUZ+fqxw6nieNWRIFoZ89y1mzZ2Pm0GPEONdAkiKQ7YPFzBu9K+i4DPDMAaS2leX0ES6evVqkUo47US6dOnSVFkiMmqrieuGUoGdMdw6I5qSVWOQNRo+tu3cheMnTsLCwhLZsmXDiGFDDTav/pUrV7Br7yF0+mZ0uooSVVbfuuQ3jB0zSgRlapNDhw6JDHnffvuteL5kyRLh723IKcs1IWtU3HXnnr04deY8Ij0KI9armEpKidqF6JIS4BT8CM7hL9CkoR9atWim1fpYxlhnRFfzrDGMbeRaNvTn4ZBQ3a+YcHRq2xotmjfVS1+MHa4zwpiEMmKMsDJiGhjDIMqyphpLli6DtUsuVKr15cJiz7r5aFCnGmpnEASqKSZNmoS2bduifPny4jllMqOUn5TdLi3fffedWMxJs41dvHhRpEqVts3qdX3UfaCA11179+PchYuIciuIWK8iXxTfTK/ug0VsBJwe7EZ0ybaQOLhmXtMmKQ5OwU/gFPEa9evWQYtmTYS7kDnXfTCW2g/6Htsocxgpz/RdkgtXRlm7GOOeRxn9YhRuWgzDMJqiZ4/uGD1mHIqXrwEnZ9dU7llWknjUqllTJ7uuYWFhyJ37v2w99NhQUpbrou4DJUHp06uHKGJIBTiBL2sppFv3wTkJqFuXrv7/SL+mTR37d3Cx/n9aZ3eyoJRFVEQYtmzZYvZ1Hwiu/ZA5JCcZJdxgGEYzsDLCMIxZQVmemjdrimunD6Bui27iHO1IXzi2E0O++0Ynu5+fF9+pswtJHxtCynJd1n3QdLwGJVBwD3kI67zOgHX6blhc94FhGMZwYGWEYRizo0GD+tg//FdUb9gOtnb2ePfqCTzcXHTmuiItOEqKhnTnlRQDQ0lZrs+6D+QGdvzEKRw4fBhRznkAr2yy7FsZ1bSh+g9ugVfhHPsRHdu1Qe1aNRUqOlz3gWEYxnBgZYRhGLODdpip5smF47uRK09BPLhxFi2bNtDZ+9Nutbu7u8hIRkH/BD02lJTl+qz7QM9btWyOJo0bYt+BQzh45BDCs5VCvGfhL+o+/P9msA96BPfQx2jbuiWaNGqoVBY0Q6jlwHUfGIZhoKBaGcMwjInTskVzZHOyQHzIS5QqXkgWSK4rqlatiqNHj4odbDooviCzVKoUZ0KHolSq6l43VIWxQ7s2mPP7NFR0iYbnm9NAcsIX1hCvV8dQPacF5v3xO1o0a6rVdMwMwzCM5uFsWiaaBYQxnywgLGvGiXydEanrjbTOCKcsTw1NUwcOHsKOg8cQVKChyLpFRQuzvTqGr7t0QL26dXTeJ2OHxzZGVxiDrDH6hZURLcGDqGlgDIMoy5rpYOjypm9Z23fgILYeOolol3xwCX+B/t06oE5t7adhNkUMXdYMQd4Y85E1Rr+wPZthGIYxClo2bwZHBwdER0XB3aMCKyIMwzAmACsjDMMwjFFA2aT8GtTXdzcYhmEYDcIB7AzDMAzDMAzD6AVWRhiGYRiGYRiG0QusjDAMwzAMwzAMoxdYGWEYhmEYhmEYRi+wMsIwDMMwDMMwjF5gZYRhGIZhGIZhGL3AygjDMAzDMAzDMHqBlRGGYRiGYRiGYfQCKyMMwzAMwzAMw+gFVkYYhmEYhmEYhtELrIwwDMMwDMMwDKMXWBlhGIZhGIZhGEYvWMPAefToEVasWAF/f3/kypUL33zzDYoWLap2+4yuBwQEYMiQIbCzs5O1L1WqFEaNGqXlT8mYAqrIamhoKJYuXYoXL16Ix7NmzUL+/Pl13mdGf9Bvv337dgQGBsLb2xudOnWCj4+PVsa2GzduYM+ePXjz5g2srKxQokQJ9OnTB15eXjr5rIz5zLM8tjEMY1KWkaioKMycORNNmjTBqlWrxN/ff/8d0dHRarVX9n6LFy/GunXrxMGKCKMNWbWwsED58uXx66+/6ryvjP4huVi2bBlq166NGTNmiL/0XFtjW0xMDNq0aYNFixbh77//hoODA+bNm6fTz8yYxzzLYxvDMCaljFy5cgWenp5o2LAhbGxsxF93d3dxXp32qt6PYZRFVdmiazSJFy5cWOd9ZfTP3bt34ebmhurVq8Pa2lr8dXV11drYVqtWLVSsWBH29vbiaNGiBZ4+fYrk5GSdfm7G9OdZHtsYhjEpN63Xr1/D19c31Tky99J5ddore7/hw4eLSZoG0549eyJ37twK+5iYmCgOKbQrRLuOtMBgzAdVZVUdWNZMh48fPyJv3rxiMSclT548Wh/bpDx48EC8H7lspQfLmvmg6XlWHVjeGMa80dt/Opl1yY9ZEeRKEBcXBycnp1TnHR0dxfn0yKx9ZtdpZ3L69OliYI2Pj8eOHTswbdo0zJkzR7RLj127dgm/byk1a9bE0KFD4eHhkel3wBgH2pBVdWBZMx15ocUW7S5TrIgUeq6tsU2ely9fYsuWLRg2bJjCPrKsmQb6mGfVgeWNYcwbvSkjP/74I5KSkhRed3Z2Fu4E5J8qD/k+k9KQHpm1V+a61LRMOzK9evXC2bNn8eTJE+EDmx7t2rVDy5YtU52jHR75HU9TJDY2FpMmTRIH7WCZMtqQVXVgWTMOWTPEsU0KBbDThku/fv1QtmxZhX1kWTMOWTNEWVQHc5Q3U5M1hjHKmBHaSaHBS9FhaWkpTMGvXr1K9ToyBefLly/de2bWXtX70e4lHRlBgyV9FvnDlAdQKRKJROyw0l9TRxuyqg4sa8Yha4Y6tpEiMnXqVHTv3h116tTJ8DOwrBmHrBmiLKqDOcqbqckaw5hsAHvVqlUREhKCEydOiN0d+kupAum8Ou0zu04Bne/evUNKSoowOa9fv14oIxmlOGQYdWSVSEhIEAdBr6HHJHuM6aPrse3t27dCEenSpQvq16+v08/KmJcsEjy2MQyjChYSA1fLKZ/58uXLRT5zysE/YMAAFCtWTFwLCgrCzz//LFJUZsuWLdP2mV0/d+6c8KUOCwuDra0tihQpInYRNbm7bSqQWZ7qFKxevVphPI25oaqsdu7c+Yt7TJw4UdS2YUxf1nQ5ti1cuBCnT58W45o88vdnTFfWdC2LPLZljrnKGsMYpTLCGCbkz0tBh+Tra+rmdEa/sKwxuoJljdEVLGsM8x+sjDAMwzAMwzAMoxcMOmaEYRiGYRiGYRjThZURhmEYhmEYhmH0AisjDMMwDMMwDMPoBVZGGIZhGIZhGIbRC6yMMAzDMAzDMAyjF1gZYRiGYRiGYRhGL7AywjAMwzAMwzCMXmBlhGEYhmEYhmEYvcDKCMMwDMMwDMMweoGVEYZhGIZhGIZh9AIrI0bOhg0bUKNGDX13gzFjWAaZ9GC5UA93d3ecOnVKPJ40aRLatm2r0fs3a9YMCxcu1Og9TQGWV4bRH6yMGBE0QdFEJU+PHj1w4cIFGBs0yVpbW8PZ2Vl2dOvWLcvfj4WFhbiXi4sLfH19MW7cOKSkpIjrP/zwA/LmzQtXV1fkzp0bP/30ExISEjT0icwDU5JB4s2bN+jTpw98fHyEzBQuXFjIib+/v7her1492NnZiWtubm4oXbo0hg8fjsDAwHTv9++//woZJNkyJ0x9bKLj6tWrMAUOHTqEwYMHw5wxJXnV5DgWHx+PX375Bbly5RIyX6ZMGbx69Up2ffny5ShatKi4T/HixbFx40adf1bGNGFlhNEbLVu2RFRUlOzYtGlTlu9JAy3dKzIyEvv378eyZcuwYsUKcY0m4EePHiEiIgK3b98Wx6xZszTwSRhjncCrVKkCGxsbsQghuTh//ryYiE+fPi1rN3PmTCFPYWFh2Lp1K96/f49KlSrh06dPqe4XHR2NH3/8kXdXTXBsooNkxZiRSCRITk7WdzcYAx7H+vbti+fPn+P69eui7bZt22RK282bN8UcumTJEvEe//zzD/r164cHDx7o5XMzpgUrIzpm7ty5KFKkiNhZKFSoEP7++2/ZNdqBoF3VdevWiZ0NGgRotyMxMRHBwcHCvB4eHi7bqTt79ixWr16N8uXLy+7x7t07NGrUSOz+00Azffp05M+fX3adJtUhQ4YgX758yJ49O77++mtxz8zeX5c8e/YMTZo0gaenp/iO/vzzT3GeBkB6TrszUlq1aiUG0PSgXZ3atWvjzp074nmJEiXg5OQkm5gtLS3x9OlTmBssg5+ZOHGikBFSWKl/9L45cuTAmDFj0LVr1y/a0/WSJUti/fr14rPNmTMn1fWxY8eie/fu4rs1Rlgu1IcWbw0aNBBjlre3t9iVln6mNm3aiM9DGyV16tQRmyBSyGo7fvx4IXe0q00LvLSQAkHfC31m+m62bNkiu0bj2F9//SV2qek67YA/fPhQdp2+3xkzZuCrr76Co6OjWDhSG+mYKrUQ0JhKVmMvLy+MGDECxgDLq2bHsfv372PPnj1YuXKlkEVqJ5Ur4uXLl+L+9evXF9f8/PyEzLAywmgCVkZ0DLkOnThxQiysaQL49ddfxS5GWjM67ULQP/nx48eFLytNEnReuvNPBy2000KLIXoP2u0gS4PUKiCFdjJCQkLEAp0GFxocaUDN7P0VQQOVoqNs2bIqfz9JSUliV7JcuXL48OEDdu3aJawXZA6mgZP+khmZLBzz58/HkydPUk1C8tCkf+bMGVSsWFF27vfffxeTD00edF26aDAnWAY/c+TIEbVcA8mFh/z45XcdL1++jGPHjmHUqFEwVlgu1IN2mEkR6dixoxizXr9+jc6dO8uUDfrc9Hnoc1eoUEFcIyWCoAUwHSRLtAlz7do1sSOdVk5JiaFF9LRp0zBgwABZm0WLFonvcd++fQgKCkL79u3FBo28+yndf82aNeJ3KVas2Bf9p3vR90kbM+fOnRMKkTRmxZBhedXsOEZ/Sdkg12ZSqEnRk/ccoA1CUvyOHj0q5Jrel6wstWrVUvm9GeYLJIxeadOmjWTatGni8cuXL2mGkjx8+FB2fcCAAZIhQ4aIxydPnpS4ubmlev2qVask5cqVE4/fvHkjXh8YGCi7PmvWLImvr694HBAQILG0tJSEhITIrj958kRiY2MjSUpKyvT9NcnEiRMl1tbW4vNIj8OHD0vOnTsncXV1lcTHx8va/vbbb5JGjRrJnk+fPl1StGhRiYuLi+T69euy8/T9UP/pXu7u7qLNlClTJCkpKV+8/4MHDyRjx46VvH37VmLumKsMkvwdOnQowzZ169aVzJs374vzCxculBQuXFg8TkhIkJQpU0Zy+vRp8bx3796SoUOHSowdc5WL9MYmOuLi4tJt//vvv0vq16+v1L1DQ0PF53j37p143qBBA8nMmTNl1z9+/Ciu0/cp7Uu1atVk12kss7W1lVy7dk08L1mypGT37t2p3sPHx0dy5swZ8Zi+37TyKy/T9D4WFhaS6Oho2fWGDRtKZs+eLTE2zFVeNTWOTZ06VfR5xIgRktjYWMm9e/eELK1du1Yme3PnzpXY29tLrKyshByuX79e45+HMU+sv1RPGG1COyNkFiUzLu0uxMTEoECBAqna5MyZU/aY3Ipo90EZaFfO3t4e2bJlk50jE7IU6XumfT9yV/r48WOW319VWrRogd27d6c6Ry4IZCK2tbWVnStYsKAwKUvp37+/CDJt3LhxKqsHQbtdyvSXXLbI+kKmc9rRNidYBj9DfaRdbXWg15FLjtQXu2rVqmL32phhuch4bCLInYdcfKTQrjpZQhS55sXGxopA4YMHD4pddPo8BFkxKIkGfS+0+y6F3Gso0Fge+c9M7jEODg4yywh9bz179oSVlZWsDVlFyMUove85PcjiTC5c8t9rWuuMIcLyqtlxjDwGSI6mTJkiZLBUqVLC+kNWt169egn3rdmzZ+PSpUvCLezu3bvCi4EsN/T/wjBZgZURHQea9e7dG4cPHxZ+u1IzqdRknxnSiUwRtIiPi4sTE510EKX3lEL+nXQPGmjlJx8p8lkzlIUGMEXQJEt+qKqQJ08e0T8yeVNAnrRfdF5eGSFXBHLB2rt3L1q3bg11oPcwt5gRlkGkcjsg5ZfkSVVXQvKtbt68uXhOyiy5YkgXr7RApUUjBZNeuXIFxgDLhXKQOw/9vmnvRVnU0oMWyxRPQu5PNIbRYtTDw0P2vdL3QsqMlICAAJHRSFnoe6P4j6ZNm6r92xgjLK+aH8doc46gsSs9aIwjRVzajv7ShiC5orEywmQV0xulDBiaxGiwpHgFGshot0zRJJYetGtGO1Y0YaUHDZA1a9YUgWu0I0cL7aVLl6bapaEBm/xaaZAlaBeH4jKy8pkUHepM9rTDTJ9zwoQJYlK+d+8eFixYICYegoI1KU6EfKBpp4YGYJoQlOnnqlWrxGKAfgPa1SH/axrIzQmWwf+YPHkybt26hUGDBomFBn0vlOqSLB3yQcLyUKwSySIFqg4bNkyco4wz9D50LzpIOaY0oaQoGwssF+pDvzUpnYsXLxZjFu3QkwWFoHgG2mEnBYTelz6/POTrTzEajx8/Ft/L6NGjVVIevv/+ezFW0uul70cLTGOwbGQFllfNj2Nk2SULH92PNupIpijeiBIwENWrVxdxItK+0F96TnFQDJNVWBnRIZTBgjLuULAjBdHRQKHKrj4FH9Lim+5DplHabUsLBXi/ePFCDLaUSYNM+PJmfxpc6LWUCpDM87TTRzt3hgJZQyglL/WJBnz6fmiwpGBCChSk4DoKJiSTN5mI6TyZkKW1RBRBuz303VDWFQrCowGWdnOkWWXMBZbB1LuNVDuCdkCrVasm+kITLrku1K1bV9Zu5MiRsvz8FCBMckmBxvT5CAr2pF1v6UE7pbTLKe+iYeiwXKSGxqC0dUbSc9si6Den4GT6fPTZKAh4+/bt4hqNXeT6QueptgPJlzzkBkPfA31WckelhR3JmrLQYphcTUku6Tsj91NzqP3A8qr5cYzklDZQLl68KD4XWduGDh0qlG2C/lJqX/JKoP8HsqiQ/NLBMFnFggJHsnwXxmChtI6UcYQyYDCMPmAZZNKD5YIxJlheGUZ7sGXExLhx44YwwZKOSbs05OLUqVMnfXeLMSNYBpn0YLlgjAmWV4bRHRzAbmKQryj5jlJudPKn/eabb1QObGOYrMAyyKQHywVjTLC8MozuYDcthmEYhmEYhmH0ArtpMQzDMAzDMAyjF1gZYRiGYRiGYRhGL7AywjAMwzAMwzCMXjCJAHaqJEpF8KS5winfNxX0obzZqrSlQj8rVqwQBfGoIJKnp6fIXU65zBnzQFOyRFB14FOnTolCVOXLl8eIESNSvZ6Koy1btkxkbbG1tRUFGDt27KiTz8kYP5nJlzyTJk0SxULl5Xj+/PlijGMYTY6NPI8yDGOWysjOnTtFCr65c+eK59OnTxeVUNNb2GXUNjk5WVTKHT9+vCgERFVXKbc4FVUqV66czj8XY7yyRJAsUXEpmpSDg4O/eD1VkKfqugsXLhSVcKdOnSoK6MkXqmIYRWQmX2mhomVU6JNhtDk28jzKMIxZummdPHkSHTp0EAOgdIKm4kSqtrW3t0eXLl1EZVKq2F20aFGUKlVKDMCMeaApWSKoGm7VqlXTragcHx+PCxcuiMq+VE3ex8cHzZo1U/heDJOWjOSLYfQ1NvI8yjCM2SkjtLNMu4L58+eXnaPHQUFBwg1G3bZEQkICnj17Bl9fX4XvTyZpeq38QecY40ObspSWDx8+CLeHtK8nlxtFsKwxWd3Z7tu3r3DnOn36dIZtWdYYTY13PI8yDGPyblpxcXHir6Ojo+wc7TQTsbGxqc6r0pbKryxevBi5cuUSu4+KIDP19u3bZc8LFCiAmTNnaujTMaYgS4rey87OLpW/Nb2GXqsIljVGXbp37448efKI2KR79+5h3rx5cHBwUDi2sawx8qg73vE8yjCMWSgjZBImaCfF1dVV9pigyVadtjSALl++HP7+/sLv1dJSsQGpXbt2aNmypew5maWl1Vtp55sxHqSy8Pr1a2TLli3V76muLCmCXk87huRfLVVI6PUZvZZlzfShRZs2IFcZKRTs3qhRI+EmqGiByLJm+qgia+qMdzyPMtoe1xjTweiVEWdnZxEY9+rVK+GjStBjOpd2t0aZtjSAUiYQMivTAJrZDreNjY040oOL2xsXNKm6u7vj3bt3Qiakiom6spQRFCNCSgjdv2DBgrLX58uXT+FrWNYYTSFd7CmCZY3JynjH8yjDMGYVM0LUq1dPmHnDwsLEQY/9/PzUaksD6OPHjzFu3DgxADPmBe0UHz16FBEREeLIiiyR1YOsHykpKWJCpcfSXT5y0apRowa2bNkidhhp95BStXL6S91Bv8exY8fE93758mUYGxnJlzzR0dEifTQlTaC2lH2LZJwC4BlGG/Msz6MMw6iChcQEth1oAl69ejXOnz//Rf7zpUuXinMDBw7MtC2ZhL///nuxQyNvUqY20tcrC92LA/BglAs8mmSvX78unlOaXXVkidi6dWsqP2iiZMmSouYDQUoI3VNaZ6Rp06Zq1RlhWVMPqtFx5PhZFCpRAdfPH8HE8WNlu776gixmypKRfFHa1eLFi4uMR6RU//7773j//r1oQ+mjmzdvrpbiy7JmOqgia6rMszyPMlmVNcb8MAllxBDhQdQ0MIZBlGVNdchCMHLUGDTrNgSe2XLiztXTSAh9jQH9++m1X4YubyxrpoOhyxrB8mYaGIOsMfrFJNy0GIZhVOHM2bPwyplXKCJEqQo1ce/+Q5FymWEYhmEY3cHKCMMwZgVVu9+5czdqNuksO2dlbY06zbthydLlwmrCMAzDMIxuYGWEMSioiBbFa9CRUQFAhlEHUjT+WbgIXzVoCxdXj1TXChYrCyePHNi9Z6/e+scwDMMw5obRp/ZlTAcKX5o9Zx48sueBrZ0DHt25jDmz/+BsLEbg102ZmqRQELi1tWEOLTt27ISVgztKVqyZ7vX6LXti85JpKFK4EMqUKaPz/jEMwzCMuWGYKwbGLLl48SKc3LOhScdvxHNnVw/s3LULX/fqpe+uMQqgOgK/zZoDK+fPdVlSEuNQsWRRDPlOtaw5uuDKlSu4euM2On8zWmEbG1s7tOw+BMuWz8bYMaOQI0cOnfaRYRiGYcwNdtNiDILQ0FBs2boddZt1k52rWLMJbt95gEePHum1b4ziVJ//LFmOkDy18ClvPXEE5m+MG3cf4Pnz5zAkyOVv/cbNaNXzR1jb2GbY1sMrB/za9hVWOmmVaYZhGIZhtAMrI4zeoWJtc+f9iRqNOsLVI1uqoOJmXQZh0eKlwhWIMSzWrN+AAAt3pLjIWQ8sLRHs8xXmzP8bUVFRMASo6N+f8xegaadvv4gTUYRv4ZIoUbEOFi5awhWgGYZhGEaLsDLC6BXKIT9n7p/IU6Q8ipWt+sX1bDlyo27Lnpg56w9hPWEMg/0HD+HsjQeIyFHxi2spTtkQ6FoMU2fMRFxcHPQJKRKLlyxD2a8awidfIZVeW6FGI8QlW+LIkX+11j+GYRiGMXdYGWH0Bi1UZ/0xB2458qNavVYK21GWo6oN2uO36TPYQmIA7N67H9sPHkdwvrrCEpIecV6F8UqSDZOmTheWCX3GIUXGJKBcNdWrjVtYWKBR2744dORffPr0SSv9YxiGYRhzh5URRm+1Hqb+Nh058pdCjYbtM21ftHRl1GzSVSgkr1690kkfmS9jRBYuWYbdxy8gOL8fYJVx7EWMdyk8t8iJUeMmwt/fH/pQdikOqUGb3kKxUAc7B0fUatIZa9au03j/GIZhGIZhZYTRA+/evcPkKVNRulpjVK7dTOnXFShWFk27DMbcP/8SdUgY3UEWKVIqzr8IRbBvPcDKRqnXxXkVxVv3chg/ZTrOnb8AXfLv0WMoUroKXN0/Z/pSl8IlKyI0PEpkDmMYhmEYRrOwMsLolJs3b2LW7Lnwa9cfJcp9pfLrc+bOj479R2LT1p3Yt38/BxdrGfp+j584idETJuO5XWFE5KwIWKg2bCS75kJA/kZYvmUvZs/7SyeB7WTFOXb8OCrWaprle5FVpUq91ti9Z59G+sYwDMMwzH+wMsLobFF78NAhrN+0FR36jUBu3yJq34t2uqlWxI07j7Fk6TKx8GS0Yw2ZOPU3rN13AgEFmiDJPa/a95LYOgrXrstBlhg2cjQuX7kKbXLhwgXkLVgSjk4uGrlfgaJl8MH/IwICAjRyP4ZhGIZhPmMh4a1lrS3kKFMUA6SkpGDV6rV48+ETmncdDDs7B43cV5KSgnP/bkPYp1cY9vNPcHJygqbx8fGBuclacnIy9h04iH2HjiDUuzwSPfJDk1jER8LT/woK5/LAd9/0h5dX1tyo0pO3kaPGoFnX7+HpnUtj971z9TQSQl5jwIB+0BaqyNvhw4dx6tQpUUOlfPnyGDFihMK2VC9l2bJluHHjBmxtbdGkSRN07NhR5f7xuGY6mOPYpipz5i/Avbt3aTcN06dNQa5cmhtPzAljkDVGv7BlhNF6DRFK3RsWk4I2vX5WShFJTkpCcKC/+JsRFpaWqN20C/IVr4rJU6YhODhYgz03TyguYtiI0dh+9g4CCjbXuCJCSOxcEOzbADei3TFi7ETs3bdfKECa4vSZM/DKmVejighRqkJN3HvwEO/fv4ch4OHhgfbt28PPzy/TtitXrhTucQsXLsTkyZNx/PhxnD59Wif9ZBhjhOaTB4+fIqhkJ0TkqIB9Bw/ru0sMY7KwMsJoDdqN/W3673DNXgANWveCpYI0sGkJCw3EitkjxV9lKFetvkj9O+23Gfjw4UMWe22exMbGYtHSFZg+7x+8ci+PcJ9qgHXG2bKyhIUFEj0LIqBQM2w9cwu/jBqDly9famQnddeuPajVtAs0DRXhrNeiBxYuWmwQ1oFq1aqhatWqcHHJ2BUtPj5euK117dpVWA9pl7JZs2Y4ceKEzvrKMMbG+s1bEe5RXIxVCV4Fcfnqdd7wYhgtwcoIo7XUvVOm/oaCZaqjWv1WaqdWVZbCJSvAr21fzJw1m1P/qsjtO3fw86+jcOplJAILNUOKc3bdvbm1HcJ9vsILl7KY+sd8rFm/Ue2FfmRkJP6YPQf1W/WCs4s7tEH+oqXhU7C0UEjIHcwYIAWd4qry5//PykWPyb1LEfQb0GaC9CBlVQr9L/Nh/AejmAcPHuD2w6eI9yr8+YSlNUK9y2LBoqWcNIVhtIC1Nm7KmDchISGYPmMmKtVtpVbGLHXJU6CYiEmh1L9DBg9C0aJFdfbexggtOFetXYeLNx8gOHcdSOzd9NaXFJccCHRqhiN3b+PmrbH49eehyJ07t9Kvpx3LmXHb/eEAAQAASURBVLP+QPmazUUKaG1CdXFO7F2LP+cvwJDvvxMxGIYM1Vuxs7ODlZWV7Jyjo2MqBSMtu3btwvbt22XPCxQogJkzZ8Lb21vr/WUYfRIaGor5/yxGcO7aqTIHJnoUwIt377Frz160b9tGr31kGFODlRFGo1C2od9n/oEajTsLa4WuyZE7P1r3HIq/F87HwAH9ULp0aZ33wVgm3Gm//wF/eCCyYGOV0/V+QUoyLOKjILFzBiz/W/SqhKUVInNWREyEPyZMm4Fv+/VG1SpVlNrFXLJ0Oeo0745CJcpD29CucoPWX+PSiT2iXs7PPw1FtmzZYKjY29uL2C2Ky5EqJGTtcHBQHL/Vrl07tGzZUvZcupNObnCcvc404GDsL4mOjsbk335HoFc5pDh4pL5oYYFQn6+w7+hRZPf2Rq2aNfTVTYYxOVgZYTQGVdkmN6l6rXohfxH9KQHZcuRGuz7DsWzFPPT5ugcqVNC9UmQMKXs/upfWSIC6082NsEhJhEVKMlKs7BBdsUeW7kd1SQLtG2HR6o0Ij4hAIwUB2rS43rlzFy5duY7WvX6CV3bVMrb8PXUIEhPixWMbWzsMGf+30q+lxXl1v7Z45uMr3BF79ugm4jcMEYoRISXk9evXKFiwoDhHroz58uVT+BobGxtxpIe+3VSmTP9dFE4tXrwEhv34vV77wpgOlOBh0tTpeG/vi0QP3/QbWdkg2Lc+Vm7YAksLC9SoUV3X3WQYk4RjRhiNQIsDsoj4teuXJUWEFohr5o8XjzcsnKr2fTy8cqBD31+wdv1GXL2q3ZoWxgTtiE+mQH/PChrLlGWRkiQUEfFYopldc4mtE4LyN8TGnftx7fr1L65//PgREydNwdvASHT9brzKighBioj8oQ6FS1RApwGjsefAvyKOJCPXJ01DyhhZPCh2hRQEepye1YJctGrUqIEtW7aI3582DSgtcIMGDWBskDve6/cf4V+oFe7dfyA+D8NowlI8duIUvLbJhzivjN17JTYOYmxatmErjhw9prM+MowpYxKWEZqA16xZg3PnzonntWvXRu/evVP5SCvbVpXc/cx/isgfs+eiSadv4ZOvUJbuRYvCpMQE8Vj6V11cPbKhfb8R2LRqtnheRQmXH1rgkb/89evXxe53nTp11JalzK7/888/4pq19X//huPHj9dqrMvyVWsR4JgfyW7Kx2PoDWs7BOetiyUrVqNE8eKyOjKnTp/Gzl17UL9lT43Fh2Rlt9/F3RMd+43A9fNHMHbceAz+bhAKF/5/4KsW2bFjR6q4jp49e6JkyZKYNGkSpk+fjuLFi4vUv0S/fv2wdOlSDBo0SMS4NG3aFHXr1oWxcerMWUS5+AqXvni3fLh48RL8/IxPqTL1edaY5lGav6bNnI0AzzJIdFdgEVGgkGza+y8CAgPRs1tXTgrAMOaujOzcuROPHj3C3LlzxXOaiGlBmV5Rr8zaSnP3371712jT+B05ehxnzl9Mda5Tu1YoX66cVlx+Zs+ZiyYdB2ZZEdEGLq4eaNf3F2xYMUv4yGcWQ/Lvv//ixYsXGDVqlKw+g7qypIxcUvG5Pn36QBdERETg9r37iC3SCsYCxaBEuvji+ImTaN6sKVauWo13/kHo+u04ODq7wlCgmjeVazdD3kIl8c+ixWjZvKlS9T+yQufOncWRHmPGjEn1nALWf/rpJxj7YvjfYycQ69tIPI/0KIzdBw6hQYP6vBA0sHnWWOZRyiS4YNEyBPpUVz2LIG2W5PfD0WsX4e8/Hz/9MNjgk1kwjKFiEm5aJ0+eRIcOHcQAKB0EFeXQz6ytsrn7DZUTJ09h8+4DuGdTDPdsi38+rApiweLlItBXk1D9AlJE6rToCR9f7e8EZ0UhafP1T1i6bAU+ffqUYdvLly+jcePGcHNzE0dWZEkVudRVQcNEl1xZD1bXMbHOuXHjzj1RPDM22Q5tew8zKEVEnhw+vujy7TicOHMRu3bv0Xd3TIqjx48j2jGn2JUmKPtbBByFdYTRPqqMZ8Ywj5KL1fzFKxDg20D9dOaWVgjNUxM3A5MxbtJUseHDMIzqGNeqREHQGe28pM2hHxQU9IU/sSptlcVQ8vGTe9Ga9Ruwbsd+BOVvgBRHD6Q4uH8+nLMjMF89zF6wGEf+Paqxvm3dth2+xSqioJZTqWoCiiGp17InFi1eKp6n93notwsLC0OePHlk59SVJWVljapg9+3bF8OGDcO+ffsyrF2RVVkjVyQJjHAH2dISIUFBsHXOhjrNuypdPFNf2Ds4CYWJAutv3brFtR80AC3ydu7ejwjvMqnOh3qXw9qNm0X6YkZ7aGPu1Nc8SqzbsAmb9h5FYIHGkNi5ZJwlMDZc/FWIhQWicpTDC6s8GD1+ksgoqc/6MYZ4MIzJu2lJJyFyQ5Ai9S2nAU3+vCptlcUQ8vGTxWPqjFn4BDeEF2iUbmpV2kUMLNgEm4+cw5UbNzFu5K8q1XFICy3ar1+/gV4//gZjoWDxcrh37ZQI4K1UqdIX12lilU6yrq6fd96lO12qypI0BiEjWaMq2L169YKzs7OwWsybN08M3PIpVTUpa7RTab96IzRNi+bN0LJ5M/GYPvXO+2HYfeWZxu5vE+mPhLhY1G7WRaMTW7OmTdG0aRPxmO6baOeEd4HRGrm3jY0tGrXrh737NqB58+Yauae5Qv9Lfy9eilCvEjKriOyavStCXfJj+eq1GDJooN76aOpoY+7UxzxKm3bTZ/6BM3dfICR/g0zTkFO6cud7OxBVugMkDhnXYYr3LIT31g6YOHU65v3xuyxzHcMwelJGaLF38eJFUfxuwIABeP/+vfD39fVVLjhM1Rz6BO2mSBeQ0p2atHn0VWmrLPrMx0/f85oNm/H45RsE56icuanZ2g5BeWojLPQ1+g/+EV9VroQuHdvB3V31atUXLlxAgWLlYSUXfG3oC0SiaJmv8O/RYyLdaVqkskApUKV1I6S/p6qyJLVwZCRr8pMVBa23bdsWZ86cUaiMaELWcmbzQGD4e40GsB84eAgH9+8TjyWWVoiq1Ftj96YdSZeQp/DIkR3W1umnmlWXQ4cPY+/ez65U1ja2GDZtuUbv75ndR+yS0v+psnDthy85evwEHn8IRXy+9GPeYrxL4fr9o8LFktyDGM2jjblT1/Mojcl/LvgHN96EISx3TWHR0DTJrj74YGmDH4b9ivGjftXKmscY4XGNyQyN+ztcu3YNo0ePFhkqzp49KysktG7dOmgD2lX28vISefOl0GM6l3a3RpW2ykK5+Om10kN+YBZuMVo4qM+/z56HMVNm4HKYIwILNlPJ5zXJwxeBhVvi6PNIDBs5FouWLheLJlX6QBORnePnnTFNLxAHDx4sjh9+HKpRRYSwd3RCdHRMup+JfjtSzEh25b9rdWRJHVnLbNdfE7I2sF9veH66DiRlLVOZrnD9dAt1a9dAbFQ4wkMCNXpvqi1CSggh/atJnty9iiJFCqv0f8Wk5uXLl9i8YzdCctdQvHi0sERwnlpYtnq9SoofozzamDt1OY+SIkLznFBEfKppRRGRkuLsjQCfmp+Lyvr7a20dYEwHw+hcGdm0aZNQRn788UeZbzeZXOUHMU1Tr149YeYl1yE66LGiTDaZtVU2d7+uof7cuHEDoydMxuTZC3ApzFkoFImeBdUbWC2tEOddAgFFWuHoqziMmjgN02fNwZMnT5QaPGjHx//1Exgb7189QcECvhm6Mh09elS4Z9GRFVnK7DpZl0ipo+/7+fPn2LNnj9Z3dvPmzYtObVrA691ZEioYMnYhL5DbOhI9u3VB7697Ye/6vxAVGaax+1ORw95DP9ey6TH4c20bTfH+9VNcPLYDPbp30+h9zQn6/5s5Zz6CaRfb2i7zujQ5q4oxTJe1XswJVeZZQ5tHd+3Zi8sPXyPMp6pWFREpKU7ZEJCjqnCfpngbhmF07KZFrlnFihVLdY7ykGcUmJtVKMNHZGQkfv75Z1n+czL7EpRbnxg4cGCmbTPL3a8PaLF6/OQpHDz8L2Jt3RDqXgwpBdXM/JEellZIyFYMAV5FERz+Ds8WroKrjQTtWjVHjerVFVZhLlSoEFISY/H62QP4Fi4JYyAyLASPb19Eny7TFLahVLv0nc+YMUM8p1oM6spSZtePHDki7kkTt6enp8jipchFS5M0a9oE7/0/4szdCwjNQzvOhhcQbh32BjkjH2HclEmiDkuFChVEkOv6pdPh16Y3fAuXgiEiSUnBzUvHcO/KCfz6yzCZux+jGrRwJcUi0KOkWNgpQ7JrLnyKD8PsPxdg7MhfDD7RgbGhyjxrSPPo7du3se/oKYQUaKLTsU7IY2IUZs75E5PHj2F5ZJgMsJBo2IZG+e2lAw9lCVq1ahXu37+PzZs3Y+pU9StqGxvk60qLp6y8fueefbhy7Tpi3fIjyrOo2P3TBZaxYXANfQz7KH/41a+HFs2apJuikUzQM36fhTa9foJXDs3EIFAF9oT4OFHw0N7RGT9OXKiR+8bFRmPHilno0qkdKleurPTr0ostMQVZo3/7hUuX4/LjdyI1ZVYmaefra0UVdk3FjNiEvUausPuYMmGscAORh+LPKCOas0cO1GraGc4uqsc7yRMc6I8Vs0ei/y8z4eWdNb/mj+9f4dS+9cibOwf69P5aFuCrCoYub1kd15Rl2crVOPXoIyJyKf+/KpBI4PH+AlpWL4POHT8XfGSMU9Y0IW/h4eH4dfQ4fMxbXyQ7UBXKpKVsALsi3N9dQJuaZdGxfVuYK8Yga4yJKSN37twRWYHq168v3F0oYxBVYh06dChKlTLM3UxDGkRpgb9hy3Y8fPIMYR5FkeBZCLDUU9KzpHg4Bj+Bc9hzVK9WBZ3atxW1N+Qht66//1mExh2/QZ78mqkcrskFIhERGoQ96+ejZbMmqF+/nskNourKGv3rr1i9FmdvP0FI3tpqy5kmlRG7kOfIFfVUKCJUyyA9yMpKKZF37d6LYuWqo3KtprBzUM9vPTkpCWGhgXD38FY7GUNYcAAuHt+J8CB/fN2rh9iIURdDlzddKCNXr17DwrVbEESZAdVRklOS4P38MH794VuUKFFCG100CQxd1rIqbzS+UdzG7WhXxHupXgfL6eZGWKQkwiIlGSlWdoiu2EOtfiA5Ed7PD2HS6F+QL18+mCPGIGuMiSkj0mxEx44dEwMJ7Ww2atQoVX5yc0DVQZT8nNdu2IQrN24j1LMUEj3zq71b/XkQpcWhBBJLG0RX6I4skZIE++CncA15jGaNG6Jt65bCdUYKBXzPm/8XSlSog0o1G4tq1IaijDx/eAunD25E3969hKuPKQ6iWZ2wt27fiUNnLiM4Xz3A2lZvyohj4EPkSfbHpHGjlSqWRulGDx46jJMnT6FU5TqoUKMR7OyyntlHWcJDg3Dl5F74v3mKDu3bonr16ll2xTB0edO2MkJxIsNHjcWnfH6Q2Dkrrv0QH/X5uoLUrJaxofDxPy9SrEozQTHGJWtZlbfzFy5g2dYDn8c1NeJENLnJYhX5EQWj7uOPGdOE27q5YQyyxugXrWy5U3Bz//79tXFrk4QW8+QfHeyYDzGFWogib1mBBlDpIKoRLK1FsHucZyHsvngbl69ew7hRv8qsJFQkcNqUyVixcjW2r5yFRu37w91Td3VW0iM+NgZnDm9BZPB7jB87Wqd1X4wJyuDVpVMHuLm5Ysuegwj2bfBFLYfMkAiLikTsIEos1BhSJBK4fLqNgg6xGDdqgtKLR2rXvl1bNGncCAcPHsL6v8ajdOW6KF+joVaVErK0XT61Dx9ePUab1i1Re0h/s1xgaIPV6zcizL2YYkVEydoPKQ4eCHXKhy3bd6J3zyxuxjBGBwWNr1m/CSG+DXUSsJ4ZyS45ERj5GvsPHkKbVtqPC2QYmLsyQu4TiqBgYCY1lJVkyoyZ+JSzukrpefWClS3CfaogJuQlJk79DX/M+E0W4E6pGId8/51I7bxu1R8oXaUeKtZsDCsr3bqY0U7/k3vXcP7fbWjc0A/Nh/TnwEElaNq4EZydnLBywxYE+fpBYqu82xNZ3qS+1TElVJxoJRK4+V9DyWw2+HXYKIUJEzKCYjM6deqI5s2b4cCBg1i/YDzKVm2A8tUbiuKDmiIqIgyXT+7FuxcP0JqUkMF9U1kImazx6dMn3Lr3EHGFW2jkftHeJXHm3H60bdXiC/dSxrRZtmoNQt11F2epDGHZK2DvgYOo8VU1rW+OUQIIqUXJ1taWN0sYg0fjM+mBAwe+WGxTBg7ylWRl5Ev2HzqMENeihq+IyJHoWQBB7wNw9epV1KhRI9U1Cg4nn/ktW7dh4z+TUbdlD+QrWFyl+5P/Prlo0V9VCAn6KAKIHe2s2BqiBrVq1oCdrQ0WrVyHoPwNVVJI1EIoIldRLpcjhg39IcsTJiklnTt3EkrJnr37sO6vcahStxVKV6yZJdfB+PhYXD19AE/vXkHLls0xdNDXrIRogb0HDiHco5jmMh5ZWiPSvRCOHDuOzh04mN1cuH3nDu48eYk4yp5lSFjbIiR7Bcz/ZxGmThyfaV0pdXn27BnmzvtT1NSChDL8JWP0qBHInt141hiM+aHxGXXWrFlfnKP6CZS+lPmSqKhoJFtr1qe5RfNmaNm8mXhMAUE774dh95VnGn2PBEs7WQXetFDRqr59eovaMitXrcbdK56o07wbXFzTD0hOCwUSqxIrkpAQL3asXzy4jp49uqFSpUpKv5ZJTZUqVZAikWDJ6o0IpADiTOo7ZAVyzSqd3R7Df/qvJpGmCrRRfQ9KYbxp8xZsWnwcDdr0Qc7c+VW2sj2+cwUXju1A3Tq18M3MGbCz0973Yc5QUoIrV68hgdxUNUicRyGcOXualREzgWIvFy1dgRCf2gbhnpVeweG3b9/g2PETaNQw/Rot6hIfH499+w/g3PmLaNd7OLxz5RXnXz65i2m/zUCbNq1Qr25dtpIwBolOtvdatWqFb7/9Fu3b84SQlob16+LKvH8Q6JaXVuEaueeBg4dwcP8+jaVaTYtFQgxcI1+hcuUBGbajpAWTJ03EmbNnsW3pdJSp2gAVazbSmOsWLRaf3r+Gc0e2oU6tmvj29+nCJM1kjWpVqyIiMgob9hxBsK9flmOY0oMSIuS3i8YvP4/Vmhsd1W75fvB3ePz4MZavWA7fYuVR3a+tUvIXEx2JoztXws4qBRPGjTHIeiHkirFmzRqcO3dOVvehd+/e6S42/vnnH9FO3qIzfvx4FC2qmQx4moibS7FzBaxUd9PLCLLuxSZJEBoaqjA7G2M6LF+9FqEuBZHikLWU39okNGcVbN6+CxXKl9PIuEJJH46fOIGTJ0+jaJmq6D54Imzt/tvgLFC0DLJ/Ow7nj27HgQOH0KxZE9SuVYsTOzDmp4xQ+lcmfQoXLoyWjepj74mTCM5bR6s70ZrAIj4S2V6fwrf9esPdPfMBn0zRdevUQZXKlbF5y1ZsXDgZDdv2Qa68hbIcRHx87xo42Fhi3JhRbILWMI38GuDV6zc49egmInJp1tJkGR2MbOGPMWbGNJ24O1ER1t+mTcHGTZuxfflMtOzxA5ycFdcc8H/3Aoe2LEa7tq3FTqK23Cmyys6dO/Ho0SPMnTtXPJ8+fbqoit2xY0eFBT379OkDQ+Txk6eIsktdU0ZTJDh64+nTp6hatapW7s8YBg8ePMCN+08QU9DA3LPSILGxR2j2cliwaKnIHKjO+EIV7W/duoUzZ8/jzdu3KFmxFrp9NwEOTulnIXRycUPj9v0RHhKIW5eOYc+ekcKduk7tmuIvx1Uy+kbjK4ERI0ak+uci0yEFJlIhRCZ92rdtDRcXJ2zavgfBPl8ZbPwIFaPzCriFHwYPRNkyZVR6Lblu9evbB8+fP8eSpcuRp2Ap1GjcAdbWNipbQ+5cOYXrZw+ie7cuqFatmsEuFo2dvl/3xIPR4xAd+VFkg9EIKcnw+nABw4f9INypdAVZzKgQ4bnz57F9+Qy06/MLXN2/XPy+fvYAJ/euxvCfh4qsgIbMyZMnhSVEuuNPlud169YpVEYMmfuPniDe3lMr946ycRd1m1gZMW03v8XLVyEkV1WNxRxp09050T0/Xr95hRs3bijtVkwuaFRN/tKVq3j29CnyFS6FYpX84NexuNIxcW6e3qjbvBtqNe6EF49vY8/BY1i8dBnKlC6Dr6pVEbXgOB6O0Qcal7rmzZunek6mQHLXyZlTQ4sZE6WRnx+KFCqEOfP/RnBUDkRmL6swh77OSYqHx8fryO2Ygl+mTfqiKrYqFCpUCNN/m4pt23dg86KpaN71O3gqGR8SFxONIzuWw9nBSux0K1OLglEfmpR+GvIdJs+ch0Dn5hqZ5B2DHqJGlYrCIqgPatWsCSdHR6xbMxddBo5NVSzx04fXOLF3NcaMGokcOXLA0FOXBgcHp6rfRI+DgoJELBcp/+llOqSDlBcqStuiRQuFO6KUiUe+vgMp/JQxT/pYG0G3KT6qFSRVlmSn7Hjw6A5vWpgwlMUx3MIJKY6as65p1d3ZwgKh3uWwfsv2DJURqiB//fp1XL5yDR8+fED+IqVRqHRt1G79TYbuppkVc6VzRUpVEkdiQryIKzl0/ByWLV+BwoWLoGqVSihfvny64wjDGIUyUq+ediYUc4AWE3NmTsemrdtx+sJBBOeqpncriXXoa3gG3kT71i3RrEljjZhzaZHbrWsXlCldCsuWz0Pdlj1RsFjZDF8THPAB+zcuQItmTeHn14AXFjqCrANlihfB2YCXSPTKmmsdVSJ2CXuGbp1nQp9Q8cuPnz7h+N61aN5lkDhHE/LhrYvx45DvDV4RkRZ8JOQXC5RNTLqDmnYR0axZM/Tq1UtYo2jhP2/ePPE/1LJl+qmYyd1r+/btsucFChTAzJkztZKhjhSo+GSJUvVtpFWxCceH+5Wqii2xd0Xw2xCR3pcXV6bJsdPnEO6axfFJx6Q4eiLiY4KQf/nYEYoBuXjpEi5cvISIiEgULFER5eu0QdPcBZS2gJAiomzhYBtbOxQtXVkcyclJePfyMS7dvI5Nm7cid+7cqFnjK5HYhGNMGINXRg4ePKiW1YRJ352EinTVrvEV5v+zGIGRXojMUV73VhKyhvhfRV4XS/w0ZaJWFiGlS5fG+HFjMHPWbMTHRqNE+erptvv4/hUObl6IwYMGonhx1dIEM1mnc4e2uDdjLgKyqIzYhTxDrepfyRbN+qRpkya4eOkyju1eLYI9gwP8Ua1KZWG5MwakCwOygri6fo5/kWa3k1ow5ClYsKDsMQWtt23bFmfOnFGojLRr1y7VNanyTxWxKXBek2zbsRMRTp8z/yhX0PVzZkYLiZL9sLBArEtubNuxA40bNsxKV02KXLmUz1ho6AR8CkBK9iIwNlLs3REQECC8De7du4dDR47i/fv3KFq6Kmo3/xrZcuZR+Z5/Tx2ChPjPmxUbFk7FjxMXKv1asrb4Fi4lDklKCvzfvsC1u5ewZdsOlCheHM2bNREbEwxjkMoI1ZtQBlZGlIcWD7N//w0bt2zDqYuHEZynFiT2uincZRX5EV7+l9GxTUs0bdJYq1YI2hEihWTab9Nha+eAQiXKf1E7hBQRY/DhN1Vod8zTxRFBsaGisrW6uEW+QtPGnWAIkEz/PPRHWXINS8tiKFeuHIwFsnDQAobSZ0tdYOkxnVNm9z+z/2kqPqmoACXFbWnS3ezI0eOIKdgU2iTSszh27NqLOrVqcXpmE8TTyxOv4sKRrIR1zZCwjI8QlszxEybB2t4ZFWo2QaPOJbI055KVNykxQTyW/lUHssL4+BYWR51mXfH84U0sWb4aHm4u6N+vj0FmGGTMXBmZOHGiJm7DpIEWA2QlqVS+LOYvXIKg7JWQ5Jb5TonEkn5WidhBlFio9hPbBz1GjugXGDV2JPLkUX1XRh1oZ3fkiF8xeco0ZMuRWwTZSQfSAxv/wcAB/VgR0TP1a9fEmzP3EaOmMmIRHwUnWyuDih2j2AlKgGCskEssuVNJrYX02M8v/doFFy5cED7gZDV58eKFqP1E2bX0CSk1CxYtQZhHcUDDtZa+eC87Z4Q5+2L5qjX4ftBArb4Xo3taNW2EF6u2INg5h0HWF0kPq/D3cLG1wNr1G9GofX/kyW8YabYVWUyKlq6CIqUq48m9a5g6bTomjB+bpfhRhpGH87kZAeTONH3yBOQJvwe7kBeZto+u0B3RJduKxzEl0nfDSA/nT7dRzDoYs6ZP1ZkiIoUGNSpYeGLfWtm5q6cPolKFsuLzM/qlcuWKcI72V/v1NhHvUa0yF6PUJB06dECRIkXw888/i4NSGJN7FbF06VJxSDly5AgGDx6Mr7/+Gn/99RcaN26s0EVLV4rIug2b8NA/EnHZiunkPaOzl8aVhy+xe+/noGTGdKA4sErFC8Dtw2UqOa6Re9KmHgWui8cqbuplhmVUILwDrqFwgQKo7tfeoBURechiU6xMFRQtW10kDWAYgw1gJ7P7xo0bcf/+fURGRqYy6a9atUrTb2c2UMzGb5MnYOykKXhnaYMkd+V8rJXFMfAhijjGYfzo0QrdM7QNBckdOvwvVs4eIbJ9xMVEYd68zzUUGP1CdVxsJIlAUgJgrXphSbf4AFSqoNmKw+YOJYIYMGCAONIycGDq3f/JkyfDUKA5YfXa9Th14yFC89XV3U62hSVC8tbB7qMnkJSUjA7t2nAiDBPi+0HfwHr5Kly+dwIhuWuIgpdZgTb1LGLD4Xxvh0qbehkikcA+5Cm8wh5jzKhfERYWhrXrNyNPgWJwdtVMocZmTZuiadPPVk+S70Q7J7wLjIamCPz4Dk/uXET7Zr9q7J4Mo3FlZMWKFaLaLdUVWbBgAX744Qfs3bsXX331labfyuwgd6aJY0Zh9PjJ+OTgIVwPNIFV5Cdkj32NMROm6U0RkQ6cFD9CBZ2kiy3OeW44UHGsTx/9keShosucJAUWUYF6S+fLGA70vz1vwT+4/z4CofnqUbCObjtgZYNgXz/sO3MWHwMCMGhAPx5jTATK9PjdwP4ofe481m7YjFDP4oj3KqKxuiNZhRQbr09XUTS3N4aMnCZS0+fLlw+dO8Zh/dLfUKl2c5SpUjfLGSsPHT6MvXv3iMfWNrYYNm25RvqfmJiAa2cP4fGtC/h+8CCTSoDA6B+N/5dSRohhw4aJXW76p6K/Q4cOxdmzZzX9VmYJBY31690Dnp80ZCJNSYHnxyv49ecfDSJ1H8kM9YMOXiQYFl9VrgCX2I9qVVzPkycv/55mDqUwHTl2Am4GAaF5auheEZFiZY2QfHVx8UUoxk2aKmo5MKZD7Vo1MWfmb6jtYwnvZwdhFfZWWCTUgTb8okp3yNLGn0ViLNw+XEWej+cwpHdnjB4xPFWNLCrGOXXKJMQEv8T6BePx5N5VjSaJyCqU7vf2pRNY99c4uNsl4fcZv4mMfAyjSTQ+GyQnJ8sqK1PWEsoUQfEA/v7q+5szqfmqWjXkcLSEZVRAlu9lG/IMFcuWEjs0DJMRZcqUgXXEB5Undqeod6hdg6tfmzMPHjzA6AmT8cqxGKKzl9F/kLGFJSJyVcJTi9xCQaKgfsa0vAiGfv8dJo0ahvI2H+H98l9YRaixBrG0gsTBTb3U+klxcPG/gRwvj6C7XwX8NfcPVKpYMd2mVAPnu28HYvjPP+L94yvY8M8kPHtwUy2lhOqGkEWEkP5VVwm5c/U01s4fh6TI95g8cbyoD2YIm5aM6aHxrUoKfH769KkIpqSc/RQ/QhlcOA2cZt2ZunfugD9Xb0dQVooiSiRwD32MLj+N02T3GBOF/o99ffMhJOoTkl1yKreDKJHAIeINqlb5VredZQyGk6dPY92WnQjKW09n6cmVJcGzIPzt3PDbH/MwqN/XwpLPmA60yTZp3GixJlmzYTM+vLyLEK8ySHbVoosRKSFBD+EU8RrNmzZG86ZDlU4nTWnUf/5pKN68eYOt23bgyqk9qFa/LQoWL6d0fNOQ8X8jONBfFD3sMXi8yt1PSU7Gg1sXcO3MAZQoURzjx47i9RtjfMpIv379ZD6PlLll2bJlwjryzTffaPqtzJqyZcvCMWWNSJmqrgnZKuIDfPPm1kpBQ8Y0adawPl5sPYKQNMqIbAcxDVZRn5Ant4+sMB9jXvx79Dg27TmIoAKNtJ6+V11SnLwQmL8RFq3agKTkZFTn+EaTg7LOTZs0XtQVIqXE/+U9hGQri2SXHJp7k6QEOAc9gFPEKzRv0gjNm/6gthWBlKhfhv8sagdt274Tl07sRtV6rVC4RAWlq7CrSlJSIu7fOI+b5w+jRPFiGDt6JK8NGONVRubPn486deqIKstUU2D8eNU1cyZzaJeEBrwNp+8iMmf6pt/M8Ah/ig4Dumm8b4zpUrFiRditXid2/5RZXLqHP0ObHq110jfGsHj06BE279qLoAJN1MrApkso81JQfj8sX7MBeXLnRt68ms1WyBgGFOtAWSlJNlet24hPIQ8Qmr18loq5IiUZDkGP4Br2FI0bNkDrFkM05sqUP39+/PrLMGEp2blrDy4c3YEKNZqgZIXqGbpguXt4o/8vM8XfzIiLjcadK6dw9+oplC9XlpUQRi9YSDQcKUXFtc6cOYO7d+8KVy1STCiTljb9DJOSkrBmzRqcO3dOPK9duzZ69+4NKysrlduqcq+MCAwMRGJiIrQJWZx++PkXfCrcArBKPTBJUxIK15l0dqwtY8PgG3QZ8+fM4vSWaWKeqHjc9evXxfdC8qstWTImWZNn646d2HH1FWJylM2wHVnt8nw4jb//nJPlDDHmgo+PDwwZVWRt+MgxeOZSFilOmnPx6JIjEC2bNxOPaeLaeT8Mu68802ghunJW7zF5/BiYOqrKmibnWUMY22jpc+PmTaxauwFhNtkQnqPcF/NoZliFv4PnpxuoXrUSunXqIIuX1RYBAQE4cPAQbty4iRLla6Bc9YZwclbP6hwa/Am3LhzFi0e3UKd2LTRp0lhrFmxDH9cYE1RGpFCGkvPnz4ssWu/evRMZIyjNrzbYunUrrl69ijFjPk8g06dPF5WVO3bsqHJbVe6VERSwL01RKw8tcOWzCmU00CrTdseu3dh34zWicpRFilw+AquURFjER0Ni55Ru8J37m7MY1LUVvqpWVUwcisQgbR8yakvIpwbWV1vqr1TBIuUiJSVF6baHDh0SNXKktRvWrl2rNVkyNlmTEh0djeGjxiGgcEuRmcgK6X+/rv7X0cOvMpo0aSQ7x7KWcVtfXxXTJusYZReH8fHxGPzTLwgo2kaj7+98fS0sUpLEYypIF1Wpt0bvTzFO3o92YuXSRTB1VF0ganKeNaSxjf7HDx4+gsPHTiA4eyUkuuaWXVM0tiE5Ae4fbyCnfTJ++G6giPXQ5dgWExODU6dO4+Sp08idvxgq12kBj2w5kJKc8X2trG3g/+4Frp0+gMjQADRp3FBsFtva2mp1bDP0cY3RP1rLtUnZIZo3b47ixYtj8+bNYodEW8rIyZMnxa6Lh8dnU2v79u2xbt26dAe+zNqqci/pwCY/uNE/JAX6Um2Vjx+/TINK5v9mzT7v7BHr168Xg016UB7vVq1ayZ7T9xgXF/dFu3qF3BCW+A5n4v/LiFXf+SMcXem+oV+0j0y0QICTpVBEqL+7d+8WtWHSg3Z6unfvLnu+f/9+sSBJD7J+UZyQlMOHDyvMokaDF8UXSTl27Bjevn0LRcgXcTt16hRevnypsG3fvn1lgznJHfkJK6JXr17i9yIuXbok7k3uhTt37tS6LBmjrBFkwq9V4yscevgEsdlLor7jezhapnPfItkQERGWyvLGsvafrFGGqbRMnDgRpgB9J5LkJOHColYmIn2RksgpqHUwzxri2Fa1fBnExkXg4vsgRGUvKzK+KRzbaFzxyos+ffrIrL76GNvKlS0t6jft3jgf2XMXRN7cPogO+wRFvP8UiqSEaHRo1xbBwcEii5yiTHKaHNtMZVxjtIdWRt2QkBBhESF3LXpMOyLaEkaq+E7/VORbKYUeU0572j1wdHRUui1p88reSwq59Gzfvl32vECBApg5c6bC/tJAI18sKCMXKdqtkG+bkauLdWK0KC6nTIEnq6RYTJ04TrYzltHkS2Z1+T5kVBSR+iffNr3dFvnPLd82Mzc++bbSQU8RpExI3zuztjly5BDxTdLPShOafF+0JUvGLGskA98NHIAL/QYiNlsxhe2kbeXvy7L2WdbS+31NCfp9aLPjxNN7iCb3Fw0hsST5kcAiJRkSC81PX66fbsGvfj21X0//17TQpf9hGiMiIyOFlwAVA5YulknOmzZthuzZvcVinVxjaLFKskEypKorky7Q5DxryGNbAeqz5Xtce3UZobmqISPotyOLiL7Hti5dugglj5SWkydPwcVFsatYn56dUb16dfG6bdu2ISN4bGN0icZH8ylTpuDx48eiJkGHDh1QuXLlDP+Zsop0h0P+H0D6T0ExFfLnM2srNW8qcy8p7dq1Q8uWLb8YFFu3bp2u6Ziuy+9yUKV6RaRtS4OOIhYuWQ7Hjw8Qk720eH4y5r9BUh7395fRtk558ZtI7027RhmZl+X70LRp0wzNwPJt/fz8lG5LPsW1atVSqi2ZlUnBVQRNetLfgeSPgq4VQQuFiIgIWcYV6S6P9HfXliwZs6xRW3LDqVSxPI69fIaTlp+/NxlJ8cjx6ijm/fG7SGkpf1+Wtc+yVq5cOTFGmjK9e3bHs8nT8DrgPmK8S2qktkh0he6yeLiYEv/9L2QZiQQun26hsKsELZs3FVmMaJebFtZ0xMTEIjomFnFxsYiNjf/8Ny4O8XFxYiz4/P9H8mcBWzt72Ds4wt7BCfaOznB0dkNSUrJwXxFYWCLZIScevwlEzIMXiI2ORFxMNOLiYhAfG4MUSQosYAFLq/8XgBX3s4eDvYN47uBgD0cHBzg5OYoxgw7yRKDFo7Z8/jU5zxr62EbKwLy//sG1DzdxMmf5/67FRcL73WmM+XWYKGGQ9r76Htto7CElbuGiJXD0yIkylesJWbp0bBeye7mgV88e4neQWpp4bGNMWhmpVKmSqLhOg6MukO5y0o6LdCCmx+lp85m1lfo5KnMv+R2O9HY5aJdE0QAifz4zlwBl2w7s3wePR47Bu+icImA0OZ16lrYhL5DXBWjdskWq+2a2E2dsbeXb08SSWfC0tK30N6bJT/pda0uWjFnWpG07tGmFKxOnItCraKqFpmPwM9SvW0e26DAEmTA0WVOmrbFDiuiUCWMxd/7fePz2DEJzVYXEJuMdVl1VxZbHIiEanh8uonyRfBgy6GdMnDgJL1/+57ri6Z0LXtl94OmdE17ZCyGXZ3bY2TvA1tZeKB42dvawtrbJcHc+m7MlmjZt8vn9LCyQaJcd7wKjMy06lxAfh8T4OPE3ISEekeEhCA74gHev/cXfkIAPSEz8L6Zi+fLlWtmZ1uQ8a+hjG/Hj94NEMcznEZ8+1ySRSJDt/UUMHtg/lcXHEMYg+bbu7u4Y8etwrFq9FhcObxDqcckSxdGhfTshdzy2MWajjLRo0QK6hMzbVOGddrJoZ4igx3Qu7aCsTFtl72Vo0AQwfOgQTPvjTwQWai4Ci9NmNvIMuovhM6byQKEA+o1pMH///r2syJM2ZclYZU0+dqQQFUGM+IBkt/9b4iQpcA57juZN++u7e4yBjEujRwzH8RMnsXn7ToR5lkC8VxGl3EkVoqCmjcqkJMMxmFKyPkPfnt1Ro0Z1cXrKlMn49OmT2BkmN+PQ0DAEh4QiNCwAD14/QmQk7QBbwMXNA86uHnBy9YCDkxscnV1FZiNH6eHkCqv/L3wPHT6MvXv3iMeUknXYtOWybkhSUhAbE4WYqAhER0eIv3TERoUjJioMURFhiAgLQWJCPBwcHeHp6QEvDw8U8a0AT4/6wl2Ixg1y7dFW1kpNz7OGDiksQ78fhIlTp8PK0U0Ehpcs7Ivy5TTncqjNvn8z4L8YOYYxBkwiUq9evXrC55SC5Ql6TKZNddqqci9Do2DBgmhcvw72Xb2FCJ/K/12QSODpfxn9e/cQi21GMZT17ejRo8LcrW1ZMmZZk9K6eRM8W70dQf9XRig1atEihbnIoQ7QR6pVdaAd2YZ+DVClciWsWb8Jt+4fRIh3OSS75dGI65bKSCSwDn0lNmeqVa6AHl1/l7kREfSdUDxdRtmm6PskNy7pERYWJpSVgIBnCA+PQEREOCIiI5CclAwHRyekpCTDkr5rCakxFjiyfRlCgz4KRYO+AkcnZ7i5ucLV1Q3ubq7I6e4Gtzx54eFRVigbnp6eWk2Pr+t51higwoN/zp4py+YlDcZnGMaIUvvqEpoYVq9eLVIJp51oly5dmipDTkZtlbluqLUfpFD/f/plJN5m/0pWyIkm3gr2QZgwZpTO+2PMdUaIunXrak2WjF3WCHI3GzTkR/gXpFo3NvB6fx4/9WyD8uX/87VmtJNuVR+pVjUha5TJbOXaDXj9MfhzFWxyg9EFEsnnuhBBd1G0QF707dVdBN5q9y0lIuaELC3kqy+NG5FaMmiBqy9LtTp1RjQ1zxrD2MZoDq4zwpiFMmKI6HMQvXb9Ov7esBvBeet+zpv/7AB+Gz8yVYYOxnQGUX1P2H8vWorjHyyR5JEP2R/vxpJ//uL0qDqQt++++04s8CgQlbh48aJIn7pw4cIstdVV3YenT59+roIdEYfQbGXSLY5Ik1Oq+kmK6j78n2QFba0iP8Ij6B7y5vBAz66dRd0Drmlj+LUf9D22MeYzjzL6hVcMJkilihXhtG4jQuKjYBkXjoL5crMiwmgNcnW5su0owqOdkCdvXlZETCDVqi7qPhQtWhQzpk7CypUrkZREwdxfBnSHJtvibOx/mQEzqvsQkWyDU7F5ZM9rO3yAq9X/PwPFuuf6nPXtxIkTXNOGaz8wDGNA8KrBBBE+2vXrYtuRc7BKjkOLQX313SXGhClWrBisQpbBI/IjKrVorO/umAXaTrWqy7oP9FyR4qIuFomxsLKJ/SKRhxSuacMwDGM4sJuWiZqXacfzypUrYqeOihwZYiEtY8AYzMv6ljWCsg7RopcWTJytTfvyRtYO2oH/66+/ZBmLyGLx448/Cl/9tJYRZdtmZhkhi4Ciug+qumml15aUkiNH/sWBf48h1Ks0Etx9kWJhpbyblsQC9sFP4R7yEB3btUb9enXTlce0fTBHNy0K0DZ0DGFsY8xjHmX0C1tGTBRaYFBGE4bRBZTth9Ed2k61qq+6D/S4TZvWqF27Fv5auAQv375DiE81wNpOXE+vfpK8NcTr/QWUzJcDg0b+lmlGN0OrEcF1HxiGMVd4hGIYhjFCpOlTKa0sHcqkWlWmraEotxPHjkKXJjXh/eIILOLCM2xvGR0M75f/om+H5hgx/CdOLc0wDGNEsGWEYRjGCOnQoQMiIyPx888/y9KntmvXTjxOm2o1o7aGCrkZNW/aBAV882HOXwsRmKcOUhy/rPVgGRWAHP4XMWbk8FRB+gzDMIxxwDEjWoJ9XU0DY/B1ZVkzHQxd3vQla8+ePcOMOfMRWKARJDb/uZZZxEUg+5sTmDR2FPLk+S+TFmP8skbw2GYaGIOsMfqFLSMMwzCMQVO4cGH07dEVyzbvQpTTf0qHS+Rr/DDoG1ZEGIZhjBhWRhiGYRiDp1atmrCyskRERITsnJdXLZQrV06v/WIYhmGyBisjDMMwjFFAacoZhmEY04KzaTEMwzAMwzAMoxdYGWEYhmEYhmEYRi+wMsIwDMMwDMMwjF5gZYRhGIZhGIZhGL3AygjDMAzDMAzDMHqBlRGGYRiGYRiGYfQCKyMMwzAMwzAMw+gFVkYYhmEYhmEYhtELrIwwDMMwDMMwDKMXWBlhGIZhGIZhGEYvsDLCMAzDMAzDMIxesIaR8+jRI6xYsQL+/v7IlSsXvvnmGxQtWlSt9qGhoVi6dClevHghHs+aNQv58+fX4adh9An97tu3b0dgYCC8vb3RqVMn+Pj4qC17GV0PCAjAkCFDYGdnJ2tfqlQpjBo1SsufkjEFVBn3WNYYXcobz6MMw5iVZSQqKgozZ85EkyZNsGrVKvH3999/R3R0tFrtLSwsUL58efz66686/iSMviEZWLZsGWrXro0ZM2aIv/RcXVlSVjYXL16MdevWiYMXh4w2xj0pLGuMLuSN51GGYczKMnLlyhV4enqiYcOG4jn9PXjwoDhfv359ldu7u7uLgVYVEhMTxSE/EDs4OMDa2qi/WrPjwYMH4vevU6eOeE5/T58+rbYsqSqbysCyxhDakK20sKwx6sobz6MMw6iKUf+nv379Gr6+vqnOkTmYzmuivTLs2rVLuPZIqVmzJoYOHQoPDw+178nonpCQEBQqVEi4Z0kpXLiw2rKkrKwNHz4cycnJ4r169uyJ3LlzK+wjyxqTlXGMZY1RB23Mm2lheWMY88ZglREyA9+4cUPh9b///htxcXFwcnJKdd7R0VGcTw9V2ytDu3bt0LJly1TnaIfHxsYGpkxsbCwmTZokDtrBMmT0IUuZXXd1dcX06dPFpB4fH48dO3Zg2rRpmDNnjmiXHixrhi9rhiirLGvKY06ypi15UwdzlDdzkzWGMUpl5Mcff0RSUpLC687OzrC3txf+rPLExMSIyTc9VG2vDDRYmvKAqQiJRIKXL1+Kv4aOPmRJmeu0Q02QK0KvXr1w9uxZPHnyRPhbpwfLmuHLmqHKKsuacpiTrGlL3tTBHOXN3GSNYYwygJ12XmiwU3RYWloK0/GrV69SvY5Mx/ny5Uv3nqq2Z0wDfciSqvcjH2k6GPNGG7KaFpY1RpfyxjAMY7TKiDJUrVpV+PqfOHFC7O7QX0olSOfVbZ+QkCAOgtrQ45SUFJ19JsY0ZCmz60+fPsW7d++EbJG7w/r168UCMaO01AyjjqyyrDG6lDeC51GGYVTBQmLkNkLKf758+XKR/5xqQgwYMADFihUT14KCgvDzzz9j3rx5yJYtW6btic6dO3/xHhMnThR5+ZnU/rwUdEi+vqZiXte0LGV0/dy5c9iyZQvCwsJga2uLIkWKoHv37rzbaCaypktZZVlTHpY1zYyNPI9mDssaw5iQMsIwDMMwDMMwjHFi1G5aDMMwDMMwDMMYL6yMMAzDMAzDMAyjF1gZYRiGYRiGYRhGL7AywjAMwzAMwzCMXmBlhGEYhmEYhmEYvcDKCMMwDMMwDMMweoGVEYZhGIZhGIZh9AIrIwzDMAzDMAzD6AVWRhiGYRiGYRiG0QusjDAMwzAMwzAMoxdYGWEYhmEYhmEYRi+wMmKEbNiwATVq1NB3N4yWSZMmoW3btvruhtHC8sfoC5Y9xpzkwhQ+l7OzM+7evavvbjAGDisjBs6pU6fg7u6e6lyPHj1w4cIFGCNv3rxBnz594OPjAxcXFxQuXBg//PAD/P39xfV69erBzs5OXHNzc0Pp0qUxfPhwBAYGprpPfHw8fvnlF+TKlUsMdmXKlMGrV69k18PCwjBgwABky5YNrq6uqFy5MmJiYnT+eY0dlr8v5e/SpUto0qSJkC1PT0/x+MGDB6ne5/z58yhXrhwcHR1Rvnx5XLx4Ueef1dhh2Ut/7NuzZw/Kli0rxrUCBQpg3rx5MCdMRS5mzZolfuP0qFmzJiZMmPDF58qfPz92794NQyW9/kVFRYn5mWEygpURRqeTcZUqVWBjYyMG2IiICLFoI4Xi9OnTsnYzZ85EZGSkUCi2bt2K9+/fo1KlSvj06ZOsTd++ffH8+XNcv35dtN22bZtsgkpJSUHLli3F+zx58kTcZ9myZeI5Y75oSv5CQ0OF/D179gwfP35E1apV0bRpUyQnJ4vrISEhQv6GDBki2n7//ffiOd2PMU80JXsBAQHo3LkzRo4cifDwcLHwmzx5Mo4cOaLHT8eow9dff43Hjx/jypUrqc7TOdrw6Nevn8r3TEpKgkQi0WAvGUZHSBitM2fOHEnhwoUlzs7OkoIFC0oWLFggu/by5UsaOSRr166VFCpUSOLm5ibp3bu3JCEhQRIUFCSxt7cX152cnMRx5swZyapVqyTlypWT3ePt27eShg0bSlxcXCQVK1aU/PbbbxJfX1/Z9cjISMn3338vyZs3r8Tb21vSq1cvSVhYWKbvr2n69Okj8fPzy7BN3bp1JfPmzUt1LjExUVKqVCnJr7/+Kp7fu3dP4ujoKAkJCUn3Hvv37xeflV6XHhMnTpS0aNFC0q9fP/Gd0W+zc+dOianC8qdZ+UtLeHi4+AzPnz8Xz5cvXy7ay1OyZEnJypUrJeYGy55mZe/69esSGxubVG3o8//xxx8SY4Ll4jNt2rSRDBo0KNW5kSNHir4T8p+rY8eOEgsLC/H56XN/++234jz1lb4/khNbW1tJRESE5OrVq5IaNWqIvpcoUUKycePGVPNfy5Ytxeen6/QdbN68WXY9JSVFMn/+fEmxYsXEdZLLBw8epBrv6LX58uUT32/lypUlb968ybB/N2/eVOq9GfOFlREdsH37dvHPSv/kJ06cEP+s586dSzXwdevWTQwi79+/l+TJk0cMQsTJkyfFP608aQfe2rVrS/r37y+JiYmRPH78WAzu8gNvp06dxP1DQ0MlUVFRkq5du0p69uyp1PunB/VH0VGmTBmFr8uVK5dYqKk6IRNjx46VVK1aVTz+559/xOJu8ODBkmzZsolJbebMmbK2NHHXr19ffE5PT0/RdvXq1bLrNCBaWVlJFi9eLCb7vXv3Suzs7CTPnj2TmCIsf5qVv7SQ/Li7u8uU3x9//FHSo0ePVG26d+8u+emnnyTmBsueZmUvOTlZLFRpPEtKShLKCS2mb9++LTEmWC5Sjx2xsbHiOf2mJCubNm1K93PRZ9i1a1eqe1Bfq1evLvoZFxcnCQ4Olnh5eUn++usvoUCdOnVKKAfS75fmP1Jot2zZIt5vzZo1QimkzyqdX8uWLSt58uSJGNNIMSGlLD4+Xlxv166dpEmTJuL9SB5v3LghCQwMzLB/8spIRu/NmC+sjOgB2g2ZNm1aqoHv4cOHsusDBgyQDBkyRKmBlwZ0er10MCBmzZolG3gDAgIklpaWqawINMjQgECDQWbvr0msra0lhw4dUmtCXrhwoVA6iKlTp4o+jxgxQgziZCnx8fERO1kETULS3SIaQGkQpgHv9OnTsgGRdovkadq0qbivOcDylzX5k+f169di8bBixQrZObK40c6fPKQ4k1yaOyx7WZe99evXSzw8PMSGCu1Ey2/EGCvmKhdS5YN+U2Lfvn1iA42UirSfK6PFvvw5ulfx4sVTtfnmm2/EIZ3/qlWrJrtGCiFZVK5duyae0+bd7t27U72e5leyQH38+FG8H4176aGMMpLRezPmi7Wu3MHMGcqIMWfOHBFgTfEMFEhNgYfy5MyZU/bYyclJaf/yDx8+wN7eXgTTSsmXL5/ssfQ9076fpaWl8HfP6vurAvWRfKDVgV5HwcIEBaxbWVlhypQpIuCzVKlSwr9237596NWrl7ieJ08e4bMvDQak7Fn79+9HnTp1xDlfX99U96fn6vbN0GH506z8SXn37h38/PyEnMn7d5P8UdyIPOTf7+3tDXODZU+zsnfixAkMGjRIjHU0lr18+RLt27cXQe/fffcdjAWWi8/QPNa7d2+sWrVKBKtL/9K8pgryn4/GJQokl6dgwYI4c+ZMup/NwsICDg4OIlZJ+v307NlT9E1KQkKCuC/1iw7591OVjN6bMV84gF0HgYs02FDmDAo+pAGtefPmSgeZ0QCZEZSZJS4uDkFBQaneU0revHnFPWiApveWHvSa3Llzq/WZaLGl6CDFQBGUdWjLli1qBeVRBhnKNkNQliLpQJYe0usZ8fr161TP6TtT9/swZFj+NC9/BE3M9evXF5P2mDFjUrWnTEe3bt1KdY6em1tGGZY9zcvejRs3UK1aNfGcPluhQoXQsWNHHDhwAMYCy0VqaCPj5MmTuHbtmlAy+/fvr/Jnlz9PG3HymSUJek7nlYG+H0oII//dkLLYrVs3sWlHmSzfvn2rUv8YJjNYcrQMpbWjQTZ79uziH/XgwYP4999/lX59jhw5xK4BDdqKBg7a+acFUWxsLJ4+fYqlS5em2oUgqwDt3koHZ9r92bVrV5Y+k6Lj/v37Cl9HWV9oUUY7ezQ50PdCaSspg4yiifrRo0di4qKd5WHDholztCNYpEgRcb/ExESRfWT16tVo06aNuN6uXTsxsSxevFhkOLp8+bKY0Fu3bi27L2XZogxbNNnTRE47jl26dIGpwfKnefmjRQwpIiQvEydO/OI1JH+krKxYsULsKNJfSt9K580Jlj3Ny1716tVx9epVkYmL7kGbKjt27ECFChVgLLBcpIbmslq1aqFTp05iIyOjzTT67JRFMiNIsaPvZuHChWJ+O3v2rLBEUfYuZaDsf5RWmOZVgjK/0fxJ3zm9P82zJMc0ppGF6ebNmwgODla6fwyTHqyMaJmSJUti7NixaNCgAby8vMTEI78ozoxixYqJnRK6D6WuPXfu3BdtNm7ciBcvXoiBoGvXrmK3Vt7MSwt1ei2llqTc9LVr1xYpcXUN7arQREqKAu3uUV9ociU3hLp168raUdpKaa59ckGgyYN2jejzEWQ+3rt3r6jdQJ+L0qoOHTpUmLcJOkcKBi0C6T1oEP7nn3/EgC+FXkPpE8n9gV67fv16MSmYGix/mpc/UmIpre+ff/6ZageUJn2CZIp2OOfPny/u8ddff4nnHh4eMCdY9jQve7TInjt3rqihRPeggnh0jr5nY4Hl4kvo85D1IiOrCEEK1t9//y36Pnjw4HTb0Dhz6NAhMafR9ztw4EAsWrQo1fyXEaSkUT0ckj/6bkqUKCG+Tylr1qwRCh/V7qJ+kGJCSp+y/WOY9LCgwJF0rzBGy4wZM8RO/9GjR/XdFcYMYflj9AXLHpMeLBcMY9iwZcQEID9iMumTXkm7OwsWLBAmX4bRBSx/jL5g2WPSg+WCYYwLzqZlApDvMZlKqUov+eF+8803mZp7GUZTsPwx+oJlj0kPlguGMS7YTYthGIZhGIZhGL3AbloMwzAMwzAMw+gFVkYYhmEYhmEYhtELrIwwDMMwDMMwDKMXTCKAnQr7UO5rab5xyhlOxaKoHoUqbamAHtWmuHv3rijwQ/UCKP855UNnzANNyZIq96LCeMOHDxcyR/nvGUYKj22MMcoiQfVRqIYIFRR0dHREhw4d0LhxYx33mmEYY8AkLCM7d+4UafyoGBQdDx8+VFhNNaO2VK2bCgaNHz9eDLpUtGfdunW4ffu2jj8RY+yypMq9aML29vbW6udijBMe2xhjlEWqNr98+XJRPI/kbc6cOShVqpTO+8wwjHFgEsrIyZMnxa4LTbZ0UOVQKnCkalt7e3t06dJFVL21sLBA0aJFxQBKA7AiaMcxJiYm1UHnGONEU7Kk7L2oSjBN3G3atMm0byxr5oe+xjaWNSYrskgbLB07dhQyZmlpCWdnZ+TOnVvhvVneGMa8MXo3raioKAQHByN//vyyc/Q4KChIDGhkHlanrdR95tmzZ6hVq5bC96edoe3bt8ueFyhQADNnztTgJ2SMUZZSUlIyvRftVi9ZskTkv1cmwzbLmnmhz7GNZY2RRxX5iouLE5ssFSpUwNChQ8X1EiVKoG/fvkKJSQ+WN4Yxb4xeGaGBj5AfDJ2cnMTf2NjYLwZJZdvS4nDx4sXIlSsXqlatqvD927Vrh5YtW8qe066jtOgS+dgyxkNoaKj4Sz71UuVAXVmSvj4jWdu7d6+Y0EuWLIn79+9n2j+WNdOHxhtDGNtY1sxL1jJDFfmKjo4WMnb16lWMGzcOLi4uWLp0qaiCPmHChHTvz/Jm2qgia4x5YvTKCLkfELT74urqKntMODg4qNWWBlLyd/X39xc+1mRmVoSNjY040oPrSRoXtra2sslVOtGqK0tkGcnoOgV1Hj16FLNmzVK6fyxr5oU+xzaWNSarstisWTNZLFznzp2FlYSUGul1eVjeGMa8MfqYEfJF9fLywqtXr2Tn6DGdS+uaoExbGvgo6wy5MIwdO/aLezCmC/3W7u7ueP/+fZZlKbPr5KsfHh4uJmhy0yKlhJQgevz06VMdfWLGkOGxjTFGWaSNnGzZsumhlwzDGCtGbxkh6tWrJ3xOixcvLp7TYz8/P7Xa0mT9+PFjYU6mAZgxL8hthSwW5LOcVVnK6Hr16tVRpkwZWdsnT54I1xlSStzc3LT6GRnjgcc2xhhlsWHDhjh06BDKly8vZI3iQUqXLp2uVYRhGMZCYgI2UPIppfoM58+f/yL/OfmqEgMHDsy0Lfmnfv/998JcLO++QG2kr1cWuhdnAzE+KKicJtnr16+L53Xr1lVLlpS5Lg/FjPzxxx9q1RlhWTMdfHx8DHpsY1kzXVnLDFVkkdxU169fj9OnT4vnlFWrX79+wvKsCixv5ilrjPlhEsqIIcKDqGlgDIMoy5rpYOjyxrJmOhi6rBEsb6aBMcgao1+MPmaEYRiGYRiGYRjjhJURhmEYhmEYhmH0AisjDMMwDMMwDMPoBVZGGIZhGIZhGIbRC6yMMAzDMAzDMAyjF1gZYRiGYRiGYRhGL7AywjAMwzAMwzCMXmBlhGEYhmEYhmEYvcDKCMMwDMMwDMMweoGVEYZhskxUVBSCg4MhkUj03RWGYRiGYYwIa313gGEY4yYhIQHfDf4esLLGN/36oE7t2vruEsMwDMMwRgJbRhiGyRLPnj2DdfYCiPStg0vXbuq7OwzDMAzDGBGsjDAMkyUuXL6KMLucSHbJgSePHyM5OVnfXWIYhmEYxkhgZYRhGLVJSUnBlavXkOSeF7C0RpKTN+7fv6/vbjEMo2GSkpKwYsUK9O3bVxwrV67MdOOBXDh/+OEH9OnTB8YI9T8gIADh4eH67grDmDSsjDAMoza3b99GgoMXYG0nnoe5FMC+Q//qu1sMw2iYnTt34tGjR5g7d644Hj58iF27dmX4mi1btsDb2xvGyt+Ll2HUlJn4afivCA0N1Xd3GMZkYWWEYRi12b5nP8LcCsueJ7v64MXrtwgKCtJrvxiG0SwnT55Ehw4d4OHhIY727dvjxIkTCtu/ePECt27dQps2bWCsVt8HDx4gsEAjxHsVxs1bt/TdJYYxWVgZYRhGLV69egX/4HAkO+f476SFBcI9imLnnr367BrDMFpI3Z0/f37ZOXpMmw4xMTFftCf3rSVLlqB///6wts48aWdiYqK4j/SIjY2VXbOwsNDLQZafZEcv4X4a7ZIPx0+d01tfjP1gmMzg1L4Mw6jFpm07EepRQigg8sR7FsLlq/vQtVNHuLq66q1/DMNohri4OPHX0dFRds7JyUn8JcVB/jyxd+9eoayULFlSqRgycvfavn277HmBAgUwc+ZMvbp4zf5zAUJdCojHKY5eCHh5RVhLcufOrbc+MYypwsoIwzAq8+nTJzx79QZJhVp8edHSGlEeRbDv4CH06NpFH91jGEaD2Nvbi79ktZBuMEgtIg4ODqnafvz4EUePHsWsWbOUvn+7du3QsmVL2XPpbnpgYKAInNc1/v7+uP/4KZIL/79PFhYIcS2CvxcvxY+DB+m8P8ZOrly59N0FxsBhZYRhGJXZve8AwtyLfmEVkRLjWRSnTh9Ep/btYGtrq/P+MQyjOZydneHl5SVcM3PmzCnO0WM6l9YqQkHulH1q6NCh4jkpE2RZIZetUaNGoUiRIl/c38bGRhzpIZFIoGtWrl2PUK/Sqca3BM9CuHl3P96/fw8fHx+d94lhTBlWRkwUMiffvHkTdnZ2KF26tL67w5gQlO7y6rXrSCjSSnEja1vEOefC1WvXULNGDV12jzFRaFG6aNkKPHn6THauQvmy6N2ju177ZS7Uq1dPuFMVL15cPKfHfn5+X7SrXr06ypQpI3v+5MkTLF68WFhK3NzcYOjcvnMHT99+QlKBcqkvWFoixLuCyLD12+QJHAvBMBrEJJQR2nlZs2YNzp07J57Xrl0bvXv3hpWVlcptDx8+jFOnTuHNmzcoX748RowYAWNNuTp/8UogKQ6zZ85A9uzZ9d0lo4ACL2mSvX79uphs6tSpo7YsZXSdAjYpZ//du3cRGRkJT09PtG7dGg0aNIAxyFaicy7hjpURES75cfTkGVZGsgCPbf+xe+9+XH74GqG5av7/jARhl88jj08u+NWvr+femT6USYvGqp9//lkmX+ReRSxdulT8HThwoNgAo0MKuXXRWEpWFEOHXM8WLVuJkFy10rX6Jrvnxfu3r3Ds+Ak0avilIsYwjBln01Il/3lmbaUpC9Pb8TEmLly+hsic5ZGQvQRu3Lyp7+4YDf/++69ISUnuBCNHjsySLGV0nZQekrXx48eLBeTgwYOxbt06sdA3dC5fv4UIx8+uGhmR4uyNt2/eGGxFdmnqTvrOyeXEEOGx7bNFZM++/dh79DRCcteAxMbh/4cjgvPWxoZte3Di5Cl9d9PkoaxYAwYMwKpVq8TRr18/maJLSggd6VGqVCmsXr0axgBZ3kJdCiLFwV1hm5BcVbB5xy4RV8IwjGawNLf855m1rVatGqpWrQoXFxcYK7RDSjnRk9zyINbNF8dOntF3l4yGy5cvo3HjxsKdgI6syFJG1ykgtEuXLsL/mnYNixYtKiZtWkwaOk+fPUOykxKWNgtLwNHdYCft8+fPY9nKNTh29ip+n/mHCLw1NMx9bKNYgz//Xoidxy8gKL8fYJUmrsDaHoEFGmLtzoNYumKVsDgyjDqcPHUad198QEy2Ehk3tLZHcM6qmDnnT+GyyjBM1rE29fzn8sF1qrRVFpr85CdAWlhKs4voy6eU/PQTnHOKiTvFwQOh/vF4+/Yt8uXLp5f+GAskA2FhYciTJ4/st1NXlmjXXRVZo0nt2bNnqFWrlsHLWnRUFCQ+qTPoKCLRxkVk3sqbNy8MiZCQEGzbvhOdBoyGi7sn8hctj0WLl2DihPHpukCZ29hmCLJGFivhMuOcHzH56itMliAWh/kb4tST27g7YjSGDPpGFtfAMMrw7t07rN+yHSEFGiuWMzmouOunmAAsXbkaQwalbxFiGMaMlBFV8p+rmitdGQwtPzq5NOzYvR/hHv8F34V4FMOe/YcwfeokvfTJWJBWDadFnDR9ZUREhFqyJM0Ao4ysUVsK8KT0h7RzbciyJlyuaLJWckGaYGkrFveGlNqRFu7jxk9A7WZdhSJCFCpRHu9fPcLa9RsweuQIgwhO1efYpk9Zo5iWOfP/xuM3HxGcq1aGLjMyLC0RmbMCoqODMOvv5ShXojB+GvKdLPMTwyiC/nfIyhGcq5pw/1OWqBxlce3BcZw7fwG1anJcHMMYnDJCbhkXL14Uu4/kY0qp8Mh1yNfXV6/5z1Vpa6z50SmDVnA8kJLDQ3Yuyd0XN+8eENd4claMVBZev36NbNmypfo9VZUlsoxkdF1eEVm+fLn4n6H4EUtLS4OWNfoMkkwC1+VJkFiJz2YorlqkiMz4fRaKlKuJIqUqpbpWu0lnHN6+DFOmTsOA/v0y/C20hbzSps+xTR+yRvdev3kb7jx4hNBsZZHkW0pppVdKilM2BBRojFMfXuD2t9+jSqUK6NKhnUgQoU9u3bqFZctXiM+TnJSEOrVro2vXLnqRMSmGtEGgT5asWIVA+9xIdlFxbrSwREiemli9fhOKFinMSWIYJgtofCS8du0aRo8eLcyeZ8+eFeeio6NFcK62859LUZT/XJW2ykK50em10iPtQlOXBy2A12zcgpBs/6VVFFhYItSzJNZt2qrzPhnTQb+du7u7kF3pOXVlSRlZo/tTRi1yzxo7dmymMmgIska7iBZWKuxhWFojJjZO778tHbQ5QopGsQp1Ua7al1nLLCwt0aTjNwiNTsb8v/4Wbkq67qMqMqZuW2XQpayRojpvwT8YMX4Kzn60QGDhFkjy8FVZEZFhYYFEr0IIKNwSx17G4JcxE7Bw6XJh+dT170lz39p167FuwxZ0+mYMBvw6RxxvPoZi2m8zUo01+pQ1c+Xa9eu49eglor3VS38vkihkrygsedINKIZhDEAZ2bRpk1BGfvzxR9muD5n4tZmtRpr/nPz96VCU/1yZtuSGQv77NLDQgE2P9WHhUIc7d+4gLNEKKY5fplBM9CyAB0+eIiAgQC99MxbITYqqB5N7Fh1ZkaXMrpMi8vjx/9g7C/Coji4Mfxt3d4IFh+Du7m6FUigtUGoUqrhToECBUqQUKVCc4u7ubsHdibsn+z9n+DdsQjbZTdb3vO19WJm9O/fuycwcmXPuYvTo0WIxaQjQ4grm79N25obUwhoRUe9C3XQJ7VuZ9OtkVGvUCeWrN1DYjsas5p0/h4W9B6ZN/x1JSUnQJcY8tpHHfMbsORg5cSqOvzFDSIl2SHYv/i7xgTowM0eSR2mhlBx6koiho8fjz/kLtTIGkrytXrMWw0aMRLzUDj2/HgNn13feVnMLC6H0lqnRHDNn/4lZf8wRmc9YQdAuZFihBBZhfrUUK77paZAkRIl/FZHqUhCvEy1w8NAhzXWWYYwctYdpkfWxVKlSmV6jmHFNWg2UzX+eW1ti06ZNmWKle/fujbJly2L8eP3fb7Fh8zaEuyrIBCIxQ5RLaWzbuRtf9PtM210zGFq2bCnCW6ZOnSqeN2zYMM+ylNP7FJJCaYTJAk1pfWVQG0UpMvUBWmQlW77bi6AM6daOePHqKXQJ3WsKzWrcoS8KFy+ba3sKSarXsjvOH9uF6TN+x/BhQxVWh9Y0xji2kSfk3zXrcffRU+GxTS3eLu9eEKWVklIIdiuBY68f4dq4X1G+XGn07vlRRjimOiDPy4ULF3D6zDkkJqWgbNX66PPdr7CyfhdCl5XiZSqjWKmKeHTvBjZs2YWIkMWoXr06atWsgYCAAL3Yt2TMbNm+A9EOhSC1eRfWmB2SpFg43NyE2MCukNoqLtgY6V0Z/23eJsLvZCGTDMMoj0SqZnPMyJEjMya5zz//XOQjDwoKwrp16zBp0iSYCrQA0maayYiICPw8arywAiqc2NNS4P1gJxYtmKvTWGVDws/PD/qONmWN0qfueZyMVPdiyn0gPQ3e97dh4bw/RZ0CbUPW/zFjx6Fms+4IKFVB5c+f3L8RFqnR+OpL7SiI+i5v+ZE18jT+u3odLt8IQoR7IFJdi2hWCVGENB1WYY/gEh6E2jWqoVeP7nkKZSOvEoVYXrl6TaRSl8IMAaUro2T5GnD3Uv13TIiLwb2gS3h0+xIiQl6LObRK5UoIDAzMcxixIcuaJsc28ooM+v4nvC3eFjC3UtiOvCLKKCOE45sr6Fm/LDq0a6v2/ho6hiBrjG5R++qgZ8+emDFjBho3biwG6zVr1oiqv0OGDFH3VzFZQrQSHAvkPLlTql87NxEyR5Y3hlF1Aj9/8SJSi73f2JwrZuYizfTZc+d1knFm8+YtKFSyUp4UEaJusy74b+k08fdVoULezmHqkL3r6NFjWL1hI6JcSyORFoB5DMWyv7IGknQKLZNCamaJuMq9VD+JxAzJHsUR7FYUB+7dxvmfh6Ff396oVbOmUt4PSjl8+cq7Qpm+BYuiUPEKaN/nRzg6vU8akh20cT0yIgQurp4iVCsrtvaOqFijkTiSk5Pw7MEtnDh3DavWrIOzsxMqVayAypUqiWx/bEzKH+fOn0eio3+OioiqxLqVxL6Dh1kZYRh9UEZowia3/8GDB0URN4oxJ2+JfP57Rv3cf/QUCVa5p8CMt3QWqTNZGWFUZeWadYh1LvZh4blciHQPxKq164WVVxMWXkXQ2HPqzBl8Onhyns9Bm9obtvkY/21cxcpIHj1TVLQw6FkoIoq2VCl1anaQIvJOGVEDZuaI9wpEgnMRLFy9GZevXseXA95XFZcpUo8fP8a5c+dx6cpVmJlZoFCJ8ihbszWadguAmQo1aUgRWfr7MPT/eRrcPXPOZGVlZY3iZSuLg4gIfYvH965jxZr/EBb8SnhNalavJmRSVyGEhszx0+cR66je2kdSK3skppuJUFZvb2+1npthjB2NxE1QCt/+/ftr4tSMAiKjoyG1yNmNTCRLrBAdHaOVPjHGw/ETJ3H68k3EUVEwFaGY7DDnEpg+6w+MHj5Ua+Fax44dR6kKtWBppfyG++zwLlAEaVKJsISzUUV5yDP+628zcD/OGrGFGuomJEsJpNYOCCvSFKceXETMH3/ilx+GiMQFtCH5yJFjcHB2Q7Fy1dH5s19g75j7GJsd8yYNQnLSu1owqxdMwuBxC1T6vKuHN1w9mqNKneZISUnG0wdBOHj8PJYt/xeVK1dC2zatOW27Cjx7+gRpxbNknVQDCbaeuH//PisjDKMial8VHDt2TOF7tBmY0QwWZKGTKpEkQCqFhYV+VJhmDINjx09gxbqNoso1FZfLC4nupXD/7RX89vssDP3xe1hZqS88QpFFfv+BA+jaf7hazlepTgts2rwVP/34vVrOZwps2bYdj2IkiPWrBL1HYoZo3+oIenESq1evwYVLl1CqQm106TcMDk5KFF3MhZTkJKSmJIvHsn/ziqWlldj8Tged68718/ht+kw0algfnTp2yHdfjR0qApouMReeMbWf28IJj54+R716aj81wxg1aldGdu3alek5pZikDC+FChViZUSDuLk4Q/Imd4+HDZIziqIxTE5QKlgKrzp69jLCijSH1DIfWWIkEkR7V8bNkJsYMWY8Rvzyo1ozGclDmfsWLV6C0pXqwdFZPcXuSpSrhhvnj+DQoUMKU+syyBTetP/gYUQFtIHBIJEg0rsqjh7fiV5fjoK7dwHoOxaWVgisWg+lK9TAqvnjUKd2LS6+p0TGT1grnxFQ1VCtN8EhGjk3wxgzaldGpk+f/sFr27ZtEwsbRnP4eHnA4uZb5BZNbZ2eqPNqxDlBm0ODbt0Wj319vEUiBEb7UC2GmXPm4mWyLaKKNlePFVEiQZxXeTyKfIbhY8bj8z69ULeOeje1U8amBX/9DQs7VzRtpMJG+1ygNKtte36LLStmIjgkFN27ddVJdjCDsj6bWQAWmvWAqRupFe1pkuD8sZ1o3L43bGzVs2ht3aoVWrVqmSFLKdb2eBESp5ZzS9PTcfPSSViam4uirUzOkIE03SJ/e5cUQXuiIiIea+TcDGPMaGU2bd++Pb788kt06dJFG19nkjg6OsJKmoJ3UcmKMUtL0tsCe1euXMHyf1ejRqP2MDMzx4HDRxAVFY2OHTtwzn0tQV6FPXv3Y/P2nQj3roJUj0Jq/45Ul0IItnPH4vU7cPzkGXzz5QA4O+ctFl8+LOvgwUPYs28fajbqiHJV6+UqMxTHT+EzBO0rGTRmXo7tbezs0X3AcJw6sAnDR4xCzx7dUbVqVZbNbKBaC9LU5Heho+oqYqgN0lNhZmGB8qWLYvX8cShTqR4q1W4KO3vHfJ12z9692L59W4Y348dfl+S7q2lpqSJE6/KJ3QgoWgRjx4zSaPgj7QFasWIFTp48mVHHpm/fvpk2/BOUipcKut64cUNERZDxq0OHDmjSpAn0AUqDn2SmmVog6VZ2iHobqZFzM4wxoxVl5N69e9r4GpOGJoB0KDHpS8z0rqI89YdSsJ67eBldP/8ZTv+vVEyZZPZsWIgnT+ehf7/PhMLFaA7KsvbnX38jONkaEcVaAxb52/idWzhDWOEmuBT+AD8NH4WPunRCs6ZNVE5ZSgUqDx46LDYbFytdBb2+HidSpCoDKSIyZURZaCFJ2bVC377EnoObsXHTFnRo3xY1a9b8YFFmytDvWKJ4cYRHvUSai3qzFmkSq/AnqFSxEtq1bYPGjRriwIGDWLdwIvyLlEalOs3h5at+5VxV4mOjcf38UQRdPoHAcmXx0w+DtVLHYfPmzbhz5w5mzZolnk+ZMgVbtmxBt27dMrWjKAhXV1eMGTNGbOSmDd1URNbd3R0VK1aErnny7AUSLByUTCP9rsaJ3e2diKvySe4nN7cSKdDpHvB4wDA6VEaGDh2ayVJIWUko1R0VQmQ0R9Dd+0i0yn0vSLyFEx48eKgXqX0prvzy5ctYs249ChUvj55fjRGbM2WQtbr9J4Nx7dwRjBw9Bu3atEHTpk04PEbN0N/omvX/4cTZCwj3roY0r5zTjqqt9oNEgiT3Egh28seqvadw8MgxDP7mS/j7+ysVRrZr914hP6Ur1UHPL8fAziHve6FUrf3q4V0A7T/5TiglJ07sxob/NgrLLylU2kxfrM/0+qgr7k+bjRAnP7VtFqasUe3atBaP6RfbHBSJrecfqOXcVBSWCiF+9P1Y8dTe3h6dOnVEu3Ztcf78eezesQISC2vUaNwRBYuWUunUNJaRjNGGc1Jo80J0RCguHN+FZw+C0KRxI3zy60StGmiOHDkiPCGkaBAU6bBy5coPlBHyivXo0SPjecmSJUWaf1JkFCkjZEyTL25Iawhb23ehVOr2PF67eQvpDhWUTCP9LrxcIlXBgGfvLtJBlyhRIj/dZBiTQu2rujZt2nwwMFE6TE47qDkoTv7SpStIpWJiuRDnUhTbd+9FkyaNdbaop0n56tWrIjuRpa0j2vT4VuFmUZqIKtVqghKB1XDu8Fbs3Tcc7du3RYP69VkpUQNBQUGY//cSRNgWQGyxNnlaNOa39oOIs/avi+joVxg7eTqaNaqHj7p2yfb3ffnyJf7buBlPnz0XGa4+/b5bJgVW25BS0rLbF4iLicK1s4cwbPhI1KpVE+3btTX5RBGU4r1ezao4GHQVMb5V1XLOXbv3YPfOHeKx1MwcsVX7Ql24vL6ANi2awdPTM9PrJId16tQRBy2o12/YiIvHLNGwbS+45VIvRAaFAIaFvBZ1Rj75ZoxK/UpKSsC5Q9vw6M4VdOzQDkO+6qv1sS82NhZhYWGZUlvTYyoCSd7JnBRwCqGkSvX1ckgxRR6WjRs3ZjwvWrQopk2b9sFvkV/evHmDiOgYpHvkLyw0JyLt/HDyzDk0aNBAY9/BMMaG2ke0Ro0aqfuUTA7QQD9t5mxEegYqVYxOauOMcGtv/LV4KQZ9NVCr8e60H+HChQsi5aedgxvqtekNH/+iSn3W3sEJTTp8mmEd3L59B1q1bCGs0ZpOE2uMUGjcspWrcfrSdYT71UG6bc7Vo7VBmpMfQuzbYNfFq7hwcTSG/jgEvr6+GXK+es063LgZhFpNO6Fhpy9FQUJ9gepP1GneBdUbthWevFFjxqJTh/ZCPk15T8mnn3yMO2Mn4GH4IyS76d4bqwjb0Dso5mqJzh3b59iudOnSYm8G7W9buWoOSlasjRoN28LcXDPKwcM713Bs12o0btQAX/f7TWcFDin0iJBXOshzJEtWoEgZIcPTwoULxd9xjRo1FJ6/c+fOaNfufcIJ2d9MSEiIWsOKZ/85DxEuJTVa8ybFtShOnNop9sxoKmOgoSEbxxlGEWoZQXfv3p0nrwmTf4/I1Bkz8STFGUnexZX+XIx3JVy4f1oMzIO+/lLji3mKnz116hS27dgJd+9CaNr5C3j6KA7FSUtNFdWKXVw9YZ7FAkj7SZp27IvY6EhcPrkXu38ZiqZNmqBFi+YZbn0md7mhYnQv0hwRU7RlnmuHaARzC0T7VUNc9CuMmTgF3wzsh8qVKuH3WbPh5FkYvQdNVKnqtbahcJxq9VuhXJW62LtxEaJjYtG5U0eYKmTBHzXsZ5HO+ZWFLdKc9G9RYhn5FH5JzzB01Hil9izRQrlKlSqiCvq69RuwdsFENO3UF74Fi6mtT3Gx0Ti2aw2S4yMwcvhQnUcWUIQDQV4QmcePHhOKxl1SRJYsWYLXr1+L/SM53VtSshQpWqqGUCqCFMhrdx8hOeBdVjONYWaBCK9KmPXnPEwal/N1MwyjRmWErN3KwMqI+rhw4SIWL1+BcLdAJHmrOAlKzERYzPnXN/DTsJEY8u1XKF5ceWVGFSWEMq9s274DPgVLoN0nQ+DqnntlWlJEKJyh/8/T4K4gDIIKkTVo0xPVG7XD5VP7MXTYCDRu3BCtWrbkmP1cwi1GjZ+IV/Ylkeypv5Zq8pIEWzfFvMXL0bt7J4SHR6HNJ5lj0/U53Sptom/T8xus+nOMSSsjBGVKGzdqOMZOnIw3ZrWQ7qA/dTDMo17CJ+Imxk0Yq/K4QQv0z/p+KjZoL/1nOVy9C6JOsy4Ka9uQcYXGNPpXEbSn5MqZQ7h+/pAoYNi4USO9WMxSBkbagP7kyZMMxYge02vZ3TdSICijFoVnkSKi6zH5+fPnmL/oH5E0QxvZ3VJci+Dpq2AsWroMXw7oZ9LeUYbRmjIybtw4dZyGUYIXL15g8fJ/8SwkBmEFm0Bq7Zj3mg/eFZAQ64sps+ejQukS6Nv744zNifkNxyJPyJat2+FbqAQ6fvoTnN3UG/srw9bOAXWbd0HVei2FUkIx+02bNBaLTJk1j3nP7Lnz8douQK9DZmRIrR0QWrgJVq/fBE9XZ1w6tR9VajdTW3iWJtKtykhOSsThbf+ievVqajunIUNZlcaMGIoJU6Yh2LcO0h00Mx6ognn0K/iGXcGEsaPyNe7RRuUpkyfh2LFj2LjkNxQrU0WE62XN6kZeXkXGlfS0NNy8fBIXj+9CtapVMHXyr3qXgp1CsGlvB4WqEfRYUQFQUkTu3r2LsWPH6vw6SBGZNHU6Qvzq5H2+zANRvtVw5tYJWK5YiX59+7BCwjA5IJGqywfKZIJiXeWzg+QXyki2et1/uHn3AcI9KyDNuaD64l6l6bAOewDnsFuoU6sGunXumKe6D6SEnDlzBpu3boOXX1HUbNIJLnlQQmQbPXPyjCgiMSEOl07uxd1rZ9CsWTO0bNEc1tZ5T1GrjZSZ2pI12vw99rfZCKbQLDVOjD28QzSX4YjSrYbcRcsAW5GG9/GT56jWoC1KBFbNd5y+rM4IDYFWVjYYNDbnOiPKyt+Ni8dx49xhNG7cCB07UM0cM6ORt/yOa7QwnDh1ep4VElm6VcpylG5urVy6VQUeEaGIjBmp1orltLdp/4GD2L9/P0pXqodqDVrDykrx+EOyd/fGBZw9tAVlypRCty6dhbdBG6gqa7R3Y/ny5cLQlLXOyKJFi8RrAwcOFDLy7bffirAredmn9vS+NuXt1q1bmDX3L6GIqCpvDpf+zUjMkedkCenpcH15ClWKeomQaFNNuqLv4xpjhMoIhYGsWbNGZOmhgkfyp1+2bBlMBXUpI69evcKaDZtw694DRLqVRYpbUc25mdNTYRt2D47h91C7ZnV07dRBKYsh/cYUqkdZjty8C6JWk05w9cg9HEvRApGsyhSuYGPngMHjFuTpPAlxMbh4ci/u3ziHNq1bCcUkLxOBIQyiysoapSedu+kwIn3Ua61Xy6SdA2bx4aiQ9gCTxo4Ui9kdu3bj9q3bKF6uKspUqgtP34I6tTqSVfvZw9u4ffUUXj29j3r16orkCnlR6PVd3tQxruVXIZEkRMHh5ibEBnaF1NY5bx6R0MtqV0TkoU3dO3buwslTp1G3RXeUKl/9gzZhb1/i4Nbl8HBzxie9emp9X4i+y1p+5e3oseP4d91GhBZqKBK36Gxck0rh9OYyitomYfgvP+rcU6QLDEHWGN2idjWd3LNU4ZTqisydOxffffcdtm/fjlq1aqn7q4w+HGvl2g24/+QZIl3LIoXS9mo61tXMAgmeZZHgXhL77j/AmRFjUK1KZXzUtZNCax0Vyluy9B9Y2DihVY9v4O6Vv0GHLNWkiBCyf/MChUjUb9kdVeq2xPmjO7B/2HD0/qSX2HhqqhQoUABW8aFictRkNhl1YxkXgoBS7wrnFSxYEN989aXYPHvu3Dkc37cGkVFRKF6uOkoGVoeHj79WFBNSQJ4/uYsHN87j8b0bYs9Vi0Z1ULGi6Vo/lYV+w7Ejhr5TSPzqIt1eexmHzKNfwyfkkgjN0pQiItvU/VH3bqIeyMK/F+Pp/esi8YbMmxd0+RQuHN0uirmWL19eY/0wRcg4tnrtehw6cwlhRVtAaqnjcF2JBNG+VXE37B6Gjx6LMSOGibBFhmHeo/ZZ8+bNm5g5c6bIuEEu2urVq4uc4b///jvats29DoapQ+FYy1etxd1HTxHhXg6pxUgJkeSxCB1ZdCyUL0Inw8wCiZ6lkeheAoeePsDF0eNQs1oV9OzeLVPthMOHj2D7zt0i5W6hYmWgj1BK4MbtPkF46Bts3PwPrl2/gb6f9tGLTaG6UEaKFfRBdOhd8fsaApKkGLhE3EaHdhMyvU4bYhs3biyOyMhInDt/Hqf2rEJkVLTwmJSqUCvHjG15gcIQnz+6I7xtT+7fFIVD69auiUED++QrFNBUFZLRw37GpN9+R0jBBlpJLW0WGwKv4PMYP0aziog8lNp15IhhWLV6NbYsnwX/gNIiE2DE2yeYNHG8VosWmgIUSjZn3l+49iwMEUWaqa3YpjpIdC+JF5YOGD3hVwz7cYhGksbIEsdcunQpIx0zeWgrVKjAe1YY01JG6A9B5oakCZrc1WRVp/R+jGLIFb3uv404euI0IjzKI4UK0OVx8MhvEboMzMyR5FEKwW7FcfDBXZwfNlKEbrVs3kxUmN299wA+/moMrG3t9D7DkZuHD7oNGI49G/7GwYOHRCpgU+T7Qd9g9PiJeBGSjgSPMmrxkJDCS7tFKI5fKlHfkGKWEAGP58fx3dcDc4yjd3FxQcsWLcQRFRUlFJOTu/9FbGw8SlWsjbJV6sLB0SXP/Qh58wJBl47j4a3LotBbvTq18N2Xn7ICooaiiEN/+A7TZs9FSOGmImGBpjBLiITnq9MYM1L7aXLJ8NGnd2/hySOPnkTiiuqffWSS4TqahNYeVHPrVlg6ov3r6qX3V2QJtKiPqTP/wIifvlerQkKydfbsWezesw8evoXh9P+sbcGvzmHT5i0iXJkiA7guF2MSyoi/v79IdViqVCkUK1ZM7B8hlzUX/1EMVbGlug/B5u6IoXAssbhTF2rYEmRmjgSvskhwC8Da/adx9vxF1K1ZDQWLlVWrIqLpDEe0KChetiqePr0NU4U8CpMnjMPvf8zFgxcnEO5bA7DIXxgDed5kcfzxZd4XLsszUimsw+7BPfIufvrhO5QsWVLpj5IVsEXz5uKgitHHT5zA5qW/wc2rACrXbYUChUsoHYZ17+ZFXD1zAJYWQNPGjTDw0246T1FqbNBvO2hgf8xdvBwhRZsDFupX8CTJ8fB4fgy/fD9IeGR0ARlWOFRZsyxZtgK3Q1MQ7VtdLxURGel2bggt2BDTZs3B1Inj8rw2omQJlF751q3buH7jJkLDwlCsTGW07TX4gz2bb148xolzR7By9RoUKlgIFcqXQ5kyZcTfAyUgYBijU0b69euXEQLz6aefYvHixcI78sUXX6j7q4yCuLg4kX//tWsFpLroZqJUGgsbRPjXQ0LIbSQcPY70lBRcO+eNCjUaGYQL+OmDWzh1YCN++ekHmDJkHBg9/BfsP3gQ/23ehgj3QCS7FcvXBE5WbbGhOJ/WbfKGuL25iNKFfPDN8Mn5CmMhb0rnTp3QsUMHXL9+Hdt2bMKZVKB+657wLlBEYbz5/aCLOHNwM4oXK4ZvvuyHQoUK5eOKmNyoXLkSPu7aAau37kVYkabqDa1JS4H7s6MY+FlvYSBjjJM7d+7g7NVbiApoodeKiAwKSwzzqIh5fy/G+FEjcm2flJQkEj88ffoUDx89xqNHjxEbFwefAoXhW7gUarf6BB7eBRTOwz7+RcVBoaakmDx7dAtnV61H6JuXcHN3Q0DRABQLKCK8lRTOy/veGG2jdombM2cOGjRoAHt7e+EOp4JH2ogTXbFihSiwlzXloKptVTmXOtizdz9CbQuqVRFp26a1RlOtJnqWwdsX4RjQqSWuXL2GdQtPiDS+RUuWz7dSQhWsaUFIm9fJM6IOgl89w7mj25AcF4lhv/wkBtucXP2UP59ibulaSJY1JUvaljV56NpaNm+OGtWqYfGyFbjzaC/CvKog3TGPGyvNzPOU2SijPymJcAq5AefkEAzs3xcVK1bM87k+6JqZGSpVqiQO2tO24t8lKFyqkihQJ793KDE+Dvs2LYa1uVTIia6rXhvyuKYqzZs2wZu3b3Hg4hlRkFUtC0ppOtyfn0Dn1k1Rs2ZNdXST0VO27torwpvVmeRF0/NoikthPH8YJDy48mGolJH00aNHePz4CR49foJnz58hLS1d7IHz8CkEr8KVULZOJ1H4V9WU5TTe+RUqJg5xXVIpoiJC8fblE1y//xSHj59FaPAr2NnaCiNMQNHCYs8vHVy3izGo1L6nT5/G8ePHcePGDWGJosUcuac1KcgbNmwQqWVHjhwpnk+ZMkVMPt26dVO5rSrnUkdKwoVL/sG+p6lIVWMROk2nWiXs3lzFwBaVRdGrhw8fitoir1+/RfnqjVGmcm3Y2Nrn+dz5qTMiIzU1BQ9uXcGN84fEvejYoR2qVauWq7K0Z88eIbtffvmleP7PP/9oTJa0LWs5QaGVi/5ZgZBECcI9K+VLsVCJtFTYhd2GU+RDdGjXBq1bttC4VY7u1bLlK3Dv/iM4ubhl2htCdUGaNm2iM0+ffApMQx7X8gJNRTP/mIvLb5IQ41M5f6l9pVI4vzqHBmUKYGD/zzXSX0PHENKtKitv3/88HI+86kBqaWdQ86jHqzP4vncHET1y5ep13Lt3DxIzc/gUKAIPvyLw8issUpdbW9sqfc7ZY74Qykh+Qp3j42IQ8voZ3r58itDXT/D21VNYWVqiTJnSqFqlMsqVK6fSOG0IssboFrXP+nXq1BEHbSSl4kj79u0T6X5r1Kgh0vxqgiNHjggrn6wmRpcuXbBy5cpsJ9rc2qpyrpwgS2R2gygtcuT/iJs0qIeLf/6FUCffD+KlSUtMx3tLjznSFX5f1rYyi6/UzCzbz6Uped6sbc3oWxJj4Bz7DBUrfiaukSwo3w/+Tux9odzua+aPg49/AEpXrIOCxcoozFxlbmGZ8Tg9LTWjJg09ps/Qv2mpKTm2zXQPpFIEv34mCh4+vH0V5QMD8Xmfj4XrWfabZIV+C9nCk7witAGwQ4cOGXsDNClL2pa1nCZ1snxNnzIJFy5exIpVaxFr5YZoj/KQWn04CaoilwpljQpthj+CU8Qd1KtVE5079hf3XL6/dF052UqoqFpe2tJ9+azvpyKpBv3mMuj7yUIpr4jkdt6s8kNhEOpoa+jjWk6yllPbb7/6ApOnzcCDsDsi+1C2smZth4TALjCzpr/R9GxlzSH4Osp62qBv715K9VdTsqbOtpqUNUPH19cHT2LCkeZsQHu66LeOfovFS5aiaMkKKFK6Kqo0/RjWNsorHprCzt4RhYuXE4eMuNhokU1w94ETWLb8X/z80w9ijzDDqAONmSBpI2mbNm1QunRprFu3ToQHaEIZIZcmuTkpy40MekwLY8ouIb/hNLe2NGArey4ZNNHJT3Y0AVBMPtVWefPmzQftacNY69bvXL8EKWw1K5alLWYftA1Ns8HphPeegWb2z2EtyX5SiUizwomEAhnZjWpUrwzbDG/U00xto9MscTTh/SBS3/YVnMyzXzzEp1vgYPz7ELJ6Vs/g4iAFPMqLcCZ5yPtF+4R6fNRdxOifPXsOYU+vZHteM3MLVG3eJ+P5g6tHEBXyIuN5w4YN8eTqQTz5//Pqrd5bNx9dPyFSYyqiSrmS+KZ/L9Gfo0ePioWYIvr06SN+L4I8eqREUxX5y5cvi9eoYrAmZEkXsrZq1apsFTLC19cX7du3R80aNVCtalVRoDQ9PThXWSMa272EnVn2581R1hwtgcLlkZwYj/Xr14vsQr16vU9DvXPnTmEZzQ6ZrMnYu3evwox9tDCjvWwyDh48KOKvFSFfJZrkhzLHKeLzzz/PWFDSGEeWTWVkjZReqg6dlXHjxhnFuKaMrMmg+UGWhpQoXMAX78wHT3ORtYhsZc029C6KWMagREA5/Pvvv9n2gWXtvawZA106tMXdPxYgxNFHbQlgNJUlUIZ1+AO4OTvA2sYepSrVQYFCxSFRQ8p5TWWkpDT5JcpVEaHUZPSjMgSsjDB6rYyEh4fjxIkTYnFHjykcQFMDn2wSk59Qab8KQa5P+ddzayuzSilzLhm0IN+4cWMmC/O0adMU9pcmNpqMZWgiHISyG0mtngk7obqQJMXCLfQ6bItSbGv2eznImyG7NhqkgoODxYY7bdO1a9eM9IWyCVkRVHxK9hvLJnr5OHpNyZK+yRrdL/m29FlaqKoTSWI0LCziAPPs5Yfuu3wf5K3GOckakVO6SrrurNeWE/Jtc5Mf2leSF1nLLSuXMY9rWWUtp5o/kjTVQsKsIh6jcPorLJg3T+yRUQTLmnFRokQJtG5SHztpzVGogVoUElGfKz1NzH3qTjttEfkMXtH3MHbSeDx48AAHDu3Gvv9eoGBAGRQsRh6JsrBzeF/TS5cZKaMjQvHkQRCeP7iJ188fomTJUvj6ywEqZTlkGK0rIxMnTsTdu3dFVVlaFFKcvibzWssGe1o4yQryyRZRWQfs3NrKXNnKnEtG586d0a5duw8mYQr1URQeIG9Vo0r1MsiSuHfffuzZfxCxjoUQ6+6T6Rc6GKd4k3tW5/6ReOUtFicSFMdz0kDsEnYODokh+PijbqhTO+f0lPLXRvtJ5MMOyDp78uQpnDx1Gu7eBfDs0R0ULFpK3JPilRrnGKKQcY63L/H02VM8vR+EypUro2GD+h9kOyKLr+x3IPnLqeo6eUKio6PFY9rgTAsw+k1l6RY1JUu6lrXc2vbo0SPT77Z42b949CYCET7VkW6deT/QkXjFCQEE0nTYhwTBJfYpan/6CSpXqpTtYjVrH1q1apWjTOQkazm1pc3b9erVU6ot7XfLafNzXmWNNujnVHnbmMY1VWQt670d/+tUmHnbId3BK1dZM4t+Bd+o2xgzaby4z+R9USQTLGvGR7cunSGRmGHXof0IK1gfUms1FJTMZ2KOD5BKYRdyEz7JrzF23GgRQVK1alVxkFHh9u3buHrtBjYf3yE24xcuWQHFSleGb8EAtXhNlCEtLRXPH97Bo7tX8OxBkNjMXr58ILq0byGUPs60xWgCtUsV/VENGTJE/JFpA3K3U5w35duWZb+hx/RaVouQMm2VPZe8RS07qxr9wSqasORfl//DpsedOnZAyxbNsXvvPuzdvw8JDgUQ7V5aDKzysfe5kd+2ZvFhcAm/A/uUSFHokBb9ygxC8teWNVMPWeu6du2Czp07iU3iu/bsxok961CjcQcUL1MZZjlYUykd4dnDW5EYF4k2rVriu4Gf5qjkyvpBVs3cqq3L2pJ8UAE9cj9rQ5Z0KWuqtKXfjVIBU7jH0hWrEeZRAeluRZWSNVJmPV6cRI0KpfH5p7/lainOSX70sW1eZS23tsY0ruW1LfWV5G785GkILtQIUhtnhbJmFhcGz+DLGD9+jFC46PyGID/6IGvGAilq3bp0EhmgFi7+B+FuZZDkVkJvUv1KkmLg/uosKpQohK+/mPjBWEjPycBGBxEREYGrV6/i3Omd2PvqFQKrNUSlWk1hZZ3zGEphVIQsm5ayxMVE4fKpvbh7/bxQOmpXr4qBn3bn4pyMYSojbdu2hbZp1KiRCCug/SkEPSbrVV7aqnIuTUHWyq6dO6F92zY4dvwEtu7YhTgLR0S4lEa6w7uqqhqBJvDol3CLuANXW3N81KMjqlerpvaJjM5H1jo6nj17hvUbNuLKqX1o1vlzUSldHkq3emz3GkSGvkTPj7qjQoUKGs10RIkWDhw4IMJSNC1L+iBrqkCWW8qQR1WOn72JQIx35RwnevOYN/B4fQ5fDfhM7ENhTHtcywsU7vnjd1/j97l/I4RqSGRTFFGSEg+PlycxfOiP8PTU4PjIGARVKlfG779NFpkqbz/ej3CfGki3e5e4QSekp8E+9Bacox9jwOd9Ub2acmMhJZto3LixOMjLtXfvPqyaNxaN2/cRafQVMWjM+1S+ykBKy82LJ3Dh2A60ad0SX/SZxml8GcNP7asLKLxp+fLlYjN41hz6ixYtyrRRMKe2yryvixSYFGZx5coVrN+8DaExiQh3K4s0pwLqs/hI02EZ/hguEbcRULAAPurSUevxoGQBogwdDdt+goDSFTNS/O5YNQetWjRHixbNtWLdk68zIttIrylZ0kdZUwbq958LFuLK03BEFqidrRxaRL2AT9hVjBkxlNM6qoD8vTL2cU0V9uzdh3X7TiC8YMPM8iZNh8eTQxjQsyPq1qmj9X4ZMqr+Xaqz7o225I088H8vXY5IS3dEeVUQhXu1Bhn3Ip/DPeQq6taqLsKcc9vrkxvktf9jzp/wK1oOtZt2ynctLjL2Hd65Emap8fjm668ywjjVDc8BjEkoI/qIpiZt2uy2esMmPH0VjHD3QKQ5++ddKZGmwyrsEVzCb6F8udLo0bVzpg2V2ob2Jvw6eQpc3H1EfOybl08weNC3GdZcXWAIg6guFoikIM+ZtwAXXsYjxidz7LpZXCh8Xp/G5AljM/beMMYhb7pSRmiaopS/V2KdkOxePON1u5BbqFPAEkO+/VrrfTI1WVNn3RttyhspRnv27ce2nbsR7VoSCe6lyT0PTWIWHw63t5dQ2NsFX/b7TK3zKt2PjZs24+y5C6jWoC3KVqoNcxX3cSQlJeD6uSO4fv4w2rZurXFjn76Pa4zuYWXEQCdtylK1bNUaPH0bgXCvqki3f1/BVRnMo17ALfgqKpYrhV4fddOb8AZZmlLC0dERbm7vi9LpAkMYRHW1QKRJfsSY8bhvXfydUkykpcLz4W6M/uV7BASor5CnqaDv8qYrWZPF0P88YgyCi7cFzC0hSUmA9+N9mDNzuklkjNK1rH399dfCu0HhmgSlQKdaNQsWLMhX25ygDf7JyclqqWsTExOD1es24OK1G4jwrPguukDNNZQkKYlwCr0B59RIfN6nFwIDA7Ptrzrqz1BCg507d+H6zSAEVm2ACjUaiRolOZ03NiYKV88cwIOgSyIZDaUAVrQnRJ11bWS1vhhGEZwWwUChP+7xo0aI/PELlyxDWJQ7on0q5ZrSkCZw1zcXUMDBHN+M/Fnv8oTTwMgb5gwDmoB+HPwtRk2YjKSEdzUazBIi0KxhPVZEGLVDMfQN69fFzpv3kOBVDg5ht9G+bWtWRLSAOuve6KquDYUgfT1wgAhXfKfgPFVfDSWpFA2tH8PBwQxwpcxvXrh48aI4NF3XZsqvE3Hw0CGs/WsCypQNhIWZYmXkzt37aNWyOb76bJoovyCfvluTdW2MqaYNoxlYGTFwypYti1nTp2L9xk04dHwvQgs2gNQm+7hPs9hgeLw6g57dOqFZkyYa3QjOmAY00Q//cbBYaBAUEy7LBsMw6qZ9m1Y4dHgYUiUWsAy9j+ZN1V9Il9Fs3Rtd17WhBXx23pa8YpYQCY8352FfvoRO6tpQUhE6vhgwAPPmzRMeIEWsXvVvRjiWTFFSBNe1YbQJh2kZUTjD9Rs38OeCRQjxb/BB9hDZhuJRw/TPG6LP6HvYjK5DZxjTkjd9kDXKMPg2OBiFCvqjVg51ORj1yRp5O6iy/J9//pmRHpo8FoMHDxaehqyeEWXb5uYZIY+Aoro2qoZpZdeWPDVLl6/EjYfPEeFXG+lWtsqHaVHq3LD7cIu6j2+/HCAMgznVtVF3mJaitpR5a8Fff+PtmzdIl6ajXLlA9P20t1AsVDmvOsO0stYCY5issGfEiKhQvjyG/zQEU2fOQZhXFVE0iZCkJsE7MgiTxo/hDcUMwxg0VPOI0S7qrnujL3VtKHTrh8HfitCiJStWI9S3JuDok3sNpfRUuL48g9LejhgyckqGV0AfatVQOOOokcPzfV759lzXhtE0rIwYGcWLF8c3A/vhxOmzcq9K0LH/96yIMAzDMDqve6Nv0EZ7st5TxrbXqeWQ4vp+v8sHpCbB4+kRtG5UB927UtV3DndmmPzCYVpGHM7AGH/YDMGyZjzou7yxrJl2nRF11b3RV3mLiorC6AmT8NKxLFJcsgktSkuBx5OD+Lhja7Ro3kxr/TJ09H1cY3QPKyMagidt48AQBlGWNeNB3+WNZc140HdZ05W8UQrp4aPH4U2B+ki3ldt7KZXC9cVJdKxfBV07d9RqnwwdQ5A1RrdwYB/DMAzDMMz/U0h/P+hruL04BYuQexmH9cvLKOZuiy6dOui6iwxjdPCeEYZhGIZhmP9TpkwZ9P/kI7ySq+9hZuaL5k05JT7DaAJWRhiGYRiGYeSoV7eOrrvAMCYDh2kxDMMwDMMwDKMTWBlhGIZhGIZhGEYnsDLCMAzDMAzDMIxOYGWEYRiGYRiGYRidwMoIwzAMwzAMwzA6gZURhmEYhmEYhmF0AisjDMMwDMMwDMPoBFZGGIZhGIZhGIbRCayMMAzDMAzDMAyjE1gZYRiGYRiGYRhGJ7AywjAMwzAMwzCMTrDQzdeqjzt37mDp0qV4/fo1fH198cUXX6BkyZJ5ah8REYFFixbh0aNH4vH06dNRpEgRLV4No0vod9+4cSNCQkLg6emJ7t27w8/PL8+yl9P7ly9fxrZt2/Ds2TOYm5ujTJky+Oyzz+Du7q6Va2X0Hx7bGEOURR7bGIYxKc9IbGwspk2bhpYtW2LZsmXi399++w1xcXF5ai+RSFCpUiX88ssvWr4SRteQDCxevBj169fH1KlTxb/0PK+ylNv78fHx6NixI/766y/MmzcPtra2mD17tlavmdFfeGxjDFUWeWxjGMakPCPnz5+Hm5sbmjVrJp7Tv7t37xavN27cWOX2Li4uYqBVhZSUFHHIoEmfBl8LC4O+tSbHrVu3xO/foEED8Zz+PXbsWJ5lKbf369Wrl+l8bdu2xdChQ5GWliasidnBsmY66HpsY1lj8iqLPLYxDKMqBv2X/vTpUxQuXDjTaxR6QK+ro70ybNmyRYT2yKhbty6GDBkCV1fXPJ+T0T7h4eEoVqyYCM+SUbx48TzLkqqyRsqQv7+/wsmaYFkzHXQ9trGsMeqSLR7bGIYxWGWE3MAUe6oIcv8mJibC3t4+0+t2dnbi9exQtb0ydO7cGe3atcv0Gll4LC0tYcwkJCRg/Pjx4iALlj6jC1lS5XyPHz/G+vXr8eOPP+Z4HSxr+i9rxjK2sawZh6zpQhbl4bFNMaYmawxjkMrI4MGDkZqaqvB9BwcH2NjYiHjWrPGqTk5O2X5G1fbKQIOlMQ+YipBKpWKioX/1HV3IkrLno02eU6ZMQb9+/VChQoUcr4NlTf9lzVjGNpY145A1XciiDB7bcsbUZI1hDHIDO1leaLBTdJiZmQnX8ZMnTzJ9jlzHhQoVyvacqrZnjANdyJIy56PJetKkSejVq1fGXhXG+OGxjTFmWSR4bGMYxiiUEWWoUaOGiPU/fPiwsO7Qv5S2kl7Pa/vk5GRxENSGHqenp2vtmhjjkKXc3n/+/LmYrHv06JHtJlDGtOGxjTFUWeSxjWEYVZFIDdxHSPnPlyxZIvKfU02IAQMGoFSpUuK90NBQ/PDDDyKtoIeHR67tiY8++uiD7xg3bhzKlSunxavSfyielzYdUqyvsbjX1S1LOb2/YMECka3LysoqUx/kz88Yr6wpA49t2sdUZU2dsshjm3KwrDGMESkjDMMwDMMwDMMYJgYdpsUwDMMwDMMwjOHCygjDMAzDMAzDMDqBlRGGYRiGYRiGYXQCKyMMwzAMwzAMw+gEVkYYhmEYhmEYhtEJrIwwDMMwDMMwDKMTWBlhGIZhGIZhGEYnsDLCMAzDMAzDMIxOYGWEYRiGYRiGYRidwMoIwzAMwzAMwzA6gZURhmEYhmEYhmF0AisjBsjq1atRp04dXXfDYBk/fjw6deoEU4HlhTFkjFV+p0yZgo8//ljX3TAajFVOcuPo0aNwcXHJeN6oUSP88ccfOu0Tw6gKKyMGNtAQn3zyCU6fPg1D5NmzZ/jss8/g5+cHR0dHFC9eHN999x1ev36dMZBaW1uL95ydnREYGIiffvoJISEhGed48eKFmHTc3d1Fm0qVKmHLli0Z7+/atQsNGjSAq6srvLy80K1bN/EZU8AY5aVfv34oUKAAHBwcULhwYfF7njp1CqbwW0okEnHddHh6eqJXr14IDw+HsWJM8pvV6BEfH4/WrVuLsSkqKgojR47E2rVrczwHjVvdu3cX94SOli1bZrxH55LJBh02NjYwMzNDaGgojB1jkhNl5kVjga6nQ4cO4jppbLt69aquu8ToCayMMFodcKtXrw5LS0sxaURHR4tFpa+vL44dO5bRbtq0aYiJiUFkZCQ2bNiAly9fomrVqnj79q14n5SM5cuXCwWFJvUFCxagd+/eePz4sXifXhs2bBieP38uXnNycsJHH32ks+tm8sbTp09RrVo1WFhY4OTJk0Jebt68iR49emD79u3ZfkYqlSItLQ3GAinbsbGx4rh3755YaJJsM4YFjWXNmzcXysK+ffvE75obcXFxaNy4MSpWrCjGMvrtf/3114z39+zZkyEbdHzxxRdo1qwZPDw8NHw1jC7mRWOA5L9Vq1bYunWrrrvC6BtSRuPMnDlTWrx4camDg4M0ICBAOnfu3Iz3Hj9+LKWf4d9//5UWK1ZM6uzsLO3bt680OTlZGhoaKrWxsRHv29vbi+P48ePSZcuWSStWrJhxjufPn0ubNWsmdXR0lFapUkU6efJkaeHChTPej4mJkX777bfSggULSj09PaV9+vSRRkZG5vr96uazzz6TNm3aNMc2DRs2lM6ePTvTaykpKdJy5cpJf/nllw/ap6enS8+cOSO1traWHj58ONtzXrt2TWpmZibOQ4wbN07atm1bab9+/cQ9o99m8+bNUn2B5eUddN7mzZvn2o76PmXKFGnNmjXF9V+/fl26cuVKITN0D+k6Ro8eLWRFBl3DX3/9JdrQfWjfvn3GNQ4ZMiTj/tFhaWkp5PLq1avifHR/ZLx48UJqZWUlffnypfTIkSPifsyfP1/q5+cndXFxEbJ8+/ZtaY0aNcT3dOzYURobG5vx+QcPHkjbtWsn9fDwkBYqVEg6adIkaVpamnhPdj556Ny1a9eW6jMsv9KMcYZ+79evX0vLly8v/fjjjzN9j+x9RcybN09aq1Ytpb4rISFB6urqKl23bp3UUGA5UX5efPPmjbR79+5inKD+jhw5MmM+yzpOyM+hdI0dOnQQ1+fk5CStX7++GMdk0FgzatQoqZeXl9TX11fIHJ2Lzilj7dq1Qn7p9WrVqklPnTqV6buGDx8ubdGihfgdK1euLMZfZaD7e+XKFRXuFGPMsDKiBTZu3Ch99uyZWAzRgpkG0pMnT2Ya9Giiio6OFosaf39/MbAqWpBkHXRpgOnfv780Pj5eevfuXTGwyw+6NIjR+SMiIsRCqGfPntLevXsr9f3ZQf1RdNCgpQga7JYsWaKyMkLQgEkLOnnou2ihSP1v0qRJxuCclT///FMsOuUXAebm5tKFCxeKz2zfvl0oM7Qw1AdYXt7h4+MjXbp0aa73i/pesmRJ6Z07d6SpqanSpKQk6e7du8W10T2kCY8m21WrVmV8hq6hcePG0rdv34rrpEmU5CIrr169EpO/TG6rVq2a6VpJCWrTpk3GvSell5Rm6sOBAweEnJHiS78nLXRIDmkRRsTFxYm+k7xT+6dPn4r3Zd+V9bcMCQkRi5aff/5Zqs+w/L6D5IkWb7SY/frrrzOUTGWVEbqObt26SVu1aiUUDVpQ79q1K9u2a9askbq7uws5MhRYTpSfF2l+69Wrl1Aunjx5Ii1btqxQrrK7F/JzaFRUlFBQ6fpIYR08eLAYK2WGGfreIkWKiPtD94kMdDSGyZQRkrcCBQpIL126JOR306ZNUjc3N6EQyr6L3icFh+bSL774QrymDKyMMPKwMqIDaAL69ddfMw16ZD2VMWDAAOmgQYOUGnRpMKfP00JFxvTp0zMG3eDgYDG4hIeHZ7x/7949sYinhVtu369OLCwspHv27MmTMrJgwQJhRcsKTb47duyQzpgxI5PlW8bly5fF/du/f3+mRUCZMmUytaMJn6zS+gjLyzsOHjworo0snd7e3hmvyxb0OUHeDuqnDLoG+XPT/SUPhTykLNBicujQoZnkUH6yLVWqlPS///7LpIzQpC6DLJKk9MogReWTTz4Rjzds2CCtVKlSpu9ctGiRWHjIzkf9lC1oJBKJtHTp0sLia0iYqvzSOEOySp6z8+fPZ/t+TsoIKZ50LVu2bBEWefrX1tZWev/+/Q/aksx8//33UkPGVOUkt3mRvK/UF/KOyFi9erW0RIkSuSojWSHFi85F55TJDc2dMui+0PsyZYQMLX/88Uemc9SpU0d4jGTfNWzYsIz3SJkkD4kysDLCyMN7RrSU5aNKlSpwc3MTm+527979wSZDHx+fjMf29vZiz4QyvHr1SmxclI8TLlSoUMbjJ0+eID09HUWLFs3YBEnxqRS7+ebNm3x/vypQH2n/R16gz9H9y4qVlRXatWuHI0eOiPssz40bN8Qmz3nz5ol4bXloI3TW53ntm7pheXkH9ZH6K6Np06Yi9p72iyQmJmZqK38NBMXlU5IDOgfF5y9cuFCle0hzJe1DovP+9ttvGa9T9qMLFy6IvUhnzpwR56QNmTJo86mtrW3Gczs7O3h7e2d6TvH9sntNe2Bk95kOStYgf5+p73TNdCQkJKB///5iA3TW69cnWH7f06RJE4wdOxYtWrTA+fPnc8ysJduITmMWQY9JhmkTPO0noH9p79z+/fszfZZkkcY/kg1DguVEuXmRkhjQtciPIwEBAUolZaEx45tvvkGRIkXE3kn6l5DdZ7pPBQsWzGhPSTLou+TvEyVakB+jaNO5fH+z3iPZ+Ea/r0ymy5Urp8IdYUwRVka0sDmtb9++mD59OoKDg8Wiok2bNmKxoww0OOYEZaWghYn8IE7fKYMGGjoHDTqyRQ0d9BnKUJQX5DO4ZD1yGnQoE8z69etV/r7U1FRs27ZNZNpSREpKCu7fv59JEaHNnFOnThWLyuw2R8tD9yyv90OdsLy8hxTI//77T+XrTk5ORpcuXfDll1+KSZMSGnz11VdK30NClgBh5cqVIuuLDJqMO3fujBUrVogkCpTBhxTivED3mhaX8veZNq8GBQVl256yzNF10OJTURtdw/L7IaNGjRLyRArJuXPnsm1DCz7ZRnTamE7QxnVlWLp0KWrUqCEyDxoKLCfKz4v+/v6iX7IELjIlgV7PjZkzZ+LSpUsZCUDoc4TsPtN9onFOBiWFkTd00H2ic8jfI0qsMHz48Fy/m8ZGmUzr63jF6A+sjGgY+kOkP3xKMUuDH1l/slq2coKsIWSNoQE7O2iwqFu3rpjMyApCC/JFixZlslqQRW3QoEEZAzNZfuRT4eblmhQdOQ06EyZMEFYVWlDRxED3hQY/yp6laDC+c+eOmLRoQfnjjz+K1yjDCFmladFJBy0KyTIo835QH0gRocwzn3/+ebbnpcxEixcvFooOpQI+fPiwyNKka1heMsvLxYsX8fXXX4sFON0XSo+qaEEnIykpSUyolPqZFvDUfs2aNUr3lxZ369atw44dO4QnIytkgSaZI5mltMN5hTx6tMCgbHDUX8oCdvfuXZG2NDtIVklmqU9kGdVHWH6zhxZvpJSQQkJjlzJ8+umnuHz5Mnbu3Cms+PQvPZdP70syQ7JoaF4RlhPl50VSjiir2s8//ywUAWozefJkMS/mBikg5OmgDJTUD7of8pCnl8afBw8eiPtE78sret9++y1mzJghFBrZ+Hvw4MF8pcqnsU6m8ND8TY9JvhnThpURDVO2bFkxCZG7nhZHNLjIh3XkRqlSpcREQ+chqyxZOLJCC61Hjx6JAbpnz57CE0CLMBk0Wcnc0OSqrV+/vhhctA2FQlGICw0+NWvWFH2pXbu2sF43bNgwox1ZEWV1RsjCTRMHLUplbmoakMnqTfeTXvvrr7/E4rFevXri/d9//10M5j/88EMm65S8ZYzSC549e1aECAwZMgSrVq1CiRIloGtYXt5DIRQkLzQBUrgK/YZ0XRTuQgszRZDszJ8/HwMHDhT9p4lbFUWTvCG0MKFc/1lDZwjy0JmbmwuFQFnrdXbQeWliP3TokAifoN+b6ojIh4mQEi7rA4VzkKeIlCRaXOgjLL+K+eWXXzBu3DihTChTJ6dYsWLYuHEjhg4dKq5j9OjR2LRpk3hdPhyRrNV0HwwJlhPV5kW6FlIWqC0pWW3bthVykRtkwKOxiu4Bec7ovPKQMYXuDY2vJFdUs4uUF9l9at++vQhTpbTRNObQmDxnzpx8KQ8UxioLZaXrpcfHjx/P8/kY40BCG0d03QlGvVBoEln6Dxw4oOuuMAYAy4vq0CKKFGWyrDK6heWXUQaWE+WKElLoFnk+9CFsmTEd2DNiBJDrnsKZSK8ky87cuXNF1V6GyQ6Wl/xBYTbkqevTp4+uu2KSsPwyysBykjsU+kkFCGnPZUREBL7//nvhJWFFhNE2rIwYARSSRGEklMmia9euwqVqaDHEjPZgeck7FN5H945CFZSpos2oH5ZfRhlYTnKHFDUKw6JQOQrTohBoVfbXMYy64DAthmEYhmEYhmF0AntGGIZhGIZhGIbRCayMMAzDMAzDMAyjE1gZYRiGYRiGYRhGJ1jARDJGUMVkWS5yyidOBYMo/7YiqBjPTz/9JAorUT5yhlFVlnJqS9lLqLgeVYonGaN6J5Rnn1LGMoy65ZHljckvLGsMw2gKk1BGNm/eLFL8zZo1SzyfMmWKqLTarVs3hZ+hIkyenp5iMGWYvMhSTm2pcjIVkRozZowoSEUVgikPPmU1yU8hPca0UFYeWd6Y/MKyxjCMpjCJMK0jR46I1H40QNJBxcqo+JEiqGrr1atX0bFjx1zPTVYgqhAtf9BrjHGiiizl1Jaq3FJVcKouL5FIULJkSZQrV05M9opgWWPyKo+qyhvLGqMtWSNY3hjGtDF6z0hsbCzCwsJQpEiRjNfocWhoqBjw7OzsPrDq/P333yIfuTJZj8kytHHjxoznRYsWxbRp09R8FYyhyZKqckdhgQ8ePEC9evUUfj/LGiOPqjKmiryxrDHakjWC5Y1hTBujV0YSExPFv/KDJRVBIhISEj4YRLdv3y4G2bJlyyIoKCjX83fu3Bnt2rXLeE6WIFnBJYqxZQwbX1/fPMmSKm1J6V24cKH4rho1aijsC8uaacmbusc2VeSNZc340RdZI1jejBtVZI0xTYxeGSGXMUHWGycnp4zHhK2tbaa2b968wYEDBzB9+nSlz29paSmO7OB6kqYrS8q2JRlZsmQJXr9+LWKszcwUR06yrDF5lUdV5Y1ljdGWrBEsbwxj2hj9nhEHBwexce7JkycZr9Fjei2rNYdiWqOiojBkyBARpkVKCVl96DFtwmNMG1VkSZm2NMlS1hkKYRg1alSOoQ4Mkx95JFjemLzCssYwjCYxes8I0ahRIxGTWrp0afGcHjdt2vSDdrVr10b58uUznt+7d0+4mEkpcXZ21mqfGcOWJWXa0mR99+5djB07Vkz2DKNJeWR5Y/IDyxrDMJrCJJQRygBCKXp/+OGHjPzoFKNKLFq0SPw7cOBAWFtbi0MGuaMpdpWsPwyjiizl1pZioffv3y9CE7755puM81Mb2ecZRl3yyPLG5BeWNYZhNIVEygGZGoEGZE5NaPj4+flB32FZMx70Xd70QdaOHDuOR4+foGzpUqhdq6ZO+2LI6Lus6Yu8MaYha4xuMfo9IwzDMIzxsGbdBuy8H4c1G96ngmUYhmEMF1ZGGIZhGIMgPDwc6RbWSPUogfiExIyUswzDMIzhwsoIwzAMYxDcuHkTibZe4nGqgxdu376t6y4xDMMw+YSVEYZhGMYgOHHmPOLs38WfR9v44tTZC7ruEsMwDJNPWBlhGIZh9B4KyXr86DHSHL3F81TnArh2/TrS0tJ03TWGYRgmH7AywjAMw+g9Z8+eRZKTPyD5/7RlbokUO09cu3ZN111jGIZh8gErIwzDMIzes2PvAcS4FM/0WqRTALbv2a+zPjEMwzD5h5URhmEYRq959OgRIuJTkG7nmun1NEcfPHv5Bm/fvtVZ3xiGYZj8wcoIwzAMo9f8t2U7IlxKffiGRIIo15LYsn2nLrrFMAzDqAFWRhiGYRi9rsJ97+FjpLoUyvb9ZLcAXLh0GTExMVrvG8MwDJN/WBlhGIZh9JZNW7cj0rWU8IJki5kFYl2KY9eevdruGsMwDKMGWBlhGIZh9BLydpDXI9mtWI7t4t1L4uCRY0hOTtZa3xiGYRj1wMoIwzAMo5fs2XdAeD1gZp5zQwtrJDj44+jRY9rqGmMC3L17F5Onz8Q//67UdVcYxqhhZYRhGIbRO1JTU3Hw8BHEu5dQqn2Meyls370XUqlU431jTIPDx07iUpgZTp4+h4SEBF13h2GMFlZGGIZhGL3jypUrSLLzBCxslGovtXZEvMRGWLMZRh0E3bqFVPfiSHf0wZ07d3TdHYYxWlgZYRiGYfSOXfsPIcopQKXPRDgWxZ4DhzTWJ8a0srglpEohtbRFlI03Tp+/pOsuMYzRwsoIwzAMo1fExcXh+fMXSHPwVulzqc4FcfNmEFJSUjTWN8Y0OHX6DGIdCorHqc7+uHr1KtLS0nTdLYYxSix03QFGMyxetgJPnj0Xj6tVqYzO7dvqukuMERMcHCwyHwUEBECiKAUrwyjJpcuXkeTkrzidryLMzJHm6I1bt26hYsWKmuoeY+TQvqMDR44hwaf+uxfMLZFs5ykUkqpVq+q6ewxjdLBnxAihifj05SDctCyNm5alsHP3HoSGhuq6W4yRkp6ejp+HDsWEKdNx8eJFXXeHMQJOnrmAWPsCefpslK0fTp69oPY+MaYD7Q+h/UdSa4eM16Kci2Hrzj067RfDGCusjBgZlGf/r8VLEe5dBem2Lki3dUWERwXMW7iYs8wwGuHZs2ewdC2AGL9quHj1uq67wxiBcvvw4QOVQ7RkpDr54caNG2rvF2M6bNy6ExHOJTO9RvL4KjgMr1+/1lm/GMZYYWXEiCBlY+6CvxFiXQDp9h4Zr6e4FsWj8ERs3LxFp/1jjJNzFy6KDZ60CLx27TorvUy+ePToEaT27oBZHqcnC2ukmFnh7du36u4aYyIhp09evESak1/mNyQSRLqUxOZtO3TVNYYxWixMJV/9ihUrcPLkSfG8fv366Nu3L8zNMxfSok2PS5cuFVY1in93c3NDhw4d0KRJE+g7tABc/M9yXHsWhjj/upnflEgQ4Vcbu48chIODA1q3bKGrbpqMLCnTdu/evTh69KjwLFSqVAlDhw6FoUFyd/zkaST7NRSLwGQLezx8+BDFixfXdddMAlXk0VDk7eLlq4iy9srXOeJsvXH16jW05LFObRijrGXHtl17EOlSItv9SsluAbh8dYdIsGBvb6+T/jGMMWISnpHNmzeLGNBZs2aJ4/bt29iy5UMvAWXKcHV1xZgxY8Sg+80332DlypW4du0a9BlSombPnY+TQU8R4V8n+02f5hYILdwEG3YewLoNG9l6rWFZUqYtyVqXLl3QtGlTGCr37t1DgpkNpFb2GalVd+7dr+tumQyqyKOhyNu5C5eQ4pS3/SIyEhwK4OQ53jeiToxR1rILcz537jySXYtl38DMHPHORXDk2DFtd41hjBqTUEaOHDmCrl27igFSNkgePnz4g3Y2Njbo0aMHfHx8REagkiVLoly5cnpd7CgsLAwjx07AxZeJiCCPiCSHn9TCCqFFmmL32Zv4bcZMxMfHa7OrJiVLyrStWbMmatSoAUdHRxgqm7fvQrjT+wrZqS6FcOPmLeFZZPRLHg1B3sLDwxEdnwCpjVO+zkNhqq9eveIxTo0Ym6xlByXgSHL0E8Y7RcS5FsP+Q0e12i+GMXaMPkwrNjZWLNiLFCmS8Ro9puxSNFHZ2dnlaCV58OAB6tWrl6NXQj6nPSkxtra2GY81yZkzZ7BkxWqEe1VGiksh5T5kZiGUliuhd/DT8JH4YdA3KFWqlEb7aYqylB+500dZyw66lgePnyKtePn3L5qZI9alGPbsO4Ae3btqvU+mhCZkTNeydvzEScQ6KjmW5YREgkSngjh3/jyaNG6sjq6ZNJqUNX0a2w6fOI0Yh5zlT2rtiLjkdLG3xNs7b0kWGIYxMWUkMTFR/Cs/WMpiPRMSEhQOohTGtHDhQvj6+goLjyLITb1x48aM50WLFsW0adPg6ekJTREZGYmpM2bi2v3nCC3SLCNERmkkEiR4lsErey9M+3MhWjSsh2+++gLW1taa6rLJyVJe5S4ndCFrObF2w0ZEZRNbHe9eEoeO7sO3X38JS0tLnfTNFNCEjOlS1ihM9iDVdvBtqJbzkVK8a99B9Pr4Y659o8eypi9jG2Vxe/rkCdJKVMi1bby9b8Z+GIZhDFQZodR4ZNUnl/yAAQPw8uVLsTmucOHCav8uCr0iyHrj5PTO9S9z3cssL9kpIkuWLBH9pP0jZjlkdencuTPatWuX8Vw26YWEhIhrUifUrxMnT+LfNesR4VoaSYUaq14UTI50O3cEF22JrRdv4Ngnn2LQV1+IsDTmPaSM5kWW8iJ3uaFNWcsN8hoePHQYScXf9ycDC2sk2Hhh+44dqFO7tlb7ZUzylhuakDFdyhpVvI4xd4LUKn8LWxmU1jwsOB0HDx5EYGCgWs5pTOiLrOnL2EbZ14RhL6dQ5/+TYO2GU+cuonr16lrpmynJGmOaWOgiJnPevHmoUqUKLl26JJQRykyxYcMGjB49Wu3fR9mj3N3d8eTJE7EXhKDH9Fp21hxa8FNGLQrPIkUkN4sPWX4VWX/VuUmcBuW5fy3C04gERBTOgzdEERRW41MJ8fGFMWPBP6hYOgADPvtU3Dcm77Kkqtwpg7ZkTRkuX76MZEdfUZk4O6KcA7DnwGHUrlVLq/0yJTQhY7qSNQrRWbV2PSJ8FYfE5oVw9/JYsnwlZk6bkqNRidGdrOnL2PbmzRukWim3xyXdxhkvX13jRDAMoya0PjqvXbsWI0aMwODBgzMmB3LJ0sCmKRo1aiTcwBTeRAc9VpTlgxSRu3fvCsVIHxbk5DretmMnho+diBup3ggv1Eh9ioj899i5IjSgBU69SscPQ0fg9OnTPNDmU5Zya0thKeRhoN+Y7jU91raHI6+QVTDaTnHGo3R7T7x88TJTHDijW3nUZ3n7b/MWRNn6QmrjrNbzpjt4IizdDnv2cYa3/GIssqaI6OhoJJspF6ostbRFbCwn6WAYg/WMUGhW1g3TlKecBi1NQRlAKLvPDz/8kJEfndzCxKJFi8S/AwcOFN6H/fv3CwsNpfWVQe3pfW1D2WBmzZ2Ptym2iAxoLbJhKU16GiRJsZBaOwjvh1JIzJDoWRpvnfyxaP1OHDl+CoO+HghnZ/UuEAwZZWUpt7bEpk2bMsVJ9+7dG2XLlsX48eOh7zx89AhpBXKov0NhFg5ueP78OQICArTZNZNCFXnUV3m7f/8+Dh49hehirTVy/gifqiLrW6UK5VGgQP5SBpsyxiBrOZGUlIQUZZdEZhZISU7WdJcYxmSQSLVs/h45cmTGwPT5559j2bJlCAoKwrp16zBp0iQYC6TY5NUqTD/J3v0HsHHrDoR5V0Oas+oTqCQhCg43NyE2sCuktnlQJqRSWIc/gGv4LXw1oB+qVqkMU8TPL0sVXiOTtbzS/6tvEFyqS45tXF5fwPc9WqBq1apa65eho+/ypm5Zi4qKwrBRY/Hat47Yw6YpQ4t5zBv4h1/B9CmT1BJWZAzou6xpe2yjQo2Lj9xBso9y+4u8727BkoXzNd4vY8AQZI0xMc9Iz549MWPGDDRu3Fi4bdesWSMqtQ4ZMkTbXdHbrCV/zPsLt1+GIzygldgMrBMkEiS5l8BbBx/M+2cVGgYF4dNPemk87pqK6O3Ze0A8rly5IhrUV28MOaMmlDJhSES4BsMoskRPmjodIW6ByisiJFVJsSobWtIcffA2qajIQjhu1AhYWBh9IklGRRKTkiFVNopADIEcxswwBrtnpEKFCsJVS9YOytxEm9fJW8JZnICIiAgMHz0OV8IkCC/YIM+KiP2VNbC/tVU8tru9M199opzqoUVb4OC1J5g0dVpGikdNQHns5/+1EL4lqqBIhfrYvGWrqPLL6B8UWkkW6pywkCYbXNEzRjuQIWrK9Jl4LvFEsmtRrYxtiR6l8TDOCrP/nK/RsGDGMImIiobUXPlQaKlUwnLEMGpCJ+lFKIVv//79MXz4cHzxxReZCimZsiIyevwkPLMriXivwHyl7JWkp0Ly/4WiRKqGTYNm5ojyq4lbsbYY/+tUYdFUN5RGefKU39CgdS+UDKyOwsXKon3vIfjr78W4du2a2r+PyR+eXt4wS4zOsY15QiS755lsFZHps/7A/ViLd2OdFse2GJ8quPYqBvP++psXkkwmnr98jXRr5Y0nZjYOIoyMYRgDVEaOHTum8DBVaHE/YfJveO1SDimu6q+1ohYkErFweJzmghmz/1Rrpq3z589j6rQZaNyhL4qVeV9Eyt3TF10+/wX/rlqHLVu38uJBjyhZPABm8aGKG6SnQ5KWxMkPmA8UkRmz5yAoNA0x3jrYhyaRCMPKhUchmP/3Yh5TGAHJwbOnT5Bu56b0Z+Jt3BF065ZG+8UwpoLWA2d37dqV6TmlCKQMHYUKFULDhuqpvGtoLFu5Gm8svJHioqeKiBzxnoG49+Ik9h04iFYtmufrXJTuceWq1Xjw+Bm69x8OR5cPJwIXN0/0+Go0juxYiSlTf8N3g77lBa4eULpEMThcP4JIBe+bJUbC24cLXTFZPCIz/0BQWBqifarky/ubLyQSRBaojfMPzkD6198Y9PWXXIPExLly5QpS7T1FlixliXMqjF37DqJxo0YZRRoZhjEQZWT69OkfvLZt2zaT3ehKbt7zl64iLrtK1voITeQ+1bFpyzY0adQQVlYqpBvOEpb2+8xZ8AsIFIqIGe1BUICVlTVadh2AW1dOY9z4CUIhKVasWD4ugskvVPjMOjVW4ftmSdHwL8RpVJl30PhOoVk3w9JEqJTOFJEsCsmFx2cxf+EifPvVQFZITFhJXr5qLSI8aqj0OUq6EBZCnv0LqFlTtc8yDJMZvRh927dvjz179sAUOX32LGKcAwADmgilljZIcfDGrTy6qKm41K+Tp6Ji3Tao27xrjoqIPGUr10GbnoMwZ+58PHr0KE/fzagHa2trQJqDASE9DbY2OsoEx+hdCMzsufMRFJKiH4qIvELiVwvnH7zFkmUruMiriUK/fZiVl0ohWjLCfapjyfKVvHeEYfKJXqyAKZ2rqfL42Quk2LjA0Igxc8Sr16/z9Nm/Fy1B5XqtxUZ1VfHyK4S2H3+LefMXiDAvRjcEBwcj1UJxvQaplT1evn6j1T4x+sm/q9fg2vNIRPtW0x9FRF4h8a+NUzceYOv2/GUezM0T/N3gIfj2u8HoP+ALXLx4UWPfxSjP+v824czNh4jxfr9XURWo1k2odzWMnzxV/MYMwxhImNbQoUMzxVfS5u23b9+KQoimiKO9PSSvE2BoWCEFdra2Kn/uyZMnCIuIRrMqea8f4u1XGAWLl8fxEyfQrGnTPJ+HyTv7Dh1FlI3iPSFp9p54eP+M2A/G6X1Nl7PnzuHY+WuILNJM/xQRGRIzhPvXw/Z9+1CiWFEEBqqW4UuZTIG/z5yNhm17o3jZyoiJDMeqZdNFeFCtWrXU+l2M8t66pcv/xclr9xBeqIGQgbyS6lwAr6VpGDl2AkYN+xn+/v5q7SvDmAJaV0batGmT6bmNjY1I7Usx6KZI9SqVcOL6RoS5q28PRNs2rdGuTWvxmAIPNgdFYuv5B2o7P1Vnt415gXLlPlP5o5s2b0GVeq3yveGvSp0W2PbvTDSoXz/P+1aYvHHx0iXcevgUqQEtFTcyM0e0WxnMW7gIw376gePxTZDY2FgsXbEKYYWbKV0pXWeYWwqFZP7fSzBn5nS1jCkU9nXo0GFs37kLzTr3Q6GA0uJ1StTRbcBwbF+7ANdu3ESfT3pxVXgtEhUVhd//+BOPY80QVaiRWkKkU1wK4ZW5NcZN/g39P+2NOrVZyWQYVZBIOVBWI1AMKRV2VMZC8/PwUXjkUE5UCVYHDpf+Ffn4CaooG1u1L9SJTeg91PRMxc/fD1b6M3SdGzduwq37T9Cxz/dqyT5y5tBWxIU9w6BvvxFKrSYwhDoZysqaOrh06TLmL1mG0MJNRYhCjkilcHl5FtWKuosNwlz12vDlTRVZW7lmLXZcf4sEb/V5GjQ9tjm+uYxeDQPRLovRTFVevXqFRYuXwsreFY3afQI7e8dsx8RLJ/fh5oUj6P3Jx6heXfWwVWOWNU2MbVeuXsVfi5ci3LUcktyLQ91IkuPh/uIkKpcJwMB+n2lsXjI0DEHWGBNQRnbv3p0nr4kho8og+uLFC4yfPA3BhZuIiuf6PGGbxQbDL/g8pk+ZpFT4DYnX1atX8d/GzXD1LoTG7T6BhaV6PBl07ksn94rJvGOH9qhXrx4sLS1haoOoNpQROv/a9f/hyJmLCCvYIHdFRIZUCqe3V+BnFo2fhgwyWQ+oscibKrL25beD8apIS8DC2mCUEUlSLAJCz+KP33/L85i0d98+7N13AI3afoKipSrk+pnI8BAc3PIPvNxd8MWAfrDNQ/irMcqaOse2+Ph4LF2xEpeD7iOsQB1IbZygMaTpsAsJglvsU3z39UCULVsWpo4hyBqjW7Riqrxw4YLJKSOqQDGm3339Beb8tRihhRprdqDMB2Yxb+H95ixGjxqeqyISGhqKU6dO49jxE3D18EX9dn3g6x+Q63fMmzQIKcnvKrxbWllj0Jh5CtuSd6Va/Xcb4S8c34XNW7ahevVqaNigvqhbw7nf1cO1a9ew6J8ViLDxQQyFZqkSciORiJoScVEvMGrCZDRv3ACdO3Z4l42LMVoSExORSmYuNSoi2ghBJSU7OiY6b5+VSrF06TK8ColEr2/Gw9pGOaWCail17TdUeEnGT5yE0SNH8D4rNXL12jUsXPwPIhwDEB/QQun9IfZX1vxf8ZVCamaJuMq9lPtCiRnivcoj0cEfM+YvQfUKZfD5p721pmQyjCGiFWVk3Lhx2vgag6ZihQr44dsvMWf+3wjxq410B688n0sqCjdJIUlPg1Sinp/YMuIJvMJvYMyo4ShQIPv6EWFhYTh37hxOnzmHxKRklKxQC537DYWjk6vS30OKiEwZURYnVw807dgXSUkJuHvtPBb/sxIJcdGoWaM6ateuhYIFC6p0PuZ9ljvKv/86KhHhXrWRbqf875iVNGd/BDt4Y/ulIBw++jM6d2iHZk2bqN2TxegHwhCgAaf7rt17sHvnDo15RvLTZ9ofQopIu16DVN4j9c6w0kooMAv++hvDhv6c534w770hi5Yux7V7jxFWoAGkNqoVyyVFROaFyws0XoYWa4VjT4Jw/Zfh+PbLAShfvnyez8cwxgwHcesR5QMDMW7kUEyZPhMhSaXzHNNKFhxJQhQcbm5CfJl8FlOUSuEQfB0FpGEYNWk8XF0zL0gpve7p06dx5NhxxMTEoUT5GmjceQDcPfNffVvVCEJra1tUqNFQHHExUbh38yL+WrwMKYnxqF+vLho1aggnJ/30OukLdM+pfszqDZvwJiIW4e7lkVZETZXUzS0R41MJse4lsfrQZWzdsQvt2rRCi2ZN2VNiZNDvaWNlKWLopVbq25ytCUOLPGaJkXB3d1f5c3Fxcdi2Ywc+/mpsvpI1BFZrgHs3zglvZMWKFfN8HlPn9u3bmDN/IcKdiiGhKHlDdOQll3lJHAti1t/LUbtyOXz+aR82wjCMrjewU4aVNWvWICgoSKT9lP/6ZcuWwVjIT6wrFQWcNnM2nsZbIcqnap6yfciUkdjArpDaqmYRyiA1GW4vT6FyMT988+UXH2SYOXLkCLZs3YaipSohsFpDePrm3wMxe8wXGZ4R2lvy469L8n1OSqUZdOUkgi6dQO1aNfFR925Kb6Y2lbhqsZn20iWs27gF4UlAhFtZtSVUUIQkJR4OobdhF/MczZs0QtvWreDgoORelHxA9+ru3bsIunVbXLcMGxtrVK5USYT46Sr7l77LmyqytmPXbqw7eg3RfurdmK2WsU0Bbi9OYUDnpqhfr55KIWmz//gTvgEVUKl2s3z3IeztS2xfPQdDf/5JoRfaFGQtL2MbrSc2bdmG3YeOib0h6bau+rM/KT0djsHX4Z0eipFDf4KnpydMBUOQNcbElJE5c+aI4kBt27bF3Llz8d1332H79u0i3zq9Zizkd4GYlpaGZf+uwqnLQe82DFvaaHXCliRGwePZcXTt0BptWrX8YP/FlStXsGHzdrTv9R3sHNTnbbhzahNatXqXMpa+M8XaCy9C4tRy7tSUZBzZuRqFfVzw0UfdjWYQzY+s0WKcPFvrNm1BrMQBEe5lkW6numU4X6QmwS7sLhwiH6Fe7Zro2rmjWjxYdG001lCdh5cvX+LZ85eizg2l9ixQuDgKFC0LCzkLZUJ8LJ7dv47Qt6/g7eODokUKo6B/ASEDtPGe4vg1vQ9J3+VNFVmjOho/DRuJp06BSHPy03tlhEJRS6Q9w9RJ45VSRskrfOLkSezYsQuB1Rujar0Px8m88uLJPRzYvBQ1qldD61Yt4eamenVwQ5c1VeWN/t7nLvgblx6+RkSBOoC5hV4mS7CIfA6v0CuiJgkZPkwBQ5A1xsTCtG7evImZM2eKxQYN+JTOsGjRovj999+NShnJL+bm5hjweV8UDziOf9dtRGihhirHvOb5u6Nfw/Ptefzw3dcKM4HQwiwhLgYhb1+gkH0ZtU3Ce/buxfbt29TqGZERFR6CiNA3qFQ29430xg7ZIC5fvoxlq9Yg2swZkV51tCZfH2BhjXjvCoj3KIs9d+/h5NCRaNywHrp17pRrakyySlPRVKoIT8ebtyF4G/xWLGJosUj7lVw9vOHi4Qf3guVRqmZbODq7CXnNLllC1bot3ikxIa8R/OY5gh6+xKnzVxER+lYoK/YODvDy8oKXpxd8vD3FY29vb2Hl5NTFmaH7MeKXHzFm4mQEm9dFur0H9BUa82hP3PBcFBFaGJNX//TZc7gVdAvFylZGl89/EfvW1JWYg/AvUhK9B03E9QtHMWnyVHi4u6NunVqoUqUKh5oqYPE/y3HhSSiiCtbX3wKbpKS7FMQbS1v8+tsMTJ4w1qQ8JAyjCK3PnmTxl4ViUFxxQkKCiNEl6yXzIY0aNoC3lydm/rkAIQU0P6FbRj6DT8R1jBkzEr6+ivcKFC9eHIMHfYN16//DsZ2rUapCLRQrWwXuXn75UkxoopYtlq2s8p+jPSYqHA9uX8WDG+eQlpKIrl06aT2fv75B3oI/F/yNx8HRiPCula9QhsxZZ97F9CuddSYr5hZI8CyLBLcS2HntNk6cHIqvBnyOypUrC3mgMeLOnTt49PgJnr94gbDQMKGwurp7wcnNE44unnAuUBaFyjeCs5snrP4vS6omS6DFqLt3AXHIQ31IjI9FZEQIosJC8PhtCK7fuYCo8GBERoSK9Y+Ptw8KFfRH8eLFUKZMGTg760jB0xPIozRq6E+YTPvgfGpqPPQvr5Zq77CrGDdq+Ad74gjypJHifvHSFTx9+hT+RUuiWLnq+Kzlp7CwsNRYYg4aC6vWbSkKvL55+RjXb1zAth27YG9nh6pVK6Na1aoiEyNnDXxn5Dx77TaiijbXa0VEBs3jIR6VxDg8adxoXXeHYUxPGaHB8/79+yhVqhSKFSsm9o9QyjsPD/21mukaWtSMHvZuQg8uUB/pdup32csmZb+om5g0YVy2k3JWAgICMHLEMJFF6+zZczi561+EhYejULEy8A8oi0LFysJexRCu3CyGuZGclIgXj+/i+cNbePYwCObmElStUgVfDuhrMi7xnKDFlEiQ4BqIlMJV1TJx5zfrzAeYWyKOPCXORfDn0lVo2eAhgm7eRGo6hFx5+QeieNVWwhqtrr0dykSr0qLP1t5RHNmlqU5NTREelJA3z3H2yl2s27AJ5QPLoX+/z2DKFClSBBPHjMSvv01HcHJJJLqXgF4glcIu9BZ8kl5i7ISxmTauUyamk6dO4cTJU4iNjUdAmcooW7M1mnYvlm+ZUzUymuSO5I2OBq17CBl7dOcq/l6yAnExkahRozqaNG4kPHSmyrbd+xDhUUHptL36QKprYbx6dEt4cdk7wpg6WldG+vXrlzGYf/rpp1i8eLHwjnzxxRfa7orBTejDfhyCqTPnIKRIc7VmqCHM4kKFdXDChLFKKSLy0CTetm0bcdBvSdmYbtwMwtbjO5GWLoV/QGkUJOUkoAysbdXbb9oH8vLZA6F8vHh4S4TSlCpdClUDy6Fvz/ZwcXFR6/cZMhTSNHXGLLzxraNBD5v6tqBRvZ3Qos2x5/hBOJmlonCJQFFTRh2JEojWrVpl2Z9kn6/9SWQl9/TxF95BOztHhIe+RmxcrFr6auiQl3Xa5EmYPmsOHr88g0if6vmO6c8XlJzj1VmU8XPB999NzBQOeO78eaxavQYlA2ugUYd+4vfUJyjskPan0EGhsnduXMC0GbNQoXw59P20j0l6SqiuVbqalVxN17Qh0m2cRd9ZGWFMHa1vYP/hhx/QoEEDceQlhWJeoI2UK1aswMmTJ8Xz+vXro2/fvmJfRn7a6qIq9ukzZ7F4zSaxSMvJCqTSJs/UJHg+2osxQ38U+3fUCWUGE8rJjSAE3boFG1t7FC5ZAcXKVBGLyrxMnFERoXhw6zKe3ruO8JDXKFGihJiIy5UrJ2L4NbnxTp2ypG1Zo1CTOWt3I9yvFtRJD+8QjU7aZrHBqCx5iiYN6uLgoSNISEpG2Sr1UaZibdjY2etN5rbIsGAEXT6Bu9fPoUjhwmjZopnYc6WKjKuy0dMQxzXaj7Nx81bsPXz8XbajvHh509NEpXQqUKhSAU45efJ4dRZd2rdBm9Yfbjr/+ZehaNDuUxQKKA1DSMxBJCbEYfnskZg0cbzSC1tVNxXrs7zRxvXDryRIdVfffkBNbWDPQJoOr/s7MHvaZLXuA/rqq6+QlJSUEQq/cOFC6BrewM7khtZNU927d8fx48exceNGEapFSgll0spto2p+2Lx5s4g1nzVrlng+ZcoUbNmyBd26dctXW11Qp3YtXL1+A8efBCHOSz0FlFzfXETXDm3VrogQNMjS70sHQZuNr1y9irMH1iEsLBwlAquhfLWGIsY/JxLj4xB05RTuXjsNM0hRvXpVNP20p9bTsKpTlrQta/RbmCfHvivspkbrqaYL0ZknRcO9gFuGEePNmzc4cvQY1vw1Hl6+hVEisAaKlCov6sxom5joCDy4dQX3b5xFWnIiGjdqgE+7T9BKBW1DHNfob/Wjbl1QqUIgZs9dgHCqiu1RRjV5NDPPWxYtaTrsg2/AM+k1fhmhOJNR/36fY8nSZXBx90GJ8jVRpGSgMKLkh4OHj2D3nj3Ck2tj54DB4xYgv6SlpeLl0wd4GHRRhG21a9dWoxZ2fZa3bp074OrEKQhx8oXU0tYgatqQLFatVDFPighFIERGRor6NvSYDgotpINeo725BClyQpZdnMReI3t7exEWT4ednZ3Yv0vRA1nT9jOM0SsjderUEQdtCjx16hT27duHpUuXokaNGiLNryagehhklZGFH3Xp0gUrV67MdmBUpW1OkGUoO4sOWcXks+7kZPVR1LZPr54IGjUWSYkFRSiLzCKdjveLcnNIxcRP/0rxvpaCjLT/tzWPeoECdlI0b9pEqf7SdeXkTJMv5pRdW0pR2bRJE3HQAHr6zBnsWPUHXD39UKtJJ7i4e31g8btwfBce3b6CunXr4qfvvxMeNdl5adCVDbwyqL8yaye9J19LIiuqtFW3LGlb1mjxVaqgN5LfXkasd6VMC8AP5UfxfcjaVmJhBUk6PZcCZpYffDZNyfNmbWuGdFjEBsMz8ha6DxqZcY30+3fr2gU9PuouvG5nzp7D2oObYOfoDL9CJeBbsBh8/IuKRV/G98ptNE5PeyeXVO2a7hEtEK2sbZCWmqKwrbhuqVQkRHj9/BHevHiAl4/viT1JVSpXxlcDPhM1IWTyk93voaqsGfO4VrJkScycNgULF/+Dm48OI8KvFqRWHy4iVZHLnGRNkhgDt9dnUb18KfTp9dUHRTblxypKzjFl8iTcu3cP585fxPrDW2BpbQP/IqXhW/idfNnm4JHLTn6+HjFbKA/k1XV29chV1rK9tvR0vH35BK+e3sOrJ3eFV7ho0QBUq1oZA/p0FQY92X1Xt6zpu7zRntO+vXpgxfpNCC/YKJMs5XVso0QcFgmRsL+1FQll2mb7uTyNbVRIOPQWCltEoVnj9pg4caKwD9FMTb8/PU6n30wqRXo6vSFFWnpaxr2gn9XSygb2js6wtrEXoc9W1rawtLIVcmpmbp4hR+YWFnAuUAZxcTGICItH8usYpCQnIDnx3UHza2xMpBgDzeieWlrC3NwC5uZmkNB/ZhLxuoTWEmT0k9D/Etja2ojfV5ZyWhPyxpgWOgvapSwzbdq0QenSpbFu3TrhztWEMkJFFmmDNe25kEGPKU6TrAhkHchLWxk0OMgPlmKTq62tqJ1CFtysFCxYEK1bvwtpIVatWiUGGUVx1u3bt894TveJ4v6JSuXLohIiKDeSeB6RZoUTCe+z/zRyi4Jdw4b/f/9dGxnRaZY4muAPpKfC7e1lVGhQW7jUs4MsJ716vc+OtHPnTuE6zw6aDGkfkIy9e/cqzJJGgxftHxJx+y1bimt7dGV/tm3tzYFZM3/PUHQOHDiAx48fQxGff/55RluSK1pUKKJPnz7i9yLOnj0rFrfyjBs3TiOyRIO1tmVt9erVcHN2QENhVH6WqW1omg1OJ7zPntbM/jmsJdlPKFllrWbturAzk5fhpx/K2v+pb/sKTubZL1Tj0y1wMP7/+0HSU9HA6gmcfMwBn/LYseOd5yWrrJUvX14c9L6QNWkswp9dE8d7JPAtVRveBYqIDEUPrh5BVMgLVK9aOdM5Lx9cJf6t3upz8S/F49+9dBAp8ZEf9NXREihdslgmWTt69Gi+ZC2rvBn7uEZWWjIukDEqLS1YKVlrbPcyi6xBOVkjvdSjpFhuUtIUVca1KpUrirTz9HvdvnMTr+6eg51d9tZ3M3MLVG3eJ+O5TNYUIZM14tH1E4h4+0Rh25tBt1C4SBGULV0K/m7l8erVuzBnKuBJh6ZkzZDkrVZFSkUfrLaxTal5VJWxLS0Zrq/Po1Zxb1haFMSxY8c+yFpJ9+H8+QviHtD6nsKPFXlPSEG9eTNIKFEUAke1kerVrZupTeTzGxmP79y8JeYeUhsKFyoIb39KepB94oNz584hLS0d6dJ0lChe/IMECfTb5GUeZRi9UUbCw8Nx4sQJEa5Fj2vWrKkxYZUt3uUHQJoECbLMy7+uSlsZ5HqmkDMZFOo0bdo0hf2hRZT84JNTPDm5TuXbqjscyTEkCG1bNhMWHZpAsoMGOPk+yHs+skL9k2+bk+tXZIiRa0spQGNiYhS2lw+pkA16iqBzyb47t7Y0wMp+4+x+X03JksxypS+ypjdI02EV/giu4bfhWq2SsCbnX9aAZ0EncXDrP7C1c0CRwkXk7JkfcnjHv3j5+C4szM1RokQxnciaKY1r5KWgRar6UexlUHVcCwwMFAexfPlykZUuO8iiHRb8Cm6evir/vcm8JYpYvWplhqxt3boVr1690oqsGbq85Qs1npeiEDyCr6DXR12FoUPR70eG2v3792U8z0nebKytsXnTf2I+IWVs7dq1ORrq1q9dneFR+u+//7JVUmWQjMnL27Vr8gYezcobY3poXRkhlyRZccia2bVrV1SrVk2j8YqyvSg02cmsC7KJL+viQZW2Mjp37ox27dp9MCh26NBBoXtZ3lvQu3dvhX3P2rZHjx6Z3ifr0+iJkxFSpAWkFpnv4ZE4P0iS4iC1ts92kydtcHeOe472bb4TE7Oi8ICsfWjVqlWOoQTybZs2bap0W9rgWK9ePaXa0v4TUmAVQRY42e9A8kWFwhRB4YK0yZ6oWLGikEttyJLMja1LWaPPUCz7rj17EW/nC4mb47tNwRTjHqc4Y1XWX/RIfOZ6HDlxIkHBRsb0NFhGPIZX2E4Eli2FPt+PESEe6pI12WKTrN80qVL4TVh4BIqWqgQzM3MkJ8fj0e2rYh9bvWoVUa5vD2E9zy0sUVOyZorjGoV3rF63AacuXUd4gXoi1CavsiZJisGthzfQolFddO7Q/gNDjrrHNeo7LRiDgm7h+M4VIp6fknSUrlgLxSo2Unje+LgY3L56BvdvnkdqUgICA8uJdNAUxpb1t9GVrBmivNHvsWv3Xuw5eAgRboGA6/t9cqqNbe89H3kd22gedgm+ijL2EgweM1xs5s5tXMnrPNq4cWM0aqRY3uS9f7qaRxlGL5SRqlWrYsiQIVorBkYLCooxf/LkibBiEvSYXsuqwavSVn6Rk51VjawPigYQ+ddzq9qcU1uyRrRv1QL/HbuKyAKZMySlmVkCtgrS2kql8Hh9VhSUU0YRlO9DbtlQ9KGtfHtahOTmUVK2rbplSdeyRs/bt22DVi2aiw3hW7bvRLyVKyLdSiPNTvlMd/Jx0yq3TU2CXdg9OEQ+QLUqVdBtyBilN+HmRX4otpwmdzoo/EMW3kKf/6JPtwzrnuwzupI1UxzXROhm3z4oXfIslv67GqH+9ZCeRQ6VkTXzmLfweH0G3331hVgYaWP8ob6TAkFH586dhKf5/PnzOLRjBSQW1qjX8iOxj0lGfGw0zhzagqcPboqwmiHffpljkVldypohyhs979K5Ixo2qIfFy1bg3uN9CPOqgnQHr/yNV6q0TUsR0QeOsc/Qp1cP1K1TRyzulRlXjHkeZRi9UEYo9lbbkKWA3MC0P4Wgx7QYyW9bfaBd2zY4cfosYqJeIM1ZOSuObehtVChZJMeJmtG8LOmLrNEioEXzZmjWtAkuXLyIDZu3ISI4DeGuZZDm5KeRisaUmtUp/DZsY16iaeOGaNOqv1rTWyoDLZRkiyVDxFjHNcoY6OPthd9+n41gFau2W0Y+g3f4dYwePUIkFNAVtCBv0qSJOCgUZvWalYiOjsp4nxZrVJdpyFd9c1Xc9AVDlDdSgIb//KPI7LXonxUIi7BChFflDA+wRpCmwzrsAZzDbqF5k4bo3PG7DxImMAyj4zojuoBcohR3Sdm7suY8X7RokXht4MCBubbVhzojity0oydOQXBAK8Ai50HPLCESvq9OYNb0qRzbmcc6I+qSJX2WNdqIvXbjFjx99RYRrmVFtWC1VGtPjIJLWBDsk8LRuUM7NGrYgNNK5qPOiLGPaxMm/4Y3XtWVUkhIEfGLuomJY0dnZPlh1FtnxJDljUJjT546LUIBYxwKIsYzEDBXvFcoL5hHv4Zb8GWUL10cn/XupXIBYWOF64wwuWESyogu0OakTezZtx9r951CRMH6ihulp8Pj0V78/E1/kaGDMY5BVJOy9uLFC6xa9x/uPX6GcI8K77xveVBKyBPiEnIdTmlR6NmtC+rUqc2ufAOUN22Pa6SQjJ00BcH+DZBu65pjIUO/4POYPGEsKyJGImuakjcqCLh523YcPHIc4R4V1WJokSTHw/XtJXhZp+Gbgf01UrPLkDEEWWN0CysjRjJp0884duJkBKV5I8U1+4HQ/u01NCnhhoH936eTZAx/ENWGrD179gxLlq/E87BYhPlUz6hvkyvpabAPCYJzzBN8/FFXNKhfn5UQA5Y3bY9rMi/db7PnIUR4fj/0oklSEuD5eB8mjBoOf3/lNxybOvoua5qWt+DgYMz/ewmehscj3KcGpFZ5iBSgekXhD+AadkuMb40bNTSMrIVaxhBkjdEtvCowEmgA/H7Q13ANviY2BWfFLCECbvEv0Lf3+9z6DKMslFp54thR+KZPN/i+OAqbkDvvKrnngFl8BDwf7kGLMp6YM3M6GjVsyIoIozK0KbxTmxZwfXPxwzelUri9Oos+H3/EigijEl5eXhg/egT6dWkFryf7RZifSqQmwu3ZUVRxisPMaZPRpHEjVkQYJo/wysCIoM16ndq3gTMpJFkn7DcXRfYs3kjH5Ifq1aqK/UYVnRLg8vKMCP3LDprYfV6dwNDBX4kMSbJ0nwyT10QdXpZJIlOWPOaRz1HYwx4N6+cQnsowCiDloUH9epj26wQUS34ExzdXcjWyEGbx4fB8tA+92zfBiF9+0nryDYYxNlgZMTJat2wBp+QQSBLf5fwmzKNfopCnMypUqKDTvjHGAaW/HTn0JzQMLAzXFyfEpk35wyrkDgpE38Jvv07IyKbDMPmBPGoD+/WFW9j1zEaWsBsY+Hlftkgz+TbkTZk4DtX8bOD68rTIiKUIUoi9Xp7AyJ+GoHnTpix7DKMGWBkxMihNZI8uneAcfjvjNbfwW+j7SU+d9osxvsVh/88+Rfv6VVHXOTLT0aCAhQjp4kwyjLrDtdztrWAWHyaem8e8RhF/X52m8GWMB0px/sPgQahZ0g8ur85n6yEh2fN6cxYTRo9A8eLFddJPhjFGDCPBOaMSdevWxcq1G0TRJbPkOLjYWiAgIEDX3WKMDLIIdu/SSdfdYEyINi2a4tXuc4i2cxdJEdr1el+1m2HUMaZ9/UV/hP02AzfC7iPRo+T7N1OT4f7iJIb/8gNvyGYYNcOeESP1jlSqVBHWr67A9vVVNGvcQNddYhiGyTfVq1WDTcQjeN7ZApu4tyhfvryuu8QYodf3x8HfwjXiNiTJcRmvuwRfQac2LdmwxzAagD0jRkqXDu2A7btgYW6GenXq6Lo7DMMwaqlsvmTRwoznHK/PaErOenbvipXr/oO5jb14zc5cirZtWuu6awxjlHCdESPKx8+oH0Nwx7OsGQ/6Lm8sa8aDvsuaPshbZGSkqOFF2NnZcTZKI5Y1RrewZ4RhGIZhGCYLLi4uuu4Cw5gEvGeEYRiGYRiGYRidwMoIwzAMwzAMwzA6gZURhmEYhmEYhmF0AisjDMMwDMMwDMPoBFZGGIZhGIZhGIbRCayMMAzDMAzDMAyjE1gZYRiGYRiGYRhGJ7AywjAMwzAMwzCMTmBlhGEYhmEYhmEYncDKCMMwDMMwDMMwOoGVEYZhGIZhGIZhdAIrIwzDMAzDMAzD6AQLGDl37tzB0qVL8fr1a/j6+uKLL75AyZIls217+fJlbNu2Dc+ePYO5uTnKlCmDzz77DO7u7lrvN2PYspRb+4iICCxatAiPHj0Sj6dPn44iRYpo8WoYU5JHljcmP7CsMQyjSYzaMxIbG4tp06ahZcuWWLZsmfj3t99+Q1xcXLbt4+Pj0bFjR/z111+YN28ebG1tMXv2bK33mzF8WcqtvUQiQaVKlfDLL79o+UoYU5RHljcmr7CsMQyjaYzaM3L+/Hm4ubmhWbNm4jn9u3v3bvF648aNP2hfr169TM/btm2LoUOHIi0tTXhKsiMlJUUc8gMxKTEWFkZ9a00OVWUpt/YuLi5iUlcFljUmr/KoqryxrDHakjWC5Y1hTBuj/kt/+vQpChcunOk1chfT68pw69Yt+Pv7K1REiC1btmDjxo0Zz+vWrYshQ4bA1dU1Hz1nDF2W8it72cGyxmhSvuRhWWO0JWsEyxvDmDYGq4yQm5j2eCiCwqwSExNhb2+f6XU7Ozvxem48fvwY69evx48//phju86dO6Ndu3aZXiMLj6WlJYyZhIQEjB8/XhxkwTJkNCFL+ZE9RbCsGb6s6cPYpgwsayxr2pI1U5U3U5M1hjFKZWTw4MFITU1V+L6DgwNsbGxEvGvWfSFOTk45nps2sE+ZMgX9+vVDhQoVcmxLg6UxD5iKkEqlQmGjfw0dTchSXmUvJ1jWDF/WdD22KQvLGsuatmTNVOXN1GSNYYxyAztZZmgwVHSYmZkJ1/KTJ08yfY5cy4UKFcpREZk0aRJ69eqFBg0aaOFKGGOUpbzIHsNocmxjmKywrDEMow8YrDKiDDVq1EB4eDgOHz4srD/0L6UapNez4/nz50IR6dGjR7Yb8xjTRVVZUqZ9cnKyOAhqQ4/T09O1dk2M6cgjwfLG5AWWNYZhNI1EauQ+QsqPvmTJEpEf3c/PDwMGDECpUqXEe6Ghofjhhx9E+l4PDw8sWLAAx44dg5WVVaZzyN5nMsfz0qZDivU1Ffe6KrKUW3vio48++uA7xo0bh3LlymnxqvQfU5Q1Tcgjy1vusKxlD8ua+mFZYxgTUkYYhmEYhmEYhtFPjDpMi2EYhmEYhmEY/YWVEYZhGIZhGIZhdAIrIwzDMAzDMAzD6ARWRhiGYRiGYRiG0QmsjDAMwzAMwzAMoxNYGWEYhmEYhmEYRiewMsIwDMMwDMMwjE5gZYRhGIZhGIZhGJ3AygjDMAzDMAzDMDqBlRGGYRiGYRiGYXQCKyNGyOrVq1GnTh1dd4PRU4xZPk6cOAF/f39dd8NkMGZZMkWePXsGBwcHREVFwZhgOWUY/YaVEQPn6NGjcHFxyfTaJ598gtOnT8NQJ8PPPvsMfn5+cHR0RPHixfHdd9/h9evX4v1GjRrB2tpavOfs7IzAwED89NNPCAkJyTjHixcvxMTj7u4u2lSqVAlbtmyBKWJM8jF+/Hh06tTpg9dJJv744w/xuH79+uL3z8t90TQSiQRXr17NsR9Tp05FQEAAnJyc4OPjI/4WIiMjoQ8YmyxZWFiIhTcdBQsWxNixYyGVSpX6vDrlZ9myZahWrZroh7e3Nxo2bIj//vtPqc+SfHz//fdQF4UKFUJsbKwYNw0VY5JTdc2J8uzfv1+MRfJy8+TJE/Ga7O+Bjvbt22e6p7L36XsKFy6MESNGID09PdO5Hzx4gO7du8PNzQ329vaoWrUq1q9fr7F7wxgPrIwwejXoVq9eHZaWlmLiiI6OxqlTp+Dr64tjx45ltJs2bRpiYmLEIm3Dhg14+fKlGPTevn0r3nd1dcXy5cvFYEwWvgULFqB37954/PixDq+OYXKnW7duuHLlipD9e/fuITk5GT///LOuu2WUtGvXTiy86Th8+DCWLFmCNWvWaLUPw4cPF0rQuHHjxPj16tUrTJw40WSNJ4xm5kQZcXFxGDx4sEIvERlyZH8TO3bsyPQeKTr0On3P3r17xRxLh4ynT5+iVq1aom+3b99GWFgYRo0aha+//hrz589X+71hjAwpo3NmzpwpLV68uNTBwUEaEBAgnTt3bsZ7jx8/JlOd9N9//5UWK1ZM6uzsLO3bt680OTlZGhoaKrWxsRHv29vbi+P48ePSZcuWSStWrJhxjufPn0ubNWsmdXR0lFapUkU6efJkaeHChTPej4mJkX777bfSggULSj09PaV9+vSRRkZG5vr96uazzz6TNm3aNMc2DRs2lM6ePTvTaykpKdJy5cpJf/nllw/ap6enS8+cOSO1traWHj58WGqIsHy8Y9y4cdKOHTvmKBNHjhwRfZCxatWqjHvn5+cnnThxosL7QqxcuVJaunRpcY66detKL126lOl7hg8fLm3RooU4X+XKlaXXr19X6j4R9H1XrlzJ1Pes/ZUnKipK+sknn0gbNGggVRcsS4plqXv37tIRI0ZkPH/79q20V69eUh8fH6mvr690yJAh0sTERIX34unTp+LaPTw8pC4uLtI2bdqIa1LEw4cPpebm5hmylx05nXPOnDlSCwsLqaWlpehD2bJlxet0v8aMGSN+Xzc3N2n79u2lL1++zDgn9fuvv/4SYyb9TvR+1t8gIiJCPKf7P2DAAGmPHj2EzJQsWVLIrKZhOdXMnEgyPGHCBNFfeiwj6++elezGqW7dukm/+eabjOd0zuz6SveJ7nN0dHQuV8uYMuwZ0QPI5UmWObJ6kHXul19+EdYPefbs2SMsprdu3cKhQ4dEDCyFIdHrMosFHRSmkpVevXqJ7yArydq1a7F06dJM7/fr1w/h4eG4fv268B6kpKRg0KBBuX6/IshFruioUKGCws/t27cPH3/8MVSFwi0ofEfeUkTQd5H7unbt2qhbt26298YQYPnIG2QFpPAGuh6y5gUFBaFVq1YK78vx48eFFe/vv/8WXjXyUlB7+fj5lStXYvr06YiIiBChNRQuocp9UgayzlOYFvWPLOT0e6sLlqXsIUvuyZMnxThB0Jq9Q4cOIlTu4cOHuHHjBq5du4Zff/1V4b2gkJUff/wRz58/F1ZiOzs7fPHFFwq/8+DBg8KKnNO4lNM5ycJN4UfffPON6APJN0HWaPpN6XoolKdkyZLo2bNnpvOS9ZzkgCzvZA2fPXu2wj5QmM1XX30lrO59+vQRf1OahuVU/XPiuXPnhMyRN04RFOJFMk+yf+fOHYXt6O+BxkuSLfm+0n3NSo8ePcRYfObMGZWvgzEhdK0NMR9CFrtff/01k8Xi9u3bGe+TpWrQoEEKLRbyVqBnz56Jz4eEhGS8P3369AwrUHBwsNTMzEwaHh6e8f69e/eEtS01NTXX71cnZOXbs2ePylYgYsGCBcKSlpWkpCTpjh07pDNmzBBeEmPAVOWDrNkkI3Q98gdZl7PzjMTGxkptbW2lCxcuFF4GebK7L9Tvr776KtNrZAlevXp1huwNGzYs472TJ08Ky60y94mg+0Tt5ftOlltFnhGyio8dO1YaFBQk1RQsS87iN6Hv7dy5sxgviPPnzwuvQlpaWsZn9u/fL6z0iu5FVsgLRh5Z+XPIQ/e9Zs2aKvU76zmzWrhpjCOZunr1asZrCQkJ4r7T70PQtcqPs9SPdu3aKfSMkFdExosXL8T75IHQJqYqp+qaE8lrU758eemxY8eylRvyBJ07d060o9/+xx9/lPr7+2eMm3RP6Zrpvso8T+S1kf295NZXLy8v4aVmGEWwZ0QPIItKlSpVxKYvspTs3r0boaGhmdqQtUIGbQwjS68yUAyyjY0NPDw8Mm1SlN+4Rta3okWLZlhqKEbVzMwMb968yff3qwL1kWJd8wJ9ju5fVqysrERs+JEjR3K0XOkzLB/vadu2rbDQyh/16tXLti31g+Ket23bJjYoUzuSA0WQhbhIkSKZXqPrlt8Qn/U6yfKqyn2ibF/yfd+5c6fC/tDvQLJLVkp1wbL0oSzR+Sm+neLy+/btm9FXek92n+ggT1nWGHx5yJtGlmGSNfJsNWjQAElJSeL8sixVsoOeKzPe5XTO7KDfkqzQ1E7Wb7qfNA6SdyUv9zhrW0JTv4kMllP1zom0p6RGjRpCLrKDZJLep78But7ff/9deIPkN/2Tt4n+JmjMW7RokfC8JSQkZOor3dus0Hnot/P09MzTdTCmASsjOoYmJZoAKfQjODhY/LG3adNG6awuNEDmBGXgSExMzDSQ03fKoEmOzkGDiPwiiT5ToECBPF2T/KSb9ShXrpzCz7Vs2TJPmTdSU1PFgpOyiiiCBsT79+/D0GD5yB9NmzbNWMhQlhcKXaCFRnb3hVIC00JEHnquTKpgTdwnmdxSH+jf/MKypBhatFEIkkw5pL56eXll6ieF68mUz+zuBWUXio+Px+XLl0V4EYWxEHR/ZVmqZAc9b9asmQijyhp+pOw5s+sHhSlRKBeF5Mj3nRaNhpLaluVU/XMihWdRhjZSGOhYt26dCEclBSQ7KHMWHdlhbm4uQgXLli0rstLJaN68uQh5ywr1n2SSwqUZRhGsjOgYmphokKWJjwZAWjhR6j1loVSQZJGhQTs7aGClOOiRI0eKCYkW5GTVkLfu0AKN4mFlgzNZf/KTzUV+0s16yOKas2PChAki9SnFJ9PkQPeFLINk1VE0IFNcK01ctFCg2GqC4mQpPpUyEdFBGT/IIk6DpaHB8pF3yIpN/aTrpxhqsizTv4ruC2VcI4ssLQ5pMp87d66wmNNCKDfUdZ8WLlyY0adHjx6J+O4mTZoIi2V+YVlSDI0f9NuXL19ePCdLOF3P6NGjxTXTfaM9G7RPQNG9IGWBFl1kWSa5ofEsJ4oVKyZSsJLnY9euXULpSEtLExZnkkVlzkn9IDmRV05o/KTzyjwh9DlDSq/Kcqr+OZEUEfoeOhcd5G2l/Ubbt28X75PySvumSP6oT8OGDRPKSE4KxJgxY8R4JfPcUF9Jaf7hhx/EvSflbevWrSKFMO21opTADKMIVkZ0DFkXaMMhLTjIqkUDjCphGaVKlUL//v3FeWjCooksuw2xNGHRIE0bGWmio43dMmixLnNF04KNNvxdunQJ2oY2FF64cEEMYjVr1hR9ocGQBjvKvS+DBkpZTvUuXbqIyePixYvi+ggKU/jyyy/F/aTX/vrrL2EJUhTOo8+wfOQd8oDMmTNHLD5IVii95MaNG8UCJ7v7QjJGCgi9TveaZIYWn8rWk1DHfaKNsLSJlMI+qD9lypRRW3ghy1JmyAsis06TYkDjjuxek/WX3qexh34Dkh8K66I6CoruBS3G6H1KLU6L3datW+faB1pUUlpfOiiMhTa002/UuXNn8X5u5xwwYEBGOI5sIzTVqqFxk35nGicpxasqi3ldw3Kq/jmRZIs8vLKDFFySe1moGd0LCgml81N4GikuJDM51ZuhBB4U9jV58mTxnD5HRkBSmug3oN+O0lT/+eefGDJkiMbvFWPYSGjjiK47wWgXmqwoU8mBAwd03RVGD2H5YNQFyxJjCLCcMoxuYc+ICUCuU3Ldkt5J1h2y/lL8PMMQLB+MumBZYgwBllOG0S/eBVAzRg3FmFLMKcXQUxwubT4jNzbDECwfjLpgWWIMAZZThtEvOEyLYRiGYRiGYRidwGFaDMMwDMMwDMPoBFZGGIZhGIZhGIbRCayMMAzDMAzDMAyjE1gZYRiGYRiGYRhGJxhFNi2qlrxixYqM4kZUoIgqkFLhKlXb/vPPP6LIEFXDtbGxEQWGqCCSrHIzw6gTljcmr+zduxdHjx4VRcYqVaqEoUOHKmw7fvx43Lt3L9OYSAUhqVgew6h7HiWo6B4VLKTq5VRkr2vXrmjRooUWr4hhGEPBKLJpbdiwQSzoRo4cKZ5PmTJFVCvt1q2bym1fvHgBDw8PsTCMjo7G7NmzRUVkGkgZRt2wvDF55dy5c5BIJLhx4wbCwsJyVUaomjRVEWcYTc+jV69excKFC/Hdd9+JCvZkbImKikKBAgW0fFUMwxgCRhGmdeTIEbF4c3V1FUeXLl1ENdW8tPX39xcLQxk02b9+/Vrhd6ekpIiBVv6g1xhGGVSRN5Y1Rh5a/NWoUQOOjo5qPzfLmumhznmUPCKkmJQrVw5mZmZwcHDIURFheWMY08bgY0FiY2OFVbBIkSIZr9Hj0NBQMaCRe1jVtlu3bsWmTZuQlJQkJvpPPvlE4fdv2bIFGzduzHhetGhRTJs2TQNXyhgrysobyxqTHzZv3izkx9PTU3hIGjZsqLAty5ppoc55lJSPR48eoXLlyhgyZIh4jbwjn3/+uVBcsoPljWFMG4NXRhITE8W/8oOlvb29+DchISHT68q27dSpkzgohIZiYl1cXBR+f+fOndGuXbtMlm1ZhVeKq2UMG19fX41/h7LyxrJm/GhK3nr16iW8cFZWVrh586YIB7S1tRWelexgWTMtWVPnPEpQ9DeFcY0ePVoYWBYtWoS5c+di7Nix2faF5c240cY8yhg2Bq+MyEJcyPri5OSU8ZigyTavbQmavAsXLowFCxZgzJgx2X6/paWlOLLDCLbjMFokN3ljWWPySsmSJTMe02b35s2b4/Tp0wqVEZY100Kd86hMPlq3bi28cMRHH30kvCSkyMiHpcpgeWMY08bg94xQLKq7uzuePHmS8Ro9ptfkLTeqtpWRlpaW454RhlEnLG+MNpBZnhlG3fMoeUkoKQfDMIzJKCNEo0aNRMxpZGSkOOhx06ZNVW5LVhvamBcXFyesMZQyk2L5K1asqOUrYkwBljcmv4prcnIy0tPThfzQ4+xCWki+Ll++LPYkUVvKvnXgwAGxAZ5h1D2PEs2aNcOePXsQHh4u5JL2g1CWwOy8IgzDMEaR2pcm4OXLl+PUqVMf5DynWFVi4MCBubalxeGMGTPw+PFjkcnD2dlZTNjkYra2tlapTxTrytlADB8/Pz+NnVtd8sayZpryRulV5Tf9EmXLlhVpfCnVaunSpUWWI0oZ/dtvv+Hly5eiDYXOtGnTBk2aNFG5fyxrxitr6ppHCVJ6V61ahWPHjonnlFWrX79+Oe6/zA6WN+NAk/MoYxwYhTKij/AgahwYwiDKsmY86Lu8sawZD/ouawTLm3FgCLLG6BajCNNiGIZhGIZhGMbwYGWEYRiGYRiGYRidwMoIwzAMwzAMwzA6gZURhmEYhmEYhmF0AisjDMMwDMMwDMPoBFZGGIZhGIZhGIbRCayMMAzDMAzDMAyjEyx087UMkz1UrffJkyfisY+PD5ycnHTdJYZhGIZhGEZDsDLC6BUb/tuIW3cfws7eAalJsRg/doyuu8TkwuvXrzFj9p9ITUtDk8YN0aldW113iWEYhmEYA4HDtBi9QSqV4uLFS2jXaxDafjwIkZHRiIqK0nW3mFw4ePgonpn54IlnHezevRfp6em67hLDMAzDMAYCKyOM3nDnzh24ePjAzt4REokEpSvWxrFjx3XdLSYHUlNTceLUKSS5F4fU2gHJtu64cuWKrrvFMAyTbx4/fowNGzdhz959wljGMIxmYGWE0Rt27NyNirWaZTwvX70hDh0+Iha8jH5y4OAhxNv7ARbW4nmEa2msXr+RJ26GYQyeZavWYv25x9iwfQ9evnyp6+4wjNHCygijF9Cm9ZCwCBQpEZjxmr2jMwoWK4ujx47ptG9M9kRHR2Pzth2I9iyf8Vq6vQdCU61x5Cj/ZgzDGC4JCQl48fIlkn0rIta5KE6fPa/rLjGM0WIUG9jJcr5ixQqcPHlSPK9fvz769u0Lc3NzldqmpKRg6dKluHHjBmJiYuDm5oYOHTqgSZMmWr8mU4Ks6P+uWo26LbqJ8Cx5ajbpiI2Lp6JunTqwtbWFMWHI8ka/2Zz5CxHhXhZSy8y/S6RPVazZsBHlA8vB09NTZ300dvbu3YujR4/i2bNnqFSpEoYOHaqwbXx8PBYvXozLly/DysoKLVu2RLdu3bTaX8Y05tGs2RF/+uknMb4tX74chsSJk6eQ5FQIkEiQ5FIUR44dRrcunWBmxjZchlE3RvFXtXnzZrHfYNasWeK4ffs2tmzZonLbtLQ0uLq6YsyYMWKg/eabb7By5Upcu3ZNy1dkWpw7dw5SM+tMXhEZjk6uKFOlHjZu2gxjw5DlbePmrbgfEocktxIfvEfKSah3NUye9jsSExN10j9TgGSnS5cuaNq0aa5t//nnH8TGxmLBggWYMGECDh06hGPscWQ0MI/Ks379eoM0SFASjm07dyPGraR4LrWyQ7yVCy5cvKjrrjGMUWIUysiRI0fQtWtXMTnLJujDhw+r3NbGxgY9evQQ9S3IQl+yZEmUK1dODLqMZoiLi8PadRvQqF1vhW2q1W+NK1evZ9QfMRYMVd6OHjuO3UdOIsKvtrAaZkeasz9eWxXAlOkzec+PhqhZsyZq1KgBR0fHHNslJSXh9OnT6NmzJ+zt7eHn54fWrVsrHCMZ00Rd86iMR48e4erVq+jYsSMMjRMnTiLGwgVS6/d/W5Hu5bB63X8GkS2QlMMNG/4Tx4sXL3TdHYYxfmWErH1hYWEoUqRIxmv0ODQ0VIQm5LWtzMX84MEDFC5cOMdQG/qs7KA4Uxm0wOQj5+PflavFpnVnVw+F99jCwhJNOvbFwr8XC2+CNvunTXKTN32QNQpdWLF+M0ILNwbMc47yjPcsiwdxVvhtxjuFRNeyZgiHJnj16pW4/1nHPQrvUoQ+yBof2pM1dc+jNE7//fff6N+/Pywsco8G1yd5I28uhZlGelbI1Md0W1dEmDlj/8FDOv/tcjuWr1iJeIkzgmOl2LRlq877wzBGv2dEFgZiZ2eX8RpZ/wga0ORfV6UtxcQvXLgQvr6+wvqoCHJNb9y4MeN50aJFMW3aNIN0TWubCxcu4PnLN+je+rNc2/oXKQmfQqVEdq3P+n4KY0MZedO1rG3avBXL121GWJGmgIWNUp+J8a6EWyHXMWX675g1/bdMf2OMdqBxz9raOlM8P/0O8gs+fZM1xrDn0e3btwsFpWzZsggKCsr1+/VJ3qbPnI0opwCRqjwrUV4VRdKOju3bwd3dHfqajtjc0hqVajVBWloqVvwxAk5OThm/EcPoIxbGEOpCkDWF/uBkj4msG56VbUsLwyVLlojK0hTPn9OGtc6dO6Ndu3YZz2VWgJCQEA5PyQGa0Gb8Pgsd+nwPiZIbAuu06Io188chsFxZFChQANqAlANNo6y86UrWKCzh39VrcOT8dYQVJkXESvkPSySI8aqIoNDb+PyLrzB25DCxUZ/RnrzRuEdeN7JWyxQSGvdySgjB45p6oXv/w48/IS0tHXFxMRg/blwmz4KuZU2d8+ibN29w4MABTJ8+Xem+6Iu8UXjT4ZNnERfQOtv3aT9cmFs5jB4/EWNGDNNLq/+KlatQrloj8djc3AIlAmtg3bp1aNOmjc76pI15lDFsDD5My8HBQVgo5PcT0GN6LasVVpm2tDCkDEcULjNq1KhcLbmWlpaijezIqtTo6qDJj8Iz3r59q9N+KDrWb/gPpSvXhZun8oOUlZU1GrXtjb8XLRELZG30U9OoIm+6kDVaZEyZ9jsOXnmIsMJNVFNE5Ij3KIOndiUwfPQ43L9/X+fyp6+HJqA9IqSEPH36NNO4V6hQIYMb1wz1OH/+PHwLFceAoTPRqusAUVNJ133S1DxKe96ioqIwZMgQEaZFSgl5TOgx/e3rq7xRH/9c8DfCaC9cDgayZNcAPAiOEenLdf0bZj0oVO7mzSCUrlAzo7+V6zTH3n0HxN4xfZA1hjFKZYRo1KiRcPNGRkaKgx4ryjCTW1taGN69exejR48Wg66hsnPXbgwfOxE/Dx+ld9mZqHjUlavXUL2+6paaIiUDYWnrJDbkGgP6LG/kqRk2agyuR1sjsgBN0B+m+FSFFJfCeONXD1Nm/inC7Zj8QQYH8njIFHN6nJ0VmUK06tSpIzIbkXJJvyulBTaEFNLGAP0mGzdtQfWG7cXzEoHV8OjxEzx//hzGOI/Wrl0bf/75p1BC6Pjqq6+EN4UeU/iVvvLPipUIty+EdLtcPLcSCSJ8a2L1+v/E3hl9Ys3a9ajRqAPM5fbpODi6oHi5ati1a7dO+8YwOSGRGoHaSoM95TA/derUBznPFy1aJF4bOHBgrm3JJfztt98KK418qAy1kX1eWehctClPF9DiZNAPP+GFb0OYJUWjssVrjBs1DPoChWcVKV8PJcpWydPno8JDsGX57/h9xjSlNkfm16qsKdQlb5qQNdrP8/c//yLUpzrSnJS4B+lpkCTFvouzzk1pSU2E+/OTqFqmKL7s/7moe8GoLm8bNmzIFGdPUIz++PHjMWXKFJQuXVpkOSJICaGxUFZnpFWrVnmqM6LLcc1Q2bR5M56/jUGjdp9kvPb0QRAuHtmMCePH6axuRVZZU9c8mhXaMzJjxow81RnRlrzdvHkTMxcuR2hAC0Ci3O9hGfEY5czfYuLYUXoRrkUhZstXrkXPL0d/EPqclJiA1fPHYcyoETrZh6PJeZQxDoxCGdFHdDlpHzt+HP9sO4Jw/7rk44bno70Y/eO3CAgIgK6hDD7z/lqEj78el68B/PD2f1GxTBE01bB11xAGUXXKGlnbV65Zh2PnLiOsYANIrZTb9ChJiILDzU2IDewKqa1z7h+QpsMx+Dp80sMw4pcfeWO0gcgbKyOqce/ePSxctBQffz0WllbWmd47tG0FCno746Puuik+qe+ypi15o/Cl738ehle+9ZBu66LSZ92eHcdnnZqiccOG0CXkFR0xajRadvsKXn7Zh1/eu3kR968cxUgd7HUxBFljdItRhGkxmdMuUi70CM+K716QSBDuVRnzFr5Li6trduzchar12uQ4GKalpiIs5LX4VxFV6rXGnj37OB5VjVCc9+jxk3Dw+lOEFm2htCKSJyRmItPWY9uSGDF2Ai5fuaK572IYHRAREYEFfy1E6x5ff6CIEA3bfIwLl67i0qVLOukf8471Gzcj0s4/e0WEPL4JUeLf7IjwrYY16zeKeVeXrFu/AQFlqilURIiSgdUgNbfB4SMcIsvoH6yMGBG0MJ8z/y9EuJbOlJYwzdEHwVInrF63QecFDu/cuYsS5arm2C4yIgRLfx8m/lWEi5snHJzdxX4LJv/QxtKhI8fgHvwQ5Vcj3/tDlCXVpSCCCzfF3CUrsW7DRoMoKMYwyliqf581G7Wbd4enj3+2bSwsrdD+k++wYuVqLkynQ8/LsZOnEesVmO37FHpKHl/6NzuklnaIci6ONet1N7dSwoDrN2+jVuMOubalel3btu8U180w+gQrI0bE5q3bcfdtLBLdS37wXpRPFRw5c1HsBdAV586dQ4nA6jDLJq44L5SpUh/Hjp1Qy7lMGcoKM3XWXLG5PNlN+6F8VOWYYrV3nwvC1BkzM+oYMIyhGoUW/r0I/sUrolT56jm2dXJxR6tuAzFr9h+Ijo7WWh+ZdyxftRYRHoGAWd73HiZ4lMa5i1cRHBwMXSi9i5f8gxZd+2fatK4IO3tH1G/VA38vWsxRBYzxKyOUrWXz5s2idoIse5J8WklG/Vy8dAk7Dx5DhF8tEZr1AWbmYg/Awn/+zbHysiY5cfI0SlesrbbzFStdETdu3uS6B3mEJqOVa9ZixaZdCAlokXsWGU1iZoGIAnVwPdIKI8aMFxl6GMYQoaxF0fGpSlmqCb/CxVG1fjvM+XMuewa1CHmjbj94hBTXfBpgzMwR4V4Oq3QQebBx02YElK0GL1/F4VlZocgEqYUdTpxgQx5jxMrIxYsXMWLECPGHLhN2Cs9ZuXKlur+K+T+k6P21ZDnCCjUEzC0VtqM9AKF+dTBlxiyxP0Db8dORUdHw9C2otnNSmIN/0VJ6l7rYEKBFz/y/F+PAhTsqVVTXKBIJ4r3K4altcYwcO0HkzGcYeagWxIb/NmHV2nXYtHmL3m2mp+rXh44cRYuuA1TaJFyuaj3YOHlh2/btGu0f856V6zYgwi0we+OdiqS4FcXNO/dFwUdtQUbf8xcuomaj98UilYUyu1G6aVmxSoYxOmVk7dq1QhkZPHhwRspCyi0uXyCJUR/k2v/t99kILVBXqQ3H6Q6eCHEth8nTZmjVo3D8+AnhFVF3Fo8yleviyNHjaj2nKXhE/l6yDOfuv0FEwbpa2x+iLCmuRfDarSLGTpzMHhImA1I8ps/6A5vO3MGmm5HYdOI6/pz/l14k5pAp+FSQtXnn/rCyVl25b9i2F44eO6nVBa2pQsbS+4+fI9W1sHpOKDFDpFtZrNmQOdW2pjet127aRRjlVMXRyRVlqtQT9cgYxiiVkfDwcJQqVSrTa5R7nN3P6ofu6bSZsxHiUgbp9h5Kfy7ZtShepDlh0VLV877nBVJ6jhw9isBqDdR+7kIBZfDy1SvekKcCO3fvwdlbjxBZgEL68j8E2F9ZA/tbW8Vju9s71dBDINXZH29cyuHXqdM5DI/Bq1evMHz0ONyJsUK8fw2kehRHTME6uPIqDmMm/KoXf/9nzpyBi6efCLvKC1ZW1qjdrAvWb/hP7X1jMrNi9TpEuKvHK5LVO0Jh6drwirx4+QYlc9mTlBNV6rbAiRMneY8eY5zKiK+vL27duvVBMZ4CBQqo+6tMng2bNuNpnDmS3IqpnJKQ0qqeD7qPs+fOabyfR48dg39AWdg7KlF/QkWouFOVem1E7CyTOzRRbt25910NGjUoIoQkPRWS/8uZRJqqVg/JK6mzyLLFmCYU3vn3kn8wetJveGhbCrHeFd8vICUSRPlWxx0UwPAxE7B85WqdbgLftXtvRpX1vFIqsBoeP3kmjHqMZqAMjA+fv0Gqi/L7LJRCYoYIjwpYukLzIen79h9AxdrN8hVpYG1ti+LlquLk/wtXMoxRKSM9e/YU1Vb//fdfYdFcs2YN5syZI15n1MejR4+w/8gJRPlWy1NKQho4wwvUwdLlq8SErylocbB9+07UbtpZY99RrkpdPHz8TBQYY3Lmn39XI8yrEmBuGFXPY7wr4sjxk1rf48ToNoyQ0pVOnzUHP48ciwOP4hFSvC3SnAsoVFqDi7fD7lsh+GHoSPwxbwEePnyo1WxBFPYjNbOAu5dfvo0rZavUExZrRv3QmmTBoqUI866qVq9IxvldCuHx20hcunwZmoLCEilhTemKtfJ9rsBqDXH0GIc5M0aojFSoUAHjx48X8b3lypUTm9dHjhwpHjPqS+c368/5CPOtla+UhLTHJNyjPObMX6iRiZvCyKjoV41GHTTiFZFBe5Oad/4cC/9eLOSNyZ6YmBg8efYcac7qSyKgccwsEOsSgGOc+cUkQrHWrt+Abwb/gOl/r8LpSEcEl2iPJM/Sue9rMrdAglcggkt0wLG3lpg8dwkG/fAzNm7eopWUqydPnkLJCurJFFi6Qk2cOn1GLediMrP+v00IM3cVeyc1gkSCMJ8aIgRaU146ijzxK1hMhPXlF1KeExNTOFkIo3PyvpLNgcKFC6N///6aODVDudFXrkK4ja9aBlTaP/L4+QvsP3gQLZs3hzpZu249JNZOIlOMpvEuUAQVazfHH3PmYtjQn2GhRM51U/SmpTp4a8QiqEkS7bxx49ZddGinetYYRr+h2PcTp87gxOkziE8BohwLIrlgU0gtbfN2QjMzpLoVRYhbUUiS47DhwmPsOXwCjrZWaFSvDurWqQ1PT0+1W9tPnz2Lj78ep5bzObl6wNLGXnh3ihXLJgSXyRPXb9zAwRNnEFWslUa/R2rjhDDXMpg5Zy7GjRqRkchHXZCiWjywhtrOR7W/zp49i3Y8vjI6RO0rtmPHjil8r2HDhur+OpOD9nicuXILMUVbqOeEEgnC/Wpiw+btKFWiBIoUKaKW0+7YuRO37z1G574/qhTXOm/SICQnvdtQt3rBJAwet0Dpz1as2QRR4SGYv+AvfDfoW7VPAsaQFjXNTHHq57zStk1rtGvTWjwm/9rmoEhsPf9AfV9gYY34+AT1nY/RfdXrEydF5ev4FCmiHQoiyasupNYOyp2A9sMlxb5rn4PHhDy/5C2hIyQxGq/OPMSOA0eFYtK4QV3Ur1sXbm75r61z6NBhFC4eCFs7JfuvBFXrt8H6DRsxYvhQtWcgNNW9cn8uWISwQo2VjiagxByS9JSMxBxxVT5R+vuS3Evg4cuz+GfFSgz4vC/UGRVx82YQPmveW23nLFWxFvasncvKCGNcysiuXbsyPafUnBQeUqhQIVZG8sn9+/exePkqhBVpLiyAasPCWqQGnjpjFiZPGAsPD+Uzc2XH9u07cPbiVXTq+6NSVWHlSUlOQmpKsngs+1cV6rf6CEd2rMTcefPx7Tdfs4dEDhcXF1imqX9Rv2v3HuzeuUM8lpqZI7aq+iZfgizc7m6uUDc0sctn+SNZYXnRDHSvKdvUzr0HER4ThxiHQkhURQHJZj9cbGBXSG2dlbZWJ9iUR4J3eaGYvD51H9v3HIS3pzvatWqOGtWr5+m3p0Xurj170fOrMVAnRUuWx43zR4Si06xZU7We29SgEKRJU6cj1LeWkANtJeaI8q2Bk1ePwmXLVnTr3Anq4PTp0wgoXTFP6XwV4eLmCQtrOzx48ADFi+ctExzD5Be1z7zTp0//4LVt27bpTS54Q4U2Z0+fPRehBRtAamWn9vNTauBgzyqitsP40SPg5eWl8jlo3wmFZsk8IpZqiGlVFbIiNm7fByf2rMfvM2fhh++HwNpa+/3QRwICAmAWEwJI09WWSUsb2Me/QZVGtdQSTkMbjW/dvo2LFy+LvQTyMkoeuRIlSqBypQoiPbm3tzdbpdWghFAq6T37DiDBwQ8xLuWR7pV3b0R+rNUyaEEab1MB8V7lERofhhebDmLFqrXo2L4NWjRrprRSQvVAfp85WxQ4tLN3hDohuWvZdQA2LJkKO3s71Kmtnv0opqiI0Jz21qMy0hy9tfvlZmYIK9gAOw8fhoW5BTp1aJfv8Wv7jl3o0OcHqJvqDdoJT9zIEcN4zGN0glbMgO3bt8eXX36JLl26aOT89Ee6YsUKnDz5LgNJ/fr10bdvX1HfRNW2e/fuxdGjR/Hs2TNUqlQJQ4cOha45c/YclqxYJRSRdFv1W4jlazu8ggSjJ/yKoT8MVslKQhbmRYuXICwqEZ0+/UFlj4g6ocG0fuseuHBsFyZP+Q1Df/kJDg7qC6FQJ9qUNysrK5QuXQrh4c+Q6qaecDyNk54Km+jnqFHjO5UWwKRo0GKRatA8f/4Sz1+8QGxsDDx9/OFbqCRqtfgYnr4FM0286WlpeP74Lq7fu4l9B48iKiIUHh6eKFjQH/4F/ODn5ycUFPIcZje2aBtVxr358+eLdvIL7TFjxqBkyZIa69/bt2/x628zEGbpiZiA1sIDq1dppCUSYYSJsPdAZEoC1hy6hIOHj2HMiKFwdc15nL1+/TqWLF2GZl36w7+IZu6hjZ09uvYbiq0rZuHVq9fo0rmTRkNP1TWPUvKapUuX4saNGyIqgkLhOnTogCZNmkCbkPyN/3Uq3rhVFHObTjC3QFjhxth64Ii4L9275j2r5JYtW1G4ZAW4uKtuKMyNwiXK4cqZfcJ7WadOHbWfn2FyQysrRk2nXN28ebNIBTlr1izxfMqUKdiyZQu6deumcluahEhpooE0LCwMuoS8SavWrsfRs5dEaJayHpH8WA8pfeZbS1tMmfknenRpLyyFuVlKaGKa8+dcSKyd0abHVyI9pa6hPtdo1A629o6YNHkKRg4fBmdnzWX0yivalree3Trj9m+zEOJayCC8I7ahd1GnVg3Y2WWWfSrURcoGHa9fv8GrN2/F4iMiPAwSM3O4uHnB1cMbzu6+KFi2Lio3LvBBRjfan0RhgQR5SAaNmYfCxcuKg5CmpwuFJPTtSzwLeY0bd88gMiwYUZFhsDA3g4enJ3y8veHr4w0fHx9xkLKirVAvVcY9omXLlvjss8+00jfykk6ZPhPPXSogzSl/6W61AW2Yj/KrifiIxyKl8NRJ47Ntl5SUJCpfB92+i86f/wxXd+Ws7dnJmjLYOzih+8CROLJjFSZOmoyvvxooZEyf51Gat2hcI2WX+krhxVOnToW7uzsqVqwIbUAeUArNeutVTffyZ26JsCJNsPP4McQnJODTTz5W2ftAyu/Z85fQ82v1hgPKoP4069wP6xZPFQmIuC4co23UPmuSZVf+D40Gb1ok9O6tvg1XWTly5IiwysisWbS4W7lyZbaDaG5ta9asKf598uSJUotDsnbQIYOu3db2XSaY/Lg7aZMnTYqvUmwRRZvVc0ttqUbrYbqdG0ICWmLNrmO4cu0Gvvv6S4WeBVJEZv8xB7YufqjbopveuXjLV28IS2tb/Dp5KsaOGQUnJ+VjhrWBKvKmDlmjvVsVy5TEydf3kehRCvqMJCUezlEP0LP7b+LvgTK+3L57Hy9ePIdEYg53Tx84u3vD2c0b/qVrIbCOFxxd3JW2HtPiULZAzPb7zcyEFfKdJbJypvdoPxMlS4gID8br0Le4++QaIkL3ISIsGNbWVihSuAgCy5URv6+9vT10Pe6pSn5ljcb9mLh4pPnrvyIiT4pLEby9cynba7x69SpW/LsSJQJroceXo2Furvz0mZus5YSlpRVadOmHB7evYPLUaWjWpDHatm2jdqVXXfOojY0NevTokdGWvG+U2p+UF0XKiDrn0adPn2LSbzMQ7Fsb6Q7q9yLkCTMLhBdqhEOXTiEpaTkG9v9c6esiZW7JP8vR5fNfhCxoCkcnVxFySKGHo0YOV3vWOYbRqjLSpk2bTM9pYKIMTWQ11ASxsbFiESefBYoeU6xofHx8JouqKm2VhaxBGze+rxBdtGhRTJs2LV9/yFRd9c8FfyPUsxJSPdVcJfZ/7Z0FdFRHF8f/cSKEeAgEEiC4u7u7u3uRosVdCoUiLVDa4i7F3V2La4DgQUKIE9f9zh2+3SYQ2U3W9/7OeWffvp19O7u5mZk71+TF1ALBeWvjTpAPxk2aihlTJqJs2bLf7X7O/2UhLLK7aqUiIqVIqUqQSJJEDMmK5ct0NoZEWbI2ecJP6NF3APyy585UALFakEjg+Ok2hg7qL3ZXyc2jZIWaKFOtOerlzKOUAM6mTZqgSZPG4pxkN97CGu8D5KtTQ5/v6JpbHN8SEx0JP9+XOHJin/hf3rRxA5RNZsYyynRIBy0g69alBW3zNBU3Zchanty5EBLqq9RK16rO3GYR8hLFi5eAm5ub7Br9pkt/Wwa/z0Fo3m1ElgsbZramk1fRssiTrwiun9mHqdOmY8zoUUqzNKhyHiW3SQqOrlGjhsrHttevX+PnhYvxOVd14YKnVRibICRPDVzxvgqbnbswdtSIDOdMUoBX/PEnWnYfIQLNVQ25HNZq1g3zFyzEgvnzxOYVw+ikMlKnTh2oE3LXIJIPgNKdSEplmvy6Im3lpW3btilS4kkHF9rJJauBot/lj79X48HLDwj2bACJmfID1RXCyAjRToXxwdoVk2b/gvo1q6Bb506yBcyFixfx5p0fWvccpbWKiJSipasgJMAPvy5ajP79+sr9vuSLEk2jTFnr16s7/tyyB0GeDbSy7ohF8Et4OmZD2TJlxOJn8A8/4PyFSzi8fSWcc+aGc04POLnlFXEf9g4umXINPHb8OA4ePCBTLsbMXZOpviYkxCPo80cE+L1D0Cdf+H98g7DgQFEjolnTxqKWhrLlTdGxrGnTpujZs6ewcNLCcOnSpUJ+0krnqQxZ+3HIIEyZMRufTLMpbYdalZnbTMPewyXsGQaOmyX+ZqQ0nDlzBgcOHkblem1QrUU1jY9zFtksUbt5N/h/fItflyyDV34P9OrZQ2ZFUITksqaqeZR+w7/++kt8VqVKadfGUIa8UebOCVOm45NrZe1TRKQYGSM4dzWcuHoB1lar0aZVyzSbXrp0Cbv3HkCrXqPh4KSazdzUyFe4FEzNLTD2p/H4YfBAFCv21W01K2jTPMrosTJy9OjRTFlNlAFZXgjakZG64NA58e0ArUhbeTEzMxNHVnfAaNClYM9P5m6I8qinVQvEJEs74bZ17NYtPHv2MyaOGyNcBHbv3oNOg6dqRYyIPFSp2wpb/5gh0nFSMLKuoSxZIypXqoTrN27h2odHiHQpCW3CKOYLHIIfY9T8ubJrtWvVEoc0IxbtgL55+xyXbp0Rweo2tnZwzeUJ1zwFkCd/EdjaOWb4OdJMWvTbmZt/HRsygtoGfnovAt0/f3iJzx99kZAQJ+TJI29eVC5TCJ5tGqXIxJXZnfD0UHQso0xqyd1m2rRpg4sXL6apjChD1ijQf/rkCZj18y/w1yaXmVQwDfuAnEH3MGv6V1fOyMhIsSMdJzFF1yHTReyZNuGay0OkE759+TgmT5mGUSN/zNIutirmUZKTNWvWCMWO4kfSc5/MqrxRm1+X/o7P9iW0Ws5kCkmeGjhw7DiKFSksMvh9mwyGslI+8vZBp4GTYGWjmGtxZuOTkpMnX2G07jUaq9YsR7MmjdCwYQOF78EwaldGbt68qTFlhHb6KDCOfO6lrmB0Tte+3R1UpK06oZgaSj9IqXU1lvUjI4xNEZa7Cp4EPhW7nZ3bt0Fuz8KwyW6n1I/JiutMRhibmKBEpXq4fOUqOnXMul+9rjN4QD+8mDRD6eXOAACcPUlEQVQVMeHOSMye+Z03iSgiJhFxShKjLA4pSQlwfH8Jw4cMSjXhACnB5BKS3EWEFiLBwcGiwvwzn+c4uv0kEpOActWbokjpymnuZisySVOMyK3Lx+F95zKcnZxQongxVGpUW/RDE5nasjqWqWuHnwJhhUIybwE+u9cWGxvahnFEAFwD72D2jKnCLYh29ynGrGCpaihTNeMEHpqCFvcVazWDe74iWLTkN4waMTyF0qnJeZT+JymjFlnhSBFR9fx66/ZtvA+LR3zefLrhEkhB7W6V8ffaDVj0y8+yy6QE/758BcytHdGh/4RMZaXMSnxSchyc3dB58BQc3fEnXr95g359+3AdJkZlKEWyZsyYAU1CrmHkc1qkSBHxnM7r16+fqbaUCYQO2p2gAZX8XWnQV9U/Id2fLCJakfVDDmKciuB9oBF2/LMbxcrWVPr9leU6kxaOzm7wffwS2oK65e3bHc6JP43G9LnzEWDRKNP1ayLLdoNRdJgoRBdVNAu59CUS2H28gca1q6NUSfmtNbRYpIUQHRUrVhTXaDeWgo0DPr4RaZ6zsqCMj4/DvvWLULyIF+bNna01aaIVGfeoWBqljqada1LaqPYTZddSB+7u7hg7YhgWLvsTAfmbiIWY1pAQA6ePVzF50jhZfMKOnbvgWaQ8ylZrqBObLG558qN512H4Y+Vf+HXhL5lO/6vMeZQUkWfPnmH69Olq+X85efYCQu0L61QxV7LghHz+Wu+I6nrRpiS5EZes3AClKysnDXJWrbLZLK1F8eIrJ3cJBf2nsaO1Zvxj9Au9UHPbt28v8pmPHj1alvOcfFCJVatWicdBgwZl2JbYs2dPikA6ygJGPpMzZ6ae6jGrnL9wEcGmTkpVRFQd5ElZmIJ9fBAc8AG6RnCAH1yctcefWN3yltrOdf9ePbB6624E5muoUNY2ZWMZ+BQFHczRqUM7pfgo/zR2DJYs/R3Hd61CjSadRLYYRfn04Q3OHtiE6lUroHWrVtDVce/EiRPiGim+VPehUaNGabpoqQJatDZrUBcHrtxEqLuW1DGQSODw4Tq6dGiTwsXp7r276DXiv91qXdhkIbctS5scQgnPbFpWZc2j5HJ88uRJ4XY1dOhQ2f2pjfT9yoY+M8k5pbuTLpCUzVYkA6A4nMVLfkO91r3h4VUc2gQptzWbdMbDmxcxa/ZcURgxozo8DKMoRhIlOzRTsOm2bdvw+PFjMVglv/369ethKNDgmDxVYVr89sdfOB+QDYlKdM+yub1JpPdV1Y4OYe73AC4Rr9B1yDS5/PPlZem0gTITs7In7cSEBBEzMnb0CLknbF2ILZFX1tKD6tmcvPkEIe7VMxWvJLWMRJRoD4ml4vVcTMLeI++XR/hl7mylunSQxYnSkB46fBQuuT1RvHxt5M1fJN04J7KEPH90C49vXYAREtClU0eUKFEC6kDb5S0rskZ/i1lz5+NJjC2inYtm6h7SGkrkEphkYpGpCuxSbD7dQ1lXU4wbPTKF5YwKpZas1hx5C2Suj+oe14jY2GhsWTYNC36ZJ/f/j7bLmiLytmDxb7gWbi/qZOnMPCqRwOXlUYwf8QNW/vk3mnT+AW7umXOzU5es+Ty6iVvnD2LmDMVc73RB1hjNovTIYzLPfvz4UezwUrAp7YyQmV4Zue/1kXx53WERHQhdI3tCGOrWrY0jO1aKxZuyoIA7adpWZaRvlUJK8dlDm1G+XBku6JQK3bt0Qkl3O2T3v6f2zzaODIJLwG1MmzRB6b7ltKtH7iNLFv+KJvWqw+f2aWz4bTJuXjwqFnDJ+RISiHOHt2Lj0kmI/PwCA/r2wNzZs9SmiOg79LeY8NNoeOKzUAQgScqUS2BksTbiPNMugUmJsP14A4VsYjFq+NDvXPh69eyO0/vXC6uYto9rRExUJA5s+g0tmjfTaOyjJmnVrDHsAx9mSqY0hVnoW7jndMamzVtQp2VPpSgiqqZQiYooUq4m1q4znI1lRkfdtB49eoTFixeLLBsiwK5iRZEzfNGiRSKvPZOShvXr4fjJ04gJd0NSdtVU1lVF2lVXyyR0aN8eFhbZsG/DYrTuMRIWllmfCCmomCwYoSEBsLN3Vt7u+KEtMJNEo2uX/kq5p75BC7LRI4Zj5px5eB7wBFGZ3LlW+HNjwuD84TImTxir0iJbNBaVK1dOHJQClOp/bF0+HWWrN4aNrT3837/Ci8e30LJFMwzt10Vna9FoO7RYnjtzGtas34RbD08gyLW8WrMfmXz5CAf/O6hVtSJ6dusCE5Pv3RLz5MmD0SN/xPIVf6BQqWqoUKspTE3NtG5cow2Wl0/v4dKxHWjVojnq11dOnIEuUrRoUVQrXxIXH11HaO4qImNVVlFqYo5vMI74DKeg+6jdvi3+veuNfIVK6kR8ElG2akNsWzlLZKXkjT1Gay0j5JMsDXCiCZ0yk1BgqSK59g1tcp46cRzcPt+AWdArpdyTBlEyK4tzZQ6iEgmsPj9EnpjXmDJhnFjgtW7VEvVqVcOOv+ci4NN7pXwMZRChQPPMZBL5lsiIL9i3YRHsrIzx4/BhmQ7uNAQoaH7qpPHIK/FHtkAflX+eUWw4nH3PY8yPQ1Jkx1I1dnZ26NypI2ZMnwqz+GBE+fsgl6MlFi6YL6worIioFnNzcwwdPAATRwxGwShvOL09JxZnKkMiEUqI85vTKJb0BtPHj0Kfnt1TVUSk0AbavJ/nwsYkGpuXTcOj25eRlJioNePax7cvsGfdQvjcPouJ438yaEVESv/ePVGloBscfC8ACVm31ivFCpcKZiGvkfPTdUyfNAFv3vqiQLEKUHZ8Enmk0PHjiJFKVUSkCk6BouXg7e2t1Psyho3SLSPkkvX8+XMULlxYFP2i+BHK4EI555nUod2FBT/PxuLfl+Ot73uE5CwPifnXIlIazW6UDOOoEDh8uoEyRfJjcP+ZslzzRIMG9ZEnjzv+/Gs5Slauh3JVG2pF7ZGXT+/jwpGt6NCuDWrVqqXp7ugE9HedNW0yps2aC99ASlZQSGW1RJx9z2Hk0EFKKaqVGWiTpEf3bhr5bOZrvZNf583Bw4cPsX3XXvi/uosQu0JIsPdId2dbYmHzNTbJIoOsPkmJMA95jRyhPsjj6oSuQ/rIsj/J+7/Qo0d3NG7cCLv37MOmZYdRtmojFCtfA2ZKdrWS1xLy9sVj3Lp4BCZIRJcO7diFMBm00URKbr4TJ7H7wGEE56yERFstKraXGAe7T3eQO1s8JsydJYLAKcifiqbqGomJCZzml9HuAHbKN06DAmUn+fTpE1avXi2sI7169VJoItB1MhPoSX+KC5cuYdvOXQi38UCEczHAJHOTXlYDimX3iYtCjsAHyJEQgsH9+qBkOilXqfDVhg2b8O6jPxq07QtHF80ErUVFhuPCkW2IjQjGkB8GiQJ0mcVQAthT+1tS7Rtf45zyBRsnJcIoNuLrAjGDjFwkm87vzmPUsMEoyYspnZI3Vcha8rljz4HDePzkKSLsvBDtWAgwVXz8M4qPgVXwM1iHvkLZ0qXRtlVzpbiTUNajw4ePipoWRctWR5kq9RUuSJcZyL3r6YN/cffKCTg7OaBN65Zis0/fZS0r8kaFUZcs/wMBidYIdS0DmMpX1DQr41qaSCQwDXkLh8D7aNG4IVq3aiGz0D99+hSbt+9Ch/4TlVbPhooexsXGiNpI2axsMGLGSigTihHdsnwaZkybIjLz6YusMXqmjFCqP9qFpoN2Hg2VrEzalObvwKHDOHXmPMLtCiDKqYjCufmzqowYxUche4A3bKI+on2bVqhfr266bg3JuX//vqjxUKB4JVSu00LpAZtpQaL8+PZl3Dh/EC3/70OdVbcsXRhEVbVApE2E2fN+wesEO6VVaTeOCoLz+8v4aeQwg9qc0Bd5U6UyIiUsLAxHjp3A2QsXEWWbFxGOxSAxyybXxolt0GNYRXxE44b10bhhA5XURKDCdGfOnMWZs+fgnr8oytdoIgrEKZvY6Cjcv3EOD2+eR8kSxUWAujLlQ9tlTRnZ244dP4l9hw4jzL7IVyuvEmJJFME4OkTEKHk422LIwH6pboz9vmw5LOxyo0pd5aUODwrww9pFE9D/pwXCNVBZSJKScHz3ahT0dEOH9u30StYYPVNGqLjWxYsXhemddm9IKalSpUoKtx5DQBmTNk16+w8exrkLFxFhlx+RjkXl3ynM5I6OUVwkbAO9YRX5Ea1bNhcB9uTjrSixsbHYu28//r1xC3Wad4dnIdXugAf6f8CZAxvg6uSA3r16KC0Pui4MoqpcIFIRxnkLF8En3BThrmUzlfZXCsUFuPhdw6SfRme6UrS+o+3ypg5lJPmmzMlTp3Ho6HF8sfNClFMx8sX5vmFSAmw+P4JthC/atW6JenXrCPcXVUPZIq9duybSRme3d0GlOi3hmttTKXFudy4fh8/DG6hVqwYaN2okEsIYmqwpS96+fPmCzdt24PYDbwS7lFFqGv20MIqPhm3AA9jFB6N/7x4oW7ZsunPlgoWL4Ji7IKrVb6MUF2dVKCNkaTm5bx3sbcwxeOAAhTb6dEHWGD1TRpLvbl25cgWXLl0SJtNKlSrhxx9/hKGgzEmblJJDR47h9NlziMyRDxFOpJQoN8iWFBfaVbSO9kfbVi1Qv25dpUzolHFj9Zq1MLOyE0qJdfbMu4ylNUBeP3cQr7xvo0/vnihVqpRS768Lg6iqF4i06Fq0dBkefY5BmFvFTCkkJl/84Pr5JqZNGi/iyhjdlDd1KiPJXQZpMXn93mMEuddMEStCFmCn95dQp1oldO7YXiPJB2gKvXv3Lnbv3Yds1vao3qhDplxUyRJy8+IR+Dz8VxSlbFC/nko38bRd1pQtb7QO+XvtBrwPjkSwazkkWaqgcF9SIqwCn8I29Dnatm6BRg0ayBVbQd9x1eo1+Bz8BY3aD4R1Ft3/lK2MULHgYzv/QqUKZdGhQ3uFXcp0QdYYPVVGpLx69Qo7duwQrjs7d+6EoaCKSZvcZg4fPY4Tp04jwq4AIkkpUdB9K/UdnEewif4k3LHq1qmt9MA0ErHzFy4IS0mVem1RrGw1pfjHvn/jgzP7N6ByxfJo165tpiw4+jCIqmOBSC4Pvy3/A3fehSEsV2WFFBLKZJQz4DZmTp2EnDlzqrSfuo62y5smlBEpt+/cxcrV6xDgUV8oJOQC4/zuIsaOGCpSu2oaGudu3bqFHf/sQp78xVGtYXuYW2STz730zmXcOHdQ1G5q1rSpWpQqbZc1VckbKY5rNmxGmLkzwlxKZyouKTVMQt/BMeAeqlQsh26dOsDa2lrxmNGLF7F3735UbdgeRUpVzvQ8mTyNdFayt1EGuTtXT+LRzXPo369vujGjui5rjB4qI8HBwcIiQu5adF65cmXhrqWprDn6NmnTTuG+A4dw9uIlhDkWR6yDl+K71UkJsA7wRvYvr0WAp7w7OFmB6jusWr0WMQlAg7b9YGWdPdMD7ZVTe/Dh9WMM/WEwPDw8oCp0YRBV1wLxP4UkHGG55LOQmIR/Qs7PN0WGrqwkEjAUtF3eNKmMSBeSv6/4AyamFkhKiBNpbZURzK1sS+Khw4dx/sJlNG4/ALk8vNJsGxXxBSd2r4attQX69e2tNPdSfZA1Vcqb+BsdOYbDx08gxKk04u09M+2CSrFK9p9uwt3WDEMH9c9ysgRKlLB23QaER8ehbsuecHDSzAYOpY+mQsGFC+ZH925ds1RQUxdkjdEzZWT27Nl49uyZ0KBJAalQoYJKdqy1HXVM2iEhIVi7cTMev/RFsFsVJFnayfU+WiA6+N1AzSoV0aVTB5F6WV2QuJ07fx77DxxC4/YDkduzoELvDwsJxJHtf6BU8SLo0qWzyhUoXRhE1blAJIVkwaIleBBshAjX0um2NY4KhsuHS5g9bTLc3LQoxaYWo+3ypmllRJfw9fXF78tWoHzN5ihWrvp3rwf5f8DBrcvRrm0r1NZA6nFtlzV1yBst/Jf/uQqvg6IQTBZfBbNumQe/gkPgQ/To2hG1atZUWkYs4vbt29iydTvyFyuPynVaymVlUwaR4WG4fOIfhAZ+QP++feDllbYyrU+yxuiZMnLkyBHUqFEDOXIoNzZA11DnpE3JAv74ew2CchROvy6EJAnZ/e/BNSkIY0YMF5WGNQX57y79bRnKVm+KEhVqyvWeD2+e48Se1ejTq4eopK0OdGEQVfcCkYLap86cg5emeRBnnz9N9z/n1ycxaexIpUxmhoK2yxsrI4oRHh6OefN/QamqTVG0TBXZ9dDgAOxd/yuGDRmsMcuOtsuauuSNlkCnz5zFjj37EZirKpJsXDJ+U1IC7D7egKetMcaMGKYyixaNtWRlu3DxMqrUa4OiZaoqVeH5tnbI3aun8ODfM2jdmly26yitSLAuyBqj5zEjhoq6J+2IiAj8uvR3vPxijDC3Ct+bnJMS4OB7EZWK5cPg/n21omCR6POixXAvWA4VazVNt+1rn4e4eGQrfho7Wik1A/RpENXEApESVIyfPA1+7rUhyfbNxoNEAse3Z9GnXVPUqc3FJvVJ3lgZyVw2pxkzZ8E0WXriiPBQ/DB4EEqXTt+6aMiypm55e/fuHeYtXIzP9iUQR25baZEQCyff82hQrQK6du6otAV7egQGBmLT5q0IDA5DvVa94JRTuUlAfF89xflDm1GieFF07tRR4XgXfZA1RrPohTJC/p8bN27E5cuXxfOaNWuid+/eqdbFyKitIvfStkk7MTERvy1fiTsfIvElV4X/XpAkwfHteTStUR6dOrRT2c5KZqC0hr8s+BUeRSuKImKp8f71M5zZvx6TJ02As7OzWvun6kFUGfKmqQXi/QcP8NvqTQjM1ziF8msR5INKDnEYP2aU2vuk6ygib8oc9+SFlZHMQb8ZjXVS6HdXp3usPLLG8+jXTRYq9vreuiDi7PN93yAhDk5vTqN7uxYi25m6IS+IDRs3I1/RcqhSrzVMTbOWwCYmKhIXjm5DePAnDBzQT2Xxl6yMMBmh3gpAKmLv3r2ikumSJUvE8eTJE+zbty9TbRW5l7ZBA/2oH4fC0yoOZsGvZdezf34oLCKU+lKbFBGCssaM+2kMvG+dg+/LJ9+9Hh4WjJN71wqLiLoVEXWgy/JWulQpFM3nDrPgV/9dTIyDXaA3fhjQT5NdMwiUOe4xqoXSpFMBRumhaUUkNXgehXAvnz19ClxDvUVdpO8svu8voVPLxhpRRAiKxZ0/by4crIBtK2fB/8ObTN/r1bMH2P7nLJQplh+zZ81QaSIYhjEIZeTcuXNo37698Nuko127djh79mym2ipyr/SgnSHa0fn2oOvJSa1NVtqSQjJ25HA4Bt6HaVwkzKICYR/1Hr17dEvzvmn1VdG23+5gyduWsnQMHzYUZw9uhO+rJ8ISIj1O7lkjguyTu2ZldN/kxj6yFmWlrapRhrxpStaIPj26wSHEGyaSRJggCTZBz1C/bi2x2NJGWVN2W2XKmqLypsxxTxdkLb3PZ1nLuqzxPPq1LSkkE8aOguPH6zBJihPjGh3WQU9QukBuoYhoUt5oQ7Fjh/YYPKAvTu5ehbvXTsv+3kmJCUhMiE/z+NomEReObsedCwcwftxY1KtXL1UZ0aV5lNF9NB84oIS4A8qI4en5n48nnZOPJaXATZ6OLqO2lClI3ntJ+fafjQYKWogdPHgQnz59+q49BY03bfpffMSWLVu+G6ikUAaili1byp5TvRaqSpwaZDVo27atOHd0dESVCuWQlPT/nR2XYti2bZusLU0OHTt2lD3fv3+/yMyVGrSL161bN9nzw4cPC9N5alCBrl69esmeHz9+HH5+fqm2pZiVfv3+2z339vZG8aKF4e9zPUW7vLmc8fjxY1Sv/l82mvPnz+P16/8sP9/St29fWcFGchPw8fFJs23Pnj1lu5TXr18X/UjOjBkzoA2yq62yRul6K5QsBhMT368v2tgg4ksYNmzYoLWydvr0aeEfnhaDBg3SiKwpIm/KHPd0ZVwjdu3aJb5ParCsZV7WeB5NKW/U3zo1qiI07B0szf6/Z2vz9ffUprGteLEiCPR9jFN+b9GgdR+8uHcOYQHvkRal6nTBoa3LUcAzN4rVqoGjR4/q/DzK6Ac6r4xIB5XkA5w0+IqKBCa/nlFbqXYvz72kkOl59+7dsuf58uXDggUL0uwvDTTJ05ym5zZFKZGTt00vUI4GjeRts2e3Ef6vaU2YydumF8xOlpbkbdOryk79S942vZTO9L2Tt82o0nDythm5OFBhPelnZ9SWFtPSv3FW8qirWna1Wdasra3SnNxZ1lQja8oc93RpXEsv5oBlLfOyxvPo9/I27IdB+OUX6oOx1sobtV286FcsX/4HjuxYiUIZZGajDG5tWjVH+3ZthWKvD/Moox/ofAA77dLQTtSyZctk1Z1pJ2XEiBFiB+PbHZ302tKOjrz3ymhHh3YyUjNP0uvJB630TJhZaUu7RGn9aVXV9ttBVlNtqb/SyYlMxvR3zWzbvHnzQhtkV9tlzd/fX/x+tFuYfAHGsqZYW3nlTZnjHo9rLGs8j+q2vNHrm7dsxYfPYWjQps93yllCYgIObFyKhvVqCrcsfZpHGf1A5y0jZP4kt6Q3b97IBj46p2vfDnrytJX3XskHgtR2OeifM61/9OTXM0qxm9m2GWUt0ee2ydvTzlFGqRcVaasp2dV2WUsvW4o2yIS+yZqyxz1dkjVDbatKWeN5VHflQtqWqqQv/e13PLx1EWWrNkjRhmJEShYvjLp168raa+vYxhgmeiExderUEWbe0NBQcdB5/fr1M9VWkXsxTFZheWO0YdxjGJ5HdRtSAKh2zb2rJ/ElNEh2nRLBBPm9RqeOHTTaP4bRazctqbmRzL9Xrlz5Lqf5qlWrUgQKptdWntflhfPx6wfqqDOSVXljWTPcOiPKGvfkhWVNf0itzgjPo7rPhQsXcOn6XZSsVFc8v3pqDwb26wUvLy+N9YnrjDAGoYxoIzyI6ge6MIiyrOkP2i5vLGv6g7bLGsHypjgUs7F12w5ERkaK57nccqJ161Ya7ZMuyBqjWXQ+ZoRhGIZhGIb5GgvSq2d3TXeDYQwvZoRhGIZhGIZhGN2DlRGGYRiGYRiGYTQCKyMMwzAMwzAMw2gEVkYYhmEYhmEYhtEIrIwwDMMwDMMwDKMRWBlhGIZhGIZhGEYjsDLCMAzDMAzDMIxGYGWEYRiGYRiGYRiNwMoIwzAMwzAMwzAagZURhmEYhmEYhmE0AisjDMMwDMMwDMNoBFZGGIZhGIZhGIbRCKyMMAzDMAzDMAyjEUyh4zx9+hRr166Fn58f3NzcMHDgQBQqVChT7UNCQrBq1Sq8evVKnC9cuBCenp5q/DaMocCyxqhr3Pv8+TOGDx8OCwsL2bXixYtj4sSJauwxYyjz6J07d3DgwAH4+vrCxMQERYsWRZ8+feDo6KjGb8QwjC6h05aRiIgILFiwAI0bN8b69evF4y+//ILIyMhMtTcyMkKZMmUwbtw4NX8TxtBgWWPUNe5J+euvv7B582ZxsCLCqGoejYqKQuvWrfHnn39ixYoVsLS0xNKlS9X8rRiG0SV02jJy48YNODg4oEGDBuI5PR49elRcr1u3rsLt7ezsxMCqCPHx8eJIvsikwdfUVKd/WkbFsKwx6hr3MgPLmuGg7Hm0Ro0aKdo3b94c48ePR2JiorCUpAbLG8MYNjr9n/727Vt4eHikuEauLnRdGe3lYd++fdi9e7fsefXq1TFy5EjY29tn+p4Mkxosa0xWxrGxY8eKBaGXlxd69OiB3Llzp9mWZc1wUPU86u3tDXd39zQVEYLljWEMG61VRsjsS76naUHm35iYGFhbW6e4bmVlJa6nhqLt5aFt27Zo0aJFimu0w2NmZgZ9Jjo6GjNnzhQH7WAxismui4uLwvdlWdN/WVPFuGdra4t58+aJBWNsbCz27NmDuXPnYvHixeJ9qcGyph+ypul59PXr19i5cyfGjBmTbj8NUd70TdYYRi+VkREjRiAhISHN121sbJAtWzbhv5oc8lelyTc1FG0vDzRY6vOAmRYSiURMNPTIKC67mYFlTf9lTVXjHllDCHJ76dmzJy5dugQfHx8Rt5QaLGv6IWuanEcpgJ2U4H79+qFUqVLp9tMQ5U3fZI1h9DKAnXZaaHBL6zA2Nham4jdv3qR4H5mK8+bNm+o9FW3PMKqSXYZR17j3LeSPTwej/2hqHiVFZM6cOejWrRtq1aqlom/HMIy+oNOrokqVKiE4OBhnz54Vuz/0SGlS6Xpm28fFxYmDoDZ0npSUpLbvxBgOLGuMOsa958+f4/3790K2yJVmy5YtQhlJL3UrYzgoex599+6dUEQ6d+6stIQKDMPoN0YSHbcRUr7zNWvWiHznuXLlwoABA1C4cGHxWmBgIEaPHi3SCjo5OWXYnujUqdN3nzFjxgyRl59J6c9LQYfk62to5nVlwbImHyxrWRv3Ll++LPz2Q0NDYW5ujoIFC4oda7YIf4+hypoy59GVK1fiwoULQtaSk/z9jOHKGsPopTLCMAzDMAzDMIxuotNuWgzDMAzDMAzD6C6sjDAMwzAMwzAMoxFYGWEYhmEYhmEYRiOwMsIwDMMwDMMwjEZgZYRhGIZhGIZhGI3AygjDMAzDMAzDMBqBlRGGYRiGYRiGYTQCKyMMwzAMwzAMw2gEVkYYhmEYhmEYhtEIrIwwDMMwDMMwDKMRWBnRIbZu3Ypq1appuhuMAcMyyKgLljVG3bDMMYxmYGVESzl//jzs7OxSXOvevTuuXr0KXWPmzJlo06bNd9fr1KmD3377TZy/efMGRkZGCA0NTfde9erVg6WlJUJCQtJtJ72fjY0NbG1t4eTkhLp162LDhg2QSCQp+mZqaiprV6JECTEhMfong9K/c44cOeDp6YmePXvi/v37KdrRdWrj7+8vu3bv3j0hS9+yadMmcf3PP//87rVBgwahcOHCMDY2lsk4kzYsa5mTNR8fH7Rt2xY5c+YUv1/16tVx5coVFX47/UGfZC48PBxDhw5F7ty5hUzlyZMHXbp0Udr9V6xYgQoVKsDCwiLVuZxhsgorI4zO8OrVKzGBWFlZya0wvH//Hl++fMG7d+/w008/YdasWRg8eHCKNi1atEBERATCwsIwd+5c9OnTR0zyjH6R/O987do1FCpUCFWqVBEylZxs2bJh9uzZGd5v7dq1cHBwEI/fUrp0aaxcuRKVKlVS6ndgdAN1yRpt3jRt2hQPHz5EUFCQGLuaNWuGwMBApX8nRnsZPXq02IC7c+eOkDuSOdrsUxa5cuXC1KlTMXDgQKXdk2GSw8qIClmyZAkKFiyI7Nmzo0CBAmJ34dud+82bN8PLy0vs0NBEEh8fLyYVmmBoIqNdDjouXbokdvXLlCmTYqHdsGFDsaNfvnx5zJs3T+y2SaFBafjw4cibNy9cXFzQq1cvcc+MPl9bWbdunfj+P/74Y6oLwPQga0rz5s2FErNmzRp4e3t/14Z+D9r1od/i211MXYVlMHXc3Nwwbdo09O7dG+PHj0/xGj1fv349Xr58meb7nz9/josXLwqZpAXAt/IybNgw1K9fXyw2DQWWNfXLGim7ZIVzdnaGiYmJWCzS44MHD2AIsMx95fr16+jatStcXV3Fc3d3d/zwww+y18kbYNmyZShSpIjoBykqT548kft7tmvXTsyN5GHAMKqAlREV4uHhgbNnz4qdeVoAjxs37jsT+rFjx3D37l2xOD5z5oxYLDs6OorrZOKnwY6OmjVrfnf/bt26ic8gM//27du/W6D369cPwcHBYmJ6/fq1GARp4Mzo89OCBrG0jlKlSkGVJCYmiomCBnMa8GlCpolZUcgfmHZ5Lly4kOpn7Nq1S0xUtJOpD7AMpk+HDh1w69YtREZGyq7R357camgnMC1oYVi2bFm0bt1a/C6KKsf6CMua5mWNLCTkslOsWDEYAixzXyH3PLKwrVq1SvQluSsyQe591PdDhw4JqxkpFy1btkRcXJxc35NhVI6EURutW7eWzJ07V5y/fv2aRgvJkydPZK8PGDBAMnz4cHF+7tw5SY4cOVK8f/369ZLSpUuLc19fX/H+gIAA2esLFy6UeHh4iPPPnz9LjI2NJcHBwbLXfXx8JGZmZpKEhIQMP1+ZzJgxQ2Jqaiq+T/LDxMREsnTp0hS/R0hISKr3OHLkiOi79PvWqFFDMnTo0DQ/M737VapUSfZ3SN43eqRj5cqVEn3FkGWQvvu3eHt7iz68f/9ePKe+79u3T/Lx40eJtbW15M6dO5K7d++KNlKo725ubpLffvtNPF+zZo3EwcFBEhMT8939a9euLZNxQ4NlTb2yRmNdsWLFJNOnT5cYKoYqcyQPixYtklStWlViYWEhcXZ2lixevFj2OsnF/v37U7wnV65ckosXL2b4PeWRbYbJKmwZUSG0A1KuXDnh60s7G0ePHv3Ol5cCD6VYW1uLXS15+Pjxo3ABSW42JVOxFDIRJyUlIV++fLKdlYoVK4qA2k+fPmX58xWFXKTIvzn5UaNGDbnfTzs15Ast/b7k8rBt2zbExMQI87rU1E5HRnz48EH8TVLrG1ldaKdNX2AZzFgWyJXi20BWcq0ZMWIEJk6c+N17pL8h7SYSHTt2RHR0NPbt2wdDhmVNc7JGrkGNGzcWYyoF0BsKLHNfocDysWPHiuB7kgVyXyN5OnnypKyvPXr0SGFpoSQw5J6V0fdkGHVgqpZPMUB8fX3Fgvn48ePCP5Oyq5DP5bfm07SgAS09yNWIFuI08EoHEfpMKZRNg+5BAw0FfH8LDU6Kkt5Cn0y8jx8/hioICAgQ5mUacKUDe0JCglAe9uzZIzKgkJldHiiwj36T2rVrf/caTRTLly8X/r0HDhwQbhG6DMtgxuzevVssIOhv/y0TJkxA/vz5v1NOSTGmRUjJkiVl18g9g64rM4ONLsGypjlZkyoixYsXx19//ZVqNi59hGUudWieJMVj6dKlwm2vUaNGoq+U1a9JkybftafkLul9T4ZRB2wZURG0OKZBkYLaaMCiHRvpLoU8UCAa7aB8/vw51ddpcCE/0cmTJ4udMgpyJH9RKbRop4GZ/FelO0W0W5OV3Vupb21qh7IUkdjYWDEwSg9SOiitJe18PX36VKS+pOPRo0cifkRe31a6F/nu0iA9YMCANH2qaVIZM2aMCDiVd1LTVlgG04b6QUGaGzduxIIFC1JtQ/7k9N2onRTyqT5y5IiQSaks0kHKMvmDSxcg5ItNMkcLSZJhqSzrKyxrmpE1ipWgBSbFnlDMhKEoIgTL3H9QlkiyilA/Kfbx4MGDIkalatWqsoQa06dPx7Nnz8RzkhvacKPvn9H3JJKPYTSm0bk03oRhlAErIyqCFrtTpkwRdTEoWG7nzp1o1aqV3O+nGgX9+/cX9yGT6uXLl79rQ25KlO6WBlXaJaOFNu2KSKGAb6npmLJkUIDe7du3oc3QAE+Zr6QHpdolhWPIkCEihzq9Lj3ILE2pMtPLRENZRei70yMtBChQ9O+//063D5SFhFwqKJhdl2EZTMnhw4dl9WQqV64sJuuMUmDSQiP5TjYtKMmFgb5rclmkBSG5i1CwMUG7kSS/5EJIQbVSWdZXWNY0I2u08KVMSmQhps+SuqoaQq0klrn/IKsQzZHUT/otyFWPlFNpAUeSLdq8o8B16mfRokXFd5P3e9LYRWPYzz//LJRhOqcxjmGUhREFjijtboxGmT9/vjDznzp1StNdYQwUlkFGXbCsMerGUGTOUL4noz2wZUSHodS25LpE+iTtxlC8AwU4Moy6YBlk1AXLGqNuDEXmDOV7MtoLB7DrMBTYTS5F5FtMfrNU8IrMzgyjLlgGGXXBssaoG0OROUP5noz2wm5aDMMwDMMwDMNoBHbTYhiGYRiGYRhGI7AywjAMwzAMwzCMRmBlhGEYhmEYhmEYjcDKCMMwDMMwDMMwGkEvsmlRVVAqECUtWkSFh3r37g0TE5Pv2h4/flwUyvP19UWZMmUwfvz4FK9TsSAfH58U7/39999FBXCGURVUzZaKOFJFXCqkxTCqgmWNSQ2eRxmG0RR6oYzs3btX5MhesmSJeD5v3jxRmbZDhw7ftbW3txdVSB8+fIigoKBU79e9e3c0b95c5f1mGClUPdjZ2VksEBlGlbCsManB8yjDMJpCL9y0zp07h/bt24sBUjpIUvXQ1KhcuTIqVaqE7NmzK+Wz4+PjERUVleKgawwjL69evcK9e/fQunXrdNuxrDFZhWWNSQueRxmG0RQ6bxmJiIgQOzOenp6ya3QeGBgoBjQrK6tM7RDt3r1b7B7Szk7t2rXTbEs7R9RWSr58+bBgwYJMfBPGEElMTMTff/8tCkxlVPKHZY3JCixrTFrwPMowjCbReWUkJiZGPCYfLK2trcVjdHS0woNot27d4O7uDnNzczx69AhLly6FpaWl2AVKjbZt26JFixay50ZGRrKKpuSDy+g2bm5uKr3/wYMHxaRfrFgxPH78ON22LGv6jyrljWWNSUvWeB5ldHkeZXQfnVdGsmXLJh5p98bW1lZ2TtDgpyiFChWSnVNgXsOGDXH16tU0B1EzMzNxpAYXt2fS49OnTzh16hQWLlwoV3uWNSazsKwx6cHzKMMwmkTnlREbGxs4OjrizZs3yJkzp7hG53QtM6blb5Hu0DCMsqFg0bCwMIwcOVI8px1A2qEkN5qJEyeiYMGCmu4ioyewrDHpwfMowzCaROeVEaJOnTrC57RIkSLiOZ3Xr18/Tb9pOpKSksSOC6W5NDY2hqmpKSIjI/Hs2TMUL15c7NKQKwPtJg4ePFjN34gxBKpWrYqSJUvKnlMqzL/++kvsXufIkUOjfWP0C5Y1JiN4HmUYRlPohTJCGUAoTeXo0aNl+dHJB5VYtWqVeBw0aJB43LNnT4pAuR49eggfasqLToMrvUb50AkKvOvVq5eYyBlG2VhYWIhDCrlH0A4i7UYyjDJhWWMygudRhmE0hZGEHTJVAgXecWpC3SdXrlzQdljW9AdtlzeWNf1B22WNYHnTD3RB1hjNohd1RhiGYRiGYRiG0T1YGWEYhmEYhmEYRiPoRcwIwzAMw2gr/v7+2LHzH8TGfnU5qle3FipUqKDpbjEMw2gFrIwwDMMwjIoqmx87fhyXLl9FtYYdYO/kivi4WOw5sAuXr1xDxw7tkDt3bk13k2EYRqOwMsIwDMNoPZRrZeOWbXj3wU92rZBXfnTu0A7aBKW7pbou585fFI/Fy9dC9+GzYGHxX/HATgMm4dmjW/ht+Z/Ibm2JenVrC0uJtPggwzCMIcHKCMMwDKP1nDx9GudueyPU6b96Ka8uXIeHey5UqVJF4wrIixcvcPXaddy5exfOOfOgSJnqqNKsD0xMvp9mjYyNUaRUJRQuWRH+H97gxt3L2LFzF/IXyI/qVauIquXJUzEzDMPoM5zaV0VwSkL9QBdSErKs6Q/aLm+akrUHDx/it5WrEZC/MWD63yLdKC4Szm9OY9LYkfDy8lJrn2jqfPXqFS5fuYrbd+7A0TkXvEpUglexcrDI9p8VREpiQgJCQwJgZ+8ME1PTVBWad6+e4vnDf/Hm+SMUKFAANapXFYoJFQ80NFkjeGzTD3RB1hjNwsqIiuBBVD/QhUGUZU1/0HZ504Ss3b59B3+sWY9Aj3qQWGT/7nXjqBA4v7+IMT8OEYX3VM2nT59w6fJlXL16HdntHFGoVBUULFYeFpZW6b4vKMAPaxdNQP+fFsDR2S3dtkmJifB9+QQ+D6/D96U3SpQogdq1aqJw4cKi0rkhyBrBY5t+oAuyxmgWVkZUBA+i+oEuDKIsa/qDtsubOmWNpqYDhw7jwPEzCMpbBxILmzTbGsWEwcn3Arp2aI2G9esrvS9hYWG4du2aCESPT0xC4dLVUKR0FVjb2Mr1/hVzhiMuNgYJ8XHIZmWDETNWyv3Z9J5Xz+7j6b2rCPL/gEqVKqJmjerImzevXssawWObfqALssZoFo4ZYRiGYbSK8PBw/LbiTzwPiEQIuWaZpO+mJMmWQ7hwbT14Bg8fP8GQgf1hafm9q5QixMXF4datWzh/4RI+BwSgYIlKqN9uIBwysGqkBmXQIqWCkD7Ki6mZOQqVqCiOmKhIPHt0E3+t2YD4mCjUrFlDWExy5MihcJ8YhmG0BVZGGIYxSBITE4XLDUE++S4uLpruEgPg7r17+HP1WoTYF0WMe1nAyEi+N5paIMijLv795I3n4ydh5LAfUKRIEYU/n3bijxw5ijNnz8HDqzjK1GoDtzz5YSRvP1RINitrlK5URxxfQoPgffcKps+cjUIFvdClcyc4OjpquosMwzAKw25aKoLNy/qBLpiXWdYUx8/PD3+vWoPY+ESYW2RDWGgQihctgm5du8Da2lpj/dJ2eVOlrEVFRWH1+o249/QVgnJVhSSbfC5QqUFxJI4fr6FqhdLo3b0rzM3N5X7vkqW/wzibHarUb4NslsqRhadX9qBJk8binJSaeAsXvA+IVMq9KfD9yb1ruHHuAObPmwsrq/RjV3RF1gge2/QDXZA1RrOwZYRhGIOA9l2eP3+O4ydO4fWbN6jeuBO8ipaVBQzfvnISEydNQeXKldCwQX24urpqussGw6NHj7Dir9UIsc2PqHwNKfdtlu6XZGWPgPxNcObZQ9wbNxGjhg9BwYIF5XpvdHQ0HB3ypJqSN7NQ4cODBw/I3K7GzF2jtHuTcmORzQoSSZKw9jEMw+gaemEZSUhIwMaNG3H58mXxvGbNmujduzdMTEy+a3v8+HGcP38evr6+ImXi+PHjv9+dW70ad+7cEbtpjRs3RocOHRTuE+/o6Ae6sKOjSVmjXdnr168jNjZWdq1UqVJa5S7y4cMHXLl6Ddev/yuyH5WoWBcFipZNNSsRBRk/vnMZj29fgmU2M9SoXg1VKldWm0++tsubsmVNjN1btuHyzfsIzl0VSZZ2UDbGkYHCStKoTk106tAuw2xUpIzs3bcf165dR16vYihQrALyFigKMzP5rSvKDGBPDUlSEvw/vsVL7zt4/vgm8rjnRtcunRWSn2/b8jyqP+zbtx8fP/mL82JFC6NunToa7Y+2j2uM5tELZeSff/7BzZs3MXnyZPF83rx5qFy5cqqD37///it2kh4+fIigoKDvBtEVK1aIzCmjRo0Sj3PmzEGXLl1Qu3ZthfrEg6h+oAuDqCZlbdeevTh04SZirZy/XkiMR05JEBbMna3RatKkgFy7fh3//nsTphaWIvi4cMlKsM6eQ+7aD4H+H/Dswb948fgmctjaolq1KqhcqZJKFRNtlzdlylpISAjm/7oYHxKy44trWUBJKWtTJSkBdn634JldggljR8PGJu3MXMkD2O/fv48bN2/j6dMnsHNwgXv+YsiTvyhc3T0Vtpwoktr3W2iaDgn8JOqQfHj9BB98XyB37tyoWL4cKmVSJr+VNZ5H9YMnT55gzfrNqN2sq7D4nt6/HrNmTtfoBpG2j2uM5tELN61z586JHRx7e3vxvF27dti8eXOqgygNrsSbN2/EIJoc2t29evWqGDjJb5yOpk2b4uzZswoPokzmOHb8BO7dfyDOXV2c0a9vH013iUmDc+cv4OjZywjJ1whItjD7FPBYLDKnTBinkK9+VgkODsbly1dw5epVGJlYoFDJSmjVeyyy234dF1KDFJG0FohOrrnh1LAdqjVo+3/F5DqOHpsDJ0dH1KpZHRUrVsxyxiZDhZTFOfMX4rNDScQ7e6r+A41NEZq7Cp4GPcfEqTMwc+okODk5pfsWkl36G9NBysD79+/x+PFjPPz3GI7seA17J1fk8igM9/xFkCtPfuF+pSzI8kEy9+71M/i9fQq/d6/h6OSI4sWKoW2LhvDyGqL0Qog8j+o+9NuvW78RDdv2R073fOJa9cYdsXrNWkwYP04rkjAwjF4qIxEREWIw9PT8b0Kj88DAQGEqljeYj/j48aMwVX97r3379qX5Htq1Sb5zQ//s0gUK/+MrPpBSFptWPUfC2MgYp/dvwNu3b1P8PRjNQwuzfQcO4tCpCwj0rJdCESGinIvDx/8Bps/+GZPHj4WtbeYDkTOC/sdpN/fCxcsIDfuCwqWroFm3kchhn/5CM7nrDLF15Zw0XWfo/9g5pzucc3ZA9Ybt4f/hDW7fu4p/du9FQS8v1K5VAyVLlkzVnYX5HspgNmveL/jsWgWJ2TMRl5OUCKPYiK91R4wV+81jHAvig0k2TJ89Fz/PmiFbeGcEyUCePHnE0aRJE/E/QAoV7UI/vncOp/ashq29E/LkLw6PgiWQM7cnjL6x9JD1jZReekyNsJBAvH72AO9fecPv/SvkdM2J4sWLolqrJqIauyqqsEvheVT3IZfZv1ethleJSjJFhChSqjLePLuPPXv3oWOH9hrtI8PorTISE/N1MZF8sJRmwyHfX0UGUbqXhYVFikUFvZ/ukxY0wO7evVv2PF++fFiwYAGcnVOfcJi02X/gAAqWqAAXt6/FvEpXaSB23ydPqqrprjHJFi3L/vgLz/y/IJgCjdOo/xDhWgovgl5g/ORpIng4MylW04IWLffu3RMF6F6/fi3iPyo17AzXXB4KLVwyU/uB7k8TPR21m3bBm+ePcOz0ZaxdtwFlypQWxegoUJoXUKlDY+ncX37FZ5dKmVJErO9ug1FSPIySEpFkYoHIct0VvkeCXR58kiSKfvwyd1amFvn093V3dxdHw4YNhXJCi/CHjx7h7sX9QlHxLFgChctUg7tnIdGe3AC/tb6FBgfA+84VvPS+BXNzM5QtUwodWjeBl5cXTL9xG1QlPI/qviKyZOlviEk0Rc06LVO8RrLXoG1f7N+4GG45c6JjR8VjdxhG1ei8MiL1S6fdG+kOLJ0TirpQ0L3IT5gykkgHUrpXevdp27YtWrRoIXsuXYSQryvtDjHyQb/7tm070L7fBNm1wiUrYtOyA2LhqanMRm5uihc401du37mDVWs3INiuMGLcS2dY/yHW0Qt+Vo5YuPxvVK9YFj27dcmS2xal4yU3vjt37oqA4sJl6qBOuyEZBiSrCmMTE+QvUloccXGxeOF9B9v+2Yew4ABRiK5Bg/pyxSYYEqvXb0KAZV4k2mbu/8ooKUEoIuJckvnxNd7eE36fgrFt5y707tEt0/eR9cvISMRw0NGkcWOxIKdx6/yFozh/aDMq1WmFQiUr/jc/fHqPqyd3ISIsCHXr1kbXNhPkttKoAp5HdRf6rVf++TdiEk3QsF3/VDdCKPlCq56jcHDz73j3/j06d+qo1nGT51FG75URmuwpMIt8V3PmzCmu0TldU2Q3RxpkRYMnuQblz59fdq+8eb/u1KcG7aqltbOmB7kB1MaBAwdRoFg5ZLdzSLHYq9awHdat38D+rhqEAlD/Wr0OT30/Ici9jkL1H5Isv6ZYPf3kIW7/NAFDBvYTLk2KQP9H23fsxK3bd1G2ehP0HtURZuYW0CbMzS1QrExVcUSGh+HhzQuYNGUqunftgipVqmi6e1rBy5cvcc/7GaLyN4E2EO5SCheuHEWj+nWVvliiBTn93ekgJXrT5q24f/00bO0dkRAfj+DPH9CzRzeRiUobxjWeR3UTcqNb+tvvcPcqjVr1WqcrSxYWlmjbZyxO71uPXxctwbChP2i0phLD6JUyQtSpU0eYeaWuIHRev379VNvSbg0dZNakQY52FWiHgEziZFquVq0adu7ciZEjR4pFGKUw7Ny5s5q/kWFBE9Xlq9fRbdjM714rWLwCnty9igsXLoi/M6M+6H/k9Jkz+GfvAYQ6FkesZwP5q2Enx9gEETnLICraA0tWbULxAnkwqF8fuWNJKDD90qXL6Dd2gVKVkKZNmnxTiM5aKYXoKGNXlXqthHK9bfNvrIz8nzUbNiPYmSqqa8aS9R3GpghxKoX1m7eJ2CZVQYrO+HFjhTIm3eWnGApNZptLDZ5Hv8ff31+kLyaLLm2iaMoKmxo3btzAlq3bUat5N1m9pIwwNTVD4w4Dce/6GUybPgM/DB6EQoUKqbyvDGMQqX1pgN+wYQOuXLnyXX70VatWiWuDBg2SpS9M7ptKFCtWDDNnzpSZk+k90vzoFKzI+dFVG4MwfcYsNOwwEG7uX3fRviUqMhw7/56LMaNGwMPDQ29SEpJ8rF27VqTHDA8Ph4ODA1q1aoV69eppXNYoyPi3FX/iY7QxQl3LQWKmpKxREgksgnxgH/wUPbt1FjEWGe0M0xC1Y+c/uP7vTZSoUBuFS1WCrV3W01QunTZQxI0osxAd9fWzny+e3ruKF9630aN7N5EOWF/kLbOyRp+5ZM02BHqmvriVF5vbm4SrFiEhJbd87yzLo/OrY5j+0wiDS5SRWp0Rnkf/48uXLxg3aQqirNxgHBmADs0bomXzZtA09Nuu37ARH/2D0KTDoBTeBIpA49TxXatQqXxZdOjQXqUxSpzalzEIZUQbYWUkY2g3bd78BShQsjpKVqyVblu/d69wYtffmD5tilhEqQtVDqLkV37gwAGR7pJiYqg6+Pz580Vu/tKlS2tM1s6cPYdtu/YiyKUcEu3yQBUYxUXBwe86irg7YcTQH+RyBaFsPxcuXhS1QxKTJMjrVQLu+Ysit2dB4YKgqUJ0EeGhePfyKd6/9obvyyci6LZGtSpid1jR3W9tl7fMyBrtno+dOAWvbEsjyTrjLGdqVUYAmIR9QEmjd5gzYyoMCV1YIGpqHiVr7Ox5v+C9lRdi7fMDCXFwenMKXds0R6OGDaApKA5pw8ZNKFW5AcpWbfBdxjZFobHv6ul9+PDqkbCSUOIAQ5U1RrOwMqIiWBlJH9qFo+wf2Z09UbV+G7ne8+LJXfx7eg+mTpmktxWxFy1aJNKHpubSkFb6S2UFeZLbxcpVa3DryRsEuVcDTFXsRiKRwDLwKVyiXmPapAkyX3V5C+bRbvuDh4/x/LkPzCwskdujENw8ConsRd8WN1RWITpRfC7IHx9e+8DP1wcffV/AwtwcRYsWRelSJcRjVmqPqDvQMy15U6asnb9wAesOnEWwe40s91cVygjJodPbsxjRtzPKlZXP3UUf0IWgYk3Mo//+ewNrNm5GkHMZxNsls8QnxMLx/WWUzJ8Lg/v3VWtyCvIg2LRpC975+aNRuwGixo0y+fj2hSiOWKlCObRv307paaRZGWEygpURFcHKSPoWkd9+Xw5LOzfUaNxRoQDOp/f/xe2LhzB5knqyz6hzEKXfZcSIEejTp0+qcQbfukZI018qA1pgTpwyHXc+RCAsZznF/fqzUPvB5Isfcgbexoqli9INcs0okJOqZd+/TwrKQ8TExCKXhxfcPAqLzFvZc6RuTUuvAjtBw2OQ/wf4vnqCT74+ovgcWRVKly6FMqVLoXjx4jqbMSs9eVOWrNEiqluvfviYpy4k5tbaqYxQ+Eh0KPIGXMf2zRvUWqiT0Z55lIparlq3Eb5BkQh2q/R1LPsWiQTZAp/CLtQH7Vq3QMP69VWegplc3TZu3oLSVRqibJX6cllDMhrX0rKSXDuzH+9ePBBWEmnyAWXAygiTEayMqAhWRtL2d120eCmc8xRGlQyyf6TF88e3ce3UbhEUqshuujYPovRvuHz5crHjP23atFQDJVVpGVm9fgPOP3qPsFyVFA5SV0btB5PwT8gVeBu/zp+rlMU9yZmPjw8ePnqMR48eIy4+AZ4FS8KreAW45S2QrtwlJMSL+iGvvO8IJcTF2RklSxZHieLFxQStysWHunarM5I3ZcnaqrXrcfp5KKJcSiil36pSRojsfrfRpnJBdDaQwnBsGflPCdn2z248ffkGwU6lkZjDPcMx0Cg+GrYBD5A9JgAd2rVG7Zo1lT4ukFvl+o2b4PveD43bD4Sdo4vc71XU4vutS/SpvWtRtXJFtGvXVinFXFkZYTJCJbMqpTK8du2a8LscMGCAKABFE5i6g48NGVpsUJAqLTK0ZeeWfP4XLlqMouVqo0yVzAeyFixeHhbZrDD/l4UYPmyIKDKn63+rNWvWiP+btBQRVaa/9Pb2xpVbDxCWr3GmsmUpo/ZDYvacCIgpgL/XrseYEcORVWjhTHEQ0lgIyuhz9+5dXLt8ECc/f0aJinVQulLdFNm5wr+E4M6l43j++JYIxq1fswJKDOkjsgMlR9f3b+SRN2XIGmUiunbzDqK8mkMXoFS/J04dQeMG9dXmBspoBpLhJ0+e4J99B+H70R8hDsWQUKD59+NfGhZfSugRlqsyvsRGYMPRq/hn9z40aVgfDZVUW+jVq1dY8cefKFq2BjoN6JPl2BBFcMuTH12HzsCl4zsxc9ZsjPhxOBefZHRPGbl16xZWrFiBcuXK4fbt20IZiYyMFGb/qVMNK0BQk1y8eBFrN2yCJCkRM6ZNFRV9NQkNrsuWr0CNJl3hVSzrftnketOy+wisWLkCnTu1R7WqVXV2UqQMRy9evBALQ0Vz+mcVCi7+mwoZulUCNJy2MsapMB75HBeyokwXAYIWl5S6lA6yBhw9dhxbVsxAqcr1RLrLiC+heHb/Klq0aIYf+i78TgHRF9Qpb7v3HUSYQ1GF3fY0hokZwu0L4vDR4+jeVffS0DIZQ2uRC5cu4ejxU4g0yoYQu8JILFA+zU0YUkRsHu1BRIn2kFh+r6CSkhKaqzLC4qOx87oPDh8/iVIlSqBF00ZiDMuM5f/MmTM4dOQ4mnQchJzuqgkozwgqklivZU+8fHIPc+bOQ7++vUVNHIbRGWVk+/btmDRpEgoXLoy+ffvK/I2plgSjPo6eOouwAo1gEhOKk2fOa1QZuX79Orbv3IVmXYbBNZfyrGNOOd3RaeAkHNi6DO/ff0CH9u20Kg+8PNDC8NmzZ5g+fbpGLFg3btxEqMQSSVZZT5WbZYyMEOxUChu37sCsaZNV9jEUa9S9W1dRJZ02T4A4OLhYovfPc7TGiqjr8kZKz9179xBXsKVS79u8WVO0aNb062cA2Ps4FPtvvFDa/WPsC+DK9bOsjOgRtOHy+PFjHD15Bj7PnyM6hycictaAxCK70j6DLCWRrqUR6VwS5/3f4v7yNbAyikfDenVQp1ZNuSxt1M+Nmzbjta8fugyeimxWmi9IWKBoGTi55saWrcvx0c8PzZp+/d9jGK1XRsg1ixSR5JDPIf2jMeqBKt8GhEYgqYAjkixz4PbdwyKQVN0LLfqb79mzF7fuPkDHgZNgk91O6Z9BWZM69p+AU/vW47ffl2HokB+0rphYev7QJ0+eFO4wQ4cOlV2n/P7SfP6qhLJnbdn5D0KdtceqlGibC+9ePxLxHqouxuXu7i4OQ0Gd8hYdHQ2JiZkoLKhMjhw9hqOHD6kkZkTc0ywbYqJjlHpPRjNQLMipM+dw7d9/EW/piBAbTyQWaq3aopvGxkhwyIcAh3zCqrLtyjMcPHoSudxc0bRBXVSoUCHVBAk0Fq/4YyXikA1teo2GcRbiNKQpy4mtK+dkOmW5lBwOzug0aDIObV2OiPAIdOrUMUv3Yxi1KCMUFEc+6ORzLYV8M3Pnzq3sj2LSYN3mrQh2/H/AqLEpIuy98M+efejXu6fa+hAbG4uVf/6FmERTdBwwURSVUxV0bzJp37x4FLNmz8FPY8fA0VELdvozgPxwyX1RUxw/cQphpvZIslS+kphpjIwQ5FIWf65eh8UL5umcpUubUae80YJLkhAnsg9lJg5JY0iSdKq7TEooNvXK1as4cOQYwqISEJrdE3H5mgGmis8/0sQchNWTwwon5iAXrijX0ohyKYXAyAC82XcWFpu2omKF8mjdopks+YqI4Vq3Hgkm1mjQsmemXLuSQ4VcKTMWIX3MKuYW2dC61ygc3Pw7rI4cRQstKP7I6BdKn+m7dOmCX3/9FZs2bRIDw7Zt2/D777+L64zquXHzJnwDwr9mBPk/UU5FcPn6TbFTpA4oWHj2nLmwcswrlARFFRFKS0jZQOhRXmgAr1S7OcrVbo05c39mt0A5gov3HjqMUBftq6uQZOOCANhg7/4Dmu4Kk0kos1DuXLlEljRdwjTEF0WKFNF0N5hMcPXqNQwbNQZrDl3Cyxzl8Dl/Y8Q5F86UIqKsxBxf32wkxrTQXFXg79USJ1/HYvLs+ViybIVIMnPhwgV89A9GvRY9sqyIqBKKrWvR/UecO38JT58+1XR3GD1D6cpIqVKlMHPmTJGOj3LwU8DY5MmTxTmjWmhgW7NhE4IoGDn5oGZsiuCcFbFk2R9KKY6XHh8/fhTWiZJVm6JynZaZGlwpPzqlJaRHRSlYrByadh6KJb8tE3UnmNTrS/yyaCmCXCsCptoZqB3mWh5HT58X8Q2MbtK7exc4+N+m3QWl3VNibCrcs8S5kZIN+wmxcAi8j+6dOyj3vozKOXTkKFbt2A8/93oioDzJUvU1qDKFiSninAoiwKs5rvpD1Hbas3c/GrUfoNaMWZnF3NwCjToMwHpKjqPjWQUZA0jtSyl8+/fvr4pbM2lAA8Pvf/yFYPuiqQbmJdq6wT/iA7bt3IVe3buqpA9kjVj62zI0aNcfefKljBtSJ665PdG+33hs2LgEHTtE6WymLVWxZv0m+Bs7ITGHFrtOmpghKHcNoUAv+uVnZM+uvGBTRj1Q0owWjerhwLmLCM5bWylZtSLLdoNRdJjIcBRVtAWURmI8HH3Po2vHdlwTQQc5f+kKgnOmUahQG5MlGBkj1qkIwoOfo0zJsrC2sYWuQElostnkwMuXLzWepZPRH5SujJDJMS1q166t7I9j/s/J06fx3P8LYvOknX7vS86yOH/1OCqULZ0ipkdZighZI5p3GSqUAU2Tw94JHQZMxJ51vwq/9WrVqmm6S1oB1dq4+egZwvM1hLaTZGWPIPsiWPHXakwaN0bT3WEyQdvWLUUBytPXzyEoT61Mu8yoEipgR4pI28b10KBeXU13h8kElEp3065DCMpbW2S20oVkCdkCfWBtLEGeAsqdi9VBLo/CIgU7KyOM1iojR44cSfE8NDRUuA/lzZuXlREVQcXL/tl7EMH5MyhaZ2yCoNzVsGzl31iycL7SagxQ/MFSLVJEpNBuU/t+47Br7QLxXQ09TzplN1uzYTOC3KorNaOMKncQYx0Kwuf1KeGu9W2WPkb7ITfNHt26wMnJEf/sO4ygPDW0yoXGOCIATh+vok/3LqhZo7qmu8Nkkrq1a8PYyBibtu9EkEt5JNrlgdaSEAN7v5vI75ANbh4llX77pk2aoEmTxrL/v3gLa7wPiFT65zCMVisjCxcu/O7agQMHROo6VUFxEBs3bsTly5dlqSp79+4tUgor2vaPP/4Qr1EAphQqDqbqNKNZWWD+tuJPBLmWB0wzTmlLC4EQ2/xiUTpi6OAsf35MTAwWLV6Keq37aJUiIsXKxlakSly3biEmjncxaBcM2smKNrFKtXiX1u4gGhkh1L4wTpw5z8qIDtOkUUN45s3zdazKURgxjgU1m2VLIoFVgDecot5i3ISx8PTUvrFL3ej6PEp1g4oULiRcOz9+eI/QnBWEu6c2YRL6Do6fb6Nj29Zo3LCB8CS5/+yZiHVUFseOH8fBg1+Tf1DymDFz10DZ+L19hvpV2yv9vozhopaIqZYtW+LYsWMqu//evXtFdoclS5aIg1IJ79u3L9NtGzdujM2bN8sObVVEiAsXL8Iv2jhF9ixBUqLwrabHb4lyKop73s9EFeassn7jJhQqXQ0eXsoxNVOO9I2/T5PlSFeWy1b9Nn2wbLnqA/i1maCgIMSZ6l7sRVI2W/h/VjyZAaNdUJYqiv8pmyNKuEWRe5QmoPoPTm9Oo2ouM5E+mhUR/ZlHXV1dMX/OTLStUQrOr47DOCoYWkFSEmz9bsMr9gXmzZwmlHOyWlSuXBkvvG8jOjIcukLAp/eICg9FgQIFNN0VRo9QizJCBcxUyblz59C+fXtRWZmOdu3a4ezZs1luq+1QLY8du/Yi1LVsqhMuBXnS4/cvGiPYpTz+XrchSxkx6O/65u17VKjRBMpCFTnSCY8CxeDiXgAnT56CoUK1fixiAqFrmEYGIL9nXk13g1ECVHh10rix6NOuMVxen4BZ8Gv1fbhEAosgH7j6nsGQnh0w6sehOlMgVR3oyzxKtYnatWmNiaOGwe3TVWQLePq13o2GMrcZxXyB0+sTqFs0J36ZO0soTFIsLS3RolkznD20WSeyU1G6/VN716JXz+5anYaY0T2U7qY1fvz4FEJKC2aKKejRowdUAVUWpx3f5LtbdB4YGCgCJ5PHRcjblkyndNAgW7duXTRv3jzN4muUwpgOKfTdaYCRnquSEydPIdzGHRJza4Xfm5jdFYHB3njw4EGmYykoJWH1xp10IiUhUaV+W+z4cxYaN26Uwn3AUKBq43lcHBAa9AJxjsoLPKRJm6JFKCe/stOt0u65XbA3WjWfodT7MpqDxsU6tWqhVIkSIgPgG993CHGrqLTA41Q/MzYCDn7/okgeZwwd/zNsbXUne5E60Md5lNw6F//yM1auWgPvV6cQ7FoOSdZO6svclhgP68AnyBH+BkMG9UfZNOZZmo8ePX6MWxePomLt5tBWSFk6fWADypYqjpIllR/rwhg2Sl+RNWuWsjIn7TzRQCWtNqpsKGaBSD5YWlt/XZxHR0enuC5P26ZNm6Jnz55iB4/cmJYuXSoGwxYtUh+MyDS9e/du2fN8+fJhwYIFotqxKqHvcuT4SUR4NMr0PYKdSmLbP3vQpEkThQd8SkwQEBio0RS+imJlnR25PQuLWihkHjdERv84FJOnz4KfsSni7ZXjnqKqdKtGcVFwensW/Xv1UPn/E6N+HBwcMHPqJJw9dx7bd+1BsHMZuWSS0rdGlGgvXxpXsoYEv4R98GP069UdVatUUU7n9Qx9nkeX/roAd+7cEbEkQcFAUI5CSMyeU2UxS0bxMbAKeY7sYa/QrEkj9O01O8NkMXPnzMao0WNxP5sVSlfOWkY3M3MLoTiQZ4GiBYfTgu538dh22FmZYPToUWkqlQyjNcpInTp1oE6kZnbakZHudtE5Id1ZUaRt/vz5Ze3Jx7VNmza4ePFimoNo27ZtU7wmXdQHBASoND5hz779X60iZpl3M6BdIv+gJBw+cgQVypdX6L23bt1Cbs9COmeqzZ2viKjUS9nd5MHNzQ36RI4cOTB35jTM/eVX+H0KRbhrKaVm1lIWVLnb0e9fDOrbE5UrVdJ0dxgVQeNH/Xp1UbpUSSxd/gfevf+IEDcKPE5nEWVsIlcSBloU2vtdh5eLLUaMmytknzHMeZTG8YXz5uDhw4fYvf8Q3r+8jbAcBRBrnz/dwq9yK74SCUwi/JEj7CUsogPRqEE9NG08SChjYWFh4siI8ePGYt4vCxAXG42KtVJu6irC8GkrEBTgJwoHdx/6Nf4yq0lyzhzYCDNJNAYMHyY8XRRF3+ZRRkuVkaNHj2bKaqIM6J/d0dFR1LmQWl/onK59uxuhSFspGS22zczMxJEaqvIBDQkJwdETpxCev2nW7+VcBus2bkHJEiVgbm6uUB9scshv8tYWsts54v0TH53wz1UV5DZBQZ7rN23Bv/dOIMitiqjpoRUkxsP28304J4Vg3NSJIs6F0X+cnJwwZ8Y0HDxyFAePHkdQrqpIssn8rrjJFz+hzHbp2BYN6tXTuU0TdWMo8yi5F9Hx+fNnHD91BpevHEecpRNCcxRAoo3r99aSDBRfciPNFvxSWEHcc+VEy67NUbZsWVlWMUX6TorclEkT8dvvy3DmQCDqtugO41QymamT2NhoHN3xJ/LmckHfPv2FRcSQ505Gy5WRmzdvakwZkVpjyMxL2VoIOq9fv36m2l69elXEUNDAQKlQKS0xZQXRqlS+y1cixKlUujs6ct/P0g4h2dywccs2DOzXR+730WCblKh7mamSEhJgquEBXhsgxXPwgH6o8fgxVq5ai1ALV3xxKaW5VJgSCUxDfeEQcA8N69ZGh3ZtDDKux5ChhU6bli1QpmQJLFzyOwJivBDjWEgxdxqJBNYBj+Aa54cJ0ycbdCpvRTGkedTFxQW9undF9y6dcO/ePRw8dhLvX95CqF1BxDl4CSUkPYyjgmAX8hTZooNQv24dNKzfW2zyZBWyOo37aSw2b9mKPet/RfOuw4R7sSYIDvyEw9tWoEG92qJ2CSv0jCpRymw/Y4Zmg0spqwcVVhw9erQs5zmZfYlVq1aJx0GDBmXYljhx4oR4D9VFIZ/mRo0apWla1gRbtu3Aq7BExLn/ZwbPKuEupXH17ikUvHARdWrXkus9tCN2/fYj6FrBJjJfu+X8L5uJoVO8eHH8tmgB9h04hBNnjiDUsQTiHAqotQaEcXQIHPxvw8M5B4bMnJoi2wxjeFCMIaUAJoXkxccbCMtVUT5XwqQE2H+4hhLu9hg5bA4sLLK+WWNIGNI8mnxTrXz58uIga8m+g4dx49YhhDkVRywpJd+Mg5QZy+HzXdibxaNLp3aoWKGC0uMnqE99evcSaft3/j0XjdsPRC4P9VY693l0E1dO7MLAAf1QokQJtX42Y5gYSdjmphLI1zV5dhBlsGvPXhy5cANBHnUz3LmRBhQLf1c5/aud3pzCgJ5dUa1qxkGecXFxGDN2HPqNXahUU/LSaQNFel9VFWzat2ERenfvlMKnOT10YWdVWbIWHByMtRu34MnLtwh2KScyrsmLovIm3hMfA9uA+7CLD8aAPj0zndVNn9B2eVPFuJaeFXj1ug24+ugVgvPUTH/MS4wXtUsaViuHbp078S6uHsiauuUtuQvy6nUb4e3rjyD3GjIPBIuQl3AMeoy+PbujcuVKapExX19fUR+LanlVrNlU7syV0piR/j8tgKOz/PEaFPR+8dgOhAW8x8gRw4UiaSiyxuiZMkJp/7Zt24bHjx+LnZPkt1+/fj0MBWUOojQpr92wCVfu+yAoby1ApFJVxeIwGo5vz6JTyyZo+n/rRHrQIOlWsAIKFlcs+F1TysiX0CAc2LgYi35dIPdEYogTNmW/+WvNegTEmSLEpax8WYuoyGZsxNe2GSjKVADMMugpbEN80LZlCzRp3DDVKs+GiLbLm7oXhzR/bN2xE6f+fYjgvLVTt5AkJcDxzVm0bVQLrVtq3+67tqLtsqYpZUTKiVOnsGPPQSC7CyQJcXAyT8T0KRPVnhaaspetW78RH/0D0bjjIGS3tZerHkhoSADs7J1hIqe7KxUzPP7P36hcsRzat2+n1DFZF2SN0SxKd8peu3at2FmguiLLly/Hjz/+iIMHD6IKp1TMtHL369Lf8TIMCMtbhxyrM3yP9d1tMEr6OoBbPTmMyHLd5fosyvMfmK8hdh47j5dv3mJw/75pBhUSLVs0w5+r1sGrWDmd2Im8dfEImjRppBN91SReXl74df5cXLp8BVt3/IOw7J6IdC6evpIhZ4YjCiwml6yKZUqi5+RfRDAsw6QF/a9279IZkZGRuPTs9leXreRIJLD/cB2NalRgRYRRKo0bNkTRwoVlmcLIfVATRTLpM4cOGYxr165h++r5qNG4EwqVqJDue0gBkdciQgr/3aun8PDGWQweNEAWB8Qw6kTpOT0fPXqEMWPGoGLFisKXkh5HjhyJS5cuKfuj9B7aoR43aSq8Y+0RlruyXIoIYZSUIArQiXOJgkHmJubCDezq6zBMmDJd+NGmBeWCd3V2xLMHN6DtBAf44f2rJ6ir5tTTurwIrFWzBn5fvBCNijrD+eVRmIQrntJRRkIs7N9fRcGYZ5g5cYwoAsaKCCOvLA7o2wfuFjEwDfFN8ZpF8AsUdLZC104dNdY/Rn+hFPC0OKdDE4pIcqpWrYoZ06bgyc3TOLl3LeL+70GQFSLCQ7Fvw2JEBLzGz3NnsyLC6I8yQgFr0kUGBRBSESRK+efn56fsj9JbyC2LAornLVmOjzmrfs0oo06MjBGesyxeWRXG5BmzRV2OtOjVszuunt6D2Oivu0faCO38UJ70nj26cYYmBaEJuF/vnpgxYQw8vzyArd9t4ZKlCCZh7+Hy6hi6NqyMBT/PlrvGC8NIIZeRMSOGwSHgrnDLEiTEwi7oMUYMHczWTsYgoLXUtKmTUdAjJ3b8ORuf/VIq54rwxucR/lk1Dw3r1cCIH4dlWJiRYXRKGXF3d8fz58/FeYECBUT8yPbt20UeeSZjvnz5glk/z8e+i3cQkL8JkqwcNdaXxBzu+OzZCKt27MeKv1aJoPVvoQq5jRrUx4VjO6CtPLx5Ac4OtiL/O5M5PDw8RIajhiXd4fTqhIgPyRBJErJ/uoMC0T6YN3OaiEPiyr1MVtKxVqtcEdmCvs4v1kFP0bRRAy5myBgUNIa2bdMaPwzqj6Pb/8DjO1cUer8kKQnXTu/Hv2d2YcqkCahZo4bK+sow8qL0lUG/fv1kVVh79eqFjx8/CtetgQMHKvuj9I7Xr19j/JTpeBzrgBD36pqr+ZAMibkVgjzr48rrL5g4dQaCgoK+a9OsWVNEBH/Eyyf3svx5ZuYWInCdkD5mhdCgz7h96Sj69ZW/hgqTOmRV6tOzO4b16w7nt6dFrv00SUqAg+9FVPXMIawhnK6XUQatWzSDpd89uHy4DAv/x2jcsIGmu8QwGoEq28+eNQMvH1zGhaPbhZKREfHxcTi0/Q8kRQdg1swZPC4z+ptNi/KO16pVSxxkUjRUFM0CcvfuPaxYtRaBuasjyTprViSb25tE3AghMTZBRPneUAZUlM4l8B6mTPjpO1cbii2ZO+8XdB48FdY2Wcs2ktm0hN+SlJiIf1bPR+cOrTNtFVF1FpCEhARs3LgRly9fluXr7927t0KZTDSRcYYU53m/LsHn3DWRZPVN+sekRJFmtXH1cujSsQO70GiJvOmqrH0LbXBRUHH27Nl5MaXnGY60Qd60Hfq/Xr1mLUIi4tGkw8A0U+3HxkRj/6YlqFiutLCsqHNc1gVZY/TMMtKxY0c8e/YMI0aMwOzZs3H+/HmRmo5JG7IcLV+1DgEe9bOsiKiSBLu8+JSzKub88ut3MUDkQkFVs0/uXp0inbMmuX7uAAoW8NRq96y9e/fi6dOnWLJkiTiePHkiqhlrO5S8YOLYUXB6f0nUC0lOjk+3UKtcMRFUzIqI9qCrspbawoYyvrEiwjBfLdY/DB6EnI42IrA9tfmX6oeQIlKnRlW0a9uGx2VG61B6NG+1atXEERYWhitXrohKrJTut1KlSiLNL5MSSlm5bOXfCMxbV756DnLQvFlTtGjWVJzTsLT3cSj233ihlHsn2TgjwLWiqI68eMG8FDEAZA27/+Ahbl8+gQo1m0CT+L56irfP7mLO7FnQZs6dOyd2p+3tv+aOb9euHTZv3owOHTootDOW2u4hTTjJA/bT22HMTFuKCevaoS22Hr2IEPdq4jWTLx/gbhGH7l06iXt8e1/qa1rKqiJtieRppzXVlvorndgpeQcln1BGW1Wgy7KmbPlhWWP0CfpbU9X25Sv+wM0LR1CpTso016f3b0C5UsXRuHEjjfWRYdJDZamFKKiwWbNmIlXcjh07hGsAKyPfc/bceVHHQZJNeYWUjhw9hqOHDyndTUtKom0uhHx5KSw6pUqVSvHagP79MHXaDOTOVwhu7vJVOVc2UZHhOL1vHSaMGwtz86zHnaiyhgzF4FD+eil0HhgYKNxQvs1uQou25As3moAoPovq+Hz69Om7++fJkwdNm35VSoktW7aIBU9quLm5oWXLlrLn9D+blkWTkha0bdtWnDeoXw8+z57BzOzt1xeFPu2OTZs2iae08CVrqZT9+/eLOkSpQVn4unXrJnt++PBh4aaRVpYvikmTcvz48TQz9tHCjGLZpJw+fRrv3r1DWgwaNEh2TpZdcklLi759/6vFQ2Ocj49Pmm179uwpi6e7fv06vL29v2szY8YMqAJ9kDVi165d4rukBsuadsgaoxloY5AsJJOnToNnoVJwyfXVlfrZw5tIjPmC9u1/0HQXGUa9ykhwcLCoK3Lx4kVxXrlyZR740uC173vEZvvG514HCDe1E77b3yojNAH+OHwoflu2Al1+mIZsltZq7RcF8VEV2XZtWiF37tzQZqQLsOQLQWvrr78XpcT+doFILjW7d+9O4Sq1YMGCNO9Piyha+ElJzzRPSlvytullvaIFUfK2trbZRX/TWpwlb5teamWKXUjeNr2Cm9S/5G3TUzrpeydvm1G9gORtpQu6tMiZM6fsszNqS25F0r+vutNo6ouspRffwrKmHbLGaA4qp9C3dy9s2roeDdv2Q2JSIi4f34np06ZwJkPGsALYKU6EYkZKliwp3HYqVKig1bvTmg68O3HyFDaevo1wt/QrqmpDAHtynN6ew/jBPVC0aNFUXz958hSu3XqAVj1GKOyfmpUA9n/PHUJipD+GDvlB6wPvaIeXdlGXLVsmFhoE7TpTvNWGDRvk3q2mXVp2ndEP1xlV1WBhWct8W4JlTTNwAHvm2LxlKz58/CjOS5UsiWZNNes2zQHsjNotI+XLlxcV1zn3u3zUrVMbh4+fQHToOyTY5YEuYBngDQ8nm3SrtTZs2ABPnz3DzYtHUal2c7X0683zR3j5+AbmzJ4JXYBcRSjj3Js3b2QLRDqna6ntZtLCJbUdXFp4pLWISX49o4KPmW2bUTYmfW6bvD3tPGa0+6hIW2XCsqb7bXVF1hjN07NHd013gWEUQukjVPPmzVkRUQCyGs2cMgnuXx7DKuAxzSBZvqfE2FRYRMS5kRL1zaQE5Ph4AwXNQjBh7Kh0LR702qCBA/Dy0XVR6VXVhAUH4OyBjRg7ZpQwVesKderUES4xoaGh4qDz+vXra7pbjB7CssYwDMMYhJuWJlAkf35GbZWRiz8z5mXy2/5rzTo88HmDYNfyWU7xaxQdBptHexBRoj0klllXDk3C3sPB/w7q1aqOrp06yP17+Pv7Y978BWjTeyzsneRLxZmYkIDQkADY2TvDJINdUyIuNgY7V/2Mnt06o0yZMlAm6qgzQm4ylHlOl2s/MLpRZ4RljUlL1vRhHmW0E3bTYgxCGfnnn39w8+ZNTJ48WTyfN2+eCJpPLWVlRm0VuZcqBlHKerJq3UaESCwR4lQSkmyZVCSSEmEUG/E1XfD/rSSZwTjiMxwCH8DdwQaD+/eBu7u7wvegrFtr129C50FTkM1KuQHt5At9aOsylC9VFC1aNDfIQZQnbP1B2+WNZU1/ZU2f5lFGu9D2cY3RPHrhSEr589u3by9SO9JB+fPPnj2bqbaK3EuefPzfHt+mu/z29YIFC2LBz7MxsG1DeARcg8O7yzCO+pqe0gRJaR7GSBmgaGJsBGPL7OIxtfYp2n77uiQR5uEf4fL2LIrEPsNPg3pizoypQhFJ63t9G/Ca/DcoXLgwmjVphMPblyMuNhqJCfHiSE5SYoLsempHWm0vHduBnE450KhRQ1kfkuvXFLyZXn8zasswDGMI6NM8qqy26c13qmqb1jyq7rY8jzJ6UWdEXSiSPz+jtrTLrkguflXn429Ut7ZI0bht116EBZqifGEPWKRh5AhJNMel6P9S2da1+gAr49Tv+yXRDOej/7Nw1LT8CFuTbwaM7JR3Mp8IfC1RooRS8vF75HbF/XM7xLmxiSnKN+wpe+3FvXMIC3if+pcDULFJX9n5qweXEOL/Rpxb/f/3IJcAVeTj55TUDMPoO/o8j3JdG83XteF5lNF7ZUSR/PkZtZVq9/Lm4ld1Pn4KxG7Tpg1at26N27dv4+ChQ2o3ZqkqH78q4Xz8DMMw8qPP8yjXtfkPrmvDaCs6r4xI//lox8XW1lZ2nto/UEZtpbnY5bmXFNpFadGixXeDYqtWrdLMx598l6NHjx5pfrfkbamA34D+/fHq1Svs2LUXvv6BCHEsIaqhE98G/pyLkqPgn0QCs+BXeBLsjRJFC6ND21aytJ9p9bdJkybp5sJP3pYy9Xzbln6TBQt/RYFS1VNc9ypTN937JsfKMQ+unD+OSRMnwMHh+4KRtAMn/TtQnZty5cqlea+wsDB8+fJFnJcuXVrUx2EYhjEkDGUeJTp37ix3W3I1S69WTfK2ZH2Rt21W59G02lKigBo1asjVtkqVKiKOJy14HmXUic4rI4rkz5enrSK5+DWRj79QoUKYPmWiUErWbdqKD2+eIdi1HJIs7VO8LzEDC4rJFz84fL6DYgXzoeePk8XOhjry5tN3GDtmNGbOmoMc9i7IW6CozG1LHr6EBuH4rlUYO3okXFxcMuwH5+NnGIZJH0ObR/Wp/gzXtWH0AWNDy5+fUVtdycWfP39+zJ05DaP6dYG7/1Vk/3RXZNDKkIRY2L+/ioIxzzB93Ej8NGpEuoqIKsiePTt+Gjsap/etQ2jQZ7nfFx8Xi4NblqFPrx7w8PBQaR8ZhmEMCUOcRxmG0Q70IrVvevnzV61alSJwK6Nc+8rIxa/ulIRxcXHYsn0nLt24i6A8tb6m800F48hAOH64gvYtm6Npk0Ya37148OABNm7Zji6Dp8LMPP1ChSSmx3b+heKFPNC6dSu19VEXUhJy+kv9QdvljWVNv+uMGPI8yhjuuMZoHr1QRrQRTQyit27fxp9rNiAwT20kWdqleM3ky0e4fr6FSePGpMhyomn27tuP528/oXH7Aem2u//vOXx+81BYVNILVjTEQZQnbP1B2+WNZU1/0HZZI1je9ANdkDVGs+iFmxbzlQrly2PcyGFwfHcBRvHRsuvGUcFCEZk9fYpWKSJEm9atEBsehOePb6fZJjjwE+5eOYYhPwxSqyLCMAzDMAzDqBZWRvSMIkWKoGen9nB8cQyub06Kw+HNWYwZMUztsSHyQK5ipGRcOr4TsdFfM64khwx3p/etR+9ePUXgJMMwDMMwDKM/6Hw2LeZ76tatg3LlyspSLFKWEm1eyFOhqfr16uDfcwdRq1mXFK/5PLwJRzsblC1bVmP9YxiGYRiGYVQDW0b0lBw5cogKsXRosyIipWmTJnj55A4iw8Nk1yRJSfj33AF065pSQWEYhmEYhmH0A1ZGGK2AKr02atgA966fll17+ew+8uZxT1E1lmEYhmEYhtEfWBlhtIY6dWrj6f3rMveyx7fOo0njhpruFsMwDMMwDKMiOGaE0Rqsra2Rz9MTO/+eC1MzM0SFh6Jw4cKa7hbDMAzDMAyjIlgZYbSK4cOGICwsTKaccCpfhmEYhmEY/YWVEUbrYkcouxbDMAzDMAyj/3DMCMMwDMMwDMMwGoGVEYZhGIZhGIZhNAIrIwzDMAzDMAzDaARWRhiGYRiGYRiG0Qg6H8D+9OlTrF27Fn5+fqI43sCBA1GoUKFMtf/8+TOGDx8OCwsLWfvixYtj4sSJavkujOFw584dHDhwAL6+vjAxMUHRokXRp08fODo6arprjB7C8sakB8+jDMNoEp1WRiIiIrBgwQJ0794dtWvXxoULF/DLL79g+fLlIi1sZtv/9ddfqb6fYZRFVFQUWrdujWLFionn69atw9KlSzF37lxNd43RQ1jemLTgeZRhGE2j025aN27cgIODAxo0aAAzMzPxaGdnJ64roz3DqIoaNWqgXLlyyJYtmziaN2+O58+fIzExUdNdY/QQljcmLXgeZRhG0+i0ZeTt27fw8PBIcc3T01Ncz0r7sWPHiknay8sLPXr0QO7cudPsQ3x8vDikUJE+S0tLmJrq9E/LqBlvb2+4u7sLF5q0YFlj1CVvLGuGA8+jDMNoGq39TyezL/k5p8WKFSsQExPznRnYyspKXE+NjNrb2tpi3rx5YmCNjY3Fnj17hBvD4sWLRbvU2LdvH3bv3i17Xr16dYwcORL29vYKfV9Gf5BHdl1cXGTPX79+jZ07d2LMmDHp3pdljVGXvLGs6Qc8jzIMowtorTIyYsQIJCQkpPm6jY2NcDcg/9VvfaNpMEyNjNrT67SLQ9COTM+ePXHp0iX4+PigTJkyqd6zbdu2aNGiRYprtMND5mt9Jjo6GjNnzhQH7WAxismuFAoopom7X79+KFWqVLr3ZVljWVOXvLGs6Yes8TyqveibrDGMXiojae2gJIdMxUeOHElxjUzF5A+tjPZkKqYjPWiw1OcBMy0kEonYYaVHRnHZlS4M58yZg27duqFWrVoZtmdZY1lTl7yxrOmHrPE8qr3om6wxjMEGsFeqVAnBwcE4e/as2P2hx5CQEHE9M+0poPP9+/dISkoSJuctW7aIQTS9FIcMkxnevXsnFoadO3dG3bp1Nd0dRs9heWPSgudRhmE0jdZaRuSBTMwTJkzAmjVrRM7zXLlyiedSt4TAwECMHj1apLB0cnLKsL2/v7/wpQ4NDYW5uTkKFiyIKVOmyL3zyDDycujQIXz58gUbN24UhxSprDKMMmF5Y9KC51GGYTSNkYRthEwmIH9eCjokX19DM68z6oVljVEXLGuMumBZY5j/YGWEYRiGYRiGYRiNoNMxIwzDMAzDMAzD6C6sjDAMwzAMwzAMoxFYGWEYhmEYhmEYRiOwMsIwDMMwDMMwjEZgZYRhGIZhGIZhGI3AygjDMAzDMAzDMBqBlRGGYRiGYRiGYTQCKyMMwzAMwzAMw2gEVkYYhmEYhmEYhtEIrIwwDMMwDMMwDKMRWBnRI7Zu3Ypq1appuhuMAcCyxqgCfZerOnXq4Lfffkvz9eLFi+Pw4cNq7RPDMIymYWVERzl//jzs7OxSXOvevTuuXr0KXSM8PBxDhw5F7ty5YWNjgzx58qBLly5KuXdsbCwGDhyIfPnyIXv27ChSpAjWrVunlHsbCixr8vPjjz+Ke9ra2orPGDVqFOLi4pR2f31Cn+SKePHiBTp27AgHBwdYW1ujfPny2Llzp0L3ePz4MVq0aJHlvvTp00fIHsMwjC7AygijcUaPHo03b97gzp07iIiIwLVr18QOojJISEiAm5sbTp8+jS9fvmDDhg0YO3YsTp48qZT7M7qFKmWNIEXn6dOnQtbu378vjoULFyrt/ox28vbtW1SpUkWMNU+ePEFQUBCmTJmCIUOG4I8//tB09xiGYbQbCaMxFi9eLPHy8pLY2NhI8ufPL1m+fLnstdevX0voz7Np0yZJgQIFJDly5JD07t1bEhcXJwkMDJRky5ZNvG5tbS2OixcvStavXy8pXbq07B7v3r2TNGjQQJI9e3ZJuXLlJD///LPEw8ND9np4eLhk2LBhkjx58kicnZ0lPXv2lISGhmb4+cqmePHi4nPSIikpSfL7779LChcuLPpRu3Ztibe3t9zf81vatm0rmTZtmsSQYFlTv6x9/vxZUq9ePUmvXr0k+grL1VfovvXr1//uOn029f3Lly/iOcnTTz/9JB7pN6tSpUoK+aLvtm/fPtnzU6dOSSpWrCj6XqxYMcmBAwdkryUmJspkle5Ff4djx46Ja6amphIzMzPxu9L7GIZhtBlWRjTI7t27Jb6+vmIBdPbsWTE5X758OcVE2rVrVzGRffjwQeLu7i4ma+LcuXNigkrOtxN5zZo1Jf3795dERUVJnj17JhYLySfyjh07ivuHhIRIIiIiJF26dJH06NFDrs9PDepPWkfJkiXTfN+gQYPERPr3339L7t+/L36P5Pzxxx+SUqVKSXx8fCTx8fFisqXFRWxsrFzfMznR0dGS3LlzS3bt2iUxJFjW1Cdr8+fPF4tA+k6Ojo6SmzdvSvQVlquv5MyZU7J27drvrpPcGBsbS06cOCGekxJib28vuXr1qnht8uTJkoIFCwpZ+1YZIfm0s7OTnDlzRigely5dktja2kqePn0qXifZzJcvn+TWrVvi93/79q1MsSHlaOTIkXL8BRmGYTQPKyNaROvWrSVz585NMZE+efJE9vqAAQMkw4cPl2sipwUCvT8gIED2+sKFC2UTOe3a0iQZHBwse50WYLSblpCQkOHnK5OYmBjJokWLJFWrVpVYWFiIHU7acZVCO3v79+9P8Z5cuXKJndSMvmdyaMLu3r27pE6dOmJyN2RY1lQrawQtDKdMmSJ29w0FQ5UrskSQVSI1XFxcJFu2bJEpI0OGDJG9RlYaUjBI0fhWGRk6dKhk1KhRKe7VrVs3yezZs8V5kSJFJBs3bkz1M1kZYRhGlzDVtJuYoWeOWbx4sfBhT0pKQlRUlAi0Tk7OnDll5xQUGRoaKte9P378iGzZssHJyUl2LW/evLJz6Wd++3nGxsb49OlTlj9fESwsLEQcBx0UcL5r1y7069cPJUqUQKNGjURfe/ToARMTE9l7KCj4/fv3MDc3T/d7SiHFm/z5nz17JuJH6HsaEixr6pM1KUWLFkXp0qVFMDHJnD7CcvUV6iP191vi4+MRGBgIZ2dn2TUPDw/ZuZmZmYgz+fDhw3fvpe939uxZrF+/PkUMHCVHkMapFCxYUOnfhWEYRt0Y1opMi/D19UXv3r1FcOvnz5/FBNmsWTOxaJaHjBbTuXLlQkxMjJgIk3+mFMr4Q/egCZQ+W3rQeygLUGag7ERpHZSyUt7FIi0GS5YsiYcPH8r6SovG5P2kRU/Xrl0z/J4E/abDhg3Dv//+KwLXc+TIAUOCZU19spbaYvT58+fQR1iu/qNhw4bYvn37d9cpm5aVlRWqVq0qu0ZKRHL58PPzS7W/9P1GjhyZ4rtR0oU///xTptRQBq/UMLTNFoZhdBsesTQETSo0abu4uIiJ4+jRowpleHJ1dRVpSmkRkBo0kVWvXh2TJ09GdHS0WBCtWrUqxW5hmzZtMHz4cNlkT7uJ+/bty9J3SuuglJVpMWvWLJHOk/qZmJiIgwcPwtvbWzaBkyIxffp0YdUgKFPRgQMHxPfP6HsS9B2vXLmCU6dOwd7eHoYGy5p6ZI0+m3axadFIvzcpOHPnzkXjxo2hj7BcpZQrytBG2dro+5BCtH//fpFel2SA0oonV1BoY4QsbrNnzxZWE8rE9S2DBw8W8nTu3Dkhq2TJo+xvlK1L+jp97r1798TfgRQ16Wv027569UpuxZBhGEaTsDKiIYoVKyZSP9arVw+Ojo5igmrVqpXc7y9cuDD69+8v7kO5+i9fvvxdm23btokJiSYmqqVAu8C0GyyF0tzSeytWrChM/zVr1sTt27ehbkxNTUUKTOon/RYzZ87EmjVrZMXPaLFBri7t2rUT/ST3F/pu8nxP2oVcuXKlWFzSTqJ0l/OHH36AocCyph5ZMzIyEq8XKFBALD5bt26N5s2bp1vkTpdhufoPchUjRYEUAvpe9HuQorFs2TJh3UgOuQVOmDBB1COhDRJSWkguv6Vs2bLC2jJ16lShsJD1ZNq0aUIpIUaMGCFkuVOnTkLeGjRoILMcDRgwQLh+0WeUKlVKTb8CwzBM5jCiwJFMvpfRMebPny98kGkC1GcM5XtqM4byNzCU76kt6PvvTdagv//+W7i7MQzDGApsGdFjyG2ACrCRvkm7hcuXLxcVgvUNQ/me2oyh/A0M5XtqC4b0e1PsCLl4kWWNYRjGkOBsWnpMQECAcEfy9/cXft0DBw4UbhH6hqF8T23GUP4GhvI9tQVD+b0p2xopWeQmSG5eDMMwhgS7aTEMwzAMwzAMoxHYTYthGIZhGIZhGI3AygjDMAzDMAzDMBqBlRGGYRiGYRiGYTSCQQSwJyQkYOPGjbI89pSLnioHm5iYpPkeKkg1duxYUZSLctkzjLJlbd26dbh586ao8J0tWzZReI/qKKRWc4BhlAHLHMMwDKNtGEQA+z///CMmYKrkS8ybNw+VK1dGhw4d0nzP5s2b8fr1a1Fwi5URRhWy9v79ezg5OYlFIVX6Xrp0KUqUKIH27dtroOeMIcAyxzAMw2gbBuGmde7cOTHZ2tvbi4OqK1PhrLQgBeTevXuigjLDqErW3N3dxaJQClXwploDDKMqWOYYhmEYbUPvbfMREREICgqCp6en7BqdBwYGClcFKyurFO0TExNFBVzKZS+P0Sg+Pl4cyTEzMxMHY1goKmvE/v37sWfPHsTGxiJ79uzo3r17mvdnWWOUgTwyx7LGMAzDqAu9V0ZiYmLEY/KFoLW1tXiMjo7+boF48OBBsYAsVqwYHj9+nOH99+3bh927d8ue58uXDwsWLFDiN2D0VdaINm3aiIPcZyjOxM7OLs37s6wxykAemWNZYxiGYdSF3isjUpcE2pm2tbWVnROWlpYp2n769AmnTp3CwoUL5b5/27Zt0aJFixRuD9LKwRTMzOg2bm5uKpG11NxnPDw8sHLlSkybNi3VNixr+o8i8pZV0pM5ljX9R52yxjAMY9DKiI2NDRwdHfHmzRvkzJlTXKNzuvbtTvXTp08RFhaGkSNHiuc06dJuN7lsTZw4EQULFvzu/um5LhhAbgAmk7KWGuQimJ7/Pssao2zSkjmWNYZhGEZd6L0yQtSpU0e4HRQpUkQ8p/P69et/147SXJYsWVL23MfHB3/99ZewlOTIkUOtfWb0W9ZIyb127RoqVaokFJV3794JP/7SpUtroNeMIcAyxzAMw2gjBqGMUHYjqhcyevRoWe0HckMgVq1aJR4HDRoECwsLcUghVxtyT6CdbYZRpqwR5K9PKaQpUJiUXUoB3KlTJw32ntF3WOYYhmEYbcMg6oxoAvKt/jYbDaN75MqVC9oOy5r+oO3yxrKmP2i7rDEMYzgYRJ0RhmEYhmEYhmG0D1ZGGIZhGIZhGIbRCKyMMAzDMAzDMAyjEVgZYRiGYRiGYRhGI7AywjAMwzAMwzCMRmBlhGEYhmEYhmEYjcDKCMMwDMMwDMMwGoGVEYZhGIZhGIZhNIJBVGBnGEZ1BAcHY+3GLYiLj0ftGlVRo1o16AIfPnzA+o2bIEmSwNraGsOHDYG5ubmmu8UwDMMwBgVbRvSU8xcv48fR4zBi7Hj4+PhoujuMnuLn54fps3/G9QBj3Ix2wbotO3HqzBlIJBJoM0lJSVi9Zh08i1VBjea9kWRqg71792m6WwzDMAxjcLAyoofQQnDP/gPwdaqEd1aFsPfgEU13idEzYmJisHPXbkydPQ/v7UsjzrkIEm3dEJCvIbYeOouZc+cLy4O2snXbdtg4uKFE+Zqwd3JFneZdcfvuA9y8eVPTXWMYhmEYg4LdtPQQb29vRCaZIcnKHkmWOfD8+SEEBQXB0dFR011jdJyIiAgcPX4Sp86cRaStJ8ILNANMzP5rYJoNQXnrIDTsHabN+xUFPfOiS4e2yJcvH7RFUd+58x+8ePMBrXqMkF03NTNHq16jsHXtQhgbG6N8+fIa7SfDMAzDGApGEm33p9BRAgICEB8frxH3k58mTsHL7CWRZOMirpkHvUBVpzj8NOq/xRcjH7ly5YK2ow5ZI2V2974DuHHrDiLs8iPKsTBgavFfg6REGMVGQGJhAxibfL0mkcAk9B0cQp/ANYe1UEpKlSoFIyMjaAL6jcg1K/hLNJp0GgxT02RK1P8JDw3G/k1L0ahBXTRu3EjtfdR2edPUuMYYnqwxDGM4sDKiZ5P2nn0HsP/KQ4TmrvLfRYkETq9PYmjvLqhYgXd89W3CVqWshYeHY8v2f3Dr7j2EORRBrEMBwPh7g6pRdBhsHu1BRIn2kFjm+O5144jPcAj2hoNFEgb17Y3ChQtDnYSEhGDJ0t/h6lEE1Ru0g5Fx2h6qsdFROLrzT+TO6Yh+ffvA1FR9BmRtlzdWRvQHbZc1hmEMB1ZG9GjSfvDwIX77cw0C8jdJ6TpDf+jYCLi8PY3Z0ybzJKQAiv5WCQkJ2LhxIy5fviye16xZE71794aJyf+tBf+HZGPt2rV4+PChWPA7ODigVatWqFevntbI2sNHj7B85d8IsSuEGLKEpLOAz0gZSa6UOPrfQo0KZdGnV3fhEqVqXrx4gRV/rETVBh1QuFQluS2MV0/tgb/vM4wdMwp2dnZQB6r831SGzLEyoj/wPMAwjLbAAex6wvPnz/H7yr8RmKf2d4oIQe4zgW5VMGf+QrGgYFTD3r178fTpUyxZskQcT548wb5932dpSkxMhL29PaZNmyaUl6FDh2Lz5s24f/8+tAHqx9I/VuFTnrqIcS6ariJifXcbrL33i3OrJ4fTvS+5Dgbka4Kzj97i9xUrVZ516/r161j+x19o3vVHuRURgpSkGo07onjlRpg1ey7evXsHXUfbZY5hGIYxTFgZ0QMePX6MX5b8jkD32pBks02zXWL2nPjkWEakYv348aNa+2gonDt3Du3btxeLPjratWuHs2fPftcuW7Zs6Ny5M3LmzCliKAoVKoTixYsLRUbTkCVh2V+rEehRN115kmKUlACjpMSv55KEjD/A2BhhuSrj7psAbNi8VWUKydmz57Bn3yF0GjgJzm55Um2TmJCAoAA/8ZgaRUpVQsP2A/Hr4qV4+fIldBltljmGYRjGcGFlRMc5c+4clqz4GwF564nsWRmRkMMdfs4VMH3OfOGGwyg30xQFent6esqu0XlgYCCioqLSfW9cXJxQAjw8PNJsQ+4xdB/pER0dLXuNFpdZPej++w8ewvzF/1dsLbJDZRgZISR3NZy791xmrVPGd5AeV69exfFTZ9C+/3hYZ0/bbSw0JABrF00Qj2mRK28BtOg2HMuW/yHSFSuzn98e6iQ9mVO1rPGh+YNhGEZb4NS+OgotJFat24Bb3q8QlL+RSKkqL2Qh+WxWF0tXrkHzhnXRtnVLtfjuG0LtDcLKykp2jSp7E7SYS349OWQZ+Ouvv+Dm5oZKldJ2JSJ3r927d8ueU7rcBQsWwNnZOUv9/vTpEw4cOoLDx44h0jo3wijmKHmmLFVhbIIQ9xq4F/IGk2b+jOJFCqFrx3YoU6ZMluTx0aNH2L13Pzr0n4hsll9//6zi4pYXjToMxNLflmHlH8vVFkOiKjKSOWXIWv/+/TNUwrURXU2DTuMLxQQxDMPoGqyM6CDv37/Hr78tw2cTF0R41gOMFF+4kftNQP7GOHD5Ju49eIixI4fr/AJLG9xgCFqA2dp+dW+SLsYsLS3TXBSuWbNGVDInX/70FuFt27ZFixYtZM+lu5tkVaDAeUWtOFeuXsWpsxcR/CUC4bb5EO3RWD1KSHLIIuOQD/72HggM/IAHC1fCLCYEVSpXRIO6ddK1FKUGWaFmz/kZLXuMhJVNxi5mipDboyDK1WyO8RMmYdrUySrJskXKgaqRR+aUIWtz585VYq8ZeaC/qTbJGsMwjDywMqJDUIafQ0eO4uDREwhyqywsHFnCxAwh7tUQGfwK4yZNQ99e3VCtalVlddfgsLGxETuqb968EX75BJ3TtdSsIrQopJ1McpWhRWFalhMpZmZm4kgNeeMuKFZoy45deObzHNE5PBCZoxSSXDJ271M5RsZItMuDQLs8QEIsjvi8xZU7f8DGVIKO7VqjerVqGbqWhIWF4ZcFv6J28+5wcs2tkm4WK1sNwQEfsWz5Coz4cfh3WdK0HXllThmyxjAMwzDywMqIDu14LV2xEn4xZggt0BQwMU//DakVoUuDOIf88LdxxaodB3Hx8jUMHTxAtrPPKEadOnWEi0uRIkXEczqvX79+qm1pUfjs2TNMnz5dKDLqsKjN+PkXBDuVQUKhVpmyqKVG82ZN0aJZU3FOy9S9j0Ox/8aLzN/Q1AJxToXw2akQAmLCsHrXUbx644te3bum+RZ/f3/8umgJKtRuhfxFSkOVVG/YHuePbMPiJb9hxI/DZBYxXUDdMscwDMMwGWEQdUZ0ufYDWUMOHj6CQ8dOIsi1PBJzuMv1PnnrPqRAIoFF8AvYB3ujd/euqF6tqsEHOmamzsiGDRtw5cqV72Rt1apV4tqgQYOEfAwbNkzsPid3k6H29LoqZI2UkZk//4JQ+yKItc+nNJcsm9ubREYtQmJsgojyvZVyX0iSYBL+CXZB3mhQtSx6dO2carNr165h+45/UL9NX3h4FZP79ivmDEdcbAwS4uOQzcoGI2aslL9rEgnuXDmBJ3cuYfiwISmSFmhr7QdlyBzXGdEfuM4IwzDagkEoI//88w9u3ryJyZMni+fz5s1D5cqV0aFDh+8CkA8cOIDatWvD1dVV1O6YP38+Ro0ahdKlFdttVcakTS41S5b9Af8ES4TmLJexNSSryoj0vXGRcPD7FwVz2mP4kEHIkUOx9+sTujBhKyJrFFNx6Ohx/HvjJuKNLRBl6YxoS2ckWjtnWjmhOiNGSfEivW+SiQUiy3XP1H2QlATj6GCYRgYgR1wgjCICkC9/frRs0hClSpX6TjEODg7GuvUb8SUyFg3b9UP2HA4KfdzSaQMRHxcrzk3NzDFm7hqFu/zx7Quc2rcOlSqWR7u2bWBhYaHX8sbKiP6g7bLGMIzhYBDKyJAhQ8TudJUqVWQ7qVTsa+XKjHdCFy1ahDx58oj8/KlBE3PyyZkWTBSsnJmg4uTWkMNHj2H/4WMIcq2AxByK+79nRRn5z0ryEvbBjzGgT09UqVwZhoguBHlmZoFI//afP3/GY29v3HvojRcvXyI2Lh5J1k4IN7VDgpUjEq0cUy2gmVW3wK8dSIJxTBiMIwNhEx8K85ggGMVFI1fu3ChVvChKFCsKLy+vVIPE6f/q6NFjOH3mLKrUb4uiZTJnwVOGMiL6Ex+Hf88fxvOH/6J7ty6oUKFCpi2K2r5AZGVEf9B2WWMYxnAwNfTaD+kFDUvz8NeoUUNt6VZDQ0MxZfos+ARGIzh/U8BUfmuIUjEyQqyjF/xtcuLvrXvxyPspxo8dneWdX0Y7oMUyWf/oqFe3rswy+Pr1azx/8RKPnvrA981NxCcBidZO+GLmgEQbVyRlyyFk4zuMTdJXehNiYRLuD6vYQFjGBAEx4XBxdUWRogVRtFB5FChQQLhFZrSIp3iHNWvXI3e+oug+bBYsLNMP+lcHpMhUb9gOxcpVx+FDW3Dm7DkMHNBfJ9PDMgzDMIxBKCMUjE3WCXKzGDBggCgkRrudiqbx1IbaD8pMt/r27VvMW7gYgXZFEZu7LLQB2ukO8KiH008f4nH/gZg2aYJYNBoKumAZURYUiF20aFFxtGr5nzJPlccfP3mG+w8fIuBtAJKyuyLMMhcScuQBTNIYQiQSGEcFwTr8HSwj/WBhLEHRIkVQpmRVFCxYUChBilgP6P9x9+49uH7zNhq1HwjXXMofK7KKvaMr2vQeA5+HNzFr9lz06tldWEkYhmEYhtEiZeTWrVtYsWIFypUrh9u3bwtlJDIyUsR1TJ06VedqPygrBebTp0+x6Pc/EJC7unCV0SqMjBHhWhpvQt9i8vRZmDl1klhMMvoPZVyieCk6unX5ai0kWb145Rru3T+EGFt3fHEqAYnZ//+XJBKYB7+EXchTuDo5oH6j6uJ/3d4+a+mDt23fgdfvA9D1h2nCEqEMmjZpgiZNGotzUoziLazxPiAyS/ek+xQuVQm5PLywfdNSMXbQ92cYhmEYRkuUke3bt2PSpEkoXLgw+vbtK3NtonoMulj7QRlQliNSRD7nrQMJucFkEWlAMWH15HDmA4q/Id7OA37G5pj183z8Mnc2p/81QMzNzUUwOR2kmJBL0r4Dh5D4f8VbkpSI4sWLo+eIyXBxcVHKZ1Jmuxs3b6HXyJ9hkpYlJhMcO34cBw8eyHLMSGpQMH3L7iOwY9syVkYYhmEYRpuUEXLNIkUkOZT2lIK2DbH2A31vqqYe6FZZKYoIQWlWKbOROJdkLog+LRJt3fA5vhD++HsNJo0bo9R7M7qnmDRt0lgcqoSsDZIkifhf0aUag4mJCQafGpthGIZhtE4ZIR98b29vFCv2Xz2AJ0+eIHdu1VRMJtq3by92V0ePHi3Lq0+xHsS3tR9Onjwp3K6GDh2apdoP8kKuaqES66xXU1cjsQ4F8eLVMeHGZkgxFYxmoE2B+vXrYN+GxWjacTCy22l/zNKHt89xcs8aDBrQT9NdYRiGYRitRu3KSJcuXfDrr7+ibt26IsB727ZtOH/+PEaOHKmyz6T0oBSbQse3JFcyKAMWxa6ok1v3HuCLleoUMZVgZIRw69xCqWRlhFEHrVu1gquLC7atnY9CJSujXPXGsLLOnqV7mplbCLdMSs2rrDiUoM8fceP8QXwJ8sPokT8qrRgiwzAMw+graldGyNd85syZOH36tPAtp+B1KkZoqJN2QkIiJMZy1nLQIpJgnOk6KgyTGahOUJkyZXDy5Cns+Gs23D2LoGTlusiZO1+m3KGGT1uBxIQEhIYEwM4+c6m4iaTERLx8dh+PbpxFTOQXtG7VQvQ1vcQXDMMwDMMYUNFDbS4ORgHAa4/fQLhbeaV9dmfXALRo1lSc0x937+NQ7L/xAsrE2fccJg7pjUKFCkGf0YXCYIZYiI4U4Zs3b+LU6bMIC49A0bLVUbRMNVjbqC+pQpD/Bzy+exnPH94U6YobNawv4uGyEiei7fJmiLKmr2i7rDEMYzioXRm5cOFCmq/Vrl0b+oK8kzalGR4xdjz88zcBTL+mIc4qNrc3iSB2QmJsgojyvaFMjKOC4RF0E78vXqj3Abq6MGEb+gKRvv+Fixdx5co15HBwQdGyNVCgWFmYmirf4hgdFYGn967jyb3LMDczQZ3atVC1ShVZ7SJ9lzdDlzV9QttljWEYw0HtblpHjhz5ruI4BZfnzZtXr5QReaHUwR3atsa245cR4l4j9erW2kRSIhw+XscPwwYoXRGhAnt79uxDcGioeG5hbo52bVvLUjIzTGpQrFeH9u3Rvl07+Pj44Pz5i9hwfKdQSEpWrAsn16zFZNF+je9Lbzy6eR6fP75F1apVMHrEMI6XYhiGYRhdVEYWLlz43bUDBw4gMfFrKlpDpHHDBrh15x4eBj5BlPN/Wca0DokEOfxuoG61iimyoWWVz58/49z5C7h8+QpKV2mAwuUriuthIYGYv2ARihUrgob164l6NPpuiWGyWHCwcGFxxMTE4Pr16zi5fw2MTCxQvkZT5CtcSiH5ocD2x3eu4N61U8jllhPNG9UTMW8cC8IwDMMwehYzQvUDBg8ejNWrV0NfUNSdgRZPE6dOh691EcTb5dVKNy2rz49QwjYWUyaMy9KCjIrlUVHJBw8f4d69+0iUAEVKV0OJ8jVhYWn1Xa2GZw9v4smdSwgPDUKpUiVRulRJUTNGWa4xynRloFiGjRs34vLly7K00L179xa1dL7l+PHjIpOcr6+vCMweP358pvrIrjPpQ7K2/8Ah+H8ORPXGHeFZsESGAekPb17ArcvHUK5sWbRo3lRYX3TddUYZ8saypj+wmxbDMAZrGUkNcq0wdLJly4bpkydi8vTZ8DPNhiQb5VSvVhYWwS+RR/IZ48fMUEgRIV2XLB8vX77E8+cv4fPiBcLCwpArT37kzlcUzbqNgK2dY5rvp4rbxcpUFUdMVCTePH+Es1fuYPPWHTA1NUFBLy8UKlgABQoUELVqUlv0q5O9e/fi6dOnWLJkiXg+b948UWSzQ4cO37W1t7dHu3bt8PDhQwQFBWmgt4aBl5cXfho7Gm/evMHGTVvw6NYF1G/dG5ZW3xc1Dfz0Hid2r4ZXAU/MmTUDdnZ20BdY3hiGYRhtRO3KCO3GJXeViI2Nhb+/P3r06AFDx8HBAdMmjcOMub/gc946SqvInlVMvnyEa/gzTJ89ExYWFum2pRig58+f48XLV3jx4iU+ffKDrb0TXHPng6t7fjQq21AoH+m5yyRPt2pi+p+IZrOyRpHSlcVBREWGw8/3Jbxfv8K5S/+KGg+04CLFpKBXfrEIdXV1Vatr17lz54QlhPpB0OJv8+bNqSojlSt//R60SObFoeqh9OHTp03B6dNnsPPvuWjVcxQcnP6LR3rhfReXj2/H4EEDUbRoUegbLG8MwzCMNqJ2ZaRZs2bfWQRokcBByl+h3f0xPw7BouV/ISB/Y8A0/cW/qjGKDoOz/01MnzEVtrbfp02lOjF3797F/QeP8Py5D8zMLZEzT36heFRtXBkOLrkUsqSsmDMccbExwl8/m5UNRsxYmWZbKnpXoGgZcUitMF9CAvHp/Wvc8X6NoyfO4EtoMDw8PVG6ZHGUL18ejo5pW2GUEYBPi7zkNXPoPDAwUGRNo2QFWYHcY5K7yJCSZWlpKTtnMoZ+p0aNGsLdPTf+/GsJipevCSMjY8TGRuP1k9uYMX2a2BQwdFjWGIZhGL1VRurUqaPuj9Q5KDi8e8e22Lz/BII86wFGisVnSIzpzyqBUVIiJEZZ+BMnxsHp/UWM+XGosDB8G+OycdNmPHrsjQJFysCjUCVUbNQD5hZZS08cHxcrFBFC+igvtEjK4eAsjsKlKn39CokJQjl58fwxTpxeBEd7Owwc0E8lMQD0mxDJlQ5pXEt0dHSWlRFy99q9e7fsOQX0L1iwQG3xDPoEZcKiDRCKJ5EyclA33hT5PyxrDMMwjF4pI0ePHs2U1cSQqV+vLp74PMeV1w8QkfPrzr+8RJbtJiwaNo/2IKpoi8x1QCKBw4fraNe8caouK1Rw7tXbj+gzan4KV6qs0rRJEzRp0limXMRbWON9QGSm70cxJ7k9Coqjav3WOHtoKw4dPoJ+fftA2ZCVjyAriNSKROeEdFc5K7Rt2xYtWvz395TuUFNQMQXOM4pBFpBKlb4qrVLLmp+fn0b7pC3pglnW9B9tkTWGYRi1KCO0cJUHVkZSMqhfHzyfNBXR4f5IzJ7SMqFqLIJfwMvFBs3/X8n9W2gR99j7CTYtm4JCJSujYIkKcM6ZJ8suHMeOH8fBgwfEuamZOcbMXYOsQq5bz73v4Nn9q8iR3QatOg+AKrCxsRFuYOSTL91hp3O6llWrCGFmZiaO1NCCpHiMHsGyxjAMw+iVMjJjxgx1fIzeYW5ujrEjh2Pm/EUIsGoKmCi/onRqGMWGwyHYGyPH/5ymckGB7D8MHiQyY127fh3XT+4Qu6Z5CxSDZ6FS8ChYAubmmol3IdesD29f4M2z+3jj8wDm5qaoWL48Rv04VOXpLMkNkVxcKPUwQef169dPo5+J4qDU1rTAo5THFF9jqkRLE8NIYXljGIZhtBGehbQcqkzfvFF97L9yG6G5q6j+AyUSOH64hkH9+6QasP4tOXLkQJPGjcVBcRGPHz/Grdt3cfHodjjlzI1CpaqiYPHyMDWVT5Ey+78CQ4slc3P5408kSUnwffUUT+9dwbtXT5A/fwGUL1cGvTu3EH1UF+3bt0d4eDhGjx4tqzNCLi/EqlWrxOOgQYPE4549e1L45VNGOYoXmjlzptr6yxgOLG8MwzCMNqL2ooeUcWjbtm1i0UqLtuQfv379eugLyiwORjuZE6fOgI9ZfiTa5ZHrPdKYkYgS7SGxlH8xbvX5MarmMhNWhKz2mYKDz1+4iIcPH6FcjSYoXbmeSqpXv3xyD1dO7oJbTlfUq1tbVMlOy8VEHwuDcSE6/UHb5Y1lTX/QdlljGMZwUP7KMAPWrl2Ljx8/il05CoQcOnQo3N3dU63DwHyFFvDkruXofxtGcVGq+5zIQDhGvsHgAX2zfi9jYxQqVAiDBg7Az3NnIyb4LfZtWCxSqCoLsoacP7IND68dw9jRIzDupzEifa+yFBGGYRiGYRhGz5SRR48eYcyYMahYsaJYsNLjyJEjcenSJXV3Raeg1Lr9enWDw/vLZHZQ/gckxMLxw1X8NOpHpWR+Sg65ew35YTCqViqDPWt/RWR4WJbvmZAQj+O7V8NcEoVpUyeL+iwMwzAMwzCMbqF2ZYQCKCnrkDQImuIMKNuQplNq6gLVq1VD9bLFkOPTLeXeWJIEx3eX0KV9a+TPnx+qolnTpmjTqil2rvoZTx/cyHRWno++L7HjzzkokMdFBNGbmJgova8MwzAMwzCMHgawk0vW8+fPUbhwYRQoUEDEj9BOvJOTk7q7opP0690T7+ctwNOAJ4hy/r7+hxSJhc3XeBGLr4pf2g0lyPHxBqqVLoJGDVLP+qRMqlWtioJeXti4aQvuXjmOqg3awcOruFwpgQM/vce1s/sQ/SUYgwb0EW5gDMMwDMMwjO6i9gB2qrtA7lmUJerTp09YvXq1sI706tVLlg5VH1BloCf9XlNmzMLbbAUQZ58vS/ey8b+PkvYSTBw3RiXB5enx8uVL/LNrD75ERKFaww7Ikz/1v39wgB+und6LL8H+6NC+LSpUqJDleib6FOTJQcX6g7bLG8ua/qDtssYwjOGgdmWEUp7WqlVLHOSepa+oetKm+h6kkHywK4WEHO6ZuodlwBN4mQZj5tRJoqaJpqCsW5u3bIO5VQ7UbdULVtbZxfXEhARcPbMPr5/cQedOHUShRXUpIbo0YfMCUX/QdnljWdMftF3WGIYxHNSujFy9ehUXL1K614fCVYuUkipVqiBbNvlrSigKZe3auHEjLl++LKv90Lt371RjDRRpq+lJOzAwEFNnzsEnl0oKV2i3CHoBj3hfzJ05TekB65mBxPDc+fM4eOgIKtdtA1MzM9y5chzFCnuhS+dOGsuQpQsTNi8Q9QdtlzeWNf1B22WNYRjDQe3KSPKd/StXrogsWu/fvxe73j/++KNKPuuff/7BzZs3MXnyZPF83rx5qFy5cqrphBVpqw2TNqVJnjF3Pj7nrokkKwe53mMW9g65vzzGvFkzkD37VyuEtvDkyRNc//emOPcqkB81a9bQaH90YcLmBaL+oO3yxrKmP2i7rDEMYzhorAI7VcVu1qyZiBPZsWOHsESoShk5d+6csG7Y29uL5+3atcPmzZtTVTAUaZseZGFJbdImNyNT0/9+9vQmdnnaOjs7Y9yoH7HwtxX4nLeeLGDdBElp1hJxDbqPmTOnyRQR6mtaOum3fUivLZHcgpGZtl5eXuL49jsrcl/qr9Sdi7K3UQFGZbRlGIZhGIZh9EAZCQ4OFhYRcteic7I8zJgxQ2UV34OCguDp6Sm7Rufk4hQVFQUrK6tMtU2+WE6uJNDCltyeDh48KAL0vyVPnjxo2rSp7PmWLVvE4jo13Nzc0LJlS9lzUtpiYmJSbVu3emWcvnoBgfkaAyamqGv1AVbGqdzXBrApUDlF9rL9+/cjJCQk1ftSGuZu3brJnh8+fFjsjqYGudpRIgIpx48fTzNlMykB/fr1kz0/ffo03r17h7QYNGiQ7Pz8+fN4/fp1mm379u0rU15IyfXx8Umzbc+ePWVuatevX4e3t3eK11UllwzDMAzDMIwGlJHZs2fj2bNnKFmyJNq3by8yI6kyeFq6eE+uSFhbW8uyUiW/rkhbKfv27cPu3btlz/Ply4cFCxak2R9asJOSISW9gGz6XZK3TS/blZ2dHTq3bobtp/5FcK4qSA9afCe/b3LLx7dQrEzytunFblD/krdN7+9K3zt524xihpK3zSjGJWfOnLLPzqgtFZOU/o1T+/syDMMwDMMwehQzcuTIEdSoUUO4aakDsnbQDvyyZcvEIpUgi8WIESOwYcOG7ywj8rbNyDJCFgF1uGklb0vKAAW0P0FuJNnlSfG6VcBj1M5ni/59eyvkeqVuNy1ltFWmmxaloNZ22I9ff9B2P36WNf1B22WNYRjDQe2WkebNm6v188jNiFIIU30TqYJB53TtW+VCkbbJF8mpWQtokZvWgjn59fSsEoq2JUYNH4KJ02fjc/bcwl2LMIoNh+2XN+jdc4HsHsnvm1GmMF1rm7w9KWgZ1U9RpC3DMAzDMAyjPAxi5VWnTh3hThUaGioOOq9fv36W22ojFNBeq3pVWAY9lV2zC3yIbp3aqzR9MsMwDMMwDMPoTDYtdUKxKeHh4aLgorR2SNu2bcX5qlWrUgRIp9dWV2jbqgUuXp6MaOdiMEqIhWV0IKpXr67pbhkEmqhpwzDywPLGMAzDaCMaqzOi72jat3rugkW4E2wGk/gItK3khW5dOmusL4bkV63PNW0Y3fbjV4a8sazpDxwzwjCMtmAQlhFDpHun9rA/eQbGxjZo0qihprtjMOhzTZu02iorAYKhJ0tQNcqQN5Y1ljWGYRhlw8qInkIphocNHqDpbhgUhlLThuKSkrsu7tq1S3yf1KCFb8eOHWXPuaZN2jVtCG2ot0SwrP0HyxrDMIxqYWWEYZSEodS0oQVR8rbpxRzQ4oxr2mi+po2i8say9h8sawzDMKqFY0ZUBPtWG55ftSHVtGHXGdW4zqiqro2i8saylhKWNYZhGNXBlhGGURKGVNNGG+rJaENbXalpo6i8saxpX1tdkTWGYRhF4RGKYZSIIdW0YXQLljeGYRhGG2HLCMMoEUOracPoDixvDMMwjDbCMSMqgmNG9ANdyMXPsqY/aLu8sazpD9ouawzDGA7spsUwDMMwDMMwjEZgZYRhGIZhGIZhGI3AygjDMAzDMAzDMBqBlRGGYRiGYRiGYTQCKyMMwzAMwzAMw2gEVkYYhmEYhmEYhtEIrIwwDMMwDMMwDKMRWBlhGIZhGIZhGEYjsDLCMAzDMAzDMIxGYGWEYRiGYRiGYRiNwMoIwzAMwzAMwzAagZURhmEYhmEYhmE0AisjDMMwDMMwDMNoBFPoOU+fPsXatWvh5+cHNzc3DBw4EIUKFUq17Z07d3DgwAH4+vrCxMQERYsWRZ8+feDo6Kj2fjP6LWshISFYtWoVXr16Jc4XLlwIT09PtfeZMQxY3hiGYRhtRa8tIxEREViwYAEaN26M9evXi8dffvkFkZGRqbaPiopC69at8eeff2LFihWwtLTE0qVL1d5vRv9lzcjICGXKlMG4cePU3lfG8GB5YxiGYbQVvVZGbty4AQcHBzRo0ABmZmbi0c7OTlxPjRo1aqBcuXLIli2bOJo3b47nz58jMTFR7X1n9FvW6DVSWLy8vNTeV8bwYHljGIZhtBW9dtN6+/YtPDw8Ulwj1wS6Lg/e3t5wd3cXLltpER8fL47kO5BkUTE11eufllGyrMkDyxqjLljWGIZhGHWhszMLucBQjEdakJtVTEwMrK2tU1y3srIS1zPi9evX2LlzJ8aMGZNuu3379mH37t2y59WrV8fIkSNhb28v1/dgtB9Vy5q8sKwxmZVPFxcXhe7JssYwDMOoC51VRkaMGIGEhIQ0X7exsRGuVuTL/21ciK2tbbr3pgD2efPmoV+/fihVqlS6bdu2bYsWLVqkuEY7iuSqo89ER0dj5syZ4qAdU31GlbKmCCxr+i9rqpJPRWFZY1ljGIZRFzqrjNCuc0aQ28yRI0dSXCO3GYoFSU8RmTNnDrp164ZatWpl+Bk0Oev7BJ0aEolEWI/oUd9RlawpCsua/suaquRTUVjWWNYYhmHUhV4HsFeqVAnBwcE4e/as2DmkR0prSddT4927d0IR6dy5M+rWrav2/jKGI2tEXFycOAh6D50nJSWpsdeMIcHyxjAMw2gjeq2MkHvChAkTcPToUfTu3RvHjh0Tz6VuC4GBgejZs6d4JA4dOoQvX75g48aN4rr0kL7OMMqSNaJHjx7iICZPnizOnzx5orHvwOg3LG8MwzCMNmIkYXs0kwnIf5yCXMm33BDdORj1wbLGqAuWNYZhGPXDygjDMAzDMAzDMBpBr920GIZhGIZhGIbRXlgZYRiGYRiGYRhGI7AywjAMwzAMwzCMRmBlhGEYhmEYhmEYjcDKCMMwDMMwDMMwGoGVEYZhGIZhGIZhNAIrIwzDMAzDMAzDaARWRhiGYRiGYRiG0QisjDAMwzAMwzAMoxFYGWEYhmEYhmEYRiOwMsIwDMMwDMMwDDTB/wCJVo10E1TFGwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 700x1200 with 35 Axes>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "''' Look at the distribution of markers within a pixel class '''\n",
    "facet_grid = whole_class_analysis.plot_distribution_exprs(unique_class = 'epithelia', plot_type = 'Violin')\n",
    "facet_grid.figure"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0bc76bec-f0c3-43ad-ad60-c03ae27e109c",
   "metadata": {},
   "source": [
    "## Do Stats\n",
    "\n",
    "The available statistics are very limited / basic. More advanced statistics should be done with a different software, \n",
    "and given that it is important to check the assumptions of the available statistical tests, it is generally\n",
    "best to do any statistical analysis w9ith at least the help of a differnet software."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "49ad2390-14c6-4f6a-b65f-0f05e1e0d202",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>antigen</th>\n",
       "      <th>class</th>\n",
       "      <th>p_adj</th>\n",
       "      <th>p_value</th>\n",
       "      <th>F statistic</th>\n",
       "      <th>avg SSA mean exprs</th>\n",
       "      <th>SSA stdev</th>\n",
       "      <th>avg TA mean exprs</th>\n",
       "      <th>TA stdev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>CD163</td>\n",
       "      <td>epithelia</td>\n",
       "      <td>2.330000e-08</td>\n",
       "      <td>7.780000e-09</td>\n",
       "      <td>609.000000</td>\n",
       "      <td>0.000481</td>\n",
       "      <td>0.000161</td>\n",
       "      <td>0.00570</td>\n",
       "      <td>0.000494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>CD31</td>\n",
       "      <td>epithelia</td>\n",
       "      <td>9.460000e-07</td>\n",
       "      <td>3.150000e-07</td>\n",
       "      <td>237.000000</td>\n",
       "      <td>0.001830</td>\n",
       "      <td>0.000828</td>\n",
       "      <td>0.01110</td>\n",
       "      <td>0.001080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>p-selectin</td>\n",
       "      <td>lamina_propria</td>\n",
       "      <td>1.050000e-06</td>\n",
       "      <td>3.500000e-07</td>\n",
       "      <td>231.000000</td>\n",
       "      <td>0.003850</td>\n",
       "      <td>0.001200</td>\n",
       "      <td>0.01690</td>\n",
       "      <td>0.001530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>CD206</td>\n",
       "      <td>lumen</td>\n",
       "      <td>1.810000e-06</td>\n",
       "      <td>6.050000e-07</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>0.000653</td>\n",
       "      <td>0.000191</td>\n",
       "      <td>0.00336</td>\n",
       "      <td>0.000417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>CD11b</td>\n",
       "      <td>lumen</td>\n",
       "      <td>1.870000e-05</td>\n",
       "      <td>6.230000e-06</td>\n",
       "      <td>109.000000</td>\n",
       "      <td>0.001450</td>\n",
       "      <td>0.000872</td>\n",
       "      <td>0.00847</td>\n",
       "      <td>0.001280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>CD8</td>\n",
       "      <td>lumen</td>\n",
       "      <td>9.660000e-01</td>\n",
       "      <td>9.660000e-01</td>\n",
       "      <td>0.001990</td>\n",
       "      <td>0.002090</td>\n",
       "      <td>0.001490</td>\n",
       "      <td>0.00205</td>\n",
       "      <td>0.000876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>CD163</td>\n",
       "      <td>lamina_propria</td>\n",
       "      <td>9.690000e-01</td>\n",
       "      <td>9.690000e-01</td>\n",
       "      <td>0.001660</td>\n",
       "      <td>0.005430</td>\n",
       "      <td>0.004530</td>\n",
       "      <td>0.00552</td>\n",
       "      <td>0.000517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>CD66b</td>\n",
       "      <td>epithelia</td>\n",
       "      <td>9.690000e-01</td>\n",
       "      <td>9.690000e-01</td>\n",
       "      <td>0.001590</td>\n",
       "      <td>0.002170</td>\n",
       "      <td>0.002720</td>\n",
       "      <td>0.00223</td>\n",
       "      <td>0.001450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Beta-Catenin</td>\n",
       "      <td>epithelia</td>\n",
       "      <td>9.760000e-01</td>\n",
       "      <td>9.760000e-01</td>\n",
       "      <td>0.000944</td>\n",
       "      <td>0.475000</td>\n",
       "      <td>0.113000</td>\n",
       "      <td>0.47200</td>\n",
       "      <td>0.168000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>areas******</td>\n",
       "      <td>epithelia</td>\n",
       "      <td>9.960000e-01</td>\n",
       "      <td>9.960000e-01</td>\n",
       "      <td>0.000022</td>\n",
       "      <td>26.900000</td>\n",
       "      <td>8.210000</td>\n",
       "      <td>26.80000</td>\n",
       "      <td>6.600000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>87 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         antigen           class         p_adj       p_value  F statistic  \\\n",
       "15         CD163       epithelia  2.330000e-08  7.780000e-09   609.000000   \n",
       "27          CD31       epithelia  9.460000e-07  3.150000e-07   237.000000   \n",
       "85    p-selectin  lamina_propria  1.050000e-06  3.500000e-07   231.000000   \n",
       "23         CD206           lumen  1.810000e-06  6.050000e-07   200.000000   \n",
       "8          CD11b           lumen  1.870000e-05  6.230000e-06   109.000000   \n",
       "..           ...             ...           ...           ...          ...   \n",
       "50           CD8           lumen  9.660000e-01  9.660000e-01     0.001990   \n",
       "16         CD163  lamina_propria  9.690000e-01  9.690000e-01     0.001660   \n",
       "42         CD66b       epithelia  9.690000e-01  9.690000e-01     0.001590   \n",
       "0   Beta-Catenin       epithelia  9.760000e-01  9.760000e-01     0.000944   \n",
       "81   areas******       epithelia  9.960000e-01  9.960000e-01     0.000022   \n",
       "\n",
       "    avg SSA mean exprs  SSA stdev  avg TA mean exprs  TA stdev  \n",
       "15            0.000481   0.000161            0.00570  0.000494  \n",
       "27            0.001830   0.000828            0.01110  0.001080  \n",
       "85            0.003850   0.001200            0.01690  0.001530  \n",
       "23            0.000653   0.000191            0.00336  0.000417  \n",
       "8             0.001450   0.000872            0.00847  0.001280  \n",
       "..                 ...        ...                ...       ...  \n",
       "50            0.002090   0.001490            0.00205  0.000876  \n",
       "16            0.005430   0.004530            0.00552  0.000517  \n",
       "42            0.002170   0.002720            0.00223  0.001450  \n",
       "0             0.475000   0.113000            0.47200  0.168000  \n",
       "81           26.900000   8.210000           26.80000  6.600000  \n",
       "\n",
       "[87 rows x 9 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "whole_class_analysis.whole_marker_exprs_ANOVA(marker_class = 'type', groupby_column = 'class', variable = 'condition', statistic = 'ANOVA', area = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a078455e-34c7-4993-9081-08003c4ec012",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "whole_class_analysis.plot_heatmap(\"p_adj\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "396dd3f2-2bdd-475e-8a63-18571e0c9c09",
   "metadata": {},
   "source": [
    "## Or export the data in tabular form to examine in another software / package:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "490e52e4-498d-42ca-bc14-65e376fdc9fe",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\benca\\miniforge3\\envs\\main\\lib\\site-packages\\anndata\\_core\\aligned_df.py:68: ImplicitModificationWarning: Transforming to str index.\n",
      "  warnings.warn(\"Transforming to str index.\", ImplicitModificationWarning)\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "        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>antigen</th>\n",
       "      <th>aSMA</th>\n",
       "      <th>p-selectin</th>\n",
       "      <th>Vimentin</th>\n",
       "      <th>CD14</th>\n",
       "      <th>CD31</th>\n",
       "      <th>CD16</th>\n",
       "      <th>Pan-Keratin</th>\n",
       "      <th>CD11b</th>\n",
       "      <th>CD163</th>\n",
       "      <th>CD45</th>\n",
       "      <th>...</th>\n",
       "      <th>Seg2</th>\n",
       "      <th>Seg3</th>\n",
       "      <th>index</th>\n",
       "      <th>sample_id</th>\n",
       "      <th>file_name</th>\n",
       "      <th>patient_id</th>\n",
       "      <th>condition</th>\n",
       "      <th>Object</th>\n",
       "      <th>class</th>\n",
       "      <th>areas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>0.003115</td>\n",
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       "      <td>0.014310</td>\n",
       "      <td>...</td>\n",
       "      <td>0.105902</td>\n",
       "      <td>0.168999</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>CRC_1_ROI_001.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
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       "      <td>lumen</td>\n",
       "      <td>16.497600</td>\n",
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       "    <tr>\n",
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       "      <td>0.004667</td>\n",
       "      <td>0.038276</td>\n",
       "      <td>0.012763</td>\n",
       "      <td>0.003151</td>\n",
       "      <td>0.006478</td>\n",
       "      <td>0.643430</td>\n",
       "      <td>0.007177</td>\n",
       "      <td>0.000741</td>\n",
       "      <td>0.037614</td>\n",
       "      <td>...</td>\n",
       "      <td>0.218496</td>\n",
       "      <td>0.217236</td>\n",
       "      <td>1</td>\n",
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       "      <td>CRC_1_ROI_001.ome.fcs</td>\n",
       "      <td>7139</td>\n",
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       "      <td>epithelia</td>\n",
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       "    <tr>\n",
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       "      <td>0.231591</td>\n",
       "      <td>0.038185</td>\n",
       "      <td>0.015873</td>\n",
       "      <td>0.008793</td>\n",
       "      <td>0.159639</td>\n",
       "      <td>0.010919</td>\n",
       "      <td>0.002667</td>\n",
       "      <td>0.175283</td>\n",
       "      <td>...</td>\n",
       "      <td>0.200154</td>\n",
       "      <td>0.181208</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>CRC_1_ROI_001.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>3</td>\n",
       "      <td>lamina_propria</td>\n",
       "      <td>47.452000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>0.052761</td>\n",
       "      <td>0.001284</td>\n",
       "      <td>0.016471</td>\n",
       "      <td>0.055562</td>\n",
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       "      <td>0.001374</td>\n",
       "      <td>0.048797</td>\n",
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       "      <td>0.000179</td>\n",
       "      <td>0.014350</td>\n",
       "      <td>...</td>\n",
       "      <td>0.067809</td>\n",
       "      <td>0.152127</td>\n",
       "      <td>3</td>\n",
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       "      <td>CRC_1_ROI_002.ome.fcs</td>\n",
       "      <td>7139</td>\n",
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       "      <td>lumen</td>\n",
       "      <td>35.531467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.441734</td>\n",
       "      <td>0.019529</td>\n",
       "      <td>0.028416</td>\n",
       "      <td>0.005586</td>\n",
       "      <td>0.002109</td>\n",
       "      <td>0.003486</td>\n",
       "      <td>0.095743</td>\n",
       "      <td>0.003626</td>\n",
       "      <td>0.000498</td>\n",
       "      <td>0.020471</td>\n",
       "      <td>...</td>\n",
       "      <td>0.148266</td>\n",
       "      <td>0.181678</td>\n",
       "      <td>4</td>\n",
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       "      <td>CRC_1_ROI_002.ome.fcs</td>\n",
       "      <td>7139</td>\n",
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       "      <td>epithelia</td>\n",
       "      <td>15.908267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>0.134013</td>\n",
       "      <td>0.023865</td>\n",
       "      <td>0.008549</td>\n",
       "      <td>0.005665</td>\n",
       "      <td>0.036053</td>\n",
       "      <td>0.004593</td>\n",
       "      <td>0.002851</td>\n",
       "      <td>0.090782</td>\n",
       "      <td>...</td>\n",
       "      <td>0.228512</td>\n",
       "      <td>0.158975</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>CRC_1_ROI_002.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>3</td>\n",
       "      <td>lamina_propria</td>\n",
       "      <td>48.560267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.043961</td>\n",
       "      <td>0.001348</td>\n",
       "      <td>0.039967</td>\n",
       "      <td>0.017418</td>\n",
       "      <td>0.001145</td>\n",
       "      <td>0.001152</td>\n",
       "      <td>0.063610</td>\n",
       "      <td>0.001428</td>\n",
       "      <td>0.000256</td>\n",
       "      <td>0.030570</td>\n",
       "      <td>...</td>\n",
       "      <td>0.074013</td>\n",
       "      <td>0.166255</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>CRC_2_ROI_001.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>1</td>\n",
       "      <td>lumen</td>\n",
       "      <td>40.148800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.050636</td>\n",
       "      <td>0.002190</td>\n",
       "      <td>0.015143</td>\n",
       "      <td>0.004244</td>\n",
       "      <td>0.001938</td>\n",
       "      <td>0.002836</td>\n",
       "      <td>0.239402</td>\n",
       "      <td>0.003481</td>\n",
       "      <td>0.000497</td>\n",
       "      <td>0.020262</td>\n",
       "      <td>...</td>\n",
       "      <td>0.093077</td>\n",
       "      <td>0.189527</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>CRC_2_ROI_001.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>2</td>\n",
       "      <td>epithelia</td>\n",
       "      <td>36.967600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.385122</td>\n",
       "      <td>0.003522</td>\n",
       "      <td>0.240166</td>\n",
       "      <td>0.021005</td>\n",
       "      <td>0.011558</td>\n",
       "      <td>0.004695</td>\n",
       "      <td>0.016083</td>\n",
       "      <td>0.007222</td>\n",
       "      <td>0.003367</td>\n",
       "      <td>0.160490</td>\n",
       "      <td>...</td>\n",
       "      <td>0.135513</td>\n",
       "      <td>0.174451</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>CRC_2_ROI_001.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>3</td>\n",
       "      <td>lamina_propria</td>\n",
       "      <td>22.883600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.048720</td>\n",
       "      <td>0.001244</td>\n",
       "      <td>0.017306</td>\n",
       "      <td>0.027874</td>\n",
       "      <td>0.000866</td>\n",
       "      <td>0.001455</td>\n",
       "      <td>0.084637</td>\n",
       "      <td>0.000899</td>\n",
       "      <td>0.000146</td>\n",
       "      <td>0.005761</td>\n",
       "      <td>...</td>\n",
       "      <td>0.128837</td>\n",
       "      <td>0.157224</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>CRC_2_ROI_002.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>1</td>\n",
       "      <td>lumen</td>\n",
       "      <td>44.958000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.238822</td>\n",
       "      <td>0.002845</td>\n",
       "      <td>0.017037</td>\n",
       "      <td>0.005089</td>\n",
       "      <td>0.001525</td>\n",
       "      <td>0.003130</td>\n",
       "      <td>0.157704</td>\n",
       "      <td>0.002277</td>\n",
       "      <td>0.000392</td>\n",
       "      <td>0.008053</td>\n",
       "      <td>...</td>\n",
       "      <td>0.175399</td>\n",
       "      <td>0.180829</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>CRC_2_ROI_002.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>2</td>\n",
       "      <td>epithelia</td>\n",
       "      <td>22.159600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.531417</td>\n",
       "      <td>0.005083</td>\n",
       "      <td>0.291689</td>\n",
       "      <td>0.020345</td>\n",
       "      <td>0.005762</td>\n",
       "      <td>0.005054</td>\n",
       "      <td>0.044761</td>\n",
       "      <td>0.004031</td>\n",
       "      <td>0.001856</td>\n",
       "      <td>0.093584</td>\n",
       "      <td>...</td>\n",
       "      <td>0.253888</td>\n",
       "      <td>0.167786</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>CRC_2_ROI_002.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>3</td>\n",
       "      <td>lamina_propria</td>\n",
       "      <td>32.882400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.035091</td>\n",
       "      <td>0.001602</td>\n",
       "      <td>0.027311</td>\n",
       "      <td>0.082346</td>\n",
       "      <td>0.001521</td>\n",
       "      <td>0.001601</td>\n",
       "      <td>0.082200</td>\n",
       "      <td>0.001488</td>\n",
       "      <td>0.000326</td>\n",
       "      <td>0.026056</td>\n",
       "      <td>...</td>\n",
       "      <td>0.047149</td>\n",
       "      <td>0.152558</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>CRC_2_ROI_003.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>1</td>\n",
       "      <td>lumen</td>\n",
       "      <td>7.479200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.110517</td>\n",
       "      <td>0.002089</td>\n",
       "      <td>0.033115</td>\n",
       "      <td>0.007243</td>\n",
       "      <td>0.001643</td>\n",
       "      <td>0.003004</td>\n",
       "      <td>0.138882</td>\n",
       "      <td>0.004171</td>\n",
       "      <td>0.000505</td>\n",
       "      <td>0.026921</td>\n",
       "      <td>...</td>\n",
       "      <td>0.157469</td>\n",
       "      <td>0.205587</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>CRC_2_ROI_003.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>2</td>\n",
       "      <td>epithelia</td>\n",
       "      <td>25.846400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.338910</td>\n",
       "      <td>0.003757</td>\n",
       "      <td>0.216403</td>\n",
       "      <td>0.024321</td>\n",
       "      <td>0.008768</td>\n",
       "      <td>0.011529</td>\n",
       "      <td>0.010334</td>\n",
       "      <td>0.009493</td>\n",
       "      <td>0.008544</td>\n",
       "      <td>0.156488</td>\n",
       "      <td>...</td>\n",
       "      <td>0.262179</td>\n",
       "      <td>0.173224</td>\n",
       "      <td>14</td>\n",
       "      <td>4</td>\n",
       "      <td>CRC_2_ROI_003.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>3</td>\n",
       "      <td>lamina_propria</td>\n",
       "      <td>66.674400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.031635</td>\n",
       "      <td>0.006760</td>\n",
       "      <td>0.021256</td>\n",
       "      <td>1.680096</td>\n",
       "      <td>0.053469</td>\n",
       "      <td>0.009906</td>\n",
       "      <td>0.005348</td>\n",
       "      <td>0.000664</td>\n",
       "      <td>0.001362</td>\n",
       "      <td>0.003080</td>\n",
       "      <td>...</td>\n",
       "      <td>0.016429</td>\n",
       "      <td>0.148124</td>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>CRC_2_ROI_004.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>1</td>\n",
       "      <td>lumen</td>\n",
       "      <td>4.778909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.183516</td>\n",
       "      <td>0.001641</td>\n",
       "      <td>0.016439</td>\n",
       "      <td>0.003520</td>\n",
       "      <td>0.000621</td>\n",
       "      <td>0.000745</td>\n",
       "      <td>0.025288</td>\n",
       "      <td>0.000837</td>\n",
       "      <td>0.000252</td>\n",
       "      <td>0.002806</td>\n",
       "      <td>...</td>\n",
       "      <td>0.047211</td>\n",
       "      <td>0.177667</td>\n",
       "      <td>16</td>\n",
       "      <td>5</td>\n",
       "      <td>CRC_2_ROI_004.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>2</td>\n",
       "      <td>epithelia</td>\n",
       "      <td>24.179636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.217762</td>\n",
       "      <td>0.002035</td>\n",
       "      <td>0.193029</td>\n",
       "      <td>0.015542</td>\n",
       "      <td>0.006711</td>\n",
       "      <td>0.002814</td>\n",
       "      <td>0.003055</td>\n",
       "      <td>0.004390</td>\n",
       "      <td>0.013288</td>\n",
       "      <td>0.042991</td>\n",
       "      <td>...</td>\n",
       "      <td>0.038650</td>\n",
       "      <td>0.154528</td>\n",
       "      <td>17</td>\n",
       "      <td>5</td>\n",
       "      <td>CRC_2_ROI_004.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>SSA</td>\n",
       "      <td>3</td>\n",
       "      <td>lamina_propria</td>\n",
       "      <td>71.041455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.062293</td>\n",
       "      <td>0.016413</td>\n",
       "      <td>0.100151</td>\n",
       "      <td>0.042670</td>\n",
       "      <td>0.007151</td>\n",
       "      <td>0.009943</td>\n",
       "      <td>0.107857</td>\n",
       "      <td>0.009370</td>\n",
       "      <td>0.003144</td>\n",
       "      <td>0.177840</td>\n",
       "      <td>...</td>\n",
       "      <td>0.084772</td>\n",
       "      <td>0.163744</td>\n",
       "      <td>18</td>\n",
       "      <td>6</td>\n",
       "      <td>CRC_3_ROI_001.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>TA</td>\n",
       "      <td>1</td>\n",
       "      <td>lumen</td>\n",
       "      <td>15.121000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.191357</td>\n",
       "      <td>0.019775</td>\n",
       "      <td>0.057836</td>\n",
       "      <td>0.018934</td>\n",
       "      <td>0.012637</td>\n",
       "      <td>0.015682</td>\n",
       "      <td>0.242961</td>\n",
       "      <td>0.015912</td>\n",
       "      <td>0.005724</td>\n",
       "      <td>0.105703</td>\n",
       "      <td>...</td>\n",
       "      <td>0.103431</td>\n",
       "      <td>0.200553</td>\n",
       "      <td>19</td>\n",
       "      <td>6</td>\n",
       "      <td>CRC_3_ROI_001.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>TA</td>\n",
       "      <td>2</td>\n",
       "      <td>epithelia</td>\n",
       "      <td>34.485600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.281676</td>\n",
       "      <td>0.018888</td>\n",
       "      <td>0.201009</td>\n",
       "      <td>0.027490</td>\n",
       "      <td>0.015082</td>\n",
       "      <td>0.020664</td>\n",
       "      <td>0.100855</td>\n",
       "      <td>0.017962</td>\n",
       "      <td>0.005775</td>\n",
       "      <td>0.407615</td>\n",
       "      <td>...</td>\n",
       "      <td>0.183162</td>\n",
       "      <td>0.180404</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>CRC_3_ROI_001.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>TA</td>\n",
       "      <td>3</td>\n",
       "      <td>lamina_propria</td>\n",
       "      <td>50.393400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.061697</td>\n",
       "      <td>0.015720</td>\n",
       "      <td>0.084369</td>\n",
       "      <td>0.089420</td>\n",
       "      <td>0.006197</td>\n",
       "      <td>0.009044</td>\n",
       "      <td>0.124590</td>\n",
       "      <td>0.009496</td>\n",
       "      <td>0.003162</td>\n",
       "      <td>0.076874</td>\n",
       "      <td>...</td>\n",
       "      <td>0.106464</td>\n",
       "      <td>0.143011</td>\n",
       "      <td>21</td>\n",
       "      <td>7</td>\n",
       "      <td>CRC_3_ROI_002.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>TA</td>\n",
       "      <td>1</td>\n",
       "      <td>lumen</td>\n",
       "      <td>12.536600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.167929</td>\n",
       "      <td>0.018500</td>\n",
       "      <td>0.051282</td>\n",
       "      <td>0.016637</td>\n",
       "      <td>0.010217</td>\n",
       "      <td>0.013284</td>\n",
       "      <td>0.239551</td>\n",
       "      <td>0.012887</td>\n",
       "      <td>0.005303</td>\n",
       "      <td>0.057870</td>\n",
       "      <td>...</td>\n",
       "      <td>0.092356</td>\n",
       "      <td>0.164743</td>\n",
       "      <td>22</td>\n",
       "      <td>7</td>\n",
       "      <td>CRC_3_ROI_002.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>TA</td>\n",
       "      <td>2</td>\n",
       "      <td>epithelia</td>\n",
       "      <td>29.006200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.208419</td>\n",
       "      <td>0.015966</td>\n",
       "      <td>0.149385</td>\n",
       "      <td>0.024263</td>\n",
       "      <td>0.013647</td>\n",
       "      <td>0.018055</td>\n",
       "      <td>0.104513</td>\n",
       "      <td>0.016503</td>\n",
       "      <td>0.005405</td>\n",
       "      <td>0.226643</td>\n",
       "      <td>...</td>\n",
       "      <td>0.169895</td>\n",
       "      <td>0.153509</td>\n",
       "      <td>23</td>\n",
       "      <td>7</td>\n",
       "      <td>CRC_3_ROI_002.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>TA</td>\n",
       "      <td>3</td>\n",
       "      <td>lamina_propria</td>\n",
       "      <td>58.457200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.053290</td>\n",
       "      <td>0.013046</td>\n",
       "      <td>0.022435</td>\n",
       "      <td>0.080215</td>\n",
       "      <td>0.005233</td>\n",
       "      <td>0.007236</td>\n",
       "      <td>0.041152</td>\n",
       "      <td>0.006740</td>\n",
       "      <td>0.002285</td>\n",
       "      <td>0.012031</td>\n",
       "      <td>...</td>\n",
       "      <td>0.045199</td>\n",
       "      <td>0.137282</td>\n",
       "      <td>24</td>\n",
       "      <td>8</td>\n",
       "      <td>CRC_3_ROI_003.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>TA</td>\n",
       "      <td>1</td>\n",
       "      <td>lumen</td>\n",
       "      <td>16.764000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.207609</td>\n",
       "      <td>0.015706</td>\n",
       "      <td>0.025147</td>\n",
       "      <td>0.013484</td>\n",
       "      <td>0.010499</td>\n",
       "      <td>0.012301</td>\n",
       "      <td>0.088116</td>\n",
       "      <td>0.010148</td>\n",
       "      <td>0.005396</td>\n",
       "      <td>0.020136</td>\n",
       "      <td>...</td>\n",
       "      <td>0.088967</td>\n",
       "      <td>0.151050</td>\n",
       "      <td>25</td>\n",
       "      <td>8</td>\n",
       "      <td>CRC_3_ROI_003.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>TA</td>\n",
       "      <td>2</td>\n",
       "      <td>epithelia</td>\n",
       "      <td>24.993600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.318935</td>\n",
       "      <td>0.017284</td>\n",
       "      <td>0.279070</td>\n",
       "      <td>0.029856</td>\n",
       "      <td>0.020118</td>\n",
       "      <td>0.016477</td>\n",
       "      <td>0.039863</td>\n",
       "      <td>0.013732</td>\n",
       "      <td>0.006054</td>\n",
       "      <td>0.100555</td>\n",
       "      <td>...</td>\n",
       "      <td>0.160039</td>\n",
       "      <td>0.145882</td>\n",
       "      <td>26</td>\n",
       "      <td>8</td>\n",
       "      <td>CRC_3_ROI_003.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>TA</td>\n",
       "      <td>3</td>\n",
       "      <td>lamina_propria</td>\n",
       "      <td>58.242400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.050464</td>\n",
       "      <td>0.015304</td>\n",
       "      <td>0.030541</td>\n",
       "      <td>0.016861</td>\n",
       "      <td>0.005928</td>\n",
       "      <td>0.008065</td>\n",
       "      <td>0.062523</td>\n",
       "      <td>0.008266</td>\n",
       "      <td>0.003270</td>\n",
       "      <td>0.038459</td>\n",
       "      <td>...</td>\n",
       "      <td>0.043146</td>\n",
       "      <td>0.134916</td>\n",
       "      <td>27</td>\n",
       "      <td>9</td>\n",
       "      <td>CRC_3_ROI_004.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>TA</td>\n",
       "      <td>1</td>\n",
       "      <td>lumen</td>\n",
       "      <td>26.593600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.114999</td>\n",
       "      <td>0.019065</td>\n",
       "      <td>0.041749</td>\n",
       "      <td>0.016181</td>\n",
       "      <td>0.010985</td>\n",
       "      <td>0.012104</td>\n",
       "      <td>0.159120</td>\n",
       "      <td>0.011640</td>\n",
       "      <td>0.006394</td>\n",
       "      <td>0.057640</td>\n",
       "      <td>...</td>\n",
       "      <td>0.052795</td>\n",
       "      <td>0.141570</td>\n",
       "      <td>28</td>\n",
       "      <td>9</td>\n",
       "      <td>CRC_3_ROI_004.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>TA</td>\n",
       "      <td>2</td>\n",
       "      <td>epithelia</td>\n",
       "      <td>18.830600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.230477</td>\n",
       "      <td>0.015477</td>\n",
       "      <td>0.069437</td>\n",
       "      <td>0.018115</td>\n",
       "      <td>0.013465</td>\n",
       "      <td>0.013979</td>\n",
       "      <td>0.053264</td>\n",
       "      <td>0.014817</td>\n",
       "      <td>0.004859</td>\n",
       "      <td>0.148455</td>\n",
       "      <td>...</td>\n",
       "      <td>0.101144</td>\n",
       "      <td>0.142696</td>\n",
       "      <td>29</td>\n",
       "      <td>9</td>\n",
       "      <td>CRC_3_ROI_004.ome.fcs</td>\n",
       "      <td>7139</td>\n",
       "      <td>TA</td>\n",
       "      <td>3</td>\n",
       "      <td>lamina_propria</td>\n",
       "      <td>54.575800</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>30 rows × 42 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "antigen      aSMA  p-selectin  Vimentin      CD14      CD31      CD16  \\\n",
       "0        0.046404    0.002377  0.021375  0.077686  0.001858  0.003592   \n",
       "1        0.279869    0.004667  0.038276  0.012763  0.003151  0.006478   \n",
       "2        0.583634    0.005288  0.231591  0.038185  0.015873  0.008793   \n",
       "3        0.052761    0.001284  0.016471  0.055562  0.001277  0.001374   \n",
       "4        0.441734    0.019529  0.028416  0.005586  0.002109  0.003486   \n",
       "5        0.461414    0.003406  0.134013  0.023865  0.008549  0.005665   \n",
       "6        0.043961    0.001348  0.039967  0.017418  0.001145  0.001152   \n",
       "7        0.050636    0.002190  0.015143  0.004244  0.001938  0.002836   \n",
       "8        0.385122    0.003522  0.240166  0.021005  0.011558  0.004695   \n",
       "9        0.048720    0.001244  0.017306  0.027874  0.000866  0.001455   \n",
       "10       0.238822    0.002845  0.017037  0.005089  0.001525  0.003130   \n",
       "11       0.531417    0.005083  0.291689  0.020345  0.005762  0.005054   \n",
       "12       0.035091    0.001602  0.027311  0.082346  0.001521  0.001601   \n",
       "13       0.110517    0.002089  0.033115  0.007243  0.001643  0.003004   \n",
       "14       0.338910    0.003757  0.216403  0.024321  0.008768  0.011529   \n",
       "15       0.031635    0.006760  0.021256  1.680096  0.053469  0.009906   \n",
       "16       0.183516    0.001641  0.016439  0.003520  0.000621  0.000745   \n",
       "17       0.217762    0.002035  0.193029  0.015542  0.006711  0.002814   \n",
       "18       0.062293    0.016413  0.100151  0.042670  0.007151  0.009943   \n",
       "19       0.191357    0.019775  0.057836  0.018934  0.012637  0.015682   \n",
       "20       0.281676    0.018888  0.201009  0.027490  0.015082  0.020664   \n",
       "21       0.061697    0.015720  0.084369  0.089420  0.006197  0.009044   \n",
       "22       0.167929    0.018500  0.051282  0.016637  0.010217  0.013284   \n",
       "23       0.208419    0.015966  0.149385  0.024263  0.013647  0.018055   \n",
       "24       0.053290    0.013046  0.022435  0.080215  0.005233  0.007236   \n",
       "25       0.207609    0.015706  0.025147  0.013484  0.010499  0.012301   \n",
       "26       0.318935    0.017284  0.279070  0.029856  0.020118  0.016477   \n",
       "27       0.050464    0.015304  0.030541  0.016861  0.005928  0.008065   \n",
       "28       0.114999    0.019065  0.041749  0.016181  0.010985  0.012104   \n",
       "29       0.230477    0.015477  0.069437  0.018115  0.013465  0.013979   \n",
       "\n",
       "antigen  Pan-Keratin     CD11b     CD163      CD45  ...      Seg2      Seg3  \\\n",
       "0           0.373355  0.003115  0.000352  0.014310  ...  0.105902  0.168999   \n",
       "1           0.643430  0.007177  0.000741  0.037614  ...  0.218496  0.217236   \n",
       "2           0.159639  0.010919  0.002667  0.175283  ...  0.200154  0.181208   \n",
       "3           0.048797  0.001126  0.000179  0.014350  ...  0.067809  0.152127   \n",
       "4           0.095743  0.003626  0.000498  0.020471  ...  0.148266  0.181678   \n",
       "5           0.036053  0.004593  0.002851  0.090782  ...  0.228512  0.158975   \n",
       "6           0.063610  0.001428  0.000256  0.030570  ...  0.074013  0.166255   \n",
       "7           0.239402  0.003481  0.000497  0.020262  ...  0.093077  0.189527   \n",
       "8           0.016083  0.007222  0.003367  0.160490  ...  0.135513  0.174451   \n",
       "9           0.084637  0.000899  0.000146  0.005761  ...  0.128837  0.157224   \n",
       "10          0.157704  0.002277  0.000392  0.008053  ...  0.175399  0.180829   \n",
       "11          0.044761  0.004031  0.001856  0.093584  ...  0.253888  0.167786   \n",
       "12          0.082200  0.001488  0.000326  0.026056  ...  0.047149  0.152558   \n",
       "13          0.138882  0.004171  0.000505  0.026921  ...  0.157469  0.205587   \n",
       "14          0.010334  0.009493  0.008544  0.156488  ...  0.262179  0.173224   \n",
       "15          0.005348  0.000664  0.001362  0.003080  ...  0.016429  0.148124   \n",
       "16          0.025288  0.000837  0.000252  0.002806  ...  0.047211  0.177667   \n",
       "17          0.003055  0.004390  0.013288  0.042991  ...  0.038650  0.154528   \n",
       "18          0.107857  0.009370  0.003144  0.177840  ...  0.084772  0.163744   \n",
       "19          0.242961  0.015912  0.005724  0.105703  ...  0.103431  0.200553   \n",
       "20          0.100855  0.017962  0.005775  0.407615  ...  0.183162  0.180404   \n",
       "21          0.124590  0.009496  0.003162  0.076874  ...  0.106464  0.143011   \n",
       "22          0.239551  0.012887  0.005303  0.057870  ...  0.092356  0.164743   \n",
       "23          0.104513  0.016503  0.005405  0.226643  ...  0.169895  0.153509   \n",
       "24          0.041152  0.006740  0.002285  0.012031  ...  0.045199  0.137282   \n",
       "25          0.088116  0.010148  0.005396  0.020136  ...  0.088967  0.151050   \n",
       "26          0.039863  0.013732  0.006054  0.100555  ...  0.160039  0.145882   \n",
       "27          0.062523  0.008266  0.003270  0.038459  ...  0.043146  0.134916   \n",
       "28          0.159120  0.011640  0.006394  0.057640  ...  0.052795  0.141570   \n",
       "29          0.053264  0.014817  0.004859  0.148455  ...  0.101144  0.142696   \n",
       "\n",
       "antigen  index  sample_id              file_name  patient_id  condition  \\\n",
       "0            0          0  CRC_1_ROI_001.ome.fcs        7139        SSA   \n",
       "1            1          0  CRC_1_ROI_001.ome.fcs        7139        SSA   \n",
       "2            2          0  CRC_1_ROI_001.ome.fcs        7139        SSA   \n",
       "3            3          1  CRC_1_ROI_002.ome.fcs        7139        SSA   \n",
       "4            4          1  CRC_1_ROI_002.ome.fcs        7139        SSA   \n",
       "5            5          1  CRC_1_ROI_002.ome.fcs        7139        SSA   \n",
       "6            6          2  CRC_2_ROI_001.ome.fcs        7139        SSA   \n",
       "7            7          2  CRC_2_ROI_001.ome.fcs        7139        SSA   \n",
       "8            8          2  CRC_2_ROI_001.ome.fcs        7139        SSA   \n",
       "9            9          3  CRC_2_ROI_002.ome.fcs        7139        SSA   \n",
       "10          10          3  CRC_2_ROI_002.ome.fcs        7139        SSA   \n",
       "11          11          3  CRC_2_ROI_002.ome.fcs        7139        SSA   \n",
       "12          12          4  CRC_2_ROI_003.ome.fcs        7139        SSA   \n",
       "13          13          4  CRC_2_ROI_003.ome.fcs        7139        SSA   \n",
       "14          14          4  CRC_2_ROI_003.ome.fcs        7139        SSA   \n",
       "15          15          5  CRC_2_ROI_004.ome.fcs        7139        SSA   \n",
       "16          16          5  CRC_2_ROI_004.ome.fcs        7139        SSA   \n",
       "17          17          5  CRC_2_ROI_004.ome.fcs        7139        SSA   \n",
       "18          18          6  CRC_3_ROI_001.ome.fcs        7139         TA   \n",
       "19          19          6  CRC_3_ROI_001.ome.fcs        7139         TA   \n",
       "20          20          6  CRC_3_ROI_001.ome.fcs        7139         TA   \n",
       "21          21          7  CRC_3_ROI_002.ome.fcs        7139         TA   \n",
       "22          22          7  CRC_3_ROI_002.ome.fcs        7139         TA   \n",
       "23          23          7  CRC_3_ROI_002.ome.fcs        7139         TA   \n",
       "24          24          8  CRC_3_ROI_003.ome.fcs        7139         TA   \n",
       "25          25          8  CRC_3_ROI_003.ome.fcs        7139         TA   \n",
       "26          26          8  CRC_3_ROI_003.ome.fcs        7139         TA   \n",
       "27          27          9  CRC_3_ROI_004.ome.fcs        7139         TA   \n",
       "28          28          9  CRC_3_ROI_004.ome.fcs        7139         TA   \n",
       "29          29          9  CRC_3_ROI_004.ome.fcs        7139         TA   \n",
       "\n",
       "antigen  Object           class      areas  \n",
       "0             1           lumen  16.497600  \n",
       "1             2       epithelia  36.050400  \n",
       "2             3  lamina_propria  47.452000  \n",
       "3             1           lumen  35.531467  \n",
       "4             2       epithelia  15.908267  \n",
       "5             3  lamina_propria  48.560267  \n",
       "6             1           lumen  40.148800  \n",
       "7             2       epithelia  36.967600  \n",
       "8             3  lamina_propria  22.883600  \n",
       "9             1           lumen  44.958000  \n",
       "10            2       epithelia  22.159600  \n",
       "11            3  lamina_propria  32.882400  \n",
       "12            1           lumen   7.479200  \n",
       "13            2       epithelia  25.846400  \n",
       "14            3  lamina_propria  66.674400  \n",
       "15            1           lumen   4.778909  \n",
       "16            2       epithelia  24.179636  \n",
       "17            3  lamina_propria  71.041455  \n",
       "18            1           lumen  15.121000  \n",
       "19            2       epithelia  34.485600  \n",
       "20            3  lamina_propria  50.393400  \n",
       "21            1           lumen  12.536600  \n",
       "22            2       epithelia  29.006200  \n",
       "23            3  lamina_propria  58.457200  \n",
       "24            1           lumen  16.764000  \n",
       "25            2       epithelia  24.993600  \n",
       "26            3  lamina_propria  58.242400  \n",
       "27            1           lumen  26.593600  \n",
       "28            2       epithelia  18.830600  \n",
       "29            3  lamina_propria  54.575800  \n",
       "\n",
       "[30 rows x 42 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "to_export = whole_class_analysis.export_data(filename = None,           #Or specify a file path to write to, usch as:   whole_class_analysis.directory + \"/my_data_export.csv\", \n",
    "                        subset_columns = None, \n",
    "                        subset_types = None, \n",
    "                        groupby_columns = None, \n",
    "                        statistic= 'mean',\n",
    "                        include_marker_class_row = False)   ## TODO: figure out csv reload with whole class analysis --> for now, not supported\n",
    "to_export"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f827203e-f6fd-4eaa-b08c-8b935128d136",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
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