T4_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a4ab43c2-3df6-4be6-a4a5-269495b4e1e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load relevant packages\n",
    "import datetime\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from esm import Alphabet, pretrained\n",
    "import torch\n",
    "from tqdm import tqdm\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy.stats as ss\n",
    "from prettytable import PrettyTable\n",
    "\n",
    "from scipy.special import softmax\n",
    "\n",
    "# # Use these packages if getting sequence from pdb website\n",
    "# import requests as r\n",
    "# from Bio import SeqIO\n",
    "# from io import StringIO\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b461c945-5d73-486b-ab34-0cf4e052a44b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save sequence\n",
    "sequence = 'MNIFEMLRIDEGLRLKIYKDTEGYYTIGIGHLLTKSPSLNAAKSELDKAIGRNCNGVITKDEAEKLFNQDVDAAVRGILRNAKLKPVYDSLDAVRRCALINMVFQMGETGVAGFTNSLRMLQQKRWDEAAVNLAKSRWYNQTPNRAKRVITTFRTGTWDAYKNL' \n",
    "data = [(\"Sars_Cov_2\", sequence)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "18ccc369-fb99-4412-b8d3-b09c4179acfd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save 1v model names\n",
    "models = ['esm1v_t33_650M_UR90S_'+str(i) for i in range(1,6) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4087fd4a-5cc7-49ac-9528-5bd17cf072f4",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>variant</th>\n",
       "      <th>pdb</th>\n",
       "      <th>ddG</th>\n",
       "      <th>ph</th>\n",
       "      <th>Change melting temp</th>\n",
       "      <th>effect</th>\n",
       "      <th>source</th>\n",
       "      <th>pos</th>\n",
       "      <th>wt</th>\n",
       "      <th>mut</th>\n",
       "      <th>...</th>\n",
       "      <th>log_wt_struct_prob_N</th>\n",
       "      <th>log_wt_struct_prob_M</th>\n",
       "      <th>log_wt_struct_prob_Q</th>\n",
       "      <th>log_wt_struct_prob_K</th>\n",
       "      <th>log_wt_struct_prob_E</th>\n",
       "      <th>log_wt_struct_prob_H</th>\n",
       "      <th>log_wt_struct_prob_F</th>\n",
       "      <th>log_wt_struct_prob_R</th>\n",
       "      <th>log_wt_struct_prob_Y</th>\n",
       "      <th>log_wt_struct_prob_W</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>I3P</td>\n",
       "      <td>1L97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[79]</td>\n",
       "      <td>3.0</td>\n",
       "      <td>I</td>\n",
       "      <td>P</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.216423</td>\n",
       "      <td>-8.071406</td>\n",
       "      <td>-8.913793</td>\n",
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       "      <td>-8.142480</td>\n",
       "      <td>-10.845514</td>\n",
       "      <td>-7.845176</td>\n",
       "      <td>-11.097267</td>\n",
       "      <td>-9.047691</td>\n",
       "      <td>-9.970913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>I3Y</td>\n",
       "      <td>1L18</td>\n",
       "      <td>-2.30</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[74]</td>\n",
       "      <td>3.0</td>\n",
       "      <td>I</td>\n",
       "      <td>Y</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.216423</td>\n",
       "      <td>-8.071406</td>\n",
       "      <td>-8.913793</td>\n",
       "      <td>-10.060715</td>\n",
       "      <td>-8.142480</td>\n",
       "      <td>-10.845514</td>\n",
       "      <td>-7.845176</td>\n",
       "      <td>-11.097267</td>\n",
       "      <td>-9.047691</td>\n",
       "      <td>-9.970913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>V87 M</td>\n",
       "      <td>1CU3</td>\n",
       "      <td>-2.30</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[66]</td>\n",
       "      <td>87.0</td>\n",
       "      <td>V</td>\n",
       "      <td>M</td>\n",
       "      <td>...</td>\n",
       "      <td>-12.369583</td>\n",
       "      <td>-15.449679</td>\n",
       "      <td>-14.032749</td>\n",
       "      <td>-16.231689</td>\n",
       "      <td>-12.467041</td>\n",
       "      <td>-14.776493</td>\n",
       "      <td>-15.759945</td>\n",
       "      <td>-16.640774</td>\n",
       "      <td>-15.491606</td>\n",
       "      <td>-19.604416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D92N</td>\n",
       "      <td>1L55</td>\n",
       "      <td>-1.40</td>\n",
       "      <td>5.7 -5.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[67]</td>\n",
       "      <td>92.0</td>\n",
       "      <td>D</td>\n",
       "      <td>N</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.080476</td>\n",
       "      <td>-11.444647</td>\n",
       "      <td>-8.490000</td>\n",
       "      <td>-11.505012</td>\n",
       "      <td>-5.416960</td>\n",
       "      <td>-10.329387</td>\n",
       "      <td>-13.879721</td>\n",
       "      <td>-12.119541</td>\n",
       "      <td>-14.275726</td>\n",
       "      <td>-15.394863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>R96D</td>\n",
       "      <td>3C8Q</td>\n",
       "      <td>-3.50</td>\n",
       "      <td>5.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[80]</td>\n",
       "      <td>96.0</td>\n",
       "      <td>R</td>\n",
       "      <td>D</td>\n",
       "      <td>...</td>\n",
       "      <td>-18.948048</td>\n",
       "      <td>-15.191552</td>\n",
       "      <td>-7.250073</td>\n",
       "      <td>-3.502644</td>\n",
       "      <td>-14.180872</td>\n",
       "      <td>-16.165663</td>\n",
       "      <td>-27.952499</td>\n",
       "      <td>-0.031315</td>\n",
       "      <td>-27.142101</td>\n",
       "      <td>-26.556032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>R96H</td>\n",
       "      <td>1L34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[78]</td>\n",
       "      <td>96.0</td>\n",
       "      <td>R</td>\n",
       "      <td>H</td>\n",
       "      <td>...</td>\n",
       "      <td>-18.948048</td>\n",
       "      <td>-15.191552</td>\n",
       "      <td>-7.250073</td>\n",
       "      <td>-3.502644</td>\n",
       "      <td>-14.180872</td>\n",
       "      <td>-16.165663</td>\n",
       "      <td>-27.952499</td>\n",
       "      <td>-0.031315</td>\n",
       "      <td>-27.142101</td>\n",
       "      <td>-26.556032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>R96N</td>\n",
       "      <td>3CDT</td>\n",
       "      <td>-3.00</td>\n",
       "      <td>5.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[80]</td>\n",
       "      <td>96.0</td>\n",
       "      <td>R</td>\n",
       "      <td>N</td>\n",
       "      <td>...</td>\n",
       "      <td>-18.948048</td>\n",
       "      <td>-15.191552</td>\n",
       "      <td>-7.250073</td>\n",
       "      <td>-3.502644</td>\n",
       "      <td>-14.180872</td>\n",
       "      <td>-16.165663</td>\n",
       "      <td>-27.952499</td>\n",
       "      <td>-0.031315</td>\n",
       "      <td>-27.142101</td>\n",
       "      <td>-26.556032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>R96W</td>\n",
       "      <td>3FI5</td>\n",
       "      <td>-4.50</td>\n",
       "      <td>5.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[80]</td>\n",
       "      <td>96.0</td>\n",
       "      <td>R</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>-18.948048</td>\n",
       "      <td>-15.191552</td>\n",
       "      <td>-7.250073</td>\n",
       "      <td>-3.502644</td>\n",
       "      <td>-14.180872</td>\n",
       "      <td>-16.165663</td>\n",
       "      <td>-27.952499</td>\n",
       "      <td>-0.031315</td>\n",
       "      <td>-27.142101</td>\n",
       "      <td>-26.556032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>R96Y</td>\n",
       "      <td>3C80</td>\n",
       "      <td>-4.70</td>\n",
       "      <td>5.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[80]</td>\n",
       "      <td>96.0</td>\n",
       "      <td>R</td>\n",
       "      <td>Y</td>\n",
       "      <td>...</td>\n",
       "      <td>-18.948048</td>\n",
       "      <td>-15.191552</td>\n",
       "      <td>-7.250073</td>\n",
       "      <td>-3.502644</td>\n",
       "      <td>-14.180872</td>\n",
       "      <td>-16.165663</td>\n",
       "      <td>-27.952499</td>\n",
       "      <td>-0.031315</td>\n",
       "      <td>-27.142101</td>\n",
       "      <td>-26.556032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>L99G</td>\n",
       "      <td>1QUD</td>\n",
       "      <td>-6.30</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[71]</td>\n",
       "      <td>99.0</td>\n",
       "      <td>L</td>\n",
       "      <td>G</td>\n",
       "      <td>...</td>\n",
       "      <td>-12.891812</td>\n",
       "      <td>-3.755546</td>\n",
       "      <td>-5.669210</td>\n",
       "      <td>-12.176689</td>\n",
       "      <td>-7.544851</td>\n",
       "      <td>-11.335819</td>\n",
       "      <td>-12.978987</td>\n",
       "      <td>-12.022253</td>\n",
       "      <td>-13.841916</td>\n",
       "      <td>-18.002825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>M102 K</td>\n",
       "      <td>1L54</td>\n",
       "      <td>-6.90</td>\n",
       "      <td>5.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[75]</td>\n",
       "      <td>102.0</td>\n",
       "      <td>M</td>\n",
       "      <td>K</td>\n",
       "      <td>...</td>\n",
       "      <td>-16.233498</td>\n",
       "      <td>-0.025517</td>\n",
       "      <td>-5.672086</td>\n",
       "      <td>-10.175391</td>\n",
       "      <td>-9.700732</td>\n",
       "      <td>-12.874337</td>\n",
       "      <td>-13.495420</td>\n",
       "      <td>-9.662448</td>\n",
       "      <td>-14.466680</td>\n",
       "      <td>-16.336973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>M102 L</td>\n",
       "      <td>1L77</td>\n",
       "      <td>-2.11</td>\n",
       "      <td>5.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[81]</td>\n",
       "      <td>102.0</td>\n",
       "      <td>M</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>-16.233498</td>\n",
       "      <td>-0.025517</td>\n",
       "      <td>-5.672086</td>\n",
       "      <td>-10.175391</td>\n",
       "      <td>-9.700732</td>\n",
       "      <td>-12.874337</td>\n",
       "      <td>-13.495420</td>\n",
       "      <td>-9.662448</td>\n",
       "      <td>-14.466680</td>\n",
       "      <td>-16.336973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>M106 K</td>\n",
       "      <td>231L</td>\n",
       "      <td>-3.40</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[73]</td>\n",
       "      <td>106.0</td>\n",
       "      <td>M</td>\n",
       "      <td>K</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.914564</td>\n",
       "      <td>-0.248584</td>\n",
       "      <td>-3.225198</td>\n",
       "      <td>-7.365138</td>\n",
       "      <td>-5.390009</td>\n",
       "      <td>-7.017539</td>\n",
       "      <td>-7.309026</td>\n",
       "      <td>-8.474434</td>\n",
       "      <td>-9.233020</td>\n",
       "      <td>-9.328678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>M120 K</td>\n",
       "      <td>232L</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[73]</td>\n",
       "      <td>120.0</td>\n",
       "      <td>M</td>\n",
       "      <td>K</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.533533</td>\n",
       "      <td>-4.049596</td>\n",
       "      <td>-7.349162</td>\n",
       "      <td>-6.827530</td>\n",
       "      <td>-4.368261</td>\n",
       "      <td>-4.098583</td>\n",
       "      <td>-2.895331</td>\n",
       "      <td>-7.886922</td>\n",
       "      <td>-2.259587</td>\n",
       "      <td>-5.685031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>V149C</td>\n",
       "      <td>1G07</td>\n",
       "      <td>-2.00</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[70]</td>\n",
       "      <td>149.0</td>\n",
       "      <td>V</td>\n",
       "      <td>C</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.434485</td>\n",
       "      <td>-13.987550</td>\n",
       "      <td>-11.916746</td>\n",
       "      <td>-15.720329</td>\n",
       "      <td>-8.669914</td>\n",
       "      <td>-13.586252</td>\n",
       "      <td>-14.553191</td>\n",
       "      <td>-16.605883</td>\n",
       "      <td>-15.047293</td>\n",
       "      <td>-17.091331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>V149G</td>\n",
       "      <td>1G0P</td>\n",
       "      <td>-4.90</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[70]</td>\n",
       "      <td>149.0</td>\n",
       "      <td>V</td>\n",
       "      <td>G</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.434485</td>\n",
       "      <td>-13.987550</td>\n",
       "      <td>-11.916746</td>\n",
       "      <td>-15.720329</td>\n",
       "      <td>-8.669914</td>\n",
       "      <td>-13.586252</td>\n",
       "      <td>-14.553191</td>\n",
       "      <td>-16.605883</td>\n",
       "      <td>-15.047293</td>\n",
       "      <td>-17.091331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>V149S</td>\n",
       "      <td>1G06</td>\n",
       "      <td>-4.40</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[70]</td>\n",
       "      <td>149.0</td>\n",
       "      <td>V</td>\n",
       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.434485</td>\n",
       "      <td>-13.987550</td>\n",
       "      <td>-11.916746</td>\n",
       "      <td>-15.720329</td>\n",
       "      <td>-8.669914</td>\n",
       "      <td>-13.586252</td>\n",
       "      <td>-14.553191</td>\n",
       "      <td>-16.605883</td>\n",
       "      <td>-15.047293</td>\n",
       "      <td>-17.091331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>G156D</td>\n",
       "      <td>1L16</td>\n",
       "      <td>-2.30</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[77]</td>\n",
       "      <td>156.0</td>\n",
       "      <td>G</td>\n",
       "      <td>D</td>\n",
       "      <td>...</td>\n",
       "      <td>-22.095886</td>\n",
       "      <td>-28.185972</td>\n",
       "      <td>-28.519749</td>\n",
       "      <td>-27.740616</td>\n",
       "      <td>-26.913807</td>\n",
       "      <td>-30.245333</td>\n",
       "      <td>-33.423195</td>\n",
       "      <td>-30.096153</td>\n",
       "      <td>-35.310284</td>\n",
       "      <td>-39.724064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>T157I</td>\n",
       "      <td>1L10</td>\n",
       "      <td>-1.20</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[76]</td>\n",
       "      <td>157.0</td>\n",
       "      <td>T</td>\n",
       "      <td>I</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.207110</td>\n",
       "      <td>-6.299634</td>\n",
       "      <td>-4.915653</td>\n",
       "      <td>-2.076097</td>\n",
       "      <td>-4.193454</td>\n",
       "      <td>-3.656439</td>\n",
       "      <td>-6.171806</td>\n",
       "      <td>-4.365052</td>\n",
       "      <td>-6.726000</td>\n",
       "      <td>-10.280515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>I3V</td>\n",
       "      <td>1L17</td>\n",
       "      <td>-0.40</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[74]</td>\n",
       "      <td>3.0</td>\n",
       "      <td>I</td>\n",
       "      <td>V</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.216423</td>\n",
       "      <td>-8.071406</td>\n",
       "      <td>-8.913793</td>\n",
       "      <td>-10.060715</td>\n",
       "      <td>-8.142480</td>\n",
       "      <td>-10.845514</td>\n",
       "      <td>-7.845176</td>\n",
       "      <td>-11.097267</td>\n",
       "      <td>-9.047691</td>\n",
       "      <td>-9.970913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>T26S</td>\n",
       "      <td>131L</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.4</td>\n",
       "      <td>1.35</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[65]</td>\n",
       "      <td>26.0</td>\n",
       "      <td>T</td>\n",
       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.574406</td>\n",
       "      <td>-2.487274</td>\n",
       "      <td>-1.634334</td>\n",
       "      <td>-2.479549</td>\n",
       "      <td>-4.193656</td>\n",
       "      <td>-5.160165</td>\n",
       "      <td>-11.659061</td>\n",
       "      <td>-0.490488</td>\n",
       "      <td>-11.359324</td>\n",
       "      <td>-14.462152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>S38 N</td>\n",
       "      <td>1L61</td>\n",
       "      <td>0.60</td>\n",
       "      <td>5.7 -5.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[67]</td>\n",
       "      <td>38.0</td>\n",
       "      <td>S</td>\n",
       "      <td>N</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.988344</td>\n",
       "      <td>-15.024984</td>\n",
       "      <td>-12.331521</td>\n",
       "      <td>-14.114929</td>\n",
       "      <td>-10.180093</td>\n",
       "      <td>-13.453718</td>\n",
       "      <td>-16.094793</td>\n",
       "      <td>-15.455302</td>\n",
       "      <td>-16.687977</td>\n",
       "      <td>-19.185911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>S38D</td>\n",
       "      <td>1L19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>2.20</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[68]</td>\n",
       "      <td>38.0</td>\n",
       "      <td>S</td>\n",
       "      <td>D</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.988344</td>\n",
       "      <td>-15.024984</td>\n",
       "      <td>-12.331521</td>\n",
       "      <td>-14.114929</td>\n",
       "      <td>-10.180093</td>\n",
       "      <td>-13.453718</td>\n",
       "      <td>-16.094793</td>\n",
       "      <td>-15.455302</td>\n",
       "      <td>-16.687977</td>\n",
       "      <td>-19.185911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>G77A</td>\n",
       "      <td>1L23</td>\n",
       "      <td>0.40</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[64]</td>\n",
       "      <td>77.0</td>\n",
       "      <td>G</td>\n",
       "      <td>A</td>\n",
       "      <td>...</td>\n",
       "      <td>-30.406574</td>\n",
       "      <td>-31.068670</td>\n",
       "      <td>-30.702740</td>\n",
       "      <td>-32.947838</td>\n",
       "      <td>-29.810358</td>\n",
       "      <td>-29.223377</td>\n",
       "      <td>-32.580826</td>\n",
       "      <td>-31.842476</td>\n",
       "      <td>-31.780712</td>\n",
       "      <td>-33.091774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>A82P</td>\n",
       "      <td>1L24</td>\n",
       "      <td>0.80</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[64]</td>\n",
       "      <td>82.0</td>\n",
       "      <td>A</td>\n",
       "      <td>P</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.718509</td>\n",
       "      <td>-6.296034</td>\n",
       "      <td>-3.880852</td>\n",
       "      <td>-2.479921</td>\n",
       "      <td>-1.676067</td>\n",
       "      <td>-5.530411</td>\n",
       "      <td>-6.841037</td>\n",
       "      <td>-4.025205</td>\n",
       "      <td>-6.686790</td>\n",
       "      <td>-7.617702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>A93T</td>\n",
       "      <td>129L</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.13</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[65]</td>\n",
       "      <td>93.0</td>\n",
       "      <td>A</td>\n",
       "      <td>T</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.426483</td>\n",
       "      <td>-7.792366</td>\n",
       "      <td>-4.712810</td>\n",
       "      <td>-4.069917</td>\n",
       "      <td>-1.726671</td>\n",
       "      <td>-6.257626</td>\n",
       "      <td>-9.077488</td>\n",
       "      <td>-5.422931</td>\n",
       "      <td>-9.761568</td>\n",
       "      <td>-10.875765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>M106 L</td>\n",
       "      <td>234L</td>\n",
       "      <td>0.50</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[73]</td>\n",
       "      <td>106.0</td>\n",
       "      <td>M</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.914564</td>\n",
       "      <td>-0.248584</td>\n",
       "      <td>-3.225198</td>\n",
       "      <td>-7.365138</td>\n",
       "      <td>-5.390009</td>\n",
       "      <td>-7.017539</td>\n",
       "      <td>-7.309026</td>\n",
       "      <td>-8.474434</td>\n",
       "      <td>-9.233020</td>\n",
       "      <td>-9.328678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>M106I</td>\n",
       "      <td>1P46</td>\n",
       "      <td>0.20</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[69]</td>\n",
       "      <td>106.0</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.914564</td>\n",
       "      <td>-0.248584</td>\n",
       "      <td>-3.225198</td>\n",
       "      <td>-7.365138</td>\n",
       "      <td>-5.390009</td>\n",
       "      <td>-7.017539</td>\n",
       "      <td>-7.309026</td>\n",
       "      <td>-8.474434</td>\n",
       "      <td>-9.233020</td>\n",
       "      <td>-9.328678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>E108V</td>\n",
       "      <td>1QUG</td>\n",
       "      <td>0.70</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[71]</td>\n",
       "      <td>108.0</td>\n",
       "      <td>E</td>\n",
       "      <td>V</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.676384</td>\n",
       "      <td>-6.453795</td>\n",
       "      <td>-4.505442</td>\n",
       "      <td>-4.695796</td>\n",
       "      <td>-0.292153</td>\n",
       "      <td>-8.129887</td>\n",
       "      <td>-10.726538</td>\n",
       "      <td>-5.754629</td>\n",
       "      <td>-11.398915</td>\n",
       "      <td>-11.815132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>T109 N</td>\n",
       "      <td>1L59</td>\n",
       "      <td>0.10</td>\n",
       "      <td>5.7 -5.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[67]</td>\n",
       "      <td>109.0</td>\n",
       "      <td>T</td>\n",
       "      <td>N</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.847973</td>\n",
       "      <td>-5.628192</td>\n",
       "      <td>-2.764118</td>\n",
       "      <td>-2.105052</td>\n",
       "      <td>-0.948811</td>\n",
       "      <td>-4.778814</td>\n",
       "      <td>-6.256803</td>\n",
       "      <td>-3.800779</td>\n",
       "      <td>-6.868489</td>\n",
       "      <td>-8.314435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>T109D</td>\n",
       "      <td>1L62</td>\n",
       "      <td>0.60</td>\n",
       "      <td>5.7 -5.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[67]</td>\n",
       "      <td>109.0</td>\n",
       "      <td>T</td>\n",
       "      <td>D</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.847973</td>\n",
       "      <td>-5.628192</td>\n",
       "      <td>-2.764118</td>\n",
       "      <td>-2.105052</td>\n",
       "      <td>-0.948811</td>\n",
       "      <td>-4.778814</td>\n",
       "      <td>-6.256803</td>\n",
       "      <td>-3.800779</td>\n",
       "      <td>-6.868489</td>\n",
       "      <td>-8.314435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>N116D</td>\n",
       "      <td>1L57</td>\n",
       "      <td>0.60</td>\n",
       "      <td>5.7 -5.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[67]</td>\n",
       "      <td>116.0</td>\n",
       "      <td>N</td>\n",
       "      <td>D</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.823436</td>\n",
       "      <td>-6.346559</td>\n",
       "      <td>-3.132391</td>\n",
       "      <td>-1.855245</td>\n",
       "      <td>-0.750515</td>\n",
       "      <td>-2.817406</td>\n",
       "      <td>-4.938764</td>\n",
       "      <td>-3.848497</td>\n",
       "      <td>-4.222532</td>\n",
       "      <td>-7.135623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>S117F</td>\n",
       "      <td>1TLA</td>\n",
       "      <td>1.10</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[72]</td>\n",
       "      <td>117.0</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.265299</td>\n",
       "      <td>-10.546600</td>\n",
       "      <td>-10.588413</td>\n",
       "      <td>-11.560900</td>\n",
       "      <td>-9.480951</td>\n",
       "      <td>-9.580183</td>\n",
       "      <td>-10.601681</td>\n",
       "      <td>-12.380770</td>\n",
       "      <td>-12.066770</td>\n",
       "      <td>-13.325095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>M120 L</td>\n",
       "      <td>233L</td>\n",
       "      <td>0.50</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[73]</td>\n",
       "      <td>120.0</td>\n",
       "      <td>M</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.533533</td>\n",
       "      <td>-4.049596</td>\n",
       "      <td>-7.349162</td>\n",
       "      <td>-6.827530</td>\n",
       "      <td>-4.368261</td>\n",
       "      <td>-4.098583</td>\n",
       "      <td>-2.895331</td>\n",
       "      <td>-7.886922</td>\n",
       "      <td>-2.259587</td>\n",
       "      <td>-5.685031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>M120Y</td>\n",
       "      <td>1P6Y</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[69]</td>\n",
       "      <td>120.0</td>\n",
       "      <td>M</td>\n",
       "      <td>Y</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.533533</td>\n",
       "      <td>-4.049596</td>\n",
       "      <td>-7.349162</td>\n",
       "      <td>-6.827530</td>\n",
       "      <td>-4.368261</td>\n",
       "      <td>-4.098583</td>\n",
       "      <td>-2.895331</td>\n",
       "      <td>-7.886922</td>\n",
       "      <td>-2.259587</td>\n",
       "      <td>-5.685031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>N144D</td>\n",
       "      <td>1L20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[68]</td>\n",
       "      <td>144.0</td>\n",
       "      <td>N</td>\n",
       "      <td>D</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.021426</td>\n",
       "      <td>-7.287958</td>\n",
       "      <td>-4.284033</td>\n",
       "      <td>-5.769155</td>\n",
       "      <td>-1.780854</td>\n",
       "      <td>-7.209849</td>\n",
       "      <td>-8.834448</td>\n",
       "      <td>-7.790079</td>\n",
       "      <td>-10.174706</td>\n",
       "      <td>-12.728216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>V149I</td>\n",
       "      <td>1G0Q</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[70]</td>\n",
       "      <td>149.0</td>\n",
       "      <td>V</td>\n",
       "      <td>I</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.434485</td>\n",
       "      <td>-13.987550</td>\n",
       "      <td>-11.916746</td>\n",
       "      <td>-15.720329</td>\n",
       "      <td>-8.669914</td>\n",
       "      <td>-13.586252</td>\n",
       "      <td>-14.553191</td>\n",
       "      <td>-16.605883</td>\n",
       "      <td>-15.047293</td>\n",
       "      <td>-17.091331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>V149M</td>\n",
       "      <td>1CV6</td>\n",
       "      <td>-2.80</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[66]</td>\n",
       "      <td>149.0</td>\n",
       "      <td>V</td>\n",
       "      <td>M</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.434485</td>\n",
       "      <td>-13.987550</td>\n",
       "      <td>-11.916746</td>\n",
       "      <td>-15.720329</td>\n",
       "      <td>-8.669914</td>\n",
       "      <td>-13.586252</td>\n",
       "      <td>-14.553191</td>\n",
       "      <td>-16.605883</td>\n",
       "      <td>-15.047293</td>\n",
       "      <td>-17.091331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>T151S</td>\n",
       "      <td>130L</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.93</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[65]</td>\n",
       "      <td>151.0</td>\n",
       "      <td>T</td>\n",
       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.716800</td>\n",
       "      <td>-5.177119</td>\n",
       "      <td>-1.825212</td>\n",
       "      <td>-4.116370</td>\n",
       "      <td>-0.446794</td>\n",
       "      <td>-2.339468</td>\n",
       "      <td>-6.560561</td>\n",
       "      <td>-5.025455</td>\n",
       "      <td>-6.770511</td>\n",
       "      <td>-8.916143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>T152 V</td>\n",
       "      <td>1G0L</td>\n",
       "      <td>0.20</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[70]</td>\n",
       "      <td>152.0</td>\n",
       "      <td>T</td>\n",
       "      <td>V</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.849098</td>\n",
       "      <td>-9.548656</td>\n",
       "      <td>-9.342344</td>\n",
       "      <td>-11.317858</td>\n",
       "      <td>-9.150127</td>\n",
       "      <td>-12.081868</td>\n",
       "      <td>-14.318321</td>\n",
       "      <td>-11.281811</td>\n",
       "      <td>-17.780228</td>\n",
       "      <td>-20.236177</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>40 rows × 132 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   variant   pdb   ddG        ph  Change melting temp         effect source  \\\n",
       "0      I3P  1L97   NaN       NaN                  NaN  Destabilizing   [79]   \n",
       "1      I3Y  1L18 -2.30       6.5                  NaN  Destabilizing   [74]   \n",
       "2    V87 M  1CU3 -2.30       5.4                  NaN  Destabilizing   [66]   \n",
       "3     D92N  1L55 -1.40  5.7 -5.9                  NaN  Destabilizing   [67]   \n",
       "4     R96D  3C8Q -3.50      5.35                  NaN  Destabilizing   [80]   \n",
       "5     R96H  1L34   NaN       NaN                  NaN  Destabilizing   [78]   \n",
       "6     R96N  3CDT -3.00      5.35                  NaN  Destabilizing   [80]   \n",
       "7     R96W  3FI5 -4.50      5.35                  NaN  Destabilizing   [80]   \n",
       "8     R96Y  3C80 -4.70      5.35                  NaN  Destabilizing   [80]   \n",
       "9     L99G  1QUD -6.30       5.4                  NaN  Destabilizing   [71]   \n",
       "10  M102 K  1L54 -6.90       5.3                  NaN  Destabilizing   [75]   \n",
       "11  M102 L  1L77 -2.11       5.7                  NaN  Destabilizing   [81]   \n",
       "12  M106 K  231L -3.40         3                  NaN  Destabilizing   [73]   \n",
       "13  M120 K  232L -1.60         3                  NaN  Destabilizing   [73]   \n",
       "14   V149C  1G07 -2.00       5.4                  NaN  Destabilizing   [70]   \n",
       "15   V149G  1G0P -4.90       5.4                  NaN  Destabilizing   [70]   \n",
       "16   V149S  1G06 -4.40       5.4                  NaN  Destabilizing   [70]   \n",
       "17   G156D  1L16 -2.30       6.5                  NaN  Destabilizing   [77]   \n",
       "18   T157I  1L10 -1.20         6                  NaN  Destabilizing   [76]   \n",
       "19     I3V  1L17 -0.40       6.5                  NaN        Neutral   [74]   \n",
       "20    T26S  131L   NaN       5.4                 1.35        Neutral   [65]   \n",
       "21   S38 N  1L61  0.60  5.7 -5.9                  NaN        Neutral   [67]   \n",
       "22    S38D  1L19   NaN         5                 2.20        Neutral   [68]   \n",
       "23    G77A  1L23  0.40       6.5                  NaN        Neutral   [64]   \n",
       "24    A82P  1L24  0.80       6.5                  NaN        Neutral   [64]   \n",
       "25    A93T  129L   NaN       5.4                 0.13        Neutral   [65]   \n",
       "26  M106 L  234L  0.50         3                  NaN        Neutral   [73]   \n",
       "27   M106I  1P46  0.20         5                  NaN        Neutral   [69]   \n",
       "28   E108V  1QUG  0.70       5.4                  NaN        Neutral   [71]   \n",
       "29  T109 N  1L59  0.10  5.7 -5.9                  NaN        Neutral   [67]   \n",
       "30   T109D  1L62  0.60  5.7 -5.9                  NaN        Neutral   [67]   \n",
       "31   N116D  1L57  0.60  5.7 -5.9                  NaN        Neutral   [67]   \n",
       "32   S117F  1TLA  1.10       5.4                  NaN        Neutral   [72]   \n",
       "33  M120 L  233L  0.50         3                  NaN        Neutral   [73]   \n",
       "34   M120Y  1P6Y -0.10         5                  NaN        Neutral   [69]   \n",
       "35   N144D  1L20   NaN         5                 2.00        Neutral   [68]   \n",
       "36   V149I  1G0Q -0.10       5.4                  NaN        Neutral   [70]   \n",
       "37   V149M  1CV6 -2.80       5.4                  NaN        Neutral   [66]   \n",
       "38   T151S  130L   NaN       5.4                 0.93        Neutral   [65]   \n",
       "39  T152 V  1G0L  0.20       5.4                  NaN        Neutral   [70]   \n",
       "\n",
       "      pos wt mut  ... log_wt_struct_prob_N log_wt_struct_prob_M  \\\n",
       "0     3.0  I   P  ...            -9.216423            -8.071406   \n",
       "1     3.0  I   Y  ...            -9.216423            -8.071406   \n",
       "2    87.0  V   M  ...           -12.369583           -15.449679   \n",
       "3    92.0  D   N  ...            -4.080476           -11.444647   \n",
       "4    96.0  R   D  ...           -18.948048           -15.191552   \n",
       "5    96.0  R   H  ...           -18.948048           -15.191552   \n",
       "6    96.0  R   N  ...           -18.948048           -15.191552   \n",
       "7    96.0  R   W  ...           -18.948048           -15.191552   \n",
       "8    96.0  R   Y  ...           -18.948048           -15.191552   \n",
       "9    99.0  L   G  ...           -12.891812            -3.755546   \n",
       "10  102.0  M   K  ...           -16.233498            -0.025517   \n",
       "11  102.0  M   L  ...           -16.233498            -0.025517   \n",
       "12  106.0  M   K  ...            -8.914564            -0.248584   \n",
       "13  120.0  M   K  ...            -5.533533            -4.049596   \n",
       "14  149.0  V   C  ...            -7.434485           -13.987550   \n",
       "15  149.0  V   G  ...            -7.434485           -13.987550   \n",
       "16  149.0  V   S  ...            -7.434485           -13.987550   \n",
       "17  156.0  G   D  ...           -22.095886           -28.185972   \n",
       "18  157.0  T   I  ...            -4.207110            -6.299634   \n",
       "19    3.0  I   V  ...            -9.216423            -8.071406   \n",
       "20   26.0  T   S  ...            -5.574406            -2.487274   \n",
       "21   38.0  S   N  ...            -8.988344           -15.024984   \n",
       "22   38.0  S   D  ...            -8.988344           -15.024984   \n",
       "23   77.0  G   A  ...           -30.406574           -31.068670   \n",
       "24   82.0  A   P  ...            -3.718509            -6.296034   \n",
       "25   93.0  A   T  ...            -2.426483            -7.792366   \n",
       "26  106.0  M   L  ...            -8.914564            -0.248584   \n",
       "27  106.0  M   I  ...            -8.914564            -0.248584   \n",
       "28  108.0  E   V  ...            -5.676384            -6.453795   \n",
       "29  109.0  T   N  ...            -3.847973            -5.628192   \n",
       "30  109.0  T   D  ...            -3.847973            -5.628192   \n",
       "31  116.0  N   D  ...            -2.823436            -6.346559   \n",
       "32  117.0  S   F  ...            -9.265299           -10.546600   \n",
       "33  120.0  M   L  ...            -5.533533            -4.049596   \n",
       "34  120.0  M   Y  ...            -5.533533            -4.049596   \n",
       "35  144.0  N   D  ...            -4.021426            -7.287958   \n",
       "36  149.0  V   I  ...            -7.434485           -13.987550   \n",
       "37  149.0  V   M  ...            -7.434485           -13.987550   \n",
       "38  151.0  T   S  ...            -4.716800            -5.177119   \n",
       "39  152.0  T   V  ...            -7.849098            -9.548656   \n",
       "\n",
       "    log_wt_struct_prob_Q  log_wt_struct_prob_K  log_wt_struct_prob_E  \\\n",
       "0              -8.913793            -10.060715             -8.142480   \n",
       "1              -8.913793            -10.060715             -8.142480   \n",
       "2             -14.032749            -16.231689            -12.467041   \n",
       "3              -8.490000            -11.505012             -5.416960   \n",
       "4              -7.250073             -3.502644            -14.180872   \n",
       "5              -7.250073             -3.502644            -14.180872   \n",
       "6              -7.250073             -3.502644            -14.180872   \n",
       "7              -7.250073             -3.502644            -14.180872   \n",
       "8              -7.250073             -3.502644            -14.180872   \n",
       "9              -5.669210            -12.176689             -7.544851   \n",
       "10             -5.672086            -10.175391             -9.700732   \n",
       "11             -5.672086            -10.175391             -9.700732   \n",
       "12             -3.225198             -7.365138             -5.390009   \n",
       "13             -7.349162             -6.827530             -4.368261   \n",
       "14            -11.916746            -15.720329             -8.669914   \n",
       "15            -11.916746            -15.720329             -8.669914   \n",
       "16            -11.916746            -15.720329             -8.669914   \n",
       "17            -28.519749            -27.740616            -26.913807   \n",
       "18             -4.915653             -2.076097             -4.193454   \n",
       "19             -8.913793            -10.060715             -8.142480   \n",
       "20             -1.634334             -2.479549             -4.193656   \n",
       "21            -12.331521            -14.114929            -10.180093   \n",
       "22            -12.331521            -14.114929            -10.180093   \n",
       "23            -30.702740            -32.947838            -29.810358   \n",
       "24             -3.880852             -2.479921             -1.676067   \n",
       "25             -4.712810             -4.069917             -1.726671   \n",
       "26             -3.225198             -7.365138             -5.390009   \n",
       "27             -3.225198             -7.365138             -5.390009   \n",
       "28             -4.505442             -4.695796             -0.292153   \n",
       "29             -2.764118             -2.105052             -0.948811   \n",
       "30             -2.764118             -2.105052             -0.948811   \n",
       "31             -3.132391             -1.855245             -0.750515   \n",
       "32            -10.588413            -11.560900             -9.480951   \n",
       "33             -7.349162             -6.827530             -4.368261   \n",
       "34             -7.349162             -6.827530             -4.368261   \n",
       "35             -4.284033             -5.769155             -1.780854   \n",
       "36            -11.916746            -15.720329             -8.669914   \n",
       "37            -11.916746            -15.720329             -8.669914   \n",
       "38             -1.825212             -4.116370             -0.446794   \n",
       "39             -9.342344            -11.317858             -9.150127   \n",
       "\n",
       "    log_wt_struct_prob_H  log_wt_struct_prob_F  log_wt_struct_prob_R  \\\n",
       "0             -10.845514             -7.845176            -11.097267   \n",
       "1             -10.845514             -7.845176            -11.097267   \n",
       "2             -14.776493            -15.759945            -16.640774   \n",
       "3             -10.329387            -13.879721            -12.119541   \n",
       "4             -16.165663            -27.952499             -0.031315   \n",
       "5             -16.165663            -27.952499             -0.031315   \n",
       "6             -16.165663            -27.952499             -0.031315   \n",
       "7             -16.165663            -27.952499             -0.031315   \n",
       "8             -16.165663            -27.952499             -0.031315   \n",
       "9             -11.335819            -12.978987            -12.022253   \n",
       "10            -12.874337            -13.495420             -9.662448   \n",
       "11            -12.874337            -13.495420             -9.662448   \n",
       "12             -7.017539             -7.309026             -8.474434   \n",
       "13             -4.098583             -2.895331             -7.886922   \n",
       "14            -13.586252            -14.553191            -16.605883   \n",
       "15            -13.586252            -14.553191            -16.605883   \n",
       "16            -13.586252            -14.553191            -16.605883   \n",
       "17            -30.245333            -33.423195            -30.096153   \n",
       "18             -3.656439             -6.171806             -4.365052   \n",
       "19            -10.845514             -7.845176            -11.097267   \n",
       "20             -5.160165            -11.659061             -0.490488   \n",
       "21            -13.453718            -16.094793            -15.455302   \n",
       "22            -13.453718            -16.094793            -15.455302   \n",
       "23            -29.223377            -32.580826            -31.842476   \n",
       "24             -5.530411             -6.841037             -4.025205   \n",
       "25             -6.257626             -9.077488             -5.422931   \n",
       "26             -7.017539             -7.309026             -8.474434   \n",
       "27             -7.017539             -7.309026             -8.474434   \n",
       "28             -8.129887            -10.726538             -5.754629   \n",
       "29             -4.778814             -6.256803             -3.800779   \n",
       "30             -4.778814             -6.256803             -3.800779   \n",
       "31             -2.817406             -4.938764             -3.848497   \n",
       "32             -9.580183            -10.601681            -12.380770   \n",
       "33             -4.098583             -2.895331             -7.886922   \n",
       "34             -4.098583             -2.895331             -7.886922   \n",
       "35             -7.209849             -8.834448             -7.790079   \n",
       "36            -13.586252            -14.553191            -16.605883   \n",
       "37            -13.586252            -14.553191            -16.605883   \n",
       "38             -2.339468             -6.560561             -5.025455   \n",
       "39            -12.081868            -14.318321            -11.281811   \n",
       "\n",
       "    log_wt_struct_prob_Y  log_wt_struct_prob_W  \n",
       "0              -9.047691             -9.970913  \n",
       "1              -9.047691             -9.970913  \n",
       "2             -15.491606            -19.604416  \n",
       "3             -14.275726            -15.394863  \n",
       "4             -27.142101            -26.556032  \n",
       "5             -27.142101            -26.556032  \n",
       "6             -27.142101            -26.556032  \n",
       "7             -27.142101            -26.556032  \n",
       "8             -27.142101            -26.556032  \n",
       "9             -13.841916            -18.002825  \n",
       "10            -14.466680            -16.336973  \n",
       "11            -14.466680            -16.336973  \n",
       "12             -9.233020             -9.328678  \n",
       "13             -2.259587             -5.685031  \n",
       "14            -15.047293            -17.091331  \n",
       "15            -15.047293            -17.091331  \n",
       "16            -15.047293            -17.091331  \n",
       "17            -35.310284            -39.724064  \n",
       "18             -6.726000            -10.280515  \n",
       "19             -9.047691             -9.970913  \n",
       "20            -11.359324            -14.462152  \n",
       "21            -16.687977            -19.185911  \n",
       "22            -16.687977            -19.185911  \n",
       "23            -31.780712            -33.091774  \n",
       "24             -6.686790             -7.617702  \n",
       "25             -9.761568            -10.875765  \n",
       "26             -9.233020             -9.328678  \n",
       "27             -9.233020             -9.328678  \n",
       "28            -11.398915            -11.815132  \n",
       "29             -6.868489             -8.314435  \n",
       "30             -6.868489             -8.314435  \n",
       "31             -4.222532             -7.135623  \n",
       "32            -12.066770            -13.325095  \n",
       "33             -2.259587             -5.685031  \n",
       "34             -2.259587             -5.685031  \n",
       "35            -10.174706            -12.728216  \n",
       "36            -15.047293            -17.091331  \n",
       "37            -15.047293            -17.091331  \n",
       "38             -6.770511             -8.916143  \n",
       "39            -17.780228            -20.236177  \n",
       "\n",
       "[40 rows x 132 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Save relevant dataframe, remove extra rows and columns\n",
    "t4_df = pd.read_csv(\"data_and_dms/T4_mutant_full_network_summary.csv\",header=1)\n",
    "t4_df = t4_df[~t4_df.variant.isnull()]\n",
    "t4_df = t4_df.sort_values([\"effect\",\"pos\",\"variant\"])\n",
    "t4_df.reset_index(inplace = True, drop = True)\n",
    "t4_df = t4_df.drop(\"Unnamed: 0\", axis = 1)\n",
    "t4_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "483d5b6b-a2b2-4fe7-9d14-11f8cacb3d38",
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Input \u001b[0;32mIn [5]\u001b[0m, in \u001b[0;36m<cell line: 5>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;66;03m# Loop over the models\u001b[39;00m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m mod \u001b[38;5;129;01min\u001b[39;00m models: \n\u001b[1;32m      6\u001b[0m     \n\u001b[1;32m      7\u001b[0m     \u001b[38;5;66;03m# Load model and check if GPU is available\u001b[39;00m\n\u001b[0;32m----> 8\u001b[0m     model, alphabet \u001b[38;5;241m=\u001b[39m \u001b[43mpretrained\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_model_and_alphabet\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmod\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      9\u001b[0m     model\u001b[38;5;241m.\u001b[39meval()\n\u001b[1;32m     10\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mcuda\u001b[38;5;241m.\u001b[39mis_available():\n",
      "File \u001b[0;32m/gscratch/spe/uwagura/miniconda3/envs/prot_processing_env/lib/python3.8/site-packages/esm/pretrained.py:24\u001b[0m, in \u001b[0;36mload_model_and_alphabet\u001b[0;34m(model_name)\u001b[0m\n\u001b[1;32m     22\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m load_model_and_alphabet_local(model_name)\n\u001b[1;32m     23\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 24\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mload_model_and_alphabet_hub\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel_name\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/gscratch/spe/uwagura/miniconda3/envs/prot_processing_env/lib/python3.8/site-packages/esm/pretrained.py:50\u001b[0m, in \u001b[0;36mload_model_and_alphabet_hub\u001b[0;34m(model_name)\u001b[0m\n\u001b[1;32m     48\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mload_model_and_alphabet_hub\u001b[39m(model_name):\n\u001b[1;32m     49\u001b[0m     url \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttps://dl.fbaipublicfiles.com/fair-esm/models/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmodel_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.pt\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m---> 50\u001b[0m     model_data \u001b[38;5;241m=\u001b[39m \u001b[43mload_hub_workaround\u001b[49m\u001b[43m(\u001b[49m\u001b[43murl\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     51\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m _has_regression_weights(model_name):\n\u001b[1;32m     52\u001b[0m         regression_data \u001b[38;5;241m=\u001b[39m load_regression_hub(model_name)\n",
      "File \u001b[0;32m/gscratch/spe/uwagura/miniconda3/envs/prot_processing_env/lib/python3.8/site-packages/esm/pretrained.py:29\u001b[0m, in \u001b[0;36mload_hub_workaround\u001b[0;34m(url)\u001b[0m\n\u001b[1;32m     27\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mload_hub_workaround\u001b[39m(url):\n\u001b[1;32m     28\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 29\u001b[0m         data \u001b[38;5;241m=\u001b[39m \u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhub\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_state_dict_from_url\u001b[49m\u001b[43m(\u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprogress\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmap_location\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcpu\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m     30\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m:\n\u001b[1;32m     31\u001b[0m         \u001b[38;5;66;03m# Pytorch version issue - see https://github.com/pytorch/pytorch/issues/43106\u001b[39;00m\n\u001b[1;32m     32\u001b[0m         fn \u001b[38;5;241m=\u001b[39m Path(url)\u001b[38;5;241m.\u001b[39mname\n",
      "File \u001b[0;32m/gscratch/spe/uwagura/miniconda3/envs/prot_processing_env/lib/python3.8/site-packages/torch/hub.py:731\u001b[0m, in \u001b[0;36mload_state_dict_from_url\u001b[0;34m(url, model_dir, map_location, progress, check_hash, file_name)\u001b[0m\n\u001b[1;32m    729\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m _is_legacy_zip_format(cached_file):\n\u001b[1;32m    730\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m _legacy_zip_load(cached_file, model_dir, map_location)\n\u001b[0;32m--> 731\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcached_file\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmap_location\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmap_location\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/gscratch/spe/uwagura/miniconda3/envs/prot_processing_env/lib/python3.8/site-packages/torch/serialization.py:712\u001b[0m, in \u001b[0;36mload\u001b[0;34m(f, map_location, pickle_module, **pickle_load_args)\u001b[0m\n\u001b[1;32m    710\u001b[0m             opened_file\u001b[38;5;241m.\u001b[39mseek(orig_position)\n\u001b[1;32m    711\u001b[0m             \u001b[38;5;28;01mreturn\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mjit\u001b[38;5;241m.\u001b[39mload(opened_file)\n\u001b[0;32m--> 712\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_load\u001b[49m\u001b[43m(\u001b[49m\u001b[43mopened_zipfile\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmap_location\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpickle_module\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mpickle_load_args\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    713\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _legacy_load(opened_file, map_location, pickle_module, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mpickle_load_args)\n",
      "File \u001b[0;32m/gscratch/spe/uwagura/miniconda3/envs/prot_processing_env/lib/python3.8/site-packages/torch/serialization.py:1049\u001b[0m, in \u001b[0;36m_load\u001b[0;34m(zip_file, map_location, pickle_module, pickle_file, **pickle_load_args)\u001b[0m\n\u001b[1;32m   1047\u001b[0m unpickler \u001b[38;5;241m=\u001b[39m UnpicklerWrapper(data_file, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mpickle_load_args)\n\u001b[1;32m   1048\u001b[0m unpickler\u001b[38;5;241m.\u001b[39mpersistent_load \u001b[38;5;241m=\u001b[39m persistent_load\n\u001b[0;32m-> 1049\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43munpickler\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1051\u001b[0m torch\u001b[38;5;241m.\u001b[39m_utils\u001b[38;5;241m.\u001b[39m_validate_loaded_sparse_tensors()\n\u001b[1;32m   1053\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m result\n",
      "File \u001b[0;32m/gscratch/spe/uwagura/miniconda3/envs/prot_processing_env/lib/python3.8/site-packages/torch/serialization.py:1019\u001b[0m, in \u001b[0;36m_load.<locals>.persistent_load\u001b[0;34m(saved_id)\u001b[0m\n\u001b[1;32m   1017\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m key \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m loaded_storages:\n\u001b[1;32m   1018\u001b[0m     nbytes \u001b[38;5;241m=\u001b[39m numel \u001b[38;5;241m*\u001b[39m torch\u001b[38;5;241m.\u001b[39m_utils\u001b[38;5;241m.\u001b[39m_element_size(dtype)\n\u001b[0;32m-> 1019\u001b[0m     \u001b[43mload_tensor\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnbytes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m_maybe_decode_ascii\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlocation\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1021\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m loaded_storages[key]\n",
      "File \u001b[0;32m/gscratch/spe/uwagura/miniconda3/envs/prot_processing_env/lib/python3.8/site-packages/torch/serialization.py:997\u001b[0m, in \u001b[0;36m_load.<locals>.load_tensor\u001b[0;34m(dtype, numel, key, location)\u001b[0m\n\u001b[1;32m    994\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mload_tensor\u001b[39m(dtype, numel, key, location):\n\u001b[1;32m    995\u001b[0m     name \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdata/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mkey\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m--> 997\u001b[0m     storage \u001b[38;5;241m=\u001b[39m \u001b[43mzip_file\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_storage_from_record\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_UntypedStorage\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mstorage()\u001b[38;5;241m.\u001b[39m_untyped()\n\u001b[1;32m    998\u001b[0m     \u001b[38;5;66;03m# TODO: Once we decide to break serialization FC, we can\u001b[39;00m\n\u001b[1;32m    999\u001b[0m     \u001b[38;5;66;03m# stop wrapping with _TypedStorage\u001b[39;00m\n\u001b[1;32m   1000\u001b[0m     loaded_storages[key] \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mstorage\u001b[38;5;241m.\u001b[39m_TypedStorage(\n\u001b[1;32m   1001\u001b[0m         wrap_storage\u001b[38;5;241m=\u001b[39mrestore_location(storage, location),\n\u001b[1;32m   1002\u001b[0m         dtype\u001b[38;5;241m=\u001b[39mdtype)\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "# set location to store models\n",
    "torch.hub.set_dir(\"/gscratch/scrubbed/uwagura/models\") # modify location for different machines\n",
    "\n",
    "# Loop over the models\n",
    "for mod in models: \n",
    "    \n",
    "    # Load model and check if GPU is available\n",
    "    model, alphabet = pretrained.load_model_and_alphabet(mod)\n",
    "    model.eval()\n",
    "    if torch.cuda.is_available():\n",
    "        model = model.cuda()\n",
    "        print(\"Transferred model to GPU\")\n",
    "    \n",
    "    # Load batch converters\n",
    "    batch_converter = alphabet.get_batch_converter()\n",
    "    batch_labels, batch_strs, batch_tokens = batch_converter(data)\n",
    "    \n",
    "    # Conduct DMS study for the given model\n",
    "    dms = pd.DataFrame()\n",
    "    for i in tqdm(range(batch_tokens.size(1))):\n",
    "        batch_tokens_masked = batch_tokens.clone()\n",
    "        batch_tokens_masked[0, i] = alphabet.mask_idx\n",
    "        with torch.no_grad():\n",
    "            token_probs = torch.log_softmax(\n",
    "                #model(batch_tokens_masked)[\"logits\"], dim=-1 # if gpu not available, use this\n",
    "                model(batch_tokens_masked.cuda())[\"logits\"], dim=-1\n",
    "            )\n",
    "        col = pd.DataFrame(token_probs[:, i].cpu())\n",
    "        col = col.transpose()\n",
    "        dms = pd.concat([dms,col],axis=1)\n",
    "        \n",
    "    # Relabel indices\n",
    "    idx_map = {0: '<cls>', 1: '<pad>', 2: '<eos>', 3: '<unk>', 4: 'L', 5: 'A', 6: 'G', 7: 'V', 8: 'S', 9: 'E', 10: 'R', 11: 'T', 12: 'I', 13: 'D', 14: 'P', 15: 'K', 16: 'Q', 17: 'N', 18: 'F', 19: 'Y', 20: 'M', 21: 'H', 22: 'W', 23: 'C', 24: 'X', 25: 'B', 26: 'U', 27: 'Z', 28: 'O', 29: '.', 30: '-', 31: '<null_1>', 32: '<mask>'}\n",
    "    dms = dms.rename(index = idx_map)\n",
    "    \n",
    "    # Relabel Columns\n",
    "    new_col = list(sequence)\n",
    "    new_col.append('<eos>')\n",
    "    new_col.insert(0,'<cls>')\n",
    "    dms.columns = new_col\n",
    "    \n",
    "    # Delete extraneous predictions and rare amino acids from DMS dataframe. Delete eos and cls token form sequence\n",
    "    dms = dms.drop(index = ['<cls>','<pad>','<unk>','.','-','<null_1>','<mask>','X','B','U','Z','O'])\n",
    "    dms = dms.drop(columns = ['<cls>','<eos>']) # DMS now has dimensions L x 20\n",
    "    \n",
    "    # Save DMS matrix\n",
    "    dms.to_csv(\"dms/dms_cov_esm_\"+str(models.index(mod))+\".csv\") # less detailed named\n",
    "    #dms.to_csv(\"dms_cov_esm_\"+str(models.index(mod))+\"_on_\"+str(datetime.datetime.now()).split(\".\")[0].replace(\":\",\"_\").replace(\" \",\"_at_\")+\".csv\") # For more detailed name\n",
    "    \n",
    "    # Isolate the Pseudoenergies of the relevant mutations\n",
    "    t4_df[\"logP_mut_\"+mod] = \"\"\n",
    "    t4_df[\"logP_wt_\"+mod] = \"\"\n",
    "    t4_df[\"log_mut_minus_wt_vals_\"+mod] = \"\"\n",
    "    for i, row in t4_df.iterrows():\n",
    "        wt, idx, mt = row[\"wt\"], int(row[\"pos\"]), row[\"mut\"]\n",
    "        assert dms.columns.values.tolist()[idx-1] == wt,  \"Wildtype at index \"+str(i)+\" does not match provided mutation\"\n",
    "        mut_pseudo_e = float(pd.DataFrame(dms.iloc[:, idx-1]).loc[mt if mt != '*' else '<eos>'])\n",
    "        wt_pseudo_e = float(pd.DataFrame(dms.iloc[:, idx-1]).loc[wt])\n",
    "        t4_df.loc[i,\"logP_mut_\"+mod] = mut_pseudo_e \n",
    "        t4_df.loc[i,\"logP_wt_\"+mod]  = wt_pseudo_e\n",
    "        t4_df.loc[i,\"log_mut_minus_wt_vals_\"+mod] = float(mut_pseudo_e - wt_pseudo_e)\n",
    "    \n",
    "    print(\"Finished running \"+mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d1b3b3d0-8bae-444d-95e1-fb92b8131fb2",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 't4_df' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Input \u001b[0;32mIn [4]\u001b[0m, in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# Save dataframe with DMS study to a csv file\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[43mt4_df\u001b[49m\u001b[38;5;241m.\u001b[39mto_csv(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mt4_df_dms.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
      "\u001b[0;31mNameError\u001b[0m: name 't4_df' is not defined"
     ]
    }
   ],
   "source": [
    "# Save dataframe with DMS study to a csv file\n",
    "t4_df.to_csv(\"data_and_dms/t4_df_dms.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e4bc7573-4ce9-486a-bc87-34cf2a5100b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>variant</th>\n",
       "      <th>pdb</th>\n",
       "      <th>ddG</th>\n",
       "      <th>ph</th>\n",
       "      <th>Change melting temp</th>\n",
       "      <th>effect</th>\n",
       "      <th>source</th>\n",
       "      <th>pos</th>\n",
       "      <th>wt</th>\n",
       "      <th>...</th>\n",
       "      <th>log_mut_minus_wt_vals_esm1v_t33_650M_UR90S_2</th>\n",
       "      <th>logP_mut_esm1v_t33_650M_UR90S_3</th>\n",
       "      <th>logP_wt_esm1v_t33_650M_UR90S_3</th>\n",
       "      <th>log_mut_minus_wt_vals_esm1v_t33_650M_UR90S_3</th>\n",
       "      <th>logP_mut_esm1v_t33_650M_UR90S_4</th>\n",
       "      <th>logP_wt_esm1v_t33_650M_UR90S_4</th>\n",
       "      <th>log_mut_minus_wt_vals_esm1v_t33_650M_UR90S_4</th>\n",
       "      <th>logP_mut_esm1v_t33_650M_UR90S_5</th>\n",
       "      <th>logP_wt_esm1v_t33_650M_UR90S_5</th>\n",
       "      <th>log_mut_minus_wt_vals_esm1v_t33_650M_UR90S_5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>I3P</td>\n",
       "      <td>1L97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[79]</td>\n",
       "      <td>3.0</td>\n",
       "      <td>I</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.093181</td>\n",
       "      <td>-2.757268</td>\n",
       "      <td>-2.984045</td>\n",
       "      <td>0.226777</td>\n",
       "      <td>-2.678515</td>\n",
       "      <td>-2.591516</td>\n",
       "      <td>-0.087000</td>\n",
       "      <td>-2.848950</td>\n",
       "      <td>-1.826837</td>\n",
       "      <td>-1.022114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>I3Y</td>\n",
       "      <td>1L18</td>\n",
       "      <td>-2.30</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[74]</td>\n",
       "      <td>3.0</td>\n",
       "      <td>I</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.679907</td>\n",
       "      <td>-3.773143</td>\n",
       "      <td>-2.984045</td>\n",
       "      <td>-0.789099</td>\n",
       "      <td>-3.789653</td>\n",
       "      <td>-2.591516</td>\n",
       "      <td>-1.198137</td>\n",
       "      <td>-3.391253</td>\n",
       "      <td>-1.826837</td>\n",
       "      <td>-1.564416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>V87 M</td>\n",
       "      <td>1CU3</td>\n",
       "      <td>-2.30</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[66]</td>\n",
       "      <td>87.0</td>\n",
       "      <td>V</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.799134</td>\n",
       "      <td>-4.193878</td>\n",
       "      <td>-2.558977</td>\n",
       "      <td>-1.634901</td>\n",
       "      <td>-3.927399</td>\n",
       "      <td>-1.835937</td>\n",
       "      <td>-2.091461</td>\n",
       "      <td>-3.739649</td>\n",
       "      <td>-1.204104</td>\n",
       "      <td>-2.535545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>D92N</td>\n",
       "      <td>1L55</td>\n",
       "      <td>-1.40</td>\n",
       "      <td>5.7 -5.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[67]</td>\n",
       "      <td>92.0</td>\n",
       "      <td>D</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.112341</td>\n",
       "      <td>-2.974851</td>\n",
       "      <td>-1.475794</td>\n",
       "      <td>-1.499057</td>\n",
       "      <td>-2.705520</td>\n",
       "      <td>-1.288987</td>\n",
       "      <td>-1.416532</td>\n",
       "      <td>-2.234180</td>\n",
       "      <td>-1.417174</td>\n",
       "      <td>-0.817006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>R96D</td>\n",
       "      <td>3C8Q</td>\n",
       "      <td>-3.50</td>\n",
       "      <td>5.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[80]</td>\n",
       "      <td>96.0</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.530868</td>\n",
       "      <td>-5.400778</td>\n",
       "      <td>-2.204632</td>\n",
       "      <td>-3.196146</td>\n",
       "      <td>-6.768423</td>\n",
       "      <td>-3.142191</td>\n",
       "      <td>-3.626232</td>\n",
       "      <td>-5.910809</td>\n",
       "      <td>-2.963436</td>\n",
       "      <td>-2.947373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>R96H</td>\n",
       "      <td>1L34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[78]</td>\n",
       "      <td>96.0</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.386983</td>\n",
       "      <td>-5.166353</td>\n",
       "      <td>-2.204632</td>\n",
       "      <td>-2.961721</td>\n",
       "      <td>-5.184538</td>\n",
       "      <td>-3.142191</td>\n",
       "      <td>-2.042347</td>\n",
       "      <td>-4.686327</td>\n",
       "      <td>-2.963436</td>\n",
       "      <td>-1.722891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>R96N</td>\n",
       "      <td>3CDT</td>\n",
       "      <td>-3.00</td>\n",
       "      <td>5.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[80]</td>\n",
       "      <td>96.0</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.814894</td>\n",
       "      <td>-5.205781</td>\n",
       "      <td>-2.204632</td>\n",
       "      <td>-3.001149</td>\n",
       "      <td>-5.674265</td>\n",
       "      <td>-3.142191</td>\n",
       "      <td>-2.532074</td>\n",
       "      <td>-4.772666</td>\n",
       "      <td>-2.963436</td>\n",
       "      <td>-1.809230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>R96W</td>\n",
       "      <td>3FI5</td>\n",
       "      <td>-4.50</td>\n",
       "      <td>5.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[80]</td>\n",
       "      <td>96.0</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.709326</td>\n",
       "      <td>-6.699885</td>\n",
       "      <td>-2.204632</td>\n",
       "      <td>-4.495253</td>\n",
       "      <td>-7.382060</td>\n",
       "      <td>-3.142191</td>\n",
       "      <td>-4.239868</td>\n",
       "      <td>-5.505838</td>\n",
       "      <td>-2.963436</td>\n",
       "      <td>-2.542402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>R96Y</td>\n",
       "      <td>3C80</td>\n",
       "      <td>-4.70</td>\n",
       "      <td>5.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[80]</td>\n",
       "      <td>96.0</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.399518</td>\n",
       "      <td>-4.853943</td>\n",
       "      <td>-2.204632</td>\n",
       "      <td>-2.649311</td>\n",
       "      <td>-5.832183</td>\n",
       "      <td>-3.142191</td>\n",
       "      <td>-2.689992</td>\n",
       "      <td>-3.377540</td>\n",
       "      <td>-2.963436</td>\n",
       "      <td>-0.414104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>L99G</td>\n",
       "      <td>1QUD</td>\n",
       "      <td>-6.30</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[71]</td>\n",
       "      <td>99.0</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.051749</td>\n",
       "      <td>-6.291917</td>\n",
       "      <td>-0.394203</td>\n",
       "      <td>-5.897714</td>\n",
       "      <td>-5.949593</td>\n",
       "      <td>-0.459273</td>\n",
       "      <td>-5.490320</td>\n",
       "      <td>-8.236081</td>\n",
       "      <td>-0.293011</td>\n",
       "      <td>-7.943070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>M102 K</td>\n",
       "      <td>1L54</td>\n",
       "      <td>-6.90</td>\n",
       "      <td>5.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[75]</td>\n",
       "      <td>102.0</td>\n",
       "      <td>M</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.271127</td>\n",
       "      <td>-5.942560</td>\n",
       "      <td>-1.941754</td>\n",
       "      <td>-4.000805</td>\n",
       "      <td>-6.232619</td>\n",
       "      <td>-1.902460</td>\n",
       "      <td>-4.330160</td>\n",
       "      <td>-8.187847</td>\n",
       "      <td>-2.149664</td>\n",
       "      <td>-6.038183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>M102 L</td>\n",
       "      <td>1L77</td>\n",
       "      <td>-2.11</td>\n",
       "      <td>5.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[81]</td>\n",
       "      <td>102.0</td>\n",
       "      <td>M</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.891957</td>\n",
       "      <td>-0.701734</td>\n",
       "      <td>-1.941754</td>\n",
       "      <td>1.240020</td>\n",
       "      <td>-0.956609</td>\n",
       "      <td>-1.902460</td>\n",
       "      <td>0.945850</td>\n",
       "      <td>-0.365208</td>\n",
       "      <td>-2.149664</td>\n",
       "      <td>1.784456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>M106 K</td>\n",
       "      <td>231L</td>\n",
       "      <td>-3.40</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[73]</td>\n",
       "      <td>106.0</td>\n",
       "      <td>M</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.536083</td>\n",
       "      <td>-7.441907</td>\n",
       "      <td>-1.841172</td>\n",
       "      <td>-5.600734</td>\n",
       "      <td>-5.004599</td>\n",
       "      <td>-1.577378</td>\n",
       "      <td>-3.427221</td>\n",
       "      <td>-6.346458</td>\n",
       "      <td>-1.964098</td>\n",
       "      <td>-4.382360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>M120 K</td>\n",
       "      <td>232L</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[73]</td>\n",
       "      <td>120.0</td>\n",
       "      <td>M</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.029042</td>\n",
       "      <td>-3.409618</td>\n",
       "      <td>-3.167665</td>\n",
       "      <td>-0.241953</td>\n",
       "      <td>-4.300396</td>\n",
       "      <td>-2.822069</td>\n",
       "      <td>-1.478327</td>\n",
       "      <td>-4.765019</td>\n",
       "      <td>-3.345756</td>\n",
       "      <td>-1.419263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>V149C</td>\n",
       "      <td>1G07</td>\n",
       "      <td>-2.00</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[70]</td>\n",
       "      <td>149.0</td>\n",
       "      <td>V</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.165637</td>\n",
       "      <td>-4.953917</td>\n",
       "      <td>-2.360339</td>\n",
       "      <td>-2.593577</td>\n",
       "      <td>-4.770191</td>\n",
       "      <td>-2.595520</td>\n",
       "      <td>-2.174671</td>\n",
       "      <td>-8.003215</td>\n",
       "      <td>-4.021777</td>\n",
       "      <td>-3.981438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>V149G</td>\n",
       "      <td>1G0P</td>\n",
       "      <td>-4.90</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[70]</td>\n",
       "      <td>149.0</td>\n",
       "      <td>V</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.861043</td>\n",
       "      <td>-4.214441</td>\n",
       "      <td>-2.360339</td>\n",
       "      <td>-1.854102</td>\n",
       "      <td>-3.984481</td>\n",
       "      <td>-2.595520</td>\n",
       "      <td>-1.388960</td>\n",
       "      <td>-8.198198</td>\n",
       "      <td>-4.021777</td>\n",
       "      <td>-4.176422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>V149S</td>\n",
       "      <td>1G06</td>\n",
       "      <td>-4.40</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[70]</td>\n",
       "      <td>149.0</td>\n",
       "      <td>V</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.389126</td>\n",
       "      <td>-3.460608</td>\n",
       "      <td>-2.360339</td>\n",
       "      <td>-1.100269</td>\n",
       "      <td>-3.443991</td>\n",
       "      <td>-2.595520</td>\n",
       "      <td>-0.848470</td>\n",
       "      <td>-7.325806</td>\n",
       "      <td>-4.021777</td>\n",
       "      <td>-3.304029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>G156D</td>\n",
       "      <td>1L16</td>\n",
       "      <td>-2.30</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[77]</td>\n",
       "      <td>156.0</td>\n",
       "      <td>G</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.279737</td>\n",
       "      <td>-3.213553</td>\n",
       "      <td>-2.469532</td>\n",
       "      <td>-0.744020</td>\n",
       "      <td>-2.967357</td>\n",
       "      <td>-1.358952</td>\n",
       "      <td>-1.608405</td>\n",
       "      <td>-4.260218</td>\n",
       "      <td>-0.124293</td>\n",
       "      <td>-4.135925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>T157I</td>\n",
       "      <td>1L10</td>\n",
       "      <td>-1.20</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Destabilizing</td>\n",
       "      <td>[76]</td>\n",
       "      <td>157.0</td>\n",
       "      <td>T</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.595764</td>\n",
       "      <td>-4.450788</td>\n",
       "      <td>-4.293965</td>\n",
       "      <td>-0.156823</td>\n",
       "      <td>-2.833375</td>\n",
       "      <td>-4.228646</td>\n",
       "      <td>1.395272</td>\n",
       "      <td>-3.979573</td>\n",
       "      <td>-3.152558</td>\n",
       "      <td>-0.827015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>I3V</td>\n",
       "      <td>1L17</td>\n",
       "      <td>-0.40</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[74]</td>\n",
       "      <td>3.0</td>\n",
       "      <td>I</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.533143</td>\n",
       "      <td>-2.834296</td>\n",
       "      <td>-2.984045</td>\n",
       "      <td>0.149749</td>\n",
       "      <td>-2.506928</td>\n",
       "      <td>-2.591516</td>\n",
       "      <td>0.084588</td>\n",
       "      <td>-2.499542</td>\n",
       "      <td>-1.826837</td>\n",
       "      <td>-0.672705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>T26S</td>\n",
       "      <td>131L</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.4</td>\n",
       "      <td>1.35</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[65]</td>\n",
       "      <td>26.0</td>\n",
       "      <td>T</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.923342</td>\n",
       "      <td>-3.355019</td>\n",
       "      <td>-0.054427</td>\n",
       "      <td>-3.300592</td>\n",
       "      <td>-2.312438</td>\n",
       "      <td>-0.126040</td>\n",
       "      <td>-2.186399</td>\n",
       "      <td>-4.492004</td>\n",
       "      <td>-0.017192</td>\n",
       "      <td>-4.474813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>S38 N</td>\n",
       "      <td>1L61</td>\n",
       "      <td>0.60</td>\n",
       "      <td>5.7 -5.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[67]</td>\n",
       "      <td>38.0</td>\n",
       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.503054</td>\n",
       "      <td>-2.593920</td>\n",
       "      <td>-2.756716</td>\n",
       "      <td>0.162796</td>\n",
       "      <td>-2.465159</td>\n",
       "      <td>-2.456443</td>\n",
       "      <td>-0.008716</td>\n",
       "      <td>-2.632498</td>\n",
       "      <td>-2.690967</td>\n",
       "      <td>0.058468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>S38D</td>\n",
       "      <td>1L19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>2.20</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[68]</td>\n",
       "      <td>38.0</td>\n",
       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>0.335653</td>\n",
       "      <td>-2.108578</td>\n",
       "      <td>-2.756716</td>\n",
       "      <td>0.648139</td>\n",
       "      <td>-2.193444</td>\n",
       "      <td>-2.456443</td>\n",
       "      <td>0.262999</td>\n",
       "      <td>-1.801580</td>\n",
       "      <td>-2.690967</td>\n",
       "      <td>0.889387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>G77A</td>\n",
       "      <td>1L23</td>\n",
       "      <td>0.40</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[64]</td>\n",
       "      <td>77.0</td>\n",
       "      <td>G</td>\n",
       "      <td>...</td>\n",
       "      <td>0.726003</td>\n",
       "      <td>-2.672495</td>\n",
       "      <td>-2.783994</td>\n",
       "      <td>0.111499</td>\n",
       "      <td>-2.534037</td>\n",
       "      <td>-2.302481</td>\n",
       "      <td>-0.231555</td>\n",
       "      <td>-2.882991</td>\n",
       "      <td>-3.674990</td>\n",
       "      <td>0.792000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24</td>\n",
       "      <td>A82P</td>\n",
       "      <td>1L24</td>\n",
       "      <td>0.80</td>\n",
       "      <td>6.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[64]</td>\n",
       "      <td>82.0</td>\n",
       "      <td>A</td>\n",
       "      <td>...</td>\n",
       "      <td>1.649426</td>\n",
       "      <td>-1.612853</td>\n",
       "      <td>-2.646938</td>\n",
       "      <td>1.034086</td>\n",
       "      <td>-2.659320</td>\n",
       "      <td>-2.728029</td>\n",
       "      <td>0.068709</td>\n",
       "      <td>-1.986326</td>\n",
       "      <td>-2.414887</td>\n",
       "      <td>0.428561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>A93T</td>\n",
       "      <td>129L</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.13</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[65]</td>\n",
       "      <td>93.0</td>\n",
       "      <td>A</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.156339</td>\n",
       "      <td>-3.337896</td>\n",
       "      <td>-2.871938</td>\n",
       "      <td>-0.465957</td>\n",
       "      <td>-3.354699</td>\n",
       "      <td>-3.050596</td>\n",
       "      <td>-0.304104</td>\n",
       "      <td>-3.421706</td>\n",
       "      <td>-3.447450</td>\n",
       "      <td>0.025743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>M106 L</td>\n",
       "      <td>234L</td>\n",
       "      <td>0.50</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[73]</td>\n",
       "      <td>106.0</td>\n",
       "      <td>M</td>\n",
       "      <td>...</td>\n",
       "      <td>0.012794</td>\n",
       "      <td>-1.651259</td>\n",
       "      <td>-1.841172</td>\n",
       "      <td>0.189914</td>\n",
       "      <td>-1.843879</td>\n",
       "      <td>-1.577378</td>\n",
       "      <td>-0.266501</td>\n",
       "      <td>-0.404736</td>\n",
       "      <td>-1.964098</td>\n",
       "      <td>1.559363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>M106I</td>\n",
       "      <td>1P46</td>\n",
       "      <td>0.20</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[69]</td>\n",
       "      <td>106.0</td>\n",
       "      <td>M</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.972444</td>\n",
       "      <td>-1.457607</td>\n",
       "      <td>-1.841172</td>\n",
       "      <td>0.383566</td>\n",
       "      <td>-1.516628</td>\n",
       "      <td>-1.577378</td>\n",
       "      <td>0.060750</td>\n",
       "      <td>-2.331169</td>\n",
       "      <td>-1.964098</td>\n",
       "      <td>-0.367071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>E108V</td>\n",
       "      <td>1QUG</td>\n",
       "      <td>0.70</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[71]</td>\n",
       "      <td>108.0</td>\n",
       "      <td>E</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.688524</td>\n",
       "      <td>-2.462082</td>\n",
       "      <td>-2.417371</td>\n",
       "      <td>-0.044712</td>\n",
       "      <td>-2.906019</td>\n",
       "      <td>-1.690442</td>\n",
       "      <td>-1.215577</td>\n",
       "      <td>-1.212643</td>\n",
       "      <td>-3.212924</td>\n",
       "      <td>2.000281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29</td>\n",
       "      <td>T109 N</td>\n",
       "      <td>1L59</td>\n",
       "      <td>0.10</td>\n",
       "      <td>5.7 -5.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[67]</td>\n",
       "      <td>109.0</td>\n",
       "      <td>T</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.702422</td>\n",
       "      <td>-3.280298</td>\n",
       "      <td>-2.455023</td>\n",
       "      <td>-0.825274</td>\n",
       "      <td>-3.609207</td>\n",
       "      <td>-1.755095</td>\n",
       "      <td>-1.854112</td>\n",
       "      <td>-2.705348</td>\n",
       "      <td>-2.174547</td>\n",
       "      <td>-0.530801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>30</td>\n",
       "      <td>T109D</td>\n",
       "      <td>1L62</td>\n",
       "      <td>0.60</td>\n",
       "      <td>5.7 -5.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[67]</td>\n",
       "      <td>109.0</td>\n",
       "      <td>T</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.673706</td>\n",
       "      <td>-4.028294</td>\n",
       "      <td>-2.455023</td>\n",
       "      <td>-1.573271</td>\n",
       "      <td>-4.333868</td>\n",
       "      <td>-1.755095</td>\n",
       "      <td>-2.578773</td>\n",
       "      <td>-4.140774</td>\n",
       "      <td>-2.174547</td>\n",
       "      <td>-1.966227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>31</td>\n",
       "      <td>N116D</td>\n",
       "      <td>1L57</td>\n",
       "      <td>0.60</td>\n",
       "      <td>5.7 -5.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[67]</td>\n",
       "      <td>116.0</td>\n",
       "      <td>N</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.239633</td>\n",
       "      <td>-3.964464</td>\n",
       "      <td>-2.034322</td>\n",
       "      <td>-1.930142</td>\n",
       "      <td>-3.512033</td>\n",
       "      <td>-2.375597</td>\n",
       "      <td>-1.136436</td>\n",
       "      <td>-6.047843</td>\n",
       "      <td>-3.283154</td>\n",
       "      <td>-2.764689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>32</td>\n",
       "      <td>S117F</td>\n",
       "      <td>1TLA</td>\n",
       "      <td>1.10</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[72]</td>\n",
       "      <td>117.0</td>\n",
       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.023962</td>\n",
       "      <td>-3.707334</td>\n",
       "      <td>-2.588590</td>\n",
       "      <td>-1.118744</td>\n",
       "      <td>-2.534822</td>\n",
       "      <td>-2.772692</td>\n",
       "      <td>0.237870</td>\n",
       "      <td>-3.615884</td>\n",
       "      <td>-4.627270</td>\n",
       "      <td>1.011386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>33</td>\n",
       "      <td>M120 L</td>\n",
       "      <td>233L</td>\n",
       "      <td>0.50</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[73]</td>\n",
       "      <td>120.0</td>\n",
       "      <td>M</td>\n",
       "      <td>...</td>\n",
       "      <td>2.340168</td>\n",
       "      <td>-0.844016</td>\n",
       "      <td>-3.167665</td>\n",
       "      <td>2.323649</td>\n",
       "      <td>-0.800666</td>\n",
       "      <td>-2.822069</td>\n",
       "      <td>2.021403</td>\n",
       "      <td>-0.767367</td>\n",
       "      <td>-3.345756</td>\n",
       "      <td>2.578388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>34</td>\n",
       "      <td>M120Y</td>\n",
       "      <td>1P6Y</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[69]</td>\n",
       "      <td>120.0</td>\n",
       "      <td>M</td>\n",
       "      <td>...</td>\n",
       "      <td>0.836217</td>\n",
       "      <td>-2.519645</td>\n",
       "      <td>-3.167665</td>\n",
       "      <td>0.648021</td>\n",
       "      <td>-2.580314</td>\n",
       "      <td>-2.822069</td>\n",
       "      <td>0.241755</td>\n",
       "      <td>-1.712410</td>\n",
       "      <td>-3.345756</td>\n",
       "      <td>1.633346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>35</td>\n",
       "      <td>N144D</td>\n",
       "      <td>1L20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[68]</td>\n",
       "      <td>144.0</td>\n",
       "      <td>N</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.413437</td>\n",
       "      <td>-3.028903</td>\n",
       "      <td>-2.529660</td>\n",
       "      <td>-0.499244</td>\n",
       "      <td>-3.177100</td>\n",
       "      <td>-2.241520</td>\n",
       "      <td>-0.935580</td>\n",
       "      <td>-2.464081</td>\n",
       "      <td>-1.119505</td>\n",
       "      <td>-1.344576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>36</td>\n",
       "      <td>V149I</td>\n",
       "      <td>1G0Q</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[70]</td>\n",
       "      <td>149.0</td>\n",
       "      <td>V</td>\n",
       "      <td>...</td>\n",
       "      <td>0.596597</td>\n",
       "      <td>-2.174500</td>\n",
       "      <td>-2.360339</td>\n",
       "      <td>0.185840</td>\n",
       "      <td>-2.317960</td>\n",
       "      <td>-2.595520</td>\n",
       "      <td>0.277560</td>\n",
       "      <td>-3.108726</td>\n",
       "      <td>-4.021777</td>\n",
       "      <td>0.913050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>37</td>\n",
       "      <td>V149M</td>\n",
       "      <td>1CV6</td>\n",
       "      <td>-2.80</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[66]</td>\n",
       "      <td>149.0</td>\n",
       "      <td>V</td>\n",
       "      <td>...</td>\n",
       "      <td>0.371019</td>\n",
       "      <td>-2.753208</td>\n",
       "      <td>-2.360339</td>\n",
       "      <td>-0.392869</td>\n",
       "      <td>-3.383894</td>\n",
       "      <td>-2.595520</td>\n",
       "      <td>-0.788373</td>\n",
       "      <td>-3.823484</td>\n",
       "      <td>-4.021777</td>\n",
       "      <td>0.198293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>38</td>\n",
       "      <td>T151S</td>\n",
       "      <td>130L</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.93</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[65]</td>\n",
       "      <td>151.0</td>\n",
       "      <td>T</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.134944</td>\n",
       "      <td>-2.597240</td>\n",
       "      <td>-2.885081</td>\n",
       "      <td>0.287840</td>\n",
       "      <td>-2.592539</td>\n",
       "      <td>-3.204352</td>\n",
       "      <td>0.611813</td>\n",
       "      <td>-3.232545</td>\n",
       "      <td>-3.757141</td>\n",
       "      <td>0.524595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>39</td>\n",
       "      <td>T152 V</td>\n",
       "      <td>1G0L</td>\n",
       "      <td>0.20</td>\n",
       "      <td>5.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>[70]</td>\n",
       "      <td>152.0</td>\n",
       "      <td>T</td>\n",
       "      <td>...</td>\n",
       "      <td>1.038397</td>\n",
       "      <td>-3.472871</td>\n",
       "      <td>-3.496645</td>\n",
       "      <td>0.023774</td>\n",
       "      <td>-2.906675</td>\n",
       "      <td>-3.188480</td>\n",
       "      <td>0.281806</td>\n",
       "      <td>-3.167342</td>\n",
       "      <td>-3.420079</td>\n",
       "      <td>0.252738</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>40 rows × 148 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0 variant   pdb   ddG        ph  Change melting temp  \\\n",
       "0            0     I3P  1L97   NaN       NaN                  NaN   \n",
       "1            1     I3Y  1L18 -2.30       6.5                  NaN   \n",
       "2            2   V87 M  1CU3 -2.30       5.4                  NaN   \n",
       "3            3    D92N  1L55 -1.40  5.7 -5.9                  NaN   \n",
       "4            4    R96D  3C8Q -3.50      5.35                  NaN   \n",
       "5            5    R96H  1L34   NaN       NaN                  NaN   \n",
       "6            6    R96N  3CDT -3.00      5.35                  NaN   \n",
       "7            7    R96W  3FI5 -4.50      5.35                  NaN   \n",
       "8            8    R96Y  3C80 -4.70      5.35                  NaN   \n",
       "9            9    L99G  1QUD -6.30       5.4                  NaN   \n",
       "10          10  M102 K  1L54 -6.90       5.3                  NaN   \n",
       "11          11  M102 L  1L77 -2.11       5.7                  NaN   \n",
       "12          12  M106 K  231L -3.40         3                  NaN   \n",
       "13          13  M120 K  232L -1.60         3                  NaN   \n",
       "14          14   V149C  1G07 -2.00       5.4                  NaN   \n",
       "15          15   V149G  1G0P -4.90       5.4                  NaN   \n",
       "16          16   V149S  1G06 -4.40       5.4                  NaN   \n",
       "17          17   G156D  1L16 -2.30       6.5                  NaN   \n",
       "18          18   T157I  1L10 -1.20         6                  NaN   \n",
       "19          19     I3V  1L17 -0.40       6.5                  NaN   \n",
       "20          20    T26S  131L   NaN       5.4                 1.35   \n",
       "21          21   S38 N  1L61  0.60  5.7 -5.9                  NaN   \n",
       "22          22    S38D  1L19   NaN         5                 2.20   \n",
       "23          23    G77A  1L23  0.40       6.5                  NaN   \n",
       "24          24    A82P  1L24  0.80       6.5                  NaN   \n",
       "25          25    A93T  129L   NaN       5.4                 0.13   \n",
       "26          26  M106 L  234L  0.50         3                  NaN   \n",
       "27          27   M106I  1P46  0.20         5                  NaN   \n",
       "28          28   E108V  1QUG  0.70       5.4                  NaN   \n",
       "29          29  T109 N  1L59  0.10  5.7 -5.9                  NaN   \n",
       "30          30   T109D  1L62  0.60  5.7 -5.9                  NaN   \n",
       "31          31   N116D  1L57  0.60  5.7 -5.9                  NaN   \n",
       "32          32   S117F  1TLA  1.10       5.4                  NaN   \n",
       "33          33  M120 L  233L  0.50         3                  NaN   \n",
       "34          34   M120Y  1P6Y -0.10         5                  NaN   \n",
       "35          35   N144D  1L20   NaN         5                 2.00   \n",
       "36          36   V149I  1G0Q -0.10       5.4                  NaN   \n",
       "37          37   V149M  1CV6 -2.80       5.4                  NaN   \n",
       "38          38   T151S  130L   NaN       5.4                 0.93   \n",
       "39          39  T152 V  1G0L  0.20       5.4                  NaN   \n",
       "\n",
       "           effect source    pos wt  ...  \\\n",
       "0   Destabilizing   [79]    3.0  I  ...   \n",
       "1   Destabilizing   [74]    3.0  I  ...   \n",
       "2   Destabilizing   [66]   87.0  V  ...   \n",
       "3   Destabilizing   [67]   92.0  D  ...   \n",
       "4   Destabilizing   [80]   96.0  R  ...   \n",
       "5   Destabilizing   [78]   96.0  R  ...   \n",
       "6   Destabilizing   [80]   96.0  R  ...   \n",
       "7   Destabilizing   [80]   96.0  R  ...   \n",
       "8   Destabilizing   [80]   96.0  R  ...   \n",
       "9   Destabilizing   [71]   99.0  L  ...   \n",
       "10  Destabilizing   [75]  102.0  M  ...   \n",
       "11  Destabilizing   [81]  102.0  M  ...   \n",
       "12  Destabilizing   [73]  106.0  M  ...   \n",
       "13  Destabilizing   [73]  120.0  M  ...   \n",
       "14  Destabilizing   [70]  149.0  V  ...   \n",
       "15  Destabilizing   [70]  149.0  V  ...   \n",
       "16  Destabilizing   [70]  149.0  V  ...   \n",
       "17  Destabilizing   [77]  156.0  G  ...   \n",
       "18  Destabilizing   [76]  157.0  T  ...   \n",
       "19        Neutral   [74]    3.0  I  ...   \n",
       "20        Neutral   [65]   26.0  T  ...   \n",
       "21        Neutral   [67]   38.0  S  ...   \n",
       "22        Neutral   [68]   38.0  S  ...   \n",
       "23        Neutral   [64]   77.0  G  ...   \n",
       "24        Neutral   [64]   82.0  A  ...   \n",
       "25        Neutral   [65]   93.0  A  ...   \n",
       "26        Neutral   [73]  106.0  M  ...   \n",
       "27        Neutral   [69]  106.0  M  ...   \n",
       "28        Neutral   [71]  108.0  E  ...   \n",
       "29        Neutral   [67]  109.0  T  ...   \n",
       "30        Neutral   [67]  109.0  T  ...   \n",
       "31        Neutral   [67]  116.0  N  ...   \n",
       "32        Neutral   [72]  117.0  S  ...   \n",
       "33        Neutral   [73]  120.0  M  ...   \n",
       "34        Neutral   [69]  120.0  M  ...   \n",
       "35        Neutral   [68]  144.0  N  ...   \n",
       "36        Neutral   [70]  149.0  V  ...   \n",
       "37        Neutral   [66]  149.0  V  ...   \n",
       "38        Neutral   [65]  151.0  T  ...   \n",
       "39        Neutral   [70]  152.0  T  ...   \n",
       "\n",
       "   log_mut_minus_wt_vals_esm1v_t33_650M_UR90S_2  \\\n",
       "0                                     -1.093181   \n",
       "1                                     -0.679907   \n",
       "2                                     -3.799134   \n",
       "3                                     -3.112341   \n",
       "4                                     -4.530868   \n",
       "5                                     -2.386983   \n",
       "6                                     -2.814894   \n",
       "7                                     -5.709326   \n",
       "8                                     -2.399518   \n",
       "9                                     -8.051749   \n",
       "10                                    -8.271127   \n",
       "11                                    -1.891957   \n",
       "12                                    -5.536083   \n",
       "13                                    -0.029042   \n",
       "14                                    -1.165637   \n",
       "15                                    -1.861043   \n",
       "16                                    -0.389126   \n",
       "17                                    -2.279737   \n",
       "18                                    -1.595764   \n",
       "19                                    -0.533143   \n",
       "20                                    -4.923342   \n",
       "21                                    -0.503054   \n",
       "22                                     0.335653   \n",
       "23                                     0.726003   \n",
       "24                                     1.649426   \n",
       "25                                    -0.156339   \n",
       "26                                     0.012794   \n",
       "27                                    -1.972444   \n",
       "28                                    -0.688524   \n",
       "29                                    -1.702422   \n",
       "30                                    -3.673706   \n",
       "31                                    -3.239633   \n",
       "32                                    -4.023962   \n",
       "33                                     2.340168   \n",
       "34                                     0.836217   \n",
       "35                                    -1.413437   \n",
       "36                                     0.596597   \n",
       "37                                     0.371019   \n",
       "38                                    -0.134944   \n",
       "39                                     1.038397   \n",
       "\n",
       "   logP_mut_esm1v_t33_650M_UR90S_3 logP_wt_esm1v_t33_650M_UR90S_3  \\\n",
       "0                        -2.757268                      -2.984045   \n",
       "1                        -3.773143                      -2.984045   \n",
       "2                        -4.193878                      -2.558977   \n",
       "3                        -2.974851                      -1.475794   \n",
       "4                        -5.400778                      -2.204632   \n",
       "5                        -5.166353                      -2.204632   \n",
       "6                        -5.205781                      -2.204632   \n",
       "7                        -6.699885                      -2.204632   \n",
       "8                        -4.853943                      -2.204632   \n",
       "9                        -6.291917                      -0.394203   \n",
       "10                       -5.942560                      -1.941754   \n",
       "11                       -0.701734                      -1.941754   \n",
       "12                       -7.441907                      -1.841172   \n",
       "13                       -3.409618                      -3.167665   \n",
       "14                       -4.953917                      -2.360339   \n",
       "15                       -4.214441                      -2.360339   \n",
       "16                       -3.460608                      -2.360339   \n",
       "17                       -3.213553                      -2.469532   \n",
       "18                       -4.450788                      -4.293965   \n",
       "19                       -2.834296                      -2.984045   \n",
       "20                       -3.355019                      -0.054427   \n",
       "21                       -2.593920                      -2.756716   \n",
       "22                       -2.108578                      -2.756716   \n",
       "23                       -2.672495                      -2.783994   \n",
       "24                       -1.612853                      -2.646938   \n",
       "25                       -3.337896                      -2.871938   \n",
       "26                       -1.651259                      -1.841172   \n",
       "27                       -1.457607                      -1.841172   \n",
       "28                       -2.462082                      -2.417371   \n",
       "29                       -3.280298                      -2.455023   \n",
       "30                       -4.028294                      -2.455023   \n",
       "31                       -3.964464                      -2.034322   \n",
       "32                       -3.707334                      -2.588590   \n",
       "33                       -0.844016                      -3.167665   \n",
       "34                       -2.519645                      -3.167665   \n",
       "35                       -3.028903                      -2.529660   \n",
       "36                       -2.174500                      -2.360339   \n",
       "37                       -2.753208                      -2.360339   \n",
       "38                       -2.597240                      -2.885081   \n",
       "39                       -3.472871                      -3.496645   \n",
       "\n",
       "    log_mut_minus_wt_vals_esm1v_t33_650M_UR90S_3  \\\n",
       "0                                       0.226777   \n",
       "1                                      -0.789099   \n",
       "2                                      -1.634901   \n",
       "3                                      -1.499057   \n",
       "4                                      -3.196146   \n",
       "5                                      -2.961721   \n",
       "6                                      -3.001149   \n",
       "7                                      -4.495253   \n",
       "8                                      -2.649311   \n",
       "9                                      -5.897714   \n",
       "10                                     -4.000805   \n",
       "11                                      1.240020   \n",
       "12                                     -5.600734   \n",
       "13                                     -0.241953   \n",
       "14                                     -2.593577   \n",
       "15                                     -1.854102   \n",
       "16                                     -1.100269   \n",
       "17                                     -0.744020   \n",
       "18                                     -0.156823   \n",
       "19                                      0.149749   \n",
       "20                                     -3.300592   \n",
       "21                                      0.162796   \n",
       "22                                      0.648139   \n",
       "23                                      0.111499   \n",
       "24                                      1.034086   \n",
       "25                                     -0.465957   \n",
       "26                                      0.189914   \n",
       "27                                      0.383566   \n",
       "28                                     -0.044712   \n",
       "29                                     -0.825274   \n",
       "30                                     -1.573271   \n",
       "31                                     -1.930142   \n",
       "32                                     -1.118744   \n",
       "33                                      2.323649   \n",
       "34                                      0.648021   \n",
       "35                                     -0.499244   \n",
       "36                                      0.185840   \n",
       "37                                     -0.392869   \n",
       "38                                      0.287840   \n",
       "39                                      0.023774   \n",
       "\n",
       "    logP_mut_esm1v_t33_650M_UR90S_4  logP_wt_esm1v_t33_650M_UR90S_4  \\\n",
       "0                         -2.678515                       -2.591516   \n",
       "1                         -3.789653                       -2.591516   \n",
       "2                         -3.927399                       -1.835937   \n",
       "3                         -2.705520                       -1.288987   \n",
       "4                         -6.768423                       -3.142191   \n",
       "5                         -5.184538                       -3.142191   \n",
       "6                         -5.674265                       -3.142191   \n",
       "7                         -7.382060                       -3.142191   \n",
       "8                         -5.832183                       -3.142191   \n",
       "9                         -5.949593                       -0.459273   \n",
       "10                        -6.232619                       -1.902460   \n",
       "11                        -0.956609                       -1.902460   \n",
       "12                        -5.004599                       -1.577378   \n",
       "13                        -4.300396                       -2.822069   \n",
       "14                        -4.770191                       -2.595520   \n",
       "15                        -3.984481                       -2.595520   \n",
       "16                        -3.443991                       -2.595520   \n",
       "17                        -2.967357                       -1.358952   \n",
       "18                        -2.833375                       -4.228646   \n",
       "19                        -2.506928                       -2.591516   \n",
       "20                        -2.312438                       -0.126040   \n",
       "21                        -2.465159                       -2.456443   \n",
       "22                        -2.193444                       -2.456443   \n",
       "23                        -2.534037                       -2.302481   \n",
       "24                        -2.659320                       -2.728029   \n",
       "25                        -3.354699                       -3.050596   \n",
       "26                        -1.843879                       -1.577378   \n",
       "27                        -1.516628                       -1.577378   \n",
       "28                        -2.906019                       -1.690442   \n",
       "29                        -3.609207                       -1.755095   \n",
       "30                        -4.333868                       -1.755095   \n",
       "31                        -3.512033                       -2.375597   \n",
       "32                        -2.534822                       -2.772692   \n",
       "33                        -0.800666                       -2.822069   \n",
       "34                        -2.580314                       -2.822069   \n",
       "35                        -3.177100                       -2.241520   \n",
       "36                        -2.317960                       -2.595520   \n",
       "37                        -3.383894                       -2.595520   \n",
       "38                        -2.592539                       -3.204352   \n",
       "39                        -2.906675                       -3.188480   \n",
       "\n",
       "    log_mut_minus_wt_vals_esm1v_t33_650M_UR90S_4  \\\n",
       "0                                      -0.087000   \n",
       "1                                      -1.198137   \n",
       "2                                      -2.091461   \n",
       "3                                      -1.416532   \n",
       "4                                      -3.626232   \n",
       "5                                      -2.042347   \n",
       "6                                      -2.532074   \n",
       "7                                      -4.239868   \n",
       "8                                      -2.689992   \n",
       "9                                      -5.490320   \n",
       "10                                     -4.330160   \n",
       "11                                      0.945850   \n",
       "12                                     -3.427221   \n",
       "13                                     -1.478327   \n",
       "14                                     -2.174671   \n",
       "15                                     -1.388960   \n",
       "16                                     -0.848470   \n",
       "17                                     -1.608405   \n",
       "18                                      1.395272   \n",
       "19                                      0.084588   \n",
       "20                                     -2.186399   \n",
       "21                                     -0.008716   \n",
       "22                                      0.262999   \n",
       "23                                     -0.231555   \n",
       "24                                      0.068709   \n",
       "25                                     -0.304104   \n",
       "26                                     -0.266501   \n",
       "27                                      0.060750   \n",
       "28                                     -1.215577   \n",
       "29                                     -1.854112   \n",
       "30                                     -2.578773   \n",
       "31                                     -1.136436   \n",
       "32                                      0.237870   \n",
       "33                                      2.021403   \n",
       "34                                      0.241755   \n",
       "35                                     -0.935580   \n",
       "36                                      0.277560   \n",
       "37                                     -0.788373   \n",
       "38                                      0.611813   \n",
       "39                                      0.281806   \n",
       "\n",
       "    logP_mut_esm1v_t33_650M_UR90S_5  logP_wt_esm1v_t33_650M_UR90S_5  \\\n",
       "0                         -2.848950                       -1.826837   \n",
       "1                         -3.391253                       -1.826837   \n",
       "2                         -3.739649                       -1.204104   \n",
       "3                         -2.234180                       -1.417174   \n",
       "4                         -5.910809                       -2.963436   \n",
       "5                         -4.686327                       -2.963436   \n",
       "6                         -4.772666                       -2.963436   \n",
       "7                         -5.505838                       -2.963436   \n",
       "8                         -3.377540                       -2.963436   \n",
       "9                         -8.236081                       -0.293011   \n",
       "10                        -8.187847                       -2.149664   \n",
       "11                        -0.365208                       -2.149664   \n",
       "12                        -6.346458                       -1.964098   \n",
       "13                        -4.765019                       -3.345756   \n",
       "14                        -8.003215                       -4.021777   \n",
       "15                        -8.198198                       -4.021777   \n",
       "16                        -7.325806                       -4.021777   \n",
       "17                        -4.260218                       -0.124293   \n",
       "18                        -3.979573                       -3.152558   \n",
       "19                        -2.499542                       -1.826837   \n",
       "20                        -4.492004                       -0.017192   \n",
       "21                        -2.632498                       -2.690967   \n",
       "22                        -1.801580                       -2.690967   \n",
       "23                        -2.882991                       -3.674990   \n",
       "24                        -1.986326                       -2.414887   \n",
       "25                        -3.421706                       -3.447450   \n",
       "26                        -0.404736                       -1.964098   \n",
       "27                        -2.331169                       -1.964098   \n",
       "28                        -1.212643                       -3.212924   \n",
       "29                        -2.705348                       -2.174547   \n",
       "30                        -4.140774                       -2.174547   \n",
       "31                        -6.047843                       -3.283154   \n",
       "32                        -3.615884                       -4.627270   \n",
       "33                        -0.767367                       -3.345756   \n",
       "34                        -1.712410                       -3.345756   \n",
       "35                        -2.464081                       -1.119505   \n",
       "36                        -3.108726                       -4.021777   \n",
       "37                        -3.823484                       -4.021777   \n",
       "38                        -3.232545                       -3.757141   \n",
       "39                        -3.167342                       -3.420079   \n",
       "\n",
       "    log_mut_minus_wt_vals_esm1v_t33_650M_UR90S_5  \n",
       "0                                      -1.022114  \n",
       "1                                      -1.564416  \n",
       "2                                      -2.535545  \n",
       "3                                      -0.817006  \n",
       "4                                      -2.947373  \n",
       "5                                      -1.722891  \n",
       "6                                      -1.809230  \n",
       "7                                      -2.542402  \n",
       "8                                      -0.414104  \n",
       "9                                      -7.943070  \n",
       "10                                     -6.038183  \n",
       "11                                      1.784456  \n",
       "12                                     -4.382360  \n",
       "13                                     -1.419263  \n",
       "14                                     -3.981438  \n",
       "15                                     -4.176422  \n",
       "16                                     -3.304029  \n",
       "17                                     -4.135925  \n",
       "18                                     -0.827015  \n",
       "19                                     -0.672705  \n",
       "20                                     -4.474813  \n",
       "21                                      0.058468  \n",
       "22                                      0.889387  \n",
       "23                                      0.792000  \n",
       "24                                      0.428561  \n",
       "25                                      0.025743  \n",
       "26                                      1.559363  \n",
       "27                                     -0.367071  \n",
       "28                                      2.000281  \n",
       "29                                     -0.530801  \n",
       "30                                     -1.966227  \n",
       "31                                     -2.764689  \n",
       "32                                      1.011386  \n",
       "33                                      2.578388  \n",
       "34                                      1.633346  \n",
       "35                                     -1.344576  \n",
       "36                                      0.913050  \n",
       "37                                      0.198293  \n",
       "38                                      0.524595  \n",
       "39                                      0.252738  \n",
       "\n",
       "[40 rows x 148 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t4_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9097278f-5226-47d7-9394-5b82d18f045f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read T4 Lysozme data with results of last dms study\n",
    "t4_df = pd.read_csv(\"data_and_dms/t4_df_dms.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2acf43d2-8f7b-4a11-bd79-5e3cbfa022cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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YL7jqeWWHqZMDgDVqae/KzH/0WmjZ+Xl9r/kXoN3I+nkfuCNi9YjYPSI+BfypwzVenpknDaKCUgfe2915fy/cBbXjzSJixUZqIkmSJE2eae+vLW+TNspY2FhpIBZpX3hy2PcerqbaYtvhMdNAOwy2xQtluzih6vvUSZI0cOW+vM/tIeshmfnbARS5WZu0nh/qB+DhbdI+2u9FMvNvEfEj4FGV5PUpHjZP7HDaQ2rHtwKf67ds4OvAR4BlCzi3o4hYBdihzUdHRdS3TwZgZWBdYEM6P7ck8N+Z+eGBVFLqzHt7Ht7fi3Zx7XgliuBYvbMtSZIkaa5p7681HQsbK6OMRdoXnjj2vYerqbbYdnjMjPr/CdkWL4rt4oRyoI8kaagiYgXgCODBXbJ+EXjlgIpdu01a1yU6B2jXNmXXlxvt1Vdo7dDMXL9TcOn+teOTMrP+oNZVZt4QET+hmIUxSDtSPETX1fdt7tXZwLMz89gF10h9iYivMfjvRa8+l5kHNVQ2eG934/29ONe1SVtr5LWQJEmSJtO099eajoWNjQZikfaFJ8tQ+95THjeD5tpi2+Ex0tD/E7ItXjhjkhPKrbskScP2Ebo/GB8DHJiZOaAyV2+T1m0/2IGIiDWYu4fpSZlZX2q0V+1Gs7dbPpKIWMbcmQM970HbxjCWo2xb9wX4E/ASYMcpedjuWUR8LyKyfL286fosFd7bPZmq+3sI99r1bdLqy05LkiRJqrG/BjQYCxtDo45FTlVfuAkD7n/b9x6Sptpi2+Gx1MT/E5qqtth2UeCKPpKkIYqINwMv6JLtd8ATM/PmARZd3z80M/O2AV5/PusD9bUgz1jE9f4M3Ebr4NwN5im77txFlH3OIs7t5D595L0NuBq4EriC4iH7t8AJS3xP3MWq7mk8iK3wVPDe7m7a7u9B32u3tEmzvyZJkiR1Z3+t2VjY2GgoFjltfeEmDLL/bd97eJpqi22Hx0iD/09o2tpi20X5S5IkDUdEPBd4a5dsZwGPysxrBlx8fQRyRMQqmXnTgMtpZ902aVcu9GKZeVtEXE3rvsDr9VH2VQste5HndtJuZP2yzBxGWVMnIpYDG5WHt7C42Stq5b3d3dTc30O61+7QJq3d0rmSJEmSWtlfazYWNhYajEVOTV+4CUPof9v3Hp6m2mLb4THR8P8Tmpq22HZRMxzoI0kauIh4HPCxLtn+ATwiMy8dQhXa7X17B2AUD9Xt9i5d7F6819Laoem0P+qqbdIW82++cRHnzhERKwP3qCWfsxQftht0v8r70zKz3bKbi/VS4I1DuG4vmvyueG/PYwrv72Hca+061VO5l7skSZLUJ/trzcbCGtdULHIK+8JNGHT/e9h972mNm0FzbbHt8Bho8v8JTWFbPGntoobEgT6SNIYiYlD7kraVmfUlNAcmInYDvsTcpSqrrgYemZnD2j7mkjZp6zGazs6/26Qtdj/T+vntyoD2/75OgaherL2Ic9vZnrkdr0lZCnNS3Lfy/jfDKCAzLwIuGsa1x5z39vym7f4exr3WblZau79nkiRJklrZX1tELGyS45DQeCxy2vrCTRh0/3uofe8pjptBc22x7XAPlvj/E5q2tnii2kUNzwrds0iS1JuI2B74DrDaPNluBB6XmScPsSrntUnbbIjlVf2rTdqyhV4sIlZgbufiij7KbrdHca8Wc2477fbJHdkDd0Qsj4gsX7dExGpl+mYR8YaI+E1EXBoRN0bEXyPivREx5yE3IlaNiGdHxI8i4pKIuDki/hkRX4+I+84tec7576jU4/Ae635E5Zy31D572sxnwCsrHz23ck719e1eytQc3tvzG/n9HRErRMStle/2JvPk/Y/affDNLtc+upL3P8u0Yd9r9b9T/8rMTv8zQZIkSdIs+2vNxsIaMwaxSGNdTFysy7738DTVFtsON2gM2mEwLmm7OKUc6CNJGoiI2Bz4Ie33xJ1xG/C0zDx2yNU5u03aqB6qLwPqI/C3W8T1tmXu3+vLOuS9hLlLi9aXrOzHjos4t512++SOcmT9TpX3fwNujIiXAX8F3gHsDGwArAJsA7waOKn8bgMQEfcBTgU+BTwC2JBihcSNgCcCv4yIfbrU456V939cQN3r59yT/pzaZ34VvLfnN/L7OzNvo5gNNGO+2Vqvqh13/FsVEXcFHlYeXgHMBCmHfa9tWjse1qp3kiRJ0lJjf63ZWFgjxiQWaayrMEmxLvvew9NUW2w73JAxaYfBuGQ7totTwK27JGkMDXtJ20ErZ4L8kO4Pri/JzK+NoEqntEnbdgTlkpnXRcRfgLtVkneKiBUz89YFXHLnNmm/71D2zRFxMq17tN43IlYoHzz7df8FnDOfdiPrTx5wGfPZqfL+VODjwPPK40sogiDrUPzuVi7T7wwcCjw2IvYFPk8RHLkJ+BNwA0WHdWY21ErApyPix5nZbjZJvR4nd6t0RNyB1u9vPfhxHfAjilkTD66kH83czjXAz7qVqbm8t7tq6v6+ktnZYW071BGxGfDkWvJ8AYgXAzN/hz+ZmdeV74d2r5X3+Z1ryb0GRyVJkqSpZn8NWEQsbNLikDBWsUhjXXPrcXK3SjcV67LvPVxNtcW2w80Yo3YYjEvaLk4pB/pIkhalfBD4LnD3LlnfnpkfHUGVyMy/RcQVtO4tuphR/P06gdYOzZrAXsD3F3CtdjNmTpgn/69o7dRsDOwB/KSfQsuR4//Rzzldrrcic2dDXJqZFw6qjB7sVHm/O8X34y/AK4AfzXT8yn/7t5idcbJ3RDyBIvAB8Gbgg5l5dZl/VeC9wEvKz9ei+L19ol6BsgNU7fyc3EO978Hs/sZX1fcxzsy3lNd+EPDzMvnizNyzh2urP97b7a/Z5P39L2B5+b7TzJmXMtvvuZRiduKydhkjYk3gwPLwFuAjM58N+V7bgbn7mP92ANeVJEmSpsVU99fGIBY2MuMSizTWVZiwWJd97+Frqi22HR6hcWmHy7oYl1wc28UJ5tZdkjTmImL3DntsdnvtN4K6rQh8GXhAl6yfzMw3D7s+NSfWjvtd2nAxftQm7fn9XiQitqToCFVdBvxhntO+3CbtNf2WvcBz5nN34A61tFEuZQytwY/1KB6I75uZP6jO7sjMvzI7+wmKEfRfBW4GHpaZb58JfJT5b6QIoJxROedePdThoszstPR3VfVa7WaGtLv2qH+208J7u70m7+8rK+/XrH8YEWsAzy0P/8DsbJZOM2eewez+71/PzAva5Nmp8n5Q/852f6Pqf8ckSZIkdWZ/bQCxsHGOQ5b1G6dYpLGuuXUY91iXfe/ha6otth2eznYYjEsulu3iBHOgjyRpMf4PeEyXPN8GXjCCutQdXTveKiLuNKKyvwlcVEvbOyIe1ed1Pszc1ff+LzNv7nRCZv6auQ94e0bE03otNCIeAjy751r2pt3ymSMLfkTEOsAWlaTzgSdUgxg1J9C6t/OKwDMz8xftMpfLzx5fSVrW4brVB+eT56lyVTX4Md85vebTwnlvt9fk/V1dNrzdzJlnMXs/fgC4aiZvGZioe2Hl/SEdyhzGvfbA2vElOGBPkiRJ6of9tWZjYaMyTrFIY12FSYp12fcevkbaYtvhkRqndhiMSy6W7eIEc+suSZosNzC7LF83Fw+zIhHxP3R/8D0e2G+Be/Au1lEUD09VuwNHDrvgcl/gjwDvrH30uYh4cGae3u0aEfE24NG15BuAXpa6fBtFp6rq0xFxXWZ+o0u5D6JYynfQ+wLfu03aKB8Yd6odv2aefcXJzNsi4mqKpTShWO74q13KuKry/toOeRYS/Nip8n6+/XGr+Xq9tvrgvd1Rk/d3xw51RKwAvKw8vJhittFOlSzLgMsr+R8CbF8e/qYMErVTvcbJfda3kz1qxz/MzHb7a0uSJElqw/4aMPhY2NjEIWEsY5HGugqTFOuy7z1kDbfFtsNDNobtMBiXXCzbxQnmij6SNFn+mZl79fjq9QGwbxHxYuD1XbKdCjwmM28YVj3mUy5Je0Yt+WEjrML7mfugtQFw7HzLaEbEsoj4FPCmNh+/NjPrMyLmyMxvAV+pJa8CfD0ivhwRDywfNKvl/kdE/B/F8pEzD6W/6lZWH9qNrD95gNfvZqfK+wuBr82XudxneP1K0iE9lHHnyvvzeqjHyd0uWP6eqns5tw1+RMTKtO6J7Kj74fHenqvJ+/vKyvv6ErmPBbYq3x9azvqqBinry+S+qPL+kHaFDeNei2L/981ryd9e7HUlSZKkKTTV/bUhxMLGIg4JYxuLNNY1tx4nd7tgU7Eu+94j1UhbbDs8le0wGJdcMNvFyeeKPpKkvkTEPsAHu2T7O7BXZl45/BrN6wvA/1SOHxsRK2XmLcMuODNvioj9gd/Q+pC3IfDFiHgLxSyBs4B/A3cE7kfxANhumcfvUyxZ2qsXANvR2nEGeEr5ui4i/gHcCmzC3AfRP1DMgvhBLb3vkfhlB6q+1+u1wJn9XmsRdqq8/2EPMwruzuyA6OuAn/ZQRvUh+8/1D8sH8e0qSfPNWJqxLbB6+f5Wis5SO9tTdFyh+D79rYdrawG8t1uNwf093xK5ryz/ez3w8fJ9dQnz2zvUEbEZ8Ljy8EKg06zGYdxrT6odXwF8bwDXlSRJkqaK/TWgwVjYsIxjLHIM+sJgrKtf9r1HpOG22HZ4CMaxHYaxaIsnPS5puzjhHOgjSepZROwOHM78K8JdDuyZmReOok5dHA68g9klN9enWCrzx6MoPDPPiIg9KDojG9U+vhvw3z1e6hvAAf0smZiZV5TLPR7D3KV8oehQ36XD6acCezO7VGRVp32+53M3YI1a2h8z87YFXGuhdqq8/2UP+at73f4uM2+aL3NErErx75zRbjT93Zl9EL+WojPbTz3+Ms9siJ0q709xec3h8t5u0fT9fWXl/e0d6oi4D7N7TB+emTNL4VZnziyrvH8BMLM39qHzBF92qrwf1L1W71R/uVubI0mSJKk9+2vNxsIGbYxjkU33hcFYV7/se49QU22x7fDgjXE7DM23xVdW3k9iXNJ2ccK5dZckqScRcU+KZftWnSfbdcCjM3PODI8mZOb5FJ2JqgNGXIffAbuwsAf5a4G3APssZLnLzLwMuD/wVuDGHk65FfgEsGtmXszc5SOh9WG0V43uWR4RK9H/kpbVoEMv+e/B7ADqTqPpq7MLTumxw1Gtx8k95nPbrhHw3r5do/c3rTNnqrOwZmbNJK3L3c6ZORMRqwDPKdOup/hZdTLQe61cIre+xPD/Lfa6kiRJ0jSb5v7aOMTCBmXMY5HGugoTEeuy792Mptpi2+HBGfN2GIxLLpjt4tLgQB9JUlcRsZxiucq158l2C8WD94kjqVTv/rd2/JSIWGeUFcjMszPz4cAjgO9SdFTmczbwAWDrzHzbYkagZ+aNmXkwsBx4MXA0xeyaa4GbgH8Ax1J0nLbJzP/MzJkHzo3bXPKKBVSj6T3Lq7OLbgJO7+Gcfh+ad6q8/2OH0fTVPCf3cE2A+1av22P5vV5bi+S9DTR/f89ZIjciNgX2KdN+lJnVvdHb7YW9L7Ozy75QmWXTzk6V9yf3W9k2nlc7/klm9rLUuSRJkqR5THl/rfFY2GJNQCyy6b6wsa7+2PduSFNtse3w4k1AOwzNt8WTHJe0XVwC3LpLkjSviNiQ4kF4k3myJfDszDxqNLXqXWb+LCL+wOzo7tWBpwMf6fH8Y5ldZnOxdTkGOKYcpX0/YHOKvYnXoFje8lLg1Mz86yDKq5X9D+DQ8tWr+9eOz690ePop+xXAK/o9b4B2qrw/rYeliVcAdqwk9Rv8OLlDnh0q7//U7YIRsRbF92TGfA/a1RlUncpXhfd2iwXd22X5Td/fV1bezyyR+xJg5fL9B2r5q//OZeV/X1xJ67bf+MDutfL7cmAtuR4IkiRJkqbSoPps09hfW2wsrGmTEIscg77wTpX3xrrmL9O+9wIthdiZ7fDCTEI7DGPRFl9ZeT8xcUnbxaXDgT6SNFmWRcSXgZ0pRpbfRvEgfDrFCPTPl8tLDkRErEGxzOQ2XbL+d2Z+flDlDsHbgG9Vjl8WER8d8b7Ztys7379oouxelftwP6yW/Jsm6jIAO1Xe9xLI2IbZvX1vBM6YJ28/ZVT3Nf9LD9d8Gq3Lop7cLlM5u2JmRsitFPtJqwHe241oWSK3/Ls1MyPltMw8upa/ZeZMRPwHs7MJj8nM0zoVNIR77WnABpXj347jgFlJkiRpKZjC/togYmEjjUPCkopFDttOlffGurqXad97TIx7W2w7bDvcp0mNS9ouLhFu3SVJk2Ud4CnAlsAdKDpodwb2At4FnBMR7ytH5C5KRKwMfI3iIXI+H8jM9yy2vGHKzG8D1eUjtwae3FB1JsWBzC4ZOeO4JioyADtV3ve7Z/mpmXnzfJkjImidFXVyh6zVn+e8+zqXM5zeWEn6Z2b+s0P2bSvv/56Zvew9rem1lO5tmDtz5iBml749pE3++l7YL6kct8tfNbB7rZxN+V+15Dcs9HqSJEmSloSB9dcGFAsbWRwSllYscgR2qrw31tW5TPve6pftsO1wP66svJ+IuKTt4tLiQB9Jmjx/B04AfkrRyaouzboq8Crg2HL08IKUnbnPUDwwzufIsrxJ8Lr6cfnvVE1EbAXUH9SvB77QQHUGobqkZb/Bj17yb8Xs0pw3Ax1H3lfcpdMH5cP24cCdKsknz3OtNSvvfbZTR0vw3obWmTPrAC8r319G+39XNfC4NUWwBOCvFPuOz2eQ99oTae2g/6xcxlqSJEnSFBpSf20QsbChxyFhycYih8lYV2/se6tntsO2wwswiXFJ28UlxP8ZJEnjL4GfUOzhumFmbpGZu2bmQzPzXhQPEM+geOCbsQuLewB9D8XyffM5GjgoM3MR5YxMZv4M+HolaSdg32ZqMxoR8Y6IuHOf5+wC/JzZZSBnHJGZVwysciMSEZsD65WHyfx7f8/oN/ixU+X9GfOMpj+/8v415QyJFhGxEfBd4HG1j+ard3X20xYR8YR58moJ8N6eVd5v15eH2zC7rPDHMvOGNvmvpwhSAjwEWK18/6Ee/p4N5F6LiBWBt1eSbmU2ECBJkiRpgo1Tf22BsbAm4pCwBGORw2Ksqzf2vaeX7fCC2Q73adLikraLS094L0rS0hAR6wE/prXj9sjM/GGf13kl8P4u2X4H7JGZ1/RXy2aVHeEzmN2T+mxgu3Jv4CUnIm4AVqIY7f9tiv2Pz6gvz1t+d3YFngU8lrkDgS8GdszMy4Ze6QGLiMcA3ykP/5qZ286XvzznEmDD8vABmfmrLvnfwezylp/LzIM65PsQrctxngF8AjiHooO2G/BUitH5xwOrMLtH7wGZeWSH665KEVjZsJL8F+AC4Jby+JeZ+fb6uZpM3tutIuIiYJNK0k3AFpn5jw75LwPWryRdCWyWmdd2KWcg91pEPJfi3p/xwcx8+XznSJIkSZoM49ZfG1YsbFBxyPJaSzYWOQzGunrrf9v3nl62w7bDozRJcUnbxaVnpaYrIEkajMy8ohzF+xeKJRuhGI3b84NdROwPvK9LtjOBR03iA11mnh8RB9D68LucYmnEpWpF4OHlC+DmsnN/FcVzwLrABkCnJUNvAp4+wQMBdqq87zpjKSI2ZfZh+TbglD7LOHmefO+lmBUxs0/vdsAH2uT7HsWMjfN6uW5m3hgRzwe+zOyz3ba0LsH523nqpck07fd21b9o7VB/sVNnunQ1rR3qT3XrTMNA77UA3jpzWbrvwS1JkiRpsoxNf21YsbBBxCFh6ccih2SnyntjXZ3Z955utsM9sh1etEmKS9ouLjGu6CNJS0xEHAYcWB5eD6w7z/Kq1fMeQdHpmrPE6hjbIzOPbboS46qcvbBq14ydXQI8ITNPGFCVRi4ivgY8qTx8XWa+q0v+vSmWEwb4S2berYcyLgA2LQ/n/U5GxH0o9jG+a5uPTwXenZlfiIi7UnTSAG4A1szMW7vU454UnbkHApsxu/QnwBMz85vd/i2aDN7brSLieIoZWDPulZknz5P/JGaDlrcCW2XmeZ3ytznfe02SJElSW9PWX1toHLI811jkAhjrup39b7VlO2w7PErGJdUkB/pI0hITEQcCh1WStsnMs7qcsyHFkpFrDrFqwzBWD3XjJiK+CDyG2WVBe3UNxRKO78nMf3bLrP6Ue+E+iOKBflXgQuCUzOxlT3XJe1uSJEmSxtS09dcWEocszzMWuYQY69I4sR22HZamhVt3SdLSc3HteAOg24PdOkzeA526yMynRsQdKEZ3PwC4J7AlcCeKjs5qFB2YKyhmKvwOOA44OjP/1Uilp0A5W+ln5Uvqm/e2JEmSJI2nKeyvLSQOCcYilxRjXRontsO2w9K0cKCPJC09q9eOr2+kFhoLmXk9cHT5krREeG9LkiRJ0niasv6acUhJY8d2WNI0WKHpCkiSBm772vHELDMpSZIkSZIkaWIYh5SkZtkOS1PKgT6StIRERAD7VpLOzsx/NFUfSZIkSZIkSUuPcUhJapbtsDTd3LpLkpaWlwH3qBx/s8fz/g0cMfjqDJ2j0yVJkiRJkqTRW2gcEoxFStIg2A5LUywys+k6SJI6iIhHAHsBH8jM8+fJtwLwCuDdwIpl8r+BrTLz0qFXVJIkSZIkSdLEMg4pSc2yHZbUDwf6SNIYi4jHU4zCTuAE4OfAn4DLgBuA9YD7AE8FtqmceivwpMz89ijrK0mSJEmSJGnyGIeUpGbZDkvqh1t3SdJkCGDX8tXNFcCzfaiTJEmSJEmS1CfjkJLULNthSV2t0HQFJEnz+jPwZeDvPeS9DHgPsENmfmuYlZIkSZIkSZK0pBiHlKRm2Q5L6plbd0nShIiITYHtgQ2B9YG1gGsoHuhOBk5PG3VJkiRJkiRJi2AcUpKaZTssqRsH+kiSJEmSJEmSJEmSJEkTwK27JEmSJEmSJEmSJEmSpAngQB9JkiRJkiRJkiRJkiRpAqzUdAUkSZLGWUSsAzy4knQ+cFND1RmGVYDNK8c/z8yrmqqMJEmSJEmStBjG8yRJS50DfSRJkub3YODbTVdihB4HfKfpSkiSJEmSJEkLZDxPkrSkuXWXJEmSJEmSJEmSJEmSNAEc6CNJkiRJkiRJkiRJkiRNALfukiRJmt/51YOXvPeT3HHz5Q1VZfD+ef65fPg1z60mnd8pryRJkiRJkjQBWuJb/3XIp9n4zls2VZeB+8ffz+E9L392Ncl4niRNGQf6SJIkze+m6sEdN1/Oplvdtam6jMJN3bNIkiRJkiRJY6slvrXxnbdk8623baouo2A8T5KmjFt3SZIkSZIkSZIkSZIkSRPAgT6SJEmSJEmSJEmSJEnSBHCgjyRJkiRJkiRJkiRJkjQBHOgjSZIkSZIkSZIkSZIkTQAH+kiSJEmSJEmSJEmSJEkTwIE+kiRJkiRJkiRJkiRJ0gRwoI8kSZIkSZIkSZIkSZI0ARzoI0mSJEmSJEmSJEmSJE0AB/pIkiRJkiRJkiRJkiRJE8CBPpIkSZIkSZIkSZIkSdIEcKCPbhcRn42ILF9faro+MyJilYi4R0TsHRHPj4jXRMQbI+LlEXFgROwcEas2XU9p0kXEYZU2ICNi+RDLqpZzbJe8B9fy7z6oaw9LRBxbrUcTdZgUEfGAys/qmojYrOk6SZIkSdKkMJ4nTTfjeYNjPK93xvMkSWreSk1XQOMhInYFDiwPbwJe1yX/scCDy8OfZ+bu8+RdDpxTTcvM6HL9xwN7A/cD7kb37+qNEfFt4NDMPK5L3mo5uwM/6yHrjcBVwCXAScAvgS9n5pULKGOPzDy21zoOS7/1iojDmP2OdHIzrT+rc4EzgN8Ax2fm5Qutr6TJEREHAZ+tJG2Zmee2y5uZJ0TE14EnAWsAHwD2GXYdJUmSJGnSGc/rynie8TxJPTKeJ0nSZHFFHxERKwCHAjOd9Y9l5jnznDIKrwaeDexAbwPSVgWeAvw8Ir4QEWsOuD6rAhuV9Xk68HHgwoh4X0SsNuCyJtnKwJrApsC9gCcArwe+BfwzIn4SEU+NiKkaZBgRB9VmpRzUdJ2kMfM64Nby/ZMj4iFNVkaSJEmSxp3xvJ4Yz+uN8bw2jOdJXRnPkySpQQ70EcD+wD3L9zcB722wLp3cSDGT5AfAl4Ejy/fntcl7AHD0EIIDdasDrwJ+GxEbDLmspWBF4CEUv7szIuKRDddH0pjIzDOBr1SS3tVUXSRJkiRpQhjPWxjjef0xniepLeN5kiQ1a6pG4WuuiFgZeFsl6fOZeWFT9am4EfgxcBRwPHBSZt7SLmNEbA+8mWIG0IxdgHcDL+qz3AuB3dqk34FiVssewHOBDSuf7QB8LyJ2zcxb25y7VH0QOKSWtgKwDrAMuCOwM8VyzbvQOrBwa+CoiHgf8F+Z6Z7Hkt4JPLV8v3NEPDEzv9FkhSRJkiRpHBnPm8N4Xu+M50kaJON5kiQ1xIE+2g/YsnJ8aFMVqdkrM2/uJWNmngbsGxFnUSwrO+P5EfGOzLy4j3Jv6bTvLMUMpB9HxHspRqo/vPLZ/YCDgE/3Udaku3Ken9WMLwFExJbAiykCNatWPn81xUyqfgM4mnCZGd1zjd+1+6jD7k3XYdJk5qkRcRzwoDLpvwEDA5IkSZI0l/G8Vsbzemc8TwtmPE91xvMkSWqOW3fpVZX3J2bmyU1VpKrXoEDNm4HqXuQrAI8bTI1mZeaVwJOAc2sfvXTQZS0VmXlOZr6KYibQWbWPXxgRz2qgWpLGz8cr73eOiAd1zClJkiRJ08t4Xp+M5/XPeJ6kHhnPkySpAQ70mWIRsQuze3kDfKGpugxCuczu0bXkrYdU1r+B99eSd4yIjYdR3lKRmSdRjO7/R+2j90XE+g1USdJ4+RZwbeX4BQ3VQ5IkSZLGkvG8RZVlPG8BjOdJ6uJbGM+TJGnk3Lpruh1UeX8b8PWG6jFIV9SO1xpiWfUgBMB2zO30qiIzL46IpwI/qySvSzGD6i39Xi8i1gMeAGwMbADcAFwKnFwuA71gEbEusBOwDcVe5asC1wNXAucBZ2TmhYspYxF12wq4G7AFsDaQwL+Aiyhm8106hDKXAbtS7G+/PsXP+W/ALzLzlkGXp0JEBHBfiu/hnYCbKNqZ4zPzggFc/97ADhT30PXAhcBJmXnOvCcOQWZeHxHfA/Ytkx4fEetk5lWjroskSZIkjamDKu+N5/XPeN4CGM8bDON508N4nvE8SZKGzYE+UyoiVgT2qST9vs+9r8fVFrXji4ZY1vlt0jYYYnlLRmYeGxE/A/aoJD8nIg7OzOx2ftlR2hd4ObAzHVYni4gLgQ8DH8rM63utX0TsQbGf8EOBFbvkvRD4AfCRzPxjJX05rUtPV302Ij47z2W3rO+XHhFrAHsDTwR2BzbqUq8/AP8LfKmcHbdgEbEt8FaKpbNXa5Pl8oj4BPD2Xn/OEVH9Pf98kHtg93LtLr+ffnwuMw9qc/1jgQfPHM+3z3hEHARUvw/PzMzDImIFiu/4i4EtO5z7C+A1mXliP5Uur/1c4HXMbTcBsrz22zLzJ+U551bynpeZy/spsw/fYTYwsBrFd36++0WSJEmSpoLxvIEwnrdAxvOM5xnPa8l7EMbzqoznSZI0Ym7dNb0eQDHrYsbPOmWcFOVSsY+qJU/8v2sJ+2Dt+E7Af3Q7KSLuAvwe+CJwP+ZvxzYF3gWcHhHb93DtiIgPAj8FHkGXoECljOfQGmgbhi8CXwKeQpegQOneFMt3Hx0RGy600Ih4PHASRUetXVAAitlArwNOjYihLK89bSJiI4rv4fvpEBQoPRD4RUTs38e116ZoGz9O+6AAQFAsy310RPQ9M2+R6u323iMuX5IkSZLGlfE8Nc14Xn+M500R43ktjOdJkjRkrugzvfaqHf+ikVoMSPmg+2VgWSX5t5l53BCL3bxN2mVDLG+p+SnFEtPVjv2uwG87nRAR9wW+z9yZVpdTdF4vo1iOdxuKpUtnLAd+GRG7Z+bJ89Tp9RRLDlfdApxCsbTvtcAdKIJqd6MIZoxKPQByNXA6cAnwb4pO+2bAjmUdZzwE+GFEPCAzb+yzzAdQzLxYpTy+CvgNxc95A4rlZ9ep5L8L8POI2K2JZWKXkDsA36OY3QZwI/A7iiV4V6RYUvzulfwrA4dFxKmZecp8F46IOwA/rlx7xo3AicDFwBrA9hQBiRWAgyNimLMpW5TLgZ8FzASZHh4RKy52JpskSZIkLQHG8xbPeN7iGM/rj/G86WE8z3ieJEkj5UCf6XX/2vHJ/Zw8yGU5F6JcqnhtYFuKmRovoNiPdsblwDOGXI2Ht0n7cz0hM4+lGE0/VpquV2b+OyJOpejIzrhnp/wRsTHwLVqDAicCbwJ+XF8iuJyJ8l7g8WXSOsBXIuI+mfnvNtdfB3hjJelW4O3ABzPzyg512oQiyPYMij21qy5gdubGk8u6zHgN8LV216yc284fKWb1HJWZp3eo0+rA/sD/MDtT6N4US/X+9zxltvMRiqDAv4HXAp/OzJsqZa0CPBt4N7BWmXwn4HMR8eBelm1uUPX306sNgO/S2tYMo8P8trKs6yn2uf9oZl5bzVAGyY5gtvO8MvABiuWp5/NOWoMCtwD/D3hv/b6IiF2Bj1Lcox+iuCd6kpmHAYf1mr+Nk5n9t61FEaiYN+ghSZIkSVPAeN7iGc9bXPnG8zoznjd8xvMKxvMkSZIDfabYfSrvr8zMTh2RsRARL6d46O3FH4GnZuacTvoA67MG8Mpa8qlLZF/0UfozrYGBO8+T99PAJrXj/+w0KyAzzwKeUC7dOzOrZxvgFRQdr7o9aV3K9h2Z+db5Kl/+vj9LsUf3HWqf3QKcCxAR9Zlhl9X37O7Bi3s5JzOvAz4VEUcDxzM7U+0FEfHOzLy6jzLXpZj19IjM/HWbsm4CPhYRJ1HMKlmj/OiBwLMofkdjqfr76UVErAl8hdagwA8pOu6DtgHFz32PzGw7Iy4zfxMRDwVOZTYos0dEbF1+9+eIiLvTOsPtNmC/zPx6hzJ+GRG7AcdQLKs9SqdQBNRm3JcBBQbKZZT7Xf56q0GULUmSJEmLZDxvcfUxnjcYxvN6ZzxvgIznAcbz+mE8T5K0pM23F66WqHImRXV5zvOaqsuAHUfxIHnvzDxjWIWUM0W+RrGsadWHh1XmEvav2nHbh/WI+A9a92v/FfC8Hpf+fCWtHYoXR8SqbfLV9zaeb4bOHJl5fT/5+9VvICEz/04RBJmxNvCYBRT9hnZBgVpZv6aYiVX1sgWUNZbKmU7foHXmzK+BJ2XmzUMq9hWdggIzyt/x/1WSAthjnlNeROvf/f/rFBSolPFv4ACK2UijVP+7dNcBXvuFFAGVfl7fHmD5kiRJktQ343mLYzxvoIzn9X79c/vMbzxvQIznGc/DeJ4kaYlzoM90Wl47HuvZP33YjWJ0+0I6PzNWiojlbV53i4iHRsTbgb8wd0/03wGfWUS506oeGLhD21xz99l+fWbe1ksBZfDgg5WkDYFdejh1o+5Zxt53gZsqxw/o8/x/Aof2mPfDFPuLz7hHRNy7z/LGTkSsAHye1qW9TwceXc62GoYLKWaW9eJ7teN7tcsUEQHsV0m6jWLZ364y82/AkT3WZ1Dqf5eWj7h8SZIkSRo3y2vHxvNmGc8bLeN5w2U8b5GM5xnPkyRpGrh113Sqd3jqnbNx9BmK/ZxnrAKsR7FM7KOAvYEVgQcBD4qIrwNPX8CsjE2Bc/o85wyKTsItfZ6nuYMNO+0B/bDK+38AP++znJ/Vjh8IHFtLqy8N/T8R8fDMvKbPskaq7LiuQbHc6yptslzB7PK02/V5+a/0+r3OzFsi4ivAiyvJuwF/6LPMcfNhYN/K8d+BPTPziiGW+aM+2pP6bMdOAa1tKdrMGb/qc4n3r1Ds3z4q9b9LSyFQJ0mSJEmLYTyvM+N5o2U8b5GM5w2d8byC8TxJkpYwB/pMp9Vrx6NewrFv5T7E7fYi/jXwiYjYATiC2f2hnwSsHRF79TpTZAFuoFhm8/VDnAmw1C2rHc/5LkbEVrTu5X0WsEUxoaFn9Q5zu/15f0Ixg2WmA3J/4MyI+DTwTeCkIX6XelbuJ7838DhgJ4p9yntty9fts7gTF5C/GhjYuVPGSRARB1MsCzvjMor9zYc9a/L0PvLWO9DrtM0F96wd/66PMhaSf7HqbeoabXMtzEeBr/Z5zla43K8kSZKkZhnPGwzjeYu3rHZsPK8L43mjYzxvUfkXy3ieJEkj5ECf6VT/vU/8zJXMPDUi9qDomGxdJj8ceAmty7wu1E3AVcClwEnAL4EvZeYkzJ4aZ/WO6qVt8mxeO96N/mdp1a1XT8jM6yLi+RR7ec/MTNoYeEP5ujIifkWxn/gvgF9n5g2LrEdfIuI5FMuztt37vAedOo2d/LXP/GfWjid21kZEvBB4SyXpGuBRmfmXERTfc7uSmTfXgmQrd8i6Qe24vmd2t3KuiIhrgDX7OW8R6n+XOv27+paZl9C6LHVXfQYiJUmSJGkYjOf1z3jecBjP64PxvNExnjenHON5kiQtYQ70mU71WRad9lGeKOWD66toHaX9moj4UGZ2WkK27rzMXD742qmDu9eO23VW1h9CuWu1S8zMb0bEXhQzBLaufbwMeGT5ArgmIr4DHJKZvx1CHVtExAeAly/yMvWllbtpN+tuPlfVjucEYCZBRDyFYonfGTcBTxjF77k0jJlmy2rH/17ANa5mdIGB+t+la0dUriRJkiSNK+N5nRnPGy3jeT0ynjc6xvM6Mp4nSdIS1e9DopaG+sP+IJdQbNpRtP77NgV2aKgumkdErM3cPab/2CZru32qF118pw8y8xiKej0R+BLwzw5Z1wT2B34TEZ+JiKEF2CJiH+YGBU4D3gTsSbFf8zJgtcyM6os+Z3rU9BpQG9b5IxcRDwMOZ/bv423A0zPzx83VaiBurB0v5L4axr3YSf3vUr9BKkmSJElaaoznqXHG83pnPG90jOfNy3ieJElLlCv6TKfza8ebtM01gTLzloj4G3CvSvLWwJ8aqpI6eyhzBxse3ybfZbXjT2Tmfw6nSoXMvIViH+9vAkTE1sAuwK4US0jfpXbKMyk65k8cUpXeWjt+E/A/Pc5sW3sR5fa7NHA9/0QthR0RO1P8zqsd4Jdk5lcaqtIg1X8Xfe3vHhEr0P/3YTHuVDuu/92SJEmSpGljPE/jwHhe74znjYDxvM6M50mStLS5os90OpfWkfmbNVSPYbm5drxqI7VQNy+rHV9AsV96XX0Gzl2HU53OMvOszDw8M5+fmVtRBJ6+WMv2hHL2yEBFxDa0zpQ6LjPf0UtQoJyVtGwRxff7s96mdtzXvslNiohtKWYQVpeyPTgzP9pQlQatPhPsHn2efzcGuK92DzatHZ8zwrIlSZIkaRydi/E8Nc94Xg+M542G8byujOdJkrSEOdBnCmXmDcBfKkl3jojVm6rPENQDHZ2WalVDImIP4MG15E926OyeRute0btERNs9uUclM0/OzP0p9v6uekKnUxZRXL2z/b0+zt2FeZY17sH9+8x/v9rxqPbAXpSI2Aw4GtigkvzRzKzPvJpkv6F1r/AHRcSKfZy/x4Dr0019GfCTR1y+JEmSJI0V43lqmvG8vhjPGzLjeT0xnidJ0hLmQJ/pVX1gX4Elsu91RGzP3CUiz2yiLmovIjZh7uyZK4CPtMufmbcCP6kkrQo8fTi169una8dbdshX30+5n1lpy2rHV7XL1MFBfeRtZ5+I6GmLxzLfU2rJ7ZZuHisRsR7wI+DOleQvAy9ppkbDkZlX09rubwI8updzIyKA5w6jXvPYsXb8mxGXL0mSJEnjyHieGmE8DzCeNzaM53VnPE+SpKXPgT7T6+e14/s2UovBO7h2/IfMvKCJimiuiNgJOA64Y+2jV2bmFfOc+uHa8VvKAEPTbqkd1wMAM66sHfdT9/pezHfr5aSI+A9gvz7KaeeOwIt6zPsSYKPK8amZ+YdFlj9U5czH7wN3ryQfAzwjM29rf9ZE+3jt+P0RsUYP570QuOcQ6tNWRKxMsZz2jFMz8/JRlS9JkiRJY8x4nkbOeN7tjOeNAeN5xvMkSVLBgT7T66ja8aiXcewoIp4VEVv3eU5ExNuBJ9c+ajurZNxFxLkRkZXXQU3XaTEiYnlEvBf4NVD/3X44Mz833/mZeSxFh23GRsBR5RKt/dRjrYjYv8NnB0REfXnRbp5ROz6jQ756+iP6KOOPteMDI2Lj+U6IiLsAX2UwezD/T0TUl/Ctl3d/4O215A8OoOyhKTufX6d1OePfAk/MzJuaqdXQfQk4q3K8NfD9iFi/0wkRcQBwyJDrVbczUA1YfH/E5UuSJEnSuDKeN8aM57UyntfCeN4AGM8DjOdJkqRST0s4aunJzIsj4kRm9+DdIyJWysz6jIYmPBb4v4j4HsWSm0d3mh1SPtzvBfw38IDax8cBhw2xntNuWUQsr6WtAKwNrANsDPwHRcfrAbQfWPgeit9dLw6kWO5zJhiwE3BKRLwL+ExmXtbupHL/7z2AxwH7UCwrfGSbrPsAh0fEz4GvAd/PzHM7XHND4LXAKyvJtwFfaJc/M8+LiLOBu5RJu0TEEcDhwDnMnTl0wcy9mJkXRcTxwG7lZ+sBP4uIZ2bmr2v1mlkG+Z3AhsANFLOU1mxXrx78C1gXODoiXkvxc7690xwRqwDPovg9VjtyxwOfWWCZo/JWirZjxj8oZrpsEBEbtD+lrWs6fffGTWbeUAYZj2P2fnww8JeI+DjwY+BiYHWK5d+fDjy8zHc8xVLWm46gqg+rHX9rBGVKkiRJ0tgznqcBMJ5nPM94nvG8YTCeJ0nSiDnQZ7p9ntnAwLoUnadjOmcfqZWAx5cvIuLvFHtzXwlcD6xFsXf3DsAd2pz/W+BxmZnDr+rUeln5WogzgZdk5o96PaEMZu1NMXttZt/2dYF3A++KiDOAsyn2vF6VYi/srYDlQFQuNd+SwgHsXr4+EhGXA6cBlwPXUnSY7gLcA1ixdu47M/P0ea79AVqXLN6/fLWzJXBu5fi1FMtzz7TZdwN+FRF/AU4FbqJYlve+tAYBXgK8kYUHBl5K0cFfG/gY8P/KgOIVwPplectq51zEZCyVe6fa8ca07nndq8+x+L3TRyYzfxkRz6Co98x3eH3gDeWrnYuBfYETqpcaWiVbZ3L+pR4AkyRJkqQpZzxPi2E8r5XxvILxvDFmPE+SJLXjQJ/p9iXgfcx2rPdhfAIDdXcuX93cCnwIeFNmXjvcKg3VarXj+r7Ok+hWis7tp4CvLmS2WWb+MSLuRTFzprpcblDsy3z3tie26udnuT7woC55bgHenplv65LvUGB74Pl9lA9AZp4QEc8FPkHr8r3blq+6Wyn2Sf9URLyx3/IqjgeeChzBbLBlz3nynwPsmZnnLKJMDVlmHhERl1Hs8b28S/Zjgf3LwFw1CPvvYdQtIralCLzN+OwwypEkSZKkCWY8b3wZz2vDeJ7xPC2e8TxJklTXbulNTYly+dzqXsr7RsRCZwoM0usoRqIfC1zT4znnUcwEuXtmvnKSgwLlfsx3rCSdCXyvoer061bgOooZAydTLNH5/4AnABtl5kMz84uLWVI6My/JzD0pOuzfopiZ0805FAGJR1IsP9zOyyhmvBxFb8GDqynunx17CAqQhRdQzLr7IPAr4BKK5Xi7yszDgAdS3Bed3ECxT/V9M/NDvVy3h3K/DtynvG59SeIZVwDvAnbIzDMHUa6Gq5x9d3eKpZq/R9GG3kDx3T+V4rv9UOAhmXlxedqyyiWuGlLVnlt5fy3wySGVI0mSJEkTyXjeeDKeNz/jecbztHjG8yRJUlW4Eup0i4htgD8zO+jrPzPzEw1WqUVErEAxw2Erir2c16aYiXAtRcfsAuCkzPxnY5UcsIh4Dq0Pw0/PzLZ7RQsiYiWKzv7WFDN21qIITlxFsfTvGZn5jz6vGeX1tqGYebYOxcybayiW/T0NOLW6v/UoRcSdgV0plqtdmSLAcBHwy8wcysyMstx1y3I3pdhb/DLgb8AvMvPmYZWr5kXEVsBZlaSvZeY+Ay5jVeBCivsY4MOZ+dJBlrFQEbE9RcAEgHd86Rg23equDdZosC782195434PrybtkJmnNVUfSZIkSfMznjd+jOf1x3ie8TwNn/G81nje/37jp2y+dbvFtCbT+Wf9hVc+8SHVJON5kjRl3LprymXmmRFxBPD0MunlEfHJcdkLu9wX+IzyNS2qT2d/Bo5sqiKToJxN9OvyNahrJsXMq7GczZKZfwf+3kC5/2JyZqNpsOpLXv9+CGUcyGxQ4HqKWZ2SJEmSpBrjeWPJeF4fjOeNtFzjedPLeJ4kSUuYW3cJ4M3AzEyG7SiWZVVz9qi8f2sZHJGkJtX3ov/VIC9ezuR7bSXpw5l54SDLkCRJkqQlxnjeeDGeJ2ncGM+TJGkJc6CPyMxzgUMqSW8pl9jViEXE3YGNy8PTgK80WB1JIiJeCNy3knQu8IsBF3MgcJfy/aXA/xvw9SVJkiRpSTGeNz6M50kaN8bzJEla+uz8acbbmF06dEeKhzSNXnX2z8HO/pE0aBFxaEQ8JSJW7JJvhYh4OfCh2kcfGmTbFBFrUPwNmvGazLxyUNeXJEmSpCXMeN54MJ4naaiM50mSpLqVmq6AxkNmXhsR+wMPL5NWbrI+0yozDwUObboekpa07YEXAv+IiK8Dvwb+AlwJrEoxC3EX4GnAXWvnnsDcQMFibQV8snx/TWZ+bsDXlyRJkqQlyXjeeDCeJ2kEjOdJkqQWDvTR7TLzl8Avm66HJGkkNgZeVL568Udgn8y8dZCVyMxTgFMGeU1JkiRJmhbG8yRpqhjPkyRJgFt3SZI0bS7rM/+NFDMTd83Mi4ZQH0mSJEmSJEmdGc+TJEktXNFHkqQpkplPjogdgYcB96NYznczYC2K54IrgSsoZuX8HPhaZl7cTG0lSZIkSZKk6WY8T5Ik1TnQR5KkKePyupIkSZIkSdLkMJ4nSZKq3LpLkiRJkiRJkiRJkiRJmgAO9JEkSZIkSZIkSZIkSZImgFt3SZIk9WGDNVZmk7VWbboaA3PjGis3XQVJkiRJkiRpaDZYfRU2WXPpxPOuX32VpqsgSWqYK/pIkiRJkiRJkiRJkiRJE8CBPpIkSZIkSZIkSZIkSdIEcKCPJEmSJEmSJEmSJEmSNAEc6CNJkiRJkiRJkiRJkiRNAAf6SJIkSZIkSZIkSZIkSRPAgT6SJEmSJEmSJEmSJEnSBHCgjyRJkiRJkiRJkiRJkjQBHOgjSZIkSZIkSZIkSZIkTQAH+kiSJEmSJEmSJEmSJEkTwIE+kiRJkiRJkiRJkiRJ0gRwoI8kSZIkSZIkSZIkSZI0ARzoI0mSJEmSJEmSJEmSJE0AB/rodhHx2YjI8vWlpuszIyJWiYh7RMTeEfH8iHhNRLwxIl4eEQdGxM4RsWrT9ZQmXUQcVGkDMiIOGmJZx1bL6pJ391q9Dh7UtYclIg6u1Xn3JuoxCSJi7Yi4pPKzenzTdZIkSZKkSWE8T5puxvMGx3he74znSZLUPAf6CICI2BU4sDy8CXhdl/zVB+9ju+RdXntA7vqgHhGPj4hPRcSfgGuBU4DvAh8D3gO8HfgAcBjwG+CqiPhyRDyoy3XvGRE3VupyW0Q8tFt9ulzz8Nq/75cRsUItT8+dmlHqs7NV7zS2e90SEddGxD8j4k8R8YOIOCQinhERW47onyWpYW3a/YM65c3Mq4G3VZIOiYjVh15JSZIkSZpwxvMWznie8TxJrYznSZI0WRzoI8pO7KFAlEkfy8xzGqwSwKuBZwM7ACv1kH9V4CnAzyPiCxGxZrtMmflH4OBKUgCfjYh1FlLJcqT60ypJ1wIHZuZtC7neErAisDqwEcXvbi/gZcDngLMj4pSIePVCf96Tqk0n6bCm6ySNmY8DZ5fvtwD+u8G6SJIkSdLYM55nPG+AjOe1YTxP6sp4niRJDXKgjwD2B+5Zvr8JeG+DdenkRuAM4AfAl4Ejy/fntcl7AHB0p+AAxQyiX1eONwc+2G+FImID4P9qya/JzLP6vdYUuQfF9+vvEfGK+kwpSdMpM28B3l1JemVEbNRUfSRJkiRpAhjPM543KsbzJM1hPE+SpGb5UD7lImJlWpdY/HxmXthUfSpuBH4MvBK4L7BmZt49Mx+Vmftl5gHl++UUM02+Ujt/F1ofMm+XmbcCzwCuqyQfGBGP67OOH6OY6TLjmMz8WJ/XmGQnAlu2ee0IPAh4PMVsqx8A19TOXRv4X+BHEbFsJLWVNO4OAy4q368BvLG5qkiSJEnS+DKedzvjef0znidpkA7DeJ4kSY1woI/2o+jMzTi0qYrU7JWZD8/MD2Tmb8vR4W1l5mmZuS/wztpHz4+ITTqccybw2lry/5WzerqKiP2AJ1eSrgSe1cu5S8gNmXlum9efMvMXmfntzHxrZj4K2Ax4FXBx7RoPo5ittcbIa69GZebumRkzr0m5dh91OLhah8w8tol6TJLMvAn4VCXpOb22yZIkSZI0ZYznzTKe1x/jeVow43mqM54nSVJzHOijV1Xen5iZJzdVkarMvHkBp70ZqO5FvgIw36yeQ4GfVI7vSLGv7LwiYmPmBlBekpkX9FjPqZOZV2Xm/1IsKf2j2sc7U8ymkqRPAreW7+8AvLDBukiSJEnSuDKeN8t43pAYz5PUI+N5kiQ1wIE+UywidmF2L2+ALzRVl0Eol/A9upa89Tz5E3gmcFUl+UkRsX+Xoj4BrFc5/kZmTvTPblQy81Lg0cDPah89PSIe0kCVJI2RMsB6XCXpeRHhs4okSZIklYznGc8bNeN5kuZjPE+SpGas1HQF1KiDKu9vA77eUD0G6Yra8VrzZc7M8yPiZRR7yc74SEQcm5kX1fNHxEHAYypJlwDPX1hVp1Nm3loulXwqsGHlo7cAP+33ehGxGsUe7ncurxfApcBZwK/nWya6x2vvCNydIhi0BsV+8/8GzgfOBP5aBplGKiLuWNZrK2AZsArFktOXAb/PzL8NocyVgV2BLYBNgKuBC4BjM/PqQZenWRFxV4pA7mYUf7svpfg9/2kA196C4h7aBFgRuJDie/37xV57gb4C7FG+3xR4OHNnDkqSJEnStDqo8t543izjeUNkPG8wjOdNF+N5xvMkSRomB/pMqYhYEdinkvT7zKzvtzyJtqgdz+nc12Xm5yLiCcwuC7wu8GngkdV8EbE5cEjt9OeVs1rUh8y8JCI+Ary1kvygiNg2M//SyzUi4n7AGyj2Bb9Dh2xXR8QXgbe1C/TMc+2tgDcBT6RLcAm4KiKOBT6bmd+uXedc5n4nAQ6MiAPnueYzM/Ow2rVWBB5MsZf8w4Bt5qtURFwAfBT4aGZeNV/ebiJiGfBG4Bm0BnNm3BgR3wT+KzPP7/Gax1L8ewAY5N7bvV57nt9PP87LzOVtrn0wRbBrxh6d9vWOiOW0LlP+ucw8qPxsb4rv+f07nHs28ObMPKLfikfEHsC7gPt2+PyvwCGZ+bHy+DCg+r3dMjPP7bfcHnyH1uW/98fAgCRJkiQZz6swnjd6xvOM5xnPa8m7HON5VcbzJEkaMZfPm14PoOgAz6gvvTpxImJ94FG15F7/Xc+jGFE/Y6+IeF4tz6eBdSrHn6t3BNWXjwL1vdsf2+2kiFg9Io4Efk0xG6tTUABgbeA/gTMj4sm9VCoiDgBOo+gAdQsKQPGdeBzwml6uvwgvo9iD/gV0CQqUNgPeCZwcEfdeaKERsS1wMvAq2gcFAFYF9gNOj4iuv0N1FxErRsSHge/SIShQugvwhYj4SET0FFyJwgcoZty1DQqU7gp8NCK+HRFr9Fr3xSqDeH+tJD3K5X4lSZIkCTCeV2c8b/SM5/XHeN4UMZ5nPE+SpFFyRZ/ptVft+BeN1GJAImJt4MsUS57O+G1mHtf+jFbljJTn07rc8fsj4seZeXZEvIBiuckZ51N01LRAmXlZRJwM7FxJ3hV4b6dzImJD4IdAvaN7PXASxYyvW4HNy+uuXH6+OvCViHhOZn5mnus/EDicYrngqr9SLOt7FcVSqGtT7Be/FaMbMFkv5ybgzxRL7c7Ua0OK5WCre84vB34aEfdZwPK/6wNHUyyjDEUg50SKpWDXBO5R+Ywy7WsR8cTM/F6fZanVB4EXle8TOAU4m2Kp6S0ovt/Vv+EvoghoVWfOdPIh4MW1tKQIAJ1Tvr8LsBPFvfBY4BPMDeQN03EUgQmADYD7AL8dYfmSJEmSNI6M51UYzxs943l9M543XYznGc+TJGlkHOgzveojyk/u5+TM3H1gNVmActnTtYFtgUdQzIrYuJLlcoplSXuWmd+IiC8ATyuT1gQ+GxHPprWzmhRLsfa8fOoglzEdpDGo169oDQzcs1PGcgbAF2kNClxEsQTtkZl5Yy3/MuC/gNdSdKoDODQifp+Zf+xQzHtoDQp8BXhdZp7doU5rAg+lWDZ7kzZZdqNoZzejNfj2deDVHeoAxb7c7fwD+BzwPTrsV17+nB5GsYTrvcrkdYAjmH8mSTtvoJgpmMCHgbdm5hW18h5O0RndqkxaGTgsIrbPzH/2Wd6ozfx+erUC8BkqywjTw3LiC/Bois4wwKcofu4XVDNExKYUnfXqrMd3RcTnM/PaThcuZ2jVgwJfA16dmefV8m4B/C/Fktf70/l7OUe5BPBi2peTa8e7YGBAkiRJkozn1RjPa4TxvPaM542G8byC8TxJkqacA32m130q76+sP3SOm4h4OfCBHrP/EXhqZv55AUW9BNidoiMH8CCKzmt1mctDM/MnC7i25qr/jjaLiBUy87Y2eV9F0Qmf8QfgEZl5ebsLZ+aVwOsj4g8UHfwAVqP4Hj2knj8iNqK143wssF9mZqfKZ+Y1wLeBb0fEnCWHZ+6rNiuwXrOAvZCPBD6YmfPOwih/dkdHxM/Luu1ZfnS/iNi9077SHcwsB/7SzPxIh/KOiYhdKGZs3K1MXh94H/D0PsoauX7bvYj4KK1Bgb9TBIUGbSYo8MKZ/bTrMvPCiHgcxZLXM+352hRLLn+63TkRsRJwaC35Q5nZdjZjGSh4UkQcCrywUq9ROKV2PN+SxH0p7/VOy1Z3slX3LJIkSZI0dMbz2jOeN1rG83pnPG/AjOcBxvN6ZTxPkrSkuUfmFIqIjWndm/q8TnknzHHAk4F7Z+YZC7lA2Zl8FsWMhxnVh+G/Uswo0WD8q3a8Eq3LNQNQdrqre2ZfBezdKShQlZlfo3X50z067HG9Re346/MFBdqUc32veRciMy/qFhSo5b8ReCaty7MesICiv9UpKFAp61KKmXPVgM6+ZVuzJETEWylmGs64jCIwdeGQijyyU1BgRjkD7C215DlBr4onMBv0hKLz/aoe6vJyimWER6n+d+mubXMtzAuBU/t8fXuA5UuSJElS34zndWY8b+SM5/V+feN5DTKeZzxvgOVLkjR2HOgznZbXjsd69k8fdgNeCjxmMRfJzGNovy/urcCBmXndYq6vFvXAAMCcmTTAU2kdsX9IZl7cRznvrx0/todzNurj+mOp/BmdUEl6wAIu8+Yey/o98K1K0soUy8NOvIh4Ea0/h2uAR2bmX4ZY7Nt7zHc0xf7uM+7VKSPFfVT17nbLRdeVAal39VifQbmI1kDT8hGXL0mSJEnjZnnt2HhehfG8kTKeN0TG8wbDeJ7xPEmSljoH+kyneoenXeds3HwG2LLy2pZij9f/pBiZfSvF9/lBwLci4mvtll7tw38B59fSDsnMXy/impqrXRvUbtbNw2vHX+6nkHJP7r9Xkh7YJtuZFN+jGS+IiLu1yTd2ImL1iLhjRGwREcurL1rv77tFm3WH5/GnzPxTH/mPrB3v1se5Yyki9gU+VEm6CXhCZv5uiMWe3etS5WWn/W+VpPkCWrtU3t8MfLOPOn0D6BpEGJQyYHFNJWmDPr+7kiRJkrTUGM/rznjeaBjPGwDjecNjPO92xvMkSVrCVmq6AmrE6rXjoS5ROgiZeTVwdZuPfg18IiJ2AI4AdizTnwSsHRF7ddgfult510bE2cDmleRT+72OulrWJq3d97HawbwJuLHs9PbjCuDO5fs5+/Nm5pUR8QNg7zJpA+CkiDiCYk/w4zLzhj7LHLiIWIFi3/knAzsDd2fuPd3JChT7Pl/VY/4T+6xePf/OfZ4/ViLi4cDnmQ1g3QY8LTN/POSiT+8zfzX4s067DBFxR6C69PLp/SxPnZnXRcTpzLaxo3AdxfcVICi+59cO4LofBb7a5zlb4XK/kiRJkpplPK97ecbzRmNZmzTjefMwnjc6xvNmGc8znidJWtoc6DOd6r/3kY3qHpbMPDUi9qDomGxdJj8ceAnwwcYqpm7WrR3fDFxZTSg7wneqJK1C64yHhVivQ/rLgfszu4/7asCzy9eNEfE7imDUL4BfZOYVi6xHXyLigcBHWFznbB16Dwz8tZ8LZ+YFEXEDxc8NJni55Ii4L8Wsl1UqyS/OzH47lAvR76zM6r7tnf6ub1A7ru+Z3Yu/M9rAQP1v08qDuGhmXgJc0s85Tj6SJEmSNAaM52lcGM/rg/G80TGe15bxPEmSlii37ppO9VHfi1kSd2yUnbRX1ZJf4/KQY+3utePzM7O+1O+6DL6tWqtdYmb+Dbgf8LM2H68K7ErxHfsWcElEHBMRTxrFdywingz8hMV3zPr5WbabdddNNeiwSkSssYBrNKpc4vkoYM1K8lsy82MjqkLfsxZ7sKx2/O8FXGMh34fFqP9tGsTsH0mSJEmaVMbzNC6M5/XIeN7oGM/ryHieJElLlAN9plP94W7iHtzncRSt/75NgR0aqou6u3/t+I9t8qzSJm1oMvPszHwIxf7Hh1Ls9d3OisDDgK8BJ0TEFsOqU3ntz9E6A+IS4APAEymCBRtQLIW6QmbGzKs8b6Ha7a/exDVGJiI2A44G1q8kH5qZb2uoSoNyY+14IffVSO9FWv823VDuXy5JkiRJ08p4nsaF8bweGM8bHeN58zKeJ0nSEuXWXdPp/NrxJo3UYggy85aI+Btwr0ry1sCfGqqSOoiIjZg7m+X4Nlkvrx3/NTO3HU6tZmXmrymW9Z2p6/0p9hbfA7gPxR7DM+4P/DQi7pOZVw6hOq+ldd/u7wJPzcxeZkSs3T1LR233h+7jnJsy87pFlD9SEbE+RVBg80ryl4CXNlOjgaovH1xfZrsXnZbIHriIWJfZJaNh7t8tSZIkSZo2xvPUOON5fTGeNwLG87oynidJ0hLlij7T6VxaR+Vv1lA9hqU+SnzVRmqhbl7I3D16v1PPlJk30dqp2TIiBrK3b68y85LM/E5m/ldm7kzRcfwfWmdV3AV49ZCq8LjK+2uAp/UYFIDW/dD7ddd+MpezZ6qdub72TW5SuSTx94HtKslHA8/IzGEsvTtqF9G6R/Y9FnCNUc6m3LR2fM4Iy5YkSZKkcXQuxvPUPON5vTOeN2TG83piPE+SpCXKgT5TKDNvAP5SSbpzRKzeKf8Eqgc6/tlILdRROaPmhbXkn2XmWR1OOaHyfmVg92HUq1eZeWFmvhF4eu2jJ3Q6ZaFllfdmtXN/XGb2tLdyRKxG62y4ftWXYu7mfrXj3y6i7JEpA01fp7X+vwGeuFSWl83M62ldSvuOEbFdp/x1EbE9sNHAK9ZZvW4nj7BsSZIkSRo7xvPUNON5vTOeN3zG87oznidJ0tLmQJ/pVX1gX4Elsu91+fBan/HQaU9mNSAiVqRYPnXD2kdvnee0H9WOnzvQSi3c14CrKsdbdshX30+5n1lpy2rHV7XL1MH+LG4f5h0iop+ZIvvXjtst3TxWImJm3/M9K8l/Bh7VxyyrSfHj2nE/99HzBlmRHtSXAf/NiMuXJEmSpHFkPE+NMJ4HGM8bG8bzemY8T5KkJcyBPtPr57Xj+zZSi8E7uHb8h8y8oImKaK6I2AD4HsW+2FWHZWb9O1l1OHBl5XifiHjogKvXt8xMoLoMbD0AMOPK2vEmfRRT34v5br2cFBHrAG/qo5xO3tZjefcBHl9Juhk4cgDlD9sHgadWjs8HHpGZ9b3kl4JP0Pp9fVFEdA0KR8Q9gRcMrVbtVf8m3QYcN+LyJUmSJGkcGc/TyBnPu53xvPFhPK8L43mSJC19DvSZXkfVjusdtcZExLMiYus+z4mIeDvw5NpHHxlczUYnIg6LiKy8Dmu6TosREetExMsplhrdq/bxicCL5js/M68E3ltL/lpE7NZnPVaMiCdGxHptPtu932BDROwNrFtJOqNdvnJ57XMrSTtHxLJeyiiXaK3OYrtXRDyiS71Wp5hltbyXMrp4fETM+/uJiA2BL9D6N+UrmfmPAZQ/NBHxJuAllaTLgT0z8/yGqjRUmXk2rcGaVYAfRUR9ts3tyqDADymW2B6JcunlXStJv83MS0dVviRJkiSNMeN5Y8x4XivjecbzhsF4nvE8SZJUcKDPlMrMiyk6ZDP2iIiVmqpPzWOBMyLimxGxX7tO3IyIWDkiHkOxpOgbax8fBxw2vGpOvdUiYnmb1w4RsWtEPDYi3hwR3wcuAD7A3GWYj6boiF3XQ3nvKfPPWAYcGxGHRsS2nU4qvyMPiIh3A3+j2Lt57TZZdwJ+HBGnR8TBEXGvclnidtdcNSKex9wZLp+bp/4/q7xfHfhhROxb/ry2rP0M16yd++Xa8Vcj4oCIaGnDywDZw4BfMRuAWUyHamb20Ycj4pCIWLeeoSzvBFpnJl0BvHoR5Q5dGVypzm66hSJAdX2H73Wn12bN/AsW7GXAxZXjOwG/j4hPRcTeEbF9+do7Ij4F/A7YGLgM+MmI6rgLsEbl+FsjKleSJEmSxprxPA2A8TzjecbzjOcNg/E8SZJGbFw6gmrG54H7le/XpZgFdExz1WmxEsWyoY8HiIi/U8yCuBK4HliL4oF2B+AObc7/LfC4cilWDcf9gHMWeO5VwFuAD2fmbd0yA2TmLRHxFIrZaw8ok1cEXgi8MCIuBE6l6JSuQNH534yiw9rP7IXtyrq9BbguIk4F/lnWeeXymvei6NxX/Rz45DzX/RDwdGbb3ftRzNJp55m0BrXeDzyL2cDK2hQzbt4XEb8r67YeRXCjuozwERQd3gPnqdd83gm8FNicokP5woj4NXAhRcdtR2CL2jk3AweO++wf5gapVqLz72M+5zGYmVYjkZlXRMReFPt7b1gmrwQ8u3y1czNwAHP3bB9W+1qdyXkbxXddkiRJklQwnqfFMJ7XynhewXjeGDOeJ0mS2nGgz3T7EvA+ZjvW+zA+gYG6O5evbm6l6IC9KTOvHW6Vhmq12nF9X+dJ9SeKgNQnM/Oqfk/OzKsiYnfgXRQd1eoMnU3LVzfX0Xnv7brV6W2/+28BT5svyJGZJ5ezhj7K3N/vvDLzyiiWFf4hsFHlo42BvTucdgRFgGG+YEU3lwF7Aj+iCA6sDDxwnvzXAgdk5vcWUaaGLDNPiYhdgU8BD+qS/Txg38w8MSLqgYN/D7pu5ay2J1WSjs7MCwZdjiRJkiRNMON548t4XhvG84znafGM50mSpDq37ppimXkFrUuT7ttmidEmvA54A3AscE2P55wHvBu4e2a+csKDAlAsdTnjFuDDTVWkT7cBN1AsL3s6RYfyQ8BBwF0yc8fMfN9CggIzMvPmzHwVcFfgYxSzc7q5HPhGWY87lktd132WYpbDEUAvezrfQtFRf1RmPqGX71xmfpZiRtKbKWZgXEDRme46kyIzT6KY4fN5ihkZbbNRLHu9T2Y+LTM75etZZp5RlvtBip9jOzdSLEe8XWZ+e7Flavgy88zMfDDwaIq/A3+l6OhfSzHb8nsU98N2mTmzLPyy2mUWfB/P41G0zs76wBDKkCRJkqSJZTxvrBnP68B4nvE8LZ7xPEmSVBWuhDrdImIb4M/MDvr6z8z8RINValGOBt8W2IpiidW1gVUpHl6vpuhYnZSZvXQOJ0JEbE3xYD7j05n5nKbqMwkiYjuKZWfXp+i83ELx/Tif4vt9dr/LPkfEJhTL/i6nWEb3DhTLTF8J/AX4Y2ZePZB/QJ8iYhmwG3AXYE2K5Y3/AfxumLMlImKVstwtgDtSBO7OB37W1M9CoxMR51O0wwCXZeaG8+VfYBnfZXZW258yc8dBl7EQEbE9xVLiAHz8u8eyfJu7dT5hwpx75p95/mN2rybtkJmnNVQdSZIkSV0Yzxs/xvP6ZzzPeJ6Gz3jebDzv8z88nrvcdenE887+6595xl67VZOM50nSlHHrrimXmWdGxBEUew0DvDwiPjkue2GXS6eeUb6mxUMq728G3tFURSZFOUtloN+RcpZQu5lCjcvMKylmaIy63JuAn466XDUvIrZkNigA8PshlHE3ihlAMw4edBmSJEmStBQYzxtLxvP6ZDxvZOUaz5tSxvMkSVra3LpLUCw7elP5fjvgCQ3WRa2Bgc9k5rlNVUSSSi+oHf9qCGW8ntnnkhMz8xtDKEOSJEmSlgrjeePFeJ6kcWM8T5KkJcyBPqLseB5SSXpLucSumrF7+d+bgP9psB6SRETsBLyskpTAFwZcxrbAUyvXf/Ugry9JkiRJS43xvLGze/lf43mSGmc8T5Kkpc/On2a8Dfh7+X5H4MAG6zK1yn1j71gefjIzz2+yPpKWnoh4UUT8V0Ss1UPehwLHAKtUkr+bmX8bcLXew+x2op/LzOMHfH1JkiRJWoqM540B43mShs14niRJqlupexZNg8y8NiL2Bx5eJq3cZH2mVWaeBkTT9ZC0pG0IvIVitud3gOOAPwGXlZ+vD9ybYtn3PWrnXgG8cJCViYi1gT8AJ5VJhw7y+pIkSZK0VBnPGw/G8ySNgPE8SZLUwoE+ul1m/hL4ZdP1kCSNxOrAfuWrF1cAj8/MCwdZicy8GnjrIK8pSZIkSdPCeJ4kTRXjeZIkCXDrLkmSps0VFPtm9+Mo4H6Z+Ysh1EeSJEmSJElSZ8bzJElSC1f0kSRpimTmhyLi68BewAOAuwN3BpYBqwHXUAQPzqJYBvjbmXlKM7WVJEmSJEmSppvxPEmSVOdAH0mSpky5XO+ny5ckSZIkSZKkMWY8T5IkVbl1lyRJkiRJkiRJkiRJkjQBHOgjSZIkSZIkSZIkSZIkTQC37pIkSerDfTdambvfaZWmqzEwp1+1ctNVkCRJkiRJkoZmxxUvYfsV1266GgOz5oqXNF0FSVLDXNFHkiRJkiRJkiRJkiRJmgAO9JEkSZIkSZIkSZIkSZImgAN9JEmSJEmSJEmSJEmSpAngQB9JkiRJkiRJkiRJkiRpAjjQR5IkSZIkSZIkSZIkSZoADvSRJEmSJEmSJEmSJEmSJoADfSRJkiRJkiRJkiRJkqQJ4EAfSZIkSZIkSZIkSZIkaQI40EeSJEmSJEmSJEmSJEmaAA70kSRJkiRJkiRJkiRJkiaAA30kSZIkSZIkSZIkSZKkCeBAH0mSJEmSJEmSJEmSJGkCONBHkiRJkiRJkiRJkiRJmgBTP9AnIj4bEVm+vtR0fQYtIlaMiB0i4oCIeFlEvCEiXhERB0bEfSJi5abrKGk8RMS5lfbw3CGWs3ulnIyIg7vkP7aaf5DXHpZaHY5tog6TIiJeX/lZ/T4ipv7ZRJIkSVJ3xvSM6UkqGNMbHGN6vTOmJ0lSs6b6D29E7AocWB7eBLyuS/5j53vIi4hjag+Chwywru+vXfuoLvnvXJZ/CfAn4AvAIcA7gP8FDgN+B/wrIj4ZEdv1UZdza3VZzOuwBf1A5q/fQR3KuiAiVlzgNSMizulw3YO6nHtwrx2aUeq3Xj3+3m+IiKsi4uyI+FVEfCEiXld21FYbxb9LUvMi4rA+AkwfAM4v398beMFQKydJkiRp4hnTM6bXxzWN6RnTk9QjY3qSJE2OqR3oE8Xo4kOBKJM+lpnnLPKyn64dHxARqyzymkQxQ+dpXcqq5n82cBrwMmC9LpdfA3gOcHJEvHYx9Vyg60dY1qbAIxZ47kOB5YOrypK1KrA2sCVwf+AA4J3Az4BLI+LIiNitwfo1otZByohY3nSdpHGRmdcDB1eS3hER3f52SZIkSZpSxvRuZ0yvN8b0emNMrw1jelJnxvQkSWrW1A70AfYH7lm+vwl47wCu+U3gisrxBsBjBnDdvYGNKseXAt9plzEiXgJ8Cliz9tHFwPeBI4DvAufVPl8FeFdEvG0A9e3H10dc3rNGfJ5mrQk8FfhFRPw4Iu7WdIUkjY3Dmf27tIwus3ElSZIkTTVjeq2M6Q3nPM0ypiepE2N6kiQ1ZKWmK9CEcjZNtfP7+cy8cLHXzcwbI+II4CWV5Gex+I7vM2vHh2fmzfVMEXF34P215L8DLwSOysys5X8w8DGgusTvGyPih5l5wjz12Y2FfXdeDLyqcnwu8JMFXKdfNwMz+5Y/NiLWz8zLez05IpYBT+hwvWn2VODXtbSVKR7olwFbAPcDdqX1OwbFbKrfR8QzM/Mrw62mpHGXmTdHxPuAD5dJL46ID2TmRU3WS5IkSdJ4MaZ3e35jej0wpteRMT1JA2FMT5Kk5kzlQB9gP4plSGccOsBrf5rWoMCeEbFJZl68kItFxMbAI2vJn+mQ/b9o7axeAuyamRe0y5yZP49iT/MTgW1migTe1KbM6nltr9dNRDy6lvSZeqBiSI6imIW1AsUsp/2ZffDsxf7AzF7Ut5XXe9wgKzih/pGZ53bJ8ymAiHgA8ErgSZXPVge+GBErZOaXhlNFjaPMPJbZJdYn5tp91qPxOkygzwH/j2Km4GrAyyn+rkmSJEnSDGN6GNPr43xjeu0Z09OCGNNTB8b0JElqwLRu3VWdgXJiZp48qAtn5h+B31eSVgQOXMQln0HrgKwTM/O0DnnrSwq/s1sHPjP/xdzlFB8SEWv0V835lcGH6rKutwGHDbKMeVwAHFM57nfJ3mr+o8vrqQ+ZeUJmPplif+9rKh+tAHwmInZopmaSxkVm/hs4spL0vIhYq6n6SJIkSRpLxvRKxvR6YkxvkYzpSerGmJ4kSc2YuoE+EbELs/t4A3xhCMV8unZcX6a3Hwd1uTYAEbEOsF4t+bs9lnEUcEvleBXgzj2e26t6R/zozDx/wGXMpzpjaqeI2KmXkyLiHsB9KkmfHWSlpk1mHkmxZPJtleQ7MNgZeJIm1xGV9+tQzL6UJEmSJGN67RnT68CY3mAZ05PUhTE9SZJGbBq37jqo8v42Fr/XdjtHUuyrfYfy+K4RsWtm/rKfi5QBjOo+yNcCnZZDbTdbp6dZKpl5fURcBmxcSV63p0r2ICLWBJ5SS24b3BiibwNXMBs4eSbwsh7Oe3bl/RXldR402KpNl8z8cUS8HXhLJflBEbFHZv6s3+tFxF2AewMbUnxvrwL+AfxqsXsBR8TmwE4UQbK1KGbzXQdcSrEf/Z8y86rFlLHAeq1M0TZsC2xS1u0G4F/A2cBvMvO6IZS7nOJnvSlF+/YP4JRBzqDUXBGxGrAbsAWwEXA1cB5wXGZevchrrww8ELgLxT10OXAhcEI5O3TUjgcupvheQ/E3+/8aqIckSZKk8XNQ5b0xPYzpdWFMb8CM6S2eMb3pYkzPmJ4kScM0VQN9ImJFYJ9K0u8Xus/2fDLzqoj4OvC0SvIzgb6CAsydMfPVchnEdi6nmMFT/Z2uBtzUY1mr1Y6v6PG8XuxLsT/rjEspOtcjk5k3RsSRwIvLpAMi4jWZ2fHnExGr0Po7PLK8zjCrOi3eT7FX7zqVtOcBPQUFymWoX0pxj2w9T76TgXcCX+t17/iIWKG87osoAgLzyYg4nWKm3Qcy85LKdQ6i82yxc+b5Hp2Xmcvb1GsT4MkUy3k/gPaBwBm3RMQPgfdk5i+6/Bu6ioi9gP+mCIjNqXhE/A14R2Ye1uP1dqf1d/3WzDx4sfXs59pdfj/9eGa7f3dEVL9vP8/M3TtdICIOo3U5+C0z89yIWAa8naIdWtbm1FvKdu31mXlhP5Uul899C0Xgs921b4yI7wCvzcxzyoDQOZXPP5eZB/VTZi8y87aI+B7w3DLp/hFxl8w8e9BlSZIkSZocxvTmZUyvxpjeUBnTM6ZnTG8272EY0wOM6UmS1IRp27rrAbTOaul7pkEf6rNbntLPHtkRsTp9zJjJzBuB39SS791jWXeh9aHwauDMXs7tUT24cXhm3jzA6/equtTv+sBju+R/XJmv3flahDK4Ve+QPTIiug4+jIg9KWa4vJN5AgKlnYCvAEeXS2F3u/Yy4Fjgk3QPCEDRQd6eosO8Yw/5F+MvwIeAhzN/QACK4ODewHER8b+9/Fw7iYj/B/wAeDBtAgKlrYDPRsQPyrZLixQR9wVOpghkLuuQbSXgGcBvI6Ln719EbA+cAbxqnmuvShFEPyki9u712gNS/9v86BGXL0mSJGn8GNNrX5YxvfaM6Q2JMb0FMaY3RYzptTCmJ0nSEE3bQJ+9aseLHhU/j58Df6scr0Uxcr9XTwbWrhz/NTOP73JOfU/kF7fNNVd9udvDM/PWHs+dV0TcjSIYUzXqJX4ByMyTKB6yZ3TbZ70azPhjeb4G55ja8TrADvOdEBHPBb5PsdRp1bll+pHA94D6XvEPA44vZzzM5ysUS55WXUMxc++rwBeAbwEnAFd2udag1dvrf1IEML5BUa9vA6cB9Xv3FcAhCykwIl5NEfCY8XeKn/OXKZZjrQf39gK+X86c08LdlSIQs0V5/C+K++WLwHeA+vLVmwDf7CXwHBHbUnxvNq19dAVwdFnG0czOAF2H4r4YdtCr6rjacf1vtyRJkqTpY0yvPWN67RnTGy5jev0xpjc9jOm1MqYnSdIQTdtAn/vXjk/u5+TM3D0zo3zt3iVvMne2SH0WzHzqebvOPMnMIykeGGc8KSJeP985EfEc4CWVpEuAt/ZayR48u3b868w8fYDX71f157hnRNypXaaI2JRilkW78/qSmQdXvjdjs0bwGNTr10B96d17dsocEQ8BPkaxp/aMI4DtM3PLzNw7Mw/IzMdk5p2BPYBTK3l3AD4xz/X3pPV3fjnF8qrrZeZumfmUzHx6Zj4hM3fNzHXLa/4Xxcycuq8BW5avr9c+e2Dls/prtw5VvA34IcU9dafM3Dgz98jMJ5X1enxm7gBsTjEzqrqE9YvKpXr7sQHwP+X7s4BHZOYW5c95v8x8ILAxxYyk6u9xd+DNfZbVhOrvp9fXfhTLqVctas/4Do4A1qPYs3sfYMPMfERm7p+ZjwM2o/huVvdsvwvwyvkuWi51fzjF73bGpcDTgTtm5p5lGXsCd6SYWXQZxd7tfQVzM/OgSvuyvM9zLyzLnVH/2y1JkiRp+hjTqzGmZ0zPmN7t1zem18qYnjE9Y3qSJE2BBS/9OKHuU3l/ZWZeMOTyDgPexmwn5oERsVVm/q3zKbcvu/ugStItwOd7LHNfiuVT9yuP/yciHkPRqf0DcBXF3tr3pHgQfGjl3EuAvTLz0h7Lmle5tOjTa8mfGsS1F+EI4L0US1iuSPHQ+642+Q5i9vd2U3meBigzr4iIS2mdyXPndnkjYk2KmT0zv5MEnpOZHYM1mXlsROxCMZNhlzJ5v4j4WGbWZxdAsaxz1ZMz89gu/4bTgNMi4n3AKrXPrqGYOUREXFM79YLMPHe+a7exYy/nZObFwBsi4mcUM0hm2vn/pggq9GpmJsmfgQe1axcy8wrgZRFxFkVwYMZrI+LwzGwXLBkL1d9PLyJiO4oZltW/m2/KzKMHXTeKTvtpwB4dfu4JHBER1wLfrHz0nIh4R/l5O88Fdq4cXwo8sN3vKTNvAQ6PiN9TzGbdoJ5nyE4BHlK+Xy8its7MswZx4YjYCNiwz9O2GkTZkiRJkhbMmJ4xPWN6Y8KYnjG9JhnTA6Ywpmc8T5KkuaZmRZ+I2JhiucIZ5w27zMy8iNaH8KD70rKUeaqzMY4qH/R7KfOGzHwqsCdwFEWH9v4Usx5+R7FP90kUAYuZgMBNFCO7d8zBLmW7N8UI8hnXUiwP2piyE1OdIdXp93FQ5f13MvPyoVVquv2rdtzpYf35tH6X3jtfQGBG2fHbF7ixkvzqDtm3qLy/vFtAoFZOZuaN3XMuXL9BhMz8MfDxStKDy1lt/bgVOKBboDAzP0zrfbUS8KI+yxpbEbE5RXBp/UryhzPzHUMq8hZgnx5+7t+iaNdn3Jn597ivL/3+4m6Bm3K2Zn0p+FGo/42+6wCv/UKKmYH9vL49wPIlSZIk9cGYnjE9MKY3hozp9V7GuX3mN6Y3IMb0llRMz3ieJEk1UzPQB1heOx72zJ8Z9Y7LgRHR8edefnZgLXkh+1+vRLHXbn1JyrrrKJbyfGNm/nMB5cynvsTvl8tOWtOqv5O7RsSu1Q8j4sG0PlgveIlfdVUPCtyhQ77qUtTXAG/vtYDMPJ9iP+IZj4iIVbuctnZErNZrGWOsvrzwA/o8/1uZ+Yce876xdvyM+dq6SRER61MEBDarJH+R4XaUv56ZZ/SY93u143u1yxQROwLbV5L+mplfaZe3Losl5Aeymk4f6n+jl4+4fEmSJEnjY3nt2JhewZieMb0mGdMbLmN6i2RMz5ieJElL3cQ/sPVho9pxvTMyLN+lWD53xma07hlc9zCK/Xhn/JNiFk9PImLTiPgp8H2KZUtX73LK6hT7d58bEe+PiE6dsr5ExCZAff/ghQQ3huFoWh846zOAqnupX1jm13DU26A5y5NGxLa0Lv971AKCSz+rvF8VuG+bPH+uvF8ZeE9EjM3+651ExEoRsSwiNo+I5dUXc3+e2/V5+SN7zZiZf6J1//R1KPY7n1gRsQZF+3u3SvKPgAPnWUp3EL7fR9568KD+t25GPSD01T7KWEj+xar/je7075IkSZK09BnTa8+YnjG9JhnTWyRjesNjTG9R+RfLmJ4kSSOyUvcsS0a9c3z9KArNzJsj4nDgVZXkZ1I8WLbzrNrx58p9VbuKiM2AX9A6Svo6ij20vwn8iWI/77UoHnL3Bl4ArEvRUXolxZ7je2bmYoMmB9L6/TojM09Y5DUHIjNvi4jPA68vk54SES/LzGsjYm3gyZXsn8/MW0dfy6mxrHbc7r7crXb897LD24/basdbUdwrVV+kuAdmvIRiadxPA9/NzHP6LHMoyiXL96FYyvsedNgDvYN1+yzuxAXkrwYCdqbYl3niRMTKwDdoDSCdCDwpM28ecvGn95G33lav0zYX3LN2/Lu2uTr7bZ/5F+u62vEabXMtzEfpP8ixFS73K0mSJDXFmJ4xPcCY3phZVjs2pteFMb3RMKY3x1KJ6RnPkySpZpoG+tT/rT11tAfk07QGBR4fEevWO94RsS7w+Nq5/Swx+wVaAwJnAY/KzDNr+f4F/Ar4VUQcCnyL4uGd8r9HRMSjFzm6vR7cGJeZPzM+A7yOYt/0tSgCAZ8D9qM1gPTZ0VdtqtQ7qe32L968dvxqOu/J3av16gmZ+buIOAR4eSV5R+CDwAcj4nzghPJ1HPDHIc8AaRERqwMHUywvu8oCL9Opw9jOdZl5YZ/Xr7c1Ezljo1ye+PPAIyrJZwCPzsxrR1CFfoKy9QDFyh3ybVA7ru+X3c3f+8y/WPW/0Z3+XX3LzEtonZXb1QRMBJQkSZKWMmN6s4zpGdMbF8b0emRMb3SM6bW1JGJ6xvMkSZprmrbuqs8qGMhytr0o92X9VSVpVWD/Nln3Lz+bcXxm/qWXMiJiT+DBlaSbKB5g6w/p9bpdBDwauKKS/EiKmUELEhEPBLapJN0MHL7Q6w1DZv6N1tkfM0v9VoMZx3f7+WnhImIDYMNacruOyvpDKH6tdomZ+QrgFRSz5Oo2B/alCBKcBJwfEe8rZ90NVUSsCfwQeA0LDwhAf23+1Qu4fv3nNif4MiE+RBEgnHE+8IjMvHxE5ddnqw3Cstrxv/s8fyHfh8Wo/40eRTBGkiRJ0ngypte+bsb0Csb0RsyYXu+M6Y2cMb25jOlJkrRETdNAn/oDzSC3AelFffZLfXZMu7R+ZszsUzv+Ymb+tZcTM/NS4NBacn2P6348u3b83XLE9bipzqx6UETsDdyvw+cavPu3Sftjm7TFdII76TicPzMPAbagWAL7aDp3RjalmNV3VkS8bNAVrHk38MDKcQLHUMwE2o1i1t9awCqZGTMvYMtFlDmImU0jmx01KBHxFuBFlaTLKQICFzRUpUG5sXbc7301jPtwPvW/0aMOSkiSJEkaH8b0OjCmBxjTa4Ixvd4Z0xsRY3odGdOTJGmJmqaBPufXjjcZcflfBq6pHN87InacOSjf37vy+b/pb8/R+l6tP+mzfj+uHd+vba4uImIt5gYoxm2J3xlfY3YEfFAs6znjGvrf81X9eXjt+F/AaW3yXVY73r/a8V3g6+D5KpaZV2XmxzNzT4pZE/cBXkxxH19Ry74qcEhEvLTHf3dfImIT4PmVpBuAvTLzEZn5ocz8ZWael5nXtNlneu1FFN3PksCdzulnudrGRcQLKJZSnnENxVLpf26mRgNV/130u7f7qGdy3al2XP8bLkmSJGl6GNObnzE9Y3qjZkyvB8b0RseY3ryM6UmStERN00Cfc2kdiT70pTmrMvMa4Cu15Opsn/qMmS/3uW/sstrxP/o4t13++t6vvarvh30h8KMFXmuoyp9v9XdSfUj+avk70xBExNrAQbXkozLz1jbZ/1k7vutQKtVBZt6SmX/IzEMzcz+KPaofBfy2lvV/ImLZEKqwN61t9Xsy8+gez613rPqxekRs2uc529SOx3HWX1sRsQ/wkUrSTcATM/M3DVVp0OpLaN+jz/P7zb9Y9e/eOSMuX5IkSdL4OBdjevMxpmdMb2SM6fXFmN4IGNPrypieJElL1NQM9MnMG4Dq3th3jojVO+UfkvosmAMiYpWIWIW5+3v3O2Pmytpxv8sYr1k7XmiHuB7c+GyHjt646LSU72dHWovp8yrmzkz5RIe8J9SOHzH46vQuM2/NzB9QLLt7UuWjNZk7o+n20xZRZL2j/b0+zn3AIsqF9ksxz6c+a7AeOBlLEfEw4AvM/k28DXhGZh7TXK0G7te14z36PL/f/Iu1XeX9bcCfRly+JEmSpDFhTK8rY3qtjOkNlzG93hnTGzJjej0xpidJ0hI1NQN9StUH1BWAHUZZeGaeAFSXi9wAeAzwWFpn25yemfUHuG4uqh3fq8/z71M77nf2EBFxd1o7BcmYd67b/E4AzszMXzRRn2lQdsDeWEs+NjOP63DKH2hd6neXiBjpvdtOZt5I0ZGs6rR/dn0v5VX7KGpZ7fiqXk6KiBWBp/VRTjtP7TVjRNyD1jb1KuDURZY/dBHxH8A3ad2v+qWZ+eWGqjQsx1MsET3jcRGxUS8nRsTGFH+nRiIiVqV1lt/pzsaUJEmSpp4xvc6M6c0ypjdExvQAY3pjw5hed8b0JEla2qZtoM/Pa8f3baAO9Vk9z6J1ud92eXpxbO34wHJWUVcREcBza8kL6RTXZ/78LDPPXsB1Ru0xFDM5Zl6PbrY6S1dEPJWiA1Zte64DXtjpnMy8Dfho9TLAhyJipaFUsj+31I7rnf8ZV9aON+mjjPo+zHfr8bwX0zlI0avHR8S9e8z7jtrx4eXvbmxFxLbAD2id/fjWzDy0oSoNTWZeSbEf/YxVgUN6PP1DtAZNhu3eQPX+PnaEZUuSJEkaT8b02jCmZ0xvVIzp3c6Y3hgwpmdMT5IkTd9An6Nqx6NethDg88DNleM9aV229Gbg8AVc95u1624BfKTs8HfzNmDnWtrX+ik8IlYGnl5LXkhwY+Qy86zMPL7yOrPJ+kTE8ojI2mt5k3VarIjYJSK+ChxJawfsVuCZmXlGl0u8n9YZQHsAn42I1fqsx50j4pEdPnt5RPS8j305u6a+PHenf0c9vZ+liv9YO351WfZ8dXsk8O4+yuhkReCIbj+XiHgxrbNDbgXGumNd7lV+NK0zLz+WmQc3U6OReA/FPuUznhoR/9spwBYRK0fEB4F9RlK7WfW/zd8fcfmSJEmSxo8xvfaM6RnTGypjesb0xo0xPcCYniRJYsoG+mTmxcCJlaQ9Rj2DIDMvoXU/3hXL14zvZualC7juucDHa8nPBX4QETu1Oyci7hoRX2Hukqs/zcwf91mFxwIbVo7/BXyjz2tosmxcBjCqr60j4j4R8dCIeFZE/F9EnEaxJ/eTa+dfC+yXmV/pVlBmXg3sS+tsm6cBf4iIA+YLDkTEJhHxzIj4DnB2eZ12DgbOj4gvR8S+EbHePNfcDvgurctaXwD8tMMpP6d1T+9XRcTbI2K3iNim9jPcrHbuD4B/V44fCHwzIjZvU6/1I+JdwHcoZnf03ZZUXEsRaLwbcEK5PHO9vPUi4hCK2SFV787M+vLZ4+arwJ0rx8cB72vzne72WrPD9cdOZp4OvKWW/Argj2VQ7H7l9/F+EfFyioDUS8t8XxphVavftatw9o8kSZI09YzptTKmp0UypmdMz5ieMb1hMKYnSdIIjcMymaP2eWYf5NelGGV8zIjr8GngCfN8tlCvpVgecddK2p7AnhFxDsXeuldTzL64G7Btm2ucCzxjAWXXlyo+IjNvaJtTS8UXF3Huj4EXZ+Zfej0hM38aEQdR3CMz+2FvR7Gn9mci4mSKfe2vofiOr0fxPe9pz+LSasBTyhcRcR5wJkWQ60aKvbW3A7aqnXcr8OzMrC/7O1P3cyPiG8CTyqRVKIJx9YAcwHnA8sq5/4qId9A6m+cxwKMi4vcUgY6VgM2B/2A2yHgN8DyKmYELcRnF8srvBrYBjil/HqdQBAw2Be4PrFw77+fAWxdY5ijdqXb8IOBvC7jOM4HDFl2b0Xk3RTDkBZW0uwMfmOecn1J8V/erpGWHvIsSERtS/C5mfNm/JZIkSZJKxvSM6WkwjOnNMqY3y5jeeDOmJ0mSWkzjQJ8vAe8D7lAe78PogwI/pOi81B9KLwR+tNCLZub1EfFoiuU1D6h9vCXd9/Y9DnhGZl7YT7lRLJe5Zy15Ipb4HVP1mSy3UHTwJt01FDNmPpqZxy/kApl5RET8hSIgsXXlo1WA+/Z4mfr+2PPZonx1u97TM/PoLvmeR3HP79JH+QBk5nsiYmuKGX0zVqT4N7f7d18OPBH4e79ltSl3Q+DVZVK3n8ePgCdm5k3z5FGDMjOBF0bEWRTBm26zlz4CvIq5gbB/t8k7CE+idUbsZ4ZUjiRJkqTJY0yvM2N648GYXgfG9IzpaXGM6UmSpLqp2roLIDOvAD5XSdp31Ms0ZuattB8t/rnys8Vc+6rMfBrwEIpldrs9nN9GMbJ7X2D3zDxvAcUeROtD3B8y8+QFXEeFB9SOD8/My9rmHD83U3QWzqNYUvtI4A0U38cNM3P/hQYEZmTm7yhm9TwN+BWtS/+2cxtwEsVexvfOzFd0yPcwik7SCUAvsw3+DrwL2Dozu+43XLY9DwQeTzEL8RTgCoqfWVeZ+TyKf/N8+81fStGJ2z4zj+vluj2U+xqKZbx/OU+2vwHPysy9MvO6QZSr4crM/wXuSjFr9HjgYoq/F/8Afg+8F9ghM19SBnmW1S5x1ZCq9pzK+19n5okdc0qSJEmaKsb05jCmN36M6c3DmJ4xPS2eMT1JkjQjioHA0yUitgH+zOxAp//MzE80WKWhiYhVgXtSLE26LsVI7+uAK4GzKDrwS2FmyZIREV9gdvbWzcC2mXlOg1UaaxGxFsVys5tRLO27GsVMo8spOtBnlPuB93PNlYHtKWY83AlYq/zo3xQz904BzsoGGtCICOAeFEv6bkixxPA/KAIxv+q01PCAyt4SuA/Fz+QOZbmnZOZJwypT4yEing18qpL04sw8dMBl3Af4XSXpSZn5jUGWsVARsT3FUvkA/OHEX3L37bZrsEaDdfoZZ3Dv+1V3CGCHzDytqfpIkiRJnRjTM6Y3zozp9ceYnjE9Dd80x/Tq8byTj/kG299163nOmCyn/fUsdnr4E6tJxvMkacpM49ZdZOaZEXEE8PQy6eUR8ckmHvCHLTNvBH5TvjQZ9qi8P8yAwPwy898MeKnuzLwZOLl8jZWynTqlfI267HMAv4/T6UG1498PoYxXVd7/kYXvRS9JkiRpiTKmpzFnTK8PxvRGWrYxvellTE+SpCVq6rbuqvj/7N13mGRFvf/x95clLEFYooIoi4EgiCgqIKIgiv5MGMCACbNX71WvIsYrYLqKOWC6BuSKGXPCBKhcREVBJCssIKIisCBI5vv7o864p892OjPd0zOz79fz9LNT1eecqu3pmen6PKeq3siKJXC3Bx4/wb5IAETEdqzY5/0m4C0T7I4kEREbAwfUqm5gxIFZtV/9k2pVr12IQb0kSZKkkTDT05xjpidprjHTkyRpYVtlb/TJzGXA+2pVh0bEKvt6aM54SO3rT2bmxRPriSQVH6Ys6zzlS5k5zJ73bRwKLKq+/mFmfm/E15ckSZK0QJjpaY4y05M015jpSZK0gK3qg+A3AVODrp2AZ02wLxKsWOL3RuBtk+yIpIUpIr4XEbsNcdztIuJoOmfl3AZ8YMT92QV4WlW8Cfj3UV5fkiRJ0oJkpqe5xkxP0liZ6UmSpLrVJ92BScrM6yLiQOBhVdUak+yPlJkHDD5KkmbkEcAjIuJM4OvAr4CLgGuB2wF3BvYCngls1Dj3nZk56r2870gJ6QHOzMzzRnx9SZIkSQuMmZ7mGjM9SbPATE+SJP3LKn2jD0BmngScNOl+SJI0y3aoHsP6HPBfo+5EZn4T+OaorytJkiRpYTPTkyStosz0JEnSKr91lyRJq5orWh7/N+Blmfm0zLx5HB2SJEmSJEmS1JeZniRJ+pdVfkUfSZJWMXcA9gQeDNwXuGtVty6QwFWUIOBXwPHAsZl5/WS6KkmSJEmSJAkzPUmSVOONPpIkrUIy8xbKYP/4SfdFkiRJkiRJ0mBmepIkqc6tuyRJkiRJkiRJkiRJkqR5wBt9JEmSJEmSJEmSJEmSpHnArbskSZJa+NtNq7PkxoXzEepvNy2c/4skSZIkSZLUdMU6W/LX22096W6MzBXr3DDpLkiSJswVfSRJkiRJkiRJkiRJkqR5wBt9JEmSJEmSJEmSJEmSpHnAG30kSZIkSZIkSZIkSZKkecAbfSRJkiRJkiRJkiRJkqR5wBt9JEmSJEmSJEmSJEmSpHnAG30kSZIkSZIkSZIkSZKkecAbfSRJkiRJkiRJkiRJkqR5wBt9JEmSJEmSJEmSJEmSpHnAG30kSZIkSZIkSZIkSZKkecAbfSRJkiRJkiRJkiRJkqR5wBt9JEmSJEmSJEmSJEmSpHnAG30kSZIkSZIkSZIkSZKkecAbfWYgIj4dEVk9vjDp/oxbRGwcEftFxIsi4nUR8W9V+U4jbOP2EbF3RDwvIl4VEa+t2nt8RGw5qnYkrSwiDqr9TsuIOGiMbZ1Qb2vAsXs1+nXYqK49LhFxWKPPe02iH/NBRKwfEX+rvVaPm3SfJEmSJC1c5nnmedJCYp43OuZ5wzPPkyRp8lafdAfmq4jYA3hWVbwJeO2A408AHlwVT8zMvfocuxS4cEAXErgRuB64HLgMOA/4HXAScFpmjuQDcUQ8CngdsBvdbw7LiDgZeH9mfqnltdcG/h/wSGBv4C4Djv8D8DHgfzLz6pZtdXs9TsrMB7a5TpdrXZeZ67U4/vDMPKxtm+PQpl/VIPHTAy55K+V9eS3wN+BPwLnAb4CfZeag97WkBaDL37FnZ+ZR3Y7NzGsi4k3AB6uq90XEDzLzn+PtpSRJkqRVjXleZ1/M88zzKuZ5kszzJEmaZ1zRZxoiYjXgSCCqqo9MYMATwGJgQ2AbSujwfMoHq98Af4qI90RE34F23wYibhcR3wC+DTyA3u+XqJ7/YkQcGxEbDnn9x1NCjWOB5zIgFKjcDXgncGZEPHyYdgbYIyIeO4LrqFgErANsBuwIPAJ4GfAZ4IKI+F1EHBwRG0ywj7MuIpY2ZoMcNek+SXPMR4ELqq+3Al4zwb5IkiRJWoDM87r2xTxPYJ7XlXmeNJB5niRJE+SNPtNzIHCv6uubKAPVuWYL4D+B8yPiIxGxpM3JEbEe8DOgOWj+J/AT4PPAdyizPOqeAHwzIhYP0cwdgXW71F8PnAJ8s2rnx8A1Xc79TkQcMEQ7g7wtIhaN4Doa7J6Un5eLI+I/q5BN0iouM28B3lGrekVEbDap/kiSJElakMzzzPM0PeZ5klZinidJ0mS5dVdLEbEG8KZa1dGZeeksNL11l7q1gSXVY3vg/sCDgM1rx6wGvAh4eETsl5lnDNneZ1gRfgDcAhwOvKe+/GI1sDuAMvNo06r6gcDHgWcO2RbAFcAxwJeAX2XmTfUnq9f9GZRB5UZV9SLgmIg4MzPPatFW0w5VXwctY6tOpwBP6VJ/O8p7ciNgZ2BXYE+gvhzy+sB7gEdGxAGZuXycHZU0LxwFHEoJttcF3gC8dJIdkiRJkrQwmOeZ5+lfzPMkjdJRmOdJkjQR3ujT3lPoHKQfORuNZuayAYd8DyAiVqfMwjkE2KX2/NbATyLiQZl5dr8LVUvoPqHePPCUzDy2S79uoyzxezrwf5SlhwGeEREfycyTB/R7GfBm4LPNMKDRzs3ApyLiRODnwB2qp9agDDAfMaCdQQ6PiM9n5g0zvM6q5IYh3pffAKiW9n0ucDCdwdVDgR9ExN6Zed1Yeqk5KTP3mo/XbtGHw4DDJtyNeSUzb4qITwBvrKqeFxFvysy/T7JfkiRJkhYE87zOfpnnrbrM8zRt5nlqMs+TJGlyXGazvVfWvj4lM0+bVEe6ycxbMvNLwG6U2TJZe3oT4KsRsc6Ay7y2Uf5Ut1Cg0e45lKWF697R7diarwHbZOan+oUCjXb+SNm7vO5hEXH7Yc6vuQ74Ua18J+A/Wl5DQ8rMqzPzPZRZZcc1nr4f8JHZ75WkOeh/gFurr9cGXjzBvkiSJElaOMzzurdrnqeezPMkDck8T5KkCfBGnxYiYnc6l7/97KT6MkgVEBxCmV1Ttx3wml7nVXt/P7BRPeye5ccAf66V94yIu/bp46XVzJ5WMvPbwMW1qtWAB7e9DvBqOoOT17bd+1ztZOblwKOA4xtPPSMiHjKBLkmaQzLzT8BPa1UvqJaUlyRJkqRpMc8byDxPfZnnSerHPE+SpMlw6652Dqp9fRvQd1bMHHE4ZaBfH3S9PCLelZnXdDl+D8pe2VMuysxzh2koM2+JiB9T9t6esj+DZwJNx2+BO9fKW7S9QGb+JiK+yIp9qTekhCY9gxPNXGbeGhFPAX7Pin3goezl+5O214uIxcDulPfDpkAAlwN/AH6RmbdMt6/VtXcC7kHZo3xd4EbgH8AlwPnAeZmZPS8yJtWst3sAd6Xsob4msBz4O3BqNVtu1G2uQfkdsRVlyeZrgD8BJ/T4faIRiYhtKMH0lpS/3ZdTvs9njODaW1F+hjan/P6/lPK+PnWm156mLwF7V1/fEXgYK88clCRJkqRhHVT72jyvwTxPwzDPGw3zvFWLeZ55niRJ4+SNPkOKiEXAAbWqUzPzskn1Z1iZeVtEHE5nMHA74KnAx7qcsmWj/PuWTTY/pD6K8QQDzcHemtO8zhuAJ1L2Bgd4aUR8MDMvnXbPNFBm/i0iPkQJrqY8KCK2HTaIiohdgddT9gVfu8dh10TE54E3ZeafexzT7dp3Bf6Lsrf97QYcfnVEnAB8OjO/0bjOMsoguulZEfGsPtd8dmYe1bjWIspMt/0p/+e79+tURPwJ+DDw4cy8esD/oa9qZtwbgGfSGeZMuTEivgYckpmXDHnNE6jN3MvMmEkfp3PtPt+fNi7KzKVdrn0YJeyasndmntCjH0uBC2tVn8nMg6rnHk15n+/W49wLgDdm5jFtOx4RewNvB+7f4/nzgPdl5keq8lFA/X27dWYua9vuEL5J5/LfB2IwIEmSJGkazPOGZp6ngczzzPPM8zqOXYp5Xp15niRJs8zl84b3AMoMkSnNpUrnrMz8KXBao/qxPQ7fqFFe3rK55vH3bHn+sO7WKE8rpKlmSXy8VrU2nYNVjc+HgeZSz73el/8SEetExOeAXwCPoXcoALA+8ELg/IjYf5hORcTTgDMpA6BBoQDABsB+wKuGuf4MvAz4MfBvDAgFKlsCbwNOi4j7TLfRiNiW8vvjlXQPBQDWosykOysiBn4PNVhELIqIDwLfokcoULkL8NmI+FBEDBWuRPFeyoy7rqFAZRvgwxHxjYhYd9i+z1QV4p1Xq3qky/1KkiRJmibzvOE0jzfPUy/mee2Y561CzPPM8yRJmk2u6DO8RzTKP5tIL6bvh8DOtfIDIiK6LFF6U6O8Vst2mscviYjNRzlbKiLuRufe6gC/nMEl30QZBK5XlQ+qlkI+ZwbX1ACZ+feIOA24X616D/rsIR8RmwLfB5oD3espyz//GbgVuFN13amZXesAX4qI52Xmp/pcf0/gfynLBdedR1nW92rKUqjrU8KpuzJ7N0w227kJOIey1O5Uvzal/GzUA76lwE8iYpdpLP+7MfADViyrfTNwCmUp2PUowV99ye31gK9ExBMy89st21Kn9wMvqb5O4HfABZSlpreivL/rf8NfQgm06jNnevkA8O+NuqQEQBdWX9+F8jcjKIHdx1k5yBunn1KCCYBNgF2AX81i+5IkSZIWBvO84ZjnaSjmea2Z561azPPM8yRJmjXe6DO85h3Yp7U5OTP3GllPpufkRnkJ5QP9RY36KxrlzVu20+34bZnmDJ0e/rNRPmfY5WG7qZadfTcrluVcBPw38PjpXrNLGyNbxnSU5kC/TqYzGGgGPv9SzQD4PJ2hwJ8pS9B+LjNvbBy/BDgEeDVlUB3AkRFxamae3qOZI+gMBb4EvDYzL+jRp/WAfSjLgHd77z+Q8nt2SzrDxGOBg3v0Acq+3N38BfgM8G167FdevU4PpSzheu+qegPgGPrPJOnm9ZSZjwl8EDg8M69stPcwymD0rlXVGsBREbFDZv61ZXuzber7M6zVgE9RW0aY8h4ctUdRBsMAn6C87n+qHxARd6QM1h9Zq357RBydmdf1unA1Q6sZCnwFODgzL2ocuxXwHsqS1wfS+325kmoJ4Jn8fjmtUd4dgwFJkiRJ7ZnnDcc8r3sbk87NupoD/TLP6848b3aY5xXmeZIkreK80Wd4u9S+Xt78kDYPdJvN0i0YOLtRvndErJmZzZlBvezepW6DIc8dqNrH+YWN6iNGcOl3UZZQ3awqPy4ids/MZqCi0Wq+L7eMiNUy87Yux76SMgif8htg38xshlkAZOZy4HUR8RvKAD+AxcB76dzjHoCI2IzOgfMJwFO6zJKrt3Et8A3gGxGx0pLDU78nuqzAeu009kL+HPD+zOw7C6N67X4QESdWfXt49dSuEbFXr32le5ha3vylmfmhHu39MCJ2p8zY2K6q3pjyM/WMFm3Nura/xyPiw3SGAhdTQqFRmwoFXjy1n3ZTZl4aEftRlrye+vu0PmXJ5U92OyciVgeObFR/IDNf1qONi4AnRsSRwItr/ZoNv2uU+y1JLEmSJEm9mOcNxzxPbZjnDc88b8TM8wDzPEmSxOwtUTmvRcQd6BzcNgfT88FVXeq67c97KnBtrbwO8MRhGqjuFn9wl6eG2Rd5mOtvSJkBsqhWfQplRsSMVAO8tzSq3zHT62qg5vtydcrstA7VoLu+Z/bVwKN7hQJ1mfkVOpc/3bvHHtdbNcrH9gsFurRz/bDHTkdm/nlQKNA4/kbg2XQuz/q0aTT99V6hQK2ty4GnA/VA58nV784FISIOp4SHU/5OCaYuHVOTn+sVCkypZoAd2qheKfSqeTxlNtqU31ECt0FeTllGeDY1/85u0/WoaYiIzSJihzYPVsxwkyRJkjRPmOeZ52lszPOGv7553gSZ55nnjap9SZLmIm/0Gc7SRnm+zf6B7sFAtxkLtwBfbFS/pVrSdJD30v09NeNgICLWoCxHuXWt+jrgmT1mi0zHRyl75k7ZMyIePaJrq7uh3pfAU+kMst7Xcp/4dzfKjx3inM0GHzK3Va/R/9WqHjCNy7xxyLZOBb5eq1qDsjzsvBcRL6HzdbgW+H8zWWJ8CG8e8rgfUPZ3n3LvXgdSfo7q3tFtueimKpB6+5D9GZU/0xk0LR3htV8M/L7l4xsjbF+SJEnS7FjaKJvndWeep7bM88bIPG80zPPM8zDPkyQtcN7oM5zmAKHbYGau6/a97jW74R1A/cPiXYBvRkTXJXsjYlFEvIfee2DPaOAeZZ3UT9B5Z3sCz83M82Zy7brqw+8bGtX/Xe2RrPEY9n35sEa5GV71Ve3JfXGtas8uh50P3For/1tEbNfluDknItaJiNtHxFYRsbT+oPP31XbRZd3hPs7IzDNaHP+5RvmBLc6dkyLiycAHalU3AY/PzF+PsdkLMrPb8uwrqX5v/bFW1S/Qqi/FfjPwtRZ9+iqdfxfGqgos6rNRN2n53pUkSZIk8zzzPI2Hed4ImOeNj3nev5jnSZK0gK0+6Q7ME+s0ymNd0nNMlnSp6/r/yMzzI+IQ4D216r2B86q9XX8C/JWyf+yuwIuAe06dDlwGbFE7d/lMOk6ZWfTMRt3LMrPV4HBIX6AsKTt1F/2OVdtHjaEtDf++rA8wbwJurAa9bVxJ2cceuizbmZnLI+J7wNSsr02A30bEMZQ9wX+amTe0bHPkqqBqL2B/4H7APVj5d1Qvq1F+bq8e8vhTWnavefz9Wp4/p0TEw4CjWRFg3QY8PTN/NOamz2p5fD386RXg3h6oL718VpvlqTPznxFxFrBTy77NxD8p71eAoLzPr5vF9iVJkiTNb+Z55nlHjaEtmee1Zp43e8zzVjDPkyRpYfNGn+E0X6dZuwt6hDbsUnd5r4Mz870RsQVwcK16M+Dw6tHLK4H9GFEwEBFvBV7WqH5NZn5wutfsJzMzIl4DHFerPjwiPl/tkazRar4vb6bxfqkGwvX305p0zniYjo161L8c2I0SCgAsBp5bPW6MiF8DvwB+BvwsM6+cYT9aiYg9gQ8xs8HZBgwfDLSaYZeZf4qIGyivG8zj5ZIj4v6UWS9r1qr/PTO/PAvNt51lWt+3vdff9U0a5eae2cO4mNkNBpp/a9cY0XU/DLT9Pt4Vl/uVJEmS5hvzvMI8T6NmnteCed7sMc/ryjxPkqQFyht9htO8S7rbnsNz3T261PX9YJiZr4qI0yhL/95xwPUvB16cmV+JiBc3nvvL0L2siYg3AK9rVB+Wme+YzvWGlZk/iIgfA/tUVXcG/p2V94XWzDXfl5dkZnOp3w0Z/TaDXfeZz8w/RsSulKWl9248vRawR/V4JXBrRBxP2Qv+q136PVIRsT9lKd2ZDo7avJbXTOP6V7MiGFgzItbNzHk1a6Na4vm7wHq16kMz8yOz1IUZLY/ew5JG+R/TuMZ03g8z0fxbO5L3UWb+Dfhbm3NcZViSJEmal8zzzPPM88bDPG9I5nmzxzyvJ/M8SZIWKPcqHk7zw9C6E+nFzOzWKF+ZmZcMOikzj6Hc+fxMyqDkfMoMjZsod4P/iLLU7zZVKLA2sFXtEtcDZ7btbES8Cnhzo/rtmdlv9tEovZrOvaVf12tPc81I8315epdj1uxSNzaZeUFmPoSy//GRlPd8N4uAhwJfAf4vIrbqcdyMVdf+DJ2hwN8oy2A/gTIrYxPKUqirZWZMParzpmsUYcdYA5NRi4gtgR8AG9eqj8zMN02oS6PSnME4nZ+rWf1ZpPNv7Q3V/uWSJEmSNCzzPPM887zxMM8bgnne7DHP68s8T5KkBcoVfYbTHEBvPpFezMxDG+WThj2xWuL2f6vHIPelc/Dym8xstTRyRLwMOKJR/d7MfG2b68xEZp4aEV8GnlRVbQS8Bpi1Pix0EbEZKy8b+vMuh17RKJ+XmduOp1crZOYvKMv6TvV1N8re4nsDu1D2GJ6yG/CTiNglM5ePoTuvpnPf7m8BTx1yZs36gw/paTphWP2cmzLznzNof1ZFxMaUUOBOteovAC+dTI9Gqrl8cLfl3wfptUT2yEXEhqyYSQYr/x2WJEmSpEHM88zzzPNGzDyvFfO8WWCeN5B5niRJC5Qr+gxnGZ13sW85oX5MS0TsBdyrUf3NMTW3T6N8QpuTq2WC39eoPjIzXzGDPk3X6+ncK/dl1T7nGo0Xs/KytSu9LzPzJjoHNVtHxKj29h1KZv4tM7+ZmYdk5v0oA8e30jmr4i7AwWPqwn61r68Fnt5i+dyZvGe3aXNwNXumPphrtZzqJEXEusB3gO1r1T8AnpmZ41h6d7b9mc49su85jWvsOKK+DKO5vPyFs9i2JEmSpIVhGeZ5wzLP07DM84Znnjdm5nlDMc+TJGmB8kafIWTmDcC5tao7R8Q6vY6fSyJiNeDQRvU1lLvax9HWQbWqBD7V4vznAR9qVH8c+I8Zd24aMvMPwP/UqtYGDptEXxaaakZNc+/346vXvJv/q329BrDXOPo1rMy8NDPfADyj8dTje50y3baq3zX1wf1PM3OovZUjYjFw7+m2zcpLMQ+ya6P8qxm0PWuqoOlYOvv/S+AJC2V52cy8ns6ltG8fEdv3Or4pInYANht5x3pr9u20WWxbkiRJ0gJgnteqrYNqVeZ56so8b3jmeeNnnjeYeZ4kSQubN/oMr/4BdzVm907omTiMlQdR78nMa8fQ1lPp3M/7h5l5wTAnRsSzKCFAffnUTwMvysxJ7gn8JqA+0+I5ETH2ZWYXsohYRAmmNm081W+/9uMa5eePtFPT9xXg6lp56x7HNfdTXqtFG0sa5au7HdTDgcxsH+YdI6LNTJEDG+VuSzfPKRExte/5w2vV5wCPbDHLar74UaPc5ufoBaPsyBCay4D/cpbblyRJkrQwmOcNZp6ngczzAPO8OcM8b2jmeZIkLWDe6DO8Exvl+0+kF0OKiNUj4h3AGxpPncXK+2WPor3NgPfUqm4D/mvIc59CmSlUDwWOAZ434VCAzPwrnf+vRcB/T6g7815EbAJ8m7Ivdt1Rmdn8Gav7X2B5rXxARDSXlZ511fuzvgxsMwCYsrxR3rxFM829mLcb5qSI2IAhfwYHeNOQ7e0CPK5WdTPwuRG0P27vp4SaUy4B9s3M5l7yC8HH6Xy/viQiBobcEXEv4N/G1qvu6n9jbwN+OsvtS5IkSVoYzPP6t2eep4HM8/7FPG/uMM8bwDxPkqSFzxt9hvfdRrk5sJkTqkBgf+Bk4BA6B9uXA0+slnwceJ0Wbd4B+Amdy0C+NzMH3rEdEY+nDPrq78UvAc+aQ/vovpPy2k3ptZzryETEURGRtcdR425znCJig4h4OWWp0Uc0nj4FeEm/8zNzOeX7UPeViHhgy34siognRMRGXZ7bq23YEBGPBjasVZ3d7bhqufBltar7RcSSYdqofl7Pr1XdOyL2HdCvdSizrJYO08YAj4uIvt+fiNgU+CyNn+PM/MsI2h+biPgvOpcSvwJ4eGZeMqEujVU1I7Me1qwJHBcRzdk2/1KFAt+nLLE9K6qll/eoVf0qMy/vdbwkSZIk9WGe1/tY87wRM8/rZJ5nnjcO5nnmeZIkqRh68Leqy8zLIuIUVuz5undErJ6Zt8xG+xGxtEv1YmADylKg21d9ezDdZxdcADw2M88Zssm3VPu9HgMcl5krLS8aERsDT6fsGV4fHJ3KEDMPIuLhlMFL/X34f8DrgTuVFTiHdm1m/r3NCcPKzH9ExFsoMwW0wuIe78v1KO/LjYGdKe/LB1X1TT8AnpSZ/xyivSMo7++pQfES4ISI+Bjwgcw8t9tJ1SDjfsB+wJMpy1FvDVzZOHRn4L0RcTYlnPoG8LvMvLXLNdcCngW8q/HUZ/r0/3jg2dXX6wDfj4j3AmdSlpOuz3b7e2M57i/SOZvvyxHxYuDz9QCtWrZ2H+DdrFgq9XJWXlZ5WFdRfrY/GBF3Bw7PzI4ZSRHxUOAjwN1q1VcCB0+zzVlRhSv12U23UAKq63u8r3u5JTP/NMq+jdnLKO+Rqb8TWwCnRsRngK8DF1b1W1NmdD2L8jv675RgbzZm3u0OrFsrf30W2pQkSZK0AJnnmedhntdknmeeZ55nnjcO5nmSJM0yb/Rp52hWBAMbUmYB/XCW2r5w8CFd3UpZ3vG13Qb3fawOPLZ63BYR5wF/oOwnvD7lw+TOlKVv634D/L9hZhlRltds7jf8ADpnOwzrM8BB0zhvWB8FXk7vPZtXRbsy/ffl1ZRA6YPDzvTKzFsi4kmU2XgPqKoXAS8GXhwRlwK/pwxKV6O8T7ekLI3bZvbC9lXfDgX+GRG/B/5a9XmN6pr3pgzu604E/qfPdT8APIMVv3d3pQRj3TwbOKpWfjfwHMrPHZT/22eBd0XEr6u+bUT5mawHg8dQBrzP6tOvft4GvBS4E2VA+eKI+AVwKWXgthMlaKm7mTKDb07P/mHFazlldXp/P/q5iNHMtJoVmXllRDyCsr/3VGC0OvDc6tHNzcDTWHnP9nEtxb5/7evbKO91SZIkSZou8zzzPPO8FczzOpnnFeZ5c5h5niRJ6sYbfdr5AuWO/7Wr8gHMXjDQ1p8pswY+VC3vOBOrUQZXg/YS/iTwssy8bobtzTmZeVO1LOhsfUBd3Cg393Wer86gBGz/0zKoAiAzr46IvYC3Uwaq9WDqjtVjkH/Se+/tpnXo3Fu4l68DT+8XcmTmaRHxAuDDrPz97Sszl1fLCn+fziW17wA8usdpx1AChn5hxSB/Bx4OHEcJB9YA9uxz/HXA0zLz2zNoU2OWmb+LiD2AT1Bm5/VzEfDkzDwlIprBwT9G3beIWA14Yq3qB/NshpUkSZKkucc8rz/zvNExz+vCPM88TzNnnidJkppWG3yIpmTmlXQu5fnkiOi2fOmsdIcyuFlOmZnzU8qHvJcC9wG2zMxXzCAU+C7wbeDaAcfdQFkW9X6Z+byFGArUfA44bZba2r329S3AB2ep3Zm6jfKeuBw4izKg/ABldtZdMnOnzHzXdEKBKZl5c2a+EtiGssTsX4c47Qrgq1U/bp+Zl3U55tOUWQ7HAMPs6XwLZaD+yMx8/DDv/cz8NCVgeyNlBsafWHmZ317n/pYyw+doyoyMrocBPwcOyMynZ2av44aWmWdX7b6f8jp2cyMliNw+M78x0zY1fpl5fmY+GHgU5e/aeZSB/nWUWZjfpvw8bJ+Zp1SnLWlcZto/x308ks7ZWe8dQxuSJEmSViHmeV2Z542HeV4P5nnmeZo58zxJklQXmeNaqW9hqva1PYcVN0m9MDM/PsEujVVELAJ2ALalzK5Yj7J88BXAucApmXnD5Hq48ETE3ehc7viTmfm8SfVnPqj2n9+Jso/4Esqg/RrKAP8c4IJs+csuIjanLPu7lLKM7trA9ZQw7lzg9My8ZiT/gZYiYgnwQOAulJ/JK4G/AL8e52yJiFizancr4PaU4PAS4PhJvRaaPRFxCWWpayj7zk93r/h+bXyLFbPazsjMnfodP1siYgfKUuIAfP9np7DNdttPsEejdd45Z/OIPXetV+2YmWdOqj+SJEnSqJnnmeeNm3lee+Z55nkaP/O8FXnej0/6Jdtuv3DyvHPPPpt99uhYvMw8T5JWMW7d1VJmnh8Rx1D25gV4eUT8T9tBx3yRmbcCv6semh0PqX19M/CWSXVkvqhmqZw94mteBnSbKTRxmbmcMkNjttu9CfjJbLeryYuIrVkRCgCcOoY2tqPMAJpy2KjbkCRJkrRqMs/TLDDPa8k8b9baNc9bRZnnSZK0sLl11/S8Ebip+np74PET7IsWnnow8KnMXDapjkhS5d8a5ZPH0MbrWPG55JTM/OoY2pAkSZK06jLP0ziZ50maa8zzJElawLzRZxqqgdr7alWHRoSvpUZlr+rfm4C3TrAfkkRE7Ay8rFaVwGdH3Ma2wFNr1z94lNeXJEmSJPM8jdle1b/meZImzjxPkqSFz8Hs9L0JuLj6eifgWRPsixaIat/Y21fF/8nMSybZH0kLT0S8JCIOiYjbDXHsPsAPgTVr1d/KzD+OuFtHsGI70c9k5s9HfH1JkiRJAvM8jYF5nqRxM8+TJElNqw8+RN1k5nURcSDwsKpqjUn2RwtDZp4JxKT7IWlB2xQ4lDJ79ZvAT4EzgL9Xz28M3IeyjP3ejXOvBF48ys5ExPrAb4DfVlVHjvL6kiRJkjTFPE/jYJ4naRaY50mSpA7e6DMDmXkScNKk+yFJ0jSsAzylegzjSuBxmXnpKDuRmdcAh4/ympIkSZLUi3meJGkeM8+TJEmAW3dJkrSquZKyb3Yb3wV2zcyfjaE/kiRJkiRJknozz5MkSR1c0UeSpFVIZn4gIo4FHgE8ALgHcGdgCbAYuJYSHvyBsgzwNzLzd5PprSRJkiRJkrRqM8+TJElN3ugjSdIqplqu95PVQ5IkSZIkSdIcZp4nSZLq3LpLkiRJkiRJkiRJkiRJmge80UeSJEmSJEmSJEmSJEmaB9y6S5IkqYXNzv8JW9xy3qS7MTLLL/zTpLsgSZIkSZIkjc2S33+Xja89fdLdGJklyy6ddBckSRPmij6SJEmSJEmSJEmSJEnSPOCNPpIkSZIkSZIkSZIkSdI84I0+kiRJkiRJkiRJkiRJ0jzgjT6SJEmSJEmSJEmSJEnSPOCNPpIkSZIkSZIkSZIkSdI84I0+kiRJkiRJkiRJkiRJ0jzgjT6SJEmSJEmSJEmSJEnSPOCNPpIkSZIkSZIkSZIkSdI84I0+kiRJkiRJkiRJkiRJ0jzgjT6SJEmSJEmSJEmSJEnSPOCNPpIkSZIkSZIkSZIkSdI84I0+kiRJkiRJkiRJkiRJ0jzgjT6SJEmSJEmSJEmSJEnSPOCNPiMQEZ+OiKweX5h0f8YhIu4YEftHxEsi4nUR8YKIeHREbDrGNjePiMdExEsj4vUR8eqq3YdGxGbjaldaVUXEYbXfZRkRe42xrWW1dpYNOPagRr8OGtW1xyUijmr0eekk+jEfRMTSiLihep1ujYhdJt0nSZIkSQufed7Y2jTPk2aRed7omOcNzzxPkqTJW33SHZjvImIP4FlV8SbgtQOOPwF4cFU8MTP36nPsUuDCIbpxM3ANcBVwJnAq8JXMPHuIc/v1dTXgqcAhwE49Drs1In4CHJGZP5pJe1Wbi4BnAi8G7jvg2AuA7wFvyMzlfY5byuDXMYEbgeuBy4HLgPOA3wEnAadlZg71nxjc/rMz86jpXGuU2vYrIg4DDh1w2Vsor+M/gL8BFwHnAr8GfpaZf55+jyXNF1WodHytau/MPKHbsZm5LCI+BLyScgPyhyNi98y8bdz9lCRJkrRqMs8zzxvEPM88T1rVmOdJkjS/uKLPDFQD5yOBqKo+kpnDDORHbQ1gY+BuwH7Am4CzIuInEbHtdC4YEXcAfgZ8lt6hAMAi4GHADyPioxGx1nTaq9rcCTgN+BQDQoHKXYCXAHeYbpv15oHFwIbANpTw5vnAB4HfAH+KiPdExF1G0NZCtjqwLuV7shPwGOBg4AuU1/DkiHhhRKw9wT7OuojYqzEb5LBJ90maY95KCbgB7g8cNLmuSJIkSVrIzPMA8zx1Ms/rwjxPGsg8T5KkCfJGn5k5ELhX9fVNwDsn2Jdu9gZOj4h925wUEVsAvwQe0HhqOXAc8Pnq36sbz78QODoigpYi4pHAycCOjaeuAn4KfLl6HE+ZoTPbtgD+Ezg/Ij4SEUsm0If5LoDdgI8CF0TEMybcH0lzRGZeRQnapxwWEYsn1R9JkiRJC5p5XifzPPVjniepK/M8SZImy627piki1qDMtJlydGZeOgtNb92lbk3KDKBdKMvk3q/23FrAVyNi58z8w6CLV/+vY4E71aqvpSz3+4nMvLlx7POBIyizPgCeRFna9Y3D/oeq5ZKPpczAmfIr4PXA8Zl5S5dztqPMdnrusO00dHsd1waWVI/tKXehPwjYvHbMasCLgIdHxH6ZecY0218IjqXM7qkLYH3Ka7gJ5T25K/BAyvt0yh0oIdIjKEsM3zT23kqa695DCWAXU/4GvbiqkyRJkqSRMM8zzzPPM8+TNFLmeZIkTYg3+kzfU+gcXB7Z68BRysxlfZ4+GfhQRBxM52ykdSnLKD55iCaeQ5mlMeVGYN/MPLlLX26m7L36O+DHrBj4HRIRnxrQVwAiYl3KcsL1UOA9wMH99tDOzHOAcyLiCKaxMtUQffte1b/VgSdQgpFdas9vDfwkIh40073T57Frh3gdjwWIiNtTApX/BDaoPX8gcLuIeJz7965aMnPpfLx2iz4chMvVtpKZf4+IL1ECboBXRMQH64G0JEmSJM2QeZ55nnmeeZ6myTxPTeZ5kiRNjlt3Td8ra1+fkpmnTaojTZn5LuCoRvUTIuJ2/c6rluh9daP6Ld1CgUZ7PwfeVqtai87ZUf38N7C0Vj46M1/ZLxRotJ2ZeeuQbbWWmbdk5pcoYck7gXq/NqHMrlpnXO0vFJn518w8HLg38OvG048BDpv1Tkmaiz5a+/qOwFMn1RFJkiRJC5J53or2zPPUl3mepCGZ50mSNAHe6DMNEbE7K/byhjKDZa55b6O8OmXZ2n52pHNW0w3Ah4Zs74PV8VMOiIj1+p0QEVtSlnKccjllhsicUwUEhwBvbjy1HfCaCXRpXsrMC4G9gLMaT70mIrad/R5JmkuqIPqCWtW/TaovkiRJkhYW87yuzPM0kHmepH7M8yRJmgy37pqeg2pf30a1nOkccwbwT6A+O+VOPY6d0gwOTsnM5cM0lplXRsSvgD2rqsXAo4Av9jntecCiWvmjmXnlMO1N0OGU/akfUqt7eUS8KzOvmVCf5pXMvC4ingCcTpktBrAG8DrgWW2vVwVQewBbAJsCtwJ/A84GfjOTJYSra9+LEgAtoez7fgNwDXAxcF5mXtDzAmMUEXei7D1/F8o+6ouAqyj/91My89IxtLk25Wd8S2Czqr2LgBMy84Z+52pmImInYAfKrJikfJ9Pzsw/jODa21GWMt8cuAW4FDgzM5sB3mz5Mitmo+4WEdtm5rkT6oskSZKkheOg2tfmeZjnmecNzzxvNMzzVi3meeZ5kiSNkzf6tBQRi4ADalWnZuZlk+pPL5mZEbGczmBgowGnbdko/75ls2ewIhiAwcHAcxvlT7dsb9Zl5m0RcTidwcDtKMtRfmwyvZp/MvPciPgc8Oxa9ZMj4j+GDVgi4uGUwcMDKcFCN3+PiE8C78jMq4btX0TsDPwX5T281oBjLwd+BHwsM09sPNdryepDI+LQPpfdOzNPaFxrTeDhwBMp77++QV9EnAe8H/jUTAftEbEFZTnmp1De703XRsRngdcPG+5FxDJgq6p40Sj34R722n2+P22cmJl7dbn2UXQGXVtn5rIe/dgLOL5WdXhmHlY99yzgYMoMzW7nng68JjO/37bjEbE/Jey8R4/nf0P52flSVT4BePDU85kZbdsc0jfpXHb+QKDfz4skSZIk9WWe15d5noZinmeeZ57XcexemOfVmedJkjTL3LqrvQcAG9bKx/c6cA5Yv1EeNDhoBgfLW7bXPP6evQ6MiLvTGUT8sVoGds7LzJ8CpzWqHzuBrsx372+U16IMfPuKiE0i4ofA94G96R0KQNl3/dXA+RExaKnrqesfApwKPIEBoUBlU0ow9Pxhrj8D76IMmJ7F4Nl8ANsARwK/iIi7TLfRiHgAJfR7Pt1DAYD1gBcB50TErtNtSytExLoR8WXgKHqEApV7Ad+r3rfDXnuNiPgiZaZN11Cgch/gixHxsSoUny2/Aq6rlR89i21LkiRJWpjM83prHm+ep37M89oxz1uFmOeZ50mSNJtc0ae9RzTKP5tILwaIiG0oH9brBi1JelOjPMygqN/x20XEaj2WWr1/o3zy1BcRsQPwDGBfygBofeAK4E+UIOarmXlKy76N2g+BnWvlB0REZOYoZhSsEjLz9Ij4G2XJ2Cl7UAYrXUXE3YDjKMvb1v2DMpj/K2XJ26WUQc3UzYwbAz+MiMdm5nF9rv804B3NrgJnUn5+rqG8zzcAtgXuDIxrFkRT88bMf1KWM76s6teawB0oA8X6AP5ewPERce9pLKV9N+CdlGWOAa4HfkF5nZdQXuP6929T4AcRsU9m/rplW1phNeBzrAgcb6W8vy+pvr4bcG8633vviIgzMvN7/S4cEQF8hZXDzFspA/KLKe/xbShLSQO8APj7dP8zbWXmzRFxMvDQqureEbFZZv5ttvogSZIkacExz+vNPM88b2jmea2Z5606zPPM8yRJmlXe6NPebo3yaW1O7rYk5Ji8qFG+BThpwDlXNMqbt2yzefxiysBpWZdj79sonx0R6wJvB17CyoOtzavH/YBDIuI44MWT2k+ZWpBRWUL5v17UPLBa3nO2Bo9DmyP9+gWdA5R79TowItYBvkZnKHAu8Hrg65l5a+P4zSnLmE7NzFkT+GxE7Nxtv+uIWA04olH9IeCtmfmXHn3aiBJgPZUysGrauvp3N+Dztfr3A+/rds1K1/aAPwJHA98BftstdIuINYDHUX6Wpl6rOwMfpizV28YRlPf2TcCbgfdm5r9mZlSzQvan/H9uX1WvD3wuIu6Vmde3bG+2bT34kA5rA8eyYsAM8OfRdedf/o0ye+1WSjDzrszs+P0cEdtS3gv1kPUDEbHNgIDypawcCnwEODQzL2+0sSPlZ+DBwGspe7gPpVqqeia/X05jRTAQlJ+hb87gepIkSZJWbeZ5vZnnmee1ZZ7XnXne7DDPK8zzJElaxXmjT3u71L5enpl/mlhPeoiIAygf/uq+0vzQ18XZjXIzBBmk2/Eb9Di2GSJcRZlVs/uQbT0c+GVE7JeZgwKPcTinS13XYEB9nUPnIOXOfY59J51Lnn4PeGKvwWdmXga8ICLOAd5dVW9CGeA+p8sp9wW2qJU/k5n/0a/z1YyaLwBfiIi1uzy/DCAiljaeWt5rf+c+jgBe2mNGXb3Nm4EvR8SPgJ+wYqbaARHxupZh2oaUwemTM/PrXdq6lbIU7G8osyGnwoG7A6+j7Is+Z7X5HkTE6sBX6QwFfsvKIewoTIUCj8vMb3c7IDPPjYiHAb9nxdLPd6Ps9/7jbudExMbA2xrVr8jM9/Zo4/cR8VBKGPJYVl4Ofpx+1yjfnxEFAxGxGWW2Wht3HUXbkiRJkibGPK838zzzvLbM84Znnjdi5nmAed6wzPMkSQtac+lI9RERd6BzoDsnBoHV/qybR8Sjqz1gv0RZ7nTK5cAw+72e2CjfNSKGGqhHxANZeflV6L0H8JJG+XWsCAWSMth6AmVf8B2Bx1OWvqzf2b4x8I2I2GqYPo5Ytzvh237Q1MqvY9fXMCK2AJ5Xq1oG7D/MDJPMfA/w3VrV06qf5abm++grg67daGess10y8+JBoUDj+KvofM1Wo8xUauuD3UKBRlvnU2at1L0oItouFz6X/Q/wmFr5D8AjMvOaMbX3jl6hwJSq7ebS1A/pc8pzgHVq5e/1CgVqbdwCHERZ3nk2Nf++bjPCa7+YEqi0eXxjhO1LkiRJmkXmeX37YJ5nnjcd5nnDX988b7LM82aXeZ4kSbPIG33aWdooz/rsn4jI5oOyDOefgW9Rlt2suxjYNzMvGXTtajnT5p3j766W8+zXp9VZMcOiadhgYMvq32uAfTLzqZn5tcz8fWaemZlfz8ynAftQ9m+esjHwyX79G5NuwcBKM0A0UPN17PUavoiyVO+UwzPzny3aqb8/1wQeMcQ5mw0+ZG7LzFPpHGA9oOUlbgLeMmRbXwN+U6vaBHhUy/bmpIh4J2VwPOUyyu/Vce0xfT29f6c2NcODe/c5thkMDfu9vYqy5O9sav59XTrL7UuSJElaOJY2yuZ5mOfVmOe1Z543RuZ5o2GeZ54nSdJC540+7TQHCkPvbzoBy4A3ADtk5mktzntro7w78L+97uSPiMXAMXTuK1vXa8ZCr/feMzPz+F6dq557eqN6n2FnKo1Qt/7320dX3TVfx16v4cNqX99Ky9k5wM8p+9pP2bPLMc3lm1/bY6bQnBLFetUswKXNB2UG4JTte1yml+Oae0kP8LlG+YEt25tzIuIQ4OBa1XLKzJ8Lx9jsydUy0gNl5kVAPSTrGmhFxLrATrWqSzPz/1r06Ustjh2F5t/XeR/USZIkSZoY87wG87wO5nntmefNkHneeJnn/Yt5niRJC9jqk+7APLNOozzWpT1naAPgysy8ts1JmXl8RHyAzj3BnwrsFhFHUgZYV1L2dt0TeAkr7sy+AbiOMitnyvIeTXXr1/GZOXA5xcz8ZkT8mDIbaMrTgZMHnTtCS7rUzeX3w1y1pFFe6TWswqddalWXAJtExCYt21pOmZUCXfbnzcwzIuIMyvLSUPZHPicijqIEEb+olj2dqIhYE9iXshT2fYDtgGGX1N2wZXOnzPD4+7U8f06JiIPoXEr3euAxmdncb3rUzmp5/HJW/H3aoMcxO9K5BPyvW7ZxPnB1n+uPWnOG37ojvPaHgS+3POeuuNyvJEmSNF+Z55nnTVnSpW4uvx/mqiWNsnneAOZ5s8c8r4N5nnmeJGkB80afdpqv1yQGCVs3yqsB6wM7AAcA+1X1GwIfjoitM3OY/bzrDqbsrVxfFnJr4F19zrkNeEZ1zHSDgaOH7yJH0xkM7NXi3FHoNsC6vEud+mu+jt1ewzsAa9TKS4GZzr7YqEf9C4DjgcVVeQPgZdXjuog4hRJA/Rw4KTP/0fUqYxIR+wHvZeXfA8NqO6g7r+Xx5zfK83bWRkQ8lrKP95RbgCdn5s9nofm2s0tvrn29Ro9jmkFac8/svjIzI+ISZi8YaP597fX/aq1aornVMs0RMarmJUmSJM0+87zezPPM86bDPK8F87zZY57XyTzPPE+StLC5dVc7zdkJs76Hc2YuazwuyMzTMvOYzHwc8BjKTJwpr4qIZ7ds4+bMPBD4T8psn0EupAzSjwU2bzz31x7nLO9S94th+9jl2G1jdj+53aNLXasP2gJWfh27vYYbd6mbqa57zWfmL4A9gN92eXpd4CHA64HvAZdHxNcj4qFj6N9KIuLlwNeZfigA0PZn5JqWx1/dKPcKYOa0iNgT+CIrwuAEnpeZ35qlLvRaIn0mljTK0wm12r4fZqL59/W6WWxbkiRJ0sJintedeV5hnteeed6QzPNmj3leT+Z5kiQtUN7o007zQ9Eolx4cicz8NvDCRvUHImKraVzrfZRByIuArwIXUD5M3lB9/W3KrJ8dMvMEylKIa9Yu8YfMXN7j8t1mFlzWont/bpQX0X353XHZrVG+MjMvmcX2F4pdG+XTuxyzZpe6meo5QM7M31CWFt4X+DRwcY9D16LMuPthRHw7IsYRYAAQEbsC725ULwPeBjyaErBsRBlMrZaZMfUATpxB0233qW8eP+/2uY+InYBvsWIWGMAhmfmZCXVpVG5slKfzczWOn8Vemn9fZzOUkCRJkrSwmOeZ500xzxsN87whmOfNHvO8vszzJElaoNy6q53mwK8522VOyMyjI2J/ymwggPUog4r9p3Gta4CPVY9Bdm+U++0HfGaXuuYH1366Hbu4S924NGd9nDSLbS8IEXFvVl5+tNsyqn9vlH+QmQ8fT6+KzEzgh9WDiLgTJQzakzILaIfGKY8CvhsRe4xp3+9D6bwx8+PAS4Zsa/0ZtNt2WdcljXLbJWsnKiK2Br5P5//7iMzst8z5fNH8XrTd3x1md0bXFo2ywaskSZKk6TLP6888T0Mzz2vFPG8WmOcNZJ4nSdIC5Yo+7Syj8472LSfUj2G8ks49UZ8YEfcfc5v7NMon9Dn2d13qlrRoq9uxV7Q4f9oiYi/gXo3qb85G2wvMyxrlG4AfdDmuuVz0NuPpTm+ZeUlmfjkzX5qZO1Z9OJLOJVnvDxw06rYjYl06f7YuYPhQAGYWYLZ9re/eKLfaN3mSIuL2lCCo/np9OjNfPaEujVpzGe17tjm5eh8uHVlvBrtjo3zhLLYtSZIkaWFZhnleP+Z5asM8bwjmebPDPK8/8zxJkhY2b/RpITNvAM6tVd05ItaZVH/6yczzKcuU1r15XO1FxO3onGF0LWVP3K4y8490vpaw8qyKfnZslC/PzJtanD8tEbEaZTZG3TXAF8bd9kISEdsBT21Ufz4zr20eW81Cq88YWxoRzQHorMrM8zPz34HXNJ56fK9TZtDcVnQusfr9YUOBiLgLcIcZtN1c0nqQ5tLNv5pB27MmItanzPy5a636m8DzJ9Oj0cvMP9A5m27niFjS4hJ7MbufGbZvlE+bxbYlSZIkLSDmeb2Z55nntWGe14p53piZ5w1lL8zzJElasLzRp736B93VWHmAOpe8Dbi5Vt43IvYYU1svpXMP1s9l5j8GnHNso/yIFu01j/1Zi3Nn4jDKB+S693Qb0Kq7aibBsXQOdm8C/rvPacc1ynNlwPbJRnnrHsc1l6Zeq0UbSxrlq1uce1CLY7vZt+Ve5Qc2yt2Wbp5TImIxJQTYuVb9M+DJmXnrRDo1Pj+ufb0W8MwW575gxH0ZZKdG+Zez3L4kSZKkhcU8rzvzPA3FPA8wz5szzPOGZp4nSdIC5o0+7Z3YKI97+dxpy8xlwNGN6pHPAqpmc7y+VnUtJZQY5Gig/sH72RExcJ/Z6pjnNqq/PUR70xYRq0fEO4A3NJ46CzhinG0vJNWeyScA92g89bZq1lovH6Fz6er/iIg2M8bGpTkTp9e+9Msb5TbL7zb3Yt5umJMiYitKYDcTa7Lye75Xe48H7lOr+jvwnRm2P1YRsQj4PPDgWvXpwGOqGZ8LzUcb5UMjYuAMsYh4JPDY8XSpp/rf1uU4A0iSJEnSzJjnNZjnmecNyzzvX8zz5gDzPPM8SZJUeKNPe99tlPeeSC+G91Y6By97V3tS9xQRqw978YjYFvgRsHat+rWZ2dw/diWZeS7wqVrVxsAn+7VfPffJ6tgpFwPHDNvnNqpAYH/gZOAQIGpPXw48MTOvH0O7J0RE1h6HjbqN2RQRt4+I/wJ+A9y38fQ3GBBYVcuU1peuXgx8NyKaAcOgfqwVEQf1eG6/iLhfm+ux8gyKs3scdwFlltOUvSNijSHb+CMlbJvy6IjoO/MwIjYBvgpsMGQb/fxHROw3oL27AR9uVH8sM3sFJXPFx4DH1coXAI/IzDazrOaNzDyBztmSGwE/iog79zonIvahz7Lt4xARW9C5n/xxC3A2liRJkqTZZZ7Xeax5nnneQOZ55nlzlHmeeZ4kSQKGHgCqyMzLIuIUVuxdu3dErD7sHruzLTMvjIijgefUqt8M7NnntKMiIih3xv+428C3+uD2AspguR4KfAc4skUX30j5YL5pVX488L2I+PcqOKi3effq2g+rVSfw8rb7eUfE0i7ViykDqSWU/WR3pcwM6DZb4wLgsZl5Tpt2F5j1uryOAdyO8jpuCuxCeR33pHNp3yn/CzwvM28bor1XVNeaWgL0zsCvI+K9wEcz85JuJ0XE2sAelBkMT6n6dVSXQ/cGXhYRvwa+TFn+9dzMXGk/7moP+5cAb2o89ZlufcjMmyLiJFYEiXcGvhkRHwXOB/7ZOOUvUzNQqnO/Djy9em4N4LiIeG5mfr/Rr0WUn6d3AUspPx9X0hmktXEVsCHwpYh4E/C+zLyu0d4TgQ8At6+d9weGmwU4MRHxAjpnEl5L+Z22uMfvh15uyMy/jLJvY/ZsyiynqaXZdwDOiohPUILviyk/q9sATwL2p/xcnw/8g85ZXuPy0Eb567PQpiRJkqQFzDyvMM8zz8M8zzzPPA/M88bBPE+SpFnmjT7TczQrgoENKR/2fzi57gz0VspMhanv9wMj4mGZ2avPiykf9g8Ebo6Is4FllA+FSyiDmh3pnA0D8APgSd0GUr1k5l8i4tHA8cA6VfVDgXMi4nTKh9EE7k7nnrtT3pSZXxu2vZoLp3EOlKWJP06Z5bQgZwm08MTqMR2XAa/KzKFnbmXmtdV75QesWO52beB1wOsi4gLgHMqyoKtTwomlwN2ARS36dt/q8Q7gmoj4PWW21z8oPxt3prwXm0HHZzOzufd43XvonDH4CHrvY783ZUnkKYdRBvzrVeUtKAHaRcBvKcHCJsD9KL+TprwNeCCdS9m28RrKUtYbAG+hvM6/AP5a1e1CZyAAcA1wYGY2w465ZotGeT3KbMa2TgT2mnFvZklm/rGa0fVNVvzOXRd4WfXo5lpKQPCB8fcQqramXI3BgCRJkqTRMM8zzzPPM88zzzPPA/O8cTDPkyRplnmjz/R8gXKH/dTMlwOYw8FAZl4QEZ8FDqpVv4nh+rwGZcbFTn2OuQV4J/DG6cyEysxfRsT/owQuW9Weulf16OZm4GWZ+ZG27U3TnynLXX4oMy+YhfYWN8rNfZ3nowR+SVne+X+ns0RyZl5SLcf7UeBpjafvUj0GWd6iyfWBBwxx3EeB/+h3QGZ+OyLeABxOu6BiajC3P/AVVoQDUH5etup+Fu/MzDdExAlt2mo4D3g08C1KKLgO8JA+x19OmRn3qxm0qTHLzB9XS75/gv6/2wF+Rwl8z61m0035xzj6FhEbAPvWqj6/QPdXlyRJkjT7zPM6meeNnnletwuY55nnacbM8yRJUtNqk+7AfJSZV9K5pOeTI2K9XsfPEW+lzF6ZsltEPLLHsV8AfgIM+jD2D8r+2jtm5utmstxxZv4UuCfwduDSPodeR9nbebsRhwIJ3EgZNP4B+CnlQ/NLKUtbbpmZr5iNUKD68L1zreoqui9NOxfdClxPmSFyBvBt4N3AU4E7ZuZumfnxmeyDnpnXZubTKaHRZxkuNPkzZd/3A4A79Djmv4HnU/bC/usQ17weOBbYPTP/bZj3f2a+lTIQezvlPfaX6joDVbOL7kvZA73XLLtbgOOAfTLzkGGuO0S7P6f0+Sg69xavu5ayP/Z2mfmLUbSr8arCm/sATwa+RFm+/J+UGVxnU5a73g/Ypbbs+pLaJcY1A/IZwFpT3QTeP6Z2JEmSJK1izPP+xTxvDMzz+jPPM8/TzJnnSZKkumixKqtqqv2lz2HFzVIvzMyPT7BLIxcRa1IGBHen7Gu9DmXg8TfgLODUzLx5DO0GcH/grlW7i4C/UwbsJ4+jzbkkIh5K5+ys/8rMt0yqP3NdRKxGeZ/eA9iIMni5gTLAWQac3Wu/7wHX3QrYljLDZgllsPJPyh7ZZwNnTGo524i4PWUJ3ztTZiJeTlk++ReZ+fcxtrtu1e6dKHujXwVcBJwwk7BHc19ELKb8TK1RVf06M+83hnbOoCwlD/CtzHzsqNuYjojYAfj9VPk3n/pv7rH1lhPs0WiddeGfuM9zXluv2jEzz5xUfyRJkqRxMc8zzxsX87x2zPPM8zR+5nmded6pHzuMeyy94wR7NFpnLbuUXV54WL3KPE+SVjFu3TVNmXl+RBxDuVsZ4OUR8T9t9rOe6zLzJuDX1WM2203glOqxKqovpXoF3gHfV2beBpxWPUZ53Ysog945JzP/Spl9NNvtXkeZYaRVz+6sCAUATh11AxGxLytCgaQsiy1JkiRJI2OeN9Z2zfNWMM8bwDxvVts1z1t1medJkrSAuXXXzLwRuKn6envg8RPsixaOejDwrswcy965ktTCvzXKJ4+hjTfUvv5yZo48fJAkSZIkzPM0HuZ5kuYa8zxJkhYwb/SZgcxcBryvVnVoteyoNC0RcTtgl6p4OfDBCXZHkoiIRwIH1KquBb464jb2AfasijcArxvl9SVJkiRpinmeRs08T9JcY54nSdLC5yB25t4EXFx9vRPwrAn2RfPfg1ixpd4R1dKqkjQyEXF4RLwgItYa4tinAl9uVH9qlDMTq0D9XbWqt2fmH0d1fUmSJEnqwjxPo2SeJ2mszPMkSVLT6oMPUT+ZeV1EHAg8rKpao9/xUj+Z+R0gJt0PSQvaVpSl6t8REV8Dfg6cBVxJ+VywKXB/4MmsmJE45Y/A60fcny2Bb1SPW4EjRnx9SZIkSepgnqdRMs+TNAvM8yRJUgdv9BmBzDwJOGnS/ZAkqYUlwLOrxzAuAh6bmdeOshOZeTFw2CivKUmSJEmDmOdJkuahJZjnSZIk3LpLkqRVzd9bHn8r8Dng/pl51hj6I0mSJEmSJKk38zxJktTBFX0kSVqFZObBEfFRYF9gd2A74E7ABsCawDXAFcA5wInAV91jW5IkSZIkSZoM8zxJktTkjT6SJK1iMvMPwB+AD0+6L5IkSZIkSZL6M8+TJEl1bt0lSZIkSZIkSZIkSZIkzQPe6CNJkiRJkiRJkiRJkiTNA27dJUmS1MYOD4Ltt590L0ZnnbMn3QNJkiRJkiRpbFbbbndW226bSXdjZFZbfN6kuyBJmjBX9JEkSZIkSZIkSZIkSZLmAW/0kSRJkiRJkiRJkiRJkuYBb/SRJEmSJEmSJEmSJEmS5gFv9JEkSZIkSZIkSZIkSZLmAW/0kSRJkiRJkiRJkiRJkuYBb/SRJEmSJEmSJEmSJEmS5gFv9JEkSZIkSZIkSZIkSZLmAW/0kSRJkiRJkiRJkiRJkuYBb/SRJEmSJEmSJEmSJEmS5gFv9JEkSZIkSZIkSZIkSZLmAW/0kSRJkiRJkiRJkiRJkuYBb/SRJEmSJEmSJEmSJEmS5gFv9JEkSZIkSZIkSZIkSZLmAW/0GZGI+HREZPX4wqT7Mw4RcceI2D8iXhIRr4uIF0TEoyNi0zG2uXlEPCYiXhoRr4+IV1ftPjQiNhtXu9KqKCL2qv0ey4g4bIxtHdVoa2mfY5c2jj1qVNcel4g4qNGHg2a7D/NFRCyKiDNrr9XLJ90nSZIkSasG87yxtWmeJ80S87zRMc8bnnmeJEmTt/qkO7AQRMQewLOq4k3AawccfwLw4Kp4Ymbu1efYpcCFQ3TjZuAa4CrgTOBU4CuZefYQ5/br62rAU4FDgJ16HHZrRPwEOCIzfzST9qo2FwHPBF4M3HfAsRcA3wPekJnL+xy3lMbrmJkxzf61vlZELAO2qoqfycyDptP2qLXpV0TsBRw/4JK3ATcC1wGXA38GzgVOA07KzLNm0l9J80dEZK14eGYe1u24zLw1Il4NfGvq2Ij4YmZeNu4+SpIkSVp1meeZ55nn/Yt5niTAPE+SpPnEFX1mqBo4HwlMDQw/kpnDDORHbQ1gY+BuwH7Am4CzIuInEbHtdC4YEXcAfgZ8lt6hAMAi4GHADyPioxGx1nTaq9rciTKI/BQDQoHKXYCXAHeYbpsaqdWAtYFNgO2BfSgBz8eBMyPiDxHxpuq9tUppzAY5YdL9keaSzPw25e8NwPrAOybYHUmSJEkLnHkeYJ6nFczzejDPk3ozz5MkabK80WfmDgTuVX19E/DOCfalm72B0yNi3zYnRcQWwC+BBzSeWg4cB3y++vfqxvMvBI6OiNazayLikcDJwI6Np64Cfgp8uXocT5ldovnnrsB/Acsi4i0RsXjSHZI0Z7yl9vXTIuKeE+uJJEmSpIXOPK+TeZ76Mc+T1It5niRJE+LWXTMQEWtQZtpMOTozL52FprfuUrcmZQbQLpRlcu9Xe24t4KsRsXNm/mHQxav/17HAnWrV11KW+/1EZt7cOPb5wBHAulX1kyjLu75x2P9QtVzysUB9oPgr4PXA8Zl5S5dztqPMdnrusO1opC4FHtilfl1gCbAhJeTZFXgQsFHtmLUo39tHRsR+mXnJeLsqaa7LzB9ExK8psz9XA94KPHayvZIkSZK00Jjnmeet4szzJI2MeZ4kSZPjjT4z8xQ6B+lHzkajmbmsz9MnAx+KiIPpnI20LuVD1pOHaOI5wG618o3Avpl5cpe+3Ax8OCJ+B/yYElAAHBIRnxrQVwAiYl3KcsL1UOA9wMGZmd3Pgsw8BzgnIo7A1akm4ZYhvr/fBoiItYGnUcKlu9eevzdwQkTskZl/GUsvNSdV+8cfNN+u3aIPRwFHTbIP89SHKUu9Azw6InbIzDMn2SFJkiRJC455nnneqsw8T9NmnqcezPMkSZoAB1Mz88ra16dk5mmT6khTZr6LlT+UPiEibtfvvGqJ3lc3qt/SLRRotPdz4G21qrXonB3Vz38DS2vlozPzlf1CgUbbmZm3DtmWJiAzr8/MT1CCgP9tPH0X4AvTWR5a0oLzBcqS8gBB599ZSZIkSRoF87wV7ZnnqSfzPElDMs+TJGkCvNFnmiJid1bs5Q1lBstc895GeXXKkqv97EjnrKYbgA8N2d4Hq+OnHBAR6/U7ISK2BF5cq7oc+M8h29M8k5nXZeYzgaMbTz0YePYEuiRpDsnM64Gv1aqeGhEbTKo/kiRJkhYW87yuzPPUl3mepH7M8yRJmgy37pq+g2pf30bZj3quOQP4J7BOre5OPY6d0gwOTsnM5cM0lplXRsSvgD2rqsXAo4Av9jntecCiWvmjmXnlMO1pXnsRZd/57Wt1b4iIozLztjYXiojVgftTZhJtSpl9djmwDDgpM2/offZQ196xemwCrAfcTNnj/lLgj8BZk5iBFhEbAfegLJ28EeXn7RrgCuA04OxhZ9G1aHM1yjLgdwG2oASBlwI/zczLR9mWOkXEnSg/M1sCawN/p/yO/3Xbn5ku196M8nt7i+rafwYuAH4x02tP05dYERQupiyr/7EJ9EOSJEnSwnNQ7WvzPMzz1Ip53gyZ561azPPM8yRJGidv9JmGiFgEHFCrOjUzL5tUf3rJzIyI5XQGAxsNOG3LRvn3LZs9gxXBAAwOBp7bKH+6ZXuahzLz+oh4O/CZWvXWwMOA44a5RkRsD7wBeDSwfo/Dro+IbwJvzMzzhu1fRNweeD1wILDxgMP/GRE/Bz5f7eNcv84JlNlNTQ+OiH6D9sMz87Au/doVeBLlddqRshRqL1dExCeA9810v/SIWAy8Cng+3cPFWyPiB8DBmXnWkNc8CnhWrWrrIfaIH8qw1+7z/WklM1f6PkTEQXT+Pnt28/3ROL7+fjgxM/eq6h8AHA48hO6r8P01It4KHDmNUO3ewDuBvXtc+08R8THg7Zl5S0QcBhxae37vzDyhTZtD+jFwHbBuVT4QgwFJkiRJM2Se15d5ngYyzzPPM89b6XjzvBXM8yRJmmVu3TU9DwA2rJWPn1RHhtAcMA2aDdEMDpa3bK95/D17HRgRd6cziPhjZl7Ysj3NX58H/taoe+ygkyJiUUS8lxJaHUjvUADKbIYnA2dGxMuG6VREPAQ4F/gPBocCUIK3fYG3DHP96YqIJwC/AF5B+bkatAf6xsCrgd9HxMNm0O4dgJOBN9F7BuEi4P8Bp0XEi6bbljpFxOuAnwIPpfff69sDHwC+EhFrtrj2K4BfAfv0ufaWwJuBE6uwbFZk5s3ASbWqPSJiyWy1L0mSJGnBMs/rrXm8eZ56Mc9rwTxv1WOe9y/meZIkjZkr+kzPIxrln02kFwNExDaUpUnrLhhw2k2N8lotm20ev11ErNbjzvT7N8onT30RETsAz6AMuO5EGfxdAfyJEsR8NTNPadk3zSGZeXNEnEjnbLo9+p0TEWsDX6e8L+pupixv+yfgRuAOlPfX1Oy31YH3RcSG3WbW1K5/d+DblECh7iLgbOCqqrw+ZcbS3YE1+vV5hJqDt1uB84ELKUv8JiUMuCfl/z9lY+A7EfHgzDyZdtYCvgPsXJVvA06lLKO8JmWp5m1qx68BfCQiMjOdsTEDEXEw8NZa1bnV4zpgc8qSy4trzz+eMoh/9RDXfiXwri5PnUV5T90I3JmytPAiShj+JUpIMVt+yoqf80WUWW9fnsX2JUmSJC085nm9medpKOZ5rZnnrULM88zzJEmaTd7oMz27NcqntTl5agnHWdC8E/8WOu+q7uaKRnnzlm02j19M+YC5rMux922Uz46IdYG3Ay9h5RkOm1eP+wGHRMRxwIszc1DYMXGZuXTSfehmDvTrZDqDgR0iYvXMvKXH8UfSGQpcDRwGfDIz/1E/sAoRXkyZmTM1gHpjRJySmd/rcf030RkK/AR4RWae3u3giFiLslTs44G9uhzylFrb9dltp1TP9bK8T/1ngW9R9tHuOqMvInanDCr3rqrWAL4QEXfPzGb4188LWTHb8fPAqzLz0kZb9wM+AuxSq/5ARPw8M89s0dYk1L8/w/pvOr9341jm/Z6sWDL968BrM/Oc+gERsSHwHuCgWvUrI+Ij/ZZMjohdKL9j604A/r35/YqITSk/Ey8CHkTZQ35o3ZZAbuG0Rnl3DAYkSZIkzYx5Xm/meV3MgdysqznQL/O87pb3qTfPGx3zvOIEzPMkSVqleaPP9NQ/AC/PzD9NrCc9RMQBwEsb1V/JzMsHnHp2o9wMQQbpdvwGPY5thghXAT+kfAAcxsOBX0bEfpk5KPBYSUQsbXtOpbnvuabvnEZ5dcr74pLmgdV7+tm1qouAvXoNgjLzeuDdEXEyZY/gxZSw6QMRsW1zVlpEBPCYWtV5wCMz88Zena+e+wHwgyqIaD7/r720y+X/5YZp7F99InDHzPznoAMz8+SI2Af4JCtesztTlkY+qkWbU6HAuzPz4B5t/SoiHgR8nxWD2TWBj9bKc1Lbvc4j4tV0hgLLKb+HRm1qyfUjMrPrjJ7MvAp4dhUQ7FdVLwKeC/xXn2sfSeff/q8CT+4WxlV/L/4tIi4AjgA2afW/mJnfNcrNGaPTFhGbAZu2PO2uo2pfkiRJ0sSY5/Vmnqc2zPOGZ543YuZ5gHnesMzzJEkLmjf6tFTtb1sf6F40qb7URcQalA9tuwDPAvZvHHI5cMgQlzqxUb5rROw+zBKhEfFA4C5dnrpdj1OWNMqvY8WgO4EvUpaXPL8q350yW+SprJgdtDHwjYjYJTPbfi/cP3zyrupStymNYKAatL+xVnUL8NhhBteZ+X8R8UbKwAbgbsDjKAOiuk2AdWvlb/ULBbq0c/2wx07HEKFe8/iMiH8HHgVsVlU/jXbBAJSlffv+7sjMf0bEgZRgcWp58QdGxH0y8zct25uTIuLZdM6cuR54TGaeMaYmfw68dojjXs+KYADgIfQIBqrZWrvWqi4DntNnxh0AmfnOiHgoKy+xPU6XUn7Opz6nbNPn2LZeDBw6wutJkiRJmuPM8/r2wTxPbZnnDX9987wJMs8zz5MkaSFr7hGrwZY2yrM++ycisvmg7MX9Z8oSoM1Q4GJg38xcaVZFU3VH/I8b1e+OiEUD+rQ68O4eTw8bDEyFAtcA+2TmUzPza5n5+8w8MzO/nplPA/YB6su6bkyZ6aD5p1swsNJMGsqStTvWysdkZnOGQD9HAvVlcR87xDmbDT5kbqtmC9WXNd41Itr+3j+sOVuqR1t/Aj7eqD6oZVtzUkQ8FvifWtUtwJMy8+djbPatQ77uZ9K5lPrOfQ5/aqP8ocy8esj+vHnI40ai+r/Xl1HetFoKXpIkSZKmY2mjbJ6HeZ6mzTxvjMzzRsM8DzDPkyRpQfNGn/aag4VuA5u5YhnwBmCHzDytxXlvbZR3B/632r94JRGxGDiG3ksx9vpw2+v998zMPL5X56rnnt6o3qfax1jzS7f3QHape1ij/MU2jVQD5F/WqrotQfv36jFl/4iY00vVTomIxRGxaURsFRFL6w86Q7Tb0W6p6qsoS/gO63ON8gNbnDsnVcsYf5GyjC6U9+fzMvPbY2z2esp+8sOqL9G+TkSs1+O4BzTKXxq2gSoE+XOLPo1C8+9r2+V5JUmSJGmKeV6DeZ5mwDxvBMzzxsc8rzDPkyRpYXPrrvbWaZTHurznDG0AXJmZ17Y5KTOPj4gP0Lkn+FOB3SLiSMoSlFdS9p3dE3gJK2ZG3QBcR5mVM2V5j6a69ev4zPzGEH38ZkT8mDIbaMrTgYFLEteuEYOPWlk12HKZ4NFY0qWu289Uc4B55TT2ZL+m9vXSiFitPsOiWhr3C8C/V1VrA8dHxFeALwA/avuzNC4RsStl2evdgR3oXH58kA0pswKHceqgZWAbTqf8DlhclXeKiDUz86YW15gzIuJewDdZ8f8BeFVmfmbMTf+x5WvWHEBvQPffr/eqfb08M//Qsl+/ZrjZc6PS3L9+VDOAPgx8ueU5dwUG/m2SJEmSNGeZ55nnLcU8b1SWdKkzzxvAPG92mOetxDxPkqQFyht92mu+Zm0+NI/K1o3yasD6lAHCAazY33VD4MMRsXVmDrOfd93BlLut60tDbg28q885twHPqI6ZbjBw9PBd5Gg6g4G9WpyruWHDLnXd9q6+U6P8ixm2uxollLiyUX8Y8P8ogwAosz6eXD1ujYjTKOHTz4GfZuZlzKKI2JGybPGDZnCZNiHCeW0unJm3RMQyYLuqahHld8Gsvk6jEBF3ocx+qr9e78jMXkuaj1LbmaU3N8prNA+olsmtBxzDhkN10zlnJpp/X1f6f01HZv4N+FubcyKmlSNLkiRJmjvM83ozz1Nb5nktmOfNHvO8rszzJElaoNy6q73m7IRu+w+PVWYuazwuyMzTMvOYzHwc8Bg69y9+VUQ8u2UbN2fmgcB/svLgqZsLKYP0Y4HNG8/9tcc5y7vUtRnwNY/dNvz0Nt/co1G+me6DyI271M3USnvNZ+YVlFk1x3Y5fhGwC2WG0BeASyPi/yLiuRExkgFLPxHxQOD/mFkoAO1+718z+JCVNPeI3mga15ioiLg98APgDrXqT2Xma2apCwP38p6GJY3yP7odNMB03g8z0fz7et0sty9JkiRp4TDP6848T9Nhnjck87zZY57Xk3meJEkLlDf6tNf8YDSqpQdHptpr9oWN6g9ExFbTuNb7KDN/XgR8FbiA8oHyhurrb1Nm/eyQmSdQZk6sWbvEHzJzeY/Ld5td0GamQHN/2UV0XzpWc9dujfLvM/PWLset2aVuprqGSJl5eWbuD9wTOAI4g+77jAclRPgEcEa1LOxYRMT6lP2X62HG1cDHKLP07g3cnvL7aFFmxtQDOHwGTXf7f0/iGrOmeq2/z4pZYFCWeH3BZHo0Mjc2ytP5mRrHz2E/zb+vsx1MSJIkSVo4zPPM8zQ65nnDdNQ8b9aY5/VlnidJ0gLl1l3tXdIoN2e7zAmZeXRE7E+ZDQSwHvBuYP9pXOsaygDkY0McvnujfEqfY8/sUtf88NpPt2MXd6nTHBQRa7LybJaf9zj878AW1dc3AOtk5lgHnJn5e+DVwKsjYgmwK7AHZUnp3en8/bkt8OOIuF9mjmO/9xfR+bvmFOAxmdltWeSm9WfQbptlgXud03bZ2omJiMWUPbx3rlX/FHhKj8BqPml+H7otsz3IbM/m2qL29Y20XJ5XkiRJkmrM8/ozz9NQzPNaMc+bBeZ5A5nnSZK0QLmiT3vL6LyjfcsJ9WMYr6RzT9QnRsT9x9zmPo3yCX2O/V2XuiUt2up27BUtztdkHUjZN77umz2OrS8XvRi481h61ENmLs/M4zLzjZn5IMpsm1fRuaztxsCbx9SF/erdAQ4cMhSAzsFVW9u0OTgiVgeW1qpuZbilwicuIhZRlnB+cK36dOCxmXlD97PmjyrYuLRWdZeIWKflZe45wi71FRHr0RlqXTTuMFCSJEnSgrYM87x+zPM0LPO84ZnnjZl53lDM8yRJWqC80ael6gPiubWqO0/jw9WsyMzzgU83qsc1cCEibkfnDKNrgS/2Oj4z/0jnawmwQ4smd2yUL8/Mm1qcrwmJiLUps2vq/gj8pMcp/9co7zvyTrWQmVdm5ruAh9MZFD42Isbxe/Xuta/PzswLWpzbnJXXxi7VYH9Y96JzFt7vMrPNrL5J+hidAcwFwCMys7lH+Xz2i9rXq9EZgvQVERtRvr+zZftG+bRZbFuSJEnSAmOe15t5noZlnteaed74mef1YZ4nSdLC5o0+0/Or2tersfIAdS55G3BzrbxvROwxprZeSucerJ/LzH8MOOfYRvkRLdprHvuzFudqsj4KbNeoe3Nm3tbj+OMa5eeNvkvtZeYpwO9rVbcDNulxeH2AvFbLppbUvh56oBoRD2Fms6U2pN3P5IGNcq+lm+eUiHgH8Nxa1V+AfTPzLxPq0rj8qFF+fotzn8Xs7um9U6P8y1lsW5IkSdLCZJ7XnXmehmWe186S2tfmeSNmnjcU8zxJkhYwb/SZnhMb5XEvnzttmbkMOLpRPfJZQBGxHfD6WtW1lFBikKMpy4FOeXZEDNxrtjrmuY3qbw/RniYoItaNiM8Az2w89RNWfp/WfY8yQ2jK/SPiOaPu3zTd0ij3mvGyvPb15j2O6aW+H/Pdh5llFBFrAP/dsp1uDhuyvS2BFzSqPzOC9scqIl4BHFKrupoy8+ePPU6Zz44B6mHt4yPi4YNOiog7Am8cW6+6a/5dPWGW25ckSZK08JjnNZjnaRjmef9injdHmOeZ50mSJG/0ma7vNsp7T6QXw3srnYOXvSNir34ntFneMyK2pdxZvnat+rWZedGgczPzXOBTtaqNgU/2a7967pPVsVMupnzoXRAi4rCIyNrjhEn3aSYiYnE1kP8NK4cCf6DsUd1zv97MvIWVByYfiYgnTKMvD42Iu3Sp3zkiHl/t7TzstXaic/nTy/osDXt27eutqp+bYZ1e+3oTBsyAqv4PH2M0oeUuwDsGtLc28DlgvVr1SZl56gjaH5uIeCbwrlrVDZQ9vE/vccq8Vs3IfH+j+ksR0fNvWEQsBX5I5yy02VDv018ovzskSZIkaSbM8zqPNc8bMfO8TuZ55nnjYJ4HmOdJkiS80WdaMvMy4JRa1d4t972dVZl5Ie1nAR0VEcdExKOrD/0riYgtIuIw4LfAHWtPfQc4skUX3whcXis/Hvhet4FTRNydEsw8vladwMvdz3vWrR4RS7s87hERu0fEIyPi1RHxVeBSSpizTeMavwH2ysy/DmosMz9HZ4i0JnBs9T7dpdd5EbEoIu4dEYdGxFmUQU635W+XAl8F/hgRR0TEA6pZNN2uuXpE7E9Zgrj+e7TfjJfjG+VvRMRBVSCxdeM1XNI49ouN8oci4qURsdLSqxFxP8qMqmdXVZc3j2lhaubRwdXrfMfmAVV7PwP2rFXfBLxoBu2OXUTcg/KejFr1a4CLe7yvez4m8h+YvjcDZ9TK6wM/jogvRcT+EbFTRGwXEftGxPuAMyn7a98AfGM2OhgRW9G5j/03+gWHkiRJkjQM87zCPG+VZ55nnmeeZ543cuZ5kiTNvjk7mJ0HjgZ2rb7ekHK38g8n152B3kqZeTH1PX9gRDwsM3v1eTHwRMoevTdHxNnAMsoykUsoA6sd6fxQDfAD4EltPsRl5l8i4tGUgdM6VfVDgXMi4nTgfMrg/+7Azl0u8abM/Nqw7Wlk7ghcOM1zb6DMvHhLZvZaGrebF1F+3urB0IHAgRFxOWWmzBXAbZQBzxaUQc3iFm1sBbyqetxUhQmXUpbqXQTcAbg3sEHjvHOAt/S57ieAgyn7fgNsC3y6x7GHA4fVyp8BXsqKfY7XoMzkOCwiTqH8nzeg/EwurZ13ImVf7foy3G18jLKn986U1/kpEfEr4CJKMLN99f9oemlm/r5L/VyyGSv/DXxf9Wir+XtwzsrMmyLiUZTw6G5VdQAHVI+upwEvofze369RPw5PbJTn/JLRkiRJkuYN8zzzvFWdeV4n87wVzPPmKPM8SZLUjTf6TN8XKAObqdkxBzCHg4HMvCAiPgscVKt+E8P1eQ3KgGSnPsfcArwTeGO1LGvb/v0yIv4fJXDZqvbUvehcSrXuZuBlmfmRtu3NA82B7FVdj5p//khZkvkjmfmXtidn5s0R8UTKoP1wOl+nTSmB0iA3A9cN2eSalEHxzgOOOwl4Qmb2vG5m/jkinkxZEnfJkO1PnXtLRDyGMpi7a+2pDSkD925+RBlgvaJNWw03Ao+kzHS6J2W2066sCEWbbqaEAh+bQZsas8y8JCL2BD5MZ8jWzRXAszLzOxHRXPL5H91OGIEn1b4+JzNPHlM7kiRJklY95nmdzPNGyzyvC/M88zzNnHmeJElqcuuuacrMK+m8K/nJEbFer+PniLcCt9bKu0XEI3sc+wXKIOSGAdf8B2W5zB0z83XTCQWmZOZPKYOPt1NmXPRyHWXmxHYLNBQAeECj/N6J9KK92yiDySuBc4EfAx8BXgjcIzPvlpmHTicUmJLFEcDWlPfKwL3jKe/T71JmMWyemb/qcswPgCdQZur8YZiuUJa4fRqwZ2b+bYi+f48yY+aVVX+WAddSXrdB514M3Af4APDPPof+lvJ6Pzwzrxl03SHavQzYjRIk9vq5vBX4PrBzZn50pm1q/DLzL5n5BMoSzR8GzqLMcrsBuIASLL0QuGtmfqc6bUnjMr32r5+2iNiBzuBpvvzukyRJkjQPmOf9i3neeJjn9WCeZ56nmTPPkyRJdeE2mdNX7S99DitumHphZn58gl0auWrP4J0oy+xuTlmK9xbgb5QPkqdm5s1jaDeA+1NmO2xOWWL175QB28njaHOuiIh1KDN+pvZr/nFmDjOzZZUVEVtTBs2bUmbF3EYJA/5M+Rk9PzNv7X2FrtfcGNiBEkBsTHnv3whcQ3kfnpaZV4zq/9Cyb+tSwqNtKUsaXw38BTg9M4cJNabb7mrA7sBdKMso30AJC346TDCi+S0ifgY8sComsEFmjnQWUER8EPj3qng5cOfMHBRQj10VWPxr+erfnHIS99h++wn2aLTOOvts7rPrHvWqHTPzzEn1R5IkSRon8zzzvHEwz2vPPM88T+Nnnrciz/vticdxj+22mWCPRuusc87j3g9+eL3KPE+SVjFu3TUDmXl+RBwDPKOqenlE/E+b/aznusy8Cfh19ZjNdhM4pXqsah7IilAA4I2T6sh8kZkXMv39xXtd8wrgp9VjTqmWFP4hs7y8eGbeRlnW+KTZbFeTV4VR96lVnTeGUGAjOpejf/tcCAUkSZIkLSzmeWNt1zxvBfO8AczzZq1d87xVlHmeJEkLm1t3zdwbgZuqr7dn8P6o0iAPqX19XGb+38R6IknFsyiz4KaMY5/tlwNTS+ZfDBw5hjYkSZIkCczzNHrmeZLmGvM8SZIWMG/0maHMXAa8r1Z1aLUcpjRd9WDA2T+SJioitgTe3Kg+esRtbAz8R63qtZl54yjbkCRJkqQp5nkaA/M8SXOGeZ4kSQufA9jReBPlbmUo+18/a4J90TwWEeuzYjnN72TmLyfZH0kLT0Q8MSLeFhGbDnHsvSnLXW9Uqz49M48fcbfeCCypvj4+Mz834utLkiRJUpN5nkbCPE/SuJnnSZKkptUn3YGFIDOvi4gDgYdVVWtMsj+avzLzGvy5lDRetwNeCxwcEd8HfgycDvwNuIUSAtwTeDTwGCBq597EiMPviFgE/BU4vKo6ZpTXlyRJkqRuzPM0KuZ5kmaBeZ4kSergAGREMvMk4KRJ90OSpCGtQRn4P2bI468HnpmZp4+yE5l5K/C2UV5TkiRJkoZhnidJmmfM8yRJEuDWXZIkrWqWA7e2POck4EGZ+ZXRd0eSJEmSJElSH8sxz5MkSTWu6CNJ0iokM78eEbcHHgHsQVnWdyvKEr+LKTN9rgQuAn4GfLea5SpJkiRJkiRplpnnSZKkJm/0kSRpFZOZV1D2znb/bEmSJEmSJGmOM8+TJEl1bt0lSZIkSZIkSZIkSZIkzQPe6CNJkiRJkiRJkiRJkiTNA27dJUmS1ELccC1x/dWT7sbIxA3XTroLkiRJkiRJ0tjEjf9gtYWU5934j0l3QZI0Ya7oI0mSJEmSJEmSJEmSJM0D3ugjSZIkSZIkSZIkSZIkzQPe6CNJkiRJkiRJkiRJkiTNA97oI0mSJEmSJEmSJEmSJM0D3ugjSZIkSZIkSZIkSZIkzQPe6CNJkiRJkiRJkiRJkiTNA97oI0mSJEmSJEmSJEmSJM0D3ugjSZIkSZIkSZIkSZIkzQPe6CNJkiRJkiRJkiRJkiTNA97oI0mSJEmSJEmSJEmSJM0D3ugjSZIkSZIkSZIkSZIkzQPe6CNJkiRJkiRJkiRJkiTNA97oMyIR8emIyOrxhUn3Zxwi4o4RsX9EvCQiXhcRL4iIR0fEpmNsc/OIeExEvDQiXh8Rr67afWhEbDaudqVVUUQcVvs9lhGx1xjbWlZrZ9mAYw9q9OugUV17XCLiqEafl06iH/NBRCyNiBuq1+nWiNhl0n2SJEmStGowzxtbm+Z50iwxzxsd87zhmedJkjR5q0+6AwtBROwBPKsq3gS8dsDxJwAProonZuZefY5dClw4RDduBq4BrgLOBE4FvpKZZw9xbr++rgY8FTgE2KnHYbdGxE+AIzLzRzNpr2pzEfBM4MXAfQccewHwPeANmbm8z3FL6f46HpOZT2/Zv+a1zszMHVsc/+zMPKpNm+PQtl8RcRhw6IDL3gLcCPwD+BtwEXAu8GvgZ5n55+n3WNJ8UYVKx9eq9s7ME7odm5nLIuJDwCspNyB/OCJ2z8zbxt1PSZIkSasu8zzzPPO8fzHPk2SeJ0nSPOOKPjNUDZyPBKKq+khmDjOQH7U1gI2BuwH7AW8CzoqIn0TEttO5YETcAfgZ8Fl6hwIAi4CHAT+MiI9GxFrTaa9qcyfgNOBTDAgFKncBXgLcYZpNHhgRO0/zXK1sdWBdyvdjJ+AxwMHAF4A/RcTJEfHCiFh7gn2cdRGxV2M2yGGT7pM0x7yVEm4D3B84aHJdkSRJkrTQmecB5nlawTyvC/M8aSDzPEmSJsgbfWbuQOBe1dc3Ae+cYF+62Rs4PSL2bXNSRGwB/BJ4QOOp5cBxwOerf69uPP9C4OiICFqKiEcCJwPN2TRXAT8Fvlw9jgcub3v9Xs0Cbx/RtdRfALsBHwUuiIhnTLg/kuaIzLyKErJPOSwiFk+qP5IkSZIWPPO8TuZ56sU8T1JX5nmSJE2WW3fNQESsQZlpM+XozLx0FpreukvdmpQZQLtQlsm9X+25tYCvRsTOmfmHQRev/l/HAneqVV9LWe73E5l5c+PY5wNHUGZ+ADyJsrzrG4f9D1XLJR8L1D8I/gp4PXB8Zt7S5ZztKLOdnjtsOz08PCL2zszjBx+qmmMps3vqAlgfWAJsQnk/7go8kPIenXIHSoD0CMoSwzeNvbeS5rr3AP9J+TtwJ8py7++ZaI8kSZIkLTjmeeZ5qzjzPEmjZJ4nSdKEeKPPzDyFzkH6kb0OHKXMXNbn6ZOBD0XEwXTORlqXspTik4do4jmUmRpTbgT2zcyTu/TlZsr+q78DfsyKwd8hEfGpAX0FICLWpSwnXA8F3gMcnJnZ67zMPAc4JyKOYOarU72DsrykhnftEN/fYwEi4vbAiygf+jeoPX8gcLuIeJz7965aMnPpfLx2iz4chMvVtpKZf4+IL1HCbYBXRMQH62G0JEmSJI2AeZ553qrMPE/TZp6nJvM8SZImx627ZuaVta9PyczTJtWRpsx8F3BUo/oJEXG7fudVS/S+ulH9lm6hQKO9nwNvq1WtRefsqH7+G1haKx+dma/sFwo02s7MvHXItqacUz2m3C8iDmh5DQ0pM/+amYcD9wZ+3Xj6McBhs94pSXPRR2tf3xF46qQ6IkmSJGnBMs9b0Z55nnoyz5M0JPM8SZImwBt9pikidmfFXt5QZrDMNe9tlFcHHjTgnB3pnNV0A/ChIdv7YHX8lAMiYr1+J0TElpTlHKdcTpklMm63Aq9r1L01Ilzlaowy80JgL+CsxlOviYhtZ79HkuaSKoS+oFb1b5PqiyRJkqSFxzyvK/M89WWeJ6kf8zxJkibDQdD0HVT7+jaqJU3nmDOAfwLr1Oru1OPYKc3g4JTMXD5MY5l5ZUT8CtizqloMPAr4Yp/TngcsqpU/mplXDtPeTGXm1yLiZGD3quruVX8+2vsszVRmXhcRTwBOp8wUA1iDEtQ8q+31qvBpD2ALYFNK6PM34GzgNzNZQri69r2A7Sj7lK9NCb+uAS4GzsvMC3peYIwi4k7A9sBdKPuoLwKuovzfT8nMS8fQ5tqUn+8tgc2q9i4CTsjMG/qdq5mJiJ2AHSizYpLyfT45M/8wgmtvB+wCbA7cAlwKnJmZzQBvtnyZFTNRd4uIbTPz3An1RZIkSdLCclDta/M8zPM0HPO80TDPW7WY55nnSZI0Tt7oMw0RsQioLwt7amZeNqn+9JKZGRHL6QwGNhpw2paN8u9bNnsGK4IBGBwMPLdR/nTL9mbq1cBPa+VDI+J/M/O6We7HKiUzz42IzwHPrlU/OSL+IzOvGeYaEfFwyvfvgZRgoZu/R8QngXdk5lXD9i8idgb+i/L+XWvAsZcDPwI+lpknNp7rtVz1oRFxaJ/L7p2ZJzSutSbwcOCJwEMYEPJFxHnA+4FPzXTQHhFbUJZjfgrQbbnwayPis8Drhw32ImIZsFVVvGiU+3APe+0+3582TszMvbpc+yg6g66tM3NZj37sBRxfqzo8Mw+rnnsWcDBldma3c08HXpOZ32/b8YjYHzgcuEeP539D+dn5UlU+AXjw1POZGW3bHNI36Vxy/kCg38+LJEmSJA1knteXeZ4GMs8zzzPP6zh2L8zz6szzJEmaZW7dNT0PADaslY/vdeAcsH6jPGiA0AwOlrdsr3n8PXsdGBF3pzOI+GO1FOysycyfAd+pVd2B2VlqWGXQWrcWZeDbV0RsEhE/BL4P7E3vUABgE8oA4/yIGLTM9dT1DwFOBZ7AgFCgsill3+HnD3P9GXgXZcD0LAbP5APYBjgS+EVE3GW6jUbEAyiB3/PpHgoArAe8CDgnInadbltaISLWjYgvA0fRIxSo3Av4XvW+Hfbaa0TEFykzbbqGApX7AF+MiI9Vgfhs+RVQD2cfPYttS5IkSVq4zPN6ax5vnqdezPPaMc9bhZjnmedJkjSbXNFneh7RKP9sIr0YICK2oXxgrxu0LOlNjfIwA6N+x28XEav1WG71/o3yyVNfRMQOwDOAfSmDoPWBK4A/UYKYr2bmKS371strgP/HihvfXhURH83Mv4/o+uoiM0+PiL9RloydsgdlsNJVRNwNOI6yvG3dPyiD+b9SlrxdShnUTH1PNwZ+GBGPzczj+lz/acA7ml0FzqT87FxDeY9vAGwL3BkY1yyIpuaNmf+kLGd8WdWvNSnB1r3oHMDfCzg+Iu49jWW07wa8k7LMMcD1wC8or/MSymtc//5tCvwgIvbJzF+3bEsrrAZ8DnhsVb6V8v6+pPr6bsC96XzvvSMizsjM7/W7cEQE8JXatafcShmQX0x5j29DWUoa4AXArP0+zMybq2XYH1pV3TsiNsvMv81WHyRJkiQtSOZ5vZnnaSjmea2Z5606zPPM8yRJmlXe6DM9uzXKp7U5uduykGPyokb5FuCkAedc0Shv3rLN5vGLKYOnZV2OvW+jfHZErAu8HXgJKw+4Nq8e9wMOiYjjgBfPdE/lzPx9RPwvK5blXB94PSOaCVQt7zlbg8ehzZF+/YLOAcq9eh0YEesAX6MzFDiX8r36embe2jh+c8oyplMzc9YEPhsRO3fb7zoiVgOOaFR/CHhrZv6lR582ooRXT6UMrJq2rv7dDfh8rf79wPu6XbPStT3gj8DRlFlrv+0WuEXEGsDjKD9HU6/VnYEPU5bqbeMISgBwE/Bm4L31ZbCrWSH7U/4/t6+q1wc+FxH3yszrW7Y327YefEiHtYFjWTFgBvjz6LrzL/9Gmb12KyWYeVdmdvxujohtKe+FesD6gYjYJjP7LWH8UlYOBT4CHJqZlzfa2JHyM/Bg4LWUPdyHUi1VPZPfL6exIhgIys/QN2dwPUmSJEkyz+vNPG/l6y9j8rnZSuZIv8zzujPPmx3meYV5niRJqzhv9JmeXWpfL8/MP02sJz1ExAGUD4B1X2l+8Ovi7Ea5GYIM0u34DXoc2wwRrgJ+COw+ZFsPB34ZEftl5qDAY5A3UgZNUzOYXhwR7++1B69G5hw6Byl37nPsO+lc8vR7wBN7DT4z8zLgBRFxDvDuqnoTygD3OV1OuS+wRa38mcz8j36dr2bUfAH4QkSs3eX5ZQARsbTx1PJpvLeOAF7aYzZdvc2bgS9HxI+AnwA7V08dEBGvaxmkbUgZnD45M7/epa1bKUvB/oYyE3IqHLg78DrKvuhzVpvvQUSsDnyVzlDgt6wcwI7CVCjwuMz8drcDMvPciHgY8HtWLP18N8p+7z/udk5EbAy8rVH9isx8b482fh8RD6WEIY9l5aXgx+l3jfL9GVEwEBGbUWartXHXUbQtSZIkaaLM83ozz1Mb5nnDM88bMfM8wDxvWOZ5kqQFrbl0pAaIiDvQOdC9aFJ9qav2aN08Ih5d7QP7JcqSp1MuB4bZ8/XERvmuETHUQD0iHsjKS7BC732AlzTKr2NFKJCUAdcTKPuC7wg8nrL8Zf3u9o2Bb0TEVsP0sZfMvJiy//GUNSkDSI1Xc0ZB1w/rEbEF8Lxa1TJg/2FmmGTme4Dv1qqeVv0cNzXfQ18ZdO1GO2Od7ZKZFw8KBRrHX0Xna7YaZaZSWx/sFgo02jqfMmul7kUR0Xap8Lnsf4DH1Mp/AB6RmdeMqb139AoFplRtN5emfkifU54DrFMrf69XKFBr4xbgIMryzrOp+bd1mxFe+8WUQKXN4xsjbF+SJEnSLDPP69sH8zy1ZZ43/PXN8ybLPG92medJkjSLvNGnvaWN8qzP/omIbD4oS3H+GfgWZenNuouBfTPzkkHXrpY0bd49/u5qSc9+fVqdFbMsmoYNBras/r0G2Cczn5qZX8vM32fmmZn59cx8GrAPZQ/nKRsDn+zXvyG9Fbi6Vj4wInYawXXVWzMYWGkWTeVFlLBmyuGZ+c8W7dTfm2sCjxjinM0GHzK3ZeapdA6wHtDyEjcBbxmyra8Bv6lVbQI8qmV7c1JEvJMyOJ5yGeV36rj2mL6e3r9Pm5rhwb37HNsMhob93l5FWfJ3NjX/ti6d5fYlSZIkLSxLG2XzPMzzNG3meWNknjca5nnmeZIkLXTe6NNec7Aw9B6nE7AMeAOwQ2ae1uK8tzbKuwP/2+tu/ohYDBxD596ydb1mLfR6/z0zM4/v1bnquac3qvcZdqZSn+teSefd9KtR9kXW+DTfA732In5Y7etbaTk7B/g5ZU/7KXt2OeacRvm1PWYKzSlRrFfNAFzafFBm/03ZvsdlejmuuZf0AJ9rlB/Ysr05JyIOAQ6uVS2nzPy5cIzNnlz9PhooMy8C6iFZ10ArItYF6kHnpZn5fy369KUWx45C82/rvA/qJEmSJE2UeV6DeZ5mwDxvhszzxss871/M8yRJWsBWn3QH5qF1GuWxLu85QxsAV2bmtW1OyszjI+IDdO4J/lRgt4g4kjLIupKyv+uewEtYcXf2DcB1lFk5U5b3aKpbv47PzIFLKmbmNyPix5TZQFOeDpw86NwB3g/8Oyv2dv5/EbFXZp4ww+uquyWN8ko/T1XwtEut6hJgk4jYpGVbyymzUqDL/ryZeUZEnEFZWhrK/sjnRMRRlCDiF9WypxMVEWsC+1KWwb4PsB0r9qIfZMOWzZ0yw+Pv1/L8OSUiDqIzLLweeExmNvebHrWzWh6/nBV/mzboccyOdC7//uuWbZxPmSHZ6/qj1pzht+4Ir/1h4Mstz7krLvcrSZIkzWfmeeZ5Gp0ljbJ53gDmebPHPK+DeZ55niRpAfNGn/aar9kkBgpbN8qrAesDOwAHAPtV9RsCH46IrTNzmP286w6m7K9cXxpya+Bdfc65DXhGdcx0g4Gjh+8iR9MZDOzV4tyuMvOfEXE48LFa9duB3WZ6bXXVHKhe3uWYOwBr1MpLgZnOvtioR/0LgOOBxVV5A+Bl1eO6iDiFEj79HDgpM//R9SpjEhH7Ae9l5d8Bw2o7qDuv5fHnN8rzdtZGRDyWso/3lFuAJ2fmz2eh+bYzS2+ufb1Gj2OaQVpzz+y+MjMj4hJmLxho/m3t9f9qrVqiudUyzRExquYlSZIkTYZ5Xm/meWrLPK8F87zZY57XyTzPPE+StLC5dVd7zRkKvfYgHpvMXNZ4XJCZp2XmMZn5OOAxlJk4U14VEc9u2cbNmXkg8J+U2T6DXEgZpB8LbN547q89zlnepe4Xw/axy7Hbxmg+vX0SOLdW3jUinjiC62pl92iUuw1WNu5SN1Nd95nPzF8AewC/7fL0usBDgNcD3wMuj4ivR8RDx9C/lUTEy4GvM/1QAKDtz8c1LY+/ulHuFcDMaRGxJ/BFVgTBCTwvM781S13otTz6TCxplKcTarV9P8xE82/rdbPYtiRJkqSFxzyvO/M8TYd53pDM82aPeV5P5nmSJC1Q3ujTXvOD0SiXHxyJzPw28MJG9QciYqtpXOt9lIHIi4CvAhdQPlDeUH39bcqsnx2q5XDvCqxZu8QfMnN5j8t3m11wWYvu/blRXsTKH35by8xbgdc1qt8WEa6ANXq7NsqndzlmzS51M9VzgJyZv6EsLbwv8Gng4h6HrkWZbffDiPh2RIwjwAAgInYF3t2oXga8DXg0JWDZiDKYWi0zY+oBnDiDpnvtsT7s8W3Pn7iI2An4FitmgQEckpmfmVCXRuXGRnk6P1fj+Fnspfm3dTZDCUmSJEkLj3meeZ5GxzxvCOZ5s8c8ry/zPEmSFigHOu1d0ig3Z7vMCZl5dETsT5kNBLAeZWCx/zSudQ1l6duPDToW2L1R7rcn8Jld6pofXvvpduziLnWtZeZXq2Vdpwau2wDPZbjXQEOIiHuz8vKj3ZZR/Xuj/IPMfPh4elVkZgI/rB5ExJ0oyz3vSZkFtEPjlEcB342IPca07/ehdN6Y+XHgJUO2tf4M2m27rOuSRrntkrUTFRFbA9+n8/99RGb2W+J8vmh+L9ru7w6zO6Nri0a5+bdXkiRJktowz+vPPE9DMc9rxTxvFpjnDWSeJ0nSAuWKPu0to/Ou9i0n1I9hvJLOfVGfGBH3H3Ob+zTKJ/Q59ndd6pa0aKvbsVe0OH+QVzfKh0bEOiO8/qruZY3yDcAPuhzXXCp6m/F0p7fMvCQzYHjl5gABAABJREFUv5yZL83MHas+HEnnkqz3Bw4addsRsS6dP1cXMHwoADMLL9u+1ndvlFvtmzxJEXF7ShBUf70+nZnN3wPzVXMZ7Xu2Obl6Hy4dWW8Gu2OjfOEsti1JkiRp4VmGeV4/5nkalnneEMzzZod5Xn/meZIkLWze6NNSZt5A537Pd56rg8XMPJ+yVGndm8fVXkTcjs4ZRtdS9sXtKjP/SOdrCSvPrOhnx0b58sy8qcX5fWXmicB3a1WbAy8f1fVXZRGxHfDURvXnM/Pa5rHVDLT6bLGlEdEcgM6qzDw/M/8deE3jqcf3OmUGzW1F5xKr3x82FIiIuwB3mEHbu7U8vrl0869m0PasiYj1KTN/7lqr/ibw/Mn0aPQy8w90zqbbOSKWtLjEXszuZ4btG+XTZrFtSZIkSQuMeV5v5nkalnleK+Z5Y2aeN5S9MM+TJGnB8kaf6al/2F2NlQeoc8nbgJtr5X0jYo8xtfVSOvdh/Vxm/mPAOcc2yo9o0V7z2J+1OHdYr6VzlschwNj2bl4VVDMJjqVzsHsT8N99TjuuUZ4rA7ZPNspb9ziuuSz1Wi3aWNIoX93i3INaHNvNvi33Kj+wUe62dPOcEhGLKSHAzrXqnwFPzsxbJ9Kp8flx7eu1gGe2OPcFI+7LIDs1yr+c5fYlSZIkLTzmed2Z52kg8zzAPG/OMM8bmnmeJEkLmDf6TM+JjfK4l8+dtsxcBhzdqB75LKBqRsfra1XXUkKJQY4G6h++nx0RA/earY55bqP620O010pm/g44pla1AZ3/T7VQ7Zl8AnCPxlNvq2as9fIROpet/o+IaDNbbFyaM3F67Um/vFFus/xucy/m7YY5KSK2ooR1M7Em8IYh23s8cJ9a1d+B78yw/bGKiEXA54EH16pPBx5TzfZcaD7aKB8aEQNniEXEI4HHjqdLPdX/ri7HGUCSJEmSZs48r8E8T8Mwz/sX87w5wDzPPE+SJBXe6DM9322U955IL4b3VjoHMHtHxF79ToiI1Ye9eERsC/wIWLtW/drMbO4hu5LMPBf4VK1qY+CT/dqvnvsknTNxLqZzAD9K/0XngK/Xcq4jExEnRETWHoeNu81xiojbR8R/Ab8B7tt4+hsMCKuqZUrry1YvBr4bEc2AYVA/1oqIg3o8t19E3K/N9Vh5BsXZPY67gDLLacreEbHGkG38kRK0TXl0RPSddRgRmwBfpQRZM/UfEbHfgPbuBny4Uf2xzOwVlMwVHwMeVytfADwiM9vMspo3MvMEOmdKbgT8KCLu3OuciNiHPku2j0NEbEHnfvLHLcDZWJIkSZJmn3le57HmeSNmntfJPM88b0zM88zzJEkS3ugzLZl5GXBKrWrvNgPp2ZaZF9J+FtBREXFMRDw6ItbudkBEbFENWH8L3LH21HeAI1t08Y3A5bXy44HvVYFDs827U4KZ+uA8gZePcj/vuirgaA56BOtFxNLGY+uI2Cki9oyIJ0TEWyPiR5Tg5k2svGzt/wJPyszbmhfv4hXA72rlOwO/rtq4U6+TImLtiHhoRHwAuISV97mfsjfwy4j4VUQcEhHbRUT0uObtIuI1wHsaT32m2/HVe/OkRt+/WYUR9+jyOi5unPv12rlrAMdFxErLYkfEooh4ImU58vtQfjau6PH/HcZVwCLgSxHx+mqZ5mZ7T6Is6VufSfIHhpsBODER8QI6ZxFeS1nOdnGX70e/x0z2TJ+EZ/P/2bvvMMmKev/j7y85s0QFERaVJIgoKlFdVDBnMGAAzOmqP+M1IWC4Zr0q5oBcA+acQCUIIiIKkvOCIEhckoQFvr8/6gxz+mx3T/dM9/SE9+t5+qFPdZ1TtTM9M10fTlXBLbXjbYGzIuJTEbFX9b7fPiL2jojvAUcBawDnU4K96fC4xvFPpqldSZIkSXOYeV5hnjfvmeeZ55nnmecNg3meJEnTbMYOZmeBw4GdqufrUAYVR42uOxP6AGW2wtj3fPeI2DMzO/V5FeDZlD16l0bE2cBi4CbK4G5Tyl7mzYHTkZSBXvbascy8MiKeAhwNrFYVPw44JyJOo3wgTWALWvfdHXNIZv641/Ym6QOUQcRaQ25nNnl29ZiMK4C3ZmbPs7Yy8+bqfXIk48vdrgq8E3hnRFwEnENZFnQFyuyXhcADKIPbXj2senwYuDEizqAEVzdRfi42pbwPV2qc983MbO49XvcJWmcLPoHOe9jvQVkSecxBlJkqa1THG1PCs0sowdx/gPWBh1N+H435ILA7rUvZ9uO/gY9Qvpbvp3yd/wz8uyrbEbhX45wbgX0z8z+TbHO6bNw4XoMyk7FfxwKLptybaZKZF0aZ0fUzxn/frg68oXq0czOwN/Dp4fcQqrbG3IDBgCRJkqTBMc8zz5vvzPNamecV5nkzmHmeJElqxxt9Ju8I4GOML2+7DzM4GMjMiyLim8D+teJD6K3PKwLbV49O7gQ+ChyYmc19jnvp318i4omUwGWz2ksPrh7tLAXekJmf77e9SfTv2oj4CGVwNB1WaRw393WejRL4C2Vp5//LzFv7vkDmP6Msx/sF4AWNl+9XPSaypI8m1wJ27aHeF4D/6lYhM38REe8GDqa/oGJsMLc38APGwwEoPyubtT+Lj2bmuyPimH7aajgPeArwc0oguBrwmC71rwaelpknT6FNDVlm/j7Kcu9fofvvdSiz7p6Tmec2ZoPeNIy+RcTawF61ou/M0f3VJUmSJI2GeV4r87zBMs9rdwHzPPM8TZl5niRJanLrrknKzOtoXdbzuRGxRqf6M8QHgPq+qDtHxJM61D0C+AMw0Qeymyj7a2+Xme+cTCgwJjOPAx4EfAi4vEvVWyjLtW49HaFAzScpM1eGqvrwvUOt6HrgsGG3OyB3AbdSZoicDvwC+DjwfOA+mblzZn5pMqHAmMy8OTNfSAmMvklvocm/KHu+70PrkrR1/wO8nLIX9r97uOatwA+BXTLz1b289zPzA5SB2IeA44Arq+tMqJpd9DDKHuidZtjdCfwWeGxmvq2X6/bQ7vGUPh9G697idTdT9sfeOjP/PIh2NVxVePNQ4LnA9yj7mf+HMoPrbOD7wNOBHTPz3Oq0BbVLDGvf8xcBK491E/jfIbUjSZIkaR4yz7uHed6Amed1Z55nnqepM8+TJEl10ceKrGqo9pc+h/Ebpl6ZmV8aYZcGLiJWogwKtgA2oswAuBO4CjgLOCUzlw6h3QAeAdy/and54BrKXsEnDqPNmSIiHkfrzKz3ZOZ0zTyadSJiOcp79IHAupTBy22UAc5i4OzM/OckrrsZsBVlhs0CymDlP8B1lIHT6aNazjYi7kVZwndTyizEqymh1Z8z85ohtrt61e59gQ0oocwlwDFTCXs081X7zN9ImREK8NfMfPgQ2jmdsow8wM8z82mDbmMyImJb4Iyx478f+1seuPWWI+zRYJ11znk85NGPrxdtl5lnjqo/kiRJ0jCZ55nnDYN5Xn/M88zzNHzmea153qlH/oBtt3zACHs0WGeedwE77FXfMc08T5LmG7fumoLMPD8ivkW5YxngjRHx5X72s57pMvMO4K/VYzrbTeCk6jHf1JdSvRbvgO8qM+8GTq0eg7zuJZRB74yTmf+mzD6a7nZvocww0vyzC+OhAMApg24gIvZiPBRIyrLYkiRJkjRQ5nlDbdc8rzDPm4B53rS2a543f5nnSZI0h7l119QdCNxRPd8GeOYI+6K5oR4MfCwzh7J3riT14dWN4xOH0Ma7a8+/n5kDDx8kSZIkqWKep0Ezz5M005jnSZI0h3mjzxRl5mLgU7Wi91ZLj0p9i4g1gR2rw6uBz4ywO5JERDwJ2KdWdDPwowG38VjgkdXhbcA7B3l9SZIkSaozz9MgmedJmmnM8yRJmvscwA7GIcCl1fPtgf1G2BfNbo9ifEu9j1RLq0rSwETEwRHxiohYuYe6zwe+3yj+2iBnJlZh+sdqRR/KzAsHdX1JkiRJ6sA8T4NinidpqMzzJElS0woTV9FEMvOWiNgX2LMqWrFbfamTzPwlEKPuh6Q5bTPKMvUfjogfA8cDZwHXUT4XbAA8Angu4zMSx1wIvGvA/dkE+Gn1uAv4yICvL0mSJEnLMM/ToJjnSZoG5nmSJKmFN/oMSGaeAJww6n5IktSjBcAB1aMXlwBPy8ybB9mJzLwUOGiQ15QkSZKkXpjnSZJmmQWY50mSJNy6S5Kk+eaaPuvfBXwbeERmnjWE/kiSJEmSJEnqzDxPkiS1cEUfSZLmkcx8S0R8AdgL2AXYGrgvsDawEnAjcC1wDnAs8CP32JYkSZIkSZJGwzxPkiQ1eaOPJEnzTGZeAFwAfG7UfZEkSZIkSZLUnXmeJEmqc+suSZIkSZIkSZIkSZIkaRbwRh9JkiRJkiRJkiRJkiRpFnDrLkmSpD7ccfyPuf3iDUfdjYG54/KrRt0FSZIkSZIkaWiWnvUX7rj50lF3Y2CWXnrlqLsgSRoxV/SRJEmSJEmSJEmSJEmSZgFv9JEkSZIkSZIkSZIkSZJmAW/0kSRJkiRJkiRJkiRJkmYBb/SRJEmSJEmSJEmSJEmSZgFv9JEkSZIkSZIkSZIkSZJmAW/0kSRJkiRJkiRJkiRJkmYBb/SRJEmSJEmSJEmSJEmSZgFv9JEkSZIkSZIkSZIkSZJmAW/0kSRJkiRJkiRJkiRJkmYBb/SRJEmSJEmSJEmSJEmSZgFv9JEkSZIkSZIkSZIkSZJmAW/0kSRJkiRJkiRJkiRJkmYBb/SRJEmSJEmSJEmSJEmSZgFv9JlARHw9IrJ6HDHq/gxDRNwnIvaOiNdGxDsj4hUR8ZSI2GCIbW4UEU+NiNdHxLsi4u1Vu4+LiA2H1a6kziJi/9rvu4yI/YfY1jH1tiaou6jRr4MGde1hiYiDGn1eNIp+zAYRsVZEXFX7Wj1j1H2SJEmSNLuZ5w2tTfM8aYYxzxsc87zemedJkjR63ujTRUTsBuxXHd4BvGOC+vUPo8dMUHdh40Njp8cdEXFNRJwfET+JiPdExDYD+LctFxEviIjTgMuA7wOfBT4AfBH4OXBFRBwZEY+bantVm8tHxAERcTLwL+BnwP8C7wc+VLV7FPDviLgwIj4bEQs6XOt3ja/TK/vsywYRcXfjGidO4t/0y8Y13tahXs+DmunU52CrOWhs97gzIm6JiH9HxOkR8euI+FREvDgiNp+mf5akEWvzN27/TnUz80bgkFrRpyJitaF3UpIkSdKcZJ5nntfDdczzzPMkNZjnSZI0u3ijTwcRsRxwKBBV0ecz8+IRdGVFYD3gAcDTKR+ezoqIP0TEVpO5YETcG/gj8E1g+y5Vlwf2BI6KiC9ExMqTaa9qc3vgVOBrwMN6OOV+wGuBe3d4/ejG8R59dmkR49/bMQ+LiDV6vUBELA/sPkG/5pvlgdWADYHtgCcAbwC+AVwUEf+IiLdExNoj7OO0azNIOmzUfZJmmC8AF1XPNwP+e4R9kSRJkjRLmecB5nldmee1ZZ7XhnmeNCHzPEmSRsgbfTrbF3hw9fwO4KMj7Es7ewCnRcRe/ZwUERsDfwF2bby0BPgt8J3qvzc0Xn8lcHhENAfTvbT5JOBEykCx7nrgOMrso+9TBtVX93jZ5gB8UZ/dald/BeCRfVzjocBateMbgb/12Y/55kGUn6VLI+L/VQGcpHkuM+8EPlwrelO47LskSZKk/pnntTLPW5Z5Xv/M8yQtwzxPkqTRWmHUHZiJImJFWpcdPDwzL5+GptsthboSZQbQjsCLgYfXXlsZ+FFE7JCZF0x08erf9UPgvrXim4G3AV/JzKWNui8HPgKsXhU/BzgXOLDXf1CU5ZJ/CKxSKz4ZeBdwdPVhsHnO1pTZTi/tcumTgVtqfbtXRGyTmWf32LVOM4YWAb+e5DWOy8y7ejx3LjgJeF6b8jWBBcC6wA7ATpTApT67ai3gE8CTImKfzFwyzI5KmhUOA94LbEz53f5u4PWj7JAkSZKk2cM8zzxvktcwzyvM8yRNxmGY50mSNBLefd/e82gdpB86HY1m5uI2j/My88TM/GxmPgJ4a+O01Sn7cPfiJcDOtePbgb0y8/P1UKDqy9LM/BxlqdY7ai+9LSIW9tJYRKxOWU64Hgp8AtgpM49qFwpUbZ+TmR8GtgLO71BnKXB8o7in5X6ru8rr+6L/rt9rVBY1jufbMr+3dXjPnp6Zf8zMn2bmwZn5JGAT4M3AFY1rPA44snqvaB7JzEWZGWOP2XLtPvpwUL0PmXnMKPoxm2TmHcBXakUvi4j1R9UfSZIkSbOOeZ55Xi8WNY7N88zz1CPzPDWZ50mSNDre6NPem2vPT8rMU0fVkabM/BjlLum6Z0XEmt3Oq5bofXuj+P2ZeeIE7R0PfLBWtDKts6O6+R9gYe348Mx8c2ZmLydn0W1GzWSX+63Xu5Uyy2nMQyNiLSbQYT/vP/TY/ryTmTdk5icoy2f/tvHyw4HPT3+vJM1AXwbGfu+vCrxmhH2RJEmSNLuY5423Z57Xhnlef8zzJPXIPE+SpBHwRp+GiNiF8b28ocxgmWk+2TheAXjUBOdsR+usptuAz/bY3meq+mP2iYg1OlUGiIhNaP1AdzXw/3psr1eTDQbqs3xOpOwrPvbvW57e9vV+GGVJ2zHXAf/osf15KzOvBp7Mst+7F0XEY0bQJUkzSGZeRvmdPOYVEeFnFUmSJEldmee1ZZ63LPO8STDPk9SNeZ4kSaOxwqg7MAPtX3t+N2U/6pnmdOA/wGq1svt2qDumGRyc1Os+ypl5XUSczPiAeRXK4O67XU57GWWQPeYLmXldL+314RTgRsr+0AAbRMS2mXnmBOctqj0/NjNvj4iTgEfXXv9lH9cYu87dE/ZYZOZdEfE84Axgg9pL72USs6giYhVgF2DT6npBCaIuAP7caUnpPq69PfBAyh7lq1OWyL4J+CdlKerzep3VNkgRca+qX/en7KG+ErAEuAY4JTMvHEKbKwK7AZsBG1F+/i4DjsnMGwfdnsZFxJaU0HoTyt/uqynf59MHcO3NKD9DG1F+b19OeV+fMtVrT9L3GA9w7wPsybIzByVJkiSpbv/ac/M8zPN6uMbYdczzemCeNxjmefOLeZ55niRJw+SNPjXV8q371IpOyczmHsQjl5kZEUtoDQbWneC0TRrHZ/TZ7Om0zoyZKBh4aeP46322N6FqgPnHqi9j9gA6BgPVYGrrWtEx1X+PZTwY6GVf70WN4/m2n/eUZOZVEfFZ4OBa8aMiYqvMPLeXa0TETsC7KPuCr9qh2o0R8R3gkMz8V6/9i4j7A+8BnkXrTK92boiIY4CvZ+ZPG9dZTBlEN+0XEft1ueYBmXlY41rLU96je1P+zVt061REXAZ8DvhcZt4wwb+hq4hYALwbeDGtYc6Y2yPix8DbMvOfPV7zGMZ/5hjk3tu9XrvL96cfl2TmwjbXPogSdo3Zo9O+3hGxELi4VvSNzNy/eu0plPf5zh3OvQg4MDO/1W/HI2IP4EPAIzq8fh7wqcz8fHV8GFB/326emYv7bbcHP6N1+e99MRiQJEmS1IF5Xlfmea0WNY7N8/pgnmeeZ57XUnch5nl15nmSJE0zl89rtSuwTu14Jg/2mvtO39a21rhmcLCkz/aa9R/UqWJEbEFrEHFhZl7cqf4U9bvcb33QfxtwUvX82Fr5DhGxdqcLRMQKLLuf90x+r8xUnwOWNsqeNtFJEbFaRHwb+DPwVDqHAlB+Tl4JnB8Re/fSqYh4ASVc2o+JQwGAtYGnA2/t5fpT8Abg98CrmSAUqGwCfBA4NSIeOtlGI2Ir4FTgzbQPBQBWBp4HnBURE34PNbGIWD4iPgP8nA6hQOV+wDcj4rMR0VO4EsUnKTPu2oYClS2Bz0XETyNi9V77PlVViHderehJLvcrSZIkqQvzvM6a9c3zuvdDEzPP64953jxinmeeJ0nSdHJFn1ZPaBz/cSS9mEC15GNzT+2LJjjtjsbxyn0226y/dUQs12F52+YHzRPHnkTEtsCLgL0oyxOvBVxLWS70aOBHmXkSvWsOyB8dEdFl6dVFted/zszba328g7Jc6vKUpZF/3uEaD6P16381XWYdqb3MvCYiTgUeXiveDfhop3MiYgPgN0BzoHsr8HfgX8BdlPfWw4EVq9dXA74XES/LzK91uf4jgf+jLBdcdx5lWd8bKO+PtYAHUJbZna4BS7OdO4BzKD87Y/3agLIcbD0IXAj8ISJ2nMTyv+sBR1KWUYYS5JxEWQp2DUpAuGmt/hrADyLiWZn5iz7bUqv/BV5bPU/gH5Tf87dTZi09nNa/4a+l/B6qz5zp5NPA6xplSQmALq6e3w/YgfKz8DTgSywb5A3TcZRgAmB9YEfg5GlsX5IkSdLsYZ7XmXneOPO8ATDP65t53vxinmeeJ0nStPFGn1bNu6xP7efkzFw0sJ5096rG8Z3ACROcc23jeKM+22zWX4UyIFjcpu7DGsdnV3ePf4jy4bU56NqoejwceFtE/BZ4TWZOFHZA+R5dz/jMrfWB7ShLE7ezqPb8mLEnmXlrlH3Ld6vV6xQMLGocHz3Rns6DXMZ0kGZAv06kNRh4cKeK1QyA79AaCvyLsgTtt2shz1j9BcDbgLdTBtUBHBoRp2TmaR2a+Qit78/vAe/o9F6MiDWAx1KWCG/3M7U75ffsJrQGjT8E3tKhD1D25W7nSuAbwC/osF959XV6HOXn7SFV8drAt+g+k6Sdd1F+thL4DHBwZl7XaG9PymD0/lXRisBhEbFtZv67z/am29j3p1fLAV+jtoww5T04aE+m/C4D+Arl635ZvUJE3IcyWH9SrfhDEXF4Zt7S6cLVDK1mKPAD4C2ZeUmj7mbAJyhLXu9L5/flMqolgKfy++XUxvEuGAxIkiRJas88rzPzvPbXAPO8qTDPa888b3qY5xXmeZIkzXPe6NNqx9rzJc0PYjNBROwDvL5R/IPMvHqCU89uHPc7QGhXv9NyuM0B0vXAUZQPdr14PPCXiHh6ZnYNPDLz7og4jrLU6pg9aBMMRMRGwFa1omMbVY5lPBjotq938zWX+Z28cxrHm3SZWfZmyiB8zN+AvTKzGXoBkJlLgHdGxN8oA/ygBFqfBB7TrB8RG9L6Pj8GeF630CczbwZ+Cvw0IpZZcnjsd0ibFVhvnsReyN8G/jczu87CqL52R0bEsVXfHl+9tFNELOq0r3QHY4Hb6zPzsx3aOyoidqHM2Ni6Kl4P+Bhltt+M1e/v+Ij4HK2hwKWUUGjQxkKB14ztp92UmZdHxNMpS16P/e1ai7Lk8lfbnVMtU35oo/jTmfmGDm1cAjw7Ig4FXlPr13T4R+O425LEfal+1jstW93J/SeuIkmSJGlEzPM6M89rvX6ded7kmef1zjxvwMzzAPO8XpnnSZLmNPfIrETEvWkd6F7Sqe50iogVI2KjiHhKRHyfMsBZvlblasosh4k0B8H3rz7M99KH3SnLPjZ12u94QeP4nYyHAgkcQbmj/EGU2TrPpAx66gOw9SiDrc166GKv+3rXy2+nfKCuO6b2/MERsU7j9bEP1rs1ig0GJu/6xvEKLPv+oRp01/fMvgF4SqdQoC4zf0Dr8qd7dNjjuvle++FEM7sa7dzaa93JyMx/TRQKNOrfDhxA6/KsL5hE0z/pFArU2roaeCFQD3SeW/1enRMi4mDKfupjrqEEU5cPqclvdwoFxlQzwN7bKF4m9Kp5JmU22ph/UAK3ibyR6V/OvPk3eMu2tSbnNcAZfT5+OsD2JUmSJA2IeV7XPpjnVczzBs48r/frm+eNkHmeed4A25ckacbxRp9xCxvH0z77JyKy+aDs2/svyrKzezdOuZTywfSfE107M68Eft8o/nhELN+ufq1PKwAf7/Byr8HA2AfRG4HHZubzM/PHmXlGZp6ZmT/JzBdQZnfcVDtvPTrcyd5wTOP40dFmygWtwcBJmXlb4/U/UZZNhvKz8ag213g4sHrt+F+ZeW4PfVR7zWAAYJmZNMDzab1j/1OZeUUf7TTfw0/r4ZwN+7j+jFR9jf5UK9p1Epc5sMe2TgF+UitakbI87KwXEa+l9etwM/DEIf/sv6/HekdS/k6MeUinipSfo7oPt1suuqkKpD7UY38G5V+0Bk0Lp7l9SZIkSbPDwsaxeR7meW2uYZ43WOZ5Q2SeNxjmeeZ5kiTNdd7oM645CGg3YJkpFlP2Md42M0/t47wPNI53Af4vIlZuVzkiVqHsA9xpicV2y7FC5/fVizOz42yZ6rUXNoof28NMpX/Qumf5usD2berVl+g9pk37twB/rRUtmuAa4OyfqWr3Xmk362bPxvF3+2mk2pP70lrRI9tUOx+4q3b86ojYuk29GSciVouIe0XEZhGxsP6g9XfZ1h1Cs05Oz8xlls3u4tuN4937OHdGiojnAp+uFd0BPDMz/9rhlEG4KDOby2C3VQ3aL6wVdQu06r9LlwI/7qNPP2I8OB26KrC4uVa0fp/vXUmSJEnzg3leg3meed40MM8bAPO84THPu4d5niRJc9gKo+7ADLJa43ioy3ZO0drAddV+wj3LzKMj4tO07gn+fGDnas/W44HrKAPrRwKvZfyu69uAWyizcsYs6dBUu34dnZkTLpWYmT+LiN/TunfzC4ETu5yT1f7Fz6oV7wGcNnYQERsDW9Reby59XC8f29e53b7eixrHBgNTs6BNWbufvfoA8w7g9mrQ24/rgE2r58vsz5uZSyLi18BTqqL1gb9HxLcoS2wf12bW2LSLiOUo78O9KTPSHsiyv786WY6y7/MNPdY/qc/uNes/vM/zZ5SI2BM4nPEA627ghZn5uyE3fVaf9evhz9rtKkTEvYD60stn9bM8dWb+JyLOon3oOiz/obxfAYLyPr9lANf9HPD9Ps+5Py73K0mSJM1E5nnmeWPl5nnTZ0GbMvO8Lszzpo953jjzPPM8SdLc5o0+45pfi2m707lm88bx2If4bYF9gKdX5esAn4uIzTOzl/28695CWTK1vuTj5sDHupxzN/Ciqs5kg4HDe+8ih9MaDCzq4ZyjaQ0GFgGfqh3XB/l30DloOBZ4e/V8+4hYNzOvg7K/Ou7nPWjNfdOX0nhfVQPhjWtFK9E642Ey1u1Q/kZKMLR+dbwK8NLqcXtE/JWyF/wfgT+OvTemS0Q8EvgsUxucrU3vwcB5/Vw4My+LiNsoXzeYxcslR8QjKLNeVqoVvy4z+x1QTka/M1Dr+7Z3+ru+fuO4uWd2Ly5leoOB5t/hFQdx0cy8Criqn3OcfCRJkiTNWOZ5nZnnYZ43JOZ5fTDPmz7meW2Z50mSNEe5dde45p3Q7fYVHqrMXNx4XJSZp2bmtzLzGcBTKTNxxrw1Ig7os42lmbkv8P8oMyImcjFlkP5DYKPGa//ucM6SNmV/7rWPbepu1cMSj80B+qOqAeWYRbXnJ3W58/14xpd7DeDRtdceQetMi0urJWQ1eQ9sHP8zM5tL/a7D4H9Xtd2PPjMvBHaifeCzMiUYejNl7+qrIuKoiHj2dCxBGhF7A79n6gOzfr6WN07i+vXQYaWIWH0S1xipaonnXwFr1Irfm5mfn6YudFpGfSoWNI5vmsQ1JvN+mIrm3+FBzP6RJEmSNLeY57VnnjfOPG/wzPN6ZJ43fczzOjLPkyRpjvJGn3HNDzwz7sNsZv4CeGWj+NMRsdkkrvUpysyfV1Hucr+I8kHxtur5LyizfrbNzGMoyxzW74S/IDOXdLh8u1kDV/TRvX81jpen/ZKw98jMM2m9o3sd4MG140W1552W+SUzbwL+3uG8RbRy9s/U7dw4Pq1NnZXalA1NFcg9hrL/8aGUvb7bWR54HPAD4E+T+TnsVXXtb9A6A+Iq4JOUmW/bU2Z4rAYsl5kx9qjOm6x2+6uP4hrTJiI2AY6kdbbjoZl5yIi6NCi3N44n83M1rT+LtP4dvq3av1ySJEmS6szzzPPM86afeV4PzPOmj3leV+Z5kiTNUW7dNe6fjePmbJcZITMPr2YCPLUqWgP4OGV/336vdSPwxeoxkV0ax932+j2zTVnzQ2k37equ0qas6RjgObXjPSh7Mt8HeECjXjfHAg+rXYM2zwH+0EOf1EFEbMiys1mOb1P12sbxeZm51XB6NS4z/0w1G63q686UvcX3AHakzBAbszPwh4jYsUtgNhVvp3X22c+B52dmLzMi1pq4Skdt94fu45w7MvM/U2h/WkXEepRQ4L614iOA14+mRwPVXD64ucx2LzotkT1wEbEOrb/3m3+jJUmSJAnM8yZinmeeN1DmeX0xz5sG5nkTMs+TJGmOckWfcYtpvVN9kxH1oxdvpnWv02dX+88O02Mbx8d0qfuPNmUL+mirXd3m4LCd5oycRdV/e93Pe0x9htB2EbF+RKzEsuGIM4Cm5jUsu0fvz5qVMvMOWgc1m1f7q0+bzLwqM3+WmW/LzIdTBo4foDXEuh/wliF14em15zcDL+wxFIDW/dD7tWU/lavZM/XBXF/7Jo9StSTxL4FtasVHAi/OzGEsvTvd/kXr340HTeIa2w2oL724T+P44mlsW5IkSdLssRjzvG7M88zzBs08r3fmeUNmntcT8zxJkuYob/SpZOZtwLm1ok0jYrVO9UcpM88Hvt4oft+w2ouINWmdYXQz8N1O9at9kc9tFG/bR5PND59XV4PDiXTa13tRrezkHmYk/JHxPXXH9vVu7ud9YWZ6R/okVTNqXtMoPjozL+hwyp9qz1dk2WWXp1VmXp6Z76Ysh133zE6nTLat6vdQfXB/XDV7r5dzVwEeMtm2WXYp5ons1Dg+eQptT5sqaPohrf3/C/CsubK8bGbeSutS2veKiG061W+KiG2BDQfesc6afTt1GtuWJEmSNEuY53VmnmeeN2jmeb0zzxs+87yJmedJkjS3eaNPq/qH2OWY3rud+/VBoP6Bda+I2G1Ibb2e1r1Vv13tfd3NDxvHT+ijvWbdP/ZyUmaeS+t+4GtTBkX1GUAd9/OuXWcJrR+gF7HsMr/O/pmkiFiesnzqBo2XDu5y2m8bxy8faKcm7wfADbXjzTvUay5fvXIfbSxoHN/QrlIH+zK1fZi3i4h+Zors2zhut3TzjBIRY/ueP75WfA7wpD5mWc0Wv2sc9/Nz9IpBdqQHzWXA/zLN7UuSJEmaPczz2jPPM88bGPM8wDxvxjDP65l5niRJc5g3+rRqDhqHvXzupGXmYuDwRvHAZwFFxNbAu2pFN1NCiYkcDtxVOz6g2qN1ovbWAV7aKP5FD+2NOaZx/CLKEqydXu+k/l7Yg2VnnBgMTEJErE/5fjaDlsMys1to83/AktrxPhHRXH562mVmMj5bDDrvXb+kcbxRH80092LeupeTImJt4D19tNPJIT22tyPwjFrRUuDbA2h/2P4XeH7t+J/AXpnZy/Lis82XaH2/vjYiJgzAI+LBwKuH1qv26n9/7waOm+b2JUmSJM0e5nkN5nmAed7AmOfdwzxv5jDPm4B5niRJc583+rT6VeO4OXiZaT5A6x6te0TEom4nRMQKvV48Irai3DG+aq34HZl5yUTnVrNxvlYrWg/4arf2q9e+WtUdcynwrV77zLID9lfWni+ldcnYbuqD1AcCzdlVQw0GIuKwiMja47BhtjdsEbF2RLyRMrOqOcPrJOC13c6vZmV9tFH8g4jYvc9+LB8Rz4qIddu8tqjfsCEingLUA6+z29WrlhJfXCt6eEQs6KWNaonW82tFD4mIvSbo12qUWVYLe2ljAs+IiK7fn4jYAPgmrX9TvpeZVw6g/aGJiPcA/1UruhZ4/FxdxjszL6I1rFkJ+G1ENGfb3KMKBX5DWWJ7WlRLL9d/556cmVdPV/uSJEmSZh3zvNa65nmFed4UmeeZ581E5nnmeZIkqfBGn5rMvIIySBmzRz8D6emWmRfT/yygwyLiWxHxlIhYtV2FiNg4Ig4C/g7cp/bSL4FD++jigUD9w9wzgV9XgUOzzS0owUx9T+QE3tjjft5jmgP2VWrP/9rH0p3HMb4Pc9C6NOs51XtlvlslIha2eWwXEbtFxNMi4sCI+CVwGfBJWvemBjiSMhCbaJ91gI9U9ccsAI6JiEPbvafGRMSKEbFrRHwYuJCyDPVabaruAPwuIs6KiIMi4iHVssTtrrlyRLyCZWe4fKNL/+vvzdWA30TEc6uv1+aNr+EajXO/2zj+fkS8IMqe9fV+RUQ8DjiR8QBmKgOqsdlHn4mIT7WbxVe19ydaZyZdB7xlCu0OXRWu1Gc33UkJqG7t8L7u9NhkNP+CSXsDUP/9tTFwSkR8pfq7sG31eEpEfAX4K3Bv4Brg99PUx11oXV7+J9PUriRJkqRZyDyvMM8DzPN6YZ5nnmeeZ543DOZ5kiRNsxk76B2hw4GdqufrUGYBHTW67kzoA8CLGf9e7h4Re2Zmpz6vAjybsvfu0og4mzIz4SbKQGtTyl7m0TjvSOA51dKmPcnMK6PMkDiaMhACeBxwTkScRpnVkMAWlEFZ0yGZ+eNe26vavDAi/gnct83Lx/Rxnesi4gyg3X7GLvNb7ARcPMlzbwDeC3wmM++eqDJAZt4ZEc+hBEi7VsXLA68BXhMRlwNnUAaly1EG/5tQBqz9zF7Ypurbe4H/VO+Df1d9XrG65kMYf0+PORb4cpfrfpqy9PTYz+pOlFk67RwAHFY7/jjwEsaDlbUoM24+FhF/rfq2LuXnqL6M8LcoA979uvSrmw8Cr6f8PL2B8nX+M3A5ZeC2PbBZ45ylwH4zffYPy4ZUK9D5+9HNJQxmptW0qH63PYEyu3ODqngFyhLrzWXWxywFXsCye7b3/PegT3vXnt9Nea9LkiRJUjfmeeZ55nm9Mc9rZZ5XmOfNYOZ5kiSpHW/0WdYRwMcYX952H2ZwMJCZF0XEN4H9a8WH0FufV6R8sO+4zCNlUPFR4MDMvLNLvU79+0tEPJESuNQHEA+uHu0sBd6QmZ/vt73K0ZSwpKnbntHtHMvogoFVGsfNfZ1nq9Mp74UvZ+YN/Z6cmTdEWc76Q5SBan2Gzn1onbHWyX/ovPd202q07i3cyU+AF3YLOTLz1GrW0OdY9vvbVWYuqUK23wAb1l66N/CUDqd9ixIwdAsrJnIN8Hjgt5RwYEXgkV3q3wK8IDN/MYU2NWSZ+Y+I2A34CvCoCapfAjw3M0+KiGZwcNOg+1bNant2rejIzLxs0O1IkiRJmnPM81qZ57W//rCZ57Vhnmeep6kzz5MkSU1u3dWQmdfRulznc9ssuznTfAC4q3a8c0Q8qUPdI4A/ALdNcM2bKPtrb5eZ75xMKDAmM4+jDLA/RJk50MktwNeBracQCkD7gfudwAl9XqddkJD0MZNoCnapPb8T+Mw0tDkId1PeW1cDZ1EGlJ+mBFf3y8ztM/NjkwkFxmTm0sx8M7Al8HnK7JyJXAv8qOrHvTos1fx1yiyHbwG97Ol8J2Wg/qTMfGYvy0hn5tcpM5IOpMzAuIzyvp9wJkVm/p0yw+dwSnjWthpwPLBPZr4wMzvV61lmnl21+7+Ur2M7t1OWI94mM3861TY1fJl5fmY+Gngy5W/eeZTf+7dQZmf+gvLzsE1mji2Bv6BxmUn/HHfxJFpnZ31yCG1IkiRJmmPM8+5hnmeeNxnmed37bp6nGcE8T5Ik1UUfK7fOG9X+0ucwfiPUKzPzSyPs0sBFxEqUmT9bUJYGXY0y0LmKMqA7ZRCDijbtBmVGxf2rdpenzDK4ADhxGG3ONhHxAMoH8zFfzcyXjao/s0FEbEN5P69HGbzcCdxIGeCfA1zUzzLV1TU3oiz7u5CyjO6qwK3AEuBc4LTMvHEg/4A+RcQCYHfgfsAalOWNr6TsWz+02RLV743dKbP57gXcTPkaHz2qr4WmT7WM+tge5tdk5gbd6k+yjZ8zPqvt9MzsNkN12kTEtpSlxAE46QOvYpv7bNjljNnl7MuvYqd3faFetF1mnjmq/kiSJEmTYZ5nnjdK5nn9M88zz9PwmeeN53knf+ptPHDTe4+wR4N11qVX8vA3fqReZJ4nSfOMW3e1kZnnR8S3KPvvArwxIr7c78BiJsvMO4C/Vo/pbDeBk6qH2ntM7flS4P2j6shsUc1SOXvA17wCaDdTaOQycwllhsZ0t3sHZQah5pmI2JzxUADglCG0sTVlBtCYgwbdhiRJkqS5yzxvqO2a503MPK9P5nnT1q553jxlnidJ0tzm1l2dHQjcUT3fBnjmCPui+aUeDHwtMxePqiOSVHl14/jEIbTxTsY/l5yUmT8aQhuSJEmS5jbzPI2KeZ6kmcY8T5KkOcwbfTqoBmOfqhW9NyL8emk6LKr+ewdlv3ZJGpmI2AF4Q60ogW8OuI2tgOfXrv+WQV5fkiRJ0vxgnqcRWlT91zxP0siZ50mSNPc50O3uEODS6vn2wH4j7IvmgWrf2HtVh1/OzH+Osj+S5p6IeG1EvC0i1uyh7mOBo4CVasU/z8wLB9ytjzC+neg3MvP4AV9fkiRJ0vxhnqdpZZ4nadjM8yRJUtMKE1eZvzLzlojYF9izKlpxlP3R3JeZZwIx6n5ImtM2AN5Lmdn6M+A44HTgmur19YCHUpa436Nx7nXAawbZmYhYC/gb8Peq6NBBXl+SJEnS/GKep+lmnidpGpjnSZKkFt7oM4HMPAE4YdT9kCRpwFYDnlc9enEd8IzMvHyQncjMG4GDB3lNSZIkSfObeZ4kaY4yz5MkSYBbd0mSNN9cR9k3ux+/AnbKzD8OoT+SJEmSJEmSOjPPkyRJLVzRR5KkeSQzPx0RPwSeAOwKPBDYFFgArALcTAkPLqAsA/zTzPzHaHorSZIkSZIkzW/meZIkqckbfSRJmmeq5Xq/Wj0kSZIkSZIkzWDmeZIkqc6tuyRJkiRJkiRJkiRJkqRZwBt9JEmSJEmSJEmSJEmSpFnArbskSZL6cMuil3DTNtuMuhsDc8vZZwNfGHU3JEmSJEmSpKH41w7PZLWt5k6e9691zwY+MupuSJJGyBV9JEmSJEmSJEmSJEmSpFnAG30kSZIkSZIkSZIkSZKkWcAbfSRJkiRJkiRJkiRJkqRZwBt9JEmSJEmSJEmSJEmSpFnAG30kSZIkSZIkSZIkSZKkWcAbfSRJkiRJkiRJkiRJkqRZwBt9JEmSJEmSJEmSJEmSpFnAG30kSZIkSZIkSZIkSZKkWcAbfSRJkiRJkiRJkiRJkqRZwBt9JEmSJEmSJEmSJEmSpFnAG30kSZIkSZIkSZIkSZKkWcAbfSRJkiRJkiRJkiRJkqRZwBt9JEmSJEmSJEmSJEmSpFnAG32GLCK+HhFZPY4YdX+GISLuExF7R8RrI+KdEfGKiHhKRGwwxDY3ioinRsTrI+JdEfH2qt3HRcSGw2pXmssiYlHt91VGxEFDbOuwRlsLu9Rd2Kh72KCuPSwRsX+jD/tPdx9mi4hYPiLOrH2t3jjqPkmSJEma38zzhtameZ40YOZ5g2Oe1zvzPEmSRm+FUXdgLouI3YD9qsM7gHdMUP8Y4NHV4bGZuahL3YXAxT10YylwI3A9cCZwCvCDzDy7h3O79XU54PnA24DtO1S7KyL+AHwkM383lfaqNpcHXgy8BnjYBHUvAn4NvDszl9TKNwbOANapVX9pZn5tCv16H/DuWtGFwIMz85ZancXAZtXhNzJz/8m2N0j99CsiFgFHT3DJu4HbgVuAq4F/AecCpwInZOZZU+mvpNkjIrJ2eHBmHtSuXmbeFRFvB34+VjcivpuZVwy7j5IkSZLUZJ5nnlersxjzPPM8aR4xz5MkafZwRZ8hqQbOhwJRFX0+M3sZyA/aisB6wAOApwOHAGdFxB8iYqvJXDAi7g38EfgmnUMBgOWBPYGjIuILEbHyZNqr2tyeMrj8GhOEApX7Aa8F7l0vzMx/VeV1n4qIzZiEiHgY8N+1oruB/eqhwDyzHLAqsD6wDfBYSpDzJeDMiLggIg6p3kPzSmM2yDGj7o80k2TmLyh/VwDWAj48wu5IkiRJmqfM8wDzvPnIPK8D8zypM/M8SZJGyxt9hmdf4MHV8zuAj46wL+3sAZwWEXv1c1I1g+YvwK6Nl5YAvwW+U/33hsbrrwQOj4igTxHxJOBEYLvGS9cDxwHfrx5HU2addJWZ36nqj1kT+Hq/fauCjm/QujLWxzLzhH6uM8/cH3gPsDgi3h8Rq4y6Q5JmjPfXnr8gIh40sp5IkiRJmq/M81qZ5wnM8yR1Zp4nSdKIuHXXEETEipSZNmMOz8zLp6HpzduUrUSZAbQjZZnch9deWxn4UUTskJkXTHTx6t/1Q+C+teKbKcv9fiUzlzbqvhz4CLB6VfwcyrKvB/b6D6qWS/4hUB9Angy8Czg6M+9sc87WlNlOL+1y6VcDj2R8htAewH8Bn+61b5QPsQ+sHZ9BH/+2OeByYPc25asDCyjLKW8H7AQ8Cli3VmdlyvfwSRHx9Mz853C7Kmmmy8wjI+KvlFmeywEfAJ422l5JkiRJmi/M88zz5gnzPEkDY54nSdLouKLPcDyP1kH6odPRaGYubvM4LzNPzMzPZuYjgLc2Tlud8uGrFy8Bdq4d3w7slZmfr4cCVV+WZubngCdQZkCNeVu1H/mEImJ1ynLC9VDgE8BOmXlUu1CgavuczPwwsBVwfoc611KCi7oP9br8cUTsCrypVrQUeHFm3t7L+XPEnR3ec2dm5gmZ+YvM/FBmPhPYhPL1bn4/HgIcMx+X/p3vMnP/zIzaY/FsuHYffTis0YfDprsPs9Tnas+fEhHbjqwnkiRJkuYb8zzzvPnAPE+TZp6nDszzJEkaAW/0GY43156flJmnjqojTZn5MeCwRvGzImLNbudVy+C+vVH8/sw8cYL2jgc+WCtamdbZUd38D7Cwdnx4Zr45M7OXk7O4q8vrv6DsET5mVeAbEbF8t+tGxGqUr2H95+eQzPx7L/2ajzLz1sz8CiUI+L/Gy/cDjpjMMtCS5pwjKEvHAwStf08lSZIkaZjM88bbM8+TeZ6kXpnnSZI0At7oM2ARsQvje3lDmcEy03yycbwCZSnWbrajdVbTbcBne2zvM1X9MftExBrdToiITYDX1IquBv5fj+31443AJbXjnVg2AGn6MLBF7fgvlBBDE8jMWzLzxcDhjZceDRwwgi5JmkEy81bgx7Wi50fE2qPqjyRJkqT5wTyvLfM8AeZ5krozz5MkaTRWGHUH5qD9a8/vpuxHPdOcDvwHWK1Wdt8Odcc0g4OTMnNJL41l5nURcTJlD20oS/c+Gfhul9NeBtRn4nwhM6/rpb1+ZOZNEXEA8HvK3eYA742IX2bmac36EbEH8Npa0a3Aft1mGqmtV1H2l9+mVvbuiDgsM+/u50IRsQLwCMpMog0os8yuBhYDJ2TmbZ3P7una21WP9YE1KMs630zZ0/xC4KxRfP8jYl3KnvJbUPZLXwW4EbgWOBU4u9fZcn20uRxlue/7ARtTAr/LgeMy8+pBtqVWEXFfys/MJpTZitdQfpf/td+fmTbX3pDy+3nj6tr/Ai4C/jzVa0/S9xgPClehLJ//xRH0Q5IkSdL8sX/tuXke5nlqyzxviszz5hfzPPM8SZKGyRt9BqhaInafWtEpmXnFqPrTSWZmRCyhNRhYd4LTNmkcn9Fns6czHgzAxMHASxvHX++zvZ5l5tER8WngDVXRSsDhEfHwzLxnP/JqOeSvMx4gALwjM88ZVt/mqsy8NSI+BHyjVrw5sCfw216uERHbAO8GngKs1aHarRHxM+DAzDyv1/5FxL2AdwH7AutNUP0/EXE88J3mvs0RcQxldlPToyOi26D94Mw8qE2/dgKeQ/k6bUfre7Hp2oj4CvCpzLyy679gAhGxCvBWyr7s7ULEuyLiSOAtmXlWj9c8DNivVrT5oPbe7vXaXb4/fcnMZb4PEbE/rb+3Dui2r3fj/XBsZi6qyncFDgYeQ/tV+P4dER8ADp1EqPYQ4KPAHh2ufVlEfBH4UGbeGREHAe+tvb5HZh7TT5s9+j1wC7B6dbwvBgOSJEmShsQ8ryvzPN3DPM88zzxvmfrmeePM8yRJmmZu3TVYuwLr1I6PHlVHetAcSE00S6IZHCzps71m/Qd1qhgRW9AaRFyYmRf32V6/3gGcWzveHjioUecTwGa142OATw+1V3Pbd4CrGmVPm+ikiFg+Ij5JCaf2pXMoAGU2w3OBMyPiDV3q1a//GMp74b+YOBSAErDtBby/l+tPVkQ8C/gz8CbKz89Ee6CvR1m2+oyI2HMK7d4bOBE4hM4zBZcHngicGhGvmmxbahUR7wSOAx5H57/X96L8HvpBRKzUx7XfBJwMPLbLtTcB3gccW4Vl0yIzlwIn1Ip2i4gF09W+JEmSpHnHPK+zZn3zPJnn9cE8b/4xz7uHeZ4kSUPmij6D9YTG8R9H0osJRMSWlCVL6y6a4LQ7Gscr99lss/7WEbFchzvWH9E4PnHsSURsC7yIMhC7L2VQeC1wGSWI+VFmntRn38ZmpLwY+BPjSwy/LSJ+npknRsQTKcsPj7kJ2H/QS6nOJ5m5NCKOpXXW3G7dzomIVYGfUL7/dUspy9teBtwO3JvyPhqb5bYC8KmIWKfdzJra9bcAfkEJFOouAc4Grq+O16LMWNoCWLFbnweoOXi7CzgfuJiyxG9SwoAHUf79Y9YDfhkRj87ME+nPysAvgR2q47uBUyjLKK9EWap5y1r9FYHPR0RmpjM2piAi3gJ8oFZ0bvW4BdiIsuTyKrXXn0kZxL+9h2u/GfhYm5fOorynbgc2pSwtvDwl9P4eJaSYLscx/nO+PGXW2/ensX1JkiRJ84d5XmfmeWphntc387x5xDzPPE+SpOnkjT6DtXPj+NR+Th5b2nEaNO/Qv5PWu63bubZxvFGfbTbrr0L54Lm4Td2HNY7PjojVgQ9R9tNuznzYqHo8nDKY/y3wmsycKOxokZl/iYj/oSwfC+XD6DciYhHwlUb1N2bmJX1ce2E/fZkuM6BfJ9IaDGwbEStk5p0d6h9KayhwA2Wm1lcz86Z6xSpEeA1lZs7YAOrAiDgpM3/d4fqH0BoK/AF4U7v93as2VqYsFftMYFGbKs+rtV2fxXZS9VonS7qUfxP4OWUf7bYz9yJiF8qgco+qaEXgiIjYor58dQ9eyfisxu8Ab83MyxttPRz4PLBjrfjTEXF8Zp7ZR1ujUP/+9Op/aP3eDWM59wcxvjT6T2izpHhErEOZlbh/rfjNEfH5bksmR8SOlN+ldccAr2t+vyJiA8rPxKuAR1H2kO9ZuyWQ+3Bq43gXDAYkSZIkDYd5XmfmeTPQDOiXeV57S7qUm+cNjnlecQzmeZIkzWve6DNY9Q/GSzLzspH1pIOI2Ad4faP4B5l59QSnnt04boYgE2lXf+0OdZshwvXAUZQPhr14PPCXiHh6Zk4UeDQdQtlv/CHV8RbAacD6tTo/z8yv9XldtdfcD30Fyvf/n82K1Xv3gFrRJcCiToOgzLwV+HhEnEjZI3gVSqj06YjYqjn7LCICeGqt6DzgSZl5e6fOV68dCRxZBRHN1+/ZS7tc/h63TWL/6mOB+2TmfyaqWM1aeyzwVca/ZptSlkY+rI82x0KBj2fmWzq0dXJEPAr4DeOD2ZWAL9SOZ6R+9zqPiLfTGgosofy+GbSxpdU/kpltZ/Rk5vXAAVVA8PSqeHngpcB7ulz7UFr/9v8IeG67MK76u/DqiLgI+AitvweH7R+N4+bM0EmLiA2BDfo87f6Dal+SJEnSjGOe15l5ntoxz+uded6AmecB5nm9Ms+TJM1pnfbxVJ+qfW/rA92eZ4cMU0SsGBEbRcRTIuL7lOUal69VuRp4Ww+XOrZxfP9qlkEvfdgduF+bl9bscMqCxvE7GQ8FEjgCeBblLvntKLMvvl29NmY94KcRUd+De0LVXrIvpix1Oab+Yfha4OX9XFNdXd+mbJkP7NWg/cBa0Z3A03oZXGfmnxrnPgB4Rpuq6wOr145/3i0UaNPOrb3WnYzMvLqXUKBWP4HX0bpv+gsm0fQpTPA7ourXvsDNteLdI+Khk2hvRoqIA2idOXMr8NTMPH1ITR4PvKOHeu9qHD+mU8VqttZOtaIrgJd0mXEHQGZ+lBKATafLKT/nY7bsVHESXgOc0efjpwNsX5IkSdIMYZ7XtQ/meerEPK/365vnjZB5nnneANuXJGnG8UafwVnYOJ722T8Rkc0HZS/uf1GWBt27ccqlwF6Zucxsi6bqTvnfN4o/HhHLt6tf69MKwMc7vNxrMLBJ9d8bgcdm5vMz88eZeUZmnpmZP8nMFwCPpey1PWY9ygyIvmTmGXS+g/5Vmfnvfq+pjtoFA8vMpKEsWbtd7fhbmdmcIdDNoUB9Wdyn9XDOhn1cf0aqBuz1ZY13ioh+f+8f1Jwt1aGty4AvNYr377OtGSkingZ8uVZ0J/CczDx+iM1+oMev+5m0Lpm+Q5fqz28cfzYzb+ixP+/rsd5AVP/2+jLKG1RLvkuSJEnSIC1sHJvnYZ6nCZnnDZF53mCY5wHmeZIkzWne6DM4zUFEuwHPTLGYsm/1tpl5ah/nfaBxvAvwf9W+xsuIiFWAb9F5icZOH3o7vS9fnJlHd+pc9doLG8WP7XWmUsPHgZMbZT/MzB9M4lrqrN33OtuU7dk4/m4/jVQD5L/UitotQXtN9Rizd0TM6KVqx0TEKhGxQURsFhEL6w9aw7I1GQ/aenE9ZQnfXn27cbx7H+fOSNUyxt9lfOZkAi/LzF8MsdlbKfvJ96q+FPtqEbFGh3q7No6/12sDVQjyrz76NAjNv6P9Ls8rSZIkSRMxz2swz1MPzPMGwDxveMzzCvM8SZLmthUmrqIerdY4Huqyn1O0NnBdZt48Yc2azDw6Ij5N657gzwd2johDKUtTXkfZj/aRwGsZnxl1G3ALZVbOmCUdmmrXr6Mzc8KlFjPzZxHxe8psoDEvBE6c6NzGde6OiLOAh9eKz+jnGurJgjZl7X52mgPM66pBbz9urD1fGBHL1WdYZGZGxBGU5XGhzEQ6OiJ+QFle+nf9/swMS0TsBOxDCee2pXWZ8YmsQ5n914tTJloGtuE0ys/6KtXx9hGxUmbe0cc1ZoyIeDDwM8b/PQBvzcxvDLnpC/v8mjUH0GvT/vfog2vPl2TmBX3266/0NntuUJpLWw9qBtDngO/3ec79cblfSZIkaS4yzzPPU/8WtCkzz5uAed70MM9bhnmeJElzlDf6DE7za9nPh+lB2bxxvBywFmXgsA/w9Kp8HeBzEbF5Zvayn3fdWyh3YdeXjNwc+FiXc+4GXlTVmWwwcHjvXeRwWoOBRX2cq+m1Tpuyq9uU3bdx/OcptrscJZS4rlF+EPBEyiAAyqyP51aPuyLiVErIdDxwXGZewTSKiO0oyxY/agqX6SdEOK+fC2fmnRGxGNi6Klqe8jM/rV+nQYiI+1FmP9W/Xh/OzE5Llw9SvzNIlzaOV2xWqJbJrQccvYZDdZM5Zyqaf0eX+XdNRmZeRete9xOKiEE0LUmSJGnmMc/rzDxPnZjn9cE8b/qY57VlnidJ0hzl1l2D05y10G5f4qHKzMWNx0WZeWpmfisznwE8ldZ9jd8aEQf02cbSzNwX+H8sO6hq52LKIP2HwEaN1zrtjb2kTVk/A8Fm3a3CT3Uz1QMbx0tpP4hcr03ZVC2zp3xmXkuZVfPDNvWXB3akzBA6Arg8Iv4UES+NiIEMWLqJiN2BPzG1UAD6+71/48RVltHcI3rdSVxjpCLiXsCRwL1rxV/LzP+epi5MuJf3JCxoHN/UrtIEJvN+mIrm39Fbprl9SZIkSXOfeV575nnqxjyvR+Z508c8ryPzPEmS5ihv9Bmc5gemQS1JODDVHrSvbBR/OiI2m8S1PkWZ+fMq4EfARZQPmrdVz39BmfWzbWYeQ5lRsVLtEhdk5pIOl28366CfGQTNfWeXp/2Sshq9nRvHZ2TmXW3qrdSmbKrahkWZeXVm7g08CPgIcDrt9xkPSojwFeD0alnYoYiItSj7L9fDjBuAL1Jm4z0EuBfl987ymRljD+DgKTTd7t89imtMm+pr/RvGZ4FBWeL1FaPp0cDc3jiezM/UMH4Ou2n+HZ3uYEKSJEnS3GeeZ56n/pnn9dJR87xpY57XlXmeJElzlFt3Dc4/G8fN2S4zQmYeHhF7U2YDAawBfBzYexLXupEyMPliD9V3aRyf1KXumW3Kmh9qu2lXd5U2ZRqhiFiJZWezHN+h+jXAxtXz24DVMnOoA87MPAN4O/D2iFgA7ATsRlk6ehdaf39uBfw+Ih6emRcPoTuvovV3yknAUzOz3bLITWtNod1+lgXudE6/y9aOTESsQtnDe4da8XHA8zoEVrNJ8/vQbpntiUz3bK6Na89vp8/leSVJkiSpB+Z53ZnnqYV5Xl/M86aBed6EzPMkSZqjXNFncBbTeqf7JiPqRy/eTOteqc+OiEcMuc3HNo6P6VL3H23KFvTRVru61/ZxvqbHvpT94et+1qFufVnoVYBNh9KjDjJzSWb+NjMPzMxHUWbbvJXWZW3XA943pC48vd4dYN8eQwFoHVz1a8t+KkfECsDCWtFd9LYk+MhFxPKUJZwfXSs+DXhaZt7W/qzZowo2Lq8V3S8iVuvzMg8aYJe6iog1aA21Lhl2GChJkiRpXlqMeV435nlqMs/rnXnekJnn9cQ8T5KkOcobfQak+uB4bq1o00l86JoWmXk+8PVG8bAGNETEmrTOMLoZ+G6n+pl5Ia1fS4Bt+2hyu8bx1Zl5Rx/na8giYlXK7Jq6C4E/dDjlT43jvQbeqT5k5nWZ+THg8bQGgk+LiGH8Xt2i9vzszLyoj3Obs+/6sWM12O/Vg2mdbfePzOxn9t4ofZHWAOYi4AmZ2dyjfDb7c+35crSGIF1FxLqU7+902aZxfOo0ti1JkiRpnjDP68w8T03meX0zzxs+87wuzPMkSZrbvNFnsE6uPV+OZQeoM8kHgaW1470iYrchtfV6Wvdm/XZm3jTBOT9sHD+hj/aadf/Yx7maHl8Atm6UvS8z7+5Q/7eN45cNvkv9y8yTgDNqRWsC63eoXh8gr9xnUwtqz3seqEbEY5jabKl16O9nb9/Gcaelm2eUiPgw8NJa0ZXAXpl55Yi6NCy/axy/vI9z92N69/TevnH8l2lsW5IkSdL8Yp7Xnnmemszz+rOg9tw8b8DM83pinidJ0hzmjT6DdWzjeNjL505aZi4GDm8UD3wWUERsDbyrVnQzJZSYyOGUZULHHBARE+5BW9V5aaP4Fz20p2kQEatHxDeAFzde+gPLvh/rfk2ZITTmERHxkkH3b5LubBx3mvGypPZ8ow51Oqnvx7xFL7OMImJF4H/6bKedg3psbxPgFY3ibwyg/aGKiDcBb6sV3UCZ+XNhh1Nms28B9VD2mRHx+IlOioj7AAcOrVftNf9+HjPN7UuSJEmaP8zzGszzVGeedw/zvBnCPM88T5IkeaPPoP2qcbzHSHrRuw/QOqjZIyIWdTuhn2U/I2Iryh3nq9aK35GZl0x0bmaeC3ytVrQe8NVu7VevfbWqO+ZSyofhWSUiDoqIrD2OGXWfpiIiVqkG8n9j2VDgAsoe1R33683MO1l2YPL5iHjWJPryuIi4X5vyHSLimdXezr1ea3talz+9osvSsGfXnm9W/Xz06rTa8/WZYAZU9W/4IoMJJ3cEPjxBe6sC3wbWqBWfkJmnDKD9oYmIFwMfqxXdRtnD+7QOp8xq1czL/20Ufy8iOv6tioiFwFG0zkKbDvU+XUn53SFJkiRJw2Ce11rXPG+SzPNameeZ5w2DeR5gnidJkvBGn4HKzCuAk2pFe/S5H+60ysyL6X8W0GER8a2IeEo1GFhGRGwcEQcBfwfuU3vpl8ChfXTxQODq2vEzgV+3G1BFxBaUYOaZteIE3uh+3kOzQkQsbPN4YETsEhFPioi3R8SPgMspoc2WjWv8DViUmf+eqLHM/DatYdFKwA+r9+OOnc6LiOUj4iER8d6IOIsyyGm3/O1C4EfAhRHxkYjYtZpF0+6aK0TE3pQliOu/R7vNeDm6cfzTiNi/CiQ2b3wNFzTqfrdx/NmIeH1ELLP0akQ8nDKj6oCq6OpmnT6MzTx6S/V1vk+zQtXeH4FH1orvAF41hXaHLiIeSHlPRq34v4FLO7yvOz5G8g+YvPcBp9eO1wJ+HxHfi4i9I2L7iNg6IvaKiE8BZ1L2174N+Ol0dDAiNqN1H/ufdgsOJUmSJGkqzPMK87x5wzzPPM88zzxv4MzzJEmafjN20DqLHQ7sVD1fh3IX81Gj686EPkCZkTH2Xtg9IvbMzE59XgV4NmXv3qURcTawmLJ85ALKgGs7Wj9sAxwJPKefD3eZeWVEPIUyoFqtKn4ccE5EnAacTxn8bwHs0OYSh2Tmj3ttT327D3DxJM+9jTLz4v2Z2Wlp3HZeRfm5qgdA+wL7RsTVlJky1wJ3UwY8G1MGNav00cZmwFurxx1VmHA5Zane5YF7Aw8B1m6cdw7w/i7X/QrwFsq+3wBbAV/vUPdg4KDa8TeA1zO+z/GKlJkcB0XESZR/89qUn72FtfOOpeyrXV9uux9fpOzpvQPl6/y8iDgZuIQSzGxT/TuaXp+ZZ7Qpn0k2ZNm/gZ+qHv1q/r6bsTLzjoh4MiU8ekBVHMA+1aPtacBrKb/fn94oH4ZnN45n/JLRkiRJkmY98zzzvPnCPK+Ved4487wZyjxPkiS1440+g3cEZcAzNjtmH2ZwMJCZF0XEN4H9a8WH0FufV6QMVLbvUudO4KPAgdVyrf327y8R8URK4LJZ7aUH07rEat1S4A2Z+fl+25tBmgPZ69vWmn0upCy9/PnMvLLfkzNzaUQ8mzJoP5jWr9MGlOBoIkuBW3psciXKoHiHCeqdADwrMzteNzP/FRHPpSyJu6DH9sfOvTMinkoZzN2/9tI6lIF7O7+jDLDe1E9bDbcDT6LMdHoQZbbTToyHn01LKaHAF6fQpoYsM/8ZEY8EPkdryNbOtcB+mfnLiGgu+XxTuxMG4Dm15+dk5olDakeSJEmSxpjntTLPmxzzvDbM88zzNHXmeZIkqcmtuwYsM6+j9W7l50bEGp3qzxAfAO6qHe8cEU/qUPcIyuDktgmueRNlGc3tMvOdkwkFxmTmcZRByYcoMzE6uYUyo2LrWR4KAOzaOP7kSHrRv7spg8nrgHOB3wOfB14JPDAzH5CZ751MKDAmi48Am1PeExPuEU95P/6KMotho8w8uU2dI4FnUWbqXNBLVyhL3L4AeGRmXtVD339NmTHz5qo/i4GbKV+3ic69FHgo8GngP12q/p3y9X58Zt440XV7aPcKYGdKYNjp5+8u4DfADpn5ham2qeHLzCsz81mUJZo/B5xFmeV2G3ARJVh6JXD/zPxlddqCxmU67V8/aRGxLa3B02z53SdJkiRpFjPPu4d53tSY53Vgnmeep6kzz5MkSXXhNpmDV+0vfQ7jN1K9MjO/NMIuDVy1l/D2lGV2N6IsxXsncBXlA+Ypmbl0CO0G8AjKLIiNKEuvXkMZyJ04jDanW0SsRpnxM7Zf8+8zs5eZLfNWRGxOGTRvQJkVczclDPgX5Wfx/My8q/MV2l5zPWBbSgCxHuU9fjtwI+X9dmpmXjuof0OffVudEh5tRVnS+AbgSuC0zOwl1Jhsu8sBuwD3oyyjfBslLDiul2BEs1tE/BHYvTpMYO3MHOgsoIj4DPC66vBqYNPMnCiIHroqsLhn+eo/nPAXttpmmxH2aLDOPftsHrPbI+pF22XmmaPqjyRJkjQK5nnmeVNhntc/8zzzPA2fed54nvfTY07kAVvNnTzvgnPP5umLdqkXmedJ0jzj1l1DkJnnR8S3gBdVRW+MiC/3s5/1TJeZdwB/rR7T2W4CJ1WPuWp3xkMBgANH1ZHZIjMvZvL7i3e65rXAcdVjRqmWFD6KaV5GPDPvpixrfMJ0tqvRq8Koh9aKzhtCKLAurcvOf2gmhAKSJEmS5gfzvKG2a56nZZjnTVu75nnzlHmeJElzm1t3Dc+BwB3V822YeN9Uacxjas9/m5l/GllPJKnYjzILbsww9tl+IzC2NP6lwKFDaEOSJEmSujHP02SZ50maaczzJEmaw7zRZ0gyczHwqVrRe6tlMqWJ1IMBZ/9IGqmI2AR4X6P48AG3sR7wX7Wid2Tm7YNsQ5IkSZImYp6nKTDPkzRjmOdJkjT3OVAdrkModzFD2f96vxH2RbNARKzF+HKav8zMv4yyP5Lmnoh4dkR8MCI26KHuQyjLXa9bKz4tM48ecLcOBBZUz4/OzG8P+PqSJEmS1CvzPPXFPE/SsJnnSZKkphVG3YG5LDNviYh9gT2rohVH2R/NfJl5I/5cShquNYF3AG+JiN8AvwdOA64C7qSEAA8CngI8FYjauXcw4JA7IpYH/g0cXBV9a5DXlyRJkqR+mOepX+Z5kqaBeZ4kSWrhAGTIMvME4IRR90OSpIYVKQP/p/ZY/1bgxZl52iA7kZl3AR8c5DUlSZIkaSrM8yRJM5R5niRJAty6S5Kk+WYJcFef55wAPCozfzD47kiSJEmSJEnqYgnmeZIkqcYVfSRJmkcy8ycRcS/gCcBulGV9N6Ms8bsKZabPdcAlwB+BX1WzWSVJkiRJkiRNM/M8SZLU5I0+kiTNM5l5LWXvbPfPliRJkiRJkmY48zxJklTn1l2SJEmSJEmSJEmSJEnSLOCNPpIkSZIkSZIkSZIkSdIs4NZdkiRJffj8bk9nXVYadTcG5jruGHUXJEmSJEmSpKH55qJnmedJkuYUV/SRJEmSJEmSJEmSJEmSZgFv9JEkSZIkSZIkSZIkSZJmAW/0kSRJkiRJkiRJkiRJkmYBb/SRJEmSJEmSJEmSJEmSZgFv9JEkSZIkSZIkSZIkSZJmAW/0kSRJkiRJkiRJkiRJkmYBb/SRJEmSJEmSJEmSJEmSZgFv9JEkSZIkSZIkSZIkSZJmAW/0kSRJkiRJkiRJkiRJkmYBb/SRJEmSJEmSJEmSJEmSZgFv9JEkSZIkSZIkSZIkSZJmAW/0kSRJkiRJkiRJkiRJkmaBFUbdgbksIr4O7F8dfjcznzfC7kxJRKwJ7A5sAqwP3AT8CzgjM88bcFvbAjsAGwArA1cClwEnZOZtg2yr0e59gAcB9wUWVG3fDNwAXAOcnpmLh9W+NGoRsRC4uFb0jczcf0htHQS8t1a0R2Ye06V+1g6PzcxFg7r2METEIuDoWtHBmXnQdPZhNomI3wJ7VYf/m5lvHGF3JEmSJM1j5nmTbss8TxoB87zBMc/rj3meJEmj5Y0+QxIRuwH7VYd3AO+YoP4xwKOrw4k+9C6k9cM7mRmT7GpX1b/jPcBj6fB+iYjTgC8AX8zMbFenh3bWBF4PvAbYuEO1myLip8BBmXnhZNpp0+4OwEuBpwGb9lD/BuAE4IfATzPz2h7bOYYev7/TaarvuzYSuB24FbgauAI4D/gH5et26mTfI5Jml4hYDGxWHU4UMr0VeBxlpcHXRcTXM/O04fZQkiRJklqZ5/XdjnneCJjnSRoW8zxJkmYPt+4agohYDjgUGBusfz4zJxpQzSgRsWJEfAE4Hng83W8KezDweeCYiLjvJNraCTgXeD+dQwGANYEXAv+IiFf3206jzW0i4lfA34HX0UMoUFkbeBLwVeCKiPhSRGw+lb7MMQGsAqwDbEkJHV4OfAb4G3BZRHwiIu43ui6ORkQsjoisHotH3R9pJsnMfwDfqg6Xp/zOkCRJkqRpY57Xd1vmeXOHeV4H5nlSZ+Z5kiSNljf6DMe+lMEylNk/Hx1hX/oWESsAPwde2XhpKSUoOKJ6/dLG648CjoqI9fpo63HAscBGjZcuqdo4ompzae211YDPRcRre22n0eYrKIPUJ7Z5eSlwKvC7qu0fU2autAt2VqQMes+LiAWT6cs8tDHw/4DzI+Lzft0k1XwQuLt6/siIePIoOyNJkiRp3jHP670t87z5xTxPUifmeZIkjYhbdw1YRKwIHFIrOjwzLx9Vfybpw5RZP3Wfpiyxe329MCL2osz+GZvRsRXwo4hYNNGSrtXSsd+l7J095kLg1Zl5VKPuOpSv6+vqfYqI85p1J2jzQODgRnFSlu79CnB8Zt7S4dz7UPac3ZsyC2jMCszfn6V2s59WpeyJvgDYBngEJTSqhz/LAa8CHh8RT8/M04fbTUkzXWaeExE/Bp5dFX0wIn7l8uCSJEmShs08zzxvnjHPkzQQ5nmSJI2OK/oM3vNoHSwdOqqOTEZEbAO8sVH85sx8QzMUAMjMI4HdgItqxY8CnttDc/8DrFs7vgDYtd1APzOvz8z/At5eK14O+FRELN9DW0TEPiwbCpwF7JCZ+2TmbzuFAlUfLs/Mr2fmkykzvL7bS7tzWWYubvM4OzNPzMxfZ+YnMvN5lKWUnwuc0rjE5sAfqved5pHMPCgzo/Y4ZjZcu48+HNPow0HT3YdZqv43c3vaz9SUJEmSpEEzzzPPmzfM8zRZ5nnqwDxPkqQR8EafwXtz7flJmXnqqDoySW+n9X3xu8z8RLcTMvNK4CWN4g92G7BXezo/p1F8QGZeNUFbHwGOrhU9ENiv2zlVe1sBX2sUHwfsVu0l25fM/Ec14H0a0LXPgsy8MzO/B+xMWfq6fkf/+pRZY6uNpHOSZozMPBo4t1b0llH1RZIkSdK8Yp5XmOfpHuZ5knphnidJ0mh4o88ARcQujO/lDfDNUfVlMiIigOYeqh/r5dzMPBY4uVa0ObCoyylPpvX99+fMPL6Xttr06YAezvkQsEbt+Cpg78xc0mObbWXmz4EHATdN5TrzRRUQvA14X+OlrYH/HkGXJM08364936MKdiVJkiRpKMzzzPPUnXmepB6Y50mSNM3m6z7Ew7J/7fndlH2iZ5MHUmZjjLkDOKaP838DPLx2vDfw+w51H9U4/m0f7fye0reVquNdI2KjzLyiXeVqGdmnN4r/KzOv7qPNjiaataS2DgZ2Bx5TK3tjRHwsM2/s50JVoPUQyn7yGwCrA9cAl1H2aJ90aFNdextK+HMvYE3gLuAW4ArKEtdnZOYdk21jCn1bk/IzuyXl53Z1SkB1HXAG8I/MvGsI7Y59re9D+T33L+BPmfnPQbelcRGxPrArsAmwNnAtcA5wYmYuneK11wYeXV17Lcp7+1LKz8+Urj1J36N1Wfb9gXeMoB+SJEmS5of9a8/N88zz1Jl53hSZ580v5nnmeZIkDZM3+gxItaztPrWiUzoNVGewTRrH52fm7X2cf3rjuDmbqFtbZ/TaSGbeHhEXUAZFUGYSPZFll/Id80Ygasf/ZPaFNnNKZt4dEQfTGgysCTwf+GIv14iI+wLvpARQ63eotjQifgccmJl/7bV/EbEW8DbKMtLN92rTHRHxF+DHwCcz855ljCPiMNovRb1ZRGSb8jHfyMz92/RrO8re6I8HHgp028/+poj4JvCxzLxogn9DV9Xvt1cDr6OEAk0ZEX8C3paZf+rxmgcB760V7TGovbd7vXaX70+/Ns/MxY1rL6J1WfKDu+3rHRGLgc2qw0syc2FVvg3wQcrv0xXbnHpjRHwc+Ghm3tpPp6sl1z8KPLXDta+JiMMpPz+3RMT+wNdrrx+QmYf102YvMvOciDgf2KIq2heDAUmSJElDYJ4HmOepR+Z55nnmecv0ZTHmeYB5niRJo+DWXYOzK7BO7fjoThVnsHUbx0v6PL9Z/77VneXT0daDutTdq3H89WHMjFB/MvM44NRG8dN6OTci3g6cD7yKzqEAlMHOE4G/RMRHqhk9E117e+Bs4F1MHApAmYm2O/Bxug/UpyQiHkoJ395NmWk3UVtrUgbzZ0TEC6fQ7hqU2X2foX0oACV42w04PiKayzhrkiLiAOCvwDNoP3CHMmPnYOCoiFjQx7WfB5wJPKvLtdcH3gScHBFb9nrtAan/Dd00Irr9jpckSZKkyTLPM89TH8zz+mOeN/+Y593DPE+SpCFzRZ/BeULj+I8j6cXUNJcrXbnP89vVfyBw4jS09cB2lSJiU2Bho/jYPtvS8BwF7FA73jUioj6Lpi4ilqPM9GrO2ribMmheTFmGdwPgEZQlUaEMXN8KbEjrktzN668LHElZ1rfuSsostWspS/2uCdyXshf5Kp3/eQPVvDEzgYspAcmNwFJKOLktsGmt3qrA/0XEbZn5g0m0+x3gcbXjfwAXVM8fAGxfey2Ad0fE8pn5zkm0pUpE7AN8lfHZi5dQ3oM3UN7fO1Peh2N2o8yee24P134O8E2WDZcuAs6i/AxtTPkZWpmy3PXPgEMn96+ZlOOAV9SOn8Cys0wlSZIkaarM88zz1D/zvN6Z580j5nnmeZIkTSdv9BmcnRvHp/ZzcmYuGlhPJu/axvFGfZ7frv5WtA8GBt1Wp5kJuzaOk3JH/bSaId/fZcyAfjXfGwsog9pLOtR/D62hwO3Ah4BDm3u0R8QKwIsoM3PGZuftFxEnZman5YTfSmsocCrwusw8oV3lqo1dKDOXDmhT5S3AQdXz4yn7YANcTpk11MnNHcpvBY4Afgr8PjPb1quWBD6Q1uXHvxYRx/W5B/3TGP/a/Y7ytTi30dZWwGdpDQ/eERFHZ+ZRfbQ1CvXvT69eW5035mbKXuqDtD7wDUoocBzwlsw8uV4hIlalfI//u1b8nIj4bGZ2DKarJbK/TGsocBrwmuYyzdW+8W+vHltV7fVsbLniSTq1cbzLFK4lSZIkSZ2Y55nndTRDvr/LmAH9Ms9rzzxvepjnFeZ5kiTNc97oMzg71p4vyczLRtaTyTuncXyfiNikj39Luw9unZb6PRt4dO14Z+ArvTRSzerZuMd2mvWuzMwbe2lH06L5noMOwUBE7ETrwOR64LGZ+fd2F87MO4GvR8QJwJ+A9aqXPhwR387MdoO5p9eeX1dd/7pOna/a+CPwx4h4T3Vcf/0a4Jqq//XX7mzuAd2D84D7ZOb1E1XMzDMog8SDGN/bek3gNfQ3EB4LBb4HPD8z727T1rkR8QTKTKF6EPGliNii+TWZSerfn15Uy+O+uVZ0B/CMzGwGnVO1evXfbwP7tfsaVvt3v6MKCN5Qe+kVdJ+B+lHK8sBjTgT2ahcyVT8j746I0ynf327Lag/auZSv70rV8SMGdeGI2JAyi6of9x9U+5IkSZJmFPM88zz1zzyvd+Z5A2aeB5jn9co8T5I0pzWXjtQkRMS9aR2Ydpq9MKNl5pWUD2N1L+rl3IhYnbI3bNOabcpg2eV2nx0Rq/XSFvDiPtqZ6t7hGq52g9xOH9jfQ+vvrBd0CgXqMvM8yt7WY9YGXt6h+ma150d3CwXatHNbr3UnIzNv7CUUaDiEsjTvmBdMounLgJe2CwVqfbsLeAllZtOYhfS4R/tsEBF7AYczvvTu3cALM/P3Q2ryAuBlPQQrh9C6dPpjOlWMiI2BZ9eK/gPs22km2ZjM/C49BreDUv276++n+/TxN2Iir6Esm9zP46cDaluSJEnSDGGeZ56nSTPP6/365nkjZJ5nnjegtiVJmpG80WcwFjaOZ+PsnzHfbBy/LSLu07Zmq/fRfhZOpwH7L2kdpC+gh5kJ1TKVb2nz0vLVnfBN6zWOb5iojUZ710RE9vBY3M91dY92A91lvo8RcX/gybWiYzPz13208wNaA7teBqwb9nH9GakazP+4VvSAiOh35sOHJxo4Vm3dDHy4Ubx/n23NSBHxCOBHwIq14tdm5veH2OzHq1k+XVXhVX2J3o2rGS7t7E3rSn7f6mMm2vspYch0av4tXTjN7UuSJEma2xY2js3zxpnnqRvzvCEyzxsM8zzAPE+SpDnNG30Go/khrN+79GeSz9I6eF4A/LpbOBARbwLe2OHlth8kqyUk/7dR/JaIeEO7+lU7mwC/ofOyvtnpXM1Y7X4Htfs+Pq5x/N1+GsnMpHXW2U4RsVKbqvWlh3eLiOf0086oRMTKEbF+RGwWEQvrD8o+4HXb9HHppOwh3qvv0Pr92y0iolPl2SAitgZ+xfjyuwAHZuYXhtz0L/uoe3bjuFMwsGvj+Hu9NpCZlwIn9dGnQWj+LZ31YZ0kSZKkGcU8zzxPk2OeNwDmecNjnleY50mSNLetMHEV9aC5/OCEd23PVJm5JCJeAvywVvwg4OyI+ALwa+BflFkaOwAvBXav1b0M2KR2vKRLcx8Ensj4Xq0BfCoi9ga+CpxK+VpuXNV7NbBGh3Zu67DUanOp1k6hgkZjQZuydj8/uzeOr6oGvf34T+35KpT31eJGnW8DD62eLwd8NyL2p8yM+00/S/8OU0RsBzwXeCSwLf3ttbzOxFXucWG173VPMvOaiLiI8f2P1wXuB1zYR5szRjXj8EhaZxJ+NjPfN+Smb87Mf/ZRvzmA7vR77sGN47/20QbAycAufZ4zFf9pHK/etlb/Pgf0O3vr/rjcryRJkjTXmOeNM89TPxa0KTPPm4B53vQwz1uGeZ4kSXOUN/oMRvPrONEerDNaZv6omonzScZnaKwJvLV6dPJpygfS/WplS7q0c0dEPItyd/32tZd2Z9mBYN21lEDitz20c23juN9g4CHA8m3Kd6bMdtDUtBukXt2m7L6N4x8MoO11WTYY+CxlOdSda2VPrB4ZEWcCJwInUJYbbp4/VBGxGfAp4BlTuEw/PwPnTeL65zMeDECZtTHrgoGIWI/yO6b+3jsCeP00NN/vLNKljeMV29ZqDZBuzMwlfbZzaZ/1p6r5t7TTv6svmXkVcFU/58zyiWySJEmS2jPPK8zz1C/zvD6Y500f87y2zPMkSZqj3LprMJozFtrtLT2rZOanKYOhc3uofjPwWspyv80lga+coJ3LKctPfpFlP9y2czTwMOCWHtu5onF874hYq4d2xvr3z8xc3Hx0aU/9eWCbskvalDX3Zh+EZfabz8zbKcsKfwm4q/FyANsBLwcOAy6OiNMi4v9FRHMW4MBFxDaUUOIZU7xUP7/3b5zE9W9oHK87iWuMVESsTgks68si/xZ4cbVs9LANa+/sBbXnN03i/Mm8H6ai+be0+XtfkiRJkqbCPM88T5Njntcj87zpY57XkXmeJElzlDf6DEbzw9KgliMcqcw8krKM6LMpS++eTVk6dylwOXA88BZgi8z8XPWBeevGZSZcSjIzb8nMVwFbAe+iDP4vowQuN1XtfgPYE3hsNTBv7kvcqZ0TGsfLATtO1CdNm50bx9d1WOK03f7bU9X2lv7q/fhKYAvgvZTlTTvN6tse+ARwfkTsMYQ+AhARK1Bmn2xUK74N+D9gf0pYthFlKewVMjPGHsABU2h6EIPg6RhID0xErEhZ6vwRteKTgGdnZi/h5Ux2e+35ZH6mhvFz2E3zb+l0BxOSJEmS5jbzPPM8TY55Xg/M86aPeV5X5nmSJM1Rbt01GM2BzEZta81CmXkX8KPq0VW1/219n+3Lqxk+vbZ1MWWf7w/2UL25r+xJHa55aUQsBhbWih9NCR80eo9rHDeDnDHXAFvWjjfOzObsroGq3o+HAIdUM0IeDuwGPIryHlq53h/gVxGxKDPbvhen6Fm0Lod9AfD4zLyoh3N7nvHWRr9LY7c7p99la0cmynquhwOPrxWfDTw5M+fC7JPrGR9srx0Ry2VmP7ONpns218aN4372OZckSZKkiZjnYZ6nSTHP64153jQwz5uQeZ4kSXOUK/oMxmJa73LfpEO9ue6xjeNjhtFI9eH9MY3iY7uccmTj+ICIaLdPt6ZRRCwCHtwo/lmH6v9uHG/ZttaQVLOCjsnMD2Tm4ylLD7+C1qWkVwE+PqQuPL1x/IoeQwFYdnDVj8l8nbdoHPe1d/KIfRp4Xu34n5QA5toR9WfQ6stor0T/398HDbAvvagvHX8byy7dLkmSJElTsRjzPDDPUx/M8/pinjc9zPO6M8+TJGmO8kafAcjM22jd+3rT6djjdwZ6aeP4K0Nq5zG0zug5NjPP71L/U7QGN5tSZlRoRCJiOcoyunU3UpazbedPjeO9Bt6pPlRBwZcp+9HXZ4bsGhEbdjptCk3WB9u30F/otusU2r1/RKzfa+Wq7v1qRdcBvQYYIxURBwKvqxVdC+zVYenp2erPjeOel6euwtRHDrY7XdtbnxLAjfnHNO2nLkmSJGmeMM+7h3meemKe1zfzvCEzz+vOPE+SpLnNG30G5+Ta8+WA7UbVkVGIiN2B3WtF52bmMUNq7u2N4y92q5yZZwM/aRR/JiI2GGSn1JeDgEWNsk9k5s0d6v+2cfyiiFhl0J3qV7W//B9qRUFraFVX30955Q51OllQe35jrwOkiHgAZXniyQpaZ8RM5Pm07pV+wmwYzEXEq4CDa0W3AE/KzHNG1KVh+V3j+GXVjMpePA2494D7001zduBfprFtSZIkSfOHeZ55nnp3EOZ5/VhQe26eN2DmeT0xz5MkaQ7zRp/BaS41+4iR9GIEqtlOX2gUv2tIbe0H7FkrOhX4fg+n/jdwU+34XsAPImIyexZrkiJihYj4MPDuxktnAR/pdF5mnk7rz9h9gXcOvoeTcmfj+Pa2tWBJ7fn6EbFiH23U98XeMCLW6fG8jzD13/Nvj4g1JqpU1Xlbo/gbU2x76CJiH+DQWtFS4FmZORcHokcCF9eOHwq8fKKTqu/tsJax7qT5N/SYaW5fkiRJ0vxgntfKPE/LMM+7h3neDGGeZ54nSZK80WeQftU47nkJxZkmIlboo+4awC+BbWvFP8zMHw6hrWcBX64V3Qm8JDObA7NlZOZ5wP6N4kcBx0fEZGZr9Towm5SI2D8isvZYPMz2hq0KBPYGTqQMHuuzDq4Gnp2Zt05wmXfRulzueyLidZ0qd+nLThHxkDblm0bEfhHR8+yciNgIeFyt6A46L217du35CvT3O+K02vPlgbf20LeDgWf20UYnmwBfrZZn7tTWcsBXq7pjFgM/HUD7QxMRjwW+yfjfwgRenJlHjq5Xw5OZdwMfaBR/NiI6zvKqltz9FbD5MPvWRv3nYylw1DS3L0mSJGl+MM8bZ543ReZ5bZnnFeZ5A2KeB5jnSZIkyodTDUBmXhERJwE7VUV7RMQKvQxaByEiFk7y1Nsy88pG2Ssj4tnA4cAvM/PqNu2tATyb8iHzPrWXFgOv6aP90yPil8APgZOqD67NtrYD3gHs23jpnZn5914byswfRcS7gffXircDTouI7wFfA47vNECtZmzsAbyIsqTpvNfhfbcKsDZledptKD8TjwY2alP3IuBpvSypmpknRMRBtC7J+pmIeDLwYeC4Du+fALYCngrsAzwcOABovnfWBQ4DPhIR3wd+DPyp3fuhuubjgM8Ca9Ze+lFm3tSsXzma1nDq6xHxAeAkygyfet9vzsxrasffpXWmxjsi4m7gQ83lkSNiK+B/GA8FrgYmu6z19ZQQ7DnAgoj4rypkq7e3JeXrsGfj3FdO1++/yYiI9ShLgK9UK/448OdJ/D69bCb/W+sy86vVrKfHV0UrAt+JiAOA/wPOBP5D+XndE3gV5WcjKbMtnzPsPkbEqrQuUf2HzLxx2O1KkiRJmn/M8+6xGPO8ecM8zzzPPA8wzxso8zxJkqafN/oM1uGMBwPrUAaR03XX8sUTV2nrWJbdWzkofd8DyIi4GDiXMkhYjbKv60Np/UA91oe9MvOqPtrfAHhz9bg5Ik4HrgBuq17bEtiszXnvz8yP9tEOAJn5gYj4N/BpYNWqeDnKvsXPA26PiDMpg6nrKF+LNYFNq760mx1yG/D1fvsyR0z2fXcX8CXgHZl5Q68nZeYhUfZir8/8eUL1uCEi/k753i0F1gI2BB4ITLhUbc2GwGurx10RcQ5wKeNL9W5A2W+4Odi+CnhTl+t+nxKkjc2S2ZjWJWbrvkEtRMjM30fEr4En1uq8C3hDRPyF8jOzBuU9uk2tztmUZbj/t0u/uvk5sD7wJGAv4NyIOBW4gPKz8QCW3XsZ4H9mwSyaNVn2ffGW6tGvzSmh6GzxPOA3jP+9gvL93avLOe+j/LzXg4Fh7df+RMrfmjEzfsloSZIkSbOaeZ553nxjnjfOPG+ced7MZp4nSZJaeKPPYB0BfIzxAec+zP7lCQO4X/Xo5mfAy9rNFurDGsAuE9S5HnhNZh4x2UYy8ysRcTzwCVoHWlAG/g/t8VK3UmZmvDczL51sfzpYpXF8fdtas8+/KF+zz2ZmpyVxu8rM/4qIk4HPUAb/Y9Zm2ZCrnbuBXsOI5SnLWG87Qb2zgKdn5hWdKmTmrRHxTMqsk/t0qtfFvpTfJw+rla0BPKZD/VOBp7DszJx+JGUQ+VPGl17doXp0qv/BzGzu2a4ZJDOXRMSelN+BL6V16e2mW4H/qmYOvbrxWqfZblNVDx+up8zGkyRJkqRhMc8zzxsU87wOzPPM8zQ15nmSJKmp4x6t6l9mXkfrncrPrZbEnW2Op8xWmGgweifwa2DPzHz6JEOBT1GWXF1midaGfwKHAPefSigwJjPPycwnAQ+hLFPa68D+Osqd8y8D7p2ZBwwhFADYtXH8ySG0MQwJ3E6ZLXMBcBzwFeD1lMBlk8x802RDgXsayTycMivrnZTZaRO5DfgDZS/sTTOz3UDjTEpQ9Jnq+UTvSYC/UWYKPTgzL+ih33+lzEh6FSUguAC4kTIjaqJzlwC7U34OrutS9Vzg7cDOmXn5RNftod2bKDND3lT1t2014E/A7oYCs0Nm3pSZL6f8DvwYZd/4ayk/v5dQfnbfDGyemV+tTlvQuEzPs/d6VS3B/Ixa0Rcy87ZBtyNJkiRJY8zzzPMGyDyvWyPmeeZ5mhLzPEmSVBeZw1qpb36KiC2Acxi/ieqVmfmlEXZp0qp9i7ekDGQ2ocy2SMqg7zzKHtwDuQM8ItaifEDdnLKE6iqUO88vB07LzLMG0c4EfdgEeBBlwLmAspTxTZR/77XAmVMd0PbRl38yviTsucC2mTnh4HG+ioiNgEdQluldl/LzdxNwJeXrd25m3tHnNdeizPzZHLgXsDplCeEbKcu6ntptxs8wRcTKlGVat6UsK34z5d96dmaePuS2d6Tskb4xJTz5F2Xv82EEZJpBIuL/gBfWirbLzDMH3MabKUEFwB3AwlH9nNVFxLbAGWPH+7AR6y6z2v3sdR138H1avswD/95KkiRJM5l53qTbMs9r7Yt5Xh/M88zzNHzmeeZ5kqS5yxt9hiAiDgdeVB2eTRnU+YVWTyJiS1pntbwgM789qv5IUhUUXwxsVhXdAqw9yMAyIlakzDLbtCr6TGa+flDXnwqDAUmSJGnuM8/TVJjnSZppzPPM8yRJc5tbdw3HgZQ7lwG2AZ45wr5o9qnv0XwWZa94SRqlJzIeCgCcPIRZiS9iPBS4GXj/gK8vSZIkSd2Y52kqzPMkzTTmeZIkzWHe6DMEmbmYslf1mPdGhF9r9aoeDBycmb3sLS1JQxERawKfbhQfPuA2VgLeWSv6n8y8apBtSJIkSVI35nmaIvM8STOGeZ4kSXOfg9XhOQQY2+N2e2C/EfZFs0S1nOai6vAM4Puj642kuSgidomIz0XEpj3U3Rw4Brh/rfjfDH5m4mtrbZzL+L7ekiRJkjSdzPPUN/M8ScNmnidJkppWGHUH5qrMvCUi9gX2rIpWHGV/NDtUe79vOOp+SJrTVgZeDbwyIo4Bfgv8DbgSuA1Yh7JM/eOBfVj279cBmXnrgPt0F3Bw9fyXmXlHt8qSJEmSNAzmeZoM8zxJ08A8T5IktfBGnyHKzBOAE0bdD0mS2liOsrT4YyaqWLkLeFNm/nrQHcnM5lLCkiRJkjQS5nmSpBnMPE+SJAFu3SVJ0nxzM3B7n+ecDjzRAbwkSZIkSZI07czzJElSC1f0kSRpHsnMv0bEBpSl6B8JPBhYCGwArEoJDa4HLqPMYj0SOLJailySJEmSJEnSNDLPkyRJTd7oI0nSPJOZNwE/qh6SJEmSJEmSZjDzPEmSVOfWXZIkSZIkSZIkSZIkSdIs4I0+kiRJkiRJkiRJkiRJ0izg1l2SJEl9eNzCBSxcedVRd2NgFt9+K99ffMWouyFJkiRJkiQNxa7rrsqmK6wy6m4MzKV3Ls/3rxt1LyRJo+SKPpIkSZIkSZIkSZIkSdIs4I0+kiRJkiRJkiRJkiRJ0izgjT6SJEmSJEmSJEmSJEnSLOCNPpIkSZIkSZIkSZIkSdIs4I0+kiRJkiRJkiRJkiRJ0izgjT6SJEmSJEmSJEmSJEnSLOCNPpIkSZIkSZIkSZIkSdIs4I0+kiRJkiRJkiRJkiRJ0izgjT6SJEmSJEmSJEmSJEnSLOCNPpIkSZIkSZIkSZIkSdIs4I0+kiRJkiRJkiRJkiRJ0izgjT6SJEmSJEmSJEmSJEnSLOCNPpIkSZIkSZIkSZIkSdIsMKNv9ImIr0dEVo8jRt2fuSwiFkTEkyLi5RHxjuq/T4qIBQO6/qoR8dCI2Dci3hAR76r++6KIeEhErDCIdiRNXkQcVPudmxGxaIhtLa61s3iCuvs3+rX/oK49LBFxWKPPC0fRj9kgIhZGxG3V1+muiNhx1H2SJEmSNHnmedPHPE+Sed7gmOf1zjxPkqTRm7E3+kTEbsB+1eEdwDsmqH9M7QPYMRPUXdj4wFZ/bD2FPh/e4ZqH9XGNFSLiwRHxsoj4QkScEhF3TPZ6PbT3kIj4MfBv4JfAl4APVv/9JXBlRPw4InaYxLUfGhGHRMTxwA3AKcC3gE8B76/+ezjwN2BJRHw1Iraf8j+qt741BxrHTOIau0bE9Y3rXBMRD2/Ua77f9h/Uv2Mq+u1Xm0Fju8fSiLg5Iq6IiNMi4mcR8dGIeG5EbDxN/zRJIxYRi3oNmTJzMfDZ6nA54HMRMWM/n0iSJEnqzDzPPG+YzPPM8yQNj3meJEmzy4z8w1t9IDgUiKro85l58TQ1f8BkToqItYBnT7bRiHh1RPwJuBE4Ffgy8ErgocCKk73uBG3+N3AS8AxgpQ7VVq5ePyki3tbjdVeJiAspQcB7gN2Y+N+wOvAS4G8R8aGIGMq/eVAi4vHAUcCCWvFlwCMz8+SRdGpmWIHyvbw3sD3wVOAtwBHAZRFxYkS8MiJWHWEfp12bQdJBo+6TNMN8gPL3D+ARwP6j64okSZKkyTDPM88zz5u1zPPaMM+TJmSeJ0nSCM3IG32AfYEHV8/vAD46jW2/KCKWn8R5zwNWm0K7jwd2AaZlwBQR7wT+h9YB+63AccB3gT8Ct9VeWwn4cES8tYfLrwDcr015AucARwLfBn4GXNSoszzwduCImKHL/0bEcyh9r3+/zwd2z8yzR9OrWSGAnYEvABdFxItG3B9JM0RmXk/5HwJjDoqIVUbVH0mSJEmTYp43ZOZ5k2eeN2nmeZLaMs+TJGm0ZtyNPtXMj0NqRYdn5uVDbnZp7flGwBMncY2XdLjeVC0BBvrvj4inUJbarfsSsGlmPjozn5eZjwI2Bb7SqPfhiHhCH83dBfyaEpxsmJnbZObjM/MFmfn0zLw/8DBKIFH3LOCgPtqZFhHxCuA7tM6YOpUSClwykk6Nzg+BzRuP+wE7AIuAvSnh0x8oAV/dvYHDI+JbEdFp9pmk+eUTjAfS9wVeM8K+SJIkSeqDed4ylmCeN2OY57Uwz5M0SOZ5kiSNyIy70YcygNy8dnxop4oDdF71GNPXcr8RsQ2wU63o55Psx82UmTefpMyC2hJYl2UH55NWzW76GOPLKAN8MjNfmZnX1Otm5tWZ+XLK3tv3XAL4eA+zpG6nfO8WZuaTMvO7zevX2jkFeAxlwF331ojYbMJ/1DSJiLcDX6T15+aPwKLMvGo0vRqpmzNzceNxcWaelpnHZuYPM/OdmflYSsh0EGVv97p9gR+4f+/8k5kLMzOqx8LZcu0++rB/rQ9R7VutLqq/Ed+rFb1ppi/7LkmSJOke5nnmeWPM82Y28zxNmnmemszzJEkanZn4YfzNtecnZeap09Tu12vPnxoRG/Rx7ktrz5cAP55E+68E1s7MR2XmmzLzO5l5fmbmJK7VzYuBrWrH5wLvmOCc/67qjXkg8IIu9W8DHpCZr8vMy3rpVGbeRfk6/rNWvBLwnF7OH7aI+DDwoUbxL4HHZ2ZzsKuGzPx3Zh4MPAT4a+PlpzIDZ3tJGokv1J7fB3j+qDoiSZIkqS/meeZ5Y8zz5gjzPEk9Ms+TJGkEZtSNPhGxC+N7eQN8cxqb/wZlWVoo+1x3G/jeo9p3+oW1ou/Quhd2T6qB0939njcJL24cfzIzb+92QvX6/05wnXr9O3sNBBrn3UprQAOwR7/XGaSIWC4ivgS8rfHSt4FnVH1WjzLzYsoywGc1XvrviNhq2TMkzSeZeSJwUa3o1aPqiyRJkqTemOeZ52GeN6eZ50nqxjxPkqTRWGHUHWjYv/b8bsqewdMiM6+IiN8CT6qKDqB1idtOngLcq3b8NWDhQDs3IBGxHvDIWtEdlAFuL75FCQfGll18dESsm5nXDbCLAH9vHG884Ov3rNpr+v9YdhbSZ4HXD2F21ryQmbdExLOA04CVq+IVgXcC+/V7vYhYA9iN8l7ZgBLwXQWcDfxtKoFbde0HA1sDC4BVKcHfjcClwHmZeVHHCwxRRNwX2Iayj/pawPLA9ZR/+0mZefkQ2lyV8jtkE2DDqr1LgGMys+9AVL2LiO2BbSmzYpLyfT4xMy8YwLW3BnYENgLuBC4HzszMZoA3Xb4PvL16vnNEbJWZ53Y7QZIkSdJI7V97bp43YOZ5/THPGw7zvMEwz5tfzPPM8yRJGqYZc6NPtUf0PrWiUzLzimnuxtcYDwa2j4gdq/2mu6kv83tGZv41IhYOpXdTtydl8DDmlMy8qZcTM/PGiPgb43uXr1Bd77uD7SJ3No5XGvD1exIRqwE/Ah7feOl9mXngCLo0p2TmuRHxbUoAN+a5EfFfmXljL9eIiMdTBg+7Mx5YNV0TEV8FPpyZ1/fav4jYAXgP8GTGw4tOda8Gfgd8MTOPbbzWKTx6b0S8t8tl98jMYxrXWonyfnw28BjgvhP06zxKmPe1qQ7aI2JjynLMzwPWbFPl5oj4JvCuXsPCiFgMbFYdXjLIvbd7vXaX708/js3MRW2ufRitQdfmnfb1johFwNG1ooMz86Dqtf2AtwDbdTj3NOC/M/M3/XY8IvYGDqYs397u9b9Rfna+Vx0fAzx67PXMjH7b7NHPGA8GAPYFuv28SJIkSRoR87xpYZ7XI/O84TLPM88zz2upuwjzvDrzPEmSptlM2rprV2Cd2vHRnSoO0c+Aa2rHB3SqCBAR9waeUCv62jA6NUDND5Yn9nn+nxrH206hL508oHE83eEQEbEAOIrWUCCBNxgKDFRz+eiVWTaIWUZErB8RRwG/oSwF3SkUAFifMsA4PyIe1UunIuJtwCnAs5ggFKhsQNl3+OW9XH8KPkb5HbUfE4QClS2BQ4E/R8T9JttoROwKnE7597ULBQDWAF4FnBMRO3Wooz5ExOoR8X3gMDqEApUHA7+u3re9XnvFiPguZaZN21Cg8lDguxHxxSq8ny4nA7fUjp8yjW1LkiRJ6o953vCZ5/XAPG/amOf1xzxvHjHPM8+TJGk6zZgVfWgdYAP8cbo7kJlLq7vY31gV7RsRb+6y5/V+jH8NlzK9e5BPRvMDYL9LRF44wfUGYe/G8V+G0EZHVdjzW2D7WvGdwEsy8/+msy9zXWaeFhFXUZaMHbMbZbDSVkQ8gPL9aQ50b6IM5v9NmeW2kDKoGbuZcT3gqIh4Wmb+tsv1XwB8uNlV4EzKPsM3UsKCtYGtgE2BYc2CaGremPkfynLGV1T9Wgm4N2WgWB/APxg4OiIeMomluR8AfJSyzDHArcCfKV/nBZSvcf37twFwZEQ8NjP/2mdbGrccZRn2p1XHd1He3/+snj8AeAit770PR8TpmfnrbheOiAB+ULv2mLsoA/JLKe/xLSlLSQO8gtbQfKiqv8UnAo+rih4SERtm5lXT1QdJkiRJPTPPGz7zvAmY500f87y+mefNH+Z55nmSJE2rmXSjz86N41P7ObndUouT9DXGg4F1gGfQeTnb+gyhX2Tm1QPqw7A0Z9dc2uf5zfpbTKEvy4iIh1MGhnU/HmQbE7S/OWXmz/1rxbcBz83Mn032utXyntM1eOzZDOnXn2kdoDy4U8Vq+eUf0xoKnAu8C/hJZt7VqL8RZRnTsZk5KwHfjIgd2u13HRHLAR9pFH8W+EBmXtmhT+sCe1FmAN3Vpsrm1X93Br5TK/9f4FPtrllp2x4lnDsc+CXw93b7lUfEipTfWx9i/Gu1KfA5ylK9/fgIJQC4A3gf8MnMvGdmRjUrZG/Kv+deVfFawLcj4sGZeWuf7U23zSeu0mJV4IeMD5gB/jW47tzj1ZTZa3dRgpmPZea19QoRsRXlvfCIWvGnI2LLzOy2hPHrWTYU+Dzw3ubfsIjYjvIz8GjgHZQ93HtSLVU9ld8vpzIeDATlZ2jSv4clSZIkDY153vCZ53Vv3zxv+pnntWeeNz3M8wrzPEmS5rmZdKPPjrXnSzLzslF0IjNPj4hTav05gDbBQETsRpkBMGamL/ML43fxj+n3bupm/bUn35VW1WDmi43iP2bmdM0A2gQ4Hti4VnYj8LTmPs0aqHNoHaRs2qXuR2ld8vTXwLM7DT4z8wrgFRFxDvDxqnh9ygD3JW1OeRit3/9vZOZ/det8NaPmCOCIiFi1zeuLASJiYeOlJZ32d+7iI8Dr24UBjTaXAt+PiN8BfwB2qF7aJyLemZkX9dHmOpTB6XMz8ydt2rqLshTs3yizNsfCgS2Ad1L2RZ+x+vkeRMQKwI9oDQX+TlnieNDGQoFnZOYv2lXIzHMjYk/gDMaXfn4AZb/337c7JyLWAz7YKH5TZn6yQxtnRMTjKGHI04B1+/2HTME/GsePYEDBQERsSJmt1o/7T1xFkiRJmpfM84ZvQePYPG+ced5omOf1zjxvwMzzAPO8XpnnSZLmtObSkSNRLa9aH2ReMqq+VOqD/D0jYpM2deoDiysp+wvPdGs0jvu9O79Zv9P+vpPxUcrSlWOWUu5Uny73p3VQeDWwh6HA0DVnFLT9sB4RGwMvqxUtBvbuZYZJZn4C+FWt6AXV75ymzRrHP5jo2o12hjrbJTMvnSgUaNS/ntav2XKUmUr9+ky7UKDR1vmUWSt1r4qIXvZEny2+DDy1dnwB8ITMvHFI7X24Uygwpmq7uTT1Y7qc8hJgtdrxrzuFArU27gT2pyzvPJ2anwO2HOC1X0MJVPp5/HSA7UuSJElzgnnetDHP68w8bzTM83q/vnneaJnnTS/zPEmSptGMuNGHsv9u3Uhm/9R8m7LEK5Sv0X71FyNideA5taLDqw9PM10zGLitba3OmgOf5vUmJSJeAryhUXxQZp46iOtP0nJAz4MwTVozGFhmFk3lVZSlesccnJn/6aOdj9eerwQ8oYdzNpy4ysyWmafQOsDatc9L3AG8v8e2fgz8rVa0PvDkPtubkSLio5TB8ZgrgL2GuMf0rbS+Z7tphgcPaVuraAZDvX5vr6cs+Tudmp8DFk5z+5IkSZImtrBxbJ43HOZ5vTPPmx7meUNknjcY5nnmeZIkzXUz5Uaf5gfwnvcNHYbMXELrXtL7N6o8h9ZB8deH3KVh6bbv6yDqTygingB8oVH8C+B/Bt3WBK6hzDoasx7w+4jo9iFbU9f8HdTpPbZn7fld9Dk7h7KMcz28e2SbOuc0jt/RYabQjBLFGhGxUUQsbD4os9nGbNPhMp38trmX9AS+3Tjevc/2ZpyIeBvwllrREsrMn4uH2OyJ1TLSE8rMS4B6SNY20KoC7e1rRZdn5p/66NP3+qg7CM3PAbM+qJMkSZLmIPO80TDPG2eeNxrmeVNknjdc5nn3MM+TJGkOW2HUHais1jge6pKZPfo643dLPyAiHpmZf6yOX1qrd2JmNgcUM9XNlD16x3SabdFJs/7NU+lMtS/6D4EVa8XHU/YPHngIMYEzgU8C36/1Z11KOPC4zPxbxzM1FQsax8v87EfEKsCOtaJ/AutHxPp9trWEMisF2uzPm5mnR8TpwIOqogcA50TEYZQg4s8zYaZfRKwE7AU8C3gosDXQ65K660xcpcVJU6z/8D7Pn1EiYn9al9K9FXhqZjb3mx60s/qsv4Txv6Nrd6izHbB87fivfbZxPnBDl+sPWnOG3+oDvPbnKL/r+3F/XO5XkiRJajLPmx7meZ2Z543Ggsaxed4EzPOmj3leC/M88zxJ0hw2U270afZj5B++gd9Rlsgc2+f3JcAfI2JLYLdava81T5zBZkwwEBE7Ar+kNRT6C/DkPpdwHZjM/GlE7E35wDi2rOw6wO8iYq/M7PeDtCbWHKhe3abOvWkNjxYCU519sW6H8lcARwOrVMdrU5ahfgNwS0ScBJxICbBOyMybptiPvkTE0ykB1uaTvES/g7rz+qx/fuN41s7aiIinUfbxHnMnJbQ8fhqa73cWbH324ood6jSDtOae2V1lZkbEP5m+YKD5OaDTv6tv1RLNfS3THBGDal6SJEmaS8zzpod5XhfmeSNhntcH87zpY57XyjzPPE+SNLfNlK27mnf99ztgHbhqBso3akX7RMQalIBgzH+Y/uUPp+KGxvEGfZ7f/JC/ZDKdiIjtgSNp/YD5d+DxmXnjZK45KJn5M8rMittrxesAR0XErJ7NMEP9f/buM0y2otzb+P2QMxsERETYZAyHIIoCoiAKHgMmgmIAzPqajlnUAxhQMGfUIyAGUMSAoAioICoYUFAUkOAGAygIiBtB0vN+qDXO6rW7Z7pnOs3s+3ddfTG1utaqmpme3l1/VlU9oFFuN1i51wDaXb3dwcw8nxL8/arN06sCjwbeAnwHuD4ivhERjxlA/5YQEa8GvsHMQwGAXkc3vf49Nt9jOgUwYy0idgW+zGRoncALMvNbQ+rCPQO45oJGeSah1jDfn5ufA24dYtuSJEmSumOeNxzmedMwzxs687wumecNj3leR+Z5kiTNU+Nyo0/zw0Y/l/SbjWOZ3GN4VcrSv8+tPf/VUQ9ke9S8O3/jtrU6a9ZvXm9aEfEAyuyq+oDhYmDPai/1kcvM01gyHFhACQceNpJOzV/Nn+dFbeqs0ObYbHUcIFfLOu9AWU73WOCaDlVXBJ5MeV2cGhGDCDAAqF53728cXgQcATyRErCsTRlMLZOZMfEAzplF070uud2sP+wlu2etCi6/xeQsMIA3ZObnOpwyV/y7UZ7J39Ug/hY7aX4OmEv/1kqSJElLC/O84TDP64J53lCZ53XBPG94zPOmZJ4nSdI8NS43+vyxUb7PSHrRkJmLgLNrh46ktW/HDrM/fXBJo7x5j+dvOs31phQRWwHfo3Xm0aXAYzLzhh77MlCZ+W3gKcDttcNrAmdExMNH0ql5JiK2Z8nlR9sto9p8bZxRH/jO8LFwqr5lcWZmPi8zNwY2AvYDPkrZ/73pCcC3I2JQ2yEeSuv79aeBLTLzLZl5WmZekpk3Zebt1ezFujVm0W6vy7ouaJR7XbJ2pCJiE+B0Wr/vozLzfSPqUj81fxe97u8Ow53RtUGj3PycIEmSJGn0zPOGwzyvS+Z5g2ee1xPzvCEwz5uWeZ4kSfPUuNzos4jWO8U3HFE/2qnv2V3/IHUVs7uzfhQubpR36vH8XRrl5vU6iojNge9T9meecDnw6Mz8a4/9GIrMPJ0yw6MeDqxBCQd2Hk2v5pVXNcq3U5aAbmq+PrYcTHc6y8w/ZuZJmfnKzHxQ1YeP07ok647AQf1uOyJWBfaoHboK+H+Z2dzzuJPZBK29/qy3aJR72jd5lCLi3sCZNMLfzHzjiLrUb81ltP+rl5Or1+HCvvVmevdtlP8wxLYlSZIkdWcR5nnDYJ7XA/O8gTPP64J53nCY503NPE+SpPltLG70yczbgctqhzaKiFVG1Z+Gk1lyn1qA49rcaT/uzgTurpV3iIi2exs3VfUeXDt0V3W9bs7dhBIK1O/ovooSClzbzTVGJTPPAJ5E677zqwOnR0QzKFGXImJrytLZdSdk5uJm3Wo57fqsm4UR0RyADlVmXp6ZLwfe1HjqqZ1OmUVzG9O6xOrp3YYCEbEprWFcr3qd7dZcuvnns2h7aCJiDcrMn81qh08BXjiaHvVfZl5B62y67SJiQQ+X2I3hfma4f6N84RDbliRJktQF87yhMc/rkXneYJjn9cQ8b8DM87qyG+Z5kiTNW2Nxo0+l/gFyGeBBo+pIXWbeBpzYOHwPcNzwezM71XK69aVUVwAO6PL0ZwHL18o/zMwbpzspIjaihAL3qx2+mhIK/KnLtkcqM8+i7Jv8r9rhiXBg19H0au6qZhKcTOtg9w7g3VOc9t1GeVwGbJ9tlDfpUK+5n/KKPbSxoFFuF1R2clAPddvZs8e9ypvvJ+2Wbh4rEbESJQTYrnb4XGD/zLy77Ulz1/dqX68IPLeHc1/U575MZ5tG+WdDbl+SJElSd8zzBsw8b2bM8/rLPA8wzxsb5nldM8+TJGkeG6cbfZrL5u44kl609zZg19rjYZk5V/cXPb5R/p+ImHKQUj3/6sbhz03XUERsQPkgurB2+M+UUKC57ORYy8zvs2Q4sBrwnYh45Gh6NfdUs8HOBh7QeOqIzLx8ilM/SZl1NuEVEfHAPndvJpozcZoBwISbG+Velt9t7sW8dTcnRcTGwCt7aKedFYC3dtneU2mdJXgDcNos2x+oiFgWOAF4VO3wRcCTqpmp883RjfKhETHtDLGIeDyw92C61FH9M8DNOANIkiRJGlfmecNhnjcD5nn9YZ73H+Z5Y8A8zzxPkiQV43Sjz7cb5d1H0os2MvP6zPxR7fGLUfdpFj5H67LKWwFHTHPOu6t6E34HfHGqEyJiPUoosHnt8LXA7pl5Vde9HSOZ+QPg8cCttcOrAt+OiN362VZEnB0RWXsc1s/rD1tE3Dsi3gb8EnhI4+lvAu+Y6vxqmdJja4dWovzcmwHDdP1YMSIO6vDckyPiob1cjyVnUFzSod5VlFlOE3aPiOU71G26EqgvgfzEiJhyhmRErAN8DVizyzam8oqIePI07W0OfKJx+FOZ2SkoGRefAp5SK18FPC4ze5llNWdk5tmU2U0T1gbOqmZqthURewBfHnDXmm1uQOt+8t+dh7OxJEmSpPnCPG84zPNmyDxv5szzzPPGlHmeeZ4kSQKWG3UHJmTmtRHxUyb3hN09Ipbrdu/auS4ilgM27PD0gkZ5tYhY2KHuDe32RZ6QmXdHxOsoS1tGdfg1EbEacEhm/r3Wp3UooUF9WdUEXjvVh7Rqn9gzaZ2pcCvwfODOKfreqc+Leqk/SJl5TkT8NyXIWq06vCpwWkQ8qZoptLRo9zoMyjLIawLrAjtQ/qZ3pXVp3wmfB16Qmfd00d5rqmtNLAG6EfCLiPggcHSnWXkRsTKwC2UGwzOqfh3XpuruwKsi4hfASZS/kcsyc4n9uKs97v8f8PbGU21nxmXmHRHxYyYDz42AUyLiaOByWmeWAVw3MQOlOvcbwLOr55YHvhsRz8/M0xv9WpYy0H0fZeZdAjcCvSzXW3cTsBbwlYh4O/ChzPxPMFa193TgI8C9a+ddwfSB40hFxIso70kTFlOWs12px/eo2zPzun72bcAOpsxyWrUqPxD4XUT8H+V97RrK3+qWwH7APpS/68uBf9I6y2tQHtMof2MIbUqSJEmaAfM887wp+ryol/qDZJ7XwjzPPM88zzxvEMzzJEkasrG50adyPJPBwFqUD9Fnjq47Q7Uh8Icu6z69erRzMNPsN56Zp0bEW4F31Q6/CHhOFc5cR1mKdEdg5cbpb2oORtrYjiX3Y12VJWd5dSumrzI8mXluRDwO+A5lEAywCnBqFQ58r/PZ88pUr8PpXAu8PjOnnElWl5mLI+KJwBlMhk4rA4cAh0TEVcCllGVBl6OEEwsps9CW7aFvD6keRwK3RMTFwPWUQdFKlEH9diwZdHwhM5t7j9d9gNaZjY+rHu3sTlkSecJhlAH/RBi1AWWZ6auBX1GChXWAh1LeOyccATyC1qVse/Em4CjKz/KdlJ/z+cBfq2M70BoIANwCHJCZzbBj3GzQKK8GnDWD65wD7Dbr3gxJZl5Zzeg6hfK+BeX9+VXVo53FlIDgI4PvIVRtTfgHBgOSJEnSuDPP64553giZ5/2HeV4r87zCPG+MmedJkqR2xu1GnxMpd65PDEb3ZekJBoYqM4+IiAQOp8wogPJz363DKXcCb8vMo4bQvbGXmT+uwoHTmQwHVga+FRFPzszZvm5XapSb+zrPRQn8DDgG+Hxm3tbzBTL/WC3HezTwrMbTm1aP6dzcQ5NrADt3Ue9o4BVTVagFcofTW1AxMZjbB/gqk+EAwMbVo533ZuZbI+LsXtpq+D1lL/tvUWYirgI8eor61wN7Z+bPZ9GmBiwzv1ctT/5/LBniNv0a2C8zL6tm00345yD6FhFrAnvWDp0wT/dXlyRJkuYT87whMc+bHfO8GTHPM8/TGDDPkyRJTcuMugN1mXkjrUtl7l8tQasByMx3U2ZcfZPW/Ybr7qie3zEzjxxW3+aCzPwJ5QPsLbXDK1OWcN1rptetPnxvVzt0E9PM6hojdwO3UWaI/AY4FXg/8Ezgvpn58Mz89ExCgQmZuTgznw1sC3yB7kKTv1D2od8XWL9DnXdTlrX+WtX/6dwGnAzslJkv7WZZ8sx8F2Ug9h7gh5TZdl39LKrZRQ+h/D0usfxw5S7gu8AemfmGbq7bRbs/ovT5OFr3Fq9bTNkfe+vMPL8f7WqwqvDmwcD+wFco+5n/i/J+dglluesnAztk5mXVaQtqlxjUvufPAVac6Cbw4QG1I0mSJKlPzPOGyzxvdszz2jLPm7rv5nkaC+Z5kiSpLtpsVztSEbEFZbnOiZuQXpyZnx5hl5YKEbEWZabDfSn7//4d+DPwk8ycD7NP5oyIeAytM9/elpnvHFV/xl1ELEMZuD4AWJsyeLmdMsBZBFzSab/vaa67MbAVZYbNAspg5V+UPbIvAX4zquVsI+LelCV8N6KEUddTlk8+PzNvGGC7q1bt3o+yN/pNwNXA2bMJezT+ImIlyt/UxIzRX2TmQwfQzm+AB1XFb2Xm3v1uYyYi4oHAxRPlTy28PwtXbK6EP3ct+vdtvHjRJfVDD8rM346qP5IkSZp7zPNGwzxvfJjn9cY8zzxPg2ee15rnfXDtTdlouebCa3PXNXfdzv/ceFX9kHmeJC1lxm3rLjLz8oj4IuUuYIBXR8RnctzuSJpnqsH/aaPuh4DWpVT/jnfATykz7wEurB79vO7VlEHv2MnMv1JmHw273VspM4y09NmJyVAA4IJ+NxARezIZCkwsRS9JkiRpDjDPGw3zvLFintcD87yhtmuet/Qyz5MkaR4bq627av6XyaVn7w88dYR9kYatHgy8LzMHsneuJPXgpY3yeQNo4621r0/KzL6HD5IkSZIGyjxPSzPzPEnjxjxPkqR5bCxv9MnMRcCHaocOrZbzlOa1iFgd2KEqXg98dITdkSQi4vHAvrVDi4Gv9bmNPYBdq+LtwCH9vL4kSZKkwTPP09LKPE/SuDHPkyRp/hvnwfbbgWuqr7cBDhxhX6RheSSTW+odVS2tKkl9ExGHR8SLImLFLuo+EzipcfiYfs5MrIL/99UOvSczr+zX9SVJkiQNlXmelkbmeZIGyjxPkiQ1LTd9ldHIzFsj4gDgsdWh5aeqL80HmXkaEKPuh6R5bWPKkvpHRsTXgR8BvwNupHwuWBfYEdifyRmJE64E3tLn/mwIfLN63A0c1efrS5IkSRoS8zwtjczzJA2BeZ4kSWoxtjf6AGTmj4Efj7ofkiTNQwuAg6tHN64G9s7Mxf3sRGZeAxzWz2tKkiRJGh3zPEmSBmYB5nmSJInx3rpLkiT13w091r8b+BKwY2b+bgD9kSRJkiRJktSZeZ4kSWox1iv6SJKk/srM10XE0cCewE7A1sD9gDWBFYBbgL8DlwLnAF9zj21JkiRJkiRpNMzzJElSkzf6SJK0lMnMK4ArgE+Mui+SJEmSJEmSpmaeJ0mS6ty6S5IkSZIkSZIkSZIkSZoDvNFHkiRJkiRJkiRJkiRJmgPcukuSJKkHRz/tday6/iaj7kbf3HrdH+ADzx91NyRJkiRJkqSBOO1V72SN+2466m70zS1/vgoOPWDU3ZAkjZAr+kiSJEmSJEmSJEmSJElzgDf6SJIkSZIkSZIkSZIkSXOAN/pIkiRJkiRJkiRJkiRJc4A3+kiSJEmSJEmSJEmSJElzgDf6SJIkSZIkSZIkSZIkSXOAN/pIkiRJkiRJkiRJkiRJc4A3+kiSJEmSJEmSJEmSJElzgDf6SJIkSZIkSZIkSZIkSXOAN/pIkiRJkiRJkiRJkiRJc4A3+kiSJEmSJEmSJEmSJElzgDf6SJIkSZIkSZIkSZIkSXOAN/pIkiRJkiRJkiRJkiRJc8CcutEnIo6NiKweJ466P/NZRCyIiMdHxAsj4s3Vfx8fEQv6dP2VI+LBEXFARLwqIt5S/fc5EbF9RCzXj3YkdS8ijqu9x2ZELBxgW/V2zp6m7mGN+rv169qDEhFn1/sxij7MFRGxc+1ntTgiNhx1nyRJkiT1j3ne8JjnSUsf87z+Mc/rnnmeJEmjN2du9ImIXYADq+IdwJunqX92Dx86FzY+SNYfW8+iz8d3uOZxPVxjuYjYNiJeEBFHR8QFEXHHTK/XRXvbR8TXgb8CpwGfBo6o/nsacF1EfD0itpvBtR8cEW+PiB8B/wAuAL4IfAh4Z/Xf44FfAjdHxGcjYptZf1Pd9e2gQQ0mImK3XgY1w9Jrv9oMGts97oiIf0bEnyLilxHxtYh4V0Q8OSLuNZzvTNKotXlPXdipbmb+BDi5Kq4KfHAYfZQkSZI0eOZ55nmDZJ5nniepf8zzJEmaW+bEjT4RsQzwcSCqQ5/MzD8MqfmDZ3JSRKwBPH2mjUbESyPiJ8AtwIXAZ4AXAw8Glp/pdadp803AT4GnACt0qLZi9fxPI+INXV53pYi4khIEvA3Yhem/h1WB5wG/jIj3RMRAvmf13fLAasB9ge2BpwKHAN8A/hoR34uIZ8ZSNsOrzSDpoFH3SRozbwburr7eJyIePcrOSJIkSZo98zzzPPO8OcM8rw3zPGla5nmSJI3QnLjRBzgA2Lb6+g7gvUNs+zkRsewMznsGsMos2t0L2AlYeRbX6FpEHAK8m9YB+23AD4EvA+cCt9eeWwE4MiJe38XllwM2bXM8gUuBM4AvAacAVzXqLAu8EThxaRtMzkPLAo+m/K4viYj/HnF/JI2JzLwc+Ert0HtG1RdJkiRJfWOeN2DmeRoC8zxJbZnnSZI0WmN/o0818+PttUPHZ+afB9zsnbWv7wPMZADzvA7Xm62bgb5+/xHxRMpSu3WfBjbKzEdl5jMy85HARsD/NeodGRGP66G5u4HvUIKT9TLz/pm5V2Y+KzOfnJmbAQ+hBBJ1TwMO66EdDd6HgU0aj80os9QeDTwT+ADwY+CexrmbA9+OiPdGRCBJZVn5CQ+NiKeNrCeSJEmSZsU8bwk3Y56n8WCeJ6mfzPMkSRqRsb/RhzKA3KRW/vgQ2vx99ZjQ03K/EXF/4GG1Q9+aYT8WU2befJAyC2pLYG2WHJzPWDW76X1MLqMM8MHMfHFm3lCvm5nXZ+YLKXtv/+cSwPu7mCX1b8rvbmFmPj4zv9y8fq2dCygDyxMaT70+Ijae9pvSsNycmYsaj6sy81eZ+YPMPDEzX5uZj6AEAR+gvA7qXgd8bOg918hlZtQeu82Va/fQh93q/RhFH+aazLyY1lD4TaPqiyRJkqRZM88zz5tgnjdezPM0Y+Z5ajLPkyRpdObCjT6vrX3908y8cEjtHlv7+kkRsW4P5z6/9vXNwNdn0P6LgTUz85GZ+ZrMPCEzL8/MnMG1pvJcYKta+TLK3qpTeVNVb8IDgGdNUf92YPPMfHlm/qmbTmXm3ZSf4x9rh1cA9uvmfI2XzPxDZr6Wsnz1FY2nXxYRz2tzmqSlz9G1rx8aEY8cWU8kSZIkzYZ5nnneBPO8Oco8T1KXzPMkSRqBsb7RJyJ2YnIvb4AvDLH5z1GWpYWyz/VUA9//qPadfnbt0Am07oXdlcz8a2Y2l0cdhOc2yh/MzOYsjRbV8x+e5jr1+nd1Gwg0zruN1oAGYPder6PxkZm/Ah4JXNd46n0Rca8RdEnSePkGcGut/NIR9UOSJEnSDJnnmedhnjevmOdJmsY3MM+TJGnolht1B6ZxUO3re4CTh9VwZl4bEd8FHl8dOpjWJW47eSJw71r5GGBhXzvXJ9VAbNfaoTuAL3V5+hcp4cDyVflREbF2Zt7Yxy4C/KpR3qDP19eQVX9bzwR+UDu8FvBK4NBerxcRawM7A+sD61CCuOuBCzPzt7Ppa0SsBWwHbAGsCawI3EaZ2Xc1cElm/nk2bcyib5sBWwMbA2sACdwE/IUyW/L6AbS5ANgFuC9wL8rP+Urg3My8q9/tqaj2vd+R8jrcgPJefR3wo5mErm2u/2DgQZS/oduAPwO/ysw/zPbavcrM2yLiVGD/6tBTImLNzPzHsPsiSZIkacYOqn1tntdn5nkaBfO8/jDPW3qY55nnSZI0aGN7o0+1R/S+tUMXZOa1Q+7GMUwGA9tExA7VftNTqS/ze3Fm/iIiFg6kd7P3WKC+F/cFmfnPbk7MzFsi4pdM7l2+XHW9L/e3izQHGyv0+foagcw8OyJ+QOuMrhdExGHdLGddDZT2B14NPJQOq5NFxJ+BjwIfqWaUdSUidqcsab0HrX8jndr4DvCxzLyodnwh0GlgdWxENGe31W2SmYsa7axKCR6fBuwGrDdNv35J2Uf9xGrp7BmLiK2Aw4EnAyu1qfL3iPg08I5uf84RUf89n9PPvbe7ufY0v59efC4zD2pz/bOBR02Up9rXOyIOonW248GZeVxELEN5jb8c2KTDuecCr8/Mn/bS6eraL6Qs7b5xmypZXfvtmfm96pxFtbpXZ+bCXtrswSlMBgMrUV7zU/29SJIkSRoT5nlDYZ6nkTDPM88zz2upexDmeXXmeZIkDdk4b921M2VWwIQfdKo4QKcAN9TKB09VOSLWBx5XO3TMIDrVRw9qlM/r8fyfNMoPnEVfOtm8UR52OKTBaS4XvQHwkOlOiohNgQsoy2g/jKnfx+4LvAf4XURM+/qM4sPA94E9mSYUqLXxAlqDzEE4ATiRsq/9lKFA5cGU5dHPiIh1Z9poRDyFMhNvf9qHAlBmA70ZuDgimn+zmoGIWI/yOnw/HUKByq7AuRFxQA/XXoPyb+rRtA8FAIKyLPcZEdHzzLxZav57/8Qhty9JkiRp5szzBs88T6Nkntcb87yliHleC/M8SZIGbGxX9KF1gA1w7rA7kJl3RsQXKHdgAxwQEa+dYs/rA5n8md7JcPcgn4kHNMpX9Hj+ldNcrx/2aZR/NoA2NBrfpyzhXR/Y7wL8vNMJEbEjcBplSd+6v1MGrzdQluPdgtbgayHw44jYLTMvnKJPh1CWHK67C/g1ZWnfW4GVKaHl1gx36elmAHIL8Dvgb8A/KYP2DYFtqj5OeDRwekTsPMV7Vyc7U2ZeTMy8+wflb/AGyu9gR8oSyBM2Bc6JiEeMYpnYeWRl4FTK7DaAfwO/oCzBuyxwf1rfb5cHjouIizPz11NdOCJWBs6qXXvCv4GfUsLXVSlB7yaU191hEfGX2XxDvaiWA7+CyWD4sRGx7GxnskmSJEkaCvO8wTPP0yiZ5/XGPG/pYZ5nnidJ0lCN840+D2+UL+zl5D4uG3kMk8HAWsBT6LycbX2G0KmD2FO3z5p36l/T4/nN+lvMoi9LiIiHUgaKdV/vZxvDkJlnU+6mHyuj7ldm/jMiLqYMZCds26l+NcPuG7SGAj8F3gac1VwiuJqJ8l7K3yyUAexXqiW7l1jSOiLWBN5aO3Q38A7gw5l5c4c+3YcSYj6Xsqd23Z+YnLmxT9WXCa8HvtrumrVz27mIEjh+OzN/16FPqwAHAO9icqbQgylL9b5pijbb+RglFPgn8Ebgs5l5R62tFSjLmx8JrF4d3gD4XEQ8qptlm0eo/vvp1jrAtyh7X08YxID57VVbt1H2uf9EZt5ar1CFZF9k8n18eeCDlOWpp3IEraHAXcC7gfc2/y4iYhfgE5S/0Y9Q/ia6kpnHAcd1W7+NC5n83lanBBVThh6SJEmSxoJ53uCZ5w3BqHOzTkbdL/M887wRM88rzPMkSdJY3+izQ+3rmzOz0wflgcrM30TEBbX+HEybYKD6ALVV7dC4L/MLsKBR/luP5zfrr9m21gxExPLApxqHz81MZwDNL5fSGgxsNEXdzwL3aZRf3GlWQGZeATy1Wrp3YlbPFsD/UAZeTXvRupTtOzPz8Kk6n5nXUmbIHFvNrKg/dxewCCAibmicekNzz+4uvLybczLzX8D/RcQZwI+A+1VPvTQijsjMW3pocy3KrKc9M/P8Nm3dAXwyIn5FmVWyavXUrsDzKL+jsVT//XQjIlYDvkJrKHA6ZeDeb+tQfu67Z2bbGXGZ+bOI2AO4mMlQZveI2Lx67S8hIh5A6wy3e4BnZObJHdr4cUQ8AjiTsqz2MP2a1hmgO2IwIEmSJM0F5nmDt6BRNs/TsJnndc88r4/M8wDzPEmSVJlqL9yRqe70rw8yrx5VXyr1Qf5jI2LDNnWeV/v6OsoHxnG3WqN8W4/nN+uv3rbWzLwX2L5WvpMll2DV3HdTo9x27+mIeAjw+Nqh84AXdbn052toHVC8PCJWbFOvubfxVDN0lpCZvf799KTXICEzr6GEIBPWAJ40g6bf0i4UaLR1PmUmVt2rZtDWWKpmOn2N1pkz5wNPz8w7B9Ts/3QKBSZUv+N6gBrA7lOc8v9o/Xf/U51CgVob/wSeRe//PsxW89/9Lft14YhYLyIe2MsD2Kxf7UuSJEnzlXne0JjnadTM87q//qIe65vn9Yl5nnke5nmSpHluLG/0oey/WzeS2T81XwJur75ehrJ3939ExKrAfrVDx1d3l4+7ZjBwe9tanTU/KDavNyMR8TyWHFQcNs1ezJqbmsHAym1rLRkKHZKZ93TTQBUefLh2aF1gpy5OXW/6KmPvW8AdtfLOPZ7/V+DjXdb9KK2zAv8rIh7cY3tjJyKWAY4HHls7/DvgCdVsq0H4M2VmWTdObZS3b1cpIgJ4Ru3QPZRlf6eVmVdS/h0cpua/+wv7eO2XUWZO9fL4Zh/blyRJkuarhY2yed5gmOdp1MzzBss8b5bM88zzMM+TJC0FxvVGn+YH8ubgYaiq/Xzre0kf1KiyH62D4m4/0I2bXvff7ft+vRHxOODoxuFTKXvOav5pvgd1ek09pvb1dcA5Pbbzg0Z51zZ1Lm2U31Ut7zrWImKZiFg9IjaIiIX1B2V/7Rtr1e/f4+W/0m3IWdX7SuPwI3psbxx9FNi/Vr4G2Cszb+xQvx++20O4fEmj3CnQ2gpYu1Y+r8cl9Ju/20Fr/rs/H4I6SZIkab4zzxsN8zwNm3neLJnnDZx5XmGeJ0nSPLbcqDvQwSqN8rCXGGznWOCZ1debR8SumXluVX5+rd55mdkcYIyrxZQ9eyd0mn3RSbP+4tl0ptoX/WRg+drhHwH7Z2bfQwiNhQWN8hJ/6xGxGa17eV8BbFwmNHRthUa53bKd36PMYJkYgDwcuDwiPksJBn/V7ayjQapmHD4ReDKwHWWf8m7fy9eavkqLn86g/str5Yd2qjgXRMRhlNkiE26g7G8+6Fmpv+uhbnMAvWbbWrBto/yLHtqYSf3Zas6uWrVtLUmSJEnjxDxvOMzzNGoLGmXzvGmY5w2Ped6s6s+WeZ4kSUM0rjf6NPs1DsvmnkXZY3Ri39/nAedGxJbALrV6xzRPHGNjEwxExA7AabSGQj9jsMtpavSaA9Xr29S5X6P8COAPs2x37eaBzPxXRLyEspf3xMyk9YG3VI+bI+I8yn7i5wLnZ2avy2PPSkS8gLI8a9u9z7vQadDYye97rH95ozxnZ21ExMuAQ2uHFgOPz8zLhtB817NeM/PORki2fIeq6zTKzT2zp2vnxohYTJ+WdO9C89/9Tt/XTHwCOKnHczbD5X4lSZKk6ZjnDYd5nkbNPK8H5nnDY563RDvmeeZ5kqR5bFxv9GnOAuh1wNp3mZkR8Tngf6tD+0bEKygBwYR/MfzlEGfjH7QOunodbDQ/9N88k05ExDbAGbQOWn5FWU7zlplcU3PGAxrldoOVew2g3dXbHczMr1fLTX8C2Lzx9ALgv6sHwOKIOAX4UGb+fAB9bBERHwRePcvL9LpdY69/f/9olJcIYOaCiNiPssTvhDuApw7j91wZxEyzBY3yP2dwjVsYXjDQ/Hf/1n5dODP/Ruv+89PqccahJEmStLQyzxsO8zyNmnlel8zzhsc8ryPzPEmS5qlePyQOS/PD6Lgs8Xcsk3sOr0pZ+ve5tee/OscGss279TduW6uzZv3m9aYVEQ+gzK6qDyAupiyneXOv19PcERFrsOQe0xe1qdpcprcvzXd6IjPPpPTracCJwF87VF0NOAD4WUQcExEDCzAjYl+WDAV+C7wN2IuyX/MCYKXMjPqDHmd6NMx2ie05t0R3RDwG+DyT/z7eAzwnM88aXa/64t+N8kz+rgbxt9hJ89/9ufRvqyRJkrS0Ms8bDvM8jYx5XvfM84bHPG9K5nmSJM1T47qizx8b5fu0rTVkmbkoIs4Gdq8OHUnrUqXHDr1Ts3MJ8NRauTnjYTqbtrle1yJiK8o+yvWZR5cCj8nMG3rsi+aePVjyZsMftanXfC18OjNfPJguFZl5F2Uf768DRMTmwE6UZb0fy5Kv/YMpA/OnDahLhzfKbwPe1eVe92vMot1elwZu1u96ydpxEBEPpfzO6wPgV2TmXJrZ2Unzd9HT/u4RsQy9vx5mY4NGufm5QJIkSdL4Mc8bDvM8jZJ5XvfM84bAPK8z8zxJkua3cV3RZxGtd45vOKJ+tFPfs7v+weoq4Jwh92W2Lm6Ud+rx/F0a5eb1OqoGWt+n7Jk84XLg0ZnZacaF5pdXNcp/oizx3NR8PWw5mO50lplXZObnM/MlmbkZsD1wQqPaU6vZI30VEVvQOlPqh5n5zm5CgWpW0oJZNN/rz3qLRrmn5VRHqQoqv03rUraHZeYnRtSlfmvOBPuvHs/fmv7uqz2d+zbKfxhi25IkSZJmZhHmecNgnqdRMs/rgnnecJjnTcs8T5KkeWwsb/TJzNuBy2qHNoqIVUbVn4aTWXLfWoDjurwbf5ycCdxdK+8QEW33Om6q6j24duiu6nrdnLsJJRSo3+F9FSUUuLaba2hui4jdgUc1Dn+mw9/Qb2n9m9up29fpoGTmhZl5AGXv77qntqvP7Ja8bQ62T+3h3J2YYlnjLjy8x/oPa5SHtQf2rETEhsAZwDq1w5/IzObMq7nsZ7TuFf7IiFi2h/N3n75KXzWXAb9wyO1LkiRJ6pF53tCY52kkzPN6Yp43YOZ5XTHPkyRpHhvLG30q9Q+UywAPGlVH6jLzNso+v3X3AMcNvzezUy2nW19adQXKHsXdeBatd4P/MDNvnO6kiNiIEgrcr3b4akoo8Kcu29YcFhH3YcnZMzcCH2tXPzPvpiwJPWFF4DmD6V3PPtsob9KhXnM/5RV7aGNBo9wumOzkoB7qtrNvRHS1xWNVb7/G4XZLN4+ViFgb+C6wUe3wl4FXjKZHg5GZt9D67+p9gCd0c25EBPDCQfRrCts0yj8bcvuSJEmSZsY8b8DM8zQK5nmAed7YMM+bnnmeJEnz3zjf6NNcNnfHkfSivbcBu9YeD8vMubrf6PGN8v9ExJSDlur5VzcOf266hiJiA8oAb2Ht8J8poUBzGUrNQxGxHfBD4N6Np14zTbD00Ub50CpgGLW7GuVmADDh5ka5l74392LeupuTIuIhwDN6aKedewP/r8u6rwDWq5UvzsxfzrL9gapmlp4GPKB2+EzguZl5T/uz5rSjG+X3R8SqXZz3MmDbAfSnrYhYnrKc9oSLM/Pvw2pfkiRJ0qyY5w2HeZ6GxjzvP8zzxoB5nnmeJEkqxvlGn283ysNeZrCjzLw+M39Ue/xi1H2ahc/RuqzyVsAR05zz7qrehN8BX5zqhIhYjxIKbF47fC2we2Ze1XVvlxIRsSgisvY4aNR9mo2IWBgR7wXOp/U1APDRzJwyWMrMs2ldSno94NvVEq299GP1iGg7yy0inhURzeVFp/PcRvmSDvWax/fsoY2LGuUDI2L9qU6IiE2Bk+jPHszviojmEr7N9h4OvKNx+MN9aHtgqsHnybQuZ/xz4GmZecdoejVwJwJX1MqbA6dFxL06nRARzwI+NOB+NT0UqAcWpw25fUmSJEkzZ543HOZ5Y8g8r5V5XgvzvD4wzwPM8yRJUqWrJRxHITOvjYifMrlH7O4RsVxmNu+4n5eqZTM7DXoWNMqrRcTCDnVvyMzFndrJzLsj4nXAKUzu/fuaiFgNOKR+13VErEMJDepLPibw2mo51k7fywLKoK4+c+FW4PnAnVP0vVOfF/VSf4ZW6rVfNTdn5s197Mu4WtDmZ7QMsAawJrA+8BDKwGtn2t9YeBTwpi7bO5Cy3OfE38V2wK8j4j3AMdXS1Uuo9v/eHXgysC9lWeEvtam6L/D5iDgH+CpwWqfXWkSsC7wReE3t8D3AF9rVz8yrI+IqYNPq0E4R8UXg88AfWHLm0J8m3usy8y8R8SPgEdVzawM/iIiDM/P8Rr8mlkE+AlgXuJ0yS2m1dv3qwk3AWsAZEfFGys/5P4PmiFgBeB7l91gfyP0IOGaGbQ7L4cDjauXrKDNd1qne67q1uNNrb9xk5u1VyPhDJv8eHwVcFhFHA2dRAttVKMvrPwd4bFXvR5SlrO87hK4+plH+xhDalCRJktQH5nnmeVP0eVEv9WfIPG965nnmeeZ55nmDYJ4nSdKQje2NPpXjmQwG1qJ8uD+zc/V5ZUPKgKEbT68e7RzMNPuNZ+apEfFW4F21wy8CnlOFM9dRlibdEVi5cfqbMvP0afq3HUvuz7oqS87y6lZMX2XWHkb3P/+mw4HD+teVsfWq6jETlwOvyMzvdntCFRY+kfK62aA6vBZwJPCeiLgEuIqy5/WKlABtM8rS0vXXzFRLCgewW/X4WET8Hfgt8HdKmLUKZXD/X8CyjXOPyMzfTXHtD9K6ZPEB1aOdTYBFtfIbKcufT7xnbw2cFxGXARcDd1CW5d2R1hDgFcBbmXkw8ErKAH8N4JPAu6v3hBuBe1XtLWic8xfmxlK5GzTK69O653W3Psfs904fmsz8cUQ8l9LvidfwvYC3VI92rgX2B35Sv9TAOgn71L6+rBmASZIkSRp75nndMc/rP/O86ZnntTLPK8zzxph5niRJamfcb/Q5EXgfk4PRfVl6goGhyswjIiIpg9qJ5UFXpgyQ2rkTeFtmHjWE7i2NVmqUm/s6z0V3Uwa3/wecNJPZfJl5UURsT5k5U18uNyj7Mj+g7YmtevlZ3gt45DR17gLekZlvn6bex4EHAi/poX0AMvMnEfFC4NO0Lt+7Fa3Lbk+4m7JP+v9Vod9M/Qh4JmUp74mwZa8p6v8B2CszZxqqaQgy84sRcQNlj++F01Q/GzigCubqwfA/B9G3iNiKErxNOHYQ7UiSJEkaKPO8ITHPGzvmeW2Y55nnafbM8yRJUlO7pTfHRmbeSLlLecL+1RK0GoDMfDdl5ss3KTMK2rmjen7HzDxyWH1bmlT7Md+7duhy4NQRdadXdwP/oswYuJCyROe7gacC62XmHpl5wmyW7M7Mv2XmXpQB+zcoM3Om8wdKIPHflOWH23kVZcbLt+kuPLiF8v60TRehAFm8lPI39mHgPOBvlOV4p5WZxwG7UgZqndxO2ad6x8z8SDfX7aLdk4Edqus2lySecCPwHuBBmXl5P9rVYFWz7x5AWar5VOBqyuvnJsqsss8BewCPzsxrq9MW1C7xjwF1rb6U/K3AZwbUjiRJkqQBMc8bLvO88WCeNzXzPPM8zZ55niRJqovMQa7WN3sRsQVwKZM3Jb04Mz89wi4tFSJiLco+zPelzIL4O/Bn4CeZOR9mo4ytiHgBrR+Gn5OZbfeKFkTEcpTB/uaU1+rqlHDiH5Slfy/JzOt6vGZU19sC2IiyR/nywGLK38JvgYvr+1sPU0RsBOxCWa52eUrA8Bfgx5k5kJkZVbtrVe3el7K3+A3AlcC5mXnnoNrV6EXEZsAVtUNfzcx9+9zGipR/Z+5VHfpoZr6yn23MVEQ8kBKYALD9az7LqutvMsIe9det1/2BX33g+fVDD8rM346qP5IkSZr7zPNGwzxvdMzzemOeZ56nwTPPa83zHnP4l1jjvpuOsEf9dcufr+KsQ1t2EjTPk6SlzLhv3UVmXh4RXwSeUx16dUR8Jsf9DqU5rhr8nzbqfiylHl37+lLgS6PqyFxQzSY6v3r065pJmXk1lrNZMvMa4JoRtHsTc2c2mvqrueT1BQNo40AmQ4HbAGeZSpIkSXOUed5omOeNlHleD8zzhtqued7SyzxPkqR5bKy37qr5XyaXnr0/ZdlQab7avfb14Zl5z8h6IklFcy/68/p58Wom3xtrhz6amX/uZxuSJEmShs48T0sT8zxJ48Y8T5KkeWxO3OiTmYuAD9UOHRoRc6LvUi8i4gHA+lXxt8BXRtgdSSIiXgbsWDu0CDi3z80cCEysnXs98O4+X1+SJEnSkJnnaWlhnidp3JjnSZI0/82lwfXbmVzachvKhwhpvqnP/jnM2T+S+i0iPh4R+0XEstPUWyYiXg18pPHUR/r53hQRq1L+jZ/w+sy8uV/XlyRJkjRS5nlaGpjnSRoo8zxJktS03Kg70K3MvDUiDgAeWx1afpT9kQYhMz8OfHzU/ZA0rz0QeBlwXUScDJwPXAbcDKxImYW4E/BsYMvGuT9hyaBgtjYDPlN9vTgzP9fn60uSJEkaEfM8LQ3M8yQNgXmeJElqMWdu9AHIzB8DPx51PyRJmgfWB/5f9ejGRcC+mXl3PzuRmb8Gft3Pa0qSJEkaH+Z5kiT1jXmeJEkC5tbWXZIkafZu6LH+vykzE3fJzL8MoD+SJEmSJEmSOjPPkyRJLebUij6SJGl2MnOfiNgGeAzwMMpyvhsCq1M+F9wM3EiZlXMO8NXMvHY0vZUkSZIkSZKWbuZ5kiSpyRt9JElayri8riRJkiRJkjR3mOdJkqQ6t+6SJEmSJEmSJEmSJEmS5gBv9JEkSZIkSZIkSZIkSZLmALfukiRJ6sEH4/tsHfcadTf65tL4O7uNuhOSJEmSJEnSgLz1ltPYepV5lOfd8nfOGnUnJEkj5Yo+kiRJkiRJkiRJkiRJ0hzgjT6SJEmSJEmSJEmSJEnSHOCNPpIkSZIkSZIkSZIkSdIc4I0+kiRJkiRJkiRJkiRJ0hzgjT6SJEmSJEmSJEmSJEnSHOCNPpIkSZIkSZIkSZIkSdIc4I0+kiRJkiRJkiRJkiRJ0hzgjT6SJEmSJEmSJEmSJEnSHOCNPpIkSZIkSZIkSZIkSdIc4I0+kiRJkiRJkiRJkiRJ0hzgjT6SJEmSJEmSJEmSJEnSHOCNPpIkSZIkSZIkSZIkSdIc4I0+kiRJkiRJkiRJkiRJ0hww1jf6RMSxEZHV48RR92c+i4gFEfH4iHhhRLy5+u/jI2LBgNpbLiJ2jIiDI+INEfHWiHh1ROwbEdtGxHKDaFdSZxFxWO09NyNitwG2tajWzqJp6h7U6NdB/br2oETEcY0+LxxFP+aCiFgYEbdXP6e7I2KHUfdJkiRJ0syZ5w2PeZ4k87z+Mc/rnnmeJEmjN7Y3+kTELsCBVfEO4M3T1D+79gHs7GnqLmx8YKs/tp5Fn4/vcM3jerjGctXA+AURcXREXBARd8z0el20t31EfB34K3Aa8GngiOq/pwHXRcTXI2K7PrW3RUR8Gvg78FPgGOBI4B3AB4GvABcCt0TEGRHx1H6026YfzYHG2TO4xs4RcVPjOjdExEMb9Zqvt4P69X3MRq/9ajNobPe4MyIWR8S1EXFRRJwSEe+NiP0jYoMhfWuSRiwidus2ZMrMRcDHquIywCciYmw/n0iSJEnqzDzPPM88b7DM8yQNinmeJElzy1j+w1t9IPg4ENWhT2bmH4bU/MEzOSki1gCePtNGI+KlEfET4BbKwPgzwIuBBwPLz/S607T5Jsrg/CnACh2qrVg9/9OIeMMs2louIt4O/A54IbDGNKesDDwW2H+mbQ5SROwFnAksqB3+E7BrZv58JJ0aD8sBqwLrA9sATwJeB5wI/CkizouIF0fEyiPs49C1GSQdNuo+SWPmXZR//wB2BA4aXVckSZIkzYR5nnke5nlzlXleG+Z50rTM8yRJGqGxvNEHOADYtvr6DuC9Q2z7ORGx7AzOewawyiza3QvYiTIgHriIOAR4N62hw23AD4EvA+cCt9eeWwE4MiJeP4O2Vga+CbyNMnCckMDFwLeBLwGnVOW7em1jmCJiP0pf67/vy4FHZOYlo+nVnBDAw4Gjgasi4jkj7o+kMZGZN1H+h8CEwyJipVH1R5IkSdKMmOcNmHnezJnnzZh5nqS2zPMkSRqtsds3OSKWB95eO3R8Zv55wM3eyeQA+T7AfwOn9niN53W43mzdDNwK3LdP1yMingi8s3H408BbMvOGWr11Kcv+vqBW78iI+E1mnt5lW0GZ/fH42uHbgaOAT7f73UbEKpTZP8+gBENjIyJeBHyS1pvkLgT2ysy/jaRTo3MyZXZPXVBmdy0A1gF2AB4GPILWWWbrA8dHxOOAgzNzrH7PkkbiA8D/ACsB9wNeVh2TJEmSNObM85ZwM+Z5Y8M8r4V5nqR+Ms+TJGlExu5GH8pgcJNa+eOdKvbR7ykD+S2r8sH0EAxExP0pg58J3wKeNoN+LAZ+BfwC+Hn13yuAQ6vHrFWzm97H5DLKAB/MzNc062bm9cALI2Ix8OqJSwDvj4gzM/PuLpp8GbB3rXwtsMdUM2Uy81+UGUPfjIixeY1GxBuB9zQOnws8KTP/MYIujdriai/eqZwMEBH3Bl5C+dC/Zu35A4DVI+IpmXnPQHqpsZSZC+fitXvow0G4XG1PMvOGiPgK8Nzq0Gsi4qOZeeco+yVJkiSpK+Z55nnmeXODeZ5mzDxPTeZ5kiSNzjhu3fXa2tc/zcwLh9TusbWvn1TNfunW82tf3wx8fQbtvxhYMzMfmZmvycwTMvPyzMwZXGsqzwW2qpUvA948zTlvqupNeADwrOkaioiNaB1I3w48ppflcDNzLJb9jYgjWTIUOI0y82dpDAV6kpl/zczDge0pgVfdk4DDht4pSePo6NrX9wWeOaqOSJIkSeqJeZ553n+Y580P5nmSumSeJ0nSCIzVjT4RsROTe3kDfGGIzX8OmJjRsjxdDHwBqhkqz64dOoHWvbC7Ug2chjED4rmN8gcz899TnVA9/+FprtPOW4DVauV3ZebvujhvbETEMhHxaeANjae+BDwlM28bQbfmrMz8A7Ab0HwdvCkitlryDElLk8w8D7iqduilo+qLJEmSpO6Y55nnjRvzvP4yz5M0FfM8SZJGY2yWUa0cVPv6HqplQochM6+NiO8yuff0wcCHujj1icC9a+VjgIV97VyfRMS9gF1rh+6gDHC78UVKODCxV/mjImLtzLyxQ1urU5ZxnXArS4YLYy0iVgA+D+zXeOpjwCsHMDtrqZCZt0bE04CLgBWrw8sDhwAH9nq9iFgN2AXYAFiXEvD9DbgE+OVsArfq2tsCW1P2KV+ZEvzdAlwD/D4zr+p4gQGKiPsB9wc2peyjvixwE+V7/2lm/nkAba5MeQ/ZEFivau9q4OzM7DkQVfciYhvggZRZMUn5PZ+XmVf04dpbAzsA9wHuAv4M/HaEQe5JwBurrx8eEVtl5mVTnSBJkiRppA6qfW2e12fmeb0xzxsM87z+MM9bupjnmedJkjRIY3OjT7XX9L61Qxdk5rVD7sYxTAYD20TEDpl5wTTn1Jf5vTgzfxERCwfSu9l7LGXwMOGCzPxnNydm5i0R8Usm9y5frrrelzucsj+ts39O7ratcRARqwBfA/ZqPPWOzPzfEXRpXsnMyyLiS5QAbsL+EfGKzLylm2tExF6UwcMjmAysmm6IiM8CR2bmTd32LyK2A94GPIHJ8KJT3euBs4BPZeY5jec6hUeHRsShU1x298w8u3GtFSivx6cDjwbuN02/fk8J446Z7aA9IjagLMf8DGD1NlUWR8QXgLd0CgvbXHMRsHFVvLqf+3B3e+0pfj+9OCczd2tz7eNoDbo2ycxFHfqxG/CD2qHDM/Ow6rkDgdcBD+pw7kXAmzLz9F47HhH7AIdTlm9v9/wvKX87X6nKZwOPmng+M6PXNrt0CpPBAJSQeaq/F0mSJEkjYp43FOZ5XTLPGyzzPPM887yWurthnldnnidJ0pCN09ZdOwNr1co/6FRxgE4BbqiVD+5UESAi1gceVzt0zCA61UfND5bn9Xj+TxrlB05Rd/dG+cwe2xqZiFhA6W89FEjgVYYCfdWcEbYiSwYxS4iIdSLiTOB0yuusUygAsA5lgHF5RDyym05FxBuAC4CnMU0oUFmXsu/wC7u5/iy8j/IedSDThAKVLYGPA+dHxKYzbTQidgZ+Q/n+2oUCUELAlwCXRsTDOtRRDyJi1Yg4CTiODqFAZVvgO9XrtttrLx8RX6bMtGkbClQeDHw5Ij5VhffD8nPKrNEJTxxi25IkSZJ6Y543eOZ5XTDPGxrzvN6Y5y1FzPPM8yRJGqaxWdGH1gE2wLnD7kBm3lndxf7q6tABEfHaKfa8PpDJn+GdDHcP8plofgDsdYnIK6e5Xt2OjfJ58J+lQp9KmUnwQMryrP+mBDK/ogzITxjVbKEq7PkusE3t8F3A8zLz86Po03yVmRdFxN8oS8ZO2IUyWGkrIjan/H6aA91/Ugbzf6XMcltIGdRM3Mx4L+DMiNg7M787xfWfBRzZ7CrwW8o+w7dQwoI1ga2AjYBBzYJoat6Y+S/KcsbXVv1aAVifMlCsD+C3BX4QEdt3OzunZnPgvZRljgFuA86n/JwXUH7G9d/fusAZEbFHZv6ix7Y0aRnKMux7V+W7Ka/vP1Zfbw5sT+tr78iI+E1mfmeqC0dEAF+tXXvC3ZQB+TWU1/iWlKWkAV5Ea2g+UNW/xecBj6kObR8R62Xm34bVB0mSJEldM88bPPO8aZjnDY95Xs/M85Ye5nnmeZIkDdU43ejz8Eb5wl5ObrfU4gwdw2QwsBbwFDovZ1ufIXRqZl7fpz4MyuaN8jU9nt+sv0W7StUMmnpbdwBXRcSjgGOBTRqnrEQZaG0G7AMcERFvz8yP9Ni/WYmITSjBxGa1w7cD+2fmKTO9brW857AGj10bk36dT+sAZdtOFavll79OayhwGfAW4BuZeXej/n0oy5hOzMxZAfhCRGzXbr/riFgGOKpx+GPAuzLzug59WhvYkzID6O42VSZe6w8HTqgd/zDwoXbXrLRtjxLOHQ+cBvyq3X7lEbE85X3rPUz+rDYCPkEJ5HpxFCUAuAN4B/DBzPzPzIxqVsg+lO/n3tXhNYAvRcS2mXlbj+0NW/O9aDorAyczOWAG+Ev/uvMfL6XMXrubEsy8LzP/Xq8QEVtRXgv1EPYjEbFlZk61hPErWTIU+CRwaPPfsIh4EOVv4FHAmyl7uHelWqp6Nu8vFzIZDATlb2jG78OSJEmSBsY8b/DM86ZgnjcS5nntmecNh3leYZ4nSdJSbpxu9Nmh9vXNmfmnUXQiM38TERfU+nMwbYKBiNiFMgNgwrgv8wuTd/FP6PVu6mb9NTvUW79R/gtl2dSv0N12cfcCPhwRDwUOzsy7eurlzGwI/IgyI2nCLcDezX2a1VeX0jpI2WiKuu+ldcnT7wBP7zT4zMxrgRdFxKXA+6vD61AGuM9rc8pDaP39fy4zXzFV56sZNScCJ1az25rPLwKIiIWNp27utL/zFI4CXtkuDGi0eSdwUkScBXwf2K56at+IOCQzr+qhzbUog9P9M/Mbbdq6m7IU7C8pszYnwoEtgEMo+6KPrV5+BxGxHPA1WkOBX1GWOO63iVDgKZl5arsKmXlZRDwWuJjJpZ83p+z3/r1250TEvYAjGodfk5kf7NDGxRHxGEoYsjewdq/fyCz8ulHekT4FAxGxHmW2Wi82m76KJEmStFQyzxu8BY2yed4k87zRMM/rnnlen5nnAeZ53TLPkyTNa90M0gauWl61Psi8elR9qdQH+Y+NiA3b1KkPLK6j7C887lZrlHu9O79Zv9P+vgvatPsFJl9vVwNvoOzjvhWwE/B6YFHjvGdTZjEMw2a0DgqvB3Y3FBi45oyCth/WI2ID4AW1Q4uAfbqZYZKZHwC+XTv0rOo9p2njRvmr01270c5AZ7tk5jXThQKN+jfR+jNbhjJTqVcfbRcKNNq6nDJrpe4lEdHNnuhzxWeAJ9XKVwCPy8xbBtTekZ1CgQlV282lqR89xSnPA1aplb/TKRSotXEXcBBleedhan4O2LKP134ZJVDp5fHNPrYvSZIkzQvmeUNjnteZed5omOd1f33zvNEyzxsu8zxJkoZoLG70oey/WzeS2T81X6Is8QrlZ3Rg/cmIWBXYr3bo+CHNUpmtZjBwe9tanTUHPs3rTVjQKK9DWc4Xyn7N98/M92bmeZn5+8w8PzPfR7mzvrmf82sjYtce+9kPywBdD8I0Y81gYIlZNJWXUJbqnXB4Zv6rh3beX/t6BeBxXZyz3vRVxltmXkDrAGvnHi9xB/DOLtv6OvDL2qF1gCf02N5Yioj3UgbHE64F9hzgHtO30fqanUozPNh+irrNYKjb3+1NlCV/h6n5OWDhkNuXJEmSNL2FjbJ53mCY53XPPG84zPMGyDyvP8zzzPMkSZrvxuVGn+YH8K73DR2EzLyZsnfwhIMaVfajdVB87IC7NChT7fs6m/qdXlc/Bw6YYmnW24EDqnp1b+2y3dm4AbizVr4X8L2ImOpDtmav+Vrp9Bp7bO3ru+lxdg5lGed6eNcubLq0UX5zh5lCYyWK1SLiPhGxsPmgzGabcP8Ol+nku829pKfxpUb5ET22N3Yi4g3A62qHbqbM/PnDAJs9r1pGelqZeTVQD8naBlpVoL1N7dCfM/MnPfTpKz3U7Yfm54A5H9RJkiRJ85B53miY500yzxsN87xZMs8bLPO8/zDPkyRpHltu1B2orNIoD3TJzC4dy+Td0ptHxK6ZeW5Vfn6t3nmZ2RxQjKvFlD16J3SabdFJs/7iKdpp53XTzZTKzLsi4jWU/YEn7BkR6w3wbnuA3wIfpMxAWr46tjYlHHhMZv6y45majQWN8hJ/+xGxErBD7dAfgXUiYp0e27qZMisF2uzPm5m/iYjfAP9VHdocuDQijqMEEeePw0y/iFgB2BN4GvBgYGug2yV115q+SoufzrL+Q3s8f6xExEG0LqV7G/CkzGzuN91vv+ux/s1M/ju6Zoc6DwKWrZV/0WMblwP/mOL6/dac4bdqH6/9CZacbTqdzXC5X0mSJKnJPG84zPM6M88bjQWNsnneNMzzhsc8r4V5nnmeJGkeG5cbfZr9GPmHb+AsyhKZE/v8Pg84NyK2BHap1TumeeIYG2UwcHVm/rCbRjLzRxFxFbBp7fCj6P2DXE8y85sRsU/VzsSysmsBZ0XEnpnZ6wdpTa85UL2+TZ31mQxroCz5OdvZF2t3OP4i4AdMLk29JvCq6nFrRPwUOI8yo+jHmfnPWfajJxHxZEqAtckML9HroO73Pda/vFGes7M2ImJvyj7eE+4C9s/MHw2h+V5nwdZnLy7foU4zSGvumT2lzMyI+CPDCwaanwM6fV89q0LmnoLmiOhX85IkSdJ8Yp43HOZ5U7drnjd85nk9MM8bHvO8VuZ55nmSpPltXLbuat713+uAte8yM4HP1Q7tGxGrUQKCCf9i+MsfzsY/GuV1ezy/+SH/5g712h0/v8e2mjMJel2idEYy8xTKzIp/1w6vBZwZEXN6NsOYekCj3G6wcq8BtLt6u4OZeT4l+PtVm6dXBR4NvAX4DnB9RHwjIh4zgP4tISJeDXyDmYcCAL2Obm7psX7zPaZTADPWImJX4MtMhtYJvCAzvzWkLtwzgGsuaJRnEmr1+nqYjebngFuH2LYkSZKk7pjnDYd53jTM84bOPK9L5nnDY57XkXmeJEnz1Ljc6NP8sNHPJf1m41gm9xhelbL073Nrz381M4f5QWm2mnfnb9y2VmfN+s3rTbia1oE1wLU9tvWXRnkQg8O2MvM0lgwHFlDCgYcNqx9LiebP86I2dVZoc2y2Og6Qq2Wdd6Asp3sscE2HqisCT6a8Lk6NiIG9RqvX3fsbhxcBRwBPpAQsa1MGU8tkZkw8gHNm0XSnPda7rd/r+SMXEdsA32JyFhjAGzLzcx1OmSua78kz+bsaxN9iJ83PAXPp31pJkiRpaWGeNxzmeV0wzxsq87wumOcNj3nelMzzJEmap8blRp8/Nsr3GUkvGjJzEXB27dCRtPbt2GH2pw8uaZQ37/H8TRvl5vUAyMy7gcsah5sfSqfTrL9S21oDkpnfBp4C3F47vCZwRkQ8fJh9ma8iYnuWXH603TKqNzTKZ9QHvjN8LJyqb1mcmZnPy8yNgY2A/YCPUvZ/b3oC8O2IGNR2iIfS+n79aWCLzHxLZp6WmZdk5k2ZeXs1e7FujVm02+uyrgsa5V6XrB2piNgEOJ3W7/uozHzfiLrUT83fRa/7u8NwZ3Rt0Cg3PydIkiRJGj3zvOEwz+uSed7gmef1xDxvCMzzpmWeJ0nSPDUuN/osovVO8Q1H1I926nt21z9IXcXs7qwfhYsb5Z16PH+XRrl5vbpfN8oLemyrWf/vPZ4/a5l5OmWGRz0cWIMSDuw87P7MQ69qlG8HzmhT76+N8paD6U5nmfnHzDwpM1+ZmQ+q+vBxWpdk3RE4qN9tR8SqwB61Q1cB/y8zm3sedzKboLXXn/UWjXJP+yaPUkTcGziTRvibmW8cUZf6rbmM9n/1cnL1OlzYt95M776N8h+G2LYkSZKk7izCPG8YzPN6YJ43cOZ5XTDPGw7zvKmZ50mSNL+NxY0+mXk7rTNGNoqIVUbVn4aTWXKfWoDj2txpP+7OBO6ulXeIiLZ7GzdV9R5cO3RXdb1Ovt0oP7CrHk56UKP8px7P74vMPAN4Eq37zq8OnB4RzaBEXYqIrSlLZ9edkJmLm3Wr5bTrs24WRkRzADpUmXl5Zr4ceFPjqad2OmUWzW1M6xKrp3cbCkTEpsD6s2i719luzaWbfz6LtocmItagzPzZrHb4FOCFo+lR/2XmFbTOptsuIhb0cIndGO5nhvs3yhcOsW1JkiRJXTDPGxrzvB6Z5w2GeV5PzPMGzDyvK7thnidJ0rw1Fjf6VOofIJdhyYHhSGTmbcCJjcP3AMcNvzezk5k30LqU6grAAV2e/ixg+Vr5h5l54xT1T6V1ud6HRkRXy0RGxFqU2RR153bVywHIzLMo+yb/q3Z4IhzYdTS9mruqmQQn0zrYvQN49xSnfbdRHpcB22cb5U061GsuXb1iD20saJTbBZWdHNRD3Xb27HGv8ub7Sbulm8dKRKxECQG2qx0+F9i/WrZ8Pvle7esVgef2cO6L+tyX6WzTKP9syO1LkiRJ6o553oCZ582MeV5/mecB5nljwzyva+Z5kiTNY+N0o09z2dzmwHCU3gbsWns8LDPn6v6ixzfK/xMRUw5Squdf3Tj8uanOycx/Al+tHVoReHmXfXw5rXt4X83UywoPXGZ+nyXDgdWA70TEI0fTq7mn2jP5bOABjaeOyMzLpzj1k5RZZxNeERG9ziobhOZMnE5719/cKPey/G5zL+atuzkpIjYGXtlDO+2sALy1y/aeSusswRuA02bZ/kBFxLLACcCjaocvAp5UzUydb45ulA+NiGlniEXE44G9B9OljuqfAW7GGUCSJEnSuDLPGw7zvBkwz+sP87z/MM8bA+Z55nmSJKkYpxt9mkvD7j6SXrSRmddn5o9qj1+Muk+z8Dlal1XeCjhimnPeXdWb8Dvgi1209TbKzI4Jh0TElPuIV883ByLvHodllTPzB8DjgVtrh1cFvh0Ru/WzrYg4OyKy9jisn9cftoi4d0S8Dfgl8JDG098E3jHV+dUypcfWDq1E+bk3A4bp+rFiRBzU4bknR8RDe7keS86guKRDvato/VvYPSKW71C36UqgvgTyEyNiyhmSEbEO8DVgzS7bmMorIuLJ07S3OfCJxuFPZWanoGRcfAp4Sq18FfC4zOxlltWckZln0zqbcm3grIjYqNM5EbEH8OUBd63Z5ga07if/3Xk4G0uSJEmaL8zzhsM8b4bM82bOPM88b0yZ55nnSZIkxuhGn8y8Fvhp7dDuEbHcqPozbBGxXEQsbPdgyaU+V+tUNyJWm6qd6sPV62jdY/g1EfGp5pKeEbFORHwa+J/6JYDXdvMhLTP/ABxVO7QicEZEvLQ5KKq+/xcDZ9C6BOzPaB0QjlRmngP8N60DtVWB0yLi0aPp1ci0ex1uEhHbRMSuEfG0iHhXRJwFXAO8nSVfy58H9svMe7po7zXAr2vljYBfVG3cr9NJEbFyRDwmIj4C/JHOr6fdgZ9FxM8j4g0RsXVERIdrrh4RbwI+0Hiq7cy4zLwD+HGj76dUYcQD2vwcV2qc+43aucsD342Ix7Xp17IR8XTK0ukPpvy9/r3D99uNm4Blga9ExFuiLNPcbG8/ypK+9ZkkVzB94DhSEfEi4Pm1Q4spy9muNMX7a7vHbPZMH4WDaQ03Hwj8LiI+FBF7Vq/7bSJin4j4CnAmZbbj5ZRgbxge0yh/Y0jtSpIkSeqReZ55nnnenGOeZ55nnmeeNwjmeZIkDdm4DbyPBx5Wfb0W5YP6maPrzlBtCPyhy7pPrx7tHMw0+41n5qkR8VbgXbXDLwKeExE/Ba6jLEW6I7By4/Q3ZebpXfYT4H8ps4f2rcqrUWYKHBER5wM3Uu5CfzhLDhr/DDy9GhiNjcw8txqUfYeytzfAKsCpEfGkzPxe57Pnlaleh9O5Fnh9ZnYzkwyAzFwcEU+khEcTy92uDBxCmV12FXApZVnQ5SizXxYCm1MGt916SPU4ErglIi4Grgf+SZl5tBFl/+cVGud9ITObe4/XfYDWmY2Pqx7t7E5ZEnnCYZSZKhPB3waUZaavBn5FWYJ6HeChlPfOCUcAj6B1KdtevIkS7q0JvJPycz4f+Gt1bAfg3o1zbgEOyMx/Md42aJRXA86awXXOAXabdW+GJDOvjDKj6xTK+xaUcPNV1aOdxcA+wEcG30Oo2prwDwwGJEmSpHFnntcd87wRMs/7D/O8VuZ5hXneGDPPkyRJ7YzbjT4nAu9jcjC6L0tPMDBUmXlERCRwOGVGAZSf+24dTrkTeFtmHtXh+U7tZEQ8hxIAvLj21AI6D4qgzPx5amb+pZf2hiUzf1yFA6czGQ6sDHwrIp6cmbN93a7UKDf3dZ6LkvJ7PQb4fGbe1vMFMv8YZTneo4FnNZ7etHpM5+YemlwD2LmLekcDr5iqQi2QO5zegoqJwdw+wFeZDAcANq4e7bw3M98aEWf30lbD7yl72X+L8je7CjDVTLfrgb0z8+ezaFMDlpnfi7I8+f8B20xT/deUWXqXRUQ9KP7nIPoWEWsCe9YOnTBP91eXJEmS5hPzvCExz5sd87wZMc8zz9MYMM+TJElNY7N1F0Bm3kjrUpn7T7d0rWYuM99NmXH1TVr3G667o3p+x8w8cobt/DszX0JZvvFMYKplgi8GDgJ2HtdQYEJm/oTyAfaW2uGVKUu47jXT61YfvrerHbqJaWZ1jZG7gdsoM0R+A5wKvB94JnDfzHx4Zn56JqHAhMxcnJnPBrYFvkB3oclfKPvQ70vrkrR17wZeSNkL+69dXPM24GRgp8x8aWbe1UXf30UZiL0H+CFltl1XP4tqdtFDKH+Pnfa4vwv4LrBHZr6hm+t20e6PKH0+jtYlrusWU/bH3jozz+9HuxqsKrx5MLA/8BXKfub/oryfXQKcBDwZ2CEzL6tOW1C7xKD2PX8OZVl4KK/zDw+oHUmSJEl9Yp43XOZ5s2Oe15Z53tR9N8/TWDDPkyRJdZHZ6fPlaETEFpTlOiduQnpxZn56hF1aKkTEWpSZDvcF7kXZB/jPwE8ys6+zTyJiXcrSvvehLE/6T8pA7CeZ+ad+tjUXRcREgDLhbZn5zlH1Z9xFxDKUgesDKMtGLwBupwxwFgGXZOYfZ3DdjSnLVG9cXXNFysDpRsrA6TejWs42Iu5NWcJ3I0oYdT1l+eTzM/OGAba7atXu/YB1KaHM1cDZswl7NP6qfeZvYXLG6C8y86EDaOc3wIOq4rcyc+9+tzETEfFASnANwNmvfRZbr3+vEfaovy697u/s9v6WldcflJm/HVV/JEmSNPeY542Ged74MM/rjXmeeZ4GzzzPPE+SNL+N29ZdZOblEfFFyl3AAK+OiM/kuN2RNM9Ug//ThtTW9ZSlQ9VefSnVv+Md8FPKzHuAC6tHP697NWXQO3Yy86+U2UfDbvdWygwjLX12YjIUALig3w1ExJ5MhgITS9FLkiRJmgPM80bDPG+smOf1wDxvqO2a5y29zPMkSZrHxmrrrpr/ZXLp2fsDTx1hX6RhqwcD78vMgeydK0k9eGmjfN4A2nhr7euTMrPv4YMkSZKkgTLP09LMPE/SuDHPkyRpHhvLG30ycxHwodqhQ6vlPKV5LSJWB3aoitcDHx1hdySJiHg8sG/t0GLga31uYw9g16p4O3BIP68vSZIkafDM87S0Ms+TNG7M8yRJmv/GebD9duCa6uttgANH2BdpWB7J5JZ6R1VLq0pS30TE4RHxoohYsYu6zwROahw+pp8zE6vg/321Q+/JzCv7dX1JkiRJQ2Wep6WReZ6kgTLPkyRJTctNX2U0MvPWiDgAeGx1aPmp6kvzQWaeBsSo+yFpXtuYsqT+kRHxdeBHwO+AGymfC9YFdgT2Z3JG4oQrgbf0uT8bAt+sHncDR/X5+pIkSZKGxDxPSyPzPElDYJ4nSZJajO2NPgCZ+WPgx6PuhyRJ89AC4ODq0Y2rgb0zc3E/O5GZ1wCH9fOakiRJkkbHPE+SpIFZgHmeJElivLfukiRJ/XdDj/XvBr4E7JiZvxtAfyRJkiRJkiR1Zp4nSZJajPWKPpIkqb8y83URcTSwJ7ATsDVwP2BNYAXgFuDvwKXAOcDX3GNbkiRJkiRJGg3zPEmS1OSNPpIkLWUy8wrgCuATo+6LJEmSJEmSpKmZ50mSpDq37pIkSZIkSZIkSZIkSZLmAG/0kSRJkiRJkiRJkiRJkuYAt+6SJEnqwe8e9UJu3WLrUXejb66+/FJ4/xdH3Q1JkiRJkiRpIMzzJEnzjSv6SJIkSZIkSZIkSZIkSXOAN/pIkiRJkiRJkiRJkiRJc4A3+kiSJEmSJEmSJEmSJElzgDf6SJIkSZIkSZIkSZIkSXOAN/pIkiRJkiRJkiRJkiRJc4A3+kiSJEmSJEmSJEmSJElzgDf6SJIkSZIkSZIkSZIkSXOAN/pIkiRJkiRJkiRJkiRJc4A3+kiSJEmSJEmSJEmSJElzgDf6SJIkSZIkSZIkSZIkSXOAN/pIkiRJkiRJkiRJkiRJc4A3+kiSJEmSJEmSJEmSJElzgDf6SJIkSZIkSZIkSZIkSXPAWN/oExHHRkRWjxNH3Z/5KCI2jIi9IuLFEfHG6vGiiHhCRKw7oDYfHBH7R8Rrqsf+EbH9INqS1L2IOKz2npsRsdsA21pUa2fRNHUPavTroH5de1Ai4rhGnxeOoh9zQUQsjIjbq5/T3RGxw6j7JEmSJGnmzPMGzzxP0gTzvP4xz+ueeZ4kSaM3tjf6RMQuwIFV8Q7gzdPUP7v2AezsaeoubHxgqz+2nkWfj+9wzeN6uMZyEbFtRLwgIo6OiAsi4o6ZXq/N9deMiGdHxBci4s/AH4HTgaOB91SPTwGnAn+LiAur0GClmbZZtbt8RLwpIq4ALgBOBN5fPU4EfhkRl1fBxPKzaavL/jQHGmfP4Bo7R8RNjevcEBEPbdRrvt4O6tf3MRu99qvNoLHd486IWBwR10bERRFxSkS8twp/NhjStyZpxCJit25DpsxcBHysKi4DfCIixvbziSRJkqTOzPPM8wbJPM88T9LgmOdJkjS3jOU/vNUHgo8DUR36ZGb+YUjNHzyTkyJiDeDpM200Il4aET8BbgEuBD4DvBh4MNCXgXJEvBz4G/B54FlANwO1bSmhwS8j4iEzbHcL4Hzg3cBmU1TdnBJMnBcRm8+krWGJiL2AM4EFtcN/AnbNzJ+PpFPjYTlgVWB9YBvgScDrKOHPnyLivCpoWnmEfRy6NoOkw0bdJ2nMvIvy7x/AjsBBo+uKJEmSpJkwzzPPM8+bs8zz2jDPk6ZlnidJ0giN5Y0+wAGUASmU2T/vHWLbz4mIZWdw3jOAVWbR7l7ATsAgB0wLgRXaHL8F+DHwdcoA7ofAbY069wfOiYhde2kwItanDKAf3HjqCuCbwCnAlY3ndgDOiIj1emlrWCJiP0q/67/vy4FHZOYlo+nVnBDAwylB01UR8ZwR90fSmMjMmyj/Q2DCYbOdeSpJkiRp6MzzBmMh5nmzZp43Y+Z5ktoyz5MkabTG7kafapnXt9cOHZ+Zfx5ws3fWvr4P8N8zuMbzOlxvtm4GBvH9/wk4AngIsHZmPiIzn5aZz8zMRwHrUmZu1AOCVYBvRpd7fVczub4BbFw7fC2wV2ZukZlPycwnZ+bmlJ/5dbV6mwBfj4hgjETEi4ATaA1YLqSEAlePpFOjczLl91R/bApsB+wG7EOZ9fV9SsBXtz5wfER8MSLahVWSlj4fAG6vvr4f8LIR9kWSJElSD8zzlnAz5nljwzyvhXmepH4yz5MkaUTG7kYfykyaTWrlj3eq2Ee/rx4TelruNyLuDzysduhbM+zHYuBc4IOUWVBbAmsD/zfD67XzG8qAbePMfEtmXpCZdzcrZeatmfl+ygBvce2ptYB3dNnWs2j9udwI7JyZZ7Rp73RgZ+Cm2uGdgf27bGvgIuKNlP3O63835wK7ZebfRtOrkVqcmYsajz9k5kWZeU5mnpyZh2TmHsBGwGHAPxrXOAD4qvv3Ln0yc2FmRvVYOFeu3UMfDqr1Iap9qzWFzLwB+Ert0Guq/1kgSZIkafyZ55nnTTDPG2/meZox8zw1medJkjQ64/hh/LW1r3+amRcOqd1ja18/qdtZLpXn176+mbJkbq9eDKyZmY/MzNdk5gmZeXlm5gyu1clHgG2rAds93ZyQmT8D3tw4vP90H9aq5ZIPbxx+zVQfjqt921/TOPzOcRg0RsSRlP3G606jzGZqDnbVkJl/zczDge2BXzSefhIlNJCko2tf3xd45qg6IkmSJKkn5nnmeXXmefOAeZ6kLpnnSZI0AiMfcNVFxE5M7uUN8IUhNv85YGImzPKU2SvTiojlgGfXDp3A5FKFXasGTl0N1mcqM6+ZYdBwDK3f0wLKAG8qj6B1Jtef6e73+XlalzbejDITaCQiYpmI+DTwhsZTXwKekpnNvc81hSr82Q34XeOpN0XEVsPvkaRxkpnnAVfVDr10VH2RJEmS1B3zPPM8zPPmNfM8SVMxz5MkaTSWG3UHGg6qfX0PZc/gocjMayPiu8Djq0MHAx/q4tQnAveulY8BFva1cyOWmf+KiMtoDW02mOa0pzbKx7dbUrhNW3dHxBeAN9YOPw34UVed7aNqr+nPA/s1nvoY8Mo+z85aamTmrRHxNOAiYMXq8PLAIcCBvV4vIlYDdqG8JtelBHx/Ay4BfjmbwK269rbA1pRAbGVKSHYLcA3w+8y8quMFBigi7gfcn7KP+hrAspSlsv9GmT355ylOn2mbKwO7AhsC61XtXQ2cnZk9B6LqXkRsAzyQMismKb/n8zLzij5ce2tgB+A+wF2UcPa3mdkM8IblJCb/DXh4RGyVmZeNqC+SJEmSpndQ7WvzvDFhnmee10/mef1hnrd0Mc8zz5MkaZDG5kafamnYfWuHLsjMa4fcjWOYDAa2iYgdMvOCac6pL/N7cWb+IiIWDqR3o3VXo7zCNPUf1yif3UNbZ9MaDPw3Sy4BPFARsQrwNWCvxlPvyMz/HWZf5qPMvCwivkQJ4CbsHxGvyMxburlGROxFeZ08ghIstHNDRHwWODIzb+pQp921twPeBjyByfCiU93rgbOAT2XmOY3nOoVHh0bEoVNcdvfMPLtxrRUor8enA48G7jdNv34PfBg4ZraD9ojYgLIc8zOA1dtUWVwFem/JzBu7vOYiYOOqeHU/997u9tpT/H56cU5m7tbm2sfRGnRt0mmp84jYDfhB7dDhmXlY9dyBwOuAB3U49yLgTZl5eq8dj4h9KEuyP6DD87+k/O18pSqfDTxq4vnMjF7b7NIptP4bcAAw1d+LJEmSpBExzxt75nmFeV4fmOeZ55nntdTdDfO8OvM8SZKGbJy27toZWKtW/kGnigN0CnBDrXxwp4oAEbE+rQPgYwbRqVGLiKDMMqjrGNpExIrA5o3D5/fQ5E8a5S2qQdFQRMQC4ExaQ4EEXmUo0FcfbpRXZMkgZgkRsU5EnAmcDuxO51AAYB3KAOPyiHhkN52KiDcAF1Bmnk0ZClTWpew7/MJurj8L76O8Rx3INKFAZUvg48D5EdH8++1aROwM/Iby/bULBQBWA14CXBoRD5tpW5oUEatGxEnAcXQIBSrbAt+pXrfdXnv5iPgyZaZN21Cg8mDgyxHxqSq8H5afA7fWyk8cYtuSJEmSemOeN6bM8wDzvEEwz+uNed5SxDzPPE+SpGEamxV9WHLGyLnD7kBm3lndxf7q6tABEfHazPx3h1MOZPJneCfD3YN8mPagNbS5g7JMaydbUZYdnfC3bmd1AGTmLRFxA2VQR3WtLYGLu73GTFVhz3eBbWqH7wKel5mfH3T7S5PMvCgi/kZZMnbCLpTBSlsRsTnl99Mc6P6TMpj/K+X1spAyqJm4mfFewJkRsXdmfneK6z8LOLLZVeC3lH2Gb6GEBWtSXucbAYOaBdHUvDHzX5TljK+t+rUCsD5loFgfwG8L/CAitu92dk7N5sB7KcscA9xGCfn+Wh17MK2/v3WBMyJij8z8RY9tadIywJeAvavy3ZTX9x+rrzcHtqf1tXdkRPwmM78z1YWroPertWtPuJsyIL+G8hrfkrKUNMCLaA3NB6r6t/g84DHVoe0jYr3M/Nuw+iBJkiSpa+Z548s8zzyv78zzemaet/QwzzPPkyRpqMbpRp+HN8oX9nJyu6UWZ+gYJoOBtYCnAF/uULc+Q+jUzLy+T30YN//TKH9vmoF+c/bPNTNo8xomgwGALRhwMBARm1Bm/mxWO3w7sH9mnjLT61bLew5r8Ni1MenX+bQOULbtVLFafvnrtIYClwFvAb7R3DM+Iu5DWcZ0YmbOCsAXImK7dvtdR8QywFGNwx8D3pWZ13Xo09rAnpQZQO32rN+k+u/DgRNqxz8MfKjdNStt2wOuBI4HTgN+1W6/8ohYnvK+9R4mf1YbAZ+gLNXbi6MoAcAdwDuAD2bmf2ZmVLNC9qF8P/euDq8BfCkits3M23psb9g2mb5Ki5WBk5kcMAP8pX/d+Y+XUt7/7qYEM+/LzL/XK0TEVpTXwo61wx+JiC0zc6oljF/JkqHAJ4FDm/+GRcSDKH8DjwLeTNnDvSvVUtWzeX+5kMlgICh/QzN+H5YkSZI0MOZ548s8zzxvUMzz2jPPGw7zvMI8T5Kkpdw43eizQ+3rmzPzT6PoRGb+JiIuqPXnYNoEAxGxC2UGwIT5uszv05nc53zC+6Y5bUGjPJO7tpvnrDmDa/RiQ+BHwAa1Y7cAezf3aVZfXUrrIGWjKeq+l9YlT78DPL3T4DMzrwVeFBGXAu+vDq9DGeA+r80pD6H19/+5zHzFVJ2vZtScCJwYESu3eX4RQEQsbDx1c6f9nadwFPDKdmFAo807gZMi4izg+8B21VP7RsQhmXlVD22uRRmc7p+Z32jT1t2UpWB/SZm1OREObAEcQtkXfWz18juIiOWAr9EaCvyKssRxv02EAk/JzFPbVcjMyyLisZTAdGLp580p+71/r905EXEv4IjG4ddk5gc7tHFxRDyGEobsDazd6zcyC79ulHekT8FARKxHma3Wi82mryJJkiQtlczzxpB5nnnegJnndc88r8/M8wDzvG6Z50mS5rXm0pEjUS2vWh/4XT2qvlTqg/zHRsSGberUBxbXUfYXnleqGTGfaRw+KTO/P82pqzXKM5kF0Dyn017C/bIZrYPC64HdDQUGrjmjoO2H9YjYAHhB7dAiYJ9uZphk5geAb9cOPat6z2nauFH+6nTXbrQz0NkumXnNdKFAo/5NtP7MlqHMVOrVR9uFAo22LqfMWql7SUR0syf6XPEZ4Em18hXA43pZxrxHR3YKBSZUbTeXpn70FKc8D1ilVv5Op1Cg1sZdwEGU5Z2Hqfk5YMs+XvtllECll8c3+9i+JEmSNC+Y540n8zzzvCEwz+v++uZ5o2WeN1zmeZIkDdFY3OhD2X+3biSzf2q+RFniFcrP6MD6kxGxKrBf7dDx1YeneSMi1gC+Rete3tdSPlBNpxkM3N621tSag6zmNQdtGaDrQZhmrBkMLDGLpvISylK9Ew7PzH/10M77a1+vADyui3PWm77KeMvMC2gdYO3c4yXuAN7ZZVtfB35ZO7QO8IQe2xtLEfFeyuB4wrXAngPcY/o2Wl+zU2mGB9tPUbcZDHX7u72JsuTvMDU/BywccvuSJEmSprewUTbPGzHzPPO8ITHPGyDzvP4wzzPPkyRpvhuXG32aH8C73jd0EDLzZsrewRMOalTZj9aB6rED7tJQRcQKlCUtH1g7fAewX2beMINLTrW/bD/PmY0bgDtr5XsB34uIqT5ka/aa70Gdfu+PrX19Nz3OzqEs41wP73ZtU+fSRvnNHWYKjZUoVouI+0TEwuaDMpttwv07XKaT7zb3kp7GlxrlR/TY3tiJiDcAr6sdupky8+cPA2z2vGoZ6Wll5tVAPSRrG2hVgfY2tUN/zsyf9NCnr/RQtx+anwPmfFAnSZIkzUPmeWPEPA8wzxsW87xZMs8bLPO8/zDPkyRpHltu1B2orNIoD3TJzC4dy+Td0ptHxK6ZeW5Vfn6t3nmZ2RxQzFkRsSxwArBH7fBdwDMy80ddXmZxo9xpVsdUmuc0r9lvvwU+CJwELF8dW5sSDjwmM3/Z8UzNxoJGeYm//YhYCdihduiPwDoRsU6Pbd1MmZUCbfbnzczfRMRvgP+qDm0OXBoRx1GCiPPHYaZfFdztCTwNeDCwNdDtkrprTV+lxU9nWf+hPZ4/ViLiIFqX0r0NeFJmNveb7rff9Vj/Zib/HV2zQ50HAcvWyr/osY3LgX9Mcf1+a87wW7WP1/4E5b2+F5vhcr+SJElSk3nemDDPM88bsgWNsnneNMzzhsc8r4V5nnmeJGkeG5cbfZr9GPmHb+AsyhKZE/v8Pg84NyK2BHap1TumeeJcFRHLUAKRp9UO3wMcWC3j2a25GAyQmd+MiH0oHxgnlpVdCzgrIvbMzF4/SGt6zYHq9W3qrM9kWANlyc/Zzr5Yu8PxFwE/AFaqymsCr6oet0bET4HzKDOKfpyZ/5xlP3oSEU+mBFibzPASvQ7qft9j/csb5Tk7ayMi9qbs4z3hLmD/HgLS2eh1Fmx99uLyHeo0g7TmntlTysyMiD8yvGCg+Tmg0/fVs2qJ5p6WaY6IfjUvSZIkzSfmeWPAPM88bwTM83pgnjc85nmtzPPM8yRJ89u4bN3VvOt/JgPJvsrMBD5XO7RvRKxGCQgm/IvhL384EFE+9RwNPKd2OIEXZGZz+c7p/KNRXncGXWoOKG6ewTV6lpmnUIKRf9cOrwWcGRFzejbDmHpAo9xusHKvAbS7eruDmXk+Jfj7VZunVwUeDbwF+A5wfUR8IyIeM4D+LSEiXg18g5mHAgC9jm5u6bF+82+/UwAz1iJiV+DLTIbWE++F3xpSF+4ZwDUXNMozCbV6fT3MRvNzwK1DbFuSJElSd8zzRsw8rzDPGzrzvC6Z5w2PeV5H5nmSJM1T43KjT/PDRj+X9JuNY5ncY3hVytK/z609/9XMHOYHpUH6KPDCxrGXZeZM9itvzgLYuG2tqTXPaV5zYDLzNJYMBxZQwoGHDasfS4nmz/OiNnVWaHNstjoOkKtlnXegLKd7LHBNh6orAk+mvC5OjYhBBBgAVK+79zcOLwKOAJ5ICVjWpgymlsnMmHgA58yi6U57rHdbv9fzRy4itgG+xeQsMIA3ZObnOpwyV/y7UZ7J39Ug/hY7aX4OmC//1kqSJEnziXne6JnnVczzhso8rwvmecNjnjcl8zxJkuapcdm664+N8n1G0ouGzFwUEWcDu1eHjqR1adKZDJrHTkR8APh/jcOvzsyjZ3jJy4C7mdw/dr2IWL3bZVEjYg1al6W8myEGAwCZ+e2IeArwdVqXfT0jIvaqZopoFiJie5ZcfrTdMqo3NMpnZOZeg+lVUc0APLN6EBH3Ax4O7EqZBfTAxilPAL4dEbsMaN/vQ2m9MfPTwP/rsq01ZtFur8u6LmiUe12ydqQiYhPgdFq/76My830j6lI/NX8Xve7vDsOd0bVBo9z8nCBJkiRp9MzzRsg8b0nmeYNnntcT87whMM+blnmeJEnz1Lis6LOI1jvFNxxRP9qp79ld/yB1FbO7s34sRMSRwP80Dr8+Mz8802tm5r+BKxuHd+rhEjs3ypdX1xyqzDydMsPj9trhNSjhQLOP6t2rGuXbgTPa1Ptro7zlYLrTWWb+MTNPysxXZuaDqj58nNYlWXcEDup32xGxKrBH7dBVdB8KwOyC1l5/1ls0yj3tmzxKEXFvShBU/3kdm5lvHFGX+q25jPZ/9XJy9Tpc2LfeTO++jfIfhti2JEmSpO4swjxvJMzzOjPPGzjzvC6Y5w2Hed7UzPMkSZrfxuJGn8y8nTJrZMJGEbHKqPrTcDJL7lMLcFw1S2DOioh3AG9oHH5Ln+52P71R3q2Hc5t1vzOrnsxCZp4BPInWfedXB06PiF1G06u5LyK2piydXXdCZi5u1q2W0/5t7dDCiGgOQIcqMy/PzJcDb2o89dROp8yiuY1pXWL19G5DgYjYFFh/Fm0/vMf6zaWbfz6LtoemmnV4OrBZ7fApLLn8+ZyVmVfQOptuu4hY0MMldmO4nxnu3yhfOMS2JUmSJHXBPG80zPOmZ543GOZ5PTHPGzDzvK7shnmeJEnz1ljc6FOpf4BcBnjQqDpSl5m3ASc2Dt8DHDf83vRPRPwv8NbG4cMz84g+NfH1Rvk5EbFs25qt/VoWePY01xqqzDyLsm/yv2qHJ8KBXUfTq7mrmklwMq2D3TuAd09x2ncb5XEZsH22Ud6kQ73mDLYVe2hjQaPcLqjs5KAe6razZ497lR/QKLdbunmsRMRKlBBgu9rhc4H9M/PukXRqcL5X+3pF4Lk9nPuiPvdlOts0yj8bcvuSJEmSumOeN0Tmed0zz+sv8zzAPG9smOd1zTxPkqR5bJxu9Gkum7vjSHrR3tsoe/lOPB6WmXN2f9GIeD1weOPwuzPzsD42cy6tSzNuyJID/naeTesSj1cCP+5jv2YkM7/PkuHAasB3IuKRo+nV3FPtmXw28IDGU0dk5lT7tn8SqM96eUVENPfVHoXmTJxOS1Lf3Cj3svxucy/mrbs5KSI2Bl7ZQzvtrMCSAWKn9p4KPLh26AbgtFm2P1BVEHkC8Kja4YuAJ1UzU+eboxvlQyNi2hliEfF4YO/BdKmj+meAm3EGkCRJkjSuzPOGxDyvd+Z5/WGe9x/meWPAPM88T5IkFeN0o8+3G+XdR9KLNjLz+sz8Ue3xi1H3aaYi4hXAUY3D78/MQ/rZTnXn/KGNwx+IiIVT9G0h8MHG4bdm5j1tqg9dZv4AeDxwa+3wqsC3I2K3frYVEWdHRNYeh/Xz+sMWEfeOiLcBvwQe0nj6m8A7pjq/Wqb02NqhlSg/92bAMF0/VoyIgzo89+SIeGgv12PJGRSXdKh3FWWW04TdI2L5Ltu4EqgvgfzEiJhyhmRErAN8DVizyzam8oqIePI07W0OfKJx+FOZ2SkoGRefAp5SK18FPC4ze5llNWdk5tmU0HbC2sBZEbFRp3MiYg/gywPuWrPNDWjdT/6783A2liRJkjRfmOcNgXnezJnnzZx5nnnemDLPM8+TJEnAcqPuwITMvDYifsrknrC7R8Ry3e5dO9dFxHKUWTLtLGiUV5tigH1Du32RqzaeB3y4cfhrwMemGrB3cHNm3jxNnS8C/4/J3+nawE8i4qBqr+x63/aiLJ+8Vu3wTxjyB9LpZOY5EfHflCBrterwqsBpEfGkaqbQ0qLd6zAoyyCvCawL7ED5/e9K69K+Ez4PvKDL8Oc11bUmlgDdCPhFRHwQOLrTrLyIWBnYhTKD4RlVv45rU3V34FUR8QvgJMryr5dl5hL7cUfE6pTX9tsbT32uXR8y846I+DGTgedGwCkRcTRwOa0zywCum5iBUp37DSZn0C0PfDcinp+Zpzf6tSxloPs+YCFlL/EbgV6W6627ifI3+ZWIeDvwocz8TzBWtfd04CPAvWvnXQH0a9nwgYiIFwHPrx1aTFnOdqUe3w9vz8zr+tm3ATuYMstp1ar8QOB3EfF/lPe1ayh/q1sC+wH7UP6uLwf+Sessr0F5TKP8jSG0KUmSJGkGzPPM8zDPm2vM88zzzPPM8wbBPE+SpCEbmxt9KsczOYhci/Ih+szRdWeoNqR1adypPL16tHMwnfcbfy7lA17d06pHrw4HDpuqQmbeUy3/eT5lIARlidPvRsTlwG+r/jwQ2Lxx+iLgae0GZaOWmedGxOOA71AGwQCrAKdW4cD3Op89r0z1OpzOtcDrM/OL3Z6QmYsj4onAGUwud7sycAhwSERcBVxKWRZ0OUo4sZDy2pp2P/mah1SPI4FbIuJi4HrKoGglymt5O5YMOr6Qmc29x+s+QOvMxsdVj3Z2pyyJPOEwyoB/IozagLLM9NXAryjBwjrAQ2kN144AHkHrUra9eBNlxuCawDspP+fzgb9Wx3agNRAAuAU4IDObYce42aBRXg04awbXOQfYbda9GZLMvLKa0XUK5X0LSkjwqurRzmJKQPCRwfcQqrYm/AODAUmSJGncmed1xzxvhMzz/sM8r5V5XmGeN8bM8yRJUjvjdqPPiZQ711euyvuy9AQD81I1s+uxlN/t9rWntqge7fwS2D8z/zro/s1UZv64CgdOZzIcWBn4VkQ8OTNn+7pdqVFu7us8FyXwM+AY4POZeVvPF8j8Y7Uc79HAsxpPb1o9pnNzD02uAezcRb2jgVdMVSEzT42It1JCtV6CionB3D7AV5kMBwA2rh7tvDcz3xoRZ/fSVsPvKXvZf4syE3EV4NFT1L8e2Dszfz6LNjVgmfm9anny/2NyRl0nvwb2y8zLqtl0E/45iL5FxJrAnrVDJ8zT/dUlSZKk+cQ8b54xz5sx87x2FzDPM8/TrJnnSZKkpmVG3YG6zLyR1qUy94+I1TrV19yQmb+nzOx6M2XP3E6urOo8vNrDeaxl5k8oH2BvqR1embKE614zvW714Xu72qGb6Dyra9zcDdxGmSHyG+BU4P3AM4H7ZubDM/PTMwkFJmTm4sx8NrAt8AW6C03+Qll6el9g/Q513g28kLL8dTeh1G3AycBOmfnSbpYlz8x3UQZi7wF+CFxXXWda1eyih1D2QO80M+4u4LvAHpn5hm6u20W7P6L0+Tha9xavW0zZH3vrzDy/H+1qsKrw5sHA/sBXKO/N/6K8n11CWe76ycAOmXlZddqC2iUGte/5c4AVJ7rJksvTS5IkSRoz5nnzk3leb8zzpmaeZ56n2TPPkyRJdTFuK6lGxBaU5TonbkJ6cWZ+eoRdUp9FxA6U/WInltr8C/D7zLxgdL0aHxHxGFpnvr0tM985qv6Mu4hYhjJwfQBl3/gFwO2UAc4i4JJO+31Pc92Nga0oM2wWUAYr/6LskX0J8JtRLWcbEfemLOG7ESWMup6yfPL5mXnDANtdtWr3fpS90W8CrgbOnk3Yo/EXEStR/qaWrw79IjMfOoB2fgM8qCp+KzP37ncbMxERDwQunih/4pSz2XiLrac4Y265+vJLedneu9UPPSgzfzui7kiSJGkOMs+b/8zzpmae1xvzPPM8DZ55nnmeJGl+G7etu8jMyyPii5S7gAFeHRGfGce9nTUzVQBgCNBZfSnVv+Md8FPKzHuAC6tHP697NWXQO3aqZbBPHkG7t1JmGGnpsxOToQAM4D08IvZkMhRIyrLYkiRJkuYA87z5zzxvWuZ5PTDPG2q75nlLL/M8SZLmsbHauqvmf4E7qq/vDzx1hH2Rhq0eDLwvMweyd64k9eCljfJ5A2jjrbWvT3JWqCRJkjTnmOdpaWaeJ2ncmOdJkjSPjeWNPpm5CPhQ7dCh1XKe0rwWEasDO1TF64GPjrA7kkREPB7Yt3ZoMfC1PrexB7BrVbwdOKSf15ckSZI0eOZ5WlqZ50kaN+Z5kiTNf+M82H47cE319TbAgSPsizQsj2RyS72jqqVVJalvIuLwiHhRRKzYRd1nAic1Dh/Tz5mJVfD/vtqh92Tmlf26viRJkqShMs/T0sg8T9JAmedJkqSm5aavMhqZeWtEHAA8tjq0/FT1pfkgM08DYtT9kDSvbUxZUv/IiPg68CPgd8CNlM8F6wI7AvszOSNxwpXAW/rcnw2Bb1aPu4Gj+nx9SZIkSUNinqelkXmepCEwz5MkSS3G9kYfgMz8MfDjUfdDkqR5aAFwcPXoxtXA3pm5uJ+dyMxrgMP6eU1JkiRJo2OeJ0nSwCzAPE+SJDHeW3dJkqT+u6HH+ncDXwJ2zMzfDaA/kiRJkiRJkjozz5MkSS3GekUfSZLUX5n5uog4GtgT2AnYGrgfsCawAnAL8HfgUuAc4GvusS1JkiRJkiSNhnmeJElq8kYfSZKWMpl5BXAF8IlR90WSJEmSJEnS1MzzJElSnVt3SZIkSZIkSZIkSZIkSXOAN/pIkiRJkiRJkiRJkiRJc4Bbd0mSJPVgxw1W4wEbrzHqbvTN725dbdRdkCRJkiRJkgbmv9Zbha03mD8Z2Br/WGXUXZAkjZgr+kiSJEmSJEmSJEmSJElzgDf6SJIkSZIkSZIkSZIkSXOAN/pIkiRJkiRJkiRJkiRJc4A3+kiSJEmSJEmSJEmSJElzgDf6SJIkSZIkSZIkSZIkSXOAN/pIkiRJkiRJkiRJkiRJc4A3+kiSJEmSJEmSJEmSJElzgDf6SJIkSZIkSZIkSZIkSXOAN/pIkiRJkiRJkiRJkiRJc4A3+kiSJEmSJEmSJEmSJElzgDf6SJIkSZIkSZIkSZIkSXOAN/pIkiRJkiRJkiRJkiRJc8BSc6NPRBwbEVk9Thx1fzS9iFg+Ih4REQdFxOsj4rUR8cyI2DEiYoDtLhcR20XEfhHx6oh4S0S8MSJeFBFPj4gtB9m+NCoRcVjtfTIjYrcBtrWo1s6iaeoe1OjXQf269qBExHGNPi8cRT/mgohYGBG3Vz+nuyNih1H3SZIkSdJ4MM+be8zzpOEyz+sf87zumedJkjR6S8WNPhGxC3BgVbwDePM09c+ufZg7u83zZzY+8H2oj319f+Pa356m/roR8d8R8b8R8a2IuLZx/sA/kEbEKhFxZZt2j5vh9bQ/pRIAAQAASURBVDaOiM8AfwfOBY4FjgLeB3wJ+Cnwx4h4T0Ss3qfvYdlq0P914B/Ar4AvAx8E3gm8B/gU8FXgMuCmiPhadc6K01x7YS+DmmHptV9tBo3tHndGxOLqdXhRRJwSEe+NiP0jYoMhfWuSRiwidus2ZMrMRcDHquIywCciYqn4fCJJkiSpM/M887wu2jTPM8+T1CfmeZIkzS3z/h/e6sPFx4GJGRufzMw/zPKyn22UnxURK8zymkTE8sCzp2mLiNggIk6Kcmf734BvA4cDTwTWn20/ZuBdwKb9uFBEvAD4PfACYKpB/32BNwK/iYhHzrLNJwCXUAb9TwFW6eK0NYGnVudcExGv6MdrYB5YDliV8jrcBngS8DrgROBPEXFeRLw4IlYeYR+Hrs0g6bBR90kaM+8Cbqm+3hE4aHRdkSRJkjRq5nlDYZ5nnjfBPK8N8zxpWuZ5kiSN0Ly/0Qc4ANi2+voO4L19uObXgRtr5XUoA6DZeiKwXq18PXBKm3rrAfsAG/ehzVmJiIcDr+zTtd4GfAZoDrAvAk6uHhc1ntsY+E5E7DiD9paPiE8CpwJbtKlyHfBj4BuUge3ZwKXAPY166wEfqR7qLICHA0cDV0XEc0bcH0ljIjNvooT4Ew6LiJVG1R9JkiRJI2eeN0DmeYB5XrfM8yS1ZZ4nSdJozesbfaoZNW+vHTo+M/882+tm5r+BLzYOP2+21wUObpQ/n5l39nD+PZSB61BUM14+y+Tr6J+zuNbelFlMdWcBW2Xmdpm5T/XYDtga+H6t3irAqRHR9eyniFiOEvC8pPHUYsrSvttm5n0y8xGZ+dTMfGZm7p6Z96fMbjmo0QeApe1D7MnAJo3HpsB2wG6U8OrdlJ/THY1z1weOj4gvOnNKUuUDwO3V1/cDXjbCvkiSJEkaEfO8wTLPM8/DPE9S/5jnSZI0IvP6Rh/gGZTByoSPd6o4A80lePeKiPvM9GLVoPa/G4ePmea0Kyn7Tr+OMhBbsxq4Dsv/Ag+ovr6asud1z6oA56NMLscMZdD+35n5+2b9zLwM2IvW2VHrAof10OxRwBMax74BbJaZb8vMX3c6MTOvz8zPZeYewB7ABT20O58szsxFjccfMvOizDwnM0/OzEOqn9NGlN/PPxrXOAD4qvv3Ln0yc2FmRvVYOFeu3UMfDqr1Iap9qzWFzLwB+Ert0Guqfx8kSZIkLV3M8wbLPM88zzxPM2KepybzPEmSRme+fxh/be3rn2bmhf26cGZeROuAcFngwFlc8rmU/ZAn/DQzf9uh7qXA2pm5eWY+IzPfXw3EFs+i/Z5ExLaUPbUnvBS4dYaXexZl4DjheuD5mXlXpxOq5w4G/l47/IKI2HK6xiLiacD/NA5/Bnh6Zv6t616Xfnwf2IkSOmUv5y5NMvOvmXk4sD3wi8bTT6K3UEfS/HV07ev7As8cVUckSZIkjYx53oCY5/2nH+Z5XTDPk9Ql8zxJkkZg3t7oExE7MbmXN8AXBtBMcxZQc6neXhw0zbX/IzNvr/Y/HYlqmdxjmAwyTsjM78ziks390D/bzfeXmTfSOktqWWDKfaKrZWWbe2+fD7w0M5t7dXclM+/MzJdTlgjWFDLzD5TZar9rPPWmiNhq+D2SNE4y8zzgqtqhl46qL5IkSZKGzzxvcMzzluiHeV6XzPMkTcU8T5Kk0Vhu+ipz1kG1r++h7D/cb18C3g+sXJW3jIhdMvPHvVykCjHqS/TeCpzYny4OxOuBB1df3wi8epbXe2Sj/N0ezj296s+EfYC3TVH/OZS7yifcBRyYmXf30GZbmXnlbK+xNMjMW6tZWBcBK1aHlwcOYQaz6CJiNWAXYAPKks93A38DLgF+OdPAp3btbSn7yC+g/K3fDtwCXAP8PjOv6niBAYqI+1HeNzYF1qAEYzdRvvefZuafB9DmysCuwIbAelV7VwNnZ+btU52r2YmIbYAHUt6/kvJ7Pi8zr+jDtbcGdgDuQ3lP/DPw28xsBnjDchKTM0wfHhFbVUu8S5IkSZr/Dqp9bZ7XX+Z5bZjndcc8rz/M85Yu5nnmeZIkDdK8vNEnIpYF9q0duiAzr+13O5n5j4g4GXh27fDBQE/BAPC8RvmkzPznrDo3INUsjUNrh17b6/K4jeutCKzTOHxxD5f4TaO8dURsOsVg7TWN8int9g3XYGXmZRHxJVpnze0fEa/IzFu6uUZE7EUZPDyCEiy0c0NEfBY4spdZcxGxHSVgegKT4UWnutcDZwGfysxzGs91Wv750Ig4tMNzALtn5tmNa61A2cv+6cCjgftN06/fAx8GjpntoD0iNqAsx/wMYPU2VRZHxBeAt1Qz87q55iJg46p4dT/33u722lP8fnpxTmbu1ubax9EadG3SaV/viNgN+EHt0OGZeVj13IHA64AHdTj3IuBNmXl6rx2PiH2Aw4EHdHj+l5S/na9U5bOBR008n5nRa5tdOoXWpeQPoPXfHUmSJEnzkHne4JjnqR/M88zzzPNa6u6GeV6deZ4kSUM2X7fu2hlYq1b+QaeKfdBckne/iFi125MjYhVgv2muORYiYhlK3yYGSt/PzONmedm12xy7uYfz29X9r3YVqxkTzQ/An+6hLfXXhxvlFSkD3ylFxDoRcSZl9tfudA4FoIRObwQuj4jmTLNO138DcAHwNKYJBSrrUvYdfmE315+F91EGTAcyTShQ2ZKy1/z5EbHpTBuNiJ0pAdwLaR8KAKwGvAS4NCIeNtO2NCkiVo2Ik4Dj6BAKVLYFvlO9bru99vIR8WXKTJu2oUDlwcCXI+JTVeA+LD+nzISd8MQhti1JkiRpdMzzBsA8T31mntcb87yliHmeeZ4kScM0L1f0AR7XKJ87wLbOAa4ENqvKq1OWm/1cl+fvQ1mmc8LvM/NH/eteX72csqQqwG3Ai/twzTvaHFuRstxkN9oN3B4AfLPN8Uc1yncBP+yyHfVZZl4UEX+jLBk7YRfKYKWtiNicshR0c6D7T8pg/q+UJW8XUgY1Ezcz3gs4MyL2zsyOS0lHxLOAI5tdBX5L2Wf4Fsprbk1gK2AjYFCzIJqaN2b+i7Kc8bVVv1YA1qcMFOsD+G2BH0TE9t3OzqnZHHgvZZljKH/351N+zgsoP+P6729d4IyI2CMzf9FjW5q0DGUp+b2r8t2U1/cfq683B7an9bV3ZET8JjO/M9WFIyKAr9auPeFuyoD8GsprfEsml6B/EXDDTL+ZXmXmnRFxHvCY6tD2EbHebGabSpIkSZoTzPMGwzxPfWOe1zPzvKWHeZ55niRJQzVfb/R5eKN8YS8nt1u2cYq6GRHHAO+qHX4e3QcDzWV+j+m27WGKiIXAEbVDh/djL1nKnsD30DrouQ/Q7bXv0+bYVh3q7tIo/zYzb+uynRmrlvcc1uCxa2PSr/NpHaBs26liNVvu67SGApcBbwG+0dyXPSLuQ1nGdGJmzgrAFyJiu3b7XVcz3I5qHP4Y8K7MvK5Dn9YG9qTMAGq3L/wm1X8fDpxQO/5h4EPtrllp2x4lhDweOA34Vbv9yiNieeApwHuY/FltBHyCslRvL46iBAB3AO8APpiZ/5mZUc0K2Yfy/dy7OrwG8KWI2HYYf1+ztMn0VVqsDJzM5IAZ4C/9685/vJQye+1uSjDzvsz8e71Ctez68cCOtcMfiYgtM3OqJYxfyZKhwCeBQzPz+kYbD6L8DTwKeDPl/bor1VLVs3l/uZDJYCAof0OnzOJ6kiRJksafeV6fmefN3JjkZksYk36Z57Vnnjcc5nmFeZ4kSUu5+Xqjzw61r2/OzD8NuL3jgLdTZh4A7BoRm2XmlVOdVC2/WV9+9C7KB71x9BlgYgnji4D39+OimXlPtffw/2fvvqNkK8q9j38fssQDAkqQpJJEzAQVBUHMOSEGwHjVe83hNQNXvV4VMxhRwIA5X1FMGFAQUBQliyBJAfGQJPO8f9QeZvee7pnumQ7TPd/PWr3O7Orau+rMdM90/dauqm1rxbvQfTCwa5uydTrU3aRxfEaXbWhwzqR1kLLZLHXfS+uSp8cAT+k0+MzMS4EXRcSZTL9e16cMcJuBHMD9gY1rx0dm5n/N1vlqRs2XgC9FxB3aPH8+3B6s1S3vtL/zLN4DvLxdGNBo82bgqxHxY+CnwL2rp54WEW+aZb/7dtalDE6fkZnfatPWrZSlYH9HmWk5FQ7cHXgTZV/0RauXn0FErAR8g9ZQ4PeUJY77bSoUeGJmfq9dhcw8KyIeDvyJ6aWf70bZ7/0n7c6JiDvSGvACvDozP9ChjT9FxF6UMOTxtF+afVD+2DjeiT4FAxGxIWW2Wi/uOncVSZIkSQtkntd/5nkaBPO87pnn9Zl5HmCe1y3zPEnSRGsuHTn2IuLOtA4MLxh0m5l5CWV/4du7ARzQxakH0HqH9PerwcyiEhHPZ/pO7NuAF2Zmt0vxduPnjePn9HDuc9uUddp3uPmhdnkP7WgwmjMK2n5Yj4iNgRfUis4HntrNDJPMfD/w/VrRs6rfE02bN46/Nte1G+0MdLZLZv5trlCgUf9ftH7PVqDMVOrVR9qFAo22zqHMWqn7j4joZk/0cfEp4HG143OBR2bm1QNq7387hQJTqrabS1M/bJZTngesXjs+plMoUGvjFmB/yvLOw9T82711H6/9Ukqg0suj3fLxkiRJkvrEPK//zPM0QOZ53V/fPG+0zPOGyzxPkqQhmrgbfSh7+dYNevbPlOYSvftVS4e2VT23X6P48L73aoGqAdn7akUfzsyT+tzM5xrHe0fEo+c6KSIeB+zZ5qlOwcAdG8fL5+6aBqwZDMyYRVP5D8pSvVMOysx/99BOfcbaKsAjuzhnw7mrLG6ZeQqtA6wH9niJm4B3dNnWN4Hf1YrWBx7TY3uLUkS8lzI4nnIpsPcA95i+nu5nWTbDg/vMUrcZDHX7s/0XZcnfYWr+7d5iyO1LkiRJGq4tGsfmeQtgnqcBM88bIPO8/jDPM8+TJGnSTeKNPs0P813vQbpA3wXqHxI3BR4+S/29mF6eEcrd1d/vUHeUDqPs6QtlgPGWfjeQmcczcxbQFyPiIe3qA0TE7sDnOzzd9SwJjVzzd1CnvYjr76Vb6XF2DvArylLaU3ZrU+fMxvEbO8wUWlSiWDMiNoqILZoPoL5P83YdLtPJD5t7Sc/hi43jB/fY3qITEa8HXlsrWk6Z+fPXATb7m2oZ6Tll5gVAPSRrG2hFxBrAjrWiizPz1z306Ss91O2H5t/usQ/qJEmSJM3KPK+/zPM0SOZ5C2SeN1jmebczz5MkaYKtNOoODMDqjeOBLr85JTNvjojPAa+pFR8A/LDDKc09hY/s8/K5CxYR+wBPqBW9JDOvG1BzzwNOpuwhDGW55p9FxNHAV4FzKMsi3w14OuVO9qllki+iBDFTlndoo/lBu9Pe3xqeZY3jGe/XiFgNuF+t6EJg/YhYv8e2llNmpUCb/Xkz87SIOA24Z1V0N+DMiDiCEkScsBjeoxGxCrA38GTgvsC2QLdL6q47d5UWJy6w/gN6PH9RiYj9aV1K93rgcZnZ3G+6307vsf5ypv/2dfq9tgOwYu345B7bOAe4apbr91tzht8afbz2YZS/K724Ky73K0mSJA2SeV6fmOdpCJY1js3z5mCeNzzmeS3M88zzJEkTbBJv9Gn+n4b5Qf5wWoOBJ0bEutUyibeLiHWBJzbObS4VPFLVoOvDtaKjM/OYQbWXmedFxBOBbzK99/YKwLOqRycnAkcBh9bKlneo25zJsKzXfqrvmgPVy9vUuTOwcu14C2Chsy+a+7tPeRHwM2C16ngd4BXV47qIOBH4DWVG0fGZec0C+9GTiHgC8AFgy3leotdB3dk91j+ncTy2szYi4vGUfbyn3AI8IzN/NYTme525enPt65U71GkGac09s2eVmRkRFzK8YKD5t7vT/6tn1RLNPS3THBFzV5IkSZK0EOZ5fWCepyExz+uBed7wmOe1Ms8zz5MkTbZJ3LqrOYOg0x7BfZeZZ1AGDVNWBfZtU3VfWu/Y/1VmnjXIvs3Dh4ENqq+vBF456AYz8xfAzsCPu6lOuYt7T2YOLv/e4ZxLGse9Lnuq/tu+cdxusNLci70f2u77npknAA8Cft/m6TWAhwFvBo4BLo+Ib0XEXgPo3wwR8UrgW8w/FIDpWXPdurrH+lc1jjsFMItaROwGfJnpoDmBF2Tmd4fUhUEsV76scTyfUKvX18NCNP92D2r2qSRJkqTFwTyvP8zzNAzmeV0yzxse87yOzPMkSZpQk3ijT/ODSz+XB+zG4Y3j5pK+7cqa54xURGxDWUp3ygeB1dvtF9zYO3hZ41JrNupsNlfbmXluZj4ceCDwPspylP8AbgKuoAzY3gPsmJkvq5Yebg7wOy1heXzjeIeIGFpwpLZ2bhz/oU2dVQbQbscBcmb+jrK08N7AZ4G/dai6KmUp7B9FxPciYhABBgARsTNwSKP4fOBdwGMpAct6lMHUCpkZUw/g5wtoutMe693W7/X8kYuIHYHvMj0LDOD1mXnkiLrULzc2jufzvhrEe7GT5t/uYYYSkiRJkobPPG+BzPM0ROZ5XTDPGx7zvFmZ50mSNKEmceuuCxvHGw25/S9TBtJrVsf3jYgdp/aArT503rdW/xp631t00JqD5YOrR6+eUj2mXEWXy+tm5m9onU01m10bx532IW4OkFYCdgOO7bId9VFE3IeZy4+2W0b1isbxsZn5iMH0qsjMBH5UPYiIuwC7UF4vDwPu0TjlMcD3I+JBA9r3++203pj5SeBlXba19gLa7XVZ12WN416XrB2piNgS+AGt/+/3ZOb7RtSlfmr+LHrd3x2GO6Nr48Zx82+7JEmSpMlinrdw5nkaOPO8npjnDYF53pzM8yRJmlCTuKLP+bTedb7pMBvPzGuBrzSK6zN+nt947svVLBbNQ/VBfqta0UWZeW67upn5N+CMRvGLBtU3zekVjeMbaB/S/KNxvPVgutNZZl6YmV/NzJdn5g5VHw6ldUnWnYD9+912RKxBWdJ6ynl0HwrAwsLRXr/Xd28c97Rv8ihFxJ0oQVD9+/XZzHzDiLrUb81ltO/Zy8nV63CLvvVmbps0jv86xLYlSZIkDd/5mOctGeZ5Y808rwvmecNhnjc78zxJkibbxN3ok5k3APX9sTeLiNWH3I3m0r3PiohVImIVZu7xvaiW+R1DvS6b/P7G8RMi4m597I+6EBHb0rqcNMDRVbDWIjOvBv5cK9oiIpoD0KHKzHMy8z+B/9d46kmdTllAc5vTusTqD7oNBSJiK+DOC2h7lx7rN5duPmkBbQ9NRKxNmflz11rxd4AXjqZH/VcFpvXZdPeOiGU9XGJ3hvuZobmE+6lDbFuSJEnSkJnnLTnmeWPIPK8n5nkDZp7Xld0xz5MkaWJN3I0+lfqH0RWAHYbZeGb+GjizVrQ+8Djg8bQubXp6Zp4wzL51IzNPre8J3O0DOKhxqSMbdZb1s58RsS6tM3huZe5g4CjgktrxSsCREbHg90JE3HXuWqpmEnyd1sHuTcD/zHLaDxvHi2XA1ny9bdmhXnM/5VV7aGNZ4/iqHs7dv4e67ezd417lzeCz3dLNi0pErEYJAe5dK/4l8IzMvHUknRqcn9S+XhV4bg/nDnu25I6N498OuX1JkiRJw2eetwDmefPuj3leF8zzAPO8RcM8r2vmeZIkTbBJvdGnuXfzTiPoQ3PA8Dx6n62i2R0CbFg7/lhmzrrva2beBLyyUfxA4ND5hgMRsXJEfAR4y3zOX0qqpZmPA7ZvPPWuzDxnllM/BtRnvfxXRDT31R6F5kycZgAwZXnjuJfld5t7MW/bzUkRsTnw8h7aaWcVunxdR8STgPvWiq4A/m+B7Q9URKwIHA08tFb8B+Bx1WzSSfPxxvHbI2LOGWIR8WhKsD1M9b/by3EGkCRJkrQUmOctDeZ5Y8Y873bmeYuAeZ55niRJKib1Rp/vN473GEEfjgJurh0/Ati7dnwz8Lmh9mgRqz6gd1s3IuK9wAG14guAN3ZzfmZ+Ffhwo/g/gK9ExPptTpmtLw8DfgP8JxC9nDvHdY+LiKw9DuzXtUchIu4UEW8Ffgfcv/H0t4H/nu38apnSz9aKVgO+HxHNgGGufqwaEft3eO4JEfGAXq7HzBkUzT3jp5xHmeU0ZY+IWLnLNv4C1JdAfmxEzDqrsXodfwNYp8s2ZvNfEfGEOdq7G3BYo/gTmdkpKFksPgE8sXZ8HvDIzOxlltXYyMzjKLObpqwH/DgiNut0TkTsCXx5wF1rtrkxrfvJ/3ACZ2NJkiRJmsk8b8yY5824rnlejXmeed6AmOeZ50mSJMoypxMnMy+NiBOZ3l92j4hYqdt9cPvUh8si4ntM7/HbHPh+NzMvn+/1qw/+a3ZZfdOItmPWWzLzovn2oc+2i4ivUWZFfTszz25WiIiVKPvKvoPWvYNvBJ7Tbj/oWbyW8sHzkbWyp1CWNv0A8NXM/FO7EyNiA+BRwH7Aw3poc9KsGRFbNMoCWIsyIN0AuB/lZ7UbrUv7Tvkc8ILMvK2L9l5dXWtqCdDNgJOrn9fHO83+iog7AA+izGDYp+rXEW2q7gG8IiJOBr5KWf71rMycsR93RKwFvAw4uPHUke36kJk3RcTxTIeUmwHfiYiPA+cA/26c8vepGSjVud8Cnl09tzLww4h4fmb+oNGvFSkD3fcBW1D2Er8S6GW53rp/AetSQrODgQ9m5nWN9p5CCdruVDvvXOBd82xzKCLiRcDza0XXUpazXa3N63o2N2Tm3/vZtwE7gDLLaY3q+B7A6RHxaUqo/jfKe3Vr4OnAUynv63OAa2id5TUoezWOvzWENiVJkiSNmHneDOZ5M5nnLZx5nnmeeZ553iCY50mSNGQTeaNP5SimB4/rUj6Q/2jIfTic6WCg3XML8T7KwLQbv+xQfgFl8LBYbAO8B3hPRFwG/ImyXCiUQceOlJ9l3fWUvXc7/R/bysybq1kNhwIvqD21FvA24G0RcSllgHMFJXy4E2WJ1q1pvxpWc3A36Z5SPebjUuB1mfmFbk/IzGsj4rHAsUwvd3sH4E3AmyLiPOBMyrKgK1HCiS2AuzEzmJvN/avH/wJXR8SfgMspg6LVKIP6ezMz6Ph8Zjb3Hq97P62zER9JazBVtwdlSeQpB1IG/FNh4MbAMRFxAfB7ymtvfeABtL5H3gU8mNalbHvx/yjvyXUogdybIuIE4B9V2f1oDQQArgb2zczF/n7YuHG8JvDjeVzn55TAcixk5l+q333fAVavitcAXlE92rmWEhA0Z04OylNrX1+FwYAkSZK0lJjnTTPPazDP6wvzvFbmeYV53iJmnidJktqZ5Bt9vkQZPN+hOn4aww8GfgBcwswPoBcDsw0gVPbqnmt2zenAszPz9/NpoNrf+4UR8V3KoO2ujSob0d3ey5cABwGfmU8/Olitcdzc13kcJfBbyvfpc5l5fc8XyLywWo7348CzGk9vVT3msryHJtem7Pk+l48D/zVbhcz8XkS8hfJa6SWomBrMPRX4Gq0z/zavHu28NzPfEhHH9dJWw9nAY4HvAssoA8nZ3peXA4/PzJMW0KYGLDN/EhG7A59mekZdJ38Enp6ZZ1Wz6aZcM4i+RcQ6tC6Lf/SE7q8uSZIkqT3zvPFmntfKPA/zPMzz1AfmeZIkqandLIaJkJlX0rrs5jMiotulcfvVh1tpv6Toke5POsMllMHV+V3U/R3wQuBe8w0F6jLzO5TZR0+j3BXfzYB1OWU52CcCW2TmJ/u1lHT14fvetaJ/0f51tBjdSvn+/QM4DfgecAjwTGCTzNyl+l71HApMycxrM/PZwL2Az9NdaHIJ8AXKz/jOHer8D+V19Y2q/3O5Hvg6sGtmvqSbn39mvpMyEHs38Avg73T3eqOaXXR/yh7oM5YfrtxCCR33zMzXd3PdLtr9FaXPR9C6t3jdtZT9sbfNzBP60a4Gqwpv7gs8A/gKZT/zf1NmcJ1B+f32BOB+mXlWddqy2iUGte/5c4BVp7oJfGhA7UiSJElahMzzxo55XsU8b3bmeeZ5WjjzPEmSVBdttqudGBFxd8rSn1M3NL04Mz85wi6pCxGxMWUgsgXlg+hKlIHHX4GTMvOSAbe/MnBPypK+G1FmPdxCCQOuoNwRf267vZ771P5etM5We2tmvmMQbU2CiFiB8nrZHliP8pq5gTLAOR84o9N+33Ncd3NKYLR5dc1VKQOnKykDp9NGtZxtRNyJsoTvZpRZjpdTlk8+ITOvmO3cBba7RtXuXSh7o/+LsmT4cQsJe7T4RcRqlPfUylXRyZn5gAG0cxqwQ3X43cx8fL/bmI+IuAdl+XkATj75ZLbffvsR9qi/Tj/9dO5///vXi3bIzD+Pqj+SJEla2szzxpN5nnleL8zzzPM0eOZ5rXneL0/4LdtuNzl53plnnM5uu+xULzLPk6QlZpK37iIzz4mIL1DuKAZ4ZUR8alADOvVHNfAf6OB/jvZvpswy+t2IulBfSvWfeAf8rDLzNuDU6tHP615AGfQuOpn5D8rso2G3ex0uU75U7cp0KABwSr8biIi9mQ4FkrIstiRJkqQlxjxvPJnnmef1wjxvqO2a5y1d5nmSJE2wid26q+ZtwE3V19sBTxphX6Ru1IOB92XmQPbOlaQevKRx/JsBtPGW2tdfzcy+hw+SJEmSxoZ5nsaNeZ6kxcY8T5KkCTbxN/pk5vnAB2tFb6+WBpUWnYhYC7hfdXg58JERdkeSiIhHA0+rFV0LfKPPbewJ7FYd3gC8qZ/XlyRJkjRezPM0TszzJC025nmSJE2+pTJAPhj4W/X1jsB+I+yLNJuHML2l3nuqpVUlqW8i4qCIeFFErNpF3WcCX20Uf6afMxOrsP59taJ3Z+Zf+nV9SZIkSWPLPE/jwjxP0kCZ50mSpKaV5q4y/jLzuojYF3h4VbTybPWlUcnM/wNi1P2QNNE2pyyD/78R8U3gV8DpwJWUzwUbADsBz2B6RuKUvwBv7nN/NgW+XT1uBd7T5+tLkiRJGkPmeRoX5nmShsA8T5IktVgSN/oAZObxwPGj7ockSYvEMuCA6tGNC4DHZ+a1/exEZv4NOLCf15QkSZI0GczzJElqsQzzPEmSxNLZukuSJBVX9Fj/VuCLwE6ZefoA+iNJkiRJkiSpM/M8SZLUYsms6CNJkiAzXxsRHwf2BnYFtgXuAqwDrAJcDfwTOBP4OfAN99iWJEmSJEmSRsM8T5IkNXmjjyRJS0xmngucCxw26r5IkiRJkiRJmp15niRJqnPrLkmSJEmSJEmSJEmSJGkMeKOPJEmSJEmSJEmSJEmSNAbcukuSJEmSJEmSJEnSRMrqMSkm6f8iSZofV/SRJEmSJEmSJEmSJEmSxoA3+kiSJEmSJEmSJEmSJEljwBt9JEmSJEmSJEmSJEmSpDHgjT6SJEmSJEmSJEmSJEnSGPBGH0mSJEmSJEmSJEmSJGkMeKOPJEmSJEmSJEmSJEmSNAa80UeSJEmSJEmSJEmSJEkaA97oI0mSJEmSJEmSJEmSJI0Bb/SRJEmSJEmSJEmSJEmSxoA3+kiSJEmSJEmSJEmSJEljwBt9JEmSJEmSJEmSJEmSpDHgjT6SJEmSJEmSJEmSJEnSGPBGH0mSJEmSJEmSJEmSJGkMTPSNPhHx2YjI6vGlUfdHc4uIlSPiwRGxf0S8LiJeExHPjIidIiIG2G5ExLYR8cSIeFlE/L+IeHNE/FdEPDci9oyI9QfVvrQYVO+7rD32H2Bbx9XbmqPu7o1+Hdivaw9KRBzY6PPuo+jHOIiItSPistr36omj7pMkSZKk0THPGz/medLomOf1j3le98zzJEkavZVG3YFBiYgHAftVhzcBb5yj/nHAQ6vDn2fm7o3nfwTsVSv6UGa+sk99PQR4da3omMx89Cz1NwDuDzygetwfuHOj2paZeX4/+tehD6sDpwFbNZ46MjP3n8f1NgfeAjwDWKtDtYsj4vPAOzPzml7baNPmCsCjgGcDjwSWdXHOJcCPgK8Dx2bmjV22VR+cHJSZB/ba30HopV/VIPGzc1zyVuBG4FrgMuAi4Czgd8AvM/OvC+mvpPEQEVsA9ff7AZl5RLu6mXl1RBwMfKQq+mBEHJuZ/x5sLyVJkiQtNuZ55nldtGmeZ54naQDM8yRJGi8TuaJPNeA7FJiaMfKxPgxIDm8cPysiVlngNYmIlSkD09naIiI2joivRsT5lAHX94GDgMcyMxQYhncyMxSYl4h4AXA28AI6hwIAmwBvAE6LiIcssM1HAX8CvgfsQxehQGVjSuD0HUpQ8eaIWHshfZkwKwKrAxsCO1ACl1cARwLnRcQfI+K1EbHOCPs4dBGxRWM2yBGj7pO0yHwcOK/6enPg/42wL5IkSZJGwDxvKMzzzPPaMc9rwzxPmpN5niRJIzSRN/oA+wL3qr6+CXhvH675TeDK2vH6wOP6cN3HUgZRUy6nDDqbNgSeSvnANFIRsQvw8j5d663Ap4BmyPIHyiybr1df120OHBMRO82jvZUj4uOUYGW7NlWuBn4LHAN8Efg/4CTgH23q3hF4B/DTXvuxhN2T8n78W0S8qgrxJC1xmXkL8L+1oldHxIad6kuSJEmaSOZ5A2SedzvzvN6Z50mawTxPkqTRmritu6oZNQfXio7KzIsXet3MvDEivgD8V634eZSB60Ic0Dj+XGbe3MP5t1Fmz2y7wH50pZr1dDjTN4ldw+yzdma71uMps5jqfgy8LDPPbtTdBjgMeFhVtDrwvYjYMTP/3mV7K1Nm/OzdeOrf1bW/Bpycmbd2OP+ewMMpM4B2rD21WjftT6ATKbOnmtaizKhaD7g3sDOwG7Bmrc7awPuBR0fE0zJz+SA7KmksHAG8nTLTcg3K8u99CaElSZIkLW7meYNlnmeeV2OeJ6mfjsA8T5KkkZjEu+/3AbasHR/ax2s3l+B9RERsNN+LRcSdKXtK131mjtP+AnwZeC2wO7BOZrabyTIobwO2r76+APjEfC5SDdI/wvRyzFBmWT2qGQoAZOZZwCNonR21AXBgD81+kJmhwDco+5+/LjNP7BQKVH04LTPfn5n3oszc+m0PbU+iGzLz/DaP0zLzl5n57cw8qNqfflPgNcCljWvsBRwbEWsMvfcaqczcPTNj6jEu1+6hDwfW+5CZx42iH+MkM28CPl0rekFErD+q/kiSJEkaKvO8wTLPM8+bYp6neTPPU5N5niRJozOJN/q8pvb1iZl5ar8unJl/AE6pFa1ImQ0yX8+ldVWlEzPzzx3qngmsl5l3y8x9MvOQzPx5Zl67gPZ7EhH3ouypPeUlwHXzvNyzgM1qx5cDz6+We2yreu4A4J+14hdExNZzNRYR+wIvbRR/EHhqZl7Wbadrffk/YFfgzZTlpDWLzLwqM99PWYL7h42nHwB8bPi9krQIfQqYCmjvwMzf25IkSZImk3negJjntfTFPK8H5nmSumSeJ0nSCEzUjT4RsSvTe3kDfH4AzTRnATWX6u3F/nNc+3aZeUNm/msBbS1IRKxEmZ00FWQcnZnHLOCSzf3QD+/m/5eZV9I6S2pF4DmznRMRqwKHNIp/Crw6M7OLvnbqy22Z+S7gifO9xlKTmZcDjwF+1njqORHxsDanSFpCMvMi4Be1ohdFxER9VpEkSZLUyjxvcMzz2vbFPK9H5nmSZmOeJ0nSaKw0d5Wxsn/t69tY+H7b7XyRMsi8Q3W8dUQ8KDOP7+UiVYhRX6L3OuBL/eniQLwOuG/19ZXAKxd4vYc0jpuzQmbzg6o/U54KvHWW+gcAd64d3wjsv5BQoC4z/9aP6ywVmXlrROwD/ImyXPOUt1MCm55ExGqU2VibVdcLyoyyc4ETZptV1uW1d6Qsb70eZZ/hGyl72V8InAOc3a/XUo99u1PVr7tS9lBfBVgOXAGckpl/GUCbKwMPAjYHNgKuBi4CjsvMq/vdnqZVMx3vRVk2eyXKa/yUzDytD9fenPIe2ogStl5MeV2fMuuJg/MVYI/q602Ah9Pb3whJkiRJ42X/2tfmef1lnteBeV5vzPP6wzxvaTHPM8+TJGmQJuZGn4hYEXhareiUzGzuH7xgmXlVRHwdeHat+ACgp2AAeF7j+KuZec2COjcgEbENZdA25TXzWR63dr1VgeY+rX/q4RLND8LbRsRWmXleh/qvahx/PTMv7KE99VlmXhYRHwUOqhU/JCK2qfZvn1NE7ExZankvpoO6pqsj4mjg4My8pNv+RcRdKWHTk4G15qh+VUQcB3w2M7/duM75lEF0034RMdsy4Qdk5hGNa60IPJQShO0F3H22TkXERcBhwGGZedUc/4dZRcQy4C2U5ck3aFPlxoj4JvD6bt9b1ffsoVPH/dx7u9trz/Lz6cUFmblFm2sfSOvvzT067esdEVsAf60VHZmZ+1fPPZbyOt+lw7nnAW/LzC/02vGI2AN4N7BTh+fPBj6YmR+rjo+gdXn7LTPz/F7b7cJ3aF3+e18MBiRJkqSJZJ43OOZ56jfzPPM887yWultgnldnnidJ0pBN0vJ5DwTWrR03lxLtp+aSvE+PiDW6PTkiVgeePsc1F4VqicXDgVWrop82ByzzsF6bsuU9nN+u7j3bVazubG/u+f3pHtrS4BwG3Nwoe/xcJ0XE6hHxReAEypLRnUIBgLWBFwPnRMRTu+lURDwL+DNlADRXKACwDvAEWmelDcIrgJ8AL2GOUKCyKfAu4NSIuO9clTupgsFTgdfQPhSA8vthH+D0iJjzZ6i5RcSKEfER4Lt0CAUqWwGfj4iPRkRX4UoUH6DMuGsbClS2Bg6LiG/38jduoaoQ7+xa0aNd7leSJEmaWOZ5A2CepwEyz+uNed4SYp5nnidJ0jBNzIo+wCMbx78cYFs/B/5CWWITyuDhqcCRXZ7/VMqAZcrZmfmr/nWvr/6TsrQnwPWUQdZC3dSmbFWg2yVZV21Ttj3w7TblD20c3wz8ust2NECZeUVEnAo8oFb8IOC9nc6JiA0oSz03B7rXA78HLgFuBe5SXXfl6vnVga9ExAsy8zN0EBG7AZ+jLBdcdzZlWd+rKEuhrg3cjfI7YFgDlmY7NwFnUpbanerXBpTlYOvh2xbATyPifvNY/veOwLGUZZShvH9OpCwFuyYlkNusVn9N4GsR8eTM/F6PbanVh4CXVV8n8EfgPMpS05tTXt/1v+EvowRa9ZkznXyY8ru9LikB0F+rr7cC7k15Lzwe+CQzg7xB+gXToe76wP2Ak4bYviRJkqThMM8bDPM8DYR5Xs/M85YW8zzzPEmShmaSbvRp3iF9ai8nZ+buPdTNiPgM8M5a8fPoPhhoLvPbcaAyStXyk++qFR2Umef24dL/ouy5Xh/obETZg7kbG7Up26ZD3Qc2jv+YmTd22U7f9HMZ035aBP36Da3BwL06VaxmABxNayhwCWUJ2i82f67V8rSvB95Aea0FcGhEnJKZf+jQzHtoDQW+Aryx0zLSEbEmsCdlmfF2r8sHU37PbkprWPl14LUd+gBlX+52/k75PfM9OuxXXn2f9qIs4Xqfqngd4AvMPpOknTdTZlYm8BHK74ArG+09nDIYnQpKVwaOiIh7ZOY/emxv2KZ+Pt1agfL7uh44dr2EdA8ew/Ry6J+mfN8vqleIiE0og/VH14rfHRFHZeZ1nS5czdBqhgJfA16bmRc06m4OvJ+y5PW+dH5dzlAtAbyQ3y+nNo53xWBAkiRJmkTmeX1mntc/iyA3a2sR9Ms8rz3zvOEwzyvM8yRJWuIm6Uaf+9W+Xt78EDUARwAHU+66B9gtIu461x32EbEV8JBa0S3AUQPp4cJ9Cpha3vEPwCH9uGhm3lbtFbttrXgXug8Gdm1Ttk6Huhs3js9uW0ujcmbjeNOIWCEzb2tT9zWUQfiU3wF7Z+Y/2104M5cDb4qI31EG+AGsBnwAeFizfkRsSOvA+Thgn8zMTp3PzGspM8++HREzlhye+j3UZgXWa+exF/IXgQ9l5qyzMKrv3bER8fOqb4+onto5InbvtK90B1PLp788Mz/aob0fRcSulBkbU+/pOwLvA57TQ1tD1+vfiYg4jNZQ4G+UUKjfpkKBl07tp92UmRdHxBMoS15P/f1bm7Lkctul4yNiJeDQRvGHM/MVHdq4AHhKRBwKvLTWr2H4Y+N4tiWJe1K91zstW93JXeeuIkmSJGkezPP6zzxPg2ae1z3zvD4zzwPM87plnidJmmgTsUdmRNyZ1oHhBZ3q9ku15+gP6t0ADuji1ANovSv6+5l5aT/71g8R8XzKLAIos3Ve2G62wQL8vHHcywDiuW3KOu293Nw/fHkP7Wjw/tU4XglY1qxUDbrre2ZfBTy2UyhQl5lfo3X50z067HG9eeP467OFAm3aub7buvORmZfMFQo06t9I+X1TP+dZ82j6W51CgVpblwPPpvyumPKM6nfzRIiIgyj7qU+5ghJMXTygJr/YKRSYUv1OfnujeEboVfMkymy0KX+kBG5zeSVlGeFhav4d37ptrfl5KfCnHh/tlpKXJEmStADmef1nnqchMc/r/vrmeSNknmee18f2JUladCbiRh/KnrV1g579M6W5RO9+1TKbbVXP7dcobnun9ihFxMaUu/enfDgz+73E4ucax3tHxKPb1qyJiMfROgtkSqdg4I6N46u66NtUWztERHb5OKLb66pFMxgAmDGTBngmrXfsf7DHQK05e+3xXZyzYQ/XX5Sq71F9D/vm0tfdeFuXbZ0CfKtWtDJledixFxEvo/X7cC3wqMw8a4DN/neX9Y6l7O8+5T6dKlLeR3X/203gWwVS7+6yP/1yCa1B0xZDbl+SJEnS4G3RODbPWwDzvNvbMs8bPPO8ATLP6w/zPPM8SZIm3aTc6NP8AN9usDEI3wUuqx1vCjx8lvp7AXepHf8D+P4A+rVQhzE9C+MCyp7JfZWZxzNzFtAXI+Ih7eoDRMTuwOc7PN1uaVgtfu1+B7WbddN8X325l0aqPbn/VivarU21c4Bba8cviYht29RbdCJi9Yi4U0RsHhFb1B+0/j7cNtqsOzyL0zLztB7qf7Fx/OAezl2UIuIZwIdrRTcBT8rMkwfY7HmZ2VwGu61q0F5fYn62QKu+TPrNwDd76NM3KEvTD0UVWFxbK1q/x9euJEmSpMXPPK+/zPM0LOZ5fWCeNzjmebczz5MkaYKtNOoO9MnqjeOBLrk5JTNvjojP0bpU4gHADzuc8rzG8ZF9Xj53wSJiH+AJtaKXZOZ1A2ruecDJTO8bvA7ws4g4GvgqZaAWwN2Ap1PuXp/6YHgRrUtWLu/QxpWN4057f2s0lrUpa/f+rQ8wbwJurAa9vbgS2Kz6esb+vJm5PCKOAR5bFa0P/D4ivkDZE/wXmXlDj232XTWTcHfgqcADgO2Z+TuwkxUo+z53OxPuxB6716z/gB7PX1Qi4uHAUUwHWLcBz87MHw+46dN7rF8Pf9r+jouIOwH1pZdP72V56sz8d0ScDuzYY98W4t+U1yuU3/2rA/34e3QY5W9ML+6Ky/1KkiRJ/Wae1yfmeRqyZW3KzPNmYZ43POZ508zzzPMkSZNtUm70af4/hjnYPpzWYOCJEbFuZrbMQoqIdYEnNs5tLhU8UhGxPq13uh+dmccMqr3MPC8inki5C31q7+0VKPsOz7b38ImUD+uH1sqWd6jb3PO5l2DgLGDLDs+9EnhFD9dSe+s2jm+m8bOsBsIb14pWoXXGw3w093qf8kpgF0ooALAa8PzqcWNEnAycAPwS+GVmNoOngYqI3YCPsrDB2Tp0Hwyc3cuFM/OiiLiB8n2DMV4uOSJ2osx6WaVW/J+Z2euAcj56ncVa37e909/19RvHzT2zu/E3hhsMNP+Wr9yPi2bmZbTO3p2Tk48kSZKkgTDP6wPzvBnM8wbPPK8H5nnDY57XlnmeJEkTalK27mrexdxuT+CByMwzgN/Uilal/T62+1bPTfnVgPeDnY8PM71v8pWUQdJAZeYvgJ2Bbu6oT8qd23syc0D59w7nNPd93qaHvt2cmee3e9A5iFBvtm8cX5iZzaV+16X/v6va7gGfmX+hvB5/1ubpVYEHUYLAbwGXRcSPIuIpw1iCNCKeCvyEhQ/MevleXj2P69dDh1UiYo15XGOkqiWevw+sWSt+e2Z+bEhdGMTS5csax9fM4xrzeT0sRPNv+aBmo0qSJEkaDfO8/jDPa+2bed7gmed1yTxveMzzOjLPkyRpQk3KjT7NDyvD/iB6eOO4uaRvu7LmOSMVEdtQltKd8kFg9eb+wG32C17WuNSajTqbMYfMPDczHw48EHgfZfnff1CWdL0C+D3wHmDHzHxZtfTwdo3LdNpf99eN4x0jYtW2NTUKuzSO/9CmziptygYmM8/LzIdR9j8+lLLkdDsrAnsBXwN+HRGbD6pP1bWPpHUGxGXAB4AnU8KC9SlLoa6QmTH1qM6br3b7q4/iGkMTEZsCxwJ3rBUfmpkHj6hL/XJj43g+76uhvhdp/Vt+Q7V/uSRJkqTJYZ63QOZ5GhHzvC6Y5w2Ped6szPMkSZpQk7J114WN442G3P6XKQPpqbvF7xsRO2bmHwEiYkfgvrX619D7fqKD1rzT+uDq0aunVI8pV9F+3+YZMvM3tM6mms2ujeNOew8f1zheuTq3Wa4hi4gNmTmb5VdtqjaXaz47M7ueyTVfmXkCZVnfqb7uQtlbfA/gfkzvL0/13E8j4n6ZuXwA3XkDrft2fxd4ZhWSzWXtuat01MvS2O3OuSkz/72A9ocqIu5ICQXuUiv+EvDy0fSor5rLBzdnUXaj0xLZfVctj79araj5d16SJEnS+DPPWzjzPA2VeV5PzPOGwDxvTuZ5kiRNqElZ0ed8Wu8y33SYjWfmtcBXGsX1GT/Pbzz35S4/0KuNiNgS2KpWdFFmntuubmZewMx9iV8wqL6pJy9l5h6932lWysybaB3UbBkRfdnbt1uZeVlmficzX5+ZD6AMHN9J66yKrYDXDqgLT6h9fS3w7B5+h2w8d5WOtu6lcjV7pj6Y62nf5FGqliT+P1pnFx4LPDczB7H07rBdQuse2fecxzV26FNfurFJ4/ivQ2xbkiRJ0nCcj3nekmGeNzHM87pnnjdg5nldMc+TJGlCTcSNPpl5A1DfH3uziFi9U/0BaS7d+6yIWCUiVmHmHt+LapnfMdTrssnvbxw/NSLu0ramhqKaUfPSRvHPOgU8tC7ZvDKw+yD61a3MvDgz3wI8p/HUkzqdMt+2qt9l9cH9LzKzq72VI2I14D7zbZuZSzHPZefG8UkLaHtoqqDp67T2/7fAkydlednMvJ7WpbTvFBHNJdM7ioh7ABv2vWOdNft26hDbliRJkjQE5nlLjnnemDPP65553uCZ583NPE+SpMk2ETf6VOofQFdguHcqk5m/Bs6sFa0PPA54fPX1lNOrJUQXlcw8tb4PcLcP4KDGpY5s1FnWz35Wyz++qFZ0K3MHA0cAl9aOVwU+GxHRvroGKSJWpCyfukHjqeZrqe6HjeMX9rVT8/c1ynLWU7bsUK+5n3Iv+8ovaxxf1a5SB/uysH2Yd4iIXmaKNEPQdks3LyrV74EjgUfUis8EHj2BMzV/3Dju5X30ormr9FVzGfDfDrl9SZIkScNhnrcA5nkaFvM8wDxv0TDP65p5niRJE2ySbvT5eeN4pxH0oTlAfR69z1bR7A6h9S70j2XmrHu9ZuaNwGsaxXsChxgODFdErA98j7Ivdt0Rmdl8D9d9DlheO35aROzZ5+71LDMTqC8D2wwApixvHG/UQzPNvZi37eakiFgHeGsP7XRycJft3Q94Yq3oZuCLfWh/0D4EPLN2fCGwd2Y295KfBJ+k9fX6soiYM0SPiHsBLxlYr9qr/w2/DfjFkNuXJEmSNBzmeUuDed4YM8+7nXne4mGeNwfzPEmSJt8k3ejz/cZxc+AxDEdRPgxPeQSwd+34ZsoAR9w+E6TbuhER7wUOqBVfALyxm/Mz82jgI43iVwFfiYjmTJRurDuPc7oWEUdERNYeRwyyvUGLiHUi4pWUpUYf2Xj6ROBls52fmcuB9zaKvxYRD+6xHytGxJMjYr02z+3ea9gQEY+l9bVwRrt61XLk59eKHhARy7ppo1qi9Zxa0X0iYu9O9at+rU6ZZbVFN23M4YkRMevPp3oPfZ7Wvylfycy/96H9gYmItwL/VSv6J/CIucLGcZWZ59Ea1qwC/DAimrNtbleFAj+gLLE9FNXSyw+qFZ2UmZcPq31JkiRJQ2WeN2bM8zozz2tlnmeeNwjmeeZ5kiSpWGnUHeiXzLw0Ik5kek/WPSJipcy8ZYh9uCwivsf0vr7Nge93F/Lhppo9sWaX1TftMLnllsy8aL596LPtIuJrlFlR387Ms5sVImIlyv7N76B1v90bgedk5rU9tPca4G7Ao2plTwUeGRGHAV8FfpeZt7U7uZpR8RjgxcBDemh3Uq0WEVu0KV8TWAe4I3Bvys/tIbR/7R4LPD0z/91Fe+8BHsp02LYMOC4iPgF8ODPPandSNch4APAE4BnA5pQlea9sVL038IGIOAP4CvBt4I+ZeWuba64K7Ae8r/HUkbP0/2dMB1urAz+IiA8Afwauo3Xf7ysar+0vA2+pHX81Il4KHF1/vVYz2vakzJSbGuxdzsxllbv1L0rw8ZGIuDtwUGa2zEiKiL2Aj1HeW1OuBF47zzaHogpX6rObbqEEVNd3eF13sph+p3bjFZTXyNQstI2BUyLiSOBbwF+r8i0pM7r2o3xWuIIS7A1j5t2uwBq1428NoU1JkiRJI2CeN4N53kzmef1lnmeeZ563uH6ndsM8T5IkzTAxN/pUjmJ68LguZRbQj4bch8OZDgbaPbcQ76N8SOvGLzuUX0B/ZgX0yzaUAd97IuIy4E+UD6AAd6IMbpqzba4HnpGZnf6PbWXmzRHxBMrSnvVlK9cEXl89lkfEmZSZAMspd8ivA9yV8kG53SpYf2dpfnDdmelBRK+uAt4OfKRTENOUmbdExNMps/0eWBWvCLwUeGlEXEx5/VxJ+TmtDWxKWRq3l9kL21V9ezvw74j4E/CPqs8rV9e8D2VwX/dz4FOzXPfDwHOY/r27M2WWTjsHUPain3IIZdnwjavjtSkzbt4XESdXfVuPEm7UlxH+AmXA2+3vjaZ3AS8H7kIZUL40Ik4ALqYM3HakBC11NwP7LfbZP0x/L6esROefx2wW2+/UWWXmlRHxSMr+3lOB0UrA86tHOzcDz2Lmnu3Zpm4/PLX29W2U17okSZKkyWWeN808r8E8r+/M81qZ5xXmeYuYeZ4kSWpn0m70+RJl8HyH6vhpDD8Y+AFwCTM/dF4M/HDIfRk3GwIPm6PO6cCzM/P382kgM2+mDG6+Qxlsbd+osgzYpcvLXQYcChySmdfNpz+zWK1x3NzXeVydRgnwPpWZV/V6cmZeFRG7A++mDFTrs+w2qR5z+Ted995uWp3WvYU7+Rblddkx5MjMUyPiRcBhzPz5ziozl1fLCv+A1j3t7ww8tsNpX6AEDLOFFXO5grJk+Q8p4cDKwG6z1L8OeFZmfm8BbWrAMvOPEfEg4NPMPZvxAkoQe2JENIODa/rdt4hYAXhKrejYMZthJUmSJKl35nnjzTxvmnleG+Z55nlaOPM8SZLU1G42w9jKzCtpXWrzGRHR7dK4/erDrbTeuT/lyHZLhi5xlwAfp3Wv405+B7wQuNd8Q4G6zPwBsANlUPVlygyKblxI2RP3scAmmXnwAEIBKEtdTrmFmfuRL1a3ATdQlpc9nTKg/DCwP7BVZu6Yme+bTygwJTNvzszXAFtTlpj9Rxen/RP4RtWPO2XmpW3qfJYyy+ELlJ/zXG6hDNQfnZlP6uZ1kJmfpcxIehtlBsZFzFzmt9O5v6fM8DmKMiOjbTXgV8DTMvPZVRC2IJl5RtXuhyjfx3ZupLyPtsvMby+0TQ1eZp6TmQ+lLF9+JHA2ZaB/HWUP+e9R3g/bZeaJ1WnLGpeZ9/t4Fo+mNVj/wADakCRJkrSImOeNHfO8zszzOjDPM8/TwpnnSZKkusgc1Ep9o1HtO3sm0zcxvTgzPznCLqkLEbExZdnQLSgfPlcCrqUsJXtSZl4y4PZXoCw7vC1lFslalNfQVZQlf/8BnLqQPdl76MvdKB/MpxyemS8YdLvjLCK2o7x+7kh5/dwCXE0Z4J8JnJc9/rKLiI0oy/5uQVlG9w6UZaaXA2cBf8jMq/vyH+hRRCwDHgxsRVmq+krKktMnD3K2RESsUrW7OWUp7msp3+Ofjep7oeGJiAspS11D2Xd+vnvFz9bGd5me1XZaZu44W/1hiYh7UJYSB+Dkk09m++2bE0jH1+mnn87973//etEOmfnnUfVHkiRJS4953ngyz2vpi3lej8zzzPM0eOZ503neL074LdtuNzl53plnnM5DdmlZvMw8T5KWmEnbuovMPCcivkDZOxfglRHxqV4HBRquauA/0MH/HO3fBpxRPUatvtzxzcA7RtWRcVHNUunrz66aJdRuptDIZeZyygyNYbd7E/DTYber0YuILZkOBQBOGUAb21JmAE05sN9tSJIkSVqczPPGk3leC/O8HpnnDa1d87wlyjxPkqTJNlFbd9W8Dbip+no74Ekj7IvUq3ow8JnMPH9UHZGkyksax78ZQBtvYvpzyYmZ+Y0BtCFJkiRp8TLP0zgzz5O02JjnSZI0wSbyRp9qIPXBWtHbq6VcpXGwe/XvTcA7R9gPSSIi7g28olaUwOf73MY2wDNr139tP68vSZIkafEzz9OY27361zxP0siZ50mSNPkmebB8MPC36usdgf1G2BepK9W+sXeqDj+VmReOsj+SJk9EvCwiXh8Ra3VRd0/gR8AqteLvZuZf+tyt9zC9neiRmfmrPl9fkiRJ0ngwz9PYMc+TNGjmeZIkqWmluauMp8y8LiL2BR5eFa08yv5I3cjMPwMx6n5ImmgbAG+nzI79DvAL4DTgiur5OwL3pSyTv0fj3CuBl/azMxGxNvA74PdV0aH9vL4kSZKk8WGep3FknidpCMzzJElSi4m90QcgM48Hjh91PyRJWoRWB/apHt24EnhiZl7cz05k5tXAQf28piRJkqTxZZ4nSVJH5nmSJAmY7K27JEnSTFdS9s3uxfeBnTPzlwPojyRJkiRJkqTOzPMkSVKLiV7RR5IktcrMD0fE14FHAg8Etgc2A5YBqwHXUsKDcynLAH87M/84mt5KkiRJkiRJS5t5niRJavJGH0mSlphqud7Dq4ckSZIkSZKkRcw8T5Ik1bl1lyRJkiRJkiRJkiRJkjQGvNFHkiRJkiRJkiRJkiRJGgNu3SVJktSDi6+9mTtcddOou9E3F19786i7IEmSJEmSJA3MhVfdzMpX3jjqbvTNhVeZ50nSUueKPpIkSZIkSZIkSZIkSdIY8EYfSZIkSZIkSZIkSZIkaQx4o48kSZIkSZIkSZIkSZI0BrzRR5IkSZIkSZIkSZIkSRoD3ugjSZIkSZIkSZIkSZIkjQFv9JEkSZIkSZIkSZIkSZLGgDf6SJIkSZIkSZIkSZIkSWPAG30kSZIkSZIkSZIkSZKkMeCNPpIkSZIkSZIkSZIkSdIY8EYfSZIkSZIkSZIkSZIkaQx4o48kSZIkSZIkSZIkSZI0BrzRR5IkSZIkSZIkSZIkSRoD3ugjSZIkSZIkSZIkSZIkjYEleaNPRHw2IrJ6fGnU/dHcImLliHhwROwfEa+LiNdExDMjYqeIiD63tWFEPCoiXli19ZaIeFVEPC8i9oyILfvdprQYRMQWtd+NGRFHDLCtAxtt7T5H/Xrd4/p57UGIiN0bfThw2H0YJxHxw9r36oOj7o8kSZKkxcc8b/yY50mDZ57XP+Z5vTHPkyRptFYadQeGLSIeBOxXHd4EvHGO+scBD60Of56Zuzee/xGwV63oQ5n5yj719RDg1bWiYzLz0bPU3wC4P/CA6nF/4M6Naltm5vn96F+HPqwOnAZs1XjqyMzcfx7X2xx4C/AMYK0O1S6OiM8D78zMa3pto2pnHeD51WP7Lk5ZHhGnAD8DfpCZp8xx/eOY5XU0Kr30KyK2AP46xyUTuBG4HrgcuBQ4G/gjcDxwambmgjotaSxExPnA5tXhXH8DXkf5W7oC8J8R8dnM/MNgeyhJkiRpXJjnmed1aMc8zzxPUh+Z50mSND6W1Io+EbECcCgwNXvjY5k510BnLoc3jp8VEass8JpExMrAs+doi4jYOCK+Wn0Auwz4PnAQ8FhmhgLD8E5mhgLzEhEvoAwqX0DnUABgE+ANwGkR8ZB5tPM44AzgELoLBQCWAXsC7wBOjohlvbY7oQJYDVgX2JoSOrwQ+AjwO+CiiHh/RPTlNTJOIuL82gyH80fdH2kxycw/Al+oDlek/M6QJEmSJPO84TDPW9rM8zowz5M6M8+TJGm0ltSNPsC+wL2qr28C3tuHa34TuLJ2vD7wuD5c97HAhrXjy4HvtKm3IfBUpu+yHpmI2AV4eZ+u9VbgU0AzZPkD8PXq0bw7fHPgmIjYqYd29ge+BWzUeOoGykD2W5QPq9+mzGC5qttrq62NgVcB50TExwxUJNW8C7it+nq3iHjMKDsjSZIkadEwzxsg8zx1wTxPUifmeZIkjciS2bqrmlFzcK3oqMy8eKHXzcwbI+ILwH/Vip9HGbguxAGN489l5s09nH8bZfbMtgvsR1eqWU+HM33z2DXMPmtntms9njKLqe7HwMsy8+xG3W2Aw4CHVUWrA9+LiB0z8+9ztHNf4NO03vB2HvB24BuZ+e825wRlZstjgCcBD+72/zWhtmxTdgfKDKllwHbATsBDaA1fVgD+A3hERDwhM08bbDclLXaZeWZEfBN4SlX0roj4vsuDS5IkSUuXed5gmectWeZ5kvrCPE+SpNFZSiv67EPrIObQPl67uQTvIyKiOaOkaxFxZ+BRjeLPzHHaX4AvA68FdgfWyczt5tuHeXgb08vkXgB8Yj4XqQKcjzC9HDOUWVaPaoYCAJl5FvAIWmdHbQAc2EVzH6AsKTnleOA+mfn5dqFA1V5m5lmZ+f7M3I3yf/44cGsX7U2czDy/zeOMzPxNZh5TfZ/2ATaj7Mve3Pt8S+CnETHM16oWgcw8MDOj9jhuHK7dQx+Oa/ThwGH3YUzV/zbvyMy/hZIkSZKWFvO8wTLPW4LM8zRf5nnqwDxPkqQRWEo3+rym9vWJmXlqvy6cmX+gdcCzIrDfAi75XFpXWzoxM//coe6ZwHqZebfM3CczD8nMn2fmtQtovycRcS/KntpTXgJcN8/LPYsyiJxyOfD8zLyl0wnVcwcA/6wVvyAitu50TkRsSpmVMuUW4FmZeXUvna0GwS/JzGt6OW+pycxbMvMrwC6UJbbrd/SvD3wjIlYfSeckLRqZ+TPgrFrRa0fVF0mSJEmLgnnegJjnmefNxTxPUjfM8yRJGo0lcaNPROzK9F7eAJ8fQDPNWUDNpXp7sf8c175dZt6Qmf9aQFsLEhErUWYnTQUZR2fmMQu4ZHM/9MO7+f9l5pW0zpJaEXjOLKfs1jj+TWZe0F0XNV9VQPB64L8bT20L/L8RdEnS4vPF2td7VEu6S5IkSVpizPMGxzxPvTDPk9QF8zxJkoZspbmrTIT9a1/fxsL3227ni8AhlP2MAbaOiAdl5vG9XKQKMerLnl4HfKk/XRyI1wH3rb6+EnjlAq/3kMbxD3s49wdVf6Y8FXhrh7obN44v6qEdLdxBlP3QH1Yre2VEvK/XWVjVPuv3AbahLPO8BnAF5Wf6q4XMzqquvR1wT+BOlH3qb6W8Ly+l7AH/p8y8ab5tLKBva1GWmt6aMotqDeAayvvwT8AfM7PvS1BHxNT3ehPK79NLgF9n5oX9bkvTImJ94IHApsA6lBmPZ1JCzZsXeO11gIdW116b8tr+G+X9s6Brz9NXKL8jpuwPvHEE/ZAkSZI0WvvXvjbP6y/zPM2Hed4CmectLeZ55nmSJA3SxN/oExErAk+rFZ2SmZf2u53MvCoivg48u1Z8AGWf6F48r3H81cW6jGx1V/bba0WvyczLFnC9VSkDnLo/9XCJ0xrH20bEVpl5Xpu6zdf+ej20owXKzNsi4iBag4G1gGfS5X7wEXEX4E2UAKj5uplyc0T8GHhbZp7cbf8iYm3g9ZQluzedo/pNEfFbyt7zH8jM25cxjogjaL/s9+YRkW3KpxyZmfu36dcOlL3RH0EJ5FZs1qm5JiI+D7yvw3uga9Xv0ZcA/0kJBZoyIn4NvD4zf93lNQ+k9ffHHv3ae7vba8/y8+nVlpl5fuPauwM/qxUdNNu+3hFxPrB5dXhBZm5RlW8HvAt4DLBym1OvjohDgPdm5vW9dDoitqIsvf24Dte+IiKOorx/rouI/YHP1p4/IDOP6KXNbmTmmRFxDnD3qmhfDAYkSZKkJcU8b3DM8zRf5nnmeeZ5M/pyPuZ5gHmeJEmjsBS27nogsG7t+GedKvZBc0nep0fEGt2eXO1p/PQ5rrkoRMQKlL6tWhX9tA8fENsNzpf3cH67uvfsULcZYDw4Iu7YQ1taoMz8BXBqo/jx3ZwbEW8AzgH+g86hAJTBzqOA30bEe6oZPXNde0fgDODNzB0KAKxCmc10CLMP1BckIu5LCb/eAjygi7bWogzm/xQRz56j7mztrkmZXfcR2ocCAAE8CPhVRDSXcdY8RcQBwMnAE2k/cIcyY+cg4EcRsayHa+8D/Bl48izXXh94NXBSRGzd7bX7pP63erOI6PS7XJIkSdJkMs8bAPM8LZR5Xm/M85Ye87zbmedJkjRgE7+iD/DIxvEvB9jWz4G/AHetjteizE44ssvzn0r5kDfl7Mz8Vf+611f/SRkIAFwPvLgP12y3XOqqwC1dnr9qm7LtgW+3Kf9N43gN4IsRsc8o90hfgn4E3Lt2/MCIiPosmroqkPoMM2dt3EYZNJ9PWYZ3A2AnypKoUAaurwM2pHXp7+b11wOOpSzrW/d3ymy0f1KW+l0LuAtlL/LVOv/3+qp5Y2YCf6UEJFcDN1NC0HsAm9Xq3QH4XETckJlfm0e7RwN71Y7/CJxbfX03YMfacwG8JSJWzMw3zaMtVSLiaZTwdSrMuoDyGryK8vrehfI6nPIgyuy5Z3Rx7acDn2dmuHQecDrlPbQx5T20KmW56+8Ah87vfzMvvwBeVDt+JDNneUqSJEmaXOZ5g2Gep34wz+ueed4SYp5nnidJ0jAthRt9dmkcn9rLyZm5ew91MyI+A7yzVvw8ug8Gmsv8fqbbtocpIragLD055aDMPLdD9V78izLAqw+ANmJ6EDKXjdqUtZ2xUC0leTJw/1rx3sC51c/wm8BvM7PbUGJWvbyOhmkR9KsZ0CyjDGov6FD/rbSGAjcC7wYOzczL6xUjYiXgOZSZOVOzAPeLiN9kZqflhF9HayhwKvCfmdl2ye6qjV0pM5cOaFPltcCB1de/ouyDDXAxZdZQJ9d2KL8e+BIl7PpJZratVy0J/DZalzn/TET8osfluB/P9Pfux5TvxVmNtrYBPkprePDGiPhZZv6oh7ZGof7z6dbLqvOmXEvZS72f1qf83QjKAPm1mXlSvUJE3IHyM/5/teKnR8RHM7NjAF4tkf0pWkOBPwAvbS7TXO0b/4bqsU3VXtemliuep1Mbx7su4FqSJEmSxo95Xp+Z5/VuEeRmbS2CfpnntWeeNxzmeYV5niRJS9xSuNHnfrWvl2fmRQNu7wjgYKY/dO0WEXfNzL/MdlK1t+pDakW3AEcNpIcL9ynKjBkoHygP6cdFq32ez6bMqpiyC90HA+0+OK7TpmzKq4Gf0vo+WI/yof+1wPURcQpwUvX4dWZ2GrBqfs5sU9Y2GIiInWkdmPwL2DMzf9/uwlWo89mIOB74NTC1lPP/RsQXM7PdYO4Jta+vrK5/ZafOV238EvhlRLy1GSRl5hXAFVX/68/d0twDugtnA5t0M0MtM/9EGSQeyPTe1msBL6W3gfBUKPAV4JmZeVubts6KiEdSZgrVg4hPRsTd+xWuDUL959ONannc19SKbgKemJn/7HPXpn6/fhHYr933sNq/+41VQPCK2lMvYvaZru+ldabpb4C924VM1XvkLRFxGuXnO9uy2v12FuX7u0p1vFO/LhwRG1JmUfXirnNXkSRJktRH5nn9Z56nfjHP6555Xp+Z5wHmed0yz5MkTbTm0pETJSLuTOvAcOCDusy8hLL/7e3doP3MgKYDmF7SEeD7mXlpP/vWDxHxfKbv9L8NeGGfP/j/vHH8nB7OfW6bsrXalAFQ3SW/P2UWSTt3oMzSeBXlA/r5EXFBRBxaDVK1cO0GuZ0+sL+V1t9Zz+oUCtRl5tmUva2nrAO8sEP1zWtf/2y2UKBNOzd0W3c+MvPqeSxDfTBlad4pz5pH0xcBz28XCtT6ditlBuPFteIt6HKP9nEQEXtTwtqp39O3Ac/OzJ8MqMlzgRd08fv1YFqXSX9Yp4oRsTHwlFrRv4F9O80km5KZXwY+PUc/+qr6f9dfT5tExOp9uvxLKcsm9/Jot2S8JEmSpAEwz+s/8zzzvD4zz+v++uZ5I2SeZ57Xp7YlSVqUJvpGH8oH07pBz/6Z0lyid79qL+K2queaexQf3vdeLVD1ofJ9taIPN5ef7IPPNY73johHz3VSRDwO2LPNUx2DAYDM/AKwM9Dth/vNKB8qT4iIn0bEvbo8T+21G+jeoVkQEXcFHlMr+nlmHtNDO1+jNRjsZsC6YQ/XX5Sqwfw3a0V3i4heZz7871wDx6qta4H/bRTv32Nbi1JE7AR8A1i5VvyyzPzqAJs9pJrlM6sqvKov0btxNcOlnafSOuPxCz3MRHsHJQwZpubf7C2G3L4kSZKk0diicWyetwDmeYB5Xr+Z5w2QeV5/mOcB5nmSJE20Sb/Rp/nhqNe75+fru0B939xNgYfPUn8v4C61438A3x9AvxbqMMqey1AGWW/pdwPV3snNWUBfjIiHtKsPEBG7A5/v8PScH2Qz8w+ZuRdlf+8PAX/tqrOwByUgeHaX9TVTu99B2aZsr8bxl3tpJDOT1tfVzhGxSpuq9aWHHxQRT++lnVGJiFUjYv2I2Dwitqg/KPuA123Xw6WTsod4t46m9ef3oIiITpXHQURsS/l9vEat+G2Z+fEBN/1/PdQ9o3HcKRh4YOP4K902kJl/A07soU/90PybPfZhnSRJkqSumOf1l3leK/O8hTPP6wPzvMExzyvM8yRJmmwrzV1lrDWXBZzzbup+yMybI+JztO79egDwww6nPK9xfORi2we32su2vt/xSzLzugE19zzgZKb3E14H+FlEHA18FTiHstzm3YCnA89kevnNiyhBzJTl3TaamacApwCvjIhNKXuE37d67Ez7/cFXA46IiMsy89hu29LtlrUpa/c+fXDj+LJq0NuLf9e+Xg3YGDi/UeeLlJ83lNDiyxGxPyV4+kEvS/8OUkTsADwD2A24B73ttbzu3FVu95dq3+uuZOYVEXEe0/sfrwdsBfylhzYXjYi4C3As0/vBA3w0M/97wE1fm5kX9lC/OYBu97sKoDlj8eQe2gA4ifJ7cVj+3Theo22t3h1G+VvSi7vicr+SJEnSsJjn9Yl5nnnegCxrU2aeNwfzvOEwz5vBPE+SpAk16Tf6NP9/wxxsH05rMPDEiFi3uSdvRKwLPLFxbnOp4JGKiPWBD9eKju5xmdWeZOZ5EfFEyhKl61XFK1D2I55tT+ITKXvuHlorWz7PPlxE+eD4Vbh9OeadKHuMP48ysJyyIvCpiLh7Zt7UvJZm1W6Qenmbsrs0jr/Wh7bXY2Yw8FHKcqi71MoeVT0yIv4M/AY4nrLccPP8gYqIzYEPMvN3Ri86DRrbOXse1z+H6WAAyqyNsQsGIuKOlDC3/tr7EvDyITTf62zVmxvHK7et1RogXZ2Zy3ts52891l+o5t/sTv+vnmTmZbTO0p3TmE9kkyRJksaNeV4fmOeZ5w2QeV4PzPOGxzyvLfM8SZIm1KRv3dWcSTBjr+BBycwzKAOIKasC+7apum/13JRfZeZZg+zbPHwYmNoH+ErglYNuMDN/QZl18+NuqlPu6N6TmQPNv/epP7dl5gmZ+TLKjIvTGlU2A57Wj7aWmO3blF3QpuyObcoWasZ+75l5I2VZ4U8CtzaeDmAH4IXAEcBfI+IPEfGqiGjONuy7iNiO8jvliQu8VC+/96+ex/Wvahyv17bWIhYRa1CW960vi/xD4LnVstGDNqi9s5fVvr5mHufP5/WwEM2/2YOadSpJkiRpcTHP6w/zPPO8QTHP65J53vCY53VknidJ0oSa9Bt9mh9i+rVMYLcObxw3l/RtV9Y8Z6QiYhvKUrpTPgis3tw3uM0+wssal1qzUWezudrOzHMz8+GUfWjfR1mW8h/ATcAVwO+B9wA7ZubLqqWHm/sV97qU5Zwy8zzg0cz8kLp3v9taAnZpHF/ZYYnTdvtvL1TbW/oz87rMfDFwd+DtlOVNO80e3BF4P3BOROwxgD4CEBErUWafbFQrvgH4HLA/ZT/6jYA1gZUyM6YelGXG56sfg+BhDKT7JiJWBr5OmfE35UTgKZnZnGkzbm6sfT2f99Qg3oezaf7NHnYwIUmSJGk0zPMWyDyvbb/M8/rHPK8L5nnDY543K/M8SZIm1KRv3dUcYGzUttbgfJkykF6zOr5vROyYmX8EiIgdmd4/GMod2b3uMzpozTuwD64evXpK9ZhyFe33c54hM39D62yq2TT3mz2xy/N6kpkXRcSXaQ12th1EWxNur8bx8R3qXQFsXTveODMvHUyXisz8K9XrvZoR8gDgQcBDgIfSOnNvY+D7EbF7Zg7iNfdkSggx5VzgEVVINZe1F9BuL8sCdzqn12VrRybKeq5HAY+oFZ8BPKYKHsfdv5gebK8TEStkZi+zjYY9m2vjxnEv+5xLkiRJGl/meQtnnteGeV7fmOd1xzxvCMzz5mSeJ0nShJr0FX3Op/Xu802H2XhmXgt8pVFcH0g+v/Hclyfkw+dIRMSWwFa1oosy89wBNnlq47jd/tTqICJ2B+7VKP5Oh+r/aBxv3bbWgFSzgo7LzHdm5iMoSw+/CKiHE6sBhwyoC09oHL+oy1AAZg6uejGf7/PdG8c97Z08Yh8G9qkdX0gJYP45ov70W30Z7VXo/ed7zz72pRub1L6+gdb3myRJkqTJdT7meUuGed54Mc/riXnecJjnzc48T5KkCTXRN/pk5g1AfX/szYax925Dc+neZ0XEKhGxCjP3+F5Uy/yOoWEvm9zc87m5l7E6iIgVKMvo1l1NWc62nV83jke6rHIVFHyKsgx1Pcx7YERs2Om0BTRZH2xfBxzXw7kPXEC7d42I9butXNWth3NXAt0GGCMVEW8D/rNW9E9g7w5LT4+rExrHXS9PHRErArv1tzuztrc+JYCb8sch7acuSZIkacTM85Yc87wxYZ7XM/O8ATPPm515niRJk22ib/SpnFT7egVgh2E2npm/Bs6sFa0PPA54fPX1lNMzs/mhbeQy89T6/sDdPoCDGpc6slFnWT/7GRHrUmZkTLmVwQcD2zeOLx5we5PkQGD3Rtn7q1lz7fywcfyciFit353qVWaeD/y0VhTAFh2q1/dTXrVDnU6W1b6+utsBUkTcjbI88XwFrTNi5vJMWvdKP34cBnMR8R+0/s66Dnh0Zp7Z4ZRx9ePG8Quq5Y278Xjgzn3uz2yaswN/O8S2JUmSJI2eed4CmOfNyjxv/g7EPK8Xy2pfm+f1mXleV8zzJEmaYEvhRp+fN453GkEfmgPU5zH82SqT7hCgPvPiY7PduR8RW0bEsvk2Vp379EbxT9tUVU1ErBQR/wu8pfHU6cB7Op2XmafR+l6+C/Cm/vdwXm5pHN/YthYsr329fkSs3EMb9X2xN6yCsG68h4X/nn9DRKw5V6WqzusbxUcusO2Bi4inAYfWim4GnpyZkzgQPRb4a+34vsAL5zqp+tkOahnrTpp/q48bcvuSJEmSRss8b2kwzxsD5nm3M89bJMzzzPMkSdLSuNHn+43jrpc27KOjKB82pzyC1qVKbwY+N9QeLWLVkpLd1o2IeC9wQK34AuCNc5z6UOD8iDh4lqVZO7W5OnA0sEGt+EbgG71cZ4429o+IrD3O79e1R6EKBJ4K/IYyeKzPOrgceEpmXj/HZd5M63K5b42I/+xUeZa+7BwR92lTvllE7BcRXc/OiYiNgL1qRTfReWnbM2pfr0Rvv4v+UPt6ReB1XfTtIOBJPbTRyabA4dXyzJ3aWoESbm5aKz4f+HYf2h+YiNgT+DzTfwsTeG5mHju6Xg1OZt4GvLNR/NGI6DjLq1py9/vAloPsWxv198fNwI+G3L4kSZKk0TLPGzPmeeZ5HZjnFeZ5fWKeB5jnSZIklsCNPpl5KXBirWiPiFhpyH24DPherWjF6jHlu5l5+XyvHxHrR8QW7R5tqm/aoe6mbeqOynYRcWZEvC4itm5XoRpo7kUZaL629tSNwHNmWTK2bh3grcDFEfG9iNh3tu9DRKwREc+mDNIe2Xj63Zl5URdtTpQOr6Vtq8H3IyLilRFxNPA34KvA/RuXOA/Yo5slVTPzeMoSwXUfiYhjImL3TgPXKjzatno9/Zayr3FzGVGA9YAjgL9FxEcjYs+IuMMs13w4ZVbCWrWnvpGZ13T4L/yscfzZiHhpRNwvIrZqfA+b+2h/uXH8xoh4R7uZORGxTUR8A3hbVTTv3y1Mzzx6OnBMu/djVfYDZs6Ie3FmNmdHLRoRcUfgW8AqteJDgBM6/T6d5THUvykLkZmH07p09srA0RHxw4h4dkTcp3oN7R4R7wTOouzlncBXhtHH6n1XX6L6p5l59TDaliRJkrQ4mOfNYJ43zTxvgczzzPPM88zz+s08T5Kk4RubDzMLdBSwc/X1upQ7i4d9N/HhdL4bf6HL/L4P2K/Lur/sUH4BnfciHoVtKMuUviciLgP+BFxRPXcnYEfKz7LueuAZmdnp/9jJSsBjqgcRcTHwF+CflL191wI2p+zhvUqb878CvKPHNifFX+eu0tatwCeBN2bmVd2elJkHR8QGQH3mzyOrx1UR8XvKQPhmYG3K8s/bA3MuVVuzIfCy6nFrRJxJCTaWV89vQAkWNmicdxnw6lmu+1XK7Iup8GljWpeYrTsS2H/qIDN/EhHHAI+q1Xkz8Ioq7LiU8n/cGtiuVucM4OPAh2bp12y+C6wPPJoya/GsiDgVOJcyi+tutA9Z/mcMZtGsxczXxWtpDRq7tSVlxtO42IcS5uxcK9ub1pmpTf9Neb/XA6BB7df+KGD12vGiXzJakiRJ0kCY500zz5vJPG/+zPOmmedNM89b3MzzJElSi6Vyo8+XKIPnqbv5n8bwg4EfAJdQBgN1F9N6N7Zm2hB42Bx1TgeenZm/7/KalwJXUWYBNW1SPeZyPfA/wLsy89Yu2+3Wao3jf7WtNX4uocxm+WhmdloSd1aZ+V8RcRLwEcrgf8o6wO5dXOI2ys++GysC96geszkdeEI147CtzLw+Ip5EmXXSzeuraV/K7636LKo16fzeOBV4LPDwebQ1JSmDyG8zvfTqvatHp/rvyszmnu1aRDJzeTWD7f3A82ldervpeuC/MvPwiHhJ47lOs90Wqh4+/Av45oDakSRJkrS4meeNN/M887zbmeeZ52lhzPMkSVLTxG/dBZCZV9J6B/Ez2i2ROeA+3EpZRrTpyAEMKsfdJZRZC+d3Ufd3wAuBe/UQCpCZP6TM4Nib8uH4RFr3XZ/N2cDBwLaZ+d8D+vk9sHH8gQG0MQhJWW55OWWWyC+ATwMvB+4LbJqZr55vKHB7I5lHAZsBb6IsRTqXG4CfUvbC3iwz2w00/kyZefCR6uvburju7ygzhe6Vmed20e+TKTOS/oMSEJwLXE2ZETXXucuBB1Nee1fOUvUs4A3ALpl58VzX7aLdayjvk1dX/W1bDfg18GBDgfGQmddk5guB+1CC8z9QZj3eSJkR+gvgNcCW1fLAAMsal+l69l63qiWYn1gr+nhm3tDvdiRJkiQtfuZ5Y8c8zzxv9kbM88zztCDmeZIkqS4yB7VS3+ISEXcHzmT65qYXZ+YnR9gldSEiNqYs67sF5UPpSsC1lCUnT8rMS/rY1qqUpUvvDmxEWQp05aq9qykflv+Qmf/sV5uz9OVCppeEPQu4hwFSZxGxEbATZbbYepT3+TXA3ynfv7My86Yer7k2ZebPlpTlpdeghEdXU0KrU2eb8TNI1Wt156p/61Jeo38HzsjM0wbc9v0oS3FvTAlPLgF+nZl/G2S7Gr2I+Bzw7FrRDpn55z638RpKUAFwE7DFqN5ndRFxD8qS8wB8+7jfcLdttpvljPFy7lln8ITdd60X9f1nK0mSJM2Hed54Ms8DzPPmZJ5nnqfBM8+bzvO+8MPj2WrrbUfYo/467+wzedYjHlQvMs+TpCVmqWzdRWaeExFfAJ5TFb0yIj6VS+VOpzFVDfz7Nvifo60bKTM/RvphKCK2ZjoUADjYUGB21cDh232+5tXAb6rHolK9Vn9RPYbd9inAKcNuV6MVEQHsViu6jhK297ONlSmzBad8YjGEApIkSZJGxzxvPJnnAeZ5czLPG2rb5nlLkHmeJEmTbUls3VXzNsodxQDbAU8aYV+kTup7NJ9O2ZNekkbpUcDmteOTBhBYPoeyhDeUWW3v6PP1JUmSJI0n8zyNA/M8SYuNeZ4kSRNsSd3ok5nnAx+sFb09IpbU90BjoR4MHJSZ3ewtLUkDERFrAR9uFB/V5zZWAd5UK/qfzLysn21IkiRJGk/meRoT5nmSFg3zPEmSJt9SHBQfDEztPbsjsN8I+yK1qJbT3L06/BPw1dH1RtIkiohdI+KwiNisi7pbAscBd60V/4P+z0x8Wa2Ns5je11uSJEmSwDxPi5h5nqRBM8+TJElNK426A8OWmddFxL7Aw6uilUfZH6mu2mN+w1H3Q9JEWxV4CfDiiDgO+CHwO+DvwA3AupTl8B8BPI2ZfycPyMzr+9ynW4GDqq//LzNvmq2yJEmSpKXFPE+LmXmepCEwz5MkSS2W3I0+AJl5PHD8qPshSdIIrUBZWvxhc1Ws3Aq8OjOP6XdHMrO5lLAkSZIktTDPkyTJPE+SJBVLcesuSZKWsmuBG3s85zTgUQ7gJUmSJEmSpKEzz5MkSS2W5Io+kiQtVZl5ckRsQFnyfjfgXsAWwAbAHSihwb+AiyizZY8Fjq2WIpckSZIkSZI0ROZ5kiSpyRt9JElaYjLzGuAb1UOSJEmSJEnSImaeJ0mS6ty6S5IkSZIkSZIkSZIkSRoD3ugjSZIkSZIkSZIkSZIkjQG37pIkSerBRmuszOZrrzLqbvTNdWusPOouSJIkSZIkSQOz/erXs/2a/x51N/pmtdWvH3UXJEkj5oo+kiRJkiRJkiRJkiRJ0hjwRh9JkiRJkiRJkiRJkiRpDHijjyRJkiRJkiRJkiRJkjQGvNFHkiRJkiRJkiRJkiRJGgPe6CNJkiRJkiRJkiRJkiSNAW/0kSRJkiRJkiRJkiRJksaAN/pIkiRJkiRJkiRJkiRJY8AbfSRJkiRJkiRJkiRJkqQx4I0+kiRJkiRJkiRJkiRJ0hjwRh9JkiRJkiRJkiRJkiRpDHijjyRJkiRJkiRJkiRJkjQGvNFHkiRJkiRJkiRJkiRJGgMrjboD/RQRnwX2rw6/nJn7DLHtALYBtgU2AdYCVgSuBq4CLgb+kJlXDKtP4y4itgXuBWwK3AG4AbgMOJfyvbxuhN2TJk5EHAc8dOo4M2NA7WwB/LVWdGRm7j9L/SOA/WpFW2bm+f249qBExPnA5tXhBZm5xbD7MC4iYl/gC9XhxcC2mXntCLskSZIkaYjM8yaLeZ40XOZ5/WOe1z3zPEmSRm9ibvSJiAcx/cHxJuCNc9Q/jukPwD/PzN3n0eYKwKOAZwOPBJZ1cc4lwI+ArwPHZuaN82h3K+ABwP2rf+9LCSKmLOhDaETkfM+tdPzQ3kXby4BXAM8DNpul6q0RcSrwtcx89xzX3B/47BxN3wrcCFxLCR8uAs4Cfgf8MjP/Osu5s2rT/ry/P/3Ua7+ag8YObqJ8H/9F+T6eB5wOnAgcn5nXzL/HksZFRBwIvH3qeI6Q6WjglZS/Z5tU571ugN2TJEmStEiY55nnzXLN/THPm8E8T9KgmOdJkjReJuJGn2qAfigw9cHjYwsZyHXZ5qOAQ4Dtejx1Y0qAsR/wz4j4APCRzLx6jvZ2p4Qd9wfW67W/4yAingZ8DLhjF9VXBO5HmR00azDQpRWB1avHhsAOlLBnqm+nAUcBn8rMq/rQ3qRapXqsRQl27l977saIOBb4OHBMZi40gBobzUESsEdmHjea3kiLS2ZmRPw/4CdV0Ssj4tOZedYo+yVJkiRpsMzzJoN53kQwz2vDPE/qzDxPkqTRW2HUHeiTfSlLwkKZgfDeQTUUEStHxMeB79M+FLga+C1wDPBF4P+Ak4B/tKl7R+AdwE+7aPrewN5MbijwduArzAwF/gb8mHKH+DeBE4BRLPF7T8rr6m8R8aoqjFJvVgUeR3lPnBwRO4+4P5IWicz8KfDr6nAlyt9GSZIkSZPNPG/MmectCeZ5ktoyz5MkabTGfkWfiFgZOLhWdFRmXjzAtr5HGaDX/Rs4DPgacHJm3trh/HsCD6fM/tmx9tRqC+jWjZRlae+6gGvM5kSg173RL+qlckS8BjiwUXw08D+ZeVqb+isAuwJPAR7RY9+g8/9pLcpyzetRgpidgd2ANWt11gbeDzw6Ip6Wmcvn0f6keB3lNV+3IuV7uIyyZOdOlJ/VfRv17gv8KiJel5kfHGgvJY2L/wG+W339lIi4X2aeMsoOSZIkSRoM8zzzvB77BuZ5/WKeJ6mfzPMkSRqRsb/RhzLA27J2fOgA2/ogM0OBbwAvyczL5jq5GuSeBrw/Ih4DvI0ycOrWzcCfgZMps4pOrq73IOBnPVynFzcMcv/piLgXrUv13gzsm5nNAeftMvM24Hjg+IiYz2u4m//Tt6v+rQM8H3gtsFHt+b2AYyNij8wcxYykxeCKLr6PR8HtodgrgAOYXklsJeADEbFyZg5s1p4Wn+p1M9sez4vy2j32Y4tR92EMfR/4K+VvegBvAJ4+0h5JkiRJGhTzPPO8Xpnn9Yd5nubFPE8dmOdJkjQik7Bc6WtqX5+YmacOopGI2Bd4aaP4g8BTuwkFmjLz/ygzI95MWZ54LkcCa2fmfTLzhZn5ycz8XWbe3Gvbi0U1qP8MrTecvXi2UKApM2/pe8dar39VZr6fspT0DxtPP4CyB7nmkJmnZeYLKDO2mu+Xd0fEXiPolqRFpAp9P1UrenJEbNmpviRJkqSxZp43pszzlg7zPElzMc+TJGl0xvpGn4jYlem9vAE+P6B2VgUOaRT/FHh1ZuZ8r5uZt2Xmu4AndlH3X5l5w3zbWqSeRusSsD/JzM+OqjOzyczLgccwc6bVcyLiYSPo0ljKzB8De1KWx56yAvCxiFhlNL2StIh8ofb1isCLRtURSZIkSYNhnjf2zPOWGPM8SXMwz5MkaQTGfeuu/Wtf3wZ8fUDtHADcuXZ8I7D/QkKBusz8Wz+uM4Ze3Dh+10h60aXMvDUi9gH+BGxQe+rtlKBIXcjMP0XEy4B6CHQ34FmNsq5ExEaU/dc3BO4IXEuZZXRSZp63kL5GxJ0o+7tvRdnPfSXgeuCfwAXAn6vQaKiqfe23qR6bUvajvwX4F/A3ymzIqwbQ7p0py5NvAqwD/AM4EzihX78PNVNErEhZ0n0ryt+ifwMXA79Y6Ouvei3tQnkt3Qm4urr2bzPz0oVcez4y828RcSLlPQ0lfH1zNTtIkiRJ0mTYv/a1ed74Mc9bgszzFs48b2kxzzPPkyRp0Mb2Rp/qg9LTakWnDPBDzKsax1/PzAsH1NaSEBF3Ax5aKzqfwe1L3jeZeVlEfBQ4qFb8kIjYJjPPGlW/xtBRlGWu71YrexFdBgMRsTJlr/WXAvecpd45wPuAz/SyLHREPIXyvn8gc+wPHRF/Af4P+FA9iIiI3en8mv5ZROfLZuaMJyNiXeBJwBOAhwDLZunWbRHxK+C9mfm92frfjYjYGXgr8EjKrIymSyLi/ZTvwZzf54jYgrJ385QjM3P/hfazl2vP8fPpxUGZeWCb658PbF4dXjDbHt8RcSAlYJyyR2YeFxGrUd4nL6A1nJ6SEfFd4A2ZeWYvna5m3L0WeDklEGi6NSKOBd6cmb+vzqmHPz/PzN17abMH32E6GNiE8rdi0f99kCRJkjQ387zxZp635JnnmeeZ503XPRDzvDrzPEmShmyct+56ILBu7XggHxoiYnNg60bxpwfR1hKzR+P4J2M0g+AwoLmX+uNH0ZFxVd3N/9FG8c7VjJtZRcT9KLNOPsYsoUDl7sAngJMiYpMurr1qRHwN+BplxsWsoUDlrpTB1aCXfP45cDjltbZsjrorUMKD70bE0RGxxnwbjYiXAr+mLHXdLhQA2JgSwJwQERt0qKMeRMTdgROBt9A+FIDy+nw88Ntelhyv3gu/A95J+1AAys/6UcBvIuIF3V67T5p/zx875PYlSZIkDY553ngzz1vCzPPmxTxvCTHPa2GeJ0nSgI3tij6UO9Hrfjmgdh7aOL6Z8iF5qdgsIj5LWd5zY2ANynKiVwC/B34BfC0zr+zxujs1jn8DEGVaxJ6UZV93ptz9vVLV3jnAj4EvZeb58/nP9ENmXhERpwIPqBU/CHjvaHo0tn7UOA5gV+BbnU6IiMcCXwZWbzx1KfAH4ErKa3R7Sigw5d7AiRGxS2ZeNEufPgo8pVF2Q3XtiyjL/K5BWVJ4O1qXfB605o2ZVwKnU94b11b92gLYAVi5Vm8fYM2IeHyv4VtEPI3yPZkKSC6jDCiXUwaUuwB3qJ1yP8rspt0y81+9tKUWGwCfAbasjq8DfktZWnlV4F6UZX+nrAV8LSJ2yMxLZrtwRGxICZnu2njq2lobyyjvmY2q9j4ZEcOc9XoS5b029dp6JPCaIbYvSZIkaXDM84bDPK/BPK9vzPN6Y563dJjnmedJkjRU43yjzy6N41N7ObmHJQof2Dj+Y2be2EtbY25Lpj+cTtmwemxPGcC/PyI+Bbw1M6/t8rr3bxyfUS3ReTjtZ1JsVj32BA6u2ntdZv67y/b67Te0BgP36lQxM48Ajhhwf3q2CPp1BmWAuaxWdi86BAMRsT3wJVpDgR8Ab8/M37apfx/gQ8BuVdEmwNERsXtm3tqm/raUJVWn/Bv4f8DhnV5nEbEl8GjggDZPn8D0e+eVwCtqzz2zer4XCfyK8j34fmb+tV2lakng5wNvowwYocygeDHw8R7b/AQlFPgHZZbT1+vfu2pm0asps1RWqYrvAXwEeHaPbQ1b/efTrbtSXp9r1spmHYjP02HA+pS9499IWa74pnqFiHgE8Dmmw6l1gf+m/Oxn83FaQ4HrKMsJfyIzb6hdPyiv7Y9SAqfP9/IfqJY/PrCXc2rn3hIRf2b678R2EbEsM5fP53qSJEmSFhXzvOEwz2vPPG/hzPN6Y57XX+Z5hXmeJEka6xt97lf7evkcd/UvxMaN47MH1M44W4My8Hl0RDw5M//cxTkbNY5Xp9z1vX4X565M2ct514h4zAD3cp9Nc//cTSNihWoJW3UhMzMizqZ1Nthm7epGxAqUmT/1JWsPzMyD2tWvrv/7avnTLwNProofTAmzjmpzSnO55pdV4cls/4e/AocCh1b7L9efu4GyVz0Rsbxx6t/nMYvtcd2cU828eV9E/Igy02Od6qnXRcQne3yNrgv8HdgtM89t09Z1wH9HxGmU5ZGnlgJ+VkR8NjN/0kNbQ1X/+XQjIu4MfJLWUODTmfnJPncNyu/BSynf97+0q5CZP4yIR1MCjqnv+z4R8crMvKbdORHxSMq+8FOuBx6Rmce3uX4C/xcRv6PMsG3OGBq0PzIdDET19Y/7ceFqFlSvs/eG/f+XJEmSJpV53uJhnmee1zPzPPO8UTLPA8zzemGeJ0maaM2lI8dC9QFtnVrRBQNsbr3G8fIBtrWY3AIcR7mz//HAfSlLp94HeAJl/97LGudsDfy42gd9Lssax59lOhS4DjgE2AvYlhICPY8y+6HuPsDXI2Jlhq+5jOlKzL3PsmZqfh87fVh/MmUJ2ylfmS0UmJKZtwD70fpafW2H6s3X7dfmun6jrRvmrjV/vQYJmfkHyoyQKVtRllLu1X+0CwUabX2LEpDUvaJN1bEUEetQZpvVl9f9FvAfA2x2v06hwJTMPBn4Zq1odWbOjq37r8bxge1CgUYbl1LeQz0tE90Hzb/rW/fx2i8F/tTj49t9bF+SJElakszzhsI8b3bmef1hntf99c/vsb55Xp+Y55nnYZ4nSZpwY3mjD2XZwbpBzf6Bsndv3VXdnhgRO0REdvk4or/dXpC3AJtk5h6Z+c7M/G5m/j4zz83MUzPzO5n5OspA6t20fmC8M/CNapnItiJiVco+sXWbVv+eDmyXma/NzJ9k5lmZ+bvM/Gxm7sbMQd2uwBsW8H+dr3b7Fd+hTZlm1/w+dvoevrz2dVKW4O1Ktfz0J2pF96yWlZ7Lht22sYh9vXHcXLp8LqdkZrcDooOB+nK0j4mIYe55PhDVzK7v0rqc98+BZ7ZbMrpPTszM5p73nXyvcXyfdpUiYhllb+wpV1GWZJ5TFR78tMv+9Evz7/oWQ25fkiRJUv9t0Tg2z+sv87y5mef1h3neYJnnLZB5nnmeJElLwbje6NP8wN5ukKZ5qsKA5uyedvVuyMw3MvOu8vtS9izuZMUO5VcBj8zMC2dp8xDgA43iV0XEmu3qD1C7986w75CfBM3v44zvYbVvdH1Ww0nZYT/rWfyscbxbmzrN5ZvfN6LZZT2JiBUjYp2I2DQitqg/mPle267Hy3+x24qZ+U/g2FrRCsxvxtGiERErUpaKrr9eTgUeP+AZX//XQ90zGsedAq1daH2/fS8zr++hna/0ULcfmn/XJyGokyRJkpY687wBMs/rinlef5jnLZB53uCY57Uwz5MkaYKtNOoOzNPqjeNePtz06srG8Tptay1hmXloROxN657IL6XDoCIz/x0RtzFzUPj+2UKBmrdSlv6d+lmsBzwK+GpPHV+YZW3KBvk6nFTLGsftvoe7UPZxn3JelzN46pqvtXb7834DeC/Ts9OeBJwZEZ8Gvp2Zp/fY5kBExLqUvj0G2JGy/Gy3N22u22NzJ86j/mNrxw8AvtPjNRaTT9H6e+0vlPDy6gG328trrTmA7vQ36l6N45N7aAPgpB7rL9S/G8dr9PHah9H734u74nK/kiRJ0kKZ5y0i5nm3M8/r3bLGsXneHMzzhso8b5p5nnmeJGmCjeuNPs1+3zLAtv7ZOO4lGDgL2LLDc69kgva8Bf6H1g/Qu0TEssxc3qH+dcBajbKjumkoM6+LiG8AB9SKd2e4wUBzgHUzS2e/935qfh8vb1PnLo3jfarHQqzXLMjMiyPiDcAHa8VbAe8C3hURlwG/rh6/BE6u9gwfimo2yuuANwPznfHWa7B5do/1z2kcj+2sjYh4D62/Yy4FHp6Z/xhC873Mar25cdxp1tr6jePmntlz+VuP9Req+d7q22y8aobrnLNc62ZZvV6SJElS98zzFh/zPPO8+TDP65J53nCZ581gnidJ0gQb1627mrMEBrmX8qWN4226PTEzb87M89s9mLxB5G9p/TC7IrD9LPWXN47/UX1funVC47jXJUwXqvl/uzAzXeq3BxGxAjPfT+0GK3ccQPPNUAqAzPwQsC8z3/dQBrlPBN4D/Ab4e0R8IiK6/p0wXxGxEvAlSgC3kGWte/2d3+tMl6saxzMCmHEQEa+lhDBTppYh73WJ6fm6bQDXXNY4vqbH8wc966mp+Xf9uiG3L0mSJKn/zPMWH/M887yemOd1zzxvuMzz2jLPkyRpgo3rjT7NDyj9XAKw6deN4x0jYtW2NZewzLyNmXeIbzDLKc2ZBe0GYrO5pHE8iMHjbHZpHP9hyO1Pgu2BtRtl7b6Pqwyg7Y6382fm0ZRlPZ9LWaa202yMOwIvAk6PiHdXQcegvAp4aqPsBMrgdQ/gbpTZPatmZtQfA+xTN8YuLIuI/Sjhz5QbgMdl5h9H1KV+ubFx3Ov7ahDvw9k0/64PO5iQJEmS1H/meYuMeZ553jyY53XPPG9IzPM6Ms+TJGmCjevWXc19nzcaYFvHNY5XBnZtU67eZmb9Gdizdtz80DqXZv3Vejx/3iJiQ8peynW/Glb7E+ThjePbKDNrmq5oHL8pM/9nMF0qMvN64HPA56oB/3aU9/2Dgb1p/Z2zAvAGysDp1f3uS0SsQlne9/buAQdk5pFdnNsMXnq1Nu2XX+6kuZRwL0vWjlxEPA74NNPB0S3A0zPzl6PrVd80fxa97u8+7NlcGzeOm3/3JUmSJI0f87zFyTxPvTDP64J53vCY583KPE+SpAk2riv6nE/rneWbDqqhzLyAmbNVXjCo9sZcc8/Y5oCurnk3/bIe22rWb+69PkgvZeb+st8ZYvtjrxpsv6xR/JvMbDcIbe6hvPVgetVeZt6WmX/OzE9n5v7AJsBDgGMbVV8xoGV/H0rrgPtz3YQClebgqle9fq/v3jjuad/kUYqIBwNfpvUG2Bdm5ndH1KV+ay6jfc8ez++1/kJt0jge1jLLkiRJkgbnfMzzFiPzPHXFPK8n5nlDYJ43J/M8SZIm2Fje6JOZNwBn1Yo2i4jVB9jk+xvHT42IuwywvbETEesDWzWKm8vx1h1Da7izVUT0Motnh8bxRT2cO2/V7J+XNop/lpnnDqP9CbIfZTnduk92qPsbWl8rD4+IkS1hm8UvgUcC36s9tQLw+E6nLaDJ5mD7e21rtffABbQLM5e0nsvOjeOTFtj+UETEjsB3aZ21+PrMPGI0PRqIExrHe/R4fq/1F2q7xvGpQ25fkiRJUp+Z5y0+5nnmeT0yz+ueed6Amed1xTxPkqQJNpY3+lTqHzhXYOZAsZ+OoHXP6VWBz45ycLII7UPr6+kfwBmdKmfmJbQu67oyrUv/zuWRjeOBL8UZESsCX2LmXuUHDbrtSRIROwAfbRSfDRzdrn41K+j3taJNgEcNpnfdy8wEPtso3rJD9ebS1Kv20NSyxvFVPZy7fw9123lmtxUj4o6UZZCndFq6eVGJiC2BH9D6fX5vZr53ND0amNNp/Tu2UxWIzCki7gA8ZyC96qzet6uBM4fcviRJkqTBMM9bXMzz1BXzPMA8b9Ewz5ubeZ4kSZNvnG/0+XnjeKdBNZSZNwKvaRTvCRxiOAARcSfgLY3i71YDp9k0B1Vd7YccEbvR+vO+Dfh+N+fOVzXD6XvMvAv+iMxsvhbVQUTsCfwYqM/Yuw14SWbePMupzSDhfRGxZr/7Nw+3NI477U2/vHG8UbtKHTT3Yt62m5Mi4gnAbj200879qut0422Ufc2nfL/D0s2LRjWj71hafx5HZObrR9SlgcnM25g5y+7QKvCcy8HAnfrfq/YiYiNal/D/RRd/TyRJkiSNB/O8RcI8zzyvW+Z5tzPPWwTM88zzJElSMc43+jQHggNdhjAzjwY+0ih+FfCViGjOCOnGugvvVX9FxDYR8bgez7kzZcBc/9B4E/A/XZz+WVpnCT0sImYNB6oP8s1A4SuZ+Zcu2utZRKwTEa8E/sDMWUcnMnNf6n61m43H7oNoZ1giYoeI+CRlENYcYLw+M386xyWOonUGwHbANyOip/dRRGwQEU/u8NyLI2KzXq4HPLdx3GnWW7N877a12vtD4/g/I2KN2U6IiPsz830yXx+PiOayzM32nsjM98KH+tT+QETE2pSZP3erFX8XeOFoejQUhwFX1o4fDHyh01L5UbwOeO0wOlfT/Hv+f0NuX5IkSdLgmOf1mXle2/bM8/rAPM88b7ExzwPM8yRJUmWlUXdgvjLz0og4kek9ZPeIiJUys3lHfj+9hvIhsr7M6FOBR0bEYcBXgd9Vd1rPEBHrAI8BXgw8pNfGI2JT2v/M7tw4XikituhwmWsz84oOz20EfCciTgM+D3wzM8/p0Je1KPsyv4WZA713ZOZ5Hdq4XWbeGhGvoHw4n7rp7JCI2Bw4MDNbZj5ExF7Ax2jdC/pfwJvmaqthtQ7fnzWBdYA7AvemvLYeUpU3HQs8PTP/3WPbk2T9Nt/HFSnfw3UoS/LuRNlX+n5tzr8FeHVmNgO3GarXylOBXwNrV8V7AX+MiHcBn8/Ma9qdGxHrAQ8Hngg8ibK38TfaVH0JZUbEMdXzP8jMS9vUowoQ3gE8pVZ8HfD1Dv+Fk4FrmX4t7RMR/wS+SdmP/qbG//f82uGJwAXA5tXx3YEfRcTzM7MlcKhmRb2UMhtnDeByZi5N3Yt/UX6//Kp6r36t/vutCiheBbyV8rOf8sXM/PEC2h2GjwP3qR2fAbwB2LTHiZ3LM3N5H/s1MJl5WUS8jNZltZ8B7BoRn6DMrL2M8v69L/A8pv/GfomypPsw7FX7+jZKYCNJkiRpApjntTDP6415Xn+Y55nnmeeZ5w2CeZ4kSUM2tjf6VI5i+kPLupS7hn80qMYy8+Zq2csPUQYRU9YEXl89lkfEmcA/Kct7rkL5kHVXyn6/7VZR+jvwrS668CumBwez2QT4a4fnjmTufX7vCfwv8L8RcRXwJ+AK4BrK//UuwL1o//r5ZGb+dxd9BCAzf1QNOOqDw5cDL4mIE4CLgTtQBurN//tNwDMzs9P/tZOd6fz9mctVwNuBj3QKgJaQ91aP+TgZeFlm/rbbEzLzzxHxFOBrlPcUlOVADwM+UgVaf6Ps/7s6ZY/mrWldMnQuKwKPrR5ExKWUmUdXAtdTXv9bU2YgNUePr8jMf3bo+3XVwGtqyfAA/rN6tHP7tatQ5PXAl2vP7wr8OSL+CJwFJLAxJYiZ2i/8FsoMpWNm/y/P6iWUAeGdq/b/ERGnUN4HdwJ2oXXZZoA/A/+1gDaHZePG8XaUfa97dRBw4IJ7MySZ+aUo+5i/q1a8GfDOWU77M2VmVD0YGMjSuxGxElBfXvrHmXnxINqSJEmSNDLmee2Z583OPK8/zPNamecV5nmLmHmeJElqZ9xv9PkS8D7KwBHgaQwwGIASDgAvjYjvAIcA2zeqLKN8WO7GZcChwCGZeV3fOtlf6wAP6qLedcCrMvNTvTaQmR+NiFspP8upQcbKzL4f8T+AJ2fmr3ttb55OowRRn8rMqwbZUESs1qa4ua/zOLqRMnPq48Ax89mjNzN/XC1jezRw/9pTK1LCo3t3cZlevpcbMff+29cDL8/Mw+eo92bK7J3H99A+AJn5lYjYmrK38lRoEJSA7l4d+vTczPxBj7NZmu1+uVpe+4OUUPNOwKNnOeV3wCMz88pZ6mjEMvN/IuJC4P3MPUPsq8ALgFsb5W1n3PXBXsB6tePPDKgdSZIkSaNjnjd45nmFed7CmeeZ52kRMM+TJElN7WajjI3qw+eRtaJnVEtdDqPtHwA7UGYKfJlyR3w3LgS+WJ23SWYevIhCgTMod4UfTxlYdONsylK7W8wnFJiSmR8DdqQsMTzbB86/U+6236bPocBtwA2UpVFPB34IfJgyW2qrzNwxM9836FCg8sDG8c8ys7mv82J1CyUkugg4hTKoOJiyPPYGmfn4zPz+fEKBKZl5LmWmy+OAH1MCh7mcQZllthvQdk9v4JmUpV5/SlmWdy5Twd42mfnpuSpn5o2Z+QTKwOeTlO/PP2ks8zvL+e+gDMp/N0u1qym/E++ZmV/r5rpdtPsRypLXxzJzcDjlEuB1wM6ZeXk/2tVgZebnKbPZ/ovyPrqI8l66grKP/GHALpn59My8mhJ61w3qd+ELal9fSOflsyVJkiSNKfO8vjPPM89bKPO8DszztJiY50mSpLpYwOfzRSEi7k5ZinPqpqUXZ+YnR9CPFYBtgG0pS+2uVfXpKsqSv/8ATh2XD83V/+fulCWKN6F8KFyNEhj8C7gUOGkQ/5+IuANl1tGmlCVGb6IM2P+QmX/sd3uLTUS8gzJbZMpumfmrUfVnsatmTO1MWQr6jpS9rK+jvE7PBc7otATvLNdckfJ+vjvldbgWZZbRtZT38p+q63YaKA9UNRtoF8qMnKj6dBFwfGbeMMB2N6J8r6d+x11G+f17gktfT7aI2JMSIEx5X2a+rs9t3JmyXPfKVdFrMvP9/WxjviLiHpT3PQC/Pelktt++OQF4fJ1++uns9ID6pEp2yMw/j6o/kiRJmnzmeYNhnjc65nm9Mc8zz9Pgmee15nm//+WP2X7bbUbYo/46/cyzuM9ue9WLzPMkaYkZ9627yMxzIuILwHOqoldGxKcWMsNgnv24jTLL4Ixhtjso1f/nrOox7Lavp/UD6FLzsNrXPzIUmF01EP55n695K2Um2Hz2eB64zDybMvtu2O1eCnxr2O1qUXhI4/iUAbTxcqZDgb9TlgWXJEmSNIHM8wbDPG+kzPN6YJ431HbN85Yu8zxJkibYWG/dVfM2ppfL3A540gj7Is1btVT1A2pFbxtVXyQJICJWBp7fKD6hz20sA15WKzo4M//dzzYkSZIkLTrmeZoI5nmSFhvzPEmSJt9E3OiTmecDH6wVvb1aqlYaNw9heqWtYzKzrx++JWke3klZ3nnKL6q/u/30GmDt6uvTgU/3+fqSJEmSFhnzPE0Q8zxJi415niRJE26SBs8HU/YCBdgR2G+EfZHma4/a128fWS8kTayIODoi9o6ImKPeKhHxbqC5d/cH+9yfTYBX14pelpk397MNSZIkSYuWeZ4mgXmepIEyz5MkSU0rzV1lPGTmdRGxL/Dwqmjl2epLi1Fmvo6ZH8IlqZ92BfYBzo+IrwMnAucBVwFrABsDuwHPpXXmD8CXM/Obfe7PXYH3Vl9fnJnH9fn6kiRJkhYp8zxNAvM8SUNgnidJklpMzI0+AJl5PHD8qPshSdIY2IKyxG63fgK8qN+dyMxfAL/o93UlSZIkjQfzPEmSurYF5nmSJInJ2rpLkiTN7Yoe619NWU7/kZl59QD6I0mSJEmSJKkz8zxJktRiolb0kSRJc3oAsDOwB7ATcDfK8r5rAgEsB/4JnAL8HPhqZi4fRUclSZIkSZIkmedJkqRW3ugjSdISkpkJnFA9JEmSJEmSJC1i5nmSJKnJrbskSZIkSZIkSZIkSZKkMeCNPpIkSZIkSZIkSZIkSdIYcOsuSZKkHnzpT5dx5+vWGXU3+ubvf71s1F2QJEmSJEmSBuabF97KiSvfMupu9M0lF9466i5IkkbMFX0kSZIkSZIkSZIkSZKkMeCNPpIkSZIkSZIkSZIkSdIY8EYfSZIkSZIkSZIkSZIkaQx4o48kSZIkSZIkSZIkSZI0BrzRR5IkSZIkSZIkSZIkSRoD3ugjSZIkSZIkSZIkSZIkjQFv9JEkSZIkSZIkSZIkSZLGgDf6SJIkSZIkSZIkSZIkSWPAG30kSZIkSZIkSZIkSZKkMeCNPpIkSZIkSZIkSZIkSdIY8EYfSZIkSZIkSZIkSZIkaQx4o48kSZIkSZIkSZIkSZI0BrzRR5IkSZIkSZIkSZIkSRoD3ugzTxHx2YjI6vGlUfdHkhYqInav/V7LiDhwgG0d0Whri1nqbtGoe0S/rj0oEbF/ow/7D7sP4yIiVoyIP9e+V68cdZ8kSZIkTSbzPEmTxjyvf8zzumeeJ0nS6HmjzzxExIOA/arDm4A3zlH/uNoHnuMazzU/PA7qsf8s/dsgIh4VEW+LiO9GxKVtzt9iAd+v4wbV9wF+Hzv+f9sMUrKL/p3f7aBmmHrpV5tBY7vHrRHx74i4PCJOj4gfR8ShEfHCiNh+SP8tSYtA43fDgZ3qZeatwBtqRQdFxEYD76AkSZKkJcU8r+fvl3meeZ55nrTEmOdJkjQ+Vhp1B8ZNRKwAHApEVfSxzPzrCLs0LxGxMfAh4AHA5iPuzmJ0/ag7MKZWAO5QPdYHtgP2nHoyIv4CfBE4LDP/PpIejkgjQPp5Zu4+qr5Ii01mfi8ifgnsBqwN/C/w3NH2SpIkSdKkMM9bMszz5sc8rwPzPKkz8zxJkkbLFX16ty9wr+rrm4D3jrAvC7Eh8FQMBdo5PjP/MepOTKi7Am8Fzo+Id0TEaqPukKRF4x21r58VEfccWU8kSZIkTRrzvMlnnjc45nmSOjHPkyRpRFzRpwcRsTJwcK3oqMy8eIGX/RpwXJd13wc8pXb8IeCDXZ57RZf1bgPOBrbtsv58bNlj/W763sv3sW5V4BRgjVrZp+dxnaXoYuDBbcrXAJYB6wI7ADsDDwHWq9VZFXgz8OiIeEJmXjjYrkpa7DLz2Ig4Gbg/5UbkdwKPH22vJEmSJI0787y+Mc+bDOZ5kvrGPE+SpNHxRp/e7EProPbQhV4wM68Fru2mbkQ06y3PzPMX2IW/ACcDJ1X/npKZ13azT/V89aHP7a7Z9fexLiL2oTUUuAb4ar/6NeFu6eJn+T2AiLgD8Czg9cDda8/fBzguIh601Jb+Xeoyc39g/3G7dg99OAI4YpR9GFOHAZ+pvn5sRNwjM/88yg5JkiRJGnvmeX1gnjcxzPM0b+Z56sA8T5KkEXDrrt68pvb1iZl56qg60gdnAutl5t0yc5/MPCQzf14NsJeS5zeOv5SZ142kJxMsM6/PzE9TgoDPNZ7eCvhSRMTweyZpkfkSsLz6Omj9uytJkiRJ82GeN3nM84bAPE9Sl8zzJEkaAW/06VJE7Mr0Xt4Anx9VX/ohM2/IzH+Nuh+jFBGbAw9rFB8+ir4sFZl5XWY+Fziq8dRDgQNG0CVJi0hmXg98s1b0zIhYZ1T9kSRJkjTezPMmj3ne8JnnSZqNeZ4kSaPh1l3d27/29W3A10fUD/XPAbTe7PanzDxxVJ1ZYv4DeACwXa3sLRFxRGbe1suFImIlYCfKTKINKPuFXw6cDxyfmTfMt5PVtXeoHusDawI3U5aVvpiyVPbpmXnrfNtYQN/WA7anLJ28HrAacDXwT+BU4IzM7OuS3RGxArAL5Xu9MXAD5fvwi8y8vJ9tqVVE3IXyntkUuANwBXAacHKv75k2194Q2I3yM70DcAlwHnDCQq89T19hOihcjbLM/idG0A9JkiRJ42//2tfmeZPBPG90zPMWyDxvaTHPM8+TJGmQvNGnCxGxIvC0WtEpmXnpqPqjhauWld2/UezsnyHJzOsj4t3AkbXiLYGHAz/s5hoRsR3wFuCxwNodql0fEd8B3paZZ3fbv4i4E/BmYF/gjnNU/3dE/Ao4utrHuX6d4yizm5oeGhGzDdoPyswD2/RrZ+DplO/TDpSlUDv5Z/x/9u47vJaq3v/4+5ucQ5VebEgRUVDEgoooKlj52bGhqFes13a99oJKs/eKnea1V/CKio2iUuWKFVSqgiAdpJ9z8v39sSZmMidl72TX7PfrefZD1srMrJVksk/mwyoRXwA+utj90iNiLeANwIuBO81wyKqI+DHw+sz8U4vXPAJ4Xq1qmxb2iG9Jq9ee4+fTlsxc7ecQEfsCh9eqnt+8PxrH1++HEzJz96r+QcBBlNmKM63C98+IeBdwyAJCtfsAHwD2mOXaF0XEZ4H3ZubKiDgQOKD2+T0y8/h22mzRz4AbgHWr8j4YDEiSJElqk3ne0mOe11/meeZ55nmrHW+eN8U8T5KkHnPrrtY8CNioVj6uXx1RxzwS2KpWvpUhX755CH0VuKxR98T5ToqI8Yj4CPAHygPDbKEAlNkMewN/jIj/bqVTEfFw4M/AfzF/KACwDvBo4J2tXH+hIuIpwCnAa4F7MncoAKXvbwL+EBGPWkS7twNOBg5m5lAAYBz4f8CZEfHShbal6SJiP+BEyvvVbP9e3xb4OPCtiFijjWu/FjgdeMQc194CeAdwQhWW9URmrgB+Vat6cERs2Kv2JUmSJC0Z5nlLj3le/5nntcE8b/SY5/2beZ4kSV3mij6t2bNR/kVferFERMTHgF2BrYENKcumXgmcTfneHtXObI0FemGjfHRmXtHlNlWTmSsi4gSmz6578FznRMTawFGUB/G6FZTlbS8CbgFuR1n+d53q88uAj0bERjPNrKldfzvg+5RAoe5C4Czg6qq8PmXG0nbA8rn63EHNh7dVwF+B8ylL/CYlDLgn5euftAlwTEQ8LDNPbrPNNYFjgHtX5QngDMoyymtQlmq+a+345cCnIyIz0xkbixARrwfeVav6c/W6Abg9ZcnltWqf34vyEP+mFq79OuCDM3zqT5R76hZgS8rSwuOUcPwblJCiV05k6vd8nDLr7Zs9bF+SJEnS8DPP6yDzPIF53gKY540Q8zzzPEmSesmBPq15YKN8ZjsnTy7ZqH97VaO8UfW6C2XZ1vdExNHAGzLz3E43Xu2F/ORGdVeX+c3Mrbt5/YUagH6dzPRg4B4RsSwzV85y/CFMDwWuBQ4EDs3Mf9UPrEKEl1Nm5kw+QO0fEadm5g9nuf7BTA8Ffg68NjN/O9PBEbEmZanYvYDdZzjkmbW2z6/Vn1p9bjbXzFH/JeB/Kftoz7hfeUTsSnmo3KOqWg58LSK2y8xb52i36T+Zmv34Vcrv5MWNtu4PfBrYuVb98Yj4ZWb+sY22+qH+82nVe5j+s+vGsu/3pOyxDSUIe0tmnl0/ICI2Aj7M9CXLXxcRn55ryeSI2Bl4b6P6eOCVzZ9XRGxG+Z14KfBQyh7yLZtpCeQ2nNko74rBgCRJkqT2mOd1lnnegBiAfpnnzeyaOerN8zrHPK84HvM8SZJGmgN9WlP/g/eazLyobz0ZDWOUB61HRMQLMvPbHb7+sykzGyb9DfhJh9tQa85ulJdRZjf8vXlgRDwdeH6t6kJg99kegjLzJuBDEXEyZY/gtSjL4348Iu7W3P+42uf9CbWqvwCPzcxbZut89bkfAz+ugojm5/+9l3a5/L/dvID9q08A7piZN853YGaeHBGPoARek9+zLSlLIx/RRpuTocCHMvP1s7R1ekQ8FPgRUw+zawCfqZUHUrt7nUfEm5geClwDPKaTfapsXP33/Zk544yezLwaeH4VEDypqh6nzG58+xzXPoTp//Z/B9h7pjAuMy8HXhYR5wHvBzZt66tYnN81yg/o1IUjYnNgszZP27ZT7UuSJEnqGfO83jLPGx3mea0zz+sw8zzAPK9V5nmSpCVttn08Van2s92gVnVhv/qyBPye8sflPpQ/8u5KGen+COBt1efr1ge+HhGP7XA/XtAoH958SFTPXD1D3Wp/sFcP7fvXqlYCT2zl4TozT2qcexdWnwEG5aFn3Vr5f+cKBWZo56ZWj12IzLy8lVCgdnwCr2T6vunPXkDTZwBvnKetGym/19fXqneLiPsuoL2BFBHPZ/rMmZuAJ2Rm832rU34JvKWF497aKD98tgOr2Vq71KouAV4wx4w7ADLzA5QArJcupvyeT7rrbAcuwMuBP7T5OrqD7UuSJEnqMvO8jjLPU5N5XuvXN8/rI/M887wOti9J0sBxoM/8tm6Unf3Tvq8AO2bmTpn5psz8amaenpl/zcw/ZObPM/NdmbkT8BygvmTrOCUcuGMnOlItc3nvWlUCh3fi2lqQmYKB1WbSUJas3bFW/nJmNmcIzOUQoL4s7hNbOGfzNq4/kKoH9vqyxrtERLvv+we2EpxVMyM/16jet822BlJEPBH4fK1qJfCMzPxlF5t9V4vf9z9S9lifdO85Dn9Wo/zJzLy2xf68o8XjOqL62uvLKG8WEevOdrwkSZIkNWzdKJvntc88T7Mxz+si87zOMM8DzPMkSVrSHOgzv+bDwUwPMppDZn6u1b19M/PLlBlB9ZkOtwEO6FB3mrN/fpqZzurqn5neg3KGukc1yl9vp5HqAfm0WtVMS9BeUb0mPS0iBnqp2kkRsVZEbBYRW0XE1vUX04O29YAt2rj01ZQlfFv1lUZ5tzbOHUjVMsZfp4SUUO7PF2Xm97vY7E2U/eRbdVbt43Ui4jazHPegRvkbrTZQhSD/aKNPndD897bd5XklSZIkjS7zvEUyz9MczPM6wDyve8zzCvM8SZKWtmXzHzLy1mmUu7qcp/69R/DbgA/Xqp8XEa/JzBsWet2IWIuyHGndoQu9njpiwxnqZvodaz5gXlU99LbjutrHW0fEWH2GRWZmRHyNsjwulJlIx0XEt4CvUUKk+lK2fRMRuwBPB3YF7sH05cjnsxFlH/tWnDHfMrANv6XMtFqrKu8UEWtk5q1tXGNgRMS9gO8x9fUAvCEzj+xy0+e2+T1rPkBvwPRllyfdq/bxNZl5Tpv9+jWtzZ7rlObS1p2aAfQp4JttnrMtLvcrSZIkDRPzvB4zzxspG85QZ543D/O83jDPW415niRJS5QDfebX/B6180eyFu5TwIGUfb0B1qAs97qYUfdPZfqD6JXAUYu4nhZvoxnqLp+h7k6N8imLbHeMci9c1ag/EPh/lIcAKLM+9q5eqyLiTOBkyn7LJ2bmJfRQROxIWbb4oYu4TDshwl/auXBmroyIC4Dtq6pxYBOmL9k6FCLizpTZT/Xv1/sy80M9aL7dmaYrGuXlzQOqZXLrAUer4VDdQs5ZjOa/t6t9XQuRmZcxfa/7eUVEJ5qWJEmS1Dvmef1hnjcazPPaYJ7XO+Z5MzLPkyRpiXKgz/yasxFm2m9YHZaZt0TEccCTatU7sbhgoLnM75cy85ZFXE+Ld/dGeQUzP0Ru0oW216MRDGTmlRGxK/BpSpBUNw7sXL1eCWREnEKZRfbFzGw+nHVUROwG/KDq92K0s2XjdfMfsprmHtEbM2TBQETcFvgxcLta9WGZ+eYedWHevbwXYMNG+V8zHTSPhdwPi9H893bBM0ClpaCaybztvAdK3XVuZt7c705IktQC87w+MM8bGeZ5LTLP6x3zvFmZ50l9ZJ6nAWKmtwQ50Gd+zT+EOrXUoOZ3QaO84P1cI2IbygyiOpf57b8HNsp/yMxVMxy3RhfannFIf2ZeTtnPe0fguZQZQTvOcHxQltrdFXhDROydmb/tQj+JiPUp+y/XQ4FrKUsQHw+cTdlv+Xrg5voSxhFxIHDAApueaX/1flyjZ6rv9Y+Y/sf30cBL+tOjjmmGoAv5nerG7+Fcmv/e9jqYkAbNtsAf+t0JjbwdgT/2uxOSJLXAPK9/LmiUzfOWHvO8Vjpqntcz5nlzMs+T+ss8T4PCTG8JcqDP/P7eKN++L70YTZ2cffUCpj/YnZ6Zv1/E9bRIEbEGqy9Z+8tZDr8CuEP18c3AOpnZ1QfOzPwD8CbgTRGxIbAL8GBgd0oYUH//vBvws4i4f2ae34XuvJTp7z2nAk+oQoz5rD//IbNqZ1ng2c5pd9navqlG138PuHet+kTgmbMEVsOk+XOYaZnt+WzciY604Q61j2+hzeV5JUmSJI0087z+Mc9bwszz2mKe1wPmefMyz5MkaYlqZ8nHUXUB00ewb9GnfoyiTRvlKxZykYgYA57XqP7CgnqkTtqH1Wd1fW+WY/9Z+3gtYMuu9GgWmXlNZh6bmftn5kOB2wJvYPqytpsA7+hSF+pLXiewT4uhAEx/uGrXXds5OCKWAVvXqlax+r7pAykixikzqh5Wq/4t8MSlsJxhFWxcXKu6c0Ss0+Zl7tnBLs0pIm7D9FDrwm6HgZIkSZKWlAswz+sX87ylzTyvdeZ5XWae1xLzPEmSlihX9JlHZt4cEX8Gtq+qtoyIdTLzxn72a0Ts0ij/Y4HXeTRwp1r5RsoDgPokItamzK6pOxf4+SynnATcp1Z+NPD5LnStJZl5FfDBiPgFcDJTs8ueGBFj9aV2O2S72sdnZeZ5bZy76yLa3TkilmXmyhaPvxcluJn0u8xsLjE7qD7L9ADmPGDPzGzuUT7MTmFqr/oxSgjyw1ZOjIiNKT/fXtmhUT6zh21LQ2GNuz6OWGshEzWl1uXN13LrX47pdzckSWqbeV5fmectUeZ5bTPP6z7zvDmY50mDxzxPvWKmNxoc6NOa05kKBsYo+9id1r/uLH0RcU9WH21+/AIv98JG+ZuZ6d6w/fUZpn6nJr1jjgfqY4FX1Movoo/BwKTMPDUi/sDUvboeZebaTEuS3gKsWX285gyfn8uGtY9bflCNiIezuNlSGwF7At9v8fh9GuXZlm4eKBHxPqa/T1wKPDozL+1Tl7rlp0wFAwAvpsVggDKLspd7eu/UKPtvrtQwfptNGV+3OVla6qxVy5b3uwuSJC2GeV6PmecteeZ57dmw9rF5XoeZ57XEPE8aMOZ56hUzvdHgQJ/WnAA8t1Z+AP6R0jXVkpsfaVSfk5l/WsC1NgGe2Kg+dKF90+JExLrAp4D/aHzq58AX5zj1h5QZQttW5QdExAsy87DO97Jtzdkxs814uYayRDBM35+7FVcDm1cfb9fKLKOIWA68p812ZnJgRPyghfa2AF7SqD6yA+13VUS8Fnhjrepaysyfc/vUpW76MvB+SoAFsFdEPCYzj53rpIi4I7B/tzvX8IBG+fgety8NvBgbJ8bG+90NLXHeY5KkIWee10PmeUuXeZ553qAxzzPPk4aVeZ56xftsNDjQpzU/aJT3AD7Zj44Mm4j4L+Dzre6JGxFrUGaHPKLxqYMW2IXnMn3U+l8y8xcLvFbPRMSBwAG1qhMyc/f+9GbxImItyuyQN7H6PtHnUPaonnW/3sxcGRH7Ux5sJn06Iq7JzO+02ZdHAuc1l8uNiHsD2wDfq/Y/buVaOzF9+dNL5lga9iymgoGtIuJumfnnFrv9W+BR1cebUmZAfW6Ofo1Tlq5tPlwtxM7A+yh7mM/W3trAV4Db1Kp/lZlndKD9romI/wA+WKu6mbKH92/71KWuysx/RcTHgLfVqr8REU/OzONmOicitqb8G7hh93s4zR61jy8F/q/H7UsDb2x8GWPOzFCX5biPi5KkoWaet0DmeQtjnjedeZ55XjeY5wHmedLQMs9Tr5jpjQZ/yi3IzEsi4lSm9pjeo819bgdSRGzK9D/k57JFRMxUvzIzL5rjvI8D+0XEl4BvAWfM9H2LiGXA44ADgXs3Pv1Tpj8QtuMFjbKzfzpnWfXQ0LQOsAFlmdh7Un5vHgZsPMOx/0d5EPvnfI1l5lci4hFM/UzXAL4dEV8BPjzbQ2j1kLwTZSbY3pS9gveg7NlctzXwHeDCiPgGcBRwemaumOGay4AnA5+gLP89aa4ZL8cBu9fKR0fEeyl7FV8L1IORazLzmlr560wFAwCfrMKWz2TmrY2+3Z/ysPvQqupyYLM5+jWXqyk/x9dHxB2AN2bmxTO092lKgDDpVuClC2yzJyLi7pT3g/ob25uBv81yX88qMy/oXM+67h2Uvcsnl6deH/hZRHwL+AbwF8rPb0vgsZTlgNehhCbHMn3f866IiK2Yvo/90XMFh9KoGlu2nLFlvVyBW6MoDZ8kSUPMPA8wz9PqzPPM88zzMM/rNPM8qTXmeeoVM73R4ECf1n2RqWBgI8qDxU/6152O+CBln9ZWzDZr5kLKA9Vcbge8vnrdEhF/BC6hPAwtpyxhujMzhxS/Bp6ykD8KqweW+r7gK5l7OVm1547A+Qs892bK/ffOzJxtadyZvJTy+7dXrW4fYJ+IuJwyU+ZKYILywHMHShCwVhttbEWZ7fIG4NaI+BNwMWWp3nHK/XwfSvhRdzbwzjmu+wXK78DkMqt3Aw6f5diDKCHZpCOBVzG1z/Fy4GOUZXhPpXzNGwA7Mv338QTKvtpvnaNfc/ksZU/ve1O+z8+MiNMpv/drUL63d5vhvFdl5h8W2GavbM7q/wZ+tHq1a8bUdBBl5q0R8TjK8tp3qaoDeHr1mvE04BWUsOBJjfpueGqjPPBLRkt9EWMuwarui7H5j5EkabCZ583MPG90medNZ543xTxvQJnnSUuIeZ56xUxvJDjQp3VfozzIrF2Vn87wBwP9sCZw3xaOS8rsije1ukzwDF7YKB+TmZcu8Fq91nyQvbovvei8cymzuT69kJ9FZq6IiKdSHtoPYvr3aTPgkS1cZgVwQ4tNrkF5KL73PMf9ihJgzXrdzPxHROxNWRJ3wxbbnzx3ZUQ8gfIwt23tUxtRHtxn8lPKA9Zr22mr4RbKLJBjKSHbGCUg3WWW41dQQoHPLqJNdVlm/j0iHgJ8iukh20yuBJ6XmcdExPsan/tXVzoIz6h9fHZmntyldqShNrZsOWPLnQGk7nI5aUnSEmCe1xnmea0xz5uBeZ55nhbPPE9aGszz1CtmeqPBgT4tysyrIuJIppav3DsiXpuZ1/ezX0PgDZTZUrsAm7Rw/OWU5SY/mZlnL7TRao/hZzWqh2mZ3wc1yh/pSy/aN8HUg/flwEWUpUPPBH6RmWcttoFqNtj7I+KLwH9Tfs5bzXPavyiz2I4Bvp6ZV85wzI+Bp1AehHdnanbErF2hzK75DPDVVmapZeYPI+JuwHMo+9bfnbJH9zpMXzJ4pnP/FhH3pSzV+qLqnJn8purTFzJzYpYlultWLXX+QMp+7C+kzPxqWkUJSl+XmX9aVIPqiSqYe0pE7Eb5HdqdMmNuLeAflKWwv0n5fZncp37DxmVm279+wSLiHkwPnoblvU/quRgbdwaQus57TJI07MzzFsw8b2HM82Zhnmeep8Uzz5OGn3meesX7bDSE22S2LiK2oyznOfkH/H9m5uf62KWhEhFbUJYF3YISEqxNeaC4GrgCODMzz+1fDwdDRKxD+Z5MDuv9WWa2MrNlZEXENpSZZZtRZsVMUMKAf1B+Z/+amavavOYmwD2AbSj36zqUGTHXAedQ7teZAoaui4h1KeHR3ShLGl8LXAr8NjPP6WK7Y8CuwJ0pD5E3U5ZBPjEzL+tWuxoMEfELYLeqmMAGmdnRWUAR8QnglVXxcmDLRcwC7ZgqsPj38tWvPfwH3G6b7eY4Y7hcev5f+fDzH1uv2jEz/9iv/mhmzftwk0ftx/INbt/HHmkUrLj2Eq78ybvrVb4/SJKGjnne4pjntcY8r33meeZ56j7zvKkcZf+vHMsd7nzXPvaos/5x3l84eJ/H1Kt8Xh9A5nnqFzO90eCKPm3IzL9GxJeB51ZVr46Izy9kv+lRlJkXUWaEaG67MRUKAOzfr44Mi8w8n4XvLz7bNa8ETqxeA6VaUvgn9Hi58cycoCxr/Ktetqv+q8Ko+jLtf+lCKLAxsG+t6r2DEApIg2ps2XLGlrnUr7rLZX4lSUuBed7imOe1zDyvTeZ5PWvXPG9EmedJg8c8T71ipjcaHOjTvv2BvSkPbjtQ9kP9Tl97pKXm4bWPj83Mk/rWE0kqnsf05aW7sc/2q4HbVB//DTikC21IS0bEmEuwquvK5F9JkpYE8zx1m3mepEFjnicNGPM89YqZ3mhwoE+bMvOCiPgo8Maq6oCIOKoaGS91Qj0YcPaPpL6qlml/R6P6ix1uYxPgv2pVb8nMWzrZhrTUjC1bzthyZwCpu5z9I0laKszz1APmeZIGhnmeNJjM89QrZnqjwYE+C3Mw8ExgS2Anysjow/vaIy0JEbE+U8tpHpOZp/WzP5KWnoh4KrAz8JHMvHyeY+8DfBvYuFb928w8rsPd2h/YsPr4uMz8SoevLy09Y+POAFL3eY9JkpYW8zx1hXmepG4zz5OWCPM89Yr32UhwoM8CZOYNEbEP8KiqymFx6ojMvA5/LyV113rAW4DXR8SPgJ8BvwUuA1ZSQoB7Ao8HngBE7dxbKWF4x0TEOPBP4KCq6sudvL60VI2Nu6e3um9s3MccSdLSYZ6nbjHPk9QD5nnSEmCep14x0xsNPoAsUGb+CvhVv/shSdICLac8+D+hxeNvAv4jM3/byU5k5irg3Z28pjQKxpcF48vca1ndNb4s5j9IkqQhYp4nSRpy5nnSEDPPU6+Y6Y0GB/pIkjRargFWAe2s3fgr4NWZ+euu9EhS+yKI8IFNXeY9JkmSJEmD4BrM86ThZ56nXvE+GwkO9JEkaYRk5lERcVtgT+DBlGV9t6Is8bsWZabPVcCFwC+AH1SzXiUNkPHxMWcAqevGx73HJEmSJKnfzPOkpcE8T71ipjcaHOgjSdKIycwrKXtnu3+2NKTGxsZ8YFPXjY15j0mSJEnSIDDPk4afeZ56xUxvNDjQR5IkSRoyMQYx5hKs6q4wE5AkSZIkSeoI8zz1ipneaHCgjyRJkjRkXOpXveAsM0mSJEmSpM4wz1OvmOmNBgf6SJIktWHFqgluXTnR7250zIpVS+drGSVlBlC/e6GlzntMkiRJkrQUrJoor6ViKX0to8Q8T73ifTYaHOgjSZIkDZmxcff0VveNeY9JkiRJkiR1hHmeesVMbzQ40EeSJEkaMmPjwZhL/arLxsbdN16SJEmSJKkTzPPUK2Z6o8GBPpIkSdKQiQjGwgc2dVcMyT0WEdsA9wbuANwGuAS4EDgpM1f0sWuSJEmSJEmAeZ56Z1gyPS2OA30kSZKkITM2PuYMIHXdoC/zGxFPA14L7DrLIVdFxNeB/TPzit71TJIkSZIkaTrzPPXKoGd66gwH+kiSJElDZmwsGBtzZoa6a1DvsYi4DfB54JnzHLox8DLgKRHxvMw8tuudkyRJkiRJmoF5nnplWO4zV+leHAf6SJIkSUMmxtxrWd0XAzj5JyLGga8Dj2186nLgN8C1wLbAfYDJX5LbAkdHxCMz85e96qskSZIkSdIk8zz1yiBmenWu0t0ZDvSRJEmShsz4sjHGXepXXTag99h7mT7IZwUlGPhcZt46WRkRdwe+wFRgsCZwVETcMzMv6VVnJUmSJEmSwDxPvTOo95mrdHeWA30kSZKkIRMEEc4AUncFg3WPRcSdgf9uVD89M49uHpuZf4qIRwA/Y2qwzybAAcBLu9pRSZIkSZKkBvM89cqgZXrgKt3d4EAfSZIkaciMOQNIPTA2ePfYAcDyWvmImQb5TMrMmyJiX+D3wBpV9Qsj4v2ZeV73uilJkiRJkjSdeZ56ZQAzPXCV7o5zoI8kSZI0ZJaPB2sM5gOblpDlA7RvfESsDTytUf2++c7LzL9ExFHAM6qqZcA+wDs72kFJkiRJkqQ5mOepVwYp0wNX6e4WB/pIkiRJQ2Z8LBgfG6wHNi09A3aPPQZYp1Y+OTPPbvHcw5ka6APwFBzoI0mSJEmSesg8T70ygPeZq3R3gQN9JEmSpCGzfHzMGUDquuXjA3WP7dkoH9/Gub8AVjL1/HufiLhtZv6zEx2TJEmSJEmaj3meemWQMj1X6e4eB/pIkiRJQ2Z8LFg2eDMztMQM2OyfHRvlk1s9MTNviIjfA/epVd8DcKCPJEmSJEnqCfM89cqAZXqu0t0lDvSRloiIOBzYtyp+PTOf2cfu/FtErAHcDdgK2AJYD1gTuB64GvgT8LvMvKVvnZQ0r2qZxMNrVc/PzCM6dO3PAS+uikdn5pM7cV1pKXNPb/XCgO3nvUOjfE6b55/L9IE+dwd+vqgeSZIkLZJ5nqRuMs+TBot5nnplwDI9V+nuEgf6SEtARDwYeF5VvBV4yzzHHw88rCqekJm7z3Hs1sD59brMnPNfiIh4MvB4YBdge+Z/r7klIo4GDsnME+e59l+A7WpVr8nMj85z/ZZExLcpo0EnfTozX9445gJKyAFwZGbu24m2F6udfkXE7sBxM3zqXZn5tjbbbV7rmMx8fDvX0NLUzvsMsD/wLOA2wJMi4nGZeUx3eygNt+Xj46yxbLzf3dASt3x8MO6xiNgY2LhR/bc2L9M8frsZj5IkSeoR8zzzPPM8DRrzPKm7zPPUK4OS6VVcpbtLHOgjDbmIGAMOASYf1j+dmefPcUovvB54cBvHr0lZeu0ZEfFl4KWZef0sxx4GvKdWfj7w0YV0si4iNgWe0Kg+dLHXHTKviYhDMvOSfndkWHRzVswoycxLI+IjwNurqo9FxI8zc0U/+yUNsrGxGLQlWLUEjQ3OPbZho3xjZt7Q5jUua5Q3WHh3JEmSFsc8zzyvg8zz2mSe1xnmeVL7zPPUKwOU6YGrdHeNA32k4bcPcK/q41uBD/SxL7O5BTgPuAC4DlgFbER5M96qceyzgTtHxKNnCQeOBN7B1PvXThGxc2aescg+PhdYXiv/tgPXHDbrAAcAL+13RzSSPgq8hjILaFvgJZTQU9IMlo8Ha4y71K+6a4ZlfreNaDsouDwzm4Ns2nWbRvmmBVyjec56C+yLJElSJ5jnmed1inme+umjmOdJLTPPU68MytZdrtLdXQ70kYZYRCwHDq5VfTEzL+5Xf2puAX4K/AD4JfCbzFw504ERcQ/KMp/PqFXvCrwPeEXz+My8JCJ+yPTZOi8AFvsQ//xGedRm/0x6YUR8ODP/0u+OaLRk5lUR8VngdVXV2yLi8My8sZ/9kgbVeDgDSN03vvqgnqMXcJmDgAMX2ZXmQJ+bF3CN5kCf5jUlSZJ6wjzv38zzOsc8T31hnie1xzxPvTJDptcvGzbKrtLdQQ70kYbbM4FtauVBGS2/Z6tLdGbmH4G9I+IcYL/ap14aEe+cZdnZQ5keDDwrIl6bmbcspLMRcT/gnrWqW4AvL+RaS8Ay4F3A0/vdEY2kTwGvpSxdfjtg36pOUsMay8ZYc5kzgNRdawzuPZY9OkeSJKkbzPMK87zOMc9TP5nnSS0yz1OvzJDpuUr3EuRAH2m4va728amZeWa/OlK3wH149weexVTQMQY8CfjMDMceA1xKeXCAsmzwXsDXFtAulBlEdUdl5lULvNYw+gVl2eVNqvLTIuIBmXlaH/ukEZSZ50XET4BHV1WviYjPZOZEP/slDaLl4zHIgzC0RAzKMr9Ac/uHtRdwjeY5M20pIUmS1AvmeYV53uKY52kgmOdJrTPPU6/MkOm5SvcS5EAfaUhFxK5M7eUN8KV+9aUTMnNVRPwY+M9a9V1mOXZlRHwReGOt+vksIBiIiLUogUTdqC3zex1l1s+Ha3XvBR7en+5oxH2ZqWDgLsCjgGP71x1pMI251K96YGz1mT5PAs5t8zKXd6ArDvSRJElLgnmeeV4HmedpkJjnSS0wz1OvzJDpDQpX6e4gB/pIw2vf2scTwLf71I9Oas66mWv5tcOYHgw8MiLulJl/b7PNvZi+R+SFwM/avMZS8Cngv4GtqvIeEbFnZv6oF41HxDLgAcCdgc2ANSn/Y/AC4FeZuZBRvktCRNwN2BG4PWXv0SuAr2XmtXOccydgB8r3c31gHLiaspfpqZl5cbf7vQhHA7cCa1TlfTEYkFazfNmYM4DUdctXv8fOrbZp6LXmv3nrRMS6be7pvXmjfM3iuiRJkrQg+9Y+Ns8zz1ss87wBZZ5nnifNxDxPvTJDptcvTt7rIgf6SEMoIsaZvufyGbPsfT1stmqU/zHbgZn554j4JbBbVTUGPA94Z5ttNpf5PXwUlxXNzFsi4u3AF2vV742IYzOza6NlI2IH4G3A4ykPsDO5KSK+B+yfmX9p4ZpbA+fXqo7MzH3b6NPxwMMmy5kZjc83r193eEQcPsflt8nMC1rpa0S8EHgVsNMM1zkVOLN2nTWAxwBPpczcutMcfSAi/gJ8DDhs0EKXzLw2Ik6gzPwBeHJErJOZN/azX9KgWT5uMKDuWz4+GPdYZl4ZEVdTtneYtCVwVhuXaf6d+ddFd0ySJKkN5nnmeZ1mnjft/OMxz+sb8zypNeZ56pUZMj1X6V6CHOgjDacHMf1/dBzXr450SkRsAjy2UT3f13UoU8EAwL4R8a5WH2QjYkumL2c7ARzRyrlL1JeB1zP1IHov4Nl0YRnpKtz6IOXBd76/bNcG9gaeGhGvz8yPdbo/gyQi1gO+QglLWvVB4L/aOP6uwCHASyLiKZl5Xhvn9sJxTAUDawGPAP63f92RBs/4GC71q64bkHE+k86i/A086S60N9DnzjNcT5IkqZfM8wrzvM4yzxsA5nmAeZ40L/M89coMmZ6rdC9BDvSRhtOejfIv+tKLDomI9YGvM33J3dMz88R5Tv0m8HGmlgTeFngocEKLTe/L9IfSn2XmhS2eu+Rk5kREvAU4plb9joj4Rmbe2ql2ImJt4Cim9m2etIIyq+Ui4BbgdpTlf9epPr8M+GhEbJSZB3aqPwMmgCOZCgUS+B1lltCtwBbA/Wc4r/ln242U/4F5CWXP9jUo3897MX0J7XsBx0XEfTKzudR2PzV/9/fEYECaxhlA6oVBWdGn8gemD/TZlRb/bYiIdVl9Ru0fOtQvSZKkVpnnFeZ5HWSeNxDM8wrzPGke5nnqlUHJ9Fylu7sc6CMNpwc2yme2c3Jm7t6xnixANftjfeBulIfDl1EeWiZdCfzHfNfJzBsi4mvAi2vVL6CFYCAigun7okOZUTRfm1vPd0w/dKpfmfmDapnVyaVut6b8fDo56+YQpocC1wIHAodm5r/qB1YhwsspSzivVVXvHxGnZuYPO9indlwEbFN9/DTgA7XPvQH41jznzmUvph7cjwTe3tynPiI2pQQnTedSlmo+BvjNTEtWR8Ry4MnAe5la2WBLyp7uz5ynb21Z5PvMbymhyOT0hl0X3SFpiRmLYDycAaTuGhuse+xHwEtq5d3bOPchTH/2/U1m/rMTnZIkSWqDeR7meXXmeT1lntcC8zypu8zz1CsDlum5SneXONBHGk471z6+JjPne9joq4h4NfCRFg//LfCszDy7xeMPZXow8LSIeGXzAXMGuzP1cAdwFWVWiuBNwCm18tsi4rAWvqfzioinA8+vVV0I7F7f57ouM28CPhQRJwM/o4QDAXw8Iu7Wj/3XM3MlcAFARFzR+PQVs30tLZoMBfbLzPfM0n6zTYD3A6+a7/uRmSuAb0bET4GfA/euPvX0iNhvUJb8zczrI+J8pv6Au2dErNWJ/ccjYnNgszZP23ax7UqdtmwsWO5Sv+qyZYN1jx0L3MTUvty7RsT2Lf7NuG+j/N1OdkySJKlF5nlTzPM6zzxvDuZ53WeeJ83PPE+9MmCZnqt0d4kDfaQhExG3AzaoVS2VpWlPpCzb+912HvYy89SI+CNwj6pqHcr+z1+Y59QXNMpfysyZZlWMnOp7+h3gKVXVpsAbgbcv5rrVrKv9a1UrgSe28iCdmSdFxP6UB2AoI36fDHxnMX0aUD+bLRSYTWb+rc3jr46IFwG/rqrGgGcB72rnOl12IVPBwLLq4z914LovBw7owHWkvlo+FgOzBKuWrkEKnzLzxoj4FvDcWvWbmP4/HFYTEXelzLCdtBL4Sud7KEmSNDvzvOnM8zrPPK/vzPMK8zxpDuZ56pVByvRwle6u8d1EGj5bN8oDPfunDbsBrwKesIBzD2uU5/sfPusz9dA72zVG3X6UB/dJr6lCqcXYA9ixVv5yZv6ujfMPAeozQJ64yP4Mqvf2opHMPIPpweKDZju2T5rvbVv3oxPSoIoIxnz56vKrZPoD5UBgRa28b0TM+vdARKwFHA6sUas+NDPP7U73JEmSZrV1o2yeZ57XDeZ5/WOeV5jnSXMwz/PVq9eAZXqTq3RP2jUitm/x3H0bZVfprnFFH2n4bN4oX92XXrTnMKYvo7sGsDFlubXHAo8HxoGHAg+NiG8Dz62WeW3F/1AeppZX5QdVy8D+eZbjn0mZKTTpjMz8bYttjYTM/HNEHMbUKNt1KbN3Xr6Iyz6qUf56m326MSJOo9wnUEbyLjX/oizB2xHVrKt1KUsIrznDIZcDW1Uf79Cpdjuk+d7WfO+TRtqysWD5+EA9sGkJGrBlfsnM8yLiY8Dra9XfiojXAp/LzFsnKyNiB8qM8HrwfSVwUE86K0mSNJ153urM8zrMPK9vzPOmmOdJczDPU68MUqbnKt3d40Afafis0yi3+vDcN5l5HXDdDJ86BfhcROwIfJmpfRafCqwfEXu2suxvZl4eEd+rzpv0fODNs5zSXOb30PnaGFEHAc9h6p57cUR8JDP/usDr7dYoXxURW7d5jfp9tHVEjPVjX+8u+u1ivp6IWAN4NGWG232B7Zk5EJjJRgttt0tubJTX7dB1PwV8s81ztgWO7lD7UkdMzs6QumlA77E3U7Z4+H9VeTnwCeDtEfF/lJD9zpR/B+tfwK3AXpl5SQ/7KkmSNMk8b/Xrm+d1h3le75nnTTHPk+ZgnqdeGcD77EDKoO3JAd77RsR3M/N7Mx3sKt2tcaCPNHyav7crZzxqiGTmHyJiD+BUyl7NUGaL/BfwsRYvcyjTg4H/iIi3Zuaq+kHV7O5dalU3AV9dUMeXuMz8RzVr/i1V1TLKns/PWOAl79Qon7LQvlXGgA2BqxZ5nUFy2UJPjIgnAR8BtlngJTZYaNtd0nxvWz7jUW3KzMto8/s8YMtcSkA1A2iAZmZoaRqk2T+TMnNVRDyDslrP3rVPbQ7sOctplwHPy8xfdLt/kiRJszDPm5l5XoeZ5/WFed4U8zxpDuZ56pVBy/Rcpbs7HOgjDZ/mjJ+1+9KLDsvMqyLidUwfZf+GiPh4ZmYLlziWsgfwFlX59pT/2XNM47jm7J9vZ+Y1C+jyqHgfZbnfTary0yLifpn56wVca5P5D2nbeiytYOBfCzkpIl5NCQUWY7D+8lv9ve2GvvRCGlBlqd+xfndDS9yghQKTMvN64JnVsr+vAx44y6FXUbYWOCAzL+9V/yRJkmZgnjcz87zuMM/rLfO8KeZ50hzM89QrA5rpuUp3hznQRxo+zSVzO7X85SD4AeXrW78q3xHYEfj9fCdm5kREHAG8rVb9AmrBQEQsY/oekOAyv3PKzGsj4t3Ah6qqoIQFj1jA5daY/5C2DeRfK70UEbsw9fOZdAFlr9KTgPOASymh4i31oC0ijgce1pOOtq/53jbTcuHSyBqP8pK6adDvscz8FmX2zzaUEOAOlH8/LgUuBH5VnxEkSZLUR+Z5MzDP6w7zvMFnnieNJvM89cog3meu0t15DvSRhs/fG+Xb96UXXZCZKyPiXOA+teq70EIwUDkMeCtTD4tPiIhNM/OKqvw44La1488DTlhEl0fFIcB/A1tW5YdHxGMy89g2r3MF5X/AAdwMrNPi7K5eG+93B9p0AGXZ40mfA16Rma0sA77+/If0zR0a5eZ7nzTSlo2POQNIXbdsSO6xzDwfOL/f/ZAkSZqDed7szPO6wzxvsJnnSSPIPE+9MqiZnqt0d5YDfaThcwGQTD38bjH7oUNpRaO8ZqsnZub5EXEc8PCqajnwHOCjVbm5zO9hA/pgOlAy85aI2B84olb93oj4cZuX+idTD3trUYKGCxffw9U0H4jb/bduo051pNsiYl2mz8Y6j9ZDARjsYPGOjbL/A1eqWRbu6a3uWxbeY5IkSR1yAeZ5MzLP6w7zvMFlnieNLvM89cqgZ3qu0t0ZDvSRhkxm3hwRfwa2r6q2jIh1MvPGfvarg5pBxz/bPP9QpoIBgOcDH42IzYHH1upXMf1BV3P7H8ro2ntW5XsDzwL+0cY1TmL67K5HA5/vROcamkvCbtjqiRGxJrBtG231O1jaiulLKP+o1VAgIu4M3K4rvVqkiAjgbrWqy9x/VZpuLIKxAX9g0/DzHpMkSeoM87x5med1h3nezMzzusA8T5qfeZ56ZVjuM1fpXhwH+kjD6XSmgoExyr7Xp/WvO50REfdg9eU9/9rmZb4DXM3ULI6dImJnYA+mv+cdm5kXL6ijI6jaM30/4H9r1e8AXtbGZY4FXlErv4juBAP/ouxfvXZVvnsb5z6CMjupVbc0yi3PWOuQDRvla9s4d9/OdaPj7gzcplYe+vc3qdOWjQfLB3GzZS0py7zHJEmSOsk8b3bmeV1gnjcr87zuMM+T5mGep14x0xsNDvSRhtMJwHNr5QewNP5wPrBR/r/MvKidC1QzpL7C9AfQFwC7Nw49tO3ejbjM/H5EnAg8tKq6M/DSNi7xQ+BcpmbYPCAiXpCZh3Wwm2RmRsSZwK5V1TYRcY/M/ONc50XEGGVP+HZc0yj3euncqxvl7Wc8qiEitgJe1fnudMwDGuXj+9EJaZCNBYwPycwMDS9Xk5YkSeoo87xZmOd1j3nejK5plM3zOsM8T5qHeZ56xUxvNDjQRxpOP2iU9wA+2Y+ONEXEC4ATM/OcNs4J4GDgaY1PLfRrOpTVZ5rUl0O9nOkzWbomIg4EDqhVnZCZu/ei7S55E3ByrbxXqydm5spqb/Av16o/HRHXZOZ32ulERDwSOC8zz5vlkJ8xFQwAvLOFvr4feFA7/QDOapQfzeoBVzedC1zP1GyZx0fEjpn5h9lOiIhNKTPlNuhB/xZqj0b5mL70Qhpgy8ecAaTuc994SZKkjjLPm5t5XveY501nntcd5nnSPMzz1CtmeqNhrN8dkNS+am/bU2tVe0TEoAzceyJwVkR8NyKeGREbz3ZgRCyPiCcAvwTe1vj0iSxwz+3M/A3wm1rVGo1D/iczVyzk2qMuM08BvruI878C1Gf8rAF8OyK+XC3JPKOIGI+I+0TEARHxJ+AnwJZzNHUYMFErPzkiDouIjZoHRsQOEXE0Zc9yWH1Wz6wy80KgHk7sWn0te0bE3SJi68aro7+nmXkrcFStajlwbETs2Ty2+h4+lbJU+H0p+5Ff2cn+dNAjax//OTPP7ltPpAE1NhaM+/LV5dfYmKGAJElSp5jnzc08r3vM86Yzz+sa8zxpHuZ5vnr1MtMbDYPyICGpfV8Edqk+3ogyYv4n/evONMuAJ1cvIuJvlL25r6HstbweZe/uHZnad7nudOBJmZmL6MOhzD6DqKNLy46g/SgB0PgCz38p5Z6tz8jZB9gnIi4Hfkt5YJ0A1qfcKzvQxl7bmXl+RHwIeEOt+vnAsyLiZOASYF3gbkxfHvfdwIOBh7Xx9XwE+ETza5nl2G2AC9q4disOpPyuTc4CugPww4i4kBKQ3QhsCtyfqb3uoXytu9He19p1EXFfyvdp0pH96os0yMYIxvCBTd3lPSZJktRx5nlzM8/rHvO86czzOsg8T2qNeZ56xftsNDjQRxpeXwM+yNSD9dMZnGCgaUvmnq0xaRXwceDtmXnDItv8MuX703yYPGW+vZ07rNl+cw/moZOZZ0fE4ZQllBdy/opqJsobgIOY/j3ajOmzP2azApjvHnkbcBemBxBrsfoyspPel5lvjYjjW2i/7hDgHrS3v3nHZOa5EfE04FtMhQMAW1WvmXwgM9+2gK+1F55R+3glJQSV1DAWMO7anOoyJ/9IkiR1nHne3MzzusQ8bzXmeZ1lnie1wDxPvWKmNxp8O5GGVGZexfSR8XtHxG1mO76H3gK8FTiestdwKy4E3gfcPTNf24FQgMy8hrJvcVOvZ/8094j+SI/b75YDKLO5FiSL91NmeryXcg/M51+U/exfAdw+M0+fp41bKfvE/xdw6WyHAScAj8rMN7fY/WY7mZkvo8zI+xhlz/PLgJsXcr0F9uFY4H7A0ZSvaSYrgWOBR2TmG3vVt3ZUSyH/R63qm5l5cb/6Iw2yCF++evOSJElS55jnzc08r+vM86baMc/rEPM8qXX9znh8jdZLS58r+kjD7cPASyiD9tanLC/6uU42kJkXQOtrvGXmWcBZwLsjYoyylOq2wBZVH9ekzNy4DrgI+E1m/rOTfa715dnAs7tx7VZExDpMLccM8LPMPLFf/ZmUmcfTxs90lmv8A1inA325lBImvSUitqHsNb0ZZUnaCUoY8A/gbOCvmbmqzetPAJ+MiE9RHpx3oix7exNwMXB6tS93/ZzdF/i1nAac1uY5F7DIn0XtWn+m7F1+W8oSvltSZgheTlna+JTMvKJxzu5tXP8I4IhO9HUOTwJuXyt/qMvtSUNrPIJxn9jUZd5jkiRJXWGeN3dfzPNmYJ5nnlc7Z/c2rn8E5nnSwDDPU694n40GB/pIQywz/xoRXwaeW1W9OiI+v8i9sDumeiibDApG0W7AGrXy/v3qyDDIzPOB87t07QnKQ3tbD+7DqAravt3vfizQ62of/29mntG3nkgDbixg3Oc1dZnL/EqSJHWeed7AM89rg3leZ5jnSaPBPE+9YqY3GhzoIw2//YG9KQ+gO1D2L55piVv13sNrHx+bmSf1rSfSgIuIhwO7VsUJYL8+dkcaeGMRjDkzQ13mPSZJktQ15nmDyzxPapF5ntQe8zz1ivfZaHCgjzTkMvOCiPgoMLlH7wERcVQ140H9VQ8GnP0jze3A2seHZuYf+tURaRg4A0i94OwfSZKk7jDPG2jmeVLrDqx9bJ4nzcM8T71ipjcaHOgjLQ0HA8+k7OG7E/A84PC+9mjERcT6lP2pAY6p9nuWNIOI2At4SFW8krLPu6Q5jAeM+8SmLjN8kiRJ6irzvAFjnie1zjxPap95nnrFTG80ONBHWgIy84aI2Ad4VFW1vJ/9EWTmdfgeK7VqPeCg6uNfZeaV/eyMNAwiykvqJu8xSZKk7jHPGzzmeVJbzPOkNpnnqVe8z0aDf7RKS0Rm/gr4Vb/7IUntyswv9rsP0rAZi2DcJzZ1mft5S5IkdZd5nqRhZZ4ntc88T71ipjcaHOgjSZIkDZmxcK9ldZ/3mCRJkiRJUmeY56lXvM9GgwN9JEmSpCEzFu61rO4zFJAkSZIkSeoM8zz1ipneaHCgjyRJkjRkxiMY94lNXeZy0pIkSZIkSZ1hnqdeMdMbDQ70kSRJkoZMVC+pm7zHJEmSJEmSOsM8T73ifTYaHOgjSZLUhufdfBJ3v/H8fnejY/508yV8ot+dUNvGxpwBpO4b8x6TJEmSJC0BT7npNO5+w8X97kbH/Ommi3lXvzuhtpnnqVfM9EaDA30kSZKkIROZRGa/u6ElzntMkiRJkiSpM8zz1CveZ6PBgT6SJEnSkImJVcTEyn53Q0tcTKzqdxckSZIkSZKWBPM89YqZ3mhwoI8kSZI0bHIV+MCmbkvvMUmSJEmSpI4wz1OvmOmNBAf6SJIkScMmE3Ki373QUucyv5IkSZIkSZ1hnqdeMdMbCQ70kSRJkoZMTKx0qV91nfeYJEmSJElSZ5jnqVe8z0aDA30kSZKkYZOrwAc2dZvL/EqSJEmSJHWGeZ56xUxvJDjQR5IkSRo2ExPlJXWT95gkSZIkSVJnmOepV7zPRoIDfSRJkqRhM7HKJVjVfRPO/pEkSZIkSeoI8zz1ipneSHCgjyRJkjRsMstL6ibvMUmSJEmSpM4wz1OveJ+NBAf6SJIkSUMm0hlA6r5wP29JkiRJkqSOMM9Tr5jpjQYH+kiSJEnDZmJleUnd5D0mSZIkSZLUGeZ56hXvs5HgQB9JkiRp2GRCTvS7F1rqXOZXkiRJkiSpM8zz1CtmeiPBgT6SJEnSkImJlcQqZ2aou1xOWpIkSZIkqTPM89QrZnqjwYE+kiRJ0rBJnJmh7vMWkyRJkiRJ6gzzPPWKt9lIcKCP1KaIOBzYtyp+PTOf2cfuLFpEbAHcA9ga2LCqvhq4GDgtMy/vUrvLgPtWbW8GrAFcX7X7F+CPmbngIafV9Xesrr8xsD6wArgBuBS4APhLZv5r4V+FNDoi4njgYZPlzIwOXXd94BzK+wDAXpl5VCeuLS1lMbHSmRnqOu8xSZK0VJjndaxd8zxpiJjnSYPFPE+94n02GhzoI7UhIh4MPK8q3gq8ZZ7jj2fqD+kTMnP32uf2BQ7veCdX9/zMPKLW7gbAE4A9gT2AO8x1ckT8Fvg0cGRm3rzYzkTEdsAbgL0pD+uzuSkifgl8OjO/28b1dwNeBuwFrD3P4RMR8RfgZOBY4CeZedUc194dOK5WtUdmHt9q37ql3X5FxBFM3ceTVgE7ZubZbbbdvNbTM/Nb7VxDS09EbA2cX6ua9j5Ul5nXRcTBwCeqqo9GxI8z88bu9lIacrkKfGBTt+WqfvdAkiRp0czzzPMwz5vvWuZ5Ms+TesE8T71ipjcSHOgjtSgixoBDgMlR75/OzPPnOGXgRMQrgQ9RZtu06l7AZ4D/joj/yMxfL7DtZcD+lDCllfeetYFHAVcB8wYDEbEh8HHguW10awzYvno9H/gY8Oo2zl9KxoF3A0/pd0eGSbdmxYygzwCvAe4MbAW8mfJ+IWk2E6vKS+om7zFJkjTkzPPM85Y487wFMM/rGPM8qV3meeoV77OR4EAfqXX7UB6Socz++UAf+7JQWzNzKHAd8HvgMuAWyqyg+zN9Bs0OwAkRsWdm/qKdRiNibeBbwGMbn0rgj8DfgGuA21AeDLanjfeniNgI+Cll6eCmi4E/UQKGpCz7uxVwV6ZCHhV7RcQDM/OUfndEoyUzV0bE+4DPVlWvjYhPZuZl/eyXNMhy1Upy5Yp+d0NLXK5ylpkkSRp65nnmeUudeZ76wjxPap95nnrFTG80ONBHakFELAcOrlV9MTMvXuRlvwUc3+KxHwSeWit/DPhoi+deMUv9RcAXge8AZ2ZOX8ctItYFXgq8g6mAYB3g6Ii4W6t7fUdEAF9jeihwM/B+4HMzfR8jYh3K7J9nUkKY+RzG9FBgoqr7aGb+cZZ+rQfsRlkSeC9g0xbaGQXvozajReqhI4ADKMHkusDbgFf1s0PSIMsVK8gVrfwTKS1crjB8kiRJw8s8zzxvhJjnqV+OwDxPapl5nnrFTG80ONBHas0zgW1q5UMWe8HMvB64vpVjI6J53DWZecECm/49cBDw3cycmKN/NwAfiohfAD+jzM4B2IgSFry0xfZeDjyxVr4EeERmnjVH2zcCR1NCiDnfpyJiD+DJtaoJYO/59pXOzH8BPwR+GBH/BTyL9pZAXqoeGhGPy8xj+t0RjZbMvDUivsDUEr8vioiDM3O2cFMabZkwMes/41JnZPa7B5IkSYthnmeeNyrM89QX5nlSm8zz1CtmeiPBgT5Sa15X+/jUzDyzXx1ZpI8Db8hs/R0+M0+LiLcAn6hV7x0R/5WZcw4JjYgtgffWqm4GHjlXKDBD+/OtL/fsRvmw+UKBGdq4hTL7YFQdxfRw5T0R8cO5giOpSz4PvJWyx/zalGDx4DnPkEZUrlxBrnQGkLrL5aQlSdKQM88zz1vKjsI8T4PBPE9qkXmeesVMbzQ40EeaR0TsytRe3gBf6ldfFisz/7bAUw+j7GG+VlXeELgPcNo8572VqZlDAO/KzD8tsA+zeUij/NUOX38UfIWy3/u9q/I9gecCR/apPxpRmXlRRJwI7FFVvSQi3mlIJc0gJ5wBpO7z7VeSJA0p8zzAPG+pM8/TQDDPk9pgnqde8S14JDjQR5rfvrWPJ4Bv96kffZOZN0bEn5kekNxhrnOqPbP3qVXdQNmLvNOa/bioC20sdQm8GfhRre7giPhaNTuq6yJiY+BBwO0o+6vfDFxO2W9+xn3ZR0FELKd8X7akfG/GgD9m5vfnOWcH4G7A7YH1KN/Pq4HzgNOq5bQH1TeYCgbuCDwKOLZ/3ZEGlDOA1AvO/pEkScNr39rH5nlTzPOWDvO8AWWeZ54nzco8T71ipjcSHOgjzSEixoGn16rOyMxL+tWfPmsuuTvf/td7M332z7erfbQ7rfk+tnEX2ljyMvPYiPg58PCqakvgFcCHu9VmRATlPnk1cH/KQ+9Mx11MWWr645l5UwvXPRA4oFa1R2Ye32KftgbOr1UdmZn7znP9+ufmWkb7hMzcvZW+VkHJO4Bnsvo9/VtgWjAQEbcHngY8gRIkrDtHP1ZGxI+A92fmL+Y4rl++B3y6Vt4HgwFpNblyJbnCBzZ1V66cb8cFSZKkwWOeN4153hJmnvfvc7fGPK/fzPOkFpjnqVfM9EaDA32kuT0I2KhWPq5fHemn6gHuzo3q+QKSPRrln3SuR9NcRnmInfQk4JQutbXUvYmyfHNU5f0i4tDMvLbTDUXEnYFvUZaMns8dKXvDvzQiHr/UZwRFxIOBr1O+7lb9mTLTpxXLgMcDj4+IjwBvzMyB+asvM/8REX8B7lpVPTYixlzuV2rIVTCxqt+90FKX3mOSJGkomedhnjdCzPMGgHmeeZ7UEvM89YqZ3khwoI80tz0b5UEcLd8Lj2B6QHIrZRbCXB7QKJ8MEBFrA3tRZjbcg7JU7y3AFcBvKAHCV9uYLXQy04OB10bEaZn53RbPVyUzfx0R32Jq1tsmwBspe7N3TEQ8ADiGsqRv3ZWUe+AKYE1gO2DH2ue3Bn4VEbtn5pmd7NMAuTPwAaZm/dwAnA5cSplRt90s5zVnT/0TOAu4CriREhrcBdgeGK8d9xrKbL5XdqDvnXQiU8HApsDOlO+DpEquXEm6BKu6zNk/kiRpSJnnFeZ5I8A8byCY5xXmedI8zPPUK2Z6o8GBPtLcHtgon9nOyc1lPYfYaxrln2XmdbMdHBEbUh5CJt0KnBcRDwMOB7ZpnLIWsAGwLWW50ndHxMGZ+fEW+vY/lOViJ60BfCcijgeOBH6UmZe2cJ15VcvFxnzH9VqH+/VWSnAz+e/DqyPik51a4joibgccxfRQ4FTg7cBPMzMbx9+F8qD85KpqA+AbEbFzl5aObsVHgSOqj78G7FL7XPPerru5xWuvR9l/ez/g8Oa+6hExUxsTlD3Zvwn8cLafV7Uk8CuB1zO1XPcrIuL7mfmjmc5ZiMy8gMXdk2c2yrvSoWAgIjYHNmvztG070bbUUTnhDCB1n5MvJUnScDLPK8zzMM/rxMXN81q6tnmeeZ40P/M89YqZ3khwoI80t51rH1+TmRf1rSd9EhFPBR7bqP7gPKfdrlH+B/AU4BvMsm9zwybAxyLi/sDz51qGNDOPiYhjgcc0PrV79SIizqcsYXt69d/Tmg9bKjLzrxHxBeClVdU6wIHAf3aoiUOB2zfK/5k58zqCmXkOsFdEfAx4VVW9HSWsOrhDfWpLZl4DXAMQETc3PnfBIi+/HmXWzsMy8w+ztH/+DNU7tdJ2FRi8NSKOA37I1N8Bb6YEC4Pid41yc0bhYrycWfZkl4aJM4DUC87+kSRJQ8o8zzxvpJjnzc88ryfM86R5mOepV8z0RoMDfaRZVDMVNqhVXdivvvRLNdPg843qb2bmz+c5dcNG+TbAl5gKBS4EDgF+SVnedWNgN+AVlOVcJz2HsmTp6+dpb2/K0rEPnuXz21SvyZlCt0TEycBXgW9UD3qachDwXGDdqvyCiPhwZv55MReNiPsxPWQ6GXhJi3s1v5YS9OxUlV8ZEe9bogHPq2cLBWbTbiCRmT+NiM8wtcTvwyLijpl5cTvX6aLm++1dZzxKGmWrVsDKW/vdCy11qwyfJEnScDHPM88bYeZ5/WWeZ54nzc88T71ipjcSHOgjzW7rRnmkZv9ExPrA/zJ9L+9LKKPn57Nho1xf1vWbwPMy86bGMadExCeBLzK1pzTA6yLi6MycdT/1zLw2InanBAhvbPR5JmsyNUPo/RHxHuBDc800GiWZeWlEfAR4W1W1DHgXZRnmxXhVo7xfi6EAmbmqmgV0aFW1GWX51+MX2adB83fgyz1q69tM38v7QZTfz0HwD8ryxZNh4tb964o0mHJiFbnKpX7VXely0pIkafhs3Sib55nnjQTzvL4yzyvM86R5mOepV8z0RoMDfaTZbd4oX92XXvRBRKwBfAe4R636VuAZmXlFC5eYbTnf04F9ZnsAz8ybI2IfykPA/WufehurL+XbPHcl8N6IOIQSLDyTMqto7Xn6ugHwXuD/RcRTMvOqeY4fFe+nLPc7Geo8NSJ2ycxTF3HNR9Y+vhQ4oc3zj2uUH8LSCwa+12pY0oqIWEaZgbceMN74dDbKO3Sq3cXKzJURcT2wflW1aUREc8/3BfoU7Qcg2wJHd6BtqXNWrgSX+lW3ucyvJEkaPuZ55nmjzDyvP8zzMM+TWmKep14x0xsJDvSRZrdOo9ycsbIkRcQ4ZQncR9SqVwLPzMxftniZ62epf/18s2yqB4LXAvUZP4+OiM0z87L5Gs7MfwGHAYdVAcf9KCHDfaqP7w7EDKc+DPh2RDzKmUDl+xgR7wI+Uqt+L7DHQq4XEdsyfS/vc4CtImb6UcxqjUZ524X0ZcD9ZjEnV0uUP50SpN0T2LKN0+ebOddrNzIVDATlPfmGxV60eh+Z972krs37VOqJXLWSCYMBdVmuGvk/iSRJ0vAxz5tinjdizPP6xjxvinmeNAfzPPWKmd5ocKCPNLvm78eSf1eMiDHgcOApteoJytK8323jUjMFAxdm5omtnJyZv4yI84A716ofRpuj9jPzVuCk6gVARGwKPAn4L+BejVN2B14EfKaddpawTwH/zdQyq7tHxGMz8wcLuNadGuXdgPMX0Tcoe8EvNW09sE6KiHWAAyk/r2aA0qoNFnhetzTfc5f3pRfSgMpVE+Sqjk0YlGbkPSZJkoaQeV5hnje6zPN6zzxvinmeNAfzPPWK99locKCPNLvmjJ/5lowdalGGuH8GeG6tOoEXZeZX2rzcNTPUndLmNU5lejDQkWVIq6WKD42Iwyh7gL+/ccjrMBgASrASEW8H/qdW/Z6I+NEClqPdpINdm7ReF67Zb/9q94SIuA3wA8rSx4sx2xLd/dJ8z1307B9pKZlYuYqJFUv+/1mozyZWup+3JEkaOuZ55nkjzTyvL8zzppjnSXMwz1OvmOmNBgf6SLO7rlFety+96J1PAC9u1L08Mw9fwLUuBG4B1qzVXdLmNf7RKHf0wbLaG/gDEbEF8Krap+4SEdtk5mJnpywVX6YEKJOzpXYCns30sKAVC52VMhfXXy3ex/RQIIGfAt8HzgAuAq4EbsnMf68LGhFbs/hZWN1Uf8+9ud53SZATzgBS9+WE95gkSRo65nnmeTLPGwbmedIIMs9Tr5jpjQYH+kiz+3ujfPsZj1oCIuLDwCsa1a/OzAXNhMnMVRHxZ8pD5KRb2rxM8/i1FtKXFnyI6cEAwPYM9gNTz2RmRsRbKDNMJr0jIr6Rme38TK9olD+Xmf+5+B523Hi/O9COiLg98NJa1c3AkzLzxy2cvv78h/RHRGzE9N/55vuxNPImVqxk1a3mZeouZ5lJkqQhZJ5nnjfyzPMGm3meNLrM89QrZnqjwYE+0uwuoIykn5xlsEX/utI9EfE+4DWN6jdk5scWeenfMT0Y2LDN85vHX7mYzswmM/8WEVcxfX/ojbrR1rDKzB9GxHHAHlXVVsDLgI+2cZl/Nsp37UDXZtP8C6adf+uG7Wf/eKYv0fv+FkMBgDt0oT+dcsdG2aBOanCpX/WCy/zOLCKOAJ63iEsclJkHdqY3kiSp4QLM8xbDPG+JMM8baOZ50ogyz1OvmOmNBgf6SLPIzJurWSzbV1VbRsQ6mXljP/vVSRHxDuCNjeq3ZuYHO3D5HwDPqZXv0eb5OzbKFy2uO3Nq/ot3bRfbGlZvpuyzPumt1b7orfoj5fu6QVXeNSLWy8y297BuQXOZ7g3bOLfd+zTbPL7TtmuUv9/GuQ/qZEc6bIdG+cx+dEIaZLnKpX7Vfd5jkiRp2JjnLZp53tJinjcz87zuMM+T5mGep17xPhsNDvSR5nY6U8HAGOVh9bT+dadzImJ/4G2N6oMy890dauL7TN/X+/4RsXFmXtVC3zYCHtCo/kWH+tVsazNg00b1xd1oa5hl5mkR8W3gqVXVpqweKs11/qqI+BnwlKpqTeC5wKc62tHiskb57m2c+7g225q23HFErNnmEsiLtWGj3FKoFRHjTA/uBs1OjfKSeN+VOmli5SpWOQNIXebsH0mSNKTM8xbOPG8JMc+blXled5jnSfMwz1OvmOmNBgf6SHM7gfLwMukBLIE/UCPiDcBBjer3dHILgcz8V0R8C3h2VbUm8Erg4BZOfyXT9/O9EPjDTAdGxH0y8zeL6OpLmFrOGcre079fxPWWsv2AJzH1b8draC+w+QRTwQDAARHx3cy8pEP9m/R/jfITaOG+i4h7ML1/rbimUb49ZZnwXrm6Ud4e+EsL570S2Kbz3emYejA4AZzYr45Ig8oZQOoF77GWPYT2Zqtf06V+SJKkwjxvgczzliTzvNVd0yib53WGeZ40D/M89Yr32WhwoI80tx80ynsAn+xHRzolIv4LeH+j+kOZuV8Xmns78HRgjaq8X0T8JDNPnqN/u7L6zKT3ZOZsS6p+NyIuBN4F/GSO42Zq6/9Vfaz7emZ2bKhrRFxA2QN70vMz84hOXb+XMvMvEXEo8J9V1TrAY9o4//iI+AnwqKpqc+AHEfGEzGz5f45FxHrAEzLzK7Mc8lfg78CdqvL9IuLJmXnUHNe8LfBNYLzVflTOapQfDXyuzWssxm8b5ddHxDFz3cPVff++7nZr4SJiOfDgWtXpmXl5v/ojDSr39FYvOPunZRdl5gX97oQkSfo387zFMc8zz6ufb57XeeZ50ogyz1OvmOmNBgf6SHPIzEsi4lRgl6pqj4hYlplD+S9xRLwA+Fij+jvAJyNi6zYvd01mXjPXAZl5fkS8n6kH/TWBH0fEG4EvZOaKWt+WAS8EPshUkABlxtXh8/TlodXrbxHxJcoyw/8325KrEXFPygyIF1GWcJ50JXDgPG2NuoMos+LWWeD5z6P8TLeoyvcGfhcR7wUOy8wrZjqpCgP2oMxAejpwFTBjMJCZGRFfYPosty9FxIsz86uN645TZv18ENiSMqNmoza+nuOYfs98ICI2pMxYuQKov1fcnJmXtnHtVvwQ+BewXlV+CCUse0Vm/r1+YERsArwBeB3l3//Lgc063J9O2BVYt1Y+qk/9kAZarljJxK1D+eeIhkgaPkmSpCFknjcn87zRZJ43nXle55nnSS0wz1OvmOmNBgf6SPP7IlPBwEaUh5Of9K87i/IfTF/WFspDUbvLm0J56DqwheP2B+5GeZgDuA1lH+d3R8QplAe8jYEHsvr+xBcDT83MW1vs05aU5Wj3A26NiD8C/6zaWFa1cw/KcqxN1wFPmu3BVEUVln2U8j1e6PmPp8yuu0NVvRFlRsp7I+Is4DzK3tRrUu6JbYGtmX7vzrc3/IeBfZlaznZd4CsR8QHg18ANlH3J789UEHA9JSz6dhtfz4kR8WvgflXV+sw+u+YEYPdWr91i+1dHxDsbbT4BeGxEnEH5Xi6jzIa6H1MznK6nLHP93U72p0OeVvt4AvhSvzoiDbKJTCYmXIJV3TXR+sRqSZKkQWOeNzPzvBFknrfa12Oe13nmeVILzPPUK2Z6q4uIIyiDlxfqoE5umdsJDvSR5vc1yuyAtavy0xneYKDnqtkYz6U8yP1n7VMbAnvOceppwF6Z+Y95mjib6UvpTloDuE+L3TwNeHFm/q7F49uxVqPc3IN5GL2P8rPcZCEnZ+ZvI+I+wP9QlsadFMDdq9d85vw+Zub1EfFk4FjgdrVP3bF6NV0B7AW0vORwzd7AMZT9tHsuM98fEXcBXlyrHqfsi/2AGU65khIG/q0H3WtLRIwBT61V/bidZaClUTKxYiUTt66Y/0BpEVxOWpIkDTHzvEUwzzPPazLP6yzzPGk0meepV8z0RsPY/IdIoy0zrwKOrFXtHRG36Vd/hlFm3pKZLwUeSQlV5toc8g+UmRsPaiEUIDP3pMz8eSXwLWDecyo3U2Y/PAV4YDdCgYi4M3DbWtVfKcsQD7XMvI6yh/pirnFZZj6GskTzUZQZOfM5H/gC8P+YmnEzVxu/q447kulL7tZdB3wWuGdm/rKFPszUznmUJYufA3yDss/3tXO02XGZ+ZKq/b/OcdjlwCeBe2TmiT3pWPsey9TMMICP9Ksj0qDLiQlfvnrykiRJGkbmeYtnnvdv5nlT1zDP6yDzPGn09Dvj8TVaLy19kS7dJM0rIrajzDSZHBz3n5n5uT52aahFxGaUpX1vT1lu9V+UJXlP6sRo/4i4HXBXyjKvG1GWF761aucK4E/An7u9N3tEvAj4fK3quZnpsqUzqPZ0vx9wF8rMovWAGykP2OcBZy1mP+yIWJ8SQmxNWY73csoMmBMz86ZFdX6AREQA96R8LzejhHCXAhcCJ3f7nl+siPhf4PFV8feZuVM/+zMpIu5BCS0B+PUn9+PuW860Yvhw+tPfLuF+r3x3vWrHzPxjv/qjmTXvw2Oe8Si223j9PvZIo+CvV13H474xbeK77w/MuNTvNpl5QX96I0mSZmOe11nmeWoyz+sM87zuaOYoZ3z+Hdx965kWhhpOf7rgYnZ+8dvrVT6vDyDzPPWLmd7qZsjzHkJ7qwJek5nXdLJPi+XWXVILMvOvEfFl4LlV1asj4vPpSLkFyczLgf/t4vUvpTwM9XuWw8NrH58NfKVfHRl01QPrKdWrG9e/jiUw+2o+1XvS76rXUImI7SkzgCYd2KeuSENh1cqVrHIJVnXZqpXeYy16a0TsAGwLbAzcRNnm4hzgF8D3M/M3feyfJEkjyTyvs8zz1GSe1xnmedLoMM9Tr5jpteSiYZ+450AfqXX7U/buXQPYgbL/73f62iMNuj1qHx+Uma6VJ81uP6ZmWZ6amb6/SnPIVUmu8p8VdVeu8v+BtehFjfIawAaU2eiPAg6OiJ8Db8zMM3rdOUmSRpx5ntplnie1zjxPaoN5nnrFTG80ONBHalFmXhARHwXeWFUdEBFH+bCnmUTE3YHbVcU/UvZ6ljSDiLgb8KyqmMDr+9gdaShMrFjFqltX9bsbWuImVqx2j21bVpVvy+WZeVlnejTUHg6cFBGvzcxD+t0ZSZJGhXme2mGeJ7XOPE9qn3meemWGTE9LkAN9pPYcDDwT2BLYibKX3+F97ZEGVX32z4EGSNKc3s/U3yRHZuYv+9kZaRisWjnBqhX+06LuWrVytXvs6AVc5iCW7vLt5wA/AM4A/gxcCwSwGXB/4CnAg2rHrwF8MiJWZuZne9xXSZJGmXmeWmWeJ7XOPE9qk3meemWGTE9LkAN9pDZk5g0RsQ9lCX6A5f3sjwZXNVPb2drSPCJifeD/gN9UVf7eSK2YcKlf9cCEy/zO4ljgM5l5yiyfPws4EfhQRDwGOBK4be3zh0TE6Zn5f13upyRJwjxPrTPPk1pjnictkHmeesVMbyQ40EdqU2b+CvhVv/shSUtBZl5HWe1BUhtWrZhg1a0GA+quQZtlFhGfBF7Rg6YOyswDZ/tkZn611Qtl5rERsStwCrB5VT0OvBd49GI6KUmSWmeeJ0mdY54nLYx5nnpl0DI9dYcDfSRJkqQhk6smnAGkrpvhHnsScG6bl7m8M70ZXpl5fkS8FPhOrfpREXGXzDynX/2SJEmSJEm9Y56nXvE+a8lbI2IHYFtgY+Am4CrgHOAXwPcz8zdznN93DvSRJEmShszEynRmhrpuYuVqy/yem5l/7Edfhl1mfjcizga2r1XvCXyyT12SJEmSJEk9ZJ6nXpkh09PqXtQorwFsAGxD2fL34Ij4OfDGzDyj151rhQN9JEmSpCGzasUqVt26qt/d0BK3asXA3WNHAxf1oJ1fdum6xzJ9oM9OXWpHkiRJkiQNGPM89coMmd62EdHuZS7PzMs606Oh9XDgpIh4bWYe0u/ONDnQR5IkSRoyOZHkKmdmqLtyYrDuscz8CfCTfvdjES5olDfrRyckSZIkSVLvmeepV2bI9I5ewGUOAg5cdGcGzznAD4AzgD8D1wJByenuDzwFeFDt+DWAT0bEysz8bI/7OicH+kiSJLXhYxP3Y9OJu/S7Gx1zxcQ5/e6CFmBixcQgrraiJWbC5aQ77aZGee2+9EKSJEmSRsxnVu7EZiu263c3OubylX/tdxe0AOZ56hUzvRkdC3wmM0+Z5fNnAScCH4qIxwBHAretff6QiDg9M/+vy/1smQN9JEmSpCEzMZFMOANIXTYxYCv6LAGbNspX9KUXkiRJkiSp58zz1CuDlOlFxCeBV/SgqYMy88DZPpmZX231Qpl5bETsCpwCbF5VjwPvBR69mE52kgN9JEmSpCGTKyaYGHcGkLornf3Tabs0yv/oSy8kSZIkSVLPmeepV2bI9J4EnNvmZS7vTG+GU2aeHxEvBb5Tq35URNwlMwdimwQH+kiSJElDZtXKVS71q65btdJ7rFMiYnPgEY3q4/vQFUmSJEmS1AfmeeqVGTK9czPzj/3oyzDLzO9GxNnA9rXqPYFP9qlL0zjQR5IkSRoyE6tc6lfd5z3WUe8D1qmVr8OBPpIkSZIkjQzzPPXKgN1nRwMX9aCdX3bpuscyfaDPTl1qp20O9JEkSZKGTK6YYCKcAaTucuuu1UXES4CvZ+a1LR4fwEHAvo1PfSAzb+xw9yRJkiRJ0oAyz1OvDFKml5k/AX7S734swgWN8mb96MRMHOgjSZIkDZlVKyZYxeA8sGlpWjVAocAA2Q94X0R8FfgmcFJm3tI8qBrgszuwf/Xfut8DH+5uNyVJkiRJ0iAxz1OvmOl11E2N8tp96cUMHOgjSZIkDZnMZCIHaglWLUHpPTabDYGXVa+VEXEWZQnia4EANgXuC2w0w7nnA3u6mo8kSZIkSaPFPE+9YqbXUZs2ylf0pRczcKCPJEmSNGRWZHLrhA9s6q4VhgKtWAbcs3rN5+vAyzLz6u52SZIkSZIkDRrzPPWKmV5H7dIo/6MvvZiBA30kSZKkIbMqYZUPbOqyVd5iMzkYeBywK3D7Fo6/Fjga+GRmnt7NjkmSJEmSpMFlnqdeMdPrjIjYHHhEo/r4PnRlRg70kSRJkobMiglnAKn7VniPrSYzDwMOg38/7O8AbAFsBqwDJHANcBXwe+CsdL1kSZIkSZJGnnmeesVMr2PeR8n7Jl2HA30kSZIkLZRL/aoXXOZ3bpl5GXBZv/shSZIkSZIGn3meesVMb7qIeAnw9cy8tsXjAzgI2LfxqQ9k5o0d7t6COdBHkiRJGjIT6RKs6j6zJ0mSJEmSpM4wz1OvmOmtZj/gfRHxVeCbwEmZeUvzoGqAz+7A/tV/634PfLi73WyPA30kSZKkIbNiIrk1fGJTd7nMryRJkiRJUmeY56lXzPRmtCHwsuq1MiLOAi4CrgUC2BS4L7DRDOeeD+w5SKv5gAN9NCIi4nCmltf6emY+s8vtbQ7sDGxBeeNYE7iB8mZxIXAecEHmwtZOi4hxYDtgm6qNDYC1gBuBa4A/A2dm5g2L+ToabW4M3K9qc0PKm961lDfB0zPz0k61JWnwRMQFwFZV8cLM3LpD190aOJvyPjkBPCAzz+jEtaWlbJUzgNQD3mOSJKmfzPMWzzxPGm3medJgMc9Tr3ifzWsZcM/qNZ+vAy/LzKu726X2OdBHS15EPBh4XlW8FXjLPMcfDzysKp6Qmbu32M4GwAur191bOOWaiDgDOA740Xx/CEfEHsBTgV2Be1D+iJ7Lqog4FvhsZn6vhf7M1GYAewOvAHab59jfAJ8BDsvMlQtpr8U+7QscPsOnXpyZX1jktQ7JzFe2cfw2mXlBO212Q7v9atzjk64Fts3MK9tsu3mt+2fmr9u5hpaeiNid8t42aY/MPH6mYzPzgoj4JPA6YAz4VETsmpkT3e6nNMzc01u94H7ekiSpX8zzzPPauJZ5nnmeOsA8T+o+8zz1ipneag4GHkf5m/z2LRx/LXA08MnMPL2bHVsMB/poSYuIMeAQymwVgE9n5vldaOcJwGdp7c1h0obAI6rXOyNio8y8Zo7jXwg8u43rjwOPBR5bBQTPy8x/tnpyRNwO+AqwR4un3IfyPXhJRDwzM89po6+dcGBEfDkzb+pxu0vFBsBbgdf2uyPDpFuzYkbQu4AXA+sDD6DM2Dysnx2SBt2KieRWfGBTd7nMryRJ6gfzPPM8tcw8bwHM8zrGPE9qk3meesVMb7rMPIzq36hqFc8dKCtsbgasAyRlhc2rgN8DZy10Fc9ecqCPlrp9gHtVH98KfKDTDVSzLw6ljFyvuxn4E/A3yjK/t6Hs77cj5SFssVYCF1CWDb6W8vVtANyNsgxw3WOAEyNi98y8ZL4LR8RmlNH72zc+tQL4DWW54gnKm+DOlGWGJ+0MHBcRu2XmhW1+TYtxR+C/gff2sM2l5uUR8bEe/9wkMvPqiDiEqRmaB0bEVzLz5n72SxpkEwmrBv9ZQ0POTECSJPWJeV5hnqdWmOepL8zzpPaZ56lXzPRml5mXAZf1ux+d4EAfLVkRsZyyFNekL2bmxR1u477AF5geCpwHHAB8JzNvnOGcAO5KWSJsL+ZZQrdmFXAS8H3gF8CvZ/ujOSK2AV4PvIyp2U93rfr6uBba+iirhwKfAQ6o3gDrbW0IvAl4I1Pfhy0os4H2bKGtTnpTRHx2EPdJHBJrUn5nnjffgVIXfBh4DSVovBPw8qpO0gxWZroEq7pupfeYJEnqMfM88zy1zTxP/WSeJ7XBPE+9YqY3Ghzoo6XsmcA2tfIhXWjjI5QldSf9CnhsZl432wnVUl9/rl4fjogdgFdRHvzn8qLMXNFKp6rljF8REWcCn6t96rERsUtmnjrbuRGxNWXmVN17MnO/Wdq6BnhLRFwMfKL2qcfM11YXbAjsB7yhh20uNc+JiA9m5u/73RGNlsy8IiK+AfxHVfXaiPhEq+970qhxT2/1guGTJEnqA/M88zy1zzxPfWGeJ7XHPE+9YqY3GppLk0pLyetqH5+amWd28uIRsQXw0FrVSuDZc4UCM8nMszLzZZn5r3mOa/uP48z8PGW2UN1e85z2hEb5n8BBLTR3CPC7ea7VDT+gLHM86ZURcacetLuUHFX7eAyXS1b/fKb28R2BZ/WrI9KgW5W+fPXmJUmS1GPmeeZ5as1RtY/N89RP5nlSi/qd8fgarZeWPlf00ZIUEbsytZc3wJe60MxDGuWTB3Qv5B8wva93mef4OzfKP87MW+ZrJDMzIv4X2KlW3dxbvBvOpzxMvKoqr0VZrvb5PWh7qfgIsAtw+6r82Ih4WGae0Mc+aQRl5skRcR5T70MvA77Yxy5JA+uKiRWswCc2dde1rOx3FyRJ0ggxz5vGPE/zMc/TQDDPk1pnnqdeMdMbDQ700VK1b+3jCeDbXWjjDo3yRV1ooxOuapTXm+f4dRvldr6uvzfKG7Vx7mK8gxIETH5t/1EtV/vHHrU/7G6kzPKqz754H/DAXnUgIm5PCSc2BzYBrgcuA07PzPN61Y9BExFrA7tRZsPcFlgFnJaZJ85xzlrA3YG7Ub6ft6H8jK+mLDF+RmbeOtv5A+CbwJuqjx8YEXfLzD/3s0PSIDomL+t3FyRJkqRO27f2sXnedOZ5ajLPG1DmeeZ50mzM8yR1klt3acmJiHHg6bWqMzLzki401Rwot3EX2uiErRrlf8xz/KWN8lpttNU8thlKdEVmXgF8oFY1BrynF20vIYcCf6mVd4mIp3SzwYhYHhEvjYjfUe7L7wKfBd4NfBz4GnBuRPwlIl4SES0NTo2IIyIia6+t2+jT7o1zD5zr+kz//dqqcW7zdUSrfY2IO0XE/1DCkR8Dh1OWYP4A8NoZrnPniHhzRJwIXAucAXwF+CjwTuDD1TVOAq6NiC9HxE7N6wyI7zXK+/SlF5IkSZKknjHPW415nlphnod53oAwz5Mkqccc6KOl6EFMn3lyXJfaaQ693S0iNulSWwsSEWsAezeq5/t+NPcAv28bTe7cKJ/exrmL9WHK/uOTnhARu/Ww/aGWmSuBtzaq310FbR0XETsDZwOfBu45z+HbUQKD0yPijt3ozyCJiCcDvwOeQ5m9M9/xGwPnUsKwhwBrzHPKWpSH7f+LiDcsqrPdcTpwQ638+H51RJIkSZLUM+Z5FfM887xWmecNDvM88zxJknrNrbu0FO3ZKDcfdDvl5EZ5XeArEfHMzLy6S222rAoFDgO2rVX/HfjGPKf+jLIc6N2q8kMiYqfM/N087d0ReGqtagXw1bY6vQiZeUNEHAwcUqt+H/DgXvVh2GXmtyLiVMqSu1DugRcAn+9kOxHxeODrwDqNT10C/JYyc2xdynK19X3h7w2cGhEPzMxBXVp7sXYBjgTWrMrXUB6UrwA2pHxPmmYatPt3yu/xtcDNwAbA9pT3g6iOGQfeHxGZmR/sTPcXLzNXRMTJwCOrqvtExOaZrmuqkXcusGO/O6GRd26/OyBJkpYs8zzM8yrmeW0wzxsI5nnmedJszPM0KMz0liAH+mgpau5DfGY7J2fm7i0ed3ZE/Bq4X6360cA5EXEYZdnS06qZFV0XEWOUPa23BfYAXsb0UOAm4NmZefNc18nMiYh4AfBzysPJGPCtiHh0Zl4wS9u3BY5i+oPeOzNzvmWFO+1zwGuAu1TlB0XEkzLz6E5cPDOPAI7oxLU6qcP9ejPTZ4kdGBFfysybOnHxiLg7ZQnf+r3yI+CAzDxthuPvA3yMMrMFyt7WX42I3TNzVSf6tACvBw6sPv5l1SeAiyn7b8/m+hau/XnK791FVTvfqn+dERGsvnw3lCDuKOA7wI8zc8ZltiPizsAbgP9kKiB4T0Qcm5m/b6F/LcnM42vXX4gzmQoGgvK+3lwCWBop1b/ff+x3PyRJkqQuMc8zzzPPWzjzvPmZ583DPE/qPPM8Sd3kQB8tRfXlZq/p8kyB11IeoOu/SxtT/qB/PXBTRJxBGcF/OnBSZl7YiYar5UC/2+Lh5wPPycyTWjk4M0+qZml8BdiMMgvjdxFxKOUh7kIggS2ARwAvAerLHH8WeEeLfeuYzFwZEW+jPHhOendEfL+PD5FDJTOPj4gfMTWT7g7Aq+nAHulVePV1yuyeSQdm5kFz9Oc3EfHw6rzJPcZ3A54NfHGxfVqIag/5KwAioh78rZwtPGvDesB5wMNmeu/KzASabVwHbN1KEJeZ5wEvq2Z6HV5VLwNeB+y78G53XHPG4QPoUDAQEZtT3tfase38h0iSJEmSFsE8b3XmeeZ5LTHPm595Xk+Y50mS1EMzLQ8oDa2IuB1lSctJHXkIn01m/oLyx/QtsxyyNuUh5jWUh+wLIuLCiDgkInaZ5ZxOOpOyVOv2rYYCkzLzp8AOwDspwcJ6lAfEHwFnUfZj/inwFqZCgbOBZ2TmS6sHmH74BvDrWvnuDNYDzzB4EzBRL1f7Ri/WU5i+TOU35goFJlWz6J4H1Jd6fX0H+jOo9m0n0MzMW9udbVfNGvt+reoZEbG8nWt0WfO9+64dvPbLgT+0+erILEJJkiRJ0urM81ZzJuZ55nntM8/rL/M88zxJknrKgT5aarZulLu+729mfpmyD+/PWjxlS8ofpqdExM8j4l5d61zZA/kVwLOq2RftmpzZNFvwUXcS8CrgWwtop2OqQOLNjeoDI2KtfvRnGFX7t3+lVrUBsF8HLv2qejOs/nOaq0/XU2aWTbpnRGzdgT4Nml9VgWMvfLv28dqU94tB0Xzv3rofnZAkSZIk9cTWjbJ5nnkemOe1xTyvr8zzCvM8SZJ6yIE+Wmo2b5Sv7kWjmfnbzHwkZX/vj1FmzLRiD0pA8JwFNPtjYJvaazvKcpj7Al9m6mF+Z8p+z8dHxKatXjwiXgycC7wN2L6FUx5U9el3EfHgVtvphsz8WdWXSVsw/aFU83s7cGut/MqI2HKhF4uIdSn7Mk86PTNb/T2ZdFyj/JAZjxpuR3XyYhGxPCI2jogtI2Lr+ouyD3jdDp1se5Ga793N93ZJkiRJ0tJhnmeeZ57XGeZ5/XFUJy9mnidJklqxbP5DpKGyTqN8Uy8bz8wzgDOAV0fEFsCuwH2r1y5MX4Z40lrAERFxWWb+eIbPz9bWjay+ty+UvcOPjIj9gCOB3av6hwA/j4gHVufOKiLeSlnit+7XwKeAXwD/oCwFezvKw95LKCEHlKVcT4iIF2bmka1+PV3wZuBRQEyWI+LzmdmTsGjYZeYFEfFp4L+rqjWBg1n4sskPBOpLyZ63gBk8zcGpS3Gf5d8s5uSI2AbYG3g45Xfx9m2cvtFi2u6w5nvUujMetTCfAr7Z5jnb4nK/kiRJktQt5nnmeZPM8xbBPK9vzPMK8zxJknrIgT5aapr39Mq+9AKo9uT9ZvWiWmr3AcBzKfts15eeHQc+HxHbZeatzWstsP2/RcT/oyxB/KCq+p7Auyh7jM8oIh4OvKNRfSBw8Az7dF9Qvb4WES8BPkN5EB8HDo2IczLzV4v7ShYmM38TEV8DnlVVbUTZf/yN/ejPkHon8Hxg/ar83Ij4YGb+YQHXulOj/MzqtRid2Gd80Fw2/yGri4hNgPdTgpuFrtY3U3DZL8337o7tN56Zl9Hm9zki5j9IkiRJkrRQ5nlT7Zvnmectlnle75nnFeZ5kiT1kFt3aalpzvhZuy+9mEFmTmTmKZn5CuAewO8bh2wJPL3Dbd4MvKxR/Z8RMdcDwLuYmjUDcGRmHjRDKNBs63PVuZPGKcse99PbmL5c7X9VM7PUgsy8AvhArWoMeM8CL7fJ4nu0mvW6cM1++1e7J0TE7Skz817A4v5dH6S/CZrv3Tf0pReSJEmSpF4wz5vepnmeed6Cmef1hXleYZ4nSVIPDdIfAVInXNcod3J5yI7JzPOAx7L6H7uP7kJbvwP+VKtaG3joTMdGxB2Zvu8ywEFtNPdepoczO0fETm2c31HV9/mztaq1aO/rEXwEuLRWfnxELGQv7TU61J86p2UUX2D6ftwrge8CL6X8Pt+JEqIsz8yYfDG1PPcgar53N9/bJUmSJElLh3ne6m2Z500xz2ufed7gM8+TJEmL4kAfLTV/b5Tb2c+2p6qlgL/eqN6+S839uVG+yyzH3btRPi8zz2+1kcy8ATilUb1Lq+d3yTuYPqvieRFx9351ZthUP9ODG9XvW8ClrmiU96s/pC7wte+Cvqi5jXfhml0TEQ+ghIyTrgB2ycynZOZnM/PUzLwoM6/PzObyueszuO7QKDff2yVJkiRJS4d53szM86aY57XBPG+wmedJkqROcKCPlpoLgPqStIO+rOuZjfJGXWpnRaO85izHbdgoXzrTQfNonrPpAq7RMZl5OfChWtU48O4+dWdYfR74a628a0Q8uc1r/LNRvuuiejS35gPwsjbO7dbvYLc8qVF+Y2b+X4vnNh++B8kdG+WWA0pJkiRJ0tC5APO8mZjnTTHPa5953uAyz5MkSYvmQB8tKdUe1vXZLltGxDr96k8LVjXK13apnWZA0nxIm3RNo7yQpZJv0yhfv4BrdNqHgMtq5SdFxIP61ZlhU80ceWuj+t0R0c5smZOZHto9KiK6tVRvc1nYDds49x5ttjXnXvc9sF2j/P02zh3k34EdGuUz+9EJSZIkSVL3mefNyjzPPG/BzPPmZJ7XHeZ5kiT1kAN9tBSdXvt4DNixXx1pQXPJ2Ys73UBEbAjcv1H91xkOBfhHo3y3BQQr922UFzKLqKMy83rKkr91C1mudmRl5jeZ/ru1A/D8Ns6/HPhNreqOwP/rTO9Wc1mj3M7Szo+d/5Bpbql9PNvMum7asFFuKVyMiA2AJ3e6Mx20U6N8Wl96IUmSJEnqFfO8GvM887xOMM+blXled5jnSZLUQw700VJ0QqP8gG40EhHbVA/dCz1/Q+AZjeqfL6ZPs3grsLxWvpwyG2MmvwOurpXXAp7bakMR8XhWX6Lzl62e32WfBc6tlXcDntinvgyrNzXKBwJrt3H+JxvlD0ZEc8ZYJzSXun1CKydFxGNo//3imtrHm0bE8tkO7JKrG+XtWzzvQGC9znalo+o/h2twBpAkSZIkLXXmedOZ5xXmeYtnnre6a2ofm+d1jnmeJEk95EAfLUU/aJT36FI7DwMuiIiDI2Lzdk6sZtV8FdisVn0L8J1Zjn9aRNyn3Q5GxEuA1zWqP52ZzSWGAajqv9Wofm9EzDuLKiK2BD7TqP5VZl7San+7KTNXAG9rVO/V7XYjIhuv3bvdZrdk5nHAsbWqO9Leg/QXgbNr5R2A70ZEW/toR8RmEfGUOQ45GbixVt4rIu43zzW3A45spx+Vs2ofL6N77zez+W2j/Ob5ToiIFwL/3Z3uLF5E3IHpe74fO9t7liRJkiQ3VAHCAAEAAElEQVRpyTDPmzrPPK9inrd45nkzMs/rMPM8SZJ6z4E+WnKqB9FTa1V7RMSyLjW3AfB24OKI+H5E7BMRzf2z/y0i1o2I51D+mN+z8en3ZuZFs5y6G3BGRPw4Il4YEbefo42xiHh4RHyfMuulvm/yX4D3zPM1HQzcVCtvCJwUEa+cadnfiFgjIp4HnMHqs3/eMk9bvfZ1Vp8dova8mQXuY1093D2N6XtuPxL4XUS8LCJmnZESERtHxN4R8VXg78Cr5mjnX5Sf9aRx4JiIePQM110jIl4MnALcltVn1MznuEb58Ih4eUTsHBF3joita69N27x2K74F1B+anxURn4+ITZoHRsQWEfF54AuU94XLu9CfTnhko3xUPzohSZIkSeod8zzzvDmY5y2eed505nmdZ54nSVKPdethSeq3LwK7VB9vRBmV/5MutrcMeFz1IiIupiwreyVwA2VJza0oewuvMcP53wDeOU8bATyqehERl1JmU1xdtbEu5cHmnsy8hOe5wCMz8+a5GsnMiyLi2cA3KQ9UVNf7BPD+iDiDsvf3BHA74H7ATMu1vjUzfzHP19RTmZkR8Sa6ey8saZl5ZvVwvs8Cz/9jRDyV8kC7QVW9BfAp4BMR8Xvgb5TwYB1KMHXX6ph2vJ0yw2vDqrw5cGxEnENZ0voWyu/LLpTfHSj7z7+J9mYCfRN4V61/dwAOmeXYI4F927j2vDLzLxHxOeBlteoXAc+NiNMoIcpawJ2BezEVFF4KvAH4n072p0OeVvv4WgwGJEmSJGlUmOetzjzPPG/RzPNWY57XeeZ5kiT1mAN9tFR9DfggU/sNP53OPwxeQvmjdYMZPndHVp8NM5ObKDNy3r2ApSxvV71a8T/AazPzilYOzszvRsSTgEMpD0+T1qbMRprLDcCbM7O5f/NAyMyfRsRPWX2WQcdFxFozVLc7w2QQvY3y8DZTyDWv6mdwP8py1/UleMeBe1ev+cz5fczMi6sA4iimB2V3qV5N51OCvdvO8Lm52rkpIvaq2mnld74bXg1sSRVMVtYEHjLL8RcAj2f6UuMDISI2AOoztb46X5gpSZIkSVoyzPOmM8+rmOd1hHneVDvmeR1knidJUn+4dZeWpMy8iumj+PeOiJlmqSymjWMpf1g/GvgwZXnhFS2e/hfKkrrbZ+Y7WggFPgK8FvgRcE2LbfyTMhNh58z8j1ZDgUmZeQxlxtJ+lNlDrbT3QeAegxoK1LyJBS5X26YHNcrHZWZzD+ahk5nns/r+7e1e4xzKfuBPAH5KmZEzn7MoM9EeAsy1p/dkGz+v2jia2X/elwMfAO6dmWfNcsx87fya8rvyUkpAcA5lBlNP9qHOzFuBJ1ICgn/McejfgXcD98rMP/agawvxXEqoAeVn9rE+9kWSJEmS1EPmeYB53lzM8xbBPG+1dszzOsc8T5KkPojMXvxtLPVeRGxHWQp3ckDbf2bm57rc5pqU2QXbAbenzDxYDlxPeVC4EPhtZl65iDaCsmzndsCdKDOQ1gZurNq4tGrjbwv/SmZsdwtgZ8rXtSFlydBrKQ9Wv6ke9FQTEe8E3lqrekhm/rJf/Rlk1WypXShLYm9CWX73BspMn3OAsxb5e7Mp8DDKkrzrUIKs84FfZObKxfV+cETEMuC+lFlUmwA3U94TzgF+nQP+j3611POOVfF/M/OJ/ezPpIi4B/CHyfJzP/4dNt1ypolkw+mKv53D/7xqWta24wCHR5IkSZKWMPM887x+M89rnXleZ5jndUczz3vxp49ms62262OPOuvyC//K51/2pHqVeZ4kjRi37tKSlZl/jYgvU0aUA7w6Ij7fzT+MM/MW4I/Vq1ttJGVGTiuzcjrZ7kXARb1scwl4eO3jnxgKzK5azvWELl7/CuDb3br+oKhCjtOq11CJiEczFQokcFAfuyNJkiRJ6gPzvI63a57XPvO8FpnndYZ5niRJWgi37tJStz9wa/XxDsBefeyLRki1tPT9a1X796sv0pB4W+3jb2bmGX3riSRJkiSpn8zz1BfmeVLbzPMkSeoTB/poScvMC4CP1qoOiAjve/XCQ5laNe2HmXlKPzsjDbKIeARlr3YoyxPv18fuSJIkSZL6yDxPfWSeJ7XIPE+SpP7yAUmj4GBgcn/rnYDn9bEvGh171D4+oG+9kAZcFdZ+sFb13szs6VLmkiRJkqSBY56nfjDPk1pgnidJUv8tm/8Qabhl5g0RsQ/wqKpqeT/7o9GQmW8A3tDvfkhDYAvg6Oq1Cnh/f7sjSZIkSeo38zz1g3me1DLzPEmS+syBPhoJmfkr4Ff97ockabrM/BtwYL/7IUmSJEkaLOZ5kjSYzPMkSeo/t+6SJEmSJEmSJEmSJEmShoADfSRJkiRJkiRJkiRJkqQh4EAfSZIkSZIkSZIkSZIkaQg40EeSJEmSJEmSJEmSJEkaAg70kSRJkiRJkiRJkiRJkobAsn53QJIkaZicfdF1rLvq6n53o2NuuOS6fndBkiRJkiRJ6prf/f1abrPyyn53o2Ouv+TafndBktRnrugjSZIkSZIkSZIkSZIkDQEH+kiSJEmSJEmSJEmSJElDwIE+kiRJkiRJkiRJkiRJ0hBwoI8kSZIkSZIkSZIkSZI0BBzoI0mSJEmSJEmSJEmSJA0BB/pIkiRJkiRJkiRJkiRJQ8CBPpIkSZIkSZIkSZIkSdIQcKCPJEmSJEmSJEmSJEmSNAQc6CNJkiRJkiRJkiRJkiQNAQf6SJIkSZIkSZIkSZIkSUPAgT6SJEmSJEmSJEmSJEnSEHCgjyRJkiRJkiRJkiRJkjQEHOgjSZIkSZIkSZIkSZIkDYFl/e6ANIgi4nBg36r49cx8Zpfb2xzYGdgC2BBYE7gBuBa4EDgPuCAzc4HXHwe2A7ap2tgAWAu4EbgG+DNwZmbesJivo9HmxsD9qjY3BILy9VwEnJ6Zl3aqLUndFRFbA+fXqo7MzH07dO19gC9XxYuB7TPz+k5cW5IkSZI0OszzFs88T1o6zPMkSVraHOgjNUTEg4HnVcVbgbfMc/zxwMOq4gmZuXuL7WwAvLB63b2FU66JiDOA44AfZeYZ81x/D+CpwK7APShhw1xWRcSxwGcz83st9GemNgPYG3gFsNs8x/4G+AxwWGaubPH6RzD1s5nNCuAWSghxGXABcBZwGvDLzLyylbZaaP/CzNx6odfqpHb7FREzBUy/ysw5f2YtXOuGzLxNu9fQ0hMRBwIHTJYzM+Y4/KvAq4H7A3eszntDF7snSZIkSVpizPPM81ps3zxv9WuZ5wkwz5Mkadi4dZdUExFjwCGU2SoAn87M8+c4ZaHtPIHysPohWgsFoMyieQTwTuDXEbHhPMe/kPKAfl/mDwUAxoHHAkdHxI8i4rYt9guAiLgd8DPKH/mtPGDeB/gscEpE3KWdtuaxHLgN5QHjPsBewH7AUcA/I+JnEfGsiHCg43QPjogn9rsTwyQito6IrL2O6HefhlE1s/HNtapXR8Td+tUfSZIkSdJwMc8zzxth5nltMs/rDPM8SZL6zz+Mpen2Ae5VfXwr8IFONxAR+wKHsvpAu5uBPwF/oyzzextgU2BHytK8i7WSMhvmPMrsmFur696Nsgxw3WOAEyNi98y8ZL4LR8RmlJlJ2zc+tQL4DWW54gnKMsM7U5YZnrQzcFxE7JaZF7b5NbVrHHh49To4Il6VmT/scpvD5N0RcUxmrup3RzRaMvPnEXES8CDK3ybvBJ7e315JkiRJkoaEeV5hnjeazPPUF+Z5kiT1lwN9pEpELAcOrlV9MTMv7nAb9wW+wPRQ4DzK0pbfycwbZzgngLsCj6PMZml1OdZVwEnA94FfAL/OzJtn6dc2wOuBlzE1++muVV8f10JbH2X1UOAzwAGZeVmjrQ2BNwFvZOr7sAVlNtCeLbRV97Gq7boxSuCxIXBbyvKhu1CWPK5/3+8C/CAiPgi8caH7pS8x9wD+Azi83x3RSHoP8L/Vx0+NiJ3nW9JckiRJkjTazPPM89pseykyz1M/medJktQnDvSRpjwT2KZWPqQLbXyEMgtl0q+Ax2bmdbOdUD2w/rl6fTgidgBeRXnwn8uLMnNFK52qljN+RUScCXyu9qnHRsQumXnqbOdGxNaUmVN178nM/WZp6xrgLRFxMfCJ2qceM19bM7gmMy+Y55ivVf3cBnglZfnj+tLHrwfWqeoFB0XEV2cLkaQu+gFwPuV9OCgB4jP62iNJkiRJ0qAzzzPPk3me+sc8T5KkPmkuNSqNstfVPj41M8/s5MUjYgvgobWqlcCz5woFZpKZZ2XmyzLzX/Mc11Io0Djn85TZQnV7zXPaExrlfwIHtdDcIcDv5rlWx2Tm+Zn5OspMoHMan355RLygW20PuBuAn9bKdwL+q0990QjLzAng87Wqp1SBniRJkiRJszHPM88bReZ5GgjmeZIk9Y8DfSQgInZlai9vgC91oZmHNMon92AP64X4QaN8l3mOv3Oj/OPMvGW+RqqZTf/bqG7uLd5xmfkbSkBzaeNTH4yITbrd/oB6E1Bf6vgt1ZLMUq99ufbxOPCSfnVEkiRJkjTYzPOmMc8bPeZ5GhTmeZIk9YFbd0nFvrWPJ4Bvd6GNOzTKF3WhjU64qlFeb57j122U2/m6/t4ob9TGuQuWmZdExLOA4xptv4qyv/pIycz/i4ivU5a7hvK9eHP16omIuDtwT2AzYH3KfXgJ8MvMvLJX/Rg0EbE5ZU/62wObAtcDP8rMv8xxzsbA3SlB28bAWsB1wJXAmcBZg7qHfWb+LSJOpXzNAM+NiLdWs4MkSZIkSarbt/axed505nlLnHne4DLPM8+TJKkXHOijkRcR48DTa1VnZOYlXWiq+fu2cRfa6IStGuV/zHN8cybNWm201Ty2GUp0TWYeHxHHAXvUql8UEQcO6kNTl70NeCqwvCq/KiI+kZkXd6vBasbVG4DnAHec5bCJiDgJOCgzfzrLMc3rXsDUfXxhZm7dRp8OZHo4tEdmHj/H9eueFxHPm+Pyz8/MI1rpa0Q8BNifcn+ON67zGmBaMBARu1D2v34UsCNlT+zZXBkRXwA+mpnN399B8D2mgoE7Ag9jeognSZIkSRpx5nmrMc8zzwPzvEnmeb1nnidJUo+5dZcED2L6zJNu/QF6WaO826AtLRsRawB7N6rn+3409wC/bxtN7twon97GuZ3wsUb5DsD9etyHgZCZ5wKfq1WtTWt7sy9IRPwHcB5lmeHZQgEo/07tBvwkIv6nukeXtIg4GDgeeCSrhwIzHf8U4BTgtZRZVHOFAgCbUL7vf4iIRy2qs93RfM95fF96IUmSJEkaZOZ5FfM887xalXlen5jnmedJktRrDvSRYM9Gufmg2yknN8rrAl+JiJ4sbzuf6oHrMGDbWvXfgW/Mc+rPgD/Xyg+JiJ1aaO+OlBknk1YAX22ttx3zc8rSznUP7nEfBsnBlKVkJ+0bEdt3upHqwfdIypK+kxI4m7LP+1eAHwKXN059DvCDiFiyq9FFxKuBtzP17/OFwDGU342fA1fPcFrz3/JVlO/lD4GvA18DfsLqs/U2AY6JiF070fcOOh24qVZuvkdLkiRJkmSeh3lejXneFPO8HjPPA8zzJEnquSX7x5XUhgc2yme2c3Jm7t7icWdHxK+ZPsPk0cA5EXEY8F3gtMxc2U77CxURY5T9urelLCf6MqaHAjcBz87Mm+e6TmZORMQLKA8ta1IeUr4VEY/OzAtmafu2wFHAOrXqd2bmfMsKd1Rm/isi/gDUg4x7zXH8vkzf/30gdKpfmXlZRHyIqaVux4H3AHst9tqTqqVw316rmgAOAT6YmX9rHBvAkygztbasqh8BvAN4S6f6tAC7Uf793ILpQeK3gdfPcd4V81x3c+AD1ccnA6/JzFPrB0TEmpQH+qZrgC9RgpUTZ/u9rUKAdzG1xPVy4GsRsV1m3jpP/1qWmQcCBy7w3JUR8Uem3it3iIgNM/OaTvSt2id9szZP23b+QyRJkiRJPWSeZ55nnod5XhvM8+ZhnidJ0nBxoI80fbnZazLzoi629VrKA3T9d29jysPE64GbIuIMygj404GTMvPCTjQcEU+mhA+tOB94Tmae1MrBmXlSRDyeMnNjM2A74HcRcSjwI8oshqQ8SD0CeAnTH24+S3nY64ezmR4MbDnbgSPig5SQaPOq/OSI2DUzmzPY2hYRWwGfrlXdAjw5M3800/HV3upHVXt6/wq4S/WpN0TE5zLz/MX2aSEm3yNKbjHN9bOFYS1au/rv94GnzvSgnpm3AM0A7QTgjpl543wNZObJEfEI4FDg+VX1lsA+wBEL7Hc3/I6pYCCqj1va070FL2f6vu2SJEmSpOFjnrc687zRZZ43D/O8njDPkySph9y6SyMtIm4HbFCr6shD+Gwy8xeUmRq3zHLI2pTZBa+hPGRfEBEXRsQhEbFLN/tWORN4AbB9q6HApMz8KbAD8E5KsLAe8GpKMHAW5QH8p5SZG5OhwNnAMzLzpdVDYD80l05td2bAkpKZ11N+hnXv69Dl38DUwy+UGS4zhgKNPl1GeXCdNE75HVmKLgee185snMy8vJVQoHZ8Aq8ELqtVP7v1LvZE8734rn3phSRJkiRp4JjnreZMzPPM88zz+sk8rzDPkySphxzoo1G3daPczdk/AGTml4FdKHtht2JLyoj1UyLi5xEx61K0HXBv4BXAs6qlgNs1ObNptuCj7iTgVcC3FtBOJzWDgbVnPGq0fAY4r1Z+yP9n777DLKnq/I+/v84MOSdBFIYcxUwyAK4YEMwuioIYcdWfOSAmZE2AcV1c10RYFcQAYsAsoICIKCImQBgDGck5zPf3R1Xb1TW3u2+ue7vfr+e5z9Q5XXXO6XSn6/PUOaec4dW1iFiZInSacCnFzK+2ZOa5TF1W92m9jGeEfSYzrx90J2WQcGqlaqcuf+cHpf5evLiJQUiSJEmSRtLiWtk8zzzPPM88r0nmeQXzPEmShsituzTfrVcr128SByIzfws8ISIeAexPcZOzSRuX7kERELw8M7/YYbc/qPWxEFgT2BbYE3gOxZ7cj6BY8vOlEfGszJxtH2IAIuLlwMeAldscz67lmC6MiFdm5pltXtdv9ZuhpmYijYzMvCci3kkxC23CByPiu5m5tMtmH8PU0OVrXbT1U+Cx5fHGEbFRfR/wOeDkfjYWEStQzMZbiWLJ3KpbKserUizFPSpfz/p7cf29uhefAr7a4TWbAd/s4xgkSZIkSd0zzzPPM8+rMc9r1Mn9bMw8ryXzPEmSanzQR/PdSrXyHcPsPDPPA84DXh8RDwR2AR5evnZi6jLEE1YAjomIazLzBx30dTuwpMWHzgWOjYhDgGOB3cv6xwI/iYidZ1tGNCLewbLLw/6K4g/wn1HsQbwUWB/YmWJP7z3K87YHTo+Il2bmse1+Pn20Rq081J+BEXYCxdK8DyvL2wMH0P2+z4+pla+IiMUdtlFf/nZTRudGth/uo9jLumvlkuDPpXgv2Y7W7yHTWZPR+XrW33PaDRxnVS4dfc2sJ1a02L9dkiRJktQc8zzzvDVqZfO8gnne8JnnTTLPkyRpiHzQR/Nd/Xfg3kZGAWTmPyieSv8qQLns5o4UM4ReQhEITFgAfDYituhk799Z+v9bRDyFYgniXcvqBwPvZ4b9kyPi8cB/1qoPBQ5rsU/3kvJ1QkS8gmJJ2aD4fD4fEZc0MBNozVr52iH3P5IyMyPiYOD7ler3RsTxmdnOUs51D6qVP16+erFWj9ePmpu6/X2OiO2Bo4DH9dB/JyHCoNXfixc1MgpJkiRJ0igyz5vs3zyvYJ6HeV5DzPMmmedJkjREo7R/p9SE+myPkdnPOTOXZuYvMvPVFE/y/652ykYUT/r3s887gf+oVR8UETPdMLyfqUuIHpuZ720RCtT7+kx57YQFwCc6GW+fbFsr/7WBMYykcoZZde/5jYDXdNnc2r2PaBmrDqDNJt0y+ynLiojHAGfRWygAo/U3Qf29+LZGRiFJkiRJGkXmeVP7NM8zz/sX87yhM8+bZJ4nSdIQjdIfAVITbq6V+7acZD9l5qXAXiz7x/ETB9DXBcAfKlUrMs0NR0RsSLF0b9V7O+juQ0wNZx4RETt0cH1PImI1YJta9W+H1f+YeBtT9zk/ZJagaDrL9Wk8VfN+/dXyZ/hEpoYkNwH/CzyfYqnm+1O8ty3IzJh40dnv6rDV34vr79WSJEmSpPnLPG/ZvszzVGWeN8LM8yRJUj/4oI/mu7/Xyhs0Moo2lEsBf6VWvfWAuvtzrbz5NOc9tFa+NDMva7eTzLwN+EWteqd2r++Df2PZ98GfD7H/kVfuO//VStVawMFdNHVdrbxr9Sa1y9cx3X5eM1gwgDYH6ZVMfd86B9giM1+ZmSdk5vmZeU1m3p6ZS2vXrja8YXbsAbVy/b1akiRJkjR/mee1Zp4nwDxvDJjnSZKknvmgj+a7JUyd3fDAhsbRrvNr5fp+1P1yT628/DTnrVErX9VFX/Vr1umijW69rlb+B/CbIfY/Lt7B1J+J10VE/cZtNlfXylv2NqQZVfeDXtjhtYP6nRqUp1eOE9gvM9vdl77T7+EwbVgrtx04SpIkSZLmvCWY57Vinqcq87zRZZ4nSZJ65oM+mtfKPayrs102ioiVmhpPG+6rlW8aUD/1gKR+Uzfhxlq5m6WSV6mVb+2ijY5FxB7AbrXqz862F/l8lJmXAJ+tVK0IHNphM2fVyn1fprqiuizsGh1eu10H547Cz8oWleM/lsuCt2uXfg+mj+pLcJ/fxCAkSZIkSaPHPG9a5nn6F/O8aY3Cz4p5niRJ6pkP+khwbuX4fsD2TQ2kDdvWypf3u4OIWAN4VK364mlOv6JW3qqLYOXhtXI3s4g6EhEbAMfXqq8H/nvQfY+xw5i6p/xLImKrDq7/MVODradFxHp9GdmyrqkcrxwRG7VzUUSsxbJ71M/krlp5uplyg7RG5bjtoDAiHg+09XVpyA6V45uBPzU1EEmSJEnSSDLPqzDP0zTM85Zlnjc45nmSJA2RD/pIcHqtvOMgOomITcqb7m6vXwP491r1T3oZ0zTeASyqlK8Fzp7m3AuAGyrlFYD92+0oIvZm2SU9B7qndkQ8FDgDuH/tQ2/MzOsH2fc4y8yrgY9WqhYAH+zg+huAL1WqVgE+3J/RLePXtfI+bV73Foqf4XbdWCtv0OqkAav+/m0REbP+vx4Ri+jgezdsZXBXnYV4hjPzJEmSJEk15nlTmedpGeZ5Ld1YK5vn9YF5niRJw+eDPhJ8t1beY0D97AYsiYjDOp35UM6qOR5Yt1J9F/CNac5/TkQ8rNMBRsQrgDfVqv8nM+tLDANQ1n+tVv2hiJh1FlU5K+PTteozM/PKdsfbiYhYHBFHAr8ANq99+JOZeewA+tw9IrL66ncfQ3YkRVA04ZkdXn8oU2fN7B8Rh0fEgk4aiYhtI+JxM5zy41r5bRGx2ixtPgN4ayfjKJcKX1KpelQv4V+Xfls5Xgd42Uwnl1/r/2VAAWif1N+Dv9PIKCRJkiRJo8w8b/I687z+9mmeN9WhmOf1m3meJEnqmQ/6aN4rb0TPqVTtERELB9Td6sC7gMsj4tsRsV9E1PfP/peIWDkiXkjxx/+Tax/+UGb+Y5pLHwOcFxE/iIiXlk/UT9fH/SLi8RHxbYobhqh8+CJmnylwGHBHpbwGcFZEvKbVsr8RsVxEvAg4j2Vn/7x9lr7q1ihv+KuvTSPioRGxW0TsGxFHRsTPgL8Ab2bZ5ViPAF7XYb/zUmbeAryvh+svA15Rq34r8POI2Gem37vye/vqiPgJ8Hvg8TN09ROK7/eEBwE/aLU0cUSsHRGHA1+n+D/xhvo5s/hp5Xgl4Hvlz9325ay/6s9mff/6fvhKrfzfEfHaiFiufmJEPIria/Pisura+jkj4gmV46XAt5oaiCRJkiRpNJnnmedhntcW87yWzPP6zzxPkqQhG9TNjzRujgN2Ko/XpHgC/YcD7G8h8NTyRURcTnEj80+KfZNXBTam2MN7mT/wgROZ/QYtgD3LFxFxFcW+uDeUfaxMsdztg8v+6v4CPKGc5TCtzPxHRLwA+CrF8q+U7X0SOCIizqPY+3spsD7wSIplXuvekZk/m+Vzqnsd3d/UXwz8v8z8fpfXz1efBl4PbNLNxZl5XESsTxE4TTxsujNwCnB7RPwGuJoibFqVYlbLtkzdu3q2PjIiXsvUmSM7AX+IiF9T/GwvoNjT+hFM/tyeDpwJHNLBp/RfFMtbT/x/uhNwwjTnvhg4poO223Es8Fom98BeBHwCODQizqF4T1kd2B5YXLnudIpltd/R5/H0pAyHnl6p+lFmXt7UeCRJkiRJI808b1nmeWrFPG8q87w+Ms+TJKkZPugjFU6g2F94xbL8XPofDFwJ3ETxR3rdhiw7G6aVOyhuqD4w3fK7M1i/fLXj/yj2uL6unZMz86SIeDrweabulb0ixWykmdwGHJyZ/93m2HpxH8UN0eeAr2bmvQPur74/9I0D7m/gMvPuiHgX8MUe2jgiIi4Ajmbqz+RKwKPbbGbGmTqZ+d2IeBtweKX6fhTB1CNbXPJD4Nksu9T1jDLz/CiWyP4Une0H3heZeW9E7EMxs2ezyofWZNlZgxN+RPG5vnHAw+vGE4C1KuUvNDUQSZIkSdLIM8+byjyvP8zzWrdhntcn5nmSJKkf3LpLAjLzeoon6Sfs2+9lOcuZJusCTwQ+SrG88D1tXn4RxZK6W2fmf7YRCnyM4o/+79H+zejVwFHAIzLzgHZDgQmZ+R2KmRqHMHWZ1Zn6+zCwXZ9DgfuA2ymCmPOBkynClGcC62Xmv2Xm8UMIBQB2rZU/NoQ+h+HLFF/brmXm9yhmEb26bGu2/c7vAc6i2Bd8y8z8RBt9HEFxc/ybGU77E/Aq4MnlUsYdy8yjga2Bd1PcdP+DIvAayh7umfk34OEUs5Fun+HU3wAHAU/KzJuHMbYuVPck/zvFEsySJEmSJC3DPA8wzxsE87xpmOf1j3meJEnqVWQO5e8WaeRFxBYUNwkTD8AdlJmfGXCfywObA1sAG1AsbboIuBW4Gfgr8NvM/GcPfQSwadnHgyhmIK1IcQNxM3BV2cffuv9MWvb7QIplVDegWKY1KGZAXQv8JjMv6Wd/oygifs7kjJbrgU1G+IasURGxFsWSvxtQzACZ+D24hiIY+1NmznTTO1v7mwO7UMxQC4rlp/+QmTOFBmMnIlamCKS2Alaj+J2b+B0f6d+5cgnov1F87wHelJkfbXBI/xIR2wEXTpQf9dZjWHmDrla7Hkm3XXkZ5x5xYLVq+8z8fUPDkSRJkqS2meeZ5/WbeV77zPP6wzxvMOp53k6HHMcqcyjPu/XKyzjnAwdUq8zzJGmecesuqZSZF0fElyj25wV4fUR8Ngf4NFxm3gX8vnwNqo+kmJHTzqycfvb7D4qZEPNSeYO2Y6XqI4YC0ytn4X13gO1fAoz0jXE/ZOZtFMsW93up8mF4LZOhwFUU+8dLkiRJkjQt87y+92ueZ57XNvO8/jDPkyRJ3XDrLmmqdwN3l8fbUCwPK3XjsUze5FxHsQyrpBYiYg2KZZ8nHNbLjC9JkiRJ0rxinqd+Mc+T2mSeJ0lSs3zQR6rIzCXAxytV74kIf0/UjcdXjo/MzFsbG4k0+t5EsTQxwB+AzzU4FkmSJEnSGDHPUx+Z50ntM8+TJKlB3vBIyzqMYl9ZgB2AFzU4Fo2vPcp/rwGOanIg0iiLiA2BN1aqXp2Z9zQ1HkmSJEnSWDLPUz+Y50ltMM+TJKl5C5segDRqMvO2iNgP2LOsWjTT+VIrmfmopscgjYnNgCPL48sz87QGxyJJkiRJGkPmeeoH8zypbeZ5kiQ1zAd9pBYy80zgzKbHIUlzXWaeAZzR9DgkSZIkSePNPE+ShsM8T5Kk5rl1lyRJkiRJkiRJkiRJkjQGfNBHkiRJkiRJkiRJkiRJGgM+6CNJkiRJkiRJkiRJkiSNAR/0kSRJkiRJkiRJkiRJksbAwqYHIEmSNE5WWWkRq628XNPD6JtYaVHTQ5AkSZIkSZIGZq2VF7H6qss3PYy+We5m8zxJmu9c0UeSJEmSJEmSJEmSJEkaAz7oI0mSJEmSJEmSJEmSJI0BH/SRJEmSJEmSJEmSJEmSxoAP+kiSJEmSJEmSJEmSJEljwAd9JEmSJEmSJEmSJEmSpDHggz6SJEmSJEmSJEmSJEnSGPBBH0mSJEmSJEmSJEmSJGkM+KCPJEmSJEmSJEmSJEmSNAZ80EeSJEmSJEmSJEmSJEkaAz7oI0mSJEmSJEmSJEmSJI0BH/SRJEmSJEmSJEmSJEmSxoAP+kiSJEmSJEmSJEmSJEljwAd9JEmSJEmSJEmSJEmSpDGwsOkBSKMkIo4GDiyLX8nM5w2x7wC2ArYGNgRWBRYANwM3AZcDv83M64Y1JkmaEBFZKZ6embv3qd1dgTPL4m3A1pn5j360LUmSJEma+8zzJKk18zxJkuYuV/SRShHxaOBFZfFu4O2znH9aRGT5Oq3LPu8XEU+NiOOB64E/AicB/w18EHgf8F/AscCPgGsj4vKIOCYi9omI5dvs55jKWHt9LZmhn8V97Ccj4sBuvq7lWJ7Yor2fd9te2eah1fZ6aaufOh1XRCxp8bW5NCKW66LvelvrdPdZaC6JiANrPxeLpzs3M88Cvl4WVwY+NowxSpIkSZLGn3meeV4bbZrnzd6WeZ7M8yRJGjM+6CNR3KADRwFRVv1PZl424D6fAlwIfBt4HrBGm5c+gCLAOAW4PCLeERGrDWSQrd0xJn29pEXdoyNi6x7anMs2AV7Z9CDGTe3m97SmxzPG3g7cVx4/JyIe3+RgJEmSJEmjzzyvI+Z5c5N5XhfM8/rGPE+SpAb5oI9U2A94SHl8N3DkoDqKiEUR8Wngu8A2LU65GfglcCrwZeA7wLnA1S3OXZtiltBPBjPalr4++yl9cTvF16BjEbEW8IxpPtwqMFDhnRGxatOD0PyTmRcDJ1aqPtTUWCRJkiRJY8M8r33meXOXeZ4aYZ4nSVKzFjY9AKlpEbEIOKxSdVxmXj7Avr4NPLH2oduBTwFfA36VmffVry2vfzCwJ8UMoB0qH1phlq7fDBzaxZAfCXy1Uk7gCzOc/w+KmSTd+CLw6Er5q5l5c5dtvRCYbhnkAyLikMy8t8u257J1KX5W3tP0QDQvfQB4fnn8qIh4VmZ+o8kBSZIkSZJGk3nejMzz5hfzPDXJPE+SpIb4oI9ULLNbvZk9aoB9fZxlQ4FvAP+RmdfMdnFm/g74HfDRiHgq8G5gxzauuw64rtPBRsTBtaqfZualM/RzL7Cki342BHauVX++03YqXlo5Xgp8H3hKWb4/sDdwcg/tz2VvjIhPZWarGWfSwGTmhRFxBvC4supgivdHSZIkSZLqzPOmYZ43L5nnqRHmeZIkNcetuyR4U+X4nMw8fxCdRMR+wKtq1R8HntNOKFCXmd8BdgHeQbE8cV9FxIoUoUlVLzfrMzkQWFApX5yZP+umoYh4JFNnR/0YeH/tNJf7nerkyvEqFIGT1IRPV44fFRGPm/ZMSZIkSdJ8Zp7XgnnevHJy5dg8T00yz5MkqQE+6KN5LSJ2YXIvbyiWmx1EP8sDH6lV/wR4Y2Zmt+1m5tLM/ADT71/di+cAq1fKNzKAp/EjIoAX16r7NfsH4JjMPBO4uFK3V0Rs0EMfc817gDsq5ZdHxOZNDUbz2snAbZXyfzQ0DkmSJEnSiDLPm5F53vxhnqdRcTLmeZIkDZ1bd2m+O7ByvBT4+oD6eTGwfqV8F3BgL6FAVWb+rR/t1NRvsL+UmXcOoJ/dgM0q5XuBY7tpqJy19PxK1c3ASeXxMUzOBFpAsS/6h7rpZw66AvgExdKqAIuA97HsDLCBiYhNgYdT7Cu+JnATcBVwdmZeMaxxjJqIWB3YFXgAsB5wJ3B6Zv56hmtWBbYFtgTWAVYGbgGuBy4ELsjM+wY89K5k5h0R8W1g37LqGRGxembe1OS4JEmSJEkj5cDKsXneVOZ584d53ogyzzPPkyRpGHzQR/NWRCwAnlupOi8zrxxQd2+olb+emX8fUF89i4jNmNxXd8LnBtRdPYD4TmZe1WVb9VlLX8nMiZktxwH/yeRKZi/BYKDqQ8ArgLXK8r9HxJGZed6gOoyIlYHXUnwvpp1xFBHnAx8AvtZOmBYRp1EETgBkZnQwpgOBoytVL87MY2Zqv2K3iJhpfO/NzEPbGWtEbEcRZD0ZWL7WzieAKcFARGxPcTP9JIqAZQHTuyUivgh8ODMvneG8ppzCZDCwAvAspn5PJEmSJEnzlHne9Mzz5iXzPMzzRoR5niRJQ+bWXZrPdqWYaTDhp4PoJCI2pngSv2pQN9n98hKgejP160HsdV7Obnh2rbqvy/xOHGTmPyj2956whfsFTypnWHywUhXA4YPqLyKeBFxKccM/27LCDwVOBH5Q/szMaRHxSuBXwNNZNhRodf7Dgd8B7wQexcyhAMCqFEvoXhgRL+xttANRfy/eu5FRSJIkSZJGkXne9Mzz5hnzvNFhnmeeJ0nSsLmij+azJ9fKPxtQP/WZAvcAZw2or56VM6NeVKvu5WZ9Js8HVqyUrwRO7aahcg/q6o3+xZlZ/zofA+xZKb8EOKOb/uaoTwL/D9ioLP9bROyZmT/sZycR8XLgf1j2BnYJ8HuKZX5XAx4CPKjy8ScAP4+IXTPzln6OaVRExDOBTzEZzF0N/Aa4AVgb2KHFZfWHdhO4jGIf+5sp3nPWBLZj8nsLxe/e/0XEnZn5tX59Dr3KzCsj4hImA6M9I2LBqC5PLEmSJEkaKvO8Fszz5jXzvIaZ55nnSZLUBB/00Xy2c618ficXZ+bubZ66a618QWbe1UlfQ/ZkYMNK+Q7gywPqqz5j59jMvLfLtuqzllrtC34SxU3nxCyS50bEazPz5nY6KJdpPbTL8Q1Mv8aVmXdFxHuYuqzqhyLiR/3afz4iHs+yocCXgA9k5h9anL87RWCxfVm1PfAZpu7dPmzPo1iCFoob8AnnMPM+6De20faxFD/Hf6BYIvyH1a99Gdxt2OK6O4ATgG8CP87MW1s1Xi4J/G6mLnP+hYg4IzOvaWN8bSmXRz6mhybOZzIYWJUi1Ligp0FJkiRJkuYC87zWzPOmYZ7XO/O8WZnnFc7HPE+SpKHxQR/NZ4+oHN9YLgU7CA+olS8aUD/98pJa+euZeWO/O4mIBwOPrFV3NdOoxaylpRR7eE+RmXdExInAy8uqlShu5D7TTb9z1HHAm5i8EX84xdfo+F4bjohVKEKmiVAggZdl5hemuyYzT4uIXYAfALuU1c+LiP/JzEZmb1X3nI+Ysl34nZm5pMfmVwXOBfYsl1+u930f8Lda9UXAhpl5w2yNZ+aFFPu1Hwq8p9Lnqxit0OsC4DmV8o70KRiIiPWAdTu8bLN+9C1JkiRJ6pl5XmvmefObed4szPOGwjxPkqQhqi8PKM0LEbE+k7NAAP46wO7WqpVvHGBfPYmIdYF9atWDWua3Pvvn9My8pMu2nsLUAOYnmfn3ac49ulauj2Ney8ylwCG16vdFxKI+NP9K4P6V8pEzhQKVMd0K7AtUZ869uQ/jGUV3Afu1CgWmk5k3txMK1BzG1BvtF3R4/aDV35O37GPbrwIu7PD1zT72L0mSJEnqgnlea+Z5Ms9rnHlewTxPkqQh8kEfzVeLa+VBzf6BYh/eqrb/4I+I7SMi23wd04exHgBUbwD/Apzeh3aniIjlgBfWqnsJIOo398dMd2Jmng38uVK1Y7n8qUqZ+S2m7nG/KXBQH5r+f5XjW4H/7GBMfwdOrFQ9MSKW78OYRs3XegjI2lYGQCdVqjYvg8FRUX9PXtzEICRJkiRJI2VxrWyeVzDPk3les8zzCuZ5kiQNkQ/6aL5ar1bu9On5uerFtfIX+rWXc83TmRqY3AR8rZuGymU7n1qpuhn4xiyX1ff7ri9vLHhbrfyucqnerkTEVsBGlarvTrfv9Ax+WjlenmL517nm5H42FhHLR8Q6EbFxRCyuvij2Aa/app9996j+nlx/z5YkSZIkzT/mea2Z52mCeV4zTu5nY+Z5kiSpHQubHoDUkJVq5fofyP10fa28esuzGhYROwPbVaruY4aZND2qz9g5PjO7/R7UZy2d2EZbxwHvY/Jhx/0j4uDMvLvLMcw5mXl2RHyTIsSB4sbszXS/7/NjauW/lTennVhaK2/G1JlKc8Fverm4nM22L/BYit/ndTq4fM1e+u6z22vllfvY9qeAr3Z4zWa43K8kSZIkNc08r8Y8zzyvyjyvMeZ5BfM8SZKGyAd9NF/Vf/bvHWBf/6yVOwkG/gxsMs3HXg+8rpsBTaN+s35qZl7Rx/YBiIgHAXvWqj/XQ5P12TvHzHZBZl4eET8CnlhWrQM8jS5nIc1hbwf2BhaU5TdFxKcy85ou2npQrfxmet+Xe60erx9F3XxtiYiNgY8Dz+ih71EKLevvyf3YUx6A8ue3o69zRPSre0mSJElS98zzlmWeZ55XZ543fOZ5BfM8SZKGyK27NF/VZ4isOMC+rqyVt2r3wsy8JzOXtHoBN/ZrgBGxMsWsgape9tieyYFMfe/5bWae101DEbErU5cnvSQzz2zz8qNr5XowMu9l5h+ZGrSsAryry+bqe9v3w6oDaLNRmXlLp9dExDbA2fQWCsBo/U1Qf0++rZFRSJIkSZJGiXlehXkeYJ63DPO84TPP+xfzPEmShmiU/giQhunmWrmfy0jWnVUr7xARyw+wv248l6k3WVcD3+53J1E8Rl/fN7yXAKJ+M795RGQ7L+D42rVPjIgH9jCWueo9TA3SDoqIzbpoZ7k+jadq3k/LiIiFwAnABpXqO4H/owjhHll+bBVgYWbGxItlfxdHSf09uf6eLUmSJEmaf8zzpjLPM8+bjnneCDPPkyRJ/eCDPpqv/l4rb9DyrP44rVZeBOwywP66Ub/BPi4zB7H88eOZunTxXcCXumkoIlYB/r0fgyrdj+JGShWZeTnwyUrVIor90Dt1Xa28X/UmtcvXod1+XjNYMPspI+VZwA6V8iXAdpl5QGYem5nnZeZVmXlbZt5Xu3a14Q2zYw+olevv2ZIkSZKk+cc8byrzPPO8lszzRp55niRJ6pkP+mi+WgJkpTywmR+Z+Vfgolr1ywbVX6ciYkvgMbXqQS3zW99/+xuZeX2Xbe1LMauhn14Sbt7bygeBGyrlfSPi4R22cXWtvGVvQ5rRlFCrnCXTrjX7PJZBe3qt/IrMvLTNa+s336Nkw1r5skZGIUmSJEkaJUswzwPM82rM81ozzxtd5nmSJKlnPuijeSkz7wT+XKnaKCJWGmCXH62VnxMRDxpgf52o36z/PDP/3PLMHkTEGhSzFar6uczvCylmF3X6OqPSxibAHj2MaU7KzBspwoEJAXyow2bqS14/sZcxzaK+LOwaHVy7XR/HMQxbVI5vY9kZhzPZtb9D6attauXzmxiEJEmSJGl0mOdNYZ43yTyvBfO8kWaeJ0mSeuaDPprPzq0c3w/YfoB9HQNcWSkvDxzd9GyTiFgAHFCrHtTsnxcAK1TKS4CfdNNQRGzD1OWSrwO+kplLOn0BX6w1Xw8cVPgk8I9Kec+IeEIH1/+aqcv97hIRg/qdu6ZW3radiyJiEbBnh33dVTlevsNr+2GNyvHNmZnTnVgVEZsDjx7IiPpjh1r5l42MQpIkSZI0aszzzPOWYJ7XLvO81szzBsM8T5KkIfJBH81np9fKOw6qo8y8C3hTrfrfgI80HA7sxdT9zG8Bvjqgvuozjb7Q7k1MC/Wb96/2sAf514C7K+VnlbOVVFHOmntPrfpDFLOB2rl+KfCpSlUA/9XhMrzt+nWtvE+b172EZZeYnc2NleMNpjtpgKpLMK8XEe0uVXwEI/o3QBnQPKxSdWFm/rOp8UiSJEmSRop5nnkemOe1xTxvWjdWjs3z+sA8T5Kk4RvJPwqkIflurTzQJV4z83iKWRRVbwBOjIh1u2iyH3sP12+wT8jM2/rQ7hQR8VCgugf0UopZUd20tQjYv1b95a4GBmTmDcD3KlUrAPt1215VRCyOiKy9Fvej7YYcC/y+Un4EsFEH13+EqbOA9qCYCbfCNOe3FBEbRcRTZjilPrPsoNmW1o6InVl2Se52/LFyvHFEbNVFG734beV4AfCW2S6IiPcCzxzYiHr3KGDlSvk7TQ1EkiRJkjRyzPPM88zzOmOetyzzvP4zz5Mkach80EfzVmZeCZxTqdpjQLMRqt4EnFqrew5waUQcHhGPjIhpfy8jYvWI2C8iTgde28tAIuL+wFNr1Z/rpc0Z1AOI72fm37tsax9gvUr5b8CZXbY1oR4suNxvC5l5H3BID9ffDOwLVGdrvRD4dUS8YKaAICI2iIgXR8QpwKVlO9P1cwnw00rVqsCPI+JRLdpdJSLeWp6/ElNn1LTjp7XyNyPiwIh4aERsUoZDE681Omy7HV+pld8eEe+LiFXqJ0bEVhHxDeDdZdW1AxhPP9SXkD65iUFIkiRJkkaPeZ55XoV5XhvM81oyz+s/8zxJkoZs0DdB0qg7DtipPF6TYkbCDwfVWWbeExFPBz4B/EflQ6sAby1fN0bEn4B/UiwjuhywOrAZsAmtH9C7is7/eD6Aqe8BF2Zm3/fNjYjlWXZGTS/7htdv2o/vYcngCacAt1J8HwAeHhEPzczze2x3zsnMUyLiTLrcDzozfxIRB1L8DEzsgb0Nxd7qX4iI84ErmPx+rAVszdQwqB1vAM4FFpXlLYBfRsSFwJ+A+yiW9X1UZRx/BP4X+HgH/XwOeDNF+ACwFXD0NOe+Fzi0g7ZnlZk/johTgeqMqHcAr4uIXwJXUnwdt6T4Ok/4I/BpiveiUfOcyvGfM/MXjY1EkiRJkjSKzPMmmeeZ583KPG8Z5nn9Z54nSdKQ+aCP5rsTgA8DK5bl5zLAYACKcAB4VTmT4SPAtrVT1gB2brO5a4CjgI90sURvfY/tXm7WZ/JMipu7CddS3Ih3LCI2BJ5Uq+56md8JmXlHRJxMMRtlwkuB/9dj0/UZLfdS3PCOu7cBP+/24sz8UkT8GTge2LzyoeWAHdtsZsaZOpn52zKAOIbJcABg+/JV92uK2WVPbLP/iX6uiIh9KX4O1+jk2j7aj+J965GVulWAx09z/vnA3sCegx1W58qlkh9cqZouZJEkSZIkzV/meZPM88zz2mWeN9mPeV4fmedJktQMt+7SvJaZ11PsUzxh31ZLZA6o7+9R3KDsTbFc501tXvp3ipuQvYENM/OwTkOBiHg0xayKCXdTzMAYhPqMnf8rw5FuHEixb/GEP2TmBV22VVcPGGZcerZNu9bK/5eZ17U8c4xk5pl0Ge5U2vgVxc/gC4Gzmbr8bytLgd8ARwAPz8w3tNHHl4HHAKfPcNrfKGbM7JqZV7Qx9Fb9nEox8+dNwHeBJRQB0NJu2uui/xspPs/DgOtnOPXPFKHOzpl5+RCG1o2XV45vAz7b1EAkSZIkSaPJPO9fzPPM89pmnrdMP+Z5/WOeJ0lSA6L3FTKl8RYRW1As/Tnx4NtBmfmZBsZxP4qbi60pliBdtRzTTRRL/l4NnJ+Zo7oPr2oi4ovAC8riPcBWmXlZg0MaWRGxKsXMtwdSzBhbgeLm+p/AxcAfyz3Bu21/Q+CxwAYUM42uBC4Bzu7DUtEjo1xaeydgO4rly2+lWAr8j5n5uybHNpty7JcDa5dVn8zM1zY4pH+JiO2ACyfKexz6JVZ7wKYNjqi/br7iUn566AuqVdtn5u+bGo8kSZIkzcY8T4Nintc+87z+MM8bjHqe95T3H8/qG27W4Ij666bL/8Kp73h+tco8T5LmGbfu0ryXmRdHxJeA/cuq10fEZ4d9s5CZSyn22f3jMPvVQO1ROT7GUGB6mXkLA1xmu5zxcsKg2h8VmXkXcEb5GjcvYjIUuAM4vMGxSJIkSZJGmHmeBsg8r03mef1hnidJkrrh1l1S4d0Uy90CbEOxD7XUtYjYGnhAWbwbeF+Dw5FGWkQspFiGeMInR3g5YkmSJEnSaDDPU1+Z50ntM8+TJKlZPugjAZm5BPh4peo95dK7UrceXzn+fGb+rbGRSKPvRcDEXljXAh9scCySJEmSpDFgnqcBMM+T2meeJ0lSg7zxkSYdBkzcvO1A8Yeq1K2JZX7vAj7Q5ECkURYRK1O8/054S2be2NBwJEmSJEnjxTxP/WSeJ7XBPE+SpOYtbHoA0qjIzNsiYj9gz7JqUZPj0XjLzOc2PQZpTGwGfLY8vjUzj21yMJIkSZKk8WGep34yz5PaZp4nSVLDfNBHqsjMM4Ezmx6HJM0XmXkBcEHT45AkSZIkjSfzPEkaLvM8SZKa59ZdkiRJkiRJkiRJkiRJ0hjwQR9JkiRJkiRJkiRJkiRpDPigjyRJkiRJkiRJkiRJkjQGfNBHkiRJkiRJkiRJkiRJGgM+6CNJkiRJkiRJkiRJkiSNgYVND0CSJGmc3HbnvXDHPU0Po29uu/PepocgSZIkSZIkDcw/b7mbO2+6s+lh9M1tt9zd9BAkSQ1zRR9JkiRJkiRJkiRJkiRpDPigjyRJkiRJkiRJkiRJkjQGfNBHkiRJkiRJkiRJkiRJGgM+6CNJkiRJkiRJkiRJkiSNAR/0kSRJkiRJkiRJkiRJksaAD/pIkiRJkiRJkiRJkiRJY8AHfSRJkiRJkiRJkiRJkqQx4IM+kiRJkiRJkiRJkiRJ0hjwQR9JkiRJkiRJkiRJkiRpDPigjyRJkiRJkiRJkiRJkjQGfNBHkiRJkiRJkiRJkiRJGgM+6CNJkiRJkiRJkiRJkiSNAR/0kSRJkiRJkiRJkiRJksbAwqYHII2LiDgaOLAsfiUzn9fgcPouIhYA2wAPAdYBVgFuB64HLgQuyMx7euxjxbKPrYF1yz5urfTxu8y8t5c+JPVfRCwGLqtUHZuZB/ap7f2AL5XFy4GtM/PWfrQtSZIkSZrfzPPM86T5yjxPkqS5zQd9pDZExKOBF5XFu4G3z3L+acBuZfH0zNy9h74/0KK/92fmO7tts9b+RsAbgf2BtWY49baIOB74aGb+sYP2Hw48A3g8sCOwaJY+vgJ8IjMvaLePsp9jmPweTScpgoibgCXAucD3gB9mZnbYx18zc3EnYxyUTscVEa0+1zMz8zFd9F1t67bMXKXTNjT3RMShwHsmypkZM5x+PPB64FHAhuV1bxng8CRJkiRJ84B5HmCeZ543e1vmeQLM8yRJGjdu3SXNIiLuBxwFTPxh+z+ZedkMl/Sz7wXAAS0+dGD5sV7bfynwe+B1zBwKAKwMvAw4PyLe1kbbK0TEX4DzgHcBj2bmUGCij5cAv46ID0XEbOd3KoBVgQcCjwHeAHwfuCQi9ulzX+Pm0RHxtKYHMU4iYnFEZOV1TNNjGkdlKHdwper1EbFVU+ORJEmSJI0/87x/Mc+b28zzOmSe1x/meZIkNc8HfaTZ7Uex/C0Us3+OHGLfT6Z4Ir5uQ+BJvTQcEf8P+BzFcrtVVwLfoVh681vAX2sfXw74UEQcNksXC4FNW9Qn8CfgB8CXgVOAS2vnLADeBpwQEcNYeWxT4JSI+NAQ+hplH+hH4CR1KjN/ApxVFhcC72twOJIkSZKk8WeeN5V53txlnqdGmOdJktQsH/SRZlDOQKneAB+XmZcPcQgv7fJjM4qIbYGP1Kr/BuwNbJiZe2fmCzPzaeWysbsD9eV93xkRu7bZ5X3AqcDzgPUyc5vMfFJmviAzn56ZmwGPBM6oXfcs4NB2P6+aTwCb1F6bAg+jCHu+CiytXfO2iHh1l/3NBdvResaZNAwfrBw/OyIe0dhIJEmSJEljyzzPPG+eMc9Tk8zzJElqiA/6SDN7HsUN5YSjhtVxRKxHcaM+4SLg4kp5n4hYt8vm38rUZXevAR6dmd9ptbd1Zp5OsVRvtf+gWMJ3JndRfM0WZ+ZemfmVzLyu1YmZeR7Fvt/H1z70lojYeJZ+WrkxM5fUXpdl5vmZeXxm/jtF4HFD7br3R8Rsyx7PZe+NiBWaHoTmpe8CE8uoB8UsQEmSJEmSOmWeh3nePGOep6aY50mS1BAf9JFm9qbK8TmZef4Q+z6AqTfvx5avCYuA/btsu75/9Qcy8x8zXZCZNwBvr1U/PiJWnuaSO4HNM/M1s7Vd6eM+iplNf69ULwf8ezvXdyozf8ayM15WB140iP5G1G3AjyrlBwH/r6GxaB7LzKXAZytVz4qITaY7X5IkSZKkaZjnlczz5izzPI0E8zxJkprjgz7SNCJiFyb38gb44pCH8JLK8VLguPJVXZ624+V+I2J1oD7D5VttXv5d4N5KeTlgo1YnZua97QYCtevuAI6uVe/RaTsd9Pdt4Lxa9RMH1d+IehvFXusT3h4RazQ0Fs1vX6ocLwBe0dRAJEmSJEnjxzyvJfO8uck8T6PCPE+SpAYsbHoA0gg7sHK8FPj6sDou98replL144mb7Ij4MbBnWb9tROycmb/ooPlWM3banaFzR0RcB6xfqV6zg77b9Zta+QED6KPqB0B1/+BtB9zfSMnMX0fEVyiWtobie3pw+RqKcp/5BwPrAqsB1wNXAj/PzH8OaxyjplzyeydgA2Ad4Fbge5l50QzXrEXxM7wFRQi4AnAz8E/gfOCPrZb0HgWZ+beIOIficwbYPyLeUc4OkiRJkiRpNgdWjs3zMM+bq8zzRpd5nnmeJEnD4IM+UgsRsQB4bqXqvMy8cohDqM/sOaZ2vGel/FKgk2DgnxSzeKq//ysAd7d5fX2/5+s76Ltd99bKyw2gj6q/18rrDLi/UfRO4NlMLi/92oj4ZGZePqgOI2Jt4C3AC4ENpzltaUScBbw3M380zTn1dpcAE/vA/zUzF3cwpkOB91Sq9sjM02Zov+pFETHTMtEvzsxj2hlrRDwWeDfF7LcFtXbeAEwJBiJiJ4olsfcEtqfYE3s6/4yIzwEfz8yrZjivKacwGQxsCOwG/LS54UiSJEmSxoF53ozM8+Ym8zzM80aEeZ4kSUPm1l1Sa7sydWbL0P4ojYhVmLqH9c3ASZXyScBNlfK+M+yrvYzMvAv4Za364W2ObVNgjdrYLm637w5sXisPOpSZ6SZqXsjMvwCfqVStCLx3UP1FxAHApRTLDE8XCkDx/9RjgB9GxP9FxKBDosZFxGHAacATWDYUaHX+syjCwTdSzKKa7ed5bYqv+4URsecs5zah/n67dyOjkCRJkiSNG/O81mMzz5ujzPNGh3meeZ4kScPmgz5Sa0+ulX82xL73BVaplE8s97kG/rXn9YmVj6/K1NlK7TiqVn5Nm9e9rlb+v8y8r8O+2/GcWrkeZPTbA2vl6wbc36g6jGIp2QkHRsTW/e6kvPE9lmJJ3wkJ/Ilif/kvA6cC19YufSHw3YiYs6vRRcTrgXcx+f/zX4HvAMcDPwFuaHFZ/f/y+yi+lqcCXwFOAH4I1Gf7rA18JyJ26cfY++hc4I5Kuf5+LEmSJElSK+Z5rZnnzW3meQ0zzwPM8yRJGjof9JFa27lWPr+TizNz98yM8rV7h33PtMzvdHX1a2aUmV+mWE5zwrMj4pCZromIlwH/r1J1DQOYIRIRjwIeXas+qdW5fVSfBfHHVidl5oGV7+viAY+pbf0aV2ZeA3ykUrUA+GCv46sql8J9V6VqKfBJYHFmbpOZT8vMF2TmXsD9gWcCf6uc/2/Af/ZzTF14DLAJ8Nha/dfL+uleX5ul3fWAI8vjs4GdM3NxZu6dmftl5r9R7O19YotrbwT+G3gSsEr5tdwrM5+Xmc/PzCdm5gYUsxurM2wWASf0e2ZVZh5a+ZnsaIZdZt4L/L5StU1ErNHP8UmSJEmS5iTzvBrzPPO8fjDPm5F5HuZ5kiQ1Yc4+RS316BGV4xsz8x/D6DQitgGqT+NfnJln1s/LzLMi4iJgy7LqMRGxVWb+uYPu9gWOBp5Xlt8fEfsAXwB+TbGc8CrAQ4D9KW7IJlwDPDkz6zM0ehIRi4D/rVX/LDMHNgMoIp4CPLJW/cNB9TcGPgz8B8VNKsAzImKXzDy714YjYmPgfypVdwHPyMzvtTo/MxM4udzT+0wml4B+S0R8JjMv63VM3Zh4P4hY5n731sxc0kPTK5b/fht4dmbe3aLvu4AratWnAxtm5u2zdZCZZ0fEvwGfB15cVm8E7EfrELIpFzD5exnlcVt7us8mItYD1u3wss360bckSZIkaaDM88zz5ivzvFmY5w2FeZ4kSUPkij5STUSsD6xeqfrrELuvz+Q5doZzj6mVX9JJR5l5Z2Y+n2LGwHeBuylmPn0G+BXFXt2/KfuZCAXuprih2CEzf9NJf206EnhYpXwP8NoB9ANAROwK/F+t+mZm/rrPaZl5K/C+WvXhfWr+LUze/AK8YbpQoDamayhuXCcsAN7QpzGNmmuBF7UKBaaTmde2EwpUzk+K5b2vqVS/oP0hDkX9fXfLlmd151XAhR2+vtnH/iVJkiRJfWaeZ56HeZ55XnPM8wrmeZIkDZEP+kjLWlwrD2v2zyKKmTYTlgLHzXDJceU5Ew7ocq/jhRQ34PfOct7twPuBd2bm1V30M6OIeAnL7hl+aGae32WTa0TE4tprk4h4SETsGxEnAGdQ7Gtc9e7MnK97ek/4NHBppfzYiNi7lwYjYmWmhleXsuxsr2ll5rnAzypVT+tlPCPsM5l5/aA7KYOEUytVO0XEKP1NUH/fXdzEICRJkiRJY2NxrWyeVzDPmz/M85pjnlcwz5MkaYhG6Y8AaVSsVyvfMKR+96n1/ZPM/Pt0J2fm5Uxd+nJ9YK92O4uIDSPiJ8B3gKcDK81yyUoUe3gviYiPRMSKs5zftoh4MsXNaNW36W0/6dcBl9Vel1Lsz34CxVLHC2rXfDQzP9FDn3NCZt4DvLNW/cEebxwfw9TZP1/LzKXTnTyN6l7UG0fERj2MZ1Sd3M/GImKFiFg3IjauB2XALZVTVwUe2M++e1R/362/L0uSJEmSVGWe15p53jxhnteok/vZmHmeJElqRzezBaS5rn6DfMeQ+q0v1XtMG9ccAzyxUn4pcMpsF0XEAylmUyyuVN8OfA44CfgdxZ7eqwJbA3tT7PO8JrA88EaKWSFPysyegpOIeDTwdWBRpfrnwL7lkqTDsAR4Y2aeNKT+xsEJFEvzTiy9vD1wAN3v+/yYWvmK8ua0E/XlbzcF/tbleEbRfRR7WXctInYCngvsAmzH1GXLZ7Mmo/P1rC9dvHIf2/4U8NUOr9kMl/uVJEmSpFFmnmeeJ/O8JpjnTTLPkyRpiHzQR1pW/fditiVwexYRDwCeXKm6GfhGG5eeRHEDP/HH/14RsX5mXjXLdV9kaihwCbBXZl5cO+8G4Gzg7Ig4imJ2wqPKjz0K+FJEPLXbG/iIeATFDKRqGPNL4Kmd7FHcodsovmZLgHOB7wPf72I2ypyWmRkRB1N8fSa8NyKOz8y7umjyQbXyx8tXL9bq8fpRc1Mne3lXRcT2wFHA43rov5MQYdDq77uLWp7VhXKP+GtmPbEiIvrVvSRJkiRpMMzzJpnnzVPmeY0wz5tknidJ0hC5dZe0rPqMn74taTuDA5m67OyJmTnrzKPMvJNipsaEhcCLZromIp4E7FapupviRrweCtT7ugJ4KlDdb/gpFLODOhYROwA/YOrNyG+AJ2Xmzd20WfPezIwWr1Uyc8PMfHRmvj4zTzUUaC0zfwD8uFK1EfCaLpur753eD6sOoM0m3TL7KcuKiMcAZ9FbKACj9TdB/X33tkZGIUmSJEkaF+Z5rfsyz5tnzPOGzjxvknmeJElDNEp/BEijon5T2s8lJpcRxaPl9WV+XxYR2c4LOKh2bb2tuufWysdn5kXtjDUzr6WYZVD14naurYqIbSn2I6/O4LgQeGJm3thpexqotwHVGV6HREQ3M0WW69N4qub9tIyIWA04kakhyU3A/wLPp1iq+f4U72MLqiEZ8N5hj7cD9ffdfoSFkiRJkqS5yzxvGuZ585J53ggzz5MkSf3ggz7Ssv5eK28w4P52o9gvtl+2LGcETOchtfKPW541vR/Vyjt1cnFEbFX2uW6l+k/AEzLzug7HogHLzPOYuv/xWsDBXTRV/97uOs0MrU5ex3T7ec1gweynjJRXMvU96hxgi8x8ZWaekJnnZ+Y1mXl7i5luqw1vmB17QK1cf1+WJEmSJKnKPG9m5nnziHneyDPPkyRJPfNBH2lZS5g64+GBA+7vpUNuc41aebb9v+vq56/T7oURsTnwE2D9SvXFwOMz8+oOx6HheQdwT6X8unIf+k7Uv79b9jakGVX3g17Y4bVr9nMgQ/D0ynEC+5Uz9drR6fdwmDaslS9rZBSSJEmSpHGxBPO8mZjnzT/meaPLPE+SJPXMB32kmnKf7D9XqjaKiJUG0Ve5ZOqzK1V3A9sBm3T42pKpe94+NyKm2+/4xlq506WMV6mVb23noojYhCIUqN6MXEoRClzZ4Rg0RJl5CfDZStWKwKEdNnNWrfzEXsY0i+qysGt0eO12HZybs58ycFtUjv+YmZd2cO0u/R5MH21TK5/fxCAkSZIkSePBPG9W5nnzjHnetMzzBsc8T5KkIfJBH6m1cyvH9wO2H1A/+1HcZE04NTP/kJlLOnxdDHyz0s7KwPOm6fOKWvlhHY75EbXyrDOIImIjilDgQZXqv1KEAv/osH814zCmhk8vKZdtbtePgfsq5adFxHp9Gdmyrqkcr1z+/M0qItYCdu6gn7tq5eU7uLZf1qgc39TuRRHxeKCtr0tDdqgc30yxHLgkSZIkSTMxz5ueed78ZJ63LPO8wTHPkyRpiHzQR2rt9Fp5xwH1U1+S98s9tFW/drrlfk+rlV8UEcu100FEBPDyWvXPZrnmARQ3hYsr1ZdThAJ/badfNa9civmjlaoFwAc7uP4G4EuVqlWAD/dndMv4da28T5vXvQVYoYN+bqyVN2h10oDdUDneIiJm/X89IhbRwfdu2CJiA6YusX5GZo7CbCtJkiRJ0mgzz2vBPG/+Ms9r6cZa2TyvD8zzJEkaPh/0kVr7bq28R787iIiHMHU2zS3At3po8vvAdZXyThHRatnSk5i6P/PGwH+XN/2zOQx4VK3ua9OdXM7w+DGweaX6SmCPDpckHUsRsXtEZPXV9Jh6dCRQ3S/6mR1efyhTZ83sHxGHR8SCThqJiG0j4nEznPLjWvltEbHaLG0+A3hrJ+MolwVfUql6VESs0UkbffDbyvE6wMtmOrn8Wv8vgws7+6H+fvudRkYhSZIkSRo35nmtmed1wDxvGYdintdv5nmSJKlnPugjtVDuMX1OpWqPiFjY527qM3ROzsw7um0sM+9l2Zv0l7Q4bwnw6Vr1y4FTI+KhrdqOiC0j4kTgnbUP/SQzfzTNNWsAPwS2rlTfRvF53xMRizt5tepDw5WZtwDv6+H6y4BX1KrfCvw8IvaZ6Xes/Dl4dUT8BPg98PgZuvoJ8JdK+UHAD1otTRwRa0fE4cDXKf5PvKF+zix+WjleCfheROwbEdtHxCa1n+NVOmy7HV+plf87Il7balZfRDyK4mvz4rLq2vo5I+IJleOl9BaYSpIkSZLmCfO8qczzBOZ50zDP6z/zPEmShqzfNzrSXHIcsFN5vCbFU+k/7EfDEbE88IJadS/L/FbbeGWlvH9EHJyZ99TOexvwcODRlbonAU+KiMuACyn20V2F4sa+1d7NS4ADZhjLQ5m6Ly8Ue43XZ1e1q50ZShq8TwOvBzbp5uLMPC4i1qdYanbiYdOdgVOA2yPiN8DVwB3AqhSzWrZl6t7Vs/WREfFaps4c2Qn4Q0T8miI0WECxp/UjymMolvg+Ezikg0/pv4D9mfz/dCfghGnOfTFwTAdtt+NY4LVM/q4tAj4BHBoR5wD/BFYHtmfqctunAz8H3tHn8fSkDIeeXqn6UWZe3tR4JEmSJEljxzzPPE/LMs+byjyvj8zzJElqhiv6SNM7geLmZMJz+9j2M4G1KuVrgZYzaTr0c+BvlfK6wNPqJ5UzjZ7K1D2WJ2xCsQfyCyj+QG8VCpwB7O4f7LOq7w99YxOD6KfMvBt4V49tHEHx83dV7UMrUYRVz6L4+XsasCutQ4EZZ+pk5ncpArCq+wGPBPYFnkOx3O1EKPBDip/7eog2o8w8n2JW052dXNcv5cy/fZg64wmKMPPJFF/HvZkaCvyI4mt77xCG2KknMPW98QtNDUSSJEmSNJbM88zzemWe17oN87w+Mc+TJEn94IM+0jQy83qKp+sn7NvHpTrry/yeWP6B35PMTJadfVDva+LcmzLzhRRLpn4DuHuW5pdSLBO6L0Uo8Ncehzsf7Forf6yRUfTfl4Hze2kgM79HEUK9umxrtv3O7wHOotgXfMvM/EQbfRxBcXP8mxlO+xPwKuDJ5VLGHcvMoylmyr2b4qb7HxTLWg9lD/fM/BvFjL7/Am6f4dTfAAcBT8rMm4cxti5U9yT/O8USzJIkSZIktcU8bxnmeZ0zz5uGeV7/mOdJkqReRXEfIamViNiC4sZh4qG4gzLzMw0OaWDK5YcfAmxDMXtgFYqbjBuBS4BfZ+atjQ1wDEXEz5lcTvl6YJMRviFrVESsRbHk7wYUM0AWAbcC1wAXAX/KzJluemdrf3NgF+D+FMtGXwH8ITNnCg3GTkSsTBFIbQWsBtxEMdPqt5l5SZNjm025BPTfKL73AG/KzI82OKR/iYjtKJZAB2DHg49l5Q26Wu16JN125WX88kMvqlZtn5m/b2o8kiRJktQL8zzzvF6Y57XPPK8/zPMGwzxPkjTXLZz9FGn+ysyLI+JLFHv2Arw+Ij6bc/AJucy8C/hl+VKPyhu0HStVHzEUmF45467b/d7baf8SioBrTsvM2yiWLf5h02PpwmuZDAWuotg/XpIkSZKkjpjnqVvmeZ0xz+sP8zxJktQNt+6SZvduJpfB3YZiP25pNo9l8ibnOoplWCW1EBFrUCz7POGwXmZ8SZIkSZLmPfM8dcM8T2qTeZ4kSc3yQR9pFpm5BPh4peo9EeHvjmbz+MrxkS6TLM3oTRRLEwP8Afhcg2ORJEmSJI058zx1yTxPap95niRJDfLmRmrPYRR7zQLsALxohnMlgD3Kf68BjmpyINIoi4gNgTdWql6dmfc0NR5JkiRJ0pxhnqdOmedJbTDPkySpeQubHoA0DjLztojYD9izrFo00/lSZj6q6TFIY2Iz4Mjy+PLMPK3BsUiSJEmS5gjzPHXKPE9qm3meJEkN80EfqU2ZeSZwZtPjkKS5JDPPAM5oehySJEmSpLnHPE+S+s88T5Kk5rl1lyRJkiRJkiRJkiRJkjQGfNBHkiRJkiRJkiRJkiRJGgM+6CNJkiRJkiRJkiRJkiSNAR/0kSRJkiRJkiRJkiRJksaAD/pIkiRJkiRJkiRJkiRJY2Bh0wOQJEkaJzttvjb3X3z/pofRN1evfDO/bHoQkiRJkiRJ0oDsse16bLDphk0Po2+uvPQ28zxJmudc0UeSJEmSJEmSJEmSJEkaAz7oI0mSJEmSJEmSJEmSJI0BH/SRJEmSJEmSJEmSJEmSxoAP+kiSJEmSJEmSJEmSJEljwAd9JEmSJEmSJEmSJEmSpDHggz6SJEmSJEmSJEmSJEnSGPBBH0mSJEmSJEmSJEmSJGkM+KCPJEmSJEmSJEmSJEmSNAZ80EeSJEmSJEmSJEmSJEkaAz7oI0mSJEmSJEmSJEmSJI0BH/SRJEmSJEmSJEmSJEmSxoAP+kiSJEmSJEmSJEmSJEljwAd9JEmSJEmSJEmSJEmSpDGwsOkBSOMiIo4GDiyLX8nM5zU4nL6LiEXATsDmwLrAUuAK4C/AuZmZfehjLWBr4EHA/YGVyw/dBFwN/CYzL+21H0n9FxGnAbtNlDMz+tTuasAlFO87AM/MzJP70bYkSZIkaX4zzzPPk+Yz8zxJkuYuV/SR2hARjwZeVBbvBt4+y/mnRUSWr9N67PsDlbYmXu/rpc1a+xtHxGeBfwI/A44GjgA+DHwZOAf4e0R8KCJW7bDtVSLi4Ij4ZkRcUfZxJnAC8AngA+XrKOBrwF8i4u8R8f6IuP8sbS9p8XXp92tJrc/dax/fvZOvx6B0Oq6IOKbF53pvRGzdRd/1tp7T7eehuSMiFtd+Lg6c7tzMvBk4rFL18YhYaeCDlCRJkiTNaeZ55nlln+Z5s7dlnifzPEmSxowP+kiziIj7Udy4Tjzt/j+ZedmQ+l4AHNDiQweWH+u1/ZcBFwEvA2a66d8QeBvwu4h4XAddrA98EHgasEGb1zwQOAT480w3E+q7BRQhjTpQCwF7niU3j30amJj9tzFwcINjkSRJkiSNOfM8wDxvPjDP64J5Xt+Y50mS1CAf9JFmtx/wkPL4buDIIfb9ZIqb8roNgSf10nBEvAv4LLBc7UO/Bb5evn5b+9jGwKkRsWMPXV9PMavom8CXKGb+/By4pXbe6sDREfGmHvpSZ54ZETs3PQjNP5l5L3B4peqNEbFeU+ORJEmSJI0987xJ5nlzm3meGmGeJ0lSsxY2PQBplEWxz3V1CcrjMvPyIQ7hpbN87LvdNBoRTwPeW6v+EfDqzLyodu5WwKeAx5dVKwHfjogdMvOqNrq7BvgO8EPgrMz86zRjWkQxU+hwYLPKh46IiJ9n5jm1Sx5De+9hD6RYwrhqkzauA7i3zfPmksOp7NssDdExwHuABwArA+8EXtvkgCRJkiRJ48c8zzyvzfPmEvM8NeUYzPMkSWqED/pIM3seU28ijxpWx+XT73tXqi6iWG54i7K8T0Ssm5nXdtjuIuCTTC5dDHAS8O/lU/hTZOafI+JJFDOCnlZWrwscCrxylu4uAzbIzKWzjSsz7wG+HhE/Ac4Ati8/dL+yr6fUzv/HbG0CRMQydZm5pJ1r56nHRcRTM/M7TQ9E80tm3h0RnwPeXVa9LCIOy8zrmhyXJEmSJGnsmOeZ58035nlqhHmeJEnNcesuaWbVZWbPyczzh9j3AcCiSvnY8jVhEbB/F+2+ANioUr4WeGmrUGBC+bEXA/+sVL8sIracqaPMvK+dUKB2zQ3A62rVT4iImfYcV29OrpU/WO5lLw3bZ4H7yuMVgVc1OBZJkiRJ0ngyz8M8bx44uVY2z1NTzPMkSWqAf/hJ04iIXZjcyxvgi0Mewksqx0uB48pX9UZ7pqWAp7NPrfz58mZ8Rpl5PfCFStUCugsm2nEacEelvJBiP3ENxpeB8yvlBzO47600rXJm3xmVqlcYUkmSJEmS2mWeN5V53pxmnqeRYJ4nSVIz3LpLmt6BleOlFEvdDkVE7ApsU6n68cTSthHxY2DPsn7biNg5M3/RQfOPq5W/38G13wPeUik/B3hXB9e3JTOXRsSNFDMAJjgDaHASOJji+zvhsIg4ITPvGsYAImItYFdgfWAd4E6K2WnnZ+bvhzGGUVQuzb0rxay99Ske0P19Zn57lmu2AbYCNqD43bkTuAG4FPhlZt4+4KH34kRgj/J4Q4r3u07epyRJkiRJ89eBlWPzvIJ53txknjeizPPM8yRJGgYf9JFaiIgFwHMrVedl5pVDHEJ9Zs8xteM9K+WXAm0FAxGxPMVNV9WFHYzrd7Xy1hGxaWZe2kEbs4qIlSj2Da+6op99aKrM/H65n/rjy6qNgFcDHx1Un1FsuL4v8HrgUUyzylxEXE6xD/1/ZeYdrc6pnX8o8J5K1R6ZeVqbY1pMsRf9hGMz88BZ2q9+LGdo/vTM3L2dsZZByX8CzwPWqrXzW2BKMBARG1AEdftQBAkrzzCOeyPie8ARmfmzGc5ryinA/1TK+2EwIEmSJEmahXnetMzz5ijzvH9duxjzvKaZ50mSNGQunye1tiuwZqX802F1HBGrAP9eqboZOKlSPgm4qVLeNyJmugmoqt9gANzYwfBanfvgDq5v1/OZ+iDiZZn51wH0o6neRjEbaMIhEbH6IDqKiE2B84DjgZ2Y+f+jDYEPAX+IiO0GMZ5REhGPBi6g2M+61e9sK38G/osiNJzt/WAhsDdwRkR8NCJG6qHfzLwCuKhStZfL/UqSJEmS2mCe11qrc83z5g7zvBFgnmeeJ0nSsPkfrdTak2vlYT4lvy+wSqV8YnXWQ3l8YuXjqzJ1ttJM7m5Rt3wHY2t17rYdXD+r8qbow7XqelkDkJm/Ar5WqVobeGu/+4mIHYFzgIfVPvRP4EfACRQBWH122mLgzIh4aL/HNEI2pZgBs2FZvo1ij/sTKGb9/Hma6+r/n19dXvcN4IvAN4HfA/fVznsD8PHehjwQ1X291wEe0dRAJEmSJEljwzyvNfO8Ocw8bySY5xXM8yRJGqKReupXGiE718rnd3JxfTnPDs20zG+17uW1a1qdV3cDxf7k1ZuIDYBL2hzbBi3qtmrz2pbK5YfXpbhJ3Jdi9k91fN9i6rKfjSmXi42mx1HX53G9A3gmk/8/vD4i/rtfS11HxPrAyUxdcvocir3hf5SZWTt/c+BI4Bll1erAiRHxiMy8pR9j6sLHmfx9O4FiBtOETWa47s42216V4nf1EODo+r7qEdGqj6UUe7J/FTh1uu9XuSTwa4A3A8uV1a+OiG9n5vdaXdONzFxCbz+T59fKuwDn9tDev0TEeiy7lPhsNutH35IkSZKkgTLPa808zzyvJ+Z5bbVtnmeeJ0nSUPmgj9Ra9WnzGzPzH8PoNCK2ofgDeMLFmXlm/bzMPCsiLgK2LKseExFbZeZ0swMmrltaXrd1pXpn2g8GdmlR19FSsBFxPvCQNk5N4FPAG+s3ixqczLw4Ij4HvLKsWgk4FDioT118nqkB0+eBgzKzPjNlYjyXAM+MiE8Ary2rt6CYuXJYn8bUkcy8kXLZ64i4s/axJT02vypwPbBbZtZnQE30cVmL6h3a6bsMDN4RET8FTmXy74CDKYKFUXFBrbxjH9t+FdPsyS5JkiRJGmvmea2Z581x5nmzM88bCvM8SZKGyK27pJpyhkL1ZneYe0nXZ/8cO8O5x9TKL2mzj9Nr5f3bvA7ggBZ1q3ZwfTvuBo4Cts/M12Rmq+WJNVjvpVhidsJLIqKnmV4AEfFIYK9K1dnAK6YLBWreyNSbxdeUs8fmotdPFwpMp9NAIjN/BHy6UrVbRGw43fkNqL/vbtnyLEmSJEmSMM+bhXne/GCe1yzzPPM8SZKGygd9pGUtrpWHNftnEVNv0pcCx81wyXHlORMOiIh2Vun6v1r5iRGxV8szp45vH+DfWnyo38HAcsALKZaYdXnNBmTmVcDHKlULgff3oenX1sqHZObSlmcuO6b7gE9Uqtal9Yy0cfd34EtD6uvrtfKuQ+q3HVcw9f1tcUPjkCRJkiSNh8W1snke5nnziXleo8zzCuZ5kiQNkVt3Sctar1a+YUj97lPr+yeZ+ffpTs7MyyPiR8ATy6r1KWZXnDJTJ5l5ZkScDuxWqf5yRDwtM89odU1E7A58cZom27qxq9iLyb2EoQgW1qdYyvMFwDYUM7BeDrwgIl6dmcd02Id6dwTFcr8Te28/OyJ2ysxzemjzCZXjq1h2NtpsflorPxY4rYfxjKJT2g1L2lGGhatQ/J4tqH24voT2Nv3qt1eZeW9E3AqsVlatExHRp2W/P0Wx93knNgO+2Ye+JUmSJEmDYZ5XY543L5nnNcM8D/M8SZKGzQd9pGWtVCvfMaR+60v1HtPGNccwGQxAsVTwjMFApa9fAWuW5dWBn0bE8RR/MF8MBLA58O/A88syFDOiHlhp68Y2+vuXzLyiRfXvgB8C74+IlwP/BaxA8b34QkQszcyZZkOpzzLzloh4P1NnAn0I2KOb9srZXNW9vC8BNo6Iaa5oablaeS7OEPtNLxeXS5U/F3gS8GBgow4uX3P2U4bqdiaDgaB4P7ht+tPbk5nXANd0ck2HP6eSJEmSpOEzzzPPm/fM8xpjnjfJPE+SpCHxQR9pWfXfi3sH3WFEPAB4cqXqZuAbbVx6EnATk3uQ7xUR65dLtU4rMy+NiGeU169VVt+PYgbOC2a49ByKJYaPqtTd2MY425aZn42Iq5l82j6AT0XEjzPz8n72pVl9Cngdk8us7h4Re2Xmd7to60G18mOAy3oYG0z+7M4lHd2wToiIlYBDKb5f9QClXavPfspQ1d97FzUyCkmSJEnSODDPm5553vxinjd85nmTzPMkSRqS+zU9AGkE1Wf8rDiEPg9k6jKcJ2bmrDOPMvNO4IRK1ULgRe10WC7ruxPwo3ZOp7hJ/DeWnSUwYwjRjcw8hSK0mLAy8Kp+96OZZebdwLtq1R+MiG7+71i7D0Oq6/d+8qPglk4viIhVgO8Bb6H7UABG72+C+ntvz7N/JEmSJElzlnlei9Mxz5t3zPMaYZ43yTxPkqQhGbU/AqRRcHOtvPIgO4tiDcn6Mr8vi4hs5wUcVLu23ta0MvOSzNwT2BX4MMXyv1cDdwPXUSw7egSwQ2a+OjNvY9l9f3/V9ifbmeNr5Se3PEuD9iXgt5XyDsw8S2w6vdywTsf1VwuHU+xvPiEpls5+HcVMq8UUIcpymRkTL2CTYQ+0Q9X33jsz857GRiJJkiRJGnXmeeZ5mmSeN/rM8yRJUk/cukta1t9r5Q1antU/u9HfvYm3jIjHZObP270gM88Gzm7z9F1q5XPaHlln/lwrbz6gfjSDzMyIeDtQXd73PyPixMy8q4OmrquVP5OZ9VBrFCyY/ZTREREbAK+sVN0JPD0zf9DG5avNfkozImJNYIVKVf19WZIkSZKkKvO8mZnnzSPmeaPNPE+SJPWDK/pIy1pC8QT9hAcOuL+XjkmbRMQmwKaVqn9k5iWD6AuoP+2//ID60Swy81Tgp5WqjYH/6LCZq2vlLXsa1Mzqe0F38lBrfSnrUbc3U/8vP6LNUADgAQMYT79sWCv3uv+7JEmSJGluW4J5XkvmefOTed5IM8+TJEk9c0UfqSYz74yIPwNbl1UbRcRKmXl7v/uKiNWBZ1eq7gYeBnTa1yKKZXknlsZ8bkS8NjM73h94FvVlhD/f5/ar6oFM/cZSw3UwU2d7vSMivtDB9b8HbgJWL8u7RMSqA/gZhWWX616jg2u367CvnP2UgdqiVv52B9fu2s+B9Fl9SfHzmxiEJEmSJGk8mOfNyDxv/jLPa808bzDM8yRJGiJX9JFaO7dyfD9g+wH1sx+wYqV8amb+ITOXdPi6GPhmpZ2Vgef1c6Dl0puvqFTdx2CDgSfWyhcPsC/NIjN/CXy9UrUO8NYOrr8P+HGlanlg//6MbhnX1MrbdnDtUzvsa8pyxxEx7Jlqa9TKN7VzUUQsAF7Y99H0zw618i8bGYUkSZIkaZyY59WY581v5nnTMs8bDPM8SZKGyAd9pNZOr5V3HFA/9SV5v9xDW/Vr+73c70eA9Srl/8nMgeyzW+5T/Ipa9TdbnauhOoSpy+i+AVi/g+s/WSu/p/xe99uva+V92rkoIrYDntVhXzfWyoP4fGZyQ628dcuzlvUaYJM+j6Wfqu+5S4EzmhqIJEmSJGlsmOctyzxP5nnLurFWNs/rD/M8SZKGyAd9pNa+Wyvv0e8OIuIhwCMqVbcA3+qhye8D11XKO5U3Oq36XtBuo1E4EnhxpfqvwNtnuW7liHhjRKw403ktrlsX+A6wWqX6euD4TtoZFRGxJCKy8jqw6TF1KzMvYuqsr5WAJ3Vw/WnADytV6wHfjYj6ss4ziohVI2K/GU65GKiGVo+MiGfM0ub9ga8Cbf9ulP5YK9dnrg3ab2vlN8/2+x0RTwEOH9yQehMRi4BHV6rOzcxrmxqPJEmSJGlsmOdNnmue1wPzvCnXn4Z5Xr+Z50mSpJ75oI/UQmZeydT9i/eIiIV97qY+Q+fkzLyj28Yy817ga7Xq+h7cE7aJiD9FxFsiYstWJ0TEwoh4AnA28ObKh+4C9s/MW2cZ0iKKWUOXRsRHI2KXiFhuupMj4v4R8SaKG62H1T78lsy8rsVlGr730vme81UvAv5RKT8UuCAi3hoR60x3URkGPC0iPg9cDnxgunMzM4HP1aq/GBHPb9Hugoh4LsVSstuw7Iya2fy0Vj6y/Fx2jojNI2Jx5dXJbKl2nUoRKk54LHBSRDyofmJErB0RHwJOoVhqeVRvtnehWK58wskNjUOSJEmSNEbM88zzNC3zvKnM8/rPPE+SpCHr942ONJccB+xUHq9JMQvoh9Of3r5y398X1Kp7Wea32sYrK+X9I+LgzLynxblbAUcAR0TENcCFTM4guj/Fnrpr1q65A9g3M3/WwZjWp1gS9g3A3RHxB+BKiiVSA1gd2BLYtCzXvSMzv9BBfxqgzLwyIj5Osexvt9fvTTHL7gFl9ZoUM1I+FBF/BC6l2Jt6eYo9qzcDFjP15+P6Wbr6KHAgk8vZrgx8uZzN9ivgNop9yR/F5M/5rcDLmLp3+WyfzxkR8SvgkWXVakw/u+Z0YPd2226z/xsi4n21PvcB9oqI8yi+lguBB5VjnJgddCvFcton9XM8ffKcyvFS4ItNDUSSJEmSNHbM88zzVGOet8znY57Xf+Z5kiQNmQ/6SNM7AfgwMLFU7XPpUzAAPBNYq1K+FvhRH9r9OfA3YKOyvC7wNGa/0VkPePws5/wBeGFm/qaH8S1HMePjoW2c+w/gtZk5ijcunVihVu50hskoOhw4CFi7m4sz87cR8TDg/5i6NG4A25av2cz4dczMW8vlfb/P1H3HNyxfdddR/F7+o8XHZrMvxfLU7e6n3VeZeUREbA68vFK9gGJf7B1bXPJPir3L/zaE4XUkIu4HPLtS9YPM7OZ7IkmSJEman8zzpjLP6455Xo15Xn+Z50mSpF65dZc0jcy8Hji2UrVvRKzSp+bry/yeWC7V25NyidMTZukL4Arg08CSNpr9NcUNx0M6DAVupgglPkURKixt45p7gZ9RzEzYZtxDgYjYlGI21YSLgW83NJy+ycybgff32MY1mfkk4HEUS7ne1sZll1Es4fsUJmfczNTHBeV5x1L8bLVyM/C/wIMz8+dtjKFVP5dShF0vBE6kWK76phn67LvMfEXZ/8UznHYt8N/Adpl5xlAG1rm9mJwZBvCxpgYiSZIkSRo/5nn/Yp7XJfO8Gdswz+sj8zxJktSLKO4jJLUSEVsAf2LyobiDMvMzDQ6p7yLiARTL+i6mWFZ1IcUyoJcB52bmFX3qZ1WKmR2LKWZkTOzZezPFTdSfgQsy885+9DcKIuJlwGcrVftnpsuWthARCylu4jenmFm0KsXe4TdRLFf7x8y8qof2V6MIIRZTLMd7LcUMmDMy846eBj9CIiKAB1N8LdcF7gOuAv4KnN2PAHKQIuJbwN5l8XeZuUOT45kQEdtRLIcOwP/73Le5/+ItGhxRf1295GI++bK9q1XbZ+bvmxqPJEmSJPXCPM88rxfmee0zz+sP87zBqOd5bzvuVDbYdMsGR9RfV156EYcf8JRqlXmeJM0zbt0lzSAzL46ILwH7l1Wvj4jP5hx6Qq688e/Lzf8s/dwCnFO+5ovq8sl/oj/7ts9J5Q3rL8rXINq/mTkw+2o25XvTBeVrrETE1hQzgCYc2tBQJEmSJEljzDyvr/2Y55nnTcs8rz/M8yRJUjfcukua3buBu8vjbSj2/ZXasUfl+L2Z2c5yx9J8dQiTf5eck5nfaHIwkiRJkqSxZp6nbpnnSe0zz5MkqSE+6CPNIjOXAB+vVL0nIvzd0YwiYluKJY0Bfk+x17OkFiJiK+D5ZTGBNzc4HEmSJEnSmDPPUzfM86T2medJktQsb26k9hxGsf8vFPtfv6jBsWg8VGf/HOrsH2lGRzC5neixmfnzJgcjSZIkSZoTzPPUKfM8qX3meZIkNWjh7KdIyszbImI/YM+yalGT49Hoy8yjgKOaHoc06iJiNeDXwG/KKn9vJEmSJEk9M89Tp8zzpPaY50mS1Dwf9JHalJlnAmc2PQ5Jmksy82bgvU2PQ5IkSZI095jnSVL/medJktQ8t+6SJEmSJEmSJEmSJEmSxoAP+kiSJEmSJEmSJEmSJEljwAd9JEmSJEmSJEmSJEmSpDHggz6SJEmSJEmSJEmSJEnSGFjY9AAkSZLGyXmXXc8qd17b9DD65tYrr296CJIkSZIkSdLA/OKSf7Lq7Vc3PYy+ueWKfzY9BElSw1zRR5IkSZIkSZIkSZIkSRoDPugjSZIkSZIkSZIkSZIkjQEf9JEkSZIkSZIkSZIkSZLGgA/6SJIkSZIkSZIkSZIkSWPAB30kSZIkSZIkSZIkSZKkMeCDPpIkSZIkSZIkSZIkSdIY8EEfSZIkSZIkSZIkSZIkaQz4oI8kSZIkSZIkSZIkSZI0BnzQR5IkSZIkSZIkSZIkSRoDPugjSZIkSZIkSZIkSZIkjQEf9JEkSZIkSZIkSZIkSZLGgA/6SJIkSZIkSZIkSZIkSWPAB30kSZIkSZIkSZIkSZKkMbCw6QFofoqIo4EDy+JXMvN5DQ5nTouINYBdgQ2BdYDrgMuBszLzxgH0txB4OLAdsC6wHHBr2edFwO8z895+9ytpsCLiNGC3iXJmRp/aXQ24hOL9AuCZmXlyP9qWJEmSJPWPed7wmOdJ6gfzPEmS5i5X9NHQRcSjgReVxbuBt89y/mkRkeXrtFnOXVw5t/7auocxHzdNm8d00MbCiHhIRLwsIj4dEedFxN3dttdGfw+LiJOAq4HvAJ8BPlD++x3gqog4KSIe2qf+toiIzwD/BM4BvgAcDvwn8DHgROB84OaI+EFEPLMf/bYYx4G1r+lpfWx791rbu/er7V50Oq6IOKbFz/K93fyOtGjrOd1+Hpo7WrwXHzjduZl5M3BYperjEbHSwAcpSZIkSWqbeZ55nnlef5nnadSY50mSNF580EdDFRH3A44CJp4c/5/MvGxI3b+4m4uieDr92d12GhH/ERFnATdT3Bh/FjiIYpbMom7bnaXPgyluzp9BMQOnleXLj58TEW/toa+FEXEY8Afg5cBqs1yyIrAnsG+3fWogFlAER+pALbjMpsczxj4NXFoebwwc3OBYJEmSJEkV5nnmeZjnjSrzvC6Y5/WNeZ4kSQ3yQR8N237AQ8rju4Ejh9j3/hGxoIvrngf08jT6k4BdKG6IBy4iDgE+yNTQ4Q7gDOArwM+AOysfWw44PCLe0kVfKwLfBN7F1K0AE7gQ+C7wZeCUsuwSv6PtmRGxc9OD0PxTLv99eKXqjRGxXlPjkSRJkiRNYZ43YOZ56oF5nhphnidJUrN80EdDExGLmLqc43GZefmAu72ncrwB8JQu2njJNO316kaKfa77JiL2Bt5Xq/4MsFFm7paZz8vMxwEbAZ+rnXd4RDy5g74COAHYq1J9J8X3+EGZ+eDMfGpmviAzn56ZDwZWp5h1dAJwVyefm4bm8NlPkQbiGOCK8nhl4J3NDUWSJEmSBOZ5LdyIeZ5Gj3memnIM5nmSJDXCB300TM8DNqmUjxpCnxeVrwkdLfcbEdsAO1WqvtXlOG6lmHnzMYpZUFsCa7HszXnXytlNH2ZyGWWAj2XmQZl5XfXczLw2M18OfLzaBPCRDmZJvQp4WqV8JfDwzHzPdIFPZt6emd/MzOcDL22zHw3X4yLiqU0PQvNPZt7N1PfEl0XEOk2NR5IkSZIEmOeZ55nnjQPzPDXCPE+SpOb4oI+G6U2V43My8/wh9Xt05XifiFi3g2urN683Aid10f9BwOqZ+bjMfGNmHp+ZF2dmv/f/PQDYqlL+M/D2Wa45uDxvwrbAC2brKCI2Aj5UqboTeEJm/rG9of5raU+NhpNr5Q9GhP8/qAmfBe4rj1ekCCAlSZIkSc0xzzPP+xfzvJFycq1snqemmOdJktQA//DTUETELkzu5Q3wxSF2fyyTf2guoo0bX4CIWAi8sFJ1PFP3wm5LZl6dmUs7va4LB9TKH8vMGZfTLT/+iVnaaeUdwCqV8vsz8w9tXKfR9GXg/Er5wcD+zQxF81lm/gM4o1L1CkMqSZIkSWqGeZ55nkaaeZ5GgnmeJEnNWNj0ADRvHFg5Xgp8fVgdZ+aVEfF9JveefjFTl7idzt7A/SvlLwCL+zq4PomItYHHVqruprjZa8eXKMKBRWV5t4hYKzOvn6avVSmWK55wG8uGCxovSTEb7HuVusMi4oTZwqV+iYi1gF2B9YF1KEK4a4HzM/P3wxjDKIqIRRRfl40ovjb3A36fmd+e5ZptKGYEbgCsSvH1vAG4FPhlZt4+4KH34kRgj/J4Q2BP4PvNDUeSJEmS5q0DK8fmeX1mnqcemeeNKPM88zxJkobBp2o1cOUe0c+tVJ2XmVcOeRhfqBzvEBGPaOOa6jK/F2bmr/o8pn7aE6juxX1eZt7SzoWZeTPw60rVwrK96ezL1Nk/X2+3L42uzPw+8JNK1UbAqwfZZxSeFxG/oAgBvkWx1OsHgY9RzBS8MCL+ERFvi4gV22z30IjIymv3Dsa0uHbtMTO1D+xW+1jO8Dqt3bFGxFoRcRRwFXAacBxwBMUS2+9r0c4GEfH/IuIHFAHAbylusD9Rnv9h4PPAT4GbIuJbEfHYejsj4pRaeb+WZ0mSJEmSBsY8byjM89QT87x/XWue1zzzPEmShswHfTQMuwJrVso/bWAMpwDXVcovnunkiFgfeHKl6gvTnTsitq+Vz+7w+rNq5e1mOHePWvmHHfal0fU2itlAEw6JiNUH0VFEbAqcR7GE9k7M/P/RhhQ3xH+IiJl+NueEiHg0cAHFftZrtXnZn4H/ogj1Vp7l3IUUMxzPiIiPlsuaj4zMvAK4qFK1l8v9SpIkSdLQmecNnnme+sE8bwSY55nnSZI0bP5Hq2F4cq38s2EPIDPvYeo+4vtFxPIzXPIiJre2q187iratlS/p8Pq/zNJe1Y618tkAEbFiROwXEadExF8i4o6IuDEiLomIr0bEK8plgjWiylluX6tUrQ28td/9RMSOwDnAw2of+ifwI+AE4CTgwtrHFwNnRsRD+z2mEbIpRZC5YVm+jWIG0AnAtykCgFbq/59fXV73DYr3r28Cvwfuq533Btpb+nzYqvt6rwO0M2tTkiRJktQ/5nmDZ56nnpnnjQTzvIJ5niRJQzRST/1qztq5Vj6/k4szc/c+jeMLwOvL4zWBZwBfmebc6gyhb2fmtX0aw6BsXiv/rcPr6+dv0eqkiFij1tfdwKURsRtwNLBJ7ZIVgNWBzYDnAB+IiMMy8786HN9IyMzTgGh6HHV9Htc7gGcy+f/D6yPiv/u1PHc5u+5kipu9CecA7wJ+lJlZO39z4EiK31cofp5OjIhHNLjE9MeBY8rjEyhmME2o/w5U3dlm26tSLNd7CHB0fV/1iGjVx1KKPdm/Cpw63fcrIjYAXgO8GViurH51RHw7M7/X6ppuZOYSevuZPL9W3gU4t4f2JEmSJEmdMc8bPPO8ITDP6515Xlttm+eZ50mSNFQ+6KNhqD65fWNm/qOJQWTm7yLivMp4XkyLYKBcZnOrStWoL/MLsEatfE2H19fPn2551/Vr5SuAZ1HsHdzOCmFrA5+IiEcBL87MezsapQYuMy+OiM8BryyrVgIOBQ7qUxefBzaolQ/KzPrMlInxXAI8MyI+Aby2rN6CYubKYX0aU0cy80bgRoCIuLP2sSU9Nr8qcD2wW2bWZ0BN9HFZi+od2um7DAzeERE/BU5l8u+AgymChVFxQa1cn3nYtYhYD1i3w8s261f/kiRJkjQmzPMGb41a2TxPXTHPm5153lCY50mSNERu3aWBKp/2r95k/rWpsZSqN/l7RsQDW5zzksrxVYzWH8vTWaVWvqPD6+vnT7ck7xot+v0ik+8lf6VYGnZXinBlF+AtwJLadS+k2KNZo+m9FEvMTnhJRGw13cntiohHAntVqs4GXjFdKFDzRqbeLL5mluW6x9nrpwsFptNpIJGZPwI+XanaLSI2nO78BtT/r9iyj22/imIZ6U5e3+xj/5IkSZI00szzhsY8T/1kntcs8zzzPEmShsoHfTRoi2vlRmb/VHyZyeU270exd/e/RMTKwL9Xqo4bk1kq9WCgnSVFq+rBQL29CWvUyutQLOcLxRKj22TmkZl5dmZelJm/yMwPA9uUH696U0Q8tsNxaggy8yrgY5WqhcD7+9D0a2vlQzJzaZtjug/4RKVqXYrgaa75O/ClIfX19Vp51yH1244rKJYvnrC4oXFIkiRJ0ny0uFY2zxsM8zz1jXleo8zzCuZ5kiQNkQ/6aNDWq5VvaGQUpXKJzpMqVQfWTvl3pt4UHz3gIQ1Kzn5KV+dP955xLrBfZraceZSZdwL7seyevO9ss18N3xHAdZXysyNip+lObtMTKsdXAad3eP1Pa+W5GCyd0m5Y0o6IWBgRa0TEgyJicfXFsr/32/Sr316Vgeytlap1IqJf+9ZLkiRJkmZmntcM8zz1yjyvGeZ5mOdJkjRsC2c/RerJSrVyp0vQDsLRwPPL480j4rGZ+bOy/NLKeWdn5p+GO7Su3QqsWSmv2OH19fNvbXnW9PVvnm2mVGbeGxFvBH5WqX5iRKyXmZ3uQa4By8xbIuL9TJ0J9CFgj27ai4jNmLqX9yXAxh3e6y1XK8/FfZZ/08vF5fLqzwWeBDwY2KiDy9ec/ZShuh1YrTwOiv9Pbpv+9LZ9imVnJM5mM1zuV5IkSdL8YZ43HOZ56ivzvMaY500yz5MkaUh80EeDVv8ZG4Vlc39EsV/sxmX5JcDPImJL4NGV875Qv3CENRkM/DUzz2ink8z8eURcCmxaqd6Nzv9I13B8Cngdk8us7h4Re2Xmd7to60G18mOAy3oYG8BaPV4/iroKySJiJeBQiu9XPUBp1+pdXjco9f8vFvWj0TKI7Ojr7OQjSZIkSfOMed5wmOdpEMzzhs88b5J5niRJQ+LWXRq0+oyfTm9Y+y4zEzi2UvXciFiFIiCYcDtw4lAH1pubauV1O7y+viTzjdOc16r+Fx32dU6tPDLLi2qqzLwbeFet+oMR0c3/HWv3YUh1qw6gzabd0ukF5fvX94C30H0oAKP3N0H9/4t+zP6RJEmSJM3OPG84zPPUd+Z5jTDPm2SeJ0nSkIzaHwGae26ulVduZBTLOprJ/WxXplj694DKx7+WmfWxj7KLa+WNW541vfr59fYm/BW4q1Z3ZYd9XVErD+KGUf3zJeC3lfIOwAu6aKeXG9bpOC2jcDhT9zdP4IcUs4EeQzGDa1VgucyMiRewybAH2qHq/xd3ZuY9jY1EkiRJkuYX87zhMM/ToJjnjT7zPEmS1BMf9NGg/b1W3qDlWUOWmUuA0ypVhzN1bEcPczx98MdaefMOr9+0Vq63B0Bm3gf8uVZdDwpmUz9/hQ6v1xCVM+beXqv+z4hYvsOmrquVP1O9Se3ytXvXn9j0FgygzYGJiA2AV1aq7gSenJlPzMz/yswzM/OvmXlrixvr1RhREbEmU98b6v+XSJIkSZIGxzxvOMzzNBDmeaPNPE+SJPWDD/po0JYwOdMG4IENjaOV6p7d1f2wLwVOH/JYenVhrbxLh9c/ulaut1d1Qa28Rod91c//Z4fXa8gy81Tgp5WqjYH/6LCZq2vlLXsa1Mzqe0Ev7ODaNWc/ZaTszdT/y4/IzB+0ee0DBjCeftmwVu51/3dJkiRJUvuWYJ43DOZ5GhjzvJFmnidJknrmgz4aqMy8k6kzRjaKiJWaGk/N11l2L2yAY8pZD+Pkh8B9lfIjIqKt/Y7L8x5eqbq3bG86362Vt2trhJO2r5X/0eH1asbBtfI7IqKTGSS/Z+rv2y7t/ox2ob5M9xodXNvpz3PT7xVb1Mrf7uDaXfs5kD7bplY+v4lBSJIkSdJ8ZJ43NOZ5GjTzvNaafq8wz5MkST3zQR8Nw7mV4/ux7I1hIzLzDuCEWvVS4Jjhj6Y3mXkd8PNK1XLAfm1e/gJgUaV8RmZeP8P532bqcr2Pioi12umoXL5zx1r1z9oapRqVmb+kCNMmrAO8tYPr7wN+XKlaHti/P6NbxjW18rYdXPvUDvuasnR1F0sg92qNWrlV2LmMiFgAvLDvo+mfHWrlXzYyCkmSJEmav8zzBsw8T4Nmnjct87zBMM+TJGmIfNBHw1BfNrd+Y9ikdwGPrbx2ysxx3Tv2uFr5DbPdpJQff32t+tiZrsnMW4CvVaqWB17T5hhfw9R9ev/KzMsKa7QcwtRldN8ArN/B9Z+sld9T7kndb7+ulfdp56KI2A54Vod93VgrD+LzmckNtfLWbV73GmCTPo+ln6r/TywFzmhqIJIkSZI0T5nnDYd5ngbNPG9ZN9bK5nn9YZ4nSdIQ+aCPhqG+NOwejYyihcy8NjN/Xnn9qukx9eBYpi6rvBXwgVmu+WB53oQ/AF9qo693AXdXyodExIz7iJcff2e9/zFcVrkjEbEkIrLyOrDpMXUrMy8CPl+pWgl4UgfXn8bUZaTXA74bEQ/sZBwRsWpEzDTD7WKgGvA9MiKeMUub9we+CizoZCzAH2vlJ3Z4fa9+Wyu/uZzdM62IeApw+OCG1JuIWAQ8ulJ1bmZe29R4JEmSJGmeMs8bDvO8EWSeN+X60zDP6zfzPEmS1DMf9NHAZeaVwDmVqj0iYmFT4xm2iFgYEYtbvVh2mc5Vpjs3IlaZqZ9yKdU3M3WP4TdGxP9GxNq1Ma0TEZ+hmMHxryaAN5XtzCgzLwOOqFQtD/wgIv6j/KO+/vkfBPyAYgniCb8Ejp6trz5YYYav6WyvNYYwvnHzXuD2Hq5/EVP3cX8ocEFEvDUi1pnuojIMeFpEfB64nBlCrzJs+lyt+osR8fwW7S6IiOdS/Dxuw7Izambz01r5yPJz2TkiNq/9PHUyW6pdpwK3VMqPBU6KiAfVT4yItSPiQ8ApFL+zo3qzvQuwcqV8ckPjkCRJkqR5yzzPPM88b04xz5vKPK//zPMkSRqyeXNzpsYdB+xUHq9JMQvoh9OfPqc8ELiszXOfXb5aeTGz7Deemd+OiHcC769UvwLYPyLOAa6iWIp0R2DF2uUHZ+b32hwnwLspZg89tyyvAnwK+EBE/AK4HlgL2JllA5DLgWdn5t0M3k60//Wvey9waP+GMv4y88qI+DjFsr/dXr83xczAB5TVa1LMSPlQRPwRuJRib+rlKX52NgMWA1FpaqZ95wE+ChzI5HK2KwNfjogjgV8Bt1HsS/6osn+AW4GXMXXv8tk+nzMi4lfAI8uq1Zh+ds3pwO7ttt1m/zdExPtqfe4D7BUR51F8LRcCDyrHODE76FaK94aT+jmePnlO5Xgp8MWmBiJJkiRJ85x5XnvM8/rPPK+PzPOW+XzM8/rPPE+SpCHzQR8NywnAh5m8GX0u8ycYGKrM/EBEJMVN7cRsnBWZ/obkHuBdmXnENB+frp+MiP0pbtAOqnxoDeDJM1z6S+CZmXlFJ/2NsRVq5U5nmIyiwym+52vPdmIrmfnbiHgY8H9MXRo3gG3L12xm/Dpm5q1RLO/7fabuO75h+aq7DngmU2cntWtf4Du0v592X2XmERGxOfDySvUCigBwxxaX/JNi7/K/DWF4HYmI+zE1HP1BZnbzPZEkSZIk9c48b0jM80aOeV6NeV5/medJkqReuXWXhiIzr6fYc3rCvrMtXavuZeYHKWa+fJOpe29X3V1+fMfM7Gp/38y8KzNfCTyBIuiZaZngCylmZOw6X0KBiNgUuH+l6mLg2w0Np28y82amzjLrpo1rMvNJwOMolnK9rY3LLqNYwvcpTM64mamPC8rzjgXunea0m4H/BR6cmT9vYwyt+rmUYsniFwInUuzzfdMMffZdZr6i7P/iGU67FvhvYLvMPGMoA+vcXkzODAP4WFMDkSRJkqT5zjxvuMzzRoN53oxtmOf1kXmeJEnqRRRbn0qDFxFbAH9i8gGzgzLzMw0OaV6IiDWBXSlmPaxN8fT/5cBZmdnX2SgRsS7F0r4bUCyjegtwddnXvHuKPyJeBny2UrV/ZrpsaQsRsZDiJn5zip/TVSn2Dr+JYrnaP2bmVT20vxpFCLGYYjneaylmwJyRmXf0NPgREhEBPJjia7kuRVh3FfBX4OzMHFpY0Y2I+Bawd1n8XWbu0OR4JkTEdhThJgC7vuM4Vtlg0wZH1F+3XnkpZ73/gGrV9pn5+6bGI0mSJGl0mOc1wzyvOeZ57TPP6w/zvMGo53m7vfuLrPqAuZPn3XLFpZx+2AurVeZ5kjTPuHWXhiYzL46ILwH7l1Wvj4jPpk+bDVR58/+dIfV1LfCtYfQ1Jh5fOf4T8OWmBjLqyhvWX5SvQbR/M3Ng9tVsyvfTC8rXWImIrSlmAE04tKGhSJIkSZJK5nnNMM9rlHlem8zz+sM8T5IkdcOtuzRs72Zy6dltKPbQleaqPSrH783MpY2NRBp9hzD5d8k5mfmNJgcjSZIkSfoX8zzNJ+Z5UvvM8yRJaogP+mioMnMJ8PFK1Xsiwp9DzTkRsS2wfln8PcVez5JaiIitgOeXxQTe3OBwJEmSJEkV5nmaL8zzpPaZ50mS1CxvyNSEwyj20gXYAXhRg2ORBqU6++dQZ/9IMzqCye1Ej83Mnzc5GEmSJEnSMszzNB+Y50ntM8+TJKlBC2c/ReqvzLwtIvYD9iyrFjU5HmkQMvMo4KimxyGNuohYDfg18Juyyt8bSZIkSRox5nmaD8zzpPaY50mS1Dwf9FEjMvNM4MymxyFJalZm3gy8t+lxSJIkSZJmZp4nSQLzPEmSRoFbd0mSJEmSJEmSJEmSJEljwAd9JEmSJEmSJEmSJEmSpDHggz6SJEmSJEmSJEmSJEnSGPBBH0mSJEmSJEmSJEmSJGkM+KCPJEmSJEmSJEmSJEmSNAYWNj0ASZKkcbL71uuxwaYPaHoYfXPl6rdyVtODkCRJkiRJkgZkj23W4wFzKM+7YvVbOb3pQUiSGuWKPpIkSZIkSZIkSZIkSdIY8EEfSZIkSZIkSZIkSZIkaQz4oI8kSZIkSZIkSZIkSZI0BnzQR5IkSZIkSZIkSZIkSRoDPugjSZIkSZIkSZIkSZIkjQEf9JEkSZIkSZIkSZIkSZLGgA/6SJIkSZIkSZIkSZIkSWPAB30kSZIkSZIkSZIkSZKkMeCDPpIkSZIkSZIkSZIkSdIY8EEfSZIkSZIkSZIkSZIkaQz4oI8kSZIkSZIkSZIkSZI0BnzQR5IkSZIkSZIkSZIkSRoDPugjSZIkSZIkSZIkSZIkjYGFTQ9AGoSIOBo4sCx+JTOf1+Bw5rSIWAPYFdgQWAe4DrgcOCszbxxAfwuBhwPbAesCywG3ln1eBPw+M+/td7/SfBcRS4CNy+JfM3Nxn9pdDPwJWB5YCuyYmef1o21JkiRJ0vgwzxse8zxpfjDPkyRp7nJFH805EfFo4EVl8W7g7bOcf1pEZPk6bZZzF1fOrb+27mHMx03T5jEdtLEwIh4SES+LiE9HxHkRcXe37bXR38Mi4iTgauA7wGeAD5T/fge4KiJOioiH9qm/LSLiM8A/gXOALwCHA/8JfAw4ETgfuDkifhARz2yjzWNqX59DZzn/wNr5i3v7rPqj03HVfuYnXjdGxNpd9F1v65FdfyKaMyJi99rPxe7TnZuZS4D/Lov3Az4VEf59IkmSJEnziHmeeZ55nnmemmWeJ0nSePE/Xs0p5R+TRwFRVv1PZl42pO5f3M1FEbEa8OxuO42I/4iIs4CbKW6MPwscRDFLZlG37c7S58EUN+fPoJiB08ry5cfPiYi39tDXwog4DPgD8HJgtVkuWRHYE9i32z7nqdWBdzQ9iHETEUsqN79Lmh7PGHs/xXsYwI5MzuCUJEmSJM1x5nnmeZjndcs8rwvmeX1jnidJUoN80EdzzX7AQ8rju4Ejh9j3/hGxoIvrnges1EO/TwJ2obghHriIOAT4IFNDhzuAM4CvAD8D7qx8bDng8Ih4Sxd9rQh8E3gXU7caTOBC4LvAl4FTyrJL/PbmVRGx8eynSf2VmTdQhLoTDo2IFZoajyRJkiRpqMzzBsw8b04zz1MjzPMkSWqWD/pozoiIRcBhlarjMvPyAXd7T+V4A+ApXbTxkmna69WNFPtc901E7A28r1b9GWCjzNwtM5+XmY8DNgI+Vzvv8Ih4cgd9BXACsFel+k6K7/GDMvPBmfnUzHxBZj49Mx9MMYvlGeV1d3XyuQkoZm0dNutZ0mB8lMlQ8UHAqxociyRJkiRpCMzzlnEj5nnqjHmemmSeJ0lSQ3zQR3PJ84BNKuWjpjuxjy4qXxM6Wu43IrYBdqpUfavLcdxKMfPmYxSzoLYE1mLZm/OulbObPszkMsoAH8vMgzLzuuq5mXltZr4c+Hi1CeAjHcySehXwtEr5SuDhmfme6QKfzLw9M7+Zmc8HXtpmP5rqhRHx4KYHofmnfB85sVL1xjLwlSRJkiTNXeZ55nnmeb0zz1MjzPMkSWqOD/poLnlT5ficzDx/SP0eXTneJyLW7eDa6s3rjcBJXfR/ELB6Zj4uM9+Ymcdn5sWZmV20NZMDgK0q5T8Db5/lmoPL8yZsC7xgto4iYiPgQ5WqO4EnZOYf2xsqZKbL/rbv5Mrx/Zj6tZeG6dOV4w2B5zc1EEmSJEnSUJjnmef9i3leR06uHJvnqUnmeZIkNcAHfTQnRMQuTO7lDfDFIXZ/LHBfebyINm58ASJiIfDCStXxTN0Luy2ZeXVmLu30ui4cUCt/LDNnXE63/PgnZmmnlXcAq1TK78/MP7RxnbrzMYoZVhP2iojdmhqM5q/MPBu4tFL1H02NRZIkSZI0WOZ55nnqiXmeRoJ5niRJzVjY9ACkPjmwcrwU+PqwOs7MKyPi+0zuPf1ipi5xO529gftXyl8AFvd1cH0SEWsDj61U3Q18uc3Lv0QRDkws2blbRKyVmddP09eqFMsVT7iNZcMF9dftwHuZOvvicGDnYQ0gIjagWPZ6PWBtiuWrrwHOzcxLZ7p2LouIFYHHUMyGuT9FCPnLzDxjhmtWoJhttxXF13MViu/xDRQz8s7LzLsHPPRefBV4W3m8c0RslZl/nukCSZIkSdJYOrBybJ7XZ+Z5c5553ogyzzPPkyRpGFzRR2Ov3CP6uZWq8zLzyunOH5AvVI53iIhHtHFNdZnfCzPzV30eUz/tCVT34j4vM29p58LMvBn4daVqYdnedPZl6uyfr7fbl3ryeabuT79TRDxrkB1GxKKIeGVEXABcQbHU9f8CHwD+CzgB+EtEXBQRryhnzbXT7jERkZXX4g7GtHvt2kNnah/YuPKhjWvX1l/HtDvWiHhQRPwfRTjyA4olxT8EHAm8sUU7m0bEwRFxBnATcB5FePdx4H3AR8s2zgJuiogvRcQO7X5dhuyUWnm/lmdJkiRJksaWed5QmOfNfeZ5mOeNCPM8SZKGzAd9NBfsCqxZKf+0gTGcAlxXKb94ppMjYn3gyZWqL0x37ojYvlY+u8Prz6qVt5vh3D1q5R922Je6UO6B/o5a9QfK4K3vyvDsT8D/AA+e5fQtKAKDcyNiw0GMZ5RExDOACyiWAl9l5rMhItYC/gJ8kGKm3nKzXLICxc32ryPiLT0NdjDOpZj5N2HvpgYiSZIkSRoY87zBM8+b48zzRod5nnmeJEnD9v/Zu+8wS6o6/+PvLww5I6AgwpAFFQMqwQQqhjWBYkJdB7Ouv12zghJURERM66K7BkAUxYCCAcQIIklEQJEcBiVIEIac+f7+qGqnuuZ29811b/f79Tz38Z7TVXW+3XSY+ljnHB/00WzwvFr75GEXkJn3MXkf8d0jYrlpTnk9i7fOq587iraqtS/t8PzLZrhe1ZNr7dOgWPI0InaPiB9HxGURcVdELIqISyPi++UMkVU6rEsVmfkD4IxK1xbAG/o9TkS8EPgdsHHtQ9cCP6eYuXIscEnt448DzoiI9ftd0wjZlmLm0+plexFFOPYd4HjgyhbntPpb/nfgVxTLnh8J/JTi5zYrxywNHBQR7+tD3X1T/j6tho+Pj4h1mqpHkiRJkjQQ5nmDZ543B5jnjQTzPPM8SZKGrq1lE6URV993+JxOTs7MHftUx6HAu8r3awC7AN+d4tjqDKGfZuYNfaphUDattf/W4fn14zdrdVBErF4b617g8oh4BsUypRvVTlkeWA3YBNiNYsbKxzLzvzusry2ZeThw+CCu3Ys+1/UhJs+i2y8ivpWZd/Xj4hGxFcWN74qV7p8D+2bmH1oc/3iKPd0n9pR/OPCdiNgxMx/oR01deB+wX/n+92VNAFdT7L89ldvbuPZXgeWAq8pxflD9PCMimLy88IT7gGOAHwK/yMybWl08IjYG3g+8FYiy+5MRcUJm/qWN+tqSmSdWrt+Nc4Bnl++D4vd8fQlgSZIkSdL4Ms8bPPM8zPP6cXHzvBmZ5xXOwTxPkqSh8UEfzQbV/bMXZeZVTRSRmX+JiLMq9exBi2AgIp5CMbNiwqgv8wuLZyNMuL7D8+vHrzbFcQ+rta8BXgp8j/ZWIHsI8IWIeBKwR7l8rTqQmSdGxM9ZPLNuPYrA65O9XjsilqL4mVip0r1fZn50mnrOjohnludN7DH+VOA1wBG91tSNzLyRcmnviKh+j92fmQt7vPwqwOXAM1r9LsvMBOpj3ArMz8xrZrp4Zl4OvD0izqAI26D4t8B7gQXdl913f661n0yfgoFyNtHaHZ62ST/GliRJkiT9i3ne4K1ea5vnzVLmeTMzzxsK8zxJkobIrbs01sq9sas3ma2WwRym6k3+zlMsSVpdOvUfFLMfRl19X+FOZ4PUj59qSd7VW4z7LRb/rroS+ADFPu5bANtTzGZYWDvvtcCBHdaoxT4IPFhtl/tG9+qlTN4f/nvThQITyoDn9UwOmEZqedo+W9BJwJmZ97YTCtTOOZxi+d8Jr4iIZTq5xoDVf5dv3sdrvwM4r8PXsX0cX5IkSZLmNPO8oTHPm1vM85plnmeeJ0nSUPmgj8bd/Fq7kdk/Fd8G7i7fL0VxM/MvEbES8IpK1xFjMkulHgzc3fKoqdWDgfr1Jqxea69FsZwvwPeBLTPz05l5WmZenJmnZ+bBwJblx6veGxFPQx3LzD9TfC9PWA3Yqw+X/s/qMBTLCrdb0+3A/1W6HhMR8/tQ06g5JTNPHtJYR1fer0CxZ/qoqP8un99EEZIkSZKkgZhfa5vnDYZ53hxintco87yCeZ4kSUPkgz4ad+vU2jc3UkUpMxcBP6p0Lagd8gom3xQfxnjKAR0/1e+kM4Hdp9pXOjPvBnYvj6v6SJvjakl7U+ypPuGdEbFBtxcrQ7HtKl1nZuYVHV7mt7X2bAx+junnxSJimYhYMyI2iIj51RfFPuBVW/Zz7B7Vf5fXf9dLkiRJksaXeV4zzPNmP/O8ZhzTz4uZ50mSpHbMa7oAqUcr1tqdLkE7CIcBry7fbxoRT6s80f/GynGnZeaFwy2ta7cDa1TaK3R4fv3426cZp5X3zTRTKjPvj4j3ANXZE8+JiHUys9M9yOe8zFwYEV8G/qvsWg74GN3v+7wdUF1K9vIuZvDUg6PZuM/y2b2cHBEbAa8EnkmxrPK6HZy+xsyHDM2dtfZKLY/qzpdYcsbgTDbB5X4lSZIkqV/M84bDPG+OMc9rjHlewTxPkqQh8kEfjbv69/AoLJv7K4r9aDcs228ATo6IzYGnVI47tH7iCGsyGLgyM3/XziCZ+fuIuBzYuNL9DDq/CVBhf2APYNWy/bqIODgzz+viWo+otV9VvnrRj33GR01XIVZEPAQ4iCK46Xa1vtW6PG8Q6r/L+7bfeBkUdvR1joh+DS9JkiRJMs8bFvO8uck8b/jM8wrmeZIkDZFbd2nc1Wf8dHrD2neZmcA3Kl0vj4iVKQKCCXcC3xtqYb25pdZeu8Pz68t0LpriuFb9p3c41hm19igtXzpWMvNG4NOVrqWAT3Z5uYf0XtESVhnANZt2W6cnRMS6FDPf3kBvf9dH6d8E9d/ldzRShSRJkiRpEMzzhsM8bw4yz2uEeV7BPE+SpCEapX8ESN24tdbu53KQvTiMxftYr0Sx9O+/Vz7+g8ys1z7KLqm1N2x51NTqx9evN+FK4J5a37UdjnVNrT2IG9K55HPAPyrtF0ZEN3tpL9uneqqcllH4GpMDsPuBHwFvo1hi+REUIcoymRkTL2CnoVfavvrv8nH6fSlJkiRJmp553nCY581d5nmjzzxPkiT1xAd9NO7+Xmt3sn/twGTmQuDEStenmFzbYcOspw8uqLU37fD8jWvt+vUAyMwHgItq3fWgYCb145fv8HxVZOYdFHt5V32qi0vdWGvvVb1J7fK1oKtPanpLD+CaAxMRTwb+rdJ1I7BtZr40M/8vM8/IzKsy8/bMrC+fuyqja71au/67XpIkSZI0vszzhsM8b44yzxtt5nmSJKkffNBH424hi2faAKzfUB2tVPfsru6HfTlw0pBr6VV9D+ftOzz/KbX2dHtC/7nWXr3DserH/7PD87WkrzJ51tb2EbFLh9e4rtbevKeKple/AZ7XwblrzHzISHlJrf2BzPxTm+fWb75HycNr7SsaqUKSJEmSNAgLMc8bBvO8uc08b3SZ50mSpJ75oI/GWmbezeQZIxtExIpN1VNzNEvuhQ1weLnv9zj5JfBApb1NRLS1n3J53BMqXfeX15vKcbX2o9qqcLFH19pXdXi+asqZIx+udR8QEZ3MljmNySHezhExqKV668vCrt7BuZ1+vzX9s7xZrf3TDs7doZ+F9NmWtfY5TRQhSZIkSeo/87yhMc+bw8zzptX0z7J5niRJ6pkP+mg2OLPyfimWvDFsRGbeBRxV634QOHz41fQmM28Efl/pWhbYvc3TXwMsU2n/LjNvmub4nzJ5ud4nRcSa7QwUEWsAT651n9xWlZpWZn6fyT9rWwJ7dHD+DcDZla6HA8/vT3VLuL7W3qqDc/9t5kMmqX6vLtfhuf2weq3dKoxcQkSsBuzS72L6aOta+w+NVCFJkiRJGhTzvAEzz5N53pTM8wbDPE+SpCHyQR/NBvVlc+s3hk3aG3ha5bVtZo7r3rRH1Nrvjohpb4TKj7+r1v2N6c7JzNuAH1S6lgPe2WaN72TyHt5XMv2ywurMB2vt/YAVOjj/f2rtgyNi5Z4qaq2+1O2L2jkpIp5L578/FlXerxURy0x14IDcXGs/ss3z9gPamsXXkOp/h0U4A0iSJEmSZhvzvOEwz5N53pIWVd6b5/WPeZ4kSUPkgz6aDepLw+7USBUtZOYNmfn7yuuPTdfUg28weVnlLYADZjjnk+VxE84HjmxjrL2BeyvtvSJi2n3Ey49/pD5+08sqR0TWXjs2WU8vMvO3wAmVrofT2Y30EcCFlfaWwI/KmVtti4i1I+Kl0xxyGnBnpb1rRDxxhmtuxgyh1RQuqLyfx/B//5xba39ophMi4o3Afw2mnN5FxHpM3vP9hMx8YKrjJUmSJEljyTxvOMzzumCeN4l5Xv+Z50mSpJ75oI/GXmZeC5xR6dopIuY1Vc+wRcS8iJjf6sWSy4CuPNWxM83EKP9h/j4m72H8noj4v4h4SK2mtSLiK8C7q5cA3tvOP/Az8wrgoErXcsAvIuLt9RkW5ef/VuAXFEsQT/gDcNhMY6ljH6LLfazL//a7MXnP7WcDfy7/2045IyUi1oyIV0bEd4C/A/85zTi3Ad+tdC0N/CwintPiustGxJuB04GHsuSMmpn8ttY+LCLeERHbRMTGtZ+xtTq8djt+AFR/pl4dEV+t/0wCRMT6EfFV4GtAADcMoJ5+eHatfUwTRUiSJEmSBsc8zzzPPG+ozPMmM8/rP/M8SZKGbM7cPGnWOwLYtny/BsVT+L9srpyhWh+4os1jX1a+WtmDGfYbz8yfRsRHgE9Uut8CvC4izgD+AaxLMSukvgTshzLz523WCbAPxeyhl5ftlYEvAQdExOnATcCawHYsGYBcDbwsM+9FfZWZ55Q35+3u6V4//68R8TKKG9rVyu71Kf7bfjEi/gL8jSI8WJHiv+3m5TGd2BvYlcXfG+sAJ0TEpcCfKfbifijF742VymP+QbGccSczgb5P8fMwUd96wCFTHPsNYEEH155RZl5chnBvr3S/ieJn8g8UIcrywMbAYykCASg+1/cD3+xnPX2yW+X9LRgMSJIkSdJsZZ7XHvM89cQ8bwnmef1nnidJ0pD5oI9mi6OAg1l8M/py5k4wMFSZeUBEJPBRYGI2zgrAjlOcch+wd2YeNMXHpxonI+J1FAHAWysfWh143jSn/gHYNTOv6WS8QYiI5Vt0dzrDZBR9hOLmbdmZDmwlM39VLr37HaC6BO/SwOPK10ym/Tpm5tVlAHEMk/eu3rR81V0BvIAiLGhbZt4VEbuW4zy8k3P76F3ABhT1T1gOeNoUxy8EXgisPdCquhARqwHVmVrfycy7m6pHkiRJkjRQ5nlDYp7XPvO81szz+u5dmOdJkqQeuHWXZoXMvInJT+2/cqala9W9zPwkxcyJY5m893bVveXHn5yZn+pynHsy820US3/+kslLmtadRzG7YodRCAVKO9Tav83M+h7MY6dcivl/e7zGpRQzxV4E/IpiRs5MLgC+SHHDO92e3hNj/KYc41imXp74BuDTwOMy84IpjplpnD8CWwFvowgILqWYwTSUfajLmW4vpggIpvve/ztwAPDYzPzrEErrxusoQg0o/pt9ocFaJEmSJEkDZJ43XOZ5bTPPm/oa5nl9Yp4nSZJ6FZldbc0qjZyI2Ay4kMUPsL01M7/SYElzQkSsQXED/HDgIcA/KZbaPTUz+zrbJSLWpljad11gLeA24LpyrKv6OVY/RMT+wIcrXU/LzN83Vc8oK2dLbQtsSPF9tBJwB8VMn0uBCzLznz1cfy3gGRRL8q5I8X1zBXByZt7fW/WjIyLmAU+gmEX1EOBuimV9LwX+mCP+R79c6vnRZfMnmfniJuuZEBGPoggfAdjrmz9n3Y03b7Ci/rr28os54HWTJlY+eoTDI0mSJEmziHleM8zzpmae1z7zvP4wzxuMep6333d+wXqzKM+75vKL2e/V1YWUzPMkaa5x6y7NGpl5SUQcSfEEOcC7IuKro/4P4XFX3vz/bEhj3QD8ZBhj9ckzK+9/aSgwtXI515MGeP0bgaMHdf1RUYYcfyhfYyUinsPiUGBiOXFJkiRJ0ixmntcM87xpmee1yTyvP8zzJElSN9y6S7PNPixeenZLYNcGa9EcVi41/aRK1z5N1SKNiY9U3n8/M89qrBJJkiRJ0jCZ52kkmOdJHTPPkySpIT7oo1klMxcCn6907RsRfp+rCU9n8appx2fm6U0WI42yiHgWxV7tUCxPvFeD5UiSJEmShsg8TyPEPE9qk3meJEnN8oZJs9HHgL+V77cGXt9gLZq7dqq837exKqQRV4a3B1e6DszMy5qqR5IkSZLUCPM8jQLzPKkN5nmSJDVv3syHSOMlM++IiN2BncuuZZqsR3NTZr4feH/TdUhjYH3g2PL1AHBQs+VIkiRJkobNPE+jwDxPapt5niRJDfNBH81KmXkKcErTdUiSppeZfwP2a7oOSZIkSVKzzPMkaTyY50mS1Dy37pIkSZIkSZIkSZIkSZLGgA/6SJIkSZIkSZIkSZIkSWPAB30kSZIkSZIkSZIkSZKkMeCDPpIkSZIkSZIkSZIkSdIYmNd0AZIkSePkjwtvZrX7bmi6jL655eqbmy5BkiRJkiRJGpi/XHULV8dNTZfRNzdddUvTJUiSGuaKPpIkSZIkSZIkSZIkSdIY8EEfSZIkSZIkSZIkSZIkaQz4oI8kSZIkSZIkSZIkSZI0BnzQR5IkSZIkSZIkSZIkSRoDPugjSZIkSZIkSZIkSZIkjQEf9JEkSZIkSZIkSZIkSZLGgA/6SJIkSZIkSZIkSZIkSWPAB30kSZIkSZIkSZIkSZKkMeCDPpIkSZIkSZIkSZIkSdIY8EEfSZIkSZIkSZIkSZIkaQz4oI8kSZIkSZIkSZIkSZI0BnzQR5IkSZIkSZIkSZIkSRoDPugjSZIkSZIkSZIkSZIkjQEf9JEkSZIkSZIkSZIkSZLGwLymC5B6ERGHAQvK5ncz81UNljOWImIpYFtgY2A94F7gauCvmXlBH8dZBnhM+VoTWBG4HbgROBc4PzMf7Nd4kvorIhYAh1W69sjMw/t07a8Aby6bx2bmLv24riRJkiRp9Jjn9c48T1I7zPMkSZq9XNFHYysingK8vmzeC+w5w/EnRkSWrxNnOHZ+5dh+vFZv83N6eETsEhGfiIgTIuKf9Wu1c502x1o5Ig4E/g6cCnwLOAj4PPB94PyIODci3hIR0cM4j4qIrwE3A2cBhwOfBfYvx/oW8Bfghoj4bEQ8YobrXVz7mryr29paXPvo2rW/1OKYhZWPH96vsXvVSV0RseMU36f7dzFu/Vo/7fqT0KzSye9cYB+KoBDgJRHxgsFWJ0mSJElqgnleb8zzWl7bPK/zcc3z1JJ5niRJ48MHfTSWopi1cggwccP65cy8osGSuhYRj4mIH0fEtcBVwI+AvYDnUMyUGcSYT6aYdfNBilk/U9ka+D/ghIhYp4txPgKcDbwRWGmGw9cE3g38NSJeP81xh9bae3RaVysRsRbwolr31/tx7THy7ohYt+kixklELKgFIwuarmkcZeY/gM9Vur4QxaxBSZIkSdIsYZ7X85jmeTXmeYB5XsfM8/rDPE+SpGb5oI/G1e7AY8v39wKfbrCWXm1CcUP6sGEMFhFbASdQLO1bdR5wNHA8xVK/VTsDP4uIFTsY5zPAx4H6P+6vAH4MHAkcB1xX+/gqwGER8cYpLv0N4P5Ke+uI2Kbduqbxulqt52bmWX247jhZEdi36SI0Z32exbOANgHe0lwpkiRJkqQBMM/rknnelMzzzPPUrM9jnidJUiN80Edjp3wq/GOVriMys34jOwgb9fC6tYvx7gcu6rnqiohYCfgZsHql+0Jg28x8TGbulpn/BmwIvAa4rXLcE4GvtTnOzsB7at1/AZ6SmRtn5ksy87WZ+QJgXWAX4JrqJYD/iYiN6tfOzGspwouqN7RT1wzqM4nm2uyfCW+MiM2bLkJzT2beRDHjcMJHOgkjJUmSJEmjyzyve+Z50zLPK5jnqRHmeZIkNccHfTSOXkVxsz3hkGEMmpkLe3g9OMPlHwQuAI4A/hPYgWImzPP6/Gm8B5hfaV9KcbP+h+pBmflAZn4beBZwX+VDr46I7dsY58O19oXAUzPz1PqBWTgWeApwY+VDywMfmOL69Zv2V0fEcm3U1VJEPBF4TKXrHooZSnPRPOATTRehOetLQJbvHwYsaK4USZIkSVIfmed1zzyvBfO8Sczz1CTzPEmSGuCDPhpH7628PyMzz2mqkD75NbBaZm6Vma/PzC9m5mmZeXc/B4mI1YH31brfVD5131JmngkcUOue9qaxHOepte4PZea0s6AycyFwYK27vsf2hJ8B/6i01wB2ne76M6jPIDpmuq/LLHQy8M9Ke7dy33dpqDLzcuCXla53R4T/VpEkSZKk8Wee1wXzvGmZ55nnaQSY50mS1Az/2GqslLNPHlvp+lZTtfRLZt6WmbfPfGTPXgKsWmmfnpkntXHeF4BqSLFTRDximuM3BJautO+j2EO8HcfW2g9vtdRnZt5PMVuqqr5Ub1siYnng1bXuubbM760sGfjUQxppWKqz7zYFdm6qEEmSJElS78zzemKe14J5HmCep9FinidJ0pDNa7oAqUMLKu8fBI5uqI5xVJ8hc1g7J2XmzRFxLPDK2rX+e4pTVqq1b+xgNtPfW/StDtzZov9QJi8F/OyIeERmtrrGdHZl8h7nV1LMypprvgT8F0WwA0UA9LzM/PkwBo+IecCTgY2BtYHlgBuAhcAp/Z4RN04iYgvg0cC6wGoUS2IflZm3THPOI4AtKb6eq1KEdTcD11PMnLx60HX34FjgXmDZsr2A9sNFSZIkSdLoWVB5b57XGfO81szzCuZ5I8o8zzxPkqRB80EfjY2IWBp4eaXrrMy8tql6xkm5VGb9KfoTO7jEiUwOBp7P1MHAP2rt5TsYp35sUtzMLCEzL4qI37N4WeGlgNcD+3cwHiy5zO9hbezBPutk5j0RsTeTZ1YdGBEnZGZOdV6vImJL4CPAC5k8Q63qroj4MbBPZl7cxjXnA1dUur6RmQs6qOlE4BkT7cyMGa5fdVhETBe6bVQuaz1jrRHxRuA/ga1bXOcM4JzKdZYFngu8DHgmMN0sPSLiYorZfYeOWuiSmbdExEks/p21S0SsmJmtAkJJkiRJ0ggzz+ueed60zPMwz6udfyLmeY0xz5MkafjcukvjZAeKvZsn/LapQsbQxkB1ydyb2rnBqji11n7UVAeWe/JWZxesUd78tGObWvuvmXnXNMfXl+RdEBHR8sgWImIDipuoCQ8Ch7d7/ix0JPDnSvuxwGsGMVBELB0RnwPOA3Zn6lAAYAWKYOqvEfFfg6hnlETEKhHxE+BrtA4FWjkY+DFFODZtKFDaHDgEOD0iNu6q0MGq/n5fHnhWU4VIkiRJknpintc987wWzPOWYJ43AszzAPM8SZKGygd9NE6eV2uf3EgV42mrWvvSDs+/rNZ+RESsMs3xX6q139nmOPWbvm/McPz3gdsq7U2Ap7c5FhRLiFZ/D/46M6/s4PxZpZz5tGet++Pl7JK+iYgVgOOAdzH5638fcCbwI+Aoipln1Vkf84DPR8R+/axnxATF9/0Ly3YC5wLHAN+jCOnua3Fe/e/5ncBZwE+BbwM/AH7P5J8XKMKf30bEmn2ovZ9+V2vXf/9LkiRJksaDeV73zPNaW4B53r+Y540E87yCeZ4kSUPk1l0aJ9vV2ud0cnJm7ti3SsbPprX23zo5OTPviIibgOrNw6bA2VOccjDFXtlPLNvvjohzM/ObrQ4uZ+3sB7y40n0B8D9t1HUU8OZK9xuAk6Y7rzLmglp3fUZRqzHnz3RME/pVV2YeVy6zOrHU7Xzg7RTLwvbLIcBzKu1bKP77fz0zJ924liHCOyiWcJ5YCnqfiDgjM4/vY02duArYqHy/G/DpysfeT3ETPt2509kVmAjdvgHsXd+nPiLWAu5pce5lFEs1/ww4u9WS1RGxDLALcCDFzECADSjCvFfNUFtHevydey5FKDIxo2/7ngsqRcQ6FPvGd2KTfo0vSZIkSXOMeV73zPNaj7mg1m2eZ57XDvO8NpjnSZI0PnzQR+Okugzsosyc6R/YfdXBcrV1N2Xmrf2spQur19rXd3GN65kcDKw21YGZeW9EPJdixsKzKGYnHBERr6FYTvYvwO1lXU8E3sjiEAGKGUrPb3Ov4a8zORjYLSLeWb/BbGFHFt/cAdxEMctC8EHg9Er7IxFxaBtf0xlFxMuBPSpdVwI7Vve5riqXev5MRJwG/JoiHAjgvyNiiyb2X8/M+4GFABFxY+3DN071ubRpIhTYKzM/OcX49TEBDgL+c6avR2beB3w/In4F/AZ4XPmhl0fEXuVS3Y3LzNsj4goWhxePiYjl+7T/+DuAfftwHUmSJEnSzMzzurd6rW2eZ543HfO8aZjnDZ55niRJw+XWXRoLEfEwJt+INrEc6xVdvt7QQK11K9fa0+2TPZX6OdMt9Utm3gTsTLEX80nAA8BzKWYonA1cQrGs65dZHArcAXwGeEK7S+5m5hnAXytdK5ZjzqT+3+VbmdlqVsWcU35Nf1jpWgv4QK/XLWdd7VPpuh94cTs30pl5au3cTSlmssxGv54qFJhKZv6tk5AkM28G3lTpWgp4dSdjDkH1d8A8FocEkiRJkqQxYJ7XM/O8JZnnTcE8r3HmeQXzPEmShsQHfTQu5tfaQ539MwvUg4FunqKvBwP1a7ayFLA0cC8w003LTcCHgY93MdPk0Fp7j5ZHlSJiVeClM1xjrtuL4sZ9wrvLgK4XOwGPrrSPzMw/d3D+IUz+3n3xVAeOuQOHMUhmnsXkm+8dhjFuB+q/5+c3UYQkSZIkqWvza23zvM6Y51WY57XFPK855nkF8zxJkobEB300LtaptW9upIrZIwd9TkRsBZwFfJtiJtAyM5yyJvB54O8RsWdELN3BcN8E7qu0d4iILaY5/lUUM4UmnJWZ53Yw3qyXmRcxOSxZickzcLqxc6393Q5ruhP4Q6XraT3WM4puo1iCty+isHJErBsR8+sv4IbK4Vv2a9w+qf+er/8d6NaXKAKqTl4v6dPYkiRJkjSXmOf1l3meed60zPMaY563mHmeJElDMq/pAqQ2rVhrd7NUbU8yM4Y9Zh/dXmuv0MU16ufUr/kvEbE18Fsm7wF+E8Wyvj8FLmTxnt6PAXal2Nd7RYolhA8AnhIRL2tn+d3MvCEifgy8rNK9B/ChKU6pL/P79ZnGmKM+CryWxT9/b46Iz2XmJV1e76m19k3lzWknbq28nx8RSzWxr/cAndvL5xMRywLPoZjh9gTgkcBybZ6+RrfjDsidtfZK/bhoZl4PXN/JOcUq1ZIkSZKkDpnn9cY8bzLzvPaY5w2fed5i5nmSJA2JD/poXNS/V+9veZSmMrRgICKWB77H5FDgDGCXzPxH7fAbKQKE30bEIcBxLN639wUUM4Le3mZ9X2dyMPDvEfHhzHygVt+WwLaVrruA77Q5xpySmddExBeAPcuuecAngFd0eclH1Nqnd1tbaSmKcOmmHq8zSjq6Ya2KiJcAnwM26vISq3U79oDUf8/PNItQkiRJkjRazPN6Y563uD7zvDaZ5zXCPG8x8zxJkobErbs0Luozfrq5sZ3Lbqm11+7iGvVlNhdNcdzrgeoyu/8EXtgiFJikXFr2BUxesvdt5WyidpzA5D2A1wWe1+K4+uyfozNzUZtjzEWfovhvOGG3iHhil9d6SB/qqVtlANdsUqf72QMQEe8CjqH7UABg1Ka51H/P39FIFZIkSZKkbpnn9cY8bzHzvM6Y5w2Xed5i5nmSJA2JD/poXNxaa/dlycc5pL4064adnBwRK7LkTd2lUxz+8lr7fzLzxnbGycwLgaNq3QvaPPdB4PBa96QQICLmAa+rHeMyv9PIzFsoll6eEBRhQTeW7b2iJYzazezQRcS2wGdq3Qsp/ru9ENiKYkbeCsBSmRkTL+CkYdbaofrv+frfAUmSJEnSaDPP6415HuZ53TDPG33meZIkqVc+6KNx8fdae91GqhhfF9Tam3R4fv34qzJzqpkKj621f93hWL+qtbdteVRrhwJZab8oItaqtF8APLTSvpzRvjEaFYcAf6u0nxkRz+3iOtWA6G5qN6ldvhb28olNYekBXHOQ9mXy3/OvAJtl5ocz82eZeUFm3pyZd2dm1s5ddXhldmy9Wrv+d0CSJEmSNNrM83pjnlcwz+uOed5oM8+TJEk98UEfjYuFTL7hW7+hOsbV5cCdlfZDImLzDs5/Sq193jTHrl5rT7vEbwv149dqeVQLmXkFxR7hE5YBXltp15f5PbTFjZJqMvMeYJ9a94ER0ensm+sq75cHNuipsKnV94Ke1+H5a/SrkEGLiJWAZ1W6Lgf+IzPrX4OpjHLI+vBa+4pGqpAkSZIkdWsh5nm9MM8rmOd1wTxvdJnnSZKkfvBBH42FzLwbuKjStUG5/KzakJkPsOTMmh07uET92OOnOXZRrd3psswr19q3d3h+fenePQAiYh3g3yr9D7Dk0sCa2jeBv1TajwNe3eE1Tq21n9NLQdOoLwm7ersnRsRydDZDrulgaUMmL6H883ZDgYjYGHjYQKrqURk6bVHpuj4zr22qHkmSJElS58zzemOeZ57XB+Z5rZnnDYB5niRJw+WDPhonZ1beLwU8uqlCxtSPau092jkpItYAXlzrPmaaU66ptR/fzjgV29Tanc4g+iFwc6W9dURsA/w7k2eCnJCZV3d47Tmr3DN9r1r3x+lsn+4Tau039VTU1G4D7qq0t+rg3GdRzE5q1z219nIdnNsPq9fat3Rw7oL+ldF3GzM5JPxDU4VIkiRJknpintcb8zzzvK6Z503JPG8wzPMkSRoiH/TROKnvvfzkRqoYX8cweWbEdhHxjDbO+09ghUr7t5n5t6kOBk6std/cVnVARKxAcQNfdXK758O/Zot9u9b9BpYMQuozhTSDzPwp8LtK18bA2zq4xPHAZZX2kyOivvxyz8rlm8+pdG0UEY+a6byIWAr4cIfDLaq1h7107s219iPbOSkiNqT42R5V9d/vJzZRhCRJkiSpZ+Z5vTkG87wq87wOmee1tKjWNs/rD/M8SZKGyAd9NE6Oq7V3aqSKMZWZi4CDa91fK2f4tBQRT2LJWR8z3Th9t9bePiJmvNkqb8r+l8n7tT/IkjOX2lG/6X8Tk2eB3AD8pIvrdiwi9ouIrLxOHMa4A/TBWnvXdk8sl6Ct7w3+5Yh4aadFRMSzy6Vqp/LrWnv/Ni57ELBDh6VcUGsPavniqVzG5OWwXxgR086OjIi1KGbKrTbIwnpU//3+s0aqkCRJkiT1yjyvB+Z55nl9Yp43mXneYJjnSZI0RD7oo7FR7ud6RqVrp4iYN9Xx/RYR83t4rTrDtR/W6jwm3yTPVEc7e/N+FlhYaW8KnFoGANUxloqIV1PcXFWXcv1OZp423QCZeSpL3nTvHxHfiohNW51TLsX7S5ac/XNYZl7U4pRpZebZwNmVrvpytN/MzPs6va4gM0+nu7Bm4vxvA4dWupYFjo6II8vvg5YiYumIeHxE7BsR51N8v2wwzVCHUgRLE3aJiENbBWERsWVEHAu8t+xa1OanQ2ZeCVxe6dq+/FyeFxFbtPg57evvrMy8l8lLby8DnBARz6sfW34NX0axbPoTKPYj/2c/6+mjZ1feX5SZFzZWiSRJkiSpa+Z5M9Zhnre4BvO8ATHPm8w8b2DM8yRJGqKh3VRJfXIEsG35fg2Kp8R/OaSxr+jh3HcDn5/m40cB7Sy7O10dJwE7TndiZt4RES8ATmXx0/+PBP4QEX8BLqbYz/ixLBlK/JH292B+I8USvVtU+l4D7B4RFwIXAXcAqwJbAxu2uMZZwHvaHK+VrwP/M8XHDp2iX+3Zi2Kf96W7PP9tFD+/1dlDu1N8f9wAnEtxw/ogxffIesCWdLDXdmZeERGfAd5f6d4DeHVEnAZcC6xE8T1aXR73AOAptP/zCPA54Iv1z2WKYzdicjjXD/sBu7B4D+z1gOMj4kqKgOxOYC3gSRRf9wkHAE+ls8914CLiCRRfpwnfaKoWSZIkSVJfmOeZ57XLPG9wzPMmM8/rI/M8SZKGzwd9NG6OoliudmKP6ZczvGBgVsjM8yPiuRT7XleXSn1M+WrlV8BrMvPONse4ISKeCRzG5KVPg+IGb8sZLvFD4C2ZeesMx03nSIrvlfrN5OmZ+dcertup+vj1PZjHTmZeGBGH0X5QVD//vnImyvuBjzL5a7Q2k2d/TOU+inBpOh+hmOVWDSCWZ+plwj+VmR+OzpdjPgR4FJ3tb943mXlZROwG/IDF4QAUgVur0A3g05n5kS4+12F4ReX9/RSBsCRJkiRpfJnn9cg8zzyvV+Z5SzDP6y/zPEmShsytuzRWMvMmJj8N/sqIWHmq49VaZp5BMcvnUxQzIabyF+CtwHMy8/oOx7gmM59LcVP2C+CBGU65D/gx8PzMfFlm9rQEabmH+Q9bfGjYs3/qe0R/bsjjD8q+wF3dnpyFgyhmehwIXNnGabcBxwH/AaybmWfOMMa9wG7A/wP+MdVhFLPnds7MD7VZfn2czMy3U8xO/AJwGnA9cHc31+uyhhOAJwLHUnxOrdwPnAA8KzM/MKzaOlEuhVxd8vv7mXl1U/VIkiRJknpnntcf5nlDZZ7Xgnlef5nnSZKkXkTmVP9+kEZTRGwGXMjiB9XemplfabCksRYRSwHbUcwGWg+4F7gGOC8zz+/jOCtR7CO8KcVyoysCt1Psn3whcE5mDu1GahgiYkWKGT8Te4r/OjPbmd0yJ0XERhTfI2tTfI88SBEGXEPxPXJJZs4UME117aUobpy3plj29i7gauDMcl/uWSMiHkqxhO8GFLMlb6AIAE/PzBubrG0m5cywH1S6npiZZzVVz4SIeBRw3kT7OR//Dqs9fONpzhgvt1x9Ob/Y+9XVrkcPeaakJEmSpFnOPK+/zPMGxzyvM+Z5/WGe13/1PO9ln/4+az5ikwYr6q+b/n4ZR7//5dUu8zxJmmPcuktjJzMviYgjgdeVXe+KiK+mT611JTMfpNjj+9QBj3MHxT7fJw9ynBHzVBaHAgD7NFXIOMjMK5h6z/per/0g8IfyNatl5nXA0U3X0aX3Vt7/ZBRCAUmSJElS78zz+ss8b6DM8zpgntcf5nmSJKlTbt2lcbUPxUwVKPaH3nWaY6WmPLPy/oTMHGj4Io2ziHgmsH3ZfBDYq8FyJEmSJEn9Z56ncWCeJ7XJPE+SpOb4oI/GUmYuBD5f6dq3XMpTGiXVYMDZP9L09qu8/3pmnjfVgZIkSZKk8WOepzFhnie1b7/Ke/M8SZKGyBspjbOPAX8r328NvL7BWqRJImJViv2pAX6WmbN+iVmpWxGxK/C0svlPYM8Gy5EkSZIkDY55nkaWeZ7UPvM8SZKaNa/pAqRuZeYdEbE7sHPZtUyT9UhVmXkr/o6V2rUK8NHy/SmZ+c8mi5EkSZIkDYZ5nkaZeZ7UEfM8SZIa5D9aNdYy8xTglKbrkCR1LzOPaLoGSZIkSdJwmOdJ0vgzz5MkqVlu3SVJkiRJkiRJkiRJkiSNAR/0kSRJkiRJkiRJkiRJksaAD/pIkiRJkiRJkiRJkiRJY8AHfSRJkiRJkiRJkiRJkqQxMK/pAiRJksbJq7ZZn40237jpMvrmiovv5RdNFyFJkiRJkiQNyKse/3A22WKjpsvom8suupujmy5CktQoV/SRJEmSJEmSJEmSJEmSxoAP+kiSJEmSJEmSJEmSJEljwAd9JEmSJEmSJEmSJEmSpDHggz6SJEmSJEmSJEmSJEnSGPBBH0mSJEmSJEmSJEmSJGkM+KCPJEmSJEmSJEmSJEmSNAZ80EeSJEmSJEmSJEmSJEkaAz7oI0mSJEmSJEmSJEmSJI0BH/SRJEmSJEmSJEmSJEmSxoAP+kiSJEmSJEmSJEmSJEljwAd9JEmSJEmSJEmSJEmSpDHggz6SJEmSJEmSJEmSJEnSGPBBH0mSJEmSJEmSJEmSJGkMzGu6ACkiDgMWlM3vZuarGixnLEXEE4DNgIeXXVcDF2fm2X0cYxlgW2BTYG3gQeAa4DLgzMzMfo0lafRExALgsErXHpl5eJ+u/RXgzWXz2MzcpR/XlSRJkiQNhnle78zzJA2aeZ4kSbOXK/qoURHxFOD1ZfNeYM8Zjj8xIrJ8nVj72ILKxwb5WjBNfWtHxPMjYp+I+ElEXNvi/Pm9fdX+NdYyEfGhiLgUOAs4CvhM+ToK+FNEXBIRHyxv6rsdZ8OI+CrwT+BkihuDg4CDgW8DZwB/j4gDI2KV3j6rtmta2OLrenlELNuHa63VwfGHd/1J9FkndUXEjlN8b+/fxbj1a/20609Cs8p0v69b2Ae4vXz/koh4wWCrkyRJkiR1yzyve+Z55nlV5nkaNeZ5kiSNDx/0UWMiYingECDKri9n5hUNltSViFgvIr4fEQuB64HjgI8CLwQeNqAxNwNOBz4JbDLNoZsCBwKnRcSmXYzzJuBi4E3AdDf9Dwc+CPwlIp7e6Th9shHwtobGni3eHRHrNl3EOGkRSC5ouqZxlJn/AD5X6fpCL4GmJEmSJGkwzPN6GtM8b0nmeb0zz+uQeV5/mOdJktQsH/RRk3YHHlu+vxf4dIO19GIdYDdgw2EMFhEPA34JPKH2oUuBY4EfUyy/W7UN8IuIWKeDcfYGvgrUZ9WcCxxdvs6tfWxD4PiIeHK74/TZR4Y1C2mWWhHYt+kiNGd9nsWzgDYB3tJcKZIkSZKkKZjndcE8b1rmeb0xz1OTPo95niRJjfBBHzWifLL7Y5WuIzLz6h4v+wOKWSDtvI6unfuFDs79QZv1PAhc2PVn00I5a+oYJocQ1wLPzczNMnOXzHxJZm4KPB/4R+W4jYAfRUQwg4h4McUspqpfAVtk5uMyc7fy9TjgkcBvKsetCPy0DDCGbW3gfQ2MO5u8MSI2b7oIzT2ZeRPwf5Wuj0TEik3VI0mSJEmazDyvO+Z5MzLP6515nhphnidJUnPmNV2A5qxXUdyoTjik1wtm5u0sfnp8WhFRP25RZi7ssYTLgD8CZ5b/e1Zm3h4R2eN1q14DbFtp3wTs0Kr2zPx5ROxAsd/3GmX3DsArKfb8bqkMbb7I4iWYAX4EvCIz728xzkUR8VyKsOXFZffawH40s/TueyLiS5l5XQNjzwbzgE8AL2+6EM1JXwLeQ/H752HAgrJPkiRJktQ887zumOfNzDyvN+Z5apJ5niRJDXBFHzXlvZX3Z2TmOU0V0gcXAmtm5qaZ+arM/ExmnlQGFX0TEUuz5Kyc90wXaJR7pL+n1r1/OZNoKq8BNqi0bwDe2CoUqIxzP7AH8M9K95uGOJPkmMr7lYF9hjTubHEyk//b7dbgcs2awzLzcoqlzCe8e4bfV5IkSZKk4THP65B53rSOqbw3z+uceZ5GgnmeJEnN8I+thi4itmfxXt4A32qqln7IzLsz8+YhDPVUJs+aupr2vnbfLI+dsAnFTKCpvKjW/no7n1+5TOehla6lgde1UV8/7AvcVWm/OSI2HdLYs8GtFLN+qg5sohAJOLLyflNg56YKkSRJkiQVzPO6Zp43NfO83pjnaZSY50mSNGRu3aUmLKi8f5Al99dWa7vW2kdk5gMznZSZD0TEt4APVrpfCvx+ilOeXmuf0H6J/Bx4f6W9G7B3B+d36xqKfdk/VLaXAfanWFJa7fkS8F8s3i9+p4h4Xmb+fBiDR8Q84MnAxhRLRS9HMftsIXBKZt49jDpGUURsATwaWBdYDbgROCozb5nmnEcAW1J8PVelCOpuBq6nmHV59VTnjoBjgXuBZcv2Ajr7PSRJkiRJ6r8Flffmee0zz5uaeV7vzPNGlHmeeZ4kSYPmgz4aqnK52upewWdl5rVN1TNmnldrn9jBuScyORh4PksuAUxELAesVes+r4Nx/lJrPzIiNi6X7xy0A4G3AGuW7VdExKcz86whjD32MvOeiNgbOKLSfWBEnJCZ/dyXfpKI2BL4CPBCihvYVu6KiB8D+2TmxW1ccz5wRaXrG5m5oIOaTgSeMdHOzKh9vH79qsMi4rBpLr9RdXnu6WqNiDcC/wls3eI6ZwDnVK6zLPBc4GXAM4FHTFMDEXExRZh26KiFLpl5S0ScxOKZP7tExIqZeWeTdUmSJEnSXGWe1xPzvOmZ5/XAPG/S+SdintcY8zxJkobPrbs0bDsAa1Tav22qkHFS3rDXl649vYNLnFprb1beSNSt2aJvUQfjtDr2MR2c37VyNsQnK10BfGoYY88iRwJ/rrQfS7HHe99FxNIR8TmK4Gl3pg4FAFYAXgn8NSL+axD1jJKIWCUifgJ8jdahQCsHAz8GXs8MoUBpc+AQ4PSI2LirQger+rdheeBZTRUiSZIkSTLP64Z53szM8/rCPG8EmOcB5nmSJA2VD/po2OqzWE5upIrxswXFUp0Trs/MW9s9uTz2xkrX0hQ3BnX3tuhbrt1xpjh2qw7O79UXgb9V2s+KCPcDblNmPgjsWev++BQhUtciYgXgOOBdTP47dB9wJvAj4CiKmWvVWR/zgM9HxH79rGfEBPANihlRAAmcCxwDfI8i5LuvxXn1v+d3AmcBPwW+DfyAYnnv22rHPRb4bUS0CgWb9Ltau/63Q5IkSZI0POZ53THPa495Xg/M80aCeV7BPE+SpCFy6y4N23a19jmdnJyZO/atkvFSn/3zt5ZHTe9vTF7GdzOWXMb3Zop91qs3GesCl7Y5xrot+rZot8BelcvV7gtUl1o9MCJ+1a/lajNzfj+u02/9qiszjyuXWZ1Y6nY+8HaKZWH75RDgOZX2LcB+wNczc9KNaxkivINij/bly+59IuKMzDy+jzV14ipgo/L9bsCnKx97P8VN+HTnTmdXYJXy/TeAvTPz79UDImIt4J4W515GsVTzz4Czy6BnkohYBtiFYmnsiZk/G1Ds6f6qGWrrSI+/r8+lCEUmllnevueCJEmSJEndMs/rjnleG8zz+nId87yZmee1wTxPkqTx4YM+GrZtKu8XZeZM/0hWYfVa+/ourlE/Z7X6AZn5YLnX7yMr3dvRfjDQ6h/vS4wzYEcA7wUeXbafQHHD850h1zHOPsjkpaQ/EhGH1m/auxERLwf2qHRdCexY3ee6KjPvAj4TEacBv6YIBwL474jYotXN76Bl5v3AQoCIuLH24Run+lzaNBEK7JWZn2x1QGbWxwQ4CPjPmb4emXkf8P2I+BXwG+Bx5YdeHhF7Zebl3ZXdX5l5e0RcweLw4jERsXw/9h+PiHWAtTs8bZNex5UkSZKkMWae153Va23zvKmZ5/XOPG8a5nmDZ54nSdJwuXWXhiYiHsbkm8Qrm6plDK1ca9/VxTXq56zS8ig4qdZ+XQdj/HuLvqnGGYjyxmivWvf+5cwHtSEzzwB+WOlaC/hAr9eNiAD2qXTdD7y4nRvpzDy1du6mFDNZZqNfTxUKTCUz/9ZJSJKZNwNvqnQtBby6kzGHoPo3Yh6LQ4JevYNi9mMnr2P7NLYkSZIkjRXzvJ6Y57XJPK935nmNM88rmOdJkjQkPuijYZpfazv7p331YKCbp+DrwUD9mhO+WWs/JyL+baaLR8SLgGe1+NBQgwGAzPwJk/eL3xh467DrGHN7Udy4T3h3Ge71YicWz8wCODIz/9zB+Ycw+Xv/xT3WM6oOHMYgmXkWk2++dxjGuB2o/42Y30QRkiRJkjTHza+1zfPaZ57XAfO8vjDPa455XsE8T5KkIfFBHw3TOrX2zY1UMTt0sz91W+dk5iksOQvo2xHx9KnOiYgdgW9N8eGhL8Va+mCtvXdETBWGqCYzLwIOrXStxOQZON3Yudb+boc13Qn8odL1tB7rGUW3USzB2xdRWDki1o2I+fUXcEPl8C37NW6f1P9G1P+GSJIkSZIGzzyvf8zzZmae1wPzvMaY5y1mnidJ0pDMa7oAzSkr1trdLFc7V91ea6/QxTXq59SvWfUG4I/AGmV7NeC3EfEd4PvAJRT7Km8KvIJiidAoj70KWL9yrUVd1NqzzDwtIo4FXlJ2rQO8D9iviXrG1EeB17L4Z/fNEfG5zLyky+s9tda+qbw57cStlffzI2KpJvb1HqBze/l8ImJZ4DnASyn2s38ksFybp68x8yFDdWetvVKfrvslit9jndgEl/uVJEmSNDeZ53XPPK9D5nl9YZ43fOZ5i5nnSZI0JD7oo2Gqf7/d3/IotTLUYCAzL4+IXYAfAWuW3UsBrylfUzkDOIJiSdYJizottI/2BF4ILF223xsRX8rM6xusaWxk5jUR8QWKryMUP8OfoAiDuvGIWvv0bmsrLQWsDtzU43VGSdffmxHxEuBzwEZdXmK1bscekPrfiGX6cdHy57+jr3OxHb0kSZIkzUnmed0zz+uOeV4PzPMaYZ63mHmeJElD4tZdGqb6jJ9ubm7nqltq7bW7uEZ9mcxF0x2cmb8DtgV+1ca1k+Kp+mex5CyCf7RZX99l5gXA4ZWulYG9m6lmbH0K+GelvVtEPLHLaz2kD/XUDX3P+AG7rZuTIuJdwDF0HwrA4ll8o6L+N+KORqqQJEmSpLnNPK975nldMM/rC/O84TLPW8w8T5KkIfFBHw3TrbV2v5ZtnAvqS6tu2MU16ufMuFxrZl6amTsDOwAHUyz/ex1wL3AjcDZwELB1Zv5HZt7BkvsC/7GLWvtpXyaHUm+NiE2aKmbcZOYtwAGVrqAIC7qxbO8VLWHUbmaHLiK2BT5T615I8d/thcBWFDP5VgCWysyYeAEnDbPWDtX/RtT/hkiSJEmSBs88r3vmed0zz+uBed7oM8+TJEm9cusuDdPfa+11G6liPF0EPMDiJWvXiYhVMrOt2QIRsSqwVqXrAdoIBiZk5mnAaW0evn2tfUa74wxCZl4dEV8EPlB2LQPsT7EPudpzCPBfwAZl+5kR8dzMPKHD69wIrFe+vxtYMTOzTzX209IzHzJS9mXyg7tfAf4jM9tZTn3VwZTUF+vV2vW/IZIkSZKkwTPP6555XpfM8/rCPG+0medJkqSeuKKPhmkhxZKwE9ZvqI6xk5n3AJfVuus34NPZoda+pLxmX0XERsDGla6rMvPSfo/ThU8CN1far4yIJzRVzLgpv1f2qXUfGJ1vdHxd5f3yLA4a+q1+Q9zpQ6315apHVkSsRLHE9oTLaT8UgNEOaB9ea1/RSBWSJEmSNLctxDyvK+Z5PTPP64F53ugyz5MkSf3ggz4amsy8m2Imy4QNImLFpuoZQz+vtXfs4Nz6scf3VMnU3lBrf31A43QkMxdRhAMTAjiwmWrG1jeBv1Taj6PzWVSn1trP6aWgadSXhF293RMjYjmgk6Wgm57BtCGTl1D+ebuhQERsDDxsIFX1qAydtqh0XZ+Z1zZVjyRJkiTNVeZ5PTPP65J5Xl+Y57VmnjcA5nmSJA2XD/po2M6svF8KeHRThYyhH9Xar4uIGZckLY957QzX6llErAG8pdL1ACMSDJS+CFxVae8cEc9uqphxk5kPAnvVuj9OZ/t015cGflNPRU3tNibv475VB+c+i2J2UrvqM+mW6+Dcfli91r6lg3MX9K+MvtsYWLnS/kNThUiSJEmSzPN6YJ7XG/O8HpjnTck8bzDM8yRJGiIf9NGwnVRrP7mRKsbTyUxe6nJ9lrzhb+W1TF4y8zLglD7WNeEzwDqV9pczc2T24C1noO1b6z6QYjaQ2pCZPwV+V+naGHhbB5c4nslLVj85IuqzxnpW7hN+TqVro4h41EznRcRSwIc7HG5RrT3spXNvrrUf2c5JEbEh8J/9L6dv6n8bTmyiCEmSJEkSYJ7XC/O8Hpjn9c48r6VFtbZ5Xn+Y50mSNEQ+6KNhO67W3qmRKsZQZj7Akje2n42I+VOdU37sc7Xuj5SzOabUzsyiyrEREZ8G9qh0Xwns2e41hugbwF8r7W0Y3L7SAETEfhGRldeJgxxvCD5Ya+/a7onlErT1vcG/HBEv7bSIiHh2uVTtVH5da+/fxmUPAnbosJQLau1BLV88lcuA2yvtF0bEtDMrI2It4IfAaoMsrEf1vw0/a6QKSZIkSRKY53XNPK8vzPN6Z543mXneYJjnSZI0RD7oo6Eq92Q9o9K1U0TMa6qefomItSJifqtXi8PXn+LY9dsY6kgmf/3WBE6NiCVuRiLiucBpwBqV7lOB77YxzpYRcWFEvD8iNm91QETMK5fKPQ14X+VD9wCvy8zbW53XpDJcqS9Xqw5k5un0sFR0Zn4bOLTStSxwdEQcGRHbTHVeRCwdEY+PiH0j4nzgl0wf6hwKVAOwXSLi0HJJ6vq1t4yIY4H3ll2L2vx0yMwrgcsrXduXn8vzImKLFj/nff19l5n3AsdUupYBToiI59WPLb+GL6NYcv0JFPuR/7Of9fRRdRnuizLzwsYqkSRJkqQ5zjwPMM9rjHle78zzJjPPGxjzPEmShmjsb8g0lo4Ati3fr0HxpPcvmyunLw4GXt/msSdP0X8lMH+6EzPzwYjYFTidxTdF61LcCFxCMbslgEcBm9ZOXwi8tFwGtR1bUMyIOCgirgfOA24sP/ZQYGsmhw5Q7KP8ysyc6nNsXGb+OCJOAZ7SdC1jbC/gxUDbM8Vq3kbxvVOdPbQ7sHtE3ACcS3HD+iCwKrAesCUd7LWdmVdExGeA91e69wBeHRGnAdcCK1F8n1eXxz2A4nvjGR18Pp+j2DN+0ucyxbEbUfws9tN+wC4s3gN7PeD4iLgSOBu4E1gLeBKTf2YPAJ5KZ5/rwEXEEyi+ThO+0VQtkiRJkqR/Mc9rzTxvCMzz+sI8bzLzvD4yz5Mkafh80EdNOIriRnqFsv1yxj8YGJrMvDYidqb4Oj6+8qHNylcrf6K4Yb+uy2HXAZ45wzHnA6/NzLO7HGOYPgj8fkhj1W9m63swj53MvDAiDgPe1OX595UzUd4PfJTJX6O1mTz7Yyr3AXfMcMxHKAKyagCxPFMvMf6pzPxwF8sxH0IRxnWyv3nfZOZlEbEb8AMWhwMAG5avVj6dmR8Z0aWnX1F5fz9FmCxJkiRJapZ5Xg/M8/rCPK8H5nlLMM/rL/M8SZKGzK27NHSZeROTn+h+ZUSsPNXxWlJmXkwxi2pPJi8zWndZecx2mXlpB0NcA/wv7c1U+BPwZuCxYxIKkJmnAD8e0nD1PaLre6yPq30pZnx1JQsHUcz0OJBiBtxMbgOOA/4DWDczz5xhjHuB3YD/B/xjqsOAk4CdM/NDbZZfHycz8+0UP5NfoFj++nrg7m6u12UNJwBPBI6l+JxauR84AXhWZn5gWLV1olwK+d8rXd/PzKubqkeSJEmSVDDP6515Xm/M8/rCPG/xOOZ5fWKeJ0lSM6L9VT+l/omIzYALWfyw2Vsz8ysNljTWyr2QN6dY4hOKG/uLM/OsPlx7PYplfecDq1OsBHY7cAVwZmZe0+sYs1VErEgx42fZsuvXmdnO7JY5KSI2othrem2KJWkfpAgDrqH4fXFJuS97N9deiuLGeWuKZW/vAq6m+B5uJ5QYGxHxUIolfDegmGl5A8XSxqdn5o3Tndu0cmbYDypdT+zH77FeRcSjKJY7B+DQ405mo80fOc0Z4+WKiy/kDf/2tGrXozPzr03VI0mSJGk0mef1l3neaDLP64x5Xn+Y5/VfPc/7/q9OZZMttmywov667KILePmzJz2TaJ4nSXOMW3epEZl5SUQcCbyu7HpXRHy1g/2mVVH+w3kg/3gub/y9+e/OU1kcCgDs01Qh4yAzr6AInAZx7QeBP5SvWa1c0vvopuvo0nsr738yCqGAJEmSJKlgntdf5nkjyzyvA+Z5/WGeJ0mSOuXWXWrSPsC95fstmbzvrjQbVPdBPyEzT22sEmnERcQzge3L5oPAXg2WI0mSJElqzTxPs515ntQm8zxJkprjgz5qTGYuBD5f6dq3XI5Tmi2qwYCzf6Tp7Vd5//XMPG+qAyVJkiRJzTDP0xxgnie1b7/Ke/M8SZKGyJswNe1jwN/K91sDr2+wFqlvImJViv2pAX6WmbN+iVmpWxGxK/C0svlPYM8Gy5EkSZIkTc88T7OSeZ7UPvM8SZKaNa/pAjS3ZeYdEbE7sHPZtUyT9Uj9kpm34u9YqV2rAB8t35+Smf9sshhJkiRJ0tTM8zRbmedJHTHPkySpQf6jVY3LzFOAU5quQ5LUjMw8oukaJEmSJEntM8+TpLnNPE+SpGa5dZckSZIkSZIkSZIkSZI0BnzQR5IkSZIkSZIkSZIkSRoDPugjSZIkSZIkSZIkSZIkjQEf9JEkSZIkSZIkSZIkSZLGgA/6SJIkSZIkSZIkSZIkSWNgXtMFSJIkjZPHrr0cW627QtNl9M2qNy/XdAmSJEmSJEnSwGy6wr1steLdTZfRN7HCvU2XIElqmCv6SJIkSZIkSZIkSZIkSWPAB30kSZIkSZIkSZIkSZKkMeCDPpIkSZIkSZIkSZIkSdIY8EEfSZIkSZIkSZIkSZIkaQz4oI8kSZIkSZIkSZIkSZI0BnzQR5IkSZIkSZIkSZIkSRoDPugjSZIkSZIkSZIkSZIkjQEf9JEkSZIkSZIkSZIkSZLGgA/6SJIkSZIkSZIkSZIkSWPAB30kSZIkSZIkSZIkSZKkMeCDPpIkSZIkSZIkSZIkSdIY8EEfSZIkSZIkSZIkSZIkaQz4oI8kSZIkSZIkSZIkSZI0BuY1XYDUqYg4DFhQNr+bma9qsJyxFBFPADYDHl52XQ1cnJln93GMZYBtgU2BtYEHgWuAy4AzMzP7NZakwYuIw4HXV7o2ysyFfbju0sCfga3Krndn5ud7va4kSZIkaXSY5/XOPE9Sp8zzJEmavVzRR2MlIp7C4n+Y3gvsOcPxJ0ZElq8Tax9bUPnYIF8Lpqlv7Yh4fkTsExE/iYhrW5w/v7ev2r/GWiYiPhQRlwJnAUcBnylfRwF/iohLIuKD5U19t+NsGBFfBf4JnAwcBhwEHAx8GzgD+HtEHBgRq3R47fltfL0fjIi7IuKmiLio/B74SkS8MyIeHxHRw+dWH39Bt9fqp07rioj9pvjaPbuLsevXel/Xn4hmldr3xX5THZeZDwAfrHR9NCLWHXiBkiRJkqShMM/rnnmeeV7lePM8DZx5niRJ48MHfTQ2ImIp4BBg4sbuy5l5RYMldSUi1ouI70fEQuB64Djgo8ALgYcNaMzNgNOBTwKbTHPopsCBwGkRsWkX47wJuBh4EzDdTf/DKW4E/hIRT+90nJnKAJYH1gA2B54BvBn4IvAn4KqI+GxEbNzncWeDA3sJTuaiiDh8EEHeXJOZP6UIEgFWBT7VYDmSJEmSpD4xz+tpTPM887x2mOd1yDyvP8zzJElqlg/6aJzsDjy2fH8v8OkGa+nFOsBuwIbDGCwiHgb8EnhC7UOXAscCP6ZYfrdqG+AXEbFOB+PsDXwVWLb2oXOBo8vXubWPbQgcHxFPbnecPlgPeDdwSUR8OSJWH+LYo24b4JVNF6E5a//K+9dExGMaq0SSJEmS1C/meV0wz1uCed7UzPPUJPM8SZIaMq/pAqR2lEvPfqzSdURmXt3jZX8AnNjmsQcDL6u0vwB8vs1zb2zzuAcpZs88ss3jZ1TOmjqGySHEtcCCzPxF7djnUSzLOzELaSPgRxHx1Jn2346IF1PMYqr6FfAfmXlx7dgtgC8Bzyy7VgR+GhFbZ+Y/2v3cKjZq0bcCsHr52hJ4MvB0oLp86FLA24DnRsRLMvMvXYw9G+0fEUdn5n1NF6K5JTN/ERF/BJ5I8fP5CeDFzVYlSZIkSeqWeV53zPPM87pgnqdGmOdJktQcH/TRuHgVk28AD+n1gpl5O3B7O8dGRP24RZm5sMcSLgP+CJxZ/u9ZmXl7REx7E96h1wDbVto3ATu0qj0zfx4RO1Ds971G2b0DxYyQo6YaoAxtvsjiJZgBfgS8IjPvbzHORRHxXIoZQRP/6F8b2I/iRr0jbfx3OL6scx7wUuADFDNdJmwE/CYinp6ZF3Q6/iy0CfAW+vAzJnXhS8Ch5fsXRsSjMvOvTRYkSZIkSeqaeV53zPPM8zplnqcmmedJktQAt+7SuHhv5f0ZmXlOU4X0wYXAmpm5aWa+KjM/k5knlUFF30TE0iw5K+c9091Il3ukv6fWvX85k2gqrwE2qLRvAN7YKhSojHM/sAfwz0r3myJi82nG6Ulm3p+Z3wO2o1gmuhrArAX8MCJWHNT4I+6YWnvviFi5iUI05x0FLCrfB5N/90uSJEmSxot5XofM85Yc0zxvSsfU2uZ5aop5niRJDfBBH428iNiexXt5A3yrqVr6ITPvzsybhzDUU5k8a+pq2vvafbM8dsImFDOBpvKiWvvr7Xx+mXkTi5/0B1gaeF0b9fWkDAg+AHy89qFHAh8a9Pgj6hSKvd0nPBRvyNSAzLyLYgbhhFdHxGpN1SNJkiRJ6o55XtfM81qPa563JPM8jQTzPEmSmuHWXRoHCyrvH6RYIlYz27XWPiIzH5jppMx8ICK+BXyw0v1S4PdTnPL0WvuE9kvk58D7K+3dgL07OL8XH6UIT55Z6XtXRBycmbcOqYZRsifwAoqABuC9EfGlzLxhGIOXM46eAqxHsfTzA8D1wAXAnzLzwWHUMWrK2XdPBjYGHgYsB1yZmd+e4Zwtytf6wCrA/cDNwN8oZlHeMuDSe/E9ihmCAMtTLPX+f82VI0mSJEnqwoLKe/O89pnnTc88bzLzvBFknmeeJ0nSMLiij0ZauVztyytdZ2XmtU3VM2aeV2uf2MG59WOf3+qgiFiOYpncqvM6GOcvtfYjI2LjDs7vWnmjWV8KeRXg1cMYf9Rk5vnANypdqzCEkCYinhsRv6HYb/7nFLPCPgUcDBxBsef9dRFxYESsMfWVJl1zQURk5bWgw5qq55443fWB19c+fEXt/OprYbu1RsQKEXEA8HfgNOBI4DPAART7Xtevs0ZEvCEijqVYQvt8ipk0XyzPOQj4KkVwd1NEnBQRL+zk6zJEvwbuqLR3b6oQSZIkSVLnzPN6Yp43DfO8yczzJp1vntcs8zxJkobMB3006nYAqjcDv22qkHFS3rBvWus+vYNLnFprbxYRy7Y4bs0WfYs6GKfVsY/p4PyeZObvgHNq3S8e1vgjaF/g7kr7rYMKaiJirYj4JUUYsBOwzDSHr0UxI+2SiKjPOJt1ImJL4E8Us7LWa/O0k4CvU3z/rj7DsUtRzNz7SUR8JyJW6rLUgcjM+yiWn57wlIhYvaFyJEmSJEmdM8/rgnlee8zzlmCeNwLM88zzJEkaNh/00airz2I5uZEqxs8WLF6yFeD6TpavLY+9sdK1NLB5i0PvbdG3XLvjTHHsVh2c3w+/rLV3iIgYcg0jITOvopgxMmFZltz7vGcRsSlwBvDs2oduo5h99l3gB8AfKZb3nvAQ4JcR8dx+1zRC1gR+SrHHPBQ/Y6dQLH97DPBnIFucV/97fhPF8tzHAN+imA10NnBf7bhXAUeN4Pf87yrvlwZ2bqoQSZIkSVLHzPO6Y57XPvO8knneSDDPK5jnSZI0RPOaLkCawXa19jmdnJyZO/atkvFSn/3zty6u8TcmL+O7GUsu43szxY1b9aZkXeDSNsdYt0XfFu0W2Cen1dqrAxsAV9YPzMyFwKjdQPW7rk8Cb2bxLJJXR8SnM/Ocflw8IlakuEmtziy6CPgwcEx93/mIWJdiSeY3l13LAt+KiMdl5tX9qKkLP2DxctgHAy+rfOxpwFVTnHd/G9fej2KZ5buBjwFfzMzbqwdExEYtzkuKIOAo4LjMvKLVxcvlkt8I7FOOA/BC4K3A/7ZRX9sys5fvyXNq7e2B7/dwvX+JiHUo9o3vxCb9GFuSJEmS5gjzvO6Y57XPPG8y87yZmee1wTxPkqTx4YM+GnXbVN4vKmcoaGar19rXd3GN+jmr1Q/IzAcj4mIWz1aAIsxpNxjYvkXfEuMM2IUt+loGA3NBZt4cEQcCB5ZdQbHHdr9m3XwaeHSlfTzwssy8a4p6rgXeEhEXUuxpDUVg9XHgDX2qqSPljfrtABFxe+3DV5VBTbdWoZj18/zMPHGK8Vvd9L+onXEz82bg4HKZ5ZNY/PP2/oj4SrnX/Sj4c6395D5e+x0Uy1pLkiRJkgbDPK87q9fa5nlTM8+rMM+bmXneUJjnSZI0RG7dpZEVEQ9j8k3inLxR69LKtXbLm64Z1M9ZpeVRxc1F1es6GOPfW/RNNc6g3Nyir9PZAbPNF5g8i+U5EfGsXi8aEesBb6p0LQR2myoUqMrMzwLHVbpeU/6OmI32nyoUmEqnYURmnsvkZZw3pnVQ15SrmTxjqtVS45IkSZKkEWOe1xPzvPaZ5y3JPK9Z5nnmeZIkDZUP+miUza+1nf3TvnowcHcX16jfrNWvOeGbtfZzIuLfZrp4RLwIaHWzOQrBwApDrmGkZObdFEvOVh3Yh32f30axVO+Ej2bmnR2c/5nK+2WB5/VYzyi6E/jvIY11dK29w5DGnVE5E+naStfaEbFSU/VIkiRJkto2v9Y2z2ufeV77zPNqzPMaZZ6HeZ4kScPm1l0aZevU2q1u4NSeHNQ5mXlKRJwEPKPS/e2IeHFm/q7VORGxI/CtKS457KVGWz3w2M3Xa7Y5HHgvsGXZfiLwcuB7PVxz58r7Byj2xu7E7ylmhUz87XoaRZ2zyW8z85Z+XSwilqYI9VZhyb/5S9faWzJabgYeUWmvDdzRh+t+ic73B98EOLYPY0uSJEnSbGee1z/meVMzz2vtcMzzmmCet5h5niRJQ+KDPhplK9ba3SxXO1fV9xnuZkZL/Zz6NaveAPwRWKNsrwb8NiK+Q/EP8Eso9obeFHgF8OqyDcXMrvUr11rURa29WL1F35z/XsvMByJiL+BHle5PRMQPM/P+qc6bSkQsD2xT6fo7sFZErNXhpRZR7OkNxc3abHN2LydHxBrArsALgK0plvBtd/W+NWY+ZKjqs8P6MgMoM68Hru/knN4nv0mSJEnSnGGe1z3zvPat3qJvzn+vmec1xjxvMfM8SZKGxAd9NMrq358d34zMYUMNBjLz8ojYheImcs2yeyngNeVrKmcARwCHVPoWdVpoj1rdDN0w5BpGUmYeExGnsngJ2E2Bt1DMoOjUw4BlKu35wBU9Fbj4e2026eiGdUI50+f9wIeZelnumazW5XmDUv+dv0zLoyRJkiRJo8Q8r3vmee0zz5uCeV4jzPMWM8+TJGlI2n0qWGpCfRbGnN5nuUP1pULX7uIa9aWWF013cLms77bAr9q4dlLcXD6LJW/M/9Fmff2yVYu+K4dcwyj7YK29T5d7Kz+kH8XUDHv/92G4rdMTImIecBTwSboPBWD0/k1Q/53fj2V+JUmSJEmDZZ7XPfO89pnnTc88b7jM8xYzz5MkaUhG7R8BUtWttXZflnmcIy6ptTfs4hr1c+rXXEJmXpqZO1PMGDmYYvnf64B7gRspljE9CNg6M/8jM+9gyX2E/9hFrb3Yrta+KTP/PuQaRlZm/h74SaXrocB7urjUsv2paBLXXy28G9it1nc6xYygnShmbq0GLJeZUX0Nuc5O1X/n1/8mSJIkSZJGj3le98zz2meeNw3zvLFgnidJknri1l0aZfWbs3UbqWI8XQQ8ACxdtteJiFUys63ZBRGxKov3Taa81ozBwITMPA04rc3Dt6+1z2h3nD55dq19ypDHHwd7UuwRPfFw6Psj4suZeWMH16gf+4vMfG5fquujcsncsRERy1Is7zshgT0y8xttnLvqwArrj/Uq7++hy2WQJUmSJElDZZ7XPfO89pnnzcw8b0SZ50mSpH5wRR+NsoUU/8idsH5DdYydzLwHuKzWXb8Bn84OtfYl5TX7KiI2AjaudF2VmZf2e5xpxt8ReGyt+8fDGn9cZOZfKfZen7AK8JEOL3Ndrb15T0VNr74XdCcPtbba432UPYPJe3F/s51QoLTezIc0IyJWBqrBxZWZmVMdL0mSJEkaGQsxz+uKeV7b4++Ied6MzPNGmnmeJEnqmQ/6aGRl5t0UM1kmbBARKzZVzxj6ea29Ywfn1o89vqdKpvaGWvvrAxpnCRGxFLBvrftWir2RtaR9gLsr7bdHxPx2T87MW4G/VrrmR8Rmfaqtrr4k7OodnPuoDsdq+ma1/jX8aQfn1gPAUVJfAvycJoqQJEmSJHXGPK9n5nnTMM/rmHlea+Z5g2GeJ0nSEPmgj0bdmZX3SwGPbqqQMfSjWvt17SxjWh7z2hmu1bOIWAN4S6XrAYYYDAD7sWQA8tnMvH2INYyNcp/zQypdywL7d3iZE2rtN/dU1NTqS8Ju1cG5L+hwrPrMuOU6PL9Xq9fat3Rw7oL+ldF3W9faf2ikCkmSJElSN8zzumeeN739MM9rm3nelMzzBsM8T5KkIfJBH426k2rtJzdSxXg6Gbii0l6fJW/4W3kt8PBK+zIGs8/1Z4B1Ku0vlzefAxUR8yLiUyy5VO35wEGDHn/MHQAsqrR3Z8mlkqfzZSYvw/v/IqLTGTft+DNF0DTh+W2GYg9lcljVjkW19rodnt+rm2vtR7ZzUkS8BHha/8vpm/rv+hObKEKSJEmS1BXzvO6Z57VgntcT87wlLaq1zfP6wzxPkqQh8kEfjbrjau2dGqliDGXmAyy5lO1np1uetfzY52rdH8nMB6cbq52brsqxERGfBvaodF8J7NnuNbpRBgK7AacBHwCi8uEbgJdl5l0DGPfEiMjKa79+jzEsmXkT8KlKVwC7dHD+pcBhla7lgeMiopMZOkTEchGxYJpx7qT47zzhYcD/m+GaKwPfY/L+2O24oNZ+Tofn9+rcWvudEbHSdCdExBOZ/N9hFFV/1/8D+FNThUiSJEmSOmae1yXzvCXGNc/rkXleS+Z5g2GeJ0nSEM1rugBpOpl5bUScAWxbdu0UEfMy8/7pzht1EbEWsHKbh68fEa3678/Mq2Y490jgP1j89VsTODUiFmTmL2o1PRc4HFij0n0q8N02atwyIn5AsVTvsZl5cf2AiJhHsbTu/pV6oFgq9XXdLrE7RdCxPMUN3uoUewNvCzyD1rMzLgdenJkXdjP+HPQF4J1MniXWifdQ/PeYWMp1A+CPEfE54H+nmgUWESsATwFeDLwKWJvi+3UqXwWeWmkfHBEJHFL9/RHFD9ezgc9SLCV+M5N/BmZyEsW+3hM/pO+NiAcoljW+Drivcmw7P7OdOoMiWNuwbG8G/DIi3piZk0KLMvx4B8X+7CtRBGJr97menkXEhkzeq/zYzGx673RJkiRJUpvM8wDzvGmZ5w2ded5k5nl9Zp4nSdLw+aCPxsERLL6RXIPiyfBfNldOXxwMvL7NY0+eov9KYP50J2bmgxGxK3A6xQ0YFDfHJ0TEJcBfKW5oHgVsWjt9IfDSDv5BvgXFUrkHRcT1wHnAjeXHHkpxI1i/4boLeGVmTvU5tuOKmQ9p6QHgK8CemdnJPshzWmbeFREfpfjadXP+7RHxQuAXLF6WdgVgL2CviLgcuJBiCd15FAHPfIrvz7ZnmlGEYm8HtivbSwOfB/aOiNPL668BbEPx/QnFMsSvYcmZh9N9Pgsj4ofAy8quZSmWka4vJQ1t/Mx2KjMfiIgPMDnA2x74a0T8GbiIIrhYj2L53Ik9x+8H/h04vp/19MnLau1vNFKFJEmSJKkX5nmtmecVzPOGyDxvic/HPK//zPMkSRoyH/TRODiK4kZ6hbL9csY/GBiachbVzhRfx8dXPrQZk5+yr/oTxQ37dV0Ouw7wzBmOOR94bWae3eUY3bqG4ibqfzLz8iGMt3ytXd+DeRwdSjGTp639o+sy8+8R8STgfyluxKs2Ll8zWTTDGA9ExCuYHEAAPAR4QYtT7qSYiXb8FDPupvMWihvv7Ts9sR8y83sRsTnwMRbPRAqK/dZb7bl+F/DvmfnzLj7XYXhF5f2FmXnalEdKkiRJkkaVeV4PzPOWYJ7XO/O8yczz+ss8T5KkIVuq6QKkmZT7CFefAH9luWSl2lQuvbstxb7Z090MX1Yes125/3K7rqG4yVvYxrF/At4MPHZAoUBSLB+8CLgU+B3wNeA/gScA62fme4YRCpTL0z6u0nUz0y9POxbK/eL36vEat2fmayluXL9Fe4HJNRQze15OsU/3TGP8HdiBYubPVPu13w18h+L78Ydt1NBqnJuAp1Hsb34E8GfgJiYv8ztQmbk/8G9Mv/f1rRS/Sx+TmT8YSmEdiohHMXkp8M81VYskSZIkqXvmeb0zzzPP6yfzvCXGMc/rE/M8SZKaEW6TqXEQEZtRLP858XDaWzOzq6VGBRGxDbA5xawFKG64Ls7Ms/pw7fUolvWdT7Gn9jzgdoolec/MzGt6HWNcRMSzmTxbbe/yBk41EbEUxffNVhR7z69OcdN+K0XgdMFU+323ef0VKPb43qy89s3A34GTZ9tSz+VsoO0oljAOir3FrwJOycy7m6xtJhHxRYo946HYc3yDUai5DCzOm2ifdeYf2GqrrRqsqL/OP/98tnnSk6tdj87MvzZVjyRJkqTZwTyvv8zzhsM8r33mef1jntd/9Tzv7FNOZKtHbtFgRf11/oUX8fin7FjtMs+TpDnGrbs0FjLzkog4Enhd2fWuiPhqB/tNq6IMAHoOAaa49jUUQYMmL3f8T+ALTRUy6jLzQeCc8jWI699FEdLM+mXCyxl/FzddR6ciYk1gQaXrwFEIBSRJkiRJ3THP6y/zvKExz2uTeV7/mOdJkqROuXWXxsk+wL3l+y2BXRusRWpHNRg4ODNva6wSafS9C5hYxv1vwCHNlSJJkiRJ6hPzPI0b8zypfe/CPE+SpEb4oI/GRmYupNibd8K+5fKg0siJiFWAbcrmDcAXGyxHGmkR8RDg/1W69szMe5qqR5IkSZLUH+Z5GifmeVL7zPMkSWqWN1UaNx+jeDIciv1/X99gLdJ0ns7i7REPysw7mixGGnH7UOy1DvDbzPx2g7VIkiRJkvrLPE/jwjxPap95niRJDZo38yHS6MjMOyJid2DnsmuZJuuRppKZPwOi6TqkURcRSwPXAR8tu45ssBxJkiRJUp+Z52lcmOdJ7THPkySpeT7oo7GTmacApzRdhySpd5n5AHBA03VIkiRJkgbHPE+SZg/zPEmSmufWXZIkSZIkSZIkSZIkSdIY8EEfSZIkSZIkSZIkSZIkaQz4oI8kSZIkSZIkSZIkSZI0BnzQR5IkSZIkSZIkSZIkSRoD85ouQJIkaazEUsVrtphNn4skSZIkSZJUlw8Wr9liNn0ukqSu+P/sSJIkSZIkSZIkSZIkSWPAB30kSZIkSZIkSZIkSZKkMeCDPpIkSZIkSZIkSZIkSdIY8EEfSZIkSZIkSZIkSZIkaQz4oI8kSZIkSZIkSZIkSZI0BnzQR5IkSZIkSZIkSZIkSRoDPugjSZIkSZIkSZIkSZIkjQEf9JEkSZIkSZIkSZIkSZLGgA/6SJIkSZIkSZIkSZIkSWPAB30kSZIkSZIkSZIkSZKkMeCDPpIkSZIkSZIkSZIkSdIY8EEfSZIkSZIkSZIkSZIkaQz4oI8kSZIkSZIkSZIkSZI0BuY1XYA0lYg4DFhQNr+bma9qsBx1KSIC2Bp4DLAusBxwJ/AP4BLgz5l5T3MVSmpHRGSleVJm7tin6+4AnFI27wAemZlX9ePakiRJkqThMs+bHczzpNnBPE+SpNnLFX00kiLiKcDry+a9wJ4zHH9iRGT5OnGGY+dXjq2+vtVFnfVrndfBuRERj4yI10XEf0fEqRFxV+16034uHYy1ekQ8KyI+GBE/iIgrW3z+O/ZjrMqY60bEZ4DrgHOAbwIHAR8HPgMcCfwBuDUiTo6IN7Vxzf2m+G9Xfd0XEbdHxLURcW5E/DgiPh0Rr4yI9Xr8nCaN38u1+qnTuiJiYYuv2+URsWwXY9evtVZ3n4Vmk4hYUPu+mD/VsZl5KnB02VwJ+NwwapQkSZIk9Zd5nnneFNc0z2vBPE+jxjxPkqTx4oo+GjkRsRRwCBBl15cz84ohDL17RBycmecMcpCI2A34D2AbYJUBjrM88HXgicBmLP56DlxEvBP4FLBiG4cvCzwVWAb4Wh+Gn1e+VgIeRjH76EXlxzIizgAOB47IzLv6MN5ssRHwNuC/my5knNSCmL7NipmD9gR2AZYGdouIZ2bmb5otSZIkSZLULvO8vo1jnmee1wnzvC6Y5/WNeZ4kSQ1yRR+Not2Bx5bv7wU+PaRxAzhwCOM8FdiRAYYCpeUpvpabM6RQICKWioivA19kyVDgEuAE4NvAscBZwLCX+A1gO+B/gcsj4nVDHn/UfSQiBv19KS0hMy8BvlfpGsbvYkmSJElS/5jn9Yd53pLM86ZnnqdGmOdJktQsH/TRSImIZYCPVbqOyMyrh1jCcyNipyGOV3UHsHBIY10O3D2A634BeEOl/QDwP8Cmmbl5Zj4vM1+Tmbtk5hOBVYHnAF8Fbu9ivKMpZq5UXxsDj6MIX3YDPgn8hiJkqnoYcEREHNnNErez1NrA+5ouQnPWAZX3T4qIlzZWiSRJkiSpbeZ55nkdMs/rL/M8Nck8T5Kkhrh1l0bNqyhu7iYc0kANnwKePOAx7gbOBf5YeZ0P/DtwWJ/Hugo4szpWZt4UEQuBDfs1SES8AHhnpes24AWZefJU52TmvcAvgV9GRDe/j27PzIUzHHN0Wd9DKZayfTewWuXjuwOrRMQumflgFzXMNu+JiC9l5nVNF6K5JTPPi4jfAU8vuz4E/LDBkiRJkiRJ7THPM8/rhHle/5nnqRHmeZIkNccVfTRq3lt5f8ag99cuXVi+JjwpIl4+wPE+AaySmdtl5jsz8/DMPG8AN6W3AQ/NzEdk5ksz84DM/EVm3tTncYiIVSmWz52QwC7ThQJ1mXl/v+uqXf+6zPwo8HiKgKTqRcB+gxx/xB1Teb8ysE9DdUjV3yNPioinT3mkJEmSJGlUmOf1j3ne5Oub503tmMp78zw1yTxPkqQG+KCPRkZEbM/ivbwBvjWkoR8A9qr1faLLGSkzyswbBn0TXI7zQGZeP+hxSv8BrF9pH5qZvxnS2B3JzCsolgE+v/ahD0XEFsOvaCTsC9xVab85IjZtqhjNacdQLHs+4e0N1SFJkiRJaoN5Xt/HMc9rwTyvJfM8jYpjMM+TJGno3LpLo2RB5f2DlEu0DkNm/igiTgO2L7s2A97E5KfR1UJEBPDmSldS7KM9sjLzjnK/4HOB5cruZSgCotc3VlhzrqHYj/1DZXsZYH+KpbeHIiI2Bp5Asa/4GsAtwD+A0zLzmmHVMWoiYjVgB2A9YB2KZcJPysw/TXPOKsBWwObAWsBKFDMCbwLOA/6cmQ8MuPSuZOZdEfFT4JVl1y4RsVpm3tJkXZIkSZKkKS2ovDfPGxPmebOCed6IMs8zz5MkaRhc0UcjISKWBqrL656VmdcOuYwP1tr7RsRKQ65hHD2Lyfuwn5yZlzVVTLsy8yLg27XuV5bLFs9FB1LcOE54RURsM8gBI2KliNgzIi4BLgO+D3yJYjns/wF+AFwdEWdHxMvLEKqd654YETnx6rCmBdVzI2LBdNevfegZtXPrr/3arTUiHhURxwDXAccBXwMOAD4L/HuL6zw6Ij4eEX8AbgZOB44oj/848Pmy/Sfg5oj4UhnGjKIfV94vD7y0qUIkSZIkSVMzzxtr5nmzg3ke5nkjwjxPkqQh80EfjYodKJ76n/DbYRdQ7j/9s0rXw4B3D7uOMbRTrf3LRqrozhdq7eWA5zZRSNPKGRbVmVsBfGpQ40XEc4HLKW52Z1pW+HHA94BflDNiZrWIeBvFvvMvYfEMtemOfwLwF+AjwJOApWc4ZRWKJXTPi4jX9lbtQNR//7+wkSokSZIkSTMxzxtf5nmzgHne6DDPM8+TJGnYfNBHo+J5tfbJjVRRLHX6YKX9/ohYq6FaxsWTa+3TACJiXkS8JCK+GxEXRcTtEXFbRFweET+NiP+KiLUbqPdfMvNcoL7v+VOaqGVEfBH4W6X9rIjYud+DRMSbKUK4dWofWlj2fxv4KfD32sefDfy+XMp2VoqIXSlmQS1fdl0H/Bz4DvALiuWP6+p/y5MidDmBYlbVt4HjmfzfFmAF4JsRsVtfiu+TcvbnpZWunctZopIkSZKk0WKeN77M82YP87yGmeeZ50mS1AQf9NGo2K7WPqeTkzNzx8yM8rVjt0Vk5nnANytdqwIf7vZ6c8QTa+0LImJr4EzgGOAVFHsLrwSsTLEs8Asolh69IiI+1vA/+k+vtR871YGZuV/l+6ytZWeHoV91ZeY9wL617gPbXWK3HRHxTODLTJ6lciTwqMzcKDNfmJmvycwXZeYGFDPMzqsc+2jgK/2qp0uvovg+3qjWf0alv9Xr821c+xsUs6/Op5iNtm5mPj8zd8/M5wLrUyzfW3cXcBiwC7BqZm6Smc/LzFeUX89/y8wNgcdQhAVVh0ZEPaTpSWYeXv2ezMyFHV7inMr7VYBH9a04SZIkSVK/mOeNL/O8hpnnDZ153gzM8yRJGi8+6KNRUd07eFFmXtVYJbAPcE+l/Y6ImN9QLSMtIpYDVq90PQBsQnGz/bg2LrESsDdwfIOzOi6stTdopIrRcQSTb8SfQHEj3LOIWJliNspEKJDAGzPztZl5fqtzMvNEYHvKmWWlV0XE0/tRUzcy8x+ZubDFze7dE/1TvBa1cflVKEK1HTLzF5k5ad/wzHwgM+szeS4GHp6Zb8jMYzPz9mlqPy8zXwF8tDbmO9qobZj+XGvXZxp2LSLWKfdMb/tF8XtNkiRJkjSZed4YMs+blczzZmCeNxTmeZIkDZEP+qhxEfEwoLpP75VN1QJQ/qP7kErXssDHGypn1K1Ra98L/IhiCVGAGyluQJ4BbEGx3/A7KfYfrtoZOHRwZU7r5lq70eWHm5aZDwJ71br3j4hl+nD5twEPrbQ/nZkz/ncvb3RfyeTA7n19qGcU3QPsXu6x3pbMvDUz69/HM/kYk2++X9Ph+YNW/zuweR+v/Q6K8KuT17F9HF+SJEmSxp553lgzz5tlzPMaZ55XMM+TJGmIfNBHo2B+rd3k7J8JnwCq/zDfvVy+VpOtXmuvADykfH8ysHm5DO3vMvPizPxjZh4CPJ4llz3dLSJeO9BqW6vfUK3Q8qg5JDN/QvHfb8LGwFv7cOn/V3l/Ox0Ebpn5d+B7la7nlDPQZpsfZOalMx/WmzIA+lGla9OIGKVQrP53YH4TRUiSJEmSpjS/1jbPGx+r19rmebOAeV6jzPMK5nmSJA2RD/poFNT3ku30Sfa+y8ybgE9VupYCDmyonFE21e+QK4EXTjUroVyu9N1MvjEB+HBEDPv3Un28bHnU3PPBWnvvcqnerkTEFkxeRvm46ZakncJvK++Xo4/Lv46QY/p5sYhYLiLWiogNI2J+9UWxD3jVlv0cu0f13x193XNckiRJktQz87zxZZ43e5nnNeOYfl7MPE+SJLVjXtMFSMCKtXb9H6tN+QLFsrTrle3nR8SO5R7DKkx1Y7dPZt7axvnvBl7C4pvzR1Ls735mH2pr1+q19qh8/zUqM0+LiGMp/vtAcWP2PmC/Li/51Fr7b+XNaScerLU3YfJMpdng7F5OjohHUyyL/DTgUcBaHZxeX7q7SXfW2iv18dpfAr7f4Tmb4HK/kiRJklRlnje+zPNmKfO8xpjnFczzJEkaIh/00Siofx/e30gVNZl5Z0R8FPi/SveBwHYNlTSKWgUD9zB5SdYpZeaVEXESsFOle0eGGwzUb4ZuGOLYo25P4IXA0mX7vRHxpcy8votrPaLWfh+978u9Zo/nj6JuvrZExIYUy2fv0sPYq/Vwbr/V/w70Y095AMrv346+zhHRr+ElSZIkabYwzxtf5nmzm3ne8JnnFczzJEkaIrfu0iioz7gYpT2Vvw5cVGlvGxEva6qYEXQrS87KOCcz7+7gGqfX2sNebnSrWvvKIY8/sjLzAuDwStfKwN5dXu4hMx/SsVUGcM1GZeZtnZ4TEVsCp9FbKACj9W+C+t+BOxqpQpIkSZI0FfO88WWeN4uZ5w2fed6/mOdJkjREo/SPAM1d9SVh+7mkY08y8wFgr1r3ARHhalhAZt4PXFHrvrbDy1xTaw/iBnI629ba5w55/FG3L5PDu7dGxCZdXGfZPtVTNeenZZS/i44C1q103w18E1gAPLH82MrAvMyMiRewx5DL7UT970A7S4dLkiRJkobHPG9MmefNCeZ5I8w8T5Ik9YMP+mgU/L3WXrflUQ3JzB8CZ1S6Ngfe2FA5o+ivtfY9HZ5fP375HmrpSEQ8niX3PP79sMYfB5l5NfDFStcywP5dXOrGWnv36k1ql6/9uv28prH0zIeMlJcCW1falwKPysx/z8xvZOZZmfmPzLyjDDqrVh1emR1br9au/52QJEmSJDXLPG+8mefNYuZ5I888T5Ik9cwHfTQKFgJZaa/fUB3T+WCtvW9ErNhIJaPnz7X26h2eXz/+n11X0rn/qrXvBn4xxPHHxSeBmyvtV0bEEzq8xnW19ua9lTStSftBdzhjr77H+6h7Sa39lsy8vM1z6zffo+ThtXZ9pqEkSZIkqVkLMc8bZ+Z5s5953ugyz5MkST3zQR81rtz/ubpv9gajdtOdmScBx1W61gXe1Uw1I+e4WvtRHZ7/6Fr7qh5qaVtEPBJ4RTCQ2QAAz3FJREFUda37O5l5+zDGHyeZuYgiHJgQwIEdXubUWvs5vdQ0g/qysKt3cG6n379N26zy/g7gxA7O3aG/pfTVlrX2OU0UIUmSJElqzTxv7JnnzXLmeSPNPE+SJPXMB300Ks6svF+KJW8WR8GewIOV9gcY/v7To+h0Jt/Mrx8Rbd1clTMznlXrPrlfhU0z7krA0UzeZ/peJt/8arIvMvm/884R8ewOzv8Tk5f73T4iBvVzfn2tvVU7J0XEMsDOHY5VXap6uQ7P7YfVK+9vzcyc6sCqiNgUeMpAKuqPrWvtPzRShSRJkiRpOuZ548s8b24wz2vNPG8wzPMkSRoiH/TRqDip1n5yI1VMIzP/DBxZ6VoN+HBD5YyM8kbkG7Xu97Z5+quZvKTn7XQ2g6FjEbFROUb9ZvGAzLxkkGOPs3Km3r617gMpZgO1c/6DwJcqXQH8d4fL8LbrT7X2i9o87w0sucTsTBZV3q/b4bn9UF2CeZ2IaHep4oMY0X8DlAHN4ytd52XmMJcAlyRJkiS1xzxvTJnnzQ3meVNaVHlvntcH5nmSJA3fSP6jQHNSfbnYnRqpYmZ7M/mJ/12bKmTEHMTk2R17RMTLpjshIjYDPl/r/p/MvK3PtU2M99CI2JvipvGJtQ8fC3x8AGPOj4isveb3e5wh+gbw10p7G2CDDs7/DJO/T3YCDouI5TspIiI2iIjnT3PIb2rtt0bEI2a45nbAZzupo3RB5f2GEbFFF9foxbmV90sD75/phIj4KKP9u+tJwEqV9s+aKkSSJEmSNC3zvPFmntd6TPO8yczz+s88T5Ik9WwQT15LHcvMayPiDGDbsmuniJiXmfc3WVddZl4ZEV8C3t3Ldaa5OVyr1l5+mmMXlXstTzfO6ky9n3H95/9hU42VmQunGyczb42IDwFfq3QfVd6AfDYz76zUFMBuFEvHrlk5/gqKgKETK7eoOYBVKGZorU1x87ot8DQmL+074ZvAm8oZKppGZj4QEXtRBCndnH9rRLwSOIHF33+vBbaJiE8AR5czjZYQEesCz6O4of034FvA8VOMc2lE/JbFAeMqwK8j4jWZWV1WnIhYGXgH8FFgeYoZNe3OogH4LbBjpX1sRBxIsQf1LUB16d0Zf2a78F3gzZX2nhHxIHBgfX/6MrT4JItDgRsofkZGTX0J6WOaKEKSJEmSND3zvH8xz+uMed4Qmee1ZJ7Xf+Z5kiQNmQ/6aJQcweJgYA2Kf9T/srlypvQJ4I3Aqj1c44o2j9t2mmM/Cuw3w/nvYsnlWafynWk+NuNyrpn59YjYksXL/M6jmFWzZ0ScBlxH8TV7EvDQ2um3ALtm5s105mXlqxvXAu/PzCNnPFL/kpk/johT6HI/6Mz8TUQsAL7O4j2wt6S40T80Is4BrqFY9nllivDokcA6HQ71buBMYJmyvRnwh4g4D7gQeIBiWd8nVeq4APg/lpyZNp2vAe+jCB8AtgAOm+LYdn5mO5KZv46I44HqjKgPA/8VEX+g+D5fGdic4us84QLgf4Ev9LOePtmt8v6izDy9sUokSZIkSTMxz1uSed70zPOGzDxvCeZ5/WeeJ0nSkPmgj0bJUcDBwApl++WMYDCQmf+MiIOA/ZuuZQS9H7gT2JPFv19WBJ41zTmXAC/OzAsHXBsUszH+ABwKfDMz7xrwePUlbO+nuOEddx8Eft/tyZl5ZERcRBFGbVr50LLAk9u8zLQhUmaeWwYQh7M4HAB4dPmq+xPF3t/PaXP8iXGuKWc1fZupZ9sN2u4UvyurS1ivDDxziuPPAV4I7DzYsjpXzlJ6TKVrqpBFkiRJkjQazPPGn3neZOZ5LZjn9Z15niRJ6slSTRcgTcjMmyj2DJ7wynIZzlH0OYon61WRhX0oZi4dw+T9z+uuoJihtHWfQ4EHgLsoZhz9BfgpxV7SrwYenpnbZeZXhhAKAOxQa38zM29seeQYycxTgB/3eI0/UszseS1wGkVoMp0HgbMploN+QmbOuNx2Zn4beCpw0jSH/Y1ixswOmXlNG6W3Gud4ipk/7wWOAxZSBEBDWT66XD74qcDHgJumOfQiilBnu8y8egildaO6bPEdwFebKkSSJEmSNDPzvPFnnrcE87ypr2Ge1yfmeZIkqVeRmTMfJQ1JRGxGsQznxENob83MrzRYknoQEatSLAm7HsVSrXcC1wN/zMxLmqxtGCLiW8BryuZ9wBaZ2e4yz3NKRKwCbAesT7G87/IUN9f/pJgldkFm3trD9R9Osa/7uhQzja4FLgVOy1n0hzAilqMI5h5FsWT67cA/KL5+f2mytpmUtV8NPKTs+mJm/meDJf1LRDwKOG+ifdYf/8hWW23VYEX9df7557PNE6sTyHh0Zv61qXokSZIkjRfzvNnFPM88r13mef1hnjcY9Tzv7N//hq0euUWDFfXX+RdexOOfOmkBKPM8SZpj3LpLIyUzL4mII4HXlV3vioivzqZ/uM8l5Y3c8U3X0aCdKu8PNxSYWmbexgCX9i5nvBw1qOuPisy8B/hd+Ro3r2dxKHAX8KkGa5EkSZIktck8b3YxzzPPa5d5Xn+Y50mSpG64dZdG0T7AveX7LYFdG6xF6kpEPJJi5hMU38/uAS9NISLmUSxDPOGLI7wcsSRJkiRpSeZ5GnvmeVL7zPMkSWqWD/po5GTmQuDzla59I8LvVY2b6rqZX8/MvzVWiTT6Xg9sXL6/Afhkg7VIkiRJkjpknqdZwjxPap95niRJDfJmS6PqY8DEjdTWFP9olMbJxDK/9wAHNFmINMoiYiWK3/kT3p+ZixoqR5IkSZLUPfM8jTvzPKkN5nmSJDVvXtMFSK1k5h0RsTuwc9m1TJP1SJ3KzJc3XYM0JjYBvlq+vz0zv9FkMZIkSZKk7pjnadyZ50ltM8+TJKlhPuijkZWZpwCnNF2HJGlwMvPPwJ+brkOSJEmS1DvzPEma/czzJElqnlt3SZIkSZIkSZIkSZIkSWPAB30kSZIkSZIkSZIkSZKkMeCDPpIkSZIkSZIkSZIkSdIY8EEfSZIkSZIkSZIkSZIkaQz4oI8kSZIkSZIkSZIkSZI0BuY1XYAkSdI4ufjme7j/hruaLqNvLr/5nqZLkCRJkiRJkgbmt9fDpas2XUX//P36piuQJDXNFX0kSZIkSZIkSZIkSZKkMeCDPpIkSZIkSZIkSZIkSdIY8EEfSZIkSZIkSZIkSZIkaQz4oI8kSZIkSZIkSZIkSZI0BnzQR5IkSZIkSZIkSZIkSRoDPugjSZIkSZIkSZIkSZIkjQEf9JEkSZIkSZIkSZIkSZLGgA/6SJIkSZIkSZIkSZIkSWPAB30kSZIkSZIkSZIkSZKkMeCDPpIkSZIkSZIkSZIkSdIY8EEfSZIkSZIkSZIkSZIkaQz4oI8kSZIkSZIkSZIkSZI0BnzQR5IkSZIkSZIkSZIkSRoD85ouQOqniDgMWFA2v5uZrxrweOsA2wDrA6sDywF3ALcAVwKXAwszMwdZhyQNWkScCDxjop2Z0afrrgpcCqxddu2amcf049qSJEmSpNFnnidJg2GeJ0nS7OWKPpo1IuIpwOvL5r3AnjMcf2JEZPk6sYNxVouI90TEX4HrgOOArwAHAR8HPgt8HfgVRTBwU0T8KiI+HBHbdPg5rR0Rz4+IfSLiJxFxbaXmidf8Tq45xTjzIuKxEfGmiPjfiDgrIu6tjXN4l9de0KLmXl5Tfr4RMb9PY+wyxfV3rB23Yzdfk37rtK6IOLzF53x/RDyyi7Hr19qt289Ds0eLn8UFUx2bmbcCH6t0fT4iVhx4kZIkSZKkxpnndc88zzzPPE/9ZJ4nSdJ4cUUfzQoRsRRwCDDxRPqXM/OKAYzzIuD/gHU7OG114Fnla/+IWCMzF00zxnrAF4AnARt2XWwbIuLtwOuAxwErDHKsPrqr6QJmqaWBA4CXNl3IOIkBzYqZg/4XeDewMcXvvQ8B+zRakSRJkiRpoMzzumOepwrzvC6Y5/WNeZ4kSQ1yRR/NFrsDjy3f3wt8ut8DlE+wH8OSocDdwJ/Kjx0JHAucQrHcbzfWAXZjwKFA6bnA9oxPKHBKZl7XdBGz2K4RsV3TRWjuycz7gU9Vut4TxVLqkiRJkqTZyzyvO+Z5qjLPUyPM8yRJapYr+mjsRcQyTF4m8ojMvLrPYzwB+BqTH467HNgX+GFm3tninAA2B14A7Ao8tccyHgQuBjpejrULiyj2Jn94H671A+DELs5bDjgLWKnS97UurrNRF+dc38U5s8WnqMxokYbocIrfqetR/Nx/BPjPJguSJEmSJA2Ged5ALMI8b64yz1NTDsc8T5KkRvigj2aDVzH55u+QAYzxOYqlUCecAvxbuRdtS5mZwEXl67MRsSXFP3IfaHPMy4A/AmeW/3tWZt4eEdlF/dO5HTi7NtalFP9A37fXi2fm7eUYHYmIVzE5FLgN+H4X4y/s9Jw57ukR8YLM/FnThWhuycx7I+JrLF7i900R8bHMvLHJuiRJkiRJA2Ge1xvzPFWZ56kR5nmSJDXHB300G7y38v6MzDynnxePiPWBp1e67gdeM10o0EpmXgC8vY1DLwTWzMybO7l+l94K3JCZD9Y/UExgatQba+2jMvOORiqZ/Y4Bdqm0PxkRx7f6vpAG7KvAhymC2BWAdzB5hqckSZIkaXYwz+ueeZ7APE+jwzxPkqQGLDXzIdLoiojtWbyXN8C3BjDM02rt0zLzygGMA0Bm3j2kUIDMvG4Ub/4iYkPgmbXurzdRyxzxbeCcSvsxwOuaKUVzWWZeBfyu0vWWiPDfKpIkSZI0i5jn9TyWeZ7APE8jwjxPkqRmuKKPxt2CyvsHgaMHMMZ6tfZVAxhDk+3B5AcRz8vMM5oqZg5I4EPAzyt9H4uIozLznmEUEBFrAjsADwPWAu4GbgDOycy/DqOGURQRy1B8XTag+NosBfw1M386wzlbAlsA6wKrUHw9bwYuB/6QmXcOuPRefA/YqXz/cGBn4ITmypEkSZIk9dmCynvzvNnDPG+4zPNGlHmeeZ4kScPggz4aWxGxNPx/9u483r5y7v/461PfSvOg0qS+TZLIXMpUSLgNISLSYAi3+74zZMjQYMoc7kxpECpCoRuZKiQhivw09zVUVCoNSqrP74+1jrPO+p5hD2vvtfc5r+fjsR+PfV1nrev6fE9nWu/WdS2eV+k6LzOvGcBU9e+TtQYwh0pR7DG8T63b1T8DlpmnR8QPmVx5tTHwn8CHBzVn+d96D+AA4JHMsMtcRFwFfBz4WGbe3sG4hzD1efQ7Z+aZHda0GLiy0vW5zNxnjvGrH8tZhj8rM3fqpNYyKHkn8AKW/plzATAlGIiI9YHdgWdQBAkrz1LHXRHxHeD9mfnjWY5ryzeAT1bae2IwIEmSJEnzgnne/GSe1w7zvH+fuxjzvLaZ50mSNGRun6dxtiOwZqV9xoDmubbWfkxE3HtAcwmeBGxSad/JYLZw1tLeRLEaaMJBEbH6ICaKiM2A84ATge2Z/ffRhsDhwP+LiG0GUc8oiYhHA7+heJ51p0HkxcDHKFbLzBYKQBF2Ph34UUR8OCJG6qbfzLwauKTS9TS3+5UkSZKkecM8b34yz2uPed4IMM8zz5Mkadj8Ratx9pRae1B3sp9Ta68MnBARa053sPr20lr765l5fSuVLDCZ+UvgK5WuewNvbHqeiNgOOBd4aO1DfwO+D5wEnAJcWPv4YuDsiHhI0zWNkM0oVsBsWLZvA86k+JycRhEATKf++/yv5XlfowjWvg78Dri7dtxrgSP6K3kgqs/1Xht4eFuFSJIkSZIaZZ43P5nntcQ8bySY5xXM8yRJGqKRuutX6tKjau3zuzm5vuXmLMddFBG/BB5R6X4ycFlEHENxAfPzzLyrm/m1tHJ7091q3SOzzW+5XWy0XUddw3W9FXg2k78fDoiI/21qG+2IWA84leJib8K5wNuB72dm1o7fAvgAk18XqwNfjoiHZ+YtTdTUgyOA48r3J1GsYJqw6Szn3dHh2KtSPH/7IODY+nPVI2K6Oe6heCb7ycC3Z/rvVW4J/BrgDcDyZfd/RsRpmfmd6c7pRWYuob+vyfNr7R2AX/QxniRJkiRpNJjnzTPmeb0xzxu6IzDPm5V5niRJ48UbfTTOqneE35SZfx7gXK8DfsjU75m1KP64fgNwe0ScR/GH6y+An2bmHwZYz3z1ImCFSvuPwPf6GXCOZywvJTNH7sJ/mDLz0oj4LPDKsmsl4BBg/4amOBpYv9bePzPrK1Mm6rkMeHZEfBT477J7S4qVK4c1VFNXMvMm4CaAiLij9rElfQ6/KnAD8PjMrK+Ampjjymm6t+1k7jIweGtEnAF8m8mfaW+mCBZGxW9q7e2aGjgi1gXW6fK0zZuaX5IkSZIWOPO8+cc8r2XmeXMzzxsK8zxJkobIR3dpLJWrCKrPGh7oRXhm/hjYB/jnDIesCDyG4mLlBGBJRPwhIo6MiO1nOEdL26/WPjYz72mlkoXtUIotZifsFxFb9TtoRDwCeFql6xzgFTOFAjWvY+rF4msiYoWZDh5zB8wUCsyk20AiM78PfKrS9fiI2HCm41tQ/5l+vwbHfjXFNtLdvL7e4PySJEmStCCZ581b5nmjwTyvXeZ55nmSJA2VN/poXC2utQe5+geAzPwixZaeP+jwlI0p/gD9WUT8MCIePLDi5oGIeDjwkEpXAse2U83Clpl/AT5S6VoEvLuBof+71j6o0+CnDA8+Wulah2L71/nmT8AXhzTXV2vtHYc0byeupti+eMLiluqQJEmSJDVnca1tnjfmzPNGh3leq8zzCuZ5kiQNkY/u0rhat9a+cRiTZuYFwJPKi9i9gGcy+zN8J+xMERC8PDO/MMgax1h99c/3G9ouuZP/Plra+ym2+5149vZzI2L7zDy3jzGfVHn/F+CsLs8/o9Z+LHBmH/WMom80ueotIhYBq1BsIbxs7cP1bbC3bmrefmXmXRFxK7Ba2bV2RET9me+SJEmSpLFinjf/mOeNFvO8dpjnYZ4nSdKweaOPxtVKtfbtw5w8M88DzgMOiIiNKFYiPKx8bc/UbYgn3As4LiKuzczvDq3YMRAR9wL2rHUf3cTYDTxjeUHKzFsi4t1MXQl0OEXI1bWI2Jypz/K+DNgkoqtHqC9fa8/H5yz/up+Ty23QnwfsCjyIYiVip9bsZ+4B+AeTwUBQ/Ny/bebDO/YJ4OQuz9kct/uVJEmSpH6Z580j5nmjxzyvNeZ5k8zzJEkaEm/00biqf+3e1UoVQGb+meKPzJMBImIZYDuKFUL7UQQCE5YFjoqILTPzzmHXOsKeC6xRaf8NOLWVSlT1CeB/mNxmdaeIeFpmfquHse5baz8GuLKP2gDW6vP8UXRtLydFxErAIRT/veoBSqemCzTbVP+5vlwTg2bmtXT5ee4ywJIkSZIkTc88b34xzxtN5nnDZ543yTxPkqQhWabtAqQe1Vf8rNhKFdPIzHsy82eZ+Z/ANsBva4dsTHGHvibVt/n9Qmb+s5VK9G9lePX2Wvd7y/CrW/duoKS6VQcwZttu6faEiFgF+A5wIL2HAjB6fxPUf643sfpHkiRJktQe87z5xTxvBJnntcI8b5J5niRJQzJqfwRInbq51l65lSrmkJlXAE9j6T9on9xCOSMpIjZl6e1jG9nmV434InBBpb0t8KIexunngnUmLssovI/i+eYTEvgexWqgx1Cs4FoVWD4zY+LF6D/vvvpz/Y7M/FdrlUiSJEmSmmCeN0+Y540887zRZ54nSZL64o0+Gld/qrXXn/aoEVBuBfylWvf926hlRO3H1Au8X2RmfdWUWpKZCbyl1v3OiFihy6Gur7U/U71I7fG1U8//sJktO4AxByYi1gdeWem6A3hKZj45Mz+WmWdn5h8y89ZpLqxXY0RFxJpM3Sa9/jNfkiRJkjR+zPPmD/O8EWaeN9rM8yRJUhO80UfjagnFXe4TNmqpjk6dX2uv2UYRo6bcMnbvWvdn26hFM8vMbwNnVLo2AV7V5TB/rbXv11dRs6s/C3pRF+eO2/fm05n6u/z9mfndDs/dYAD1NGXDWrvf579LkiRJktq3BPO8sWeeNx7M80aaeZ4kSeqbN/poLGXmHcDFla6NI2KlturpwN219t9bqWL0PBm4b6X9D+CklmrR7N5ca781IrpZQfI7pn7d7xARg3omd30r8DW6OHebLufKuQ8ZqC1r7dO6OHfHJgtp2Na19vltFCFJkiRJao553rxhnjc+zPOmZ543GOZ5kiQNkTf6aJz9ovJ+GeCBbRXSgQfU2le1UsXoeWmtfXJm1i/qNAIy8+fAVytdawNv7OL8u4EfVLpWAPZqprqlXFtr17//ZvMfXc71z2qjhy2Q+7VGrd1R6BgRywIvbrya5mxba/+8lSokSZIkSU0zzxt/5nljwjxvRuZ5g2GeJ0nSEHmjj8bZWbX2doOYJCI2jYg1+jh/DeD5te4f9lPTfBAR9waeWes+uo1a1LGDmLqN7muB9bo4/+O19sHlM6mb9qta+xmdnBQR2wDP6XKum2rtQfx7ZnNjrX3/Ds97DbBpw7U0qfrz/B7gR20VIkmSJElqlHneGDPPG0vmeUu7qdY2z2uGeZ4kSUPkjT4aZ9+qtXce0DyPB5ZExGERsW43J5bbD58IrFPp/ifwtQbrG1d7ActX2pdk5o/bKmZQImJJRGTltU/bNfUqMy9hanizErBrF+efCXyv0rUu8K2I2KibOiJi1YjYc5ZDLgX+VGk/IiJ2m2PM+wAnA8t2Uwvw+1r7yV2e368Lau03lKt7ZhQRTwXeN7iS+hMRywGPrnT9IjOva6seSZIkSVKjzPPGm3nemDHPm5Z5XsPM8yRJGj5v9NHYysxrgHMrXTtHxKIBTbc68Hbgqog4LSL2nO1iJiJWjogXU/zR/pTahw/PzD/PNllErB0Ri6d7TXP4RjMcO+fFVkQsmmWeNWqHrzLTsRGxylxzTWO/WtvVP+PhUIpnr/dqb6D69f8Q4DcR8caIWHumk8ow4JkRcTTFVtnvmenYzEzgs7XuL0TEC6cZd9mIeB7FVrJbs/SKmrmcUWt/oPy3PCoitqh9n3SzWqpT3wZuqbQfC5wSEfetHxgR946Iw4FvUGy1PKoX2zsAK1fap7ZUhyRJkiSpYeZ5/2aep2Eyz5vKPK955nmSJA3ZoC6ipGE5Hti+fL8mxSqg7818eN8WUTzz9z8AIuIq4HLgb8BtwKrAJhTPEF5+mvO/DLyrg3k+SHEB1YmZVs38AVg8x7kbAVd2OM9zy9d09gWO63AcIuKRwIMqXXdR/LfUiMvMayLiCIptf3s9/+kUK/g2KLvXpFiRcnhE/B64guLZ1CtQBFSbU3wtR2WoG+aY6sPAPkxuZ7sycEJEfAD4JcX369rAI8v5AW4FXsbUZ5fP9e/5UUT8EnhE2bUaM6+uOQvYqdOxO5z/xoh4V23OZwBPi4jzKD6Xi4D7ljVOrA66FXgFcEqT9TRk98r7e4AvtFWIJEmSJGkgzPPM8zRE5nlL/XvM85pnnidJ0pB5o4/G3UkUF9Erlu3n0XwwcA3FRcrq03xsw/I1l9uB9wLvycy7G6xtXL201v6/zPxLK5UM3r1q7W5XmIyi9wH7A/fu5eTMvCAiHgp8nqlb4wZFqPaADoaZ9fOYmbdGsb3v6Ux97vhM37PXA89m6uqkTu0B/B+dP0+7UZn5/ojYAnh5pXtZiudibzfNKX+jeHb5H4dQXlciYhmmBpDfnWvFpCRJkiRp7JjnjSfzvPFmnjeVeV5DzPMkSWqHj+7SWMvMG4DPVbr26HHb2dnmOJ3imdxPplhVcC7wrw5PvwQ4DLh/Zr7TUAAiYkWgvuXqvNzmNyI2A+5T6boUOK2lchqTmTcD7+5zjGszc1fgcRRbud7WwWlXUmzh+1QmV9zMNsdvyuM+R7HKbDo3A58GHpSZP+mghunmuYJiy+IXU6zy+z1FmDjTnI3LzFeU8186y2HXAf8LbJOZPxpKYd17GpMrwwA+0lYhkiRJkqTBMM8bP+Z55nnlGOZ5DTLPkyRJ/Yji0afS+IqILYGLmLxxbf/M/MyA51wB2ALYElifYovf5Si2z7yZYpvdCzLzb4OsQ6MtIl4GHFXp2isz3bZ0GhGxiOIifguKlUWrUjw7/O8U29X+vp9VYhGxGkUIsZhiO97rKFbA/Cgzb++r+BESEUGxjfYjKALNu4G/UPxMOiczhxZW9CIivgk8vWz+NjO3bbOeCRGxDXDhRPvE753NZvdrZcHXQFxxyUW8cJdHV7semJm/a6seSZIkSfOfeZ5GlXle58zzmmGeNxj1PO/DX/sh991iqxYratafLruY1z3nCdUu8zxJWmB8dJfGXmZeGhFfBPYquw6IiKNygHexZeY/gd+VL2km1b+0LwJOaKuQUVdesP6sfA1i/JuZB6uv5lL+3PtN+RorEXF/ihVAEw5pqRRJkiRJ0oCZ52mEmed1yDyvGeZ5kiSpFz66S/PFO4A7y/dbUzybV2rbzpX3h2bmPa1VIo2+g5j8u+TczPxam8VIkiRJkgbOPE+jyDxP6px5niRJLfFGH80LmbkEOKLSdXBE+PWt1kTEA4D1yubvKJ71LGkaEbEV8MKymcAbWixHkiRJkjQE5nkaNeZ5UufM8yRJapcXTppPDqN4Ri/AtsDeLdYiVVf/HOLqH2lW72fycaKfy8yftFmMJEmSJGlozPM0SszzpM6Z50mS1KJFcx8ijYfMvC0i9gR2KbuWa7MeLWyZeSRwZNt1SKMuIlYDfgX8uuzy+0aSJEmSFgjzPI0S8zypM+Z5kiS1zxt9NK9k5tnA2W3XIUnqTGbeDBzadh2SJEmSpHaY50nSeDHPkySpfT66S5IkSZIkSZIkSZIkSRoD3ugjSZIkSZIkSZIkSZIkjQFv9JEkSZIkSZIkSZIkSZLGgDf6SJIkSZIkSZIkSZIkSWPAG30kSZIkSZIkSZIkSZKkMbCo7QIkSZLGyV6v+QCx4pptl9GYvP3GtkuQJEmSJEmSBuaNb/mYeZ4kaV5xRx9JkiRJkiRJkiRJkiRpDHijjyRJkiRJkiRJkiRJkjQGvNFHkiRJkiRJkiRJkiRJGgPe6CNJkiRJkiRJkiRJkiSNAW/0kSRJkiRJkiRJkiRJksaAN/pIkiRJkiRJkiRJkiRJY8AbfSRJkiRJkiRJkiRJkqQx4I0+kiRJkiRJkiRJkiRJ0hjwRh9JkiRJkiRJkiRJkiRpDHijjyRJkiRJkiRJkiRJkjQGvNFHkiRJkiRJkiRJkiRJGgPe6CNJkiRJkiRJkiRJkiSNAW/0kSRJkiRJkiRJkiRJksbAorYL0MIUEccC+5TNL2XmC1osZ16KiI2AbYDFwBpl943AVcDPM/O6Acz5MGBLYMOy6yrgksz8ddNzSRquiDgTePxEOzOjoXFXAy4D1im7np2ZpzYxtiRJkiSpOeZ5g2eeJ6lJ5nmSJM1f7uijoYuIRwN7l807gbfMcfyZEZHl68w5jl1cObb+un8fNR8/w5jHdTHGooh4cES8LCI+FRHnRcSdvY43zfirR8SLI+ILEXEV8CfgO8CngMPL16eB04BrI+L8iNg/Iu7V65zlvMtFxJsj4jLgPOAk4EPl6yTgVxFxaUS8KSKW62euDuvZp/Y5PbPBsXeqjb1TU2P3o9u6IuK4ab6W7+rle2SasXbv9d+h+WOan8X7zHRsZt4MHFbpOiIiVhp4kZIkSZKkjpnnmecNknmeeZ7aZ54nSdJ48UYfDVVELAMcCUzcOf7JzLxySNPv28tJUdyd/txeJ42IV0XET4GbgfOBo4D9gYcBjVwoR8RrgGuBzwMvAjbo4LQHU4QGv4qIR/Q475bAz4D3ApvPcugWFMHEORGxRS9zaeCWBd7TdhHjphZcZtv1jLFPAVeU7zcB3txiLZIkSZKkCvM88zzzvJFlntcD87zGmOdJktQib/TRsO1JcUEKxeqfDwxx7r0iYtkeznsB0M/d6LsCOwAr9jHGXBYDy0/TfzNwNnAKxWqcHwG3147ZGjgrIh7bzYQRsR7wPYqAo+oy4OvAN4DLax97OPDdiFi3m7k0NM+OiEe1XYQWnsy8C3hfpet1/pyQJEmSpJFhnjcYizHPU//M89QK8zxJktrljT4amnKb1+p2jsdn5lUDnvZflffrA0/tYYz9ZhivXzdRPPO6aX+mWMnxCGCtzHxMZj4nM1+YmY+neG7uG5gaEKwEfD0i1ll6uKWVK7lOpbhTf8I1wK6ZuWVm7paZz8rMLSg+53+pHLcpcEpENPI8YDXufXMfIg3EccDV5fuVgbe1V4okSZIkCczzpnET5nkaPeZ5astxmOdJktQKb/TRML2A4qJwwpFDmPOS8jWhq+1+I2JrYPtK1zd7rONW4MfARyhWQd0PWAv4bI/jTee3wO7AJpn51sw8LzPvrh+Umbdl5oeAncq6JqwJvLPDuV7E1M/LDcCOmfndaeb7DrAjcGOle0dgjw7n0nA9LiL+o+0itPBk5p1M/Zn4sohYu616JEmSJEmAeZ553iTzvNFlnqdWmOdJktQeb/TRML2+8v7czDx/SPMeW3n/jE5XuZReWnl/E8WWud3aH1g9Mx+Xma/LzBMz89LMbPL5vx8DHpyZX83Mezo5ITN/Dryl1r1HuVJrRuV2yYfWul+XmUtmmetK4HW17neVK4nUvlNr7ff630YtOQqYCDRXBF7dYi2SJEmSJPM887ypzPNGx6m1tnme2mKeJ0lSC/zDT0MRETsw+SxvgC8McfrPMfmH5nIUq1fmFBGLgBdXuk4E7uh28sz8a6cX673KzD/2GDQcw9R/0xrAQ+c45zFMXcl1FZ399/w8U7c23pxiJZDadwJwfqX9IGCvdkrRQpaZfwZ+VOl6hSGVJEmSJLXDPM88D/O8UWaep5FgnidJUjsWtV2AFox9Ku/vAb46rIkz85qIOB14Wtm1L3BEB6c+HbhPpX0MsLjR4lqWmf+IiIuZGtpsMMdpz661j59uS+Fp5ro7Ir4AvKnS/RzgJx0Vq0FK4M3Adyp9h0XESZn5z2EUEBFrUQRF6wFrUwRW1wHnZ+bvhlHDKCpX5O0IbEzxuVkG+F1mnjbHOVsDWwHrA6tSfD5vBK4Afp6Z/xhw6f34MrBz+X5DYBfg9PbKkSRJkqQFa5/Ke/O8EWGep5J53ogyzzPPkyRpGLyrVgNXbg37vErXeZl5zZDLOKbyftuIeHgH51S3+b0wM3/ZcE2j4q5ae/k5jn9KrX1mF3PVj31qF+dqgDLzdOCHla6Ngf8c5JxReEFE/IwiBPgmxVav7wU+QrGy7MKI+HNEvCkiVuxw3EMiIiuvnbqoaXHt3ONmGx94fO1jOcvrzE5rjYi1IuJI4C8U3zfHA+8HDgfeNc0460fEf0XEdykCgAsoLrA/Wh7/QeBo4Azg7xHxzYh4bKeflyH7Rq29ZytVSJIkSdICZp438szzZJ43ea55XvvM8yRJGjJv9NEw7AisWWmf0UIN3wCur7T3ne3giFiPqRfAx8x07DiLiAA2q3XPGNpExArAFrXun3Ux5U9r7S0jYq4gQsPzJorVQBMOiojVBzFRRGwGnEexhfb2zP77aEOKC+L/FxHbDKKeURIRjwZ+Q/E867U6PO1i4GMUq2VWnuPYRRQrHH8UER8utzUfGZl5NXBJpetpbvcrSZIkSUNnnjeizPNUY543AszzzPMkSRo2f9FqGOorRn487AIy819Mfe70nuVF7kz2ZvLRdvVz55MnMjW0uZNi5cBMtgKWrbSvzcybO52sPLYa0CwL3K/T8zVY5Sq3r1S67g28sel5ImI74FyWfn7834DvAycBpwAX1j6+GDg7Ih7SdE0jZDOKIHPDsn0bxQqgk4DTKAKA6dR/n/+1PO9rFD+/vg78Dqhvy/1aOtv6fNiqz/VeG+hk1aYkSZIkqTnmeaPLPE//Zp43EszzCuZ5kiQN0Ujd9at561G19vndnJyZOzVUxzHAAeX7NYHdgC/NcGx1hdBpmXldQzWMmtfW2j+Y40K/vvrnjz3M+UeKP/QnbMnSF4AjKTPPBKLtOuoaruutFM9tn/j9cEBE/G9T23OXq+tOZerXwLnA24HvZ2bWjt8C+ADF9yvA6sCXI+LhmXlLEzX14AjguPL9SRQrmCZsOst5d3Q49qoU2/UeBBxbf656REw3xz0Uz2Q/Gfj2TP+9ImJ94DXAG5jc1vs/I+K0zPzOdOf0IjOX0N/X5Pm19g7AL/oY798iYl1gnS5P27yJuSVJkiRpjJjnjS7zvC6Y5/XPPK+jsc3zzPMkSRoqb/TRMFTv3L4pM//cRhGZ+duIOK9Sz75MEwyU22xuVemar9v8Phd4Wq37g3OctkatfW0PU9fPGchWsupNZl4aEZ8FXll2rQQcAuzf0BRHA+vX2vtnZn1lykQ9lwHPjoiPAv9ddm9JEWod1lBNXcnMm4CbACLijtrHlvQ5/KrADcDjM3PawCwzr5yme9tO5i4Dg7dGxBnAt5n8O+DNFMHCqPhNrb1dg2O/Gji4wfEkSZIkaT4yzxtB5nmajnne3MzzhsI8T5KkIfLRXRqo8m7/6oXfH9qqpVS9yN8lIjaa5pj9Ku//wmj9sdyIcgXBUbXukzPzh3OcukqtfXsP09fPWbWHMTRYh1JsMTthv4jYaqaDOxURj2BqGHUO8IqZQoGa1zH1YvE1c2zXPc4OmCkUmEm3gURmfh/4VKXr8RGx4UzHt6D+u8ItwSVJkiRpSMzzRpN5nuZgntcu8zzzPEmShsobfTRoi2vtVlb/VJzA5Haby1A8u/vfImJl4PmVruMz864h1TYUEbEa8E2mPsv7Goq74udSDwY62bq0rh4M1MdUyzLzL8BHKl2LgHc3MPR/19oHZeY9HdZ0N/DRStc6FNu/zjd/Ar44pLm+WmvvOKR5O3E1xfbFExa3VIckSZIkLUSLa23zvJaZ52ku5nmtMs8rmOdJkjREPrpLg7ZurX1jK1WUMvOmiDgFeGHZtQ9TL3iez9QL1WOHVNpQRMTywNeAbSrddwLPz8zrexgy5z6kkXM0fO+n2O534tnbz42I7TPz3D7GfFLl/V+As7o8/4xa+7HAmX3UM4q+0WlY0omIWETxM21VYNnah+vfi1s3NW+/MvOuiLgVWK3sWjsiov7M9x59guLZ593YHPh6A3NLkiRJ0jgwzxsh5nnqgnleO8zzMM+TJGnYvNFHg7ZSrd3L1rBNO5bJYGCLiHhsZv64bL+0ctw5mXnRcEsbnIhYFjgReGKl+y7gBZn5kw6HubXWXrGHUurn1MfUCMjMWyLi3UxdCXQ4sHMv40XE5kx9lvdlwCYR0c0wy9fam/dSy4j7dT8nl9urPw/YFXgQsHEXp6859yFD9Q8mg4Gg+H1y28yHdyYzrwWu7eacLr9OJUmSJGncmeeNCPM8dcM8rzXmeZPM8yRJGhJv9NGg1b/GRmHb3O9TPC92k7K9H/DjiLgf8OjKccfUTxxXEbEMRSDynEr3PcDemXlKF0MZDCwsnwD+h8ltVneKiKdl5rd6GOu+tfZjgCv7qA1grT7PH0VdXbBOiIiVgEMo/nvVA5ROrd7jeYNS/32xXCtVSJIkSdLCY543Aszz1CPzvOEzz5tknidJ0pAs03YBmvfqK356uZBsVLlV5OcqXc+LiFUoAoIJ/wC+PNTCBiSKW9c/BexV6U7gZZl5QpfD/b3WXqeHkurbP9/Uwxgagsy8E3h7rfu9ZdDUrXs3UFLdqgMYs223dHtC+fPrO8CB9B4KwOj9TVD/fdH36h9JkiRJUkfM81pmnqdemee1wjxvknmeJElDMmp/BGj+ubnWXrmVKpZ2LJPPs12ZYuvfl1Q+/pXMrNc+rj4OvLzW9+rM7OV55ZfW2ptMe9Ts6ufUx9Ro+SJwQaW9LfCiHsbp54J1Ju6/WngfxfPNJyTwPYrVQI+hWMG1KrB8ZsbEC9h02IV2qfr74o7M/FdrlUiSJEnSwmKe1z7zPPXDPG/0medJkqS++OguDdqfau31pz1qyDJzSUScyeTzid/H1OfZ9nLRPHIi4sPAf9a6D8jMT/U45MXA3cCyZXvdiFg1MztatRARqwFrV7ruxmBgpGVmRsRbgOr2vu+MiC9n5j+7GOr6Wvszmbl//xU2btm5DxkdEbE+8MpK1x3AszLzux2cvtrch7QjItYE7lXpqv8ukSRJkiQNjnlei8zz1C/zvNFmnidJkprgjj4atCVMrrQB2KilOqZTfWZ3NRS4AjhryLU0LiLeB7y21n1gZn601zHLC8HLa907dDHEjrX2pV1eXKoFmflt4IxK1ybAq7oc5q+19v36Kmp29WdBd3NT65pzHzJSns7U3+Xv7zAUANhgAPU0ZcNau9/nv0uSJEmSOrcE87xWmOepKeZ5I808T5Ik9c0bfTRQmXkHxaqRCRtHxEpt1VPzVZZ+RjXAceVzv8dWRLwTeGOt+62Z+cEGhv9Orb1TF+fWj/12X5VomN5ca7+1XNHVqd8x9ftth4gY1DO569t0r9HFudt0OVfbPyu2rLVP6+LcelA3Srautc9vowhJkiRJWojM89phnqcBMM+bXts/K8zzJElS37zRR8Pwi8r7ZYAHtlVIVWbeDpxU674HOG741TQnIt4BvK3WfWhmvqehKU6ptfeKiDm3Ry2PefEcY2lEZebPKcK0CWuzdPg02/l3Az+odK0A7NVMdUu5ttZ+QBfn/keXc01ZwRYRK3R5fr/WqLWnCzuXMsP34yjZttb+eStVSJIkSdLCZZ43ROZ5GgTzvBmZ5w2GeZ4kSUPkjT4ahvq2udu1UsX03g48tvLaPjPH9tmxEXEgcGit+72ZeUiD0/yYqdtubkRnFxgvZur2nZcDZzdYlwbvIKZuo/taYL0uzv94rX1w+Uzqpv2q1n5GJydFxDbAc7qc66ZaexD/ntncWGvfv8PzXgNs2nAtTar+nrgH+FFbhUiSJEnSAmWeNyTmeRow87yl3VRrm+c1wzxPkqQh8kYfDcO3au2dW6liGpl5XWb+pPL6Zds19Soi/gt4f637Q5l5UJPzlCs5Dq51fzgiFs9S22LgI7Xut2XmPU3WNooiYklEZOW1T9s19SozLwGOrnStBOzaxflnAt+rdK0LfCsiNuqmjohYNSL2nOWQS4FqwPeIiNhtjjHvA5wMzLmareb3tfaTuzy/XxfU2m+Ya0VeRDwVeN/gSupPRCwHPLrS9YvMvK6teiRJkiRpgTLPGwLzvNFknjfl/DMxz2uaeZ4kSerborYL0PyXmddExLnA9mXXzhGxKDPvmu28+SIiFlGskpnOGrX2KrNcYF+fmbfOMMd+wEdr3V8D/ne2C/YZ3JSZN81xzBeB/2Tyv+lawE8jYp/M/G6ttl0ptk9es9L9U+BLXdbVq3v18DmY0MnnYqE5lGKL3pV6PH9vim1bJ74nHgL8JiIOB47JzOunO6l8/vfOwLOA5wE3ACdMd2xmZkR8lqmr4b4QES/PzBNr4y5Lserng8DGFCtqql+rczkDOKTS/kBErEGxYuV6pq6YuiMz/9LF2J34NnALMPF89McCp0TEf9ZXM0bEvYEDgddT/P6/Dlin4XqasAOwcqV9akt1SJIkSdKCZZ5nnod53nxinjeVeV7zzPMkSRoyb/TRsBzP5EXkmhR/4H9v5sPnlY2YujXubJ5bvqazLzM/b/wlQNT6nkP325ZCcTF1yGwHZOY9EfFs4GcUF1NQbHF6ekRcCvyurGcbYIva6UuA52Rm9lBbL7an889/3Zyfi4WmDPqOoNj2t9fzn06xMnCDsntNihUph0fE74ErKJ5NvQJFeLY5sJipX+M3zDHVh4F9mNzOdmXghIj4APBL4DaK55I/kskg4FbgZUx9dvlc/54fRcQvgUeUXasx8+qas4CdOh27w/lvjIh31eZ8BvC0iDiP4nO5CLhvWePE6qBbgVcApzRZT0N2r7y/B/hCW4VIkiRJ0gJnntcZ87zmmec1yDxvqX+PeV7zzPMkSRoyb/TRsJxEcYf9imX7eSycYGBeKi/wdqH4b/vQyoe2LF/T+RWwR2b+ddD1jZB71dr1ZzCPo/cB+wP37uXkzLwgIh4KfJ6pW+MG8IDyNZdZP4+ZeWu5ve/pTH3u+IZMfbb8hOuBZwN/7mDuuj2A/6Pz52k3KjPfHxFbAC+vdC9L8Vzs7aY55W8UoeEfh1BeVyJiGaaGo9/NzF7+m0iSJEmS+meeN8+Y53XMPK/GPK9Z5nmSJKlfy7RdgBaGzLwB+Fyla4+IWKWtetSM8hnP2wNvoVhpMJPLy2MelZmXDaO2URARmwH3qXRdCpzWUjmNycybgXf3Oca1mbkr8DiKrVxv6+C0K4HPAk9lcsXNbHP8pjzuc0zdcrfqZuDTwIMy8ycd1DDdPFdQbFn8YuDLFM/5/vssczYuM19Rzn/pLIddB/wvsE1m/mgohXXvaUyuDAP4SFuFSJIkSdJCZ543P5nnzc48b9YxzPMaZJ4nSZL6EcPbbVMLXURsCVzE5A1m+2fmZ1osSQ2LiIcD92PyD/urgUsy87z2qmpPRLwMOKrStVdmum3pNCJiEcVF/BYUK4tWBf5BcYF9BfD7fp6HHRGrUYQQiym2472OYgXMjzLz9r6KHyEREcCDKD6X6wB3A38B/gCck5lDCyt6ERHfBJ5eNn+bmdu2Wc+EiNgGuHCivWir3YgVu3n0+2jL22/krotPrXY9MDN/11I5kiRJkkaIed78Z543lXle58zzmmGeNxjmeZKk+c4bfTRUEXE8sFfZ/D3Fneh+EWpeiogTgBeWzYsovt7vabEkaWRFxP2B3zEZHj83M7/WYkn/ZjAgSZIkaSEzz9NCYp4ndc48rz3meZIkH92lYXsHcGf5fmuKZ+hK89XOlfeHGgpIszqIyb9Lzh2VUECSJEmSZJ6nBcU8T+qceZ4kSS3xRh8NVWYuAY6odB0cEX4dat6JiAcA65XN31E861nSNCJiKyZXyyXwhhbLkSRJkiRVmOdpoTDPkzpnnidJUru8IFMbDqN4li7AtsDeLdYiDUp19c8hrv6RZvV+YFH5/nOZ+ZM2i5EkSZIkLcU8TwuBeZ7UOfM8SZJatGjuQ6RmZeZtEbEnsEvZtVyb9UiDkJlHAke2XYc06iJiNeBXwK/LLr9vJEmSJGnEmOdpITDPkzpjnidJUvu80UetyMyzgbPbrkOS1K7MvBk4tO06JEmSJEmzM8+TJIF5niRJo8BHd0mSJEmSJEmSJEmSJEljwBt9JEmSJEmSJEmSJEmSpDHgjT6SJEmSJEmSJEmSJEnSGPBGH0mSJEmSJEmSJEmSJGkMLGq7AEmSpHGy+eN2ZcV1Nmm7jMbcft0fuPjiU9suQ5IkSZIkSRoI8zxJ0nzjjj6SJEmSJEmSJEmSJEnSGPBGH0mSJEmSJEmSJEmSJGkMeKOPJEmSJEmSJEmSJEmSNAa80UeSJEmSJEmSJEmSJEkaA97oI0mSJEmSJEmSJEmSJI0Bb/SRJEmSJEmSJEmSJEmSxoA3+kiSJEmSJEmSJEmSJEljwBt9JEmSJEmSJEmSJEmSpDHgjT6SJEmSJEmSJEmSJEnSGPBGH0mSJEmSJEmSJEmSJGkMeKOPJEmSJEmSJEmSJEmSNAa80UeSJEmSJEmSJEmSJEkaA97oI0mSJEmSJEmSJEmSJI2BRW0XIM0lIo4F9imbX8rMF7RYzrwUERsB2wCLgTXK7huBq4CfZ+Z1A5jzYcCWwIZl11XAJZn566bnktS/iFgCbFI2/5CZixsadzFwEbACcA+wXWae18TYkiRJkqR2mOcNnnmepLmY50mSNH+5o49GWkQ8Gti7bN4JvGWO48+MiCxfZ85x7OLKsfXX/fuo+fgZxjyuizEWRcSDI+JlEfGpiDgvIu7sdbxpxl89Il4cEV+IiKuAPwHfAT4FHF6+Pg2cBlwbEedHxP4Rca9e5yznXS4i3hwRlwHnAScBHypfJwG/iohLI+JNEbHcHGO9r/b5uCgiVuyjtvtExHW1MfevHbNP7eOLe52vSd3WVfs+mXjdFBH37mHu+liP6PkfonkjInaqfV3sNNOxmbkE+N+yuQzwiYjw7xNJkiRJGlPmeeZ5s4xlnlcyz9OoMc+TJGm8+ItXI6v8w/BIIMquT2bmlUOaft9eToqI1YDn9jppRLwqIn4K3AycDxwF7A88DJj1QrmLOV4DXAt8HngRsEEHpz2YIjT4Va8XfhGxJfAz4L3A5rMcugVFMHFORGwxy3FvB35baW9VnterTwFrV9qnZ+an+xhv3KwOvLXtIsZNRCypXPwuabueMfZuip97ANsxuepTkiRJkjRGzPPM88zzhso8rwfmeY0xz5MkqUXe6KNRtifFBSkUq38+MMS594qIZXs47wXASn3MuyuwA9DzSpYOLAaWn6b/ZuBs4BSK1Tg/Am6vHbM1cFZEPLabCSNiPeB7FAFH1WXA14FvAJfXPvZw4LsRse50Y2bmncBLgH9Vuv8rInbuprayvpcAu1W6bgRe2u0488CrI2KTuQ+TmpWZN1IEwRMO6XfFoSRJkiSpFeZ5g7EY87x6feZ5BfM8tcI8T5Kkdnmjj0ZSuc3rYZWu4zPzqgFPW73AXB94ag9j7DfDeP26ieKZ1037M/Ae4BHAWpn5mMx8Tma+MDMfD6wDvIGpAcFKwNcjYp1OJihXcp3K5LOAAa4Bds3MLTNzt8x8VmZuQfE5/0vluE2BUyIimEZmng8cWp0OOLZcidWRiNgQ+Git+zVD+HobRSsw9ftOGqYPA3eU7+8LvLrFWiRJkiRJXTLPW8pNmOctxTyvceZ5apN5niRJLfFGH42qF1BcFE44cqYDG3RJ+ZrQ1Xa/EbE1sH2l65s91nEr8GPgIxSroO4HrAV8tsfxpvNbYHdgk8x8a2ael5l31w/KzNsy80PATmVdE9YE3tnhXC9i6uflBmDHzPzuNPN9B9iRYgXOhB2BPWYZ/3Dg3Ep7E4rPXac+C6xRaX81M0/o4vz55sUR8aC2i9DCk5nXA1+udL2uDIklSZIkSePBPM88b4J53nCZ56kV5nmSJLXHG300ql5feX9uudJjGI6tvH9Gp6tcStWtYW+i2DK3W/sDq2fm4zLzdZl5YmZempnZw1gz+Rjw4Mz8ambe08kJmflz4C217j3m+qO93C750Fr36zJzySxzXQm8rtb9rnIl0XTH3w3szdRVSvtFxNNnq62s7xXAUypdfwVeOdd589CplffL0N+z0aV+fKryfkPghW0VIkmSJEnqmnmeeV6Ved5gnVp5b56nNpnnSZLUAm/00ciJiB2YfJY3wBeGOP3ngImVMMtRrF6ZU0QsAl5c6TqRyS0rO5aZf+30Yr1XmfnHHoOGY5j6b1oDeOgc5zyGqSu5rqKz/56fZ+rWxptTrASaVmZeDLy51n1URNx7pnMiYjHwwVr3K8pVCAvNRyi2X57wtIh4fFvFaOHKzHOAKypdr2qrFkmSJElS58zzzPMwzxs28zyNBPM8SZLasajtAqRp7FN5fw/w1WFNnJnXRMTpwNPKrn2BIzo49enAfSrtY4DFjRbXssz8R0RczNTQZoM5Tnt2rX38dFsKTzPX3RHxBeBNle7nAD+Z5bSPA88CnlC21wM+wTTbBJfPCD8GWLXSfWxmfmOu2uapf1Cs1Kquvngf8KhhFRAR61NsCb0ucG+KraWvBX6RmVfMdu58FhErUgRsG1L8jLkb+Hlm/miWc+4FPADYiuLzuQrFf+MbgYuB8zLzzgGX3o+Tmfzef1REbFWGf5IkSZKk0bVP5b153ogwz5vXzPNGlHmeeZ4kScPgjj4aKeXWsM+rdJ2XmdfMdPyAHFN5v21EPLyDc6rb/F6Ymb9suKZRcVetvfwcxz+l1j6zi7nqxz51toPLVU37AjdXup8fES+Y5vD/AnautP8IHNBFbfPR0Ux9pv32EfGcQU4YEctFxCsj4jfA1RTbY38aeA/FltQnAZdHxCUR8YpypV0n4x4XEVl5Le6ipp1q5x4y2/gUz5CfsEnt3PrruE5rjYj7RsTnKcKR71JsQ3448AGW3gqbiNgsIt4cET8C/g6cB5xAEWy+C/hwOcZPgb9HxBcjYttOPy9DVg/o9mylCkmSJElSR8zzRp553vxlnod53ogwz5Mkaci80UejZkdgzUr7jBZq+AZQ3e5139kOjoj1mHoBfMxMx46zctXMZrXuGUObiFgB2KLW/bMupvxprb1lRMwaRGTmdBf4R5arSybq2hJ4b/U0YN/MvJkFLDPvAt5a635PGdY1rgzcLgI+CTxojsO3pAgMfhERGw6inlESEbsBv6HYPnyVDo5fC7ic4uv6scwd2N2L4mL7VxFxYF/FDsYvgNsq7ae3VYgkSZIkqSPmeSPKPG9+M88bHeZ55nmSJA2bN/po1NRXjPx42AVk5r+Y+tzpPcuL3JnszeRj8OrnzidPZGpocydwwSzHbwVULyqv7ebiuzy2GtAsC9yvg/OOBb5Z6VoL+CxARCwDHAesVPn4xzPzh53WNZ9l5leAcytdWwH7NT1PRDwd+BHTB03foVi58nXg0trHHwKcGxEbNV3TCNmeYuXTGmX7JuB7wInAt4E/THPOdL/L/wR8n2Kr9C8CpwGXUQRhE5YF3h8Rb2ig7saUP4PPqXQ9NCLWbaseSZIkSdKczPNGl3nePGeeNxLM88zzJEkauo62TZSGqP4M4fO7OTkzd2qojmOYXEmyJrAb8KUZjq2uEDotM69rqIZR89pa+wdzXOjXV//8sYc5/wisXWlvCVzYwXkvL4+bOPdpEfEyipBgx8pxlwBv7rSYzDyOIlgYKQ3X9Wamrrw7JCK+kJm3NzF4RDyA4sK3Gs58Bzg4M38+zfEPBT5KsbIFimdbnxgRO3XyfPgBeQNwSPn+J2VNAFdRPH97Jrd2MPZRwArAn8t5vlL9d5Yr8TaZ5rx/AacCXwO+m5k3TDd4RGwGHAjsD0TZ/d6IOD0zf9tBfR3JzDMr4/fifOBJ5fug+N1Q3wJYkiRJkjQazPNGl3meeV7fzPPmZJ5XOB/zPEmShsYbfTRqqs/Pvikz/9xGEZn524g4r1LPvkwTDETEoylWSUyYr9v8Phd4Wq37g3OctkatfW0PU9fPWb2TkzLzrxHxKuDkSveHmboF6t3AS5q64J0vMvPMiPgOk6vxNqAIyd4740kdKldgfQlYudJ9SGYeOks9v46IJ5TnTTxj/DHAi4Dj+62pF5l5PeXqtIioPuf+rsxc0ufwqwJXAI+f7udf+ez6+hw3A4sz8+q5Bs/MK4BXRcS5FM/4huJvgdcD+/ReduN+U2tvR0PBQLmaaJ0uT9u8ibklSZIkaZ4yzxtB5nkLh3ne3MzzhsI8T5KkIfLRXRoZ5bOxqxd+021pOUzVi/xdZthetLoN6l8oVjLMKxGxKcWqhKqTO9get/4s4l4uwOvnrNrpieW2tV+snVvdsvm9mXkums6bgHuq7fK50f16DvDASvvLs4UCE8rnje/N1KBopLanbdg+3YSimXlnJ6FA7ZzjKLb/nfD8iFiumzEGrP7zf85tvrvwaooVgt28vt7g/JIkSZI0b5jnjSbzvAXJPK9d5nnmeZIkDZU3+miULK61W1n9U3ECcEf5fhmKC5N/i4iVgedXuo4vL2DmjYhYjeL52NVneV9D8Yf1XOrBwB3THjW7ejBQH3Mur6HYfrXufOCwHupZEDLzNxRf/xNWBw5qYOj/rk5Dd9ss3wp8utL1oIhY3EBNo+bszPzxkOb6auX9ihTPTB8V9Z//i9soQpIkSZI0p8W1tnley8zzFibzvFaZ5xXM8yRJGiJv9NEoWbfWvrGVKkqZeRNwSqVrn9ohz2fqheqxzCMRsTzF84G3qXTfCTy/3Oq0WzmkcyZPLv4bvmqaD+2Vmf/qZ+wF4O0U/70nvCYiNu51sDJIe1Sl6xeZeWWXw5xRaz922qPG26lNDhYRy0XEWhGxcUQsrr4ongNetXWTc/ep/vO//vtBkiRJkjQazPNGiHnegmee145TmxzMPE+SJHViUdsFSBUr1dqj8KzlY4EXlu+3iIjHVu7Of2nluHMy86LhljY4EbEscCLwxEr3XcALMvMnHQ5za629Yg+l1M+pj9mJ39Y7MvPCHsZZUDJzSUR8EvifsmsFilVT+/Q45KOA6layV/Swgqd+c+p8fM7yr/s5udyaew/gCRTbKq/fxelrzn3I0Pyj1l552qN68wng5C7P2Ry3+5UkSZKk6ZjnjQjzPJnntcY8r2CeJ0nSEHmjj0ZJ/etxFLbN/T7Fs2U3Kdv7AT+OiPsBj64cd0z9xHEVEctQBCLPqXTfA+ydmadMf9a0RiUYUO/eBewLrFa294qID/YYrNy31n5B+epHE88ZHzXXzn3I0iLi3sD7KYKbXnfrW73H8wah/vO/seeNZ+a1dPl5joimppckSZKk+cY8bwSY56nCPG/4zPMK5nmSJA2Rj+7SKKmv+OnlQrJRmZnA5ypdz4uIVSgCggn/AL481MIGJIq/fj8F7FXpTuBlmXnC9GfN6O+19jo9lFTf3vOmHsZQj8otnT9Q6VoGeG+Pw927/4qWsuoAxmzbLd2eEBHrAz+m+LnUz+/1UfqboP7z/7ZWqpAkSZIkzcU8r2Xmeaoyz2uFeV7BPE+SpCEapT8CpJtr7Sa3duzHsUw+W3pliq1/X1L5+Fcys177uPo48PJa36szs5fnlV9aa28y7VGzq59TH1OD9xHgL5X20yOil2dpL99QPVUuyyh8lqnP474LOAV4JcUWy/elCFGWy8yYeAE7D73SztV//s+Xn7GSJEmSNN+Y57XPPE915nmjzzxPkiT1xUd3aZT8qdbu5lm0A1M+2/hMJv+Ifh9Tn33by0XzyImIDwP/Wes+IDM/1eOQFwN3A8uW7XUjYtXM7GiFQ0SsBqxd6bobg4Ghy8zbIuIwiucgT3gfsGOXQ11fax+Umb2uJhqkZec+ZHRExHbA0ypd1wO7ZuavOjh9tbkPac0GtXb994MkSZIkaTSY57XIPE/TMc8bbeZ5kiSpCe7oo1GyhMmVNgAbtVTHdKrP7K6GAlcAZw25lsZFxPuA19a6D8zMj/Y6Zmb+E7i81r1DF0PULzwvLcfU8B3F1FBmh4jYrcsx/lpr36+vimZXfx50Nze1rjn3ISPlWbX2GzsMBWDpi+9RsmGtfWUrVUiSJEmS5rIE87xWmOdpDuZ5o8s8T5Ik9c0bfTQyMvMOilUjEzaOiJXaqqfmqyz9jGqA48rnfo+tiHgn8MZa91sz84MNDP+dWnunLs6tH/vtvipRzzLzLuCtte73REQ3q2XOYWrwt0v5DPlBqG8Lu0YX527T5Vxtf/9vWWuf1sW53a7iGqata+3z2yhCkiRJkjQ787x2mOdpLuZ5s2r7+988T5Ik9c0bfTRqflF5vwzwwLYKqcrM24GTat33AMcNv5rmRMQ7gLfVug/NzPc0NMUptfZenVxMlse8eI6xNESZeTJTvz+3Bvbt4vzrgF9XujYEntpMdUu5ttZ+QBfnPm3uQ6aorkpboctzm7BGrT1dgLmUiFgd2K3pYhq0ba3981aqkCRJkiR1wjxviMzz1CnzvBmZ5w2GeZ4kSUPkjT4aNfVtc7drpYrpvR14bOW1fWaO7XNmI+JA4NBa93sz85AGp/kxU7fo3IilL/in82KmbvV5OXB2g3WpN2+qtQ8BVuzi/P+ttT8YEav0VdH06lvdPqOTkyJiV7r/mXNT5f3aEbFcl+f368Za+/4dnncIsGqzpTSq+t/hJlwBJEmSJEmjzDxvSMzz1APzvKXdVHlvntcc8zxJkobIG300ar5Va+/cShXTyMzrMvMnldcv266pVxHxX8D7a90fysyDmpwnM+8GDq51fzgiFs9S22LgI7Xut2XmPU3WNiwRkbXXTm3X1KvMPAM4vdK1Id1dSB8PXFRpbw2cEhFdPUc7ItaJiOfMcsg5wD8q7WdHxCPmGHNL4HPd1FH6feX9Iob/M+uCWvvNc50QES8F/mcw5fQvIjZg6jPfTy9/lkiSJEmSRpN53hCY5w2Ped4U5nnNM8+TJEl980YfjZTMvAY4t9K1c0QsaqueYYuIRRGxeLoXS2/pucpMx862qiIi9gM+Wuv+GvC/s4w306te03S+yNT/pmsBP42IJ09T264UF3XVC8WfAl/qYB4Nx5vp8TnW5cXd7kx95vaTgN9ExKsiYsYVKRGxVkTsEREnAn8C/nuWeW5h6tfMssD/zfA1t3xEvBz4GXAfll5RM5czau1jI+LVEfHwiNis9v2ydpdjd+IrQPWi+YURcVRE3Lt+YERsFBFHAZ8FArhuAPU04Um19qltFCFJkiRJ6ox5nnke5nmjzjxvKvO85pnnSZI0ZAvmgktj5Xhg+/L9mhR31H+vvXKGaiOmbo07m+eWr+nsy8zPG38JxUVB1XPKV7cOpdgydEaZeU9EPJviwmvjsnt94PSIuBT4XVnPNsAWtdOXAM/JzJ4uRNW8zDy/vDjfs8fzfxcRz6W4oF297N4I+ATw8Yj4LfBHivBgJYpA7H7lMd14O/BsJgO1dSm+5i4DfkPxLO77UPysWbk85i8U2xl3sxLoZODdlfo2AI6c4djPAft0MfacMvOSiPgM8KpK98uAvSLi5xQhyr2AzYAHM/m9/xfgQODzTdbTkN0r7/+OwYAkSZIkjQPzvM6Y52nozPOWYp7XPPM8SZKGzBt9NIpOAj7I5LOCn8fCCQbmpcy8JiJ2ofhv+9DKh7YsX9P5FbBHZv510PUNSkTca5rubleYjKK3UVy8Ld/LyZn5/XLr3ROB6ha8ywIPKV9zmfXzmJlXlQHEqUx9dvUWLB1AQRHI/QdFWNCxzLy9DL5OZepz6IfpAIrQ7T8qfSsAj53h+CXA04F1BlpVDyJidaC6UuvEzLyjrXokSZIkSR0zz5tnzPOmMM8zz2vaAZjnSZKkPvjoLo2czLyBqXfg7zHb1rUaD5l5CcVqi7cAV8xy6OXlMY/KzMuGUdsA7Vhrn5GZ9Wcwj53MvBL4VJ9jXEbxPPBnAN+nWJEzl98DH6e44J1zxVpm/rCc4+vMvD3xdcAHgIdk5u9nOGaueX4JPAB4JUVAcBnFCqahPIc6M+8EnkkREFw9y6F/At4DPDgzfzeE0nqxF0WoAcV/s/q25JIkSZKkEWSeNz+Z5wHmedUxzPMaYp4nSZL6Fe6gqVEUEVsCFzF5M9r+mfmZFktSwyLi4RRbuG5Qdl0NXJKZ57VXVbMi4l3AWytdj83Mn7RVzygrV0ttD2wC3Jti+93bKFb6XAb8PjP/1sf4awOPp9iSdyXgrxSrfn6cmXf1V/3oiIhFwMMoVlHdG7iDYlvfy4Bfjvq22eVWzw8sm9/MzGe2Wc+EiNgGuHCivdXLP8mK62zSYkXNuv26P3DxUdXdonngCIdHkiRJkkaUed78Z56nKvO8ZpjnDYZ5niRpvvPRXRpJmXlpRHyR4m5wgAMi4qhR/6NWnSsDgHkTAszgCZX33zMUmFm5netZAxz/euCrgxp/VJQhx8/L11iJiCczGQokcGiL5UiSJEmSumSeN/+Z56nKPK8Z5nmSJKkXPrpLo+wdwJ3l+62BZ7dYi9SVcnvqR1a63tFWLdKYeFvl/cnzaTWgJEmSJC0g5nkaW+Z5UtfM8yRJaok3+mhkZeYS4IhK18ER4desxsXjmNw17duZ+bM2i5FGWUQ8keJZ7VBsT3xQi+VIkiRJknpknqcxZ54ndcg8T5KkdnmRpVF3GPDH8v22wN4t1iJ1Y+fK+4Nbq0IacWXg+8FK1+GZeXlb9UiSJEmS+maep3Flnid1wDxPkqT2LZr7EKk9mXlbROwJ7FJ2LddmPVKnMvNA4MC265DGwEbA18vX3cD72y1HkiRJktQP8zyNK/M8qWPmeZIktcwbfTTyMvNs4Oy265AkNS8z/wgc0nYdkiRJkqTmmOdJ0vxlnidJUvt8dJckSZIkSZIkSZIkSZI0BrzRR5IkSZIkSZIkSZIkSRoD3ugjSZIkSZIkSZIkSZIkjQFv9JEkSZIkSZIkSZIkSZLGgDf6SJIkSZIkSZIkSZIkSWNgUdsFSJIkjZPDnr8tm2+1ddtlNObyi1dnj6ParkKSJEmSJEkajA++6KFsef/5k+ddetFaPMM8T5IWNHf0kSRJkiRJkiRJkiRJksaAN/pIkiRJkiRJkiRJkiRJY8AbfSRJkiRJkiRJkiRJkqQx4I0+kiRJkiRJkiRJkiRJ0hjwRh9JkiRJkiRJkiRJkiRpDHijjyRJkiRJkiRJkiRJkjQGvNFHkiRJkiRJkiRJkiRJGgPe6CNJkiRJkiRJkiRJkiSNAW/0kSRJkiRJkiRJkiRJksaAN/pIkiRJkiRJkiRJkiRJY8AbfSRJkiRJkiRJkiRJkqQx4I0+kiRJkiRJkiRJkiRJ0hjwRh9JkiRJkiRJkiRJkiRpDHijj0ZWRBwbEVm+Tmq7HklayCo/jzMizmxw3B0r494aERs1NbYkSZIkabjM8yRpdJjnSZI0f3mjj0ZSRDwa2Lts3gm8ZY7jz+z0D9aIWFz7A3fi9YUe6qyPdWEX50ZE3D8i9oqIj0XETyPi9kH98T1LHU+Z4fOxU8PzLBMRZ08zz5ldjHHIDLVWX/8qLy6uiYgLIuIbEfGBiNgjIjbo898wZf5+xmpSt3VFxJJpPm9XRMTyPcxdH2vt3v4Vmk8iYp/a18XimY7NzJ8CXy2bKwMfGUaNkiRJkqRmmeeZ580whnneNMzzNGrM8yRJGi/e6KORExHLAEcCUXZ9MjOvHMLUe0bEQwY9SUTsHhFnAH8Hfg8cD/wXsANwr0HPX6tlVeDTQ5ruv4AdhzDPIoqLi/WAbYFnAG8ATgL+HBHnRMT+EbHiEGoZJ5sCr2y7iHEz7CBvHnsLcHf5fveIeEKbxUiSJEmSumOeNzzmeaowz+uBeV5jzPMkSWqRN/poFO0JPLh8fyfwgSHNG8DhQ5jnMcBOwKpDmGsu7wM2HvQkEbEp8O5Bz9OBAB4FfAq4IiL2armeUfO2MiyShiozLwW+XOkaxs9iSZIkSVJzzPOGxzxPVeZ5aoV5niRJ7fJGH42UiFgOOKzSdXxmXjXEEnaNiJ2HOF/VbcCSYU0WEY9jcsXH3cDtA5zuKIpVOQC3NDjuVylWrlRfmwEPoQhfdgfeC/yQImSqWg84PiK+2MsWt/PUOhSrpaQ2vKfy/pER8ZzWKpEkSZIkdcw8zzyvS+Z5zTLPU5vM8yRJaok3+mjUvIDi4m7CkS3U8L4hzHEHcC7Fv29f4EHAasChQ5ibcpvbzzK5nfJHgGsHNNfLgCeWzZtp9s7+WzNzSe11ZWZekJlnZeZXM/OgzHwixUqnQyi2WK7aE/hKucW04HURcZ+2i9DCk5kXAj+qdL25rVokSZIkSV0xzxsC87wpzPOmMs9TK8zzJElqj38Ia9S8vvL+3Mw8fwhzXlS+JjwyIp43wPneDayamY/KzNdk5nGZeWFm3jPAOesOA7Ys318JHDyISSJiA+CDla43A1cPYq65ZOZfM/NQ4KHAL2sffgZFaLBQnVp5vwrwjpbqkD5Vef/IcqWiJEmSJGm0mecNh3neVOZ5k8zz1CbzPEmSWuCNPhoZEbEDk8/yBvjCkKa+Gzio1vfuiFg0iMky87rMvGsQY3ciIh4JvLbS9crM/MeApvsksHr5/mym/tHfisy8kmIb4P9X+9CbI2Kr4Vc0Eg5m6lbPL4+ILdoqRgvaqRTbnk94VUt1SJIkSZI6YJ43HOZ55nnTMM/TqDgV8zxJkoZuIBc+Uo/2qby/h+J5zUORmadExDnADmXXlsDLGIEL2SaVz0w/Gli27PpCZn53QHO9EHhm2bwTeEVmZkTMctZwZOZt5fOCLwBWKLuXowiI9m6tsPZcDXyUya1VlwPeRbH19lBExGbAwyieK74mxZbMfwHOycxWVo2NgohYHdgR2ABYl2Kb8LMy81eznLMq8ADgfsDawMrALcANwIXAbzLz7gGX3pPMvD0iTgP2KLt2i4jVM7O+RbckSZIkaTTsU3lvnjcA5nkF87ylmOeNKPM88zxJkobBHX00EiJiWaC6ve55mXnNkMt4U619cESsPOQaBu2tFM8PB/gbU1cCNSYi1gY+Vul6b2bWV9y0KjMvBk6ode8REau1Uc8IOJziwnHC8yPi4YOcMCJWjoi3RMSlwOXAycAnKLbD/l/gK8BVEfHriHhedJgqRcSZEZETry5r2qd6bkTsM9v4tQ89vnZu/XVIp7VGxDYRcSrwV+BbwGeB9wAfBl4yzTgPjIh3RsTPgRuBnwHHl8e/EziibP8KuDEiPlGGMaPoG5X39wKe01YhkiRJkqSZmecNjXleyTxvKeZ5mOeNCPM8SZKGzBt9NCp2pLjrf8IZwy4gM38M/F+laz0GdOHchoh4IFO3NH5tZl4/oOk+TrHyAOD3FBc0o+ijtfYKwK5tFNK2coXFeytdAbxvUPNFxK7AFRRfG3NtK/wQ4MvAd8sVMfNaRLyS4rnzz2Jyhdpsxz8M+C3wNuCRTK7wm8mqFFvoXhgRL+6v2oGo//x/eitVSJIkSZLmYp43YOZ50zLPK5nnjQ7zPPM8SZKGzRt9NCqeUmv/uJUqiq1O76m0DyxXs4y1coXVMRRbuAJ8LzM/P6C5nsHkFrFJscXvnYOYq1+ZeQFwba370W3UMiI+Dvyx0n5iROzS9CQR8XKKEG7d2oeWlP0nAKcBf6p9/EnAT8qtbOeliHg2xSqoe5VdfwW+A5wIfJdi++O6+u/ypAhdTqdYVXUC8G2m/rcFWBH4fETs3kjxDSlXf15W6dql/BkmSZIkSRot5nkDZJ43PfO8pZjntcw8zzxPkqQ2eKOPRsWjau3zuzk5M3fKzChfO/VaRGZeCFQvmFej2B533L2OYmUAwD+AVw5iknJ1RvU56J/OzJ8MYq4G/azWfvBMB2bmIZWvs/YfTl5qqq7M/CdwcK378E632O1ERDwB+CRTV6l8EdgmMzfNzKdn5osy8xmZuTGwM8VzqCc8EPhMU/X06AXApuWr6txK/3SvIzoY+3MUq6/+H8VqtPUz86mZuWdm7gpsRLF9b93twLHAbsBqmbl5Zj4lM59ffj6flpmbUGz1fXLt3GMioh7S9CUzj6t+TWbmki6HOL/yflVgm8aKkyRJkiQ1xTxvsMzzZmaeNzmOeV5nzPPmYJ4nSdJ4WdR2AVKp+uzgmzLzz61VAu+g+MN/YovNV0fER3v4w3YkRMSWwKGVroMz84oBTfchYIPy/dUUK6pG3UXAMyvtjdsqZEQcD7ye4gIc4GEU3w8n9jtwRKxCsRplIhRI4GWZecxM52TmmRGxA8Xqlx3K7hdExCcz80f91tSLzPz3KpxaZnJHAz8nVgV+AexSbr9cn/tull7JcwmwYWbeONfgZfj5/PL54hMh0KrAq4FDei+7cb8BqiuTtiv7+laGIOt0edrmTcwtSZIkSfOMed6AmOfNyTxvKvO8OZjnDYV5niRJQ+SOPmpdRKwHVJ/T+4e2agHIzD8CR1a6lgfe2VI5fSlXbnyWYktPgF8DHxnQXE8EXlrpes10FzYjqH4x1e0Fw7ySmfcw9dnvAO+KiOWmO75LrwTuU2l/YLZQoFLTrcAewD8r3W9ooJ5R9E9gz26+dzLz5k5CgZrDmHqh/aIuzx+0+u+B+zU49qspVpV18/p6g/NLkiRJ0tgzzxsc87yOmOdVmOe1zjyvYJ4nSdIQeaOPRsHiWrvN1T8T3g1U/zDfMyK2bauYPrwKeFz5/m6K1RZ3Nz1JRKwMHFXpOjUzT2l6ngGpX1CtOO1RC0hmfhP4caVrM2D/Bob+r8r7W+kicMvMPwFfrnQ9OSJWmOn4MfaVzLxs7sP6UwZA1e/RLSJilEKx+u+BxW0UIUmSJEma0eJa2zyvOeZ5czPPqzHPa5V5XsE8T5KkIfJGH42C+rNku72TvXGZeQPwvkrXMsDhLZXTk4jYmKk1H5GZvxrQdO9h8vnGNwOvGdA8g1D/OZitVDF63lRrv73cqrcnEbEVU7dR/la5sqcbZ1Ter0Cx/et8c2qTg0XEChGxdkRsEhGLqy+K54BXbd3k3H2q/x5o9JnjkiRJkqS+mecNgHlex8zzpmee145TmxzMPE+SJHViUdsFSMBKtXb9j9W2fJTiAnfiGdVPjYidMvPM9krqyqcpntULsITiWeWNi4gdmRoEvDkzrxrEXAOyRq09Kl9/rcrMcyLi68Czyq51KbbXPaTHIR9Ta/+xvDjtxj219uZMXak0H/y6n5Mj4oEU2yI/FtgGWLuL09fsZ+6G/aPWXrnBsT8BnNzlOZvjdr+SJEmSVGWeNxjmeZ1Zo9Yela+/VpnntcY8r2CeJ0nSEHmjj0ZB/evwrlaqqMnMf0TEoRQX2BMOBx7VUkkdi4i9gadUul6ZmfU/tJuYZwXgaCZX0fwU+FTT8wxY/WLoulaqGE1vAZ4OLFu2Xx8Rn8jMa3sY67619hvo/7nca/V5/ijq5XNLRGwCHAHs1sfcq/dxbtPqvweaeKY8AOXXb1ef54hoanpJkiRJmi/M8xpmntcV87yZmecNn3lewTxPkqQh8tFdGgX1FRej9Ezlo4GLK+3tI+K5bRXTiYi4D/DhStcXMvP0AU13MHD/8v2dwMszc9y2yn1Arf2HVqoYQZn5e+C4StcqwNt7HO7efRe0tFXnPmS8ZOYt3Z4TEVsD59BfKACj9TdB/ffAba1UIUmSJEmaiXleg8zzumaeNwPzvOEzz/s38zxJkobIHX00Cm6utZvc0rEvmXl3RBwEfLXS/Z6I+HpmjsRKpWkcwOTKiNuAj3a4pWr958F6tfNuLp91DkBErAwcWPn4ccA/OpirvvXovaY554+ZWd/WdVC2r7UvGNK84+JgYE8mL9T2j4gjMvPyLsdZvtmyAFjwyzIiYhFwErB+pfsOiq1sfwBcCFwF3ALckZl3V87dBzh2aMV2p/57oP57QpIkSZLULvO8Zh2AeV43zPNmZ543wszzJElSE7zRR6PgT7X2+tMe1ZLM/FpEnMvkBeT9gJcydQvgUVK9c35l4Bc9jnNirf1RitBhwnJM/RnyivLVre2BK2t9awI39TBWVyLioSwdVPxk0POOk8y8KiI+Dryx7FoOeBfwwi6Hur7W3jMz619jo2DZuQ8ZKc8Btq20LwN2zcwrOjh3tcGU1IgNau367wlJkiRJUrvM85plntch87y5meeNPPM8SZLUt1Ha1k8L1xKguj3sRi3VMZs31doHR8RKrVSiJv1PrX0H8N02Chlx7wVurLT3iIiHdTnGX2vt+/VX0qymrM4rV8l0qv6M91H3rFr7FR2GArD0xfco2bDWroeHkiRJkqR2LcE8T+0wz+uMed7oMs+TJEl980YftS4z72Dqc7M3HrWL7sw8C/hWpWt9pq6G0ZiJiPuz9CqWEzPz1jbqGWWZeRNFODAhgMO7HOantfaT+6lpDvVtYdfo4txtGqxjGLasvL8NOLOLc3dstpRGbV1rn99GEZIkSZKk6ZnnqQ3meZ0zzxtp5nmSJKlv3uijUVHdjnYZ4IFtFTKLtwDV50y/Ebh3S7XMKDMPyMzo9gX8oTbUzrVjDqjNc1OP8+xbm+esaY67aXCfoX8/j/yrTH3O9J1MvfjVVB8H/lxp7xIRT+ri/F8xdbvfHSJiUN/n19baD+jkpIhYDtily7n+WXm/QpfnNmGNyvubMzNnOrAqIrYAHj2Qipqxba3981aqkCRJkiTNxjyvIeZ5czPP64l53vTM8wbDPE+SpCHyRh+NirNq7e1aqWIWmfkb4IuVrtWBt7ZUjnoUEZtSrJKoXyy+JzMvHX5F46FcqXdwrftwitVAnZx/D/CJSlcAH+tyG95O/arWfkaH5+3H0lvMzuWmyvv1uzy3CdUtmNeNiE63Kn4/I/o3QBnQPLTSdWFm/q2teiRJkiRJMzLP01CY5/XGPG9GN1Xem+c1wDxPkqThG8k/CrQgfavW3rmVKub2dqbe8f/stgpRdyLiPhHxdoqLxkfUPvx14J0DmHNxRGTttbjpeYboc8DvKu2HAxt3cf6HmLoKaGfg2Ii4VzdFRMTGEfHUWQ75Ya29f0Tcd44xHwV8uJs6Sr+vvN8kIrbqYYx+XFB5vyxw4FwnRMShjPbPrkcCK1fa/9dWIZIkSZKkWZnnaaDM8xphnrc087zmmedJkjRk3uijkZCZ1wDnVrp2HtDKgL5k5h+YuoqhJ+UF41IvYO3aofea6diIWKPfOuaBVab5vGwaEdtGxGMj4jkR8e6I+D7wR+Awln6+8+eB55crVDSLzLwbOKiP828G9gDuqnS/GPhVRLxotoAgItaPiH0j4hvAFeU4M81zGXBGpWtV4AcR8chpxl0lIt5YHr8SU1fUdOKMWvvrEbFPRDyk/Foc9Pfsl2rtt0TEuyJilfqBEbFVRHwNeEfZdd0A6mlCfQvpU9soQpIkSZI0O/M887wemecNkXnetMzzmmeeJ0nSkI3chZcWtOOB7cv3a1KsDvhee+XM6N3AS4HV+hjjyg6P236WYw8FDumjhvngueWrF9cAB2bmF+c8Uv+Wmd+IiLPp8XnQmfnDiNgHOJrJZ2BvDXwBOCYizgeuBm4FVgHWAu4PrNvlVK8FfgEsV7a3BH4eERcCFwF3U2zr+8hKHb8HPg0c0cU8nwXeQBE+AGwFHDvDsY1/z2bmDyLi20B1RdRbgf+JiJ9TfJ2vAtyP4vM84ffAp4CPNllPQ3avvL84M3/WWiWSJEmSpLmY5y3NPG925nlDZp63FPO85pnnSZI0ZO7oo1FyEnB7pf28tgqZTfls2fe3XYd6khQrzfYHNh9CKFBf0XIXxQXvuHtTPyeXn/fHAJfVPrQ8sB2wG8XKoN2AxzF9KDDrSp3MvADYB/hX7UMPpLjw3KOsYSIU+BXFypO/d/SPmJzn6nKsm7o5r2F7Ar+s9a0CPAF4EfAspoYC5wO7ADcPo7hulFslP6jSNVPIIkmSJEkaDeZ5GjTzvGaY503OY57XIPM8SZLa4Y0+GhmZeQPFM4Mn7DHddpUj4iMUd9Zr9NxNETD9FfgtcBrFs6RfCGyYmY/KzM9k5u2zjNGUHWvtz2fm9dMeOUYy82zgG32O8UuKlT0vBs5h6va/07kH+DVFKPewzHxtB3OcQHHxf9Ysh/2RYsXMjuVFftcy89sUK39eD3wLWEIRAA1l++jMvIni33kYcMMsh15MEeo8KjOvGkJpvXh55f1twFFtFSJJkiRJmpt5nhpinjdg5nlLzWOe1xzzPEmSWhCZ2XYN0r9FxJYU23BO3IS2f2Z+psWSpJ5FxBcoVmBAsRJlq8zsdJvnBSUiVgUeBWxEsb3vvSgurv8GXAr8vnwmeK/jbwg8FlifYqXRNRQrkM7JefSLMCJWoNgifBuKLdNvBf5C8fn7bZu1zaWs/Srg3mXXxzPzv1ss6d8iYhvgwon2l753NptvtfUsZ4yXyy/+PXvsMmX37gdm5u/aqkeSJEnSeDHP03xintc587xmmOcNRj3P++aZP2PL+8+fPO/Si37PM3Z6VLXLPE+SFphFbRcgVWXmpRHxRWCvsuuAiDhqPv3hrgVl58r74wwFZpaZtwDfG+D4V1FsJz6vZeY/gR+Vr3GzN5OhwO3A+1qsRZIkSZLUIfM8zTPmeR0yz2uGeZ4kSeqFj+7SKHoHcGf5fmvg2S3WIvUkIu4PbFA27wTe1WI50kiLiEVMfVb8x0d4O2JJkiRJ0tLM8zT2zPOkzpnnSZLULm/00cjJzCXAEZWugyPCr1WNmydU3h+dmX9srRJp9O0NbFa+vw54b4u1SJIkSZK6ZJ6necI8T+qceZ4kSS3yYkuj6jBg4kJqW4o/GqVxMrHN7z+B97RZiDTKImJlip/5Ew7MzJtaKkeSJEmS1DvzPI078zypA+Z5kiS1b1HbBUjTyczbImJPYJeya7k265G6lZnPa7sGaUxsDhxVvr81Mz/XZjGSJEmSpN6Y52ncmedJHTPPkySpZd7oo5GVmWcDZ7ddhyRpcDLzN8Bv2q5DkiRJktQ/8zxJmv/M8yRJap+P7pIkSZIkSZIkSZIkSZLGgDf6SJIkSZIkSZIkSZIkSWPAG30kSZIkSZIkSZIkSZKkMeCNPpIkSZIkSZIkSZIkSdIYWNR2AZIkSePk42ddwaqXtl1Fc265+oq2S5AkSZIkSZIG5hNnX8nqS+bP3gd/v+rKtkuQJLVs/vxWkyRJkiRJkiRJkiRJkuYxb/SRJEmSJEmSJEmSJEmSxoA3+kiSJEmSJEmSJEmSJEljwBt9JEmSJEmSJEmSJEmSpDHgjT6SJEmSJEmSJEmSJEnSGPBGH0mSJEmSJEmSJEmSJGkMeKOPJEmSJEmSJEmSJEmSNAa80UeSJEmSJEmSJEmSJEkaA97oI0mSJEmSJEmSJEmSJI0Bb/SRJEmSJEmSJEmSJEmSxoA3+kiSJEmSJEmSJEmSJEljwBt9JEmSJEmSJEmSJEmSpDHgjT6SJEmSJEmSJEmSJEnSGPBGH0mSJEmSJEmSJEmSJGkMeKOPFqSIODYisnyd1HY9mltELBcRj4mIfSLiwIh4fUS8MCK2i4houz5pviu/97Ly2qfBsT9TGffUpsaVJEmSJM0f5nnjxzxPapd5niRJ85c3+mjBiYhHA3uXzTuBt8xx/JmVP1jPnObj36v9sXxEg7V+qDb2t+Y4fp2IeGpEvCMivhkR19TOz4hY3FR9M9SwUkRcPs28x/U43iYRcRTwN+DHwLHA+4EPAicA5wJ/iojDI2LVLsdeXK+zg3OW9PtvGoRu6oqInab575MR8a4e5q2PdVrP/wjNK3P97Kx5B3Br+f5ZEfEfg61OkiRJkjROzPPM8ypjm+eZ52lAzPMkSRof3uijBSUilgGOBCZWjHwyM6/sc9ija+0XRcTyfY5JRCwHvHiOuYiIDSLi5IhYAlwLfAs4FHg6sF6/dfTg3cBmTQwUES8DLgFeBsx20b8h8CbgtxHxuCbmXqBeGxHrt13EOIkBropZSDLzL8BHKl0fLX8GSpIkSZIWOPO8oTDPG1/meV0yz2uGeZ4kSe3yRh8tNHsCDy7f3wl8oIExTwFuqLTXBp7RwLhPB9attK8DvjHNcesCuwObNDBnXyLiUcB/NzTW24GjgHrIcgHw1fJ1Qe1jmwDfjojtmqhhAVoJOLjtIrRgHcHkKqDNgVe0V4okSZIkaYSY5w2Qed7YM89Tm47APE+SpFZ4o48WjPJu8sMqXcdn5lX9jpuZ/wS+WOver99xgX1r7c9n5r+6OP8e4KIG6uhIuerpaCZ/rtzSx1jPpFjFVPV9YKvMfEhm7l6+HgLcH/hh5biVgNMioo3VT/PBSyPifm0XoYUnM28APl3peltErNRWPZIkSZKk9pnnDZZ53rxhnqdWmOdJktQeb/TRQvICYNNK+8gGx65vwbtrP1umlhe1T611HzPHaZcDXwLeAOwErJ6ZW/daQw/eATygfP8Hpv6B37EywPk4k9sxQ7HK6qmZeUn9+My8GNiVqauj1gEO6WV+sYhiu2apDZ8Asny/HrBPe6VIkiRJkkaAed5gmefND+Z5apN5niRJLfBGHy0kr6+8Pzczz29q4My8ADiv0rUssHcfQ76E4gJtwrmZ+bsZjr0IWCszt8jMF2TmhzLzrMy8dYbjGxcRD6Z4pvaEVwG39Tjci4CNK+3rgJdm5l0znVB+bF/gb5Xul7mSpWM/Zurnbne3S1YbMvMK4HuVrtdGhH+rSJIkSdLCZZ43IOZ5Y888TyPBPE+SpHb4y1YLQkTswOSzvAG+MIBp6quA6lv1dmOfOcb+t8y8IzNv7GOuvkTEIorVSRNBxomZ+e0+hqw/D/3oTv595Tah1VVSywJ79VHHQnIzS6/6ObyNQiSmbp2+BbBLW4VIkiRJktpjnjc45nnzgnmeRol5niRJQ7Zo7kOkeWGfyvt7gK8OYI4TgA8BK5bt+0XEozPz7G4GKUOM6ha9twEnNVPiQBwIPKx8fwNwQJ/jPa7WPr2Lc79T1jNhd+DtfdazUHwC+B9gk7K9c0Q8JTO/M4zJy4BpO2Aziq2aV6BY/bUEODsz7xhGHaMoIrYCHgisD6wOXA+clJl/n+Wc+1L8HNkMWI0iKLsRuJZiReFVg667D18H7gSWL9v70N3PAUmSJEnS/LBP5b15XrPM8+YH87wRZZ5nnidJ0qB5o4/mvYhYFnhepeu8zLym6Xky8+8R8VXgxZXufYGuggFgv1r75My8pa/iBqS8YDm40vX6zLy2j/FWANaudV/YxRC/rbXvHxGblduHahaZ+c+IeDtwfKX78Ig4PTNzpvP6FRFbA28Dnk5xATud2yPiG8A7pnuu+zRjLgaurHR9LjP36aKmM4HHT7QzM2ofr49fdWxEHDvL8Jtm5pJOao2IlwL/DWw7zTjnAudXxlme4tn2zwWeANx3lhqIiEuAjwLHjFroUv4sPYvJlT+7RcRKmfmPNuuSJEmSJA2Ped7gmOfNH+Z5U84/E/O81pjnSZI0fD66SwvBjsCalfYZA5yrviXv8yNi5U5PjoiVgOfPMeZIKJ+zezTFSg2AH2bmcX0Ou9Y0fTd1cf50xz6op0oWpi8Cv6m0H0zxjPXGRcSyEfERiuBnT2YOBaBYVbcH8LuI+J9B1DNKImLViPgm8FmmDwWm80HgG8DezBEKlO4HHAn8LCI266nQwar+nL4X8MS2CpEkSZIktcI8bwDM8+Yl87wRYJ4HmOdJkjRU3uijheAptfaPBzjXWcDllfaqFNvNdmp3pl4gXZKZP2misAF4DfDo8v3twP4NjHnnNH0rTNM3k+mOfUCPtSw4mXkP8JZa9zvL1SWNiYgVgW9RbAtd/T30L+AXwCkU21ufCVRXfSwCjoiIQ5qsZ8QE8DmKFVEACVwAnAp8Gfgpxeeprv77/B/AecBpFNuQfwX4CVBfTfhg4IyImC6Ua9OPau36z3FJkiRJ0vxmnjcY5nnzjHneSDDPK5jnSZI0RD66SwvBo2rt87s5OTN36uLYjIhjgHdXuvej+EO/E/Vtfo/pdO5hKrcnfU+l69DMvKyBoW+keOZ69SJnfaDTsdefpm+rfouqyszFTY7XlKbqysxvldusTmx1uxh4FcW2sE05Enhypf134BDg6Pq21mWI8GrgXRQrQQDeERHnZua3G6ypG38GNi3f7w58oPKxAykuwmc7dzbPpggUofi58fbM/FP1gIhYG/jnNOdeTrFV8/8Bvy6DnikiYjlgN+Bwiud9A2xM8Uz3F8xRW1e6+dk5jQsoQpGJbZZ36LugUkSsS/Hc+G5s3tT8kiRJkqSOmOc1zDxv9JjnDZV5XgfM8yRJGh/e6KOF4OGV9zdl5lx/mPfrOOAwYNmy/diI2DwzL5/5FCi323xcpesupj5feZQcBUxsYXwB8KEmBs3Me8pnDd+/0v0oOg8Gprt4WL3vwhaeNwE/q7TfFhHHNPFs+Yh4HsWz7if8Adip+pzrqsy8HfhQRJwD/IAiHAjgYxGx1XQXv4OWmXcBSwAi4vrah6+f6d/SoYlQ4KDMfO8M89fnBHg/8N9zfT4y81/AyRHxfeCHwEPKDz0vIg7KzCt6K7tZmXlrRFzJZHjxoIi4V0PPH381cHAD40iSJEmSBsc8r3nmefObed4szPMGzzxPkqTh8tFdmtciYj2mXhj+YdBzZubVwHeqZTD1Qmgm+zJ5tzvAtzLzmiZra0JEvBR4Utm8B3h5eaHUlLNq7b26OPcl0/StOk2fZpGZ5wJfq3StDbyx33EjIoB3VLruAp7ZyYV0Zv60du4WFCtZ5qMfzBQKzCQz/9hNSJKZNwIvq3QtA7ywmzmHoPrzehGTIYEkSZIkaR4zz2ueed78Z57XOvO8gnmeJElD4o0+mu8W19qDXv0zob5F794RMeP3W/mxvWvdRzdeVZ8iYgPgg5Wuj2XmLxqe5vO19pMj4mlznRQRzwCeOM2HDAZ6cxDFhfuE15ZBWz92Bh5YaX8xM3/TxflHAtUVIM/ss55RdfgwJsnM85h68b3jMObtQv3n9eI2ipAkSZIkDd3iWts8rw/meQuKeV57zPMK5nmSJA2Jj+7SfLdurX3jkOb9JnBtZf6NgF2A02c4/knAfSvtvwLfGlh1vfsEsEb5/g/A25qeIDPPrj1TGuCEiHhmZv5ounMiYifgCzMMOfStYOeDzLy4fD79K8qulSlW4Ly6j2F3qbW/1GVN/4iInzO5JfZj+6hlVN1CsQVvI8pVVytTBGQrTHPIdcAm5futm5q3IfWf1/Wf5736BHByl+dsDny9ofklSZIkSbMzz2uWed4CYZ7XGvO8SeZ5kiQNiTf6aL5bqda+fRiTZua/IuLzwOsr3fsyczCwX639uYa3z+1bRLwAeFal61WZeduAptsP+CWwZtleHTgjIk6k+IP+UoptkbcAnk+xRenENsl/pghiJtw0oBoXgkOBFzP5ffTyiPhIZl7a43iPqbVviIjFXY5xc+X94ohYpo3neg/QBf38eyJieeDJwHOAhwH3Z/pAYDprzn3IUP2j1l65iUEz81qK4LZjRb4iSZIkSRoS87yGmOctSOZ5w2eeN8k8T5KkIfFGH8139a/xYV5sH83UYGC3iFizfJbuv0XEmiz9bOL6VsGtioi1gY9Vuk7MzG8Par7MvCIidgNOAdYqu5cBXlS+ZnIucDzFlrATbhpAiQtCZl4dER8F3lJ2LQLeTRHG9OK+tfbPeq2ttAzFirQb+hxnlHR1wVoVEc8CPgJs2uMQq/c694DUf14v10oVkiRJkqRhM89rgHnewmSe1wrzvEnmeZIkDcmMzxiW5on6ip8VhzVxZv4eOKfStQKw5zSH7snUO/R/kpkXD7K2HnwMWKd8fwNwwKAnLLf13R74fieHU2zf+USWXsXwl4ZLW2jeB/yt0t49Ih7R41j3bqCeuvn2zPZbejkpIg4ATqX3UAAmV9GNivrP60GtOJQkSZIkjRbzvGaY5y1c5nnDZZ43yTxPkqQhcUcfzXc319qNbBXZhaOBHSrt/Zi6OmWir37OyIiIrSi20p1wBLBSB1u0rlFrr1I7557M/ONsA2TmZcAuEbEDxdalO1GsIlmT4r/tn4DvAZ/PzAvLeuvPJf7lHHVqFpn594h4D/ChsisowoIn9jDc8o0VNmnULmaHLiK2Z/K/z4QlwAnAT4ErKAKy24F/ZmZWzj0TePxQCu1e/ed1/ee5JEmSJGl+Ms/rk3newmaeN/rM8yRJUr+80Ufz3Z9q7fWHPP+XKC6kVynbD4uIbTPzNwARsS3Fc3cn3ELxzOpRUr8L/7Dy1a3nlq8Jf2fp8GBamXkOU1dTzWaHWvvcDs/TzI4E/gfYuGw/ISJ2zcyZnlE/k+uBDcr3dwArVS9SR8iybRfQpYOZukPfZ4D/zMxOtjZfbTAlNWKDWrv+81ySJEmSND+Z5/XPPE/meaPNPE+SJPXFR3dpvltCsQ3shI2GOXlm3gp8udZdXfHz0trHvpSZbmfZo4jYFNis0vXnchWR+pCZ/wTeUes+PCK6XX3z18r7ezEZNDStfkHc7U2t9e2iR1ZErMzU1VhX0HkoAMMPS7uxYa19ZStVSJIkSZKGbQnmeQuGed5gmOeNLvM8SZLUBG/00byWmXcA1edjbxwRKw25jPrWvS+KiOUjYnmWfsb3SG3zO4ZGetvkMfd54LeV9kOYugV0J35aaz+5n4JmUd8Sdo1OT4yIFYDNu5ir7RVMmzB1C+XvdBoKRMRmwHoDqapPZei0VaXr2sy8pq16JEmSJEnDY5634JjnDY553vTM8wbAPE+SpOHyRh8tBL+ovF8GeOAwJ8/MnwIXVbrWBp4BPLN8P+H/ZebPhllbJzLz/MyMbl/AobWhPlc7Zo0m64yINYFXVLruxmCgMZl5D3BQrfuddPec7vrWwC/rq6iZ3ULx/OoJD+ji3CdSrE7q1D9r7RW6OLcJa9Taf+/i3H2aK6NxmzG5RTrAz9sqRJIkSZLUCvO8PpjnCczzZmGeNxjmeZIkDZE3+mghOKvW3q6FGuoXqPvhapWmfQhYt9L+ZGb6DOAGZeZpwI8qXZsBr+xiiG8Dl1fa20VE/fugb+Vzws+vdG0aEdvMdV5ELAO8tcvpbqq1h7117o219v07OSkiNgH+u/lyGlP/OX1mG0VIkiRJklpjnrcwmOcNmHnetG6qtc3zmmGeJ0nSEHmjjxaCb9XaO7dQw/HAvyrtXZm6zem/KLZSFRARy3ZxbETEB4B9K91/AN7SeGE9iIhDIiIrrzPbrqlPb6q1n93pieUWtPVng38yIp7TbRER8aRyq9qZ/KDWflcHw74f2LHLUn5faw9q++KZXA7cWmk/PSJmXeUYEWsDXwNWH2Rhfar/nP6/VqqQJEmSJLXFPG/MmOeNNPO8qczzBsM8T5KkIfJGH8175XNgz6107RwRi4Zcw7XAaZWuZcvXhG9m5nW9jh8Ra0fE4ule0xy+0QzHbtTr/AOwdURcFBEHRsT9pjsgIhZFxJOAc4A3VD70T2CvzLx1uvPUn3I76lP6OP8E4JhK1/LAVyPiixHx8JnOi4hlI+KhEXFwRPw/4HvAxrNMdQxwT6W9W0QcU24JXR9764j4OvD6suumDv85ZOYfgCsqXTuU/5anRMRW03yfNfqzJzPvBE6tdC0HnB4RT6kfW34On0ux/fnDKJ5H/rcm62nQkyrvL87Mi2Y8UpIkSZI075jnLcU8Tz0zz5vKPG9gzPMkSRqioV4cSS06Hti+fL8mxd3l3xtyDUcz82qJfrf5/SCwd4fH/niG/j8Ai/uso0lbUazIeH9EXAtcCFxffuw+wLYU/y2rbgf2yMyZ/o1qxkEUz6TveKVWzSsp/ttVvx/2BPaMiOuACyguWO8BVgM2ALami2dtZ+aVEfEh4MBK977ACyPiHOAaYGWKr7Pq9rjvAR4NPL6Lf89HgI/X/y0zHLspsKSLsTtxCLAbk8/A3gD4dkT8Afg18A9gbeCRTP2eeQ/wGLr7tw5cRDyM4vM04XNt1SJJkiRJapV53iTzPPXLPG8q87wGmedJkjR83uijheIkiovnFcv28xh+MPAd4GqKP9qrrgJOH3It42Zd4AlzHPP/gBdn5q+HUE836hez9Wcwj53MvCgijgVe1uP5/ypXohwIHMrUz9E6TF39MZN/AbfNcczbgC2YGkDci5m3+35fZr61h+2YjwS2obvnmzcmMy+PiN2BrzAZDgBsUr6m84HMfNuIbj39/Mr7uyiCXUmSJEnSwmOeN97M80aIed5SzPOaZZ4nSdKQ+eguLQiZeQNT7yLfIyJWmen4AdVwN3DcNB/6XPkxTboa+BSdrZT4FfBy4MEjGArA0s+I/kgrVTTvYIoVVz3JwvspVnocTrECbS63AN8C/hNYPzN/McccdwK7A/8F/GWmw4CzgF0y880dll+fJzPzVRSrDD9Ksf30tcAdvYzXYw2nA48Avk7xb5rOXRQh5BMz843Dqq0b5VbIL6l0nZyZV7VVjyRJkiSpPeZ5Y8c8b/SZ503OY57XEPM8SZLaEZkz/f0gzS8RsSVwEZM3uO2fmZ9psSR1ICI2oNjWdzGwBsVOZLcCVwK/yMyrWytuDhGxEsWKn+XLrh9kZierWxakiNiU4lnT61BsSXsPRRhwNcX37qW9hmgRsQzFhfO2FNve3k6x+u4X5XO5542IuA/FFr4bU6x6vI5ia+OfZeb1s53btnJl2FcqXY/IzPPaqmdCRGxDsd04AI952+dZdYPNWqyoWbdcfQU/edde1a4HZubv2qpHkiRJkiaY540n87yFwzyvGeZ5zavneU9994msvuHmLVbUrL9fdTnffusLq13meZK0wPjoLi0YmXlpRHwRmPi/mQdExFHp3W4jrbzwH9mL/zk8hslQAOAdbRUyDjLzSorAZxBj3wP8vHzNa5n5V+CrbdfRo9dX3n9zFEIBSZIkSVJ7zPPGk3newmGe1wzzPEmS1C0f3aWF5h3AneX7rZn6rF+padXnkJ+emT9trRJpxEXEE4AdyuY9wEEtliNJkiRJGh3meRom8zypQ+Z5kiS1xxt9tKBk5hLgiErXweUWoNIgVIMBV/9Iszuk8v7ozLxwpgMlSZIkSQuHeZ6GzDxP6twhlffmeZIkDZEXRFqIDgP+WL7fFti7xVo0T0XEahTPpwb4v8yc91vMSr2KiGcDjy2bfwPe0mI5kiRJkqTRY56ngTPPkzpnnidJUrsWtV2ANGyZeVtE7AnsUnYt12Y9mp8y82b8GSt1alXg0PL92Zn5tzaLkSRJkiSNFvM8DYN5ntQV8zxJklrkH61akDLzbODstuuQJEFmHt92DZIkSZKk0WaeJ0mjwzxPkqR2+eguSZIkSZIkSZIkSZIkaQx4o48kSZIkSZIkSZIkSZI0BrzRR5IkSZIkSZIkSZIkSRoD3ugjSZIkSZIkSZIkSZIkjYFFbRcgSZI0TrZYbxXW3mi1tstozPX3rMJP2i5CkiRJkiRJGpBN11mFdTeYP3netXeu0nYJkqSWuaOPJEmSJEmSJEmSJEmSNAa80UeSJEmSJEmSJEmSJEkaA97oI0mSJEmSJEmSJEmSJI0Bb/SRJEmSJEmSJEmSJEmSxoA3+kiSJEmSJEmSJEmSJEljwBt9JEmSJEmSJEmSJEmSpDHgjT6SJEmSJEmSJEmSJEnSGPBGH0mSJEmSJEmSJEmSJGkMeKOPJEmSJEmSJEmSJEmSNAa80UeSJEmSJEmSJEmSJEkaA97oI0mSJEmSJEmSJEmSJI0Bb/SRJEmSJEmSJEmSJEmSxoA3+kiSJEmSJEmSJEmSJEljwBt9NJIi4tiIyPJ1Utv1aG4RsVxEPCYi9omIAyPi9RHxwojYLiKi7fok9Scizqz8XM4Gx10tIq6tjL1bU2NLkiRJkobHPG/8mOdJ85t5niRJ85c3+mjkRMSjgb3L5p3AW+Y4vvrH6pnTfPx71T9mI+KIBmv9UG3sb81x/DoR8dSIeEdEfDMirqmdnxGxuKn6ZqhhpYi4fJp5j+txvE0i4ijgb8CPgWOB9wMfBE4AzgX+FBGHR8SqXY69eJo6J17376XectzjZxjzuDnO26l2/E691tCkbuuKiOOm+bff1cvndJqxdu/136H5Y5rv3X1mOjYzbwYOq3QdERErDbxISZIkSVJjzPPM8ypjm+d1wDxPo8Y8T5Kk8eKNPhopEbEMcCQwsWLkk5l5ZZ/DHl1rvygilu9zTCJiOeDFc8xFRGwQESdHxBLgWuBbwKHA04H1+q2jB+8GNmtioIh4GXAJ8DJgtov+DYE3Ab+NiMc1MTewby8nRcRqwHMbqmE+WRZ4T9tFjJsY0KqYBehTwBXl+02AN7dYiyRJkiSpC+Z5Q2GeZ543HfO8HpjnNcY8T5KkFnmjj0bNnsCDy/d3Ah9oYMxTgBsq7bWBZzQw7tOBdSvt64BvTHPcusDuFH/stioiHgX8d0NjvR04CqiHLBcAXy1fF9Q+tgnw7YjYroES9oqIZXs47wWAqwum9+zya0Qaqsy8C3hfpet1EbHuTMdLkiRJkkaKed4AmecB5nmzMc9TK8zzJElqlzf6aGSUK2qq2z0en5lX9TtuZv4T+GKte79+x2XpFSifz8x/dXH+PcBFDdTRkXLV09FMft/f0sdYz6RYxVT1fWCrzHxIZu5evh4C3B/4YeW4lYDTIqKX1U/Vz+/6wFN7GKP6376b/14LxfvmPkQaiOOAq8v3KwNva68USZIkSVInzPMGyzzv38zzZmeep7Ych3meJEmt8EYfjZIXAJtW2kc2OHZ9C95dI2L9XgcrL2rrF6XHzHHa5cCXgDcAOwGrZ+bWvdbQg3cADyjf/wH4dC+DlAHOx5ncjhmKVVZPzcxL6sdn5sXArkxdHbUOcEgP019SviZ0td1vRGwNbF/p+mYPNcx3j4uI/2i7CC08mXkn8NlK18siYu226pEkSZIkdcQ8b7DM88zzOmGep1aY50mS1B5v9NEoeX3l/bmZeX5TA2fmBcB5la5lgb37GPIlwKJK+9zM/N0Mx14ErJWZW2TmCzLzQ5l5Vmbe2sf8XYmIB1M8U3vCq4DbehzuRcDGlfZ1wEvLrTqnVX5sX+Bvle6XRcT9epj/2Mr7Z0TEOl2c+9LK+5soAg3BqbX2eyPC3w9qw1HA3eX7FYFXt1iLJEmSJGlu5nkDYp73b+Z50zu11jbPU1vM8yRJaoF/+GkkRMQOTD7LG+ALA5imvgqoq9UjNfvMMfa/ZeYdmXljH3P1JSIWUaxOmggyTszMb/cxZP156Ed38u/LzBuYukpqWWCvHub/HJMXDstRBBVzKj8PL650nQjc0cP889EJwPmV9oPo7b+N1JfM/DPwo0rXKwypJEmSJGk0mecNjnlewTxvVuZ5GgnmeZIktWPR3IdIQ7FP5f09wFcHMMcJwIco7ioHuF9EPDozz+5mkDLEqG7RextwUjMlDsSBwMPK9zcAB/Q53uNq7dO7OPc7ZT0Tdgfe3s3kmXlNRJwOPK3s2hc4ooNTnw7cp9I+BljczdzzWAJvpvjvM+GwiDgpM/85jAIiYi1gR2A9YG2K0OY64PxZVtfNe+XW2jtSrLpbj+IG3d9l5mlznLM1sBWwPrAqxefzRuAK4OeZ+Y8Bl96PLwM7l+83BHahu58zkiRJkqTh2Kfy3jyvWeZ5BfO8mZnnjSjzPPM8SZKGwbtq1bqIWBZ4XqXrvMy8pul5MvPvLB049LIKaL9a++TMvKW3qgYrIrYCDq50vT4zr+1jvBUoLtqqLuxiiN/W2vePiM16KKW6kmjbiHh4B+dUt/m9MDN/2cO881Zmng78sNK1MfCfg5wzCi+IiJ9RhADfpNjq9b3ARyhWAl4YEX+OiDdFxIqzDFcd95CIyMprpy5qWlw797jZxgceX/tYzvI6s9NaI2KtiDgS+AtwJnA88H7gcOBd04yzfkT8V0R8lyIAuIDiAvuj5fEfpFipeAbw94j4ZkQ8ttPPy5B9o9bes5UqJEmSJEkzMs8bHPO8KczzZmGe9+9zzfPaZ54nSdKQeaOPRsGOwJqV9hkDnKu+Je/zI2LlTk+OiJWA588x5kgot8c8Glih7PphZh7X57BrTdN3UxfnT3fsg3qo4xvA9ZX2rAFPRKwHPKXSdcxMxy5wb6JYDTThoIhYfRATlYHQeRRbLm/P7L+PNqS4IP5/EbHNIOoZJRHxaOA3FM+znu57bjoXAx+jWC0z18+0RRQr4n4UER8ut8EeGZl5NXBJpetpbvcrSZIkSSPHPG8AzPMmmed1zDxvBJjnmedJkjRs/qLVKHhKrf3jAc51FnB5pb0qxXazndodWK3SviQzf9JEYQPwGuDR5fvbgf0bGPPOafpWmKZvJtMd+4Bui8jMfzH1ue97lquTZrI3k48qrJ+rUrkq6iuVrnsDb2x6nojYDjgXeGjtQ38Dvk+xdfYpLL26bDFwdkQ8pOmaRshmFMHXhmX7NooVQCcBp1EEANOp/z7/a3ne1yi+3r8O/A64u3bca+lsq+xhqz7Xe22gk1V+kiRJkqThMc8bDPO8SeZ5HTDPGwnmeQXzPEmShmik7vrVgvWoWvv8bk7OzJ26ODYj4hjg3ZXu/YDPdThEfZvfkVxJEhGLgfdUug7NzMsaGPpGimeuVy9C1gc6HXv9afq26rGWY5h8PvmawG7Al2Y4trpC6LTMvK6XCTPzTCB6OXeQGq7rrcCzmfz9cEBE/G9T22+Xq7FOZeqW0edSPNv9+5mZteO3AD5A8d8XYHXgyxHx8Ba32D4COK58fxLFCqYJm85y3h0djr0qxffaQcCx9eeqR8R0c9xD8Uz2/9/efYfJUtX5H39/iUoGgZV8EUQQxBUDiglUjLhGFAEl7Kq7ruvqT1nXSDChYkBXTKsCCooYMKzumgiKiKCigKAgXpSgiMSL5Pv9/VE1TE3dCd3T1V1dM+/X8/Rz+5yp8O2+PaE+T51zTga+PdP/V0RsQhEavg5Yrez+14j4Zmb+73T7zEdmLmWwz+R5tfajgHMGOJ4kSZIkqVnmeQ0zz1uBeV7vzPPm9kHM82ZlnidJUrd4o4/GQfXO7hsy84ohn+9Y4Ahg5bL92IjYJjN/N/Mu90xN+rhK110U6+yOo08yOd3nL4H3NXHQzFweEb8Ftq90P5Leg4FHTdM3r6lkM/P8iPgZk5+fg5gmGCinTa2GD2MZ5oyLzLwkIv4b+Oeyaw3gMJoZQQbF9NOb1Novz8z6yJSJei4FnhMRRwOvKrvvTzFy5YiGaupLZt5AOW11RNxW+9rSAQ+/NnAd8PjMrI+AmjjH76fp3rmXc5eBwZsi4lTg20z+HfCfFMHCuPhVrf2Ipg4cERsDG/W52zZNnV+SJEmSFgjzvOaZ55XM8/pjnjc387yRMM+TJGmEXLpLrSpHA1QvDC8f9jnL9WKrfwAHc6wJXTqIqXe0f6upURFNioh/BJ5UNpcDL83Muxo8xem19ov72Pcl0/StPUAt1Yv8PSNi82m2qY7a+hPjdfEzrg6nmGJ2wsERMd+RWveIiIcBT690nQW8bKZQoOb/MfVi8ZVzTO/cZa+eKRSYSb+BRGZ+D/hYpevxEbHZTNu3oP67YLsGj/0Kimmk+3l8rcHzS5IkSVKnmec1zzxvBeZ5/TPPa5d5nnmeJEkj5Y0+atuSWnvYo38m1EeBHBARM34/lF87oNb9qcarGlBEbAocVen6UGY2PT3mZ2vtJ0fE06fdsiIingk8cZovDRIMnMjk9Kkr/B9FxJrACypdxzcckixImfkn4AOVrlWYOj32fL2q1n5jZi7vsaa7gaMrXRsx/YiyrvsjcMKIzvXlWnu3EZ23F1dRBJsTlrRUhyRJkiRpRUtqbfO8AZjnmec1wTyvVeZ5BfM8SZJGyBt91LaNa+3rR3TebwDXVNqbA3vOsv2TgC0q7T8D3xpCXYM6BlivfH458OamT5CZZ7LiKKATI+Jx020PEBG7A5+b4cs9XRjOUMsNwFcrXQfWNnkBsFal/Zn5nmsReg9wbaX9vIjYdaaNe/SkyvM/seLnaC6n1tqPHaycsfT1XsOSXkTEKhGxXkRsERFLqg8ga5vv0NR5B1UGeMsqXRtGRFPr1kuSJEmSBmOe1yzzvKnM8+bPPK8d5nmY50mSNGqrzL2JNFRr1Nq3juKkmXlnRHwWeG2l+yDg/2bY5eBa+7hxG0kSEfsAz6p0/Utm3jLT9gM6GDgXWL9srwucGhGfB04GLqGYFnlbiovzFzE5TfIVFEHMhBsGrOUz5fEBto2Ix2bmD8v2P1a2OyszLx7wXItGZt4cEe9g6kigI4E95nO8iNiGqWt5Xwps1ee13mq19kJcZ/kXg+xcTp++N/AU4EHAln3svv7cm4zU34B1yudB8fuiiZ9px1D8nOrHNjjdryRJkiRNMM9riHkeYJ7XGPO81pjnTTLPkyRpRLzRR22rfwZHebH9KaYGA8+OiPUzc8oopIhYH3h2bd/6VMGtiogNgQ9Vuj6fmd8e1vky87KIeDbF6JsNyu6VgP3Kx0zOBo4HPlLpu2HAcr5HMdppq7J9MPDDiNgOeHRlu7H6P+uIY4B/Z3Ka1d0j4umZOZ/Rb1vU2o8Bfj9AbTD52VtIrpl7kxVFxBrAYRT/X/UApVfrznO/Yan/Pli1iYNm5jX0+T47+EiSJEmSpjDPa4B5nnnekJjnjZ553iTzPEmSRsSlu9S2+oife4/qxJl5EXBWpWt1YN9pNt23/NqEH2Xmb4ZZ2zx8iGKNY4DrgFcP+4SZeQawK8WF+ZybU1xkPpEVRxn8acA6Ejiu0rV3RKzF1FFbfwO+OMh5FqPMvAN4S637XeUa9/26TwMl1Q2yHvy4urnfHcrP+/8ChzD/UADG72+C+u+DYY1olCRJkiT1xzyvGeZ5k8zzGmKe1wrzvEnmeZIkjci4/RGgxeemWnvNEZ//U7V2fUrf6frq+7QqIh7A5FS3AB8E1qiv3zvNer7r1Q61Vm2bOacIzcxLM3NPYDfgKIrpf/8M3EGxHvQvKNaG3jkz/7Wceri+bvC5fb/oFX2GyfWJ16R4P15S+fqXMrP+WVNvTgB+WWnvzOyjvGYyyAXrTByWUXg3U9c3T+C7FKOBHkMxgmttYLXMjIkHsPWoC+1T9ffBbZl5Z2uVSJIkSZKqzPMGZJ4HmOcNk3ne+DPPkyRJA3HpLrXtj7X2JtNuNTwnUVxIr1W2d4mInTPzVwARsTOwS2X7m+l/Ldhhq98lf0T56NfzyseEG1kxPJhWZp7F1NFUs3lUrX12j/vNdv6lEXEak+tNv5upI40+M+g5FqvMzIh4A1Cd3vdtEfHFzLy9j0NdW2t/IjNfPniFjVu57QL6ERGbAP9c6boNeFZmfqeH3deZe5N2lFOs36vSVf9dIUmSJElqj3ne4MzzzPOGxjxvvJnnSZKkJjijj9q2lMmRGwCbj/LkmbmMFaeArY74+cfa104qR7FoHiJia+B+la4rMvPShg5fXbO7GgpcBpze0DkWpXJ9+FMrXVsB/9LnYf5ca283UFGzq68F3c9NrfWpqMfdXkz9Xf6eHkMBgE2HUE9TNqu1B13/XZIkSZLUnKWY5y0a5nndZJ431szzJEnSwLzRR63KzNuA6vrYW0bEGiMuoz51734RsVpErMaKa3yP1TS/HTTMaZO/TDFqqe7Yct1vDeY/a+03RUQ/I0guZOr/z6MiYlhrctendV6vj3137PNcbX+27l9rf7OPfXdrspCG1acEP6+NIiRJkiRJKzLPW3TM87rLPG96bX+2zPMkSdLAvNFH4+CcyvOVgJ1GefLM/DFwcaVrQ+CZwD+Uzyf8OjN/MsraepGZ51XX6e31ARxeO9RxtW3Wa7LOcurOl1W67qbBYCAzbwW+UOteDhzb1DkWs8z8KUX4MmFD4D/62P9u4PuVrtWBFzdT3QquqbUf2Me+z+jzXFOmO46I1fvcf1Dr1drThWMriIiVgf0br6Y5O9faP22lCkmSJEnSTMzzBmCeVzDPGy7zvBmZ5w2HeZ4kSSPkjT4aB/VpWB/RQg31C9SDGe5olcXofcDGlfZHM7PpdXrfAjy28th1COdYzN7I1Gl0XwPct4/9P1xrH1quSd20n9faz+xlp4jYEXhun+e6odYexuuZzfW19vY97vdKYOuGa2lS9ffAcuCMtgqRJEmSJE3LPG9xMM/rPvO8Fd1Qa5vnNcM8T5KkEfJGH42Db9Xae7RQw/HAnZX2U4AnV9p3Ap8daUVjrBw90Ou2ERHvBQ6qdF8OvKHpujLzL5n5o8rj3KbP0a+IWBoRWXkc2HZN85WZv2VqQLYGxfdKr/ufBny30rUx8K2I2LyfOiJi7YioT8NddQlQDYQeFhHPnuOYfwecDPT82S5dVGs/edqthueXtfbr5vr+jIinAe8eXkmDiYhVgUdXus7JzL+0VY8kSZIkaVrmeR1jntc787wp+5+GeV7TzPMkSdLAvNFHrcvMq4GzK117RMQqI67hGqauhbsyUy8QvjHIH6YRsWFELJnuMc3mm8+wbV8XT0O2Q0RcHBGHRMR2020QEatExJOAs4DXVb50O/DizFw2ikLVuMOBvw2w/wHAFZX23wO/ioj/iIgNp9/lnjDgHyLiU8CVwDtn2rZcw/2/a92fi4gXTXPclSNib4qpZHdgxRE1czm11n5v+VoeGRHb1r6H+xkt1atvAzdX2o8FvhoRW9Q3jIj7RMSRwNcpploe14vtRwFrVtqntFSHJEmSJGkG5nkrMM/TODPPm8o8r3nmeZIkjdhIL76kWRwP7Fo+X59iFNB3Z958KD4FPGeWrw3iKIoLol78cIb+y4ElA9bRpAcA7wHeExHXABcA15Zf+zuKNXnXr+1zK/DCzJzpNWrMZebVEfFBiml/57v/XhQj/zYtu9enGJFyZERcBFxGsTb16hRrVm9D8dmPyqGum+NU7wcOZHI62zWBE8vRaOcCt1CsS/5wJj+ny4B/Yura5XO9njMi4lzgYWXXOsw8uuZ0YPdej93j+a+PiLfXzvlM4OkR8TOK93IVYIuyxonAcxnwMuCrTdbTkOdXni8HPtdWIZIkSZKkWZnnTTLP09gyz1vh9ZjnNc88T5KkEfNGH42LL1BcPN+7bO/N6IOB/wWuYvJiZcKVwP+NuJau2Rh4whzb/BrYPzN/MYJ6xsm9au1+R5iMo3cDLwfuM5+dM/OXEfEQiumzq1PjBvDA8jGXWd/HzFxWTu/7f0xdd3yz8lF3LUUweMU0X5vLC4H/off1tBuVme+JiG2Bl1a6V6ZYF/sR0+zyV4q1y/8wgvL6EhErAc+rdH0nM+fzfyJJkiRJGj7zvG4zz5uZeV6NeV6zzPMkSdKgXLpLYyEzrwOOq3S9MCLWGnENdwPHTvOl48qvadJVwMeApT1s+3OKC5YHL7ZQICLuRzEaasIlTJ1SupMy8ybgHQMe45rMfArwOIqpXG/pYbffU0zh+zQmR9zMdo5fldsdB9w1w2Y3AR8HHpSZP+qhhunOcxnFlMX7A1+kWOf7xlnO2bjMfFl5/ktm2ewvwH8BO2bmGSMprH9PZ2o4+4G2CpEkSZIkzc48r3PM83pgnjfrMczzGmSeJ0mSBhHF0qdS+yLi/sDFTN6A9vLM/ESLJakHEbEpxbS+SyimZV2FYhrR3wPnZOZVrRXXsoj4J+CTla4XZ6bTlk4jIlahuIjflmJk0doUa4ffSDFd7UWZ+acBjr8ORQixhGI63r9QjIA5IzNvHaj4MRIRATyI4r3cCLgb+BPFVOFnZebIwor5iIhvAHuVzfMzc+c265kQETtSTGcOwIH/9VU23HLbFitq1rV/uJRjXzllpvudMvPCtuqRJEmS1B3med1knjcz87zemec1wzxvOOp53is+8Q02XnL/Fitq1jVLL+GYlz2z2mWeJ0mLjEt3aWxk5iURcQLw4rLr1RHxyfRutLFWXvgv2ov/OVSnP74YOLGtQsZdecH6k/IxjOPfxAIYfTWX8uflr8pHp0TE9hQjgCYc1lIpkiRJkqQemed1k3nerMzzemSe1wzzPEmSNB8u3aVx81bgjvL5DhRr7EpdtUfl+eGZuby1SqTx90Ym/y45OzO/0mYxkiRJkqSemedpITHPk3pnnidJUku80UdjJTOXAh+sdB0aEX5O1TkR8UDgvmXzQoq1niVNIyIeALyobCbwuhbLkSRJkiT1wTxPC4V5ntQ78zxJktrlBZfG0REUa+1CsVb0AS3WIs1XdfTPYY7+kWb1HiaXEz0uM3/UZjGSJEmSpL6Z52khMM+TemeeJ0lSi1aZexNptDLzlojYF9iz7Fq1zXqk+cjMjwAfabsOadxFxDrAz4FflF1+30iSJElSx5jnaSEwz5N6Y54nSVL7vNFHYykzzwTObLsOSdJwZeZNwOFt1yFJkiRJGox5niQtDuZ5kiS1z6W7JEmSJEmSJEmSJEmSpA7wRh9JkiRJkiRJkiRJkiSpA7zRR5IkSZIkSZIkSZIkSeoAb/SRJEmSJEmSJEmSJEmSOsAbfSRJkiRJkiRJkiRJkqQOWKXtAiRJkrrkqutv45Y1/tZ2GY258frb2i5BkiRJkiRJGprLr72FG+91c9tlNOaGa29puwRJUsuc0UeSJEmSJEmSJEmSJEnqAG/0kSRJkiRJkiRJkiRJkjrAG30kSZIkSZIkSZIkSZKkDvBGH0mSJEmSJEmSJEmSJKkDvNFHkiRJkiRJkiRJkiRJ6gBv9JEkSZIkSZIkSZIkSZI6wBt9JEmSJEmSJEmSJEmSpA7wRh9JkiRJkiRJkiRJkiSpA7zRR5IkSZIkSZIkSZIkSeoAb/SRJEmSJEmSJEmSJEmSOsAbfSRJkiRJkiRJkiRJkqQO8EYfSZIkSZIkSZIkSZIkqQO80UeSJEmSJEmSJEmSJEnqgFXaLkBqQkR8BjiwbJ6Umfu0WI7GQERsDDwU2BxYD1gduAW4EbgcuAxYmpnZVo1SV0TE7sCpla7DM/Owho79RuAdZfPnwMMzc3kTx5YkSZIkjTczPdWZ6UnNMdOTJGnhckYfdV5EPBo4oGzeAbxhju1Pi4gsH6fVvnZg5WvDfBw4S30bRcTTIuKtEfGNiLh6mv2XDPB+nTas2tt6TZXzrBsR/y8iLgT+DHwL+ATwHuBtwPuBTwHfowgFrouI70XEmyLioT0cf8bPTpv6qSsilszw//q5eZy3fqwL5v0itKBExLGVz8XSOTb/APDH8vkuwL8MtThJkiRJ0lgw0+v7/TLTM9Mz09NQmelJktQdzuijTouIlYCPAFF2fTQzf99iSfMSEZsCRwMPB7ZquZxGjPo1RcQzgY8Dm/Sx23rAE8vH2yNi/cy8ofnqOmHfiDgqM89ru5CuiCGOiFlMMvPWiDiMIrCD4nvx85l5XYtlSZIkSZKGyExvfJnpdY6ZXp/M9JphpidJUruc0Uddty/w4PL5HcB7W6xlEBsDz2eBBAKlkb2mckTSKawYCNxGMW3oKcAJwNeAMymm+tVUARzZdhFatD5LMf02FGHdrKM4JUmSJEmdZ6Y3vsz0usVMT20y05MkqSXO6KPOiohVgSMqXcdn5pUDHvZLwGk9bnsU8LxK+2jggz3ue22P2y0Hfgts3+P287F1n9v3WvtMGn1NEbEL8N9MvXHxMuBQ4CuZ+bdp9glgO+AZwHOAxzRRywLwlIjYIzNPnXtTqTmZeWdEHAV8uOx6ZUR8IDOvarMuSZIkSVLzzPQaY6ZnpjfBTE+tMNOTJKk93uijLtuHqRe0Hxn0gJm5DFjWy7YRUd/uhsxcOmAJvwPOBc4p//1ZZi6LiBzwuDNqoOa5DPs1fQBYudI+E3h6Zt400w6ZmcBvysf7I2IH4FXA3Q3V1GXvBh7RdhFalI4D3gWsBdwLeDXwH20WJEmSJEkaCjO9BpjpmenVmOmpLWZ6kiS1wBt91GWvrTw/u+PrEF8MbJCZ17ddSIOG/poiYnPgcZWuu4D9ZgsEppOZFwH/0mRtHXJx+e/EaKyHR8TemXlyWwVpccrMmyPiROBlZdfLIuJtmXlzm3VJkiRJkhpnpjfezPS6wUxPY8FMT5Kkdqw09ybS+ImIRzG5jjfA59qqpQmZedsCCwRG9ZoeW2uflZmXT7ulZnI38MZa3zsiwhtB1YYTKs/XBfZtqxBJkiRJUvPM9MafmV5nmOlpnJjpSZI0Yv7Rp646sPJ8OfDllupQuzatta9opYqOy8yvRsRZwKPKrvsD/wR8bBTnL9dXfwjwAGAjYE2KdeOvAH60mEd/RMRWFO/NJsAGwA3AV2db5zoi/g54ILANsB6wWrnftRTTbP9uqEUP5kfA1RSvF4qf9R9vrRpJkiRJUtMOrDw301u8zPQaYKY3vsz0zPQkSRo2b/RR50TEysDela6fZebVbdWjVtV/hm3QShULw+uBMyrtQyPis5l5y7BOGBFbUIw8ej6w4Qyb3RkR3wPempnn9njc6lrxp2fm7n3UdCxwQKVr6/qa97OsRX9oRBw6y+H3yMzTeqk1Ip5NsZb1I4GoHedK4JTKMVYGHk/xPj6JItSZUURcARwDHJOZN8627ahl5vKI+Cbw0rLrkRFxv8y8rM26JEmSJEmDM9NThZlec8z0MNNrm5meJEmj59Jd6qLdgPUr7VPbKkStu6bWfkxE3KeVSjouM38I/E+l677Aa4Z1voh4PXAJ8M/MHAgArAo8DfhpRLynHCm0YEXEKhHx38BXKUZj9fJ6/x34PsWa9LMGAqXNgXcC50XELvOtdYjqP9Of0UoVkiRJkqSmmelpgpleQ8z0xoOZHmCmJ0nSSDmjj7roqbX2D1upYoGIiKMpLj6WUEwJugz4K3AxxXt7Smb+tq365nBWrb0mcGJE7LPQ1kcfkf+kuACfuAn0kIj4WGZe29QJImIl4NNMHWEDxXTd5wNLgVsopvt9BMWazlBcHB8CbMzUab4XmqOAf6y0fwP8luI92QR4+DT71G/avYPi+/cK4EZgZYr388FMHSG3BPhBRDx0zKb+PaPWfirw4TYKkSRJkiQ1ykyvQWZ6qjDTa5+ZnpmeJEkj5Y0+6qJH1trn9bNzP1N+LhKvqrXXLx/bAnsB74qIrwGHjNmFA5l5cUScCzys0v1k4NKI+DTFCIqfZuZdDZ1v9yaO07Sm6srMCyLis0xesK8DvIlmRwG9hamBwO3AkcBHMvMv1Q0jYhXgxcD7mBzxd0BEnJWZba7xvHX57yOBz1f6jwY+OMt+f5rjuLtQTNcLxUisQzLzouoGEbE2sPoMxz4O+Cbwk+k+82Ug8ySK9/shZfe6wAms+HN1IJl5IPMMbzLzyoi4lslRYY3WFhEbU4Qk/dimyRokSZIkaZEy02uWmV7v59u9ieM0zUxv5Mz05jCumZ55niRJK/JGH3XRQyvPb8jMK1qrZHFYCXgO8MSIODgzv9x2QTX/D/gBU3+ebQC8rnzcGhE/A84pHz/OzMtHXmV3vBXYh8kLz1dExNH1Na3nIyJ2LY8/4XrgiZn5i+m2Ly9sPxMRZwI/BiamcH53RJyYmTcPWtN8TLwXEbGk9qUbBnyf1i7//TjwL5m5wrrh5Wuuv+4TgaMz887ZDp6Zy4HvRMTpwNeAp5Rf2jUidq+vNd6yXwFPKJ9vEBHbZualDR37FcBs665LkiRJkobDTG+0zPQWFzO9OZjpjcSwMj3zPEmSaupTA0pjLSLuy+S0nwBe3M3f+cB7gH0pplPdDngQ8ETgzeXXq9YBToqIp4+yyLmU61AfSDGKZDr3Bh5DMYLlRGBpRFweER8pL1JVkZl/AD5S6VoNeFtDh38LU3/v7DdTIFCr6bcUa1VPWBd4aUM1jZuLgFdNFwjMJDOvmisQqG1/O3AQUN1nv95LHIn6z/btWqlCkiRJktQIM71GmemZ6a3ATK91ZnoFMz1JkkbEG33UNUtqbUf+9O9EYKfM3DkzX5+Zn8/MczLzksy8IDN/kJnvyMydgf2ZOtJgZYpgYLNWKp9BZp4A7Ap8v8ddtqQYBfCTiPhBRDx4aMV10zso1oGesG9E7DzIASNiG+AZla7TM/PbfRziS0y9UPyHQeoZY+/PzDuGfZLMvJpiRNWE3YZ9zj7Vf7YvaaMISZIkSVJjltTaZnr9M9Mz05uLmV57zPQKZnqSJI2IS3epazauta9vpYoOy8xP9LHtCRHxW+A0YI2yey2KaTJf1nx185eZvwSeFBEPpVgD+h+YXHd5NntQhAMvzczPDbPGrsjM6yLi3cA7y66VKNaAHmTk15Nq7ZP6rCnL6WlfUnbtGhGrjeICesS+1uTBImINiumD7wVE7cvVn5/bR0T0M+poyOo/2+s/+wdxDHByn/tsQ8P/N5IkSZK0yJjpDchMbwVmejVmeq0y0ysMK9Mzz5MkqcYbfdQ1a9Tat7ZSxSKSmedExJuB91e6D4iI12TmLW3VNZPM/BnwM+DVEbE58Chgl/KxK1OniZ5wL+DYiLgmM78zsmLH29HAK4FNy/bTBlzz+TG19jXTrIc9l79Vnt+rrG3pPOsZR1dk5l/mu3NErATsDjwfeDjwQFb8mTmTlSim8r5xrg1H5G+19ppNHTgzrwGu6WefiHqeIkmSJEnqk5neiJnpLVpmeqNnpjdpKJmeeZ4kSSvyRh91Tf0ze1crVSw+xwCHUVw0QLHG8x7AN9sqqBeZeQXFnf4nwz0XTY+gGB10MMWF5YSVgU9GxP0X4IiSvmXm3yLicODjle4jgUfO85Bb1NpfmudxqjZgYYUCfV2sVkXEY4H/AgaZjnldxicUqP9sX7WVKiRJkiRJTTHTa4eZ3iJjptcKM71JZnqSJI3ISm0XIPWpPtrn3q1Uschk5u3AqbXugdZ3bkNmLs/Mn2TmvwI7AufXNtkS2Hv0lY2tTwG/qbR3jYjnzfNY92mgnrq1h3DMNt08n50i4vkUa9kP+j05Tn8T1H+2j91IQ0mSJElSX8z0WmCmt2iZ6Y2Wmd4kMz1JkkZknP4AkHpxU63d2HIumtPSWnujNopoSmZeRrE+df1i48ktlDOWMvNu4I217ndGxHxmg1utgZLqFv38qxGxFXAcU0fHXAN8AHguRVCwIcV0vytlZkw8yv3GVf1ne/1nvyRJkiSpW8z02rO01jbTW+DM9MafmZ4kSRqUS3epa/5Ya2/SShWL04IbeZWZV0TESRRT/k7Yvq16xlFmfiUizqZYCx1gO+AfmTr9by+uLfedsGlmXt1AiU1bue0C+vR6pq7Z/Q3gRZnZy2iZdebepDWb1tr1n/2SJEmSpG4x02uPmd4iZKY39sz0JEnSQJzRR12zFMhKe/OW6liMNqy1r22liuadV2uv30YRY+71tfahEbHGtFvO7M+19nbTbtWMuyvP+72htWv//8+qPF8G7N9jIAArXniPk81q7d+3UoUkSZIkqSlLMdNri5ne4mWmN77M9CRJ0kC80Uedkpm3MXV94S3ncXGi+dm11r6qlSqad3etfWMrVYyxzDwd+FalaxPg1X0e5se19jCnU65OCbten/vu2Me2Ofcmw1P+7Kte2J+RmT1NhxsR9wIeMpTCmrFD5fly4Py2CpEkSZIkDc5Mr1VmeouUmd6MzPSGx0xPkqQR8UYfddE5lecrATu1VchiEREPAh5U6z6thVKG4YG19pWtVDH+3kBxcTbhP4D79LH//9XaLy4vTIfhmsrz+0fEqjNuWREROwBL+jjP7bX26n3s24T1au1+Aq19Gc4a6wOLiNWZOjrs15m5rK16JEmSJEmNMdMbMTM9YaY3HTO9ITDTkyRptLzRR110eq39iFaqWCQiYmXgA7XuSzPz123UUxURW0fEegPsvx7wglr3DwapaaHKzF8BJ1S61gXe1Mf+5zP1e3cL4I3NVLeCn1eer0bvI43e2ud5bqi1N+lz/0FdX2v3tBZ9RKwLvKX5chqzC1OnZz6tpTokSZIkSc0y0xshMz2Bmd4Mbqi1zfSaYaYnSdIIeaOPuuhbtfYerVTRQRHxb/2MuIiI1YBPAk+sfenwRgubv8cDSyPiiIjYuJ8dyylSPw9sVOm+HfhKU8VFxIERkZXH0qaO3ZK3MHXEy3P63P9NTJ0a9y0R8cp+i4iIXSNitilqv19rHxYRs67rHRH/BuzTZymXAXdU2nv0OtKoCZl5K3BJpeshETFrAFJ+7r9Af6OcRq3+M/1/WqlCkiRJktQ0M715MtObZKY3L2Z6U5npDYeZniRJI+SNPuqczLwaOLvStcdcf/B3QURsGBFLpntMs/nmM2y7+Ryn+RDw+4h4b3lhNe37FhGrRMSzKN7ng2pf/h5TR4G0/ZomRjJcGRHfjIh9Z9snItaMiP2BXwJPrX35yMy8opfXthhl5uXAMQPsfyZwWK37wxHx7YjYPSKm/Z0Uhe0j4pCI+CnwE+DBs5zqJKau6f0w4JSI2LS+YURsERH/TfG9ASuOqJlRZt4BnFnp2hL4ekQ8KyIeOM1neRjTGp9Ua58cEfvV38vyPXwScBaTn/u/DKGeJjyp8vxGHP0jSZIkSQuCmR5gpldlpjciZnpTmekNjZmeJEkj1PkLKS1axwO7ls/Xp7hb/LvtldOIo4ADetz2hzP0X87cd/XfF3hd+bg9Ii4Erqb443tVYGPgocBa0+x7LvDczMxpvjadUb0mKH6ePaN8EBFXAr8D/grcAqwNbEWxfvd06xh/EXh7j7UuZu8A/hFYZz47Z+YREbERUB3189TycWNE/ILiYvXO8hwbU/yfTfd5nOkcyyLiDcBHKt3PAC6PiLOBP1CsvX0/inAhym1OLM/b62cW4P1MHa0y8VqmswfNX+C+DzgYmAg81gE+BxwVEedSfF9vAPw9U6chPgG4i/5e69CVn43HVbpOyszb2qpHkiRJktQ4M73pmemZ6Q2bmd5UZnoNMtOTJGn0vNFHXfUFigvOe5ftvel+KNCG1SnWzp1LAh8GXj9mf6BPhBnrTvO1zcrHXG4F3gW8MzPvbrA2gPpoj55HloyrzPxrRLyHAQKUzPy3iDiH4jNVDRfWBXbv4RDLKf7fZ/NRijDhXyt9qwCPLh91n6UIOz7Zw/nvkZnfjIg3U0x9vXI/+zYhM2+IiL2A/6UIUCbcF9hrht1OoBjV19drHZHnMfV9/HRbhUiSJEmShsJMrxlmemZ6fTHTm8pMr3FmepIkjZhLd6mTMvM64LhK1wsjoufRAYvYIRTrof+1x+3/QjGC4oGZ+e9jFgiQmf9HsR73kylGYZxNMXqjF78FjgC2z8y3DSEQANit1v7AEM7Rhg9QBDLzlpnHU0yL+0bgNz3schvwA4rP8JaZ+dU5jp+Z+UpgP4pRYDP5GbBPZr4kM3v97NTP9Q5gZ+BI4AzgTxRh00hk5i8oRvccz8yf/wR+BOydmfvP97WOwD9Vnv8kM8+ecUtJkiRJUueY6c2bmd4kM735M9Obei4zveaY6UmSNGLR+2yd0niJiPsDFzN5w9rLM/MTLZbUKeWa1w8ANgfuQzGS6m6KESrXAudl5mwXU2MpIlYHtgXuTzGt6doU0xcvo1jj+XLgl5nZazAySC1/pHh/objw3XFI4UPnRcQmwCMoRrBsQPF9fTPFBfZvgN+U62fP9/gPoljXeyOK6W2vpPgcXDxg6WMlItYDHkMxhfFawHUU7+G5475WfUQ8lGIq8QnPy8yvtFVPVUTsCFww0X7y2z7Pupvdr8WKmnXjlZfxnbe8qNq1U2Ze2FY9kiRJkhY2M73BmOmZ6Y0TM71mmOk1r57nPeOdX2C9zbdpsaJm3XDF7/ifN+5T7TLPk6RFxqW71FmZeUlEnAC8uOx6dUR8so+1phe18gJhrC8S5iMzbwcuLB+tiYjtmAwEAI4wEJhZZl4NfG2Ixz8fOH9Yxx8XmXkD8M2265in11ae/xKYdYSXJEmSJKmbzPQGY6Y3XGZ6/THTa4aZniRJ6pdLd6nr3gpMjAjYAXhOi7VIVU+oPP81xRr0kqYREdsCL6h0vcGAV5IkSZIWNDM9jSszPalHZnqSJLXHG33UaZm5FPhgpevQiPBzrXFQDQUOz8zlrVUijb9DgZXL59/NzG+3WYwkSZIkabjM9DTGzPSk3pnpSZLUEi+etBAcAfyhfL4zcECLtUhERAC7l80LgJPbq0Yab+U63vuVzTuAV7ZYjiRJkiRpdMz0NFbM9KTemelJktSuVdouQBpUZt4SEfsCe5Zdq7ZZj1ROT7px23VIHbEZRbgLcGFm/rbNYiRJkiRJo2Gmp3Fjpif1xUxPkqQWeaOPFoTMPBM4s+06JEn9ycyvA19vuw5JkiRJ0uiZ6UlSN5npSZLULpfukiRJkiRJkiRJkiRJkjrAG30kSZIkSZIkSZIkSZKkDvBGH0mSJEmSJEmSJEmSJKkDvNFHkiRJkiRJkiRJkiRJ6oBV2i5AkiSpS+68ezl33LW87TIac+fdC+e1SJIkSZIkSXV33p0LLM/LtkuQJLXMGX0kSZIkSZIkSZIkSZKkDvBGH0mSJEmSJEmSJEmSJKkDvNFHkiRJkiRJkiRJkiRJ6gBv9JEkSZIkSZIkSZIkSZI6wBt9JEmSJEmSJEmSJEmSpA7wRh9JkiRJkiRJkiRJkiSpA7zRR5IkSZIkSZIkSZIkSeoAb/SRJEmSJEmSJEmSJEmSOsAbfSRJkiRJkiRJkiRJkqQO8EYfSZIkSZIkSZIkSZIkqQO80UeSJEmSJEmSJEmSJEnqAG/0kSRJkiRJkiRJkiRJkjrAG30kSZIkSZIkSZIkSZKkDlil7QKkCRHxGeDAsnlSZu7TYjmaRkRsDuwILAHWK7uvB64EfpqZf2mnMknDFhFZaZ6embs3dNzdgDPL5i3A9pl5RRPHliRJkiQNl3ne+DPPkxYv8zxJkhYuZ/TRWIiIRwMHlM07gDfMsf1pEZHl47Ta1w6sfG2YjwNnqW+jiHhaRLw1Ir4REVdPs/+SAd6v04ZVe+0860bE/hHxuYi4Evgj8L/Ax4Ajy8fHgW8C10TEeRHx8oi413xf2xz1vKn2Os5r8NjPrB37uohYvbbNYdVtmjr3oPqtKyKWTvOZuCwiVpvHuevH2nB+r0ILyTQ/h5fMtG1m/hj4ctlcE/jAKGqUJEmSJA3GPK/v98s8zzzvHuZ5GjfmeZIkdYs3+qh1EbES8BEgyq6PZubvWyxpXiJi04g4OSKWAtcA3wIOB/YC7ttmbfMREa+keB2fBfYDNu1htwdThAY/j4iHDaGsY4G7q+eLiF0aOvbBtfYJmXl7Q8fugq2Bf267iK6pXfye1nY9HfYGJr+3nx8RT2izGEmSJEnS7MzzxpN5nnme5mae1xjzPEmSWuSNPhoH+1JcUEIx+ue9LdYyiI2B5wNbtV1IQ5YA040IuYliWs6vAl8AzgBurW2zA3B6RDy2yYIy80rg/2rdBw163IjYCHhGrftTgx63g94cEWu3XYQWn8y8BPhipevItmqRJEmSJPXEPG88LcE8b7Exz1MrzPMkSWrXKm0XoMUtIlYFjqh0HV9e/A3iS8BpPW57FPC8Svto4IM97nttj9stB34LbN/j9vOxdZ/b91r7hCuA44GvAOdlZnUUDhGxJsXokbcB9y671wC+FhEPaHit708BT6+0942I1w04WufFwKqV9s8z87wBjtdVGwGvAw5tuxAtSu8EXlQ+f3hEPDczv9JmQZIkSZKkFZnnNcY8zzyvCeZ5apN5niRJLfFGH7VtH6Ze1H5k0ANm5jJgWS/bRkR9uxsyc+mAJfwOOBc4p/z3Z5m5bJhrQDdQ80zOp5iu+KuZuXyW898CvC8ifgh8H1ir/NL6FGFBk1PIfoNiCuKNy/YGwLOYOnqgX/VRRItx9M+E/xcRx2Tmn9suRItLZl4QEWcAjyu7/pMijJQkSZIkjRfzvAaY55nnNcg8T60wz5MkqT0u3aW2vbby/OyOj7q4GNggM7fNzH0y832ZeXoZVHTRh4AHZ+aXZwsFqjLzpxRr81a9sBzp1YjMvJNinfGq+nrcPYuIRwA7VbpuA06c7/E66pTK87WAt7ZUh/SxyvOHR8TjZtxSkiRJktQW87zxZZ63eJxSeW6epzaZ50mS1AJv9FFrIuJRTK7lDfC5tmppQmbelpnXt11HUzLzD5k5n1FLn6a4uJ6wHvCQRoqaVB+hs2dEbD7PY9VH/3wlM2+Y57G66lCmrsv+0ojYtq1itKidAtxSaf9LS3VIkiRJkqZhnjfezPMWFfM8jYtTMM+TJGnkXLpLbTqw8nw58OWW6lCDMvNvEfEbpoY+mzZ8josi4izgUWXXSsABwDv6OU5E3ItiuumqxTjN71UU69n/Z9leFXg7K743QxMR9wN2oVhXfH3gRuBPwFmZedWo6hg3EbEusBvF99DGFKHb6Zn581n2WRt4ILAdsCGwJnAzcB1wAfCrzLx7yKXPS2beGhHfBF5Ydj07ItbNzBvbrEuSJEmSdI8DK8/N8xYI87xOMs8bU+Z55nmSJI2CN/qoFRGxMrB3petnmXl1W/WocXfV2qsN4RyfYjIYgCJo6isYAJ5HMUJpwu+BUweqqruOBF5GsUY6wAsi4r2Z+bNhnTAi1gReRTFV84wjjiLiPOCdwJd6GZUWEacBj59oZ2b0UdOBwGcqXQdl5rGzHb/i8RExW32HZ+ZhvdQaETtSfJ6fCqxeO87RwJRgICJ2oriYfgpFwLLyLHXcHBGfA47KzMtm2a4tX2cyGLgX8Fym/p9IkiRJklpgnrfgmed1j3ke5nljwjxPkqQRc+kutWU3irv8JyzWi7EFJyICuF+texihz0lAdb30beex/m99mt9Pz3N6484rR1i8q9IVwLuHdb6IeApwGcUF/1zTCv898EXgO+WImAUtIv4ZOBd4FiuGAtNtvwtwPvBm4OHMHgoArE0xhe4FEbH/YNUORf33wV6tVCFJkiRJqjPPW6DM87rJPG98mOeZ50mSNGrO6KO2PLXW/mErVSwQEXE0xWiYJRQjWpYBfwUupnhvT8nM346onCcyNfS5A/hl0yfJzGUR8UWK0SMTDgLO6GX/iNgKeEKlazlwbGMFdtOHgX8DtizbT4yIPTPzu02eJCJeCnyUFS9glwIXUkzzuw7FdNFbVL7+JOBHEbFbZt7cZE3jIiKeAxxDEcwA/Bn4BXA9cB9g52l2q9+0mxSj2S4BbgLupPie3JHJ/1uAewOfjYjbMvNLTb2GQWXm1RFxKZOB0Z4RsfK4Tk8sSZIkSYuIeV6DzPPuYZ43GPO8lpnnmedJktQGZ/RRWx5Za5/Xz86ZuXtmRvnYvbGquutVFHf+b0SxHvP6FH9U70UxiuOiiPhKRGwzglpeU2t/PzNvGtK56utv7x0Ra/W470FMXnwBfCczr5hth8w8rPK563n62GFrqq7MvB04tNZ9ZDmqqxER8QRWDAVOAHbMzK0zc6/M3C8zn5mZWwJ7UKxDPWEn4BNN1TNP+wBbl4+qsyv90z0+2MOxj6P4XP6aYtreTTLzaZm5b2Y+BdgceP80+91KMR3us4F1MnObzHxqZr6gfD+fnplbAQ8CTq7t++mI2LiH2nqWmcdWP5OZubTPQ5xXeb42RaghSZIkSWqXeV6zzPMK5nnmeaNgnjcH8zxJkrrFGX3UlodWnt8w1wWZBrYS8ByKER0HZ+aXh3GSiHge8PRa91HDOBdAZv44Ii4Gti+71gReAHx6tv3KC90Dat31kGGxOh54LcUFOBTrQ+8DfH7QA5ehzYlMhgIJ/FNmzvj/lZmnRcSjgO8wuYb7PhHx0czsabRX0zLzTxPPa5nJbfO4AK5bGzgH2LOcfrl+7ruBP9S6fwtslpnXz3XwzLyAYr32w5gMgdYGXgEcNv+yG/cr4PmV9iPKvoGVIchGfe42ilBVkiRJksaded5omedVmOfNyjxvDuZ5I2GeJ0nSCDmjj0YuIu4LVNflvbytWhaA84H3APtS/OG8HcUd/k+kWN/3/Nr26wAnRUT94n1gEbE18Mla98mZ+YOmz1VTv6A/eNqtpnoCxbTIE64Fvt5UQV2WmcuBN9a63x4RqzZw+H8G/q7Sfu9soUClpmXAC4HbK92va6CecXQ7sO90ocBMMvOmXkKBmiOYeqG9X5/7D1v998J2DR77FRSjyvp5fK3B80uSJElS55jnNco8zzyvUeZ5rTPPK5jnSZI0Qt7oozYsqbUd/dO/E4GdMnPnzHx9Zn4+M8/JzEsy84LM/EFmviMzdwb2B6rrH69MEQ5s1lQxEbEO8A2mruV9NcUf4MN2PHBXpf3oiJjrIqIeHnw2M+9otqzuysxvUKwFP+F+wMsbOPS/VZ4vA97WR01/BL5Y6XpyRKzeQE3j5kuZeemwT1IGQF+tdG0bEf2Oihmm+u+FJW0UIUmSJEm6x5Ja2zyvf+Z5k8zzGmae1yrzvIJ5niRJI+SNPmpDfe3Yfu9cX/Qy8xOZeWGP255AMSLob5XutVhx7eZ5iYjVgK8wdc3dO4AXZOa1TZxjNpl5DfDNWvdBM20fEetSTHtcNecolEXo9bX2W/pYL30FEfEAYMtK17fKkT39OLXyfHWKUW8LzSlNHiwiVo+IDSNiq4hYUn1QrANetUOT5x5Q/fdCo2uOS5IkSZL6Zp43IPO8SeZ5Q2Oe145TmjyYeZ4kSerFKm0XoEVpjVq7/sepGpaZ50TEm4H3V7oPiIjXZOYt8z1uRKxMsdbzEyvddwH7ZOaP5nvcefgU8OxK+yUR8eZy/eO6FwH3rrR/Wq5zrIrMPCsivgY8q+zamGJ63cPmecjH1Np/KC9O+7G81t6GqSOVFoJfDLJzROxEMS3yYynCug372H39uTcZmb/V2ms2eOxjgJP73GcbnO5XkiRJ0uJmnjdi5nlTmOf1wDyvNeZ5BfM8SZJGyBt91Ib65+6uabdS046huKhbp2yvBuzBiqNnehIRKwGfAZ5b6V4OHJCZX51+r6H5NnAVsGnZ3hR4CvCtabatT/NbXxNck94A7EUxPTTAayPimHLUVb+2qLVfx+Drcm8w4P7jaD7vLRGxFfBBpgZk/Vp3gH2bVv+90MSa8sA9owb7ep8joqnTS5IkSVJXmee1wzyvYJ7XO/O80TPPK5jnSZI0Qi7dpTbUR/zce9qt1KjMvJ2pU6UC7DyfY0XxV/LHgBdXTwH8U2aeOL8K568c6XNcrXuF6X4jYkfg4ZWuvwFfGGJpnZaZFwHHVrrWAt4yz8PdZ+CCVrT2EI7Zqsy8ud99ImIH4CwGCwVgvP4mqP9emPdIRUmSJElSI8zzWmCeZ57XL/O80TPPu4d5niRJIzROfwRo8bip1m5yCkfNbmmtvdE8j/Nh4KW1vldk5mfmebwmfJoinJjwDxFRvxitj/45OTPrn0dNdShTw7yXR8Q28zjOag3VU7Xoh2VExCoU4dYmle7bgM8CBwIPK7+2FrBKZsbEg2nCszFS/73g96kkSZIktcs8rz1La23zPPO8uZjnjTHzPEmS1ARv9FEb/lhrbzLtVhqGgUdfRcT7gX+tdb86Mz8276oakJmXAmdUulYD9ptoRMSqwP613T49gtI6LTOvpAiCJqwKvH0eh7q21t63epE6z8dh831ds1h57k3GynOZOpLvUmDHzHxJZh6XmT/LzD9l5i3TrHG/DuNr01q7/ntDkiRJkjRa5nntMc+byjxvDuZ5Y888T5IkDcwbfdSGpUwdqbF5S3UsRhvW2vWLtVlFxLuB19S6D8nMoweqqjn19bmrI372AjautC/JzDNQL94FXF9pvzAidunzGH+utbcbrKRZTVkPuhwl06v1G65l2J5Va78sMy/rcd/6xfc42azW/n0rVUiSJEmSJizFPK8t5nmTzPN6Z543vszzJEnSwLzRRyOXmbcBv6l0bRkRa7RVzyKza619Va87RsTbgP+odb8pM48auKrmfAm4sdJ+cOUCtj6tqaN/epSZN1CEAxMCOLLPw/y41n7yIDXNoT4t7Hp97Ltjg3WMwv0rz28BTutj392aLaVRO9Ta57VRhCRJkiSpYJ7XKvO8SeZ5PTLPG2vmeZIkaWDe6KO2nFN5vhKwU1uFLBYR8SDgQbXu03rc963Am2vdh2fmOxsorTGZeSvw+Vr3QRFxX+Bplb67geNGVtjC8GHgikp7z4h4Uh/7/5ypI84eFRHD+r6/ptZ+YC87ldNB79nnuW6vPF+9z32bsF7l+U2ZmTNtWBUR2wKPHkpFzdi51v5pK1VIkiRJkqrM80bMPM88b0DmedMzzxsO8zxJkkbIG33UltNr7Ue0UsUiERErAx+odV+amb/uYd9DgMNr3e8a0nrKTahP97sv8FKgOt3rtzLz6tGV1H3lyL1Da91HUowG6mX/5cAxla4APtTnNLy9+nmt/cwe9zuYFaeYncsNleeb9LlvE6pTMG8cEb1OVfwexvRvgDKgeUil64LM/Gtb9UiSJEmS7mGeN0LmeeZ5gzLPm9ENlefmeQ0wz5MkafTG8o8CLQrfqrX3aKWKDoqIf4uIe/Wx/WrAJ4En1r5Uv9if9lwUFxBV78vMN/Z6/lHLzHOBX1W6NmDF0UsjmeY3IpZERNYeS0Zx7iE5Driw0n4osGUf+7+PqaOA9gA+08/nGSAitoyIp82yyQ9q7ZdHxBZzHPORwPv7qaN0UeX5VhHxgHkcYxC/rDxfGThkrh0i4nDgOUOraHAPB9astP+nrUIkSZIkSVOY582Ted7szPOGyjxvReZ5zTPPkyRpxLzRR60oR1+cXenaY0gjAUYqIjYsLwZXeEyz+eYzbLv5HKf5EPD7iHhvROw60/sWEatExLMo3uf6etbfA06Y47UcDBxd6/4K8F8zvcZZHuvN8ZqaVh8FtFrl+Z+Bb46wlgUjM+8G5h0KZeZNwAuBuyrd+wM/j4j9ZgsIImKTiDgoIr4OXFYeZ6bzXAqcWulaG/h+RDx8muOuFRH/UW6/BlNH1PTi1Fr7axFxYET8fURsPYLvg5Nq7TdExNsjYq36hhHxgIj4CvDWsusvQ6inCfUppE9powhJkiRJ0lTmeYB53jCZ5w2Bed60zPOaZ54nSdKIdf5CTJ12PLBr+Xx9itEA322vnEYcBRzQ47Y/nKH/cmDJHPveF3hd+bg9Ii4ErgZuBFYFNqYYnbHCxQFwLvDcHtb+fQkrTuP63PLRr8OBw+ax33x9jmLk0nRrLB+fmXdN068eZObXI+JM5rkedGb+ICIOpAhvJv5/dqD4P/t0RJwHXAUso/j8bgBsT/GZ7sdrgHMovh8A7g/8NCIuAC6mWNd9M4rRJhN1XAR8HPhgH+f5b4rvw7XL9gOAz8ywbePfB5n5/Yj4NlPXrH8T8O8R8VOKnwtrAdtRvM8TLgI+xorh3zh4fuX5bzLzJ61VIkmSJEmqM8+bnnne4MzzhsQ8bwXmec0zz5MkacS80Udt+gLFhfS9y/bedD8YaMPqwC49bJfAh4HXl+szL1iZeV1EnML0o0RGMs1vqT6i5S6KC96uez3wo/nunJknRMRvgM8D21a+tBrwiB4PM+tIncz8ZRlAHMtkOACwU/mo+znF2t9P7vH8E+e5KiJeCJwIrNfPvg3al+Jn58MqfWsBT5hh+/OAvYA9h1tW/6KYKvlBla6ZQhZJkiRJUjvM85phnldjnjd05nmT5zHPa5B5niRJ7XDpLrUmM6+jWCN4wgunm55SKziEYk30v/a4/V+AjwAPzMx/X+ihQEV9ul+AH2fmxSOsYbda+7OZee20W3ZIZp4JfH3AY5xLMbJnf+Aspk7/O53lwC8oRnbtkpmv6eEcJwKPAU6fZbM/UIyY2S0zr+qh9OnO822KkT+vpfjeXEoRAC2fz/Hmcf4bKF7nEcB1s2z6G4pQ55GZeeUISpuPl1ae3wJ8sq1CJEmSJEkrMs+bN/O83pjnDYl53grnMc9rjnmeJEktiLln+5SGJyLuTzHt5sRNZy/PzE+0WFKnlOt/PwDYHLgPxWiquylGR1wLnJeZv2uvwsUtIj4H7Fc27wQekJm/b7GksRURawOPpPgsb0AxemoZRQB2CXBRuSb4fI+/GfBYYBOKkUZXA5cCZ/Uw7XVnRMTqFFOo70gxhfoy4E8U79/5bdY2l7L2Kyl+lgF8ODNf1WJJ94iIHYELJtp7HHYC62x6vxYratZNV13GqYftV+3aKTMvbKseSZIkSePNPG8w5nnjzTyvd+Z5zTDPG456nvfkt32edTdbOHnejVdexnfe8qJql3meJC0yLt2lVmXmJRFxAvDisuvVEfHJhfSH+jBl5hXAFW3XoRntUXl+rKHAzDLzZoY41Xc54uULwzr+uMjM24EzykfXHMBkKHAr8O4Wa5EkSZIkzcA8bzDmeWPPPK9H5nnNMM+TJEnz4dJdGgdvBe4on+8APKfFWqRGRMT2wKZl8w7g7S2WI421iFiFYhriCR8e4+mIJUmSJEnmeVqAzPOk3pnnSZLULm/0UesycynwwUrXoRHhZ1Nd94TK809l5h9aq0QafwcAE3Pn/gV4V4u1SJIkSZLmYJ6nBco8T+qdeZ4kSS3y4kvj4ghg4sJpZ4o/EqUum5jm93bgnW0WIo2ziFiT4nfAhEMy84aWypEkSZIk9c48TwuNeZ7UA/M8SZLat0rbBUgAmXlLROwL7Fl2rdpmPdKgMnPvtmuQOmIb4JPl82WZeVybxUiSJEmSemOep4XGPE/qmXmeJEkt80YfjY3MPBM4s+06JEmjk5m/An7Vdh2SJEmSpP6Z50nS4mOeJ0lS+1y6S5IkSZIkSZIkSZIkSeoAb/SRJEmSJEmSJEmSJEmSOsAbfSRJkiRJkiRJkiRJkqQOWKXtAiRJksbcatXGLddc0VYdQzHN61ltuu0kSZIkSZKkjpiSby378x/bqmMopnk95nmStMhEZrZdgyRJ0tiKiH8AvtZ2HSP0rMz8ettFSJIkSZIkSfNhnidJWuhcukuSJEmSJEmSJEmSJEnqAG/0kSRJkiRJkiRJkiRJkjrApbskSZJmERHrAo+vdP0RuKOlcoZhNWCLSvv0zLyxrWIkSZIkSZKkQZjnSZIWOm/0kSRJkiRJkiRJkiRJkjrApbskSZIkSZIkSZIkSZKkDvBGH0mSJEmSJEmSJEmSJKkDvNFHkiRJkiRJkiRJkiRJ6gBv9JEkSZIkSZIkSZIkSZI6wBt9JEmSJEmSJEmSJEmSpA7wRh9JkiRJkiRJkiRJkiSpA7zRR5IkSZIkSZIkSZIkSeoAb/SRJEmSJEmSJEmSJEmSOsAbfSRJkiRJkiRJkiRJkqQO8EYfSZIkSZIkSZIkSZIkqQO80UeSJEmSJEmSJEmSJEnqAG/0kSRJkiRJkiRJkiRJkjrAG30kSZIkSZIkSZIkSZKkDvBGH0mSJEmSJEmSJEmSJKkDvNFHkiRJkiRJkiRJkiRJ6gBv9JEkSZIkSZIkSZIkSZI6wBt9JEmSJEmSJEmSJEmSpA7wRh9JkiRJkiRJkiRJkiSpA7zRR5IkSZIkSZIkSZIkSeoAb/SRJEmSJEmSJEmSJEmSOsAbfSRJkiRJkiRJkiRJkqQO8EYfSZIkSZIkSZIkSZIkqQO80UeSJEmSJEmSJEmSJEnqAG/0kSRJkiRJkiRJkiRJkjrAG30kSZIkSZIkSZIkSZKkDvBGH0mSJEmSJEmSJEmSJKkDvNFHkiRJkiRJkiRJkiRJ6gBv9JEkSZIkSZIkSZIkSZI6wBt9JEmSJEmSJEmSJEmSpA7wRh9JkiRJkiRJkiRJkiSpA7zRR5IkSZIkSZIkSZIkSeoAb/SRJEmSJEmSJEmSJEmSOsAbfSRJkiRJkiRJkiRJkqQO8EYfSZIkSZIkSZIkSZIkqQO80UeSJEmSJEmSJEmSJEnqAG/0kSRJkiRJkiRJkiRJkjrAG30kSZIkSZIkSZIkSZKkDvBGH0mSJEmSJEmSJEmSJKkDvNFHkiRJkiRJkiRJkiRJ6gBv9JEkSZIkSZIkSZIkSZI6wBt9JEmSJEmSJEmSJEmSpA74/7GJJi3dKaW/AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 3000x3000 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot prob vector from average pseudo energy at each site: \n",
    "fig,ax = plt.subplots(1,2,figsize=(10,10),dpi=300,gridspec_kw={'width_ratios': [1, 1]})\n",
    "\n",
    "# Method 1: Take the average of the (logP_mut - logP_wt) values from each model\n",
    "method_1 = []\n",
    "for i,row in t4_df.iterrows():\n",
    "    method_1.append( ((row['log_mut_minus_wt_vals_esm1v_t33_650M_UR90S_1'])+\n",
    "                                   (row['log_mut_minus_wt_vals_esm1v_t33_650M_UR90S_2'])+\n",
    "                                   (row['log_mut_minus_wt_vals_esm1v_t33_650M_UR90S_3'])+\n",
    "                                   (row['log_mut_minus_wt_vals_esm1v_t33_650M_UR90S_4'])+\n",
    "                                   (row['log_mut_minus_wt_vals_esm1v_t33_650M_UR90S_5']))/5\n",
    "                        ) \n",
    "\n",
    "method_1= np.array(method_1)\n",
    "\n",
    "# Plot the vector\n",
    "method_1 = method_1.reshape(40,1) # note that the imshow function expects a vector with more than one dimension\n",
    "im1 = ax[0].imshow(method_1,cmap='RdBu')\n",
    "ax[0].set_title(r'$\\frac{1}{5} \\sum(\\logP_{mut} - \\logP_{wt}) $')\n",
    "ax[0].set_xticks([])\n",
    "ax[0].set_yticks(range(len(t4_df[[x for x in t4_df.columns if 'mut_struct_prob_diff' in x]])))\n",
    "ax[0].set_yticklabels(labels=zip(t4_df['variant'].to_numpy(),t4_df['effect'].to_numpy()))\n",
    "fig.colorbar(im1, ax=ax[0],orientation='vertical', aspect=1, pad=0.1)\n",
    "me_sum = method_1\n",
    "\n",
    "# Method 2: Take the log of the averaage P_mut, subtract the log of the average P_wt \n",
    "method_2 = []\n",
    "for i,row in t4_df.iterrows():\n",
    "    method_2.append( np.log( (np.exp(row['logP_mut_esm1v_t33_650M_UR90S_1'])+\n",
    "                                np.exp(row['logP_mut_esm1v_t33_650M_UR90S_2'])+\n",
    "                                np.exp(row['logP_mut_esm1v_t33_650M_UR90S_3'])+\n",
    "                                np.exp(row['logP_mut_esm1v_t33_650M_UR90S_4'])+\n",
    "                                np.exp(row['logP_mut_esm1v_t33_650M_UR90S_5']))\n",
    "                            / \n",
    "                            (np.exp(row['logP_wt_esm1v_t33_650M_UR90S_1'])+\n",
    "                                    np.exp(row['logP_wt_esm1v_t33_650M_UR90S_2'])+\n",
    "                                    np.exp(row['logP_wt_esm1v_t33_650M_UR90S_3'])+\n",
    "                                    np.exp(row['logP_wt_esm1v_t33_650M_UR90S_4'])+\n",
    "                                    np.exp(row['logP_wt_esm1v_t33_650M_UR90S_5']))\n",
    "                                 )\n",
    "                         )\n",
    "\n",
    "\n",
    "method_2= np.array(method_2)\n",
    "\n",
    "# Plot the second vector\n",
    "method_2 = method_2.reshape(40,1)\n",
    "im1 = ax[1].imshow(method_2,cmap='RdBu')\n",
    "ax[1].set_title(r'$ \\log(\\frac{1}{5}\\sum P_{mut}) - \\log(\\frac{1}{5}\\sum P_{wt}) $')\n",
    "ax[1].set_xticks([])\n",
    "ax[1].set_yticks(range(len(t4_df[[x for x in t4_df.columns if 'mut_struct_prob_diff' in x]])))\n",
    "ax[1].set_yticklabels(labels=zip(t4_df['variant'].to_numpy(),t4_df['effect'].to_numpy()))\n",
    "fig.colorbar(im1, ax=ax[1],orientation='vertical', aspect=1, pad=0.1)\n",
    "plt.savefig('plots/T4_mutant_log_differences_wt_structures.pdf')\n",
    "plt.show()\n",
    "me_log = method_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7ca44090-fa88-4d1b-b288-9c4b91bde7d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add combined results to T4_df\n",
    "t4_df[\"Avg_delta_log\"] = method_1\n",
    "t4_df[\"Diff_log_sum_probs\"] = method_2\n",
    "\n",
    "# Save combine dataframe\n",
    "t4_df.to_csv(\"t4_df_with_averages.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "69c24913-e013-4090-92c4-63f2eb6b1e41",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read T4 dataframe with averages from two methods above\n",
    "t4_df = pd.read_csv(\"data_and_dms/t4_df_with_averages.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "60742410-2318-41fb-9a2d-42a193eb9d9e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------+--------------------+------------------------+\n",
      "| Method |     Spearman R     |        P-Value         |\n",
      "+--------+--------------------+------------------------+\n",
      "|   1    | 0.6108558242709287 | 0.00015957799838907548 |\n",
      "|   2    | 0.6108558242709287 | 0.00015957799838907548 |\n",
      "+--------+--------------------+------------------------+\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1500x750 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate Correlations between \n",
    "t4df_no_nan = t4_df[~np.isnan(t4_df[\"ddG\"])]\n",
    "delta_delta_G = t4df_no_nan[\"ddG\"]\n",
    "method_1_no_nan = t4df_no_nan[\"Avg_delta_log\"]\n",
    "method_2_no_nan = t4df_no_nan[\"Diff_log_sum_probs\"]\n",
    "\n",
    "avg_delt_log_rho,avg_delt_log_p = ss.spearmanr(delta_delta_G,method_1_no_nan)\n",
    "diff_log_sum_rho,diff_log_sum_p = ss.spearmanr(delta_delta_G,method_1_no_nan)\n",
    "\n",
    "# Plot correlations\n",
    "fig,ax = plt.subplots(1,2,figsize=(5,2.5),dpi=300,gridspec_kw={'width_ratios': [1, 1]})\n",
    "\n",
    "# Get minimum values of each array for plotting vertical and horizontal lines\n",
    "min_x  = min(method_1_no_nan)\n",
    "max_x = max(method_1_no_nan)\n",
    "min_y  = min(delta_delta_G)\n",
    "max_y = max(delta_delta_G)\n",
    "\n",
    "# Method 1\n",
    "ax[0].plot(method_1_no_nan, delta_delta_G, 'bo')\n",
    "ax[0].set_title(\"Method 1\")\n",
    "ax[0].hlines(0, min_x, max_x, colors = '00', linestyles = \"dashed\" )\n",
    "ax[0].vlines(0, min_y, max_y, colors = '00', linestyles = \"dashed\" )\n",
    "ax[0].tick_params(labelsize = 9)\n",
    "ax[0].set_xlabel(r\"Network Prediction, $\\frac{1}{5} \\sum (logP_{mut} -  logP_{wt})$\",{'fontsize': 'xx-small'})\n",
    "ax[0].set_ylabel(r\"$\\Delta \\Delta G$\",labelpad = -7)\n",
    "\n",
    "# Method 2\n",
    "ax[1].plot(method_2_no_nan, delta_delta_G, 'ro')\n",
    "ax[1].set_title(\"Method 2\")\n",
    "ax[1].hlines(0, min_x, max_x, colors = '00', linestyles = \"dashed\" )\n",
    "ax[1].vlines(0, min_y, max_y, colors = '00', linestyles = \"dashed\" )\n",
    "ax[1].tick_params(labelsize = 9)\n",
    "ax[1].set_xlabel(r\"Network Prediction, $log(\\frac{1}{5} \\sum P_{mut}) - log(\\frac{1}{5} \\sum P_{wt})$\",{'fontsize': 'xx-small'})\n",
    "ax[1].set_ylabel(r\"$\\Delta \\Delta G$\",labelpad = -7)\n",
    "#plt.show()\n",
    "\n",
    "# Display Correlations as table\n",
    "correlations = PrettyTable([\"Method\", \"Spearman R\", \"P-Value\"])\n",
    "correlations.add_row([\"1\", avg_delt_log_rho, avg_delt_log_p])\n",
    "correlations.add_row([\"2\", diff_log_sum_rho, diff_log_sum_p])\n",
    "\n",
    "plt.savefig(\"plots/ddG_vs_prediction.jpg\")\n",
    "print(correlations)\n",
    "# print(\"For the first method ( taking the average of Delta Log values), the Spearman R value is: \", avg_delt_log_rho, \" and the p-value is: \", avg_delt_log_p)\n",
    "# print(\"For the second method ( taking the difference of the log sums), the Spearman R value is: \", diff_log_sum_rho, \" and the p-value is: \", diff_log_sum_p)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1d258ca6-0299-4b5d-ba3b-ced7ca3f09fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save pseudo energies as numpy arrays\n",
    "method_1 = t4_df[\"Avg_delta_log\"].to_numpy()\n",
    "method_2 = t4_df[\"Diff_log_sum_probs\"].to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "54e21c26-e907-46c1-af39-338d9582e717",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x750 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot ROC curves\n",
    "\n",
    "# Styling for AUC text on plot\n",
    "font = {'family': 'serif',\n",
    "        'color':  'black',\n",
    "        'size': 10\n",
    "        }\n",
    "\n",
    "box = {'facecolor': 'none',\n",
    "       'edgecolor': 'green',\n",
    "       'boxstyle': 'round'\n",
    "      }\n",
    "\n",
    "# Method one\n",
    "num_mutations = method_1.size\n",
    "num_n = 0\n",
    "num_d = 0\n",
    "total_n = t4_df[t4_df[\"effect\"] == 'Neutral'].shape[0]\n",
    "total_d = 40 - total_n\n",
    "points_x = [0]\n",
    "points_y = [0]\n",
    "auc_1 = 0\n",
    "\n",
    "for i, row in t4_df.sort_values(\"Avg_delta_log\").iterrows():\n",
    "    if row[\"effect\"] == 'Destabilizing':\n",
    "        num_d += 1\n",
    "    else:\n",
    "        num_n += 1\n",
    "        auc_1 += (num_d/total_d)*(1/total_n)\n",
    "        \n",
    "    points_y.append(num_d/total_d )\n",
    "    points_x.append( num_n/total_n )\n",
    "\n",
    "fig,ax = plt.subplots(1,2,figsize=(5,2.5),dpi=300,gridspec_kw={'width_ratios': [1, 1]})\n",
    "ax[0].set_xlim(-0.1,1.1)\n",
    "ax[0].set_ylim(-0.1,1.1)\n",
    "ax[0].tick_params(labelsize = 9)\n",
    "ax[0].text(.50,.1,\"AUC: \"+str(round(auc_1,2)),fontdict = font,bbox=box)\n",
    "ax[0].plot(points_x,points_y)\n",
    "ax[0].plot((0,.5,1),(0,.5,1),linestyle = 'dotted',linewidth = 0.5,color = 'black') # Add diaganol line for random guess ROC curve\n",
    "\n",
    "num_n = 0\n",
    "num_d = 0\n",
    "points_x = [0]\n",
    "points_y = [0]\n",
    "auc_2 = 0\n",
    "\n",
    "for i, row in t4_df.sort_values(\"Diff_log_sum_probs\").iterrows():\n",
    "    if row[\"effect\"] == 'Destabilizing':\n",
    "        num_d += 1\n",
    "        \n",
    "    else:\n",
    "        num_n += 1\n",
    "        auc_2 += (num_d/total_d)*(1/total_n)\n",
    "        \n",
    "    points_y.append(num_d/total_d )\n",
    "    points_x.append( num_n/total_n )\n",
    "\n",
    "ax[1].set_xlim(-0.1,1.1)\n",
    "ax[1].set_ylim(-0.1,1.1)\n",
    "ax[1].tick_params(labelsize = 9)\n",
    "ax[1].plot(points_x,points_y)\n",
    "ax[1].plot((0,.5,1),(0,.5,1),linestyle = 'dotted',linewidth = 0.5,color = 'black') # Add diaganol line for random guess ROC curve\n",
    "ax[1].text(.50,.1,\"AUC: \"+str(round(auc_2,3)),fontdict = font,bbox=box)\n",
    "plt.savefig(\"plots/T4Lys_roc_curves.jpg\")\n",
    "#plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "144272e8-4368-4a31-9025-673d1694fd3f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}