industry_community.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ca947037",
   "metadata": {},
   "source": [
    "# Community Detection\n",
    "\n",
    "_Realize that everything connects to everything else_ - Leonardo DaVinci\n",
    "\n",
    "\n",
    "Concepts\n",
    "- Industial Taxonomy\n",
    "- Community Detection\n",
    "\n",
    "References\n",
    "- Gerard Hoberg and Gordon Phillips, 2016, Text-Based Network Industries and Endogenous Product Differentiation. Journal of Political Economy 124 (5), 1423-1465. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ae4b5be6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import zipfile\n",
    "import io\n",
    "from itertools import chain\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pandas import DataFrame, Series\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import networkx as nx\n",
    "from finds.database import SQL\n",
    "from finds.readers import requests_get, Sectoring\n",
    "from finds.structured import BusDay, PSTAT\n",
    "from finds.recipes import graph_info\n",
    "from secret import credentials\n",
    "# %matplotlib qt\n",
    "VERBOSE = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5594dc59",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last FamaFrench Date 2024-03-28 00:00:00\n"
     ]
    }
   ],
   "source": [
    "sql = SQL(**credentials['sql'], verbose=VERBOSE)\n",
    "bd = BusDay(sql)\n",
    "pstat = PSTAT(sql, bd, verbose=VERBOSE)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b69912c",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "## Industry taxonomy\n",
    "\n",
    "Industry classification, or industry taxonomy,\n",
    "classifies companies into industrial groupings based on similar\n",
    "production processes, products, or behavior in financial markets.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8a6eeab",
   "metadata": {},
   "source": [
    "### TNIC\n",
    "\n",
    "Hoberg and Phillips (2016) calculate firm-by-firm pairwise similarity scores by parsing the product descriptions from the firm 10Ks and forming word vectors for each firm, after basic screens to eliminate common words are applied. The words used only include nouns or proper nouns (see paper for details), and exclude geographic terms.\n",
    "The cosine similarity score is computed as a continuous measure of product similarity for every pair of firms in our sample in each year, producing a pairwise similarity matrix.\n",
    "\n",
    "These product descriptions are legally required to be accurate, as Item 101 \n",
    "of Regulation S-K legally requires that firms describe the significant products they offer to the market, and these descriptions \n",
    "must also be updated and representative of the current fiscal year of the 10-K. Hence a a Text Based Industry Classification (TNIC) scheme, derived from the textual similarity of product descriptions, may better reflect firms' changes in the product market space over time.\n",
    "\n",
    "Source: https://hobergphillips.tuck.dartmouth.edu/industryclass.htm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8c59bc4b",
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    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>gvkey1</th>\n",
       "      <th>gvkey2</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24633638</th>\n",
       "      <td>2021</td>\n",
       "      <td>1004</td>\n",
       "      <td>1210</td>\n",
       "      <td>0.0085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24633639</th>\n",
       "      <td>2021</td>\n",
       "      <td>1004</td>\n",
       "      <td>1823</td>\n",
       "      <td>0.0071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24633640</th>\n",
       "      <td>2021</td>\n",
       "      <td>1004</td>\n",
       "      <td>2285</td>\n",
       "      <td>0.0077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24633641</th>\n",
       "      <td>2021</td>\n",
       "      <td>1004</td>\n",
       "      <td>4091</td>\n",
       "      <td>0.0339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24633642</th>\n",
       "      <td>2021</td>\n",
       "      <td>1004</td>\n",
       "      <td>9698</td>\n",
       "      <td>0.0039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>25478201</th>\n",
       "      <td>2021</td>\n",
       "      <td>349972</td>\n",
       "      <td>322154</td>\n",
       "      <td>0.0444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25478202</th>\n",
       "      <td>2021</td>\n",
       "      <td>349972</td>\n",
       "      <td>331856</td>\n",
       "      <td>0.0169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25478203</th>\n",
       "      <td>2021</td>\n",
       "      <td>349972</td>\n",
       "      <td>332115</td>\n",
       "      <td>0.0214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25478204</th>\n",
       "      <td>2021</td>\n",
       "      <td>349972</td>\n",
       "      <td>345556</td>\n",
       "      <td>0.0781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25478205</th>\n",
       "      <td>2021</td>\n",
       "      <td>349972</td>\n",
       "      <td>347007</td>\n",
       "      <td>0.0711</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>844568 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          year  gvkey1  gvkey2   score\n",
       "24633638  2021    1004    1210  0.0085\n",
       "24633639  2021    1004    1823  0.0071\n",
       "24633640  2021    1004    2285  0.0077\n",
       "24633641  2021    1004    4091  0.0339\n",
       "24633642  2021    1004    9698  0.0039\n",
       "...        ...     ...     ...     ...\n",
       "25478201  2021  349972  322154  0.0444\n",
       "25478202  2021  349972  331856  0.0169\n",
       "25478203  2021  349972  332115  0.0214\n",
       "25478204  2021  349972  345556  0.0781\n",
       "25478205  2021  349972  347007  0.0711\n",
       "\n",
       "[844568 rows x 4 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Retrieve TNIC scheme from Hoberg and Phillips website\n",
    "tnic_scheme = 'tnic3'\n",
    "root = 'https://hobergphillips.tuck.dartmouth.edu/idata/'   \n",
    "source = root + tnic_scheme + '_data.zip'\n",
    "if source.startswith('http'):\n",
    "    response = requests_get(source)\n",
    "    source = io.BytesIO(response.content)\n",
    "\n",
    "# extract the csv file from zip archive\n",
    "with zipfile.ZipFile(source).open(tnic_scheme + \"_data.txt\") as f:\n",
    "    tnic_data = pd.read_csv(f, sep='\\s+')\n",
    "\n",
    "# extract one year of tnic as data frame\n",
    "year = max(tnic_data['year']) # [1989, 1999, 2009, 2019]\n",
    "tnic = tnic_data[tnic_data['year'] == year].dropna()\n",
    "tnic"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34d451af",
   "metadata": {},
   "source": [
    "### Industry classification\n",
    "\n",
    "TODO\n",
    "- SIC, 2-digit, 3-, 4-\n",
    "- NAICS, 2, 3, 4, 5, 6\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0c79af05",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>lpermno</th>\n",
       "      <th>sic</th>\n",
       "      <th>naics</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Non-missing</th>\n",
       "      <td>4218</td>\n",
       "      <td>4218</td>\n",
       "      <td>4216</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "             lpermno   sic  naics\n",
       "Non-missing     4218  4218   4216"
      ]
     },
     "execution_count": 4,
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   "source": [
    "# populate dataframe of nodes with gvkey (as index), permno, sic and naics\n",
    "nodes = DataFrame(index=sorted(set(tnic['gvkey1']).union(tnic['gvkey2'])))\\\n",
    "        .rename_axis(index='gvkey')\n",
    "for code in ['lpermno', 'sic', 'naics']:\n",
    "    lookup = pstat.build_lookup('gvkey', code, fillna=0)\n",
    "    nodes[code] = lookup(nodes.index)\n",
    "Series(np.sum(nodes > 0, axis=0)).rename('Non-missing').to_frame().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "92da5732",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>lpermno</th>\n",
       "      <th>sic</th>\n",
       "      <th>naics</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Non-missing</th>\n",
       "      <td>4218</td>\n",
       "      <td>4218</td>\n",
       "      <td>4218</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "             lpermno   sic  naics\n",
       "Non-missing     4218  4218   4218"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "# supplement naics and sic with crosswalks in Sectoring class\n",
    "naics = Sectoring(sql, 'naics', fillna=0)   # supplement from crosswalk\n",
    "sic = Sectoring(sql, 'sic', fillna=0)\n",
    "nodes['naics'] = nodes['naics'].where(nodes['naics'] > 0, naics[nodes['sic']])\n",
    "nodes['sic'] = nodes['sic'].where(nodes['sic'] > 0, sic[nodes['naics']])\n",
    "Series(np.sum(nodes > 0, axis=0)).rename('Non-missing').to_frame().T "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9ed00de",
   "metadata": {},
   "source": [
    "### Sectors\n",
    "\n",
    "An industry taxonomy may include detailed classifications, and groupings into\n",
    "broader sector\n",
    "- Fama and French group 4-digit SIC codes into broader groups of 5, 10, 12, 17, 30, 38, 48, or 49 industry sectors.\n",
    "- The Bureau of Economic Analysis groups 6-digit NAICS codes into a few dozen \"summary\" level groups, using definitions that were updated in 1947, 1963 and 1997.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "91c0143e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4259 codes5\n",
      "4259 codes10\n",
      "4259 codes12\n",
      "4259 codes17\n",
      "4259 codes30\n",
      "4259 codes38\n",
      "4259 codes48\n",
      "4259 codes49\n",
      "4218 sic2\n",
      "4218 sic3\n",
      "3943 bea1947\n",
      "3943 bea1963\n",
      "3943 bea1997\n"
     ]
    },
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>lpermno</th>\n",
       "      <th>sic</th>\n",
       "      <th>naics</th>\n",
       "      <th>codes5</th>\n",
       "      <th>codes10</th>\n",
       "      <th>codes12</th>\n",
       "      <th>codes17</th>\n",
       "      <th>codes30</th>\n",
       "      <th>codes38</th>\n",
       "      <th>codes48</th>\n",
       "      <th>codes49</th>\n",
       "      <th>sic2</th>\n",
       "      <th>sic3</th>\n",
       "      <th>bea1947</th>\n",
       "      <th>bea1963</th>\n",
       "      <th>bea1997</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gvkey</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1004</th>\n",
       "      <td>54594</td>\n",
       "      <td>5080</td>\n",
       "      <td>423860</td>\n",
       "      <td>Cnsmr</td>\n",
       "      <td>Shops</td>\n",
       "      <td>Shops</td>\n",
       "      <td>Machn</td>\n",
       "      <td>Whlsl</td>\n",
       "      <td>Whlsl</td>\n",
       "      <td>Whlsl</td>\n",
       "      <td>Whlsl</td>\n",
       "      <td>50</td>\n",
       "      <td>508</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1045</th>\n",
       "      <td>21020</td>\n",
       "      <td>4512</td>\n",
       "      <td>481111</td>\n",
       "      <td>Other</td>\n",
       "      <td>Durbl</td>\n",
       "      <td>Durbl</td>\n",
       "      <td>Trans</td>\n",
       "      <td>Trans</td>\n",
       "      <td>Trans</td>\n",
       "      <td>Trans</td>\n",
       "      <td>Trans</td>\n",
       "      <td>45</td>\n",
       "      <td>451</td>\n",
       "      <td>48</td>\n",
       "      <td>481</td>\n",
       "      <td>481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1050</th>\n",
       "      <td>11499</td>\n",
       "      <td>3564</td>\n",
       "      <td>333413</td>\n",
       "      <td>Manuf</td>\n",
       "      <td>Manuf</td>\n",
       "      <td>Manuf</td>\n",
       "      <td>Machn</td>\n",
       "      <td>FabPr</td>\n",
       "      <td>Machn</td>\n",
       "      <td>Mach</td>\n",
       "      <td>Mach</td>\n",
       "      <td>35</td>\n",
       "      <td>356</td>\n",
       "      <td>333</td>\n",
       "      <td>333</td>\n",
       "      <td>333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1076</th>\n",
       "      <td>10517</td>\n",
       "      <td>6141</td>\n",
       "      <td>522220</td>\n",
       "      <td>Other</td>\n",
       "      <td>Other</td>\n",
       "      <td>Money</td>\n",
       "      <td>Finan</td>\n",
       "      <td>Fin</td>\n",
       "      <td>Money</td>\n",
       "      <td>Banks</td>\n",
       "      <td>Banks</td>\n",
       "      <td>61</td>\n",
       "      <td>614</td>\n",
       "      <td>52</td>\n",
       "      <td>521CI</td>\n",
       "      <td>521CI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1078</th>\n",
       "      <td>20482</td>\n",
       "      <td>3845</td>\n",
       "      <td>334510</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Other</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Instr</td>\n",
       "      <td>MedEq</td>\n",
       "      <td>MedEq</td>\n",
       "      <td>38</td>\n",
       "      <td>384</td>\n",
       "      <td>334</td>\n",
       "      <td>334</td>\n",
       "      <td>334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>345556</th>\n",
       "      <td>16069</td>\n",
       "      <td>2836</td>\n",
       "      <td>325414</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Other</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Chems</td>\n",
       "      <td>Drugs</td>\n",
       "      <td>Drugs</td>\n",
       "      <td>28</td>\n",
       "      <td>283</td>\n",
       "      <td>325</td>\n",
       "      <td>325</td>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>345920</th>\n",
       "      <td>20194</td>\n",
       "      <td>3524</td>\n",
       "      <td>333112</td>\n",
       "      <td>Manuf</td>\n",
       "      <td>Manuf</td>\n",
       "      <td>Manuf</td>\n",
       "      <td>Machn</td>\n",
       "      <td>FabPr</td>\n",
       "      <td>Machn</td>\n",
       "      <td>Mach</td>\n",
       "      <td>Mach</td>\n",
       "      <td>35</td>\n",
       "      <td>352</td>\n",
       "      <td>333</td>\n",
       "      <td>333</td>\n",
       "      <td>333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>345980</th>\n",
       "      <td>20333</td>\n",
       "      <td>5961</td>\n",
       "      <td>455110</td>\n",
       "      <td>Cnsmr</td>\n",
       "      <td>Shops</td>\n",
       "      <td>Shops</td>\n",
       "      <td>Rtail</td>\n",
       "      <td>Rtail</td>\n",
       "      <td>Rtail</td>\n",
       "      <td>Rtail</td>\n",
       "      <td>Rtail</td>\n",
       "      <td>59</td>\n",
       "      <td>596</td>\n",
       "      <td>44RT</td>\n",
       "      <td>44RT</td>\n",
       "      <td>4A0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>347007</th>\n",
       "      <td>15533</td>\n",
       "      <td>2836</td>\n",
       "      <td>325414</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Other</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Chems</td>\n",
       "      <td>Drugs</td>\n",
       "      <td>Drugs</td>\n",
       "      <td>28</td>\n",
       "      <td>283</td>\n",
       "      <td>325</td>\n",
       "      <td>325</td>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>349972</th>\n",
       "      <td>15642</td>\n",
       "      <td>2836</td>\n",
       "      <td>325414</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Other</td>\n",
       "      <td>Hlth</td>\n",
       "      <td>Chems</td>\n",
       "      <td>Drugs</td>\n",
       "      <td>Drugs</td>\n",
       "      <td>28</td>\n",
       "      <td>283</td>\n",
       "      <td>325</td>\n",
       "      <td>325</td>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3943 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        lpermno   sic   naics codes5 codes10 codes12 codes17 codes30 codes38  \\\n",
       "gvkey                                                                          \n",
       "1004      54594  5080  423860  Cnsmr   Shops   Shops   Machn   Whlsl   Whlsl   \n",
       "1045      21020  4512  481111  Other   Durbl   Durbl   Trans   Trans   Trans   \n",
       "1050      11499  3564  333413  Manuf   Manuf   Manuf   Machn   FabPr   Machn   \n",
       "1076      10517  6141  522220  Other   Other   Money   Finan     Fin   Money   \n",
       "1078      20482  3845  334510   Hlth    Hlth    Hlth   Other    Hlth   Instr   \n",
       "...         ...   ...     ...    ...     ...     ...     ...     ...     ...   \n",
       "345556    16069  2836  325414   Hlth    Hlth    Hlth   Other    Hlth   Chems   \n",
       "345920    20194  3524  333112  Manuf   Manuf   Manuf   Machn   FabPr   Machn   \n",
       "345980    20333  5961  455110  Cnsmr   Shops   Shops   Rtail   Rtail   Rtail   \n",
       "347007    15533  2836  325414   Hlth    Hlth    Hlth   Other    Hlth   Chems   \n",
       "349972    15642  2836  325414   Hlth    Hlth    Hlth   Other    Hlth   Chems   \n",
       "\n",
       "       codes48 codes49  sic2  sic3 bea1947 bea1963 bea1997  \n",
       "gvkey                                                       \n",
       "1004     Whlsl   Whlsl    50   508      42      42      42  \n",
       "1045     Trans   Trans    45   451      48     481     481  \n",
       "1050      Mach    Mach    35   356     333     333     333  \n",
       "1076     Banks   Banks    61   614      52   521CI   521CI  \n",
       "1078     MedEq   MedEq    38   384     334     334     334  \n",
       "...        ...     ...   ...   ...     ...     ...     ...  \n",
       "345556   Drugs   Drugs    28   283     325     325     325  \n",
       "345920    Mach    Mach    35   352     333     333     333  \n",
       "345980   Rtail   Rtail    59   596    44RT    44RT     4A0  \n",
       "347007   Drugs   Drugs    28   283     325     325     325  \n",
       "349972   Drugs   Drugs    28   283     325     325     325  \n",
       "\n",
       "[3943 rows x 16 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# include sectoring schemes\n",
    "codes = {'sic': ([f\"codes{c}\" for c in [5, 10, 12, 17, 30, 38, 48, 49]]\n",
    "                 + ['sic2', 'sic3']),\n",
    "         'naics': ['bea1947', 'bea1963', 'bea1997']}\n",
    "sectorings = {}   # store Sectoring objects\n",
    "for key, schemes in codes.items():\n",
    "    for scheme in schemes:\n",
    "        if scheme not in sectorings:\n",
    "\n",
    "            # missing value is integer 0 sic2 and sic3 shemes, else string ''\n",
    "            fillna = 0 if scheme.startswith('sic') else ''\n",
    "\n",
    "            # load the sectoring class from SQL\n",
    "            sectorings[scheme] = Sectoring(sql, scheme, fillna=fillna)\n",
    "\n",
    "            # apply the sectoring scheme to partition the nodes\n",
    "            nodes[scheme] = sectorings[scheme][nodes[key]]\n",
    "\n",
    "        # keep nodes with non-missing data\n",
    "        nodes = nodes[nodes[scheme].ne(sectorings[scheme].fillna)]\n",
    "        print(len(nodes), scheme)\n",
    "nodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ccfb41d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2021</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>transitivity</th>\n",
       "      <td>0.874473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>average_clustering</th>\n",
       "      <td>0.585098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>connected</th>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>connected_components</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>size_largest_component</th>\n",
       "      <td>3908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>directed</th>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weighted</th>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>negatively_weighted</th>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>edges</th>\n",
       "      <td>405305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nodes</th>\n",
       "      <td>3925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>selfloops</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>density</th>\n",
       "      <td>0.052631</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            2021\n",
       "transitivity            0.874473\n",
       "average_clustering      0.585098\n",
       "connected                  False\n",
       "connected_components           8\n",
       "size_largest_component      3908\n",
       "directed                   False\n",
       "weighted                    True\n",
       "negatively_weighted        False\n",
       "edges                     405305\n",
       "nodes                       3925\n",
       "selfloops                      0\n",
       "density                 0.052631"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# populate undirected graph with tnic edges\n",
    "edges = tnic[tnic['gvkey1'].isin(nodes.index) & tnic['gvkey2'].isin(nodes.index)]\n",
    "edges = list(\n",
    "    edges[['gvkey1', 'gvkey2', 'score']].itertuples(index=False, name=None))\n",
    "G = nx.Graph()\n",
    "G.add_weighted_edges_from(edges)\n",
    "G.remove_edges_from(nx.selfloop_edges(G))  # remove self-loops: not necessary\n",
    "Series(graph_info(G, fast=True)).rename(year).to_frame()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7582539f",
   "metadata": {},
   "source": [
    "## Community structure\n",
    "\n",
    "TODO\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d49aa2dc",
   "metadata": {},
   "source": [
    "### Measuring partitions\n",
    "\n",
    "TODO\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2bf97917",
   "metadata": {
    "lines_to_next_cell": 1
   },
   "outputs": [],
   "source": [
    "# evaluate modularity of sectoring schemes on TNIC graph\n",
    "def community_quality(G, communities):\n",
    "    \"\"\"helper to measure quality of partitions\"\"\"\n",
    "    out = {'communities': len(communities)}\n",
    "    out['modularity'] = nx.community.modularity(G, communities)\n",
    "    (out['coverage'],\n",
    "     out['performance']) = nx.community.partition_quality(G, communities)    \n",
    "    return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "eeaba37f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Quality of sectoring schemes on TNIC graph (2021)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>communities</th>\n",
       "      <th>modularity</th>\n",
       "      <th>coverage</th>\n",
       "      <th>performance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>bea1947</th>\n",
       "      <td>40</td>\n",
       "      <td>0.337511</td>\n",
       "      <td>0.791471</td>\n",
       "      <td>0.928649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bea1963</th>\n",
       "      <td>58</td>\n",
       "      <td>0.331096</td>\n",
       "      <td>0.748338</td>\n",
       "      <td>0.950073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bea1997</th>\n",
       "      <td>61</td>\n",
       "      <td>0.331030</td>\n",
       "      <td>0.748153</td>\n",
       "      <td>0.950577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>codes10</th>\n",
       "      <td>10</td>\n",
       "      <td>0.340272</td>\n",
       "      <td>0.938264</td>\n",
       "      <td>0.850497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>codes12</th>\n",
       "      <td>12</td>\n",
       "      <td>0.340412</td>\n",
       "      <td>0.931380</td>\n",
       "      <td>0.879861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>codes17</th>\n",
       "      <td>17</td>\n",
       "      <td>0.278554</td>\n",
       "      <td>0.737459</td>\n",
       "      <td>0.788439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>codes30</th>\n",
       "      <td>30</td>\n",
       "      <td>0.339191</td>\n",
       "      <td>0.927052</td>\n",
       "      <td>0.900273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>codes38</th>\n",
       "      <td>36</td>\n",
       "      <td>0.339822</td>\n",
       "      <td>0.803928</td>\n",
       "      <td>0.893095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>codes48</th>\n",
       "      <td>48</td>\n",
       "      <td>0.337848</td>\n",
       "      <td>0.765192</td>\n",
       "      <td>0.946618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>codes49</th>\n",
       "      <td>49</td>\n",
       "      <td>0.337751</td>\n",
       "      <td>0.764032</td>\n",
       "      <td>0.952728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>codes5</th>\n",
       "      <td>5</td>\n",
       "      <td>0.341942</td>\n",
       "      <td>0.944133</td>\n",
       "      <td>0.819802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sic2</th>\n",
       "      <td>69</td>\n",
       "      <td>0.333970</td>\n",
       "      <td>0.755767</td>\n",
       "      <td>0.944701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sic3</th>\n",
       "      <td>236</td>\n",
       "      <td>0.294952</td>\n",
       "      <td>0.706283</td>\n",
       "      <td>0.959787</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         communities  modularity  coverage  performance\n",
       "bea1947           40    0.337511  0.791471     0.928649\n",
       "bea1963           58    0.331096  0.748338     0.950073\n",
       "bea1997           61    0.331030  0.748153     0.950577\n",
       "codes10           10    0.340272  0.938264     0.850497\n",
       "codes12           12    0.340412  0.931380     0.879861\n",
       "codes17           17    0.278554  0.737459     0.788439\n",
       "codes30           30    0.339191  0.927052     0.900273\n",
       "codes38           36    0.339822  0.803928     0.893095\n",
       "codes48           48    0.337848  0.765192     0.946618\n",
       "codes49           49    0.337751  0.764032     0.952728\n",
       "codes5             5    0.341942  0.944133     0.819802\n",
       "sic2              69    0.333970  0.755767     0.944701\n",
       "sic3             236    0.294952  0.706283     0.959787"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "modularity = {}   # to collect measurements of each scheme\n",
    "for scheme in sorted(chain(*codes.values())):\n",
    "    communities = nodes.loc[list(G.nodes), scheme]\\\n",
    "                       .reset_index()\\\n",
    "                       .groupby(scheme)['gvkey']\\\n",
    "                       .apply(list)\\\n",
    "                       .to_list()    # list of lists of node labels\n",
    "    modularity[scheme] = community_quality(G, communities)\n",
    "df = DataFrame.from_dict(modularity, orient='index').sort_index()\n",
    "print(f\"Quality of sectoring schemes on TNIC graph ({year})\")\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36733f6b",
   "metadata": {},
   "source": [
    "### Detecting partitions\n",
    "\n",
    "TODO\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "568616be",
   "metadata": {
    "lines_to_next_cell": 1
   },
   "outputs": [],
   "source": [
    "# Run community detection algorithms\n",
    "def community_detection(G):\n",
    "    \"\"\"Helper to run community detection algorithms on an undirected graph\"\"\"\n",
    "    out = {}\n",
    "    out['label'] = nx.community.label_propagation_communities(G)\n",
    "    out['louvain'] = nx.community.louvain_communities(G, resolution=1)\n",
    "    out['greedy'] = nx.community.greedy_modularity_communities(G, resolution=1)\n",
    "    return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e3d6d43b",
   "metadata": {},
   "outputs": [],
   "source": [
    "communities = community_detection(G)\n",
    "quality = {}\n",
    "for key, community in communities.items():\n",
    "    quality[key] = community_quality(G, community)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3a336afc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Modularity of community detection algorithms on TNIC graph (2021)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>communities</th>\n",
       "      <th>modularity</th>\n",
       "      <th>coverage</th>\n",
       "      <th>performance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>greedy</th>\n",
       "      <td>26</td>\n",
       "      <td>0.347560</td>\n",
       "      <td>0.982830</td>\n",
       "      <td>0.507290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>label</th>\n",
       "      <td>109</td>\n",
       "      <td>0.355460</td>\n",
       "      <td>0.990437</td>\n",
       "      <td>0.906120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>louvain</th>\n",
       "      <td>19</td>\n",
       "      <td>0.363978</td>\n",
       "      <td>0.835415</td>\n",
       "      <td>0.823403</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         communities  modularity  coverage  performance\n",
       "greedy            26    0.347560  0.982830     0.507290\n",
       "label            109    0.355460  0.990437     0.906120\n",
       "louvain           19    0.363978  0.835415     0.823403"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = DataFrame.from_dict(quality, orient='index').sort_index()\n",
    "print(f\"Modularity of community detection algorithms on TNIC graph ({year})\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "bcd03885",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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EtWvXUqdOHYORlaf18MHtgIAA4P9+r5ycnHL9vcot5kqVKqEoChUrVsTHx+ex5z9s6/Tp07m2lddRt2f9e3Xt2jVee+01dDod0dHR+k7Tf1WvXh0rKyuOHj1K165d9fn3798nNjbWIA8ejFIFBwfz559/snv3bqPpdyHUSp6REgUyfvx47Ozs6NevH1euXDE6np+RiK5du5KVlcWHH35odCwzM1P/Bz0gIAAnJydmzZpl8CbfQ1evXgUe/Iu4du3arFq1itTUVP3xXbt2cebMmRxj6NWrF2fOnGHcuHFYWlrSvXv3J8bt7u7OwIED2blzJ5999pnR8ezsbObOnctff/2FpaUlr732Gt9//73BaN2VK1dYt24dTZs21U8VqkGlSpXYv3+/Qd6XX3752BGpp2Fvbw/w2FXCg4KCeOmll5g9ezb79u0rlNGodevWsXz5cho3bsyrr74KQL169ahUqRJz5szJcbr64e9VbjF37twZS0tLpk2bZvS7rygK165dA6Bu3bpUrFiR+fPnG9Xx3/OedG8eepa/V+np6bz++uv8/fff/PTTT4+dxnR2dqZ169asWbPGYNp79erVpKWl0aVLF31eVlYW3bp149ChQ2zcuJHGjRsXSqxCPAsyIiUKxNvbm3Xr1tGjRw8qV66sX9lcURTi4+NZt24dFhYWeVrRu3nz5rz99tuEh4cTGxvLa6+9RrFixTh//jwbN25kwYIFvPHGGzg5ObF06VJ69epF3bp16d69O6VKlSIxMZEff/wRf39/Fi1aBEB4eDht27aladOm9OvXj+vXr/PZZ59RrVq1HP9Ytm3blpIlS7Jx40aCgoIe+7zWo+bOncvFixcZMWIEmzdvpl27dhQvXpzExEQ2btzI2bNn9Z2yGTNmsGvXLpo2bcqQIUOwsrLiiy++QKfT8fHHH+fj7he9AQMG8M477xASEkKbNm04ceIEO3bsKNRX0itVqoSLiwuff/45jo6O2Nvb07BhQypWrAg8eK6oe/fuLFq0CEtLS/3SA3n17bff4uDgoH+QfseOHRw8eJBatWqxceNGfTkLCwuWL19OUFAQ1apVo2/fvpQrV46///6bPXv24OTkxA8//AA86HQBvP/++3Tv3p1ixYoRHBxMpUqVmDFjBmFhYSQkJNCxY0ccHR2Jj4/nu+++Y9CgQbz77rtYWFiwdOlSgoODqV27Nn379sXNzY2zZ8/yxx9/sGPHDoN2RowYQUBAQK6d+2f1e9WzZ09iYmLo168fcXFxxMXF6Y85ODjQsWNH/eeZM2fSpEkTmjdvrl/ZfO7cubz22msEBgbqy40dO5atW7cSHBzM9evXWbNmjUGb/+08X758WT+a+HAZkxkzZgAPRqHzugyJEIXGNC8LiufNhQsXlMGDByteXl6KjY2NYmtrq1SpUkV55513lNjYWIOyDxfkfJwvv/xSqVevnmJra6s4OjoqNWrUUMaPH2+0cvqePXuUgIAAxdnZWbGxsVEqVaqkhIaGKkePHjUot2nTJsXX11fRarVK1apVjRbkfNSQIUMUQFm3bl2+7kFmZqayfPly5ZVXXlGcnZ2VYsWKKR4eHkrfvn2NlkY4fvy4EhAQoDg4OCh2dnZKy5YtlV9//dWgzMPX1I8cOWKQ/7jX+h+9r/9dkPO/Hi6CuXHjxie2l5WVpUyYMEG/aGNAQIBy4cKFxy5/8GisD9v671IFjy5/oCiK8v333ytVq1ZVrKysclwKISYmRgGU1157TcmrRxfOtLGxUV5++WWlXbt2ysqVKw2Wefiv33//XencubNSsmRJRavVKh4eHkrXrl0NXu1XlAev/JcrV06xsLAwWgph06ZNStOmTRV7e3vF3t5eqVKlijJ06FDl3LlzBnX88ssvSps2bfQLaNasWVP57LPP9MczMzOV4cOHK6VKlVI0Gk2eFuR82t+rnL6rnHh4eOS4UCiPLCny0IEDB5QmTZooNjY2SqlSpZShQ4cqt27dMijTvHnzx9b56J+pxy3iChj9XgnxLMhee0I8YvTo0axYsYKUlBTs7OxMHY4ATpw4Qe3atfnqq69kxEEIoSryjJQQ/3Hv3j3WrFlDSEiIdKJUZNmyZTg4ONC5c2dThyKEEAbkGSkheLBG1e7du/n222+5du0aI0eONHVIggdb9Jw5c4Yvv/ySYcOG6R++FkIItZCpPSGAvXv30rJlS0qXLs2kSZOees8xUbgqVKjAlStXCAgIYPXq1XlaPV4IIZ4l6UgJIYQQQjwleUZKCCGEEOIpSUdKCCGEEOIpycPmQgghhDBiWz5/i98+C3cT15s6BCPSkSpi5RfsM3UIuUoc2ZxsJeftUtTAQlMV+NPUYTyBDxJjYZAYC07t8YHEWFgev5ejeKBChQpcvnzZKH/IkCEsXryYe/fuMXbsWL7++mt0Oh0BAQEsWbKEMmXK5Kud53pqLzIyEhcXF1OHIYQQQohn7MiRIyQnJ+vTrl27APT7PI4ePZoffviBjRs3sm/fPv7555+nWqvOLDpSSUlJ9OvXj7Jly2JtbY2HhwcjR47UbwAKD3qe8+fPN12QQgghxHNEo7FQXcqPUqVK4erqqk9RUVFUqlSJ5s2bk5qayooVK/j0009p1aoV9erVIyIigl9//ZXDhw/nqx3Vd6QuXbqEn58f58+fZ/369Vy4cIHPP/+c6OhoGjduzPXr1595TBkZGc+8TSGEEOJFp9PpuHXrlkHS6XRPPO/+/fusWbOGfv36odFoOHbsGBkZGbRu3VpfpkqVKpQvX55Dhw7lKybVd6SGDh2KtbU1O3fupHnz5pQvX56goCB2797N33//zfvvv0+LFi24fPkyo0ePRqPRoNFoDOrYsWMHvr6+ODg4EBgYSHJyssHx5cuX4+vri42NDVWqVGHJkiX6YwkJCWg0GjZs2EDz5s2xsbFh7dq1z+TahRBCCPF/wsPDcXZ2Nkjh4eFPPG/Lli3cvHmT0NBQAFJSUrC2tjZ6/KdMmTKkpKTkKyZVP2x+/fp1duzYwcyZM7G1tTU45urqSs+ePdmwYQPnz5+ndu3aDBo0iIEDBxqUu3PnDnPmzGH16tVYWFjw1ltv8e677+o7Q2vXrmXy5MksWrSIOnXq8PvvvzNw4EDs7e3p06ePvp6JEycyd+5c6tSpg42NTdFfvBBCCGFCGhWOtYSFhTFmzBiDPK1W+8TzVqxYQVBQEGXLli30mFTdkTp//jyKouDr65vjcV9fX27cuEFWVhaWlpY4Ojri6upqUCYjI4PPP/+cSpUqATBs2DCmT5+uPz5lyhTmzp2rf8CsYsWKnDlzhi+++MKgIzVq1KhcH0LT6XRGw4t5+XKFEEIIkTdarTbff1svX77M7t272bx5sz7P1dWV+/fvc/PmTYNRqStXrhj1I55Efd3NHBRkFxs7Ozt9JwrAzc2Nf//9F4D09HQuXrxI//79cXBw0KcZM2Zw8eJFg3r8/PxybedphxuFEEIIUXQiIiIoXbo0bdu21efVq1ePYsWKER0drc87d+4ciYmJNG7cOF/1q3pEysvLC41GQ1xcHJ06dTI6HhcXR/HixSlVqtRj6yhWrJjBZ41Go++YpaWlAbBs2TIaNmxoUM7S0tLg85N2nX/ccOPKz/P39L8QQgihBvl9S06NsrOziYiIoE+fPlhZ/V+Xx9nZmf79+zNmzBhKlCiBk5MTw4cPp3HjxjRq1Chfbai6I1WyZEnatGnDkiVLGD16tMFzUikpKaxdu5bevXuj0WiwtrYmKysrX/WXKVOGsmXLcunSJXr27FmgWJ9muFEIIYQQRWf37t0kJibSr18/o2Pz5s3DwsKCkJAQgwU580v13c1FixbpL3D//v0kJSWxfft22rRpQ7ly5Zg5cybwYB2p/fv38/fff/O///0vz/VPmzaN8PBwFi5cyJ9//smpU6eIiIjg008/LapLEkIIIcQz8Nprr6EoCj4+xivB29jYsHjxYq5fv056ejqbN2/O9/NRYAYdKW9vb44ePYqnpyddu3alUqVKDBo0iJYtW3Lo0CFKlCgBwPTp00lISKBSpUq5TvU9asCAASxfvpyIiAhq1KhB8+bNiYyMpGLFikV1SUIIIYTqmXrxzYIuyPmsaJSCPMktnkj22isY2WuvsEiMhUPtMao9PpAYC0vR77XnWLFvkbeRX7fjI0wdghF1du+EEEIIIcyAjEgJIYQQwoiTp/ED2qZ269JKU4dgRNVv7T0P7mcfM3UIubK2qIe6h7B9uJN5wNRB5MrO6hXUfQ/BfKYqJMaCUXt8IDEWlqKf2hN5I1N7/19oaCgdO3Y0dRhCCCGEMCNm2ZE6dOgQlpaWBquUFtSCBQuIjIwstPqEEEII82ahwqQ+6ozqCVasWMHw4cPZv38///zzT4HqysrKIjs7G2dnZ6NdoIUQQgghcmN2Ham0tDQ2bNjA4MGDadu2rdEo0tatW/H29sbGxoaWLVuyatUqNBoNN2/eBCAyMhIXFxe2bt1K1apV0Wq1JCYmGk3tZWdn8/HHH+Pl5YVWq6V8+fL6xT+FEEKI552p14wyl3Wk1BlVLr755huqVKlC5cqVeeutt1i5cqV+77z4+HjeeOMNOnbsyIkTJ3j77bd5//33jeq4c+cOs2fPZvny5fzxxx+ULl3aqExYWBgfffQRkyZN4syZM6xbt44yZcoU+fUJIYQQwnyY3Vt7K1as4K233gIgMDCQ1NRU9u3bR4sWLfjiiy+oXLkyn3zyCQCVK1fm9OnTRiNJGRkZLFmyhFq1auXYxu3bt1mwYAGLFi2iT58+AFSqVImmTZs+Ni6dTodOpzPI02q1aIo95gQhhBBCmD2zGpE6d+4cMTEx9OjRAwArKyu6devGihUr9Mfr169vcE6DBg2M6rG2tqZmzZqPbScuLg6dTserr76a59jCw8NxdnY2SOHh4Xk+XwghhFATU0/jmcvUnlmNSK1YsYLMzEzKli2rz1MUBa1Wy6JFi/Jcj62tLRqNJtfj+RUWFsaYMWMM8rRaLXA633UJIYQQwjyos3uXg8zMTL766ivmzp1LbGysPp04cYKyZcuyfv16KleuzNGjRw3OO3LkSL7b8vb2xtbWlujo6Dyfo9VqcXJyMkgPOlJCCCGEeF6ZzYhUVFQUN27coH///jg7OxscCwkJYcWKFXzzzTd8+umnTJgwgf79+xMbG6t/qy+3EahH2djYMGHCBMaPH4+1tTX+/v5cvXqVP/74g/79+xfmZQkhhBCqpDGfsRaTMpu7tGLFClq3bm3UiYIHHamjR49y+/Ztvv32WzZv3kzNmjVZunSp/q29/I4OTZo0ibFjxzJ58mR8fX3p1q0b//77b6FcixBCCCGeD8/9psUzZ87k888/JykpySTty157BSV77RUOc9k7TGIsGLXHBxJjYSn6vfaKew0p8jby68aFJaYOwYjZTO3l1ZIlS6hfvz4lS5bk4MGDfPLJJwwbNszUYQkhhBBmRa1vyanNczciNXr0aDZs2MD169cpX748vXr1IiwsDCur567PKIQQQhSZEt7qG4S4fj7vb+g/K89dR0ptxsf8bOoQcvVxg1aoewjbh9M3okwdRK6qF2+Huu8hmM9UhcRYMD5kK2dMHUSuLDRVUfc9BPV/z/AspvakI5U3Zj1ul5CQgEajITY29rFl9u7da7DXnhBCCCGezNSLb5rLgpzqjOr/Cw0NRaPR6FPJkiUJDAzk5MmTT13nw45V8eLFuXfvnsGxI0eO6Nt66OEmx0IIIYQQj1J1Rwoe7KeXnJxMcnIy0dHRWFlZ0a5duwLX6+joyHfffWeQt2LFCsqXL1/guoUQQgjxYlB9R0qr1eLq6oqrqyu1a9dm4sSJJCUlcfXq1RzL//TTT/j4+GBra0vLli1JSEjIsVyfPn1YuXKl/vPdu3f5+uuv9ZsUw4PRq759+5KamqofqZo6dWphXp4QQgihSqaexpOpvSKQlpbGmjVr8PLyomTJkkbHk5KS6Ny5M8HBwcTGxjJgwAAmTpyYY129evXiwIEDJCYmArBp0yYqVKhA3bp19WWaNGnC/PnzcXJy0o+Kvfvuu0VzcUIIIYQwO6pfEyAqKgoHBwcA0tPTcXNzIyoqCgsL4z7g0qVLqVSpEnPnzgWgcuXKnDp1itmzZxuVLV26NEFBQURGRjJ58mRWrlxJv379DMpYW1vj7OyMRqPB1dU11zh1Oh06nc4gT/baE0IIIZ5vqh+RatmypX6D4piYGAICAggKCuLy5ctGZePi4mjYsKFBXuPGjR9bd79+/YiMjOTSpUscOnSInj17PnWc4eHhODs7G6Tw8PCnrk8IIYQwJY0K/6dGqu9I2dvb4+XlhZeXF/Xr12f58uWkp6ezbNmyAtcdFBTE3bt36d+/P8HBwTlOF+ZVWFgYqampBiksLKzAMQohhBBCvVQ/tfcojUaDhYUFd+/eNTrm6+vL1q1bDfIOHz782LqsrKzo3bs3H3/8Mdu2bcuxjLW1NVlZWU+MS6vVylSeEEKI54ZaH+5WG9XfJZ1OR0pKCikpKcTFxTF8+HDS0tIIDg42KvvOO+9w/vx5xo0bx7lz51i3bh2RkZG51v/hhx9y9epVAgICcjxeoUIF0tLSiI6O5n//+x937twpjMsSQgghxHNA9R2p7du34+bmhpubGw0bNuTIkSNs3LiRFi1aGJUtX748mzZtYsuWLdSqVYvPP/+cWbNm5Vq/tbU1L730ksEinP/VpEkT3nnnHbp160apUqX4+OOPC+OyhBBCCPEckL32ipjstVdQstde4TCXvcMkxoKRvfYKh9q/Z3gWe+2V8R1X5G3k15W4T0wdghHVj0gJIYQQQqiVjEgJIYQQwoiMSOWN2b21Z25kWqqgzGWIXWIsOImx4NQeH0iMhaXop/bkrb28kbskhBBCCPGUzLoj9XAj4ccl2WBYCCGEEEXJrKf2kpOT9T9v2LCByZMnc+7cOX3ewz36hBBCCJFfZj3W8syY9V1ydXXVp/9uLuzq6krp0qX59NNPefnll9FqtdSuXZvt27frz23VqhXDhg0zqO/q1atYW1sTHR0NwJIlS/D29sbGxoYyZcrwxhtvPNPrE0IIIYS6mXVHKjcLFixg7ty5zJkzh5MnTxIQEED79u05f/48AAMGDGDdunXodDr9OWvWrKFcuXK0atWKo0ePMmLECKZPn865c+fYvn07zZo1M9XlCCGEEEKFntuO1Jw5c5gwYQLdu3encuXKzJ49m9q1azN//nwAOnfuDMD333+vPycyMpLQ0FA0Gg2JiYnY29vTrl07PDw8qFOnDiNGjHhsezqdjlu3bhmk/3bShBBCCHOi0VioLqmROqMqoFu3bvHPP//g7+9vkO/v709cXBwANjY29OrVi5UrVwJw/PhxTp8+TWhoKABt2rTBw8MDT09PevXqxdq1a3PdZy88PBxnZ2eDFB4eXjQXKIQQQghVeC47Unk1YMAAdu3axV9//UVERAStWrXCw8MDAEdHR44fP8769etxc3Nj8uTJ1KpVi5s3b+ZYV1hYGKmpqQYpLCzsGV6NEEIIIZ6157Ij5eTkRNmyZTl48KBB/sGDB6latar+c40aNfDz82PZsmWsW7eOfv36GZS3srKidevWfPzxx5w8eZKEhAR+/jnnvfO0Wi1OTk4GSavVFv7FCSGEEM+AqafxzGVqz6yXP8jNuHHjmDJlCpUqVaJ27dpEREQQGxvL2rVrDcoNGDCAYcOGYW9vT6dOnfT5UVFRXLp0iWbNmlG8eHF++uknsrOzqVy58rO+FCGEEEKo1HPbkRoxYgSpqamMHTuWf//9l6pVq7J161a8vb0NyvXo0YNRo0bRo0cPbGxs9PkuLi5s3ryZqVOncu/ePby9vVm/fj3VqlV71pcihBBCCJV64TctTkhIoFKlShw5coS6desWev2y115BmcueVxJjwUmMBaf2+EBiLCxFv9deuepTiryN/Pr79DRTh2DkuR2RepKMjAyuXbvGBx98QKNGjYqkEyWEEEKI59sL25E6ePAgLVu2xMfHh2+//bbI2nkw4qN2Rf8vm4JRe3wgMRYWibHg1B4fSIziefLCdqRatGjBs5jVPHL1xyJvoyDql2qLuoewzWWIXWIsOImx4NQeH0iMhaXoO3pqfUtObZ6Lu9SiRQtGjRpl6jCEEEII8YJRbUfq4VYt77zzjtGxoUOHotFo9KuQb968mQ8//PAZRyiEEEI8vzQajeqSGqm2IwXg7u7O119/zd27d/V59+7dY926dZQvX16fV6JECRwdHU0RohBCCCFeYKruSNWtWxd3d3c2b96sz9u8eTPly5enTp06+rxHp/YqVKjArFmz6NevH46OjpQvX54vv/zSoO6kpCS6du2Ki4sLJUqUoEOHDiQkJOiP7927lwYNGmBvb4+Liwv+/v5cvny5yK5VCCGEEOZH1R0pgH79+hEREaH/vHLlSvr27fvE8+bOnYufnx+///47Q4YMYfDgwZw7dw54sPRBQEAAjo6OHDhwgIMHD+Lg4EBgYCD3798nMzOTjh070rx5c06ePMmhQ4cYNGiQaocVhRBCiMJm6u1gZIuYQvLWW28RFhamHw06ePAgX3/9NXv37s31vNdff50hQ4YAMGHCBObNm8eePXuoXLkyGzZsIDs7m+XLl+s7RxEREbi4uLB37178/PxITU2lXbt2VKpUCQBfX99c29PpdOh0OoM82WtPCCGEeL6ps3v3H6VKlaJt27ZERkYSERFB27Zteemll554Xs2aNfU/azQaXF1d+ffffwE4ceIEFy5cwNHREQcHBxwcHChRogT37t3j4sWLlChRgtDQUAICAggODmbBggUkJyfn2l54eDjOzs4GKTw8vGAXL4QQQghVU/2IFDyY3hs2bBgAixcvztM5xYoVM/is0WjIzs4GIC0tjXr16hltYAwPOm7wYIRqxIgRbN++nQ0bNvDBBx+wa9cuGjVqlGN7YWFhjBkzxiBPq9Vy8tbuPMUrhBBCqIlG/WMtqmAWHamHzy5pNBoCAgIKXF/dunXZsGEDpUuXxsnJ6bHl6tSpQ506dQgLC6Nx48asW7fusR0prVYrU3lCCCHEC8YsupuWlpbExcVx5swZLC0tC1xfz549eemll+jQoQMHDhwgPj6evXv3MmLECP766y/i4+MJCwvj0KFDXL58mZ07d3L+/PknPiclhBBCiBeLWYxIAbmOHOWXnZ0d+/fvZ8KECXTu3Jnbt29Trlw5Xn31VZycnLh79y5nz55l1apVXLt2DTc3N4YOHcrbb79daDEIIYQQaqbWt+TURqM8iw3nXmCy115BmcueVxJjwUmMBaf2+EBiLCxFv9dehdofFXkb+ZUQO9HUIRiR7qYQQgghxFOSESkhhBBCGKlY52NTh2Ak/vfxpg7BiNk8I2Wu/kr/wdQh5Opl+2DUPYRtLkPsEmPBSYwFp/b4QGIsLEU/tSfyRqb2gKlTp1K7du1cy4SGhtKxY8dnEo8QQgghzIPZd6RSUlIYOXIkXl5e2NjYUKZMGfz9/Vm6dCl37twxdXhCCCGEWdJgobqkRmY9tXfp0iX8/f1xcXFh1qxZ1KhRA61Wy6lTp/jyyy8pV64c7du3N3WYQgghhHhOmXVHasiQIVhZWXH06FHs7e31+Z6ennTo0IGHz9EnJiYyfPhwoqOjsbCwIDAwkM8++4wyZcrkWG9WVhbjxo1j5cqVWFpa0r9/f+SZfCGEEEI8Sp3jZHlw7do1du7cydChQw06Uf/1cH+9Dh06cP36dfbt28euXbu4dOkS3bp1e2zdc+fOJTIykpUrV/LLL79w/fp1vvvuu6K6FCGEEEJ9NBbqSypktiNSFy5cQFEUKleubJD/0ksvce/ePQCGDh1K69atOXXqFPHx8bi7uwPw1VdfUa1aNY4cOUL9+vWN6p4/fz5hYWF07twZgM8//5wdO3bkGo9Op0On0xnkyd57QgghxPNNnd27AoiJiSE2NpZq1aqh0+mIi4vD3d1d34kCqFq1Ki4uLsTFxRmdn5qaSnJyMg0bNtTnWVlZ4efnl2u74eHhODs7G6Tw8PDCuzAhhBBCqI7Zjkh5eXmh0Wg4d+6cQb6npycAtra2zzSesLAwxowZY5Cn1Wq5mrnzmcYhhBBCFAbZay9vzPYulSxZkjZt2rBo0SLS09MfW87X15ekpCSSkpL0eWfOnOHmzZtUrVrVqLyzszNubm789ttv+rzMzEyOHTuWazxarRYnJyeDJFN7QgghxPPNbDtSAEuWLCEzMxM/Pz82bNhAXFwc586dY82aNZw9exZLS0tat25NjRo16NmzJ8ePHycmJobevXvTvHnzx07XjRw5ko8++ogtW7Zw9uxZhgwZws2bN5/txQkhhBAmpNFoVJfUyGyn9gAqVarE77//zqxZswgLC+Ovv/5Cq9VStWpV3n33XYYMGYJGo+H7779n+PDhNGvWzGD5g8cZO3YsycnJ9OnTBwsLC/r160enTp1ITU19hlcnhBBCCLWTTYuLmOy1V1DmsueVxFhwEmPBqT0+kBgLS9Hvteflt6DI28ivC0dHmjoEI2Y9IiWEEEKIoqHWLVnURkakhBBCCGHE2+/xj8CYyvmjw00dghEZkSpiaRl7TR1CrhyKtUDdQ9jmMsQuMRacxFhwao8PJMbCUvRTeyJvZNwujypUqMD8+fNNHYYQQgjxTGg0FqpLaqTOqPIpJSWF4cOH4+npiVarxd3dneDgYKKjo00dmhBCCCGeY2Y/tZeQkIC/vz8uLi588skn1KhRg4yMDHbs2MHQoUM5e/asqUMUQgghxHPK7EekHq4VFRMTQ0hICD4+PlSrVo0xY8Zw+PBhABITE+nQoQMODg44OTnRtWtXrly5oq/j4sWLdOjQgTJlyuDg4ED9+vXZvXu3qS5JCCGEMD2NRn1Jhcy6I3X9+nW2b9/O0KFDsbe3Nzru4uJCdnY2HTp04Pr16+zbt49du3Zx6dIlunXrpi+XlpbG66+/TnR0NL///juBgYEEBweTmJj4LC9HCCGEEGbGrKf2Lly4gKIoVKlS5bFloqOjOXXqFPHx8bi7uwPw1VdfUa1aNY4cOUL9+vWpVasWtWrV0p/z4Ycf8t1337F161aGDRuWp1h0Oh06nc4gT6vVmnlXVQghhBC5Mes/83lZAisuLg53d3d9JwqgatWquLi4EBcXBzwYkXr33Xfx9fXFxcUFBwcH4uLi8jUiFR4ejrOzs0EKDw/P/0UJIYQQamChwqRCZj0i5e3tjUajKfAD5e+++y67du1izpw5eHl5YWtryxtvvMH9+/fzXEdYWBhjxowxyNNqtWRwqECxCSGEEEK9VNq/y5sSJUoQEBDA4sWLSU9PNzp+8+ZNfH19SUpKIikpSZ9/5swZbt68SdWqVQE4ePAgoaGhdOrUiRo1auDq6kpCQkK+YtFqtTg5ORkkrVZboOsTQgghhLqZdUcKYPHixWRlZdGgQQM2bdrE+fPniYuLY+HChTRu3JjWrVtTo0YNevbsyfHjx4mJiaF37940b94cPz8/4MHI1ubNm4mNjeXEiRO8+eabZGdnm/jKhBBCCBMy9Rt68tbes+Hp6cnx48dp2bIlY8eOpXr16rRp04bo6GiWLl2KRqPh+++/p3jx4jRr1ozWrVvj6enJhg0b9HV8+umnFC9enCZNmhAcHExAQAB169Y14VUJIYQQwhzIpsVFTPbaKyhz2fNKYiw4ibHg1B4fSIyFpej32vNpvLTI28ivPw8NNnUIRsz6YXMhhBBCFBGVTqWpjYxICSGEEMKIT5PPTR2CkT9/fSdf5f/++28mTJjAtm3buHPnDl5eXkREROifkVYUhSlTprBs2TJu3ryJv78/S5cuxdvbO89tyIhUEbMt38PUIeTqbuJ61D2EbS5D7BJjwUmMBaf2+EBiLCxFP7Vn7k9R37hxA39/f1q2bMm2bdsoVaoU58+fp3jx4voyH3/8MQsXLmTVqlVUrFiRSZMmERAQwJkzZ7CxsclTO2Z+m4pOhQoVmD9/vv6zRqNhy5YtJotHCCGEEHk3e/Zs3N3diYiIoEGDBlSsWJHXXnuNSpUqAQ9Go+bPn88HH3xAhw4dqFmzJl999RX//PNPvv7ev5AdqaSkJPr160fZsmWxtrbGw8ODkSNHcu3aNX2ZI0eOMGjQIBNGKYQQQoj/0ul03Lp1yyA9uj3bQ1u3bsXPz48uXbpQunRp6tSpw7Jly/TH4+PjSUlJoXXr1vo8Z2dnGjZsyKFDeV9M+4XrSF26dAk/Pz/Onz/P+vXruXDhAp9//jnR0dE0btyY69evA1CqVCns7OxMHK0QQghhGopGo7qUn+3YLl26pH/eaceOHQwePJgRI0awatUqAFJSUgAoU6aMwXllypTRH8uLF+4ZqaFDh2Jtbc3OnTuxtbUFoHz58tSpU4dKlSrx/vvvs3TpUipUqMCoUaMYNWqUaQMWQgghBPD47dhykp2djZ+fH7NmzQKgTp06nD59ms8//5w+ffoUWkwv1IjU9evX2bFjB0OGDNF3oh5ydXWlZ8+ebNiwIU+bIQshhBDi2crPdmxubm76reAe8vX1JTExEXjwdx/gypUrBmWuXLmiP5YXL1RH6vz58yiKgq+vb47HfX19uXHjBlevXs133fmZtxVCCCFUT6PClA/+/v6cO3fOIO/PP//Ew8MDgIoVK+Lq6kp0dLT++K1bt/jtt99o3Lhxntt5oTpSDxXFiFN+5m2FEEIIUbRGjx7N4cOHmTVrFhcuXGDdunV8+eWXDB06FHjwNv6oUaOYMWMGW7du5dSpU/Tu3ZuyZcvSsWPHPLfzQnWkvLy80Gg0xMXF5Xg8Li6O4sWLU6pUqXzXHRYWRmpqqkEKCwsraMhCCCGEeAr169fnu+++Y/369VSvXp0PP/yQ+fPn07NnT32Z8ePHM3z4cAYNGkT9+vVJS0tj+/bteV5DCl6wh81LlixJmzZtWLJkCaNHjzZ4TiolJYW1a9fSu3dvNE+xLL5Wq33sPK0QQghhdizMf4uYdu3a0a5du8ce12g0TJ8+nenTpz91Gy/UiBTAokWL0Ol0BAQEsH//fpKSkti+fTtt2rShXLlyzJw509QhCiGEEMJMvHAdKW9vb44ePYqnpyddu3alUqVKDBo0iJYtW3Lo0CFKlChh6hCFEEIIYSZeqKm9hzw8PIiMjMy1TEJCgsFnWRJBCCHEC+UpHnN5Eb1wI1JCCCGEEIVFo8hQixBCCCEe4d1y2ZMLPWPn9ww0dQhGXsipvWep7c5fTB1Crn58rSnwp6nDyIUPmdknTB1ErqwsanE/+5ipw8iVtUU91P09A/ggMRaU2uMDibGw+BR9EzKzlycytSeEEEII8ZTMqiOVkpLC8OHD8fT0RKvV4u7uTnBwsMHy7k8rISEBjUZDbGxswQMVQgghxAvBbKb2EhIS8Pf3x8XFhU8++YQaNWqQkZHBjh07GDp0KGfPnn0mcdy/fx9ra+tn0pYQQghhMs/BgpzPgtmMSA0ZMgSNRkNMTAwhISH4+PhQrVo1xowZw+HDh4EHK5QuX76cTp06YWdnh7e3N1u3btXXcePGDXr27EmpUqWwtbXF29ubiIgI4MHmhQB16tRBo9HQokULAEJDQ+nYsSMzZ86kbNmyVK5c+dleuBBCCCFUyyxGpK5fv8727duZOXMm9vb2RsddXFz0P0+bNo2PP/6YTz75hM8++4yePXty+fJlSpQowaRJkzhz5gzbtm3jpZde4sKFC9y9exeAmJgYGjRowO7du6lWrZrBqFN0dDROTk7s2rWryK9VCCGEEObDLDpSFy5cQFEUqlSp8sSyoaGh9OjRA4BZs2axcOFCYmJiCAwMJDExkTp16uDn5wdAhQoV9Oc93Ki4ZMmSuLq6GtRpb2/P8uXLc53S0+l06HQ6gzzZe08IIYTZkgU588Qspvbys9RVzZo19T/b29vj5OTEv//+C8DgwYP5+uuvqV27NuPHj+fXX3/NU501atR44nNR4eHhODs7G6Tw8PA8xy2EEEII82MWHSlvb280Gk2eHigvVqyYwWeNRkN2djYAQUFBXL58mdGjR/PPP//w6quv8u677z6xzpymEx8VFhZGamqqQQoLC3vieUIIIYQqaVSYVMgsOlIlSpQgICCAxYsXk56ebnT85s2bea6rVKlS9OnThzVr1jB//ny+/PJLAP2IU1ZW1lPFqNVqcXJyMkgytSeEEEI838yiIwWwePFisrKyaNCgAZs2beL8+fPExcWxcOFCGjdunKc6Jk+ezPfff8+FCxf4448/iIqKwtfXF4DSpUtja2vL9u3buXLlCqmpqUV5OUIIIYR4DphNR8rT05Pjx4/TsmVLxo4dS/Xq1WnTpg3R0dEsXbo0T3VYW1sTFhZGzZo1adasGZaWlnz99dcAWFlZsXDhQr744gvKli1Lhw4divJyhBBCCHWz0KgvqZBsWlzEZK+9gpK99gqD7LVXWNQeo9rjA4mxsBT9XnvegSuLvI38Or+9n6lDMGI2I1JCCCGEEGojI1JCCCGEMOIdpMIRqW3qG5EyiwU5zdmVu1ufXMiEyti2R91D2D4cufqjqYPIVf1SbVH3PQTzmapQf4zZyhlTB/FYFpqqmMM9lBgLQ9FP7Ym8kam9PNi7dy8ajSZfyywIIYQQ4vlnlh2p0NBQNBqNUbpw4YKpQxNCCCGeC4pGo7qkRmY7tRcYGEhERIRB3sP98oQQQgghngWzHJGCByuJu7q6GiRLS0v27dtHgwYN0Gq1uLm5MXHiRDIzM/Xn6XQ6RowYQenSpbGxsaFp06YcOXLEoO6ffvoJHx8fbG1tadmyJQkJCc/46oQQQghhDsy2I5WTv//+m9dff5369etz4sQJli5dyooVK5gxY4a+zPjx49m0aROrVq3i+PHjeHl5ERAQwPXr1wFISkqic+fOBAcHExsby4ABA5g4caKpLkkIIYQwDVMvvmkmC3Ka7dReVFQUDg4O+s9BQUH4+Pjg7u7OokWL0Gg0VKlShX/++YcJEyYwefJk7t69y9KlS4mMjCQoKAiAZcuWsWvXLlasWMG4ceNYunQplSpVYu7cuQBUrlyZU6dOMXv27Fzj0el06HQ6gzzZa08IIYR4vpntiFTLli2JjY3Vp4ULFxIXF0fjxo3R/OeBNH9/f9LS0vjrr7+4ePEiGRkZ+Pv7648XK1aMBg0aEBcXB0BcXBwNGzY0aCsve/mFh4fj7OxskMLDwwvpaoUQQgihRmY7ImVvb4+Xl5epw9ALCwtjzJgxBnlarZab2TtMFJEQQghRAOqcSVMdsx2Ryomvry+HDh3iv4u1Hzx4EEdHR15++WUqVaqEtbU1Bw8e1B/PyMjgyJEjVK1aVV9HTEyMQb2HDx9+YttarRYnJyeDJFN7QgghxPPtuepIDRkyhKSkJIYPH87Zs2f5/vvvmTJlCmPGjMHCwgJ7e3sGDx7MuHHj2L59O2fOnGHgwIHcuXOH/v37A/DOO+9w/vx5xo0bx7lz51i3bh2RkZGmvTAhhBBCqJLZTu3lpFy5cvz000+MGzeOWrVqUaJECfr3788HH3ygL/PRRx+RnZ1Nr169uH37Nn5+fuzYsYPixYsDUL58eTZt2sTo0aP57LPPaNCgAbNmzaJfP/Xt7yOEEEIUGZUugKk2smlxEZO99gpK9torHOayd5j6Y5S99grKPL5n84ixaHm1X1XkbeTXha19TB2Ckedqak8IIYQQ4lmSESkhhBBCGPHq+JWpQzByYUtvU4dg5Ll6RkqNVl9Q9/IHvbwCyMw+YeowHsvKohbmMMSu5ukekCmfwqPu71q+58JiLjEKNXjup/b27t2LRqPh5s2bjy0zdepUateunWs9oaGhdOzYsVBjE0IIIVRLo8KkQqrvSD2uA5OXDpIQQgghRFFSfUdKCCGEEEKtnouO1OXLlwkODqZ48eLY29tTrVo1fvrpJ4Myx44dw8/PDzs7O5o0acK5c+ceW19WVhZjxozBxcWFkiVLMn78eOSZfCGEEC8UjUZ9SYWei47U0KFD0el07N+/n1OnTjF79mwcHBwMyrz//vvMnTuXo0ePYmVllesCm3PnziUyMpKVK1fyyy+/cP36db777ruivgwhhBBCmBmzeGsvKirKqGOUlZWl/zkxMZGQkBBq1KgBgKenp1EdM2fOpHnz5gBMnDiRtm3bcu/ePWxsbIzKzp8/n7CwMDp37gzA559/zo4dub99p9Pp0Ol0Bnmy154QQgjxfDOLEamWLVsSGxtrkJYvX64/PmLECGbMmIG/vz9Tpkzh5MmTRnXUrFlT/7ObmxsA//77r1G51NRUkpOTadiwoT7PysoKPz+/XGMMDw/H2dnZIIWHh+f7WoUQQghVMPU0nkztFR57e3u8vLwMUrly5fTHBwwYwKVLl+jVqxenTp3Cz8+Pzz77zKCOYsWK6X/W/P8vIzs7u9BiDAsLIzU11SCFhYUVWv1CCCGEUB+z6Ejlhbu7O++88w6bN29m7NixLFu27KnqcXZ2xs3Njd9++02fl5mZybFjx3I9T6vV4uTkZJBkak8IIYR4vpnFM1JPMmrUKIKCgvDx8eHGjRvs2bMHX1/fp65v5MiRfPTRR3h7e1OlShU+/fRTWa9KCCHEi+W5GWopWs9FRyorK4uhQ4fy119/4eTkRGBgIPPmzXvq+saOHUtycjJ9+vTBwsKCfv360alTJ1JTUwsxaiGEEEKYO9m0uIjJXnsFI3vtFQ7Zg62wqPu7lu+5sJhLjEXLq8uaIm8jvy5sfMvUIRh5LkakhBBCCFHIVPqWnNrIiJQQQgghjHh1XWvqEIxc+KanqUMwIiNSRc4chofVHKMPV+5uNXUQuSpj2x5130NQ//cMEmNhUHt8IDEWlqKf2hN5I8/kA1OnTqV27dqmDkMIIYRQD40KkwqZXUfq6tWrDB48mPLly6PVanF1dSUgIICDBw+aOjQhhBBCvGDMbmovJCSE+/fvs2rVKjw9Pbly5QrR0dFcu3bN1KEJIYQQ4gVjViNSN2/e5MCBA8yePZuWLVvi4eFBgwYNCAsLo3379sCDDYw7dOiAg4MDTk5OdO3alStXrhjU89FHH1GmTBkcHR3p378/9+7dMzh+5MgR2rRpw0svvYSzszPNmzfn+PHjz+w6hRBCCFNTLDSqS2pkVh0pBwcHHBwc2LJlCzqdzuh4dnY2HTp04Pr16+zbt49du3Zx6dIlunXrpi/zzTffMHXqVGbNmsXRo0dxc3NjyZIlBvXcvn2bPn368Msvv3D48GG8vb15/fXXuX37dpFfoxBCCCHMh9ktf7Bp0yYGDhzI3bt3qVu3Ls2bN6d79+7UrFmTXbt2ERQURHx8PO7u7gCcOXOGatWqERMTQ/369WnSpAl16tRh8eLF+jobNWrEvXv3iI2NzbHN7OxsXFxcWLduHe3atcuxjE6nM+rcabVatNrLhXPhRUbtb6fIW3uFQ+3fM0iMhUHt8YHEWFiK/q29Sm+uL/I28uviuh6mDsGIWY1IwYNnpP755x+2bt1KYGAge/fupW7dukRGRhIXF4e7u7u+EwVQtWpVXFxciIuLAyAuLo6GDRsa1Nm4cWODz1euXGHgwIF4e3vj7OyMk5MTaWlpJCYmPjau8PBwnJ2dDVJ4eHghXrkQQggh1MbsOlIANjY2tGnThkmTJvHrr78SGhrKlClTCq3+Pn36EBsby4IFC/j111+JjY2lZMmS3L9//7HnhIWFkZqaapDCwsIKLSYhhBBCqI9ZdqQeVbVqVdLT0/H19SUpKYmkpCT9sTNnznDz5k2qVq0KgK+vL7/99pvB+YcPHzb4fPDgQUaMGMHrr79OtWrV0Gq1/O9//8s1Bq1Wi5OTk0HSarWFdIVCCCHEM2bqNaPMZB0ps1r+4Nq1a3Tp0oV+/fpRs2ZNHB0dOXr0KB9//DEdOnSgdevW1KhRg549ezJ//nwyMzMZMmQIzZs3x8/PD4CRI0cSGhqKn58f/v7+rF27lj/++ANPT099O97e3qxevRo/Pz9u3brFuHHjsLW1NdVlCyGEEEKlzGpEysHBgYYNGzJv3jyaNWtG9erVmTRpEgMHDmTRokVoNBq+//57ihcvTrNmzWjdujWenp5s2LBBX0e3bt2YNGkS48ePp169ely+fJnBgwcbtLNixQpu3LhB3bp16dWrFyNGjKB06dLP+nKFEEIIoXJm99ae+TGHNz/UHKO8tVc41P49g8RYGNQeH0iMheUZvLXX6+sibyO/Lq7ubuoQjJjViJQQQgghhJrIiJQQQgghjMiIVN6Y1cPm5igz+4SpQ8iVlUUt1D2ELVN7hcNcpiokxoJRe3wgMRaWop/aQ6PS1+RURqb2hBBCCCGektl2pEJDQ9FoNPpUsmRJAgMDOXnypKlDE0IIIcQLwmw7UgCBgYEkJyeTnJxMdHQ0VlZWj90Lr7BkZGQUaf1CCCGEKph68U0zWZDTrDtSWq0WV1dXXF1dqV27NhMnTiQpKYmrV68CkJSURNeuXXFxcaFEiRJ06NCBhIQEgzqWL1+Or68vNjY2VKlShSVLluiPJSQkoNFo2LBhA82bN8fGxoa1a9c+y0sUQgghhIqZdUfqv9LS0lizZg1eXl6ULFmSjIwMAgICcHR05MCBAxw8eBAHBwcCAwP1e+atXbuWyZMnM3PmTOLi4pg1axaTJk1i1apVBnVPnDiRkSNHEhcXR0BAgCkuTwghhBAqZNZv7UVFReHg4ABAeno6bm5uREVFYWFhwbp168jOzmb58uVo/v+bBxEREbi4uLB3715ee+01pkyZwty5c+ncuTMAFStW5MyZM3zxxRf06dNH386oUaP0ZR5Hp9Oh0+kM8rRaLZbFCvOKhRBCiGfEQqVzaSpj1iNSLVu2JDY2ltjYWGJiYggICCAoKIjLly9z4sQJLly4gKOjIw4ODjg4OFCiRAnu3bvHxYsXSU9P5+LFi/Tv319/3MHBgRkzZnDx4kWDdh7u05eb8PBwnJ2dDVJ4eHhRXboQQgghVMCsR6Ts7e3x8vLSf16+fDnOzs4sW7aMtLQ06tWrl+MzTaVKlSItLQ2AZcuW0bBhQ4PjlpaWRu08SVhYGGPGjDHI02q1wNm8Xo4QQgghzIxZd6QepdFosLCw4O7du9StW5cNGzZQunRpnJycjMo6OztTtmxZLl26RM+ePQvctlar/f8dJ0OZ2QWuWgghhHj2ZGovT8y6I6XT6UhJSQHgxo0bLFq0iLS0NIKDg2nQoAGffPIJHTp0YPr06bz88stcvnyZzZs3M378eF5++WWmTZvGiBEjcHZ2JjAwEJ1Ox9GjR7lx44bR6JIQQgghxKPMuiO1fft23NzcAHB0dKRKlSps3LiRFi1aALB//34mTJhA586duX37NuXKlePVV1/Vj1ANGDAAOzs7PvnkE8aNG4e9vT01atRg1KhRJroiIYQQQpgT2bS4iMleewUle+0VDnPZO0xiLBi1xwcSY2Ep+r32PAdsLPI28uvS8i6mDsGIWb+1J4QQQghhSjIiJYQQQggjnoO+NXUIRi59+YapQzBi1s9ImYNs5YypQ8iVhaYq6h7C9pF7WCjMZapCYiwYtccHEmNhKfqpPZE3L+zUnkajYcuWLaYOQwghhBBmzOQdqatXrzJ48GDKly+v34Q4ICCAgwcPmjo0IYQQ4sWl0agvqZDJp/ZCQkK4f/8+q1atwtPTkytXrhAdHc21a9dMHZoQQgghRK5MOiJ18+ZNDhw4wOzZs2nZsiUeHh40aNCAsLAw2rdvDzyYgvviiy9o164ddnZ2+Pr6cujQIS5cuECLFi2wt7enSZMmRvvjLV26lEqVKmFtbU3lypVZvXp1rrFMmTIFNzc3Tp48CcAvv/zCK6+8gq2tLe7u7owYMYL09PSiuRFCCCGEMEsm7Ug93Ch4y5Yt6HS6x5b78MMP6d27N7GxsVSpUoU333yTt99+m7CwMI4ePYqiKAwbNkxf/rvvvmPkyJGMHTuW06dP8/bbb9O3b1/27NljVLeiKAwfPpyvvvqKAwcOULNmTS5evEhgYCAhISGcPHmSDRs28Msvvxi0IYQQQjzXLDTqSypk8uUPNm3axMCBA/X74zVv3pzu3btTs2bNBwFqNHzwwQd8+OGHABw+fJjGjRuzYsUK+vXrB8DXX39N3759uXv3LgD+/v5Uq1aNL7/8Ut9O165dSU9P58cff9TXu3HjRr777jt+//13du3aRbly5YAHK55bWlryxRdf6M//5ZdfaN68Oenp6djY2Bhdh06nM+oMarVaillfNCqrJup/40ze2isc5vIWksRYMGqPDyTGwvIMFuQcvLnI28ivS0s7mzoEIyZ/2DwkJIR//vmHrVu3EhgYyN69e6lbty6RkZH6Mg87VQBlypQBoEaNGgZ59+7d49atWwDExcXh7+9v0I6/vz9xcXEGeaNHj+a3335j//79+k4UwIkTJ4iMjNSPmDk4OBAQEEB2djbx8fE5Xkd4eDjOzs4GKTw8/OluihBCCCHMgsk7UgA2Nja0adOGSZMm8euvvxIaGsqUKVP0x4sVK6b/WfP/n9rPKS87Oztf7bZp04a///6bHTt2GOSnpaXx9ttvExsbq08nTpzg/PnzVKpUKce6wsLCSE1NNUhhYWH5ikcIIYRQDQsVJhUy+Vt7OalatWqB1njy9fXl4MGD9OnTR5938OBBqlatalCuffv2BAcH8+abb2JpaUn37t0BqFu3LmfOnMHLyyvPbWq1WrRarVF+tqwbL4QQQjy3TNqRunbtGl26dKFfv37UrFkTR0dHjh49yscff0yHDh2eut5x48bRtWtX6tSpQ+vWrfnhhx/YvHkzu3fvNirbqVMnVq9eTa9evbCysuKNN95gwoQJNGrUiGHDhjFgwADs7e05c+YMu3btYtGiRQW5ZCGEEEI8R0zakXJwcKBhw4bMmzePixcvkpGRgbu7OwMHDuS999576no7duzIggULmDNnDiNHjqRixYpERETQokWLHMu/8cYbZGdn06tXLywsLOjcuTP79u3j/fff55VXXkFRFCpVqkS3bt2eOiYhhBDCrKh0AUy1Mflbe887eeOsoOStvcJhLm8hSYwFo/b4QGIsLM/grb1h3xV5G/l1aVEnU4dgRKWPbgkhhBBCqJ8qHzZ/njwYrVA7de8iLvewsEiMhUPtMao9PpAYzYRKF8DMq6lTpzJt2jSDvMqVK3P27FkA7t27x9ixY/n666/R6XQEBASwZMkS/TJLeSUdqSJ2P/uYqUPIlbVFPdQ9hO0j97BQmMtUhcRYMGqPDyTGwiIdvbyoVq2awYtmVlb/1+0ZPXo0P/74Ixs3bsTZ2Zlhw4bRuXNnDh48mK82pCP1H1OnTmXLli3ExsaaOhQhhBBCPOJxu4jktPwQPOg4ubq6GuWnpqayYsUK1q1bR6tWrQCIiIjA19eXw4cP06hRozzHZHbPSGk0mlzT1KlT81xPQdaqEkIIIZ5nikajupTfXUTOnz9P2bJl8fT0pGfPniQmJgJw7NgxMjIyaN26tb5slSpVKF++PIcOHcrXfTK7Eank5GT9zxs2bGDy5MmcO3dOn+fg4GCKsIQQQghRxMLCwhgzZoxB3uNGoxo2bEhkZCSVK1cmOTmZadOm8corr3D69GlSUlKwtrbGxcXF4JwyZcqQkpKSr5jMriP13yE6Z2dnNBqN0bDd9OnT+fzzzzl16hQlS5YEoG3btty5c4fo6Gg8PT2BB4txAnh4eJCQkGDU1t69exk/fjx//PEHxYoVo1q1aqxbtw4PD48iujohhBBCJVQ4Z5XbNN6jgoKC9D/XrFmThg0b4uHhwTfffIOtrW2hxaTC21Rw77//PhUqVGDAgAEALF68mF9//ZVVq1ZhYWHBkSNHgAfzocnJyfrP/5WZmUnHjh1p3rw5J0+e5NChQwwaNEi/r58QQgghzIeLiws+Pj5cuHABV1dX7t+/z82bNw3KXLlyJcdnqnJjdiNSeWFpacmaNWuoXbs2EydOZOHChSxfvpzy5csDUKpUKeDBTX3cDbt16xapqam0a9dOv1Gxr6/vY9t83ANwmmKPOUEIIYQQz0xaWhoXL16kV69e1KtXj2LFihEdHU1ISAgA586dIzExkcaNG+er3udyRArA09OTOXPmMHv2bNq3b8+bb76Zr/NLlChBaGgoAQEBBAcHs2DBAoPnsx6V3wfghBBCCFWz0Kgv5cO7777Lvn37SEhI4Ndff6VTp05YWlrSo0cPnJ2d6d+/P2PGjGHPnj0cO3aMvn370rhx43y9sQfPcUcKYP/+/VhaWpKQkEBmZma+z4+IiODQoUM0adKEDRs24OPjw+HDh3MsGxYWRmpqqkEKCwsr6CUIIYQQ4in89ddf9OjRg8qVK9O1a1dKlizJ4cOH9bNS8+bNo127doSEhNCsWTNcXV3ZvHlzvtt5Lqf24MEbfZs3b2bv3r107dqVDz/80GCF02LFipGVlfXEeurUqUOdOnUICwujcePGrFu3Lsfe6uMegLufXbDrEEIIIUT+ff3117ket7GxYfHixSxevLhA7TyXI1J//fUXgwcPZvbs2TRt2pSIiAhmzZplMJpUoUIFoqOjSUlJ4caNG0Z1xMfHExYWxqFDh7h8+TI7d+7k/PnzuT4nJYQQQjw3NBr1JRV67jpSiqIQGhpKgwYNGDZsGAABAQEMHjyYt956i7S0NADmzp3Lrl27cHd3p06dOkb12NnZcfbsWUJCQvDx8WHQoEEMHTqUt99++5lejxBCCCHUS6MoimLqIJ5nsk9cQclee4XDXPYOkxgLRu3xgcRYWIp+r72K7/5Q5G3kV/ycYFOHYOS5fUZKCCGEEAWQz7fkXlTSkSpiD0Yr1E7du4jLPSwsEmPhUHuMao8PJEbxPJGOVBGr8P5Ppg4hVwkzX0fdQ9jmMcR+XbfV1EHkqoS2PeZwH7OVM6YOIlcWmqqo+z6ax38vEmNhkI6eWkhHSgghhBDGZGYvT8zirb1Dhw5haWlJ27Zt833u1KlTqV27duEHJYQQQogXnll0pFasWMHw4cPZv38///zzj6nDEUIIIYQAzKAjlZaWxoYNGxg8eDBt27YlMjJSfywyMhIXFxeD8lu2bEHz/xftioyMZNq0aZw4cQKNRoNGo9Gfn5iYSIcOHXBwcMDJyYmuXbty5coVfT0nTpygZcuWODo64uTkRL169Th69GhRX64QQgihCoqFRnVJjVTfkfrmm2+oUqUKlStX5q233mLlypXkdemrbt26MXbsWKpVq0ZycjLJycl069aN7OxsOnTowPXr19m3bx+7du3i0qVLdOvWTX9uz549efnllzly5AjHjh1j4sSJFCtWrKguUwghhBBmSPUPm69YsYK33noLgMDAQFJTU9m3bx8tWrR44rm2trY4ODhgZWWFq6urPn/Xrl2cOnWK+Ph43N3dAfjqq6+oVq0aR44coX79+iQmJjJu3DiqVKkCgLe3d65t6XQ6dDqdQV5Oe+8JIYQQ4vmh6hGpc+fOERMTQ48ePQCwsrKiW7durFixokD1xsXF4e7uru9EAVStWhUXFxfi4uIAGDNmDAMGDKB169Z89NFHXLx4Mdc6w8PDcXZ2Nkjh4eEFilMIIYQwGQuN+pIKqbojtWLFCjIzMylbtixWVlZYWVmxdOlSNm3aRGpqKhYWFkbTfBkZGYXS9tSpU/njjz9o27YtP//8M1WrVuW77757bPmwsDBSU1MNUlhYWKHEIoQQQgh1Uu3UXmZmJl999RVz587ltddeMzjWsWNH1q9fj4eHB7dv3yY9PR17e3sAYmNjDcpaW1uTlZVlkOfr60tSUhJJSUn6UakzZ85w8+ZNqlatqi/n4+ODj48Po0ePpkePHkRERNCpU6cc49VqtTKVJ4QQQrxgVNuRioqK4saNG/Tv3x9nZ2eDYyEhIaxYsYIdO3ZgZ2fHe++9x4gRI/jtt98M3uoDqFChAvHx8cTGxvLyyy/j6OhI69atqVGjBj179mT+/PlkZmYyZMgQmjdvjp+fH3fv3mXcuHG88cYbVKxYkb/++osjR44QEhLyDO+AEEIIYUIadU6lqY1qp/ZWrFhB69atjTpR8KAjdfToUf766y/WrFnDTz/9RI0aNVi/fj1Tp041KhsYGEjLli0pVaoU69evR6PR8P3331O8eHGaNWtG69at8fT0ZMOGDQBYWlpy7do1evfujY+PD127diUoKIhp06Y9i0sXQgghhJnQKHldS0A8Fdlrr6DMY88r2WuvMMheewVnHv+9SIyFoej32qsweVuRt5FfCdODTB2CEdWOSAkhhBBCqJ2MSAkhhBDCiIxI5Y1qHzZ/Xly49YOpQ8iVl1Mw6h7CNpchdomx4CTGglN7fCAxFpain9qTh83z5rmc2tNoNGzZsiXXMqGhoXTs2PGZxCOEEEKI55NZdqRSUlIYPnw4np6eaLVa3N3dCQ4OJjo62qhsQkICGo3GaH0pIYQQQoiCMrupvYSEBPz9/XFxceGTTz6hRo0aZGRksGPHDoYOHcrZs2dNHaIQQghh/lS6JYvamN2I1JAhQ9BoNMTExBASEoKPjw/VqlVjzJgxHD582Kh8xYoVAahTpw4ajcZos+M5c+bg5uZGyZIlGTp0qMEWM0uWLMHb2xsbGxvKlCnDG2+8UaTXJoQQQgjzYlYjUtevX2f79u3MnDlTvyXMf7m4uBjlxcTE0KBBA3bv3k21atWwtrbWH9uzZw9ubm7s2bOHCxcu0K1bN2rXrs3AgQM5evQoI0aMYPXq1TRp0oTr169z4MCBorw8IYQQQpgZs+pIXbhwAUVRqFKlSp7PKVWqFAAlS5bE1dXV4Fjx4sVZtGgRlpaWVKlShbZt2xIdHc3AgQNJTEzE3t6edu3a4ejoiIeHB3Xq1HlsOzqdDp1OZ5Ane+8JIYQwWzK1lydmNbVX2EteVatWDUtLS/1nNzc3/v33XwDatGmDh4cHnp6e9OrVi7Vr13Lnzp3H1hUeHo6zs7NBCg8PL9R4hRBCCKEuZtWR8vb2RqPRFNoD5cWKFTP4rNFoyM7OBsDR0ZHjx4+zfv163NzcmDx5MrVq1eLmzZs51hUWFkZqaqpBCgsLK5Q4hRBCCKFOZtWRKlGiBAEBASxevJj09HSj4zl1ch4+E5WVlZXv9qysrGjdujUff/wxJ0+eJCEhgZ9//jnHslqtFicnJ4MkU3tCCCHMlaLRqC6pkVl1pAAWL15MVlYWDRo0YNOmTZw/f564uDgWLlxI48aNjcqXLl0aW1tbtm/fzpUrV0hNTc1TO1FRUSxcuJDY2FguX77MV199RXZ2NpUrVy7sSxJCCCGEmTK7jpSnpyfHjx+nZcuWjB07lurVq9OmTRuio6NZunSpUXkrKysWLlzIF198QdmyZenQoUOe2nFxcWHz5s20atUKX19fPv/8c9avX0+1atUK+5KEEEIIYaZk0+IiJnvtFZS57HklMRacxFhwao8PJMbCUvR77XnM2lXkbeTX5ffamDoEI2Y3IiWEEEIIoRYyIiWEEEIIIzIilTdmtSCneTKH4WE1x+hDWsZeUweRK4diLVD3PQT1f88gMRYGtccHEmNhKfqpPVT6lpzayNSeEEIIIcRTUmVHKjQ0FI1Go08lS5YkMDCQkydPmjo0IYQQQgg9VXakAAIDA0lOTiY5OZno6GisrKxo166dqcMSQgghXgwWGvUlFVJtR0qr1eLq6oqrqyu1a9dm4sSJJCUlcfXqVQBOnTpFq1atsLW1pWTJkgwaNIi0tDQA9u7di7W1NQcOHNDX9/HHH1O6dGmuXLkCQFJSEl27dsXFxYUSJUrQoUMHEhIS9OX37t1LgwYNsLe3x8XFBX9/fy5fvvzsboAQQgghVE+1Han/SktLY82aNXh5eVGyZEnS09MJCAigePHiHDlyhI0bN7J7926GDRsGQIsWLRg1ahS9evUiNTWV33//nUmTJrF8+XLKlClDRkYGAQEBODo6cuDAAQ4ePIiDgwOBgYHcv3+fzMxMOnbsSPPmzTl58iSHDh1i0KBBaOTBOyGEEC8KU48+mcmIlGrf2ouKisLBwQGA9PR03NzciIqKwsLCgnXr1nHv3j2++uor7O3tAVi0aBHBwcHMnj2bMmXKMGPGDHbt2sWgQYM4ffo0ffr0oX379gBs2LCB7Oxsli9fru8cRURE4OLiwt69e/Hz8yM1NZV27dpRqVIlAHx9fXONV6fTodPpDPK0Wi2y3Z4QQgjx/FLtiFTLli2JjY0lNjaWmJgYAgICCAoK4vLly8TFxVGrVi19JwrA39+f7Oxszp07BzzYrHjt2rVs2rSJe/fuMW/ePH3ZEydOcOHCBRwdHXFwcMDBwYESJUpw7949Ll68SIkSJQgNDSUgIIDg4GAWLFhAcnJyrvGGh4fj7OxskMLDw4vm5gghhBBCFVQ7ImVvb4+Xl5f+8/Lly3F2dmbZsmV5ruPXX38F4Pr161y/fl3f8UpLS6NevXqsXbvW6JxSpUoBD0aoRowYwfbt29mwYQMffPABu3btolGjRjm2FRYWxpgxYwzytFotIM9VCSGEMEPqnElTHdWOSD1Ko9FgYWHB3bt38fX15cSJE6Snp+uPHzx4EAsLCypXrgzAxYsXGT16NMuWLaNhw4b06dOH7OxsAOrWrcv58+cpXbo0Xl5eBsnZ2VlfZ506dQgLC+PXX3+levXqrFu37rHxabVanJycDJJW5vWEEEKI55pqO1I6nY6UlBRSUlKIi4tj+PDhpKWlERwcTM+ePbGxsaFPnz6cPn2aPXv2MHz4cHr16kWZMmXIysrirbfeIiAggL59+xIREcHJkyeZO3cuAD179uSll16iQ4cOHDhwgPj4ePbu3cuIESP466+/iI+PJywsjEOHDnH58mV27tzJ+fPnn/iclBBCCCFeLKqd2tu+fTtubm4AODo6UqVKFTZu3EiLFi0A2LFjByNHjqR+/frY2dkREhLCp59+CsDMmTO5fPkyUVFRALi5ufHll1/So0cPXnvtNWrVqsX+/fuZMGECnTt35vbt25QrV45XX30VJycn7t69y9mzZ1m1ahXXrl3Dzc2NoUOH8vbbb5vkXgghhBDPmqLSt+TURjYtLnLmsF+TmmOUvfYKh9q/Z5AYC4Pa4wOJsbAU/V575T/dU+Rt5FfimJamDsGIaqf2hBBCCCHUTkakhBBCCGGk/Ly9pg7BSOLoFqYOwYhqn5F6Xsi0VEH5cCfzwJOLmZCd1Suo+x6CuUxVZCtnTB1Eriw0VVH3fTSP71liLAxFP7Un8kam9oQQQgghnpKqO1KhoaFoNBo0Gg3W1tZ4eXkxffp0MjMzTR2aEEII8Xwz9b56stde4QgMDCQiIgKdTsdPP/3E0KFDKVasGGFhYSaJJyMjg2LFipmkbSGEEEKoi6pHpODBiuGurq54eHgwePBgWrduzdatW/n000+pUaMG9vb2uLu7M2TIENLS0vTnRUZG4uLiwpYtW/D29sbGxoaAgACSkpIM6v/++++pW7cuNjY2eHp6Mm3aNIMRL41Gw9KlS2nfvj329vbMnDnzmV27EEIIIdRN9R2pR9na2nL//n0sLCxYuHAhf/zxB6tWreLnn39m/PjxBmXv3LnDzJkz+eqrrzh48CA3b96ke/fu+uMHDhygd+/ejBw5kjNnzvDFF18QGRlp1FmaOnUqnTp14tSpU/Tr1++ZXKcQQghhUhoVJhVS/dTeQ4qiEB0dzY4dOxg+fDijRo3SH6tQoQIzZszgnXfeYcmSJfr8jIwMFi1aRMOGDQFYtWoVvr6+xMTE0KBBA6ZNm8bEiRPp06cPAJ6ennz44YeMHz+eKVOm6Ot588036du3b67x6XQ6dDqdQZ5WqzXDrqoQQggh8kr1f+ajoqJwcHDAxsaGoKAgunXrxtSpU9m9ezevvvoq5cqVw9HRkV69enHt2jXu3LmjP9fKyor69evrP1epUgUXFxfi4uIAOHHiBNOnT8fBwUGfBg4cSHJyskE9fn5+T4wzPDwcZ2dngxQeHl6Id0IIIYQQaqP6EamWLVuydOlSrK2tKVu2LFZWViQkJNCuXTsGDx7MzJkzKVGiBL/88gv9+/fn/v372NnZ5anutLQ0pk2bRufOnY2O2djY6H+2t7d/Yl1hYWGMGTPGIE+r1ZLBoTzFIoQQQqiJheqHWtRB9R0pe3t7vLy8DPKOHTtGdnY2c+fOxeL/f9PffPON0bmZmZkcPXqUBg0aAHDu3Dlu3ryJr68vAHXr1uXcuXNG9T8NrVb7YCrvERkZBa5aCCGEECql+o5UTry8vMjIyOCzzz4jODiYgwcP8vnnnxuVK1asGMOHD2fhwoVYWVkxbNgwGjVqpO9YTZ48mXbt2lG+fHneeOMNLCwsOHHiBKdPn2bGjBnP+rKEEEII1dCo9OFutTHLgbtatWrx6aefMnv2bKpXr87atWtzfB7Jzs6OCRMm8Oabb+Lv74+DgwMbNmzQHw8ICCAqKoqdO3dSv359GjVqxLx58/Dw8HiWlyOEEEIIM/XcblocGRnJqFGjuHnzpknjkL32Ckr22isc5rF3mOy1V1Dm8T1LjIWh6Pfaq7h4X5G3kV/xQ5ubOgQjZjm1J4QQQoiiJVN7eSMdqSL2YMRH7dS9i/iDER+1U/c9fED9MT4Y8VE7td9HtccHEqN4njy3U3tqcTntB1OHkCsPh2DUPYRtLkPsEmPBSYwFp/b4QGIsLEXf0fNcor6pvUtD1De1Z5YPmxeGhIQENBoNsbGxpg5FCCGEUB2NRqO6pEaq7EiFhoYa3LiSJUsSGBjIyZMnTR2aEEIIIYSeKjtSAIGBgSQnJ5OcnEx0dDRWVla0a9fO1GEJIYQQQuiptiOl1WpxdXXF1dWV2rVrM3HiRJKSkrh69SoAp06dolWrVtja2lKyZEkGDRpEWlqa/vzs7GymT5/Oyy+/jFarpXbt2mzfvv2x7WVlZdGvXz+qVKlCYmIiiqIwdepUypcvj1arpWzZsowYMaLIr1sIIYRQA41GfUmNVNuR+q+0tDTWrFmDl5cXJUuWJD09nYCAAIoXL86RI0fYuHEju3fvZtiwYfpzFixYwNy5c5kzZw4nT54kICCA9u3bc/78eaP6dTodXbp0ITY2lgMHDlC+fHk2bdrEvHnz+OKLLzh//jxbtmyhRo0az/KyhRBCCKFyql3+ICoqCgcHBwDS09Nxc3MjKioKCwsL1q1bx7179/jqq6/0GwovWrSI4OBgZs+eTZkyZZgzZw4TJkyge/fuAMyePZs9e/Ywf/58Fi9erG8nLS2Ntm3botPp2LNnD87OzgAkJibi6upK69atKVasGOXLl9dvLZMTnU6HTqczyMtp7z0hhBBCPD9UOyLVsmVLYmNjiY2NJSYmhoCAAIKCgrh8+TJxcXHUqlVL34kC8Pf3Jzs7m3PnznHr1i3++ecf/P39Der09/cnLi7OIK9Hjx6kp6ezc+dOfScKoEuXLty9exdPT08GDhzId999R2Zm5mPjDQ8Px9nZ2SDltG2NEEIIYQ5MPY0nU3sFZG9vj5eXF15eXtSvX5/ly5eTnp7OsmXLCrWd119/nZMnT3Lo0CGDfHd3d86dO8eSJUuwtbVlyJAhNGvWjIyMjBzrCQsLIzU11SCFhYUVaqxCCCGEUBfVdqQepdFosLCw4O7du/j6+nLixAnS09P1xw8ePIiFhQWVK1fGycmJsmXLcvDgQYM6Dh48SNWqhisnDx48mI8++oj27duzb5/h4mO2trYEBwezcOFC9u7dy6FDhzh16lSO8Wm1WpycnAySTO0JIYQQzzfVPiOl0+lISUkB4MaNGyxatIi0tDSCg4Np0KABU6ZMoU+fPkydOpWrV68yfPhwevXqRZkyZQAYN24cU6ZMoVKlStSuXZuIiAhiY2NZu3atUVvDhw8nKyuLdu3asW3bNpo2bUpkZCRZWVk0bNgQOzs71qxZg62tLR4eHs/0PgghhBCmoDGboRbTUm1Havv27bi5uQHg6OhIlSpV2LhxIy1atABgx44djBw5kvr162NnZ0dISAiffvqp/vwRI0aQmprK2LFj+ffff6latSpbt27F29s7x/ZGjRpFdnY2r7/+Otu3b8fFxYWPPvqIMWPGkJWVRY0aNfjhhx8oWbJkkV+7EEIIIcyD7LVXxGSvvYIylz2vJMaCkxgLTu3xgcRYWIp+rz2fZfuLvI38+nNgM1OHYES1I1JCCCGEMB21viWnNjIiJYQQQggjlZerb0Tq3AAZkXrh2JbvYeoQcnU3cT1nb0aZOozHquLSjvvZx0wdRq6sLeqRmX3C1GHkysqilsRYCKwsaqHuKR9zmZKSGAuu6Kf2RN5IR0oIIYQQRixkai9PVPdyY2hoKBqNRp9KlixJYGAgJ0+eLLQ2vvvuOxo1aoSzszOOjo5Uq1aNUaNGFVr9QgghhHgxqK4jBRAYGEhycjLJyclER0djZWVFu3btCqXu6OhounXrRkhICDExMRw7doyZM2c+dsVyIYQQ4kVk6u1gZIuYAtBqtbi6uuLq6krt2rWZOHEiSUlJXL16lb1796LRaLh586a+fGxsLBqNhoSEBAAuX75McHAwxYsXx97enmrVqvHTTz8B8MMPP+Dv78+4ceOoXLkyPj4+dOzYUb+R8Z9//olGo+Hs2bMGMc2bN49KlSo9k+sXQgghhHlQZUfqv9LS0lizZg1eXl55Xgxz6NCh6HQ69u/fz6lTp5g9ezYODg4AuLq68scff3D69Okcz/Xx8cHPz89oBfS1a9fy5ptvFuxihBBCCPFcUeXD5lFRUfqOT3p6Om5ubkRFRWFhkbd+X2JiIiEhIdSoUQMAT09P/bHhw4dz4MABatSogYeHB40aNeK1116jZ8+e+r3xevbsyaJFi/jwww+BB6NUx44dY82aNY9tU6fTodPpDPJkrz0hhBDmSq1TaWqjyhGpli1bEhsbS2xsLDExMQQEBBAUFMTly5fzdP6IESOYMWMG/v7+TJkyxeBBdXt7e3788UcuXLjABx98gIODA2PHjqVBgwbcuXMHgO7du5OQkMDhw4eBB6NRdevWpUqVKo9tMzw8HGdnZ4MUHh5egLsghBBCCLVTZUfK3t4eLy8vvLy8qF+/PsuXLyc9PZ1ly5bpR6X+u47oow+KDxgwgEuXLtGrVy9OnTqFn58fn332mUGZSpUqMWDAAJYvX87x48c5c+YMGzZsAB5M/7Vq1Yp169YBsG7dOnr27JlrzGFhYaSmphqksLCwAt8LIYQQQqhXvjtSFSpUYPr06SQmJhZFPDnSaDRYWFhw9+5dSpUqBUBycrL+eGxsrNE57u7uvPPOO2zevJmxY8eybNmyx9ZfoUIF7OzsSE9P1+f17NmTDRs2cOjQIS5dukT37t1zjVGr1eLk5GSQZGpPCCGEufrvUkRqSWqU747UqFGj2Lx5M56enrRp04avv/7a6NmggtLpdKSkpJCSkkJcXBzDhw8nLS2N4OBgvLy8cHd3Z+rUqZw/f54ff/yRuXPnGsW4Y8cO4uPjOX78OHv27MHX1xeAqVOnMn78ePbu3Ut8fDy///47/fr1IyMjgzZt2ujr6Ny5M7dv32bw4MG0bNmSsmXLFuo1CiGEEML8PVVH6uGzS76+vgwfPhw3NzeGDRvG8ePHCyWo7du34+bmhpubGw0bNuTIkSNs3LiRFi1aUKxYMdavX8/Zs2epWbMms2fPZsaMGQbnZ2VlMXToUHx9fQkMDMTHx4clS5YA0Lx5cy5dukTv3r2pUqUKQUFBpKSksHPnTipXrqyvw9HRkeDgYE6cOPHEaT0hhBBCvJgKvGlxRkYGS5YsYcKECWRkZFCjRg1GjBhB3759VTsM9yzJXnsFI3vtFQ5z2cfOHGJU9x5s5rJHnMRYcEW/116Nrw4UeRv5dar3K6YOwchTP2yekZHBN998Q/v27Rk7dix+fn4sX76ckJAQ3nvvPRnFEUIIIYQqfPTRR2g0GoPt4O7du8fQoUMpWbIkDg4OhISEcOXKlXzXne8RqePHjxMREcH69euxsLCgd+/eDBgwwGBpgNOnT1O/fn3u3r2b74CEEEIIYXrPy4jUkSNH6Nq1K05OTrRs2ZL58+cDMHjwYH788UciIyNxdnZm2LBhWFhYcPDgwXzVn+8FOevXr0+bNm1YunQpHTt2pFixYkZlKlas+MS33F4UHnN+NnUIubr8bivUPYTtI9M9hcJcpiokxoLx4V7WYVMHkSsby0ao+x6C+r9neBZTe2p8Oudxi18/7i35tLQ0evbsybJlywyep05NTWXFihWsW7eOVq1aARAREYGvry+HDx+mUaNGeY4pX1N7WVlZrFy5kvXr19OlS5ccO1HwYB2oiIiI/FT9WBqNhi1bthRKXUIIIYQwX/ld/Hro0KG0bduW1q1bG+QfO3aMjIwMg/wqVapQvnx5Dh06lK+Y8tWRsrS05O233zbYMLigUlJSGD58OJ6enmi1Wtzd3QkODiY6OrrQ2hBCCCGE+cvP4tdff/01x48fz7GjlZKSgrW1NS4uLgb5ZcqUISUlJV8x5Xtqr3r16ly6dImKFSvm91QjCQkJ+Pv74+LiwieffEKNGjXIyMhgx44dDB06lLNnzxa4DSGEEELknxqn9nKbxvuvpKQkRo4cya5du7CxsSnSmPL91t6MGTN49913iYqKIjk5mVu3bhmk/BgyZAgajYaYmBhCQkLw8fGhWrVqjBkzRr/PHcD//vc/OnXqhJ2dHd7e3mzdutWgntOnTxMUFISDgwNlypShV69e/O9//9Mfb9GiBcOHD2fUqFEUL16cMmXKsGzZMtLT0+nbty+Ojo54eXmxbds2/Tk3btygZ8+elCpVCltbW7y9vQttulIIIYQQRefYsWP8+++/1K1bFysrK6ysrNi3bx8LFy7EysqKMmXKcP/+faMZtitXruDq6pqvtvLdkXr99dc5ceIE7du35+WXX6Z48eIUL14cFxcXihcvnud6rl+/zvbt2xk6dCj29vZGx/873DZt2jS6du3KyZMnef311+nZsyfXr18H4ObNm7Rq1Yo6depw9OhRtm/fzpUrV+jatatBfatWreKll14iJiaG4cOHM3jwYLp06UKTJk04fvw4r732Gr169dJvXDxp0iTOnDnDtm3biIuLY+nSpbz00kv5vV1CCCGEeMZeffVVTp06RWxsrD75+fnRs2dP/c/FihUzeIzo3LlzJCYm0rhx43y1le+pvT179uT3lBxduHABRVEMlk14nNDQUHr0eLCw5axZs1i4cCExMTEEBgayaNEi6tSpw6xZs/TlV65cibu7O3/++Sc+Pg/ebKhVqxYffPAB8GCO9aOPPuKll15i4MCBAEyePJmlS5dy8uRJGjVqRGJiInXq1MHPzw94sB9fbh73JoEQQghhjtQ4tZdXjo6OVK9e3SDP3t6ekiVL6vP79+/PmDFjKFGiBE5OTgwfPpzGjRvn6409eIqOVMWKFXF3dzdatVxRFJKSkvJcT36Wr6pZs6b+Z3t7e5ycnPj3338BOHHiBHv27MHBwcHovIsXL+o7Uv+tw9LSkpIlS1KjRg19XpkyZQD09Q4ePJiQkBD9aFXHjh1p0qTJY2MMDw9n2rRpBnlTpkwBh2Z5vk4hhBBCPBvz5s3DwsKCkJAQdDodAQEB+u3k8uOpOlLJycmULl3aIP/69etUrFiRrKysPNXj7e2NRqPJ0wPljy6zoNFoyM7OBtBvZjx79myj89zc3HKt4795DzuGD+sNCgri8uXL/PTTT+zatYtXX32VoUOHMmfOnBxjDAsLY8yYMQZ5Wq2WiM/yt7CXEEIIoQYWZjwilZO9e/cafLaxsWHx4sUsXry4QPXm+xkpRVFy3EMvLS0tX0/GlyhRgoCAABYvXkx6errR8bwusVC3bl3++OMPKlSogJeXl0HK6dmr/ChVqhR9+vRhzZo1zJ8/ny+//PKxZbVaLU5OTgZJpvaEEEKI51ueR6QejrZoNBomTZqEnZ2d/lhWVha//fYbtWvXzlfjixcvxt/fnwYNGjB9+nRq1qxJZmYmu3btYunSpcTFxT2xjqFDh7Js2TJ69OjB+PHjKVGiBBcuXODrr79m+fLlWFpa5iumhyZPnky9evWoVq0aOp2OqKgofH19n6ouIYQQQjyf8tyR+v3334EHI1KnTp3C2tpaf8za2ppatWrx7rvv5qtxT09Pjh8/zsyZMxk7dizJycmUKlWKevXqsXTp0jzVUbZsWQ4ePMiECRN47bXX0Ol0eHh4EBgYiIXFU+/JjLW1NWFhYSQkJGBra8srr7zC119//dT1CSGEEObEnB82f5byvWlx3759WbBgAU5OTkUV03NF9torKNlrr3CYy95hEmPByF57hUPt3zM8i7326q1X36bFx3rkf9PiopbvIZuIiAiDTtStW7fYsmWLrEIuhBBCiBdOvkekunbtSrNmzRg2bBh3796lVq1aJCQkoCgKX3/9NSEhIUUVqxBCCCGeEb+v1TcidbS7+kak8r38wf79+3n//fcB+O6771AUhZs3b7Jq1SpmzJghHalH3MlU3y/if9lZvYJt+R6mDuOx7iau5+b9n0wdRq5crF/HPKYBJMaC8yEtY6+pg3gsh2ItMId7KDEWhqKf2hN5k++pvdTUVEqUKAHA9u3bCQkJwc7OjrZt23L+/PlCD1AIIYQQQq3y3ZFyd3fn0KFDpKens337dl577TXgwSa/hbXDcmhoKBqNRr9oZpkyZWjTpg0rV67UL5gphBBCiKKjsdCoLqlRvjtSo0aNomfPnrz88suULVuWFi1aAA+m/P675UpBBQYGkpycTEJCAtu2baNly5aMHDmSdu3akZmZmeM5GRkZhda+EEIIIcST5LsjNWTIEA4dOsTKlSv55Zdf9Gs1eXp6MmPGjEILTKvV4urqSrly5ahbty7vvfce33//Pdu2bSMyMhJ4sDjo0qVLad++Pfb29sycOZPIyEhcXFwM6tqyZYvRauwzZsygdOnSODo6MmDAACZOnGiwoOjevXtp0KAB9vb2uLi44O/vz+XLlwvt+oQQQghh/p5qxUo/Pz86depksFFw27Zt8ff3L7TActKqVStq1arF5s2b9XlTp06lU6dOnDp1in79+uWpnrVr1zJz5kxmz57NsWPHKF++vMECoJmZmXTs2JHmzZtz8uRJDh06xKBBg3LcGkcIIYR4Hmk06ktqlO+39p7UWVm5cuVTB5MXVapU4eTJk/rPb775Jn379s1XHZ999hn9+/fXnzd58mR27txJWloa8GBtrNTUVNq1a0elSpUAnrg9jE6nQ6fTGeRptVp4uh1qhBBCCGEG8j0idePGDYP077//8vPPP7N58+Y8bzRcEI9umuzn55fvOs6dO0eDBg0M8v77uUSJEoSGhhIQEEBwcDALFiwgOTk51zrDw8NxdnY2SOHh4fmOTQghhBDmI98jUt99951RXnZ2NoMHD9aP3hSluLg4KlasqP9sb29vcNzCwoJH1xh9mofQIyIiGDFiBNu3b2fDhg188MEH7Nq1i0aNGuVYPiwsTL+x80NarZYsYvLdthBCCGFqap1KU5un39X3v5VYWDBmzBjmzZtXGNU91s8//8ypU6dyXfSzVKlS3L59m/T0dH1ebGysQZnKlStz5MgRg7xHPwPUqVOHsLAwfv31V6pXr866dese265Wq8XJyckgabXaPF6ZEEIIIcxRvkekHufixYuPXZbgaeh0OlJSUsjKyuLKlSts376d8PBw2rVrR+/evR97XsOGDbGzs+O9995jxIgR/Pbbb/q3/B4aPnw4AwcOxM/PjyZNmrBhwwZOnjyJp6cnAPHx8Xz55Ze0b9+esmXLcu7cOc6fP59ru0IIIYR48eS7I/Xo9JWiKCQnJ/Pjjz/Sp0+fQgts+/btuLm5YWVlRfHixalVqxYLFy6kT58++iUXclKiRAnWrFnDuHHjWLZsGa+++ipTp05l0KBB+jI9e/bk0qVLvPvuu9y7d4+uXbsSGhpKTMyDaTg7OzvOnj3LqlWruHbtGm5ubgwdOpS333670K5PCCGEUDOZ2subfG9a3LJlS4PPFhYWlCpVilatWtGvXz+srAptkOuZatOmDa6urqxevbpQ65W99gpG9torLOayd5j6Y5S99grKPL5n84ixaDXa9EuRt5Ffh0OamjoEI/nu9ezZs6co4nim7ty5w+eff05AQACWlpasX7+e3bt3s2vXLlOHJoQQQggzku8RqefB3bt3CQ4O5vfff+fevXtUrlyZDz74gM6dO5s6NCGEEEIVmmxW34jUr53NdESqTp06eV7V+/jx4wUK6FmwtbVl9+7dz6Ste1mHn0k7T8vGshHZyhlTh/FYFpqqZGafMHUYubKyqIV5TANIjAWn9hjVHh9IjIWl6Kf2RN7kafmDjh070qFDBzp06EBAQAAXL15Eq9XSokULWrRogY2NDRcvXiQgIKCo480zjUbDli1bHns8ISEBjUZjtDSCEEIIIUy/HcxztUXMlClT9D8PGDCAESNG8OGHHxqVSUpKKpSgQkNDWbVq1YMArax4+eWX6dKlC9OnT8fGxqZQ2hBCCCGEKKh8P2y+ceNGjh49apT/1ltv4efnV2h77QUGBhIREUFGRgbHjh2jT58+aDQaZs+eXSj1Pw1FUcjKyjLbNxOFEEIIUbjyvbK5ra0tBw8eNMo/ePBgoY4WabVaXF1dcXd3p2PHjrRu3Vr/Vl2FChWYP3++QfnatWszdepUg7zk5GSCgoKwtbXF09OTb7/91qids2fP0qRJE2xsbKhevTr79u3TH9u7dy8ajYZt27ZRr149tFotv/yivofvhBBCiMKmsVBfUqN8D62MGjWKwYMHc/z4cf1Gv7/99hsrV65k0qRJhR4gwOnTp/n111/x8PDI13mTJk3io48+YsGCBaxevZru3btz6tQpfH199WXGjRvH/PnzqVq1Kp9++inBwcHEx8dTsmRJfZmJEycyZ84cPD09KV68eKFdlxBCCCHMW747UhMnTsTT05MFCxawZs0aAHx9fYmIiKBr166FFlhUVBQODg5kZmai0+mwsLBg0aJF+aqjS5cuDBgwAIAPP/yQXbt28dlnn7FkyRJ9mWHDhun37lu6dCnbt29nxYoVjB8/Xl9m+vTptGnTJte2dDodOp3OIE+r1RbiJjxCCCGEUJun+jPftWvXQu005aRly5YsXbqU9PR05s2bh5WVVa6bFeekcePGRp8ffUvvv2WsrKzw8/MjLi7OoIyfn98T2woPD2fatGkGeVOmTGHipMB8xSyEEEKogVrfklObpx4vuX//Pv/++y/Z2dkG+eXLly9wUAD29vZ4eXkBsHLlSmrVqsWKFSvo378/FhYWPLqOaEZGRqG0+7hYniQsLMxoH0KtVovC70UVlhBCCCFMLN+Pbp0/f55XXnkFW1tbPDw8qFixIhUrVqRChQpUrFixKGLEwsKC9957jw8++IC7d+9SqlQpkpOT9cdv3bpFfHy80XmHDx82+vzf56MeLZOZmcmxY8eMyuSFVqvFycnJIGm12nzXI4QQQgjzke8RqdDQUKysrIiKisLNzS3PK54XVJcuXRg3bhyLFy+mVatWREZGEhwcjIuLC5MnT8bS0tLonI0bN+Ln50fTpk1Zu3YtMTExrFixwqDM4sWL8fb2xtfXl3nz5nHjxg369ev3TK5JCCGEUKtn9ffd3OW7IxUbG8uxY8eoUqVKUcTzWFZWVgwbNoyPP/6Y8+fPEx8fT7t27XB2dubDDz/McURq2rRpfP311wwZMgQ3NzfWr19P1apVDcp89NFHfPTRR8TGxuLl5cXWrVt56aWXntVlCSGEEMKM5XvT4vr16zNv3jyaNlXfxoFqJHvtFYzstVdYzGXvMImxYNQeH0iMhaXo99pr9oPxmpGmtj/Y39QhGMn3M1KzZ89m/Pjx7N27l2vXrnHr1i2DJIQQQgjzZ+p99cxlr718j0hZWDzoez06d6ooChqNhqysrMKLTgghhBAm0TxKfSNS+9qpb0Qq389I7dmzpyjieG6tOLfD1CHkqn/lANQ9hO0jU3uFwlymKiTGglF7fCAxFpain9oTeZPvjlTz5s2LIg7Vmzp1Klu2bDFa0FMIIYR4Hql1Kk1t8vSM1MmTJ/ULb548eTLXVNSuXr3K4MGDKV++vH5j44CAAP1GyhqNhi1bthR5HEIIIYQQeRqRql27NikpKZQuXZratWuj0WiMVhYHnskzUiEhIdy/f59Vq1bh6enJlStXiI6O5tq1a0XarhBCCCHEo/LUkYqPj6dUqVL6n03l5s2bHDhwgL179+qnGD08PGjQoAEAFSpUAKBTp076YwkJCQB8//33TJs2jTNnzlC2bFn69OnD+++/j5WVlb7ud999l++//x6dToefnx/z5s2jVq1az/YihRBCCBWQqb28yVNHysPDI8efnzUHBwccHBzYsmULjRo1MtqC5ciRI5QuXZqIiAgCAwP1q50fOHCA3r17s3DhQl555RUuXrzIoEGDgAcbC8ODldNtbW3Ztm0bzs7OfPHFF7z66qv8+eeflChR4tleqBBCCCHMQr7XkTIlKysrIiMjWbVqFS4uLvj7+/Pee+/pn816OGrm4uKCq6ur/vO0adOYOHEiffr0wdPTkzZt2vDhhx/yxRdfAPDLL78QExOj31LG29ubOXPm4OLiwrfffpun2HQ6ndGaWjqdrgjughBCCCHUwqw6UvDgGal//vmHrVu3EhgYyN69e6lbty6RkZGPPefEiRNMnz5dP6Ll4ODAwIEDSU5O5s6dO5w4cYK0tDRKlixpUCY+Pp6LFy/mKa7w8HCcnZ0NUnh4eCFdtRBCCPFsWWjUl9Qo38sfqIGNjQ1t2rShTZs2TJo0iQEDBjBlyhRCQ0NzLJ+Wlsa0adPo3LlzjnWlpaXh5ubG3r17jY67uLjkKaawsDDGjBljkKfValmTYFynEEIIIZ4PZtmRelTVqlX1Sx4UK1bM6M3BunXrcu7cOby8vHI8v27duqSkpGBlZaV/YD2/tFqt0TNbQgghhLlS6wiQ2jxVRyoxMZHk5GQsLCzw9PSkZMmShR1Xjq5du0aXLl3o168fNWvWxNHRkaNHj/Lxxx/ToUMH4MGbe9HR0fj7+6PVailevDiTJ0+mXbt2lC9fnjfeeAMLCwtOnDjB6dOnmTFjBq1bt6Zx48Z07NiRjz/+GB8fH/755x9+/PFHOnXqhJ+f3zO5PiGEEEKYl3w9I7VkyRI8PDyoWLEiTZo0oVGjRpQuXZqmTZty7NixoopRz8HBgYYNGzJv3jyaNWtG9erVmTRpEgMHDmTRokUAzJ07l127duHu7k6dOnUACAgIICoqip07d1K/fn0aNWrEvHnz9G8gajQafvrpJ5o1a0bfvn3x8fGhe/fuXL58mTJlyhT5dQkhhBDCPOV50+I5c+Ywb948wsLCsLGx4dNPP6VHjx7Ur1+fdevWsWnTJvbt2yejN4+QvfYKSvbaKxzmsneYxFgwao8PJMbCUvR77QXs+KXI28ivHQFNTR2CkTxP7S1evJjly5cTFBQEQLNmzWjSpAkpKSkEBgZSvHhx3nvvPXbu3FlkwQohhBBCqEmeR6Ts7e35448/9A9jK4qCtbU1iYmJuLm5ceLECZo2bcrt27eLMl4hhBBCPAMyIpU3eR6R8vHxYdeuXQwcOBCAPXv2YG1tjaurK/BgGQGNrCdv5H520T87VhDWFvVQ9xC2uQyxS4wFJzEWnNrjA4mxsBT91J68tZc3ee5IhYWF8dZbb7F7925sbGzYvHkzI0aM0Hee9u7dS/Xq1Yss0PyKjIxk1KhR3Lx509ShCCGEEOI5lee39rp27cr333+PlZUV6enpfPrppwYrd7/xxhv88MMPhR5gaGgoGo3GKF24cKHAdUdGRurrs7Cw4OWXX6Zv3778+++/hRC5EEIIIZ53+VpHKigoSP+w+aOKci2pwMBAIiIiDPIe7qNXUE5OTpw7d47s7GxOnDhB3759+eeff9ixw/htu6ysLH2nSwghhHieyV+6vCnwfXrY8ShKWq0WV1dXg7RgwQJq1KiBvb097u7uDBkyhLS0NKNzt2zZgre3NzY2NgQEBJCUlGRwXKPR4OrqStmyZQkKCmLEiBHs3r2bu3fvEhkZiYuLC1u3bqVq1apotVoSExOL9FqFEEIIYT7yPCJ18uTJHPPXrl1Lhw4d8PT0BKBmzZqFE9kTWFhYsHDhQipWrMilS5cYMmQI48ePZ8mSJfoyd+7cYebMmXz11VdYW1szZMgQunfvzsGDBx9br62tLdnZ2WRmZurrmD17NsuXL6dkyZKULl26yK9NCCGEEOYhzx2p2rVro9FoyGm1hJCQEBRFQaPRGO1zVxiioqJwcHDQfw4KCmLjxo36zxUqVGDGjBm88847Bh2pjIwMFi1aRMOGDQFYtWoVvr6+xMTE0KBBA6N2zp8/z+eff46fnx+Ojo76OpYsWUKtWrVyjVGn06HT6QzytFotmmL5v14hhBDC1Cw0eVod6YWX56m9mjVrEhQUxJkzZ4iPjyc+Pp5Lly5haWnJjh079J+LQsuWLYmNjdWnhQsXsnv3bl599VXKlSuHo6MjvXr14tq1a9y5c0d/npWVFfXr19d/rlKlCi4uLsTFxenzUlNTcXBwwM7OjsqVK1OmTBnWrl2rP25tbZ2nUbbw8HCcnZ0N0n8fxhdCCCHE8yfPHamYmBi8vLwICQnh+vXreHh46BfnLFu2LB4eHvq96wqbvb09Xl5e+qTT6WjXrh01a9Zk06ZNHDt2jMWLFwNw//79fNXt6OhIbGwsp0+fJj09nf379+Pj83/rc9ja2uZpfaywsDBSU1MNUlhYWP4uVAghhBBmJc9Te9bW1syfP59t27bRvn17hgwZwoQJE4oytsc6duwY2dnZzJ07V/8G3TfffGNULjMzk6NHj+qn8c6dO8fNmzfx9fXVl7GwsMDLy6vAMWm1WrRarVH+/ewCVy2EEEI8c7IgZ97k+629oKAgjh49yoEDB2jRokURhPRkXl5eZGRk8Nlnn3Hp0iVWr17N559/blSuWLFiDB8+nN9++41jx44RGhpKo0aNcnw+SgghhBAiv55q+YMyZcrw008/8cYbb9CuXTucnJwKO65c1apVi08//ZTZs2dTvXp11q5dm+PzSHZ2dkyYMIE333wTf39/HBwc2LBhwzONVQghhBDPrzxvWiyejuy1V1DmsueVxFhwEmPBqT0+kBgLS9Hvtddp94EibyO/vmv9iqlDMJLvEalVq1bx448/6j+PHz8eFxcXmjRpwuXLlws1OCGEEEIINcv3iFTlypVZunQprVr9v/buPC6q6v8f+OuyDTsEIoMKiLKrKO5KCiQGaiapaUopbqWCpriOLWilo/YhyzRtUTDLrXILMxcUUlRcUVPEJRUzXBMU1GG7vz/8OV/HAWJ17uDr2eM+Hsy5597zvoPWu3POPecl7N+/H926dcPnn3+OxMREGBkZYf369bUVKxERET0j/ZKk1yP1Szfp9UhVaq89ALhy5Yr6LbeNGzeif//+ePvttxEQEKCzyedSlleYrOsQymVpHARpd2HrSxc7Y6w+xlh9Uo8P0JcYi0qO6zqIchkZlL9IND07lR7as7S0xO3btwEA27dvR/fu3QEApqamePDgQc1GR0RERCRhlU6kunfvjpEjR2LkyJE4e/YsevbsCQA4deqUeoHO2nbt2jW8++67cHd3h6mpKRwdHREQEIAlS5ZorGxOREREVSMIouQOKar00N7ixYvx/vvv48qVK/jll19gb28P4NEimYMGDarxAJ/2119/ISAgALa2tpgzZw5atGgBmUyGkydP4ptvvkHDhg3x6quv1nocRERERJXukbK1tcWiRYuwadMmhIWFqctnzZqF9957r0aDK83YsWNhZGSEw4cPY8CAAfDx8UGTJk3Qp08fbNmyBb1798alS5cgCALS09PV1+Xk5EAQBCQnJwMAkpOTIQgCkpKS0LZtW5ibm6Nz587IzMxUX3P8+HEEBwfDysoK1tbWaNOmDQ4fPlzrz0hERET6oUoLcu7ZswdvvvkmOnfujKtXrwIAVq5cib1799ZocE+7ffs2tm/fjqioKFhYWJRapyL74j3pvffeQ1xcHA4fPgwjIyMMHz5cfS4iIgKNGjXCoUOHcOTIEUyfPh3GxsbVegYiIiJ9YCBI75CiSidSv/zyC0JDQ2FmZoajR49CpVIBAHJzczFnzpwaD/BJ58+fhyiK8PLy0iivV68eLC0tYWlpWen9/2bPno3AwED4+vpi+vTp2LdvHx4+fAgAyMrKQkhICLy9veHh4YHXX38dLVuW/qaESqXC3bt3NY7H3w0RERHVTZVOpD755BMsXboU3377rUbvTEBAAI4ePVqjwVXUwYMHkZ6ejmbNmlU6efHz81P/7OTkBAC4ceMGACAmJgYjR45ESEgI5s6diwsXLpR5H6VSCRsbG42jtG1riIiIqO6odCKVmZmJrl27apXb2NggJyenJmIqk7u7OwRB0JjHBABNmjSBu7s7zMzMAAAGBo8e68m1RgsLC0u955PJ4ONhwZKSEgDAzJkzcerUKfTq1Qu7du2Cr68vNmzYUOp9FAoFcnNzNQ6FQlHFJyUiItItAwkeUlTpuORyOc6fP69VvnfvXjRp0qRGgiqLvb09unfvjkWLFiE/P7/Meg4ODgCA7OxsddmTE88rw9PTExMnTsT27dvRt29fxMfHl1pPJpPB2tpa45DJZFVqk4iIiPRDpROpUaNG4d1330VaWhoEQcA///yDH3/8EZMnT8aYMWNqI0YNX331FYqKitC2bVusXbsWGRkZyMzMxA8//IAzZ87A0NAQZmZm6NixI+bOnYuMjAykpKTg/fffr1Q7Dx48QHR0NJKTk3H58mWkpqbi0KFD8PHxqaUnIyIiIn1T6XWkpk+fjpKSEnTr1g33799H165dIZPJMHnyZIwbN642YtTQtGlTHDt2DHPmzIFCocDff/8NmUwGX19fTJ48GWPHjgUALF++HCNGjECbNm3g5eWF+fPn4+WXX65wO4aGhrh9+zaGDBmC69evo169eujbty9mzZpVW49GREQkGQYSXQBTaiq9afFjBQUFOH/+PPLy8uDr6wtLS8uajq1O4F571aUf+3IxxprAGKtP6vEB+hIj99oDBien1HoblbUqKFDXIWipdI/UYyYmJvD19a3JWIiIiIj0SoV6pPr27VvhG65fv75aAREREZHuvZkivR6pHwL1tEfKxsZG/bMoitiwYQNsbGzQtm1bAI/22cvJyalUwiVlM2fOxMaNG6v8pt+THH2mVD+gWnQ941NIu5vdEw+LD+g6iHKZGnbEmZxEXYdRLm/bVyDt3zOgL0M+0o7REyXiaV0HUS4DwRfS/g4B6f+egUcxkhRU6K29+Ph49eHo6IgBAwbg4sWLWL9+PdavX4+//voLb7zxBurVq1drgUZGRkIQBIwePVrrXFRUFARBQGRkZK21T0RERPS0Si9/sHz5ckyePBmGhobqMkNDQ8TExGD58uU1GtzTnJ2dsWbNGjx48EBd9vDhQ6xatQouLi612jYREdHzRNeLb9bZBTmLiopw5swZrfIzZ86oVwSvLa1bt4azs7PGPKz169fDxcUF/v7+6rLff/8dL774ImxtbWFvb49XXnlFa3uXv//+G4MGDYKdnR0sLCzQtm1bpKWladRZuXIlGjduDBsbG7zxxhu4d+9erT4fERER6ZdKJ1LDhg3DiBEj8Nlnn2Hv3r3Yu3cv4uLiMHLkSAwbNqw2YtQwfPhwjdXFly9frtVufn4+YmJicPjwYSQlJcHAwACvvfaaOtHLy8tDYGAgrl69is2bN+P48eOYOnWqRiJ44cIFbNy4EYmJiUhMTERKSgrmzp1b689HRERE+qPSyx/873//g1wuR1xcnHoLFicnJ0yZMgWTJk2q8QCf9uabb0KhUODy5csAgNTUVKxZswbJycnqOv369dO4Zvny5XBwcMDp06fRvHlzrFq1Cjdv3sShQ4dgZ2cH4NE+fk8qKSlBQkICrKysAABvvfUWkpKSMHv27FLjUqlUWhsmc4sYIiLSVwaCriPQD5VOpAwMDDB16lRMnToVd+/eBQBYW1vXeGBlcXBwQK9evZCQkABRFNGrVy+tSe7nzp3Dhx9+iLS0NNy6dUvd05SVlYXmzZsjPT0d/v7+6iSqNI0bN1YnUcCjZPHGjRtl1lcqlVqrnsfGxlblEYmIiEhPVHlBzps3byIzMxMA4O3tXatv7D1t+PDhiI6OBgAsXrxY63zv3r3h6uqKb7/9Fg0aNEBJSQmaN2+OgoICAICZmdl/tmFsbKzxWRCEcueAKRQKxMTEaJTJZDIsWVu5Pf6IiIikgFvEVEyl50jl5+dj+PDhcHJyQteuXdG1a1c4OTlhxIgRuH//fm3EqCUsLAwFBQUoLCxEaGioxrnbt28jMzMT77//Prp16wYfHx/cuXNHo46fnx/S09Px77//1lhMMpkM1tbWGgeH9oiIiOq2SidSMTExSElJwa+//oqcnBzk5ORg06ZNSElJeSZzpIBHyy1kZGTg9OnTGsswAMALL7wAe3t7fPPNNzh//jx27dql1VM0aNAgyOVyhIeHIzU1FX/99Rd++eUX7N+//5nET0RERHVDpROpX375BcuWLUOPHj3UPS89e/bEt99+i59//rk2YizV47afZmBggDVr1uDIkSNo3rw5Jk6ciE8//VSjjomJCbZv34769eujZ8+eaNGiBebOnauVlBERET2vDATpHVJUob32nmRubo4jR47Ax8dHo/zUqVNo37498vPzazRAfcctYqqLW8TUBG4RU1OkHiO3iKkZUv89A89ii5iRe5NrvY3K+u7FIF2HoKXSPVKdOnVCbGwsHj58qC578OABZs2ahU6dOtVocERERERVsWTJEvj5+alHsDp16oStW7eqzz98+BBRUVGwt7eHpaUl+vXrh+vXr1e6nUq/tffFF18gNDQUjRo1QsuWLQEAx48fh6mpKbZt21bpAIiIiEh6pLolS0U1atQIc+fOhYeHB0RRxIoVK9CnTx8cO3YMzZo1w8SJE7Flyxb89NNPsLGxQXR0NPr27YvU1NRKtVPpoT0AuH//Pn788Uf1VjE+Pj6IiIio0LICREREJH1vS3Bo75tqDu3Z2dnh008/Rf/+/eHg4IBVq1ahf//+AB5tdefj44P9+/ejY8eOFb5nldaRMjc3x6hRo6pyqWQkJycjODgYd+7cga2tba21E/lHSq3duyYkdA2EtOcC6MtcBcZYfYyx+qQeH8AYa0rtz5GSorJ2Efmv5YaKi4vx008/IT8/H506dcKRI0dQWFiIkJAQdR1vb2+4uLhUOpGqdM+dUqnE8uXLtcqXL1+OefPmVfZ2apGRkQgPD9cqT05OhiAIyMnJqfK9iYiIqHIMBFFyh1KphI2NjcahVCrLfIaTJ0/C0tISMpkMo0ePxoYNG+Dr64tr167BxMREqyPF0dER165dq9z3VNkv9uuvv4a3t7dWebNmzbB06dLK3q7WPV7NnIiIiPSbQqFAbm6uxqFQKMqs7+XlhfT0dKSlpWHMmDEYOnQoTp+u2TdbK51IXbt2DU5OTlrlDg4O6k2Ma8vt27cxaNAgNGzYEObm5mjRogVWr16tUScoKAjR0dGYMGEC6tWrp175/LfffoOnpyfMzMwQHByMS5cuqa8RRREODg4a62C1atVK4zn37t0LmUz2zFZvJyIiIk2V3UXExMQE7u7uaNOmDZRKJVq2bIkvvvgCcrkcBQUFWqNd169fh1wur1RMlU6knJ2dS53RnpqaigYNGlT2dpXy8OFDtGnTBlu2bMGff/6Jt99+G2+99RYOHjyoUW/FihUwMTFBamoqli5diitXrqBv377o3bs30tPTMXLkSEyfPl1dXxAEdO3aFcnJyQCAO3fuICMjAw8ePFBPqE9JSUG7du1gbm5eq89IREQkBbpefLM2FuQsKSmBSqVCmzZtYGxsjKSkJPW5zMxMZGVlVXopp0pPNh81ahQmTJiAwsJCvPTSSwCApKQkTJ06tdpbxCQmJsLS0lKjrLi4WP1zw4YNMXnyZPXncePGYdu2bVi3bh3at2+vLvfw8MD8+fPVn2fMmIGmTZsiLi4OwKOuvpMnT2rM6QoKCsLXX38NAPjjjz/g7+8PuVyO5ORkeHt7Izk5GYGBgWXGXtYEOCIiInr2FAoFevToARcXF9y7dw+rVq1CcnIytm3bBhsbG4wYMQIxMTGws7ODtbU1xo0bh06dOlVqojlQhURqypQpuH37NsaOHauef2Rqaopp06aVO05ZEcHBwViyZIlGWVpaGt58800Aj5KqOXPmYN26dbh69SoKCgqgUqm0eonatGmj8TkjIwMdOnTQKHs64wwMDMS7776LmzdvIiUlBUFBQepEasSIEdi3bx+mTp1aZuxKpRKzZs3SKIuNjQVeCq7YwxMREVGNuXHjBoYMGYLs7GzY2NjAz88P27ZtQ/fu3QEACxYsgIGBAfr16weVSoXQ0FB89dVXlW6n0omUIAiYN28ePvjgA2RkZMDMzAweHh410vtiYWEBd3d3jbK///5b/fOnn36KL774Ap9//jlatGgBCwsLTJgwQWtCuYWFRaXbbtGiBezs7JCSkoKUlBTMnj0bcrkc8+bNw6FDh1BYWIjOnTuXeb1CodDaHFkmk+GdNGlvb0JERFQaqe5tV1HLli0r97ypqSkWL16MxYsXV6udKq0jBQCWlpZo165dtRqvrNTUVPTp00fdQ1VSUoKzZ8/C19e33Ot8fHywefNmjbIDBzQTHEEQ0KVLF2zatAmnTp3Ciy++CHNzc6hUKnz99ddo27ZtuQlaRdaxICIiorpFr1aA9/DwwI4dO7Bv3z5kZGTgnXfeqdC+OKNHj8a5c+cwZcoUZGZmYtWqVUhISNCqFxQUhNWrV6NVq1awtLSEgYEBunbtih9//LHc+VFERET0fNKrROr9999H69atERoaqp7DVNoink9zcXHBL7/8go0bN6Jly5ZYunQp5syZo1UvMDAQxcXFCAoKUpcFBQVplREREdV1BhI8pKhKe+1RxXGLmOrSl60aGGP1Mcbqk3p8AGOsKbW/Rcz4/btrvY3KWthJei9wSTXBIyIiIpK8Kk82JyIiorrLQOCAVUVwaI+IiIi0TDiwS9chaPm840u6DkFLneiREgQBGzZsqNDE82fttZ17dB1CuTaEdIG05wLox1yFh8XSXi/M1LAj9OF7LBFrdjPRmmYg+ELa36N+/H3RhxiLSo7rOohyGRm0rPU29H0dqWdFL+ZIRUZGQhAErSMsLKzS90pISCj1XqamprUQOREREdVletMjFRYWhvj4eI2yqi6AaW1tjczMTI0yQWDqTURERJWjFz1SwKOkSS6XaxwvvPBCqXX//vtvDBo0CHZ2drCwsEDbtm2RlpamPi8Igta9HB0d1efz8/MxZMgQWFpawsnJCXFxcQgKCsKECRNq+zGJiIgkQddrRunLOlJ60yNVUXl5eQgMDETDhg2xefNmyOVyHD16FCUlJRW+x5QpU5CSkoJNmzahfv36mDFjBo4ePYpWrVrVXuBERESkd/QmkUpMTISlpaVG2YwZMzBjxgyNslWrVuHmzZs4dOgQ7OzsAEBrI+Tc3Fyte3Xp0gVbt25FXl4eli1bhh9++AHdunUDAKxYsQKNGjUqNz6VSgWVSqVRxr33iIiI6ja9SaSCg4OxZMkSjbLHidKT0tPT4e/vX+q5x6ysrHD06FGNMjMzMwDAhQsXUFBQgA4dOmi04+XlVW58SqUSs2bN0iiLjY0FXuxW7nVERERSxLf2KkZvEikLCwutnqXSPE6IymNgYFChe1WGQqFATEyMRplMJsMbew7WaDtEREQkHVKdu1Vlfn5+SE9Px7///lul65s2bQpjY2ONyel37tzB2bPlr3sik8lgbW2tcXBoj4iIqG7Tmx4plUqFa9euaZQZGRmhXr16GmWDBg3CnDlzEB4eDqVSCScnJxw7dgwNGjRAp06dAACiKGrdCwDq168PS0tLjBgxAlOmTIG9vT3q16+P9957DwYGdS7nJCIiKpPALWIqRG8Sqd9//x1OTk4aZV5eXjhz5oxGmYmJCbZv345JkyahZ8+eKCoqgq+vLxYvXqyuc/fuXa17AUB2djbkcjk+/fRT5OXloXfv3rCyssKkSZOQm5tbOw9GREREeksvEqmEhAQkJCSUef7p7QJdXV3x888/l1o3MjISkZGR5bZnaWmJlStXYuXKleqyLVu2VDheIiIiej7oRSJFREREzxbf2qsYTvwhIiIiqiJBfHpcjIiIiJ57isNJug5Bi7Kt9NZmrDNDe4IgYMOGDQgPDy/1fHJyMoKDg3Hnzh3Y2to+s7jMXAY9s7aq4kHWahSVHNd1GGUyMmgJoPylJ3TPE4yxJjDG6pN6fABjrCmetd4Ch6wqRm++p2vXrmHcuHFo0qQJZDIZnJ2d0bt3byQlVSxj7ty5M7Kzs2FjY1PLkRIREdHzQi96pC5duoSAgADY2tri008/RYsWLVBYWIht27YhKipKawmE0piYmEAulz+DaImIiOh5oRc9UmPHjoUgCDh48CD69esHT09PNGvWDDExMThw4IC63q1bt/Daa6/B3NwcHh4e2Lx5s/pccnIyBEFATk4OgEdLKtja2mLjxo3w8PCAqakpQkNDceXKFfU1x48fR3BwMKysrGBtbY02bdrg8OHDz+y5iYiIdMVAECV3SJHkE6l///0Xv//+O6KiomBhYaF1/sn5TrNmzcKAAQNw4sQJ9OzZExEREeVuFXP//n3Mnj0b33//PVJTU5GTk4M33nhDfT4iIgKNGjXCoUOHcOTIEUyfPh3GxsY1+nxERESkvyQ/tHf+/HmIoghvb+//rBsZGYlBgx5N7p4zZw4WLlyIgwcPIiwsrNT6hYWFWLRoETp06AAAWLFiBXx8fHDw4EG0b98eWVlZmDJlirptDw+PMttWqVRQqVQaZdxrj4iI9BXXkaoYyfdIVWZ1Bj8/P/XPFhYWsLa2xo0bN8qsb2RkhHbt2qk/e3t7w9bWFhkZGQCAmJgYjBw5EiEhIZg7dy4uXLhQ5r2USiVsbGw0DqVSWeHYiYiISP9IPpHy8PCAIAgVmlD+9LCbIAgoKSmpctszZ87EqVOn0KtXL+zatQu+vr7YsGFDqXUVCgVyc3M1DoVCUeW2iYiISPokn0jZ2dkhNDQUixcvRn5+vtb5x5PHq6KoqEhj8nhmZiZycnLg4+OjLvP09MTEiROxfft29O3bF/Hx8aXeSyaTwdraWuPg0B4REekrA0F6hxRJPpECgMWLF6O4uBjt27fHL7/8gnPnziEjIwMLFy5Ep06dqnxfY2NjjBs3DmlpaThy5AgiIyPRsWNHtG/fHg8ePEB0dDSSk5Nx+fJlpKam4tChQxpJFhERET3fJD/ZHACaNGmCo0ePYvbs2Zg0aRKys7Ph4OCANm3aYMmSJVW+r7m5OaZNm4bBgwfj6tWr6NKlC5YtWwYAMDQ0xO3btzFkyBBcv34d9erVQ9++fTFr1qyaeiwiIiLSc3qRSAGAk5MTFi1ahEWLFpV6vrRJ6U8O+wUFBZVap2/fvujbt69WuYmJCVavXl31gImIiPSYoa4D0BN6MbRHREREJEVMpIiIiIiqSBArs1ATERERPRfmpO/QdQhaZrTqrusQtOjNHKmqSk5ORnBwMO7cuaOxncyzUlBy5Jm3WRkmBm1g5jJI12GU6UHWagBndR3Gf/AEY6wJjLH6pB4fwBhriqeuA6D/T+dDe5GRkRAEAaNHj9Y6FxUVBUEQEBkZWWPtPd68uLTj2rVrNdYOERER1X2S6JFydnbGmjVrsGDBApiZmQEAHj58iFWrVsHFxaVW2szMzIS1tbVGWf369WulLSIiIn0j1QUwpUbnPVIA0Lp1azg7O2P9+vXqsvXr18PFxQX+/v7qspKSEiiVSri5ucHMzAwtW7bEzz//rHGv3377DZ6enjAzM0NwcDAuXbpUapv169eHXC7XOAwMHn0dxcXFiImJga2tLezt7TF16lQMHToU4eHhNf7sREREpL8kkUgBwPDhwzW2X1m+fDmGDRumUUepVOL777/H0qVLcerUKUycOBFvvvkmUlJSAABXrlxB37590bt3b6Snp2PkyJGYPn16pWOJi4tDQkICli9fjr179+Lff/8tc489IiIien5JYmgPAN58800oFApcvnwZAJCamoo1a9YgOTkZAKBSqTBnzhzs3LlTvS1MkyZNsHfvXnz99dcIDAzEkiVL0LRpU8TFxQEAvLy8cPLkScybN0+rvUaNGml8dnV1xalTpwAAn3/+ORQKhXqhzqVLl2Lbtm3lxq9SqaBSqTTKZDIZBOMyLiAiIpIwDu1VjGQSKQcHB/Tq1QsJCQkQRRG9evVCvXr11OfPnz+P+/fvo3t3zVcfCwoK1MN/GRkZ6NChg8b5svbi27NnD6ysrNSfjY0fZTy5ubnIzs7WuI+RkRHatm1b6srojymVSq3tY2JjYzHjw97lPTYRERHpMckkUsCj4b3o6GgAjzYqflJeXh4AYMuWLWjYsKHGOZlMVum23NzcanQ5BIVCgZiYGI2yR3H9WWNtEBERkbRIKpEKCwtDQUEBBEFAaGioxjlfX1/IZDJkZWUhMDCw1Ot9fHywefNmjbIDBw5UKgYbGxs4OTkhLS0NXbt2BQAUFRXhyJEjaN26dZnXyWSyUhO6gpJKNU9ERCQJhhzaqxBJJVKGhobIyMhQ//wkKysrTJ48GRMnTkRJSQlefPFF5ObmIjU1FdbW1hg6dChGjx6NuLg4TJkyBSNHjsSRI0eQkJBQals3btzAw4cPNcrs7e1hbGyMd999F3PnzoWHhwe8vb3x2WefaWyATERERARILJECoLW205M+/vhjODg4QKlU4q+//oKtrS1at26NGTNmAABcXFzwyy+/YOLEifjyyy/Rvn17zJkzB8OHD9e6l5eXl1bZ/v370bFjR0yaNAnZ2dkYOnQoDAwMMHz4cLz22mvIzc2tuQclIiIivce99iooMjISOTk52LhxY6Wu4xYx1cMtYmoKY6wZUo9R6vEBjLGm1P4WMQv+lN5eexObS2+vPcmsI0VERESkbyQ3tEdERES6ZyBwwKoiOLRHREREWr44tV3XIWh5t9nLug5BC3ukalnq9S26DqFcAY69IO25APoyV4ExVh9jrD6pxwcwxppS+3OkqGLqxByp/fv3w9DQEL169dJ1KERERHWCgSC9Q4rqRCK1bNkyjBs3Dn/88Qf++eefat2rsLCwhqIiIiKiuk7vE6m8vDysXbsWY8aMUe/V96RNmzahdevWMDU1RZMmTTBr1iwUFRWpzwuCgCVLluDVV1+FhYUFZs+eDQDqDZBNTEzg5eWFlStXPsvHIiIiIj2g94nUunXr4O3tDS8vL7z55ptYvny5enPhPXv2YMiQIXj33Xdx+vRpfP3110hISFAnS4/NnDkTr732Gk6ePInhw4djw4YNePfddzFp0iT8+eefeOeddzBs2DDs3r1bF49IRET0zBlK8JAivZ9svmzZMrz55psAHu3Vl5ubi5SUFAQFBWHWrFmYPn06hg4dCgBo0qQJPv74Y0ydOhWxsbHqewwePBjDhg1Tfx40aBAiIyMxduxYAEBMTAwOHDiA//3vfwgODi41DpVKBZVKpVFWlc2UiYiISH/odY9UZmYmDh48iEGDHq3MbWRkhIEDB2LZsmUAgOPHj+Ojjz6CpaWl+hg1ahSys7Nx//599X3atm2rcd+MjAwEBARolAUEBKj3ASyNUqmEjY2NxqFUKmvqUYmIiEiC9LpHatmyZSgqKkKDBg3UZaIoQiaTYdGiRcjLy8OsWbPQt29frWtNTU3VP1tYWFQ7FoVCgZiYGI0ymUyGwzk7q31vIiKiZ02qb8lJjd4mUkVFRfj+++8RFxeHl1/WXKArPDwcq1evRuvWrZGZmQl3d/dK3dvHxwepqanqIUEASE1Nha+vb5nXyGQyDuURERE9Z/Q2kUpMTMSdO3cwYsQI2NjYaJzr168fli1bhk8++QSvvPIKXFxc0L9/fxgYGOD48eP4888/8cknn5R57ylTpmDAgAHw9/dHSEgIfv31V6xfvx47d7J3iYiIiP6P3s6RWrZsGUJCQrSSKOBRInX48GE4OTkhMTER27dvR7t27dCxY0csWLAArq6u5d47PDwcX3zxBf73v/+hWbNm+PrrrxEfH4+goKBaehoiIiJpMRBEyR1SpLc9Ur/++muZ59q3b69eAsHPzw+hoaFl1i1rq8ExY8ZgzJgx1QuSiIiI6jS97ZEiIiIi0jW97ZEiIiKi2mPIt/YqRBDLGtsiIiKi59ayzG26DkHLCK+yp+roSp3pkRIEARs2bEB4eHip55OTkxEcHIw7d+7A1tb2mcWVV5j8zNqqCkvjIABndR1GOTwh7fgAxlhTGGP1ST0+APDEw+IDug6iXKaGHaEP3yNJg97Mkbp58ybGjBkDFxcXyGQyyOVyhIaGIjU1tULXd+7cGdnZ2aW+5UdERESaDATpHVKkNz1S/fr1Q0FBAVasWIEmTZrg+vXrSEpKwu3btyt0vYmJCeRyeS1HSURERM8TveiRysnJwZ49ezBv3jwEBwfD1dUV7du3h0KhwKuvvqqud+vWLbz22mswNzeHh4cHNm/erD6XnJwMQRCQk5MDAEhISICtrS02btwIDw8PmJqaIjQ0FFeuXFFfc/z4cQQHB8PKygrW1tZo06YNDh8+/Myem4iISFd03fukLz1SepFIPd5weOPGjVCpVGXWmzVrFgYMGIATJ06gZ8+eiIiIwL///ltm/fv372P27Nn4/vvvkZqaipycHLzxxhvq8xEREWjUqBEOHTqEI0eOYPr06TA2Nq7RZyMiIiL9pReJlJGRERISErBixQrY2toiICAAM2bMwIkTJzTqRUZGYtCgQXB3d8ecOXOQl5eHgwcPlnnfwsJCLFq0CJ06dUKbNm2wYsUK7Nu3T31NVlYWQkJC4O3tDQ8PD7z++uto2bJlqfdSqVS4e/euxlFe0kdERET6Ty8SKeDRHKl//vkHmzdvRlhYGJKTk9G6dWskJCSo6/j5+al/trCwgLW1NW7cuFHmPY2MjNCuXTv1Z29vb9ja2iIjIwMAEBMTg5EjRyIkJARz587FhQsXyryXUqmEjY2NxqFUKqvxxERERLqj62E8Du3VAlNTU3Tv3h0ffPAB9u3bh8jISMTGxqrPPz3sJggCSkpKqtzezJkzcerUKfTq1Qu7du2Cr68vNmzYUGpdhUKB3NxcjUOhUFS5bSIiIpI+vUqknubr64v8/PwqX19UVKQxeTwzMxM5OTnw8fFRl3l6emLixInYvn07+vbti/j4+FLvJZPJYG1trXHIZLIqx0ZERETSpxfLH9y+fRuvv/46hg8fDj8/P1hZWeHw4cOYP38++vTpU+X7GhsbY9y4cVi4cCGMjIwQHR2Njh07on379njw4AGmTJmC/v37w83NDX///TcOHTqEfv361eCTERERSZOhwI1PKkIvEilLS0t06NABCxYswIULF1BYWAhnZ2eMGjUKM2bMqPJ9zc3NMW3aNAwePBhXr15Fly5dsGzZMgCAoaEhbt++jSFDhuD69euoV68e+vbti1mzZtXUYxEREZGe04tESiaTQalUljt5u7QtAx+vGQUAQUFBpdbp27cv+vbtq1VuYmKC1atXVy1gIiIiei7oRSJFREREz5ZeT6J+hvg9EREREVWRIJY23kVERETPtTUXftd1CFreaBqm6xC01KmhvYSEBEyYMEFjbpSuBWzYq+sQypX62otIvb5F12GUKcCxF0rE07oOo1wGgi+As7oO4z94gjHWBKnHKPX4AMZYUzxrvQWpLoApNZIb2ouMjER4eHit3T8hIQGCIGgdpqamtdYmERER1U11qkeqoqytrZGZmalRJghMvYmIiKhyJNcjVZ7PPvsMLVq0gIWFBZydnTF27Fjk5eVp1du4cSM8PDxgamqK0NBQXLlyReO8IAiQy+Uah6Ojo/p8fn4+hgwZAktLSzg5OSEuLg5BQUGYMGFCbT8iERGRJOh6Xz3utVcLDAwMsHDhQpw6dQorVqzArl27MHXqVI069+/fx+zZs/H9998jNTUVOTk5eOONNyrVzpQpU5CSkoJNmzZh+/btSE5OxtGjR2vyUYiIiKgO0KuhvSd7hBo3boxPPvkEo0ePxldffaUuLywsxKJFi9ChQwcAwIoVK+Dj44ODBw+iffv2AIDc3FxYWlpq3LtLly7YunUr8vLysGzZMvzwww/o1q2b+h6NGjUqNzaVSgWVSqVRxr32iIiI6ja9SqR27twJpVKJM2fO4O7duygqKsLDhw9x//59mJubAwCMjIzQrl079TXe3t6wtbVFRkaGOpGysrLS6mEyMzMDAFy4cAEFBQXqRAwA7Ozs4OXlVW5sSqVSa/uY2NhYoGVI1R+YiIhIR7jXXsXoTSJ16dIlvPLKKxgzZgxmz54NOzs77N27FyNGjEBBQYE6kaoIAwMDuLu712h8CoUCMTExGmUymQw7fjtUo+0QERGRdOjNHKkjR46gpKQEcXFx6NixIzw9PfHPP/9o1SsqKsLhw4fVnzMzM5GTkwMfH58KtdO0aVMYGxsjLS1NXXbnzh2cPVv+miIymQzW1tYaB4f2iIiI6jZJ9kjl5uYiPT1do6xevXooLCzEl19+id69eyM1NRVLly7VutbY2Bjjxo3DwoULYWRkhOjoaHTs2FE9rAc82uD42rVrWtfWr18flpaWGDFiBKZMmQJ7e3vUr18f7733HgwM9CbnJCIiqjapviUnNZJMpJKTk+Hv769RNmLECHz22WeYN28eFAoFunbtCqVSiSFDhmjUMzc3x7Rp0zB48GBcvXoVXbp0wbJlyzTq3L17F05OTlrtZmdnQy6X49NPP0VeXh569+4NKysrTJo0Cbm5uTX/oERERKTXuNdeBQUFBaFVq1b4/PPPK3Udt4ipHm4RU1P0ZcsLxlg9Uo8PYIw1pfa3iPk1a2utt1FZvV166DoELRyvIiIiojpHqVSiXbt2sLKyQv369REeHq61q8nDhw8RFRUFe3t7WFpaol+/frh+/Xql2mEiRURERHVOSkoKoqKicODAAezYsQOFhYV4+eWXkZ+fr64zceJE/Prrr/jpp5+QkpKCf/75B3379q1UOxzaIyIiIi1brkhvaC+k/kulLn5dkbfkb968ifr16yMlJQVdu3ZFbm4uHBwcsGrVKvTv3x8AcObMGfj4+GD//v3o2LFjhWKS5GTzusTNf76uQyjXxWNTIe25APoyV0H6Me68+puugyhXSMOenA9XbfrxZ5Ex1oTanyMlRWUtfj1z5sz/vPbxS2N2dnYAHi2rVFhYiJCQ/1s429vbGy4uLpVKpCQ/tCcIQrlHRb48IiIi0n8KhQK5ubkah0Kh+M/rSkpKMGHCBAQEBKB58+YAgGvXrsHExAS2trYadR0dHUtdIqksku+Rys7OVv+8du1afPjhhxqTxZ7cM08URRQXF8PISPKPRUREJGmGElxHqqLDeE+LiorCn3/+ib17a/5Nesn3SMnlcvVhY2MDQRDUn8+cOQMrKyts3boVbdq0gUwmw969e3HhwgX06dMHjo6OsLS0RLt27bBz506N+zZu3Bhz5szB8OHDYWVlBRcXF3zzzTfq8wUFBYiOjoaTkxNMTU3h6uoKpVL5rB+fiIiIqiE6OhqJiYnYvXs3GjVqpC6Xy+UoKChATk6ORv3r169DLpdX+P6ST6QqYvr06Zg7dy4yMjLg5+eHvLw89OzZE0lJSTh27BjCwsLQu3dvZGVlaVwXFxeHtm3b4tixYxg7dizGjBmj7u1auHAhNm/ejHXr1iEzMxM//vgjGjdurIOnIyIiosoSRRHR0dHYsGEDdu3aBTc3N43zbdq0gbGxMZKSktRlmZmZyMrKQqdOnSrcTp0YA/voo4/QvXt39Wc7Ozu0bNlS/fnjjz/Ghg0bsHnzZkRHR6vLe/bsibFjxwIApk2bhgULFmD37t3w8vJCVlYWPDw88OKLL0IQBLi6upYbg0qlKvVNAiIiIn1kIOj3S/1RUVFYtWoVNm3aBCsrK/W8JxsbG5iZmcHGxgYjRoxATEwM7OzsYG1tjXHjxqFTp04VnmgO1JEeqbZt22p8zsvLw+TJk+Hj4wNbW1tYWloiIyNDq0fKz89P/fPjIcMbN24AACIjI5Geng4vLy+MHz8e27dvLzcGpVIJGxsbjYNDgURERLqxZMkS5ObmIigoCE5OTupj7dq16joLFizAK6+8gn79+qFr166Qy+VYv359pdqpEz1SFhYWGp8nT56MHTt24H//+x/c3d1hZmaG/v37o6CgQKOesbGxxmdBEFBSUgIAaN26NS5evIitW7di586dGDBgAEJCQvDzzz+XGoNCoUBMTIxGmUwmw4pNX1T38YiIiKiSKrJMpqmpKRYvXozFixdXuZ06kUg9LTU1FZGRkXjttdcAPOqhunTpUqXvY21tjYEDB2LgwIHo378/wsLC8O+//6rXoHhSVd8kICIikqI6MWT1DNTJRMrDwwPr169H7969IQgCPvjgA3VPU0V99tlncHJygr+/PwwMDPDTTz9BLpdrrTdBREREz686mUh99tlnGD58ODp37ox69eph2rRpuHv3bqXuYWVlhfnz5+PcuXMwNDREu3bt8Ntvv8HAgDk6ERERPcK99moZt4ipLn3ZqkH6MXKLmOrjFjE1gTHWjNrfImbXP9L7d8ZLDXrqOgQt7F4hIiIiqiImUkRERERVxKE9IiIi0pKSLb2hvUAn6Q3t1cnJ5pcuXYKbmxuOHTuGVq1a6TQW957xOm3/v5z/bRikPRdAX+YqMMbqY4zVJ/X4AMZYU2p/jhRVjGSH9gRBKPeYOXOmrkMkIiKi55xke6Sys7PVP69duxYffvihekNhALC0tNRFWERERM8Ffd9r71mRbI+UXC5XHzY2Nuq98B4fa9asgY+PD0xNTeHt7Y2vvvqq3PudOnUKr7zyCqytrWFlZYUuXbrgwoULAB7tqxceHo45c+bA0dERtra2+Oijj1BUVIQpU6bAzs4OjRo1Qny8tIfpiIiI6NmSbI9UeX788Ud8+OGHWLRoEfz9/XHs2DGMGjUKFhYWGDp0qFb9q1evomvXrggKCsKuXbtgbW2N1NRUFBUVqevs2rULjRo1wh9//IHU1FSMGDEC+/btQ9euXZGWloa1a9finXfeQffu3dGoUaNn+bhERETPnIGg6wj0g14mUrGxsYiLi0Pfvn0BAG5ubjh9+jS+/vrrUhOpxYsXw8bGBmvWrFFvVOzpqTlRz87ODgsXLoSBgQG8vLwwf/583L9/HzNmzADwaFPiuXPnYu/evXjjjTe02lCpVFCpVBpl3HuPiIiobpPs0F5Z8vPzceHCBYwYMQKWlpbq45NPPlEP1T0tPT0dXbp0USdRpWnWrJnG9i+Ojo5o0aKF+rOhoSHs7e1x48aNUq9XKpWwsbHROJRKZRWfkoiIiPSB3vVI5eXlAQC+/fZbdOjQQeOcoaFhqdeYmZn9532fTrIEQSi1rKzNjxUKBWJiYjTKZDIZfnht1X+2TUREJDUc2qsYvUukHB0d0aBBA/z111+IiIio0DV+fn5YsWIFCgsLy+2Vqg6ZTMahPCIioueM3g3tAcCsWbOgVCqxcOFCnD17FidPnkR8fDw+++yzUutHR0fj7t27eOONN3D48GGcO3cOK1eu1FhOgYiIiKiy9DKRGjlyJL777jvEx8ejRYsWCAwMREJCAtzc3Eqtb29vj127diEvLw+BgYFo06YNvv3221rrnSIiItJ3BhI8pIh77dUybhFTXfqyVQNjrD7GWH1Sjw9gjDWl9reISbuxpdbbqKwO9XvpOgQtUk3wiIiIiCRP7yabExERUe0T+NZehXBoj4iIiLQcvCm9ob32DtIb2mOPVCkuXboENzc3HDt2DK1atUJycjKCg4Nx584d2NraVupeLl+k1E6QNSTr3UBIey6AvsxVYIzVxxirT+rxAYyxptT+HCmqmDo9RyooKAgTJkzQKk9ISFAnRI83LH6Ss7MzsrOz0bx589oPkoiISIIECR5SxB6pUhgaGkIul+s6DCIiIpK4Ot0j9V9mzpyJFStWYNOmTRAEAYIgIDk5GZcuXYIgCEhPT9d1iERERCRhz3WP1OTJk5GRkYG7d+8iPv7Rek92dnb4559/dBwZERGRbvGtvYp5rhMpS0tLmJmZQaVSVXsoT6VSQaVSaZRx7z0iIqK67bke2qtJSqUSNjY2GodSqdR1WERERFSL6nQiZW1tjdzcXK3ynJwc2NjY1GhbCoUCubm5GodCoajRNoiIiJ4VXe+rpy977dXpoT0vLy9s375dq/zo0aPw9Hy0BoeJiQmKi4ur3ZZMJuNQHhER0XNGqglejRgzZgzOnj2L8ePH48SJE8jMzMRnn32G1atXY9KkSQCAxo0bq8/dunULhYWFOo6aiIhI9wRBlNwhRXU6kWrSpAn++OMPnDlzBiEhIejQoQPWrVuHn376CWFhYQCAUaNGwcvLC23btoWDgwNSU1N1HDURERHpizo9tAcA7dq1K3V47zEHB4dSzz+5BWFQUBC4JSERERE9rc4nUkRERFR5XEaqYur00B4RERFRbRJEjlkRERHRU9JvJ+o6BC2t7F/RdQha6uzQniAI2LBhA8LDw0s9n5ycjODgYNy5cwe2trbl3qsydZ/m3jO+UvWftfO/DUNRyXFdh1EmI4OWuP5gs67DKJej2auS/g6BR98jcFbXYfwHT734HqUco778nhljTfCs9Ra4RUzFSH5ob+nSpbCyskJRUZG6LC8vD8bGxggKCtKom5ycDEEQcOHChWccJRERET2PJJ9IBQcHIy8vD4cPH1aX7dmzB3K5HGlpaXj48KG6fPfu3XBxcUHTpk11ESoRERE9ZySfSHl5ecHJyQnJycnqsuTkZPTp0wdubm44cOCARnlwcLD6861bt/Daa6/B3NwcHh4e2Ly57CGiy5cvo3fv3njhhRdgYWGBZs2a4bfffquVZyIiIpI6QYKHFEk+kQIe9Urt3r1b/Xn37t0ICgpCYGCguvzBgwdIS0vTSKRmzZqFAQMG4MSJE+jZsyciIiLw77//ltpGVFQUVCoV/vjjD5w8eRLz5s2DpaVl7T4YERER6TW9SaRSU1NRVFSEe/fu4dixYwgMDETXrl3VPVX79++HSqXSSKQiIyMxaNAguLu7Y86cOcjLy8PBgwdLbSMrKwsBAQFo0aIFmjRpgldeeQVdu3atcIwqlQp3797VOFQqVbWem4iIiKRNLxKpoKAg5Ofn49ChQ9izZw88PT3h4OCAwMBA9Typ5ORkNGnSBC4uLurr/Pz81D9bWFjA2toaN27cKLWN8ePH45NPPkFAQABiY2Nx4sSJSsWoVCphY2OjcSiVyqo9MBERkY4ZCNI7pEgvEil3d3c0atQIu3fvxu7duxEYGAgAaNCgAZydnbFv3z7s3r0bL730ksZ1xsbGGp8FQUBJSUmpbYwcORJ//fUX3nrrLZw8eRJt27bFl19+WeEYFQoFcnNzNQ6FQlHJJyUiIiJ9oheJFPBoeC85ORnJyckayx507doVW7duxcGDBzWG9arC2dkZo0ePxvr16zFp0iR8++23Fb5WJpPB2tpa45DJZNWKh4iIiKRNbxbkDA4ORlRUFAoLC9U9UgAQGBiI6OhoFBQUVCuRmjBhAnr06AFPT0/cuXMHu3fvho+PT02ETkREpHckOpImOXqVSD148ADe3t5wdHRUlwcGBuLevXvqZRKqqri4GFFRUfj7779hbW2NsLAwLFiwoCZCJyIiojpKbxKpxo0bo7RtAV1dXUstL60sJydH/XNQUJBGnfLmQz1dl4iIiAjQo0SKiIiInh3utVcxejPZnIiIiEhqBJFjVkRERPSU0zmJug5Bi6/tK7oOQQuH9sogCAI2bNiA8PBwXLp0CW5ubjh27BhatWpVqfuYuQyqnQBryIOs1QDO6jqMcniioOSIroMol4lBG5SIp3UdRrkMBF9I+/cMAJ78HqvNE9KODwA8UVRyXNdBlMvIoCX04XusbRzZqxi9HtqLjIyEIAgQBAHGxsZwc3PD1KlT8fDhQwDApUuXIAgC0tPTK33v7Oxs9OjRo4YjJiIiorpE73ukwsLCEB8fj8LCQhw5cgRDhw6FIAiYN29ete4rl8trKEIiIiL9wx6pitHrHing0Yricrkczs7OCA8PR0hICHbs2AEAcHNzAwD4+/tDEAT1iuiHDh1C9+7dUa9ePdjY2CAwMBBHjx7VuK8gCNi4ceOzfBQiIiLSM3qfSD3pzz//xL59+2BiYgIAOHjwIABg586dyM7Oxvr16wEA9+7dw9ChQ7F3714cOHAAHh4e6NmzJ+7du6ez2ImIiEj/6P3QXmJiIiwtLVFUVASVSgUDAwMsWrQIAODg4AAAsLe31xiqe3pz42+++Qa2trZISUnBK69U7Y0AlUoFlUqlUca99oiISF8ZcGyvQvS+Ryo4OBjp6elIS0vD0KFDMWzYMPTr16/ca65fv45Ro0bBw8MDNjY2sLa2Rl5eHrKysqoch1KphI2NjcahVCqrfD8iIiKSPr1PpCwsLODu7o6WLVti+fLlSEtLw7Jly8q9ZujQoUhPT8cXX3yBffv2IT09Hfb29igoKKhyHAqFArm5uRqHQqGo8v2IiIhI+vR+aO9JBgYGmDFjBmJiYjB48GD1XKni4mKNeqmpqfjqq6/Qs2dPAMCVK1dw69atarUtk8k4lEdERHUGR/YqRu97pJ72+uuvw9DQEIsXL0b9+vVhZmaG33//HdevX0dubi4AwMPDAytXrkRGRgbS0tIQEREBMzMzHUdORERE+qbOJVJGRkaIjo7G/PnzoVKpsHDhQnz99ddo0KAB+vTpAwBYtmwZ7ty5g9atW+Ott97C+PHjUb9+fR1HTkRERPqGe+3VMm4RU13cIqYmSH9rE4BbxNQEbhFTE7hFzCPn7/5a621Ulrt1b12HoKXO9UgRERERPStMpIiIiIiqiEN7REREpOWCBIf2mkpwaK9OLX9QHZGRkcjJyanx/fWaDlpVo/eraRdWD4a05wJwPkXN0I+5M4yxuqQeH8AYa0rtz5GiipHs0F5kZCQEQcDo0aO1zkVFRUEQBERGRj77wIiIiIj+P8kmUgDg7OyMNWvW4MGDB+qyhw8fYtWqVXBxcdFhZERERHWbIEjvkCJJJ1KtW7eGs7Mz1q9fry5bv349XFxc4O/vry4rKSmBUqmEm5sbzMzM0LJlS/z888/q88XFxRgxYoT6vJeXF7744oty2/7555/RokULmJmZwd7eHiEhIcjPz6/5hyQiIiK9JelECgCGDx+O+Ph49efly5dj2LBhGnWUSiW+//57LF26FKdOncLEiRPx5ptvIiUlBcCjRKtRo0b46aefcPr0aXz44YeYMWMG1q1bV2qb2dnZGDRoEIYPH46MjAwkJyejb9++4Lx8IiIiepLkJ5u/+eabUCgUuHz5MoBH++StWbMGycnJAACVSoU5c+Zg586d6NSpEwCgSZMm2Lt3L77++msEBgbC2NgYs2bNUt/Tzc0N+/fvx7p16zBgwACtNrOzs1FUVIS+ffvC1dUVANCiRYty41SpVFCpVBpl3HuPiIj0leR7WiRC8omUg4MDevXqhYSEBIiiiF69eqFevXrq8+fPn8f9+/fRvXt3jesKCgo0hv8WL16M5cuXIysrCw8ePEBBQQFatWpVapstW7ZEt27d0KJFC4SGhuLll19G//798cILL5QZp1Kp1EjWACA2NhZ8s4KIiKjuknwiBTwa3ouOjgbwKCF6Ul5eHgBgy5YtaNiwoca5xz1Ca9asweTJkxEXF4dOnTrBysoKn376KdLS0kptz9DQEDt27MC+ffuwfft2fPnll3jvvfeQlpYGNze3Uq9RKBSIiYnRan9l5C+Vf2AiIiIdk+rkbqnRi0QqLCwMBQUFEAQBoaGhGud8fX0hk8mQlZWFwMDAUq9PTU1F586dMXbsWHXZhQsXym1TEAQEBAQgICAAH374IVxdXbFhwwatZOkxmUzGoTwiIqLnjF4kUoaGhsjIyFD//CQrKytMnjwZEydORElJCV588UXk5uYiNTUV1tbWGDp0KDw8PPD9999j27ZtcHNzw8qVK3Ho0KEye5fS0tKQlJSEl19+GfXr10daWhpu3rwJHx+fWn9WIiIi0h96kUgBgLW1dZnnPv74Yzg4OECpVOKvv/6Cra0tWrdujRkzZgAA3nnnHRw7dgwDBw6EIAgYNGgQxo4di61bt5bZ1h9//IHPP/8cd+/ehaurK+Li4tCjR49aeTYiIiKp4chexXCvvVrGLWKqi1vE1Ax92fKCMVaP1OMDGGNNqf0XmbLypLfXnoul9Pba49uNRERERFWkN0N7RERE9Ozwrb2K4dAeERERabmSL72hPWcL6Q3tPbc9UkFBQWjVqhU+//zzWm3HzGVQrd6/uh5krYa05wLoy1wFxlh9jLH6pB4fwBhrChd7lgrJzZGKjIyEIAjqw97eHmFhYThx4oSuQyMiInpuCBI8pEhyiRTwaAHO7OxsZGdnIykpCUZGRnjllVd0HRYRERGRBkkmUjKZDHK5HHK5HK1atcL06dNx5coV3Lx5EwAwbdo0eHp6wtzcHE2aNMEHH3yAwsJC9fUzZ85Eq1atsHLlSjRu3Bg2NjZ44403cO/evTLb3LJlC2xsbPDjjz8CAJKTk9G+fXtYWFjA1tYWAQEB6o2TiYiIiAA9mCOVl5eHH374Ae7u7rC3twfwaDXzhIQENGjQACdPnsSoUaNgZWWFqVOnqq+7cOECNm7ciMTERNy5cwcDBgzA3LlzMXv2bK02Vq1ahdGjR2PVqlV45ZVXUFRUhPDwcIwaNQqrV69GQUEBDh48CIGvMBAR0XPCgP/JqxBJJlKJiYmwtLQEAOTn58PJyQmJiYkwMHjUgfb++++r6zZu3BiTJ0/GmjVrNBKpkpISJCQkwMrKCgDw1ltvISkpSSuRWrx4Md577z38+uuv6r367t69i9zcXLzyyito2rQpAPzn9jAqlQoqlUqjjHvvERER1W2STKSCg4OxZMkSAMCdO3fw1VdfoUePHjh48CBcXV2xdu1aLFy4EBcuXEBeXh6Kioq0tpBp3LixOokCACcnJ9y4cUOjzs8//4wbN24gNTUV7dq1U5fb2dkhMjISoaGh6N69O0JCQjBgwAA4OTmVGbNSqcSsWbM0ymJjY6v8HRAREZH0SXKOlIWFBdzd3eHu7o527drhu+++Q35+Pr799lvs378fERER6NmzJxITE3Hs2DG89957KCgo0LiHsbGxxmdBEFBSUqJR5u/vDwcHByxfvhxPL6cVHx+P/fv3o3Pnzli7di08PT1x4MCBMmNWKBTIzc3VOBQKRTW/CSIiIt3Q9Rt6+vLWniR7pJ4mCAIMDAzw4MED7Nu3D66urnjvvffU56s6Cbxp06aIi4tDUFAQDA0NsWjRIo3z/v7+8Pf3h0KhQKdOnbBq1Sp07Nix1HvJZDIO5RERET1nJJlIqVQqXLt2DcCjob1FixYhLy8PvXv3xt27d5GVlYU1a9agXbt22LJlCzZs2FDltjw9PbF7924EBQXByMgIn3/+OS5evIhvvvkGr776Kho0aIDMzEycO3cOQ4YMqalHJCIiojpAkonU77//rp6PZGVlBW9vb/z0008ICgoCAEycOBHR0dFQqVTo1asXPvjgA8ycObPK7Xl5eWHXrl3qnqmpU6fizJkzWLFiBW7fvg0nJydERUXhnXfeqYGnIyIikj5B4A5yFcG99moZt4ipLn3ZqoExVh9jrD6pxwcwxppS+1vEXHuwudbbqCy52asVrvvHH3/g008/xZEjR5CdnY0NGzYgPDxcfV4URcTGxuLbb79FTk4OAgICsGTJEnh4eFQqJklONiciIiKqjvz8fLRs2RKLFy8u9fz8+fOxcOFCLF26FGlpabCwsEBoaCgePnxYqXYkObRHREREuiXFt+TKWrOxtJe9evTogR49epR6H1EU8fnnn+P9999Hnz59AADff/89HB0dsXHjRrzxxhsVjomJVC17NHQmdVLfRVzq8QGMsaYwxuqTenwAY6SqKmvNxsrOk7548SKuXbuGkJAQdZmNjQ06dOiA/fv3M5GqrKCgILRq1Qqff/55jd9bH+ZIlYindR1GmQwEXxSUHNF1GOUyMWgD/ZhPwRirT+oxSj0+gDHWlNpP9KS4K5pCoUBMTIxGWVWWHnq8MoCjo6NGuaOjo/pcRT1XiVRkZCRWrFihVZ6WlvafW8AQERGRbklxzcbnbrJ5WFgYsrOzNY42bdpobCdDREREdZdcLgcAXL9+XaP8+vXr6nMV9dwlUjKZDHK5XOPo1q0bJkyYoK7TuHFjzJkzB8OHD4eVlRVcXFzwzTff6C5oIiKiZ0zX28HU5hYxbm5ukMvlSEpKUpfdvXsXaWlp6NSpU6Xu9dwlUhUVFxeHtm3b4tixYxg7dizGjBmDzMxMXYdFREREFZCXl4f09HSkp6cDeDTBPD09HVlZWRAEARMmTMAnn3yCzZs34+TJkxgyZAgaNGigsdZURTxXc6QAIDExEZaWlurPZb0a2bNnT4wdOxYAMG3aNCxYsAC7d++Gl5dXqfXLeiWTiIiInr3Dhw8jODhY/fnxJPWhQ4ciISEBU6dORX5+Pt5++23k5OTgxRdfxO+//w5TU9NKtfPcJVLBwcFYsmSJ+rOFhQUGDdJ+s87Pz0/9syAIkMvluHHjRpn3LeuVTCIiIn2k70NWQUFBKG/zFkEQ8NFHH+Gjjz6qVjvPXSJlYWEBd3f3/6xnbGys8VkQBJSUlJRZv6xXMuctj6xSnERERCR9z10iVVuk+EomERER1S4mUkRERKRFigtySpG+D4ESERER6cxz1SOVkJBQanlycrLG50uXLmnVefz6JBEREdFjz1UiRURERBXFsb2K4NAeERERURUJYnmLLBAREdFz6V/Vr7oOQYudrLeuQ9DCob1aZuaivdinlDzIWg3grK7DKIcnpB0fwBhrCmOsPqnHBzDGmuJZ6y0IHNqrEL0b2ouMjKz0PjhEREREtUHvEildKyws1HUIREREJBF6nUgFBQVh/PjxmDp1Kuzs7CCXyzFz5kz1eVEUMXPmTLi4uEAmk6FBgwYYP368+rwgCNi4caPGPW1tbdXLJFy6dAmCIGDt2rUIDAyEqakpfvzxx2fwZERERLolCAaSO6RI7+dIrVixAjExMUhLS8P+/fsRGRmJgIAAdO/eHb/88gsWLFiANWvWoFmzZrh27RqOHz9e6TamT5+OuLg4+Pv7V3pXaCIiIqq79D6R8vPzQ2xsLADAw8MDixYtQlJSErp3746srCzI5XKEhITA2NgYLi4uaN++faXbmDBhAvr27VtuHZVKBZVKpVHGvfeIiIjqNmn2k1WCn5+fxmcnJyfcuHEDAPD666/jwYMHaNKkCUaNGoUNGzagqKio0m20bdv2P+solUrY2NhoHEqlstJtERERSYMgwUN69D6RMjY21vgsCAJKSkoAAM7OzsjMzMRXX30FMzMzjB07Fl27dlVPGBcEAU8vo1XaZHILC4v/jEOhUCA3N1fjUCgUVX0sIiIi0gN6P7T3X8zMzNC7d2/07t0bUVFR8Pb2xsmTJ9G6dWs4ODggOztbXffcuXO4f/9+ldqRyWQcyiMiojqD60hVTJ1OpBISElBcXIwOHTrA3NwcP/zwA8zMzODq6goAeOmll7Bo0SJ06tQJxcXFmDZtmlYPFxEREVFZ9H5orzy2trb49ttvERAQAD8/P+zcuRO//vor7O3tAQBxcXFwdnZGly5dMHjwYEyePBnm5uY6jpqIiIj0Bffaq2XcIqa69GWrBsZYfYyx+qQeH8AYa0rtbxGTW7Ct1tuoLBuTUF2HoKVO90gRERER1SYmUkRERERVxKE9IiIi0nK3cIeuQ9Bibdxd1yFoqXNv7V26dAlubm44duwYWrVqpetwEJiYqusQypXySgCKSiq/bc6zYmTQEvoxV4ExVp8nSsTTug6iXAaCL6T9PerH75kx1oTanyNFFaN3Q3uRkZEQBAGCIMDY2Bhubm6YOnUqHj58WGr9xxsPl3YcOHDgP9tLSEiAra1tDT8FERER1QV62SMVFhaG+Ph4FBYW4siRIxg6dCgEQcC8efPKvGbnzp1o1qyZRtnjZRCIiIjoaVyQsyL0rkcKeLSKuFwuh7OzM8LDwxESEoIdO8ofy7W3t4dcLtc4Hi++efz4cQQHB8PKygrW1tZo06YNDh8+jOTkZAwbNgy5ubnqXqyZM2c+gyckIiIifaCXPVJP+vPPP7Fv3z71auVVERERAX9/fyxZsgSGhoZIT0+HsbExOnfujM8//xwffvghMjMzAQCWlpY1FToRERHpOb1MpBITE2FpaYmioiKoVCoYGBhg0aJF5V7TuXNnGBhodsDl5eUBALKysjBlyhR4e3sDADw8PNR1bGxsIAgC5HJ5ufdXqVRQqVQaZdx7j4iI9BX32qsYvUykgoODsWTJEuTn52PBggUwMjJCv379yr1m7dq18PHxKfVcTEwMRo4ciZUrVyIkJASvv/46mjZtWqmYlEolZs2apVEWGxsLtJXeq5pERERUM/RyjpSFhQXc3d3RsmVLLF++HGlpaVi2bFm51zg7O8Pd3V3jeGzmzJk4deoUevXqhV27dsHX1xcbNmyoVEwKhQK5ubkah0KhqNLzERERkX7Qy0TqSQYGBpgxYwbef/99PHjwoMr38fT0xMSJE7F9+3b07dsX8fHxAAATExMUFxf/5/UymQzW1tYaB4f2iIhIXwkS/EeK9D6RAoDXX38dhoaGWLx4cZl1bt++jWvXrmkcDx8+xIMHDxAdHY3k5GRcvnwZqampOHTokHoYsHHjxsjLy0NSUhJu3bqF+/fvP6vHIiIiIomrE4mUkZERoqOjMX/+fOTn55daJyQkBE5OThrHxo0bYWhoiNu3b2PIkCHw9PTEgAED0KNHD/V8p86dO2P06NEYOHAgHBwcMH/+/Gf5aERERCRh3GuvlnGLmOrhFjE1RT9i5BYx1aUfv2fGWBNqf4uYvMLkWm+jsiyNg3QdgpY60SNFREREpAt6ufwBERER1S5BkObkbqnh0B4RERFpyS9K0XUIWiyMAnUdghb2SNWyyD+k9wfxSQldAyHtuQD6MleBMVaffsQo5Xlc0p/DBejL71k/YiQpkPQcqcjISPVmwSYmJnB3d8dHH32EoqKiKt/z/v37UCgUaNq0KUxNTeHg4IDAwEBs2rSpBiMnIiLSd4IED+mRfI9UWFgY4uPjoVKp8NtvvyEqKgrGxsaVXjW8uLgYgiBg9OjRSEtLw5dffglfX1/cvn0b+/btw+3bt2vpCYiIiKiuknSPFPBoxXC5XA5XV1eMGTMGISEh2Lx5M1QqFSZPnoyGDRvCwsICHTp0QHJysvq6hIQE2NraYvPmzfD19YVMJkNWVhY2b96MGTNmoGfPnmjcuDHatGmDcePGYfjw4QCAGTNmoEOHDlpxtGzZEh999NGzemwiIiLSA5JPpJ5mZmaGgoICREdHY//+/VizZg1OnDiB119/HWFhYTh37py67v379zFv3jx89913OHXqFOrXrw+5XI7ffvsN9+7dK/X+EREROHjwIC5cuKAuO3XqFE6cOIHBgwfX+vMRERFJga63g+EWMTVMFEXs3LkT27Ztg5+fH+Lj4/HTTz+hS5cuaNq0KSZPnowXX3xRvUceABQWFuKrr75C586d4eXlBXNzc3zzzTfYt28f7O3t0a5dO0ycOBGpqf+3aGazZs3QsmVLrFq1Sl32448/okOHDhobHT9NpVLh7t27GodKpaqdL4OIiIgkQfKJVGJiIiwtLWFqaooePXpg4MCB6N+/P4qLi+Hp6QlLS0v1kZKSotGTZGJiAj8/P437de3aFX/99ReSkpLQv39/nDp1Cl26dMHHH3+srhMREaFOpERRxOrVqxEREVFunEqlEjY2NhqHUqmswW+CiIiIpEbyk82Dg4OxZMkSmJiYoEGDBjAyMsLatWthaGiII0eOwNDQUKO+paWl+mczM7NSFxQzNjZGly5d0KVLF0ybNg2ffPIJPvroI0ybNg0mJiYYNGgQpk2bhqNHj+LBgwe4cuUKBg4cWG6cCoUCMTExGmUymQzvpB2oxtMTERHpiuT7WiRB8omUhYWF1pCav78/iouLcePGDXTp0qXabfj6+qKoqAgPHz6EiYkJGjVqhMDAQPz444948OABunfvjvr165d7D5lMBplMVu1YiIiISH9IPpEqjaenJyIiIjBkyBDExcXB398fN2/eRFJSEvz8/NCrV68yrw0KCsKgQYPQtm1b2Nvb4/Tp05gxYwaCg4NhbW2trhcREYHY2FgUFBRgwYIFz+KxiIiISM/obb9dfHw8hgwZgkmTJsHLywvh4eE4dOgQXFxcyr0uNDQUK1aswMsvvwwfHx+MGzcOoaGhWLdunUa9/v374/bt27h//z7Cw8Nr8UmIiIikR9dv6OnLW3vca6+WcYuY6tKXrRoYY/XpR4zcIqa69OP3rB8x1q4HRftqvY3KMjPqrOsQtOhtjxQRERGRrunlHCkiIiKqXaW99U7aOLRHREREWh4W79d1CFpMDTvpOgQtz0WP1DfffIOPP/4YV69exWeffYYJEyY8s7bNXAY9s7aq4kHWauQVJus6jDJZGgdBP+YqMMbq80RRyXFdB1EuI4OWkPb3qB+/Z8ZYE2p/jhRVjOTnSN28eRNjxoyBi4uLegPj0NBQjW1dynP37l1ER0dj2rRpuHr1Kt5++20EBQU902SKiIhI/wgSPKRH8j1S/fr1Q0FBAVasWIEmTZrg+vXrSEpKwu3btyt0fVZWFgoLC9GrVy84OTnVcrRERET0PJF0j1ROTg727NmDefPmITg4GK6urmjfvj0UCgVeffVVAI8SpT59+sDS0hLW1tYYMGAArl+/DgBISEhAixYtAABNmjSBIAiIjIxESkoKvvjiCwiCAEEQcOnSJbRt2xb/+9//1G2Hh4fD2NgYeXl5AIC///4bgiDg/Pnzz/hbICIiIqmSdCL1eDPijRs3QqVSaZ0vKSlBnz598O+//yIlJQU7duzAX3/9pd4Xb+DAgdi5cycA4ODBg8jOzsYXX3yBTp06YdSoUcjOzkZ2djacnZ0RGBiI5ORkAI82Kt6zZw9sbW2xd+9eAEBKSgoaNmyotV0NERFRXSTAQHKHFEkzqv/PyMgICQkJWLFiBWxtbREQEIAZM2bgxIkTAICkpCScPHkSq1atQps2bdChQwd8//33SElJwaFDh2BmZgZ7e3sAgIODA+RyOWxsbGBiYgJzc3PI5XLI5XIYGhoiKCgIe/fuRXFxMU6cOAETExNERESok6vk5GQEBgaWGatKpcLdu3c1jtKSPyIiIqo7JJ1IAY/mSP3zzz/YvHkzwsLCkJycjNatWyMhIQEZGRlwdnaGs7Ozur6vry9sbW2RkZFRqXa6dOmCe/fu4dixY0hJSUFgYCCCgoLUiVRKSgqCgoLKvF6pVMLGxkbjUCqVVXlkIiIiCdD1xHL9mGwu+UQKAExNTdG9e3d88MEH2LdvHyIjIxEbG1ujbdja2qJly5ZITk5WJ01du3bFsWPHcPbsWZw7d67cHimFQoHc3FyNQ6FQ1GiMREREJC16kUg9zdfXF/n5+fDx8cGVK1dw5coV9bnTp08jJycHvr6+ZV5vYmKC4uJirfLAwEDs3r0bf/zxB4KCgmBnZwcfHx/Mnj0bTk5O8PQse90OmUwGa2trjUMmk1XvQYmIiEjSJJ1I3b59Gy+99BJ++OEHnDhxAhcvXsRPP/2E+fPno0+fPggJCUGLFi0QERGBo0eP4uDBgxgyZAgCAwPRtm3bMu/buHFjpKWl4dKlS7h16xZKSkoAAEFBQdi2bRuMjIzg7e2tLvvxxx/L7Y0iIiKqax6/2S6lQ4oknUhZWlqiQ4cOWLBgAbp27YrmzZvjgw8+wKhRo7Bo0SIIgoBNmzbhhRdeQNeuXRESEoImTZpg7dq15d538uTJMDQ0hK+vLxwcHJCVlQXg0TypkpISjaQpKCgIxcXF5c6PIiIioucT99qrZdwipnq4RUxN0Y8YuUVMdenH75kx1oTa3yKmoORwrbdRWSYGZY826YrkVzYnIiIiXZDmUJrUSHpoj4iIiEjKOLRHREREWgpKjug6BC0mBm10HYIWDu3Vsjar9+g6hHIdGdQF0p4LoC9zFRhj9THG6pN6fABjrCm1P0dKqluySE2d/ZYiIyNLfXWSmw4TERFRTanTPVJhYWGIj4/XKHNwcNBRNERERFTX1OlESiaTQS6Xa5RFRkYiJycHGzduVJdNmDAB6enp6n31goKC4OfnB1NTU3z33XcwMTHB6NGjMXPmzGcXPBERkU7xrb2KqLNDe9W1YsUKWFhYIC0tDfPnz8dHH32EHTt26DosIiIikpA63SOVmJgIS0tL9ecePXrAwsKiQtf6+fmpN0b28PDAokWLkJSUhO7du5daX6VSQaVSaZRxrz0iIqK6rU73SAUHByM9PV19LFy4sMLX+vn5aXx2cnLCjRs3yqyvVCphY2OjcSiVyirHTkREpEuCBP+RojrdI2VhYQF3d3eNMgMDAzy9dFZhYaHWtcbGxhqfBUFQb25cGoVCgZiYGI0ymUyGX9cfrGzYREREpCfqdCJVGgcHB/z5558aZenp6VqJU2XJZDIO5RERET1n6vTQXmleeuklHD58GN9//z3OnTuH2NhYrcSKiIjoeVfaWoy6PqTouUukQkND8cEHH2Dq1Klo164d7t27hyFDhug6LCIiItJD3GuvlnGLmOrSl60aGGP1Mcbqk3p8AGOsKbW/RUyxeKLW26gsQ8Hvvys9Y8/dHCkiIiKqiOdu0KpK+C0RERERVRGH9oiIiEhLiXhK1yFoMRCa6ToELc/V0F5CQgImTJiAnJyccusJgoANGzYgPDy82m02HbSq2veoTRdWD8bf+b/qOowyNbLoDf2Yq8AYq48xVp/U4wMYY02p/TlSVDF1ZmgvMjKy1MQnOTkZgiCUmjzNnDkTrVq1qvXYiIiIqG56rnqkiIiIqKKkuW6T1NSZHqnKSkhIwKxZs3D8+HH1Ql8JCQnq87du3cJrr70Gc3NzeHh4YPPmzboLloiIiCTpuU2kBg4ciEmTJqFZs2bIzs5GdnY2Bg4cqD4/a9YsDBgwACdOnEDPnj0RERGBf//9V4cRExERkdTUqaG9xMREWFpaapQVFxeXWtfMzAyWlpYwMjKCXC7XOh8ZGYlBgwYBAObMmYOFCxfi4MGDCAsLK/V+KpUKKpVKo4x77xERkb6S6pYsUlOneqSCg4ORnp6ucXz33XdVupef3/+tnmphYQFra2vcuHGjzPpKpRI2NjYah1KprFLbREREpB/qVI+UhYUF3N3dNcr+/vvvKt3L2NhY47MgCCgpKSmzvkKhQExMjEaZTCbDyshfqtQ+ERERSV+dSqQqy8TEpMyhv8qSyWQcyiMiojqkTg1a1Zrn+ltq3LgxLl68iPT0dNy6dUtrjhMRERFReZ7rRKpfv34ICwtDcHAwHBwcsHr1al2HRERERDVo8eLFaNy4MUxNTdGhQwccPHiwRu/PvfZqGbeIqR5uEVNTGGPNkHqMUo8PYIw15VlsESPF76Byz7127VoMGTIES5cuRYcOHfD555/jp59+QmZmJurXr18jET3XPVJERERUd3322WcYNWoUhg0bBl9fXyxduhTm5uZYvnx5jbXBRIqIiIj0gkqlwt27dzWOsuY3FxQU4MiRIwgJCVGXGRgYICQkBPv376+5oETSCw8fPhRjY2PFhw8f6jqUMjHGmiH1GKUenygyxprCGKtP6vHpm9jYWBGAxhEbG1tq3atXr4oAxH379mmUT5kyRWzfvn2NxcQ5Unri7t27sLGxQW5uLqytrXUdTqkYY82QeoxSjw9gjDWFMVaf1OPTN2XtIlLa8kP//PMPGjZsiH379qFTp07q8qlTpyIlJQVpaWk1EtNzvY4UERER6Y/KrNlYr149GBoa4vr16xrl169fL3VruKriHCkiIiKqc0xMTNCmTRskJSWpy0pKSpCUlKTRQ1Vd7JEiIiKiOikmJgZDhw5F27Zt0b59e3z++efIz8/HsGHDaqwNJlJ6QiaTITY2VtLb0DDGmiH1GKUeH8AYawpjrD6px1fXDRw4EDdv3sSHH36Ia9euoVWrVvj999/h6OhYY21wsjkRERFRFXGOFBEREVEVMZEiIiIiqiImUkRERERVxESKiIiIqIqYSEncH3/8gd69e6NBgwYQBAEbN27UdUhalEol2rVrBysrK9SvXx/h4eHIzMzUdVgalixZAj8/P1hbW8Pa2hqdOnXC1q1bdR1WmebOnQtBEDBhwgRdh6I2c+ZMCIKgcXh7e+s6LC1Xr17Fm2++CXt7e5iZmaFFixY4fPiwrsNSa9y4sdb3KAgCoqKidB0aAKC4uBgffPAB3NzcYGZmhqZNm+Ljjz+G1N5LunfvHiZMmABXV1eYmZmhc+fOOHTokM7i+a9/V4uiiA8//BBOTk4wMzNDSEgIzp07p5tgqUYxkZK4/Px8tGzZEosXL9Z1KGVKSUlBVFQUDhw4gB07dqCwsBAvv/wy8vPzdR2aWqNGjTB37lwcOXIEhw8fxksvvYQ+ffrg1KlTug5Ny6FDh/D111/Dz89P16FoadasGbKzs9XH3r17dR2Shjt37iAgIADGxsbYunUrTp8+jbi4OLzwwgu6Dk3t0KFDGt/hjh07AACvv/66jiN7ZN68eViyZAkWLVqEjIwMzJs3D/Pnz8eXX36p69A0jBw5Ejt27MDKlStx8uRJvPzyywgJCcHVq1d1Es9//bt6/vz5WLhwIZYuXYq0tDRYWFggNDQUDx8+fMaRUo2rsV37qNYBEDds2KDrMP7TjRs3RABiSkqKrkMp1wsvvCB+9913ug5Dw71790QPDw9xx44dYmBgoPjuu+/qOiS12NhYsWXLlroOo1zTpk0TX3zxRV2HUSnvvvuu2LRpU7GkpETXoYiiKIq9evUShw8frlHWt29fMSIiQkcRabt//75oaGgoJiYmapS3bt1afO+993QU1f95+t/VJSUlolwuFz/99FN1WU5OjiiTycTVq1frIEKqSeyRohqXm5sLALCzs9NxJKUrLi7GmjVrkJ+fX6PbBNSEqKgo9OrVCyEhIboOpVTnzp1DgwYN0KRJE0RERCArK0vXIWnYvHkz2rZti9dffx3169eHv78/vv32W12HVaaCggL88MMPGD58OARB0HU4AIDOnTsjKSkJZ8+eBQAcP34ce/fuRY8ePXQc2f8pKipCcXExTE1NNcrNzMwk10sKABcvXsS1a9c0/l7b2NigQ4cO2L9/vw4jo5rAlc2pRpWUlGDChAkICAhA8+bNdR2OhpMnT6JTp054+PAhLC0tsWHDBvj6+uo6LLU1a9bg6NGjOp3nUZ4OHTogISEBXl5eyM7OxqxZs9ClSxf8+eefsLKy0nV4AIC//voLS5YsQUxMDGbMmIFDhw5h/PjxMDExwdChQ3UdnpaNGzciJycHkZGRug5Fbfr06bh79y68vb1haGiI4uJizJ49GxEREboOTc3KygqdOnXCxx9/DB8fHzg6OmL16tXYv38/3N3ddR2elmvXrgGA1mrajo6O6nOkv5hIUY2KiorCn3/+Kcn/K/Ty8kJ6ejpyc3Px888/Y+jQoUhJSZFEMnXlyhW8++672LFjh9b/ZUvFkz0Sfn5+6NChA1xdXbFu3TqMGDFCh5H9n5KSErRt2xZz5swBAPj7++PPP//E0qVLJZlILVu2DD169ECDBg10HYraunXr8OOPP2LVqlVo1qwZ0tPTMWHCBDRo0EBS3+HKlSsxfPhwNGzYEIaGhmjdujUGDRqEI0eO6Do0es5waI9qTHR0NBITE7F79240atRI1+FoMTExgbu7O9q0aQOlUomWLVviiy++0HVYAIAjR47gxo0baN26NYyMjGBkZISUlBQsXLgQRkZGKC4u1nWIWmxtbeHp6Ynz58/rOhQ1JycnrcTYx8dHckOQAHD58mXs3LkTI0eO1HUoGqZMmYLp06fjjTfeQIsWLfDWW29h4sSJUCqVug5NQ9OmTZGSkoK8vDxcuXIFBw8eRGFhIZo0aaLr0LTI5XIAwPXr1zXKr1+/rj5H+ouJFFWbKIqIjo7Ghg0bsGvXLri5uek6pAopKSmBSqXSdRgAgG7duuHkyZNIT09XH23btkVERATS09NhaGio6xC15OXl4cKFC3ByctJ1KGoBAQFaS2+cPXsWrq6uOoqobPHx8ahfvz569eql61A03L9/HwYGmv9pMDQ0RElJiY4iKp+FhQWcnJxw584dbNu2DX369NF1SFrc3Nwgl8uRlJSkLrt79y7S0tIkN0+TKo9DexKXl5en8X/8Fy9eRHp6Ouzs7ODi4qLDyP5PVFQUVq1ahU2bNsHKyko95m9jYwMzMzMdR/eIQqFAjx494OLignv37mHVqlVITk7Gtm3bdB0agEdzPp6eU2ZhYQF7e3vJzDWbPHkyevfuDVdXV/zzzz+IjY2FoaEhBg0apOvQ1CZOnIjOnTtjzpw5GDBgAA4ePIhvvvkG33zzja5D01BSUoL4+HgMHToURkbS+tdw7969MXv2bLi4uKBZs2Y4duwYPvvsMwwfPlzXoWnYtm0bRFGEl5cXzp8/jylTpsDb2xvDhg3TSTz/9e/qCRMm4JNPPoGHhwfc3NzwwQcfoEGDBggPD9dJvFSDdP3aIJVv9+7dIgCtY+jQoboOTa20+ACI8fHxug5Nbfjw4aKrq6toYmIiOjg4iN26dRO3b9+u67DKJbXlDwYOHCg6OTmJJiYmYsOGDcWBAweK58+f13VYWn799VexefPmokwmE729vcVvvvlG1yFp2bZtmwhAzMzM1HUoWu7evSu+++67oouLi2hqaio2adJEfO+990SVSqXr0DSsXbtWbNKkiWhiYiLK5XIxKipKzMnJ0Vk8//Xv6pKSEvGDDz4QHR0dRZlMJnbr1k2Sv3+qPEEUJbZcLREREZGe4BwpIiIioipiIkVERERURUykiIiIiKqIiRQRERFRFTGRIiIiIqoiJlJEREREVcREioiIiKiKmEgRERERVRETKdI7giBg48aNug6DnpGZM2eiVatWtd4O/1xVXkJCAmxtbf+zHr9bqsuYSNEzExkZKbl9pZKTkyEIAnJycnQdSp1x6dIlCIKA9PT0Sl9b2n9wJ0+erLHZa23Jzs5Gjx49ar2dumTgwIE4e/as+nNZSS+/W6rLpLVbJpFEFRQUwMTEpNr3KS4uhiAIMDCo+f+HqakYpcbS0hKWlpa13o5cLq/1NuoaMzOzCm1Mzu+W6jL2SJHOBAUFYfz48Zg6dSrs7Owgl8sxc+ZMjTrnzp1D165dYWpqCl9fX+zYsUPjfGk9Sunp6RAEAZcuXQIAXL58Gb1798YLL7wACwsLNGvWDL/99hsuXbqE4OBgAMALL7wAQRAQGRmpji06OhoTJkxAvXr1EBoaiuHDh+OVV17RaL+wsBD169fHsmXLSn3Gx0Mfmzdvhq+vL2QyGbKysqBSqTB58mQ0bNgQFhYW6NChA5KTk7Wu27hxIzw8PGBqaorQ0FBcuXJFXefx//1/9913cHNzg6mpKQAgJycHI0eOhIODA6ytrfHSSy/h+PHj6uuOHz+O4OBgWFlZwdraGm3atMHhw4fV5/fu3YsuXbrAzMwMzs7OGD9+PPLz89XnGzdujDlz5mD48OGwsrKCi4sLvvnmG/V5Nzc3AIC/vz8EQUBQUBAA4NChQ+jevTvq1asHGxsbBAYG4ujRoxr3BYDXXnsNgiCoPz/dy1FSUoKPPvoIjRo1gkwmQ6tWrfD777+rzz/uEVu/fj2Cg4Nhbm6Oli1bYv/+/aX+jh57sjesqvfIycnBO++8A0dHR5iamqJ58+ZITExUn//ll1/QrFkzyGQyNG7cGHFxcRrXN27cGJ988gmGDBkCS0tLuLq6YvPmzbh58yb69OkDS0tL+Pn5afy+Hv9ZSUxMhJeXF8zNzdG/f3/cv38fK1asQOPGjfHCCy9g/PjxKC4uLvV5H7O1tUVCQkKFv4Mnh/YSEhIwa9YsHD9+HIIgQBAE9b2ebuvKlSsYMGAAbG1tYWdnhz59+qj/vgKP/l63b98eFhYWsLW1RUBAAC5fvlzud0+kM7reNZmeH0OHDhX79Omj/hwYGChaW1uLM2fOFM+ePSuuWLFCFARB3L59uyiKolhcXCw2b95c7Natm5ieni6mpKSI/v7+IgBxw4YNoij+347rd+7cUd/32LFjIgDx4sWLoiiKYq9evcTu3buLJ06cEC9cuCD++uuvYkpKilhUVCT+8ssvIgAxMzNTzM7OVu8eHxgYKFpaWopTpkwRz5w5I545c0ZMTU0VDQ0NxX/++Ufd1vr160ULCwvx3r17pT5zfHy8aGxsLHbu3FlMTU0Vz5w5I+bn54sjR44UO3fuLP7xxx/i+fPnxU8//VSUyWTi2bNnNa5r27atuG/fPvHw4cNi+/btxc6dO6vvHRsbK1pYWIhhYWHi0aNHxePHj4uiKIohISFi7969xUOHDolnz54VJ02aJNrb24u3b98WRVEUmzVrJr755ptiRkaGePbsWXHdunVienq6KIqieP78edHCwkJcsGCBePbsWTE1NVX09/cXIyMj1e26urqKdnZ24uLFi8Vz586JSqVSNDAwEM+cOSOKoigePHhQBCDu3LlTzM7OVreblJQkrly5UszIyBBPnz4tjhgxQnR0dBTv3r0riqIo3rhxQwQgxsfHi9nZ2eKNGzfUz9myZUt1+5999plobW0trl69Wjxz5ow4depU0djYWP3dXbx4UQQgent7i4mJiWJmZqbYv39/0dXVVSwsLCzzz+eTf66qco/i4mKxY8eOYrNmzcTt27er/6z99ttvoiiK4uHDh0UDAwPxo48+EjMzM8X4+HjRzMxMjI+P1/puly5dKp49e1YcM2aMaG1tLYaFhYnr1q0TMzMzxfDwcNHHx0csKSnR+LPSvXt38ejRo2JKSopob28vvvzyy+KAAQPEU6dOib/++qtoYmIirlmzptTnfczGxkYdT0W+g/j4eNHGxkYURVG8f/++OGnSJLFZs2Zidna2mJ2dLd6/f1+rrYKCAtHHx0ccPny4eOLECfH06dPi4MGDRS8vL1GlUomFhYWijY2NOHnyZPH8+fPi6dOnxYSEBPHy5ctl/u6IdImJFD0zpSVSL774okaddu3aidOmTRNFURS3bdsmGhkZiVevXlWf37p1a6UTqRYtWogzZ84sNabSrn8cm7+/v1Z9X19fcd68eerPvXv31kgynhYfHy8CUCcqoiiKly9fFg0NDTWeSxRFsVu3bqJCodC47sCBA+rzGRkZIgAxLS1NFMVHCYaxsbE64RBFUdyzZ49obW0tPnz4UOPeTZs2Fb/++mtRFEXRyspKTEhIKDXeESNGiG+//bZG2Z49e0QDAwPxwYMHoig++o/9m2++qT5fUlIi1q9fX1yyZIkoiv/3H+Bjx46V+b2I4qPEw8rKSvz111/VZaX9x/3pRKpBgwbi7NmzNeq0a9dOHDt2rEb73333nfr8qVOnRABiRkZGmfGUlkhV5h7btm0TDQwMxMzMzFLPDx48WOzevbtG2ZQpU0RfX1/156e/2+zsbBGA+MEHH6jL9u/fLwIQs7OzRVH8vz8r58+fV9d55513RHNzc40EPzQ0VHznnXdKfd7HSkukyvsOnkykRFH7d1VaWytXrhS9vLzUiaAoiqJKpRLNzMzEbdu2ibdv3xYBiMnJyVr3IZIiDu2RTvn5+Wl8dnJywo0bNwAAGRkZcHZ2RoMGDdTnO3XqVOk2xo8fj08++QQBAQGIjY3FiRMnKnRdmzZttMpGjhyJ+Ph4AMD169exdetWDB8+vNz7mJiYaDznyZMnUVxcDE9PT/X8H0tLS6SkpODChQvqekZGRmjXrp36s7e3N2xtbZGRkaEuc3V1hYODg/rz8ePHkZeXB3t7e417X7x4UX3vmJgYjBw5EiEhIZg7d65Gm8ePH0dCQoLGtaGhoSgpKcHFixfV9Z58HkEQIJfL1b+3sly/fh2jRo2Ch4cHbGxsYG1tjby8PGRlZZV73ZPu3r2Lf/75BwEBARrlAQEBGt/L0zE6OTkBwH/G+LTK3CM9PR2NGjWCp6dnqeczMjJKjfvcuXMaQ25Ptuno6AgAaNGihVbZk3GYm5ujadOmGnUaN26sMbfM0dGx0s//dDxV/R6fdPz4cZw/fx5WVlbqP2N2dnZ4+PAhLly4ADs7O0RGRiI0NBS9e/fGF198gezs7Cq3R1TbONmcdMrY2FjjsyAIKCkpqfD1jydti6KoLissLNSoM3LkSISGhmLLli3Yvn07lEol4uLiMG7cuHLvbWFhoVU2ZMgQTJ8+Hfv378e+ffvg5uaGLl26lHsfMzMzCIKg/pyXlwdDQ0McOXIEhoaGGnUrO6n66Rjz8vLg5OSkMd/qscdzWWbOnInBgwdjy5Yt2Lp1K2JjY7FmzRq89tpryMvLwzvvvIPx48drXe/i4qL+uSq/t6FDh+L27dv44osv4OrqCplMhk6dOqGgoKCCT1s5T8b4+PuvzJ+tyt6jIpOuq9rmf8VR2u/jv35HgiBo/L0BtP/uVKTtysrLy0ObNm3w448/ap17/D8F8fHxGD9+PH7//XesXbsW77//Pnbs2IGOHTtWuV2i2sJEiiTLx8cHV65cQXZ2tvr/hA8cOKBR5/G/eLOzs/HCCy8AQKmv3Ts7O2P06NEYPXo0FAoFvv32W4wbN079ltuTPQLlsbe3R3h4OOLj47F//34MGzas0s/l7++P4uJi3Lhxo9wkrKioCIcPH0b79u0BAJmZmcjJyYGPj0+Z17Ru3RrXrl2DkZGRerJ2aTw9PeHp6YmJEydi0KBBiI+Px2uvvYbWrVvj9OnTcHd3r/RzPVbWd5qamoqvvvoKPXv2BPBowvGtW7c06hgbG5f7u7C2tkaDBg2QmpqKwMBAjXs//p50xc/PD3///TfOnj1baq+Uj48PUlNTNcpSU1Ph6emplVA/Cw4ODho9PefOncP9+/erdU8TE5P//LvUunVrrF27FvXr14e1tXWZ9fz9/eHv7w+FQoFOnTph1apVTKRIkji0R5IVEhICT09PDB06FMePH8eePXvw3nvvadRxd3eHs7MzZs6ciXPnzmHLli1ab0JNmDAB27Ztw8WLF3H06FHs3r1bnYy4urpCEAQkJibi5s2byMvL+8+4Ro4ciRUrViAjIwNDhw6t9HN5enoiIiICQ4YMwfr163Hx4kUcPHgQSqUSW7ZsUdczNjbGuHHjkJaWhiNHjiAyMhIdO3YsN2EICQlBp06dEB4eju3bt+PSpUvYt28f3nvvPRw+fBgPHjxAdHQ0kpOTcfnyZaSmpuLQoUPq72PatGnYt28foqOjkZ6ejnPnzmHTpk2Ijo6u8PPVr18fZmZm+P3333H9+nXk5uYCADw8PLBy5UpkZGQgLS0NERERWr04jRs3RlJSEq5du4Y7d+6Uev8pU6Zg3rx5WLt2LTIzMzF9+nSkp6fj3XffrXCMtSEwMBBdu3ZFv379sGPHDly8eBFbt25Vv1E4adIkJCUl4eOPP8bZs2exYsUKLFq0CJMnT9ZJvC+99BIWLVqEY8eO4fDhwxg9erRWL1ZlNW7cGBcvXkR6ejpu3boFlUqlVSciIgL16tVDnz59sGfPHly8eBHJyckYP348/v77b1y8eBEKhQL79+/H5cuXsX37dpw7d67c/4Eg0iUmUiRZBgYG2LBhAx48eID27dtj5MiRmD17tkYdY2NjrF69GmfOnIGfnx/mzZuHTz75RKNOcXExoqKi4OPjg7CwMHh6euKrr74CADRs2BCzZs3C9OnT4ejoWKGEISQkBE5OTggNDdWYv1UZ8fHxGDJkCCZNmgQvLy+Eh4fj0KFDGsNn5ubmmDZtGgYPHoyAgABYWlpi7dq15d5XEAT89ttv6Nq1K4YNGwZPT0+88cYbuHz5MhwdHWFoaIjbt29jyJAh8PT0xIABA9CjRw/MmjULwKNelZSUFJw9exZdunSBv78/Pvzww0o9p5GRERYuXIivv/4aDRo0QJ8+fQAAy5Ytw507d9C6dWu89dZbGD9+POrXr69xbVxcHHbs2AFnZ2f4+/uXev/x48cjJiYGkyZNQosWLfD7779j8+bN8PDwqHCMteWXX35Bu3btMGjQIPj6+mLq1KnqHprWrVtj3bp1WLNmDZo3b44PP/wQH330kXrJjWctLi4Ozs7O6NKlCwYPHozJkyfD3Ny8Wvfs168fwsLCEBwcDAcHB6xevVqrjrm5Of744w+4uLigb9++8PHxwYgRI/Dw4UNYW1vD3NwcZ86cQb9+/eDp6Ym3334bUVFReOedd6oVG1FtEcSnB8mJqFx5eXlo2LAh4uPj0bdv31ppIyEhARMmTOCK60REEsc5UkQVVFJSglu3biEuLg62trZ49dVXdR0SERHpGBMpogrKysqCm5sbGjVqhISEBBgZ8a8PEdHzjkN7RERERFXEyeZEREREVcREioiIiKiKmEgRERERVRETKSIiIqIqYiJFREREVEVMpIiIiIiqiIkUERERURUxkSIiIiKqov8HWyu8Cwob3fwAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 600x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize Fama-French 49-industries in the detected communities\n",
    "key = 'codes49'\n",
    "for ifig, detection in enumerate(communities.keys()):\n",
    "\n",
    "    # count industries represented in each partition\n",
    "    industry = []\n",
    "    communities_sequence = sorted(communities[detection], key=len, reverse=True)    \n",
    "    for i, community in enumerate(communities_sequence):\n",
    "        industry.append(nodes[key][list(community)].value_counts().rename(i+1))\n",
    "    names = sectorings[key].sectors['name'].drop_duplicates(keep='first')\n",
    "    df = pd.concat(industry, axis=1)\\\n",
    "           .dropna(axis=0, how='all')\\\n",
    "           .fillna(0)\\\n",
    "           .astype(int)\\\n",
    "           .reindex(names)\n",
    "\n",
    "    # display as heatmap\n",
    "    fig, ax = plt.subplots(num=ifig+1, clear=True, figsize=(6, 8))\n",
    "    sns.heatmap(df.iloc[:,:10],\n",
    "                square=False,\n",
    "                linewidth=.5,\n",
    "                ax=ax,\n",
    "                yticklabels=1,\n",
    "                cmap=\"YlGnBu\",\n",
    "                robust=True)\n",
    "    if scheme.startswith('bea'):\n",
    "        ax.set_yticklabels(Sectoring._bea_industry[df.index], size=10)\n",
    "    else:\n",
    "        ax.set_yticklabels(df.index, size=10)\n",
    "    ax.set_title(f'{detection.capitalize()} Community Detection {year}')\n",
    "    ax.set_xlabel(f\"Industry representation in communities\")\n",
    "    ax.set_ylabel(f\"{key} industry\")\n",
    "    fig.subplots_adjust(left=0.4)\n",
    "    plt.tight_layout(pad=0)\n"
   ]
  }
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