Lab 5a - hierarchical_clustering.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d0fa5561",
   "metadata": {},
   "source": [
    "# Lab 5a - Hierarchical Clustering Methods"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63fe6ef3",
   "metadata": {},
   "source": [
    "This notebook introduces the first of two Classic Clustering Methods, i.e., Hierarchical Clustering. Special aspects considered include the visualization and spatial analysis of the cluster results.\n",
    "\n",
    "It is part of the Spatial Cluster Analysis course taught at the University of Chicago in the Winter Quarter of 2025.\n",
    "\n",
    "Prepared by: Luc Anselin (anselin@uchicago.edu) and Pedro Amaral (pedroamaral@uchicago.edu)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06c7b3cb",
   "metadata": {},
   "source": [
    "## Preliminaries\n",
    "We will consider agglomerative clustering as an example of hierarchical clustering.\n",
    "\n",
    "The empirical illustration is based on the material in Chapter 5 of the Spatial Cluster book."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d76e4c1e",
   "metadata": {},
   "source": [
    "### Required packages"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5be87c72",
   "metadata": {},
   "source": [
    "The conda enviroment used for this exercise was created from a yml file with the same specification as in the previous notebooks:"
   ]
  },
  {
   "cell_type": "raw",
   "id": "86259abc",
   "metadata": {},
   "source": [
    "name: sp_clusters\n",
    "channels:\n",
    "  - conda-forge\n",
    "  - defaults\n",
    "dependencies:\n",
    "  - python=3.12\n",
    "  - numpy \n",
    "  - nb_conda\n",
    "  - notebook\n",
    "  - geopandas\n",
    "  - scikit-learn\n",
    "  - matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59b325a0",
   "metadata": {},
   "source": [
    "In addition to the usual numpy, geopandas and matplotlib, we also import several specialized packages from scikit-learn. Specifically, to carry out variable standardization we import `StandardScaler` from `sklearn.preprocessing`. The specific clustering method is `AgglomerativeClustering` from `sklearn.cluster`. In addition, an alternative method to obtain hierarchical clusters, which is somewhat easier to visualize, is contained in `scipy.cluster.hierarchy`. \n",
    "\n",
    "Finally, to implement some of the *spatialization* of these methods, we import several functions from the `spatial_cluster_course` utility module (this requires that the latest version of the file spatial_cluster_course.py is in the current Python path):\n",
    "- `cluster_stats`\n",
    "- `plot_clusters`\n",
    "- `plot_dendrogram`\n",
    "- `cluster_center`\n",
    "- `cluster_fit`\n",
    "- `cluster_map`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e49b893f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.cluster import AgglomerativeClustering\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage\n",
    "\n",
    "from spatial_cluster_course import cluster_stats, plot_dendrogram, cluster_center, cluster_fit, cluster_map"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "737ad673",
   "metadata": {},
   "source": [
    "### Load data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51281568",
   "metadata": {},
   "source": [
    "For this exercise, we will use a data set on socio-economic variables for Chicago Community Areas in 2020 in Chicago, IL. This is also a GeoDa sample data set. Detailed source and information available at https://geodacenter.github.io/data-and-lab/Chi-CCA/\n",
    "\n",
    "The following files will be used:\n",
    "- **Chicago_2020.shp,shx,dbf,prj**: shape file (four files) for 77 community areas\n",
    "\n",
    "We follow the usual practice of setting a path (if needed), reading the data from the shape file and a quick check of its contents (`head`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a2bd865b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(77, 233)\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>area_num_1</th>\n",
       "      <th>community</th>\n",
       "      <th>shape_area</th>\n",
       "      <th>shape_len</th>\n",
       "      <th>districtno</th>\n",
       "      <th>district</th>\n",
       "      <th>TOT_POP</th>\n",
       "      <th>2000_POP</th>\n",
       "      <th>2010_POP</th>\n",
       "      <th>UND5</th>\n",
       "      <th>...</th>\n",
       "      <th>KOREAN</th>\n",
       "      <th>OTHASIAN</th>\n",
       "      <th>OTHER_EURO</th>\n",
       "      <th>OTHUNSPEC</th>\n",
       "      <th>2000_WHITE</th>\n",
       "      <th>2000_HISP</th>\n",
       "      <th>2000_BLACK</th>\n",
       "      <th>2000_ASIAN</th>\n",
       "      <th>2000_OTHER</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>35.0</td>\n",
       "      <td>DOUGLAS</td>\n",
       "      <td>4.600462e+07</td>\n",
       "      <td>31027.054510</td>\n",
       "      <td>7.0</td>\n",
       "      <td>South Side</td>\n",
       "      <td>21325.0</td>\n",
       "      <td>26470.0</td>\n",
       "      <td>18238.0</td>\n",
       "      <td>1107.0</td>\n",
       "      <td>...</td>\n",
       "      <td>145.0</td>\n",
       "      <td>571.0</td>\n",
       "      <td>1290.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>1745.0</td>\n",
       "      <td>295.0</td>\n",
       "      <td>22635.0</td>\n",
       "      <td>1390.0</td>\n",
       "      <td>405.0</td>\n",
       "      <td>POLYGON ((-87.60914 41.84469, -87.60915 41.844...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>36.0</td>\n",
       "      <td>OAKLAND</td>\n",
       "      <td>1.691396e+07</td>\n",
       "      <td>19565.506153</td>\n",
       "      <td>7.0</td>\n",
       "      <td>South Side</td>\n",
       "      <td>7227.0</td>\n",
       "      <td>6110.0</td>\n",
       "      <td>5918.0</td>\n",
       "      <td>574.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>342.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>5957.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>POLYGON ((-87.59215 41.81693, -87.59231 41.816...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37.0</td>\n",
       "      <td>FULLER PARK</td>\n",
       "      <td>1.991670e+07</td>\n",
       "      <td>25339.089750</td>\n",
       "      <td>7.0</td>\n",
       "      <td>South Side</td>\n",
       "      <td>2394.0</td>\n",
       "      <td>3420.0</td>\n",
       "      <td>2876.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>3225.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>POLYGON ((-87.6288 41.80189, -87.62879 41.8017...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 233 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   area_num_1    community    shape_area     shape_len  districtno  \\\n",
       "0        35.0      DOUGLAS  4.600462e+07  31027.054510         7.0   \n",
       "1        36.0      OAKLAND  1.691396e+07  19565.506153         7.0   \n",
       "2        37.0  FULLER PARK  1.991670e+07  25339.089750         7.0   \n",
       "\n",
       "     district  TOT_POP  2000_POP  2010_POP    UND5  ...  KOREAN  OTHASIAN  \\\n",
       "0  South Side  21325.0   26470.0   18238.0  1107.0  ...   145.0     571.0   \n",
       "1  South Side   7227.0    6110.0    5918.0   574.0  ...     0.0      22.0   \n",
       "2  South Side   2394.0    3420.0    2876.0   120.0  ...     0.0       0.0   \n",
       "\n",
       "   OTHER_EURO  OTHUNSPEC  2000_WHITE  2000_HISP  2000_BLACK  2000_ASIAN  \\\n",
       "0      1290.0      555.0      1745.0      295.0     22635.0      1390.0   \n",
       "1        98.0      342.0        40.0       58.0      5957.0         8.0   \n",
       "2        15.0        0.0        18.0      116.0      3225.0         6.0   \n",
       "\n",
       "   2000_OTHER                                           geometry  \n",
       "0       405.0  POLYGON ((-87.60914 41.84469, -87.60915 41.844...  \n",
       "1        47.0  POLYGON ((-87.59215 41.81693, -87.59231 41.816...  \n",
       "2        55.0  POLYGON ((-87.6288 41.80189, -87.62879 41.8017...  \n",
       "\n",
       "[3 rows x 233 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Setting working folder:\n",
    "#path = \"/your/path/to/data/\"\n",
    "path = \"\"\n",
    "\n",
    "# Load the Chicago community area data:\n",
    "dfs = gpd.read_file(path+\"Chi_CCA/Chicago_2020_sdoh.shp\")\n",
    "print(dfs.shape)\n",
    "dfs.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c4524a8e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['area_num_1', 'community', 'shape_area', 'shape_len', 'districtno', 'district', 'TOT_POP', '2000_POP', '2010_POP', 'UND5', 'A5_19', 'A65_74', 'A75_84', 'OV85', 'WHITE', 'UNEMP', 'NO_VEH', 'POP_25OV', 'LT_HS', 'MEDINC', 'TOT_HH', 'OWN_OCC_HU', 'RENTOCCHU', 'VAC_HU', 'HU_TOT', 'MED_HA', 'MED_HV', 'MED_RENT', 'AVG_VMT', 'FOR_BORN', 'POP_OV5', 'NOTENGLISH', 'LING_ISO', 'INCPERCAP', 'Und20', 'Ov65', 'Minrty', 'Unemprt', 'Noveh', 'Lt_high', 'Rentocc', 'Rntburd', 'Noeng', 'Vacant', 'Forborn', 'Ownocc', 'Liteng', 'CLhc5', 'GEOID', 'GEOG', 'A5_20', 'A20_34', 'A35_49', 'A50_64', 'A65_75', 'A75_85', 'MED_AGE', 'HISP', 'BLACK', 'ASIAN', 'OTHER', 'POP_HH', 'POP_16OV', 'IN_LBFRC', 'EMP', 'N_IN_LBFRC', 'T_WRKR16OV', 'WORK_HOME', 'TOT_COMM', 'DROVE_AL', 'CARPOOL', 'TRANSIT', 'WALK_BIKE', 'COMM_OTHER', 'AGG_TT', 'ONE_VEH', 'TWO_VEH', 'THREEP_VEH', 'HS', 'SOME_COLL', 'ASSOC', 'BACH', 'GRAD_PROF', 'INCLT25K', 'INC2550K', 'INC5075K', 'INC75100K', 'INC100150K', 'INC_GT_150', 'HU_SNG_DET', 'HU_SNG_ATT', 'HU_2UN', 'HU_3_4UN', 'HU_5_9UN', 'HU_10_19UN', 'HU_GT_19UN', 'HU_MOBILE', 'MED_ROOMS', 'HA_AFT2000', 'HA_70_00', 'HA_40_70', 'HA_BEF1940', 'BR_0_1', 'BR_2', 'BR_3', 'BR_4', 'BR_5', 'HVLT150K', 'HV150300K', 'HV300500K', 'HVGT500K', 'CASHRENTHH', 'RENT_LT500', 'RENT500999', 'RT10001499', 'RT15002499', 'RENTGT2500', 'COMPUTER', 'SMARTPHONE', 'NOCOMPUTER', 'INTERNET', 'BROADBAND', 'NOINTERNET', 'TEMPRES', 'RESNAICS1T', 'RESNAICS2T', 'RESNAICS3T', 'RESNAICS4T', 'RESNAICS5T', 'RESNAICS1C', 'RESNAICS2C', 'RESNAICS3C', 'RESNAICS4C', 'RESNAICS5C', 'TOTEMPWRK', 'WRKNAICS1T', 'WRKNAICS2T', 'WRKNAICS3T', 'WRKNAICS4T', 'WRKNAICS5T', 'WRKNAICS1C', 'WRKNAICS2C', 'WRKNAICS3C', 'WRKNAICS4C', 'WRKNAICS5C', 'RESCITY1T', 'RESCITY2T', 'RESCITY3T', 'RESCITY4T', 'RESCITY5T', 'RESCITY1C', 'RESCITY2C', 'RESCITY3C', 'RESCITY4C', 'RESCITY5C', 'WRKCITY1T', 'WRKCITY2T', 'WRKCITY3T', 'WRKCITY4T', 'WRKCITY5T', 'WRKCITY1C', 'WRKCITY2C', 'WRKCITY3C', 'WRKCITY4C', 'WRKCITY5C', 'AVG_VMT_1', 'TRANSLOPCT', 'TRANSMDPCT', 'TRANSHIPCT', 'WALKLOWPCT', 'WALKMODPCT', 'WALKHIPCT', 'OSPACE1000', 'TOT_ACRES', 'SF', 'Sfperc', 'MF', 'Mfperc', 'MIX', 'MIXperc', 'COMM', 'COMMperc', 'INST', 'INSTperc', 'IND', 'INDperc', 'TRANS', 'TRANSperc', 'AG', 'Agperc', 'OPEN', 'OPENperc', 'VACperc', 'CT_1PHH', 'CT_2PHH', 'CT_3PHH', 'CT_4MPHH', 'CT_FAM_HH', 'CTSPWCHILD', 'CTNONFAMHH', 'HCUND20K', 'HCUN20KL20', 'HCU20_2029', 'HCU20_30', 'HC20Kto49K', 'HC2049L20', 'HC20492029', 'HC204930', 'HC5075K', 'HC5075LT20', 'HC50752029', 'HC507530M', 'HCOV75K', 'HCOV75L20P', 'HCOV752029', 'HCOV7530M', 'NATIVE', 'ENGLISH', 'SPANISH', 'SLAVIC', 'CHINESE', 'TAGALOG', 'ARABIC', 'KOREAN', 'OTHASIAN', 'OTHER_EURO', 'OTHUNSPEC', '2000_WHITE', '2000_HISP', '2000_BLACK', '2000_ASIAN', '2000_OTHER', 'geometry']\n"
     ]
    }
   ],
   "source": [
    "# the full set of variables\n",
    "print(list(dfs.columns))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4024a438",
   "metadata": {},
   "source": [
    "#### Selecting variables and checking their correlation"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "c63b04c2-f618-47f4-94fa-a87e77adce0e",
   "metadata": {},
   "source": [
    "Following Section 5.4 of Anselin (2024) (https://lanselin.github.io/introbook_vol2/implementation-3.html), the variables in our Chicago Community Areas sample data set form a subset of the variables identified in Kolak et al. (2020) in an analysis that includes all U.S. census tracts.\n",
    "\n",
    "List of variables:\n",
    "| Column Name | Description                                                                 |\n",
    "|-------------|-----------------------------------------------------------------------------|\n",
    "| INCPERCAP   | Per capita income                                                          |\n",
    "| Und20       | Population share aged < 20                                                |\n",
    "| Ov65        | Population share aged > 65                                                |\n",
    "| Minrty      | Percentage of minority population |\n",
    "| Unemprt     | Unemployment rate                                                         |\n",
    "| Noveh       | Percentage of households with no vehicle                                   |\n",
    "| Lt_high     | Percentage of population without high school education                    |\n",
    "| Rentocc     | Percentage of renter-occupied housing                                      |\n",
    "| Rntburd     | Rent burden                                                               |\n",
    "| Noeng       | Percentage of population with limited English proficiency                 |\n",
    "\n",
    "We start by computing simple descriptive statistics by applying the `describe` method to the subset of the data frame that contains the selected variables. The results are rounded to two decimals."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "21ec3a2c",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>INCPERCAP</th>\n",
       "      <th>Und20</th>\n",
       "      <th>Ov65</th>\n",
       "      <th>Minrty</th>\n",
       "      <th>Unemprt</th>\n",
       "      <th>Noveh</th>\n",
       "      <th>Lt_high</th>\n",
       "      <th>Rentocc</th>\n",
       "      <th>Rntburd</th>\n",
       "      <th>Noeng</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>77.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>77.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>32501.26</td>\n",
       "      <td>24.56</td>\n",
       "      <td>13.69</td>\n",
       "      <td>72.05</td>\n",
       "      <td>10.56</td>\n",
       "      <td>12.73</td>\n",
       "      <td>16.00</td>\n",
       "      <td>45.20</td>\n",
       "      <td>25.71</td>\n",
       "      <td>33.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>19482.12</td>\n",
       "      <td>6.35</td>\n",
       "      <td>4.61</td>\n",
       "      <td>26.91</td>\n",
       "      <td>6.87</td>\n",
       "      <td>8.01</td>\n",
       "      <td>9.63</td>\n",
       "      <td>15.75</td>\n",
       "      <td>8.26</td>\n",
       "      <td>26.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>11857.00</td>\n",
       "      <td>8.90</td>\n",
       "      <td>4.80</td>\n",
       "      <td>16.79</td>\n",
       "      <td>0.37</td>\n",
       "      <td>1.93</td>\n",
       "      <td>1.73</td>\n",
       "      <td>9.13</td>\n",
       "      <td>11.23</td>\n",
       "      <td>2.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>19842.00</td>\n",
       "      <td>20.25</td>\n",
       "      <td>10.12</td>\n",
       "      <td>51.74</td>\n",
       "      <td>5.01</td>\n",
       "      <td>6.04</td>\n",
       "      <td>9.12</td>\n",
       "      <td>31.70</td>\n",
       "      <td>20.40</td>\n",
       "      <td>7.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>25944.00</td>\n",
       "      <td>25.08</td>\n",
       "      <td>12.82</td>\n",
       "      <td>85.51</td>\n",
       "      <td>8.74</td>\n",
       "      <td>10.53</td>\n",
       "      <td>14.69</td>\n",
       "      <td>48.36</td>\n",
       "      <td>23.94</td>\n",
       "      <td>26.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>36736.00</td>\n",
       "      <td>29.41</td>\n",
       "      <td>16.09</td>\n",
       "      <td>96.37</td>\n",
       "      <td>15.74</td>\n",
       "      <td>19.92</td>\n",
       "      <td>21.70</td>\n",
       "      <td>56.20</td>\n",
       "      <td>29.80</td>\n",
       "      <td>55.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>101727.00</td>\n",
       "      <td>44.28</td>\n",
       "      <td>26.52</td>\n",
       "      <td>99.50</td>\n",
       "      <td>30.42</td>\n",
       "      <td>34.31</td>\n",
       "      <td>44.65</td>\n",
       "      <td>76.92</td>\n",
       "      <td>49.85</td>\n",
       "      <td>86.53</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       INCPERCAP  Und20   Ov65  Minrty  Unemprt  Noveh  Lt_high  Rentocc  \\\n",
       "count      77.00  77.00  77.00   77.00    77.00  77.00    77.00    77.00   \n",
       "mean    32501.26  24.56  13.69   72.05    10.56  12.73    16.00    45.20   \n",
       "std     19482.12   6.35   4.61   26.91     6.87   8.01     9.63    15.75   \n",
       "min     11857.00   8.90   4.80   16.79     0.37   1.93     1.73     9.13   \n",
       "25%     19842.00  20.25  10.12   51.74     5.01   6.04     9.12    31.70   \n",
       "50%     25944.00  25.08  12.82   85.51     8.74  10.53    14.69    48.36   \n",
       "75%     36736.00  29.41  16.09   96.37    15.74  19.92    21.70    56.20   \n",
       "max    101727.00  44.28  26.52   99.50    30.42  34.31    44.65    76.92   \n",
       "\n",
       "       Rntburd  Noeng  \n",
       "count    77.00  77.00  \n",
       "mean     25.71  33.38  \n",
       "std       8.26  26.73  \n",
       "min      11.23   2.19  \n",
       "25%      20.40   7.38  \n",
       "50%      23.94  26.71  \n",
       "75%      29.80  55.36  \n",
       "max      49.85  86.53  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "varlist = ['INCPERCAP', 'Und20', 'Ov65', 'Minrty', 'Unemprt', \n",
    "           'Noveh', 'Lt_high', 'Rentocc', 'Rntburd', 'Noeng']\n",
    "data_cluster = dfs[varlist]\n",
    "\n",
    "round(data_cluster.describe(),2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3ff8925",
   "metadata": {},
   "source": [
    "## Hierarchical Clustering"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "932c4f16",
   "metadata": {},
   "source": [
    "The first class of traditional clustering methods builds up the clusters step-by-step in a *hierarchical* fashion. There are two approaches. One, agglomerative clustering, starts from the bottom and works its way up. More precisely, initially, each observation forms a separate cluster and subsequently pairs of observations are systematically grouped into larger entities, until the whole data set forms one cluster. In the other approach, divisive clustering, the opposite path is taken. One starts with the full set of observations as one cluster, and subsequently splits this into subclusters until each observation is again its own cluster. Here, we only consider agglomerative clustering. A form of divisive clustering is considered in the discussion of spatially constrained clustering.\n",
    "\n",
    "There are two important elements to be considered in the grouping of observations:\n",
    "- linkage option, i.e., how to decide which observations/clusters are *closest*\n",
    "- update function, i.e., how to compute the *distance* between clusters\n",
    "\n",
    "The main methods are characterized by different linkage options. Here, we consider the four most common ones, i.e., *Ward's* method, *single linkage*, *complete linkage* and *average linkage*.\n",
    "\n",
    "An important aspect of hierarchical clustering is the so-called *dendrogram*, which visualizes the process of grouping observations/entities into larger entities and the associated distance criterion. The number of clusters is not set initially, but is determined by the *cut* of the dendrogram.\n",
    "\n",
    "We start by considering Ward's method, which is arguably the most robust and most commonly used method. However, it only works for a squared distance criterion, whereas other measures work with any distance. We illustrate four important aspects of the solution: computing the clusters (cluster labels), visualizing the dendrogram, calculating characteristics of a cluster solution, and visualizing the clusters in a *cluster map*."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1991b7a9",
   "metadata": {},
   "source": [
    "## Ward's method"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5894cca0",
   "metadata": {},
   "source": [
    "### Cluster Computation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "782510fe",
   "metadata": {},
   "source": [
    "One approach to obtain the cluster computation is by means of the `AgglomerativeClustering` class of scikit-learn. For details, see https://scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html. The second option, using `scipy.cluster.hierarchy` is considered in the discussion of the dendrogram next.\n",
    "\n",
    "The main arguments to create an instance of the `AgglomerativeClustering` class are the number of clusters, `n_clusters`, the `linkage` option, as well as an option to compute the distances from an initial array of inputs, `compute_distances = True`. As before, the input data frame is first standardized using `fit_transform` from `StandardScaler`. Once an instance of the class is created, the `fit` method returns the results, with the cluster labels contained in the `labels_` attribute. Other attributes are provided as well, but the labels are our main interest (see the docs for details). We summarize the results with our `cluster_stats` utility function (contained in `spatial_cluster_course.py` and outlined in a previous notebook).\n",
    "\n",
    "We illustrate this for Ward's method with a cluster size of 5."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3360a669",
   "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>Labels</th>\n",
       "      <th>Cardinality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Labels  Cardinality\n",
       "0       0           21\n",
       "1       1           15\n",
       "2       2           15\n",
       "3       3           13\n",
       "4       4           13"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select the desired number of clusters and linkage method\n",
    "n_clusters = 5\n",
    "method = 'ward'\n",
    "\n",
    "# Standardize the data (Z-transformation)\n",
    "X = StandardScaler().fit_transform(data_cluster)\n",
    "\n",
    "# Fit Agglomerative Clustering\n",
    "agg_clust = AgglomerativeClustering(n_clusters=n_clusters, linkage=method, compute_distances=True)\n",
    "agg_clust.fit(X)\n",
    "cluster_labels = agg_clust.labels_\n",
    "cluster_stats(cluster_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6dfb779b",
   "metadata": {},
   "source": [
    "The resulting clusters are labeled from 0 to 4. They are relatively balanced, with 21 observations in the largest cluster, two clusters with 15 and two clusters with 13. \n",
    "\n",
    "An interesting piece of information is contained in the `distances_` attribute. This shows the distances at which each cluster is formed, increasing from the smallest distance (here 0.36) to the one between the final two clusters that form the full data set (here 20.3)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "64b0c852",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.36274015,  0.53936027,  0.68178409,  0.71372655,  0.78778369,\n",
       "        0.79647585,  0.84125925,  0.84297015,  0.85370346,  0.8831146 ,\n",
       "        0.88675916,  0.92955806,  0.98841925,  1.05998996,  1.06438798,\n",
       "        1.07255791,  1.0765715 ,  1.1538963 ,  1.21130411,  1.25532594,\n",
       "        1.27768021,  1.32193569,  1.35293476,  1.36454495,  1.37498667,\n",
       "        1.37632845,  1.39756016,  1.41986327,  1.42228951,  1.42756184,\n",
       "        1.46881725,  1.51405012,  1.52158604,  1.53340115,  1.5670125 ,\n",
       "        1.73174358,  1.73496471,  1.78386891,  1.84018742,  1.89045915,\n",
       "        1.91123968,  1.94707456,  1.95727687,  1.99076458,  2.00088467,\n",
       "        2.04991017,  2.14413004,  2.28039251,  2.31301355,  2.41508411,\n",
       "        2.43475984,  2.47209374,  2.5891719 ,  2.63945666,  2.70434923,\n",
       "        2.85506842,  3.01764305,  3.08092386,  3.10174269,  3.14956205,\n",
       "        3.2148449 ,  4.25006606,  4.29530368,  4.56351567,  4.97645808,\n",
       "        5.18803816,  5.32611836,  5.50111751,  5.85655264,  6.29068946,\n",
       "        6.77711462,  7.92611783, 11.16248439, 12.85337461, 17.02788825,\n",
       "       20.30116606])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg_clust.distances_"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae818af1",
   "metadata": {},
   "source": [
    "### Dendrogram"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89218055",
   "metadata": {},
   "source": [
    "The scikit-learn functionality does not return a dendrogram. To visualize the hierarchy of grouping decisions, we use an alternative implementation, which is part of `scipy.cluster`, namely `scipy.cluster.hierarchy`. The setup is somewhat different from the scikit-learn approach and provides functions to compute hierarchical cluster results, with `linkage`. This returns a hierarchical cluster as a numpy array (see below), which can then be visualized as a `dendrogram`. In addition, other summaries are available as well, see https://docs.scipy.org/doc/scipy-1.15.0/reference/cluster.hierarchy.html for details.\n",
    "\n",
    "We illustrate this for our example. In a first step, we create the cluster result by applying `linkage` to the array `X` with the standardized values (the same as used above). A second argument is the method, again `\"ward\"`. This returns a numpy array with all the linkage information expressed in a n-1 by 4 matrix. In each row, the first two elements refer to cluster indices that are being combined, with values less than n referring to original observations, and values of n and larger referring to clusters that are combinations of earlier clusters. The third column gives the inter-cluster distance and the last column shows the number of original observations contained in the cluster.\n",
    "\n",
    "The inter-cluster distance shown in the third column is the same as what we had in the `distances` attribute of the cluster constructed with scikit-learn.\n",
    "\n",
    "In our example, we list the first five rows. In the first row, individual observations 59 and 62 are combined to yield a cluster of two (element in column 4). In the third row, observation 50 is combined with 77, which is the first cluster (or 59 and 62). As a result, it now consists of 3 elements (shown in the fourth column)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "24d7d591",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(76, 4)\n",
      "[[59.         62.          0.36274015  2.        ]\n",
      " [13.         21.          0.53936027  2.        ]\n",
      " [50.         77.          0.68178409  3.        ]\n",
      " [18.         20.          0.71372655  2.        ]\n",
      " [ 5.         22.          0.78778369  2.        ]]\n"
     ]
    }
   ],
   "source": [
    "Z = linkage(X, method='ward')\n",
    "print(Z.shape)\n",
    "print(Z[0:5,:])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8a1b140",
   "metadata": {},
   "source": [
    "The full set of distances (column 2) is identical to the values contained in `distances` above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "04f43880",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.36274015,  0.53936027,  0.68178409,  0.71372655,  0.78778369,\n",
       "        0.79647585,  0.84125925,  0.84297015,  0.85370346,  0.8831146 ,\n",
       "        0.88675916,  0.92955806,  0.98841925,  1.05998996,  1.06438798,\n",
       "        1.07255791,  1.0765715 ,  1.1538963 ,  1.21130411,  1.25532594,\n",
       "        1.27768021,  1.32193569,  1.35293476,  1.36454495,  1.37498667,\n",
       "        1.37632845,  1.39756016,  1.41986327,  1.42228951,  1.42756184,\n",
       "        1.46881725,  1.51405012,  1.52158604,  1.53340115,  1.5670125 ,\n",
       "        1.73174358,  1.73496471,  1.78386891,  1.84018742,  1.89045915,\n",
       "        1.91123968,  1.94707456,  1.95727687,  1.99076458,  2.00088467,\n",
       "        2.04991017,  2.14413004,  2.28039251,  2.31301355,  2.41508411,\n",
       "        2.43475984,  2.47209374,  2.5891719 ,  2.63945666,  2.70434923,\n",
       "        2.85506842,  3.01764305,  3.08092386,  3.10174269,  3.14956205,\n",
       "        3.2148449 ,  4.25006606,  4.29530368,  4.56351567,  4.97645808,\n",
       "        5.18803816,  5.32611836,  5.50111751,  5.85655264,  6.29068946,\n",
       "        6.77711462,  7.92611783, 11.16248439, 12.85337461, 17.02788825,\n",
       "       20.30116606])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Z[:,2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6626ee24",
   "metadata": {},
   "source": [
    "We can now proceed and graph the dendrogram. The `dendrogram` function takes the linkage array (`Z`) as well as several other arguments to fine tune the looks of the graph. The most important of these is `color_threshold`, which is the cut-off distance to define the clusters. Since the distances in `Z` are sorted from smallest to largest, the top distance corresponds to a single cluster, the next to last to a result with two clusters, etc. As a result, the cut-off distance for `n_clusters` is contained in position - (n_clusters - 1), or 1 - n_clusters. We pass this distance to `color_threshold` so that all the branches corresponding to each cluster are colored the same in the graph.\n",
    "\n",
    "Other arguments, are `orientation` (`top` for a top-down graph), `leaf_rotation` (`90` for the top-down graph), and `leaf_font_size` (size of the font of the observation label, here `7`). Some experimentation with these may be needed for each particular instance.\n",
    "\n",
    "We use `plt` to set the `figsize` and plot the graph. There are also options to create a dendrogram for larger data sets, where the full graph is no longer practical. This is not further considered (see the docs for details).\n",
    "\n",
    "The `dendrogram` function returns a dictionary that contains all the details necessary to construct the graph. Typically, this is not needed, except for an interesting application, shown below.\n",
    "\n",
    "First, we create the dendrogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5c328a8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,7))\n",
    "R1 = dendrogram(Z,orientation='top',leaf_rotation=90,\n",
    "           leaf_font_size=7,color_threshold=Z[1-n_clusters,2])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6a4acea",
   "metadata": {},
   "source": [
    "The dendrogram illustrates the steps by which the clusters are constructed, with the horizontal bars drawn at the height of the corresponding distance. For example, from the contents of `Z` above, we know that the first step is to combine 59 and 62, for a distance of 0.36. Indeed, we can find the lowest horizontal bar connecting 59 and 62 in the purple cluster. The second grouping, between 13 and 21, for a distance of 0.54 is shown in the brown cluster, etc.\n",
    "\n",
    "An interesting side result of the dendrogram calculation dictionary is the `\"leaves_color_list\"` item. It contains the color codes associated with each cluster as a distinct string. We can now use the `cluster_stats` function from our helper module to create a table with the cluster cardinality. Note that unlike what is the case in scikit-learn, cluster labels are not explicitly provided by the scipy.cluster functionality.\n",
    "\n",
    "The result again shows the five clusters, but now in a slightly different order."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "af835fff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Labels Cardinality\n",
      "0     C1          13\n",
      "1     C2          15\n",
      "2     C3          15\n",
      "3     C4          13\n",
      "4     C5          21\n"
     ]
    }
   ],
   "source": [
    "print(cluster_stats(R1[\"leaves_color_list\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d41261aa",
   "metadata": {},
   "source": [
    "#### `plot_dendrogram` helper function"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37caf93b",
   "metadata": {},
   "source": [
    "The helper function `plot_dendrogram` provides a one-line way to create a dendrogram plot. The first required argument is either the result of a `linkage` function as input (a numpy array), or a standardized data matrix. The default is to have the linkage result. If a standardized data matrix is the input, then the argument `package` must be set to `\"scikit\"` (the default is `\"scipy\"`, for a linkage result). The second required argument is the number of clusters, `n_clusters`.\n",
    "\n",
    "Other arguments include `labels` (default `None`) for any labels other than sequence numbers to be assigned to the leaves of the graph, a linkage method (default `\"ward\"`, only required when a standardized array is passed, otherwise ignored), and a couple of customizations of the plot. These consist of `figsize` (default `(12,7)`), and `title` (default \"Dendrogram\").\n",
    "\n",
    "Note that this function only works well for smallish data sets. Large data sets require further customization, not further considered here.\n",
    "\n",
    "In the example below, we pass `X`, keep the number of clusters to `n_clusters`, set\n",
    "the `package=\"scikit\"`, use the `community` variable from the data frame as the labels, and customize the title to `\"Ward Dendrogram\"`. The result dictionary is passed to `R2`, which is then used to summarize the cluster labels. The dendrogram is identical to the one above, except that now the community area names are used as labels for the observations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1a855a47",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "R2 = plot_dendrogram(X,n_clusters=n_clusters,package=\"scikit\",labels=dfs['community'].values, \n",
    "                title=\"Ward Dendrogram\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "b2f74d10",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Labels Cardinality\n",
      "0     C1          13\n",
      "1     C2          15\n",
      "2     C3          15\n",
      "3     C4          13\n",
      "4     C5          21\n"
     ]
    }
   ],
   "source": [
    "print(cluster_stats(R2[\"leaves_color_list\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51d70337",
   "metadata": {},
   "source": [
    "### Cluster Centers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b9933bc",
   "metadata": {},
   "source": [
    "A useful property of each cluster is its *center*, i.e., the mean or median of the variables for those observations included in the cluster.\n",
    "\n",
    "We accomplish this by means of a `groupby` computation on the cluster labels. These are first added to the data frame with the original observations (not the standardized values). The resulting centers can be visualized in a number of different ways, for example in a parallel coordinate plot or as a conditional box plot. This is not further pursued here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5c2bda9c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster Means \n",
      "          INCPERCAP  Und20   Ov65  Minrty  Unemprt  Noveh  Lt_high  Rentocc  \\\n",
      "cluster                                                                      \n",
      "0         34837.81  24.17  14.66   50.99     5.46   5.66    13.66    33.37   \n",
      "1         22405.93  23.39  19.44   94.75    16.61  13.73    16.41    40.44   \n",
      "2         62399.07  16.61  10.79   42.53     4.29  18.05     5.73    54.33   \n",
      "3         18938.69  30.29  10.61   89.55    10.88   6.69    30.92    41.98   \n",
      "4         19440.38  29.99  11.92   96.43    18.75  22.93    16.20    62.47   \n",
      "\n",
      "         Rntburd  Noeng  \n",
      "cluster                  \n",
      "0          19.05  45.71  \n",
      "1          28.29  12.52  \n",
      "2          21.55  25.26  \n",
      "3          25.13  73.03  \n",
      "4          38.88   7.23  \n",
      "Cluster Medians \n",
      "          INCPERCAP  Und20   Ov65  Minrty  Unemprt  Noveh  Lt_high  Rentocc  \\\n",
      "cluster                                                                      \n",
      "0          31267.0  23.60  15.63   57.22     5.21   5.80    14.69    30.76   \n",
      "1          21723.0  24.65  18.23   98.39    16.13  11.99    15.41    41.20   \n",
      "2          57167.0  17.34   9.62   43.40     4.02  19.41     5.77    56.28   \n",
      "3          19446.0  30.50  10.43   87.37    11.35   6.12    29.41    44.43   \n",
      "4          18641.0  29.41  11.94   97.45    17.07  22.14    13.45    61.76   \n",
      "\n",
      "         Rntburd  Noeng  \n",
      "cluster                  \n",
      "0          19.55  49.63  \n",
      "1          27.92   7.29  \n",
      "2          21.52  24.57  \n",
      "3          24.81  77.56  \n",
      "4          38.31   5.06  \n"
     ]
    }
   ],
   "source": [
    "dt_clust = data_cluster.copy().assign(cluster=cluster_labels)\n",
    "clust_means = dt_clust.groupby('cluster').mean()\n",
    "clust_medians = dt_clust.groupby('cluster').median()\n",
    "print(\"Cluster Means \\n\",np.round(clust_means,2))\n",
    "print(\"Cluster Medians \\n\",np.round(clust_medians,2))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a15c4cae",
   "metadata": {},
   "source": [
    "We have created a helper function in `spatial_cluster_course.py` to compute the cluster means and medians in a single command. The required arguments are a data frame with the variables used in the clustering exercise and an array of cluster labels. The function `cluster_center` returns a tuple with data frames of the means and medians.\n",
    "\n",
    "To illustrate this, we pass the `data_cluster` data frame and the `R2[\"leaves_color_list\"]` set of labels, and print out the means."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4bf2f407",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         INCPERCAP  Und20   Ov65  Minrty  Unemprt  Noveh  Lt_high  Rentocc  \\\n",
      "cluster                                                                      \n",
      "C1        32349.54  24.53  14.64   70.26    11.19  18.16    10.97    55.98   \n",
      "C2        29496.73  25.42  11.35   69.98     7.73   9.53    19.70    47.75   \n",
      "C3        40604.53  20.07  14.86   72.58     9.56  17.65    15.36    50.04   \n",
      "C4        30449.69  26.57  13.76   77.16    12.43  10.43    16.15    38.07   \n",
      "C5        30223.24  25.93  13.90   71.09    11.75   9.57    16.82    37.65   \n",
      "\n",
      "         Rntburd  Noeng  \n",
      "cluster                  \n",
      "C1         28.84  23.32  \n",
      "C2         26.47  46.41  \n",
      "C3         26.31  28.09  \n",
      "C4         23.28  31.36  \n",
      "C5         24.31  35.32  \n"
     ]
    }
   ],
   "source": [
    "c_means,c_medians = cluster_center(data_cluster,R2[\"leaves_color_list\"])\n",
    "print(np.round(c_means,2))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ddb7e04",
   "metadata": {},
   "source": [
    "### Cluster Fit"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71ab064a",
   "metadata": {},
   "source": [
    "The main objective of a clustering exercise is to decompose the total sum of squared differences from the mean (TSS) into a within cluster (WSS) and between cluster (BSS) part. The more similar the members of a cluster are, the smaller WSS will be. As a consequence, BSS will be larger, since the two are complements: TSS = WSS + BSS. The higher the ratio of BSS to WSS, the *better* the fit. \n",
    "\n",
    "Since we typically standardize the variables before the clustering exercise, the mean is zero and the variance for each variable equals 1, hence the TSS will equal k x n, where k is the number of variables and n is the number of observations. In our example, this would be 770. This is a direct result of how `StandardScaler` carries out the standardization, i.e., it uses n as the denominator in the computation of the variance/standard deviation. In contrast, `GeoDa` uses n-1 as the denominator (for an *unbiased* estimate). As a result, `GeoDa` will report 760 as the TSS. We address this in our helper function (`cluster_fit`), by rescaling `X` with $\\sqrt{(n-1)/n}$.\n",
    "\n",
    "First, we illustrate the steps using the `StandardScaler` approach. Note that the ratio BSS/TSS is not affected by the choice of the standardization, but the individual WSS and the TSS measures are.\n",
    "\n",
    "In order to compute the WSS by cluster, we need to compute the cluster means. In contrast to what we just carried out, now the calculation must be done for the standardized variables, but otherwise the approach is the same, using `groupby` for the cluster labels. In each cluster, the WSS is the sum of squared deviations from the mean. The sum of all the cluster-specific WSS is the total WSS. The BSS is obtained as TSS - WSS. The final ratio is BSS/TSS.\n",
    "\n",
    "First, the TSS."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5302a0e2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TSS 770.0\n"
     ]
    }
   ],
   "source": [
    "tss = np.sum(np.square(X))\n",
    "print(\"TSS\",tss)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b029dca",
   "metadata": {},
   "source": [
    "We compute the WSS for each cluster by first calculating the cluster mean using the same `groupby` approach as above, but now applied to the standardized variables. We then square the difference between each cluster member observation and the mean and sum the result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a147c882",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster WSS\n",
      " [81.496 68.007 57.317 22.29  44.942]\n"
     ]
    }
   ],
   "source": [
    "data_tmp = data_cluster.copy().assign(cluster=cluster_labels)\n",
    "wss_per_cluster = []\n",
    "for cluster in range(n_clusters):\n",
    "    cluster_data = X[data_tmp['cluster'] == cluster]\n",
    "    cluster_mean = cluster_data.mean(axis=0)\n",
    "    wss = np.sum(np.square(cluster_data - cluster_mean))\n",
    "    wss_per_cluster.append(wss)\n",
    "wss_per_cluster = [float(wss) for wss in wss_per_cluster]\n",
    "print(\"Cluster WSS\\n\",np.round(wss_per_cluster,3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ddb0cd7",
   "metadata": {},
   "source": [
    "The total WSS is simply the sum of the cluster-specific WSS."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2368fb8c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WSS  274.052\n"
     ]
    }
   ],
   "source": [
    "wss = np.sum(wss_per_cluster)\n",
    "print(\"WSS \",np.round(wss,3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a5c980d",
   "metadata": {},
   "source": [
    "Finally, the BSS is the complement of WSS, or TSS - WSS and the ratio BSS/TSS can be computed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "13b4748f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BSS  495.948 BSS/TSS  0.644\n"
     ]
    }
   ],
   "source": [
    "bss = tss - wss\n",
    "btratio = bss/tss\n",
    "print(\"BSS \",np.round(bss,3), \"BSS/TSS \",np.round(btratio,3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef5f6985",
   "metadata": {},
   "source": [
    "The helper function `cluster_fit` carries out these calculations and returns them as a dictionary, optionally listing the result.\n",
    "\n",
    "Its required arguments are `data` for the original cluster variable observations, `clustlabels` for the cluster labels (to carry out the `groupby`), and `n_clusters`, the number of clusters. Optional arguments are `correct` (default is `False`) and `printopt` (default is `True`). Computing the standardized values with n-1 as the denominator is achieved by setting `correct = True`, and avoiding a listing of the results is set with `printopt = False`.\n",
    "\n",
    "We first illustrate this for the standard options. The results are identical to those shown above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b4a66b06",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Total Sum of Squares (TSS): 770.0\n",
      "Within-cluster Sum of Squares (WSS) for each cluster: [81.496 68.007 57.317 22.29  44.942]\n",
      "Total Within-cluster Sum of Squares (WSS): 274.052\n",
      "Between-cluster Sum of Squares (BSS): 495.948\n",
      "Ratio of BSS to TSS: 0.644\n"
     ]
    }
   ],
   "source": [
    "clusfit = cluster_fit(data=data_cluster,clustlabels=cluster_labels,\n",
    "                 n_clusters=n_clusters)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7070a04a",
   "metadata": {},
   "source": [
    "With `correct = True`, the standardization is different. The results now replicate those given by `GeoDa`. Note how the BSS/TSS ratio is unaffected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "be4e1df3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Total Sum of Squares (TSS): 760.0\n",
      "Within-cluster Sum of Squares (WSS) for each cluster: [80.437 67.124 56.572 22.    44.358]\n",
      "Total Within-cluster Sum of Squares (WSS): 270.493\n",
      "Between-cluster Sum of Squares (BSS): 489.507\n",
      "Ratio of BSS to TSS: 0.644\n"
     ]
    }
   ],
   "source": [
    "clusfit = cluster_fit(data=data_cluster,clustlabels=cluster_labels,\n",
    "                 n_clusters=n_clusters,correct=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55645f78",
   "metadata": {},
   "source": [
    "### Cluster Map"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c00f373",
   "metadata": {},
   "source": [
    "A final summary of the cluster results is a cluster map, a simple categorical thematic map that highlights the membership of clusters.\n",
    "\n",
    "We proceed in the usual fashion, first adding the cluster labels to a temporary geodataframe, then creating a simple map for the `column` equal to the cluster label and the color map as `Set2`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "369a7862",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "    gdf_temp = dfs.copy()\n",
    "    gdf_temp['cluster'] = cluster_labels.astype(str) \n",
    "    fig, ax = plt.subplots(figsize=(5,5))\n",
    "    gdf_temp.plot(column='cluster', ax=ax, legend=True, cmap='Set2',\n",
    "            legend_kwds={'bbox_to_anchor': (1, 0.5), 'loc': 'center left'}) \n",
    "    ax.set_title(\"Ward Hierarchical Clusters\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "596c1405",
   "metadata": {},
   "source": [
    "The cluster map is implemented in the helper function `cluster_map`, with some very simple defaults. It takes as required arguments the geodata frame and the cluster labels. Other arguments are `figsize` (default `(5,5)`), `title` (default `\"Clusters\"`), and `cmap` for the color map (default `\"Set2\"`).\n",
    "\n",
    "In our example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "adf5f90f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cluster_map(dfs, cluster_labels, figsize=(5,5), title=\"Ward Linkage Clusters\", cmap='Set2')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd47d611",
   "metadata": {},
   "source": [
    "## Other Linkage Functions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a18130ab",
   "metadata": {},
   "source": [
    "The other linkage functions are invoked with methods `\"single\"`, `\"complete\"` and `\"average\"`. Rather than completing the same commands each time, we create a loop over the linkage functions and use our helper functions to list the cluster results, centers, measures of fit and the cluster map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7f6cc3d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---------------------------------\n",
      "\n",
      "Clusters single linkage \n",
      "    Labels  Cardinality\n",
      "0       0           73\n",
      "1       1            1\n",
      "2       2            1\n",
      "3       3            1\n",
      "4       4            1\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster Means \n",
      "          INCPERCAP  Und20   Ov65  Minrty  Unemprt  Noveh  Lt_high  Rentocc  \\\n",
      "cluster                                                                      \n",
      "0         33320.42  24.59  13.31   70.78    10.01  12.04    15.64    44.51   \n",
      "1         19972.00  13.31  26.52   99.50    20.14  16.95    15.41    36.60   \n",
      "2         11857.00  44.28   4.80   98.79    30.42  30.33    15.69    76.92   \n",
      "3         16519.00  19.88  26.44   96.37    23.62  34.31    21.40    56.20   \n",
      "4         21858.00  18.54  24.82   86.05     8.21  19.92    37.18    61.19   \n",
      "\n",
      "         Rntburd  Noeng  \n",
      "cluster                  \n",
      "0          25.49  34.05  \n",
      "1          29.95   4.41  \n",
      "2          30.71   3.09  \n",
      "3          31.26   7.38  \n",
      "4          27.29  69.47  \n",
      "Cluster Medians \n",
      "          INCPERCAP  Und20   Ov65  Minrty  Unemprt  Noveh  Lt_high  Rentocc  \\\n",
      "cluster                                                                      \n",
      "0          26943.0  25.14  12.73   82.70     8.34  10.01    14.41    48.32   \n",
      "1          19972.0  13.31  26.52   99.50    20.14  16.95    15.41    36.60   \n",
      "2          11857.0  44.28   4.80   98.79    30.42  30.33    15.69    76.92   \n",
      "3          16519.0  19.88  26.44   96.37    23.62  34.31    21.40    56.20   \n",
      "4          21858.0  18.54  24.82   86.05     8.21  19.92    37.18    61.19   \n",
      "\n",
      "         Rntburd  Noeng  \n",
      "cluster                  \n",
      "0          23.62  28.02  \n",
      "1          29.95   4.41  \n",
      "2          30.71   3.09  \n",
      "3          31.26   7.38  \n",
      "4          27.29  69.47  \n",
      "\n",
      "Total Sum of Squares (TSS): 770.0\n",
      "Within-cluster Sum of Squares (WSS) for each cluster: [677.299   0.      0.      0.      0.   ]\n",
      "Total Within-cluster Sum of Squares (WSS): 677.299\n",
      "Between-cluster Sum of Squares (BSS): 92.701\n",
      "Ratio of BSS to TSS: 0.12\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---------------------------------\n",
      "\n",
      "Clusters complete linkage \n",
      "    Labels  Cardinality\n",
      "0       0           21\n",
      "1       1           29\n",
      "2       2            3\n",
      "3       3           10\n",
      "4       4           14\n"
     ]
    },
    {
     "data": {
      "image/png": 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AkCEBDbh//fVX6dSpk9x3330iIlK+fHmZN2+ebNmyJZDZAgAAAAAgwwLapLxp06ayevVq+fPPP0VEZNeuXbJx40bp0KGDYfr4+Hi5cuWKyx8AAAAAANlRQGu4hw0bJleuXJFq1apJvnz5JDk5WcaNGyc9evQwTD9+/HgZO3ZsFucSAAAAAADzAlrDvWDBApk7d6589dVXsn37dpkzZ45MnjxZ5syZY5h++PDhEhsb6/g7fvx4FucYAAAAAADfBLSG+5VXXpFhw4bJY489JiIitWvXlmPHjsn48eOlV69ebunDw8MlPDw8q7MJAAAAAIBpAa3hjouLk+Bg1yzky5dPUlJSApQjAAAAAAAyR0BruB944AEZN26clC1bVmrWrCk7duyQd955R/r27RvIbAEAAAAAkGEBDbjfe+89GTlypDz//PNy9uxZKV26tPznP/+RUaNGBTJbAAAAAABkWEAD7kKFCsnUqVNl6tSpgcwGAAAAAACZLqB9uAEAAAAAyK0CWsMNAACQHamq2BKTA50N5CJxCUmGj4HMEBGaT4KCggKdDRgg4AYAAHCiqvLIh7/J78cuBToryKXqv7k60FlALlO/XFFZ+FwTgu5siCblAAAATmyJyQTbAHKUbccu0Sonm6KGGwAAwINtr7WTAmH5Ap0NADAUl5As9d9cFehswAsCbgAAAA8KhOWTAmEUlwAA/qFJOQAAAAAAFiDgBgAAAADAAgTcAAAAAABYgIAbAAAAAAALEHADAAAAAGABAm4AAAAAACxAwA0AAAAAgAUIuAEAAAAAsAABNwAAAAAAFiDgBgAAAADAAgTcAAAAAABYgIAbAAAAAAALEHADAAAAAGABAm4AAAAAACxAwA0AAAAAgAUIuAEAAAAAsAABNwAAAAAAFiDgBgAAAADAAgTcAAAAAABYgIAbAAAAAAALEHADAAAAAGABAm4AAAAAACxAwA0AAAAAgAUIuAEAAAAAsAABNwAAAAAAFiDgBgAAAADAAgTcAAAAAABYgIAbAAAAAAALEHADAAAAAGABAm4AAAAAACxAwA0AAAAAgAUIuAEAAAAAsAABNwAAAAAAFiDgBgAAAADAAgTcAAAAAABYICTQGYCIqootMTnQ2UAmiEtIMnyMnC8iNJ8EBQUFOhsAAADIQQi4A0xV5ZEPf5Pfj10KdFaQyeq/uTrQWUAmql+uqCx8rglBNwAAAHxGk/IAsyUmE2wDOcC2Y5doiQIAAABTqOHORra91k4KhOULdDYAOIlLSJb6b64KdDYAAACQAxFwZyMFwvJJgTB+EgAAAADIDYjuAAAAAGRbDDDsGQP2+iaQg98ScAMAAADIlhhg2HcM2OtZIAe/ZdA0AAAAANkSAwwjMwRy8FtquAEAAABkewwwDLOyw+C3BNwAAAAAsj0GGEZORJNyAAAAAAAsQMANAAAAAIAFCLgBAAAAALAAATcAAAAAABYg4AYAAAAAwAIE3AAAAAAAWICAGwAAAAAACxBwAwAAAABgAQJuAAAAAAAsQMANAAAAAIAFCLgBAAAAALAAATcAAAAAABYg4AYAAAAAwAIE3AAAAAAAWICAGwAAAAAACxBwAwAAAABgAQJuAAAAAAAsQMANAAAAAIAFCLgBAAAAALAAATcAAAAAABYg4AYAAAAAwAIE3AAAAAAAWICAGwAAAAAACxBwAwAAAABgAQJuAAAAAAAsQMANAAAAAIAFCLgBAAAAALAAATcAAAAAABYg4AYAAAAAwAIE3AAAAAAAWICAGwAAAAAACxBwAwAAAABgAQJuAAAAAAAsQMANAAAAAIAFCLgBAAAAALAAATcAAAAAABYg4AYAAAAAwAIE3AAAAAAAWICAGwAAAAAACxBwAwAAAABgAQJuAAAAAAAsQMANAAAAAIAFCLgBAAAAALAAATcAAAAAABYg4AYAAAAAwAIE3AAAAAAAWICAGwAAAAAACwQ84D558qQ88cQTUrx4cYmIiJDatWvLtm3bAp0tAAAAAAAyJCSQH37p0iVp1qyZtGnTRlasWCElS5aUv/76S4oWLRrIbAEAAAAAkGEBDbgnTpwokZGRMmvWLMeyChUqeEwfHx8v8fHxjudXrlyxNH8AAAAAAPgroE3Kly1bJvXr15euXbtKqVKlJCoqSj755BOP6cePHy+FCxd2/EVGRmZhbgEAAAAA8F1AA+6///5bZsyYIVWqVJEffvhB+vXrJy+++KLMmTPHMP3w4cMlNjbW8Xf8+PEszjEAAAAAAL4JaJPylJQUqV+/vrz11lsiIhIVFSV79+6VDz/8UHr16uWWPjw8XMLDw7M6mwAA5HmqKmqzBTobWSIlIfm/j+NskpKUL4C5yTpBERESFBQU6GwAQK4S0ID7tttukxo1argsq169unz99dcByhEAAEhLVeVY9x5i27Ej0FnJEjfyhYk8kFoZ8Fez5pI/OSHAOcoaEdHRUm7ulwTdAJCJAhpwN2vWTP744w+XZX/++aeUK1cuQDkCAABpqc2WZ4JtEZH8yQmy4pshgc5GlrNt3y5qs0lQgQKBzgoA5BoBDbgHDRokTZs2lbfeeku6desmW7ZskY8//lg+/vjjQGYLAAB4UOWXjRIcERHobCATpdhs8lez5oHOBgDkSgENuBs0aCBLliyR4cOHy+uvvy4VKlSQqVOnSo8ePQKZLQAA4EFwRIQEUwMKAIBPAhpwi4jcf//9cv/99wc6GwAAAAAAZKqATgsGAAAAAEBuRcANAAAAAIAFCLgBAAAAALAAATcAAAAAABYg4AYAAAAAwAIE3AAAAAAAWICAGwAAAAAACxBwAwAAAABgAQJuAAAAAAAsQMANAAAAAIAFCLgBAAAAALBASKAzAMAzVRVbki3Q2cjT4hKTnR7bRILyBTA3iAiJkKCgoEBnAwAAwCcE3EA2parSc0VP2XluZ6CzkqdpSqiIvCEiIq0XtJKg4MTAZiiPiyoVJXPunUPQDQAAcgQCbiCbsiXZCLazgaDgRClUfVigs4H/t+PsDrEl2aRAaIFAZwUAACBdBNxADrCu2zqJCIkIdDaAgLEl2aT1gtaBzgYAAIApBNxADhAREkGNHgAAAJDDMEo5AAAAAAAWIOAGAAAAAMACBNwAAAAAAFiAgBsAAAAAAAsQcAMAAAAAYAECbgAAAAAALJDhgPvGjRuZkQ8AAAAAAHIVvwLulJQUeeONN+T222+Xm266Sf7++28RERk5cqR89tlnmZpBAAAAAAByIr8C7jfffFNmz54tkyZNkrCwMMfyWrVqyaeffpppmQMAAAAAIKfyK+D+/PPP5eOPP5YePXpIvnz5HMvr1q0rBw8ezLTMAQAAAACQU/kVcJ88eVIqV67stjwlJUUSExMznCkAAAAAAHI6vwLuGjVqyM8//+y2fNGiRRIVFZXhTAEAAAAAkNOF+POmUaNGSa9eveTkyZOSkpIiixcvlj/++EM+//xz+e677zI7jwAAAAAA5Dh+1XB36tRJvv32W1m1apUULFhQRo0aJQcOHJBvv/1W7r777szOIwAAAAAAOY5fNdwiIi1atJCffvopM/MCAAAAAECu4VcN99atW2Xz5s1uyzdv3izbtm3LcKYAAAAAAMjp/Aq4+/fvL8ePH3dbfvLkSenfv3+GMwUAAAAAQE7nV8C9f/9+iY6OdlseFRUl+/fvz3CmAAAAAADI6fwKuMPDw+XMmTNuy0+dOiUhIX53CwcAAAAAINfwK+C+5557ZPjw4RIbG+tYdvnyZRkxYgSjlAMAAAAAIH6OUj558mRp2bKllCtXTqKiokREZOfOnXLLLbfIF198kakZBAAAAAAgJ/Ir4L799ttl9+7dMnfuXNm1a5dERERInz595PHHH5fQ0NDMziMAAAAAADmO3x2uCxYsKM8++2xm5gUAAAAAgFzD74D7r7/+krVr18rZs2clJSXF5bVRo0ZlOGMAAAAAAORkfgXcn3zyifTr109KlCght956qwQFBTleCwoKIuAGAAAAAOR5fgXcb775powbN05effXVzM4PAAAAAAC5gl/Tgl26dEm6du2a2XkBAAAAACDX8Cvg7tq1q/z444+ZnRcAAAAAAHINv5qUV65cWUaOHCmbNm2S2rVru00F9uKLL2ZK5gAAAAAAyKn8Crg//vhjuemmm2T9+vWyfv16l9eCgoIIuAEAAAAAeZ5fAfeRI0cyOx8AAAAAAOQqfvXhBgAAAAAA3vlVwy0icuLECVm2bJn8888/kpCQ4PLaO++8k+GMAQAAAACQk/kVcK9evVoefPBBqVixohw8eFBq1aolR48eFVWV6OjozM4jAAAAAAA5jl9NyocPHy5DhgyRPXv2SP78+eXrr7+W48ePS6tWrZifGwAAAAAA8TPgPnDggPTs2VNEREJCQsRms8lNN90kr7/+ukycODFTMwgAAAAAQE7kV8BdsGBBR7/t2267TQ4fPux47fz585mTMwAAAAAAcjC/+nA3btxYNm7cKNWrV5eOHTvKyy+/LHv27JHFixdL48aNMzuPAAAAAADkOH4F3O+8845cu3ZNRETGjh0r165dk5iYGKlSpQojlAMAAAAAIH4G3BUrVnQ8LliwoHz44YeZliEAAAAAAHIDvwPurVu3SvHixV2WX758WaKjo+Xvv//OlMwBAKyhqmJLsgU6Gz5zzmtOyrddREiEBAUFBTobAAAgi/kVcB89elSSk5PdlsfHx8vJkycznCkAgHVUVXqu6Ck7z+0MdFb80npB60BnwbSoUlEy5945BN0AAOQxpgLuZcuWOR7/8MMPUrhwYcfz5ORkWb16tZQvXz7TMgcAyHy2JFuODbZzqh1nd4gtySYFQgsEOisAACALmQq4O3fuLCIiQUFB0qtXL5fXQkNDpXz58jJlypRMyxwAwFrruq2TiJCIQGcj17Il2XJkjTwAAMgcpgLulJQUERGpUKGCbN26VUqUKGFJpgAAWSMiJIJaV0BSu1qoLeeND5AZUpy+d0oe3QZ2QRGMtwAgc/nVh/vIkSNuyy5fvixFihTJaH4AAACylKrKse49xLZjR6CzEnB/NWse6CwEVER0tJSb+yVBN4BME+zPmyZOnCgxMTGO5127dpVixYrJ7bffLrt27cq0zAEAAFhNbTaCbYiIiG379jzb0gGANfyq4f7www9l7ty5IiLy008/yapVq2TlypWyYMECeeWVV+THH3/M1EwCAABkhSq/bJTgCMY1yGtSbLY8X7sPwBp+BdynT5+WyMhIERH57rvvpFu3bnLPPfdI+fLlpVGjRpmaQQAAgKwSHBEhwQUY1wAAkDn8alJetGhROX78uIiIrFy5Utq1ayciqX2gjObnBgAAAAAgr/Grhvuhhx6S7t27S5UqVeTChQvSoUMHERHZsWOHVK5cOVMzCAAAAABATuRXwP2///u/Ur58eTl+/LhMmjRJbrrpJhEROXXqlDz//POZmkEAAAAAAHIivwLu0NBQGTJkiNvyQYMGZThDAAAAAADkBj4H3MuWLZMOHTpIaGioLFu2zGvaBx98MMMZAwAAAAAgJ/M54O7cubOcPn1aSpUqJZ07d/aYLigoKGcPnKYqkhiXdZ+X4LStEuJEJF/WfG5oAZGgoKz5LAAAAADIg3wOuFNSUgwf5yqqIjPbixzfnIWfGS4is1Ifv11ZJCg+az43srFI35UE3QAAAABgEdN9uFNSUmT27NmyePFiOXr0qAQFBUnFihXl4YcflieffFKCcnIAlxiXtcG2iBQIipej+btn6WeKiMjxTanfN6xg1n82AAAAAOQBpgJuVZUHH3xQli9fLnXr1pXatWuLqsqBAwekd+/esnjxYvnmm28symoWG3JIJKxAoHOR+RLiRCYzdRsAAAAAWM1UwD179mzZsGGDrF69Wtq0aePy2po1a6Rz587y+eefS8+ePTM1kwERVoDaXwAAAACA34LNJJ43b56MGDHCLdgWEWnbtq0MGzZM5s6dm2mZAwAAAAAgpzIVcO/evVvuvfdej6936NBBdu3aleFMAQAAAACQ05kKuC9evCi33HKLx9dvueUWuXTpUoYzBQAAAABATmcq4E5OTpaQEM/dvvPlyydJSUkZzhQAAAAAADmd6VHKe/fuLeHh4Yavx8dn0RzSAAAAAABkc6YC7l69eqWbJleMUA4AAAAAQAaZCrhnzZplVT4AAAAAAMhVTPXhBgAAAAAAviHgBgAAAADAAgTcAAAAAABYgIAbAAAAAAALmBo0DQAAAACA7EBVJcnL1NSJCcn/fXwjXhJTkjymDQkPl6CgoEzNnwgBNwAAAAAgh1FVmT9qqPz75wGPaRKDQkTKPyMiIjOe7SGh6jngLl21hjw2dmKmB90E3AAAAACAHCUpPt5rsC0iEqpJMuDIDJ/W9+8f+yUpPl5C8+fPjOw5EHADAAAAAHKsfh9/KaHh/gXKifE3ZMazT2Ryjv6LgBsAAAAAkGOFhufP9JrpzMIo5QAAAAAAWIAabkBSB12wJdkCnQ0XzvnJbnmziwiJsGQ0RwAAACA3IOBGnqeq0nNFT9l5bmegs+JR6wWtA50FQ1GlomTOvXMIugEAAAADNClHnmdLsmXrYDs723F2R7atfQcAAAACjRpuwMm6buskIiQi0NnI9mxJtmxb6w4AAABkFwTcgJOIkAgpEFog0NkAAAAAkAtkmyblEyZMkKCgIBk4cGCgswIAAAAAQIZli4B769at8tFHH0mdOnUCnRUAAAAAADJFwAPua9euSY8ePeSTTz6RokWLBjo7AAAAAABkioAH3P3795f77rtP2rVrl27a+Ph4uXLlissfAAAAAADZUUAHTZs/f75s375dtm7d6lP68ePHy9ixYy3OFQAAAAAAGRewGu7jx4/LSy+9JHPnzpX8+fP79J7hw4dLbGys4+/48eMW5xIAAAAAAP8ErIb7999/l7Nnz0p0dLRjWXJysmzYsEHef/99iY+Pl3z58rm8Jzw8XMLDw7M6qwAAAAAAmBawgPuuu+6SPXv2uCzr06ePVKtWTV599VW3YBsAAAAAgJwkYAF3oUKFpFatWi7LChYsKMWLF3dbDgAAAABAThPwUcoBAAAAAMiNAjpKeVrr1q0LdBYAAAAAAMgU1HADAAAAAGABAm4AAAAAACxAwA0AAAAAgAUIuAEAAAAAsAABNwAAAAAAFiDgBgAAAADAAgTcAAAAAABYgIAbAAAAAAALEHADAAAAAGABAm4AAAAAACxAwA0AAAAAgAUIuAEAAAAAsEBIoDMAAAAAqKqozRaQz05x+tyUAOUhKCJCgoKCAvLZAKxDwA0AAICAUlU51r2H2HbsCHRW5K9mzQPyuRHR0VJu7pcE3UAuQ8ANAMjTVFVsSdbUaDmv16rPiAihVgw5n9ps2SLYDiTb9u2iNpsEFSgQ6KwAyEQE3ACAPEtVpeeKnrLz3E7LP6v1gtaWrDeqVJTMuXcOQTdyjSq/bJTgiIhAZyPLpNhsAatVB2A9Am4AQJ5lS7JlSbBtpR1nd4gtySYFQqkVQ+4QHBEhwdTyAsglCLgBABCRdd3WSURIzqlVsyXZLKs1BwAAmYOAGwAASe0LTS0xAADITMzDDQAAAACABQi4AQAAAACwAAE3AAAAAAAWIOAGAAAAAMACBNwAAAAAAFiAgBsAAAAAAAsQcAMAAAAAYAECbgAAAAAALEDADQAAAACABUICnQEAAAAAOYeqSlJCSpZ8VmJC8n8fxydLogZlyeeKiISEBUtQUNZ9HnInAm4AAAAAPlFVWfz2djn9d2yWfF6CqEiR1MczX9koYZJ1AfBtlQpLlyHRBN3IEAJuAAAAAD5JSkjJsmBbRCRMguSVyxFZ9nnOTh2OlaSEFAkNzxeQz0fuQMANAACyFVUVtdmy7PNSnD4rJQs/Nygigpoz5Gh9JjXPlcFoYnyyzBq6MdDZQC5BwA0AALINVZVj3XuIbceOgHz+X82aZ9lnRURHS7m5XxJ0I8cKDc+XKwNuIDMxSjkAAMg21GYLWLCd1Wzbt2dpTT4AIOtRww0AALKlKr9slOCIwPTdtFKKzZalNekAgMAh4AYAANlScESEBBcoEOhsAADgN5qUAwAAAABgAQJuAAAAAAAsQMANAAAAAIAFCLgBAAAAALAAATcAAAAAABYg4AYAAAAAwAIE3AAAAAAAWICAGwAAAAAACxBwAwAAAABgAQJuAAAAAAAsQMANAAAAAIAFCLgBAAAAALAAATcAAAAAABYICXQGAPhPVcWWZMvyz3X+zEB8fkRIhAQFBWX55wIAAABmEHADOZSqSs8VPWXnuZ0BzUfrBa2z/DOjSkXJnHvnEHQDAJDLqaokJaRk6WcmxicbPs4qIWHBlHFyEQLu3EJVJDEu/XQJccaPvQktIMJBn+3YkmwBD7YDZcfZHWJLskmB0AKBzgoAALCIqsrit7fL6b9jA5aHWUM3Zvln3lapsHQZEk3QnUsQcOcGqiIz24sc32zufZMr+5YusrFI35UE3dnYum7rJCIkItDZsJwtyRaQGnUAAJD1khJSAhpsB8qpw7GSlJAioeH5Ap0VZAIC7twgMc58sG3G8U2pnxFW0LrPQIZEhERQ2wsAAHKtPpOa5/oANDE+OSA16nmJqkpSfLzLssT4G4aP7ULCwzPU2oCAO7cZckgkLJMCr4Q432vBAQAAAIuEhufL9QE3rKWqMn/UUPn3zwMe08x49gm3ZaWr1pDHxk70O+gm4M5twgpQEw0AAAAATpLi470G2578+8d+SYqPl9D8+f36XAJuAAAAAECe0e/jLyU03HsAnRh/w7DG2ywCbgAAAABAnhEant/vGmuzgrPkUwAAAAAAyGMIuAEAAAAAsAABNwAAAAAAFqAPNwDkEKoqtiRbhtfjvI7MWJ9I6lzwGZmjEgCQ/aiqJCWkuCxLjE82fGwXEhbM9QBwQsANADmAqkrPFT1l57mdmbre1gtaZ8p6okpFyZx751DIAoBcQlVl8dvb5fTfsR7TzBq60W3ZbZUKS5ch0VwPgP9HwI1cxZ8awIzU9lGrh6xiS7JlerCdmXac3SG2JJsUCC0Q6KwAADJBUkKK12Dbk1OHYyUpIUVCw/NZkCsg5yHgRq6RGTWAZmv7qNVDIKzrtk4iQiICnQ0RSb0RkFm15ACA7KnPpObpBtCJ8cmGNd5AXkfAjVwjEDWA1OohECJCItjnAABZJjQ8HzXWgJ8IuJErWV0DSK0eAABIj6qK2rx3V0txej0lnbR2QRF0aQNyitwZcKuKJMaZf19CnPFjM0ILiHACDDhqAAEAQCCpqhzr3kNsO3b4/J6/mjX3KV1EdLSUm/slQTeQA+S+gFtVZGZ7keObM7aeyZX9e19kY5G+Kwm6AQAA8jC12UwF22bYtm8XtdkkqACVC0B2l/sC7sS4jAfbGXF8U2oewgoGLg8AAADINqr8slGCIzLe1S3FZvO5FhxA9pD7Am5nQw6JhGXRnb+EOP9rxQEAQI7nS39dEfrs5kXBERESTG00kCfl7oA7rAA1zQAAwHL+9NcVoc8uAOR2wYHOAAAAQE5nZX9dkf/22QUA5Cy5u4YbAAAgi2VWf10R+uwCQE5HwA0AAJCJ6K8LALCjSTkAAAAAABYg4AYAAAAAwAIE3AAAAAAAWICAGwAAAAAACzBoGmBAVcWW5Hn6FefXvKUTEYkIiWDeVAAAACAPIuAG0lBV6bmip+w8t9On9K0XtPb6elSpKJlz7xyCbgBAnqCqpucMT3FKn+LnfONBEdzgBpD9EHADadiSbD4H277YcXaH2JJsUiCUKWIAALmbqsqx7j3EtmOH3+vwd97xiOhoKTf3S4JuANkKATfgxbpu6yQiJMKv99qSbOnWfgMAkJuozZahYDsjbNu3i9psEsQc6ACyEQJuwIuIkAhqpgEA8EOVXzZKcIR/N63NSLHZ/K4VBwCrEXADAAAg0wVHREgwtc0A8jgCbgAAsqGcPluCPwNniWTO4FkiDKAFAMgeCLgBAMhmcvpsCZkxcJaI/4NniTCAFgAgewgOdAYAAIArq2ZLyCqBHDjLzj6AFgAAgUQNN4BMlV4z2Iww04Q2IwLR/BbwJKfPlpBVA2fZMYAWACA7IeAGkGnMNoPNCCuDiKxufgt4k9NnS2DgLABAXkaTcgCZJrObwQZKVje/BQAAQO5EDTcAS2SkGWygZIfmtwAAAMg9CLgBWCKnN4MFAAAAMoom5QAAAAAAWICAGwAAAAAACxBwAwAAAABgAfpwAwAAAIAPVFWSElIsWXdifLLh48wWEhbM1KdZiIAbAAAAANKhqrL47e1y+u9Yyz9r1tCNlq37tkqFpcuQaILuLBLQJuXjx4+XBg0aSKFChaRUqVLSuXNn+eOPPwKZJQAAAABwk5SQkiXBttVOHY61rJYe7gJaw71+/Xrp37+/NGjQQJKSkmTEiBFyzz33yP79+6VgwYKBzBoAAAAAGOozqbmEhucLdDZMSYxPtrTmHMYCGnCvXLnS5fns2bOlVKlS8vvvv0vLli0DlCsg+1FVsSXZXJY5P0/7mkjqPNg0FQIAAMh8oeH5clzAjcDIVn24Y2NTm2gUK1bM8PX4+HiJj493PL9y5UqW5AsIJFWVnit6ys5zOz2mab2gtduyqFJRMufeOQTdAAAAQIBkm2nBUlJSZODAgdKsWTOpVauWYZrx48dL4cKFHX+RkZFZnEsg69mSbF6DbU92nN1hWPMNAAAAIGtkmxru/v37y969e2XjRs/9CoYPHy6DBw92PL9y5QpBN/KUdd3WSURIhNc0tiSbYY03AAAAgKyVLQLuF154Qb777jvZsGGDlClTxmO68PBwCQ8Pz8KcAdlLREiEFAgtEOhsADmC0dgHaaU3FoIRxkcAAAC+CmjAraoyYMAAWbJkiaxbt04qVKgQyOwAAHIJX8Y+SMvXliGMjwAAAHwV0IC7f//+8tVXX8nSpUulUKFCcvr0aRERKVy4sEREeG82CwCwji+1wyLZt4bY37EPfGEfH4HWJsgoVRW1eT9uUpxeT0knrV1QRO5oheHL9hExv41yy/YBkDMENOCeMWOGiIi0bt3aZfmsWbOkd+/eWZ+htFRFEuN8S5sQZ/w4PaEFRDjpA8hG/KkdFsm+NcS+jH3gC8ZHQGZSVTnWvYfYduzw+T1/NWvuU7qI6GgpN/fLHB1U+rN9RHzbRrlh+wDIOQLepDzbUhWZ2V7k+Gbz751c2fe0kY1F+q4k6AaQbVhZOyyS9TXEjH2A7EhtNtPBpK9s27eL2mwSVCDn7vdsHwC5RbYYNC1bSozzL9g26/im1M8KK2j9ZwGASZlVOyxCDTHgSZVfNkpwJnSlS7HZfK4Fz0nYPgByMgJuXww5JBKWyXdBE+LM1YQDQABQOwxYLzgiQoKpbfWI7QMgJyPg9kVYAWqgAQAAAACmBAc6AwAAAAAA5EYE3AAAAAAAWIAm5QAASPpzj5uZczwr5hrPK3ydi9nOn3mrRZibGUDOoqqSlJBi6j2J8cmGj30VEhbMedIPBNwAgDzP7Nzj6Y22ntVzjedW/s7FbGdmRGrmZgaQU6iqLH57u5z+O9bvdcwautH0e26rVFi6DInmPGkSAXdepZo6HZk3CXHGj70JLcCc4gBynMyeezyr5xrPraycizkt5mYGkFMkJaRkKNj216nDsZKUkCKh4fmy/LNzMgLuvEhVZGZ7c/OM+zqFWWRjkb4rCboB5FgZmXucucatk1lzMafF3MwAcrI+k5pbHgAnxif7VSOOVATceVFinLlg24zjm1LXzzRqAHIo5h7PnpiLGQDchYbno8Y5myPgzuuGHEqdZzyjEuJ8rwUHAAAAgDyAgDuvCytAbTRytfRGnnZmZhRqZ4xIDQAAACME3AByLbMjTzsz0w+XEakBAABgJDjQGQAAq2T2yNOe2EekBgAAAJxRww0gT8jIyNMiqbXlN5JvuCyzJdmkw+IOjsdp0dQcAAAgbyPgBpAnZGTkaV+aphs1QaepOQAAQN5Gk3IASIe/TdNpag4AAJC3UcOdFVRT56Z2lhBn/NhZaAERasaAbMWXpum2JJupQdcAICdSVVGb603FFKfnKTb3G45BEXS1AZC3EHBbTVVkZnuR45s9p/E0f3VkY5G+Kwm6gWwkI03TASC3UFU51r2H2Hbs8Jjmr2bN3ZZFREdLublfEnQDyDNoUm61xDjvwbY3xze514wDAAAEmNpsXoNtT2zbt7vVigNAbkYNd1YackgkzIeasYQ4z7XeAAAgTzJqwu0svebczjKzaXeVXzZKcIT3rjYpNpthjTcA5HYE3FkprIBIWMFA5wIAAOQwvjThdpZecJuZTbuDIyIkuABdbTJDdr2pAsB/BNzIkVTVbfRn5+fMiQwAyE38bcLtib1pdxCBcraRnW+qWEVVJSkhxePrifHJho+NhIQFZ+vviryLgBs5DnMiAwDyMl+acHtC0+7sK6/dVFFVWfz2djn9d6xP6WcN3ej19dsqFZYuQ6Ip5yHbIeBGjpPROZEZYRrIfEatTtJKrxWKM1qkAJ7RhDv3yws3VZISUnwOtn1x6nCsJCWkSGh4vkxbJ5AZCLiRozEnMnKL9ALW7Bys+tLqJK30jklapADIy/LaTZU+k5r7HSgnxienW/sNBBIBt0jqXNlpp99KiDN+bBdagPmxswHmREZuYDZgzW7Bqr+tTryhRQoA5B2h4fmomUauRcCtKjKzvfe5so2m6IpsLNJ3Zd4Juo1uSjhL7waFM25WAC4yO2ANZLDqS6sTb2iRAgAAchMC7sQ478G2J8c3pb43L0zz5ctNCWfpzSGe125WACZkJGDNDsEqrU4ABApTagHIjgi4nQ05lDpXtjcJcekHlLmNvzclPMlLNysAkwhYAcC8vDilFoCcgYDbWVgBgsD0+HJTwpO8eLMCgEdGA8WlNzgco5cDMJLXptSCNZgXHFYg4IY53JQAkAl8GSjOqHk8o5cDSE9emFILmY95wWEVAm4AQJbzd6A4Ri8HkJ68NqUWMgfzgsMqBNwAvEpvfmhnZuaKdkYz4bzNl4HissOAcACAvIF5wZGZCLgBeGR2fmhnZoIjmgnnbQwUh6xiNIp1eiNXM1o1kPcwLzgyEwE3AI8ye35oT2gmDMBqvoxibdR3l9GqAQAZQcANwCcZmR/aE5oJA8gq/o5izWjVAICMIOAG4BOa/QKwUlY29/ZlFGtGqwYAZAYCbgAAEFBZ3dybUawBAFklONAZAAAAeVtGm3sDAJBdUcMNAACyDZp7AwByEwJuAAByAVUVW5Jrba/z87SviaSOzZDdRt+muTcAIDch4AaQJXJLMADYZad9WlWl54qeXqfxM5oRIKpUlMy5dw7HGQAAFiHgBmA5ggHkNtltn7Yl2bzmxZMdZ3eILcnGDAQAAFiEgBuA5QgGkNtk5316Xbd1EhHivQ+0LclmeEMAAJC3qKokJaR4TZMYn2z42JuQsGAqTP4fATeALEUwgNwmu+3TESER3KQCAKRLVWXx29vl9N+xPr9n1tCNPqW7rVJh6TIkmqBbCLgBZDGrgoHs1J8WeQsBLgAgJ0pKSDEVbJtx6nCsJCWkSGh4PkvWn5MQcAPI8bJbf1oAAICcpM+k5pkSHCfGJ/tcC55XEHADyPGyc39aAACA7C40PB+10RYh4AaQq2S3/rRWoQk9AABA9kfADSBXyQv9aWlCDwAAkDMQcAOZgNpGZCWa0APwhaqK2lyvPylOz1Ns7temoAiuTQCQmQi4gQyithGBlFea0AMwR1XlWPceYtuxw2Oav5o1d1sWER0t5eZ+ybUJADIJATeQQdQ2IpDyQhN6AOapzeY12PbEtn27qM0mQQU4r+QEtGIAsj8CbiATUdsIAMhuqvyyUYIjvF+bUmw2wxrv3CynB6t5sRWDqkpSQorLssT4ZMPHdiFhwTnyuyL3IOAGMhG1jQCA7CY4IkKCqbF2kRuC1bzWikFVZfHb2+X037Ee0xjN/3xbpcLSZUh0tvjNkDcRcAMAACBPyW3Bal5oxZCUkOI12Pbk1OFYSUpIyZFzTBvV6ItQq5/TEHDDGqoiiXGuyxLijB/bhRYQ4eQAAACyUG4IVvNaK4Y+k5qnG0Anxicb1njnFL7U6ItQq58TEHAj86mKzGwvcnyz5zSTK7svi2ws0nclQTcAAMgyeS1YzQ1Cw/PlyBprM/yt0RfJ2bX6uREBNzJfYpz3YNuT45tS3xtWMPPzBAAAAORAvtToi2RNrb6nZu7OeTB6bCSvNH0n4Ia1hhwSCUvnrnFCnHGNNwAAAJDHZZcafV+budulF/znlabvBNywVlgBaqwBAACQ6+S1acoy0szdSF5p+k7ADQAAAAAm5PVpynxt5m4kpw9oZxYBNwAAAACYkBenKXOWXZq55wQE3AAAAADgp7wwTRn8R8ANAAAAAH6ithfeBAc6AwAAAAAA5EYE3AAAAAAAWICAGwAAAAAACxBwAwAAAABgAQZNAyAiqfNJ2pJsLsucn6d9TUQkIiQix88jCQAAAFiFgBuAqKr0XNFTdp7b6TFN6wWt3ZZFlYqSOffOIegGAAAADNCkHIDYkmxeg21PdpzdYVjzDQAAAIAabgBprOu2TiJCIrymsSXZDGu8AQAAAPwXATcAFxEhEVIgtECgswEAAADkeDQpBwAAAADAAgTcAAAAAABYgIAbAAAAAAALEHADAAAAAGABAm4AAAAAACzAKOUAAAAAgEynqpKUkOKyLDE+2fCxXUhYsAQFBVmet6xCwA0AAAAAyFSqKovf3i6n/471mGbW0I1uy26rVFi6DInONUE3TcoBAAAAAJkqKSHFa7DtyanDsW614jkZNdwAAAAAAMv0mdRcQsPzeU2TGJ9sWOOd0xFwAwAAAAAsExqeL92AO7eiSTkAAAAAABYg4AYAAAAAwAIE3AAAAAAAWICAGwAAAAAACxBwAwAAAABgAQJuAAAAAAAsQMANAAAAAIAFCLgBAAAAALAAATcAAAAAABYg4AYAAAAAwAIE3AAAAAAAWICAGwAAAAAACxBwAwAAAABggWwRcH/wwQdSvnx5yZ8/vzRq1Ei2bNkS6CwBAAAAAJAhAQ+4Y2JiZPDgwTJ69GjZvn271K1bV9q3by9nz54NdNYAAAAAAPBbSKAz8M4778gzzzwjffr0ERGRDz/8UL7//nuZOXOmDBs2zCVtfHy8xMfHO57HxsaKiMiVK1f+myjhuki8yv+/IBKW7D0D2S19dsxTNksflxgnybbk/09+RZJCk0ifgfTZMU+kz93ps2OeSO89fUpcnFxL/m/64KSclT475on0uTt9dsyT2fSJ8cliS7juSB8ano/02Th9dsyT5elv3JAbiYn/TZ+QkGXp7fGnqnpdh4hIkPqSyiIJCQlSoEABWbRokXTu3NmxvFevXnL58mVZunSpS/oxY8bI2LFjsziXAAAAAAC4On78uJQpU8ZrmoDWcJ8/f16Sk5PllltucVl+yy23yMGDB93SDx8+XAYPHux4npKSIhcvXpTixYtLUFCQ5fkFAAAAAORtqipXr16V0qVLp5s24E3KzQgPD5fw8HCXZUWKFAlMZgAAAAAAeVLhwoV9ShfQQdNKlCgh+fLlkzNnzrgsP3PmjNx6660ByhUAAAAAABkX0IA7LCxM6tWrJ6tXr3YsS0lJkdWrV0uTJk0CmDMAAAAAADIm4E3KBw8eLL169ZL69etLw4YNZerUqXL9+nXHqOUAAAAAAOREAQ+4H330UTl37pyMGjVKTp8+LXfeeaesXLnSbSA1AAAAAABykoBOCwYAAAAAQG4V0D7cAAAAAADkVgTcAAAAAABYgIAbAAAAAAALEHBnA7GxsR5f+/3337MwJ7kD2zNjLl++bOn6ExMTM7yOnP4b5/T8e2P1/pMd5cXvDDjLjPN6IOX0/ANG2K+9y8prd44PuAcOHOh4PGXKFJfXnnzyyQyvv0aNGvLMM8/IzJkz5eDBg+mm//LLLx2P169f7/Lau+++a/ietm3byoULF9yWL1++XB566CFT+T1x4oTbsitXrnhMf+TIEbdln3/+udc/M+Lj492WOW/H69evu7z2yy+/mFq/EbPb8/jx4x7X9f3332c4P2b98MMPHl8bNmxYpnxGnz59xGi8xGPHjknz5s0zvP4xY8YYLr98+bLcfffdhq85HzvpycxjJjOY3afN5j8r9onExERZtmyZvP322/L222/Lt99+6/FibfX+449Zs2YZLk9ISJDu3bu7Lf/222/l2LFjjuejR4+WOnXqyP333y+HDx92S5/R73z+/HlZvHixbNu2Ld20VrD6vJuVrl27JteuXcv09R4+fFh++uknx/M333xThg4dKkOHDpUDBw54fN/u3btl4cKFsnDhQtmzZ0+m58sq//zzj9e/tPw5r5th9hg2y2z+/SnPZZVLly7J1q1bZevWrV6DBrNlZLPnCbPbaOfOnR7z+uGHH7ot87RPeGK2/Gr22pqZ5WMRkf3797s8N7t9RKw/Lr0xKuNv2LDB619GTZo0yfF43rx5Lq+9+uqrbumzTXlFc7ioqCjDx0bP7TZt2qR16tTRggULauPGjXXfvn0e13/o0CH94osvtH///lqvXj295ZZbtGPHjvrGG2/omjVrMiU/c+bM0Vq1aunJkycdyz799FOtVKmS7t+/3/A9v/76qy5YsEBPnTqlqqq7du3S7t27a5kyZbzmqWXLlunmaciQIW5/gwYN0sjISA0JCXFL36xZM8fjxx57LN31+7ONVFX37dungwYN0o4dO2rHjh118ODBhtvH7Pa844479NChQ27LP/roI61cubLH/GSGn376Sdu3b++yrGrVqrpkyRKXZYmJidq9e3e9//77TX/GjRs33JY9/fTT2rVrV01MTHQs27lzp5YrV06/+uort/QTJ050PE77+tChQ93S238fZ8ePH9eaNWvqhAkTDPPp7bdPy59jxqwDBw44Hl+7ds3ltY0bN7o8N7tPm82/P/vE2bNndfv27Y7ns2fP1g8++EA/+OADPX78uEvaY8eOacWKFbV169Y6aNAgHThwoLZu3VqrVKnillbV/P6jqlq+fHmtUKGC48/5ecWKFQ3fM3PmTMPlRurXr6/Tpk1zWRYbG6utW7fW5557zi197dq19fr166qqumTJEr3jjjt027Zt+tlnn+ldd92V4e/csWNH3bt3r6qqnjhxQkuVKqX333+/1qhRQydPnuyWfv369V7/Msqf8+4XX3zheLxu3TqX16ZOnZrhPJn17rvvapkyZbRYsWJatGhRjYyMdPvNnc2ZM8frX1qdO3d2+Z5Vq1bVOXPm6IwZM/Thhx92S3/hwgVt1qyZVqpUSbt06aKdO3fWSpUqacuWLfXSpUtu6b/66iuX7VarVi0tUaKElixZUj///HO39GPHjvX49/rrr3v83gkJCbp06VKdNGmSTpo0SZctW6YJCQlu6YKCgrRatWraoEEDbdCggdavX9/x16BBA7f0/pzXzeTH7DGsau43Npt/f8sqqqoXL17ULVu26JYtWwz3BWfLli3To0ePOp6PGjVKa9eurffdd59b2cRms2n37t21cOHCGhUVpXfeeacWKVJEe/XqZXitN/sdrE5fsWJF/e2339yWDx8+XOvXr++2/Mknn9RmzZrpzp073V4zYrb8avbaanb9Rv7880994403tGbNmnrnnXe6vGZ2+6ia368//vhj/euvv1RVNTk5WZ988km96aabtGbNmrp161a39GbL+I888ojbX9euXTUyMlKDg4Pd0rdu3VrbtGlj+Ne2bVu39Gb3OX/KK2bKf77KkwF3vXr19Mcff9QbN25oTEyMW8DjzZUrV3Tq1KlasWJFwx3H+eBJeyClfe7s66+/1qpVq+qhQ4d09OjReuedd+q///5rmHbIkCF6xx136GOPPaZRUVE6dOhQLVGihE6ZMkXj4uIyLU+qqvHx8Tp9+nStWrWq9u3bV//4448Mr9+f/Kxfv15vueUWHTNmjC5dulS/+eYbHTNmjJYuXVp/+eUXt/RmtudPP/2klStX1j179jiWvfbaa1qvXj3HDY20evfurX369DH869u3r1v61atXa5UqVbRAgQL62GOP6fbt2zU6Olrr1q2rixYtcklrP1HaC7uxsbF611136dNPP61JSUmG+TF7QlRVHTRokHbo0EFv3LihP/74o5YpU8bwJlLadfhynCUkJGjXrl316aefVtXUG0Lly5d3KcB7+wxfmPmNf/jhB/30008dzzt06OAoZH7//ffp5ie97+zPPm0m//7sE0888YR+/fXXjudVqlTRsWPH6quvvqo9e/Z0Sdu9e3d9//333dYxffp07dGjh+H6zew/qqkXLee/ixcv6rvvvqsVKlTw+BlmCluXL1/W5s2b65tvvqmqqUFu7dq1Hc/Tqlu3ruNxz549ddKkSY7nmXHM1KhRw/H49ddf1969e6tq6naoVauWW3qzhRRV95sYaW9mOPNnHzV73Js5L9oDzZIlS2qJEiUcz2+++WbNly+f27rHjBmjDzzwgB45csSx7O+//9ZOnTrpqFGjDPMfFBSkdevW1UGDBukrr7ziUkh+5ZVX3NLXq1fP5XnTpk0dj5s3b+6W/rnnntNhw4ZpcnKyY1lKSooOHz5c+/Xr55a+YcOGevbsWcdz+3aPi4vTVq1auaV///333f7efPNNjYyM1JtvvtnwO5u5eTZhwgRt1qyZdunSRefNm+dWsEzLn/O6mfyYPYZVzQVAZvPvzzFjNiBWNXfzz37+vnr1qmPZ1atXtXfv3jps2DC3dZs9hq0uz+3atUsrVaqkq1evVlXVpKQkffLJJ7Vjx44e979ffvlFGzZsqAMGDNA9e/bovn37HH/e+FJ+9efaamb9dkeOHNHx48frnXfeqfXr19fixYvr33//7ZbOn+1jdr+uUaOGI/j8/PPPtV69enr+/HldvXq1yznPLiMxhKrq8uXLtUWLFtq2bVv96aef3F7fu3ev29+7776rkZGRhuddf/JjtrySkZttnuT4gLtatWq6f/9+3bt3r1avXl3379+v+/btczw3kvYH8bbxzpw5o0uXLtVhw4Zp27ZttUWLFtqvXz+dM2eOHjx40C19Rn6kH374QUuUKKF33323y8k0rerVqzsC6wsXLmiBAgX08OHDHtP7k6dr167pxIkTtVKlSjpw4EDDWi5/1+9Pftq1a6cbNmxwW75x40a9++67Dd/j6/ZUTT2hV6pUSTdu3Ki9e/fWe+65x+t7vvvuO7e/d955RyMjI90KuqqphftVq1bpjRs3dNGiRRoREeG1hujMmTMaHR2t48aN0zvvvNNrbYaq/yfE0aNHa506dbRixYouNxwyY/3Jycnap08fbd++vUZGRuqqVau8foeQkBBHAdz5z14QN+Lrb9y8eXOXi1vt2rX16NGjun//fsPazLTfK73v7O9xb2YfNbtPREdHe8xz2ovYHXfc4XE93l7zdf9xFhcXp1OnTtUqVapov379DAsdzswUtuLi4rR9+/b69NNPa8WKFQ1rMe3uvPNOPX/+vMbHx+ttt93mEtR7unao+v6d69Sp43jcokULXbhwoeO5c7DvSXqFFNX/3sS4evWq1qlTx+2mhjN/9lGzx73Z86Kz8+fP68iRI7VChQr6P//zP26vV6lSRePj492W37hxw2NLpE2bNunLL7+s9erV0//85z+6evVqTUlJ8ZiHKlWqeHzN6DOqVavmEmzbJSUlabVq1dyWpw3onWufPNVe2Z05c0aHDh2qFSpU0Ndff91jrak/N88OHz6s48eP12bNmukjjzyiv//+u8d8mD2vm82PmWM4LV8CIDP59+eYMRsQq5q7+VejRg212Wxu64iLi3O5yWdntoycFeW5P//8U6tUqaJz587Ve+65R/v27ZtucLt27VotVqyYtmrVSlu3bu2oFTVipvyqav7aanb9DRo00Dp16uj48eMdZfXy5ct7TO/P9jGzXzvvb926ddP33nvP8TwzW6UuWLBAo6OjtXPnzrpp0yav+bf75ptvtFGjRtqhQwfDMr89/3FxcXrt2jXH4+vXr+v169e9XlvNlFcyepPBSEjWNV63xq233irPP/+8iIjccsstjsf250auXLkiy5cvdzyPjY11ed6xY0eX9UdFRclLL70ko0ePlvz583vNz+7du6VUqVKiqnL58mUpVaqUiIioqseBkkqWLClBQUGiqnL16lXZtm2bVKxYUVRVgoKC5OzZsy7p8+fPLxERESIiUqxYMbnjjjukYsWKHvN08uRJGTp0qKiq47E9T//++69b+lGjRsncuXOlR48esnnzZilevLjX73zu3DmZPn26qKrjsX3958+fd0t/5MgR6datm6iq47E9/dGjRw0/459//pEWLVq4LW/WrJlLP0wR89szLi5O7rzzTpkzZ4506tRJ2rZtKwsWLJDg4GCJi4uTAgUKuH3ufffd53i8e/duGTdunBw4cEDGjRvnsa/ZXXfdJSIiDz/8sIwYMUJeeuklw3T2fXHw4MEyYMAAueuuu6RevXqO5c77p11QUJDhY6PnIiJdu3Z1bKPjx49LtWrV5PXXX3e8vmDBApf0qio2m01SUlIcj/X/+8SoQd+YV155RYKCgqRYsWLyzTffSMOGDeWHH35w9Jdy7oNjV6tWLdmxY4fhNknL7G9848YNqVChguN5mzZtpFy5ciIiHvuCmtmmZvdps/n3Z5+Ii4tzeb5u3TrH43Pnzrm8VrBgQaNN4PE1s/uPSOp59v3335dZs2bJww8/LBs2bJBbb73V4+faNW3aVCZOnCgPP/yw7N6927Htg4KCZM2aNY509vNO+/bt5Y033pBWrVrJtWvXHMudrw0iImPHjpWoqCgREbnnnnukbt26IiLy888/S/ny5TP8natXry4jR46U0qVLy8GDB+Xee+8VkdTrT0pKisfvu3DhQpkwYYKULVtW3n77bWnUqJHHtM6/Tb58+bz+jv6cd82eV/w5L/7777+OMQOeffZZ2bVrlxQqVMgwbVhYmNuy8PBww7yIiDRq1Mix/TZt2iQLFy6U/v37y/jx46Vz585u6StUqCA//fSTW7/HVatWGe4T+fPnl+Bg96Fw8uXLZ1hWuHz5sqSkpDjeY+9vmJSUJBcvXjT8DseOHZOJEyfKqlWrpH///rJ3717Da5Ldtm3bZO7cuW7L+/XrJ1OnTjV8T8WKFaVNmzZy7tw5+e677+Sff/6R6Ohot3T+nNfN5MfsMWx3/fp1+eCDD+Tjjz+WBx54QFatWiVlypTJcP79Kc99++238vvvv7v8/jfddJNMnz5d6tevL+PHj3d7T1BQkFy4cEEKFSokP/30kwwePNjx2o0bN1zShoSEGO5bEREREhLiXqQ3W0Y2e54wu43sfZbfffdd6dGjh7Rr105efvll+eOPP0QkddwkZ6dOnZKXX35Z/v33X1m3bp3Url3bbZ3OzJZfzV5bza5fRKRmzZqybt06OXjwoBw8eFDKli3r8ZxldvuImN+vw8PD5dChQ1K8eHFZtWqVvPnmm47XbDab2/rNlvFnzpwp77zzjkRHR8sXX3xhmGdnKSkpMm/ePHn77belatWqMmPGDMe12cjly5elZs2ajrJnjRo1HNdmI/6UV8xe+3wRpJ5ymIv16dPH42tBQUEyc+ZMx/Nt27bJpk2bZNOmTXLkyBEpWbKkNGrUSBo3biwNGzb0WsCxStGiRR0FAlWVVatWuRQQ0u48c+bM8bq+Xr16uTwPDg6Wm266ya0g4ykYGDt2rNf1jx492uV52oE10mrVqpXbsnr16nkcvdnba76oUKGC43vaDwf7wRkUFCR///234ft++eUXGTdunFy8eFGGDx8unTp18vgZlSpVkvfee8/x/MUXX5Rp06Y5njuf1M3sn3aRkZEyfPhwUVWZMGGCDB8+3PF9Jk6c6DYAjtnfoHz58hIcHOxyQnM+waUdfM/sPiciEhUV5XPAbValSpUMB8Ly9pr9OEt7jKmqrF692qWA7M8+bYY/+0SzZs3kvffecys4b9++XV544QX59ddfHcvs+09ambX/iIgULlxYihQpIs8884wUK1bM7XWjwrRzYeu9997zWtgyex5as2aNtGzZUq5evSpFixZ1LL9+/bqoqtx0000u6c1+5+vXr8u0adPk9OnT0rt3b0cB4rfffpNDhw65DVjkXEgZNmxYuoWUtKKjo2X79u0eX/fnNwsJCZFixYo5CtP27WQvTCckJLi9x9fz4qFDh2TixIny888/y0svvSR9+/aV8PBwj/m7//775YknnpDHHnvMZXlMTIzMmTPH5aZ5WkePHpWYmBj59ttvpVSpUvLaa68ZBpT79u2TTp06SatWreTOO+8UkdRBjNavXy9Lly6VmjVruqRPe163U1V56aWX5NChQy7LX375Zbl69aq8++67jpvmNptNBg8eLPnz55f//d//dUnfs2dP+eWXX+Sll16Snj17ut1wMAq8ve0HaV/btm2bLFiwQNauXSvR0dHSrVs3ad26teTLl8/w/f6c183kx+wxLOIaAL300kteAyB/8m9W3bp1ZdeuXaZeW7p0qQwYMEBEUgfUnD17toik3vwbP368y75dvXp1Wbx4sVtwoarStWtXt0G4zLL6WtamTRu3Zc7lLeebqCIid9xxh4waNUqeeOIJn9Zvtvxq9tpqdv12iYmJ8sMPP0hMTIysX79eLl++LF999ZXcfffdLuc9s9tHxPx+/euvv8pTTz0lFy9elH79+jkGXVu5cqXMnj1b5s+f75Le7HEZHBwst956q9x+++2G22jLli0u6StWrCjJyckycOBAqVq1qtv6jSoUzPBnnzZT/vNVrgi4z507J/PmzXPcAapWrZp0797dpztPZp0/f17mzp0r06ZNk3/++cfjKL67d+925Kd69epSq1Yt058VGxsrM2bMcBsp0eoTYmay2WyOgoUvNm3aJI0bN3Zb7nyTwZmZnd/T9vRHixYt5J9//pGXX35Z2rVr5/Z62sKyPwGTGf4UVDzx9Bt44lxj44sTJ04Y1j689957jkKHs59++kmmTJkiK1euTHfdnn7jp556SsqVKyejRo1yWT5u3Dg5dOiQ4UiogTjOMnMf3bhxozzxxBPy1FNPuQQPM2fOlC+++MJldM6s2H/GjBnj9c6w0WdUqVJFRo8ebVjYatSokWzevNmnPBmdh9ILUM0w+s7dunUzvHPuidlCioi41DQ432iz81QjaBUz58WQkBC5/fbb5aGHHpLQ0FC3tGlrZY4fPy5dunSRQoUKOYLl7du3y5UrV2TJkiVStmxZt3VMnjxZli1bJiVKlJCuXbvKgw8+mO5NcpvNJnPnznWMSl69enXp3r27YXDr7bwu4j7CcmJiorz66qvy+eefS7ly5Rw1Lk8++aRMmDDBLaAuX768S4sOEdebwkY3g83cPAsODpbatWtL27ZtJSQkxO34NKqx9sTTed3szTxPPJUl/A2AfM2/J57OP/4GxElJSW43/+Li4uTSpUty++23O5YZBWTO1q5d61P+V61aJZMnT/bpumo3cOBAj60kMqPMa+Shhx6SxYsXZ8q6sov4+HhZvny5xMTEyNq1a+XMmTOWfZbRfv3ll1/6fAPDH2lbnaZlb11o17t3b49lAzPl47/++kumTJnicTR3I57KK1aU/3J8wL1nzx5p166ddOzYUaKiokRVZefOnfLDDz/ITz/95HZH2m7Xrl0yZcoUx8mvRo0a8vLLLzuaFdrZbDbZunWr/Pbbb/Lbb7/Jli1bpGTJktKkSRNp0qSJ252jixcvyoMPPiinTp2SunXriqrKnj175Pbbb5elS5dKkSJF3PJy/PhxeeONN+TkyZPy4IMPSo8ePWT06NEyZ84c6d69u0tNqEhqk8Sbb77Z8HsdOXLEpems3aeffioffPCB/PnnnyKSelNiwIAB0rt3b7e0/fv3l6ZNm0qTJk28NlV3dvLkSfn333+lbt26EhYWJmfPnpV3331X5syZ4zZVWXJysixYsEBOnDgh7du3lzp16sh3330n48ePl+vXrxtOi2Bm5ze7PT3xdvC2bt3apSCUtubX6C6kGcnJyXLx4kUpWbKkiKROizJnzhyZOnWq7Nu3z9S6jAoq/vwGnpQtW9aw0PTbb7/JiRMnpEWLFnLrrbfK7t27ZeLEibJhwwbDqdjWrFkjzz33nON3Gzp0qDz99NOSnJwsI0eOlIcfftiR1p9jpk+fPrJ7926pU6eOiKSeO2rVqiWzZs2SwoUL+/x9RdxP0vPmzZOzZ886ugnUrl3bcRGdMmWKW22mP/uoP/vEv//+K9OnT3cJHp5//nkpXbq0qe9rlJfM2n+88Xaui4yMdNuPzJyHzAbcZr+z2fWbLaSImLtRYnYfTY9RwGHmvDh79myvN2A81TauXr3a5bpt76pjJDg4WKpUqeLYh5yDVk83MbJCXFyco1VNpUqVvDYR98TTjU4z+4S3mrGgoCDp2bOn23Kz53WzN/PMHMP+MJt/T4zOPyKux4ARXwLia9euyTfffCPz58+XHTt2yMmTJ33OV1pmrqvpMbrW+1PmNeLpBoDZ86g/5Vcz19a0XbXS8vVYvnjxohQpUkRu3Ljh03vSu0FiZr/252bzqlWrZPr06S4Vm/3795e2bdt6fM/ff//tcq729HvYz8e+2r17twwZMsSxT7/wwgvy4osvyqZNm+Tll1926ZIhkvHyir0Lnn3/8JupHt/ZUKdOndyG9FdN7XjfqVMnw/csWrRIq1SporNmzdJdu3bprl27dObMmXrHHXe4DGyjqlqqVCm977779I033tBVq1bplStXvObH7KilqqlD4r/22mu6cuVKffHFF7Vy5cratWtXlymDnJmd5uuTTz7R6OhoXbt2rcbGxurly5d17dq1Wr9+fcNpdz799FN96qmntGbNmnrbbbdp586dddKkSfrzzz8bjrL5v//7v1q8eHFt3Lix1qlTR6dPn65FihTRAQMGGH6HXr16aevWrXXYsGHasmVL7datm1auXNlttG4jcXFxumfPHt2zZ4/hiOyq5rfnrl279O6779YaNWrosGHD9MSJE/rQQw9p6dKldcqUKenmyRcvvfSS43HaKYGeeOIJl+fz5s3TQoUK6W233aZNmzbV7777Tm+//XZ94IEHdNu2bR4/48SJE7plyxbHwEJnzpzRESNG6O233+6WNiO/QVpGU9GZHUlf1dzAcmZ/Y7u//vpLly1bpsuWLXNMi+FJUlKSfvXVVzpp0iTdtWuXqqp+++232rRpU7eBOcyOPmw2//7uE2YsW7ZMmzdvrsWLF9fixYtrixYtdNmyZYZp/dl/unbt6nicdgoTo6k/0hMZGeny3Ox5qECBAo6R6p3/PE2JZPY7V6xYUb///nuPf75KTk7WefPm+ZzeE7P7aHqMjntvLl++bPozvPnzzz8dg+d5Gv356NGjXv/S8jTqu7ep63bu3KlPPvmk1qtXT+vVq6dPPvmkx1H1M2Pqt59//ln79+9vevubcebMGf3ggw/clvtzXjfD7DGsqvr888/rl19+6XXgWCvyn/b8k1HXr1/X+fPna+fOnbVs2bJauHBhXbt2bbqDZdkZTTGqan7AVm+MvrPZMq+ZGVtUzZ9HzZZfzV5b7eeI8uXLu/15GhhyzJgxjmmmbDabtmzZUosWLaolS5bUlStXZmj7qJrfr82Osr148WKtUKGCI2bauXOnzpo1SytVqmRYRrh06ZJ26dJFK1asqF26dHF5bDTYY7FixbRdu3Y6cuRIXbFiRbrT6DVs2FA//fRTPXjwoE6ePFmLFy+ugwYN8ngM+1NeSU5O1hEjRmjRokW1WLFiWqRIES1evLiOHj3a68Cb3uT4gNvbCLpVq1Y1XF6rVi39559/3JYfP37ccLoWT4wOXrOjlqq6jmarqlq6dGmvJ1mzo+fVr1/fcBTFf/75J92RUa9cuaI//fSTjh07VitWrKjh4eFuaapVq6bnzp1T1dSpD8LCwnTz5s0e11mjRg3H94uLi9Obb77Z8X5PEhISdNCgQVq8eHGNjo7WqKgoLVGihA4ePNht5Fqz29PswauaOorx008/rZ999pnLfH2eeBvlMe1vVqNGDcfoqlu2bNHQ0FBdvHix1/WbLaj48xt4YnQRNjuSvqr7yM3ejm2zv/GxY8e8/hkxc5I2O/qw2fz7s0+Ymdvygw8+0IYNGzpuysXGxuqaNWu0cePGhiMM+7P/OO/n6R0Dzvky+nv//fe1WLFiLmn9OQ+ZCcbMfudixYppnz59tHfv3m5/ffr0cUsfGxurb731lj7//PO6fPlyTU5O1mnTpmm5cuX0gQceMPyMl19+WT/++GO35Z988okOHTrUZVlGRsg24kvAcfXqVf3iiy/0vvvu09KlS7u8Zp/2zNNfWsOGDdOxY8c6npcrV07btGmjTZo00ZEjR/qcb5vNposWLTL8DLNT15m5eW//zmanflNNHW194MCBWr58eS1YsKDOmjVLz58/b5jW37m7L1y4oB9//LHeddddjtGX0/LnvK7q+808s8ewqrkAy2z+zZx/7Py5qdK1a1ctV66cYyT9pKQkj6NYmw3IzFxXVdVlFgjnv7179+ptt93mlt5smdfsDQCz51FnvpRf/bm2mlW9enVHkDZ9+nRt27atJiUl6cGDB93Oy/7cIDG7X5udEaZZs2aGo3rv3bvXcNqu7t2767hx41wC05SUFH3rrbf08ccfd0tvs9n0559/1rffflsffvhhjYyM1Bo1auhTTz1lWCmYdp/2NuK7qn/llQkTJmj79u1dpqE8cuSIdujQQd9++22v7/Ukx49S7q0/lqdmGsnJyRIZGem2vEyZMpKcnOyyrHnz5rJx40YREXn88cdl3rx5jteaNGni1izD7KilIqlNt5xHfS5ZsqQkJCQ4nqf9HmZHz4uLi/PYt8pT85jY2FjZtGmT/Pbbb7Jp0yaJjY2VVq1aGY6YGxERISVKlBCR1D5nVatWlYYNGxquVyR1hET7oCwRERFSqVIlx/s9GTx4sCQmJsrRo0cdgxldvXpVXn31VRk0aJB88MEHjrRmt2d8fLw89dRTIiJStWpVef/99+Wdd97xmp9vv/3WsW2mT58uJ06ckHr16kmTJk2kadOmXpvZpJX2NwsPD5c77rhDREQaNGggVapUkS5dunhdx0cffSQHDx6UEiVKyNGjR6Vq1ary888/e/wdzP4G9lEw01IPI5GaHUlfJPX3dB4cJjk52ePsAWZ/44cfftiliav9u5w8eVJOnz7tdtyLiGzdulV2794t+fLlE5vNJrfeeqscPnzYcDuZHX3YbP792Sfef/99t2WrV6+WyZMnuzVPnjZtmmzevNmlaX2bNm1kxYoV0rhxY+nfv79bfswew96ajHl6Le1o6s5efPFFl+dmz0NhYWGGzbQ9Mfudy5UrZ2pshieffFIKFy4szZo1k88++0zefPNNCQoKkq+//lrq1atn+J61a9fK5MmT3Zb37dtX6tSpIxMnTnQs82eEbHsf8bRUVa5fv274WlxcnHz77bcyf/582b59u8TGxsqSJUukZcuWLuleeOEFw/d78sMPP8imTZscz4sWLSpr1qwRVZUWLVq4jDqbVmJioqxYsULmz58vK1askE6dOhmOmm4vT9hsNvn444/lgw8+kHbt2snq1asNu2qNGTNGVq9e7VKeqFOnjtx9993SoUMHeeSRR1zSL1y40OX5ihUrZPz48VKlShXDfeXVV1+VxYsXS6VKleTRRx+VkSNHSr169Qy7gtkZjV1z+fJl+eijjyQ2NlZGjhzpWG7/bebPny+HDh2Szp07y8GDBz023fbnvD59+nSZM2eOTJw40dH3/vfff5cRI0bIP//843JuMXsMi6SOz2G/fl+9elU2b94sv/76q/Tq1UtOnjzpMsq32fybOf/YGQ2iFxQUJJs2bZKTJ08aXmvOnTsnBQsWlFtvvVVuueUWyZcvn8dz4uDBg2XGjBnSvHlz+e6776RZs2Yyfvx4j7OemLmuiojbud6Z0YBW/pR5fZ2xRcT8eVTEXPnV7LX1xo0bcunSJbnttttEJLXJvn0fa9q0qWETeufxBVauXCmPP/645MuXT6pWrWq4P5jZPiLm92szM8KIpI5dZdQnv2bNmoajlG/dutVtZoKgoCAZPny4VKlSxTD/zZs3d4wrc+rUKVmwYIFMmzZNPv/8c7exMuLj4+XAgQOO8lJERITL87RjKPlTXvnqq69k3bp1LmMqlC9fXr788ktp06aNDBkyxOv7jeT4gNt5mitn6mHKK5HUwuy+ffvc+nfv27fPraDrXKg4ePCg22eklXbKMee0V69eNcxP2iHuRf67wxgNjGJ2mi9vU5kZjQpbvXp1KViwoHTp0kVatGghgwYN8trHNW0ezpw54/KbpB145Y8//nBcRFXV8Vy99KtbuXKl/PXXXy7LChUqJO+//77jZGlndnuaPXhFUvvdVapUyTHwxNWrV2XmzJkybdo0GT16tNtJ1GazyYEDByQlJUVu3LjhWL+quk374TztgkjqPuX83GggJLMFFbO/gbcBUIz6GxtNJ2J/LmI8DUPLli1dCqQtWrRwPA8KCnIpGJj9jbdu3eryfP/+/TJhwgS5du2axz6GZk7SnTp1kueee85w9OEHH3zQLb3Z/PuzTzif35YuXSrjx4+XYsWKydy5cw2n2DM6xj31v/PnGI6NjZUVK1ZISkqKy1SMqipXrlwx/Bxvg7Wlnb7E7HnIPk2Xr8x+Z6PrgzeHDx+WvXv3iojI008/Lbfeeqv8888/XgedTHvusAsODnabeszsPipiPuDo1q2bbNmyRe69914ZMGCAtGrVSipXrmw40NMHH3xgalC55ORkl0HF7DcagoKCPF5bV6xYITExMbJmzRpp06aNdO/eXX799VfHKNBpmZ26zszNe2e+Tv22aNEiKVmypDz22GPSuXNnKVKkSLp9HZ0DprNnz8qUKVNk4cKF8swzz7gNSlmqVClp2LChTJo0SZo0aSIiIl9//bXHdftzXjdzM8/sMWzna4BlNv+ezj9JSUny448/Gr5m9qaKSOqNs9OnT8uiRYvkueeek4sXL8rly5dl7969htdeMwGZmeuqPS+eGN1cN1vmNXsDwOx51Gz51ey19eWXX5batWvLc889JyKp5+pWrVqJzWaTlStXGpaHbr75ZlmzZo3ceuutsn79esf6k5OT3a5jZrePiH/HpRlmKzY9TXtpL/OmtWXLFsfxe+zYMSldurQ0bNhQZs2aJfXr13dL7zzVnYjrdHdGYyj5U15JSUlxCbbtihUr5nVaT29yfMDtbRRN57v7zqZMmSIdO3aUvn37uox2OmvWLLcLsdna5LQnN2dGhVwR8TgHqojxjuv8ndN+f6PvvGvXLsfciM481U4+9dRTsnnzZvn+++9l9+7dsnv3bmncuLHUq1fPcB7UtHlwfm60jTI6bYWz4OBgt88wuz3NHrwiqQUZ+wliy5YtkpiYKLVq1ZLRo0cbFp7MzIX59NNPuxR0nZ97KmyZLaiY/Q08DWB09uxZWbRokdvyb775xuW5L7VZRiOFe2L2N7bbunWrvPXWW/LPP//Iq6++KrNnz/Y4wrqZk/SECRPk1VdflcjISMPRhzOaf3/2CTNzW95yyy2yfv16t5E3N2zYYHju8OcYbtmypePCb1QI9MTXQZTMnoeqVasmn3/+ucfPTTtglNnvvHTpUlPpnc+t+fLlk8jIyHRneChcuLBs377dbYqrHTt2uBUyze6jIuYDDjM1dWmnzEpPUlKSnD9/3nHTyx50nDt3zuNsIffdd580a9ZMfvzxR6lWrZqIeK6ZFEkdFMp56rq0oyOnLXybuXkvYn5+2sOHD8vWrVslJiZGxo0bJ3fccYdcu3ZNYmNjvQYRvs7d/fHHH8uCBQukV69e0rlzZ8d8tZ74c14X8f1mntljWMRcgOVv/kVSz6erV6+WmJgYWblypTRo0MDrdEW+3lSxu/XWW+WFF16QF154QU6ePCkLFiyQp59+Ws6fP+9yrJgNyMxcV42kN4Cb2TKv2RsAZs+jZsuvZq+tv/76q0vrscKFCzu2sfPMH84++ugjeemll+TMmTMyZcoUx6jza9ascfu+ZrePiPn9um/fvl5fT+vgwYOGFTj2clFa9957r/Tr10+mTJniOO/ExcXJK6+8Ivfcc49b+saNG0tUVJS89NJL8vDDD6c7k4TZm0L+lFfsLRvT3iBQVY/TJqYnx49S7q9///1XZsyY4TKCXr9+/dxG7zU7v3Fm2bhxo8yfP1+WLl3qNsKgt6kZMtuJEydk06ZNsnnzZvnuu++kcOHCLs36vLEHY75MTXPjxg35/vvvJSYmxvBuXI8ePaRWrVpu04tMnDhRdu3aJV999ZXX9Xvbnt54KtgEBwc7ThDdunXz2opAJPXEaqaZuRF7IdfohOvPaLNppfcb2F28eFG+/vpriYmJkaNHj8oDDzzgNn+sJ7///rvExMR4vFHm6+wBRrz9xmvWrJHx48dLfHy8DB8+XDp06JDu+vwZNTojow/7s4962yfMzG25Z88e6dy5s7Rs2dLlJuSGDRtkyZIljpHdvfF1/zHy66+/StOmTd2WT506Vd58802pUqWKxMXFyXPPPScjRoyQJ598UoYNG+bTaOuezkOvvPKK4/EXX3zhMkp3UFCQT1MiefvOFSpU8NgNw6gVg/Oc1yLimPfant5oeqONGzdK9+7d5amnnnL53WbOnClz5841LAD6u48aBRxLlixxS2evqYuJiZGLFy/KqVOnZMOGDW41dZ7msLZLu09/+umn8umnn8rkyZMd54Ndu3bJ0KFDpXfv3vLss8+6rePYsWOyYMECiYmJkeDgYOnatau89957Hq/bZqeuW79+vfTs2dPjzfvWrVu7pPdn6jdnv/76q+McUblyZVm9erVbGn/m7r506ZIsXrxYYmJiZOPGjdKvXz/p3Lmz1xthzryd11u1aiWvv/664c281157TTZs2JDu+r2VJSZPniybN2+WkydPSmRkpDRu3NhrgGUm/6oq69evl/nz58vKlSulfv36snHjRvn77789HjfON1WGDRuW7k2V9GzcuNHlOPZnilGz11Vv3UL8DTZ8sX//frftVbJkSa/nUW/TvmWk/Orp2lqrVi1HSyQRkQMHDkj16tUNX8tsRtvHG0/79dixY72e59JOn2q2LJSQkCCvvvqqfPHFFy43d5944gmZMGGCW8va8+fPy6ZNm2TTpk2ydetWiYuLkxo1ajiOZfv29cSfUf3TK6+UL19egoODDWvkPU3JmJ4cH3Cnd0fWW8HPZrO5FDyMahPMTmnhqc+bnbfgc/PmzTJ//nz55ptv5Ny5c/L+++/LAw884NYny+yQ/v5MY5CYmCjbt2+X3377TX799VfZvHmzRERESJMmTbzeMTUTjBn1q+vcubN07tzZLe3ly5elb9++snv3bsdFYufOnVKnTh2ZNWuW4d1yX7dnWr4cvNu2bXOcII4cOSIlS5aURo0aSePGjaVhw4Zud+j8nfPX10KuJ+nd9PD1NzDq6zd//nyfpmnZvXu3zJ8/XxYtWiSlS5eWLl26GDaB+/rrr2X48OEyYsQIl75+EyZMkHHjxrn1hxTx/TcODg6WMmXKSKNGjQzPF74GiN5O0ufOnZN58+a5TJvx+OOPe+0r5M8+6us+YXZuS5vNJl999ZVLoax79+5ea1nNHMPeeJparnr16vLzzz/7PDaBndmbQlFRUT73afP1O9u7I6mqNGvWTH799VeX19O7i++rU6dOyfTp09O9eSxifh/1J+BwdvLkScexkramrnjx4tKpUyePBRqjwGHZsmUyadIkxzR3NWrUkCFDhkinTp3Szcvhw4clJiZGYmJiJDQ0VDp16uTSn9lfvt68F/HvJp4RVZUNGzYYzgXrz9zdzs6dOyeLFi2ShQsXep3e0tfzur838/y5sWsmwPIl/7fddptUrFhRBgwYIA888IAULFhQKlSoIEeOHPGYh4zeVEnL07nRiFFAZva66twtpFu3bo5uIZ6+c0bKvCKp06/GxMTI/PnzJTQ01FTfYk/8Lb/6cm2Njo6Wr7/+2m1Mh7///lsefvhhj/n/9ttv5e2333Y5T7zyyivywAMPeP0uZrePL/u185hHEydOdIznYeetH78Z/t7cjY2NldmzZ8u0adPk6NGjht1z/LkplFnlFX/l+IDbn8nJExMTHXdfypYt67j70rNnTxk/frzPd0WNmA3QRdwHRunUqZPUq1fP4wmuevXqsnjxYo99W9KecO01Lb7eqWnSpIkcPnxY6tSp45hvvHHjxlKsWDHDzzMbjKXtV9e1a1d54YUXvDaztTt8+LDjhFW9enWpXLmyWxqz21Mk43d0z58/L3PnzpVp06bJP//849bE0UzAndFCri8FFbO/QXh4uFtfP28FjwMHDjgK2iVLlpSuXbvK22+/7bXAWbt2bVm+fLlbn8gTJ05Ihw4dZM+ePY5lZn9jf84Tdr6cpPfs2SPt2rWTjh07SlRUlKiq7Ny5U3744QdZtWqV2zFpNv8Z3Sd85eu8mRk5ho14mtM27XFTp04d2b17t+E6MnJTyJfjMyPf2Zf1p232FhQUJCVKlDA192dCQoLs3btXbr/9dreuKmb3URH/Ag5Pjh49KuXLl3c89/cmZFpmWlLZHTx4UGJiYtyux0bjwTjz1OrBl5v3/vA2EJyIe01UejzN3e0rf87rIr7fzPP3GPY1wDKb/7Fjx8qiRYukePHi0q1bN3n44YelSZMmXm9aZNZNFTtP50a79AIyM9dVkdT+9WfPnpWuXbtK165dpWbNmlKxYkWP39mfMu/Ro0dl/vz5EhMTIyEhIXLkyBHZunWr4cCEW7dulQsXLriNubFy5UopUaKEWx9fe/m1bt260rhx43TLr2avrUuXLpWhQ4fKa6+9JnfeeaeIpFb+vPXWWzJ+/HjD4M3bwIFPPPGEW4BrZvuI+H9civh2s9mfVgZmbu7++eefji6av/32m5w9e1YaNGjgiD/Sls/M3hTy59qdXjN0f1qu5PiAO63ExETZs2ePYYHDbsCAAZKYmCiTJ092G/E6KCjI5e6Pp9GZ7XxpdpieSpUqScmSJeW5555zDIzi7QRXqFAhadCggccA2ttdaV/s3r1batWq5fOF2WwwFhwcLM2aNZNPPvnE0a/O2/e1i4+Pl7lz57pdtNM25za7Pc0evCKpBYitW7c6ThBbtmyRkiVLOk4Qafs8FyxY0K2fn4jxXW9/CrlmCypmf4M5c+bIggUL5K+//nL09Xv00Uc9prevf+bMmY5RKdP7jWvUqOHxJJf2NbO/sT/MnKQ7d+4svXv3drvYLl26VGbNmuXWx8ps/v3ZJ8zUPKRtQaKqsmvXLqlbt67MnDnTrQWJv8ewJ55qcW655RbHsaSq8vnnn7scW87nX7PnIWe+BH8Z+c6+rN9oYLGLFy9KcnKyfPHFF4b97//zn//ISy+9JDVq1JBLly5J48aNJSwsTC5evCgTJ050DOooYn4fFTEfcKTXN9C51tpMq4K0fK39TK+5ctqR0711zRFxH8vC7M17swXXkJAQqVWrljz00ENSokQJt2u+rzVRnrqr2PNjH8/Ffpx7yo8/53U7X27m+XMMmwmw/M3/3r17JSYmRhYuXCjHjh2TSZMmSadOnaRs2bLpfm+RjHW3MTo3mgnIzFxX7XztFuKPhg0bSnx8vDz++OPSrVs3qVixotffuG3btjJnzhy3Gwb24yxtf16j8qu37e/PtXXHjh0yZcoUR0ub6tWry8svv+xxjJRq1aq5DRwoknrdbdy4scuAzGa3j0jGjsvMuvHpzOzN3ejoaGnatKnj+K1UqZLjNaNunWZvCvlz7Ta6Htv5G2fl+EHTzBQ47MyMeG32BPPJJ59ImzZtpHLlypKSkiJ9+vSRJUuWSNmyZWXOnDmG07s4D4zy5ptvStWqVb0OjFK5cmVTP/axY8ekSJEijnWtXr1ali5dKuXKlZMXXnjBrT9FnTp1DPv8DB482HFHz5nZgVeOHDkiCxYskCeeeMLRry4pKcnrd3BulmY/qW3YsEHGjRsn33zzjdSuXduR1uz2NDPQj1358uWlQYMG0rhxYxkwYIA0bNhQChUq5DW9p4FF0nruuedk0aJF8uGHH8rFixcdU1p5489os2Z+g169ekmvXr0cff3+53/+R06fPi0vv/yyYV+/tWvXyoIFC+See+6R+vXrS7du3dId2dHMAERmf+MGDRp43YZGzfzMDLh04MABwzvbnTp1cmuu5U/+/dknvI0wnVb//v2lfv368vXXX7s0Q50wYYI8//zzbmMk+HMMe/oNVNVjPzxvgyilZfY85BxsXL582TE4nKdgw+x3tt/wUFW3kXBF3JtaehoIZufOnTJgwAD5+eef3V77+eef5aOPPhKR1GC2Ro0asmTJEjlz5ozcc889Ltc/s/uoSGrt1OjRox0BR6tWreTUqVPy3nvvGQYcixcvlvLly0u3bt3kzjvv9DrCcNoA//z587JhwwYpW7as4ci0ZqewEnGdomn16tWOgdZEUgtNaQNuo8EhL168KEWKFDG8AW2frvLIkSPpTlcpYu6YFEmthVy0aJEsWbJEwsLCpGvXrtKlSxfD0XPTMuqukrY20jk/vtwA8ee8buZmntljWCR1QCqjAMt+Q8Y5wPIn/yKp5cBatWrJG2+8ITt27JCYmBhp06aNo1WDEV+nohMxd250Dsi+/vprR0DmqfbT7MB+Iu4DuMXExBgO4CZivsxbs2ZNWbdunRw8eFAOHjwoZcuW9fobX7161XAmgMjISMPpDO1dFHzd/v5cW6OiouTLL790Wfb777/L0KFDPV6jfB040Oz2ETG/Xzt3M01JSXEbHCztfhEXFyehoaESGhoqIqnXkhUrVki5cuXk4Ycfdlv/yJEj5aOPPjK8uTtixAi3c3/agD+9bp1mR/X3p7zibWA2vxnMzZ2jVK9e3fF48uTJ2rlzZ1VVPX36tNapU8fwPZUrV/a4vrSvffDBB3rmzBmf81OjRg1NTExUVdXPP/9c69Wrp+fPn9fVq1dr06ZNfVrHL7/8oi+++KKWLVtW27Zt6/b6nXfe6XN+VFUbNGigJ0+eVFXVbdu2abFixXTy5Mnau3dv7dWrl1v6RYsWaZUqVXTWrFm6a9cu3bVrl86cOVPvuOMOXbhwocfPuXjxon766ad69913a0REhA4ePFg3bNjgNW+HDh3ScePGaZ06dbRevXr6+uuvG6Zr2bKlrlmzxm352rVrtUWLFl4/I73tqap66tQpfe+997R58+Zao0YNLVq0qO7Zs8freu2uXr2qV69e9ZrG22+WkpJiuHzPnj362muvadWqVTV//vw6bdo0PXbsmGHa2bNna8eOHbVKlSr6yiuv6JYtW7RChQo+5d/X3yCts2fP6vTp07VNmzYe0yQnJ+uqVav0mWee0VKlSulDDz2kn3/+uWHadevWadmyZXXMmDG6bNkyXbZsmY4ZM0bLlSuna9eu9ZqX9H7jo0ePev0zcvToUZ00aZLWq1dPGzRooJMmTdLIyEjDtFFRUR7z5u01X/NvZ2afMKNKlSoeX/N2vlT1ff/x5zfw5saNG4bL/TkPmeXLdx4zZozXPzM87UPO55V77rlHv/jiC8fzunXr+rSO9F5La/v27frqq69qxYoV3V5LSEjQb7/9Vp988klt0KCBjhw5Unfv3m24no4dO+revXtVVfXEiRNaqlQpvf/++7VGjRo6efJkt/RhYWHavHlz/fXXXx3Lypcv73O+fblujhkzRg8cOKCqqjabTVu1aqVFixbVkiVL6sqVK93Sezo2kpOTtVKlSj7n7fLlyzp+/Hivaf79919955139JZbbtHZs2d7TDd06FCtXLmytm/fXmfOnKkXLlzwaTuZ2QfMnNe7d++u48aNc7nOpaSk6FtvvaWPP/644Xv8OYYTEhJ06dKl+vjjj2uRIkW0V69eumTJkgznX1V1165dumDBAl2wYIHH/dlu+fLl2qtXL42MjNSePXvqt99+q+XKlfP6HjPnxt69e2v58uW1V69e+v3332tiYqLXa31Grqtnz57Vs2fPOp4fOXLELY0/ZV77eeKJJ57QyMhILVSokH777beG5/RKlSppcnKy2/KkpCTDY8yf7a/q37V1165dOmLECK1SpYq2atVKp06dapiuZcuWum7dOrfl69evNyy/mtk+znzdr8uXL68VKlTQ8uXLu/0Z7UvNmjXTv/76S1VVDx48qEWKFNEXXnhB27Vrpy+//LJb+jvuuMNjHqtWrWq4/Pr16zp//nzt3Lmzli1bVgsXLqxr1qzRpKQkr99ZVfX48eM6ZcoUbdSoUbrnXV/LK5s3b9ZTp045ns+cOVMfeOAB7d+/v54/fz7dPBnJ8QG3mQKHXffu3fWtt95yWz5hwgS3C8CAAQO0TJkyetddd+nHH3+sFy5c8Jof58/s1q2bvvfee47nni5oZ86c0Zdeeknvu+8+HT58uMbGxqpq6kXJ6CD97bffvOYhrdq1azsev/TSSzps2DDH+mvVquWWvlatWvrPP/+4LT9+/LhheiO+BGNp7d+/32NBtFq1ah7fl/Y1s9szrRMnTug777yT7sE7bdo0LVOmjBYrVkyLFi2qkZGROm3aNMO09m3u7Oeff9b+/ftrmTJlDN9z7tw5x2NvhVxnZgoqS5Ys0bffftulIOntN7AXaCZNmqSTJk3SZcuWaUJCgse87NixQxcuXKj79+9XVdXExERdvny59u7d2+N7/v33X33ttdf0oYce0oceekhfe+01x80iZxn9je2Sk5N13rx56aZL7yRdqlQpfeWVV9z+hgwZorfcckum5d/MPjF27FiPf2nz72k/T0lJ8fia2f0nLZvNptevX9fr1697TNOsWTPH48cee8zlNaPz6dmzZ3Xr1q166dIlx/MZM2b4dB76888/dd++fbpv3z6PBZuMfmd//P3339qwYUPD1zp06KCffvqpfv/991qkSBFHQcBms7ncjFY1v486MxNw2MXHx+usWbO0ePHi+u6777q9XqNGDcfj119/3XFeuHbtmuF1JiM3FVV9CyirV6/uCAzt16+kpCQ9ePCg1qtXzy29mZv3qqr//POPPvPMM9qxY0f98MMP9erVqzp48GAtXry4DhgwwHA9KSkpunbtWn3uuec0OjpaBw4c6Cj8GqlYsaI2atRIZ82a5TgOfNlOvgbcZs/rZm/mmT2GzQZYZvJ/4cIFbdasmVaqVEm7dOminTt31kqVKmmrVq0c+UsrKChImzdv7rhxo+rb9neW3rnRbEB28uRJn66rqqnXxBEjRmjRokW1aNGiWqRIES1evLiOHj3asHLAnzKvsxs3bujixYv10Ucf1VKlSrm9PnjwYH3qqadctsX169f12Wef1YEDB7ql93f7+3pt3b9/v44ePVqrV6+uLVu21Pfee0/Lli3rdd27d+/WihUrau/evXXatGk6bdo07d27t1asWFF37drl9b3pbR87f8pbvnI+Hw8bNsxxrkpISNCaNWu6pTd7c7dr165arlw5/c9//qOrV6/WpKQkUzdTnRndFFI1f+2+88479eLFi6qqumbNGi1durQuWrRIR40apZ06dfIrbzm+D3fHjh3l4Ycflttuu0169Oghhw4dkuLFi8uNGzckOjrasH+K0YjXu3btktq1axuOeK3/PyLoggULZNmyZVKrVi159NFHpUuXLm7NRBo1aiRz586V4sWLS+XKlWXTpk2OPhXVq1d39Plwdu+990q9evWkZcuW8u2338q1a9fc5gN31qZNG6+jD6edKqRWrVqye/duCQ4Ollq1asm7777raFpXu3Ztt0EzzPb5MTvYT9qmlfb0jRs3Nmw6JJLaB2bLli1y8803uyyPjY2Vhg0buswFaHZ7/vXXXzJkyBA5fPiw1K5dW6ZMmeIYYTbtQD92Y8aMke3bt8u0adMcrx85ckQGDRokdevW9TiQiC+jUn/77bfSt29fCQkJkXz58smCBQsMp0xKj7fRZp9//nnZt2+fNG3aVFavXi0PPvigvPbaax7X9c8//0ibNm2kbNmyLn1yTp48KWvXrnXMK2n3+uuvy5dffin16tWTzZs3y4gRI+Tpp59ON887d+6UQ4cOSc2aNb1OBWH2N75y5Yp88MEHcuLECbn//vulffv28sEHH8iUKVOkTp06smzZsnTzZnfgwAFZuHChy4BFZvt+ms2/P/tE2uasIqnnvo8++khiY2Nd5qt84YUXJDk52XDeTFU1bA5tZv8REXn33XfFZrPJsGHDRCS1SWBoaKgkJSXJoEGDZNCgQW7vcW7mmrbJa9rnn376qYwYMUIqVaokR44ckY8//lgefPBBj/kZPny4REREOH7HcuXKScWKFSU+Pl7atWvnNmCV2e+8bds2+fvvv6Vbt24iktr96dKlSyIiMmjQIEfXDzuj5rMXL16UY8eOyaxZswyn+Dp9+rSMHj1aTp8+Lc8995xjurt169bJ1q1bXaY+M7uP2j//wQcflNOnT0udOnVEVWXPnj1SpkwZ+eabbwybRMbGxsrixYtl0aJFEhcXJ507d5bu3bu7XQ/q1q0ru3btEpHUvtQvvviiY8TkO++8U3bu3GmYT3+nsPKlr6LzPtWpUyd54IEHHOctoybXZqerbNOmjTRv3lyaN28uy5cvl+XLl0tUVJRMnTrVcFTzF154QTZt2iQtWrSQbt26ue0znti7qyxdulTuuOMO2bp1q/z1119u5RX7GDVqMD6CiHsXDn/O65UrVzacc11VpUqVKi6vmT2GRcz1zzSb/379+kmRIkVk3Lhxjibrqir/8z//I5cvXzYcJ8PsVHQi5s6NaUcij4+Pl+XLl0tMTIysXbtWzpw543V7pWfixImydu1a+fDDDx1lm6NHj8rzzz8vbdu2lSFDhrikN1vm3bRpk/znP/9xlLdmzpzpuNbHxcW5NWdOO8WUSGp55Mknn5QJEya4jZNgdvubvbb621/a14EDzW4fEfP79Y0bN+TSpUty2223iUjqtKk3btwQEZGmTZu6nded44SGDRvKqFGj5P777xcR1/O4nfPYK85UVb744gs5ffq0y3KzfbLTdsGwxxAtWrSQgQMHuo3r5E95xfl7/ec//5Hbb7/dUVbwdn3yyq8wPRs5deqUPvvss9qpUyddvny5Y/natWt10qRJXt976NAhRxMb+x3j+fPne32PvclG3bp1NTw83O31jRs3arVq1bRUqVI6evRox/IVK1boo48+arjOtE3f07sruHfvXre/d999VyMjI7V58+Zu6V9//XVt27atduvWTWvXru1onnP48GFt0qSJW/p69eo5mvql/Vyju/ytW7d2+6tTp47WrFlTd+zY4ZbeqHnliy++qNWrV9evvvrK8Du///772qhRI12/fr1euXJFr1y5ouvXr9cmTZro+++/75LW7PZs3ry5fvzxx3rw4EGdOHGiPvTQQ17Tq6betY+Pj3dbfuPGDcO79maa+dWuXdtxd3bTpk3asmXLdPNjVs2aNR1Nda5fv274uzrr3r2723ZWTa0F6tGjh9vyGjVqOO5Inz9/XuvXr59unsaOHatVqlTRxx57TCtUqKCffPKJx7Rmf+MHH3xQn3zySf3www/14Ycf1qZNm2qzZs1027Zt6ebLiKcaR1+ZzX9G94kzZ87o0KFDtUKFCvr666+71c7Ex8frwIEDtXjx4hodHa3R0dFaokQJHThwoGGtidn9R1U1OjrapeuFvXVSYmKi4XlL1XW7pN1GaZ/XqFHD0fzx8OHD2rhxY6/5iYqKcjmG7flJSUlxqVm3M/ud7777bpfaixo1aui6det0+fLl2rFjR7f069atc/lbv3697t271/A8k1Wee+45HTZsmEuTzpSUFB0+fLj269fPLf19992n9evX1zfffFP/+OMPRy2dUW3do48+qq+99ppOnz5dS5Ys6dg3YmNjXVpleZNe7Wf9+vW1QYMGWr9+fS1QoIA2aNDA8bxBgwZu6Vu2bKmrV6/Wffv2aeHChfXEiROqmtp81agp5KVLl7RLly5aqVIlR+1hpUqVtHPnzoY1oGmP+9KlS3ttMhkUFKTFixfXEiVKaIkSJbRkyZJasmRJx2NfeOuuMnv2bK9/aflzXu/fv78+99xzbjWUzz//vNs+ZPYYVjXX9cds/qtVq+axObO3Vnd2vjZfNXNurF27ttaqVUvfeOMN/fPPP11eM6oRb926tbZp08bjX1p16tRx1Ow5u3DhgmE3TbNl3nr16umPP/6oN27c0JiYGG3fvr1bGiPXr1/X3bt36+7du722inLmy/Y3e21dt26dPv/881qhQgV95JFHdMGCBT41WfeVP9vH7H79/PPP64wZMxzPK1SooL1799ZHH33UsKXN888/rz179tShQ4dq2bJlHWWC06dPa3R0tFt6s+cVVXPdOo26XWzfvl0HDx6sffv2dUvvT3mldu3aarPZNCUlRStUqODSlcm5dZYZOT7gzmyeTtSqqhs2bNABAwZo2bJltWPHjjpnzpxM+cy6detqXFyco1CS9rk333zzjTZq1Eg7dOjgtY/Tr7/+qosXL3Y5qf/xxx/6+++/u6XNSJ8fZzt27PBYkDZy6dIlr4HHN998o82bN9dixYpp8eLFtUWLFoZ9tMxuTzN9He28NZMzes1MM7/0Agsj9gJYiRIlNDQ0NN2CmdnP8NYnx+i1tOszOimnZeaiYfY3dm72lJSUpCVKlNC4uLh08+RJ2vPEI488ol27dvX4l9H8+7NPqKZemPr166dVqlTRqVOnpns+8bVQ409+0vahde5b5un9ZcqU0Q8++EDff/99x2P787S/gdl9Lm3hcdWqVR5fM1p/et857f77yCOPOB77Op7HuXPnPI7xYF+nr/ud2X1U1XzAUa5cOZe+gPY/o76B165d07feektffPFF3b59u2P5r7/+atjvcMuWLbpixQq35cuXL9etW7ca5t/suAEHDhzQe+65R+vWrauffvqpY/mPP/6ogwYNMvwMVeOb90Yycq3PqOTkZK99v+0uXLhg+Jur+ndeN3Mzz5/1O0svwDK7fm/9/s2OpbN//34dO3asT+tK79xobwpbs2ZNjYqK0gkTJujff/9tuG57pcyePXu0WrVqbpU1aXnrNuhrl0Jv0n5XM2MHZISn7e/vtdXMOADO58L0zov+bB9/9mvn64rzZxrdbE5OTtavvvpK33nnHZfuptu3bzcc28KIt/NKWr526zRidFz68xt//PHHWr16dW3cuLHeddddjuU7d+7U1q1bm8qTXY5vUp7Z0s55uHHjRkfTrOrVq0u3bt3koYce8mmUUF+VL19egoODXUYJtDfzMponOyUlRebNmydvv/22VK1aVYYNG+ZxOgJ/nTp1SqZPn+7S/KVfv36Gzd68MTvlgKeRUs+dO+fzfLRmt2faec0feeQR+frrrx3Pjebbu//+++WJJ56Qxx57zGV5TEyMzJkzR5YvX+72Hl+b+UVGRro0URw/frzL8/Tmm/VltFnnacpUVfbv3y81a9Y0nKZMxPvvaPRa0aJF5e6773asf9WqVY7nImI4NUra9dSrV09+//13w880+xunXXdGp8JIO1WL2Xm+zebfn32iZ8+e8ssvv8hLL70kPXv2dGt659w0rUaNGtKsWTNp0qSJNG3a1NE00xOz+4+IyB133CE7d+50axJ3/fp1iYqKkj///NPtPWbmeDUzhZhI6miw69evd5sX9Ny5c9KqVSu3rjJmv7OnprQiqdPCpR3heM2aNfLKK69I0aJFZcyYMfLMM8/I5cuXJSkpSWbPni333Xef23rM7Hf+zEXv7VxidlqvjM4BbXZ6IBGR5s2by8aNG/3+zPR07NjRcdw0atRIChYs6DW90XFvZ3Tce9OoUSPZvHmzqfymPW+NHTtWHn30UalWrZrcuHFD7r33Xtm9e7eEhITIF198Ie3bt3d5vz/ndbu4uDiXucqNmsaaPYa9Mer6Yzb/lSpVchnp3k5V5aWXXvJ4fHvi6Tfz59xot2/fPlmwYIHMmzdPihUrJps2bfKY1pfr3p133im//fab2z6qqtKsWTP/mtI6SbtNBwwY4PK8Y8eOGVq/N0bbP6PlLRGRpKQkWbVqlcyaNUtiYmLcXu/YsaOcO3dOOnfuLN26dXMrRzufN/zZPmb361q1asnevXsdzw8cOOBotp72NX+YPa94s3HjRsPuVEaSk5MlOjrarYm7P+UVEZGTJ0/K2bNnpW7duo5r16lTpyQxMdHnKQGdEXCnkfaC1KZNG3nsscfkoYce8jngs1rFihUlOTlZBg4cKFWrVnV7PaMnrG7dupmeK9LIkSNH5LHHHvO5UDBv3jz54osvDIPVyMhIyZ8/vyMgaNKkidSpUyfd6RJ84c98e8ePH5cuXbpIoUKFJDo6WkRSpza4cuWKY0oMb3799VfHvKiVK1d26XdvJsgw4stF9dixY15ft/eVskt7UbJTVZk4caJb/yh/CvcZKcylJyQkxDEvq/7/NFBFixb1OAWUiOd5rFVVRo0aJRcuXPDpszdt2iSNGzf2O+8i/u0T5cuXdxwfzlN92Z87F+4PHz4sv/32m2zatEk2bdokJ06ckHr16jmOt7Zt27qs2+z+IyLy1ltvyW+//SYzZsyQMmXKiEjqtEcvvPCC1K9f37BP1fLly+Wee+6RkJD0Z7A020f5008/lU8//VQmT57sMpbH0KFDpU+fPvLMM8+4pDf7nR955BF54IEH3D73iy++kCVLlsjixYtdlkdFRclnn30msbGx8uCDD8qaNWukQYMG8ueff0rXrl3dChEiIgsXLpSmTZu6jaFglqd9NDMDjrTX1rRzUjv3wxs3bpzLuBYiqf32tm7darhuo36EIuZvCqSd4qh3796yZMkSKVeunOEUR6tXr3YcN9u2bZPbbrvNcX1q2rSp4VzTmSVt5YA/76lRo4bs27dPgoKCZMaMGbJw4UL56aef5NChQ9KjRw/Ztm2by/v9Oa+buZnnzzgD3qQNsMzmv0+fPl7Tz5o1y1R+jObUFvHv3CiS2hfX3n/7l19+kXvuucdlrvu0fCkbmL0ZbJa3bRoUFOQ1/xlltP39ubaePHlS/v33X6lbt66EhYXJ2bNn5d1335U5c/6PvTOPqzH9///rZBvbjH2MCEVppdAq2Q0G2cq+7yRFsoxhxpIQCjV8bEl0KirDGCNbliJLIjshGWTaLEnL/fuj37m/5z73fU7nOkuLuZ6Ph4fOue9zn+ucc9/Xfb231ztYbpvCrKwsREVFITIyEvn5+RgyZAhGjhzJc/iq8v2QntdWVlY4fPgwr5Xc06dPMWzYMKI5UwjSeUURQr+ZkI2QlZWFsLAwdOjQAatWreJsU2W9okhzQTIuUv6TBrfsjV6CZCFeUFBQDqNSnokTJyoUTVN3wiKN/pGK/Uj3v5VQvXp12NnZYcuWLewNR5aXL1+yBkFCQgIePXoEc3NzODg4lDppaprc3Fx8++23OH36NCcLQLrPqzRz5sxhF2LSizDm/wvyCS1UVEXd6K0Q6joBlEGVxZw2IfnMRUVFCA8Px8uXL9G3b19YWFjg2LFj8PHxwcePH9WOCpQ179+/x549exAQEIBnz56hqKhII8cNCAjA+vXrWYGWmjVrwsvLC25uboJz2qBBg3Dt2jX0798frq6u6Nmzp1pRUlmOHj2K9evXs8I+JiYmWLhwIQYPHqz2sdPT0+Hs7Ixvv/0WHTp0AFAiCpiTk4OYmBiekSxtHJqamiIlJUVwmzTjxo1DfHw8CgoKYGdnxxo1lpaWPCeFKueoJg0OZQzErKwsHDhwAOfOncPhw4c529q0aYOHDx/yfv+ioiIYGRkJGv/yHIUSZKNXpqamuHXrFhuJ8ff3x8mTJ3Hr1i0sX74cly5dUjj+x48f49ixY9i6davgdXPgwAG2N/r58+c5c5q/vz/c3d0VHl8aecYbyWtIReJUgdSZp0lU+Y60iaLxSM+NDMOgVq1aWLhwIebNm8eZG/Pz83H8+HGEh4fjwoUL6NmzJ1xcXNC3b1+2T7I0EuOEYRjMmzeP50BTN0Bz5swZrf6GpFkkitDE+bBlyxasXr0abdu2xadPnzBz5kwsXboU48aNw+LFi0vNAv3y5QsOHjyIBQsWYMWKFZg3b55a41GFmJgYLFq0CD///DPn3rR27Vr4+Pjw+meTosl5Rei+IXtfEolEaNiwIbp27YqBAweqNXYJEmE2WcdTeno6Xr9+rdKaqNIb3LJKsrJIpxOVBXFxcQq3d+3atYxG8n+QptXJi2pIkJ2gZQ0lycnftm1bXhqrJvjy5QuuXbuGuLg4/O9//8Pnz5+Rnp6u8fdRBKlRu3v3bnbRkZmZCRsbG9YA79y5M2rUqKHWeEjVZisiEieGEKmpqTxvrLqkpaWxaqbyUoqUZeLEiXj+/DlsbW1x+fJlNG3aFDdu3MC6deswbNgwDY2YDBIP7du3b5GQkID4+HhcvXoVBQUFMDMzg62tLWxsbAQzadTh/fv3AIC6deuWum9OTg6io6MRHh6OW7duYeDAgXB1dYWTk5NGMly0TWxsLGvQGxsbo2fPnoLjlqRyFhcXw8HBgZPWaW9vr9Bp8+7dO9aguXLlCm7fvg0jIyPO3Fze5yjJYldofl2wYAFycnIQEBDAUdL38PBArVq1sHnzZt5xfvjhB8yaNUswhRvgOwql1WddXV3h6OiIuXPnyh0T8/9V2+Pj4xEfH48HDx6gQYMGsLGxgY2NDS91UvoYypS5qJJlI+QAl7zmxIkT+PDhA/uck5MTVqxYgaZNm8Le3h4pKSnQ1dVFUVERTE1Ncf/+fcH3VwdtOfOEUNfA2r9/v9xtIpEI48aN4z2vbmZUaXNj06ZN0b17d7i4uKB///6lrh1II6akkT1tOPilIc0i0VRmmjyMjY1x4cIFNGrUCM+ePYORkREuXLgAa2trua8pLCzE33//jfDwcNy7dw99+vTB8OHD2cyq8uDmzZvw8/Pj3JsWLFggWJ5KmvWqyXmlojjN7t69i3Xr1uHatWvw9PRUquuOLKXn6VVwpNPOfH194e3tXY6jAcdQPX36NHr16sVJ49SEwT1//nxs2bIFAODn54cFCxaw28aNG4eQkBDO/h8/fiQ6fnZ2NiIjI+XWmcka3BIv/cOHD9kLSV9fX6Gx/enTJxw4cIDdv1OnThg+fLjc14SHhyMhIQFJSUkQiUSwtLSEtbU1zp49q1Jqh7qQ+qmmTJmCKVOmACi5oV65cgWXL1/GhAkTkJ6ezkb8VMXMzAxAye+zfPlyAMC3335LPE55KHJsSb+nOnTr1o29cTs5OXGMhWHDhmnkpv7PP/8gIiICYWFhuHnzJry9vbFz507BfRcuXAgjIyNeavGuXbvw6NEj+Pr6ss8lJiYiOTkZVapUQV5eHpo2bYonT57w0sXKEiEjSp6HtmnTprC0tIS7uztWrFjBa6uhaZQxtCV89913mDBhAiZMmIDs7GxERUXB3d0dGRkZePXqlcpjkDip5KGuk+rTp08ASoxl6TYzeXl5AMCr18zOzmbryoCSaLt0KqciatWqhdq1a6NWrVqoWbMm9PT0eJEWVc/RoqIiZGZmsiVVX758QXBwMLZs2cKJwgPyv1OGYTht6BSRl5eH4uJi3vM+Pj7w9vaGnp4eWrZsCYZhkJaWxrYHEuKHH34gcrrXqFGDbS0aGxuL1atXc8Yly7fffgtDQ0PMnj0by5cvh4GBgcLjS8/HQjWysmRkZMg9lrzImMRBoMy2HTt2wN3dHW/evIGfnx+bdXHmzBmN1dLKc+atWLECNjY2ah9fkYFFuvaRRbZlKlByPURGRuKff/4RNLhV+c1krxvp8grZUo8bN27IjaIKOaZJ095J7htlQc+ePTmZg5IskhUrVgg6bFT5/kmoWbMmO2e2atUKRkZGCo1toCSrU09PDy4uLqxDLD09nQ0UabNuXR6WlpY4cOCAUvuSahWQziuybb4kMAwjWO4HAEeOHMGGDRvYlsCdOnXC8uXL4ejoiJycHJ42kqokJiZi7dq1ePHiBby9vbFv3z6Vs+wqfYRbGk2lQElz//59tubo48ePnHSWS5cuwcHBoUzHAyj2kgu9J2laHanHMjMzExMmTMDdu3dZj11ycjK6d++OHTt24K+//uJcZElJSRg8eDB69OjBetNu3LiBlJQU/PXXX9i4cSN8fHw471GvXj0YGBhgxowZcHR0VNijWTrF6dGjR2yvRKCk5nHEiBFKfzZ5yOszKEFosZ6Tk8MuPBISEpCTkwNjY2PY2NhgxowZao8pICAAGzZsYBcZderUYVPSZFmxYgWWLl2qdGSdpKezqpD0XCb9jYOCgiAWi9lej8OHD8egQYOQmpoqdzzyRNuKi4thYWHBERZRVZQtOTmZvWG0a9cO5ubmpb5GVRR5aK9du8ZGSFNTU9G4cWPY2NjA1tYW1tbWaqXxaYq0tDRERERALBbj48ePcHFxUSuDSdP1orK0bt1a7iJCE7WQQMncfffuXdSsWROdOnWCjY0NrK2t0aRJE96+qpyjYWFhmD59OurUqYPWrVtj6dKlmDFjBqysrLBixQpeTTPJdypkKGVmZiImJgaTJ0/GrFmzBI+hjPiWBHn34OvXr0MsFvPm6UuXLmHq1KnIzMzErFmzsHLlSgDAX3/9hX379iEsLIyzf2RkJBISEnDjxg0UFxejffv2sLW1ha2trWBGDmmEWxFisRiurq6858s6U6g0dHR0WGeei4uLxp15ZVHuBJQ4mnbv3g1/f384ODjA29sbhoaGvP3S0tJ4wn4Sjh8/Lih+KHTdZGZmIjIyEsOHD+f04ZY+T2Qd00Ln0B9//AELCwu2TnXFihWszoy/v3+pTqLSInvSglTSyBOkIk1BJ80iIeXhw4eCv6M8VBH203YZqCLy8/N56zx5WTASlBUPlEDiMBCat0hrrP39/XHw4EH4+vqyGkrXr1/H8uXLMX36dGzcuBHJyclKjUeefsmZM2fg4+OD/Px8LFmyBP369VPqeIr4qgxubaS2qHODVHY80jXl0tHw/Px8fPz4EYWFhWqNiTStjtRRMGrUKJibm2PJkiWcz+Hr64uzZ8/ixYsXbNoKADg6OuK3337jiZWdO3cOI0eOhLW1NY4ePcrZxjAMUlJSWKPg/v37+Pbbb9G5c2fY2tpyLgbS7+f58+eoV68e6xE7ffo0YmJioKenBzc3N0GjtGXLlgqjvrKLdWNjY9SuXRtDhgyBra0tOnXqJNcDpyiNDShRn5bl119/xY0bN+Dv749WrVoBKFlceXh4oH379rxFyfLly3HkyBH4+vrip59+Uvh+srx9+xZ+fn6IiIjApEmT4Obmhnr16nH2+fvvv5GWlsZG9fv37493794BAFauXCk4QZP8bqS/cd26dVkxDUkqsr6+vkKjR7aOVhoTExOOijWpCmZmZiYGDRqE169fw8LCgl1U6OrqIiYmhvd9qnJOSJD10A4fPrxUD+27d+8QGhqKgIAAvHjxgqdr0b17d4ULCGkRQAmq1PpJjOzw8HBkZ2fDxcUFLi4ubEaHNJrMwhBapKjymUlQRaRl4MCByMjIgKGhIezs7GBra8tRVJVGFaVWU1NTREVFsV0VHBwcIBaLMWTIEOLPJ5uNJTsnSaJ6EpVcWUewkFCONEJzSkFBAVvXmpycjLCwMERGRqJZs2YYMmQIUc10aRQWFiIpKQnnz59HUFAQ3r9/jzdv3nD2kYg3Sgs3Av+XAfDlyxel309eqiWJQSadKrpgwQL4+fmx23r27Cl4Tu/atQvbt29nlbPbtWsHNzc3TJw4UXCcJM68ssikIh3/x48fsX37duzcuRMDBw7EggUL5OrMAICRkRH+/PNPniG7c+dObNiwAY8ePVJ6rJ8/f4atrS2nnITEMQ0AFhYWSEhIQK1atRAdHQ1vb28cPHgQt27dwsGDBxEbGyv43sreN0xNTRVem7LGEuk6vW7dumwWSbdu3Up1EJBiamqKQYMG4ZdffkHNmjVL3V/bjlpVylKly0ZHjRqFQ4cOsduEvm9SvZyGDRti8ODBcrNeSRwGmkgRNzIywtWrV3lr6OzsbOjq6iIwMJDzO6iiX6Kjo4PmzZvDxsZG8L6viohvpU8pl6TtASWRp7y8PM5Jocj7rQykKWCqIJsC8++//8Lf3x8HDhyAm5sbb/+8vDzcu3cPxcXF+Pz5M+7duwempKe6YGoyaVpddHQ00fivXbvGucCBkotw8eLF8Pf357WpePfunaAyeLdu3VC7dm1ERETwtolEIpiZmcHMzAxTp07F3bt3cfLkSWzbtg2rV6/mpBWR/mYjRoxAdHQ0vvvuO1y/fh0uLi5YunQp7ty5gxkzZmDfvn281zRs2JBoYp0yZQquXLmC48ePIzk5GcnJybC1tUXHjh15afTSaWwhISGctDV5C/7Q0FDcuXOHc6zWrVtDLBbDzMyMt7hdtWoVJk+eDE9PT+zYsQMzZszg3EyFFq/Pnz+Hr68vYmNjMWfOHNy5c0fu9bVq1SqOkfjy5Uv88ccf+PTpE9zc3ASPn56ejkWLFoFhGPZvoOQ3k00dJv2N3759i2PHjmHbtm2YPHky+vXrV2oa/3fffYcbN26wHlQJN2/e5E30si2kSmPZsmWsGrPke2cYBsuWLcPSpUt50b/SUhuFDG4SD21eXh4SExPZKMLVq1fRuHFj9O7dG3Z2drz9t23bxnvu9OnT2Lhxo6DiJ1CSok/qEO3WrRtcXFwQFBRUautDWVVrgJuFIbtYV7RIsbOz442V9DOTCmQNGzaMTSG/d+8eTExMOA5YIYP4jz/+AFCS8peQkIDdu3fj9u3bqFatGjp16sRJtSY9R4GSFGtJ9Kdz585o27atSsY2UPKZpQ1uaUevJJoXHh6OTZs2CQrfCN0XJAiVOgEl34tYLEZ4eDgaN26MESNGID8/H+fOnZN7rFu3bsHPz48jhrlgwQK59ZYvXrxgr5vLly/j2bNnsLKyErxuZJ3n6iBv/SH9fG5ursLXSBt/sm3VMjMzecfetWsXgoKCsHnzZlhZWYFhGNy8eRNeXl5gGEawXrhTp07o1KkTm84uceZNnTqV58wjvYYlxMbGIjAwkJMtNGfOHJ6Dj3T8v/zyC0JDQzFmzBhcuXJFcHyybN++HT/++COioqJYx+Dy5ctx4sQJXLhwodTXS/PNN9/w7vmyqefytknQ0dFh79NRUVGYOnUqOnbsiI4dOwrOaaSRverVq8ud8zXB3r17kZCQgNDQUISEhJSaRULKzZs3sXHjRnTq1AmrVq3C0KFDFe7v6uqK9+/f87oWZWRkKCyVUrY0RyiSLBKJkJCQgPT0dMGUfunSCdn6aKF5wtLSUmEWjCwtW7bUWBReE3aTSCQSDFjVq1cPzZs3563Np0yZwuqXuLm5KaVfItRmUm2YSo6kcXyrVq3Yf/IayquCdIN0ZZqnd+rUiencuTPTqVMnplatWkznzp3Zx507d1b4Xunp6cz8+fMZAwMDxtfXl8nNzRXcz8nJienWrZvcf7IINYLXJPIa0xcXFwtuMzIyYnJycnjPZ2dnM0ZGRoLHOnnyJPPrr78yP/74I9OkSRPG2tqacXd3Zw4dOsQ8e/aMsy/pb2Zubs7+7e7uzixevJgdv5mZmeB4evXqJfi8MqSlpTERERHMwoULmXbt2jE2NjZy91X2t2vbtq1K2/bv3880b96cGT9+PDNx4kRm4sSJzKRJk3j7jRs3jtHX12f8/f2ZrKws5uPHj5x/snTq1InzeN68eezf8j7vvn37FP6ThvQ3lub9+/dMaGgoM2jQIKZ58+bM5MmTBfe7ePEi06JFC2blypXM0aNHmaNHjzIrV65k9PT0mAsXLih8j9Jo164dU1RUxHu+sLCQadeuncLX5ufnM4GBgYyRkREzefJk5sGDB4L7iUQipkWLFszw4cOZESNG8P5J06RJE2bAgAHMqlWrmNjYWLlzjxDR0dGMjY0N069fPyYuLk7ufqX9LkLcvXuX/fvDhw+cbRcvXpT7ujdv3jCLFi1iWrduzfz2229MVlYWbx/pa0v2OivtulPmM6tzjpLO2UVFRczNmzeZ7du3M+PGjWNatGihkftf8+bNme3bt7P/ZB+THkua7OxsZu/evUzfvn0ZAwMDZsGCBYyurq7aY5ZGJBIxXbp0YR4+fMg+p+h7iYyMZNq2bcvs3buXuXXrFnPr1i1mz549jKGhIRMREcHbv1mzZoypqSkzZcoUZteuXUxKSorC8Zw+fZr9W3pMDMMw4eHhyn4shmEYpkWLFoLPk5x3qqxv0tLSeM+/ePGCN+dL+PTpE3P+/Hlm3bp1zODBg5kffviBsbCwYGbMmMGb16VR5hpmGIY5cuQI07p1a/Y3S0pKYvbu3csYGBgwR48eVWv8IpGIqVu3LtOoUSOmcePG7D/JY3lcunSJMTAwYC5evMhMnDiR6dOnD/P+/Xu5+8veTz9+/Mi8fPmSWbt2LePq6srZt0mTJoyXlxezcOFC9m/J4++//5537A4dOjDv3r1j8vPzmR9++IFJSkpitxkbGwt+ZmXvGwzDsOslZZFeF0v/U2aNXFBQwCQmJjIbN25kDAwMmCZNmhC9tyJu377NfPvtt0zDhg0V/sZTp05loqOjec/HxMQwM2bMEDz2oUOHmLp16zI//PADY29vzxw7dozR1dVlBg4cyFy7dk3huP7880/G0dGR6dGjB3Pq1CnBfUivY+nnunbtWur+mrQh5M1bJHTt2pU5d+4c7/nz588zjo6OvOdNTEyYwsJChmFK5qNvv/2WycjIUPn94+PjVXpdpY9w//nnnwrredUlNTUVLi4uYBiG/Rso8dI8e/aMt39kZCTxezx+/Bi+vr64cOEC3N3dkZKSorC2VpF3Xoi4uDhOat29e/dw4sQJ6OnpYfjw4cTjleXHH3/ErFmz4Ofnx1GP9fLyEqyvcXNzQ58+fbB+/Xo2anXz5k0sXrxYMKIPAL///jvs7OywbNkydOrUSWEd2IMHD2BtbQ2GYdi/gZLfTJJGJk1xcTGKi4uho6OD2NhY+Pv7A5AfTQZKolfz58/H48eP2XR6eR5DCQUFBbhx4wYbCbly5Qpq1qyp8PxVVoXZ0NAQYWFhGDlyJOd5sViMNm3a8Pa/desW5syZA319fVy7dg3ff/+9wuPHxcVBJBJh8+bN2LJlC69Vgmxqtmx0RPKdAvJFTUgyBkh/Y2nq1KmD0aNHY/To0cjOzkZMTIzgfqmpqbhy5QoCAwPZLAdjY2PEx8eX2vqjNL755hvB9LwqVarIPbdlUxtjY2MVpjaeOXNG6fNHNvW1NIqLi3Ho0CFs2LABRkZGSkWgpX8naRgFKc1jxoxhI82Ojo6cqLObm5tgeYiyWRikkSLSz8wQZmGU9v5CLFmyBAkJCUhJSUG7du1gZ2eHIUOGYP369WjatKlSx1DE1KlTOder7GNZpDPOpBH6vE2aNIG1tTXWr1/PRoNlW4FJo0pZxdmzZxEeHo6+ffuiY8eOcHFxERRkk7By5UqcPn2aU4NrYWGB3r17o1+/frz7ZUpKCq/8QxHSWR6urq6c89fHx4enPVFaC1MhSDKFcnJycOLECRQXFyMnJ4fTQko2Og6U/L5Cc06LFi3k/vatWrViS7/c3NxgbW2tMBJIcg0DJaUKR48e5ZSZtG/fHp07d8bMmTM52RKk41d0rsjj06dP6NChA4KDg1mtmvDwcOjo6ODTp0+Cn8XU1JTTgkjS6cXJyQk7duzg7CtdIyxbLywt5Clh5cqV7DzVp08fNlPjwoULbPmZNKSRPXt7ezx//lzpGvFWrVopzFYRgiSLBChZ32zcuJHT7tHT05NtgSXLzp074efnh3Xr1mHmzJkK59+bN2/if//7H+/5QYMGYdmyZYKvWbVqFa5du0ZUmhMREYF169ZBT08PGzZsUCgwmJGRgcDAQDAMw/4NlFzHklI+aRiCLBiAn/X67t07xMXFQU9PD506deLtTzpvkaqgb9u2Dc7OzujatSubgXjjxg3ExcUhKiqKt3+NGjVQpUoVACWidwYGBkqJhWq61WulN7ilF2TaQPpEk1X4FFIDHTNmDFELLqAk/UlXVxdDhw5FamoqL21KdlI9cOAARCIRxowZw3k+NDQUIpEIo0eP5jzfr18/7Nu3D23atMGDBw9gb2+PsWPH4sSJE7hy5Qo2bNjA2Z/05N+0aZOgeuzYsWMF1WPnzJmD5s2bY9myZWzanqmpKRYtWiS3/9+RI0eUHg9p6qSrqyt69+6NRo0aQUdHh013f/r0qdyFwYQJE9CxY0e4ubnhjz/+wLx58wRTzyXY2dnhyZMnbDrUxIkT8fvvv6NBgwZEY5VHUFAQhgwZgh07dnAmoNzcXMEJaOLEiQgICICjo6NSxxdyLimiW7du+O2333ilDGvWrJGr1E9S9036G8tT9q9Xrx5iY2MFjf1NmzZh7NixWLVqFdF7KUNubq5g3RvDMGxbGGlUSW3s1q2b0uOZPHmy3G0ikQi7d+/mPNemTRsUFRVh/vz5MDIywj///IN//vmH3S6U3qvKQovEaB0/fjwuXboEd3d3rF27li2vkCykZRe6pIsU0s9MatCrwg8//MA6LmX7bmsCUsEpWcNBGtkewTt37kR4eDgmTJgAZ2fnUoV8VCm1cXJygpOTE4qLi3H27FmIxWLk5eVh2LBhcHZ25qlMFxUVCQpeNW/eXDCVc/r06UQ10KROGEXODXmQGGRdu3Zlx9+1a1fO9Sl0b1Dk6JYXJFDkzJPVSiC9hoGSxb+QpoOpqSnvOiYd/5w5c9gWVLLtp+QhuQaAkvrjxMREWFpaKhRLVCTeKYsix7T0+Sdh8ODBGDBgAN6/f89qBgAltb1C67y3b9/C3t6eVZYujWXLlrFlg9HR0QgLC2NrxGfMmMGrESdNQdfV1UX9+vVha2sLOzs7TJ8+HSYmJnL3P3z4MJYsWYKlS5fCy8sLQImglqurK9asWcNzmllbW8PCwgKXLl1SqquI0P1ZgqzWiQSS0pw9e/Zg06ZNsLKyQkhIiMLPKkHaESrrFJWsp6QhvTfNnj0b69evh6mpKdLT02FlZQVra2s8ffoUkydP5pQKAeTzFqkKurm5Oe7cuYODBw+ya8EuXbogMDBQsA5fNigjHbCR5+xXJQ29NCq9aJq2lMAlnDx5Uq4K4uLFi3kGpSrjUSTCIBKJeJ57GxsbnD17lnfz+fTpE7p06cJzQJibm7OLlSVLluDjx48ICAhAQUEBLC0tOWrLgOricyTqsaRIK/5Ke4El/0veV5qsrCz2Qm7btq3CSER8fDxev36N3r17o06dOgBK1Cs/fPjAq+EFSjzot27dYh+X9p0lJyfDzMxMqXYCEu+gxBsoLawjEonktkkASmpKpWsPpdtpSCOJ6JOQn5+P0NBQzvHHjBkjuFDJzc3FpEmTkJycDAsLCwAlC2YzMzPs3btXsP7G0dER+/fvZ+uyLCwsOHXf8sRdgBJxGUk0Qui8U0X8kOQ6IHVSKeqNCvBbuejo6KBOnTqoUaMG54ao6JyQ9TJLt5pZs2YNx2g/fvw47/UPHz7E5s2bUbVqVd4iURXVVVXmRpLfrVWrVpw5AeDOFbKfgVTdmPQzkwpkSQxOhmEQGxuL3r17c7YLnV+kdeISJAsi2TpEWVQR1SIlKysLR44cgVgsxsWLFzFr1iw4OzsrdAaqc98vLCzEqVOnEB4ezrvOOnXqhODgYJ7qckpKCiZMmIBr167JHYcyHUNI5yFZx6LkGi7td5MlMzMT9erVU7mdjQTJOS2LvHMaIBN0kr2GS8ukAuR3kxDaRjr+3bt3s11FMjMzYWNjwxrgnTt3VrrLhwRF9903b95g+/btnPvrnDlzSs0+k0YTglTjxo1DfHw8CgoKYGdnx/a7lufUk+5dP2HCBJiZmbGGrtA5vWTJEl4XGkVkZ2cTZZGYm5vjzz//5DnOXr58iX79+vH0UK5cuULUnq5Pnz7w8vLizc+xsbFYt26d4DpFtlOQj48P57G0QKSOjg6aNm0KXV1dwXu9kHFIikRpnZFRWWcYBiEhIXj9+jVnf2kB2VWrVuHp06fYu3cvPn78CFtbW953StpFRl0V9NIi7qQq6EDJZ9Z0q9dKH+F+9uwZm+YthCpKctK4u7tj3bp1nMhrYWEhJkyYIJhy9e7dO7l9IQF+Cy6A3GOZn58vaFTUqlWrVFGW06dPs1HHatWqsWkW0kinlgkhe/JfvXoVenp6aNq0KczNzbF3714sW7YMenp6+PXXX3nRuP/973/o3r072rRpA4ZhMHHiRDYFad++fYIXjKxT4MuXLwgJCcGWLVt4aUWfP3/GlClTcPz4cejr67Pp/4MHD8aOHTsEb5JCqUnff/89jhw5Imhwi0QijkCfrGCf7O+zZ88epXunP378WOUegrI9K+VhYGAgOJlLPpusA+P27dtsCo8kPS0uLg5r1qxBdHQ0r53Vt99+i8OHD+Px48dsWpexsbFgeruEz58/c0RQunfvzk6EHz584Ozr7++PvLw8LF68GECJQ6VatWooLCyEh4cHp42Kqty+fVuwvZKQkUvqoSXtjapKaqOQlzkrKwsHDhzA9OnTOem70q1qkpOTsWbNGty7dw9r1qzhZcwAUJjNIY8ff/yR+DUkJT2KsjCEvj/S6C3pZyYVyJLOmFLUS1kaSRYGAHh4eHAWt8HBwRyDu7i4GMuXL0dQUBBEIhGKi4tRpUoVzJ07FytWrBB0JpCKasneNyQGoqmpqVwHbP369TFlyhRMmTIFGRkZOHz4MFasWIEzZ87I/dzKZgjIMz5MTU0FHS5+fn7o378/Jk+ezMkU2rt3r+Dvr2gcQttIS2HmzJnDey4zMxNFRUUICQkRLGn49ddf4erqinbt2uHz58/48ccfkZycjKpVqyIkJIQXQCDps66K6BuJoBNpJpXkmPJKVSQiahJIxy85L4GSyOaVK1dw+fJlTJgwAenp6aUKb0q4ePEiwsLCEBMTg7S0NN728+fPY/z48Zg0aRIbYLlx4wZsbGwQHBzMU42WhybiZ5K1yLt371h1+aVLl+L27dswMjLiKVyLRCL8+++/qFu3Lk6dOgVPT092m9D34+Pjg7t372LXrl0ckbupU6cKlteRZpGQZqn4+fkRHX/z5s0YOHAgnJyceOnMst11JJCU5pBkO0i4du0anj59yt4fZ8yYgaysLAAl9wXZ9S1pWYK0o+XUqVNsq9natWsL2hCkpTPZ2dmIjIyUq4Iua3MMGDCAKOKel5ensL2zkMGtShp6aVR6g7tRo0aCNyVNERsbix9//BEfPnzA2LFjkZubi6FDh6J169aCNWWFhYV49+6dxhTMZZVdgZIb4rt373g//rt37wRvKF27dsWECRPQtGlTvHnzhvXMvXnzRtBjSXryz5gxg10cnT17Fj///DMCAgKQnJyMKVOm8Oo/tmzZwkb4Dhw4gJSUFKSmpuLWrVtwd3fHpUuXeO8ruUDy8vKwc+dObN++Hb169cLp06d5SpUrV65E1apV8fLlSzZa/eHDB7i5uWHlypU872paWhpWr16Nly9fYtCgQRgzZgxWrFiB/fv3Y9SoUbyxACVOCekoCMMwnBY7sp546VYPoaGhnN9UdlHTvXt3rZZJAGQODKDEANi1a5dgK7c5c+bwWllIFrrVq1fnqPtKnhdqcURS971//37Ojb9Ro0a4efMmCgsL0b17d57BTarsDwBmZmZKR9FInVQAuRoyUOI5li7DEFL7V0T9+vXh5uYmaPBfunQJa9asQWZmJpYsWYLBgwcrPBbp+Elr/QDykh5ZFC10FbUgAiDY2UGV30xZZBfVBQUFbKs4eVEukhTlDRs24Pr167hx4wZbu/ns2TPMnj0bfn5+WLhwIe/4pAalUMlAZmYm7ty5g507d5bqDGzcuDFmzpyJmTNnKtxPWUiV352cnBAfH4+goCDWwDYxMcHly5cFdRtIa6BJS2Hk1dMmJSXBzc1NUPVaLBaz5+7evXuho6ODjIwMPH78GGPGjOEY3Ir6rJdWMy+LjY0Nrly5wnueNH2VJJMKUE19Xwh548/JyUFCQgIb6c7JyYGTk1OpUdErV64gLCwM0dHRyMjIwLZt2+Rm1SxcuBDHjh3jOK4HDRqE4cOHY+LEiZzMChKdBHWoVasWateujVq1aqFmzZrQ09MTvAZIa8Tj4uLg4uKCWbNmYcaMGWAYBklJSejVqxciIiJgb2/P2Z/U6VerVi2kpKQIZqkIOf1Ijy+J9kqnMzs4OMhNZwbInLuS++PTp08514CikoalS5di48aN7OOLFy8iMDAQnz59wurVq3kZbKSty4yNjbF8+XI0a9YM9+/fZ53nubm5gs5s0tIZUhX0Z8+esb/vnj170L9/f07EXdZmGj16NJEWDKBaGnppVHqDu06dOkp7/1ShefPmOHPmDPr164cXL14gIiICQ4cOlduegrQFV2kInZweHh7o378/Nm7cyBEdW7RoEebPn8/bf+vWrRCLxXj9+jUuXrzI3rhevXqFtWvX8vYnPfmLi4vZdMmwsDDMmDEDw4YNw7BhwwRFKqpVq8Ya+seOHcPEiRPRsGFD9OjRQ3DRB5Tc9LZt24a9e/di2LBhiIuLkysK9Mcff+D69euceq06deogMDAQnTp14hnc48ePR5cuXTB06FD8+eefsLS0hKWlJW7duiVXHEu2nYZ0D1lNtqLTFiQODKCkrkteKzchT630Qhf4v4VVeno6Xr9+LehpJqn7Li4uZp0pAFivetWqVTkRFQlNmzZls0u+//57TqYJScqePEidVNJ1ZpJzXtKSTqjOLC0tDUOGDEHdunXZaz4yMhJeXl44cuSIoANDHnl5ebybpKOjI168eIEFCxagV69eALgLWdk6MtLxA+S1fgDfCFUGZRe60pk3vr6+8Pb2Vnhc0s8sXRqSk5PDpkXKKwOYMWMG3N3dYWJigqysLNja2qJ69erIzMyEr68vG8mWhsSYOXjwIM6dO8ep42zVqhUOHDiA7t27C869pAalvMyNly9fYujQoWqlQ8qW2kiyTxSVVSQmJrJ/W1paKvX+zZo1E9RtSEhIgK2tLec50hpoyWKapNxJiA4dOgjOcwA4ZSd//fUXRo8ejSpVqsDIyIg376oi5iQPWUE2CSRaCaSZVIBqBoqy4zc2Nkbt2rUxZMgQODo6wsPDo9TsM29vbxw5cgQGBgZwdXXF8uXL0bFjR7l9voGSqJvQZzMzM+MZ2CQ6CYD8LA8JsveO2bNn4+7du6hZsyY6deoEGxsbTJ06VTDbCyCvEV+1ahUiIiI418fgwYPRq1cvrFy5En///Tdnf1Knn7azVICSiKdQbbQ8SEpzsrOzMXnyZNy6dYt1Xkj+3rNnj+BckZWVxZbuASXnv+TeuXr1at7+kyZNUvi5Zdf/u3fvRkBAAO7fv4+TJ0+ya6+UlBRWlFEaUicb6ZqXNOKuioCpphx50lR6g1v6JJMmJycHQUFBbMqpqkgWGJ6ennBzc0PPnj3RsWNH9nnZhbQqxhKpx3LatGlo0qQJKzomEolgbGwsNyr18OFDNlIrfZO2tLQUjCaTfgZJlLBGjRo4deoUQkND2W1CIhI1atTA48eP0bBhQ8TGxnImhLy8PMH30NPTQ7169TBt2jQ0aNCAJ6ImbUBVrVpVUBylZs2aghH9zMxMdoHVt29fREZG4tChQ4IXroTIyEjeTU9RJIckwvrq1SvBSUyCbAqQKpA4MID/W2DLKrHn5OQIejilF7pAyeS1bt06fPjwQa6Xf/PmzZg0aRLatm3LXtfJyclsmYI0Hz9+5Ci+SsSPPn78yEs/BxQrr8pbkCgSEpOF1ElFqoY8e/ZseHp68tK7Dx06hFmzZgnWYAuVtmRlZSE6OhozZszgPF+lShXo6+sjKiqKJ7InEol46b2k4wfI+8ECJb//r7/+ivr168Pb2xuzZ89GfHw89PX18b///Y8TZSJd6EpnRu3atavUTCnSzyztiFKm5vjChQusIvGePXtgYmKCqKgovHnzBn369BE0uJOTk9GkSRNBIzQnJ4ezr7RjVJoGDRrILVkgNSjl0bx5c7mCQsqiioCYNMqkoUsr0/74448wNzdXqEyrqDTk8uXLvOdUKXcSIjU1VdC4AkrKec6cOYOmTZvi/Pnz7DxQVFTEu79qss+6vO+XRNCJNJMKUM1AUXb8U6ZMwZUrV3D8+HEkJycjOTkZtra26NixIyvoJktkZCQaN26MkSNHwtnZGfXq1Sv13KtSpQrS09N5QmXp6em8mm/SlGPSLI+0tDR8/vyZjWjr6uoqTKVdv349Fi1ahPr16+PQoUPsWrN27drw9vbmpSi/ePFCcO5wcHAQrLUldfppO0tFFUii6HPmzEGnTp1w+PBhjhbJunXrMHv2bBw8eJB3fEn6uATpeVq2HhsA517l7u7OySYUonbt2pyacwnVqlVDcnIy73nS0hlSFXTSiLsqAqayOhkikUhuBoOyVHqDe9WqVZg+fTrS09OVTgcmQfrElRizkueEIlf79+/neEaUETkh9VhKxlJayqcE0nQK0pPfzc0NVlZW+O6776Cvr8+mJN+6dUvQK7pp0yYMHDgQmZmZcHNzYwUV/vrrL7mpmR4eHhCJRCgqKip14fXlyxfWoJWGYRjBRZ9sPXbjxo3x5csXufXYAHkkhyTC+s033/DSoTQNiQMDUNzKTeJdFCIxMRFr167Fixcv4O3tjX379skVjSGp+544cSJcXV0RFBTEtnl5+fIl5s6dK9geSBFdunQRNLozMzPlph2LRCJOlgupk4q0zuzhw4eCtdSjRo3CypUrBd9D9jqRtJrZvXs3z1FJ2mqQdPyS9yep9QNKnIve3t7IycmBvb09duzYgWPHjuHSpUuYO3cux7GjykJXemylocpnJjm+tLH1999/s06k77//Xu7rSWpSJeIvQvOiPOeil5eXUiq5pREfH19q28TSSExMxL///svTAvjrr7/QqFEjwXsTKdLKtHPnzlVLmXbkyJG8eYW03ElIuT0zMxPPnz+Xew/asWMH3N3d8ebNG/j5+bFG3JkzZ3jrFemIM1CyYJV+LHsfkKdPwzCM3Ii7onRasVjMeUyaSQWQGSik45fO+nj58iUSEhJw5MgRTJ48Gd999x2bsSPNkydPkJiYCLFYjNWrV8PQ0BAfPnxATk6O3Oj4ihUr0KNHDyxdupQTlfXx8eFFKEl1EkizPP744w8AJbokCQkJ2L17N27fvo1q1aqhU6dOPKHgsLAwNkCwYcMGzrr71KlTPINbOjNNFqFtqjj95GWpCKEpp6IiSKLoiYmJnKCVZJ8lS5ZwxMekkbShk00VDwkJEVxTS2u2/Pzzz5zHpZGcnIywsDBERkaiWbNmgg460ugwqQq6ooi7RLBPGtL2zgDXLpP8n5+fDwsLC/z++++C5RKlUekN7gkTJqBLly4YNmyY0unAJCjyYAudVELGR2kiJ6qIJJBAmk5BevJPmzYN/fv3x9u3bzkXd5MmTQQV2B0cHFiDSpoff/xRrrCSPKNCCFmDVnabLNnZ2Wz9tQTJIlOeMqo85EVySHpbNmzYkLjGhhRFDgyhm4NsKzeRSAQTExO5rdzOnDkDHx8f5OfnY8mSJejXr59S4yooKMDdu3c5YjctW7bkOZ6WLl2KgIAA2Nra4vPnz2AYBrVq1cLChQvlKjPLQ56xLOTVz87Oxo4dO5CTk8MxuEmdVKR1ZsXFxSgoKOB9D1++fJEbnSSpG5NEKQBwohQABKMUpOMHyGv9gJLPN3ToUADAunXr2L979OjBu86kF7pr1qwpdaErnVkkK3oo+YzqfmYSfvjhB+zevRs//PADrl69yhoKnz9/FlR/FuLRo0fs92JgYMAx4oXmOXmOXgkjR44EwzBwdXWFq6ur3AWfhM6dOwsaiPXr11fYjUMZvL29BY9hamqK8ePHC86x0srv0gstCbIpr4mJiRpTphX6XknLnWR1CiROs7Zt28qNsLZr1w4nT57kPd+7d2+esjJpn3VF2xQ5XuXh5eUFV1dX9jFpJhVAZqCoMv6CggLcuHGD7QF95coV1KxZU1DgS0Lnzp3RuXNn/PLLL0hKSsLhw4fRvn17GBgYCCr7Dx8+HAYGBti0aRMCAgIAlKxBDh48yBNtVUcngaQdob6+Pj58+IDc3Fzk5ubi3LlzePr0Kc/gJl1fSot7ye4rtBYmFRg9dOgQ3r59y64DzM3N2dZ0fn5+vFaApFkqpB1JALIourzzXJIRKYS/vz+cnZ2xf/9+towzKSkJOTk5vLWJLMqcE/fu3YNYLEZ4eDgaN26MESNGID8/X66jnqTtG0Beky0v4i5R1ZdFFS0YeXbZ0aNHMWPGDME5tjQqfVsw2fZMurq6ePHihcJ0YHV49OgRxGIxwsLCUK1aNaVFlRSJnADkQiEkkLYiIW0BUBaQ1MBkZmZqrL81KfHx8Vi8eDFPyTMjIwMvX75kDY7g4GDWoz5o0CA2SguULIxOnTrFO3ZxcTHCw8MxcuRIrY2/sLAQf//9Ny8SEhgYiOHDh8ut45JFR0cHzZs3h42NjeCELnTDevHiBbp37w49PT22b2lSUhLS09Nx5swZznckjaQvZt26deWOXxHKtFJ5+/Yt/Pz8EBERgUmTJsHNzY2TqkiqmilRpZVXZ9ZNpof2ihUrkJSUhK1bt7I1dy9evIC7uzvMzc3lRuJ37dqFwMBAjhqsm5sbL82adI4gHb+EwsJCXq3fx48fwTCMYHRDlXZuEi5fvswKprVp04a30JW0GhQyQIUcbYo+8969e3mROS8vL/Z40q1XJMiWhrx+/RorVqzA69evMXPmTNZJJRaL8ejRI/z888+8z7hkyRLUrFmT1T1o2bIl9PX1kZ+fj169epUqDCdBUbuie/fuITw8HBEREahevTpcXV3h4uIiqPUgmxIqMRClVWFVpXPnzrxSFQmy6wAJ4eHhyMjI4PVpvnPnDpo0acJTyyU9xxQhNK/IG6eibdHR0Xj8+DHMzc3ltiiV5Y8//sCGDRs46wkvLy8MHDiQ8FNolxYtWnDEDLdv346QkBDBTKoxY8YIln20adNGsEsEwzBo27YtcQcJaezs7PDkyRO0b9+e7QNta2tb6voiICAAGzZswKdPn9i5zdPTE+3btycWulQWZXQSlDmflyxZgoSEBKSkpKBdu3bs57azsxMsO+vQoQPi4+NRXFwMBwcHxMfHs3Oqvb09rwxDdm0ki6xuhyLxPpFIxDOgbWxscOzYMTarVFLOk5eXh379+hFlcwldw6rMCSRtQOfOnYuioiL4+fmxjtxPnz7By8sLDMMo7IIUGxvLyQ6UOF9k12DSwcLhw4fj8OHDggEnCTo6OnBwcMCePXtYJ5a+vj5RMEoR0nNf165dMW/ePDbtXbrtnDaYP38+20FIWVS9L1T6CLcq6cCkPHv2DGFhYRCLxahatSpSU1ORmJgouOCQhyKRE1WEQkggTacgFSQoC0hqYGxsbODl5YXp06crdWxVetmSRnI8PT0xZMgQ9vddvXo1xo4di7y8PCxbtozzmsjISPj4+ODly5f46aef0LdvX2zfvh1+fn6wsLDQuMFdXFyM06dPQywW46+//kLnzp15Buv9+/fRsWNHGBkZYeTIkRg2bJhgPagEkoi+hCVLlsDT05O3qJJoMRw4cEDwdbVr12bHf+LECVhbW/PGL5SaCZRcA0JKpBKeP38OX19fxMbGYs6cObhz547gnELqoSWtM/v111/h7+8PBwcHdr6rXbs2PD095Ub0d+3ahaCgIGzatAlWVlZgGAY3b95kb9zSiwDSKIWTkxMSEhIQGBjIjt/U1FTu+AHyWj+ArEZZFnt7e9jb28Pf31+w9pM0s0joM0t+sx9++IG3v7SRp4zuQtOmTdka7szMTPzvf/+DWCxGamoqBg0aJPiakydPctJaGzRogLNnz4JhGDg6OiptcLdq1Uqu08nY2BgrVqzAihUrkJKSgvDwcPTt2xcNGjTgpdR+//33+P3331kDccqUKYK6GaqQlZUl6BgoKiqSe289fPgw5s2bBwcHB87zVatWxbZt23gGN6kyrdB9QPJaIRE30nKn2bNnIyUlBfb29li+fDkSExMFHS/SBAYGIjg4GL6+vqxj6Pr161i6dClevHjBmV9J2wlpui+77HdHmkkFlGTGzZo1S9BA6dOnj1rj37FjB8zMzDjn3OfPn3H48GE24ifLr7/+iuvXr3Myd1JTU+Hh4YHMzEy5BreyzlF5yMuuI83y+OGHH1iHh/S1+/btWwQGBvKyB2UzZ0xMTDiOS1kUCWHOnz+ft10owFNUVITIyEj8888/PIO7qKiIU8IpWS/VrFlT7jwhD6F7nyodSUii9Js2bYK3tzf09PTYSPGLFy8wduxYXnaBLL169WJFTy9evAg3NzfBDh3Sc4BsRqiQZsvZs2fZeb9jx45wcXFRqVWpPEhrsjXJkSNHiAxuRevF0qj0Ee5WrVpBR0dHrjqwuh4Ya2tr5OfnY9SoUXBxcYG+vj5at25NvFhLTU3FyJEjBdtOODk5YeXKlYJCIb/88gtvsVhauw7ZGlZSj+LIkSPRtm1bNGvWDCtWrMDTp09Rp04d5ObmokuXLoIiCdqGJNL17t07LFu2DLdu3cK2bdtKre1TJYpGGsnp2LEjrl+/zj6WFlFydHTkZD4MHjwY3333HRwcHHDq1Cn8888/EIlE8Pf3R8eOHRV+FmVhGAbnz59HWFgY/vrrL3Tq1AkXL17E06dP5TqpGIZBXFwcwsPDcfToUZiZmcHV1RVDhgxRuW+4NEZGRry+qfK2kY6fNNIFlFxHly5dgru7O8aPH89L4ZR+H1U9tHl5eWzPcwMDA6VEOaQj+oro3LkzoqKieJkBaWlpGDp0KCdaSBqlkOXLly+4c+eOwhZW6kSrlYHUeNAkymRJlEZOTg6ioqIQFhaGx48fw9nZGWFhYXj58qXc18hGRU+fPs1GNRRFU2WRjTQK8fnzZ/z5558Qi8W4dOkS+vTpwxMKdHV1RbVq1eDo6IgTJ06gVatWxNEDeSxYsAA5OTkICAjgGFYeHh6oVasWNm/ezHuNtbW13Iifubk5bzEvJNokjWyqJOn+pUU3ZR2VZmZmuHXrFqpUqYJPnz6ha9eunBZRQrRr1w5XrlzhzcnZ2dmwtbXl9MLu06cPNm7cyGo6mJqasu2Etm3bxhNjlL5vyV6z8oQBJeryskicaNJGonRpi7J8+fIF3t7eCAkJQcuWLcEwDNLS0lgDRTpLUJXxAyVp5SdOnEBYWBhOnDiBwYMHw9nZWdAJYGhoiDt37vDuF/n5+TAzM+MEDyRInKN+fn485+js2bNLjZAC8rPrSNd/0mRmZrLOhWfPnmHgwIGC15mmKG0e/fLlC3bv3s06n729vVnRPwlt2rTBw4cPeY65wsJCGBkZsfdbVcfTsGFDDB48WK7NISSeSrJmP3PmDHr06IFPnz5x1gbKBA+vXLkCsViMqKgotkPHwIEDOR051KG4uBhnz56FWCxGTEwMunTpAmdnZ57TgzTt/uPHjwgICMDr168xceJENjAVHx+Px48f846viJcvX8rNhhRC3jknyVCTJjMzE3FxcfD19VVJXLLSR7jlFbxrClNTU5w7dw7379/H/fv3oaenp7DmQRWRE1KhEOlFQkhICOdkFBrb27dvYW9vz1PAlAepIAEpQtEmaWRbQAFkNTCNGjXCjh07cOXKFfTu3RsGBgasU0YoSqFKywDSGhVZJXrptCbZ3/jJkydsn+ypU6eiadOmePHihdoKidI0a9YM+vr6cHNzg5+fH2rXro3WrVsrnNRFIhGcnJzg5OSErVu34uzZs1iwYAFmzpzJE72SF/mRILQIVpR2KruNdPykkS6g5DwViUTYvHkztmzZwks9lnbmkXpoCwoK2EWinp4eu0gcP348fHx8eIu1P/74AxYWFmjZsiXq1q2rVA/rT58+Cd54WrRowTsfSaMUqrSwUuU6I4G0F6km0cT4mzRpAmtra6xfv551Dhw+fFjhawoLC/Hu3Tu2xlhibGdkZBCpgsu7VvPz83H8+HGEh4fjwoUL6NmzJ8aNG4cDBw4ICnrevXuXvT9NmTKFjRZrAh8fH8HIz7hx4+RGfmTVe6UR6ohRUFCAN2/e8OaJy5cvCzqSZO8Dnz9/Zq93obmINPOnevXqbFZZrVq1lI72CDlANdFOSJUWSiTq8tICXMpSvXp1bN68GWvWrCnVQCEd/4kTJyAWi3HmzBl0794do0ePxuXLlwXbS8mOSRbpdm2y7NixAzExMZz5ulu3bjhy5AiGDh3KMbhJs+u2b99OZPwIOf7u378v1/E3YMAA2Nvbw87ODjY2NhopH5Hl48eP2L59O3bu3ImBAwciNjZWrlE1ePBgzJw5E/7+/uyaKS8vD56enoKZQqRZKqQdSQCyNfvChQtx48YN1KpVS+nsVtkOHT///HOprehUQUdHBz179kTPnj0RGBiIU6dOISIigmcQk5ZxFBUVya3Jltc9Jz4+Hi9fvoSjoyOaNm2K5ORk+Pr6Ii4ujuc8lifixjCMXOFR2eCMJKi2du1apUsrZan0Bjeg3frnvXv3oqCgACdPnsShQ4cwc+ZMZGdn49ixY+jduzfvPVQROSEVCtmwYQP7d2xsLOexEEePHsWSJUtQUFDA1uLY29vzUoYkkJ780h5s6XYT+fn5+PjxI++E3rp1K+8YIpEICQkJSE9PF1T8JVWSjI2NhaenJ6ZPn46ZM2fKrU+UvLfQ30KPVaVBgwa4ceMGm+InWRDduHGDVw8mfZ5UqVIFLVq00KixDQAzZ85EZGQkfv/9d2RmZrKtQ5ThwoULiIiIQExMDMzMzDhq0xIiIyOJxySrmCtBqF8r6fhTU1N5i2igRMBv5syZgq8hceaROqk8PT1RUFCA1NRUdt/379/D29sbHh4e2L59O2d/VXpYC7XGkyA7b5E6LlVpYcUwDNsDXPK3ZL7QhMFKajwIzbmqool5YufOnQgPD8eECRPg7OwstwxCGg8PD/z000/YuHEjpyXSokWL4OHhwdlXyGMPKE7Pb9myJbp37w5XV1cEBweXek+VNsI1lUougcSwkmBhYYF9+/bxFp779+8XXMy6u7sL3k/r1asHd3d3HDt2jPO8v78/8vLy2Pajbdu2RbVq1VBYWAgPDw/eb0AKaYo7UJIiKlsaBZQ4EGUXiqTthDTRQkmRsJ+QeKE08n7rN2/eYPv27Zw14Jw5c3hOEtLxDxgwAA4ODvj777/Rrl07AKWLwxkaGiIsLIxX+iUWiwU7bgBkzlHZe2tp2XWkxg+p48/T0xPx8fHYtGkTrl27hh9++IE1wO3t7Xn90EmNn19++QWhoaEYM2YMrly5Umq0dt26dfD29kaLFi04GQ/jxo0TLFsiXauocq8iXbOTok6HDmUQKrusWrUq+vXrJ9jmizTtvlu3bmy2iZOTEycrY9iwYbzsNy8vLxw9ehRWVlbw8fFB7969sWfPHixZsgS7du3ivZ+ilp9GRkaCz2tDuLjSp5QL1T/fuHEDFy5c0Ej9syz5+flsWt3Zs2dZ9UNZnj59ypn8ZScdaVQRCpFAkor57t07JCQkICEhAVeuXMHt27dhZGTESzmSPqbsya/M+/3777/w9/fHgQMHMHr0aMHFrjQnTpyAj48PqlWrhiVLlrA1KNIoaqlx/fp1Tqr10KFD8f79e2zdupW9SSqiatWqaNCgAZviJqlNlixElVUIVsTFixcxduxYTJkyhaMiuWfPHoSEhKBLly6C4wHAjkmyyBLyuqrKnTt3IBaLERERgefPn2P9+vUYPHgwK8wlPX5JGpGxsTGbSv7lyxccPnyYV9fl4uKCkSNHon///goNP2nk9eeWIKS6rez427ZtK5jKB8gX3QGUd+YpMt5SU1N5eg/yxlNcXAxDQ0PeeKTT0idMmAAzMzPWkJd3TUrOI1mEzmtSHQPp9Mu+ffti3Lhx7OvlpdALlf9Ii5ap261B0e9oYGDASyUkTWNXZLDu3Lmz1JpyZcnKysKRI0cgFotx8eJFzJo1C87OznJb1Bw9ehTr16/HvXv3IBKJYGxsjIULF/LaRpamEi60wJDuda8M0uec9HyqjblLGdLT0zF48GDUrVuXI3T3/v17REdH84wcRSnoQin6HTt2xPnz51mnmeS6KCwsRPfu3eWKpCoLaco6wF0TSX/muLg4REVFcZxSw4cPx8CBAwXbCUVFRfHaRZKIP0kgEfarUaMGdHV1lRYyBLhihtJrwH379iE4OJgzl5GO//nz5wgPD4dYLIaOjg5GjBiBrVu3Kkx7TktLw5AhQ3jnXG5uLpuVJItsyZk08uapM2fOcO5LPXr0EHy9gYGBYJBDgqzxExwcjPDwcDx69Ih1/Lm6uipdnvn48WMcO3YMW7duxbNnz3gBFNKyCh0dHdSpU4eXIVDanCKUkn337l212xy+ePFC8DdUltLuO7Vr1xZsC6vIyQaA7dARExMDQ0NDJCYm4tGjRxop9yMtByNNu5deT8iWdgiVepiYmOD69euoWbMmMjMz0aJFC9y+fVuhnSUPeb9ncnIyfv31V9SvXx/e3t6YPXs24uPjoa+vj507d8LW1pb4vSq9wU1a/6xJDh48yOuNm5OTg0mTJiE5OZm9sd26dQvt27fHnj17BNO6ACAmJgYbN27kCIV4enrKFQqRQLJo/PTpE65cuYL4+HgkJCTg9evXMDAwwKFDhzj7kZ78El69eoUNGzbgjz/+wPTp0zFr1iyFdaYRERFYt24d9PT0sHjxYtjY2Mjdt2PHjvj777953s0TJ05g5syZnIVJeHi4YNuJ8ubVq1cIDAzkqEjOnj1bI+3rNMHNmzdZ41XWOOnevTtGjhyJoUOHQkdHB4cPH0Z4eLjcui6JwRAXF4cePXrA1dUV/fr1k9tXnhQhZUlF4x82bBgGDhwoGOmKiopCVFQU7z1InHmkTipFDgChbZaWloiNjUXdunXRqlUrnDhxgo1ompiYEPe9lIX0htq/f38MGzYMP/zwA8aMGYPHjx+jYcOG+Pz5M6ysrNQejyqQGg+K5jIhSA1WRYJlsn3c5ZGRkcFea7JCNpokPz9fMHqtKN1S0eKvonH69Gn2nDQ2NhZ06gLCjhlF22TPIel0UU3oEqhKXl4eDh48yDHIRo8ezcuUSk9Ph7OzM7799lteO6GYmBily9AUYWVlhYSEBDZzS/KdSYT9Ll68yO5Lek0CJefonj17eMGVO3fuYOLEiaXWvCvLkydPIBaLIRaLUa1aNQwePFjhNSx9zpmYmChs10XiHJU26KXvSx8+fMCRI0d4xoMqNceA8o4/hmFw+/ZtxMfHIz4+Hg8ePECDBg1gY2MDGxsbpZX1tUVpnYUk3SokSJdRiUQi3jVPur8spc0LpqamCqPDypQzltahQx6PHj2Cn58ffv/9d87zpDYB6dxHuv4g0V8oDXk13DY2NvD29kZOTg4WLVqEHTt2YMCAAbh06RK8vb3ldsxQRKU3uI2NjQV7Ope2TRMI/VBjxoyBqakplixZwkmzXrduHW7fvs32VlUHSQq3UERWyOM3e/Zs3L17FzVr1kSnTp1gY2MDa2truXUIpCf/48eP4evriwsXLsDd3R2TJ09WmHq4Z88eVjl58eLFSnkc9+/fjw0bNuDkyZOsgbp79274+Pjgjz/+4PTEJBWVk0VRypsmkNS0SStpCiHtwTY1NdVaOxEJ7969Q8OGDQUX2NnZ2YiKioJYLFZa0AkoWfgdO3YM4eHhuHz5Mnr37o2RI0cK9lsvrXZPWumZdEInjXQBZM480hvSmDFjYGZmxivd8PX1xa1bt3jzRExMDNzc3ACU9KCW1BBeuHABPj4+Cm/QykA6fnktrM6dO4fExEQirQd5N3lSSI2H77//XmHamDLK4kCJRkZkZCQvy0O2LADg9nHXREScRHW5S5curHEzatQojqNVWXFIWUi1LCo6kydPhp6eHlauXMl5ftWqVXjy5AmvdtfQ0BBJSUm8LICPHz/C0tKSl25ZmrCeOpGz0lDUVlKonZDQfUBRSyIAvGsAIBP2U2XhrMjhKLtNlfELce/ePURERLBR+7Jk4MCBGDVqFC/Yc+jQIRw4cICnVaEJx48ix1/dunVhaGiI2bNno1u3boJ6IrIoWwKgKiSdhWSVy798+YKQkBBs2bIF9vb2vO4opPsDZGt2dYxHWSRCt7LlJcnJyVi4cCHS09MxaNAgzJ07F/PmzUNCQgIWLFjAKxMktQlIP4PkXizbQpNhGISEhPDKW+rXr4/evXuz+8TGxrKPAeG2s/KQJxgq/RlkRXtVbVVW6Wu4SeufNf3esiQmJiI0NJTznEgkwpIlS9j+dbIsXLgQRkZGmDZtGuf5Xbt24dGjR7y6k8ePHxOliaSlpeHz58/Q09NDs2bNoKury4rsCJGeno5FixaBYRj2b6Dk87569Yq3f7t27aCrq4uhQ4ciNTWV5/WVXbhKhMDu3bvHiTgqipqMHz8ederUQY8ePXD8+HGEhIQgJiYGFy5c4LXkIRWVk01569Wrl0q9bBVRXFyM5cuXs0YFwzDQ0dHB3LlzsWLFCs64hDzYkZGR8PLyEvRgq8KZM2fg5eWF+vXrY+XKlZg2bRqys7NRWFiIffv2YcCAAZz9v//+e2JBJ6CkFceIESMwYsQIXLt2DVOnTkVISIhgnb5QGpU88vLyBNvrSJB14ujq6uLatWucqEO/fv3kRroAMjFDUh2A7du3Y/LkyWjTpg2n9tbc3FwwLXPw4MEYMGAAr4e1lZUVp+5SVUjHL93CSppu3brJ7cFd2k1eXXR1dZGYmMgxHvr16yfXePjmm2+IzjlphNR7ZZEuBZLu4z5t2jTWeaIuJO0SpReK0krVALk4pMR4K0uDuyyM1S1btmDixImc6zI5OVnudTlx4kS4uroiKCiIddq9fPkSc+fOFXTsSrQmGIbBvXv3YGJiwtE90UTGQG5uLrZv346XL19i4MCB6NOnDwIDA1k1ciGDW7qdkCJIBNAkkAj7ybY8U8b5XaVKFaSnp/Mcaunp6TztFlXGL4SxsTGOHz9eLgb3w4cPecY2UOJEk3UUAZrRx2jcuDFmzpzJmzeAkjT8hIQEhIaGIiQkhO1ZbmtrK2jgSpcASK6RGzduwMbGhlcCoArSnYUOHz7MdhaS18ZXUvuel5eHnTt3Yvv27ejVqxdOnz4t+BrS/QGy804oGFEapXXokGXatGmYPn06unTpgmPHjqF9+/YYP348Dhw4IKgXRNqeMzo6mvP43bt3iIuLg56enmDXIGkbQdZeEKq7lz2+rHYWCfJq3aWfl9VHUKQJpfC9KnuEW536Z3URinDLqyNkGAZt27YV3Cavfqe4uBgWFhasYrUEVT2Wjx8/Zmu4b9++jWrVqqFTp048hVfS1ElF+4tEIt7CQ52oyd9//40xY8bA0tISR44cYWvn5KGMp40k5U1VfH19cfbsWfz+++9sb85nz55h9uzZ6NGjBxYuXMjuS+rBVgVLS0vs3r0bOTk5GDRoEM6cOYPOnTvj4cOHGDFiBK9WUdW6rgcPHiA8PBwRERGoUaMGXFxc4OLiQrxQl231ULduXXTu3Flumpwm0m/btWuHq1evCjrzrK2tOR5PUg+thCdPnnBSXeWJ6sgjNjYWGzduxF9//UX0OllIdQxKE/QS8jDb2NhwbvI+Pj4YP3481qxZo3FRQGlycnLYXu7SkHrhVWnbJdvHfdq0aUQ10aVBEnlQpS2btPH2008/oW/fvti+fTv8/PxgYWGBo0ePauyzlIYkvV2bxqqEx48fcyK+iq7LgIAArF+/Hp8/fwbDMKhVqxYWLlyIefPmKbxGlDn/SNvrAGXTVpKEXbt2YdeuXYLCfpMmTeIEGhYvXoxatWqxhmyrVq2gr6+Pz58/y3V+R0ZGYunSpVi2bBkne8nHxwerV69m2zNqGk20AlSFtm3b4u7du7zyrC9fvsDU1JRXjnT37l12zQGUXCuqzrelfebCwkIkJSXh/PnzCAoKwvv373k6R9ouAZg0aRLOnTsHJycnuLi4oE+fPjA0NJS7VsnJycG2bduwd+9eDBs2DB4eHnKVsVXZn5Tg4GCF84aQI4+0vZ9shFaVVseKGDBgANavXw9TU1Okp6fDysoK1tbWePr0KSZPnsxzsCcmJsLKyortyKBp5K1XGIbBiRMn8OHDB942bWg7VfoI95w5c9C8eXMsW7aMk367aNGiUuuflaG0HpKy/Pjjj5g1axb8/Pw4vUK9vLzQp08fwfeQbakkQUdHRzBKr6qPRF9fHx8+fEBubi5yc3Nx7tw5PH36lGdwm5iYEJ38itIypVMcJQgZW58/f8bx48chFosFFxjSKTnv37/HtWvXoK+vX6pwhjJKjUVFRRxlcElrIZFIxPY8VpeDBw/i3LlznOhkq1atcODAAXTv3p1jcJN6sFVFsjjR09ND586dAZSkSAp57yZMmIAJEyawdV3Lli3D69evsWDBAsG6rlWrViEiIgI6OjpwcXFBVFSUUqlmyrZ6aNOmjVZrWgHAzc0Nffr0EXTmySrVknpo+/fvDwcHB9jZ2aFHjx6ltlI5c+YMZs6cyUaHFy1ahKlTp6KoqEipWuDSkNcaQx6qeJTz8/MxZcoUACUpWtu2bcOmTZuIjyOPtLQ0rFq1ii0fGD16NFasWIHg4GDB60lRlo8QpOq90n3c165dy84xEtVhTRjeJKrLki4ADMNwOgIIdQGQMG7cONZ42717N1avXg2RSITDhw+XufEmXTNnaWmp1frxNm3aKO38mjdvHubNm8feKxTplkijzL2JVGEa0G5bSekyhZUrVyp1P5o6dSqaNGmCxYsXs04MExMTeHt784T9/v77b7YbA1CSOnrmzBnW+S1kcLds2RIHDx6Ev78/Kw5mYmKCgwcPsvc4dcZf0Rg9ejSGDx+OrVu3slkdL168gLu7O0aNGsXbf8CAARzhOYZhkJ+fDwsLC04AQBnkrT1fvHjB1nBfvnwZz549g5WVFTtPSvPx40dBMWMzMzOeIrsqkHYW0tPTQ7169TBt2jQ0aNCAp/UhW2ZAuj8p0gE2ZTI0AfIOHfn5+ZwMwZo1a3Ieqyss9+zZMzZ7bM+ePejfvz/27t2Ljx8/wtbWlmdwe3p6sk5UaYV7eWWXsnaZSCRCo0aN4OjoiDVr1vC0nhStV+RtI10TKUOlN7iBEo+u7MStKUhTkDZt2sTpFSppSTB27Fi5vUK/++47TssoCTdv3hRMHX/16pXCelfZBf+SJUuQkJCAlJQUtGvXDnZ2dhgyZAjWr18v6JkjPfkV4e/vLzddtKCgACdOnEBYWBhOnDjBLpKF0FQqmBCa6mWriOLiYo6xLaFBgwY8p0pxcTEKCgoEPdiaKpOQbtFUrVo1pVs01a9fH1OmTMGUKVPYuq4VK1bwjF9JyqmQSnxCQoKgwiNpqwd55OXlaWRxSeLMI3VSLViwgKiViqenJ4KCgtjosIODA3x8fHjq4ZpGXnRYOu1PWU0Cbd/kx48fjy5dumDYsGH4888/YWlpCUtLSyQnJwsKE0o7CpVRZidt20XSx11VSNolTp06lf2tpP8GwDpCZNGm8aYOmmx5ow7q6oWUBml7HUC7bSWlyxSOHj2qtME6aNAgwR7Isqji/JasVyS15/b29nLXK6Tjl1fzzTAMr5a3rPj111/h7+8PBwcH9r5du3ZteHp6Ct4P5EUujx49ihkzZuDkyZOc5xW17RIqBdPV1UX9+vVha2sLOzs7TJ8+XeFcTlICoCrVqlXDTz/9hJ9++ontLHTgwAFMmTKFF3H38PCASCRCUVGRUutM0v1JUaWFGGl7v++//57jGJB+rIkMQemWkKdOnWIDFLVr1xZcI124cIHNjkhISEBERAS8vLzAMAzs7e15WbRC33tWVhYOHDiA6dOn8xzh6pYpaIpKn1KuCSVYbSDUkkAeFy9exOjRozFlyhROStSePXsQGhrKaRkFlHh0FX1u2YhzQEAA7Ozs5PbdFkL65E9ISMDVq1flnvyKEBIkOHHiBMRiMc6cOYPu3btjxIgRmDt3LnEvYHmQisqRpLypSocOHRAfH88zZhmGgYODAye9Z8WKFUhKShL0YJubm2ukplzbLZoKCwsRERGBly9fom/fvrCwsGDTiD9+/CgoOEHS6iE+Ph56enp49eoV2rdvj+rVq+Pt27fw9/dHcHBwqWJumsbR0VEtJ1VprVRkU8BkRTzURTo6PGjQIIwZM4YTHQ4ICODszzAMfv75ZwQFBUEkEqG4uBhVqlQR1CSQoEj0TxM3eVkBJl1dXbx48UKuE0SVFGuAvG1XZYbkeylLKso4hMQBi4qKEBkZiX/++YfnsJU4aYSEfgB+KYYqCtMkrdlIFZcVXTPyIFmjmZqa4vz587zsk4yMDDg5Ock1BpVdr5COX5VWlWUJaVaFLELfAWnbruzsbLndd4SIjIzEsmXLsHTpUq2UAGRkZCAjI4Nn9KekpKBu3bpaFSbUNMpeY6QdOrTNyJEj0bZtWzRr1gwrVqzA06dPUadOHeTm5qJLly5ITk6W+9pnz57h8uXLSEhIwKlTp1C/fn1cvnxZ6fcW+s5II+LaotIb3GWhBEvC1atXoaenx0aO9+7dy/Ze/PXXX+X+sK9evUJQUBCnnlNey6iyXGwoc/LLSwNiGAbt2rXjGdw6OjpwcHDA//73PzYCqq+vr5GIj6pI97IFSow/oV62qqLIwBWKdvn7+2Pjxo2CHmxtR3eKi4vV9jRPnDgRz58/h62tLS5fvoymTZvixo0bWLduHYYNGyb4GpJWD1u2bMHq1avRtm1bfPr0CTNnzsTSpUsxbtw4LF68WCOt1kpzbMgK5pA4qUhbqcj2Up03bx7HCBaKdJHQvXt3dOnSBV26dMGff/7JRoi3bNki+F2SaBKUFbJOLXt7e85jWacnqTJ7YGAgRowYwXGiZGRkIDIyEhEREYIOA2X7uKsKSYSVpAuAhIrUV5vUWFWH5ORk1qHVrl07wRRYWb58+YLdu3ez0Udvb28YGhpy9pFuFyiEbCRG2/d6UsVlSY9ghmFw9+5dNm1UkeApyRpNXed3amoq2/ZUaL2iyvgrGu/fv0dwcDDq168PV1dXrF+/HpcvX4a+vj5+/vlnud1nZMnMzESvXr3KxXF18+ZNbNq0iTMvenh48LI8VcHV1RXz5s2Dg4MD5/lLly5h27ZtvDa4qsyLf/zxB2+96OXlJSieqQ7KXv+kHTrWr1/Pfu5Dhw5xShG8vb0Fy+BI+PjxIwICAvD69WtMnDiRLcmLj4/H48ePOWnykvEkJCTg7du3aN26NdtJydLSkqiVbF5eHuzs7JRSEJdExM+dO6eUALAmqPQGtzTSSrCTJk2Cm5sbkedNE1haWuLMmTOoX78+zp49i7FjxyIgIADJycm4desWT11PFXr37o1Tp07xnlfU9oME0pNf4iWX54WXNSafP3+O8PBwiMVi6OjoYMSIEdi6dWu5CJBUdNT1YKuCJsRgTExMcPv2bVSpUgV5eXlo2rQpnjx5orBulqTVg7GxMS5cuIBGjRrh2bNnMDIywoULF2Btba3WuKWpWrUqzMzMMHToUDRq1Ih3fssTZFTGSUXaSmXSpElytynqpaospNHh9u3b8zQJgJJFXPfu3XmiexK02Q5GyKklQWgeIo1wz5s3D1FRUTAyMoKrqyuGDx8uWCYigaSPu6pIR1iF6v2kF4ukYpgVDVJjVRUyMzMxaNAgvH79GhYWFqxjTFdXFzExMYLriY8fP2L79u3YuXMnBg4ciAULFgi2GQTIRdA02SJIEbKKy15eXoKKy+q2iVNmjUbq/CZZr3wNbe4GDhyI1q1b48OHD7h16xYcHBwwYMAAXL58GVevXsWJEyc4+3t5efGc9JmZmYiLi4Ovry+GDBlSlsPXOtbW1nIdJ+bm5pwuNgD5vBgYGIjg4GD4+vqyDoLr169j6dKlGDt2rNpCzaQZmtIo295P1ewuZRHqHCUhNTWVN7eYm5ujRo0a6N+/P+zs7GBra6vw3ipU6pGVlYXo6GhMnjwZs2bNUnqsZRnA/CoMbm0rwZIgvXCdMWMGdHV12UiYvN5t3bt3VyhNL9u0PicnB4GBgVpTjiU9+dXhyZMnEIvFEIvFqFatGgYPHlwuZQB//PEHNmzYwDEENOmxPHDgAMaOHQug9HpRbdcFloa8voQkqDKJkyyoZY9nYWGhME1JFV6/fo3IyEhERUWhevXqGDFiBIYMGSJ4LZA6qSIjI5GQkIAbN26guLi41FYq2oY0Oiy0cCltm3Q7GGkDdN++fRppB0OKKiqkkr6m4eHhOHr0KMzMzODq6oqhQ4fyFhgkfdw1QWnGWX5+vsYi6+WBKordpMyaNQv16tXDmjVr2CwfhmGwbNkyZGdn8xZ6v/zyC0JDQzFmzBi4u7uXmppIurh7/vw5xwgsrb0OKZpSXC7N2a/NNZom1iuaClaUBZJ7HcMwaN68OdLT09ltso5TgG9QikQiNGzYEJ07d1Y6Gq5JkpOT8euvv6J+/frw9vbG7NmzER8fD319fezcuVNQ34WEtm3b8pTaJQh1EUpKSmKjwrL8/vvvmDlzJue5du3a4cqVKzx9pezsbNja2gq2TqtokGZ3kSI9zzk5OXHWdvLmwPfv3+PKlStsduC///6LNm3awM7OjvcbyJZ6SM5pR0dHjnhcaZBExDVBpTe4pZVgx48fzxHcADSjBEuChYUFrl69iho1asDAwAChoaGsUqOpqSlSUlJ4rxF67vTp09i4cSNatmyJCxcucLZpqu2HPEEkgOzkBzSTOnn//n2IxeIyr4vStscSIPMoktYFahpNRLglqXsAOOl7mkrdk7ThkhxfuhUXIJwGpg7//PMPwsLC4OvrC19fX57XW51FnzKtVObPn48tW7YAKFH+lxYiHDduHEJCQtT6fKTRYRJNAgnabgcDaD+FW5ri4mKcPXsWCxYswP3793ndJoyNjdlogyyKtqlKacac9Pbp06dj586dGn1/bVMWkQhjY2OkpKTwSmqKiopgZmbG+810dHRQp04d1KhRQ7AWWjYaJVsaIotsaQhpex1SvvvuO47isiyyisuqtIkjWaOpqsmj7HqlIrW5UxVVo5N5eXkcXSFNCh8WFRUhMzOTLbf58uULgoODsWXLFt761sbGBt7e3sjJycGiRYuwY8cODBgwAJcuXYK3tzenG4EqDBs2DAMHDsTEiRM5z+/fvx9RUVGIioriPC9Zp8sa+kuXLsWpU6d442nXrp1co1rRNlVRphc9KZL7d3FxMRwcHHjOdnUNUHUM+qysLLbU7uDBg3j16hXy8vLk7i9p6aWoRbAmI+LqUOlVymWVYIH/U1nWlBIsCW5ubrCyssJ3330HfX191ti+deuWXG+ixDABgJiYGPj4+KBBgwYIDQ0VFOIhVY5NS0vD6tWr8fLlS44g0v79+wXbSAAlKa+9evVCx44dYWVlxZ784eHhPINbKHUyLi4Oa9asEUydzMjIwMuXL9l9g4OD2VoyeWq52iQgIIDnsezevTtOnDgBW1tbjRjc0oaJkJEijbQqpXRdYO/eveHt7a32WADhNDPJWDSheyBP3EYRijzf//vf/2BjY8PuK2tQa9rAlsAwDM6fPw+xWIyrV69i1KhRvNowoOQakF70BQUFleqkImmlIh0NDQ0N5Sy0pduIqAqpYGF2djbrQJEgrUkghLbbwZDOQ+pw4cIFREREICYmBmZmZvD09OTtI2nNJdTHXVPdBkiQ/q004dwoa1RR7Cblm2++EdSvqFKlCr755hve86S/Y3Z2NiIjI+U6tmQ/A2l7HVJIFZdVaRNHskYTyhCQrveWZ3Aru14hHX95Z5sJkZqaChcXFzAMw/4NlHynQvN4QUEBvL29ERISAj09PbZzzvjx4+Hj48NzgJTmbJcVHQsLC8P06dNRp04dtG7dGkuXLsWMGTNgZWUl+P19+fIFQ4cOBQCsW7eO/btHjx4aCSYEBARg8ODBCA4O5oiyvX//XrCkMyoqCkOHDsXOnTvRo0cPFBUVYdKkSfj3339x7tw53v7ff/89L0sRKDnPNZExsGTJEtSsWZPNjO3Vqxf09fWRn58vtxc9KbL3bxMTk1Lv3yTICpTJ2yZh586dSEhIwOXLl5GXl8dm+4WGhsqt69+6dSvWr1/Prh1q164NLy8vuLm58faVndskEfHdu3cTRcTVpdIb3JpSttYU06ZNQ//+/fH27VtW9AMo6eEqr1akuLgYhw4dwoYNG2BkZISgoCB2wSgEadsPSbucoUOHctrl3Lp1S1AQifTknzt3Lnbt2iWYOjlnzhxe6qSnpyeGDBnCfsY1a9ZgzJgxyMvLw7Jly4hU0DWFUPs1Tdb/k05AsnWBsbGxcusCVcHMzEzuNllFalVQpRZu2rRprOfb3t4eO3bswLFjx3Dp0iXMnTuX42mWjjAr4+FUhblz5yIhIQGOjo4YP348goKCFO5P4qQibaWiCE3cID9//oysrCz88MMPAEr6fksitvb29rxrQZV5V9vtYEjnIR0dHTRs2JD9/mSdB7LRyYsXL0IsFiMmJgbGxsZwcXFhHURCkPRxVxXZej/Jgk8owlpRWmmpCqmxqgq5ubmCRj3DMIJtqc6cOYMePXoAKIlEtW3blt0WERGBESNGcPZv2bIlkd4CaXsdUhS1xRKKKqnSJo5krpB2bkvXe0+bNk1wIQ2QrVdIxy9dGqNsT2RtI200yvYQFuop7OnpiYKCAqSmprL3yPfv38Pb2xseHh48Ubthw4axc4qk84a0g0Q2O23VqlW4du0aDA0NkZiYCAcHB4jFYrm14dLfW+3atTnbNHEf0NXVxbVr13D69GnW8d+vXz/06tVLcH8LCwucOHECAwYMwMqVKxEcHIzmzZvj6NGjgtfYtm3bWMeutEEfFxfHi56rwsmTJzm96Bs0aICzZ88q7EVPirbtpvT0dCxatAgMw7B/AyXz6KtXr3j7379/H/369cNvv/2m1Dp35cqVrB6KRLQ1NTUVHh4eePfuHS/lfPHixRWjnIqhlDutW7dm9PT0mE2bNjHHjx/n/ZOlSpUqTOPGjZlGjRoxjRo1YqpWrco+bty4MW9/CwsLzuNmzZoxhYWFcsfj4eHBhIeHM2lpaUqNv127dkTbrKysOI87dOjA/t2lSxel3lOTdO3alTl37hzv+fPnzzOOjo4aeQ/p30zye0keV6tWjbPv8uXLGX19fWb58uXMu3fvNPL+yvLmzRtm+/btah9Hci7K/pN3jjIM9zwwNDTkbGvfvj1v/4CAAKZ58+ZMgwYNmAYNGjAtWrRgAgIC1B67BJFIxDRs2JC9zhR9hh07djCTJk1ijIyMGD09PcbFxYXZtGkTEx8fz+Tn5/OOnZWVJfieRUVFzKFDh3jPt2vXjrl79y5z584dxtjYmLl79y6TkpLCPlaX2bNnM0FBQezj1q1bMxMnTmRcXV0ZNzc33v4hISHs37LXzpYtWwTfIyIigjE0NGT27dvHJCcnM8nJycy+ffsYIyMjJiIiQu3PQDoPzZw5k+nYsSMzf/58Jj4+vtTjd+vWjQkKCmLevn3LeV7RNRMdHc106dKFadCgAdOwYUPG0dGRiYqKKvW9tIGiOUjeNVmRsLS01Pp7TJw4UeE/RWOSHZ/QeKXnOGVwdXVlfv75ZyYwMJBp3Lgx8/79e4ZhGCYnJ4cxNzcnOpY8Xr58yVy9epWdp968ecMsXbqU0dXV5e2rzGeUhXSuePbsGTNr1iymbdu2zJYtW5iPHz8qPD7JekWV8Usg/e0qCm3atBF8vqioiDEwMFD4WmU+s+x3aGJionB/krWQKnz8+FHhP1lSUlKYlJQU5s8//2Tq16/PjBgxgn0uJSVF8D0+ffrE7Nq1i/H09GQ8PT2ZXbt2MZ8+fVJ77AzDX6/HxsbK3aYqz58/V/hPXfbt26fwn7q0bdtWcF31+fNnwfNd+hydNm2a2u+vKpU+wv010LVrV4hEIiQnJ/OEn4Q894WFhUTHF4lEbHspoCQq8uXLF7mCSJs2bSI6PkOYOimbPiqdtqNMWpum0bbHEiD7zVavXo06deogKCgIv//+O/s8o6VWPJmZmTh8+DDEYjGePXumEaE4VX5HEs83qYdTFUjSRUk9tDo6OvDx8ZFbSygr3vP999+z9ZTSf0seq8vly5exbds29vF3332HvXv3AgC6dOnC23/Tpk2sCKCHhwenbjA4OJgjAihh+PDhMDAwwKZNm9gsClNTUxw8eFAj7WBI56GgoCAUFxfj3Llz2LdvH+bOnYtu3bph1qxZgqrx0v1npa+Z1NRUDBo0iLe/pPWKploLqgvpfaOiwQhEtjWN5JxXFoagVAgoKQeRvv+JRCKF0eHdu3cjICAA9+/fx8mTJ9kIZUpKiqDWBymK2isK6WwkJydzsigkWRWK7k0kc4V0vffatWvZbD7JdyakyUOyXlFl/BIqe4aILDo6OqV+JmU+c0ZGBqdGNjc3l/NYVgdA2/OQqamp3HI5oTJT6ayK9u3bIyMjA3PnzmX3F2r3WLNmTa2VPxYWFuLdu3dsR5eePXsCKPmeNaXfQ5rFQIqJiQmsrKw0koUjD9lSCAA8LQ0J0nNxeZZTUYO7ArBv3z6VXnfmzBk2ZcbU1JSXSilBqN5Skr6qiTp30tTJBg0a4MaNG+wiW5LOfePGDUHhFm1jbm6OO3fu4ODBg+z32aVLFwQGBmpUWERZyqK+MycnB1FRUQgLC8Pjx4/h7OyM+/fv4+XLl1p/b3lIFkOMQHqsbF35wYMHcefOHc6k27p1a4jFYpiZmWnE4CaB1ElFWksoVEumSQoKCjg3qoMHD7J/Z2dn8/YnNTSAEkEzS0tLtQXe5KFKCreOjg569OgBY2NjhIWFYd26dTA3Nxc0uEmvmbCwsFJ7vFYEFIlnViRIjVVVUFSzKxKJeP1jSUuFBgwYwKmVZBgG+fn5sLCw4PS0l1BUVIQlS5bwjmNnZ6eSmrgsO3bswP3795Vur6iKsUQyV2hbk6eyO51UwdraGj4+PrzzyNfXF507d1b7+FOnTuU42GUflzWpqalE+0s7UpVBX19f8Hl5Bj0pHh4e+OmnnwR70Xt4eKh1bAnS5XmWlpYa7z/v6enJGvL29vaws7ODvb09K6qnLoaGhggLC+MFJsRiMdq0acPbv6I4y75ag7uiLSIUjUdIQU8aWQ9hWloahgwZgrp167ILy8jISHh5eeHIkSM8UQtF9RqaMO7mzJmD5s2bY9myZbh79y5EIhFMTEywaNEiODs78/b39fXF0KFDMWXKFLYdQ1JSEvbs2aO1xXhpCHksi4uLBS/qr4EmTZrA2toa69evZ0W6Dh8+XK5jIl0MkXg4KxqktYTe3t7w9fUFABw7dgw//fSTRsdTvXp1Tn9MY2NjAMDTp08F25qRGhpAiZGgTZVs2XkIKHFEypuH3r59i8jISBw5cgTVq1fHsGHDcPfuXbmtnUivmeLiYk5mkSxl3UEjLS0Nq1atQnp6Okc8Mzg4GKNHjy7TsagCqbGqCkLt7KQ7RMga3A8ePIC1tTUYhmH/BkoW3w8fPuQdS54xcPToUcyYMQMnT57kPN+tWze57XWGDRumtmp7zZo12Uhaq1atYGRkJNfYlkdaWhrCw8NZYUlZSOaK8tDkUTR+Eo2Eisr27dsxefJktGnThjXgkpKSYGFhIZjRMWLECPYzS4uySZBtzUfaVYZUO4MUUtG3AwcOQCQSYcyYMZznQ0NDIRKJeHNju3btkJGRAWdnZ7i4uAjqIKnD1KlT0aRJEyxevJjTi97b21sr2VLaWC9duHCB7b6SkJCAiIgIeHl5gWEY2Nvbq63TFBQUhCFDhmDHjh2crNTc3FzBrFRFwZyyvI4rfVuw0hS4NSEApe3xKIrGiUQiVq1QwsCBAzFq1CjeRHDo0CEcOHAAx48fL3WcFy9eRFhYGGJiYtTuuawKr169QmBgIDuhGBsbY/bs2RqfvJRBulXIwIED0adPHwQGBmLjxo2VplUIKcHBwQgPD8ejR4/g7OyMESNGwNXVtcxV/VXlp59+wtixYwU9nMHBwQrVjCsCpH3KFbWC0QQxMTFYtGgRfv75Z44TbO3atfDx8eEZrKr0sJZuB1IWLZ5Ko2rVqjA1NcXQoUPRqFEj3sJD1tFJes3UqFEDurq6cpXcy/pa6969O7p06YIuXbrgzz//ZAU0t2zZUi7zrqY4evQotm/fzjNW1UW6Q4SDgwO8vb1haGjI2ef58+cKj0EiHil0TWi7X66q7RX/+ecfREREICwsDDdv3oS3tzecnZ0F+xmTzBWldbdQVVhS1fHn5OQICqqWN7t27cL27dtZp067du3g5ubGa4UlzZMnT9jv19jYWDASCIDj1BFCVp3bxcWFNcIXLFgAPz8/dlvPnj1x+vRpzv6zZs1CYmIiHB0d4erqqnbfbVk6d+5MlC5tY2ODs2fP8hygnz59QpcuXQTvU1lZWYiKikJkZCTy8/MxZMgQjBw5knVeVSa0fS9+9uwZLl++jISEBJw6dQr169fH5cuXNXJsaWE8ExMTNv2+olLpDe6KtojQ9HjEYjFcXV05zxkZGeHBgweC+yvaduXKFYSFhSE6OhoZGRnYtm0bBg4cKDeioywLFy6EkZERpk2bxnl+165dePToERuZk0WbfSFJ0FRf88pIVlYWjhw5ArFYjIsXL2LWrFlwdnYWbEdXkZDO8hDycMp6sSsa0otQAOxCVJ7HVdsGN1CSfu3n58fxqnt6eirsmECCtj9Daeqtso7LlStXKvTuy4vcKHvNaMIg0iTt27fHrVu32Me6urp48eKFVuvsygpNnk+yHSIWLFig0Q4RQmRmZqJXr168z6Bqz2VlKS3SJG18AyWRJbFYjLdv32LEiBEYPnw4Bg0aRJzGKw95ZXEA5NbTkkA6/orgGJRl165dCAoKgp+fH6ysrMAwDG7evAkvLy/Mnj0bkyZN4uz//Plz1KtXj3UcnD59GjExMdDT04ObmxtPvVnagFYGRY5UeXOgRDsjPDwc165dU6idoQ7KzMEdOnSQ23fawsKCp6skzZcvX3Dw4EEsWLAAK1as0Ej3CXktWyVoogWqdBZDbGwsevfuzdlO8vsLsX79eiQkJODt27do3bo1bGxsYG1tDUtLS8GMuf8Kld7grmiLCE2PR09Pj5ci07ZtW9y9e5d34n758gWmpqZ49OgR53lvb28cOXIEBgYGcHV1xeDBg9GxY0eN3SQ7duyI69ev854vLi6GhYUFr08waV9IbWNmZsaOsaioSKlWJ18jGRkZOHz4MMLDw9Ve2JQVlc3DqSqSSJRQFArQXh9yTaIo0qWJtK6qVavCzMyMjVjL3tqkxXE0haJrpqIZ3B06dEB8fDz7vdjb23Mel3WKu6aQZ6yqwi+//ILQ0FCMGTMG7u7uajujZRFaTGdmZiIuLg6+vr68VkryrnuGYRASEoLXr19rdHylUbduXXTo0AGrVq2Ck5MTRCIR9PX1K01mFOn4K9o1DJREcKOionhOoLS0NAwdOpRTnwuU1HBHR0ejWbNmuH79Ovr06YOlS5fizp07YBiGpyFE6mRQxyn0zz//sNoZ69ev593X1EWZz2JiYoK4uDhedPrdu3fo2rUrL+uisLAQf//9N8LDw3Hv3j306dMHw4cP57QBVgdSJ5gqkGYxkGJubo4aNWqgf//+sLOzg62trdz2maogW5YgoaKXelT6Gm5SBe7KNh4hf8jo0aMxfPhwbN26lY3kvXjxAu7u7hg1ahRv/8jISDRu3BgjR46Es7Mz6tWrp9G6DUm/Xll0dHQEa8RJ+0JqG9K+5l8rjRs3xsyZM3k9oysinz9/xu+//47Hjx/D3NwcU6ZM4fSsrSwoK3wobVBXBuNaCG0LFr18+RKRkZGIiopC9erVMWLECAwZMkTujV7i5ZcgEonQqFEjODo6Kq3boOia+fnnnzmPHz16xKrMGhgYlHlfUG2LZ2qb0oxVTaDtDhFmZmacxyKRCA0bNsTatWvZukJpFF33mvjMkvRb6fFIroH58+fjm2++4ez/9u1bHDt2DNu2bcPkyZPRr18/ufd/VYiLi1O4vWvXrmodn3T8r169Uih8WB5z8adPnwQzLlq0aMHrAAOU3Csl2ZUhISGYPn06FixYAIZhYGFhwds/JydHYUmWbNecnJwcnDhxAsXFxZzXSrpGyEKqnaFtPDw80L9/f2zcuJEjtrlo0SLMnz+ft3/jxo2hp6cHFxcX9h6Snp6O9PR0APzvhxRFBrWmRG1NTEyQkZHBK9G4e/euRoTNbt++jffv3+PKlStISEhAUFAQ/v33X7Rp0wZ2dnZqrzFnzJjBliW4uLiwmioVnUof4W7VqhV0dHQEDdPyWERoejxCEW4A8Pf3x8aNG1njvnbt2vD09IS7u7ugMZ2YmAixWIyYmBgYGhoiMTERjx490kh9kr29PbZt28Zr7XPz5k3Mnj0b8fHxnOfbtm3Li8IDJRFxQ0NDPH78WO0xkSCJvAHgRN8qurfsv4yrqyuqVasGTYlSkQAAMR5JREFUR0dHnDhxAq1bt8bmzZvLe1hKIyR8eOPGDXz48EFQ+DA/P7/MDbTKjCRy4uvrC19fX8FFjJCXPzMzE4cOHUKrVq3UXkwvXrwYtWrVYlPZW7VqBX19fXz+/Bm9evUqNQW+LCkuLua13qtoyEZ+JMZq586dBY3VsoA0/VaCsuVUiYmJWm2vI1SDnpmZiQMHDiA7Oxu7d++W+9oPHz7g6NGjEIvFuH79Ovr27atwf2UYMWIE+/fp06c5GUsikUjtVFdplBl/y5YtFV6nmo7IKoO8jEJAOKJrZmaG5ORk6OjowMzMDP7+/uz3am5uzhMKbNiwIQYPHix3Dbtnzx7OcxMnTlQYwJEVZiPVziBFlXTpmJgYbNy4kZMtt3DhQkGRMkWfV+j7UYX4+Hi8fPkSjo6OaNq0KZKTk+Hr64u4uDiNaC65urpi3rx5cHBw4Dx/6dIlbNu2DYcOHVL7PSRkZWUhPj4e8fHxOHjwIF69eoW8vDy1j1tWZQmapNIb3IqoaIsIeeORKGHKIjH+FPXee//+PYCSVClluXz5MsRiMaKjo9GmTRueqAUpFy9exOjRozFlyhROPe2ePXsQGhrK6+Mrz+AubRuFIkF6oVBYWAhra+sKV2unCFLhQ+mFlDYUviU9oys7DMPg/PnzrOJw165dMWfOHLkCQUIUFxfDyspKbl2fslhZWSEhIYHNoJGkpzIMA0dHR1y8eFGt42uC8hbPVIWy1v5QpGJNmn5LWk7l6Oio1fY6iiBJp87JyUF0dLRGDdCyTOeWN/6KWMMtHSCQRp5g5apVq3Du3Dk0atQI9+7dQ1JSEnR0dPD06VOMHTuWJ2BF+pklgQllUVU7Q1m0nS6tiMuXL8Pe3l6tY3h5eeHo0aOwsrLCgwcP0Lt3b+zZswdLlizBrFmzNDLfWVtby20FJuSEIWXnzp1ISEjA5cuXkZeXB1tbW9ja2sLOzg5WVlYaLRvVdlmCJql8OZhKUNEWEaWNh7RnoaJeoQAwfvx4hdvt7e1hb2+PLVu2lJrCpQxdunRh00Yk9UDGxsaIj48XFIrTdl9IytePtH5BZUwlf/jwoWArplGjRmHlypW856X9oteuXdP4eCpLz2hFzJ07FwkJCXB0dMT48eMRFBSk0nE05aQtKiriLCw2btwIoCQKInGUlgdC4pll3bdeFcpS+0NIxVrIyUWafktaTqXt9jryKCoqEiwHe/LkCZ4+fcpGDVevXs2mDcuKdamLNtoVkY5fXppzcXExwsPDy6VlKGlpzvLly9GrVy+8fv0avXv3Zue3wsJCbNu2jbc/aQyuUaNGsLKyYp1Btra2qFevntz9he5vmoQ0XZpUbFMRI0eOLLUtWWkcP34cSUlJqFmzJjIzM9GiRQvcvn1bbv9vVcjKypK7TRPR5/v376Nfv3747bfftCI4WdHKEpTlq4lwa0uBuyKOx8vLi/ecdK9Q2Yg4adsGbZOdnY3JkycjOTmZFZq4desWzM3NsXfvXoWTNYUCVP4yAFLhQ20rfMsKaslSGQS1dHR00KBBA3ahLt3nVeicEGpBlJWVhQMHDgCAyga7BFNTU5w/f54nxpORkQEnJ6dSWyBpGm2LZ2obNzc3FBQUYOPGjTxjVSQSaUT7g1TFmjT9Vp1yKm201xFyFmRlZSEsLIwVF5NmyJAhmD9/PhslbNeuHZYsWYK8vDzExsYiMjJSrfFIo415jnT8OTk5CAwMxMuXL/HTTz+hb9++2L59O/z8/L7alqF3797l9LQXiUQKo6qfP3/GtWvXkJCQgISEBFy9ehV169aFnZ0dHBwceI4MTWhnKII0XVqTYpstWrRQO8inrNK7OgwbNgwDBw7ktZHbv38/oqKiBHtZVyS0XZagLSq9wV3RFhFlPR5leoWq0raBhO7duyusaZFn0Av1hRRqg0ahfG2sWLECSUlJgsKH5ubmPK+7thW+K1rP6LJAVqBOUhPctWtXzJw5U+32Jbt27cKuXbuwceNGjmNx0aJFmDRpEq+NorYxMDBgRd4k4pmVSWG6LLQ/SFWsSY1C0nIqbbfXkTWGpK+BgQMH8vbv1KkTJ8PGwcEBly5dAlCS/n7hwgW1xiPdQ/nu3bswNTUF8H/znLw0WGUhHX9FbBkqKUGUnavz8/Px4cMHFBUVqXX81q1bc+Z+hmGQn58PCwsL/P777xxjXIh//vkH4eHhCAgIQFpaGi/FXdvaGaTp0q9fvyYS21SEPM0lEurXr89mYAjVoWtCxyA9PR2DBw/mtVV9//49oqOjtd4GUV20XZagLSq9wV3RFhFlNR6SXqHa7uWZkpLCe+706dPYuHEjWrZsSXQT1sSERaFUBkiFD7VJRWx/U54MHz5cI9G6o0ePYv369Zze5vLEeMoCbYpnapuy0P7Iy8vDsWPHIBaLcePGDfTr1w9RUVF49eqV4P6k182YMWNgZmYmWE5169YtHDx4kPO8ttvrkGJoaIiHDx8KbtPEbyAk4iZNy5Yt1To+6fgrQ8vQf//9F/7+/jhw4ABGjx6N1atXa+V9jh49iu3bt+PkyZOc569evYqEhATEx8fj+fPnaNasGaytrWFra4tOnTopnR2lKe0MRedhmzZtFDrmlBHblFX2l8AwDG7fvq22an9Z1qBLt1U1NjZGr169kJeXV6HOb1Iq9PiZr4CrV68yCxYsYNq0acP079+fady4MZOdnf3Vjmf58uWMvr4+s3z5cubdu3el7q+vr8/8+eefzLFjxxh9fX3m+PHjzPHjx5ljx44xBgYGGhsXwzBMdHQ0Y2Njw/Tr14+Ji4sjfn3z5s01Oh4KpaKTm5vL5ObmKtzn9OnT7N8PHz7kbAsPD1d7DB06dFD7GF8TLVq0KO8haJ1Lly4xbm5ujJ6eHtOjR4/yHk6pjB49mlm7di3v+XXr1jGjRo3S+Pu9f/+eCQ0NZQYNGsTo6uoykydP5u3z7NkzzuOMjAzm8OHDTGJiouAxs7KymCFDhjAGBgbM0KFDmaFDhzL6+vqMs7Mzk5WVJfia3Nxc5tSpU8yqVauYgQMHMvb29sz48eOZoKAgtT9jbm4us3XrViYkJIQpKChg1qxZwwwYMIBxc3Nj3rx5w9u/T58+zN9//817/tSpU0yvXr3UHo8spX2fpJCO39LSUuHj8iQ9PZ2ZP38+Y2BgwPj6+pZ6D9EEQp9fJBIxVlZWTHBwMPPhwwe1jt++fXu1Xs8wDDN06FBm7969vOeDg4MZZ2dnwdcUFxczZ8+eZWbOnMlYWVkx8+fPZx49eiS477NnzxT+qyy8fPmSuXr1KpOfn88wDMO8efOGWbp0KaOrq1vOI1OOyjj+Sh/hlkXTCtwVcTw6OjqoU6cOatSowfG0MXLSS0sTM5Ft20BKcXExDh06hA0bNsDIyAiLFy9mWx2RQiPclP8CpMKH2s5SOXz4MIYNG6bWMb4mNDEPKRLjEYlEWL58uVrH1xQMwyAuLk6r6r2aQEj7IykpCRYWFlrX/sjJyUFQUBAWL17MeX7AgAFYv349TE1NkZ6eDisrK1hbW+Pp06eYPHkyFixYIHg8oXKq0tBGe52BAweidevW+PDhA27dugUHBwcMGDAAly9fxtWrV3HixAnO/ikpKRg8eDCcnJzQoUMHACW/wfnz5xETE8OmgKuKqt+nspCOX7qUB0CF0Ap5/PgxfH19ceHCBbi7u2Py5Mll0jIyMzMTvXr14t1r3r17x9ZvJyYm4tOnTzAxMWGVqY2NjTn7a1s7gzRdWlpsU5mezvfv30e7du0AlGSa1q5dm9126dIlXu04KcnJyfj1119Rv359eHt7s6119fX18b///Q82NjZqHR8AtmzZgtWrV6Nt27b49OkTZs6ciaVLl2LcuHFYvHixoNhxRaKyjv+rM7glVLRFREUbjybR19dHUVER5s+fDyMjI952WaVWddqgUShfA6TCh9Kpq7JprJpIB580aZJCHQZ1++tWROSpSzMMg0mTJqm9mBYS8crOzsaOHTuQk5ODnJwctY5PyrVr1/D06VO4uLgAAGbMmMGq1Xp4eJS60KwoqGKsKktRURHCw8Px8uVL9O3bFxYWFjh27Bh8fHzw8eNHXrqrqakpW1K1atUqPH36FHv37sXHjx9ha2vLqxd9/vw56tWrx6bwnz59GjExMdDT04ObmxvPcNJ2ex0LCwskJyeDYRg0b94c6enp7Lb27dvj1q1bvNfk5eUhNDSULZMwNjbG6NGjNSKsSPp9qoI2x18WVK1aFbq6uhg6dKhgHb+6NdBeXl68e0FmZibi4uLg6+uLIUOGKHx9Tk4O9u3bh4CAADx79oxXU65IO2PGjBka6zYglC4tBKnYprad3zY2NvD29kZOTg4WLVqEHTt2YMCAAbh06RK8vb2RmJio1vGBku/jwoULaNSoEZ49ewYjIyNcuHAB1tbWah+7LKis4698/XRkkKfALRKJ8Ntvv5V5hLuijQdQHE0TiUQYN26cWsfv2rUrRCIRkpOTkZyczDu+rMFN2gaNQvna2LBhA/u3tPBh79694e3tzdtfVtVV3jZVGT58OO+5hw8fYvPmzZWy7ZoyREREyN02YMAAtY8vrW779u1b+Pn5ISIiAtOmTYObm5vaxydl6dKlbGsyoKRdZWBgID59+oTVq1fzer9XNCTGqoGBAQwMDHD69GkEBATINVZVYcqUKXj+/DlsbW3h5uaGpk2b4saNG1i3bp1gBoj0tXHq1CnMmzcPAFC7dm1UqVKFt/+IESMQHR2N7777DtevX4eLiwuWLl2KO3fuYMaMGWxbTQnabq8jGb9IJML333/P2SY0fgCoWbMmpk6dqvGxSI8HUO77VAVVxn/mzBnWeDM1NeUZjWWJIuenJu4FZmZmvGM2bNgQa9euRZMmTXj7P3z4kK3hjo+Px9u3b2FtbY1p06YJOvHOnj2r9hiVoWfPnujZs2ep+wm1v1OEdIxSNl6pifjlly9fMHToUADAunXr2L979OihsWBUzZo12e4ZrVq1gpGRUYU3VqWprOOv9CspaXEE2Qs5MzOzrIdT4cYDQNArLB1NU9fgll0kUCiU0pEVPoyNjZW7qH7w4AGsra3BMAz7N1Byg5cnAkSCtIGZnJyMNWvW4N69e1izZo1gv/CvAUWlNJpq2fX8+XP4+voiNjYWc+bMwZ07d8otkpaVlQULCwv2sYmJCZtxpS2hJU1CaqyqQmJiIpKTk1GlShXk5eWhadOmePLkCa+1mwRjY2MsX74czZo1w/379/Hjjz8CAHJzcwUX8p8/f2bTHUNCQjB9+nQsWLAADMNwfhsJmzZtUvszKSI1NRUuLi5gGIb9GyiZV549e6bV9xaC9PvUNmlpaRgyZAjq1q3LlslFRkbCy8sLR44cYTtMlCVCQl7A//Um1tTx8/Ly8OTJEwAlYsDyhKhGjhzJtgBbuHAhDAwMFB6ftJyqoqFt57f0MaTT1QGwPdTVJT09HYsWLQJQcq2/efOGfQyonyWhbSrr+Cu9wa3oBC9rpd/S3rM8xgOQR9NICQwMVLi9ovbEo1DKi19++QWhoaEYM2YMrly5goYNGyrc/+7du1qfPy5duoQ1a9YgMzMTS5YsKTcl7fLi0aNHEIvFCAsLQ7Vq1dRO0x8/fjwuXboEd3d3rF27lk2V/PTpE4Cy720uSR+XIB3hf/36dZmORRVIjVVVqFGjBhtJrVmzJgwMDOQa20BJtDEgIAD379/HyZMn2f7gKSkpgmUjxcXFKC4uho6ODmJjY+Hv7w+g/NYG0dHR7N9z587lbJN9XBYo+j6lF9RlxezZs+Hp6clzOh46dAizZs0q96yQzMxMHD58GGKxGM+ePRNs5UZKQUEBvL29ERISAj09PTAMg7S0NIwfPx4+Pj68lG9JCrXEQL9z545CA106ABQSEsIJ+JTXdUCCtp1UycnJaNKkCVtiKckqYBhGY2VIsgap9OPK8BtU1vFXeoM7JycHJ06cQHFxMXJycti6PIZhkJub+58fjwSSaBopilLEK/LJT6GUF6tXr0adOnUQFBSE33//nX1eXt1Yp06d5F5LNWrUQOvWrfHrr7+qnOro6OiIFy9eYMGCBWytm3SU18TERKXjVnSePXuGsLAwiMViVK1aFampqUhMTETr1q3VPnZcXBxEIhE2b96MLVu2APi/lMPy6G3eoUMHBAcH8yJkISEhrAhZRaYsjFXZ7BHpzBKhPtBFRUW8Fl8AYGdnh6ZNm/Ked3V1Re/evdGoUSPo6Oiw1+vTp09Rt25djX0OZSHVlJEumdMGtWvXFvw+q1WrxitXUwXS8T98+FAww2fUqFFYuXKl2uNRhZycHERFRSEsLAyPHz+Gs7Mz7t+/j5cvX2rk+J6enigoKEBqairr8Hj//j28vb3h4eHB06YgNdClA0CxsbGcx5UBbTupCgsL1T5GaWg7S0LbVNbxV3rRNG0rcJNS0cYDcKNp7u7upUbTNIlYLIarq2uZvR+F8l+jqKgId+7cwdixY1UWFerWrZtC0bQzZ86oM8QKibW1NfLz8zFq1Ci4uLhAX18frVu3RmpqankPTSukp6fD2dkZ3377LUehOScnBzExMdDV1S3fAZbCqlWrcO7cOTRq1Aj37t1DUlISdHR08PTpU4wdOxaXL19W+z1I+0BLiyQ5OTlxeujKE1CKj4/H69ev0bt3b9agefjwIT58+MCqKpcVsgKmIpEIjRo1gqOjI9asWcNbK2hCFEpZkpOTERYWhsjISDRr1gxDhgyBu7u7WsckHX/btm1x9+5dnjjZly9fYGpqqpHe76TUqFED1tbWWL9+PVsjrcl5S14f6+LiYhgaGvL6WLu5uaGgoAAbN27kGegikUhQPFJCWZ5PFGGEsiQ2b95c3sNSmso0/kpvcFNKh7SNmCahbb4olLJh3759mDhxYnkPo9IwadIknDt3Dk5OTnBxcUGfPn1gaGioschzaXXg5ZU1EBsby1Fo7tmzZ6XJRCprY/Xz589s7bBQCYC2uweUB5IWTefOncPhw4c52wwMDLB161a5r5UVSCXl3r17EIvFCA8PR+PGjTFixAhs2LChVEeIspCOf8WKFUhKSsLWrVvZeu0XL17A3d0d5ubmClv/aYvg4GCEh4fj0aNHcHZ2xogRI+Dq6qqxeUuewS1vG6mBLk1lNLjLom2XthHKkggLC9NYloS2qazjr/QGt7YVuEmpaOMpb1q0aIG0tLTyHgaFQlGArA6DJNJla2uLFi1alNOotE9BQQFOnjwJsViM8+fPIzs7GwcPHkTv3r3VVr1WlN7/tWYNVHb8/f2Rl5fH9ttu0aIFqlWrhsLCQnh4eMDDw4Ozv7ZbBJUnQuNv2LAhBg8eLKjGLBKJsGfPHrXeU0dHBw4ODtizZw/atm0LoKTtqKaMSVXG7+/vj40bNyIvLw8Mw6B27drw9PSEu7t7uTqqsrKycOTIEYjFYly8eBGzZs2Cs7MzHB0d1TrumDFjYGZmxkvt9/X1xa1bt3Dw4EHO86QGuiSrQlKjXL9+fQBlEwDSBGXRtkvbaDtLQttU1vFXeoObtJ/tf2085Q2NcFMoFZ9ff/2V91xmZiZOnTqF5cuXY9SoUeUwqrIlPz8ff/75J8RiMc6ePYs3b96U95AoZUzHjh1x/vx5NnouiVIXFhaie/fuuHDhAmf/77//HhMmTADDMNi/fz9bW8gwDEJCQiqFGJ0QeXl5sLOz4/Ud17YT4fz58wgPD8eJEyfQsWNHuLi4wMvLS2OK6eqM//379wBQLrX2pZGRkcGm1arbdis7OxuTJ09GcnIyq+2QlJQECwsL7N27F/Xq1ePsT2qgV3akM1eMjIzw4MEDdluHDh1410xFRNtZEtqmso6/0hvc0kgrcDs4OMDb2xuGhoZ0PFpGtg5MgsSD+V9zMlAoXwvZ2dno0aNHpY7UySMjIwMZGRm81O6UlBTUrVtX7ZY/cXFxCrd37dpVreNTNI9sGri0irKQsRYcHKzwePLEfSoKQh1GsrKyEB0djUmTJvE6jJRVmnxxcTHOnj0LsViMmJgYdOnSBc7OzmpnCJKOv6K2sCoqKkJmZiYaN24MoGStGRwcjM2bN2uspeGTJ0/YYxkbG6NNmzaC+wkZ6Ldu3YK5ubmggV7Z+ZqyWrSVJVFWVLbxfxUGt6wC94IFCzSmwP01jIdCoVBUpbLWopaGq6sr5s2bBwcHB87zly5dwrZt23Do0CG1jj9ixAj279OnT6Nnz57sY5FIpFW1Z4pqGBoaIikpiVev/fHjR1haWvJ63icmJsLKyoptJVbZkM1sEYlEaNiwIRwdHQVbrT1//pwjHPfu3TvExcVBT08PnTp1Uns8Qt9nYWEhTp06hfDwcLVFZ0nHXxEzFsPCwjB9+nTUqVMHrVu3xtKlSzFjxgxYWVlhxYoV6Nixo1rHf/78OerVq4fvvvsOQMncFRMTAz09Pbi5uckttREy0L9G0dyqVauiQYMGginxOTk5+PLlSzmPUDUkWRLh4eGVstypUoyfqeQsX76c0dfXZ5YvX868e/euvIdT4cZDoVAoqnLw4EGmX79+5T0MrdC5c2e528zMzDT6Xh06dNDo8SjaYc2aNcxPP/3EpKWlsc+lpaUxgwcPZlatWsXbv0uXLkzDhg0ZR0dHxtvbm4mOjmbevn1blkPWCm/evGG2b9/Oe75///7MnTt3GIZhmJcvXzJNmjRhfvrpJ8bExITZuHGj2u+r7e9TnfHn5+czgYGBjJGRETN58mTmwYMHGhsXCSYmJux7X716lalWrRpz5MgRjR2/c+fOTHp6OsMwDHPt2jWmQYMGzMaNG5mJEycyEyZMIDpWixYtNDYuCqWyU+kj3OWpwF0ZxkOhUCilIS1kI6F69eqws7PDli1bvsoMHUViP23atFGorktKZUs1/C8TEBCA9evX4/PnzwCAmjVrwsvLC25uboKlU4WFhUhKSkJCQgISEhJw9epVMAwDe3v7UlPOKxLKtNcxNTVFSkoKgJI2bU+fPsXevXvx8eNH2NraqtyWUBptfp+qjL+iZSzKziXSn0kTWFhYsD3P58+fj5o1a8LHxwcMw8DCwoLoN6aiuRTK/1G1vAegLpKWHRWFijYeCoVCKY2MjIzyHkKZY2FhIdhKbf/+/TA3Ny+fQVHKnXnz5mHevHlKi2RVrVoVnTp1QqNGjdCgQQM0aNAAp06dKpcezaQItde5f/++3PY6Vav+35Lx1KlTmDdvHgCgdu3aGkur1+b3STr+X375BaGhoRgzZgyuXLnC60teHmRkZHBq73NzczmPZevuSSkuLkZxcTF0dHQQGxsLf39/AFBJkb2ytBukUMqCSh/hplAoFIr65OfnIzQ0lK3DMzExwejRo/HNN9+U88i0Q3p6OgYPHoy6deuyPZxv3LiB9+/fIzo6Wu0oVufOndmsgbt378LU1BTA/2U7Xb16Ve3PQClf1q9fj4SEBLx9+xatW7eGjY0NrK2tYWlpiWrVqpX38EqFtL3OyJEj0bZtWzRr1gwrVqzA06dPUadOHeTm5qJLly5sZFRVtP19ko6/ImYsCnWUkGbFihVqHX/VqlU4d+4cGjVqhHv37iEpKQk6Ojp4+vQpxo4di8uXL3P2p6K5FIpyUIObQqFQ/uPcvn0bzs7O6Nq1KywtLQGUGJ8XLlxAdHT0Vx3xPX36NEfsp1evXho57vPnzxVulxZvolROzM3NUaNGDfTv3x92dnawtbVlRZQqA6TtdT5+/IiAgAC8fv0aEydOZOeK+Ph4PH78WG0VcW1/n4rG/+TJE4wdO1Zj71WZiY+Px+vXr9G7d2+2Rd7Dhw/x4cMH1jlJoVDIoAY3hUKh/MdxcnLCypUr0b17d87z586dwy+//FJqiytK6Wha0ZlSMXj//j2uXLnC1hv/+++/aNOmDezs7DBz5szyHp5SKNteJzc3F99++63gMVJTU9G6dWu1x1Ie3+e1a9cQHh6O9evXa+X4muTatWt4+vQpXFxcAAAzZsxAVlYWAMDDw4PNVKBQKBULanBTKBTKfxxjY2Pcu3ePeBtFPgMGDMD69ethamqK9PR0WFlZwdraGk+fPsXkyZOxYMGC8h4iRUliY2OxceNG/PXXX3L3ycrKQnx8POLj43Hw4EG8evUKeXl5ZThKzaCovY60YJeTkxPOnz8vuE0TaPv7TE5ORlhYGCIjI9GsWTMMGTIE7u7uGju+tujTpw82btzItm0zNTVFYGAgPn36hG3btuH48ePlPEIKhSKETnkPgEKhUCjlC8MwyM3N5T2fk5NDhSBV5NmzZ2zd9p49e9C/f3/88ccfuHr1Kvbt21e+g6MIcubMGRgaGqJ27doYNWoUbt68iY4dO2LhwoWYNm0ab/+dO3di8uTJaNeuHTp06IDg4GA0aNAAoaGhyMnJKYdPoD6NGzfGzJkzBXvZSsdnZOcLTcRutP193rt3DytXroSJiQnc3NzQrFkz5Ofn49y5c5XC2AZKHBHSPdJNTEzg5OSEfv36ITs7u/wGRqFQFFLpVcopFAqFoh5ubm7o06cP1q9fz9Y13rx5E4sXL2aVfClklIWiM0WzeHp6IigoCF26dMGxY8fg4OAAHx8fucbY/fv30a9fP/z2229fZes8WaTFsWSFsjShSK3t79PU1BQODg6IiYlB27ZtAQCbNm3S+PtoE0n6uISIiAj279evX5f1cCgUipJQg5tCoVD+48yZMwfNmzfHsmXLWAExU1NTLFq0CM7OzuU7uEqKsbExli9fjmbNmuH+/fv48ccfAZREBmnWQMWlZ8+eAIBhw4Zh6dKlCiOflc1YU5f09HQsWrQIDMOwfwMl0e1Xr16pfXxtf59nz55FeHg4+vbti44dO8LFxaXSXYuSyP+ECRM4z4eEhKB9+/blNCoKhVIatIabQqFQKBQNQxWRKx8GBgbYunUr+3jevHkICAhgH/fv3788hlVhCA4OVrhd1gisqBQXF+Ps2bMQi8WIiYlBly5d4OzsrLbKelmQnp4OZ2dnfPvtt+jQoQMAICkpCTk5OYiJiYGurm75DpBCoQhCDW4KhUL5j/Pbb78p3P7LL7+U0Ui+fiqTIvJ/jUmTJsndJhKJsGfPnjIcTcUjMTERVlZWX1VJRGFhIU6dOoWIiIhK9fvGxsayYpbGxsbo2bOnRtL6KRSKdqAGN4VCofzHqVq1KszMzDB06FA0atSIJ4A0Z86cchrZ10FlVUSmUKRxdHTEvXv3YGJiAnt7e9jZ2cHe3h6NGzcu76EpxYEDB9jMkvPnz8PJyYnd5u/vT69JCoWiNajBTaFQKP9xXr9+jcjISERFRaF69eoYMWIEhgwZgvr165f30Cot9+7dg1gsRnh4OBo3bowRI0Zgw4YNeP78eXkPjSKH+fPnY8uWLQAAPz8/Tuu2cePGISQkpJxGVnEoLCxEUlISEhIS2F7ZDMPA3t6+1JTz8ka6dZlsGzNNtzWjUCgUaWhbMAqFQvmP07RpU8ydOxenT5/Gnj17kJOTA2Nj4wq/gK7ImJqa4vTp04iJicH58+cxd+7cryoV92skLi6O/Ts0NJSz7c6dO2U9nApJ1apV0alTJ/z000/o378/fvzxR1StWhWPHj0q76GVinR8STbWRGNPFApFm1CVcgqFQqGAYRicP38eYrEYV69exahRo+Dg4FDew6q0fA2KyJT/g9bHAuvXr0dCQgLevn2L1q1bw8bGBmPHjoWfnx+qVatW3sMrFW23NaNQKBR5UIObQqFQ/uPMnTsXCQkJcHR0xPjx4xEUFFTeQ6r0ODk5wcnJiaOInJeXh2HDhlUaReT/Gnl5ebh37x6Ki4vx+fNn3Lt3DwzDgGEYfP78ubyHV+6EhISgRo0a6N+/P+zs7GBra1upyk6Sk5PRpEkTMAyD7OxsNGnSBECJszEnJ6ecR0ehUL5maA03hUKh/MfR0dFBgwYN2CiP5H+GYSASifD27dvyHF6lREjRWaKIHB4ejr1795bj6ChCdO/eXeH2s2fPltFIKi7v37/HlStX2Prtf//9F23atIGdnR1mzpxZ3sOjUCiUCgk1uCkUCoVC0TCVXdH5v8iZM2fQo0eP8h5GpSArKwvx8fGIj4/HwYMH8erVK+Tl5ZX3sCgUCqVCQg1uCoVCoVC0QGVWdP4vQpWqFbNz504kJCTg8uXLyMvLg62tLWxtbWFnZwcrKytUr169vIdIoVAoFRJaw02hUCgUihaQKDo3atQIDRo0QIMGDXDq1KlKoehMochy//599OvXD7/99huaN29e3sOhUCiUSgONcFMoFAqFomGEFJ2tra1haWlZKRSd/4vUrl0bpqamvOclWgZXr14th1FRKBQKpbJDDW4KhUKhUDSMubl5pVZ0/i9iamqKP//8U+72li1bluFoKBQKhfK1QA1uCoVCoVC0AFV0rlxYWlri5s2bgtskUW4KhUKhUEihBjeFQqFQKFqEKjpXDpYsWQIfHx/OcxcvXkRYWBhiYmKQlpZWTiOjUCgUSmWGGtwUCoVCoWgYquhcebly5QrCwsIQHR2NjIwMbNu2DQMHDkTDhg3Le2gUCoVCqYRQg5tCoVAoFA3j6ekJOzs72NnZUUXnSoK3tzeOHDkCAwMDuLq6YvDgwejYsSNSU1PLe2gUCoVCqcRQg5tCoVAoFMp/HgMDAzRu3BgzZ86Es7Mz6tWrB319fTx9+rS8h0ahUCiUSoxOeQ+AQqFQKBQKpbx58uQJtm7dijt37qBz584YMGAAPnz4gJycnPIeGoVCoVAqMTTCTaFQKBQKhSLD5cuXIRaLER0djTZt2uD06dPlPSQKhUKhVEKowU2hUCgUCoUiB4ZhEBcXBycnp/IeCoVCoVAqITSlnEKhUCgUyn8eFxcX9u8FCxawf4tEIvz222/lMSQKhUKhfAVQg5tCoVAoFMp/nkePHrF/nz17lrMtMzOzrIdDoVAolK8EanBTKBQKhUL5zyMSiVTaRqFQKBSKIqqW9wAoFAqFQqFQypucnBycOHECxcXFyMnJwZ9//gmgpIY7Nze3nEdHoVAolMoKFU2jUCgUCoXyn2fSpEkKt+/du7eMRkKhUCiUrwlqcFMoFAqFQqFQKBQKhaIFaA03hUKhUCgUCoCioiJkZGSwj798+YL//e9/MDU1LcdRUSgUCqUyQw1uCoVCoVAo/3nCwsJQv359tG/fHg4ODjh+/Dj09fXxxx9/YP/+/eU9PAqFQqFUUmhKOYVCoVAolP88pqamiIqKgqGhIRITE+Hg4ACxWIwhQ4aU99AoFAqFUomhBjeFQqFQKJT/PFZWVrhx4wb72NTUFCkpKeU4IgqFQqF8DdC2YBQKhUKhUP7zZGRkIDAwkH2cm5vLeTx79uzyGBaFQqFQKjnU4KZQKBQKhfKfZ+rUqRzBNNnHFAqFQqGoAk0pp1AoFAqFQqFQKBQKRQvQCDeFQqFQKJT/PNeuXcPTp0/h4uICAJgxYwaysrIAAB4eHrCzsyvP4VEoFAqlkkLbglEoFAqFQvnPs3TpUrRr1459fPHiRcyZMweTJk3C6tWry3FkFAqFQqnMUIObQqFQKBTKf56srCxYWFiwj01MTODk5IR+/fohOzu7/AZGoVAolEoNNbgpFAqFQqH855Gkj0uIiIhg/379+nVZD4dCoVAoXwnU4KZQKBQKhfKfp0OHDggODuY9HxISgvbt25fDiCgUCoXyNUBVyikUCoVCofznSU9Ph7OzM7799lt06NABAJCUlIScnBzExMRAV1e3fAdIoVAolEoJNbgpFAqFQqFQ/j+xsbG4d+8eAMDY2Bg9e/aESCQq51FRKBQKpbJCDW4KhUKhUCgUCoVCoVC0AK3hplAoFAqFQqFQKBQKRQtQg5tCoVAoFAqFQqFQKBQtQA1uCoVCoVAoFAqFQqFQtAA1uCkUCoVCoVAoFAqFQtEC1OCmUCgUCqWMadWqFbZs2VLew9AY586dg0gkQnZ2dnkPhUKhUCiUCgU1uCkUCoVC0SBpaWmYPHkymjVrhurVq6Nly5Zwd3fHv//+W95D0wjdunXD/PnzOc/Z29vjn3/+wXfffVc+g6JQKBQKpYJCDW4KhUKhUDTE06dP0alTJzx69AiHDh3C48eP8fvvv+P06dOws7NDZmZmuYyrqKgIxcXFWjt+9erV0bRpU9qvmkKhUCgUGajBTaFQKBSKhpgzZw6qV6+Ov//+G05OTtDT00O/fv0QGxuL9PR0LFu2jN33/fv3GDVqFGrXrg1dXV1s376d3cYwDFauXAk9PT3UqFEDzZo1w7x589jt+fn5WLhwIXR1dVG7dm3Y2Njg3Llz7PZ9+/ahXr16OHr0KExMTFCjRg3s2rUL33zzDS/t293dHT169AAA/Pvvvxg1ahR0dXVRq1YtmJub49ChQ+y+EydOxPnz5+Hv7w+RSASRSIRnz54JppQfPnwYpqamqFGjBlq1agU/Pz/O+7Zq1Qpr167F5MmTUbduXejp6WHnzp3s9i9fvmDu3Ln44Ycf8M0336Bly5bw8fFR6XehUCgUCqW8oAY3hUKhUCgaIDMzEydPnsTs2bNRs2ZNzramTZtizJgxEIvFYBgGALBhwwa0b98eN2/exOLFi+Hu7o5Tp04BKDFWN2/ejB07duDRo0eIjo6Gubk5e7y5c+ciPj4eYWFhSE5OxogRI/Djjz/i0aNH7D6fPn2Cr68vdu3ahZSUFIwZMwb16tXD4cOH2X2KioogFosxZswYAMDnz5/RsWNHHD9+HHfu3MH06dMxbtw4XL16FQDg7+8POzs7TJs2Df/88w/++ecftGjRgvddXL9+HS4uLhg5ciRu376NlStXYvny5di3bx9nPz8/P3Tq1Ak3b97E7NmzMWvWLDx48AAAEBAQgKNHjyI8PBwPHjxAaGgoWrVqpeKvQ6FQKBRK+VC1vAdAoVAoFMrXwKNHj8AwDIyNjQW3GxsbIysrCxkZGQAABwcHLF68GABgaGiIS5cuYfPmzejduzdevHiBpk2bolevXqhWrRr09PRgbW0NAHjx4gX27t2LFy9eoFmzZgCAhQsX4q+//sLevXuxdu1aAEBBQQECAwPRvn17dgwjR47EwYMHMWXKFADA6dOnkZ2djWHDhgEAdHV1sXDhQnZ/Nzc3nDx5EuHh4bC2tsZ3332H6tWro1atWmjatKnc72LTpk3o2bMnli9fzn6+u3fvYsOGDZg4cSK7X//+/TF79mwAgLe3NzZv3oyzZ8/CyMgIL168QNu2bdGlSxeIRCK0bNlSyV+CQqFQKJSKA41wUygUCoWiQSQR7NKws7PjPb537x4AYMSIEcjLy4O+vj6mTZuGqKgoFBYWAgBu376NoqIiGBoaok6dOuy/8+fP48mTJ+zxqlevDgsLC857jBkzBufOncOrV68AAKGhoRgwYADq1asHoCTivWrVKpibm6NBgwaoU6cOTp48iRcvXhB9B/fu3YODgwPnOQcHBzx69AhFRUXsc9LjE4lEaNq0Kd6+fQugJH09KSkJRkZGmDdvHv7++2+iMVAoFAqFUhGgBjeFQqFQKBqgTZs2EIlErNEsy71791C/fn00bty41GO1aNECDx48QGBgIGrWrInZs2eja9euKCgowIcPH1ClShVcv34dSUlJ7L979+7B39+fPUbNmjV5ImadO3eGgYEBwsLCkJeXh6ioKDadHChJc/f394e3tzfOnj2LpKQk9O3bF1++fFHxW1FMtWrVOI9FIhEr7mZlZYXU1FSsWrUKeXl5cHFxwfDhw7UyDgqFQqFQtAVNKadQKBQKRQM0bNgQvXv3RmBgIDw8PDh13K9fv0ZoaCjGjx/PGsEJCQmc1yckJHDS0WvWrImBAwdi4MCBmDNnDtq1a4fbt2/D0tISRUVFePv2LRwdHYnHOWbMGISGhqJ58+bQ0dHBgAED2G2XLl3C4MGDMXbsWABAcXExHj58CBMTE3af6tWrc6LUQhgbG+PSpUuc5y5dugRDQ8P/194dg0Ifx3Ecfz9ukIFE6kohHCUpFxYLg854w+WGqxsZDWeUAZe64aYzSVKKXFlECotCuAxSdANXJiW76XmGp9TVUwzPv6en3q/19/v/+o7/z//3+33/hEKhb9fa0NBAMpkkmUySSCSYnJzk/f2dpqamb68hSdK/5A63JEl/SaFQ4OPjg1gsxtnZGS8vLxwdHTExMUFrayvZbPZz7vn5OblcjnK5zOrqKsVikdnZWeB3l/H19XXu7+95enpia2uLuro62tvb6enpIZVKkU6n2dvb4/n5mevra1ZWVjg4OPiyxlQqxe3tLdlslkQiQW1t7edYJBLh+PiYi4sLHh4emJmZ4fX1ter5jo4Orq6uqFQqvL29/fF3Y5lMhtPTU5aWliiXy2xublIoFKruh38ln8+zvb3N4+Mj5XKZYrFIOBz+PP4uSdL/wMAtSdJfEolEKJVKdHZ2MjU1RVdXF9PT04yPj3N5eVm1M5vJZCiVSgwODrK8vEw+nycWiwHQ2NjI2toao6OjDAwMcHJywv7+Ps3NzQBsbGyQTqfJZDL09vYSj8e5ubmhra3tyxq7u7sZGRnh7u6u6jg5wPz8PNFolFgsxtjYGOFwmHg8XjVnbm6OUChEX18fLS0tf7zfHY1G2d3dZWdnh/7+fhYWFlhcXKxqmPaV+vp6crkcQ0NDDA8PU6lUODw8pKbGVxdJ0v/jx8/vdneRJEmSJEnf5mdiSZIkSZICYOCWJEmSJCkABm5JkiRJkgJg4JYkSZIkKQAGbkmSJEmSAmDgliRJkiQpAAZuSZIkSZICYOCWJEmSJCkABm5JkiRJkgJg4JYkSZIkKQAGbkmSJEmSAvALugMA27azEAsAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster Means \n",
      "          INCPERCAP  Und20   Ov65  Minrty  Unemprt  Noveh  Lt_high  Rentocc  \\\n",
      "cluster                                                                      \n",
      "0         19837.71  28.62  13.65   96.50    18.62  19.02    16.47    54.96   \n",
      "1         35389.38  22.82  15.51   56.44     6.54   8.46    11.63    36.30   \n",
      "2         19449.67  17.24  25.93   93.97    17.32  23.73    24.67    51.33   \n",
      "3         72820.90  16.13   9.23   35.95     3.33  16.38     4.45    51.17   \n",
      "4         19511.07  29.66  10.55   88.80    10.52   7.20    30.73    43.41   \n",
      "\n",
      "         Rntburd  Noeng  \n",
      "cluster                  \n",
      "0          35.69   8.86  \n",
      "1          20.52  36.37  \n",
      "2          29.50  27.09  \n",
      "3          19.69  23.27  \n",
      "4          24.97  72.51  \n",
      "Cluster Medians \n",
      "          INCPERCAP  Und20   Ov65  Minrty  Unemprt  Noveh  Lt_high  Rentocc  \\\n",
      "cluster                                                                      \n",
      "0          19493.0  26.77  14.36   97.45    17.07  20.12    15.69    53.08   \n",
      "1          31866.0  22.95  15.71   57.22     5.39   6.05    10.82    31.36   \n",
      "2          19972.0  18.54  26.44   96.37    20.14  19.92    21.40    56.20   \n",
      "3          73295.0  15.91   8.75   35.95     2.89  15.92     4.24    54.05   \n",
      "4          19699.0  30.39  10.31   87.36    10.42   6.16    29.23    45.87   \n",
      "\n",
      "         Rntburd  Noeng  \n",
      "cluster                  \n",
      "0          34.59   6.04  \n",
      "1          21.07  37.18  \n",
      "2          29.95   7.38  \n",
      "3          19.38  23.52  \n",
      "4          24.37  76.95  \n",
      "\n",
      "Total Sum of Squares (TSS): 770.0\n",
      "Within-cluster Sum of Squares (WSS) for each cluster: [ 86.209 149.571  14.489  29.811  27.436]\n",
      "Total Within-cluster Sum of Squares (WSS): 307.515\n",
      "Between-cluster Sum of Squares (BSS): 462.485\n",
      "Ratio of BSS to TSS: 0.601\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---------------------------------\n",
      "\n",
      "Clusters average linkage \n",
      "    Labels  Cardinality\n",
      "0       0           18\n",
      "1       1           30\n",
      "2       2           27\n",
      "3       3            1\n",
      "4       4            1\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster Means \n",
      "          INCPERCAP  Und20   Ov65  Minrty  Unemprt  Noveh  Lt_high  Rentocc  \\\n",
      "cluster                                                                      \n",
      "0         60754.28  18.41  11.65   36.84     3.74  14.52     5.42    45.22   \n",
      "1         25780.70  26.63  12.71   70.96     8.09   6.53    22.38    39.64   \n",
      "2         22292.00  25.85  16.07   95.23    17.21  17.52    15.17    49.59   \n",
      "3         21858.00  18.54  24.82   86.05     8.21  19.92    37.18    61.19   \n",
      "4         11857.00  44.28   4.80   98.79    30.42  30.33    15.69    76.92   \n",
      "\n",
      "         Rntburd  Noeng  \n",
      "cluster                  \n",
      "0          19.30  23.58  \n",
      "1          22.54  61.68  \n",
      "2          33.26   8.24  \n",
      "3          27.29  69.47  \n",
      "4          30.71   3.09  \n",
      "Cluster Medians \n",
      "          INCPERCAP  Und20   Ov65  Minrty  Unemprt  Noveh  Lt_high  Rentocc  \\\n",
      "cluster                                                                      \n",
      "0          55224.5  18.07  10.34   37.36     3.73  15.92     4.63    54.05   \n",
      "1          26443.5  26.32  11.92   73.81     7.19   6.04    19.62    42.87   \n",
      "2          20439.0  25.46  15.64   97.45    16.17  18.84    14.41    50.28   \n",
      "3          21858.0  18.54  24.82   86.05     8.21  19.92    37.18    61.19   \n",
      "4          11857.0  44.28   4.80   98.79    30.42  30.33    15.69    76.92   \n",
      "\n",
      "         Rntburd  Noeng  \n",
      "cluster                  \n",
      "0          19.38  24.43  \n",
      "1          21.91  58.43  \n",
      "2          30.28   5.11  \n",
      "3          27.29  69.47  \n",
      "4          30.71   3.09  \n",
      "\n",
      "Total Sum of Squares (TSS): 770.0\n",
      "Within-cluster Sum of Squares (WSS) for each cluster: [103.805 124.272 139.236   0.      0.   ]\n",
      "Total Within-cluster Sum of Squares (WSS): 367.312\n",
      "Between-cluster Sum of Squares (BSS): 402.688\n",
      "Ratio of BSS to TSS: 0.523\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "clustmethods = ['single','complete','average']\n",
    "for cl in clustmethods:\n",
    "    clust = AgglomerativeClustering(n_clusters=n_clusters, linkage=cl, compute_distances=True)\n",
    "    clust.fit(X)\n",
    "    cluster_labels = clust.labels_\n",
    "    print(\"---------------------------------\\n\")\n",
    "    print(\"Clusters\",cl,\"linkage \\n\",cluster_stats(cluster_labels))\n",
    "    plot_dendrogram(X,n_clusters=n_clusters,package=\"scikit\",\n",
    "                    method=cl,labels=dfs['community'].values)\n",
    "    c_means,c_medians = cluster_center(data_cluster,cluster_labels)\n",
    "    print(\"Cluster Means \\n\",np.round(c_means,2))\n",
    "    print(\"Cluster Medians \\n\",np.round(c_medians,2))\n",
    "    clusfit = cluster_fit(data=data_cluster,clustlabels=cluster_labels,\n",
    "                 n_clusters=n_clusters)\n",
    "    cluster_map(dfs, cluster_labels,title=\"Cluster Map\")\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0cf644af",
   "metadata": {},
   "source": [
    "The results highlight the superiority of Ward's method, with only Complete Linkage coming close with a BSS/TSS ratio of 0.60 (compared to 0.64 for Ward's method). Single linkage typically results in one or two very large clusters and several singletons. Average linkage is somewhere in-between."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "py312",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}