predictive_maintenance_starting_kit.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Context and Objectives\n",
    "\n",
    "The advancement of industrial Internet of Things (IoT) and industrial Big Data Analytics has spurred huge promise of economic values through data-driven predictive modeling in a variety of industries. Fault detection and prognostics are common problems in industrial plant monitoring and are at the core of systems health management.  \n",
    "One of the most important tasks in prognostics is Remaining Useful Life (RUL) prediction, in units of time (e.g., hours or cycles). The objective of RUL prediction is to estimate the remaining working time of a system before its health condition deteriorates below a threshold indicating a faulty condition. \n",
    "\n",
    "In the age of Internet of Things and Industrial 4.0, the prognostic and health management (PHM) systems are used to collect massive real-time data from the mechanical equipment, through the use of sensors that capture the asset behaviour over time. This technological advent creates a paradigm shift that opens up significant business opportunities. The direct costs and reputation loss caused by poor asset reliability can significantly impact organizational performance. The ability to predict an asset's reliability is therefore a core capability. \n",
    "\n",
    "Reliably estimating the RUL of an asset is an opportunity that decision makers need to seize in order to save costs. RUL predictions help *avoid unscheduled maintenance*, *increase equipment usage* as well as *improve operational safety*. The US Department of Energy found that predictive maintenance can **cut on-going maintenance costs by up to 30%, eliminate 75% of breakdowns, and reduce energy consumption by up to 20%**. In addition, a report by Deloitte University Press, <a href=\" https://www2.deloitte.com/insights/us/en/focus/industry-4-0/manufacturing-ecosystems-exploring-world-connected-enterprises.html\">Industry 4.0 and manufacturing ecosystems</a>, provides examples in which, for companies like Schneider Electric and Caterpillar, predictive maintenance and understanding root cause of failures **can offer millions of dollars in potential savings along with far fewer days of equipment downtime**.\n",
    "RUL estimates provide decision makers with information that allows them to change operational characteristics (such as load) which in turn may prolong the life of the component. It also allows planners to account for upcoming maintenance and set in motion a logistics process that supports a smooth transition from faulty equipment to fully functional. Aircraft engines, medical equipment, power plants, etc. are some of the common examples of these types of equipment. \n",
    "\n",
    "In this challenge, we will be using aircraft engines Run-to-Failure simulated data, from the <a href=\"https://ti.arc.nasa.gov/tech/dash/groups/pcoe/prognostic-data-repository/\">Prognostics Data Repository</a>.\n",
    "The Dataset consists of a multivariate sensory data collected from the engines operating from normal to failure. The engine starts with different degrees of initial wear and manufacturing variation.  This wear and variation is considered normal, i.e., it is not considered a fault condition. \n",
    "There are three operational settings that have a substantial effect on engine performance. These settings are also included in the data. In additon, the data is contaminated with sensor noise.\n",
    "The engine is operating normally at the start of the time serie, and develops a fault at some point during the serie. In the training set, the fault grows in magnitude until system failure. In the test set, the time series end some time prior to system failure. The RUL estimates are in units of time (cycles for engines)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Presenting the data\n",
    "\n",
    "The dataset is constructed of 26 dimensions/columns, wherein the first column is the unit number for different engines, the second column is the time index (cycle), the third through fifth columns are the settings of operational conditions, and the other 21 columns are simulated sensory data. \n",
    "The train data covers the Run-to-Failure process of 100 testing engines and consists of 20,631 data points. The test data contains the data collected in the running process with no failures, which is used to predict when the failure will occur—in other words, to estimate the RUL. The operational conditions of train and test are the same but have different initial states, which are caused by the variant initial wear and manufacture bias.\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evaluation metric\n",
    "The objective of the challenge is to predict the number of remaining operational cycles before failure in the test set, i.e., \n",
    "the number of operational cycles after the last cycle that the engine will continue to operate.\n",
    "\n",
    "For results evaluation, estimated RULs are compared with actual RULs provided in the RUL column of the test data. In PHM context, it is generally desirable to have early RUL estimates rather than late RULs. Another criterion is the accuracy of prognostics model evaluated by a \"relative\" **Root Mean Squared Error** or **RMSE**, since it penalizes large errors severely, which will force the algorithm to forecast RUL as accurately as possible.\n",
    "\n",
    "$$ realtive\\ RMSE = \\sqrt{\\frac{1}{n}\\sum_{i=0}^n (\\frac{y_i - \\hat{y_i}} {y_i + 1})^2} $$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading the data\n",
    "\n",
    "Data source <a href=\"https://c3.nasa.gov/dashlink/resources/139/\">here.</a> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
    "import matplotlib.pyplot as plt\n",
    "from math import sqrt\n",
    "from sklearn.ensemble import RandomForestRegressor , AdaBoostRegressor, GradientBoostingRegressor\n",
    "from sklearn import preprocessing\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.neural_network import MLPRegressor\n",
    "import os\n",
    "import IPython.display as dis\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "np.random.seed(8)\n",
    "path = os.getcwd()\n",
    "\n",
    "pd.options.display.max_columns = 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(os.path.join(path, \"data\", \"train.txt\"), sep=' ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.unit=data.unit.astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>unit</th>\n",
       "      <th>os1</th>\n",
       "      <th>os2</th>\n",
       "      <th>os3</th>\n",
       "      <th>s1</th>\n",
       "      <th>s2</th>\n",
       "      <th>s3</th>\n",
       "      <th>s4</th>\n",
       "      <th>s5</th>\n",
       "      <th>s6</th>\n",
       "      <th>s7</th>\n",
       "      <th>s8</th>\n",
       "      <th>s9</th>\n",
       "      <th>s10</th>\n",
       "      <th>s11</th>\n",
       "      <th>s12</th>\n",
       "      <th>s13</th>\n",
       "      <th>s14</th>\n",
       "      <th>s15</th>\n",
       "      <th>s16</th>\n",
       "      <th>s17</th>\n",
       "      <th>s18</th>\n",
       "      <th>s19</th>\n",
       "      <th>s20</th>\n",
       "      <th>s21</th>\n",
       "      <th>RUL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.0</td>\n",
       "      <td>20631.00</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>2.063100e+04</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.0</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>2.063100e+04</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.0</td>\n",
       "      <td>20631.0</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.000000</td>\n",
       "      <td>20631.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>51.506568</td>\n",
       "      <td>-0.000009</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>642.680934</td>\n",
       "      <td>1590.523119</td>\n",
       "      <td>1408.933782</td>\n",
       "      <td>1.462000e+01</td>\n",
       "      <td>21.609803</td>\n",
       "      <td>553.367711</td>\n",
       "      <td>2388.096652</td>\n",
       "      <td>9065.242941</td>\n",
       "      <td>1.3</td>\n",
       "      <td>47.541168</td>\n",
       "      <td>521.413470</td>\n",
       "      <td>2388.096152</td>\n",
       "      <td>8143.752722</td>\n",
       "      <td>8.442146</td>\n",
       "      <td>3.000000e-02</td>\n",
       "      <td>393.210654</td>\n",
       "      <td>2388.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>38.816271</td>\n",
       "      <td>23.289705</td>\n",
       "      <td>107.807862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>29.227633</td>\n",
       "      <td>0.002187</td>\n",
       "      <td>0.000293</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.500053</td>\n",
       "      <td>6.131150</td>\n",
       "      <td>9.000605</td>\n",
       "      <td>1.776400e-15</td>\n",
       "      <td>0.001389</td>\n",
       "      <td>0.885092</td>\n",
       "      <td>0.070985</td>\n",
       "      <td>22.082880</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.267087</td>\n",
       "      <td>0.737553</td>\n",
       "      <td>0.071919</td>\n",
       "      <td>19.076176</td>\n",
       "      <td>0.037505</td>\n",
       "      <td>1.387812e-17</td>\n",
       "      <td>1.548763</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.180746</td>\n",
       "      <td>0.108251</td>\n",
       "      <td>68.880990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.008700</td>\n",
       "      <td>-0.000600</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>641.210000</td>\n",
       "      <td>1571.040000</td>\n",
       "      <td>1382.250000</td>\n",
       "      <td>1.462000e+01</td>\n",
       "      <td>21.600000</td>\n",
       "      <td>549.850000</td>\n",
       "      <td>2387.900000</td>\n",
       "      <td>9021.730000</td>\n",
       "      <td>1.3</td>\n",
       "      <td>46.850000</td>\n",
       "      <td>518.690000</td>\n",
       "      <td>2387.880000</td>\n",
       "      <td>8099.940000</td>\n",
       "      <td>8.324900</td>\n",
       "      <td>3.000000e-02</td>\n",
       "      <td>388.000000</td>\n",
       "      <td>2388.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>38.140000</td>\n",
       "      <td>22.894200</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>26.000000</td>\n",
       "      <td>-0.001500</td>\n",
       "      <td>-0.000200</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>642.325000</td>\n",
       "      <td>1586.260000</td>\n",
       "      <td>1402.360000</td>\n",
       "      <td>1.462000e+01</td>\n",
       "      <td>21.610000</td>\n",
       "      <td>552.810000</td>\n",
       "      <td>2388.050000</td>\n",
       "      <td>9053.100000</td>\n",
       "      <td>1.3</td>\n",
       "      <td>47.350000</td>\n",
       "      <td>520.960000</td>\n",
       "      <td>2388.040000</td>\n",
       "      <td>8133.245000</td>\n",
       "      <td>8.414900</td>\n",
       "      <td>3.000000e-02</td>\n",
       "      <td>392.000000</td>\n",
       "      <td>2388.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>38.700000</td>\n",
       "      <td>23.221800</td>\n",
       "      <td>51.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>52.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>642.640000</td>\n",
       "      <td>1590.100000</td>\n",
       "      <td>1408.040000</td>\n",
       "      <td>1.462000e+01</td>\n",
       "      <td>21.610000</td>\n",
       "      <td>553.440000</td>\n",
       "      <td>2388.090000</td>\n",
       "      <td>9060.660000</td>\n",
       "      <td>1.3</td>\n",
       "      <td>47.510000</td>\n",
       "      <td>521.480000</td>\n",
       "      <td>2388.090000</td>\n",
       "      <td>8140.540000</td>\n",
       "      <td>8.438900</td>\n",
       "      <td>3.000000e-02</td>\n",
       "      <td>393.000000</td>\n",
       "      <td>2388.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>38.830000</td>\n",
       "      <td>23.297900</td>\n",
       "      <td>103.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>77.000000</td>\n",
       "      <td>0.001500</td>\n",
       "      <td>0.000300</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>643.000000</td>\n",
       "      <td>1594.380000</td>\n",
       "      <td>1414.555000</td>\n",
       "      <td>1.462000e+01</td>\n",
       "      <td>21.610000</td>\n",
       "      <td>554.010000</td>\n",
       "      <td>2388.140000</td>\n",
       "      <td>9069.420000</td>\n",
       "      <td>1.3</td>\n",
       "      <td>47.700000</td>\n",
       "      <td>521.950000</td>\n",
       "      <td>2388.140000</td>\n",
       "      <td>8148.310000</td>\n",
       "      <td>8.465600</td>\n",
       "      <td>3.000000e-02</td>\n",
       "      <td>394.000000</td>\n",
       "      <td>2388.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>38.950000</td>\n",
       "      <td>23.366800</td>\n",
       "      <td>155.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.008700</td>\n",
       "      <td>0.000600</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>644.530000</td>\n",
       "      <td>1616.910000</td>\n",
       "      <td>1441.490000</td>\n",
       "      <td>1.462000e+01</td>\n",
       "      <td>21.610000</td>\n",
       "      <td>556.060000</td>\n",
       "      <td>2388.560000</td>\n",
       "      <td>9244.590000</td>\n",
       "      <td>1.3</td>\n",
       "      <td>48.530000</td>\n",
       "      <td>523.380000</td>\n",
       "      <td>2388.560000</td>\n",
       "      <td>8293.720000</td>\n",
       "      <td>8.584800</td>\n",
       "      <td>3.000000e-02</td>\n",
       "      <td>400.000000</td>\n",
       "      <td>2388.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>39.430000</td>\n",
       "      <td>23.618400</td>\n",
       "      <td>361.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               unit           os1           os2      os3        s1  \\\n",
       "count  20631.000000  20631.000000  20631.000000  20631.0  20631.00   \n",
       "mean      51.506568     -0.000009      0.000002    100.0    518.67   \n",
       "std       29.227633      0.002187      0.000293      0.0      0.00   \n",
       "min        1.000000     -0.008700     -0.000600    100.0    518.67   \n",
       "25%       26.000000     -0.001500     -0.000200    100.0    518.67   \n",
       "50%       52.000000      0.000000      0.000000    100.0    518.67   \n",
       "75%       77.000000      0.001500      0.000300    100.0    518.67   \n",
       "max      100.000000      0.008700      0.000600    100.0    518.67   \n",
       "\n",
       "                 s2            s3            s4            s5            s6  \\\n",
       "count  20631.000000  20631.000000  20631.000000  2.063100e+04  20631.000000   \n",
       "mean     642.680934   1590.523119   1408.933782  1.462000e+01     21.609803   \n",
       "std        0.500053      6.131150      9.000605  1.776400e-15      0.001389   \n",
       "min      641.210000   1571.040000   1382.250000  1.462000e+01     21.600000   \n",
       "25%      642.325000   1586.260000   1402.360000  1.462000e+01     21.610000   \n",
       "50%      642.640000   1590.100000   1408.040000  1.462000e+01     21.610000   \n",
       "75%      643.000000   1594.380000   1414.555000  1.462000e+01     21.610000   \n",
       "max      644.530000   1616.910000   1441.490000  1.462000e+01     21.610000   \n",
       "\n",
       "                 s7            s8            s9      s10           s11  \\\n",
       "count  20631.000000  20631.000000  20631.000000  20631.0  20631.000000   \n",
       "mean     553.367711   2388.096652   9065.242941      1.3     47.541168   \n",
       "std        0.885092      0.070985     22.082880      0.0      0.267087   \n",
       "min      549.850000   2387.900000   9021.730000      1.3     46.850000   \n",
       "25%      552.810000   2388.050000   9053.100000      1.3     47.350000   \n",
       "50%      553.440000   2388.090000   9060.660000      1.3     47.510000   \n",
       "75%      554.010000   2388.140000   9069.420000      1.3     47.700000   \n",
       "max      556.060000   2388.560000   9244.590000      1.3     48.530000   \n",
       "\n",
       "                s12           s13           s14           s15           s16  \\\n",
       "count  20631.000000  20631.000000  20631.000000  20631.000000  2.063100e+04   \n",
       "mean     521.413470   2388.096152   8143.752722      8.442146  3.000000e-02   \n",
       "std        0.737553      0.071919     19.076176      0.037505  1.387812e-17   \n",
       "min      518.690000   2387.880000   8099.940000      8.324900  3.000000e-02   \n",
       "25%      520.960000   2388.040000   8133.245000      8.414900  3.000000e-02   \n",
       "50%      521.480000   2388.090000   8140.540000      8.438900  3.000000e-02   \n",
       "75%      521.950000   2388.140000   8148.310000      8.465600  3.000000e-02   \n",
       "max      523.380000   2388.560000   8293.720000      8.584800  3.000000e-02   \n",
       "\n",
       "                s17      s18      s19           s20           s21  \\\n",
       "count  20631.000000  20631.0  20631.0  20631.000000  20631.000000   \n",
       "mean     393.210654   2388.0    100.0     38.816271     23.289705   \n",
       "std        1.548763      0.0      0.0      0.180746      0.108251   \n",
       "min      388.000000   2388.0    100.0     38.140000     22.894200   \n",
       "25%      392.000000   2388.0    100.0     38.700000     23.221800   \n",
       "50%      393.000000   2388.0    100.0     38.830000     23.297900   \n",
       "75%      394.000000   2388.0    100.0     38.950000     23.366800   \n",
       "max      400.000000   2388.0    100.0     39.430000     23.618400   \n",
       "\n",
       "                RUL  \n",
       "count  20631.000000  \n",
       "mean     107.807862  \n",
       "std       68.880990  \n",
       "min        0.000000  \n",
       "25%       51.000000  \n",
       "50%      103.000000  \n",
       "75%      155.000000  \n",
       "max      361.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "unit      int64\n",
       "os1     float64\n",
       "os2     float64\n",
       "os3     float64\n",
       "s1      float64\n",
       "s2      float64\n",
       "s3      float64\n",
       "s4      float64\n",
       "s5      float64\n",
       "s6      float64\n",
       "s7      float64\n",
       "s8      float64\n",
       "s9      float64\n",
       "s10     float64\n",
       "s11     float64\n",
       "s12     float64\n",
       "s13     float64\n",
       "s14     float64\n",
       "s15     float64\n",
       "s16     float64\n",
       "s17     float64\n",
       "s18     float64\n",
       "s19     float64\n",
       "s20     float64\n",
       "s21     float64\n",
       "RUL     float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As indicated below, there are 100 differents units in the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(np.unique(data['unit']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For some sensors, the distributions of the thresholds for several units are almost the same "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x105c8aa90>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x105910150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['s4'].plot.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10b549610>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x104279d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[data['unit']==1]['s4'].plot.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x105b3de90>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b631710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[data['unit']==10]['s4'].plot.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On the other hand, some sensors seem to have constant values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x105b29250>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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uQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b4faf50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['s19'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For each unit, we have records of sensors only before reaching a failure once."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10b50b050>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b51e310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[data['unit']==6].reset_index()['RUL'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Correlation Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10bb0e5d0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Ja+fT/dX7QKPUW8ZYrqdoezqGBq5qNcS7tzlWT5m2Rc63mwmss56ByQmcq41Vq3bkvFWsltWJ1d/LEeK1Nj71jcSn/6gEcszxmffDb/hYxad/cgJ6O/HpEuaP31V9yF66tqnVAUC4nXh1rVMnruY6sY7X8IvEq1eXCHI27QdAn1dCdUkZfnFRdtO2RJwYK6oo2mzKX62u4fy+E+jCA2y+82JtvMFme184VqNR6PzsbZY2PuKOq+yuV+WZXM4fOF1vKrRabUCtMp24aXTOKJr6XWNH6g+I+v5ofz7v172oBqN5+SO4hpvaDEO5nsJLaGtD6vTtGzveWPftL3ZeETA0htIDpyk1z9CqLjzf4CxUj7jO6E9mUXU6G7W6hoLvNuE7sr9NGt+R/chfvh6Awh+34DU4pt73+F9/BYX/NbVFuvYh6E9kUVNgOqco2bQXv2sGNKlOhGjSYIOiKIOa8tmfjWuYv+WkHKAyq6Bep8Q1zJ/KrIILaTLrp6nr3PfbMJTrGb73XYbtWszxd36gus5Vqz+at0uQD1U5po5uVU4RLkE+ALh3DMPJx4O+Xz9L4uo5hN18Rf31bhuEV68OFJs7Kn8Wbe9JJnfVTst61+o6+25Ov/cj25Nnsvee1+nxxsQGvqFhQVcn0H/Tm8R+9hQHH30HAF2oP/rMC9tIn5lfb4BGF+aP3rwdVYMRQ2k5zv6ND5BFzriF0+98bzkxboqWKgtA7BczGbz/fWrOV5Dz/dbGyxFWpxxZBbiEBdhJY759wWCkprQcpzrlCLw2kfP7jpuuJHmbrvp1ePIW4lfPp/v703AO9KmfuUYhce18rtz/Pvm/7qWkkfgNv3UYeeYrZv5XxuAeFcr25JlsHT4d79hIfBO7N7qedXV96S7TIJedg3ur1kkdrmH+VFqVpaKBdqXCul3JyrdJ023GWK5KWUzETYMsV42ttb11KDmXMMvAZt2Bqqx8dHXK5NJA/WjcXWnz8BhOvVa/HE3lFuZHRab1+hbgFuZXP01Ww2miJoxk2Lp5xL95P852ZlaFX9uPon0nMVZduNLU+8un6b96LhF3JDVYNo2bC4HD4sg2T+f26BxB6JiB7Lj2WbYmTUc1GAm7qX4bfjE9Fj5I4tr5tH/0JpvP67cjBehC7cRqhmlbqOZtUbcdCbKK1VpdFz5E37Wv1suzMY4Qry5h/lT9gfiMeHgMp+3EZ+RL4zn50qf1TpgvxrVOvJrqxK9+mqyG00RNGEnSunn0torX4v2nCRvVB0Wrwb1dEL4xkbiF2+/LtGScADh5uxMwsg+FG/fZZtyENr7N+JEM2raQzs/cRvrTHwMQcdtwakor2J48k22jZtLm9uG4tguyu24N0YUHkLj+Fa7Y9TanFn9nO6vBbp20Xn9A1Nec/fk2tw4ld+3vm0mnC/Onok456rYnOjvlqJumLo+OYagq9P3iKQasmUvkQ9c1mNYlzJ+qLKs27Vw+LnXbtFCrNAYjhpJynPxsY9XvusHkf2cabNCfzMK1YzgubYJBq8FvVH9cwgMbLfP/IlU1Ovw/R9TUmQ2LmviZAHzjO6IajKyLfZBfEqYQ+cDfcGsf3LKZmjs0ilaLd2wUu2+fT8otc4madiPuUWGWZFp3HXEfPEr6M5/YXCVwdLoQP0KuS+TMv1bW+1vAkGi6zZ1A4tr5xP37SZy83ExXPS5B7oodbBv8KPvufpWo6eOaq9j1ePZsj1uHEPJW7GixPC7VnlvmsDlmIhoXZ8uVmJbk3rUNkbNu48gTSwDTrApdRCAlO9PZPXI6JTsPE/XcnfUXNKpsTZrOxrgH8endye70cTBdGfaO68jJf5runQ4YGkPAlTEkrp1P4s/z8OgUgXtUaJPLGziiN1V5JZTuPXHpK9tEv7tOWsCheV/xc5+HyfjPZjpMGGXzt4BBPWj3j2EcnL3sspSl/RNjyVjyA8by1ptifOLjNazuP5X1SU9RmV1Er+dvs/m7V9cIes76B6lP/Mvy2Y7rnmXbiBnsunUubcePanBwK2hkH4p2pFtuofC/ohfeMZH0XzWHxLXz8b+i1yUfO9ImLWLr0CfYMfo5fBK7E3LzkEtc48a5d21D1DO3kf74EstnBya9xc6hj7F79DMtkmdjWjNe2z0xlkw78ek3og/VecWU7b2020qaw/GP17Cq/1TWmuM12hyvp5b9QkVmPsNWzSbmxTso2HkE1XBpAyGXwl6cgGk6ePd3p5Lxr5+oPJVju1AT2vizH61mc/9HODL7cyIfvRGAgCtjCLv5ChLXzqf/ipdx9vfCPTKs3rKN0Wfms3XYk2xOfISwcVfiHHTxwd0/yhH7A391HaeOQa0xkPmfTa1dFBuKVotf/67smbSYbaOfI+SaBPyvaLn+mkd8Z4yVeirTTTMpDMVlnHrqPaLeeZxuX89BfybHMhNEiItpdA6koigDgIFAkKIo06z+5A1oG1nufuB+gLdfn829d/6jGYraPNqPH0lb872LRanHcI24MFpfd9QT6o+OuobXT1NX+I2DyF23B7XGQFVeCYU70vGJjSJ4eJwl75I/mHdVbjEuwb6mWQ3BvpbbJSqz8qkuLMVQrjdN/9p6CK+e7Sg/noXipCX2w2lk/WcTOT85zsFNF+KHvs5VhLq8ojvgHhnKoK2me/C1bi4M2rqQzYmm+9m3XzOr3oNy4r+YiS7Ih5I9xzkw7b0mlaVo60Hc2ofg7O+F/lyBzTRPXXgA+nO220ifVYAuIgB9VoHpthkv9wbv0wbw6dsF79goBuxYjOKkxSXQh/ivn2P3jS80Wq6WKIs1o76avJU7CEpOoHDDvgbT6bPqlCPMn6qsfDtpAqnKKgCtBicvd8stAC5h/vT48AnSJy+m8lQ2ADUFpRjKKy0PP8z7/jdCbx3eYBlqSsop3LSfwGGxlB2ynbrsPySayKk3svOG5y1X0xRF4cRb35Hx6c82aduMH0mb201XnXffOq/BGPTt15WgUX0ITIpD4+qCk6cbXRdPJv3hRQ5RJx3Gj6DdbbVt2nFcrcri1kC74mbdroQF2G3TMr7eRL+l0zn86v8B4NW9HbGv38+2W+eZpnA2Ue2613IJM8WotaoG6scrvjOB1yYS+cwdOHl7oBqNGPVVZH1Yf9DRWuT4EXS4bRgAhanHba7gmq6U227riqzCOnVyIY3e6kGHp5auI/HTJ2zS9f9wGimT36Hc6sRJf860bHVeCTk/bccnviNFW+s/jC90zECbWyhQFDK/2sDRl21PjoOuTqDj438H4MC092weGlZXbd6Gskpyvt6Ed3xnss3Teuu3I/7oz9mJ1YhASzviZNWO6ML86fXRExx8+EKsAlSZ2yJ7edblaPFalVVgc4XuUuLTM74zAdcm0qFOfOpC/fEfmYBfUm80Ome0nu50XjyFIw+/ZbcMUY3Eq6lObOO1sk68WqexjteTS9cxwByvqsHIvuc+s/ztyu+f5/zx+tO1oeXiBKDL6xOpOJHF2SU/2c0bGm/ja537Zgvd5t9r+kVRSJ/5Mfm/7LFJ0/GpcQRd1RuArUnTG8zPZr2yCzl/6Ay+/buR+8OFB/I6Un9AmDR3fz5i3JUEj+jNtr/PvqRytBs/kjbmchSnHsMtIoDa+beuYf712hO9nXLUTVNXZVY+hb8dtMRT7s+peEd3oGBjWr20VVkFuIRZtWmhAaa2yzrNOVOa6qx80GrQertTU3ghVv1HX0HBtxttlin+eQfFP5vOHQJvGylvZhBNdrGZDS6AJ6ZBCS+rfyXA3xtaSFXVJaqq9lVVta8jDTQAnPpoNZuSZrApaQbZK3YSYb4C49unEzWl5ejrTNHX5xRRc74C3z6dAIi4eQjZK3c2mkdFRj6Bg3sCppkEvr07U3Y0k1MfrWZr0gy2Js0gZ8VOws15+5jzrnt7QJU5bx9z3uE3DyHXnHfuqhTCx5mWDx83hJzaz1fuxLd/NxStBo2bC769O1F2xPQAo55vTqTsSAan3mv4IN8aLjbQAJD38242RE9kU8JkNiVMxlBRZRpoAPJ/3Uvbe5ItaT17tgdg9y1z2Jo0/aIDDW4dQi4sGx2JxsWZ6oJSSncfwz0qDNd2QSjOWoLHDCRvle22z1uVQtjYoQAEXZdIofme2IZkfLKGzbEP8FvCw+wa/SzlxzOb1LFoibJo3XWW54QoWg0BI3pTdrTxJ3uXph7FLSoM13bBKM5OBI0ZRP5q23Lkr95JyNgrTeW4NtHydgWttzu9PnuKEy8vpWRHep1lUvAdaNpnfK+ItnkQGZiey+FkvrVA4+qM/5XRlB3NtEnj1asD3V+9lz13vmLzJPy89XuIuHWoZbaLLtQP50Bvzn60mq1J09maNL3RGDz68jI2xk9iU8Jk9k1cSNHmNMtAQ2vWSa2TH61hw1VPseGqpzi3cidtx5qm3fv27kR1A21a9fkKfHub2pW2Y6/g3KoUADwiL8z4CEnuy3lzHbtFBJDw4aPsfviflB0/12Bd2VOaehTXqDB0VvVTsNp2sNNUP0PN9TPAUj97xzzDjoRJ7EiYRMb7P3LmrW8uOtAAcOKjNay/aibrr5pJ1sqdtDPXiV/vTtSUVjTYzvuZ66SdVZ1Y328bdnUCJYdM28HZ250Bnz3B/pe/oGDHYUsarbsOrYcrABp3HQFDYzhv54TJycsNvwE9LG03QMHGfYRc2x9n84N9nXw9cG0TSO6KHZZYbWygQdFqLNO2FSctASP6UHbowlsYSnfbxmrwmEF22pGdhNbG6nWJFJrfOOHk7U700qc4Pts2Vi+WZ12OFq+1+29j8VmweifB5vgMvHYAxeb4TBvzDCkJk0hJmETm+z9y9q1vOPfhSk7N+ZydvSeSkjCJ9AcWULw5rcGBBoDjH61h3VUzWWcnXqtLK6isUyeV5jqxjtdMc51YP98h3CpetW4uljYweEgv1BoDpQ28yaEl4gRMtww4eblzdNbH9fJ0DvC+aBvvbrW9A0fEU2EeLMn/ZQ9t7h6B4mS6BuYeFYbGXcexuV9a9pvG6ML80bg6m8rv44Fvv66UH7PN25H6A8KkOfvzgcNiiXroOlLufPWSb2k5/dFqtiTNYIudvn1DbVrdvv3Fzivy1u/Fs3s7NG4uKFoNfgO7N/gmlrI9R3CNDMOlrWn/9b9+MEVrttukKVqznYCbTQOcfn8bSOlmq4tMioLfdYMo+K/tYINTgGm2j9bHg+A7ryb38/pvbPmfZzQ6/j8HpDTlfkJFUdqrqnrq92RQnXf8d8/Te+K5eezYvZeiohIC/H2ZdM8d3HTdqIsvaMeanjPtft5z7ngCh8dhrNCz95F3La+vHLx2HpuSZgDgExtFjOVVOamWV9+EXJ1Ajzl34xLgTU1JGSVpp9hxy1y07jpiFj6IZ5cIUBTOfvELJ942vUbPeipJN3Pehgo9+x9519KJTFw7j63mvL1jo+hleT1OKofMeTv7eRLz/lRcIwKoPJvHnvsWWKbidph0LeG3DDW94nLpOk4vWYFvv670+/4FSg+cQjXfd350zhf0/nzG76rP5vRrr/vpv3ouTl5uqEYVQ1klW654DMP5CuKXzuDAtPfqnQwOO/6J5dWXzv5edJs3AY/OEShaLUVbD3LwyX/Vy6ftvcl0eGg0LsG+VOcVk7c2lQPT3qPDw6MJu3kIao0BY2UVR1/41PLqy4CkeDq/dBeKVkPmsvWcWvANkU+OpXTPMfJWpaDROdNj8cN4RkdSU3SetIkLLFNDB+xYjJOXO4qLEzXFZaSOm23z5GrXtkHEfDa9ya+6au6yVBeeJ/bT6Wh0zqBRKNy8n6PPfGIzNc5Jqb/7+iXF0/HFu02vMVy2njMLv6b9k+MoTT1GweqdKDpnui2ejGevSKqLznNo4ptUns6h3dQbaTvlBiqsOv/7bjG9Ik/XJpBuiyaj9fGgOr+Ew1PfttwPDODcvQM935qEotWgaDRkf/cbx9/4Dx2fvJmSPcfJXZVC7+Wz8OzelirzQ/sqM/JIvfNV07a/72oizFdTDWWVpE1aTEWdK24uQT4NxqFl3Qf2IHLStfVffdkKdVLcwMS0XnPHEzwsFkOFntSp71natCE/z2XDVU8Bpjat9lWCOetSSZv5MQB9/zUVj07hYFQpP5vLvic/oPJcITGv30f0/ZelAAAgAElEQVTY3/pRcfbCPdobRz0NgC8Xf3CWX1I8US+aXhmXvWyd3frpungKnr06UGNVP9baPT4WQ1llo6++zMfF7ucxc+8mZFgsNRV6dk99j6I9pltihv08h/VXmY4NvrGR9K59veK6Pew110mfRQ/i3as9qFB+JpfUJz5An1NEl6lj6DJltM3J7OZb5uHk7sqAjx4FTCfi577ZzIkF39DmTtND62qfph827koCh8exb6LtG1NCrh9A5JQxoFFQqw0ceupDmyfy1xq8Y5HNPr1r3MtUnM0j4dvnTQ/Y02go2riPo89+YtMB8U+Kp9NLpljNWrae0wu+psOT4yjdc4z8VTvRmGPVK9oUqwcmvknlqRzaP3oj7erE6p5xL2Eo1xP/7YuWPAvt5AlQqjhGvPrbiVe/pHgiXzS9+jJn2TrOLvyadk+O47xVfHZZPAUPc3ymT3wTfZ34bGuOz8w68ek9sCcRD46u9+rL7AZiFSDWHK+GCj0pVvE6/Oc5rLOK1z5W8bqntk4WPYiPVbzufuIDKnOKcG8byKBlM1CNKpXnCkmZtsRSP/5q/Tpp7jjRODsxIPU9yg6ftcw6y/hwBVnmh+569GhH17cebrSN7zr7LvyviEatMVBdXMahpz6kLP0sKAqdnhpH4Mg+KIpCVX4Je+56lZpS21tFveM6EvvRYzj7emCorKYqp4jfrnwc/yHRdHnhDtPzRRXI+HAlmZ/Wf7Bna/UHhmd/1WCs/NX8FHJLg3/7I/35K7cuMF1oMl/dL0o5QtqTHwAwdMcinLzc0Lg4UV1cxo5xczh/OKPBq7Xd544nyNy332fVtx+4dh5brPr20ZbX2qdy0FyOYKvziuqSMkrTTrHzFlPbEXbTYKKmXA9A7s+7OfzS5wAEOte/zdBneB/aPj8BNFryv/yZrEX/R/jj/6Bsz1GK1+xA0TkTuXAq7r2iMBSVcmzS61SdNvWJvAb0IuKpOzg02naQLnLxNNx7RAKQueBLCv9b/1aTvme/rf9E4/8hVWf3tdy9Z83EpU20w22DRgcbFEVZoKrqVEVRvqf2Mc9WVFUdfbEM/shgQ3NqaLDhcnO0d42OzP6itYvAmpCWe0bCpdDWD/G/PHuDDa1BrzrOi3N0imOMHDc02HC5NWWw4XJpaLDhcvNQL/Jmncuk3qsvW1FDgw2Xm73BhtbQ2GDD5WZvsKE1VDvIC9IcrS8ggw0XNDbYcLk5RrTaH2xoLTLY0PoccbDhYkf/T83/v9bSBRFCCCGEEEIIIRyOg77twdE1OtigqmqK+f9fL09xhBBCCCGEEEII8WfXpHmNiqIMAp4H2puXUQBVVdWoliuaEEIIIYQQQggh/oyaehPlB8CjQArgGDejCiGEEEIIIYQQLc0op8C/R1MHG4pVVV3RoiURQgghhBBCCCHE/4SmDjasVxTlVeBrQF/7oaqqu1qkVEIIIYQQQgghhPjTaupgQ3/z/33M/yuYXoU5vNlLJIQQQgghhBBCOAp5G8Xv0tTBhl/sfObw7xoVQgghhBBCCCHE5dfUwYbzVj+7AtcCB5u/OEIIIYQQQgghhPiza9Jgg6qqr1v/rijKa8CqFimREEIIIYQQQggh/tSaOrOhLnegTXMWRAghhBBCCCGEcDhGeWbD79GkwQZFUfZx4RkNWiAIeLEpy67pOfP3layZjdg/p7WLAMDGnjNauwiiASpKaxfBwuAgZVFVeTRLXXpV09pFAEDnII/NqUTb2kWwcEc6AtaMDtKOALg6yIO1yh0kXj0dKFYNOEab5igc5fgr7Pu9V0mbm6PswQXVrq1dBCEa1dR99lqrn2uAbFVVa1qgPEIIIYQQQghhw1EGGoQQTdfUZzacaumCCCGEEEIIIYQQjkZ1kBl6fzYyd04IIYQQQgghhBDNSgYbhBBCCCGEEEII0azk9ichhBBCCCGEEKIh8jaK30VmNgghhBBCCCGEEKJZyWCDEEIIIYQQQgghmpXcRiGEEEIIIYQQQjRE3kbxu8jMBiGEEEIIIYQQQjQrGWwQQgghhBBCCCFEs5LbKIQQQgghhBBCiIYYDa1dgj+lVhts6PHyXQQlxWOo0LN3yjuU7DtZL413TCSxbz2IxtWF3LW7OfD0JwCEXtefzo//Hc8uEWxJnkXxnuMAKE5aot+4H5+YSBStlozlGzj21nfNUt5Zc95gw+bt+Pv58u1n7zbLd9byHxZL59njUbQaspau5dQi2zIrLk70WPwwXjFRVBeWsv/+BVSeycXJz5PoD6bhFdeJc1/8wuGZHwKgcXOh1/vTcOsQgmowkr8mhWOzP2/WMjcn907h9Fz4IN7RkRyd+wWn3vnBbrq+3z2Pk6cbAC6B3hTvPsaeu19rcj7B1yXS8fG/49Elgu3JT1NijhsAzx7t6PHqfWg93UBV2TFqJkZ9Nf7DYuky+24UrYbMpevsbpueix+ybJu0+xdSeSYXgPZTxhB+6zBUg5HDT39MwS97AGh739WE354EQObSdZxZ8lOj5e5qta+kTXmHUjv7ildMJL3eehCteV9JN+8rTr4exC55BNe2QVSeyWXPfQupKS7Db2AP4j55nIrTOQDk/Lid4298jXvHMGKWPGL5Xvf2wRx/ZTllRzIuWz1EPv53wm9Pojq/BIBjc5aRuzaVoOS+dJw+Fowqao2B9Gc+oWh7er266PP1s+hC/DBWVgGQMu5lqvNKGq1ja20njKLd/dfgHhnKL93vpbqg1FSXXm70ensyrhGBKFoNp975Aa/oDgSat83+Ke9Quu+E3W3T861JaF1dyFu7m/SnP7Zsm5glU3FrG0TFmVz23reAmuKyBvcHjc6Zvt89j8bFGUWrIfuHbRx79f+AlokRJx8Pei6YiHuHEIz6avZPfZfzh85e+EKNQuLqOTj5eIDB2Kx1YFqnuxusW62nGwM3vk7Oih2kz/wIgPhlT6EL8UPRaijcdghjtYGgpLhmrZNa3nFR9PvxJfZNfIvsH7bh2iaQuI8eA42CxklL9n9/I2B43EXbtF5vT8Y7Ngq1xkDx7qMcfPx91Jqmd2YupU3bOeopS5vW2sebxrZtrebabwAG71hETVklGIyoNQa2jZpJwLBYuprbtIyl6zhppx56LX4Ib3M97LVq0zpMGUOEuU1Lf/pj8n/Zgy48gF6LH8Il0AdUlbOfreXM+ysA6Dh9LEHJfcGoUpVXzP4p71CZXWRVH82//9aqG6sAIzI/p/TgaQAqM/LYd+erAM1+vHPvGEavJVMty7uZjydnlvxEryWP4N4x3LQO3u4YKqtQq2ps0h57ZTmnrY6PTT0GNKShGDEd92zLecx83LtcMQLQ9p5k2o4fiWowkvfzbo68tLTJ6/ZX1Np9oyOvLOfUkhX18uz+8l0EJsVjrNCzr5Hzm2jz+U3e2t0cNJcr5Lr+dDKf3/yWPMvSpru1DWLwxtcpO5YJQFHKEQ48+cFlqZOg5D50mj4W1bLf/Zui7el49WxP91fuwcnTDdVo5PiCbxvZWuKvrFUGG4KS4nCPDOPXxKn49ulEr1fuZcvVs+ql6/XKPex7bAlFKUfp+/kMgobHkbsuldJDZ9g14Q16vXqfTfqw0YlodM5sHPokGjcXhmx4ncxvtlBhbvz/iDHXjODWm0Yz86Wmn9w2iUah67x72D12NvrMfPqumkvuqp2UH86wJAm/dTg1RWVsTZxC8JiBdHzmNvbfvwCjvprj877Eo1s7PLu1tfna0+98T9Hm/SjOWuL/71n8h8dRsC61ecveTKqLzpP+9McEXd230XQ7r3/e8nPMB9PIXbnzkvIpO3SGPRNep3uduFG0Gnr982EOPPRPzh84hZOfJ8bqGvO2mcDusS+jz8wnYdVc8lbtpKzOtqkuKuO3xEcIGTOQTs/cStr9C/HoEkHImIFsHfIYulA/4pfP4rcBU/Ho0obw25PYkTwTtaqGuC9mkrc6hYqT2XbLHJgUh0dkGJsSp+LTpxM9XrmXbXb2lR6v3MOBx5ZQnHKU3p/PIHB4HHnrUomcfD35G9M4uei/dJg8msjJ13PEfCJQtO0Qu29/xeZ7yo9lsTVphukXjcKVe94hd+UO4pfPuqz1cOa9Hzld5wStYMM+yzb37NGOmCVT2TJ4mt16S5u0yObE61IUbU8nd80u+n79rM3nbSaM4nz6WVLveAXnAC8Gb1tE0c50Nic+gk+fznR/5R6229k23V+5l4OPLaE45Qjxn88gYHgc+etSiZw8hoKNaZxc9B0dJl9Ph8nXc3T25w3uD0Z9NSk3voihXI/ipCXh+xfJW5eKs69ni8RI1CNjKE07xZ7xb+DeKZzu8yaQ8vfZlu9rf9/V1JRU4Brmz68972/WOghMisM9MrTBuu00YyyFWw/a5LH3vgXUnK8EIOH759G6u7bIfoNGocszt5L/y17L9+izC9n2t2dQq2rQuusYuPE1Dj7xL3z7d62Xp7Vz/9lI2qRFAES/O4WI24Zz9pM1jS5j7WJt2sGHFttp01r3eHOxbVurufabWik3vmgZOESj0G3eBHaNfZnKzHz6m+vBuk2LMNfDZnOb1vmZW9lnbtNCxwxki7lN67N8FpsHTEWtMXD4uU8p3XcCrYcr/dfMpeDXvZQdzuDkP7/n2PyvAGh7bzJRj91kOVFoyTbeXqwCGCqrLrTzgNactrmPd+XHstieNN1SlsF73iX3p+0ApN2/0PK9nZ6/A0NJOcfe+I8l7ZA975JjTlvrUo4B9jQUI6bj3oVyDtnzLjkrd9Bn+azLFiN+g3oSlNyX34Y/iVpVg3Ogd5PX66/IEfpG2T/tsFsu98gwNlqVa2sD5Uozl6uPVbnOHzpD6oQ36FmnTQcoP5XNFqv99nLVScGGNH5bmQKY9rvYJY+wefBjGCqqSHv4bcpPnEMX4kfimjkAvkBRvUzFX1qrPLMhJLkvGcs3AFCUchQnb3d0wb42aXTBvjh5ulGUchSAjOUbCDEfIMqOZFJ2LKve96qqitZdh6LVoHV1Qa2uoaa0vFnK3DcuGh9vr2b5LmvevTtRfuIcladyUKsN5Hy7haDkBJs0gcl9yfrqFwByv9+K3+BeABjL9RRvT8eor7JJb6yoomjzfgDUagOl+07gGh7Q7GVvLtV5JZSkHkOtbtoVPa2nG/6De5KzwtTQa9x19FjwAP1Wvkz/n+eZriDZUXYkg3I7cRMwNIbzB05z/sApAGoKz4NRxbt3JypOZFu2Tfa3Wwiss22CkvuS9dWvAORYbZvA5ASyv92CWlVD5elcKk5k4927Ex6dIyjZdQRjRRWqwUjhlgME/a1/g+salNyXTPO+UmzeV1zq7Csu5n2l2LyvZC7fYOlMBSf3JfNL0/KZX24g+CIDOjb1ckU0FSezcQn2bfV6ADCU6y0/a911qGqTVwUA5wAvYj6YRr+Vc+i3cg4+CfZPBEvTTlquTtlQscys0Xq4oqoqWV/WbpsjOHl7NLJtjgCQtXwDwVeb6i4ouS+ZX5rqLPPLXy2fN7Y/1NaB4qxFcdKC2nIx4tElgoJNpnak/Ggmbm2DcAnyAUAX5k/giN4YyiqozMpv9joISk4ga7n9uvWKicQlyLf+CdT5ClPdOGlxDQug8LeDzV4nAO3uTSb7h+1UWc2WUasNlquyGp0zoHB+/6mLtml5ay+ckBfvPoou3N/0HS3YprX28aaxbVurufebunx6d6L8RDYV5no4Z6cegpL7kmnVpvmb6yEoOYFzVm1a+YlsfHp3oiqnyDJDw1BWSdmRDHShpu1ZG5sAWndT22GTTwu18fZitSEtcbyz5m8+nlSezauXd8joRM59s/miaRs7BrSfdB39Vs4hcf0rRD1xs911bEqM1OatC/a9rDHS5q4RnFz0naUduZTZeH9Frd03Km8oluuUy7mR8xvrcl3s/KYpWqpOGtrvyo9nUX7iHGAacDe3M0G/q/B/FqrR8f85oN892KAoypLfu6xrmD+VGfmW3yuzCnAN86+fJqvgQprM+mnqOvf9NgzleobvfZdhuxZz/J0fqC4qa3SZ1qYL9UefeaEu9Jn5loOPJU2YP3pzfakGI4bScpz9mzbw4eTtTuDIPhRs3Nd8hW5lwVcnULAxzdKBi5p6AwUb09ie/DQpN75I52dvQ+Oua/L3uXcMR1VV4r6YScKaebR7aDQArqH+VNbbNn42y9bdNjXmbaML9UOfceFApM/KxzXUn/OHzuDbvxtOfp5o3FwIvCoe14iGO+Z/dF9xCfKhKsc0yFyVU2Q5WQTw6dOZAevm0/vzGXh0bVMv79AbBpD9zeZWqYc2E0bRb/0rdF/wgGmavlnQ1QkM3PQG8Z/N4MCj7zRYbz0WPkji2vlEPnqj5bOus+/m9Hs/sj15JnvveZ0eb0xscHl7znywEo8uEQzZ+y4DfnmN8mOZVFqtW2VWfpO2jS7MVHeNbZsGaRQS187nyv3vk//rPop3HW2xGCk9cJqQv/UDwDu+I65tAtGZl+n20l0cfnEpzv5eGCovnHw2Vx3owvzqrJP5exWFLs/fweHnP7VbPb2/eIqh+99DcdJapow3Z53oQv0IvjqBMx/Xn32gCw9gwPr5DNn1T04u/g59dqHdMtqjOGkJ+/sQ8teZbjFqrjYttk6b5gjHmwa3rZVm32+A3l8+Tf/Vc4m4I6mBerBt06z3q7ptWmWdNq1uHbq2DcKrVyTFu45aPuv41Diu2PVPwm4azLFXvrKbj6k+Wj5WNTpn+q96mX4/vWQ50WiJdt5ayA0DybYaUKjlm9idqtxiKswnLQChNwy0GXywZu8Y4H9lDO5RoWxPnsnW4dPxjo3EN7G73eUvpjbvyx0jHh3D8O3fjX4rZtP3m+fwjuv4u8r/V9HafaNz32yxWy5dmD8VdcqlC6vfxtZv3xo/vwFwaxfEwJ/n0u+bZ/Hr363e31uyToKvTmDQptfp/dl09j9a/1Zy7/iOKM5OAMcuuiLiL6fR2ygURWko+hXgmkaWux+4H+Bhr75c7XZ5Gk3f+I6oBiPrYh/E2deDxO+eJ2/DPipO5VyW/B2NotXQ891HOPOvFVT+D9VB6A0DyVi6zvJ7wJUxBI3qS4dJ1wGg0bngFhFI2ZGMhr7ChqLV4Ne/GztGzcRQoaf3/z1D6d7fNwX/YsqPZHBy8X+J//JpDOV6StNOohou40ikeUi6ZO8JNvZ5GEO5nsCkOOI+fozNAx61JFOctQSN7MPxl5fha+eg9kc1Vg8Zn6zhxBv/ARWiZoyl8wt3sH+q6eCWu2IHuSt24JvYnY7Tx7Hr5tn1vjtt0iL05wrRergS++E0Km8eQtbyDQQMicazy4WOg5OXG1p3nc2ofWMChsVSmnaSlBtfxK1DCAN+eRWNW9NPAC+qKVM1jCpbk6bj5O1O7MeP49mtfkeoucpx4q3v6Db7LhLXzuP8wTOmez8NRgJH9KYqr5jSvfXvs2+uvBvSdvxI8tamorfqLFnbdctcNDpnrtjxFt4xkRRtPdSs5er60l2mqbZ2yqnPzOe3YdPRhfgR98lj5FgNdlxMt/n3ULj1IEXbTOVtrjZt56inMFToif+/Z1usTbPOs1WON03Yb3Zc9yz6c4U4B3rT56tZNgNRzU3rriP2g2kcfuYTmxkNx+Z+ybG5X9JhyhjaTki2PG+l2TUhVjf2eRj9uULc2gfT9/+eYfeB0y1TFjPFWUvgyD4ce3lZvb+ZBiG22KQNGtmHo3bSgv1jQMDQGAKujCFx7XzANPPMPSqUojq3WjWlnLV5t8Rxr5a9GFGctDj7ebL96ll4x3ck5v2pbEqY3GJlEHVcYt/oyMtfXNbiVWYX8mvvh6kuPI93TCTxHz/OpiGP27Qxzc6q7chZsYOcFTvwS+xGp+ljSbn5ZcvfXIJ9iV78EGlT3qb/T7Md89K6aFUXe2ZDLnAK0+BCLdX8e3BDC6mqugRYAvBTyC0qQPvxI2l7+3AAilKP2VzFrDvSBvVH5FzD66epK/zGQeSu24NaY6Aqr4TCHen4xEY59GCD/lwBOqspp7rwAPTnbNdTn1WALiIAfVaB6RYRL/cL9542ouvrEyk/cY6zF3kAYWvThfg1+Sqgs78X3vGd2DP+9QsfKgp7JrxebzpxjwUP4h3dAf25QnbfNq/B76zMKqDwt4OWOs37eTde0ZEUbT9kMx3YtG1sy1l32ziZt43+XCG6iMALy4YFUGnerlmfryfr8/UAdJx5C5WZttu7zfiRhJkfnFjyB/eVqtxiXIJ9TaPUwb6W6bTWB6i8tal0n3cPzv5eljoITIqjZN9JqnKLqTxXcFnroSq32JLeqK8h5IZBeEVHsvvWeZY4Kdp6ELf2wTZltpTFXDZDWSVZX2/GO76jadq2orD9mlkY9dU26eO/mIkuyIeSPcc5MO09GhJ+y1DKj2VZOrTVxWX49O5Iwa+m6fyuYQFN2jb6rELLetrbNk0RetNgPDqF0/vLmeT9vLvFYqR2kAfgih2LKD+VQ+dnb8V/UE8ibhuOajCgaEzPB0h7aHGz1YE+q7DOOpm+t13fLvj270bbu0eg9XBF4+KEobySo7OX0Wb8SCLM+03Z0UwCh8dx2vzwruaqE5+4KGLeNT0kzDnAi6Cr4jAaDOSu2Enb8SOJMB/jyo5mNPlkJeqxv+MS4M2ex1uuTcu3atNa43gTMX6U5WGwxfXatJbfb2rbhOq8EnJ+2o5LgJederBt0yqzCnBtoE1zrdOm1dah4qQl5sPHyPrPpnrPG6h17j8b6ffTy5ZbY1qqjW8sVmvXteJUDgVbDuAV3aHF2nmAgKR4SvedsGnbwTRAFfy3fmwf8ZTls8AG0tZlfQxQFIUTb31Hxqc/26RpM34kbcxxZ338aIh13vb7Zi0XI5WZ+eT8aPq9ZPcxVKMR5wAvqvMvvu/9lSSuNbV7jtA3qtVu/EjamNv+4tRjuEUEWB5a4BrmX29wXG+3fWv8/EatqqG66rxp3feeoOJktmk2TO9Olrxbqk6sFW49ZNP30nq60XvpdI7O/dJya4YQdV3sNorjwFBVVSOt/kWpqhoJ2H+iXQNOfbSaTUkz2JQ0g+wVO4m4eQgAvn06UVNajj7H9nki+pwias5X4NvHdN9fxM1DyL7IAwErMvIJHNwTMI0c+/buTNnRzEsp5mVXuvsY7lFhuLYLQnHWEjxmIHmrbNczb1UKYWOHAhB0XSKF5vuoGxM1YxxOXu4cmfVxC5S6eV3KdOOQa/uTt2aXzQlj/i97aHtPsuV3r14dADgw9R22Jk1vtFMOkL9+D57d26FxczFdERzYg7LDZ83bJtSybULsbpudhI29EjA9Gb522+St2knImIEoLk64tgvCPSqUEvN0ydoHP+kiAgi6ph/ZX2+y+c6zH61ma9IMtibNIGfFTsLN+4qPeV+pqrOvVJn3FR/zvhJ+8xDLQ7RyV6UQPs60fPi4IeSYP7eeHucd3xE0is0JRegNgyzTWC93PVjfY2goqyBv5U62Jk1H4+Zi+dwrOhKNi3O9kyBFq7FM+VactASN6E3ZoTMA5P+61yZOPHu2B2D3LXPYmjS90YEGMD21vaa0nK1J09l1yxw0Ls74DTS1Nz59Ol9k23QGIOzmIeSuND1rJHfVTsLHmeosfNyVF33gqXOAF07e7gBkLltP+YlsDjz+rxaLESdvdxRnLQARtw+ncOtBDOcr2DVuLj+3uZ2f297Osde/pqa0nLSHFjdrHeSu2kmYZZ0ufG/apEVs6vMQmxImc/iFz8j8agNHZy9D664j58ftbE2awbaRM1G0GsuJU3PWycaEKWxMmMzGhMlkf7+Ng9M/JHfFTnRh/mQsW8/WpBnsvPElvKMjKT928WNPxG3DCRgWw74HFtpcRWruNs13YHerNu3yH28yPlrF1qTpbE2aTu6KHXa3rbXm3G807jq0Hq6WnwOGxpC3LtWmTQsdM5DcOvWQu2on4VZtWu3zS3JX7SS0TptWOxW+x5sPUHYkg9Pv/WjzXe6RoZafg5ITKNqR3uJtfEOx6uTjgeJius7k7O+Fb78uLXq8A9PxJNvOtHO/IdGUHcm0OdEyHXvsT1F36xBi+dn6GJC3fg8Rtw5Fa77VSBfqh3Ogt/lYaoq7pvQzrPMuqVMfLR0juSt24D+oBwDuUWFonJ1koMEOR+ob1Tr90Wq2JM1gi51yVTdyfmNdroud3zgHeIHGdN3XrX0w7lGhVJzK5vRl6C/a7ncdLPud4qwl7uPHyFy+oUVnizkUo9Hx/zkgRW1kCqKiKA8Bm1RV3WPnb5NVVV10sQxqZzbU1XPueAKHx2Gs0LP3kXctr68cvHYem8xPW/WJjSLG8urLVA6YX3EWcnUCPebcjUuANzUlZZSknWLHLXPRuuuIWfggnl0iQFE4+8UvnHjb9ET7EfvnXKyojXriuXns2L2XoqISAvx9mXTPHdx03ahL/p6NPes/STYgKZ7OL91let3UsvWcWvANkU+OpXTPMfJWpaDROdNj8cN4RkdSU3SetIkLLNNUB+xYjJOXO4qLEzXFZaSOm42htIJBqe9SdvgsRvPDhs5+uJIsq1sPag3P/qreZ5fbr73up//quTh5uaEaVQxllWy54jEM5yuIXzqDA9Pes3QU+nz9LCcXfUf++gshqXF1putLd+OT0AVFUag4k0NqnScJg+lez25zxuMS4E11SRmlaafYfYspLkJvGkzklDGA6SrgUfMrpwKS4ujy0l2g1ZC17BdOLviGqCdvpmTPcZtt4xXdgeqi86RNXGjZNh2m3kDYP4ai1hg58swn5Jufzt7nu+dx9vPCWGPgyHP/pnBjWr2yGqwmE3Uz7yuGCj37H3nX8paFxLXzLE9H9o6NopflNUqpHDLvK85+nsS8PxXXiAAqz+ax574F1BSV0XbCKNredZXpnuzKKtKf/ZTinYcB00DdFSmL2dRvCqr5AauXsx56LH4Ir14dUFWVyjO5HHr8fSpziujw8GjCbh6CWmPAUFnFkagcKggAACAASURBVBc+s7z2LHHtfNOAhLuOhG+fNz1AUaOhYOM+0p/9NxhVnP296DZvAh6dI1C0Woq2HuTgk/+qV/dt702mw0OjcQn2pTqvmLy1qRyY9h66ED96vvUgLiF+5itp3+LbtwsBw2MxVFRx4JF3rLbNfMvTzb1jo+j51iQ0rs7krU21vKrR2c+T6Pen4hYRSMXZPPbe9yY1RWW4BPnY3R/c2gXR861JKFoNikbDue9+4/gbX7dYjPj07UyvtyaBqnI+/Sz7H33P5pV6AH4De9DrrQdMcdSMdWBapwl267ZW2Lgr8Y6NIn3mR7gE+RD36XQ0OifTdt+8H0WrIWBobLPWibWeCx8kb80usn/Yhv+QaLq+cLtl3l/m8g20v++ai7ZpSRmfU3k2F4P5LRqm16z9p5nbNJX8n3dzzNKmtc7xxrZNs79tW2K/cQnwIvajxwHTYOS5bzZzYsE3BJrbNFM9/MKJBd/Q0dym5ZrroZdVm7Zv4kLLLMnIqTcQbm7T0s1tmm+/riR8/yKlB06B0dTtOTpnGXlrU4n5YBoencJRjUYqz+Zx8In3qTxXZFUfzb//NhSrPn270OO1e01l1CicXrKCc5+vM8dG87fzGncdg1P+yeZ+kzGU2k757r7wQUpSjpDxb/OMBHcdV5jT1pjTtrnzKlNM/fvnRo8Bbe+7mojbTFd4DWWVpE1aTMUp22tiDcWI4XwFGjt5X84YUZy19FzwIF69OmCsquHwC59aBnNGZH+JMFkdcovl59bsG9WUVtDQaV33ueMJMpdrn1W5Bq6dZ3mbhHdsFNGW10+mctBcrmCr85vaNn3nLXMJ+Vs/Oj15M2qNAdWocvTV5eSu3gXYXjVuiTrp8PBowm++AmONAWNlFYdfWErR9nTCbhpMz4UPcD79wiuxvXt1iAcc89V3zUC/f+0lPpr88tP1TFIunuryanSwoTk0NNhwuf3RwYbmYm+woTU5wmDDmpBxrV0EoJVezdIAA47RVmhxiN23wYP6X5nqIDGiOEiMgNRJXY6y/4LjtGmOwlFiFRwnTqSdt08GGy6wHmxobY4Sr47Udx2Z/YXjNGwtQAYbfp8mxaiiKDcriuJl/nmWoihfK4rSu2WLJoQQQgghhBBCtLLWfq3l//irL59RVbVUUZTBwFXAB0DD750TQgghhBBCCCHEX1ZTBxsM5v//BixRVfVHwKWR9EIIIYQQQgghhPiLutirL2tlKIryHjACmK8oig7Huk1ICCGEEEIIIYRofg76tgdH19TBhrHAA0AacDuQAjzRUoUSQgghhBBCCCHEn1dTZyfcC0wAAoFgYAnQraUKJYQQQgghhBBCiD+vps5suBfor6pqGYCiKPOB34C3WqpgQgghhPh/9u47Poqif+D4Z+8uvZHeaKEECL13KREFbCAqClYUVFREkCICKiIgKiIWioroY0H92R4VKQ+CIhB67zWUBNJ7v9vfH5ccudRLcpcc8n2/Xr4kd7M735ubmd2bnZ0VQgghRF1TVX3liUQpls5sULi2SCSF/7a753gKIYQQQgghhBCi7lk6s+EzYIeiKD8V/j0M4+MvhRBCCCGEEEIIIcxYNNigquoiRVE2A30KX3pMVdV9NotKCCGEEEIIIYSwB6o8jaI6LJ3ZgKqqe4G9NoxFCCGEEEIIIYQQ/wIWDzbYbQYW2tJ6el2HAEDfIwvqOgRxHdCi1nUIACh2Eoc9LRFjL99Nnp2UiaOdlAdAgZ2UiShNbyffjSP2cWXKnuqq9PPm7KWPF6XZR+s1snTRO1uzn/YrRNnspa0IIYQQQgghhBDiX8JeJh4IIYQQQgghhBD2x2BPc2uuHzKzQQghhBBCCCGEEFYlgw1CCCGEEEIIIYSwKrmNQgghhBBCCCGEKI88+rJaZGaDEEIIIYQQQgghrEoGG4QQQgghhBBCCGFVchuFEEIIIYQQQghRHoO+riO4LsnMBiGEEEIIIYQQQliVDDYIIYQQQgghhBDCqmr1NooWbzyCf2RH9Nm5HJ6wlPRD50ul8WgXRpslT6N1diR+4z5OvPy5MdB6brRf8TzODfzJuRjPgbHvUZCaCYB3rwhavP4wGp2WvKR0dg+fg1OIL20/GI+jnxeoKjFf/o9LH/9hlpfPgPY0n/sYilZD7FcbiX7/F7P3FUcdER88i0e7JuQnp3Nk3GJyLsaj83an7aeT8OjQjCurN3NyxkoANC6OtPl4Ei6NA1H1BhI37OHM3K+tWoYz5y3i76078fGux89fLrPqvuuS8Tt8BEWnJT8pnd3DXyudpk9rwl95CI2jjrQDZzn6wjJUveUrwwbc0YOmL96DW3goOwe/TNqBs6b33CMaEvHWWLTuLmhdnVDz9aBRiPnqzzLrResPnjHVi8Pj3iPnYjwAjSYMI2TUAFS9gZMvryJp8wFcmwbTZsVE0/YujQI4u/B7Lq5YQ5Np9+E3uAsYVPISUjk6YSl5V5NNaX0GtCd87qMoWo1VYgFoMHYIIQ9GAhDz1Z9cXLHGVD5hheWza/DLpBcrn+Ks3W4AOv74Co6B3hhy8gDYP3Iu+QlppvcjFj+F/6BO5CWksb3fi2XGZUkdKo+DtzvtPp2EZ4emxKzezIkZn137PA5aWs4fg3evCDConJ2/mvjfd9i8TIq0/WIqLo0C2FnO5y6p1RuP4BfZEUN2LocmLCWtjH7Ws10YbZc8jcbZkYSN+zhW2M8G3tGdZi/eg3t4KNsHzzS1keARvQkbf4dpe4+Ihmy7+SXSj0SXG4ctyqT9NzNwDKyHotWSuuM4J6Z/Aga1zPxtcbzx7hVBh89fJPtCHABxv+/k7KIfr+1Qo9Br81s4h/iQHW1M49IogDMLv+dCYTsDaDT+DoJH9DGWg06LW/NQNkc8QUFKZrnlWVxN6qu9HfdsUV8dvN3p8OkLeHVoyuXVf3GsWPmUxRZ1NXB4bxo9PxxUldwryRx95n3yk9LLzL82z400Tg50/eUVNI4OKFoNV3/bQfRb39VKmRQpr0+rrJ93bRZC6/eexrNtGKfnryZ66W9llmd5Kmo3nX+cjVMFxyBblEltnDPeSOqyL7FFG248/naCCo8TmsLjxKaIsRSkZNLwyaHUHzUAgIxjFzjy/FIMufm0eONR/ArjODJhKemHzpUZR+sl49EWlsGJl1eZ4mi3YiIuDfzJvhjPwbGLKUjNrLDdNRg7hPqF55OXv/rTgm/pOidPo6iWWpvZ4BfZAbewYP7pMZGjL35MxMInykwXsfBxjk5ewT89JuIWFozfwA4AhD13F4lbDrO15wskbjlM2HN3AaDzdKXVgjHsf/gttvWbwsGxiwFQC/SceOU/bLvpRXYMnUX9x27FNTz0WkYahRYLHufAqHns6PsCAcN7m78PhIwaSEFKJlE9JnBx+e80nTUaAENuPmcXfMvpV/9TKv4LS39lR58X2HXzVLy6tsCnMH5rGTZ0EMsWzbXqPuuaztOVlgseZ//DC9ne70UOjH23dCJFoc2S8Rx68j2293uRnEvxBI/sV6V8Mo9f5MCYd0jefsx811oNbT58luNTPmHHgCkA7Bs1n6i+kwgc3hu3MupFfkom23s8z8Xla2g2axQAbuGhBA7rRdRNk9n/wDxavDkGNApZZ2LZGTnN+N+g6eiz84hfsxOA6A9/ZeeAqeyMnEbChr2ETR5xLSONQosFY9hvxVjcWjYg5MFIdg2ewc6BU/Eb1AmXxoEAZBy/yKEx75BSonzM2KjdABwdv4RdkVPZFTm11ElezOq/2Hv//HLDsqgOVUCfm8+ZBd9yqozYwibeTV5CGtt6vcC2vpNJ2X7UPIENy8R/aDf0mTkWfw6/yA64hgWzpcdEDlfSzx6evIItPSbiWqyfzTh+kf1jFpG8/bhZ+tgftrItcjrbIqdz8NkPyb4QX+FAg63K5PDYd9k1cCo7+03GwdeTgDt7llsOtjjeAKTsOE5U5HSiIqebDzQAjcYOIf1INMlRx4iKnEZUYXuPK2zvRaI/+tX4fuQ0Tr3xNcnbj1o80ACW19cdfSeZ11c7O+7Zqr4acvM5teA7Trz6ZeVB2KBMFK2G5nMfZd/dr7FzwBQyjkZTf8zgcsugNs+NDLn57L77dbYPnMb2yOn4DeyAZ+fmNi+TIhX1aZX18/kpGZx4eRXnl/5abpqKVNRuAA6Pf5+oyGllHoPsre0Ic3XZl9iqDZ//6DfTsebUG9+YjhNOQd40emIwUbfOYFu/KaDREDisV2EZBLG1x/Mce/FjWi18vMw4Wi18gmOTV7C1x/O4hgXha4pjGElbDrO150SSthymcWEc5bU7t5YNqP9gJDsGzyCq8HwSaFZuQYkbVq0NNvgP7kLM938DkLrnNDpPVxwD6pmlcQyoh87dhdQ9pwGI+f5v/Id0ASBgcBdivjVuH/Pt3wQUvh58d2/i1uwk53IiAHmFB4i8uBTTyKI+M4fMU5dxCvIx5eXZqRlZ566QEx2Hmq8n7udt+A/uahaP3+AuxH63GYD4X6Pw7tMGAENWLqk7T2DIzTNLb8jOI2XrEQDUfD3ph87hHOJbzRIrW5cObfHy9LDqPuta0N19zL7DUgd5wMHHHUN+AVlnYwFI/OsQgbd1B0Dj6kTE4qfotvYNuv9vAf6Du5SZT+apy2SdiS31um//dmQcvUDG0WhjvTgTS875q6j5eq7+vA2/EvXCf3AXYr/7C4C4YvXCb3BXrv68DTWvgJwL8WSfu4pnJ/N+16dvW7LPXyXnUgIA+oxs03taV2dQr12l9ezUjOxzV0111BqxuDUPJW3vKQzZeah6A8nbjuJfWI5Z5ZRPcbZoN5ZIiTpGfkpGue9XVIeCRvSh29o36LHxTVq9NRY0SqntDVm5pOw8gT43v9R7oQ/059ySn41/qGqpq5O2KhOtqxMNnrqd8+/+UO7nLimwRD/r4OmKU4l+1qmMfjawsD/NPBVDZiV1IHh4b2J/3lZhGluVSVF7UXRaNI46s/ZSnK2ONxVxCvbBb1Ans6s7Jdt7WYKG9+bKT1uv/W3D+mpvxz1b1Vd9YfkYyiifkmxSVxUFUNC6OgGg83Al92pSmfnX9rlRUfmAcRaMotOWakd11adV1s/nJ6SRtv+MceZhCTVtN5Wxt7YjzNVlX1Ibx5ug4b2J/enacVfRatE4O6JoNWhdHcm9koz/4K7EmuI4hc7TrYI4TgEQ+/3fBAzpeu1zfPtXYRx/mV4vr925NQ8ltcT5JHB3uQUlbli1NtjgHOxjOugB5MQm4RzsUzpN7LUDck7MtTSO/l7kxaUAxoEER38vAFybBqPzcqPLj7PpsX4ewff2LZ13A3882oSRtve06TWnIB9yY67FkxuTaDYYAcaTx9zCmFW9AX16Fg4+lv3Q13m64ndLZ5K2HLIo/Y3MtWkwDl5udP5xNt3Xzyf43ptKpclPTEfRavFs3wQwTnlzCjUelJtMHE7SlsPsHPwye+6eQ/PZo9EUnuRZln8IqqrSYfUMWn/0HDovN9N7xnrhbZa+ZL0oKKwXTkHe5F6+9qMiNzYR5xJ1KnB4L64W+2EB0OSlkfTe+yFBI/pwduG16azOQT7klKqjNYsl4/hF6nVvic7bHY2LI343d8Q51PKTG1u2m1bvjafrxoU0fmFEpWlLKq8OuTUPJWhYL3bdPpuoyGmoegPBI0r3EeXReboC0GzafXTfsIB2H7+AQ2HfU8RWZRI2/X4uLP0VQ7blgzNOwT5kl+hnnYJLx1Kyny2ZpiLBd/UktkQdLhWHDetJ+9Uz6HPkYwoyson7NarMNLY63gB4dW5Ozz/fpNPX03FrUd/0esvXH+HknK9Qi93WETS8l9lAQkkaF0f8BnTg6m/G2xysXV/blKiv9nbcq436WmkMNigTtUDPiWkf023z2/Q+uBy38FBiypliXCfnRhqFHhsX0P/IChL/OmR2bmSrMoHq9WmWqGm7KRLx3tP02Phmmccge2s7wlxd9iW2PN5A0XGivek4kXslmfNLf+OmvR/S7+AyCtKySfrrIE7B3iXiSLQoDqdgb4viKCmz8HzSodj5JNCgwo2udwaD/f9nhypcs0FRFC3wBFAfWKuq6tZi781UVbXu5vMXjsQX/QDdc89cNM6OdPt9Dql7TpuugGtdnejw6QucmrXK7CqyLSlaDa2XPc/FT/4gp/C+XVE+RavBo30T9tzzOlpnR7r9/jqpe06ZvsMih556j/A5D6NxciBx80EoXK/Bt187/G/tQuPCe8o1To64hPqReeqyxfl7d2/Jrltn4NO/HeFzHsG7bxuStxy27ud00OJ3S2fOvPGN2etn53/L2fnf0mjCMOqPGcy5t763ar7FZZ26zPkP/kvHb19Gn5VL+uHzVVr3wlaOjF9C3pVktG7OtF05maB7b+JK4Qi9JcqrQz592+DZLozu6+YBoHF2JC8h1fL96rQ4h/qRsuskJ1/5Dw2fvI3mrzzE0Wc/qPJnrAr31o1waRzI6dmf49zA36Z5VYVXp2bos3PJOH6pzmI4cP88NE4ORHw0Ae8+bUj+uxZOzguPN2kHz7Gl87Pos3Lxi+xAh1WT2drzBfwGdSIvIZX0g+eMayVgbO/+t3TmdIn2Xpz/LZ1J2XXCdAuFtetr4yeH1kp9BTnuFafotIQ+egu7IqeRHX2V8HljaPz8cM6/+2PlG9eUJedGBpWoyOnoPF3psGoybi0bkHn8ok3DsmWfVtN2A8ZbKHILj0EdVk6q8jGoJqTtCDMlZhqVPE7ovNwIGNyZLV2foyA1i/afTDSt7WDLOErKLDyf7FTsfLJel3B5NqQopbIFIpcDrsBOYImiKH+pqjqp8L27gTIHGxRFGQeMmz59uv+zG+bgoXEkbf8ZsyuoJUfXoPRooHPItTR58ak4BtQzjrYF1DNNCcyJTSQ/OR19Vi76rFySo47j0bohWWdjUXRa2q+cROwP/5jukS+SeyUJp2LT1ZxCfMm9Yh5PbmwSTqG+5MYmGacqebiWu8BTcS3eeZKsc1e4VGxBMFG+3KvJJG46gCErF0NWLslRx3Bv3ajUYEPq7lPsvutVAHz6tcO1SbDxDUXhwJh3St0CELH4aTzbNib3SjL7Ri8oN/+c2CSStx8jPymd7AtxFKRn4dE2jOQthwvrRbJZ+pL1QldYL3KvJOMU6mdK5xTsS06xOuUb2ZH0Q+fIiy/7JOjKD1vo8PVLpsGGnCtJZlMqrRVL7NebiP16EwBNZ9xPTkzZ03vLYqt2k1f4ufSZOVz58R88Ozar0olebmwSickZpeoQikLMd3+X+sHnP6QrTV+8B4Cjk5abLRZaXH5SOvqsHOJ+N/YfV3+NIrRwUSZT3jYoE68u4Xi2b0LPXR+g6LQ4+nnR8cdX2Hd36UUvGz52C/UfHAhA6v4zuIT6klL4nnOwD7mxpWMp2c+WTFOe4GG9zKZylseW/SsY76NNWLsL/8FdTYMNoY/dSnDhQlW2Ot4UH7BO2LifVgsex8HHg3rdwvG/tTN+kR3RODugc3eh07cvV9jeAYKGlZj5YOX6GvdrFMGjBpret4fjXm3WV0vYokzc2zQGIDv6KgBx/91Ow2LrftRGXa3o3KhIQVoWSf8cwWdAB7PBhrru06qshu0GMB1byzsG2UPbEebqsi8pnret2nCRoGE9zY67vje1IetCPPmJ6TR47BY82oZRr1sL4v7YVSIOX4viyI1NtiiOssR8vYmYwvPJZjPuBzhZ6UbihlPZbRTdVFUdparqYqA74K4oyo+KojgBpW+IK6Sq6gpVVbvMnz+/0ZFBs4mKnE7cH7sJKZza7NW5GQXpWabpOkXy4lIoyMjGq7PxPveQe28ifu1uAOLX7SFkpHH7kJE3EVf0+trd1OveEkWrQePiSL1OzUxXtFu/+ySZpy4Tvbx0B56+7wyuTYJxbuiP4qAlYFgvEtbtNkuTsG4Pwff1B8D/jh4k/3OkkuKCJtNHovNw5dTMVZWmFUbxa3ZRr3sL03fo1al5mbMSHPw8AeOKz42fu5NLX2wAIHHzARo8fm3xLY/CE72jE5cSFTmtwoEGgMRNB3Bv1RCNiyMZB8/hFOxLfnI6ioOWwDLrxW6C7zMuThlQrF4krNtN4LBeKI46nBv649okyGx6atDw3lwt8UPNJSzI9G//wV3JKva5jXU0yFRHrRVLUTk6hfriP7QbV3/8p8LyKc4W7UbRakxTTRWdFr9Bncmo4lU2Yz9Qug4lbTlE4O3dTZ9ZV88N5/p+xP+xy7RAX0UnoADx6/fi3dt4tdqnbxuyTppf1bdFmVz+fANb2z/F9q7PsvfO2WSdjSn3pPzCZ+tNizeW7Gfz07PILdHP5pbRz15du7vUfktRFILu7FHpeg1gmzLRujqZ7j9VtBp8B3Ui8/S19nL5s3WmxbRsdbwpPq3Us2NT0CjkJ6Vz+o3V/N3xGbZ0fY6DTy4haeth8uJTuVLBwIzOwwXvnhGmfQNWr6/eJeqrPRz3aq2+WsgWZZIbm4RbeH0cfI39mne/dmZ9e23U1fLOjRx8PUy322icHfDt146s0+bH27ru06qqpu3GkmOQPbQdYa4u+5ILn623eRsG43HCp2eEKS1AzuVE6nVqhsbFkYufrSd56xHOvvMD8X/sMt1C6tW5eSVxGBeFDb73JuLX7iqMYzchhQuvh4zsZ5ZneYranHOoLwFDuwHI41REKYpawTQZRVGOq6rassRrs4FbgQBVVZuXveU16wPvN2XQcv5j+A3sYHwky/PLTJ1/j40LiIqcDoBn+ya0MT2WZj/HCx8z4+DtTruPJ+Ic6kvOpQQOjF1smlLUePzthNzfH1SVS1/9yYUVf1CvWwu6/foa6UejUQ0qCnB23jckbtxnis03siPNX3/E+FjBbzYRvfgnwqbeR/qBMySs22OcqvvBs7i3DaMgJYPDTy42TXHruesDdB6uKI46ClIz2T9yLvr0bHrvX0bmyUsY8goAuLRyLbHF7tXse6TiH76VmfLKAnbtO0hKShq+PvUY//hDjLjj1mrvz8GvSY3isYYNgSNpNP4O03d4+as/TY+J6/jVdI5OWk7u1WSazx6N36DOKBqFS59vMKXRODvQ4vVH8eoajqIoZF+MY/+DC0vl4z+kKy3nPYajryf5aZmkH45m3/3GaZdBI/oQNmEYYJwa5hHRELQaYr/ZzPnFP9Fk6r2kHThrVi882jYmPyWDw0++Z6oXjScOJ/iB/qgFBk7N+pzEP/cbY3R1os+eD9na7Tn06deujrb9dBKuzUJQDQZyLiVwYsrHZrMXfCM7EP76I1aNpfMvr+Lg7YGhQM+pV74w3S7iP6Qr4YXlU1BYPgfuf6NUOVq73eRcSqDTz6+hcdCCRkPylkOcmv252SMNI5Y9j3evCBx8PMiLT+XMW9+j0WkBuPTF/wDKrUOBd/U0frcaBTVfz/GXVpoWRyquz673zWLbO/INMk9exrm+H20+eBadlyt5iWkcf/4j0325tiqTrJPXTv6dG/jT7stppR4Tl1fOWHGr+Y/hX9jPHirWz/bauIBtxfrZtqZHcO03Pc4rYEhXIuY9atZGdheuDu/TK4LwmQ8QNXSWWX6OlH0bjrXLJD85g/b/mYbGyQE0Cslbj3B61udmtwEVFCsTWxxvGoy5lQaP3Gy8HzsnjxOz/0PqbvMLOd69Imj87B14dWzG1m7PUVDY3us/fDNwrb4Gj+yH38AOHHryPbPtrVlf8xPTOFaivtbFcQ9qv7722/U+Wg8XNIWx7ho5j8yTl8usr7ZovyEPD6LB2CGoBXpyLiVwdMKHFCRfW/zQ1nUVyj43co9oSJslT6NoNSgaDVd+2c6FRf9XK2VSpLw+rbJ+3tHfi+7r56PzcEE1qOgzc9jWdzL6jOwatZvsSwl0/flV44KZ5RyDbFEmlradgVdLP5r0RrU28P5y36vtvqR4j2arNhwysh++A9tz6MklZp+16ZR7CLqrJ6reQNqhcxydtBw1r4CW88fgO7A9+uw8jj6/tFgcbxIVOc0UR+sl49E4O5Cwcb/pEbAO3u60/XgiLqF+ZF9K4ODYdylIyayw3XUpPJ9UC/ScfOULOv/frHIvRP8b5Gz/puJ7S+yAc88H7O47qGyw4UvgS1VV15Z4/QlgqaqqDpVlUHywoS7pyjkhrm01HWywNnsZbLAHtbZa6nVEwS6aL/ryJ1LVOq2dlEl5P95qW3mDDXWhwE7KxF7ajb3UVZD6WpK91FWwn/Mje+nn7andgAw2FFfRYENts5cWbC/HG4BBV7+1j0ZsIzLYUD0VthVVVR8sOdBQ+Ponlgw0CCGEEEIIIYQQ4sZj0cCcoij3KoriUfjvWYXrNnS0bWhCCCGEEEIIIUQdq+vHWl6nj760dBbQLFVV0xVF6QNEAp8Cy2wXlhBCCCGEEEIIIaxBUZTBiqKcUBTltKIo08t4v6GiKJsURdmnKMpBRVGG1jRPSwcbip6behuwQlXV3wHHmmYuhBBCCCGEEEII21EURQt8CAwBIoAHFEWJKJFsJvCdqqodgfuBj2qar87CdJcVRVkODALeLHz0pb2sjSKEEEIIIYQQQtiGnd6mUAXdgNOqqp4FUBRlNXAXcLRYGhXwLPy3FxBT00wtHWy4D3gKOAw8COwBptQ0cyGEEEIIIYQQQthUKHCx2N+XgO4l0rwKrFcU5TnADbi5pplaOjvhCWAM4AcEACuAljXNXAghhBBCCCGEEDWjKMo4RVF2F/tvXBV38QCwSlXV+sBQ4D+KotTobgZLZzY8AXRXVTUTQFGUN4HtwJKaZC6EEEIIIYQQQtgzVdVXnqiOqaq6AuOkgLJcBhoU+7t+4WvFPQ4MLtzXdkVRnDFONoirbkyWjlQoXFskksJ/K9XNVAghhBBCCCGEELViF9BcUZQwRVEcMS4A+d8SaS5gfPIkiqK0ApyB+JpkaunMhs+AHYqi/FT49zCMj78UQgghhBBCCCGEnVJVtUBRlGeBdYAW8Q9hWgAAIABJREFUWKmq6hFFUeYAu1VV/S8wGfhYUZQXMC4W+aiqqmpN8rVosEFV1UWKomwG+hS+9JiqqvtqkrEQQgghhBBCCGH3rv+nUaCq6hpgTYnXZhf791GgtzXztHRmA6qq7gX2WjNzIYQQQgghhBBC/PsoNZwZYQmbZyCEEEIIIYQQos78q9fzy9680u5/07r0H2N334HFMxuEEEIIIYQQQogbjnr930ZRF2r03EwhhBBCCCGEEEKIkmSwQQghhBBCCCGEEFYlgw1CCCGEEEIIIYSwKlmzQQghhBBCCCGEKM+/4NGXdUFmNgghhBBCCCGEEMKqZLBBCCGEEEIIIYQQViW3UQghhBBCCCGEEOWRR19Wi8xsEEIIIYQQQgghhFXJYIMQQgghhBBCCCGsSm6jEEIIIYQQQgghyiNPo6gWmdkghBBCCCGEEEIIq5LBBiGEEEIIIYQQQlhVhbdRKIriCjwLqMD7wP3A3cBxYI6qqhk2j1AIIYQQQgghhKgr8jSKaqlsZsMqIBAIA34HugBvAQqwtLyNFEUZpyjKbkVRdq9YscJKoQohhBBCCCGEEOJ6UNkCkeGqqt6nKIoCxAI3q6qqKoryD3CgvI1UVV0BFI0yqNYJVQghhBBCCCGEENcDi55GUTjAsEZVVbXY3zKIIIQQQgghhBDi302eRlEtld1GsVtRFHcAVVXHFL2oKEpTIN2WgQkhhBBCCCGEEOL6VOHMBlVVnyjn9TOKovS1TUhCCCGEEEIIIYS4nln06EtFUe5VFMWj8N8zFUX5Eehg08iEEEIIIYQQQghxXbJozQZglqqq3yuK0ge4GeMTKZYB3W0WmRBCCCGEEEIIUddkzYZqsWhmA6Av/P9twApVVX8HHG0TkhBCCCGEEEIIIa5nlg42XFYUZTkwElijKIpTFbYVQgghhBBCCCHEDcTS2yjuA54CDgMPAnuAKbYKSgghhBBCCCGEsAuq3EZRHZbOTngCGAP4AQHACqClrYISQgghhBBCCCHE9cvSmQ1PAN1VVc0EUBTlTWA7sMRWgQkhhBBCCCGEEOL6ZOlgg8K1RSIp/Ldi/XCEEEIIIYQQQgg7Ik+jqBZLBxs+A3YoivJT4d/DgE9tE5IQQgghhBBCCCGuZxYNNqiqukhRlM1An8KXHlNVdZ/NohJCCCGEEEIIIcR1y9KZDaiquhfYW9UMNgSOrOomohYNuvptXYdAfsLZug4BgM2tX6rrEEQ5+h+ZX9chmEg9EZWxl/oqdVVcT6TdlM0eztPsifyusF//+roqT6OoFkufRiGEEEIIIYQQdUIGGoS4/shggxBCCCGEEEIIIazK4tsohBBCCCGEEEKIG448jaJaZGaDEEIIIYQQQgghrEoGG4QQQgghhBBCCGFVchuFEEIIIYQQQghRHnkaRbXIzAYhhBBCCCGEEEJYlQw2CCGEEEIIIYQQwqpksEEIIYQQQgghhBBWJWs2CCGEEEIIIYQQ5ZFHX1aLzGwQQgghhBBCCCGEVdl8ZoNrsxBav/c0nm3DOD1/NdFLf6swfYs3HiXkgQFsavJIlfJpMOZWGo4bimtYEJtbPUF+UjoA/oO70HTafWh0OpxCfdE46jj9xjflxtHll1fRubsA4OjnSeq+Mxx49G2L4wi4owdNX7wHt/BQdg5+mbQDZ03vuUc0pNVbY3EKqIdjQD2yL8SRn5DG7uGvldqPd5/WhL/yEBpHHWkHznL0hWWoestH1CyJo+hzXu9mzlvE31t34uNdj5+/XFbt/TR8ciihowYCkHHsAkeeX4ohN9/0fvDIfoTPfpDcK0kAXFy5jstf/Wnx/strC04hvrT54Bkc/bxAVbn05UYufvyHxdtbysHbnXafTsKzQ1NiVm/mxIzPANC4ONLu4xdwbRyIqjcQv2EPp+d+A0CfXe9TkJkDegNqgZ4dt84w26d3rwjafz6FnAtxAMT9vpOzi36ocUzFdfhiCrp69SlIuVSlz1ucteoIgM7TlYhFT+LesgGqCkdfWErq7lPX3vdyo/Xip3BpHIghN58jE5eRefxilfJoPGEYoaMGoOoNnHh5FYmbDwDQYOwQ6j8YCYA+MweXRgHkJaSxvd+LpeP0cKHNR8/hHOqHotUQvfQ3YlZvtjiGqtTXxE0HLKqbtuzXuq2fj2ebRqgFBvY//JapzIoEjehD42fvBEVBn5HNsamfknE02uK8K6qrHb95CadAbxSthpQdxy3eZ3msVV8jFj+F/6BO5daRuuhTyuLZoSldf3+dQ0++R9xvOyzOvzp9qqWf2VZ1tXiZxf2xC9fGgRaVf9OXRhJ4Rw9Uvcqlz9dz8ZO1NY7F56a2NJ85CsVRh5pXgM7DhcwzMex/cKHZ9s71/YhY/BSOvp7kJ2dw+JkPyI1Nsjj/8spc4+RAl19eRePogKLVoHF1x5CVbPF+S6qtdlPTPt7S455Lo8Ay87/RNRp/B8Ej+gCg6LS4NQ9lc8QTFKRkmqVr/d7TePeKoCAtC4DDEz4i44jlfX557cazY1Mi3h5nTKQonHnre+L/2GXazrtXBC1efwRFpyU/Kb3Mc/zyVOU4c2z6p2BQK62vtXWe5tIo0OJ9ihuLzQcb8lMyOPHyKvyHdKk0rWf7Jui83KqVT8rOE8Rv2EuXH2ebvZ709yHi1+7Gwc8Tn75taDlvTIX72X3Xq6Z/t/t0EvFrd1cpjszjFzkw5h1avTXW7HVFq6HNh89ybOqnRLwzjp1DXibj+EUcfDxK70RRaLNkPHvumUvW2ViaTr2X4JH9iPl6k9XiOPzMh2QcjWbQ1W+r9Pns0bChgxg14k5mvG75oFApGi0NnxjCtr6TMOTk03bFRAKH9SL227/Mkl35ZVuZHa0lymsLaoGek6/8h/RD59C6OdN9w3yS/jpI5snLFm1vKX1uPmcWfIt7ywa4tWxg9l700t9I3noExUFL5/+bhe/ADiT+uR+APXfPMQ3elSVlx7FSJ6fWiAkgYGg342BHDVmljhRqMfdREjcd4OAT76I4aNG6OJm9H/b8MNIPR3PgsXdwbRZCywVj2HvPXIv37xYeStCwXmy7aTJOQd50/n4mW3tOxC28PvUfjGTH4BmoeQV0/WMuRyYtp/mMB8rcT/0xt5Jx4hL7H1qIg68HvbcuJvaHLaj5eoviqEp9TT9wtvK6acN+zS08FAdPV3bePps2HzxDyzfHsLXnRDCopjTZ0XHsHvYaBamZ+A7sQMQ7Y9k5ZKbFeVdUVw+OXYw+IxswHjcURzfUvMyydmMRa9XXmNV/cfHTdbT54Jky36+rPsWMRqH5rFEkbT5Y5fyr06da9JltWFeLl5lHh6YWlX/I/f1xDvFjW+9JoKo4+HlaHEdFseQnpbP/oYXkXk2m2ezRNBxzK5lnYkptH/7KQ8R+9zex3/2Nd5/WNHv5AY48+6HF+ZdX5obcfPbcPQd9Vi6KTsvA8ytRdFmoBblV+nxFaqvd1LSPr63j3r9V9Ee/Ev3RrwD43dKJRk/eVmqgocjJ176s0gBmceW1m4zjF9lxy0uoegOOAfXouWkhf6/fg6o3oPN0peWCx9n3wDxyLidWua1W5TgTeGdPrv68rdL6CtfHedp1QW6jqBab30aRn5BG2v4zlZ/gahSav/Igp+Z8Zfayg68H7T6dRLe18+i2dh5eXVuUuXn64fPkXIwv9bo+K9cUR87FeFDVUmnKonV3wadPa+IKRys1rk5ELH6KbmvfoPv/FuA/uOyTg8xTl8k6E1vqdd/+7cg4egGP1o2IW7OTjKMXwKCSn5BWKq2DjzuG/AKyzhr3k/jXIQJv627VOKpyRc/edenQFi/PMgZtqkjRatA4O6JoNWhdHcm9YvkVlkbj76Db2nn02LSQJlPuLTNNeW0hLy6F9EPnAOPV6sxTl3EK8rF4ezBete229g16bHzTeGDUKKXSGLJySdl5An2x2RoAhuw8krceAUDN15N+6BzOIaXzr6qaxASgdXWi4VO3ce7dH2sci7XqCIqCd89Wphktar7edNWkiFt4fZL+OQxA1ukYXBr44+jvBVhWJv6Du3Ll522oeQXkXIgn69xVvDo1w615KKl7T2HIzjNeLf5jN16dw8uPVcU0e0nr5kx+SgZqgfFAae36qnF2rLSft2W/5j+4K5e/3kRefCpqvt5UZsWl7j5JQarxhDR1zymcgn1N79W0rhadACo6LRrHmo/hW6u+pkQdIz8lo9z37aFPafjEEK7+toO8hFSz123Vp1pyTmLLulq8zAw5eRadH9V/dBBn3/k/0/lL0XlDTWNJP3ye3KvJOAX74NkuzNg/KKVPC93CQ0n6x/h9Jv9zhIBi+dTke4Jr52iKgxZFKV3HqqK22k1N+/jaOu7dCIKG9+bKT1urtE2N23DhMRhA4+yAWux3RdDdfYhbs5Ocy4kAZuf4Vj/OFOZbWX2tiNRXURuqPdigKMoKawbS4PHBxK/bTV5citnrLeY+yoXlv7Nz8AwOPv4OEYuerPK+/Yd0pdc/i+j45XSLZyoEDOlK0pbDpsbdZOJwkrYcZufgl9lz9xyazx6NxtWpkr1c49o0BFVVafzsndR/6GZ671hC9/XzCb73plJp8xPTUbRaPNs3ASDwju44hfpaNY6Oq2fQfcMCi7f71zPoOb/0N/ru/YibDi6nIC2bpL9KX2kLvL07PTYtpN0nL+AUYvxOfPq1w7VJEDsHzyBq4DQ824dRr0eraoXh3MAfjzZhpO49bfE2bs2NV8J33T6bqMhpqHoDwSP6Vit/nacrfrd0JmnLYdNrnb59me7r5xP6UGSZ23h1DqfHnwvp+PV03FrUt1pMTaePJHrpb+iz86r1WWxC40BeYhqt33ua7v9bQMSiJ0u1v4yj0QTc1g0wTrd0ru+PU7CPxWXiFORNzuUE09+5sYk4BfmQefwi9bq3xMHbHY2LI343d8QpyLvcUC9+uha38FBuOriMnpvf5sTMVaCqdVZfbdmvlVdm5QkdNcB0ld1a7afj6hn0O7KCgozsGs1qsAe27lOKOAV5EzCkK5dWbTB7va77VFvW1epwaRRI0LBedF83j45fT8c1LMiqsbR4/RESNx0g82wsqKWv3KUX69MChnZD5+GKg7e7db4njUKPjW/S78jHGPKyqz2roTbVtI+viF0e9+yUxsURvwEduFrBzIVmL91Pj00LCZ/zMErhQLA12o1np2b0/Ottem5+m2NTPjENPrg2DcbBy43OP842O8e3xXHm6q9RFm93Q52nCbtT4SUYRVHKO1tTgKHWCsIp0JvAO3qwp4z7mnxvaot7eH3T3zoPF7SuTqbRcEvE/7GL+D92Ua9HK1oveZrMU5cr3SZoeC+z+/F9+7XD/9YuNB5/BwAaJ0dcQv0s2hcYr5p7d29J0t+HcI9oiKqqnH//F8JnjSZ1zynTFZQih556j/A5D6NxciBx80Eo7MisFceOW2egz84l8vx/LNruX0/REDC4C/90fZaC1CzaffICQSP6cOWHf0xJEtbv4cpPW1HzCgh96GbavD+ePSNex7d/O3z7taPHxjcB41Vk1yZBpEQdq1IIWlcn2n86iZOzPjcNclnCp28bPNuF0X3dPAA0zo6lrhJaQtFqaLtsAhc/WUt2tPHevl13zCb3SjIOfp50/m4mmadizD5X2sFz/NP5GfRZufhFdqDDqhfZ2nNijWNyb90I18aBnJz9Bc4N/Kv8WWxFUcCjbRjHZ3xG2t7TtJj7CGHP3cWZN78zpTm35BdazH2UHhvfJP3YBdIPnUfVG2pcJpmnLnP+g//S6duX0Wflkn74PIqjQ7npfQe0J/3wefbcPQeXxoF0/n4m26Om1ml9tVW/VhXevVsTMmogu+803nJnrfaz7/55aJwcaPPRcygOLqj5lrdhe2PLPqW4Fq8/yqm5X5eacVjXfSrYR10tonFywJCTz45bZxAwtBsRi59i912vWiUWv0GdUAv01H/4Zs4s+I6gEb1LpTn16pe0mD+GkJH9SIk6Rk5MIqreYJ3vyaASFTkNnacr/Y58BFoH0Je+gmpPbNXH2+txz17539KZlF0nyr2F4tQb35AXl4LiqCPi7XGEPXsXZxf9YJV2k7b3NNv7vYhb81Bavz+exD/3Y8jNR9Fq8GjfhD33vI7W2ZFuv79O6p5TNjnO+PRpQ9LfhyqP9QY7T7MpC2fHC3OVzfeMB6IxDi4UUQv/Dihvo6+++urrzp07DwPY4pVK31SvCjPxaNsY17Ageke9B4DWxZHeUe+xtcfzoCjsHDrTbKE+MI7uOfl7GRdumrS8zP3Wf+wW02Jq+0YtICXqGA5ebmgrGcF08PHAs2MzDjz2zrUXFYUDY94pNaUqYvHTeLZtTO6VZPaNLnumQP3HbqHB44PRubuQFX2VnNgk1AI9ro2DSI46hnvrRqUGG1J3nzKtH2G8ehBc4zgAcmKTSN5+rMJ78G9EioML2RfOkp9oLJe433dSr2sLs8GG/ORr09Quf7WR5rNHG7dVFM4t+YXL//mf2T5L1r/cq+XflqHotLRbOZnYH/4hbs3Oqu1DUYj57m9Ov2G+AJv/kK40ffEeAI5OWm62mF5ZWr0zjqxzV7iwYo3ptaJbSfIT0ohbsxOvjk3NTiSLn8AnbNxPywVa4zokNYypXpdwPNs3oc+u91F0WtA6oPUKRp9aekpjbVL1enJjEkkrvEp69dcdNH7uLrM0+oxsjk5cavq7z673yY6Ow7tHK4vKJPdKMs6hfqb3nYJ9TYuSxny9yXTfeLMZ9xuvJpS4XaBIyP39Of/+LwBkn79K9oU43JqHWK2+dls3D52HK00mjyB1z6kK0xexVb92rcxOAOZlVpx7REMiFo1j3wMLrrVnK7UfMN6DHr92N36RLa/rwQZb9inF65nO05W2yyYA4ODrid/NHVH1eqv3qY6B9Uw/iCvbroit6mrRZ9DVcydpS+U/FAByYxK5usZ49TZuzU4i3nvaKrGAcVAy4I4e5CemET7nYXTuLoXrOn1wLf+ryRwcYzwf0ro6EXBbdwrSsqzyPRUpSMtCzc9G4+iKIbvqP8JqU037eEuPe45+XnQusQ7Zja7HxjdNdSpoWK8Kb6Eomimt5hUQs3ozjcbfbnzDCu2mSOapy+g8XemxaSGG7Dyu/Hc7iZsOYMjKxZCVazrHt8Vxxn9wF4sGG2rrPM3RzwtgM9C/0qDEDaWywYazQKSqqhdKvqEoSrlL744ePXpU0b/7pnpVOgyU8L99/N322u0RA85+bhxoABL/OkiDxwebFoNxb92IjCPR7Lt/XmW75dJn60ncdIDs81cB4xVJRautdFZE4O3dSdiw12yAI3HzARo8Pti0OKBHm8akHz5vdsCpKI4rP26l8//NImHjflq8+hCqqnLxs3WEjOxH9PI1pbZx8PMkPyENxVFH4+fu5Nzin2ocB0DipgM0fuZONC6OqHkFFm1zQzAU4NWpORoXRwzZefj0bVOqg3UMqGc6ePnf2sU0Cp6w6QDNpt/HlR+2oM/KxSnIG0OBnkufrefSZ+styj7i3afIPHWZC8t/N3vdkn0kbTlEh8+nEL38d/IT0tDVc0Pn7mKa0WOJptNHovNw5egL1wbuNK5OKIqCPjMHjasTvv3bcfYd8xWMHf29yIs3nhh6dmwKGg35Sek1junS5xu49LlxarVzA3/6RC2q84EGAFQ9OTGJuDYNJutMLD5925B50vwpGTpPV/TZuaj5ekIfHEhy1HH0GdkWl4k+J4+2SycQvew3nIK8cW0SZJoCXtQvOIf6EjC0GwfHvkvQsF5lhppzOQGfvm1I2XEcR38vXJuGkB0dZ7X6mrj5ICdnfV6l4rNVvxa/bjdtl07g6m9RKA5aszIr4hzqS/uVkzn8zIdmg7s1rataVye07i7GK2haDX6DOtr9ldnK2KpPgfL7tNbvPU38hr3E/7EbfVae1ftUS7crYqu6WvQZgkf2M92mUZm4tbvw6d2amAub8e4VYfqRVNNYdJ6uePdoxaGxi4lbsxPvXhE0Gn+72UADGC/A5CdngKrS+PlhxHxjHPCsaV/i4OthWvdG4+yA4uiCIcu+Bxqg5n18eUoe9zp+OY09d8/5VyzkbS1RkdMA4yxn754RHCpRV4szO2cb0pWMwieG1LTdODf0J/eycXaPc30/dG7ObB8wlfykdNyah9Ji/mMoWg2Kow6vTs2JXr6GzBMXrX6cSYmy7MlHtXWe1vHLabi3bNDfoqDEDUVRK5gSoijKM8A/qqoeKOO951RVfb+yDP5qM07tvn4+Og8XVIOKPjOHbX0no8/IpuNX041X8kqMeg84+7np0ZcOPh60XDAGt+ahKFotKVHHODb1k1L5NHhiMI2fuRPHgHrkJ6SSsHE/Ryctp/Gzd5rumXJtEoRaoMeQr68wjs4/zub8+7+QuOnax9Y4O9Di9Ufx6hqOoihkX4wrc2VX/yFdaTnvMeMjotIyST98bWAkaEQfwiYMw8HHA0WnJS8uhctf/Wm66lM8juazR+M3qDOKRuHS5xtMaawZB4B7GSvL1rb8hMpHcisy5ZUF7Np3kJSUNHx96jH+8YcYccetVd7PhVV7CbqrJ6reQNqhcxydtJwmE4eTduAs8ev20OzlB/C/pTOq3kB+SgbHpn5C1mnjyt0Nxg4hdLTxsZn6zBwOj/+A7OirZvt39PeirLbgEdGQrr/OIf1otGn1/NPzviFh436LttdnZBN4V0/jd6pRUPP1HH9pJal7TlFSn13vo/NwRXHUUZCayd6Rb1CQns1N+5eScfIyap7xR9LFletI+ucw7T8zPkZJ0Wq48tNWzi3+ifoP3wzApS/+R4Mxt1L/kUGoegP6nDxOzv6C1N0nAWoUU/EncRQNNtTk0ZfWqiMAu+9bRutFT6I46siOjuPI80sJuqsnYCwTry7Nab1kPKiQceISR19YZlqY0NIyCZs4nJAH+qMWGDgx63PT+gJdfnkVB28P1AI9+cnGExsHHw/y4lM589b3aHRaUxxOgd60XvI0joHehVcgfzbN1LF2fT3/4X9pPmt0pf28Lfu1HpsWGm+50xpPpE7N/dqsPCIWPUnAbd3IuWRc26H4o1xrUlfzkzPo8J9paJx0KBoNSVuPEHxXBQt3WsBa9TVxSyzevSLKrSO13adU9KjgosGGopXjbdWnVvSZa6uumsrMSYfWyQF9Tj5qQfnnJTpPV+NjbOv7oc/M4diUT8g4Gl3jWMJeuJuwCXeRdfYKYLwNIjs6jr0j36Dp1HtNx76A27vT/OUHUFWVlCjjI/eKLlbU5HtyaehP6yXjjT/MNBpcGrhhyDZft6sqaqvdWKOPt+S41/HLaWzv96IMNhSzIXAkYHwUud/ADhx68j2z94u3m84/zMLB1xNFUUg/fJ5jUz5Gn5Vb43YTfE9fGj93F2qBHtWgcnbR/xH/x7X14BqNv4OQ+/uDqpqd41v7OHNy1ueoegNtl02osL7W1nla4WBDzVZ5tXPZ37xi9/dRuDzwmt19BxUONpgSKcq9wFpVVdMVRZkFdATmqqq6t7JtNwSOtPsv5kZmDwexmg42WMvm1i/VdQiiHP2PzK/rEEyknojK2Et9lboqrifSbspmD+dp9qJosEHYp0FXv7W7H7rWJIMN1WPp0yhmFQ409AEigU8By+YbCSGEEEIIIYQQ4oZi6QPBix6OfBuwQlXV3xVFmWujmIQQQgghhBBCCPtgKP1oYFE5S2c2XFYUZTkwElijKIpTFbYVQgghhBBCCCHEDcTSAYP7gHXAraqqpgA+wBSbRSWEEEIIIYQQQojrlkW3UaiqmgX8WOzvWMAOnkMnhBBCCCGEEEIIe2Ppmg1CCCGEEEIIIcSNR5U1G6pD1l0QQgghhBBCCCGEVclggxBCCCGEEEIIIaxKbqMQQgghhBBCCCHKI4++rBaZ2SCEEEIIIYQQQgirksEGIYQQQgghhBBCWJXNb6PQoto6C4uoKHUdgijH5tYv1XUIAPQ/Mr+uQzDJ//7dug4BACWkQV2HANhPHQEIdc+o6xAAGJJysa5DAOD4krvqOgST9JV/13UIgP3U1z4re9Z1CCZNRq+o6xAAOPvhiLoOAYDYBTvqOgST4Jm96zoEwI7azTz7OO6J0p4xnKnrEExUO/l946FzqesQTAbVdQC2ptrHd369kZkNQgghhBBCCCGEsCoZbBBCCCGEEEIIIYRVydMohBBCCCGEEEKI8sjTKKpFZjYIIYQQQgghhBDCqmSwQQghhBBCCCGEEFYlt1EIIYQQQgghhBDlkdsoqkVmNgghhBBCCCGEEMKqZLBBCCGEEEIIIYQQViWDDUIIIYQQQgghhLAqWbNBCCGEEEIIIYQojyprNlRHnQw2+AxoT/O5j6FoNcR+tZHo938xe19x1BHxwbN4tGtCfnI6R8YtJudiPDpvd9p+OgmPDs24snozJ2esLLXvtl9MxaVRADv7vWhRHOFzH0XRaoj56s8y42j9wTOmOA6Pe4+ci/EANJowjJBRA1D1Bk6+vIqkzQcAaDB2CCEPRgIQ89WfXFyxplbydm0aTJsVE03buzQK4OzC77m4Yg1Npt2H3+AuYFDJS0jl6ISl5F1NrrR8akvDJ4cSOmogABnHLnDk+aUYcvNN7weP7Ef47AfJvZIEwMWV67j81Z8W79+1WQit33saz7ZhnJ6/muilvwHgFOJLmw+ewdHPC1QVjbMLhpy0an+OmfMW8ffWnfh41+PnL5dVez9VtfV8Am/9dRyDQWVYm/qM6RpWKs36k1dYFnUGBQj392D+kHbWyfvEJRb+EoVBNTC8WwvGDGhv9v5b/41i15lYAHLyC0jKyOGfOQ8BMP6TtRy8EE/HxoG8P+aWSvOyl3qS8f0aklb9t9z9uN3UmaBZ41C0GpK/XU/i8u/N8+namsCZ43BuGcal598kfe1WABxC/Km/dCaKRgM6Lclf/EryN39YHH9lXp0/jQE39yU7O4cXn533djVrAAAgAElEQVTF4YPHzON2d+X731aZ/g4OCeSn739nzssLa5z31tOxLFy3H4NBZXjHMMb0aVUqzbojF1n+1xFQIDywHgvu7gFAbGomr/26m6tpWSgovD+qL6H13KoVh2PXbrg/8xxoNOSs+Z2s1V+bve9yz324DL0N9HoMKSmkvfUmhrirOHToiPvTz5jS6Ro2JHXuHPK2/lNmPvZSV7X6M+jP769wX1uPXWDhz/8Yv5serRgT2cns/bd+3squ05eBwjacns0/8x43vZ+Rk8fdb65mQJswXhrR1+LPUJbX35xB5KCbyM7OZuL4GRw6ULqO/vzHl6a/Q0IC+eG7X5n90gKefOYRRj10DwX6AhITkpn07EwuXYypcgz2UlcBXHp3wXfa0yhaDWk/riX102/N3nfu3BbfqU/hGN6EuKnzyNywxfSezwtP4HpTN9BoyN6+l8QFH1U7jq2nYli4Zg8GVWV4p6aMual1qTTrDkezfNMhQCE8qB4L7u0NwLvr9rHlZAyqqtKjaRBTh3ZGUZQy87GbdpOyB/2Rstu2qUzOxrFw42FjmbRryJgezUuXyfEYlm89AUB4gBcL7uhETGoWk37ahQEo0Bt4oFMY93ZsbPFnEJaZOe9F+t3cm+ysHKZPeJWjB0+USuPgoGP2gql0690Z1aCyaN5HrP/NWJ+G3HUzz00Zh6qqHD9yislPzaxWHLPmTTHFMW3Cqxw9eLycOKbRvXdnDAaVd+d9yLrf/mTG65Po0acLAM4uzvj6+dC5Wf9qxTHl9efpE9mTnOwcXpk4j+OHTpZKo3PQMX3eJDr37IhBNfDhghX8+ftfdOrRnslzJtC8VVNeeupVNv6+uVoxiBtX7Q82aBRaLHicfffNJTcmkS7r5hO/bjdZJy+bkoSMGkhBSiZRPSYQMKwXTWeN5si4xRhy8zm74FvcWjbEvWWDUrv2H9oNfWZOFeIYw7773iA3JpGu6+aTsG43mSXiyE/JZHuP5wkc1otms0ZxeNx7uIWHEjisF1E3TcYpyJuO389ke8+JuIXXJ+TBSHYNnoGaV0CH1TNIWL+H7PNXbZ531plYdkZOM+2/z4FlxK/ZCUD0h79y9s3vAKj/xGDCJo/gxNRPLCunWtDwiSFs6zsJQ04+bVdMJHBYL2K//csszZVftnFixmfV2n9+SgYnXl6F/5AuZq+rBXpOvvIf0g+dQ+vmzIBTH2PIzwZ9fjl7qtiwoYMYNeJOZrz+drW2rw69QWXBpmMsvbszge7OjP4min5N/Gnq625KE52cycpd51h1Xzc8nR1Iysq1Ut4G5v+0jWVjBxPo5cbo9/9Lv4iGNA30NqWZcmcP07+/2XqE45cTTX8/0q8dOfkF/F9U6YNvSU5B3nZTT3pvnEfGP/vIO32x9E40GoJffZroR2aSfyWBJj+9S/rGKLO0+THxxEx9F9+xd5vnH5/M+Xsno+YVoLg60/SPj0jfuIOCuKRqfZ7iBtzch7AmjejX9XY6dmnH3LdnMuyW0WZpMjOyGNr/PtPfv21czdrfNtY4b73BwPw/9rLswX4Eerow+pP/0a9FCE39vUxpohPTWbn1GKseG4iniyNJxfrxmT/v5Ik+rejZNIisvPxyf6hUSqPBY8JEkqdOxhAfj/dHy8ndvhV9dLQpScHpUyQ9PQ5yc3G54y7cxz1F2tzXyN+/j+QnnwBA8fDA94uvydu9q+xs/Pzspq72P7gYQ8IF1Iyy65DeYGD+j1tY9tQdxjb87g/0a92YpkE+pjRThvU2/fubLYc4fjnBbB8f/rGTTk2Cq/U5ihs46CaaNGlEr06D6dSlHQveeYXbbr7fLE1mRhaD+l5rN+s2f8+aXzcAcOjgMQYPuJfs7BweHjOSma9N5qkxk6sUg93UVQCNBr+XnyV23HQKriQQuvp9sjZtJ//sBVOSgtg44me9jdcj95ht6tQ+AueOrbk04ikAQr5YhHOXduTsPljlMPQGA/N/282yRwYay2T5Ovq1rE/TgOJlksbKv4+y6olbjGWSYSyT/Rfi2X8hnu+fGQLAY59sYPf5OLqGBZbOyMXDftrNvrcxXD6FmnK1zP3oDSrz/3eIZff1INDDhdFfbKFfsyCa+nlcK5OkDFZGnWLV6N54OjuSlGk87vq7O/PFg31w1GnJyitgxMrN9GsWRICHc7U+kyit3829adykAYO6Dad95za8tvAl7h38aKl0/8/efYdHUfQBHP/u3aX3fmlAEpr0XkINASkqVYqAIiAgFooIUsQGUm2IihXbiwooWEAI0rv0QOgtCem93yW5u33/uHDhSEIKJVHn8zw+ktvZnd/NzbbZmdnJ08eRmpJO7w5DkCQJZxdHAGoH+jNp6lhGPDKerMxsXN1dSqxb0ThqB/rTs91AWrRuwlvL5vB4nzGlxDGetJQ0Hu4wuCgO4761aP57pjRPPjOcRk0bVCmOTj06UCvQnwHBI2jaqjFzlrzMmEcmlkj3zNSnSEtJZ1DnJ5AkCaei8oiPSeSNqYt4cvITVcpfEB74nA2OreqSdz0BbVQScqGepF8P4tGnrVka9z5tiF+3G4DkPw7j0rkJAIa8fDKPXMSQX1Biu0pbK/yffZTI93+pcBya64mmOBJ/PYj7bXF49GlD/DrjiS7pljjc+7Ql8deDyAU6tNHJaK4n4tiqLnb1fMk6cRmDpgBZbyD94Dk8Hmn/QPK+lWuXpmgiE9HGGC8K9TmaW8rJGmS5QmX0oEhKBQprSySlAqWtJfkJFe91Ufu5x2i3dREddi0jcObQUtMUpmSRdeoqcqHe7POCpAyyz1wHQJ+rRdYVIimq3v7WpkVTnBwdyk94D0UkZOLvZIufky0WSgW966vZfTXJLM3GiFiGNffH0doCAFdbq3uT941k/N0d8XNzxEKlpHfzQHafjS4z/ZZT1+jTIsj0d/t6PthaWVQ4v5pSTwqu3MDCy63Ubdg0r09BVByFNxKgUEfmpr049OxglqYwNon8i5FguG0/LNQhF+gAUFhaICnu4kblNr36hvDL2j8AOHnsNI5ODnh6uZeZPiCoNm4erhw5dPyu846ITcPfxR4/F3sslEp6N67F7ovmT5w3nLjG8DZ1cbSxBMDVznjhfTU5E71BpmOQGgBbSwtsLKq2j6oaPoQuNhZDfDzodOTv2olVcGezNIWnTkK+8aag8Pw5FB4eJbZj1bU7BUf+NqUrTU2pq3JOGpK1fWmbACAiOgl/d6fifbhlXXZHRJaZfsvJy/RpWXy+OXcjmbRsDR0blGz8r6w+/Xqw/idjD78TFaijgUG1cXN35fBBYx09uO8IGo3WtL63Tyk3tOWoKXUVwKppAwqj49DFJIBOR+6WPdiFBJul0cUlUnDpeinndBnJyhLJQoVkaYGkUqFPrVpvxoiYVPxd7fFztTfWkaa12X0hxizNhmNXGd6+XnGZ2BvLRAIKdHoK9QYKdAZ0Bhk3+7JvqmvMfpORiGTrWGZeEfHp+Dvb4edsZzzvPuTD7isJZmk2nI5meMs6OFrfrCfG866FUoGlSmnMV29ArmHXY/8GoX26sXGtsVdx+PEIHJwc8CjlnD1kZH8+W2FsuJJlmfS0TACGjR7EmtXryMrMBiAtpWr7Ts8+3fh17WYATh2PwMHJHo9SjmmPj+zPp2ZxZJRI8+ig3mzaEFalOLr36cKm9VsBOHPiLA6O9rh7liyP/iMeYfWH35viyCgqj/iYBC6fv4pBvPYR2SDX+P9qogfes8FK7Up+XPHTzfy4VBxbmXc/s/J2Jb/oCaisN6DPzsPC1YHCtOwytxswewTRq/7AoCnZEFEaa7Ur2hJxmN+03x6HrigOK7ULWccvF68bn4q12pWcCzcImjMclYs9Bm0B7j1bkhV+7YHkfWvnf69BwSRuPGC2vcA5w/Ee2hVdtoYTg9+sUBk9KJGrNtHlxCcYNAWk7jlN2p6ST1+8Hm2PS8eHyLsaz8XXviM/LhXXbs2wDVRzpM9ckCRafD8T5w4PkXH4fCm53Jm1vweSygpZV8GeMTVEUq4Wr1ueiHg5WBORkGmWJio9F4Cn1x7BIMtM6hBEpzplX8RXOO/MPNROxV2EvZxsOVM01Od2cenZxKVl065u1Z6A5iek15h6Yt04EE14yS6ZACovNwrji5/86hJSsGle8acRKm93an35Bpa1vUlcsvqe9GoAUHt7EhdbfDGcEJeIl7cnSYkppaZ/bFAfNm2s2oXN7ZKyNaidbE1/eznacCbW/HtFFR3bx6zegUGWebZbYzrV9SYqNQcHawteWneA2Ixc2gd4MTW0KUpF5dvJle7uGJKLG+IMycmoHirZRf4m6779jI0Kt38e0oO8n9eVuZ4hJaXG1FXJyQNDRkKZaZIyc1Hf0s3fy9mOM1FJpaaNS8smLjWbdvV8jd/TIPPu7wdZNCqUw5diSl2nMm6vo/FxiXh7e5VZRwcM6cfvG7eWuuyJ0YPZtX1fqcvupKbUVQCVpzu6hOLjqS4xGatmDSu0bn74eTRHTlFr509IkkTmj79ReL2UnlgVYCyTW+qIoy1nYsx/k6jUojL5YpuxTEKa0qmeD81redA2wIueyzeCDMPb1yfwll4iZjTZNWe/cfPFkFx2w3lSjha1g01xTA7WnIkzv0GMSssxlska4xClZzs1oFOgJwAJWRpe/OVvbqTnMq17I9Gr4R7z8vYgIa74WJIYl4iX2pPkxOLrbgdHYyPstNmTadepNdGRMbw1exmpyWkEBNUC4MfNX6FUKFi5/HP27TxUhTg8iY8r7h2TEJeEl9qD5FuOabfG0b5TG6IjY3hz9lJSk4uPOz5+avxq+3JoX+m96crjqXYnMa74uJ4Un4SHtzspScXlYV8Ux3OvPEPr4JbERMaxdO57VW5oEYRb3fEsKEmSUpKkSZIkLZAkqdNty6o2gOk+sG9cG5s6XqRsqdqOeK/kXY4l8qPfabl2Hi1+nEt2RCSy/sG2BEoWStwfbk3SH4fNPr+2eC0HWj1Pwi/78RvX54HGVB7PPm3Y3/YF9jZ/FqWtFeoh5k8bU7YdZ1+bFzgcMovUPWdosvI5ANy6N8OtWzM67FhKh+1LsKvri22gutL5K22taP7VS+hzU2pcr497QS/LRGfk8cXjbVjctykLtp8lW1u1oSJVFXbqGj2bBlT9wtvJrsbUk4QFX2C4pbfQvaSLT+HaIy9wpccEnAeHonRzvi/5lKf/4D78tqH0+WbuB71BJjothy/HhLBkcAfe2nSMLG0BeoOBk9EpvNSrOWue6Ulseg6/h0fe93isevbCon4D8tb9ZPa5wtUVVUAgBUePlLmuZG9fY+pq4bk9oKtYA3x5wk5eoWfzQNM+vO5ABJ0fqoWXc9k9J+6ngYP78evPm0t8PmTYYzRv2YRPPiw5p9O9UNPqamlU/j5YBtYiuudIokKfwKZ9C6xbNblv+ekNBqLTsvlyXE+WDO3EW78dIUtTQHRqNteSs9g2YyDbXh7I0WsJnIgsvTELC+uas98c/g0K7264od4gE52ey5cjglnyWGveCgsnq+i8q3a0Yf3Y7vw+IZQ/ImJIzb03QxuFilOplHj7qjlx9DSDQkdz6ugZZr9hnPdMqVJSJ9CfJwdM5KVJ81j43jxTo8C9j0OFt6+ak0dPMzB0FCePnjbFcdOjg3qz9Y/t97VngUqlRO3rRfjRCEY9PJ7TxyOY/vrz5a8oCBVQXs+GzwBb4AjwoSRJe2RZfqlo2WBgYWkrSZI0EZgIMN2hNY/aBJqW5SekYeVT3H3HysfNNNmPKU18Gla+buTHpxm70znY3rFXg1Ob+jg2D6Tj0Y+QVEos3Z1oueF1Tt7hCb42IQ3rEnGYt+DdHoeqKI78hHSsfIufDFt5u6Et+g7xP+wi/oddAATNHYE2ruSTyfuVN4BbaEuyz1ynINn86fZNCb/so8UPc7i+fH2py6uDJjqJwqInI0mbj+DctgEJvxRPzlSYnmP6d+yaHdR7zTjWXJIkrn/4G7Hfbzfbnt/Yh/ErmqTz5Mgl5N9hMkxJpaTZ6hnE/7KfwCmdy0xXU3naWZOYXdwbIzFbi4ed+TAJT3trmqqdsFAq8HWypbaLHdEZeTRWl/GEqaJ5O9mSkJlbnHdmHp6OpU+GtjX8GnMGBpe6rCJcuzatMfVEv+1gmel0ialYeBfvnyq1O4W3PE2pKF1SGtpLUdi2bWyaQLKynho/nBFPDgHg9Mmz+PgWX3yrfbxIjC/9ov+hxvVRKpVEhFf+qWBpPB1sSMjMM/2dmKXB85angmB8gtzE181YR13sqe3qQHRqDl6OtjTwcsbPxXihF9LQl9MxqQxqWfk49CkpKDw8TX8rPDwwpJR8am7RqjV2I58k/aUpUGjeKGfVPYT8/ftAry+x3k2WrdqQU0Pqaq32d+4Z4+lkR0LGLftwRi6eTmXsw6euMGdw8QSQ4VGJnLwWz7oDZ9EUFFKo02NrZcHURzuUun5pnn7mCUaNMXZ5Dz9xxqyOevt4ER9f+pj5Rk0aoFQpOR1+zuzzLt06MnXGRAY9MoaCgso3qNaUugqgS0pBpS4exqPy8kBfwWOJXWgntKcvIBcNK8nbfxSr5g+hPRFR6TiMZXJLHcnKw9PR1iyNl6MtTfxuKRM3B6LTsjl2PZFm/m6m4XKd6vkQfiOFVnU8uZ3CKxBNVA3Zb2rfuZw87a1JyC5ucE7M1pboneDlYEMTH2djmTjbUtvFnuj0XJp4FzcgezpYU9fDgRMxqfRq4HPHPIU7GzVuKMOeHAjAmZPnUPuoAePE7V4+XiQmmJ/v0tMyycvVmCaE3PL7dh4f1R8w9kAIPxGBTqcnJjqOyKvR1AmsxZlT5sebsuIY/uQgAE6fPGc2nEvt40lignnvz/S0DPJyNYTdEsfQUQPM0jwy6GHeeGVpRYsCgGFPD2bQqMcAOBt+Hi+f4n3O09uT5Hjzc19GWiaaPA07/zQO397+xy4GPvFopfL8TxBDSaqkvMeM7WRZHinL8gdAe8BekqQNkiRZYRyOVypZlj+XZbmNLMttbm1oAMg+eRXbQG+sa3kgWSjxHBhMStgxszQpYcfxHtYdAI/HOpC+/+wdg4z99i8ONH+WQ21f4ET/18i7FnfHhobiONSmOLxKjeMY3sO6AeB5SxwpYcfwGhiMZKnCupYHtoFqsk5cAcDC3TjOz8rXDY9+7UjcUHJG4/uVN4B6UCcSN5rfDNkEFF/AefRpS97lWGoSp1b1UNwc69mlCbm3xWfpWXxy9ujdxrQ8ZVc4viO7oyyag8BK7YKFuyMxX2/jcOgrHA595Y4XFwCN3n+W3MuxRH9W8gnZP0FjtSPRGXnEZuZRqDcQdimB7kHmF3IhQZ4cizHedKRrCohKz8XXyaa0zVUubz8PolOyiE3LplCnJyz8Gt0a1SqR7npSBlmaAprXLnmBWVHa2JR/RD3RnL6EZR1fLPy8wEKF06NdydlRsit+aVRqNyQr4/dTONpj26YxBdeq3j39u6/W0q/7MPp1H8a2P3cyZLjxwqNlm2ZkZ2WX2T29/5C+/L6h9O7pVdHY15XotBxi03Mo1OsJOxtNt/rmF9YhDXw5VvTEMz0vn6i0bPxc7Gjs40J2foFpEr4j15MI9Ch7LPWd6C5cQOXrh0KtBpUKq5Ae5B80b8hR1a2H4/QZZM6fg5xRctysdUgo2l13njRTn5T4j6irAI39PYlOziA2Ncu4D5+8QrcmdUqku56YTlZePs3rFF84Lx7dk62vPcmW+aOZ/lhHHm3ToFINDQDffPkjvboMpleXwWzZvIOhI4wX2a3KqaMDh/Tj11/Me940afYQyz54nTFPvEBqStWGH9WUugqQH3ERi9q+qHyN9dWubzdyd1esK7cuPgnrNk1BaXyzjU3rZhReq9owisa+bkSnZRvLRKcn7EwU3Rr6mqUJecivuExytUSlZuPnYo+3kx3HI5PQ6Q0U6g0cjyy7TOS8zH/OfuPtTHR6LrEZRefd83F0q2vekyKknppj0cbGofS8fKLSc/BztiUxW4O2aM6ILG0BJ2PSqONaPb2D/k3WrF7PgJBRDAgZxfYtuxk0vB8AzVs3IScrx2wIxU27tu2jfafWAHTs2pYrl4zzdmzfstv0uYurE3WCanEjqmLXzWtWr6d/yEj6h4xk+5bdDBz+CAAtWjchOyvHbAjFTTu37aV9J+OkpcFd25niAAisWwdHJ0dOHq3c5K7rvtnAE73G8kSvsezeso9Hhxp7NDdt1Zic7ByzIRQ37d12gDbBxtbRdp1bc+1SZKXyFISylNezwfLmP2RZ1gETJUl6HdgJVOnoKOsNXJqzmhY/zTO+9vHHXeRejCFg1jCyw6+SEnac+B920uijF+hw+EN0GTlETPrAtH7Hox+hcrBFslTh3rctp4YvNHuTRWXiuDhnNS1/mgtKBfE/7ib3YgyBs4aSFX6NlLDjxP2wi0YfvUDHwysozMghYtIKAHIvxpD0+yE67HsXWWfg4uzVpsnemn31EhYuDhh0ei7OWY0uK++B5a2wtcK1a1POv/y5WX51Xx2JbV0fZIMBbUwKF2d+Uenyup8SN/1Nh7+WIOsNZJ25Tsz32wkqKovksOPUmtAXj4dbI+sNFGbkcHaK8RVeaXtOE1/fl7Z/GjvY6HO1RDz3EYUp5q+vtPRwov22xagcbJANMrUm9uNglxk4NKqFz7CuZJ+LosOOpaicvdHnpiEXVq2L/MzXl3D05GkyMrIIHTia58Y/yZDHet9d4ZRDpVDwSkhDntt4AoMsM6CxL0Fu9nxy6AqNPB3pHuRJcG03DkWlMvi7AygliWld6uNsY1n+xsvLW6lg9oCOTP5yKwaDzIC29amrduGTsOM08nOne+PaAGw9dY0+zQNLzMw+9pNNRCZnkpdfyMNv/8gbj3chuIFfqXllnbhSY+qJhcJA0rvfkrP7WIk40RtIeHMVtb5ZgKRQkPHzX+RfjsZj2mg0Zy6Ts+NvrJvWw3/Vqyid7LHv0Q6PqaO41vc5rIL88Zr7jHEojySR+uUG8i9FlcyjCnb+tY+QXl3Ye2yz8dWXL843Lftz9zqzt1A8OqA3T4947p7kC8Y6OrtvKyav2Wusoy0CqOvpxCe7Imjk40L3Br4EB6k5dDWRwZ9sRaGQmN6zOc5FNw7TezZn0vd7kIGHvF0Y0irwzhmWxaAne+UHOC99B0mhQLPlT/RRkdg9PY7CixcoOHQQ+4nPItnY4PiasbHakJRE5vy5ACi81Cg8PSkMv/OrJHUXzpNeQ+qqlb8dhRcPYEiOLP23USqYPbgLkz/fZNyH2zWkrtqVT7YcoZG/B92bGF+ju/XkFfq0rHt3b1cox45tewnt1ZVDJ7eiydMy/fl5pmV/7dtg9haK/oP6MHros2brz3/rZezsbPn82/cBiI2J4+knXqhUDDWmrgLoDaQs+gj1p4uQlAqyN4ZReDUKl+efIv/sJfJ2H8aqcX28VryOwsEB224dcHnuSWIGTST3r33YtG+B34bPQZbJO3CMvD2Hy8+ztDJRKpj9SBsmf7fLWEdaBVLX05lPdpymka8r3Rv6EVzXm0NX4hm8chMKSWJ67xY421rRs7E/R64nMvTjP5EkCK7rTbeGpR/j5bRYEsNryH7jbUHhsS0YYkp/U5JKoWB2zyZMXn/YWE+a+lPX3YFP9l2gkdqZ7vXUBAd4cCgymcFf7TKWSfdGONtYcigymfd2nUVCQkbmqbZB1LuLRimhpN1/HaBbz05sP/IrGo2WOVOKHz7+tmsNA0KMPWKWv/Uhyz95i7kLZ5Cems7sonT7dh6ic/cO/Ll/HXq9gWVvfEhGeum9he8cx3669ezEjiO/odEYX8F50++7fqB/yEhTHO98soB5C2eQdkscYOzVsPnXbVUpBpP9Ow7RObQjvx1ai1aj5Y3pi0zLfvzra57oNRaAD99exYKV83n5rSmkp2bwxvTFADRq3pB3Vy/C0dmBrr068ezM8Qzt/uRdxST8t0h3mglXkqT/Af+TZXnrbZ+PBz6VZbncqeR3eg2rEYPg5bI7YvynhSauLT/RffaX1/DqDgGA7mcXV3cIJoXr36/uEACQfO5+lvl7Yf/Eu38rwr3ia59TfqIHoG9G1Z5U3msXPhxQfqIHJHv13uoOAYDwiMqPF78fOq/uWN0hmASO+rz8RA/AtY+HVHcIAMQvqViPpwfB+9VO5Sd6APZPKb+b+oPQeVHNOO/dZDP+wb1Ou6ar79Gm/EQPiEyNuL3BQXX3PVXvlRPx+//VN1t5q16sGT/6HdhOXlnjfoM79myQZXk0gCRJQ4GtsixnF00M2QrjsApBEARBEARBEARBEAQzFZ0afn5RQ0NnoCfwFbDq/oUlCIIgCIIgCIIgCMI/VUUbG25Ovf0I8Lksy5u5ZT4HQRAEQRAEQRAEQfhXMsg1/78aqKKNDbGSJH0GDAf+LHobRUXXFQRBEARBEARBEAThP6SiDQbDgDCgtyzLGYArMPO+RSUIgiAIgiAIgiAIwj9Wea++BECW5Txgwy1/xwPx9ysoQRAEQRAEQRAEQagRDIbqjuAfSQyFEARBEARBEARBEAThnhKNDYIgCIIgCIIgCIIg3FOisUEQBEEQBEEQBEEQhHuqQnM2CIIgCIIgCIIgCMJ/kpizoUpEzwZBEARBEARBEARBEO6p/0zPBj1SdYcAgBK5ukMQylC4/v3qDsHEYuj06g4BAN2O76s7hBpHb6gZbbRWCsvqDgEAOSujukMwUTlWdwQ1jCanuiMwsVVZV3cIQM2pr9YOhdUdQjGtprojqFHkgvzqDkEog7XSorpDMDHINeN6XiUpqzsEQbij/0xjgyAIgiAIgiAIgiBUWg1pYPqnqRmP6ARBEARBEARBEARB+NcQjQ2CIAiCIAiCIAiCINxTYhiFIAiCIAiCIAiCIJRFvI2iSkTPBkEQBEEQBEEQBEEQ7inR2CAIgiAIgiAIgiAIwj0lhgX5Hm8AACAASURBVFEIgiAIgiAIgiAIQlkM4m0UVSF6NgiCIAiCIAiCIAiCcE+JxgZBEARBEARBEARBEO4pMYxCEARBEARBEARBEMoii7dRVIXo2SAIgiAIgiAIgiAIwj1VLT0bXEOaU2/hWCSlgvg1O4ha+ZvZcslSRaOPXsChWSCF6dmcnfgB2hvJqFzsafrVSzi0qEvCT7u5NHe1aZ3mP87F0ssZSakk8+8LXJz9ZZkTeTR4ewweoS3Ra/KJmLKK7DORJdI4NAugyYeTUVpbkrzjJBfnfQuAytmO5p9PxdrfA+2NZMInrECXmYtLcCNafPsymugkAJI2H+HaexuwDfKm2edTTdu1re3JtWXryb0cS/2FTyMpFcSt2VlqGTT+6HlTGURMXIH2RjIAtacMxGdkCLLewKV535C2OxwA/wl98RkdCkDcmp3c+PxPADwf60DAy49jV9+Xo33mkR1+rcK/VXWxretD4xWTcWwawJXFPxG1alOl1rdwsafZVy/h2CKIuJ92c3Hu1wAobCxp9sV0bOt4IesNJP91nCsLf6xSjAciU1i+5wIGg8zAJn6MaxtQIs22Swl8evgqElDfw4HFfZtVKa/KeHXRe+w9cARXF2d+/d+n9zWvA5fjWPbncQyyzKBWQYzr2rhEmrCIKD7bdQaQqK92ZsnQTgC8H3aSfZfikGWZDkFqZvVrjSRJFc67ptYR+66t8Hl9AigUpK/9i+RPfzaPu11jfOZPwLphHaKnLCNry0EArB8KwHfhcyjsbZENepI/Wkfm5v2V+k63e3XRy3Tr2QlNnpbZU97g3OmLJdJYWKh4bcks2nVqjWyQeW/RJ2zbtBOAvgN68uLMiciyzIWzl5nx7Kt3FQ9U735j0bIdtuNfBIWC/O2b0W74wWy5Ve/+WPUdBAY9slZD7ifvYIiJQtW8DbZPTgSVBegKyft2FbozJyuVd02tr7c6cCmWZZuPYTDIDGpTl3HdmpgtX775KEevJQKgLdSRlqtl//wRVcqrNK8tmkn3np3RaLTMevF1zp6+UCKNhYWKN5bOpn2n1hgMBt59+2PCNu3E21fNOx+/iYOjA0qlkuULPmT39gN3FU91H+Ot2rfFadoLoFSS98dmcr43/13tRgzF9rF+oNdjyMgkY9Ey9AmJpuWSrS2eP3yDdu9+Mt/7sMpxHLiayLK/ThuP881rMy64QYk0Yedi+GzfBZCgvqcTSwa2NS3LyS9k8OfbCanvw5zezSuV9z9iv6mh1wL/Za8snE6X0GC0Gi3zpy7g/JlLJdKoLFTMXTSDNsGtkA0yK5d8yvbNuxn61CBGjB2CXq8nL1fDWzOXcO1SZJXimPP2S3QJ7YhWk8+8KQs4f6bkOVhloWLe4pdpG9wKg8HAh4s/Y/vmXQx7ahAjxg3BoDeQl6vhjZcXVzmOGQumENyjPVpNPm9NX8zFM5dLpFn18we4e7mRr80H4MURL5OemoGXryevfzAXByd7FAoFHy/6jIM7/65SHMJ/04NvbFBINFgynpPDFpIfl0qbsMUkhx0j71KsKYnPyB7oMnI53GEKngODCZo/irMTP8CQX8i1JWuxa1gL+4b+ZpuNmPA++hwNAE2+moFn/44k/XqwRPbuoS2wC/Bmf4dpOLWuS6Nlz/B335IX0I2WjefcjM/JPH6FVj/Mxr1HC1J2niLgxQGk7osgcuXv1HmxPwEvDuDyQuMFa8bfFzg5epnZdvKuxnM4dLbpu3cLX0Xy1qO0XP8qJ4e9TX5cKm3DFpMSdozc28qgMCOXQx2m4jUwmLrzRxIxcQV29X3xGhjM4a4zsFK70HL9qxzqOA27+n74jA7laJ+5yAU6Wvw0l5Rtx9FEJpJz4QZnxr1Lw+UTqvabVYPCjBwuzvsGj75tqrS+Pr+Qq0vWYt/QH7vb6krUqk2kHziLZKGk9c/zcevRgtSdpyq3fYPMkl3nWTW4NV721oz68TDdAj0IcrMvzic9l9VHr/PNsHY4WluQlpdfpe9SWQP79WLkkP7MXfDOfc1HbzCweNMxPh3TAy9HG0Z9Fka3hn4EeTqZ0kSlZrF67zm+eeZhHG0sScvRAnAqOplT0cmsf74vAGO//ItjkUm0DfCqcP41so4oFPi89SzXn5yPLiGVoN/eI2v73+RfuVEcd2wyMTM/wH3CILNVDdp8bsx4j4LIeFSertT9432y957EkJ1bpe/XrWcn6gT606vdIJq3bsKby+YwtM/TJdJNnj6O1JR0encYgiRJOLs4AlA70J9JU8cy4pHxZGVm4+ruUqU4blWt+41Cge3EaWS/MQNDajKOyz6j4MgBDDFRpiT5e7eTH/Y7ABZtg7Ed+zw5C2YhZ2WS/fYc5PRUlLUCcHhtORnPPF6p7Gtkfb11+wYDi/84wqdje+LlaMuoVVvo9pAfQZ7OpjQzHym+gfzx0AUuxKVV6buUpnvPTtQJrEWPdgNo0bopby2fw5DeY0qke+6lZ0hNTqNn+0FF9dV4vHlhxjNs/u0vfvj6Z+rWD+Crn1bSrdWjVY6n2o/xCgVOL08ldepM9EnJeHz1Kdp9B9FFFtfXwkuXSRn3LHJ+PraD+uP43CTSX3vLtNxh4jjyT52+qzD0BpnFYeF8+kQn43H+6110q+dNkIejKU1UWg6rD13im6e6Go/zuebl8PGe87Tyd69S/jV/v6m51wL/VZ1DO1I70J9HOw6lWavGvLp0FqP6PVMi3cRpT5OWkk7/TsORJAmnonPfnxvCWP/dRgC6P9yZmW9MZfLI6ZWOo0toR2oF+NOvw1CatW7M/GWzGNl3fIl0k4rieDR4mFkcmzeEse5mHL27MOvNqTz7ROXjCO7RHv8AP4Z0GkWTVo14ZfFLjHt0cqlpX3t+IedveygxbupT7PhjF7989xsB9Wrz/v+WMrD9vWtkFv79HvgwCsdWdcm7noA2Kgm5UE/Srwfx6NPWLI17nzbEr9sNQPIfh3HpbHy6YsjLJ/PIRQz5BSW2e7OhQVIpUViqQC69V4NHnzbErd8LQObxK6gcbbG85WIKwNLTGZW9DZnHrwAQt36v6UTn2acNcWuN68et3YtnJU6Abl2aoolMxNLTGc31RFMZJP56EPfbysCjTxvi1+0BIOmWMnDv05bEXw8iF+jQRiejuZ6IY6u62NXzJevEZQyaAmS9gfSD5/B4pD0AeZdjybsaX+E4a4LClCyyTl1FLtSXWKYe0pl2W9+mw46lPLR8AihKPg035OWTceQi+vxC8881BaQfOAuAXKgn+8x1rH1cKx1fREIm/k62+DnZYqFU0Lu+mt1Xk8zSbIyIZVhzfxytLQBwtbWqdD5V0aZFU5wcHe57PhExqfi72uPnao+FSknvprXZfSHGLM2GY1cZ3r4ejjaWALjaWwMgAQU6PYV6AwU6AzqDjFvRsoqqiXXEtnk9CqLiKbyRiFyoI/OPvTj2am8ed2wS2guRJXpeFVyPoyDSuJ/qktLQpWaicnOkqkL7dGPjWmPvpvDjETg4OeDh5VYi3ZCR/flshfFpnyzLpKdlAjBs9CDWrF5HVmY2AGkp6VWO5abq3G9U9R7CEB+LITEedDoK9u/Esl1n80SaPNM/JSsb07/11y8jp6ca/x19HSytjL0cKqEm1tdbGfdnB/xcHYz7c7Pa7D5/o8z0W05H0qd5nUrnU5aefbuzcZ3xqfWp42dwdHLAw6vkDerQkf1ZtcLYq9FYXzNM/7a3twPAwdGBpITku4qnuo/xFo0aoouJQx9nrK+a7Tux7tLJLE3BiVPI+cYb14Kz51B6ehSv36A+SlcX8o8cvas4IuLS8Hexw8/FzlgOjfzYfdn8emLDqUiGtw4sPs7bFZfDufh00nK1dAz0rFL+NX6/qcHXAv9VIb278se6LQCcPnEWB0d73D1LnvsGjniUr1Z+BxiPHxlF577cnOLzgI2tDTJVe91hSJ+u/L7eeA4+fbzsOAY98RhffvhtOXFYl3VbU66uvTvz589hAEScOIeDkz1unhWv67IsY+dgC4C9oz0pialVC+TfwCDX/P9qoDs2NkiSZCtJ0ixJkmZKkmQtSdLTkiT9LknSMkmS7O+0blms1K7kxxVX1Py4VKzU5pXeytuV/FhjGllvQJ+dh4Vr+TdPzX+aS+ezX6DL0ZD0x+FS01h7u6KNLc5fG5+GtbdryTTxxU9stHHFaSw9nChIMl7cFCRlYOlR/BTXqXU9Ou5cSqsfZmPXwK9E3upBHUnceABrtSvaEmVg/tTw9jLQFZWBldqF/NiU4nXjU7FWu5Jz4QbO7RuicrFHYWOJe8+WWPuWPKj909nV80U9MJijj77G4dBXkPUGvId0qdK2VI62uD/cmrR9EZVeNylXi5dD8c2xl4M1ybc9zYlKzyU6PY+n1x7hqZ/+5kBkyu2b+UdLytagdrIz/e3laEtSVp5ZmqjUbKJSshnzxTae/DyMA5fjAGhey4O2AV70XL6RXss30rGuN4G37Et3ozrriErtRmF88e9cmJCKhbry+6FN83pIFioKohIqve5NXt4eJMQVr58Yl4iX2vyC38HReBifNnsyG3f8jxVfLcHNw3isCwiqRZ3A2vy4+SvWbfmaLj06VjmWm6pzv5Fc3dGnFN8EGFKTUbiVvJm16jsQp1U/YDPmWfK+XFFiuUXHbuivXQJdYYllVVFjjmlZebftz3YkZWpKTRuXnkNcWg7tAtVVirM0Xt6exMUWDwFIiEtC7e1hluZmfZ0+5zl+27mGlV8tNdXXFcs+Y+DQfuw/vYWvfvqQN+eY9zKsrOo+xis93NEnFtdXfXIySo+yewfYPdoP7eGirs2ShOOLk8lcuequ40jK1qJ2LG5483KwISlba5YmKi2HqLQcxny3hye/2c2Bq8bf0SDLvLsjgpdCm951HLerMfuNuBaocTy9PUiIKz6WJMYn41nGseT5WRNZu+0b3vnibbPee8PHDmHz4fVMn/88S+a9V6U4vLw9SIgt3ocT45PwKiOOF16ZxLq/vuXdL942HdMARowdwpa/f2bG/BdYXMU4PNXuJMYVx5EUl4yn2qPUtPPfn83//vqScdOeMn32xbtf02fww/xxbD3vf7+Ud+aVPC8Kwp2U17PhG8ALCAA2A22A5RgfTJZ5FpMkaaIkScckSTq2SfPg5gcIH7GIA80mobC0MPUEuO+KmhqzTl9nX+sXONTjFaK/2kqLb2aYJZMslHg83LrMRpC7lXc5lsiPfqfl2nm0+HEu2RGRyPp/36yprl2a4NgsgPZhi+iwYymuXZpgU7vyT0wkpYKmn07hxpdb0UQllb9CFehlmeiMPL54vA2L+zZlwfazZGvvzQ3KP4XeYCA6LZsvx/VkydBOvPXbEbI0BUSnZnMtOYttMway7eWBHL2WwInIe/M7/JPqSGlUHi74v/cSMTNXlNlD657lpVLi7avmxNHTDAodzamjZ5j9xjQAlColdQL9eXLARF6aNI+F780zXRjdT9W93+Rv+ZXMySPRfPcZNkOfMlum9K+D7VOTyP303XuW3z+xvoadiaRnk1ooFQ+2c6RKpTLW1yPhDOgxipPHTjPnTWO34scG9+aXn/6gc7O+jB8xhXc+WVCpOWCqorrr6k02vXti0bABOWvWAmA7eAD5h/7GkPxgbmqNx/kcvhzVhSUD2/LWnyfJ0haw7vg1Ogd54XVLY8W98k/ab2pKPRGKKVVK1L5ehB87w/CHnyb82BlmvP6iafnar3/hkQ5D+WDhJ0ycPva+x3Hq6GmG9RpD+LEIXr4ljp++/oW+7R/nvYUfM2n60/ctDoDXXljIyNCxTBz4Ii3aN6Pf470B6D2wJ5vWbeGxNkOZ/uQrvLFy3n0/tgr/LuXN2VBfluVhkrFWxQM9ZVmWJUnaD4SXtZIsy58DnwPs9BpmdrWcn5CGlU/xkz4rHzfyE8zHfebHp2Hl60Z+fBqSUoHSwZbCtOwKfSFDfiEpW4/i0act6XvPAOA7tjfeRRMnZp26avbE//ZeDFCyt4O1T3GaguRMLD2djb0aPJ0pSMkCiodxAKTsOMVDS8Zj4epgits9tAVZZyIpSM5Em5CGdYkyMO+ifHsZqIrKID8hHSvf4qcbVt5uaIvKL/6HXcT/sAuAoLkj0N7D8bQPgt/Yh/Er+p1OjlxCfmIp3bYlibh1e7nytvlETh592xL0snEM9bmXPiOrnEkwH3p3InnXE4gumkSzsjztrEm85elOYrYWDzvzrpGe9tY0VTthoVTg62RLbRc7ojPyaKy+N0/wq5ungw0JmcXzCSRm5eHpaGuWxsvRliZ+bsYycLGntpsD0WnZHLueSDN/N2ytjN1KO9XzIfxGCq3q3PlisabXEV1CKhbexfunhdqNwoSKdzlU2NtQZ/XrJLzzPZpTJSeSKs+ocUMZ9uRAAM6cPIfaR83NQ7WXjxeJCeYX0+lpmeTlakwTQm75fTuPj+oPGJ8sh5+IQKfTExMdR+TVaOoE1uLMqXOVjuum6txv5LQUlO7F9Uvh5oEhteybsYL9O7CdVDw+VnLzwH72QnJXLMKQEFehPGt6fb2Vp6PtbftzLp5Opd8kbj0dyZzH2lUpn1uNHjeM4U8a5y45c+osPr5eHC9apvbxJCHefChEeloGebkawm7W19+2M3SUsb4PHTWQccNeAODksdNYWVni6uZMahWH/1T3MV6fnILSq7i+Kj080JfSeGDZphX2Y0aT+vw0KDTewFo2aYxl86bYDh6AZGODZKHCoNGQveqLSsfh6WBNQlbx9U1itgZPB/Mhb14ONjTxcTWWg7MdtV3tiU7LJTw2jZM3Ull34jqaAh2FegO2lkqmhtz5YdA/ar8R1wI1wvCxQxhSdO46e+o8ap/i+Z+8vD1Iuu1YkpGWiSZPw/bNuwHY9sdOBo18rMR2t/z6F/OWzqxwHCPGDuHx0QMAiDh1HrVv8T7s5e1JYilx5JnFsYPBpcWx8S/mL50FLKhQHI8/PZCBo4xz1pw7dREvn+I4PH08Sh1mlpxgPL7k5WoI27idRi0b8ufPYfR/oh9TRhnL4Mzxs1hZWeLs6kR6akaFYvk3kQ3/voe4D0KFHkvIsiwDfxb9/+bfVXrkln3yKraB3ljX8kCyUOI5MJiUsGNmaVLCjuM9rDsAHo91IH3/2TtuU2lrZZp3QVIqcOvVitwrxZMtxn4dxuHQ2RwOnU3SlmP4DO0KgFPruuiy80zDIm4qSMpAl6PBqXVdAHyGdiV5qzHG5LDj+Aw3ru8zvCtJRZ/fOpzCsWUQKCSzBhL1oE4kbDxwSxmoTWXgVWoZHMN7WDfA+DaJm2WQEnYMr4HBSJYqrGt5YBuoJuuEcW4JC3fj+G4rXzc8+rUjccPdzWT/oMV8vY3Doa9wOPSV0i8ugLR9Z/B6tL3pu6qc7bD2cyd5y1HTuuVdXATNHo7KwZaLr35b5Vgbqx2JzsgjNjOPQr2BsEsJdA8yv1EOCfLkWIyxwSddU0BUei6+ZVy8/xM19nUjOi2b2PQcCnV6ws5E0a2hr1makIf8OFbUYyE9V0tUajZ+LvZ4O9lxPDIJnd5Aod7A8cgkAj3Kn5+gpteRvNOXsarjg4WfF5KFCqfHupK1/UiF1pUsVNT+dB7pG3aa3lBRWWtWr2dAyCgGhIxi+5bdDBreD4DmrZuQk5VDciljLXdt20f7Tq0B6Ni1LVcuXQdg+5bdps9dXJ2oE1SLG1GxJdavjOrcb3SXL6Dw9kPhqQaVCsvOPSg8av62AoV3cf21aN0RQ7xxDhLJ1h6HeUvI+/4zdBcq3tW6ptfXWzX2dSM6NZvYtGzj/nw6im63TagHcD05kyxNAc1rld4NtzL+t3odj4U8wWMhT7Dtz90MGma8OG7RuinZWTkkJ5a8ud65bS8dOhvnSgru2o4rF41lEx+TQHBXYwNIUL0ArKytqtzQANV/jC88fwGVny9Kb2N9tenZA+1+8+OCqn5dnF95ibRZ8zCkF1/HZLz5NkmDR5A05AmyPlqFZsu2KjU0ADT2cSE6PYfYjFxjOZyLoVs9b7M0IfV9OBZtvHlJz8snKi0HP2dbFg9oy9YX+rDl+d5MD23Co01rldvQAP+w/UZcC9QIa7/+hWE9xzCs5xh2bt3LY8OMk083a9WY7OxcUpJKnvt2b9tP2+BWALTv0sb0podaAcXDoLv27ET09bLnrrndT1//wuOhT/F46FPs3LKH/kON5+BmrRuTk51Tahx7tu2nbaebcbTlatE5uFZA8fG3a69ORF+reBw/f/Mro3s9w+hez7Bn6z5TL4UmrRqRk5VLapL5w0ilUomTq/E+RqlS0rlnR65dMMaREJtE287Ga4E6dWtjaWX5n2xoEKpOku/QTVeSpC+BabIs59z2eRDwrSzLnUtfs9jtPRsA3EJbUm/BGONrH3/cRdQHGwmYNYzs8KukhB1HYWVBo49ewL5pALqMHCImfYC2qHtbx6MfoXKwRbJUocvM5dTwhRSm59D8+1dQWFmAQiL9wFmuzP/WbBiB7pZ2lYaLx+LeowV6TT5np35qOiF12LHE9OYIx+aBNPlwMgprS1J2nOJC0euSLFzsafbFNKx93dDGpBA+4QN0Gbn4j+uN/5iexjkmtAVcfO17Mo8ZX7WjtLWiy/GP2N9uCnJ2XlEZtKD+gjGgVBD/424iP9hI4KyhZIVfMysDh6Z1KMzIIWLSClMZ1Jk2CO8nuiPrDFye/61p9uTWv72BhYsDBp2ey69/R3rR+EOPvm2pv2gslm6O6LJyyY6I4tSIRQCEJq4t7ye87/7yGl7iM0sPJ9pvW4zKwQbZIKPP1XKwywz0ORq8BnQkYMpAUEjIhXouzFlN5vGSr/HpfHSlWV05MfxtdNkaup5aRc6lWOQC41OgG6vDiF2zk05vVK4L5r7rybyz5yIGWWZAY1+eaRfIJ4eu0MjTke5BnsiyzLt7L3EwKgWlJDG+XQB9GniXv2HAYmjlZxy+aebrSzh68jQZGVm4uTrz3PgnGfJY7yptS7fj+zsu33cpluVbTmAwyAxoFciEbk34ZMdpGvm60r2hn7EMtp7g4JV4FJLEM90a06dpHfQGA4s2HeNEZBKSBMF1vXm5b+sy89k/peTT9OqoIwBq27wS27mVQ/fWeL9W9OrL9dtJ/ngdntNHoTlzmeztR7BpVo/an85F6WSPIb8AXXIGl3s/j/PA7vgtm4r2crRpWzEvf4D2/PVS8xmSU/6kr68vnUWXkGA0Gi1zprxJRPh5AH7btYYBIaMA8PFTs/yTt3BwdCA9NZ3ZU94kvmjs/Jy3ptOlR0f0egOfvr+azb9uK5HHqbcqN5fD/dxvtNvuPPO+Rav2xa++3PEn2p//h80T49BduUDh0YPYjn8RVbPWoNch5+SQ98UH6G9EYv34k9gMGYU+vngC1Ow3X0bOLP2C6/jBknMZVEd97fxx5cbK77sYy/LNR42/Tau6TAhpyifbT9HI143uDxkvfFftCKdAp2dq71aV2naTZzeUm+aNpbPp2qMjWo2WV6a8wZlTxvr6x64feSzkCQB8/Lx5d9UCHB0dSEtNZ9aLbxAfm0Dd+gEsen8+tna2yLLM0jdXsH93yWGLZxZ0KvFZWe5nXc34vvxGK6uO7XGa+jwoFeRt2kLOt2tweGYsBRcukr//IG4r3kEVFIAhxXjjoE9MJO0V87dr2fTrjWXDBnd89aXLpPZlLgPYdyWB5dtPYzDAgOa1mdCpAZ/sOUcjbxe61/c2lsOOMxy8moRCIfFMcAP6NDaft+q301Gci8+446sv988qeaz7r18LANhOXlmpeP7Nmqkrdr6Zu/hlOoUYX/U4f9pCzoUbX6O7bvu3DOtpfMuNt5+aRStfw8HJgfTUDOZPW0hCbCKvLJhG+65t0RXqyMrMZvHcd7l6sWTdNFRgmOO8xS/TuUcHNBot86cu5GxRHD/v+I7HQ58yxbH4o9dxdDIe016daoxj9sLpdOjSFp3OGMfbc94pNQ5bZfkTjs5cNI2O3duh1eSzYPoS0xsn/vfXl4zu9QzWNtZ8tvFDVCoVSqWCI/uO88EbH2MwGAioV5u578zEtmiyzJULP+XvPcdKzedI3J5/9fiK3MVjauYMjLewm/NtjfsN7tjYYEokSUOBrbIsZ0uS9CrQGnhbluXSa9stSmtsqA66B//ijVIpqzir7f1SUxsbqkNlLzDup7tpbLiXymtseFBKa2yoLuU1NjwoFWlseBAq29hwP5XX2PCglNbYUB0q29hwP1WkseFBqExjw/1UkcaGB6W8xoYHpbTGhupQk64FQDQ23KqijQ0PQkUaGx6EijQ2PCj/+saGt5+qGT/6HdjN+67G/QYVvQOfX9TQ0BnoCXwJfHz/whIEQRAEQRAEQRAE4Z+qoo0NN19w/AjwuSzLmwHL+xOSIAiCIAiCIAiCIAj/ZOW9jeKmWEmSPgN6AUslSbKi4g0VgiAIgiAIgiAIgvDPJIu3UVRFRRsMhgFhQG9ZljMAV6Di74IRBEEQBEEQBEEQBOE/o0I9G2RZzgM23PJ3PFAzZicTBEEQBEEQBEEQBKFGqegwCkEQBEEQBEEQBEH47zHU+JdR1Ehi3gVBEARBEARBEARBEO4p0dggCIIgCIIgCIIgCMI9JYZRCIIgCIIgCIIgCEJZDOJtFFUhejYIgiAIgiAIgiAIgnBP3feeDSqpZkymIcs1Iw6JmhGHUJLk41/dIZjodnxf3SEAoAp9srpDKDKnugMwsbTSVXcIAMQlplZ3CABIdepVdwgmBu3p6g6hRpFqNajuEExic1KqOwSg5tRXl/n1SJj9R3WHYeRdq7ojKHK9ugMA4MAbSXRe1by6wxDKEK9Jq+4QAFAgVXcIANhb2FZ3CIJwR6JngyAIgiAIwgNUYxoahBJEQ0PNVVMaGgRBqDgxZ4MgCIIgCIIgCIIglEW8+rJKRM8GQRAEQRAEQRAEQRDuKdHYIAiCIAiCIAiCIAjCPSWGIw9tTwAAIABJREFUUQiCIAiCIAiCIAhCWWTx6suqED0bBEEQBEEQBEEQBEG4p0RjgyAIgiAIgiAIgiAI95QYRiEIgiAIgiAIgiAIZRFvo6gS0bNBEARBEARBEARBEIR7SjQ2CIIgCIIgCIIgCIJwT4lhFIIgCIIgCIIgCIJQBtkg3kZRFdXS2OAS0oKgBWORlAoS1uzgxke/mi2XLFU0WPkiDs0CKUzP5vyk98m/kYxz12YEzBuFwlKFoUDH9be+J+NAhHEdCxV1F43HKbgRGGQil/xIyua/S+TtGtKc+gufRlIqiFuzk6iVv5XIu/FHz5vyjpi4Au2NZABqTxmIz8gQZL2BS/O+IW13OAD+E/riMzoUgLg1O7nx+Z8ABLz8OD6jQylMzQLg6qIfSdtxstSY6i00lkf8mh2lxtTooxdMMZ2d+AHaG8moXOxp+tVLOLSoS8JPu7k0d7VpnZYbXsfSywWDtgCAU8MXUpiSVcFf6MHqfHQlulwt6A3IOj1/955rttwluBHNv52JNjoJgKTNR7j23i8V3r6Fiz3NvnoJxxZBxP20m4tzvy6RpsV3M7HqWJv8XSWX3erAxRiW/XYYg2xgULsGjAtpbrZ8+e+HOXo1HgBtoY60HC3733oSgOe+3Mrp6GRa1vFi5biHKxx/qXFcjmPZn8cxyDKDWgUxrmvjEmnCIqL4bNcZQKK+2pklQzsB8H7YSfZdikOWZToEqZnVrzWSJN1VPGV5ddF77D1wBFcXZ37936d3ta3y6ol6SGfqvNAfJAl9jobzs74i51xUhbdf0XriGOBOZP/JZW7HtnNrvOY9CwoFmT9vJe2L9WbLbdo0wXPOJKwaBBA3Ywk5YftNy+qf3UT+pUgAdPHJxD73ZoXjL83yd17n4d7d0eRpmTTpZcJPnTVbbm9vx7bt60x/+/qo+emnX3ll1gL8/X1Z9elS3N3dSE/PYPz46cTFJlQpjgPno1i2Yb9xv+nQiHE9W5vHuXE/Ry/HAEX7TbaG/UsmANBq+ifU9XYFwNvFgRUTHqlSDLezaN0Ou2dfRFIo0G7djGb9D2bLrfv1x/rRQWDQI2s15Hz4DvroitWn8uqqbV0fGq+YjGPTAK4s/omoVZsqF3sF66plk3oURGy747YOnL7E0u//xGAwMKh7a8Y/1s1seXxKBq9+/gvZeVoMBgNThz1MlxYNOHM1hgWrjeduWYZnB/cgtE2jSn2P27377pv06RNCXp6GCRNmcOpURIk0w4b1Z9asF5Blmfj4RMaOnUpqajqLFs3lkUd6UlBQyLVrUUyc+DKZmZU/59WkumoT3AbXV55DUijI3riFzNVrzZZbt2qK66zJWNYLJOmVt8nbvs+0zGXaM9h2aQdAxudryA3bU+U4DpyLZNkvezAYZAZ1bMy4h9uaLV/+y57iMinQkZaTx/5lxmNkfFoWb/64g8T0bCRJYuWzA/B1cyw1n5qy31h1qE3+ji8qvN0DF2NZtumIsXza1mNc96Zmy5dvOsLRa8Zjp7ZAT1quhv2vj6xU7ELlLFo6j54PdyMvT8uU52ZzOvyc2XI7ezs2bVlj+tvbV83Pa3/n1TmLGDFyEK8vmEVCXCIAX33xP/733c9ViuPtpfMIfbgrmjwtU56bw5lS4vh9y//M4vhl7e/Mn7OY4SMH8dqCmaY4Vn+xhjVVjOO1RTPp3rMzGo2WWS++ztnTF0qksbBQ8cbS2bTv1BqDwcC7b39M2KadePuqeefjN3FwdECpVLJ8wYfs3n6gSnEI/00PvrFBoaDu4vGcGbaA/Pg0Wm5dTOq2Y+RdijElUY/sgS4jh6MdX8RjQDABr47mwqT3KUzL4uxTSyhITMe2oT9Nf3yVv1tOAqDWtMEUpmRyrNNUkCRULval5C3RYMk4Tg57m/y4VNqGLSYl7Bi5l2JNSXxG9qAwI5dDHabiNTCYuvNHEjFxBXb1ffEaGMzhrjOwUrvQcv2rHOo4Dbv6fviMDuVon7nIBTpa/DSXlG3H0UQaDw43PttM9C0nxBK3dAqJBkvGc3LYQvLjUmkTtpjksGPk3RaTLiOXwx2m4DkwmKD5ozg78QMM+YVcW7IWu4a1sG/oX+LrnnvuQ7LDr1XhR3rwjg9+i8K07DKXZ/x9nlOjl1Vp2/r8Qq4uWYt9Q3/sSiknz37tjBc45W3HYGDxxoN8OqEPXk52jFr5O90a1SLIy8WUZmb/DqZ//3jgLBdiU01/j+nWDG2hjp8PlzzIV+r7GAws3nSMT8f0wMvRhlGfhdGtoR9Bnk6mNFGpWazee45vnnkYRxtL0nKM3+9UdDKnopNZ/3xfAMZ++RfHIpNoG+B1VzGVZWC/Xowc0p+5C965J9u7Uz3RRCVxbOCb6DJzcevRgkbvTuBI31crvO17Uk8UCrxee56YcXMpTEyh9voV5Oz8m4Kr0aYkhfFJJMx5F5dxQ0qsLmsLiBr0QoVjvpOHe3cnqG4dmjcNoW3bFnywYiEh3QaZpcnJySW4Q/EN0b4Dv/P7b2EALFo8lx9+2MAPazbQrVtH3nxzFhOeeanScegNBhb/vJdPJ/fHy9meUe+tp1uTAILUrqY0Mwd1Nv37x72nuRCTbPrbykLJulkjKp3vHSkU2D8/jcy5MzCkJOO84jMK/j5g1piQv3s72j9/B8CyfTB2E54na/6sCmdxp7pamJHDxXnf4NG3TZXCv5fHtEXf/vF/9u47PIrif+D4e+8uufTeE0pIQgm9B6QX6dJFQSwoVbGAiCBgQwELoqLYwPJTURABQelVQXrvLQRI771c2d8fl1xyXA4ujYSv83oeH8nt7O7n5mZnZ2d3Zvly5lP4ergwet4XdGvViJBAH2Oar9fvpk+7Jjzcqz1XoxN47oMf2NSiAaFBPvz81mRUSiWJaZmMnL2Uri0boFIqy/Wd+vTpTmhoXRo37kK7di355JN36NJlsEkapVLJBx+8QcuWPUlOTuWdd2YzefKTzJ//ETt3/s3cuYvQ6XTMnz+LGTOeZc6cBWWKoUaVVYUCz9lTiZs4E218EgE/LyVn979orhXXJdq4BBLnvo/rEyNNVrXv3A51w1CiH56EZGuL/zcfkPPPYeTsnDKHodPrWbB6N188O9SQJ+//Qtem9Qjx9zSmmTG8uINq5Z4TJnky5/+28kyftnRoWIec/IK7dmzfD8eNyTb1ehb8cYAvnn4QXxcHxnz2J10b1SLE182YZsbAdsZ/r9x/ngsxKeWKX7BOr95dqBdSl3YtH6R1m+a8t/gN+vZ82CRNdlY23TsPMf69fc8a/txQ3DG7/ve/eHXG2xWKo2fvLgSH1CGiZZ/COF6nX89RZnH07Fx8Xt66Zw1/bthWIo5NzK5gHN16PUDderXp0W4wLVo35a33ZzG8zxNm6aZMe4bkxBR6tR+KJEm4uRvalM9Nf4Y/12/j529/I7R+MMt/+ZSurQZWKCbhv+Wez9ng3DKU3Mg48m4kIGu0JK7bh2cf0xOHZ5+2xK8y9MInbjyAe6cmAGSfuU5BfCoAORduorCzRbI19Jf4PdKdG5+uNWxAltGWcrJyaRVKbmQ8eVEJyBod8ev249XXtIfeu28bYgv3nbCheN9efdsSv24/coGWvBuJ5EbG49IqFMewQDKOXUafW4Cs05O6/xzeA9pbnR8urULJiYwzxpSwbj/et8Xk1bcNsat2G/KjREz6nHzSD11En19g9f7+1/gN70S7ze8QsWMRjd4fDwrzhow+J5+0QxfR5WvMlikd1NSeNIDIj36/677O3EyklpcLQZ4u2KiU9Glej91nb1hMv+nENfq2CDH+3T4sAAe1jZXf7A5x3EqmlocTQR5Ohjia1mH3hVsmaX4/cpVR7cNwsbcFwMPJDjB0dhVodWh0egq0erR6Gc/CZVWhTYumuLo4V9n2S0o/cglterbh30cvoy7RGL5X5cSuWX00N2LQ3IoDjZbMv/bg1DPCJI02OsHw9IJctbMaDxzYm5U/GeI9fPgErq4u+Pp5W0wfGhqMt7cn+/YdAqBhw1D27P4XgD17/mXAwF7liuNMVAK1vFwJ8nI1lNeWYew+HWkx/aZjl+nbun659mUtVf1G6GKi0cfFglZL/p6d2EZ0Mkkj55S4MLOzh0r8uTRJGWScuIqs0Zktu6d12tVb1PL1JMjHAxuVir4RTdl99LxpIgmy8vIByMrJw9vNcDzbq22NHQv5BRoq+nDUoEEP8tNPhifWDh06jpubC35+PiZpJElCkiQcHR0AcHFxIjbW0LG/ffvf6HS6wvWPERTkV+YYalJZVTdpgOZmDNroONBqyd68G4duHU3SaGPi0VyONJsh3bZeHfKOnTY8IZCbR8Hlazg8UL4L9DNR8aZ50ro+u09bvomx6eglY55cjU1Gp9fToWEdABzUttjblv8cWFOOm5LO3EyilqcLQR7Ohe2CYHafv2kx/aaTkfRtHlymfQhl03dAT35daXjq6uiRk4Zzn6/lc1+9kLp4eXny7/4jlR7H6pXrjXG4uLrgc9c4PDhQyXH06teNtasMNz1PHD2Ni6sz3r5eZulGjn6IZR8bnpCWZZnUlDTjv52cHAFwdnEmIS7RbN3/DL1c8/+rgcrc2SBJ0qWK7FDt70F+TPHd3vzYFGxLXBQUp0ky/KHTo83MQeVhesHiNTCCrNPXkAu0KF0MDY+6rzxCy62LaPT1NGy8XLmdnZ8HeSX3HZOM2s/dJI3a34P8wrvRcuG+bTycUfu5kx+dVCLuZOz8PMi6cBO39g1RuTuhsLfFq1dL7AKLv0/QuD602/UejZZMQuXqaJ4ffrflR0wy6hJ3UUqLSVcY0900+ngKbXe8R92XzO+g1jStfn2N9lsXEDi2Z6nLXVvXJ2Lne7T8+VUcGwQB4BgWiN+QjhweOI8DPWci6/T4D+9cpv2GvDqKqGUb0eXevcMmIT0HvxK/oa+rAwkZ2aWmjUnNJCYlk3ah/mWKxxoJmbmmcbg4kJBhescqKjmTqKRMnvh6K2O/2sK+yzEANK/tTdtgX3q9v5be76+lQ6g/9bzNj5Wa6m7lpEjg6O4k7zwB3NtyovL1QhNbfCLWxiWh8vW8wxqmJLUtdX77mNq/fIRTzw5livF2/gG+3LoVa/w7JjqWgADLF2AjRg5kzW9/Gv8+ffo8gwf3AeChwX1wcXHGw8PN0uoWJaRn4VfiSTNfNycS0i0cNykZxKRk0C4s0PhZgVbH6A9XMfaj39h5qnKe1FJ4eaFPTDD+rU9KROFp3viyGzgE9xU/4/j0JLK++LhM+7C2rJZ0z+u01Az8PIqPfx8PF+JTTYceTB7Wkz/3naT38+/x7Ac/8OrjxXe0Tl25ydBXP2HE7KXMeWpwuZ9qAAgI8DMpr9HRcWblVavV8vzzr3HkyFYiI4/QqFEY3377i9m2nnhiFFu27C5zDDWprCp9vNCVaNTrEpJQlXKBUJqCS9ew79gWyU6Nws0Fu7YtUN7WcWOthLQs/NyL2xu+bk4kpGWVmjYmJYOY5HTa1Tc8NRCVkIazvZppX29k1KKfWbzub3R3GfN8Pxw3JSVk5Jifjy2VmdQsYlKzaBdS9o4wwXr+/r4mQ/5iYuLwC7D89ObQ4QNYt/Yvk88GPvQgu/f9wYofPiYgsHy/l7+/L9HRxXVabEwc/neIY8jw/qxfu+m2OHqza996vqlAHL7+PsRExxv/jotJwM/ftNPD2cVQ7700awrrd/7Ep8sX4eltuBb5+L0vGTKyP/+c2sTyXz7hzVnle8pY+O+64zAKSZIyKb6fU9RN7FD0uSzLpQ+8q2IODYIInjOG06PmGwJTKVEHepFx5CLX3viewIkDqff641yc+mmVx5JzOZrrS/+g5a+vocvJJ/PMdWSd4WQa/f02IhevARnqvfowYW+O5cKLy6o8JoCzUz6hIC4VpaMdTVdMx29kF+JW770n+y6rw4PmkR+Xio2XC61XzSH7cgxpB4rvrmWciuSf1s+iy8nHq2cLWnz3Mvs6vIhH5ya4NAum/ZZ3AVDY2VKQlG71fp0a18Ghri+X5v2AXS3Lvc3lseXENXo1DUapqJ4Xvuj0em6kZPLNuF4kZOQwbvl2Vj/bn7ScfK4lZrB1uuHxwUnf7+TYdX9a1S1fQ/Reuls5KeL+QGMCRvfgyEPzAGp0ObndtR5PoE1IxibIj1rfLyT/0nU0N2PvvmIlGDFiEM+UGCYxe/a7LF78JmPGjmDfP4eIjo413jmuKluOXaFX8xCT4+aveY/j6+bEraR0xn+2nrAAT2qV0plcFfI2riNv4zrU3Xrh8OjjZH1o3WP51pbV29XEsrrp31M81LklT/TvxMnLN3jti99Ys2AqCoWCZqG1WLvwea5FJzDnqzV0ahaGugJ3ru9GpVIxYcJYIiL6c+1aFB999BavvPIsCxcWn+tnznwOrVbLypVrqywOqHlltaTcf49i27gB/t9/jD41jfyT56CKj12ALUcv0atFmDFPdHo9x6/G8MvM0fi5OzPz27/44+A5hnZoUur6/0vHTWm2nIqkV5M61dYuEEo3dHh/pkwsHiK3ZdMufv9tIwUFGh5/ahRLv1jEsEHmww4q25Dh/Xlu4kzj31s37WJtYRxjnxrFp18sZPigJ6tk3yqVCv9AP44dOsm7cxczbvIYZr35Ei9PmcugYX1Y88sGln/+Iy3bNOODz9+mX6eRyFX8dKbwv+NuczZ8C7gBM2RZjgeQJClSluU7PgMmSdIEYALAdOdWPORQz7gsPzYFdUDxnT61vwcFsckm6xvSeFEQmwJKBSpnB+OwCFt/D8JXzODi1KXkRRl66rQpmehy8owTQiZt+Be/0T3M4sqLS8Gu5L4DPMmPSzXfd6An+bEpSIX71qRkkh+Xijqw+K6C2t+TvDjDuLvYn3cR+/MuAEJmP0Je4Xi8gsTik13Mjztp/uNMbpcfd1t+BHiSH2c6nu/2mJSFMd1JQeH30mXnEff7P7i0DK2xnQ1Fv4EmKYOEvw7h2jLEpIGhy8o1/jtpxwkaLlQanuyQJGJW7eXKOytNtufdry0hL48A4Ny0L8mwMG+FW5v6uDSvR6fDnyKplEhObtg+8AgF+8zvlAH4uDoQV+KORXx6Dj4u5k+rAGw+eY1ZQzqWuqyifJztTePIyMGn8OmeIr4uDjQJ8sRGqSDQ3Yk6ns7cSMnkSGQ8zWp5GodzPBAWwMmbSfdFZ8PdygmAU3htwhdP4PijC9GkFt59q+RyYuvlQq0fFnHzcfPjWRufhE2JOwYqPy+08clm6SzRJhjSam7FkXPoFOrwkDJ1NkyYOJYnnzKMGT969BRBQcVP1gQE+hMTU/oEj02aNkKpUnHiePGEfHGxCYx+1DDJm6OjA4OH9CU9/c71Tml8XJ2ISy2+ExqfloVPKU95AWw+fplZI7qYfObrZrjjEuTlSpvQQC7cSqzwBZw+KQmFd3GZV3h5o09Ospg+f88OHJ97yertW1NWS1XZdZqdM7YNu1JwofTJAX3cXYhLKT5PJaRk4Otueg9h7Z6jLJvxOADNw2qTr9GSmpmDp2vxEwD1An1wUNty5VYCjesFYq2JEx9n3LhHAfPyGhjoZ1Zemzc3TEB57Zphbo01azby8stTjMvHjh1Bv3496dfvUatjKKkmlVVdQhLKEsOelD5eaOMtl9HbpX/zM+nfGCY99V4wC01U9F3WKJ2PmxNxqcXHfXxaFj5upcyJBWw+dolZI7sZ//Z1c6JBkDdBhXnQvVkIp67HMdTCQ1s15rhxdsO28xgK/v6p1PQl+bg4mJ+PLZWZk9eZNdj6YbaC9cY9M5qxTxjmZTh+/LTJUwABAX7GSRZv17hJA1QqJadKTJ6cmppm/PeP36/m9TdnWB3HU8+M5rHCOVROHD9NYGBxneYf4EeshTjCmzRApVJZjOOn71cz782XrY7jsXEPM2qsYS6I0yfOEhDoy9HCZX4BPsTFmg6FSE1JIyc7ly0bdwKwaf12Ro4x3JQaOWYI4x42zCV1/Mgp1GpbPDzdSE4yvX4SBEvu2L0qy/LzwMfASkmSnpckSYEVI1dlWf5KluU2siy3KdnRAJB54gr29fyxq+2DZKPCe8gDJG81HZ+UvPUIvg8bJhzyHhhhfOOE0sWBJj/OIvKdn8g4fPG2dY7i1tEwI79b56YmE04a9338Kg71/LCr7Y1ko8R3SEeStpjuO2nLEfwL9+0zKILUf84aP/cd0hHJVoVdbW8c6vmRcewKADZehsaZOtAT7/7tiP/dMLu8rU/xI8fe/duSfcF8HJ8hJn9jTD6lxnQU/4e7GbZTIiZLJKXCOMxCUinx6t2arFL2XVMoHQ1zBigc1Hh2a2YWq22Jx/xdWoaAQoEmJZOUv0/jO7C9Mf9Vbo7YBXmRuOkwB3rO5EDPmRYbFwC3vt/G3uaT+aftVA4/9DpyVorFjgaAxkHe3EjKIDolE41Wx5aT1+gaXtssXWRCGhm5BTSvUzUX8I0DPbmRkkl0apYhjtNRdG1o2sDv3iiII9cNj4mnZucRlZxJkLsT/q6OHL2egFanR6PTc/R6AvW8q+UBpTJROKjvWk7sAj1pvmI6Z579jJxrxRfolV1OCq5Hl9rRAJB3+hI2dQKwCfQFGxXO/buStfOAdd/RxQnJxtAJpHRzwb5lOAVXLM8JUpqvvvw/OkYMoGPEADZu2MqjY4YB0LZtCzIyMom3MNZy5MhB/Lb6D5PPPD3djZO5vTxjCv/3w+rSVr2rxrV9uJGUTnRyhqG8Hr9M1yZ1zdJFxqeSkZNP87rFjcSMnDwKtIY7sqlZuZyIjKXebcPMykN76QLKgCAUvn6gUqHu2oOCA6azaysCio8p23Yd0EWbn1NKpba7a1m1pNLrtLxMix0NAI3rBXIjLplbCSlotFo2HzhN11YNTdL4e7py8Kxhn9eiEyjQaPFwceRWQgrawrvlMUmpXI9NIsC7bMNsvvzyB9q370f79v34448tjBljGPLXrl1L0tMziYtLMEkfExNPw4ZheHkZykDPnp25cMFwHu7duyvTpk1mxIinyc0t2yR/RWpSWc0/exGb2oGoAg1l1LFvN3L2/GvdygoFCldDG8AmLBjb+sHk/lu+ceCNa/tyIzGN6KR0Q54cvUTXpvXM0kXGpZCRk0fz4OKLq8Z1fMnMyScl0zDM79Clm5bzRKmqOcdNZopVHQ0AjYO8bmsXRNK1UZBZusiEdDJy82leu2qfjvuvWvHNz3TvPITunYewaeN2Rj1quFBu3aa54dwXX/q5b9iIgfxeYvggYDK/Q9/+Pbh06arVcXz7zc/07DyUnp2HsmnjDkY+OtgYR2ZGJgkW4xjA2tviKDm/Q5/+Pbhchjh+XLGKQd0fZVD3R9n6126GPmwY/taidVMyM7JILKXjcufWvUR0Mszt0rFLO65cNBwzsbfi6NjFMMlpSFgwajv1f7ejobrnY7hP52y469soZFk+KklSL+A5YA9QsdnkdHquzF5Ok5WvGV59uXIXORdvUeeVUWSeuErK1iPE/byThkun0vbfT9GkZXFh4kcABI7ri32wH3WmjaTONEPP4elH3kaTlEHk/B9p+OlU6r39JJrkDC69+Ln5d9HpuThrBS1/mQ1KBbErd5N98Rb1XhlJxslrJG05SszPuwhf+hwdDnyMJi2LMxMN43SzL94i4Y9/ifj7Q2StnouvrjD+qM2WT8PG3Rm9VsfFWSvQFo6fD503BucmdZFlmbybiVx42fxVSrJOz6VZK2jxiyE/YlbuIvviLYJfeZjMk1dJ2nKU2J93Er70OSIOfII2LYszE5cY1+9weCkqZwckWxVe/dpyYtR88m4l0fyX11DYKEGhIPXv08T8uL1CP1tVarvhLcDQSRK3dh/Ju04S9LhhMrpbP2zHd1AEQU/0NsxXkVfA6aLf5FI0Vxb+SutfXwOFhKzRcWHWCvJumVeinQ5/aswnn35tOTbqHZO3kFhDpVTw6uAOTP5mM3q9zOC29Qn1c+fzLUcJD/KiW2PDJFibT1yjb/N6ZrNuP/X5Rq4nppOTr+HBd1byxojOdGxg3iixKo4BbZj8wy5DHK3qEerjxuc7ThEe6EG3hkF0DPXn3yuxDPt0IwpJ4qU+LXBzUNOrcS0ORcYz8rO/kCToGOpP14Zlj8FaM15fyOHjp0hLy6DnkMeY8vRYhg/qU+btqL1daf6toVffUjmpN30ENu5ONFr0NIDx1Wn3tJzo9CS8vYyg5fNBoSR9zVYKrtzAc+pY8s5cInvXQeya1Cdg6VyULk44dW+P9rnHuD5oErYhtfB7cyqyXkZSSKR8vcrkLRZltWXzLvr06c6pM7vJzcll0qTix0T3H/jT5C0Uw4YPYPjQp0zW79w5gjfemoEsw759h5j24rxyxaFSKnh1eGcmf/GHoby2b0Sovyef/3WQ8No+dGtieFBu87HL9G0VZnLcXItPZf6q3SgkCb0sM65XK5M3A5SbXkfWsiW4zv8AlArytv6F7sZ1HMaOQ3vpAgUH92M/aBg2LVuDVos+K8vqIRQKd/e71mm23q6037oAlbM9sl6m9oT+7O88vRrqNCWzHh/I5Pe/R6/XM6RLa0KDfPlszXYaBwfSrVUjpo/ux1vL1/Hj5v1IErw1YRiSJHH8UhQrNv6NjVKBJEnMfmIQ7s6l39G1xubNO+nbtzvnzv1NTk4uEyYU38U7eHAT7dv3IzY2nnfeWcL27avRaLTcuBHN+PGGoT9LlryNWm3Ln38aLhIPHTrO1KmzS92X5fyoQWVVpyd5wVL8li0AhYLMdVvQXI3CbcoTFJy9RM6ef7FtXB/fj95A4eKEQ9cIdFMeJ3rYeCSVEv9vDe0mfXYOibMXga5874dXKRW8OrIbkz9fh16WGRwRbsiTP/8lvLYv3Qo7HjYfu0TfVvVN8kSpUPDS0E5MXPo7sgyNavkwvGPpQygkW4f75rgxy5+H2jN5xXb0sp7BbcII9XXn823HCQ/0pFvhDYluUkQWAAAgAElEQVTNpwwTQ1bVa6aFYtu27qHXg105dGIbuTm5PP9scT2w6+91Jm+heGhoPx4dMcFk/fGTxtKnXw+0Wh1pqelMnTyrXHFs37qHng924eCJreTm5PFCiTh2/L3W5C0UDw3tx+hS4niwX3d0hXE8X844dm/7h269OrHz8HrycvOY+fwbxmUbdq1kUHfDk2CL3vyED5e9zZz5L5OSnMorUw3p3p23mHc/mstTk8YgyzKvPPd6ueIQ/rska8bcSJI0EtgCOALjgRbAfFmWj91t3b1+I2tEN4tGrhlj5KTKnNK8EvSIX1XdIbDNd9TdE90Dnb5qffdE90pe7t3T3AOqnmOrOwQAdjcu30m2KtR2z7h7onug9Y2KvUK1siSusX54QVXL/mRNdYcAwPFjNWMCuM4bRlR3CEZuXaZXdwgApK61/lHkqhT36obqDsHI7/2hd090D/wz1vJTOPdSp2XNqzsEE/bDytZp9r/M27VBdYdgpDB/mX21cLJxuHuie+Rq0rGakSlVJGvG0Jp1EVcKp/fX1rjfwNor8LmyLGcAIUB3YDlwb2Y6FARBEARBEARBEITqIutr/n81kLWdDUXTGA8AvpZl+U/AtmpCEgRBEARBEARBEAThfmZtZ0O0JElfAqOAvyRJUpdhXUEQBEEQBEEQBEEQ/kPuOkFkoYeBvsAHsiynSZLkD1j/LhhBEARBEARBEARBuB/V0Lc91HRWdTbIspwD/F7i71jA+pe/C4IgCIIgCIIgCILwnyGGQgiCIAiCIAiCIAiCUKmsHUYhCIIgCIIgCIIgCP85shhGUS7iyQZBEARBEARBEARBECqV6GwQBEEQBEEQBEEQBKFSiWEUgiAIgiAIgiAIgmCJGEZRLuLJBkEQBEEQBEEQBEEQKpUky1XbS7PNd5ToBqrBesf/Wt0hoEm6Vt0hALC78azqDkGwoNvZBdUdgpEoJ8Ld1JTyKsqqcD8Rx03pakI7rabY5juqukMQ7qB3/K9SdcdQlTKfH1jjr2mdP9lY434D8WSDIAiCIAiCIAiCIAiVSszZIAiCIAiCIAiCIAiW6PXVHcF9STzZIAiCIAiCIAiCIAhCpRKdDYIgCIIgCIIgCIIgVCoxjEIQBEEQBEEQBEEQLBGvviwX8WSDIAiCIAiCIAiCIAiVSnQ2CIIgCIIgCIIgCIJQqcQwCkEQBEEQBEEQBEGwRAyjKBfxZIMgCIIgCIIgCIIgCJVKdDYIgiAIgiAIgiAIglCpqnoYhV27ze+gsLVBUiqI33iQa++vNklQe+IAAsf0QNbpKEjO4NyLX5B3K8nqHTiEBtD448m4NA3myoJfiFq20TSBQqL91gXIOh0KWxvQy8haHRfnfk/aoYtm22v9+zzUvu7o8woAODrqHTRJGVbHU2tcH2pP6I9DsB+7Gz2DJiUTAJWzPU0+n4pb2wYone0pSEzn7xaTS92Ge8dwGrz9BJJKiSYlkyND37R6/zbuTjRbPg2XFiHE/LKbi7O/NS6TbJQ0XDAO947hoJe5suAXq7dbk815dzF79x3Cw92NdT9+Ue7t1J7Yn8DRPQDIOn+Dsy8sQ5+vMS73H9WV+vMeIz8uBYCbK7YQ/dNOq7dvqayqAzxpsvRZbL1cQZa59eMObn69yer1rWWpbCjsbWn29Us41PVF1ulJ3HaUK/NXAtDp8Kdos/NAp0fW6jjYZ7bJNv2Gd6Lucw+BJKHLyuX8K8vJOhdV4ZhKavHDDFRuQWjTbpXp+5ZUWWUEQOXiQPjiiTg1rIUsw7mXlpF+5HLxcldHGi+ZhH1dX/T5Gs6++AXZF26WaR91nx9C4OjuyDo9F1/7juTdJwGoNb4fQY/1BECXnYd9HR8KkjL4t+vL5nEW1jl2gV5ISgVRyzYS88tuq2MoS3lN3nXSqrLp3qkx9V8fi8JWRcbJa5x76Qtknd7qmHwGRRDy8ggc6wdyqO9rZJy8ZlzWbusCXJrUQdbqOfH4+8Y8K1KVZbXlylmofd2RlArSDl6wepuWVFZ5DV8yCe/erSyWkeqoU0rj0iKEtn++zemJH5Ow8aDV+y9PnWrtd66qsloyzxI2Hcahrq9V+R8yaxS+gyKQdTK3vt/KzW82VzgWjy5NCZszGslWhVygReVsT/bVGE489p7J+nZBXoQvmYStpwua1CzOPLuU/NgUq/dvKc8VahvarH/D2EZUODihz0m1eru3q8x6/nbWnqctCZk1ioCRXVC5ObGr3hNmy30GtKP5iukcfHCWSb0mmKszZRD+wzsBIKmUOIYFsjv8GbRp2aWmb/DOkwQ82r3UfL8TS+15775tCJn5sMXriapqw99+njn/6nLQy3et56sypiItfpiBfR1fq7d5v5Ll+38YhSRJfYGPASXwjSzLCy2kGw78BrSVZflIRfZZ1Z0N+UeHvYUuJx9JpaTthjdJ3nmC9KPFDfPMM9c52GcW+twCgp7oTdi8MZye8LHVO9CkZXHxte/w7tem1OW1x/cn+3I0KjdHTjxqyE+n8No0++pF9neaVuo6Z6Z8Wu7KPu3QRRK3HaPN7/NMPg8a14esi7e4/tkGJJWC1qteQ7JRImt0JulULg40XPg0xx99l7zoZGy8XMq0f12+hqsLf8WpYS0cG9YyWRb84jAKkjLY3/ElkCRs3J3K9R1rmiH9ezN6+EPMfvuD8m9EoaT2M/3Y33ka+jwNTb96Ed8hHYn9dY9Jsrj1+0utaK1hqazKWh2XXv8/Mk9HonS0o/22BaTsOUX2pWir1rfWncpG1LKNpO47i2SjpPVvc/Hs0YLknScAODrsLeNJ9na5UQkcGfIm2vRsPHu0IPzD8RzqN6dSYgLw6d/O0NlRQZVSRgo1mP8kybtOcuqZj5BslCjt1SbLg18YQuaZKE4+9SEOoQE0XDiOYyPmW719x/qB+A3pyP4u01H7udN69Rz2dXgRx/pBBD3Wk4N9ZyMXaGm7aT5np31J2OxHS91OUZ1zYux72Hg688C+JcSu+duszrGkLOU18+S1u5dNSaLJJ1M4OmI+OddiCXllJP6juhLz8y6r8yb7wk1OjvuQRu+PN/ncsX4gNi4OHBo4jyZLn6XhonHs6/CiyfjKqiyrp8YvQZeVC0Cz5dOQbB2RC0pv+FqjssprzC97uLl8C02WPlvq8uqqU0woJMLmjiZl96ky7788dapV37kKy2rJPHNuEWJV/gc80g27AC/2PzANZLnM7QJLsWhSMjkx9j3y41MJnTeG2uP6kH01xmz9+q+PJXbVXmJX7cW9U2NCX3uUs899ZvX+LeW5Pl9DyTZij+srkFQ5yNr8Mn2/IpVZz9/O2vO0JUlbj3Fz+RYeOGDevlU62lF7fH/SSrSNBcuiPt9A1OcbAPB6sBV1Jg6w2NHg0rweKlfHcu3HUns+Ze9pEjcbrr1uv56oyjb87ecZ34c6EL9u/13r+aqMCSqvnSZUPUmSlMBnQG/gFnBYkqQ/ZFk+d1s6Z+AFwPre/zuo6mEUsi7HcNKQbJRIKpVZr1DqvrPocw1PEaQfvYydv6dxWZ0pg2i3+V0idr1HvRkjS92BJimDjBNXS21Aq/098Ord0nD3ucQdCaWDmrJ2Ttl4OtNs+TTabX6XdpvfxbVtg1LTZZ65Tt7NRPMFMqic7Ek7cB69Rous0yNrze+S+A3rRMJfh8iLTjZ+P+Oy4Z1ot/kdInYsMjQaFJLZ+vqcfNIOXURX4o58kcBHuxH5ybrCeGSLF5D3mzYtmuLq4lzh7UhKBQo7WySlAqWDLflx1t9hqUhZLUhII/N0JGC4W519ORq1n4fV60PFyoY+t4DUfWcBkDU6Mk9HYhdgvv/SpB+5hDbdcJJPP3oZdYnjt6LlVemgpvakAUR+9LtVsdxJZZURJAn3Do2MT7TIGh3ajByTJI71g0j55wwAOVdisK/lja23K2Bdnnj3bUvcuv3IBVrybiSSExmPa6tQHMMCST92GX1ugeFu8aYjuLaubznWwjoHDI1ZTVqWsc6p7PKqsLO1WDaL2Hg4oddoybkWC0DyntP4DmgPgMJBTfiSSbTb/A7tty/Eu2/pF1/Zl6PJuRpbap5F/7yLgsR0ZI3OmGclVWVZLWoASiolCtuK9+FXVnlNO3AeTVqWxeU1oU6p/Uw/4jcepCAp3eTzqqpT7/Sdi1RlWS2ZZ/q8grvGAhD0ZG+uffgbRQ2XonZBRWPJPHOd/PhU1P4euDQLNtQPknmz0LF+ICn/GH7P1H/O4lNiPxVtp5m0ESXzMlYWlVbPl8JSmbKv40vLlbNov3UBbda/gUNoQKnrpx+9TEFCWqnLQl4dxfWl641P1ArW8xv6AHFr95W+UCER9vpjXH7rJ5OPK9qeLyqzYH49UZVteLPzTOGO71bPV2VMldlOE+6JdsAVWZavybJcAPwCDC4l3dvAIqBSepGqfs4GhUTEjkV0Pfs1yXtOkXHsisWkAaO7k1R458OjazMc6vlxqO9sDvSYiUvzYNwiGpVp1w3efsJQyRTe3fLu15aO/yym5Y+vcu6lZRbXC/94MhE7FhH80rDibc1/khtf/smhvrM59fSHhC+eWKZYbi7fjGP9QLqc+oJWv7xGfnwapfV4OIT4Y+PqSOvf59F+6wL8R3YBwDHMcLfz8MB5HOg5E1mnx394Z6v3r3JxACB05sO037aQZl+/ZLwAEgC9juvLNtL52Od0OfUl2oxcUvaY32nzHdieiF3v0eybl1AHGC5WKqOsFrGr5Y1zk2DS73Cc3K6iZaMklYsDXg+2JuXvM8bPWv36Gu23LiBwbM87rhs4urvxzmVlxBTy6iiilm1El1uDGmAKGwqSM2j88WTab19I+OKJKBxMn2zIOheFz4B2ALi0DMEuyBu1v4fVeaL2cycvungoWX5sMmo/D7Iv3MStfUNs3J1Q2Nvi1aslaj93i6GWrHM67P6Ai3O+A1mutvKqSc5EUipxaV4PAN9B7VEHGo6hei8OJeXvMxzq+xpHh71F2LwxZvl6J5byzJLKLqsALX+ZTdezX6HNyq3QUw01QVXXKUXUfu749GvLre+2mXxe3XVqVZbV8rCv44vfkI603/IuLX9+FYdgv0qNpcHbT5C86yTZ12JBNr8JklmiTvPp3w6VswM27k6V8zuVaCPqC3LL/VTDvVSyTDX6cDwXZ3/LwQdncenNH2m06Okybcu5aTB2AZ4kbT9eRdH+71LY2+LVvQXxFoZe1Xq6L4lbjph18lS0PQ+Wryeqqg1fpOR5Jn7DAavWqcqYamQ7rSrp5Rr/nyRJEyRJOlLivwklvkEgUHJc763Cz4wkSWoF1JJl+c/KyrY73oKRJKmZLMunCv9tA8zE0CtyBpgvy3LOndYHQC9zoOdMVC4ONP/uZRwb1ip1/LLf8E64tAjhyJA3APDs1gzPrs2I2LEIMNyZc6jnR9qB81Z9Ma/C8UuZpyINcxQAiZsOk7jpMG4RjQiZOYpjI80fbT4z5VPy41JROtrRfMU08kZ2IXb1Xjy7NMWpfpAxncrZHqWD2qSH8048uzcn88x1jg57C7cOjWi9ag5KJ3tjT2URSanAuXk9jo54G6WdLe3+fJv0o5fx6NwEl2bBtN/yLgAKO1uzO0F3IqmU2AV6kXb4Epde/z9qTxxA2OuPWb3+/zxJgU/fNvzT9jm06Tk0++Yl/IZ3Im7NP8YkSVuPErd2H3KBlsCxvWjy6RSODn+7wmW1iNJBTfPl07g093uzcnEnFS0bRSSlgqZfPM/NbzaTG5UAwOFB88iPS8XGy4XWq+aQfTmm1O/l/kBjAkb34MhD8yolJqfGdXCo68uleT9gV8u7zN+lqkiSoXF4Yfa3ZBy7QoP5TxA8dTBXF60ypon8ZD0N5j9JxI5FZJ6/Qebp68g6fYXzJPtyNNeX/kGrX19Dl5NP5pnrSLY2FtOXrHPs6/rSevUc/j3wSrWW19OTPqb+W4+jUNuQvPuU8Ykzz67N8O7ThrpTBgGgUNtiH+hF9mXrHlEui8ouq0WOP/IuCrUNTT6fimRjj6yx/hiuaaqyTimpwdtPcnn+z2Yd79Vdp0LNKKtFFGob9HkaDvaZjU//doQvmcSRwW9USixevVsha3UEPd6LqwtX4Tf8AbM0l9/4kQYLxhEwqitpB86TF5OMrNNXzu9Uoo3Y9eznoLQBnfkd1JqiZJlCr8etTQOaffOScfmd6mQzkkT9N8dy9gXLN78Ey7wfbE3a4YulDqFQ+7rjOyiCo6XMTVDR9jxYvp6oqjZ8kZLnGY9OTUjZe/qu61RVTDW1nfZfJ8vyV8BX5VlXkiQFsBh4sjJjutvznt8BrQr/vRDwBD4EhgBfAI+XtlJhL8oEgBecWzPAPgRtRg6p/5zFq3tzs84Gjy5NCX5xGEeGvoFcoC3aBpGfrCf6/7abpA166kHjBGnHRy8kP770R93d2jXAb2hHAsd0B0mBrNXS5LPnOPPsUtIOnMe+jg82Hs5mQwmKHp3XZecR+/s+XFqGELt6L0gSh/rPMZkwEAy9jGpvV8MEUtO+tJiRAY904/qn6wHIu5WEXqPFMSyAjONXTfcfm0Jyahb6nHz0OfmkHjiPU+M6IEnErNrLlXdMJ9ny7teWkJdHAHBu2pcW55rQpGSiy8kj4c9DAMRvOEDg6O4W4/2vkWzsyb1xDU2yoTwk/HkIt7YNTDobNKnFj6lF/7SDsHljDOtWsKyCoTOo2YrpxK75h4S/DpVtGxUsG0UafTiBnMg4bnz1l/GzouNBk5RBwl+HcG0ZYtaQdAqvTfjiCRx/dGFxHlUwJrc29XFpXo9Ohz9FUilBaYPS1R9duvmjwPeSrNORH5NsfEIrfsNB6k41fQJNl5XLuReLG4+dDn9KblQC7hGNrMqT/LhU7AK9jMvV/p7GSUljft5lHDceOvsRw92E24YLFClZ5+Rejyf3RgKOYQGVVl7bbXkXlbMD9aYPJ/3o5TumL5J+5DJHBr8BFN299i/coMTJcR+aPeodvmQyLk3rkh+XyvExpc5hBFAizwyTdJXMs5KqoqyWpM/XkLj5CF49G97XnQ1VWaeULGcqFweafvE8ADaeLnj1aoms01V6nWrr62a8IL7bekWqqqwWfQeVmxMpf9/9QgEgPyaZ+L8Md28T/jpE+MeTKyUWMHRK+gyKQJOcQf23HkflZG9sKxn3H5/KqXEfAoaLbZ8B7dFm5FTK71REm5GDrMlFYeuAPrfsF2H3wu3naaWTPdqMbA70nGmaUCERsc2Q74lbjnD1vdWlbA1UTnY4NaxlnBPA1seNFj/M4MTj74tJIi2I2LHIWKb8hnS0OITCuWldHIL9jHNkKO1teeDAx+yLeKHC7fmS0g6cx7lxHTrsfh9Zpyfuj39J3nWy0tvwJRWdZ7z7trGqs6Gqritub6fZerkC7Aa63TUoobpEAyUn3ggq/KyIM9AE2F04rM0P+EOSpIcqMknk3TobSg7e6YlhRkqNJEl7gZMW1inZq+K9K+ypBG1GDgo7Gzy6NuX60j9M0jo3qUuj95/h+CMLTMYRJe06SeirDxO35m90Ofmo/dzRa3Xc+nYrt77detcvduWdlcYDyL1jOMHThxtPns5Ng1HY2ph1NEhKBSpXRzQpmUgqJd69WxkP5OQ9p6j1dF/jpDROjeuQdTaK44+8e9dYAPKik/Do3IS0gxew8XBGYasq9U5P4uYjNFjwFJJSgWSrwrVVGFFf/kX2xZu0+H4GUV/+iSYpA5WbIyone2PvqjUStx7D/YFwUv85i0fnJmRfisaplMle/pP0WlxbhaGwt0WfW4BH5yZmFaytj5vxcTzvPm2Md48qWlYBwj+aRPblaG58afrUkjXbSPn7dIXLRsiro1A5O3DupeITrMJBjSRJ6LLzUDio8ezWjGsfrjFZzy7Qk+YrpnPm2c+M45srI6Zb32/j1veGR6vtannT6cDiau9oAEDWkReTjEOIPzlXYwuPI9O3ZKhcHNDl5iNrdAQ+1oPUAxfQZeVanSe6vAKaLnueqC82ovZzx6Gen/ERcBsvFzRJGdgFeuLTvx2nxn+E35COpYZass6x9XbFISSA3KiESiuvybtPGe7ulUFR/JKtirpTHyJyyVoAknefpNbTfY2Trzo3qUvmmesmnTZ3krjlCE2XPU/8xgNINkqTPCtSVWVV6aBG6WRPQUIaklKBV++WNfrOrDWqqk4By3Va448nk7jtGImbjqDLKaj0OtXa9YpUVVkt+g7+o7oah2ncTcLmw3g80JiYG7tx7xhu7FyoaCwqFwfcIxpxevwSEv46hHvHcOpMGWjS0QAYbsykZoEsU/eFIcSsNHR4VrQusfF0Ns57o7CzQbK1R59TMzsawLxM6bJyyb2RgM+gCBIKH2l3Cq9D1rko8w6IUmgzc9kTXjxpZ+vf53H5zR9FR8MdFOWrytke9w7hnL6trBZJ2n6cvU2Lh0d0v/a9oaOBirfn7ev6kns9HjBcT+gLtPzbbQZgGJpQFW340s4zaQese/NRVV1X3N5Oa/njTJwa1upmVVD3K7189zQ122EgTJKkYAydDI8Ao4sWyrKcDhjvdkmStBt4uaJvo5Du9BoPSZKuAdMxzO0wX5blRiWWnZRlufldtt8s43TkSUmpQFIoiF//L9cWryHklZFknLxG4pajtFo9B6dGtSiIN1zE5UUnceLx9wHDa94CxxheRajLzuPMlKXkRsWb7MDW25X2WxegcrZH1svosvPY33m6ySOT7h3Dafje06AzvKZGl1fA5Td/NL6qJmLHIg70nInCQU3bdW8YJipSKEj5+zQX5/0AehkbD2caLhyHY1ggklJJ2oHznH/lG7MvXOuZvtR99iFsfdzQJKWTtOME56Z9idrXncafTMalZShKRzskCfLj07j6/moUKiUAt34w3B2oM2UQAY90A1km+qedxrtCvoM7EPz8EFBIyBodF2atMHmzR5FOhz9F5eyAZKtCm57NsVHvkH0pGrsgL5osfQ6Vq4PhNaMvLKPzsc/v8hNWPU1SxU6sM15fyOHjp0hLy8DTw40pT49l+KA+Zd7Oje+O4Te4A7JOT8bpSM5N+5J6Lw41ltXQ1x7F+8HWyDo9mrQszr/yDTlXDDN3V6SsOofXpu2Gt8g8F2WsyK68u5KkHSesWl+XlVuhsqHNzKXLiWVkXYpGLjBcJN1csYWUf87Q/FvDa5QkpYK4tfuIXLKWoMd7AYbyGr54Ij4D2hlfV1vy9ZgVLa9FijobKvLqy8oqIwBHHv6CxosnIhV2GJ59YRl+gzsAhjxxbRNG40+mgAxZF29x7qUvjBMTWpsnwS8OJeDRbshaPRfnfm+cX6DN+jewcXdG1urQpGbiGBaIjYczBYnpZnVJUZ1j6+teeAdynfFJncour9c/+4OwuWNKLZstf3rV8MRGfCph88bg1bs1kkLi1vfbjHWbws6GBm8/iWvb+kiSRO7NBLPX74HhjkvDd58yvIIvI5vMM8UNxIhd7xkejVUq0KRkcnn+zyb5UVVlVZOaRYv/m4lCrTKcN/adxX/wHSbutEJlldfkv2Nx7xhusYzc6zrlTq8KLupsKHr1ZVXVqXf6zveqrBrzTK1CqbZBl6cxtE0sxKJycTC8xjbIC112HudnfEPWuagKxxL80jCCnx9MzrU4wDAMIjcqgWOj3jFpp/kMbE/Ya48iyzJpBwyv3Ct6CrUiv5N9bW8afzKFojaifS1H9LmlT6Jojco6bnY3nmX2mVu7BqWWqazL0TRa9IzhlYQqJfHr9nNt8Rqz9cPmjsFv2AOo/dzJj0sl+qedXPvgN5M0ljobesf/Wubv8L9qm+8owPAqcq8eLTg90fTtHiWPm5K6X/ve+OrLirbn6z73EP4ju5R6PQFV04Yv7Txzae73yDo9Tb94/o71fFXFdHs7rbCzoWKzvNZwGU/3rvG9DS7Lt93xN5AkqT+wBMOrL1fIsvyOJElvAUdkWf7jtrS7uQedDbe/4+9VWZbjJUnyA36SZfnOM8YB23xH1fgf5r+sJpzEKtrZUFlKa2AINUO3swuqOwQjUU6Eu6kp5VWUVeF+Io6b0tWEdlpNUdTZINRMveN/FZ0N1exunQ3V4Y7DKGRZfgpAkqSRwBZZljMkSZqDYR6HGfcgPkEQBEEQBEEQBEEQ7jPWvhB8rizLqyVJ6gT0At4HlgHtqywyQRAEQRAEQRAEQahm8v0/Z0O1UFiZTlf4/wHAV4Xv3rStmpAEQRAEQRAEQRAEQbifWdvZEC1J0pfAKOAvSZLUZVhXEARBEARBEARBEIT/EGuHUTwM9AU+kGU5TZIkf8ScDYIgCIIgCIIgCML/OjGMolys6myQZTkH+L3E37FADXjpvSAIgiAIgiAIgiAINY0YCiEIgiAIgiAIgiAIQqWydhiFIAiCIAiCIAiCIPz36Ks7gPuTeLJBEARBEARBEARBEIRKJTobBEEQBEEQBEEQBEGoVGIYhSAIgiAIgiAIgiBYIIu3UZRLlXc2qKWaMcAlX64ZD3EoEQX1drsbz6ruEAAIdMqq7hCMdPqaUV5t1drqDgGoOWUEoNvZBdUdAgBft5xX3SEA0NMxubpDMIpNdaruEICaU17reKRXdwhG27O8qjsEAHo5JVV3CABEpbhWdwhGtd0zqjsEoOYcNzWpLSCYumZjU90hGNWMVlrNiUMQLBFlVBAEQRAEQRAEQRCESiWGUQiCIAiCIAiCIAiCJWIYRbmIJxsEQRAEQRAEQRAEQahUorNBEARBEARBEARBEIRKJTobBEEQBEEQBEEQBEGoVGLOBkEQBEEQBEEQBEGwpGa8YPG+I55sEARBEARBEARBEAShUonOBkEQBEEQBEEQBEEQKpUYRiEIgiAIgiAIgiAIFsji1ZflIp5sEARBEARBEARBEAShUonOBkEQBEEQBEEQBEEQKlW1DKNw796CkLefQlIqiPtpBzeXrjNZLtmqaPDpVJyb1UOTmsn5iR+RfzMRtyaicqAAACAASURBVC7NCH5tDApbFfoCLZFv/R9p+84Y1rFREfru07h2DAe9zPWFK0n682Cp+2/wzpN49WyJLjefs88vI/N0pFka52bBNP5kCko7W5J2HOfia98BoHJzpNlXL2Jfy5vcm4mcGr8EbXo2DqEBNP54Mi5Ng7my4Beilm0EQKG2oc36N1DY2iApFSRuPEDk+6tN9uXRvTlh8w35EfvTDqI+XW+WH+FLnzPmx9kJS8i7mYjK3Ymmy6fh3CKUuF92c2n2CrPv0fSHV7Cv48Ohri9b9+NUA5WLA+GLJ+LUsBayDOdeWkb6kcvFy10dabxkEvZ1fdHnazj74hdkX7hZpn3UfX4IgaO7I+v0XHztO5J3nwSg1vh+BD3WE4Cs1ZtI+W79nTaDY5fW+M2dgKRUkPrrVpK/NP0tHdo2xnfOBOwaBnPrhUVkbt4HgE2AN0HL5iApFKBSkvrDBlJXbirTdyjJqUsrAl4fDwoFqb9uI/GL30zjaNeYgLnjsWtYlxvPv0fGpv0A2DUKJnD+FBRODsh6HYlLV5H+5z/ljsOhU2t8X5sECgXpv20m5WvT/LBv0wSfWRNRNwgmZvpCsrYU76v+2Y3kX7oOgDY2kegpb95xXzWlnCjs7NHnZZRpu0XmvLuYvfsO4eHuxrofvyjXNsqi05tjqdOjBdrcfHZM+4qkM9fN0rR/ZSQNhndC7erI1w2fMVkWMrA9bV8aBrJM0vkbbJ/6ebniuJfl5HYe3VsQWqJ+vfGp+fmm0dLi8825CR8Z69fGy6fjUli/Xp693LiO9+CO1HlxGJJCQfK2o1yb/5PJNmtKWc1Z+ydpP6y702Zw6NQan9mTjb9N6jerTJbbt2mC96xJqOsHEzt9AVlbi38blb83vm+/iMrPG2SZ6Inz0MbEl+l7lFQTymt15EdVtEn8hnei7nMPgSShy8rl/CvLyToXBUD4kkl4925FQVIG/1rRNrhXx29NOW7up7aAULqOb42ldmFdsvul0uuStq+MpP4IQ12yosEzZsuD+7flwa9eYE3/uSSdMj8mrdHhrbHUKoxjz0tfkVxKHG1eGUlYYRzflRJH3f5t6f3VC6ytQBwRJeLYayGO1q+MJLQwjh9KxNHwsR40erI3sk6PJjuPfTOXk3Y5plxx3PfE2yjK5d53NigUhC54mtMPv01+bAotNy8geesRci7dMibxG90DbVoWhztMxXtwR4LnPMaFiR+hScng7OMLKYhPxaFhLZqunMPBlhMBqP3iMDRJ6Rx54AWQJFTuTqXu3qtnCxyC/dgX8QKurcNo9N7THOo3xyxdo/ee4fz0r0g/epmWP7+KZ48WJO88QfDUIaT8fYbrn66n7tTB1J06mCvzf0aTlsXF177Du18bk+3o8zUcHfYWupx8JJWSthveJHnnCTKOFp5AFRINFj7N8Yfnkx+TTJstC0jccoScS9HGbQSM7oE2LZsDEc/jM6QjIXPHcHbCEvT5Gq4t/BXHhrVxaljL7Dt492+HLjuvzD/RvdZg/pMk7zrJqWc+QrJRorRXmywPfmEImWeiOPnUhziEBtBw4TiOjZhv9fYd6wfiN6Qj+7tMR+3nTuvVc9jX4UUc6wcR9FhPDvadjVygJWL1TDJ3HUITFVv6hhQK/N+YTNQTc9DEJVFv7Udk7jhAwZXixo4mJpGYVz7Cc/wwk1U1ialcHzkduUCL5GBHyKbPydxxEG1CivUZVSKOgLcmETl2Ltq4ZELWLyZj+0HyS8YRncitGUvwGj/UZFV9Xj43py+m4HosKh8PQjd8RObe4+gzs8sVh++8Z7k1bjaa+CTqrP6YrJ0HKbh6oziO2ATiZn2I+7jhZqvLeQVEDX3O6t3VlHLS4/pyKMgBvdbqbRcZ0r83o4c/xOy3PyjzumVVu3tzXIP9+KnzdHxbhtD13SdZ89AbZumubzvG6e+2MWavaUyudX1p9ewg1g57k/z0HOw9XcoXyD0uJ7fvO2zh05x8+G3yY1JovWUBSVtMzzf+heebgxFT8RnSkXpzH+PchI/Q52u4vvBXHBvWwrFhbWN6lbsTIfPGcvTBmWiSM2j4ybO4dW5C2t9njGlqSlntsOYVsncfRHPDcp3mM/dZop8u/G1WfUL2rgOmv01MInGzPsSjlN/Gb+EMUr5cSc7+40gOdlCB8aw1orxWQ35UVZskNyqBI0PeRJuejWePFoR/ON643Zhf9nBz+RaaLH3Wqjy5V8dvTTlu7pu2gFCqWj0Mdckvnabj0yqETgueZN2gN8zSRW0/xtnvtvHI3+bnYxtHO5qO60P8sSsVjmNViTjWlxLHjcI4RlmIo0kF4wjq0RyXYD9Wd5qOd6sQOi54kg0W4jj33TZG3hbH1XX/cuHHnQDU7t2K9q8/xpbH3it3PMJ/zz0fRuHcMpTcyDjybiQga7QkrtuHZx/TC3TPPm2JX7UHgMSNB3Dv1ASA7DPXKYhPBSDnwk0UdrZItob+Er9HunPj07WGDcgy2pTMUvfv3bctsav3ApB+9DIqF0dsfdxM0tj6uKFysie9sEMgdvVefPq1LVy/DTG/GmKL+XWP8XNNUgYZJ64ia3Rm+9Tl5AMg2ShRqJQgFzdAXFqFkhMZR15UArJGR8K6/Xj3bWuyvlffNsSu2m3Ijw3F+aHPySf90EX0+QVm+1Q6qKk1aSDXP1pTaj7UJO4dGhH9k6EikzU6tBk5Jssd6weR8o+hIZ9zJQb7Wt7YersC4De8E+02v0PEjkU0en88KCSz7Xv3bUvcuv3IBVrybiSSExmPa6tQHMMCST92GX1uAbJOT86h07j06WgxTvvm9SmIikFzMw40WtI37sW5V4RJGk10AvkXr5s3MjVa5ALDxanC1gaplDit5dA8jIKoWDQ345E1WtI37MWld3uzOPIumMdREBlDwXVDA0qbkII2OR1VOS8i7ZrVR3MjBs0tQ35k/rUHp56m+aGNTjDc1ZIrNqmOytm+xpQTWZOHQu1Yru/RpkVTXF2cy7VuWQU/2JqLawx3GOOPX8XWxRGH2+q6omU5CWlmn4eP7s6Z77eTn27I59zk8j3NcS/Lye1cWhWeb6IM55uEdfvw6mt6vvHq25a4ovONWf16AX2+xiS9fR1fciNj0RTmR+re03gPKP4+SmeHGlNWcw+fxqn3Axbzx65ZAzQ3Yo2/TcZfe3Ds0cEkjTYmnoJLkWYTY9mG1EZSKsnZf9zwPXPykPPyLe7rbmpCea2O/KiqNkn6kUto07ON21X7exq3l3bgPJq0LCvz5N4cvwqnmnPc3C9tAaF0dR9szaXfDHVJwrGrqC3UJQnHSq9LANrOGMGJzzeiu63+L4s6D7bmcok4bF0csbcQR66FOFrPGMHJSojjSmEciXeII9FCHJqsXOO/VQ5q5Eo+Twv/++7Y2SBJ0nOSJHkV/jtUkqS9kiSlSZJ0UJKkpuXZodrfg/yYZOPf+bEp2JY4CRanSTL8odOjzcxB5WHaQPcaGEHW6WvIBVqULg4A1H3lEVpuXUSjr6dh4+VqYf/u5EUX7z8vNhk7fw+TNHb+HuTFFvcy58WkoPZ3B8DW25WCwoOxICHNeKK7I4VExI5FdD37NSl7TpNRoodS7XdbfsQko/YzjUft70F+YcyyTo8uMwcbjztfsAS/+gg3lm1An2veEVHTFCRn0PjjybTfvpDwxRNROJjezcg6F4XPgHYAuLQMwS7IG7W/B45hhrsUhwfO40DPmcg6Pf7DO5ttX+3nTl50kvHv/FhDHmdfuIlb+4bYuDuhsLfFqWsbbPy9Lcap8vVEE1u8HW1cEja+nhbTm63v70W9P5cS9s93JH35W7nvZKj8TOPQxCVj42d9HEXsm4ch2agoiIorXxy+XmhiE41/a+OSUJUhP/6fvbsOj+L4Hzj+vrh7chECRHBIsOAQSAIJ7tAiX1qkLS20SHErFG9LvaX0Vyrf4iV4cdeiwS0Ejbv77e+PSy+5CDlCSK7fzut58jy529mdz+3N7s7NzszKDA2o9ceX1Nz4OWb+bZ+b1qimg9aUE5mBCeho/4N8TB2tSStybkmPTMDU0Vrj9S3dHbFyd6R/8HwG7PgI185eFYqjKstJcSXPrwkYOpZyvSn43qWC683zzq+ZD6Mw8XDGyNUema4Odt19MHQp3KaxFpVV004+yi79ZdBzsCUvqsh3E635OU2/tgv5qWk4fTWPmlu/we7DsaBT8fsX2lBeq2N/VEWdxGVYF+KPhGj0OYqrquNXv4aj1hw3/5S6gFA6U0dr0oudS0xe4Fxi17g2ps42PKngMVM0jpc5p9k2ro2Zsw1PXzIOk2L7I+MF4wBoMCqAwac+w2fOa5yb/9tLxfNPJikkrf/TRuVdCcdLkvT3GfVL4HNJkqyAGUCZA45lMtlbMpnsokwmu7gzI6ySQi1kUq8GbnOHc3/aGmV+eroYutiRcvEuV7rNIOXiPdwX/KfS8y2VJi18Colz/jM42XQ8Fs09MC1lyENlMmtUC+PacuL2Xnil+VQW8yZuPP31IH8FzCQ/Iwu3iX3Vlj/8agd6Fqa0ObwC1zFBpF5/hJSvwKZjYyy83Gi9fyltDq/ApmNjjGs5aJxv+v1wHn2zk+ab5tB8w2yyboch5ZfsmVJZ8iLjCOs5gVC/cVgN8EfXtmTLclXRs7fGddUUnk37stLvJmsqzG8Ujwd9QOSHK3CY/Tb6rk5lptXR09WaciLlaX8DXmXQ0dXF0s2RHUOWcHDCt3RZMQaDgobdqvQi5aQq5CWnc2/GjzRcM5mmOz8m62ks5BcO5JTp6WhNWc2+8wAUr2aQqUxXF+MWjYlb+SNPhryPvqsjFv27vpK8NFHd5VVr9kex87l1+0Y4D/Pj/sfryljh1dL4+NWic/y/qS4gFCOT0XbBcM4uWl/tcbRZMJxz1R1Hgdu/HmJLh6lcWLqRpu/3q+5whH+Y8m7PFV3uIEnSNgBJko7JZLIyb/1IkrQGWANwwnGw2pUvOzIBQ+fCFmBDJxtyIuMpmcaOnMgE0NVBz9xENSzCwMmGhmuncXfiN2Q9Vk68lJeQSn5GlmpCyLhdZ3Ec5qfantObgTgODwAgOeQBRkXuQhk52ardMQDIikxQu7Ng5GxDdqRy+EZObDIGDlbKOwgOVuTEad5VMy8lg8RTN7Hp0lQ1qVF2VLH94WxLdpR6PNmRCRi62JIdmYBMVwddcxNyyxgmAmDZsi4W3u60vfANMj1dDOwsaRa8gCsDXmxitaqSHRGv6u0RvesvaherYOSnZXJr0veq1x0ufE3m4xis2zQgYvMJQpdsUEtv390Hjw8HAXBryg9kRyVi5GKnWm7oVLiPI9YfJWL9UQCaLRhAbpR6WSwqLzoefafC7eg52pEbXXb6MrcTk0DWvceY+DRSTRr1QutHqceh72j73LiL0zEzpvbaBUR9+l8yQ+6+cP6qOKLj1O7+6DnakfcC+yMvRpk291kUGeevYdjQg9ynpY+RzYqI15py4vdwNSheXUX0ZTQeFUDD17sAEHM1DLMi5xZTJxvSoxI13lZ6ZALRIQ9Q5OWT+jSWpLAorNwcibn6Yg3IVVlOiit5frUhO6qU642Lner8qlfO+RUg/sAl4g9cAsBpZABSkcaG7IgErSmrzRf1Jy86jrLkxcSr9XzQk2t+TsuLjiP7zgNl93og7fBZjL3rk7J1v0brg/aV16raH5bDetOmf0/g1dZJzBrWpOGqt7jy+nJyEzUbNlHa56qK4zcvKk5rjpt/Sl1AKNRoVAD1hynPJbFXwzAtdi7J0PBcYmBmhHW9GvTZMgcAY3tLgtZOYd/oVRpNztiwWBxmzrb8PUXsi5zT9M2MsKlXg15F4ui2dgoHNIyjwagA6hXEEVdsf5i84Lm1qLAd52i/9M0KrSv8e5XXs+EPmUz2i0wmcwe2yWSySTKZrJZMJnsTeFLOuqVKDQnF2N0Jo5oOyPT1sO/XnvgDF9XSxB+4iHyILwD2vdqonjiha2FC499n8XDJOlIu3C22ziWs2jUCwKpjE7UJwCJ/3s85/xmc859B7N4LOA3uBIBlizrkpWaouiD+LScmiby0TCxb1AHAaXAnYvcpewnE7r+I81BlbM5DfYndpx57cfq25ugV3F3RMdLHxteLjNDCyR9TrzzAxN0Jo5r2yPR1cejXjrj96tuM238JpyGdlfujdxsST918bp7hvx7ktPc7nPWZwOU+88kIi9DahgZQ/pA08VDe7bDp2Jj0It8dKGeolunrAuAywo/Ec3fIT8sk4eR15L1ao2+nnHNAz8oUoxp2xO69oPq+U66GEbv/Io792iEz0MOopj0m7o4kF1Ro/l7XyMUW88B2JO88VmacmdfuYVDbBf0actDXw7JXJ9IOl/7Ek+L0HG2RGRoAoGNhhknLRuSEPStnrdJlXLuPYW1n9GvIkenrYdm7EymHzmu0rkxfj1qr55AYfET1hIqKyrp+D/1azui7KPeHeQ9f0o6c02hdHQszZPr6AOhaWWDcrCE5oWWfUnJik7WmnOgYmKLIrljF/VW78eshNgfNYXPQHB7uv0S9gR0AkDfzICc1o8zxqaUJO3AJ5zYNADCyNsPK3ZHkxzEvHFNVlpPiUq+oX28c+rUv5fx6Ece/rze925B46kZpm1KjKkuWpri8EUjkusOqZTmxSVpTVs27tid199EyP0fW9bvo13JGr+C7sejhS/pRzb6brOv30DU3Q9da2W3fpLU32Q9erFqgbeW1qvZH8vpdr7xOYuRii/faqdx471sywjRrnCvrc1XF8Zsfl6g9x80/pC4gFLr56yG2Bs5ha+AcHu27RN1BynOJQ/MXO5fkpGbym9d41redzPq2k4m58kDjhgaAW78eIjhwDsEFcdQpFkdZczMUl5uayX+9xrOx7WQ2FsShaUMDKHsibA+cw/bAOTzedwnPgjjsm3uQ+wJxAFi4yVX/u/o3JflhxYbe/k9Q/AP+tJCsvIk+ZDLZG8B4wAMwBJ4C24EVkiQll5dB8Z4NANb+zfBY9Iby0ZcbjvL0y2BqTR9KasgDEg5cRGaoT/1vJmLW2I3cpDTuvP05WU9iqDlpAK7v9yczrLCgX3/tY3LjUjCsYUf9ryeia2lKbnwK9yZ9pxqHC5AtFbar1F82Gls/b/Izc7j1wfekFNz5aHN4Bef8ZwBg4e1Oo6/eRcdIn7jDIdyd/TMA+tZmNPlxEsYudmQ+i+PauM/JS0rHwN6S1geWoWdujKSQyE/P4kzHqRjXtKfRV+8i09VBpqNDzI4zPFqlPmmjrX8z6nw8CpmuDhEbjvL4i224TR9C6tUHxO2/hI6hPg2/mYBZEzfyktK48fYXZBVUotpe+AY9cxNkBnrkJacTMnSx2pMsjFzt8fp9RpmPvvSL3lzq+1XprN90Gq16G5mBHpmPY7j5wfc49lWO7Xz22yEsW9ah0VfvggRpd59xa/Jq1cRX8r5tcXu/H+jIkHLzuTNrrWoSraLcJvXH+fXOSHkK7s77VTV+teWOj9C3NkfKyydh+Q+kn7n63FjNOrdEPvctZDo6JP1xkLjvNmE/aQSZ1++TdvgvjJrUwfX7uehamqHIziEvNpGw7u9i2r4p8tljlV1cZTIS/rubpI37yswnX/H8dkDzzi1wml/w6Msth4j9djMOk4eTef0+qYfOY+xVh1qrZxeJI4n7ge9h1a8zNVZ+QNb9wgrfsw+/IOt26RcwA8PnP3HBtJMPDrPfAh1dkrceIOGHjdhOHEnWjXukH/0Lo8Z1cf5mHroWZkg5yv3xqPc7GDVrgOPCiUgKCZmOjMRft5O89UCZ+TxJtMCsUS2tKCfGNfSRciv2lJdpC5Zz4co1kpJSsLWx4t0xIxnYO7BC2/qx2fxy03RcPIqanb3Iy8zhyNQ1xBZUVIbsW8LmIOUdk7azX6NOv3aYyq1Ij07i9oZjXPg8GIB284dT09cLSaHg0tc7CN1Z8keGv2n5d/SqqpxEJpZ8CpGNfzM8P1ZebyI3HOXJF8HUnj6U1KsPiN9/EZ2C6415E+X15tbbn6vOr20ufIuuuQk6BefXq0MXk3HvGQ1Wf4BZw9oAPF61hZjt6g13ho3ctKKsJn36PZnnnj/e17STD/az3gYdHVKCi34390k/eg7DxnVx/noeuhbmyu8mLpHHvZVPgTJp1wz76W+BDLJuhhK94EvILf2ccSjNrtT3i6qK8hpgVnZPj6rcH48TCudWeBV1koar3sahZyuynhXMR5KXz1+BswFosvp9rNs1RN/GnJzYZJK+/e25x1VVHb8Jzk204rjRproAQMMHe567/N/khxojNErXYfEoanT2Ii8rh2NT1qh+pA/cv4StgcpzSes5r+FZ5FxyZ8MxLq0KVttO7y1zOPvx+lJ/5GsyQ027xaNwLYjjeJE4BuxfQnBBHK3mvIZHkTjubjjG5WJx9Nwyh79eIo62RfbHySJx9Nu/hO0FcfgUxGEityKjII4rq4Jps3Akzh0aocjLJzs5nbNzfyWpyO+MosY8+/1/esbThL6+2jkpQhE2O45r3XdQbmMDgEwmGwLskyQpRSaTzQOaAR9LknSlvHVLa2yoDkUbG6qTLlqxO1S0obHhoHxodYcAgIuZ9tytLq+xoaqU19hQVZ4kVvCxi69A55vLqjsEQLPGhqqgSWNDVSmtsaE65Fb9g55KVcum3PsBVUaTxoaqUF5jQ1Up2thQ3WpaV+xJM5VNW87z2lQXANHYUJSmjQ1VQTvO8toTB4jGBm2gjY0NmpbRuQUNDR0AP+AnnjNBpCAIgiAIgiAIgiD8L5AU2v+njTRtbPh7NrSewI+SJO0BDF5NSIIgCIIgCIIgCIIg/JNp2tgQLpPJfgCGAn/KZDLDF1hXEARBEARBEARBEIR/EU0bDIYA+4FASZKSABtg2iuLShAEQRAEQRAEQRCEfyw9TRJJkpQBBBd5HQlU/FlKgiAIgiAIgiAIgvBPoKVzImg7MRRCEARBEARBEARBEIRKJRobBEEQBEEQBEEQBEGoVBoNoxAEQRAEQRAEQRCEfyNtfbSkthM9GwRBEARBEARBEARBqFSisUEQBEEQBEEQBEEQhEolhlEIgiAIgiAIgiAIQlnEMIoKeeWNDcla0p5hiFTdIQCQg6y6QxDK0D3paXWHoGKoY1DdIQAQER1f3SEAsM28VXWHoPJjs/nVHQIA464squ4QAJC7BVZ3CCrTbVpXdwgAtMjKre4QAGjy8GZ1h6CSfHRldYcAgHM37Th+v7DQjrIKMCwyrLpDAGC9UdPqDgGAnknPqjsENQ+rOwAt8p8fWlZ3CNonMba6IxCE5xLDKARBEARBEARBEARBqFTa0e1AEARBEARBEARBELSQeBpFxYieDYIgCIIgCIIgCIIgVCrR2CAIgiAIgiAIgiAIQqUSwygEQRAEQRAEQRAEoQxiGEXFiJ4NgiAIgiAIgiAIgiBUKtHYIAiCIAiCIAiCIAhCpRKNDYIgCIIgCIIgCIIgVCoxZ4MgCIIgCIIgCIIglEHM2VAxomeDIAiCIAiCIAiCIAiVqtp6NjRaPAq5f1PyM3MI+eB7kq8/KpHG0suNpl++g66RAdGHQ7g591cA6k0fjGNQSySFgpy4FK58sJrs6ERcBrTHc0IfkEFeWhbXZ/xEyq0nJbZbb8ko7P2bkZ+ZzY33vye1lLzNvdxo/NV4dI0MiD18hbtzlHnrWZniveYDjFztyXoay9VxX5KXnI6epSmNvngbk9pyFNm53Jy0mrQ7zwo3qCOjzYGlZEUlcnnEyhL5NVgyCjv/Zigys7n+/veklBKThZcbTb4aj46RAXGHr3C7ICZ579Z4fjgIs7ounA2aS8rVMACcBrbH7d3ehZ+pYU3OBMwi9ebjMr+X6tDwi3ew79qcnLgUzvp+WGK5nrkxjb+biJGLHTJdHR5/v5uIjcc03r6JpzONvhyPRRM3Qpdt5PH3uwEwdLal8TfvYWBnCZLEm7+u5+c1614o9o+WzaBLQEcyM7P4cMI8bly7rbbc1MyELbt/Ub12cpazbcseFs0pWQZe1NylH+Ib0J7MjCxmvv8Rt67dLZFGX1+P+cun06p9CySFxKql33Fg9xEAuvcNYOK0t5AkiTs37zP1nbkViuOTTxfQLbAzmRlZvP32h1wNuam23MzMlAOHNqteuzg7snHjdmZM/xhXVxe+X70COztbEhOTGDNmMhHhUSXy0JYy8uz3w9z/9VC52+uwcCS1/JqSl5nN4SlriLvxqESa1tMHU29gBwwtTfmx/li1ZR69WuMzeQBIEnG3n3Bo4ncafxZNzV26ihOnz2NjbcX231dX+vaLW7ZyHl27+ZKZmcl778zg2tVbasvNzEzZs3+D6rWzi5wtG3cye+YSliybTYdObQAwNjHC3s4WN9cWFYoj4KOReHRpSm5mNns+XEN0se9Gz8iAft+/j3VNBxQKBaGHrnB8xSYAfMZ2x/u1zijy8slISOXPaWtICY8vkYe2lNcJP/4f33y7ttztrfpsIUFBfmRkZDJ23BRCQm6USDNkSF9mTJ+AJElERkbzxpvvEx+fyLKlc+jZM4CcnFzCwh4z7q2pJCenaPxZ/nb62n1WrN+HQqGgf6fmjOnVUW15ZHwSc3/cTmpGFgqFgg8GB9DRuy5JaRlM/WYzNx+G06dDU2aP7PnCeRf3MmUVoF//7syY/T6SJHHj+h3eGjOlwrH4LBqJi19T8jOzOT15DQmlnEuazhiMx6AOGFiasqFu4bnEoXU9fBaOxLqBKyfe/YYney5UOI6lK+YQ0M2XjIws3n93Zol9Ympmyu69hddPJxdH/ti0k7mzlvLasP4s+Hg6URHRAPz04+/8/tsfJfLQluPmjV/X88ua9eVub8GyGXQO6EBWwfX/5rU7JdLo6+uxcMUs2rT3QSEp+HTJ1+zbdRiXGk6s+HohtrbWJCUmM3n8bKIiYjT+LELZTt9+wsrtp1AoJPq3acBo/+ZqAlSUugAAIABJREFUyz/ZfpoLoeEAZOXmkZCayamlY1TL07JyGLBiI10auzFroPp56B8ZR2gUK/eHoJAk+jdzY3T7+iXS7L/5lB9O3AJk1JVbsnxAawAikzNYuPsi0cmZyGTw9esdcLEyrXAswr9TtTQ2OPg3xczdkSNtJ2PV3JMmK8Zwqse8EumarBjN1ak/knQ5lNbrZ+Dg503Mkas8+G43d1duAcBtTCB1pwzg+oyfyHgSw5n+i8hNTsfBzxuvT8eV2K6df1NM3Zw41WYSli08abhyLH91L/kjq+HKMdyauobkS6E0Xz8TO7+mxB0JwW1iX+JP3uDR1zupPbEPbhP7cn/xetw/6EfqjcdcfXMVJp7ONFg+mkuDFqu2V2tcd9LvR6BrblwiLzv/ppi4OXGySEznyojpRkFMLYrElHbnKSGjV9Hok3Fq6SO3niZy62kAzBq40vyXD7WuoQEgYuNxnv60n8bfvFfq8hqjA0m7+4yQkSvRtzWn/ekviNx6Eik3X6Pt5yalcXfOL9h3b6n2vpSXz70F/yX1+kN0TY34z4GFnDp+lvt3wzTabpeADri518LXpxfNWnqx+NO59Os2XC1NeloGPToPUb3efXgj+3Yf1mj7z+Mb0J7a7q50bdUf7xaNWbhyFoOD3iiRbvzk0cTHJRLYZiAymQwrawsAarm78vYHb/JazzGkJKdiY2ddoTi6BXbGw7M23k264OPTlC++XEwX3/5qadLS0mnXpvAHwMnTO9m5Yz8AS5fNZv36YNavC8bXty0LF05n3NiSFXNtKSOtDy7D+swtEu9HlLmtml28sXRzZF3HqcibeeC79A229vmoRLpHBy9z/ZeDDD/xqdr7lrXlNH+vN9sGLCQ7OQNjWwuNPsOL6tejK8MG9mH2x5+Wn/glBXTzxcOjFi2bBtDSpymffb6Irn6D1NKkpaXj276P6vWRE9vYtesAAHNmLVW9P+7tkXh5N6xQHO5dvLF2c+QH36k4N/MgcPEb/NbvoxLpzq/Zw5Ozt9HR1+X19bNx7+xF2LFrRN98xC+95pGXlUOzEf50mfU6OyZ8U2J9bSmv7+xfwKHDJ7lz536Z2woK7IKnpxsNG3WkVatmfP3VUjp26qOWRldXl88+/YimzfyIj09k6ZLZjB//BosXf87hIyeZO285+fn5LFk8i+nT3mPO3GUafY6/5SsULP3vn/wwbSRyGwuGLfyRzs3q4eHioErz484TBLZqxBA/Hx6ExzBh1Tr2flYXA3093hvQhdBnMYSGv/yPtZctq+4etZg09R2Cug4lOSkFOzubCsfi4ueNhZsj2ztMxa65B62XvcHe3h+VSPfs4GXu/nyQfqfUj+X08HhOT/6BRu/0qHAMAAFdO+HuUZtWzbrRoqU3K1d9RJD/ELU06WnpdOnYT/X60PGt7CnYJwA7gv9k5rSPn5uPthw3/zmwiFPHzxH6nLpA54AO1HavSRef3jRt2YTFn86lf7cRJdK9N2Uc8XEJ+LXuU3ANtgRg9qIpBG/aRfDGXbTt2Irp8z5gyvg5Gn0OoWz5CgXLgk+y+p3eyC1NGf75Vnwb1cbDsfA4nNavver/DSevcyc8Tm0b3+49T3N3p/+ROCSW7bvC6uEdkVuYMPz/DuNb1xkP+8J6xeP4VNaevssvb3TBwtiAhPQs1bK5O84ztkMD2rrLycjJQyZ7qXD++aR/+w6omGoZRuEY2IKnm08CkHQ5FH0LEwwdrNTSGDpYoW9mTNLlUACebj6JY5DyApGXlqlKp2tiBEgAJF68T25yuvL/S6EYOZW8yNsHtSRiywkAki+FomdhgkGxvA0crNAzMyb5kjLviC0nVBcnh6CWRGxSrh+x6QQOBe+b1nUh4ZTyjm5GaATGrvYY2CsvKoZONth1bU74uiOl7g95sZjK2h/FY5IX5J1+P4L0B5GlbvtvTv3bE7n9zHPTVJekc7fJTUorO4EEembKRhpdUyNyk9KQ8pQDp2q925tW+5bS5uhK3KcNLnX13LgUUkIelKiQ5MQkkXr9IQD56VmE3n+I3MmhtE2Uqmv3LmzdtAuAKxevYWFpjoPcrsz0bh61sLW34fzZSxrnURb/IF+2bfoTgKuXbmBuaY693LZEuoHD+vDDlz8DIEkSiQnJAAwZ0Z91azeTkpwKQEJcYoXi6NWrKxvWBQNw4UIIlpYWyB3ty0zv6emGvb0tp0+fB6B+fU+OHzsLwPHjZ+nZK6DU9bSljKTfD8fU8fk/Hty6teDu1lMARF95gIGFKSbFjue/l2XEJJV4v+GwLtz49RDZyRkAZMa/+F1iTbRs2gRLC/NXsu3ievQMYOOG7QBcvBCChZU5cnnZ5cTDszb29racPV3yTuzAwb3YumV3heKo07UFNwq+m4grDzC0MMW02HeTl5XDk7PKHkqK3HyibzzCvOA7f3L2NnlZOQXrh2JeyjUGtKe83rkTiouLY9lxAL17d+P3dVsBOH/+ClZWFjg6qp8HZTIZMpkMU1MTACwszIiMVN6lPnToBPn5yjj+On8FlxovXjm+ERaOq9yGGg426OvpEdS6MceuFOupJZORlpkNQFpmNvbWyrJrYmhA87q1MNSvnHsnL1tW//PGUH768XeSk5THbVxcQoVjcQ1swYM/lOU17vIDDCxNMS7lXBJ3+QGZpZxL0p/FkXT7KZJCqnAMAEE9/dlUsE8uXbyqPM8/Z5+4e9TGzs6Ws2cuvlA+2nLchN4Pw7GcukDX7l0ILrj+h1y8joWlOfalXP8HD+/Hd18oexcpr8HK78mzngdnTyivg2dPniege+fn5ido5saTGFztLKlha4G+ni6BzTw5VkpvoL/tvXKfoGaeqte3nsaSkJpJ23qu/xtxRCTgam1GDWsz9HV1CGzkyrG76jdLgq88ZKiPBxbGBgDYmBoB8CA2hXyFRFt3OQAmBnoYV9J5Vvh3qZbGBiMnG7IiCrueZkYmlGgYMHKyITOy8CKdFRmvlqb+zCEEXPoGl4HtVb0cinId1pmYIyGl512k22tWGXlnFc07ojCNgb0lOQUX9ZyYJFWDQuqtJ8h7tgLAopkHRjXsMCxYp/7Ho7i3aF2ZF3xDJxsyi8VkWCwmw1JiKp7meZz6tiVy22mN02uTpz/tw7SuC52urabtsU+5O/cXkCRsfL0wcXfkfNBszvnNwMLbDas2DSqUh5GrPY2a1Cfk0nWN13F0clDr8h8VEf3cxore/YPYvW1/heIrTu5kT1REYd7REdHIi/1AMLcwA2DSzPFsO/w7X/60HFt7ZZlx86hJbfdabNjzE5v3/kxHv7YVisPJWc6zZ4UNXRHhkTg7l/3jZtDgXmz9Y4/q9fXrt+nbNxCAPn0DsbAwx8amZGW6PFVVRswbuxF95cFz05k6WpNW5PyWHpmAqaPmPUcs3R2xcnekf/B8Buz4CNfOXhWKV5s4OcsJDy9aTqJwcpaXmX7AwF5sC95T4v0ars7UrFWDE8fPVigOc0drUot8N6lRCZjLy/5uDC1M8AxoxqPTN0ss8xrqS9ixqxWKo6rKq3fTRpw/f+W56ZydHXn2rLDyGV7KMZyXl8fE92dz6eJBHj28SP0Gdfn5540ltvXGqCHs33/0hWONSUzB0abwTpuDtQXRieqNbOP7dWbP2Wt0nfwZ761ax8wRL3e3viwvW1Y9PGvj4enG3oMbOXBkC/4BFe/+bOJoTUaR8poRmYDJC5xLKouTk1ztWhcREYXjc/ZJ/4E92b7tT7X3evXpxrHTO1n725c4l9MAVpaqOm4aalAXkDs5EBkerXodGRFdooHCvKAxd8qs99h1ZCPfrv0Eu4Jr8O0bdwns5Q9AYC9/zM3NVL0ehIqLSU7HsUg3f7mVKTEFNyGLi0hIJSI+lVZ1XABQKCQ+23mGKX0qVh/SyjhSMnG0KOxRLbcwJiY1Uy3N4/g0HsenMurno4xce4TToVEF76dibqTPlM1nGLrmEKsOXSP/JRsuhX+n5zY2yGSyYJlMNkImk5lVVUCaurN8M4daTCB862lqjw5UW2bbviE1X+/C7cUbyli7EknKA+/hVzvQszChzeHl1BwTpJwHIl+BXdfm5MQlk3rt4auPpQyWzT3Jz8xWn0PiH8S2izepNx5xwusdzvlNp/6y0eiaGWPb2QtbXy/aHF5Bm0PLMfV0wcT9xSsxuiaGeP80hUVzVpKWWvrFoDL0GRDEjuA/y09YSfT0dHFyceTyhWv09x9ByIXrzPxoEgC6errUdndlZN+3mPL2HBavmqNqnHiVBg3qzZYtO1WvZ89eSoeOrTl9djcdOrQmPDxSdZf0RVRVGbk371dy0zLLX+El6OjqYunmyI4hSzg44Vu6rBiDgYXJK81T2wwY1LPU3gsDBvVi53bluP5XTaarQ5+v3+Piz/tJfhqrtqxR//Y4NnHnrx9KNohooqrK64cffkRq6nPuFGtIT0+Pt98aSes23ant1pIb128zffoEtTQzZkwkLy+fDRu2vXR+pdl77jp92jfl4OdT+XbKcOasCa6SclCe4mVVT08Pd49a9O4+grFvTuaLr5dgYVk1PYi0Rf+BPQgu0qi8f+9Rmjfxo3P7Phw7eoZvVq+o0Har6rj5eM4nlVIX0NPTxdnFkcvnQ+jt9xqXL1xj9qKpACxdsIrW7Vuy++gmWrdrQWRENPn51V+e/032XwklwNsdXR3lT6HNp2/QoUFN5FZV+5OnuuPIlxQ8SUjj//7jy/L+rVm05xIpWTnkKySuPIljSlcv1o31IzwxnZ1XH1VJTNpKUmj/nzYqrz9Ma0ABfCWTyQ4BG4A9kiTlPG8lmUz2FvAWwLvmLQky8aT2m12pOdwPgKSQMIycC7t8Gxe7aw/Ku/vGRe7cGznZlkgDEB58ilbrZnDvE+VkQ+YNauL92Vv8NWw5uYnKSlbtN7tSqyDvlJAHGLnYFtlu6XkX7e1g5FyYJic2GQMHK2WvBgcrcuKUd1/y0zK5OalwkrWOF74m43EM8n5tsQ9sgZ1/M3SM9NEzM8br2/dIunifGiOUMSWHPMDYxZa/O0EaOdmQXSym7FJiKp6mLE792hG5TTuHUGjC+bXOPPp6BwCZj6LJfBKDaR1nZDIZD7/aQfh/1Sfsq/FmN2qMUN4xuDJsOdnRZQ8RkOnp4rV2KpFbT2k0l8J/xgzltZEDAbh25abaHRpHZznRkaWPGW7QqC66urrcuHq71OWaGD56MENGKsfEXr9yC0dnR0B5Z1XuLCc6Sj3vxIRkMtIzVRNC7t15iEHDleOMoyJiuHr5Bnl5+Tx7EsGjB0+o7V6T6yHqk36V5q23R/LGm68BcOnSNWoU6Tbt7OJERETJCR4BGjdpgK6eHiFXCiefi4qMYdjr4wEwNTWhb78gkguGdryIqiojMX+eBwP9kp9tVAANX+8CQMzVMMyKnN9MnWxIj9J8mEp6ZALRIQ9Q5OWT+jSWpLAorNwcibmq2Vwi2mLMuOH8542hAFy5fA0Xl6LlxJHIiOhS12vUuD66erolJhoFGDCwJ9OnfvRCcTT/TwDerym/m8hrYZgX+W7MHW1ILeO77758DIkPo7i4Vr03Uq32jWg7oQ/rhywhPyfvhWL5W1WV1x079pWa5p23RzF69OsAXLx0lRo1nFXLXEo5hr29GwEQFqac8+ePrbuZ9uG7quUjRw6mR3d/grq/ptHnL87B2oKohMKeDDGJKcit1ecq2XbiCt9PVY6J9/Z0JTs3j8S0DGwroZG0MstqRHgUly5eJS8vjyePnxEa+hAPj9pcuaxZr7l6owKoM1xZXuNDwjApUl5NnGzIeIFzycsYPXYYI0cp52W4cuW62rXO2dlRNdljcY0a10NPT5drRfZJYmLhEI/ff93CgoXTKhRTVR03+8uoC4wcM5TXRg4AlNd/J5fC3h1OznKiIotfg5PISM9U1S3+3HGAISOUcxrFRMUyfpRyfiITU2OCegeQmvLi1z5BnYOlKVFJhQ1F0UnpOFiWPqHhvpBQZg0o7Hl09XE0V8Ii2Xz6Jpk5ueTm5WNiqM8Hvdr8c+OwMCYqpfAGSXRKJg7F5o6Tm5vQ2MUGfV0dXKxNqWVjxpOENOQWxtSTW1HDWnmO7VLPmWvhCajPyiUI5StvGEWMJEmDgNrALmAcEC6TyX6WyWTdylpJkqQ1kiS1lCSpZZCJcgzSo58PciJgFicCZhG17yKuQ5QHllVzT3JTM8guNt4wOyaJ3LRMrJor13cd0pGo/cqx7qZuhRc9eVBL0kKVXUCNXWzxWTuZKxO+JT2ssLL06OeDnPOfyTn/mcTsvYjz4E4AWLbwJC81QzUs4m85MUnkpWVi2UKZt/PgTsTuU449jN1/CeehyvWdh3YipuB9PQsTZPq6ALiM8CPx3G3y0zIJXbKRE83e46TPRK69/RXxp29y7b1vefLzAc74z+RMKTGVtT+KxxS9T4PxkDIZjn3aaO18DZrICo/DpmNjQDmMxcTDmczHMcQdvYrLsM7omhgCYOhojb6dBc9+PsA5/xmc85/x3MoFQMPP3yH9fjhPNLxD+dtPm+jReQg9Og/hwJ9HGDhU+bSPZi29SE1JJSY6rtT1+gzszs7g0iv+mlq3dgt9uwynb5fhHNp7jP5Dld2IvVs0Ji0ljdjokrPiHz1wktbtlbP2t+3kQ+g9ZQ+bQ3uPqd63trGktkdNnj4O1yiONT/8l3ZtetKuTU927zrA68OVlS8fn6akpKQSHRVb6nqDB/fmjyK9GgBsba2RFcw49OG0d/nvbyWHRGmiusvIjV8PsTloDpuD5vBw/yXqDewAgLyZBzmpGaXOzVCWsAOXcC7oAmxkbYaVuyPJj/95s5T/9OM6fNv3wbd9H/bsPsRrrysbylr6NCUlOZXo6NLLycDBvQgupVdDnbruWFlZcP6v5w8LKO7yb4f4ucccfu4xh/sHLtG44LtxbuZBdmoG6aV8Nx0/HIShuTGHFv6u9r68US2Clo1m65hVZLzEXBrVXV5X//ArrVoH0ap1ELt27mfEcGUDaqtWzUhOTiWqWMNlREQU9evXUU126O/fkTt3lPMHdevamalT3mHgoNFkZmZREY3cnHkSHc+z2ERy8/LY99cNfJvVU0vjZGvJX7eUDW5hEbHk5OZhY145s6JXZln9c/dB2ndUDqm0sbXG09ONR4+eahzL3V8PsbvbHHZ3m8OT/ZfwGKQsr3bNPchNySh1boZXYe3/radLx3506diPvbsPMbRgn7Ro6a08z5exTwYM6qXWqwFQm98hqIcf9+49fyhaWar7uPnvT5vo2XkoPTsP5cCfRxlQcP1v2rIJqSlpxJZy/T+8/zhtOvgA0M63NaF3lZ/d2sZKde17d9IYtqzb/oJ7QyhNI1cHnsQmER6fQm5ePvuvhOLbuHaJdA+jE0nJyMa7dmGD0bIRAeybP5K980YwuXdberWsV6Ef+FoVh7M1TxLSCE9MJzdfwf6bT/Gtqz6vTpd6zlx8rDyeEzOyeZyQRg0rUxo525CalUtCunKunPOPYnC3+3f10hIqh0ySyh5/I5PJLkuS1LzYe7bAYGCIJEl+5WWwy/H1UjNovOxNHLp4k5+ZTcikH0guuGvX6dAyTgTMAsDS21316MuYIyHcmP0LAC3/bxKmns6gkMh4Fsv16T+RFZWI12fjcOrZisxnyhO+lK/gZKBydl/DIp+z/rI3sSt4lNTND1arHhXZ5vByzvnPBMDC253GqsdMhnBntnKSPX1rM7x+nISRiy1Zz+K4Ou4L8pLSsWxZh8ZfvQuSRNrdZ9yc/AN5xcZnWbdrSK13e5X+6Mtlb2JfENP1IjG1O7ycM0ViaqJ6HGcItwticujuQ8Olb2Bga0FuSjqpNx5z8TXlbOA27RpSd+7rnCvlaR8AQdElx91Wtahtp7Fu1xB9G3NyYpN58MkWdPSUDTfPfjuEodyaRl+Nx0BuXXAHYztRBZO8uY7rjktBr5X89CxuvPsNmY/V77gY2FvS+sAy9MyNkRQS+elZnOk4FfOGNfHZtYjUW49BIfFEyuKTxV9x9NApjWP/eOVsfP3aKx99OXGeqmfAn8c2qz2F4uSlP3njtXd5cP+RRts11DEoN82CFdPp2KUdmZlZzHp/oarXxI6j6+jbRflUDOcajnzy3SLMLcxJjE9k5vsLVeNMZy2aTEe/tuTnK1j9+Vr2bD9QIo+I9JINGMWt+nwRAV07kZmRyTvvTFfdwTtzbo/aUyiu3zzOwP5vcu9e4R36fv2689GiaUgSnD59nimT5pOTU7LjVOi637WijAAcX7mFJ0efP1a/4+JR1OzsRV5mDkemriG2YBjVkH1L2BykPCe1nf0adfq1w1RuRXp0Erc3HOPC58rJNtvNH05NXy8khYJLX+8gdOe5EnmMu7LouTGUZ9qC5Vy4co2kpBRsbax4d8xIBvYOLH/FYuRumq2z8rMF+Ad0IjMzkwnjZ6p6uBw/vVNtZv/L144wdNBY7t9T78kxY9ZEDI0MWbSg7KdnTLdpXW4cXT8ehbuvF7mZOfz54RqiCiaGe/PPJfzcYw7mjja899dXxIWGk5+t7Llw6beDXNt4jNfWzcS+nitpBT/4UiLi2Tp2VYk83vhivFaU17D8dObPX8G+cuZR+PKLxXTr1pmMjEzGvTWVy5evAXD+r320ah0EwLixI5gwYTS5uXk8efKMseOmkJCQxK2bJzEwNCAhXvlj7vz5y0yYOLtEHslHn/+435NX77Fy/T4UCol+HZsxrk8nvg0+QiM3Zzo3q8+D8BgW/byLjOwcZMCkoV1p11jZ+N596uekZWWTm5ePuYkRqz8cqfYki6Kcu81/bhzw8mV18bJZ+Ad0Ij8/n1WffE/w1pI/YL+wKL+sArRaMgqXgnPJmSlriC84l/Q6sITd3ZTnkuZzXsOtfztM5FZkRCcRuv4YV1cFY+vtTuefJmFgaYIiO5fMmGR2+s0skcfUtPIfibni0/nKxzxnZPL+e7O5WrBPjp7crvYUigtXD/H6oLcIvV+4T+YumEJgdz/y8vJJSkxm2pSP1Jb/7fova7XiuHkqZfHJ4q85Vk5dYNHKWXQquP5Pnzhfdf3fc0zZKAHgUsOJVd8rh9LExycyfcJ8IsKj6N47gGnz3gcJzp+9xPzpS8nJyS01n4fxFZsb5n9R5p4vyk1z8tZjPtlxGoVCom+r+ozr2oLv9p6noas9nRu7AfD9vgvk5OWX+SN+x/k73Hoa+1KPnKyyOBJLb/hTxXE/kk8OXEUhSfT1rs24jg347thNGjpZ07meM5Ik8dnBa5x5EIWOTMbYDg0IaqycmPJsWDSrDl5DkiQaOFkzv1cL9HXLvk9tPGLJ//TjGiI7dNH6SSucTh3Vuu+gvMaGE5IkdXqZDMpqbKhqhs/5nFVJ24bTaENjw0H50OoOAYCxeRUf4lDZNGlsqAqaNDZUhW3mrao7BJX7pQyjqA4v29hQWTRtbKgKmjQ2VIUWWaX/aKhqvZK1p0dbeY0NVUWTxoaqoGljQ1XQpLGhKqw3alrdIQDwVt6d6g5BjWhsKKRJY8O/TjmNDVVJNDZUP21sbHjuMIq/GxpkMtlgmUxmXvD/3IKJI5tVRYCCIAiCIAiCIAiCIPyzaProy3mSJKXKZLIOQADwE7C6nHUEQRAEQRAEQRAE4R+tup808U99GoWmjQ1/P4uuJ7BGkqQ9gHb08xYEQRAEQRAEQRAEQato2tgQLpPJfgCGAn/KZDLDF1hXEARBEARBEARBEIR/EU0bDIYA+4FASZKSABugYg9KFgRBEARBEARBEAThf5qeJokkScoAgou8jgQiX1VQgiAIgiAIgiAIgqANJEnrHvTwjyCGQgiCIAiCIAiCIAiCUKlEY4MgCIIgCIIgCIIgCJVKo2EUgiAIgiAIgiAIgvBvpK2PltR2omeDIAiCIAiCIAiCIAiVSjQ2CIIgCIIgCIIgCIJQqV75MAorcl91FhrJQre6QwDAAKm6QxDKcOervtUdgoqUklTdIQAgq12nukMA4NQbp6s7BBV/0/jqDgEAuVtgdYcAQPTD/dUdgsq+xnOqOwStkrR3QXWHoOIQoB3fTczhZdUdAgC/DtpV3SGoPPl5VHWHAMCp8VerOwQAbq3sWt0hCGVoNOrX6g5BRdKSPvXORrbVHYLK6RHVHcGrJSnE0ygqQvRsEARBEARBEARBEAShUonGBkEQBEEQBEEQBEEQKpV4GoUgCIIgCIIgCIIglEESI+ErRPRsEARBEARBEARBEAShUonGBkEQBEEQBEEQBEEQKpUYRiEIgiAIgiAIgiAIZRBPo6gY0bNBEARBEARBEARBEIRKJRobBEEQBEEQBEEQBEGoVGIYhSAIgiAIgiAIgiCUQQyjqBjRs0EQBEEQBEEQBEEQhEpV7T0brLs0xf3jN5Hp6hC17jDPvtmutlxmoEe9rydi5uVObmIad95eRfbTWNVyQxc7Wpz4nMefbiH8+51l5lNvyRvY+TcjPzObm+9/T+r1hyXSmHu50eird9E1MiDu8BXuzvkFAD0rU7zWTMLY1Z7Mp7FcG/cFecnp5W5X18yYdic/I2bvBe7O/hkA7w2zMZBbIdPVJfmvO9yd+X/Y+HpRZ7FyH0SuO8zjr3eU2AcNv5mAuZc7uYmp3HzrC7KexqJnbUaTn6Zg3tSTqI3HuDd7rWqd0vJBoZ0PiDXxdKbRl+OxaOJG6LKNPP5+d6nprDs0ou6CkegY6JFyNYxbk1cj5Ss0zsehdxs8PhyEaV0XzgfNIeVqmGpZ7ff7YdinG0gSuRf3oIgMLXUbp0MjWbk/BIVCon8zN0Z3aFAizf6bT/nh+E2QQV25FcsHtAEgMjmdhbsuEp2SgQwZXw/riIuVqcbxl+X0ozg+OX4HhUKiX+MajPZxK5HmwL0oVp97gAyoa2/Osu5eL50vwOnbj1kZfAqFpKB/m4aMDmihtvyTbae4cP8ZAFm5eSSkZnJq+TgAmk+/zA6nAAAgAElEQVT+Dk8nGwCcrM35clzP5+alLeWk1ghfUCiIXvI9Gacul4yzQwvkc94BHR2S/9hHwo9b1JYbt2yMw6y3MaznRsTU5aTtP6VaVvfmbrLvPQIgLzKW8HcXahx3aZatnEfXbr5kZmby3jszuHb1ltpyMzNT9uzfoHrt7CJny8adzJ65hCXLZtOhk7LsGpsYYW9ni5ur+vdbGeYuXcWJ0+exsbZi+++rK337AI0Wj0Lu35T8zBxCPvie5OuPSqSx9HKj6ZfvoGtkQPThEG7O/RWAetMH4xjUEkmhICcuhSsfrCY7OhGXAe3xnNAHZJCXlsX1GT+RcusJoD1l1bB1D0Ai9/5ZFAnhpW7j9M2HrNx8WHlOa+/F6KDWass/2XyEC/eUnysrJ4+E1AxOff4+AJ9vPcbJG2FIkkSbBrWZPsQPmazid35WfjKfboGdycjMYvzb07gaclNtuZmZKfsOblK9dnF2ZNOmHcyc/jGurs58u3oldnY2JCYkMW7MFCIiol44htPX7rNi3Z/K/eHbnDG9Oqktj4xPYu6aYFIzslAoJD4Y0pWO3nW5/uAZH/+irINIksQ7/brg37JhBfaCunaLRlLTryl5mdkcm7yGuBuPSqTxmT6YuoM6YGhpytp6Y0ssd+vhQ7c1H7C1xzzirpWs+7yI03fDWbn7vHL/+NRhdOcmass/2X2eC2HK/Z6Vk09CeianFgzTaNtac9wM7goKBbnntqMIv1fqNk6HxbDy8A0UkkR/r5qMblOnRJr9dyL44fRdAOo6WLK8d3MikjOYsu0CCiAvX8Hrzd0Y3Ky2xrELmpm/dDqdA9qTlZnFtIkLuHntTok0+vp6fLRiJm3at0ShUPDZkm/Zt/swzjWcWPnVAmxsrUlKSmHKO3OIioypUBwLls2gc0AHsjKz+HDCvDLjWLhiFm3a+6CQFHy65Gv27TqMSw0nVny9EFtba5ISk5k8fjZRERWLY9KiCbT1a01WZhZLJq/k3o37JdJ8vWUVdnJbsrOyleu8Pp2k+CQA/Hr7MnrKKJDg/q0HLJywpEJxCP9O1dvYoKODx7Kx3BiyiOzIBJruW07CgYtk3HumSuI4zJ+8pHQutp2Ifd/2uM0dwZ23P1ctd184ioQjIc/Nxtq/GSZujpxu8wGWLerQYOUYznefWyJdg5VjuT11DcmX7tNs/Uxs/ZoSfyQEt4n9SDh5g0df76D2xL7UntiX0MXrsfNv+tztes4cQuK522p53Bj3OflpmQA0/mkqDn3b4TFzKFeGLCY7Ip6W+5cRu/8iGfcKK4bOw/zIS0rnXJv3cejXDo95w7n51hcosnMJW74J0/o1Mavv+vx8+rQlZvuZ8r6RapGblMbdOb9g371l2YlkMhp/9S6XBi0mIywSj+mDcRrqS8T6oxrnk37nKVdHf0aDT8apvW9a1wXHfu3I3v01MmNzDPzfJHvXFyCpN87kKxQs23uZ1SN8kVsYM/z/DuFbzxkPe0tVmsfxqaw9fZtf3vTDwtiAhPQs1bK5288ztkMD2no4kpGT+1KV8sKYJJYfvc33A1ogNzNi+IZz+Lrb42FrVhhTYjprLzzklyGtsDDSJyEj+6XzVeatYNkfJ1g9vg9yKzOGr9qCb2M3PBxtVGmm9e+g+n/DiWvceVakoVBfl83TX9M4P20pJ496vYOegw01fl7Gw6CxoChSydXRQT7/PZ6Nnk1udBy1tnxJ2pG/yHnwpPBzRMYQNeszrEcPLJG3lJXD4/4TNI71eQK6+eLhUYuWTQNo6dOUzz5fRFe/QWpp0tLS8W3fR/X6yIlt7Np1AIA5s5aq3h/39ki8vF/+h1Np+vXoyrCBfZj98aevZPsO/k0xc3fkSNvJWDX3pMmKMZzqMa9EuiYrRnN16o8kXQ6l9foZOPh5E3PkKg++283dlcoGI7cxgdSdMoDrM34i40kMZ/ovIjc5HQc/b7w+HafarraU1ezzW5EZmmDQtAfZ57YApZzTNhxk9QdDkFubM3zZf/H18sDD2U6VZtoQP9X/G45e5s7TaABCHoQT8iCcLfPeAODNT9Zz8d5TfOrV1Dj+oroFdsbDszZNvfzw8WnK5198jF/nAWpp0tLS6dC2l+r18VM72LljHwCLl85m4/pg1q8LppNvWz5aNI23xk59oRjyFQqW/rabH6aPQm5jwbCPfqBzs/p4uDio0vy44ziBrRozxL8VD8JjmLDqd/Z+NgXPGg6s/+ht9HR1iU1KZfDc7/BtVg89Xd0K7Q8AVz9vLN0c2dhhKg7NPeiw7A229/6oRLrHhy5z85eDvHay5DGkb2pEk9GBRF8uvQH9ReQrFCzbeY7VY7ohtzBh+Ld78G3giofcSpVmWq9Wqv83nLnNnYgEjbevNcfN1k+QmVhi0P0tsv9YUUpdQGLZoeusHtIGubkxw387ia+nIx525qo0jxPSWHvuPr8Mb4+FkQEJ6crrrr2ZEb+N6ICBni4ZOXkMXHsMX09HHMyNNI5feL7OAR2o7V4Tv1Z9adqiCR9/MpsBgf8pke69KWOJj03Av3U/ZDIZVtbKutzshZMJ3rSH4E27aNvRh2nzJjL13ZLXDE3j6OLTm6Ytm7D407n07zailDjGER+XgF/rPupxLJpC8KZdBG/cRduOrZg+7wOmjJ/zwnG09WtNDTcXhnYYSaPmDfhw2STe6v1eqWkXTljCnWvqDWw13FwYOWEY4/u9T2pyGla2VqWuKwhlqdZhFObNPMl6GEXWkxik3Dxit5/GJtBHLY1toA/Rm48BELv7LFYdClvRbYN8yHoSQ8bdp8/NxzbQh8gtJwBIvnQfPQtTDBzUDxYDByv0zIxJvqRs7YvccgKH7spY7INaErHpOAARm44Xeb/s7Zp7uWFgb0X8sWtq+fzdACDT00XHQA/j2nIyHkaR9TgGKTefmO1nsA9S3wd2QS2J/Hsf7DqHdYfGACgyskk+fxdFdk6Jz1w8n+IXS22SG5dCSsgDpNz8MtPo25ihyM0jIywSgPjj15H3VN6B0zExpOEX79Bq3xJaH1qOfVDpFZX0++FkPIgs8b59kA9R28+AIh8pPQkpNR4d2xol0t0IT8DV2owa1mbo6+oS2Kgmx+5GqKUJvhzG0JaeWBgbAGBjqqxAPIhNJl8h0dbDEQATA32M9V++re9GVDKulibUsDRBX1eHwLqOHHug3vK97UY4Q7xdsTDSV8ZkYvjS+QLceByDq50lNews0dfTJbBZHY6V0mPob3sv3yeoRd0K56ct5UTKzSU3PJrcJxEYeal/HiOvuuQ+iSD3WRTk5pH653HM/NuopckLj1H2XnjFx2SPngFs3KDsKXbxQggWVubI5fZlpvfwrI29vS1nT18osWzg4F5s3VL6XcaX1bJpEywtzMtPWEGOgS14uvkkAEmXQ9G3MMGw2Pnf0MEKfTNjkgp+kD3dfBLHgvKRV3AuBdA1MeLvH+yJF++TW9DDLfFSKEZOhY1s2lJWkRRIWWlImSnoWJT87m88isTVwZoa9lbKY9inPseulf2jdO+F2wS1VPbmkskgJy+f3Lx8cvLyyctXYGtR8Z5aPXoGsGH9NgAuXAjB0tICuWPZ5dXT0w17e1vOFJTX+vU9OX7sLAAnjp+lR8+AF47hRtgzXOU21HCwQV9Pj6DWTTh2udidSJmMtII7f2mZWdhbKcuusaGBqmEhOzePSmhLpna3Ftz7Q9nzKebyAwwtTDFxKFnRj7n8gIyYpFK34TNtECHf7SY/O/el47nxNA5XWwtq2Jgry4u3G8dul13/2nv1IUHeJXvalUVrjhtFPlJaAlJKPDr2JRvPbkQm4mplSg0rU+V1t4Ezx0LVe9EEX3vC0Ga1sTD6uy6gvO7q6+pgoKcsJzn5CiQtrpv9UwV092XbZuX1KuTSdSwszbGX25VIN2hYX77/UtkjWJIkEhOUx5BnPXfOnjwPwNmTFwjo3rlCcXTt3oXgTbuUcVwsO47Bw/vx3RelxeHB2RN/x3G+wnF0CGzHvj8OAnDz8m3MLc2wdbApZ61CfYb1JPiXHaQmpwGoejv8G0mS9v9po2ptbDB0siE7Ik71OicyHkMn9QPAoGiafAV5qRno2ZijY2JEjQn9ePypehfl0hg42ZIVHq96nRUZr1YxBDBysiErsrAFPisiAUMna+X69pbkFFzIc2KSMCi4k23oZF36dmUy6n40knsf/bfUeLw3zqbDzR/JS8skIzSC7IjCbWRHxGPoqB6boZMN2QX5SPkK8lMz0Lcpv3JeNJ+YXefKTa/NcuNTkenqYuHtDoC8d2sMXWwBcJ/Un4STNzgfNIdLAxZRZ/5wdF7gB7WhozVZ4YXlUMpIAWOLEuliUjNxtDRRvZZbGBOTmqmW5nFCKo/jUxm19jAjfzrE6VBlheZxfBrmRvpM2XyaoWsOsOrgVfIVmnf7LEtMehbyIndE5OZGxKar91x4nJjOk8QM3th0nv9s/IvTj+KKb6ZieSen4Whd2INCbmVGTMGPr+IiElKISEihVR0X1Xs5efkM+2wzIz//gyPXwkpd70VVZTnJjYpDr1jFQU9uR25kYe+N/2fvvsOjKP4Hjr/3SnrvhRo6hFBC6EqXIiICAqKIoIA0pVcFla4/EVRAQMCGYkO/CkgH6SUQQpNeE9J7L3f7+2PDJUdy5AIJCTqv5+F5yO7szuf2Zmf3ZmdmcyNj0Xi6mp2HZGlB1V+WUWXjJ9h1amX2dkXx9vEkPDz/hvpueCTePp4m0/fp25PfNm0ptLxSZR+qVK3E/r+PPFI85cXK24XMAnVsRkR8kfV/RsH6/75rRN3p/el88nN8+7Yx9HIoqPKg9kQX08Pufo+1TstMA0ubQumiE1Lxcs6/lng62ROdkFrkPu/GJXE3NonmdZUfX438fAmqXZnO01bSZeoKWtWvjp+3+WX9fj4+XoSF5ZfX8LuR+Hh7mUzft19PNv2aX17PnbtIr+e7AvBcr644ONjj4lKyJ3DRCSl4ueT3VPNwcSAqIdkozagXOrDlcChdxv8fYz7+jumv5A//OnPtDi/M+Ix+s5bzzpDnHqlXA4CtlzNpBcpuWkQ8Nl7OZm/v5l8NWx8XbpewbJoSnZyOl2N+g5Kng43pOj8hlbsJqTSvYfo7fBiP9bxJSwQbx0LpolMz8bK3NvztaW9FdEqmUZpb8ancSkhjyIaDDP72AIeu5z8EiEzO4MX1++i2cievtagpejWUMi9vDyLC8xt/Iu9G4eXtYZTG3kG5d5k4Ywx/7Pmez9d+iJu7UudfPH+Zrj2VHl1dn+2Ivb2dobdBSXh6exARHmX4O6LIOOwNcfy5ZyPL131kiOOfc5fo2rOTEkfPTg8dh7uXG9EFhl9ER8Tg7lW40QNg5pKpfLVjNa+Nz++BUdmvEpX9KrHy909Z/efntGgfVOS2gmDKAxsbJEnykyRpnSRJ8yRJspMkaY0kSeckSfpZkqRqjyfEolWd0p/w1ZvRp2cWn7i0FdN0VHnoM8TuPk1WRNHdB0MHLuBQwEhUFlrs6j1cl1NzFMznXm+IJ9nZN5dR+4NXab5tPrmpmZA3RtO1XQDV3+pNy92LafbbHFSWFlj7Fl2RljWdXuZ2fCpfDunAoj4t+WBzMMmZ2ej0ekJuxzKxSyM2vNGZ8IRU/gi9+XhikmVuJ6azpl8zFnZvyNxd50nJfPSnXCWx/dRVOjeqgVqVX+Vsnf0q30/qz8LBXfjot4PciU0qlbyehHJiyvWOQ7jV720iJi/GY+ZItJW9H1veffo9W2TvhT79evLH79vQl0Lj2JPq4qKf2BU4lvBfD1FtWFejda5t6lPlpQ78M+8HE1ub9iSV1e3BF+nctLbhHL4dncD1yHh2LHyTHYtGceLSLU5dCStmL6Wnb7+e/PLTn4a/Z81YQJu2LThw+E/aPtWc8PAIdDrTT8gf1l9Hz9CrbRN2Lp3M8kmvMGv1r4ZzI6BGZX5bOI7v3xvJ2s0HyMp+vPWsEUmi1ZyXOfLB9+WS/fYzN+jsX9Wozi8tT8J5o9PL3E5I48uBrVn0XCAfbA8lOe+66+Vgzc9D2/PH8E78eS6MuLTSGdoomE+j0eDj68Wp46H06jiIkOAzzHh/AgAL5nxCi9aB/LnnB5q3DiTiblSZ1CVKHOq8OE7zXMeBnDpxhpkfTMqLYwkt2jRj894faWGIo+yuw++PW8Crnd9g9Atv06h5AN36dQFArVFTqXolxvabwJzR85j20STsHqEXm/DfU1w/7q+AHwBH4CiwHvgAeAZYB3QsaiNJkkYAIwAm2zehl41fkTvPiojHssDYUAtv10I/0LPz0mRHxINahcbehtz4FOyb1MKtZ0uqvzsYjYMtsl6PPiubiHXK+E3vod3wellpEUw5fQ0r3/wnLlberka9GAAy73vaZeXjQlZEghJDTBIWHk5KrwYPJ7Jjk/PiTyhyv1Wa1capRV0qv9YFta0VKgsNuvRMrha4GdVn5RC77QRuXZuhtstv1bb0cSUr0ji2rIh4LH2VYyOpVajtbciJTynymN7vXj7u3YJI2H/WrG0eN0tPZ7KiEopNlxR8heDn3wPApV0ANn55P8QkidBhHxfqFll/6SgcGlYjKzKBkJcXmdxvVmQCVr5ugNLyK9k4QEZyoXQe9tZEJqUb/o5KzsCjwNMNUHo7+Pu6olWr8HW2o6qLPbfjUvF0sKGOpxOV8noCdKjry5mwOF5oUuzHfiAPWyuiCjxRiUrJxN3W+EmOh50VDb0clZgcbajqbMvtxHQaeJW8hdxov452RBZ4ChqVmIqHY9EXoG0hV5jRz3iiNU8n5VhUcnOkWU1fLobFUNnNOCZ1lQA0lRvQcncvQgYtqhDl5N6lXuvlRm6UcS+R3KhYtN75Xb81Xm7kRsVhrtxoJW1OWCTpx89gWb8GOXcKd/c15fXhL/PqawMACDl1Bl/f/MYKH18vIu5GFbldA/+6qDXqQhPyAfTp+yxTJ71ndgwVQbWhXajysnJ5Sjx9HSuf/Hra+r5ebKDU/9YF6/8irhEA4ZsO0nzDNC5/9AsA9vWq0OjjERwbtAjf3q0MeYZWkLIKylNnycoWstILpfNwtiMyIf9aEpWYgkeB3koFbQu+yIyB+UMT9py+QkB1b2zyuom38fcj9Ho4TWsVHoJmyvARgxkyVCmvp06eoVKl/PLq6+PF3YiiJ3j0b1gXjUbD6dPnDMsiI6N5ZdAoAGxtbej1fDeSksy7Tt7j4WxPZHx+o2d0fDKezsa93H77+xQrJyvjvxvVrEJWTi4Jqem4OuQfNz8fd2ysLLgaHk2D6r6URIMhnak7qAMAMaHXsS1Qdm29XUiPLL5cAVjYWeFcpxK9flbGeFu7O9Jt3US2DVvy0JNEejjYEFmgJ0NUcrrpOj/0JjOeb1HkuoLUfoFoqjUGwNJzTgU5b24pu7N1gvTCjeAedlZEFujVGJWSWah3gqe9Nf4+Tsp118mGqs523E5Iw987v7eNh70VNd3tORUWR5c6PsV+bsG0wcP6M2CwMsfLmdPn8fbN71Hj5eNZaILHhPhE0tMy2LZ5NwBb/7eTF1/uDUB0ZAyjXpsMgI2tNd2e60RKctE9vgrF8foABt6LI+Q83r75vQm9zYpjB/1feSE/jiETC8TRmZRk8+q0PkOep9fLSq+rf05fwsMnv0eFh7c7MZGFe7jG5i1LT8tg5++7qd+4Htt+2UlMRAznT11El6sj4k4kd66HUal6JS6GXjIrln8T8erLh1Nck7O9LMsrZVleBDjIsvyxLMt3ZFleC5jsyyfL8mpZlpvJstzMVEMDQMrpq1j5eWNZxQNJq8G9dxvidxiPF47bEYxn//YAuPdsReIh5ebiTO93ORE0mhNBowlfs4U7n/5maGgAiFi/jZDOUwjpPIW4bcfxflH5oeMYWIvclHTDsIh7sqMTyU3NwDFQmVHY+8WnidmmxBKzPRifAe0A8BnQjphtwYblRe333OjPOBg4hoNB47j8/nfc/Wk/V+f9gNrG0jCng6RW4dqlKQlHL2Dj541VFXckrRqP3q2J3R5sFFvs9pN43zsGz7Uk4WDhHwQFFZVP2tWiZyKvCMy5uQDQuik3fZKFhmrjehH2jTIGLW5fKJVf72ZIZ+9fDYAL41dytNO0B95cgPI9evVuDSo1kq0Tkr0r+rjCT+ga+LpwOz6V8IRUcnQ6tp+/TbvaxjcIHer4EnxTuZgkpGdxKz6FSs62NPBxJiUr2zBh5PEb0fi5Fx6qUVINvBy4nZhOeFI6OTo92y9H0r6GcTe9DjU8CA5TfjglZGRzKyENX0fronZXsryreHA7NonwuGRycnVsD7lCu7xjX9CNqASS07NoVC3/4p+cnkl2rvKkICE1g9M3IvDzKjyGUHf7DFmHfuBop2kVppxIWi1aX0+0VX3IvG8ipcyzl9FW9UHr6wlaDfY92pG6x7whTCoHOyStMq+G2skB6yb1yb56u5itjK1ds4F2bXrRrk0vtmzexcCXlJunZkGNSU5KISoqpsjt+r7Yk01F9GqoVdsPJycHjh8LKVEc5e3m+p3s7zyD/Z1nELktmMr9nwLAqWlNclLSybqv/s+KTiQnNQOnpjUBqNz/KSK3nwTAtnp+ufXs1ozUq8o8Lda+rgStm0DI2OWkXY80yrOilFUkFZKVHZK1A/rkwt99g6re3I5OIDw2UTmHT1ykXUDNQuluRMaRnJZJI7/8+s7bxYGTV+6Qq9OTo9Nx8vKdEg+jWLP6W9q26knbVj3Z8udOXhqk3GQHBTUmOTmFqMiiy2u/F3vxy89/Gi1zcXU2TLo7cfIovvum+CGW92tQ3ZfbUfGExSSQk5vLtmNnadekrlEab1dHjl1Qhn1dvxtDdk4uLva2hMUkkJv39PNubCI3I2LxcSv5RGrnv97Fr11n8WvXWdzcdpLa/ZRJdj2a1iA7Jd3k3Az3y07J4JuAUXzfagLft5pAdMi1R2poAGhQyY3bscmEx6co5SX0Bu3qFW5cuhGdRHJGFo2qmJ5z4x7d9ZNk7Vmr/Kso541KjWTnguTghj6mcB3cwNuJ2wlphCfmXXf/uUu7msbDRTrU8iL4ttJ4nJCexa2EVCo52RCVkkFm3pwUyZnZhITFU82l6AY+wXzfrvuJnh0G0rPDQHZu3csL/ZWJZBsHNiQlOZWYqMI/rnfv2E/Ltsq8Hq2fbs7VS8p57eziZKhLRr09jJ+//1+hbU3GsfZHnm0/gGfbD2DH1r30GfCcEkezB8Sx/W9atlWGJrRu14Krl64VimP0+Nf5ecPvhbY1ZdPX/+O1Z0bw2jMj2L/9oKGXQoOm9UhNTiMu2rgxXa1W4ZjXsKrWqGnduSXXLyl1xf5th2jauhEAjs4OVParxN3b5j8EEYTiejboJUmqDTgBNpIkNZNlOViSpFrAow1GBNDpuTbzS/x/eAdJrSLqhz2kXwqj6tQBpJy+RvyOYCK/302dz9+i2ZHPyE1MNXoThbkSdp3CsWMgbY4tQ5eRzYW3VxrWtdy9mKOdpgFwcdpaGnw6GpWVltjdp4ndrYxzvPnZ/2i4Zjy+gzqQERbLmeFKDLG7QnDr1KTI/RZFbWtFwDdTUVlqQSWRcOg8d9fvIPNGFI03zkJSq7j7w17SLoVRfWp/UkKvEbv9JBHf76H+52NpefRTchNTOTdyqWGfrU58jsbeBslCg1v3IE4PmEdOQmrhfL7eWeLj9rhYuDvSYsdCNPbWyHqZKiN6cPipSehSM2iyYToXJq4iKyqBaqOfw61LIJJKIuzrnYZGl+tLfqXO3Ndoue8jJEki4040p1/5sFA+7t2DqLtgKBauDjTeMI2Uc7cIGbiAtEthRP1xBL+xb4GsJyd4c5FDZTQqFdO7N2XUhv3oZZnnG1enpocjK/aeo76PM+3r+NK6hhdHrkXRZ8U2VCqJCZ0b4ZQ3ZnRC50aM/PZvZKCetzN9m5puiDOXRqViWoe6jP7tlBJTA19quNqx4shV6ns40L6GB62runLkVhx9vjmEWpIY/1RtnPImsHykvNUqpvd9ilFf/IFeL/N8i3rU9HZlxdZj1K/iQXt/ZWKwbaeu0K1pLaO3b1yPSmDeT/tQSRJ6WWZY56ZGb7EoSkUpJ9W2rAKdjugPVhi/iQJApyd67koqrZ0HKjVJv+4g++ptXMcNJvPcZdL2HsPKvzY+n7+L2sEOuw4tyB37CjefexOLGpXxen8csl5GUknEr/nJ6C0WJbVz+z66PNOOk6G7ycjIYOyo6YZ1fx/6w+gtFL1f6MGAfoVfmden77NG4+LLwpQ5izgRcobExGQ69X6F0a8Ppu9zXYvf0EzRu0Lw6NSYjkeXosvI4vT4VYZ1T+9ayP7OMwA4O3294dWX0XtOE51X/9ebNRDbmj6gl0kPi+Hs1LUA1JrYB62zHQ0XDQOU+XQOdFWeIleUsuo3vp9Sp10+zP1vooC8c3hAZ0Z9+gt6vZ7nWzekpo8bK/44SP2qXrRvpDQ8bDtxkW5BdY3O4c5Na3P80i1enLseCYnWDaoV2VBhru3b9/JM1/aEnt1LekYmo0dONaw7eGSz0VsoXujTg359hhlt/9RTLXnv/SnIssyhQ8eZNGFOiWPQqNXMGPwsoz76Br1eT++nm1KzkgfLN+2mQTVf2jety6SXuvHBuv/x3fbDSJLEB2+8gCRJhFy+xbrNB9Bq1EiSxMxXe+Js/2hdjW/vOU2Vjo0YePBjcjOz2TdxtWFd3+3z+TWvvLWYNZCavVujsbbg5ROfcvGHfZxcsumR8i6KRq1ieq8WjFq3C72s5/lmtajp6cyKnSHU93WlfX1lWOi2M8rEkCV941KFOW/GTFFefXnkN9P3Ap39GfXzUeW627AyNd3sWXHgIvW9nGhfy4vW1d05cjOGPmv3opIkJrSvj5O1BUduxrBk73kkJGRkXg2qQa1SePAg5Nu78yDtO7dl74k/yMzIZOpb7xnWbd67kZ4dlO5PoBkAACAASURBVLdgLX5/GUtWzuPdeZOJj0tg6jglXcs2zZjy7jhkWeb4kVPMmbrwIeM4QIcubdkXvJmMjEymjpttWLdln9IoocSxlCUr5zN7/hTi4hKYOnZ2gTjeAhmOHznJ7KkLisynOEd2H6NVxxb8dOg7MjMyWTAx/5z4asdqXntmBFoLC5Z8/yEajRq1Ws2JAyf5Y4Ny7T+27wTN2zXju73r0Ov0LJ+7iuSEwr1/BcEU6UEz4UqS1AlYAeiB4cAEIABlWMVwWZaLbe474NWvQsyNmSk/ettIaVAXccNXnjpG/VTeIbDTc0B5hwBA2yUP/6aE0iYnV4zZfqVqhd8dXh4OvnaovEMwqOJcMS6yrcIf/VV2pSHqxvbyDsFgm3/JXwtWFqzkijG/RduNXco7BAPPng93o1zaonc/3A+H0vZ1vz+LT/SYvPpp2bzWtqQOjgot7xAAaLugcvGJHiPr18vmtcBPIj+3Rxx7WorkClLP+1g9/MS8pe1Q+J5/9TiDa/5dK9aPuCLUOLe9wn0HD+zZIMvybqCOJEn9gVBZlvtKkjQbCAIe/L5JQRAEQRAEQRAEQRD+k8ydJvgdWZZTJElqC3QAvgAePGZAEARBEARBEARBEIT/JHMbG+698+VZYI0sy1uARx/0LQiCIAiCIAiCIAgVmKyv+P8qInMbG8IlSVoFDAC2SpJkWYJtBUEQBEEQBEEQBEH4DzG3waA/sB3oKstyIuACTCmzqARBEARBEARBEARBeGIV9+pLAGRZTgc2Ffg7AhAvWRUEQRAEQRAEQRD+1fRyhXvRwxNBDIUQBEEQBEEQBEEQBKFUicYGQRAEQRAEQRAEQRBKlWhsEARBEARBEARBEAShVJk1Z4MgCIIgCIIgCIIg/BfJYs6GhyJ6NgiCIAiCIAiCIAiCUKrKvGdDHBZlnYVZbNCXdwgA5CJaxSqqlHX7yzsEA41DeUeg0GeeKe8Q8niVdwAGEQl25R0CAFNdWpR3CABs859V3iEYdDs3v7xDAGBfgxnlHQIAKfO+Le8QDN5xa13eIQCws/fv5R0CAEODZ5Z3CAbJw8eWdwh5KkY9n7ktuLxDMGL9enlHUHG8aFe3vEMwkMs7gDwxZJd3CILwQGIYhSAIgiAIgiAIgiCYIOvFA+OHIYZRCIIgCIIgCIIgCIJQqkRjgyAIgiAIgiAIgiAIpUoMoxAEQRAEQRAEQRAEE+SKMlHHE0b0bBAEQRAEQRAEQRAEoVSJxgZBEARBEARBEARBEEqVGEYhCIIgCIIgCIIgCCaIt1E8HNGzQRAEQRAEQRAEQRCEUiUaGwRBEARBEARBEARBKFViGIUgCIIgCIIgCIIgmKCXxTCKhyF6NgiCIAiCIAiCIAiCUKrKrWdDw3mv4tmpMbqMbE69/QVJZ28WSuMYUJ2my0aitrIgavdpzr7zDQB1J/el6ssdyI5LBuDCwp+I2n0a96f9aTDrJSQLNXK2jnMfbCD20IVC+60zfwjunZqgy8ji3FsrSSkib/uA6vh/Ogq1lQUxu0O4NOtrADROtjRa/TZWld3JvBND6PBl5CalGbZzaOxH8y1zOTvyU6I2H8OqkhuN108ClYRKo+b22u2EfbOrzOJwbl2fxl9PJuN2NADRW45zfcmm/B2qJFruWEBWZAIhr3xY/Bf1GNRf+ibuXZqSHZvMkXaTC6336tuWamN7gSShS83gn6lrSb1wy+z9a53tCFg7EYfGNbi7cR+XZq43rGvywwwsPZ2R1CrUV06R8ulS0OtN7ssiqDl2Y8aBSkXm1i2kb/zeaL11v/5Y93gWdDr0iYkkf7QYfXQU2sZNsBs1xpBOU6UKSfM+IPvQQbM/h9FnatIcm9eVOLJ2bSFzk3Ecll17Ydn9BdDrkDMzSFvxf+jDbqFp1AybwSNAo4XcHNK/Xknu2ZCHiqFQTIHNsX1zHJJKRea2LWT8bByTVY9eWPXMjyn10/9Dd9u877GilJHEYxe5Ov3LQmXEpUNjas4biqRWEbFhN7c/+91ovWShod7n47AP8CMnIYULIz4h804MGmc7GqydhEPjmkRu3MeVmWsN27g/35qq4/sgqVTE7TzJ9XkbzP4893R+bzA1OjQmJyOLLZNXE3XuptF6jZUFvVe+hXMVD/R6PVd3hfD34h8BCHqjO40GtkefqyM9PoWtU1aTHB5XovwbzBtiqOdPv73SZD3feNmbhnr+/DtKHVdn6ot4dWuGrNeTHZtMyNtfkBWVgG+fNtQc2wskyE3N5Oy0tSRfuF3iY3O/dxYsYf+h47g4O/H7d1880r4qSnl9kuo0gE7vDcYvr7z+ZaK8Pr/yLZyqeCDnldf9eeW1UvM6dJozGPe6lflj3Odc3nqiRHmXRVl1bV2PoK8mk553PY7YeoIrBa/HxTh4PITFy9ej0+vp06MTb7z0gtH6u1ExzP5oOfGJyTg62LFwxtt4ubsqeUXFMOfjlUTGxCEhsWLhTHy9PEp0TO4ptm5/oT9W3fLKSFIiqZ8oZQTAZthILIJaApD+wzdk799rMp+Kct5ob4eQvvbB542mcXNsho4FlZqs3VvI+t34mFh06YVVt97Iej1kZpC2SrkG3yO5eeD4yddk/PQVWX/+aPZnEMzTa84Q6nRoTE5GNj9NXsnd8zeN1mutLHh5xXhcq3og62Qu7D7JtsUbAXDydePFD0di6+JAelIqP45fTlJk/EPHUbdAHOFFxPFKXhx6ncw/u0/y131x2OXFsfER4hg0ZxgBHZqSnZHN2smfcev8jUJpJn79Do4ezqjVai6fuMC3736JrNdTuV5VXp0/EisbK2LDYlg1fimZqRkPFYfw31QuPRs8OzXGzs+LXa0mcnrylzRaPKzIdI0XD+P0pC/Z1Woidn5eeHRsZFh3bfVf7O08k72dZxK1+zQA2fEpHH31I/Z2mM7Jt1cS+PnoQvt069QY2+reHGw5nguT11D/wzeKzLv+h69zYdJqDrYcj211b9w6Ngag+rjniTtwjkOtJhB34BzVxz2fv5FKova7g4jbd8awKCsqgWPPvsvRTtM51v0dqo97HktP5zKNI/HYRY52ms7RTtONGxqAqsO7k3blbpF5lZe7G//m1MCFJtdn3IomuPf7HG0/hetLNlH/4+El2r8uK4dri37kynvfFlp3ZvhSjnacypF2k5EcnbBs1970jlQq7N8aT+KMqcQPG4Jlx06oq1Y1SpJ79Qrxo0YQP3wYWfv/xm7EmwDknA4hYeQbJIx8g8TJE5Azs8gOLtnNcME4bEaMJ2XuVJLeGoJF206oKhnHkbV/F8njh5I88Q0yf/sBm6HKjwI5OYmU+TNIHj+UtE8XYvf2rIeLoYiY7MaMJ/ndqSSMHIJl+06oq9wX075dJI4eSuLYN8j4+Qdsh48xsbPCKkoZ0bo64NGrpXEClYpai17nzKD5HH9qAh4vtMGmdiWjJN6DOpKbmMqxluMIW7UZv3dfAUCflcPNRT9y7b1vjNJrnO2oMXswof0+4ES7iVh4OOH0lH+JPpNfh0Y4V/diVbtJbJuxlq7zXisy3fHVW1jTaSrre8yiUrPa+LUPACDq/E2+6vku67rN5NLW43SY8VKJ8vfIq+f3tJpA6OQ1NFz8epHpGi4eRuikNexpNcGonr+2YjN/d5zG/s4ziNp5itoT+wCQfjuawy98wN8dpnHlk00E/F/JvmtTevfowhdL5pXKvipKeX1i6jTyy+uadpPYPmMtXUyU1xOrt7C201S+6jEL32a1qZ5XXpPvxrF10iou/O9wifMuq7IKEH/sIvs7z2B/5xklamjQ6XTM//RLViycxf/WfcJfew5y7eYdozT/98XXPNelPZu+XMKbg19k2Zf5DZIzF3/Ga/2f54/1y/hhxUJcnBxLckjymVG3665dIfGtESSOHkb2wb+xHaaUEW1QSzQ1apM45g0Sx4/Cuu9AJBsbk1lVmPPGwRFty/amd6RSYfP626TOn0byhCFYtOlY6BqcfXAXyZOGkTLlDTL/9wM2Q4yvdzZDxpATcqxE8QvmqdO+MW7Vvfio/QQ2zVzDC/OLPp/3r9nMx50ms+zZ6VQLrEOd9sr5/OzMlzm56QBLu09j97JNdJs68KHiqJsXx4ftJ/BrMXH8XxFx9Jz5Mqc2HeCT7tPY9QhxBLRvimd1b6a3H8tXM1cyeP6IItOtGPMxc7pP4p1nxmPv4kjQs60AGLpoNL8s/o53u03k1PZjdB/xfJHb/xfIslTh/1VE5dLY4NU1kNs/HQAg4dRVtA42WHo4GaWx9HBCY2dNwqmrANz+6QDe3Zo9cL9J526RGZUIQMrFMNRWFqgsjDtvuHdrxt2f9yvpT15F42CDxX15W+TlnXRSyfvuz/tx767k7dGtGXd/VLa/++N+PLrnx1TljW5EbT5OdmyyYZmco0POzgVAZakFlVTmcZhi6e2CW5emhG/YU2zaxynx6D/kJKaaXJ8UfNnQeyTp5BUsvV0N67z6tqX5tvm03L2Yeh8NNxzfgvTpWSQev4QuK6fQOl1e66ykUSNptSDLJuPQ1K1Hbng4+ogIyM0la+8eLFu3NUqTczoEsrKU//9zAZW7e6H9WD7dnuzjxwzpSkpTqx76iHD0UUoc2Qf3YNHcOA4y0g3/lSytDf/X3biCnKA8ndbdvgEWlkovh0ekqV0P3d1w9JF5x+bvPVi0NI5JTs+PCStrMH2oC6koZURloSlURBya1iTjRiSZt6KRc3KJ/v0QbvfVVW7dgoj86W8AYv48inNbf0O+Sccvor8vX+uqnmTciCAnr/dWwv6zuD97XyNHMWp1CeTcr8pT5rsh17B0sMX2vjomNzOb20f+UWLJ0RF17ib2Xi4A3D7yD7mZ2XnbX8Xe26VE+Xt1DeROXj2f+IB6XmtnTWJePX/npwN45R273AJPTtQ2VtwrMAnBV8jJ+64TTl7FqoRxmdKscUMcHexLZV8Vpbw+KXUaQM0ugZzPK68RIdewKmF5TQ6LJebiHWR9CSqWPGVVVh/F2YtXqeLrRWUfT7RaLd07tGHvYePGnOu3wmjRRKlLmjf2N6y/dvMOOp2e1s2UHy021tZYW1k+VBzm1O05ZwqUkYsXULkpZURTpRo550JBr4OsTHQ3rqENbGEyr4py3ijXRNPfobpmXfSR4eijlWOSc2gPFs3aGCcqcA3G0sroPNQGtUUfHYHuzk2TeQgPr8EzgZzcpJzPt0OuYm1vg7278fmck5nN9SNKz2ddjo7w8zdw9FLKk2etSlw7fA6Aa0fOU79L4EPFUf+ZQE6ZEcc1E3F41KrE1QJxNHjIOJo8E8ThTcr9x/WQK9jY2+J4XxyAobeCWqNGo9UYyqxndW8uHVNiPH8wlMDuJbsXEYQHNjZIkqSSJGmYJElbJEkKlSTplCRJGyVJav8omVp7O5NxN78rUGZEPNbezoXTRJhO4zfsGTrsWUSTT0agdbQtlIdPz+Yknr2JPu+H/j1W3i5kFugKnBkRX+hm1crbhcyCed/NT2Ph7kh2tNKgkR2diIW78rTA0ssZj+5B3PlqZ6FYLH1cabV3MU+fWs7Nz/8gKyqhzOIAcAysRas9i2n6/XRs6+Q/Ya07dwiXP9jwUDdjFYXvoA7E7VF6stjW8sWrd2tO9JzN0U7TkHV6vPs+VeJ9Ntk4k3bnVyOnp5O1/2+T6dRubuhjog1/62NiULm5mUxv1b2HcgN+//IOHcncu7vEcd4jubihiy0QR1wMKtfCcVh2743jyu+xHvIm6V8uK7Re26oduuuXIbfwjVdJqe4/NrFFx2TVszfO677H9vU3Sf2icEyloSzLSG5qBjF/HjVaZ+nlQtbd/HM56248ll6uxmm8XcgKjwVA1unJTUlH62L6h23GjUhsavhgVdkdSa3CrXsQlr6uJtMXxd7LmZQCcaVExmPv6WwyvaWDDTU7N+HmofOF1gUMaMf1faElyt/K24XMAvlnmKjjjOv5OKM0daf3p/PJz/Ht24ZLH/5cKI/Kg9oTnfddP6lEnaaw93Im+SHK660iymtJlWVZdQ6sxdO7F9Hi+2nY1THu8fQg0bHxeLnnfxee7q5ExRp3oa5doxq7Dijfx+6Dx0hLzyAxKYWbYRHY29owfs6HvDhyMh+v+gadTmd23gWZW7ffY/VMD7KDlZhyb1zFIrA5WFoqvQUCmqAuorHqYZTleUNmOjlHTZ83Khd39HExhr/18TFIrkU0wnXtjcNnG7B55U3S132qLLSyxqr3S2T8/HWJ4xPM4+DpQlKB8zkpMh4HL9ON0lYONtTr1JSrh5Qf9nf/uYV/t+YANOgahJW9DTZOdiWOw9HThcQCcSRGxuNYgjgiCsTh/whxOHm6EH831vB3QmQczl5F309M+uZdlp1cR2ZaBie2Kvc6d6/cockzShzNerTGxdv0+S8IRSmuZ8NaoAqwENgLbM5b9o4kSeNMbSRJ0ghJkoIlSQrekX611IK958ZXO9nRYjx7O80gMyoR//deNlpvX8eXBu+8xOkpX5Z63oXktfzVmTuEK/O+L/IpUtbdOI50mMbBluPxGfC0UcNAaceRfOYGBwLHcqTjNG6v3UbjryYB4NalKdmxSaScKTxO60nh3KYBPoM6cmWu0lXU5Sl/HAKq02L7AlruXozLU/5YVy35mNSQgQvYH/AmaLVomzQtlVgtO3dBW7sO6T9tNFqucnFBU92P7BPHSyWfB8n663eSRg0i45tVWL/4qtE6deVq2Lw6krQvPi7zOArK3Pw7CcMGkb5uFTYvvVr8BiVU1mVEZaE19EooS7lJaVyetob6qyfQ+I+5ZN6JAZ3p8cOPSlKr6PXZGILXbyfpTozRugYvtMGroR/HVm0ps/xNubjoJ3YFjiX810NUG9bVaJ1rm/pUeakD/8z74bHHVVpEnfZwJLWK5z4bw8kiymt5KaqsJp25ya5m49jfaTo31m4naP3EUs1z8shXCT5znhdHTiY49AIebi6o1Cp0Oh2nzl1k0sgh/LBiMWERUfxv+75Szbsolh26oKldh4xflTKScyqY7OCjOH28HPtps8m5eF6Zw+ARlfl5o9Gi8W/yyHFmbf+d5HEvk75hFVZ9BwNg/eJrZG7+GTLFmPeKQKVWMejTcRz+ajvxd5RGtS3zN+DXoh5vbVmIX8t6JEXEoS+FcmtOHIeKiOPtvDgSH0McH786l/HN30BjoaVea+VeZ+3UFXR8pStz/vwQazsrdDm5xexFEIwVN0FkoCzLQ/P+f1CSpKOyLM+WJGk/cBr4rKiNZFleDawG+N1rkAxQfWgXqr3cAYCE09ex9slv3VOeGCQY7SMjIgFr76LTZBUYpnBrwx5afjvFKF2LdRM5OW4l6beUE7b60C5Uz8s7+fQ1rAo8Iby/9wAU7mVg5ZOfJjsmCQsPJ6U3gYeTYciEY2M/Ar54GwCtqz3unRuj1+mI+SvYsB+PHkFYV/Okxda5xO0/WyZx6Ap054zdfZp6i15H62KPU/PauHcNxK1TE1RWWjR21vgvN3/MfHmzq1+F+ktGEPLSInIS8rpZShJ3f9rP1fnGPzbcuwdRY3I/AC5MXEVy6PVi96/PyiH78CEsW7ch52RwkWl0sbGo3PNvYFTu7uhjYwul0zYNxHbQYBImvgU5xr0GLNt3IOvgAXjIp0wAcnwsarcCcbi6o48rHMc92Qd3YzNyguFvydUdu+nzSFu2AH1k6czfob//2Lg9OKasv3djO3aCyfUP43GUkZhtwbh1CyJhf4F5WSLjsfTJP5ctfVzIijSeSDErIh5LXzeyIuKR1Co09jbkxKc8ML+4HSeJ23ESAO/BnZHNaGxo+mpnGg1U6rqIM9exLxCXvZcLKVEJRW7XfdHrJNyIJHjddqPlVds0oNXYXnzffz667OJvMKoN7UKVlzsCkHj6OlYF8rc2UccZ1/OuhdIAhG86SPMN07j80S/KZ6lXhUYfj+DYoALf9RNG1GnQ5NXOBOSV18gz13HwcSU8b92DymvXvPJ68r7yWhKPo6wWHF4Rvfs0DRcNw8LFnuxizn0ADzcXImPyv4uomDg83VwKpVn6/lQA0jMy2HngKA52tni6u1KnRjUq+3gC0LFNc0IvXKYPnYrN937m1u3axoFYDxxM0lTjMpKx8TsyNn4HgN3Ud9GF3ym0bUk8jvMm58QhtEFtyT1zsug08TGoCvRkULm4I8eZbvTKObQH2+ETSF8O6lr10LZsh/UrbyLZ2oGsh5xssrb9VmxsgmmtBneh+UvK+RwWeh3HAuezo5cLySYmVuyzcDixNyI5uO4vw7KU6AS+ffMTACxsLGnYrTmZyelFbl9UHC3y4rgTeh2nAnE4ebmYnOCxbxFxJN8Xh38J4ug4uBvtXuoMwI3Qq7j45PdGcPZyJSHS9GTPuVk5hOw8TtMuzblw8AyR18L5+NW5gDKkIqDDww3n+Dd4wKhE4QGK69mQI0lSDQBJkpoC2QCyLGdRwkGJN9bvNEzoGLEtmCr9lS5uzk1rkpuSQVbekIB7sqITyU3NwLlpTQCq9H+KyO1KxV9wLKV39yCSL4YBoHWwodV3Uzg/fyPxJy4b5X1vwsTov4LxefFpABwDa5Kbkm4YjnBPdl7ejoFK3j4vPk3MNuVmLWb7SXwGKNv7DHia6LzlB4Le4kDQOA4EjSPqz2P8M20dMX8FY+ntgspKGRMfsekQOfGphLz6UZnFUbDXhEOTGqCSyIlP4er8jexvMoYDQeM4M/JT4g+d59yY5cV8axWDla8rjdZN4tyY5aRfjzAsjz9wFs+eLdC6OQDKGzqsKrkR89cJjnaaxtFO0x54c6G2sTTMkyGpVVi0aInutulZ7XMvXkTjWwmVlxdoNFh26EjW4UNGaTQ1a+EwYRJJ785ATkwstA+rDp0eubtx7pWLqLwrofJQ4rBo25GcE8ZxqLx9Df/XBrZCH6GcI5KNHfazFpH+7SpyL557pDiMYrp8EbVPJVSeecemXUeyj94Xk09+TBbNW6ELDyu1/B9XGXHr0oT0q+FGaVJCrmLt541VFQ8krQaP3m2I3W784y52ezBe/dsB4P5cSxIOFn/sDTE72uL7WlciNhRfbk59s4v1PWaxvscsruw4iX9fZWy1T5MaZKWkkxZduEw+NbkflvbW7Hr/O6Plng2q0m3hMH59fQnpccmFtivKzfU7DZPhRW4LpnJePe/UtCY5KelF1vM5qRk45dXzlQvU87bVvfJj6daM1KtKw5i1rytB6yYQMnY5adcjzYqrohF1miLkm1183WMWX+eV1wZ55dX7AeW1bV553X1feS2px1FWLQtcj52a1ECSJLMaGgD869bkVngEYRFR5OTk8NfeQ7RvHWSUJiEp2fCk88vvf+OFbsqPHP86NUhJTSM+MQmAYyHnqFHV/CEcBZlTt6tr1MLurUkkvz8DOanAcVOpkOyVsqyu5oemup/Jhi9zPK7zRhvYEn246fNGd/WS0TVY26Yj2cHGE5OqvApcg5u2RBehXDdSZ79F8piBJI8ZSNaWX8jctEE0NJSCI9/uZFmPGSzrMYPzO4IJ7KOcz1Wa1CQzJZ2UmMJ1yTOT+mNlb82fHxhP0GzjbI8kKXN+dBj9PCd+2leiOJb2mMHSvDiaFogjw0QcXc2MI7gEcez5dhtzekxmTo/JnNpxnNZ9lPsPvya1yEhJJ+m+OCxtrAzzOKjUKhp1DCTimlJm7V2V80qSJJ4b2499G3aYHYcgAEjyA5ppJEnqCHwFZKH0ghgoy/IxSZLcgSmyLE8tLoN7PRvuF7DwNTw7NCI3I4uQ8atIDFW693fYtYC9nWcC4NSoOk3vvWZqTyhnZn4FQOBno3DwrwoypN+J4fSUtWRFJ1J7fG9qv9XL6Ab00MBFZMcmYyPnPxWsu3Aobh0bo8vI4vzbXxguQi13L+Jop+kAODTyw//TUaisLIjdfZqLea9I0jrbEbBmPFa+rmSGxRI6fCm5ifmvvgRosGwUsTtPEbX5GC5PN6TO+68oTTMS3F63g/Bvd5dZHJWHdaXyEOUpqC4zm0uzvyUp+LJRfM6t61NtdE9CXvmQZ6KMu8SWh8jfDuHcuj5aF3uyY5K49tHPqDRqAMK+2UX9JSPxeLY5mWF5Y95zdRzrqpQRz+dbUf2t3qCSkHN0XJyxjqSTVwrl0fbEZ2jsbZAsNOQmpXFqwHxyElJp/O00VJYaJJUK1T8nSF3xuTKZlQkWzVtgN0Z5BVjGX1tJ//47bF8bRs6li2QfOYzThx+j8fNDF6e0Guujo0l6V4lV5emF86efEzfwxWKbRzUODz5m2qYt8l99uXsrmb98h/VLw8i9epGcE4exeX0cmoBA0OUip6aSvmYpujs3seo3GOu+L6OLyP+hn/L+ZOMbxAL0mQ+OwyimoBbYjRgHahWZO7aSsfE7bAYPI/fyRbKPHcZ25Di0TQIhNxd9aippK5aiu33TrH3njlhQIcpI/KHz3Hh3faFeBi6dmlBz7mvKqy9/2MvtpZuoNnUAKaHXiNsejMpSS93Px2HfsDo5ialcGPkJmXk9r1qeWI7a3gZVXr6hA+aRfjmMel+8jV39agDcWvIz0b8b38weNWPCty5zh+DXLoCcjGy2Tl5N5Fmlnh26dT7re8zC3suFMcc+JfZqOLospefCyW92cmbjPgZumI57ncqk5v3oSr4bx69vLCmUR4Ms0+eL/8KheHRohC4ji9PjV5GUV8c9vWsh+zvPAMCxkZ/hdYLRe05zLq+eb/bleGxr+oBeJj0shrNT15IZmUDAx8PxfrY5GWH5c2Ac6Kq8VaXbufnFHhNTpsxZxImQMyQmJuPq4sTo1wfT97muxW9YhLgDERWivFakOu2rq5WLPW6d5w6hersAcjOy+atAeR2ydT5f95iFnZcLo499StzVcHLzymtIXnn1CvDjhdXjsXS0QZeVQ1pMEuu6TC+URz0T5bUsymq1Yc9QbUgX9Lk69JnZnJ/zdd8tFAAAIABJREFULQnBynfZNXhmscdj/7FTfJj36ssXundkxMt9+Xz9RhrUqUGH1kHs+PsIy9ZuQEIiMKA+s956AwsL5eHG4eBQ/u+Lr5GB+rX8eG/iSLTaoicDTh4+9oFxFFe3Oyz4GE01P/TxeZMPx0ST8v5M0Frg9PkaAOT0NFI/W4LuuumhtRWlntfcOEHGV8sfeN5omrTA5rWxoFKRvfcvMjd9h9WAoeiuXSIn+DDWQ8eibRiIrNMhp6aQvnYZ+rCbRvuwevE15MyMYl996fzzvgeu/y+ZVs28tyI9/8FQ6rRrRHZGFj9PWUX4WeV8fnvrQpb1mIGjlwszjy4n+mo4udlKT5zDX+/gxI97adi9Od2mDkSW4cbxf/h99voie/aZ88S1931xhOXFMX7rQpbmxTHr6HKiroajKxDH8bw4uheI4zcTccQoz4Ef6JUP3qBhuyZkZ2Sxdspybp69BsD7W/+POT0m4+DmyPi1M9FYaJFUEhePnOOHuevR6/R0GfosHQd3A+Dk9mP8sth0Q+/6m79WzNchlJIz1Z6r8H0bAm7+WeG+gwc2NgBISrPai8A2WZaTJUl6B2gKzJNl+VRxGZhqbHjcCjY2CPkqQmPDTs8B5R0CAI38K85T0uIaGx6XkjQ2lKWQU17FJ3pMtFSMusScxobH4UGNDY/bozQ2lKZ9DWaUdwhAxarTzGlseBxMNTY8buY0NjwuxTU2PC4VpZ5v9nRUeYdgRDQ25DO3seFxqBA/bjCvseFx+bc3Npyu2quifO0mNb71R4X7Dop99aWstEa8k9fQ0BbojDJJ5MqyDk4QBEEQBEEQBEEQhCdPsY0Nee49CngWWC3L8hbAomxCEgRBEARBEARBEAThSVbc2yjuCZckaRXQBVgsSZIl5jdUCIIgCIIgCIIgCMITSZYr3AiFJ4K5DQb9ge1AV1mWEwEXYMqDNxEEQRAEQRAEQRAE4b/IrJ4NsiynA5sK/B0BRJjeQhAEQRAEQRAEQRCE/ypzh1EIgiAIgiAIgiAIwn9OMS9wFEwQ8y4IgiAIgiAIgiAIglCqRGODIAiCIAiCIAiCIAilSgyjEARBEARBEARBEAQT9OJtFA9F9GwQBEEQBEEQBEEQBKFUicYGQRAEQRAEQRAEQRBKVZkPo7CVdWWdhfCEa39+YXmHAMC+BjPKOwTBhIpSRqDilJPAzJzyDqHCqSjfTUUprxXleAA0QZTXgv4OnFfeIRTgVd4BAOK8MaVLeQdQgXTO0Jd3CBWQGBEvVGyihAqCIAiCIAiCIAiCCbKYs+GhiGEUgiAIgiAIgiAIgiCUKtHYIAiCIAiCIAiCIAhCqRLDKARBEARBEARBEATBBPHqy4cjejYIgiAIgiAIgiAIglCqRGODIAiCIAiCIAiCIAilSgyjEARBEARBEARBEAQT5PIO4AklejYIgiAIgiAIgiAIglCqRGODIAiCIAiCIAiCIAilSgyjEARBEARBEARBEAQTxNsoHk6ZNza0PfEZuWmZoNMj5+o41nWm0fqqo5/Du29bACSNGttavuyr/wa5iWlm7V/rbEfA2ok4NK7B3Y37uDRzvWFd4KbZWHo6o8/MRmWhJTc9E/t6Vbi6cCO3Vm4ucn/+K8bh0MgPOVdHUshV/pm8BjlXZ/bn9XiuJTUm98O2ti/Hu80iOfS6YZ1d/So0+HQ0trV8AUi/FoF1FXeuffgzt1dvfSzHRNKqqbtwGM6t64P+3zH66J0FS9h/6Dguzk78/t0XD72fKiN74DuoIwCp/9zm/Nsr0WflGNZ7D2hH7dmvkBUZD8CdddsJ37DH7P3b1PShwbJRODSsblQGLX1c8f98DBZujiDLhH23mztr/jJ7e3OZKhcqawsC1kzApponsk5PzM6TXJ33A1D8+VtWMRXU+JspaJwqkZsYVqJ9F1RaZQRA42BD/SUjsatbGVmGCxNWkhR8JX+9oy0Nlr6JdTVP9Fk5nB//BWkX75Qoj2pv9cZ3UAdknZ5Ls74ibl8oAJWHd6fSK50A0KVlYl3Vg+zYZI60m1w4Tntr/FeMw8rXDUmt4tbKzdzduM/sGEpSXuP2hppVDpzbNqD2nMGoLDQkh17nwoQvkHV6s2N6UP3afMdCHPyrIufqOf3qR4Zjdo9X37ZUG9sLJAldagb/TF1L6oVbZuf9oLLa5IcZWHo6I6lVJB67aPY+TSmt8lp/6Zu4d2lqsoyUR51SFIfGNQjaMpezI5cRvfmY2fk/TJ1q7mcuq7Ja8JhF/3UCm2qeZh3/GjMG4PlcS2SdTNjXO7jz5bZHjsXl6YbUemcQkoUGOTsXjb01adfucvqVD422t6rkRv2lb2Lh6kBOQirnxnxOVkS82fmbOuYqSy3N/vceKgstklqFysYOfXqC2fu9X2mdN+Zckx/Xtc+6qudDf45/q5LeI9eZ/xo+L3Vgr9+QEuVTeVhXqozogU11L/bVe4Oc+BQA3Ls1o8a0/qCXkXN1XHr3axKPXzJs59y6PnXmDkHSqMmJTyH4hffNzrMk15l/pq8FvVxsPX9PadezBiqJFjsWGu6NBeF+j6Vnw8k+HxhO0vvdWvEnt1b8CYDbM02pOvJZs39UA+iycri26Efs6lbGtm7lQuvPjf6M5NDraN0csK7kjnv3Zg/cX+SvBzg3+jMAGn7xFr4vdyTs651mx5N28Q6hwz6m3kfDjZZLahX+y8dybsxyUi/cQutsR05KOk+HrCR663GjtGV5TKqP70N2bDKHW08ASaJL5Eaz91tR9e7RhUF9ezFz7v89/E5Uaqq80Z3DT01En5lDw9Xj8ezdmogf/zZKFvm/w0XeFJgjJzGVS7O+KlQG5Vwdl+d8S8rZG6htrWixcyHxf58h7XK4Wdub60Hl4tbKzSQcOo+kVRP4y7u4dmxM3J7TwIPP37KMCcCjR3OlseMRlUoZyVNn3mvE7Q3lzBufIGnVqK0tjdZXf7s3KeduETr0Y2xq+lB30TBO9Ztn9v5ta/vi1bs1h5+ehKWXM4E/v8OhVuOxrV2JSq904li3mcjZuQT9NY/zE1dRa+ZLRe6n0rCupF4K4/TgD9G62tPm0FIifj2AnGNe42lJymtK6PXiy4Ek4f/paE72m0f69QhqTH0R7wHtuPv9XrOPjan61ba2L1oHG473nI3/52Oou3gYh1qNN2pQzbgVTXDv98lNSsO1Y2Pqfzyc493fMTvvB5XVM8OXokvNACBg7UQkC1vkbPPr7PuVVnm9u/Fv7qzdjv/nY4pcX151ihGVRK13BxG/70yJ83+YOtWsz1yGZbXgMbNvXMOs4+8zsD1WPm4cbjMRZBmtm4PZcTwolpz4FE4P/pCsqARqzn6ZKsO6knbtbqHta88ZTMRP+4n4aT/ObRtQc9ZLnB+73Oz8TR1zfVYOJ/t8gC49C0mjpuPNdUiadOTcrBJ9vntK67wx55r8pFz7/o1Kco/s0MgPjaPtQ+WTePwSMTtP0WzTbKPl8fvPErMtGFAeIgasHs/hthMB5WFE3UWvE/LSAjLD40p8rpbkOuPZqxVRvx8utp4HyqSevafK8B6kXQlHY29d4n0L/w0Vas4GrxfaEPnbofy/+7al+bb5tNy9WLlIqgp3X9GnZ5F4/BK6Ak+gi5ITm0zy6WvF3mjH7s6/GUoKuYqljwsAKhtL6i99k+bb5tNi1yLcuxV90qVdCSf9WkSh5a7tA0i9cNvwJC0nIRWXNv5k3IwiMyzWZDylfUx8X2rPjU9/V/6Q/x09G5o1boijg/0j70dSq1BZWSCpVahtLMiKNP8JS9XRz9F82wJa7v0QvykvFpnGVBnMjk4k5ewNQHlanXYlHEsvF7O3h0crF/qMbBIOnQdAztGRcvYGVj6F8y/JZ3rUmADUNpZUefNZbnyyyaxYHqS0ygiShHOreoYeLXKOjtzkdKMktrUrEX/wHADpV+9iXdkdC3dHwLxj4t4tiMjfDyNn55J5O4b0G1E4Nq2JbS1fkk5dQZ+RrTwt/isYx8DapmOVQWOnXPzVtlbkJKYi5ypPZku7vKqsLIqtX7Uuduhzckm/rtSPcX+fxfPZFsCj16/u3YII/34v2TFJyDk6wzErKCn4MrlJyg1p0skrWHq7GtY9alm9dwMoadSoLB69Db+0ymvi0X/ISUw1ub4i1ClV3uhO1OZjZMcmGS0vqzrVnHuBsiyrBY+ZPjPbrPuSSq914frHvxiu2TmxyaUSS8q5m2RFJWDp7YJDQHWlfpAK3xba1vYl/qDyfSYcPI9HgXwe5XsC0KUrDQuSVo0kPVoX5dI6b8y5Jj8p175/u/vvkY2oJGrNeYUrH2wwWqx1tSdg7USab1tA820LcAyqU+TmKeduknknptDye2UWlO+q4K20V5+2RG89TmZ4HJB/rkIZXGfyMi6unoeyqWcBLL1dcOvSpES9fJ9ksixV+H8VkVmNDZIkeUqS1DTvX4n7dDX9cRYtdizEd3An04FYW+DWoTFReV17bGspT/dO9JzN0U7TkHV6vPs+VdKsqb9sFC13L6b6hD4l2k7SqPHu9zRxe5SuuH7jXyD+wDmOd5vFyT4fUGv2y6hsLIvZSz6bGj7IskyTjTNpsXMRVcf0wuuF1qYrSUr/mGgcbACoOa0/LXYuImDNBLO3/dfT67i5cjNPnVrB02dWkZucQfzfhVuAPXu2oOXeDwn4cgKWPsqPFZd2Adj4eXG820yOdpyGQ6PqOLWs91BhWFV2x96/Okmnrpq9TWmdK6CUEbdnAok/cM6wzJzztyxiqjF9ALdWbkaXkV2i7cqUSkt2XDINlo2ixa5F1F8yslA9kHrhFh7PNgfAoUkNrCq5Y+ntYvYxsfRyJjM8vwEyKyIOSy8X0i7ewalFXbTOdkrd0LkJll7OJkO9s3YbtrV9efrMF7Ta939ceucrkOVyK685cSlIajUOjfwA8HyuBZa+yjn0qPWrqWNmiu+gDoan7KV1/jTZOJN251eTm5rxSL0aKoKyrlPusfRyxqN7EGFfGfceLO86tSzL6sOwruqJV+/WtNi+gCbfT8emulepxlJn7hDi9oaSdj0C5MJDRVIK1GkePZqjsbdB62xXOt+TSqLl7sW0O78GfXbGQ/dqKCslLT//2mtfBXT/PfL9Kr/ejZjtwWRHJxotrzPvNW6v2sLxbjM58/rH1F8yssR5u3cPovXBJTT5bjoXJqw0LLep4Y3W0ZbATbNpsWMh3i8+DZTNdSbqz6NmbVOW9WyduUOUxpx/ybBsoWw88BGMJEmNgS8AR+Be/7FKkiQlAqNlWT5VXAYnnptNVmQCWjcHAn96h7Qrd0k8+k+hdO7PBJJ44pKhK5TLU/44BFSnxfYFAKisLAq1yBXn3OjPyIpMQG1rRaN1E8nMO+nNUXfx6yQc/ccw/ta1XQDuXZtRbfRzSjyWFlj7upF2JfxBuzGQ1CqcW9TlWNeZ6DKyCPz1XexqVeLqfNPjWEv7mEgaNVa+biSeuPz/7N13eBTF/8Dx9+YuCem9J0ASei+hSq8BaVJVROkd/AkCgmABpIoFUYr9qwKidGkiiBRBaiD0HiC910u5u/39ceGSI7k0Ajl0Xs/DQ+52dudze7Nzu7Mzs1x/9wcqj3sejz4tS7z+v5pkhntwEEebTUadnEGDr97Ac0AbojYf1SeJ+/0MUVuPIWer8RnWhXqfTeTMgAW4dGiAS/sGtDywFNDdRbYO8Cy0nBdFYW1Jw6+ncX3e9/oW7JIoj2MFdGW0/pqp3P9qL6qwGKDkx295x2RbtwrWVT24/s7/qOTnVurP8qRIEtjV9+fqnG9JOXuTmgtfw39KX24t3aRPc2fldmouHE7LA0tJvXKP1NC7yBrtY++T9Bvh3F21gyY/v40mI4vUi3eRLMyNpnfp2JDUi3c5038+VlU9aPrLXI6fmFmh5TV0/KfUmP8qZpbmxB+6ALlj4B+3fi0Np+fq4v1yJ0730XWNLa/j59yLizCzNKfeF1OQzK2Qc0p+DJuaJ1mn5FdzwXBuLFxfoJddRdepYBpl9SEzS3O0mTn8030O7j2bU+eT8Zzu+165xOLatQmyWoPvq124tWQTngOeK5Dmxns/UnPxSLyHtCfpxBUyI+KRNdry+Z60Mic6z0Jpb037S1+Awhw0RfdUfVrKUn7+rb99pujRc+T8LD2c8OjdkjOFzJfg0q4+tjV89a+VdlYorC0NeiwUJ3bPKWL3nMKxZW0CZw3h7CDdUElJYYZdwwDODFyAopIFzXctIPnMjSfyO+Pcph4Jh0OLXedJ1bOuufNEpF64o5sHThCMKK6/53fAOFmWDZoNJUlqCXwLNCxsJUmSxgJjAV63a8rzVoHkxKUQs/skDo0DCy3Inv0eucsvSURsOlzgYtytRzMC3xwIwOVpaw0mCHuUW49m+snUwjcewr5xoNGx5/kFTB+IhYs9599cYRDP+ZErCnRFrPPJBOzrVyUrKpFzQ5cY3WZmZAKJx6/o81fdjcbc0ZbsWOOVTXnvk5yEVDQZmcTs0s0REb3zBDXnv2o0//8SydwK1b3b5MTrvp+YXSdxbFbToLEhJzGvm1r4Tweo/s5Q3bqSxJ2V2wn/4Q+DbfqO6KYvf+deXkJWtPFhGZJSQYNvphO5+ajBHB4l2kY5HCsAtVeMJeNOlMFkpQ+HkhR3/JZ3TI5BNbBvGECbU58hKRWgMEfh4IUmuWBX4KdJ1mjIiognJfcuV/TOf6g6pa9BGk2aisv/l3eno82pz1CFxeDUsnaJ9klWVCKVfFz1yy29XPQTL0Ws/1M/brzanBd1d74eGS7wkPeLHbj72XZAV9+o7sVgU9273Mpr832LUNpZEzB9AMlnbhSZ/qHk0zc43fc94OFdFa/cDT5e/Zq3z3STdOXfZ/nZ1qlMnY/Gcu6lJXnHczkdP6Abgx679zSunWs9040NT7JOyV/OlPbW1F8zFQBzF3tcuzRG1mjKvU618HDUn1AXt95DT6qsPvwMSkdbEo4Uf6EAkBURT/Ru3WlYzO6T1Pl0QrnEArpGSffeLcmJT6HG/FdR2lrlzi+1Ki//6EQujNSdDymsLXF/vgXqlIxy+Z4eUqdkIOeoMLOwRqsq/UVYeTP2m1z8iuX722fh6lDmz/Bv1PLAUn2ZKnCOnI9d/apY+3vy3IlPAVBYWfDciU851vJ1kCRO9pxrMAE46HoNWLo56CaEnba2RPEknbiCXd0qtDq0HFmjJWrHceL/PI82IwttRhaJJ65gW7fKE/mdcQsOKlFjg32jgCdSzzo2r4lb96a4dm6EWSWLh8M2fwReKTYo4T+luMYGm0cbGgBkWT4hSZLRGVdkWV4HrANsDga8lqZJz8TM2hKXDg24vWJzwSDsrHBqVYfQfD9uCUdCafT9DMLW7iInLgWlow1KWyt9a2JxJIUZ0duP8+Db35GUCuqvmUrC4VAs3B2LXM9naCdcOjbgzMAFBq2A8YfO4zcqWD85oF29qqRevGtwUVGU+D/PU3VSH8ysLJCz1Ti3rV/kEIonsU8AYn8/i9NzdUg8egnntvVKtM5/glaNQ5PqmFlZoFVl49y2XoFK38LdUd8dz617kP7uUdyf56n21mCiNh9Bk5GFpacTWrWGB9/+zoNvfy9R9nU+Hk/6jXDurd1l8H5JtlEe5SLwrSEo7ay5/EbeD6yZtSWSJFHc8fskYnrw/X79xKyV/Nxoc+KjCm9oAEDWkBkRj3WgFxm3InFuW4/064ZPyVDaW6NRZSHnaPB5pROJJ66iSVOVeJ9oMrOpv3oqYWt+w9LTCesAT30XXnNXe3LiUqjk44J7z+ZcGPMxnv1aFxpqZngczm3rkfTPVSzcHLAO9EYVFlNu5TX+0AWuz/u+VLvvYfyShZKqU/pw55OtwOPXr7H7TlN/9VSifzuBZK4w2GcPVfJxoeE307k46XP9WHx4/LKqsLZEYWtFdkwSksIM166NTebObFk9qToFjNdpdT+dQOz+s8TuOY0mI7vc69SSrvfQkyqrDz+D15D2+mEaxYnZewrn5+oSce8QTq3r6BsXHjcWpb01Ti1rEzrmE2J2n8SpdR2qTOxl0NAAYO5sp2uck2Wqvt6PiA26Bs/HrUvMXez0896YVTJHsrBCm1HxDQ1g/De5OOX929f4x1nYFjKB5H/Vic6zgMLPkfOL++Mch+vnDY/oePt7XUMDEP/XBfxGBesnmbStW4W0S2Gce3FRiWKwquqB6m40oOvpqM1Wc7zDDEA3XKLm4hFICjMkCyUOTaoTtnY36dful/vvTNKJkj356GizKfq/y7OevfnBBn3jycO6w61r0391Q0PJn0ck5CfJRUwSKEnSSiAQ+B/w8NltfsCrwB1ZlicXs/2A1Etht0B38R+19Rh3PtmK76tdAHjwP11rmteQ9rh2akTouE8NVvbo2wr/qf3ATELO0XB19jckn7nBo9qc+gylnTWShRJ1cjpnh3yA6kEczba9p5t0yMyMpNPXcO3UGKWdFbJWRpOeyd9tp6NJU9H4p7d0dxSjE+kcvp7MB7Fo0nSzAMfsOsntjzZjVsmcmguG49CsBpIkobofU+DxUKBrpay1aITuEVEp6aRezKvAPAe00X0eScKqijuH641Fnaq7+/U09kn69XAq+bpSb9VklA7WZMen4NK2fjFf4ZOXE1d8S25RZry7hFPnLpCUlIKLsyMTRw1jQO/upd7Ove/O4tm3FbJGS0roHS5PW0vA/71AyvnbxO47Q7W3X8KtW1NkjZacpDSuzPyKjJu6mbv9xvTAZ6jusZma9EwuTlyFKizaYPsWbg60+H1xgTJoV6cyzXbOJ/VymH7c281FGwwmKy1qfU2a6rHKhTpVRbuQ1aRdD0fO1l0k3f9mHwlHL9LwW91jlIwdv08qpvyzfj9sbHicR1+WVxkBOD14DXU/GodkoUQVFsOl11fj2bcVoNsnDkHVqbtyIsiQdu0Bl99Yo5+YsKT7xP//XsD7pQ7Iai3X5n2vn18gaPt7mDvZIas15CSmYlPdB3NnO7Jjk7m1/BfMlAp9HJYeTtRdOQELD6fcOxjb9D11yru83v18B9XnDS22fq3+zlBcuzZFMpN48P1+/R3v8qhfW/65TNc1VmFGTkIqNxauN9gfdT4ah/vzzfUT8uZ/lOvjlNWcxDQa/TALM0slkpkZCccu4dW3iIk7S6C8ymv8kUicWtcxWkaedp1S1CRiD0+CHz6S7UnVqUV95qdVVvX7zFKJwtIcTWYOslpjNBalvbXuMba+rmjSM7ky4yvSLoc9diz+b/THf2pfMm5HAbpu1KqwGM4O+YDAmYP0v33uvVpQ/e2XkGWZpBO6R+7J2erH/p6sKrtRd+VE3YWZmRlWfjZoVYbj60ujvI6bkBHfFVp+HvY4e5q/faKxwdB+jyGA8XPk/MdNfh1vf69/9KW5sx21lozEproPkkJB0okrXJn5VYG8/EYHU3VSHyzcHcmJSybuQAiXp62l6uQ+eA1qpztmM7O58f6PBo++rDKxN94vdgBZJvyng/q6o7x/Z67P+x5Zo6X+mqlF1vP5lWc9m39oUb7GBtOcobCcHPEcaPKTU7SN+tXkvoMiGxsAJEnqAfQFfHLfCgd2yLK82/haefZ7DDH5L+a/rGv0zxUdwmM3NpSXQ3VnV3QIghEdLi2u6BD0RDkRimMq5VWUVeFZIo6bwpnCeZqpeNjYIJimrtE/m9yFbnkSjQ1lU+wzumRZ3gPseQqxCIIgCIIgCIIgCIJJkTG56/hnQokefVkYSZLWlWcggiAIgiAIgiAIgiD8OxT36EtjDyqXgJ7lH44gCIIgCIIgCIIgCM+64oZRxAJhYNBvRM597f6kghIEQRAEQRAEQRAEU6A1+RkbTFNxjQ23gc6yLN97dIEkSfcLSS8IgiAIgiAIgiAIwn9ccXM2fAI4GVlW8PlKgiAIgiAIgiAIgiD85xXZs0GW5c8BJEkaBOyVZTlVkqR5QGNg4VOITxAEQRAEQRAEQRAqjFY8jaJMSvo0inm5DQ1tgM7A18DqJxeWIAiCIAiCIAiCIAjPqpI2Nmhy/38eWCfL8i7A4smEJAiCIAiCIAiCIAjCs6y4CSIfCpckaS3QFVgqSZIlJW+oEARBEARBEARBEIRnkiyGUZRJSRsMBgP7gO6yLCcBzsCMJxaVIAiCIAiCIAiCIAjlQpKkYEmSrkmSdFOSpLcKWW4pSdLPucv/kSSp6uPmWaKeDbIsZwBb8r2OBCJLsq452rJFVs7EpB6m61Dd2RUdAgBtvmlV0SHkUaVVdAQASJVrVnQIgOmUEYAqzskVHQIA9e9cqugQAEja825Fh6CXuvCHig4BMJ3y2uHS4ooOQc/Ku21FhwBA6r73KzoEAMIn/VLRIej5fD6ookMATOe4afNls4oOQTBicPqZig7B5NhbWld0CHphFR2AUCRJkhTA5+hGKjwATkmStEOW5cv5ko0CEmVZriZJ0ovAUmDI4+QrhkIIgiAIgiAIgiAIghHaZ+BfMZoDN2VZvi3LcjawEej7SJq+wPe5f/8KdJYk6bHu2IvGBkEQBEEQBEEQBEH49/IB7ud7/SD3vULTyLKsBpIBl8fJVDQ2CIIgCIIgCIIgCMIzTJKksZIknc73b2xFx1TSp1EIgiAIgiAIgiAIgmCCZFleB6wzsjgc8Mv32jf3vcLSPJAkSQk4APGPE5Po2SAIgiAIgiAIgiAIRshIJv+vGKeA6pIk+UuSZAG8COx4JM0O4LXcvwcCB2VZlh9nv4meDYIgCIIgCIIgCILwLyXLslqSpMnAPkABfCPL8iVJkuYDp2VZ3gF8DfwgSdJNIAFdg8RjEY0NgiAIgiAIgiAIgvAvJsvybmD3I++9k+/vTKBcn4csGhsEQRAEQRAEQRAEwYgSPFpSKISYs0EQBEEQBEEQBEEQhHIlGhsEQRAEQRAEQRAEQShXFTKMwrljI6otHIGkMCPypwPc+2ybwXLJQkntVVOwaxDCKfeTAAAgAElEQVRATmIql8d+TOb9WJzaNSBg7lAkCyVytppb838g6ehFABpteQ8LDye0mdkAnB+ygJy4lGLiaEj1fHGEfba9QBx1Vk3Wx3Fp7Cdk3o9F6WRL/a+nYdeoGlEbD3F9zjcAmFlZUO/LaVhV9UDWaInff4ZbC9eXYH+YRhwVpc4n43Hr2oTsuBSOt3+zwHLrat7U/XQC9vX9ubl4I2GrfyvV9s2dbGnw9TTsGwUSsfEQ1+Z8C+j2U4Mv38A6dz8plVGorx0rclvHrtxj2bajaLUyL7SszcjOTQyWL992jFM3dU+RycxRk5Cq4uiiUfrlaZnZ9F+6kY71/Jk9oG2pPofRmK6Hs2zXaV1MQdUY2b6eYUy7TnHqdnReTOmZHJ332PO96PK+cJ2lP+xGq9XyQoemjOrd3mB5ZFwSc9dtJjUjE61Wy+uDu9G2UU1Cbz1gwTe6416WYXz/TnQOqmM0H1MpI7H7z5DzxZoit2XdpinucyaAmRnJv+4l8atNBsutgurhNns8ljX8iZy+mLTfj+qXKb3c8Fjwfyg93UCWCR/3DuqI6FJ9lvw+WvE+wcGdyMhQMXrMNEJCLhZIM3hwX2bNnIwsy0RGRjN8xFTi4xNZvOhtnn++C9nZOdy+HcaYsdNJTi66TjXm2KU7LNt0QFdGn2vAyOAWBsuXbzrIqev3AMjMVpOQmsHRj6cC8PHmQxy5eBtZlmlZuyozB3dCkoqdcblQFs2aYztpCpiZkbl7FxkbDetFq4GDser5PGg0aJOSSFm+FG1MNOaNGmM7YZI+nbJyZZIXzif72NFHswBMp7yaWduhzUgo1bbzm7voIw4fO4mzkyPbfiy63JeHjz+aT4/gTmSoVIwa9QbnCimvQ4b05a1ZU3TlNSKaV4dPIT4+kXfmTWPUyJeJjdN93nnzlrBn78FSx2AqZRXAuk0QrrPHg0JByq97SHqkLqnUtB6us8djWSOAqDcXkf5IXeI+/w1dXYJMxLh5Za5LntY+MZXjRqmIQH3lSNH75Op9lu04rtsnzWsyslMjw32y4zinbkbo9kmOmoS0TI4ueI2r4fEs2nKUtKxsFJIZozs3onujwFJ9DqF4S5bPo2u3DqhUKiaOm8WF85cMltva2rD79w36194+nmzauJ05sz7ggyVv07adroxbWVnh5uZCVV/Dc71nLY5Hvbd4Fh27tEWlyuTNyfO4eOGKwXIbW2t++e07/Wsvbw+2/rKL+W8vK5f8n1ViGEXZPP3GBjMzqi8ZxfnBC8iKSKDpvsXE7TtNxvUH+iReL3dCnZTGPy2n4N6vNQHzXuHy2I/JSUghdNgSsqMTsanlR4ONczneaJx+vSsTPyX1/O0SxiFRc8kozg1eSFZEPEH7FhO77zQZ1/MeN+r9cifUSemcaDkV936tCZw3lEtjP0GblcPtJT9jU6sytrX8DDZ7b/VOko5dQjJX0PjXd3Du1IiEgyGmH0cFitj4F/e/3ke9VZMKXZ6TlMa1t7/DrUdQmbavycrh1pKfsa3lh80j+yls9W8k5u6njheWY+ZWFW3s3cK3o9WyeMsR1ozvjYeDDUM/3kz7ulUJ9HTWp5nR7zn93xuOhHI1PM5gG5/vOUmTAK8yfQ6jMe08yZoRXfCwt2bo6j20r+1LoLtjXkzPN8uL6fhVrkaU/eLj0bwXfb+TtbNG4OFsz8vvrKFDk9oE+rjr03y5/RDdm9djcJcW3AqPYfKH/2NPo5pU83Vn/fwJKBUKYpNSGTRnFe0b10SpUBSal6mUkaa/ziO9bRAZR04XviEzM9znTSJ81BxyouOosmkl6X+eIPvWvbxYI2KJmr0C55EDCqzuuWQGCWs3kPH3OSTrSqAt+9OGgrt3pFo1f+rUbUvz5o35bOUi2rbrY5BGoVCw4sP3aNS4E/HxiSz6YA4TJgxn4cKPOXDwCHPnLUGj0fDBwtnMnDGJt+cuLnUcGq2WxRv2s+b1wXg42TF08Q+0bxBIoLerPs2MwZ30f2/48yxX7+suikJuhRNyK5xf5g0HYMTy9Zy+fp9mNSuXfoeYmWE39f9InDkdbWwsTl+sJev4MTRhYfok6ps3SJgwFrKysOrdF9ux40lZ+D45IedIHDcaAMnODpf/rSf79CmjWZlKee1052skcyvkHFWZ8unXsysvD+jDnAUflmn90ugR3Inq1fypVacNLZo34fNVi2ndprdBGoVCwccr5lO/YQfi4xNZsvhtJk0cwfwFHwHw6cov+ejjtWWOwWTKKoCZGW5zJxE+ejbq6Dj8fv6M9D9PkJOvLlFHxhIzZwWOIwYWWN1j8QwS1m5EdfzsY9UlT3OfmMpx0/H8Mszc/dHG3Cl8O1oti7ceY83YnrpzgZXbaF+3CoEeTvo0M/q00v+94ehFrkboHlNvZaFgwYsdqOLmQExyOi9/upVWNX2xt7Is02cSCurarT2BgVVp2rAzQc0aseKT9+na0fAYSUtLp13rvN/DP49s47cdvwPw9lsf6N8fM34YDRoYvxHyLMTxqI5d2uAfUIX2zXrROKgBCz+cS79uQw3SpKdl0LPDYP3r3w5sZO9vB8olf+G/56kPo7BvUg3VnSgyw2KQc9TEbDuGa7DhD4drcDOiNv0FQOzOEzi10d2pTbt4l+zoRADSr97HrJIFkkXZ2kvsm1QjQx+Hhphtf+MW3MwgjWtwEJGbDhWIQ5uRRfLJa2izsg3Sa1XZJB3TtVrKORpSQ+9QydvlmYijIiWduEJOUprR5TlxKaSE3ELO0RRY5jmgDc33fkDLA0upvXwMmBW8Y6LNyCLp5DU0WTmG76uyScy3n+TkGKRKtkbjuHgvBj9XB3xd7DFXKujeuBqHLt41mn7PuRsEN66mf335fiwJqSpa1fQzuk5pXXwQj5+zHb7OdrqYGlTh0JX7xmO6cJfghlXLJ+9bD/DzcMHX3RlzpZLglvU5dMawdRwJ0jKzAEjLyMTN0Q4AK0sLfcNCVnYOxd38M5Uykhp6B3NP1wLrP1SpQU1y7kWS8yAKctSk7P4Lm06tDNKoI6LJvn4H+ZGTf4vAykgKBRl/n9Pll5GJnLvvyqJ37278+NNmAE6ePIejoz2enu4GaSRJQpIkbGysAbC3tyUyUneh8Mcfh9FodPvzn5Pn8PEtWyPZxbuR+Lk74evmqCujzWpx6MJNo+n3nLpCcFDt3PggW60hR60hW61BrdHiYm9TpjiUtWqjDg9HGxkJajVZfx7EsnUbgzQ5IecgS7fPc65cxszNrcB2LNt1IPvkP/p0hTGV8iqrs8Gs7PcUghrVx8Herszrl0bv3t354adfAfjn5FkcHB2KLa92dnZEPEbPn0eZSlkFqFS/Jjn3IlDn1iVpew5ha6QuQWt4v808sDIoFKiOnwUery55mvvEZI6b5OhizgVi8XO1zzsXaBTIoUthRtPvCblFcG7vhSpujlRxcwDA3cEGZ1srEtMyja4rlF7PXl3YuGErAKdPheDgYI+HR8G6/KHAalVxc3Ph72MFG5AHDuzN5l9K14PG1OJ4VNceHdn8804Azp2+gL2DHe4exs9r/AOr4OLmzMnjZ8olf+G/p8yNDZIkGa+Ji2Dp6UxWbgsvQFZEApaehhfCll7OZOXeEZY1WtSpGZg7G57wuPVqSVrobeRstf69mp9OIujAcqq8UfCOYfFxxGOZ7w51Xhzx+jg0hcRhjNLeGtduTUk4EvpMxPEssqnug2e/1pzq9Q4nOs9C1mjxKuPQBKW9NWYeAWjj7hlNE5Ocjqdj3omSh6MNMcnphaaNSEglIj6V5tV9ANBqZVbs+JtpfVoVmr6sYlIy8HTIF5O9DTHJhd/FjEhMIyIhjeYBnuWTd2IKns4O+tfuzvZEJxp2s5/QvzO7jp2n69RlTPrwf7z1ai/9sgs37/PCWysZOGcVc0f0Ndqr4XGUdxlx7daUjOPGewgp3V1QR8XqX6uj4zD3KFlDn3lVHzSpaXitnEflzatwfXM0mJW9Pdjb25MHDyL0r8PDI/H2Nvzu1Wo1U6bO4czp/dy9c5patWvw7bcbC2xr+GuD2bfvzzLFEZOYhqdTXn3l4WhHTGLhFxQR8clExCXTvJbuzmfDAB+a1fCjy6zVdJ35Ba3q+BPgVbaGU4WrK9rYGP1rbWwsZq5FNBz16KlrVHj0/Y6dyPzzydzhKfc6zcK6zL0anjYfb08e3M9XXh9E4lNIeZ00ZTYhZw9wP+wsdWpX55tv87ogT5wwgrNn9vPluhU4OjpQWqZSVgEUHi7k5K9LouJQuBsvr/lZVPVBm5qO56fz8Nv8OS6PUZeY0j4xpvzPBQKLPhdIScfTMe8U2MOhiHOBxFQiElJpXs27wLLQezHkaLT4udiXKVahcF5eHoQ/iNS/joiIwsvbw2j6/gN7sWXzrgLv+/l5U7mqL4f/Ov5Mx/EoTy93IsKj9K+jIqLx8HI3mr73C8H8tnVfueT9rJORTP6fKXqcng2Xyy2KUrKu6UvAvKFce3NdXjATV3K6w3TO9ZmHQ8vaeAxqV1HhISnMqLvmde5/tYfMsJjiV/iXx/GkOLeth30Df1rsW0TLA0txblsPqyrGK0xjJIUZ9ddMRX0nBFlVtjHpj9p37iZdGgagyD3B23TsIm1qV8bDsUxtdOUTU+hdutSrrI/padhz/AJ92jZm/8qZfP7mq7y95le0uXfhGlTzY+uSqax/fzxf7/yLrOycYrZWeuVdRu5/tVfXa+EJkBQKrJrWI27Zl9wbPBVzP0/sX+j6RPJ6SKlUMm7sMFq07EFV/yAuhl5h5szJBmlmzZqCWq1hQ+4dmidp3+mrdGlSQ19G78Ukcjsqgd8Xj+f3JRM4dS2MszceFLOVx2fZpSvmNWqSscmw4cXM2RmlfwDZp04+kXzLu7xqVcmgVRe/wjNCqVQyfuyrBDXvjl+VJlwIvcJbs6YAsGbt/6hRqzVNg7oRFRXD8mXvFLO1x2MqZbVQCgWVmtYjbvmX3B88BXNfL+z6Pdm6BCpun5T/ucBZ5IzkcoltX8gtujTwL/C7G5uSwdyNh3h/cDvMCumFITw9/Qf2YvMvOwt9f8e2vfpzlv9KHI/q0z+Y7Vt2V0jewr9Dkf0rJUmaZmwRYPSqSZKkscBYgGl2TehtFaBflhWVgGW+Lv2W3s5kRcUbrJ8VmYCljytZkQlICjOUdtbkJKTq0ns5U+/bGVyZvIrMsLzuk9lRunHomvRMYrYcxb5xdaJ/OWz0sxWMw4WsKMOx7Lo4XPRxKPLFUZSaK8aRcSeKB+uKPzhNJY5nkiQRsekwNz/YYPC2W49mBL6pGxd3edpaUoqZx6P2irFk3InCJvNakencHWyISsq7exGdlI67Q+FdQveG3GR2/7w7K+fDojl3O5JNxy6hys4hR63B2tKc13u1LDLP4rjbWxOV745KdEo67g5Whcd04S6zezd/rPwM8nayJyoh74QsJiEFDyfDOzRb/zrD6hmvAtCwemWyctQkpmbg4pBXfQT4uGNtacHNBzHUDfApt/iAci8j99btpoqz8XTqmPjcCdl0lB6u5ETHG18h/7rRcWRdvaVvzEg7cByrhrVI2VzyOwrjx73GyJEvAXD6zHl8ffPupvn4eBERYdhQ0rBhXQBu39Z1Af5182/MeHOifvmwYYPo2aMzwT3KPqGou5MtUYl59VV0UiruToX/fOw9fZXZL3bRvz4YcoMG/l5YV7IA4Ll6AZy/HU6T6r6ljkMTF4eZW94FiJmbG9q4uALpzJs0xeblYSROmwo5hg1glh06knX0CGgKduMuF+VcXh0alv7u/tM0YfxrjBqlGyt8+nQIvn75yquvF+GPlNdGj5bXX3cyc4ZufH9MTN53+dXXP7F92/eljsdUyiqAJjoe8/x1iacrmpiC5bUw6qg4sq/e0g3BANIP/I1lw1qkbin93UlT2idGlfe5QPqlItO529sQlW+4R3RyUecCt5n9wnMG76VlZjPlm71MDg6iQRXjd7qFkhs99hVeHa6bY+DsmVCDYX/e3p5EGhluVa9eLZQKBedDCn7n/Qf2Ysa0d5/JOB716qghvDhM1+v7wrlLePvk9Rrz9PYgOrLwG5K169ZAoVBw8fyVQpcLQkkUd4tzEeAE2D3yz7aodWVZXifLcpAsy0H5GxoAUs/dxCrAi0qV3ZHMlbj3e464fYaTrcXtO43nYN2s9m69W5KY+8QJpb019X+aze2FP5FyKu/CUFKY6YcVSEoFLl2bkn7VeBc4XRy3sA7wolJlNyRzBe79WhcSxxm8BnfIF0fRP0AAAW8NQWlnzY253xWb1pTieBYlHAnFo1cLzF11F7hKRxsq+boSu+cUJzrP4kTnWcWeXATm7qdrc4s/Ma3r58692CTC41PIUWvYd+4m7etVLZDuTnQiKRlZNKyadxKx+JUu7H1nGHvmvcIbvVvRK6jmYzc0ANT1ceFefCrhCam6mC6E0b5WwTkh7sQmk6LKpmFl4+MFS513gA/3ouJ5EJNAjlrN3hOhtG9SyyCNl4sD/1zSfQe3w2PIzlHjbG/Dg5gE1LkXbBFxidyNjMPbzbFAHo/raZeRzNBrmFfxRunjAeZK7Hu2J/3PEyWKNTP0Ogo7WxROugtE6xYNybpVdD32qDVrv6d5i2Catwhm5459vDJUd3LRvHljkpNTiYoyPKGIiIiiVq3quLrqWlA6d27L1au68djdunZg+rTxDBg4EpWq7GOK61bx4l5MIuFxSboyeuoq7RtUK5DuTlQ8KemZNAzIu+D0crbnzI37qDVacjQazly/X+Zu2OqrV1H6+GLm6QlKJZYdO5H1t+HTZ5TVqmP/xnSS581GTkoqsI1KHTs/sSEU8PTLa0VbveZ7gpp1I6hZN3bs2MewoboLwxbNm5CSnFKgvIZHRFG7dl557dKlnb685p/foV/fHly6VHTjcWFMpawCZF68hnkVH31dYtujQ4nrkqyL1zGzs8Usty6xatnIYGLJ0jClfWLM0z8XcONeXArhCbnnAiG3aF+n4KSXd2KSSFFl0TBfL4sctYZp3++nV9PqdG0QUGAdoWy+Wvcj7Vr3oV3rPuz+bT8vvvQCAEHNGpGSkkp0dGyh6w0Y1JvNvxacC6F6jQAcHe05+c+5ZzKOR/3v65/p2WEwPTsM5vfdBxkwRDf5buOgBqSmpBITXXhDZp8BPdixZe9j5f1vopVM/58pkmTZ+AzFkiT9DUyRZbnArCCSJN2XZbnYme4OeQwqkIFz58ZUWzBc96jHDX9y75MtVJ05hNTzt4jfdxozS3NqrZqCXX1/cpLSuDzuYzLDYqjyRn8qT30B1e28ux3nhyxAk5FF423zkcwVSGZmJB4J5eY73xtMmqQtZByLS+fGVF/wGpLCjIgNfxL2yVb8Zw4m9fwt4vadwczSnDqrJmNb3x91UhoXx32iH47Q6tQqlHbWSBZK1MnphAxZiCZVxXMha0i//gBt7lwSD77ZS+RPRT9+qyLj6BS9qcB7T1vU1mM4ta6DubMd2bHJ3Fr+C2ZK3fj9B//7Aws3B1r8vhilnRWyVkaTnsnfbaejSVPh0bcV/lP7gZmEnKPh6uxvSD5zo0AebU59ZrCfzg75AHWqinYhq0m7Ho6cnYONnw3qsBA094035hy5HMby7cfQamX6Nq/FmK5N+WLPSer4udGhnj8Aq/eeIlutMdqYsP3kVS7fjy360Zcq45NkFYjpWjjLd51CK8v0bVKNMR3r88UfIdTxcaFDbd0huvrAeV1M3Uv32CSpcs2i8w65xrKfdI++7NeuKWP6duDzzX9Q19+HDk1qcys8hvlfbyMjMxtJgv97sTut61dn59FzfPPbEcwVZkiSxLh+HelUxKMvk8K9TaKMAKT/vI2UX43/+Nq0a4bb7HFgZkbKlt9JWLsRlynDyLx4g/Q/T2BZrwben81DYW+HnJ2NOi6RsN66p+pYt26M28yxIEHmpZtEv/sp5BTeDb7+neIbHT/9ZCHdunUgI0PFmLHTOXv2AgAn/9lL8xbBAIwZ/QqTJ48kJ0fNvXsPGD1mGgkJSVy+dAQLSwsS4nWT8p48eZbJU+YU/G72FH/H5UjobZb/chCtVkvf1vUZ07MVX+w4Sp0qnnRoqLtwWb3zGNlqNa+/kPf4VI1Wy6IN+zl74wESEq3rVuXNQZ2MZUPqwh+KjMOieQtsJ01BMjNDtWc3Get/xGb4SHKuXSX7+N84LluBMiAATbyuN4o2JobkebrPbObhidPKVcS/OEj3vNYiaCcvMonyalvLC40qBTmr+J5whZnx7hJOnbtAUlIKLs6OTBw1jAG9u5dpW1bexY+hX/npB3Tv1oEMlYrRo6dxJre8nj71O0HNugEwdswwpkwZRU5ODvfuhTNy1BskJCTy3bcradiwDrIsExb2gAkTZxVorABI3fd+kTE8rbIaPumXYveHdbtmuL41HsnMjJStv5O4dgPOk18l89J1MnLrEq+V72CWry6532csAFatmuA6cwxIElmXbhDznvG6xOfzQSaxT5KTapvEcWPjZ436zjk094zPdXXkyj2W5z76sm/zmozp3Jgv9p2mjq8bHepW0e2T38/ofnd75vUo3HXmBu9u+ouAfE+umD+kA7V8jDfCWPUp+BjQ/yon24INXYVZ/tF7dO7SDpVKxaTxswg5p7tpefjvHQZPfzgXepDBA0Zz47phY9SsOVOpZGnJ++8uf6x4n0Yc9pbWpY5rwbI5tO/0nO7Rl1PmERqiGxm/+9Amg6dQHDmzm+EvTuTWjbsl2m5Y/AUTvdwtHzs9Xyr7I8Kekt5RG0zuOyiusaEmEC/LcoEmL0mSPGRZLnYa6MIaGypCYY0Ngmk0Nuz3GFLRIQDQ5pvynbzxsZSiseFJKq6x4Wk50vvXig5Br4pz+YzlfVwlaWx4GkrS2PC0FNfY8LScv1g+k7A+rg6XSv+o0ielJI0NT0NxjQ1PS0kaG56W4hobnpajL+6v6BAAaPNls+ITPUWisSFPSRsb/kvK0tjwpIjGhopnio0NRc7ZIMuy0X6IJWloEARBEARBEARBEAThv6fMD+CWJGmdLMtjyzMYQRAEQRAEQRAEQTAlopd82RT3NApj865LQM/yD0cQBEEQBEEQBEEQhGddcT0bYoEwMGjKkXNfl/4hxoIgCIIgCIIgCIIg/OsV19hwG+gsy3KBZyZJknT/yYQkCIIgCIIgCIIgCKbB5GeHNFFmxSz/BHAysmxZOcciCIIgCIIgCIIgCMK/QJGNDbIsfy7L8nlJkgZJkmQHIEnSPEmStgDHnkqEgiAIgiAIgiAIgiA8U4rr2fDQPFmWUyVJagN0Br4GVj+5sARBEARBEARBEASh4mmfgX+mqKSNDZrc/58H1smyvAuweDIhCYIgCIIgCIIgCILwLCtpY0O4JElrgSHAbkmSLEuxriAIgiAIgiAIgiAI/yHFPY3iocFAMPChLMtJkiR5ATOeXFiCIAiCIAiCIAiCUPG0klTRITyTStTYIMtyBrAl3+tIILIk66ZKJW3PeLIqyaYxkkWDKKimKmDouooOQc9aWamiQwAgPC2uokMAYKdDq4oOQe+PNNeKDgGA5D9N44FA7l3erugQ9Oa6tq7oEABoTE5FhwCAlXfbig5BTxVxpKJDAMClSpeKDgGALxxMo6wCTO2ztKJDAOBn6yYVHQIANYd/X9EhGLiX8GZFh2BSIjb/X0WHoCOZSAfv+OiKjkAQimQiR4ogCIIgCIIgCELhTKahQRCEEjONbgeCIAiCIAiCIAiCYILkig7gGSV6NgiCIAiCIAiCIAiCUK5EY4MgCIIgCIIgCIIgCOVKDKMQBEEQBEEQBEEQBCNM41EDzx7Rs0EQBEEQBEEQBEEQhHIlGhsEQRAEQRAEQRAEQShXorFBEARBEARBEARBEIRyJeZsEARBEARBEARBEAQjtFJFR/BsEj0bBEEQBEEQBEEQBEEoV6KxQRAEQRAEQRAEQRCEclVhwyjqLnwNj86N0KiyCXl9NcmhdwukcWjgT6NPx6OoZEH0gRAuzf0egJozB+EZHISs1ZIdl8K519eQFZ2IT//nqDa5D0igTsskdNbXpFy+V2C7NT8YjmvnxmhUWVyauprU0DsF0tg18KfuyokoKlkQd+Ac197+DgClow0N1v0fVn5uqO7HcmHMJ6iT07Gu5k3dTydgX9+fm4s3Erb6N/222pz6DHV6Jmi0aNUajnd/u0B+tT94DdfOjdGqsgidupqUQvaHfQN/6q+cgFluTFfe1u0Pj94tqPbmQGxr+HA8eC4p528DYO5kS6Ov38ChUSDhG//iypxvi/1eTI19o0Ca7VpA6LhPifntnxKvZ+z7sPR2od6qSVi4OoAs8+DHA9z/ck+pYlqwdA6du7ZDpVLxfxPnEHr+isFyG1trtu35Uf/a29uDzZt28s7sJYyb9BovDxuIWqMmPi6RaZPn8uB+RKnyf+idRTPo0KUNKlUmM6e8y6ULVwukMTdX8t7St2jxXFO0Wi0rPvicfb8dxMvHkw8/fx87ezsUCgXLF6zk0B/HyhTHihXvExzckYwMFWPGTCck5GKBNIMH92HmzMnIskxkZDQjRrxOfHwiixbN4fnnu5CdncPt22GMHfsmyckppcrfFMtIm/eHUaVTI9SqLA5MW0fcxbsF0rSYOYiaA9pg6WDDl7VGGywL7NWCZm/0B1km7so9/pjyRanyBzh24QZL1+9Fq9XyQrsmjOrV1mB5ZHwSc7/cRmpGJlqtltcHdaFtwxokpWUwfdUmLt0Jp0+bRswZ9nyp8y7MsuXv0K17BzJUmUwYN4PzIZcMltva2rB3/8/61z7envz883bemrkAPz9vPl+zDFdXZxITkhgzahoREVFliqPze8MI6NiIHFUWe95cR/Qj342ykgV9V0/FsbI7slbLzT/OcXipLi7f5jXp/O4w3Gr5sWPKKq7vPlXq/E2xvH780Xx6BHciQ6Vi1MIx8GMAACAASURBVKg3OFfIMTxkSF/emjVFdwxHRPPq8CnExyfyzrxpjBr5MrFxCQDMm7eEPXsPlir/4sxd9BGHj53E2cmRbT+uKddtF6aiy2rQgmH45NYfx99YR0Ih5wPO9avS6pNxKCtZEH4whNPzfgDAsU5lWiwZgdKmEukPYjk2aTU5aSokpYKWH47GuX5VzJRm3P7lKJdW7SxxTIuXzaNrt/aoVComjZ/FhfOXC+yTXfs26F97+3jwy8YdzHnrAz5YPIc27VoCYGVdCTdXF/z9mpZqn5jicZPf+4vfomPXtqhUmUyfNJeLFwqeF/y663v9ay9vD7b+8hvvz1lW5jyFwh27HMayLYfRamVeaFWHkV2DDJYv33KEUzceAJCZrSYhLYOjS8cB0OT1VVTzdgHAy8mOT8f2eow47rJs81+5cdRlZLdmhnFs/qtgHMsmABCZkML7Gw4QnZiKJEl8Nr4vPi72ZYvjRiTL9p7VxdEkgJFt6xRIs+/iPdYeuggS1PBwZMnA1py6E83yvef0ae7GpbBkYGs61fYtUxz/BlrEOIqyqJDGBvfOjbAN8ORgqzdwbFKN+ktHcbTnvALp6i8dyfnpX5J09iYt1s/CvVNDYg6e59YXv3Ft2S8A+I/qTo1p/Qmd9TUZ92L4+4X55CSn496pIQ0+HFNgu66dG2Ht78mxlq/j0LQ6tZeN4mSPuQXyrr1sNFemryP5zA0ar38Ll06NiD8Ygv+UfiQcucjdz7ZTdUpfqk7py82F68lJSuPa29/h1iOowLYAzvSfT05CKppCCqouJi+OtPw/HJpWo86y0ZwoJKY6y0Zxcfo6ks/cpOn6t3Dt1Ii4gyGkXb1PyMiPqLt8jEF6bVYON5Zswq6WH7a1/Ix/IabKTKL6vJdJOHSh1Ksa+z5ktYbr7/5AaugdFDaVaLF/MQl/XSD9eniJttupazsCAqrQukkwTYIasGTFuzzf5UWDNOlpGXRt21//et+hX9i9cz8AoReuENxxECpVJq+OHMLc96czfuT0Un++Dl2eo2pAZTo170ujpvWZv3w2A7q/ViDdxGmjiY9NoEuLF5AkCUcnBwAmTx/Nru37Wf/tr1Sr4c/XGz+jfZPS/6h2796RatWqUrduO5o3b8zKlR/Qrl1fgzQKhYIPP3yPxo07Ex+fyAcfzGHChOEsXPgxBw8eYd68pWg0GhYunM2MGZOYO3dxyQMwwTJSuWNDHPw9+antdDwaB9J+0XA293mvQLq7+88S+t1+hh7+0OB9h6oeNJnUm6393ycrOQOrMpxgaLRaFv2wm7UzhuHhbM/L739Jh8Y1CfRx16f5csdhujevy+BOzbgVHsPkj35iz4oaWJgrmdS/IzcfxHAzPKbUeRemW/cOBFarSqMGnWjWrBEff7KATh36G6RJS0unTau8MvjX0e3s2L4XgIWL5rBx/RbW/7SFdu1b8d78GYwdXfrjJqBjQ5z8Pfmy/XS8GgfSdeFwfuz3XoF0p9bt4t7xK5iZKxiyfg7+HRpw59AFUiLi2T19Lc3G9ix13oBJltcewZ2oXs2fWnXa0KJ5Ez5ftZjWbXobpFEoFHy8Yj71G3YgPj6RJYvfZtLEEcxf8BEAn678ko8+Xlvqz1RS/Xp25eUBfZiz4MPiEz+mii6r3p0aYufvyfbnpuPaJJDmi4ezt9d7BdI1XzKCf2Z8RdzZW3T8cQbeHRsQ8ecFWn04mjPz1xNz4iqBL7ajzoTnOb/8V6r0bo7CUsmuzrNRWFnQ+9BS7m47TvqDuGJj6tKtPYGBVQhq1IWgZo1Y8fF8unYaWGCftH+uj/71wcNb2bnzdwDenr1I//6YccNo0LDgxU6RTPC4ya9jl7ZUDaxCu6DnaRzUgA9WzKVv16EGadLTMujRfpD+9a6DP7Nn54FS5yUUTaPVsviXQ6yZ1A8PR1uGfvgz7esFEOjlrE8zo39ew/uGv85z9UGs/rWluZJNs14qxzhe0MWxfCPt6wcQ6OWSF8eA9vniCDGIY+4PvzO6ezNa1apCRlY2klS2i1yNVsvi3adZM6wjHvZWDP1yP+1r+hDo7qBPExafyjdHL/PdqC7YW1mQkJYJQDN/DzZNCAYgOSOL3it30SrQs0xxCP9tFTKMwrN7U+5vOgJA0tmbmNtbY+nuaJDG0t0Rc1srks7eBOD+piN4But+LNRpKn06hXUlQAYg8fQNcpLTdX+fuUmlfJXLQ27BzYj85TAAyWduoLS3weKRvC3cHVHaWpF85gYAkb8cxr1Hs9z1g4j4+S8AIn7+S/9+TlwKKSG3kHM0pd4fHsFBROhjMr4/dDHp9kfEL4fxyP3xTL8RQfqtyALb1WRkkXTyGtqsnFLHZAoqj+5B9G//kB2XbPB+lYm9ab53ES3/XEbAjEGFrmvs+8iOSdL3ZNGkZ5J+IxxLz4LlxJjgnp34ZeN2AM6evoC9gx3uHq5G0wcEVsHF1ZkTf58B4O8jJ1GpMvXre3l7lDjv/Lr06MDWTbo7NCFnQrF3sMOtkDgGvdyH1Z9+A4AsyyQmJOn/trW1AcDO3o6YqNgC65ZE797d+OmnzQCcPHkOR0d7PD3dDdJIkoQkSdjYWANgb29LZGQ0AH/8cQSNRpO7/ll8fUv3Q2aKZcS/W1OubT4KQPS5W1jY22D9yPH8cFlGTFKB9+u83JGL3/9BVnIGAKr40vX0ALh4Oxw/D2d83Z0xVyoJblGPQ+euGSaSJNJUWQCkqbJwc7IDwNrSgiY1qmBpXn5t0T2f78KG9VsBOHUqBAcHezw83Yymr1bNHzc3F/4+pus5UKtWNf46dByAw38dp+fzXcoUR7WuTbmU+91EnrtFJXsbbB75btSZ2dw7rrsrqc3REH3xLna533/Kgzhir95H1splyt8Uy2vv3t354adfAfjn5FkcHB2KPYbt7OyIiIgucR6PK6hRfRzs7Z5KXhVdVv26N+XOr7oyGnf2FhYONlg9Ukat3B0xt7Mi7uwtAO78ehS/3PMjuwBPYk7oerlFHr6I3/O5d1NlUFpbIinMUFSyQJutJiffuVRRej7fhY0btgFw+lQI9o52eHgY3yeB1ari5ubC8WMFe/4MGNSLzb/8VshaxpnicZNft54d2bxxBwDnTl/A3r7o8wL/wCq4uDlz8viZMuUnGHcxLBo/N0d8XR0wVyro3qQGh0JvG02/58x1gpvWeDJxuDrkxdG05HHcioxHo9XSqlYVQPebbGVhXrY4whPwc7bD19lWF0e9yhy6ZtigtuXMLYY0q469lQUAzraVCmxn/+X7PFfdCysL8VwBofQqpLGhkpczmRHx+teqyIQCDQOVvJxRRSboX2dGxhukqfXWYLqcWYXPgOf0vRzy83u5AzEHQwq8b+nlRGZ4Xt6PblcfX/68IxKw9HICwMLNgezcC4TsmCQs3BwoiSY/v02L3xfjO6xzITE5ozKIKQHLR2KyLDSmsv0wPgssPZ1w79GMB9/tN3jfuX0DrAM8ORk8hxOdZmHf0B/HlrXLlEclPzfs6vmTnNugVRKeXu5EhOd1iY2MiMbLy3iDQd8BPdmxdW+hy156pT9//nGk5AHn4+HlTkR43sl+VEQMnl6GJ3929rYAvDF7ItsP/sRnXy/FxU1XZj5dtpZ+g3py9MIevt64kvdnl60rp7e3Jw8e5DV0hYdH4e1t2GCgVquZOvVtTp/+nTt3TlO7dnW+/XZjgW299toQ9u07VOK8TbWM2Hg6kZavfkuPTMDG06nE6zsEeOIY4MkLW96h//b38OvQoFQxA8QkpuDpnNcjwt3JnuhEw0aLCf06sOv4Bbq+sYJJH/3EW6+U8W59CRQoJxFReHsZb1gaMLAXWzbv0r++ePEqffp2B6B3n+7Y29vh7FywAac4dp5OpOT7blKjErDzMP7dWNpbU61LY8KOXTKapqRMtbz6eHsaDOUKfxCJTyHH8KQpswk5e4D7YWepU7s633yb12V+4oQRnD2zny/XrcDRsWS/iaaqosuqlacT6fnrj4gErB6pP6w8ncjIdz6QP03y9Qf4BuuGKFTp1QIbb12dH/bbSdQZWQwIWUX/U59wec1uspPSSxSTl7cH4eF5+yQiPKrIhvL+A3qxdcuuAu/7+nlTuYovh/86XqJ8wXSPm/w8vdyJzHdeEBURjaeXu9H0ffr3YKeR8wLh8cQkpePpaKt/7eFoS0xyWqFpIxJSiEhIoXmNvGEB2Wo1Ly//mWErNnHwwq3HiCMNT6e8BlIPR1tikoqIIz6Z5jV0PZDDYpKws7Jk2pe/MWTpej7adgSNVlu2OFJUeNpb58Vhb0VMimEjY1h8KmHxqbz29R8M+3I/x24UvHm57+I9etSrXKYY/k3kZ+CfKSqysUGSpPqSJJ2QJOm+JEnrJElyyrfs5JMPz7irSzbxR9PJhG8+RtWR3Q2WuTxXh8ovdeTKwg1G1i5HcvFf7ane7/BP17c4+/JiKo/ohlPLWk8+rmdczQXDubFwfYH969KhAS7tG9DywFJa/rEEm2o+WAeUvluXwtqShl9P4/q879GU8O5OWfTr35NtvxY86RowuDcNG9fji5XfPLG8lUolXj6enD15nr6dhnLu9AVmv/8GAL37d2fzxp20adCDUS9O5cMvFpS5m15J4hg7dhgtW/bE3z+I0NArzJw5ySDNrFmTUavVbNiwtcTb/beUkUeZKRQ4+HuyffAH7J/8OR2XjsIi38lCedlzIpQ+zzVi/8fT+XzaUN5etwVtGU9oytuAgb34dVPeePK3Zy/iuTYtOPL3Ttq0bU54eKS+R8yTIinM6P3ZJM58u4/k+2Xr+ZPfs1xelUol48e+SlDz7vhVacKF0Cu8NWsKAGvW/o8atVrTNKgbUVExLF/2TrnmbepMoazmd3zal9R4rQs99i5AaVsJbbYaANfGAcgaLZsbT2Fri2nUGd8T28rGeyc8jv4Dny+090L/gb3YsW1vqeqZZ/m4MaZP/2B2bC77/BBC+dh35gZdGlVDYZZ3KbT7veGsnzGExa91Z/mWI9yPTS5iC+UVx3W6NKquj0Oj1XLuVgTTXmjLT2++SHhcMjv+uVzMVspOo5W5l5DKV8M7sWRgK+bvPEmKKlu/PDZVxc2YZFpV83piMQj/bsX1h1kNvAecAEYDRyVJ6iPL8i3AaJ8eSZLGAmMBJtoFEWxdjaojulJ5aCcAkkJuU8k7b9yS1SN37UF3d98q3537Sl4uBdIAhG85SvOfZnF9ua4bqF3tyjRcMZZ/Xl5CTqKuFbHqiK5Uzc07OeQWlXxcitxu5iM9LSp5O5MVmQhAdmwyFu6Oul4N7o5kxxXfxTkrSrduTlwKMbtP4dC4Gna1K+P7Sl5MVj4uPOxQXcnLmaxHYsoqNKaC++NZ5juiG76v6Hp+KO2tqb9mKgDmLva4dmmMrNEgSRJ3Vm4n/Ic/jK577uUlZEUnGs1HUipo8M10IjcfJWZ38W1mw0e/xNDXdF00z58Nxdsn74TGy9tDPyTgUXXq1UShVBSYSKtt+1a8Pn0sLzz/GtnZJR/i8srIwQwZ9gIAoSGX8Pbx4GEnTE9vd6IiDS+IEhOSyEhXse833WRte7b/waCh/QAYNLQfIwdPBnTdPi0tLXB2cSQ+zvh+e2jcuFcZOVI3pvHMmQv4+ub9APn4eBaYDK1h7vjc27fDANi8+TfefHOifvmwYQPp0aMzPXoUP07SVMtIvde6UOeljgDEnL+Nbb76zcbLmfSo4vfrQ+mRCUSH3EKr1pB6P5ak21E4+nsSc954F8xHuTvZE5WQVzfFJKbg4WQ498PWw+dYPf0VABpW8yMrR01iWgYu9raUhzFjh/HaiCEAnH20nHh7EhFZ+KR59erXQqlUGkw0GhUVwysv6ybOsrGxpk/fYJKTU0sUR+NXu9DgRd13E3XhNvbeLjzsRGrn6UyqkXLQfckoEu9EceabfSXKpzCmWl4njH+NUaN0Y8pPnw7B189bv8zH14vwR47hRg3rAnnH8K+/7mTmDF2DYUxM3pj/r77+ie3bvudZU9FltcbwLlQbqiuj8SG3sfF24WFtbuPtjOqR+kMVlYh1vvOB/GlSbkZy8KWlgG5IhU/nRgBUfaE1EX9eQFZryIpPIebUdZwbBpB2r/CGtFFjhvLqcN0+OXf2Aj4+efvE28eTSCPDaOrWq4VCqSgwqSZA/wHPM3P6e0XuCzDd4ya/V0e9yEuvDgDgwrmLeOU7L/D09iAqsvD5bmrXrYFCoSD0/JO7ePwvc3e0ISpfD4LopDTcHQr/Tdt79jqzB3UweM8jt1eEr6sDQdV8uPogFr8S9mA2jMOWqMS84z46KQ13x5LF4eFoS01fN3xddfl2bBDIhbtRvNCq1GHgbm9FVEpGXhwpKtztrQzSeNhbUc/XBXOFGT5Otvw/e/cdFcX1sHH8Oyy992qj2AuIIBasoKLR2DUxMRpjj8beNfnF2KIppmmi0XRrNEVj74oaC2LvKEjvve/O+8eShRVQRA345n7O8SS7c2fmYfbO7OydO3dq25gRkZxBk6LfSvuuRtCpgQt6CvEAQ6FyHtfYYCbL8j99vT6SJOk8sEeSpKE8oreGLMtrgDUAOxxflQHuf7ef+9+pu8HZBzbHdURXon8/iaW3BwUZ2eQ9dO9yXnwqBZk5WHp7kBpyh5qD2nFvnfqkz8TVkax76i9/hyAfMu+ou4Aaudjgu34KFyZ8RVZY8cnB/e/2E1t0wmgb2JyaI7oR+9tJLFrUpTAjW3NbxD/y41MpzMzBokVd0s7fxmlgex6sU2+GhL3ncB7cgftf/IHz4A4k7Dn3yA2oY2yAJEkos3LRMTbApmMz7n68jcTDF4n4Tj14kl1gc2qN6EbMbyexaFH+9lBn8iDt/B2cB7YnfN3/r254kd/tI7Jom5TU+LNxJOwPIWH3OZTZ+XjMHkTstuMos/MwcLRCVagsd96yNPp0LFm3o4j4pnSPg7J8/+1Gvv9W3UsmoGt7Rox6jd+37cLbpxkZ6RnEx5U9wFaf/j34fdsurfeaNGvI8pXvMaT/GJISn6yx6Of1W/h5/RYAOnbx5423BrNj+168WjQlIz2ThDJyHNp3jFb+Ppw6fpY27Vty56b6B2tMZCxt2rdk26YduNd1xcDQoEINDQDffPMj33zzIwBBQZ0ZN24YW7b8ScuWzUlLyyA2VvskKzo6jgYN6mJra01iYjIBAe24cUPdXbVLlw5MnTqOLl0GasayeJTqWkeu/HCAKz+oT3prd/aiyfAu3PnjFA7N3cnPyC5zbIbyhO07T92XW3NjyzEMrUyxdHMkLfzJBmps7OpMRFwSkQkpOFiZsefvKywd21+rjJONBX9fC6N3u+aERSeQX1CItZnJE63nUdau+Ym1a9Qj5Hfr1onRY4fy69Yd+Pp6kZ6eQVw544QMGPgyv27VHiXf2saKlORUZFlm6vRx/Pxj6VvnynPhxwNc+FH92bh19sJ7WBeu/3kKp+bu5GVkk1XGZ+M/fQAGZkbsmflthddTlupaX1d//QOrv1Y3CvToHsD4ccPZvPkP/Fp6k56WXmofjoqOpWHD4n04MLC9Zh92dLTXlO/TuztXrz40NsgLoKrr6q3vD3Dre3UddQnwot6bXbj/+ylsvd3JT88m56E6mhOfSkFGDrbe7iSG3MV1gD8316vrioGNOXlJ6SBJNJ3Um9s/qQchzIpKwtG/Mfe2BaMwMsDW24Mba8s/h1i39hfWrf0FgC7dOjJq9Ots/3UnPr5epKdlEBdX9jbpP7An28vo1VC3nhuWluac+ftCGXNpq677TUk/rtvEj+vUtwN27tKOYaOG8Of23TT3aUZGema55wW9+/fgz+2iV8Pz0riWAxEJqUQlpWFvYcrekFssGdatVLl7ccmk5+Th6VrcSJSenYuhnh76egpSMnMIvRfD8IAne2pKqRyJadhbmrL3/C2WDA8qnSM2mfTsXDxdixvzGtd2ICM7j+SMbKzNjDlz6wGNalVufK/GztZEJGUQlZKJvZkRe69EsKS/dqtFpwY12H0lnD7N3UjJyiM8KYMaVsUNI3suR/BO4JPfzvn/kUo8jKJSHjvShyRJFrIspwHIsnxYkqT+wDag0gMGxB+4gH2AF51Pr0SZk0fo5OJRrNsfWMqxwDkAXJ79nebRl/GHQok/qB6DoeG8VzDxcAaVTHZkApdnrgOg7tR+6FmZ0nTZCABkpYrjDz1mMvHABWwDmtP2789Q5uRzbdJqzbRWBz/kdMAsAG7MWkfjz8ejY6hH4sFQEovWff+LP2i6djIuQzqRE5nIpVGfAuqxHPz2LUXXzAhZJVNrdA9OtpuGvo0Znt9NV29LhQ7RvwWTePiiVqaEAxewDfCi/d+foczJ4/Kk4kd7tTm4jJMBswG4Nms9TT8fh8JQn4QSmey7+9JoyXD0bcxp8ctMMq6Ec+4V9Yj+Hc5+gcLMCB19XRy6+3B28JJKjbZcXSQfvURMPRd8dy0C1AM7XRn/JQUP9TAp7/Mwa1QL50HtybgWTquD6qs/d5Zs1GzLxzm47xgBXdpz6sIecrJzmfJ2cf3af3y71lMoXu4bxOsDx2rNv2DhdExMjFnzg7reREVGM/zVCU+8HY7sP0HHQH8Onf2D3JxcZr3zP820HYc30quTupfAh+9/zserP2D+oukkJ6Uwc6K63JJ3P2HJpwt4c+xryLLMzAnvPXEGgD17DhEU1Ilr146TnZ3D6NHTNdP+/ns3fn7diYmJY/HilRw4sJWCgkIiIqIYNWoqACtXfoCBgT5//aU+qT1z5gITJ86tVJZ/VHUdCT8USq3Onrx24mMKc/I5NG2NZtqgPYvZEqSuM63nvkLdPm3QNdLnjTOfc33jEc5+up0HRy5Rs31TXjn4IbJKxcnFG8kr517P8ugqFMx5vQfjPvoJlUqmT7vmeLjY89X2QzR2daZj8wZMe6UrC7/bwc/7TiMBC0f20dxK033ap2Tm5lFQqORwyA2+nj5U60kWT2rv3sN07daRi5cPk52Ty/gxMzXTTpzaqTWyf99+PRjQb4TW/O3ateJ/789AlmWCg88wbUrl6mvYoVDcOnky6pj6s9k9vfizGbZrMT/0mIepozVtJvYh6U4Uw/5S16ELP+7n0qYjODZzo++ayRhYqMdy8J/Sn/VdZlcqyz+qur7u2n2QoKDO3LweTHZODiNHTtVMO3d2Hz6+XYmJieODRZ9y+NB2CgoKiIiIYsRb6luyli2dj6dnI2RZJjw8knHjZz3V9ijLjPeWcfbCJVJT0wno8zrj3xpK/16lf0A8C1VdV6MOhuIc4Envk+o6empKcR3tsX8xu7qojx9n5nxPm5WjURjqE334ItGH1OcVdfq0pv5w9aCUEbvPcXeTevDpW9/tp/Wno+l5eBlIEmGbj5F6/UGFMu3fe4QuXTtw/uJBcnJymDCuuM4fDf5T6ykUffr2YPCAkaWW0a//S1pjWzytqt5vSjq0/zidurTn+Pld5OTkMn1C8dPEdh/dqvUUip59ujFs8PiyFiM8A7oKHWYP6MC4VX+iUqno3aoRHk42rPrrNI1q2dOxqRsAe87fJsi7rtbto2GxKSzafBgdCVQyjAhsofUUiyfOMbAj41b9jkqWS+Q4RaNaDsU5Qm4R5F1PK4dCR4cpff0Z8+V2ZBka1rSnf5smlc/RowXjfjqKSlbRu7kbHvYWrDp0mUbO1nRs4EIbD0dO3Y2l35e70NGRmNLFC0tjAwCiUjKJTc+mRe3Kf/8LgiQ/YswBSZKGAGGyLJ9+6P1awAJZlkeVPWexf3o2VDVDuXrci1zWoy+rUlBc6YH6/m37HQZXdQQA3si7XNURNIx1S48GXBWiMh//WLR/ww6LSvQffE5uV3JU6GdtxJaXqjoCAPaB8x5f6F8y37ZNVUcAoHlu9XgCUPeUE1UdQSMnunKD4T5rNrUr9ySTZ22VRfWoqwDvZPxd1REA2GzsXdURAHiroHrd4hCRXH3OTapazt4vqzpCMama3FaQ9O89GehxjF59v3r9yHnGfnR5vVr8pn2UN6J+rnafwSN7NsiyvKGc9yOAxzY0CIIgCIIgCIIgCMKLrHpctn7xVLpZTpKkNY8vJQiCIAiCIAiCIAjCf80jezZIklTezUoS8Pweyi4IgiAIgiAIgiAIwgvrcQNEJgDhoDXQgFz0WowWIgiCIAiCIAiCIAhCKY9rbAgDAorGaNAiSVLFhjEWBEEQBEEQBEEQhBdUtR8dspp63JgNKwGrcqYtf8ZZBEEQBEEQBEEQBEH4f+CRjQ2yLH8ly/JFSZIGSpJkBiBJ0gJJkrYDwf9KQkEQBEEQBEEQBEEQXigVfRrFAlmWMyRJ8gcCgHXA6ucXSxAEQRAEQRAEQRCqnkqq/v+qo4o2NiiL/vsSsEaW5b8A/ecTSRAEQRAEQRAEQRCEF1lFGxuiJEn6BhgM7JIkyeAJ5hUEQRAEQRAEQRAE4T/kcU+j+McgIAj4SJblVEmSnIAZzy+WIAiCIAiCIAiCIFQ9VVUHeEFVqLFBluVsYHuJ1zFATEXmtaagcsmesWwUVR0BAH1RVautsK/6V3UEDTk9taojACDVqVvVEQA4Mbz6jEcbaJpY1REAcO76blVHACD+4NKqjqCxv8/vVR2hWsnY+35VR9CwqR1Y1REASAo/UNURAFjvVT32X4CoH96s6ggAnBh3saojAHBzRbeqjiCUo/Fr66o6goYsV4/zeWdDm6qOoBH8alUnEKojcSuEIAiCIAiCIAiCIAjPVEVvoxAEQRAEQRAEQRCE/5zq0ZflxSN6NgiCIAiCIAiCIAiC8EyJxgZBEARBEARBEARBEJ4pcRuFIAiCIAiCIAiCIJRDlqo6wYtJ9GwQBEEQBEEQBEEQBOGZEo0NgiAIgiAIgiAIgiA8U6KxQRAEQRAEQRAEQRCEZ0qM2SAIgiAIgiAIgiAI5RCPvqwc0bNBEARBEARBEARBEIRnqkp6Nlh2FYMoIAAAIABJREFU8sLtgzdBoUPcLweJ+vJ3remSvi71vpiISTM3ClMyuTnmE/IeJGim67vY4n3sUyI+2kr06j+LZ9TRwXPvh+THJnN96NIy123TyZP6i4YjKXSI+uUQ97/4o9S6m3z5NubN3ChIyeDS6M/ILVp3nXf64DKkE7JSxc1535N05CIGzjY0+fJt9G0tQJaJ/PkgD9buBsB91iDsgnxAJZOfmMbVd1ZTGJdcKpN1J0/qLnoTSaFDzC8HCS8jU6MvJ2BWlOnq6JXkPkhA18qUpuumYublQeymI9yau14zj0PfttSe1BdkmbzYFK69/QUFyRkV+HT+fcYezjT+bBzmTV25s3QT4at3llnOyr8x9d4bio6+LukXw7g25WtkZcXbGe17tcJ9+gBM6rlwJmge6RfDANCzMqXZuqkYtvRAGXaBgnN/lbuM4DsxLN8bikol07e5KyP8G5Yqs/fqA745ehUkqOdgybJ+rQCIScvi/R3niEvPRkLiiyHtcLE0qXD+cjPdT2TF0RuoVDJ9mtRghK9rqTL7bsXy9em7SEA9OzOWdm/21OsFCL4ezvLtJ1DJKvq2asSIwBZa01f8doKztyMByC0oJDkjhxPLRgHgPWUVHk7WADhZmfHZqJfKXU91qSPmXu5k/r6P+EWrys/q3wL7ueNAR4e0X/eQ8u0WrelGPk2wmzMWg3quxExbSua+E5ppuk52OHwwGV1HO5Blosa8S2F0XIXzP2zp8gV06dqBnJwc3h47i0sXr2lNNzU14a+9GzWvnV0c2LrpT+bOXgxAn77dmTX3HWRZ5srlG4x+a2qlcgRfus2Hv+xS7zcdvHmrZ3ut6TFJqcxfs52M7FxUKplJg7rQzrMel+9G8sH36mO8LMuM7dOJAJ9GT7z+xouG4RDghTInn9BJq0m7fL9UGYtmrnh9NhaFoT5xB0O5Ov8HAOrPHIhjkA+ySkV+YjoXJn1NXlwKNm0a4vv9dLIj4tV/w66z3P5kO1B96quhXz2UsbcouH2q3GUEX73H8i0H1Z9N22aMCPLTmr5iyyHO3ooAIDe/kOSMbE58+g4An247wvErYciyTKuGdZg5qDOSVPnhupeveJeu3TqSnZPLuDEzuBh6VWu6qakJe/Zv1rx2cXZk8+Y/mD3zA2rWdOarr5dja2tNSnIqo96aSnR0bKWzlGf+kk84FnwGaytLfv/562e+/Ie1WTiUWp29KMzJ48iUNSReuV+qjO/MgdQb4I+BhQnr64/UvF9vYDtazX+VrNgUAK5+v58bG488VZ7gm1Es33lGXV986zKiY1Ot6St2nuFsmHq75+YrSc7K4cR7Qyq07Gqz37T0QHn7HAWnfit3GcFh8Sw/eAWVLNO3WS1GtKpbqszeG9F8E3wTgHr2Fizr5U10WjZTfzuLCihUqnjV25WBzetUOLtQMe8umUnHwLbk5uQyY+J7XL10o1QZPT1d/vfhbFq19UGlUvHx4q/Ys/MgzjWcWP75e1jbWJGams7UsfOIjYmvVI73ls6iY6A/uTm5TJ+woNwc7384h1ZtfVHJKj5a/AV7dhzEpYYTH37xPjY2VqSmpDFl3FxioyuXY/LCCbTu7EduTi6Lpyzn1pXbpcp8sfUTbB1syMvNU8/z6kxSk1IB6NyrAyOmDgMZbl+7y/sTFlcqh/Df9O83Nujo4LZ0JFcHLSQ/JhnPPctI3neOnFuRmiIOQwIoTM0ipPVEbHu3pc7817k55lPNdNf3h5FyKLTUop1H9SDndiQKM+Ny1i3RYNkIQgYtJjc6Cb+9S0nYe46sW1GaIi5DOlOYmkVwq0k49GlD3QVDuDz6M0zqueDYpw0n20/DwNGKFlvnE9x6MnKhklvv/UTG5XsoTAzx27+U5KOXyLoVxf2vdnD3Q/UPjZojg3Cb1p9bM9eWylR/2VtcGLSIvOgkfIoyZZfI5FyU6XSrd7Dv0wb3Ba9xdfRKVHkFhC3bjEmDWpg2qKkpLyl0qLtoOH+3m0pBcgbuC16jxogg7n209Yk+qn9LQWomN+d9j113n/ILSRJNPh/P+QGLyA6LwX3mQJwGdyB6w+EKryfrxgMujviYhitGab2vzCvg7rLNeC7wQcfCvtz5lSoVS3eH8PXrHXAwN+K1bw/Qob4z7nYWmjLhSRmsD77O9292xtxIn+SsXM20+b+fYaR/Q1q7O5KdX/BUJ+XFmWSWHb7O6n4tcDA15LWNp+ngZoe7jWlxppQs1p+9x/eDWmJuqEdydt5Tr1e9bhVLfz3G1+NexsHSlNc+2UqHJq64O1pryszo66/5/43HLnEjsrjR0EBPwZaZr1RoXdWljpg2qImTl0P5C9DRwX7B20S9NZeCuERqb/mcrMOnyb8bUfy3RCcQO+djrEf0LzW747IZJH+zkeyTF5CMDUElVzj7wwK7dsDdvTY+XoH4+Hrx8acL6dJ5gFaZzMwsOrR9WfP60LHf2LFjHwBu7rWZPG0sQV0Gk5aajq2tNZWhVKlY8uNOvpk5DAdrc4b87xs6Nm+Au0vxvrb2j6N0a9mEQQEtuRsVz4RPfmb3x1PxqGHPhv+NQVehICE1g4HzV9GheX10FYoKr98+wAtTN0cOtZ6CpbcHTT98ixM9FpQq1/TDEVyctpbUkDv4bZiFfWdP4g9d5O6qndxcrj52ur7VjXpT+3F51joAkv++wZmhK0otq7rUV8+PuqJjYlXu/EqViqUb9/P1pEE4WJnx2tKf6NDMHXdnW02ZGYM6a/5/4+EQbjxQN36F3o0i9G4UWxcMB+DNFRs4d+sBvvVrVTh/SV27dcTdow5ezTrj6+vFpys/oHPHflplMjOz8G/dU/P66Ik/+POPPQAsWjKXTRu2s+GX7bTv0Jr/LZzB6JHTKpXlUfr06MKQ/i8z94OPnvmyH1azsycWro5s8p+Gvbc7/kuH83uv/5UqF34ghKvf7+eV46Uz3d1xmuD5Pz6TPEqViqV/nubrt7riYG7Ma1/9RYeGNXF3sNSUmdGzpeb/N568zo3o0hdYylNt9pvZnuhYOZY7v1Ils/TAZb4e1AoHMyNe+/E4HTwccbc105QJT85k/enbfP9aW8wN9UnOUn/v2pka8uPr/ujrKsjOL6T/+iN08HDE3sywwvmFR+sY6E8dt1p0btkbrxZN+WDFXPp1e6NUubenjiQpIZkAvz5IkoSllfpcbu77U9i++S+2b95B63a+zFgwkWnjS39nVDRHJ99eePk0ZdFH8+nb9fUycowiKTGZzn4va+dYOJXtm3ewfdMOWrdrycwFk5g6bt4T52jd2Y8ari4M9h9KY++GTF86mdG93i6z7PsTFnPj0i2t92q4ujB0whDG9XmHjLRMLG0sy5z3v0DcRlE5//ptFGbNPci9F0teRDxyQSEJvwdj3c1Xq4x1N1/itxwBIHHnKSz8i1vOrYN8yYuIJ/vmA6159J2ssQpsQdwvB8tdt4W3B9n34sgJj0cuUBL7+0nsgrTXbRfkQ/SWowDE7ziNtX+Tovd9if39JHJ+IbkRCWTfi8PC24P8+FQyLt8DQJmVS9btKAyKfmwpM3M0y1UYGyLLpX84mHt7kH0vltyiTPFlZLIN8iGmaHsk7DiNVVEmVXYeaWduosrL116oJAESCmMDAHTNjMkro0dFdVGQmE566F3kAmW5ZfSsTVEVFJIdFgNA0tHLOLykvgKnY2xAo5VjablnMX4Hlql7k5Qh63YU2XdjSr2vys4j9cxNUBY+MueVqGRqWplSw8oUPYWCbo1rceRmtFaZ7SFhDPbxwNxIHwBrE/UJxN2ENJQqmdbu6hMYY309jPSevq3vSmwaNS2MqWFhjJ5Ch271HDlyV7vl+7crUQzyrIm5oZ46U1G9eOp1h8dT09aCGrYW6Okq6Na8LkeK9oWy7A65TVCLepVaV3WpI8q8gkfmNGxWn4KIGAoiY6GgkPRdRzHp3FqrTGF0HPm37iE/1JCg714LSaEg++QFAOTsXOTcyjcM9XgpkE0b1b3Gzp0NxdzSDAcHu3LLu3vUwc7OhlPBZwF4Y/hg1q39mbTUdAASEyt3DLkSFklNB2tq2Fujp6tLkF9TjoQ8dHVHksgs+lszc3Kxs1SftBsZ6GsaFvIKCqlM+5xjtxY82HIcgNSQO+iZG2Ngr32yZGBviZ6pEakhdwB4sOU4jkV1pPCh4zg8vgGoutRXVOWvH+DK/Rhq2ltRw85SvQ/7NuDIpTvllt999jpBPureXJIE+YVKCgqV5BcqKVSqsDGvfE+tHi8FsnGD+kry2bOhWFiY4+BYfn318HDFzs6Gk0X1tUEDD44eUffgOHb0FD1eCqx0lkfx8WqKhbnZ4ws+A3W6tuDWr+qeT/EhdzEwN8HYvvSJfnzIXbLjU597nisPEqlpY04NazN1ffF05cj1B+WW333xHkGepXvalafa7DfKRx/nr8SkUNPShBqWJurv3YbOHLmj3Ytm+6UIBjevg7nhP+cC6u9dPYUO+rrqY1q+UlXmeaHwdAK7d+C3LepeMaHnL2NuYYadg22pcgOG9Gb1Z+oewbIsk5Ks3oc86rtx6vgZAE4dP0tg946VytGleye2b96hznGu/BwDX+vDqpVl5XDn1LF/cpypdA7/bm3Y8+t+AK6GXMfMwhQb+4pfPHh5yEts//4PMtIyATS9HQShop64sUGSpMpd3iqi72RNfnSi5nV+TBIGTtalyuT9U0apojAjG11rM3SMDXGZ0IeIMq7Qu37wJvc/+OmRB24DR2vyopM0r/OikzBw1L7qY+hkTW6UuoxctG49azMMHK3IjSrOnReTpGlU0Mxb0w6zJq6khRSfrLnPGUy7kK9w6u/P3eXa3anLz6S9XAMna/JKZFIWZSqPXKjk5qy1tDzyEW0vfYNJPReifzlUbvkXQUFSBpJCgbmnGwAOvfwwcLEBwG1yX5KPX+FM0DzO91tI3XdfQ+cZ/aAuKT4jB0eL4l4zDuZGxGfkaJUJT84gPCmDYesPMnTdAYLvqE9owpMyMTPUY+qWYAav2ccn+y+iVD19G2l8Vi4OJa6IOJgZkpCl/QM1PCWLiJRshm8+wxub/ib4fuLDi6ncutMycbQq7kHhYGlKfFpWmWWjk9OJTk6nZV0XzXv5hUqGfLyFoZ/+yqFLYU+dpzrUEV17Gwpji3tvFMYloudgU6F59eq4oMzIxOnzBdTa9iW200eCTuXbg52cHYiKKj6hjo6Kxcm5/F4Z/fr35LftxbcQuXvUwd3Dld37N7Hv0FYCAttVKkd8SgaO1sW9f+ytzYlLSdcqM65vJ/46eZEukz/i7Y9/ZvbrxbfUXLr7gL5zvmDAvK+YP6zXE/VqgKJjeoljbE5MMoYPfecYOlmTE1PcmJIbk6RVpsHsQQSe/xKX/m01vRwArFrUpf3BZfhtmIVp/RpPlKs61Nf4lEwcrYq/SxwszYhPySyzbHRSGtGJabRsoO654Onmgm+9mgTOWk2Xmato3cgVN6eK1fWyODs7EhlZXF+jomNxdir/6nL/AT3Zvq24vl65coOXe3cDoNfL3TA3N8Pa+sW+AmfiaEVWibqbFZOMsWP5PVXK4tq9JQP2L6HLN+9g4vRUp2/Ep2fjaFHcoORgblz+MT8lk+iUTFq6l/8ZVka12G8yc3E0M9K8djAzJD4jV6tMeHIm4SlZDPvlBEN/Ok5wWPFFgNj0HAZ+d4Sg1fsZ7uchejU8Y45O9sREFTf+xEbH4eik3WvVzFx97jJ1ztv8eWgDX65bjq2dev+4cfUW3Xqqe3R1e6kzZmammt4GT8LByZ6YqOLbIGPKzGGmybHj0Ca+Wr9Ck+P6lZt06xmgztEzoNI57BxtiS9x+0V8TAJ2jqUbPQDmfjKT7/etYfjk4h4YNd1qUNOtBqt//5w1O77Er6NvmfMKQnkeeSYrSVJbSZKuS5J0VZIkP0mS9gNnJUl6IElS60fN+zzUmjGI6DU7UWVrH9SturSgIDGNrGfwg6WyFMYGeK6byq0FP2j1aLi7dDPHvd8mZtsJao4I+leySLoKXIZ35WzALIKbjSHzWgR1JvX9V9b9PF0e+xn1Fr5Byz2LKczMhaJ7NG06NMP1nT60OvghPr+9h46BPkYuZR9InzelSiYiOZNvh3ViWb9WLNx5jvTcfJQqFRciEpnaxZNfRgYSlZLJnxfv/zuZZJmI1GzWDvBhafemfHDgKhm5j75y86ztDblDoKc7ihI/nne9+wYbpg1i6dAurPjtBA8S0556PS9CHSmPpFBg1KIJicvXEjHoHfRqOmLet8u/tv5+A15i29bie6R1dXVxc69Nr+6vM/LNKaz8YjHmFs/niu7u05d42b85+1dO56tprzNvzTZURY1xzdxr8tvSiWz43xjW7TxOXv6/W3cBbizbwoEWE4jaFkydEeoftGmX7nPAZyLHAmZzb91efL978vEsXqT6uvfcDQK962n24Yj4FMJik9m3dCz7lo3j7M1wQm5HPmYpz07/AT35dcsOzet5c5bQ1t+P4yd34N+uJVFRMSiVj+7Z8f9d+P4LbGg9mV+7zCXy2BU6rRzzr61776V7BDaprXXMf1ZehP1GqZKJSMni21fasKxXCxbuvUh60feuo7kRW9/syJ+jAthxJZKkrGdza6NQcbq6uji7OBJy5iIvdx7ChXOXmPP+FACWvPcpfm1asOPQRlq2aUFMdNxzO5bo6iqKcoTSq/MrhJy9xNyF04pyfIJfWx92Ht6MnybH8+vI//7EJbwROJLxfSfh2bIZQQPU5x8KXQU1XGswYcAU3hu/iFkrpmH6FL3YXmTyC/CvOnpcP+5PgUGAKfAX0EeW5ROSJHkDXwBty5pJkqTRwGiAGWbN6W3sppmWH5OMfon7QfWdbMiL0e6emx+TjIGzLfkxyaDQQdfMmMLkDEyb18WmZyvqLBiKrrkJskqFKi8fA0drrLv6YhXgjY6BHgpTY+p++Q63J3yutdy82GQMnIuvvBg425BXNHDSP3JjkjF0UWeSitZdkJxBXmwKhiW+tAycbMiLVeeWdBU0Wz+NmG0niN91pswNGbvtOM03zCF8hXbvhrIzaW+PvJhkDEpkUhRlKo9pkzoA5ISrW1Tj/zxFrYm9yy1f1QwcrMiLS3lsubRztznX+38AWHdohrGbk3qCJHFxxMelukU2WjkO86Z1yItN4cJry546p72ZEbFp2ZrXcek52Je4ugHq3g5NXGzQU+jgYmVKbWszIpIycTA3pr6DJTWKegJ0auDCpcgk+jZ/ykwmhsSVuKISl5GLnYn2lRx7U0OaOlqoM1kYU9vKhIjUbBo7PnkLudZyLUyJLXEVNC41E3uLsr+A9ly4zZwB2oMCOliqt0UNWwt8PFy4EZlATdviTIpazdCt2RgAA4drL0QdKYxPUg/uWETXwZaCuKRHzFFi3rhE8m7cVd+CAWQePIWRZwPSt+2t8PrfGvUabwwfDMCFkEu4uDhppjm7OBJTzmCTjZs0QKGr0BqQLzoqlvPnLlJYWEhEeCR37tzD3b0OF0IuVzgPgL2VGbHJxQ1J8cnpOFiZa5X57WgIq6er76n19KhFXkEhKZnZ2JgX95xxc7bD2FCfO1HxNHZ14VHqvNmFWq+pr0ylhoZhWOIYa+RkTe5D3zm5MckYlbjqa+hkU6oMQNT2E7T8ZRa3VvyqdXtF/MFQmn85ng5HliMXKrk4ZNkLUV/trUyJTSn+LolLzcC+RG+lkvacu8GcV4pvTTgUeptmrk4YF3UTb9vEjYthUXjXrXgPj1GjhzLsTXV9DTl/iRo1iuuri7Mj0TFlD/DYpGkDdHV1CQ29onkvNjae14eMA8DExJiXeweRllY9B0V+lMbDAmkwpBMACRfDMClRd02crMmOfXy9+kdeavHx+cbGw/jNq9gYOeWxNzcmtkRPhrj07PKP+RfvM6e3X5nTSlK4tUC3jhcABg7vvRj7jakhsSV6NcZl5JbqneBgZkQTZ0v1966lMbWtTIlIyaKJU3FvG3szQzzszAiJTKJLfeenzvVfNnTEIAYPVY/xcin0Kk4uxT1qHJ0dSg3wmJKcSnZWDnt2qm+93vXHfga+1geA+NgExg2fDoCxiRFBvQLISC+7x1epHG8N5pV/cly4ipNLcW9Cpwrl2Meg1/sW5xg2tUSOQDLSK3ZM6zesNy+/pu4heD30JvbOxT0q7J3sSIgt3cM1sei97Kwc9v9+kEZeDdnz634SYhK4GnIDZaGSmAexPAiLpIZrDW5cvFmhLILwuCZnPVmWL8uyfApIkGX5BIAsyyGAUXkzybK8RpZlH1mWfUo2NABkhN7ByM0Jg1r2SHq62PVpS/K+s1plkvedw35QRwBse7YmLVh9QnGlzwLO+47nvO94otf+ReTnvxG7fg/hSzZwznsM533Hc3PsStKCr5RqaABIv3AXYzdHDGvZIekpcOzThoS957TKJOw9h/OgDoB6xOLkE1c17zv2aYOkr4thLTuM3Rw1t0s0+nQsWbejiPhG+ykGxq7FBzu7IF+ybkfxsIwLdzF2c9Jksu/ThsSHMiXuPY9T0faw69WKlBNXSy2npLyYZEzq1UDPRn0V0qpDM7LLWHd1UZGTCwA9W/UPFElflzoTXybyR/U9aElHLlLzreJeI2ZFjS3XJq/mdMCsZ3JyAdDYxZqI5EyiUjIpUCrZezWCDvW0TxA61Xfh3H31l0lKdh7hyRnUsDKhsbMVGXn5mgEjz9yLx83OvNQ6njiTozkRqdlEpWVToFSx91YsHd21u+l1crfnXKT6h1NKTj7hKVm4WJS7+1Z83bXsiUhMIyopnYJCJXsv3KZD0bYv6V5cCunZeXjWKd4f0rNzyS9UXylIycwh9F4Mbg/dPqSMuERe8Eb1vxekjuRevolebWd0XRxATxfzHh3IOny6gvPeQmFmiqKom6Sxnyd5JQaWrIh1a3+hQ9uX6dD2Zf7aeYBXXlWfPPn4epGelkFcXEKZ8/Uf2JPtJXo1AOzauZ+27dSDvVnbWOHh4cr9++Xfn12exq4uRMQlE5mQQkFhIXv+vkyH5g20yjjZWPD3NXXPtLDoBPILCrE2MyEyIYXCoitK0Ymp3I9JxNn28V3j73+3n2OBczgWOIfYPeeoOUh9C4iltwcFGdnkPXR/e158KgWZOVh6ewBQc1A7YveeB8CkxHHcIciHzDvqcVoMSgwMa9ncHWVWHkc7zuRY4JwXpr42ru1ERHwKUYmp6n347A06NPMoVe5ebBLpWbl4uhUf75yszTl/+wGFShUFSiXnbz144tso1q75Cf/WPfFv3ZO/duzn1SHqk2xfXy/S0zOIiy27vg4Y+DK/bt2h9Z61jZVm0N2p08fx84/Vc0Dkx7n6wwG2dZvHtm7zuL/nPPUGqAfZtfd2Jz8j+4nGZig5vkPtri1IvRP9iNKP17iGLRGJ6UQlZ6jry8V7dGhYunHpXnwa6Tl5eNYqf8yNfyjDzpN3aJ3634uy3zhZEpGSRVRq0ffu9Wg6eGjfLtKpriPnItQNzSnZeYSnZFLD0pi4jBxyi8akSM/N50JkMnWsy27gEyrup/Vb6NnpFXp2eoX9uw7Td5B6IFmvFk3JSM8kIa70j+uD+47Ryl89rkeb9i25c1P9HWRlbak5loybNIKtG/4oNW+5OdZt5qWOg3mp42D27TpMv8G91Dl8HpFj71Fa+atvTWjTwY87N++WyjF+8lts/eX3UvOWZ/sPfzC862iGdx3Nsb0nNL0UGns3JDM9i6R47cZ0hUIHi6KLAApdBW0CWxF2Uz0G17E9wXi38QTAwsqcmm41iI4oPeaJIJTncT0bSjZGzHlomn6l1qhUETb3WxpvnA8KHeI3HiLnZiS1Zg4mM/QuyfvOEbfhIPW+fAfvU19QmJqp9SSKpyErVdycsx7vTXORFDpEbzxC1s1I3GcOJP1iGAl7zxO94TBNvpxA29OfUZCayeUxnwGQdTOSuD9P0eb4x8iFKm7MXg8qGcuW9XEe1J6Ma+G0OvghAHeWbCTxYCge84dg4uGMrFKRG5nI9Rlry8x0a856vDbNK8p0mKybkbjOHETGxbsk7j1PzIZDNPpyAq1Of05haiZXxqzUzN/67Jfomhkj6eti292X0MGLyL4Vxb2PfsX79/eRC5XkRiZy7Z2vnsk2fB707Szw27cUXTMjZJVMrdE9ONluGsrMHJr/MptrU78hLy6FOuN7YdulBZKOROQP+zWNLmGfbKP+B8NpdWQFkiSR8yCe0NeXl1qPXXdfGix5E30bc7x+mUXGlXAuvLIEAP+zX6DnYAo6ChQ1G5J38AfkdO0TXV0dHWZ392bcL8dQyTK9vVzxsLdg1eErNHK2omN9F9q4O3Lqbhz9Vu1BR0diSqAnlkX3jE4J9GTMT0eRgYZOVvT3dns44hPT1dFhVqcGjP8tRJ2psQvuNqasOnWHRvbmdHS3p01tG06FJ9Hvx2AUksTkdvWwNKrc7qu1boUOs/u3Y9zXf6JSyfT2a4iHkw2rdv1No1r2dGyiHhhsT8htgrzraj19IywuhUVbjqAjSahkmRGB3lpPsXhYdakjumbGKPQVmAS0JmrkPK2nTACgVJGwaBU1vl0MOjqkb99H/p1wbCYOJffKbbIOn8agST2cv1iAwtwM005+2EwcSnivMaBSkbBiLTW+WwYS5F69Q9rW3ZX+fPbvPUKXrh04f/EgOTk5TBg3WzPtaPCfWk+h6NO3B4MHjNSa/+CB43QK8OfU2d0olUrem/+hZuCqJ6GrUDBn6EuMW/EjKpWKPu298ahhz1fbD9K4jgsdvRsw7dUgFq7/g5/3nkSSJBaO7IskSVy4Fc76ncfR01UgSRJz3+iJldmTdd+MP3AB+wAvOp9eiTInj9DJ32imtT+wlGOB6q+2y7O/0zz6Mv5QKPEH1U88ajjvFUw8nEElkx2ZwOWZ6idROPXyo86wLqgKlahy8zk/triBu7rUVz0nc5AUKGzlH/0XAAAgAElEQVTrkHdxN3K29uenq9Bh9uBAxn3+KyqVit5tmuLhbMuqP0/QqLYjHT3VDQ97zt4gyLeB1j4c6F2PMzfDGfjBd0hItGlcp8yGiorau/cwXbt15OLlw2Tn5DJ+zEzNtBOndmo9haJvvx4M6DdCa/527Vrxv/dnIMsywcFnmDblvUpneZQZ7y3j7IVLpKamE9Dndca/NZT+vbo9l3VFHAqlVmdPXjnxMYW5+RyZukYzrf/exWzrph6Z3m/eK3j0aYOukT6vnf2cGxuPcP6T7TQZ0ZXaXbyRlUpyU7M4MuWb8lZVIboKHWa/7Me49QdQySp6+9TFw8GKVfsv0MjFho6N1ON57LmkHhjySZ+4VG32m3/OBWo3Jm/PWuRU7R5hujo6zA5swritp9Xfu01r4mFrxqrjN2jkaEnHuo60cbXj1P0E+q07jI4kMaVjIyyN9Dl1P4FPDl9FQkJG5g1fd+o+gwsPQrHD+0/QMdCfw2f/JDcnl5nv/E8zbefhTfTspO7h8+H7n/HJ6kUsWDSd5KQUZk5Ul2vV1ocZCyYiyzJnToXw3syllcxxnE5d/Dlybic5ObnMnPiuZtpfR9SNEuocK/lk9WLeXTyDpKQUZk54t0SOd0CGM6fO8+7MJZXKcerg37Tu7MeW4J/JzcllydTifeL7fWsY3nU0evr6fLJhObq6ChQKBWePn+fPX9QXUP8+cpaWHXz4+fB6VEoVX33wDekPjbv0X6F6+ofI/SdJjxpQUZKkl4EDsixnP/S+O9BfluXSR/GHBDsOqBa3kGTLTzao2POiqGZ31HSOKz1o5b9tv8Pgqo4AgP8nlXtSwvMgp1eP0X6lOqWfHV4VTgwPruoIGrWtn35siWehVeTdqo4AQPT+RVUdQWN/n4pf+XmeDOXq8YAs/03/3pgfj+PQs3Inys9aUviBqo4AwHqvdx9f6F/yxueNqjoCACfGXazqCAD4L6n5+EL/IqO3nv9jVl8UbrZPee/pMyRXk+O8s2HlB+Z91oKjDv2//jn+Wa3Xq9ePuDJMivi52n0Gj+zZIMvyn+W8fxd4bEODIAiCIAiCIAiCIAj/PZUeJliSpDWPLyUIgiAIgiAIgiAILy7VC/CvOnpkzwZJksq7iVoCejz7OIIgCIIgCIIgCIIgvOgeN0BkAhCOunHhH3LRa/sy5xAEQRAEQRAEQRAE4T/tcY0NYUCALMulnr8mSdKTPwNNEARBEARBEARBEF4g1fU2herucWM2rASsypkmBogUBEEQBEEQBEEQBKGURzY2yLL8lSzLFyVJGihJkhmAJEkLJEnaDlSfZ9EJgiAIgiAIgiAIglBtVPRpFAtkWc6QJMkfCADWAaufXyxBEARBEARBEARBEF5UFW1sUBb99yVgjSzLfwH6zyeSIAiCIAiCIAiCIFQP8gvwrzqqaGNDlCRJ3wCDgV2SJBk8wbyCIAiCIAiCIAiCIPyHVLTBYBCwF+gmy3IqYA3MeG6pBEEQBEEQBEEQBEF4YT3u0ZcAyLKcDWwv8ToGiKnIvHHV5G4L02rywJJCpKqOIJQjZtnfVR1Bw9CsoKojAJCXdaOqIxSxruoAGuHJFlUdAYCV5n5VHQGAHwbsqOoIGm+em1vVEQA42mJRVUcAIOrtrVUdQWOVRZuqjgDAeq93qzoCACNCF1Z1BI2owDFVHaFI9TjOp353vqojaDF6q6oTVB8TjRtXdQSN6vGrAqJ0Cqs6wn+GSvyEqxRxK4QgCIIgCIIgCIIgCM+UaGwQBEEQBEEQBEEQBOGZqtBtFIIgCIIgCIIgCILwX1Rdbp150YieDYIgCIIgCIIgCIIgPFOisUEQBEEQBEEQBEEQhGdK3EYhCIIgCIIgCIIgCOWQqzrAC0r0bBAEQRAEQRAEQRAE4ZkSjQ2CIAiCIAiCIAiCIDxT4jYKQRAEQRAEQRAEQSiHStxIUSmiZ4MgCIIgCIIgCIIgCM+UaGwQBEEQBEEQBEEQBOGZqrLbKJotegPHAC+UOfmcn/Q1qZfvlypj2cyVFp+NQWGoT+zBUC7N/xGAhtP7U+e1TuQlpQNwdekW4g6GIukp8F4xEktPV2SVzKUFP5J48nqp5dZfPAy7gOYoc/K48s5qMspYt1kzV5p8Pg6FoT4JBy9wc94PAOhamuC5ZhKGNe3IfZDAxVGfUZiWpZnP3MuNln99wOUxnxO3828AukRvION6BAC5UYmEvvHRc81h1aYR9T94Ax1dBfnJGZzruxAdAz18/3gPHX09JIUOcTv/5u6KXyvyUT13xh7ONP5sHOZNXbmzdBPhq3eWW9Z9zmAcerVCVspE/rCPB9/uqfB67Hu1wn36AEzquXAmaB7pF8MAsG7flLrzh2BoLCEXFJL08Vpyz4SWuQyjtj7YzBqHpNAhffse0tZt1ppu2KIpNjPHol/PjfiZS8jaf1wzzXrKSIzbtwQdHXJOhZC0bFWFsz/MwM8Xi8kTQKEge8dfZP60UWu6ySsDMe7VA5RKVKlppC5ZjjI2TjNdMjbGfsP35B47Qdonn1c6h1EbH6xnjUfS0SHjt92krX9oe3g3xXrmOPTruhE/azHZB4q3h9XkkRi3awlA6ppfyNp7tNz1VJc6IunrIucXcmvhz6ScuEr9xcOxLdqHr76zmozL90ot06yZK40/H4/CUJ/Egxe4Oe97QL0PN1szGaOaduQ8SODSqJUUpmXh2N+fOhNeBklCmZnD9ZnryLwWDkCjlWOx6+JNfmI62wPmPPbv8V04FJfOXihz8giesobkK/dLlfGaNRD3Af7oW5iwsd7I4m3hVx/f94di1bAmx8Z/ScRfZyu8HcvSZuFQanX2ojAnjyNT1pBYRhbfmQOpN8AfAwsT1tcfWWq6aw9fuq6ZxLYeC0i8VHpbP86JMxf48KvvUKpU9OsRwMhX+2pNj45L4N0VX5Gcmo6FuSlL50zC0c4GgJi4BN77eDWxCUlISKxaOhcXR/sy11Nd6quBUdEx7aO15Px9seys/j7YzhkLCgXpv+4m9dstWtMNWzTBds5YDOq5ETt9CVn7Tmim6TrZYb9wCrqOdoBM9JgFFEbH8SR8PlDX0cKcPE5NWUNyGd+D1k3r0HrlGHQN9Yk6FMq5BT8BYNmoFn7L3kTXxJCsyASC315NQWYOkq6CVh+NxLppHXR0dQjbeoKrX+6ocKanqav1Braj1fxXyYpNAeDq9/u5sfHIE22Tipi/5BOOBZ/B2sqS33/++pkvvySjNj5YzxwPOjpk/rabtO+0j/MG3k2xnqE+zifMfug4P2kkRiWO89n7qv9x3sgUKCwk/auvyQ+5UOYyDPx8MZ80AXQUZO/8i6yfH/oOHjwQo57F38FpS5ejjFPvG45HD1AYpj5+KePiSJk9v8LZhYrp+P5QXDt5UZCTx75pa4gvYx9uM2Mgjfqr9+GvGhbvw2YuNnT9aDRG1mbkpmaxZ9JqMmOTK5WjU1GOwpw89pSTo+2MgTQuyvHFQzm6fTQa46Icu54iR9/3htGwU3Pyc/LYOH01UVdL5xj9w2zM7a3QUegQdvYG2xasR1bJePbwo9vkAdh7uLCy93wiL4dVKoPw31UlPRscArwwdXNkX+uphEz/Fq8PR5RZzuvDEYRM+5Z9radi6uaIQ2dPzbQ7a3ZzKHAuhwLnEndQ/cPQ9fXOABzsNJvgwUtp+t7rIElay7QN8MLE1YkTrSZzbfpaGi0vfUIL0Gj5W1ybtoYTrSZj4uqEbWcv9Tom9ibp+BWCW08h6fgVXCf2Lp5JR6LegiEkHbmktSxlbj6nA2ZzOmC2pqHheeXQNTem4bIRhL6xgpMdZnBp1EoAVHkFnOv3Aac6z+JUwGxsO3th0cKjzHX+2wpSM7k573vur370yaDzKx0xdLblZNupnGo3ldjfTz7RerJuPODiiI9JOaXdAFWQnEHo0OVE9htD/LwV2C+ZWfYCdHSwnTeB2PHzeNB7FKbdO6LnVkurSGFMPAkLPiJz1yGt9w08G2HYvDGR/ccS2Xc0Bk3qYejT7Inyl8xhMX0SSdNmEz9kOEaBAejWqa39N926TeKIsSS8MZKcw0cxHz9Ga7rZ6BHkhWrX08rksJk7kbjxc4nsOxKToE6lt0dsPAkLVpC5W3t7GLVriUEDD6IGjSX69XeweGMgkolxuauqLnXkdMcZXHlnFU2+nIBtgBfGro4Et5rE9elrabj8rTKX2XD5SK5PW0Nwq0kYuzpio9mH+5B8/ArBrSeTfPwKdYr24ZzweM71eZ/THWcQ9sl2Gn08SrOs6E1HCXllaYX+FpfOnpi7OvK7/zROzVqH39LhZZaL3B/CrpfeK70topIInvIN955wG5alZmdPLFwd2eQ/jWOz1uFfTpbwAyH81rN0FgA9E0OajuhGXMidSmVQKpUs/vxbVi2dxx/rP2X3oRPcvf9Aq8xHX/9Ary4d2f7tJ4wdOpDPvv1FM23uh18wfFBv/vzuMzauWoq1pUW566ou9fVBn7HEz1mBw7Lyj2l2898mesx8InqNwqxHJ/TcHz6mJRA/92My/jpcanaHpTNIWf8rEb1G8WDwOyiTU58ov3NnT8xcHfmj7TT+nrmOluXUi5bL3uTvGd/yR9tpmLk64txJfexs/dFILizZzF8Bc3iw+xyNxr0EQO1eLVEY6PJXwBx2BS2g7tDOmNSwrVCmZ1FX7+44zbZu89jWbd5zaWgA6NOjC19/sui5LFuLjg7WcyYS9/ZcovqVfZxXxsaT+O4Ksso4zus39CB68FhiXn8Hi2EvxnE+cdhbpC5aiuWCchp0dXQwnzqJ5OmzSXj9Ed/BI8eSOHwkuUeOYlbiO1jOyyfxzVEkvjlKNDQ8B3U6eWJZx5Hv2k/jwOx1dF48vMxyYQdC2Phy6X24/fwhXN92gp+7zeXvz37Df/agSuVw7eSJVR1H1refxv7Z6wh8RI5fysjRYf4Qrm07wY/d5nLqs99oV8kcDTt6YevqxJKOk9k6dy0DFpf9e+OHtz/jo+6zWN51BqbW5ni+1AqAmJsP+G7sJ4SduVGp9f9/onoB/lVHT9zYIEnSy0+7UuduLYjYom75Tgm5g565MYb2llplDO0t0TM1IqXoxDJiy3Gcg3weuVyzei7En7gKQF5iOgXpWVh5uWmVsQvyIXrrMQDSzt9B19wY/YfWrW9via6pEWnn1euO3noMu+7qddsH+RC9WT1/9OZj2HcvzlRrZBBxO8+Qn5j+2G3wvHI49WtL/K4z5EYlAWhlUWbnASDpKZB0FdXmgbEFiemkh95FLlA+slyN4V0I+/hXkGXNfAA6xgY0WjmWlnsW43dgGXbl1JOs21Fk340p9X7GlfvkxamvQhXcuY9kqA96eqXKGTStT0FENIWRsVBYSNbuo5h0aqNVpjA6jvxb9zQZi8lIBvpIerpI+npIurook1Ie+feWR69RAwojo1FGx0BhITkHDmHYrq1WmfyQUOQ89eedf/UaCnu74vnr10NhbUXemae7Um3QpD4FD6IpjCraHnuOYNyx9PYouH0PVNrbQ9+tNrkhl0GpQs7JJf92GMZty9+/q1MdybrxAIWhPnY9WhKj2Ydvo2tu8oh9+DYAMVuPYd/dFyg6BmxWX+WL3nxU837auVuaXkpp529j4GSjWV7q6esUpGY+chv8o2a3Ftz9VX0VOjHkLvoWJhg9lO+faTnxpX8kZkUmknr9AbLq6Q8Udbq24FZRlviQuxiYm2BcRpb4kLtkl5EFwHfGAEJX7USZV1CpDJdv3KGWiyM1nR3Q09Oje6e2HD6pvQ+EhUfi17wJAC29mmim373/AKVSRRsfdYO3sZERRoYG5a6rOtXX/DvhSIYGZR7TDEse0woKydx9BNPOrbXKaI5pKu3TGD33WqBQkHMqBAA5Oxc5N++Rf+/DanZrwb3H1FEje0v0zIxIDLkLwL1fT1CzaHuYuTkSf1p9Ahxz7Ao1X1LvQ8iga2yApNBBYaiPKr+QgsycCmV6FnX13+Dj1RQLc7Pnvh6DJvUpLHmc3/uI4/xD33t6brXJPV90nM/NJf9WGEYvyHG+8N59JIOy9xu9hg1QPvQdbOD/0HfwhVAo+R1sZ1dqOcLz4d61Bde3qffh2AvqfdikjH049sJdssrYh23quhARrP4t8eDkNdy6tKh0jmtFOWIekSPmETkelMjhXskcTbr6cG67+lwl/MIdjMyMMbMrnSOv6Bipo6tAoaer+Y0QfzeahLDS+4sgVNQjGxskSer30L/+wJp/Xld2pYZOVuREF3cFyolJxtDJqnSZmPLLuI3oSsChZXh/Oho9CxMA0q5G4NStBZJCB+Nadlg2c8XI2fqh5VprfogD5MYkY+hURpkS686NLi6jb2dBftFBIT8+FX079dUtA0cr7Lv78uD7/aX+Xh0DPfz2Lqblrg80jQXPK4exuxO6Fib4bH+XVvuW4DSwXYkgEq0OLqPj1TUkHb1MWiWvEFYVo9oOOPZpg9/eJTTfMBtjV0cA3Cb3Jfn4Fc4EzeN8v4XUffc1dIzL/yHwKCZd2pF3/Q4UlP5Bo2tvS2FsguZ1YVwCCgebUuXKknfxOjlnQql1aBO1D20iO/gcBfcePH7GMijsbFHGxWteKxMSUNiVf9XOpGcPck+rb+lBkjCfOI60L1ZXat1aOextUZbYHsr4RHQdKnb1MP9WGEZtfJEMDdCxNMfQ1wtFOV3Sn8S/UUfse/qRfvkeBg6WD+3DSRXahw2KjmPl7cMluQzpRNKhsm/peRxjRyuyo4vzZcckY+xo9X/s3Xd4FEUfwPHv3l167xUCCQQIoRM6hN5UpIqCiKJSxIpKFRsqiA0UBUGsL4gNGwIBFFA6BAiEDoEE0ntvd7fvHxcuOXKXXCAhQefzPD6S29md3+3Nzs7Ozs5WsUbdsfN2Ib9CLPk1jMU9tAl2vq7E3eS+AEhJy8C7wnHi5eFGcprhkNTgoCbs+Ed3rPy55yD5BYVkZedy5VoiDna2PPvKUsZNe4H3Pv0ajabqCyJz3JY6bXAvik8br9OUXm6UVqzTktJQepp3DFs28UObm4/38oU0+ulj3F54DBQ1u39hc2O5SMjA5oZyYePtQkGFY6himuzz1/AfqmuAB9zdFbuy833spkOoC4oZc3wFow8v4/SqzZRk5WOOWy2rAE2HdWHs9rcY9OnT2N1QJ9xplJXOe+aXEV3ngmE9r/K6M+p56759KD1/wfhx4+GOJqX8HKyt5hxse/dwig8e1P8tWVri9tkq3D79GKsbbhQIt87e24XcxPJjOC8pA/saHMOpp+NoXtb532xoZ6wcbLB2tr/lOHJvIo5mtRCHo5crWRXqtKykDJy8jddLU7+ex+uRn1KcX0TU5gM1zksQjKluzobvgAggBbj+PIIdcA+6Pq+NxlaSJGkqMBVgmkMYg21rd7h+zJfbOfP+RpAhZM442rw6kaPPrSb22104NPelX8QbFFxLI+PIBWRNHd++L+tZb7FoMhfeWG/kjjb80+lJipMysQnwpPOPC8k7fXMXmebEISmVOLYLJHLsGyisLenyx+tkR16kICYRtDIHBsxF5WhL+y+fx76lf+3HUYcUVhZoi0o5OGQ+nsO7ELJsOkfufRW38LZ4DOlMkyfuKUtniY2fO/kX4mu0fYugAFyfe5TEqdU/C19Tqka+WAY2Jm7gBAB81iyhcG8oRUejaz2vimyGDMSiZQuyZz4LgO3oeynefxBtalqd5ludwv2RWLZugc9Xy9FmZlEcdRpq4eKtrsuIXQt/mi+cwNH73qLFm5NvOV4DN9QdLj1b4zuhP0dGvFy7+dxpJInur0xk53Of1nlWL0x7iLc++oxft+2kU5sQPN1dUSgVaDQajkaf5ftV7+Dj5c6Li97n14hdjB4+4Jbyq+vyatksAPdZjxL/+PxbitMopRLrTqFcHfME6sQUvN9bgMPIQeRujKj9vEzYP2sNnRc9RJtnR3Jt21G0JWoA3DsEImu0/NThKSyd7Bjyy0KS/okmLy61mi3eutjtx7j46360JWpaTexPv2XT2DTevEef/m2K9kdSWFbPazKzKD5xGrQNv55XNW2Cw4ypZDxn4vGjGrAZrDsHpz/5rP6zlLH3o01LQ+nrg+vy98m4dBlNQsIt5yXUjr/fXE+/1ycTMrY38YfOkZuYgay9/QPUd7+5ngGvTyZ0bG+u3aY4Vj+0GJWVBQ8ue5LmPUI5v+dkneZ3p2kgA8LvONV1NvQAlgCHZVleCSBJUl9Zlh+paiVZllcDqwE2ek+QAQIfGUSTif0AyDweYzDiwMbHlaJEwyHlRYmZ2PgYT1Nc4dGAK+v+ovs3L+ry1Wg5+cr/9MvCf3+VvJhEAh8ZRGBZ3jnHL2HtV343+sY7j7q8DUcZWPuWpylJzcbS01l3J9LTWf+YglP7QNquegYACzcHPAa2R6vRkLrlCMVlE0W592+P0sGGzj8uIP3vk3USR1FiOqWZuWgKitEUFJN54CwOrRvrOhvKqHMKyNhzCrd+7WkIrLxc9EMXq1KckE7yZt3dgZTNhwhZPkO3QJKImvJepWGRIctm4NimCcVJmRybuKTqGHxc8Vq2gJT5S1FfMz5cTJ2SVjYRmo7KywNNcrrRtDeyG9CTohNnkQuLACjYcxirdq1uqrNBk5qGssLdIaWHBxojnQeWnTtiP/lB0mc+q787YxnaGst2bbAdfS+SjQ2ShQptYSG5K9fUPI6UNJQV9ofS0x11svmdGNmfrSf7s/UAeCyeR2msYYPQYfwIHEYPB+Dqfe80iDLS6aeFqHMLaff5LLIr1SVuZh3DxWX1mKljGMA+pDEh70/l2ANLKM0077EJgBaTB9K8rK5LPx6DrW95fLY+rhQk3dyjOzej9eSBtJygiyU1Kga7CrHY1SAWS3trXFr4M+KHBQDYeDgx9PNZbJ3yfo0mifR0dyWpwnGSnJqOl7trpTTLXtNdYBQUFrL9nwM42tvh5eFGi6AmNPL1AqB/zy5EnT7PaMo7GxR2rijsdNtrKHWa94cLSJ73Duqrxus0TXI6FhXrNG93NCnmHcPqpDRKzl7SPYIB5P+5D6t2LavtbAh+eCDNKpRRO183rncB2Pm6UnhDuShMysS2wjFUMU3OxUT+euBtQPdIhd8A3TmtyageJOw8gazWUJyeQ8rh87i2CzTZ2VBbZRWguMJjTme/3UnXBfebvW5DpKl03jO/jIBhPe9eTT0fN65h1PMub80n640lJjsANKlpKD3Lz8GKqs7BDz2o62ioMEJCm6ZLq0lIpOTYcSyCm4nOhlvU7qGBhD6gO4aTT8TgUOHxQ3tvV/JqcAznJ2exadpyACxsrWg2LIzinAKz1m3/0EDalMWRdEMcDjcRx28V4mhegzh6ThpMtwd089hdjbqEc4U6zdnblewqJppUF5cSvf0IoYM6i84GoVZUOeZRluXDwCDAUpKknZIkdeEmO3Zivtiun9AxcesRGt+nG97v0rEZpbmFFN3wvFJRShaleYW4dNSNimh8X28SIiIBDOZ38B0WRs7ZawAobSxRlg2Z8+wTiqzWkHs+npgvtusnaEzZcgTfcX0AcOrUDHVugX4o83UlKVmo8wr1Eyj6jutD6tYjAKRGROI7Xre+7/g+pJR9/k/Y0/wT9hT/hD1F8u8HOTPnc1K3HEHlZIdkqevTSfp1P6WZuRyd+HadxZG69QjOXVsiKRUobCxx7tiM/AvxWLg5oHLUTcyksLbALbwt+RcbxsnNnMYFQMrWw7j2bA3o3rhxvUGRviuKRo8O1adzCG0CwOlnV3JgwJxqGxcqR1s6rJtLxrK1FB8/bTrO6HNYBPih8vMGlQq7YeHk79pvVuzqxBSsO7cBpQJUSmw6taU05uZGuJSeOYvK3w+ljy4Om4H9KdpjOEGWKrgZznNmkTF7AdrM8nKV9dqbpIy+n5QxD5CzYiWFW7bdVEcDQPGpc1g0rrA/hvalYLd5+wOFAoWT7nlji+ZNsQxuSuH+IwZJcr/7jYTx00kYP73BlJGzs9eyr/uzHBgwh9Qth/HRH8PNqzmGmwPgM64PqVt18wCkRhzBd3w4AL7jw/XHtrWfG+0+f57omR8bdBKa49xXO9g0eAGbBi8gLiKSoLG9AHDvGERpToHRuRnqyqmvdugnybuyNZLgslg8OwZRkltg9vPuJbmFfN12Buu7P8f67s+RcuxSjTsaAEJbNiM2PpFricmUlpayZede+vYIM0iTmZ2DtuzO0Wfrf2bUUF1jLbRFELl5+WRkZQNw8Fg0QQGGI8O0+RmoUy6iTrnYYMpr+vufU3TMdJ1WpK/TvMBChf2wvuTvNG/obHH0eRQO9ihcdI//2HRrT+mluGrXO//lDjYPWsDmQQu4tjWSphXKaImRMlqYkkVpbiHuHYMAaDq2F1fL2gJWbo66RJJEm2fu5cI3fwK6yU29e+n2q9LGCveOzcip4nxXW2UVMJjfIWBwJ7IayHn2ZhWfOoeqsR8q37J6fsgt1PPN74x6PnflGkpPmr4RUHr2LMpGhufg4r03nIObN8PpxVlkzF2ANqu8/EgO9vp5ICQnRyzbhKK+EmvW9xZMi/p6B+uGLWDdsAVcioik1RjdMezdQXcMG5sTwRRrF3v95PJhM0dw6jvTb1C50fGvd/DNsAV8M2wBFyMiCSmLw6dDEMU1jMOmQhxdZo4gugZx7P1mG+8Nn8t7w+dyctsROo/WtVUCOjSjKLeA3FTDOCxtrfTzOCiUClr170jKpTu77hIaDkk2MuzfaEJJ8gWWAZ1lWQ6sLv1110c23Kjd4ofx6tcOTWExkc9+SlaUruHYf8db/DVQN+TTuV1TOi2fjtLakuS/ooia/yUAnT+agVNoAMhQcDWVYy+upSglC9tG7vT8di6yVqYoKZPIWaspvKbrQbaXy4cetVz8CO5lr4M79cwq/WuPuv25hAMD5gLg2C6Q0A9noLC2JO3P45yd/wUAFi72tCPbvqcAACAASURBVF3zLNZ+bhRdSyPq8WWob3gWtPXyGaRtP0rypoM4dQ4m5N3HdBPkKSTiVm8hfv3OOo2jyRN343t/X5Blrq37i7jVW7APaUzoh7pXNkoKBUm/7ifm/Y0MTt5g7k9ZZ3aHTqXrtsWoHGyQtTKa/CL29X4eTV4hHdbN5fSsTylOzkTlaEvoJ09h7e+OJr+IMy9+Rt7pWBTWFrRY9DBOYcFIkkTh1RSOP7i0Uj4ew8Jo+dYjWLo5UpqTT250LMfuf4umz42m6dP3oo4rv+OSOG0eWiMzq9v0DsNttm4/5v4cQdaab3GZ+RDFp85TsOsAVq2D8Vr+CgoHB+SSEjRpGVwbNVX3JouXnsK6UxuQZQr2HiHjHdPDwq0dqp4Ez6p7V5yemQlKBQWbtpD31TocHnuEkrPnKN6zD7fl76IKaoq27Jl0TXIyGXMMZ722GT4Ey5Ytqnz1ZXF+1YOfbHp1wW32DFAoyP0lguzP1uP8xGRKTp2nYPd+LFsH4/XBqygc7ZGLS9GkZxA/+nEkSwt8N+jmjdDmF5D+xnJKzl0ymU+cpmmDKCMFMUn6tJHj3yTo+bG49W+HprCE08+srHAMv82BAXMA3THc+sMnUFhbkPbncc5VOIbbrHkWGz93Cq+lceLxD1Bn5RPy/jQ87+pCUVndJas1HByiqxPbrHoalx4hWLg6UJiWQ9S7P3Fxg+kGSJc3J+PXty3qwhL2zVpNetkF+t3b3mTTYN1IgY4L7qfpqB7YejlTkJzFxfW7iHp/I27tAum79lksnWzRFpdSmJLNb/3nVsqjUKr0kVG93piMf9+2qItK2DVrtb6zYEzEm/w0RBdL1wX302xkD+y8nMlPzuLst7uIfN/wab17fljA/kXrjXY2PHJgTpUx/H3wKEvLXn05alh/pk4cw4ovNtC6RRD9eoSxbfd+lq9dh4REp7YhLHj6MSwtdRcG+45E8e6qr5CBkOaBvDprGhZGJo8D2D/0owZRXivWaQmPzUOTkV1pG7Z9wnCfOx1JoSDn521kfvotrk8+RNGp8xTsPIBVaDA+H76MwlFXp6nTMrk6YioANt074j77cZAkik9dIOXV5VCqNrpPDmQZnyAv7K3J+JaV0f3PrSaj7Hcdvv1NNg/SlQvXtk3psWwqSmtLEnZGcXiB7jXYLR4dQouHBwIQt+UIx9/SvZJRZWtF9w+m4hTsB5JEzHd/c3rlHwDkmzGtxK2U1S5z7yNgUEdkjYairHz2zPuCLCOTEU45/nr1gVThxVeWcPjYCbKycnBzdeaJRycx5p4hN7Wt+IHTqlxu06sLri/q6vm8X8vq+RmTKT59nsKyet7zfcN6PmGMrp73+VZXz8v5BaS/WXU9H6tuGPW8Nv6aPm3Gcy8adBZcZ9WtK47PzNS9yvqPLeR9vQ77Rx+h9Ow5ivfuw3XZu6gCm6JNLz8HZ859CYvQ1ji9OEv32Jwkkf/9TxT+sbnK/e+zp/KbYP6rPmj8oFnp+i2aTJOyemXbC6tJLjuGJ255k3XDdMdw7/n30+LeHth7OZOXnEX0hl0c+GAjzYeH0XPOeF0b+uA5di78Ek1J5XrNnAcaBpTFUVpYQkSFOCZteZNvyuLoM/9+WlaI4+SGXewvi6P3nPHIskz8wXP8aSKOeIXxOrei0a8/Qstw3atAv31xlf71lc9vXsJ7w+di7+7EY2tno7JUISkUXNx/il8XfY1Wo6XNkDBGvfow9q6OFObkE38mltUPGX807P0rG8xsEdyZXg2Y2OCfpHg1dl2D+w3M7my4WaY6G263ip0NQrmG0Nmw3Wt8fYcAQJDn7RtiXp3qOhtul+o6G26Xi0l39iRrdSFRZfxC93Yzt7Phdqius+F22d3pNryS0AxN3ervbQk3MtXZcLuZ09lwO9xqZ0Ntqq6z4Xa5kNgw6vnQ5inVJ7qNRGdDOXM7G26HhnJVYU5nw+0iOhvqX0PsbLjp064kSatrMxBBEARBEARBEARBEP4dqrxtKUmSqW5mCRhe++EIgiAIgiAIgiAIQsOhbXBjBu4M1Y2RTgViKX/tJegmiJSAW39ZsiAIgiAIgiAIgiAI/zrVdTbEAANkWa40xbQkSTc3lb4gCIIgCIIgCIIgCP9q1XU2LANcAGPvs6o8xa8gCIIgCIIgCIIg/ItoafDzQzZIVU4QKcvyx7IsR0mSNE6SJAcASZIWSpK0Edh7WyIUBEEQBEEQBEEQBOGOYu7bKBbKspwrSVIvYACwFlhZd2EJgiAIgiAIgiAIgnCnMrezQVP2/7uA1bIs/wFY1k1IgiAIgiAIgiAIgtAwyHfAfw2RuZ0N8ZIkfQqMBzZLkmRVg3UFQRAEQRAEQRAEQfgPMbfD4D4gAhgiy3IW4Aq8WGdRCYIgCIIgCIIgCIJwx6rubRQAyLJcAGys8HcikGjOuq5y6c1FVss0DWQghtRgB7kIPi/1rO8QyhUV1ncEOj6N6zsCAC5O2l3fIeg1dsmp7xAAmJAYU98hABD3xeT6DkEv5/En6zuEMt71HQAAfh+Pq+8Q9J4e8XZ9hwBA/FeP1HcIAMQPnFbfIej57fi0vkMA4ELrefUdAgDRFzzptaxlfYchmPBBXlR9h9CgOFjY1ncIglAlszobBEEQBEEQBOHfTnQ0NFyio0GoT9r6DuAO1TBu9wuCIAiCIAiCIAiC8K8hOhsEQRAEQRAEQRAEQahV4jEKQRAEQRAEQRAEQTBBK+bduyliZIMgCIIgCIIgCIIgCLVKdDYIgiAIgiAIgiAIglCrxGMUgiAIgiAIgiAIgmCCeIji5oiRDYIgCIIgCIIgCIIg1CrR2SAIgiAIgiAIgiAIQq0Sj1EIgiAIgiAIgiAIggna+g7gDiVGNgiCIAiCIAiCIAiCUKvqZWSDa7/2NHvjESSlgsR1fxL30S8GyyVLFa1WPIVD20BKM3M5PfUDiq6m4tKnLYEvTUSyVCGXqLn0+jdk7YlGYWNJ6zXPY9PEC1mjJX17JDFvrDORdzuC33gYSakgYd1fxH70a6W8W6+Yqc87eupyiq6mAhDw9Eh8J/RD1mg5v+BLMnZFYRvkQ+jqZ/Xr2wR4ErP0B66u3kzo6mewDfIFQOVoizqngMMDZhuNqXmF/WEsppAVT+pjOjV1GUVXU1G52NNm7Swc2jcjacMuzs//vNK223w9G5sATw6Fv2DGL1OPFBJdty2mOCmD4w8uNVhk7e9OyLLpWLo5UpqZR/TMFRQnZpi9adtmvrRePgPHNk25uHgDsSs36bK0sqDzr6+isLRAUipQqWNQn9pV5bb2Xkhg6eZItLLMqI5BTOnTulKaiOhYPt15EpAI9nZmybieAHwQcYx/zicgyzLdgryZPbwTkiSZ/T0M4riUzNLtJ3RxtAtgSo8WleM4fY1P/zkLEgR7OrFkZJh+WV5xKaNX76BfsC/zhrS7qRgA9p6+wtKfdqPVyozq3popg8MMlr/z024OX7gGQFGJmoy8AvYsnQFAYkYOr337J8mZuUiSxEfT78XPzdF0Zg2gjCRvOoj6s7VVb6tXJ7wWTAeFguwft5Kx5geD5TadQ/GcNw2rFk1JeH4JeRF79MuCT22i+PwVANSJqcQ/8ZrZ38GYt95ewMDB4RQUFPH0E3M5EXXaYLmdvR2btpTXlT5+3vz43W+8NO8t7p8wilcWzSYpIRmAtWv+x/++/vGW4gHYey6epZsO6cpMWHOm9G1jsPydTYc4HJMEQFGJhoz8Qva8MuGW8wWw6NQFu+lPISkUFG39g8If1hsstx51H9ZD7wKNBm12FnkfvI02Rff9badMwzKsGwAF335Nyd87q86sAZRXlVUq6itHq9zW3lOXWfr9n7rfo2dbpgztarD8ne//4vD5OKDsGM4tYM8HTwPwwU+7+Cc6RlentWrC7Pv633SdBrB46UIGDQ6nsLCQmdPnVCqv9vZ2/BHxrf5vXz8vftjwG/Pnvsmbi+fTq4/u97GxtcbD3Y2mjTrddCxQv2UVwKZHZ1xnPwEKBXk/byH7i+8Mllt1bIPrizOwbB5I6tw3Kdjxj36ZyzOPYdO7CwBZq9dRsG13rcVV0Utvvc/few/h6uLML/9bdesbbAjHTekl1NFVH997LySydOtRXdnoGMiU3iGV0kREx/HprmjdOdjLmSVje3D4cjLvbD2mT3MlLYclY3vQv5W/2d9DqN5ri+fSb1BvCguLeH7mS0SfOGOw3M7elh//+Er/t4+vFz//sInX5i+lS/dOvPLWbFq1DubJx2az+bft9R7TrZr35iz6DOhBYWERC55exJmT5yqlsbBQsWDxi4T16IhWq+XDxavY/kf5cTDorn4s+3wJ9w2ezKmos7cck/Dfcfs7GxQKmi95lKj7FlGckEGniMWkRRyh4Pw1fRKfCf1RZ+VxsNtTeI7sQeDCBzk99QNKM3I4OWkJJcmZ2LVsRNsNL7G//TQArq78jay9p5AsVLT78WVc+7cn46/jN+Qt0WLJFI7d9ybFCemEleWdfz5en8R3Qn9Ks/LZ3+0ZvEb2oNnCCURPXY5dsB9eI3twoM/zWHm70OGHl9jf/VkKLiVyaMAc/fZ7Ra0idfMhAKKnLtdvt9mrk9DkFBjZHxItljzKsfveoDghnc4Ri0mNOELBDTGps/I50O1pPEf2IGjhRE5NXYa2uJSYJd9h17Ix9i0bVdq0x/AuaPKLavwT1YfGjw8n/0I8KgebSsuCX5lE4vd/k/j937j0ak2zBQ9w6smPzd52aVYe5xZ8icewzgafa4tLiRz9OpqCYiSVkv4nlqJJuoCcHm90OxqtlsWbjrBqcn+8HG2Y+GkE4S39CfJ00qeJTc/h879P8+Vjg3G0sSQjT7f/j8elcjwulR9mDgPgkc+2c+RKCmFNvcz+HuVxyCyOiGLVAz11cXyxk/DmPgR5lF+ox2bk8fn+83z5UB9dHPnFBtv4ePcZOjZyr3HehnFoWfzDLlbNHIWXsz0T39lAeJtAgnzc9GleHBOu//e3u49z9lqq/u+XvtnGY0PC6N4ygILikmovUhpCGQn7/TWyDrekyNSJVqHA6+WZXJsyn9LkNAJ+WE7eXwcpuRRXnldiCknz3sNlyphKq8tFJcSOetLsuKsycFAfAoOa0KXDYDp1bsfS919l6ID7DNLk5+XTr/dI/d87dv/EH79v0//968bNzH1xUa3EA2Vl5rcDrHp0MF6Otkz8+A/CWzUiyMtZn+bFu7vo//3tvjOcTTD/YqJKCgX2M58le/7zaNNScV7+KSUH96KJiy2P79IFsp6eCsXFWN91L3ZTppO75DUswrqhCgoma+ZjYGGB09LllB45iFxgpE4v0xDKa/8zy9BkXEXOSTW6HY1Wy+Jvt7PqmfvwcnFg4uJvCG8bRJBved3w4n399f/+dudRzl7Vdb4cvxTP8Uvx/LDwYQAeeWc9R85fJaxFY7O/R0UDB4cTFBRA5/YD6RzWnvc+eJ1B/ccapMnLyye85wj933/9/TO/l5XXBfPe0n/++LRJtG1X+eKvJuq1rAIoFLjOe4rk6XNQJ6fhu24FBbv3UxpTXpdoklJIe/kdnB4aZ7CqTe8uWLZqRsL46UgWlnivfZfCvYeR802X15s1cvggJowZwfxF79bK9hrEcRO1FE3iBeT0a0a3o9FqWbz5CKsm9dOdg9dsJ7yF3w1tgVw+33OaLx8daNAWCGvqxfczhgKQXVDMPR/+Qfcgb7O/g1C9fgN70yQogD6d76JD57a8+d5L3DtookGa/LwChoWXHzd//PUdW37/E4CEa4k8P3Mh056c3GBiuhW9B/QgoGkjhnUbS9tOoby8dDYPDHu0Urqpzz5CRloGd/UYhyRJOLmUtylt7Wx58PHxREVG33I8dzKteB/FTbntj1E4dmxG4eUkimJTkEvVpPyyF/ehhhW/+9Awkr7X9cKn/n4Al16hAORFX6EkOROA/LNXUVhbIlmq0BaWkLX3FAByqZq8k5ex8nXjRrq8k8vy1pD8yz7chxreifUY2pnEsrxTKuTtPjSM5F/2IZeoKYpLpfByMo4dmxms69q7DYVXkim6llYpb68R3Uj6ea/RmAr0+0NDyi/78LghJvehnUn8flel/aEtKCb70Dm0xSWVtqu0taLR9Lu58sFPlZY1NFY+rrgP6kD8ur+MLrcL9iNjj+73zdxzCs8K5SXgiXvosvUtuu1cSuCL44yuX5qWQ87xS8ilmkrLNAW6i3DJQgkKZZXvtYm+lk4jV3v8Xe2xUCkZ0iaAXWcNGyMbj1xifNfmONpYAuBqb63bPlCi1lCq0VKi1qLWyriVLaup6IQMGrnY4e9ih4VSwZAQf3ZdSDSM4/gVxncKLI/Dzkq/7HRiJhn5RXQP9Lyp/PVxxCbTyN0Jf3cn3f7oFMyukzEm02+JPM/QTsEAXEpMR6PV0r1lAAC2VpbYWFqYXLehlBFJpQLZdCGxbhtMaVwCpdeSoFRN7ubd2A/oZpBGHZ+iG71QxXZqw9C7BvDdt7pRY5FHonBycsTLy8Nk+sCgJri7u7F/35E6iyn6ahqN3Bzxd3XQlZl2Tdl15qrJ9FuiLjO0XdNayVsV3ApNQjzapERQqyne/ReW3XoZpCk9cQyKdb936dnTKNx1+0vVuAml0VGg1UBxEZrLl7Do1LVSHtc1lPKKVPUpPvpKIo08XfD3cNb9HmEt2XXiosn0Ww6fYWjnVrrtS2V1mlpDiVqDWqPFzdGuyvyqMvyugWwoK69HDh/H0dmhyvIa1KwJHh5u7N97uNKyMePu5qcfNt10LFC/ZRXAKrQF6qsJqOOTQK0mP2IXtn17GKRRJyRTeuFypbrEIjCAosiToNEiFxVRcj4Gm56G7aza0rl9G5wcHWplWw3muFEoqKoxEB2fQSNXh/K2QGhjdp0zvEmxMfIS48MqtwUq2n76Kj2b+2BjKaZPq02Dh/fjpw2/AXDsyAkcHR3w9DJ9c6VpUABuHq4c2h8JwLWrCZw9fR6ttvbO0bca063oP7QPv/2wBYATkdE4ODrg7ln5GmnUA/ew5kPdyApZlsnKyNYve3ruNNau+IbiouJK6wlCdWrc2SBJkuutZGjl7UpxQrr+7+KEDKy8DQu9lY8rxfG6C3ZZo0WdW4CFq+HJzOPubuSdjEEuURt8rnK0xW1wJzL/OVkpb2tvV4oM8k7HytvFSN7plfK28nbRxwRQnJiOtbfhrvAa1YNkIx0Kzt1aUZKaTeHlJDP2RzpWN2z3xpg0RvbHjZrOvZ+4lb+jLazcEdHQtFg0mQuvrwMTFXvu6Vg879LdQfIc3gWVgy0WLva4hrfFNtCbQ0Pnc6D/HBzbNcW5W6uaZa6Q6Pbn24SfWoMmKQY5w/ioBoCU3EK8ncob016OtqTcMFolNj2X2LRcJq/ZxqTVEey9kABAu8YehDX1YuA7PzPonZ/p3syHQA8nbkZKbhHejuV3fbwcbEjJNRzBEpuRR2xGHpO/3s2kL3ex95LubqRWlnnvz2hmDTAcDnxTcWTl4e1SXg69nO1JycozmjYhI4eE9Gy6BOtG4MSmZOFgY8WsNZsY//Z63v/lHzRa01PvNJQykr77BEUnKg8/vE7l5U5pYvldZHVSGiqvyid1UyQrSwJ+XE7jDR9gP6B7zeK8gY+PFwnx5XVOQkIS3r6mR9KMGnMXv/y82eCzu0cMZtfe3/j86+X4+t363beUnILKx1B2vtG0CZl5JGTm0aWW7vop3N3Rpqbo/9ampaJwM93Ysx48nJIjBwFQX76IZacuYGWF5OiERdsOKD1MXwg3lPKqyYg3OaoBICXzxmPYgZRME8dwejYJadl0aakbudAu0I+w4EYMnLOSQbM/oXtIUwJ9zC/rN/Lx9SI+vrzTNCE+CZ8qyuvoMXfz88Y/Kn3u38iXxgH+/L17/03HAvVbVgGUnu6okyrUJclpKD3NG42m61wIQ7K2QuHsiHVYe1Ret9a5fDs0mOMmKcbkCEeAlJxCvB1t9X97OdqQklNokCY2PZfY9Fwmr93BpDXb2XvDDQHQPWYxLPTmRgIJpnn7eJJY4dyXlJCMt4/p8j9i9DB+/3nrvzYmTx8PkuKT9X8nJ6bg5WN4/nJwtAfgqTnT+GH7V7y/5i3cPHTXIq3atMDb14u/d1S+vhEEc1TZ2SBJ0ksV/h0iSdJ5IFKSpCuSJJm+rVPHbFv4E7hwIudeWG3wuaRU0GrVs8R/tpmi2BQTa9cNyUKJ++BOpPx+oNIyXSfEvtsWi33rAGyaeJG2pfIdn4aoJC2H3BOXTS6/8Or/cOkeQtcdS3Dp0YqihHRkjRa3vm1xC29Ltz/fptuOJdg188M2sIaNPa3MgQFz+Kf9DBSuvkhOpi8gzKHRaonLyOWzKQNZMq4nr/96iJzCEuLSc4lJzWHb8yPZ9sJIDsckcfRK3ZVRXRx5fDaxN0tGhvH65mPkFJXwfWQMvYK88HKsPES1LkVEnmdg++YoFQp9fMcuJTBrVG/WvXA/8WnZ/HbwtNF1Fe4BDaaMOHVshmXzgJqtXwMx/ScTO/YZEl94G8/507Bo5FNned1o1JjhbPyx/OItYstOOrbpT9+eI9i1cx8rVr1922IBiDhxmYGhAfoycztZ9RuEKrgFhT9tAKD06BFKjhzA+b2PcZjzMqVnTyGb6Byz6NK9wZRXhaMHkp1L9euYIeLIWQZ2DNb/HnEpmcQkZbBt8XS2LZnB4XOxHL1gfNh5XRg99i6joxdGj72b337ZiraKzsvaVp9l1Zii/ZEU7jmEz1fL8Vgyn+ITp3WjchowycK24Rw3bn5ITrfWOaPRyrq2wMP9WTK2O6//rmsLXJeaW8jFlGy6N7t9dbxg3IjRQ/ntpy31HYaB2x2TUqXEx8+L44dPMm7QZKKOnOSFV55GkiRmv/YMS19dXv1GBMGE6sZujQbeKPv3O8AzsixvkSSpC7AM6GFsJUmSpgJTAWY5dOQem0D9suKkDINHHKx8XSlOSjdYvzgxAys/d4oTM3ST9TjYUpqRq0vv40roFy9y5skVFMUmG6wX/N40Ci8ncm214d2564qSMrA2yNuN4qRMI3m7Vcq7OCkTK7/yuwpWPm4UJZU/n+k2oAO5Jy9TkpptsD1JqcDzri4cGjTPaEyV94cbxUmGz33eGJOywv4wxqlzMI7tAul+eAWSSomluxMdNr7CsdG3NtlcXfEY0gn3Ae1RWFuisrch9OMniZ65Qr+8ODmTE1PeA3SPh3je1RV1TgGSJHH5w1+J/2aHwfb8HxmM/4MDADg2YQnFyYa/sTHqnAK0KVdQejdDnW38TqCngw1JFe5sJecU4Fnh7gbo7n6F+rthoVTg52JPgJsDcRm5HLmcTNtGbtha6R4V6Nncl6iraXRsUvMGjaeDNUkV7qIk5xbi6WA4RNPLwYZQX1ddHM52BLjaE5eRT1R8BseupvP90csUlqgp1WixtVTyTL/QmsfhbE9SZnk5TM7Kw9PZ3mjarUfPM29c3/L4nO1p4e+Bv7tudEe/tkGcuJLEKCM38xXOPngMCWgQZSRzzykcenem5EKs8TTJaVhUuGOg8nZHnZxuNK3R9VN0aUuvJVFw6ARWIUGUXq18R8yUKY9NYNJk3bwMx46dNBiN4OvrrZ/s8UatQ1ugUik5cfyU/rPMzCz9v//31Q+88tqLZsdhiqejbeVjyMn40PutUVeYd2/t9Wlr09JQeJQfbwp3D7TplR95s2jfCZv7J5E9+2koLdV/XrjhfxRu+B8A9rMXook3PqTeIiQUj94NpE7LSkTp6o8633h6T5cbj+FcPF1MHMNHzjLv/oH6v/86foG2TX2wtdYNE+8ZGkhUTDwdm5s/0d2jj0/koYfH677X0RP4+ZVfePn6eZNosry2RKlSElWhvF43esxdzH7+VbNjMKU+yyqAJiUNlXeFusTLHU1K5fJqSvZn68n+TDcBqvvieZTGmr5T3xBIFlYNpy2QfBmlTzPU2cZvCHg62pBUYVRjck4hnjd04Hs52hhtC4T66dp7207F0a+lHxbKhtFBdad76NH7eeAh3TxIJ45F41Ph3Oft60VSovHfslXrYJRKJSejjN/suFNjeuCRsYx98F4Aoo+fxtuvfJSYl48nyYmG7dysjGwKCgr1E0JG/P4noyeMwM7eluYtg/hy4ycAuHu6seLrd3nyoRf+k5NEihkbbk5NajlfWZa3AMiyfAgweWtUluXVsix3lmW5c8WOBoDcYxexCfTBurEnkoUKz5E9SYswfEY4LeII3vfpJpbzuKcbmXt0E5KoHG1ps24eMW+sI+ew4VDmpnPvR+Vgy8WXvjT5BXKPXcI20Bvrxh5IFkq8RvYwmrdPWd6e93Qjs+z5wLSII3iN7IFkqcK6sQe2gd7kHC1/ttV7VE+joxdc+rQh/0KCyRmTdTH56GPyNBpTJD739a2wPyo3sCqK/2o7e9tNZ3/Ykxwd8TIFMQkNtqMB4J8OT7An7ClOTltOxt5og8YFoHtkpGzywCbPjCThW11lmLYzCr8JfVHa6uYjsPJ2wcLdkWtfbOPAgDkcGDCnysaFhZsDqrLOAoW1BQrvQLQ5phtzrf3ciMvIJT4zj1K1hoiTsYS39DNI06+VP0fKRixk5hcRm56Lv4s9Pk52RF5JQa3RUqrREnklhUCPKt68UIXWvi7EZeYRn5VPqUZLxOlrhDc3vDvSL9iXI3G6k0lmQTGxGXn4O9uy+N4wtj45lC0zh/DcgFDubtP4pjoaAFo39iIuNYv4tGzd/og8T3ibwErpLidlkFNQRLum5TG2DvAit6CYjFxdg+3Q+asEeht/Qkt98UCDKSOu4W0oiTH93HbRyfNYBPhi4ecFFiochoeT91fl0U7GKBztkSx0nVFKZ0dsOoRQcjGumrUMff7Zevr1Hkm/3iPZsmkH4x/QTf7YqXM7cnJySU423pE2euzdBqMaAIPn5YcO78/585dqFIsxrf3diUvLIT4jDS+wTwAAIABJREFUV1dmoi4TbmQW9ssp2eQUFtOu8a2NNKpIff4sSl9/FF7eoFJhFd6fkgOGw0KVQc2xf/p5cl6bh5xd3tmCQoHkoDtelU0CUTUNpDTS+NwWBV+uaTDlVeHih7Ygy2T61gE+xKVkEp+Wpfs9Dp8lvG2zSukuJ6WTk19Eu0Bf/Wc+ro5EXrhaVqdpiDx/tcaPUaxds47wniMI7zmCPzbt4P6y8to5rD052abL65hxd7PRyKiG5sGBODs7cujgMSNr1Ux9llWA4lPnUDX2Q+WrK692Q/pSYO6jIQoFCifd4zEWzZti2bwphfvrbi6W2qAtyGw4x413UNVtAV9X4tIrtAWi4whvcUNboGXFtkCxvi1w3daTcQxrU3ej5P5rvl67gWHh4xgWPo6IP/5izP26iWQ7dG5Lbk4eKcnGf897xwznt411M4KgPmP69osfGTNgEmMGTOLPLX8zYpxucvK2nULJy80jLaXyTZBd2/bQpWdHALr1DuPS+cvk5ebTK2QIg8NGMThsFFGR0f/Zjgbh5lU3siFQkqTf0M1v5y9Jkq0sy9e7c03P5lYFWaPlwry1tN2wQPeqx293UnDuGk1mjyc36hLpEUdIWv8XLVc8RdcDH1GalcfpaR8A4PfoUGyaetPk+XE0eV43AVDU+EUoLFQEPDeG/PPX6LxD94qY+M+3kHjDJEOyRsu5eZ/TYcN8UCpI/HYX+eeuETh7HDlRMaRFRJKwfichK56k+4HllGblET1NN3Qo/9w1Un7bT7d/3kNWazk393P9c4UKWytc+7ThzA2PdQB4jTQ+j0PFmM7P+5z2Zfsj4dud5J+7RtPZ95EbdYm0iEgS1/9FyIon6XbgQ9RZeURPW6Zfv/vhFagcbJEsVbgPC+P4+DcM3mRxpwoq+01SIyJx6RFC8wUP6CasOXCWM3N1rx7M2H2CxGA/wjbrBt9o8ouIfmIFpWk5Btuy9HCi67bFqBxskLUyjacOZ1/v57HycqH1h08gKRVICgXapItoEy+YjEmlVDD3rs7M+HonWq3MvR0DaebpzCd/niDEz5W+Lf3p0cyH/RcTGf3RJhSSxHND2uNsa8XA1o04dDmZcR9vRpKgRzMfwlve3KuuVAoFcwe3Y8aGvWi1cG+7AJp5OPLJ7tOE+LjQN9iHHoGe7L+czOhPd6BQSDzXPxRnW6vqN16TOJQK5o7ry4xPfkEry9zbLYRmPm588sd+Qhp70bes42Hr0fMM7Rhs8LYJpULBc6N6MW3FRmQZWjXyZEyPmnV61EcZSf51P+pdh0wHpdGSsmgl/mvfAIWS7J+2UXIxDrenJlEUfZ78nQexDg3Gd8VClI722PfrivrJB7lyz3Qsgxrh/dpTyFoZSSGRseZ7g7dY1NT2bbsZODicQ8e3U1hQyNMz5+uX7fznF4O3UIwYNYwHxk41WP/x6ZMYMqw/arWGrMxsnpphfHRWTaiUCuaO6MqMz3eglbXc27k5zbxc+GT7MUL83Ogbont+eesJ3WR7t/IaxUq0GvJWLsPpjXdBqaBo22Y0cVewnTQF9fmzlBzch92j05GsbXCcr+uc1aSmkPvafFCqcHr3IwDkgnxy33mzxsPS66VOy4xHm266c0ylVDB3/EBmfPgjWq2We3u0oZmvO5/8toeQAG/6ttN1PGw9fJahYS0Nfo+BHYM5dC6WcYu+QEKiR+smRjsqzLU9YheDBocTGfUnhYWFPDljrn7Z7r2/GbyFYuSo4Ywf+1ilbYwecxcbf6o8j8PNqNeyCqDRkrFkBV4rF+tefflrBKWXYnGeMZni0+cp3L0fy9bBeL7/KgpHe2z6dMN5xkMkjHkcSaXE+3Ndu0nOLyBtwdugqZvHSl58ZQmHj50gKyuHASMf5IlHJzHmniG1tv36aQtcQJtw3mRMKqWCucM7MeOb3bqy0SGQZp5OfPLXSUJ8Xenb0o8ezbzZfymJ0Ss2687Bg9rrz8HxmXkk5RTQKaDhz6NxJ/pr+z/0G9SHfyI3U1hYxAtP6p8IZ8vuHwze+HD3yCFMHv+EwfptO7RmzTfLcXJyYODQcGbNfYKBPUbVa0y34u8de+kzoAdbDv5EUWERLz1T/oapn/78hjEDJgHw/qIVLFnxKnMWPUdmepZBOkG4FZJcxYzokiSF3/BRpCzLeZIkeQFjZVmu9p1Du7zGNYhRJ5rb/+INo6QGNginf/L39R0C273G13cIAPT68NZelVarigqrT3M7+DSMyav2TKqbd8TfjMYuOdUnug16JZp+88ftFPdF7b0e7Fblr4mo7xAAOHa0YbzKrteGQfUdgp7fiNs754cp8V89Ut8hAJD8+s7qE90mfjs+re8QANjV+tY7NGtDr2Ut6zsEAzYPNNyRqbdbY9dbn9z638bBwrb6RLfJqeSDtdzr2rA80+T+hnURZ8TyKxsa3G9Q5cgGWZaNtvBlWU4GzH+5sSAIgiAIgiAIgiAI/xk3fbtfkqTKzwwIgiAIgiAIgiAIgvCfV+XIBkmSjM/YppvDYXjthyMIgiAIgiAIgiAIDYfcwB6Fv1NUN0FkKhCLrnPhOrnsbzGzjSAIgiAIgiAIgiAIlVTX2RADDJBludKU6JIkmZ7iWhAEQRAEQRAEQRCE/6zqOhuWAS6AsfevLa39cARBEARBEARBEASh4aibFwj/+1U5QaQsyx/LshwlSdI4SZIcACRJWihJ0kZg722JUBAEQRAEQRAEQRCEO4q5b6NYKMtyriRJvYABwFpgZd2FJQiCIAiCIAiCIAjCncrczgZN2f/vAlbLsvwHYFk3IQmCIAiCIAiCIAhCw6BFbvD/NUTmdjbES5L0KTAe2CxJklUN1hUEQRAEQRAEQRAE4T/E3A6D+4AIYIgsy1mAK/BinUUlCIIgCIIgCIIgCMIdS5Lluh1ysd1rfMMc0yEAMCj5u/oOgdK0mPoOAYBdrefVdwiCCX1PLa7vEPREORGq01DKqyirwp1EHDfGNYR2WkOx3Wt8fYcgVGFQ8ndSfcdQl55ocl+Dv6b95Mr3De43qO7Vl4IgCIIgCIIgCILwn9XgexoaKDHvgiAIgiAIgiAIgiAItUp0NgiCIAiCIAiCIAiCUKvEYxSCIAiCIAiCIAiCYEJDfbVkQydGNgiCIAiCIAiCIAiCUKtEZ4MgCIIgCIIgCIIgCLVKPEYhCIIgCIIgCIIgCCZo6zuAO5QY2SAIgiAIgiAIgiAIQq0SnQ2CIAiCIAiCIAiCINQq8RiFIAiCIAiCIAiCIJggi7dR3JS67myw7rL1TRSWFkhKBcmbDhLzzg8GCfwfGoj/lCGg0aLOL+LMC6vJPx9vdgbO3VrRYtFk7EMac3LaclI2HdRl7O9Ouy9eQFJIKGytUFpbUpqRC4BNgCeXlv5A3OrN+u14DO1M0Jz7QCsjqzWcW/gVWYfOmR2HbTNfWi+fgWObplxcvIHYlZt0nwf50Hb1s/p0di380RaXUnQtjf3hL5i9HXNZuNjTdu0sHNsHkbBhF+fmf6Ff1mnjy1h5uaAtKgEgcvybNdp2Q/XSW+/z995DuLo488v/Vt30dhpPG47fhP4A5J2J49QzK9EWl+qX+4wPJ/jlBylOygDg6ucRxK/7y+ztm/ptrXzdCF0xE0t3J5Blrv3vT66u2WL2+uYyVTYUNpa0XfMctk28kDVaUrdHcvGNbwHodfgj1PlFoNEiqzUcHDL/tsRUUfuvX0Tl7I8661qNtl1RbZURAJWjLSHvT8O+ZSNkGU4/t5LsIxfKlzvZ0XrZdGyaeKEtLuXUs6vIP3u1Rnk0eXokfhP6IWu0nFvwJem7ogBo9Pgw/B8cAIAmvwibAE9K0nKM1iUqBxtCP3kKaz93JKWC2JWbSNiwy+wYalJe03dGmVUOXHq1JviVSSgsVeRExXD6uVXIGvOfgvS8pxtBL4zFLtiPQ0MXkBMVo1/WZdtiHEMDkNVajj/0jn6fXec9phdNnhwBkoQmr5Azs9eSdzrW7LyrKqsdvp2HlZcLklJB1sGzZm/TlNoqryHLpuMxqKPJMlIfdYoxju2DCPtjkcE53Bw3U6ea+53rqqxW3GcpWw5j28TLrP0fNG88Xvd0Q9bIXPtqG1c/23rLsbj2aUPzlyYgWaqQS9SoHGzIv5TA8QeXGqxv7e9OyLLpWLo5UpqZR/TMFRQnZpidv6l9rrCyoPOvr+rbiApbe7QFmWZv90a1ddyYc06uqzajnkKi67bF+vaGUC7giXvwGdMLAEmlxK65H7tCHkOdlW80fYs3H8b3gX7sDJxco3waTRlC46nDsW3qza5Wj+mvIar77V16hNBi0WQklZLSjFyOjHrN7Dxrcp45M3ctaGWzy6L3qB40eWYUyDLFSZlEz1yh/07mCJo3Ht9xfVA52xvsyxvaxseBFcBnZm9Y+Ner686G4sjRr6MpKEZSKQn7/TXS/zpOdmR5wzxx416ufb0DAI8hnQh+7SGOPbDY7AyK4tM49cwnBMy4xzDj5EwO3fUScokapa0V3Xe/y7EJSyhOzaJP1CpSNh8ySJ/x90lStx4BwD6kMW1XP8u+XrPMjqM0K49zC77EY1hng88LLiVyYMAc3R8KifDTa4h+8mOCF06s0XbMpSku5dKS77Bv2Qi7lo0qLY9+4iODBvq/wcjhg5gwZgTzF7178xtRKGn82DD29Z6FtqiUNqufxWtkDxK/222QLOnXfUYviM1h6reV1RrOv/INuScvo7Szpuv2xWTsPlGp060uy0bsyk1k7j2FZKGk048LcevfnvS/jgMQOfp1kyekui6vnsO76Do7blGtlJEyLd54mPSdUZx47AMkCyVKGyuD5U2fGUludCxRj7yHbTNfWi6ZwtGxb5i9fbtgP7xH9mBfn+ex8nah0w8vsbf7s9gF++P/4AAODp2PXKImbMsbnJr1Kc3nP2B0O/5ThpB37hrHJy3Fws2BnnuXkfjTP8ilGrPiqEl5zY2Kqb4cSBKhHz5B5Ng3KIhJJGj2OHzGh5OwfqfZ+yb/7FWiprxHq3ceN/jcLtgPC0dbDt39MqErZtLy7Sns7f4saMvvQhTGpnBk5Guos/Nx69+ekPce59Cwl8zOu6qyeuLxZWjyCgFou3YWkqUdconxhq85aqu8JmzYzdW1EYSumGl0eX3VKQYUEs0XTiBj14ka538zdapZ37kOy2rFfebQPsis/e97f1+sfd3Z13MWyDIW7o5mx1FVLKUZuRyftJTi5EyavTyRxlOGkH8podL6wa9MIvH7v0n8/m9cerWm2YIHOPXkx2bnb2qfa4tLqdhG7H/lcyRVAbK6uEbf77raOm7MOSfXVZvxusaPDyf/QjwqB5tb+i7/RrGf/E7sJ78D4D64IwHT7jLZ0eDYLhCVk91N5ZN16Byp24/SeePLBp9X9durHG1pueRRjj3wFkXx6TU+VmtynvEa0Z3kX/aZVRYlpYIWbzzMvt7PU5qRS/OFE2k0ZQgx7/5odmxp245ydW0EPQ8sr7Tsett4UPJ37Wv0hYX/hLrubJA1BbqThmShRFKpkGXDISjXDxwApa0VXF+ukGj+0gRcerRGYaXi6ufbiP9mR6UMiq6m6v6hNbzjULFBrbCyAIVuegrX3m0ovJJM0bU0wzgKyk9uSlsrKoYZ8MQ9eI3ojsJKRcrmw5VGZwCUpuVQmpaD+8AOpvYFrr3bUHAhgfxzpu/QVrUd7zG9aPz4MBQWKrKPXuTMnM8MGtMA2oJisg6dw6apt8k8/m06t29DfGLyLW9HUipQWFsil2pQ2lpSnGT+HZZbKSMlKVmUpGQBurvV+RfisfJ2rdzZUEdlQ1tYQubeU4DuuMk9eRlrX1ezvnddllelrRWNp9/FmRdW4z2ii1nxmFJbZQRJwqV7K049/Qmg21/q0gKDJHbB/lz56FcACi4mYNPIA0sPJ0pSs83aJx5Dw0j6ZR9yiZqiuFQKLifj1LEZVj5uZB+9gLZQNzIpdcsRnDoFm45VBpW9rqGqtLOmNCsPWa2rJ2u7vCqsLck6dK7K+s/C1R5tqZqCmEQA0nefpOnTI0lYvxOFrRUt33oE+5aNkFRKYt79Ud94qij/gvFRbx5Dw4hfv5OS1GzkUg2Fcak4dWxmMOIk+8j58n9HXsDKx03/962W1evnMUmlRGF566fV2iqvWQfOYN3Iw+TyhlCnNH5sGMmbDuLUPsjg87qqU805V9dlWa24z7RFJeQcv1RlLAD+Dw/i5PQP9e2j0rQcgFuOJTf6CgBWPq44tm2qqx+kylN52QX7ce6VrwHI3HOK9l++wKmyZbfaPjJoI0pSlfuhOrV13JhzTq7LNqOVjyvugzpwednPBEy/65a/z7+Z96ieJP281/hChUTzVx7k5PQP8Rxe3oawcHOg1dLHsfZzB+Dcwq/IPlx5JMD14+NGVf323qN7kbL5EEXx6UD5sQp1cJ4py7iqePQkCZBQ2lpRmpGLysGGgitJANgEeNFyyRQs3RzRFBZz+vnVFFys3OlY8Ubxf5V4G8XNqdEEkZIkNZMkaYwkSSHm5yDR7c+3CT+1hvTdJ8g5erFSEv9HBtPz4HKaL5zIuQVfAuA3sT/q3EIODZ3PwSHz8X+wP9aNTTeajLHydaPbzqX0PvoJV1b8SnFyJt6jepismDyGhdFjz/t0+N9cTj+3EgDX8LbYBnpzaOh8DvSfg2O7pjh3a1WjOK6rKu/q2DXX3e08fPfLHBgwB1mjxWdM7xpvJ2T5DLr9+TZNnxt9U3H8a2k1XFm5id5HP6HPiU9R5xSSsbvynTavu7vSbedS2n72HFa+uouV2iwj1o08cAhtSraR48SU2ioboOuVdx/ciYx/ovWfdfxuAV23LcZv0oDbGlPQ3PHErtyEpuziukFQWFCSnkPr5TPoumMJIe9PQ2FrOLIh73QsnnfpGjaOHYKw9vfAysfV7H1i5e1CUXx5Z2hxYrquoXv2Ks5dW2LhYo/CxhL3gR2w8nYxGerVtVuxC/ajz4lVdN/1Lude+hJkud7Ka2l6LpJSiWO7QAC87umKlZ/uGAp8dhQZ/0RzaOgCIke/TvOXJ1bar1Uxtc9M8ZvQT3+XvbaOnw4b5hN+ajXqvMJbGtXQENR1nXKdlbcLnsPCuPbldoPP67tOrcuyejNsArzwHtmDrhFv0WH9XGzLLkRqK5YWiyaTvjOK/JhEkCs3p3Mr1Gmew7ugcrDFwsW+dn6nCm1EbUnhTY9qqCtVlZ+6ajO2WDSZC6+vq3QhKhhS2Fji3q89ySYevWr06FBSI47oO46ua/HGw8R9+geHhs7nxKPvEfL+tBrnbey3B92j0xZOdnTa+DJdty3GZ1wfoG7OM8m/H6g2nutktYYzcz6j+6536HNiFXbB/vrHgFu99zjn5n/BwcHzOP/a/2j19qM1jut62xj4Eag8TFX4T6vyFowkSTuBcbIsp0mSNAlYCPwNvCpJ0mpZlj+qNgetzIEBc1A52tLuyxewa9mo0vPL177YxrUvtuE9uidNnxvNqac/wS28LfYhjfG6u6suUEdbbJv6UBSXavaXK05I50C/2Vh5udDuqxdI3XoEj8GduPim8WdHU7ccJnXLYZy7tSJozniOjnsDt75tcQtvS7c/3wZ0dwhtA73JOnDG7DhA12t/PW+FtWWN1gX4P3t3HWdF9f9x/DXbXWzSsHR3dyhggAGo2IGCCoKigGBLGV8b5at81Z8dWIAgqYAgIdIlsdQmu8t23Tu/P+5y2WWTDXbR99OHD7jMmTmfmXtm7syZEwG9W+HTpgFdl88CwMHNhay4sxe1jd3j3yQzKgFHTzfaLpxMRu5FUADDgeAhnVjf+SFyzqbR5v1JhN7Qi6hv19uTxP2yjajvNmBm5VDrtkG0enM82254vsLKiKOHK20/mMzBmR/la/FTkoooG2Br2dH63QmceH8Z6RExAGy55ikyoxJwDvSh41czSD10ulT7Vd6YvFrWw6N+CAef+rjYN7OXmmGAd+sG7J/+P5L+/JumL9xBg4eHc3juV/Y0R9/4gaYv3Em3VXNJ3nec5F3HMC3Wch+T1EOnOPbWj3T48kksaZkk7z6G4eJcZPoa/duSvPsY265/Dvf6IXT8egYbNz1epeV11wOv0+S523FwdebM2p2Q2we+Rt82BF3Zifrjbd3hHFxdcK8VWOQb2fLw79mSmrcMYOu1tqaxFXX+bL9pFg6uzrR652EMZ3fM7NKfw9VNZV5T8mr6/J0ceuEzLnwVV9XXVKgeZfUcB1dnrBnZ/HHldIKHdaHFaw+wdfgzFRJL4OAOmDkWat8+iMNzviL0hp4F0hx65hOazr6bmqP7krhpHxmnz2BarBXzPeW5R+y75x1wdAZLdsnrXQIllZ/KuGcMzB1jJXnnUfx7lP693r9R0BUdSdxyoNAuFK4h/oRc041thYyXUKNPa7ya1LZ/dvJ2x9HDNV8LgZIU9t2D7Zrn3bYh2258Hkc3F7oseZ6z2w5Vyu9MQK9WxP+2q9h4zjGcHKl952A2DZxKekQ0TWfdRYOJ13H8vSX4dWpKm/cnnU9bzH1FYfLeGw+O/nIF8BEw4KJ3Tv6xSmrvGWSa5rnXRROA7qZpnjEMwwPYBBRa2WAYxlhgLMBE745c5R5OTlIaCev3ENi/bZGDpUV99zvN5t57biMcmP5hgUG+wqeNJmhQB4DzYyGUIDM6gZT9J6hzzxCSdx0lK7b4Ezxx0z7c6wXjHOCNYRgcfeOHAl04at91hX2gtu23zCEzuvgm94ED29vzLtPDk2Fw+qvfClSUBA3tTPhjNwKwd/J7xY7HcK5bgCU1g8hFG/BpH15k2n8bw9md9ONHyD5jG5sgZslm/Do3zVfZkJ2QYv/7qU9X0fgp27gbFVFGDCdH2ix8lMhv1+cbT6RU26iAsgHQ/JWxpB2Nyjdw6rkykx2XRMzSzfi2Dy/dTVM5Y/Lr1ASftg3pteVNDCdHcHTG0TcMy9nIkvOuRKbFQubpM/YWWtE//UH9h4fnS2NJSWfvI+ffLPTa8ibpETH4d2teqmOSGZVgb94J4BpWwz5I2OnP1tj7jTeafpOt1UeHRoXGWvOmfvbuHOnHokk/HoNn45oVVl67LJ+Fk7cHDR+9gbPbDpV4DQQ4u/UQW4c/A5x7AxiWu0GDHXe/Qtrh/N9vi9fG4dO6PplRCWwfM6fI7Z4/ZramsHmPWV5eLerS4tWxbL95zvnzuYLOH7D1QY9dtpXAgc0u68qGyrym5C1nTj4etH53AgDONXwIHNQe02Kp8GuqS4if/eGvNL/XUHll9dw+OPl5Eb9uV4lxgO3FSfRS29vbmKWbafH6uAqJBWyVksHXdCP7TBJNnrsdJy93Wr39ELsffOt8/tEJ7Lz7FcD2AB58VVdyktIq7P4IICcpDTM7HQcXD6zpF/8QVtGK+k0uTEXeM/p1aUrQlR0JHNgOBzcXe1c4sem2aq79+IWOKLq1sHfr+ng0CLWPL+Do7kLPTa+zodtEMAw2D5uRbwBwsLUacA3ytQ0IO/m9UsWTuGkf3i3r0X3tS5gWK1E/buTMmh1Y0zKxpmWSsGkfXi3rVfjvjCUtg9bvTiAzMj5fecpbFvOOteXdqj4A6RG2bkbRP26iwcPDOf7fn8lJSi34POVg0G2F7doRu3wrh+cV7Ap0Tt57Y2wDQ84rIullT7NRlE1JlQ3ZhmHUMk3zFJACnKs+zAQci1rJNM0FwAIgaE3ju2JyktJwcHMmoG9rjr31Y760Hg1CSTtq6zcUOLg96ef6SK7dQe07BxO/fjdmjgWPhmFkRMVzePaXHJ79ZYk75hoWQHZCMtaMbJx8PfHr0pT0iGiivvu90PTu9UNIP2Y7Cb1bN8DBxZns+GTi1uyg0dRRRH27DktaJq6h/lhzLPbWGKVl61dWeN6lEb9uF+0+mkLEe0vIjkvCyc8TJy93e21mSQxHB5x8PcmOT8ZwciRocAd7jagA1hx8OzTGwd0Fa3oWAb1bFbjouwT72ZvjBV3Zyf72qCLKSIv/PEDqoVMcf29Jvn8vzTbKWzbA1mXByduDvZPO/8A6eLhiGAaW1AwcPFyp0a8NR175tlTbK29MJz9awcmPbE2r3eoE0WvTq1Ve0QCAaSHj9Bk8wsNIOxxJQO9WpB7MPwaLk48HlvRMzGwLtW4dQMKm/VhS0kt9TCwZWbSeP4GIdxfjGuqPR8NQexNe50AfsuOScKtVg+BhXdh5338IHdGj0FAzTsUR0LsViX/sxyXIF4/wmqRHxFRYeT2zdicHZ350UYfvXPyGixP1H76Wo699B9iu93XuGWIffNW7VX2Sdx/LV2lTnNjlW2k9fwLRizdhODvmO2bnuNWqQduFj7L7wbftffGh/GXV0cMVRy93smISMRwdCBzcvtq8mS2ryrqmQNHXtJavjyN2xZ/E/rwVS1pWhV9TL+b3GiqvrJ7bh7DRfe3dNEoSs2wLAT1bcvr4Wvx7tLBXLpQ3FicfD/y7NWfXfa8Rs3Qz/j1aUG/81fkqGgDbg0tCCpgm9SeO4PTntgrP8l5LnGt428a9yb1HNFzcsaZVfUUDFP2bfE5l3TP+/eLn9gfSc99H0OCOFbdjl7lzD8VO3u74d2/BrgvK6jlxK7fzW+vz3SP6H/nIVtEAnPl1J3XuGWIfZNKrZT1S9kSw/aZZpYrhwu/empXDxn5TAFt3iaaz78JwdMBwccK3Q2Mi3ltK6oETFfo74+DqzJGXv+HEwuW41w+xp8tbFvPKjIzHq0ltnGt4k30mmRp9W5N66BSWlHTSj8cQfE03YnK7ZXi1qEfK3ohSv9DNe28MXAtcXBM0+cczLhywMd9Cw+gHvA18CwQAHYDlQC9guWmaJQ352yZp19EdhqMDhoMD0T9s5Mir3xL++EiSdhwhdvk2mr5wBwG9W2PmWMg+m8r+aQttAygaBo2mjSbwio4YhkHWmSR23PESOcn53xb5tAun7f8exdnPE0tGNlkxiWzs+xj1o5hVAAAgAElEQVQBfVrT5NnbwAQMOPnJKsIfG8mGLg/bt1H79kEAnPx4JfUfupawkX0wcyxYMrI49Own9qlj6tw3lFpjbC2CLKkZ7B7/lr128ByXIF+6/jIbJ293TKuJJTWD33s/iiUlHQcPV3pve5sNXR6m+Uv34d+jBc4B3mTFnuXwS1/j4ORoj6O47YQM706DCSPAwcDMtrB/2sJCB2zpteVNnLw9MFycyDmbyp+jXyT9ZBydv3/GNgiTgwPx63Zx4KmPGRz5RQlfYeXLjivf7BhTnp7Dlu07SUxMokaAH+PvuY0brrnyordz/MM/CR3eHdNiJWnXUfZOfo+Gj1xnL6uNnryZoCs6YlqsZCemsO/x9+2D6JSnjHi3qEvnn54jeW+EvY/m37M+J27VX6Vav7xlIyc5nT5/zSfl4CnMLNtD0omFy4lfv5u2/7NNl2c4OhD13QaOvvZdvvOmsmLKOxDXucqG8kx9WVFlBGDrqHdp+er9GC5OpEfEsGfifEKHdwdsx8S3U2NavjEeTEg5cJK9k94l56ytnra0x6TBI9dR8+Z+mDlWDsz8yD6+QKcfnsHZ39t2vUxIxrNxrSKvJa4h/rR8YxwuIf65b9u+t7fUqejyeuztH2k8c0yh5aD9p1NtLTaiE2j81BgCB3fEcDA4+dEK+xtvBzdnmj5/J76dm2AYBuknYgpMvwe2t0DNZt1lm4IvKZXk3edvELutmWdrGuvoQHZ8Mode+Czf8Wjx6v0EX9XFPjhw3qlcy1NWsxNSaPd/T+Dg6mS7tm7YQ9jwYgbuLIWKKq9n1kVWye9NUdeU4qYKPlfZcG7qy8q6pha3z5eqrNqPmasTjq7OWDKybfceRcTi5ONhm8a2diCW1Az2TXmflL0R5Y6lwaTraTBhOGlHbC98HD3dSI+I4c/RL+a7Twu+uiuNn7wZ0zRJ3GSbcs/Myin39+ReN4iWb4zn3D2iex1PrOn5+9dfjIo6b/6668NCy8+5FmeVfc94jiobCloRMhqwTbcYOKAdu+7PPzNC3vMmr/5HPrJP1+gc4E2zOXfj2bgWhqMjiZv2se/xgjM11rl3CPUfvBaXYD+y484St+ov9k5+r9jvHmwDhNa8qR+YJqc+XW2/dlT078zBmR9hWqzFxtNt1Vx7pUHt2wdR575hmDk5ZJyMY8+Ed8hOSMGtbhDN595rm1bTyZHo73/nyKsFXyw1njmG0Ot74hrqT2ZUAqc+Xc2Rl7/Jd2/s3bLeWmAcUP45oKuhu+rfUO2bNvzv2LflG2m3EhRb2QBgGIYvcAvQBFtLiJPAD6ZplqogrQgZXe2/mH+zwdEltxKpbOWtbKgoa1tOq+oQpAj99pR+OtzKpnIiJaku5VVlVS4nOm8KVx3u06qLc5UNUj0Njv6y2j3oVqR/emWDYRgBwJdAfeAYMMo0zUL7fBmG4QPsBb43TfOh4rZb4hxdpmmeBUrXJk9ERERERETkH+RfMPXlVGCVaZpzDMOYmvu5qP40z2ObNKJEFzX1ZV6GYSwo67oiIiIiIiIiUi0MxzabCLl/jigskWEYHYEQoFSDIZU09WVRE5UbwLDSZCAiIiIiIiIi1VaIaZrnRtCOwlahkI9hGA7AK8CtwKDSbLSkbhSxQAS2yoVzcodcJLg0GYiIiIiIiIhcrqwljHNYHRiGMRYYm+efFuTOEnlu+UogtJBVn8z7wTRN0zCMwnZ4PLDUNM2ThlG64SFKqmw4Agw0TfP4hQsMwzhRqhxEREREREREpNLkViwUOdSBaZpFtkYwDCPaMIww0zQjDcMIA2IKSdYd6G0YxnjAC3AxDCPFNM2pRW23pDEbXgP8i1hWcH4lEREREREREbmc/Ajckfv3O4AfLkxgmuYY0zTrmqZZH3gM+Li4igYoobLBNM23TdPcYRjGSMMwvAEMw5hpGMYiYEMZdkJERERERETksmFeBv+X0xxgsGEYh7CNxzAHwDCMToZhvF/WjZY49WWumaZpfm0YRi9gIPAStukwu5Y1YxERERERERGpWqZpnsH2nH/hv28F7i3k3z8EPixpu6Wd+tKS++dV2AaaWAK4lHJdEREREREREfkXKW3LhlOGYbwHDAbmGobhSukrKkREREREREQuS9aK6KjwL1TaCoNRwHLgStM0E4EAYEqlRSUiIiIiIiIil61StWwwTTMNWJTncyQQWZp1HatJLZCF0s0FWtmqy/GoTta2nFbVIQDQa1adqg7BzszKrOoQADBCwqo6BKD6lBGAWl4pVR0CAFclnqzqEADYO29wVYdgl7Fsa1WHAFSf8trrv52rOgS7pnd+VNUhAHDgpSurOgQAEv+3rapDsPN7sE9VhwBUn/Om357ZVR2CFGGCebSqQ7Azq8n9vIeja1WHYFd97gakOiltNwoRERERERGRf53qUsF0udG4CyIiIiIiIiJSoVTZICIiIiIiIiIVSpUNIiIiIiIiIlKhNGaDiIiIiIiISBGsVR3AZUotG0RERERERESkQqmyQUREREREREQqlLpRiIiIiIiIiBTBqqkvy0QtG0RERERERESkQqmyQUREREREREQqlLpRiIiIiIiIiBTBVDeKMqmSyoaA/m1p/MJdGI4ORH66iog3f8i33HBxosVbD+HdpiHZCcnsGfsaGSdicfL3ovUHk/Fu14ioL9ZycPrCAttu/fHjuNcLZnPfxwrNu0b/tjR94U4MRwdOfbqaY4Xk3eqtB/HJzXvn2NfJOBELQP0JI6h1S39Mi5UDT37ImbU7cK1Zg1ZvPYhLoC+YJic/WcWJ//5s316de4ZQ564rMC1W4lZu58jzn1T68XBwd6HVfyfjXj8E02LlzIptHH7hs1J8M1WjxWsPEDS4A1lxSWws5Htz8vWk5WsP4F4/BGtmNnseeZfU/SdKvX1nfy/afDAZn3bhnP5iLQem/69AmnYfT8G1S20yF71c7LY2HIlh3qrdWE2T69rU5e5ujQukWb7/NO9tOABAk2Bf5lzTgdNn05j83RasQI7Fys0dGjCyff1S70OxMR2L46Vf92O1moxoVZu7OzcokOaXg1G8u+kwBtAkyJvZQ9tUSN754jhwinmLN2O1mlzXuTF392udb/lLizez5UgUABlZFuJT01n/9C1lyquk864k4dNGU3NkH5z8vFjT8I4Cy4Ov6kLbhY/yxxXTSNpx5KJi8+zTkdCZYzEcHUj48hfOvPd1vuUenVsSMmMsbs0acHLiXJKXbQDAuWYQtefPwHBwACdHEj7+iYTPS79PhXl69hP0G9SLjPQMHntoJnt27i+QxtnZiWfnTqNbz85YTSsvv/gmy35aRa3aYcx981lq1PAnMeEsk8ZNJ+p0TJniqC7njVO7Lnjc9RA4OJK5agmZ3+e/LroMvha3ISMwrVbISCf1vZexnoywLzcCg/H9z0ekf/UhmT99WWgeRo0gOi56qtiy6dGoJi1fH4dP6wb8PfsLIuYvvqj9KPU1rXt9Mtd+WOy2Nuw/wbwfN9rO2y5NuXtAu3zLX/pxI1v+Pg1ARnYO8SkZrH/+DvafOsOsRetJyczC0XDg3oHtuLJd+EXtR3GenT2V/oN7k56ewaMPzmD3zn35lnt6efDNko/sn8NqhvDd14t5dvq8cuVbXcoqgGvXzvhMtJXXtMVLSP3k83zLPUePxP3qYWCxYE08y9nZ87BERwMQ+utKco4cBcASHU3C1BlljmPDoUjmLfvTVkY6NOTu3i0KpFm++zjvrd0NBjQJ8WPOjT3YcjSal5Ztt6c5FpfEnBt7MKB57QLrGx4+JZ43QUM6Ef7EKLCamDkWDsz8iMTNB0q9HyWedw4GXX+ZjaNPMJak6FJv90IzZr3Kbxs2E+Dvx/efvFvm7UjZTX/xUfoM6kFGegbTH36OvbsKlhNnZydmzJ5Cl54dsVqtvDZ7PisWr2HE6KuY8vQEoqNs9/6fffA133z6Q4H1S+PJFx+lz6CeZKRnMO3hZ4uMY+bsx+nSswNWq8lrs9/hl8VrABhy7SAemnIfpgkH9hzksXEzyxTHlOcn0mtgdzLSM3j6kVns33WwQBonZyemzppMx+7tsZpW3p6zgNVLfqVDt7Y8+twEGjcPZ9oDz7BqydoyxSD/Xpe+ssHBoOmce9g+6gUyT5+h0/LZxC7fStrBU/YkNW8ZQE5iKpu6TSB4RA/CZ45hz9jXsGZmc2TOl3g2q4tXszoFNh00rAuW1Ixi8242527+HPUiGafP0DU379Q8edfKzXtDt4mEjOhB45m3sGvs63g2qUXoiB783udRXEP96fj1DDZ0fwQzx8LBp/+P5F1HcfR0o+uK2cT/upPUg6fw79mSoCGd2DjgccysHJwDfS7Z8Tg+/ycSN+zBcHak/TdPETCgHfGr/7qIL+rSOf3Fr5z4YDmt3nqw0OUNJo4geXcEO+56BY9GNW3f4Y0vlHr7lsxsDs/5Eq9mdfAspNwED+tCTnHl5tx2rCazV+7i3VHdCPF2Z8zH6+jbKJTwQG97moj4FBZuOsSHY3ri4+ZCfGomAEFebnx8ay9cnBxJy8rhhoVr6dsolGBvt1LvR1ExzVmzj/nXdyTEy40xn2+ib8Mgwmt4nY8pIZWFW47y4agu+Lg5E5+WWa48C4/DyuwfN/HuPVcQ4uPBmLeX0Ld5HcJD/Oxpplzdxf73z3/fx/7T8WXOr7jzrjTifvmTEx8sp+em1wssc/R0o+59w0jcdujiA3NwIOyZcUTcMYPsqDgafvcfkldtIuvv85Vj2adjOf34f6hx3/X5Vs2OTeDYyEcxs3IwPNwI//kdklf9QU5M2Y5Tv0G9qN+wLv07X0O7Tq154eUZXHfFrQXSPTj5Ps7ExTOg67UYhoGfvy8A05+bzKIvf2LRFz/RvXcXHp85kcnjnrzoOKrNeePggMc9E0l5/jGs8bF4z36X7K0b8lUmZK1fSdaKHwFw7tQDjzseJOXFx+3LPe54kOztf5SwwyWXzezEFA48+SFBQztd/H5Qkdc0K7O/28C7Y4cR4uvJmDe+p2/LeoSH+NvTTLm2u/3vn6/fzf7TZwBwd3Hk+Zv6US/Il5izqdzy+nd0b1obH3fXMu1TXv0H9aZ+eD36dLqK9p3a8OIrMxg+eEy+NKkpaQztO9L+ecnqL/n5p1XlyrfalFUABwd8Jk8kftIULDGxBL7/Lpnrfyfn2Pnymn3wEKn3PgCZmXiMuBbv8feT+PRzAJiZWcTddV/ZD0Yui9XK7KVbefe2/oT4uDPmvyvo27QW4cG+9jQRZ5JZuH4vH94zCB93F+JTbGWvc4MQvho3BICzaZlc88YSuoeHFpqPabWWeN7E/7aL2GVbAfBqUZc2Cx7h916TS70vJZ13de8bRuqhU3g1DS71NgszYthgbrnhWqY/X/zLC6kcfQb2oF7DOgzpegNtO7biqXlPcNPQuwuku3/SXcTHJTC0+40YhoGv//l79J9/WMEL08r3/dniqMuVXa+nbcdWPD1vKqOH3lUg3QOT7uZMXDxDLoijXoM6jJ14J7dcfS9JZ5MJCPQvsG5p9BzQjboN6zC8x0207tCSaXMe446rxhZId+/E24mPS+C6XjfniyPyZDTPTJzFbeNuLlP+Ipd8zAafDo1IOxpFRkQMZraFmO9/J2hI53xpAod0IvKrtQDE/rQJ/16tALCmZXJ28wGsmVkFtuvo4UqdB67m2H++LTJv3w6NSDsaTXpu3lGF5B00pBOnv/oVgJifNhGQm3fQkM5Eff87ZlYOGcdjSTsajW+HRmTFJJK8K/ftQWoGqYdO4RoaAEDtOwZz7M0fMLNyAMiOS7okx8OankXihj0AmNkWkncdxa1mjSKPS1VL3LSP7MSUIpd7NqlN/PrdAKT9fRr3OkG4BNludEJv6EWXZS/SbdVcmr90HzgYBda3pmWSuPkAlszsAsscPVyp+8BVHP3PohLj3B2ZQB0/T2r7eeLs6MCVzWuy9u+ofGkW7TzO6Pb18XFzASDA03bj7ezogIuTIwBZFiumWTFNsXZHnaWOrwe1fT1sMTUJZe3h/G+fv9t9ilFt6+Dj5myLyaP8DwMF4jgRR50aPtQO8MbZyZEr2zZg7b6iW5/8vOMoQ9oWbIFRWkWdd+71Qmj/+TS6/jKbTj88g0ejmoWuf3bbIbJiEgtdFj51NMfe+gFrRsHrTEnc2zYhK+I02SeiIDuHs4t/w3tQt3xpsk/FkHngGFgvKAPZOfZrhYOLM0YhZfliDB7an0Vf/gTAX1t34ePrTVBIYIF0I8eM4J3XbK2iTNMkId52XBo1DWfjb5sB2LhuM4OG9itTHNXlvHFs1Axr1CmsMZGQk0P2htW4dOqZP1F62vm/u7pBnvycO/fCGhOJ5cSxYvMxE+OL/E04JzsuiaS/DmNmWwqsf0mvacdjqRPoQ+0aPrbztl04a/dEFJn+578OMyS39UK9ID/q5V6Hg309CfByJyGl5AqO0rhiWH++/cJW6bN96058fLwJLqTsntMgvB41ggLYvHFbufKtLmUVwLl5MywnT2M5bSuv6StX49orf3nN2v4XZNoqO7L27MUxKKhceRZm96l46gR4UzvAy1ZGWtVl7YH8lbqLth1mdOfG+LjnHhOvghUsK/aeoGfjMNxdinjHlZFS4nljyVNR7ujhmvf0pN74a+iybBbd1syj4ZSRFKa48841LIDAwe059enqwuO7CJ3atcbXx7vkhFIpBgztww9fLQVgx7bdtt++4IL3wNfffC0L3vgQsP32JcafrdA4Bg7tyw9fLSlzHCNvG8FnC78m6WwyAPFxCWWKo9+Q3iz+ehkAu/7cg7ePF4GFxHHtTVex8I3/KxBH5MkoDu07jNVqLVP+/yTWy+D/6qjYygbDMPyKW14WrqEBZOa+GQHIPH2mwA+Ka1gAmadsaUyLFUtyGs4BxV+4G0y9iePzf8KaXvQDQuF5568pdAsLICNP3jm5ebuG+pNxKu78upEF43arE4R3qwac/fNvADzDw/Dr2owuP79Ap++exqeQJqaVdTzOcfLxIPCKjsSv21Wq9NVRyt4Igq+yvRX3aR+OW+0gXMMC8Gxsa22y5eqn2DTwCUyLlbAbel/UtsOnjiZi/mIsxZSbc2JSMgj1drd/DvF2IyY5/811RHwKEQmp3PHpem77v3VsOHL+wT8qKZ2R/1vLkPkruLNro3K3agCISc0gJM92QrzdiE3N33IhIiGV4wlp3PnlZm7/4g82HIu7cDPljyMpjVBfz/Nx+HgQcza10LSnE1I4nZBClyLecF2svOdd81fu48D0//HHFdM4+OwnNJ97z0Vty7t1A9xq1iBu5faSExfCKaQG2ZHnj29OVBzOIaWv6HMKC6ThkrdovP5D4t77psytGgBCwoKJPHW+KXDk6WhCw/K/sfPOvSGePO1Bflr9BW8vfInAINv1Z9/uA1x59UAArrx6IN7eXvZWDxejupw3DgFBWM/E2j9b42MxahR8OHO9cgQ+b36Kx60PkLbwDds/urnjNuJm0r/+qED64lz4m1CSS35NS0ol1O98K6gQX89izttkTscn06WQCrxdx2PItlipU6OQ1ntlEBoWTOSp8w/5UYWU3byuvX4oP323rNz5VpeyCuAYFIgl5vy2rbGxOAYVXeHicfUwMv843+rGcHGhxvvvUuO9t3Ht3bPI9UoSk5ROqI+H/XOIjzsxSen50kScSSbiTDJ3fLCS2/67gg2HIgtsZ/nu4wxtVbdUeRZ33gQN7UyP9a/S/pOp7J00H4CAvm3waBjK5iHT2TTgCXzaNsCvW/OL2U2aPn8Hh577tGAlsFx2QkKDiTp9/rcv6nQMwQV++2zXvQlTH+DblR/zn/dnUyPo/L33FVcP4Pu1n/LaB7MJrVm2li4hoUFEXhBHSBFxTJz6AN+u/D9eyxNH/fC61A+vy2eL3+eLpQvp1b87ZREcGkh0ni6QMZExBIXlv5Z45cYx/ol7+fSXD5i74Pkyt6QQuVBJLRviDMNYaRjGPRdT8WAYxljDMLYahrF1cfrF9XcuC6+W9XCvH0Lcz1sqPa+iOHq40vaDyRyc+RGWFNsPseHkiLO/F5uHzuDgc5/Q5r+PXNKYDEcHWr47kRPv/0xGRNn6WlcHR9/4AScfT7qtmkude4aQvOsYpsVKQO9W+LRpQNfls+i2ai4BvVvhXq/0PwpeLevhUT+E2AosNxaryfGEVN6/qQdzrunIc8t3kJRhe/sY6uPO13f148f7BvLT7pOcSa347gyFxmSaHE9M4783dmL20NY8v3IPyRkF34heKst3HmVQq3o4OpS/YVXe8w6rFb9OTWnz/iS6rZpLi5fuwyX4In4sDYMmz97GwWf+r9xxlVVOZBxHrnqIvwfch9/1A3GsUeH1vfk4OTlSs1Yof27+i2sG3MSfW3Yy/blHAZj19Kt07dmJxWu+pGuPjkSejsZiqZx68+p03mQu/56kh8eQ9ul7uN1wGwDuI+8kY/HXkJFewtrnFfabUJLqeE07Z/lfhxnUpkGB8zY2KY0ZX6zl2VF9cChna5yyuvb6Ifz4bfnGNymt6lRWz3G/YhDOzZqS8tn5cURibryJM/c+QOKzL+Az4SEcaxbeyqsiWKwmx+OTef/OAcy5sTvP/bSZpDyVXbHJ6fwdc5bujcJK3FZJ503sz1v4vddk/rrzZcKfGA1AjX5tqNG3Dd1WzaXbyjl4NqqFR8PSV2YH5o4ZlbzzaKnXkcubo5MjYbVC2L55JzcMup2/tu7i8WcmALD2l/UM7DicEf3G8Puvm5n95jOXKI7bcuOYCICToyP1Gtbh9hH38+gDM3j+1SftlRMVzcnJkdBaIezYspsxV9zDzm27mfR04V2bRS5WSWM27ANeA24G5hmGsR74HPjBNM0i755M01wALABYHTIqXzVxZlQ8rnma9LvWrEFmVP63d5mR8bjWqkFmZDyGowOO3h5kxycXGaRvpyb4tG1I9y1vYTg54hLoS/tFT7P9+mfzb7fQvPM3S8qIjMctT95OuXlnRiXgVut8TaBr2Pm4DSdH2ix8lMhv1xOzdPP5bZ0+Q8wS2+ek7YcxrVaca3iTfeb8vlTG8Tin6Sv3k3Y0ipMLlpaYtjqzpKSz95H59s+9trxJekQM/t2ac/qr3/j7xfyDZgUN7Uz4YzcCsHfye0UO8OeXW256bXkTw8kRw8cXl2HjyFo6v9D0wV5uRCWfL/bRyRkF3lyFeLvTqqYfzo4O1PLzoJ6/F8cTUmkVdv6hMdjbjUZB3vx58gyDm5bvBjDY043oPG/eopMzCPLM300i2MuN1qG+tph8Pajn78nxxDRahl78W+oi4/DxICrPG9HopDSC87R0yGvZjmNMG9613HleeN45ermTk5TKpoFP5E/oYNBtxRwAYpdv5fC8rwvZGjh5ueHVrA6dFj0FgEuwH+0+nsJft79U6kEic6LP4JznjYFTaCDZ0WeKWaOI7cTEk3EwAo/OLe0DSJbGbfeM5qbbbGNB7Ny+h7BaIfZlYTVDiIrMX+mYEJ9IWmo6yxbb+rov/eEXRt16HQAxUbGMu8PWH9rD050h1wwiOank686Fqst5Y42PxSFPSwaHgCDMPC0dLpS9YTWe900i7W1wbNwc5259cb/1AQxPLzCtkJ1F5rLvCl23qN+EEhlGxV7TvPxw6TGarN8LH8wy2MeTqDxd2KLPphZ93v51hGnX5X9DnpKRxcMLl/HQkE60qRdS6Hqldfs9N3Hz7TcAsHP7bsJqnX9YDC2k7J7TvGUTHB0d2bVjb7nyh+pTVgEssXE4Bp+vaHIICsISW7BVmkunDnjdfitnHnoEss9XIlvjbGktpyPJ2v4Xzk0aYTl9+qLjCPZxJyrpfPei6KR0gn3c86UJ8XGnVe0atmPi70W9Gt4cj0+mVS3bvc0ve47Tv1ktnB2Lr2C+mPMmcdM+3OsF4xzgjWEYHH3jB07938p8aWrfdQW1b7W1ztp+yxwyowtvhu7XpSlBV3YkcGA7HNxcMJzdcfQKwpJS9PVBqpdb7r6RG28dAcDu7XsJrXn+ehRaM5iYC64fifFnSUtNZ8US20CMy39cyY23XGtblnC+O8U3n/zAY089fBFxjGRkbhy7tu8l7II4oouI45fcOJb9uIobbhkOQFRkDDu37SEnx8Kp46c5dvg49RrWZfdfJV/rRt15PdeNuQaAPTv2EZKndUZwWDCxkfmvJYnxZ0lPS2f1Uls38pU/rWHEzVeXer//LSqqC/S/TUmvFrNN01xsmuYYoDbwKTAKOGkYRpmmN0jefhiPhmG41Q3CcHYkeEQP4pZvzZcmbvk2wkb1AyDomm4krN9T7DZPfbSCDW0fYGPnh/jz2qdIO3K6QEUD2B74PRqG2vMOHdGD2Avyjl2+lZqj+gIQfE034nPzjl2+ldARPTBcnHCrG4RHw1B7E78W/3mA1EOnOP7ekvzb+nkLAT1tozZ7NAzDwdkpX0VDZR0PgIZTR+Pk7cGhGR+WmLa6c/LxwHC29YWtdesAEjbtx5KSTvy6XYRc3dU+8KaTnydutQOJ/XkLmwY+waaBTxT7kHjyoxX81nYc6zs/zJZrn8ZMiiuyogGgZZgfxxNSOZWYRrbFyvJ9p+nbKP/bk/6NQ9l63PZwmZCWSURCCrX9PIhOTicjt59oUkYW20/GUz+g/DXULUN9OJ6YxqmzuTEdjKJfeP43of3Dg9l60laBlZCeRURCKrV83QvbXNnjqB3I8bgkTsUnk51jYfmOo/QtZMTxozFnSUrPpG3d8vctvvC8s6Skk348huBrzo+R4NWiHlhNe3koqqIBICc5nV9b3Mf6zg+zvvPDnN126KIqGgDSdx7EpX4tnGuHgLMTvlf3IWVVCQMK5nIKrYHhauvz7ODjhUenlmQdOVnqvAH+74MvuarfaK7qN5pflq7h+tG2m412nVqTnJRCbHTBh5VVy3+lWy/bODE9+nbl7wOHAfAP8MMwbM3A3Z8AACAASURBVG+qxz9yD19/+v1FxXJOdTlvLH8fwCGsNg7BoeDkhHPPAWRt/T1fGofQWva/O3fohiXS1jc95akJJD14E0kP3kTmkm/IWPRpkRUNUPRvQkkq/JqWklBkRQNAyzpBuedtku28/eswfVsUbOp+NCbRdt7maWWRnWNh8kcruLpjYwa3aXhR+1mYjz/4gqF9RzK070iWL1nNDTfZbvzbd2pDclIKMYWUXYDhNwzjx0UV06qhupRVgOz9+3GsUwvHMFt5dR80gMwN+curU+NG+E6ZTPzUJ7Emnh+DxvD2AmfbGD2Grw8urVvlG1jyYrSsGcDxM8mcSkixlZHdx+nbtFa+NP2b1WbrMdtDVEJqJhFnkqntf37fl+06ztDW9UrMq6Tzxr3++Qc379YNcHBxJjs+mbg1O6h1Sz8cc8cjcg31xznQh5P/+8V+3hRV0QDw94ufs679eNZ3fphd97+OmZ2uiobLzGcLv+H6Abdy/YBbWfXzrwwfNQyAth1b2X77YgpW+q/9ZR1denYEoFvvzvx90NayJe+4CgOG9OHIwdK3ePls4ddcN2AM1w0Yw6qf1zJ81FUlxrEmTxzde3fm8EHbNX7l0l/p0rMDAH4BvtQPr8vJiNINgv3Vh4u4efBd3Dz4Ltb+vI6rR9oGam3doSUpySnEFRLHb79soFOP9gB06dWRIwePlXq/RYpTUssGe5vI3JYMXwFfGYbhC4woS4amxcrBaQtp98WTGI4OnP58DakHTtLg8VEk7zhM3PJtRH62mhZvPUS3TW+Qk5jC7vtfs6/ffctbOHl7YLg4ETi0M3+NfiHfzA0l5X1g2kI6fDE9N++1pB44SfjjI0nacYTY5ds4/dkaWr31ED03vU52Ygq77reNVp964CTRP26kx7pXMHOs7J+6EKwmfl2aUnNUH5L3RtBt1VwA/p71OXGr/uLU52to+do4uv/6MtasHHZPeOeSHA9Lcjr1J91A6sGTdF5pi+nkwmVEVsDAR5Wh9bsT8O/RAucAb3pvf4fDL32NQ+5AWyc/Xolnk1q0fGM8mJBy4CR7J9mmkko9eIq/53xJxy+fBAcDM9vC/mkLyThZ8Ka015Y37ccpeGhn/hz9YqlnLjjHycGBqYNaMe7rTVhNk+Gt69Ao0Jt31u2nRagf/RqH0qNBEBuPxXL9B2twMAwm9WuBn7sLG4/F8uqaPRgYmJjc3jmcxkHl79/s5ODAE/2bMf67P20xtaxFeA0v3tn4Ny2CfegXHkyPejXYGHGG6z/egKNh8EjvJvjlDuRVUZwcHZh6bVfGLVyJ1bQyvFNjGoX4886K7bSoVYN+uQ8wy3baBoY89xBbVkWdd7vGv0nzuffScNL1GE6ORH//Oyl7C95kN545htDre+Lo7kLv7e9w6tPVHHn5m3LFBIDFStSz86n74fMYDg4kfrOCzEPHCXrkVtJ3HSJl1R+4tW5MnfkzcPT1wmtAF4ImjuHI0PG4htchZPq9tkEJDYMz7y8i82DZHhAA1qxYR//BvVi7dTHp6Rk8/vBT9mVL1toqJQDmPvsar85/kadenMKZMwk8/pAtXbeenZgycwKYsHnjNp56fFaZ4qg2543VQtoHr+P15Evg4EDWmp+xnjyG2+i7sBw+QPbW33Edeh3OrTtiWiyYKcmkvjX7orNxbNa60LJ5rmXcyY9X4hLkS9dfZuPk7Y5pNak7dhi/93700l/THB2YOqIH4/77M1aryfAuTWkUGsA7y7fSonYQ/VraHhCX5Q4Mmfe8/WXHEf48EkliagY/brFNo/bc6H40q1X+wYhXr1hH/8F9WLdtKenpGTz20PlpG3/+9et8s1BcPeJK7hg9vtx5QjUqqwAWK0mvvkHAq/PAwYH0JT+Tc/QYXvfcRfb+A2Ru+B2fBx/AcHfH//lnbKvkTnHpVK8evlMm268lKZ98XubKBidHB6YO68i4//vVdm1v35BGwb68s3oXLWoG0K9ZLXo0CmXj4Siuf2spDg4Gkwa3wy/3wf9UQgpRSWl0LKE7kENgXWoOLv68Cbm6K2Ej+2DmWLBkZLFrrO1eKP7XnUQ2qUXnpbZZqiypGewe/1aBQbmLOu9K282ptKY8PYct23eSmJjEwBG3Mv6e27jhmisrNA8p2q8rN9BnUA+Wb15ERloG0yc+b1+2aPUnXD/ANivTK8+/xdy3n2XaC5OIj0vkyYm2mVxuvW80A67sQ47FwtmEs0yb8Fw54ujJL5u/y43j/Ha+W/0p1w0YkxvHm8x9+1mmvzCZ+LhEpk+0vSxdv2Yjvfp3ZfG6L7FarLz07Ov5Wl2U1vpVG+k1sDs/bPySjPQMnpl0/rf88xX/4+bBthky3nhxPs+/OZPHnptAwplEnplk+/1r0bYZryychY+fN30G9+SBKfcwst9tZTom8u9kFNckxDCMx0zTLNfcLxd2o6gqFqqmL+mFHKkWh8NuQPRXVR0CK0JGV3UIAPSaVXAKuapiZl2avr4lMUJK7mN7Kawft6OqQ7Cr5VX0zCmX0lWJF9fqobLsnTe4qkOwy1i2teREl8DW38rXpaCi9Ppv55ITXSJN77y4wTUry4GXqsdDX+L/yjdzRkXye7BPVYcAwPpH9ld1CAD023PxlYyVyTmw/C2H/imaB3cpOdElYlaT+3kPx4qfYays/oxcXz0etirJ8LpXV48vvRg/HF9c7b6DYrtRlLeiQURERERERET+fco8HLxhGAsqMhARERERERER+WcodswGwzACiloEDKv4cERERERERETkclfSAJGxQATkG/DAzP1c+sm/RURERERERC5D1qoO4DJVUmXDEWCgaZrHL1xgGMaJyglJRERERERERC5nJY3Z8BrgX8SyeRUci4iIiIiIiIj8AxTbssE0zbcBDMMYCSwzTTPZMIyZQHvghUsQn4iIiIiIiEiVqS7TnV5uSjsbxczcioZewEDgA2B+5YUlIiIiIiIiIper0lY2WHL/vApYYJrmEsClckISERERERERkctZSQNEnnPKMIz3gMHAXMMwXCl9RYWIiIiIiIjIZcmqbhRlUtoKg1HAcuBK0zQTgQBgSqVFJSIiIiIiIiKXLcM0K72WRtVAIiIiIiIi/1xGVQdQmYbVHVbtn2mXHl9a7b6D0najEBEREREREfnXuQQv6P+RNO6CiIiIiIiIiFQoVTaIiIiIiIiISIVSNwoRERERERGRIlirOoDLlFo2iIiIiIiIiEiFUmWDiIiIiIiIiFQoVTaIiIiIiIiISIXSmA0iIiIiIiIiRTDR1JdloZYNIiIiIiIiIlKhVNkgIiIiIiIiIhVK3ShEREREREREimBVN4oyUcsGEREREREREalQqmwQERERERERkQpVYjcKwzCcTNPMyf27F9AMOGKaZnxlByciIiIiIiJSlUxT3SjKotiWDYZh3AlEG4Zx0DCMocBOYC6wwzCMmy9BfCIiIiIiIiJymSmpG8WjQFPgSuBLYLBpmgOBTsC0olYyDGOsYRhbDcPYumDBggoLVkRERERERESqv5K6UVhM04wD4gzDSDFN8zCAaZrRhmEUuZJpmguAc7UManMiIiIiIiIilyXNRlE2JVU2HDcMYzbgDew3DOMVYBEwCIis7OBERERERERE5PJTUjeKW4Ek4CRwLfA7tu4TwcCdlRqZiIiIiIiIiFyWim3ZYJpmEjA7zz99m/u/iIiIiIiIyD+eqW4UZVJSy4YiGYahkR9FREREREREpIBiWzYYhhFQ1CJgWMWHIyIiIiIiIiKXu5IGiIwFIrBVLpxj5n4OrqygREREREREROTyVVJlwxFgoGmaxy9cYBjGicoJSURERERERKR6sJoas6EsShqz4TXAv4hl8yo4FhERERERERH5Byi2ssE0zbdN09xhGMZIwzC8AQzDmGkYxiJgwyWJUEREREREREQuK6WdjWKmaZrJhmH0AgYCHwDzKy8sERERERERkapnXgb/V0elrWyw5P55FbDANM0lgEvlhCQiIiIiIiIil7PSVjacMgzjPWA0sNQwDNeLWFdERERERERE/kVKmo3inFHAEOBl0zQTDcMIA6ZUXlgiIiIiIiIiVc9abTsqVG+lqmwwTTMNWJTncyQQWVlBiYiIiIiIiMjlS10hRERERERERKRClbYbhYiIiIiIiMi/jrpRlI1aNoiIiIiIiIhIhVJlg4iIiIiIiIhUKHWjEBERERERESmCaaobRVmoZYOIiIiIiIiIVChVNoiIiIiIiIhIhVI3ChEREREREZEiaDaKslHLBhERERERERGpUKpsEBEREREREZEKpcoGEREREREREalQGrNBREREREREpAimxmwoE7VsEBEREREREZEKVaqWDYZhBAG1AQtwxDTNlEqNSkREREREREQuW8VWNhiG0QJ4A6gP1AW2A8GGYfwKTDRN82ylRygiIiIiIiJSRUxT3SjKoqRuFAuBB03TbAT0AvabptkA2AB8UNRKhmGMNQxjq2EYWxcsWFBx0YqIiIiIiIhItWcUV0tjGMYO0zTb5vn8p2maHXL/vs80zealyEPVQCIiIiIiIv9cRlUHUJk6hfWu9s+0WyPXVbvvoKQxGw4bhjETWA1cD/wFYBiGMxpcUkRERERERP7hrHp/XiYlVRjcDXgD04AMYGLuv3sAd1RiXCIiIiIiIiJymSq2ZYNpmonA44X8+1lgU2UFJSIiIiIiIiKXr1JNfVkYwzAWmKY5tiKDEREREREREalONBtF2ZQ09WVAUYuAYRUfjoiIiIiIiIhc7kpq2RALRJB/dFEz93NwZQUlIiIiIiIiIpevkiobjgADTdM8fuECwzBOVE5IIiIiIiIiItWDZqMom5Jmo3gN8C9i2bwKjkVERERERERE/gGKrWwwTfNt0zR3GIYx0jAMbwDDMGYahrEI2HBJIhQRERERERGRy0pJLRvOmWmaZrJhGL2AgcAHwPzKC0tERERERERELlelrWyw5P55FbDANM0lgEvlhCQiIiIiIiJSPZiXwX/VUWkrG04ZhvEeMBpYahiG60WsKyIiIiIiIiL/IqWtMBgFLAeuNE0zEQgAplRaVCIiIiIiIiJy2Spp6ksATNNMAxbl+RwJRJZm3aUhN5UtsgpWqh29BKxVHcAFhkR/UdUhsCJkdFWHAMCD1sNVHYKdm6NzVYcAQGR6fFWHAMBnbu2qOgS7I87V47u5/b1OVR0CAC3v+KiqQ7Ab6dWsqkMAYFB69bjSj0rdVtUh2J3+9pGqDgGAlmM+qOoQAHjYo2VVh2D3n5QdVR0CAB84t6jqEACYYB6t6hDy2RezuapDqDay445UdQh2OWs/q+oQbM4mVnUEdu73vFzVIVQqq1k9uylUd+oKISIiIiIiIiIVSpUNIiIiIiIiIlKhqkvvAhEREREREZFqp7rO9lDdqWWDiIiIiIiIiFQoVTaIiIiIiIiISIVSNwoRERERERGRImg2irJRywYRERERERERqVCqbBARERERERGRCqVuFCIiIiIiIiJF0GwUZaOWDSIiIiIiIiJSoVTZICIiIiIiIiIVqsq6UbR48Q6CBrbHkp7JzgnzSdp1rEAanzYNaPvGOBzcXIhdtZ29T34EQLOnxhB8RQes2TmkHYtm58R3yUlKw9nfiw4fTMK3XTgnv/iVvdP/V2jeTfPkvXvCfJILydu7TQNavTEOx9y8D+Tm7eTnSdsFE3GrE0TGiVh23Pc6OWdT8e/RgnYfPUb68RgAYpZs5siri/AID6PNgon27XrUC+bQvK+JWPBzvvyav3gHgQPbY03PZFcxx6N17vGIW7WdfbkxhVzTlUaP3YhXk1psHDKDpB1HAHD296Jd7vE49cWv7CvieFS1euOvIeyGXgAYTo54Nq7F2hb3kpOYmi9dy9fH4d+jBTlJaQDsnvAOKXsiSp1P8DXdCH/sRjyb1GLzkCftx8mnfTgtXh7LD2RiYPDmSwtYsXRtkduZMesx+g7qSXpaBlMnPMPenQcKpHF2duKpOY/TpWdHTKvJq7Pe4ZfFqwEYOnwQD08Zi2ma7N9ziEcfmFHqfcjriRcm0XtgDzLSM5g58Xn27TpYII2TsxPTZz1Kpx4dMK0mb855l5VL1jLy9uu46a4bsFgspKWm89yUORw5eKxMccya+ySDruhLWloGE8ZPZeeOvfmWe3p5svjnT+2fw2qF8s2XPzJj2ixuuuU6nn7+caJORwPwwX8/4ZOPvyk0n9KWk3OavngnNW/uz5qGd1zU/tS5+0rqjh2GR4NQ1ja/l+z4ZACChnQi/IlRtDfBzLHw+zOfELWl4DEH6PHcbdQd0I6c9EzWTlpA3O5jBdJ0fnwkTW7shauvJwub3ltgeYNhnbliwUS+HTaTuJ1HL2ofADbsO86879djtZpc1605dw/skG/5S99vYMvfpwDIyM4hPjmd9bPusS9Pycji+rlf0L9VA6bd0Pui87/QU7Mep9+gnmSkZzDl4afZs3N/gTTOzk48M3cq3Xp2wmq18sqLb7Ns8Spq1g5j3htPE1DDn8TEJCY/8CRRkTFliuPap++gaf92ZKdn8dVj8zm951j+GNxcGPPOI9SoF4xpMdm7ahvL5n4BgF+tQEbOux/PAB/Szqbw5SNvczYqvkAe1aWs/paTSk6OhelPvMCmjduK3M6cl2Yy+Ip+pKenM/7+J9i5Y0++5V5eniz95XP755q1Qvnqix+Y/sSLvDjnSXr36QqAu7s7QUE1qF87f1krjQ17I5i36Ddbee3egrsHd8q3/KVF69hy6CQAGVk5xKeksX7u/QB0mPgWjWrWACDM35vXx1590fnnVV3KKkC/Z2+jQf92ZKdn8sujC4gp5FrSY8pIWtxgu5a83fz8tcS7Vg2ueHks7gHeZCSmsmzifFIKKa+l8ezsqfQf3Jv09AwefXAGu3fuy7fc08uDb5Z8ZP8cVjOE775ezLPT59Gle0eenvU4zVs24aF7H2fpjysKzaO6nDeLrJlYcizMnvkqf/6xo8jtTH/xUfoMsv0GT3/4OfbuKvxeYMbsKXTp2RGr1cprs+ezYvEaRoy+iilPTyA6KhaAzz74mm8+/eGi9kMu3oxZr/Lbhs0E+Pvx/SfvVmpeGw6eYt6SrbZrWqdG3N23VYE0y3cd471VO8GAJqH+zBlt+619bdmfrDtgu96N7d+GK9vUL3scR2KYt2o3VtPkujZ1ubtb44Jx7D/Nexts5bdJsC9zrunA6bNpTP5uC1Ygx2Ll5g4NGNm+7HH8E2g2irKpksqGoIHt8GgQxq/dHsGvYyNazbuX34cWfOBqNe8edj26gMRtf9Pps6kEDWhH7Oq/iPt1Fwde/BzTYqXpjFsInzCCAy98hjUzm4NzvsK7WR28mtUpNO/Age3wbBDG+m6P4NuxES3m3csfheTdYt497H10AWe3/U2Hz6YSOKAdcav/osHDwzmzbjfH3vyR+g9fS4OHh3Pohc8ASPxjP9tvnZdvO2mHI9k0cKrtg4NB3x3ziV66pUBMHg3CWJcnpk1FxLQ7N6aOeWJK2X+Cv+5+lZYv3ZcvvTUzm0MlHI/qIOKdn4h45ycAAq/oQL37ryry5uLgs58Qs/iPMuWTuv8EO+5+heYXHKeU/Sf444ppjM8+RFBIDX5c8zmrl6/DYrEU2EbfQT2p37AOg7tcR9uOrXh23jRGDrmzQLpxk+7mTFwCV3a7AcMw8PP3AaBewzrcP/EubrrqHpLOJhMQ6F+mfek1sDv1Gtbh6u4jadOhJTPmPs6YYQUfWMc+cifxcQlc23M0hmHgmxvH0kXL+frj7wDod0UvpjwzkXG3TLroOAYN7kPD8Pr/z959x1VV/w8cfx32BpkXEEXBvcWJCiKoYO6dI0uzslJTc2em5ci++bX6tqys7Gc50syFWxRXLhD33kzZ4wLCPb8/Lly4XHYat/o8v48eX+89n3M+b879nPU5n0GHNr3wadeKFSvfIzhwuFaazIxMAroN1Hzef3gzO7fv1Xz+fcsu5sx8v8K8qlJObFrVx8jWssp/D0DKqWsk7DtHuy3van2fdOQCCbvPcNvYGPsmHgR9OZmN3WfprO/RoxW29RSs7zoD57ZedF32Ilv7vaf79+w/x6Uf9jEy/D86y4wtzWgxvjdx525W62/IV6lYtiWcr17rh4utJaP/uxn/Zp54Kew1aWYO7KL59y/hF7j66LHWNj4PPUXb+q7Vyr+k7kFd8axfhx4dBtDapwXvfzSPwb1f0En3xvSXSUxIIrDjwILjxhaAeYumsWXDTrZs2E7nbu2ZuWAyM15fUOU4GnVvjWM9BR91n0adNt4MWjKBzwfqbufINzu4feIyhsaGTFz3Do26t+Ja2Hmemzeas1vCObf5CF6dmxE8ayQbpn+hs76+lNXhmWdp1qwRa376lI5te5e6jZ69/PHy8sSnVSDt2rfm41WL6BkwVCtNRkYmfr79NZ8PhW9lxzb1MTx/zhLN9xNfG0vLlk2r/Hfkq1Qs2xTGV28MxMXOitH/2YB/8/p4uRYrr4OLKrx+OXyeqw8TNJ9NjY3YOPv5KudbGn0pqwCeAa2w81Twvd8MFG286LHkRdYPeE8n3e395zj/4z5ePKx9LvF7ZxRXNh/l8q/hePg2peuc4ex+q+oPWAFB3fD0qotfu+do064lSz5+hwE9R2ulyczIIsR/mObzzoMbCN1+AIDohzHMeGMBr75ZfqWAvhw3U+Q7NGzqzX+/WcpzXYaXug2/QF/q1vcguOMQWvk0590VsxkZMl4n3avTXiLpcTIhnYdqXYMBQn/fxwdzdc//wrMzsE9PRg3pz7z3n+1+z1epWLb9FF+9FISLjQWjvwzFv0ltvJztNGnuPU5jzeGL/PBqb2zMTUnKUAJw5OpDrkQnsuHNvjzJz2fCt/vo0tANKzOTasQhs2z/Bb4a3gkXa3NGrw3H31uBl6N1URxJGaw5eYMfRnfBxsyEpMwcAJyszFg7pismRoZk5eYxZE0Y/t4KnK3N/uTeEf5taqQbhUtwOx5tOgJAytmbGNlYYFrsAAQwdbbDyMqclLPqm+1Hm47gEqJ+0/H4cBRyvqpg/RuYualvSPKzckg+dY38nCdl5u0U3I7ogrxTC/I2KZG3SUHeqQV5R286glNB3s7B7YjeoF4/esMRnEO0376Ux6FbC7LuxpH9UPum3qVETMbl7I/iMRXuj8wb0WTeitHJLz8rh5RT11CVsz/0jWJQF2J/O1aldQwsTGm66jU67F5Cx/3LcQou/TfJvPGIrFL2k0qZqylPpqamyOXUXAYG+/Pbhl0AnD97EWtba5xcHHTSDRnVn68/UbckkWWZ5KRUAIaPGcS6NRtJS1W/SUl6nFyFv7RIQG8/tm9Ut46JOncJaxsrHJ114xg4si/ffbZWE0dKQRyZGVmaNOYW5tUe9Cb4uUA2/LIVgLNnzmNra4OLi1OZ6et7eeLo6MCJ42eqlV+hcsuJgUSDhWO4sXid1tfGDta0/G46HXYvpcPupdi2b1Tq6ukX75L9IEHn+/ysnKJtmZtCGeXEs5cP1389CkD8uVuY2lhiUeJ4LlyWFZ9S6jbazxxK5Bc7yj2Xlefi/Xg8HG2p7WCDsZEhvdt4E1bKG9FCoRE3CG7jrfl8+UECSelKOjd6OpWUQSH+/LZxBwCRZy9gY2uNk4ujTrqhowbw5SdrgMLjRr1/vBvV50T4KQBOhJ8mKKR7teJo1suHs1vCAbgfcRNzawusnbR/myfZudw+oW6dk/8kn0eX7mCrUB9bLg1qc+v4RQBunbhE054+FeZZ02XVwtKi3HNan75BrP9FXfF45nRkhcewl7cnTk4OHD92WmfZ0KH92LxpR5nrluXivTg8nOyo7WirLq9tGxJ24XaZ6UPPXifYp2GV86kMfSmrAF69fLiyWX0uiY1Qn0ssSzmXxEbcIrOUc4lDA3fuH1O3Unlw/DL1K1FeS9OrTwCb128DIOJMFDY21jiXsk8K1fOqi4OTPacKWtM8fBDN1cvXUakqf52p8ePGwrzc46ZHiB+/byy6F7CxtcaplGvw4Of7s/rTHwDta7BQM9q1boGtjXXFCf+kiw8T8bC3pra9tfqc1rIuYVceaKXZcuYGIzo2wsbcFAB7K3MAbiek4uPpgpGhAeYmxjRU2HHsRnT14ohJxsPOktp2lhgbGtC7iRthN2O144i6z4g2ntgUVGbYW6rjMTY0wMTIEIDcfFW5x4MglKdSlQ2SJLlIktS24D+XP5upmas92Y8SNZ+zY5IwK/YGQ5Mmpqi5X3a0bhqA2qO6k3Ag8i/L28TJltyCi3pufAomTraadLY+Deh88EPa/jwHy0a1dfJWDOpMzG/Hdb43dbVHWSIm0xIxmZYSU8k0f3cG5iY4BrQmrpyWC95zR9Lp0AoaLn4ByUTdMKf+W4NICr/IqeD5nB28mAbvjsbAwrRKedu09WZn+Aa2H1nPwpnLSm3VAODi6kRsdNGJOi46DheFs1YaaxsrAN6aM4nfDvwfn3y3HAcn9W9Vz6sOnvXr8svO79gY+j3denSuUpyFnF2dNF0PAOJiEnB21X5AKIzjjVmvsGHvD/znmyVaLSlGvDSEnSc3MW3BGyyfv7Jacbi6uhD9qGh/REfHonAr+xQxaMhzbP1tl9Z3ffv3IuzYNtas/QQ3d0WFeVZUTjwmBJOw54zmOC3U6IMXuf/1Tk4FzyNqwsc0XflqhXmV5BTSnuFhKwhe+zaHZ3xTahpLRS0yo4uO58yYJCwUlW/B4tjcE0s3e+4frPx5raT41EwUdkVv/VzsLIlPLf0NYXRSOtGJ6XRo4A6ASiXz8bbjTO9fvbJZGoWrMzHFyklsdBwK19KPm+lz32DbwZ/533crcCw4bq5euk7vvj0A6P1cD6ytrTRvkqvCxsWe1GK/TWpsEjaKss+jZjYWNAlsy81j6gqG6Cv3aB7cAYBmvdtjZm2BhZ1VmevXdFn949weNvz6Au523gAAIABJREFUDZMnzS0znaurC48eFlXCRkfH4lrOMTx4aF+2bN6p+7d4uFHHszZHDp+ocqzxKZkoiu1HFzsr4lMzSk0bnZRGdFIaHRoWXWNz8/IY9dEGxn68kYNRt6qcf3H6UlYBrBS1SI8pKq8ZsUlYVeFcknD5Pg1C2gPgHdwOU2tzzMopr2WpzD4prv/gELb/trvK+RSq6eNm57GNfLluJe+89UGZ6VwUzlrX4NjoeJzLKCdT5rzG5v1r+e+3yzT3AgC9+vZga9g6Vn23DIVb2ftT+PuJT8tCUazljYuNJfGpSq009x6ncS8xjXFf72bsV6Ecu67u1thQUYtjN6JR5uaRnJnN6dtxxKVmUR3xGdkorM2L4rA2Iz49WzuOpAzuJWcybt1Rxv4UzrHbRd2+YtOUDPs+jOAv9/FiR2/RqkGolnIrGyRJai1J0kkgDFhR8N9hSZJOSpJUZqdMSZJekSTpjCRJZ0KVf+7CXx6vtwYi5+UTXVDzXyMKavrSou4Q7vMmJ3rM5v53u2n9wwytZJKxIU69fIjdfrImovxbcOrlQ8rpa2U2m7yx5BeOd5nGH73nYWxnRb03BwDg4N+SelMG0unAh7T7bSEGpiaYu5f91qU0aedu8ly3EQzt+QKvTn0JE9OqN1crZGRkiKu7gnOnoxgUOIbI0xeY895bABgaGeJZ34OxA15h+qvz+WDlfM0NydNmaGSIwt2F82cuMKLXi5w/c4EZCydrlm/4fjPPdRrGqg++4JVpLz2TGEoaNKQPW34telDZE3qIti160L1Lf8IOHed/X31Y4TbKKyemLrVw6deJB9/q3ug6+LWg8bLxdDrwIa3XzsLI2hzDKlZKJYSeZmP3Weyd8F/azRxa8QpVJUl0XjiaE4t/fvrbLsOeiJsEtaqPoYH6crDx2EW6NqmDSzUeSv4MIyMj3NwVnDt1nv49RhFxJoq5i9Rde5Yu/C8dfX3YfvAXOvj6EBMdV2aF4NNiYGjAqE8nc/yHPSQ9UN987VyyjvodmzBl5zLqd2pCakwiKpWqzG3UdFnt2LY3Y56fxLwFb1Vp3fIMHtqXzZu2l/r9tq27y90fT8OeszcIau2tKa8Au957kZ9njmDZuN58tCWcBwnP9u2xvpXVshxZ8jPuHRszetcH1O7UhPSYJORn/PsA9B8czLbNoRUnLENNHzfPdRnO5HGzmDKn6pUVxRkaGeLq7kLEqSiGBL1A5JkLzHpvCgBhe48S6DOAgd1Hc/zwKZZ99t6fykv4+8lXydx/nM63L/di+fCuLN56kjRlLr4N3Oja0J1xX+9mzoZwWtZxxECSnm0cyZl8O9KX5f18WLznPGnZ6laVChtzNr3UnW0TA9l+8SGJmTkVbO2fTf4b/E8fVTRmww/Aq7Isa1UvS5LUCfgeaFXaSrIsrwZWA+xyGSkD1H2pFx5j1LX9KZG3MHMvam5WsiUB6LY4MHPTTuM+wh/nnm35Y2jZNc+Fiued9ifzzk1IxcTZTt2qwdmO3MdpAORnFNVYPj4QSZPlEzC2t9YMPOQY2Jq0C3fJLbgJqvNSL2oXxJQaeQtzdwcK6+jNXO3JKRFTTikxlUzzd2XqUoucuGQUA33L7UJR+BZDzs0jen0YdV8vGARMkjg//mOdLhJNV03CpoUnObHJRIxeXqlYbt24S2ZmFg0be3HxvHoArNHjhzF8rHrMgQsRl1G4KQD1oFEubi7ExWoP/pWclEpWplIzIGTotv0MHa3u7xwbHc/5cxfJy8vn4f1o7t66j2f9OlyI1B5UsTQjXhrCkILtXIq8otWCwMXVifgY7WahKUmpKLOU7N8ZBsDe7QcZNKqfznZDt+5j/oczK8y/0PiXRzF2nLofa0TEBa3WCG5uCq23PcU1a94IIyNDoiKLBp9LTi56M/V/P25i4SLtOArzqmtgTsSo5RWWE+sWnljUU9Dl5CcAGJqb0OXkJxzrNBUkiVN93tHpVtRm/TxMnWxJO3+by9O/rtQ+iPnjGjZ1nDGrZUV2cgbNxgXReFQAAAnnb2PpVnSOsXS1Jyu2ct1lTKzMqNWoNv03zQfA3MmW4DXT2T1+ZZUGiXS2tSS22I16XEomzmX0b94deZO5xfrDn78XR8TtGDYeu4Qy9wlP8vKxMDVmat9Olc4fYOz44YwYOxiAqMhLuBYrJwo3F51B85KTUsjKVLJ7h7qf967f9zFstPq4i49NYNKLbwNgYWlOcL9A0tNKf/NdUuexPenwvPpc+/D8bWyL/Ta2CnvSyhgwb/CyiTy+E8vRNUUPTenxyfz02n8BMLEwpUVwB7ILBqwtns/NkfpTVo8fO42npwf2DrVISlSXw5dfGcMLL6qP4XNnL+Beu2hsDjc3BTFlHMPNmzfGyNCQ85GXdJYNHtqXmdMXViqmkpztLIlNKfo941IycLYtvbJr97nrzB3WXeu7woqx2o62tPN25+rDBDycKt+aQF/KKkCrF4Jo/rz6XBIXdRtr16LyaqWwJ6OS5xKAzLgUdryqLl/GFqZ4h7QnJ61yb0hfmDCS518YAkBUxMUK90mhJs0aYmhoyIXzFV/TSuaTOHqV3hw3Z05GULuuO3b2tpquD6PGD2XoGPXvfDHistY1WOHmTHyJfZJScC+wb+chAPZs28/QUepreEpyUYXYr//3O2+/Oxnhn8PZxoLYYq0J49IycbY110rjYmNBcw9HjA0NcLe3pq6DDfcT02he25GJAS2YGNACgDkbwqnraEN1OFuZEZte9HwSl56t0zrBxdqc5m526jjsLKhby4r7yZk0dy3qsuVsbYa3kzXnHibSs5FbtWIR/r0q6kZhWbKiAUCW5ZNAlUbmuff9Xo4GzuFo4BziQs/gPswPADsfb/LSs8gp0RwuJz6FvAwldj7qfsTuw/yI263u5+0Y0Ir6b/Tj7AsfoVLmVirvk4FzOBk4h/jQM7gV5G1bkHfJpni5BXnbFuTtNsyPhIK8E/acxW2Een23EX7EF3xfvDuFTRsvMJA0FQ2g2//w/vd7OR44h+OlxPSknP1RPKbC/fF3lxOXjJG1ObU6N9Xsz9IUH1vDKaQ9GVfV/d8Sw87jMSFYs8y6uScAl9/6kpOBsyusaDCr44RkqD4U3GorqN/Ak0cPivrHrVuziQEBoxkQMJr9oWEMGtEHgFY+zclIyyAhLlFnm4f2htOxi7p/bGe/9ty8rn5Q3B8apvm+lr0tnl51eHDvUbnxFdrw/WaGB41jeNA4Du4+Qr/hIQC0bNuM9PRMHsfrxhG29yjtfdWNkDp2a6eZcaJOvaImyH5BXbh/54HOumVZ8+3PBHQbSEC3gYTu2M+I59U3Xz7tWpGWlk5cnG5fWChofv2rdvPr4n3Dg/v04Pp17ZZQhXmdDJxdqXLyeH8ER1q8ytH2kznafjL5ylz1TSiQeDhKq5xYNasLQMTIpZwMnF3hTai5Z9GNpWNzTwxNjchOVj9EXPpxP5t7z2dz7/nc3X2WhkPVI6o7t/UiNz2rzLEZSspNV7K25SR+7jyNnztPIz7iVpUrGgCaeThzPyGFR4lpPMnLZ0/ETfwLjovi7sQlk5aVQ6tif9uyMUHsfncsoQvGMK1fZ/q2a1TligaAn9ZspG/ASPoGjGTfrkMMGq6uHGzt04L0tAwS4h7rrHNg7xE6dVWPueLr14Gb19T99mvZ2yEVvNmZNHU8m36u/KjtJ37axyd95vJJn7lc2nsGn4KKlTptvMlOzyI9Qfe36TVjOGbW5mxfvFbre4ta1po4Al4fwOmNYaXmo09ltWWrZpiYmmgqGgC+Xf1/+Pn2x8+3P7t27GPk84MAaNe+dbnH8JBh/dj8q+6YDA0a1sfOzoZTf0SUG1dZmtVxKSivqeryeu46/i3q6aS7E5dEmjKHVvWKHnzTsrLJfaJuOZCcoSTyTgz1y+kaUxp9KasA59fuZ13IfNaFzOfWnrM0KZidQdFGfS4pbWyGspjVsoKCWNq/0Z9LGw5Xet21360nxH8YIf7D2LPzIENGqh+S27RrSXpaBvGl7BOAAUP6sG1L5Vs1FM9Hn46bpi0aYWJirDXGws9rfmVwjzEM7jGGA6GHGTC86F4gPS2DhFKvweF0KLjmd+pWdC9QfHyHHsF+3L5e9RmHBP3VzN2B+4npPEpKV5/Tou7hX2Kg9oCmHpy5o67YTc7M5l5iGrXtrclXqUgpGD/kemwyN2KT6exdvcGam7nacT85k0cpWTzJV7HnSjT+3trdVQMaKDhzX112k7NyuJecQW07C+LSlWQXnFvTsnOJeJiEp/1f2+JR+GeoqGVDqCRJO4G1QOHTiAfwAlDtDnkJ+yNwDmyN/x+foFLmEDW1aHTkrgeWc7Rg9oZLs9fQUjP1ZaRmbIZmy17CwMSYDhvVb/9Szt7g4qzvAOh++jOMrM0xMDHCJaQdp0csJeN60cPc4/0ROAa2pusfn5CvzOFSsbw7HViumTniyuw1NNdMMxnJ44K873z2Oy2/eQv3UQFkP3zM+YmrAHDp1wmPcUHI+Srys3OJevVTzXYNLUxx8GvBlbdL7+OdUBCTX0FMF4rF5HtgOccLYro8ew0tNNNxFsXkHNKepktfxMTBBp91s0i/eI8zI5cB4H/6MwxL7I/M65V7uP0rOfXpQOLhKFRZ2k202qybw+XpX5MTl0yLLydj7GCDJEmkX7zLlZnq/Xl75WYavf8incI+QpIklA/iiSwxKwioKygaL30JEwcbWq+bTfrFe0SMXEqtDo3xnDyA3/OyUKlkFs1arhnQsaSwfcfwD+rC/lNbUSqzmTtlkWbZ74fWMSBAPUL3R4s/5aMvFjPvgxkkJyYzpyBd+METdO3eiV1HN5Kfr2LFe59qveGorPD9x+kW6MvOk5vIVuawoFjf0o37f2R4kHrU71UffMHSz95l1vtvkZyYokn3/PihdPRrT96TPNJS03lnSsWzQZRm397DBPXy51TkPpRZSqa8MU+z7FD4Vq1ZKPoPCuH5oa9orT/xtbH0DulBXl4+Kcmp5fYth8qVk7Jcm/8DjZePp9OhFUiGhqScvMKVWd/qpPN4ORjPN/pj4mxH50MreHwgksvTv8alb0dch/nRpuAY3z/pf6Xmc/9gJHV6tGLk0Y/Jy84lbPpqzbIhe5awubf6vNVx/ki8B/piZG7C6NOfcvWXMM6u3FLu319ZRoYGzBncjUmrd6BSyQzo0BhvhT1fhJ6iqYcT3ZurH+R2R9wkuI235uHoWTm07yjdg7py6PQ2spXZzJrynmbZjkPr6RswEoAPF33Cyi8/YMEHb5OUmMysyep0nbq0Y+aCyciyzKkT51g4a1m14rh6KIJGAa2ZdXgVucocNs0seviYumsZn/SZi63CnsDJg4i/+YgpO5cCcPzHvZzecAivTk0InjUSWYY7p66w9d2ypxPWh7J6JDcdpTKHCeOmlpKL2t49YfTs3Z1zUQdRKpW88dpszbIjx7dpzUIxcHAIw4foznpTWkViVRgZGjBnqD+TvtiGSqViQKemeLs68MXOkzSt40z3FvUB2H32BsFtG2iV19uxyXyw4RAGEqhkGB/kozWLRVXpS1kFuHMwEs+AVrwU/jF5ylz2vl10LhkduoR1IepzSbd5I2k0wBdjcxNe/uNTLq4P4+R/t+DRuQldZo8AWebhH9c4tOCHasVxcF84AT39CD+7C6Uym7ffLJotK/TwJq1ZKPoO7M24Ea9rrd+yTTO++ekTbG2tCQr2Z/qc1wnyHVRqXvpw3GzJU5KTncP0V+aXmdfh/cfwC/Jlz6ktZGdlM29q0TV0y8H/Y3CPMQB8/P7/+PDzRcz9YBpJj1OYP3UxAGMmjqBHbz/y8vNJTU5l7pTFZeYlPD0zFy7ndEQUKSlpBA4cw+sTxjKkX+kz9fwZRoYGzOnXgUk/HEAlywxo6423ix1f7I+kqbsD3Zt44NvAjRM3Yxi8ahsGBhLTgttiZ2FKzpN8xq/eA4ClmTFLhnXFyLB64/kbGRgwJ6g5kzadVMfRwgNvR2u+CL9KU4Ud3Rso8K3nxIm7CQz+7hAGksS07k2xMzfhxN0EVh66hISEjMwL7b1o4FS9Fhb/FGLqy+qRKhpdVJKkEGAA4F7w1SNgmyzLu8peq0hhN4qaViNzfJbi2feWrJrguPU1HQL7XEbUdAgAvKF6duOLVJWZoXFNhwBAjFI/uur8bNa6pkPQuG2sH7/NC19XfiacZ6nZuB9rOgSNYVaNazoEAIKU+nGmH555tqZD0Ije/PTGjfgzmo3+rqZDAGCyRbOaDkHjvxnnazoEAL4zrvq0qc/CFFm/WhlciT9V0yHojSePy56l5q+WF/bXja1UrtTKt3Z61swn/OfZvrmoYV6ObfXimbY8tx6f07vfoMJncFmWQ4Hqj/QjCIIgCIIgCIIgCMK/SkWzURhKkvSqJEnvS5LkW2LZO2WtJwiCIAiCIAiCIAj/BDU908TfdTaKijoBfQ34A4nAZ5IkrSy2bPAzi0oQBEEQBEEQBEEQhL+tiiobOsiyPEqW5VVAR8BKkqQtkiSZAnrXJ0QQBEEQBEEQBEEQhJpX0ZgNJoX/kGU5D3hFkqSFwEFAzH8iCIIgCIIgCIIg/KPJsn4M/vx3U1HLhjOSJAUX/0KW5UXAGsDzWQUlCIIgCIIgCIIgCMLfV7ktG2RZHgMgSdIwYLcsy+kFA0O2Rd2tQhAEQRAEQRAEQRAEQUtFLRsKLSioaOgKBAHfAV8+u7AEQRAEQRAEQRAEoeapkPX+P31U2cqG/IL/fw5YLcvyToqN5yAIgiAIgiAIgiAIglCospUNjyRJ+hoYAewqmI2isusKgiAIgiAIgiAIgvAvUtkKg+HAHqC3LMspgD0w85lFJQiCIAiCIAiCIAjC31ZFU18CIMtyFrCl2OcYIKYy6+pL8wd9maxEX/aHoEvWo75OKlk/YjFAqukQ9I44hrXp01RQ+nHUCKWS9OPI0Zfyqh9RCKXRp3sBQVte2M81HYKGUfdRNR0CAHnbv6rpEP41ZD25N/+70Y+rvyAIgiAIgiAIgiAI/xiiskEQBEEQBEEQBEEQhKeqUt0oBEEQBEEQBEEQBOHfSF+nltR3omWDIAiCIAiCIAiCIAhPlahsEARBEARBEARBEAThqRLdKARBEARBEARBEAShDGI2iuoRLRsEQRAEQRAEQRAEQXiqRGWDIAiCIAiCIAiCIAhPlehGIQiCIAiCIAiCIAhlUIluFNUiWjYIgiAIgiAIgiAIgvBU1VjLhiZLxuEY2AaVMocLU74k7cJdnTQ2LevR4tNJGJiZ8PhABFfm/wiAS7+OeL89FKuG7pwIfoe087c161g1rUPzj17G0MocZJkTveejynnyl8Zh7uFE1/CPybwVDUDK2RtcnvWdznYbLRmHU2Ab8pU5XJzyJeml5G3dsh7NP52EoZkJCQciuFaQt5GdJa1WT8XMw4nsBwmcn/gJeamZeL7eF8WQrgAYGBli2cCdQ00nkpeSSZ1X+1B7VAAA6Vfuc2nqV2XuF31Qy7cpjd4fh2RkyJOkdM4MWlTpdY1rWdHyu+nYtPYien0Y1+Z9r1nW5pe5mLrUQjI0IOWPq1yZ8x2oKl9buWDpTPyDuqDMymb2lPe4HHVVN39jI95dPpuOXXxQqWT+u/Rz9uw4yLz3p9OpazsAzMzNcHC0x8e7e6XzLm7ukul0C+xMtjKH+VPe58qFazppjIyNmL/sbdr7tkWlUvHpsq/Zv/MQw18YxMjxQ1Dlq8jKVPLe28u4ff1uteJY8uF8Anv5oczKZsrrc7lw/rLWcksrS7aF/p/ms6u7gs0btrFg7jJGjBrEu+/PJDY6DoA136xj3dpfK523vpaRzovH4tGjNXnKHA5PW03ixbs6adrNGkaDoV0xtbXkh0Yv6yz37NOenqun8lufBTyOulPpvAsdu3KfFVuPolLJDOrUhPGBbbWWf7T1GKdvPgIg+0keSelKji6doFmekZ3L4A/XE9C8HnOHdKty/iUtXDab7kFdyVZm8/abC7hUxnGz6MO5dOrSHpWs4j9LPmP39gO413blw88W4eBQi5TkVKZNmkdsdHy14ui/cByNA1rzRJnLxre/5NGlu9oxmJkw5ou3cKjrjCpf5sqBs4R+uB4AO3dHhq14FSt7G7JSM1j/1uekxiZVOm99La/LP1pAz17dUSqVvP7qbKLOX9JabmVlya69v2g+u7kr2Lj+d+bNXsKS5fPp5tcRAHNzc5ycHPCsrV3WKuPY5bus2HxYXV47N2N8r/Zayz/afJjTNx4CkJ2bR1JGFkdXTAIgJimNRb8cIC45HUmS+Oy1Abg72FQ5hkL6UlYBAhaNpV6A+lyye8Zq4ks5l3SZOYxmQ9Tnks+aFJ1LrN0d6P2fV7CwtyY7JZNdU78kowrltSyLls0hoGc3lMpsZrzxDhejrmgtt7Sy4NedP2o+u7q58NumHSyat6Ja+enrcTN/yQz8grqQrcxm7uRFXC7lGmxsbMSCZbPo0KUtKpXMqmVfsHfHIQCC+wfx5syJyDJcu3SdtyctqHTeQtmOXX/Eip1n1OeSdt6M92+uk2bPhbt8fSAKJGioqMXyEepr3Krd5wi/pj7PvBLQkt4tPZ9JjO8sXcmRY6ewr2XH1v97tvfix27HsWL/BVQqGNSqDuM7N9RJs+fKI74+ehUkiYbONizv306zLCPnCYO/PUhAA1fm9mr5TGMV/plqpLLBMbA1FvVcCe/0FrY+3jRd8TInQ97RSdd0xQQuzlhN6tmb+Pw8B8cerXl8MJKMqw+IHL+SZh9N1EovGRrQ6vM3iHrjc9Iv38e4lhWqJ3l/eRwAWffiOB44p9y8Leu5crRY3n+UkfflgrzbFsu73uQBJIZf5O5n2/Cc3J96kwdw44OfufvFDu5+sQMAp15tqftqH/JSMjFV1KLuy8Ec6zYDVfYTWq6eimKgb5nx1TQjGwsaL59AxPNLyX6UiLFj1W4c83OecGv5Bqwae2DZ2ENrWdTEVeRnKAFo+d10XPp3Jm7r8Upt1z+oC3XrexDUYSCtfZqzeMVchgaP00k3adoEkh4n0avTYCRJwq6WLQBLF6zUpBn78giatmhUpb+rULfAztSp50GfTsNo6dOMBStmMSpkgk66V996kaTHyfT1HY4kSdjWUu/HnVv2sHHtbwB0792NWYum8trz06ocR2BPP+p51aVTm974tGvFipULCQkcoZUmMyOTwG6DNJ/3Ht7Mzu37NJ9/3xLKvJnvVzlvfS0jHj1aYVtPwcauM3Bu60XXZS/ye7/3dNLd33+OSz/sY0T4f3SWGVua0Xx8b+LO3azS31QoX6Vi2ZZwvnqtHy62loz+72b8m3nipbDXpJk5sIvm37+EX+Dqo8da2/g89BRt67tWK/+Sugd1xbN+HQLa96N1uxZ88J93GNRrjE66N6ZPJPFxEj069tc6buYtns6WDdvZsn47nbt1YNaCqUyfNL/KcTTu3hrHegpWdJ9GnTbeDFoygf8N1L3BP/LNDm6duIyhsSGvrHuHRt1bcS3sPH3njebclnDObj6CV+dmBM8ayYbpX1Qqb30trz17+ePl5YlPq0DatW/Nx6sW0TNgqFaajIxM/Hz7az4fCt/Kjm17AZg/Z4nm+4mvjaVly6ZV+rugoLxuCuOrNwbhYmfF6I/W49+iPl6uDpo0M4f4a/79y+FIrj5M0Hx+56e9vNy7PZ0b1yUrJxdJkqocQyF9KasA9QJaUctTwRq/Gbi28SJoyYv8POA9nXS3958j8sd9jD+sfS7xf2cUlzcf5fKv4Xj4NqXbnOGEvvXnHmwCgrrh6VUXv3bP0aZdS5Z8/A4Deo7WSpOZkUWI/zDN550HNxC6/UC18tPX48Yv0Je69evQu+NgWvk0Z+GKOYwIeUkn3WvTxpP4OIngzkO1rsF163nwytQXGdX3ZdJS07F3rFWlv0soXb5KxbLtp/jqpSBcbCwY/WUo/k1q4+Vsp0lz73Eaaw5f5IdXe2NjbkpSQRk4cvUhV6IT2fBmX57k5zPh2310aeiGlZnJU49zYJ+ejBrSn3nv617/n6Z8lcyyvVF8NdIXF2tzRv9wGP8GCryKHUf3kjJYc+IGP4ztho2ZCUmZOVrb+PzIVdp6OJTc9L+SjOhGUR010o3CJbgd0ZuOAJB69ibGNhaYFjsRAJg622FkZU7qWfXNdvSmI7iEqGvaMm9Ek3krRme7Dt1bkn75PumX7wPwJDmj3FrqZxVHZTiVyNvIxgKTEnmblJK3U0HezsHtiN6gXj96wxGcQ9pRkmJQF2J+K7pwSoaGGJiZIBkaYGhhSk5scrVi/ysoBnclftcpsh8lAvDkcVrRsiFd6bB7CZ0OfEiTjyaCge6NpSorh5RT18gvpVVL4c2FZGSIgYkRVKEPVlCwP1s37AQg8uxFrG2tcHJx1Ek3dFR/vvpE/QZFlmWSk1J00vQd1JsdW/ZUOu/iAoL92LZpFwBRZy9hbWOFo7PuxWDQ8/349tMfNXGkJKUC6pvBQuYWZlXZBVqCnwtk0y+/A3D2zHlsbG1wdnEqM319L08cHe05efxM9TIsRl/LSN1ePtz49SgA8eduYWJjiXmJY7twmTJet1wA+MwcyvkvdpQaW2VcvB+Ph6MttR1sMDYypHcbb8JKeSNaKDTiBsFtvDWfLz9IICldSedGHmWuUxU9QwLYsmE7AJFnLmBja13qcTNs9EC+WLUG0D5uvBt5ceLIKQBOhJ8iKKR7teJo2suHc1vCAbgfcRNzawusnbR/myfZudw6oW6dk/8kn0eX7mCrUB9bzg1qc/P4RQBunbhEs54+lc5bX8trn75BrP9FXfF45nQktrY2uJRzDHt5e+Lk5MDxY6d1lg0d2o/Nm3ZUOu9CF+/Fqcuro626vPo0JOzC7TLTh569TrCP+u3crZhE8lUqOjeuC4CFqQnmJsZVjqGQvpRVAK9ePlzerD6XxETcwtQSPvhBAAAgAElEQVTGEstSziUxEbfILOVc4tDAnQfH1K1UHhy/jFcVymtZevUJYPP6bQBEnInCxsYa51L2T6F6XnVxcLLn1Imz1cpPX4+bwBB/ft+ovhc4f/aiupyUcg0e/Hx/Vn/6A6B9DR42diA/r9lEWmo6AEmP9fd+7O/k4sNEPOytqW1vrT6XtKxL2JUHWmm2nLnBiI6NsDE3BcDeyhyA2wmp+Hi6YGRogLmJMQ0Vdhy7Ef1M4mzXugW2NtbPZNvFXYxJxqOWJbXtLDE2NKB3U3fCbsRqpdly/h4jfOphU1CpYm9pqll2OTaFpKwcOns6P/NYhX+ualc2SJJkVd11TV3tURZcOACyY5IwdbXXSZMdU9TcLztaN01Jll6uyDK0Wz+XzvuWUe+NfjUSB4B5HSd89y+jw2/vUqtjY53lZq72motnYd5mJbZrVkrehWlMnGzJLbi5yI1PwcTJVmtdA3MTHANaEbfjDwByYpO5++UO/M59jn/UV+SlZZF4OKrCv6OmWHi5Ymxric+Wd+m4dxmuw/wAsGzgjmKgL6f7vsvJwNnI+Spcq9HEu836efhfWk1ehpK47ScrvZ6LqzMxBU3+AWKj43FRaN+YW9uoD4235kxi64F1fPrdhzg4af+2brUV1K7rzolw3Rv2ysXhROyjoqa5cTHxuLiWHsebs19l474f+fibJVpxjHxpCKF//MqMBW+ybP5KqsPV1YVHj4oq3GKiY3F1cykz/cAhffj9t1Ct7/r278mhY7/z7dpPcHNXVDpvfS0jlopaZEQXHduZMUlYKir/1sqhuSdWbvY8OBhZpXiLi0/NRGFnqfnsYmdJfGpmqWmjk9KJTkynQwN3AFQqmY+3HWd6/87Vzr8kF1dnYh4VHTcx0XEoXLVvXqwLbrymz32D7QfX8/maj3AsKK9XLl6jd99AAHr3DcTa2krzJrkqbF3sSSn226TEJmGrKPt8bmZjQZPAttw8pq5giLlyj+bBHQBo3rs9ZtYWWNhV7lKor+XV1dWFRw+LjuHoCo7hwUP7smXzTp3vPTzcqONZmyOHT1QtcCA+JQNFraIbbxc7K+JTMkpNG52URnRiKh0aqivC7sWnYG1uyvRvdjDiw59ZuTWcfJWqyjFo8taTsgpgpahFekxReU2PTcKqCueShMv38Q5Rd0fxDm6HqbU5ZpUsr2VRuDoT86joYSW2lP1TXP/BIWz/bXe189PX48ZF4aR7L6BTTtT7euqc19i8/ydWfbtMcw329KqDp1cdft7xLet3raFrwNM73/6bxadlobAtdu2zsSQ+VamV5t7jNO4lpjHu692M/SqUY9fV3QkbKmpx7EY0ytw8kjOzOX07jrjULP7O4tOzUVibaz67WJsTn56tleZeUgb3kjIY91M4Y9ce4dhtdblWyTIfH7jI9IBmf2nMwj/Pn2nZcLniJH8tydCQWh0bcf71//FH/4W49GmPfTfdvlrPWnZcMofbvsnxoLlcXfgTLb+crB5D4lkqUSPv1MuHlNPXyEtRP2AY2VriHOxDePvJHG41CUMLU1wLxnbQR5KhAdat6hMx5kPOjVxK/emDsajvin235ti0rEfHPUvpdOBD7Ls1x7xu1WtcI0Yu5UjL1zAwMca+69MtI0ZGRri6K4g4HcXAwNFEnI5izntvaaXpO6g3u7fvR/UnboorYmhkiMLdhcjTUQzvOY7zZy7y9sLJmuXrv99MSMehrPzgc16d9uIzi6O4gUP68NuvRQ8qe0MP0a5FIAFdBnD40HE++2p5pbf1dy4jZZIkOi0czcnFP/81+QF7Im4S1Ko+hgbqy8HGYxfp2qQOLn/yoaSqjIwMcXNXcO5UJP16jOTc6SjmLZ4BwNKFK+nYpR07Dm2go68PMdFx5Oc/u2MHwMDQgFGfTubYD3tIeqCu2Nu5ZB31OzZh6s5l1O/UhJSYxEofw/+U8jp4aF82b9pe6vfbtu5+puc0gD1nrxPUuoGmvOarVETcimb6oG6se3skjx6nsu2PZ3t7om9ltSyHl/yMR8fGjN31AR6dmpAek4T8jH+fkvoPDmbb5tCKE5bh73zcGBoZ4uruQsSpKIYEjSXyzAVmvTcVACNDQ+rW9+CFga8y47V3eH/lfE3lhPBs5atk7j9O59uXe7F8eFcWbz1JmjIX3wZudG3ozrivdzNnQzgt6zhi8Ce6ZP1d5Ktk7idl8O2oLizv78Pi0EjSsp+w8dwdunq54GLzjJ9fhH+8csdskCRpelmLgDLPipIkvQK8AjDZuh19zL2o81Ivao/pAUBq5C3M3R0obPRn5mpPToz2oEU5Jd70m7nppikpOyaR5BNXeJKkbpaWsD8SmxaeJIVf1KT5K+KQc/N4kqt+K5MWdQfl3TgsvVyxa+utyTst8hZm7kVN7kq2YlD/Pbp5F6bJTUjFxNlO3arB2Y7cYk0LARQDO2t1oXDwa07W/QSeJKr3TdzOU9i11x0kpibVfqkXtceo3wjFbjtB4qHzqLJyUGXlkHzyClbN6oIkEb3xCDeX/KK1rlNIe7zeVvczvjz9a61BQ8uiynlCwu4zOAW3I+nIhTLTjR4/jBFj1WMOREVc1nrrp3BzJi42QSt9clIKWZlK9uw4CEDotv0MGz1AK81zg3rx3uwPK4yxuJEvDWHoGPV2LkZeQeFedGPl4upMXIx2HClJqWRlKdm/MwyAvdsPMHiUbmuf0N/2seDDWUDlxk146eVRjBmn7o8bGXEBd/eifv2ubgqttz3FNW3eCCMjI6IiiwafS04uavq77sdNvLvo7XLz1tcy0nRcEI0LBl9NOH8bKzcHCveCpas9mZXssmRsZYZ9o9r03aTu423uZEuvNdPZO35llQaJdLa1JDalqCVDXEomzsXe9hS3O/ImcwcXvRE8fy+OiNsxbDx2CWXuE57k5WNhaszUvp0qnT/A2AkjGDl2MABREZdwdS86blzdXIiN0R40r/C42b1D3bd71+97GT5GfdzFxyYwaZz6cmRhaU5wvyDS09IrFUfnsT3p+Lz6vPvg/G3s3IrOu3YK+zIHeByybCKP78RydE3Rg1JafDI/vfZfAEwsTGke3IHstLLffOlreX35lTG88OJwAM6dvYB77aJj2K2cY7h588YYGRpyPvKSzrLBQ/syc/rCCmMsjbOdFbHJRb9nXEoGzmVUdu0+d525w7prPrvYWdGothO1HdWtBwJaehF1N5ZBVXhRrC9lFaD1C0G0eF59LomNuo11sXErrBX2ZFSh+2NmXArbXv0EAGMLUxqEtCennPJalhcmjOT5F4YAEBVxEddiLdAUpeyfQk2aNcTQ0FBn0OCK6OtxM2r8MIaNGQjAhdLuBUrsh5SkVLIylezdqR4Qcve2AwwZpb6Gx8bEE3X2Enl5+Ty6H83dW/epW78OFyP17j3e34qzjQWxxVrxxaVl4myr/bDsYmNBcw9HjA0NcLe3pq6DDfcT02he25GJAS2YGNACgDkbwqlbxTFC9I2ztRmx6UUtO+LSlThbm2mlcbE2p7mbnXp/2FlS196K+8kZnH+UTMTDRDaeu4PyST5P8lVYmBgytfu/t6WDLKa+rJaKWjYsBWoB1iX+sypvXVmWV8uy3E6W5XZ9zL0AuP/9Xo4HzuF44BziQ8/gVtAUztbHmyfpWeSU6G+YE59CXoYSWx91P2K3YX7E7S6/n/fjQ1FYNamDgbl6XIJavk3ILGgeVeiviMPYwVrTd9C8rjMW9RUo78Vx//u9nAycw8lS8s5Lz9J0iyiUW0reCQV5J+w5i9sI9fpuI/yILxaTkbU59p2batICZD9KxK6tNwbm6j5ZDt2ak3FDe9/UtIff7+Vk4GxOBs4mYddp7Do2QjI0wMDcBNu2Dci88Yik8Au49O2oGSTKyM4Ss9qOJISe1qxb3s2FoYWpZmwMydAAx55tyLpZfp+8dWs20T9gFP0DRrE/NIyBI54DoLVPc9LTMkiIe6yzzsG9R+jYRT2Ohq9fB25eL3pQrO/tiY2tDRGnq9aNZf33mxka+AJDA1/gYOhh+g/rA0BLn2ZkpGfwOD5RZ53De4/Svot6ZPiO3dpzqyCOOvWK+uL79ezC/dsPdNYty/ff/kxgt0EEdhtE6I4DDHteffPk064V6WnpxMcllLre4KHPabVqALTGd+jdpwc3rt8qN299LSOXf9zPlt7z2dJ7Pnd3n6XBUHWrIee2XuSmZ5U5NkNJT9KV/NRyEus7T2N952nER9yqckUDQDMPZ+4npPAoMY0nefnsibiJf3NPnXR34pJJy8qhlWfRTfOyMUHsfncsoQvGMK1fZ/q2a1TligaAn77bwHPdR/Bc9xHs3XWIwSPUFV2t27Uo87g5sOcwnbqqm337+nfk5jV1eahlb6cZ9O/1tyawad3WSsdx4qd9rOozl1V95nJp7xnaFlSs1GnjjTI9i/QE3d+m94zhmFmbs33xWq3vLWpZa+IIeH0AZzaGlZu3vpbXb1f/H36+/fHz7c+uHfsY+bz6Qbld+9akpaUTV8YxPGRYPzb/qjsmQ4OG9bGzs+HUHxHl5luWZnVc1OX1caq6vJ69jn+L+jrp7sQmkZaVTat6RZUjzeq6kJ6VQ1K6+iH61PUH1C+na0xp9KWsAkSu3c9PIfP5KWQ+N/ecpWlBC0TXNl7kpGeVOjZDWcxrWUFBLB3e6M/FDYerFEuhtd+tJ8R/GCH+w9iz8yBDRqoHC23TriXpaRnEl7J/AAYM6cO2LVVv1aCvx83PazYxqMdoBvUYzYHQMAYMV98LtCq8FyjlGnxobzgduqjHyujcrT23rqtj2r/rMB0Krs129rZ4etXh4T39uif7O2rm7sD9xHQeJaWrzyVR9/AvMTBoQFMPztxRV6gmZ2ZzLzGN2vbW5KtUpGSpB0e8HpvMjdhkOns/nUGSa0ozVzvuJ2XyKCWTJ/kq9lx+hL+3dnfVgIYKztxXl93krBzuJWVQ286SZf192P16L0Jf78W0gGb0be7xr65oEKqvotkozgFbZVnWGdlHkiTdudoqKWF/BI6BrfH74xPylTlcKDYFo++B5ZpZHC7PXkMLzbSPkTw+oO7D7BzSnqZLX8TEwQafdbNIv3iPMyOXkZeayd2vdtJ59xJNPgn7y775eVZx2HdqgvesYch5+cgqmUuzvuVJinZ/6ccFeXctyLv4NJSdDiznZEHeV2avoblm2s2ivO989jstv3kL91EBZD98zPmJqzTrO/fpwOPDUeRnFY0om3ruJnE7/qDzvmXI+SrSLtzl4U8HaLJUd/RkfZB54xGJB8/T6dBHIMs8WneQzKvqB+Kbyzfgs2E+GEjIT/K5OncN2Q91b3a6nv4MI2sLJBMjnEPac27EEp4kZ9B67SwMTI2QDAxIOnaJhz/u01m3LGH7juIf1IUDp35HqcxmzpT3NMu2HfqZ/gGjAPho8af854v3mf/BDJISk5kzpWiqrucG9WLn1r3V3DNqR/Yfp1ugL6F//IpSmc2CqR9olv16YC1DA18AYOX7n7PsfwuZ8/40khKTeacg3agJQ+nUrT15eXmkpaYzb8riasWxf+9hAnv58UfkXpRZ2Ux9Y55m2YHw37Rmoeg/KIRRQ1/RWn/ia2PpFRJAfl4+KcmpTJk0t9J562sZeXAwEo8erRhx9GPysnM5PH21ZtngPUvY0lvdaqHD/JF4DfTFyNyE509/yrVfwji3ckul8ymPkaEBcwZ3Y9LqHahUMgM6NMZbYc8Xoado6uFE9+b1ANgdcZPgNt5/avT+yji0L5yAnl0JO7MDpTKbWZPf1SzbGaZ+0AP4cNEqVn65hHeXzCQxMZlZb6rTderSjpkLpoAMp06c5d1ZS6sVx9VDETQOaM3sw6vIVeawaebXmmVv7VrGqj5zsVXYEzh5EHE3HzF1pzqf4z/u5dSGQ3h1akLIrJHIMtw5dYXf3v2+rKx06Gt53bsnjJ69u3Mu6iBKpZI3XputWXbk+DatWSgGDg5h+BDdS//goX3Z8qvuOA6VZWRowJxh3Zn0xVZUssyATk3xdnXgi50naFrHhe4FFQ+7z10nuG1DrfJqaGDAtEFdefV/W5BlaOLhzBDf6jeH15eyCnDnYCT1A1oxIfxjnihz2fN20blkbOgSfgpRn0v85o2k8QBfjM1NeOWPT7mwPowT/91C7c5N6DZ7BLIs8+iPaxxY8EO1Yyl0cF84AT39CD+7C6Uym7ffLJpFK/TwJq1ZKPoO7M24Ea//qfz09bg5vP8YfkFd2HvqN7Kzspk3tega+tvBdQzqoZ6h4+P3P+PDzxcx74PpJD1OYd5U9b3A0UMn6BrQkR3hG1Dlq/ho0SekJKf+mV0lUHAu6deBST8cUJ9L2nrj7WLHF/sjaeruQPcmHvg2cOPEzRgGr9qGgYHEtOC22FmYkvMkn/Gr1YN2W5oZs2RYV4wMn804+jMXLud0RBQpKWkEDhzD6xPGMqRf76eej5GBAXN6tWTShhPq/dGyDt5ONnxx5ApNXe3o3sAV33rOnLiTwOBvDqj3R0Az7Myf/gwcwr+XVF6TEEmSGgFJsizrvOaQJMlFluXS21oWs9tlpGhzUkyNTP9Rjl5x62s6BPa5jKg40V/gdVX1phl8FkwNqj+a+tOUkF35t2jP0v+ZtarpEDTuGuvHbzPma90ZaGpC0xcq/8D9rA2zrvq0i89CT2XN9NEvaXhm9WYAeBait5TVK/Ov1fT5rytO9Bd407JFTYeg8UnG+ZoOAYDvjPXj+J0sV9z14q90Nb56A0n/Eyl//aDiRH8Ro+6jajoEAPK2/7npbJ8m85dW/KMHuXCybaT3z7QJqdf07jcot2WDLMvXyllWYUWDIAiCIAiCIAiCIAj/PuW+aJckyVCSpFclSXpfkqQuJZa9U9Z6giAIgiAIgiAIgiD8e1XUqv9rwB9IBD6VJGllsWWDn1lUgiAIgiAIgiAIgqAHZFnW+//0UUWVDR1kWR4ly/IqoCNgJUnSFkmSTFFPfykIgiAIgiAIgiAIgqClosoGzXCksiznybL8CnAeOIh6+ktBEARBEARBEARBEAQtFU19eUaSpGBZlncXfiHL8iJJkh4C+jP8qSAIgiAIgiAIgiA8Ayo97aag7yqajWIMgCRJw4DdsiynFwwM2RZ1twpBEARBEARBEARBEAQtFXWjKLSgoKKhKxAEfAd8+ezCEgRBEARBEARBEATh76qylQ35Bf//HLBaluWdFBvPQRAEQRAEQRAEQRD+iWp6pol/6mwUhR5JkvQ1MALYVTAbRWXXFQRBEARBEARBEAThX6SyFQbDgT1Ab1mWUwB7YOYzi0oQBEEQBEEQBEEQhL+timajAECW5SxgS7HPMUBMZdZ1NM6uXmRPWdITs5oOAQAJ/WziIoC1kXlNh6BhJBnWdAgAWBlb1HQIekdvmnQlJ9R0BAC4mTnUdAgaCeTWdAgFKnVpfeZsTPXo+E2Mq+kIAP0pr48M8mo6BA1rcZ7XYmFoWtMhCGVJTanpCDTytuvHpHxG/V6r6RD+NVTiGa5a9Oa+WRAEQRAEQRAEQRCEfwZR2SAIgiAIgiAIgiAIwlMlKhsEQRAEQRAEQRAEQXiq9KNjqSAIgiAIgiAIgiDoIX2dWlLfiZYNgiAIgiAIgiAIgiA8VaKyQRAEQRAEQRAEQRCEp0p0oxAEQRAEQRAEQRCEMqj+4d0oJEmyBzYAnsBdYLgsy8mlpFsBPIe60cI+YKpcTh8T0bJBEARBEARBEARBEP695gAHZFluABwo+KxFkiRfoAvQEmgOtAf8y9uoqGwQBEEQBEEQBEEQhH+vAcCPBf/+ERhYShoZMANMAFPAGIgrb6OiG4UgCIIgCIIgCIIglEHmn92NAnCRZTmm4N+xgEvJBLIsn5Ak6RAQA0jA/2RZvlLeRmukssGmexvqLHoZDA14/Ms+Yj/forVcMjGi3qq3sGjpRV5yOrcn/Yfch/HYD/JD8dogTTrzJnW5HDwD5eU71OrXBdcpw5AMDEg5cIZHS9eWmX+jJeNwCmxDvjKHi1O+JP3CXZ001i3r0fzTSRiamZBwIIJr89UVPUZ2lrRaPRUzDyeyHyRwfuIn5KVm4hTsg/fs4cgqGTkvn2sL1pJy6hrWzerSZMUEjKzMkVUq7qz6jbjfTxTE8SKOBXFcmvIl6RfulBpHs09fx9DMhMcHIrg2/wdNHC1Xv4W5hxPKBwlETVxFXmomFt5uNPtkEjYt6nFz2XrufblDsy2PiSHUHhMIwKN1B7m/elflfrBnrOmq13Dq2Zbcx2mc8H9bZ3kt36a0+nEm2ffjAYjfeYrbKzdXevvGtaxo+d10bFp7Eb0+jGvzvtdJ03rtTDbWtWd4wAsVbm/m+1PpGtiZbGU2C99aytUL13XSGBkbMWfpdHw6t0Elq/h8+WoO7jxM206tmLF4Cg2aeDH3tfc4sDOs0n9HSTPen4Jvj45kK3NYPG0Z1y7c0Enz5a+rcHRxICc7B4DJI98mOTEFF3dnFq6ah7WtFQYGBny+9GuOH/yjWnG8u3Qm3YO6olRmM2vyQi5FXdVJY2xsxHsfzqFjFx9UKhUfL/mcPTsO4uqu+P/2zjs8iuL/46/JJYFUkgBphBJ6L6GHIL0qVZBeVERFQJoCNlQUELGBXwsCYkFFFEWU3qQI0gOhSW9JSEghvc/vj700Lu3C5e70N6/nuee52529ee/s7MzsZz7zWZb87w1cXF3Q6XS8O38pe3YcMDi+uDoCWj2pN38cwlZHenQ8Rwe9UeJzKGkdcajuxY3uc4v9v3ZvjqFq1+ZkJKeyd/pyokKuGaRp+eJQag8JolwFJ76uNyFne/3RXWkwvgcyM4v0xBQOzF5J7MXQEp9LNgcuhbN460mypGRQC3+e6FDfIM3WMzf5fO9ZQFDXqwKLBrcFIOxeEm/8fpQ795IRApaNCKKKm5PRGvIy7c3JtO/alpTkFN6evph/Qgzr67J17+err9NGvEhsVCwAXft14okZ40DCxbOXeWPy26XSMXLeEzTtEkBachorZy3j+hnDdnfGV69QwdMdnU7HP0fO8s2rK5BZWVRtUJ2xbz9Necfy3L0VyefTPiQlIdng+JLUVwDX5rVo/cd8Tj/9ERG/l/z+K6qdB8BG0HbbQlaF3uCJkVNK/L8Ary+cTZfuHUlOTmHW5FcJOZV/DOHk7Mi631fn/Pbx9eKXdX/w5suLjcrnfg5cDGPxluNkZUkGBdTkiY4NDdJsDbnB53tCQEBdLzcWDQnkyNU7vLvlRE6aa3fjWDQkkK4N/EqtxVrqKsCgeeNo0KUFacmpfD/rU26fuWaQZuJXc3D1dMdGZ8OVI+f5+dVVyCxJs75t6TVtCJ61q/DhgFe4dfpKqXXMfXsGD3ULJDk5hZenzufc6QsGaezsbHl54Qu0DgwgKyuLpQs/Y/sfu3P293i4Cx+uWsRjPcdxJtiwn6jcuxW1Zj8GOeOor4g9bJiP96BAajw/CKQkNTyGkOc+Jj06vsTnUmvuMHyHPoStmzO7a47L2e4zrBN1XxvN9+HaJN3aL3/m1+9+L+xvrGYsoMjPgSsRLN4ZovV9TavxRLs6Bmm2ng/l8wNa3arrWYFF/QIIvZfEjF+OkAVkZGYxIsCfoS1qPICOOyzecZqsLBjUrBpPtK9rqOPcbT7ffx6EoK6nK4v6t8rZl5CazuAVu+hSx4e5PZuWWkdxvLLgffYeOIyHuxu/fvtZmeWjMA9CiInAxDyblkspl+fZvwPwLuDQl/P+kFJKIYSBdUUIURtoAGR3stuFEB2llPsK02R+Y4ONDdXeepp/Rs4jPSyKBn+8S+y2w6RcvJWTpNLwHmTcSyAk6Fnc+wfh99JYrkxaQvQve4n+ZS8ADvWrU2vFXJLPXkXn5oLfK+M512cmGdFx1PhgKi4dmhJ/4JRB9pW6NcfJ34f97aZRoWVtGi6ewN99XjFI13Dxk5yduZx7xy4R8N0cKnVtzt1dJ/GfMoCofSFcW/YbNab0x3/KAC6+9R3Re0M4uOUYAM4Nq9Fs+fMcCJpJZnIaIZM/IelqOOW83Gm3fQFRu4Nxa10XR39vDrR7ngot69Bg8ZMcLkBHg8UTODdzOfeOXaTFd3Oo2LU5UbtO4j9lINH7Qri2bAM1pgygxpQBXHrrO9JjE7jw8moq92mV73+c6lfFb3Q3/u79EjItgxY/vETktmMPdClNRegPf3Jz5VYaf/xcoWli/z7HydGlG8xmpqZzedFanOtXxal+VYP9nn3bkJGYUqL/6tC1HdVqVmVA4HCaBDRi7qJZjHt4okG6Cc+PJfpuDIOCRiCEoIK7KwBht+7w+vMLGPPsiFKdSzaBXdtS1d+PRzuMonFAQ2YvnMETjzxbYNrXnnuLc6fyD9ieeH4sOzfu5uevN+BfpzoffPsOA9sON1pH5+4dqFGzGl3bDKB5yya8+e5cHu01ziDdpBkTiIqMpnvbQQghcHOvAMDkmRP4Y8N2vvvyJ2rX9WflD8voFPCIwfHF1RFbV0fqL3qSEyMWkHI7CrtKrkadhynriF/XZrj6e7MuaCaVA2oRuHA8G/u9bpDuxo7jnF29naH7luTbfvnXg5z/dhcA1XoE0HbeaLYaWfczsyQLt5zgs1Ed8XJ1ZNSKnXSq60utyrnlcj0qnlUHLrB6fBdcHeyJznN+r2w4zISgBrSv6UVSWgZCGJW9Ae27tsXPvwrDgsbQKKABsxZOY2K/gq/lG5Pf5vyp/IN2P/8qjJk8kmcHTiX+XgJuFd1KpaNp5wC8/H2Y03kyNVvUYczbE3lroKHx6JPn3ssxIjz36Qu0frg9hzce4PFFk1i74Csu/H2WjkO70mfiAH55/weD40vSpmEjqPPqSKL3GPZTxVFYO59Ntaf6knjxNhhpH+rSPQj/mtXp1PoRWrRqyltLXmFgz1H50iQmJNG382M5v3/f+QNbft9p9DnkJTMri4WbjvLZmC54uTow6ovtdKpXheYjGeYAACAASURBVFqeFXLSXI+KZ9X+s6x+srtWXxO0+tra34sfn+0NwL2kVPot/YP2tQoaR5UMa6mrAA06N6eSvw8LOk+jeovaDHl7Ah8NNBwnfPXcR6Tq6+v4T6fT7OF2nNx4kLALN/nymfcZuuCpUmsA6NgtkOr+VenTbghNWzbmtcUvMqLPkwbpJk57nOi70TwcODRfvwfg6OTI6KeGEXwspNB8oveeJnLLUUAbRzVdPo2/gmbkSyN0NtR7azx/dZxJenQ8dV4dRdUnenFlyU8lPp+7245zc+VWOhz6yGBf+Ia/GPHKW8X+h7WMBRT5ycySLNxxms8ea4eXiwOjvt5Hp9re1KrkkpPmenQCqw5dZPWoDriWtyc6UTMYVnYuz9ejg7C31ZGUlsGjq/bQqbY3ni7lS6dj2yk+Gx6o6Vj9J53qeFMrz9jkenQCqw5eZPWYjvl0ZPO/vecJqFqxlCVRcgb27cHIR/vz0vwlxSdWWD16w8LyIvZ3L2yfEOKOEMJHShkmhPABIgpINgg4JKVM0B+zGWgPFGpsMHvMBqfmdUi9FkbajTvI9AyiN+zHrWfbfGncerYhap1mDY/54y9cggwteh4DOhLzm3Ze5ap7kXo1jIzoOADi9p/CvW/7AvOv3LsVoes0g8W9Y5ewdXXE3jP/YMDe0w1bZwfuHbsEQOi6vTmDOs/erQhdqx0funYvnvrtmUm5jYTOsRzZMTmTroSRdDUcgNQ7MaTdjcO+oiuVe7cmLEfHRWxdnYrQoc2qhK3bi2ef1rnnsfZPvY4/c7an340j7uRlZHpmvv9yqlOFe8cvkpWchszMIuavs3g+nL/cLUXsoXOkxyaU6ljvR4Nos+Vt2u18hwbvPgU2hk9FWUmpxB6+QGZqusE+nWM5qj3zMFc/WG+wryA69+7I7+u2AHD6+BlcXJ2p5GnYGfQf/jCrln4DgJSS2Oh7AITdCufiuctkZWWV+BwL4qFeQWz6aSsAIcfP4lLBmYqeHiU+XkqJk4sjAM6uzty9E1UqHd37dOaXH7WZn5PHTuNawYXKXpUM0g0d2Z9PP1qVk3dMdGzOd2dn7YnIxdWFiPDIAvMpro54Dw4iYtNhUm5r55F+Ny53n5nrSPWeLbn0034AIo9fxt7VCQdPwweOyOOXSY6INdienmem3NaxHEUE+C2UkNBoqro74+fujJ3Ohl6NqrLnQn7viPUnrjKsdS1cHewB8HDSBlSXI+PIzJK0r6l5zzna2+Jg92B26aBegWz5aTsAZ46fM7q+9h/5MOtXbyD+nlYHsmeQjaVFz9b8tV5rN6+cuIijixMVKhtem2xDg85Wh62dLdkNupe/Dxf+Pqudx/5gWvZpV2A+JWnTqk3ow53f/ybt7r1826tP6kebLQtot3sxNV8YWuCxhbXzAOV8PKjUowW31+wqMv+C6NGnCz+v3QjAiaOncK3ggmcB93M2/rWqU7GyB4cPPpjhOuR2NFU9XPDzcMbOVkevxtXYc+F2vjTrj11mWOs6ufXV2fABYPvZm3So44ODfenrq7XUVYDGPVtxdL02Trh+4hIOLo64FFBfsw0NNrY6dHa2ZHv6RlwOJfJKmEF6Y+na+yF+W7cZgFPHQnBxdSmw3xs0oh9fLNW8QPP2ewBT5zzNyo+/yfEEKYjCxlH5EAIQ6BzLAWDr4kDqHS1YukN1L1p8P5e22xbSasPrONb2LTCfe8cuklZA22sM1jIWUOQnJCyGqm5O+Lk5aX1fA1/2XArPl2b9qRsMa1ED1/LZfZ9Wl+x0Ntjb6gBIy8wqVd+bT4d7Hh0Nq7Dn4n06gq8zrKW/gQ6As+GxRCel0r6GZ6k1lJRWzZtQwdWl+IQKsqS0+s8D8huQPWM4DthQQJobQCchhK0Qwg4tOGSRyyhKbWwQQqwtzXH2Ph6khd3N+Z0WHoW9T/6O3N47T5rMLDLjkrB1z38juPcLImqDZmxIvRZG+Vq+2Pt5gs4G915tsfcteIBU3scj54EEICUsmvL35V/ex4OUsOjcNKG5aewrV8jppNIiYrGvnDvz4tmnNR32v0fAt7M5M93QFcm1RS2EnS1J1+5Qzsf9Ph1RJdJRzse9WB0FkXj+Jm5t62Pn7oyNgz2VuregfJWyt5iaigot69Ju12JafDcHp3qa545TnSp4DwzkyCOvcajbbGRmFj6PdjTqf2vNGcb1T38nMzmtROk9vStxJzTX0BcRFkFln/x1zdnVGYBJsyewZttK3lk+H49K7kbpMlpHaCSe3pULTPvqB3P4dvsKnpiWu0Tki/e+pPfgnmw8uo4PvnmHJS8bzvCUBC8fT0Jv58aFCQ+NwNsnvw4XfXlMnzuJDbvWsGzlO1SsrNX1jxZ/zsChfdl/ajMrf1jKG3NL573iWMsHuwpOtFz/Gm23LcRn6EOAZeqIo7c7iaG593ZSWDRO3sZd/wbjujN0/3u0fnk4h14rfElYYUTEJePt6pDz28vVgYj4/O7+16MSuB4Vz7gvdzNm1S4O6Adk16PicSlvx4wf/2LY8h28v+MUmVkP1oFV9q5ERL77JpLK3gW30S+9/yKrty1n/LTROduq1vSjak0/Pv11Kcs3fkzbzq1LpcPNy4Po0Nz+JyY8CnfvgtvBmV+/ykfHVpGSmMyRTYcACL14kxY92wDQqm8gHj6FP4gXRTlvdzz7tObW6u35tnt0aopjTW8O936JQ11n49rMH7d2DYz673rzx3HxzTVQimvm7eNJ6O3cAXF46B28fAof7PYb1Jvff9lqdD73o9VXx5zfXq4ORMTdX1/jtfq6cgdjvtjOgYuGD9FbQ27Qp3G1B9JiLXUVwNXLg9g8bUlseDQVvAs2fEz8ei5vHvuc1MQUgvX11VR4+lQmPE87fycsAq9C2vkps59m3faveP+LBTntfIMm9fD29WJvAUvk7qdyn9YE7n+fFt/O4ez0Tw32y4xMzs1eQfs97/LQqc9wquuXY1hr8N5TXHjpS/7uOZd/3viWBu8Yel8Uh9cjbVm7czWLv5iPl2/hdd9axgKK/EQkpODtkqfvcylPRHx+r8Tr0Qlcj0lk3Jr9jPlmHweu5F7H8Lhkhn65h96fbmd829ql8moAiIi/X4dDwTqiExj3zT7GfL2XA1e0eyxLSt7bGcKMLo1KlbdC8QAsAnoIIS4C3fW/EUK0EkKs0Kf5CbgMnAaCgWAp5cai/vRBPBsKdh0wA04t6pCVkkrKhRsAZN5L5Prcz6n56Szqr19A6s0IZKaZrMV5rEgRm49wIGgmJ8cvofbsx/Ils/d0o8nHz3F22qcUbK43nY6CSLx4m2sf/0bA2pcJ+P4l4kOuma+MHpC4U1fZ3/I5DnV9kZsrt9B8tbYG2qNjY1yb+tN26wLa7XwHj46Ncaheciuwc6PqONbwInLzEZPqtbXV4V3Fi+AjIYzq+SSnjoUwfV4R7tRlyGuT32Jkt8eZOHAKzds2pe+QXgD0Gtid33/cTL9WQ5k+ZjavL3sZ8aC+8oVga2uLTxVvjh8OZkDXUZw4eoq5b0wHoN/gXvz8w0aCmvbhyeFTWfLJ/FLpEDobXJrV5MTodzg+fAE1ZwzGsaaP1daR4jj31Q7WBc3kyIIfaD61oGDAD06mzOJGdAIrxnZi0aC2vPnHMeJS0sjMkpy4cZcZPZqyZkJXbsck8lvwtTLRcD9vTFnA2O4TmDToeZq1aUrvIT0AzcPAz9+PyUOmM2/SW8x+dybOrg8WQ6I43hs7n2ltJmBrb0eDwMYArHzxE7qO7sW8jYtxcC5PZnpGqf673vzxXHzrO4N2u2LnplTs1JR2O9+h3Y5FONWugmPNki8JqKSPExF/yjAORVnQf3BvNqw3T+yfzCzJjeh4VozvyqIh7Xlz42Hi8hgAI+OTuRRxj/a1fcyix5rqKsDysQt5vc2z2NrbUkdfX82JzlaHTxUvTh45zdAe4wg+eppZ86YihODFN55n8eslM2hHbj7CX0EzODl+CbVmDzPYL2x1+I3vwaFuc9jb9Bniz17H//lB6BzL4daqHk1XTKfdzndo+O5T2Hsa92B/d9sx9rWazLBu4/l771He/OjlYo8pCmsaCyhyycyS3IhJZMXwQBb1a8mbW4OJS9G8Gr1dHVj3eGd+e6obG0NuEZVYuCeOSXREJ7BiZAcW9W/Jm5tPEpeSzo/HrxJUywuvPBMGCoU5kFJGSSm7SSnrSCm7Symj9duPSikn6L9nSimfllI2kFI2lFLOKPpfyyhmQ97gFHPdmjHYqUbOvrSwaOzzWH/tvSuSlmf2HiAtXEuTHhYFOht0ro5kxOQG//Ho35HoX/MvDbm34wj3dmgPBJVG9YQ8rmmVx/Wh7gjtISvu5OV8M/r3ew+AobdDed/cNGmR97D3dNO8CTzdSMvjrp1NzKHzOFT3xM7DhfToeHTODgSsmU3MofM0WKwFgrtnoKNiiXSkhsWUWMf9hH63m9DvtOUptV8aTkpodDFHWAeZedzK7+48Sf1FOuw8XEAIQn/cy6W3v8+XvnKf1tSaNQSAszM+Jy644KBYbq3q4tqsJkFHliFsdegqubL852VMfDR/QLXHxg9m0Kh+AJwJPpdvtsPTx5PIPJ46ALHR90hOSmbXJs1de8fG3QwcYRiHwFiGjB/IwFHa/5w9eSG/Dt/KBS5BiAzXtCUlJrP1lx00bFGfTT9tpf+Ivkwd9QIAp4+doVw5e9w8KhBTApff0U88xrAxWqDW0yfP4FvFi2wnam9fT8LD8uuIiY7V8v9dm33avGEHQ0dpD9BDRw3kiccmA5rbdrly9nhUdCPqbkxJiwWA1LBoomISyEpKJSsplZhD53BuVN3kdcS+UgX6rnuZTUPzB3xrMK479UZ2AeBu8BWcfHPvbUcfDxLDjTufbK5sOESHBY8bfZynqwPheWaG78Ql4+mSf+Di5eJI4yoe2OlsqOLuRHUPZ25EJ+Dl6kA9Lzf83LVZuS71fDl1O5pBGMfgcQPoP+phAM6dvIBnvvumck7dzMvdPPV1+687adi8AVt+2k5kWCRnjp8nMyOTsJvh3LxyCz9/P84HGwaPu5+uY3rTaYS2RPFq8CU88ni9uXtXJCa88CVEGanpnNh+mIAebTi7/xThl2/z3tj5gLakommXliUoCUNcm9ekyWdTAbCr6Eql7i2QmZkIIbi6dAO3v9mRL73f4z1zgvueGLkox238ftza1KNyr5ZU6tYcm/L2ZDmX48PPFjDtmZcK1TL2yWEMH/MoAKdOnMG3Sq5xw9vXizthBS3ZhAaN6qLT6QgJLtJ7skRo9TUp5/eduGQ87xtoe7k60Nivor6+OlO9ogs3ouNprO9Ht525QZf6VbDTGT+HYi11FaDDmJ60G9EVgJvBl3HL05a4eXtwL7zwfjsjNZ2Q7Udp3KMV/+w/XaL8CmPE40MYMnoAACEnz+JdJTcouZePJ3fua+djo++RlJScExBy68adDB7ZHydnR+rUr8Xq9Z8AUMmzIh9/vYTJY2dxJvh8vnwiRr6fU7djD53LN47KxqVxDQCSr2uzwHd+O4T/lAHc+GIzGXGJHOo2O/+J2AjabV8EQOTWo1xevK7Qc06P0S99soFf1mxk6iv54yBZy1hAUTiezuUJz+PFdyc+xcA7wcvFgca+blpb4uZIdXdnbsQk0tgnd4mSp0t5ald24fitKHrUK3g5TpE6XO7XkVyMDn0fHJNA8O0YTtyK4sfjV0lOzyQ9MwtHex3Pd1aeDpbmQZbW/H+myF5ZCBFQyKcl2ns1C0RKuVxK2UpK2SqvoQEgMfgi5f19sK/qibCzxWNAELHbD+dLE7v9MBWHagN394cDiT+Qp9MUAvd+HYj+Lb+xwbaitoxAV8EJz7F9iPwu1z018qvNHOo2h0Pd5hCx+Si+ehfrCi1rkxGfZLB2Ly0iloyEZCq0rA2A79CHcoIWRW49hu8w7XjfYQ8Rod/uUCO3I3ZpUgMbezvSo+MRdjqar55J6Lq9nJ25nEPdZnOo22wiNx/JcfWu0LJOMTq0SLo+Qx8icssRvY6j+A7rpNfRKUdfUWQHzStfpSKefdsQvn5/scdYA3mXiLi2qAU2NqRHxxO97zRej7TNOS9bNyfK+1UicvORnHIu7CES4NZX29nb7Fn2t57Ckf7zuH7lpoGhAeDH1esZ0eNxRvR4nD2b9/HIUC0YWZOARiTEJ3A3wvBhZe+2A7QKbAFAm6CWXPnn2oMUAQA/rf6V0T0mMLrHBP7csi/HS6FxQEMS4hKJisg/CNXpdFTw0N8XtjqCurfnynltxjP8dgStg7QHpRq1q2Nfzr5EhgaAb1f9SL8uI+jXZQTbNu1h0GPa4Kl5yybExyUQecdwYL5r217aBWnxTQIfasOlC9p1CbsVTuBDmlt6rTr+lCtfzmhDA0DklqO4ta2H0Nlg42BPhYA6JF68bfI6knQlzMDQAJonwq+9XubXXi9zfcsxag8JAqByQC3S45MKjM1QGK7+uW1J1W7NuXc1vIjUBdPI150b0QncjkkkPTOLrWdu0qlu/hnfLvV8OXpde2CISUrlenQCfm5ONPL1ID4lPSdY1eFrEdSsZPx6zvVfbWB8z4mM7zmRvVv358z8NgpoUEh9tckJnqaz1RHYvR1XLmj1de+WAwQENgOggrsrVWv6EXqjZGvRd32zhXl9ZzGv7yyObztM4GCt3azZog7J8Unci8x/bco5ls+J42Cjs6FZ15aEXdbiB7hU1PQJIeg3eQh71mwzulwA9reekvOJ2HiIc7NXErn5KHd3B1NlZOec9ejlvN2xq+TKrS+35dTXwgwNAJfe/p59LSaxv/UUTj/9EX/tO1ykoQHg65Vr6dv5Mfp2foxtm3bx6DDtYapFq6bEx8UTUcD9DND/0T78tn5Lqc7/fhr5enAjKp7bMQmkZ2SyNeQGnepVyZemS30/jl7TDB8xialcj4rPMYgBbDl9gz5Nqpcqf2upqwAHvtnGe33n8F7fOZzedpRWg7VxQvUWtUmJTyL+vvpq71guJ46Djc6GBl0DiLhs/Ntr7uf7L3/i0W5jeLTbGHZu3kv/oX0AaNqycaH93p5t+2nTIQCAdh1bc/mfqyTEJxLUsBc9Ww+iZ+tBBB8LyTE03J+PjT4eB4BLE/+ccVReUsOica7rh11FrU2q2KkJiRdvk5mQTPKNCDz75cZRcW5YHbJkzr1TlKEByBc3q1OvIK5dvJ5vv7WMBRSF08jHjRsxidyOTdL6vnOhdKqd3zusSx1vjt7QrlVMUirXYxLwc3PkTnwyKfo4OHEpaZy4FU0ND2eDPEqsIzqR27H6PvjsbUMdde/Toe+DF/ZvyZZJPdk8qSfTuzTikcZVlaFB8a+mOM+G94rYZ/jeopKQmcWNV7+g7pp5YKMjau0OUv65ie+sESQGX+Le9iPc/WEH/h9No/H+T8mMjefypFwZLu0akRZ6l7Qbd/L9bdU3nsSxoT8AoR+uJfVqwZ3t3R0nqNStOUF/f6S9cvL53NgK7XYu4lC3OQCcm72Kxkufxaa8PXd3nuTuzpMAXF22gaZfTKPKyC6k3LpL8FMfAto6P9+hHcnKyCQrJY1TEzWXQe/+7XFvp8VK8B3WCQGETP1Er6MFHf7+iMzkNM4+/2keHe/kWOfPz15Jo6WTsClvl0/HtWUbaKLXkXzrLqee+gDQHszbbluIrYsDMktSbWJf/uo4k8yEZJqtnIGduwsyI5Pzc1eRkWcmyZI0+Wwq7oENsfNwoeOJT7j87jps9EF6bn29A69+7fAbp70KMDMljdNPa2Wb+M9tLi1aS8u1L4ONQKZr55Vyy3BwHHRkGbYujgh7Wzz7tOb4sLdJ/Oe2Qbri2L/zIEHd2rPh4FpSklN4ffqCnH3fb/+SET20Weilb3/K/GWvMuvNqcRExfL69IUANGxWn/dWLcDVzYWHenTgmReeZGjnMUbrOLDzEIHd2rH+r+9ISU5l/vRFOfu+3b6C0T0mYGdvx9Lv3sXW1hadzobD+47x6xotmONHb/yPl5a8wMinhiKRvKnXZyx7tu+nc/cgdh3ZQEpyCrOnvp6zb+Pu7+nXRYu0/c4bS3nv0/m88tYsoqNieHGKlm7Ba++z4INXefyZUUgpeXHyvALzKa6OJF68TdSuYNrtfhek5PaaXSSevwlg9jpyc9dJ/Lo2Y+j+98hISWPfjNygwAO3vs2vvTTX3NYvD6fWwEBsHewZfmQpF77fw4n319NwfE98gxqRlZFJ6r1E9k7/3GgNtjY2zOndnGe/20eWlAxoVoPanhX4ZM8ZGvq407meL4G1vDh45Q6DP92KjRBM79YUN/1D7vQeTXn6271IKWng486jATWN1pCXgzv/pn3Xtvx44FtSklNYMCM3NsfqbcsZ33Midvb2vP/dYmxtdeh0Oo7sO8Zva/4A4O89R2jTqRXf7l5FVmYW/5v/OXExxXtz3c+p3cdp2iWAd/78H2nJqax84X85+97YtIR5fWdRzrEcz6+Yi629HcJGcP5gCLvXaHEJ2vXvSNcx2gPGsa1/s29dwUEYi6uvhRH95ynC6lah9SYtGn5mYgohkz7OF/AUim7nH4Rd2/fRpUdH9h79Q3v15ZRXc/Zt2vNjvrdQPDKgF+OHT3qg/LKx1dkwp29Lnv3mT7JkFgNa1NTq667TNPT1oHP9KgTW9ubg5XAGf7wJGxvB9B7Nc+rr7ZgEwuOSaGnEEqnCsJa6CnBu9wkadGnOS39+RHpyKt+/kDtemblpEe/1nYO9Y3meXPECtva2CBsbLh08w19rtMmWJr1aM+j18Th7uPLUqhe5fe46y8ca39bv3XGAh7oFsvnvn0lJTuGV5+fn7Pt55zc82k3rw96f/zGLPn6d2fOnExMVmy9dSfB6pC0+Qx9CZmRqff3ED3P2ZY+LUu/EcGXJT7T69Q1kRgYpt+5yZqrmNXF60jIavDOBmtMHI2x13Pn1LxLOXjfIp86ro/Ae3AGdgz0dT3zC7TW7uLLkJ6o91YfKPVvyQ2Yq92LjmDet8FeWWstYQJEfWxsb5nRvzLPrDml9X5Oq1K7kwif7ztPQ243OdbwJ9K/MwWuRDF65W+v7OjfEzcGeg9cieX/3GQQCiWRs61rUqWzcm63y6ejZlGfXHtR0NK1G7cqufLL3HA193Ohcx4dAf08OXo1k8Bc7tTatSyPc8hjczMUL8xZx5MQpYmPj6DZwNJOeHMOj/XqZXYfiv4soa5eQo34DrcLnJDq9dEFeTI3AKoojhx53ShXn06Rs9zJcl2kJZtsY/2BZVtgKnaUlABCVVvJ3l5cln+kM35NtKW7YFerUZVZGLirdLK6p6T77oKUl5FDXzjqCr41MNv9bpQtiQsaDL3EwFec/NnYhTtnQfVahb+cyK23tyj7KfEnZmmyeGB/F8SE1LC0BsK6xAMDxsH+HF6o5SF45y9IScrEx+wv9CsS23zOWlpCDXaWaZRP8y0ooX76adT3EFUBKyg2ruwZFjoiEEIPv2ySBu8BJKaV1PIUoFAqFQqFQKBQKhUJRRkgrmzD+t1Dc9Eu/ArZ5AE2FEE9KKY1/kbdCoVAoFAqFQqFQKBSK/zRFGhuklAWGQRdCVAd+BNqWhSiFQqFQKBQKhUKhUCgU/15KtbBUSnldCGEdC5cVCoVCoVAoFAqFQqEoI9SrL0tHqaKbCCHqAakm1qJQKBQKhUKhUCgUCoXiP0BxASI3gkE0DA/ABxhdVqIUCoVCoVAoFAqFQqFQ/HspbhnFkvt+SyAKuCilTCsbSQqFQqFQKBQKhUKhUFgHahlF6SguQOSfBW0XQtgIIUZJKdeUjSyFQqFQKBQKhUKhUCgU/1aKjNkghHAVQswVQnwshOgpNKYAV4DHzCNRoVAoFAqFQqFQKBQKxb+J4pZRfAPEAAeBCcBLgAAGSilPlrE2hUKhUCgUCoVCoVAoLIpaRFE6ijM21JRSNgEQQqwAwoBqUsqUMlemUCgUCoVCoVAoFAqF4l9Jca++TM/+IqXMBG4pQ4NCoVAoFAqFQqFQKBSKohBFRdYUQmQCidk/AQcgSf9dSildy1yhpmOilHK5OfIqDmvRonQYYi1alA5DrEWL0mGItWhROgyxFi1KhyHWokXpMMRatCgdhliLFqXDEGvSovhvUaRng5RSJ6V01X9cpJS2eb6bxdCgZ6IZ8yoOa9GidBhiLVqUDkOsRYvSYYi1aFE6DLEWLUqHIdaiRekwxFq0KB2GWIsWpcMQa9Ki+A9R3DIKhUKhUCgUCoVCoVAoFAqjUMYGhUKhUCgUCoVCoVAoFCbl32JssKY1RNaiRekwxFq0KB2GWIsWpcMQa9GidBhiLVqUDkOsRYvSYYi1aFE6DLEWLUqHIdakRfEfosgAkQqFQqFQKBQKhUKhUCgUxvJv8WxQKBQKhUKhUCgUCoVC8S/hX2dsEEK0EkIs1X/vLIQItJCOyUKIS0IIKYSoZAkNebSsEUJcEEKECCFWCSHsLKRjpRAiWAhxSgjxkxDC2cz5W8U1UdejSE1LhRAJFsx/tRDiqhDipP7T3EI6hBDibSHEP0KIc0KIqZbQodeyL095hAohfrWQjm5CiON6HfuFELUtpKOrXkeIEOIrIYStGfMusA3T15el+n2nhBABFtRSXwhxUAiRKoSYZUEdo/RlcVoI8ZcQopmFdAzQ6zgphDgqhAgqSx1Facmzv7UQIkMIMcQSOvRjs3t52pXXLKEjj5aTQogzQog/y1JHUVqEEC/kKY8QIUSmEMLDAjoqCCE26scGZ4QQj5eVhmJ0uAshftHfO4eFEI3LUoc+zwLHZuZuX4vQUWZtq76+Zde9jUIIN/32zkKI3+9Luzq77RBC7BFCtDKlFsX/P/51xgYp5VEpZfbAvDNgEWMDcADoDly3UP55WQPUB5oADsAEC+mYLqVsJqVsCtwAJps5f2u5Jup6FIC+w3K3pAY9L0gpm+s/Jy2kYTxQFagvpWwA/GAhHUgpsdlyXQAACOVJREFUO2aXB3AQWG8hKZ8Co/Q6vgNeMbcAIYQN8BUwXErZGK0tGWdGCYW1YX2AOvrPRLSyspSWaGAqsMQMGorScRXoJKVsAsyn7NcbF6ZjJ9BMX2+fAFaUsY6itCCE0AHvANssqQPYl6edfdMSOvQPVJ8A/aWUjYChZayjUC1SynfztLNzgT+llNHm1gE8B5yVUjZDG0O/J4Swt4COl4CT+vHJWOCjMtSQTWFjM3O3r4XpKMu2NVlf/xrr83muDPJQKArE4sYGIUQNIURInt+zhBCv661p7+gtnv8IITrq93cWQvwuhKgBPANM11vrOppIzwy95S9ECDFNCOEkhPhDbwUOEUIMA5BSnpBSXjNFnibQsknqAQ4DfhbSEadPL9Aa0DILCFKQBnNckxLqKNPrYYQOs12P4rToB8DvAi+aQ0NhOsyVdwl0PAu8KaXMApBSRlhQS/Y+V6ArUOaeDYXokICrPkkFINTcOtAeRtKklP/ok2wHHjVH3sW0YQOAr/XNyiHATQjhYwktUsoIKeURIN1U+ZdSx19Syhj9z0OYsJ01UkeCzA1+5YSJ29lS9HVTgJ8Bk7YpVt7nFqZjJLBeSnkDTN/OPkCZjAC+t5AOCbjoxwXOaA+eGRbQ0RDYBSClPA/UEEJ4mUJHEVoKG5uVWftqjI6ybFvv4yBQpYzzUChyMJt7aCmxlVK2EUL0BeahWUcBkFJeE0J8BiRIKU1iBRRCtAQeB9oCAvgb0AGhUsqH9WkqmCKvstAiNFesMcDzltIhhPgS6AucBWaaSkcB9C5Mg5kpVEdZXA9jdZjxehSnZTLwm5QyTBvjWExHH+Btobn17gTmSClTLaDjE2CYEGIQEAlMlVJeLGMdhWnJZiCwM9tIZQEdocAmIUQyEAe0s5COxUKIVlLKo8AQNA8Uc+VdGFWAm3l+39JvC7OAlrKktDqeBDZbSof+Pl4IeAIPm1CHUVqEEFWAQUAXoLWldOhpL4QIRruvZ0kpz1hAR13ATgixB3ABPpJSfm0iHcZqQZ/GUX+cKT0NjdHxMfAb2nVxAYZlG73NrCMYGAzsE0K0AaqjPXTfKWstBYzNyrJ9tZYxYnaeOqAbsNJceSoUFvdsKIZsd95jQA0z5BcE/CKlTJRSJujzTwd6CM3LoqOU8p4ZdJRWyyfAXinlPkvpkFI+DvgC54CynEk+XZgGM1OUjrK4HkbpMOP1KFQL2mzfUGCZmfIvUIe+TOaiuS+2BjyA2RbSUQ5IkVK2Ar4AVplBR2FasjHpbFspdEwH+kop/YAvgfctpGM48IEQ4jAQD2SaMW9LYS1ajNYhhOiCZmww5b1slA4p5S9SyvpoBrv5JtRhrJYPgdkmfHgsrY7jQHWpueovw7TeUsbosAVaohmAegGvCiHqWkhLNv2AA9K0SyiM0dELOIk2LmgOfCw0rzZz61iE5kFwEs0b5wSmbWutemxmAR0O+rIOB7zQvPagcE8s9apChcmwBmNDBvl1lM/zPXvGMRPLemEEoDUYb4kyDnRUWi1CiHlAZWCGJXUASCkz0dagl4n7sT6Pf4rSYC4K02Hu61FUeZjjehSlBXgKqA1cEkJcAxyFEJfMrUMI8ZqUMkzvvZiK9kDbxhI60GZOso2pvwBNy1pHEVoQWuCuNsAfFtIxD23d+9/6JGsxQzyeQurIQanFsWgD7AX+KfJPTJh3Eclvk9/Dwk+/zRJaygxjdQghmqLFSBggpYyylI48x+0FagoTBig2Uksr4Ad9OzsE+EQIMdDcOqSUcfrJCaSUm9C8C0xSJkaWxy1gq36y5C7a/WyyQKKlrCfDMbFR10gdj6MtLZFSyktosU/qm1uHvo48LrUYFmPRxktXTKGjKC2FjM3KrH21ljEi+pgNaB4kgtyYDVEYxtLyAO6aSZfi/wHWYGy4A3gKISoKIcoBjxhxbDyaG5ip2AcMFEI4CiGc0NwRjwFJUspv0dacl3kUcGO1CCEmoFmrR5TBjEaJdAiN2no9AugPnDexlhyEEL73ayirvIzVUcbXo6Q6WprzehSjpYWU0ltKWUNKWUO/r8zfNFDItfHR7xNos5AhRfxFmelAm+nrok/SiTJ6oC2hFtAeTH6XUqZYSEdroEKeWcceaN445tYRIITw1O8rhzZb/pm58i4i+W/AWH072w64J6U01RIKq25Pi0hbDc1gN0bmxtiwhI7a+vYEoUWxL4c2gDe7Fimlf5529idgkpTSJF4FRpaJd54yaYM21jRJmRhZVzcAQUIIW6EtX2iLCdsVY+8bobnQd9LrMhlG6riB5kaP0GIk1MNED/lG1hE3kRuYcgLaDL/JlvAZOTYrs/bVWsaI2Ugpk9CCUM4U2puWLgK+QogGer3V0QxylgqerfgvIqW0+Aet4l9GszqvBl4H9gCt9PsrAdf03zujDYpBW493Cu2m6GgiLTPQHkBCgGloDUJ2HkfyaJqKZjXPQFv7tqIMyqWkWjL05XdS/3nN3DrQBhMH0Ky3IWjRdl3LsM4UpKHMr0kJdZTp9SihjjbmvB7Flcl9+xMspQMtIFV2mXwLOFtIhxuaF8FptGBNzSx5bdDa297m0FBEmQzSl0ewXk9NC+l4F+2B5AIwzcx5F9iGoc1E/U/frpy+/54ysxZv/fY4IFb/3SRti5E6VgAxedrZoxYqj9nAGX3ag0CQpa7NfcetBoZYqEwm68skGC14Z6ClygN4AS1mUYip7+dSaBkP/GBKDaW4Nr5obyrJ7gdHW0hHezQj+wU0o6G7GcqkwLEZZdi+GqmjLNvWhPt+b0Qz1AJ00N+n2Rp75Em3B21S+Jb+s87U9Vd9/vsfIaValqNQKBQKhUKhUCgUCoXCdFjDMgqFQqFQKBQKhUKhUCgU/yGUsUGhUCgUCoVCoVAoFAqFSVHGBoVCoVAoFAqFQqFQKBQmRRkbFAqFQqFQKBQKhUKhUJgUZWxQKBQKhUKhUCgUCoVCYVKUsUGhUCgUCoVCoVAoFAqFSVHGBoVCoVAoFAqFQqFQKBQmRRkbFAqFQqFQKBQKhUKhUJiU/wNH0DG2MAl8ggAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10baeed10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "corr = data.corr()\n",
    "plt.subplots(figsize=(20,15))\n",
    "sns.heatmap(corr, \n",
    "            xticklabels=data.columns.values,\n",
    "            yticklabels=data.columns.values,annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature extraction\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting submissions/starting_kit/feature_extractor.py\n"
     ]
    }
   ],
   "source": [
    "%%file submissions/starting_kit/feature_extractor.py\n",
    "\n",
    "class FeatureExtractor(object):\n",
    "    def __init__(self):\n",
    "        pass\n",
    "\n",
    "    def fit(self, X_df, y_array):\n",
    "        pass\n",
    "\n",
    "    def transform(self, X_df):\n",
    "        return X_df.drop(\"unit\",axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The regressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting submissions/starting_kit/regressor.py\n"
     ]
    }
   ],
   "source": [
    "%%file submissions/starting_kit/regressor.py\n",
    "from __future__ import absolute_import\n",
    "from sklearn.base import BaseEstimator\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "\n",
    "class Regressor(BaseEstimator):\n",
    "    \n",
    "    def __init__(self):\n",
    "        self.reg = RandomForestRegressor()\n",
    "\n",
    "    def fit(self, X, y):\n",
    "        return self.reg.fit(X, y)\n",
    "\n",
    "    def predict(self, X):\n",
    "        return self.reg.predict(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Local testing (before submission)\n",
    "\n",
    "It is <b><span style=\"color:red\">important that you test your submission files before submitting them</span></b>. For this we provide a unit test. Note that the test runs on your files in [`submissions/starting_kit`](/tree/submissions/starting_kit), not on the classes defined in the cells of this notebook.\n",
    "\n",
    "First `pip install ramp-workflow` or install it from the [github repo](https://github.com/paris-saclay-cds/ramp-workflow). Make sure that the python files `feature_extractor.py` and `regressor.py` are in the  [`submissions/starting_kit`](/tree/submissions/starting_kit) folder, and the data `train.csv` and `test.csv` are in [`data`](/tree/data). Then run\n",
    "\n",
    "```ramp_test_submission```\n",
    "\n",
    "If it runs and print training and test errors on each fold, then you can submit the code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[38;5;178m\u001b[1mTesting Predictive maintenance\u001b[0m\n",
      "\u001b[38;5;178m\u001b[1mReading train and test files from ./data ...\u001b[0m\n",
      "\u001b[38;5;178m\u001b[1mReading cv ...\u001b[0m\n",
      "\u001b[38;5;178m\u001b[1mTraining ./submissions/starting_kit ...\u001b[0m\n",
      "\u001b[38;5;178m\u001b[1mCV fold 0\u001b[0m\n",
      "\t\u001b[38;5;178m\u001b[1mscore  Relative RMSE\u001b[0m\n",
      "\t\u001b[38;5;10m\u001b[1mtrain\u001b[0m          \u001b[38;5;10m\u001b[1m0.275\u001b[0m\n",
      "\t\u001b[38;5;12m\u001b[1mvalid\u001b[0m          \u001b[38;5;12m\u001b[1m0.600\u001b[0m\n",
      "\t\u001b[38;5;1m\u001b[1mtest\u001b[0m           \u001b[38;5;1m\u001b[1m0.456\u001b[0m\n",
      "\u001b[38;5;178m\u001b[1mCV fold 1\u001b[0m\n",
      "\t\u001b[38;5;178m\u001b[1mscore  Relative RMSE\u001b[0m\n",
      "\t\u001b[38;5;10m\u001b[1mtrain\u001b[0m          \u001b[38;5;10m\u001b[1m0.255\u001b[0m\n",
      "\t\u001b[38;5;12m\u001b[1mvalid\u001b[0m          \u001b[38;5;12m\u001b[1m0.599\u001b[0m\n",
      "\t\u001b[38;5;1m\u001b[1mtest\u001b[0m           \u001b[38;5;1m\u001b[1m0.449\u001b[0m\n",
      "\u001b[38;5;178m\u001b[1mCV fold 2\u001b[0m\n",
      "\t\u001b[38;5;178m\u001b[1mscore  Relative RMSE\u001b[0m\n",
      "\t\u001b[38;5;10m\u001b[1mtrain\u001b[0m          \u001b[38;5;10m\u001b[1m0.272\u001b[0m\n",
      "\t\u001b[38;5;12m\u001b[1mvalid\u001b[0m          \u001b[38;5;12m\u001b[1m0.604\u001b[0m\n",
      "\t\u001b[38;5;1m\u001b[1mtest\u001b[0m           \u001b[38;5;1m\u001b[1m0.445\u001b[0m\n",
      "\u001b[38;5;178m\u001b[1m----------------------------\u001b[0m\n",
      "\u001b[38;5;178m\u001b[1mMean CV scores\u001b[0m\n",
      "\u001b[38;5;178m\u001b[1m----------------------------\u001b[0m\n",
      "\t\u001b[38;5;178m\u001b[1mscore   Relative RMSE\u001b[0m\n",
      "\t\u001b[38;5;10m\u001b[1mtrain\u001b[0m  \u001b[38;5;10m\u001b[1m0.267 ± 0.0089\u001b[0m\n",
      "\t\u001b[38;5;12m\u001b[1mvalid\u001b[0m  \u001b[38;5;12m\u001b[1m0.601 ± 0.0024\u001b[0m\n",
      "\t\u001b[38;5;1m\u001b[1mtest\u001b[0m    \u001b[38;5;1m\u001b[1m0.45 ± 0.0047\u001b[0m\n",
      "\u001b[38;5;178m\u001b[1m----------------------------\u001b[0m\n",
      "\u001b[38;5;178m\u001b[1mBagged scores\u001b[0m\n",
      "\u001b[38;5;178m\u001b[1m----------------------------\u001b[0m\n",
      "\t\u001b[38;5;178m\u001b[1mscore  Relative RMSE\u001b[0m\n",
      "\t\u001b[38;5;12m\u001b[1mvalid\u001b[0m          \u001b[38;5;12m\u001b[1m0.601\u001b[0m\n",
      "\t\u001b[38;5;1m\u001b[1mtest\u001b[0m           \u001b[38;5;1m\u001b[1m0.433\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!ramp_test_submission "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Submitting to [ramp.studio](http://ramp.studio)\n",
    "\n",
    "Once you found a good model, you can submit it to [ramp.studio](http://www.ramp.studio). First, if it is your first time using RAMP, [sign up](http://www.ramp.studio/sign_up), otherwise [log in](http://www.ramp.studio/login). Then find an open event on the particular problem and sign up for the event. Both signups are controled by RAMP administrators, so there **can be a delay between asking for signup and being able to submit**.\n",
    "\n",
    "Once your signup request is accepted, you can go to your sandbox and copy-paste (or upload) feature_extractor.py, regressor.py from submissions/starting_kit. Save it, rename it, then submit it. The submission is trained and tested on our backend in the same way as ramp_test_submission does it locally. While your submission is waiting in the queue and being trained, you can find it in the \"New submissions (pending training)\" table in my submissions. Once it is trained, you get a mail, and your submission shows up on the public leaderboard. If there is an error (despite having tested your submission locally with ramp_test_submission), it will show up in the \"Failed submissions\" table in my submissions. You can click on the error to see part of the trace.\n",
    "\n",
    "After submission, do not forget to give credits to the previous submissions you reused or integrated into your submission.\n",
    "\n",
    "The data set we use at the backend is usually different from what you find in the starting kit, so the score may be different.\n",
    "\n",
    "The usual way to work with RAMP is to explore solutions, add feature transformations, select models, perhaps do some AutoML/hyperopt, etc., locally, and checking them with ramp_test_submission. The script prints mean cross-validation scores.\n",
    "\n",
    "     ----------------------------\n",
    "     train  0.267 ± 0.0089\n",
    "\t valid  0.601 ± 0.0024\n",
    "\t test    0.45 ± 0.0047\n",
    "     \n",
    "The official score in this RAMP (the first score column after \"historical contributivity\" on the leaderboard) is relative root mean squared error (\"Relative RMSE\"), so the line that is relevant in the output of ramp_test_submission is valid Relative RMSE = 0.601 ± 0.0024. When the score is good enough, you can submit it at the RAMP."
   ]
  }
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