notebooks/Paper_plots.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Notebook to generate various plots for the paper\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import json\n",
    "import sys\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "sys.path.append(\"../src\")\n",
    "from process import *\n",
    "from fitting_util import *\n",
    "from plotting import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Viz19, 125 topics, 'astro-only' high-impact journals, 2nd run with SED removed\n",
    "version = '19_2_125_rec8' #rec1, rec3' # rec5, rec6, rec10\n",
    "\n",
    "# use filtered? means no Grav Wave topic\n",
    "use_filtered = True\n",
    "\n",
    "# RI CAGR offset\n",
    "cagr_offset = 0.05"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set filtering\n",
    "filtered = \"_filtered\" if use_filtered else \"\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>topic</th>\n",
       "      <th>raw_doc_tcs</th>\n",
       "      <th>doc_tcs</th>\n",
       "      <th>tcs</th>\n",
       "      <th>cagr</th>\n",
       "      <th>keywords</th>\n",
       "      <th>ri</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>17.675846</td>\n",
       "      <td>0.014942</td>\n",
       "      <td>609.900815</td>\n",
       "      <td>0.103800</td>\n",
       "      <td>black hole mass, central black hole, black hol...</td>\n",
       "      <td>93.802862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>6.550303</td>\n",
       "      <td>0.005537</td>\n",
       "      <td>370.527983</td>\n",
       "      <td>0.017668</td>\n",
       "      <td>surface brightness profile, density field, den...</td>\n",
       "      <td>25.072953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>10.614325</td>\n",
       "      <td>0.008972</td>\n",
       "      <td>852.054470</td>\n",
       "      <td>0.046986</td>\n",
       "      <td>dark matter halo, density profile, peculiar ve...</td>\n",
       "      <td>82.637339</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   topic  raw_doc_tcs   doc_tcs         tcs      cagr  \\\n",
       "0      0    17.675846  0.014942  609.900815  0.103800   \n",
       "1      2     6.550303  0.005537  370.527983  0.017668   \n",
       "2      3    10.614325  0.008972  852.054470  0.046986   \n",
       "\n",
       "                                            keywords         ri  \n",
       "0  black hole mass, central black hole, black hol...  93.802862  \n",
       "1  surface brightness profile, density field, den...  25.072953  \n",
       "2  dark matter halo, density profile, peculiar ve...  82.637339  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d_filename = f'../results/decadal_report_results_{version}{filtered}.csv'\n",
    "dcs_data = pd.read_csv(d_filename)\n",
    "dcs_data[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>topic</th>\n",
       "      <th>raw_doc_tcs</th>\n",
       "      <th>doc_tcs</th>\n",
       "      <th>tcs</th>\n",
       "      <th>cagr</th>\n",
       "      <th>keywords</th>\n",
       "      <th>ri</th>\n",
       "      <th>avg_cites</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17.675846</td>\n",
       "      <td>0.014942</td>\n",
       "      <td>609.900815</td>\n",
       "      <td>0.103800</td>\n",
       "      <td>black hole mass, central black hole, black hol...</td>\n",
       "      <td>93.802862</td>\n",
       "      <td>250.375532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>6.550303</td>\n",
       "      <td>0.005537</td>\n",
       "      <td>370.527983</td>\n",
       "      <td>0.017668</td>\n",
       "      <td>surface brightness profile, density field, den...</td>\n",
       "      <td>25.072953</td>\n",
       "      <td>165.021635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>10.614325</td>\n",
       "      <td>0.008972</td>\n",
       "      <td>852.054470</td>\n",
       "      <td>0.046986</td>\n",
       "      <td>dark matter halo, density profile, peculiar ve...</td>\n",
       "      <td>82.637339</td>\n",
       "      <td>183.341705</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  topic  raw_doc_tcs   doc_tcs         tcs      cagr  \\\n",
       "0           0      0    17.675846  0.014942  609.900815  0.103800   \n",
       "1           1      2     6.550303  0.005537  370.527983  0.017668   \n",
       "2           2      3    10.614325  0.008972  852.054470  0.046986   \n",
       "\n",
       "                                            keywords         ri   avg_cites  \n",
       "0  black hole mass, central black hole, black hol...  93.802862  250.375532  \n",
       "1  surface brightness profile, density field, den...  25.072953  165.021635  \n",
       "2  dark matter halo, density profile, peculiar ve...  82.637339  183.341705  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load the citation data \n",
    "#cite_filename = f\"../data/ri_vs_citation_{version}{filtered}.csv\"\n",
    "min_inference = 0.2\n",
    "contentType = 'decadal'\n",
    "cite_filename = f'../results/ri_vs_citation_{contentType}_{version}_{min_inference}.csv'\n",
    "cite_data = pd.read_csv(cite_filename)\n",
    "\n",
    "cite_data[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>topic</th>\n",
       "      <th>raw_doc_tcs</th>\n",
       "      <th>doc_tcs</th>\n",
       "      <th>tcs</th>\n",
       "      <th>cagr</th>\n",
       "      <th>keywords</th>\n",
       "      <th>ri</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3.394672</td>\n",
       "      <td>0.012389</td>\n",
       "      <td>609.900815</td>\n",
       "      <td>0.103800</td>\n",
       "      <td>black hole mass, central black hole, black hol...</td>\n",
       "      <td>93.802862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0.257885</td>\n",
       "      <td>0.000941</td>\n",
       "      <td>370.527983</td>\n",
       "      <td>0.017668</td>\n",
       "      <td>surface brightness profile, density field, den...</td>\n",
       "      <td>25.072953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2.594233</td>\n",
       "      <td>0.009468</td>\n",
       "      <td>852.054470</td>\n",
       "      <td>0.046986</td>\n",
       "      <td>dark matter halo, density profile, peculiar ve...</td>\n",
       "      <td>82.637339</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   topic  raw_doc_tcs   doc_tcs         tcs      cagr  \\\n",
       "0      0     3.394672  0.012389  609.900815  0.103800   \n",
       "1      2     0.257885  0.000941  370.527983  0.017668   \n",
       "2      3     2.594233  0.009468  852.054470  0.046986   \n",
       "\n",
       "                                            keywords         ri  \n",
       "0  black hole mass, central black hole, black hol...  93.802862  \n",
       "1  surface brightness profile, density field, den...  25.072953  \n",
       "2  dark matter halo, density profile, peculiar ve...  82.637339  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_filename = f'../results/whitepapers_results_{version}{filtered}.csv'\n",
    "whitepaper_data = pd.read_csv(w_filename)\n",
    "\n",
    "whitepaper_data[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_cagr</th>\n",
       "      <th>mean_ri</th>\n",
       "      <th>mean_doc_tcss</th>\n",
       "      <th>stderr_cagr</th>\n",
       "      <th>stderr_ri</th>\n",
       "      <th>stderr_doc_tcs</th>\n",
       "      <th>min_inference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.717052</td>\n",
       "      <td>0.466473</td>\n",
       "      <td>0.422832</td>\n",
       "      <td>0.009027</td>\n",
       "      <td>0.015821</td>\n",
       "      <td>0.025271</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.729840</td>\n",
       "      <td>0.479821</td>\n",
       "      <td>0.433271</td>\n",
       "      <td>0.008316</td>\n",
       "      <td>0.016416</td>\n",
       "      <td>0.025271</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.748643</td>\n",
       "      <td>0.517094</td>\n",
       "      <td>0.452238</td>\n",
       "      <td>0.007763</td>\n",
       "      <td>0.015062</td>\n",
       "      <td>0.025271</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_cagr   mean_ri  mean_doc_tcss  stderr_cagr  stderr_ri  stderr_doc_tcs  \\\n",
       "0   0.717052  0.466473       0.422832     0.009027   0.015821        0.025271   \n",
       "1   0.729840  0.479821       0.433271     0.008316   0.016416        0.025271   \n",
       "2   0.748643  0.517094       0.452238     0.007763   0.015062        0.025271   \n",
       "\n",
       "   min_inference  \n",
       "0           0.01  \n",
       "1           0.10  \n",
       "2           0.15  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vers = version.split('_rec')[0]\n",
    "mt_filename = f'../results/mlcr_min_inferences_{contentType}_{vers}{filtered}.csv'\n",
    "mt_data = pd.read_csv(mt_filename)\n",
    "\n",
    "mt_data[:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def research_plot_decadal_tcs_vs_ri (version:str, dcs_data:pd.DataFrame, label_fontsize:int=14):\n",
    "    \n",
    "    ''' Figure for paper/poster '''\n",
    "    fig, ax1 = plt.subplots(1, 1)\n",
    "    \n",
    "    # plot LHS\n",
    "    x=np.array(dcs_data['raw_doc_tcs'])\n",
    "    y=np.array(dcs_data['ri'])\n",
    "    plot_data (x, y, ax=ax1)\n",
    "    #ax1.set_title(\"RI (1998-2010 Literature) vs DCS (2010 Survey)\", fontsize=label_fontsize)\n",
    "    ax1.set_title(\"\", fontsize=label_fontsize)\n",
    "    ax1.set_xlabel(\"$TCS_{DS2010}$\", fontsize=label_fontsize)\n",
    "    ax1.set_ylabel(\"$RI_{1998-2010}$\", fontsize=label_fontsize)\n",
    "    #ax1.set_ylim([0, 200])\n",
    "    \n",
    "    # write to disk for distribution\n",
    "    fig = plt.gcf()\n",
    "    fig.set_size_inches(8.0, 6.0)\n",
    "    fig.subplots_adjust(left=0.15)\n",
    "    \n",
    "    plt.savefig(f'../plots/ri_vs_dcs2010_diagram_{version}.jpg', transparent=False, dpi=600)\n",
    "    \n",
    "\n",
    "def research_plot_cagr_mlcr (version:str, data:pd.DataFrame, label_fontsize:int=14):\n",
    "    \n",
    "    ''' Figurefor paper/poster '''\n",
    "    \n",
    "    # 2 plots horizontally side-by-side\n",
    "    fig, ax2 = plt.subplots(1, 1)\n",
    "\n",
    "    # plot RHS\n",
    "    x=np.array(data['avg_cites'])\n",
    "    y=np.array(data['cagr'])\n",
    "    plot_data (x, y, ax=ax2)\n",
    "    #ax2.set_title(\"CAGR (1998 - 2010) vs MLCR, min inf 0.2\", fontsize=label_fontsize)\n",
    "    ax2.set_title(\"\", fontsize=label_fontsize)\n",
    "    ax2.set_xlabel(\"MLCR\", fontsize=label_fontsize)\n",
    "    ax2.set_ylabel(\"TCS_CAGR$_{1998-2010}$\", fontsize=label_fontsize)\n",
    "    #ax2.set_ylim([-0.025, 0.12])\n",
    "    \n",
    "    # write to disk for distribution\n",
    "    fig = plt.gcf()\n",
    "    fig.set_size_inches(8.0, 6.0)\n",
    "    fig.subplots_adjust(left=0.155)\n",
    "    \n",
    "    plt.savefig(f'../plots/cagr_vs_mlcr_diagram_{version}.jpg', transparent=False, dpi=600)\n",
    "    \n",
    "    \n",
    "def research_plot_doc_tcs_mlcr (version:str, data:pd.DataFrame, label_fontsize:int=14):\n",
    "    \n",
    "    ''' Figurefor paper/poster '''\n",
    "    \n",
    "    # 2 plots horizontally side-by-side\n",
    "    fig, ax2 = plt.subplots(1, 1)\n",
    "\n",
    "    # plot RHS\n",
    "    x=np.array(data['avg_cites'])\n",
    "    y=np.array(data['doc_tcs'])\n",
    "    plot_data (x, y, ax=ax2)\n",
    "    #ax2.set_title(\"CAGR (1998 - 2010) vs MLCR, min inf 0.2\", fontsize=label_fontsize)\n",
    "    ax2.set_title(\"\", fontsize=label_fontsize)\n",
    "    ax2.set_xlabel(\"MLCR\", fontsize=label_fontsize)\n",
    "    ax2.set_ylabel(\"TCS$_{DS2010}$\", fontsize=label_fontsize)\n",
    "    #ax2.set_ylim([-0.025, 0.12])\n",
    "    \n",
    "    # write to disk for distribution\n",
    "    fig = plt.gcf()\n",
    "    fig.set_size_inches(8.0, 6.0)\n",
    "    fig.subplots_adjust(left=0.155)\n",
    "    \n",
    "    plt.savefig(f'../plots/ds2010_tcs_vs_mlcr_diagram_{version}.jpg', transparent=False, dpi=600)\n",
    "    \n",
    "\n",
    "def research_plot_tcs_mlcr (version:str, data:pd.DataFrame, label_fontsize:int=14):\n",
    "    \n",
    "    ''' Figurefor paper/poster '''\n",
    "    \n",
    "    # 2 plots horizontally side-by-side\n",
    "    fig, ax2 = plt.subplots(1, 1)\n",
    "\n",
    "    # plot RHS\n",
    "    x=np.array(data['avg_cites'])\n",
    "    y=np.array(data['tcs'])\n",
    "    plot_data (x, y, ax=ax2)\n",
    "    #ax2.set_title(\"CAGR (1998 - 2010) vs MLCR, min inf 0.2\", fontsize=label_fontsize)\n",
    "    ax2.set_title(\"\", fontsize=label_fontsize)\n",
    "    ax2.set_xlabel(\"MLCR\", fontsize=label_fontsize)\n",
    "    ax2.set_ylabel(\"TCS$_{1998-2010}$\", fontsize=label_fontsize)\n",
    "    #ax2.set_ylim([-0.025, 0.12])\n",
    "    \n",
    "    # write to disk for distribution\n",
    "    fig = plt.gcf()\n",
    "    fig.set_size_inches(8.0, 6.0)\n",
    "    fig.subplots_adjust(left=0.155)\n",
    "    \n",
    "    plt.savefig(f'../plots/tcs_vs_mlcr_diagram_{version}.jpg', transparent=False, dpi=600)\n",
    "    \n",
    "    \n",
    "def research_plot_ri_tcs_whitepaper (version:str, data:pd.DataFrame, label_fontsize:int=14):\n",
    "    \n",
    "    ''' Figure for paper/poster '''\n",
    "    fig, ax1 = plt.subplots(1, 1)\n",
    "    \n",
    "    # plot LHS\n",
    "    x=np.array(data['raw_doc_tcs'])\n",
    "    y=np.array(data['ri'])\n",
    "    plot_data (x, y, ax=ax1)\n",
    "    #ax1.set_title(\"RI (1998-2010 Literature) vs TCS (2010 Whitepapers)\", fontsize=label_fontsize)\n",
    "    ax1.set_title(\"\", fontsize=label_fontsize)\n",
    "    ax1.set_xlabel(\"$TCS_{whitepaper}$\", fontsize=label_fontsize)\n",
    "    ax1.set_ylabel(\"$RI_{1998-2010}$\", fontsize=label_fontsize)\n",
    "    #ax1.set_ylim([0, 300])\n",
    "    \n",
    "    # write to disk for distribution\n",
    "    fig = plt.gcf()\n",
    "    fig.set_size_inches(8.0, 6.0)\n",
    "    fig.subplots_adjust(left=0.15)\n",
    "    \n",
    "    plt.savefig(f'../plots/ri_vs_whitepaper_diagram_{version}.jpg', transparent=False, dpi=600)\n",
    "    \n",
    "def research_plot_paper_inference_thresh (version:str, data:pd.DataFrame, label_fontsize:int=14):\n",
    "\n",
    "    fig, ax1 = plt.subplots(1, 1)\n",
    "\n",
    "    y=np.array(data['mean_cagr'])\n",
    "    x=np.array(data['min_inference'])\n",
    "    y_err=np.array(data['stderr_cagr'])\n",
    "    plot_data (x, y, ax=ax1)\n",
    "\n",
    "    ax1.plot(x, y, marker='o', markerfacecolor='red', linestyle=' ')\n",
    "    plt.errorbar(x, y, fmt='ko', yerr=y_err)\n",
    "\n",
    "    ax1.set_ylabel(\"Mean R (TCS_CAGR$_{1998-2010}$ vs MLCR)\", fontsize=label_fontsize)\n",
    "    ax1.set_xlabel(\"I$_{paper}$ minimum threshold\", fontsize=label_fontsize)\n",
    "    ax1.set_title(\"\", fontsize=label_fontsize)\n",
    "    \n",
    "    # write to disk for distribution\n",
    "    fig = plt.gcf()\n",
    "    fig.set_size_inches(8.0, 6.0)\n",
    "    fig.subplots_adjust(left=0.15)\n",
    "    \n",
    "    plt.savefig(f'../plots/mlcr_vs_stable_thresh_diagram_{version}.jpg', transparent=False, dpi=600)\n",
    "    \n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.lines as mlines\n",
    "\n",
    "\n",
    "def makeline(p1, p2, color:str=None, dashed:bool=False):\n",
    "    ax = plt.gca()\n",
    "    l = mlines.Line2D([p1[0],p2[0]], [p1[1],p2[1]])\n",
    "    if color:\n",
    "        l.set_color(color)\n",
    "    if dashed:\n",
    "        l.set_dashes([2, 2,]) \n",
    "    ax.add_line(l)\n",
    "    return l\n",
    "\n",
    "def tcs_ri (ri:float, cagr:float, offset:float=cagr_offset)->float:\n",
    "    return float(ri / (cagr + offset))\n",
    "\n",
    "def cagr_ri (ri:float, tcs:float, offset:float=cagr_offset)->float:\n",
    "    return float(( ri / tcs ) - offset)\n",
    "\n",
    "def points_by_ri (ri:float, cagr_min:float=0.0, cagr_max:float=0.15, offset:float=cagr_offset)->list:\n",
    "    p1_x = tcs_ri(ri, cagr_min, offset=offset)\n",
    "    p1_y = cagr_ri(ri, p1_x, offset=offset)\n",
    "    \n",
    "    p2_x = tcs_ri(ri, cagr_max, offset=offset)\n",
    "    p2_y = cagr_ri(ri, p2_x, offset=offset)\n",
    "    \n",
    "    return ((p1_x, p1_y), (p2_x,p2_y))\n",
    "\n",
    "def research_plot_tcs_cagr (version:str, data:pd.DataFrame, label_fontsize:int=14):\n",
    "\n",
    "    fig, ax1 = plt.subplots(1, 1)\n",
    "\n",
    "    y=np.array(data['cagr'])\n",
    "    x=np.array(data['tcs'])\n",
    "    #y_err=np.array(data['stderr_cagr'])\n",
    "    plot_data (x, y, ax=ax1)\n",
    "\n",
    "    ax1.plot(x, y, marker='o', markerfacecolor='red', linestyle=' ')\n",
    "\n",
    "    ax1.set_ylabel(\"TCS_CAGR$_{1998-2010}$\", fontsize=label_fontsize)\n",
    "    ax1.set_xlabel(\"TCS$_{1998-2010}$\", fontsize=label_fontsize)\n",
    "    ax1.set_title(\"\", fontsize=label_fontsize)\n",
    "    \n",
    "    ax1.set_ylim([-0.03, 0.16])\n",
    "    \n",
    "    # write 'iso-ri' lines in plot\n",
    "    cagr_step = 0.005\n",
    "    for ri in [20, 50, 100]:\n",
    "        for cagr_min in [i * cagr_step for i in range(-8, 32)]:\n",
    "            cagr_max = cagr_min + cagr_step\n",
    "            (p1, p2) = points_by_ri (ri, cagr_min=cagr_min, cagr_max=cagr_max, offset=cagr_offset)\n",
    "            #print (p1,p2)\n",
    "            makeline(p1, p2)\n",
    "    \n",
    "    ax1.text(1280, 0.0225, r'RI = 100', fontsize=12, rotation=-15)\n",
    "    ax1.text(1280, -0.0125, r'RI = 50', fontsize=12, rotation=-10)\n",
    "    ax1.text(875, -0.028, r'RI = 20', fontsize=12, rotation=-10)\n",
    "    \n",
    "    #makeline((500.,0.15), (1000.,-0.025), color='orange', dashed=True)\n",
    "        \n",
    "    makeline((275.,0.15), (275.,0.075), color='green', dashed=True)\n",
    "    makeline((275,0.075), (775,0.075), color='green', dashed=True)\n",
    "    makeline((775,0.075), (775,0.15), color='green', dashed=True)\n",
    "    makeline((275,0.15), (775,0.15), color='green', dashed=True)\n",
    "                    \n",
    "    # write to disk for distribution\n",
    "    fig = plt.gcf()\n",
    "    fig.set_size_inches(8.0, 6.0)\n",
    "    fig.subplots_adjust(left=0.15)\n",
    "    \n",
    "    plt.savefig(f'../plots/tcs_vs_cagr_diagram_{version}.jpg', transparent=False, dpi=600)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>topic</th>\n",
       "      <th>raw_doc_tcs</th>\n",
       "      <th>doc_tcs</th>\n",
       "      <th>tcs</th>\n",
       "      <th>cagr</th>\n",
       "      <th>keywords</th>\n",
       "      <th>ri</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>31.466498</td>\n",
       "      <td>0.026599</td>\n",
       "      <td>952.827311</td>\n",
       "      <td>0.159414</td>\n",
       "      <td>giant planet, extrasolar planet, planetary sys...</td>\n",
       "      <td>199.535135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>41</td>\n",
       "      <td>19.241782</td>\n",
       "      <td>0.016265</td>\n",
       "      <td>942.232127</td>\n",
       "      <td>0.138898</td>\n",
       "      <td>stellar mass, massive galaxy, stellar masse, &lt;...</td>\n",
       "      <td>177.985593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>91</td>\n",
       "      <td>9.598240</td>\n",
       "      <td>0.008113</td>\n",
       "      <td>1150.848472</td>\n",
       "      <td>0.042754</td>\n",
       "      <td>high energy, low energy, energy spectrum, sola...</td>\n",
       "      <td>106.745256</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    topic  raw_doc_tcs   doc_tcs          tcs      cagr  \\\n",
       "31     32    31.466498  0.026599   952.827311  0.159414   \n",
       "40     41    19.241782  0.016265   942.232127  0.138898   \n",
       "90     91     9.598240  0.008113  1150.848472  0.042754   \n",
       "\n",
       "                                             keywords          ri  \n",
       "31  giant planet, extrasolar planet, planetary sys...  199.535135  \n",
       "40  stellar mass, massive galaxy, stellar masse, <...  177.985593  \n",
       "90  high energy, low energy, energy spectrum, sola...  106.745256  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dcs_data.sort_values('ri', ascending=False)[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>topic</th>\n",
       "      <th>raw_doc_tcs</th>\n",
       "      <th>doc_tcs</th>\n",
       "      <th>tcs</th>\n",
       "      <th>cagr</th>\n",
       "      <th>keywords</th>\n",
       "      <th>ri</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>31.466498</td>\n",
       "      <td>0.026599</td>\n",
       "      <td>952.827311</td>\n",
       "      <td>0.159414</td>\n",
       "      <td>giant planet, extrasolar planet, planetary sys...</td>\n",
       "      <td>199.535135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>41</td>\n",
       "      <td>19.241782</td>\n",
       "      <td>0.016265</td>\n",
       "      <td>942.232127</td>\n",
       "      <td>0.138898</td>\n",
       "      <td>stellar mass, massive galaxy, stellar masse, &lt;...</td>\n",
       "      <td>177.985593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>91</td>\n",
       "      <td>9.598240</td>\n",
       "      <td>0.008113</td>\n",
       "      <td>1150.848472</td>\n",
       "      <td>0.042754</td>\n",
       "      <td>high energy, low energy, energy spectrum, sola...</td>\n",
       "      <td>106.745256</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    topic  raw_doc_tcs   doc_tcs          tcs      cagr  \\\n",
       "31     32    31.466498  0.026599   952.827311  0.159414   \n",
       "40     41    19.241782  0.016265   942.232127  0.138898   \n",
       "90     91     9.598240  0.008113  1150.848472  0.042754   \n",
       "\n",
       "                                             keywords          ri  \n",
       "31  giant planet, extrasolar planet, planetary sys...  199.535135  \n",
       "40  stellar mass, massive galaxy, stellar masse, <...  177.985593  \n",
       "90  high energy, low energy, energy spectrum, sola...  106.745256  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dcs_data.sort_values('ri', ascending=False)[:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Make Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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j7OxsJCcnw9raGtbW1li6dCkCAwPh4OCAy5cv44MPPoCNjQ1eeOEFAICVlRVmzJiBBQsWoHPnzrC2tsY777wDT09PZXUAIiIiIhI30YbVU6dOYfjw4crHinmk06dPR0REBFJTU/Htt9/izp07cHBwwPDhw7Fr1y5YWFgon7N27VoYGxsjODgY9+/fR0BAALZu3QqpVNrq74eIiIiINCcRBEHQdSfErLi4GFZWVigqKuL8VSIiIiIt0CRfGcycVSIiIiIyPAyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaWgurlZWV+OGHH/DOO+9g2rRpmDZtGt555x3s3bsXFRUVGl/vt99+w7hx4+Do6AiJRIL9+/ervNZ7770HT09PtG/fHo6OjnjllVeQl5enco1hw4ZBIpGo/EyePPlR3yoRERERtRKthNWMjAy4u7vjlVdeQVJSEioqKlBRUYGkpCRMmzYNffr0QUZGhkbXvHv3Lvr164d169bVO3fv3j2cPn0aYWFhOH36NCIjI3Hx4kWMHz++XtuZM2ciPz9f+fP1118/9PskIiIiotZlrI2LvPnmmxgwYADOnj2LDh06qJwrLS3Fa6+9htDQUMTExDT7mmPHjsXYsWPVnrOyskJ0dLTKsS+//BK+vr64cuUKunXrpjzerl072Nvba/BuiIiIiEgstDKyGhcXhw8//LBeUAWADh06YMmSJTh58qQ2XqpBRUVFkEgk6Nixo8rx7777DjY2Nujbty/eeecdlJSUNHqd8vJyFBcXq/wQERERkW5oZWTVxsYGqamp6NOnj9rz586dQ+fOnbXxUmqVlZXh/fffx9SpU2Fpaak8/tJLL8HV1RX29vZIS0vDwoULcfbs2XqjsrWFh4dj2bJlLdZXIiIiImo+rYTVt99+G6+99hqSkpIwfPhw2NraAgAKCwsRGxuLDRs2YOXKldp4qXoqKysxefJkVFdXY8OGDSrnZs6cqfxvDw8P9OzZEwMHDsTp06fh5eWl9noLFy7E/PnzlY+Li4vh7OzcIn0nIiIiosZpLaza2dnh888/x9q1ayGXywEAUqkUAwYMwMaNGzF16lRtvJSKyspKBAcHIzs7G0eOHFEZVVXHy8sLJiYmyMjIaDCsmpqawtTUVOt9JSIiIiLNaSWsAsDUqVMxdepUVFZW4saNGwBqpgeYmJho6yVUKIJqRkYGYmNjmzXN4Ny5c6isrISDg0OL9ImIiIiItEtrYVXBxMREK2GwtLQUmZmZysfZ2dlITk6GtbU1HB0dERQUhNOnT+Pnn3+GXC5HQUEBAMDa2hoymQxZWVn47rvv8Oyzz8LGxgbnz5/HggULMGDAAAwZMuSR+0dERERELU8iCILQ0i9y+/Zt/PTTT3jllVea/ZyjR49i+PDh9Y5Pnz4dS5cuhaurq9rnxcbGYtiwYcjNzcXLL7+MtLQ0lJaWwtnZGc899xyWLFkCa2vrZvejuLgYVlZWKCoqanKaARERERE1TZN81Sph9ezZs/Dy8lLOZdUnDKtERERE2qVJvtLKNIArV640er7uNqhERERERM2hlbDavXt3SCSSBs8LgtDoeSIiIiIidbQSVjt16oRVq1Zh2LBhas9fuHABgYGB2ngpIiIiImpDtBJWvb29cf36dfTu3Vvt+bKyMrTC1FgiIiIiMjBaCauhoaG4e/dug+e7deuGLVu2aOOliIiIiKgNaZVqAPqM1QCIiIiItKvVqwEANTtKRUVFIT4+HteuXQMA2NnZwc/PD+PGjYNMJtPWSxERERFRG2GkjYtkZGTA3d0dr7zyCpKSklBRUYGKigokJSVh2rRp6NOnDzIyMrTxUkRERETUhmhlZPXNN9/EgAEDcPbsWXTo0EHlXGlpKV577TWEhoYiJiZGGy9HRERERG2EVsJqXFwcTp06VS+oAkCHDh2wZMkS+Pr6auOliIiIiKgN0co0ABsbG6SmpjZ4/ty5c+jcubM2XoqIiIiI2hCtjKy+/fbbeO2115CUlIThw4fD1tYWAFBYWIjY2Fhs2LABK1eu1MZLEREREVEborWwamdnh88//xxr166FXC4HAEilUgwYMAAbN27E1KlTtfFSRERERNSGaL3OamVlJW7cuAGgZnqAiYmJNi/f6lhnlYiIiEi7dFJnVcHExAQODg7aviwRERERtUFaWWAFANXV1UhLS0NeXl69c5WVlfjtt9+09VJERERE1EZoJazm5OTA09MTTzzxBJydnTF+/HjcvHlTef7WrVsYPny4Nl6KiIiIiNoQrYTVd999F05OTrhy5QrOnj2L8vJyDBkyRGWUVctTY4mIiIioDdBKWD127BhWr14NJycneHh44NChQ3jqqafw1FNP4cqVKwAAiUSijZciIiIiojZEK2H13r17MDU1VT6WSCTYtGkTRo0ahaeffhpZWVnaeBkiIiIiamO0ElZ79+6NU6dO1TseERGBZ599Fs8//7w2XoaIiIiI2hithNVJkyZh586das9t2LABISEhnLNKRERERBrT+qYAhoabAhARERFplyb5Smt1VomIiIiItI1hlYiIiIhEi2GViIiIiESLYZWIiIiIRKvFwqpUKlVuCEBERERE9DCMW+rCLDJARESGSl4tICH7FgpLymBrYQZfV2tIjbhTI1FLaLGwSkREZIgOpeVjRVQqrpZUKo85WZhg8QRPjPFw0GHPiAwTwyoREVEzHUrLR+iOJARkJuKLuF3ofT0H6V1csME/BKElFYh42ZuBlUjLuMCKiIioGeTVAlZEpSIgMxEb9y6HV1462leWwSsvHRt/WI6ArESsjEqFvJrT4Ii0iWGVqBXJqwXEZd1EVPJfiMu6yb/UiPRIQvYtXC2pxOy4XTCC6v93jSAg9ORu5JZUIiH7lo56SGSYOA2AqJVwnhuRfissKQMA9L6eo/Z87xs5Ku2ISDsYVolaAee5Eek/WwszAEB6Fxd45aXXO59u46LSjoi0o8WmASxatAgdO3ZsqcsT6Q3OcyMyDL6u1nCyMMEG/xBUQ7VMVTUkiPAPhrOFCXxdrXXUQyLD1GJhdfny5bC0tGypyxPpDc5zIzIMUiMJFk/wxGE3H8wKCkOSoztKZeZIcnTHrKAwHHbzwaIJnqy3SqRlnAZA1MI4z43IcIzxcEDEy95YESVDoJuv8rizhQkiOP+cqEUwrBK1MM5zIzIsYzwcMLKPPXewImolLF1F1MI4z43I8EiNJPBz64wJ/bvCz60zgypRC9JaWE1LS8O3336LnJyaW5p//vkn/vnPf2Lu3LmIjo7W1ssQ6R3OcyMiInp4WpkGsHfvXkyePBlWVlaoqKhAZGQkgoODMXDgQEilUjz77LPYtm0bpk6dqo2XI9I7nOdGRET0cCSCIDxyvRwvLy8EBwfj/fffx549ezBz5ky8++67+OCDDwAAn3/+ObZu3Yrk5ORHfalWV1xcDCsrKxQVFbG6AT0yebXAeW5ERNTmaZKvtBJWO3TogLS0NHTv3h0AIJPJkJSUBE9PTwBAdnY2PD09UVpa+qgv1eoYVomIiIi0S5N8pZU5q1ZWVsjPzwcAXLt2DVVVVSgoKFCez8/Ph5WVlUbX/O233zBu3Dg4OjpCIpFg//79KucFQcDSpUvh6OgIc3NzDBs2DOfOnVNpU15ejrfeegs2NjZo3749xo8fj6tXrz7cmyQiIiKiVqeVsDpu3DjMmDEDq1evxqRJkzBlyhQsWLAAhw8fRmxsLP75z3/imWee0eiad+/eRb9+/bBu3Tq151evXo01a9Zg3bp1SExMhL29PUaOHImSkhJlm3nz5mHfvn34/vvv8fvvv6O0tBTPP/885HL5I71fIiIiImodWpkGUFpainnz5uGPP/6Av78/vvjiC3z++ef497//jcrKSjz11FPYtWsX7O3tH66TEgn27duHiRMnAqgZVXV0dMS8efPw3nvvAagZRbWzs8PHH3+Mf/zjHygqKkKXLl2wfft2hISEAADy8vLg7OyMgwcPYvTo0Wpfq7y8HOXl5crHxcXFcHZ25jQAIiIiIi1p9WkAHTp0wDfffIPU1FR8/fXXMDU1xXvvvYeioiIUFRXh2LFjDx1U1cnOzkZBQQFGjRqlPGZqaoqhQ4fi5MmTAICkpCRUVlaqtHF0dISHh4eyjTrh4eGwsrJS/jg7O2ut30RiIq8WEJd1E1HJfyEu6ybk1Y/871YiIiKta9EdrMzMzGBmpv1deRTzYe3s7FSO29nZKeu8FhQUQCaToVOnTvXa1J5PW9fChQsxf/585WPFyCqRITmUlo8VUam4WlKpPOZkYYLFLKNFREQio7Wweu/ePfz3v//FiRMnkJ+fDyMjI7i6umLChAkYOXKktl5GhUSiWvJHEIR6x+pqqo2pqSlMTU210j8iMTqUlo/QHUkIyEzEF3G70Pt6DtK7uGCDfwhCSyoQ8bI3AysREYmGVqYBpKenw93dHYsWLUJMTAx++eUXSCQSJCUl4dlnn8WkSZNQUVGhjZcCAOWUgrojpIWFhcrRVnt7e1RUVOD27dsNtiFqa+TVAlZEpSIgMxEb9y6HV1462leWwSsvHRt/WI6ArESsjErllAAiIhINrYTVuXPnYvz48cjPz8eVK1ewevVqVFVVIS4uDunp6UhJScGyZcu08VIAAFdXV9jb26ts41pRUYFjx47B398fAODt7Q0TExOVNvn5+UhLS1O2IWprErJv4WpJJWbH7YIRVAOpEQSEntyN3JJKJGTf0lEPiYiIVGklrJ48eRLz5s1T3l6fN28ejhw5ghs3buCxxx7D559/ju3bt2t0zdLSUiQnJyt3vcrOzkZycjKuXLkCiUSCefPmYdWqVdi3bx/S0tLw6quvol27dsotXa2srDBjxgxlCa0zZ87g5Zdfhqenp8ZltIgMRWFJGQCg9/Ucted738hRaUdERKRrWpmz2rlzZ9y8eRM9evQAANy+fRtVVVUwNzcHAPTt2xeFhYUaXfPUqVMYPny48rFi0dP06dOxdetWvPvuu7h//z5mz56N27dvY9CgQfj1119hYWGhfM7atWthbGyM4OBg3L9/HwEBAdi6dSukUumjvmUivWRrUbPgMb2LC7zy0uudT7dxUWlHRESka1qpszp37lycPHkSq1evhpmZGT788EPcv38fx48fBwBER0fjH//4By5duvTIHW5t3G6VDIm8WsDQ8Gi4J5/Axh+Wq0wFqIYEs4LCkN5/CI4uHAmpUeOLFYmIiB5Wq9dZDQ8PR48ePTB27Fg8/fTTKCkpwdatW5Xnq6ursWrVKm28FBE9AqmRBIsneOKwmw9mBYUhydEdpTJzJDm6Y1ZQGA67+WDRBE8GVSIiEg2tjKwqlJWVoaqqCh06dNDWJXWOI6tth7xaQEL2LRSWlMHWwgy+rtYGG9rU1Vl1tjDBItZZJSKiVqBJvtLqpgAtsQEAUWtoa0Xyx3g4YGQf+zYTzomISH/p9aYARNrQVovkS40k8HPrrOtuEBERNUor0wDS09MxcuRIVFRUQCaT4erVq3j22Wdx8+ZNnDp1CuPGjcP3338PmUymjT63Kk4DEB9t3q5XLjg6cwIb93LBEVFb0Jam/BCJVatPA1BsCvDll19CIpHg008/RUxMDOLi4nDp0iWMGjUKy5Ytw8qVK7XxctSGaft2vaJI/heNFMkPdPNFQvYtjkISGYC2NuWHyBCIdlMAoroUt+vdz5xA5PYFOLcmCJHbF8A9+QRCdyThUFq+xtdkkXyitqMlfocQUcvTSlhVbAqgoI1NAYhqa6k97WsXyVeHRfKJDENL/Q4hopanlbA6fvx4hIaGIiYmBr///jteeuklDBkyBO3btwcAZGZmwtHRURsvRW1US+1p7+tqDScLE2zwD0E1VOesVUOCCP9gOFuYwNfV+pHfAxHpTkv9DiGilsdNAUgvtNTtehbJJ2obOOWHSH9pZYGVhYUFdu/e3eCmAKNHj9bGy1Ab1pJ72o/xcEDEy95YESVDoJuv8rizhQkiuOiCyCC05O8QImpZrbIpwO3bt/HTTz/hlVde0ebLURtS+3a9uj3tH/V2PYvk6wZLCFFraenfIUTUcrS63WpDzp49Cy8vL8jl8pZ+Ka1jnVXxUBbvz0pE6Mnd6H0jB+k2LojwD8ZhNx+DLd5vqFhCiFobf4cQiUer11m9cuVKo+fz8vK08TLUxvF2veFoq7uGkW7xdwiRftLKyKqRkZGyxqo6giBAIpFwZJW0greO9Rt3DSNd4+8QIt1r9ZHVTp06YdWqVRg2bJja8xcuXEBgYKA2XoqIe9rrOe4aRrrG3yFE+kUrYdXb2xvXr19H79691Z4vKytDK0yNJWrT9GW0iCWEiIhIE1oJq6Ghobh7926D57t164YtW7Zo46WISA19WqzEEkJERKQJrYTVF154odHznTp1wvTp07XxUkRq6cuoYkvQt8VKLCFERESaaPYCq6tXr8LJyaml+yM6XGAlfvo0qqht+rpYiSWEiIjathZZYNWtWzfY2tpiwIAB8Pb2hpeXF7y9veHi4vLIHSZ6WIrQMyIzEbMunYJZZTnKTExxzG2gKEcVtU1fFyuxhBARETVXs8Oqh4cH/vzzT/zyyy/45ZdflKWqOnXqpAyuiv997LHHWqzDRAryagErolLhmZ+JdJtuONzjQehxulMAz4JMrIySYWQfe1GNKmqTPi9W4q5hRETUHM0OqykpKSgvL8fZs2dx+vRpJCUl4fTp00hLS0NMTAxiYmKUAdbS0lIZXFevXt1inae2TTGq+Je9W818zZ8+eTBfc3AwDvfwgVBSKbpRRW3S98VKLCFERERNeeRNASorK5GSkqISYFNTU1FeXq63GwHUxjmr4rXv9FW8898kDLuUhE2RK+rN15w5aTGOPuaNT6d44wUvcc+3ftgFYso5q8kn1C5WEuucVSIiattadVMAExMTeHt7w9vbGzNnzgQAVFVV4dy5c0hKSnrUyxM16NbdCsilxpgTv1vtfM3Z8XtwuOcg3LpboaMeNs+jLBCTGkmweIInQksqMCsoTP1ipQmeDKpERKS3tFK6qt5FjY3Rr18/9OvXryUuTwQAsO5gCqDp+ZqKdrWJpdSVNspOcbESEREZMo3C6oULF/Cf//wH169fh7u7O9544w3Y2NiobZuXl4eoqCiEhoZqpaNEdQOmrUVNCG1qvqa9pep8TbGUulIsEAvITFQpO+WVl46NPyzHrKCwZi8Q42IlIiIyVBotsPL398f9+/eVW6euXr0aMTEx8PLyAgBcunQJe/bswb59+3Dq1CkIgsCwSlqhLmB27WAMGzMjrPcPwSY18zU3qCkuL6YC+touO8XFSkREZIiaHVY//PBD3Lt3Dy+88AJGjRqFrKwsREREICQkBEePHsUbb7yBX3/9FQAgCALs7e3x/PPPt1jHqe1oLGDGuPngiJsPZgaFYXat+Zob/INxpM58TW2OZGqDPpedIiIiai3NDqsJCQl48sknsXfvXuWxKVOmYNCgQRg6dCguXboEJycnTJs2DePHj8egQYNapMPUtjQnYJ7p64f0fkOanK8ptgL6+l52ioiIqDU0O6zm5eXh5ZdfVjk2YMAAjBs3Dvv27cOMGTPw1VdfQSqVar2T1HY1N2B+N2MgjIwkjc7XFNtIpq+rNZwsTLDBP0Rt2akINdMYiIiI2ppmh9Xq6mqYmdUf4XF3d4dEIsGHH37IoEpa19yAeeNuOSb079rotcQ2ksmyU0RERE175NJVMpkMAODgwPI41DhNykUp2mZcKwUAnLftDp+//qzXTpOAqRjJbGhB1nq/FyGVV+H23fKHeXsPhWWniIiIGqdRWP3yyy+RkJAALy8veHl5YcCAAS3VLzIwmpSLUtf21eAP8cmBz/HsxZPKY5reKpcaSfDBOE/MLq7AG4GLMSduz4ORzMEvItbNB57XshD+kzlGezi02ogmy04RERE1rNlh1cPDA3/++ScOHjyIgwcPQiKp+YvUyMgIABAWFoYBAwbAy8sL3bt3b5HOkn7SpFxUQ23X+YVg9sSF+L9j2zD9zIGHvlXeqb0MkEiQ7OiOwGmfKo873ylAxP5wdCm9jUD7T1ttkZUCy04RERGpJxEURVOboby8HGfPnsXp06eRlJSE06dPIy0tDZWVNSNgigDbsWNHDBgwAN7e3vj4449bpuetRJO9a6k+5d71Z06orOYH6u9dD6DRtm8EhuGYqxfk0pp/YzlbmGCRhrfKP/zpHLb9lqm8BgDYlN7Ch9Ff4dmLJ1EqM4fH23vw/yb3b3IOLBERET0cTfKVRtMATE1N4evrC1/fB3PrKisrkZKSohJgU1NTceTIEcTGxup9WKVHo0m5KACNtp0TtxtHevhi7nA3DOnRReNb5YfS8rHlRDaGZydhbtzuByO8g4MxZ+L7ypFVgOWiiIiIxOKRF1iZmJjA29sb3t7emDlzJgCgqqoK586dQ1JS0iN3kPTbw5SLaqptTzsLjW+ZK+q1jshMxKa9K1TrtUauwKxJi7Fy+Az0unmF5aIIgGYLAomIqOU8clhVe1FjY/Tr1w/9+vVricuTHnmYclEtUVqqyRHe+D0InPYpcjva4SuWi2rzNFkQSERELctI1x0gw1a78H01VANg3dX8mrTVVHNHeGcMcWUYaeMUi/zcz5xA5PYFOLcmCJHbF8A9+QRCdyThUFq+rrtIRNSmMKxSi1IUvj/s5oNZQWFIcnRHqcwcSY7umBUUhsNuPlj090imJm01VXuEVx3FqO0zfewf/s2S3qu7va9XXjraV5Ypt/cNyErEyqhUyKubvS6ViIgeUYtMAyCqTZPC9y1VJJ9bm1JzaLIgkKXGiIhaB8MqtQpNCt+3RJF8bm1KzfEwCwKJiKhlMazSI9FkxbQmhe9rt9XWqmxubUpNeZgFgURE1LL0Oqx2794dOTn1R0Bmz56N9evX49VXX8W2bdtUzg0aNAjx8fGt1UWD1horprX9GtzalBrD6SJEROKj12E1MTERcrlc+TgtLQ0jR47Eiy++qDw2ZswYbNmyRflYJpO1ah8NlSZbqIrtNbi1KTWE00WIiMRHo+1WxW7evHn4+eefkZGRAYlEgldffRV37tzB/v37m32N8vJylJeXKx8XFxfD2dmZ263WoskWqg/7l3prvAZRQ9SN6D/M9r5ERKRei223KmYVFRXYsWMH5s+fD4nkQXg5evQobG1t0bFjRwwdOhQrV66Era1tg9cJDw/HsmXLWqPLeqs1VkxzVTbpEqeLEBGJh8GE1f379+POnTt49dVXlcfGjh2LF198ES4uLsjOzkZYWBhGjBiBpKQkmJqaqr3OwoULMX/+fOVjxcgqPdAaK6a5Kpt0jdNFiIjEwWDC6ubNmzF27Fg4Ojoqj4WEhCj/28PDAwMHDoSLiwsOHDiASZMmqb2Oqalpg0GWarTGimlDWZXN/eWJiIgejUGE1ZycHMTExCAyMrLRdg4ODnBxcUFGRkYr9cwwtcaKaUNYlc395YmIiB6dQYTVLVu2wNbWFs8991yj7W7evInc3Fw4ODAoPIrWWDGt76uyW6NaAhERUVug99UAqqur4erqiilTpuCjjz5SHi8tLcXSpUsRGBgIBwcHXL58GR988AGuXLmCCxcuwMLColnX12S1WlvTGium9XFVNisZEBERNa5NVQOIiYnBlStX8Prrr6scl0qlSE1Nxbfffos7d+7AwcEBw4cPx65du5odVNuq5s6zbI0V0/q4KpuVDIiIiLRH78PqqFGjoG5w2NzcHL/88osOetT6tLmIR9N5lq2xYlrfVmWzkgEREZH26H1Ybeu0uYiH8yy1w1AqGRAREYmBka47QA9PES7dz5xA5PYFOLcmCJHbF8A9+QRCdyThUFp+s68lrxawIioVAZmJ2Lh3Obzy0tG+sgxeeenY+MNyBGQlYmVUKuTVej3FuVXUrmRQDdURbn2pZEBERCQWDKt6StvhUjHPcnYj8yxzSyqRkH2rJd6OQVFUMjjs5oNZQWFIcnRHqcwcSY7umBUUhsNuPlgk4koGREREYsJpAHpK24t4OM9Su8Z4OCDiZW+siJIh0M1XedzZwgQRIq5kQEREJDYMq3pK2+GS8yy1Tx8rGRAREYkNpwHoqdrhUh1Nw2VLzLOUVwuIy7qJqOS/EJd1s03Od1VUMpjQvyv83DozqBIREWmII6t6StvbkWp7x6jGqhS01GijNkt4tQZ96y8REZEuMKzqqZbYjlRb8ywbK4H1ZkkFbMykuFFWrWz/sKW26r5m3XBsYy7FBC9nPNPHXnRBUJslx4iIiAyZ3m+32tLEvt1qS2xH+igjfo1tNXqwlz9mT1yIEVkJmBu3WyXEHnbzeeg6rrXD8ey4XbhiZY/w4a/jmsWDhWViCoJ1+6utz4GIiEhfaJKvGFabIPawCojrdnJc1k1M2RSPyO0LVBZqySVGGDprI3pfz8GmyBX1pi3MCgpDev8hOLpwpEZ9rxuOf+01GKETF9YEwfgHgXi9fwiOiCAINhbmH+VzICIi0iea5CsusDIAYlrE01CVggSnvrja0R5z4ndrtY5r7fqwgkSCFcNn1NSejVyhUnt2k0g2NmA9WyIiIs0wrBooXa3Eb6hKQWGHTgC0X8dV0b7HjVxs9XoeVzvaY7aWA7E2sZ4tERGRZrjAygDpcvFOQ1UKbEtvA9B+HVdF+5FvRCjnqIo5CF6+cRcA69kSERE1F0dWDYxi8Y77mROI3L4A59YEIXL7Argnn0DojiQcSstv0ddvaKtRaXUV2lfcwzo/7dVxBYDbdysAQYDHtUx8+OsGANqrPatt8moBu+Oz0b78HtYPDlb7Oaz3e7jPgYiIyFAxrBoQebWAFVGpNXM29y5XmbO5sRXnbCpKYP3ZfwgCp30Kj7f3IPjlT2BmaYHYHqohNsnRHbOCwnDYzQeLNCy1Ja8WsOqnVARkJWLT3hV4KfkQnO4UYEMDQfBhA7G2JGTfwl+lVZgTtxtHevhg1qTFKp/DzEmLccTNB0GDXLm4ioiI6G+cBmBAFIt3vmhk8U6gmy8Ssm/Bz61zA1fRjoa2Go0+X/DIdVwV6r1fQcDi2M0InbgQsyYtRmj8nkeuPatNiukH00//jMdu/4UVw2cgcNqnyvNOd64BEgm627TTSf+IiIjEiGHVgIht8Y6iSkFtDYXYhwmQ6t7vmItxiNgfXi8IPmwg1qbai8/GXIzDyIw/kODUF4UdOsG29Dak1VUIfvkTzlclIiKqhWHVgNQOQ2JevKMuxNbVnNqxDb1fRRDc0X8slowKRdhzj+PVIbq/tV538ZlUqIZfbiqABzVWOV+ViIhIFcOqAakdhiL2rsQppz7KUbuBV8/rfM5mczW3mkFDlQcAQCIIOO7mDWcLE1EEVaB5W+TOG+SKn1PydL65AxERkVhwB6sm6MMOVrUdSsvHmzuS0L7iPu7KHsx9bF9xD3dl5vhK5Ft5aroVqbJ9VqLa8KfrHavUURfGu5gZoRoS3CyTK4+JaYtYIiIibdIkX3Fk1QBJAAy6koq5cQ+2G13nF4LYHj667lqj6lYzUIyUKqoZzAoKw8ooGUb2sVeOOCoqD2hr0VZrqDtv9/KNu1gbcxHPqAnooSUVogzcRERErYUjq03Qp5FVfd93Pi7rJqZsikfk9gVq59wmObojcNqn+O/MwfXmvDZnjqsY6fufGRER0cPQJF+xzqoB0fd95x+lmoFi0daE/l3h59b5kYJda25Vq+9/ZrXpaotfIiIybJwGYEDEVrpKU2KoZtDaW9Xq+5+Zgi63+CUiIsPGkVUDUjvsqSOW0lUNqb26Xxc7UOliq1p9/zMDdL/FLxERGTaGVQOi67D3qBSlnQ67aW9L1ubS1Va1+v5nJpYtfomIyHBxGoABaU4dT11uN9oculrdr6utavX9z0xMW/wSEZFhYlg1MPpYyqkubW7J2ly6nDuqz39mhjLnloiIxIth1QDpIuxpW3O2ZNUmXS/u0tc/M11/bkREZPg4Z9VAabOUU2vQddkjMcwd1bc/M0AcnxsRERk2jqySzomh7JG+zx3VFX5uRETU0riDVRP0aQcrfaQoexSgZqvRw24+rb7VqLrg7GxhgkUinzuqa/zciIhIE5rkK4bVJjCsthyxbjWqr1u36ho/NyIiai5N8hWnAbQRYgwSYi171NqLuwwFPzciImoJDKttgBjmhKrDskdERETUFIZVA1d7TugXdeaEhpZUtPqc0NpY9oiIiIiawtJVBkzsW2Gy7BERERE1hWFVDzxsDVLFnNDZjcwJzS2pREL2rZbodpMUZY8Ou/lgVlAYkhzdUSozR5KjO2YFheGwmw8WsewRERFRm8ZpACL3KPNN9WFOqD5vNUpEREQtj2FVxB51vmljc0LlEiPs7TsCAHCjpBzyaqHeCGZrVRB42K1GxVjhgIiIiLSLdVaboKs6q9qoQaq8RvIJbPzhwTUO9fLDiuEzcLWjvbJt3dFasVYQUBB7/4iIiKhhrLNqALRRg1TdVphXOtph/vMLMCIrEV/89Ina0VoAoq0gAIi7wgERERFpF0dWm6CrkdWo5L/wr++TcW5NENpX1p9TWiozh8fbe7A2uB/srcwbvRVeexRSKq/C0OwkfLN3hdrR2j/7+QOQ1IzGimhXKQWx7npFREREzadJvtLragBLly6FRCJR+bG3f3BrWxAELF26FI6OjjA3N8ewYcNw7tw5Hfa4+WrPN1VHUYM0/Kc0TNkUj399n4wpm+IxNDwah9LyVdqO8XDAsYUjsehZd8ilxuiXn4E/nD0glzz441eM1l4trcLVUvFWEBB7hQMiIiLSLr0OqwDQt29f5OfnK39SU1OV51avXo01a9Zg3bp1SExMhL29PUaOHImSkhId9rh5mqpBumzkPwBBgGdqHCK3L8C5NUGI3L4A7sknELojqV5gjT5fgK8OXwQArH3qZUyZGo6hszbiUC8/ZRtFdQBAvBUE9KHCAREREWmP3odVY2Nj2NvbK3+6dOkCoGZU9fPPP8eiRYswadIkeHh4YNu2bbh37x527typ4143rbEapDODwnCuiysCshKxqRnF/hVzPPufi1cNttdzEDpxoTKwKkZrgaZHdBUVBFpbc0ecuesVERGRYdD7sJqRkQFHR0e4urpi8uTJuHTpEgAgOzsbBQUFGDVqlLKtqakphg4dipMnTzZ4vfLychQXF6v86IqiBumf/YcgcNqn8Hh7DwKnfYoUDz/IpcaY04xb4YpdrEZkqgm2kSsQkJmIlcNnoFIiRYR/MJw6GMOpQ8Mjuuv9giGVV2H5gQtqpxy0NO56RURE1LbodTWAQYMG4dtvv0WvXr1w7do1rFixAv7+/jh37hwKCgoAAHZ2dirPsbOzQ06O+lvIABAeHo5ly5a1aL81oa4GaUFxGd7eldysW+FNVhWIrwnAIS99hDNd3REx8QkAQGjpgwoCvW/kIN3GBev9gnHEzQeQSGBXchPWBbcQuqN1V9+rq3Cg6F+EfzAOu/kggrteERERGQy9Dqtjx45V/renpyf8/Pzg5uaGbdu2YfDgwQAAiUQ1tAiCUO9YbQsXLsT8+fOVj4uLi+Hs7KzlnmtGaiSBr6u1MrDeKi0HoL7YP6B6KzzmfE1obyrYnnXsjVlPP6YMnep2lbIruYHPf/oU3YoKsGFwMA738IFnQSZWRskwso99qwVE7npFRETUduh1WK2rffv28PT0REZGBiZOnAgAKCgogIPDg/BSWFhYb7S1NlNTU5iamrZ0VzWirgC+TJBjvX8INv1Qv3yT4la4t0snvLUjEUDTwbZfXjo2/ibBgG6dMMbDAWM8HDDC3Q6+H/4CxysXsfjIZgy6eg5SoRoAsDFyBWZNWoxUezdc+3vKQUP1XlvCw+56RURERPpF7+es1lZeXo4LFy7AwcEBrq6usLe3R3R0tPJ8RUUFjh07Bn9/fx32UjOKxVHuZ06oLo66dgmHH/PBzDqLr2YFheGwmw8WTfBEUs5t3Lgvh13JTWwYHKx+jufgF+F8pwC7vnu/3sKspJzbuFNRjRXREfDPTVUGVaBmCsGsP37ANQsbAMCJzOutvuBKaiSBn1tnTOjfFX5unRlUiYiIDJBej6y+8847GDduHLp164bCwkKsWLECxcXFmD59OiQSCebNm4dVq1ahZ8+e6NmzJ1atWoV27dph6tSpuu66WnX3uvd26YQVUakIyExUKYDvlZeO/dvmY+L0NTj+mDcO17oVbmNmhHlP9sDIPvb4OSUPALAw9j94e9wCzJy0GLPj9zyY4zn4RRzu4YOI/eEwEeT1dsVqrEzUoV5+WD7iDeXjdbFZ2H/qCrc7JSIiIq3S67B69epVTJkyBTdu3ECXLl0wePBgxMfHw8Wl5tb2u+++i/v372P27Nm4ffs2Bg0ahF9//RUWFhY67nl96m7125pLUXhf3uDiqCXRXyNw2qcI8nLCkfP5uFUmx42yaqyNuYg9f2TjxUGuAIBuRQWI2B+ORaNmI3Dap8prON+pOT7mYhyA+jVKa5eJqj2F4FAvP4ROXIgRmYn48sfV3O6UiIiIWgy3W21Ca2y3Wnuv+9m19rpf7x+Cw4/54POfPsXEC8fqPU+x5aoEQr3nbvAPwWE3H1ibGWPAuThs/GE54rp54qUpq/D28R3wzT0H31pzUAEgydEdgdM+xX9nDoafW2fl1qa9k08o58bKJUYYOmsjel/PwaZI9Vu2crtTIiIiakyb2W7VECjqoCpu9deug7rph+UYkZWI8OGvqWyNqnC+S3dI5VUYoea5is0BjCAg5u+NBUzklehadA0p9j0xKDdNJaiqq1GqKBN1xO3B3NhjrgNwtaM95sTv5nanRERE1OL0ehqAIWiqDuqcuN0InPYp/nDqC//cB1vJVkOCj4a/3uTmAIFuvvDtbo1kMz8E/z239S9LW7wRGIY5cU3XKG2oTBS3OyUiIqLWwLCqY83d635VwAws+/UrlXB5uqt7s56bcPk2AKC9kYCn+zigt50FfrCQIbBH82qU1i4TdSLzOtbFZjWrxisRERHRo2JY1bGGFjEpKMJfQffeqoujLEzw9qDuWBuToXyuXGKEBKe+KOzQCbaltyGtrgIAbNm9BFblpVjnF4L/yX2QkHkdyyc9gU7tTZtdo1RRJsrX1Rr7T13BBv8QbGykxiu3OyUiIiJtYFjVsdp73TcW/g6/9wyScm6joLhmByvr9jLYWpjBqYMJ1vuHIDAlBquGv46rHe2Vz29ffg+d797G05fPQCpU45u9yzFz0mLEd/PE7J2n8dXL3nj+CUckZN/Czyl5zQ6t3O6UiIiIWgurATShVasBZCWqD39/l4I6mJKHf+9LwY37cuVzO5gYobSi5nFAZgLmxO9WVgRY5xeCWLeBKuWpFCv+vf66gBw3D5gbG+Fq6YNyWU4WJs2qlaqu1JazhQkWtUCd1br1Z7lTFRERkX7TJF8xrDahNcIq0HT4Cz94Ht/EZkAufTAY3vFeMe6YW8Csqhz+OWfxzV41paQmLUZ6Fxcc3TgLUqFaWe7q+fPH8PPjTyMgKxFz1JS8ak6t1NYIkeo+l+YGaiIiIhInTfIVpwGIRGN73R9MycfXxy4hIDupZgV/rZHTI24+KDMxw9y4BkpJxe9B4LRPkeDUF365qco5sPHdPDEiKwGbagVcRcmrWUFhWBklw8g+9jodwaxdf/aLOoGamw8QERG1DQyrIqJYxFSbvFrA0n1n1QbLb/Yux7hX1uKcQ4+mS0l16IRqSLBh8IuwvleEGx2sGw64dbZdVaelRzzr1p8Va6AmIiKilsVNAUQuIfsWCu/LGwyWwanRAGqqCaijGEm9Y2aBNwLDcLiHL26ZdQDw8LVSFSOe7mdOIHL7ApxbE4TI7QvgnnwCoTuScDAlD3FZNxGV/Bfism5CXq35TBNF/dnZjdSQ5eYDREREho9hVeSaqsM68fxRSOVVWD84GNVQHWGshgTr/YIhlVdhyahQXLTphnePbVOWyGoq4KqrldrYjlsbf1gOz4JMzPvuFKZsise/vk/GlE3xGBoejUNp+Vp939x8gIiIqG1gWBW52nVY1cns7Ay51BhHevhg1qTFSHJ0R6nMHEmO7ngjMAxH3Hzwyumf8d+dC3Fs4yzM/uMH7Nq5EO3L72GdX4jagNtYrdTGRjx/7TUYqXZueDLrlNoRV00Ca1Pvm5sPEBERtQ0MqyKnqMO63l99sFzvF4z25fcw/7ftuGDbHYHTPoXH2zWLqo65euHdY9uw5Mg38MtNhVSoBgCYCHLMjtuNI24+mFkn4M4KCsNhNx8saqBWakMjnnKJEVYMn4ERmYn4Zu+KeiOuAVmJWBmV2uwpAbXrz2oaqImIiMhwMKyKnKII/xE3H8wMClM7cmrUoT0+Gzodf1nZAQCszaQY62EHudQY00//rPa6088cACQSJDv2Ugm46f2HNLrKvqERzwSnvrja0R5z4htetKXJHFPF+z7s5oNZdd53U4GaiIiIDAerAeiBMR4OiHjZGyuiZAh081UetzOXYsML/TDao37Jq4TsW/hf2rUGt3E936U7AGDy2V9w18QcW30mIOy5x/HqENdGA2BDO24VdugEQHXEtfb2rxbld2vaaTDHtKH37WxhggjWWSUiImoTGFb1RGN1WAHUKzHV2DauB3v54/+enQcAWO8/GQAgq5bDwcq8yZFKqZEEH4zzxJySCswMDMPsuJodt+6YWQCAMhwf6uWHFcNnqGz/KpVX4fKNe1p930RERGTYuINVE1prB6uWoG4b120DnsMnQ6djeFYChl9KglllOcpMTBH72EAc7dHwzlWK3apizhcg6nQubtyXQyqvUtlRy1hehaHZpxGYGoM5E99HQGYiZtfd/rWR1yAiIqK2gdutapE+h1WgfvF+qbwKjxdewh1zS5VRT6c7Beh4vwRFvfrg6MKRKiOX6jYAkMqr8Pi1SwhOi1EG3t1PjESaXQ+0r7yPwTmp2BSpZvvXoDCk9x9S7zWIiIio7eB2q6SkuI2+9UQ2lh+4ALnUGOfse9RsYfrTJw+2MB0cjMM9fCD8vQhKMa1AMTo7os6Wp+v8ghHr5gPbP/ZgzMU4AMDLZ/6HgJkRyLZ2anShVaCbL7aeyIaNhSlv6xMREVGjWA2gDZAaSWBjYVrz3/IqjMhMxMbIOuWlIldgRGYipPIqHM+4Dnm1oLIBwKY6GwB8s3cFAjITsXL4DMglNV8jQSKB99ULAJou5r/8wIVH2jSAiIiI2gaG1TZCUXJKLjVucNRzdvweyKXG2HA0C0NXRWPdkYzGtzyN34PcjvZIcOqLQ738MHTWRvzwxEgATRfz//DXDY+0aQARERG1DQyrbYSvqzU6mtbcam9q1PNfv+9Ar+QTWBtzsVntY3r6InTiQrhfz8GeHe+ga9G1RrZ/fRHOdwrwUvKhR9o0gIiIiNoGhtU2QmokwTN9HQE0Peo5+Mo5fLN3OQb89Wez2kc9PhQBf08t8PnrT4Qd+QZHetTfHeuNwDDEuvlgUexm5W5awMNtGkBERERtA8OqnpFXC4jLuomo5L8Ql3VTo5HIIT1sIJVXNTjquWFwzain79VzMIKAhbH/qWnf4FavL8L67h3c6GCN2bWmFoy5GIeI/eFI7+JSb/vXtT99plyQVZtilFaTTQOIiIjI8LEagB5RV0LK2kyK6U8+hrkjeja5ot7eyhxyqbFy1HN2/B70vpGDdBsXbBj8Io708EHE/nDlqGef65dr2j9Ws+WpolZruo0L1vsF44ibDyBRP7VgzMU4jMz4A8dcB+D1F5dhYn9H7E/OQ7eiArV9U4zSKubWEhEREQEMq3pDWeA/MxFTr57HdwPG4i8rO9wqk2NtTAa2/56FFUH9Gy22r9jVyjrjvHLUU8H5TgEi9oerjHoqAuQYT3ukWg6pt9XrawOcUFUtYHv8FbXbukqFaliV1Wyz+qK3M05lXVe7o1Y1JIjwD4azhQl8Xa0f7YMiIiIig8Kwqgdql5CaVGt3qC9/XK2yO1RombzR3aGkRhIsnuCJ0B0VGJaZiBmJ+/DFkKlwvfUXdu1cCBNBrmyrmBYglVfh5UHdMXiqt9otT+XVAmLP5TcZQge7da557ZKKeqO0Ef7BOOzmg4gJnqy3SkRERCq4g1UTxLCDVVzWTUzZFI89O97B28+/A/frOdioZneomUFhuNiM3aH+X0wGvvjl/IOtUgUBI7ISMSeu/m3+zubGSPj36Eavp25b1/NduuOj4a/jdFd3vP1ML4QO64GknNuIPl+An0/novD+g2DsbGGCRRM8uQUrERFRG8EdrPScvFpQGcUsKK5ZdFQqa4+rHe3xxU+fqK+T+vfuULV3oFKnu007yKXG2LJ7CYrN2uNyR0fseWKkyrQAqbwKkAArg/o1GlTl1QKszGV4fYgrosyMlVMFpPIqZRheG5OB9dF/okIiVT7PxlyKCV7OeKaPPXewIiIiogYxrIqMukVUNuY1IS/FoSeApuuensi8ofZ2vSIAFxaXAwCsyksxPDsJADA3fjcSnPqisEMn3DGzwJJRoZgX0KPR0U51fZXKqyA3kmJodhLmxu2utz3r2p8+Q7eiAmzwD8F/7lfBh0GViIiIGsGwKiK1F1F9EbdLGfTW+4fgaHcvHHvMGwDULmYCHiyIWhebqTzmZGGC5wY44cCZq/VC5Xq/YGzaWzOdQCpUwy83tWY6waTFkMqr4NO94dHZhvq6zi8ER9x8EJR6WNlHxfassyYtxmdPT8PRjbOw8YflmBUUhpVRMozsY8/ASq2i7l0LjuoTEYkf56w2obXmrMqrBQwNj4b7mRPYuLf+QqWJ09cgxa4HpNVyDM1Owjd7689ZfSMwDCddnkBI8iE8fj0HFcYm2PPESKTa9UBAViLm1AqV/37mTaTZ90BAZoJKCauIwS/icA8fCBIj/L/J/TGhf1eN+zpz0mJc7OKCoxtnqRT/T3J0R+C0T/HfnQvhl5uqfPzdG4MwpIdNC32yRDXU3QlwsjDBYs6XJiJqdZyzqocSsm/hakklvojbpXY+6sj0kzjXxbWm7qmbL94IDKuzIOpFHHHzgaS6Gtt8JiqfK6uqgGdBBjbVCpVeeen48dv5mDDtMxx3HYDDPQcp2zvfKcD8Y9vx2bDpyLhWirism/VGn5rq6+z4mk0AEpz6wi83VXlOWfi/QyeVx2/tOIVVQf0wso89R72oRTR0J2CDfwhCSyoaraJBRES6xbAqEoqdm3pfz4FcYqScP2pbehu3zS2x5ulpGJ6ViLlxu3HFyh7hw19XWRBlV3IDkEgwID8di2M3q9yWj3UbiF97DVapoWoEAUsPb0TgtE8RFrMRNvfuwLb0Nm6aW+K95/4FoGY6wbrYzHqjT7X7CqBef/sUXqpp93coVVAW/i+9rfK4e1Ya3txRBRszKW6UPRiJ5agXaUPt0m8b6/yjjdNRiIjEj2FVJBQ7N23zeh47+4/B1Y72ynOyqgqMyEpUzi/1ykvHuD+P4w+nvlg1fAauWVjjf/+ZC69/fY9XTh+oM1d0OWZOWoyVw2dgZMYfKrflFSObJabtEJR2GKuGvYZd/UZjRFaCyuKouqNPir6md3FBYQdrrBg+Q6W/tiU3a/7371AK1N/OtRoSRPz9+PWE/Tg98X08kRbX6OsSPYym7gSENrOKBhER6YaRrjtANXxdrdHZTIrVQ6ej9/UcRG5fgHNrgvDhrxtQYSzDnLjdKn/RSoVq+OemYlnMV7jewRo/PT4UAGBXekvluorb8rkd7ZHg1FflnGJk8/OnXsaAt77DD57PYERWAr7ZuwJeeeloX1mmHH0KyErEyqhUyKsF5U5YS0e+idCJC+Feq7+R2xfA41omIAg41dUdpTJzJDm6443AMBzp4Yv5x7cj2aEXZk1ajMM9fLAw9j/4aPhrCMhs+nWJHkbdOwF1Kaen/N2OiIjEhWFVRCQQMCIrAZsiH4Q2q7JSAE3/RbvriZFw+nvUsqE2tW/LK3aX6mwmhQQC+hdkQC41xtw6oRh4MPqUW1KJhOxbkBpJ8ME4D5zr4ooRWYnYGKkaMr/ZuwIjshLx+ZMvwePtmvmrx1y9IEgkeHvc/yFw2qdI7+KCiP3h6HS/BFc72mNOfNOvS/Qwat8JUEc5PeXvdkREJC4MqyKRkH0LN8qq64VF5fzOJv6iPW/nhqnJh1Ru89dtc8fMQjnSOSsoDDFuPpBAQEBmIl5J+hlA06H4f2n5iMu6Cat2MsilxvVGfIGakDknbnfN+RPfw+uvC7BuLwMAvH18B/67cyGObpyFMRfjHiy24qgXtRDFnYAN/iGohuqc1NpbAvu6Wuuoh0RE1BiGVZFo6Fal79VzcLpTgPWDg9X+RbveLxgm8kpY37uD010fV9tmg18wTAU5lowKVY50pvcfgref6YUbZdWYHbdLOX2gqVD8bVwOpmyKx1s7Tqntr4IiZB7rMRBnurpj2aT+cLIwQapjLwzKTVOG6uaGcW2MesmrBcRl3URU8l+Iy7rJqQVthNRIgsUTPHHYzQezgsKQ5Oiu8o+2w24+WDTBk4uriIhEigusRKL2rcraBf+lQjUWx25G6MQP1JSrqtkVSoCArkXXcbiHD2ZOWqxSN3WDfzCOuPlg/VRvdGovUykL9XNKHoCawGlWVQGnOwXYMDgYGyPr13Bd7/ci7EpuIPqb2ci0ccaKEW/gVtfHm9yg4Fr33ogI7IcxHg4wMgJCSyowKygMoSdr3oe0ugrtK+5hnV8IvlFTs1Vbo16ssdm2jfFwQMTL3lgRJVNuCQwAzhYmiOB3gIhI1LgpQBNafVOA5BPY+INqaDvYyx+zJy5E+4r7uGvaTnm8ffk93JWZ4R8JkfjZ/Sn8ZWVXs92p9MG/QZwtTLCogb+M47JuYsqmeERuXwCvvHQc6uWH0IkLEZCZiNBagXe934uIdfNBxP5wZfmrSokU/ef9F4OupKkNmTODwpDm4Yfji0ZBZvxgAF9daOxsJsWtsioEZCUqQ2y6jQsi/INx2M3nkasB1K6xObtOjU1tXJ/0B3ewIiISB03yFcNqE1orrAK1QlWt0Ha+S3e8FrwMg66k4uvIVTjl1EdZz3Tg1fMIfeEDpHdxwScH1mDyS6sxe5gbOreXwbqDKewtG//LWF1APtTLr14pKruSG1gW87VKnVYAWD8oCJ8MnY6AS4mYrUHIVBcYos8X1AuxjQXt5mpqt61ZQWFI7z8ERxeOZGghIiJqJQyrWtSaYRVQP/IIQDn6WZdiy1Kvvy7guvsTOLpwJAA0e/SooYD80fDXcbqrOwAJUtYGw7LiXr3nlsrM4fH2HnQ2NcLN8gcLux42ZLbEqFfd0eO6lFvAzhzMGptERESthNut6il5tQArcxkWjO2DW3crYN3BFFmFpVgXm9nkQqbTXd3x1QRPtSOU6uZmKoJheVU15j3TC7s7mKjM5bM2kyKojwN+OH0VmTbOjc5L/eJlHxgZSR45ZEqNJFoPjKyxSUREpN/0OqyGh4cjMjISf/75J8zNzeHv74+PP/4YvXv3VrZ59dVXsW3bNpXnDRo0CPHx8a3d3UY1tADoxUHdAdRfeKWgCIxvP9MLAJq1/7na1+pgguefcEBc+jXcLK/GrTI5fjh9FTJBjqUj38T+bfMbXPw02K2zaG+hN7RwTYE1NomIiMRNr0tXHTt2DHPmzEF8fDyio6NRVVWFUaNG4e7duyrtxowZg/z8fOXPwYMHddRj9RS34t3PnEDk9gVIWRuMD3/dgI6ZF7A25iI6m0oarBG54e/AOOtpNyzeexZ9C7LwesI+9MvPULsT1MGUPJXXUuw6ZZ15Hj+fzUP/c/Eqx5+6lIQUux6YOH2NXpb8YY1NIiIi/WZQc1avX78OW1tbHDt2DE8//TSAmpHVO3fuYP/+/Q91zZaes1p3AdCvvQbXW+BkUi1HpZERnmlgtfyspx/DvsQrKLwvVz7H6U4BFsduVi6KUszNtDGXon9qnMpiI7nECE/P2gi7u7fwStIB2JXegu/Vc5AK1aiUSBHy0kdIceyNKsmDf9toY/FTa1E3L1eb1QaIiIhIM212zmpRUREAwNpadZTs6NGjsLW1RceOHTF06FCsXLkStra2aq9RXl6O8vJy5ePi4uKW6zBqFkJdLanEF3G78GuvwcrSUV/89InyNv46vxDEuvngTF+/ejUiZw1wwsbfLmFEZiLm1L71PzgYoRMXKstNKeZm3rgvx+y4XSq39NcNDkaBhQ3+6miP0137AKgJu8+l/44DvZ9UCc6dTY3wylM9MHdED1GPqNbGGptERET6y2BGVgVBwIQJE3D79m0cP35ceXzXrl3o0KEDXFxckJ2djbCwMFRVVSEpKQmmpqb1rrN06VIsW7as3vGWGlmNSv4L//o+GSlrg/Hsa1/A/XpOvaL8itHNy24eCB3RCzYdZLC3Moe3SyeM+Dim4bJMkxYjvYsLjm6chWSHXgic9ikA4NyaILSvrFlQpKitOjwrEXPjdivD7tKAfyDFoScCMhMwJ363QdQmZY1NIiIicWiTpavmzJmDAwcO4Pfff4eTk1OD7fLz8+Hi4oLvv/8ekyZNqnde3ciqs7Nzi4VVRWmlD3/dgH+Pml2vxJK6uqeK1f1W5rJmlWXauXMh/jPoBaR6+OHafbmyvVxihKGzNqL39RxsqhWQlcdv5GDT3vq7WbE2KRERET0KTcKqXi+wUnjrrbfw448/IjY2ttGgCgAODg5wcXFBRkaG2vOmpqawtLRU+WlJigVAu/uNAqBaYkkx6ul+PUdl0ZN78gmE7khCzPmCes+pTXHrf1XADBx288GSF/qpLDZKcOqLqx3tMSd+t0ogVR6PUz0OAEYQEHpyN3JLKpGQfUurnwURERFRXXo9Z1UQBLz11lvYt28fjh49CldX1yafc/PmTeTm5sLBQRy3sKVGEiye4Ik3d1QAeFBiSS4xworhMxCQmagyLUCxun9WUBh+NDdWeU5dirJM17r3RkRgP4zxcICRERBaUoFZQWHwyLsIoH7YLezQSe1xBdYmJSIiotai1yOrc+bMwY4dO7Bz505YWFigoKAABQUFuH//PgCgtLQU77zzDuLi4nD58mUcPXoU48aNg42NDV544QUd9/6BMR4O2DDVCzJBjnV+qqOes+MbHt28fl8OW3Npo2Wt7MylOLFolHJ+qWKx0Z/9h+Dzp14GUBN2a7Mtva32uAJrkxIREVFr0euwGhERgaKiIgwbNgwODg7Kn127dgEApFIpUlNTMWHCBPTq1QvTp09Hr169EBcXBwsLCx33XtWzTzji85d8ENvDBzODwvCHc18ATY9uPu/lXFO+KihMpQ7qzKAwHHHzwbLAfpAZq/4xj/FwwLGFI/HdjEHobGqE9XXCru/Vc3C6U4B1fsGsTUpEREQ6pffTABpjbm6OX375pZV68+iefcIBEUbeeO97CQ7/XWKpqVv8I/vYw9fVGot/kKqUZZLKq2Bt1vAfr9RIgiE9bbDyxf4I3SHHrKAwlRqk1mUlOOLmi5lBYZitrjapyDcDICIiIsOg12HVEFVXCygpr8KAgou40tEB6wcHq6zUB1R3rvJ1tUb0+QLcKJPD668/MfRSEp7Iz0CHirv42i8YoWVVjZaZaqwG6T8GOOGAJWuTEhERke4YTOmqltLSO1jVJq8WMGj5L7jxd3mpwg7Wyk0CQuP3KEc31/sFI7ZHTa3TkX3sVXbAetgyUw3VIGVtUiIiItK2NruDlb5LyL6FG39vmdr7eg688tIRsT8cK4bPUBb0B2pu8b82xBVjPBwQl3VTuQNWQwuxAt18kZB9C35unRt8bamRRO35ho4TERERtQaGVRGpXQpKMVd1zMU4jMz4A/HOHojr5okCCxv88MRIBLjbAQAKimoqH2RaO6FcKoPv1XOQCtXK67DMFBEREekzhlURUZSCsiu5iQ2Dg5X1VaN7Dqq3i9W/diQicJAL9iVeAQC8+9zbAACnOwVYHLsZYy7GAWCZKSIiItJvDKsiotjNyrrgFg738MGsSYsx4K8L+HToKxiRmYgvfvoEva/nIL2LC9b5heDrMjk8CzLxVcxXyuMbBgcjdOJCROwPx6iL8SwzRURERHqNC6ya0JoLrADgUFo+QnckwaMgEwXtrXGrnRWGZifhm731KwK8ERiGizbdcGzjLOWt/2pIMHPSYqTZu8Gj8BKOuPk0Wg2AiIiIqLVpkq/0elMAQ6QoJXXN1R3XLTpDLjXG3Dj1u1jNiduNqx3tkeDUV+X47Pg9uGZhgxQPPwZVIiIi0msMqyI0xsMBC8d5KB83tYtVYYdOao9/MJ71UImIiEi/MayKlL2VufK/07u4qG2jXDxVelvtcXtLLqoiIiIi/cawKlK+rtbo2sEY7SvuYf3gYFRDtRB/NSRY7xcM25Kb8P7rgspxLqoiIiIiQ8GwKlJSIwnCJj6BuzJzHO7hi5mTFiPJ0R2lMnMkObrjjcAwHHHzQaFFZzz55mbs6zMUSY7umBUUhsNuPlg0wZM7TREREZHeYzWAJrR2NYC6DqXlY9EPZ3Hnbjnk0geVxuxKbmBh7BZ0KyrAOr8QHHHzASQSOFuYYNEEzlUlIiIi8dIkXzGsNkHXYRUA5NUCTmbcwJwdiXDOzcCiI5sxqNZOVdWQYGZQGNI8/HB80SjIjDlgTkREROLF0lV6SF4tIC7rJqKS/0Jc1k3Iqx/8G0JqJIGxsRGKKwUsj46Af26qypaqRhAw++RuXLsvR1LObXWXJyIiItJL3MFKBA6l5WNFVCqullQqjzlZmGBxrdv5hSVlAJpRxurvdkRERESGgGFVxxQ7VgVkJuKLuF0Ptk31D0FoSYWyqL+tRU0ZqvQuLvDKS693HWUZKwuWqyIiIiLDwWkAOiSvFrAiKhUBmYnYuHc5vPLS0b6yDF556dj4w3IEZCViZVQq5NUCfF2t4WRhgg3+IWrLWLFcFRERERkihlUdSsi+hasllZgdt0vtdqqhJ3cjt6QSCdm3IDWSYPEETxx288GsoDCVMlYsV0VERESGitMAdEjTeahjPBwQ8bI3VkTJEOjmq2znbGGCCJarIiIiIgPEsKpDDzMPdYyHA0b2sUdC9i0UlpTB1sIMvq7WHFElIiIig8RpADr0sPNQpUYS+Ll1xoT+XeHn1plBlYiIiAwWw6oOcR4qERERUeM4DUDHOA+ViIiIqGEMqyLAeahERERE6jGsioRiHmpzyKsFBlsiIiJqExhW9UxztmYlIiIiMhQMq3qkuVuzEhERERkKVgPQE5pszUpERERkKBhW9YQmW7MSERERGQqGVT2h6dasRERERIaAYVVP1N6aVR11W7MSERER6TuGVT3xsFuzEhEREekzhlU9wa1ZiYiIqC1i6So9wq1ZiYiIqK1hWNUz3JqViIiI2hKGVT2kydasRERERPqMc1aJiIiISLQYVomIiIhItBhWiYiIiEi0GFaJiIiISLQYVomIiIhItBhWiYiIiEi0GFaJiIiISLTaRFjdsGEDXF1dYWZmBm9vbxw/flzXXSIiIiKiZjD4sLpr1y7MmzcPixYtwpkzZ/DUU09h7NixuHLliq67RkRERERNkAiCIOi6Ey1p0KBB8PLyQkREhPLY448/jokTJyI8PLzJ5xcXF8PKygpFRUWwtLRsya4SERERtQma5CuDHlmtqKhAUlISRo0apXJ81KhROHnypNrnlJeXo7i4WOWHiIiIiHTDoMPqjRs3IJfLYWdnp3Lczs4OBQUFap8THh4OKysr5Y+zs3NrdJWIiIiI1DDosKogkUhUHguCUO+YwsKFC1FUVKT8yc3NbY0uEhEREZEaxrruQEuysbGBVCqtN4paWFhYb7RVwdTUFKampsrHiim9nA5AREREpB2KXNWcpVMGHVZlMhm8vb0RHR2NF154QXk8OjoaEyZMaNY1SkpKAIDTAYiIiIi0rKSkBFZWVo22MeiwCgDz58/HtGnTMHDgQPj5+WHjxo24cuUK3nzzzWY939HREbm5ubCwsGhw6oAmiouL4ezsjNzcXFYXaCZ+ZprjZ6Y5fmaa42emGX5emuNnpjl9+cwEQUBJSQkcHR2bbGvwYTUkJAQ3b97Ehx9+iPz8fHh4eODgwYNwcXFp1vONjIzg5OSk9X5ZWlqK+kskRvzMNMfPTHP8zDTHz0wz/Lw0x89Mc/rwmTU1oqpg8GEVAGbPno3Zs2fruhtEREREpKE2UQ2AiIiIiPQTw2orMzU1xZIlS1QqDlDj+Jlpjp+Z5viZaY6fmWb4eWmOn5nmDPEzM/jtVomIiIhIf3FklYiIiIhEi2GViIiIiESLYZWIiIiIRIthlYiIiIhEi2GViIiIiESLYbUFbNiwAa6urjAzM4O3tzeOHz/eaPtjx47B29sbZmZmeOyxx/DVV1+1Uk91Lzw8HD4+PrCwsICtrS0mTpyI9PT0Rp9z9OhRSCSSej9//vlnK/Vat5YuXVrvvdvb2zf6nLb8HQOA7t27q/3OzJkzR237tvgd++233zBu3Dg4OjpCIpFg//79KucFQcDSpUvh6OgIc3NzDBs2DOfOnWvyunv37kWfPn1gamqKPn36YN++fS30DlpXY59XZWUl3nvvPXh6eqJ9+/ZwdHTEK6+8gry8vEavuXXrVrXfu7KyshZ+N62jqe/Yq6++Wu+9Dx48uMnrGup3DGj6M1P3fZFIJPjkk08avKY+fs8YVrVs165dmDdvHhYtWoQzZ87gqaeewtixY3HlyhW17bOzs/Hss8/iqaeewpkzZ/DBBx/gn//8J/bu3dvKPdeNY8eOYc6cOYiPj0d0dDSqqqowatQo3L17t8nnpqenIz8/X/nTs2fPVuixOPTt21flvaempjbYtq1/xwAgMTFR5fOKjo4GALz44ouNPq8tfcfu3r2Lfv36Yd26dWrPr169GmvWrMG6deuQmJgIe3t7jBw5EiUlJQ1eMy4uDiEhIZg2bRrOnj2LadOmITg4GH/88UdLvY1W09jnde/ePZw+fRphYWE4ffo0IiMjcfHiRYwfP77J61paWqp85/Lz82FmZtYSb6HVNfUdA4AxY8aovPeDBw82ek1D/o4BTX9mdb8r//nPfyCRSBAYGNjodfXueyaQVvn6+gpvvvmmyjF3d3fh/fffV9v+3XffFdzd3VWO/eMf/xAGDx7cYn0Us8LCQgGAcOzYsQbbxMbGCgCE27dvt17HRGTJkiVCv379mt2e37H6/vWvfwlubm5CdXW12vNt/TsGQNi3b5/ycXV1tWBvby989NFHymNlZWWClZWV8NVXXzV4neDgYGHMmDEqx0aPHi1MnjxZ633WpbqflzoJCQkCACEnJ6fBNlu2bBGsrKy02zmRUveZTZ8+XZgwYYJG12kr3zFBaN73bMKECcKIESMabaOP3zOOrGpRRUUFkpKSMGrUKJXjo0aNwsmTJ9U+Jy4url770aNH49SpU6isrGyxvopVUVERAMDa2rrJtgMGDICDgwMCAgIQGxvb0l0TlYyMDDg6OsLV1RWTJ0/GpUuXGmzL75iqiooK7NixA6+//jokEkmjbdvyd6y27OxsFBQUqHyPTE1NMXTo0AZ/twENf/cae46hKioqgkQiQceOHRttV1paChcXFzg5OeH555/HmTNnWqeDInH06FHY2tqiV69emDlzJgoLCxttz+/YA9euXcOBAwcwY8aMJtvq2/eMYVWLbty4AblcDjs7O5XjdnZ2KCgoUPucgoICte2rqqpw48aNFuurGAmCgPnz5+PJJ5+Eh4dHg+0cHBywceNG7N27F5GRkejduzcCAgLw22+/tWJvdWfQoEH49ttv8csvv2DTpk0oKCiAv78/bt68qbY9v2Oq9u/fjzt37uDVV19tsE1b/47Vpfj9pcnvNsXzNH2OISorK8P777+PqVOnwtLSssF27u7u2Lp1K3788Uf897//hZmZGYYMGYKMjIxW7K3ujB07Ft999x2OHDmCzz77DImJiRgxYgTKy8sbfA6/Yw9s27YNFhYWmDRpUqPt9PF7ZqzrDhiiuqM1giA0OoKjrr2644Zu7ty5SElJwe+//95ou969e6N3797Kx35+fsjNzcWnn36Kp59+uqW7qXNjx45V/renpyf8/Pzg5uaGbdu2Yf78+Wqfw+/YA5s3b8bYsWPh6OjYYJu2/h1riKa/2x72OYaksrISkydPRnV1NTZs2NBo28GDB6ssKBoyZAi8vLzw5Zdf4osvvmjprupcSEiI8r89PDwwcOBAuLi44MCBA40GsLb+HVP4z3/+g5deeqnJuaf6+D3jyKoW2djYQCqV1vsXXWFhYb1/+SnY29urbW9sbIzOnTu3WF/F5q233sKPP/6I2NhYODk5afz8wYMHi/pfhS2pffv28PT0bPD98zv2QE5ODmJiYvDGG29o/Ny2/B1TVJvQ5Heb4nmaPseQVFZWIjg4GNnZ2YiOjm50VFUdIyMj+Pj4tNnvnYODA1xcXBp9/239O6Zw/PhxpKenP9TvNn34njGsapFMJoO3t7dypbFCdHQ0/P391T7Hz8+vXvtff/0VAwcOhImJSYv1VSwEQcDcuXMRGRmJI0eOwNXV9aGuc+bMGTg4OGi5d/qhvLwcFy5caPD9t/XvWG1btmyBra0tnnvuOY2f25a/Y66urrC3t1f5HlVUVODYsWMN/m4DGv7uNfYcQ6EIqhkZGYiJiXmofxgKgoDk5OQ2+727efMmcnNzG33/bfk7VtvmzZvh7e2Nfv36afxcvfie6Wpll6H6/vvvBRMTE2Hz5s3C+fPnhXnz5gnt27cXLl++LAiCILz//vvCtGnTlO0vXboktGvXTnj77beF8+fPC5s3bxZMTEyEH374QVdvoVWFhoYKVlZWwtGjR4X8/Hzlz71795Rt6n5ma9euFfbt2ydcvHhRSEtLE95//30BgLB3715dvIVWt2DBAuHo0aPCpUuXhPj4eOH5558XLCws+B1rglwuF7p16ya899579c7xOyYIJSUlwpkzZ4QzZ84IAIQ1a9YIZ86cUa5e/+ijjwQrKyshMjJSSE1NFaZMmSI4ODgIxcXFymtMmzZNpfLJiRMnBKlUKnz00UfChQsXhI8++kgwNjYW4uPjW/39aVtjn1dlZaUwfvx4wcnJSUhOTlb53VZeXq68Rt3Pa+nSpcKhQ4eErKws4cyZM8Jrr70mGBsbC3/88Ycu3qLWNfaZlZSUCAsWLBBOnjwpZGdnC7GxsYKfn5/QtWvXNvsdE4Sm/38pCIJQVFQktGvXToiIiFB7DUP4njGstoD169cLLi4ugkwmE7y8vFTKME2fPl0YOnSoSvujR48KAwYMEGQymdC9e/cGv3CGCIDany1btijb1P3MPv74Y8HNzU0wMzMTOnXqJDz55JPCgQMHWr/zOhISEiI4ODgIJiYmgqOjozBp0iTh3LlzyvP8jqn3yy+/CACE9PT0euf4HXtQrqvuz/Tp0wVBqClftWTJEsHe3l4wNTUVnn76aSE1NVXlGkOHDlW2V9izZ4/Qu3dvwcTERHB3dzeYwN/Y55Wdnd3g77bY2FjlNep+XvPmzRO6desmyGQyoUuXLsKoUaOEkydPtv6bayGNfWb37t0TRo0aJXTp0kUwMTERunXrJkyfPl24cuWKyjXa0ndMEJr+/6UgCMLXX38tmJubC3fu3FF7DUP4nkkE4e+VFkREREREIsM5q0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0REREQkWgyrRERERCRaDKtEREREJFoMq0TUZgiCACsrK0gkkmb9SKVSlJaWKp+fmJiIOXPmoE+fPujYsSNMTU3RvXt3vPTSSzhy5Ija14yKisKECRPg6OgImUyGzp07w9PTE6+//joOHTrUWm+diEhvGeu6A0REraW0tBRvv/22yrG8vDxs2rQJjz32GKZNm6ZyztLSEh06dEBlZSXmzp2LTZs2QSqVYuTIkRg9ejSMjIyQmpqKPXv2YOfOnfjmm28wY8YMAEB5eTleeukl7N27F7a2thg9ejQcHR1x7do1pKWlYcuWLbC0tMSYMWNa7f0TEekjhlUiajMsLCywdOlSlWM7d+7Epk2bMHr06HrnAKCqqgoTJ07EwYMHMXz4cHz77bdwcnJSaZOdnY3Zs2ejW7duymMLFy7E3r178eabb2Lt2rUwMzNTeU56ejoqKyu19t6IiAwVwyoRtWmnT58GAHh5eak9v3TpUhw8eBABAQE4dOgQjI3r/9p0dXXFgQMHUFVVBQCoqKjApk2b0L59e3z++ecwNTWt95zevXtr8V0QERkuzlklojbtzJkzANSH1UuXLuGjjz6ClZUVvvvuO7VBVcHIyAgymQwAcP36dZSWlsLY2BhGRvw1S0T0KPhblIjatDNnzkAmk8HDw6PeuTVr1kAul2POnDmws7Nr9jXt7e3RqVMnFBUVYeTIkdi1axdu3bqlzW4TEbUZDKtE1GZdvnwZt2/fRt++fZWjorX99NNPAIApU6ZodF2pVIqdO3fCwcEBx44dw+TJk2FjY4MnnngC//73v1FQUPBI/X7zzTfx6quvNtrmpZdewty5cx/pdYiIxIBzVomozWpsvuqNGzdw5coVdOjQAX379tX42mPGjEFOTg5iYmLw66+/4siRI0hJSUFqaiq+/PJLnDx5Eo8//vhD9TslJQVBQUGNtvniiy9gbm6ufPzGG29AEARs3rz5oV6TiEhXOLJKRG1WY2H1+vXrAABbW1tIJJKHur6JiQnGjh2LtWvX4uzZs7h48SK8vLxw584drFq16qGuKQgCUlNT0a9fv0bbde7cGe3atVM+TkxMxMCBAx/qNcVGEATI5XJdd4OIWgnDKhG1WY0trmrfvj0A4Nq1axAEQSuv17NnT2Wd18uXLyuP9+vXD1u2bFE+fvLJJ+Hg4KB8/L///Q8ODg6orKxEVlYWSktLcf/+fTz55JNo164dvL29cenSJWX7P//8ExKJBHfu3EFZWRmkUilSUlIwe/ZsSCQShISEAKhZQDZp0iRYWlrC1tYWb731FioqKpTXuXz5MiQSCdavX4++ffvC3NwcgwcPxsWLF5VtFi5ciMcffxzt2rVD165dsWzZMpX33JxrNNUPxfvZv38/fHx8IJPJcPbs2Yf9YyAiPcOwSkRt1unTpyGVStWOUjo7O8POzg53795FYmJio9eprq5u9mvm5+cDANzc3JTHOnbsiJKSEmWfsrKycPv2beX5iIgIvPnmmzAxMcHZs2chlUqxbt06rF69GomJiaiqqsLq1auV7VNSUtCtWzd07NgRMpkMMTExkEgkyMzMRH5+Pr755htcuHABvr6+GDRoEJKSkhAZGYn//e9/+Pzzz1WuAwCbNm3C5s2b8ccff6CyshJz5swBAFRWVsLU1BRbt27FhQsXsHbtWnz88ccqu3k1dY3m9kMqlWL16tX47LPPkJqaqnZBHBEZKIGIqA3Kz88XAAh9+/ZtsM3y5csFAEL//v2F3NzceudLS0uFL774Qli9erXy2LZt24Rjx46pvd7vv/8uWFtbC1KpVEhISFAeHz9+vLBy5UpBEAThlVdeEcLDwwWpVCrcv39fyMnJEczMzIT8/HxBEAQhLCxMcHR0FIqKipTPnz9/vhAYGKh8/MEHHwjPP/+88vF3330nuLq6qvTlqaeeUum3IAjCRx99JIwdO1b5+MMPPxTatWsnFBQUKI/t2rVLaNeundr3JwiC4O/vL2zYsKHZ12hOPz744AOhU6dOKtcgoraDC6yIqE1qajMAAHj//fdx+vRp7Nu3D71798aYMWPg5uaGqqoqXLx4EcePH0dxcTEiIyOVz9m0aRN+//13uLm54amnnoKjoyNu376N5ORkxMXFwdzcHFu3boWPj4/yOYqR1cLCQvz4449Ys2YNPv74Y9y5cwcbN27EpEmTYG9vDwA4e/YsQkJCYGlpqXz+5cuX0aNHD+XjlJQUldHiuo8zMjJw/PhxnDp1SuW2fWVlJUaPHq18fPbsWUydOlWlbJdMJlNOi7h06RI+/vhjHD9+HHl5eaiqqsL9+/fxf//3f826RnP7kZKSghdffFGj8mFEZDgYVomoTWpsvqqCsbExIiMj8f3332Pr1q347bff8OOPP8La2hpdu3bFSy+9hPHjxyMgIED5nNWrV+Onn37C0aNHERMTg8LCQshkMjz22GNYsGAB5s6di+7du6u8TseOHVFaWoqvvvoKgYGB6Ny5MywtLXH9+nVs3rwZ+/btU7ZVhL/akpOTERgYqNJm2rRpKo99fX2Vj1NSUtC1a1ccPXq03nuuHYLPnj2Lf/3rXyrnT58+jX79+qGwsBC+vr547rnn8OWXX8LR0REFBQUYMWIEnnjiiWZdQ5N+TJ48uV4bImobGFaJqE1atGgRFi1a1Ky2kydPbnZY8vPzg5+fn0Z96dixIzIzM7F3714cOnQIQE1Y27JlC7p27YrBgwcDAIqKipCTk6MySlpcXIzs7GxlQLxz5w5yc3NV2qSmpmLGjBnKxyYmJrh9+za6deumtr4sAJSWliIrK0tl1f39+/exadMmLFmyBD/99BNkMhm2bdumPL9161ZYWlrC1dW1WddoTj8U76d///7N+iyJyPBwgRURkY517NgRUVFR6NWrlzJ0WlpaYuPGjfjnP/+pbHf27FmYm5ujZ8+eKsdkMhnc3d0bbFNZWYnk5GTk5+ejpKQEfn5+kMlkmDFjBtLS0nDx4kX8+OOPWLp0qfI5qampkMlk+Oabb3Dq1CmkpKTgueeeQ/fu3TFjxgx07twZN2/exKFDh5Ceno4lS5bg66+/xhNPPKEs9dXUNZrTj7Nnz8LMzEz5/oio7WFYJSLSsU6dOuHu3bsqwdTS0hLt2rVTlpkCaoJb3759IZVKVY49/vjjMDauuVGWkpKCvn37wsjowa/3lStXYvPmzXB0dMRXX32FLl264Oeff8bly5fh5+cHX19fhIeHo1evXirX9fDwwD//+U8899xzePLJJ9GjRw9ER0fDxMQE48ePx7Rp0/Diiy8iICAAUqkUzzzzjMoIaFPXaE4/UlJS4OHhofKeiahtkQiClgoIEhGRwQgNDUVZWZlK/VddXIOIiCOrRERUz9mzZ+Hp6anzaxARMawSEZEK4e8tXR+l8L42rkFEBHAaABERERGJGEdWiYiIiEi0GFaJiIiISLQYVomIiIhItBhWiYiIiEi0GFaJiIiISLQYVomIiIhItBhWiYiIiEi0GFaJiIiISLQYVomIiIhItBhWiYiIiEi0GFaJiIiISLT+P+VS7YMDWRv6AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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oqfgkpsNnOfBmNnyWg3diOh2jp0riLISdkaRZlEv7RvVo5mWuWf5rXXNOYQ7KHAVljkJOoWy7bI/qOjvw/JDrG54cSiXlcp7KEQmhPoNeT6OdkSgJepSVuZBsgCIg2YBmZS4k6PHfOUdKNYSwI5I0i3K7M6QhAFuOZ6gciahpj/dpQffmnuQXGVkQdVztcIRQ3bE9UfhqLqJsL31TJ82OAvw0WRzbE1XDkQkhqoskzaLc+rYxt57blpBR6pbawn4pisIrw4JQFPguNpkD5y6rHZKwEKPJSHx6PPHp8RhN0iGlvPIuJZs/STeUfsL148XnCSFsniTNoty6NK2Pm6OWrJxC4lKuqB2OqGHtAzy4LzQAgNd/OiIbntiJvKI8QhaFELIohLwiKb0pL5f6jcyf+JaxePL68eLzhBA2T5JmUW6OOg3h11vPbb1eouHi4ELclDjipsTh4uCiZniiBjw3pC0uDlr2nb3E+sOpaocjhGoCewwh3eiJMcKp1MeNvZ24YPQisMeQGo5MCFFdJGkWFdK3rblEY2uCOWnWKBqCfYMJ9g1Go8iPk71r4OHME33NG57838/HyC8q49a0EHZOq9ORHB4JbXQYx7lCgBYcgQCt+es2OlLCZ6PV6dQOVQhhIfK/WVTIjbrm/UmXuJJbhIerg8oRiZr2eJ8WrNx7jvOX8liy8wxT+rVUOyQhVBE6ZCKxQCNTJL5tLxYfzzB6kRI2m9AhE9ULTghhcYpJChOtRnZ2Nh4eHly5cgV3d3e1wynTwHe2ciL9Gh+N78ywDg3VDkeoYF3MeZ5dc5A6Tjo2z+iHT93Sb1ELURsY9HqO7Yki71IyLvUbEdhjiMwwC2FFLJVfyf10UWH92two0UgnX5/P6DWjGb1mNPl62S2utrg3tBEdAjy4VqDn3U0JaocjhKq0Oh3B4cPoOvxxgsOHScIshJ2SpFlUWHFd8/EMivRFrD2ylrVH1mIwSn1rbaHRKLw8LAiAlXuTiDl78TbPEEIIIWybJM2iwro180SrUbhwtYBNR9PVDkeopHtzT/q28cFogklL92E0So9fIYQQ9kuSZlFhzg5a6rmYFwCuiTmvcjRCTU/0MXfSuJxbxLLdSSpHIyojtyiX4IXBBC8MJrcoV+1whBDCaknSLCplVBfzJhe5BSZm953N7L6zcdBKJ43aJqyVN4OD/ABYvO0UeYVSomNrTCYTRzKOcCRDNqwRQohbkaRZVMoj4c0AOHg+h391nUlkv0gctY7qBiVU8f64UBrVcyH5ch4Lt5xQOxwhhBCiWkjSLCqloYcLQQ3dMZlgy/XdAUXt5OKo5ZXh7QD4ZOspzmTmqByREEIIYXmSNItKG9DOF4Dfj8liwNpuSHADIlp7U2gwMufHeLnNb0OcdE6sHrWa1aNW46STfttCCFEWSZpFpQ1o54cJAz8krGPF4VXojXq1QxIqURSFyBHBOGgVNh/PkK4qNkSn0TE6eDSjg0ej00h/YSGEKIskzaLSOjTywNMNzmveZPy34yjQF6gdklBRS586TOpt7qYx96d48otkUaAQQgj7IUmzqDSNRqFPG1+1wxBW5F93tKKhhzPnLubx8daTaocjhBBCWIwkzaJK+rf9M2mWOlbh5qRj1jDzosBFW05y7qL0/bV2hYZCIrdEErklkkJDodrhCCGE1ZKkWVRJeCtvHI1NcDA24XSmJEgChrVvSFhLLwr0Rub8eETtcMRtFBmKmLN1DnO2zqHIUKR2OEIIYbUkaRZV4lPHnbFN1+BfsJBdJ6+qHY6wAoqiMHdkMDqNwqajF/jt6AW1QxJCCCGqTJJmUWWdm9QD4OOtp9QNRFiNVr51izfAmfL1fq7kym1/IYQQtk2SZlFlYS29ALiYU8hp2dhCXDepd3M0ChQajExbdVDtcEQZtBoto4JGMSpoFFqNVu1whBDCaknSLKqse3MvvOuYN0XYdSpT5WiEtWjo4cJjEeYWdNsT0zmRLuU71shZ58ya0WtYM3oNzjpntcMRQgirJUmzqJKcwhyUOQoxhkEYyef3o7KltvjTzKGBDAj0RW+Emd8exmiUDitCCCFskyTNwqK2J2aQWyg7AwozRVGYe08Iro5a/jhziZV/nFM7JCGEEKJSJGkWFtO4vgsFeiNbj8tss/hTo3ouPDu4LQDzfj5Kena+yhGJvzKajMSnxxOfHo/RZFQ7HCGEsFqSNAuLGRBo3ugkKj5N5UiEtXkkrBkdAjy4mq9nzk/Su9ma5BXlEbIohJBFIeQV5akdjhBCWC1JmkWVuDi4EDcljrgpcQzr0AyA346lU2SQGSvxJ61G4c1726PVKKw/lMrvx6R3sxBCCNsiSbOoEo2iIdg3mGDfYLo29cK7jiNX8/XsPpWldmjCyoQ08mBS7+YAvPJ9PDkFUvsuhBDCdkjSLCxGq1EYFOQHSImGKN20ga1pVM+F5Mt5vLMxQe1whBBCiHKzy6R54cKFNG/eHGdnZ7p06cL27dvLPDc1NZXx48fTtm1bNBoN06ZNu+mcTz/9lIiICOrXr0/9+vUZOHAge/fuLXFOZGQkiqKU+GjQoIGl35rVGxxsfs+/xl+Q9mLiJq6OOl6/NwSAJTtPc/j8FZUjEm6ObphmmzDNNuHm6KZ2OEIIYbXsLmletWoV06ZNY9asWcTGxhIREcHQoUNJSkoq9fyCggJ8fHyYNWsWHTt2LPWcLVu28MADD7B582Z27dpFkyZNGDx4MMnJySXOCw4OJjU1tfjj8OHDFn9/1iZfn8/oNaMZvWY0+fp8wlp6UcdJR/rVAg6ev6x2eMIK9W/ry4iO/hhN8OK3h9BL/bsQQggbYHdJ8zvvvMOkSZN47LHHaNeuHe+99x6NGzdm0aJFpZ7frFkz3n//fR5++GE8PDxKPeebb77hySefpFOnTgQGBvLpp59iNBr57bffSpyn0+lo0KBB8YePj4/F35+1MRgNrD2ylrVH1mIwGnDSaenR3BNAbr+LMr0yPAh3Zx3xKdk8vXy/2uEIIYQQt2VXSXNhYSExMTEMHjy4xPHBgwcTHR1tsXFyc3MpKirC09OzxPHExET8/f1p3rw548aN49SpU7d8nYKCArKzs0t82IMATxcAdp/KwmiUWURxM5+6TtzVviEAv8Rf4I8zF1WOSAghhLg1u0qaMzMzMRgM+Pn5lTju5+dHWprlFqa9+OKLNGrUiIEDBxYf69GjB1999RVRUVF8+umnpKWlERYWRlZW2V0k5s2bh4eHR/FH48aNLRajmp7s1wqNAkUGE3Ep9nEhICzvjXtC8HJzBOCtn49KDbxKcotyCV4YTPDCYHKLctUORwghrJZdJc03KIpS4muTyXTTscqaP38+K1as4Ntvv8XZ2bn4+NChQ7n//vtp3749AwcOZP369QAsXbq0zNeaOXMmV65cKf44d872thh20Dowu+9sZvedjYPWAQA/d2fpoiFuS6vV8P1T4bg5atl39jJLos+oHVKtZDKZOJJxhCMZRzCZ5MJFCCHKYldJs7e3N1qt9qZZ5fT09Jtmnyvj7bff5s033+TXX3+lQ4cOtzzXzc2N9u3bk5iYWOY5Tk5OuLu7l/iwNY5aRyL7RRLZLxJHrWPx8WEd/AFYfyhV/hCLMjX2dGXmXe0AWBB1jNOZOSpHJIQQQpTOrpJmR0dHunTpwsaNG0sc37hxI2FhYVV67QULFvDaa6/xyy+/0LVr19ueX1BQwNGjR2nYsGGVxrVVAwJ9cdJpOJOVy5FUKdEQZXuwRxPCW3mRX2TkuTUHMUiZhhBCCCtkV0kzwPTp0/nss8/44osvOHr0KM888wxJSUlMnjwZMJdEPPzwwyWec+DAAQ4cOMC1a9fIyMjgwIEDHDlypPjx+fPn8/LLL/PFF1/QrFkz0tLSSEtL49q1a8XnzJgxg61bt3L69Gn27NnDqFGjyM7OZuLEiTXzxq2Mm5OO/m19AfNssxBlURSFt+7vcL1M4xJLdp5WO6RaxUnnxOpRq1k9ajVOOie1wxFCCKulmOzw3vnChQuZP38+qamphISE8O6779KnTx8AHnnkEc6cOcOWLVuKzy+t3rlp06acOXMGMLelO3v27E3nzJ49m8jISADGjRvHtm3byMzMxMfHh549e/Laa68RFBRU7rizs7Px8PDgypUrNlOqoTfq+e7odwDc2+5edBpd8WM/HExh6opYmnm5snlGP4vVlQv79M2es8z6Lg4nnYaf/x1BC586aockhBDCDlgqv7LLpNlW2WLSnFOYQ5155uTm2sxrJXYUyynQ0/m1jRTojfz0r96ENCq9D7YQYF6QNuHzvew4kUmXpvVZ/UQvtBq50BJCCFE1lsqv7K48Q1iPv5ZobDgsJRri1hRF4f/ub08dJx0xUqYhhBDCykjSLKrVsA7mhZDrD0sXDXF7AfVdeam4m8ZxTmZcu80zRFUVGgqJ3BJJ5JZICg2FaocjhBBWS5JmUSWKohDkE0SQT1CpNct3BPri7KDhbFYu8bLRiSiHB7o3JqK1NwV66aZRE4oMRczZOoc5W+dQZChSOxwhhLBakjSLKnF1cCX+yXjin4zH1cH1psfdnHT0beMDwPu/ld2zWogbzGUaHajjpGN/0mWmrYxVOyQhhBBCkmZR/RrWcwFg87F0jEajytEIW9CongsP9mgCwI+HUvnt6AWVIxJCCFHbSdIsqt3T/VuiAHqjiT1nLqodjrARL9zZlvqu5q3Z/+/nYxToDSpHZJ+0Gi2jgkYxKmgUWo1W7XCEEMJqSdIsqp13HWdGdDQvCPzlcNptzhbCTKPRsH5qbzzdHElMv8bbUcfVDskuOeucWTN6DWtGr8FZ56x2OEIIYbUkaRZVklOYgzJHQZmjkFOYU+Z593QOAOCnQ6kUGaREQ5SPfz1X5t/fAYBPt59mR2KmyhEJIYSorSRpFjWidytvvNwcycopZMcJSXxE+Q0M8iuub352zQEu5UhbNCGEEDVPkmZRIxy0muKezT8cSFE5GmFrXh4WRAsfNy5kFzDz28PS89uCjCYj8enxxKfHYzTJXSAhhCiLJM2ixozs1AiAqPg0cgv1KkcjbImLo5YPxoXioFX4JT6NNfvOqx2S3cgryiNkUQghi0LIK8pTOxwhhLBakjSLKnFxcCFuShxxU+JwcXC55bmdm9SjiacruYUGNh6RFmKiYkIaeTB9UFsAIn+M53Rm2TX0QgghhKVJ0iyqRKNoCPYNJtg3GI1y6x8nRVEY2ckfkBINUTmP92lBzxae5BYamLbqgCwqFUIIUWMkaRY16kbSvDUhg4uyoEtUkFaj8M6YTrg76zh47jIfyi6TQgghaogkzaJGtfKtS7C/O3qjifWHU9UOR9gg/3ouvHFvewD+u/kEf8iGOVXi5uiGabYJ02wTbo5uaocjhBBWS5JmUSX5+nxGrxnN6DWjydfnl+s591xfEPjlztPVGZqwY3d39Oe+zo0wmuCJZTGkXpEFbEIIIaqXJM2iSgxGA2uPrGXtkbUYjOXb5rhvGx8ATmbksPd0VnWGJ+zYnBHB1HXWcTGnkNEf75I2dEIIIaqVJM2ixrVpUBcPFx0A3+5PVjkaYavqOjvw4tBAAM5fyuObPWdVjkgIIYQ9k6RZqGLm0HYA7DyZidEoM4Sich7s0ZR/3dEKgLk/HSUu+YrKEdme3KJcghcGE7wwmNyiXLXDEUIIqyVJs6gSB60Ds/vOZnbf2ThoHcr9vJGdGlHHSce5i3nslYVcogqeGdiGAYG+FOqNPL18P1fzi9QOyaaYTCaOZBzhSMYRKXERQohbkKRZVImj1pHIfpFE9ovEUetY7ue5OGoZfn1b7bUxsrubqDyNRuE/YzrSqJ4LZ7JyeVG22RZCCFENJGkWqhndNQCADYdTySmQbbVF5dVzdeTD8aHoNArrD6Xy9W6pbxZCCGFZkjQL1XRuUp/m3m7kFhrYID2bRRV1blK/eGHga1LfXG5OOidWj1rN6lGrcdI5qR2OEEJYLUmaRZXojXrWxK9hTfwa9MaKzRYrisKoLubZZinREJYwqXdzBrbzo9Bg5Mlv9pMt9c23pdPoGB08mtHBo9FpdGqHI4QQVkuSZlElBfoCxqwdw5i1YyjQF1T4+feGNkJRYM/piyRlycp9UTWKovCf0eb65qSLubyw9pDUNwshhLAISZqFqvzrudC7lTcAa/fLbLOoOg9XBz56sDMOWoWf49L4apfUNwshhKg6SZqF6m6UaKyLOS89m4VFdGpcr7gX+Ovrj3Do/GV1A7JihYZCIrdEErklkkJDodrhCCGE1ZKkWVSJoigE+QQR5BOEoiiVeo0hwQ2o66wj+XIe62VBoLCQR8ObMSTYjyKDice/iiH5kpT/lKbIUMScrXOYs3UORQapARdCiLJI0iyqxNXBlfgn44l/Mh5XB9dKvYazg5aghu4ALIg6ZsnwRC2mKArzR3XEu44jadn53LswGoPBqHZYQgghbJQkzcIq3BvaCIBzF/O4nCO3iIVleLg4FLehS79awDsbE1WOSAghhK2SpFlYhTFdA2jm5YoJ+O5AstrhCDsyqktjnr6jFQAfbTnBpiMXVI7Iumg1WkYFjWJU0Ci0Gq3a4QghhNWSpFlYBY1Gw6TezQFYvidJ2oQJi5oxuC0P92oKwDOrDnAy45rKEVkPZ50za0avYc3oNTjrnNUORwghrJYkzaJKcgpzUOYoKHMUcgpzqvRaI0Mb4eKgJTH9GvvOXrJQhEKYvTI8iO7NPLlaoOefX+2TjU+EEEJUiCTNwmq4Oztwd8eGAKzYk6RyNMLeOGg1fPRgZxp6OHMqI4fpqw5Ii0MhhBDlJkmzsCrje5hvof90OJXLubIgUFiWT10nPn6oC446DZuOpvP+b7Iw0GgyEp8eT3x6PEaTdBcRQoiySNIsrErHAA+CGrpTqDeybr8sCBSW17FxPd64JwSA939L5Nf4NJUjUldeUR4hi0IIWRRCXlGe2uEIIYTVkqRZVImLgwtxU+KImxKHi4NLlV9PURQe6NEEgBV7ZUGgqB6juzbmkbBmAExffZAT6bIwUAghxK1J0iyqRKNoCPYNJtg3GI1imR+nezr54+Kg5UT6Nf44IwsCRfWYNawdPZp7cq1Az+OyMFAIIcRtSNIsrE5dZwdGdPQHzLPNQlSHGwsD/T2cOZWZwzMrZWGgEEKIsknSLKzS+OslGusPp5J6ReosRdkMej3xO9ez76fFxO9cj0GvL/dzves48fEE88LA346l8+aGo9UYqXVyc3TDNNuEabYJN0c3tcMRQgirJUmzqJJ8fT6j14xm9JrR5OvzLfa6HQI8aOjhTKHeyOz/xVvsdYV9iY1aStbc1gRvHE/Xfc8RvHE8WXNbExu1tNyv0SGgHvPubQ/AZztOM68WJs5CCCFuT5JmUSUGo4G1R9ay9shaDEaDxV5XURS6NfMEYFtChtw2FzeJjVpKx+ip+CSmw2c58GY2fJaDd2I6HaOnVihxvr9LAO0a1AXg0+2nOHjucjVFLYQQwlZJ0iys1svD2uHsoCFfb2RrQoba4QgrYtDrabQzEiVBj7IyF5INUAQkG9CszIUEPf4751SoVOPbJ8No26AuRhM89tU+ki9LWZAQQog/SdIsrJavuzMPXd/s5MvoM+oGI6zKsT1R+GouomwvKPVxzY4C/DRZHNsTVe7XdHHUsW5KGIEN6pJxtYBJX/7B1VrQUSO3KJfghcEELwwmtyhX7XCEEMJqSdIsqsRB68DsvrOZ3Xc2DloHi7/+w72aoSiwNSGDkxnSS1eY5V26vvFNehklQdePF59XTnWcdHzxSDd86jpxLO0qTy+PRW+w713yTCYTRzKOcCTjiPRFF0KIW5CkWVSJo9aRyH6RRPaLxFHraPHXb+Llyh1tfQFYtuusxV9f2CaX+o3Mn/hqSz/h+vHi8yrAv54Ln0/sirODhq0JGcz5UZJJIYQQFk6ai4qKWLt2LTNmzGDChAlMmDCBGTNmsG7dOgoLCy05lKhFHglvBsCafedqxe1ycXuBPYaQbvTEGOFU6uPG3k5cMHoR2GNIpV6/Q0A93h8XiqLAst1n+WLnmSpEK4QQwh5YLGlOTEwkMDCQhx9+mJiYGAoLCyksLCQmJoYJEyYQFBREYmKipYYTtUjvVt609HEjp9DAupjzaocjrIBWpyM5PBLa6DCOc4UALTgCAVrz1210pITPRqvTVXqMIcENeGloOwBeX3+EjUcuWCZ4K+Okc2L1qNWsHrUaJ13pFyFCCCFAMVnovuOAAQOoX78+X375JXXq1Cnx2LVr13j00Ue5dOkSmzZtssRwdik7OxsPDw+uXLmCu7u72uGUi96o57uj3wFwb7t70Wkqn6TcyrJdZ3jlf/E093bjt+l90WiUahlH2JbYqKU02hmJr+Zi8bELRi9SwmcTOmRilV/fZDIx6/s4lu9JwsVBy5rJvQhp5FHl1xVCCFFzLJVfWWymedeuXcydO/emhBmgTp06zJ49m+joaEsNd0sLFy6kefPmODs706VLF7Zv317muampqYwfP562bdui0WiYNm1aqeetW7eOoKAgnJycCAoK4rvvvqvSuPaiQF/AmLVjGLN2DAX60jsZWMJ9nQOo66TjdGYO2xKl/ZwwCx0yEa9XE4kftJx9XRcQP2g53q8mWCRhBnO/8Dkjgolo7U1ekYFJS/+QHSqFEKKWsljS7O3tzeHDh8t8PD4+Hi8vL0sNV6ZVq1Yxbdo0Zs2aRWxsLBEREQwdOpSkpKRSzy8oKMDHx4dZs2bRsWPHUs/ZtWsXY8eOZcKECRw8eJAJEyYwZswY9uzZU+lxRcW4OekY1TUAgKXSfk78hVanIzh8GF2HP05w+LAqlWSUxkGr4aMHO9PGrw4XsguY9OU+cgrK3/9ZCCGEfbBYeca7777LrFmzePrpp+nfvz++vuaOB+np6WzevJmFCxfyxhtv8O9//9sSw5WpR48edO7cmUWLFhUfa9euHffccw/z5s275XP79etHp06deO+990ocHzt2LNnZ2fz888/Fx+68807q16/PihUrqjzuDbZYnpFTmEOdeea7C9dmXsPN0a3axjqTmUP//2zBZILfpvelpe/NdzWEqC7nLuZy78KdZF4rpH9bHxZP6IqDzvYbEBUaCnlz+5sAvBTxUrV0wRFCCDVZXXnGM888w2effcaWLVsYMWIE3bp1o1u3bowYMYItW7awePHiak+Ybyw8HDx4cInjgwcPrlJpyK5du256zSFDhhS/ZmXHLSgoIDs7u8SHrVEUhSCfIIJ8glCU6q0zbubtRpcm9QGYujK2WscS4u8ae7ry6cNdcdJp2Hw8gxEf7bCLVnRFhiLmbJ3DnK1zKDJIdxohhCiLRadJxo8fz969e8nNzSU5OZnk5GRyc3PZu3cv48ePt+RQpcrMzMRgMODn51fiuJ+fH2lpaZV+3bS0tFu+ZmXHnTdvHh4eHsUfjRs3rnSManF1cCX+yXjin4zH1cG12sfr09YHgPiUbNKv5lf7eEL8VWiT+kzq3QyAo6lXeWPDUXUDEkIIUWOq5d6ig4MDDRs2pGHDhjg4WH6XuNv5+4ynyWSq8ixoeV6zouPOnDmTK1euFH+cO3euSjHWBk/1bYmXm/n28VppPydU8Pyd7Rga0gCAz7afZuVeWbcghBC1QY0V5F26dImvvvqqWsfw9vZGq9XeNLubnp5+0yxwRTRo0OCWr1nZcZ2cnHB3dy/xIW5Nq9Uw8y5z79wlO89QoC9jG2UhqtGih7rwVP+WALz03WF+iav8nSy1aTVaRgWNYlTQKLSaMnZYFEIIUXNJc1JSEo8++mi1juHo6EiXLl3YuHFjieMbN24kLCys0q/bq1evm17z119/LX7N6hpXlG5ER38auDuTcbWA/x1IUTscUUvNGNyWcd0aYzSZa+x3ncxSO6RKcdY5s2b0GtaMXoOzzlntcIQQwmpZrDfT7VqrpaTUTHIzffp0JkyYQNeuXenVqxeLFy8mKSmJyZMnA+aSiOTk5BKz3gcOHADMm7BkZGRw4MABHB0dCQoKAuDf//43ffr04a233mLkyJH873//Y9OmTezYsaPc49qrmuyecYOjTsOj4c2Y9/MxPt12ilGdA2SzE1HjFEXh9XtCuJRbSFT8Bf751T5WPt5TNj8RQgg7ZbGkuVmzZres37VEXXF5jB07lqysLObOnUtqaiohISFs2LCBpk2bAubNTP6e4IeGhhZ/HhMTw/Lly2natClnzpwBICwsjJUrV/Lyyy/zyiuv0LJlS1atWkWPHj3KPa6wrAd6NOHD30+QmH6NLQnp3BFY+fIbISpLp9Xw/rhQJn6xlz2nL/LIkr2snRxGM+/qv3gUQghRsyzWp9nLy4s333yTfv36lfr40aNHuf/++zEYpAa1LNKnuWLe3HCUxdtO0aO5J6ue6FVj4wrxd9n5RYz7ZDdHUrNp4unK2sm98HW3jVIHo8nI0QxzF5B2Pu3QKLbfe1oIIf7K6vo0d+nShYyMDNq2bVvqR/Pmze2ip6mwHo+GN0OnUdhz+iIHz11WOxxRi7k7O7D0H91p6uVK0sVcJi75gyt5ttHzOK8oj5BFIYQsCiGvSLYIF0KIslgsaZ4yZQrNmjUr8/EmTZqwZMkSSw0nrISLgwtxU+KImxKHi4NLjY7d0MOFEZ38AVi87VSNji3E3/nUdWLZP3rgU9eJo6nZ/POrfeQXyZ01IYSwFxYrzxBVZ4vlGWo7lpbNne9tR6PAlhn9aeJV/RusCHErR1KyGfvJLq4W6BkU5MeiBzuj01pvyYOaJVZCCFETrK48A6CoqIi1a9cyY8YMJkyYwIQJE5gxYwbr1q2jsLDQkkMJAUBgA3f6tvHBaILPdshss1BfkL87n07siqNOw8YjF3jpu8NSmiaEEHbAYklzYmIigYGBPPzww8TExFBYWEhhYSExMTFMmDCBoKAgEhMTLTWcEMX+GdEcgK93n+V05jWVoxECerbw4sMHQtEosHrfeUZ9HK12SGVyc3TDNNuEabZJZpmFEOIWLFaeMWDAAOrXr8+XX35JnTp1Sjx27do1Hn30US5dusSmTZssMZxdssXyjHx9PhO+mwDAsnuXqbI5gtFopN2rURTojdJJQ1iV+b8cY+GWkwCM6dqY+aM6qByREELUPlZXnrFr1y7mzp17U8IMUKdOHWbPnk10tPXOtojKMRgNrD2ylrVH1mIwqrPoSaPR8EhYMwDiUq6QnW8bXQtsgUGvJ37nevb9tJj4nesx6PVqh2RTnr8zkP5tfQBYve8cH20+oXJEQgghKstiSbO3tzeHDx8u8/H4+Hi8vLwsNZwQJbxwZyBt/OqQU2Bg6c4zaodjF2KjlpI1tzXBG8fTdd9zBG8cT9bc1sRGLVU7NJuy5NHuPDekLQALoo7zqXR6EUIIm2SxHQGfeeYZHn30UWJiYujfvz++vr4ApKens3nzZhYuXMgbb7xhqeGEKEGjUXiqfyv+vfIAn+88zaO9m1PHyWI/3rVObNRSOkZPRUnUw/YCSDeArxbvCD3eylRigdAhE9UO02Y81b8VeoOJdzcl8MaGo2g1Cv/o3VztsADILcql26fdAPjjn3/g6iAdaIQQojQWTZr9/Px47733ePfdd4t3/tNqtYSGhrJ48WLGjx9vqeGElXDQOjC77+ziz9U0vIM/729K5FRmDst2nWVKv5aqxmOrDHo9jXZGoiTqUVbm/vlAsgHNylyM41zxN83BMOBBtDq5MCmvfw9sjd5o5MPfTzD3pyM4aBUm9GqmdliYTCaOZBwp/lwIIUTpqqVPc1FREZmZmYC5bMPBQd1kylbY4kJAa7Mu5jzPrjmIp5sjO17oj6ujJHUVFb9zPcEbx8NnOZBcSp16gBYmuRE/aDnB4cNqPkAbZjKZeOuX43y81bw4cN597XmgexNVY5I+zUIIe2d1CwH/ysHBgYYNG9KwYUNJmEWNGtnJnyaerlzMKWT5niS1w7FJeZeSzZ+kl7Gw8/rx4vNEuSmKwgt3tmXS9dKMl747zJp951SOSgghRHlYNGk2Go3ExcWRkpJy02NFRUVs27bNksMJcROdVsNT/c1lGZ9sOyXbGFeCS/1G5k98taWfcP148XmiQhRF4eVh7XgkrBkmEzy/7hDfxZ5XLR4nnROrR61m9ajVOOmcVItDCCGsncWS5rNnz9K+fXs6dOhA48aNGTFiBFlZWcWPX7x4kf79+1tqOGEl9EY9a+LXsCZ+DXqjdbQjuzc0gEb1XMi4WsDKvTLbXFGBPYaQbvTEGFF6AmXs7cQFoxeBPYbUcGT2Q1EUZt8dxIM9mmAywbOrD/LjwZsnG2qCTqNjdPBoRgePRqeRciYhhCiLxZLm559/noCAAJKSkjh48CAFBQWEh4eXmHWWRSb2p0BfwJi1YxizdgwF+gK1wwHAUacpXgT48dZTFOhltrkitDodyeGR0EaHcZyruYbZEQjQmr9uoyMlfLYsAqwiRVF4bWQIY7s2xmiCaasO8PPhVLXDEkIIUQaLJc1bt25l/vz5BAQEEBISwi+//EJERAQREREkJZln+xRFsdRwQtzS6K4BNHB3Ji07nzX71Lv1batCh0zkYNgHZLb2hUluMNMdJrmR0dqPg2EfSLs5C9FoFObd1577OjfCYDTxrxWxbDxyQe2whBBClMJiSXNubi5OTn/ezlUUhU8//ZTBgwfTp08fTp48aamhhLgtJ52WJ/q2AGDez0fJLbSO0hFbEjpkIl6vJhI/aDn7ui4gftByvF9NkITZwjQahQWjOjKykz96o4knlu3jg98Sa2z8QkMhkVsiidwSSaGhsMbGFUIIW2OxpLlt27bs27fvpuOLFi3irrvuYvjw4ZYaSlgRRVEI8gkiyCfI6u4kjOoSgEaBnAIDr3wfp3Y4Nkmr0xEcPoyuwx8nOHyYlGRUE61G4T+jO9K1WX2MJnhnYwJLo8/UyNhFhiLmbJ3DnK1zKDLIFvRCCFEWiyXN9913H8uXLy/1sYULFzJ27FipabZDrg6uxD8ZT/yT8Va3k1hdZwcGtPMDYMvxDOmkIayaTqth6aPd8XM337Gb82M838dKWz8hhLAWFkuaZ86cyYYNG8p8fNGiRRiNRksNJ0S5fDCuE/4ezmTlFLJs11m1wxHiltycdGx7rj/3hTbCaIJnVh+QfuNCCGElqmVzEyGshYujjmkD2wCwcMsJrubL7Wdh3ZwctLw9uiMP92qKyWTeAOWz7aeqbTytRsuooFGMChqFVlNGb24hhBCSNAv7d1/nRrTwceNSbhGfbT+tdjhC3JZGozBnRHBx68TX1x/l/U2J1VLi5qxzZs3oNawZvQZnnbPFX18IIeyFJM2iSnIKc1DmKChzFHIKc9QOp1Q6rYZnB7UF4LPtp7iYIx0ChPUzb7kdyHNDzD+7725KYN7Px2RtiBBCqESSZlErDA1pQEgjd3IKDSzcfELtcIQot6f6t+LV4UEALN52ipe/j8NolMRZCCFqWrUmzVqttnhjEyHUpNEozBhsnrH7avdZUi7nqRyREOX3j97Neev+9igKfLMniRlrDqI3WGZhtdFkJD49nvj0eIwmWawthBBlqdakWW4jCmvSt40P3Zt7Uqg38uHvNbd5hBCWMLZbE94fF4pOo/BtbDJPL4+1yBbxeUV5hCwKIWRRCHlFcjEphBBlkfIMUSUuDi7ETYkjbkocLg4uaodzS4qi8Pz1+tDV+85zKuOayhEJUTEjOvqz6KEuOGo1/BKfxuNfxZBXKP3HhRCiJkjSLKpEo2gI9g0m2DcYjWL9P05dm3lyR6AvBqOJdzYmqB2OEBU2KMiPLx7phouDlq0JGTyyZC/XCmSbeCGEqG7Wn+UIYWE3apt/OpTKL3GpKkcjRMX1bu3NskndqeukY8/pi9z53jaSsnLVDksIIeyaJM2i1gnyd6eNXx0AXvouTuVohKicrs08WfF4T1wdtZy/lMfAd7dyKrPiJUdujm6YZpswzTbh5uhWDZEKIYR9kKRZVEm+Pp/Ra0Yzes1o8vX5aodTbjdaeF3MKeT3oxdUjkaIyglp5MF/RndEo0Ch3si4T3YTn3JF7bCEEMIuSdIsqsRgNLD2yFrWHlmLwWg7C5J6t/bh4Z5NAZj38zGLte8SoqYNbd+QDVMjaONXh/SrBYz9ZDfbEzPUDksIIexOtSbNs2bNol69etU5hBCV9uyQttR3dSAx/Ror9ko/cWG7Ahu6s2ZyGD1beHKtQM+jS/5gXcx5tcMSQgi7Uq1J82uvvYa7u3t1DiFEpXm4OPDMoDYAvLMxgSt5RSpHJETlebg4sPQf3bm7oz96o4ln1xzkv78n3rZffm5RLsELgwleGExukSwmFEKIskh5hqgSB60Ds/vOZnbf2ThoHdQOp8LGd29CK986XMot4r+y4YmwcU46Le+P7cQTfVsA8PavCbz0Xdwty49MJhNHMo5wJOOIbEglhBC3oJjkt6TVyM7OxsPDgytXrsgMfQ3afDydR5f8gYNWYeMzfWnmLR0ErJ1Br+fYnijyLiXjUr8RgT2GoNXp1A7LqiyNPkPkj/GYTHBHoC//HR+Kq+PN/0Y5hTnUmWfuJnNt5jXpoCGEsDuWyq9kplnUev3b+tKnjQ9FBhPzfj6qdjjiNmKjlpI1tzXBG8fTdd9zBG8cT9bc1sRGLVU7NKsyMawZix7sgpNOw+/H0nlg8W4yrxWoHZYQQtgsiybNcXFxfPXVV5w9exaAY8eOMXXqVJ5++mk2btxoyaGEsKiXh7VDq1GIir/ArpNZaocjyhAbtZSO0VPxSUyHz3LgzWz4LAfvxHQ6Rk+VxPlv7gxpwPJ/9qS+qwMHz1/hvoXRnM7MKXGOk86J1aNWs3rUapx0TipFKoQQ1s9iSfO6desIDQ1l+vTptG/fnk2bNhEWFsaxY8c4efIkd911F8uXL7fUcMJK6I161sSvYU38GvRG293Kt41fXR7o3hiA19cfwWCUqiVrY9DrabQzEiVBj7IyF5INUAQkG9CszIUEPf4752DQ2+7PYXXo0rQ+66aE0djThaSLudy3cCf7ky4VP67T6BgdPJrRwaPRaaTERQghymKxpPmNN97gtddeIzMzk88//5xRo0YxY8YMfv31V37++WcWLFjA/PnzLTWcsBIF+gLGrB3DmLVjKNDb9q3fZwa2oa6zjviUbNbtl3Zd1ubYnih8NRdRtpf+c6bZUYCfJotje6JqODLr18KnDt9OCadDgAeXcot4YPFufo1PUzssIYSwKRZLmhMSEhg3bhwAo0ePJjc3l7vvvrv48ZEjR3LixAlLDSeExXnVceJfd7QC4M0NR8m8atsXAfYm71Ky+ZP0MjbRuX68+DxRgk9dJ1Y+3pM7An0p0BuZ/HUMr/5PtpEXQojysljS7OHhQWpqKgAXLlxAr9eTlvbnTEZqaioeHh6WGk6IajExrBnuzjou5xYx+esYtcMRf+FSv5H5E19t6SdcP158nriJq6OOxRO68ED3xhhN8NWus9z94WZe/X02kVsiKTQUqh2iEEJYLYslzXfffTeTJk1i/vz53HfffTzwwAM8++yz/Pbbb2zevJmpU6cycOBASw0nrISiKAT5BBHkE4SiKGqHU2VOOi0PdG8CwP6kS5zMuKZyROKGwB5DSDd6YowofbGasbcTF4xeBPYYUsOR2RadVsOb97anVwsvAA4mX+S17XOZs3UORQbZ4EcIIcpisaT57bffJiwsjGXLlhESEsIXX3zBgw8+yF133cWAAQNwc3PjrbfestRwwkq4OrgS/2Q88U/G4+rgqnY4FvHCnW3p3qw+RhO88n2cbPhgJbQ6HcnhkdBGh3GcKwRowREI0Jq/bqMjJXy29GsuB0VRWPF4T166KxAXhz9n7k9mXFUxKiGEsG7VvrlJfn4+RUVF1K1btzqHsQuyuUlJam5gkZSVy6B3t1KgN/L+uE6M7CS3/K1FbNRSGu2MxFdzsfjYBaMXKeGzCR0yUcXIbNMfZ1Po/qX557ud8Xs+HNeTAe38VI5KCCEsx1L5lewIaEUkaf5TaYlRutGT5PDIGkuM/vt7Im//moB3HSd+n9EXd2fb2ybcXsmOgJaTr89n7JoH2X/2EprL/0KjOPLckLZM6dvSLkquhBDCKpPm3NxcVqxYwc6dO0lNTUWj0dC8eXNGjhzJoEGDLDWM3ZKk2ezGBhZKgt7cXizdAL5acy1rGx0Hwz6okcS5QG9g6PvbOZWRw8ReTZkzMqTaxxRCLYV6I3N+jOebPUkAjOjoz1v3d8DFsYyFl0IIYSOsbhvt48ePExgYyKxZs9i0aRNRUVEoikJMTAx33XUX9913H4WFsjLb3uQU5qDMUVDmKOQU5tz+CbdhTRtYOOm0vHY9UV62+yyHz1+p9jGFUIujTsMb97bntXtC0GkUfjiYwphPdpF6JU/t0IQQwipYLGl++umnGTFiBKmpqSQlJTF//nz0ej27du3i+PHjHDp0iDlz5lhqOGGnrG0Di/BW3ozo6I/RBC9/f1h2ChR2b0LPpnz9WA883Rw5nHyFuz/cSczZi7d/ohBC2DmLJc3R0dFMmzatuAZu2rRp/P7772RmZtKiRQvee+89li1bZqnhhJ2yxg0sXh7WjrpOOg6ev8KKvUk1Nq4QNcFoMhKfHk98ejxGkxGAni28+N9T4QQ2qEvmtQIeWLyH1X+cUzlSIYRQl8WSZi8vL7Kysoq/vnTpEnq9HhcXFwCCg4NJT0+31HC3tHDhQpo3b46zszNdunRh+/bttzx/69atdOnSBWdnZ1q0aMHHH39c4vF+/fqhKMpNH8OGDSs+JzIy8qbHGzRoUC3vz55Z4wYWvu7OPDu4DQDzfzlGhuwUKOxIXlEeIYtCCFkUQl7Rn6UYjT1dWTcljKEhDSg0GHl+3SHm/BiP3mBUMVohhFCPxZLmESNGMGXKFDZt2sSOHTt48MEHCQ8Px83NDYATJ07g7+9vqeHKtGrVKqZNm8asWbOIjY0lIiKCoUOHkpRU+gzh6dOnueuuu4iIiCA2NpaXXnqJqVOnsm7duuJzvv32W1JTU4s/4uLi0Gq1jB49usRrBQcHlzjv8OHD1fperYGLgwtxU+KImxKHi4NLlV/PWjewmNCrGcH+7mTn65n389EaHVsItbg56fhofGemDWwNwJKdZ3hkyR9czpX1KUKI2sdi3TOuXr3KpEmT+O677zAYDPTo0YOvv/6ali1bAhAVFcWlS5cYN26cJYYrU48ePejcuTOLFi0qPtauXTvuuece5s2bd9P5L7zwAj/88ANHj/6ZCE2ePJmDBw+ya9euUsd47733ePXVV0lNTS2+KIiMjOT777/nwIEDlY7dlrtn/H0RoIuDCxrlz2uyfH0+BuOfJRcOWgcctY7FX+uNegr05hncg5u+ocOeGbgmGNDs+LN7xtUIR2it43CPt+k48MEqjQHmDR7+viHLrd7HgXOXGblwMyaTkXfHduTO4IYWH6Mm3oeMIWP8dYycwhzqzKsDwLWZ13BzdKM0v8SlMn31QXILDTTxdOX1e0Lo08an1HOFEMKaWCq/slhj07p167J69Wry8/PR6/XUqVOnxONDhlT/zGBhYSExMTG8+OKLJY4PHjyY6OjoUp+za9cuBg8eXOLYkCFD+PzzzykqKsLB4ebevJ9//jnjxo0rTphvSExMxN/fHycnJ3r06MGbb75JixYtyoy3oKCAgoI//xBmZ2ff9j1aqxt/dG+ImxJHsG9w8dcTvpvA2iNri7+e3Xc2kf0ii7/+7uh3jFk7pvjrFm7+7GrtiG/bPxcguSvX/33+eAL+eKLKYwT5BBH/ZHy530enxvVw9F7IiWubGPUD8IPlx6iJ9yFjyBiljXE7d4Y0pKmXG//8ah9JF3N5+Iu9TO7bgheHtiv3awghhC2zWHnGDc7OzjclzDUlMzMTg8GAn1/J3az8/PxIS0sr9TlpaWmlnq/X68nMzLzp/L179xIXF8djjz1W4niPHj346quviIqK4tNPPyUtLY2wsLASdd5/N2/ePDw8PIo/GjduXN63avec69TD69VE4gctZ1/XBcQPWq52SAC09lPnZ1uI6uLm6IZptgnTbFOZs8w3tGvozrdTwqjrbJ5v+XjrKWb/L44CfRkLd4UQwo7Y1eYmKSkpNGrUiOjoaHr16lV8/I033mDZsmUcO3bspue0adOGRx99lJkzZxYf27lzJ7179yY1NfWmxXxPPPEE0dHRt61XzsnJoWXLljz//PNMnz691HNKm2lu3LhxrS/PAOu+xf3h78f58PcTaDUK306OILTJn7eobel9yBgyxl/HqIi8Qj3TVh0gKv4CAB0CPPhofGcae7re5plCCFHzrK484/jx4wwaNIjCwkIcHR05f/48d911FzExMXzyySfcfffdrFy5EkfHyv2SLg9vb2+0Wu1Ns8rp6ek3zSbf0KBBg1LP1+l0eHl5lTiem5vLypUrmTt37m1jcXNzo3379iQmJpZ5jpOTE05OpS94szW3m6Fy1jnf8nGdRofO8dY/jtYyxnODO3Imw8D6w6nM/PYoPzzthaNOY9ExbkXGkDGqY4yKcHHU8cmErvx+7ALTVx/k0Pkr3PXBdt4e3ZEhwdI1SAhhn+xqcxNHR0e6dOnCxo0bSxzfuHEjYWFhpT6nV69eN53/66+/0rVr15vqmVevXk1BQQEPPfTQbWMpKCjg6NGjNGzYsILvQtiCOSOD8XRz5FjaVT7afELtcIRQxR2BfqyfGkHnJvW4mq/niWUxvPbTEQr10pZOCGF/LFae4ebmxsGDB2nVqhUAer0eV1dXUlJS8Pb25qeffuLJJ58ss/WbpaxatYoJEybw8ccf06tXLxYvXsynn35KfHw8TZs2ZebMmSQnJ/PVV18B5pZzISEhPPHEE/zzn/9k165dTJ48mRUrVnD//feXeO2IiAgaNWrEypUrbxp3xowZ3H333TRp0oT09HRef/11tm7dyuHDh2natGm5Yrfl7hm10Y8HU/jXilh0GoX/PR1OsL+H2iEJoYoig5H5vxzj0+2nAfOi2f+ODyWgvpRrCCHUZ6n8yu42Nxk7dizvvfcec+fOpVOnTmzbto0NGzYUJ643ZsJvaN68ORs2bGDLli106tSJ1157jQ8++OCmhDkhIYEdO3YwadKkUsc9f/48DzzwAG3btuW+++7D0dGR3bt3lzthFrZneIeG3BncAL3RxHNrDlEkmz6IWspBq2HWsCAWT+iCu7OOA+cuM+yDHfx29ILaoQkhhMVYbKb56aefJjo6mvnz5+Ps7MzcuXPJy8sr3o1v48aNPPHEE5w6dcoSw9klmWm2PRlXCxj07lYu5xYxfVAbpg5orXZIQqjq3MVcnl6+n4PnrwDwRJ8WzBjSFgetxZs1CSFEuVjdTPO8efNo1aoVQ4cOpU+fPly9epUvv/yy+HGj0cibb75pqeGEsAo+dZ2YM8LcC/fD3xM5lma7vbaFsITGnq6smRzGI2HNAPhk2ykeWLyb1Ct5t36iEEJYOYu2nAPK3NxE3J7MNNsmk8nE48ti2HjkAiGN3PnuyXCZVbNTBr2eY3uiyLuUjEv9RgT2GIJWZ7EmRHbn58OpPL/2EFcL9Hi6OfLOmI70a+urdlhCiFrG6maabyhrc5NLly4VL74Twp4oisIb94Tg4eJAXHI2i7dJCZI9io1aStbc1gRvHE/Xfc8RvHE8WXNbExu1VO3QrNbQ9g35aWpvQhq5czGnkEeW/MGCqGPopf5fCGGDamw6LCkpiUcffbSmhhOiRvm6OzP77iAA3t+UyKHzl9UNSFhUbNRSOkZPxScxHT7LgTez4bMcvBPT6Rg9VRLnW2jq5cbayWFM6GleFP3R5pM8+Nkezmbm3OaZQghhXSxWnnG7VnLx8fEMHz4cg0G2Wy2LlGfYNpPJxCNL/mBrQgaujlpiXh6Iy202pBDWz6DXkzW3NT6J6Sgrc2963DjOlYzWfni/miClGrfx48EUXlx3iJxCAxoFnh3chqf6y+JZIUT1srodAZs1a4aiKGU+bjKZbvm4ELZOURSeGdiarQkZ5BYamPntYd4bF6p2WKKKju2JIlhzEbYXlPq4ZkcBfm2ziN8TRXD4sBqLyxbrq+/u6E+wvzvDP9xBbqGBBVEJpF0pYOZdgbjKBaYQwspZ7LdU/fr1efPNN+nXr1+pjx89evSm3sdC2JtOTerzz4jmfLr9NP87mMK47k3o2cLr9k8UVivvUrL5k/Qy7pJdP158Xg2IjVpKo52R5mT+RhhRniSHRxI6ZGKNxVEZLXzqEP3iHTy65A9iz11m2e6z7DiRyTtjOhLapL7a4QkhRJksljR36dKFjIwM2rZtW+rj+fn5WLhRhxBWadawIC7nFrEm5jzPrDrAz/+OoJ6rY6VfzxZnFO2JS/1G5k98tZBcSuLsqy15XjW7UV+tJOrNs9/pBvDV4h2hx1uZSixYfeJcz9WR754KZ0diJjPWHOR0Zg6jPt7F0/1b8fQdraT7jBDCKlnsN9OUKVNo1qxZmY83adKEJUuWWGo4Iaxa5Ihgmnu7kXolnxfXHa70BaN0bFBfYI8hpBs9MUY4lfq4sbcTF4xeBPYYUu2xGPR6Gu2MREnQm+urkw1QBCQb0KzMhQQ9/jvnYNDrqz0WS+jd2puoaX0Y0dEfg9HE+78lcv+iaE5mXFM7NCGEuInFkuZ7772Xhx56qMzH69evz8SJ1j37IYSluDnp+GBcKA5ahV/i01j5x7kKv4Z0bLAOWp2O5PBIaKPDOM4VArTgCARozV+30ZESPrtGZv+P7YnCV3MR5Vb11Zosju2JqvZYLMXD1YEPHgjlgwdCcXfWcej8FYZ9sJ2vdp2Ru5NCCKsi98CEqCbtAzyYMdhcrjTnx3hOpJd/9szeZhRtXeiQiRwM+4DM1r4wyQ1musMkNzJa+3Ew7IMaK4ewxvpqSxnR0Z+oZ/oQ0dqb/CIjr/4vnolL/uBCdr7aoQkhBFDNSfPp06d55JFHqnMIIazaPyNa0LuVOQmYuiKWAn35Wi7a44yirQsdMhGvVxOJH7ScfV0XED9oOd6vJtRo/XCJ+urS1HB9taU19HBh6aPdibw7CCedhm0JGQx+dxs/HUpROzQhhKiepDkpKYl//vOfBAYGsmzZsuoYQgiboNEovDOmI55ujhxJzWb+L8fL9Tx7nlG0ZVqdjuDwYXQd/jjB4cNqfEGmNdVXVxeNRuGR8OasnxpB+0YeXMkr4unlsUxbGcuVvCK1wxNC1GIVTpp37NhB//79cXd3x9PTk5EjR3L8uDkRyM3NZfr06bRp04bPP/8cHx8fPvjgA4sHLYQt8XV3Zv79HQD4fMdpthxPv+1z7H1G0VIMej3xO9ez76fFxO9cb/flKtZUX13dWvnW4dsnw5g6oDVajcL3B1K4871t7DyRqXZoQohaqkI7AsbExBAeHk5hYWGJ4w0aNGDbtm3cc889HDlyBH9/f1544QUef/xxnJxKnxERN5MdAe3b7P/FsXTXWbzrOPLzv/vgU7fs/xs3dqHzTkw31zD/jexC92evYt+/9io22kav4qoq7b1fMHqREj7bLt/7/qRLTF91gDNZ5v8Lj4Y344U7A3F2KOOiUggh/sJS+VWFkuaxY8eyZs0a5s2bx6RJkwD4+OOPefXVV/Hz8yMjI4OXXnqJl156CWdn50oHVVtJ0mzf8osMjPzvTo5fuEq/Nj58PrEr2lv0o73RPYMEPZodf/bjNfZ2gja6Gl2AZm2KexUn6M113zf+bSJqz79NbevfnVuo5431R/lmTxJgnol+d0xH2gfUUzcwIYTVUyVpDggIIDAwkE2bNpU43r9/f7Zt28aCBQuYPn16pYOp7SRptn/H064y4r87KNAbuSukAQsf6nLL82vbjGJ53JiF90lMN3cW+RuZhbdvm4+l8/y6Q2RcLUDB3Ot58YQuuMg23EKIMlgqv6pQTXN6ejpdutz8R75bt24A0odZiNto26AudwY3AGBDXBqbj1245fnW0LHB2khnkdqtf6AvUdP60L25JyZge2ImQ9/fTmzSJbVDE0LYuQolzXq9Hjc3t5uO3zjm5eVlmaiEsGPvju1IU09XAF5Yd5j0q7fuQ6t2xwZrI51FhKebIyv/2YPx3Rvj4qDhTFYu9y2KJvKHeK4V2PdiUCGEemRzEyFqmEajYf2/I2jlW4f0qwU8/U0sRQaj2mHZDOksIsD8/+jN+zqw44U7uC+0ESYTfBl9hsHvbOX329zBEUKIyqhQTbNGo6FVq1a0atWqxPETJ05w8uRJhgy5uTeooiisX7++6pHWAlLTXLuczLjGyP/u5FqBnn+EN+fVu4PUDskmSGcRUZptCRnM+v4w5y7mATC8Q0Nm3x18yy41QojaQZWFgBpNxSemFUXBYCjfLmi1nSTNtU9UfBpPLIsB4P1xnRjZSWZHy0M6i4jS5BbqeW9TIp9tP4XRBB4uDsy6qx2juwagKIra4QkhVKJK0nz27NlKDdK0adNKPa+2kaS5dpr/yzEWbjmJi4OW754KI7CBfO/LQzqLiLLEJV/hhXWHiE/JBqBXCy/evK89zb1vXpMjhLB/qiTNonpJ0mw9DHo9R3Zt4Nqx3wGFOoH9Cep1V7Xc7jcYTTyyZC/bEzNp6uXKD0/3xsPFweLj2KPa1qtYlJ/eYOSLnad5Z2MC+UVGHHUa/j2gNY/3aYHDLfqjCyHsjyTNdkiSZusQG7WU5jteoh5XQfvnLd3Lhjqc7v1mtcxiXswp5O4Pd5B8OY8Bgb58+nBXNBq5nSxEVSVl5TLr+8NsTzRvvx3YoC7/d38HOjWup25gQogao1rSfPHiRfLz82nYsGFxjVh0dDQ7duy46dwOHTpw5513Vjq42kaSZvUV7zSHCSVBD9sLi+tlTX0cobUDB6qpXvbw+Svc/3E0hXoj0we1YeqA1hYfQ4jayGQy8V1sMq/9dIRLuUUoCjwS1oxnB7eljpPcmRDC3qmSNF+8eJEWLVrQpUsXfvvtt+Ljc+bMYe7cufz9pTw8PDh58iSenp6VDrA2kaRZXQa9nsy5rfAtuohyRg8r8246x/SAC+mtGlRbZ4bVf5zj+XWHUBT44pFu9G/rW2asUpYgRMVkXSvgjfVH+TbW3MPb38OZ1+8N4Y5AP5UjE0JUJ1V2BFy2bBlXr15l/vz5pT6+ZMmS4o933nmHK1eu8PXXX1c6uNoqv0i6jajh2J4o/DSXUJwU8wxzKZTthdW629yYbo15oHsTTCaYtvIASVk3t1SLjVpK1tzWBG8cT9d9zxG8cTxZc1sTG7W0WmISwl541XHinbGd+Oof3Wns6ULKlXz+8eU+nl6+n4yrpe8wKYQQN1RoamrDhg20a9eu1K204eZttJcvX8769euZOnVq5SOshb7Zc5Zn7qqvdhi1Tokd5FTcbS5yRBBHUrM5eO4yd/93B1tm9KO+myPwl/KRRD1s/7PVmneEHm9lKrEgnSOEuI0+bXyImtanuD3dT4dS2XT0And38Of/7muPVhYKCiFKUaHfDIcPHyYsLKzc53fq1InDhw9XOKja7tuY82qHUCuV2EFOxd3mnHRaPhofikaBK3lF3LNwJ0ajCYNeT6OdkSgJepSVuZBsgCIg2WDe5CNBj//OORj0so2wELfj6qjjpbva8b+netPGrw75RUbWxJxn4Ltb2Z90Se3whBBWqEJJc1ZWFr6+N9dY9unTh5deeumm476+vly8ePGm4+LW0q4WUKCXEo2aFthjCBeM9TEVmCDCsdRzTBGOXDB6Edjj5t0vLSmgviuzhrVDAc5m5TI/6jjH9kThq7mIsv1vt5EVoKkWTYoeP00WR3ZtqNbYhLAn7QM8+P7JcO4I9EGrUTidmct9C6N5ZtUBLmTnqx2eEMKKVKg8w9nZmdzcm2ss+/fvT//+/W86npubi6Nj6cmHKFtBkZFtCZkMCpLFKTVJq9OREj4Hn+ip0EaHMs4Fdvyle0aEuXtGSths/Gpg0d2k3i2o7+rA9NWH+HjrSUytLhEMJUtHAnUw2Bnq/3n92/jXycTmXqqVZRqyQFJUhquTji8e6c6F7Dz+82sCa2LO811sMlHxaTzVvxWTejfH2aGMu09CiFqjQn9NAgICKlRucejQIRo1km2BK+PHgymSNKsgdMhEYsHcp7nVVWj75yYjlw11OBNW+T7NlUno7uvcmKSLeby3KZFPT9YnXNeePr67zaUZgToY4wIJeliXV5zce0To6aiZSozBiLOHb61JIG/sEBj8lx0C06M8SQ6PrJUXEKLi/NxdmD+qIw/1bErkD/HsT7rMgqjjrPrjHLOGtWNwkJ9sxy1ELVahlnOTJ09myZIlHD9+nGbNmt3y3FOnTtG2bVv+8Y9/8Mknn1Q1zlrhRkuUxtNW41anLjGvDMTV0X6THGtm6R0BS9vyOd1YvoTOZDLx7OqDfBubjBt5rE15mXZfH4d/1TEnyqW1xhvnirGVA1rtn/+9yzueLSpeIJmgN5evXL+AMEY4QRsdB6upt7awXyaTie8PJPN/Px/jQra5JKp3K29m3x1Ea7+6KkcnhKgIVfo0Hzx4kNDQULp3787PP/9M/fqld3i4ePEid955JzExMezbt4/Q0NBKB1ib3Pim9przIym5Ch8+EMrdHf3VDktUkSUSugK9gYc/38ue0xdpSCbfZc6iQcBV+CzHPOv8dwFamOQG6/PgYJFdJ5AGvZ6sua3xSUw3L5D8G+M4VzJa+1Vbb21h33IK9CzccoJPt5+mUG9Eq1GY0LMpzwxsg4erbHcvhC1QpU9zx44dmT59Onv37iUoKIg5c+awdetWEhMTSUxMZMuWLcyePZvg4GD27dvHv//9b0mYK2FoSAPAXKIhbJulOl446bR8MqELLbzdSMWbf/jMJNfkdNvWeOSb7L7DRpkLJK/T7Cio1t7awr65Oel4bkggm57py+AgPwxGE19Gn6Hf25v5evdZDMYKbaorhLBhFW5GuWDBAl544QUyMzOZO3cud9xxB4GBgQQGBjJgwABee+01MjIymDFjBm+//XZ1xGz3hrY3J81bjmeQnV+kcjSiKiyZ0NVzdWTJo93wdHPkiKkZ/y56CoNfGTNdN1rmXS35B90eE8jintkq9tYW9q+JlyuLH+7K15N60MavDpdyi3j5+ziGf7iD3aey1A5PCFEDKpw0K4rCvHnzOHr0KC+++CL9+vUjMDCQtm3b0qdPH2bOnMmRI0eYP38+Go00iK+M1r51ae1bh0KDkV/jL6gdjqgCSyd0Tb3c+PThLjjqNGw0duX1ux8r/cTejnDJCEl/G9cOE8jintkq9tYWtUfv1t5smBrBnBHBeLg4cDQ1m3GLd/PUN/s5f+nm8iAhhP2odIFfq1ateOONN257nl6vRyd1hBWiKAp3d/TnnY0J/HgwhVFdAtQOSVRSiYSutNrjSiR0XZp68p/RHfnXiliWuA+j6T/TeOTnH4prpYlwhNY6WJ0Hf79zbIcJZGCPIaRHeeIdoTeXoPyNsbcTGTXQW7s2qq0t/nRaDRPDmnFXsC+zl2/ml7Mm1h827yo4uW9LJvdtiYujtKgTwt5U21TwkSNHePbZZwkIkISvMm4sANxxIpOLOYUqRyMqK7DHENKNnuZFeKUw9naq1GYpd3f057khbQGY6/kovz8SDjPdYZIbhpaOGFOMcOzmuuXKjmfNtDodyeGR0EaHcZyreRGkIxCgNX/dRkdK+OxakczVpNiopWTNbU3wxvF03fccwRvHkzW3NbFRS9UOrUbERi3F9J9gFl4Yz0+OM+mhHKFAb+T93xIZ8J8t/HgwhQqssxdC2IAKdc+4nWvXrrFy5Uo+//xz9u7di8lkwtHRkfx82VWpPP6+unP4B9uJS8nmH+HNePXuYLXDE5V0o3sGCXo0O/7SPaN31bpZmEwmXlh3iNX7zuOggX+1zmJAGy/yr1wgdM8zFh/P2pXW1u+C0YuU8Nl2+X7VpEaLP2ua1S7t/Zt8tawf0od5Pg+TjA8ALXzceGZgG+mCJITKVGk5V5YdO3bwxRdfsGbNGnJzczGZTISGhvLoo48yfvx4PD09qzpErfD3b+qkL//gt2Pp1HXWcTjSfmYGa6PqSuiKDEaGfbCdhAvX0CiwbnIYoU3r19oE0poSK3ulRou/qvQ5t7Tbvf/cBzx4t/l4vlLupkBvBKBPa2/mjgyhmbdbjcYqhDBTPWm+cOECS5cu5YsvviAxMRGTyUSDBg1IS0vj4Ycf5ssvv6x0ULXV37+psUmXuHdhNACbZ/SluXcdlSMUVVFdCV3SxRwGvrONQr0Rfw9n1k4Jw7+eiySQolrE71xP8Mbxt+0RHj9oOcHhw6o8nrVtXFPe9/9t1+W8HedCymXz5kM6jcLYbo2ZOqA1fu7ONRavEEKlPs1Go5Eff/yRe+65h8aNG/Piiy+SlJTEmDFjWL9+PefOnQPA0dGx0gGJP4U2qU9Ea28Avt1vP90OaiutTkdw+DC6Dn+c4PBhFktgm3i6sfGZPjT3diPlSj4PfbaHzGsF1TaeqN1qssWfpfqcW1J5338Tkol+8Q6+nRJGv7Y+6I0mvtmTRN8Fm5n381Eu58paFSFsTYWS5oCAAO655x5+/PFHevbsyeLFi0lLS2PFihUMHToUrVZWC1vamK6NAVgXc16a6IsyNfVy4+vHetCongunMnOY8PleruRKj29heTXZ4s8aN66p6Pvv3LQ+Xz7andVP9KJr0/rkFxn5ZOspIuZv5qPNJ8gttJ+NhoSwdxVKmtPS0lAUhRkzZvDDDz/w2GOPVWmaW9zeoCA/3J11pFzJJ/pkptrhCCvWqJ4LXz/WA+86ThxNzWbikr1cK5A/yMKyqqsjTGmsceOayr7/7s09WTO5F1880pXABnW5mq9nQdRx+szfwtLoMxRer38WQlivCiXNDz30EM7Ozrz99ts0bNiQ0aNH88MPP6C3oy15rY2zg5aRncwzFmv2nVc5GmHtmnu78c1jPajn6sCBc5f559J95BeVkXAIUQk12eLPGjeuqcr7VxSFOwL92DA1gvfHdaKJpyuZ1wqY/UM8d/xni9xRFMLKVXgh4NWrV1m+fDmff/45+/btQ1EU6tevz7hx43jooYcICwvjscceY/HixdUVs90qq1D90PnLjPjvTpx0GvbOGoiHSxlbJwtx3cFzlxn/6W5yCg0MCPTl4wldcNDKDp3CcmqiQ8uNThXeiemlb1xTDZ06yssS779Qb2TVvnN88FsiGVfNJSht/OowY3BbBgX5oShKtcQuRG2jevcMgLi4OD777DO++eYbsrKyiv+D9+7dm2XLltGkSZNKB1YblfVNNZlM3Pnedo5fuMob94bwYI+mKkYpbMXuU1lM/GIvBXojwzs05P1xoWg18kdYWE5NdGiprj7nlmCp959XaODL6DMs2nKC7HzzndvQJvV4bkhbwlp6WzpsIWodq0iabygqKuK7777jiy++YNOmTRiNRjQaDf379+cf//gHDzzwQFWHqBVu9U39dNsp3thwlE6N6/H9U+EqRShszZbj6fzzq30UGUyM7dqY/7u/vcxeCZtTW/qOX8kt4pNtJ1my8wx518uqIlp789yQtnQIqKducELYMFVazpXFwcGBMWPG8Msvv3DmzBkiIyNp0qQJv/32Gw899JAlhqiQhQsX0rx5c5ydnenSpQvbt2+/5flbt26lS5cuODs706JFCz7++OMSj3/55ZcoinLTx993OqzouBVxT2gjtBqFA+cucyL9qsVeV9i3fm19eX9cKBoFVu07x2s/HZWtfYXNCR0yEa9XE4kftJx9XRcQP2g53q8m2FXCDODh6sDzdway9fl+PNyrKQ5ahe2JmYz4706e/CaGE+nX1A5RiFrN4kWOAQEBvPrqq5w6dYpff/2VsWPHWnqIW1q1ahXTpk1j1qxZxMbGEhERwdChQ0lKSir1/NOnT3PXXXcRERFBbGwsL730ElOnTmXdunUlznN3dyc1NbXEh7Pznw3qKzpuRfnUdaJ/W19AFgSKirmrfUPmj+oIwBc7T/PupkSVIxKi4mpT33Hfus7MHRnCb9P7cW9oIxQFNhxOY/C7W3l+7UGSr2+YIoSoWRYpz7AmPXr0oHPnzixatKj4WLt27bjnnnuYN2/eTee/8MIL/PDDDxw9erT42OTJkzl48CC7du0CzDPN06ZN4/LlyxYbtzS3u30QFZ/GE8ti8HBxYO9LA3BykL7YovyWRp9h9g/xAIzqEsDbozuqHJEQojyOpWXzdlQCm45eAMBRq2FQkC/TB7Wlpa/sFCvE7ahWnvHGG2/w0ksvUVRU9sYJhYWFvPTSS/zf//1fpQOrjMLCQmJiYhg8eHCJ44MHDyY6OrrU5+zateum84cMGcK+fftKvMdr167RtGlTAgICGD58OLGxsVUaF6CgoIDs7OwSH7fSv60PWo3Clbwi/rv5xC3PFeLvJoY149nBbQBYG3Oep77Zr3JEQojyCGzgzmcTu7JuShg9mntSaDCy/nAaA97ZyrSVsVzIzr/9iwghqqxCSfOmTZt49dVX8fLywsGh7LZnjo6OeHt7M2vWLH7//fcqB1lemZmZGAwG/Pz8Shz38/MjLS2t1OekpaWVer5erycz07yZSGBgIF9++SU//PADK1aswNnZmfDwcBITEys9LsC8efPw8PAo/mjcuPEt35+jTktQQ/MVUlT8hVueK2yTQa8nfud69v20mPid6y2+PfDT/VvRqXE9ANYfTuW/v0uphhC2okvT+qx8vCdv3d8BZwfzn+/vD6QQ8dZmXvruMElZN7flE0JYToWS5q+++or69evz9NNP3/bcp556Ck9PT5YsWVLp4Crr790BTCbTLTsGlHb+X4/37NmThx56iI4dOxIREcHq1atp06YNH374YZXGnTlzJleuXCn+OHfu3G3f2//d1x6AhAtXOZ2Zc9vzhe2IjVpK1tzWBG8cT9d9zxG8cTxZc1sTG7XUYmMoisK3U3rxaFgzAN7+NYH5vxyTxYEWUt0XPUIoisLYbo2JjxzCO2M60q1ZfQoNRpbvSaL/f7bwzKoDJFyQxeJCVIcKraSIjo5m4MCBODmVvn3oXzk5OTFw4MBblidYmre3N1qt9qbZ3fT09JtmgW9o0KBBqefrdDq8vLxKfY5Go6Fbt27FM82VGRfM/0bl+bf8q+BGHvRv68Pm4xl8vfssrwwPqtDzhXW60YtWSdTD9j970XpH6PFWphILFusUoNFomD0iGP96Lryx4SgLt5wkt9DAq8OD0Egf50q70RYt+C9t0dKjPEkOj7S7Lg81oSZ6QNsyrVbDfZ0DuK9zAHtPX+SjzSfYmpDBd7HJfBebzJBgP57s14qO1+8sCSGqrkIzzSkpKbRo0aLc5zdv3pzU1NQKB1VZjo6OdOnShY0bN5Y4vnHjRsLCwkp9Tq9evW46/9dff6Vr165llqCYTCYOHDhAw4YNKz1uVTzcqxkAa/adI69Qtki2dQa9nkY7I1ES9CgrcyHZAEVAssG8C1qCHv+dcyw+a/nPPi147Z4QAL6MPsPMbw/LFr6VdOOixycxHT7LgTez4bMcvBPT6Rg91aJ3C2qDmrjrYk+6N/dk6T+68+PTvRka0gBFMZfwjfxoJxM+38PuU1lyN0kIC6hQ0qzRaG65APDvioqK0Ghqduve6dOn89lnn/HFF19w9OhRnnnmGZKSkpg8eTJgLol4+OGHi8+fPHkyZ8+eZfr06Rw9epQvvviCzz//nBkzZhSfM2fOHKKiojh16hQHDhxg0qRJHDhwoPg1yzOuJfVt40MTT1ey8/X870CyxV9f1Kxje6Lw1VxE2V5Q6uOaHQX4abI4tifK4mNP6NmUt0d3LO7j/MyqAxQZjBYfx56pddFjr+QCpPLaB3iw6KEubHymD/d1Nvf2356YybjFuxn18S5+P3ZBkmchqqBCGa2/vz9xcXHlPj8uLo5GjRpVOKiqGDt2LO+99x5z586lU6dObNu2jQ0bNtC0qXnr6dTU1BK9k5s3b86GDRvYsmULnTp14rXXXuODDz7g/vvvLz7n8uXLPP7447Rr147BgweTnJzMtm3b6N69e7nHtSSNRuGhnuYtyr/adVZ+Cdq4vEvXL3zSy7hrcP148XkWNqpLAB8+0BmdRuGHgyk89c1+CvRyB6O81LzosTdyAWIZrXzr8s6YTmyZ0Y+HejbBUach5uwl/vHlPu76YAc/HUqRu0pCVEKF+jRPmjSJr7/+muPHj9OsWbNbnnvmzBnatm3Lww8/zKefflrVOGuFivQRvJxbSI83f6NAb2TdlF50aepZQ1EKS4vfuZ7gjePNs2rJpSSrAVqY5Eb8oOUEhw+rtjh+O3qBKd/sp1BvpE8bHz55qAsujtIL/Hb2/bSYrvueM8+IlnYjzhGY6c6+rgvoOvzxmg7PKpVVr2wt/xfsTXp2Pp/vOM3Xu8+Sc72kr7m3G1P6tuSe0EY46mr2jrAQNU2VPs1PPfUURUVFjBo1qrgdW2mysrIYPXo0er2eKVOmVDo4UbZ6ro6M6OgPmGebhe0K7DGEdKMnxojSF4UaeztxwehFYI8h1RrHgHZ+LHmkGy4OWrYlZDBxyV6uFciM3u241L9+N823jAuM68eLz6vlblWvrPZdF3vl6+7MzLvasfPFO5g2sDUeLg6czszh+XWH6LdgM1/uPE1+kdxdEuJ2KpQ0d+7cmWnTprF//36CgoJ49dVX2bx5M4mJiSQmJrJlyxZeeeUVgoKCiImJ4ZlnnqFz587VFXutd2NB4IbDqWRcLf3WsLB+Wp2O5PBIaKPDOM7VPJvmCARozV+30ZESPrtGOgeEt/Lmq0ndqeukY+/pizz42R6u5JZ/HUNtVNmLntrYnu529cqFF65v2iQXINWinqsj0wa2YeeLd/DSXYH41HUi5Uo+kT8eofdbv7Nwywmy8+X/uxBlqfA22iaTiVmzZrFgwQKMxpsXDJlMJrRaLc8//zyvv/76LfsUi5Iqc/vgno92cuDcZZ4d1IZ/DWhdzRGK6nSjZZnvX1qWXTB6kRI+u8Zblh06f5mHv9jL5dwi2jV0Z9mk7njXqVh7xNrkRjJIgh7Njj9bBhp7O0EbHQfDPijxPSzte51utO/2dAa9nqy5rfFJTDfXK/+NcZwrGa39ACM+iRnmGuYyzvF+NUHaz1lAfpGBtTHn+XjrSc5fygOgrrOOR8Ka8Wh4czzdHFWOUAjLsFR5RoWT5htOnjzJkiVLiI6OLu5P3KBBA8LDw3nkkUdo2bJlpYOqrSrzTf0u9jzPrDqIT10ndj7fH0cHqUG1ZdbUm/ZYWjYPfbaXzGsFNPNyZdGDnWnn76FKLLagvBc9xT25E/TmxYM3EuyI0hNse1HeeuVdjR+nR9Licl+AiKorMhj58WAKC7ec5ET6NQBcHLSM6hLAuG6NCW4k/++FbVM9aRaWV5lvaoHeQIfIXynQG3mibwtmDm1XzVGK2uRUxjXGf7qHtOx8dBqFpf/oTngrb7XDslq3u+gp72yrPc6kVmTBpNbByWruutQmRqOJX4+k8dHmkxxOvlJ8vF2Durw1qgMdAuqpF5wQVaDKQkBLmDNnDjo7+2OgJiedlmB/8w/Ad7HJ0n5OWFQLnzp88EAntBoFvdHEE8ti2H0qS+2wrJZWpyM4fBhdhz9OcPiwmxJfe2lPV5l67IosmAwdMhGvVxOJH7ScfV0XED9oOd6vJkjCXM00GoU7Qxryw9PhfPWP7sXlGUfTrjLivzu5b+FOfjyYIr3cRa2lSvYqiZ1lvXFve0b8dwfp2QXsPX2RHi1K3/5biMro3tyLH58OZ/rqgxxLu8qEz/fw1v0duK9zgNqh2Rx76A5R2e3CA3sMIT3KE+8Ifen1yr2dyPjLgskbFyCi5imKQp82Pux/ZRAr9yYRfTKLn+NS2Z90mf1Jsfi5OzGhZ1Me6N4ELytd62BNpW7CfshPkB1o19CdMV0b882eJD7eelKSZmFxQf4efP9UOM+uPsj6w6lMX32Qs1m5TBvYWhb7VkCJ2dbS6nqtvDtEcT12oh7+Uo/tHaHHW5lKLJSZON/oEuOtTMU4zrXUeuWUsNn4SWJjVcZ1b8K47k1Iv9qO5XuS+Hp3EheyC3j71wQ++P0EIzr680hYM0KsqO65shd2QtxOjdc0z5kzh7lz52IwSE/Iv6tKzc3ZrBz6v70Fowl+mRZBYIPK1+zYIplVqBlGo4kFvx5n0ZaTANwb2oj/u789TjpZgFoeN2qavRPTba47hKXqsa2pS4youAK9gQ2HU1my8wyHzv9Z99ytWX0eDW/O4CA/dFr1NkuprQttxa1ZqqbZun4ri0pr6uXG0PYNWX8olU+2nuLdsZ3UDqnGyKxCzdFoFF64M5Cmnq7M+j6O72KTSb6cx+IJXajnKu2pbseWZ1uP7Yky/x+7VT122yzi90TdsqwidMhEDAMeJP5vF7nW+J7FzZx0Wu4NDeCeTo2IPXeZL3eeYcPhVP44c4k/zlyioYczE3o1ZVy3JjXesq54G/ZEfckLu+vbsBvHueJvmoNhwINWd1EqbIP81NiRKX1bsv5QKj8cTOHZwW0IqO+qdkjVriq3i0XljevehEb1XXjy6/3sPX2R+xZG88Uj3Wjm7aZ2aFYvdMhEYoFGpkh82/55oZdh9CIlzHpnWy1Zjy31yrZPURQ6N6lP5yb1mTWsHd/sPss3e5JIvZLP/F+O8/6mRO7p1IhHwpvRrmHN3Pm01IWdEGWRDeftSEgjD3q38sZgNPHZ9tNqh1PtimcVEq7PKiQbzK2srs8qkKDHf+ecWrHTmhoiWvuwdkoYjeq5cCozh3sX7mTfmYu3f6Kwye4Qsl24KIufuzPTB7dl54t38PbojgT7u1OgN7Jq3zmGvr+dsZ/s4pe4NPTV3HXDHhbaCusmSbOdmdzXvKnMqj/OcSmnUOVoqpe9tO+yZW0b1OW7p8LoEODBpdwixn+2hx8Opqgdlk24XXs6a1PZ7cJF7eF8fUOUn/7Vm7WTezGsQ0O0GoU9py8y+esY+i7YwidbT3I5t3r+NsmFnahukjTbmfBWXoQ0cievyMDSXWfUDqdayayCdfCt68zKx3syOMiPQr2RqSti+e/vidJa0s7cqMemjQ7jOFfzDn6OQIDW/HUbHSnhs60++RfVT1EUujbz5KPxndnxQn+e6t+S+q4OJF/OY97Px+g57zdmfnuY42lXLTquXNiJ6lbjSbPJZJI/ptVIUZTi2eal0WfILbTf0gSZVbAero46Fj3Uhcd6Nwfg7V8TeH7tIQr1sgmCPQkdMpGDYR+Q2doXJrnBTHeY5EZGaz/pSiBK1dDDheeGBLJr5gDm39+Bdg3dyS8ysmJvEkPe28b4T3ez8cgFDMaq5wVyYSeqm0Vbzun1eg4fPgxASEgIDg4ON51z5coVLl++TNOmTS01rN2wVEsUg9HEHf/ZwtmsXF4aGsjj15Noe2PL7bvs2bJdZ5j9QzxGE/Rs4cl7YzvRwMPlls+RloG2Rb5forJMJhN7T1/ky+gzRMWncSNXbuzpwsRezRjZyR+fus5VGkPaGoq/s1R+VaGk+fTp02zevJnevXvTpk2bEo/99NNPTJo0iczMTADq16/PwoULGTNmTKWDq20s9U0FWLTlBG/9chytRuFw5GBcHe3zD9qN7hkk6Ett3yWzX+rYfCydp5fvJ6fQgKNW4YtHu9G7lU+p55b2By7daF8tAyXJFOJm5y/l8vXuJFbsTeJKXlHx8Va+dZh3X3u6Nq1f6c2T5P+c+CtVkuaXXnqJt956i1OnTpWYKT5x4gQdOnQgPz+fpk2b4urqyrFjx9BoNOzdu5fQ0NBKB1ibWDJpvphTQJfXN2EywaTezXlleJCForQ+pc8qeHKq6Sgc/FrLL0yV7D6ZxfjPdmM0gbNOwztjO3FX+4YlzqkNGxHUhosCIaoir9DA9weSeefXBDKu/bmwu7VvHcZ0bcy9nRvhbaXbdQvboErS3KdPH65du8b+/ftLHP/Xv/7FRx99xFNPPcWHH34IwLfffsuoUaN49NFH+fzzzysdYG1iyaQZ4MV1h1j5xzkaejizeUY/nB3sd9e2v84qFF44QauzayRJsQJxyZeZuuIApzJzAPhHeHNm3hWIg1ZjsR3mrFltuCgQwlKMRiNLos+wPTGT3aeyyC8yr4nQaRQGtPNlbLfG9Gnto+qOg8I2qZI0N27cmH79+rFs2bISx1u3bs25c+fIyMigbt26xcf79u1LamoqCQkJlQ6wNrF00pxfZKD/21tIvZLPK8ODmHR9kZY9kyTF+ugNRhb8epxPtp4CoEvT+nw0vjNZcb8RvHE8fJZj7rH9dwFamORG/KDlNrkRgUGv5+qcpnicuISyMu+mx+3hokCI6nI1v4gfD6ayet85Dpy7XHzcz92J+zsHMLprY5rLZkqinCyVX1Xoci0zM5PGjRuXOHb58mVOnjxJjx49SiTMAJ06dSI5Wdp9qcXZQcvUAa0BWLj5BDkF9ttJA2xzsxODXk/8zvXs+2kx8TvXW1VslqLTapg5tB2fTOhCXWcdMWcvMeyD7ew5bV7/YK8tA/cunUk97TWU7aX3pJU+4kKUra6zA+N7NOH7p8KJmtaHx3o3x9PNkQvZBSzccpL+b29hzMe7WBtz3q67RAnrUqHpDZ1Ox+XLl0sci42NBaBr1643nV+nTp3KRyYsYlSXAD7eepKzWbl8GX2Gp/q3UjukamMrW6jeKCXJPvg9bVN/Jlj7Z6/S9Cj7LSMZEtyAwAZ1mfz1fo6mZvN6nDe5upE86bsCTXIpf/RsuGWgQa+n3dlvzNMSdnpRIKqXLGT7U9sGdXl5eBDP3xnI78cusOqPc2xNyGDvmYvsPXORyB/iubtjQ8Z0bUynxvUqvXhQiNup0P/ANm3a8Ntvv5U49uuvv6IoCmFhYTedn5KSQsOGDW86LmqOg1bDMwPbMG3VAT7ZepKHejbFw+XmVoD2wBY2O7mxKCxYcxFMJjihh+2FxWUk3hF6vJWpxIJdJs5Nvdz47skwXvk+jjUx53lbP5aY+1rx7qcLqJd/rcS5xt5OZNjoRgTmCzhzHTe+2tLLT2z4osBSJDEsXYnfE9fZ8wV1eTnqNNwZ0pA7QxqSdiWfdfvPs3rfOc5m5bJi7zlW7D1Ha986jO3WmHtCZfGgsLwKlWfcf//9JCYm8sQTT3Do0CG+/fZbFi1aRJ06dbjzzjtvOn/nzp20amW/M5u24u6O/rTxq0N2vp5Pt51SO5xqU5XNTmqiTOJGvbVPYjpkGyFBDyvzbKKMxJKcHbQsGN2R+fd3wFFjYrNrF4Y/9QGHOrS1m40Iii/MLhshwrH0kyIcuWyoY5MXBZYQG7WUrLmtCd44nq77niN443iy5rYmNmqp2qGpqsTvic9y4M1s+CwH78R0OkZPrfX/Pjc08HDmqf6t2DKjHysf78l9nRvh7KAhMf0ar68/Ss83f2Pyshh+P3YBvUE2WRKWUaGFgHl5efTs2ZPDhw8X3/4wmUwsWLCAZ599tsS5+/bto3v37qU+Jkpn6YWAf/VLXBqTv47B1VHLtuf72+UVeGU3O6mJlmAlOkXsKoBH3Ox2AVxFxCVfYdKnW7mQr8WRImbrljJe+zvpJtveiCB+53rzIsdN+TDAyXyBtOPPOwr0doQ2OqKbTCZs0ny1w61xsmC3dLWho0x1ys4v4seDKazed56DpSweHNO1Mc1k8WCtZKn8qkL/61xcXNi5cyfvvvsuu3fvxtPTk9GjRzNixIibzt2/fz8jR44s9TFR84YE+9EhwIND56+waMtJu+zbfGMLVW9lKsZxrqVudpISNhu/vyXMHaOnoiTqzbXQ1VQmUaLeuv71ejsrLiOpKSGNPPj1haE8uyqWTccymKV/jN8aPMYH/xhIqKv5ws4Wb+EH9hhCepQn3o3T0azOg8HO5m2nrzMVmLhsrEuPiW+qGKU6ihfsJupLJobX77QYx7nib5qDYcCDVv99tjRbWZdhrdydHXiwR1Me7NGU42lXWb3vHN/FJhcvHly45STdm3sytmtjhrZvYLebfonqU+GfmDp16vDKK6/c9rzHH3+cxx9/vFJBCctTFIUZg9vy8Bd7Wbb7LI9FNKfhbbY2tkWhQyYSCzQyReLb9s+Z4wyjFylhJWcua/KPd4l6a9318hE7rnWtSKLr4eLA4oe78cm2UyyIOsbv5+H+T/aw6KHOXNm/ziZrO0tcwAGa7/LACfDXYmzpAI21nAl7k9BalhSCJIa3YgvrMmxF2wZ1eWV4EC/cGchvRy+wat85tiVksPf0RfaevsjsH+K5u6M/Y7oGyOJBUW617zd2LRbR2pvuzT3Ze/oiH/6WyJv3dVA7pGoROmQihgEPEv+3pM3vbwlKTf7xLlFvnWSAS9drXUvr32vDC+CgcouYNBqFKf1a0qlxPf61IpbjF64y7L3NLFC+ptPJ9Gq9C1BdKnIBV5tIYli2Er8n7PSC+oaauoPkqNMwtH1DhrZvSOqVPNbFnGf1vvMkXcxlxV7zFt5t/K7vPBjaCC87LF0UllOhmmaAN954g5ycHObMmYODQ+ldGAoLC4mMjMTd3Z0XX3zRIoHWBtVZ03zD3tNZjPlkNwCrHu9JjxZe1TKOLdj302K67nvOvNCmqJQTHIGZ7uzruoCuw6t21+SmeutAHYxxuanW9UYZia3WdFqiVjU9O5+nvtnPH2cvAdA+NZHlK2ZStyi/+Bxbqu20xfKS6lRc711La/pv9fNQ2XUZtkbtreWNRhN7Tl9kzb5zbIhLLd55UKOAT10nJvRsymMRLex6F93aRpXNTTZt2sSrr76Kl5dXmQkzgKOjI97e3syaNYvff/+90sEJy+vWzJN611vOzVh7UOVo1FWVbhsVdeN2PW105s4Q10zwbR40NCcIzHSHSW5ktPaz2YTZUpvL+Lo783LIJUZodgJwuGFrhj36AXF+LYvPsaWNQbQ6HcHhw+g6/HGCw4fZdLJjCYE9hpBu9DRfSJXC2NuJCzZ8p+VWbtcx5KbfEwFau+koc4M1dAfRaBR6tfTinbGd2DtrIG/cG0KHAA+MJriQXcDbvybQ5bWNTFsZy6YjFyjQl3FXpIbVhs2wrF2FZpoffvhhNmzYQHJyMk5Ot76FUVBQQEBAAHfeeedN226L0tXETDPAT4dS+NeKWEwm+OaxHoS38q62sazRjZme3KxztPzjdeqduFRjszqlzbBcNLiT0HAodTuOtOlZSEvOIP7xw8d02/8C87eOZGnH4eQ4u6Ez6JkavZInd61G52C02F0AUfNuJE4k6EtdsGurF463UpG7MKX9nrhgtO2OMmDd3UFMJhPrD6WyePspMq4WkHrlzztb7s46hgQ34O6O/oS19EKnrdB8o0VYYnY+Ly8PFxf7W8tUHqp0z4iOjmbgwIG3TZgBnJycGDhwINHR0ZUOTlSP4R382XfmEl9Gn2HOj/FsmBqhyi8BNdxUb6sFUystxsfc0PySf9tuG1VVVr11TxtNlP/KUrWqsVFLafnH66CF5xOX89ie//Hy4CfZENibdyIe4reW3flPzHu04rJd1HbWRrWt3ruii47Luy7D1ljzIlBFURje0Z/hHf0xmUzsT7rMT4dSWH8olfSrBayJOc+amPN4ujkyNMScQHdr5olWU/0LCC3V5ennn3/mySefpFGjRgwbNoz777+fjh07Vnv89qRC/wNTUlJo0aJFuc9v3rw5//vf/yoclKh+zwxsw/8OJJNw4Rpf7z7LI+HN1Q6p2pX1i4cIJ5Q2uhItwarzj/eN2/X2xhKLmIq/Ryf00FADEY54rszmo//9Hz8k9OWVwVM46N+GYQ3eY0rRjzzVbXB1vBVRA+w1MSxNZZJFe/w9YSuLQBVFoUvT+nRpWp+XhwXxx5mL/HgwhZ/j0riYU8g3e5L4Zk8SvnWdGNahIXd39Ce0mjpwWKrLk16vJzExkYyMDIYPH86GDRtYsGABAQEBTJs2jaeeesrisdujCk0vajQaiopKWzFVuqKiIjSa2jGDaWs8XB2YMaQtAO9sTCDrWum/zO3Freptlev1ttkGV/Z0fJP4QcvxfjXB7ma7qltVa1Vv+h79nA9tdDDOBSVAy8iTW/l1w7/ok3eAAo0j7xnuZ8KX+zh38ebbvMI21JZ6b1tJFqtbTa4jsRStRqFnCy/euLc9e18awFf/6M7oLgHUddaRfrWAJTvPcN/CaHq/tZl5Px8lLvkKFeyvcEvH9kThq7loLukpRXnXd1y+fJnt27cTGhrKBx98wM6dO9m1axehoaG88sorfPfddzc9p7Cw0CLvwZ5UKKP19/cnLi6u3OfHxcXRqJH1/PCLksZ1a0JQQ3ey8/W8/WuCanHUxOKG2/3iUXYU4K7NpfX+eRRey7TbP97VqaqLmG76Hh3Tw+o88x/S64slG4wv4N26H/NEm2u4OGjZfeoiQ9/fzuo/zln0D5UQlmSLyWJ1sPVFoDqthj5tfFgwuiP7Xh7IZw935Z5O/rg5akm+nMcnW08x/MMd3PGfrfzn1+MkXLha5TEtdcGVkpJCbGwsffr0wdXVFScnJzp16sTTTz9NTk4OX331FUDxxOjhw4dp2bIlzz//fJXfgz2pUGYQERHB119/zZkzZ2jWrNktzz1z5gy///47Dz/8cFXiE9VIq1GYMzKY0R/vYuUfSTzYowkhjTxqNIbK9PStjPL+4ql34TL1oq2/B7C1qkqt6tWD10u5/vo9OqaH49egida8k+JIV051e4mZI8cyPiuHZ1cfZN/ZSzy/7hBR8WnMu789vnWdq+ndCVE5xTtERuhLX3Rs473Zy6syu7ZaKyedloFBfgwM8iOv0MDm4+n8dCiF346mczozhw9/P8GHv5+gjV8d7u5grpVuXoktvC3Vu/v48eOkpqbSt29fDAbz62i1Who2bIi/vz+KonDx4kU8PT0BiI2NJTs7G29vc6MAg8GAVist+Co00/zUU09RVFTEqFGjyMzMLPO8rKwsRo8ejV6vZ8qUKVUOUlSfbs08GdHRH5MJIn+Ir9HZuppsPVTemR7Nr/nlbo0mShc6ZCJeryYSP2g5+7ouKFe5S2zUUrpfWGX+4u/fIxNw1gCZ5p9NV+8mADT1cmPVE72YOTQQR62G346lM+Tdbaw/lFodb0uISrO2VnJqti4LHTKRg2EfkNna127abbo4armrfUMWPtiFmFcG8f64Tgxs54uDViHhwjX+szGB/m9vYfiH2/lk60nOXyp/SZklZufz8vLYv38/7u7uDBgwAK1WW5wAHzhwgLNnz9K+ffsSXSWio6NxcHBg0KBBALJj4nUV3txk+vTpvPfee3h7ezN58mT69+9PQEAAAMnJyfz2228sXryYjIwMpk+fzttvv10tgdujmmo593epV/K44+2t5BUZeH9cJ0Z2qv5bhDXdeuh2mwYwzsWcrH14DRrZ9+YK1qbEz4KvxjzzVNpOibf4mTiedpXpqw8Qn5INwIiO/swdGUw9V8caeQ9ClIc1tJJTe2ORG2rDpj9XcouIOpLGjwdTiD6ZhcH4Z7rVuUk9hnfwZ1iHhvi53/ruWFVbNJ47d46nnnqKn376iRYtWjBkyBAGDx7MiRMnePPNN2nYsCHff/89rVq1AsxJ9h133EFeXh6xsbF2kTBbKr+qcNJsMpmYNWsWCxYswGg0lvq4Vqvl+eef5/XXX7eLf+yaolbSDPDR5hMsiDpOA3dnfnu2L25O1fvLS41dwUr0Sf3LLx56O5oXnK3OM5cDWHAnQHF7JX4W6iql7pRIhCOm1g4cuMUfh0K9kQ9/T2ThlpMYjCb83J146/4O9GvrW8PvSKjJ2pMxNeOzxI6donKyrhXwc1waPx1KYc/pi9zIvBQFejT3ZHgHf4aGNChzG++qXHDt2bOHoUOHMmbMGFq1akVUVBRbtmxBo9Hw3HPP8dhjj9GsWTOKiopwcHBgz5493HvvvQwdOpTPP/8co9Fo800dVOnTDOYp+jfffJNJkyaxZMkSoqOjSUtLA6BBgwaEh4fzyCOP0LJly9u8krAmk3o3Z9Uf50i6mMvCLSd4bkhgtY6nxmryG/W2TY2z8Gz7lwUal4x/JsxQaxblVJal/+iX+FlIxvy9GOxcogUgBhO7/cbQ6xZ/HBx1Gp4d3JYB7fyYvvoApzJyeGTJH4zv0YRZd7Wr9gtBUTmW/HmqqTUSVaFWKzlLtS4TleNVx4mHejbloZ5NuZCdz4bDqfx4MIX9SZfZfeoiu09dZPYP8YS19OLujv4MCW6Ah8ufOy9XpUXjkSNHuHz5MuPHj6dPnz48/fTTrFixgieffJLLly8Xr1G7kRjv3r2bnJwc+vbtC3DLsk2j0YiiKLVmgrRCM81arZbIyEheeeWV6oyp1lJzphng1/g0Hl8Wg6LAyn/2pEcLr2obS42Z5hsK8/O59kYr6l24bK5hTjKY62avq4ldqSyVKNT0rFV13Not9WdBwbz4r64CzgoMc6nQz0JeoYH5UcdYsvMMAK6OWp6/sy2PhNl/P3JbYsmfJ5lFvTU1f+eKsp2/lMv6Q6n8eCiFuOTs4uMOWgXvOk70b+vL1AGtaeBRuQXO165d4/nnn+fHH39k//79+Pj4FD921113sWvXLk6cOIGX159/78ePH8/mzZvZuXMnLVq0wGQylSsp/usCQ2ujykyzyWSStk52bFCQH/VdHbiUW8ST3+xn38sDq+3qUc3V5I7Ozpzt/Qb1oqdi7OWExlCzK7gtNRtW07Nq5dmVqsOAByucxJf6s3Bj8R/XL2Iq+LPg4qhl9t3BDGrnx5Rv9nMlr4jIH44Qc+YSr9wdJB02rICldjkDmUUtD+kVbZ0C6rvyRN+WPNG3Jaczc/jpYAo/Hkoh4cI1Uq/ks3xvEiv2JtG1WX0GtPNjYDtfWvrUKfff5tTUVH788Uc6d+5c3BnjRhnG/fffzy+//MKWLVu4//77AcjMzCQ+Pp6WLVsWb2ZX1lg//fQTBw8eZPDgwXTr1q1EsmwymYpnoctb2nH16lWys7OLu3lYo9r520OUSlEU3h3biUe//IOsnEJW/nGOB7qbOxVYekZT7dZDam3ja6lEwZIJR3mUJylpZnyJrEok8dX5sxDWypuf/hXOxCV/cCojhx8PpbLleAbTB7dhQs+mtWb7eGtj6STXmrdnthaWal1madZeg16Tmnu78a8BrfnXgNZsPZ7Ofzef4HRmDpnXCvnjzCX+OHOJ//v5GM28XBnQzo8B7Xzp1swTh1v8HvPw8GDgwIH07du3OKnVXf/3bdasGRqNhoSEP/dp2L9/PykpKcXtgm/Vas7BwYF169YxZ84cHBwc6N69O/fccw8jR46kWbNmFZpxLigo4OOPP+brr7/G2dkZBwcHHnzwQSZOnIirq2u5X6e61c6fTFGmfm19mXVXO15ff5Q31h+lTxsf0vesrpYZTbUS17+OX5Pb+FoqUVBjVu22Sck5PfXbXMWUYKhUEl+dPwuNPd34/dl+HDx3mVf+F8eh81eY8+MRVu87z2sjg+nazLPSry0qx9JJrsyi3p419oq2hRr0v6rJBL9vW1/6Xl/EnHw5j9+PXmDT0XR2ncziTFYun+84zec7TuPurKNfW18GtPOlXxtfPFwdSryOr68vS5YsKXFMURRMpv9v777DoyqzB45/p6T3QjoJkAABQg+E0BSQJgq7a8PComtjrciqiBURRdSfqLvqim11LeAKrgXpSyd0QgkJCSQkkBDSe52Z+/tjyMCQQNokmSTn8zw8IXfu3Llzb2bmzLnnPa/CuHHj8PLyYuvWrTz22GO4uLiwb98+9Ho9119/vWndq5k8eTKTJ08mKyuLHTt28Pvvv/PBBx/w1FNP4eXlxXXXXcett97KtGnTcHFxuebzValUuLq64u/vj4+PD9988w1FRUWMHz+e3r17N+EItowmDQQUHdt9o7rz+7HzHEor4LHl6/ix5AnULZTRbO3A9UoNGZRjqTdKSwUKbZFVu2ZQogIibSFRh+ryVnGNDOJb+m9hYFd3fnpkFCv2p/HWupPEny/i1n/GcOvQIJ6bGo73VUatC8uzdJBrrVlUa9LWV/eu1NpXy5qrLQP8QHcHZkV3Y1Z0N0oqdexMymZTfBb/S8gir7SKX45k8MuRDDRqFcO7eTKhjw839PGl2zUmU6kZvDd//ny2bt2Ks7MzAOvWrUOr1RIdHQ1Qq7Sipr55165dfPvttwwcOJA//OEP3HLLLaYSj6SkJLZs2cLatWt55JFHGDlyJL/99ts1n6OtrS0PP/wwDz/8MGfPnmXjxo2MGzfumrNKnzt3Dg8PD5ycGj9pTFM1+tWxbNmyWt9arkWlUnH69OnGPoxoQxq1irdvG8jU93dwOM+WH3PGcMeKNZdWsHBGs61GkzeEJd8oLRUotEVW7ZpBSbAG3NXwY+3eytC4IL6l/xY0ahV3R4UwpZ8fb607ycoDZ/nx4Dk2xGXyzOTe3BUVgkYtiYGWZukg1xqzqNaora/u1WhvNejWFOA722mZEuHPlAh/9AaF2LP5bIrPYnP8BRIvlBCTnEtMci6L18QT2sXJOGthH1+GBHvU+d42b9485s2bBxj7M0+cOJFevXrh7e1d5wDAmt99fX3R6/UsWrSIRx55BH9/f2644QZuueUWJk2axEMPPcRDDxlbtl64cAGg3tZ1NaUgKSkpXLhwgSFDhpiC+cvl5eWxePFitm/fTlJSEoGBgcydO5f77rsPGxubOrZsOY3+aywoKKCgoKAFdkW0loZkTkO7OHNPLwNfnIDFrrMY67IH/+Jcs3U6ep2gpd8oLRUotEVW7ZpBicvFN9V2dGncy9mOpbcO4PZhXXnpv8c5cb6Il36OY+WBs7w2I4LBwR5tvYsdmqWDXGvLolqztr66B+2rBt2aA3yNWsXQEE+Ghngyf0o4abllbIq/wOaEC+xNzuN0dimntyXzybZkPBxtGNfbhxv6+jKmpzcu9rWDSwcHB1555RXT79eqLAgLC+OTTz6hpKSElJQUtm7dyrp167j33nspKCigT58+TJs2jVtuuYXhw4cDtbPWtZ7PxRrorVu34uHhQZ8+fWqtU1payt13382GDRtYsGABS5YsYfPmzSxevJiAgABuuummBh27pmr0GV64cCEvv/xyS+yLaAWNyZxO9kjnkKqMWNuePD/5Mb748VXMXkJWGAxZSku8UVoqUKgovIBer0Iz1ha+r2PmvBbIql0zKBlmhxra5aXxoSEe/Pr4aL7Zk8o7G05yPL2IP328m5nDuvLs5HA8nGRGwZbQEkGutWRR24O2vrrXnmrQ21OAH+zlyF9Gd+cvo7tTVFHNtpPZbI6/wJaT2eSXVbP6cDqrD6djo1ExoocXE8J9mNDHl66eTR9o5+zsTP/+/enfvz+PP/44eXl5nDhxgs2bN7Nu3TrWrFnD8ePHG7y9yspKtmzZQv/+/enatStgnqH+4osv2LRpE3//+9955JFHUBSFIUOGEBsby9/+9rc6g+aYmBiSk5Ob/BwvJ1+7O5HGZk6dPQN5x+Zpbix/gy2hw1gVMZ5bj//v0gZbKRhqi9HVLfFGaYlA4fD6rxi89ylUmXroqTVO/33ZzHlKC2bVrh6UeGKnr8K1nV4a16hVzB7ZjRv7+/Pm2gRWHTrH9/vOsvZ4JvOnhHNHZFfUUrJhcS0R5FpDFlXUrz3VoLenAP9yrvY23DwwgJsHBqDTGziQms/m+Atsjs8iOaeUHUk57EjKYeGvJwj3czHVQQ8Mcm/W+52npyejR49m9OjRvPjiixQXGycSa2iv58zMTA4fPsxf//pXU4u8mvulp6fz5ZdfMnXqVFP9tE6nw8vLi2nTprFw4UKOHz9OREQEYJw+/LnnnmPbtm3Y2hoTIH/60594//336devX5Oen7yTdBJNyZyGR00md/1jPFn0H972uJtFEx5izJlYfEuMH3CtEQy11eCLlnqjbE6gUOschmtrzZyn16s4ErWMoS10bK4WlBzd/C0D1e370ngXFzv+7/aB3DGsKy//fJyEzGIWrD7Giv1nWTwjgv5Bbm29i22iJb+0tkSQ29ZZVFG/9lSD3p4C/KvRatSM6OHFiB5evDCtL6ezS9h8sRvHgTN5JGQWk5BZzIdbTuPtbMf48C5M6GMs43C0bcZrUaPB3d0daHgTidjYWIqKioiMjMTOzs7svseOHePYsWM8+eST+Pr6ApdKPvLy8lCr1eTmGstICwsLefbZZ9m8eTNz585lxowZREREkJOTw6JFi/j2229Nrfcaw7o/xZroo48+4u233+b8+fP069eP9957jzFjxlx1/W3btjFv3jzi4uIICAjg2WefZc6cOabbP/30U77++mvTJYahQ4fyxhtvmOp0wFi28uqrr5pt19fX1zTFeFtrSua0JjP64K65rCuO4ph9GM9PfYzPYl5v0YxmjbYcfGHJN8org44BE+6GJgQKtc5hgg5OlpjNnKed5oC9m0+jnmtj1RWUdKRL48O7e/Lb46P5KiaVZRsTOXK2gOkf7uSeqBCentS7Vkunjqw1vrRKkNv5tKca9PYU4DdUaBdnQrs489DYUPJLq9iamMWm+Cy2n8wmp6SSHw6c44cD57DVqhkV6mXqCe3v5tDi+7ZlyxYCAgLo2bMncClDrdPpiI2NxdbW1tTZAy7VQefl5VFRUUFoaCgAK1eu5IcffuCjjz7i4YcfpqjIONvizJkzeeONN9ixYwfjxo1r9P61/V+kha1cuZK5c+fy0UcfMWrUKD755BOmTp3KiRMnCA4OrrV+SkoKN954Iw8++CDffPMNu3bt4pFHHqFLly6m9P/WrVu58847GTlyJPb29rz11ltMmjSJuLg4s3Yo/fr1Y9OmTabfrWkqyaZmTmuCoed3fMJs3bNs7jGc//aexEhVgsWDocuDSzs3PwJ2vdJmgy8s9UbZ4t03Lps5D1tgmkObXSbsSJfGtRo194/uzk0D/Hnj93h+js3g33tS+f3YeZ6bGs4tQ4I6fMmGNXUMEB1Pe/mi3Z4C/KbwcLLlj4OD+OPgIKp0BvafyWPjCeNgwrN55Ww5mc2Wk9m8+F/oF+DKDX2M3TgiAl2b3YK4JiBOTU3Fzc14JW/79u1ERkbWitc0Gg3x8fGEhoaapvyuuX9ubi4JCQl4eHgQFBREeXk5v/zyCz4+Ptx///2mdQFGjx5NSUkJ+fn5TdrnRp1lg8HQpAdpTe+++y73338/DzzwAADvvfce69ev5+OPP2bJkiW11v/nP/9JcHAw7733HgB9+vThwIEDvPPOO6ag+dtvvzW7z6effsqPP/7I5s2bTbPmgHGWHT8/vxZ6Zs3TnMxpTTB0x7/X8++TMF//KD8/OpLBgZbrMFBXcImiwFldneu39OALS9UfW2P3jZbU0bKGvq72vD9z8MWSjThOZZXwzI9HeX9zEvOnhHPzwIC23sUWYc0dA0TH0V6+aLeXAL+5bLVqRoV5MyrMm1du7ktSVokxgI6/wOGzBcRlFBGXUcT7m5PwdbWjh7cTw7t7Miu6W5P63KtUKioqKhg8eDDDhw+nb9++xMfHM2XKFLN1alrRJScnmyUq9Xo9Wq2WEydOcOzYMSZOnAjAkSNHOHbsGBMmTECr1Zqm8wZMPZ1raq0by7r+MpupqqqKgwcP8txzz5ktnzRpErt3767zPjExMUyaNMls2eTJk/n8889N87NfqaysjOrqalOReo2kpCQCAgKws7MjKiqKN954wzR3e10qKyuprLxULlFz+aAlNDdzqtFqefnPU/ll8SYKy6u554sD7H/hBotk264WXDLWFibYQa7BWIpwuVYYfGHR+uMaVtB9QzTeyFBvfn9iDF/uSmHZpkTO5Zfz+PeH+Tk2nRen9b3mJALtUXvqGCDat/byRbu9BPiWolKp6OXrQi9fFx4dF0ZOSSVbErLYFH+BHUk5XCiq5EJRJTHJefz9f6cYEuzByDBvRod5M6irO7baa7eXq6HVannjjTfYuHEj//73v6msrOTjjz8mOTmZSZMm8Ze//MV01d7V1ZWMjAxTprkmEF6zZg1FRUXcdtttABw9epSCggJT+YWiKOj1xpghNjYWMLbXa4qGPat2IicnB71ebyoQr3Gt2uLMzMw619fpdOTk5NR5n+eee47AwEBuuOEG07KoqCi+/vpr1q9fz6effkpmZiYjR440FaXXZcmSJbi5uZn+1bRXaQk1mVN6aTHMdIQgjfFyfpDG+HsvLRmjXrlmAGejUbPkT/0ByC2t4uNtzZ+0xhRcJl4MLtP1UI3x5/flkKgzDna7MjZvpazq4Mmz8Xo5ibiJ33Eg8m3iJn6H98uJ9WYWEvaux0edh+paQYc6l4S96xu8L5Y4h6LpbLVqHr4ulG8fiMLfzR6ATfFZ3PDuNl746RgXiiraeA8bRq/TEbdrDQd+W07crjXodbWv5rTXjgFCtKSaAD/ypofoN2pap3qv9Xa247bIrnwyK5JDL03kk1lD6OnjjI1GhUGBA6n5fLA5ids/iWHQog3c++U+PtuRzImMIgwG5arb1Wq1zJkzh1WrVpGdnc3p06d55ZVXOHHiBGvWGCdVqwl4b7vtNo4cOcLWrVtRFAWNRkN6ejqfffYZ48aNY/z48YBxMpXy8nKzWQ1ryjM2bNiAv78/3bp1a9Jx6JBn/Mo6m/pandS1fl3LAd566y2+//57tm7dir29vWn51KlTTf/v378/0dHRhIaG8tVXX5lm27nSggULzG4rKipq0cDZEpeYbuzvz5I/9WfB6mP834aTDAn2IDrUq8n7VF9Gi51Vxu4QwZpLtbu0bla15o2ypub68Lov6u0iYI3dN9paW7QObAlDQzyJWTCBI2cLWLYpka0ns/l2bxqrDp1j9shu/PW6UNwdrbO/c0Nr7NtDKVBr6Sh/t0JYir2Nhsn9/Jnczx+As3ll7D6dw85Tuew+lUNuaRVbT2az9WQ2AF5OtowM82ZUqBejwryv2Re6e/fuzJ07l7lz55qW1cRiN998M7feeitz587l4YcfJj8/n08++QRnZ2deffVVHB0dURTFNItgt27dTPFfTaeM//3vfwwfPtw00LCxOtQr39vbG41GUyurnJWVVSubXMPPz6/O9bVarekSQI133nmHN954g02bNjFgwIBr7ouTkxP9+/cnKSnpquvY2dmZWqq0FktcYrpzeDAHU/P58eA5nlhxmDVPjMbHxb7+O9ahocElIRo433aDLxo7oK8lgw5LXiZsrYCgrVoHtqSBXd35133D2Zucy1vrT3IwNZ9PtiXz3d405lwXyn2jujWrXZOlNabGXkqBjDri360QltbV05E7PIO5Y1gwBoPCyQvF7DqVw65TOexNySO3tIpfj2Tw65EMAII9HRl1sZQjOtQLz3omkappK+fl5cXrr7/O+++/z9KlS3F2duYPf/gDs2bNYsiQIeh0OrRaLZ6entjZ2ZGUlMTAgQPNtpWdnc3UqVPx8GjamCyVUpNW7SCioqIYOnQoH330kWlZ3759mTFjRp0DAefPn8+vv/7KiRMnTMv++te/EhsbS0xMjGnZ22+/zeLFi1m/fj0jRoyodz8qKysJDQ3loYceavAMikVFRbi5uVFYWIirq2uD7tNWyqv0/OHDXZy8UEx0Dy++eSCqznnt6xO3aw39Nt4Fn5XWHVwGacz6EANcMHiRMar1sqqmYCNRZyy3qBkQOMYYvB8Z+UGtfdHrdOQu6ol3UlbdQcdMR7J7+uL9cmKbZa1qAgKfywMCgzEgGDDhbosF0005fu2Noij8LyGLt9efJCHTOMDE29mOx8eHcefw4AbX97WUmr/HLklZ5jX2F9X191hz3kjU1TkQtiOct2vpDH+3QrS0Kp2B2LMFpiA69mwBuivKNfoFuJoGIA7v5omDbcM6jxUXF+Pi4lJr+dGjR5k6dSoTJ07kww8/xMnJiQ0bNjB58mQiIyNZs2YNPj5Na83a4YLmlStXMmvWLP75z38SHR3N8uXL+fTTT4mLiyMkJIQFCxaQnp7O119/DRhbzkVERPDwww/z4IMPEhMTw5w5c/j+++9N3TPeeustXnrpJb777jtGjRpleixnZ2fTZYCnn36am2++meDgYLKysli8eDHbtm3j2LFjhISENGjf21PQDHAqq4Tp/9hJWZWeJ8aHMW9S70Zvo6HBZdbE96gszGz1y6NNCTZqWHPQca2AQNVLS6HBGXdNiWn9mmC6sfvbnOPXHhkMCr8ezeD/NiSSlmd8vkEeDsyb2IsZgwKb9MXSEhr65TRu4ndmg7Lq+mLV2l9a20Jn+7sVorWUVOrYl5LLzqRcdp/OMSUZathq1AwOdmd0mDcjw7wZGOSGVtP4pMPnn3/O4sWL6d69O6Ghofz4448UFBSwdu1as+4cjdXhgmYwTm7y1ltvcf78eSIiIli2bBljx44F4N577+XMmTNs3brVtP62bdt46qmnTJObzJ8/32xyk27dupGamlrrcV555RUWLlwIGBtmb9++nZycHLp06cKIESN47bXX6Nu3b4P3u70FzQA/x6bz5IpYVCr4133Dua5Xl0Zvw5qDy6YGGzWsMeioLyBQ7nSAEC2qb8rgQvOya009fu29jrRKZ2DlgbN8sDmJ7GJjvX4vX2eentSbiX19m93ftLEO/LacyAPPwBtFxoG2V7IFFrhyIPJtIm96yOym9n4umqK5r3shRMNkFVcQczr3YiY6l/SCcrPbXey0RPXwYlSYF6PDvAnzcW7w++e+ffv47rvvSE5OJioqihdffLHZ8VWHDJrbq/YYNAO88NMxvt2bhqeTLWueGN2kWYOsMbiE5gUbNawt6GhwScy/Ss0HXzYhu9aU43etspH2lt0sr9Lzr91n+HjrKYoqjF0qBge78+zk8GYNoG0sCQIbxxKveyFE4yiKQmpuGTsvlnLsPp1LYbn5C9DHxc5UyjEqzKvB8Yal4quOnS4QreKlm/oSe7Hx+ePfHeb7h0Zg08jLKdbaA9MSA/qsrQ9pgwdfuph/m7+yN++VMzgCtUpoGnv82vMsdHV9OXKw1fLX60O5KyqY5dtP88XOMxxOK+DOT/cwpqc3z04Op3+QW4vvmwzsaxzpHiJE61OpVHTzdqKbtxP3jAhBb1A4kVHEzlM57D6dw76UPLKKK/npcDo/HTZ+jvXo4sSoUGMQHd3DCzfH2nNrWHQfJdNsPdprphkgNbeUmz7YSXGljofH9mDBjX0A68uyNlZ7GNDXWE3NNF+eXdPY2Jlng/UKaC4F2ZcPKGzo8QPabR1pQ7PjWcUV/ON/p/h+XxrVeuNb7439/Zg3sTfdPe1b9LVizWVQ1qYjvu6FaO8qqvUcSstn1ylje7tj5wq4fEyhWgX9A91MmeihIR7Y2xi/4FoqvpKg2Yq056AZYO2x8/z120MAfPbnSLzOrusQl9k7WrBRX00zMx2MmbS/l8Dl7w4Xg+mYrg8RlbbcOIjwrM44a2OiDnZU1dlhAGjQ8WuvJQRN6bKQllvGsk2J/Dc2HUUBNQo3qWN4zuY7AlTG10tLvFastQzKGtV63Wfrob8NhsG24K/hcNQyht74l7beTSE6rcLyavYkG3tD7zyVw+nsUrPb7bRqIrt5MCrMm0G+tozqGyJBc0di7UFzQ7LGr/4ax5e7zmCvUfhO/RKDTyV2iHZNHS3YOLz+KwbtfgJVUrVZsMsYW+iphR/Ka01dXpNdAwM+SdmoVpbB487G+64or/UYl2fjjm7+tt7j1x7rSJvbZSEhs4iXvtnE/hxjv3ZbfRVjUg7xfNxXdB+U2yKvlfZ+9ac1mb3ur3I1pT2+/oXoiDILK0yt7XaeyiGr+NKkaYbKMs6+d7sEzR2JNQfNDb38XKUzMOH/tnI2vxwHQwW7P7gXj8oSs221xqXNqooKDq56G1V+CopHd4be8gy29k2bgKVGRws29i27g+F5a80CAYoN4KwyZo53VtXKCu8JfpiRZz8xZoO1wL1ODc4M13f82mOmubn7XBN0n0114+2qO9gTcnHSJEXhT8f/xxOeP+HQXSVlAG3o4O9fMmTvXJB+zUK0G4qicDq7hJ1JOew6ncuuE2nEL71FBgKKlteYwVm2WjWPhZfzXIyBcrU9T05/mi9+XIRWMZi2d+WAMkuL+ecjDE//jmjNxe+DOaB//f+ICbyL6DkfXfvO19CSA/raIiBXhY6DwnXwTSk4qKBYgTQ99NbCJHuzSWVqpum2ra6Esxj/Bnpf3L8GThVe3/Frj4PVmjtdes008j6bz/J9+hH+PehG3hj/Fyps7FndfwL/NVzPVN1+bli/nj9Os44vCp2JXqej655FkKQzv5KQrke9ogzDTEcClFfRT7hbvtQIYUVUKhVhPi6E+bhw76ju5OWH4bW0+duVV7m4Jr1OR+Cuhaga8aERqknnM5tveLTsSbb3iOTliX/l9Q0fYspnXgwkik5s5ICFg8SYfz7CiPPfwCnzGlv1GFtGqL8h5p8QPecjq8oaX2uq3sbMzNfY5+To1dX4nwrg9GWlGAk6OFkCQ21gmgMxoU/h3G0I+sJMqgsvGNfx0RiD7Jr/W6DDgEarJX3UQrxVT2CY6Vhn/XNrTp3eEM3tsnB50K0C/hz7O3fHrmVT2HC+GzyVbT0iWWMYwZodsDI9hofHhnJ97y6t3ue5s6r5UsOOyjpvb+kEgBDCMpoyQUqd27HIVkSH1ZQPDQePQCI1R3h/17vMue45vhs8la6Fmfx17yrjnYbZgl4hOv1LqIkZ1je/PrCqooLh6d/BKR2qy2ts0/WoVpSjzHRgmOE7Dvw2hOB9r9cZpLb2Zdb6svhFO5+n3+Uz811lP68VeF/tOdVkdruM0dWux1VACbOhQO9Mj6R/4Xt6mekmvV6FeoydsaY532Csg66rprkJmeHBk2dzGAhUFuLT+9Jzqcl0W9tl8OZmx+sKujUoTD61l8mn9hIf0YNPb76Nn5Ux7EnOY09yHr18nXlwTA9mDAps8+m5O7rmXkkQQnQsEjSLa2rKh0ZNIDGxeywvb/6UV294mKXX30dAUTYzlN0oF7stqC7LBFuiD+/BVW8bSzJ2VNV5u2pnFdreNgzZ/zer6AN8zSx+bBVKLw1up/LNMuZ17WdTextfntlV6sjsqnppcaMEVaL5dlVT7aGXBuUOR1QHq4zdM2Y61FkD3ZTMsLX27K5Lc7Pj9QXdvSMyma/9gaeeeIGv957l+31nSbxQwjM/HuWdDSe5b1R37ooKxtW+ZXuTdlbSr1kIcTnr+xQSVqUpHxqXBxKz2cy5eD8+7zODZ6Y9ha+mnKjE47UywZaoD1Tlpxj/U9+kHQUGq6hPvGoWXwVMsjcGq/UcJ6DR5TOXu1Zm185Qidupgtrb/awUwwNOKGE2aGrqmsO00NvG7P7NyQxb24Qw19Kc7HhDg+7B3i68MK0vj43vyff70vhiZwoXiip5c20C//jfKe6KCua+Ud2aNBunuLr2WGcvhGg5EjSLa2rqh8blgcQLqh/IqPZjLVE8xNOsPvIsYaTW2lZz6wMVj+6QQ70Bvjqhrn5mrV+feNUsfrAGPNSwqnbJA4B6l3E/Y758Bhw9iW5mzWVdmV2DQU//zbOuvt11FcaezT2fxsbNt84ZAa0xM9xSmpMdb0zQ7eZgw5zrQrlvVDd+js3g0+3JJGWVsHx7Ml/sTGH6oAAeGtuDcD/r6r7TXrXHOnshRMuRV7q4puZ8aNQEEvF713NPTjqnDhWQVOnOvde9xOq0p/EpLTC/QzPrA4fe8gz61/8P9Rhb80z2RcpoW1R6BbbVHQi2dn3iVbP4NdNX15UxD9fCZGPrvOj0Ly4tb2bN5ZWZ3QO/LW/Qdm3cfK2mZ7IlNWWgaHOy440Nuu20Gm6P7MqtQ4LYmpjFJ9uS2ZuSx+pD6aw+lM71vbvw0NgeRPfwkkGDzdTadfbWNEhZCGFOXomiXs29/FwTSLzqsobnN2Zyxs2P+295hZXfP4dj9WUBbDPrA23t7YkJvIsR6m9QZjqguqzGVhltC720oFKBt3XUJ141i1/TlcJXAxqMQXSxAo4quM3B2EP5x3Ljcxto7HBh6ZrLzlzL2ZRBlZbQlKBbrVYxPtyX8eG+xJ4tYPn206w7nsnWk9lsPZlN/0A3Hhrbg6kRfhYbPd4ZtVadfVv97QkhGkYmN7Ei1jy5CTQ/A6LX6Yh9NZoHK+aRp3Flwql9fLJ6samHs6UmPanp06zRXPrT1ulV7A+4k9Dz6/BOyqq71KQVJl25Up1TdPtqUGY5ggFUdpdlCasV4+2fXbbvKuBxZ5QsfZ3Z9aY+p5pJN0zHSoWxbORiAG+Itmv1Y9UamjIltrVJzS3lsx0p/OfgWSqqja+trp4OPDC6B7dFBuFo23HOV0fSEf72hLBWloqvJGi2ItYeNFvC4fVfod/5d+6ufIFKtS2zYn9jUdynKKMt+8FwtRkB6wxSLys1aYsPprpmW1QUILHarMMIY68yxXW4Fm53gCTz3tTNfU6mY5WhR+2iAtdLmUpFr7An8J5mTRZjbZo7JfaV22rrS+y5JZV8HZPK1zFnyC8z1vG7O9rw5xEh/HlkN7yd7Vp1f8TVWfJvTwhRmwTNHVBnCJrBGIwl7viJ53T3o6Dmz5r1PKr5jYxRrdOHt64g9YLBq9Uevy41QVZZThqhB17H41R+nR+ezLxYivH3Erj8lRuhhT84mE2JbYnnZJws5ltUidVmAbkyxg6lg2W/LDWNd0OnnG8t5VV6fjx4lk93pJCWZ/ybstOqmT4wgFsjg4jq7tXq+yTMtccp5IVoTywVX8lXVtHqBk+ezYAJd3Pqu/V8egK+1k9GN/QB3pg8oNUe39r6ANfUs8btWoOnpviqXSvYWWWc3jpYA6mXfbgWKKBRmbpZWOI56XU6QjPWGjPYtSaLKUPpYFMIW2Iii6b2zG5JDrYaZkV3466oENYdz2T59tMcOVfIfw6e4z8HzxHk4cALN/ZhQh9fmSyljcgkKkK0D+3/k060SxqtlgX33Mj2D3ZwMrOY7/adZUCQOzOHB7fa41tjxqahH56mDhsX1bT+G37HAosFsJ1tCuHmDn5sypTzrUmjVjFtgD839vdjb0oe81bGklFYwbn8cv767SHcbPTcEKzhrzePJszPrdX3rzPrzANvhWhPJK0g2oxarWLN46O5McLY4/e51cf4957a/Zs7E7MPz7rULLdXgS0QpMEw09HY+m/UKxYNxjpb9is8ajJZBk/jwKs6GEbbceEaE1kk7F2PjzrPOIirDuqdlfiqc0nYu95i+9wUKpWKET282L1gAi8OKGSWagNdyKewWsOq03DDezu5ccl/+enwOSqqr3LuhUU1929PCNE6JGjuxPQ6HXG71nDgt+XE7VqDXqer/04WptWo+fDuIdw/ujsAL/33OP/aldLq+2Et6vvwVEbboderjG3mFrjC/U5k9/RtkdrihgbwHSX7VdOTnF5a4xeRIE2jvpi0ty8Zh9d/xV9O/pVFZz4j5tu/sPzn15hwbh9qxcCJQhueWnmEYa9v4uWfj3Mio6itd7dDa+7fnhCidcgrsJOypn6gKpWKF6f1QatR8cm2ZBb+egKdQeGBMT1adT+sQUMmk4mNWoa9m0+d9diW7NpQ00e6yxhd3SP6O+AUws3pSd6eLrFfWUqiBSaxl0kJeznv4sV/7prK9+4TOV/hdbEDRyoDgtyYOSyYmwf642JvU+9jiMZp7UlUhBCNJ90zrEhrdc+w1n6giqLwfxsS+ceWUwDMnxLOX68PbfX9sAZN6fBh6a4Nh9d/Rfedz+OuLrZ4Oztr15QvH7V6W1/BmtqGNaRbg+Evznw3+FtiyvzZEJdJtd74UeFoq+GmAf7cMSyYIcHuMuOghVlDu0IhOhrpniGaxJoHK6lUKv42qRdajYr3NiWxdF0COr2Bxyf0bNX9aAtXflAOmHA3NKLDh6W7Npi2d0oHZ3UQaWvs2nFRod6ZMyPf6JABMzRtoGhzppxvbQ0pJVGrFMK16dxz1zRySyr56XA63+9L43R2KT8cOMcPB87Ry9eZO4YF86fBgXg42bbeE+jArHWQshBCguZOx9o7IqhUKube0AutWsU7GxL5v42J6AwKc2/o2WEzWs0tlbH0F6E6t7e7yjQjoGGYHVVBtsbAXphpL5fYG1tK4uVsxwNjenD/6O4cTM3n+31nWXMsg8QLJbz22wmWrk1gcoQfM4d1JbqHF2p1x3ytCiE6NwmaO5n2MljpsfE90WrUvLk2gfc3J6EzGHh6Uu8OFzhbIkNs6S9CdW5PwdQXWl2g4Ht/XodpNWdp1tgH/Eo19ereY3R1l5JcpV5dpVIR2c2TyG6evDK9Lz/HZrByfxrH04v49UgGvx7JINjTkTuGdeW2oUH4uNq31lMSSGmHEC1NXk2dTHsarDTnulC0ahWL18Tz4ZbT6PQKz00N7zCBs6UyxJb+ItRevlhZM2u/xG6JUhJXextmjQhh1ogQjqcXsmJ/Gj8fziAtr4y315/k3Y2JjOvtw53Du3Jdry5oNdKsqSVZ0+BuIToqCZo7maZmmNrKA2N6oFWrWPjrCT7Znky1XuGlm/p0iMDZUhliS38Rak9frETTWbKUJCLQjcWB/Xn+xj78fiyTlfvT2H8mn03xF9gUfwFfVztuG9qVO4Z1paunYws8m86jrmzy0c3fWt1MlEJ0RNI9w4q0dvcMEnV1ZpissSPCN3tSefG/xwG4bWgQS2/pj1rdvjNXB35bTuSBZ+CNIqiuYwVbYIErByLfJvKmh666HUt3bWjI9orDXIn3mYziGcrQW57B1l4uw7dXLXVJ/1RWMSv3n2XVoXTySqtMy8f09OZPgwOZ1M8XJztpXdcYdXfV8cBOqcbtVEHdrSGtqGuLEG3FUvGVBM1WpLWCZmhaS7O2tmJfGgtWH0MBwro48dvjY7C3vcrEG+1AQ9p+cb8TcRO/q/dSv6W/CF1te8pUe/BVo9JcyvTr9Sr2Bd5F9JyPGrx90XlU6vRsOpHFiv1p7EjKMS1XAYOD3fnbpN5EdfeU8o16XLVV6CR71MEai7yPCNFRSdDcAbVm0Aztc9DI/FVHWbn/LABDg935dPYwPNtpqytLZ4gt/UWoru0pigKJOlSX9WxWxthCLy17/O+RwFlc09m8Mn44cJZPtidTpTOYlns52TKpnx/T+vszoocE0Feqea/okpRVO5scoYVbHJt9xUqIjkyC5g6otYNma9PQIP7tdQl8ufsMZVV6gj0d+Wx2JL18Xdpgj5vP0hliS38RqtleSfYZIg++gPpUFaoV5bXWU2Y6oA+zxfBCppRqiHqVV+n4dEcKKTklbD2ZTX7ZpWjP08mWyf18ubG/P9E9vCSApp6rUiEauNdJMs1CXINMbiI6lMaM/H5mSjgzBgdy/1f7Scsr408f7eaDOwcxPty3tXe72ay9r29NF4iYb19Do1GMswLWQbWzCm1vG2JWvU303S+18l6K9sbBVssTFyctqtYb2JOcy+/HzrPueCZ5pVV8v+8s3+87i4ejDZP7+RkD6FAvbDppAH3NjjZpeigwwFhb+L72F1prG9wtRHsmQbNoc03pVdzL14WfHx3NnG8Osi8lj/u/OsDzU/vwwJju7a6zhqX6+rZkyylVfsrFDV67DZ1pPSEayEajZkzPLozp2YXXZkSwJzmPNcfOsz7OGECv2H+WFfuNAfSkvn7cOMCfkZ0sgL5mRxsFOFAFE+xQZjqisuKZKIWo0R7LQ0HKM6xKZyzPuGatHvXX9VbpDLz883FWXKxzvm1oEIv/GIGdtv0OEGyKqw4SGmOZjigx375GdNI79V4Cjun5tGSahUXo9Ab2plwMoI9nkntZBw53Rxsm9TWWcIwK8+7wAXRDxj8UhrlTrbJtV4O7RedU13iZLEPL9hSXmuYOqDMGzZboIKEoCl/uOsPiNScwKBAZ4sE/Zw3F29muhffeOjT3i0dDVFVUoHndz1jTHFMFLiooVoyXhhWpaRYtS6c3sC/lUgY6p+RSAO3mcDGAHuDPqFBvbLUdM4BuyPiHARPubpfZO9F5tHSC52qkpll0CJaYfU6lUvGX0d0J9XHmse8OcSA1nxn/2MVnsyPp49/xv3xYehrtutja23PYJZpBYbug92W9dYsMKMUGCNCw3/8uoiVgFi1Aq1EzMsybkWHeLJoRwd6UmhroC+SUVPKfg+f4z8FzuNprTV04RoV1rAC6oeMfZLCfsFaWmgW3LVnnXolOw5Kzz13Xqws/PTKKB77az5ncMm75eDfv3TGISf38LLnLVqc1pr0+vP4rBpbuhlN6s7pzxtpCTy2xTqOk3ZxoFRq1ipGh3owM9ebV6RHsS8nj92PnWXs8k5ySSn48eI4fLwbQE/v6MW2AH6PDunSIANpS4x+EaAutkeBpafJKE23K0tN6h/k4899HR/HIt4fYfTqXh785yDOTe/PX60Lb3QDBhmrpaa+vlR3g+3KUmY4E9DyJXqez2uyA6Jg0ahXRoV5Eh3qxcHo/9p+5FEBnF1ey6tA5Vh06h5MWJkUEcNPAAEb39G7XYx5qOtoI0d60RoKnpbX/r96iXdNotaSPWgi9tBhmOhprmG2BII3x915aMka90qhgzN3Rlq/+Mpx7RgSjKPDWupPM++EIFdVXeaG2c+FRk8kyeBprwupgGG3HhTq+eOh1OuJ2reHAb8uJ27UGvU5X5/0T9q7HR51nrD+rg3pnJb7qXBL2rm/eExGiGTRqFSN6eLFoRgQfD03nn9plzNasx4d8SnXwU2wG9391gMjFm5i3MpZNJy5QqeuY7wnC8hr6fimuzizBU5dmJnhag6SFRJtriV7FNho1i//Qn96+Liz89QQ/HU4nJaeUj+4eQoC7gwX3vvVcrUVPzRcPb9UTGGY61jlI6MqWU41pT9cRsgOiZVhj26jD679iSMwTqE7rmLJjK69k/YMD/SJYEz2Wda5RXKjwZPXhdFYfTsfFTssNF7twjOnpjb1N+81Ai5bTku08OxNLX1luC9I9w4p0xu4Zl2upD+Bdp3J45NtDFJZXo1GrePNP/bktsqsF9rj1NKRFT0On0W7s6OWGdjiJ6foQ0fe/3QLPXlijtmgbVZ/6OsnoZjqxOXQEu4ctY13cBS4UXbp6olGr8HO1Z1Z0CH8aHIiPqwxqFW3X7aGjsvQsuA0lLec6oM4eNLek5OwSpr6/g0qdAYBHx4Xy5IRe7WJwUGPetOv74tGU9nT19YhlpgNKNy2KrUo+QDoJaw0kGtPCsk/0jRxKy2fNsfOsOXqerGLz8qNwPxeu62WcdCWym4dkoTuh1mjn2Rk1NMFjSRI0d0ASNLess/ll/OXL/SRllQDQL8CVZXcMopevSxvv2dVZ+k27qX2xL83aWI1qR9Wl7hmjbaGXFn4oxzDIVj5AOgFrDiQO/LacyAPPwBtFUF3HCrbAAlcORL5N5E0PmRZXVev54cA51sVlUlRRzbH0Qi7/ZLS3UTOihxdje3ZhbK8uhHZx6rADi8UllphHQNSttUu7pE+zEI3U1cORjfOu4/dj53n+p2PEZRRx09938uzk3vxlVHfUauv7ELR0i56m1icPnjyb3efiGGn4J/S6rE9zvgF+KIcEHeoSxerbBV2NNdbmWitrbhvV1E4ytjYa7okO4Z7oEADySqvYkZTN9sQcdiRlk1VcydaT2Ww9mQ1AoLsDY3p6M7ZXF0aFeuPmaIPoeGQ8R8tpr11g5FNBdDo39vcnMsSDZ1cdZevJbBaviWdT/AXeuW0gQR6Obb17Ziz9pt2c9nS2vmFwVgXflIKD+YyATdkXayGDfBrHmgMJSw008nSyZcagQGYMCkRRFE5eKGZ7ojGI3ncmj/SCclbsP8uK/WdRq2BQV3fGXizlGNTVHY0VfgEXjdfS7TxF+yNBs+iUfFzt+fLeYXy3L43Fv8WzJzmPqe/tYOH0fvxpSKDVXHq19Jt2c4IK02NUAKfraLfUDj9ALpWd6MwmbfEeo8Nb9QSHQQLnK1hzINGUTjL1UalUhPu5Eu7nykNjQymv0rMnJZftidnsSMrhVFYJh9IKOJRWwHubknC11zK6p7eplKO9dusRHaPbg7AsqWm2IlLT3DbO5JQy74dYDqUVADClnx9v/Kk/nk62bbtj1D8Iryn1o00dvdwS+9KWrLk215q1h7+D1hxolF5Qzo7EbLYnZbMzKYeiCvMvlGE+zozt2YUxvbwZ0d0LB1sZUNietFW3B2FZMhCwA5Kgue3o9AY+2Z7Mso2J6AwK3s52vHVrf8aH+7b1rrXIm3ZTg4qO9AEig3yarj38HbRFnbpOb+DIucKL9dDZxJ4twHDZJ6ytVs3wbp6M7WWsh+7t62I1V7XE1bVFtwdhWRI0d0ASNLe94+mFPLUy1tRh487hXXlxWl+c7Np+wgZLv2k3NajoKB8gTe20IIw6yt9BSyosq2bX6ZyL9dDZZBRWmN3u42LHmJ5dGNvLmzE9u1jF1S1RNxks3L5J0NwBSdBsHSqq9by9/iSf70wBINjTkXdvH0hkN8823S9retO2pn1pKsk0N19H+DtoLYqicDq71BhAJ2WzJzmXimqD6XaVCvoHuplqoQcHu2Ojsf4+8kK0BxI0X8NHH33E22+/zfnz5+nXrx/vvfceY8aMuer627ZtY968ecTFxREQEMCzzz7LnDlzzNZZtWoVL730EqdPnyY0NJTXX3+dP/7xj8163CtJ0Gxddp/O4ekfjpBRWIFaBXOuC2XuDe1jQhRRv/ZQmys6ropqPQfO5LP9YilHQmax2e3OdlqiQ70Y26sL1/XsQrCXdXX2EaI9kaD5KlauXMmsWbP46KOPGDVqFJ988gmfffYZJ06cIDg4uNb6KSkpRERE8OCDD/Lwww+za9cuHnnkEb7//ntuueUWAGJiYhgzZgyvvfYaf/zjH/npp594+eWX2blzJ1FRUU163LpI0Gx9iiqqWfhLHKsPGdtn9fU3TojS2896J0QRDdceanPbO8lGN0xWUQXbk4ylHDtP5ZBXWmV2ezcvR1Nbu+hQL5zbuGRMiPZEguariIqKYsiQIXz88cemZX369OEPf/gDS5YsqbX+/Pnz+eWXX4iPjzctmzNnDkeOHCEmJgaAO+64g6KiItauXWtaZ8qUKXh4ePD999836XEBKisrqay8NEFAUVERXbt2laDZCq07fp4Fq4+RX1aNWgXjw334x51DsJeR8FarocGa1Oa2nLqObZbBcj2wO2pAbjAoHM8ovFjKkcOh1Hx0l40otNGo8HC0pZevC/eMCGZMzy5tPu5CCGsmMwLWoaqqioMHD/Lcc8+ZLZ80aRK7d++u8z4xMTFMmjTJbNnkyZP5/PPPqa6uxsbGhpiYGJ566qla67z33ntNflyAJUuW8Oqrrzb06Yk2NCXCnyEhHjz67SH2n8lnU3wW497ZwsIZEUzq6ysj4K1MYyYsGTx5NvoJdxN3RfDlq9V22KCsNbR0D+yOPCmNWq1iQJA7A4LceWx8T4orqok5nXuxlCOHtLwysoorySquZOepHNQq6OPvytAQD4aGeDAk2IMgDwd5XxLCwjrUu39OTg56vR5fX/M2Yb6+vmRmZtZ5n8zMzDrX1+l05OTk4O/vf9V1arbZlMcFWLBgAfPmzTP9XpNpFtbJx8We7x8cwbOrjrL2WCbniyp5+N8HGdHDk5du6ku/ALe23kVB04K1uqZ07chBWUvT63QE7lqIKkln3gM7XY96RRmGmY4EKK+in3B3k76EdLZJaVzsbZjUz49J/fwAOJZeyMdbTxF/vpgqnYH0gnLiMoqIyyji65hUwNiZwxREh3jQL8AVO61cGROiOTpU0Fzjym/XiqJc8xt3Xetfubwh22zs49rZ2WFnZ3fV24X10WrUvHv7IBbN0PHx1lN8uiOFPcl53PT3ndw2NIinJ/XGx9W+rXez07JUsNbZgjJLS9i73vhlY0dlnberd1bi2zuXuL3rG92ZpKUD8vagf6AbH9091PT7+cJyDqUWcDA1n4Np+cSlF5JVXMna45msPW5M3Nhq1QwIdDMF0UOCPejiIp8/QjRGh3pH8fb2RqPR1MruZmVl1coC1/Dz86tzfa1Wi5eX1zXXqdlmUx5XtG/OdlqemRzOncODWbruJL8eyeCHA+f47eh5Hrk+lAfG9MDeRrI6rc0SwZoEZc1Xnm8cOEtWHa38LltuWq8RWjIgb6/83RyYNsCBaQP8AWNnjqPnCo1BdGo+h9LyySut4kBqPgdS8033C/FyZGiwMYgeGuJBL18XNGop6RDiajrUO76trS1Dhw5l48aNZu3gNm7cyIwZM+q8T3R0NL/++qvZsg0bNhAZGYmNjY1pnY0bN5rVNW/YsIGRI0c2+XFFxxDk4cjf7xzMvSO7sXjNCQ6nFfDOhkS+25vG/KnhTB8YYLV1hR2xXtcSwZoEZc3n4BFo/I+Ppu4e2D4a8/UaoSUD8o7C3kbD8O6eDO9u7C2vKApncstMQfThtHxOXigmNbeM1NwyVh82HitnOy2DurqbgujBwe642tu05VMRwqq070/IOsybN49Zs2YRGRlJdHQ0y5cvJy0tzdR3ecGCBaSnp/P1118Dxk4Z//jHP5g3bx4PPvggMTExfP7556auGABPPvkkY8eOZenSpcyYMYOff/6ZTZs2sXPnzgY/rujYhoZ4sPqvI/nlSAZL1yaQUVjBkyti+XLXGV66qS9DQzzaehfNdNR6XUsEaxKUNV941GSy1nviPUZXdw/s0XZkG7wIj5rc6G23ZEDeUalUKrp7O9Hd24lbhwYBxnaasWkFpkz04bQCSip17DyVw85TORfvB718XExB9NAQD7p5OVptIkCIltbhguY77riD3NxcFi1axPnz54mIiOD3338nJCQEgPPnz5OWlmZav3v37vz+++889dRTfPjhhwQEBPDBBx+YejQDjBw5khUrVvDiiy/y0ksvERoaysqVK009mhvyuKLjU6lUzBgUyOR+fny2I5mPtp4m9mwBt3y8m5sHBjB/Sm+CPNp+goKOXK9riWBNgrLm02i1pI9aiLfqCQwzHevsgZ0x8hV8m3BloyUD8s7E1d6Gsb2Msw8C6A0KiReKjUH0xdro1NwyTl4o5uSFYr7fZ/zc9HSyZUjwpSB6QJCblKKJTqPD9Wluz2Ryk44lq6iC/9uQyA8Hz6IoxoE4D4zuziPjwtpsYoKaWfC6JGWZ1+te1BFmwWvuhCUyU6DlNLUHdn2lQzIpTevILq7kUNrFIDo1n6PphVTpDGbraNUq+gW6MTS4plOHO/5uDm20x0LUTSY36YAkaO6Y4jIKWfxbPDHJuQB4O9vx9KRe3BbZtdUH3cTtWkO/jXfBZ6V1Z1GDNHC/E3ETv2vX9brNnbBEgjLLaWztfEMnRJFJaVpfpU5PXEaRKYg+mJpPVnHt2v8AN3uzko4+/q7YaNRtsMdCGEnQ3AF15KC5Iw46awxFUdh44gJv/B7PmVxj9rKPvysvTevDyDDvVtuPA78tJ/LAM/BGEVTXsYItsMCVA5FvE3nTQ622Xy2huX9zEpS1PlPpUKIO1WWlQ4YxdX9Z6ezvK21NURTSC8rNSjrizxejN5iHFfY2agYGuZtNvuLhZNtGe905JSUlcfDgQYKDg+nfvz8uLi5tvUutSoLmDqijBs0tPZVue1KlM/B1zBk+2JxEUYUOgBv6+PL8jeH06OLc4o/fWTLNliJBWevpDKVDnUFppY4j5wpM2ehDaQUUltf+ht6ji5OppGNoiAehXZxRS7u7FvPVV19x3333oVKpUBQFd3d3oqOjmTVrFnfccUeHH9wp02iLdqEjDzprClutmgfG9OCWIUG8tymRb/amsSn+AltOZtE/0I3/u30goS0YPMsgqsapa6ZA0TKk1V/H4GSnZWSoNyNDjVfQDAaF5JwSUznHwdR8TmeXknzx338OngPA1V5Lv0A3NGoVo3p48cchQfi62nX4YK416HQ6MjMzcXFxYcOGDdjZ2REbG8uKFSt48sknKS8v57777jO7z6pVq/D39ze11hVGkmm2Ih0t0yyZo/qdyirm9TXxbDmZDRhbPM0cFswDY7q3WPAs9brCGnWm0qHOLr+0isNnLwXRR84WUl5d+8qXu6MNffxcCfd3oY+fK338Xenp6yzdOhqpuLiYxx9/nF27dnHw4EFTfBEbG8vNN9+MSqUiOTkZtVqNWq0mLy+PiIgIPDw8iIuLa+O9twzJNAurJ5mj+oX5uPDlfcNZtjGRT7afpqLawPf70vh+Xxo39PHhwTE9GN7d06LZlsGTZ3MYCFQW4tP7UslMtsGLjJFSryvahrT66zw8nGwZH+7L+HDjjLk6vYGEzGJWHzrH+rgLlFfpKKzQUVBWTUxyrmkQNYBaBT26OBPu50Iff1f6+LsQ7ueKv5u9ZKWvori4mKSkJMLCwrC3tzctDw8P5/rrr2fbtm0cOXKEoUONU7OfO3cOOzs7U5ZZr9ej0cgXFZCgWbQgmSSi4Z6a2IsnJ4RxMK2A5duT2RR/gU3xWWyKz2JgkBsPju3BlH5+aC00An3w5NnoJ9xN3BX1uk3pmyuEJUjpUOel1aiJCHQjItCNl2/uBxinAj+VVUL8+SLizxeTkFlE/Pki8suqOZVVwqmsEn47et60DTcHm1qBdC9fFxxsJdjLz88nOTmZOXPmYGt7aQBmUVERKSkpdOnSxWxgYGJiIgUFBYSHh7fF7lo1+YQULUYyR42jVqsZ1s2TYd08OZ1dwuc7U1h18BxHzhXy2HeHCfJw4C+junPHsK44WaDPs9TrCmvSkhOiiPbH3kZjCqRrKIpCVnEl8eeLSMgsNv48X8zp7BIKy6vZm5LH3pRLV8/UKujm7WQs8bgYUIf7uxDo7tCpstIZGRmUl5dz/vx5U8a5uLiYRYsWsXv3bpYuXUr37t1N6ycmJmIwGOjbty9ApzpW9ZGaZivSUWuaZZKIpsspqeTfMan8e08qeaVVgHHAzN0jQrh3ZDd8Xe3r2YIQ7Yu0+hONVakzZqUTzhebBdS5F98zr+Rir71UK+1vDKh7+7ngaNsxP4e+/PJLHnjgAby9vcnPz0dRFHx8fFCr1fztb3/j0UcfxcbGBoPBgFqt5r777mPt2rXExMTQvXt3FEW5auCs1xsTYiqVCrW66VdCS0tLiY+Px9nZmd69e1s8UJeWcx1QRwuaQQadWUpFtZ5Vh87x2Y4UUnJKAbDRGKftfnBMD3r7da6em6Jjk1Z/whKyiitIMJV2GAPp09klVOtrhz0qFXTzciLcz1ja0ediQB3k0b6z0lVVVbz66qt89NFH7NmzBwcHBw4cOMCSJUtITU1lw4YNDBo0yOw+48eP58KFCxw9erRJtcw1gTQYr6Be6/jVBOQnT55k+vTpJCUlodVq8fT0JCIigt69e/Pggw/W2sfGkoGAol2QQWeWYW+j4e6oEO4cFsym+At8uiOZ/Wfy+fHgOX48eI7renXhobE9GBnq1a7f4IUAKR0SluHjYo+Piz1je3UxLavSGTidXUJCprG048TFzHR2cSUpOaWk5JSy9nimaX1nO60xkDZlpY2ZaUuUyLWG0tJSEhIS6NatG8HBwTg4OBAcHEyXLl2YMmUKCxYsYO3ateh0OrRaLRkZGWRkZNCjRw80Gs1Vs8yKovD222+zceNGhg0bRnR0NEOGDCEwMLBRgXbNtouLiykoKGD+/PnMmDGDuLg4jh49yubNmxk2bFidQXNWVhaOjo44O7f8HAc12sdZF+2aDDqzHLVaxaR+fkzq58ehtHw+25HMuuOZbEvMZltiNn39XXlwbHduGhBgddPWSvZQCNHWbLXqi4MFXWHwpeU5JZWmrPSJi7XSp7JKKKnUcSA1nwOp+WbbCfFyvFQnfTEz3dXD0eomaCkqKiI1NZV+/fphZ2dnWj5mzBhuueUWfv/9d44cOcLAgQMBSElJIT8/n169egFgMBjqDIINBgPDhg0jLi6OLVu2sHz5cvLy8rCzsyM4OJhBgwYxfPhwoqKiGDJkCI6Ojtfcz4yMDHJzcxk3bhwjRowgKioKg8FQZ+cOg8HAxx9/zPfff8/Ro0dxdHTkrrvuYuHChS1+lV4+sUSrkMyR5Q0J9uCju4eSmlvKFztT+OHAOU6cL+KplUd4a91J7hvVjZnDg3G1t2nrXTXVqfa7fFbI9Z1zVkghhPXxdrZjdE87Rvf0Ni2r1htIzi41K+9IyCziQlElqbllpOaWsT7ugml9J1sNvf1cCL8YlPe5WCvt0obvwZmZmRw6dIjJkyebao5rAtFx48bxzTffcPjwYVPQnJSUREVFhWkQ4NXU3H/cuHGAMfN85swZ4uPjiY2N5fDhw3z++ec8//zzTJw4kd9+++2qWWuDwcCZM2cwGAym7h4qlQqNRlNnwP7666/zyiuvcO+997Jw4UKSk5N59dVXMRgM/N///V+LtseTmmYr0hFrmkXrKSir4tu9aXy56ww5Jcbe2M52Wu4c3pX7RnUnwN2hTfbLNCtkog7VZbNCGsZIXbsQovU196pXXmkVCeeLiM8svviziMQLJVTpDHWu39XT4WI22hhIh/u7EuLZOlnpwsJCVq5cyfDhw2uVOOTl5REeHs6YMWP417/+hYuLCy+88AKffvop//3vfxk5cqRpcGCNmsA3JiaG119/HbVazdixY4mKimLAgAG4ubmZPUZZWRlFRUX4+fldNWguLi7m3Xff5YMPPsDe3p7c3FxGjhzJ3LlzmT59utm6p0+fpk+fPtx1113861//AowzHi5btoznnnuOpKQkevToUesxZCBgByRBs7CEimo9v8RmsHxHMqeySgDQqlXcNMCfB8b0MGvh1NJkVkghhDWpqztLlqH5V710egMpOaWXAumLtdLnCyvqXN/BxpiVvryvdLi/S6tfGXz66afZunUrmzZtwt3dnQkTJrBz507S0tLw9fW96v2ysrJYvXo1W7Zs4eTJkyQnJ1NSUoKLiwthYWEMGTKE6OhoIiMjGTBgwDX3obKykiNHjpCXl0dgYCAnT57kww8/JDExkU8++YSbbroJMGakly5dyptvvsn69esZMWKEKWuekJDAgAEDWLZsGY8++mitx5CguQOSoFlYksGgsC0xm+Xbk81m1BoQ5Mbkfn48PLaHxSZLuZq4XWvot/Eu+Ky07l7dQRq434m4id9J+Y4QokW1xVWvgrIq0+QsCeeLic8s4mRmMZVXyUoHujvQx9+Fnr4u6A0Kw7t5MjLUC8dWGni4efNmjh8/zpNPPtng+1RXV1NYWMj58+c5efIksbGxxMbGEh8fT2ZmJrt27WLQoEHXbF13pdTUVCZOnIivry+//vor7u7uZGdnc88991BZWckvv/yCq6urKWjev38/N910E/fddx9vvvlmrceS7hlCiGtSq1WMC/dhXLgPx84V8umOZNYcO8/Rc4UcPVfIh1tOcefwYGYMCqB/oFuLdN2QWSGFENZAr9MRuGshqiSd+VWvdD3qFWUYZjoSoLyKfsLdFr3q5e5oS3SoF9GhXpf2xaCQklN6KZC+mJVOLyg3/dsUnwXA8u3JAPi52hPi5Ug3LydCvC/+9HIkxMsJZwsG1BMmTGDChAmNuo+NjQ3e3t54e3vTv39/br31VgDKy8spLCzEx8cHuPokKXq9HkVR0Gg0qFQqFEUhJCSEadOm8cknn5CYmMjw4cPJy8sjMTGR6dOn1wp8CwoKqKysNJWHNCZAbwwJmoXoBPoHufHBnYOZPzWch74+QFxGEWVVej7fmcLnO1Po7u3E9IEBzBgUQI8ulmvfI7NCCiGsQcLe9caByDsq67xdvbMS3965xO1d3+JXvTRqFWE+zoT5OHPTZZULheXVJFwMoHefymFHUg6VegN6g0JmUQWZRRVmMx7W6OJiR7eLAfSln8bgui0Hgjs4OODgUP9YmisH7tUEvDqdDp1Oh7+/PwAVFRXk5ubSs2dP07o1gXFGRgZFRUVERESYLbc0CZqF6EQC3R1Y88QYCsuq2X8mj5+PZLDxRCYpOaW8vzmJ9zcnMSDIjekDA7h5YECzZxwMj5pM1npPvMfo6p4VcrQd2QYvwqMmN+txhBDiWtrDVS83BxuiengR1cOL2SO7mZbnl1ZxJreU1NyyWj/zSqvILq4ku7iS/Wfya23T08n2Uob6ip8eTrat+OzqlpeXx7fffssf/vAHAgIC0Gg0qNVqSktLWb9+PWFhYXTt2hUAd3d3SkpKcHZ2Ng1QrBmkeOLECdRqtakLiATNQgiLcXO04Ya+vtzQ15fSSh0bT1zgv7Hp7EjKMZVvvP57PNE9vJgxKIApEf64OTQ+Y6HRakkftRBv1RMYZjrWOStkxshXpGe3EKJFteerXh5Otng42TI42KPWbYXl1aSZguhSzuSWmX5mF1eSV1pFXmkVh9MKat3XzcGmdoba2/jTy8m2RSfKqskmp6am8ve//52tW7cyevRo+vTpQ2JiIp9++inJycl89tlnpvtoNBrs7e1JTk426+hRVVXF1q1b6devH8HBwS22zyADAa2KDAQUbS23pJLfj53n59gMs2b+tho148K7MGNQIOPDfbC3aVwfzLpGrF8weJExSmaFFEK0vJpOPt5JWXVf9eqAnXxKKnWkXp6ZzrmUoc4sqrurRw1nO23dGWpvJ3xc7CwWUBcXF7Nu3Tr++9//snPnTnJzc+nSpQv9+/fnnnvu4fbbb7/0fEpKuOuuuzh9+jQHDx7Ezs64Hz///DO33XYbixcv5tlnn62znlm6Z3RAEjQLa3I2r4xfjmTwc2w6iRdKTMud7bRM7ufHjEEBjAz1anAHDpkRUAjRlmq6Z5Coq/OqV2fqGV9epSctr44MdU4ZGYXlXCsydLDR1DkosZuXE36u9s3qP60oChkZGbi5udU5Pfa6det47LHHGDFiBLNmzWLHjh28//77jBkzhhUrVuDq6ipBc2chQbOwVgmZRfwcm8EvsRmkF5Sblns723HTAH9mDApgUFf3Fr2cJ4QQzSVXvepXqdNzNq+c1NxSUnLMa6jP5ZdhuEbUaKtVE+J5WcmHt/FnNy8nAtwd0FhgQpdVq1bx9ttvEx8fT1BQEDNnzuS+++4jKCio1mQsNSRo7oAkaBbWzmBQOJSWz39j01lz9Dz5ZdWm24I9HZkxyNiBI8zHpQ33Ugghrk6uejVdlc5AekH5xXKPSxnq1Nwy0vLK0F0jorbRqOjqYSzxuLL0I9DDAZsmzBtQWFhYaxbCukjQ3AFJ0Czak2q9gZ1JOfwcm86GExcoq7o0uKavvyt/GGzswOHv1jbTdwshhGg9Or2B84UVnKkp97gYVJ/JLSUtt4wqfd0TuoCxDV+Qh8MVbfOMP7t6OmCnbdw4mitJ0NwBSdAs2quyKh2b4rP4JTadrSezTdkGlQqGd/NkxqBAbuzvh7tj27c4EkII0bpqek1fnp2+vH1eRfXVA2qVCgLcHOh+ZYba24lgT8cGDUyXoLkDkqBZdAT5pVX8ftzYgWPfZY34bTQqruvVhemDApnYxxcH2+ZlDoQQQrR/iqKQVVzJmZzavajP5JRSWnWV3toX+btdNlviZRnqEC9HnC7OlihBcwckQbPoaNILyvn1SAY/x2YQf77ItNzRVsPkfn4MCHLjjmFdcbSVekIhhBDmFEUht7SKMznmPahrBikWV+iuef+a2RL9HBT+ce9oCZo7EgmaRUeWeKGYX2Iz+PlIOmfzLnXgUAFjenpzfW8fRvf0pqePs3ThEEIIcU2KolBQVn3N2RJrGCrLOPve7RI0dyQSNIvOQFEUDp8tYPm2ZNbHZXLlG1AXFztGhXoxMsyb0WHeBLjLQEIhhBCNc/lsifGpF5g/Y4gEzR2JBM2is6mq1rM7OZeEzGJ2ncph/5m8WgNCeng7MTLMi9Fh3kT38MbNsfHTeQshhOi8pKa5A5KgWXR2lTo9h1IL2HUqh52ncjh6rsCskb5KBf0D3RgV5s2oUG8iu3k0ekpvIYQQnYsEzR2QBM1CmCssr2Zvci67T+ey81QOp7JKzG631aoZ1s2DkaHGUo6IQDeLzDglhBCi45CguQOSoFmIa8ssrGD3aWMWevepXDKLKsxud7XXEh1qLOUYGeZND28nGVQohBCdnATNHZAEzUI0nKIonM4uNQbRSTnEJOfWaj/k72ZvLOUI82JUqDc+rvZttLdCCCHaigTNHZAEzUI0nU5v4HhGkbEeOimHg6n5taZt7enjzKiLXTmienjiYi+DCoUQoqOToLkDkqBZCMspr9JzIDWPXady2XUqh+MZhVz+bqdRqxgY5GYq5Rgc7I6dVgYVCiFERyNBcwckQbMQLaegrIqYiwMKd5/OJSWn1Ox2BxsNw7p7MjrMi1Fh3vTxc0UtgwqFEKLdk6C5A5KgWYjWcy6/jN2nctl1Ooddp3LIKakyu93TydY0qHBUqDfBXo5ttKeiKZKSkjh48CDBwcH0798fFxeXtt4lIUQbkaC5A5KgWYi2oSgKiRdK2HnKGEDvTc6ltEpvtk5XTwdGhXozKsyboSEeMlOhlfvqq6+47777UKlUKIqCu7s70dHRzJo1izvuuEO6qgjRiVgqvtJacJ+EEKJdUqlU9PZzobefC/eP7k613sCRswWmeuhDafmczStnRd5ZVuw/C4CtRs34Pj4MDHKnX4ArfQNc8Xa2a+NnIgB0Oh2ZmZm4uLiwYcMG7OzsiI2NZcWKFTz55JOUl5dz3333md1n1apV+Pv7M3LkyDbaayGEtZNMsxWRTLMQ1qm0Use+M3nsSsphU/wFzuSW1bmej4sdfQNcjUG0vxt9A1wJ8XSU2uhWVlxczOOPP86uXbs4ePCg6f00NjaWm2++GZVKRXJyMmq1GrVaTV5eHhEREXh4eBAXF9fGey+EsDTJNAshRCtxstMyrrcP43r78OJNfUnILGL3qRwqdAZOZBRxIqOIlNxSsooryTqZzdaT2Zfua6uhj78xE93X35V+AW709HWW6b9bUHFxMUlJSYSFhWFvf6k3d3h4ONdffz3btm3jyJEjDB06FIBz585hZ2dnyjLr9Xo0Gjk/QghzEjQLIUQjhfu5Eu5nnq0ordSRkFnMifNFnMgo5ERGEQmZxZRW6TmQms+B1HzTuhq1irAuzqayjr4Xg2p3R9vWfiodUn5+PsnJycyZMwdb20vHtKioiJSUFLp06WI2MDAxMZGCggLCw8PbYneFEO2EBM1CCGEBTnZahoZ4MDTEw7RMpzeQklNKXEbRxWC6iLiMQvLLqjl5oZiTF4pZfTjdtH6gu4MpK93vYjAd5OEgg9YaKSMjg/Lycs6fP2/KOBcXF7No0SJ2797N0qVL6d69u2n9xMREDAYDffv2BZDjLYSokwTNQgjRQrQaNT19Xejp68IfBgcCxk4dmUUVFwNoYyB94nwRaXllpBeUk15Qzqb4C6ZtuNprL2aj3UxZ6Z6+ztho1G31tKzeuXPnKC4u5qeffuKLL75AURR8fHxQq9W8++67PProo9jY2GAwGFCr1SQlJeHg4GDKNF8raNbr9aZ11Oqmn4Pq6mqysrIACAgIkEBdiHZAgmYhhGhFKpUKfzcH/N0cmNDH17S8qKKaeLOMdBFJWcUUVejYk5zHnuQ807q2GjU9fZ0v1ki70jfAjT7+LjItOFBVVcWpU6dwdXVl+/btODg4cODAAZYsWUJqairXX389NjbG41QT9KampuLl5UVwcDBw7aC5rlrnmkC6Zpv1Bd0ajYaVK1fy73//mwsXLnD27Fm8vLyYPn06TzzxhGk/hBDWRYJmIYSwAq72NkT18CKqh5dpWZXOwKmsEk6cN5Z11GSliyt0xF0MrP9z8NI2gj0dTWUdxhIPN3xd7TpVFrO0tJSEhAS6detGcHAwDg4OBAcH06VLF6ZMmcKCBQtYu3YtOp0OrVZLRkYGGRkZ9OjRA41Gg6IodR4vRVF4++232bhxI8OGDSM6OpohQ4YQGBjYqEGDNevq9Xr69OnDrFmz8PX1JSEhgeXLl3Pq1Ck++ugjAgICat03KysLR0dHnJ2dm36AhBBNJkGzEEJYKVut2liSEeDKrUODAGPwdi6//LI6aWMwnVFYQVpeGWl5Zaw9nmnahqeT7WVBtDGg7u7thLaDlncUFRWRmppKv379sLO71Dd7zJgx3HLLLfz+++8cOXKEgQMHApCSkkJ+fj69evUCwGAw1BkEGwwGhg0bRlxcHFu2bGH58uXk5eVhZ2dHcHAwgwYNYvjw4URFRTFkyBAcHa89g+Ts2bOZPXu26ffrr7+eXr16MXXqVK6//nrmzp1r9tgff/wx33//PUePHsXR0ZG77rqLhQsXSntSIVpRh3rXzM/PZ9asWbi5ueHm5sasWbMoKCi45n0URWHhwoUEBATg4ODA9ddfb9anMy8vj8cff5zevXvj6OhIcHAwTzzxBIWFhWbb6datGyqVyuzfc8891xJPUwjRialUKrp6OjIlwo95E3vx2exh7F4wgcMvTeS7B6J44cY+/HFwIL19XdCoVeSVVrHzVA7Ltyfz5IpYJi7bTr9X1jPjw10sWH2Mf+9J5VBaPmVVurZ+ahaRmZnJoUOHCAkJMZVf1JRPjBs3jry8PA4fPmxaPykpiYqKCtMgwKvRaDSMGzeOr776ipiYGLKzszl9+jSrVq1i9uzZGAwGPv/8cyZMmMDtt98OGD9frsVgMJj+b2Njw+TJkwkICGDLli1mt73++us8/vjj9OrVi9WrV7No0SJWrlzJyy+/bFYaIoRoWR0q03zXXXdx7tw51q1bB8BDDz3ErFmz+PXXX696n7feeot3332Xf/3rX/Tq1YvFixczceJETp48iYuLi+nS3TvvvEPfvn1JTU1lzpw5ZGRk8OOPP5pta9GiRTz44IOm3+USmhCitXg42TIyzJuRYd6mZRXVehIvFJvKOuIyiog/X0RZlZ4jZws4crbAtK5KBd29nUy9pGsGHXZxaV+zHIaHh/PPf/6T4cOHm5bVZI5nzJjB/Pnz+fXXX7nllltwcXEhKSkJOzs7IiIigNr1zDXlGjExMbz++uuo1WrGjh1LVFQUAwYM4MYbb+TGG280rV9WVkZRUVGD9vXKgYQnT56koKAAX19f022nT5/mtdde489//jNffPEFYJzxsLCwkOeee44nnniCHj16NPIoCSGaosPMCBgfH0/fvn3Zs2cPUVFRAOzZs4fo6GgSEhLo3bt3rfsoikJAQABz585l/vz5AFRWVuLr68vSpUt5+OGH63ys//znP9xzzz2Ulpai1Rq/d3Tr1o25c+eaXVJrLJkRUAjR0gwGhdS8MrMa6biMIrKLK+tcv2aWw8vrpNvzLIdPP/00W7duZdOmTbi7uzNhwgR27txJWloavr6+V71fVlYWq1evZsuWLZw8eZLk5GRKSkpwcXEhLCyMIUOGEB0dTWRkJAMGDGjQvlxeP52WlsasWbOIj4/nhx9+4Prrr6e6upp33nmHN998k/Xr1zNixAjTQMKEhAQGDBjAsmXLePTRRy1ybIToqGRGwCvExMTg5uZmCpgBRowYgZubG7t3764zaE5JSSEzM5NJkyaZltnZ2XHdddexe/fuqwbNNQe9JmCusXTpUl577TW6du3KbbfdxjPPPGPWWP9KlZWVVFZe+qBqaHZCCCGaSq1W0d3bie7eTtw04NJgs6ziCuLPF5t6SZ84X0RKTt2zHGrVKuxs1PTzd2V4dy+CPBwI8nCkq6exK4it1nor/9555x2z359//nmOHz9+zYAZwMfHhzlz5jBnzhyqq6spLCzk/PnznDx5ktjYWGJjY3n99dfJzMxk165dDBo06KqDCsF81sHt27fz8MMPU1hYyIcffsj1118PQEFBAVu3bmXw4MG1ykeKi4vx8PDg7NmzANd8LCGEZXSYoDkzMxMfH59ay318fMjMzKzjHpiWX/lm6evrS2pqap33yc3N5bXXXqsVUD/55JMMGTIEDw8P9u3bx4IFC0hJSeGzzz676j4vWbKEV1999ZrPSwghWoOPiz0+LvZc16uLaVlZlc4YSF9sg3cio5CEzGIqdQZ0lXr2ncln35l8s+2oVODnan8pkL74s+Z3f3d7q+oxPWHCBCZMmNCo+9jY2ODt7Y23tzf9+/fn1ltvBaC8vJzCwkLTZ9HVgtiazh16vZ633nqLRYsWER0dzRdffEF0dLRpvYKCAhITE5k+fXqt7FhBQQGVlZW4ubkBEjQL0RqsPmheuHBhvYHl/v37gbrfoBryRnK1GrYrFRUVMW3aNPr27csrr7xidttTTz1l+v+AAQPw8PDg1ltvZenSpXh5eV25KQAWLFjAvHnzzLbftWvXa+6raBi9TkfC3vWU56fj4BFIeNRkNFqr/3MXwqo42tY9y+Gm+AvsSc7D2U5DQXk15/LLL/4ro6LawPnCCs4XVrD/ioAaQK0CfzcHAj0cTIF0kIcDXS/+9Hezb7edPRwcHHBwcKh3Pa1WS1xcHH/729/YsGED8+fPZ+7cubUSOOXl5eTm5tKzZ0/TsprPpoyMDIqKiq5aiy2EsDyrjyIee+wxZs6cec11unXrxtGjR7lw4UKt27Kzs6962c3Pzw8wZpz9/f1Ny7Oysmrdp7i4mClTpuDs7MxPP/1kao5/NSNGjADg1KlTVw2a7ezszFoiCcs4vP4rAnctpJ/60mQQWes9SR+1kMGTZ1/jnkKI+mg1aqZE+DMlwr/WbYqikFtaxdm8MrNA+vKflTqDaebDfSm1t69Rq0yZ6q6ejmaBdZCHA36u7TeoBuPkKz/++COLFi2ivLycn376iRkzZtS5rpubGyUlJTg7O5tmL6wZIHjixAnUarWpdZ4EzUK0PKsPmmsugdUnOjqawsJC9u3bZxo1vXfvXgoLCxk5cmSd9+nevTt+fn5s3LiRwYMHA8Y3tG3btrF06VLTekVFRUyePBk7Ozt++eUX7O3t692fmpZGlwfjouUdXv8VA3c/gSpJBzsqIUsPPhq8x+jwVj3BYZDAWYgWolKp8Ha2w9vZjsHBHrVuNxgUckorzQLqs3nGn+kXl1XpLwXVe1Pyam1Dq1bh725PkLujWS11TWDt62qPxgoHKdYEvbt37+aee+4BYN68eXTt2pWzZ8/i5uaGi4uLWfCr0Wiwt7cnOTnZrNNGVVUVW7dupV+/fjJ7oBCtqMN0zwCYOnUqGRkZfPLJJ4Cx5VxISIhZy7nw8HCWLFnCH//4R8A4eG/JkiV8+eWX9OzZkzfeeIOtW7eaWs4VFxczceJEysrK+Omnn3BycjJtq0uXLmg0GmJiYtizZw/jxo3Dzc2N/fv389RTTxEZGcnPP//c4P2X7hnNo9fpyF3Uky5JWahWlNW63TDTkeyevni/nCilGkJYIYNBIaekkrP5tTPVZ/PKSC8op1p/7Y8srVpFgLuDMZCuCawvD6pd7Nu080daWhr//ve/OXz4MLt27SIrKwsbGxuCgoIICwtj7ty5TJkyBYCSkhLuuusuTp8+zcGDB7GzM87u+PPPP3PbbbexePFinn32WalnFqIe0j2jDt9++y1PPPGEqRvG9OnT+cc//mG2zsmTJ80mJnn22WcpLy/nkUceIT8/n6ioKDZs2ICLiwsABw8eZO/evQCEhYWZbSslJYVu3bphZ2fHypUrefXVV6msrCQkJIQHH3yQZ599tiWfrrhCwt71xpKMHXW3zlLvrMS3dy5xe9fTb9S0Vt47IUR91GoVPq72+LjaMzSk9u0Gg0JWcaVZIH0uv5xzBcaf6fnl6AyKaWZEyK21DRuNikB385KPy8tAujjbtWhQHRwczAsvvGD6XVEUTpw4wd69e9m5c6dpshKdToezszOPPPIIjz32GA888ACzZs1ix44dvP/++9xwww3MmTOnxfZTCFFbh8o0t3eSaW6eA78tJ/LAM/BGEVTXsYItsMCVA5FvE3nTQ629e0KIFqY3KFwoqqhVS302zxhYZxRUoDdc+yPPVqsmyL1moOKlwLqmDKSLs12rZ3VXrVrF22+/TXx8PEFBQcycOZP77ruPoKAgU9mHEOLqJNMsxBUcPAKN//HRQHodU8v6aMzXE0J0KJqLpRkB7g4M7+5Z63ad3sCF4krO5ZVxto5BiucLK6jSGUjOKSU5p7TOx7DTqs0C6q5XBNbezrYWD6pvueUWbrnlFsA4T0BNmzmoPaugEKLlSNAsOozwqMlkrffEe4wOdV01zaPtyDZ4ER41uQ32TgjR1rQaNYHuDgS6OxBVx+06vbFdnlktdf6l0o/zhcbuH8nZpSRn1x1U29uoa2WoLw+uPZ2aF1RfHjALIVqXBM2iw9BotaSPWoi36gkMMx1R77zUPcMw2g56ackY+Qq+MghQCFEHrUZNV09Huno6ArVbhVbrDWQWVlzWUu/SgMWz+WVkFlVQUW3gVFYJp7JK6nwMBxtNnbXUNT89HG1kUJ8QVkqiB9GhDJ48m8NAoLIQn96X2lVlG7zIGPmKtJsTQjSZjVlQXVuVzsD5wtpdP2oC6wvFFZRX60nKKiHpKkG1k62mzlrqmmVuDhJUC9FWZCCgFSksLMTd3Z2zZ8/KQMBm0ut0JB7YTHlBBg7uAfSKnCBt5oQQbapSpyezsMLYhzq/nIyL/agzCipIzy8ju6Sq3m042WkIdHegoKwKNwcbRoR64+9mj7uDDe6Otrg72uDuaIObgy2u9loJsIXg0ozLBQUFzSpxkijCihQXFwPIVNpCCCGuKuGy//+vzfZCiPanuLi4WUGzZJqtiMFgICMjo9asUJer+bYk2ei2I+eg7ck5aFty/NuenIO2J+egbTXm+CuKQnFxMQEBAc3qOCOZZiuiVqsJCgpq0Lqurq7yIm1jcg7anpyDtiXHv+3JOWh7cg7aVkOPvyU6z0iDRyGEEEIIIeohQbMQQgghhBD1kKC5nbGzs+OVV17Bzs6urXel05Jz0PbkHLQtOf5tT85B25Nz0Lba4vjLQEAhhBBCCCHqIZlmIYQQQggh6iFBsxBCCCGEEPWQoFkIIYQQQoh6SNAshBBCCCFEPSRoFkIIIYQQoh4SNFuBJUuWMGzYMFxcXPDx8eEPf/gDJ0+eNFtHURQWLlxIQEAADg4OXH/99cTFxZmtU1lZyeOPP463tzdOTk5Mnz6dc+fOteZT6RCWLFmCSqVi7ty5pmVy/Fteeno699xzD15eXjg6OjJo0CAOHjxoul3OQcvS6XS8+OKLdO/eHQcHB3r06MGiRYswGAymdeQcWNb27du5+eabCQgIQKVS8d///tfsdksd7/z8fGbNmoWbmxtubm7MmjWLgoKCFn521u9ax7+6upr58+fTv39/nJycCAgI4M9//jMZGRlm25Dj3zz1vQYu9/DDD6NSqXjvvffMlrfqOVBEm5s8ebLy5ZdfKsePH1diY2OVadOmKcHBwUpJSYlpnTfffFNxcXFRVq1apRw7dky54447FH9/f6WoqMi0zpw5c5TAwEBl48aNyqFDh5Rx48YpAwcOVHQ6XVs8rXZp3759Srdu3ZQBAwYoTz75pGm5HP+WlZeXp4SEhCj33nuvsnfvXiUlJUXZtGmTcurUKdM6cg5a1uLFixUvLy/lt99+U1JSUpT//Oc/irOzs/Lee++Z1pFzYFm///678sILLyirVq1SAOWnn34yu91Sx3vKlClKRESEsnv3bmX37t1KRESEctNNN7XW07Ra1zr+BQUFyg033KCsXLlSSUhIUGJiYpSoqChl6NChZtuQ49889b0Gavz000/KwIEDlYCAAGXZsmVmt7XmOZCg2QplZWUpgLJt2zZFURTFYDAofn5+yptvvmlap6KiQnFzc1P++c9/KopifIHb2NgoK1asMK2Tnp6uqNVqZd26da37BNqp4uJipWfPnsrGjRuV6667zhQ0y/FvefPnz1dGjx591dvlHLS8adOmKX/5y1/Mlv3pT39S7rnnHkVR5By0tCsDBksd7xMnTiiAsmfPHtM6MTExCqAkJCS08LNqP64VsNXYt2+fAiipqamKosjxt7SrnYNz584pgYGByvHjx5WQkBCzoLm1z4GUZ1ihwsJCADw9PQFISUkhMzOTSZMmmdaxs7PjuuuuY/fu3QAcPHiQ6upqs3UCAgKIiIgwrSOu7dFHH2XatGnccMMNZsvl+Le8X375hcjISG677TZ8fHwYPHgwn376qel2OQctb/To0WzevJnExEQAjhw5ws6dO7nxxhsBOQetzVLHOyYmBjc3N6KiokzrjBgxAjc3NzknjVRYWIhKpcLd3R2Q498aDAYDs2bN4plnnqFfv361bm/tc6Bt4vMQLURRFObNm8fo0aOJiIgAIDMzEwBfX1+zdX19fUlNTTWtY2tri4eHR611au4vrm7FihUcOnSI/fv317pNjn/LS05O5uOPP2bevHk8//zz7Nu3jyeeeAI7Ozv+/Oc/yzloBfPnz6ewsJDw8HA0Gg16vZ7XX3+dO++8E5DXQWuz1PHOzMzEx8en1vZ9fHzknDRCRUUFzz33HHfddReurq6AHP/WsHTpUrRaLU888USdt7f2OZCg2co89thjHD16lJ07d9a6TaVSmf2uKEqtZVdqyDqd3dmzZ3nyySfZsGED9vb2V11Pjn/LMRgMREZG8sYbbwAwePBg4uLi+Pjjj/nzn/9sWk/OQctZuXIl33zzDd999x39+vUjNjaWuXPnEhAQwOzZs03ryTloXZY43nWtL+ek4aqrq5k5cyYGg4GPPvqo3vXl+FvGwYMHef/99zl06FCjj1VLnQMpz7Aijz/+OL/88gtbtmwhKCjItNzPzw+g1jeirKwsUxbCz8+Pqqoq8vPzr7qOqNvBgwfJyspi6NChaLVatFot27Zt44MPPkCr1ZqOnxz/luPv70/fvn3NlvXp04e0tDRAXgOt4ZlnnuG5555j5syZ9O/fn1mzZvHUU0+xZMkSQM5Ba7PU8fbz8+PChQu1tp+dnS3npAGqq6u5/fbbSUlJYePGjaYsM8jxb2k7duwgKyuL4OBg02dzamoqf/vb3+jWrRvQ+udAgmYroCgKjz32GKtXr+Z///sf3bt3N7u9e/fu+Pn5sXHjRtOyqqoqtm3bxsiRIwEYOnQoNjY2ZuucP3+e48ePm9YRdZswYQLHjh0jNjbW9C8yMpK7776b2NhYevToIce/hY0aNapWm8XExERCQkIAeQ20hrKyMtRq848EjUZjajkn56B1Wep4R0dHU1hYyL59+0zr7N27l8LCQjkn9agJmJOSkti0aRNeXl5mt8vxb1mzZs3i6NGjZp/NAQEBPPPMM6xfvx5og3PQqGGDokX89a9/Vdzc3JStW7cq58+fN/0rKyszrfPmm28qbm5uyurVq5Vjx44pd955Z52th4KCgpRNmzYphw4dUsaPHy+tnpro8u4ZiiLHv6Xt27dP0Wq1yuuvv64kJSUp3377reLo6Kh88803pnXkHLSs2bNnK4GBgaaWc6tXr1a8vb2VZ5991rSOnAPLKi4uVg4fPqwcPnxYAZR3331XOXz4sKk7g6WO95QpU5QBAwYoMTExSkxMjNK/f39peaZc+/hXV1cr06dPV4KCgpTY2Fizz+bKykrTNuT4N099r4ErXdk9Q1Fa9xxI0GwFgDr/ffnll6Z1DAaD8sorryh+fn6KnZ2dMnbsWOXYsWNm2ykvL1cee+wxxdPTU3FwcFBuuukmJS0trZWfTcdwZdAsx7/l/frrr0pERIRiZ2enhIeHK8uXLze7Xc5ByyoqKlKefPJJJTg4WLG3t1d69OihvPDCC2YBgpwDy9qyZUud7/2zZ89WFMVyxzs3N1e5++67FRcXF8XFxUW5++67lfz8/FZ6ltbrWsc/JSXlqp/NW7ZsMW1Djn/z1PcauFJdQXNrngOVoihK43LTQgghhBBCdC5S0yyEEEIIIUQ9JGgWQgghhBCiHhI0CyGEEEIIUQ8JmoUQQgghhKiHBM1CCCGEEELUQ4JmIYQQQggh6iFBsxBCCCGEEPWQoFkIIYQQQoh6SNAshBBCCCFEPSRoFkKIZlKpVI36d7mDBw9y//3307NnT5ycnHBwcCA0NJRZs2axcePGWo9VVlbGG2+8wZAhQ3B2dsbe3p6goCDGjBnDggULOH36dGs9bSGE6FS0bb0DQgjR3r3yyiu1lr366qu4ubkxd+7cOu9jMBh4+umnWbZsGVqtlvHjxzN9+nRsbGxITk5mzZo1fPPNNyxatIiXXnoJgOLiYkaPHs3Ro0cJCwvjnnvuwd3dnbNnzxIXF8ebb75JaGgooaGhLfl0hRCiU1IpiqK09U4IIURHo1KpCAkJ4cyZM3Xe/vzzz7NkyRIGDRrEjz/+WCvQLS8v5x//+Ae5ubm8+eabALz22mu8/PLL3H///Xz66ae1stYpKSlUVlYSHh7eIs9JCCE6MwmahRCiBVwraD516hTh4eG4u7sTFxeHr6/vVbdTWVmJnZ0dADfeeCNr167l8OHDDBo0qIX2XAghRF2kplkIIVrZv/71L/R6PQ8//PA1A2bAFDADeHp6AsagWwghROuSoFkIIVrZrl27ABg/fnyj7nfbbbcBcP/99/Pcc8/xv//9j/z8fIvvnxBCiNokaBZCiFaWmZkJQFBQUKPuN2PGDN566y0MBgNLly5lwoQJeHp6EhYWxmOPPUZSUlJL7K4QQggkaBZCiHblmWeeISMjgx9++IG5c+cyevRo0tLS+PDDDxkwYAC//PKLad3Vq1czceJEPD09UalUddZXFxUV8dhjj9G1a1ccHR2ZMGECCQkJjVqnuLiYOXPmEBAQgJOTE4MHD+bHH3+0+HNfsmQJkZGRuLi44Ovry+23317nc1q2bBldu3bFwcGB8ePHk5iYaLqtIcekvm0IITonCZqFEKKV+fn5AZCent6k+7u4uHDbbbexbNkyduzYQXZ2No888ggVFRXcf//9VFVVAVBaWsqYMWN4/fXXr7qtBx54gJ07d7Jy5UpiY2MJDw9n4sSJlJSUNHidp556iq1bt/LDDz9w7Ngxbr/9dmbOnMnRo0eb9PyuZtu2bTz++OPs3buXdevWUVBQwNSpU9HpdKZ1vvvuO55//nmWLl3K/v378fDwYMqUKVRWVjb4mNS3DSFEJ6UIIYSwOEAJCQmp87YXXnhBAZTnn3/eYo9nMBiUkJAQBVAOHDhgdlt8fLwCKCkpKWbLy8rKFI1Go6xbt860TK/XKz4+Psry5csbvE6/fv2UJUuWmG3b09NT+fLLLy32/OqSlpamAMqRI0dMyyIjI5V58+aZfi8qKlLs7e2VlStXmt33asekMdsQQnQukmkWQohWdu+996LRaFi+fDnZ2dnXXLeh2U2VSoWjo2Oj9kOn06HX63FwcDAtU6vV2NramgYrNmSdkSNH8vPPP5OZmYmiKPznP/+hsrKS6667rlH701iFhYXApa4iVVVVHD582GyApYuLC1FRUezZs6dB27TENoQQHZMEzUII0crCwsJ49tlnycnJYerUqaSkpNRap6KignfffZeFCxealn3yySfs37+/zm2uXr2ahIQE3N3diYiIaNB+1ASDixYtIisri+rqat555x3OnTvH+fPnG7zOBx98QPfu3fH398fW1pb777+f1atX071790YemYYzGAz87W9/48YbbzQNqMzJyUGv1+Pj42O2ro+PDxcuXGjQdi2xDSFExyTTaAshRBtYvHgxFRUVLFu2jN69ezN+/HgiIiKwsbEhJSWFTZs2kZuby+LFi033Wbt2LXPmzCEsLIxRo0YREBBASUkJsbGx7NixA7VazUcffWTW27k+33zzDbNnz8bX1xeNRsP48eOZOnUqymXzXtW3zvvvv8/Ro0dZu3Yt/v7+/Prrr9xxxx3s2rWLvn371nrMF1988Zo1xYDZ49d128MPP0xKSoop2y2EEC1NgmYhhGgDarWad999l7vuuouPP/6Y7du3s337dgwGA/7+/kyaNIn77ruPiRMnmu6zdOlSRo0axcaNG9m+fbsp0xsYGMjs2bN5/PHHGTp0aKP2IywsjF27dlFcXEx5eTk+Pj6MGDGCIUOGNGid8vJyXnrpJX777TcmTZoEwMCBA9m2bRsfffQR//jHP2o95tNPP80DDzzQlMOGoig88sgjbNq0ie3bt9OlSxfTbd7e3mg0GrKysszuk5WVZfZ8rsUS2xBCdEwSNAshRAu4Vqb0cpGRkXz++ecNWrd3794888wzPPPMM83ZtTq5uLjg4uJCcnIyBw4cMCsLudY61dXVVFdXo9FozNbVaDQYDIY6H8vd3R13d/dG76OiKDz66KOsWbOGbdu20bVrV7PbbW1tGTx4MFu2bGHatGkAlJSUsHfvXh555JEGPYYltiGE6JgkaBZCiA4qLy+PtLQ0Uy/iEydOUFBQQHBwsGnw3Lp161Cr1YSFhXHixAmefPJJpk2bxpQpU0zbqW+dMWPG8Mwzz/D3v/8df39/fvnlFzZu3MiaNWss+nweeeQRVqxYwa+//oqDg4NpkhhPT09sbW0BmDt3Lg8++CCRkZFERETw6quv4u/vz/Tp0xt8TOrbhhCik2q7xh1CCCFa0pdffqkAtf5d3gruu+++U7p166bY2NgogYGByvz585Xy8nKz7dS3Tnp6unLPPfcofn5+ioODg9K/f3/l66+/tvjzqeu5AMqWLVvM1nv33XeVwMBAxc7OTrn++uuVhISERh2T+rYhhOicVIrSwGuIQgghhBBCdFLSck4IIYQQQoh6SNAshBBCCCFEPSRoFkIIIYQQoh4SNAshhBBCCFEPCZqFEEIIIYSohwTNQgghhBBC1EOCZiGEEEIIIeohQbMQQgghhBD1kKBZCCGEEEKIekjQLIQQQgghRD0kaBZCCCGEEKIe/w83dlaZ0kw9OQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "versions = ['19_2_125_rec1', '19_2_125_rec2','19_2_125_rec3','19_2_125_rec4','19_2_125_rec5',\n",
    "            '19_2_125_rec6', '19_2_125_rec7','19_2_125_rec8','19_2_125_rec9','19_2_125_rec10'] \n",
    "'''\n",
    "for version in versions:\n",
    "    print (version)\n",
    "    research_plot1 (version, dcs_data, 14) # rec3\n",
    "'''\n",
    "\n",
    "research_plot_decadal_tcs_vs_ri (version, dcs_data, 14) # rec8\n",
    "research_plot_cagr_mlcr (version, cite_data, 14)\n",
    "research_plot_doc_tcs_mlcr (version, cite_data, 14) \n",
    "research_plot_tcs_mlcr (version, cite_data, 14) \n",
    "research_plot_ri_tcs_whitepaper (version, whitepaper_data, 14) # rec8\n",
    "research_plot_paper_inference_thresh(version, mt_data, 14)\n",
    "research_plot_tcs_cagr(version, dcs_data, 14) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:strat-paper]",
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