yingminc/holiday_info_v2.ipynb

## holiday_info_v2.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from datetime import datetime, timedelta\n",
    "from holidays_jp import CountryHolidays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = datetime(2004, 1,1)\n",
    "de = datetime(2018,2,7)\n",
    "\n",
    "delta = de-ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "dates = [ds+timedelta(days=i) for i in range(delta.days+1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "d_dates = pd.DataFrame(dates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "d_dates.columns = ['date']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>0</th>\n",
       "      <td>2004-01-01</td>\n",
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       "      <td>2004-01-02</td>\n",
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       "      <th>2</th>\n",
       "      <td>2004-01-03</td>\n",
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       "      <th>3</th>\n",
       "      <td>2004-01-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2004-01-05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "        date\n",
       "0 2004-01-01\n",
       "1 2004-01-02\n",
       "2 2004-01-03\n",
       "3 2004-01-04\n",
       "4 2004-01-05"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d_dates.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "d_dates['weekday']=[i.weekday() for i in dates]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "holidays = [i[0] for i in CountryHolidays.between('JP',2004,2018)]\n",
    "for i in dates:\n",
    "     if i.weekday()>4:\n",
    "            holidays.append(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "holidays = sorted(holidays)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "d_dates['holiday'] = [1 if i in holidays else 0 for i in dates]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>weekday</th>\n",
       "      <th>holiday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2004-01-01</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2004-01-02</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2004-01-03</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2004-01-04</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2004-01-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  weekday  holiday\n",
       "0 2004-01-01        3        1\n",
       "1 2004-01-02        4        0\n",
       "2 2004-01-03        5        1\n",
       "3 2004-01-04        6        1\n",
       "4 2004-01-05        0        0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d_dates.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "holiday_p = []\n",
    "for i in dates:\n",
    "    if i == dates[0]:\n",
    "        holiday_p.append(-3)\n",
    "    else:\n",
    "        delta = max([h for h in holidays if h<i ])-i\n",
    "        holiday_p.append(delta.days+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "d_dates['holiday_previous'] = map(abs,holiday_p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>weekday</th>\n",
       "      <th>holiday</th>\n",
       "      <th>holiday_previous</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2004-01-01</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2004-01-02</td>\n",
       "      <td>4</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2004-01-03</td>\n",
       "      <td>5</td>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2004-01-04</td>\n",
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       "      <td>2004-01-05</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2004-01-06</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2004-01-07</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2004-01-08</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2004-01-09</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2004-01-10</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  weekday  holiday  holiday_previous\n",
       "0 2004-01-01        3        1                 3\n",
       "1 2004-01-02        4        0                 0\n",
       "2 2004-01-03        5        1                 1\n",
       "3 2004-01-04        6        1                 0\n",
       "4 2004-01-05        0        0                 0\n",
       "5 2004-01-06        1        0                 1\n",
       "6 2004-01-07        2        0                 2\n",
       "7 2004-01-08        3        0                 3\n",
       "8 2004-01-09        4        0                 4\n",
       "9 2004-01-10        5        1                 5"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d_dates.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "holiday_n = []\n",
    "for i in dates:\n",
    "    if i == dates[0]:\n",
    "        holiday_n.append(1)\n",
    "    else:\n",
    "        delta = min([h for h in holidays if h>i ])-i\n",
    "        holiday_n.append(delta.days-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "d_dates['holiday_next'] = holiday_n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5152"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(d_dates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([   0,    2,    3,    9,   10,   11,   16,   17,   23,   24,\n",
       "            ...\n",
       "            5120, 5121, 5126, 5127, 5133, 5134, 5140, 5141, 5147, 5148],\n",
       "           dtype='int64', length=1666)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "holi_ind = d_dates[d_dates.holiday==1].index\n",
    "holi_ind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "group_holi=[]\n",
    "for ind, i in enumerate(holi_ind):\n",
    "    if (ind == 0):\n",
    "        current_list=[i]\n",
    "        \n",
    "    elif i == holi_ind[ind-1]+1:\n",
    "        current_list.append(i)\n",
    "        \n",
    "    elif i > holi_ind[ind-1]+1:\n",
    "        group_holi.append(current_list)\n",
    "        current_list=[i]\n",
    "    \n",
    "    if i == holi_ind[-1]:\n",
    "        group_holi.append(current_list)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "d_dates['holiday_length']=0\n",
    "for g in group_holi:\n",
    "    length=len(g)\n",
    "    d_dates.loc[g,'holiday_length']=length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# for ind, i in d_dates.iterrows():\n",
    "#     if i['holiday']==0:\n",
    "#         d_dates.loc[ind,'holiday_length']=0\n",
    "#     else:\n",
    "#         length =1\n",
    "#         num = 1\n",
    "#         num2 = 1\n",
    "#         while True:\n",
    "#             if (ind == len(d_dates)-num) or (d_dates.loc[ind+num]['holiday'] == 0):\n",
    "                \n",
    "#                 if (ind-num2 < 0)or (d_dates.loc[ind-num2]['holiday'] == 0):\n",
    "#                     d_dates.loc[ind,'holiday_length']= length\n",
    "#                     break\n",
    "                    \n",
    "#                 else:\n",
    "#                     length +=1\n",
    "#                     num2+=1\n",
    "#             else:\n",
    "#                 length +=1\n",
    "#                 num+=1\n",
    "                "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "holy=pd.DataFrame(CountryHolidays.between('JP',2004,2018))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "holy.columns = ['date', 'holiday_name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "holyct = {k:v+1 for v,k in enumerate(set(holy['holiday_name']))}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "holyct['祝祭日以外']=0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "d_dates=pd.merge(d_dates,holy,on='date',how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "d_dates=d_dates.fillna('祝祭日以外')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "d_dates['holiday_ind']=d_dates['holiday_name'].replace(holyct)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "hd = d_dates\n",
    "for ind, r in hd.iterrows():\n",
    "    for i in range(1,4):\n",
    "        if ind+i<len(hd):\n",
    "            if hd.loc[ind+i,'holiday']==1:\n",
    "                hd.loc[ind,'holiday_{}'.format(i)]=1\n",
    "                hd.loc[ind,'holiday_name_{}'.format(i)]=hd.loc[ind+i,'holiday_ind']\n",
    "            else:\n",
    "                hd.loc[ind,'holiday_{}'.format(i)]=0\n",
    "                hd.loc[ind,'holiday_name_{}'.format(i)]=0\n",
    "        else:\n",
    "            hd.loc[ind,'holiday_{}'.format(i)]=0\n",
    "            hd.loc[ind,'holiday_name_{}'.format(i)]=0\n",
    "            \n",
    "        if ind-i>=0:\n",
    "            if hd.loc[ind-i,'holiday']==1:\n",
    "                hd.loc[ind,'holiday_-{}'.format(i)]=1\n",
    "                hd.loc[ind,'holiday_name_-{}'.format(i)]=hd.loc[ind-i,'holiday_ind']\n",
    "            else:\n",
    "                hd.loc[ind,'holiday_-{}'.format(i)]=0\n",
    "                hd.loc[ind,'holiday_name_-{}'.format(i)]=0\n",
    "        else:\n",
    "            hd.loc[ind,'holiday_-{}'.format(i)]=0\n",
    "            hd.loc[ind,'holiday_name_-{}'.format(i)]=0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
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       "      <th>holiday</th>\n",
       "      <th>holiday_previous</th>\n",
       "      <th>holiday_next</th>\n",
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       "      <th>holiday_name_-1</th>\n",
       "      <th>holiday_2</th>\n",
       "      <th>holiday_name_2</th>\n",
       "      <th>holiday_-2</th>\n",
       "      <th>holiday_name_-2</th>\n",
       "      <th>holiday_3</th>\n",
       "      <th>holiday_name_3</th>\n",
       "      <th>holiday_-3</th>\n",
       "      <th>holiday_name_-3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5147</th>\n",
       "      <td>2018-02-03</td>\n",
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       "    <tr>\n",
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       "      <td>2018-02-04</td>\n",
       "      <td>6</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5149</th>\n",
       "      <td>2018-02-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5150</th>\n",
       "      <td>2018-02-06</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5151</th>\n",
       "      <td>2018-02-07</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           date  weekday  holiday  holiday_previous  holiday_next  \\\n",
       "5147 2018-02-03        5        1                 5             0   \n",
       "5148 2018-02-04        6        1                 0             6   \n",
       "5149 2018-02-05        0        0                 0             5   \n",
       "5150 2018-02-06        1        0                 1             4   \n",
       "5151 2018-02-07        2        0                 2             3   \n",
       "\n",
       "      holiday_length  holiday_ind  holiday_1  holiday_name_1  holiday_-1  \\\n",
       "5147             2.0            0        1.0             0.0         0.0   \n",
       "5148             2.0            0        0.0             0.0         1.0   \n",
       "5149             0.0            0        0.0             0.0         1.0   \n",
       "5150             0.0            0        0.0             0.0         0.0   \n",
       "5151             0.0            0        0.0             0.0         0.0   \n",
       "\n",
       "      holiday_name_-1  holiday_2  holiday_name_2  holiday_-2  holiday_name_-2  \\\n",
       "5147              0.0        0.0             0.0         0.0              0.0   \n",
       "5148              0.0        0.0             0.0         0.0              0.0   \n",
       "5149              0.0        0.0             0.0         1.0              0.0   \n",
       "5150              0.0        0.0             0.0         1.0              0.0   \n",
       "5151              0.0        0.0             0.0         0.0              0.0   \n",
       "\n",
       "      holiday_3  holiday_name_3  holiday_-3  holiday_name_-3  \n",
       "5147        0.0             0.0         0.0              0.0  \n",
       "5148        0.0             0.0         0.0              0.0  \n",
       "5149        0.0             0.0         0.0              0.0  \n",
       "5150        0.0             0.0         1.0              0.0  \n",
       "5151        0.0             0.0         1.0              0.0  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hd.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BEARBEIT5g+tO1Wv10HRiNx6PA5DNZo/wlQiCIAiCIAiVuK47q3qt6cRuR0cHACMjI1iW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7k50jQnS8TR79PGFS/xrLquGLpFIz+DPoB1wzwSSSZxxox+ZoLJ8hKkdDELHtYUn8VSp0pc0CwD\nQHw5cu7wXlUdd48wDwTx5ogfTNMCUmNAYoA0zJF8tK377YrDkarKwOQDtGH0Kjw//XzL99dDN+wh\nraBWXwuLQLNiz549WFhYwLXXXosXXngBlUpl0TVf+tKX8OUvfxmf/OQn8cADD2DlypX4vd/7vabV\nL3bu3Il3vetdePOb34xHHnkEN9xwA2699VY89thjwb9RC3DllmUZiqL4N0jUr5HdKX8rHvIsF0zT\nJk9hbpAaAEzc38Cy2zmONE0BKlOkTDAADJwLpFcuCk7zp2YKpjjFdR6JKBOLzo8ZfZ3Tct5rf/7f\n1sHbmlK1aOBVmBO0OHPkd/cIr+zGmSOeMAyLCNB3FmkoHQGqs77o+2YQhSPPVc/LxCABg9tweP4I\ngM6uj6Kv10tBkhbra2ERSNl9/etfj4997GO46aabGl5z11134Y1vfCO2b9+OwcFBfOADH8Dc3Bx+\n+tOfNrznW9/6FjZv3owbb7wRPT09uOGGG7BlyxZ8+9vfDiIepqenl/zHulckk0lIklQTeUsnR9Va\nrMwHRVRfIt7ytBu6bvqV3eP3OItB43uWm6NEQgVe+BE8ZWjspbBtmwlOIzKwKWOCBvN0wzwSSyYx\nxozdXLJa1nuthPQ142FNYcem6gtQC2O1jCdHAOXJtm2vnzDp2eLMEU+YpkW+Z/9m2jj7eMuWXVE4\nUlUFsAxgdhdp6D0D0HowWZikPXR8fRRtvW4NkiQt0tfCIrxNuA6mpqZw4MABXHzxxV5bT08PtmzZ\ngkcffRSvfvWr6963Y8cOXHPNNb62Sy65JLArwyWXXLLkNffcc4+XmFjTiJ+Pz8/PZp9eqsydrZPc\n1JcooDGFhzzLCV03kRy+GFBSJHfisZ9CkiRomkrSkznoFEdEFgU4+p+0cdXLfFZd9/dUMphcmwEV\ng7jOIxFlIp9P/nZ6zFiktDQjX7gNmLc1pcwou6Esu13AUUEveP6bYVw9uoEjXjBNC2r/FtowsxPq\n4KWB++kkR6oqA/O7AVcB7D8XADBVnGL66Mz6KOp6HQS1+lpYcA1QO3ToEABgaGjI1z40NOS9Vw8H\nDx4MfE9YaJrmkedW5jBMqoT5nl6YAQ22KPDzJeIjz/KhWjWJojvsPHgUDwKFg3VcGTrDkZcixg0m\nUNLAyOU+RdxFOULkenznkYgyUXR6zNjNRWM3l9D16KNbU+plY7BtO3C2ikXyxIgjgFq7FphysVZU\ny27MOOINw7CIG5mL6YehKM1PAl2IwpGqysDs47RhYAtJxcmsP51bH8Ver5eCJGGRvhYWXJVdwyAK\nQ60Grmla08oXpmkuuieRSMAwDO6ZGVRVRbVa9T4DqLXs0s8zQ5TTJH3Q11F9iXjIs5wwTYuUghy5\nnDYev3eRstspjhIJBZh/BigeJg0jlwFKwnNhYH+4xUhWwnjOIxFlEmnM2M0lo2a812wZ42Ay8bCm\n0Gt1x2IVxoWByBNXjug8yldpfEk4y258OeINksHnXMBVVqd+BUlyCjQsCTE4UhTFr+z2b4ZlWUKs\njyKu18EgLdLXwoKrsjswQKIq5+fnfe1zc3Pee43uq71ndnYWg4OD3KNF0+m05wOSTpOjD3Zi27C9\nQa1a0Z3Co/oS8ZBnuaHrRk1xiZ8t8sPqFEeJhAoc+xFtWHkdTNNiygTTm9gghaCbXlznkYgyiTVm\n9HUu0eO9DhshzsOawl7rBuOGseq698WRIxYVn6tHmAC1+HPEC4ZhAkoS6NtEGuZ3A9W5lpRdEThS\nFCdV2vQO2ti/GZZlC7E+irletw5JwiJ9LSy4+uyefPLJ6O3txVNPPYXzzjsPAElFtnv3btx8880N\n79u8eTOeeuopX9vTTz+NzZs3N7ijPh544IElr0kmk5iZIdVRent7Afif5AEyqBIkXzBHZ/2t+Mmz\nHCB+uxcBkgLYJjD5gOcry1Yoc7FcHMmyRJKWsyWCV1zjk4n94foegkJuenGeR6LIJOqYJZSU91oO\nuSPwtqboTh9RTsziyBH70fMVangJY9kF4slRO0Bym9uQhi8GZh4FYAMzO6D2BfPb7RRHquq4xU09\nRBpSY0BmDayKIcz66EI0eVqBJEmL9LWw4GrZlWUZV1xxBb773e962viPf/xjTE5O4vLL6bH2nXfe\niXvvvdf7/9VXX4377rsPhw+To+UjR47gnnvuwVVXXRXo8wcHB5f8B1DLc39/PwBgobLg68c94qsa\novhbRZNnuaHrJqBmATfwYO5JoDrjc2XoBEeapgCWSf11tX6gf3Ndf10AKBvRSqvGcR6JKBOLTo8Z\nC9ZHLiw/vK0pJgdlN54c0YsLOuPGEMJnF4grR+3BIr/dABkZXHSKI1WVgcIBQJ8lDYPbAEmCZVlC\nrI+ir9fN4J7q1+prYRFoRj344IPYvn07XvISUhL2fe97H7Zv346Pf/zj3jXvfe97USgU8MpXvhK3\n3HIL3v3ud+Pd7343Tj31VO+az372s/j0pz/t/f+1r30ttm/fjuuvvx7veMc7cP311+OSSy7B6173\nukhfrhFmZ8nE7OvrA0Cib1nUm/DBwNuXKKo8ywv3aZ2mILOBiQdqjqaWn6NkUiWJv6ukFCRWvBSQ\n5BrLbv0j8VD5NmM5j8STSawxo31kGUtK2KNVgLoc8LCmuJyEdWMA4smRr/BGxPRsQDw5ahdM0wL6\nN9GG2SdaLhvcaY6Iv+4TtKF/Cwn+tEVZH8Vbr1uF62lRq6+FRSA3hg0bNvgUWxdjY2Pe6xUrVuA/\n//M/8dOf/hRTU1O47bbbsG7dOt/1X/nKV3xauqZpuPPOO/Hwww9jz549uOmmm3D++ecH/S4tY3KS\n5L8bHh4GAMyX/ZZdd0C5OIVz8CWKKk8nYBgmtJHtwJ5PkIapB6GtfJn3fic40jQVeOEHtGH1q2AY\nJgmoq4MowU6tytT8fvpalHkkokwsOj1mpA+iPGU0hp8INd0t24IsyaGtKey1UZRcr48YcsSiGjE9\nG3tfXDniCcMwgb5zQJRKG5h+1AlSk4nVtwk6zZGqysDcLtrQf463n4iwPoq+XjeD62pRq6+FRSBl\nt7+/HxdccMHSnaoqrrvuuobvb926tW77+eef31Yl14XrA+K6NcyVZ33vuxsCWys7/BEUB18ijvIs\nF3TdgjZM8y1j8kHHZ1aCafo3kOXgSFVlEkgwzhQ3WXHNIhcGv5WQUZxCHGfGfR6JIpOoY5Zi+JEi\neIxFt6bQL+B+vygqbxw5YudQSS95r0NbdmPIUbtgGBbQ0wP0bSQlg2cfB4wSNE1ZUtl10QmOJAnE\nAj3LKLt9VNkVZX10IZo8S8F9ZqnV10L3F1WgExFTUyTZs0veQrXGsuv9ZbeEsMEFPHyJ+MmzXNB1\nE8isBVIrSMPUQ4Bt1Y2yXQ6ONE0F9DwNJOjdAGRWLyoRzBoF5iq0Prphh1GcmssUBCLOI1FkEm3M\n3A1TVVSPo7DHhmx/PKwp1FIZJUDN/Rsfjnzp6/RopwNAPDlqFwzDJLINOcYR2yAngXXKzNeikxx5\npWvdtGOSCvRugOWUHRZlfXQhmjxLwX0ArdXXwqIrlV3XB8QLWCvP11zhWD+iRCxz9SWKLs9ywzBM\nsoMMX0Qa9Dlgfk9NkNrycZRIKCQLg6sAjV0Nf4lgF4yFxzkSt2wrJPfxnEfiySTamNHXaZVwFNaS\nQiQS7WQnfhz5LLtmdMtuHDlqF2zbse6OXUUbxxfnZm90r4vl5khVZVImeGEPaeg9E1ASXhpLUdZH\n8dbr1iDLhPhafS10f5ElOgFRKJAglkyGOGyXmKpLBNFXAHcu8PElEmBFCgjLssmPfugi2jj1kM+y\nu5wcaZoCjP+ENqz8tbpp0HyBKs68CL/hxXMeiSaTaGPGQlNIBHS0oBn3rygnO/HmqMRYds0QpwNR\nPrsRROOIN3TdBEavoA3jP4Esy4GyMiw3R4oiA/nnAcvx7+3dCACem54o66No63XQz6rV18KiK5Xd\n8fFxANThuTb1mDucPApa8PAl4inPcsIwTGCI8fGeeqju4tVujlRVJu0T99PG0SsaKLuLfffCph+K\n+zwSRSbxxoxulEklCYBswGGPDnlaU+j3isD3or7CQCyO2K9SMkpeX6H78/qND0fthK4bQHYd0HMa\naZj6JWAUWrDudo4jRZFJEQwXjAsDIM76KKo8S8G17Nbqa6H7iyzRCQiXvJUrV2K2POtVFaqF/wcT\nbIHg7UsUVZ5OwDAsYJAJOJx2S0GSabdcHBF/3QVg5jHS3Hc2kBhoatnNV/OeVSdsYvlmMrUKEeeR\naDKJN2b0dUplE7mH3SCibixUINlZ8nlsVfHiiN4ftaSyv9c4cdQ+6Lrjtzt2JWmwdGB6x5KV1DrJ\nkaLI1IUBAHrPhGlawq2PosnTKmqV3ZUrV0brL7JEJxiq1aqXymJsbAwzpZmG17IDGvRhmLcvUVR5\nOgFdN4FEP5A7nTTM7AQs3VvAlosjTVOAiZ9Tf93RKxv46zJO8aUpry1qQEfc5pFoMok2ZizYoJCw\nHEW1prDyu32Et3wxfcWIIxbhXRcWI64c8YZtO/l2B5mTwJlHA7kxLDdHiiIBC8/ShtwZMAxbuPVR\nNHlahaJIi/S1KOg6ZXdqagq2bUOSJIyMjGCyMLXoGneiqzKfaspRfYl4y7NcMAxn0xhwUs1ZFWDu\n6boLWDs50jSFVk0DgNErqWwNsFBlSoaGPRLvgnkkkkyijBl7BOqLgI7gSwjwsaZ44xRhr4sjR+ze\n7yq7UXISx5GjdmNRJbWZHVAUuWkQXac4UhSJjLFP2T3NC05zIdL6KKI8S31Wrb4WBV2n7B4/fhwA\nMDQ0BFmWfamKXLgTXYk0oPx8ifjIs/ygT+vbaOMMezTVfo4Uxcmv6/PXvXJRyrFaVJigxTBlZ5vJ\nFAwiziMRZRJnzNiPzmpZ77Ui8Ts6DGtNkR0Zolh2486R4TwoRfFtjTtH7YBhmED/ZkAmawrG74Ek\nSU39djvFkVfhzVV2E4NActBRdkVbH0WTpzXIsrxIX4vUHw+hTiRMTEwAoCbx6eL0omvcpxclSlQn\nR18iHvJ0CoZhAgNbaMPsE4zPLm1uF0eapjj+Xw+ThuzJQHqsrmWX/diKSSvo2AjnuxfXeSSSTGKO\nGSWoL0krRYb1k+NpTaEWnQjKbsw5sjhaduPKUTtQrZqAmqbpKgv7gcpUU7/dTnEkyzJgVoDiEdLg\nuOoRn116XafXR0Cs9ToIZFlapK9F6i9yDycYXGfn0dFRAMBsTfU0gH16WZwmKwyi+hLxlmc5YRgW\n0HcWbZh/GpIkec7nLtrFkaYpwPQOwHSsfsOXAEBdf11WAahatGRodCthfOdR52USb8zY63uYEp2h\nFXqO1hTVtexGcWOIOUcmV8tuPDlqB7zgrn7GODKzo6nfbqc4UhQZKB6CZzXNrgMAXzYGQIT10Q/R\n5GmE2uA0V1+L1GfkHk4wuGZxz7JbWmzZdRHlKKQdvkRRj2Y6AdO0gPRqQOslDU5pRVWVl4UjVVWA\nqQdpw8ilTsWexff60w/RI3E7YlR23OaRSDKJPma9iV7aZ0RrU9gNnJ3rrsWKR4BanDhirVyWcyrA\nYw+PE0fLAZLBZyttqMnNXotOcaQoEpDfRxt6ToZlkeA0kdZHQDx5WoE7DrX6WhSIO+vbhPl5EsTS\n19cHYHGOXYAe9fmPMsKnjYnqS8RDnk7BMCyikfSdTRqKBwF9AYoit50jSbKJVWDyAXrh8EUN662z\nilOeKSFtWuEUp7jOI5FkEnHMWOQSOe916A04sjVl8WYXJfF+PDmi4FFSOe4ctQuGYQLD22nD8ftp\n3MUSWE6OZFkmbhYusuu94DSR1kcR5WkFrrJbq69FQdcpu3NzJCCtt5c8BbJ10AFCskt0mvFvCX4E\nxceXiJc8nYJ3NOVUlwEAzO92lN32ciS7/Uz8wuk4A/RvaeDCALBH4mVfsFNwxSnO80gsmcQbMxYZ\nZnOJomAC4a0prPwJlQSoSJIULkAlphzxxIschYeum8T/NTlEGmYeAWx7yXy7wLx8hiAAACAASURB\nVPJyJMuS48bgfvhaz4VBrPVRPHlagRuLVquvReozcg8nGBYWiPXHfVLIVwu+99kfCevMHRS8fIl4\nydNJmKYN9J9DG2afgKoqbedIVWWgdIxYkwFSzU1Wmyi7jMxMntYwgSpxnkciygSIM2YA3WAyvoCQ\ncMstT2tK0neMGVzZ7QaOolaZ6waO2gVdN8lxjZuusnwcKB5aIiPD8nMkyxLZW1ykV8CybEce2izC\n+iiaPK3A/Q3W6mtR0HXKrvukkMuRI49SjWWXHdCkYwUBggcr8PIl4iVPJ2GaJtC/iTY4GRnazZGi\nSMDUr+iFQxfCsuxFuRBdNIrsD2MljPM8EkkmEceM3EP+sptCqIAQDtYU9lpNjhagEl+O6MVRq8zF\nlaPlgGXZRGkcvpg2Hv9ZS+nHlosjWXauKx2ljelVjLIrzvooojytwB2HWn0tCrpW2e3vJ+b8+Rqf\nXfb4okejT0FRxjOKL1E75FluGIbld2NYeG5RRoZ2cKQoCk05BgBDFyxRTILKUzFpZH+YYKdumUed\nl0nsMdNkzXsdxm2AjzWFfoGUkmL6Dn6cHV+OFvcXNoivGzhqJ3TdBEYuow3TD7dUSW25OPL2LdeN\nQdaA1GhdI0rn10ex5WmEWmXX1deioGuVXdcsXtRr3BiYxMWsD1CUp5covkTtkGe5QTIyrAQUZwHJ\nk0TcXmJu8OdIkpxFafpReuHgtobBae49LnSLtRKGOBLvknnUaZlEHzO/719nLKnspRktU7fvluWJ\nKUc+eVwl4P+z9+bBlhxnveCvqs5696X3bnW3Wi1Z+2rJlowtWfbDBvyAmCGYMA4UNtjCgB2YJZjw\nOAwEwQx4GBMeMJ4AgpB4AzE2z2aCQM+YwWAJni1syVq6tdtqtWT1drv77veerZb5Iysrs+rcc++p\nzDz3fMrqX4R0quvU8ru/zJP11Zdffp9ifrYiaDRIsNzst4gdC0/AcZzU82IjbJdGibHbOMM+a3sB\nx008uzKGPT5S59ML/KeXtdd0UDhjd22NGbejo6yx1juN1PfyD0ZeuagCE7FEJvkMC0EQAo4LjB1h\nO1ZPAmEAz3MGplHyw1x8mn2WJ4DRy7csE8zhS+VmVeI/be9HFDlRarPkmpL3RMV2MuFNkR9G9bI8\n1Zt/+LdVIxm66dmKoNEg4fsBUNuZ5K7FxceB0N80lAHYPo1c1wGiEGgvsB3Vmfi4SDqH1vhIjc9W\n4J7drL2mg8IZu+028/5UKhV0gk7X9/IDYLSi9/ZiIpbIJJ9hIQhirnGVGYQtYO0kPM8bmEau67DB\niE81Td0IOM6mnl0Zct9Q0dr2fkSRE6U241BZBJbiZNibks5WouDZtVSjdFwzmw5Xiftk59mp0Xah\n04nH6Nm4klqwDiw9u2Uow3Zp5Lou0DwHRPGC2PoBAEh5dqmNj9T4bAVOTbbXdFE4Y7fVYnF91WoV\n7Q2NXdEBeB1pYHjxVoPgs92IonjRwfhVYufqCbaALIZpjVzXARaeFgdN3YQo6r04DUh7A9px/KfK\nQqdenAD7+tGwOVFvM12Y8KbI/FPGrtJUr50apeKaSyyuWTV9lb0abQ+ScXrmNrEzzuAzSPSrEcvE\ncEbsGNkvnnEZDHt8pM5nK8j2mi4KZ+zKbvGWlJeTQ54KkVcu6kAnlmgQfIaBIAiB8aNix/KLqRgs\n0xq5rgMsHhMHTd/Uh1dX3LcTshch7bg/2N2Phs+JdpsFkRQ2o0DLjDdFNuT0PLu2aiQfyh/kqrmI\nbdVoO8HKzMvpKo9tGbO7XRo5jgO0pcqrlemeOg5/fKTNpxcuhTEYQLPJDNxarYa2lKqIQ+4MU9Vp\nAPpvLjqxRIPgMwwwY/dKsWPtldTD1rRGjpMxdqdu3NSrm72vH+dsVYn97MXJxn40bE7U2yzQjCM2\n4U2Rj02txtbMxmCTRjK8VBVGBWO3ABoNGmyR2s1ix8JTcN10Bp8stksjz3OA9VNih5R2LIthj4/U\n+fQC5ybba7ootLHb2sDYlZNJT9d4g+q1qE4s0SD4DANhGAL1/WJH43Rq4DKpUZIvcel5cdDktX0v\nTgOEl0BV66L0I0qcKLaZnyp0kR+mvSnTtZlkO504vz8UQaOKZuGNImg0aPh+nMGHV1JbPA4Am4Yy\nbJdGjuOyYhccUkGJ7mPpjI8U+fQC53nJ2FWE7/vwffaDqNfrG4YxcG9jxask6UeGaVxS46OKMIyA\nkQNix9qrALDpm3q/yGrEVstGwNJz7ICRA0B5fEvPrgzuJVBVmlq7UeMDmOdEqc34M4WHVqhey5Q3\nhT+M+UMKyJ9nE7BXI/m+srGrk57NNo22EyyDjyNCGZpngdbFDRepbbdGjgMgkLI4eaMDGUupjdnb\nzSdrr+miUMZupyN+DOVyOfUmyME7/GhqNabefXViiQbBZxgIgggo1YHqDrYjngbib3AmNWILCE4D\nnUV2wOR1ANB3JgaZj0pxgo04sWspXaqLE7vY8PlQ40SxzdJjTP6Lmfam1FOph9Sn6G3TKLWIL1V4\nQz09m20abSeCIGT8UpU3N4/b3S6NHMcB/FXpxJGe7UtpfKTIpxccx+my13RRKGM3DMVD0HXdrsTz\nDpzE2zEq5dlT9xUxqMYSDYrPMJBoz3MnNl4Hwk7i2TWpkes6wMpL4qCJa3qulk1dS3r4q67o78WJ\nwb5+NGxOdNssnoaTZo90Cl3oelP4OY7jJJ7LvIac3RqJ40crUhXGnHHNdmu0vfD9kKWM5IjLzHdj\nezVyXScdxlDd2fPZMuzxkTqfzZC113RRKGNXxkZeDU8SdKxiLvG2aizRoPgMA0muXR63G4VA83wy\nBWVSI5aJ4bg4aPKaXF5dQBhOarFfxelHlDhRajPerxv+erJPxRgfhDclSc+XN6m8xRrJx8vXuaTR\n8BAEmYwMS89u6NndTo26qqcBm8bsUhofKfLpF7o5lIECG7tRFHUJKMewjUsB6sOKtzLNZ5iIoojx\nru8TO9d/kAweJjXqXpx2fa543Qzz3GcUoR9R5CQw/DbjkL1NecMrTHpTUqm1SqrGrr0apfWRwxjU\n0zPZptF2g6Ufu0bsWHp+07LB26FRYuw2Y2PXrQCVmZQXEqA3PlLjkxcm7lMoY1d2hYdh2JVlzpHk\nqEkD3rDirQbFZ1hgi9SkjAzNs8kLhymNkkwMyy+Igyav0TB286NI/YgiJxWY5CPbR+sa3iaz3hRx\nkqpn126NxAl1T72kst0abS+CIAQqU0BtD9ux8iIApIzd7dYosSG4Z7e2B3Ccvjy7FMZHanw2Q9Ze\n076e9hXeQJA9ucyzm/7zZXHTDTqceCvzfIaLMIxEzC4ArHw/eVM2pVHSxGuvsM/KNFCZzh3GIPqK\nQpWpQvQjepzotJm4/3pnLdkOcj+AzXlT5FMqUg7RPNODNmskH14ryfrke0TarNF2I3FQTLyJfTbn\ngPZCxrO7vRq5rgMELaB1ge2InTfdxi618ZEan60QddlruiiUsSs3WBAEXVNUriRHvaSf1003lsg0\nn2HD90Ng4mqxY/mFpEOb0oilHQvFm/cIr1vezzXFD4pXTlKJFCpCP6LDiV6bpUsYi1ze+adWzXlT\n5HNGSiPJdp4FWLZrlFynLPTJ69ktikbbgSQjAzd2AWD5ez09u9uhEVucdlbsiMPyeoUxDH98pMln\nK0RRt72mi0IZu6WSSC3i+37XQC+LK6fo0R0UVGOJBsVnWAiCEBg7InasvRqHHZjTyHEclsM3jAe+\nsSvie28tmqwr7xsqgfFF6kfD5kS/zVrJdt4V4ia9KfI5cinUPLl2bdeIY7Qk66Pu2bVZo+1CEETp\nypsr30OptPHvezs0YsbuebGjtitej7LxdYc9PlLnsxmy9pouCmXsuq4rYkR9v2ugl9/i6yW5FnP+\nFjURS2SSDwWEYQhUZoBSXLJ09WUAzDgxpZHjxDl2OUYPicVxOVD2WF4/R2VK3PJ+RJETQKnNNp5a\nzRtHOChvimq2Ads14mPEqI5n13KNthtdZeZXvpcyvLZbI8dxgPaC2FGZ7nq2UBsfqfHp+54Ze037\netpXeIOBJydmnt10ucxUg5Z13170Y4nM8hk+kqo4Y4fZjvXXgSiE6zrGNHIcB2ieEwfUdm+ZX5cj\nHdeolot0I04bXb9/UOxHdDjRbDMBnUUzJr0p8gO5XlIz5uzXiH1OVaeTh6yXs6Sy7RptN8IwTGbn\nAACrL/fMxrAdGnWFMdQ2SjtGZ3ykyWdr8OvK9pouCmvsdjodlLo8u6JT1Lzhx1uZ5EMByaAwEi9S\nC9tA4zQcxzGmkeMgnQNxw8GoF/RXrG/ESQcU+xEtThTbTH64SA/gMF/c2aC8KdwDDuRcoGa5RvyF\noOSVUI3/Pi+3Z9dujbYbQRACo4fFjrjMPDd4t1sj13WA1rzYUZ3ter7QGh/p8ekPTFPZXtNF4Yzd\napU9EFutFspSDXQG0aB5Y7U2g3os0WD4DAthGIcTyNNSyy/BdR1jGrmuA6y+Ir4ePdR32jH5ttz7\nlaQyy4Xi9KNhc6LYZvLpS62lZNuPNB7Amt6UjTzgAODmCvkojkZjcVxznphmBrs12m4EQQSUx4Dq\nLNsRG7s8i892a8TCGCRjtzy1aYjcsMdH6nx6gVOT7TVdvPEtqJzg4jWbTVQzxq789lJ2s4ZwPpiI\nJTLJhwpYDJY8LXWCxewa0KjiVeMwBmmaaWR/Ds+ugLxIIX/cnt39iCIngE6byQ8Gvvo5jMLcceNm\nvSni3rKxmye1lu0ayfeerEzG13dzhnrYrdF2I8lywCtvNs8koW8M26uR62bWhNT3buDZpTU+UuOT\nB7K9povCGbuVCmuodruNkpeOx5IXtvApURMrVlVjiQbFZ5hgGRmOih0rzLNrQqNkYUn89g8AGDnQ\nd0JqWduqlGszf2L54vSjYXOi2GayU5mvflYpXzoob0rZkY3d/j27tmsk/y0T1clku5Qjbtd2jbYb\nIvTtsnhHB2iek8IYxLGD1sh14xkjOUxuC2fKsMdH6nx6gV9bttd0kS/6vg/8+Z//+Yb7b775Ztxx\nxx0bfvfiiy/ikUce6dr/kY98xEhNZBkjI8wgajQaSaNxyPeS49pUYCKWyCQfKvD9ENXJa8WOxeNw\nHCf1QFHVqF6J38hXvs8+a7uB0iiCoJGbZ8WVDad8fdD2fkSRE0CzzRod1veCnDGEgFlvSircoyxX\nCMth7BZII9WMFbZrtN3goW+OXGa+cQZunYU1bKdGyb14QQmAlQpe8zc+DjTGR2p88kC213Rh3Ng9\nduxYypO2srKC73znO/j93//9nsbus88+i89//vP4oR/6IdN0usDFW19fh+d6qHiVJGhbbtBK3OFV\nX15MxBKZ5EMFLIzhAKts1l4AFo8DAEYrYoW4qkbVUhXorIowhvGj4p59IF1FSUxl5a2iZHs/osSJ\nYpvxS622VxHEmuSt6AQMzpsiT9OqGnI2apTKWCGlH8vjDbVdo2EgDCN4cXEgAMD663BHbwSwvRol\noRP8+VLdAbglhGEnc5zYHvb4SJFPP+Day/aaLowbu5///OdT/37wwQfxzDPP4L3vfe+m583OzuIL\nX/iC1r3n5+d7fler1TAyMtIlXrVUFcYuMoaTFvRjiczyoQHfj9OPTd0AzP0b0DgFtOaxY5S9qetp\nVAFWnhVfjl+JKIpyGLtS4v2yWpWpbk429iM6nCi2GX8wXGxcTPYFYf7UOYPypqRidnMsULNdI7n7\nTkphDHn6ku0aDQNhGMFLeXZPJYbndmrEqnNGIrVlbXfML/t8oTM+0uSzNTg10saujCiK8JWvfAU/\n9mM/lpDeDLwknOflXQHLcOedd/b87oMf/CA++clPYnycFTRYWVkBwKarVlpsO9XhXd2pA7GtGktk\nkg8V8BKQztRNzNgFgMXj2DUaDxwaGnmuB6x8T3w5fmWuxWnyb3+8Kuqj512RbXs/osSJYptxrLSX\nk22VqVXT3pQoYm2nmnrMfo3kXMT63m87Ndp+hGEIjB4UO9Ze68q1ux0aeZ4LNOeAIF4sNXIw5tc7\n9diwx0eKfPoBN8Sz9poOBhqtfvz4cbz00kv4qZ/6qS2PPXfuHG6++WZcd911eP/734+HH37YKBf+\nZjA2NgYAWF1dBZCOXzMJU7FENiIIQkCO2116BnvGmLGro5HrusDKS2LH+FV9e3WBzAKVimQ4KeRt\nNQWK/YgSJ4ptxtGSSnPmLV8KDM6bUpKK6ahUmzMJShql07OJa5leN5IXlDQaBoIgSgxLAMDaa1I2\nBobt0Mh1nfTi57g652bZGIY9PgL0+PQD3oRZe00HA30ifPnLX8bRo0dx0003bXrc0aNH8cd//Mf4\nh3/4B3zxi1/Enj178Iu/+Is4duyYMS48T1u9zoxbHvBc6cq1y6A7wJmKJTLFhxJ8P2RhDBwLT2Pv\n+F6U3bKyRmW3zAajZcnYnXhTLmNXxkRFmsbMWUVJho39iCIngEabyae25ATuUIgjNO5NiRO1K3p2\nZdirUXytSxqRQZdnd/01AECpJMyX7dDI81xg7aTYMXZ4w5lDauMjNT79gDsxsvaaDgYWxtBoNPDQ\nQw/hYx/72Jbi3Hjjjal/33DDDXjxxRfxpS99qes7VfA8bbVaLfXvXsauLkzFEtkI3w+AqRvBYoki\nYOFJeK6HyyYvw/zZp5WuOTMywzbWfyB2jh5C0Mr3o+ZTvemYveF7din1I2qcaLWZGOvaoWoC98Ei\nnUprGC/R9DVKeXaHkqGTvkbbhSCIgNIIUJlhBR3iMV4u8bsdGnmeC6yeEDtGL9/QmUJtfKTGpx/w\nJszaazoYmLH7T//0T2i1WviJn/iJ3Od6noejR4/i9OnTWx8s4dFHH+35HS87l31T6DVlEUWRkTcY\n3Vgi03wowPdDYGycVVJbeYllZAg7ODR1CE+cfkLpmjwMAqtx2rHKDFCeQLCe940wAuBk0jPpVPiy\ntx/R4USnzeTTGtLUap7SnBtfV7/N+EuBvOBK9bq2asRR89RyEcuwXaPtQrIAbOSy2Ng9BUQRPE9e\neDV4jVzXyawJObrpzCGd8ZEmny3uAuAN4tn98pe/jHe+852YnZ3t+m51dRWu6/ZctLa2toann356\nywwOWczMzGx5DI8BWVtjlURGpBXcchnsECE8qC2Uk6EVSzQAPhTg+/EPbeY2ZuyGLWDpOVw+fVhZ\no71jewF/DVh/ne2ISxLnDWPgBsFYZQyO4yCKopQHIQ8nwO5+RIUTpTaTnwGrbbGoIuizsMl2QJ6m\nzfXIKoBGvC+VpFyruXI2F0Cj7UYSKlCNn++RDwTrcKTY80Fr5HkuM/BWXhQ7x6/cdOaQyvhIlc+m\nt8vE7HJ7TQcDMXZPnjyJxx57DH/2Z3+24fd333037rrrLvzJn/wJAOCTn/wkDh8+jMOHD2NhYQFf\n+tKXsLKygp/5mZ8xzo2v7lteZm85srErN38URlBtT1PxVqb4UEMUMSPUm7kVePX/YTvnH8fls+9W\n1mjP+N70W/fEmwCoGLvMS+g5HipuBa2gldtLaHM/osiJUpvJ5mMz9XDRewCb9KakU2n1f81iaMT6\nUk0xPVsxNNpeJItQK5Izq3UBritK9Q5aI89z2YNr6Xm2o74PKI8jyKTEojY+UuPT9/0y2Ri4vaaD\ngQQjnThxAj/5kz/Zs0jEXXfdhbe+9a3Jv6+55hp8+9vfxuc+9zl88YtfxO23346vfOUrOHTokHFu\no6OsMg5/U5BTzMhNGuRIuNwNU/FWpvjQg+8HwMztYsfF7+DAxH6FCj9MowMT+4FFKcfu5LXKi9M4\n+LR43pytdvcjipwEht9mAnJcXIS8+qDLm2IKjrSSPZ/dUxyNKsoFSoqj0XYhimLjp7ZL7GzOpQzS\nQWtUKrmsclo7zuU/cQ2AOCQvBWrjIzU+fd4tvl3WXtPBQDy79957L+69996e33OPLsd9992H++67\nbxBUusDF2yj1mNz8Og1qKt7KFB+K8P0Q1ZnbAMcFohC48ChKbglXzh7F+bXzfV+Ha7RvfB9w6nnx\nxeR1GwxEfVxPGgTGyuNYbC7Ccz04cPoeRG3uRxQ5UW0z2ZOi4m0alDfFVfRxFEGjJK5ZulCe94Ei\naDQMhGEEr7pD7GjNwx13EKfmH7hGnucCS8+JHZPX9kg7JrYpjI/U+PR9v3hMz9prOhh+Msptxo4d\n7AczNzcHAJgdkWKKpYemTgC3sXgrQ3woIggCoDwGTN3Mdiw+A7QXcd2u6/JdKIpQL9UxXh0HVr4v\n9o9fqeTZlZsotbo/T5ECi/sRRU6U2kw2jVqB8KSoLZoZjDdFeRq7QBrJfSeXXgXSaDsRRVE6jKE9\nn2qXQWtUKrnAopQKdfK6HpkYxDaF8ZEan37BXyKy9poOCmfs7tmzBwBw/jzzHk5IVZfkt5dOxOpd\nqz0XzMRbmeNDD74fsQFs19vjPRFw/pu4ftf1ua4TAdg3vpf9gxeUcFxg9LCSsSt7CccrY8l2HsPJ\n7n5EjxOlNpPP6YSytyn/1Cq1mZ0iaVRSzNNcJI22E13GbutCqrDEoDXyvIyxO31Tj5lDauMjNT79\nIwyjLntNB4UzdrPl50bkMAapA/jStIgOdGKJBsGHEsIwAna+XeyYexg37Lk+V+LzKApxYPIAEAbA\nchzGMHYU8KqKMbuijerS4sU8C56K0o/ocKLZZr7kAVGLIxyMNyVSMAbYecXRKOXZzbNArUAabSfC\nMAJqO8WO1oWUsTVIjZJMDIvPiJ2T14msQj1AZ3ykyWfre0ZvnHLBFMFjQHj54FpJjtkVHaCTdPj8\nry+m4q1M8aEIx4kzJey+R+w89w3USjVcteOqvq8TIcKBiQPA6suiZvkU8w6rxeyK7YqrlmvT5n5E\nkROlNpPRCTri+preJpPelNQCnBy0iqRRKq45V+ax4mi0nYgiACUxawN/NfX7HqRGpVK8rmQpNnZH\nD7NMDFuEMVAYH6nxyXXPqNte00HhjF2e27fT6aDT6aBeFqtu5d+IH78F6U4d6MQSmeNDEQ4bLKqz\nwOS1bNfCU0BnBTfv3by8tIwoAg5OHgQWpcprUzciDENlDxZHSSoZ6uby7oht+/oRRU4Cw24z+Zx2\nrI9qKqTBeeTVvGBF0ki9kITYtl2j7UQYRkB9r9ixfirVRoPUqFz2WBl6P14kNc3WmWwVxkBjfKTG\nJ889oy57TQeFM3a5WxxgrvGR8mjyb3ngb0sdIy9MxVuZ4kMRjsMGMBa3ezfbGQXAhUdx054cxi4i\nHJw6CCzIxm6veKo+ric1UU0uGZpnStzifkSRE6U2kx8unbAT81MMGxiQN0U1brNIGpngY7tG24kw\nDIHabrGjxWI4+Xg0SI1KJReY/644ePZ2BEHYlYlB5sOuM/zxkRqffIi67DUdFM7YLZfLSQm65eVl\njFYkY1d622kZalCdWKJB8KEGFrcr5WOe+zfctOfGvuMtd47swFhlDFh4UuycvnnLeKreEG1UkQyn\nPFWUitKP6HCi02bpOEI/ZqcaI9t9LRPeFNkgyMOsSBoph3oUSKPtRBhGLIyBr+eI891y7+4gNfI8\nL704bermvpwpdMZHmny2Qhh222s6KJyxCwCTkyw90eLiYmr1tvy2Y+rtRSeWaBB8qCEIQmDXPWLH\n3CMYr47jipkjfZ1/ZOYKNlLxN+/KDDB6SNmzK2NEcbFTUfoRRU6U2ox7UIfvJWTgD++25OHJw60I\nGnGohnoUSaPtRMQTIJen2I4WN3bZPwelkec5LOtDyplyU1/OFGrjIzU+W4FzlO01HRTS2J2aYj+Y\nxcXFnp7dpi8aNO9bsKl4K1N8KIL/DWEYASP7gLEr2I6L3wH8Bm7Ze0tf17lq9kpg/XWgeY7tmLkN\ncBxlz648BoxKL0JujopcNvcjipwotZkMbjCpRo4PypvSVkwuXySN/NTKdTU+tmu0nUhCBkb2s8/G\naSAMEs/uoDTyPI8NMAtPsR3VnUB9X09nCrXxkRqffPdkrSnbazoopLE7NsYeiKurq/BcD5W4DnqY\n6vBN6Yy8LWom3socH4qIB6kgZH8nz8oQtoGL38bNe2/u6ypX73wTcPE/xI7ZO+LKNvoM655YvJhn\nStzufkSRk8Dw20xAeJvUOqN5bwr7WzrKXkv7NUo8hXL6qVzeb/s1GgaCgBu7B9ln5APNs8LYHZBG\n5bIHrJ1MYoQxfcsWzhRq4yM1Pv2D85TtNR0U0tjlMSDNJmu0ahznJw/8cpoOnbcpnVgiU3woQv4b\nXl96Hdj5DrHj7Nfx5v23wdvCM+c5Hq6cvRI4/6jYueNOBEGkpREfCyoGFjvZ1o8ocgIotZk4QXVl\neMLJsDeFn9cKGtI9cmRjKIBGHDz9FJCvfxdJo+1EFMWLmev7xM7G6USnQWlULrtstpFj510Iw40X\npwH0xkdqfHLdM75l1l5TRSGN3Wy95XpcWEJ+u+NvQbrQiSUaBB+KeP7888De/yR2nPkaxipjuGH3\n5tXUjs4eRa1Uy3h238JW7mqB6V71RM7WfF7CYvQjWpzotRl/AKtOrQ7Km9IM1FZlF0kjOf2Ualyz\n7RptN1jI236xY/2UCIcbkEae56UzMUzf0vd6EFrjIz0+W4HzzNprqiiksTs7OwtAlKCbqU8DyAap\nm6paoh5LNAg+FHHs3HGWQ3EqTjk2/11g/XW84/DbNz3vpj03An4DmH+c7Ri/CqjtMGDsMsg5W/M8\nGIrSjyhyotRm8tXVzhqMNyW1UAX9/1aKoRGfFhe65IrZLYRGwwEzdg+IHeuvp0oGM5jTyHHixWmp\ntGN3oNPpbz0ItfGRGp8t7xnfMmuvqaLQxu7CwgIAsahFnsropAaF4cRbDYIPRbx44UWstdeAAz8p\ndp7+R9x18G2bnnf97uvYQMTfNHe+DVEUxWEM6hrxH1nJKSX78lyuKP2IEieKbaYLk96UdCUl4bnK\n49m1XSNAylihuHK9CBoNC0EQiphdAFh/zZiuG2nkeQ4QsDUkAFgIRX2PzSd+ngAAIABJREFUgmd3\n+OMjRT5bgTutsvaaKgpp7GYDnkc2CGNo+o3uE/uEqXgrU3woIlXqMezg+LnjwP4fEwf84P/FwanL\ncGjqUM9rXL/r+nQIw463aldNk1F2hZfQyeEltLkfUeQkY9htJkNopWjAG/WmCA7rnbVkO08b2q+R\nQFPOWJHD+10kjbYbrIqaHLN7JtFmEBq5rsuyMPjx7yVOkbmZZ5fa+EiNTx7wW15aoKYBXpWDJynm\nuTnTcTtmpnt0YokGwYciwijEd08/Acy8GajHMVlz3wD8dbzt4F0bnrN/fB/2jO8Bzj0sdu64K1m1\na0Kj9Fur6sp+e/sRRU7DbzOhBje2Vf8kk94U+ZS1tmTs5gj5sV0jGW1F73eRNNpuhGEE1HaKHc05\nAEzbQWjkeY4IkQOAHXfC94O+HSrUxkdqfLYC1zlrr6mikMbuzMwMAGB+niWmnqqzPG5yJ06/AZto\nUYUVkAPlQwvHzh1jcXL7fpTtCJrA2X/GXT2M3dsP3M7CF+YeYTtqu4DJ69hUFwATGnmuyAaR52rF\n60d0OA27zeTnIM8mompUDMqb0pRSK+Xx9hRJI/nvy5eLuDgabTfCMGRFg7y4cMz6awCYLoPQyHVd\n4MK3xEGzb1YsVkRnfKTJZ2PwjBdZe00VhTR2d+3aBQCYm2NvhlM1ZuzKA/9aR7jMh/UCTI3PILHe\nWWdZGfb/Z7Hz7L/g+t3XoV6qdx3/lgNvAS48CvixLrvfDThOYuya0MiVfx45rket3ajxAQbHiVKb\nlePFcnnCKXpx0k8ZJ05KxezmmqK3XSOx3Q7VUo/ZrtEwEYYRI80Xqa3/AIjY+gzTGnlefJ0LcZic\nVwOmb+17cZouqI3Zw+DDDeysvaaKQhq7POCZvymMV5mbPIzCpFFXUw2q3qI6sUSD4EMR/O85fu4Z\nYNc7AL7I6NRDqLhlvOWyO1LHe46HW/beDJz9uti5770sX2/mmiZ45UVR+hFtTsPhI3vkeLGaPGWL\n09cy502R/4xGR62Cmu0apeKa/fVkO2+oh90aDQ/JrN3oYfbprwHtebiuY1wj13VZmMTqy2zn9K2A\nV8lVmZPa+EiNz1aIItYuWXtNFYU0drvy7EqeQ96gbZ9GvJUZPhTRrdETZ54AKpPArrvZF2uvAEvP\n4a0H3pI685pd12CiNgGc+Sexc/e9eOH8C+KaQ9bI3n5EkZMZmG4zXqxG9QE8KG+KXFQib5o+mzWS\nz1nvCGM3yPFCIHOyUaNhIinkUN8jdjbOwnHMa+R5Lps55Nh5F6Io6iOMgdr4SI1PPkTRpTy7WqhU\n2Ftgu80areyJdEX8Da8dqq9aNRlvZYIPRWyk0WtLr+Hs6rl0VoZz38BNmdLBt+y5GeisiMUDk9cD\nI/txbO64UY48VQsjnO9cW/sRRU4yKLVZvcRiCx3HUdLIpDclFcYgVYgKc4pkt0ZiW45tzZvhxWaN\nho0wDMUiZgBY/wEcxzGuEcuv+4Q4YPYtfYUwUBsfqfFRuGuXvaaKQhq7tVoNANBqsUG/IlVd4h1e\nTryuA1OxRKb4UISs0ROnn2ChDBzn/w2Hpg5itj6b7Lpl3y3A3L8D/G181zvghz6en3veKC+ehBvI\nF7cHFKMfUeREqc1qpVqyretxMulNacgxu4qeXTs1EifJqcfCKF+cpt0aDRdBEAFjh8WOtZNwHMeo\nRpPVSWYQyp7dmdtyL06jNj5S49MPoqjbXlNFoY1dXmu5Ek+BAOLtJYiCJL6JQryVDh+K6KXRU2ee\nYpXUyhPsy3MPA1GEW/fdkhx7454bgLmHxQV2vxMvz7+MZtA0qpFOzl5b+xFFThtdc1h85PtXS2Jc\n0dVI15uSKioRG3JhFOZ+ISiKRrIHNG8Yg80aDRtBEAJjR8SO1Zfhuo5RjfaO72ED3ULs2a3tAkYP\n5/bsUhgfqfFRuWfWXlNFIY1d7hb3fR9hGKLsijAGeWDjixSGGW9lhg9FbKzRE6efBNwSsDMuFdw6\nDyy/iJv2sFLCt+67leVFPvVQfLYD7HpHEq9rUqOO4opswOZ+RJGTwPDbTKDiyg/gYXtT5GwMzEOi\n8mJgs0byg3u1LRm7YT7Prs0aDRthGALjV4odK9+D4ziYrE4lu3Q12j9xgGV6aF1kX0zfAjhOn4vT\nqI2P1PjkR9ZeU0Uhjd1yWVRZ8n0/lZtTXp3cSBYpqL9N6cYSmeBDEb00OrN6BnOrc+lQhrlHEs/u\nrXtvAdZPActxyMKOO4HaLjx59ikAZjTizeRH/oZ8+4Gt/YgiJ8aBfVJqM3lq1RmyNyUdjyo8u/n5\nFEUjaRFfbs+uvRoNG0EQAfUDgBuHHq58HwCwa1QUm9DV6PDUIVY5jWP6FoRhJBbIbXoNsU1hfKTG\nJ/89u+01VRTS2HVd8WeHYZh605HfXvjbvc6YoBtLZJoPRWQ1eurs08Dud4oDzv0LDk8fxmx9lhm9\nc/8mvtv9Tqy2VnFi/gQAsxp1FBPLA8XoRxQ5DbvNZG/paFyZERCLQ/LClDeFP9wafiMxdv0w/4PD\nZo3kBzc3CFVeCOzWaLgIghBwPRHKsPJ9IApTxq6ORg4cHJ09Cpz/7+KL2dtzpRzjoDY+UuPTL7L2\nmvJ1TJB5o8HzxI8ha+zKD0jVajMm461M8KGIzTR67NTjLK8hj9udewSIItx75J24dte1wOmvigvt\nvgfPnX8umbI2oxH7BbcDeUo8H2ztRxQ5MVBpM7E9Xp1ItuXZI1VOOt4U/lBaaS0l+/JOz2f52KoR\nYM77bZtGw0aySGziTewzbAFrr2KHbOxqaLRvfB8zCi8+Jr7Y8ba+i0lQGx+p8VFB1l5TRSGN3c0g\nlw2U4/9UoRtvZZoPRWQ1eur0k+ztncftNueA5efx0Tt+gWVgOPvPbH9pFNj5Djx+6rvJ+SY1SqWx\nyr2y3/5+RJHTsNtMfrhMVCQjxUCcnI43hXt216T8sSqGnM0ayUiMXYWHa1E0GgaiKA4nmLha7Fx+\nAdN1EbOro9HVO68GgjZw8dts58hlQH23UplgauMjNT7bjUIau/IA5jhOamCJpPKZqqUVTcZbmeBD\nEZtpdGrlNMu3mwpl+Abq5Tpw8XGgeY7t230v4FXw3TPC2DWhURL/Ka1cln/o/cDWfkSRk3zOsNtM\nxkRlMtn2pEWwuTgZ9qastleSbSWvpcUa8ReCKIqSh3mecsoJH4s1ooAgCIGJa8SOpecxVhlL/qmj\n0dGZK4CFJwFeeCUucNTp9BfyQ218pMZHBVl7TRWFN3Zd100lVpe/W2kvJ9t5RDYZb2WCD0VspdET\np5/oMnYBCK8uAOx/H04unMSppVPJLpMarXfkxPI585Fa2o8ocpIx7DZj92Wfk1XJSFHO/anvTZHp\np3Lsqnh2LdUIEDottUWoh5Jn12KNKMD3A2DyWrFj+TlUSxWUXbaQSUejy6cvB+aF8wSzd8D3g74X\nu1IbH6nxUUHWXlNFIY3dIBBTnZ7nIZRi1+Rp0LX2mtL1TcZbmeBDEVtp9MTpJ+J8u/FAf/7f2Ulz\nj4gTd78Lj516bGAaNTRWZNvajyhykjHsNmNgItXLogy5cm5LI94UcfBaWz1/LDvHVo3EQ3upKcU1\n5ywokT3HNo0ooMuzu3gcjuNg38Q+AOoajZTr2D+xH7jwLbFz9o5cIQzUxkdqfPLCcbrtNVUU3th1\nXTf1UJTfgOUE3KpvU7rxVib4UMRWGj195mkWt7vjTvZFHLeL8//O/j1yABg7gidOP2lUI/mcNY3E\n8rb2I4qcKLUZIB4wY5Wx5FxVj4QJb4p86Locs6sZj2qTRjIavtAouKQROfh+CJTHREaGxWeAKMTB\nycsAqGt0aOoQ21h4kn26ZWD6llyZGKiNj9T4qCBrr6mikMZup8OmcVzXheu6qRQ8YSq2Sa9iB6Af\nb2WaD0VspNGpldNYaCwIYxcAnv8/AD4Nu+fdCBHhiTNPGtVI/t22NdJYFaEfUeFErc34A8ZzPFRc\nvapFJrwp8sNoRYrZVfFa2quR2F7RjGu2VSMqCIJY36kb4h3rwOorODTJjFVVjQ5NHQSCFrD8Itsx\ncQ3gVcT9coLK+EiVT7/I2muqKLSxy5MV9zJ2ZS+I6kIe3XgrU3woYiuNnjn3DLDzh8QJJx4Q23v+\nE148/yJWWisD00iuNpS3QIHN/YgiJw4KbSaDT0Gr5v404U2RD01nY9Azdm3SKBXqkZoduKQRNbAC\nDyEweb3YufQsLos9u6oaXT59hM0e8jaPjekgyLnQldj4SI1PHjiO02WvqaKQxi6vwsHFkwc0Ofek\nvHI5/6BgJt7KHB+K2Fyjp84eA2bvADbSbc+78Z1TLBeiSY1SuTY1FvPY3Y9ocaLWZvLU4Vh5HACL\nkXMU8pqa8aaI+653hFdPZYreVo1k+ukXprzZmu3ViBJ8P2vsPpPE7KpqdMXMFcD8k2LH1E19VU3r\nBq3xkR6ffMjaa6oopLHbbLIfe63GUnHIU59hFCaDzLqv/zalG29lig9FbKXRs+eeZbFZUzemT5y8\nHqjtSvLrmtQoNeXbErFteT08NvcjapyotZlsQ6a8KQqLQkx4U9KeXcnYVfRa2qiRjHWNRY78HNs1\nGjaCIASmJGN34RimalNJCrK8GrmOi8unDwOLx8TOmVsQhuEbfsymxicPHKfbXlNFIY3dRoMNZvU6\ne9Np+q3U93xgkI3gvNVmTMZbmeBDEVtp9MKFF5iXRY7bBYA970bLb+H4uePJrkFotJrygqlPZ9rW\njyhy4qDUZgAwnsr/qbAC2oA3RT60FXu+oyhS8loCtmpkLowBsFMjSvD9kFVR44US5h8HAJY6DPk1\n2ju+l+WhXXpG7Jy8AWEYKXvkqYyP1Pjkg9Nlr6mikMZuq8WM22qV/VDSDSegOtBloRtvxWGKD0Vs\npFE7aOP15deBmdvTB+95N54++/SG7aarkTywtTRzkprixEGxH1HgRK/NhJFSl3JbqjxgzHhTxME8\nx2qUu5hyN+zSSKAtOT9UXwg4bNVo2Oh0ApYtYeY2tmP1ZaA1jyOxsZtXoyumpcwOAFDdAdR2xcau\nOk8K46MMany2guN022uqMG7sNptNrK6upv7jlvlWWFpawrFjxzA/P2+aVgqrq+zNfWyMvS23ujy7\nbFCQF67lnzowGW+lz4ci+tGo6lWB2TenT9z1Dnzv4vdTuwahUSu1sj//Q8/WfkSREweNNhPb3JPC\nrqP2h5n0pvB4VB0jzkaN0t7vdFibGh/7NKKEIIiNd27sAsDCUzg4eRBAfo2OzBwBmheA5lm2Y/J6\nwHHimN1hxlrb+QzpF47jdNlrqjBu7P7O7/wObrvtttR/H/nIR7Y874EHHsA999yDj3/847j33nvx\nuc99Tvutuhe4eOPjrOGzqVi410Nu0LwwGW9lgg9F9KPRaGUUKE8ghfI4VlorqV2mNEo99HxpylfB\nE2ZrP6LGiVqbySh5YlGFq2lYqHpTZH34NfKWUpZho0ayQdMK9D27dmpEC74fAtM3iR2LT+PgFDN2\n82p0ZOZIOoRh6gblUB9q4yM1Pv2Cj1tZe00VakWkt8B73vMefOpTn0r+vdUqukcffRSf+cxn8Kd/\n+qd417vehccffxwf/OAHcdVVV+FHf/RHjfNbWmIVcvibghywDyB5pVaJ+ROX6B1vlbujGOCTBe9I\n/A1YfLJt9k8ndaw414lpRfD9UDkPYT8ajVXGgFcfSp/YWekesA1pJHsEeL9QfjhY2o+ocaLXZmK7\n5ompN5V69AAzTD2Y8abwa2iFMVio0UYvTOy6iqEwFmpEDb4fojx9i9hx8TvYc/WvYqI6jrnV87mu\ndWjqEDAvlaKfvDbJxKDjSaUwPlLj0y+SioYZe00VAzF26/U6du/e3ffxX/3qV3HrrbfiXe96FwDg\nzW9+M+655x589atfzWXsbhX+4HkeJicnE/FmZmYAoKeXUCfmz2S8lRk+QKnkolIx2eQOPM9FGEbo\ndAIFo3dzjUbKdfb2ee5f06ctPYvDU4czVzKjkQxeelb1h21rP6LJiYFam1UkI8VVtCxMelOELvqe\nXZs0MpW+LsvHJo2owfcDlqmnNAr4a6yUfBThqtk34cT8K31fx4HDqq+dfFHsnLhaY2aZ2vhIjU9/\nyBq73F5TxUCM3Zdeegm//du/jXq9jrvvvhtvfetbN42hefLJJ3H33Xen9t122234i7/4i1z3vfPO\nOzf9/vbbb8df//VfY3FxEQAwMcGmx+V0PDJCqZ64aqlHwEy8lS4fAHDdwbzGu66DarWEIAjRavU/\nkG6l0VRtmu1Yfy194uIxHJ1N9xcOXY34OUEUmPGCaXKi2I+ocaLWZjJGNB8uAIx6U/hDykSImF0a\nCf48ptXEA90ujWih0/EBtwbsuAs4+89A4wyw/jqOzlyRS6OdoztRLVWB5ZfEzok3KebYpTc+UuPT\nL7i9krXXVGHc2B0bG8Nll12GarWKkydP4sEHH8T73vc+/OEf/mFPUc6ePYvp6enUvqmpKVy8eBG+\n76NUMkOTu8GXl1kuzslJFr+y0lpNHcf7hqmYYd14K1N8eG69KIrw7dPfRhB1sNZZw1p7De2wjabf\nxHpnHavtFaz762gH7cSA8EMfQRggjEKEYIsDDk9ejvcd/c+4fierNKPT6TfS6NzqOcytzmHXdZ8C\nzn5dHOyvwcmEm5vSiP8Ji83FZJ9K8n2TnDio9CMZFDhRazP51FFp2tBVXAGt602Rf5YmsjDYqJGM\n5IVJK64Z+tcgrBEFBEGEMIzgzr6FGbsAMPcIrt55Zy6N9k/sZxurL7PP0ihQ24Mwh+OmFyiMj5T5\nbAY+bmXtNVUYN3Y/9alPpYyer33ta/iVX/kV3Hfffbjxxht7npc1lOS4UFPgedrW1pgnd3R0FEA6\nRovBwAPBaLyVGQ34m9Jry6/hweN/qX29k0uv4E+f+BP8X+/5c6Xzt9IoiAJ8+l9+G3/4ns9g4n+Y\nA577A6B1ATj8Abxw8tvZqylxyCKZOmktJPsC5Wk/O/sRNU7U2kxG3ROJ0FWnnznUvSniWBPGro0a\nbZSNQWcRn40aUUSn46O6+27g2d9jOy48ioMH/ydUvP6rbe2b2AeEAbB2ku0YvRxwnMT20PGkUhgf\nqfHpF1z3rL2mCuPZGLId4z3veQ/Gx8fx6KOP9jxn165dWFhYSO1bXFzE9PS0dok4GTzm4+LFiwCQ\neJNX29kwhvSiLTWYjLcywUdgubW45TFRFCEIAwRhgE7gox100PbbaPmtrlRt0lk5mWyt0fFzx/H+\n//oB/LdXH0Pjht9D+NYH8B/nX8H/+a0/zlzLrEbN1CIV1R+4rf2IIidKbSYeMBUDC4tMelP4NTTn\nP9j/LdUoMBIKY7dGVNDphOk87BcfQ9kr43KeN7cPHJjYDzReB8I4Jdv4FQCgHMZAb3ykxqfPO8X3\nyNprqhhIzK6MVquFZrO56Uq6m2++GU8//XRq3xNPPIFbbrmlxxkbYzODGhCe3bm5OQBIFtFdbFxM\nHeckn3KDqg8QuvFWpvnUSqISSRiFmFudQxhFLEQhCpNwhc1wYHI/qqWqUq6+jbCZRguNBfyvj/xv\n+N///Q8xUh7BUmup63zTGrXj5PvsKorTx4Y5UetH1DjRarMIgIOqJ2Lk1D1ygzBONMJGkk87NUrG\nPp3QmuTTTo2owPcDYGySVVNbfpGV+w19XDFzBN967Vt9XWPP2B5g9aTYMXokfnHWf7ZRGh8p8tkM\nfCY6a68pX0+bkYRWq4VvfOMbaLfZG9LKygo+/elPAwB++Id/ODnu137t1/CXfymm0X/kR34Ejz/+\nOL75zW8CAI4dO4aHH34Y733ve3Pdf2ZmZtP/uLHLvcjT09MIoxCrmZhdDrkz5B33TMdb6fKRzxmT\n+Ky117HWXkej00DLb6ETdHLFdG2nRp2ws6Gha4qP/AxppxLLa8ZKW9qPKHCi2GYySqnpVNWH5/Z5\nU/LAJo02ykVsIuTDJo0owvfjxXY8BVnYApaewZWzV/Z9jT3je4C1V8WO0UO4sH6x9wlbgNL4SJFP\nv+D9VLbXdGDUs+v7Pj7xiU8gCAJMTk7i4sWL2LVrF/7oj/4IO3fuTI575JFHcOLECfz8z/88AODt\nb387Pv7xj+OXf/mXsXv3bpw9exYf+MAH8OM//uMm6SXgSYonJibQ6DS6BjX+1mLKa6kbb2WOD/MS\n6KYfMcuJgY5GDM2OmBKPVBcGWa4RNU6U2iyKmAFVcsQQq2pjbKc3pR/YqVF3XLNeEIONGtFDFAFh\nGMKdvQN49Yts5/lv4erd/dsOe8f2AOdPih1jh3Fx/QKmx3fwuyjzozQ+UuSzGbhnV7bXdGDU2B0d\nHcVjjz2GEydOYGFhAdPT07jqqquSLAAc3/jGN+B56beKX/qlX8JP//RP48SJEzh06JC2y7oXoijC\n+fMs4fT09DRW2ht4deNOoJziJbkXu5R2vJVhPiMlA2lsLNRI9ni0AgPxnxZqRI0T1TbjKLvCI6f7\ngDDrTdHgYrlGRmJaLdeIEoIggrvjLrHj4new78qPYrQ82jOtKIfneNgxuiOd3nL0EC4uXMTRuGCX\n6uwXhfGRKp/+buV02Ws6MB6zW6lUcPXVV296TC8LfceOHdixY8eG35lCq9VCo8ESz+/cuROnG2e6\njuFDiUo5vTTMxFuZ4sMGcQcVrwLP8RBEgXL8l60acciDpHLKp/jTTo3ocaLVZvH1Upqo/tbMeVP4\nA0TrGvGnrRoJ6Mfs2q/R8BEEIcrTNwFuhS0yO/9NuI6L63dfj2+/ns3ak8Z0fZoZbrIdUNuLxeYr\nmqyojY/U+GwN13W67DWt65kg9UYCT2MBME90s9PoOsYx/PaiG29lmg8AlGNOuh41mzRKlZ31RQlp\n1dKzNmqUxbA5UW8z+aGgbGJocxJGmxsP+Trmjp0amcUljbYPQRACXg2YuY3tWP0+0JrHNTs3d7oB\nwL7xfWyDpx1zq0BtJxYbCz3PyYNhj4/U+Wx+r257TQd29fo+wMWrVqsolUpJeVEZ/M235ArHt85C\nHt14K1N8ZPBKKsoLOizXqBNIK/sVL2SzRhQ5UWozDlceYjVjLVW9KTJ//pDS8e7ZqFHqWklHvqTR\nGwFhGLHf++wdYueFb+HmvTdtee6e8d2sYXg2hrHDgONivqln7FIbH6nx6fduWXtNB4Uzdi9cuABA\nxH9kq6cBYrCT46R0oBtvZYpPqmxgiRm7uh41mzSSf/zpnK2qlavs04gaJ+ptZmLlu0lvSnINrZBd\nuzVKrqlzbkE0ooIwjICdbxc75v4d1+26fssxaffYbqA9DwTxrNDIQQAs3aUJDHt8pM5nM7iu02Wv\naV1P+wpvMPA6y7zAxPKGOVtZg3qp1Bwa8Vua8Vam+MjerrEyS0HiOq7SQGqjRqkpcSPxn/ZpRI0T\n9TYzAZPeFC++hgnPrl0aiYONxEZbqRFdBEEI7JQWqc0/jtHKCA5OXrbpeXvGutOOhVGIVWnhuo5G\nwx4fqfPZ9F5Ot72mg8IZuysrKwCA8XG21HI9E7PrwEk6RKUkVi7qdHideCuTfFL59soi356XM9+e\nzRpxtAJRJU7FcCqCRtQ4UWyzVOywcoIIc96UUvxb1wlfslEjmT8fD1WNXls1oowwjID6XqAex+DO\nPw6EAa7fff2m5+0d39tl7M43FnI/E3uB0vhIkU/Pezmsv2btNR0UzthdWmKe3KmpKQBIvcEB6YeA\nvHJRBzrxVmb5iF5Zka6V98Fnq0ayDJ1QL/7TVo2yGDYn6m0WhMJIUS1SoOtNkaUwtTAVsEsjGSLU\nQ9HYLYBG1BCG8cstT0HWWQYWj+GGPTdset7usV1dxu7F9QvGNBr2+Eidz1b3ytprOiicscsDnkdG\nWK7ZRsazKz8EqlICZp10PTrxVib5yKekU5Dk6wb2aiQ48GpcqtPh9mpEjRPtNtNP82XCm9L9kqvq\ntbRXIwHu/VLt2UXQiBqiaKNQhu/iTTuu2vS83WO7gTUpx+7IQVxcv2hMo+GPj7T59AKnmbXXdFA4\nY7fZZItYajXWWC2pxCgAeFIBjHpJX2BdDIpPrVRPtvPm2yuCRtyTovpDLoJGujDNiWKbpbzNCh4i\nE94UWY5SPIXtOI6SwWurRjL4inVVw6AIGlFEJ+iIssEAsPAEjkwf6Rm2US/VMVIeAZpSjt2RA5hv\nzJPQiNqYvb18WH/N2ms6KLyx2/bTxq789lIvy28v6vfUibcyyUc2AsqpMAZ1z65tGmX5qE4ZFkEj\napwotRm3LfzI17qOaW9KvSSXC80//NuqUfqFQG8Rn60aUQXXqOW3gZlbxRcXH0fZK+OKmSMbnjdZ\ni4tbtebFzso0VttrxjSiND5S5NMLvE0vGbsaWFhgKUUmJycBAOud9dT3qQb1hPdTq8NrxFsNgg+Q\nidnNOajbqlE6/tNXuoZpTjIoaESNE/U260gzR5FCeIUJb4rMvyYZuyqeS1s1kpEYu4qe3SJoRBGN\ndgMoTwDjV7IdS8eB0MdVPUIZdozGFbkar7NPrwZUprHYXDQ+QwjQGLOp8ekF/tvL2ms6KJyxu7y8\nDEDOs7uS+t6RJKkYmsrQirEZAB8gvSI3bxhDETTy42lD9cUg9msE0OJEq83Yb6otF7pQuIppb0pV\nekjJBlC/sFUjuR9X4xcC13HVcpFaqhFdMI1WW7HjiocyBE1g+QVcNdvD2B2ZZRvrp9lnfT/gOFho\nzBvTiNL4CNDj0/NesU2Stdd0UDhjlwc889JzzUwFNTk1x1hFpLvQqsalEW9lkk+vBWp5B3SbNeLQ\nj/+0XyNqnCi2Wbpscf4LmfCmyIemPbv5h39bNZJRkxYnqXh3i6ARRXTCDi6sX8zE7T6Jq3ZcueHx\nk9VJIAyADsvliuoOAMBya9mcR57Q+EiRTy9kF6jplgoGCmjs8iTF3C2+kkk9Jns7xqsTybZaKiP2\nqRNvZZKPPEjKMUl5Y/ds1Uh+sIVQW9FvmhPjxT4paESNE/k2C8UopM9KAAAgAElEQVT0c6hyHQPe\nlF5hDK7C8G+vRmK7JFeZUjJ27dSIKmSNXlt8FZi+WXy58BSumLliw7y549VxoCMVlSrz0MaGtkZU\nxkeqfLaC6zLCWXtN65raV3iDoauoRLt3zO5oSf9tAtCLtzLJJ+3hkb0X6gvUbNMoC9WfcVE0osiJ\nUpvJRWvUYi3NelMqqZSDejG7dmkkDq5opGXMnmOXRrSx3mng1cVX04vU5r+LermOyzaopLZzdCew\n/rrYMcIKUiy3ls15UomNj9T49AJ/ybxUVEIDPEkxF6/h986zWy+zqQz1zq4fb2WWj0DFE8Zu3ode\nETQSb6smVvbbqBE9TrTajEEeX1Ty/5r2ppQ1vZa2aiQfOl4WD1aVSlq2akQdDb+BVxZPArVdopLa\n4jEginBkg4wMu8d2ZYzdy7DUXIIf+gY0ojY+UuOzObJFJS4Zuwrgq/tmZmbQ6DSSRPQcriO/AfOS\nupor1jXirQbBBwCqnnpcWlE00kFRNKLISRWm+Mi/p7WOCJMKFIwUE94UUzM6jI+tGom/YbQsrqGy\niM9WjSgiq9Hry7HxOhmXCW4vAM2zuHz6cNe5M/WZdI7d+n7MN1gaMlMaURsfqfHpBd6ssr2mi8IZ\nu+vrLGxhZGQETb/Z9b08uE1WWZyI6tuLiXgrk3xkyJ5dJ2c3KIJGYhDVTyxvo0Y0OdFoM/ndsa2Z\nMsqMN0WK2fVESiWVKXp7NRKolcXiJLVFfPZrRAVZjS6sXUDLbwGT14ovlp7D5dOXd51bL9cB6SUC\npbGkoqquRtTGR2p8tgIfy2V7TReFM3Y7HebGL5fL8EO/63u5fjifwtKd6tGJtzLNh5/Kc0kC+UvA\n26uROIdfU7W4or0aUeNEu8068rShwqVMeFPk+1ZKejG7RdAoFeqhlHrMTo2ooxN0ECHC6ZXTGWP3\nWRzZwNidqE4C7YtiR3UWa3HefVMaDX98pM2n573in51sr+nikrGbAX8DLhtcsaoTb2WeD+ucZWnB\ngmpRCds0kn+3qtWTOGzViBonim0m25DNQMwe6cZamvCmpFKPKQz/9mokThiRCgrIC7v6hb0a0cNG\nGr2+fAqYulF8sXgMl01e1pVhYbI2AbRkY3cHVlosr6spjYY9PlLnsxUuGbsa8H1m4JbL5VQ1EQ4+\nuI2WxYCnNgVlJt7KFJ8sSqlywWp5dm3WiP+wVQ0omzWiyAmg2Wb84Qlk4+X6vJZhb4qcP1QtjMFO\njVIL1BKv3iWNqGMjjV5f+gEweZ04aOk5eK6XyshQK9WY8dteEMeVJ9HoNLQ1ojY+UuPTHxhn2V7T\nReGM3X49u7IHRG1xgdjWibcyxSeLsqM+VVcEjRKPjmbJUBs1osgJoNNmMlY7a8n2Ri/X/XLSn7Vg\nf4dsyKktvrJXI45KKge5esYKmzWiCK7RqZVTQHkMGImN2+UXAAAHJw8mx87W4wVPDXmB2h4stpaM\neuQpjI/U+PSDS2EMmgiCAGHIGrhSqaCTMXblt/iaZ66komq81SD48HNT03M5BvQiaASIuD3dXKQ2\na0SNE5U2kz0pLe3pZzPeFH7OVHU64Zd3it52jTgqGtUli6IRFWyk0ZmVs2zHeFwmuL0ANC/g4JTw\n7E7U4iIFbZZ9AW4VKI1hpbVsVCNK4yNFPpsha6/polDGLneJA4DneV1vyHKDVku6A5XYVo23Mskn\nCzl/ZJ7h3GaNUgt54geeblJ52zSixolim8lopTwp+S9mypvC713ySkn1xLw5ZIui0WhZPdTDdo0o\ng2t0Yf0CM+rGpTLBK9/DgYn9yT8nubHLY3arM4DjYLW9ZtSTOuzxkSKffuA43faaLgpl7AaBMG49\nz0OYiX2S3xLlPLRqHV4/3soknyzSD7r+zV27NRLn8B+00mpsqzWixolim4ntVpzeMIqi3LXoB+VN\nqSq+FNiuET9npCzF7OYM9bBdI2rYSKMgDJh3d/yo+HL1ZeyfOJD8c7I6wQTg2Rgqs+yw9qpRj/zw\nx0d6fPq8Y5e9potCGbsymLGbbij5ISnXR9eFarzVoPgAgOOKa+cxDWzWKOUldJlB4DhO7gV8NmtE\njRPFNpPvvR6nMlJZVGR21kLKNhBP07qOm+vFwHaNOGRjJ2/GiqJoRAW9NHp9+fW0sbvyfRyYFJ7d\nmZFZoLMMcE9nbRcAVirYpEbDHh+p8+kXl4zdnOie/skYu9IPp+yJPLTDircyyScLV276HHaBzRrJ\n54xIcVt5p3tt1ogaJ4ptJoOn+lFZVGTSm5LWaTS5fp6XAvs1EqEePCQmb1yz7RpRhqzRqeVTwNgV\n4svVE9gxsiNp150js0DjtPi+vhcAsNRcMupJHfb4SJFPvzCdLaRQxm430gO9/ICU3+51BwXVeKtB\n8QHypxvjsFujbu8XkH+6126NqHGi12b8txVEQZLxJe/UMzDAWQvFtINF0qheYnG7eRc72q4RNfTS\n6MzKGWD0sDhw/VUAwN6xPQCAXWO7gfXXxfcjl2GltYp20Daq0fDHR9p8thOFNXajKOoa6OWBra6d\n205sq8ZbmeRjCjZrJJ8jv93nfeDZrBE1TpTbbLG5mOwLwvwr6M16U8RJcq7dPB5w+zUSKHs8s0fe\nBWrF0YgCeml0dvUsSz9WiVOMrTFjd884M3Z3jMwCjVPiQvX9WGiwzAz6nlSxPezxkSIfFZjw8hbK\n2JXjPoIg6BrInFQgfxU6MBFvZZJPFqqdpygapUqG5o3/tFwjipwAem221BIJ64MNcnpvBZPelF7h\nHnmMOds1Si12jP++3HHN1mtEC700Ord6jv1jNM6tu34KiELsHN0JAJgdmQWa58SF6rux1FoCYM4j\nD9AYH6nx6RdZe00XhTJ2SyXxxub7PrzMQC//eyT19qI3KKjGWw2Kjw5s1kg+h3t2gPyLVGzWiBon\nym3W9OX4OJV0USZnLSTPrmzs5sg2YL9GYrtWEt7vfKEedmtEFVmNzq+dZ/+o72OfkQ+0LmDHyA64\njotdo7sSby8AYOQg5hvMYDap0bDHR+p8eiGKoi57TReFMnY9z0sGrna7OzYn/fZiJv2ITryVST5Z\ndEI5uXT/FyyKRhWNKXHbNaLICaDTZhxt+TcGlennwXhT0gv5VD27dmskxzXn6UtF0ogSshotNBaZ\nQceNXQBYP4UdIzuwY2QHezFefUV8N3o4MZBNeVKpjI/U+PSLrL2mi0IZu47joF5nb+yNRgO1UrpT\ny1N6dSmxuNq92KdOvJVJPlm0/FaynS92x16N5B+uXFbV1ag0ZZtG1DhRazPZLpJLc6p45MzOWojt\nupRayclh7NqvkTgnvYjvkkYUsZlGQRQwT21dpBtD4xR2ju3EvnGWeQFrsbHr1YHaLlxYZ8aurkaU\nxkeKfPoBX1Ml22u6KJSxCwCjoyztztraWlejybXiR8vjWvcxEW9lko/gxT7boeKqTIs1knUYl66V\nN42VzRpR40SxzTiaHTG1mrcOPWDamyLHo4pr5YnZtV0j+ZzROD0bkK8v2a4RVWyk0fm1OWBENnbP\nYLY+g/0T+4EoBFZPsv1jlwOOg7nEs2vGk0phfKTIpx9w3WV7TReFM3ZHRthb2/r6emraE0inaOEL\nFHTffnXirQbBhyNdIztHGENBNKpXxMMud6WpgmhEjROFNuud01Il1nIwsxZy0vxcU/TWayTuP1md\nSrbz5Nq1XSNK2EqjpeayyMYAAK0LmKxNsYwMjTNAGM9ujh4BAMytzQEwpxG18ZEan83Ary3ba7oo\nnLFbqbDpqXa7nUoxAiA1L+LlLBPZC1rxVgPgwweIViDCGHJ1/AJoBGTSM+W9bkE0osaJWputSdWK\n8iRw34iHSW9KTQ5jyPMIsFwjeRgck0Ji8sQ1264RVWyk0YX1C8DIZeKg9R9g1+hO7B3fm16cNnYY\n7aCN5SYrpWtKI2rjIzU+/UC213RROGO3XGaL0trtdiouC0iXmPDcjCGcA6birUzx2QgdOYwhR8yu\n7RrxN8pU/GduL6EZThQ1osiJVptJaX584Y1QKfM6sFkLT9WzK2CjRvJ5E5WJZDufZ1fARo0oYSuN\n5rJhDOunUPbKuHbnNV2L0y6sXUieg3oeebFNYXykxqdfcHqyvaaLwhm72TeFdDyW9PaSM+avF/Ti\nrczz4UgHqOfp+HZrlMQKaRhOtmvEQYUT1TZTDRVKYNibwinUFBeoFUEjjvGKFP+da7FjcTSihI00\nOr92HqjtAXg7xBXTDk8fBlZPiJPHLse5OIQBMKcRlfGRKp9+cMmzq4Fqlb21cfF6lc7kDaoToA7o\nxVuZ4rMRmoq8bNeID5T1Uj3pG/kednZrRJETrTYT2+kYOYWFRdK2GW8K+4NK0rXy5JAthkYMI2W1\n+O8iaTRsbKXR3Np5wPWYwQukK6atfE9sj1+Jsytnkn+a8shTGB+p8ekXfEzP2ms6MNrzwzDEP/7j\nP+Lhhx/GK6+8gomJCbzlLW/Bz/7szyaBxhvh8ccfx9/+7d927f/MZz6TuxLSVhgfZ2/sy8txfE5l\nNEm0LN+pbKg+tk68lWk+spSNjkjlkYeX7RrJP+CJ6gQurF9IGQfD4ATQ0oiDCidKbZauVqQXazko\nb0pZfsHPUx1MvoalGvGURyOpohI5jF1p21aNqGArjebXL7Id9T3M0G2dZ4OF4wArL4kLjV2B0y8/\nlvzTlEZUxkeqfDYDH9Oz9poOjHp2W60Wfvd3fxcTExP4wAc+gDvvvBN/9Vd/hV/4hV/YdPrltdde\nw9e//nXs3bs39d8gMDPDVmfOz7M62BNVEZvlGBoUTMVbmeIjX5Gj4at1fNs1kvsp9+7kLhlqsUYU\nOVFqMxnpRaAqKaNMz1qwz4q78WzWlnwKpJFcQU01Y4WtGlHERhqttuNnXHmSfUYh4K+ybW7sjlwG\nlEZwdvVscr4pTyqF8ZEan37Bx/SsvaYDo57dSqWCf/3Xf01yowHAVVddhfvvvx8vvvgirr766p7n\nTk5O4ld/9Ve17r+ZIOVyGePj4xsYu9LKS2lMyzsN2gta8VaG+aQ8u77k2c2TYNpyjWRUMyEufXMr\niEYUOQ27zeTfmGqVwg0oGfWmpMIY8pxYII3ka+V5aSqSRsPGVhrNN2J7oLZbHNg8BwRNoB3nnJ14\nEwDg9Mrp5BBTGlEbH6nx2QxhSNzY9TwvZegCwJ49LF6m1WptdEqCKIpw8uRJtNttHDlyJFUXuV/c\neeedm3734IMPYmqK5U8UYQxjGx6vEz5hMt7KBJ+N0JB5KZSgBOzUKFVFyZXLz7raXpX854ptKhpR\n5ESpzeSnAl/9rKrNoLwpbmpCT+1vtV2jXguX88B2jYaPzTVq+k20/BaqqVy7F4GGMGwx/ia0gzYu\nrJ1HJa6oqudJFdsUxkdqfPoFH9Oz9poOBh6t/jd/8zfYv38/rr322k2PO3PmDN73vveh0+lgenoa\n999/P37u537OGA9ebi5bkSNbMtgEzMZbmYPMK9Xxc5YONM2FkkYyqlLRke34gWdBUSOKnGQMu81k\nBCGbKlRO8zQgb4rjigsPVyG6GsnXGnI3IqsRJfTSaL4xj711KSSycRpoipAFTF2HHyz9AKGUkUjP\nI09rfKTGp1/wdjRZQW2gxu6Xv/xl/N3f/R0eeOCBJF/aRrj11lvxta99DYcPH8ba2hoeeOABfOYz\nn8EVV1yBu+++2wgXLtbEBIvRXVxkdaLHq4NNsq0bb2USg3jLMwFKGsljZUkqOpInbm8QoKQRBxVO\nVNuMx8XlyWPdCyYN95Rnd9iGHFGNhv2iJIOqRpTQS6O5tfPYO3JA7Fj/AbD8gvj35A34/sWXU+eY\n0ojK+MhBjc9m4GN61l7TwcBSj331q1/F7/zO7+Czn/0sbr/99k2PPXz4MC6//HI4joOxsTF87GMf\nw0033YS///u/N8ZnYYHF6OzYsQMAcPEiW6k5WZvc8HidpNsm461MnMsh/4hX2mJaIFRIVK7LiapG\nMqqeYqUpCbZpRJGTDFpt5mtfbxAwHe6T//5im6pGJnBJo8GiH43Or80BKWP3FLD0rPj35LV4ZeEV\nmAK18ZEan37BY3az9poOBuLZ/drXvobf/M3fxB/8wR/gPe95T+7zHcfBzp07c1vzjz766KbfR1GE\n3btZsPrp0yxuZ+fIzg2PDRHCg+p0hrl4KzN8YlZSx19trybbgWIYg40ayT/kVMlQxakt+zSix4lW\nmwn48cPFhEeOGmzXKLVaXZGa7RpRQi+NlprLwMwRsaOzCCweZ9v1fUB1BicWTsAcqI2P1Pj0hyiK\nNrTXdGDc2P3617+O3/iN38Dv/d7v4X3ve9+Gxxw/fhxjY2O4/PLLAQCdTicV5nDu3Dk89thjuO++\n+3Ldm6/c2wz79u0DwGKEAWB6ZDr5Tn5oBmEAz9NvUJ14K/N8RMdf66wm180ziNqukUwhZTjlyLVp\nu0bUONnYZlnw/K/DRJE04ryAfEZmkTSihF4arbZXgZIUqrj0nMjEMHUjAODl+RNwpTh2UxpRGR+p\n8tkKYRh12Ws6MGrszs/P4xOf+ASmpqbw8MMP4+GHH06++9CHPoSbbrop2b7jjjvwhS98AQDw4Q9/\nGDt37sThw4exuLiIhx56CGNjY3j/+99vkh4AYRAvLy8jDEOMlcXDUe4CfuinqqupQifeyjQf+ffL\nE0znzbdnu0byFWupxU45DCfjnKhpRI0TnTaTH5KqWU42gklvSt7fPEeRNPLjaXEgn2O3SBoNG/1o\n1PSbQEnKuHT+v4vt6Vuw0lrBmZUz2D+5L3UtExrRGR9p8tnynlHUZa+5GqWcjefZ/ehHP7rhd2Nj\nosN9+MMfxtGjR5N/f+hDH8I3v/lNvPTSS6hUKvj1X/91vPe9702qZ5gED3iOoghra2sYq4hUafLb\nSzNoYqQ8orQS11S8lSk+ghc7ueW3xJRGzhAG2zWSKVQ8OY1V/xe1WSOKnCi12YbXVj1vQN6UKBTX\nzdN0RdCI/z2q8Y1F0IgyshqttleBytTGB8++GS9eeJGdZ0gjauMjNT757tltr+nYhEaNXb64bCtk\nDeJ77rkH99xzj0kqPVGr1VAqleD7PpaXlzEyKsoYR1IsS9vXr8UM6MVbmebDjd2F5kKyT/ZgDIMT\n40BHIxkVVS9hQTSiyIlSm4kHhJqZMmiPfPddtuBTII3S4+Iljaijl0bz6/OAVwUq0yJ8gWPqRnz/\nlce7zjKlEbXxkRqfre8ZddlrOsbuwLIxUIXjOIlrfG5uDjN1EecbSm8vPE2HbuyOTpyMaT781MWW\n+NHnndK0XSMZNWllfx4vYVE0osiJUpvpIutNAczkfJV/83larhgasZPTqRn7V6kYGr1xcGE9XsVf\n25P+ojwJjB3BixdY2eBBaERtfKTGZ8t7hlGXvaaDwhm7ALB3L0syPTc3h/HquFQ+U5rKiDobnNkf\nzMVbmeEDpH+4y1LaMXkhxnZyoqhRFrWSahorezWiyEnGsNtMhtBK7aFgfmaHfaqnICqORg1/PdmX\nb/W6/RpxjIxUUv/VauVN/6vXy6jX2bH1ehmeZ8786KXRQiN27NR2pU+YvQNwXDw79xwAcxpRGx+p\n8ckDnn5Mttd0UEhjd9cu1vHPnmWVVGbrswDS7v1OoLaIoxdUJqAGxSedXDofsyJoxCURL0H53vKL\noFH6+irnmOVEp83EdXiZVlX/x6C8KcpT9AXSSPbsRjmM3SJplIXrOpv+5zhO6jfpeQ5KJTf+TuWO\nW2s0txYbSKOH0l/sfidWWis4tXwKwGA1ojA+pq+tcs5gnyEbgRu7WXtNFQMvF0wRPHfb+fPnAQCT\ntQmcWzuXWqxh6u1FJ97KJB/5h7vWVi8baLNG0lUBOKhKcVturvhP85zoaUSNE402k6/jKJsnydWS\nLTMaMT5txZdd2zWSbZt1Rc+u7RrJaAdt+KEPz/HYf66Xes5EUYQQIYIwgB/6aAZNtP02WkELQdRB\nJwhQL9dxcOIgAGB9PZ9HtR+N2kEbp5dPY9/sHcAr/4XtvOx/BK7+VXzt+X+QjDjzGtEaH+nx2Qp8\n8XzWXlNFIY1dnhlidZXlmq2X6wCASHLzd3JP75vHoPisSTWy86ceK4ZGQLYaV46V/QXSSBWD4kSp\nzVzHRRAFysaKaW8Kt0PUvZa2ayQ4rKfGyEsaySiXPfh+gNXOKv6Xh/9nrWt99NZfSoxdHWym0UMv\n/jfcf+uHATjAyH5g/4/j6yf+FZ//jy8kxwzDc7kZqI3Zw+DDDeysvaaKQhq7fEXf8jKLXR0ts/Rj\nspej0Wkk246TfrPJA8dx4jeq/AOVST7yG7c8kOdNPWazRhxRxM5PVeBSXOxkq0bUOFFsM8/1WHys\n4nTooLwpjUB/8ZWNGskUeGpGdo/+x0jbNQKQhB6stvJl8tkIzY6YZRiURv/lqf8bjuPgnZf/MFpB\nG//1G7+L/+/7/5w6ZhC/NUrjI0U+W4F7orP2mioKaexOTk4CkIzdONduKL2xrPnyW4SDfK5/0aEc\nOIgQKb2Tm+OTHgNWO1Kp4LzZGCzWKIuKK6bE83hV7NaIIieB4beZQNkto4lmrqwQMgblTWl21Kbo\nC6WRrxbqURSNPM/tKjMvzxhIN0cU+01ZCdgQY1WRc387NAqjEA888SAeeOLBnueb04ja+EiNT//g\nxm7WXlNFIY3d0VFm3K6tMQ9ntcRyc8rTVXJca963F1PxVqb4sHMEj1ZqIM/n2bVZoyxkL2Ge54zN\nGlHkJINSm/FcnXlih2WYndkR2y3Za5ljhbb9GvWY/coxRtquETuP6SQvdF5uruD8Wn8xlavtNewZ\nZ3GYtmlEbXykxicP+HWz9poqCpmNgbvFV1ZWAABjFfamKQ9qTT/d4VXBf3wqHW0QfLLXymvsFkUj\ndg21ixRFI4qcht9mYuSvxmnQVB8ym3tT8kJ62VUOY7BdIwHVBWpF0mitsyLucUmjLlAbH6nx2QrZ\nMAZur6nikrELaYHaBulHGNRbNPE0KfQKk3zk2zfizsqmlfK9ltms0WbXVj3PZo0ochp2m6W8TXFI\nBUu5lP/v2sybkhfyOalsLDli9u3XSPbsSsZujmlt2zWSIXtAwxzhcEXRiNr4SI1Pv/e8ZOxqoF5n\nxm2jwX6sPBF96u1F8n7odPiyWwaQr5oTh1k+4iSeZzOvV9c8JwY6GplBUTSiyEkVpvjID+CRsihF\n7jneBkfn4KTpTZENgMXWUrIdRP0vMrJdI1d6Gi5JGvk5DDnbNZLPaZqYIbBQIw5q4yM1PluBt2/W\nXlNFIY3dbAxILYnZlaYyUm93Gm+cGrFEpvhsdt1hcaKuEZCpOJPDYWizRhQ5yRh2m8k3lR/AKhoN\namZnrS0tUM3h2bVdI/kcXkEtjMJcswW2a9TT+50rrtlejaiNj9T45EUURZdidnUwMsJ+GOvr7MfK\n433kKb0VqaTusGKJzPFJn5PUyFZYRWmzRlnIpZTzaGW3RhQ5CQy7zeSHS9WrJtuUvCntUCxQy5eN\nwW6NUl7LOLNA7jUNlmskoxmoLXS2WyNq4yM1PvmRtddUUUhjN5ukeCQpKhElD8uVlogP0Xqb0ogl\nMsUnCx6fpBLfWASN+Kly1oo8WtmsEUVO7Dz2Oew2k8GnDVWvY9KbIp8jV1C7pJGAfA6PRw1ypqGy\nXyOx3ZA8u3lLKtuqEbXxkRqfvIiiyFhRiUvGLoBaqZ58xzu9/HaXFyZjiUzw6bpmHLOr4tk1xYm6\nRkBm1XpOrWzViCInGcNvM3HPsic9gBWG2kF5U+SCCWGO1GOA3Rrxc1bbq8nfmad6GofNGsnT+vLf\nl1cnWzWiNj5S45MXUWSuglohjd1ymf0wOh1WKaXkinTDfDqjE3aSxh1mLJEZPmnwBWqqK9ft18hJ\nrseRVyt7NaLICaDTZgIVzalVk96UjaboVbKx2K0RO+di42KyjzsG8sBujcR2JxDaXOpH4kocNMZH\nanzyIYqiLntNFYU0disV5s4PggBhGKKcMnZZ54iiKJVaJQ/MxhLp8wHSg5SqR9ckJ4oacXAKDV9t\nms4UJ4oaUeQE0Gyz8YqoFOW6+T0pgElvihzGwDy7atlYbNaIQfbs5Q1jAIqhEQD48otlzmeKrRpR\nGx+p8VFB1l5TRSGNXf6mALC3BU82dqXBjQ96w4wlMsdHnMMHJlWT116N0mjK0715PRcF0Igip2G3\nmezhGi+PJ9sq04aAOW9KyrMbx+zm1QewWyOOlq+WUis5x2qNxDktxdhvwHaNGKiNj9T49IMo6rbX\nVFFIY9fzxI8hCAJ4kktfDlRfaC0CUInbMRdLZIJPFqrhCxxF0AgAOoHsuVCLSdPhRFEjipxkDLvN\nZNQro8m2bhlTkzM7rSTTQH6vpa0apfRRLKfMYatGwMb9iF3/0m+Nn8tBYXykxkcFWXtNFYU0drNv\nI/K/5WmrpeaidIzavXRjiUzzSUNxgVpBNJIXO+V9QSiCRhQ5UWqzuicWvnqu4gPY8MxOO2gnDy0V\nr6W9GklhHqGcUuuSRjLSMwQaxq7FGnFQGx+p8ekXprzHhTR2s3Ef8kPRlxp0ta0WqG4ylsgEnyzE\nuWrXsFmjtIdH/aFnq0YUOVFqM0CMJyl9FL1Npr0pbU2vpa0aycc3fPmF6ZJGaUjZGBRzEQP2akRt\nfKTGRwU6cboyCm/sep6XSpuSTi7dggpMxhKZ4BOzSrZ4UmnVLmqvRukfbjNV+z3vYic7NaLIiVKb\nAeIBM2riAWzIm8KP14mzBOzVSD5WfpDnqTDHYatG2ePX4jy7aov47NSI2vhIjY8KsvaaKgpp7MpB\nzuVyOfVGJ3cOEzWydWOJTPGRn2u8o6tUUjHJiYOKRlksyw+9nPGNRdCIIicKbcavUy/VkxKdnuIK\ncXPeFHZ8U3Pxlb0adXssATWvpb0apdHRyOpRBI2ojY/U+PQDx+m211RRSGO31WJvJaVSCa7rpha1\nyIs25EFP1Q+qG0tkmg/jwbJPqP6IbdYoXftdVNLJO5VisxlPgr8AACAASURBVEbUOFFrM9mGnKhO\nAEjn8s7HyZT3m322AnXPNzvHXo045Ny6SiXVLdaI/9aCKEheJtVmCOzViIPK+EiVT7/I2muqKLSx\nW62ygO12jzg/ecpP9Y1TN5bIFB8ZlTgFibqxa69G8jnt1EuQWs5WXU4UNaLGiWqbAcBImXlTXMdV\nmkkx7U1ZkUqh6uTZBezSqFc2hksapcGPX2otJftUqszZrBG18ZEanzxwHKfLXlNFIY3dtTU24I+O\nsh9H05fj2KS3O18/ubRuLJFpPgBQKVWU+QyCExWNspALFOR96NmsEUVOHBTaTEY1nloF1F4uTXhT\nUnGWbVFyUyX1mK0aycem45pVpuht1Ujce/VSP+oJauMjNT554Djd9poqCmnsNhrsra1eZ279XnFs\n7dTbi9oqUd1YIlN85AVqPAWJasyuvRqlz2n4Ooud7NWIGieqbQYAFVdO9zMsb4psyEljndLiKzs1\nko/thOqFSbLn2KSRjIbGQtAsH9s0ojY+UuOTB47jdNlrqiiksZt1i/tSje9QSscjT4nmhalYokHw\nkcMYVAxeWzUC0gObPJWVu0KQxRpR40StzWTIJTrVXiz0vSnp3KhSyJZKPKqlGsmQFyopxewWQKM1\nXzMcxmKNqI2P1PjkxaUwBg10xexKb/LyA1J+wx9WLJEpPjLk8sg6nj1dThQ1kvVYixc7BWGQ+6Fn\ns0bUONFrM7Fd8sRvTacePWDGmyKnZlObordfo1QVPs2MFTZpJB+70lpOtlVSj9mqEeNEa3ykxicP\nLsXsaiLrFm9JMbuAVCPb2BunbiyRPp+UZ1fiozIomOIkg4JG8r2jKMJKi6WfURnMTXLioKIRNU60\n26yWbKuU6DThTUllq5A83yo5ZAFbNRLb3NBR8VgmnCzXSDcXMWCnRt2chj8+UubTDy6FMWige4Fa\nesqCv8HIHt/8QermYolM8EnH7ModXnWRmo0aCax11pLUOr7CAgxTnChqRJETQLPNxqRFISpxcia8\nKfKx8gI+lQpqMiebNJL5d8JO13VVOdmlkYBuJT6Zk20aURsfqfHpF9wYv7RATQPz8/MAgOnpaQDA\nSms19T1/e5F/0Dquet1YItN80h1ez7Nrm0b8nHTsp57nwjaNqHGi1mayjZR6ACu+WOp7UyTPbkcY\nu7oeOZs0kvn7cZ5dlXjdLB+7NJIWgmrma5bPs0mjLCiMj5T5bAbXZRfO2mvK19Nm9AbExYsXAQCz\ns7MA0qUBAeED1ZnGMhlLZJpPxRNVSFSmewbBiYJGgBgAVlKpdRQ9FwY4UdSIGidqbSbPotRSD5fh\nzKKkc8jKOcUvabQRdIolJHziT5s0Ss0QdPSqzAF2asSuIbYpjI/U+PQLPq5n7TVVFNLYXV5mwfWT\nk5MARI3vBHHvUI37y0I3lsgMHzlIfSTZVs21a6dGAguthWTblyoq5YLlGgG0OFFps/SL5fBnUVLG\nbiqnuKIxZ6FGMvjfpW7qwnqN5HAY1RkC2zUCaI2PFPlsBl4sLWuvKV9Pl9AbEYuLzJM7McHScKy2\nVlLf8+mrQIr704nb0Y4lMsJHbPMVmYyPqmfXPo1MrjY2xYmaRtQ4UWwzGRUT3qb4U92bIv4AefGV\n6jS9nRoJCM+uhjfNQo3k31oqX7OyZ9c+jQBa4yNFPv2C97esvaaKQhu7ImY3a+zyT/lhoD6VoRtL\nZIaPOHeyIt6QPMU64jZqlF7Iox+TZqNG1DhRbDMZNcmTouptMulN4dOzJqbobdJINuRMGMw2aiRD\nLqms2pds1YjS+EiRT7/IGruXYnYVsLrKYvvGx8cBpNPxMLCG1HkgmI0l0ucjnzpVk4xdJ//bnSlO\n1DSSkY5tVL2mrRpR5ESpzQRqJc1pQ5jwfottnlJJXR/GCLBLIxnc2NX76+zTKNWP4nCYKIo0FvLZ\npxG/SsKJxPhIjU9/4Lpn7TVVFNLY3axcMANTWacMntlYIn0+Mqfp2kyyr6QwlWGKEzWN0rGNok+o\nT2fapxE1ThTbjN2ffZZSBVwUr5V86ntThNdS52Flt0bdV1WBjRqJY5NQj0sa9eQDDH98pMin7zvF\n9zCVZ1dtDnsLhGGIRx99FHNzc7j99ttx4MCBvs574YUX8Nxzz+Ho0aO48cYbB0ENALC0tARAxIDI\ndb4B0bXTFUbUf9S6sUSm+ERRBMdxMFUT0wEqcTsmOXHQ0Eic2zQQk2anRtQ4UW2zCICTSuKuvBjU\noDclNGCk2K6RCdiukYlcxLZrBFAYH2nz2fResbGbtddUYdzYnZ+fx/3334+zZ8/i6NGj+K3f+i18\n/OMfx/3339/znDAM8elPfxoPPfQQ3vzmN+PJJ5/E2972Nnz2s59FpVLpeZ4qVlZYjO7ExARafqtr\n5TZvSPkHo9P3dWOJNuIDAJ7nwnFYp3AcB67rxNuio/DbOY4Dz3Phug5qKOO37vktAMwDxleeRlGE\nIAoRRAH8oAM/9Nl2GMAPfbT8FlZaK1htr6Jaqv7/7Z13fFTVtsd/0/tk0iGAAkIooQWwgChSr/jE\nUEWu14AdRURA1MtDQSHApYiADwtcKVKEAFcQBWkS5IHwUIqUiOGCgfTJTKb3Oe+PYR9mCCUJSU5u\nXN/PZz6Z2bPPOSvr7LPW2muXgSfggS/gg0QiAscBHCcKe89VSmc1oaPK3rPwy7rDttYJXBc4KaVK\n6BV6qKRKKGUqqGVqqKRKKKSK0EuigEqmQkNdAyhlKqikSsjl7FHjrr4XRVwv9L78/81xHMRiMQAO\nrROS8ULn5+EL+uDwOlHmLoPD64DNa4fDa4fT54LdY4fT50SZ2wyzqyxyOK6a2zVQc/ct1J5ZOxaF\ntfNr7V0kCj0D7Dno07wX7m9yL6QSGfwBHyRiacS8tFD7DsAX8MMX9MEb8MLpc4ZeXiccPgdkYhl8\nQR88AQ/EYtFV/YSuVRVdRa5+rmo2pPqyKQqJHPHqeEjFUtwddTeildFQy9VQSpWQiWVQyVRX27Ac\nSqkKcqkcUpEUErEEUnHor0qqhEgU0rlSGdrGkOM4yOUyANee+2s2gIuwCcEgd7Vdh+6tUnotY1MX\ndCQSia4GO3cwSnQTmy0Wi66+xPz7a7Y7Un5WDgAN5YmY8vDf4Q/64fV7Yfc64Pa74PCG2q/da4fV\nY4Xb74Hb74LNY4fNY4XD60CJ03jVxlffKArzmXcyHaay9ihcX+H2QCaTQCQSIU4bi9Gpo6CQKCEV\nS+APBiATS/l2KxKJI+xBkAsiEAwgyAVDeg14IRFLEeSCCHIByOXSq202MgDmOA7BIMe341vJXBf8\nWmXlkYgkUMlU0Mg0UF71aUqpCrHqGNxlaAKNXBuyFzLJVbsogUwm5X1YeMwRCbMD4e+56+IFjtev\nRBI6Xq/XQ61W171gd9GiRXA4HNi5cye0Wi327NmDsWPHomfPnmjVqtUNj9m5cye2bt2KLVu2IDk5\nGXl5eUhLS0NmZiaefvrpCl+bbT58M6KioiCRSLBp0yY4HA506NABIpEIbz/0Flw+F6weKzwBL9Qy\nJdxXg2Dm8O7EhobPJYpSRoHjAJlYBplECqVMBYUk5FxUV4MmpVSJaFU0DCoD4tSxiNfEQy3TQCNT\nQ6WSlzOKlYHjOAQCATTRNEYgED4vKXQ+iUQCmUx2NcC6M8KdG2vczECwv1KpGBwHxGli0TquFZw+\nF5xqJ9QyDVw+F3xBL4IcFzJAweBVQxQKyLmr5eHyS2+z4I7pLtxoisXi6wInEfon98Mj9/SEWqaC\nXCKHXCKHQqKAWqaGWq6+5TUqQzAYhN/vRyAQvKqXa4G1WCyGXC6HRBK6FzFSA3o261mp81vdVpS6\nSmFxW+H0OWD32mH32iGVSgBwEImAQEACjgsiGKx8RuNGbTu00j8IEcSQSWRQiOWQXw2gZBIZNHIt\n9Aod4tRxuMtwF+LUsTAoo6FSyRAe2FaW5Phk/j3HcfB6vfD7r3VkRSIRpFIpZDJZpc+v0ymvM8zl\nHV7ocxAcd61NyaUyRCujYffaoZarEauO5fVTkXYN3DibIhKFnEFkWy7fGRCLRZBKJfznpQOXVlqv\njGAwCK/XG9FGfT4vpFIpJBIJpNKq2SS1OhZfDl0Nt98Np88Jq9sKpy/U+TC5zHB47bC6bShzW0KB\nnNcGi8sCh88Jt88Fp98FpVRRTkeVyzhdC25FEIEDB41MjXtimkMikkApU0En10Gr0EAhUUAmkUEn\n10Ej14Rsg1QBrVwDtUwDpVSJeE0cNDIN5FI5VFJ5pdobx3Hw+/3w+bz88yiRSNAyuiUkEkmVng2b\nxwZPwAO71wG7xxYRyLGOXHi7Dslxrex6s8Dap0wiRQNd4tWgkbtt22YdKrVMjbsNd0Ov1CNaGQ2p\nNGR3ZTIJ5HJpRAeAdQ5uhxxS9Gnep1x5MBhEIBBAIBAoZ19D7VZ6W50qFLJbfh/u01i8wHHA3TGN\nMbTtUHj8HrgDbpidZti8dtg8Frj8Hji8DljdVv7+VNWv3YhIHxd6n6CNQ5/mfaCTa6GSqSAVy6CV\na6GRaxCtNCBBkwClTHn7k99GF36/H36/j9d3qHMnrlJsceDAAQCIuHdVQcRV47gPx3Ho2bMnnnnm\nGbz44ot8We/evTFy5MibZnfffPNNWCwWLFu2jC97++23YTQa8c9//rPC179ZMM04cuQIoqKiYLVa\noVQqIZdXzggxwnt4zCCEPkfWY73yAOeH2W2G8mogK5PIKjXMwnEc3G43rFYrTCYT8vPzUVRUBKPR\nCKvVCofDgbKyMphMJphMJthsNng8Hni9Xvh8Pni9XjidTjgcDrjd7go1GtYwWXAgk8mgVqsRHR2N\nqKgo6HQ6GAwGaDQa6PV6REdHQ6lUQqlUQqPRRNSJi4uDRqOBRqOBQqGolM59AR+fhfMHrmWaA5yf\nNwpBLshP0ZCKpWisaxKRiQvvcVb2fvt8PthsNl5/NpsNhYWFMBqNcDgcfJndbofL5YLb7YbL5YLd\nbuePYy+v1wuPxwOPxwOfzwefz1eh4FIqlUboVqFQQC6X83pmL51Oh6ioKOj1eiQkJCAxMRHx8fFI\nSEhAbGxshUdJrs/IRZaFYJ1Af9CLfEcBpGIJHwSopKEOQmWmyAQCARQXF8NkMqG0tBT5+fkwm828\nju12O5xOJ2w2G69vpmObzQa32w2fzwe32w2Px3PbNi6TyaBSqaDT6aDX66HVaqHX62EwGKDX6xEV\nFcW/NxgMiImJQVRUFLRaLXQ6HeLj4xEdHV2p9uQNeOHxexC4OlLiC/oRCPrh5wIIXs0wAaEsDnvJ\nJDJIxVIopKGOVlWcnsPhgNFoRHFxMfLy8nDlyhWYzWaUlpaiuLgYVqsVTqcTbrebb+cejwcOhwMu\nlws+ny+i03AjQoGKDHK5HHK5HFKpFCqVClqtFhqNBiqVCkqlElFRUYiOjoZer4der0dMTAwaNGjA\n65bpWqvVQqlUVkq/QS4Ij98LpVRxy0CtvOzXOggA4PDZIZPIIjpyFYXjOPh8PhiNRpjNZrhcLlgs\nFt5OOxwOlJSUoLCwECUlJfzLYrHw7fpWuhaJRJDL5ZDJZNBqtbzeoqKiEBMTA7VaDY1Gg5iYGBgM\nBhgMBjRu3Bjx8fGIiopCbGwsoqKiqpzMYPbK5DLDH/SFbPHVNsyF2WEg1I5Z22WjXeE/VX87XC4X\nTCYTzGYz8vPzkZeXh+LiYlgsFjidTt7OOp1OWCwWmEwmXscOh4P3feFJnZshkUigUCj41/X2gelW\noVBAr9cjMTGR1yWzCXFxcYiNjYVWq620nwNY+/XAF/QhEAxc83tXd4Zoomty9R5EJiWu929V8XOB\nQAAlJSW4fPkySktLI/ya2+3m221paSnsdjscDgdvj51OJzweD39PbufXWCwRbh+USiW0Wi2fwY2P\nj+ftQFRUFOLj49GvXz8olVUPxKs1s1tUVISioiKkpKTwZSKRCG3btsWJEyduetzJkyfx2GOPRZSl\npKRg8eLF1SkepFIpvF4vDAYDLxszEixQYDeAGQq9Xo/Y2FjExMTwRps9ECqVig8+2APCejAsg8oe\nOJ/PhxJ7Cf9wMkfCnLXD4YgweEVFRSguLkZBQQFMJtNtnU11EwwG+cAsnD/++OOOzqtSqRAfHw+t\nVovo6Gg+EGNBs8Fg4IM3rVbLGw7mLFnwrZQpIZFIIJFIIJaIeeMdCARgtVp4vbvdbrjdbni9Xjgc\nDt7Bs06B3W5HaWkp/4AzA1pWVgaLxcJPjhcSv9/PB3dGo7FK5xCJRIiLi0NiYiISExOh0WhgMBgQ\nGxuL6OhoxMXF8e2ddVyYU5XJZFAqlVAoFCF9i8V8cMBxHGJE0fB6vHC5XDC7zHx7drlcfKDPHBBz\nTKWlpSgsLERhYSHy8/NRUlJSq/MtWWfDarUiLy+vSueQSqW8/tRqNeLj4xEfHw+NRsMHzyxIjo2N\nhcFggFqt5oNCpVIZcqoyFZ8dBcBnofw+fyjo9IR0WVZWFuF87HY7rFYrH1ixzzabDVarlQ8A2Kbs\nNQnLpHu93ttXriBKpRKJiYm8jWYBR7jNZrpmnTy1Ws07zvA2HN5mAVzNwHP8yAprD6yzypILVqsV\nbrcbNpstwtm7XC6YzWaYTCa+jVssFlgslhq11RzH8XbZbrejsLCw0ueQSqVISkpCQkIC1Go1/2Lt\nVK/XQ6FQQKPRQKfT8UFeeHDC/J1cLodaoY7QMZMzEAjA4/bA4XSg2FHMJ2tYG2U+z2w28/6uqKgI\nJSUlfMKmtggEAvx9rA60Wi0aNGjAt0Pmy5jfYzZDp9PxnT8WTzC7oFQqoVKpoJKH7IPT6Yhovyxj\n7ff7eV/H4gmbzYbS0lLeLrhcLng8Hr7caDTCYrHwSbLasBEMn8/HPyuVwWw2151gl/2s2/W/dGEw\nGHDhwoVbHscCUEZUVBRsNhu8Xm+1zduVSCRwu8NXbHMoKyvj93Gr64hEIuj1ejRs2BBJSUm8A2WB\nInMIer2ez7CwF+vxq1QqPvNy/ZAYc7KBQIAP0MNfTqeTDxJtNhssFgscDgfMZjMsFgsfWDqdTpSV\nlcFms/E9c2a4XC4XcnNzhVJhlWG9UZbVS0hI4A2/Xq+PyF4xp8AcBevFsgCHOQqpVMq/2L1gDoM5\nYp/PxztfFuSwrD1zFkzXLINksVginEdpaSk4juOzSKdPnxZanTdELBbzjiApKQlxcXF8u2W9fp1O\nB51Ox+uXvWcOIrzjGZoCIuE7QiywYZn18M4m6+CwAIe1afaefWbZZBbUsA5+XUehUCAuLg6NGzdG\no0aNeNvBsqosSGT6ZsEO02t4e2U6ZQ6XOVvWwWTv3W43nwVibZjpkenQaDSiqKgIVqsVdrsdZrOZ\nd7xut/uOO9dCwdqySqXiO/HhWdekpCS+cxQfHw+DwcC3ZWafWQDJAkemZ6bf8M6N2WxGWVkZ37Es\nLS3lO5Usk886S36/H7m5uf8RdlgikfDttHHjxkhMTOT1yuwsywaypAl7hY80sDbL/jKdhvs7j8fD\njwyx9muz2fjEBxv9KCsrQ3FxMUpLS/mMvdVqRUlJCd927XY7cnJyBNZe5RCLxWjQoAHv21hnko0o\nxsbG8okqjUbD22PWGWJ+jtlhqVQaYXuZrWBJEJZYYiPO4Vn64uJilJWV8aPWpaWld/wLatUa7LLM\nxPU9W7/fz393QyGkUvh8vnLHhJ+zOhCLxaFFaR4PXC4XP0wS7uSYA2RGlxkMNqTKekjsHCz4uFVv\nns2DZT278MCTOWwWNLEh1fj4eL7hJSQk8AFVdcylvRV+vx85OTm8c1MqlWjevPkdX5cFyyUlJbxu\nWY+e6ZYFFyaTiQ8q7HY7r2s2VO3z+So0FYPJz4b9tVotYmJikJCQwHcKWE+bPcSsFx6e2dfpdJDJ\nbj1nqy4TDAZRUlKCoqIiFBQUwGg08h0X9grv6bPnINyxVmRqADN44UPXLNhnDijcMSUmJiIpKYn/\nGxsbC6m0RjaIgd/vx9mzZ/lnUSaT4Z577qmyfXG73TAajfwQtMPh4NsyM+CsI80ygMx4h2cRr7d7\n18McB8u8sTYanj2OjY3lh09Zew2fisEC2orCOlNutxsxMTHVaoMrAsuyhQ/xMxvMMqrheg7v6LGA\nhGXAKzKEDVybtsWmCymVSn4aFrMJ8fHxiIuLg1arhUql4kdGwjOjUVFRfEa0ptpyOOHTBiqCx+NB\ncXExrly5wg/7h2emjUYjn1VlumXD1OHBSfg0udvpmGUs2agRm3LF2iuzvw0aNOATCUyXer3+jhcd\n+v1+nD9/ns+EchyHdu3a1cj98fv9vC0oLi4uNxLDEkAseLZarRGjBSzwCx9lqOhUt/B4QqfT8ckv\n1l4VCgV0Oh1vL9goakxMDKKjoxETE1MrbVYoqvU/S0pKgkgk4jO8DKPRiEaNGt30uEaNGpVbXFZa\nWoqGDRtWytAePnz4lt9LJBL4/f4Iw5aYmFgtK3hZFi78wa/OxV61hdVqRVpaWkTZ4cOHERMTc5Mj\nKoZMJuMNWHUQPozDhiSBaxPhw3uV1Y3L5cKSJUsihuhnz559x6tFq4rFYsGLL74Y0WmaMmUK1OrQ\nQjqxWMxPX6jqln7h2SWWda6JRY01hdVqxfDhwyPK7qRdK5VKNG7cuMLbKt4KNowevpiDZVFrYz9L\nhslkQo8ePSJsWHU8+5VFIpHwDrtZs2Z3pANml8NtBCO0Q42kRm1FTWM2m9GzZ08+gFQqlVi1atVN\nbZFCoUCTJk3QpEmTapOBTdcL1zHTbV2wC1arFYMHD44oq6l2LZVKeT+XnJx8+wNuA1vsdb2fY/pl\ntqI6OgQ///wzP43E6XTi+eef531IfaBag129Xo+WLVviyJEj6N27NwDA6/Xi+PHjeOutt256XOfO\nnXHkyJGIsiNHjqBz586Vuv7tGq/JZEK3bt0iyqqr0YvFYigUittXDMPpdGLRokV8r85ut2P+/PmC\nBU11EbfbjW+//TZizmiPHj14IypET9TlcpVbODljxoxal4MRCARw8uTJiLKJEydWq6FiOxlUVN9u\ntxtr167lM/IOhwOTJk2CVqu9/cF/ErxeL44dOxYR2LZv317Q7EpFM6G1hdlsRo8ePRAdHc1ntb/8\n8ssK28iq2OVbYbVa8dxzz/FzZs1mM/bt21frHYJwvF4vnwUHyo+s1jRs7QTD7/fj1KlT/O4dbrcb\nDz74YLXeh/90bDYbPvjgA34UUaVSIT09vdycVLbws6ZHFq1WK9LT0yPKnn76aQp2b8XQoUPx8ccf\no3fv3ujYsSPmzZsX2sqpf3++TlpaGtq1a4eMjAwAwODBg7Fu3TqsXr0aI0eOxHfffYdDhw5F7M5Q\nH3G73Vi5cmVEWW0bqrqO0+nElClTIsqEyDYRlcPpdGLu3LkRZePGjRNImrqJ3W7Hs88+G1FGbbs8\ngUAARqORX5wppI30+/349ddfBbv+fwJWqxUjR46MKDt8+DAFu2H4fD5s27YtomzYsGF3tACLuDXV\nHuymp6fDZrNhzJgxcDqdaNu2LZYtWxZhwC0WC/Lz8/nP7dq1w8KFCzF37lxkZGQgPj4eM2bMQI8e\nPapbPIIgCIIgCOJPRLUHu2KxGOPGjcPLL78Mh8MBg8FQbj7J/v37yx336KOPol+/frBYLNDr9fV6\nojRBEARBEARRO9RYRMm2/KgMEomEhvAIgiAIgiCIauM/cwkqQRAEQRAEQVQACnYJgiAIgiCIegsF\nuwRBEARBEES9hYJdgiAIgiAIot4i4iryW3QEQRAEQRAE8R8IZXYJgiAIgiCIegsFuwRBEARBEES9\nhYJdgiAIgiAIot5CwS5BEARBEARRb6FglyAIgiAIgqi3ULBLEARBEARB1Fso2CUIgiAIgiDqLRTs\nEgRBEARBEPWWP12wGwgE4Ha7hRYjAqfTCZ/PJ7QYRCXhOA52ux3BYFBoUeosbrcbdel3azweT51/\n1rxeL7xer9Bi1FmCwSCcTqfQYkTgdrvpnv0Hwmx4IBAQWpQ6i8fjqRc+Tiq0ALXF4cOHsXTpUhw/\nfhw+nw/x8fFIT0/HCy+8ALFYmJg/IyMD27ZtQ1lZGcRiMVq3bo1JkyahR48egsgTTnFxMZ555hmI\nxWLs2LFDMDmmTJmCQ4cORZT16NEDM2fOFEiikGNbvnw51qxZA7PZDLVajfHjx2P06NG1LktRURFG\njBhxw+/eeustPPbYY7UsUciBLF++HCtXroTRaIRarUb//v3x7rvvQqvV1ro8AJCdnY3Zs2fjp59+\ngkQiQVpaGiZPnoyYmJhauf62bduQlZWFs2fPwuVyYefOnVAqlRF1SktLMWfOHHzzzTcQi8UYPHgw\n3nrrLURFRVW7PHl5eVi9ejVOnz6NvLw8PPPMM3j++ecj6pw+fRqbNm3C6dOnYTQaMXXqVPTt27fa\nZWFkZmbif//3f3Hu3Dn4/X7s3bs34vszZ85g4cKFOHbsGFwuFwwGA5588kmMGzcOcrm82uW5ePEi\n1q5di9OnT6OwsBBjxozBU089FVHnk08+wdq1a1FSUgKRSIRmzZph3LhxNfbcrVmzBkePHkV2djaU\nSiW2bdt207p2ux3p6ekwmUzYvn17jTx7v/32GzZs2IDTp0+juLgYkyZNwsCBAyPqfPjhh+XkbN26\nNT799NNqlwcAli9fjuPHj+P8+fOIi4vD+vXry9UJBAJYvXo1VqxYgaKiIigUCqSnp+PNN9+sdnl+\n/fVX/jkqLS3FtGnT0KtXL/77YDCI3r173/DY5557Dunp6dUu08cff4zTp0/j999/R/PmzbFs2bJy\ndTIzM7F06VLk5+dDoVDg4YcfxnvvvYeEhIRql6c2+NMEu9nZ2ejatSvefvttGAwGZGVlYebMmdBo\nNHj66acFkSklJQV9+/bFXXfdBZvNhs8//xxjxozB3r17kZiYKIhMQChYmT59OgCgsLBQMDkAwGw2\nIyUlBX/961/5stoKUG4Ex3GYNGkSLly4gJkzZ6J954j+7QAAFuFJREFU+/YoKCiA3W4XRB6DwYCM\njIyIsqysLHz55Zfo0qWLIDJ9//33WLBgAebOnYtevXrh4sWLeO211zB37lx88MEHtS6Px+PBCy+8\ngA4dOiArKwsejwdvv/02Jk2ahC+++AIikajGZTh+/DjUajVSU1OxefPmctlujuPw5ptvwmq14vvv\nv4ff78cbb7yBqVOnYsmSJdUuT0FBAf744w9069YN69evh81mK1fnwoULKCsrQ//+/bFgwYIaHxH7\n+eefERUVhXbt2mHnzp3lvv/999/RokULjB07FomJiTh27BjeffddiMViTJgwodrluXz5MgoKCtCz\nZ08sX74cDoejXJ3mzZtjzpw5aN68OdxuN9avX48JEyagefPmaN26dbXL9H//93+Ii4tD69atceTI\nkVvW/fDDD+FwOFBQUFDtcjAuXboEo9GIvn37YtGiRXC5XOXqWCwWNGrUCK+++ipfVpOd3qNHj+Ku\nu+6C3+/HhQsXblgnIyMDu3fvxltvvYV7770XRqOxxnxdTk4OLBYL+vXrh4ULF5bTkUgkKmfDT506\nhY8++qjGbPiRI0fQtm1buN1uGI3Gct//8ssvmDp1Kv7+979jyJAhKCwsxMSJE/Hee+/VWCelxuH+\nxIwdO5b729/+JrQYPGazmUtOTuZ27twpqBzffvstl5aWxq1atYrr1KmToLKMGTOGmzlzpqAyhHPi\nxAkuOTmZO3v2rNCi3JRnn32We+mllwS7fkZGBvfEE09ElM2ZM4d7/PHHBZFn9+7dXHJyMldUVMSX\nsft46dKlWpVl165dXHJyMud0OiPKc3NzueTkZO6nn37iy/bt28clJydzpaWlNSpT//79uYULF970\n+0AgwCUnJ3PffPNNjcrB2Lx5M9e2bdsK1f3ggw+4/v3717BEHNe9e3du+fLlt60XCAS4Dh06cKtW\nrapReVauXMndd999N/3+6NGjXK9evbivv/6aS05O5mw2W43Kw3Ec1759e27Dhg3lyt977z1u3Lhx\nNX7961myZAnXp0+fcuVXrlzhkpOTuf3799eqPB6Ph0tOTua+/fbb29Z95513uLS0tBqXafbs2dyg\nQYPKlS9fvpy7//77I8pWrFhxyzZX1/nTzdkNx+12CzaseiOOHTsGiUSCNm3aCCaDyWTCrFmzMHPm\nTEgkEsHkCCc3NxerV6/Gli1bUFpaKqgs+/btQ6tWrRAbG4uNGzdi48aNKCkpEVSmcPLy8nDo0CEM\nHTpUMBlatWqF/Px8mEwmAKFhunPnziE5OVkQeYqKiiCTyRAfH8+XNWzYEEDomasL/PLLL5DJZBGZ\nnAceeID/jrgxdc2GnzlzBm63G+3btxdMBpfLhf/+7//GtGnToNFoBJMjnOLiYqxZswYbN26s0Uxz\nRdi/fz8MBgM6duyILVu2YN26dbhy5YqgMoVjt9uxY8cOwW241WrF5cuXAYRGns6ePSuYDa8O/rTB\n7k8//YSDBw8KNoWBcezYMYwaNQqDBg3C9OnT8cknn+Cuu+4STJ6ZM2di4MCBaNeunWAyhCMSiZCf\nn4/9+/djyZIleOihh/Dll18KJs/Zs2fh9/vxxBNPYM+ePcjMzMQjjzyC7du3CyZTOP/6178QHR2N\nRx55RDAZBg0ahFGjRmHIkCF49dVX8fjjj0On02Hq1KmCyNOiRQv4fD789ttvfNmZM2cAhDpSdYHL\nly/DYDBAKr02s0ylUkGtVtcpR1yX+O2337Bt2zbBbXhOTg5Gjx6NoUOH4oUXXsC8efOQmpoqmDyL\nFy9G+/bt0bNnT8FkuJ6ysjL88MMP+Oc//4lHHnkECxcuFEyWc+fOQaPRYODAgfjmm2+wY8cO9O3b\nFytXrhRMpnB27NiBQCBQbu5zbfLggw/i73//O5555hm88sorGDJkCIqKivCPf/xDMJnulD/NnN1w\ncnJyMH78eLzwwguCLwZLTEzEY489BpPJhK1bt+Kzzz5D165dBemR79mzBydPnqwzgRsAzJ07l8/c\nBAIBzJ8/H7Nnz8Zf/vIXQSbKe71eXLhwAUuXLkWfPn3AcRxmzJiBWbNm4dFHH40IVmqbYDCILVu2\nYNCgQTWyYKeiFBQU4Pvvv0fTpk3RsWNHGAwG7N+/H6dOnRLEAXft2hWtW7fGhAkT8Oqrr8LtdmPp\n0qVQKpV1ZhW23++HTCYrVy6Xy+H3+wWQqG5TWFiIV155BQMGDMDgwYMFlcVgMGDAgAGwWCzYuXMn\nli1bhu7duyMuLq7WZTlx4gS+/vrrOmXDJ0+ezNtwjuOwcuVKzJkzBwMGDKiRec23w+v1Ii8vD9Om\nTePXgnz66adYsGABhgwZAr1eX+syhbNp0yb069cPBoNBMBnMZjN27NiBhIQEdOjQAQ0bNsR3332H\no0ePYtCgQYLJdSf86TK7Fy9exOjRo/HYY49h0qRJQouDJk2aYMSIEXjllVewYcMGnD9/HpmZmYLI\n8v7776N///44evQosrKykJOTg0AggKysLMGGnsKHKCUSCcaNG4dgMIgDBw4IIk9MTAz0ej369OkD\nIJR5HjRoEEpLS5GdnS2ITIzDhw8jLy9P0OEvILQwRqPRYMWKFXj55Zcxa9YsPPXUU3jnnXcE2cJG\nIpFg5cqVePTRR7FmzRrs2rUL77//PsRiMT+dQWiio6NhsVgiyoLBIKxWK6KjowWSqm5SXFyMUaNG\nISUlBbNmzaqVBYa3Ii4uDiNGjMBLL72E9evXw+Fw4IsvvhBElpkzZ6JXr144ffo0srKy+BGMgwcP\n4tKlS4LIFG7DRSIRRo8eDYPBUG63jdqCLXAOD9oGDx4Mr9cr+LSmnJwcnDhxQnAbvmzZMpSUlGDN\nmjV45ZVX8N5772HChAmYNm0arFaroLJVlT9VZvePP/5Aeno6evbsiXfffVdwI3k9UVFRSExMRF5e\nniDX12g02Lt3L2+ErFYrPB4PMjIy8MYbb9SJwIC7uopdqHvXqVMnHDx4EBzHlZNBqC3sGJs3b0an\nTp3QokULQeXIyclB586dI/TTtm1bmEwmlJWVCbKbRnR0NMaPH4/x48cDAE6ePAmn04mHH3641mW5\nER07doTD4UBubi4/jen8+fMIBoPo2LGjwNLVHUpKSjBq1Cg0a9YMCxYsEHQk5UYoFAo0bdpUsKkn\nSqUSx44d44M2th/xvHnzMGrUKDRt2lQQua7nRvaztujUqdNNvxM6Jti8eTOSkpLQrVs3QeXIyclB\nixYtIkYI27RpA7fbjfz8fMGz31XhT5PZvXz5MtLT09G9e3fMmDFD8MDE4/Hwk78ZBw4cwL///W/c\nf//9gsi0c+dO7Nq1i3+NGzcOarUau3btEmS/VqfTGZFR9vv9WLx4MSQSiWBBSs+ePWG327Fnzx4A\nIaO9adMmJCQkoFWrVoLIBITmxO3evVvwjAAQ2lLv0KFD/HZswWAQu3fvRlJSkmBDc+Fba1ksFvzj\nH/9At27d0KRJE0HkuZ62bdsiPj4e69evB8dx4DgO69atQ5MmTdC8eXOhxasTmEwmjB49Go0aNcLi\nxYsFnarDuH5rq1OnTuGXX37hFxfWNmzkgr3YFpJbt26tkf1ab0cwGMTFixf5z9zVPbgtFstN95at\nae6//36o1Wps2bKFL9u0aROUSiXuvfdeQWQCQtMrvv76awwZMkTw+CQlJQXHjx/ntyXjOA67d++G\nRqOpMzazsog4rg79vFENMn36dKxfvx4GgyFil4G77777hptO1zRlZWV44IEHcM899yAuLg5GoxE5\nOTkYMmQIMjIyBG/sALB27VrMnz8fx48fF+T6eXl56NOnD1q2bIno6GhcunQJJpMJU6ZMidh3t7ZZ\nuXIlvwei2WzGhQsX8NFHH0VsFF7bfPnll1iwYAEOHjwo+Or0S5cu4fnnn4fH40GHDh2Qm5uLvLw8\nzJ49G48++qggMo0YMQIejwd6vR6nTp1CmzZtsHjx4ogdGmqSRYsWYcOGDfB4PLDb7YiJiYFIJMKH\nH37IB0ZZWVmYOHEiWrZsiUAggNzcXCxevLhGOr8mkwmPP/44gND8PIVCAbVajc6dO+Pjjz8GENoF\n4rXXXgPHcTCZTNBqtVAoFBg8eDAmT55c7TLNmjUL27dvh9vthsPhQGxsLADg888/R7t27fDJJ5/g\no48+QlRUVERGV61W853P6uTy5cv8D7aYTCaoVCqoVCo89NBD/EKdjh07okGDBmjQoAHKysqQnZ2N\nXr16YdGiRVAoFNUu05QpU7B//364XC44nU5eR2vXrkWzZs3K1d+zZw/Gjh2Ln3/+uUbsQnZ2Np57\n7jkAoR9FUavVUKlUGDBgAN599134/X6kpKSgefPmSEhIwJUrV5CXl4exY8di3Lhx1S4PALz++us4\nduwYnE4nPB4PPw1o69at/PO+bds2TJs2De3bt4ff78fJkyfx/vvvY9iwYdUuz7Fjx/D666+Xe46G\nDx8esT/0rl278Prrr2Pv3r1o1KhRtcsRzvPPP49z587B4XDA5/PxSYg9e/ZArVbDaDTiueeeQ2Fh\nITp37ozi4mKcP39ecN97J/xpgt1Lly7dcIsohUKBDh06CCBRaCHP8ePHUVpaCp1Oh/vvv79OTBVg\nFBUV4cqVK4L9OAHHccjJycHZs2dhtVoRGxuLHj161IkhlPz8fBw4cABKpRK9evWqkV+5qgw5OTnw\n+XyCblsXjtfrxeHDh1FQUICYmBh07dpV0B8DycvLw7Fjx2C329GmTRukpqbW6pBlbm4uioqKypW3\nbNkyIttdVlaGPXv2QCwWo1+/ftDpdDUij9frxcmTJ8uV63Q6ftGQ1WqN2MGCER8fXyPD4f/+979v\nuLVgmzZtoNVqkZ+ff8MpXmKxuEZslNvtxq+//lqu3GAwoGXLlgAAo9GI48ePo6ioCCqVCl27dsXd\nd99d7bIwcnJyYDaby5W3a9cOKpWqXLnJZMKFCxeQmppaI1M+7HY7zp07V648NjYWzZs3B8dx+OOP\nP3DmzBmYTCZERUXhwQcf5IP0miA7O/uGP5LSsWPHiNEAk8mEvXv3QiQS4ZFHHqmxBYU3e44SEhIi\n2kpubi7MZnOtTFs6e/bsDX8kpXPnznwyMBAI4OjRo8jNzYVOp0Nqamqdik8qy58m2CUIgiAIgiD+\nfAg/Vk4QBEEQBEEQNQQFuwRBEARBEES9hYJdgiAIgiAIot5CwS5BEARBEARRb6FglyAIgiAIgqi3\nULBLEARBEARB1Fso2CUIgiAIgiDqLRTsEgRB3ILs7GykpaUhNzf3js9VWFiItLQ0nDlzhi974okn\nsGrVqlsel5eXh7S0tBtu4F/T/Nd//RfWrFlTLefKzMzEs88+Wy3nIgiCqCgU7BIEQdwCt9uN7Oxs\neL3eOz6Xz+dDdnY2XC4XXxYMBuH3+295nNfrLXdcbREIBG4rX0VhP4tOEARRm1T/7wcSBEEQFWb7\n9u1Ci3BLdu7cKbQIBEEQdwQFuwRBEBXA7/dj5cqVOHjwIFQqFYYPH46HH344ok5BQQG++uornDx5\nEnq9HgMHDkSfPn0gFt98EG3JkiVITU1Fjx49+LITJ05g9erVsFgs6NKlC3r37l3uuAMHDuCHH37A\npUuXIBaLcd9992H48OGIiYkBABw+fBgHDhzApEmTIJVeM/U+nw8ffvghevbsiQceeOC2//eiRYtw\n7733onv37gCAr776CnK5HO3atcOKFSuQn5+PTp06YfTo0YiOjo7Q19dff40dO3ZApVJh0KBBt70W\nQRBETUDTGAiCICrAtGnTcOjQIXTp0gVOpxMvvvgifv75Z/77nJwcPPHEE9i3bx+6desGg8GA119/\nHdOmTbvleTMzM3Hq1Cn+8969e/HUU0/BbrejR48eOHXqFN55551yx33++ecQiUTo1asXUlNTkZmZ\niREjRsDpdAIAGjZsiC+++AL79++POG7//v344osv0LBhwwr93xs3bsTp06f5z3v27MGKFSswZswY\nxMTEoFOnTli3bh0mTpwYcdzUqVMxffp0tGjRAh06dMC8efMoS0wQhCBQZpcgCKICtGjRAjNnzoRI\nJEIwGMTjjz+OTZs2oUuXLgCA//mf/4FGo8FXX30FjUbDH5ORkYHRo0fjnnvuqdB1Fi5ciIcffhif\nffYZRCIRRo8ejddee63c4rRVq1ZBIpHwn0eOHIm+ffsiKysLAwYMQNOmTfHggw9i48aN6Nu3L19v\nw4YN6NatG+6+++4q6+LixYvYvn07mjZtCgBo1aoVJkyYgCtXrqBx48a4cOEC/vWvf2H27NkYMmQI\nAGDYsGHo168f1Gp1la9LEARRFSizSxAEUQHS0tIgEokAAGKxGO3bt8eVK1cAhBZxZWVlIS0tjQ90\nAWDEiBEQi8XYu3dvha6Rl5eH33//HcOGDeOvJRKJMHz48HJ1xWIxTp06hczMTHz22WfIzMyERqPB\niRMn+DojR47EgQMHkJ+fDwC4cuUKDh48iBEjRlRNCVdJTU3lA10A6NChAy8/AGRlZUEmk2HgwIF8\nnZiYGPTr1++OrksQBFEVKNglCIKoAOHzUQFAqVTC4/EAABwOBxwOB5KSkiLqKBQKxMbGoqioqELX\nYPUaNGgQUX7950AggBdffBHp6enYtWsXLl26hPz8fPj9frjdbr5er169kJCQgE2bNgEITZmIiYlB\nnz59KiTPzbheFyqVCgD4axcWFiIhIQEymSyiXmJi4h1dlyAIoirQNAaCIIgKwDKtN0KpVEIikaCs\nrCyinOM4WCwWaLXaCl1Dp9MBACwWS0T59ef94Ycf8OOPP+K7776LmB5x8ODBiHpSqRRPPvkkNmzY\ngJdffhmbN2/G0KFDIZfLKyRPVdHpdCgrKwPHcRF6u/7/IgiCqA0os0sQBHGHyOVy3Hfffdi3bx84\njuPLf/zxR3i9Xjz00EMVOs8999yD+Ph4ZGVlRZRf/zk/Px8qlQrNmjXjy7Kzs/lpBOEMHz4cpaWl\nmD59OkpKSvDkk09W5l+rEt26dYPD4YhYwOf3+/Hjjz/W+LUJgiCuhzK7BEEQ1cCoUaMwZswYTJ06\nFcOGDUNBQQEyMjLQvn17pKamVugcYrEYf/vb37B48WI0aNAA3bp1w9GjR/HNN99E1OvUqRNcLhfm\nzJmDIUOGIDc3FwsWLEBUVFS5cyYmJqJv377YsmULevTogSZNmlTL/3srUlNTkZKSgsmTJ2Pq1KmI\njY3FypUrYbfbazyrTBAEcT0U7BIEQdwClUqFlJQUKBSKiPKkpCR+zi4Qmh+7dOlSLFu2DH/961/5\nfXbHjh3L75ogk8mQkpISsSNBq1atEB8fz39+6aWXIJFIsGLFCnz00Ufo0qUL5s+fj7lz5/LHdejQ\nATNmzMAnn3yCNWvWoFmzZnjzzTexZ8+ecvOGgdDiuu+//75KWd3WrVsjLi6O/9y0adNyupBIJEhJ\nSeGna0gkEnz66aeYP38+xo8fz++z+8Ybb1R4sR5BEER1IeLCx9wIgiCIO+b6uao1eZ6K1Jk3bx62\nbt2KH374odyisZqmunRBEARRVSizSxAEUc1UV3BXkfPcqs6lS5dw4cIFrFu3Dq+99lqtB7pA9emC\nIAiiqlCwSxAEUU+ZOHEicnNz0a9fP6Snp0d8ZzQaMWPGjJse27hxY0yePLmmRSQIgqhxKNglCIKo\np2zZsuWm3ymVSnTv3v2m3xsMhpoQiSAIotahObsEQRAEQRBEvYX22SUIgiAIgiDqLRTsEgRBEARB\nEPUWCnYJgiAIgiCIegsFuwRBEARBEES9hYJdgiAIgiAIot5CwS5BEARBEARRb6FglyAIgiAIgqi3\nULBLEARBEARB1Fso2CUIgiAIgiDqLf8PkuelJq5i3k4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fbd57f2c310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.xkcd()\n",
    "hd.loc[hd['holiday_ind']!=0,:].groupby('holiday_ind').count()['date'].T.plot.bar(color = 'green',alpha=0.5)\n",
    "hd.loc[hd['holiday_ind']!=0,:].groupby('holiday_ind').count()['date'].T.plot(color = 'orange')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "hd.to_csv('holiday_info.csv',header= True,index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}