{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 외국인_군집 분석"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime as dt\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.pyplot as ticker\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#지수표현식 없애기 \n",
    "pd.options.display.float_format = '{:.5f}'.format\n",
    "\n",
    "#되돌리기\n",
    "#pd.reset_option('display.float_format')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 한글 깨짐 해결\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.family'] ='Malgun Gothic'\n",
    "plt.rcParams['axes.unicode_minus'] =False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 0. 데이터 가져오기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_out = pd.read_csv('./따릉이 대여이력 정보/서울특별시 공공자전거 대여이력 정보_23하반기(전처리완_외).csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>대여 대여소번호</th>\n",
       "      <th>대여 대여소명</th>\n",
       "      <th>반납대여소번호</th>\n",
       "      <th>반납대여소명</th>\n",
       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>이용자종류</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>대여일자</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>대여월</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>134</td>\n",
       "      <td>연세로 명물길</td>\n",
       "      <td>162</td>\n",
       "      <td>봉원고가차도 밑</td>\n",
       "      <td>6</td>\n",
       "      <td>1291.15000</td>\n",
       "      <td>외국인</td>\n",
       "      <td>ST-36</td>\n",
       "      <td>ST-219</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   대여 대여소번호  대여 대여소명  반납대여소번호    반납대여소명  이용시간(분)    이용거리(M) 이용자종류 대여대여소ID  \\\n",
       "0       134  연세로 명물길      162  봉원고가차도 밑        6 1291.15000   외국인   ST-36   \n",
       "\n",
       "  반납대여소ID        대여날짜        반납날짜  대여시간  반납시간  대여일자    대여요일  대여월  \n",
       "0  ST-219  2023-12-01  2023-12-01     0     0     1  Friday   12  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 34590 entries, 0 to 34589\n",
      "Data columns (total 16 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   대여 대여소번호  34590 non-null  int64  \n",
      " 1   대여 대여소명   34590 non-null  object \n",
      " 2   반납대여소번호   34590 non-null  int64  \n",
      " 3   반납대여소명    34590 non-null  object \n",
      " 4   이용시간(분)   34590 non-null  int64  \n",
      " 5   이용거리(M)   34590 non-null  float64\n",
      " 6   이용자종류     34590 non-null  object \n",
      " 7   대여대여소ID   34590 non-null  object \n",
      " 8   반납대여소ID   34590 non-null  object \n",
      " 9   대여날짜      34590 non-null  object \n",
      " 10  반납날짜      34590 non-null  object \n",
      " 11  대여시간      34590 non-null  int64  \n",
      " 12  반납시간      34590 non-null  int64  \n",
      " 13  대여일자      34590 non-null  int64  \n",
      " 14  대여요일      34590 non-null  object \n",
      " 15  대여월       34590 non-null  int64  \n",
      "dtypes: float64(1), int64(7), object(8)\n",
      "memory usage: 4.2+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "display(df_out.head(1))\n",
    "print(df_out.info(show_counts=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. 모델링 적용 전 전처리"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>대여 대여소번호</th>\n",
       "      <th>대여 대여소명</th>\n",
       "      <th>반납대여소번호</th>\n",
       "      <th>반납대여소명</th>\n",
       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>이용자종류</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>대여일자</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>대여월</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>134</td>\n",
       "      <td>연세로 명물길</td>\n",
       "      <td>162</td>\n",
       "      <td>봉원고가차도 밑</td>\n",
       "      <td>6</td>\n",
       "      <td>1291.15000</td>\n",
       "      <td>외국인</td>\n",
       "      <td>ST-36</td>\n",
       "      <td>ST-219</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>680</td>\n",
       "      <td>꿈마루어린이도서관 앞</td>\n",
       "      <td>634</td>\n",
       "      <td>외국어대 정문 앞</td>\n",
       "      <td>8</td>\n",
       "      <td>651.71000</td>\n",
       "      <td>외국인</td>\n",
       "      <td>ST-2280</td>\n",
       "      <td>ST-401</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>390</td>\n",
       "      <td>충무로역 1번출구</td>\n",
       "      <td>390</td>\n",
       "      <td>충무로역 1번출구</td>\n",
       "      <td>27</td>\n",
       "      <td>2581.88000</td>\n",
       "      <td>외국인</td>\n",
       "      <td>ST-944</td>\n",
       "      <td>ST-944</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4713</td>\n",
       "      <td>현대 뜨레비앙 아파트 앞</td>\n",
       "      <td>4778</td>\n",
       "      <td>대신파이낸스센터</td>\n",
       "      <td>36</td>\n",
       "      <td>3130.00000</td>\n",
       "      <td>외국인</td>\n",
       "      <td>ST-2623</td>\n",
       "      <td>ST-2523</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>249</td>\n",
       "      <td>여의도중학교 옆</td>\n",
       "      <td>4564</td>\n",
       "      <td>63스퀘어</td>\n",
       "      <td>112</td>\n",
       "      <td>4744.66000</td>\n",
       "      <td>외국인</td>\n",
       "      <td>ST-297</td>\n",
       "      <td>ST-2814</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   대여 대여소번호        대여 대여소명  반납대여소번호     반납대여소명  이용시간(분)    이용거리(M) 이용자종류  \\\n",
       "0       134        연세로 명물길      162   봉원고가차도 밑        6 1291.15000   외국인   \n",
       "1       680    꿈마루어린이도서관 앞      634  외국어대 정문 앞        8  651.71000   외국인   \n",
       "2       390      충무로역 1번출구      390  충무로역 1번출구       27 2581.88000   외국인   \n",
       "3      4713  현대 뜨레비앙 아파트 앞     4778   대신파이낸스센터       36 3130.00000   외국인   \n",
       "4       249       여의도중학교 옆     4564      63스퀘어      112 4744.66000   외국인   \n",
       "\n",
       "   대여대여소ID  반납대여소ID        대여날짜        반납날짜  대여시간  반납시간  대여일자    대여요일  대여월  \n",
       "0    ST-36   ST-219  2023-12-01  2023-12-01     0     0     1  Friday   12  \n",
       "1  ST-2280   ST-401  2023-12-01  2023-12-01     8     9     1  Friday   12  \n",
       "2   ST-944   ST-944  2023-12-01  2023-12-01     9     9     1  Friday   12  \n",
       "3  ST-2623  ST-2523  2023-12-01  2023-12-01     9    10     1  Friday   12  \n",
       "4   ST-297  ST-2814  2023-12-01  2023-12-01     9    11     1  Friday   12  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_out.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (1-1) 따릉이대여소 마스터 정보(위도, 경도 조인)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 따릉이 대여소 정보 읽어오기\n",
    "ll = pd.read_csv('./서울시 따릉이대여소 마스터 정보.csv', encoding='cp949')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>대여소_ID</th>\n",
       "      <th>주소1</th>\n",
       "      <th>주소2</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-999</td>\n",
       "      <td>서울특별시 양천구 목동서로 280</td>\n",
       "      <td>목동아파트 8단지 상가동</td>\n",
       "      <td>37.53340</td>\n",
       "      <td>126.87650</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   대여소_ID                 주소1            주소2       위도        경도\n",
       "0  ST-999  서울특별시 양천구 목동서로 280  목동아파트 8단지 상가동 37.53340 126.87650"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ll.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (1-2) 따릉이대여소 마스터정보(대여소ID, 구 정보 조인)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "lll = pd.read_csv('./서울시 따릉이대여소 마스터 정보(대여소ID, 구).csv', encoding='cp949')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>대여소_ID</th>\n",
       "      <th>구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-999</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   대여소_ID    구\n",
       "0  ST-999  양천구"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lll.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (1-3) ll과 lll 정보 합치고, 필요없는 컬럼 drop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 조인\n",
    "ll_join = pd.merge(ll, lll, how='inner', on='대여소_ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>대여소_ID</th>\n",
       "      <th>주소1</th>\n",
       "      <th>주소2</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-999</td>\n",
       "      <td>서울특별시 양천구 목동서로 280</td>\n",
       "      <td>목동아파트 8단지 상가동</td>\n",
       "      <td>37.53340</td>\n",
       "      <td>126.87650</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   대여소_ID                 주소1            주소2       위도        경도    구\n",
       "0  ST-999  서울특별시 양천구 목동서로 280  목동아파트 8단지 상가동 37.53340 126.87650  양천구"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ll_join.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 필요없는 컬럼 drop\n",
    "ll_join = ll_join.drop(columns=['주소1', '주소2'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>대여소_ID</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-999</td>\n",
       "      <td>37.53340</td>\n",
       "      <td>126.87650</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   대여소_ID       위도        경도    구\n",
       "0  ST-999 37.53340 126.87650  양천구"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ll_join.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ll_join.to_csv('./서울시 따릉이대여소 마스터 정보(전처리).csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (1-4) df_out과 조인"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 대여대여소ID 기준 merge\n",
    "df_out = pd.merge(df_out, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 반납대여소ID 기준 merge\n",
    "df_out = pd.merge(df_out, ll_join, how='left', left_on='반납대여소ID', right_on='대여소_ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여 대여소번호</th>\n",
       "      <th>대여 대여소명</th>\n",
       "      <th>반납대여소번호</th>\n",
       "      <th>반납대여소명</th>\n",
       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>이용자종류</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>...</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>대여월</th>\n",
       "      <th>대여소_ID_x</th>\n",
       "      <th>위도_x</th>\n",
       "      <th>경도_x</th>\n",
       "      <th>구_x</th>\n",
       "      <th>대여소_ID_y</th>\n",
       "      <th>위도_y</th>\n",
       "      <th>경도_y</th>\n",
       "      <th>구_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>134</td>\n",
       "      <td>연세로 명물길</td>\n",
       "      <td>162</td>\n",
       "      <td>봉원고가차도 밑</td>\n",
       "      <td>6</td>\n",
       "      <td>1291.15000</td>\n",
       "      <td>외국인</td>\n",
       "      <td>ST-36</td>\n",
       "      <td>ST-219</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>...</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12</td>\n",
       "      <td>ST-36</td>\n",
       "      <td>37.55789</td>\n",
       "      <td>126.93808</td>\n",
       "      <td>서대문구</td>\n",
       "      <td>ST-219</td>\n",
       "      <td>37.56626</td>\n",
       "      <td>126.94667</td>\n",
       "      <td>서대문구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   대여 대여소번호  대여 대여소명  반납대여소번호    반납대여소명  이용시간(분)    이용거리(M) 이용자종류 대여대여소ID  \\\n",
       "0       134  연세로 명물길      162  봉원고가차도 밑        6 1291.15000   외국인   ST-36   \n",
       "\n",
       "  반납대여소ID        대여날짜  ...    대여요일  대여월  대여소_ID_x     위도_x      경도_x   구_x  \\\n",
       "0  ST-219  2023-12-01  ...  Friday   12     ST-36 37.55789 126.93808  서대문구   \n",
       "\n",
       "  대여소_ID_y     위도_y      경도_y   구_y  \n",
       "0   ST-219 37.56626 126.94667  서대문구  \n",
       "\n",
       "[1 rows x 24 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_out.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (2) 필요없는 컬럼 drop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1_out = df_out.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여 대여소번호</th>\n",
       "      <th>대여 대여소명</th>\n",
       "      <th>반납대여소번호</th>\n",
       "      <th>반납대여소명</th>\n",
       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>이용자종류</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>...</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>대여월</th>\n",
       "      <th>대여소_ID_x</th>\n",
       "      <th>위도_x</th>\n",
       "      <th>경도_x</th>\n",
       "      <th>구_x</th>\n",
       "      <th>대여소_ID_y</th>\n",
       "      <th>위도_y</th>\n",
       "      <th>경도_y</th>\n",
       "      <th>구_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>134</td>\n",
       "      <td>연세로 명물길</td>\n",
       "      <td>162</td>\n",
       "      <td>봉원고가차도 밑</td>\n",
       "      <td>6</td>\n",
       "      <td>1291.15000</td>\n",
       "      <td>외국인</td>\n",
       "      <td>ST-36</td>\n",
       "      <td>ST-219</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>...</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12</td>\n",
       "      <td>ST-36</td>\n",
       "      <td>37.55789</td>\n",
       "      <td>126.93808</td>\n",
       "      <td>서대문구</td>\n",
       "      <td>ST-219</td>\n",
       "      <td>37.56626</td>\n",
       "      <td>126.94667</td>\n",
       "      <td>서대문구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   대여 대여소번호  대여 대여소명  반납대여소번호    반납대여소명  이용시간(분)    이용거리(M) 이용자종류 대여대여소ID  \\\n",
       "0       134  연세로 명물길      162  봉원고가차도 밑        6 1291.15000   외국인   ST-36   \n",
       "\n",
       "  반납대여소ID        대여날짜  ...    대여요일  대여월  대여소_ID_x     위도_x      경도_x   구_x  \\\n",
       "0  ST-219  2023-12-01  ...  Friday   12     ST-36 37.55789 126.93808  서대문구   \n",
       "\n",
       "  대여소_ID_y     위도_y      경도_y   구_y  \n",
       "0   ST-219 37.56626 126.94667  서대문구  \n",
       "\n",
       "[1 rows x 24 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_out.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1_out = df1_out.drop(columns=['대여 대여소번호', '반납대여소번호', '대여 대여소명', '반납대여소명', '이용자종류', '대여소_ID_x', '대여소_ID_y'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>대여일자</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>대여월</th>\n",
       "      <th>위도_x</th>\n",
       "      <th>경도_x</th>\n",
       "      <th>구_x</th>\n",
       "      <th>위도_y</th>\n",
       "      <th>경도_y</th>\n",
       "      <th>구_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>1291.15000</td>\n",
       "      <td>ST-36</td>\n",
       "      <td>ST-219</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12</td>\n",
       "      <td>37.55789</td>\n",
       "      <td>126.93808</td>\n",
       "      <td>서대문구</td>\n",
       "      <td>37.56626</td>\n",
       "      <td>126.94667</td>\n",
       "      <td>서대문구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)    이용거리(M) 대여대여소ID 반납대여소ID        대여날짜        반납날짜  대여시간  반납시간  \\\n",
       "0        6 1291.15000   ST-36  ST-219  2023-12-01  2023-12-01     0     0   \n",
       "\n",
       "   대여일자    대여요일  대여월     위도_x      경도_x   구_x     위도_y      경도_y   구_y  \n",
       "0     1  Friday   12 37.55789 126.93808  서대문구 37.56626 126.94667  서대문구  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_out.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1_out.columns = ['이용시간(분)', '이용거리(M)', '대여대여소ID', '반납대여소ID', '대여날짜', '반납날짜', '대여시간', '반납시간', '대여일자', '대여요일', '대여월', '대여위도', '대여경도', '대여구', '반납위도', '반납경도', '반납구']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "      <th>반납구</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>6</td>\n",
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       "      <td>12</td>\n",
       "      <td>37.55789</td>\n",
       "      <td>126.93808</td>\n",
       "      <td>서대문구</td>\n",
       "      <td>37.56626</td>\n",
       "      <td>126.94667</td>\n",
       "      <td>서대문구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)    이용거리(M) 대여대여소ID 반납대여소ID        대여날짜        반납날짜  대여시간  반납시간  \\\n",
       "0        6 1291.15000   ST-36  ST-219  2023-12-01  2023-12-01     0     0   \n",
       "\n",
       "   대여일자    대여요일  대여월     대여위도      대여경도   대여구     반납위도      반납경도   반납구  \n",
       "0     1  Friday   12 37.55789 126.93808  서대문구 37.56626 126.94667  서대문구  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_out.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 34590 entries, 0 to 34589\n",
      "Data columns (total 17 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   이용시간(분)  34590 non-null  int64  \n",
      " 1   이용거리(M)  34590 non-null  float64\n",
      " 2   대여대여소ID  34590 non-null  object \n",
      " 3   반납대여소ID  34590 non-null  object \n",
      " 4   대여날짜     34590 non-null  object \n",
      " 5   반납날짜     34590 non-null  object \n",
      " 6   대여시간     34590 non-null  int64  \n",
      " 7   반납시간     34590 non-null  int64  \n",
      " 8   대여일자     34590 non-null  int64  \n",
      " 9   대여요일     34590 non-null  object \n",
      " 10  대여월      34590 non-null  int64  \n",
      " 11  대여위도     34590 non-null  float64\n",
      " 12  대여경도     34590 non-null  float64\n",
      " 13  대여구      34590 non-null  object \n",
      " 14  반납위도     34590 non-null  float64\n",
      " 15  반납경도     34590 non-null  float64\n",
      " 16  반납구      34590 non-null  object \n",
      "dtypes: float64(5), int64(5), object(7)\n",
      "memory usage: 4.5+ MB\n"
     ]
    }
   ],
   "source": [
    "df1_out.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (3) 전처리"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 대여시간, 반납시간 0 >> 24로 바꾸기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1_out.loc[df1_out['대여시간'] == 0, '대여시간'] = 24\n",
    "df1_out.loc[df1_out['반납시간'] == 0, '반납시간'] = 24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df1_out.to_csv('./따릉이 대여이력 정보/(모델링 전 전처리_외) 따릉이 대여이력 23하반기.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1_out = pd.read_csv('./따릉이 대여이력 정보/(모델링 전 전처리_외) 따릉이 대여이력 23하반기.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>대여일자</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>대여월</th>\n",
       "      <th>대여위도</th>\n",
       "      <th>대여경도</th>\n",
       "      <th>대여구</th>\n",
       "      <th>반납위도</th>\n",
       "      <th>반납경도</th>\n",
       "      <th>반납구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>1291.15</td>\n",
       "      <td>ST-36</td>\n",
       "      <td>ST-219</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12</td>\n",
       "      <td>37.55789</td>\n",
       "      <td>126.93808</td>\n",
       "      <td>서대문구</td>\n",
       "      <td>37.56626</td>\n",
       "      <td>126.94667</td>\n",
       "      <td>서대문구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)  이용거리(M) 대여대여소ID 반납대여소ID        대여날짜        반납날짜  대여시간  반납시간  대여일자  \\\n",
       "0        6  1291.15   ST-36  ST-219  2023-12-01  2023-12-01    24    24     1   \n",
       "\n",
       "     대여요일  대여월      대여위도       대여경도   대여구      반납위도       반납경도   반납구  \n",
       "0  Friday   12  37.55789  126.93808  서대문구  37.56626  126.94667  서대문구  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_out.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (4) 대여구, 반납구 간단 EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='count', ylabel='대여구'>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tmp = df1_out.groupby('대여구')['대여구'].value_counts().reset_index().sort_values(by='count', ascending=False)\n",
    "sns.barplot(data=tmp, y='대여구', x='count', color='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='count', ylabel='반납구'>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tmp2 = df1_out.groupby('반납구')['반납구'].value_counts().reset_index().sort_values(by='count', ascending=False)\n",
    "sns.barplot(data=tmp2, y='반납구', x='count', color='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (5) 대여구, 반납구 전처리"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 대여구의 강남구와 반납구의 강남구가 동일한 숫자로 라벨링 되도록 학습\n",
    "import pandas as pd\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "# LabelEncoder 생성 및 학습\n",
    "le = LabelEncoder()\n",
    "combined_values = pd.concat([df1_out['대여구'], df1_out['반납구']])\n",
    "le.fit(combined_values)\n",
    "\n",
    "# 대여구와 반납구 컬럼 변환\n",
    "df1_out['대여구_e'] = le.transform(df1_out['대여구'])\n",
    "df1_out['반납구_e'] = le.transform(df1_out['반납구'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>대여일자</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>대여월</th>\n",
       "      <th>대여위도</th>\n",
       "      <th>대여경도</th>\n",
       "      <th>대여구</th>\n",
       "      <th>반납위도</th>\n",
       "      <th>반납경도</th>\n",
       "      <th>반납구</th>\n",
       "      <th>대여구_e</th>\n",
       "      <th>반납구_e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>1291.15</td>\n",
       "      <td>ST-36</td>\n",
       "      <td>ST-219</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12</td>\n",
       "      <td>37.55789</td>\n",
       "      <td>126.93808</td>\n",
       "      <td>서대문구</td>\n",
       "      <td>37.56626</td>\n",
       "      <td>126.94667</td>\n",
       "      <td>서대문구</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)  이용거리(M) 대여대여소ID 반납대여소ID        대여날짜        반납날짜  대여시간  반납시간  대여일자  \\\n",
       "0        6  1291.15   ST-36  ST-219  2023-12-01  2023-12-01    24    24     1   \n",
       "\n",
       "     대여요일  대여월      대여위도       대여경도   대여구      반납위도       반납경도   반납구  대여구_e  \\\n",
       "0  Friday   12  37.55789  126.93808  서대문구  37.56626  126.94667  서대문구     13   \n",
       "\n",
       "   반납구_e  \n",
       "0     13  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_out.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- null값 제거"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1_out = df1_out.dropna(subset=['대여구', '반납구', '대여구_e', '반납구_e'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 각 구에 부여된 label 확인"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>대여구</th>\n",
       "      <th>대여구_e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>강남구</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>강동구</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1265</th>\n",
       "      <td>강북구</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>강서구</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>관악구</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>광진구</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>구로구</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2107</th>\n",
       "      <td>금천구</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>노원구</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1476</th>\n",
       "      <td>도봉구</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>동대문구</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>동작구</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>마포구</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>서대문구</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>서초구</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>성동구</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>성북구</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>송파구</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>양천구</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>영등포구</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>용산구</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>은평구</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>종로구</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>중구</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>350</th>\n",
       "      <td>중랑구</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       대여구  대여구_e\n",
       "67     강남구      0\n",
       "38     강동구      1\n",
       "1265   강북구      2\n",
       "110    강서구      3\n",
       "34     관악구      4\n",
       "20     광진구      5\n",
       "186    구로구      6\n",
       "2107   금천구      7\n",
       "11     노원구      8\n",
       "1476   도봉구      9\n",
       "1     동대문구     10\n",
       "149    동작구     11\n",
       "45     마포구     12\n",
       "0     서대문구     13\n",
       "15     서초구     14\n",
       "46     성동구     15\n",
       "10     성북구     16\n",
       "8      송파구     17\n",
       "83     양천구     18\n",
       "4     영등포구     19\n",
       "7      용산구     20\n",
       "890    은평구     21\n",
       "3      종로구     22\n",
       "2       중구     23\n",
       "350    중랑구     24"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 각 구에 어떤 lebel이 붙었는지 확인\n",
    "df1_out[['대여구', '대여구_e']].drop_duplicates().sort_values(by='대여구_e')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 대여구, 반납구 컬럼은 지우기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1_out = df1_out.drop(columns=['대여구', '반납구'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>대여일자</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>대여월</th>\n",
       "      <th>대여위도</th>\n",
       "      <th>대여경도</th>\n",
       "      <th>반납위도</th>\n",
       "      <th>반납경도</th>\n",
       "      <th>대여구_e</th>\n",
       "      <th>반납구_e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>1291.15</td>\n",
       "      <td>ST-36</td>\n",
       "      <td>ST-219</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12</td>\n",
       "      <td>37.55789</td>\n",
       "      <td>126.93808</td>\n",
       "      <td>37.56626</td>\n",
       "      <td>126.94667</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)  이용거리(M) 대여대여소ID 반납대여소ID        대여날짜        반납날짜  대여시간  반납시간  대여일자  \\\n",
       "0        6  1291.15   ST-36  ST-219  2023-12-01  2023-12-01    24    24     1   \n",
       "\n",
       "     대여요일  대여월      대여위도       대여경도      반납위도       반납경도  대여구_e  반납구_e  \n",
       "0  Friday   12  37.55789  126.93808  37.56626  126.94667     13     13  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_out.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. 특성 추출\n",
    "\n",
    "일 평균 방문 고객 수   \n",
    "주말-주중 일평균 방문고객 비율  \n",
    "점심시간 이후 방문고객 비율  \n",
    "새벽 방문고객 비율   \n",
    "주중 출근시간대 방문고객 비율\n",
    "주중 퇴근시간대 방문고객 비율  \n",
    "주중 해당 대여구 고객 비율  \n",
    "주말 해당 대여구 고객 비율\n",
    "주중 해당 반납구 고객 비율  \n",
    "주말 해당 반납구 고객 비율\n",
    "특정 시간대의 대여 횟수  \n",
    "특정 요일의 대여 횟수  \n",
    "평균 이동거리\n",
    "평균 이동시간  \n",
    "주중 평균 체류시간 대비 야간 체류시간 비  \n",
    "주말 평균 체류시간 대비 야간 체류시간 비  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      대여대여소ID  총대여횟수     평균이용시간       평균이용거리    주말대여비율    오전대여비율    점심대여비율  \\\n",
      "0       ST-10    122  79.131148  5754.217869  0.336066  0.032787  0.245902   \n",
      "1     ST-1002      2  22.500000  3910.000000  0.000000  1.000000  0.000000   \n",
      "2     ST-1005      1  37.000000  3207.220000  1.000000  0.000000  0.000000   \n",
      "3     ST-1006      2  59.000000  1822.870000  1.000000  0.000000  0.000000   \n",
      "4     ST-1010      9   9.222222  1381.175556  0.222222  0.000000  0.555556   \n",
      "...       ...    ...        ...          ...       ...       ...       ...   \n",
      "1838   ST-991      1  41.000000  5870.390000  0.000000  0.000000  0.000000   \n",
      "1839   ST-992     10  25.300000  3244.275000  0.300000  0.000000  0.200000   \n",
      "1840   ST-993      1  13.000000  1360.000000  0.000000  0.000000  0.000000   \n",
      "1841   ST-994      2  14.000000  1760.000000  0.000000  0.000000  0.000000   \n",
      "1842   ST-996      1  11.000000  1280.240000  1.000000  0.000000  0.000000   \n",
      "\n",
      "        오후대여비율   새벽대여비율    저녁대여비율    야간대여비율  \n",
      "0     0.344262  0.04918  0.163934  0.049180  \n",
      "1     0.000000  0.00000  0.000000  0.000000  \n",
      "2     1.000000  0.00000  0.000000  0.000000  \n",
      "3     1.000000  0.00000  0.000000  0.000000  \n",
      "4     0.222222  0.00000  0.000000  0.222222  \n",
      "...        ...      ...       ...       ...  \n",
      "1838  1.000000  0.00000  0.000000  0.000000  \n",
      "1839  0.300000  0.20000  0.300000  0.000000  \n",
      "1840  1.000000  0.00000  0.000000  0.000000  \n",
      "1841  0.000000  0.00000  1.000000  0.000000  \n",
      "1842  1.000000  0.00000  0.000000  0.000000  \n",
      "\n",
      "[1843 rows x 11 columns]\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "df1_out['대여일자'] = pd.to_datetime(df1_out['대여일자'])\n",
    "\n",
    "# 주중/주말 구분\n",
    "df1_out['주말여부'] = df1_out['대여요일'].isin(['Saturday', 'Sunday'])\n",
    "\n",
    "# 시간대 구분\n",
    "df1_out['새벽시간'] = (df1_out['대여시간'] >= 0) & (df1_out['대여시간'] < 6)\n",
    "df1_out['오전시간'] = (df1_out['대여시간'] >= 7) & (df1_out['대여시간'] < 10)\n",
    "df1_out['점심시간'] = (df1_out['대여시간'] >= 10) & (df1_out['대여시간'] < 14)\n",
    "df1_out['오후시간'] = (df1_out['대여시간'] >= 14) & (df1_out['대여시간'] < 18)\n",
    "df1_out['저녁시간'] = (df1_out['대여시간'] >= 19) & (df1_out['대여시간'] < 22)\n",
    "df1_out['야간시간'] = (df1_out['대여시간'] >= 22) & (df1_out['대여시간'] < 24)\n",
    "\n",
    "# 대여대여소ID 기준 그룹화하여 통계 피처 생성\n",
    "grouped = df1_out.groupby('대여대여소ID').agg({\n",
    "    '대여일자': 'count',  # 총 대여 횟수\n",
    "    '이용시간(분)': 'mean',  # 평균 이용시간\n",
    "    '이용거리(M)' : 'mean', # 평균 이용거리\n",
    "    '주말여부': 'mean',  # 주말 대여 비율\n",
    "    '오전시간': 'mean',  # 오전시간 대여 비율\n",
    "    '점심시간': 'mean',  # 점심시간 대여 비율\n",
    "    '오후시간': 'mean', # 오후시간 대여 비율\n",
    "    '새벽시간': 'mean',  # 새벽 대여 비율\n",
    "    '저녁시간': 'mean',  # 퇴근 시간대 대여 비율\n",
    "    '야간시간': 'mean'  # 야간 대여 비율\n",
    "}).reset_index()\n",
    "\n",
    "# 컬럼 이름 변경\n",
    "grouped.columns = [\n",
    "    '대여대여소ID', '총대여횟수', '평균이용시간', '평균이용거리',\n",
    "    '주말대여비율', '오전대여비율', '점심대여비율', '오후대여비율',\n",
    "    '새벽대여비율', '저녁대여비율', '야간대여비율'\n",
    "]\n",
    "\n",
    "print(grouped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# grouped 이용시간 표준편차, 이용거리 표준편차 null값 0으로 채우기\n",
    "grouped['이용시간표준편차'] = grouped['이용시간표준편차'].fillna(0)\n",
    "grouped['이용거리표준편차'] = grouped['이용거리표준편차'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1843 entries, 0 to 1842\n",
      "Data columns (total 12 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   대여대여소ID   1843 non-null   object \n",
      " 1   총대여횟수     1843 non-null   int64  \n",
      " 2   평균이용시간    1843 non-null   float64\n",
      " 3   이용시간표준편차  1843 non-null   float64\n",
      " 4   평균이용거리    1843 non-null   float64\n",
      " 5   이용거리표준편차  1843 non-null   float64\n",
      " 6   주말대여비율    1843 non-null   float64\n",
      " 7   점심시간대여비율  1843 non-null   float64\n",
      " 8   새벽대여비율    1843 non-null   float64\n",
      " 9   출근시간대여비율  1843 non-null   float64\n",
      " 10  퇴근시간대여비율  1843 non-null   float64\n",
      " 11  야간대여비율    1843 non-null   float64\n",
      "dtypes: float64(10), int64(1), object(1)\n",
      "memory usage: 172.9+ KB\n"
     ]
    }
   ],
   "source": [
    "grouped.info(show_counts=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. k-means 군집분석"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### (1) 최적의 k 찾기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Elbow Method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "# 군집분석에 사용할 피처 선택\n",
    "features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "sum_of_squared_distances = []\n",
    "K = range(1, 15)\n",
    "for k in K:\n",
    "    km = KMeans(n_clusters = k)\n",
    "    km = km.fit(features)\n",
    "    sum_of_squared_distances.append(km.inertia_)\n",
    "    \n",
    "# 시각화\n",
    "\n",
    "plt.plot(K, sum_of_squared_distances, 'bx-')\n",
    "plt.xlabel('k')\n",
    "plt.ylabel('Sum_of_squared_distances')\n",
    "plt.title('Elbow Method For Optimal k')\n",
    "plt.axvline(2,c= 'r',alpha =0.4)\n",
    "plt.axvline(3,c= 'r',alpha =0.4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> 2~3개가 최적으로 보임"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- silhouette_score(실루엣점수)  \n",
    ": 각 군집간의 거리가 얼마나 효율적으로 분리되어 있는지 (효율적으로 잘 분리 = 다른 군집과의 거리는 멀고, 동일 군집과의 데이터는 서로 가까운 것)  \n",
    ": [-1, 1] 1에 가까울수록 좋음 (= 근처 군집과 멀리 떨어져 있다는 의미), 0에 가까울수록 근처 군집과 가까움"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "k : 2 score : 0.7021455522337939\n",
      "k : 3 score : 0.5898948412013755\n",
      "k : 4 score : 0.5785144285546303\n",
      "k : 5 score : 0.5586525199221611\n",
      "k : 6 score : 0.5331808532721656\n",
      "k : 7 score : 0.535029791158913\n",
      "k : 8 score : 0.5376623480468821\n",
      "k : 9 score : 0.5346895245835437\n",
      "k : 10 score : 0.522847910792645\n",
      "k : 11 score : 0.5225641622925354\n",
      "k : 12 score : 0.5258821744475276\n",
      "k : 13 score : 0.5179064928290729\n",
      "best n : 2 best score : 0.7021455522337939\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import silhouette_score\n",
    "k_range = range(2,14)\n",
    "\n",
    "best_n = -1\n",
    "best_silhouette_score = -1\n",
    "\n",
    "for k in k_range:\n",
    "\n",
    "  kmeans = KMeans(n_clusters=k, random_state=200)\n",
    "  kmeans.fit(features)\n",
    "  clusters = kmeans.predict(features)\n",
    "\n",
    "  score = silhouette_score(features, clusters)\n",
    "  print('k :',  k, 'score :', score)\n",
    "\n",
    "  if score > best_silhouette_score:\n",
    "    best_n = k\n",
    "    best_silhouette_score = score\n",
    "\n",
    "print('best n :', best_n, 'best score :', best_silhouette_score )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (2) k-means 군집분석"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      대여대여소ID  총대여횟수     평균이용시간       평균이용거리    주말대여비율    오전대여비율    점심대여비율  \\\n",
      "0       ST-10    122  79.131148  5754.217869  0.336066  0.032787  0.245902   \n",
      "1     ST-1002      2  22.500000  3910.000000  0.000000  1.000000  0.000000   \n",
      "2     ST-1005      1  37.000000  3207.220000  1.000000  0.000000  0.000000   \n",
      "3     ST-1006      2  59.000000  1822.870000  1.000000  0.000000  0.000000   \n",
      "4     ST-1010      9   9.222222  1381.175556  0.222222  0.000000  0.555556   \n",
      "...       ...    ...        ...          ...       ...       ...       ...   \n",
      "1838   ST-991      1  41.000000  5870.390000  0.000000  0.000000  0.000000   \n",
      "1839   ST-992     10  25.300000  3244.275000  0.300000  0.000000  0.200000   \n",
      "1840   ST-993      1  13.000000  1360.000000  0.000000  0.000000  0.000000   \n",
      "1841   ST-994      2  14.000000  1760.000000  0.000000  0.000000  0.000000   \n",
      "1842   ST-996      1  11.000000  1280.240000  1.000000  0.000000  0.000000   \n",
      "\n",
      "        오후대여비율   새벽대여비율    저녁대여비율    야간대여비율  군집      PCA1      PCA2  \n",
      "0     0.344262  0.04918  0.163934  0.049180   3  0.269506 -0.175693  \n",
      "1     0.000000  0.00000  0.000000  0.000000   3 -0.737956  0.948048  \n",
      "2     1.000000  0.00000  0.000000  0.000000   0  0.375758 -2.626842  \n",
      "3     1.000000  0.00000  0.000000  0.000000   0  0.344172 -2.627848  \n",
      "4     0.222222  0.00000  0.000000  0.222222   3 -0.933399  0.600215  \n",
      "...        ...      ...       ...       ...  ..       ...       ...  \n",
      "1838  1.000000  0.00000  0.000000  0.000000   0  0.367674 -2.360867  \n",
      "1839  0.300000  0.20000  0.300000  0.000000   3 -0.790091 -0.000801  \n",
      "1840  1.000000  0.00000  0.000000  0.000000   0 -0.507381 -2.537223  \n",
      "1841  0.000000  0.00000  1.000000  0.000000   3 -2.110896  0.893802  \n",
      "1842  1.000000  0.00000  0.000000  0.000000   0 -0.106713 -2.727284  \n",
      "\n",
      "[1843 rows x 14 columns]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "# 군집분석에 사용할 피처 선택\n",
    "features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "# 표준화\n",
    "scaler = StandardScaler()\n",
    "scaled_features = scaler.fit_transform(features)\n",
    "\n",
    "# K-means 군집분석\n",
    "kmeans = KMeans(n_clusters=4, random_state=42)\n",
    "grouped['군집'] = kmeans.fit_predict(scaled_features)\n",
    "\n",
    "# PCA 적용\n",
    "pca = PCA(n_components=2)\n",
    "pca_features = pca.fit_transform(scaled_features)\n",
    "\n",
    "# PCA 결과를 데이터프레임에 추가\n",
    "grouped['PCA1'] = pca_features[:, 0]\n",
    "grouped['PCA2'] = pca_features[:, 1]\n",
    "\n",
    "# 결과 출력\n",
    "print(grouped)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- k=2,3,4 일 때의 군집화"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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oamrC5/MRDAbJz8+nuLi403coL7vsMsaPH8/333/PwIEDGTFiRErnzZ8/P+Hd5ubddebNm5dwgWowGEx5Z6OllZWVxa3DSNWvv/6acEpRdx111FEd7ra0dNJw4IEH8tNPPxGNRolEIoTDYQ477DAcx6GhoaHlse+++3a6cOKgQYO6NA3mwAMP5JJLLuHoo4/m6aefbjfRufPOOzn22GPjpgA1GzNmDFOnTm1ZJN5T1lxzTQYPHsydd96Z8K59IsOGDePbb7+NO/b+++8nbOvz+TjkkEP4448/+L//+7+W44FAoM17YKuttuKjjz5itdVWwxjTyVfiKSkp4bzzzmPmzJm88cYbLd/PzqzRGDt2LMcccwwTJ05st90ff/zR5fejiEgmKdEQyaLOLN7tSFlZWcIPju054IADmDFjRtLnky0mHz16dNIPdB0ZN25cl84bMWJEu5XK11577S71C3DcccfFffhc2tIfNi+88EJqa2sxxuDz+fD5fAQCAfLy8ggGg4RCIQoLCyksLEx5OlezjTfemPfeey/uznkqAoEATzzxBDvuuCOjR49m/PjxbLjhhjQ1NTF79mweeughrrnmGubMmcPXX3/Nvvvum7Cfgw8+mMmTJ/PNN9+w+uqr89lnn7HZZpvx559/ZvSuuc/n4+qrr+boo48mEAhw0EEH4TgOjz32GKeddhrLLbdcm3MOOuggxo0bxzHHHMNWW23F22+/zW233RbX5tJLL2Xo0KGMHj2a+vp6Hnvssbjf61VXXZWbbrqJ6dOnU1JSwkYbbcS4ceNYb731GDt2LCeffDJlZWV89dVX3HvvvTzzzDPtvo4jjzyS/fbbj9VWW42ff/6Z999/P67ORaprNL799lv++9//ct1117X5vff5fHGjG++//z6bbLJJSv2KiPQkJRoifdgbb7zRI9dZuHBhu0kCeAta29ve03XddnduikajXQ2PaDTa4boYn8/XEl93kpqO7LDDDhx66KFEo9FOVYgHb1Rg1qxZXHPNNVx66aX8/PPPBINBhg0bxm677Ua/fv24+OKLWW+99Rg1alTCPrbYYguGDRvGHXfcwdVXX82MGTPYeeede2RqzhFHHEFxcTFXXHEF//nPfyguLmaHHXZIeu2jjz6aX375hbFjx1JTU8Nmm23Gv//9b/baa6+WNiNGjOCyyy7jl19+YcCAAeyzzz5xIwSHHXYYzz33HHvssQcbbbQRb775JiNGjGDGjBn84x//YOeddyYYDLL66qunNDpVXl7OiSeeyKJFixg5ciTnnHNOh1O1Emke1frrX//a5rn+/fu3vBdc1+X111/nvvvu6/Q1REQyzopITqqoqLCAnT17trXW2tVWW83eeeedXe7vyCOPtCeffHJ6guuEtdZaywIdPqZPn560jyeeeCKlPrry/TnyyCNT6vvmm2/u0ut/6623bGf+1Lqua9dYYw37yCOPdOl66bbffvvZ++67L9thSBKPPPKIXWONNazrutkORUSkDWOttT2S0YhIt0SjURzH6fKc8eaiYYkWsEpmRSIR/P7UB5AfeughJk6cyEcffdSp89LNWsvw4cP58ssv29QF6aw333wzaX2QESNGtFlrIR2LRCJssskmnH322W2KCYqI5AIlGiIiOeiQQw5h5ZVX5tJLL812KGlRV1fHL7/8kvC5QCDASiut1MMR9X4XXXQRX331VVp2dRMRyQQlGiIiIiIivYC1lnvvvZebb76Z9957L2GbTz/9lBNPPJG5c+dSWFjIpEmT2HHHHXs4Uo8Wg4uIiIiI5LgXX3yRf/zjH9TX1yedVltdXc2ee+7JXXfd1VJfae+99+abb75hyJAhPRyxCvaJiIiIiOS82tparrrqKm6//fakbaZNm8Ymm2zCDjvsAMA222zD1ltvnZVCrKARDRERERGRnLf//vsD7W9N/95777HlllvGHRs9ejSzZs3KYGTJLVOJhuu6/P777xQXF3d5Zx4RERERyRxrLdXV1Sy33HI5uRNiQ0MD4XA449ex1rb5vBoMBgkGg13uc+7cuWy//fZxxwYNGsQHH3zQ5T67Y5lKNH7//fe4aqkiIiIikpvmzJnDCiuskO0w4jQ0NDBqRBHz/ux6EdhUFRUVUVNTE3fsX//6FxdddFGX+4xEIiy9z1M0Gs3aDficSjROOeUU7r33Xvr169dybMaMGYwYMSKl85urx86ZM6fbe76LiIiISPpVVVUxbNiwls9tuSQcDjPvzyg/fzySkuLMjbZUVbuM2OinNp9ZuzOaAVBeXs6CBQvijs2fPz8rC8EhxxINgHHjxnHxxRd36dzmbK2kpESJhoiIiEgOy+Vp7kXFhqLizMXnkpnPrBtttBHvvvsuZ555Zsuxd999l4MOOiht1+iMnJsYV1ZWlu0QRERERER6nUMPPZTXXnuN119/HYDnn3+er7/+mgMOOCAr8eTciIYSDRERERHJpqh1iWawpHXUumnr67777mPmzJlMmjSJFVZYgQcffJCTTjqJRYsWsfLKK/PMM89QWFiYtut1Rk5VBj/llFN49NFHycvLY6WVVmLChAnstNNOSds3NjbS2NjY8nXznL/KykpNnRIRERHJQVVVVZSWlubk57Xm2P78dkTG12gMWu3nnPwepFNOTZ264YYbmDdvHrNnz+Yf//gHBx54IB9//HHS9hMnTqS0tLTloR2nRERERKS7XGzGH31BTiUazXsp+3w+dtttNw455BCefPLJpO0nTJhAZWVly2POnDk9FKmIiIiIiLQn59ZotBaJRMjLy0v6fHeLmoiIiIiILM3FJX2rKBL33xfk1IjGSy+9hOt63/iXX36Zxx57rKXcuoiIiIiI9B45NaJx3XXXcfjhh1NQUMDw4cN54oknWHPNNbMdloiIiIj0IVFriWZwv6RM9p1LcirRePHFF7MdgoiIiIiIpEFOJRoiIiIiItmW6Z2htOuUiIiIiIhIF2lEQ0RERESkFRdLVCMa3aYRDRERERERSTslGiIiIiIiknaaOiUiIiIi0ooWg6eHRjRERERERCTtNKIhIiIikoC1FsIfYBtfBluH8a0E+fthfP2zHZpkmAr2pYcSDREREZGlWLcCW3ECNH2K93HJYrFQcx2UXIQpODDbIYrkPCUaIiIiIq1Ya7EVJ0PTf2NHIq2edbFV54NvMCa4TTbCkx7gxh6Z7L8v0BoNERERkdaaPoWmj4BokgYOtubmnoxIpFfSiIaIiIhIK7bxVbyPSJEkLVxo+gTrLsY4ZT0XmPSYaIYL9mWy71yiEQ0RERGR1mx9iu0aMhuHSC+nEQ0RERGRVox/NWzS0YzmRiXgaPepZVXUeo9M9t8XaERDREREpLXQHmDyAZOkgQMFB2NMoCejEul1lGiIiIiItGKcIkzp1XiJhm+pZx3wr4EpPDELkUlPcXvg0Rco0RARERFZigntjCl/APL+QsvIhlMOhSdhyu/DOIVZjU+kN9AaDREREZEETN6GmPJbsbbRW/htijFG92j7AhdDNOnUufT03xco0RARERFphzFBMMFshyHS6yjREBERERFpxbXeI5P99wUa/xMRERERkbTTiIaIiIiISCvRDK/RyGTfuUQjGiIiIiIiknZKNEREREREJO00dUpEREREpBVNnUoPjWiIiIiIiEjaaURDRERERKQV1xpcm8GCfRnsO5doRENERERERNJOIxoiIiIiIq1ojUZ6aERDRERERETSTiMaIiIiIiKtRHGIZvB+fDRjPecWjWiIiIiIiEjaaURDRERERKQVm+Fdp6x2nRIREREREekajWiIiIiIiLSiXafSQyMaIiIiIiKSdhrREBERERFpJWodojaDu07ZjHWdUzSiISIiIiIiaacRDRERERGRVlwMbgbvx7v0jSENjWiIiIiIiEjaaURDRERERKQV7TqVHhrREBERERGRtNOIhoiIiIhIK5nfdUprNERERERERLpEiYaIiIiIiKSdpk6JiIiIiLTibW+buQXbmew7l2hEQ0RERERE0k4jGiIiIiIirbg4RFWwr9s0oiEiIiIiImmnEQ0RERERkVa0vW16aERDRERERETSTiMaIiIiIiKtuDi4WqPRbRrREBERERGRtNOIhoiIiIhIK1FriNrM1brIZN+5RCMaIiIiIiKSdjmbaJx44omsvvrq2Q5DRERERPqYaKyORiYffUFOvso5c+Zwzz33ZDsMERERERHpopxMNM444wyOPvrobIchIiIiIn2Qa52MP/qCnHuVzz33HAsXLmTMmDEdtm1sbKSqqiruISIiIiIi2ZdTicbChQs57bTTuPnmm1NqP3HiREpLS1sew4YNy3CEIiIiIrKs0xqN9MiZV2mt5ZhjjmHcuHEpLwKfMGEClZWVLY85c+ZkOEoREREREUlFztTRuPLKK2lqauKUU05J+ZxgMEgwGMxgVCIiIiLS17hkttaFm7Gec0vOJBo33HADtbW19OvXD4BIJEJ9fT1lZWXMnDmTVVZZJcsRioiIiIhIqnIm0Zg7d27c12+88QYnnHAC33zzTZYiEhERERGRrsqZRENEREREJBe4OLgZXMqcyb5zSc6+ym233VajGSIiIiIivZRGNEREREREWolah2gGi+plsu9c0jdepYiIiIiI9CiNaIiIiIiItOJicMnk9raZ6zuXaERDRERERETSTiMaIiIiIiKtaI1GevSNVykiIiIiIj1KIxoiIiIiIq1EcYhm8H58JvvOJX3jVYqIiIiISI/SiIaIiIiISCuuNbg2g7tOZbDvXKIRDRERERERSTuNaIiIiIiItOJmeI2G20fu9feNVykiIiIiIj1KIxoiIiIiIq241sHNYK2LTPadS/rGqxQRERERkR6lEQ0RERERkVaiGKJkbmeoTPadSzSiISIiIiIiaacRDRERERGRVrRGIz36xqsUEREREZEepURDRERERETSTlOnRERERERaiZLZBdvRjPWcWzSiISIiIiIiaacRDRERERGRVrQYPD36xqsUEREREZEepRENEREREZFWotYhmsFRh0z2nUv6xqsUEREREZEepURDRERERKQVi8HN4MN2YUer+vp6jjvuOEaMGMEKK6zA2WefjbW2Tbsnn3yStdZai+HDh7Ppppvy9ttvp+Nb0iVKNEREJC1s5Bfcqstx/9wS94+NcBcejK1/FmvdbIcmItLrnXXWWbiuyw8//MCXX37J9OnTmTx5clyb2bNnc8QRR3D33Xfzyy+/cPnll7PXXntRWVmZlZiVaIiISLfZ8Ezsgj2g7j5w54OthqZZ2MozsYvPwNq+smu8iCwLmtdoZPLRGTU1Ndx9991cffXV+P1+SktLmTBhAnfccUdcu88//5xVV12VjTfeGIAdd9yRgoICvvvuu7R9bzpDiYaIiHSLtQ3YipOAMPFlqGIjGY0vQN39WYhMRGTZ8PHHHzNq1CjKy8tbjo0ePZovvviCaHTJ392//OUv/Pnnn7zyyisATJs2jfLyctZdd90ejxm065SIiHRX/fNg2xuWN9i6O6HgcIzJXKVdEZF0ca3BtZn7e9Xcd1VVVdzxYDBIMBhs037u3LkMHjw47tigQYOIRCJUVla2JCD9+vXj3//+NzvttBOFhYWEw2Heeust8vLyMvRK2qcRDRER6RbbNIv271tZiP4GtqKHIhIR6R2GDRtGaWlpy2PixIkJ20UikTYLv5tHMlrfwPnwww8599xz+fTTT6murub5559n//3356effsrYa2iPRjRERKR7TKr3rPS/HBHpHaI4RDN4P7657zlz5lBSUtJyPNFoBkB5eTkLFiyIOzZ//nxCoRClpaUtxyZNmsTJJ5/M+uuvD8AOO+zAvvvuy2233cbll1+e5lfRMY1oiIhIt5i8LYFIey3AvwbGKWmnjYhI31NSUhL3SJZobLjhhnz77bdUVCwZGX733XcZPXo0jrPk43w4HMbvj7+pEwgECIfDmXkBHVCiISIi3RPcDnwrAL4kDSym8O89GZGISLc0r9HI5KMzhgwZwi677MK5555LJBJhwYIFXH755YwbNy6u3QEHHMCNN97IL7/8AsCsWbO455572HfffdP1rekUjWOLiEi3GOOHflOxi44A9w/AABYv8YhC4cmY/D2yG6SISC83depUjjnmGIYOHUphYSHjx49nn3324b777mPmzJlMmjSJAw88kKqqKnbZZRdqa2vp168ft956K1tssUVWYjY2UUnBXqqqqorS0lIqKyvj5ruJiEjn2ehCbzcpZxDGKeq4vVsDDc9gG14CWwf+1TEFB2MCa/ZAtCLSW+Ty57Xm2E55e1+CRYGMXaexponJWz2Rk9+DdNKIhoiIxLHhD7HVN0DTh7EjAWxoT0zxOIxvSNLzjFMEBYdgCg7pmUBFRCSnaY2GiIi0sA2veVOgmj5qdbQJGp7CLtwfG52btdhERKR3UaIhIiIAWBvGVp6Dt77CXerZKLiLsFVXZSEyEZGeFbUm44++QImGiIh4Gl6NVfhOtnQvCo0vYd1FPRmViIj0UlqjISIinuhPeP9baK8mRtSr8u2U90xMIiJZ0JUtaDvbf1+gEQ0REfGYQiCaQruOd6ASERFRoiEiIp7Qjh00MOBbGXwjeyIaEZGssdbBzeDD2r7xEbxvvEoREemQ8S0H+WPwCu4lYjHFp2NM3xjyFxGR7tEaDRERaWFK/oW1UWh4HK+yt8GbTpWHKTkfE9o5uwGKiPSAKIZo0psu6em/L1CiISIiLYzJw5RdiY2cCA3PY90qjH84hPbAOMXZDi/trG2A8Eyw9eBfFeMfme2QRESWGUo0RESkDeMfAUUnLrP33Kx1ofYWbO2tYGuXHA+MxpRe5r1+EemzXJvZnaHcZLuIL2O0RkNERPocW30Ftua6uCQDgKaPsAsPVAV0EZE0UKIhIiJ9io3Mhrp7kjwbBVuFrZnSozGJSG7J5I5TzY++oG+8ShERkRhb/yTeQvdkolD/ONY29VBEIiLLJq3REBGRvsX9I4VGjWBrwPTLeDgikntcDG4GV6llsu9cohENERHpW5z+KTQKqAK6iEg3KdEQEZE+xYT2wasNkowPQnthTKCHIhKRXBO1JuOPvkCJhoiI9CkmsAqEklVA94EpwBSd2NNhiYgsc7RGQ0RE+hxTegnWKYW6e4Hwkif8q2FKr/aKFIpIn5XpnaG061SWXH311ay66qoMHz6cddZZh6effjrbIYmIyDLGGD9OyT8xg97FlN2AKb0K0/8JnAFPYgKrZjs8EZFlQs6NaIwePZozzjiDQCDAm2++yc4778yvv/5K//6pLN4TERFJnXFKILRLtsMQkRzjYjJbGVy7TmXHNttsQyDgLcDbeuutKSgoYP78+VmOSkSkfdZarFuDtfXZDkVERCQn5NyIRrOGhgamTJnCJptswuqrr56wTWNjI42NjS1fV1VV9VR4IiIAWBuFumnYursg+ot3LLABpvA4TOiv2Q1OREQki3JuROOHH35g2LBhFBQU8OCDD/Kf//wnaduJEydSWlra8hg2bFgPRioifZ21LnbxmdjqSyE6Z8kTTZ9hF5+Irb09e8GJiEiX2VjBvkw9rKZOZcdKK63EnDlzqKur47TTTmPzzTfnu+++S9h2woQJVFZWtjzmzJmTsJ2ISHdY24Stfxx34QG4f2yKO/+vuNWTsHUPQOMLgI09mrneedVXYyPfZyNkERGRrMvZqVOhUIixY8fy2muvcffdd3PZZZe1aRMMBgkGg1mITkT6CmvD2IrjIPwu3r0ZF6KLofZmvDoMhvgkozUftu4hTMl5PRStiIikg2szvBi8jxTsy9lEo1kwGCQ/Pz/bYYhIH2VrJkP4/dhXbqtn3ETNlxKFpq8zEJWIiEjuy6lE47fffuPNN9/kgAMOwO/38+abb/LEE08wY8aMbIcmIn2QtWGoe4DUkopEDBjdKBER6W1UsC89cirRCAaDTJ06ldNPP53i4mJGjhzJE088waqrqniSiPQMG/kBor+CKcMSBNud3ewsJrRj2mITERHpTXIq0RgwYACvvvpqtsMQkT7INn2BrboYmj5bctAZ1I0efeAMgNAeXYvHWmiaha1/Atz54AzE5O8HgfUwpm/M7RURyRat0UiPnEo0RESywTZ9hV14CNAU/4T7Z4o9hIBGlmzkFwXfEEy/OzBOQefjsWFsxUkQfpMli80dbP2DENwNyq7BmECn+xUREelJSjREpM+zVRPxkozOrsXwgX9N6HcXpvFZbNNngA8T3BqC23cpGbDWYhceDJEvmo/E/o3F1vgCtnoQpuTcTvedbdaGoXE6ROeBUw7B7TBOUbbDEhFpo7neRSb77wuUaIhIn2ajv0HTBym29gFRWkYZfCtg+t2E8RVDwSEYDul+PLW3t0oyEraAugewRadgnJJuX6+n2PpnsVWXgF1MyzbB5EPxaVDwN00HExFZBinREJG+LTovhUY+yB8DthYiP4JTigntCfm7Y9K4q5S1Uai9JYWWYQh/AL1koblteBlbeWarI80jR/XY6qswGCj8WzZCExFJSGs00kOJhoj0bU55Co2imMB6mIIxmY0l8m3qu1zZcGZjSRNrLbb6atorbGhrboD8g7u0nkVERHKXEg0R6dOMfxTWvyZEviH5Go08CO2U8BlrG6BxBkTng28QBLfFmLyuBWMbU28bWLNr1+hpkS8h+kv7bWydt3Yjf/eeiUlEpAMa0UgPJRoi0ueZ4rOxFX8j2V13U3RywvUQtu5B7269rVlyrimFknMx+ft2PhD/KLw/y5EO2q2B8Y/qfP/Z4Fak0Mik2E5ERHqTvlGWUESkHSa4BabsZq/uRdwT+Ziif0DhCW3OsXWPYKsujCUZ0JKg2Eps5T+x9c90Pg6nDEK70/6fZgfKJne676zxLZdCIwu+5TMeiohIqppHNDL56As0oiEiApjQdhB8E8LvtFQGJ7gNxils09baMLb6mnb7s9VXQ2g3jPF1Lo6SCd42udGfaTu64od+U3D8wzrVZzYZ/0pY/7qxnbQSTU0zsa1ut+rp0EREJMOUaIiIxBjjg+DWHTcMvxfbprUd7h/Q9DHkbdq5GJxy6P8ItvYOqHsQbAWQB/l7YwqP7T1TploxJRdgFx2KNyWsdbJhYs9fpAKEIpJTtEYjPZRoiEjOsdEF0PAcNvITROeAu9B7Im9DTMEhGP/KWY0Pd1F62y3FOKWY4jOwRePwKo7nYUzvnelq8taD8vux1ZdD06wlT/hWxJT8ExPcNluhiYhIBinREJGcYa2F2puwNTfhFcZbSuQbbN19UHIxpuDgHo+vhTM0ve2S8IrYhbrVR64weeth+j+MjcyG6FxvupR/NRXqExFZhinREJHcUXeHV1MhKS/5sFX/Av+qmLwNeyaupeVt6iUR7jwS14Yw4BsJgXV7OLDcZ/yjYrtriYjkLgu4ZO5GSOKqQsue3jsWLyLLFGsbYiMZqXC8NQxZYoyDKb0Yb43B0v8jcgAntu5Ad+tFRKTvUqIhIrkh/EGrrWI7EvV2h8oiE9wW0+928K0U/4R/FUy/uzDBzbMTmIiIdJu2t00PTZ0SkYyzNgwNr2Ij32OcAgjugPGPjG/kVney12RVvHuOCW4FA57zqoq7C8AZ7CUaGskQERFRoiEimWGthcY3vHoT0e+XHAeovhob3BVTdiXG5HtPdGrevg8CG6Uz3C4zxkBgjWyHISIiaaTtbdNDU6dEJO2stdiqy7CLj49LMuI0voCtOGPJ1/41wb8aqf1ZimIKj0pDpCIiIpIpSjREJP0anoP6eztuF34d2/QV4I0MmNIrgDwgWTXt2J+swpMxqRTWExER6QKt0UgPTZ0SkbSztXfi7cbU8QZ+tv45TGBNAExgHej/MLbmOmh8o9X5eWDyIW8TTMHhXVpobSPfQ8N0IAz+NSC4jVcJXERERDJCiYaIpJW1UYh8Qcq7hDdX/Y4xgdUx/W7Buou8ytpOOcYp73o8bjV28ZkQnoE3ImKAqLdwu+wGTN4GXe5bRESWTVqjkR6aOiUiadbJP57+4Yl7ccox/pW7l2RYF1txHITfjh1xaak47s7HLjoSG/mhy/2LiIhIcko0RCStjHEgbzSpJhwm/6DMBRN+D5o+piW5iOMCTdiaqZm7voiI9ErWmow/+gIlGiKSdqbwGFKaOhXaH+Prn7E4bMNzJF9YDhCFhme8rXhFREQkrZRoiEjameA2mOKzO27ozsWGP8lcIG41HRf2awQimYtBRER6HReT8UdfoERDZBljrYttfAdbewe2bho2Oi8rcZjCYzH9n4b8A8AMJuFUqvD72EWHYhvf7LA/G/4Yt+Ik3Hlr485bA3fBGGz90+2PRviH0+GfOWcgxgQ6vL6IiIh0jhINkWWIDX+KXfBXbMXR2OqrsVUXYedvi7v4HKxt7PF4TGB1nNLLIW8dEv+5cQEXW/lPrG1K2o+tfxy7aCw0xranxdvZylaOx1adnzTZMPljSLw+o5mDKRib8usREZG+QXU00kOJhsgywka+xy46EqJzY0dcvHUSLjQ8iV08PjtxRedD4+sk/8BvvS1uG2ckOf93bOW5Xru4PmJTouof8QoEJmD8o6DwpCTX9YF/ZSg4suMXISIiIp2mOhoiywhb8x+gicRrElxofAnb9CUmsFbPBhadkySm1nwQmQ2AjfyCrX8Imv4HTgHYJtpfWO5g6+7B5O+R8FlTdDr4hmJrp0D0t9jRIOTvjyk+E+MUdfIFiYjIsi7TO0P1lV2nlGiILAOsDUPDi7Q/TciHrX+65xMNU5hCIxecImztXdjqiXiDrdHYvx0lKS40fZn88sZAwUHeWpHoj2DD4BuuBENERCTDlGiILAtsHSntnOQuznQkbflXBd/w2MhGspEJgyUE1f+Kfd2cMHWUZCw5362+zlvUHdwaE1i3bQvjeFOlREREOqDK4OmhNRoivZy1TdjGD4COdk6y4Fu+J0KKY4zBFI2jvSSD/IOh/kG6/icpDLW3YWtuwi4cg7twLNZd1MW+REREJB2UaIj0YrbxXez8baDyVDoe0bCYgv17Iqw2TP4emOIL8ZIhE/vX8f47fwwUnQ5Nn5L6CEYiEVpGQpo+xS46GmtVH0NERCRbNHVKpJeyTV9hK/7OkgSjg+rWhSdhsjCi0cwUHgb5e0D9s9joHIxTBqHdMf7hWHdxKnXEm3ui46rjUYh87W2HG9qxO2GLiEgfpMXg6aFEQ6SXsjU3sWQL23Y4gzBFJ0H+Iem9vo1C45vYhme9tR/+4Zj8AzCBNWPPW4h8DtGF4BsM/jW85KLwsLal+0wpOEPBnbv0M/FCe4Ft8BZ0h9/Fq6mRjINteB6jRENERCQrlGiI5AivmvfdsSlEDgS3xRQe2fLBPa6tbYDG12h/qpEDoT0wpVdhjC+9sbqV3mhK0yxadoYK+7B192PzD4e8zaHmSoj+suQk/ypQfAEmuFmb/owxUHgEtvpqEidOBkw+puSilt2i3HmrdxClC251116giIj0aTbDi8H7yoiG1miI5AC3ehK24mgIvwW2EmwFNDyNXbgftv6ZtifYOjpez+CAyUt7kgFgF58FTZ/HvmqOI7Y+ov5eqDwptstUK5HvvYrlje8n7rTgCMjbOvZF6z/APsCHKZsUvyWtb4Wl2i3NB/5RKbwaERERyQQlGiJZZhvfgtqbYl+1roMRBVxs5T+wkV/jTzIlKdSncDG+YekLNMZGvofwm7RfswPajkx4Vcpt1SXetKqlGBPA9PsPpuSS2Da0PjD5ENoL0/9xTHCb+PYFh3Zw/Sgm/8AO2oiIiLRlAWsz+Mj2C+whSjREssTaMG60Alt1QwctXWzdtLgjxvi9AnR0MFqRv1+3Ykyo8U3aH0loj4Xo9xD5KuGzxgQwBQfjDHgOZ8jXOIM/wym7ChNIME2q4BAIrEfbP2Ox2AqPxwRW6WKcIiIi0l1aoyHSw9zwp1BzG4Sn0/GoQEzjG8A/4g6ZohOwja9CdG7ifvxrQ3SetxC7i6xbBw3PYps+A/yY4JZY20hqOz+1IzoPulmh3JgQ9LsLWzsZ6qaBrfWe8K2AKTw+loh1jY18j625Axpf8Baf+0ZgCg6DggMxJq9bcYuISO5zMZgu31RLrf++QImGSA+xje9hq66E6NedP9md3+aQccqh/GFs9b+h4RmgKb5B5EvsogOw+QdhSi72KmN35pINL8PiM2m9s5OtnwamP92rdwE4/bt3foxxCjDFZ2OLTofoHC8xcivAOGCrvSlmnWQbP8BWHIOXvMUSuOhsbPWl0Pgy9LtdyYaIiEgKlGiIZJB1q6DhFWz43Vgy0FWJRz6MbwCm7ErchX9A03vEJwDNi7MfAt8wKDoucYzWhfA72LqHvQXcTn/wrwV1UxKHYhd2/WVgvEXcgXW70UcCtglbMxUangIisbGWPGz+GEzJOd7oRyrd2Ebs4lPwapO0/l7GRm/CH0LtrVB0SjqjFxGRHKM6GumhREMkA6y1UDslVuuivVoPKXL6Jb9W5Htoeqf9eGqnQuFRbe7EW9uEXXyGd6ceH15y4ni7X2WExRT/s9OjK+32aMPYRUdB5Avik4Mw1D+Ijf4I/e7w1rV0pOEFb9evpFxs3X1QeEJq/YmIiPRh+j+lSBrY6HxsdC5EvoWm/0LTFxD5Mk29OxDaPfnTje/Q4ZoJW+HFFlgn/nDNjdD4Suyr5lGTbk6LahEEGpd86fTHFF+ACe2Upv5j6p+CyH+TPOlC+H2v5kho5w67sk1f4v1ZjCRv5C4C90/wLdeVaEVEpBdwrcFkcNQhkzU6cokSDZFusE1fY6uvgfDbGbqCAyaEKWivqneElBZn2/gPz9bWQ929HZ+XlD927tLTunzgWx7KH8Y0fQLuAvANgbwtMSbQxWslZ+sfpv3X72DrHsakkGiQcnzpfx0iIiLLGiUaIp1go39C9DesuwDqX4LG50jfCEACphjT71aMb0jyNoF1UoghDxv51iuy5xsGwb9A01dLdmrqkgiQD9QvdalNMaXXYHzl4NuhG/2nKDqX9pMlF6K/pdSVydsaW3t7Oy0cr8K5M6AzEYqISC/TXO8ik/33BUo0RFJgI7OxVZdAuP21EGljiqHodEz+GIxT0H7bwCbgWxGiP5N40bgBIlB1Ibb5zr8zwKvE3W1h8K0EhX/zNurL2xDjXykN/XaCMyC2K1fyEQ2cgan1lTca/Gt608wSfi9dTOHxGNM3hrxFRES6QwX7RDpgIz9hF+7fM0mGKYXC4zAD38ApPKLjJAMwxmDKbvSSk4QF/LyK3Ev+G3AXQs11dP9eQxSiP2B8wzAFB/R8kgGYDosSupiC/VPryxhMv1vANzJ2pPlPpPd9NUVnYPL36EqYIiLSizTvOpXJR1+gEQ2RBGzke4j8DE6Jt22qrcnQlRwIbgdFZ2B8A8CUYkwH1b6bY7RhLy5T4lXAHvA0tu4eqH8C3CpvXUT0NxJPq7LetU1xbJelRG1SLcrnx4bfxAQ3SynutMvfD+ru87bmTbRexL8qhHZLuTvjGwwDnobGV7ENL4JbC/6VMQUHYvwrpjV0ERGRZZkSDRFi29E2/Rfb8Do0PAHuvAxdyQEMhHbF5G0CoT0xTlGnerBN32Fr/wMNLwJRMPlevYjCE3CKz4bis712dQ9hqy5spyfX243KvzpEviE+sYhNNyo8HqovSSWoTr2GdDJOEZTfj608e6lRJwPBbTClV3a6wJ4xAe9nFNo1vcGKiEivoDoa6aFEQ/o8G56FrTwHoj9m/mJ5m2KKz8EE1uzS6Tb8KXbRkXhVwGN372091D2AbXgZ+j+yZOG4W4GX2CQu9tei+DxMdDa27kFvBMTp501HKjgITDG2drK3pWtSEcxS2+b2NOMbiCm/Exv5EcKfAAbyNsH4h2c1LhERkb5MiYb0STYyG1v/JET+B41v0OGH8S4zkLcZFJ6M8S+P8S3f6R6sbYCmb70K3pVn4hUAXHqqUxTcBdiqSzH9bvIO+ZYjlddl/CMwwdGYgoMTNyg4DFszOcE1wZt+VQKhXVJ+PZlk/CuCpjeJiIjkBCUa0idYa8FWYm0T1EyG+mksqYSdIc7ymMKjoWBsl6pIWxv2CurV3ZfiNrRRaHwNG52P8Q2E0I5QVdjOuT7I26z9rXMBCo+D8EwIv0f89CofEMD0u6nTU5NERERymQr2pYcSDVmmWWuxdY9C9bXAwqWeTXeSUQBFf4f8fTGmGExRytugWhuGhue9URZ3PjjLe/92urq4C5EfwTcQY/Kh+AJs1TkJ2jlg8jDF/+ywR2PyoN9tUP8otu5+iMwGkw+h3TGFR2mBtIiIiCSUc4nG66+/zgUXXMAff/yBtZZx48Zx6qmnZjss6WWstdjah6FmIlCX4as5kH8IpugEb8eiTrJuBXbREbHaDQ7eFKXvuh6OCS35z4L9wMnHVv87titTTGAjTMkFmMDqqXVp8ryRmYKxXY9LRESkl1DBvvTIuUTjqaee4o477mC11Vbjxx9/ZOutt2aVVVZhl11yYw645C7r1mDrHoaa24EFGbiCD/IPgfCHYBvAvwYU7A95W+E4XX8r2Ypx3loRoNtVxp1BEFg77pAJ7QrBXSDyFbiLwTdMi6RFREQk43Iu0Zg0aVLLf6+44ooceOCBvP7660o0JCFrw9j6V6BuGkQ+otsf1NtTeDxO8bi0dWebvsJWXw9N76WtT1N0YsI6HMYYCKyVtuuIiIgsy7wRjUxub5uxrnNKziUaS5s/fz6rr554ekdjYyONjY0tX1dVVfVUWJID3PCXUPE3rxZERhkoPAlTdFpaerPWYmuuhdpb0tBbc1LhQuFJkJ+9qU02+mds+lcA8tbHtJrCJSIiIn1PTicaH374Ic8++yyXXJK4YNjEiRO5+OKLezgqyRYb+QVbcx80PAZU98xFfatAv//g+Eekr8+GJ9KTZAQ2A/8KGN9y3gL0Lmydmw42uhBbeRGEX2bJjlQhbOExmKJTUq50nrZ4rIsxTo9eU0REli0q2JceOZtoPPjgg4wbN467776bUaNGJWwzYcIEzjzzzJavq6qqGDZsWE+FKD3IXXwhNDyYwSsYwA+BTcA/DPyrYoKbY/wrd6k369aCrQOnzKsy3XzcWmzNrcRvE9tZPnCGeNvKOsVd7CM9rFuJXbgPuH8s9UwD1N6EjfyE6Xddz8RRexfUP+TVEzFFkL8fpvBvXiImIiIiPS7nEo1oNMqpp57K9OnTeemll1hvvfWStg0GgwSDwR6MTnqSG66FRQcB/+uwbXpYb71E00xMyXldSjJs+DNszU0QnuH1Z4qw+Qd4ayecMnD/7H4F8sBamLIbsp5kAF4hvzZJRiuNz+GGj8DJ2yBzMUQXYhcdBNFfaVmjY2ug7n5s/VPQf1qXE0YREembLF2/HZhq/31BziUa48aN48cff+Sjjz6isLAw2+FID7PWYisugvC0nr4yEIn9dxO26iJw+nk7NqXaQ+Mb2IoTW/VH7APvPdiGF7CB9SH8UddDDGyAKTkfE1in632kW93DHbepmQzlUzMWgq26FKK/kbBauq3BLh4H/Z9JuaaJiIiIpEdOJRoNDQ3cfPPNzJkzR0lGH+NGqmDhoWC/zXYoMQZbfQMEd0npA6q1jdjF4/E+7C59nyIK7jxofCnBcx3HARaCu2LKrsmpCtzWWqC+44aRzP1MbXQ+NL5I8t3Got7WwU2fQd76GYtDRESWLVqjkR45lWj8+OOPuK7L5ptvHnd8tdVW46WXXspSVJJJbvgzWHwWuL9kO5SlWIj+ANGfwL9kjZC1LrbuIQi/AfggtDcmtBM0vAK2o13POplkOEMhuD2mYF9MYN1Oxp95xpgUX1EG/5hG/kfHWxobr8K6Eg0REZEelVOJxpprronrZrAOguQMNzwLFh0PZHpr2m6ytd4/bg229laovZ0lU6yAxlexlcWQvyve2ymSqJcuMFD+EI5/SJr6yxBTDLaDHcAymSSlNMJjgdwZCRIRkV5AizTSQntASo9zGz+MLfLO8SQDP9ZZHltzM/bPzaF2CokTiWqof4x0Fws04dfT2l9GFBzecZvCUzN3/cC6YEo6aORA8C+Zi0FEREQSUqIhPcpaFxaPo3ek8hGYvy225jqgsYO2UdKbaDje9rg5zhQdD75VkzcoOAonL3HBzbRc3wQxhce008KB0J4YX46PDImISG6JrdHI1IM+skZDiYb0rPB7YBdkO4pOSGGxcws/6XtLRcG3Upr6yhxj8jH9H4KCo4BWW007gzElF2GKJ2Q+iMLjIf+g2Be++H/ztsCUJi74KSIi0pvU19dz3HHHMWLECFZYYQXOPvvs2MYs8ay1XHvttay22moMHz6clVdemaampixEnGNrNKQPiMxOU0cGAltA0ztp6i8dfJC3VWyhuIO3CDrRLlQdccDpnzPTfaxbCfWPYuuf89Zj+FfBFBwMeX/BGINxCjEl52KLz4DIz2AC4BvVY9W5jXEwpZdiCw7B1j8K0bmxrYn3hrxNta2tiIh0mrXeI5P9d9ZZZ52F67r88MMP1NbWssMOOzB58mROPTV+ivLll1/Oq6++yltvvcWgQYP4/fff8fl8SXrNLCUa0rOc7m5bbKDwLEzR37F/bpWWkNLG9MPk74mN/gzRWELlDIbgNrE1HOBNsQIvEUk01coHGEzpNRiT/benjfyIXXQYuAtpSZiiv2IbX4XQvlA6sSWhMCYfApmbJtURE1gTE7gwa9cXERHJlJqaGu6++27mzJmD3++ntLSUCRMmcOmll8YlGvPnz+fKK6/k66+/ZtCgQQAst9xy2QpbiYb0sOC2eB+mox00TKQUM/hdjAlgm74COz+9sXWXfwVs5VnETZ9y50P9w5B/ADil0Piut5NV9He8RCNWJ6NZYANMyTk5sZ2ttS624nhwK4gflYn97BqegMCaUHhkNsITERHJmJ6qo1FVFb81fjAYJBgMtmn/8ccfM2rUKMrLy1uOjR49mi+++IJoNNoyYvHss8+y1VZbMWzYsIzF3hlaoyE9yjj9oKCrH0wroXE6ALbheVKvz9ADv+amHJqaq363HqmI/Xf9I5i8bTBlkyA6jyW7V7X+AG8g8gP4RmQ83JSE34Loz7SXFNraO7wF/iIiItJpw4YNo7S0tOUxceLEhO3mzp3L4MGD444NGjSISCRCZWVly7HPP/+cESNGcPzxxzNq1CjWX3997rnnnoy+hvZoREN6nCkej3VroeGhTp7p8z6IA7jVeAlEKiMjGf4gHNg0Nlrxejvx+LB194NvEF6SkWhypgW7GOofh8KjMxVtymz4QzqsDeLO9R6+5XsqLBERkWXGnDlzKClZsk17otEMgEgk0mbhdzTqfeZovRaxurqa5557jnvuuYcpU6bw2WefsdNOOzFixAi22WabDLyC9mlEQ3qcMX6csksxA16FwlMguAPk/TWFM10w3hoP4x9OVrfIdYZ59SEGfYTT/z6IfEP7SU/Uq07d8HIH7Sy24eX0xtplKX5/M7laTkREJBuat6DN5AMoKSmJeyRLNMrLy1mwIH7Xzvnz5xMKhSgtLW05NmDAAHbZZRd22GEHjDGsv/76HHbYYTz99NOZ+161Q4mGZI3xD8cpPg2n338w/f4TmzLU3nQoi43+hnWrILQP2fn1jcWXtxGm6GQcJ3YXwoQ6PjX6G7jzOm5nG7oeXhqZwCZ0WOncGQy+oT0Sj4iISF+14YYb8u2331JRsaTY8bvvvsvo0aNxnCWfh9Zcc02qq6vjznUch1Aohc8pGaBEQ3KCMQZTdBod3kWvuxu7cD+vXcFZPRHaUmLxNTyJrbnZOxKdD4GN6fjtlMoULh8E1u5cRNF52LoHsLW3YxumY20HyUGqgluDbwWW1KZoyxQehTHZ2TJPREQkU5q3t83kozOGDBnCLrvswrnnnkskEmHBggVcfvnljBs3Lq7dmDFjeOedd3j11VcB+Prrr3nggQc46KCDEvSaeVqjITnD5O8JbgW2+kqS30l3IfobtvJfrRZfZ0ntJNy6e8EuSmOnUUzBISm1tDaMrboE6h/FS4Bia1acQVB6DSa4ebciMcYHZbdgKw4HdzFLEqXYrmGhPWKF+kRERCTTpk6dyjHHHMPQoUMpLCxk/Pjx7LPPPtx3333MnDmTSZMmkZ+fz2OPPcZJJ53E/PnzGThwIFOnTmXddbOzm6WxiUoK9lJVVVWUlpZSWVkZt7BGehe38QOoODzLUfQHFnbjfAfvw3+qby+vroYpOgNTdGLLUdv0FbbhJbC1GP8oCO2FcYoBcBePh4ZnElzDAXyY/g9hOjk6koh1F0Hdw9iGZ8GtAf/KXjIU3K7HivKJiMiyI5c/rzXHNuK2C3AKMjfdyK1r4Oe/X5qT34N00oiG5BwTnZPNZd4x3UkyDJgivF2kqjtsDUBgfUzhsZjQDgBYtxZbeQY0vkFzET9LFKquhNJLvelVDckWdnn1OWzNZEy/Kd14HbFX45RD0QmYohO63ZeIiIj0HUo0JKdYtxIb/iDbYXSTBVvlLW6PdpBoOCtgBr6IMXnxPVSeCY1vxr5qvUtVI7bynxDanfYLH0ahcTrWrcE4RV17GSIiIn1UTxXsW9Zp3oPkDFv/JPbPLdu5U9/L+Feh/beYD0LbtU0ymr6OFSZMtnjcQPh9Oi5Y2IkRFREREZE004iG5ATb+Da28uxsh5FebjXtJgsYTMFhbZ7x6mi0N1rhgruAju8TBMEpx9oohN+ByPdgCry1Fb7BHZwrIiLSx2V/Hnevp0RDss5Gf8MuHp/tMNLMtLMrlgH8mLJJ3gLvpdlaOh6taO4nGR/k7wNNn2MXn+VV725ZoH4RNn8MpuTCNqMpIiIiIumiqVOSVTYyBzt/7zRvEZsBph/t1ZNILNmIRAAGPN+y8LvNpfwr0mGhPJMPRacnedIHTjmEdsEuOgrcP2LHXbxEw4X6R7CVEzp6ASIiIn1S8xqNTD76AiUaklW26jKgKtthtM+UwICnvJoRpnlhdRD8a9O8I5Q3OGhiXzePHCQTxjR9nvzp0B5APslHLHyQPwan6ARM6ZXgW77Vcw4E/4rp/yjUTcNLdhJN37LQ8Ay26X/txCkiIiLSdZo6JVljo/MhPD3bYXTIFP8T4xsCJf/EFp8Ntg5MCGN8Xo2Jhhew0fkY30CsszwsPq6DHv3YyA9J0wjjFEHpFd7OU7H6Gkv4wDcMU3SK1zZ/PwjtA5Fvvbh8IzC+AVi3Dhpfpf1q5D5swzOYQDYqrIuIiOSwzpTC6mr/fYASDcka2/TfbIfQPqc/pugfmIL9Wg4ZY8AULvnaKYeCQzHgjQ4saru4uy23wy1nTf7u3kLumpug6cPmg5B/AKboZIzTr1VMDgTWiO/A1tB+kgFgYhW/+w5rmyA6F4wfnKHez1NEREQyQomGJGSthfD72LD3IdfkbQx5m3e5ErS1LoTfg6ZZgAN5W3i7IHVLe9W3mz9AduGWQeHJmLyNIG80xgRSOsXaMLbibyluJ+tiTTG24gSI/AROGSZ/71jV71ZJTHBzTHBzrFvhjVY4A1NfvO2UASGgod04TNy0q2WXtWFszc1Qdz/Yxd5B3wgoPB7y91fCISIiSzGktjFLd/pf9inRkDZs5BfvQ3D0e5p/RWztTeAbBf2mJN4pKVlf0d+w9c9D7S1eEbsW14EztJuRJrtj7wB+KLsWqq+D6A+pd+lfG1N0WkofPG10HjS8gnUXQHgmuH+meJF8qDqfli1sowbb9AnUToXy+7xpWq14oxf9EnWUlDF52Pz9oP4hki9Kx9uZahnnJYHHQvhD4n5nor9gq86F6E+Y4mVt1zMREZHsU6IhcaxbhV10aKxOA8TtfhT9xXtuwPMYp6yDfhZjK8+DxleSN3LndjveeA7kbYbJ2wIKxmCccmxwW2/6Ue0UOh7dKMD0+0+HSYa1Tdiqy6H+Qbo2ibM+9m9zAhA7P/obdvEp3kLuNDBFJ2EbXwV3IYmSDVN0epukBrzkELcKfEM7/Dn3CvWPxQocLi32fa+9FRvaDRNYs0fDEhGRHKY1GmmhXackXv1jsTvzie6CR70PrXWPtNuFtQ3YRYdD4+sZCTE5A4E1MUXHeWsn8O7sO8VnQHDXjk8vuz7hB++l2apLoH4aS7aLTZcoNP0XG/4sLb0Z3yBM/0cg+Ffi3urOEEzJZZiiE+Pa28a3cOfvi52/HXbh3tg/N8Wdtybu4vHYyE9piSkbbN39dFRzxNY/3FPhiIiI9Bka0ZA4tv4Z2v/wbLENT2OK/p68Sf1T3i5IPS4KDa9BcXyFcRv+BBpfaP/UvO0wwW289taFyJexu/orYPwjlvQVmQP1D5O5WxEOhD+AvPXS0pvxDcX0m+zt8BX9yVtQ7l8DY+Jrgtj657CVZyToIQINT2MbXoLyuzF5G3YpDtv0Obb2bmh8C4hC3kaYgiMwwS271F+nRH6m/Z9XFCKdmF4nIiIiKVGiIfFsCjUtIt/h/rERBNbFFBwBwW3jphvZ+sfw7iBnY1ywqc0RW3sr3h399tcqGGOw9c9ja/4N0V+XnB/YGFNyASawBjS8QGZfW2b6Nr6B4BuY8Dlr67FVF3TQQyN28SkwcEaHC+Rt05fY2nsh/C5gvDofTR8T9zNofBPbOB2KTmvZqjdjTAHYxnYaOF6tFBERkWaaOpUWmjol8fwr0XEFbNfbXSn8Pnbx8djqid4uVc2if5Kdd5APAhvEHbE2Co1v0G6SgQ/CM7B1j2Irx8UlGQA0fYJdeDC26RusrSSzb5so5G2cwf4TaHg5th1uB9wF0Phau01s3YPYhftBw1PgzvPW4TR9hPf70Ppn4P23rbkB2/hel0NPSf4etP877WJCKUytExERkU5RoiFxTP7BtP+hvLVYu7q7oPFlrFuBrX/Wq1GQFVFMwdJ1LJJVxm7NgluDrb4syfMuEMZWX4XxDSP1709n+cC/OgS6Nj2pq7z1Fx0llwA+bDsVzW3TV9iqf9E2qeigz7p7UmzbNabgSDB5JP5z5/N2UwvtlNEY0slaG5/Yi4hI+lmT+UcfoERD4gW3hbztOnmSwVZehv1zK6+adfSXTETWDu9Dsik6A5MXP6JhTB74htPxftWOV6siqSiE38EGNgFSrGXR3G/KTQdgyib3eE0H45TQcTLWLPm0KVt7H53/kxKF8MedPKdzjH84pt/d4PSPHfHTklj5V8eU35N6fZIssdZi65/DXXgA9o81sH+sibvob9jGd7IdmoiISFJaoyFxjDFeXYhOrRWwYP/IYFQdyNsCU3gUJviXhE+bgsOx1Ve004GJJSOxuhbtifzgTW0Kt/cBL5YoFJ8PkW+gvv1duiCIKT7dq/rtlHbQNgNCO0P1xBQaRjHBbZM/3fQ+XRrt6YERMJO3Pgx8Axpfi1Wk93u/L4GNc75Yn7UWW3UZ1N+Ll8jFksLwe9jw21B8PqbwiGyGKCKyzLHWe2Sy/75AiYbEsU1fQST59JjcYiC4K06/69tvVjAWGmfEkoPW72wf4GJKLwcbxqZyV7/yLOJqiySSNxpTeKJX1bvhFWz9kyRapO5xMP1uxwRHd3ztDDG+5bDBPaDx2XZaORBYBwLt7YbVlQFSH+Rt3fKVdRdB3WPYxjeACAQ2xBQcHLfzV1cZE4DQLpjQLt3uq0c1vhFLMiB+5Cm2zqX6cghugfGv3NORiYiItEuJhsRr+iLbEXSCxYS27bCVMQHodwvU3YutuxeivwEG8jbHFB6PCY7GuhVQdSnJE4JmyXYvMlB4IqbwGIxT7EUX/gi7+FSSjwwFvQKBsSTD2iiE3/I+ZNsmr4BcaG+MU9Tha+wqG/kRW3UxhDtYkG1KILQf3vcnyTSjvK06rkTeNoKWu/E2/Am24pjYFLbY96zpv9i6O6HkMkzBmE70u+zw1rC0N9rmYOsewJRc2INRiYgs47TrVFoo0ZB4HWxdmlOcwRDbLcha2zIFxrpV4M4Hp1+rwn0BKPwbFBwNth6MP25evnH6YQuPh9rJXQzGQv3jUHTakiM1N+FNo0o2UtIITinWRrH1T0D1FbHdnwxgsPWPQPXVUHo9JtTZdTMdRGuj2MjPsOigdnacap6m43i7jFX/C1s7GVv2H4w7z6utYevAvxIm/0BM4WHY+gdTjMAHWEzpNZjAml4l+YpjvZ9N3F/f2F37qvPAv7I3BaqvafqC9pM3r9CjiIhIrlGiIfHytiD19RkprGnIJN9G2Pk7Yt0/AReLDy/2JVObbN6WmKJxmFgBPGOMV1chAVN0Krb2dqCha/G487wExzcY69Z0sI4DwIet/jc0/Q/solbHW91GsfXYxSdD/0e9EY5usg3TsbVToWkmHf+M3aX+xdvidtFBsWlmsZ9/4wxs7e2YojMxpf/GVo7H+zk0/27EFl6HdoXoPJq38DX5B2P8w7zn6h8DW9tOTA629k5M3qROvuJlgAmk8HYM9kQkIiJ9R6Z3huoju04p0ZAW1lrvA19HiYazHPgGezUr6l8AO7enQozX9PxSBxIkPeH3sIs+gH53YIKbtdudMQbb7cQp9pZqdwerZlEIv59CO4utnYop+7/uBIatuQ1bcw3eSEVXx2xbjyVH4/61Nf+HKZuEGfAitu6BJQX78rbEFIzF+Icn77Xx7Q5i8qaV9UnBHWIbCiT73TSY0PY9GZGIiEhKlGjIErVTsDXXt98muCum7P8wxo8brYa6O3oktK7z7sbbynNg4OsYk3jBsnUXeW06XKORjAHfyhCbqoXTD0xRaoXwOhT1iup1g236JpZkQOpb2XaWwdZMwRnwFKbk3E6em0qCl8XRsywyhUdg6x8l8Q0Ax/s9y98/C5GJiCy7jPUemey/L1AdDQHAutWxNQUdaHwZ2xCrDh35LLNBpY0L7u9JFzxb24BddAQ0dueOucUUHRvbHngR1D8N/rVJ31ssjLVdTxBs3YOkVpSvOyxEvsZGF3b+1MCGtP+9alv1va8w/pUxZTfhLcI3rR6AKcGU34VxyrIWn4iISDIa0RBP42tAOIWGUag8FeubBtF03K3vKQbb9KU35csZEP/BrP5piPwvxW4KY2sJmu8ux9YpFB6HDe6BrboC6u6jwy1wO8s3MuloTDI28pNXRK9xurd+pMdGBFL5PYpnCg7E1t5K8tGWqFfhu48yoe1g0Ayofxwb/gTwYYJbQmhPjFOY7fBERJY92nUqLZRoiMddTFwxsA7Yqn9jSs7pRe8TCzX/xtb8GzDY4Pbe4uXAKti6x1I4Pw9TchE2tCum4Vlsw4vetCj/apiCgzCBdXAr/wX1D9LxX4/OL6I3BYd1qr1b/wJUnkHmpkklYfqBM7Dzp/mWg9Krkywkj0Lh39O+81ZvY5xyKDwWo7xCRER6CSUa4vEtT6c+lEY+xvpXBoqB6gwFlSkWGt/Aht+F8mkQnd3xKc4ATMEYbxwjfwzGtwJEfwZTgnUGY2tugfpp7XRgvCrUZddiK/8B4Q9J+fudtyUUHJxaW8CN/ASVp6fcvi0fEAJqO3meAwWHYrpY6dvk7wH+FbG193ijMEQgsAGm8AhMcOsOzxcREUkb7TqVFko0xBPcBkwZ2MUpn2JoxJZeDJVnZiyszImCbcQuPj82FaoDzgAAbOO72MoJ4HZ2py0LTR+BCWIKDsOmtNuUzysCWHSCVwcklavYBlh0TCdjM7FrneAlXQ3PkXCLX1MMob1a7YAUbXU+XiJVdHwnr73UJQJrYsqu7FYfIiIikhu0GFwAMCYPU3oJLR8aOxQAU4qTvweUXEXSatE5zYXoF6S001RglVjl6mNj6x26woJbCcEdY1W2IeH325RC0ekw8EOc4tPiCgu227tbh114OLhzUozH8a5v8jH9bvWqrDc8F3suwdQuW43J3wPT/wkI7Q3ke+f7RmCKz8OU34ExqucgIiLLANsDjz5AiYa0MKFdMGVTwJSk0LgUIl8C4BTsixk8C0J7ZjbATvFDaLc0drcKtvr/8KY7dfWvgx+c/hhjMKVXYEouA9+KS54OrIcpuxFn8EycopNxfMWd6t3WTobI5ym2diC0i5cgDHwTE9wKW3s/7e9M5cPW3YcJrIJTdiXOkM8wg7/BGfiyN70pxYRIRERE+gZNnZI4JrQd1vcELPxr+w3tAuzCA7AlE3EK9sMYP6bs/3DrNoGqK4FUCtZlig8KxmLyRmMbli7q10XO4Fg17W7EFNod4xQBeDtIFRzo7bbk1oLxYUyozVnWeoXqbPhjwGDyRkPe5m12oLK2EeqmkfK6D2cFnLLr4481zaL9RepRCH8ad8SYrs0xtdF5UP8ItukrMHmY4LYQ2k0jIiIikhu061RaKNGQNgzVKf7+W6g6BzcyG1N8JtAEtfeR3SQDbwvagkOwdc913Dal/orBN7IbHThevYOixAu0k21Papu+wy4+HqK/0vxWtbVTwLcS9LslvtJ2dE5qa02aFR6aIJAURiTSMGph65/AVp6L91fWBRxswwtQfR2U34Xxr9hBDyIiItIbKNFYxtjoAoh8CyYAgXUT3iXvUOS7zrWvuwWLhcYZEE2xHkVXmQKw7SUyPsjbAhaMofO7JiVhw+AbQuLKzCkIbIkp/RfGv0Lql4wuxC46DGxV7EiruhzRn7znBjzfMkLSqTUyzpDENSmC28V+9slGRXwQ7GCkqwM2/FGsAnvr72Pseu587KKjYOCrmoYlIiKyDOjUGo2vvvqKKVOmMG3aNGpq2hZr+/vf/562wKRzrLsIt2Icdv5W2IqjsYsOw/65BbbmRm/6TWeY/M4HUHcrRL/t/Hmp8m8KA96CgR9jis/G2341kSg0vkjakgwAGr0P/MHt6NxbxkDhCTj9p8aPPqSi/kGwlSSeyhQF9w+of3zJId8w8A2nw8X8zvKY/o8nLP5nCg5hSfXpNs8CPkzB2FRfQUK29naSfw+j3kL7hhe7dQ0REZFu02LwtEj5U9MjjzzCVlttxSuvvMLNN9/MKquswsyZ8XPWX3vttbQHKB2zbhV24cHQ+BJxd6NtjZdoVJ7fcR/WYhvfw9bcjG36ltzaRcqArx+OfzDYKmzDyyTcfjWTah/EFI/vXBIW3B5TdFqXLmfrn6aj9Ra2YcnUMGMMpvAEkv/lMuBfFTPwNYxvQOIWvqGYfrfGXqOJP5cgpt8UjH9YJ17FUvFaC41v0v46EAfbOL3L1xAREZHckfLUqYsuuohXX32VDTfcEICnnnqKfffdl/fee49hw7r+4UPSoO4eiP5C0g+mDY9hmw7BBNZN+LSNfI+tODlWuM7HkrnzucJC40u4Vf8HdXeQ0na06RZ+F1M6AcofxC4eB9Ef2mlsoPgCTMEhGNPeLk7t6HC9hQV3qUKJ+ft7azVqb2ZJ9fHmau9+sC7UTsHmH4Tx9U8ceXAzGDgd6h/HNn4AWEzeplCwv1eZulsscVPAkrWx4W5eR0REpJtUsC8tUk406uvrW5IMgL333pvZs2dzyCGH8NZbb3V59xnpPlv3EO0nBj5s3WOY0raJho3+iV14aKu1AJ2cZtWT6m7J4sW9D/4msBq2/3NQcTQ0vZe4aWgvTMHBXU8yAPwrQngB7a6X8K8Ud8QYgyk+A5u/J7b2IWh8OVZY0AGaIPo9tuZ6qLkeG9gMU3w6Jm+jNj0bpx8UHoMp7Gzhv/YZ42D9q8bWgSQfeTGBtdN6XREREWnr8MMPT/j5fciQIfztb3/j8ssvj3veGMPdd9/dqWuknGj079+fefPmMWTIkJZj48aNY8aMGRx77LHccks2PwT2ce6fHTSIQvT3hM/YuvtjawFyaQQjB/m8hdzWulB9QfIkA6Dhaayth7IbEq6FSIUpGNtB9fAopuDgxOf6V4bAqtj65j8GCX62Te9jF70PJZck7ScTTMGR2Krz2mnhQP6YHotHREQkEWO9Ryb7z7Yddtgh4fGSkhLKy8vZeeedOe2005g8eTKu63LaaZ2fDm6stSm91EcffZSXXnqJ2267Le54fX09Bx54IDNmzCAcDtPQ0MNz51upqqqitLSUyspKSkpSKDq3jHD/2BTs4nZa+CC0F07ZVW3P/XOb2F1vaVfptTj5e2DrHsBWXZTSKabsRkxo5y5dzloXu/g0aHyFhHf/Q/t7Rf8S3Imw1mIX7BqbCtfR29tgBjyPWWp0JFOsjWIXnwmNLxC/i5c3Zc+UXoPJz6XCjyIikm65/HmtObbhV1+Gk9+FnTtT5NY38MvZ5+fk96C1oUOHMnfu3Db/naqUb7eOGTOmTZIBkJ+fzzPPPMPHH3/ME0880amLS5rk70f7FZ2jENob2/RfbMN0bNPXtOSX7qKeiLB3c5bDhHbyPsDX3kGHOzt5J2HrHujyJY1xMGXXY4rOBKfV4m1nCKb4XEzp5cmnK9oqiP5IaltaONi6B7scZ2cZ48OUXYspuQL8q+F9LwMQ/Cum/EElGSIikhv6yK5Tp58eX+Prv//9L+efv2QToaWnTnVW1+Z1JODz+XjnnXfS0pe1lnvuuYfNN988Lf0t60zhUWBKSJxsOOBfHaouwC4cg118PHbh3tg/t8Cdtw7Q2LPB9jo+TPm9Xl0Hd0Fs0X0qfx1ciPzYrSsb48cUHY8Z+CZmwCuYAa9iBk7HFB7V5SlZbUUh/HGa+kqNMT5MwRicAU9jBn+DGfwFTr/JmLz1ezQOERGRvm7atGkt/93Q0MCJJ57IX/7yl5ZjKU58Sqpbn1YaGxu5//772W677Vh77bX55ptvuhUMwIsvvsi6667LJZdcQkVFRbf76wuMbwim/7TYHeLWHAhsCJFvwJ0T/5RdSPqSDEMac9bcUnhS17d0NcVpCcEYP8Y/AuMfntoCc1MCvhVJbeQFr7hjlhhjMrKRhHUXY2tuxp3/V9w/NsCdvyu29k6sm876KiIiIsuG33//nT333JNdd92VnXfu2rTvRLr06fDjjz/mpJNOYsiQIRx55JEceuih/P777zz66KPdDqi2tparrrqK22+/vdt99SXGvyKm/xOY8kcwJRdhSi6H8heg6fMMXzkE/rVYZheTR2djrbclq3XraH+K2lLyd8tMTB3wamocQ6pTp0xw2wxH1LNsdC52wT7Ymknedr+2FqI/YquvxC46COsuznaIIiIiOaGqqoqtt96aVVZZhR133DFu2hR0bbpUaynvOlVRUcF9993H7bffzsKFCznyyCN5//33WX/99Tn22GO7FURr+++/PwBvvPFGh20bGxtpbFxyV76qqqqd1ssOay1EvvUK8plSTPgtbOR/QAgT+ivWvz5UngPR9nb3SRP/ihD5IvPXyZaG57DOQCg+CxYfTacSKlPaYRNrXSDiTc1Kp/wx0PQF1E9rp5EDJgT5B6T32llmF//Dq5we97OKJV2RH7BVl2DKrs1GaCIi0ksYMrzrVOa67pRQKMQJJ5zQsuHTHnvswZprrskPP/zA5MmTqaqq4swzz8RaS3V1dccdLiXlRGPo0KGsvfbaXH311ey44444jjcYks36GRMnTuTiiy/O2vWzwdY/69VCiP6y5BjQfKfd1nd9AXKXRL7q2ev1OAt192EjP0L0186dGn4PCg9P3GvTl9iaW2O7SkWwzlBMwWFQeDjGdH+XC2MMlFwEoZ2w1ddD5LOlW4DJx/S7NWml8N7INn0HTR+20yIKDc9joxMwvoE9FpeIiEguysvLY+zYsYwdO5YZM2awxx578MorrxAKhRg5ciSXX355S9vLLrus0/2nnGhMnDiRO++8kzPOOIOjjjqKI444Iq6mRjZMmDCBM888s+XrqqqqZbpKeftbq+Zwob1erwnCMzp/WngmbtVFmPwDMYE1Ww7bxhnYihPxUsTYz82di635NzS+CuV3py/ZCG6JCW6Jjc6D+kew4Y8AHya4JeTv5xXnW5Y0LZ1QJeJC5EvwbZvpaEREpLfqI5XBWy/23mabbbjxxhs56KCDmDlzZpsdqboi5UTjjDPO4IwzzmDmzJlMnTqVtddem0022QTXdYlGo/h83aiC3EXBYJBgMNjj180G61ZhqzqfSUoW2Uqoe8hLEP1rQ2BNcJaD2lvxEoylx2QtNH2GrbkFU9z9N7dtfNPbjjf8kXcgbxNM4TGY4Nbd7jtnpbwbV8p/+kRERJZZTz31VNzXu+++OzU1NWmbsdTp/9tusskmbLLJJlx//fU8+uijNDQ0MGjQIPbcc08OOOAAdt9997QE1tdZ2wCNb0B0PvgGYSNzgUi2w5JOi41YRL6ITTPraPNsF+ruxxadjDFd/zBsa27G1lyHN6UuFkP4fWz4HSg6A1N0Ypf7zml5mxNfCDCRIATW75l4RESkd8p0rYscqaOxxRZbtDl20EEHpa3/Lu9JGgqFOOyww5g+fTozZ85k+eWX56STTkpbYH2ZrXsQ++cW2MWnYasvwy4+FWquyHZY0m0uKf1lsYu9mh1dZMOzYkkGxE+p8/7b1lyHDc/qcv+5zPiGQnAXkv9pM1BwCMYp6smwREREeo1Bgwalra+UE42GhgaampoSPrfiiity4YUX8t1336UtsL7ERubgVl+Du2Bf3D+3xVZdCLam+dmsxiZZ0o1dqGzdfbS/Da8v1qadPtwqbP3j2No7sA0vYW24y/H0NFN6easRC1/8v8HtMMXjsxCViIj0Kn2kMnhNTQ11dXVxn/GTFel76aWXOt1/ynMztt9+e6655hq23HLLhM+/8sorTJs2jfvvv7/TQSSy7bbbpqUAYK6zDS9hF59B3MJg6V2cUeD+RHr+ajjgXwvjlHe9i6ZPaf93KQpNsxI+Y62F2inYmpuAsBcPLphSbNHpGN8gwA95G2Ockq7HmEHGKYLy+6BxOrb+CXDng7McpuAAyNsirqq6dSuhbhq2/lFvFMkZhCk4EPIP1qiHiIgs80pLSykoKCAajeK6Lnl5eYRCiTekOfzww/nzzz871X/KicaPP/6YNMkA2HXXXTnttNM6dfG+zkZ+jCUZiRYGS+/gB/dn0vfzc9OwfiKV0ZAk1cBrb/a2T24VD+AtbK++pNWrzMPmH4Qp+Wf6a4CkgTF+CO2ICe2YtI2N/oFddAhEf6fldUZ/wlZfA3WPQP9p3Uv4REREctygQYOYO3duy9eNjY1Jd3BNNtLRnpQTjcLCwnafz8auU72JjfyArXsUoj8DPnD6QdM3pDxvX3KQofsL9B28n7+3gNkUn4cJ7dC9LkPbQ+1skhcX9EHor22OWrcaW/OfFC8Shvr7sO6vUDYlq/V0uspWngPRubT9PlmI/oKtvADT76ZshCYiIllmbIYL9uXIR7+l///d3m6uXfl/fcqJRigUorq6muLi4oTPNzU1JV3D0Ve5bhNEF0DdXVB/Jx3vhiO9hjMKAqtD48t0bcqbD/K2BN9AsHXgWxFTcADGt1xcK+tWebtQ1T0Sm9rT35sCVDAW45Ql7NkUjMXW3oM39Wnp3zcD+DEFY9ue2Phq7JxUWWic7hUmDLbdtSKX2chsCL/TTosoNL6Kjc7D+LJbL0hERKQn1dbWcuGFF7Z83b9/f04//fTMjmjss88+TJo0ifPPPz/h8w888ACbbbZZpwNYFrk1t0DNf4D6pZ5RkrGsMMUnYhteJ/moQbtng28Ypuyadgvm2ej82NSeX5dcx/0NW3MD1D8C5dPafAi21vX6L7kcqs4HGlnyexerBl52c5uExut7MS1rMlLmw9Y/hulliQZN/02hkYWmz0GJhohI39NHtrdNxBhDKBRqSSy6U7Mu5UTjn//8J5tvvjl5eXmMGzeOvDxvXra1lilTpnDRRRfx+uuvdzmQ3s7aBmz9S1B1MVDTYXvpzRxve1jfULwP5p0c0QjtCwUHYWtuwUZ/A6cMk78nBDaJG5a0VedD9DfafvB3IToPWzkByv4P6h7DNrwC7lxwq2hJcJ2BENgcXAvGYIKbQv5+gB/rLgJTFrcwGt/yCa7VkWhs+lFvk+pUTxX2ExGRvqWgoIBzzz23zfGMTp0qKSlh+vTpHHfccVxxxRWsu+66RKNRvv32W/r378/jjz/OWmut1ekAejvXjULtFKi7zZsCI32AC7YKU3ACtu7OTp47wBuhWHQQ3oddF3Cw9Q95U6nKbsI4BdjIr17BxqS3PKIQfgc7fwewtYnbufO9qU2h3TGl/weNr2MrjoOmz7znnUHYgsMg+FeM8WPztgJT5tXxSJmvd97xzxtNx6M3eZC3YQ8FJCIiOaUPj2ikU6du1/l8Pv72t7+x3377EQqFcF2XlVZaiY033rhXLgbtKusuwtbeBQ3Pxu4495Hflh6TT9tpZznGrcAEVsXmHwb17dekiLcAmpqL8UXj/w2/h606D1N2HUS+JLXifkmSjNYansMSgobHiCud4/4JNddCzbVeD05/CG4FDc81d57C64li8vdNoV1uMb6B2NDe0PAUiZMNB/IPxDilPR2aiIhIj2lv3cWHH37I7rvvjjEGay0VFRWd7j/lRGPmzJnsttturLzyylRXVxMMBpk+fTolJbm5l36m2Ma3sBUn4c19l8zI8SQDIPwFAKbkfPANxtbe7m0B6x2la8mnCw3PY6PjSX1qTyrXcWJJRuwaSS+/0Esy/Bt6ryX6fcf95m3mjcT0QqbkX1j3dwh/gPf9ji75N28rTMk52Q1QRESypq/sOvX5558nfW7DDTfkiy++6Fb/KScaEyZM4Oabb2bMmDEAXHHFFVx++eVcddVV3QqgN7GRn7AVJ9K5nXk6Q7tS9RrG29bWGAeKjscWHAy1d0JkLoRfjo00dI2tugqcMjq/MDuZzvRhIfIxlN6E8Y8AtwJrAlAzydtdqoUPQvtgSi+MX+fRixinAPrdBY1vYusfB/ePWGG//SFvy177ukRERFI1YMCANseaRzn8fj+DBw/uVv8pJxrfffddS5IBMG7cODbbbLO+lWjU3Uf36ya0e4UM9i3p4wP/2i1f2brHofrSWHLR3eTAQuNLeG/NbP0++KD+QUz5VMBLfym/29sStum/Xmx5m2F8/bMUX/oY44PQdpjQdtkORUREcok13iOT/eeoTz/9NG19pZxoLF2Qr6CggJqaPra7UsOrpOcOs/RuUUzhYdjoPGz9k946hxbp+P2wQLKaNLGpPb4VITqb1JORzoyWRSHyY9se/KPAPyrFPkRERKQ3WmGFFdLWV8qJxuLFi7n66qs7PHb22WenJ7KcpIKEfVtstCJvJ2z1ZIh+24PXNuBfF/zDILQbRBdB9cV4I2ztJRA+IAh0ckc0J3FhThERkT5Bu06lRcqJxt57783XX3/d7rFlfuepwDrQOIOuVYKW3s8HzmBvDUaPs5iCA4EwtnJ8bCvl9kYpYs85g6HsJqg8A6JzSO1312Dy90pT3CIiItJXpZxo3HlnZ+sFLHtMweHYxhSLEjoDIG8XaJoRq+ycidTVAf86EFgD6p+m03etpZOavKJ43eYAFkwh2Bogj443GHCwjW9B44utji31O2WKwDfSK7znLI8JbgLBbTHGhy2/G7voWIh+x5IdlhLxgdMP8sckeV5ERJYlc779jT9+XkBJ/yJW2XDFZf+mcYr6yq5Tmaayt51ggltiC/8OtbclbxTYHIrH4+St483hn9+ZGgudZSHyNRT+3avOHH6TPjMW12v5IPAXyNsA4x+ODaznHVuwLe3/7FxofLP9rk0Bpv8j3gLnpZ/yDYUBz0D4bWzjG+BWQOOHYOd718cAEfANw/S7BeOUde3liYhIr/DtzO+56fQ7+Pr971qOLbfyEP5+1WFste/oLEYmyxIlGp1kisZDYD2vYF/TJ3h3pvtD3kaYolMxgVWXNLaZ2ga35QJAGCpPyfB1JH2i0PQGNL0RSyscb81F3pax7WMTjTQ4YEo6rtjt/gnhjyCY+H8QxjgQ3BoT3BqIbV8XfhcbnglYTN6mkLf5Mrmtq+u6vHbfWzxx4/P8+N+f8Qf8bL7XRow5cy9W23ilbIcnItKjvv3oB87c5kIiTfH/z/n9h3lcvP+/mXDfaWw/9i9Zii5HaI1GWijR6CRjDIR2woR2atlnOOkwo28ImNJWhdw67D32b2/57fMBBUB1tgPpxbwiffhXiyUTVcQnG473KDig/ZG0Zjb1qp3GGAhuiQn2zoJ7qXJdlysPv5Hp097GOAbrWqJNUd569H3efOR9zn1gHNscsHm2wxQR6TFTzryLSFMUN7rUTomxjx+TT53KVvtvRl4w0PPByTJl2bt12YOMMe3OZTQmDwrGkvq3OdPpc3c4S/1r8LZyVZLRfa43Ba7oFAjtwZL833gVqsunYYLbpNaVb7lMBdlrvXTndKZPexsA6y55f0UjbiwJuYGKP1O9GSAi0rv9/sM8vnj7m7ZJRivVFbV88OzHPRhVDrJL1mlk4pGzH/fSTIlGhpmiEyGwAd4H89ZJSS/51vs3wZT+G/K2gcBG4G+eGtaH3iU9woHG6Thl12AGzcQMeBUz6AOc8tsxeetBYGNwliP+d2ip830reZsDSJwnbnge4yT5vlmIRqK8dEeKmzyIiPRy8+cs7LCN43P44+f5PRCNLOt6yafd3suYEKb8LkzxueAbDhgwBd62oznPgH8Ytv4FaJoJTbMg8k22g1pGueD+AYBxCjH+4XELso1xMKWX0jZhhebpVabkIu0WspRoNMrsz3+JG8low8L/Pv6h54ISEcmikgEd10lyoy6lA0t6IJocZnvg0Qco0egBxgQxhUfiDHwFM/gbnMGzwO34jkL2WWh4HMKvxbZhVf2QzHHAGdp+k7wtoGxqq1GlGP+amPK7MUkWgfdlxhgcX/t/5oxj8OdpuZqI9A0j1xrGiLWGtXtjKpifxxZ7b9KDUcmySolGD1vyxlaVcWnNxRQc0OaotS627lHcBXti/1gDFh/rjYaVTMT0uwsz4HmcAY9j8vQ/hEQcx2HjnddrN9lwoy6b7rphD0YlIpI9xhj+ftVhsS8StznsgjEUlhT0XFCyzFKikTX52Q6gj8ulKUYOBDaB4F/jjlrrYivPxladC5H/xY5GIfwOVJ0L0TkY/8o9H24vc+A/9sZ1Ey96dHwOA1boz9ZjNuvhqEREsmf0bhtywSNnUTrAmx7VfBM0WBDk2CsP46B/7pPF6HKEpk6lheYLZEtoN2h4tAcv6ODtEiWedL7DA6Q8QuVbBaI/sORn4YfQPpiS8zFmqbdjwzPQ8HTsi9bxelPYbNW/IG9LjH+FrofeB6y3zVqceesJXH/8LWAMbtRt2ea23+BSrnr5AvJCedkOU0SkR/1lv9FsvudGfPTSZ/zx83xK+hez2R4bkl+kG6GSPko0sqXkXGh4EajpYgc+Ul8zEYT+z0PDk17NhuiP9JlUuicUnw/V/0qtbfQ7KDob4x8OOJC3IcYpT9jU1t5D+wmiwdY/hCk+qwtB9y27HvNXNtpxXZ679VW+/3Q2gVCAzfbYmO0O3oJgfjDb4YmIZIU/4GezPTbKdhg5qWUb2gz23xco0cgSxynCHfgKLDoSov+Lf9K/HpgyaHqbpJWiQ/uCO6+datKt+xsOC3fy2vlWguKzIbA5LBoDRNLxcvoo4y3gbnihc6fV3QsDp3dcgTvyDe2PQkWh6cuULmkjv0DTR15+mbcRxj8i1WiXGYOGD+Toyw7JdhgiIiJ9hhKNLHJ8/WHgs7jRudDwGl4CsROObwDWrcAuOgIi3+KtJ7C03N0OrIcpOQ9sFXbhQeD+ScIPpKYQbC1EfqQlGYn+CNVXx9YDKMnoHgvu796jM9y53s81sEb77UwAbHtTsgyY9u/GW7cCW3kONL5B61Esm7c1puzqpKMpIiIiIt2lxeA5wPENxSk8DKdwLI5vAADG6Yfp/wim5HKv4J9vBQhsjCn9N6b8Xq/Wgm8oZsCTUPh3MP1ivRVBcEcovhxsQ+xY6xGP2Aqkxtd67gVKWy0/m3YE/4o3RS5pJ5jg9smftQ3YRYdD45u0mSoXfge76DCsrU8lWhEREZFO04hGDjMmBAUHJNz2tKWNU+7N0S8+C2vdluk4tuY/2A7XYYSAFD7wSpr5IIWpS6bwb9iG51gyorVUH0455O+RvIP6Z1rtVrW0KES+h/qnoODgFOMWERHpIzK9M1QfWaOhEY1lSOs5/7bpK9r/LbYoycgGH4R2SWnKkgmshSmbhHc/oLkieOxn7AzwivSZ5LuD2PrHaH8bX4Ot78mdz3KbtZYPX/iU8/a4gjGD/sYhw47nxlNuZ863v2U7NBERkV5JIxq9gHUroG6a96HQrQBnCKbgIMg/EOMkKahj8kh8J3zpdgPBzk93yJKQD5zBmOIJKZ9hQjvDoLeg7lFs0+dgApjg1hDaFdPB+gzcBXSYbEbmYG2k7da6fYy1lpvPvIsnJj2P43Nwo96ap2dvfYXnb3+Ni584m0133SDLUYqISE/RrlPp0bc/XfQCNvobduEh8Qu+oz9iqydC/aNQfj/GKW1zngluj214NoULKMnoEaYQ8sdgCk/A+PrHPWUj32Prn4DofPANxOTvG1eIzzjlUHRc50sMOkMh+ivt7lxlK7AL9oDyuzC+IZ29wjLjzUff54lJzwO0JBkAbsTFGsslY/7NA79MoaR/cbZCFBER6XU0dSrH2cXjwZ1P/IfF2MTByA/YqksTnxjaCUyS0Q7peeWP4JScF5dkWBvFrbwQu2A3qL3DK9BXewd2wW64ledjbap1UhIzBQeRUpHG6M/YimOxtu8WdHzs+mdxnMSpnLWWcGMTL931Rs8GJSIi2aWq4N2mRCOH2aZvoeljktfJiELDc9jowjbPGJMHeVtlND5JnYm0rXdha26E+gdjX0VbPYD6h7E1kzp1DWstNvKrN0Li1kFoZwhsRMdv86i3aDz8Tqeut6yw1vLNB9/huu385beWr977tueCEhERWQYo0chlTbNSaBSFyFcJnzHBbdMZjXTLkm1qbfQP3PAsbxSjPbV3Yd3UKsfbhhewC/fALtgeu2A37J+bYasuh9JrIbRPCj34sY3TU7rWssiYDiamGYNJMuIhIiLLoEyOZvShUQ0lGjmtvRoKKbTL392rMK4fc5b5IG80NjwTd+Eh2Pl/gUUH0vGuXw0Qfr/D3m3tPdjFp3vb1bY+t/4hqDgKik5ILUwbTq3dMsYYw/rbrYXjS/4+sdaywfbr9GBUIiIivZ8+geay4Oa0vz0pQD4E1kv4jDH5mH63gslHP+osCu0NTV94xfOaPu3cuR0U9rPR+djqK5q/WurZKER/gbqHwRnUwYWimMCanYttGXLA+L3jFoG35jgOxf2K2OGwv/RwVCIiki3Nu05l8tEX6NNnDjO+5SG4M8l/TAYKD8U4hcn7yFsfM+AFKDyR1EdIJG1MIRRPwFZNwEsEOrng2r9q+8/XP95BB1Gofxjyx5I8aTVACEJ7dS62ZcjGO63H8f8+AgCff8n7zTiG/JIQE184j/yi5DVLREREpC1tb5vjTOkV2Io/YnfCfXiLhWP/Bv+KKRrXcR++IZji03HDH0LTzMwGLPGc5SD8BriLOnmiDwLrYALtJxo2+hMdjnrZKigYA00ftJqK1XwrxQcYTNl1GKeokzEuW8acuScb7bguz9z8Mt98+D15+QE233MTdvnbdpQOKMl2eCIi0pNUGTwtlGjkOOMUQfn90DgdW/+kt9Wtb3lM/hjI26LjRayt+wrtjO1WopFCAUCJF/0BqifhjUqlOprhA1OEKb2y46amGEtHqYaDcUqg321Q9yC27l6I/gwEILQTpvBYTGCtFGNbto1aZwSn/efv2Q5DRERkmaBEoxcwxg+hHTGhHbvXUf6+UDMZbCWpJQwGCILTH9y5eHe/m7oXQ5/jgvtrJ9oHIX9fTNHx3tS5dlhrefXhAnbYo716Gz4IbgdutbdlbsPrYEKQfxDkj8XJW6MTsYmIiIikTolGH2KcYii/C7voaLAVLBmhcLz/ztsKmj4CWwuEwDcUorNjSYZLp9cXSIwP73uXLLkz4AyH/o9gnCIvsUzBUze9yE2nvU2/B4pYf6safEudZm1s29bgNtgFO8YWlsd+hpHvof4hbPG5mMKjuvayREREllGZXrCtxeCyTDKBNTEDX8OUXAzB7SFvG0zRKZiBb+CU3wblD0PeNkCDl2QASjC6ywXfcJJPcLKY4jNwfGUpJxlN4SbuuehhwHDp30fy4WveGoJoBJpiu9TWVPpoCl0J1VfFJxleS+/K1VdgG9/ryosSERERaZdGNPog4xRBwSGYgkPijtumb2DRwWAbsxTZssqBYGxEof5+vITDwfuwn4cpOR+Tv1ubsxbOrWDGQ+9S8WclA1foz7YHb0FJeTEA/53xFdWLvGJ+9bU+Ljp6FCNWbWCLXSoJ5rv89G2Id54vZfKMzxg5opbkoyk+bO0dmODmGXjdIiIivZQWg6eFEg1pYasuSnDnW7ovCs4Ab4pS0d+h4XmsuxjjWwFCu7fZ7cl1Xe48bxoP//tprLU4Pgc34nLzmXdxzBVjGXPmntRW1rW5ys//C/Hz/0Jxxwrz/9txbGGNaIiIiOS6+vp6Tj/9dF566SWi0Shjx47lqquuSroxUG1tLSNHjuSss87inHPO6eFoPUo0BAAb+RGaPsl2GMuumiuxka8wpVdjCo9pd5eo+y99jAeverLl66jrTXOKhCPcMv4eCkoKWG2TlVK6bH5RHh3fNukjt1VERERSlYMjGmeddRau6/LDDz9QW1vLDjvswOTJkzn11FMTtr/pppuoqKjoZqDdozUa4on8nO0Iln0NT0P9I+02qa2q48Grnmi3zV0XPsjItYaxyoYr4vgSv4UdxzBs9eUoGvQX2n+b+yBvww4CFxERkWyqqanh7rvv5uqrr8bv91NaWsqECRO44447Erb//fffmTp1KnvvvXcPRxpPIxricVSQLPMMtvZuTMFBSVvMfOFTwg3tbyFcMW8xX733P8bdchxnbvMvmhqbcKNLprs5Pgef32H81JMw+QOwNTcBYRLfPokSNmN57vpneeWeGTTWhVl5g5EcduEBjFhjhZRelbWWz974kmenvMyP//2Z/OJ8tj1wC3b+23Yta0pERER6k57adaqqqirueDAYJBgMtmn/8ccfM2rUKMrLy1uOjR49mi+++IJoNIrP54trP27cOM4991ymT5+e/uA7QSMa4gmsD86gbEexjLMQ/R5rw0lbJFp7kUhdVR2rbrQSN753OZvuusGS+ZkGNtxhXa5/+zLW3Hw1jK8/puwGvHsKrf8Ief9dWTeWA4bfz5Qz7+aHWT/x6/9+542H3uXYtc7g5jPv6vgVWcvkU6fyj79ezNtPfMCcb3/nfx/9wG3n3Mff1hjHz1/NSen1iIiI9EXDhg2jtLS05TFx4sSE7ebOncvgwYPjjg0aNIhIJEJlZWXc8QceeICFCxdyxBFHZCzuVGlEQwAwxgdFZ2CrJmQ7lGVc845TiS2/ytCUellu5SGAV8n60qfPYfH8Sir+qKRsUCn9BpXGXzG0HQx4Flt3HzS8CjRBYH2i/oM5ctXbaKhNvMvY49c/xwqrDmXPE3ZOGscLt7/G0/95CYBoZMmoinUt1YtqOG/3idz93Y34/L5kXYiIiOSeHlqjMWfOHEpKlswqSTSaARCJRLA2PqBo1FvD2Xox+OzZsznvvPN48803ky4S70ka0ZAWpmB/TPH5QF7siH490ssHeZu3Wytj3W3WZMioQRgn8R8Hx+ew1parMWy1+KrhZQNLGbX2cPoNKqVqYTVvPfY+r097m1//9zsAxj8Kp+QCnEEzcAa9i9PvPzx7Vw31NQ3tRnzXhQ8lfc5ayyP/93TS8iBu1OWPn+fz/rMft3sNERGRvqqkpCTukSzRKC8vZ8GCBXHH5s+fTygUorTUu8FYX1/Pfvvtx1VXXcWwYcMyHnsqNKIh8fwjgXyWzOlvrh7uo7nIm3Sk+Xu2tCim8Nh2z3Qch/F3nMQ5O12Ka2ybtRfBgjxO/8/fE54bbmzilrPu5vnbXiXStORntd52a3H2nSczaPjAuPav3D2jw1dStaCaxfMrKRtY2ua5xX9W8uv/5rZ7vi/gY9b0L9hyn007vJaIiEjOyLFdpzbccEO+/fZbKioq6NevHwDvvvsuo0ePxnG8G8OvvfYa33zzDccddxzHHXccAHV1dfh8Pl577TVeeeWVtL6EVOiWtbSw4VnYiuOB5oVJrd9lSjJSUnINOANiXzTf6vcBBlN8Pia4VYddrLfNWlz31qWst+1aLceMMWy2x0bc+P5ERq0zos051louP+Q6npnyclySAfDFW19z+pbns3h+/BzOZFOmlvbh84m3PV56CDepLO2e67ouMx5+l7O2+xf7D/wbh448kdvOvpc/f5mfnYBERES6aMiQIeyyyy6ce+65RCIRFixYwOWXX864ceNa2uyxxx7U19ezePHilsfYsWP517/+lZUkAzSi0afZpu+wdXfF5u1H8PJOF9VV6AanH2bAK9DwDLbhNaAB/GthCg4G33A+ff1zPn3tc9yoy1pbrs6mu23QZqcIgNU3XYWrX7mQRfMqqFxQTfmQMkoHJN8Z7PO3vubdJ2cmfC4acVk0bzFPTHqeoy9bUg1+hdWWY863v3X4kiadeBurj16V4avHT9fqN7iMIaMGMe+nP5P+ykSboqz9lzU6vEa6RaNRJh46iRkPv+cVPIy6VC2s5tHrnuWZW17mqpcvZI3Rq/R4XCIi0jv01K5TnTF16lSOOeYYhg4dSmFhIePHj2efffbhvvvuY+bMmUyaNCn9gXaTsSnfluwZna162FpVVRWlpaVUVlbGLayRtmzDa9jFp+J9QtRoRdoERuP0v7fN4Xk//ckFe13JT1/M8RZGG+9D+KDhA7jkqX+y0noju3XZ/zvmP7xy74y4BdlL6ze4lIfn3t7y9c9f/8qxa53RYd8+v8MuR2/PuFuOb/Pck5Nf4KbTEu/h7fgcygaVcv9P/8Ef6Nl7Go9d9yxTxt+dMAFyHIeS/kXc/8sU8oKBjMVQX1PPq/e9xcwXPqUp3MRqG6/MbsftwKBhAzo+WURkGZbLn9eaY1v9tCvwBUMZu060sYFvbjg3J78H6ZRzU6daVz388ssvmT59OpMnT852WMsUG12IXTwOL8FQkpFWkS9pbKimKdyE67p8/tbXPH/7q5y62bn8/PWvAEQjUaKx6U0LflvEP7a/iIVzu1e5c+G8xe0mGQCL58fv1T1ijRXY/pCOp3JFIy7TH3on4XN7nbQzOxy+NUBc8UDHcSgozufyZyf0eJLhui6PT3ou6SiL67osnl/F249/kLEYfvzvzxy+0inccPJtvP/sx3z00mdMu/IJjljpZF65p+O1MSIikmW2Bx59QE4lGp2teihdVP8Y0ESf+S3vIdaCG60h/Msm/PHJBsx6YmPevv9Ebj/7Jhb/WYmNtv1+u1GX2qp6noltEZu8b8vPX83h249+oLqips3z/Yf2w+dv/+1cttS2twDn3HcaQ0Z1XD8l2XoOx3E4+65TuOSpf7LRjusyYPlyhq2+PIeevz9Tv7qOlTcY1WHf6bb4z0r+/GVBu218AR9fvvNNRq5fX1PPP3e8hOpFNWCXrGVxoy7RiMs1R9/EV+99m5Fri4iI5JKcWqPR2aqHjY2NNDYu+QC0dHVFScw2zUJJRmY4DhQUuxSWhBk6Isy6m9dw6JnzOG/sinzzSWHCc9yoy+vT3uaoSw9O+Pwr987g3osfYe6PfwDgD/jY7pCt+PvVh7fUzNj5qG158Y7Xk8flc9jt2L+2OW6MYcu9N+GJG1+I2+Fq6TbNdTuSPb/5nhuz+Z4bJ23Tk1qPrKSjXWe9dv/bLF5QlfQt5vgMj177LBc+slpGri8iIt2Xi2s0eqOcGtHoTNVDgIkTJ8ZVU8yVPYNzX0792JcZLcW5W/3rOJBf6HL5/T9SVBpJem5dVeKK4A9f8xRXHzm5JckAiDRFef2Btzht83Op+HMxlQuqWHH9kfxl/9EJ62/4/A79l+vHvqftlvAaux23Y9Iko9neJ+3S7vO5pHRACcPXWL7ddV3Rpigb7rBuRq4/88VPMcmKi+BNRUu2k5eIiMiyJKc+caZa9bDZhAkTqKysbHnMmTOnR+LszWz9MxD+EI1odE1T2PDOCyU8cfsAXn+8jLqaxG+hSBP88WuAxQv8+HzeKMeOByZeh+E4hhWWKsAHsOC3hUydcH/Cc6IRlz9+ms9ho05mzKBj2LvkCKoWVrPVvpsSCMYPVK6/3dpMeudyGusaefCqJ5ly1t08dt2zVPyxGIDhqy/PERcdCLR9nxnHsM7Wa7DbcTu0+33JJcYYDjp7n6Tb7zo+h+VWGsymu22Qkes3hdv+HVtaJKK1USIiOU1rNNIip6ZOpVL1sLVgMJi0gqK0ZWvvw1Zf0okzHPCvCaF9oebSjMWV6+rrIJQPM54qY/K5y1O92I9xLNY1BPNdDh8/jzEnzMcYaKhzeGDSIJ67pz81ld7ba5V16zjktD/YZLsqnrhtYJv+Xdey14k7tTn+8t0zYsMjif8aWWsJ14dbvv78rW/+v737jnOi2gI4/ptJtvdCXXpv0qv0IiAKUlWqioKKT7GiNBERKVawo2ABFUTpXXrvvffel+09mXl/hF2Im+xml2QLnO/nk897O7lz5yRk1zm599yLrum89u0AggsHkpJsonzt0hQuXZAf3v6NuZOWoKgKqqpgNmv8+O50+n3wFD2HdqHv+z0oWrYwf46bw7nDlqJ1/xA/Or7cll7Dujq8OpOu65zYfZorp6/jF+xL9WaVc7wYHOCRfs05d+gCf326AINRxWzSUBTLOxlUKICxS4bbXFbYGSrVK8euFfvsjhKpqkKF2mVccm0hhBAiL8lTiYYjux6K7NG1KPSY8Vk8S0PxfRHFsx2a20MQ+wmk7MKy18aD4+fxRShfLYFPXy9J6k2/rlm++U9KUPlpTFEUBR7vd5Mh3ctwYr83mnZnZODkQS8+fKE0nfrb2ChOgVotq9GkW4N0T105ddWhZZ1Tpd7YfjN4GrMuTcE/xM8S/4g/01Zh0s062u0v082azs8j/sQ30IdOg9rRundTWvVqQvjlW6QkmyhQLCRLScLBTUeZ9PIUzh68M7IYUMCf/h/1pMOAnB0RURSFARP70qRbQxZ9v4LT+8/h7e9Fs+6NeKRfc7z9vFx27Q4DWvPHx//YfV7TdDrbmcYmhBBC3E/y1N27I7seimxKWIhlpSlH3P6m1+cF8LB806561EQN+R218FHwfPxOmwdAvRYx/P5lYRRFBztz73+dWJhZXxfk+H+SDLiTlCz82Xr/BNUA6LBn9UF6lXiZ6R/OJjnpzr+Rb5BvtuI1m8xpS6jGRcUx+/OFGQ7R/vDObyQlWBZVUBSF0LAQipQulKUk4+j2E7zTenTaaEiqqBvRfPHiD8z7amnWX4gTVG5Qnnd+foXvdk3kszWjeeKV9i5NMgBCw0J45+f/oaiK1Upg6u36mUdfaE3Lpxu7NAYhhBD3SKZOOUWeSjTAsuvh5cuXKVKkCHXr1mXgwIF07tw5t8PK93TzJRxLDgLAvSlK0DRUvyG2v1E3X+N+3X8jOUlh/KDizPkxlJhIy/sVEGLmylkPdN3+6EJyosqCn0PRMxjsSZ22X+PhGMvP2p2/MlE3opn+4WxGdhyHKcVSNN7i6caYszGXX1UVzh6yjCpsX7qXlMSME8zkhGQmPnNve9VMeWc6mlmzek13+2no78THJNzTNfKT1r2bMnnzWJp0a4injwdGdyMVG5Rn+J+v88YPL2ZppEoIIYTIr/LU1CmA0NBQ5s+fn9th3HcUNRDdgSlPSsHlKGpwuuO6boLEpejxf0LKAVeEmOt0HVSDTkS4gavn3Nm6wp8GbaKIiXAkQdPTajLsUqB05Xj2bfa7fb3/jnzo7F51gGXT1vD4i49QsW5ZGnWsy7bFu9Ds3MDbu5Cnt6V2KcHBm/uNc7YTeSOKwALpa6Eyc/XsdQ5sOJJhm6T4JDbN3c4j/Zpnuf/8qlL98oz4M/Od14UQQuQ9CvbmMDiv/wdBnhvREC7i2YGMx+lUcH/YTpKRjB7xEnrUW5CyG7C9eVt+pyhgNML4mWd5ecxlWnePwDdQo0CYI1PO7BdtpzIYoEL1BFp2tr8LuILCgu+Wpf087M/Xafbkww6+AguzyUzjLvUBKFaxqEPnaJrG1oW7snSdVLcc2NXcYFS5eelWtvoXQgghRP4kicYDQjEWB6+nsZ1DK4CK4jvY5rl67DeQvOH2T/m3EDyTFUetpO6BoapQonwSFWvFoap2OlD0DOs3UplNCk07RjLk6/PUbhZjJ0adi8evpP3s6e1B22daOBy3alSpVL8cNVpUBeChppUJCUufPKY7z6ASH51+9CMhNoGti3ax7q/NnDty0caZEFQoMNP+zWaNoMKZtxNCCCHyBKnRcApJNB4giv9I8O6LpVbDklwAoIagBP2A4p5+XwFdT4b438nvvxGaBglxjn3cbU2ff2XsJQxuerpkQ1F0y2pOGdRvgGVKVokKifj4m0mIU+n79lW7bb18rJdsnv3pgkx3sU4tNK5QuwxjFr6XVgOgKAr/m9w/w3PBsmJVWIUiaT+bzWamDJlO90IvMLLTeD56+gteqPoGbzQbycXjl63OLVKmEJUbVUiLwRZ3Dzeadq2faRxCCCGEuH9IovEAURQjqv8IlAIbUPw/RPF7ByXwe5QC61E8mto+yXQa9OicDdQFrl1w58lqVbh6wZilkY1UFWsm8Nnck1Ssbb2Dd+GSyRjdNOwnYpbjCnD+uCdvdKxAz5pVWbcgkOCC6adkGYwqLZ66syKRpmnsW3Mw0527/UP8mLjyfSZv+ThdnUWTLg2o2rii3XMVVSGkaBB129UA4NyRizxb4TVmf7rAap8OgMNbjvPaw8O5ds56qd6BE/uiqKrNnckBnv3waXwCfDJ8DUIIIUReoeiufzwIJNF4ACmGUBTvp1B8nkfxbIWiZFTEfH+UK+k6pKSoTBpSAl23jHDYapORijUT+HLBSaZtPML4Waf4buUxPvztFKaU1BGi/1B0yxK26JjNd55PSlBZMC2U2GjrInNVVTC6u9H19cf+E1fmf40ib0Sz9KdVdtu+8/Mr+AX7ohqs41QNKqqqMuSX/2EwGDi59wyD6g7h6pnrNvvRzBpx0fHMHD/X6ni1xpUYv3wERcoUsjruG+jDK5P60/2tjpm+BiGEEELcXyTReADpeiJ6/Ey08O5o15ujhT+NHv+PZZrUfxnLgI0C8fxE1yHqlhF0hd3r/BjzQimib68kZTbfTkKSFXatc2zfirAyydRqGkuZKokkJ6q8MPIy4/86SdPHI1ANlht9T28zjdtHoZltr1uhaQrJiZYCctVoyXr8Q/yYsGIkYeXuTGFSVZXydcpmOC0p1ZqZm1g7c5PtmMsV4Zsd42nxVGMMxjsJTs2WVfl8/YfUblMdgM+e/47kTJbD1UwaK35bl27p3Zotq/HLscl8sf5DhvzyP8YseI9ZV36k86uPynKuQuSC6+dvMPvTBUwd9gdLflxJXHR85icJISykRsMp8tzytsK1dC0C/VZfMB0nbaUk7Sp6ym6I/wOCf0VR79xwK4obeD+DHvsl+fm3Ys3cwLT/v3lZANtX+VG/dQxFSiYRE2lk20pfWnWNom6L2Cz1W6pSEif2m5jyQRhnjniiGnTqtYqm28vXWfZHKAaD9WiGNcvxomUK0O+DPjTpWh83d7d0rbq9/hjj+kzONBZVVZj/zTJa9bozDc5sNpMYm4injydFShdi6IzBvPbtACKuRuIb5GM1zerk3jOc3HPGodednJBMfEwCfv/ZVFBRFKo1qUy1JpUd6kcI4Xxmk5lvBk9j0ff/Wha2MKiYTGa+ef1nXpnUnw4vtM7tEIUQDwhJNB4wetQwMJ1K/cn6f02H0KNHowR+Yn2Sz0BIOQZJS3IqTOfTb0+IvF20bUpR2bzMupaheiPrJCMuWuXobstO3+WrJxAYarJ6XtPgk1dLsHZ+IIpqKQg3mxR2r/Nn5xp/ChVPziDJuOPiiZtUbljeZpIB0LJnEw5tPsaCb5dn2I+m6Zw5cB6AW1cjmDl+HsumrSYhNhE3DyOtejbh6aFdKVa+CD7+3unOv3D0crpj9rh7ubt8h20hRPb88PZvLPp+BbrO7amiltHH5IRkvhj4Pb6B3jTr3iiXoxQiH8i/36/mGTJ16gGimy5C0mrs7+qtQeIidPPN/xxXQHF3cXSuoyjw8pgrfPzH6XTJBFhWhCpYLJkGbSxF78lJCt+9X5Sna1RlWK+yjOhThp61qjDh1eLERt35lfn3ryDWzg8EFHTtTkJhNivoOlw9744jf6UUFLYt3p1B/Ar/++p5ytYslWlf7p7uXD9/g0F132X+N8tIiE0EICXJxMoZ6xlUdwgn99oetfDy9cy0f7CMnDzSt7nVFCwhRN5w62oE879ZZrfmTFHg55EzHar9EkKIeyWJxoMkZTeZ3/ia0eN/sT6UuAQS57kmphyiKFC7aSyf/HOK7i+nFjrrKKqOX6CJj2acwmC0jFJ8+Hwp5k8LJTnpzq+HZlZYOy+It7uVIzHeklTM+6kAit3fIOU//5tBbKqSbnWn9PErPDbwkQy7MxhVmnZrwFf/m0rk9ah0K1WZTRpJ8cmM7zPZ5k1GzVbV8PLLPNnwDvDm6fc6Z9pOCJHzNs3bga7Z/zuv63Dx2GXOHba9L44QwkJWnXIOSTTyOV3X0ZO3o0V9gBb5JlrMJMvIhU0OFuTGTUFPvDNNR4+fQU5+VMKvq8REOv96qUnBgJFX+HLRcT6fd5Iv5p9k6oajlKxgudHfsdqPHav9rUYoUmlmhTNHPFkxKxhdhzNHPG22u+uKDsWlmTWHRiva9GlKSJEgm3tqKIqCalBp/uTDbF28C7PJ9nK4mlnj3OGLHN5yPN1znt4e9Hyva4YxFCgeyqRNYylcqmCm8Qohcl5cVHy61eXstRNCCFeTRCMf07VY9Fv90G/1gYRZlpGHuO/Rb7ZGj/0u/QnudXD05lePHouu355iZTpCTu0IrutweLsfvv6uu56uQ6VaCVSpF0/lOvH4Bd651vI/g9NWjrJn8fQQAAzGe/86QjWoFC5dkJqtqmXa1svXi09WjSL09k7fBqMBg1EFBTx9PRmz4D1SklIcmlOaWsvxX0+/15mn3+2MoloSF4Px9t4YCrTv35Lfz35LiUphWXqNQoicE1a+iN0vGlIpikKRMvJlgRAZklWnnEKKwfMxPepNSNl5+yfrugs99gswFELxuvMNtWIoiu7xCCStJNPEQbsKyTvAoyHgBiQ4M3S7dA3qtY526fYdGa20qgMBwSaaPh6Ff7CJaxfc2bAogMT42/UIusL5E57ERCrUaxXN9pUBDhV822Iwqrh5uDFi5huoqu2cPyU5hU1zt3Nk6wlUg0qdtjX4+dgktizYxc7lezGbzVRuUIHWvZvi7efFvnWHHLq2h5ftmhtFUXh+XG86vdKeVb9v4NaVCIKLBNG6d1MKFAvJ1usUQuScho/XJiDUj+jwGJt1GqpBpcFjtQkuHJTzwQkhHjiKfh9VhEVHRxMQEEBUVBT+/v65HY5L6Skn0MMfy6CFAobiKKH/Wu1hoGtR6Dc7g3Yp02soAZ+geD2BFjn0do2GvSJy59HM3N7kLvekbuanmcFghMR4le/eL8ryP1NvtHVqNI7FlAyHd/re/o951pINNw83WvVqwtPvdqZYhaI22xzeepxRnScSeT0Ko5sBXbcsW1michhjFw+zOX0pOSmFp4sOICYizu61DUaVPy9OIahggN02Qoj8a+uiXYzqMhF0He2ueg2DUcUnwIevtn5M0bKFczFC8aDLy/drqbE99MLHGNwdWyQlO8zJiRz4aViefA+cSaZO5VdJq8n4n08H83kwn7U6qqgBEPCRY9dQC1jO8XmWHNsh/B4uoztptpWqWh5GN8voh6e3xpufXaTp45G3Wyjs2+RHk8ejeXvSBQxGUFXHxkGN7kb+vPgDi+Jm8PbUQXaTjKtnr/Ne2zFEh8cAYEoxp22Qd+nEFd5u9QGJ8UnpznP3cOPp97rYvb6iKnQY0EaSDCHuYw0fr8PEle9T5eGKaccMRpUm3Rry9fZxkmQIIXKMTJ3Kp3Q9EUuikcndtZ7+ZlRxb4iuFgHtiv3z1ILg3sDS3q0iuvczED81+wE7wGyGpASV2EiV0KIm7MwmAkhbH15RLA9dJ4MVoO5Nav9vfHaBy+fcuHnZnahwI/5BJtp0j6RWkxiW/RnMsb3e7FrrhynF9m7gqlGlVc8mBBcOZM+qA5zefx4PL3caPl6bgiUKWLWdN3kJSQnJ6VaOAsvqUdfO3mDtzE20798q3fM93u5ExLUo/v58YVrhuKJYzmvWvREvf/GsU94XIUTeVaN5Vb5YP4abl28RcyuW0LDgdBtsCiGEq0mikU8pbpXQMWXSygMMxdOfqxjAfxh65Kv2+/d7z9IObi+FmngP0TrGbFL44NnSlKyYyKCPMp7alZpgpE5zyqju4uIpd6JuGalSNz7Ddpldz8dP49vlJ9P6jI6w/PqEFDbR+w3LkrnbV/nxwbOl0bFMvUqlGlQKhIXQrEcjnin/KlfPXEdVVXRd4+tXFVr3acrr3w/Ew8sDgDWzNttMMu42bcSf1G1Xg9Aw69oJRVF48dN+PPbiIyz/eQ03Lt4ksEAAbfo0o1yt0tl7A4QQ+VJo0WBCiwbndhhC5D+uLti+bwoXMiaJRn7l0QrUUNBuYXtUwwBeXVFUH5unK57tIHAyevRHoF2/84RaAMVvGIqXpf5D103oUe9C4kLnv4a7aGZYNz+AfZt92b/FhzJVEni09y1MJjAab0+LUqwTitQRjegIFf9ALd2IRkykgYmvFWf7ygACQ1KYvvMIRjc9w5ESR4WVTqZY2WTOHvOgZIWktLjqt47h07mn+X1SVXauTgQdPLw9aPtMC1r2bMzQ9mMtK0MBWmqWhM6q3zcQH53A6LlDAEiMzTyxi7gayasNh/H19vGEFElf2FmsfBGe/7jXvb9YIYQQQohskEQjn1IUNwj8Ev1WfyxF2ncXaqtgLI3i92bGfXi2B49HIHmbJdlQC4B7AxTlzsdCj/0GEhe55DVYB3OnCFzXFb58pxjrFwbSoW84pSom4utvJqig9QhOTKSBHav92LjEn2r142nT4xYBwZabd7MJhj5dhlOHvACIDHdjwislGPb9OUyaJXm5p3BvJyulKibx9/ehdHvxZlqyUaVuAmNnFyFBGUV8TCIBBfxx93BjfL/JpCSn2Byp0DWdzfN3cGzHSSrWK0eJymEc23kqw423ACKuRfLjkOk8M/opQosF4+budm8vTAghhBAu31RPNuwTeZ7iXh8lZA54PkZazqgGg8/LKMGzLIXfmfWhGFA8Hkbx6ozi0dg6ydATIf5XcmJ8T1GgULFkjG4aiqJjMOrs2eDL+EEl2Lw0gMACd5IMswmmfFiEp6pXYeKrJdm8NIgpo8PoWbMqnwwuzq3rRjYvD+DEfm+0u5ae3bgkkNceK8/6BYEkxKlWU5uyy5QCBcJS2LHaL+1Y+DWFhb8UYN7Xyzi8+djtdibWzdqMlsH69gajgVW/bwCg06D2mSYZYKm7WPX7BvqV+x9PFRnAzyP+JCkhfV2OEEIIIUROkxGNfE5xq4AS+Cm6PsFS+K14WS1nmx26FglJG9FNR0GPdU6gmVAUqNYgnj/3HGbdwkBuXTMSUthEs46R+AdZZwRfDwtjyYwQ/ltwbTaprJ4TxL5NvpSsmICi6ul27j55wJsJ/ysJQGiRZH7ddsRqdCN1sWdH30KjG5SpnMiU0UWp0zyGH0aHsfCXEHRtB6phF2aTGb8gHwZNeg5TSsaZja7rRN+yrDLVqlcT1v29hW2LdjkWCBATEcfM8XPZv/4wE1aMxN3T9l4ZQgghhMiE1Gg4hYxo3CcUxYCiet9TkqHrJrTocejXG1s2A4yb4sQIHeMfbKbjM+E8M+Qaj/cLT5dkXDzlzpIZodhbB1czK9y47Mb+Lb7pkoz/Cr/qxr9/BZGcZGkXG62yZXnW1rLWNIiPVTl92JPv3g9jwbQQNLOCrutpy9HGRMQx4ZmvcffKfFpT4ZKWvTEMRgMf/PO2QzuGW8ejc2jTMRb98G+WzssNkTeiOLjpKCf3nrmrXkUIIYQQ9wsZ0RBp9KgRkDiXvJZm65qlJsJshlX/BKEoOrqeURKhkJKkWiZAZtBO1xW+fLsEk4cUx8NLIzFeRdcVBo25SMfnwh0uGl+/MBCzGRb+EprBi4DkxBQUVbE7JUrTNNo91zLtZ6Obkf9N7s8L1TKutUl/KZ0F3y6j6+CMNnTMPeFXIvj+rV/Y8PdWzLenkhUoHkKfEd159IXWNpPl+JgEkuKT8A/xw2DM5R0dhRBC3P9kRMMpJNEQAOgpxyFxTm6HYZOiwpTRRdB1hb0bfXFkL/uME5E7PLzMtOgcSaVa8WhmhV3r/Pjxo6J4eGu07xmRtrKV3dgUKFIiifgYB25+dSwrZ9lJNnoP60aRMoWsjpWsUpxWvZqwZuYmh2o2Uq9z+dQ1dF2/52l09hzbeYpTe8/i5mGkbtsaBBUKdOi8iOtRvNZoGOGXb6UlGQA3LoTzxYs/EHEtit4juqUd37fuEH+M/YfdKw8A4Bvow2MD29BzWFd8/L2d+pqEEEII4VySaAgA9MT5gAHr1atyn6bBztV+zP2xAFraVCjHbribPh7BhkWB2JtmVb1RLKOmncHHX8N8u9b88WfCuXLOneG9S7N/ky9Dvr6A2WSp3TDenvl0d/KhKPBon1uUrZbIO93LWkZSMqBrOtWaVuLwluNpheEhRYPoNawbHV9ua/Oct6YOwuhu5N9f11leiq5nmmx5enu4JMk4d+Qi4/tM5uSeM2nHDEaVds+14pVJz2VaFzJz3FxuXrpld4+QX0fN4pFnmlOweCjr/trM2J5foqh3XkdsZByzP1vI9qV7+GLDGEk2hBBCuISsOuUckmgICy08tyNIJy5aZcHPocz4vFBakmEp8M74PNWg81DDWIZ+dx6zSWXzMn/+m2wULZ3ERzNOY3TXUZQ7SQRAgbBkJvx1iuebVuJECy+SE1UCQ01MWmTZrO+/9+8GA1SsFc+jvcNZMM16h+90sRlVqj1ciVF/v83FY5dx93KnbM1SGAwGzCYz25bs5syB83h6e9CoU12Kli2Mu4cb70x7hX6jnmTTvO0c3X6SNX9utHsNg1GlxdONM36TsuH6+Ru80XQkcVHxVsfNJo2lU1cReSOKD/55x26CYzaZWTptVYYbESqqwopf1tJlcAc+6f8NOjq62fqvsWbWOHf4In989A8DJva99xcmhBBCCJeQRENYqIXJKxMGb10z8vlbxdi/1ZekeBXLfCMdBShRPpE6zWOYM6WgzXMVRQcd+r51DYMBipVNwmDUMZusb347P38Dg5uOwcaMJ6MRQouYaNUlkqV/hAA6T75yHVOKdULyXx2fyTzRULAUegcWCCCwwJ3lh/evP8zYnl9y60oEBqMBTdP4/q1fad6jEW9NG4SXjyeFShag6+DHMJvMnD14nvNHLlpNPwJQVQWD0UD3NztmGEd2/PXJAuKi4+3vAzJvBzPHz+XiiSuYkk2Ur12Gts+2wD/YsvRvbGQcCTEZb0SoKHD1zHVW/7GRpIRkux9JzayxaMpKnv3oadk7RAghhPNJjYZTyKpTwsKzM7Z3GM95wYVMDPnqAk+/ep3CJZLx8jFTvGwSAz+4zKRFJ6lUOw6j239jtfzGGow6I6ac5aGGcQB4+Zht1ms06xiV4aZ9ug5NHo+8/ZNCkZJJGSYZqgqFiydbxWKL2aRRq81DVsdO7z/He+3GEHE14nYbc1o9xoY52xj79Bfod82VMhgNjF8+gvK1y6T9bHSzZEx+wX6MWzaCEpXCbF7/4okrTB36O2N7fsHkV37i4KajVn3bo+s6K35dm+E+IADThv/JqhnrWTtrM1OGTKdnsRfZ8M9WALx8PVENmf3JUfAP8eXcoQsYMyn6jo+OJ/J6dKaxCyGEECJ3yIiGAEDRb+Sp5No/yMxTr1ynyws38PDU03YNXzEriM/eKEH6m3lLMmFKUTh33JPGHSw3oI07RPHrxCLp+nf3zPiGWVXBy/tOm2kfF6VqvRN4eNk/Jz5WpXCJJK6e97Ddp1GldLUSVG9Wxer4j+9NJyXJZPMczayxbfFuju04SaX65dOOBxcOYvKWjzm85TjbFu8iJclEhbpladK1vs1v+HVdZ9rwP5k5fq7lZl/XUVSVhd8tp267mrz/91t4+XjafW2mFBMJsRmPRqS6e5QlJcnER09/weQtH1OxblmadmvAxjnb0o3E3DnXTMueTVj312aHiv49vGWvECGEEM6n6DqKI/8huof+HwQyoiEsTKdy5DL2fq9S6y7MJstu2wC3rrvxbo9yLJ03DDzakhAfwtfDipG2fJNNCrO/K0hSguX5khWSaNwhkv8mJmePemLOoO7dZIJTh+9kFSf2e/HXN4XstjebYNXfwVy/5M5j/W6kvipLRLeLmQuXLMCH89+1qmE4c/A8O5ftsx8IlhGLNX9uSndcURSqPlyR/mN78eKn/Wj5dGO704gWfLucmePnApbkRdPu7POx+9/9fPb8dxnGYHQz4hfkk2EbWywrX8Hfny8AoPfwbqhGg1WBd9rrURWadK1P+dplaNK1QVp8tqiqSrUmldKmZQkhhBAi75FEQ1gozlq9x3qQLDrCwMyvCvJ8k4p0rlCNl1pXYML/irPw12Cunrd8G63rkJKiMHZgCX6ZWJhZXxfk/X6l6Ve/Msf3+bBk2mHUoK/ZuP5jkhJu12xkID7GwOGdlpviq+fdKVQ8CTcP60Rj4S+hNusz0l6FEZZMD7nriMKcKQVIiEt/bbMJEuJU5k4NRTMr9B96lU/+OYGbh0LJKsWo3aY6b00dxJT9n1GwuPVeG9OG/ZHhawHQdI3YqLhM29ljNpv5c5z9pYs1TWPd7M1cOXPNbhtFUegwoI0DU59sXN+ksXneDgBKP1SSiStGEhoWDIBqUFEUBUVRaN27KUNnDAagYr1y1GxVze71NF2j94juWY5FCCGEcIieA48HgEyduo/pug4pO9Hj/wbtMqgFULyeAPemKMp/buA8mgFuQMo9XFEBVFBLgnaey2fdeLtrOW5dN94esVA4e9SLs0e9WD0nCICmj0XR8bmbVKoVz5CvL5AQq+LpY+aJstVvrzSlc+2cZYTg6pnrKAYl3SpEtmxe6s+8n0LZutIfReH2LuGp5ymsnRdIo3ZRNHs8Ch3SNuczmy2rSP06sTBnjljPk4qPNbB2XiCP9o6wWvL2+iV3PnyhFDcuuePtZ+aLt4uzeVkAmhnOHb5IuVqladKlPh5eHsRGxnHp5FU8vd0JKBjAtiW7M39bNShS2v5oSmbO7D9P+OWIDNsoisK2Rbvp/Oqjdtt0f6sjq//cyK0rEXanPtmTkmxK29ejWpPKTD/9DbtW7OfcoQt4eHvQ8PHaFCxxp5BeURRG/f02H3SdyL61hy2b9CmgmTQMbgZe/34gddvWyFIMQgghhMhZkmjcp3Q9BT3yHUhawp39MQzoiYvAvQEEfo+i3pkKo6iB6N79IH4a2U+zdcAE2jl0HT4aUJKIG8bbN/n/ZTm2YXEAGxYHMOijSzzRPxy3YPPdTwPgH+KX9r+ObVqns+CuXbrvFIMrdx2DCf8rwcHt4Tz9v+uEFLbUSJw84MXsbwve3n8jvS/fKcGCXwpQt2U0RiMc2+PF7vV+6LqCouokxKm3k4w711r1+waObDtBxXpl2fDPNkzJlmuFhAU79Hp0Xaftsy0ceN22JSUkZ9pGURSSEzNuF1gggMmbxzJp0I9sW7TboSLy1L5LVilmNWXMYDBQ/9Fa1H+0lt3zfAN9+GTVBxzZepz1f28lMTaRElWK0aZvM5kyJYQQwqVkHw3nkETjPqXHToKkpbd/Mlv/b/IO9OhRKIGfWp2j+L2FrsdDwp9YkpO7z709WpHphn6Wb7qP7PLm1CFHpmNZbj7n/BjKE/3DMZvh+D7vtBt1RVVo92xLAJp2b8h3b/7i4A1u5pvVNWgTTbunIggpbOLITm+G9SpDfGxGKx1ZakNOH/Li9CFPq2uoBsuyupoGuo1rXz55lcunrlrlcOGXbjnwOqDeo7XSTbnKiuKVimIwGjKsedDMGmVqlMq0r9CwEMbMf4996w7xdssPHLq+rut0/p/9kZKMKIpClUYVqdKoYrbOF0IIIUTukRqN+5CuxUH8dOyPTGiQuAjdfNXqqKIYUQNGo4T+i+L7Cng/jeL7NgT/jeL7Fnj1IfOPjAK4c2i7j+Xm20HhVy31GgYDzJ1iualWjSohRYNp3KUesz9bwKfPfYO7R0Z7JqROenRgR2wFkhJVkhIUrl9yo2SlRAzGjCdNqqrt59w9NGo0jrk91SuDa2fz24vB3w3I3om3+Qf70eLph+3WO6gGhYIlQqnVuprDfVZvVoUiZR2YzqXAw0/Uo/3zrRzuWwghhMh1UqPhFDKicT9K2Qt6QiaNNEjeDF5d0z2jGEuC7/+wmnDkXh0F0MznIHkD9kc2dPBoiqLuz9IvkXJ7DPHv7wuwfqGlfqN8zdIUrxzGgIfeRMukLsPT20xifMb7Lvw3zF1r/dm11h8Abz8T8TEGMkoUNO3uG3VLO/+gFOq2iubCSS/LOKiNPTvuVUpixnUz187dYPnPa7h69jp+Qb607NmYivXKWU1VeumzZziy9QRXz1y33nBPAc2sc/38TXoWe5GOL7ej+1sdM1zqFiwjDb2GdeOz57+128bD250Xxveh40ttMWRUeS+EEEKI+5IkGvelzKY33abb3rshI4rP8+jJa+08q4ISAAEfU7P5ILQPHe8/OdHAyOfa0KBjJwZN0qn6cEXmfbWUFb/au9bddNp0j2DRb9mfXhQfk71fhegIN1b/E5J5w3tgtrETN1imJP3+0T/89sFfKKpiSX0UhTmTFtPgsdp0GtSeVb+v58rp6wQVDKDn0C5cPHaZJT+tIuZW7O1O7vQXcS2KGR/OZuuiXXy65oNMk412z7bgxoWb/Db6L1RVRdd0VIOC2aRRpVEFxi4ehm9g1pfEFUIIIcT9QRKN+5GxMpYpTpmsDORWPctdKx4NwP8D9OjR3KnZuP3NueKPEvwzihrE6bP9UdQpaftjOGL78htg3MPYhUM5d+Sig0kGgJLFJMPB6VV5gF+wL0XtTFFaOnU1v46aBZBuJa5ti3ezbfFuDEYVs0lDNahsXrCDCnXL8N2uiTxf9XWS4tMXf2uazsk9Z/jz4zn0H9srw9gURaHv+z1o3bspS6eu5vKpq/j4e9Pi6cbUalXNakRFCCGEyE+kGNw5JNG4DymGAuge7SBpBbZHNwzg9hCKW6Xs9e/dC9wbocfPhJT9oHigeLQCr84oqj9zJi3muzd+yVbf2xfv5vCWY2xfuiftJjlrHEki8s8NcLvnWtrchE/TNH7/6O9Mz099/1KnS53cc5aRncZnuBKVZtZY8N1ynhn9lGVZ2UwULVuY5z/OOCkRQgghxINHEo37lBIwCj38KJjPYT2yoYIajBLwqb1THevfWBrFf2jaz7qus/yXtcz+bAHnD1+8p74XT1mJu6dbNr8RzztJhKJaNqLTdd2yE7amozm0PG9qB9h9L88evMD18zezHJNm1jhz4DyqUUXLIImLi4xndPdPeefnV/AL8s3ydYQQQoh8zdUF2zKiIfIzRQ2GkH8g/nf0hFlgvg5qEHh1Q/Hui2JwXl2Brut88eIPLP1plVP627/+MI8NaJON0YycZXAzYE65M2KkGpS0onXfQG9KVilOnbY1aN+/FZdPXeXjXpO4dSUCg9GApmnomp6WiNikw/Zle9iyYCcXT1wBXadqk0pUblCexPike4rdkf07ti3ezTutPuDLTWPx9Pa4p+sJIYQQ4sEjicZ9TFF9wfdFFN8XndqvruuYTWaMbpaPz+b5O5yWZIBlB/B/Ji12eEO43KCoSroRgbtXxoqNiufQ5mM81KwKBYqFUKBYCH+c+45tS3Zz5sB5PLzc8fb34ouBP2R8IR3e7zwBVVVAUdDMGuVrl+aNH1/KdG8Mu7ErikOJhmbWOLX/HCunr+fxFx/J8nWEEEKI/EpqNJxD9tEQDts0bxv9Kw+mnfEpHvXoSdfQ5/h97D/MnbzE7h4N2RV5Lcqp/TnV7dlZGSZCt5+aOX4uJ/eeAcBgNFCuVmmqPlyRGi2qElw4yOFLapqeVmdxav853n9iIo271kc1Zv1913Wd0g+VcOjfTEFhyU8rs3wNIYQQQggZ0RAZ0nUdU4qJzwd8z8rp662ei7kVyy8jZ6IaVOu9Ge5jqdOlHB1tUVWF8X0mU7xSGOePXOL8kTs1F6HFQrL13mkmjfDLtyhRMYyCxUO5fv5mur0x7M39NBhVylQvybhlIxjx+DiObj+Z4bV0XefmxfAsxSeEEELke1Kj4RQyoiFsunU1gh/e/o0uwc/SwbNXuiTjbg9KkgHgH+KXpfaapnPu8EU2ztlmlWQA3LwYjmbWslX0rms6G+ds4+tt4+g6+DF8ArwBSyLRtGsDSlQuZkk47upaNagEhPozYtabBIT6M3nLx5SvUybj+nkFQooGZzk+IYQQQggZ0RDpXD17ncGNRxB5PeqBSiIcEXE10ul9/nd0RFHAkQGTqPAYAkL9efHTfrwwoTfx0Ql4+njg5u5GYnwSy6auZvGUf7l+/iZ+wb60faYFHQe1I6hgwO3rKHR/syPjek/K8Drt+7fK9msTQggh8qsHpY7ClSTREOl89sJ3RN24f5MMRSVLGwnmNEeSDFVVKFq2cNrPBoPBahlaT28POr/6KJ1ffTTDfpp2a8CcSeU4set0un9v1agSVq4IbZ9pnrUXIIQQQgiBTJ0S/3HxxBX2rj6Y55eWvRf/TTIUxTIR02jMP69Z03SnrATl5u7GhOUjaNa9oWWvj1QK1G9fi8/XjcbL1+ueryOEEELkK7ru+scDQEY0hJUz+8/ldgg5TtcVFEXHzVPDFKeAnnc2/bNFURVqtKhKi6cedkp/PgE+DP/zDV78tB/71x9B13SqPFyBIqULOaV/IYQQQjyYJNEQVtw83HI7hFyh6woJsUYq1orjxD5vNO0eko0MVn26V+6ebnQa1J7nPno6bR8TZwkNC6FVzyZO7VMIIYTIj2QfDeeQRENYqd68Ch5e7iQlJOd2KDlAxy/IzIgfzhEQYuLKOXcibxpJSVI5fdiTjJdjyrBbl1BUhfodavPip/1ccwEhhBBCCCeSGg1hxdvPiy6vdSAbK67mQwoxEUYCQ1MoXTmRBm2i6dDnFq9/eh53z7xXr6FrOpdOXMntMIQQQoj7n54DjweAJBoinWfHPE3rPs0Ay27WiqJgMBoAqNywfG6G5hKRNy3TxQy3x/fKV0+k1+DruRiRfQ/q1DYhhBBC5D8ydUqkYzAaePfXV+k6+DFW/LKW8Cu3CCoUSOs+zfigy8TcDs/pggulWP2sqtCp/03+nFyIpATX5+IGo+rwKl9h5Qpn3kgIIYQQ90TRLA9X9v8gkERD2FW+dhnK1y6T9vO2JbuJuBbl3Iso4BPgTXx0ArqWw+OIik65agmUKJ+U7ikfP40yVRI4ssvHZZdXDSrVmlbGL8iHA+sPEx0em+k55WqVdlk8QgghhBDOlCcTjfj4eMaMGUN0dDTffPNNbofzQEtKSGL+18uY/80yrp+/6fT+FUXB29eLuMh4p/edMR10eGHkZbstFBcPZmhmjSff7kSDDrWJDo/hqaIDMKWYMzynWpNKrg1KCCGEEMJJ8lyNxueff07ZsmWZNWsWZnPGN13CtRLjk3inzYf8NPR3lyQZYClwvnEx3CV9Z0wBFCKu2655SExQOHPY02VXV1WFmi2rUbddDQD8Q/xo2asJqsH2r6RqUChTvSSVG1a4p+tePHGFbUt2c3DTUcwm+f0SQgghbJJicKfIcyMaBoOB5cuXM2fOHK5evZrb4TzQ/vx4Dse2ncj5KU05RFF1Fv4aQquukVbHzWZY+nsICXEGF11XoWyt0ty6GknPYi9SsGQBHhvQhhfG9ebErtOcO3zR6j1XDSp+QT6MmPUGSjaXAzt76AKTB/3IgQ1H0o4FFwnimdFP0eGF1vf8moQQQggh/ivPJRqDBw8GYM6cOZm2TUpKIinpzvz66Ohol8X1oDGlmFj43XK0LCYZXn5eJMQkuCgq59I1hZP7vblyzo0iJVPQzKAa4NAOH34eV8Sp13pvxmuYU8zERccz+9MFnNxzJi2ZiLwRzbHtJ6nSqALjl49k5fT1LPphBTcvhuMb5EvbZ1rQZXAHQosGZ+vaF45dYnDj4STGWdei3LoSwRcDvyc+Op7ub3a859cohBBC3C9kwz7nyHOJRlaMGzeO0aNH53YY96VbVyKIiYjL0jmFShXg1tVI1wTkIslJCi+1rsjIn87i46exZEYIq+cEYkpx3qxCnwBvmnSpj4eXB280f59bVyKsRixS///R7SeZPvovXv/+RZ4a8oTTrj912B8kxiWhmW0vcTF12B+0fbYF/sF+acdO7D7NP18uYtvi3WgmjYr1y9H51Udp1LFutkdVhBBCCPFgyXM1GlkxdOhQoqKi0h4XLlzI7ZDuG9nZr+HauRukJKVk3jBPUUiMNzC8V1le71ieFbOCnZpkAAQU8OfI1hOcOXCOgxuO2F3KVjNrrPh1LbGRWUvwMhJ9K4bN83fYTTIAzClm1s7cnPbz6j838kr991g7cxOxEXHExySwb+0hRnWeyPdv/YquPyBfwwghhHhw6brrHw+AXEs0SpUqlfbo1KlTtvrw8PDA39/f6iGcI6hQIOVqlUZRs/Dt9QNU3JQVV89c453Wo/nj4zmWGvQMpCSZOLnnjNOuHXE1MtMaG4NR5fr5GwBcv3CTic98ha7pVglRaqIy58vFbJ6/w2nxCSGEEOL+lWuJxtmzZ9MeCxYsyK0wRAZ6De923xaC5yTNbHkP187a7FAilqXkLhPnDl/KtI1m1ggsGADAkh9XZvgli2pQmTt5ibPCE0IIIfKk1BoNVz4eBPl66pRwraZdG/Dip/1QVMXusqtZIlP7M+Xh7UGFOmUyb+iA3asOMLbnF5k3VBRaPN0YgCNbj2c4zUozaxzddsIp8QkhhBDi/iaJhshQ9zc78tvJr+n5XheqN69yb509INl7ZuwVUyuqQseX2uLl63XP19B1nW9em+pQPUX3Nx5PW9HK4GbMNCF0StIphBBC5GWyj4ZT5NlVpz744IPcDkHcVrhUQZ4d8zS6rvNmi1Ec3nwsw2+9RcZSb/4VVUHXdFSDimbWqNuuJs+N7emUa5zcc4bzRzKfNtXy6cY8P7532s9129Zg57K96Hb+AhqMKvU71HJKjEIIIYS4v8lXk8JhiqIwZv671GhRFbDcdBrdXLOp3f3O09eT6s2rULJqceo/WovR84YwZsG7uGdjtS9bbl665VC7mi2roap3/gy0faYFPoHeVsfuppl1ur7+uFNiFEIIIfIqqdFwjjw7oiHyJt9AHyb++z7Hd51i87wdJMYn4eHlzswJ89A1LX0hscIDMzyYFYmxiSTGJtHyqcY8+kIrggsHObX/oEIBDrUL/E8730Afxi0dznvtPyI+KiFt9EU1qKDrvPnTy/gG+vDjuzO4cfEmAaH+tOnTjIr1yjk1fiGEEELkf5JoiGypUKcsFeqUBSx7Ndy8dIuVM9ajmzUUVUFRFDSzRqmqxTl70LH9TULCgilfqzR71xxMt4t1fuHh405SfLJDydWxHSc5vusUv4/9h5F/vUmjjnWdFkfFeuUoWrYQV05fs7uKlF+QD3Xb1Ux3vFL98kw/9Q3//rqObUt2kZJsokrDCnQY+Ajzv1rKp/2/xWBU0XXLKNe8r5bSpGsDhs54DXdPd6e9BiGEECLXuHqvC9lHQ4jMndx7hmcrvMa/09fdqdvQdTSzRqdB7flmxwSCiwRlWED8zOgn+WbHeH4/+y1jFrzHX1d+pEmX+jn0CpwrKS6ZUlWLO9xe13RSklL4sPunXDiWeU2FoxRF4aXPn7XkO3aKuwdM7Gt3qpZfkC9dX3+MCSve5/O1H/LC+D5s+HsrcyYtBsBs0tDMGmaTGYBN87bz9WvTnBa/EEIIIfI/STREtiUlJDG0/VjiouKt9ttITdIXfLuMXSv2MX7ZcPyCfKxWWzIYLR+9vu/3oM/IHlSoUxaDwVLvERedwKZ8vCnc+SOXLKM6WdgPw5RiZuaEeU6No1HHuoz6+21CilhPy/IP8eOtn17m0edbO9xXclIKsybaj0/XdJb/soZbVyOyG64QQgiRZ0iNhnPI1CmRbWtmbibyepTd51WDyl+fzKflU41x93JPm+/v7ulGpQblGfhJPyrWLZu+3z83Za20I4/Vgdy9IpeqKmgObnq4asZ6Bn87wKnTj5p0aUCjTnXZs+ogNy+GE1gwgDptq+PmnrWi82PbTxJzKzbDNppJY/vSvbR/ruW9hCyEEEKI+4QkGiLb9q4+kLY0qy2aWePgxqMc3HjU6nhyUgr71x1m4z9bbSYakdciLf1qZscCcXGS0WFgG7Yt2k34ZcdWcrqbo0kGWKYjrf97K236NMvydTJiMBio27ZGls87vf8cZw+ex8Pbw7ETFEhJTM7ydYQQQog8x9V7XeShL0hdSRINkW3m7O6lcfuXa+aEeTzcuT6VG5S3ejokLDj7fTuZ0c1A615NWTJlZY5cb+2szU5PNLLq7KELfNr/W47tOJl2zKFRFh3K1CjlusCEEEIIka9IoiGyrWqjiqybtTn7HSjw2Qvf0rp3M4qULsjulQeIvBFFQKi/84K8R08OeYKk+JxbASsuKi7HrmXL5VNXeb3pCBJiEq2OJ98eqVAUxeZu46pBpXilMKo0qpAjcQohhBCu5Oo6CqnRECITj/RrxrThf5AYn2RVDO4wHc4dusi0YX84Pzgn+ePjOTTt2jBHrmUwqpSoFJYj17Lnj7H/kBCbaHc6nK7r6abLGYwqHt4eDJ3xmlXBvxBCCCEebLLqlMg2nwAfPpjzDkZ3I6rxzkcpo6Vs8x0dNvyzFW8/11/KbNLoMPAR11/IjuSkFFb9sRHNZH/ammJQqFivLD4B3oClsL/dsy35btdEysq0KSGEEELcRUY0xD2p3aY6P+7/jPlfL2PDnG2kJCZTrlZprp69waUTV3I7PKeJj7l7xMbJ39rfXjWr2xuP2yyOzylxUfGYkk0ZtlEVlZJVivPlxo9Iik/Cw9sDVb2TWMZFxbH+763cvHSLoEKBNOvREP/gHMjShBBCCGfSdMvDlf0/ACTREPcsrFwRBn35HIO+fC7t2D9fLOKHt3+zOZ8/v/Lw0khKULFUszsv2ShSuhBPDXmCDgPaOK3P7PAJ8MbNw0hKkv1kQ9d1QooGoaoqXr5eVs/NmbSYn4b+TkpSCgajAc2k8c3gafR9vwc9h3aRaVVCCCHEA0YSDeEShUsXRDWoaTtH538KSQkGXhh5iT++KER87L396rwwoTeNOzfAYFQpVLKA1ahAbnH3cKNVr6asnL4Os53pU5pZo03f5umOL/lxJd+98Uvaz+YUy7+7KdnEzyP+xN3Tje5vdnRJ3PmZpmkcWH+EK6ev4RvkQ912NfF0dDlhIYQQriPL2zqFJBrC6TbP38Ho7p+6bjRDgZCiQYRfytldqFVV59Y1N4eSjJCiQRSvFMbRbSdIjEtKK6B293Sj76gnefLtJ/LkN/y9R3Rj07ztxEcn2CwIf+J/7SlWvojVMVOKiZ9Hzsyw3+kfzqbjy23x8JKb6FR7Vh/g8wHfc/XM9bRjXn6e9B3Zg+5vdcyTnw8hhBAiKyTREE5lSjHxxYs/gK67JFtXFAgsGICHZ87fsOo6XD6b+XWNbgZaPNWYlz57hsT4JDbP286Ni7cILOhPky718QnwyYFos6dI6UJM2jSWz57/lsNbjqcd9/T15Mm3OtF7ZLd05xzceDTDHeIB4qMT2LViPw8/Uc/pMedHhzYfY2j7sWiadTKXEJPIlCHTSU5Koffw9O+1EEKInKHg4uVtXdd1niKJhnCqHcv2ZnrTeS90HSJvRBF5I9pl17B/bYWtKwLIrEbDbNIIK1fYco6mER+TyLnDFzh/VEE1qDTv0cixDfBySYlKYUzaNJazhy5w7vBFPL3dqd6iKl4+njbbx0Q4tvdHbGTu7hGSl/z47nR0TbO7LPSMMX/T8eW2UkgvhBAiX5NEQzjVldPXUFQle/tqOEjXwJHhEjcPI4qikJyYkmG7UtWKc+7QxSxM9cr4ewg3Tzda9WrCvnWHGNV5InHR8aiqiqLAil/W8uOQ6YxbNiLPLwdbqmpxSlUtnmm7omULOdRfkTKOtbvfXTt3g0ObjmXYxpxiZsPfW3ksF5c7FkKIB5quWx6u7P8BkPsVqOK+4hfsm60ko1XPJvQb9aTT5qUrikKXVzvw6ZrRKKr9PvuM7E5xJ22Sl3qdV79+gehbsQzv8DEJMQmgW4qoUwuso27GMKTNh0TfinHKdXNb2RqlKFuzFKqd91lRFYqWK0y1JpVyOLK8yZERP9WgEnHNdSODQgghRE6QREM4VaOOdXHzdMvyeev/2UrFBuXQnVTY0aZfM/p/3IvKDcrz+drRFKtgXcDsG+jDK5P70++DJzEYUpeszbq7NycsU70kH85/l/bPtWTBN8tJSTah2Ui6NLNGTEQsy39em61r5kWvfz8Qo7tbus0aVVXBYFB5c8pLUtx8W0jRoEzbmM1mQouF5EA0QgghbFF01z8eBDJ1SjiVb6APPd/twm+j/8rSebqmsX72Fjq+1JZF369IN6KoqgqaAwXmPgHefL7uQ8pUL5l2rFqTykw7Momj209alhEN9KFmq2q4e1gSojqP1GDtrM1Zihcs39T3H9uT+o/WwsvPi8KlCqY9t+GfrTZXbbrzenU2ztlKj7fujyVfK9Uvz5cbx/DjuzPYs+pA2vGqTSrxwvg+VGlYIRejyxm6rnNsx0n2rjmErulUbVyRh5pWTpdghYaFUKv1Q+xbe8juZ8TD052m3RrkRNhCCCGEy0iiIZyuz/vd0TSNmePnYjKZMRhUu/sypDKbNNb/vYW5t37By9eTOZOWWO1SXbhMIUpXK8HWRTvt9qUaFMpUL8neNQe5eekWddpWx2AwAJapVJUblKdyg/LpzqvcKHs3wbqmU7RsYUo/VDLdc0kJyZmenxiflK3r5lXla5dh4r/vc/NSOOFXIgkqFEDB4qG5HVaOuHkpnNHdP+PothNpozqaWaNUteKM+ueddEsCD5zYl8FNRmBKNtlMNl6Y0Acff+8ciV0IIYQNeXAfjYSEBAYPHszy5csxm8306tWLCRMmWH2hlZKSwrhx45g9ezaRkZGUKlWKr776ipo1azov9iyQREM4naIoPDP6Kbq81oEN/2wl6mYM6/7axOn95zM8LzE+iRO7TtO4c306vdKegxuOEh+TQInKYVRvVoVzhy+yecEOu+drZp0DG45wcNNRdE0nNCyYd375H7VbP5Thdbct2oWiZL0uyzfQhwaP1bb5XNmapdiz6oDdb6wNRpXytctk7YL5RGhYCKFhD860n4S4RN5qMYpr524AWP2bXzh6ibeav8+PBz7HP+TOClLlapXm87WjmfTyj5zYfTrteFDhQPp/1JP2/Vvl3AsQQgiRL7z11ltomsapU6eIi4ujTZs2fP3117z66qtpbY4fP47JZGLr1q34+Pjwww8/0LFjR06fPo2bW9antt8rRXfZrmo5Lzo6moCAAKKiovD398/tcMRdfhwynb+/WJThdKK7uXu60b5/K14Y3xsvX6+04yt+Xcunz3+Lqip3RjYUbH4zoNyuD/h8/RibIxmppg3/g9mfLsCUkrVdzN+aOoj2z7W0+dyWhTt5/4kJGZ7/9fbxVKxbNkvXFHnP4in/8uXLU+x+O6WoCs+N6UnPoV1sPn/mwDmunL6Ob5APVR+uiMFocGG0QgiR+/Ly/VpqbE1bjMJotL2suzOYTIlsWDva4fcgNjaWQoUKceHCBYKDgwGYM2cOY8aMYc+ePRmeGxwczMaNG6lSpYpTYs8KKQYXOeLRAW0cTjIAkhNTWPTDv7z28HA+6f8NL9V6m8FNRhB1M4bP1oym3bMtKVyqIKFFg+3e4Omajqbp/DZqVobXKlq2cJaSDA9vd96Y8qLdJAOg4eN16DCwDYDVqlepKzP1G/VkWpJx8fhllk5dxdKpq7h4/LLDcYi8YdUfG1AyWPJY13T+nb7O7vOlHyrJw0/Uo3qzKpJkCCHEAyY6OtrqkZRke1r1rl27KF26dFqSAdCgQQMOHjyI2Wz/HiY+Pp74+HgCAgKcHrsjZOqUyBHFyhehafeGbPh7q8PnaGaNswctm8alLpl7ZMtxfAK9+XT1B7wx5SVmjp/LzyNn2k1iNLPGzn/3cebQeUpXLWGzTc1WVbP0WpLik/lm8M94envQqldTm20UReH17wZSuUEF5ny5iDMHLNPGKtQry5NvP0HTbg2JuB7FJ89+zY5le63OrduuBkN+fZWggrnzR0FkTXR4bKZ7sMhmhUIIkc9otx+u7B8oXtx6v6pRo0bxwQcfpGt+5coVChWy3o+qYMGCmEwmoqKirBKQuw0fPpwWLVoQFuacpfyzShINkWMKlSiAalCzNLIBWO3Loes6sRFx/K/BUL7a+jFRN2MsK1JlNCChw8CH3qJ68yo891FPqjW23s9h5fQNKIqShQ37IDkhmXF9JuMT4E2Dx+rYbKMoCu2fa0n751qSlJCEoihpO4InxifxdstRXDxxJd15u1cd4O2Wo/hmxwQ8vT0cjknkjmIVinDh2CU0e4sUqApFyxbO4aiEEELkBxcuXLCaOuXhYfu/+yaTKd19SupIhq3l4+Pi4hg0aBAHDhxg+fLlTow4a2TqlMgxPgHOW0XHlGxi8MPDcfMwYnYwcTmw4QhvtXif5b+ssTq+csb6LCUZd/t8wPcOtfPw8khLMgBWTl/P+aO2b041k8b5I5dYNWN9tmISOeuxAW3sJhkAmqbz+Iuyw7cQQuQniq67/AHg7+9v9bCXaAQHB3Pz5k2rYzdu3MDT0zPdtKhTp05Rr1493Nzc2LhxIwUKFHDNm+QASTREjmnWo1GWRzMykpyUwuHNx25vuJc5XdPRzDqf9v+WV+q/y941BwGIjYjNdgy3rkZy/sjFLJ+34pc1mS5tN/+bZdmMSuSkuu1q0uKph7G1H6GiKtR5pDotn26c84EJIYS4b9SuXZtjx44RERGRdmzz5s00aNAAVb1zHxQZGUmrVq144403+Omnn/D2zt2l0iXREDmmRKUwWjz1cFpB9D3TYd/6wzxtZzWfjJzYdYZ3245h2+JdFC1XxKpgO6t237VBnaNuXY3MtI0UhjtfTEQsG+duY+2sTTanrWWHoii8N/01nvnwaaslbL39vXnqnSf4cMF7UuQthBDinhQuXJj27dszbNgwTCYTN2/eZOzYsbz++utW7WbPnk2lSpUYMGBA7gT6H1KjIXLU29MGgaKwduYmq43Nsk2H2q2rE1w4kOmjZxNxLcqx03QdNPhswPf0/6gnR7Yez3YInj5ZX/7O298r0zYpSSYunriSbrM34Zi46Hh2LN1DTEQchUoWYPvS3Sz5cSUpSXc2gqzV+iHenvoyBUvc27CywWig9/BuPPlOJ84fuYSu6RSvVBQPL6mxEUKIfCkPbtg3depUnn/+eYoUKYKPjw9vv/02nTt3ZsaMGezYsYNJkyZx4sQJtmzZQqlSpazOHT58eK4kH7KPhsgVF49fZsM/21j/9xZO7T2b7RoJgBZPPsymBTtISUzJ1vmj5w3hh7d/4/LJq9k6f+rhLylRKWurOUx89mv+/c3+kqepPl46nHrtamYrrgeVruv8MXYOf46bk+kO7QajSlChQL7dNVFW+RJCiBySl+/XUmNr1uR9l++jsX7jh3nyPXAmmTolckWxCkXpObQLlRuUTxvZyA6Dm4G1szdnO8lQFIXr52+SkmzKvLENlRuWz3KSAZZv0h3hH+yb5b4fdL+OmsUv78/MNMkAMJs0bl2NZN7kJTkQmRBCiHxD113/eABIoiFyVfXmVTCbsrYj993MKeZ7GtrUdR0Pb3dunL+ZeeP/CAj1Y+iMwdm67sNP1MPdyz3DNoVKFaB8nTLZ6j+n6brOrn/3MbbXlwxuPJzRPT5ly8KdGW4i5AoR16OYOX5els7RzBpLp65yTUBCCCHEA0xqNESuatylPsFFgoi8HmW3VqNW64fYk42Ca0e4e7rR6HHb+2DcTVEUVIOC2aTh7e/Fo8+3pvtbHS07k2eDj783vYZ15ZeRM+22ef7j3lYrSeRVyUkpfPTU52xZsBPVqKKZNFSDysZ/tvFQs8qMXTQUL9/Ma1KcYf3sLdmq+Ym8HoWu6zbXIhdCCPHgUXTLw5X9Pwjy/l2MuK+5ubsxdtFQfPy9rFZ+MhgtH83HX2pL3XY1IJv3fwEFMp732GtYNwILBlKzZbUMp3Dpus57M15jSeIfzIv4lZc+e4bQosHouoaecgg9eTu6+VqWYus1rCv9Rj2J0d0ICmkrE3n5evLmjy/lmyVRp773O1sX7QJI208i9Wb/0KZjTHr5xxyLJepGNKox63/WAgsGSJIhhBBCOJmMaIhcV65WaaYemcSSH1ey7q/NJMYlUaZ6STq+3Jbabaozvu9kVDXrO4oDVG5QnoefqMd3b/xCQmwiBqMBs9mM0c1Iz/e60Gt4VwCefq9z2r4a9qybvYUWT965+dfj/0GPnQxa6jKpCrpHSxS/ESjGYpnGpigKfUf14IlX27Pxn21E3oimYIlQGnepj1c2VrLKDXFRcSz6YYXV7u1308waq//cyAsT+mR79CcrChQPyfJUPNWg8ujzrV0UkRBCiHzJ1XUUD0iNhiQaIk8IKhhA7+Hd6D28W7rn3NzdbG6G5ojabarz6POtafF0YzbO2cb18zcJLOBP024NrfY8qPNIDYpXLMqFY/b3rtj4zzbOHDxP6Wol0OOmosdM+E8LHZLWoafsg5A5KAbHlqX1D/ajw4A22Xl5ue7wluMkZ1KIr2s6e1cfpE2fZi6Pp1n3hnz96jSSEzMvBAdQjSrBhQLpMriDiyMTQgghHjwydUrkeQ0eq43ZlL29NpLikwDw8vHkkb7N6T28G48NfMQqyQCIvhWTYZIBlulc6/7ajG4OR4/5zE4rM2iR6DGTsxVvfuPov8u9FPxnhU+ADwM/6etw+5otqjJp81gCC8jStkIIIe5QNNc/HgQyoiHyvEad6lK0bCGunruRVgPgCIPRYLU5mz26rjN99OxM2ymKQlxUPCTOBzKKw4w5dh67t3emdpt6+aKgO7vK1S6Noip2p06lqtSgfA5FBE+80h5vPy+mDf+Dm5dupR2v8nBFnh/Xi+ibMZiSTZSrXUY2QxRCCCFcSBINkecZ3YyMXzGSdx8Zw5XT11ANKrqmZTq90WwyU6JK5rUSM8fPY95XSzNtZzZphJUrgm7aidkMBoP9tgajmS+e/xg375KMWfAuxStmfa+N/CC0aDBNuzZg49ztNmtoDEaVak0qUbKy/X8Hs8lMclIKnt4eTivIfqRfc1r1bsKx7SeJjYynSJmC9+2/gRBCCBeQGg2nkERD5AtFShdi6uEv2DR3O1sW7iQ5MYUrp69x+sA5dHP6X1ZFUfAP8eXhJ+pm2G9CbAJ/fPyPQzEY3Q207tOUozuXUr5ixiMrmgax0QaSrl3jrZYf8NPBz/EP9svwnPzqtW8HcObgBS4ev2w1sqGoCiFFgxny66s2zzu24yR/jp/LlgU70cwawUWC6PRyO7q9+Tie3h73HJfBYKBKo4r33I8QQgghskcSDZEn6brOoU1HWf7zGq5fuElQ4UAe6ducZj0a0eIpy8pPEdejeK3RMK6fv2n1bbpqUFFVhXenv4abu1uG19m5fB+JcUkOxfS/r17A29+LH9+P4LMMchOzCXau8SM+xgBoRF6PYtnU1Tz5zhMOXSe/CQj15+tt41g8ZSWLp/xL+OVbBBYIoP3zrej4clubCdbWRbv4oOtEdP3OUri3rkTw6wez2LJwJ5+sHpVvVt4SQghxH9K5pw2BHer/ASCJhshzTCkmJvT7irWzNmMwqphvbwC3asYGard5iNHz3sXT24OgggF8vW0cf4ydw9Jpq0iISURRFep3qEWfEd2pWK9cpteKjYxzKKaeQ7vQ4YXWnDl4noNbElk+M4hHnozgv+UXZjNomsL0zwqnHdM1nTUzN923iQaAt58XPd7qSI+3OmbaNiEukY97T0Izp5/+pms6J3af5s+P59B/bC8XRZu56FsxXDx2GXcvd0o/VAJDRvPkhBBCCGGTJBoiz/n1/Vms+2sLcGdVo9RvvfeuPshXr/zEOz+/Ali+TX/5i2cZMLEPEVcjObrjJAkxiSTEJqJpWqaF2EXLFc7w+VStezcFwJRsKS6fNKQ4ifEqj/cLR1VB0y01G7euG/nktRKc2O9tdb6jCc2DYO3MTSTEJNh9XjNrLPp+Bf0+eBKjW87+iYq8EcUPb//G2pmbMKVYVsoKLRZCr2FdefzFR2RTPyGEeEAouo7iwjoKV/adl0iiIfKUhNgE5n61FN3OL6Cm6aycsZ7+H/cipEhQ2vEVv67jp/dmEHMrNu1YgeIhDP52AA0eq3P7XA1d162+nX6oaWWKlCnE1bPXba6cpKgKFeuWpWSV4gAUq1AEDy93khKS+XZEMf6cVIiGj0Tj5atx/oQHu9f5oWnWN6OqQU1XlH7mwDmunL6Ob5APVR+umLYreF60e9UB/vlyEftWWzY0fKhpZbq+8Tj12tXMVn+n953D6GZIu5G3JSYijltXIylYPDRb18iO6FsxDG48gqtnrltNxbt5MZzJg34k/PItnv3w6RyLRwghhMjvJNEQecrhLcfT9r6wRzNr7F65n0f6Ngdg8ZR/+fKlKena3bwYzshOE+j3wZPsW3uIfesOoWs6xSsV5aGmVajRoip129XgrakvM6T1aJvTJXVNp3rzqmk/e/l60e65liz64V80s0bEDTeW/hGSabwdX2wLWAqgJ738Iyd2n057PrhIEP3H9qTdsy0z7Cc3zP50AVOGTE+bwgaWxGPnin08O+ZpmxssZsbdy92hxTbcPTOur3G22Z8sSJdk3O33sf/Q9pkWFC3r2CiYEEKIfExWnXKK+3eBf5EvpU5NcrRdUkISP747w2YbXQcdnV9HzUpLMgAuHL3Mkh9XMq73JJ4sMoAF3y5Hy2AfiL8+nc+pfWfTfu7/cS9KP1QCRXVgGo0CLXs2ocFjtTm55wxvthjFqb1nrJrcuhLBp/2/Zf43yzLvLwcd33WKKUOmA9Yb86XeiP8yciYHNx3Ncr+NOtXNcAM/VVWoWK9cjm6ip+s6i6f8azfJsMSlsvznNTkWkxBCCJHfSaIh8pSyNUs5dAOfWui9fckeyyZ69tzOH+xtKGdOMbN+9hbI4JIGg8rCb5en/ezj780XG8bw/Me9KVyqIKqq4BPgTdWHKxJY0D+tXUjRIAZO6Mu7v/0PRVGY8s5vmJJNdpOaH4dMJz6D2oWctuCbZRiM9v9EGIwqC7KRHFV9uCJVH66IarDdt6bp9B6R9ZGSe5EYl0hMRCZ1NLrOlTPXciYgIYQQ4j4gU6dEnhIaFkLjzvXZPH+H3Q3gKtYrR5nqJQGIuBaFoih2azoclsHpZpPGwc3HrI55+Xjy1JAneGqI9UpSZrOZ6+duAlCwZGhaPciNi+HsuV3jYE9SYjIb/tmaZ6ZQHdpy3Gok47/MJo3DW45nuV9FURg9bwjDHxvHsR0nMRgNVv9+g758jkYdM97/xNncvdwxuhszHFFTVBW/IN8cjEoIIUSu0YGMt8y69/4fAJJoiDzntW8HcHr/Oa6evmb17b9qUAkI9ee96a+lHQspGnTvSYYDjA4WaxsMBoqUKZTuePjlWw6de/Ni5u1yipt75n8ejO7ZK2IPCPVn8pax7Fl1gA1/byUhLpESlYrRrn9LQosGZ6tPgLioOOZ/szxtPw+/YF/aPduSLoMfs1o84L8MBgMtnnqYNX9utJtcmU1mWvVqmu3YhBBCiAeNJBoi1yQnJrNy+noWTfmXa2dvEBDqR9tnW/LYwDZ8s308879ZxpIpKwm/GoF/iB/tn2tJl9c6EFQoMK2Peo/Wwi/IJ/NpL/dANag0eKz2PfURWDDzegOz2UxQoZyrS8hMw8frcO7wRbt1C6pBpVHHetnuX1VV6jxSgzqP1Mh2HwBx0fGYTWY0s8abzd7n4okraVPlIq9HM/uzhSz7eQ1fbvyIYuWL2O3n6fe6sOHvreiaCU2zfs2qQaV2m+pUaVThnmIVQgiRP8jyts4hNRoiV8THJPBWy1F88dIPnNx9hujwGC4cu8y04X/wYs23iY+Op/fwbvx+7juWJc1k1N9vc/XsDV5tOIznKr3GlHd+48qZa7h7uPHyl8/ZvogTtjxQFAWju5HHXnzknvopXKogVR6uiJpB/Ymbu5Gm3Rve03WcJfxKRIYF24qiYDCqdBrULgejsrb+7y28Uu9dOgc+Q7fQ/vQt8woXj19JV4+jmTVibsXyca8vM+yvZOViTFw1itBilhEV1aBa6oUUaNqtIe///ZbsoyGEEEJkgYxoiFwx5Z3fOL7zNNxeGSqVruncuhLB2J5fMmnTWAB+/+gffnl/ptUSq/98uZh53yzjw3nv8kjf5hjdjEwZMp2bF8PT+ipWvgjhlyNISkjOcDWhVEY3A5pZS5uupagK7p7ufDj/Xafs5zBgQh/ebvkBCprN4vTeI7rniRqApVNXMenlKeiabnMKqaIquHm48cE/b9ucJpYT/vh4Dj+P+NMqcUuMs78ssmbWOLHrNMd3naJCnbJ221VpWIHpp79h14p9nN5/HndPNxo+XifXXqcQQohcouPi5W1d13Veoug5McHdQbqu89133/HDDz8QGRlJSEgIn376Ka1atXLo/OjoaAICAoiKisLf3z/zE0SuiImI5amiA0hJyngp2+92TyTiaiTDOnxs83lFUXD3cuP3s98REOqP2Wzm0KZjRN2IpmCJUCrULcvJPWcY2n4sUTejM7xW51cf5al3O7P0p1XsX38YRVGo1eoh2j/fiiAHpj05aveqA3wx8HuunrmedszLz5O+I3vQ/a2Ouf6N+a5/9/Feu49sP6lYiuB7vteF9i+0tvu+xEXFMXfyUhb/+C+3LkfgG+xLu2da0PWNx++p/iLVmYPnGVj9rayfqMBr3wyg40tt7zkGIYQQ2ZeX79dSY2tV8z2MBg+XXcdkTmL13vF58j1wpjw1ohEXF8fevXtZu3YtQUFBLFmyhG7dunHs2DEKFiyY2+EJJzm971ymSYaiKBzefJzN87ejGlSbIxK6rpOcmMLyn9fw5DtPYDAYqNakEntXH2TFr2tZ+N0KylQvyXe7J7Bz+T42z9/B0e0nibweldaHt783T77TiZ5Du6CqKn3f7+H013u32q0f4tcTX3Fg/RGunL6Gb5APddvVxNPbdX/MsmLm+Hl23290SIhNpFydMnaTjMgbUbzRdCSXT15NGxmKvhnDP18uZsWva/liwxiKVwy7pxiXTFlpNbrlMN2xAnchhBBCNuxzjjz1X11fX1+mTLmzw3OHDh0oXbo0O3fupEOHDrkYmXAmR/bJ0NFRVIX9G45kOO1J13T2rj3Ek+88QcS1SIY/No4Tu09juL1KlKZp/DT0d96e+jJjFrwHwJXT1zhz8DweXu5Ua1IJD6+cvclXVZUaLapSo0XVzBtnk9lkZufyvVw/f5OAAv7U71A702QmMT6JvWsyXoLXYDSwZf4O6rWrafP5r1+bxuVT19LtFaKZNWIi4vi41yS+2zUxS6/lv07tP5v1JANL8lr7ker3dG0hhBBCOC5PJRr/pes64eHhBATknZV4xL0rX6cMnj4eGc6pR4eAAn7oDtRWKIqCpmkMf2wcp/efBbAqZE5JSmF8368ICQumRvOqFClT6L6ec7/hn61MfuUnq5EbLz9PnhvTk86vPmp3elZKUopD/Scn2m4XcS2SDX9vtZsYamaNk3vOcGzHybQNF7PDy8czy3unqAaV5k82ckqtjRBCiAeAhlMWlcmw/wdAnl51avLkyfj6+tKoUSObzyclJREdHW31EHmfl48nnQa1tzuyoagKbp5ujOnxOaYU+ysfpbat2aIqe1Yd4MTu03a/6VZUhZnj591r6HmWrutcOHaJSS9P4cMen1klGQAJMYl8+/rPzJ28xG4fvoE+hIRlXEOhmTXK1ixl87nT+89lXnSvwPGdpzJuk4kmXRtkmmSk5lKpu48/1LQyb/zw4j1dVwghhBBZkydHNEwmEyNGjGD27NksW7YMVbWdD40bN47Ro0fncHTCGZ4d8xTnj15k68JdaTUBqqqgaTq6ppNi51vzuymqgoeXO+2ea8kv78/CYDTYXZJVM2vsWrGXpISkHJ8q5QwXj1/mypnr+Af7Ur5OGavfiRW/rmXGmL+5cvpapv38MnImj77QGi8fz3TPhV++RfGKRQm/ZGfTQAXcPIw80q+5zaeNjtQ/6A62y0DLnk2Y/uFswi9HpEtsFFXBYDTw8BP1iIuMI7BQAG36NKd2m4fs/h0RQggh/kv20XCOXEs0SpUqlfb/q1evzoIFCwC4ceMGnTt3JiQkhO3btxMSEmK3j6FDh/Lmm2+m/RwdHU3x4sVdFrNwHjd3N0bPHcLO5ftY8tNKrpy6hm+gDwc2HHFoSoxqUDG6G/lw/rv4h/iRGJ9IZmvF6TqkJJnyVaJxcs8Zvn5tKoc2HUs75unrmVZE5uHtQdQNx0fyEmIT2b54N82ffNjq+Palexjd7ROS7UyfUo0quqbz7m+v4hvoY7NNpfrl8Pb3Ij46we71FUWhTtt726DP09uDT1aNYtijY7l86lpaPY7ZZMbbz4sP5rxDzZbV7ukaQgghhLh3uZZonD17Nt0xk8lEu3bt6NChAx99ZGeJzbt4eHjg4ZF/bhqFNVVVqf9oLeo/WguAWRPnc3DjkYwXYlCgROViNH6iHo+/1DZtzn3paiXRtPUZXi+4SCDe/l7OCt/lTu07y+tNRpCSbL1CV2Js4p3/n1Gdiy0KRPxnWtX18zf4oOvEDFcC8wv04YO5Q6jWuJLdNh5eHnR7/XGmj5ltM+dTDSotnnrYKXUSYeWKMO3IJLYt3s3O5Xsxm8xUrF+elj0b2xytEUIIIbJEVp1yijw1dWrNmjXEx8c7lGSI+8+1czcs06i0DOoydBi3dHi6m9W2zzRn2vA/MCXbvllWVIVOg9rnq+kzP7z1KynJJoc2G3SYTrr3buF3KzKthYm6GcOhTccyTDQAeo/sxrXzN1jxy1oUVbHamLB8nTK87sQ6idQpUg8/Uc9pfQohhBDCefLUXdeJEyc4f/48pUqVsnqMGjUqt0MTOcA/xBctkwxfVRWbU3cCQv1588eXUBQlrQD47nMqNyhP9zcfd2q8rnTt/A32rD7o3CQDcPdyp96jNa2O7Vi21+ZO5f81d/JizOaMExKDwcCT7zyBf4ivVZ+qQeHY9pPM+WJxtuIWQgghclTqiIYrHw+APDWiMWjQIAYNGpTbYYhc0qpXU37/6B+7z6sGlUYd6+LtZ3v60yN9m1OgWAh/jpvD7pUHAAgqHMgTg9rT/a3H83xtxsk9Z1j43XL2rTvMlTOZF3ZnR8/3OuPm7mZ1LLPkIVX45QjCL92iYIkCdtukJKcwtP1HxEbGWx3XzJY/qL+8P5MSVYrRtGuDLEYuhBBCiPwmTyUa4sFWolIYj/Rrzsrp69MVhFtWE1LpM7I7YFnO9dLJqyTEJFCoVAH8g/0AqNmyGjVbViMxPomUpBR8Arzz/HSp2Og43n1kDMd33Nuyr5kpXrEovUd0T3f8oaZVOHfogkNfrqiphddmM+ikFWKn2jxvBzcuhNs/X1X4a+I8STSEEELkbVKj4RSSaIg85c0fX8LT15PFP/xrteRtgWIhvPvbq5SrVZqNc7fx66hZnD14AQCDUaVZj0YMmNCXAsUsq5R5entkuhN2bkiMT+LmpVt4+XoSUMCfn4f/wV+fLshswax7VqpacT5ZNcrmZn1PvNKOhd8tz7SPYhWKcHznKT7+/EsObrAU7ZevU4bubzxOy55NUBSFXf/uz3iZYU3n6PaTJMQlStG2EEIIcZ+TREPkKUY3I699/QJ9RnRj66LdJMYmUqJKsbR9EJb8tIovBn5vdcNsNmms+2sL+9Ye5pvt4wgNs78kcm65dS2SCX2/Ys+qA1na0TrLFNKSFqObgZJVi9NzaBeadmtod2SnZJXivP7dQL58eUqGXZesUpxRnSeiGtS0L2JO7jnDuD6TObzlOK9M7n+7piTz1+fs2hMhhBDCqWRncKeQREPkScGFg+jwQmurY7GRcXzz2lSAdDfrmlkj6kYUv7w/i7en5q06n1tXI3im/KtZX4o2iyrUKUP9DrUpU6MUDR6rhbuHu8PnPvbiIwQWCmBcn8kkxd+JU1EUdF2nROUwNs3bDlgnCakF3/O/WUb9DrWp3LA8y39dY/c6igJh5YvYrbMRQgghxP1DEg2Rb6z5c2OGez2YTRqrft/AK5Oew8s3925kr1+4yfKf13Dp5BV8/L3Zt/aQS5OMoMKBPP1uZzq/+ug91aM07lyf2Vd/ZNXvG5n96QIun7qKjo5qULlw9HKG56oGlXlfLWHkX2/y47sziI9JsLmSla5D19cftzmFSwghhBD3F0k0RL5h2QVazXDPB1OyifArkRQrn7OJRnJiMhHXIln+y1pmfPj3nScUHFo6NqsaPFabJ/73KGHlClOoVAEMBkPmJznAy9cLD293Lp+6ajmgOzbNSTNrnNh9Bi9fy87cwx8bh9lkwmyynKsaVDSzRuveTXlsYBunxCqEEEK4iqLrKC6c6uzKvvMSSTREvuEb5IPmwE27T4B3DkRjceXMNd7vPJGzB87bbuCCvyOKorB9yR62Ld5N/Q61ePe3V9NW3bpXuq4z48PZ2TrX3dOybG7NltX4Yd+nzP9qKev/3kJSYjKlHypJ51fa07S7/VoRIYQQQtxfJNEQ+UbzHo34ZeRMu8+rBpVqTSoRVDAgR+KZN3kJ37z+c45cy+BmQNd0NLNmVZ+yc/k+hrYfy6RNH2F0y/jXOTo8hpN7zqCoChXrlbNZJ3H+6CUun8r6Hh4Go0qTLneWrC1WvgivTO7PK5P7Z7kvIYQQItfJ8rZOIYmGyDeKVShKm77NWPX7hnTTkRTF8m18vw+edHkcMRGxjOg4jsObj7v0OgY3A827N8LobmTljPU2pzBpZo3jO0+xZcFOmnZraLOfuOh4vn/zV/79bV3asrOKolChXlmGzniNsHJF0tpmp5ZEURVUo4En/tc+y+cKIYQQ4v4liYbIV96Y8hKqQWXFr2tRFQXFoGJOMeMT6MM7016hRvOqLrnu7lUHmP/1Uo7tOEl0eCwpSSkuuU4qRVEwp5i5cvoa1y/czLBOQjWorPx9vc1EIzkxmXcf+ZDju05bJWe6rnNs+0meqzSYMQuH0uDRWgAULVsIo5shwzoYsCQXlo4se5Z8MHcIRcsWzsYrFUIIIfIgTQfFhaMOLqjfzIsk0RD5iruHG+9Me4V+o55k45xtxEcnUKxiURp3qY+7h5vTr6frOlOH/s6sifMxGNW04mZXS50edWzXqUyLyTWzRtT1aJvP/fvbOo5lsOO4rul80GUiM858S0iRIPyCfGn+1MOsmbkJzcZrVVQFL19P6neoDUDVhyvySN9m+AT4OPrShBBCCPGAkERD5EuFShag2xuPu6TvvWsOsuC75Zzcc4aUxBRuXroF4LIko3ilolw6cdX21KjUa961Ed9/GYwqRcoWsvnc4h9XZnp9U7KJJVNW0ndUDwAGTuzLwY1HuXEh3Com1aCiGlRG/fMOtVs/lGm/QgghRL4lNRpOIYmGEMD+DYf5+n9TOXf4Yo7uWh0SFsTF41cyHLVQVCXD580mjUefb23zuevnbjgUx66V+9ISjeDCQXy9bRx/jJ3DsmmrSYhNRFUVGnWsS+8R3Shfu4xDfQohhBDiwSaJhnhgxUXHc2jzMSa9NIXr52/mSgz9P+rJJ899m3EjBfyCfYmLik+fBCnQuldTHmpa2eapAQUCiLoZk2kc/01kAgsEMOjL5xj4SV9iIuLw8vXE09sj036EEEKI+4OLRzRcsf59HiQL2osHzsl9p+lR+AU6Bz7D8A4fuzTJCCjgT8ueTQgtFmx1PLRYCCP/epNH+rUgqFAmy/Hq0L5/K0KKBqV7SgG8/bxIjEu0eWq7Z1tkGqOiKFS3U0RvdDMSVDBAkgwhhBBCZJmMaIgHwpmD51n8w7+s/H0dcZEJLr1W3fY1eGF8H4xuRsLKFcboZkTTNA5sOEL45QhCigRRrWmltN28Ow1qz2+j/7I7PUpRFTbP255WK3I3XYeF36/g8NYTfLHhQ7x8PK2e7zCgDX9/sYiIq5F241UMCo+/+Ej2X7AQQghxv5EaDaeQREPct3RdZ/ZnC5g+ena29ofIEgUCQv3pPaIbjw1og7unu9XTqqraXXq3+1sd2bZ4F8d3nrK987kOl05ezfDyp/adYd7kpfQc2sXquG+gD99sH8+bzd/n6pnr6c5TDQrDfn+dQiULZPIChRBCCCGyRqZOifuO2Wxm5sR5tHd/ih+HzHBJkqGoCgajZURCNSigW3be/nbwz7xUewi3rkY43Je7pxtPvdeZwMK2p1A5VJyuw4Jvl9l8qkCxEKaf+oZ3f3uVCnXL4BPgTXCRIB5/8RGm7PuM5j0aORyrEEII8UDQdNc/HgAyoiHuGyd2n+K99mOJdqD4ObsKlymIf7AfPgHe7Fl1AADNbPljkTr16dLJK4x58nO+WD8mw75uXY3g+K4zfDt4KldOpx9tyKqbl26RkpyCm7vt/UTa9GlGmz7N7vk6QgghhBCOkERD5Etms5ntS/awbvZmdq3YT+SNKJcv4PDyF8/SdfBjpCSn8HTYi3bbaSaNgxuPcmL3aZtLwV45c42RncZz7tBFp8ZndDdidJNfaSGEEOKe6Zrl4cr+HwByVyLynd2r9vN+pwkkJSTnyPVKP1SCN6a8SOUGFQA4d/gi0eEZj5qoBpXdKw9YJRqnD5xlSJsxRN2wvYv3vVBUheZPNkJRFKf3LYQQQgiRHZJoiHwjJTmF/lUGc/W0Y5vQOYPR3ci7v71K2Rql0o45uqFfarszB88zpsdnXDh22RUhApbdwZ8a0tll/QshhBAPFFl1yimkGFzkaZqmMeuT+XTw6kkHz145mmSAJVmY/uFsq2MlKhfDy9fTzhl3zgstFsSOZXsYVGeIS5MMv2Bfxi0dQelqJVx2DSGEEEKIrJIRDZEnXT5zjdcaDnPJNKOs0MwaW+bvID4mAW8/LwA8vT14bOAjzPlyke3laG+b+Mw3Lonp0edbkRiXTEABP6o0qkjjLvVx97BdAC6EEEIIkVsk0RB5ypGtxxjS9iMSY23vdJ0bNE0nNjIuLdEAeHbMUxzfdYr96w7naCwvftqP7m92zNFrCiGEEA8cTcelq8zI8rZC5IzExESeKfsat644vvdETnLzMBIQ6md1TDNrBBcJypHrG4wGmnVvSJ/3e1CiUliOXFMIIYQQ4l5JoiFyzaZ52/mo5+eYksy5HYpdBqNK697N8PDy4OLxy8ydvITVf24gNiLexdc1UKt1NZ545VHqd6iFqko5lRBCCJFjpBjcKSTREDku8kYUb7cazblDF3I7lAypBhWfAB/a9G3Ksl/W8MXA79FMrlv3OqCAP40716POIzV4+Il6sieGEEIIIfI1uZMROSouOp5XGwzl6tmcXT0qO9w8jESHx/B2y9Euv9bjL7Vl8LcDXH4dIYQQQjhAx8UjGq7rOi+RREPkqMU//OuyJEM1quiajn4PBVZ129bg4skrXD19naR4124IaHQ3Ur9DLYb/+TruHu4uvZYQQgghRE6TREPkqCU/rXJ6n0YPI9WbVWH/usOYTKZ76mvnin1Oiiq9ivXKUrZmKfyC/Xj0+ZaElSvqsmsJIYQQ4h5IjYZTSKIhclS4C1aWMiWZ2LfmIGYX1k9kl6Iq6LrOYwMf4dWvnsdgNOR2SEIIIYQQOUISDZGjAgv4c9UFe2TktSSjcOmC1G9fkwIlCtD8yUYUKV0ot0MSQgghhKM0DXDhvYWWt+5bXEUSDZGj2vdvxS8jZ+Z2GC7j7efJmz+9TPMeD+d2KEIIIYQQuUoW5xc5qtOgdhQqWQBFybxtjyGdwIF2eYGbhxuDJj3LnPBfJMkQQggh8rvUGg1XPh4AMqIhcpRfkC9fbBjDJ899w55VB9I9X7R8YT5Z/QEFw0IAOHfgAjv/3efS/SuySzWqFAgLoePL7XhsYBt8A31yOyQhhBBCiDxDEg2R4woUC2Hiv+9z4dgljm47icGoUqNlNUKKBKVr+/a0QbzedCRXTl+7s2ytQq6uP20wGpiwYgQ1WlTLvSCEEEII4Tqy6pRTSKIhck3ximEUrxiWYZugQoF8u3MCS35cxbJpq7l1NYKQIkHous6FY5fvac+MrPIO8KLds614bmxPvLw9cuy6QgghhBD5kSQaIs/z8femx1sd6fFWRwDiYxMY2XE8549ccvm1i5QtSOtezej+dkd8/Lxdfj0hhBBC5AGajkunT+TgF6W5SRINka9cO3edZyu8hinF7NLr+Ab78MOeTylYPNSl1xFCCCGEuF9JoiHyDV3XGVT3PZclGQaDSoW6ZRk28w0KlyzgkmsIIYQQIu/TdQ1dd91CNK7sOy+RREPkG3tWHyA6PMapfbp7udOkawMGjO9N6O2VroQQQgghxL2TREPkG6v/3Oi0vhRF4en3OvPMh09hMBic1q8QQggh7gO67to6Cll1Soi8xZx871Om3DyMdH39MXqP6I6Xj6cTohJCCCGEELZIoiHyjUoNyrFyxvosn+fu6Uafkd3p8XYnjG7ykRdCCCGEyAly1yXyjda9m/HdG79iNjk2slGgWAiDvxtAg8fquDgyIYQQQtxXdBcvb/uATJ1SczsAIRzlG+jD0N8HZ9jG4GagZa8mzIv4hT/Ofy9JhhBCCCFELpERDZGvNO/RiJAiH/L9279xbPtJABQFSlQuxrCZr1OmWslcjlAIIYQQ+Z6mgeLCJWhleVsh8qZqTSrz9dZxJCcmk5yYgre/F6oqg3NCCCGEEHmJJBoi33L3dMfd0z23wxBCCCHE/UZqNJxCvgYWQgghhBBCOJ2MaAghhBBCCHEXXdPQXVijoT8gNRoyoiGEEEIIIYRwOhnREEIIIYQQ4m5So+EUMqIhhBBCCCGEcLo8lWjouk7Pnj0pV64cYWFhtGrViiNHjuR2WEIIIYQQ4kGi6a5/PADyXKIxYMAATp48ycWLF2ndujV9+vTJ7bCEEEIIIYQQWZSnEg1VVWnVqhUAiqLQqVMnLl26lMtRCSGEEEKIB4quW3bvdtnjwRjRyLPF4Ddu3GDixIkMHjzYbpukpCSSkpLSfo6Ojs6J0IQQQgghhBCZyFMjGgC///47hQoVomDBghiNxgwTjXHjxhEQEJD2KF68eA5GKoQQQggh7ke6prv88SDIc4lG7969uXbtGuHh4RQqVIjGjRuTnJxss+3QoUOJiopKe1y4cCGHoxVCCCGEEELYkmuJRqlSpdIenTp1Svd8cHAw48ePJzo6mvXr19vsw8PDA39/f6uHEEIIIYQQ98Sl9Rm3Hw+AXKvROHv2rEPtPDw88PLycm0wQgghhBBCCKfKU1On1q1bx5YtWwDQNI1JkyZhMBioW7duLkcmhBBCCCFE7klISGDgwIGULFmSYsWKMWTIEHQbq1ft2bOHhg0bUrJkSapUqcK///6bC9Fa5KlEw83NjZdffpnChQtToUIFdu7cybJly/Dw8Mjt0IQQQgghxAMiLxaDv/XWW2iaxqlTpzh06BBr1qzh66+/tmoTExNDx44d+eijjzh37hzfffcdPXr04OrVq856a7JE0W2lQvlUdHQ0AQEBREVFSb2GEEIIIUQelJfv11Jja6F0wai4uew6Jj2Ftfpch9+D2NhYChUqxIULFwgODgZgzpw5jBkzhj179qS1mzJlCkuXLmXu3Llpxzp16kTr1q0zXMnVVfLsPhpCCCGEEELkCl0DXFiwncVi8F27dlG6dOm0JAOgQYMGHDx4ELPZjMFgAGDLli00btzY6twGDRqwd+/eew45O+6rRCN1cEY27hNCCCGEyJtS79Py8qQaEyngwvBMpADp71k9PDxslgxcuXKFQoUKWR0rWLAgJpOJqKiotATkypUrtGrVKl27bdu2OTN8h91XiUZMTAyAbNwnhBBCCJHHxcTEEBAQkNthWHF3d6dw4cJsvLrE5dfy9fVNd886atQoPvjgg3RtTSZTusTMbDYDoChKpu3ubpOT7qtEo2jRoly4cAE/P79ce0PvVXR0NMWLF+fChQt5bt5ifiTvp3PJ++k88l46l7yfziXvp3PJ+2lN13ViYmIoWrRoboeSjqenJ2fOnLG7WbQz6bqe7n7V3gJIwcHB3Lx50+rYjRs38PT0tErW7LUrXLiwk6LOmvsq0VBVlWLFiuV2GE4hGxA6l7yfziXvp/PIe+lc8n46l7yfziXv5x15bSTjbp6ennh6euZ2GFZq167NsWPHiIiIICgoCIDNmzfToEEDVPXOIrJ16tRh8+bNvPnmm2nHNm/ezFNPPZXjMUMeW95WCCGEEEIIYa1w4cK0b9+eYcOGYTKZuHnzJmPHjuX111+3ate7d29WrVrF6tWrAViyZAlHjhyhR48euRC1JBpCCCGEEELkeVOnTuXy5csUKVKEunXrMnDgQDp37syMGTPSlq4tVqwYM2fOZNCgQRQsWJCPPvqIhQsX4uPjkysx31dTp+4HHh4ejBo1SjYpdBJ5P51L3k/nkffSueT9dC55P51L3k/hDKGhocyfPz/d8T59+tCnT5+0n9u1a8fRo0dzMjS77qsN+4QQQgghhBB5g0ydEkIIIYQQQjidJBpCCCGEEEIIp5NEQwghhBBCCOF0kmjkIl3X+fbbb6lRowYlS5akdu3aacuR/dfNmzdRFIWSJUtSqlQpSpUqxRtvvJHDEedNCQkJDBw4kJIlS1KsWDGGDBmSbldMgD179tCwYUNKlixJlSpV+Pfff3Mh2rxv9erVNG7cmHLlylG2bFm++uorm+2qVatGoUKF0j6PjRo1yuFI877//e9/BAQEpL1HpUqV4ty5c+nayWfTMUuXLrV6L0uVKkWhQoXw8/NL19bX15ewsLC0drm1tGNeo+s6v/32W7rf16x8Br/88kvKlStHWFgYXbp0ITw83NVh51m23s+UlBQ+/PBDHnroIYoXL07Tpk3Zu3evzfN37tyJwWCw+kx/9tlnORS9EDlAF7kmJiZGHzBggH7r1i1d13V98eLFemBgoH7t2rV0bW/cuKEriqKbzeacDjPPe/nll/Xnn39eT0lJ0SMjI/W6devqkydPtmoTHR2th4WF6f/++6+u67q+du1aPSAgQL9y5UpuhJynvfbaa/rRo0d1Xdf1U6dO6WFhYfrSpUvTtatataq+evXqnA4vX3nllVf0999/P8M28tm8Ny+++KI+fPjwdMd9fHz006dP50JEedfSpUv1atWq6WXLltUrVqyYdjwrn8FZs2bptWrV0sPDw3WTyaS/9NJLeteuXXPsNeQl9t7PgwcP6iNHjtRjY2N1Xdf177//Xi9WrJienJycro8dO3boJUqUyLGYhchpMqKRi3x9fZkyZUraDo8dOnSgdOnS7Ny502Z7Pz8/q90fBcTGxvLrr78yceJEjEYjAQEBDB06lGnTplm1+/PPP6lXrx5t2rQBoHnz5jRr1oxZs2blRth52qRJk6hYsSIAZcqU4cknn7Q70hYYGJiDkeVPmb1H8tnMvtOnTzN37lzeeecdm8/L59NaXFwcEyZM4KeffrI6npXP4JdffsmoUaMIDg7GYDAwZswYFixYwK1bt3LkNeQl9t7PqlWr8uGHH6btW/Diiy8SFxfHiRMnbPYjn1NxP5O71jxE13XCw8MJCAiw+bz8MUpv165dlC5dmuDg4LRjDRo04ODBg5jN5rRjW7ZsoXHjxlbnNmjQwO5wtrjjxo0b8pm8B5m9R/LZzL7x48fzyiuv2Px8qqpq93P7oOrWrRsdOnRId9zRz6DJZGLnzp1WbUNDQylVqhQHDhxwScx5mb3387/i4+OJj4+Xv6PigSSJRh4yefJkfH197c51v3r1KqVKlaJKlSq88cYbREVF5XCEec+VK1coVKiQ1bGCBQtiMpms3h977R7kucWO2L59O4sWLaJXr17pnlMUhRYtWqSNehw/fjwXIsz7hg4dSokSJWjZsiUrVqxI97x8NrPnxo0bzJo1i5deesnm84qiULZsWSpUqMDzzz/P5cuXczjC/MPRz+DNmzcxm82EhoZm2lbcMXz4cFq0aEFYWJjN53fu3EnJkiWpXr06o0ePJikpKYcjFMJ1JNHIA0wmE++99x6TJ09m3rx5NqdHhYaGkpiYyNmzZ1mzZg0XL17kueeey4Vo8xaTyZSu8Dt1JENRlEzb3d1GWJs5cyadOnXi119/pXTp0ume37dvH+fOnePQoUPUqlWLNm3aEBsbmwuR5l2TJ0/m6tWrnDlzhnfeeYcnn3ySXbt2WbWRz2b2TJ8+nS5dulCwYEGbz0dERHDmzBl27NiBt7c3HTt2tLlIhHD8M2gymQDk8+qguLg4nnnmGdatW8f06dNttqlTpw5xcXGcO3eO+fPns3r1aoYOHZrDkQrhOpJo5JC7V5To1KlT2vEbN27QvHlzDh8+zPbt2ylfvrzdPlL/kBcqVIivv/6ahQsXPvDffAQHB3Pz5k2rYzdu3MDT09NqmNpeu8KFC+dInPmJ2Wxm0KBBjB49muXLl1t9Xu+WmhB7eXkxdOhQfHx82LZtW06GmuelvkcGg4EOHTrQs2dP5s2bZ9VGPpvZ8/PPP9O7d2+7z6e+9wEBAUyaNIljx45x+vTpnAovX3H0MxgUFISu60RERGTa9kF36tQp6tWrh5ubGxs3bqRAgQI2292doJUuXZqJEycye/bsnApTCJeTRCOHnD17Nu2xYMECwPLtULt27WjZsiULFiwgJCTE4f5MJhMGgwGDweCqkPOF2rVrc+zYMav/8G3evJkGDRpYjQzVqVOHzZs3W527efNmWZLVhtdff53Tp0+zc+dOatSo4fB5JpMJd3d3F0aW/9l6j+SzmXV79+7l8uXLtGzZ0qH2mqahaZp8Pu1w9DPo4+NDxYoVrdpeuXKFa9euZelvxf0uMjKSVq1a8cYbb/DTTz/h7e3t8Lnyd1Tcd3JvwSuxYsUKqyXxMrJv3z794sWLuq7remRkpN6lSxe9X79+rgwv3+jUqZP+0ksv6SkpKfqNGzf0hx56SJ87d65VmwsXLuiBgYH6qlWrdF23LCVcsmTJtOUHhUVCQoJuMBj0y5cvZ9ju2rVr+q5du3Rd13WTyaSPHTtWr1Chgp6QkJATYeYby5YtS1uSevny5XpQUJB+6NAhqzby2cy6cePG6Z07d7b7/MmTJ/Vjx47puq7riYmJ+qBBg/RmzZrlVHh53po1a6z+25OVz+Dnn3+u161bV4+IiNCTkpL0Z555Rn/99ddzLPa86L/v55QpU/S2bds6dO7WrVv18PBwXdd1/cqVK3rjxo0zXRJbiPxERjRy0YkTJzh//ny6DahGjRoFwIQJE5g4cSIA58+fp1GjRhQrVow6depQrlw5vv3229wMP8+YOnUqly9fpkiRItStW5eBAwfSuXNnZsyYweDBgwEoVqwYM2fOZNCgQRQsWJCPPvqIhQsXpi0/KCxOnz6Npmk0atTI6jPZrl07Vq1axZNPPglAYmIi/fr1o0iRIpQrV469e/eyfPlyPD09c/kV5C1ffPEFhQsXplSpUnz00UfMnTuXKlWqyGfzHm3bto3atWtbHbv7Pb116xYdOnQgLCyMypUrk5yczN9//50boeYLmX0Ge/TokbbE9eDBg2nevDkVKlSgVKlSeHl5MX78+NwMP885ceIEW7ZsSfff9h9//BGA1157jd9//x2A/fv3U61aNUqUKEHz5s3p0KEDI0eOzM3whXAqRdelOk4IIYQQQgjhXDKiIYQQQgghhHA6STSEEEIIIYQQTieJhhBCCCGEEMLpJNEQQgghhBBCOJ0kGkIIIYQQQgink0RDCCGEEEII4XSSaAghhBBCCCGcThINIYQQQgghhNNJoiGEEC727LPPEhQURKlSpShevDitWrVi+/btac9HRUUxbNgwqlSpQunSpSlUqBANGzYkPj7eqp8vvvgCDw8PwsPDbV7HZDLx+eef07lzZ1e+HCGEEMIhkmgIIUQOePfddzl79iwXLlzg5ZdfpkOHDty4cYPr16/TqFEjPD092bJlC2fOnOHq1at88sknGAwGqz6mTZtG1apVmTFjRrr+Z8yYQfny5fn2229JTEzMqZclhBBC2CWJhhBC5LAePXpQtmxZNm/ezIABA+jbty/vv/8+AQEBACiKQtOmTfHw8Eg7Z/v27aSkpDB27FimTp2ars/k5GRmzJjBiBEjcux1CCGEEBmRREMIIXJBbGwskZGRrFmzhjfeeCPT9lOnTuWZZ56hbdu2hIeHs2PHDqvn+/fvT+PGjV0VrhBCCJFlxtwOQAghHiRxcXF8+eWXuLu74+npSfXqwnRV6wAAAdVJREFU1fH09MzwnISEBGbPns2BAwcwGAz069ePqVOnUq9evRyKWgghhMg6GdEQQogcMGHCBEqVKkWDBg3SRjI0TcNsNmd67t9//029evUICwsDLMXlM2fOJCEhwdVhCyGEENkmIxpCCJED3n33Xd577z2rY2XLluXYsWOYzeZ0hd93mzp1Kps3b7Ya+UhOTubvv/+mb9++LotZCCGEuBcyoiGEELmkbt26hISE8MMPP9htc+rUKfbt20dsbCyJiYlpjx9++MFmUbgQQgiRV0iiIYQQuURVVX7++WdGjRrFzz//THJyMmDZD2PhwoUkJiYybdo0OnbsiLu7u9W53bt3Z9u2bZw8eTI3QhdCCCEyJYmGEELkoiZNmrB69WoWL15MmTJlKFWqFOXKleOPP/5AURR+++03unfvnu68oKAgHn30UaZNm5YLUQshhBCZU3Rd13M7CCGEEEIIIcT9RUY0hBBCCCGEEE4niYYQQgghhBDC6STREEIIIYQQQjidJBpCCCGEEEIIp5NEQwghhBBCCOF0kmgIIYQQQgghnE4SDSGEEEIIIYTTSaIhhBBCCCGEcDpJNIQQQgghhBBOJ4mGEEIIIYQQwukk0RBCCCGEEEI43f8BewH+WOZOX6cAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 2일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "#T_5461b_row0_col0, #T_5461b_row0_col4, #T_5461b_row0_col5, #T_5461b_row0_col7, #T_5461b_row0_col8, #T_5461b_row0_col9, #T_5461b_row1_col1, #T_5461b_row1_col2, #T_5461b_row1_col3, #T_5461b_row1_col6 {\n",
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       "#T_5461b_row0_col1, #T_5461b_row0_col2, #T_5461b_row0_col3, #T_5461b_row0_col6, #T_5461b_row1_col0, #T_5461b_row1_col4, #T_5461b_row1_col5, #T_5461b_row1_col7, #T_5461b_row1_col8, #T_5461b_row1_col9 {\n",
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       "</style>\n",
       "<table id=\"T_5461b\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_5461b_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_5461b_level0_col1\" class=\"col_heading level0 col1\" >평균이용시간</th>\n",
       "      <th id=\"T_5461b_level0_col2\" class=\"col_heading level0 col2\" >평균이용거리</th>\n",
       "      <th id=\"T_5461b_level0_col3\" class=\"col_heading level0 col3\" >주말대여비율</th>\n",
       "      <th id=\"T_5461b_level0_col4\" class=\"col_heading level0 col4\" >오전대여비율</th>\n",
       "      <th id=\"T_5461b_level0_col5\" class=\"col_heading level0 col5\" >점심대여비율</th>\n",
       "      <th id=\"T_5461b_level0_col6\" class=\"col_heading level0 col6\" >오후대여비율</th>\n",
       "      <th id=\"T_5461b_level0_col7\" class=\"col_heading level0 col7\" >새벽대여비율</th>\n",
       "      <th id=\"T_5461b_level0_col8\" class=\"col_heading level0 col8\" >저녁대여비율</th>\n",
       "      <th id=\"T_5461b_level0_col9\" class=\"col_heading level0 col9\" >야간대여비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
       "      <th class=\"blank col9\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_5461b_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_5461b_row0_col0\" class=\"data row0 col0\" >11.714286</td>\n",
       "      <td id=\"T_5461b_row0_col1\" class=\"data row0 col1\" >65.869644</td>\n",
       "      <td id=\"T_5461b_row0_col2\" class=\"data row0 col2\" >5654.443088</td>\n",
       "      <td id=\"T_5461b_row0_col3\" class=\"data row0 col3\" >0.374553</td>\n",
       "      <td id=\"T_5461b_row0_col4\" class=\"data row0 col4\" >0.024182</td>\n",
       "      <td id=\"T_5461b_row0_col5\" class=\"data row0 col5\" >0.111910</td>\n",
       "      <td id=\"T_5461b_row0_col6\" class=\"data row0 col6\" >0.684776</td>\n",
       "      <td id=\"T_5461b_row0_col7\" class=\"data row0 col7\" >0.019382</td>\n",
       "      <td id=\"T_5461b_row0_col8\" class=\"data row0 col8\" >0.075927</td>\n",
       "      <td id=\"T_5461b_row0_col9\" class=\"data row0 col9\" >0.019786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5461b_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_5461b_row1_col0\" class=\"data row1 col0\" >22.131410</td>\n",
       "      <td id=\"T_5461b_row1_col1\" class=\"data row1 col1\" >61.503930</td>\n",
       "      <td id=\"T_5461b_row1_col2\" class=\"data row1 col2\" >5190.505023</td>\n",
       "      <td id=\"T_5461b_row1_col3\" class=\"data row1 col3\" >0.359062</td>\n",
       "      <td id=\"T_5461b_row1_col4\" class=\"data row1 col4\" >0.064604</td>\n",
       "      <td id=\"T_5461b_row1_col5\" class=\"data row1 col5\" >0.286160</td>\n",
       "      <td id=\"T_5461b_row1_col6\" class=\"data row1 col6\" >0.153848</td>\n",
       "      <td id=\"T_5461b_row1_col7\" class=\"data row1 col7\" >0.059838</td>\n",
       "      <td id=\"T_5461b_row1_col8\" class=\"data row1 col8\" >0.225866</td>\n",
       "      <td id=\"T_5461b_row1_col9\" class=\"data row1 col9\" >0.091485</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x27465926b90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 3일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
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       "</style>\n",
       "<table id=\"T_6d7d6\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_6d7d6_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_6d7d6_level0_col1\" class=\"col_heading level0 col1\" >평균이용시간</th>\n",
       "      <th id=\"T_6d7d6_level0_col2\" class=\"col_heading level0 col2\" >평균이용거리</th>\n",
       "      <th id=\"T_6d7d6_level0_col3\" class=\"col_heading level0 col3\" >주말대여비율</th>\n",
       "      <th id=\"T_6d7d6_level0_col4\" class=\"col_heading level0 col4\" >오전대여비율</th>\n",
       "      <th id=\"T_6d7d6_level0_col5\" class=\"col_heading level0 col5\" >점심대여비율</th>\n",
       "      <th id=\"T_6d7d6_level0_col6\" class=\"col_heading level0 col6\" >오후대여비율</th>\n",
       "      <th id=\"T_6d7d6_level0_col7\" class=\"col_heading level0 col7\" >새벽대여비율</th>\n",
       "      <th id=\"T_6d7d6_level0_col8\" class=\"col_heading level0 col8\" >저녁대여비율</th>\n",
       "      <th id=\"T_6d7d6_level0_col9\" class=\"col_heading level0 col9\" >야간대여비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
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       "      <td id=\"T_6d7d6_row0_col0\" class=\"data row0 col0\" >10.716263</td>\n",
       "      <td id=\"T_6d7d6_row0_col1\" class=\"data row0 col1\" >65.575097</td>\n",
       "      <td id=\"T_6d7d6_row0_col2\" class=\"data row0 col2\" >5649.756732</td>\n",
       "      <td id=\"T_6d7d6_row0_col3\" class=\"data row0 col3\" >0.377526</td>\n",
       "      <td id=\"T_6d7d6_row0_col4\" class=\"data row0 col4\" >0.023967</td>\n",
       "      <td id=\"T_6d7d6_row0_col5\" class=\"data row0 col5\" >0.109596</td>\n",
       "      <td id=\"T_6d7d6_row0_col6\" class=\"data row0 col6\" >0.690794</td>\n",
       "      <td id=\"T_6d7d6_row0_col7\" class=\"data row0 col7\" >0.018578</td>\n",
       "      <td id=\"T_6d7d6_row0_col8\" class=\"data row0 col8\" >0.075580</td>\n",
       "      <td id=\"T_6d7d6_row0_col9\" class=\"data row0 col9\" >0.016476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6d7d6_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_6d7d6_row1_col0\" class=\"data row1 col0\" >23.829372</td>\n",
       "      <td id=\"T_6d7d6_row1_col1\" class=\"data row1 col1\" >63.398585</td>\n",
       "      <td id=\"T_6d7d6_row1_col2\" class=\"data row1 col2\" >5284.557567</td>\n",
       "      <td id=\"T_6d7d6_row1_col3\" class=\"data row1 col3\" >0.359150</td>\n",
       "      <td id=\"T_6d7d6_row1_col4\" class=\"data row1 col4\" >0.068813</td>\n",
       "      <td id=\"T_6d7d6_row1_col5\" class=\"data row1 col5\" >0.300997</td>\n",
       "      <td id=\"T_6d7d6_row1_col6\" class=\"data row1 col6\" >0.162662</td>\n",
       "      <td id=\"T_6d7d6_row1_col7\" class=\"data row1 col7\" >0.062021</td>\n",
       "      <td id=\"T_6d7d6_row1_col8\" class=\"data row1 col8\" >0.234321</td>\n",
       "      <td id=\"T_6d7d6_row1_col9\" class=\"data row1 col9\" >0.049908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6d7d6_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
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       "      <td id=\"T_6d7d6_row2_col1\" class=\"data row2 col1\" >38.659816</td>\n",
       "      <td id=\"T_6d7d6_row2_col2\" class=\"data row2 col2\" >4038.801170</td>\n",
       "      <td id=\"T_6d7d6_row2_col3\" class=\"data row2 col3\" >0.341147</td>\n",
       "      <td id=\"T_6d7d6_row2_col4\" class=\"data row2 col4\" >0.001149</td>\n",
       "      <td id=\"T_6d7d6_row2_col5\" class=\"data row2 col5\" >0.066584</td>\n",
       "      <td id=\"T_6d7d6_row2_col6\" class=\"data row2 col6\" >0.098265</td>\n",
       "      <td id=\"T_6d7d6_row2_col7\" class=\"data row2 col7\" >0.027712</td>\n",
       "      <td id=\"T_6d7d6_row2_col8\" class=\"data row2 col8\" >0.084390</td>\n",
       "      <td id=\"T_6d7d6_row2_col9\" class=\"data row2 col9\" >0.662416</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x274739c0790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 4일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_a82f8_row0_col6, #T_a82f8_row1_col1, #T_a82f8_row1_col2, #T_a82f8_row1_col3, #T_a82f8_row1_col4, #T_a82f8_row1_col5, #T_a82f8_row2_col9, #T_a82f8_row3_col0, #T_a82f8_row3_col7, #T_a82f8_row3_col8 {\n",
       "  background-color: #ccffcc;\n",
       "}\n",
       "#T_a82f8_row0_col7, #T_a82f8_row0_col8, #T_a82f8_row1_col9, #T_a82f8_row2_col0, #T_a82f8_row2_col1, #T_a82f8_row2_col2, #T_a82f8_row2_col3, #T_a82f8_row2_col4, #T_a82f8_row2_col5, #T_a82f8_row2_col6 {\n",
       "  background-color: #fffff0;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_a82f8\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_a82f8_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_a82f8_level0_col1\" class=\"col_heading level0 col1\" >평균이용시간</th>\n",
       "      <th id=\"T_a82f8_level0_col2\" class=\"col_heading level0 col2\" >평균이용거리</th>\n",
       "      <th id=\"T_a82f8_level0_col3\" class=\"col_heading level0 col3\" >주말대여비율</th>\n",
       "      <th id=\"T_a82f8_level0_col4\" class=\"col_heading level0 col4\" >오전대여비율</th>\n",
       "      <th id=\"T_a82f8_level0_col5\" class=\"col_heading level0 col5\" >점심대여비율</th>\n",
       "      <th id=\"T_a82f8_level0_col6\" class=\"col_heading level0 col6\" >오후대여비율</th>\n",
       "      <th id=\"T_a82f8_level0_col7\" class=\"col_heading level0 col7\" >새벽대여비율</th>\n",
       "      <th id=\"T_a82f8_level0_col8\" class=\"col_heading level0 col8\" >저녁대여비율</th>\n",
       "      <th id=\"T_a82f8_level0_col9\" class=\"col_heading level0 col9\" >야간대여비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
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       "      <th class=\"blank col8\" >&nbsp;</th>\n",
       "      <th class=\"blank col9\" >&nbsp;</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_a82f8_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_a82f8_row0_col0\" class=\"data row0 col0\" >11.267658</td>\n",
       "      <td id=\"T_a82f8_row0_col1\" class=\"data row0 col1\" >52.555332</td>\n",
       "      <td id=\"T_a82f8_row0_col2\" class=\"data row0 col2\" >4852.363651</td>\n",
       "      <td id=\"T_a82f8_row0_col3\" class=\"data row0 col3\" >0.369357</td>\n",
       "      <td id=\"T_a82f8_row0_col4\" class=\"data row0 col4\" >0.020757</td>\n",
       "      <td id=\"T_a82f8_row0_col5\" class=\"data row0 col5\" >0.106927</td>\n",
       "      <td id=\"T_a82f8_row0_col6\" class=\"data row0 col6\" >0.689185</td>\n",
       "      <td id=\"T_a82f8_row0_col7\" class=\"data row0 col7\" >0.019803</td>\n",
       "      <td id=\"T_a82f8_row0_col8\" class=\"data row0 col8\" >0.078043</td>\n",
       "      <td id=\"T_a82f8_row0_col9\" class=\"data row0 col9\" >0.018274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_a82f8_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
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       "      <td id=\"T_a82f8_row1_col1\" class=\"data row1 col1\" >211.333343</td>\n",
       "      <td id=\"T_a82f8_row1_col2\" class=\"data row1 col2\" >16189.345067</td>\n",
       "      <td id=\"T_a82f8_row1_col3\" class=\"data row1 col3\" >0.471360</td>\n",
       "      <td id=\"T_a82f8_row1_col4\" class=\"data row1 col4\" >0.077824</td>\n",
       "      <td id=\"T_a82f8_row1_col5\" class=\"data row1 col5\" >0.378878</td>\n",
       "      <td id=\"T_a82f8_row1_col6\" class=\"data row1 col6\" >0.274088</td>\n",
       "      <td id=\"T_a82f8_row1_col7\" class=\"data row1 col7\" >0.029617</td>\n",
       "      <td id=\"T_a82f8_row1_col8\" class=\"data row1 col8\" >0.140258</td>\n",
       "      <td id=\"T_a82f8_row1_col9\" class=\"data row1 col9\" >0.015620</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_a82f8_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
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       "      <td id=\"T_a82f8_row2_col1\" class=\"data row2 col1\" >39.096645</td>\n",
       "      <td id=\"T_a82f8_row2_col2\" class=\"data row2 col2\" >4085.616829</td>\n",
       "      <td id=\"T_a82f8_row2_col3\" class=\"data row2 col3\" >0.341352</td>\n",
       "      <td id=\"T_a82f8_row2_col4\" class=\"data row2 col4\" >0.001235</td>\n",
       "      <td id=\"T_a82f8_row2_col5\" class=\"data row2 col5\" >0.068336</td>\n",
       "      <td id=\"T_a82f8_row2_col6\" class=\"data row2 col6\" >0.092076</td>\n",
       "      <td id=\"T_a82f8_row2_col7\" class=\"data row2 col7\" >0.023405</td>\n",
       "      <td id=\"T_a82f8_row2_col8\" class=\"data row2 col8\" >0.081102</td>\n",
       "      <td id=\"T_a82f8_row2_col9\" class=\"data row2 col9\" >0.686419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_a82f8_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_a82f8_row3_col0\" class=\"data row3 col0\" >25.322669</td>\n",
       "      <td id=\"T_a82f8_row3_col1\" class=\"data row3 col1\" >52.133832</td>\n",
       "      <td id=\"T_a82f8_row3_col2\" class=\"data row3 col2\" >4383.932761</td>\n",
       "      <td id=\"T_a82f8_row3_col3\" class=\"data row3 col3\" >0.350391</td>\n",
       "      <td id=\"T_a82f8_row3_col4\" class=\"data row3 col4\" >0.067304</td>\n",
       "      <td id=\"T_a82f8_row3_col5\" class=\"data row3 col5\" >0.284642</td>\n",
       "      <td id=\"T_a82f8_row3_col6\" class=\"data row3 col6\" >0.169628</td>\n",
       "      <td id=\"T_a82f8_row3_col7\" class=\"data row3 col7\" >0.063811</td>\n",
       "      <td id=\"T_a82f8_row3_col8\" class=\"data row3 col8\" >0.237905</td>\n",
       "      <td id=\"T_a82f8_row3_col9\" class=\"data row3 col9\" >0.053459</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x2746d6d05d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 2일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   1\n",
      "1     ST-1002   1\n",
      "2     ST-1005   0\n",
      "3     ST-1006   0\n",
      "4     ST-1010   1\n",
      "...       ...  ..\n",
      "1838   ST-991   0\n",
      "1839   ST-992   1\n",
      "1840   ST-993   0\n",
      "1841   ST-994   1\n",
      "1842   ST-996   0\n",
      "\n",
      "[1843 rows x 2 columns]\n",
      "n_clusters = 3일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   1\n",
      "1     ST-1002   1\n",
      "2     ST-1005   0\n",
      "3     ST-1006   0\n",
      "4     ST-1010   1\n",
      "...       ...  ..\n",
      "1838   ST-991   0\n",
      "1839   ST-992   1\n",
      "1840   ST-993   0\n",
      "1841   ST-994   1\n",
      "1842   ST-996   0\n",
      "\n",
      "[1843 rows x 2 columns]\n",
      "n_clusters = 4일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   3\n",
      "1     ST-1002   3\n",
      "2     ST-1005   0\n",
      "3     ST-1006   0\n",
      "4     ST-1010   3\n",
      "...       ...  ..\n",
      "1838   ST-991   0\n",
      "1839   ST-992   3\n",
      "1840   ST-993   0\n",
      "1841   ST-994   3\n",
      "1842   ST-996   0\n",
      "\n",
      "[1843 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "# 변수 초기화\n",
    "cluster_results = {}\n",
    "\n",
    "# n_clusters 값을 2, 3, 4로 설정하여 K-means 군집분석 및 시각화\n",
    "for n_clusters in [2, 3, 4]:\n",
    "    # K-means 군집분석\n",
    "    kmeans = KMeans(n_clusters=n_clusters, random_state=42)\n",
    "    grouped['군집'] = kmeans.fit_predict(scaled_features)\n",
    "\n",
    "    # PCA 적용\n",
    "    pca = PCA(n_components=2)\n",
    "    pca_features = pca.fit_transform(scaled_features)\n",
    "\n",
    "    # PCA 결과를 데이터프레임에 추가\n",
    "    grouped['PCA1'] = pca_features[:, 0]\n",
    "    grouped['PCA2'] = pca_features[:, 1]\n",
    "\n",
    "    # 군집 시각화\n",
    "    plt.figure(figsize=(10, 7))\n",
    "    plt.scatter(grouped['PCA1'], grouped['PCA2'], c=grouped['군집'], cmap='viridis')\n",
    "    plt.xlabel('PCA1')\n",
    "    plt.ylabel('PCA2')\n",
    "    plt.title(f'대여소 군집 결과 (PCA, n_clusters={n_clusters})')\n",
    "    plt.colorbar(label='군집')\n",
    "    plt.show()\n",
    "    \n",
    "    # 각 군집의 평균 값 계산 (대여대여소ID 제외)\n",
    "    grouped_means = grouped.drop(columns=['대여대여소ID', 'PCA1', 'PCA2']).groupby('군집').mean()\n",
    "\n",
    "    # # 컬럼 별로 가장 높은 값을 가진 군집의 셀에 파란색 배경 추가\n",
    "    # def highlight_max(s):\n",
    "    #     is_max = s == s.max()\n",
    "    #     return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "    # styled_means = grouped_means.style.apply(highlight_max)\n",
    "    \n",
    "    # 컬럼 별로 가장 높은 값을 가진 군집의 셀에 연한 초록색 배경 추가\n",
    "    def highlight_max(s):\n",
    "        is_max = s == s.max()\n",
    "        return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "    # 컬럼 별로 가장 낮은 값을 가진 군집의 셀에 연한 노랑색 배경 추가\n",
    "    def highlight_min(s):\n",
    "        is_min = s == s.min()\n",
    "        return ['background-color: #fffff0' if v else '' for v in is_min]\n",
    "\n",
    "    styled_means = grouped_means.style.apply(highlight_max).apply(highlight_min)\n",
    "\n",
    "    \n",
    "    # 결과 출력\n",
    "    print(f\"n_clusters = {n_clusters}일 때 각 군집의 평균 값:\")\n",
    "    display(styled_means)\n",
    "    \n",
    "    # 각 대여소가 속한 군집 저장\n",
    "    cluster_results[f'cluster_{n_clusters}'] = grouped[['대여대여소ID', '군집']].copy()\n",
    "\n",
    "# 결과 데이터프레임 확인\n",
    "df_out_2 = cluster_results['cluster_2']\n",
    "df_out_3 = cluster_results['cluster_3']\n",
    "df_out_4 = cluster_results['cluster_4']\n",
    "\n",
    "print(\"n_clusters = 2일 때 각 대여소가 속한 군집:\")\n",
    "print(df_out_2)\n",
    "\n",
    "print(\"n_clusters = 3일 때 각 대여소가 속한 군집:\")\n",
    "print(df_out_3)\n",
    "\n",
    "print(\"n_clusters = 4일 때 각 대여소가 속한 군집:\")\n",
    "print(df_out_4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. DB Scan 군집분석"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DBSCAN을 사용한 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<table id=\"T_c85b8\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_c85b8_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_c85b8_level0_col1\" class=\"col_heading level0 col1\" >평균이용시간</th>\n",
       "      <th id=\"T_c85b8_level0_col2\" class=\"col_heading level0 col2\" >이용시간표준편차</th>\n",
       "      <th id=\"T_c85b8_level0_col3\" class=\"col_heading level0 col3\" >평균이용거리</th>\n",
       "      <th id=\"T_c85b8_level0_col4\" class=\"col_heading level0 col4\" >이용거리표준편차</th>\n",
       "      <th id=\"T_c85b8_level0_col5\" class=\"col_heading level0 col5\" >주말대여비율</th>\n",
       "      <th id=\"T_c85b8_level0_col6\" class=\"col_heading level0 col6\" >점심시간대여비율</th>\n",
       "      <th id=\"T_c85b8_level0_col7\" class=\"col_heading level0 col7\" >새벽대여비율</th>\n",
       "      <th id=\"T_c85b8_level0_col8\" class=\"col_heading level0 col8\" >출근시간대여비율</th>\n",
       "      <th id=\"T_c85b8_level0_col9\" class=\"col_heading level0 col9\" >퇴근시간대여비율</th>\n",
       "      <th id=\"T_c85b8_level0_col10\" class=\"col_heading level0 col10\" >야간대여비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
       "      <th class=\"blank col9\" >&nbsp;</th>\n",
       "      <th class=\"blank col10\" >&nbsp;</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <td id=\"T_c85b8_row0_col0\" class=\"data row0 col0\" >21.983923</td>\n",
       "      <td id=\"T_c85b8_row0_col1\" class=\"data row0 col1\" >69.101059</td>\n",
       "      <td id=\"T_c85b8_row0_col2\" class=\"data row0 col2\" >59.732077</td>\n",
       "      <td id=\"T_c85b8_row0_col3\" class=\"data row0 col3\" >5818.241393</td>\n",
       "      <td id=\"T_c85b8_row0_col4\" class=\"data row0 col4\" >4072.451529</td>\n",
       "      <td id=\"T_c85b8_row0_col5\" class=\"data row0 col5\" >0.380687</td>\n",
       "      <td id=\"T_c85b8_row0_col6\" class=\"data row0 col6\" >0.130223</td>\n",
       "      <td id=\"T_c85b8_row0_col7\" class=\"data row0 col7\" >0.055440</td>\n",
       "      <td id=\"T_c85b8_row0_col8\" class=\"data row0 col8\" >0.027813</td>\n",
       "      <td id=\"T_c85b8_row0_col9\" class=\"data row0 col9\" >0.159854</td>\n",
       "      <td id=\"T_c85b8_row0_col10\" class=\"data row0 col10\" >0.236015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c85b8_level0_row1\" class=\"row_heading level0 row1\" >0</th>\n",
       "      <td id=\"T_c85b8_row1_col0\" class=\"data row1 col0\" >1.355932</td>\n",
       "      <td id=\"T_c85b8_row1_col1\" class=\"data row1 col1\" >36.045198</td>\n",
       "      <td id=\"T_c85b8_row1_col2\" class=\"data row1 col2\" >2.933670</td>\n",
       "      <td id=\"T_c85b8_row1_col3\" class=\"data row1 col3\" >3295.829609</td>\n",
       "      <td id=\"T_c85b8_row1_col4\" class=\"data row1 col4\" >131.661238</td>\n",
       "      <td id=\"T_c85b8_row1_col5\" class=\"data row1 col5\" >0.997579</td>\n",
       "      <td id=\"T_c85b8_row1_col6\" class=\"data row1 col6\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row1_col7\" class=\"data row1 col7\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row1_col8\" class=\"data row1 col8\" >0.000000</td>\n",
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       "      <td id=\"T_c85b8_row1_col10\" class=\"data row1 col10\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c85b8_level0_row2\" class=\"row_heading level0 row2\" >1</th>\n",
       "      <td id=\"T_c85b8_row2_col0\" class=\"data row2 col0\" >1.214286</td>\n",
       "      <td id=\"T_c85b8_row2_col1\" class=\"data row2 col1\" >19.535714</td>\n",
       "      <td id=\"T_c85b8_row2_col2\" class=\"data row2 col2\" >1.022293</td>\n",
       "      <td id=\"T_c85b8_row2_col3\" class=\"data row2 col3\" >1707.919464</td>\n",
       "      <td id=\"T_c85b8_row2_col4\" class=\"data row2 col4\" >92.455376</td>\n",
       "      <td id=\"T_c85b8_row2_col5\" class=\"data row2 col5\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row2_col6\" class=\"data row2 col6\" >1.000000</td>\n",
       "      <td id=\"T_c85b8_row2_col7\" class=\"data row2 col7\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row2_col8\" class=\"data row2 col8\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row2_col9\" class=\"data row2 col9\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row2_col10\" class=\"data row2 col10\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c85b8_level0_row3\" class=\"row_heading level0 row3\" >2</th>\n",
       "      <td id=\"T_c85b8_row3_col0\" class=\"data row3 col0\" >1.526882</td>\n",
       "      <td id=\"T_c85b8_row3_col1\" class=\"data row3 col1\" >27.973029</td>\n",
       "      <td id=\"T_c85b8_row3_col2\" class=\"data row3 col2\" >2.685334</td>\n",
       "      <td id=\"T_c85b8_row3_col3\" class=\"data row3 col3\" >2903.829837</td>\n",
       "      <td id=\"T_c85b8_row3_col4\" class=\"data row3 col4\" >193.771614</td>\n",
       "      <td id=\"T_c85b8_row3_col5\" class=\"data row3 col5\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row3_col6\" class=\"data row3 col6\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row3_col7\" class=\"data row3 col7\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row3_col8\" class=\"data row3 col8\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row3_col9\" class=\"data row3 col9\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row3_col10\" class=\"data row3 col10\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c85b8_level0_row4\" class=\"row_heading level0 row4\" >3</th>\n",
       "      <td id=\"T_c85b8_row4_col0\" class=\"data row4 col0\" >1.484848</td>\n",
       "      <td id=\"T_c85b8_row4_col1\" class=\"data row4 col1\" >31.743001</td>\n",
       "      <td id=\"T_c85b8_row4_col2\" class=\"data row4 col2\" >1.320349</td>\n",
       "      <td id=\"T_c85b8_row4_col3\" class=\"data row4 col3\" >2734.097554</td>\n",
       "      <td id=\"T_c85b8_row4_col4\" class=\"data row4 col4\" >211.973663</td>\n",
       "      <td id=\"T_c85b8_row4_col5\" class=\"data row4 col5\" >0.002165</td>\n",
       "      <td id=\"T_c85b8_row4_col6\" class=\"data row4 col6\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row4_col7\" class=\"data row4 col7\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row4_col8\" class=\"data row4 col8\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row4_col9\" class=\"data row4 col9\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row4_col10\" class=\"data row4 col10\" >1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c85b8_level0_row5\" class=\"row_heading level0 row5\" >4</th>\n",
       "      <td id=\"T_c85b8_row5_col0\" class=\"data row5 col0\" >1.318182</td>\n",
       "      <td id=\"T_c85b8_row5_col1\" class=\"data row5 col1\" >30.590909</td>\n",
       "      <td id=\"T_c85b8_row5_col2\" class=\"data row5 col2\" >0.464424</td>\n",
       "      <td id=\"T_c85b8_row5_col3\" class=\"data row5 col3\" >2358.645682</td>\n",
       "      <td id=\"T_c85b8_row5_col4\" class=\"data row5 col4\" >113.913103</td>\n",
       "      <td id=\"T_c85b8_row5_col5\" class=\"data row5 col5\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row5_col6\" class=\"data row5 col6\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row5_col7\" class=\"data row5 col7\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row5_col8\" class=\"data row5 col8\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row5_col9\" class=\"data row5 col9\" >1.000000</td>\n",
       "      <td id=\"T_c85b8_row5_col10\" class=\"data row5 col10\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c85b8_level0_row6\" class=\"row_heading level0 row6\" >5</th>\n",
       "      <td id=\"T_c85b8_row6_col0\" class=\"data row6 col0\" >1.100000</td>\n",
       "      <td id=\"T_c85b8_row6_col1\" class=\"data row6 col1\" >22.700000</td>\n",
       "      <td id=\"T_c85b8_row6_col2\" class=\"data row6 col2\" >1.202082</td>\n",
       "      <td id=\"T_c85b8_row6_col3\" class=\"data row6 col3\" >2505.301500</td>\n",
       "      <td id=\"T_c85b8_row6_col4\" class=\"data row6 col4\" >34.542166</td>\n",
       "      <td id=\"T_c85b8_row6_col5\" class=\"data row6 col5\" >1.000000</td>\n",
       "      <td id=\"T_c85b8_row6_col6\" class=\"data row6 col6\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row6_col7\" class=\"data row6 col7\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row6_col8\" class=\"data row6 col8\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row6_col9\" class=\"data row6 col9\" >0.000000</td>\n",
       "      <td id=\"T_c85b8_row6_col10\" class=\"data row6 col10\" >1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x232805fe4d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.cluster import DBSCAN\n",
    "from sklearn.decomposition import PCA\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 데이터 준비 및 전처리\n",
    "df1_out['대여일자'] = pd.to_datetime(df1_out['대여일자'])\n",
    "\n",
    "# 주중/주말 구분\n",
    "df1_out['주말여부'] = df1_out['대여요일'].isin(['Saturday', 'Sunday'])\n",
    "\n",
    "# 시간대 구분\n",
    "df1_out['점심시간'] = (df1_out['대여시간'] >= 12) & (df1_out['대여시간'] < 14)\n",
    "df1_out['새벽시간'] = (df1_out['대여시간'] >= 0) & (df1_out['대여시간'] < 6)\n",
    "df1_out['출근시간'] = (df1_out['대여시간'] >= 7) & (df1_out['대여시간'] < 9)\n",
    "df1_out['퇴근시간'] = (df1_out['대여시간'] >= 17) & (df1_out['대여시간'] < 19)\n",
    "df1_out['야간시간'] = (df1_out['대여시간'] >= 19) & (df1_out['대여시간'] < 24)\n",
    "\n",
    "# 대여대여소ID 기준 그룹화하여 통계 피처 생성\n",
    "grouped = df1_out.groupby('대여대여소ID').agg({\n",
    "    '대여일자': 'count',  # 총 대여 횟수\n",
    "    '이용시간(분)': ['mean', 'std'],  # 평균 이용시간 및 표준편차\n",
    "    '이용거리(M)': ['mean', 'std'],  # 평균 이용거리 및 표준편차\n",
    "    '주말여부': 'mean',  # 주말 대여 비율\n",
    "    '점심시간': 'mean',  # 점심시간 대여 비율\n",
    "    '새벽시간': 'mean',  # 새벽 대여 비율\n",
    "    '출근시간': 'mean',  # 출근 시간대 대여 비율\n",
    "    '퇴근시간': 'mean',  # 퇴근 시간대 대여 비율\n",
    "    '야간시간': 'mean'  # 야간 대여 비율\n",
    "}).reset_index()\n",
    "\n",
    "# 컬럼 이름 변경\n",
    "grouped.columns = [\n",
    "    '대여대여소ID', '총대여횟수', '평균이용시간', '이용시간표준편차',\n",
    "    '평균이용거리', '이용거리표준편차', '주말대여비율', '점심시간대여비율',\n",
    "    '새벽대여비율', '출근시간대여비율', '퇴근시간대여비율', '야간대여비율'\n",
    "]\n",
    "\n",
    "# null 값 제거\n",
    "grouped = grouped.fillna(0)\n",
    "\n",
    "# 군집분석에 사용할 피처 선택\n",
    "features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "# 표준화\n",
    "scaler = StandardScaler()\n",
    "scaled_features = scaler.fit_transform(features)\n",
    "\n",
    "# DBSCAN 군집분석 >> eps, min_samples 값 조정 필요!\n",
    "dbscan = DBSCAN(eps=0.7, min_samples=20)\n",
    "grouped['군집'] = dbscan.fit_predict(scaled_features)\n",
    "\n",
    "# PCA 적용\n",
    "pca = PCA(n_components=2)\n",
    "pca_features = pca.fit_transform(scaled_features)\n",
    "\n",
    "# PCA 결과를 데이터프레임에 추가\n",
    "grouped['PCA1'] = pca_features[:, 0]\n",
    "grouped['PCA2'] = pca_features[:, 1]\n",
    "\n",
    "# 군집 시각화\n",
    "plt.figure(figsize=(10, 7))\n",
    "plt.scatter(grouped['PCA1'], grouped['PCA2'], c=grouped['군집'], cmap='viridis')\n",
    "plt.xlabel('PCA1')\n",
    "plt.ylabel('PCA2')\n",
    "plt.title('대여소 군집 결과 (PCA, DBSCAN)')\n",
    "plt.colorbar(label='군집')\n",
    "plt.show()\n",
    "\n",
    "# 각 군집의 평균 값 계산 (대여대여소ID, PCA1, PCA2 제외)\n",
    "grouped_means = grouped.drop(columns=['대여대여소ID', 'PCA1', 'PCA2']).groupby('군집').mean()\n",
    "\n",
    "# 컬럼 별로 가장 높은 값을 가진 군집의 셀에 연한 초록색 배경 추가\n",
    "def highlight_max(s):\n",
    "    is_max = s == s.max()\n",
    "    return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "styled_means = grouped_means.style.apply(highlight_max)\n",
    "\n",
    "# 결과 출력\n",
    "print(\"DBSCAN을 사용한 각 군집의 평균 값:\")\n",
    "display(styled_means)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5. k-means 보완\n",
    "- 비율..이라고 해놓고 mean을 구해놓은 건에 대하여.. 새로고침"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      대여대여소ID  총대여횟수     평균이용시간       평균이용거리    주말대여비율   새벽대여비율    오전대여비율  \\\n",
      "0       ST-10    122  79.131148  5754.217869  0.336066  0.04918  0.032787   \n",
      "1     ST-1002      2  22.500000  3910.000000  0.000000  0.00000  1.000000   \n",
      "2     ST-1005      1  37.000000  3207.220000  1.000000  0.00000  0.000000   \n",
      "3     ST-1006      2  59.000000  1822.870000  1.000000  0.00000  0.000000   \n",
      "4     ST-1010      9   9.222222  1381.175556  0.222222  0.00000  0.000000   \n",
      "...       ...    ...        ...          ...       ...      ...       ...   \n",
      "1838   ST-991      1  41.000000  5870.390000  0.000000  0.00000  0.000000   \n",
      "1839   ST-992     10  25.300000  3244.275000  0.300000  0.20000  0.000000   \n",
      "1840   ST-993      1  13.000000  1360.000000  0.000000  0.00000  0.000000   \n",
      "1841   ST-994      2  14.000000  1760.000000  0.000000  0.00000  0.000000   \n",
      "1842   ST-996      1  11.000000  1280.240000  1.000000  0.00000  0.000000   \n",
      "\n",
      "        점심대여비율    오후대여비율    저녁대여비율    야간대여비율  \n",
      "0     0.245902  0.344262  0.237705  0.049180  \n",
      "1     0.000000  0.000000  0.000000  0.000000  \n",
      "2     0.000000  1.000000  0.000000  0.000000  \n",
      "3     0.000000  1.000000  0.000000  0.000000  \n",
      "4     0.555556  0.222222  0.000000  0.222222  \n",
      "...        ...       ...       ...       ...  \n",
      "1838  0.000000  1.000000  0.000000  0.000000  \n",
      "1839  0.200000  0.300000  0.300000  0.000000  \n",
      "1840  0.000000  1.000000  0.000000  0.000000  \n",
      "1841  0.000000  0.000000  1.000000  0.000000  \n",
      "1842  0.000000  1.000000  0.000000  0.000000  \n",
      "\n",
      "[1843 rows x 11 columns]\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "df1_out['대여일자'] = pd.to_datetime(df1_out['대여일자'])\n",
    "\n",
    "# 주중/주말 구분\n",
    "df1_out['주말여부'] = df1_out['대여요일'].isin(['Saturday', 'Sunday'])\n",
    "\n",
    "# 시간대 구분\n",
    "df1_out['새벽시간'] = (df1_out['대여시간'] >= 0) & (df1_out['대여시간'] < 6)\n",
    "df1_out['오전시간'] = (df1_out['대여시간'] >= 7) & (df1_out['대여시간'] < 10)\n",
    "df1_out['점심시간'] = (df1_out['대여시간'] >= 10) & (df1_out['대여시간'] < 14)\n",
    "df1_out['오후시간'] = (df1_out['대여시간'] >= 14) & (df1_out['대여시간'] < 18)\n",
    "df1_out['저녁시간'] = (df1_out['대여시간'] >= 18) & (df1_out['대여시간'] < 22)\n",
    "df1_out['야간시간'] = (df1_out['대여시간'] >= 22) & (df1_out['대여시간'] < 24)\n",
    "\n",
    "# 대여대여소ID 기준 그룹화하여 통계 피처 생성\n",
    "grouped = df1_out.groupby('대여대여소ID').agg({\n",
    "    '대여일자': 'count',  # 총 대여 횟수\n",
    "    '이용시간(분)': 'mean',  # 평균 이용시간\n",
    "    '이용거리(M)' : 'mean', # 평균 이용거리\n",
    "    '주말여부': lambda x: x.sum() / x.count(),  # 주말 대여 비율\n",
    "    '새벽시간': lambda x: x.sum() / x.count(),  # 새벽 대여 비율\n",
    "    '오전시간': lambda x: x.sum() / x.count(),  # 오전시간 대여 비율\n",
    "    '점심시간': lambda x: x.sum() / x.count(),  # 점심시간 대여 비율\n",
    "    '오후시간': lambda x: x.sum() / x.count(),  # 오후시간 대여 비율\n",
    "    '저녁시간': lambda x: x.sum() / x.count(),  # 퇴근 시간대 대여 비율\n",
    "    '야간시간': lambda x: x.sum() / x.count()   # 야간 대여 비율\n",
    "}).reset_index()\n",
    "\n",
    "# 컬럼 이름 변경\n",
    "grouped.columns = [\n",
    "    '대여대여소ID', '총대여횟수', '평균이용시간', '평균이용거리',\n",
    "    '주말대여비율', '새벽대여비율', '오전대여비율', '점심대여비율', '오후대여비율',\n",
    "    '저녁대여비율', '야간대여비율'\n",
    "]\n",
    "\n",
    "print(grouped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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WrFkYNWoUzp8/jy+//LLUrVFFad++PX788UcMGTIE1apVw9SpU/VUMZEZtcgUZfny5ZgwYQJat24NQPxP1t3dvVT/E1Or1TqdAYHSd/Sjiik1NRUNGjTQ2dq0aVPse9555x1Ur14dPXr0QJ8+fWBtbY2jR4/C3d1de860adOwcuVKbN68GW3btsXgwYNRrVo1HD9+vEDfmV69eiE5OVln/pgePXrg9u3bBW5FlMWYMWNQu3ZtTJo0qdjz2rRpg/379+PMmTPo2LEjunfvjvXr12PUqFE653399dc4dOgQnn32WZ2h5qWxZcsWvPLKK/jwww/RsmVLBAcHY/Dgwdi6dav2vx9LS0vs2bMHPj4+GDZsGLp06YJ79+5h1apVZfuDF2P48OHYtm0boqKi8Pzzz6Nnz5548OABjh8/Dh8fH9nXrVWrFv744w+MGTMGS5cuhb+/P5599lmEhoZi7Nix+P3337V9T/LbsGEDfvzxR/j7++P999/HG2+8gW+//VbnnDlz5sDa2hrPPvssfvjhB9k1FsbX1xerV6/GTz/9hNatW2PlypVYt26dXv6fNnDgQHz55ZeYNm1amW/xExVHJT35m7iSO3ToEN544w3ExMQAEE35p06d0unQmZaWhuXLl+uMIHjyfQAwbNgwtG3bVmf0R0hICG7fvo2VK1ca4U9DRJXBoUOH0LlzZzx8+BBVq1ZVuhwik2L2LTJ16tTBzJkzcf36de2WkJBQYBhkYVq3bo2oqCidY1FRUWUe3k1ERETymH2QGT16NEJDQ7XDJR8/fozt27eX6r2jRo3CwYMHtXN87NmzB5cuXcLQoUMNVi8RERHlMfvOvoGBgViwYAEGDRqER48ewd7eHiNGjED//v1LfG+9evUQHh6OiRMn4sGDB/D29sbOnTtLnHeEiIiI9MPs+sgQERFR5WH2t5aIiIjIdDHIEBERkcmq9H1kcnNzERcXBycnJ87vQkREZCIkSUJqairq1KlT7KSMlT7IxMXFFTsrKxEREVVct27dQr169Yp8vdIHGScnJwDii3B2dla4GgNQq4ENG8T+//4HWCn4I61ItRARkUlLSUmBh4eH9vd4USr9bxrN7SRnZ+fKG2Ts7cW+s7PyQaai1EJERJVCSd1C2NmXiIiITBaDDBEREZksBhkiIiIyWQwyREREZLIYZIiIiMhkMcgQERGRyWKQISIiIpPFIENEREQmi0GGiIiITBaDDBEREZksBpkymDsXCAkp/LWQEPE6ERERGQ+DTBlYWgKzZxcMMyEh4rilpTJ1ERERmSuu6lcGH34oHmfPFusjDhwIbNsGzJsHzJ+f9zoREREZB4NMGeUPM/Pni32GGCIiImXw1pIMH34IaFYVt7JiiCEiIlIKg4wMISGAJIl9tbroDsBERERkWAwyZaTp2Nu7t3ju61t4B2AiIiIyPAaZMtCEmPnzgXffFcfUavGcYYaIiMj42Nm3DHJy8jr23rsnjsXGAu+9l/c6ERERGQ+DTBnkn/DOzQ2oXh1ITARiYtjhl4iISAm8tSSTSgU0ayb2L1xQthYiIiJzxSBTDgwyREREymKQKQcGGSIiImUxyJQDgwwREZGyGGTKQRNkrl0D0tOVrYWIiMgcMciUQ82aYpMk4NIlpashIiIyPwwy5cTbS0RERMphkCknBhkiIiLlMMiUE4MMERGRchhkyolBhoiISDkMMuWkCTLXrwOPHilaChERkdlhkCmn6tUBd3exz5FLRERExsUgowe8vURERKQMBhk9YJAhIiJSBoOMHmiCTHS0snUQERGZGwYZPWCLDBERkTIYZPRAE2Ru3QJSUpSthYiIyJwwyOhB1apAnTpi/+JFRUshIiIyK4oGmcWLF6NJkyaoX78+nnrqKezYsaPQ886ePYu2bdvC09MTfn5+OHDggJErLRlvLxERERmfokEmICAAFy5cwM2bN/HVV19h+PDhSExM1DknNTUVQUFBWLBgAW7cuIEVK1Zg6NChuHv3rkJVF45BhoiIyPgUDTIdO3aEtbU1ACAwMBAODg5ISEjQOWfjxo1o06YNunXrpn1PYGAgfvrpJ6PXWxwGGSIiIuOzUroAAMjMzMQ333yDNm3awNfXV+e148ePo3379jrHAgICcO7cOSNWWDIGGSIiIuNTtEUmNjYWHh4ecHBwQHh4OL7++usC58THx6NWrVo6x9zc3ArcgtLIyspCSkqKzmYMfn7i8c4dICnJKB9JRERk9hQNMo0aNcKtW7eQnp6Ot99+G+3atcPff/+tc45arYYkSTrHcnJyoFKpCr3mwoUL4eLiot08PDwMVn9+Li5AvXpinyOXiIiIjKNCDL+2s7PDyJEj0bdvX6xbt07nNVdXV9y/f1/nWEJCAtw1KzU+Yfr06UhOTtZut27dMljdT+LtJSIiIuOqEEFGw9bWFvb29jrHWrdujaioKJ1jUVFRaNeuXZHXcHZ21tmMhUGGiIjIuBQLMnfu3MHGjRuhVqsBAEeOHMHWrVsxdOhQnfNGjRqFgwcPIiIiAgCwZ88eXLp0qcB5FQGDDBERkXEpNmrJ1tYWq1atQnBwMJycnODl5YWtW7eiSZMmCAsLw6lTpxAaGop69eohPDwcEydOxIMHD+Dt7Y2dO3fC0dFRqdKLxCBDRERkXCrpyZ60lUxKSgpcXFyQnJxs8NtMqamA5iMePACqVTPoxwlqNbB6tdh/5RXASsER9RWpFiIiMmml/f1dofrImDonJ6B+fbHPVhkiIiLDY5DRM95eIiIiMh4GGT1jkCEiIjIeBhk90wSZ6Ghl6yAiIjIHDDJ61ry5eGSLDBERkeExyOhZ06bi8d9/gScmJCYiIiI9Y5DRM0dHoEEDsc9WGSIiIsNikDEAdvglIiIyDgYZA2CQISIiMg4GGQNgkCEiIjIOBhkDYJAhIiIyDgYZA/D1BVQqMWrp33+VroaIiKjyYpAxAAcHoGFDsc9WGSIiIsNhkDEQ3l4iIiIyPAYZA2GQISIiMjwGGQNhkCEiIjI8BhkDyR9kJEnZWoiIiCorBhkD8fUFLCyABw+Ae/eUroaIiKhyYpAxEDs7oFEjsc/bS0RERIbBIGNA7CdDRERkWAwyBsQgQ0REZFgMMgbEIENERGRYDDIGpAky0dEcuURERGQIDDIG5OMDWFoCyclAXJzS1RAREVU+DDIGZGsLeHuLfd5eIiIi0j8GGQNjPxkiIiLDYZAxMAYZIiIiw2GQMbDmzcUjgwwREZH+McgYmKZF5uJFjlwiIiLSNwYZA2vcGLCyAlJSgNu3la6GiIiocmGQMTAbG6BJE7HP20tERET6xSBjBOzwS0REZBgMMkbAIENERGQYDDJGwCBDRERkGAwyRsCRS0RERIbBIGME3t6AtTXw6BFw86bS1RAREVUeDDJGYG0tFpAEeHuJiIhInxhkjIT9ZIiIiPSPQcZIGGSIiIj0j0HGSBhkiIiI9I9Bxkjyj1zKzVW2FiIiospCsSATERGB9u3bw9vbG40aNcKyZcsKPa958+aoVasWvLy84OXlhXbt2hm5Uv1o1EgsV5CeDly/rnQ1RERElYOVUh+8fft2rF69Gj4+Prh69SoCAwPRuHFj9OzZs8C54eHh6Ny5swJV6o+VFeDrC/z5p7i91LCh0hURERGZPsVaZEJDQ+Hz35jkhg0bYtiwYYiIiCj03KpVqxqxMsNhPxkiIiL9qjB9ZBISEuDi4lLoawwyREREVJgKEWROnjyJXbt2YeTIkQVeU6lU6NSpk7bV5sqVK8VeKysrCykpKTpbRcEgQ0REpF+KB5nw8HD069cP69atQ4MGDQq8fv78edy4cQMXLlzAM888g27duuHRo0dFXm/hwoVwcXHRbh4eHoYsv0w0QebSJSAnR9laiIiIKgPFgkxOTg4mTpyIefPmYf/+/ejXr1+h51lYiBLt7e0xffp0ODo64sSJE0Ved/r06UhOTtZut27dMkj9cjRsCNjZAZmZwLVrSldDRERk+hQbtTR58mRcvXoVp0+fhqOjY6nfp1arYWNjU+Trtra2sLW11UeJemdpKUYunTsnbi95eytdERERkWlTpEUmMzMTK1aswJo1a4oNMf/++y/+7//+D4Bowfn4449hYWGBNm3aGKtUvWveXDyynwwREVH5KdIic/XqVeTm5haY3M7HxwfTpk3DypUrsWnTJmRmZmL06NFITEyEnZ0d2rRpg/3798POzk6JsvWCHX6JiIj0R5Eg4+fnh9xi5unv2rUrAKB+/fqIjo42VllGwSBDRESkP4qPWjI3miATE8ORS0REROUlK8hkZGQgJ99v4VOnTiEyMlJvRVVmXl6AgwOQlQXExipdDRERkWmTFWSeeeYZ3L59G4BYM6lXr16YNGkSFi9erNfiKiMLC6BpU7HP20tERETlI7tFxtPTEwAwd+5c7NixA2fOnMG6dev0WlxlxX4yRERE+iGrs6+LiwsSExNx7tw52NjY4LnnngOACrUcQEXGIENERKQfsoLMlClT0KRJEzx+/BhbtmwBAFy5cgVVqlTRa3GVFYMMERGRfsgKMmPHjkVgYCCsrKxQv359AGIJAU2ooeJpgszly4BaDVgpNr8yERGRaZM9/LpOnTq4du0aNm/eDADw8PCAn5+f3gqrzOrXBxwdgexs4J9/lK6GiIjIdMkKMmfOnEHjxo3x3nvvYdKkSQCAHTt2ICQkRK/FVVYWFoAm81Wy+f6IiIiMSlaQmTRpEtasWYNTp07BwcEBANCrVy9s3LhRr8VVZuwnQ0REVH6ygszdu3fRrVs3AIBKpQIAWFtbIyMjQ3+VVXIMMkREROUnK8i4ubnh3LlzOseuXLlS7ErWpItBhoiIqPxkBZlPP/0UL7zwAubNm4e0tDR8+eWX6NWrF2bOnKnv+iotTZC5ckV0+iUiIqKykxVkAgMDcfjwYdy/fx/+/v7466+/sHbtWowYMULf9VVaHh6Ak5MYfv3330pXQ0REZJpkzWCSmZkJb29vLFu2THtMrVYjOzsbNjY2eiuuMlOpxMilEyfE7SVNCw0RERGVnqwWGX9/f9y4cUPn2OXLl9G3b1+9FGUu2E+GiIiofGQFmZSUFDRq1EjnWLNmzRAbG6uXoswFgwwREVH5yAoyTk5OSEpK0jmWnp6OnJwcfdRkNhhkiIiIykdWkBk1ahRGjx6tDTMZGRmYMGECevfurc/aKj1NkPn7byArS9laiIiITJGsIDNt2jR4enqiVq1a8PLygqurKx4+fIhPPvlE3/VVanXrAi4uQE6OGIZNREREZSMryFhZWWHZsmVISEjAli1bEBsbix07dsDZ2Vnf9VVqKhVvLxEREZWH7NWvAeDx48eoWbMm1Go1bt68iZs3b+qrLrPBIENERCSfrHlkDh8+jDFjxuDmzZuwtbXVHlepVEhPT9dbceaAQYaIiEg+WS0yEydOxJQpU5Ceno6MjAztxhBTdgwyRERE8slqkUlJScHbb7+t71rMkibI/PMPkJkJ2NkpWw8REZEpkdUi88wzz7A/jJ64uwPVqgG5ucDly0pXQ0REZFpktch069YNffr0wauvvoo6derovDZs2DC9FGYuNCOXjh0Tt5eeflrpioiIiEyHrCCzdetW1KhRA9u3b9c5rlKpGGRk0ASZ6GilKyEiIjItsoJMZGSkvuswa+zwS0REJI+sIKORlJSE7OxsnWNubm7lKsgcMcgQERHJIyvI/Prrrxg7dizu3btX4DUuHFl2miBz9SqQng44OChbDxERkamQFWSmTJmCr776CtnZ2YiOjsaUKVMwZ84cdO7cWd/1mQU3N6B6dSAxEYiJAVq1UroiIiIi0yBr+HVaWhoGDhwIPz8/3LhxA9WqVcPSpUvx4Ycf6rs+s8A1l4iIiOSRFWTs7e2RmpqKJk2a4M8//wQA5Obm4sGDB3otzpwwyBAREZWdrCAzYcIEbNmyBba2tmjevDl69OiBLl26oF27dvquz2wwyBAREZWdrD4yb731lnZ/zZo1CAsLQ1ZWFsaOHauvuswOgwwREVHZyWqR+fzzz7X71tbWePnllzFu3DisWrVKb4WZG02QuXYNSEtTthYiIiJTISvILFu2rMAxlUqFxYsXl7sgc1WzptgA4NIlZWshIiIyFWW6tTRq1Cg8fPgQ9+7dQ+/evXVeu3HjBpo0aaLX4sxNs2bAoUPi9pK/v9LVEBERVXxlCjJjxoxBXFwcTp06heHDh+u85urqih49eui1OHOTP8gQERFRycoUZDRB5fLlyxgzZoxBCjJn7PBLRERUNrL6yIwfPx6pqana55s3b8aaNWuQm5tb6mtERESgffv28Pb2RqNGjQrtdwMA169fR/fu3eHp6Qlvb2+EhYXJKdkkNG8uHhlkiIiISkdWkOnatSsyMzMBAKtWrcKMGTOwceNGTJs2rdTX2L59O1avXo1//vkHBw4cwKJFi7Bv3z6dc3JychAUFIRRo0bhxo0b2LFjB95++22cO3dOTtkVnqZF5sYN4NEjZWshIiIyBbKCTG5uLmr+N8Rm0aJF2LZtG/bu3Yvdu3eX+hqhoaHw8fEBADRs2BDDhg1DRESEzjkHDx6ElZWVdn4aPz8/vPTSS1i3bp2csis8V1fA3V3sX7yobC1ERESmQFaQqV69OmJjY7Fx40Z4enqiWbNmsLS0RHJysuxCEhIS4OLionPs+PHjaN++vc6xgICAStsiA7CfDBERUVnImtl33rx5eOqpp2BjY4ODBw8CAM6cOQN3TXNCGZ08eRK7du3C/PnzdY7Hx8ejbt26Osfc3NyQmJhY5LWysrKQlZWlfZ6SkiKrJqU0awYcPMggQ0REVBqyWmT69OmDxMRE3L17F61btwYANGrUCPv37y/ztcLDw9GvXz+sW7cODRo00HlNrVZDkiSdYzk5OVCpVEVeb+HChXBxcdFuHh4eZa5JSZoWmehoZesgIiIyBaVukUlLS4Ojo6P2ub29vc7rVatWLdMH5+Tk4K233kJkZCT279+Pp59+usA5rq6uuH//vs6xhISEYlt+pk+fjilTpmifp6SkmFSY4a0lIiKi0it1i0y/fv20+/b29nBwcNDZNMdKa/Lkybh69SpOnz5daIgBgNatWyMqKkrnWFRUVLGrbNva2sLZ2VlnMyWaIHP7NlCOLkdERERmodQtMj///LN2PyYmplwfmpmZiRUrVuDWrVs6rTxPCgoKwjvvvIOwsDC89NJLOH36NLZv346TJ0+W6/MrsqpVgTp1gLg4MXKpmMxGRERk9kodZKpVq6bd9/T0LNeHXr16Fbm5uQVaVnx8fDBt2jSsXLkSmzZtgoODA3bu3Ilx48ZhypQpcHd3x48//oh69eqV6/MrumbNRJC5cIFBhoiIqDilDjIvv/xysZ1sNVavXl3iOX5+fsXOAty1a1ftfuvWrfF///d/pSuykmjWDDhwgP1kiIiISlLqPjK+vr7w8fGBj48P7O3tsWvXLri5ucHHxwfW1tbYvXt3gVFHJA87/BIREZVOqVtk3n//fe1+ly5d8Ntvv6FFixbaYy+++CI2bNig3+rMFIMMERFR6ciaRyY2NlYnxABA586dcejQIX3UZPb8/MRjXByQlKRoKURERBWarCDj7OyMf/75R+fY7du3oVar9VKUuXNxATT9mdkqQ0REVDRZQWbGjBno3r07Vq5ciSNHjiAsLAwvvPCCdnFHKj/eXiIiIiqZrLWWRowYgRo1amD58uVYtmwZatSogTfffBNvvPGGvuszW82aAfv3M8gQEREVR1aQAYDu3buje/fuhb726aefYurUqbKLIrbIEBERlYasW0slWbFihSEua1YYZIiIiEpmkCDz5IrVVHaakUt37wIPHihbCxERUUVlkCBTmhmAqXhOTkD9+mKfrTJERESFM0iQIf3g7SUiIqLi8dZSBda8uXhkkCEiIiqcQYLMZ599ZojLmh22yBARERWv1MOv58+fX6rzZs+ejcGDB8suiPJogkx0tLJ1EBERVVSlDjLx8fHa/aSkJGzfvh39+vVDtWrVcPXqVZw4cQKjRo0ySJHmqmlT8ZiQILaaNZWth4iIqKIpdZDJPzfMgAEDsGvXLnTp0kV77Mcff8TZs2f1W52Zc3QEGjQArl0Tt5c6dVK6IiIioopFVh+Zs2fP6oQYABg5ciS2bdumj5ooH/aTISIiKpqsIGNvb4979+7pHEtKSkJaWppeiqI8DDJERERFkxVkJkyYgN69e+PXX3/FzZs3cezYMfTv3x8DBw7Ud31mj0GGiIioaLIWjQwODoaDgwOmTp2K2NhY1KxZE0OHDsW8efP0XZ/Zyx9kJAngpMlERER5ZK9+PW7cOIwbN06ftVAhfH1FeElMBP79F6hVS+mKiIiIKg7ZE+Lt2LEDL7/8MgYNGgQAuHbtGu7cuaO3wkhwcAAaNhT7vL1ERESkS1aQ+fTTTzF79mz4+/vj1KlTAIDk5GS89dZbei2OBPaTISIiKpysIPP999/j0KFDePPNN2FlJe5OtWzZEtGcgtYgGGSIiIgKJyvIqNVqVK1atcDxzMzM8tZDhWCQISIiKpysINO+fXvtCCXVf8NovvvuOzTXLNdMevXkyCUiIiISZI1aCg0NxcCBA7Fu3TrcvXsXrVq1QmZmJnbt2qXv+ghi5JKFBfDwIXD3LlC7ttIVERERVQyygkx8fDwiIiJw9uxZXL16FXXq1EFAQIC2vwzpl50d0KgR8PffolWGQYaIiEiQlTx69OiB27dvo3Xr1mjdurW+a6JCNGuWF2S6dVO6GiIioopBVh+Zjh074o8//tB3LVQMdvglIiIqSFaLjL29Pfr3749WrVrB09MTFhZ5eejrr7/WW3GUh0GGiIioIFlBxsPDAxMnTtR3LVQMrrlERERUkKwgM2fOHH3XQSXw8QEsLYHkZODOHaBePaUrIiIiUp7sYUZXrlzBxYsXkZ2drXN82LBh5S6KCrK1BRo3BmJiRKsMgwwREZHMIPPZZ58hJCQEbm5ukCQJjo6OuHz5Mp577jkGGQNq1iwvyLzwgtLVEBERKU/WqKWvvvoK0dHRWLZsGQYNGoTz58/j22+/RYcOHfRdH+XDDr9ERES6ZAUZSZLg4eEBb29vXLt2DQAwevRobNy4Ua/FkS4GGSIiIl2ybi3Vrl0bV69eRaNGjfDXX38hPT0dSUlJSE9P13d9lI8myFy8yJFLREREgMwWmQULFuDixYtQqVR47bXX4OHhAT8/P7z++uv6ro/yadwYsLICUlOBW7eUroaIiEh5slpkunbtqt1/7733MGjQIGRnZ8PX11dvhVFBNjZAkyaiRebCBaB+faUrIiIiUpasFpknNWzYkCHGSNhPhoiIKI+sIGNvbw8HB4dCt7KQJAnr169Hu3btijynSpUqqFu3Lry8vODl5YWhQ4fKKbnSYJAhIiLKI+vWUkxMjM7zxMREfP3112jZsmWpr7Fv3z5MnToVGRkZsLIqvoxjx46hQYMGckqtdBhkiIiI8shqkfH09NTZWrVqhe+//x579uwp9TXS0tKwaNEifP/99yWeW7VqVTllVkr5Ry7l5ipbCxERkdJkL1FQmNTU1FKfO3jwYADAoUOHij3PwsICLi4upb5uVlYWsrKytM9TUlJK/V5T4O0NWFsDaWnAzZuAF5cqICIiMyYryJw8eVLn+aNHj7Bt27Yy95EpDZVKhUaNGsHa2hrPP/88QkJCUKdOnSLPX7hwIebNm6f3OioKa2uxgGR0tLi9xCBDRETmTFaQGT58uM5zJycn+Pv7Y+3atfqoScfDhw9hYWGB5ORkzJo1C0FBQTh9+jRURcwGN336dEyZMkX7PCUlBR4eHnqvS0nNmuUFmT5cc4mIiMyYrCCjWZbAGCwsRDceFxcXhIaGwtnZWTurcGFsbW1ha2trtPqUwA6/REREgl7mkTGW3Nxc5ObmwsbGRulSFMUgQ0REJMhqkbGwsCjy1g4g5odRqVTIycmRXRgAxMbGIicnB02aNEFWVhamTJmCNm3aVLpbRWWlCTKXLomRSyaVRomIiPRI1u/A0NBQ9O/fH9HR0YiLi8Pvv/+OXr16Ydu2bYiLi0N8fDzi4uJkFRQWFobg4GAAwIMHD9C7d2/UrVsXTZs2RXZ2Nn7++WdZ161MGjUSyxWkpwPXrytdDRERkXJUkiRJZX2Tj48Pzp07B3t7e+2xBw8eoGfPngVGNCktJSUFLi4uSE5OhrOzs9Ll6M3TTwN//gns+EWNoITV4uArr4hVJZWiVgOrK0gtRERk0kr7+1tWi0xmZqZOiAEAV1dXxMfHy7kcycB+MkRERDKDTLNmzbBa8y/v/+zcuRM1a9bUS1FUsvwz/BIREZkrWW3/y5cvR9euXfH999/D19cXt2/fxqlTp7Bt2zY9l0dF0QkynZSshIiISDmygkzDhg0RExOD3bt3IzY2FoGBgdiwYQNq1aql7/qoCM2bi8eYmP9GLnHoEhERmSHZvTFtbW0xaNAgAEBcXBzS0tL0VhSVrEEDwM4OyMwEEhIAZkgiIjJHsv4d/9xzz+Gff/4BABw9ehQ+Pj4ICAgwyBIFVDhLS6BpU7Efxz7WRERkpmQFmZs3b8Lb2xsAMGvWLPzwww+4cuUKvvjiC33WRiXQ9JOJlzdlDxERkcmTdWvJ2dkZmZmZuHjxIhISEtCvXz8AQFJSkj5roxJogozMuQeJiIhMnqwgM3bsWLRs2RLJycn4/PPPAYh+MhbscWpUDDJERGTuZAWZadOmoU2bNrC1tcVzzz0HQMzAt2rVKr0WR8XTBJm7d4GcHMBS2XKIiIiMTvaopc6dO+s89/X1ha+vLwAgICAAJ06cKF9lVCIvL8DBHlBniJFL7koXREREZGQGWQzn33//NcRlKZ+5c/ONXPo/cXtJE2RCQkQLzdy5ytVHRERkDAbp1KJSqQxxWcrH0hKYPVsEFiBvCHZIiDhuyftMRERkBrg8sYn68EPxOG820ApiCPaCBcDsecD8+XmvExERVWYMMibsww+Bvy8B2AicPg2sOs0QQ0RE5qXUt5b++OOPUl9UkiRZxVDZLVokHiUA1lYMMUREZF5KHWSGDRum3W+qmRu/CNeuXZNfEZVJ/hHvj9WijwwREZG5KPWtJQ8PD8ydOxd+fn5ITEzEpk2bCj0vf+AhwwoJAebNAzZ0AiIPiWOzZ4tHtswQEZE5KHWQ2bBhA2bPno3Dhw/j0aNHWLFiRYFzVCoVg4yRaEYnhcwBRtQBkpOB1WeBp55imCEiIvNR6iDTsGFDhIWFARCT30VGRhqsKCpZTo7o2DtrOoDVQO/eAM4CFy4AwcF5w7KJiIgqM1mjlmJiYgCIZQlu3bqFBg0awMHBQa+FUfG0k92pxUP9+kDvXsDOvUBqKsCFyImIyBzImhDv0aNHGDZsGFxdXdG1a1dUq1YNEyZMQHZ2tr7rozKYPl08rl8P3LihbC1ERETGICvITJs2DQ4ODnj48CHu3r2L+/fvIzs7GyEcMqOodu2Arl0BtRpYvFjpaoiIiAxPVpDZv38/Vq5cCScnJwCAk5MTvvrqK2zZskWvxVHZzZolHletEusvERERVWay11qytbXVeW5nZ4f09PRyF0Tl07Ej0L49kJUFfPaZ0tUQEREZlqwgU79+fRw5ckTn2JEjR1C7dm29FEXyqVR5rTLffAMkJChbDxERkSHJGrX00UcfoX///njttdfg6+uLK1euYOXKldi8ebO+6yMZXngBaN0aOHMG+Pxz4OOPla6IiIjIMGS1yDz33HM4cuQI0tPTsXnzZjx48AC//fYbOnfurO/6SIb8rTLLlwMPHypbDxERkaHIXv26adOmCA0NLfS14ODgIl8j4+jXD2jeHIiOBpYty5vtl4iIqDKR3dm3ODt37jTEZakMLCyAmTPF/hdfiEnyiIiIKhuDBBlJkgxxWSqjoUOBxo3FraVClsYiIiIyeQYJMiqVyhCXpTKytARmzBD7S5YAHB1PRESVjUGCDFUco0YBXl7Av/8C33+vdDVERET6xVtLlZy1NfDBB2J/8WIxUR4REVFlYZAgEx4ebojLkkxjxwJ16gB37gDr1ildDRERkf7IGn6dnJyML7/8EufPny+wLMGePXsQEBCgl+JIP2xtgWnTgMmTgYULgZdfFi01REREpk5WkBk9ejTS0tIwYMAA7cKRVLGNGwd89BFw/TqwcSMwerTSFREREZWfrCBz6tQp3Lx5E1ZWsufTIyNzcADefVf0l/n4Y9EJ2NJS6aqIiIjKR1YfGXd3d2Sx16jJmTABqFYNuHwZ2LJF6WqIiIjKT1aQWbx4MQYOHIjt27fj5MmTOhtVXM7OQHCw2F+wAMjNVbYeIiKi8pIVZFJTU3Hq1Cm89tprGD58uHZ78cUXy3QdSZKwfv16tGvXrshzzp49i7Zt28LT0xN+fn44cOCAnJLpP2+9BTg5AX/9BezapXQ1RERE5SOrk0twcDDCwsLQp08f2R+8b98+TJ06FRkZGUX2tUlNTUVQUBDWrl2Lbt264fDhw+jfvz9iYmLg7u4u+7PNmasr8OabwCefiFaZoCCxWjYREZEpktUiY2NjU64QAwBpaWlYtGgRvi9mutmNGzeiTZs26NatGwCgY8eOCAwMxE8//VSuzzZ377wD2NsDp04BbOAiIiJTJivIDBs2DLt37y7XBw8ePBi9e/cu9pzjx4+jffv2OscCAgJw7ty5cn22uXNzA8aPF/sLFihbCxERUXnIurV09uxZhIaGwtfXF7Vq1dJ5bc+ePXopDADi4+PRpUsXnWNubm44ceJEke/JysrSGVGVkpKit3oqk/feA77+Gjh6FDhyBAgMVLoiIiKispMVZF588cUyd+yVQ61WF1i3KScnp9jVtRcuXIh58+YZujSTV7cu8MorwDffiFaZX39VuiIiIqKykxVkxowZo+86CuXq6or79+/rHEtISCi2o+/06dMxZcoU7fOUlBR4eHgYrEZT9v77wHffiX4yJ04AXFmCiIhMjawgs2nTpiJfGzZsmOxintS6dWtERUXpBJOoqCgMHz68yPfY2trC1tZWbzVUZl5ewP/+B6xdK5Yv2LFD6YqIiIjKRlaQWbFihc7zBw8e4MKFC2jfvr1eg8yoUaPwySefICIiAl26dMGePXtw6dIlDB06VG+fYe6mTxcrYu/cCZw7B7RsqXRFREREpScryERGRhY4FhERUe6RTAAQFhaGU6dOITQ0FPXq1UN4eDgmTpyIBw8ewNvbGzt37oSjo2O5P4eEJk2A4cOB8HCxBlMxjW1EREQVjkp6sjdtOfTu3Vuvo5b0ISUlBS4uLkhOToazs7PS5eifWg2sXi32X3kFkLGQ519/AS1aiInxLlwAmjZVrhYiIiKg9L+/Zc0jU5jU1FTcuXNHX5cjI3rqKWDAAECSgIULla6GiIio9GT9k3nixIk6zx89eoSIiAi8+uqreimKjG/mTGDbNuDHH4E5c4BGjZSuiIiIqGSygsyTk+A1btwYr732GgI5q5rJ8vcHevYE9u0DFi0Cvv1W6YqIiIhKVupbS1u2bMHly5cBAHPmzMGcOXPw1ltv4fbt2/jpp5+wf/9+5OTkGKxQMrxZs8Tj2rXArVuKlkJERFQqpQ4yb731FqpXr659LkkSBgwYgL///hsffPAB7ty5g5CQEIMUScbRvj3QqRPw+DHw6adKV0NERFSyUgcZlUqFGjVqaJ9v2LABMTEx2LlzJwYMGIAVK1bgl19+MUiRZDyaVpnvvgPu3lW2FiIiopKUOsi4uLho99VqNebPn48ZM2bAyckJAGBvb4/09HT9V0hG1aUL0LYtkJkJLF2qdDVERETFK3WQ6dixI77++muo1Wp88MEHUKlUmDRpkvb1tLQ0pKWlGaRIMh6VKq9V5uuvgcREZeshIiIqTqmDzPz58xEWFgZbW1ts2rQJP//8M6zyTXgWHh6OFi1aGKRIMq7evcVSBWlpQGio0tUQEREVrdRBpmbNmoiKisL9+/dx48YNPP300zqv9+nTBxs3btR7gWR8+VtlvvwSSE5Wth4iIqKilHlm32rVqkGlUhU47u7uDldXV70URcobOFAsVZCcDHz1ldLVEBERFU5vSxRQ5WJhIWb7BUSnX3Z/IiKiiohBhoo0fLhYqiAxEVi5UulqiIiICmKQoSJZWQHTp4v9Tz8VQ7KJiIgqEgYZKtb//gd4eIjJ8VavVroaIiIiXQwyVCwbG+D998X+okVAdray9RAREeXHIEMleuUVwN0duHkTCAtTuhoiIqI8DDJUInt74L33xP7ChYBarWw9REREGgwyVCrjxwPVqwP//ANs2qR0NURERAKDDJVKlSrAO++I/Y8+AnJzla2HiIgIYJChMpg0CXBxAS5eBLZtU7oaIiIiBhkqAxcX4O23xf6CBYAkKVsPERERgwyVSXAw4OgInD0L7N2rdDVERGTuGGSoTKpXByZOFPshIWyVISIiZTHIUJlNmQLY2QF//AFERipdDRERmTMGGSozd3dg3Dixv2CBsrUQEZF5Y5AhWaZOBaytRYvM778rXQ0REZkrBhmSxcMDGDtW7H/0kaKlEBGRGWOQIdk++ACwtBSjl86cUboaIiIyRwwyJFvDhsDIkWKfrTJERKQEBhkql+nTAZUK2LoViI5WuhoiIjI3DDJULk2bAkOGiP1PPlG2FiIiMj8MMlRurq7icdMm4N493ddCQoC5c41eEhERmQkGGSq3unXFY64E7NuXdzwkBJg9W3QIJiIiMgQGGSq3Dz8EXn9d7B8/Dty/LybKmz0bmD9fvE5ERGQIVkoXQJXDypXAod+A3KvAzJnAKjDEEBGR4bFFhvRm0ybxqFlH0skJyM1VrBwiIjIDDDKkNzt3ikfVf8/feQfo0QO4fVuxkoiIqJJjkCG9CAkB5s4D+vUDvvkG6NtHHD94EHjqKSA8XNn6iIiocmKQoXLTjE6aO0cEGJUK2LYNePtt8XpSEjBiBDBqlNgnIiLSFwYZKrecHNGxd9Ys3eOhocCcOUBgIGBhAfz4I9CihVgxm4iISB8UCzIZGRl4/fXX4enpiXr16mHatGmQJKnAeVWqVEHdunXh5eUFLy8vDB06VIFqqThz5xY9OmnuXODwYeD334FGjYBbt4CuXYH33gOysoxZJRERVUaKBZl3330Xubm5iI2NxYULFxAZGYnly5cXeu6xY8dw/fp1XL9+HZs3bzZypaQPbdsC584B48YBkgQsWQK0aQP89ZfSlRERkSlTJMg8evQI69atw+LFi2FlZQUXFxdMnz4dq1evLvT8qlWrGrdAMogqVYBvvwW2bwdq1hQhxt9fhBoO0yYiIjkUCTJnzpxBgwYN4KpZpAdAQEAAoqOjkZOTo3OuhYUFXFxcjF0iGVC/fiLE9O0LZGeL20xduwI3bypdGRERmRpFgkx8fDxq1aqlc8zNzQ1qtRrJyck6x1UqFRo1aoQmTZrg1VdfRVxcXLHXzsrKQkpKis5GFU+tWsCOHWJGYAcH4NAh0RH4xx+VroyIiEyJIkFGrVYX6NiraYlRqVQ6xx8+fIhr167h1KlTcHBwQFBQUKGdgjUWLlwIFxcX7ebh4aH/PwDphUol1mg6dw4ICACSk8UQ7REjgIcPla6OiIhMgSJBxtXVFffv39c5lpCQADs7uwK3kSwsRIkuLi4IDQ3F5cuXcfXq1SKvPX36dCQnJ2u3W7du6f8PQHrVuDFw7JgY4WRpKSbPe+opMZkeERFRcRQJMq1atcLly5fxMN8/u6OiohAQEKANLoXJzc1Fbm4ubGxsijzH1tYWzs7OOhtVfFZWYs6Z338XwebOHaBbN7HMQWam0tUREVFFpUiQcXd3R8+ePTFjxgyo1Wrcv38fH330ESZPnqxzXmxsLK5cuQJA9H0JDg5GmzZteLuoEgsIAM6eBd54Qzz/4gsxsun8eUXLIiKiCkqxeWRWrVqFuLg41K5dG/7+/nj99dcxYMAAhIWFITg4GADw4MED9O7dG3Xr1kXTpk2RnZ2Nn3/+WamSyUgcHYEVK4BduwA3N+DCBTHnzOLFYhZhIiIiDZVUXM/ZSiAlJQUuLi5ITk6unLeZ1GpAM//OK6+IezSVqJaEBDGJ3vbt4nlgILB+PeDpWe5LExFRBVba399ca4kqtJo1ga1bge+/Fy01R46IYdobNogZgomIyLwxyFCFp1IBr74q+sm0awekpACjRwPDhwOJiUpXR0RESmKQIZPRqJFokQkJEXetNm8Ww7R//VXpyoiISCkMMmRSrKyAWbOA48cBHx8gPh544QXg7beBjAylqyMiImNjkCGT5O8P/N//ARMniufLlgH16wMTJhR+fkiImHCPiIgqFwYZMlkODsBXXwF79gDu7sD9+8A33wDdu+sO0w4JAWbPFrMGExFR5cIgQyavVy+xmvagQeL5b78BDRsC167lhZj584EPP1S2TiIi0j8FJx0h0p8aNYCffwbWrQPGjwdu3hRhBgCGDQOmTFG2PiIiMgy2yFCloVIBY8cCMTFiX2PTJjEfzZAhYkHK1FTFSiQiIj1jkKFKJyxMTJZnbS2eV60qRjRt2QKMGCFCzYABwA8/AMnJSlZKRETlxSBDlUr+PjHZ2eIxKUksQjl9OuDtDWRliSUPXnpJrOUUFCSWPUhKUrp6IiIqKwYZqjQK69j74Yfi+TffAPb2wJUrYobgWbPEPDTZ2WJxyjFjRKjp3VssF/XggbJ/FiIiKh0GGao0cnIKH52kCTM5OaLvTIsWIvRcugRER4v5ZZo1Ax4/BvbuFcsh1KolJtr77jsxrJuIiComrn5t6ir56tfGdOmS6Efz88+i1UbD0hLo1El0Fh44UIQcIiIyLK5+TVRGTZuKW07nzolbUB9/DLRqJVpyDh4UswbXqQN07iwm4ouPV7piIiJikCEqROPGonPwmTNAbCyweDHQpg2QmwscOgRMmgTUrQsEBgJffgncvq37/rlzxe2rwnC5BCIi/WGQISpBw4bA1KnAyZPA9evAkiVAu3ZiiPfRo0BwMODhATz3HPD552IyPktL0fH4yTDD5RKIiPSLQYaoDDw9xSzBUVEisHzxBdChg+hEfPy4eM3TU4yE6tFDN8xwuQQiIv1jkCGSycNDtMYcPSpuLS1bBnTsKELNyZPAr7+K82bPFv2eZ88WLTsMMURE+sMgQ6QHdeqIfjOHDgFxccDXXwNdugAW//0XplmN+9NPRd+a/v1FC83evUBCgmJlExGZPNMaH0tkAtzdxQinCROADz4AFi0SgSY3V7TWxMUBO3aITaN+fcDfX3Qo9vcHWrcGqlVT7s9ARGQqGGSIDCQkRIQYTZ8YTR+Z114DmjcHTp8W2+XLor/NzZvAL7/kvb9RIxFqNFurVkBlnAqJiKg8GGSIDKCo5RKAvOMbNojnKSnA2bPAqVN54SY2Nm/76ae86/r46IabZ54BHB2N+2cjIqpIGGSIDKC45RI0r2s4O4tOwh075h178AD4v//LCzanTwM3bojWm8uXxcrdgLhl5eenG26efhqws8u71ty5Yrh3YZ2MQ0JELZzXhohMFYMMkQEUFwxKM2rJ1RXo1k1sGgkJYoK+06fzWm/i4sR6UdHRwNq14jwrK3HrShNs7t0Ti2Y++dn5W42IiEwVgwyRiahZE+jZU2wacXF54UYTcBISxDIL584B338vztNM0Ldzp1jp+/RpEXzmzeNwcCIybQwyRCasTh2xBQWJ55Ik5rTJH2xOnwYePhSvnzolNo2lS4E9e8Q6U02bAr6+4rFBA5Nb85OIzBT/V0VUiahUYqI+Dw+xUjcgws21ayLQjByZ1z/HwgJITgZOnBBbfjY2Yr0pTcDRhBwfH8DBwbh/JiKi4jDIEFVyKpVYL+qHH0SIsbEBsrPFSt9DhwKXLoktJkY8Xr4MZGQAFy6I7clreXrmtdzkDzk1ahRfBzsdE5EhMMgQmYEnh4NrnltZFQwWubliThtNwMkfchITxcKZ168D+/bpvq9GDd3bU5r9+vVF64+mnw7ATsdEpD8MMkSVXElz2uR/DojQ4eUltl69dK+VkJAXavKHnBs3gPv3xbpTR4/qvsfBQdySatpULNswezbw77/AZ58BixdzIU0iKh8GGaJKrixz2pSkZk2xPf+87vG0NHFLKn/IiYkBrlwB0tPFhH9nz+adv3y52ACxpMPx42LG49q18zowa/Zr1QKsrcv+5y4Ob3MRVR4MMkSVXHnntCkNR0exhEKrVrrH1Wrg6lXd21OXLonVwTXu3hWLZxZFpRLh6cmA8+R+rVqlH2nF21xElQeDDBEZjJUV0KSJ2Pr3F8dCQkSQ0XQ6/t//gE6dxJw48fHiUbMfHy/C0L//iu3cuaI/S6UC3NyKDzu1a4vAU9ittcJuwRkDW4eIyodBhoiMpqhOx40bF/6LPDdX9L3JH3CKCjw5OWIW43v3dG9jPUmlEmGmdm0RsGbPFhMD5uQAvXsDdesCmzYBVaoUvjk6iuChLxWldYiBikwVgwwRGUVZOx0DouOxm5vYnn666Gvn5oqOyE8GnCf3794Vv5Dv3hWbhqaf0J49YiuJvX3RQaeozcmp8OOTJonPV7p1qKIEKqKyYpAhIqPQZ6fjJ1lYiFaWWrWAli2Lr+H+/byA8913wPbt4pd4To5Yo8rTE3j0qPBNU2NGhtgSEuTX/CRNkNCECTc3YPduICJCBKcnNweHwo+X5jVbW9EylR9vt5GpYpAhIqMwRqfjklha5gWeXbtEiHnyNtewYYXXI0lAVlbRIae4LTW16Neys8X1nwxymn5BhqBSiRXSCws5Xl7ie5g7V7R0tW4tAtv77xcdjuztC79e/q0st+MqUusQQ1XFxyBDRGZHzm0uzS9/O7uSZzEui+xsMXz9o4+AJUvEUPPHj4HRo4HBg0XLT3p6XitQYVtxr+d/TROWJCnvWFFyc8XjmTNiKy9r6+KDzpNbu3biZ3HokJjPKDJS3PYbNEj0bdq2TbQs2dqKn4lmP/+mOW5jI1rt5KgooaoiBaqKVAvAIENEZsiQt7nKysYGWLRIhJgnW4e8vfXbWvX4cckBKCwM2LxZjDhTq4GuXYG2bYsPUkVtmtYmzWc/fgykpJSt5ogIsWn88ovYysrauvjgU1wY0oSqiAjghReAI0fElAGDBonJHnfuzGuRKurR1lZ+mAIqTqCqaLUADDJEZIYqwm0uDTmtQ3JZW4vN2bnoWjZvLhioOnYEFiwo++fl5ACZmWULP0+ev3y5aB2ysAD69hW39/JvmZmFH8sfooC8IPXoUdn/HBqHDolNo6yhShOMigo8JYWhnj3Fz+PsWXELdOtWMcJu+HDRv2v7dtFyaGGR91jUfnlef/FFsVzJ7NnAw4dAcDCwZo0Y/afELN2KBZmMjAwEBwdj//79yMnJwciRI7Fo0SKonuiBdvbsWUyYMAHx8fFwdHREaGgounfvrlDVRET6VVFahwwRqCwtxXB1R0f5NeXm5s055O9f+hokSbynpNBTXBh68tiXX+aFqn79dINXUY/5f36a6yQny/s+NLZuFZvGTz+JTQmffy42QLmlRhQLMu+++y5yc3MRGxuLtLQ0dOvWDcuXL8dbb72lPSc1NRVBQUFYu3YtunXrhsOHD6N///6IiYmBu7u7UqUTEelNRWkdqiiBSqOoOYfy11QclSrv9pC+6skfqlq1Kl0danXRQaekEFTU47ZtIqipVGK5kNxc8Tw3V3e/sGP6fl3TwmVtreB6aZICUlNTJQcHBykxMVF7bMuWLVLLli11zlu5cqU0YMAAnWNBQUHSF198UerPSk5OlgBIycnJ5Su6onr8WJJWrhTb48eshYhM3vz5kgSIx9IcN3Y9StWR/7NtbJSrwVi1lPb3tyItMmfOnEGDBg3g6uqqPRYQEIDo6Gjk5OTA8r9xesePH0f79u113hsQEIBzxc1TTkREJq0itQ4Zsw9TWWspaytVZa1FkSATHx+PWrVq6Rxzc3ODWq1GcnKyNuDEx8ejS5cuBc47ceJEkdfOyspCVlaW9nlKWbvIExGRoirK7Tag4oSqihyolKwFUCjIqNVqSJKkcyznv78N+Tv7FnXekx2C81u4cCHmzZunx2qJiMhcVZRQVVECVUWrBVAoyLi6uuL+/fs6xxISEmBnZwcXF5cSzyuuo+/06dMxZcoU7fOUlBR4eHjoqXIiIiLjqyiBCqhYtQBAOabnka9Vq1a4fPkyHj58qD0WFRWFgIAAWOSbMah169aIiorSeW9UVBTatWtX5LVtbW3h7OyssxEREVHlpEiQcXd3R8+ePTFjxgyo1Wrcv38fH330ESZPnqxz3qhRo3Dw4EFE/Det4549e3Dp0iUMHTpUgaqJiIioolEkyADAqlWrEBcXh9q1a8Pf3x+vv/46BgwYgLCwMAQHBwMA6tWrh/DwcEycOBFubm5YsGABdu7cCUe5sysRERFRpaKSnuxNW8mkpKTAxcUFycnJlfM2k1oNrF4t9l95RSyQwlqIiMjElfb3t2ItMkRERETlxSBDREREJotBhoiIiEwWgwwRERGZLAYZIiIiMlkMMkRERGSyKv34WM3o8kq7eKRaDWRkiP2UFOWHX1eUWoiIyKRpfm+XNEtMpZ9H5vbt21xriYiIyETdunUL9erVK/L1Sh9kcnNzERcXBycnp2JXzTZlmoUxb926VTkn/ZOB30nh+L0UxO+kIH4nheP3UpAhvxNJkpCamoo6derorMP4pErf9m9hYVFskqtMuEhmQfxOCsfvpSB+JwXxOykcv5eCDPWduLi4lHgOO/sSERGRyWKQISIiIpPFIFMJ2NraYs6cObC1tVW6lAqD30nh+L0UxO+kIH4nheP3UlBF+E4qfWdfIiIiqrzYIkNEREQmi0GGiIiITBaDDBEREZksBhkTFxERgfbt28Pb2xuNGjXCsmXLlC6pQpkwYQJ8fX2VLqPCOHnyJAIDA+Hp6Yk6dergl19+UbokRd25cwdBQUGoW7cuGjZsiJCQEKVLUoQkSVi/fj3atWunc/zs2bNo27YtPD094efnhwMHDihUoTIK+14eP36M+fPn46mnnoKHhweef/55nDt3TrkijayovysaaWlpqFmzJj755BOj1VTpJ8Sr7LZv347Vq1fDx8cHV69eRWBgIBo3boyePXsqXZribt26hfXr13OJiv/ExMRgwIABWL9+Pbp164bs7GwkJSUpXZaiRo8eDX9/f+zYsQMPHz5Ely5d4OHhgbFjxypdmtHs27cPU6dORUZGBqzyrY+WmpqKoKAgrF27Ft26dcPhw4fRv39/xMTEwN3dXcGKjaOo7+XKlStQq9X4448/4OjoiJUrVyIoKAhXr16FtbW1ghUbXlHfSX5fffUVHj58aNS6OGqpkpkyZQqsrKywePFipUtR3JAhQ+Du7o7ffvsNMTExSpejuMGDB8Pf3x/Tp09XupQKw9XVFUeOHEHz5s0BALNmzUJSUhKWL1+ucGXGs2XLFtjb28PBwQFvvPGG9r+Vb7/9Fnv37sXWrVu15/br1w9du3ZFcHCwUuUaTVHfS2FcXV1x7Ngx+Pn5GbFC4yvpO4mLi0Pnzp3RvHlztGnTBh988IFR6uKtpUomISGhVFM6V3a7d+9GYmIihgwZonQpFUJmZiZ27dqFl19+WelSKpQhQ4Zg+fLlyM7Oxo0bN7B9+3az+zszePBg9O7du8Dx48ePo3379jrHAgICzOY2SlHfy5PS09ORnp5uFv/fLek7mTx5MmbMmAEnJycjVsUgU6mcPHkSu3btwsiRI5UuRVGJiYl4++23sWLFCqVLqTCuXLkCe3t7REZGokWLFmjYsCHGjx+PlJQUpUtT1EcffYR9+/ahWrVqaNCgATp37oxOnTopXVaFEB8fj1q1aukcc3NzQ2JiokIVVUwzZ85Ep06dULduXaVLUdSPP/6IxMREjB492uifzSBTSYSHh6Nfv35Yt24dGjRooHQ5ipEkCa+++iomT57MTr75pKamQq1W4/Tp0zh58iTOnz+PhIQEs7hFUJScnBz07t0bkydPRnJyMu7cuYPz588jNDRU6dIqBLVajSd7HuTk5EClUilUUcWSlpaGMWPG4PDhw9iwYYPS5Sjq2rVrmDlzJtauXavI3w8GGROXk5ODiRMnYt68edi/fz/69eundEmK+uSTT/D48WNMmjRJ6VIqlBo1auDx48f45JNPYGdnBycnJ8ydOxc7duxQujTFREREIDs7G5MnT4aVlRVq166NpUuXsn/Zf1xdXXH//n2dYwkJCWbR0bcksbGxaNOmDaytrXHs2DHUrFlT6ZIUk5GRgUGDBmHRokWKDazgqCUTN3nyZFy9ehWnT5+Go6Oj0uUo7ssvv0RaWhqqVasGQPyrMiMjA1WrVsWpU6fQuHFjhStUhqenJ2xsbJCZmakdWWFhYQE7OzuFK1NOdnZ2gZEX1tbWyM7OVqiiiqV169aIiorClClTtMeioqIwfPhwBatSXlJSErp06YJZs2Zh3LhxSpejuIMHDyImJgavv/46Xn/9dQCi35ClpSUOHjxolCH7bJExYZmZmVixYgXWrFnDEPOf+Ph4pKSkICkpCUlJSdi1axcaN26MpKQksw0xAGBnZ4fRo0fj3XffhVqtRlZWFubMmYOXXnpJ6dIU06FDB9y9excbN24EADx69AgzZ840u86+RRk1ahQOHjyIiIgIAMCePXtw6dIlDB06VOHKlLV582b4+voyxPynb9++yMjI0P4/NykpCSNHjsScOXOMNu8Qg4wJu3r1KnJzc9GuXTt4eXlptxdeeEHp0qgCWrRoETIyMlC3bl00a9YM3t7eZjsBHAC4uLhg//79WLNmDby8vNCiRQt4e3tjyZIlSpdWIdSrVw/h4eGYOHEi3NzcsGDBAuzcudPs/9H0999/4/jx4zr/z/Xy8sJ3332ndGlmi/PIEBERkcliiwwRERGZLAYZIiIiMlkMMkRERGSyGGSIiIjIZDHIEBERkclikCEiIiKTxSBDREREJotBhohMjpeXF/744w+lyyCiCoBBhoiIiEwWgwwRERGZLAYZIjJpR44cgZubG44ePap0KUSkAAYZIjJZp0+fxvDhw7F582Y8//zzSpdDRApgkCEik3Tx4kUMGjQIP/zwAzp27Kh0OUSkEK5+TUQmx8vLCxkZGejfvz++/fZbpcshIgWxRYaITNI333yDyMhIfPbZZ0qXQkQKslK6ACIiOWrXro2DBw9q+8a89957CldEREpgkCEik1W/fn0cPHgQgYGBABhmiMwR+8gQERGRyWIfGSIiIjJZDDJERERkshhkiIiIyGQxyBAREZHJYpAhIiIik8UgQ0RERCaLQYaIiIhMFoMMERERmSwGGSIiIjJZDDJERERkshhkiIiIyGQxyBAREZHJ+n81DjNlvzrYKwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "# 군집분석에 사용할 피처 선택\n",
    "features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "sum_of_squared_distances = []\n",
    "K = range(1, 15)\n",
    "for k in K:\n",
    "    km = KMeans(n_clusters = k)\n",
    "    km = km.fit(features)\n",
    "    sum_of_squared_distances.append(km.inertia_)\n",
    "    \n",
    "# 시각화\n",
    "\n",
    "plt.plot(K, sum_of_squared_distances, 'bx-')\n",
    "plt.xlabel('k')\n",
    "plt.ylabel('Sum_of_squared_distances')\n",
    "plt.title('Elbow Method For Optimal k')\n",
    "plt.axvline(2,c= 'r',alpha =0.4)\n",
    "plt.axvline(3,c= 'r',alpha =0.4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "k : 2 score : 0.7021455505846309\n",
      "k : 3 score : 0.5898948354135013\n",
      "k : 4 score : 0.5785144202753115\n",
      "k : 5 score : 0.5586525086004476\n",
      "k : 6 score : 0.5331808325690884\n",
      "k : 7 score : 0.535029768724388\n",
      "k : 8 score : 0.5376623167040239\n",
      "k : 9 score : 0.5346894929728859\n",
      "k : 10 score : 0.5228478615790602\n",
      "k : 11 score : 0.5225641130381654\n",
      "k : 12 score : 0.5258821143667881\n",
      "k : 13 score : 0.5179064213131632\n",
      "best n : 2 best score : 0.7021455505846309\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import silhouette_score\n",
    "k_range = range(2,14)\n",
    "\n",
    "best_n = -1\n",
    "best_silhouette_score = -1\n",
    "\n",
    "for k in k_range:\n",
    "\n",
    "  kmeans = KMeans(n_clusters=k, random_state=200)\n",
    "  kmeans.fit(features)\n",
    "  clusters = kmeans.predict(features)\n",
    "\n",
    "  score = silhouette_score(features, clusters)\n",
    "  print('k :',  k, 'score :', score)\n",
    "\n",
    "  if score > best_silhouette_score:\n",
    "    best_n = k\n",
    "    best_silhouette_score = score\n",
    "\n",
    "print('best n :', best_n, 'best score :', best_silhouette_score )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      대여대여소ID  총대여횟수     평균이용시간       평균이용거리    주말대여비율   새벽대여비율    오전대여비율  \\\n",
      "0       ST-10    122  79.131148  5754.217869  0.336066  0.04918  0.032787   \n",
      "1     ST-1002      2  22.500000  3910.000000  0.000000  0.00000  1.000000   \n",
      "2     ST-1005      1  37.000000  3207.220000  1.000000  0.00000  0.000000   \n",
      "3     ST-1006      2  59.000000  1822.870000  1.000000  0.00000  0.000000   \n",
      "4     ST-1010      9   9.222222  1381.175556  0.222222  0.00000  0.000000   \n",
      "...       ...    ...        ...          ...       ...      ...       ...   \n",
      "1838   ST-991      1  41.000000  5870.390000  0.000000  0.00000  0.000000   \n",
      "1839   ST-992     10  25.300000  3244.275000  0.300000  0.20000  0.000000   \n",
      "1840   ST-993      1  13.000000  1360.000000  0.000000  0.00000  0.000000   \n",
      "1841   ST-994      2  14.000000  1760.000000  0.000000  0.00000  0.000000   \n",
      "1842   ST-996      1  11.000000  1280.240000  1.000000  0.00000  0.000000   \n",
      "\n",
      "        점심대여비율    오후대여비율    저녁대여비율    야간대여비율  군집      PCA1      PCA2  \n",
      "0     0.245902  0.344262  0.237705  0.049180   2  0.245833 -0.141989  \n",
      "1     0.000000  0.000000  0.000000  0.000000   2 -0.660566  0.713492  \n",
      "2     0.000000  1.000000  0.000000  0.000000   0  0.439748 -2.719725  \n",
      "3     0.000000  1.000000  0.000000  0.000000   0  0.408740 -2.723297  \n",
      "4     0.555556  0.222222  0.000000  0.222222   1 -0.842512  0.332279  \n",
      "...        ...       ...       ...       ...  ..       ...       ...  \n",
      "1838  0.000000  1.000000  0.000000  0.000000   0  0.430901 -2.429184  \n",
      "1839  0.200000  0.300000  0.300000  0.000000   1 -0.719402 -0.060928  \n",
      "1840  0.000000  1.000000  0.000000  0.000000   0 -0.434010 -2.655542  \n",
      "1841  0.000000  0.000000  1.000000  0.000000   1 -2.037697  1.071950  \n",
      "1842  0.000000  1.000000  0.000000  0.000000   0 -0.037295 -2.847305  \n",
      "\n",
      "[1843 rows x 14 columns]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "# 군집분석에 사용할 피처 선택\n",
    "features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "# 표준화\n",
    "scaler = StandardScaler()\n",
    "scaled_features = scaler.fit_transform(features)\n",
    "\n",
    "# K-means 군집분석\n",
    "kmeans = KMeans(n_clusters=4, random_state=42)\n",
    "grouped['군집'] = kmeans.fit_predict(scaled_features)\n",
    "\n",
    "# PCA 적용\n",
    "pca = PCA(n_components=2)\n",
    "pca_features = pca.fit_transform(scaled_features)\n",
    "\n",
    "# PCA 결과를 데이터프레임에 추가\n",
    "grouped['PCA1'] = pca_features[:, 0]\n",
    "grouped['PCA2'] = pca_features[:, 1]\n",
    "\n",
    "# 결과 출력\n",
    "print(grouped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 2일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_911e9_row0_col0, #T_911e9_row0_col4, #T_911e9_row0_col5, #T_911e9_row0_col6, #T_911e9_row0_col8, #T_911e9_row0_col9, #T_911e9_row1_col1, #T_911e9_row1_col2, #T_911e9_row1_col3, #T_911e9_row1_col7 {\n",
       "  background-color: #fffff0;\n",
       "}\n",
       "#T_911e9_row0_col1, #T_911e9_row0_col2, #T_911e9_row0_col3, #T_911e9_row0_col7, #T_911e9_row1_col0, #T_911e9_row1_col4, #T_911e9_row1_col5, #T_911e9_row1_col6, #T_911e9_row1_col8, #T_911e9_row1_col9 {\n",
       "  background-color: #ccffcc;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_911e9\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_911e9_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_911e9_level0_col1\" class=\"col_heading level0 col1\" >평균이용시간</th>\n",
       "      <th id=\"T_911e9_level0_col2\" class=\"col_heading level0 col2\" >평균이용거리</th>\n",
       "      <th id=\"T_911e9_level0_col3\" class=\"col_heading level0 col3\" >주말대여비율</th>\n",
       "      <th id=\"T_911e9_level0_col4\" class=\"col_heading level0 col4\" >새벽대여비율</th>\n",
       "      <th id=\"T_911e9_level0_col5\" class=\"col_heading level0 col5\" >오전대여비율</th>\n",
       "      <th id=\"T_911e9_level0_col6\" class=\"col_heading level0 col6\" >점심대여비율</th>\n",
       "      <th id=\"T_911e9_level0_col7\" class=\"col_heading level0 col7\" >오후대여비율</th>\n",
       "      <th id=\"T_911e9_level0_col8\" class=\"col_heading level0 col8\" >저녁대여비율</th>\n",
       "      <th id=\"T_911e9_level0_col9\" class=\"col_heading level0 col9\" >야간대여비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
       "      <th class=\"blank col9\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_911e9_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_911e9_row0_col0\" class=\"data row0 col0\" >10.470890</td>\n",
       "      <td id=\"T_911e9_row0_col1\" class=\"data row0 col1\" >66.785920</td>\n",
       "      <td id=\"T_911e9_row0_col2\" class=\"data row0 col2\" >5722.842685</td>\n",
       "      <td id=\"T_911e9_row0_col3\" class=\"data row0 col3\" >0.374960</td>\n",
       "      <td id=\"T_911e9_row0_col4\" class=\"data row0 col4\" >0.019814</td>\n",
       "      <td id=\"T_911e9_row0_col5\" class=\"data row0 col5\" >0.023130</td>\n",
       "      <td id=\"T_911e9_row0_col6\" class=\"data row0 col6\" >0.112640</td>\n",
       "      <td id=\"T_911e9_row0_col7\" class=\"data row0 col7\" >0.688650</td>\n",
       "      <td id=\"T_911e9_row0_col8\" class=\"data row0 col8\" >0.119278</td>\n",
       "      <td id=\"T_911e9_row0_col9\" class=\"data row0 col9\" >0.018742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_911e9_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_911e9_row1_col0\" class=\"data row1 col0\" >22.617156</td>\n",
       "      <td id=\"T_911e9_row1_col1\" class=\"data row1 col1\" >61.117050</td>\n",
       "      <td id=\"T_911e9_row1_col2\" class=\"data row1 col2\" >5162.830642</td>\n",
       "      <td id=\"T_911e9_row1_col3\" class=\"data row1 col3\" >0.359009</td>\n",
       "      <td id=\"T_911e9_row1_col4\" class=\"data row1 col4\" >0.059284</td>\n",
       "      <td id=\"T_911e9_row1_col5\" class=\"data row1 col5\" >0.064739</td>\n",
       "      <td id=\"T_911e9_row1_col6\" class=\"data row1 col6\" >0.284299</td>\n",
       "      <td id=\"T_911e9_row1_col7\" class=\"data row1 col7\" >0.156690</td>\n",
       "      <td id=\"T_911e9_row1_col8\" class=\"data row1 col8\" >0.302855</td>\n",
       "      <td id=\"T_911e9_row1_col9\" class=\"data row1 col9\" >0.091343</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x274751e1050>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 3일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
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       "<table id=\"T_9bb8f\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_9bb8f_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_9bb8f_level0_col1\" class=\"col_heading level0 col1\" >평균이용시간</th>\n",
       "      <th id=\"T_9bb8f_level0_col2\" class=\"col_heading level0 col2\" >평균이용거리</th>\n",
       "      <th id=\"T_9bb8f_level0_col3\" class=\"col_heading level0 col3\" >주말대여비율</th>\n",
       "      <th id=\"T_9bb8f_level0_col4\" class=\"col_heading level0 col4\" >새벽대여비율</th>\n",
       "      <th id=\"T_9bb8f_level0_col5\" class=\"col_heading level0 col5\" >오전대여비율</th>\n",
       "      <th id=\"T_9bb8f_level0_col6\" class=\"col_heading level0 col6\" >점심대여비율</th>\n",
       "      <th id=\"T_9bb8f_level0_col7\" class=\"col_heading level0 col7\" >오후대여비율</th>\n",
       "      <th id=\"T_9bb8f_level0_col8\" class=\"col_heading level0 col8\" >저녁대여비율</th>\n",
       "      <th id=\"T_9bb8f_level0_col9\" class=\"col_heading level0 col9\" >야간대여비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
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       "      <td id=\"T_9bb8f_row0_col2\" class=\"data row0 col2\" >5595.946234</td>\n",
       "      <td id=\"T_9bb8f_row0_col3\" class=\"data row0 col3\" >0.376845</td>\n",
       "      <td id=\"T_9bb8f_row0_col4\" class=\"data row0 col4\" >0.020650</td>\n",
       "      <td id=\"T_9bb8f_row0_col5\" class=\"data row0 col5\" >0.011941</td>\n",
       "      <td id=\"T_9bb8f_row0_col6\" class=\"data row0 col6\" >0.117817</td>\n",
       "      <td id=\"T_9bb8f_row0_col7\" class=\"data row0 col7\" >0.687711</td>\n",
       "      <td id=\"T_9bb8f_row0_col8\" class=\"data row0 col8\" >0.124885</td>\n",
       "      <td id=\"T_9bb8f_row0_col9\" class=\"data row0 col9\" >0.020011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9bb8f_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_9bb8f_row1_col0\" class=\"data row1 col0\" >10.680328</td>\n",
       "      <td id=\"T_9bb8f_row1_col1\" class=\"data row1 col1\" >61.034456</td>\n",
       "      <td id=\"T_9bb8f_row1_col2\" class=\"data row1 col2\" >5299.142268</td>\n",
       "      <td id=\"T_9bb8f_row1_col3\" class=\"data row1 col3\" >0.360479</td>\n",
       "      <td id=\"T_9bb8f_row1_col4\" class=\"data row1 col4\" >0.068096</td>\n",
       "      <td id=\"T_9bb8f_row1_col5\" class=\"data row1 col5\" >0.015875</td>\n",
       "      <td id=\"T_9bb8f_row1_col6\" class=\"data row1 col6\" >0.298764</td>\n",
       "      <td id=\"T_9bb8f_row1_col7\" class=\"data row1 col7\" >0.130114</td>\n",
       "      <td id=\"T_9bb8f_row1_col8\" class=\"data row1 col8\" >0.338662</td>\n",
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       "    <tr>\n",
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       "      <td id=\"T_9bb8f_row2_col6\" class=\"data row2 col6\" >0.221531</td>\n",
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       "      <td id=\"T_9bb8f_row2_col8\" class=\"data row2 col8\" >0.166904</td>\n",
       "      <td id=\"T_9bb8f_row2_col9\" class=\"data row2 col9\" >0.048625</td>\n",
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       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x274755eb2d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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k5uYyZswYTNMkOzvb/briiisqvHBigwYNKjUM5pprruG5557jlltuYdq0aWUmOp999hm33357kSFABUaOHMknn3ziLhKvLp06daJhw4Z89tln7vqY8sTExLBly5Yi25YsWVLisQ6Hg+uvv56DBw/y3//+173d39+/2M/AoEGDWLFiBe3bt8cwjAp+knwRERE88cQTLF++nLlz57q/n57WaKxevbrYtmnTpvHqq6/y559/0qhRI/f2gwcPVvrnUUTEl5RoiNSgihTvlicqKqrEG8eyXH311cybN6/U/aUVk/fr16/UG7ryjB07tlLntWjRosyVyrt06VKpdgHuuOOOIjefJzrxZvOpp54iIyMDwzBwOBw4HA78/f0JCAggMDCQoKAgQkNDCQ0N9Xg4V4E+ffqwePHiIk/OPeHv78+UKVM499xz6devHw899BC9evUiLy+PnTt38u233/Lqq68SHx/Ppk2buOKKK0ps57rrruPdd99l8+bNdOjQgbVr13LmmWdy6NAhnz41dzgcvPLKK9xyyy34+/tz7bXXYpomP/zwA/fddx9NmjQpds61117L2LFjue222xg0aBALFizgf//7X5Fj/v3vf9O4cWP69etHVlYWP/zwQ5G/1+3ateO9995jzpw5RERE0Lt3b8aOHUv37t0ZNWoUf//734mKimLjxo18+eWX/PTTT2V+jptuuokrr7yS9u3bs3v3bpYsWVJknQtPazRKmj1szZo1OByOYvuWLFlC3759PWpXRKQ6KdEQOY3NnTu3Wq6TlJRUZpIA+QWtpU3VC/lF1mXN3ORyuSobHi6Xq9y6GIfD4Y6vKklNeYYPH87o0aNxuVwVWiEe8nsF1qxZw6uvvsq///1vdu/eTWBgIDExMYwYMYI6derw7LPP0r17d1q2bFliGwMGDCAmJoZPP/2UV155hXnz5nH++edXy9CcG2+8kfDwcF588UXef/99wsPDGT58eKnXvuWWW9izZw+jRo0iPT2dM888k9dee41LL73UfUyLFi14/vnn2bNnD/Xq1ePyyy/npZdecu8fM2YMP//8MxdffDG9e/dm/vz5tGjRgnnz5vHwww9z/vnnExgYSIcOHTzqnYqOjubuu+/myJEjxMbG8uijj5Y7VKsqLMti9uzZfPXVVz67hohIpdkiUislJyfbgL1z507btm27ffv29meffVbp9m666Sb773//u3eCq4DOnTvbQLmvOXPmlNrGlClTPGqjMt+fm266yaO2P/jgg0p9/j///NOuyK9ay7Lsjh072pMmTarU9bztyiuvtL/66quaDkNKMWnSJLtjx462ZVk1HYqISDGGbdt2tWQ0IlIlLpcL0zQrPWa8YNGwkgpYxbecTid+fp53IH/77be89NJLrFixokLneZtt2zRv3pwNGzYUWxekoubPn1/q+iAtWrQoVmsh5XM6nfTt25dHHnmk2GKCIiK1gRINEZFa6Prrr6dNmzb8+9//rulQvCIzM5M9e/aUuM/f35/WrVtXc0Qnv2eeeYaNGzd6ZVY3ERFfUKIhIiIiIlLLvfLKK4wbN47s7GwiIyN54YUXitSkFVi9ejV33303CQkJhIaG8tZbb3HuuefWQMRKNEREREREar158+YxYMAA/P39mT9/Pueffz579+4tsqhsWloaHTt25PPPP3evr3TZZZexefPmItNiVxcN1hYRERERqeWGDBmCv78/AIMHDyYkJMS97lWBCRMm0LdvX4YPH+4+Z/DgwTWyECtoelsRERERkZNGdnY2H374IX379qVDhw5F9i1evJiBAwcW2davXz/WrFlTjREed0olGpZlsX//fsLDwys9M4+IiIiI+I5t26SlpdGkSZNaORNidnY2ubm5Pr+ObdvF7lcDAwMJDAws8fgdO3YwdOhQ9u3bxxlnnME333xT7JiEhATOOeecItsaNGjA0qVLvRd4BZxSicb+/fuJiYmp6TBEREREpBzx8fE0a9aspsMoIjs7m5YtwjhwqPKLwHoqLCyM9PT0ItuefvppnnnmmRKPb926NfHx8WRnZzN58mT69+/PggULaNu2rfsYp9PJieXXLperxh7An1KJRsHqsfHx8VWe811EREREvC81NZWYmBj3fVttkpuby4FDLnavjCUi3He9LalpFi167yp2z1pab0ZhQUFBjBo1ilmzZjF+/Hief/55977o6GgOHz5c5PjExMQaKQSHUyzRKMjWIiIilGiIiIiI1GK1eZh7WLhBWLjv4rOo+j1rYGAgwcHBRbb17t2bRYsW8eCDD7q3LVq0iGuvvbbywVZB7RsYJyIiIiIibvv27WPChAk4nU4A5s+fz5QpU7j66quLHDd69GhmzZrF7NmzAfjll1/YtGlTseOqyynVoyEiIiIiUlUu28Llw5XmXLZVoeMDAwP55JNPuP/++wkPDyc2NpYpU6bQrl07vvrqK5YvX85bb71Fs2bNmDhxIvfccw9HjhyhTZs2/PTTT4SGhvrok5TtlFqwLzU1lcjISFJSUjR0SkRERKQWqs33awWxHdrSwuc1Gg3a766V3wNvUo+GiIiIiEghFjYWvnsW78u2axPVaIiIiIiIiNepR0NEREREpBALi4pVUVS8/dOBejRERERERMTr1KMhIiIiIlKIy7Zx+XC+JF+2XZuoR0NERERERLxOPRoiIiIiIoVo1invUI+GiIiIiIh4nXo0REREREQKsbBxqUejytSjISIiIiIiXqdEQ0REREREvE5Dp0REREREClExuHeoR0NERERERLxOPRoiIiIiZdiflMK0xRtJSEolMjSIC/p2oFOLhjUdlviQFuzzDiUaIiIiIiWwbZsPpy9m3C9LMUwD49j2r2at4uwerXnx1hEE+utWSqQ0GjolIiIiUoLv5//F/35Zig1Ylo3r2Atg3to4XvxmVs0GKD5jVcPrdFCrEo1//OMfREZGEhsb637t3r27psMSERGR04zLshg3Y2mp+y3b5uelmziYnFaNUYmcXGpVogEwduxYdu3a5X61aNGipkMSERGR08yW+EMkpmSUeYxt2/y5Lq6aIpLq5Dq2YJ8vX6eDWpdoREVF1XQIIiIicprLynWWe4xhGGR7cJzI6arWVTBVJNHIyckhJyfH/T41NdUHEYmIiMjppmXDaEzTwLJKf/Js2TZtmtarxqikurjs/Jcv2z8d1Loejccee4zmzZtz9tln89tvv5V57EsvvURkZKT7FRMTU01RioiIyKksOiKEYT3b4jCNEvebhkGTuhGc0b55NUcmcvKoVYnG22+/zYEDB9i5cycPP/ww11xzDStXriz1+Mcee4yUlBT3Kz4+vhqjFRERkVPZQyOHUD8yrFiy4TAN/P0cvHDrhZilJCJyctOsU95RqxIN08wPx+FwMGLECK6//np+/PHHUo8PDAwkIiKiyEtERETEG+pHhfHVo6O47uyehAT6A+BnmpzXuz1fPzaK7q2a1HCEIrVbravRKMzpdBIQEFDTYYiIiMhpKjoihH+OHMLYK88iPSuXkEB//P0cNR2W+JiFgQvf9VZZPmy7NqlVPRozZ87EsvI7k3777Td++OEHrrrqqhqOSkRERE53DtMkMjRISYZIBdSqHo033niDG264gZCQEJo3b86UKVPo1KlTTYclIiIiIqcRy85/+bL900GtSjR+/fXXmg5BRERERES8oFYlGiIiIiIiNc3l4xoNX7Zdm9SqGg0RERERETk1KNEQERERERGv09ApEREREZFCNHTKO9SjISIiIiIiXqceDRERERGRQizbwLJ9uGCfD9uuTdSjISIiIiIiXqceDRERERGRQlSj4R3q0RAREREREa9Tj4aIiIiISCEuTFw+fB7v8lnLtYt6NERERERExOvUoyEiIiIiUojt41mnbM06JSIiIiIiUjnq0RARERERKUSzTnmHejRERERERMTr1KMhIiIiIlKIyzZx2T6cdcr2WdO1ino0RERERETE69SjISIiIiJSiIWB5cPn8RanR5eGejRERERERMTr1KMhIiIiIlKIZp3yDvVoiIiIiIiI16lHQ0RERESkEN/POqUaDRERERERkUpRoiEiIiIiIl6noVMiIiIiIoXkT2/ru4JtX7Zdm6hHQ0REREREvE49GiIiIiIihViYuLRgX5WpR0NERERERLxOPRoiIiIiIoVoelvvUI+GiIiIiIh4nXo0REREREQKsTCxVKNRZerREBERERERr1OPhoiIiIhIIS7bwGX7bq0LX7Zdm6hHQ0REREREvE49GiIiIiIihbh8vI6GSzUaIiIiIiIilaMeDRERERGRQizbxPLhOhqW1tEQERERERGpHPVoiIiIiIgUohoN71CPhoiIiIiIeJ16NERERERECrHw7VoXls9arl3UoyEiIiIiIl6nRENERERERLxOQ6dERERERAqxMLF8+Dzel23XJqfHpxQRERERkWqlHg0RERERkUJctonLhwv2+bLt2uT0+JQiIiIiIlKt1KMhIiIiIlKIhYGFL6e39V3btYl6NERERERExOvUoyEiIiIiUohqNLyj1n7Ku+++mw4dOtR0GCIiIiIiUgm1skcjPj6eL774gpiYmJoORUREREROMy5MXD58Hu/LtmuTWvkpH3jgAW655ZaaDkNEREREpFaYPXs2AwcOpE2bNrRu3Zp33nmnxOO6dOlCw4YNiY2NJTY2lv79+1dzpMfVuh6Nn3/+maSkJP7xj3/wxx9/1HQ4IiIiInKasWwDy/bhrFOVaHvq1Kl8+umntG/fnri4OAYPHkzbtm254IILih07ceJEzj77bG+EWiW1KtFISkrivvvu4+eff+bAgQPlHp+Tk0NOTo77fWpqqi/DExERERGpEW+99Zb761atWnHNNdcwe/bsEhONqKioaoysdLVm6JRt29x2222MHTvW4yLwl156icjISPdLNR0iIiIiUlXWsRoNX70sL9yCJyYmEhkZWeI+JRon+M9//kNeXh7/+Mc/PD7nscceIyUlxf2Kj4/3YYQiIiIiIt6Tmppa5FV4pE5Zli1bxvTp0xk1alSxfYZhMHToUHevx9atW70dtsdqzdCpt99+m4yMDOrUqQOA0+kkKyuLqKgoli9fTtu2bYudExgYSGBgYHWHKiIiIiKnMMs2sXy41kVB2yeOxnn66ad55plnyjx34sSJjB07lvHjx9OyZcti+9euXYtpmmRlZfHmm28yfPhwNm7cSFhYmNfi91StSTQSEhKKvJ87dy533XUXmzdvrqGIRERERER8Jz4+noiICPf7sh6gu1wu7r33XubMmcPMmTPp3r17iceZZn4SExwczGOPPcYXX3zB0qVLGTZsmHeD90CtSTRERESq05/r4vhm9mrW7UzANA0Gdo5l9LDedIltVNOhiUgNc2HgwnezThW0HRERUSTRKMvYsWOJi4tjxYoVhIaGenwtp9NJQEBApeKsqlqbaAwdOlS9GSIi4hNvTfmT8b+twDQNLMsG4I9V2/ht5VaeueE8LunfuYYjFBE5Ljs7mw8++ID4+Pgyk4xDhw6xd+9eevXqhcvl4uWXX8Y0Tfr27VuN0R5XaxMNERERX1iwfifjf1sB4E4yAFzHvn72y9/p2aYpzepH1UR4IlILVFeNhqfi4uKwLKvY4nvt27fnkUce4aOPPuK7774jOzubG2+8kaSkJIKCgujbty8zZ84kKCjIm+F7TImGiIicVibMWY3DNNyJRTEG/LBgHfdfcVb1BiYiUopOnTphWVap+wvqL5o3b8769eurK6xy1ZrpbUVERKrDX3EJpScZ5PdyrN2xvxojEhE5NalHQ0RETisOs/xnbP5+jmqIRERqKxf4uBj89KAeDREROa0M6tISh1n6DYRhwMDOsdUXkIjIKUqJhoiInFZGD+uJXcrIKdMwCAkM4FLNOiVyWisoBvfl63RwenxKERGRYzo2b8hzN5+PwzQwC/VsGAYEB/rz7j+uICosuAYjFBE5NahGQ0RETjsjzuhIj9ZNmbxgHWt37MfPYTKgcyyX9u9MZGjNTAMpIrWHyzZx+bDXwZdt1yZKNERE5LTUpG4E/7hsYE2HISJyylKiISIiIiJSiI2B5cNZp2wftl2bnB79NiIiIiIiUq3UoyEiIiIiUohqNLzj9PiUIiIiIiJSrdSjISIiIiJSiGUbWLbv6ih82XZtoh4NERERERHxOvVoiIiIiIgU4sLE5cPn8b5suzY5PT6liIiIiIhUK/VoiIiIiIgUohoN71CPhoiIiIiIeJ16NERERERECrEwsXz4PN6Xbdcmp8enFBERERGRaqVEQ0REREREvE5Dp0RExOvSs3I4dDSd8JBA6keG1XQ4IiIV4rINXD4s2PZl27WJEg0REfGag8lpvDt1ITNXbMHpsgDo0boJd18ygL7tY2o4OhERqU4aOiUiIl5x4EgaY/7zDb8u3+xOMgD+ikvg7rd+YPaa7TUYnYiI5wqmt/Xl63SgRENERLzizcnzOZqehcuyi2y3bBvbtnn2y9/IyXPWUHQiIlLdlGiIiEiVHU3PYtbqbcWSjAI2kJaZw9w1O6o3MBGRSrBtE8uHL9s+PW7BT49PKSIiPrU/KbXUJKOAn8Nk96HkaopIRERqmorBRUSkysKCA8s9xmXZhAYFVEM0IiJV48LAhQ9nnfJh27WJejRERKTKYupH0qZJXYwy/+20Oadnm+oKSUREapgSDRERqTLDMLjn0oHYpYyeMgy4fEAXGkdHVG9gIiKVYNm+nnmqpj9h9VCiISIiXjG0e2uevuE8Av39MMivyTANAwO4tH9nHr3unJoOUUREqpFqNEREpEyWZWOano0nvmxAZ4b1bMNvK7eyN/Eo4SGBDO/Vjpj6Ub4NUkTEiwpmh/Jl+6cDJRoiIlJMVm4e385dw6T5f5GQlEpQgB/n927Pjef1oWWj6DLPDQsO5MpBXaspUhERqa2UaIiISBGZ2bnc+db3bNx90F1zkZ3rZPrSjfy6YjPv33cVPds0rdkgRUR8yMLA8uHMUL5suzY5PfptRETEYx/9vIRNuw8VK+x2WTZ5TouHP55OnstVM8GJiMhJQ4mGiIi45eQ5mbxgHVYp00dZts2RtEzmrdUK3yJy6nLZhs9fpwMlGiIi4rY/KZWM7Nwyj/FzmGzac6iaIhIRkZOVajRERMTN31H+8yfbtgnwc1RDNCIiNUOzTnnH6fEpRUTEI03rRdK8QVSZZYouy+asrq2qLSYRETk5KdEQERE3wzC47YIzKG3RWodp0KttUzq1aFitcYmIVCcLX64K7tsZrWoTJRoiIlLExWd24s6LzgTyE4vC/2/XrD6v3nFJjcUmIiInD9VoiIhIEYZhcOfF/Tm/T3umLFxPfOJRQoMCOLd3OwZ2jsVhVu4ZVZ7Lxdw1O1gbtx/TMOjbPoYBVWhPRERqNyUaIiJSothG0Txw1WCvtLVpz0HGvj+VxJQM/Bwm2PDVrFXE1I/i7b9fTouGdbxyHRERb7B9vGCfraFTIiIiVZd4NJ073/yBpNRMAJwuC6dlAbA/KYW/vTGJtKycmgxRRER8QImGiIj41Hfz1pKZnVviIoAuyyYpJYOfl2ysgchERErm00LwY6/TgRINERHxqZkrt5S60vjxY7ZWUzQiIlJdVKMhIiI+lZmdV+Z+G8jIKns1chGR6qQF+7zj9PiUIiJSY1o3qYtplD5MwGEatGlatxojEhGR6qBEQ0REfOrqwd3KHDrlsmxGntWtGiMSESmbajS8Q4mGiIj41Dk92nJe73bFthf8M3vt0B70atuseoMSERGfq3WJxiuvvEK7du1o3rw5Xbt2Zdq0aTUdkoiIVIFpGrxw64U8OHIIDeuEubfHNIji/0YP55FrhtZccCIiJbCOraPhy9fpoNYVg/fr148HHngAf39/5s+fz/nnn8/evXupW1fjd0VETlYO02TMsF6MOrsnh1MzMAyoFxGKUUbthoiInNxqXaIxZMgQ99eDBw8mJCSExMREJRoiIqcA0zRoEBVW/oEiIjXI13UUp0uNRq1LNApkZ2fz4Ycf0rdvXzp06FDT4YiIiIiISAXUukRjx44dDB06lH379nHGGWfwzTfflHpsTk4OOTk57vepqanVEaKIiIiInMLUo+Edta4YvHXr1sTHx5OZmcl9991H//792bZtW4nHvvTSS0RGRrpfMTEx1RytiIiIiIiUpNYlGgWCgoIYNWoUF198MePHjy/xmMcee4yUlBT3Kz4+vpqjFBEREZFTjdbR8I5aN3TqRIGBgQQHB5e6LzAwsJojEhERERGR8tSqRGPfvn3Mnz+fq6++Gj8/P+bPn8+UKVOYN29eTYcmIlKm7Fwnv67YzG8rtpCamUOrxtFcdVY3urdqUtOhiYhIBalGwztqVaIRGBjIJ598wv333094eDixsbFMmTKFdu2KrygrIlJbHDiSxh1vTmJvYgqGAbYNW+IPMX3JJq4d0p1Hrj1b60WIiMhpp1YlGvXq1eOPP/6o6TBERDxm2zYPfDCVhKTUY+/zt7us/C++nbeW2EbRXDu0Rw1FKCIiUjNqVaIhIlKb7T6YzLdz1zB/XRxOl0W3Vo3p2aYpW/YmlnneF7+v4OrB3TFN9WqIiJwMbMDCd7+zbZ+1XLso0RAR8cC8v3bw8MfTsW3b3VsxZ812/li1DcMwsO3S/9lIOJLG/qQUmtWPqqZoRUREap4SDRGRciSmpPOv//2My2UVeQpVkHCUlWSceKyIiNR+Kgb3DiUaIiLl+HHhepwnJBkVERkaRJN6EZW+/sHkNDbsPojDMOjeuglRYSVP+S0iIlKbKNEQESlBQS+FYRis2rYPy4Nei5IYBlw7tAf+DkeFz01Oz+Lp8TNZuGGnu8jcz2FyWf/O/PPqoQQF6Fe4iIgvqEfDO/SvlIhIIQvX7+SLP1aycttesKFbq8ZkZud6dK5pGljHhkiZhoFl2/Tv2ILbLjijwnEkpqRz1TPjST/h2k6XxZSF64k/nMJ7916BwzQr3LaIiEh1UKIhInLMp78u492pC91JAsBfcQnl9mY4TIO+7ZvTsXkDflm2mczsXFo0rMPIwd0YcUZH/BwVSwbyXC5ufuXbYklGAcu2WbZ5DwvW72RIt9YValtERMqnHg3vUKIhIgJs3H2Qd6cuBCiSWHgyZMpl2dx2wRn0bteMey8fVOVYZq/aTsKR1DKPMQyYumiDEg0REam1lGiIiACT5q3FYRqlzg5lGgb5M58f7+0oOP7hq4fSu10zr8UydfH6co+x7fwicRER8T71aHiHEg0REWDdrgNlTkFr2TZ1I0K46qxuzP8rDqfLRffWTbh6cHfaNavv1VgOJad7dFz9qDCvXldERMSblGiIiAABfuXPChUU4M9dF/fnrov7+zSWBnXC2HngSLnT6V7av7NP4xAROV3ZtoHtw14HX7Zdm2i6EhER4OwerY8NjyqZwzQ4u3v11ENcNqBLuUlGTP1IBndtVS3xiIiIVIZ6NEREgCsGdmX8byvIznUWKwA3DHCYJtcM6V7iuXlOF3PWbmfFlr1Ytk33Vo05t3f7Sq9zcU7PNnRv1Zi/4hJKTDjCggP59OFrKzyblYiIeMbCwMKHNRo+bLs20b9SIiJAvchQ3rv3SkKDAjDITy4KXoH+frx1z2U0qx9V7Lwd+w9z6ZOf8ui4X/hx4XqmLtrA01/8xojH/8fauP2VisXf4eC9e69kRL+OOMyi/xgN6hLLT/++lbrhoZVqW0REpLoYtl3J5W5rodTUVCIjI0lJSSEiIqKmwxGRk1B6Vg4/L93Eiq3xWDb0bNOUS8/sRERoULFjUzOyueKZz0nJzHYv1FfANAyCAvyY9NSNNI6u/O+jpNQM1mzfj41N15aNaVgnvNJtiYjUBrX5fq0gtn4/3odfaKDPruPMyGHp5W/Xyu+BN2nolIhIIWHBgVw7tAfXDu1R7rHTlmzkaEYWJT2usWyb7Dwn38//q0pra9SNCGVYr7aVPl9ERKSmaOiUiEgl/bFqa4lJRgHLsvlt5dbqC0hERLyiYNYpX75OB+rREJFaLTM7lxnLN7N4425clkXn2EZcMbALdSN8W6Ow73AKvyzbxOGUDOpHhjGiX0ea1C3avZ2Zk1duO9m55R8jIiJyKlKiISK11pb4Q9z99mSOpme5t83/K46Ppi/mpdtGMLxXO69f07JsXv9hHhNmr8YwDUwjfyXwD6YvYsyw3oy98iyMY9PgdmhWn50JSaUu9OcwDdo2ref1GEVExLe0Mrh3aOiUiNRKCUkp3PLad0WSDAAbcFk2/xr3M1viD3n9uv/7ZQnfzF6NTX7S4XRZWJaNbcOXf6zks5nL3ceOHNy9zNXEXZbNNUN6eD1GERE5/cyePZuBAwfSpk0bWrduzTvvvFPicbt27eLcc8+lRYsWtGnThq+++qqaIz1OiYaI1DrLNu/h8mc+L3PYkW3DfybO9up1M7Nz+eL3lWUe89nM5WTnOgHo1qoxN5/XB4DCs9AWfHnJmZ0Y0k2L6omISNVNnTqVTz/9lO3bt/P777/z8ssv8+uvvxY5xuVycckllzB69Gh2797NtGnTuO+++1izZk2NxKxEQ0Rqlf1Jqdz//lTynFa5x66NSyA3z+m1ay/dvIescmoqMrJzWbk13v3+3ssH8fwtF9C6yfEhUjENonh81DCevuE89zArERE5edTGYvC33nqL9u3bA9CqVSuuueYaZs8u+sBt1qxZ+Pn5cfPNNwPQqVMnxowZw/jx46v8PakM1WiISK3y/fy15LlcHh+/cMMuzu7RxivXLi/JKFC4CNwwDEac0ZERZ3QkLSsH27IJDwlUgiEiIuVKTU0t8j4wMJDAQM/W70hMTKRDhw5Fti1evJiBAwcW2davXz/GjRtXtUArST0aIlKrzFm7o9jid2U5dDTda9du2Si6SseFBwcSERqkJENE5CRnHysG99WroEcjJiaGyMhI9+ull17yKL5ly5Yxffp0Ro0aVWR7QkICDRs2LLKtQYMGJCUleecbU0Hq0RCRWqWiQ6HqeXGa247NG9IhpgFb9yWWmOyYpkHnFg1po5mkRETEC+Lj44usDO5Jb8bEiRMZO3Ys48ePp2XLlkX2OZ1O7BMWeHK5XDX2AEyJhohUi6ycPH748y9+W7GFHKeLbi0bM3JwN9rHNChyXMM64SQcSfOozbCgAAZ1bVn+gRXwzI3ncetr35KT5ywyo5TDNAgO9OepMed69XoiIlL72FDmgqzeaB8gIiKiSKJRFpfLxb333sucOXOYOXMm3bt3L3ZMdHQ0hw8fLrItMTGRRo0aVTXkSlGiISI+tT8phTd++JNZq7cV2b5t32F+WLCO2y/sxz2XDnBvb1YvkjU79nvU9n1XnkWgv3d/jbVrVp+vHh3Fx78s4Y+V23BaFn6myXl92nPHRf1o3qCOV68nIiLiibFjxxIXF8eKFSsIDS25N7937968+uqrRbYtWrSI/v37V0eIxSjREBGv2Lo3kd0HkwkJCqBPu2YE+vuxac9B/vb6pDJX0B43YyktG0Vz4Rn5BW3NG9TBMMp/knTPJQMYeVY3j+OzbZu/diYwZcE6dh1MJio0mPP7tGdYzzYEnJCsxDaK5sVbR/Dk6DxSMrKJDA0iONDf42uJiMjJzcLAwIcL9lWw7ezsbD744APi4+NLTTIALrnkEh544AG++uorxowZw4oVK5g6dSrLli2rasiVokRDRKpkc/whnvvydzYXWjwvPDiQ20ecwcQ5a8pMMgr8b8ZSLujbHsMwGNC5Be//tKjM4xvVCePWC87wOEbLsnlp4ix++HMdDtPAZdmYhsH8dXF88ms0H40dSd0Saj2CA/2VYIiISI2Li4vDsqxiPRPt27fnkUce4aOPPuK7774jJCSEn376ib/97W88+OCDNGrUiG+++YZmzZrVSNxKNESk0rbvO8ytr31Lbl7R6WjTsnJ444c/PW5n14EjpGRkExUWTKcWjejVpilr4/aXuur2rRecgWl6/jTomzmr+eHPdQDuNq1jXSa7Dybz8MfT+fShaz1uT0RETm2VXeuiIu1XRKdOnbCs0teXGjZsmPvr3r17s2rVqkrH5k2a3lZEKu39nxaR53S5b9qrwlXoF+ird1zsXgDPPDZThuNYYnHD8N5cVYEhUy7L4ovfV5Sx32bNjv1s3H2wMmGLiIhIKdSjISKVkpKRzby/dnhlVo7QIH/qhIW439cJD+HLR69n/l9x/LZyK2mZ2TRvUIcrB3WlXbP6FWp798FkDqdklHmMaRos3ribTi0alnmciIicHizbwPBhj4blw7ZrEyUaIlIpR9IyvTb131VndSs2FMrf4WBYz7YM69m2Sm07XaV3NRcwKNqjIiIiIlWnRENEKqVOWLBHs0MZHJ8vvCR1I0L4x2WDvBlaEc0b1CEk0L/MonSXZdO1ZWOfxSAiIicX2/bxOho+bLs2UaIhIpUSFRbMoC4tWbRhV6lF26Zh0KpxNNv3J5XaTlJqJv/8cBpPjjmXepFlr/Kd53IxY9lmvp//F/GJRwkPDmREv45cPbgbKWY6a5N3Y2DQM7olLULzazyCAvy46qxufD1rVYm1JA7ToHHdCPp1aF6BTy8iIiLlUaIhIpX290sHsmxzPJbtwi7hJv7WC87gjovO5M91ccxYtpklm3aTnp1b7LhFG3dxy6sT+eqx0USGBpV4rZw8J/e/P5Vlm/dgGgaWbZOSkc24X5by6ayl2AOSMMKPz351Zr22PNvtauoEhHH3JQNYtzOBNTv2F+mFMU2D0KAAXrvjkgrNYiUiIqe22jbr1MlKs06JSKUlpmQQFhxQLMkI8HNw3+WDuPuS/vg5TM7u0YZrh/YoMcmA/KFLCUfS+G7emlKv9fHPS1ixJR6gSM+EZds4cyxcyyKKdEUvT9rB3cvGke3KIyjAjw/vv4rHrz+Htk3qERzoT4OoMG4c3pvvnryxwgXmIiIiUj71aIhIpSzbvIf73/+xxJ6MXKeLoAA/DOP4E5tpSza4F8sriWXbTF6wjr+NODP/vWWzff9hMnNyaRAVxqR5a0ufRtc2IN0P+7A/Rv38WgyXbRGXfojfEtZyabM+BPj7MXJwd0YO7l7FTy4iIqc69Wh4hxINEakw27b57/fzsG271IK2d6Yu5LIBXdwrax9KTi81ySiQlJIJwC/LNvHBT4vZdzgFwKOicwwbjvhD/eNF3wYG0/et4tJmfTz7YCIiIuI1SjRETkEuy2L+X3FMW7yBQ0fTaVgnnMv6d2ZQ15Y4zKqPmNx54Ajb9h0u85isnDzm/bWDC/p2AKBeZGiZPRoAdcKDmTB7Na9Omltku8ezc5zwgMjGJiknzcOTRURExJuUaIicYrJy8rjvvR9ZuW2vu2h6y95E5q7dQd/2Mbx5z2UEB/hX6RpJqZnlHmMaBocLHXdxv478vHRTmcef37cDb0yeX7mgbAOjftEaEBODJsHRlWtPREROW1qwzztUDC5yivnPxNms3r4POF40bR3rRVi5dS+vfTe3yteoX840tAXXbhB1/LgzOjRnYOdYTKP4L1eHaVAvMpTIkMDKLZxn2FAnD6OOs2gM2Fweo2FTIiIiNUGJhsgpJCk1g1+WbSq1aNqybX5aspHk9KwqXSe2UTSdWjQsMWkoEBYUwOCurd3vDcPg1Tsu4bIBnYsN32rbtD5PjTmXI2mZHg3tKpiJ1n35EBeOvqlFj8Ggb93WDGnQybMPJSIickzBgn2+fJ0ONHRK5BSyatu+cguunS6L1dv3cU6PNlW61kNXD+GON77HtkouCH9w5BCCAor+igkK8OPJMefy90sHMvevHfy8dCPr4hLYHH+If7w7hdCgAI96NIZ0b01CUhqRoUEM692GzeE7mHFwNXnHTg00/bg8pi9/b3cBfqajSp9TREREKkeJhsgpwrJsdh9M9vDYSgxPOkGP1k354P6reGnCLOISjri3148M5b4rzuKifh1LPdffz+TL31ey9/DRIolRRinrbBQwTYN+HZrz3zsvPWFPd+7Lu5DNKfvAgE4RzQjzL3nhPxERkfLk9zr4cnpbnzVdqyjREDkFzFy+hbd//JOEI+XPsGQY0Dm2kVeu27ttMyY9eSOb9hwiISmVqLBgerRp4h7+dOhoOpMXrGPF1vyF9s5o35wrBnXhu7lriU88Wvq6GKXEbWBw18X9S9wf4R/MGfWq1ksjIiIi3qNEQ+QkN2XBOv799R8eHeswDc7q2orG0RFeu75hGHRq0ZBOLRoW2T7vrx088vF0XJbtTijWbN/Pp78uw89hlptkFDxHMo9NiRsdHsJzN11A15aNvRa7iIhISbRgn3co0RA5idi27V5t27Ztvpq1ijd+KH86WOPYf2Ia1OHJ0cN9EltWbh5b4xPJcTpxmCYPfzwdl8uicDph2TZ5The5TleZbZmGwVldWzKwcywZ2XnENqzDwC4t8XNo/goREZGThRINkVou4UgqX/2xip+WbCQ9K4f6kaFcdVY3DhxJ5cdFGzxqo1n9KK4e0p0rBnYhNCjAq/EdOJLGy9/OZv66OI/GnHoyWMowoEFUGCMHd69yfCIiIhVl49m/V1Vp/3SgREOkFkpKzeBgchpH07N5+H/TycrJc+9LTMngw+mLK9Tev2++gG6tvD/kaH9SCqNe/JrUzByvtuuybM7v077C5+XmOVm36wA5eU5aN65LwzrhXo1LREREPKdEQ6QW2XngCG9Ons+C9Tu9OiNFnfDgMvdbls3iTbvZvOcQ/n4mg7q0pFXjusWOS8hKZkr8cjakxONv+pEwz6p0kmGQX99xYq2GaRj0bR9DzzZNPW7Ltm3G/76C8b+tICUjO799AwZ3bcWj152jhENERCpENRreUesSjdmzZ/Pkk09y8OBBbNtm7Nix3HvvvTUdlojPxSUkcdMrE8nKyfVakmEaBh2bNyCmflSpx2zcfYBH/vcz+5NScZgGtg1vTv6TQV1a8sItFxAeEsTG3Qd587fZrDywGyPQwmiejRFk4dwWzfGybc85TIMBnWPZuvcwB5PTcJgGlp2fMJzTow3P3HieuxbFE//9fh7fzF5dZJttw4L1O7n5lYl8/dhooiNCKhyniIiIVF6tSzSmTp3Kp59+Svv27YmLi2Pw4MG0bduWCy64oKZDE/GpV76dXe46EhVl2zZXDOxS6v74xKPc8cb3ZOc6AYqsabF44y7ufe9HDAzWxu0HwwY7ANsAdgZD/Rwqk2QUXOfuSwbQtmk9lmzczdZ9iQT4+XFW11Y0bxBVobZ2HjhSLMkofJ3DqRmM/30FD1w1uFKxiojIaUhFGl5R6xKNt956y/11q1atuOaaa5g9e7YSDTklOV0W2/cl8sOCdSzbstfr7dvA89/MYvrSTfzn9otoEBVWZP+Xv68kJ89Z4lSzLsvmr7iEQo0ZxxsFSKx4Ubnj2FS1D189lA4xDQAY2KUlA7u0rHBbBaYt3uButyQuy2bKgnXcf8VZmObp0VUtIiJSG9S6RONEiYmJdOjQoabDEPEql8vi41+WMGneWo4eqynwpXU7E7j99e+Y8PiYIrNO/bJsU6k36OUzOJ51lH4DbxoQEhiAYRj07RDD6HN6Vaj+ojwHj6SVO9QsPTuX7Nw8Qrw845aIiJyifFyjgWo0at6yZcuYPn06zz33XIn7c3JyyMk5XoiamppaXaGJVFie08WcNTuYung9y7fE43RZVW4zJNCfzJw8d21FaYvguSybfYkpTF+ykWuH9gDyh1VlFprNqnLK/0X54MghjDqnVxWvU7o64cH59RxlZBsBfg6CAvx9FoOIiIgUV2tXv5o4cSKXXnop48ePp2XLkodVvPTSS0RGRrpfMTEx1RyliGeWbd7DeY9+zKOf/Mzijbu9kmQ4TIPJT9/EuAev5tYLziA6vPxi5+lLNrq/NgyDhnXCyjjaM0bTbEoabGoY8PdLB3D92T2rfI2yjDijIy6r9O+nwzS4qF9HDZsSERGP2bbvX6eDWtej4XK5uPfee5kzZw4zZ86ke/fSF+x67LHHePDBB93vU1NTlWxIrWLbNv/7ZWmF170oT6C/H+/843Ia1AmnQZ1werVtxs9LN5UdC5CcnlVk28izuvP+tIVVqkkz22fi1y2T64zhbNyRCDb0bd+Ma4f2IDwkqAote6ZzbCOG9WzD7DU7sE+cKtc0CA7w5+bz+/o8DhERESmq1iUaY8eOJS4ujhUrVhAaGlrmsYGBgQQGBlZTZCIV9+7UhXw2c7nX2gsLCuCm8/pyxcAuREeE4LItUvMyCTIDaFY/kgNH0kodPmUaBg2iwvhj1VYMDLq1bsz1Z/fgiz9WkFaZtTAMGyM6D0e4xTPdruH8JjW3ivcLt1zIK9/NYeqiDUVqTmIb1uHFW0eUOb2viIjIibSOhnfUqkQjOzubDz74gPj4+HKTDJHaxrZt4hKOMGv1Vuas3cGO/UleGSJVICwogK8eG03zBlFkOHP4YOtvTI5fRkpeJgbQuksTrEM5cKTkgmfLtlm7Yz9rduwH8hOP8/q045webZi2eEPFunENG/xtzhjakHv7jqZTZLOqf8AqCPD34/9Gn8tdFw9g0cZd5OY5adu0Pt1aNa7QehwiIiLiPbUq0YiLi8OyLPr3719ke/v27Zk5c2YNRSVSvulLNvLxz0vYezjF620bBgzr2ZaxVw6mSd0IMpw53LH0Y3akHcA6NujJBuLyEvAbZONaEYG9v+SevsK5hGXb/LZiK80bRlV4rGiAw48Xb76Qc3q2rdyH8pF6kaFc2r9zTYchIiIi1LJEo1OnTlhlFHWK1DZ7E4/yxg/zmbN2h9fbbhQdzvM3X0Dn2EYE+h//Uf1sx5wiSUYBCxvDgIA+6Rh/hJCd6QLyZ1zKdbpKvIZl2+w6kEybJnWJSzhSbNiVaRg4TIN7rziL+EPJ5LlcdG/VhPP7dCAooFb9+hAREfEe2/DtFLQaOiUiJ7Jtm2Wb9zD+txWsjdtP1rEVtb0lNCiAQV1iOa93e87q2go/R9GJ4ZyWi8nxy4olGe74AMuweODvfehoxwLw3+/nsmH3wVJ7LUzDIDQogMHdWjF37Q5Mw8A0DZwui8jQIF68bQT9OjT34qcUERGR04ESDREPpWfl8Pd3prBuZ0L5B1dQeHAgD1w1mMsGdC6zpiApN510ZzkL/NkGqw/t5rozBwBwODWzzKFRlm2TlJrJZw9fx84DR5i3dgfZeU7aNKnLkG6t8fdzVOYjiYiInLR8PQWtprcVkSKe+GyG15OMyJAgnhg9jKHd2xTrvShJkFn+onOWbTNr+XZei5/LP0cOoUFUGIeS0yhtAfCC2agAWjaKpmWj6Ip8BBEREZESKdEQKUVunpPlW+JJyczGMAz+XLfT69dIzcwm4UiaR0kGQGRACN2iWrD+6J5Sh08ZJrgSAvlm42paN67L5QO68Fdc6QmSZdtcPrBLpeIXERE5JdmUtBatd9s/DSjREDlBelYO42Ys4/v5a8nMyfPptWxg/G8r2HMwmfW7DhDg72BIt9ZcMbALdUpZ6fu21mdz/8rPS27PAvuIHyT7YQDjf1/BxCfG8N28tWzbl1hkjQnIX9CuQ7MGnNe7nXc/mIiIiJz2lGiIAMlpmXz08xJ+Xb6Z1MosXlcFR9IymbJwnXto0/pdB/ls5nLeu/dKurVqXOz4/vXb8WSXq3hh3WQsbPc4T8MEO9kPa1kkYGADew4dJTUzh4/GXsXz38xi1qpt7pmlTMPg3F7teHzUMAL8y/9VsDV1Pz/EL2NL6n5CHAGc3bAzFzbtSZif71f/FhERqU5asM87lGjIaW/xxl088MG0UqeArQ6FOxps2yYjO5c73pjEk2OGc16f9vg7ihZkX9KsN+uWHOHH3cuxw5zgNHDtD4QjfkDRX14uyyI8JIiXb7+Ig8lprI3bj4FBj9ZNqH+sNqM847bP4uPts3AYJi47fwrqlUfi+HTHHN4/43ZahjWo0ucXERGRU49nA8NFTkF/xSVwz9uT+fs7U7yaZDg8rLcoT67TxZOfz2TE4+NYG7e/2P6+LVvg3B6MtSYca30YHPHnxCSjfmSou9AboGGdcM7r3Z5ze7fzOMmYdWAdH2+fBeBOMiB/2NfRvAzuX/EZTqvmkjQRERGfsH34Ok0o0ZDTisuySExJZ9qiDdz62rcs3bTbq+07TIORg7pimt7rEk1Oy+Ketyaz59DRItuH9mhNvchQzFKmwzWA68/picOs2o/5F3HzMSn5Gi7b5kB2CnMPbazSNUREROTUo6FTclrIys3j1W9n89PiTbh8NHl1k7oR/G1EP76duxartLlkK8GybXKdTr6etYrHrj/Hvd3f4eDNuy/lzjd/ICs3z31N0zCwbJuhPVozZljvKl0705nDptR9ZR7jMEyWH97O8EZdq3QtERGR2kI1Gt6hRENOabZt8+vyrTw1fkaxGZcqwwC6tW7CJw9ezaY9h1i+JR5/PwftY+qzdW8iz375O550ZgT4OWjeIJLt+494dF2XZTNj+eYiiQZApxaNmPTkjXw3bw2/rthCVk4eLRtFc82Q7pzbu12VezMsD5MyZ6EhVSIiIiKgRENOUcnpWYz7eQnfzltT6kJ1leEwTR64cjCmadI5thGdYxsBsG5nAq9Nmgfg0fVGD+vK76sqti5HVk5uidsbRYdz3xVncd8VZ1WoPU+E+gUSE1KX+MykUo9x2RZdo5p7/doiIiI1RutoeIUSDTmlZOXm8eAH01i6eY/X2w4PDuSNuy8tccrZiXPW4DCNUnpNbMDAYVq4LJOLu2/m8vZfMf63UVSkTKppvchKx15ZhmFwfexAXtk4reT9GIT6BXJ+4+7VHNnpyemyWLVtL0czsmgcHUGX2EYYpdToiIiI1DQlGnJKWLppD+9O/ZMNuw/5pP1hPdvywq0XEOBX8o/Miq3xJSYZ3WISiAjKYV9yBOFBOQxpv5Prz1zHr+vaYlVwfOY1Q2rmZv7KmDP46+geft2/BhPDvSK5wzDxM0xe6zWGYL+AGontdDJt8QbenrKAI2mZ7m0tGtbhiVHD6NMupgYjExE5FRmcOJOj99s/9SnRkJNansvFS9/M4sdFG3x6nezcPG597TsysnNp27QeI8/qRt/2Me6nySU/VbbZeySCo5nBWHZ+z8VfexszflEvzmi5FwPPe04N4Kqzunnjo1SYaZg803UkZ9XvwPd7lrA97QCBDn+GNerCNc0HEBNat0biOp1MXrCO57/+o9j2PYeSufutyXw09ip6tW1WA5GJiIiUTomGnHSycvL4evZKPv55KU5X9RQhL9ywy/313sSj/LFqGyPP6sZj15+DYRj079SC6Us2FuvVOJIRWqyt1KxA/tjYpkLX7966MYEerN7tK6Zhcm7jbpzbuGaSndNZVm4eb/wwv8R9tg0WNv/9fh5fPza6miMTETmFqUbDK5RoyEnlfz8v4YPpi2s0hoJk4vs//6J9TH2uOqsb15/dk58Wn7iWhHHCOxvb3RVrl3hMae68eECVYvaUbaVC1o/YOQsAF0ZATwi+GsPRsFquL8XN/yuOjOySJwKA/JnVNu05xM4DR2jZKLoaIxMRESmbEg05Kew+mMR1L3xNTl7tWYHaAL78YyVXDupKu2b1eebG83hq/MwixzSKTOOGAWu4qNsWwoLyOJwWzOSVnflmSTfScwLxJOEYM6wXZ7T3/Rh8O3ctdvKtYKcXbMHOXQjpH0DU6xhB5/s8BinucEqGe22UsiQeTVeiISIitYpWBpda7bOZS+l19xtc8cwXtSrJgPwUYc+ho9z08gRmrd7GRf06Etuwjnt/g/A0rum7jubRRwkJzAOgXngWtw1eyfi//UBUSBZntoovtf3gAD+eub4R9w/9EPtQD6yDfbCOPoqdt9n7n8VKPpZkZFC0v9gCnNhHx2LnbfH6daV89SJCPVrPpF5k8WF6IiJSSXY1vE4D6tGQWunNH+bxxR+rajoMj6zffZCHP55O/chQwoMDj221OZQWzjt/9MfGoHFUKs9ePpteLRJwmDZNo1L55/kL+WZpV07szWgUHc7Is7pxXe/JBLneAadJ/g1/FmRPxc6eBlFvYwQN996HyPrhWE9GadPzgp0xHiPqRe9dUzwyuHsrQgL9yczJK3G/YUD7Zg1o1VhF+SIiUruoR0NqlW/nrKbX3W+cNElGYYkpGew5lHzsXX7yYB/7/4GUMP7+5cVs2l8PAD+Hzbmdt5NwNKJYO+MfuY5bhuwlyDX52JbCBe8uwJXfw2B5tqo4gNNyserITuYd3MiOtAPF9ts5cyn78YoLcmZ7fD3xnuAAf+4vZTFGw8if8eyBqwZXc1QiIqc42/D96zSgHg2pFdbs2Mfdb/5AjrN2DY+qKGcpy4LbtonLgo/m9uXNUTOA/GSjdf0jrNzdtMixOblO7LwvyH8OUNKsWjaQB1mTIfT2cmOatncFH2z9jaTcdPe2jhFNebTz5XSMPHZtu/Ri4+NKfqLuLbYrETvzK8iaAnYqOJpiBF8HIVdjGEE+vXZtd/WQ7jgcJu/8uICUjGz39iZ1I3li1DD6VkMNj4iISEUp0ZAatWrbXsa+P5X0MmbVOVVYtsnCbS1IzQogIjj/8+a6HEWOCQ0KoH5kMBw5cQar4uzctRjlDMv/dvci/rtperHtW1L3c8fSj/nkzDtpF9EEl9kdrLU4zJITJafLIM/shK+qAGznDuwjo8E6iju5cm7HTnsesqZC9OcYZpiPrn5yuHJQVy45sxPLtsRzND2LxtHh9GzTVCuDi4j4gG3nv3zZ/ulAQ6ekxsxavY3bX5908iUZ4U6MxjkYDXKhlBvz0tgYpGTlP50/mhnEpv313ftM0+DKQV0J8Pen/B9NA4yynxOk52Xz7pZfS9xnYZNnO3l3S/4sWfO298UoY+iUn8Nm6tpe5cRUObZtYyffB1YKRXtwjlXLOddjp7/mk2ufbPz9HAzsHMtF/TrSq20zJRkiIlKrKdGQGpGelcOj436u6TAqJtyJ46xk/M5JxnFGKo7+KTguSMJok4mn00c4TBfRoVkAfLGwB04rv0fDNAzaNKnH30b0wzBMCBgIOMpoycIILHncfoFZB9eTazlLb8G2WZq0jcTsVKYvz+I/v+SP83e6jt+8Oq38r79c1J2Pfw/w4BNWQt5KcG0jv/6kxEgh8wdsK72U/SIiIl6mWae8QkOnpFrYts0fq7YxYc5qtsQfwrIptop2rRbqxHHWUXAUjdnwt3F0zsDyt7A2lT20x2FYDO+0g9DAPGas783Xi3sCUCcsmKuHdOeG4b0JDcq/mTdCb8PO/bOUlkww60LQiDKvl5idgsMwcdqlr55uA4k5qWTl5jF5XWfiEuswuv9azmy1F4dp8dfeRkxY0o15W2IJ9PdR/UzeWkqvRymQA85tENDTNzGIiIiI1ynREJ+xLJvMnFze+GEe0xZv9EliER4SSFpmjtfbPZHZPhMcNkYpfYBG2yzYGYR/uEFeYvGeCMOwCPB30iw6hes+uIaUnOYsePNWcl0uQgMDMM0TVhEPHAART2OnPkf+TbgL9zS4ZhRGnU/LLZCODgjDVUaSUaBuQBhtm9Zj1ba9rNnThDV7mpQQPz6cPtXDX0NGWT08IiIiXuTrmaE065RI5fy+cisf/7yEHQlJPr/W0O6t+Wlx+YXTVeKwMZrmlJpkFDC6ZmA3ySVoSSgc8Sc7z9+9z7YNsnID+GR+32NbMkjNzKZ+VOm9IEbIaAgYhJ05AZzrgUCMoGEQdKlHhdHnNOrKa5t+KrVHw8SgW50WNAyO4qqzuvHN7NWltmXbcO3QHuVeszRpeVlMjl/G1L3LOZKTTt3AcC5r1pcrm59BaOBASCsnITKiwK9Dpa8vIiIi1U+JhnhNdq6Tv73+HRt2H6yW6xnAoeQ0QoMCyPBlQXmAVW6SAWA2yuXswP08fftSHIbF+r0Nyczxp2WDoxxOC+bBiSM4mhnsPt5hlt+o4dcCI+LRSoUdFRDCba3P4aPtfxRvFwPDMPhHu/MBaNkomvuuGMTbUxZgGoZ7JeqC5y1De7Tmon4dKxXH4exU/rb0YxKykrGODUrNzEziva0zmbZ3BR/3u4OogEGQu5jS6jSM0FswDB/ViIiIiJzAsPNfvmz/dKBicPEKl2Vx1bOfV1uSAfn1BUs3xxMUUJF8uRI/2XkGHoxAouFBF8+3X0yAw4W/w6ZniwMMbBdPk6g0OjVJ5M3rfwFsDAPaNKlLnfDgctusqltbn80/2l1AsKPoTXrj4Cje7nML3eq0cG+7+by+/PfOS+gc2/D4cXUjeHDkEF6+/WKPEqOS/Hv9ZA5kH3UnGQVsbPZlHeHFDVMwov4Lfu2O7Sm4zrGhUkGXQ+gdlbq2iIiI1Bz1aEiV5OY5mbV6Ox9NX0zCkbQaieFIWmYFjq7EmEiniZ0QAI1zy+zZ+Furddg2OEo4xs9h06XZIfq23Mfync24+fy+GIaBbdskpWZiGBAdHuL16UoNw+DGVoO5uvmZLDm8lTRnNs1CoulRJxazhA9zdo82nN2jDRnZubhcFuEhgVWKaW9mEosPby11v8u2+PPQZg7mXELDut9Dzh/YWdPAOgKOFhghV4N/H03jKiIi1cvXM0OdJj0aSjSkUuITj/KfibNZsml39S86E+HEbJmFUScPXAbWgQDYHQy5JqYBvpjMqn1WK/b47SDPchZ/Mm+DERfIRVduxyzjftjpMji7YxzdO1zF+b3b8928tXz1x0r2Hk4BoHmDKMYM781Vg7p6/cY62C+Asxt18fj4gtmvqmrD0b3lHmNjszFlL42Cu0DQhRhBF3rl2iIiIlKzlGhIheQ5Xbw9ZQFfz15VMwHEZOLXKwPbAsM8tnJnmBP2BgIGlpdncWgcHc43j48mMjSYzSn7eG79D2xPO+DebzvB2hZCyG5HmUkG5PcuXNC7BZGN+/Psl78zbfGGIv0r8YeO8uI3s9iy5xCPjxp2SjzFNz38DA5PimBERESqi2ad8golGuIRp9PixYmzmLFsEzl5PlpPoVw2JARhp2dhhB0rmrCAmXXB8saNqk3B0KqwoADuvqQ/159zfDXsDpFN+XrAvWxK3cfujEQ2Ht7P1x9vAZdBJjZJ6cHUDcsqtXWHaRMZ3oWFG3YxbfEG9xULXx3ghwXrGN6rLf06tijWxsmmd3QrHIZZ5jS7/oaD7nViqy8oERERqRZKNKREGdm5fD9/LVMWrmd/UipOlwfV0D5ngAusraE4euXXg7g2hFQxyTieXBSWmZvHa9/PIzo8lPP7tj8egWHQKbIZnSKbMSS6M1+7th5rxWDS8i78bcgKHGZpY7ccEHwlk+bNx2Eapa4r4jANJv351ymRaEQHhjGiSU9+3req2JAzyJ/96tJmvYkKCKmB6ERETm/7dxxg5mdzOLgnkYjocIaNPov2fdvUdFi1g2o0vEKJhhSzYms8/3h7Mrm1Irk4gW1gxwfiis3ErOPKr82ojGAnRmw2+NmQ5sB2kr8qXXwwLeomM7LvBvq23IvBt2QnXURg5I0YfkVv/EOCAhjQqQVLNu3Bsm2+XNSdgW1306lJYpFkw7ZNDMPGiPg3hhnNtv2Hy1y80GXZbNt7uHKfqwKyc51YlkVwoL9Ph2k93OkSErKOsuLIDkwMLGz3//vVbcPYDhf57NoiIlKcbdt8+sQEJv5nCuaxGUwMw2DK278w4PK+PPHNWAK8VKsnpzclGlLEog07uffdH2t5om1g/xmNy99V8d4M08bslobRPH818YL7a9sGa1k453XZynNXzMa282eKArByv8Y+/A1EvV6sUPlvF53J4k27Achx+nP3F5dy48DVXN1nA3VCs/OvEdAHI+xujMCBAIQElv/L21vF2CWZvWY7439bzrqd+bUmLRrWYfSwXlw5sGuRFcpTcjOZtGcxU/euICknneiAUC5t1odrWgyoUA9EkCOAd/rewuLErUzft4pD2Sk0DI7kkqa9ObNe2xJnvxIREd+Z+u6vTPzPFACsEx4qLp62grfu+R8Pf/r3mgit9lCPhlco0TiN2bbNkbRMsnLz+G3FFj6ZsYysXGdNh+W5vIrcoOb/RJs90/JX+S7hAb6jbxrXtVuNadhFprE1jfxfwvbRB6FeRwy/WPe+JnUjCPJ30K7hXjo3PUSey8Eva9szbl4fokKyCfAP4esn7qJO4PGel/P7tOOj6Uvci+KdyDDgvN7tStxXVZ/MWMZ70xYWKdLeczCZF7+Zxdod+3n2xvMxTYPE7FRuX/ohB7NS3EOeDuWk8umOOfy0byXjzryLhkGRHl/XYZgMatCBQQ20ureISE1yOV188+IPpe63LZvfv5jHzc9dR/1mdasxMjkVKdE4Tf26fDOfzlzO9n2+H6LjOwU3yyXXWRxnQ6CFX5ABzXJKbskAA5vPDnbk9dYLS28p82uMiCfc72ct/5XPb/ua1g2ScVkGhmFjGjBnUyzPTD2H5Ez4ceE6bjn/DPc5Vw7qytezVpGelVss2TBNg4iQIC4b6PlUtJ7aujeR96blf7bC1y346uelmxjctRXn9m7H8+sncyg7tVhdhYXN4Zw0/r3ue97te5vXYxQREd/atiqO5IMpZR5j2zZLf17FxXeeW01RyamqQmMWNm7cyIcffsiECRNIT08vtv9vf/ub1wIT3xk3YymPfzrjJE8yCniQZDTNoeGludx0S5cyp1G1DYPFaY1Id5WWf7sgZ8Hx410HuKD1v8l1OliwtTmbE+q5IxncfjdvjfoFA4vfV24r0krdiFA+fuBq6kWGAuDnMPE7Nka2fmQYH48dSZ0w768a/sOff+EoYw5e0zD4du4a9mUeYfHhraXOFOWyLZYl7WDrkQR+Xb6Zr2at4reVW8g+mXrDREROUzlZueUeYxgGuR4cd0qzq+F1GvC4R2PSpEnceeednH322SQmJvLggw8ybdo0+vbt6z5m1qxZPglSvCMjO5cfF67n/WmLajoULzLAsMAuKYGwIcDC0S2dpFybVUfiypxmNf8Mg5X7GjM4Jr7E4VWFfzOsWDeeV6dcwvZDx7uWY6KP8sB5ixjcfjc9mh+gf5t49qYU73pu16w+Pz1/K/PXxrFyW/6idn3axzC4ayt30uFtm/YcKrMI3bJttu47zKbUfeW2ZcUFceMv35GbZ2EaBpZtExYUwIMjh3C5D3pjRETEO5p3aIrpMIvVZhRmWzYtuzWvxqjkVOVxovHMM8/wxx9/0KtX/roCU6dO5YorrmDx4sXExMT4LECpuoSkNO58c5J7BepTTrCF0TwTe1sIuApu0vN7Mhxd0zECbLBhw5F94Ci7KdsF/xx/EV0aH+S1a2dSLzyz0F4HBJ4J5M/Mdc///LDsOkXO33skkn9OvJCXr5nJ4Ha7GNFtG3N3ltz17O9wMKxXW4b1alvJD14xwQH+GJT9ECXQ34G/UfY3ydoZhLUunFzy/5EqGIaVnp3Lc1/9jr+fg4v6dfRS1CIi4k11GkZx1pX9+HPKUixn8WTDdJg0iq1Pj7NP84dGWrDPKzxONLKystxJBsBll13Gzp07uf766/nzzz9PiVWMTzU/LljHCxNmlfkU++RnY8Tk4Gifhd02C476YbsMjAgnRmChz22AKxMIo5SeCrAtsPcEgWWwKaEBd46/lG/umkSgX8EChTZGyBhs2+bliXOw7Pypa0+IBrB55ZezGNx+F5HBWVw9pJsvPniFnd2zDSu2xpe632EaDO/Vjp7RLfE3HeRZxRdmtF1gbQot8zpvT/mTC/q2x2HW7GxSm/Yc5Lu5a1m9Yx8O02RQl5ZcM6Q7Tet5XsQuInIquvvNW9i0dBuH9x0p0rPh8DPxD/Tn8W/G6r7uNHDDDTeU+OfcqFEjbr31Vl544YUi+w3DYPz48RW6hseJRt26dTlw4ACNGjVybxs7dizz5s3j9ttv56OPPqrQhcV3Zq/axr8++fkkSjDKq7Mo4zx/GzM2fzVuwwSinSW2ZFtgp/lhHzJxtM7GtosmHLYF5JhYW/KnbXVZJruT6vDHhtZc1H0HYGNEvojh14bN8YfYkZBE6SVOBofTQ1myvRnhYbH0aNusEp+t6izbYsnhbXy/ewn7so4Q6RdOaKg/mVlOrBP+bhhGfq3I9Wf3IMI/mCuancGkPUuwT+j/sBMDyp3tKzElgzXb99O7Xc18boBvZq/itUnziiyMuOdQMhPnrOa/d13KoC4tayw2EZGaVrdxHd5b/h++fXkqMz6ZRUZKJn7+Ds6+fhDXPXoFzTs0rekQa5xh57982X5NGz58eInbIyIiiI6O5vzzz+e+++7j3XffxbIs7rvvvgpfw7DtUubYPMH333/PzJkz+d///ldke1ZWFtdccw3z5s0jNzeX7OzsCgfhLampqURGRpKSkkJERESNxVFTjqZncfH/fUJmTl5Nh+IZfwtHvxRcG8Ig2d/z8ww7v8vR38Lsll7qdLUnci2OxD7kj9EsG7NDJkbosWlrLbD3B2BtCIPs48OGDMOiZ/MEXhzlon7jOzH886dmnbd2Bw98OK3c6/3fJXO5fPhzmAHdPf9sXuK0XNyzbBxrju4ust1OdcDSaFyZuAvDXZZNaFAA/73zEs7okD8mN9dy8viaCcw/tAmHYeKyLRyGSd5uf6zV5f9svXrHxQzrWT1Dwk60attebn99Uon7DMDfz8FPz99K/ciw6g1MRKQWsiyLrPRsgkICcfiVM77YS2rz/VpBbM1feR4zOMhn17GystnzyP/Vyu9BYY0bNyYhIaHY157yuEdj5MiRjBw5stj24OBgfvrpJ7Zt28b27dsrdHHxjp0Hknh2/G/8tetATYdSIWa3dIh2YjbMxUr2w7NejUJ5cZ6JtTICtjlx9EjDqFPyrEe2nZ9I2If8AQN7bzCuvUEQ7spfGTzDAbnFn9Lbtsmq3U15648OvHDr8fUfosI9mxGqTp1eNZJkADy+ZoI7ybBdYB8MgCwHBFowJJHWGc3o6myLy7Lo2qoxI/p2IOTYIoG2bbP08HayXXkEO/xx2TZR/iF0jGxKr+gOvL66/MkEGkfX3C/Nb+asLtKTUZgNOF0Wk/9cx50X96/+4EREahnTNAmN8HwR1tPGabJg3/33389bb73lfv/XX3/x3Xff8fzzzwMUGzpVUV5bR8PhcLBw4UIuvPDC8g8Wr/h95Vb+Ne7nmg6jEmyIzsNocqwnokUWbAsBlydDqIziP5ypDlwLonCclQxOA6KcGMf+Ztu5BlZcMPbWkBPaNiDND0+Gbe08cASAPJeLpZv2cOhoOtHhwRxJyyr1nPBgGND7sXI+i28cyUlj7qGNAFjxgVjrwo4Ndzr2WR02Ozsm8Z8br6R1eKMi59q2zZubf2HC7oU4DAPXsQ7Po3mZLErcyoXde9I4OpwDyWmU1BdqGNCqUV06Nm/g409ZuuVb4sudXWv51njuRImGiIic3iZMmOBONLKzs7n77rt56qmn3Ps9HPhUqiolGjk5OXz//feMGzeOpUuXMmLEiCoFI57ZtOcgY176prYkw5Vi9Eh1r75tBNmY/VKwlkYeSzagYjUbBlg2rj/rgJV/I024M/++Os0vf1tZ55YjyN+PX5dv5rVJc8tMLgo7t3dXAgMCPAvfy77ZdWxRvv0BWKsiOJ6ZHfusLgNrfRgfzFzIayOvKnLu3EMbmbA7/3xXoV8uLtvCAJ7+axJPXn09T378Gxh2kWTDNAxMw+DR68/x6KnHgSNpTFm4jtXb92EaBmd2bMFlAzpTJ7yKT9ZO5h8MERGRMti2zZdffskHH3zA4sWLSzwmLCyMyMhI/P3zh6X37duXSZNKHlJcYP/+/dx0001ceOGFnH/++V6Lt1KJxsqVK/nkk0+YMGECaWlpfPjhh0yZMoWoqCivBSbFzV69lSc++5WcvOKzAZ1sjIRgKDR1rFk/D2N4EvbuYKxD/pDpKFIv4UGLYNl0bZbAur2NMVIcxWaEqqztCYd5/NMZFTrnx4XrOa93O3fNQ3Xal3kE2wZrfRhl9djMm7+HwxemUS803L1t4q6FmBjFVgTnWEuWbbEvLIH37ruSN36Yz9a9ie79HZs34J9XD6FH6/KLCGet2sZjn/6CZdnu6XGXb43nf78s5a2/X0afdpWfMrt3u2b8uS6u1F4N0zCq1L6IiEhN+PXXX3n44YfJysrCz6/sW/gFCxbQsmX5E5+kpqYyePBgVq5cydNPP80jjzxSZH9VZx/zONFITk7mq6++Yty4cSQlJXHTTTexZMkSevTowe23316lIKR0tm3z+W/LeX/aopNoFqnyWUf8is3ZZATZGO0zMduDa1k4dkJFi9IMWtVP5tozNvDlou5sOVDfo7MKFpwrTXolV0f9cPriGkk0GgVHQbJffk1GGVx5MObHj/lm5J1EB+YXRq9PiS8xyShgYbPu6B5u7zOMiU+MIS4hicMpGTSICiO2UbRH8e3Yf5hHP/kZyyo6p5VtQ06ek/ve+5Fpz93qXjm9okYP68XctTtK3GeQP7vWVYO6VqptERE5PRj4eNapSpyTkZHByy+/TEhICHfddVeZx3r68D8oKIi77rrLPeHTxRdfTKdOndixYwfvvvsuqampPPjgg9i2TVpaWoVj9jjRaNy4MV26dOGVV17h3HPPxTw2R77mWfadWau38PDHv9R0GL5RRmeDbYFdQnF2+WzaNUzigq7buKDrNjLy2nHDuKvYm5hSYiJhGgatGtcl1+lkz6Gjlbhe6SzbZs2O/RxOyaj0DXNlnd+4O18eXeHBkTZH0jJ5eeNUXu45GgATEyi7x8xRaEG/Vo3r0qpx8ZXPyzJhzppjVy/Osm1y81xMWbiOv404s0LtFujdthkPXjWY13+YX6Qo3GHmD+165Y6LqR+lGadERKTmpaamFnkfGBhIYGBgicdedVX+cOe5c+eW2aZpmkRGerZmVEBAAKNGjWLUqFHMmzePiy++mN9//52goCBiY2N54YUX3McWFIhXhMd3cy+99BK5ubk88MADvPbaaxw44LsZjmzb5osvvqB//9OzWDPP5eLJz2f4JMlw1Ja8MCovf+2KE9gWYAHpFe3NsDENm8t6bTr23kFoRC+evuE89w1mYaZp4HCY/N/o4WTkVK7HwhPpWTk+a7s0m9YdwVoXXv6BGFjBTuYe3MjB7PxV4/vXa4vDKP3XggH0q9emSvEtWL+z3GLtP9ftrNI1xgzvzVePXs+IMzrStF4kLRpEcd3ZPfn+6ZsY3LVVldoWEZHTQMHK4L58ATExMURGRrpfL730UpVDNwyD1q1b065dO2677Tb2799f+scs9CB2yJAhvPPOO1x77bU0adKE+++/v9irojzu0XjggQd44IEHWL58OZ988gldunShb9++WJaFy+XC4fDO3MsVGX92KsrNc3LPO5NZtW2fV9vt1LwBz954Hlc//5VX260cAzaF4kpzYHbOwAiw3ZtxGbiWRkCOA4JdkGVSfgdj/vn3Dl+Mn2nz67q2TF7ZkX0pjakTPpdrh/Zgw64DrN5x/Aetd9tm3H/FIA4HJ5Psl0L+j4J3szB/PwcNqvnJ+Zb4Qzz/zR8eHGlDoIVRPw8b2JK6n4ZBkYxqOcg9Y9WJTAxC/QK5qEmvKsXodJWQYVbimPJ0atGIZ29qVP6BIiIiNSQ+Pr7IOhql9WZURHJyMqZpkpKSwv/93/9xySWXsGLFihJHIU2dOrXI+4suuoj09HSvjViq8J1837596du3L2+++Sbff/892dnZNGjQgEsuuYSrr76aiy66qEoBVWT82anof78s9XqSYRrw1WOjiUtI8mq7VWPAviCsIwGY/Y9CpgM7IRB7byA4jw3L65GKvT4c0hwUTQKKFjgH+Tu579zFXNpjM/d8dTGrdjXFNMCyszl0NJst8YdoUjeCL/91PS7LYtvew+xJPMoPS9YyPXcJdnMgybvrPjhMgxF9OxAU4M/8dXFMXbieA8lp1IsIpXe7ZnSIaUBMgyiP1pvYsOsAE+euYeXWvRiGQf9OLbhuaA/aNK1X7NiJc9dgFpqWtmT5+8zu6e6Zvwp6MXrUieXxzlfw0oYfj7WTf8NvACF+gbzd5xbC/Ku2gFG3Vo3LLNZ2mAY92zSp0jVERESqpJrW0YiIiPD6gn0F5Q2RkZG89dZbREREEBcXR+vWrYsdO2DAgGLbrr32Wq/FUukug6CgIMaMGcOYMWOIi4vjk08+4Z577mH37t3ln1wGT8efnYpy85x8N2+t19u1bPj3V7/zz5FDCPAzyXVW/WmxV9gGZJnYO4MxO2dgbwtxJxkA9pbQ0pOMRtkY9fIICM/lH23WsHtbPUa+dx0HUvKHDBXcw9rH/nvAkcTDM78jK8NJyk4bP9sPl21hWxEQ6oQ6ucdWJ696Bu8wDaLDQ7j9wjO4770pLNq4u0itwJ/rjw8L6tehOQ9fM7TUOoeJc9fwyrdzipw/ddF6fly0nn/fdAEXntGhyPHlrSEBgAnmGamYDfOHjAWafnSPauHefXlMX3pHt2Jy/FL+OrqHANOPQfU7cHHTXkQGVH1Rp+vP7llqsTbkD50aObhmFjoUERE5lViWhWVZBFRgyv0GDRpw6NAhr1zf4xqN7Oxs8vLyStzXqlUrnnrqKbZt2+aVoDyVk5NDampqkdfJLD7xKGk+GtM/ZeF6lm7ew7Be7XzSflF2Kf8v6VADe3cQtg1m97Sixx4p6cb/2PsDQRjRTpwh8NqXw/h2STcOpEQUO96om4tj+BGM/kdJbH6AjE6HcVyQhNU2DbvghjzDAUf9K/wpY+pH8bcR/egQc3xxOj+HyQV9O/Dlo6P4ctYqlmzaA1Dqzf+KrfHc9MpE96KAha3fdYBXvp1T7HyXZWNZNk+O/5U9h5IrHDchLneSYWBwZUy/Yr0UMaF1ub/DCD458y4+OON2Rrcc5JUkA6Bv+xjuvCi/0NthHv/zcpgGBvD49cNo6eEMViIiIj5hV8PLB3bs2MHWrVuB/Pvk+++/n759+xITU/K07unp6WRmZha5xy9tkb6ZM2dWOB6PezTOOeccXn31VQYOHFji/t9//50JEybw9ddfVziIynrppZd49tlnq+16vlbQ1eUr439bwZNjhjNj2WbPTwqwIMyVv+J26om9C6UxaFX/CF2aHiQlK5CF21rgtMqo4XGZWIsi8xfWC7Ty6zPKvYSdn6A4C+IpIa6oPMz+Ke50umC4oeEA2mViOmysDWEcX228/J/6bq0ac/N5fakXGUrnFg0xDIO7LxnA/qQU0rNyaRwdTnhIEKkZ2UxZuL7MaXMhP2nIzs3jzcnzeeuey4vsmzB7dZGejGLfAmDS/L/458gh7m1ndmzB1EXrS+/VMGyMBrk4DBOXbTGkQUf+0d57C/N46s6L+9O1VWMmzF7Nmh37MYz82EcP60X3Vho2JSIi4qmvvvqK5cuX89Zbb3HkyBGuv/56srKyCAwMZNiwYXz//felnhsZGUlISAgul8vd8xEUVPIQ6RtuuKHCPR0eJxpxcXGlJhkAF154Iffdd1+FLl5Vjz32GA8++KD7fWpqaqkZ28mgeYMo6keGkpiS4ZP21+86QMtG0TSrH8nexJSSDypYVdvfwmyejdEk1z2O3840sbaEYO8JLuMqNk3rpNKhcSJdmx1k5+E62J4Uc7t7LwrfIJdxnm1gJ/sdG1pVMrNjBhjHE4zCDANonQU7ggstDFhw/ZKvaxgwrGdbhnYvPsaxSd2i08j9tTOBPKdnCyu6LJsF63eSlJqBHWixNXU/fqaD5VvLHgblsmyWb4kvsu3aoT34ceH6Us8xMOjSvS4tGkZzSbPe9IluVWNTVA/oFMuATrE1cm0REZGT1dChQ9m8+fhD44JSBsivpd6+fbvHbTVo0ICEhAT3+5ycnFLvpUvr6SiLx4lGaGjZawF4a9apiihrruGTkcM0uWF4b17/Yb5P2rdtm7ve+oH9h0sYYuawMTtmYLTIwvArOP6Em/RgC0fPdFxBFvbW4n8fDGxsDBKSwzlwNJxf/mpHcEAeLqusnpoTb+w9vem1IbXQTFEOK79H5Nh0cQRYmA1KHupXJOamOdg7Cg8JKvn6pmEQFOjHpf07s3VvIj8v3URyWiYN6oRzaf9ONG9Qp8jxLqtidTC2DU8t/YGVri3uBfNcuXUpb3TjiTlC26b1eObG83jmi98wDIqsIQHwwq0Xcl7v9hWKTURE5HRj2D5esK+WrMF84sPGsu6rK/Ng0uNEIygoiLS0NMLDS56fPy8vr9QaDvHcqHN6EZdwhB8XrS9z2Exl2MCKrXuL7zBtHP2PQrSzyI3riX+fCt6bHTJx7QmCbBMDGNR2Fyt3NSErL79XwsJ0d0xk5/pzvJeipL+glX2aXui8EBeOQUexdgRj7wjO3xfgwY2+DUZgaetgH0+ATMMg0N+P1++6lFe/m8MvyzYXqS349NdljB7WiweuHIx5bHtl1s9YmbYdK6RQNPVzID7oePJ0AtM06N+xRbHtF5/ZiU4tGjJp/l8s27wHw4B+HVpwzZDutGhYp4SWRERERPJlZGTw1FNPud/XrVuX+++/37c9GpdffjlvvfUW//d//1fi/m+++YYzz6zcSr5ynGkaPDlmOBed2ZHJf65j18EjRIQEsWzLHirx5+sRo1l2sSSjzBixCW2XSupfdWgQkYZhQpbTH7uEp+92wXCkMBek++V/bXDs5rn0YUqes3H0TcE/KI8bzl7PGrsVy+NiMHPzF/8rY+25/NKM0kY3+dsQ5CIyKJjr+/XhikFd+HzmcmYsz++qPDEB/HrWKuqGh3DNkO7c//5UVm4rIaErLQwDiMzDCnEW2W62yspP6Er4PhnkJ0AjB3crsc1Wjevyr2vPLvO6R1Iz2bovET+HSefYRgQH5BfEHzqazuzV20jLyiGmfhRn92hDoP/pt6aNiIicxqppetvayDAMgoKC3IlFVUYPeXz38K9//Yv+/fsTEBDA2LFj3dNk2bbNhx9+yDPPPMPs2bMrHciJThx/djoxDIPebZvRu20z97Y+f3+zUpmkJ8zY7DL32xbYh/0gzR+jeTYOf4tzem0jMashC7e14GBqeatQ5xdbO4YdwU4IwHYZ2If98+syqvqR6jjxr5PHG60W0DssEXv0JuZubsmPqzryV1IIOfWskos0jjGbZePaEkqRG3nDxmiWzdDhzXmh+3UEOfzZezSZ7+avLTPZ+2zmcn5buYXN8Ykeh2+Q/zNkdipel2NEujB7pmGtDscwcF/bYRoYhsErf7u4WG2IJ46mZ/HKd3P4feVWd8IUEujPdUN7kpaVzQ9/rsPGxjRMXJZFeHAgT44ZzvBqmbFMREREalJISAiPP/54se0+HToVERHBnDlzuOOOO3jxxRfp1q0bLpeLLVu2ULduXSZPnkznzp0rHIB4plWjaLbvr/yCe8H+eTSISCcz15/EtBNWqw51ldmbYZhAgI1rfShsDcEckExk/VzuvGQuF71xA5ZdTh0BNv2a7+Wyzuto3DOT/TkhvLu4L/uTGlb687gd9ePCQ4fo0y0x/zMYNsM6xTGsUxy7s8O4bvP52KX0nBgGEGZjNMzFPliQrdtgG/zniis4t20nDuek8Z8NPzJj2SZcrrITqrSsHI+TjIL+nKiwYDI6H8KqX/KwQ7N5DkYdJ/UTGhKWEuFesO/qwd1pWq/iSUZGdi63/fc79hxKLtIrk5mTx6czlxU5tmCxvvSsHP417mfeuzeQM0sYqiUiInLKOY17NLypQuMhHA4Ht956K1deeSVBQUFYlkXr1q3p06dPjc1cc7LKys0jO9dJREggDg+mtf37pQN54MNpFb5OdGgmd5+zlIu6bSXAL//GccO++nw0ty+Lth+7acwzIKD0v/G2BXaOCRiQC3mLozi7xz7qh2fSr9VeFu9oXuq5/g4XL18zk8HtduO0DfwMmw4hyQwcfpDz195Edl6hgu7KsA1Gdt1UvHAdCHU4y53xyrbAqJdXKNEwePqG8zi3bSeSctK4dfEHJOak4nJ5vtCNJ+67YhDNG9RhUNeWXDr/FZJySu9V8ouw6N2uPv/uXvWVOifNW8uug8kV6h0rSNPen7ZIiYaIiMgppKz7gWXLlnHRRRdhGAa2bZOcXPG1uzxONJYvX86IESNo06YNaWlpBAYGMmfOHK8vm36qW719H5/MWMrijbuxgcjQIK4e3J2bzutDaFDpN7NDurcmOiKYI6lZHl+rTkgmn98+mQbh6fg5jv9F6tA4kbdG/cLTP57DL3+1x9oThNkhs9ReDcMEa2/BnMoG5DjYtbM+nbsfoUmdshdJvHf4Ega1yV8t3u/YFAuZ2f58t6wrwf55xxKNqtVqNI9OoXCulpYdwPKdTTmcHYSd5sCIKGea2YKJqvxMPv3ndXSKze9pGbd9dn6SYVsY4c4yGqgY0zS4YXgfd+H4JU1780XcPEorS3fZNiOa9PTKtX9YsK5SQ/BsO3965P1JqTSpq595ERE5tZ0us06tW7eu1H29evVi/frSp8z3hMeJxmOPPcYHH3zAyJEjAXjxxRd54YUXePnll6sUwOlk1qpt/Gvcz/nj7Y9tS8nI5tNfl/HnujjG/fOaMpONvLyKTZl619nLiyUZAA4TLBsev3ge8za3JGNXMLTMwg6wixVP2xaQ7sDef7wQyDQslu5sysU9tpCaFXT8p+WEAu+QgGzaNUzk1RlnsSspisNpIeQ6TRLTwshzOU7obShrZqqyZeX6ExzgxOkyefuPfkxa3pU8V6HplqNzcfRKwwgt/v0zTLCS/DENgysHdXMnGTmuPKbvW+UePkQdJ0Q4S1+00LAJ9PcjJ7f8tTMGdW7pTjIArm3Rn5/2ruBoXubx6x1jYtAzOpZ+9dqU/43wwKHktCqdX5nZtERERKR2qlevXrFtBQ8k/fz8aNiwasPcPV6Ketu2be4kA2Ds2LHMmDGjShc/naRn5fDk+F+xbbvYjEWWbbNt32E+mbG01PMTjqSSVoGbvEC/PC7qvqVYklHANCDAz8X5XbeBy8DafXwVSNs6XnhsJ/njWhSVv0ZF4Zgtk6xcBwu2toBIJ44hRzD7pELU8Sf/QUFO7vricr5f2ZnlO5ux83Ad9h2NIrdYkgH5N++V69X4dX0bnC6Dp388mwlLuhdNMgCS/XHNr4OdVfSvu22BnWViHwjAsm2iI0KYOGc1SzbtZm9qMtkZLuxCHRlm91TwK+ERh2Hn17C0Svco3pvO61Pkfd3AcMadeRcdI5oW2W5icG7jbvy3142YZU6fVbrEo+l88NMirn7uCy598tMqDXE0TYMGUWHlHygiInKysw3fv2qp1atXe60tj3s0TlyQLyQkhPR0z26sBH5dsYWcXGeptT+WbfP9n+u4+9IB+B/7Xh9Nz+JIaibLt8Xz6YxlpZxZsvrhmQT5l/103WWZNK93lMBzjuIMPj69rbUzGLJM7MSAY4viFWXbBt1iDpCUHsKHt/zI3xMHkW35YUTmYDbNwXaB668wjuwJdR+f78T/e8eEJd1o1+gwM9eXMiuSbUAeWNuCcXTLn93JtgCXgb0sEmyDZnVSCcx+lYGxOwnwc7Hpr/r02d6VpXFNIcSCHAOjXRZGvxSID8LeG5SffDlsjObZmG0zIdAisH4ezlwb62AA9t5AcBZNEJ4acy492zQtFmLTkGg+7X83W1P3szFlH36mg751W9MwyPOC75w8J8s27yElM5umdSMxDPjHO1PIznViHcscK5tnOEyDc3q2JSqsrFXhRURE5GTXrFmz8g/ykMeJxtGjR3nllVfK3fbII494J7JTiMuyWLRhF4ZpYJexAF96Vg5HUjNJSs3g/WmLWLRxd6WvmZHjX+4xBjbDe/bk0kZjuX/l52xNjceFieFvYa0v+cm1gUWQv4uLum0lLCiXZqRRPzmL+NxCMzI5jfyF5rycUJQmISWCx74/D4dh4SptBizbwN4TjNUuE8NlYO8NwtqVv+hgg3opvHPddBpHpbl7gOq02UOAn4t1exuSmRkA2Nib8hMno0U25oWHMSwD/IoON3NF52DYYDbMhQ4Z+b1BqX60aFCH1+68hNZN6pb5WdpFNKFdRJMi2/IsJ3MPbmRp0nYs26JrVHPOb9ydEL/84Wy2bfPtvLV8MG1RkV4v49hItsJ/48oqz3APfDOKHucwDcKDA7nv8kFlxi4iInLK0KxTXuFxonHZZZexadOmMrdp5qniZizbzJuT55OYUnydhJIs27yH57/+A1cV18xIzgxh9e5GdIs5iMMsuS0/h02ENZOQzHg+6/tPkhP/zraMTBytLWYYnfhxVWdMw3JPX+swLEzT4tVrfyUsKNfdzhX1dvB7cgybs6KxMbAPBfigS7DsGo7kjBDK/al1GVgzC41FdNgYLbJJirEYufkCzCyDhilObmq1gZZ1j3L/NyOwrOK9MPbu/N4Ms1cp9Q7GsYFggRBydiYfd7+L9o1LHuOYmJLO9CUbiT+UQnhIIOf3aUenFo3c++PSD3Lf8s85lJOC41hGM33fKt7Z8iuv9hxD77qt+GrWKt74YX6xtivyV8gwYHivdgzr0YZxvy5j+77DQP6igEO6teaBqwZXajpdEREROX0Ztq9WgasBqampREZGkpKSUitmw5q+ZCNPjZ9ZY9fvE7uX92/8CcivyThRwZ+8Oz90tAHXDsDGtmHelli+XdaVLQn1CPBzcU7HOK7tt44WdVOKTSf75cF2vJ/QFZv8eg9rTXmL+JFf2+BxQlJWolGJWasCLBwDj0J4/vAywzi+kriV6E/Y6kDSswPLXCPE6JCO2SYLw1HqIQD8q9NlXNW8X7HtX/2xkjen/Jm/WPqx7geXZTOoS0tevv0iXA4XI+e/TkpeRrHE08AgwHQwrvfd3PzsJHLyyi9CLzG2a4cS6O/PGR2au2eTsm2b+MSjpGfl0Dg6gjrhIZVqW0REpCS17X6tsILYWj39ImZQUPknVJKVnU3cs4/Xyu+BN1VoHQ3xXG6ek/9+P6/Gru/vMFm1uxmPfX8eT106h5CAPJyWiZ9puROEYh1Qru1AEDZ5GIaLwe13MbTDrhLbP/Hci6J382FCF1yAEenJVLA25oCjWKsjINPh3lZ6wlAwsOcEQS7INss5N79tI3+9awDM3qkQVnShQvcQqAgnqVmR5bZnbw6F1sWnG7YzTaydwdgHA8CCTzauoONVLYr0VMxYtpnXC/dCFEokFm3YxdPjZ9Ln/Lok56aX2E9jY+O0Ld6eO6fSSQbAlWd1c9cEFTAMg+YN6lS6TRERERFQouEzizbuJiWj9EXYfMXPYfK/B66mW6vGXPfCV8zaCAu3Nefczjs4p+MOzmq3p5wWnBxKq0tYSBI5lh8Rfrnu9S8KlLQ4XrR/DjcGbWfcwt7YB/JrGvKVPBUsDXIxop04+h+FOVG4rFKmjS164gnvbYyhyZiZDqy4YOx9gccuW/Q407CoE5rF13d8T0aOPxPWdOGneg1xlTLpmuH0ZAYso8j/CliH/LGWRh4b25m/88C2XMb8ZwJRYcGc2bE5wQH+/LFqW6ktW7bNH6u3kdhyf5mDwVy2xV/Ju3F0d0Kd3Pw6lIMBx2pPyu5mMQ2Dji0aFEsyREREBNVoeEnl5syUch1Oqf4ZuRymwcVndqJ76yYYhsElZ3bCMCA7z5+f1nQgPMiT6XGd/HtqP26bcgl3bR9KfE5+UbjTNrBOHGpVyB8bW/HJd/0x9gUcm2mp4KASpoINtHB0T8cwwQizaNXlID2a76/UZ7b/jML1Vxh2qgOaZ2M0z4YTalJ6tdjPp7dOoV54JjHRKfxr2EJeiF2Cg1LWJQm0irVRqqN+FCx9YWcb+UmGRYlDwo6mZ/Hr8i1MWbi+3KmKTcPg4K7yE9WcpmnQPAsj0oUR5cRom4lj2BGMerllnmfZNp1aNCQuIanca4iIiIhUhno0fKRuRGi1Xs80DPwcBmPOysLOWQwBfbhsYBe+nbuGhOQ0LMsm2P/4kCaXZbApoT6ZOf40r3uURpHHi9UD/XLZcbgpjpxUrt98Hr3CEukakkSH4GTOrlM8IUhKD+bJycOxbaPo+hgmGLFZ2HuC8pMPfyt/xqY2mRiB+TfytgU7jHCsPR7UdBRjQEahlcVT/fK/6phBpJnLIx1W0K7RYWLrpRwP6VhqPSRyP5fU3cWPSa3c++x0B3aaAxw2NMmGveXPnGXFBePom18Ubu8Jzk8yvDDblmkaRPuFk2wcKraIXxEGxYZ/2QaY/VJw/V4Xckt/ljBp3l9MmvcXvds25dmbLtCK3yIiIgV8vDL46dKjoUTDR1o2qoO/n4M8Z+XHz5fHYRoYhoHTZRERnMPLV/9CbGACdjJgRhMWNpZx/7yGW979hgP7M9l6sC7tGyfx46qOfDS3D4lp+b0VBjb92+zhkQsX0Cw6lZ2J0diZfseGSBmsSm/AqvQGnBWxv1iisX5fA174aQh5rsK9GMeYNo6uGdhdMvJ/YEu75/W096BURWeGsjeFcfV1CxjWLg5HKb8lbOCaetv4MakVdrqJa204HC60Krvj2M19sYL1orUg9v5ArJ15mC2zsRLLn1LYU06XxfntOvFOWulDrEpjGGA7wGyRjRkXxkX9OrIuLoF9Sank5BWvn1mzYz+3vDqRiU+MOeULv3Ozc1kwZRnxm/cREh7MoCv70bhV1VY9FRERkZIp0fCyfYkp3PTKBI6kFy8SrgzTMLDs/H6CRtHhtGpcl+G92tKkbiRLN+8hN/cQHaI+55yO2wjwK3QTaR3BTn2KBuFZ3HRjV/675Fc+OdCBIwtCeGdWfwqn0jYGS3fEcNO4K/niziWk5zWG7CzshABolEvbkKN0D03CNCzSnX6EOvIX9/txVQde+GnosVZKeIrvNLAzTAixSk8yDLCPeu8GveATtbXSMcp4XGAaEBuUBlkGrj/rQN4J8buOFZgHu44Vqx/bH2JBgAuOFiQlBtZfYdiH/fPXD/ECw4Co0GCuO7MPuTsz+Gj7H5gYWMc+Tyll8cWENLV5+7KR9GjdlKWbdnP325NLPM5l2SSlZTJx7hruvmSAVz5DbbRo6nJevfU90pMzcPg7sF0WH//rS4aPHswDH99JQFBA+Y2IiMjpQTUaXqFEw0vSMrP5YPpiJs5Z47U2g/39uGRAZ1o0qMMFZ3SgzgmrMvdtH4N15FbI3QqU3HNipf2X8MPjsJP92OcXzruzC6ZZLXpT7LJN0nMC+d/8ftw8cBmv/9qVenEGLw6cS4/Iw+76jIJpcncfjuCF6UOLDpUqxsCKC8bsUvIaIradH7YdH1j2N6LCDHKdjvwVycvo93RaBs6NIZBbWvG3AZl+GP2T8+tJAmzsMBdGmgPX3DoU7kmx9wflJ4VV/M1R0Ev1wq0X4u9wcFubc2gV1oAvds5nQ8peAJqH1mN/ZjJ5dum9ZYYBXVs1pkfr/FXIpy/dhMM0cJWyYKRl2fy4cP0pm2j8NX8jz458DdvK76lyFZqpa9Y3f+JyuXj867E1FJ2IiMipSYlGFbksi/enLeLLP1bidJUxlr4SGkaHM6BzLIO7tipxv+06BLkLKSsttu1cVqz6BNfaTgVbSj3WZZnMXBvIIw8vISUjh0t7bqZhWH5Re+F1OCwbQgKdBPnlkZVX9lNge2cwdv1caJgHHK8nKCg7sNaHYrbJggALK8MBO4PAqvocBX9ujeWCrttL3T99TTs+mHMGpJY3VMjGXlwH27CJap5K8y5JJNYLJCEg6liCcpzlhSVpYupH8dzN59MltrF729mNunB2oy5ku3Jx2TYhjgDGrvycpYe3l5rYmBj0qtPS/f5wSkapSUaB5DTv9MLVRl8+OwkoeRFD27KZM2Eho/9vJC06NqvmyERERE5dmnWqkrbuTeT/PpvBkAff57OZy72eZADsPpTM2PenMmPZ5pIPsBIpr+/NZZk0CC9/VXKHYRETfZRGkWkcSA3j7nOW0yQqDT9H8fZNA+qHZzK8c1z5H8I2sJZFYq0Ng1QHtgW2E+x9AdgH/HH0yMBomwlNciDJ/1iSUfUb9tmbWrEvORynq3hPxYdz+vDM1GEcTA3zoKWCzMggLT6cLTNb8mzYSl4fOYOGEYVXBi+oGqta7LsPJvPd3LWUtI5mkCOAUL9ADMPg+thBZfaeOEyTy5r1cb9vWCccR0mrNhZSL7J6JzCoLimHU1kzZz1WGT+jpsNk/qTF1RiViIjUanY1vE4DSjQqKCk1gzvf/J7rXviKX5ZtJjMnr0rtlTRVbIGCe80XvvmDrNwSrmPWLbd9h2lxMKXwDXXRCwY48nj28lnM/tcnTLl3AlPunUBkcA7ZeY4yY7MsuKj7lnKvD+Sv77A7GNfcaFw/1cf1c33IMzEaH+vlMMFeFwYpBR1sVa91yHM5uOeLSzmQkj+bldNl4LIMth2IZtz8vpW6jssyyXU6eOKHc+kXu5fxt0+mfnh6foJhAA1yqxy6Tf4wp/W7DpR53Jn12nJnm+EAOAoVwDgMEz/D5D89RlEv6PgsUpf071Rmj4ZpGFw5qGvVgq+lMlIyyz3GNA0yjpafkIuIiIjnNHSqAjKzc7n99UnsPpjstTY9GW2TmZPHrNXbuLhfpyLbDUcjbP9+kLccSlkTwmWZ/LahdYn7zumwg+ev+oMAv6Ln1g3LKjcu04S6oeXfwJWqcQ5kmrh2B2OnOOBQAN5IMI6z2Xc0nKveu46h7XdxVrtdBPhZjF/YnfJXES+rVYPEtDDe+G0AD12wkFvPWsnLvwzJTzZyDa88ofh/9u46PorjfeD4Z3ZP4k7Q4E6LFSmuBUpLS0sLtV+Nuru7UW+pu3/rCi0thVKsaHGKuwWI+13uduf3xyUhIWcJMci8X6/7fpO92dm5cEn3uZlnHl0TTP1xAW2aJGC1aAw6uTV9OiQhjor8JrcdTs+4Vny7ZzFrM/Zg0XQGNejI+c1PpUVEgzJte7ZtyogebZmzelu5f1tdEzSKi2LikG7HPvg6KK5xLNYQKy6H7w8FDLdJ4zaNfD6vKIqi1C+imre3rdatc+sQFWhUwC+L/mNPFQYZwbLoGvtTsrw+JyLvQqZfWPRd+WDjg3m9vOZR9Guzh2cn/omv1TT+ZjMADAkHMqOK9kI6emIs8I28uT0MtoeW2kKpKoOMI/0Zps5fG9vw10bvwVZlff/vyXRqksq47lt46Y+BuE0dMop3z6p8IAOeXaBWbtvP2p3JSAlfzllFh2YNeO3G8TSIKbvcq0dcK3rEtfLR0xFCCJ65ciyv/7yQ7+avwVmUDC0EDDypFQ9eNJKo8JBKj7kuCwmzc9olg5n5yd8Ybu8BucWmM+LiQTU8MkVRFEU5salAowJ+WbS+VpbUmaYkMsyOlJJDGbkYpklibARWXUfYukHcp8isB8DYXXJOrsPKu3N789XSrgDER+TRv+1erLqbf7a04OaRSwLeCnvqaHh/ThfwU24LpC48UQfgubk2CXiTLSRsL0rCrtIf6NGdVfJmXzcRTQqR++1g+upD8sbsUzmj6xaiQ52k5YVBrNtToHBVJOWCDSE99UKM4Fcrls772XYgletf+4GvH/w/UrPy2J6cRojNQtdWjbFa9KD6k1Iyokc7endIItdRSIjVQsfmiTSOO/EL9V36+CSW/bGajIMZZYINIQRSSm56/SoiYk7MHBVFURRFqS0q0KiA1OxjWCp0jPKdLs5+5CP2pWYDEBMRyqQh3bhidG9stt7I+D8Q7lVg7KHQiOCsFzaRnW9g1Q3uPn0BZ/fYhK5JTAnamQuCuqYQ3oMNU8KSnIYsEonoI9Mwd4ciD1shx+K5v3ZD4E/1K/qpfzDtBTTPhz2hFey7dBcSkeRE75aL7JKLsTgasrzV+RBk5Ify08qOZBV4tufV2uUjGhYiQ03MzWGQVjSTpHsqoouWBci5cZ6clQoGWIYp2ZGczuUvfM3GPYdKzo8OD+HyUb259LRTyi2tKmaakk/+XM7ns1eQlefwDEkTjDqlA93bNq3YQI5T8Y1jeWPpFD647wvmfv0P7qIZnZYnJXHZ45MYML5PLY9QURRFUU48Qnrb3uY4lZ2dTXR0NFlZWURFVf2ntBdP+R+b9hyu8VkNu1UvWepSmhDQp00hUy/4CoueD3ozCL2I+79KZNbK7QA8d/4fDOu4E60Saf9SQmZ+CGE2F3ar5/r5Lgs/prXm3UNdcMmiT9LzdNwrIkstHapqpWdM/LSJdaOdko05O1CSvK/+JGigD8tARBieLXjdAuOvOCgM5gcoEU2caN1zEVaJLBSeIn52E1H0o2q3px2Zuw2S03P8d+WDr2J9/zfyFG6fMNjrOc98+RffL1hb7riuCZolxPDZvRcQGXZiLpvyJjczj0O7UwiLDKVRq0SfAZqiKIpSPar7fu1YFI+tzf3PoIdU338bDYeD7VMeqJM/g6qkZjQq4JwBJ/HMnjlBte2Q1IBLR5zCI5/9iWEe29a33oIM8AQCS7dZ+XVNC8b33AjGPhav/orF/52GwEanJimM6Lyz0tf9ZGEPPl7YEyEkHRulIhFsPNCAAtOCSCwEq0TL0zHTLAQ/g1BqZiLGhdamwNOXAJluQe4IRZYkhpe+pQ7Qf8NC9FOKb94rMltStGOUFGCT6H2yERFF+QsaSKtEtHAgtwaqt+EZo0y2YxTo6AMzETYJtlIV2NMtbFufjWlUPlT1debns1cwYdDJNE+MLXN8455DXoMM8MyS7E3J5Ou5q7l67KmVHtPxJiImXC2TUhRFUZQaoAKNCjjz1C78sGAdWw+kYvrYKrRtk3ieuXIsbZsmsCM5rVJBhr8KzkcTSL5d3tkTaAB9Wu9j7n0fkVVgZ39GFG5DeK2F4Y+UkOu08dGCniWJ5Ct2l11iI5M9y4WOhEDB3tx7AgjR3InWPcdzn188WdDAhdbQhbk5DHNTOEHnfDR2YOlTaoagUSEcsnmCBx9jEMPSEU4NecjmGUOMG9HEWTLzUJrW2IlRLtDw8XqlgAwr8qAN0aTwyGEJxvIoTLfpddmUEBBqs1LgdFVqxkzXBNMWb+CmsweUOT5t8Qb/FcGl5Pv5a+tVoKEoiqIogahdp6qGCjQqIMRm4b3bz2PK13P4898tZSpBN4yN4JZzBjHqlPboReuUIkPtFeq/+La1IovZhnXaya0jF5V8r2uek6NDnUSGpFQ4U6E4J+P5GYMCVv0udRYVyokINz1BBqWCjFJfax3ykWlWZIoNT6kX/z8QcdS7WO+Yh3HYVvSD9DYuCVvCEJ3y0Lrk+R26ECDLBWqB/oEk5p4QtNKBxiEbOHSfZ0oJhS6j0svyJHAwPbvc8eS07IBBa0pWHlJKtYRIURRFUZQqpQKNCooMC+GZK8dyx4Qh/LfrIEITdG3VmJiI0HJtG8RE0K11Y9btPFgmKPGluEWwaTMW3eD5iX/6DEw0UbGgBWB3WjSvz+7HvM2Bt0z1qPhWrlqLgrIzGUf3aIJoXVAUaAQxglRrmaR1EW2g98/EWBkF+XqpMR7JzZD77RjZOvqwTP+ZHxJkvreB+jtLgPOoc7IsaJqn0KEvbtOkc/NENu1NKfN+8ZWXcfRoYiPLL++KiQgNOEMWEWpXQUYpGYezmPXpXPZs3E9oRAgDJ/Sl6+DO6mekKIpS39STWYfqpAKNSkqIDmdIt8C1Ga4f158bXvsxqJvFiooKcQL+a14EqjxuSk/V7K+WduWPde3ZdjieigUOFb/5kpkWz9KmRoVexyc0IK64uFoQgUyBjky1IBq4j/QR70YfmY7M1Tz9WSU4hWeHrN0hniTtXAsyQ0fEec+BAc/PTzRyIYalI50awm5i/BsFObrvcQmJCDMQCCSSUN1Gj0YdWLBpn//XATx88WnMX7+Db+auJj2nAIDOLRoSZrexcts+nwGDYUrO6Nup3PHT+3Rk2uL/fF5P1wTjTu3s8/n6ZsYHf/Haje9jGiaaJgDBz2/8zkkDO/L4z/cQFRdZ20NUFEVRlOOGCjSqWZ+OzXn+mjN5/PM/ycl3YtE1TFMGNcPhj0AyovP2Sp9vmBopOWH833sTyMgPJtHZm8oVppPJduSBEAgz0PtllSRfl+sagu7f3BWCSMgtE7gIAUSYJV9Lq/QslWpZgLEw1hN4LIpBnJ5WLjejeIbE3BKKuTUM0dTpSVyPNNBaODDX+0kmloJODZowrlM7Ym3hDGrQicXrdjN/rv9AIzYihHbNGtCheSJXjulDek4+NouF6PAQ9hzO4KJn/oej0F3uvSMEnNazPR2TEsv12adDEr07JLFiy75y5+maICzExiUje/odV32x7PdVvHLNOyXflw7qNizewuPnvsiLfz+mZjYURVHqA0n1zmjUk9mSSmx6qlTU8O5t+fPZa5hy5ViuHtuXO84bTIjt2GI8XTOZ2Htd0O2zC44sQ5JSMH9zc6748JxjCDKOQXGSdoGG8U800lX2xk2aIA8Gmx8CoqkDvVdu+csUBQslS6qKvw4rzhERYAjkHi+5NJk6xvJIzI0R4NaQe0Iw5sZiplgRLQogyvCbyXX/6aOZ1KI/oxp3I9RiY+mmPQFfR3R4aNGn6KBrGg2iI4guqtbdPDGWD++cSMtGZXeV0jXBeYO68uTlY7z/bITglevOYmTPdmV+DgAtG8bx4R0TK12wb9/WZDYs2ULqgfRKnV/XfPHU9wjNRy0Sw2Tt/A1sXLq1hkelKIqiKMcvNaNRQ+xWC6N7dyj5/sXv5h1Tfw+MP0jLBlkB20kJ2Q47Ow/H0a15Mj+tOJn353cnJSfimK5fJQX5pACHhtxrR7R2lIwXwNwRTAAkwW6i9SxKLD/qcr4+eBYa0LAQwgzI15AZNmjlWYZmbgvB3BgO5lExuPQkvJjLo9BHpaEPzMRcG+GpHl6yu5XnNXfr0YAuLRqVOX3D7kMBX016jv+CkB2SEvnu4UtZuyOZrftTsFstDOjSirgo/z+rsBAbz151BrekDWLRhl24XAadWiTSrXWTSn06v+z3VXz04JdsX73Lc0BAn9N7cM0Ll9KiU7MK91cXZKflsHHxFr9tdIvOop+X0fnU9jU0KkVRFKW2qF2nqoYKNGpJRbaw9ea0vhMQ+dMCthPCswNV9xbJbD4YzzO/Daz0Ncuxmp5cB6/byAZ/A2sesKO1dngK5AHmykjIDuatKaBQw9zp2eHJ2BGK3G9HNChE71F+hqPMmQJErAuZb4einbqkBHN7GJi+t8XFBfKAHa25E61nDmYDJ3JVtOfpEBNrewcvXXZVuTNDbIGLGdqsgV+zEIJubZrQrU2TgG2P1iQ+ivMGda3weaXN/34xT056uWyAIuHfmWtYv/ABXlv8zHEZbDjynQHbCAHO/MKA7RRFURRF8VBLp2pJ19aNK3WeJgRdWjQkLPJUsJ4KeCn84MPPKzuha8dWPPAIAU0LPEnWZRYyVjR48sxqmKlW5LYwjNlxyP0VqMQpBXJ9pOe87aFQoIMryLe16Un2FYlFN49OAQ4/Sd5Fw5XFFdCzdOT6ouRgXSKaObm81wBCRfnxD+3Wxm9ivq4JRvRoF9y4a0mh08Wr174LEuRRQbJpmDjynLxzx6e1NLpjE9cohvBo/zNDbrdBy5OSamhEiqIoSq2SNfCoB1SgUUvumTisUueZUnL56N4IIRCxb4GteIZC40jQ4T342JsWg3H0kiCvgnz37wqDSBeeG/Piu+hKJMrmWTD/ifEsWSrwFTgFGJNJycyKTLOWzI74Ik2QaRbQTUSjokAjyN8G6dAw/o3EmB97JKgxBHJbKO9/tJoRd7/D1J8W4HIfSXI/q1/nMjkYpQkBmqZx4bDuwQ2gliyZ/i85GXk+nzcNk3//XE3KvrQaHFV5+7Ym8+EDX/LMxa/yxs0fsmHx5oBbRlusFs645jQ03fubQAhBSJidYRdW4YygoiiKopzgVKBRSzokJfLCNWeie7nxtFl0EqM9ORSaKE4OFgjglnMGlnzyLbQItLj3EfHTEBE3Q/hkRPSLEHE73v5pI0MdaCLwjEaI1XXUEV83aQLSKlaUsHKC2d2q1POFArzWvijqTYLca4dCHZo5MXeHIDMtCJuESDd+gxop4KDdM+tSbsmY53tHoZvPZv3L3e/9WlJBPjIshHdunUBsUb0VXRNowvNvGmqzMvWGs2meGEtdlrzjsM8b8RISDu06XDMDOvrSUvLh/f/jig638O0LvzDv28X8+u4sbh3wEA+f/VzA5VEXPzSBVic3L/caNV1DaIJ7Pr2ZsMjy9XIURVEURfFO5WjUohE92vHP1Jv4dOa/LN64G00ITjulPecP7orbMJmzeht/rdpKvtNF2yYJnDvwZFo0LH8zKqwdwdrxyK22YyaS8gHFqC7bmfWfv+U5koHtdvPSBb+z8UADHvzxNJIzIzFlLcejdhOcwS8RE20LINx3QCWdYK6OBCTsDkUCBoBmliynOlZSwvx1O1i0YRcDT/IUP2zfrAG/PjWZWSu2sHTTHgzDpGubJpzZtxMRFawiXxsiY8Mx/VUcLG4Xd6wbDVTOL2/8wdfP/Qx4ZldKWz5jJa9e+y73fX6Lz/PDIkN5Zf4TfPP8L0x/50+yU3MQAnqN6c5F959Ll/4dfJ6rKIqinFhUMnjVEDLYMtTHgezsbKKjo8nKyiIqqnJbdp4IpCxEHh4IMrPMcbcpuOz9CWw7FI8hBT1bJDPm5C3EhDk4mBXBjDXteea8P2ken8Pva9vx8E8ja+cFlHGkmndQhEQflYYI8f62lhKMZVFw0Oalz8rVBfFF1wSDTm7Ny9edVWV91qas1GwuaHoNbpf3AodCCJp3asr7616u8VoThtvgwubXkXEw02cbIQRf7HyTxOYNAvZnmia5mXnYQ23Yj4MgUFEU5XhSl+/XisfW/q5n0O0VyBmtIMPpYMuLD9TJn0FVUjMaJyAhbBD9ODLztqIjnptuiyZ58/9m8MmCblzcbzUNogo8y4gA04SLTl3HgYwI3Kbg1zUd0IRZ+7MZQIVu/iMMn0EGAOkWOOjrxrFqb44NU7I/NfAWxMeL6IQozrtjXMmswdEkkiufuahWCtptW73Lb5DhIVn620rGXT86YH+apqkq4IqiKPWZKthXJVSgcYISIadDbCgy50VwH6kPEBMRzW2jF5fUqxDCc3utFa1Mahzjqa6dlhsWMMjQhMlVg1dgSli/ryGbkhuQWVDNa9ijXYgIw1PQz/CyzCnAPa65L8QzX+l1S96qJYAwe+BtbY8nlz05ieSdh5n//WKkKdE0gWlKwqPDuPmNq+h/Vu9aGVdhQeBtZ4Wm4QyinaIoiqIoVUMFGicwYR8KtiFgbAczE+laBzlTPM/5KmZXdLxJTDY7UmL9BBuSNonprNzdmH93NTsqydzfEqSKLk86UgxPtM1H7g5FZll895GrI10CYfXxUYFTq7FPESSwZkcyV7/8HfddMIw2TRKq7VoFeQ72b03GareS1KEJmlb1M1GH96by4BnPsGv9Xk/CtAamKbGH2bj/f7fSd2zPKr9msJI6NkG3aBhu3zkkpmHSulvLmhuUotQiwzBY+OMyfn33T/ZvPUhUfAQjLxnMmCuHExETXtvDU5S6T81oVAkVaJzghBBgaevZ3jP70aDPO6vHJuZvaeW3TVa+nR2H4wDKBCRCSGS5GYPK5D+Uys9oXYDcFeopEOivH1Mgd4VA2wLvwVSI4Tm9Bn/BV23fz2XPf83n911Eq0Zx7Mg9xMLDmyk0XbSLbMyABh2waMEnu5eWn1PAxw99xe8fzsFZtKtSWFQop555Cje/eRUR0VVzQ1HodHHPyCdI3umpcF462dpZUMhj5z7POytfoEXn2qkzEdMgmsHn9WPe94sxvQQbmq7RsEUDug/rUgujU5Sa5Sp08di5L7Bsxio0XcM0TFL2pbJjzW5+nPobL897gkYtE2t7mIqi1AN1YQG+UhNkNri3Bt18YLvdnNpmj9ftcDVh0jQmm8M5kRheZjyk1Ch/Jy/AYhS943zd5UuIcZV/XpMITQYOMoqYm8KRqZ4lS6XraUgJorGzRpZNlRmPKXG63Lz60zxuX/EpFyycyltbZvLh9r+5e9UXnDXveVZn7Kpwv458J3cNe4xf3vyjJMgAyM8uYM6XCzmvwZX8/uFfVfIaFv64lP1bk73exCPBXWjwzEWvYri9J4rXhOtfuZzEpIRy29PqFg1biJUHv7qtWmZ6FKWu+fzx71j+x2qg1IcC0rMFdFpyBo9PeDFgbRlFqe+Kd52qzkd9oP6rW28EfkebEgxTYJieJVTPT5zJpD7rsVvcJW00zeSMbptJissMUJOj1M285pl/FI1caN1zip4+ejwSot3oAzLROuYf6UMAsS7kYW+7RPl6IQJzcTTGykjItCCdApmrYW4Ow1wRHUQHVf/bb5iSBWt3sWifJ9gzkRhFUVC6M5ebl3/MztzD7N+WzGs3vM85cZczxjaJKzrdyk+vzaDQUT63YPpbM9m2eme5Kt0l13SbvHz1Oyz4cekxj3/hT0u9FhssbcfaPbxy7bvHfK3Kim0Yw5vLnuX8O8eVLA2x2q2MvGQwb694ng6929ba2BSlphQ6CvnlzZk+/y6YbpNtq3ayYfEWr88riqJUJbV0qr4Q0aC3BGM3vm6kNQFP/zoIm8Vg4ZaWTDhnBacN3ETf3tv5Y0cbFmc3oluTQzzaaSFXfHhO0DtSiaFpyDkJYJGIZk60EBNzaxik2IoaSLBIsJqegKJdPuwOAYcG8YWIKKMo0Aik1PIsKZB7QzD2VmZruuqb8TAdAnHUplcmErc0eH3pdLaO/xuX01WSa7B/SzJv3/4J879fzLMzHyqz1er0d3zfTJT2ycNfMfCcPse0G5Qj11FSfNCfmR//zYTbzqDVyS0qfa1jERUfyVXPXsLkKRfjyHNgC7Wh65VblqYox6PdG/aRn53vt42ma6ybv0HVhlEUf1SORpVQMxr1hBACEX4lvt7ZhilIzw3l1zUd+GbZyezPD+et9JO4essw7vhnBH8s6UTWiniWzm7H98u70CQmG13zN6Nx5DotyUO3GpCne3a5inchmheAzfC0k4BLg1Qb5vJozCVRiGYOkAKtrQP95DyIcQeYZ5TVGR9UHbuPn780WZi/DafDVSahWUqJlJINizbzxRPflznn4K6UoC65Z+N+9mzaX/kxAy06JyH0wD9g3aIx67N5x3StqiCEIDQitM4EGWqZilJTgv5AoRa2oVYUpf5RgUZ9EjoRQs4DwG0c+Y+MYQoKCi3c/tXpuIyiHZ3cGtINxsIYzFVRnvoTBTrOdDvPzhjEmj2NMUwfbx9NQpgJdoPLB67gu0EzuKj3WkSqjrHDjvFnHHJFNBTqnmuVRAhF/59iQ2ZZEEkORKJnyZDeqiBAboWo258OCBAJhYgQP8GZVWD6CKZMUzL9nT8pdLpKjoVFBr+VcF6W7084s1Kz+faFX3hy0ss8c/GrzPpsXrmlWmOvHoE0Av+ApYT0gPUs6gfTNJn12Txu6HUPY6yTGBt6IY9PeIENizfX9tCUE1jzzs0C7iplGibdhqqNERTFL1kDj3pABRr1iBAaIvpp/tl3H0t3NONwdji706L5ZGEPzn/rAv470PBIY1N4chwyilfXlQ4GBAezIxAcddNsMdG65KKPScVyWjqWMel8ZWvB35lNuGLgSuLCC5DrojxbzPofKaTaECfnHPnQLdaNaJdX9E3p307P17ZQJ4GnNORR/18zhPA8LJ38L2cQGW6E2/fY8rLyObTrcMn3wy8ahAiQNwEgNEHjVt53mFn401IuTLqOD+7/Hwu+X8K8bxfx/OVvcGnbm9i9YW9Ju6QOTbniqQsCX0tAfOPYgO1OdKZp8sLlb/L85W+wbfUuTFPicrpZPP1fbhv4MLM+r/1ZH+XEZLNbGX/z6T5nNjSLRofebejYR+UsKYpS/VSgUc8IIdic0oU7vj6Lsa9cyoQ3LuLtv/uSkhNRvnGyHd837wJZ+u1jMdEHZiJaFyBK1ahzR0ju39Wf6VktkCX7ygYxZW8K5I5QZJoV0ykwN4chd4YgGjs8y6iKPw4INcHqprDASw5HmOEJfE5LQx+TiuibBdGu8u2qWWJMBI9fPRLifF9bSLD/kR2wL4vtSFrV+XeOwx7qP3dF0zX6n9Wb2IYx5Z7btnonT016GXehG2l6lmiZRbMWGYeyuGfkExTkFpS0v+iBCfQa1c3v9Qy3yWmXDQ34Ok50f/1vAbO/mA9QJo/GcJtIKXlp8luk7k+rreEpJ7iLH5pAv7N6ARzZha1o8jgxKYFHvr/rmHK2FKU+ULtOVQ0VaNRDzRKiMUx/+RXFgv8Pkda2ACINxFHvqOL/lr2e3I00V0iF+pSbIjxLt/6IR24OB7eOTA6BTCsl/9Us0MHlZU+D+EL0YemewCfMRNglWqILy9DMop2vquo33H8/Fw/vwW9PXcWZ3U/mqrYjgPI/AQ1BEz0G2/cZvjsS0KRtozJ73zdu3ZAX5zxGdEKk11M0XSMiJpxrX7zU6/M/vPKr5xV4yR8wDZP0Q5nM+XJhmeO3v38d0Q2iym0hWzzGsVePpGWX2qmlUZf89NoMv7NN0oTfP5hTgyNS6hOL1cKjP9zFYz/eTa9R3WjSthEd+7Tjptcm8+7qF0lMqr7ioYqiKKWpQKMeGtqtLREhweziFCyJaFlQLsgo2wJEc6fvBn4FE5yUqsKnS/Q+2aBRZkwlX9uCmVWpmkDkyzmrWL/rIABXtRnOQyedS+PQI0uL7JqFc5L68OnQm+jSva33G/ii4Vx43znlPoXs0Lst3yS/z5XPXESDpPiS47pFY/D5p/Lm8mdp3Lrh0b0BsOiX5X4raQsES35dUeZYYlICU/95ii4Dyu5WExJu5+IHJnDLW1f57K++kFKyfZXvbYfBs7Rq87/banBUSn2jaRoDxvfh6d8e4NMtr/P64mc4+8YxFcrtUpR6TeVoVIk6t71tQUEBt956KzNnzsQwDC666CKee+45Nc1bhUJsFh64aAQPfPR71XRokQgfuymVkCAi3NX8e+V5j4hmDrBKn5uqmFvCCLyEy99zR5/ruy9NE/xvzkq6tj4DIQRnNevFmU17sicvlULTTdOweMItni1rH/vxbu4d9SQ71+0pqearWzQMt8mF95/D6CuGeb2GrutceN85XHjfOaTuTyMnI4+EpnFExnpZDleKu9Dt8zkJGA11Dpnll3M1bduYl+c+wZ5N+9m1fg/2UBtdh3QmNELdwIBneaJus2A6/CyV0wS2EKvP5xVFURTlRFDnAo0777wT0zTZvn07eXl5jBw5kjfeeIObb765tod2QhnTuyPhITae+t9sUrLyAp/gjyk8VbcDxYJGBXI0joGIc/m8jCwURUuv/KlIEFJqJsULw5Qs3rCrzDFNaLSMKJ+cHdswhrf+fY7F0/5l3neLyMvKp1n7Joy9eiStTmoeYMweCU3jSWgaH7gh0KZbSzYv3+a1PoYAtMNuti/byY1/vMOzIy4j0lo2kGjesSnNOzYN6lr1Td+xPVk0bbn3Sup48jb6jD2lhkelKIqiBKu68yhUjkYtyM3N5dNPP+X555/HYrEQHR3N/fffz0cffVTbQzshDTq5NX9MuZpbzhmI1deSnWCYAnnQhvST9iE0MA8UF5ur5t8uf9vgGtUR5Hjp05ToaXnoKbl+P9k+msVqYdCEU3no6zuY8vtD3Dj1yqCDjIoaf/PpfovwCRNEupt1H6zgthWfllQyVwI7/85xPrcD1nSNuEYxDJ3Uv4ZHpSiKoig1q04FGitWrKBVq1bExcWVHOvbty/r16/HMIxy7Z1OJ9nZ2WUeSsUIISh0GbiMit5Elr2J8ixH8tRRKNfSBDPNAmkWRK/sag/jZYrVd76I3QRbNd4wS4l9fTIxX64g5vs1xPy4lrAPlvDaDe+Td6wzR1Vs6AUDSGgW57eNMMH2RzbrMnazJHVrDY3s+Ne5Xwfu+fQmdIuGpnnejMXJ4TGJ0Tw/+xFCwuz+ulAURVFqk8rRqBJ1KtBITk6mYcOyiauJiYm43W6ysrLKtZ8yZQrR0dElj6QktdtNRa3atp93fl3st83JLRtxdO2KEEupLWaRkGnFXBYFbs8yKmlSMsMhU62YS6NBCuTKKJBV+Lazlg8aZLIdWaB5nWERGohWBfj+DZegV/4vQNjS3UT8sxMt70jBO+k2+O392dwx5NEy28XWNk3TCA0PCdhO5JtoTvjjwOrqH9QJZOQlg/li51tc8vB5nHrmKQw8pw93fngDn259nRad1d8qRVEU5cRXp3I03G53ua02i2cyvCWD33///dxxxx0l32dnZ6tgo4K+mbsaXRMYPpbQCAHrinZNAujfdjf3jp1P09hc9qZFsXBrC7IddtbtbciSHc0xZtoQTZyIKDcYAiPZBlmlciKqbDKhaLzeZkdMgbE4Gn1AJtImS16HNIt2nrIanmCiZJKs+L0lPRW8T8lBrogsej74pVZ6ej6haw6U6bFkSIbJzvV7+Pn1P7jw/nOC7rO6hUYEDjSkTWDaIKvQf8FBpbyEpvH836Pn1/YwFEVRFKVW1KlAIy4ujtTU1DLHUlJSCAkJITo6ulx7u92O3a6WHxyLtTuSfQYZULwUypMcPfqkLTw94a+S5VFJ8dlcGL+uJBH80Z+H8duajsi9IdU8I1gqWbvQx+xIjgVjVhwkFoIpPLkZmoR8DfIsXiYsivqUIFdHgKEVLbMyIFf3n/dRxL7lIFL4XhkmTcn0d2bWeqCxOzeFFGc28fZIxl5zGluufddnW6lB4YhIdF2naZj/ZVaKoiiKcsKo7uVN9WTpVJ0KNHr27MnmzZvJyMggNtZTa2DRokX07du3ZJ2zUrWsFj2IVgJNmNw2arHX3aWE8AQkt4xcwh/r2mGYwfR5LI7e9ckHQ4Pk4k/si3+jj25fdLxlAewKA1OCU4AA7ZRssJmY/8SAK8C1pMTiyA74hyNlbxpLf19F39N7+G9YDVZn7OKVjb+xMXt/ybH2nRtj7R9L4aKM8j8ZDQjRcJ4Xh5QmZzfrVaPjVRRFURTl+Fan7t4bNWrEmDFjeOCBB3C73aSmpvL0009z22231fbQTliDu7ZG91PBuFiPFsk0iMz3uYWtEBAfUUCvlgeqeIRVpaiSuJfjwukidHoKsZ8vJ/79xcR9tIzwJdvQ3flo0Qb60AxES4dnqsJllM14lxL9cA4x//sX6+b8oBZaPXTmM/zy5h/s25pMoTP4HamOxcr0HVy/7AM2Z5f999mac5D0hxpgGRpXkjpT/OrMJBu5LzRDNrZyXlJfOkarrWwVRVGU+kHUwKM+qFMzGgAffvghkydPpnHjxoSHh3PXXXcxfvz42h7WCWvSkG58O28NpjS87hhVLDYsuCTmuPC6k+wcDOFwEfXzOvRsR8mSJ+E2sa87jP1mjdznmmK2CcHSKIPQzw5i2ehAhlhxN4xAApZDuWgOV8X+YEh44+YPAQiPDmPcdaO4+OHzqm0XIiklz/73C6aUyKOmXGTRkjH7I225elsXPv37TzJiCnG3tWN0DCHWHsGlrQZzUcuB1TI2RVEURVFOXHUu0EhISOCXX36p7WHUG80axPDK9Wdx5zvTKXS7S4INIcCq6xS6PRnTh7L9V5kuFmy7uiJs8a4yQUYxYYJ0mIQ9c5C8Z5oQceteRLbp+RTC4cK2O6NKrp+Xlc+3L/zCuoUbeX7WI9hCbFXSb2kbs/ezKy/F5/MSSbIjg1bndmLaVWPJdTnYmXcYq9BpG9kIi1bdS+EURVEUpY5RORpVos4FGkrNchsmfTo0Z8bTk/l50XpWbt2PENCrfRJn9O3E9VN/YNuBNNbta8je9CiaxmTjLV3GNOFgViSrdjeu4AiKkrBjXJBpIfjJxKLzhEQ0KkQkeLaTlelW5AG77+RtTSIaFIJNQqaJbXuqz+RtYYKe7CL0jcOIHLPapjlNU7Jh0RZ+fWcW5952htc2hU4X879bXFIxvEWnZpxxzWm07dEqYP/JBcEFRZ52rYiwhnByTPUUCVQURVEUpf5QgUY9ZJom//trFT8vWs/Og+kAdG/ThEtP68UVo/uUafvOredx8xs/sXHvYZ79bTCvXfwbpinLBBumCRLBczMGISt6Ox5iop2Uh2jkxFgSDak2yuwq5ZOASBf6qdmIMLOkZobW2oF05GIsjYZMa9kzWhSgdc5D2I5EFrldWhD6xmGsK7xv3So1sKwqqO4ag0gpmfbWH14DjZR9adwz8nH2bUlGaAJpSjYs2syv785i4t1nc9WzF3vd/rlYtDXsyDeGxLImH5FpYMZbME4KBb2okJwtvMpfl6IoiqIcj4Ss3vrC1X1fUVcIeXThiuNYdnY20dHRZGVlERUVVdvDqZN+WbSel76fR25BYZnjAs/t/XVn9uOaM04t85xpmlw85Uu27Euhd6t93DlmIW0Sj3xKviMllpdn9mfJ9op8Ci4hzEAfmomwet6C0gRzUxhyaxgBAw2rgT48A2yyXBVwaeKp4TEnFhyeZT+iVQF619zy/RRt7Rv+4H4sa8rnlwQT8vhSmXOf+OVe+o07sruTlJIbet3LznW7Mdzei5A079SU9IOZWG0WBp7Tl/G3jKV5xyOJ227TYNzc58ieeYCQ91PRMksKiGAmWCi4vgFhgxvw+7D7sWrqswdFURSletXl+7XisXW57hl0e+BaU5VlOB38984DdfJnUJXUXUU98uHvy3hz2j9enyuONt/5dTEDurSkS8tGJc/9u2Ufm/d51vgv29mMSW9Pon3DNBpE5pGaG8bmgwn4u6UOtVtwGyaukhtlCY0K0bvllAQZABRoyO1hXvs4mmjuBLv0uguW0Dx5B1pLB+amcNAlWmcvQQaAJsCUFFzTgIgb91T58qiKBhuPnP0clz46saTI29r5G9i2aqffc/ZsPLJd7YwPZvP7R3N44ud76D2mB2nJGWxevo2T5tlZ/cqhcktCRaqbsCeTGfvBqT6DjFRnDttzDmLVdLpEJ2HXrV7bKYqiKMoJQ+VoVAkVaNQTB9KyeWu69yCjNF0TfDtvDY+XCjT+WL75qOrhgi2HEthyKCGoazucbpo2imLfwSzPgWZO9J455YIEc2do0S9e4FtzrYnT7/NCA5o6YVM4opET4e+drgnMVnbM5jb0PUdmeqQAd2Ik1kM5AcdzNKmDDNUQLhPpBHTADG6q9LPHv6XHyJM5aUBH/p25Bt2iY7iNwCcChttECMnj571Ir9HdWTztX0zDE+B5C3pE0f+snrIIecWFZZZgpTtzeXHjdOYcXI9Z9BcxwhLCxS0HcnmboehHTyUpiqIoiqKUou4U6olpi//zu46/mGFKNuw+VOZYVr4D00/18EAkFAUZRTtHH7AVJX4f1S7ZTxL30T1aTZ81PUpYisZsN/1u3VvMjNM9H2AU9etqHIWjQ2KZ1+FlJEe+1iipRWE2t5H7TFOyv2pDwZ0NcU6Kw3F5fFAvT7doTHvzD08/bqPC66+klDjzC1n08/KSIAP8dCMhefshNi3bVnIo21XA1Uvf5e9D/5UEGQC5bgfvbpvNlPU/VWxQiqIoinK8kdX4qCfUjEY9sS8lM+i2VkvZ+LNpfBRamRmNyih1m2sKjH9i0IZkoEWW+qTeewpCKUWfyTdwQbj/xtIEmV20LatDDxyUAK64WGTLUMwQC862DXAnRRKasYvcJ5ugJxdi/zQNkSdLj+TI0BtYcA6PhDANo30I4Q/tJ+qWvbi7hOC8MA7nCM/6y5BvMiDf/9gNt8nGpVsB6NCnLYYruNmMo1U0/So9+Ujezde7/mF/fnqZIKO0aftXMKH5qXRSRfwURVEURfFBzWjUE1FhIYggPxrfcziTXUW7UQGMH3DSMQYZRxNggLkttOxMQ4zb99qicDeiVQHawAz0flnlEsDLXUEDuTMUAHnQhnQJn7MaUoLM0Cno25Tcq1qSPykJd9sw9CHpuP4vAqNHGIVnxuK49MhSMXH0/6e7sa7Ip/CcGPS9hYii2EDf4CDsoQNY52SD0wSHr1v3smwhnjyI/mf3Jq5RDJpe/b+q8U1iS77+ed9yn0EGgC40pu//t9rHpCiKoii1oXjXqep81Acq0KgnRvVqj2EGnDIAwFHo4uY3fsJtmGzdn8rTX/7ls60mICGqMtuiCtgTgsw4MqmmtSrwvnRKl+hDM9C75qHFu8vNTpQOIKT0PMw9duTBouJ3psBcH4EQlAs2ZPEUpt3EMigTvWcOet9sLKdlIiJMT+VCzXOi/adMn7fewgDLNieWpXnYvzoSpBX/IQl97TC2GUU5Kpr/FWKartH/bM82wxarhcd+ugd7qK3agg0hBM3aN6ZD77aAZyYk1ek/L8WQJnszU8lKza7wzImiKIqiKPWDCjTqiW6tm9C3Y3O0INYQmRL2p2Xzw4K1XPHC16zZccBv2ybxUXRv0wRNq+ieTQJzQSzu2XG458dgroz03qqxw28yd5mXlK9hrovAXBVJ6cVNck8IxopIcBz1ls/XPIFG6NGlwfEEGMXfHnajH3T5nROSGoS9fAgto+xSJwFQKLF/k45rWCR5TzcBm/AabAhNYLVZGHfdaSXHOvVtxzurXySpY9UvUxJCgIAbXr2iJIdHCEGkJdT/iYZk5fcrOS9xMtd0u5PZX8xXAYeiKIpy4qjO/Ix6lKehAo16QgjBS9eOY0jX1kG1t2gan89egdPlDpgIvn7XQdbtPFi5G00hIU/3JIc7Ncr/5kmIcweVzO1eEokxO65oyVT5u3i5LwTjzzjcC6MwlkXinheDzNc8BcYDxEjCCDwAYYIo8N5OAOiCgpsSEW5wnhsDNkqSz4sf9jA7T//2AInNG5Q5f+fa3ez+b2/gMQiBPcwesF2xRq0TeWr6/fQe06PM8TOa9vS/q5QusP3tmfXYvWEfz136Oh89+FXQ11UURVEU5cSnksHrkbAQGy9ddxZrth/gihe/8dtWSsmBtOyg+jWL1ytViASrRDR2QpIDEWoi99uRh+zgElCggW6ij87wBAHS2+asR8m1+GkjEU2caK0LINYNEmSaBa2BO6jRmg2smJEaWk5wy8+80TIMIi/agVYqGDFjdcymVmSUzqnDevDgHZOJjI0oc966BRt5cfJbAfuPbxLHxLvOYuC5fbl31BMk7zhUrsif0ATNOzblogfPpWGLRDr3a+91N7KLWw1kxoGV5LmdGPKo12xI9DX56EUFDmVRIPr1sz8xaEJf2p/SJqifh6IoiqLUVaoyeNVQMxr1UNfWjWl41M3s0YxqXQYjPUX0RqQjIg3kyijM2fHIjRFggEgoqmURKpGb7dgeSAen7/F4krktkOcrbpZoJ+ei986BWDdCA6GDFu8KfshWQeG4mOB23/VDO2rGQ2Qa6JscDL55CM88cXO5IGPRtOXcNfwxcjPyAvad0CyOc287g8TmCbw87wl6juxa9lqaYMj5/Zi66GmGXziILv07+NzyuGFINB/0vZbWEQ3LPmFKrHNzCH8yuVxIp1s0fn3nz4DjVBRFURSlflAzGvXQN3NXczjDR6VsPHMCkWEhZOc7qm8QfTMxF8R4lk2VlmVBZhVVns4U6GsNnK2bIn/VkR0kWisHaBKZafEMNM6FsEqM/zwJ6aLARcjGg9g3pyCcbsxIOwXjGmK29lynzGogvWJRg3NSLPqGAiyrPZ/kV0UVcc8nJoL8d3ejTdLIy8pj+5rdaJqgeedmPH/5G8ggk/jtobaSr2MbxvDMjAc5sP0gGxZvQdMEJw/uTINm8UGPrWVEIl/0v4kNWfvYmL2f9279FGNhJlqa91kgw22yY+3uoPtXFEVRFKVipJR8/vnnvP322yxevNhrm1WrVnH99deTnJxMeHg4U6dO5bTTTvPatrqpQKOe+WP5Jp7/dq7fNhJ4+JKRfP33alZt2+9ZGlVlJDR3wLIYcBcV8CtDlGnqahZzJCl7u8TYEVq2nZBgN8Gho2U7iP5lHaLABbKoPKDTjWjrBCPUd2AhZeAkDQCrRv4TTbH+mYX9hwz05CM33Da7lUJnBWZISl/ekKyZ+x/PX/Y6c79bjMvh6cdqt+JyupB2gbtXOGa0jnbYhWVlPuKo2EMIwYDxfcr13aRNI5q0aVTueLCEEHSJSaJLTBI//PsxqT6CDE9bCI0IkESuKIqiKMeD6k7YrkTff/zxB3fffTcFBQVYLN5v4XNychg3bhyffPIJI0eOZN68eZx99tls2rSJRo0qfz9QWWrpVD0ipeTt6d6j39I0IVi7I5mbzh6AECKoe3CfYlxoPbPRR6Whj0pDG5DpycHwGmR4HcyRr4Uo+sUsHYwIcOggJRGzNiMKXJ5ZguJTAKOd3f/shbd9b32xCFxjY8j9sBVGM8/MS2RseKWDjNJmfT6/JMgAKHS6cJ4dQ/b/WpP/YGMcNzYg/4mm5HzeCle/I1sKa5ogKj6CUZcNPeYx+DNkYn+/W+xKYPD5/ap1DIqiKIpSX+Xl5fHcc8/xwQcf+Gzz1Vdf0bt3b0aOHAnAkCFDGDx4MN984z83t7qoQKMe2ZGcxt4gKoSbUvLXqq10a9OEN24+h8QY//kcvohWBViGZCKaOhGhpucR50bvnYNIcgbRgbf9X30EDEIg7RavyVXCHSCIkBIKKp7kbbS2I4Gm/VtU+NxgFJ4Tg+PaBhBW9Gta9NpltE7+g41x9QoDIDIugudmPUJETGXqmQRv/M2nYwuxet3GWNM1EprEMfKSQdV2fbdpqC10FUVRlBpRUwX7srOzyzycTt/3RxMmTGDs2LF+x7148WIGDBhQ5ljfvn1ZvXr1sf5IKkUFGvVIfgU+dXcUepbI9O3YnN+euorHLx1dsYvFuNC7evJASudFFH+t9ciBiOB2fAqKlDg7JHp9yrI0DwIEG1qKm5B3DxP61AHsn6cGd02XxGxq5d9LC9G6VC4Y80WGCBz/5yOfouhG3zE5gfhmcXyx623adGtZpdf3plHLRJ7782Ei4zz1TnSrjm7Vi55rwAtzHqvypVMF7kI+3j6XM/9+lv5/PszAWY/w2Nrv2J5zqEqvoyiKoii1ISkpiejo6JLHlClTjqm/5ORkGjYsu5FLYmIiaWlpx9RvZakcjRPEjuQ0UrLyiI8Mo02TeK+7CTVLiEbTRMC6GJoQdEg6UsdB0wTj+nXm23mr+W93cDd4WqsCpHlU8nURIUCanjbmOu9F+ipMCMxwm9en7D9n4hoR5akuePSn8UX5GWYzG45rE9FX5hE25SDOiXFg9xOHO02wC/JebAYRAm5rBldvqprXArj6hkOIn+trArOFnXNfG0NIBepmHKvO/Trw5Z63mf/9EjYs3oJu0egx4mT6ntETXdcDd1ABeW4n1y17n63ZyZhFi1ldpsHM5DXMPriO13pdTs+44OrCKIqiKEqF1FCOxt69e4mKiio5bLcf23/T3W53udl/wzB87jJZ3VSgcZxbuXUfL303j417D5cca9c0gTvOG0Lfjs3LtI2NDGNEj3b8tXIL/mINU0omDe1e7vid5w9h8kvfBpXOIBJcXoOMkuc1IMHXDEvxBSrwS2FKtLxCr0/puwsJm5JM/r2NPO/4kgSOUpX6inI4jO5hOM+KwTY9i8JzY8oHJkXXosCk4J7Gnu9dJq7Hd1GVt9kyxuI9MDpKy0GtqvCqwbGF2Bh5yWBGXjK4Wq/z7tbZZYKMYoY0kVJy/+qv+G3ofVi0qg1wFEVRFKWmREVFlQk0jlVcXBypqWVXZqSkpNRKIjiopVPHtRVb9nHtqz+waV9KmePbDqRy42s/8s/6neXOuWPCYOKiwv3ewp8z4CQGnVT+BrZ7m6Y8esmo4AYXzKcAPtsUJX1XZD2+JrAlpyF9vKOti/OIvGwX9s/SsCzJw7IkD5HmJdDRBIWTYrF/m4Z1rqfyNW7puekvWn5lmZeDdfaRYobWv3PQ9h17MniZYaS4fAcZLpPiSDHRHsW/adv5Zd+//H3oPxyG92DreOMwXPyyb3m5IKOYiSSjMI95hzfU8MgURVGUekHWwKManHLKKSxatKjMsUWLFtGvX+1s1qJmNI5TUkqe+eovTGmWux/3FNH2PD/9ycllkncbxkbyv/su4p3fFjN90QbcpWo0NE2I5qrT+3JWv84+p9jO6t+FpMRobpj6I0634Xt8h23QwuFzVkOaRW0orvhdqvJ3joOwVfvJH9i6aI2VduSFeRuXKbHuz8Q9WMOSb0PfXYgUnkSr0vXEtSyDkG8zPF0JcHcNJX9Ks/L92TSMDqGEvXgI9y+eZVdmnI6WbmD9Kxt9qxN3nzBc5xU1/z3L58/BF6GJkora3liW5SNyDGS45gk4HCb2XzKx/ZqJlmYgdbANieemfW9xuNmR4CJMt3F12xFc1HJgrU2TVoXkggwKAgRNFqGxOTuZEY1OrqFRKYqiKErddvHFF/Pss88yZ84chg8fzowZM9i4cSPnn39+rYxHBRrHqY17DrHzYLrP56WE5PQcVm7bR6/2SWWeaxATwcMXn8Zd5w8lPTsfq64RGRZCqN3q95q7D2Wwavt+BIIvH7iET/5czm/LNpbJ+WgYlc2h7EjYZYcWDh+xgef23yzQoGEhZFnAcSQiCV99APumQ1gP5eA4qTGupBgkYDmcixluw2gYWaYv26ZDRCzaRcHNCeS+nIR1SS62HzOxbHf6nLkREqxrChCHXMiGXl530YmWrU4sW8vOGElBme1ytcPuChfv6z26OytmrcEwTK+fagi3JOTtFAruaQQFJuH37UPf5ixpKwwonJsG89OwPNYEd0/PjlP5RiFTN/+OW5pc1npIBUdVd9i0wH+aJGAPop2iKIqiVFTpnaGqq/+q8sUXX7B8+XKmTp1Ks2bN+Prrr7nhhhtIT0+nbdu2TJ8+nfDw6t2Z0hf1X+njVHJaTpDtsn0+F2qz0jQhOmAf6dn5PPzpHyzeULbqc+tGcUSHhZCRW1By7K4x/9AoOocfVpzEwi2NyOxgIKREFkUbGiYa4FwejdaoEHFSHsbSKHAUJXJLiX3LYYQES3o+EfO3lxuPOzoEx+gGuEZEEfrzAewLMhCAZX0BrlHRuHuEYZ2bg9weOMtDO+TCODrQcEv0rX6235VgNLWiJRdiNrIio3VkhlGhYGPs1SMZfcUwnrnoVcBTVRs828SahkmPESdzw9Qr2BGXxYt3vEfhdme5P0rC9ASUoc8eJOeLVmA7Eqy9v+0vzk3qQ6T1+Cyg1yQ0luZhCezJ970DmCFNBiZ2rMFRKYqiKErtGzp0KJs2HdmA5pJLLuGSSy4p+X706NFlnq9NKtA4TsUEuY1osO18KXC6uOqVb9l7OLPcczu8zKh8vLAnn139Iw81mQfAXmc4P6a24d+cRISQ9I44TOgBnXcO9kPEFeU1lF5eZZgIt/+aFnq2A/umVMJmHUDLOLJ8yzo/F3eXLELfPAxB7pwrI49KJDYk1rk5aFnel4UV3+uHfJ9JyPeZGC1s4JYVntHIOJxF8vZD9BvXm0N7Uji0KwVpmnTs247xN4+lz+k9AGjibMTUGZm4fPxIhASRa2JdmItr+JFkMpfpZs6h/zi7Wa8KjqxuEEJwZZthPLbuO6/P60KjZ2wrOkQ1qeGRKYqiKPVCHawMfjxSgcZxqnvbJjSIDiclK89nm+jwkHI7T1XU9CUb2H0wI+jfhw0HGjJjbTtGddmGRZck2fO4telaAAxT4DI0LvpxIgDmvhAs7QrQGhZiHvTMaGiZjjJ5FV4Jz+zF0YMShZLQqYeLmwQkbaDtL8RsZfckVwvQdjoJfSelfNuyly+h7S6scJBhsVmYet176BYNEJ5t6KTkiqcv4oJ7x5dpm7Y/nfzsAq/9lIxNB32HE9fwUuMSGunO3AqOrG4Z27QHyY4M3ts6G02Iok24BIY06RjVhGe6X1jbQ1QURVEUxQ8VaByndE3j1nMH8dDHf/hsc+PZA7BZK/dPvHnvYfamZPLlnJUVDrqfmjaU9g3TaNswHZchAIFVN8lx2Lj7mzHsSY/xNMy2YO6zQ1MHbAxHS3UQ8+OagP0Lk5Jk73LPVWSgLgh/5iCOCQ5cgyOx/ZGF7a8cRGH5jn3melTkekXcLs90i3HUzM2H9/+PPz/5m6btGzNgfF+GXdAfqz24fz9pLTsSQ5okhlTddnnB2rluN7+8OZN1Czag6Rp9x/bkzOtG0ail92KKgUxuM5zRjbsxbd+/7MlLJdwSwmmNu9Invg2av/2TFUVRFOUYCCkRFdn9shL91wdCHl3V4ziWnZ1NdHQ0WVlZVboncV32y6L/eOn7eeQWOBHC8+l4mN3KLecMYuKQbkH1IaVk9fYDbN6XQkpmLvPWbmdHsu9E8+BI+rTaT/92e7BoJv/tT2TOhtYUmpayu2QJiS1uP0aXMMLu2Y9tf3C5J1XN2yxKwJmVIAgBukXHMEw0TZQLLryf5Ll4wxYNeH72Izw+4UV2rt/jd5eq3JeTMDqGlHwfqtv4fdj9hFlqrpjfD6/+xjt3foKua2VyTnSLxqM/3E3fsT1rbCyKoihK3VWX79eKx9b9/55Gt4UEPqGSjEIHqz9/sE7+DKqSmtE4zp3dvwtjendgwbodHM7MJT4qnMFdWxNq87+DVLEt+1K4/8MZfnewqhzBsp3NWLbTs31siM3C1JvO5r3flrBy235EtgOt0I0ZYiX8/b0QIRBZQdyE4/n03tU/HLOJDZFnYP0nDy0tyKSMCr2CYw82wmPCGXvVSBo0i6cgt4CPH/7ab8AAlKzTSt2fxoNnPMOlj0/imQtf9d5UA6NzCEaHsgHFzR3G+AwyCvIcrPprHY5cB0kdm9Ku57FV196xdjdv3voRa+d5alqUDqZMw0SaJk+c9yKfbn2dhKbxx3QtRVEURakRKkejSqhA4wRgt1oY2bN9hc/bn5rFVS99S0Fh1RWbE8IkOtQkv9BOodsgNiKUMb07csv4AdhtVqzJWTz45HRc2Q6g1I18VnC/ca4BEeTfmggRuqeAngaOaxpgnZFF6LspCN+lPfyPu4LHg5WbkcdVz16MEIKvn/vZM+sU5F8Xw22yb0syoeEhXPPCpbx/7+cls1bFsyPW9pHkPNSgZA/hBHskN7QfzZlNy88emKbJV1N+4uvnfsaR6yg53qZ7S+768Aba9qh4lfH/Fm3m7pGP43L4fg9JCe5Cgxnv/8Wlj02s8DUURVEURTk+qUCjHvv0z38pKHRhBPqEvQKk1Ljn9NmMHvoOUmtepljg8j9W8cAZz5SJ4ityI+/qEUb+/Y2OHLAcOds1NhoEhL1ZPpG7NoVGhJQUzmvZJQnTCG7WprR/fl7GnR9cz+DzTuX3D/9i35YDhEaEMvj8fpxyWld25B1mf346UdZQusa2QPeRu/Dhff/j2xenlTu+c90ebh/8MG8se5YWnbwUMPTBNE2eu/R1jMLAs0mmabLyr7Uq0FAURVGOC8dTHY26TAUa9ZSUkl+XbqjCIMMzNzGx9zpO67IdCpejhbUoedZwGzx/+ZvHNFXovLRo2Y3mJTzRBK7TozG/zUBLKXvjK4vWQNV0nWzdojH0ggH88/MyFk1bjiPXQWhkKI48R+DlU6XsXOepX9KwRQMuf+KCcs+3jWxE28hG5Y6XdnhPCt+9NN3rc6ZhUuh08dmj3/Dwt3cGPa618zaQvONQ0O0r8poVRVEURTn+qUCjnnK5DRxBfBIdLAG8MOl3hnTYRV62xuwvNrNi3jOYbpPO/TrQsHUimYezKt2/2cCC0SFwUpZrYAT2nzLLHixanyWrIdiQYRpmYys4TbR9rpL+NV1Dt1pYPWcdv3/wF5pF89xoS+kZhyaCvvE+uKv8LM36hRv5ceoMVv21Fimh29AunHvrGXQb2sVrH3/9b6Hnmob3a5puk4U/LSMvO5/wqLCgxrV7w76SpVyBaLrmc2yKoiiKUueoHI0qoQKNespq0YkODyErzxG4cRBCbC6GdNjF7/+L482HmuIuXF3y3MrZ64LOS/BFRgSxlanhvZ2g6oMMM0rHcUW8p0he0day2oFCQr/JxDIri5jEKGwhNg7v8VS2No/abUqaMuhgw5lftkr5z2/8zpu3fIRuObK709LfVrDol+Vc/dwlTLz77HJ9pB/MQNMEpp8cFtMwyU7LCTrQCI0ICSrIQICmCc689rSg+lUURVEU5cSgNqKvp4QQnDvw5DI5FJWlayaDWu/gtnFtmHpPEu7Csm8r0zSPedmMSHGDj0/jS1hAS666xHZfzAiNvJea4Rp5JMgAMBvbyLs9EX49mdz3W7F9koazi91riKXpGl0Hd+bUcYG3fI1vElfy9fY1u3jz1o+Asrs7FX/9/r1fsHHp1vJ9NI7FDPBvoFs0ohOC32Kv7xk9sVj1gO10XeeBr24nsXmDoPtWFEVRFOX4pwKNeuz/Rp5C49hI9ADBRrjdSmSo3Ws7IU1smw6z7qF0Nq2MOOYx+boV1nJNLAtzPTtNeWNKcEisC8pXw67q2UnnxDjMRlbQj/p5FH2bpTlI0XJx948gb0ozCq5vUG4MpmGyZu5/DJ7Qz++1hCYYe9WIku9/efMPdN33r61u0fjljd/LHR9xyWC/sw+6RWPghFMJiwz1O57SohOiGHfD6JJkd2+6Du7M++teYtC5fYPuV1EURVFqW3EyeHU+6gMVaNRjMRGhfHLPBQzv3g6t1M1iVJid8wd35YnLRvPK9Wcx6/nr+Py+i2gUGwmArgk0TSCkJHLxDsL+3kFhnu/rVGSZo7+QJ/TjVESeUT7YMCVogtA3DyOcR54rvq4I0G9FSA0Kz4guH2R4U7QrlmtcDK7R3mcKXrjyLZ+na7pG07aNOKPUkqP/Fm7yW/TPcJusW7Cx3PEGzeKZdM94r+eIogAy63A2Xz/7E5kpwefSXPP8/zFm8vCS8epWHU3XEJrgsscn8eLfj5HUoWnQ/SmKoiiKcuJQlcEVAFKz8tiRnIbdaqFzi4ZYLeWXxOTm5PPwPZ+wYmcyLsMgdE8m+taa3U7WTLRQcGUC7gERJTf72g4nIZ+lYVmWVy3VvUv35RoYQcEDjSt2oinR9ruIuHZ30GMRQtDvrF7c9u61xCZGlxy/uusd7Fq/1++5jds05LOtb5Q7LqXkm+d/4aspP5Gfne/9uprAarPw8Ld3cuqZpwQ5Wti35QBzvlxIZko2ic0TGPl/g0koteRLURRFUYrV5fu14rH1vKD6K4Ov/FpVBldOADuS09h+II0Qm4Ve7ZMItZevGp4QHU5CdLjvPtbt5qa+9+NyuLAD3mtOVz/tsJvwZw9iRmnIRCvkmYhkV9GsRdmwoiqDjCMqXgcDTWAm2ZBROiI7uIqCryx4ki79O5Q73ndsT/Zs3O+zHoema/Qd68n7yM8p4K8v5jP320XkZxfQ8qQkzrjmNL5Nfo9FvyznpaveptDhKpM/I02Jy+ni8Qkv8M7qF4Ouq9GsfRNVI0NRFEVRlDJUoHEC230ogye+mMWqbftLjoXarfzfyFO4ZuypARPBC50u/vlpGesXbmTG+7NxuypZdrsaaNkmZDsBSUiYidOhIc2yr6eqgwwBWP5zQo4BkYGToL12EKR7T3uCJu0aMXbySEZfOYzQcM+nKuOuH82PU39DmrJ8zkXR7k5n3ziGA9sPctfwx0jZl1ay69bOdbuZ/fl8xt98OvFN4soFGcWk9Mx+/PzaDG59+5qKv05FURRFOc6pgn1VQ+VonKCS07O5/IWvWbvjQJnjBU4X7/22hOe//dvv+ev/2cRFSdfxzEWv8uu7s+pUkFFamy4FCI1yQUZ1EVkG4Y/s99yNB0uCdsCFyDJo2CIhqFOcBYXsXLeHN2/7iFv6PUB2eg7gKdr3+E/3YLVbygSKmq5hsXqWPDVp24gHz5xC2oEMkEeGWpzb8fPrv/P7h3/53QnMcJvM/mI+qfvTgn+diqIoiqIopahA4wT10R/LyC1w+qz8/e28New6mO71uf3bkrlv9FMlN7e+lukEo3oDdknaIavP2hDVcW1hgr7Vif3zo27A/QUeAu4ccS4zCr7k482voQexJaynT89jz8b9vHb9+yWHe4/pwec73uT/Hp1I1yGdOXlwJy5+cAKfb3+D/mf3ZsWstezbfMDnv5sQgpS9qQEv78hzcnmHW1kz77/gxqsoiqIoJwpZA496QAUaJyCXYfDrkg0+gwzw7Bw1fckGr8/9+OpvuAu9L6upqOqdZxBkplpp1saJppcfq6D6gg37NxmeJVTFJFBY9sZeF55fr3FNezKheV9sditWm5XB552Kbgn+V880TOb/sKTM7EJco1guefg8Xvr7cV6e+wSXPjaRhKbxAKyavdZvMCOlxOV0I4LYOavQUcjD454lJ6P8tsGKoiiKoij+qEDjBJTvcOEMYqlTapb3PWnnfvOP3y1UfaqZ1UvlJLV1YBr+Ly6P+v9jJSRomWV/xqFPH1mmlmCPpG98W17ueSkPdjkXl8OFYXjaX/TABCxWC5oW/K+fNCWbl28Pqq1pmEH9U8hABRCLruvIczLzY/9L7RRFURTlRKNqaBw7FWicgMJCrNi8bE97NF+7TDnynJW7cC394sybFuvz4qJofrJ4duPoWY7KDlkKkDFHfsa2HzKQHcKwCp2Xel7KjGH381yXC9n30UYubnE9Z4ZfwtiQi3ji/JdwFhTy/OxHaJDkmYHwV/CuzGsJsop7lwEdA+bUxDeJ5bqXLwuqPyklq/9eH1RbRVEURVGUYirQOAFZdZ2xfTv5rfhtmJIz+nby+lxSx6ZB3/zWLk+YIE3wPZ1ypFyfKHUEPMGCJRKatnNQkZBDauDuG46M1KHAxP7BYUK/z2TA4B58cepNDErsiCPfyV3DH+PDB78kdb8nF8Y0TBb+tNST3J2Wy2fb32DKHw9x8UMTAv68LVadkwZ0DGp8/c7qRXyTWDQfFcSFEJxzyxlMuO1Mnp/9SFABzAlUbkdRFEVRApOy+h/1gAo0TlCTx/QhLMTmNdgQwDkDTqJ143iv5551/ejj5Mby6NChgmdLMHIkYy9MC7oPWTwlYkrCHzlA1PnbCfkpC3IM/r1mNvd2fJAfXvmVL5/+gU1Lt5WLX6QpMQ2Tpy54BWdBIb1GdeOyxycx7MIBfm/4I+MjsYfZghqjxWrhiV/uJTQipEywUfx1//G9Oe+OMwHoMfxkug/t4jMoAUBAo1YNj5P3hKIoiqIodYUKNE5QTROi+fiuSXRMSixz3G61cPno3jxw0Qif5466fCinjOpW7sa3+FP38+8ax32f31z1g64FmgZbVodhsQaXk2K2tFFwV0Nkh1Bidgl0RJlgIuNQFu/c+SnfvjDNbz/OfCc3nHIPk5pczRUdb6VBs3i/dU0yD2XyxZM/BDVGgPantOGD9S8z8e6zadiyAVHxkXTu34EHvryNh7+9A73U0roJt5/pf2cxCdPe/IOrTrqd1XPVEipFURTlxFed+Rn1KU9DyBPoY8q6XNK+Nm3Zl8L2A2nYbRb6dEgiIjRwXW9XoYtvn5/Gz2/8TubhLABadG7GpHvHM/KSwfz67ixeu+H9AL3UfUKTDBybRUaqhfVLwvE3s2GGCXK+ao22sxD7jCxss7MrVSjc6ziECDhjEBETzrcH38dqK1/Z/Vh99ti3fP7Ed+gWLeBGAJ36tefqZy/h5EHel94piqIoij91+X6teGy9znsKizWk2q7jdjn49/uH6uTPoCqpyuD1QPtmDWjfrEGFzrHarFz80AQuuG88aQfS0a0W4hrFlMxqxDWKqYaRlhfdJZ60BoXo83KqJfqXJqxZFE52upVAeRpavsSyNA+zqQ3r7GykWXUbbQUT7+dm5nFw52GSOjStoqseceljE+k+/CR+fPVX/vl5ud+2Gxdv4c5hj/Lgl7cxZGL/Kh+LoiiKotS66q51ccJ8zO+fWjql+KVbdBKbNyC+cWyZhOXeY7oTEeN916pgSMDdJYSCqxMouCkR51nRyIiyb0ehCeLv6Ujh+NiggwwzRkcG+a4u3o/KE2RAoLBB6mD5rwB9UwGiCoOMirDYqu+zga6DO3Pqmb2CemHSlDx/xZvkZnrfIllRFEVRFKVOBhr5+fncf//93HjjjbU9FMUHW4iNix48N+j24VEG4yen8OC7u7j9vX3YP21I3gtJFJ4VQ+GoKBzXNCD7i1YUDo0EPDf11sQQ9jd14Gpnw93W7jOAkKVujAtPj0KGaV7betvWtkLBggQsAvtv2RU5q8okNIujUcvEwA2PQdqBDHQ9uMrlLoeL2Z/Pr9bxKIqiKEptEGb1P+qDOhdovPzyy7Rp04ZvvvmmpMCZUjd17NMuqHbdBuTw+fIN9Lrbxb7eDXi/VS/SGkR4ntQFWARonv8vuKsh7q6hGB1CSH22IYXSDUKQ/0BjZKzuqV9R1G/xrKbZoPSn/ILcqUkUjotBhnne3maMTuGp4WApG2CIUv0EQ5ggdjrRd1Syzsgxik6IqvZth+MaxwT9e6fpGrvW76nW8SiKoiiKcvyqc4GGruvMnDmTSy+9tLaHogQQHh0WRCtJ3ysLuGzvady8YwivH+zGflckpre3XtGuS3mPNiHvxSRItBEhbWiAbGQl96UkzAaWMsX3EKAfdpd0YfsrG9nIiuPaBmR/34asX9uS82VrjJNCwfA+gxHsrbsEbCsLgmwNTds18vRfRcHBjjW7cLvcgRseg0ETTsVqDz7Z3BYa3Ja7iqIoiqLUP3Uu0Lj11lvp2rVrUG2dTifZ2dllHkrNaXVycxq2DJBkLuCdF5M4UOjJ55CBbus1AaFFb0vDpI25tmRjp5DP09BS3MXdev7/qOkIM94zbaFtd6BtLihpaJ2Xc8yJVxUNF/ZvPchJAzrS/+xeNGnTiDbdW9L3jJ6Vvr6UUOhwVfr81P1pfPLw11x10u38X5sbeXLiS6yZ+1+ZNhEx4Vz22KSg+jPcBgPG96n0eBRFURSlzpI18KgH6lygURFTpkwhOjq65JGUlFTbQ6pXhBB0HdTZfyMp0DY6kSkVXwYndcHopnu5uMFmRLob65zAO08VDggn4pY9RN68l9B3UqBoNkHkmrWSvL3+n02cPLgzn259nXdWvsATv9zLmCuHAaBbin79ghxYbKMYQiMqt9XehsWbubLTbXz17E/s3rCPgzsP88/Py7hr+GO8f8/nZXa9mnj3Wdw49UpC/FxL0zU69mlL1yEB/v0VRVEURam3jutA4/777ycrK6vksXfv3toeUr2T2DzBf1XpIiKngllPpiTeUsDguIPc1GQdw2b+F9TOU6GfpaPtKgRA3+xE2+4At8Rsbgt6N6qq9sG9X1CQ61lypWkad7x/Pc/NeoQB4/vQoksSXfp14PKnLkDTfUccQhOcdf3oSi3DKsgt4MEzp+DMd5YpzFdcL+PbF6cx79tFR64lBONvPp0fUj7i3NvO8IxLgNBFSaG/tj1a8eT0+6o9Z0RRFEVRaoMq2Fc1aq2ORsuWLUu+7tq1K9Om+a+k7I3dbsduD1x8Tqk+jVolYpr+gwipgUyowFvNlGguk8vSV7MmLZwW7R3smhXk+S5Z8ssrgLAnD2C2CsGyPK/WdnhwuwzmfLmQM645zTMuIeg54mR6jji5TLuouEheu+F9hCaQ5pG/QJqu0bZHKybccWalrj/ny4XkZvjehlbTBN+9NJ2hkwaUOW6zW7n+5cu58P5z+POTuezeuA97qJ2B5/alx/CTVJChKIqiKIpftRZo7Nq1q7YurVShwef3441bPsKZ730nJqmBq38EMqr8lqmNbXmcn7CN4TH7CNEMthZE831KW5Y+JghfmMOHjgQgwRP2y8A3tZLynxDohw20w3nldpiq6VvkFbPXlgQavoy7bhQNmsXz5ZQf2bh4CwCRseGced0oLnzgXELDK7dsat2CjWi6VmY2ozTTlGz5dzuuQpfXquMxDaKZePfZlbq2oiiKohyXpPQ8qrP/ekBVBlcCktINznlI1zqE0ME2GKxdEUIQFhnKTa9P5qXJbyFE2d8bTdfQI6zkXR5frs9u4Sm82nohVs3EUhwd/OtAvnUI+z+RuEuv6gsiyADfwYMIok11WzFzDWdF/R+RcRGMumwoZ904htjE6HLtTj3zFE498xSy03JwFhQS2zAai/UYf03VxIOiKIqiKLXguM7RUKqfdK1DpgxHZl4Pee8hc99Cpp+PTJ+ENFIAGHPFMB75/i6SOjYtOU8IQULTOEShJOKq3UResRPbd+ngMLELNy+0WoRNM0qCjGkfx/PQxa1ZtySiVl5ndcvPKaAg18HhPal8+cyPXNvtTvZtTfbZPio+kgbN4o89yAC6DursczYDPEunOvRu63U2Q1EURVHqI5WjUTWElCfO3E12djbR0dFkZWURFRVV28M57kn3PmTaOJAFwNE3qjpYWiPif0IITy0FKSV7Nu1n/YJNvHXbRxhuoyThGDwTE0ZbO8M/cvNA65XFG0JxcI+Ny/t1RAY5c3Ei0Cwarbok8fbKF6o916Egz8HFLa4nLyvfZ8Dx0Ne3M2Ri/2odh6IoiqJA3b5fKx5b33FPYrFWbslyMNwuB0unP1wnfwZVSc1oKD7J/E9BOigfZAAYGM6t5B3+raSStBCCZu0a89nj3+IudJcJMsATvVt3FHJmjgPEkU/qZ3wRh6hn70TTbbJ9zW42LtlS7dcKDQ/hqV/vxx5mQ9OO/KCLt9e94N7xDD6/X7WPQ1EURVGOG6qORpVQORqKbwXTgfL1Lw7vt/LtG4n8+W0czoIvsYd+z2mXDmHC7WewbsFqYuP3Ex0j2L0lBNMo+2m9NCQH/jvESSeb6EX54dv/Cy3X7ngkNE/itLOgEKEJ8jLzA7QXbFyylc79OlT72Dqf2p6PN73Gb+/OYuGPS3EWFNKuV2vOvmEMJw/qVO3XVxRFURSl/lGBhuKbzC13aP8OG7ef1Y6cLL0kOHAWFPLnZzNp3PBTzrgkjdFneGYyMlIs/PBuA75/u0GZZVGrFoRz+sVpJd/bQ82gd5aqy6Tp2cr2l8zP2LBkC7f2fzDACZTUpagJ8Y1jufSxiVz62MQau6biX0Geg7+/+od/Z67C7TLo0Lstp08eTlyj2NoemqIoSr1W3XkU9SVHQwUaim96CzC2UXp+7+U7k8oEGQBWm8kz/9tB5955JbMUALEN3Ex+MJmkNg5evjOJ4u2P/vk9msMHrcQlurFokn6js/lnRkzNvKZqZrgN3C43CU1iCY8J8zurIaWkx8iTfT6vnNh2rN3NvaOeJPNwVkntlCW/ruCLJ77jvs9vUTkziqIoynGvnq2MVypChF9U5vs9W+2sXxpRbpnTyPMzOKlP2SCjpA8Boy/M4KS+RwrGudwat+0eSLZhw5Qw6MxMQsIMToQFi86CQs6K/j8ubnkD+Vm+gwxN1+g1pjstOjWrwdEpdUV+TgH3nPYE2Wk5ACUFGqUpcbsNnrl4KltWbK/NISqKotRvxXU0qvNRD6hAQ/Et9HywnkLx22TnRu+7L5x5aZrf3xe3izJLpdw9Q9lhjWPiptG8ur8bG4x4hl+TXZUjrzWGy8DlcAPla4oAJcnYrbu24P7Pb6nx8Sl1w19fzCcrNdv7LmDSE6D/+OpvNT8wRVEURalCaumU4pMQNoj7CJn7OuR/hT3EezTRuIUTzU+qgcUKTVsVlnzvuMRTwC/XsPFtaju+TW0Hg0yi3t0BBTLo+nLRiVFkHT4OAhThycVo36sNsYnRDL2gP4bLYMrFU0k/mEliiwROv3IEfc/sie5tWkg54SydsRKB7zk8w22yeNq/NTkkRVEUpRSVo1E1VKCh+CVECCLybmTErXQbtxV72NM4811l2uRm64RH+S4IZxqQk3nkBtr+fQaOaxORCUfefiLLwNUrHOvCXKQMrpj1cRFkAEhwOV1Muudsug3twn2jnmTLih0l6/J3/beXJdNX0GtUNx7/+R5sIbbaHjEAKfvSmPvNIrJTs0ls0YChk/oTGXtiFlSsaYUOV8BZc5fLXTODURRFUZRqopZOKUERwkZ4bBcm3DauXBTw1/exGOV3wS2h6TDnxyO76FgX5RFx6x5Eiidgsf6ZReTkXVj/ya2yCD+hWVzVdFRFdIvO7v/28dLkt9m2ehdwZF1+8fKZFbPX8sF9/6utIZYwDIO3bvuYi1tcz/v3fs73L0/n9Rs/YFKTq/n5jd8Dnm+aJvu3JbN3835cha6A7U8UO9ft5vnL32Bc5CWMtkxk8km3M+2tmbi9BAwderUpWU7njaZrtD+ldXUOV1EURfFH1dGoEirQUCrk0scnMvaqEYCn4JsQgumfJJCbqWN4+QDW7YZdm+0s/C265JiQnhmMkA9T0f8rIPTVw5516UWTIse6ya3QqHNLkEzTxFng5J9flvmszi1NyW/vzSIvK8/r8zXl4we/4qfXZyCl9CQnuwyklLicbt685SNmfzHf63lSSn558w/+r/WNXN7+Fq7sdBuTGl/NJ498TaHzxA44ls9czQ2972POlwtw5DkxTcnejft44+YPeOjMKeUCrrHXjPSbCGgaJuNvOr26h60oiqIo1UoFGkqF6LrO7e9ex/vrXmbCbWcy/KKBNO3QlXvOa8eBXXbAE1wUBx0b/w3n3vPb4Cos+1YTJljn5xLy1mHQjj24KE2acGh3ShX2eOykKQmLCgv4CUahw8WmZdtqZlBeZKfl8MMrv/od58cPf41plg+W3rzlI964+UMO70ktOZaTkceXz/zIw+OmeP1k/0RQkOfgyYkvY7gMDPeRn0vxpiIr/1rHDy//Wuacxq0actu714IAzXLkd0PTPL8JYyYPV9vbKoqi1KLiHI3qfNQHKkdDqZSWXZK4+vn/K/k+/WAGsz+fx4olK2jZPg1HnpsvnjvA1rWhPvsQgGVnoc/na4IkcJATTBu/BHQZ3pms1OBySkyz9v76LJ7+L26Xn3VwwOHdKWxduZMOvdqUHNuwZAu/vPmH1/bSlKycvY5Zn83j9MkjqnS8dcHfX/1DQW6Bz+BMmpKf3/idifecXbLrGMDpk0fQrH0TvntpGst/X4VpmLTt2Zpzbz2D4RcNRIjju4CloiiKoqhAQ6kScY1imXj3eGA8AD9O/Y1t6z6pxREFx9+tXHGAISM0RK7vZHcoVdS8+GZT85wsDJA2wX9/beC/vzYEHI9u0Wt1bX5eVn5Jkro/+dlla4TMeG8WukUr84l+aUITTH/nzxMy0Njy73Z0i47hJ0BLO5BBVmoOsYnRZY6fPKgTJw/qBHiWnqngQlEURTmRqEBDqRbte7Wu1Vo0QghkkAPwNWNRvP2ocEpknIZI95FbIcA1MAKsAqOFDVEo0VLdiBQ31pX54AxuHJquMfzigUQnRAXVvjo0a98kYJAB0KRNozLf796432eQAZ5P9fdvTT7m8dVFVltwf0YDtVNBhqIoSh1iSs+jOvuvB1SgoVS5jEOZPDnxlVq7vhAEHWQE7AuQLolIl+hW759am02sFNzfuOzBfJOoi3cEtexKCIFE0qZbS26cemWVjLuyThnVlfgmsaQfzPQacGi6Ro/hJ9GwRYMyxyNjwwPOhIRF+l5Gdzzrc0ZPv7txaZqgfa82RMSE1+CoFEVRFKX2qWRwpcr9+OpvZB7OqrXrSwnWEGuZJFt/AuZo6GBG6XQc2K4kWTcQ68IccAYuPhgZF06bHi255c2reWXBE4RHhQXVf3XRdZ27P74RTRPltl/VdI2wqFBufK18MDR00gC/QYama4y4eFCVj7cuOOW0rrTokuTz/WaakgvuO6eGR6UoiqIcE7W9bZVQgYZS5X7/aI7PLVxrSruerenSr8Mx9WHGWyi4sQE537Uh5+vWLLnLpPX0YdAypEw7LdmFyCy7o5J2yA1B7LD7/OxHefvf5xl33SjsofZjGm9VOeW0brw09wm6Du5cckzTNQad25c3lk4hqUPTcucMndSfpu0ao3u52dZ0jdDIEM4+Qbdr1TSNZ2Y8QJPWDT3fFwVomu7ZTu2aFy5lwPg+tTlERVEURakVaumUUqWklGQHubtSdRp5yWDGXDmMsaEXVepTA7OhhdyXk5BROuieeQlTSFaL/VjebkXXLy1s+WJdSf2PJss1Dpx25FIySocgYq0be99Lv3G9mXjP2XQ+tX3FB1pNuvTvwAt/PUr6wQyy03KJbxJbrip46oF0/v1jNc6CQtp0a8ELfz3Co+e8wNYVOzwBhxAYLoOEpnE8/vM9NGgWX0uvpvolJiXw3tqXWPTzchb+tJSCXActuyQx9uqR5fJZFEVRlLpPUL1b0NaXrDwVaChVSghBTGI0GYcqsXSqOPv6GEUlRDLykkEU5Doq3V/BjYllgoxihjSRSA5fFcuXz7xD6r50ohMiSWzVgIfXfMNfh9ajIXANiiDk/ZSA1zcNyeJf/2XRtOU8+OVtda52QlyjWOIaxZY5Vugo5PWbPuTPT+diGmZJ4n3zTk25/4tbceQ5WDFrLYbboNOp7ekztkedK6BYHaw2K0Mm9q9z/4aKoiiKUltUoKFUudMnj+Dr536u+PKpKvrk4L7PbiY0IhSbYWC1W3FVsCq1mWjBfUqYJ6vc2/NIduelcCAsl25925Ucf7r7BYw+vIkf9y5ld0gKcmIhBd/sDxxsuE0Q8Oylr9N9+Em1uutUIFJKnrl4Kot+WV6Sk1GceL9vSzJ3DnuUt/59jssen1Sbw/Sq0Oli/neLmfXZPDIPZ9G4dUNOv2oEvcd0L1PfQlEURVFKqq5WZ//1gAo0lCp37m1nMOvzeaQnZ/jd8rQyQiNCPcXRvBBC0O6UVvQe0wPwJDYPPr8ff30xP2C/8Y1jST/k2WnJaG4rG2RIib6+AMvKfDDB6BiCu08423MO0i22RUkzTWgMbdiZoQ09uQ3mYJOPW37N9y9Px10YoCq2BMNtMPPjv5l499kBx1tbNi/fxj8/LfP6nGmYOPOdfPPcz9zx/vU1PDLv9m9L5sD2QwgheO+ez9i5dg+aJjBNya7/9vLPz8s4ddwpPPLdnVht1toerqIoiqKcUNTHeEqVi06IYuo/T9NjRNcq7/uKpy/wfHHUZIOmCXSrXm572HNuDpyArFt0+p3Viy4DOnq+dx3pXKS4iLhpDxH37sf+fQb2HzMIfzKZyCt3kbMp3W+/mqYx+ZmL+Gb/e9z27jUBxyGEYNvqnQHb1aa/vliAbvG9DMpwm/z1vwUYhv/q4tVt57rd3DH0ES5vfwsPnP409495ip1r9wBHKq8Xz7gt/W0lnz7yTa2NVVEURal7hKz+R32gAg2lWjRoFs+U3x/ks21v8Mh3d/Lwt3cQGhkS+EQf2VGartF1SGfOuXksj/5wF42Ldvgp1qZ7K16c8xidj9ppqnW3FoRF+a/fYLgNOvfrwMtzH+e1xc8waexI7IUaOEzC792PtrvQMzTD8wAQaW5+nPQ1KfvSAr6kqPhIxlwxHBFga1whwGqv25+qZ6VlB6xRUuhwUVhQWEMjKm/3xn3cOvAh/vtnc1DtpSmZ9tZMCvIc1TwyRVEURalf1NIppVo1bt2wJCjIz3Hw0uS3/J8gy1f11nQNq93K9a9cDsDAc/oyYHwftvy7ncyUbBKbJ9DqpOZeu7ParIy7bhTfvTTda86I0ARhUaEMPv9UhBB06tuOTn3bEb5zIW+99hXaQZf3quEmOHIdTHvzDyZPuTjgz0G36JxyWjdWzl7rM3fFcJucemavgH3VpsSkBF+pKyXCo8Owh9XeVr0f3PsFzvzCCuUIFeQ62LpiR5ktfRVFUZR6rLprXagZDUWpWmOuGEbrbi0DtmvYsmzV6ZMGduTVhU/StnurkmNCCDr0bkvfsT19BhmFjkJmfzGf/JwCohMiy82W6BYNXdd48MvbytWwuKjlAFost/rdf840TP76ckHA11PsgnvHY5reb341i0aTto3of1bdDjRGXzHMb96NpmuMvWpErSVXZxzOYulvKytVx8VfwUFFURRFUSpOzWgoNSY3K48da3b5baNbNIac348RFw8iOy2XxBYJNG7V0O853qyZ+x+Pn/ciOem5WKy6Z3MHCbpVx3AZ6BaNgRNO5YJ7xtO2R6ty5wshiHOFkhLg3jM/x3tiujfdhnbhzg9u4NVr30GaEik9MyqmYdKoRQOe+/Nhv/kPdUFSh6ZMuP1Mfnjl13LP6RaNuMaxTLyn9pLZ0w6kB1za5Y3VbqFN95ZVPyBFURTluCSkRFTjzlDV2XddogINpcb8+MpvgRsJQX52Aa1ObhG4rQ97Nu3n/rFPl+z05HaVSkyWkqQOTXh71fPYQ/wv72neqSlbV+3wbD/rbaiaoFn7JhUa25grhtFrVFf++OhvdqzdhS3ERr9xveg/vvdxs+vRtS9eSnzjWL5+7mey03IAz8/i1HG9uOn1ycQ0iK61sVVma2BN1xh12VAiYsKrYUSKoiiKUn+pQEOpEY58J9+/Mj1gO9MwadL22Copf//SNEy34XUpjOE22bv5AEumr2TI+f189vHvn6tZO+8/n0EGeJbajLtuVIXHl9A0nksePq/MMdM0yTicha5rRMZFIAIlQtQiIQTn33UW4285nc3LtlHocNG8czMSmsTV9tBo0Cyekwd14r9/NpXsLuWL0ATSlHTo3YZrX7y0hkaoKIqiHBfMokd19l8PqEBDqREr/lxDQU7gXX2EEJx26ZCS7wsdhcz7djHrF25ECEG3YScx8Nw+fj/9n/vtIv95BJpgwQ+LfQYanz32DZ8/8X3AsQKsX7SJ0ZcPC6qtN4bb4KfXZvDj1N9I2evZwap11xZMunc8wy8cWOl+a4LVZuWkgZ1qexjlXPn0hdw1/DGExOsyqqi4CIQmaNgykTOuOY2RlwzCFmKr+YEqiqIoyglOBRpKjchJzw2q3Zgrh5Usf9m0bCsPnfksWanZJbkLv70/m7jGsUz5/UFad/W+vMqZ739rVdOU5PsIeras2B50kAHwxwdzOO/2cbTo1Czoc4oZhsGTk15m0c/LyhQI3bl+D1Munsqejfu4/IkLKtxvfXfSwE489esDvDT5LVL3pyOEpwCrNcTKBfeM55JHzlOVwBVFURS/VI5G1VCBhlIjGrVKDKrdWTeMASB1fxr3jnoSR54T8HzyXyzzcBZ3DX+MjzdN9bomv3HrRPZvPej3OkkdvOdWvH/vF0GNs5hu0Zj16VyuevaSCp0HMOfLhV6rbBcv+frfUz8w8Ny+ZXbbUoLTa1Q3vtj1FitnryN5+yEiYsLoe0ZPwqNVHoaiKIqi1BT1sZ5SI7oO6UxiiwY+cw+EgDbdW9KmaPvb6W//iSPP6XWbUtMwyc3M4/cP53jtK5gE7aML/hXbuGRLwHPLkJCWnFGxc4pMe2smmp8ifrpF47d3Z1WqbwV0Xaf36O6cdcNohl80SAUZiqIoilLDVKCh1AhN07jjvWvRdFGuQrama1hsFm556+qSY/O/X+y3FoI0JQt+WOL1ud0b9vkdixCCVX+t89lvhQiIaxRbsXOK7Nmwz2/CsuE22bF2d6X6Pp6kJWewadlWDmz3PwulKIqiKDVG1sCjHlBLp5Qac8pp3Xhu1iO8f88XbF6+reR4lwEduPaFS+nQu23JseIlU/44cj15FukHM5jx/l8sm7ESwzBJ3Zfm9zwpJekHM70+175XG9Yv3BTEq/Ew3CajLhsSuKEX9jCb3zocQghCI0Mr1ffxYPfGfbx392cs+31VyR/cdqe05qopF9NzZNdaG9e6BRv57qVprJy1FtM06XRqeybcdib9zupVp3cDUxRFUZS6RgUaSo3qNqQLbyydwv5tyWQcyiKhaRyNWpbP32jdvSXpBzN9zmroFo023Vuy+u/1PDTuWVyOwoDbmRbTdI2GLRK8PnfBfefw0JlTgnsxAsZeNYIWnZOCa3+UIRP7M+3tmT630JVSMvg831vwHs92b9jLzf0e8CTul/pn27ZqJ/eNeYpHv7+LAeP71Pi4pr/zJ6/d8D66RSvZuWz9wk2snbeBiXedxdXP/1+Nj0lRFEWpBVJCdSZs15NkcLV0SqkVTds25qQBHb0GGQBnXT/a79Ipw20ydFJ/Hhr3LIUVCDLAk+Mx5soRXp/rc3oPzr31jIB92ENtXHjfOWWWe1XUObeMxWqzes3T0HSNBknxDLtwQKX7r8veuu1jnPmF5f6NPRXTJa9c8w5ul7tGx7Rn035ev/EDgDLbIxeP8dsXp7H8j1U1OiZFURRFOZ6pGQ2lTslOz2H9gk243QbDLxzAnK/+KdmeFI4UWTvvjnHsXL+XQkdhhfIqhCY49cxT6Dny5HLPuV1uFv2yHN2qM+i8U9m5dg8HticjhEazDo0545rTiGkQjT3URvfhJxF2jMuamrRpxJTfH+TRc54nJz0X3erZwtdwGTRu3ZBnZjxAaHjIMV2jLjq8J4WVs73nyAAgISs1h6W/razRWY1f3/kToQuk2/v7SdM1fnr9d3qP6VFjY1IURVFqh5CeR3X2Xx+oQEOpEwodhbxz56f8/uEc3IVHPslu070lBbkODmzzJAondWhC624tceQ5mPfdogoFGfZQG2deN4rJUy4qV0dh49KtPHbO86QfzPTc8EvPlrpturfkyWn30aBZfNW80KOcPKgTX+19h/nfLWHjki3oFp1TRnWj9+nd0XW9Wq5Z25J3Hg7YRtM1knccqoHRHLFhyRa/leBNw2TTkq01OCJFURRFOb6pQEOpVltWbOfn139n9d/rEQh6ntaV8TefXrKNLYBpmjx6zgusmLWmXOCwa/0eGrZM5ItdbzL368V8/NBX7N18AE3XMFwGgYRFhfLgV7ejWzQ69m1HeFRYuTbJOw9x72lPlBT6K93vrvV7uHvE47y35sVqqx5tD7Vz2qVDylREP5FFxkYEbGMaJhFBtKtKNrvvavPFLLYTM/hTFEVRjqJyNKqECjSUavPru7OYesN76PqRxNpZn81l5sd/c+eH1zP68mEA/DtzDf/OXO21D8NtkrzjEB898BVzvlx45LgZOMjQLBpdh3Smz+n+l7r8NHUGzoJCTLP8p9mG22T/1mTmf7+EkZcMLvOcaZqs+HMN/y3ajKZp9BhxMtYQK8t/X4W70E27U1rTb1yvkqrmxzNXoYsVf64ldX86cY1i6DWme1A35t60Ork5Tds15sC2ZJ9/Zy02C/3P7nUMI664PmN7sv6fTT5nyXSLRr9xNTsmRVEURTmeqUBDqRZbV+5g6g3vFS1BOnIDX/z1S1e9Tcc+bWnROYk/P/0bTdd8Jn9LUzL/u8VlcjWCYbpNzrklcGL331//4zfxXGiCud8uKhNo7PpvL4+c/RzJOw6hW3Qkks+f+M7TXhdommfGJa5xLI9+fyed+3UIfuB1zF//W8Dbt39MVmpOybHI2HCueeFSxlw5vML9CSGYPOVinjjvRZ9tJt51FlFxkZUaL8DBXYfZumIHFpuFkwd1IiImcLG+0ycP56spP+LIdZTfXEB4/mf8LWMrPSZFURTl+CFMz6M6+6+ogoICbr31VmbOnIlhGFx00UU899xz5bZej4iIIDo6GqvV84Fg7969+e6776pi2BWmdp1SqsUvb/yOrvt+e2ma4Jc3ZwKQsjfN740+gNtlBB1k6BbPdS97fBI9R5RP+j6aI8/h93lpSvKz8ku+zziUyZ1DH+XQ7hTAk8tRem2/NGTJ8qvMw1ncc9qT7NuaHNzg65i/v/6HZ//vtTJBBkBORh4vXfU2f346t1L9Djq3L3d/fCOhkZ5kd92iI4RAt+hccO94LntiUqX6TT2QzoPjpvB/bW7kifNf4pGzn2Ni46t56/aPcRW6/J4bnRDFlD8eIjQq1PNHu+jvtqYJLFYLD31zO61Oal6pcSmKoijKsbrzzjsxTZPt27fz33//8ffff/PGG294bbtw4UJ27drFrl27ai3IADWjoVSTNXM3lJnJOJrhNlkzdz0A8U3j/M5oBEMIgT3cjj3UxkkDOjL+5tPpPuykoM5t1r4J29fs8rtkpnmnZiXfT3trJrmZeUGN1zRM3IUuvn9pOre9c01wL6aOMAyD9+7+zG+b9+75nOEXDcRirfifklGXDWXw+f1Y+ONSDu1KISo+goETTiU2MbpS481Oz+H2QQ+Tsje1TG0Ol9PFz6//zuHdqTz6w11+i+51PrU9X+x4iz8/ncvK2WsxDZMu/TsyZvJw4htXrgK8oiiKchyqYzkaubm5fPrpp+zduxeLxUJ0dDT3338/Tz75JDfffHO59jExMVU00GOjAg2legRRQLn4hm/UpUNZ8P0Sv31pQvitlSGl5O6PbqhUgbtx14/mlWve8fm84TY589rTSr6f8+WCCgVFhttkzlcLjrtAY/3CTaTuT/fbJislm1Vz1tN7dPdKXSMkzF4u9yVYWanZTH/7T2Z+8jfZqTlYQ6xkp2Z7/dstTck/Py9j7fwNdBvSxW+/ETHhnHvrGUHVU1EURVGUmrBixQpatWpFXFxcybG+ffuyfv16DMMos1OlpmlER1fuQ7uqppZOKdWi16huJUuYvNF0jabtGvPDK7+ScSiTkwZ1LLflLHhmExq1TGTQeaei+ehPaILohEj6neU/UTdlXxqbl2/j8J6UMsdHXTaEbkN933w2btOQFl2OzGjklVpGFSxHnhN5nO0wkXk4O8h2WdU8kvIO7jrMdT3u5vPHv+XgzsPk5xSQleI9yCimWzRmfvJ3zQ1SURRFOX7JGngA2dnZZR5Op9PrcJKTk2nYsGGZY4mJibjdbrKyyv53WAhBmzZtaN++PZMnT+bAgQPH9KM4FirQUKrF2Ted7vemzzRMFv2ynPfu/oyXr36HTUu30aJLMzS97FRIjxEn88qCJ7nh1StIaOJZYlWapmtomsa9n92M1eZ9F6QtK7Zz94jHuaj5ddzU934ubnkDtw9+mA2LNwNgsVqw2Cw+l9Qk7zjEJw99XfJ9s/ZNvFbz9klAo1aJfpfs1EUNkoKrHZKYlFDNIynvmYumkn4os0IV4Q23Seo+/zM0iqIoilKTkpKSiI6OLnlMmTLFazu3213uA0vD8OSDHn1/kZGRwc6dO1m+fDlhYWGMGzeu1j7sVEunlGrRsksS9352M89d+joISpKlNa3sEqjir92Fbnau38OZ146i+9AuGG6DDn3a0rRt45K2byydwudPfM+fn87Fme8EAb1Gd+OSh8+nU992XsexcelW7hz2aLmaGxsWb+HOoY/y7J8PE984lhV/rvH9YiRMe3smlzxyHqERoYy7fjT/Ldoc9M9CIDjr+tFljm3+dzuLfl6GM99Jy5NbMHRSf0LC7EH3WRM69W1XtA3tQa9/oISABkkJnDy4k9fzDcMg7UAGmq4R3zi2ygKtbat3snHJlgqfp+ka8U1UnoWiKIoSmJASUY0358V97927l6ioqJLjdrv3e4G4uDhSU1PLHEtJSSEkJKTcMqniFSLR0dFMnTqVqKgoduzYQZs2baryJQRFBRpKtRl+4UDa92rD9LdmsmrOOoQQZKVmk56c4X22Q8KM92dzycPneU28jW0Ywy1vXsV1L19Gdmo2oZGhXgvwlXQnJVOvexej0F3uk2/TMJFS8PLV73DeHeM8OSV+/p448pxsWbGDbkO6MHRSf+Z8uYDlM1cHrEyu6RrtT2nNuOtHAZCbmccT57/Eqr/WFe205NlR6+3bP+a+z2+pM3Uadm/Yy/cv/0rq/nQfQYYnaLj5javKLXlzu9x8/9J0fnp9BunJmQA0a9+YSfeMZ/QVw4454NhYyercpmFy2qVDj+naiqIoilKVoqKiygQavvTs2ZPNmzeTkZFBbKznHmnRokX07dvX69LzYqZpYpomNlv1FB0ORC2dUqpVs3aNuf6Vy3lvzUs89ev9pB3wEWQUkVIy79tFAOzeuI9Xr3uPiY2v4pz4y7nntCdYNG05VpuFhKbxfoMMgO1rdrF9zW6fy2ukKTmw7SAHtiYHk7teElToFp3HfrqbSx46j8i4I9WrI2LCy3wfGhnCubeewfN/PYo91I6UkkfOfo41c/8DPNviuotmWgpyCnh8wgtsXFq5m+iqtHL2Wq4/5R5mfVY0c+RF0/aNeXL6fZx65illjhuGweMTXuSjB78qCTIA9m1N5qWr3ub9ez4/5vH52zbZF6EJep/egx7Dg9uJTFEURanninedqs5HBTRq1IgxY8bwwAMP4Ha7SU1N5emnn+a2224r02779u1s2eKZ9Xc6ndx666307t2bpKSkqvrJVIia0VBqTFZq4ORiTdfITsth6W8reOzcF5BSlmyTu2buf6z6ax1n3TCam16fHPCT8eTth4IaV0RseMDfd6vdQpvuLY98b7Ny6WMTufCBc0jecRhNEzRu0xBN0ziw/SDuQjeNWiViDz0yBbpuwUbWLdjotf/ivzlfTfmRJ36+N6hxV4eCPAdPnP8S7kLD53Kps286nRtevcLrz3/OlwtZ8uuK8h0XdfXdS9MZMrE/HXq3rfQYe4w8OeAMVGm6RWfM5OHc8Mrlx12ejKIoiqIU+/DDD5k8eTKNGzcmPDycu+66i/Hjx/PFF1+wfPlypk6dSnp6OhdeeCEFBQXY7XZGjBjB999/X2tjVoGGUmMaNItHaMLvciPTbRAVH8kTE1/GcJct0le8pey0t2bSZUBHhl840O/1ImIDV4MGaNW1BV36d2DTsq1ea39ousaoy4YSGRtR7jmrzUrzjk3LHCudV1Lagu+XoFt0DLfh9XnTMFny6woKHYXYQmpninPeN4v87qolJSz8cSnX+7hpn/bWzHJ5OKXpFo1f3511TIFG41YNGTC+D4un/et1m2EhBKdfNZyug7tgsVnoNrQzMQ3qxjZ/iqIoilJZCQkJ/PLLL+WOX3LJJVxyySWApwr4tm3banpoPtWppVNSSt566y26detGixYt6NmzJ3PmzKntYSlVJDohiv5n9S63c1RpthAbBTkOXE6Xz1kGTRP8+OpvmCKUnQAAKfRJREFU5Y4n7zjE27d/woXNr2NCgyv58pkfCYv2v7zKFmKl3SmteeCr24hvEocotZtU8dfte7Xm2hcvDeIV+pefW4AM8DG8NCXOgsJjvlZlbVq2Dd2q+22Tuj+9XKXwYns37fe7E5ThNtn1395jGiPA3R/dQPterQFK3k/F2yn3H9+bm9+4ihEXD2LI+f1UkKEoiqJUnATManwcXzveV1qdmtHIy8tj9erVzJ07l9jYWGbMmMGECRPYvHkziYmJtT08pQpMnnIRq/9eT0Guw+un0de9fDkrZq3x+wtompLNy7ex7PeV9B7TAyEEa+b9x4Njn8FV6C7pd+28DQEL6xU6XFza5iYue2wi76x6gd8/+IuZn8wlKyWLhi0TOeOa0xh5yaAqmWFIat8kYPJ4VHwk4QGCo2BsWLyZH1+bwcpZa0FCt6GdOefWM+g6uLPf86w2S1B//Kw27386QsLtfmdEhBCERYUGvkAA4dHhvLrgKRZP/5dZn80j/WAmjVolcvrkEfQYfpJaIqUoiqIodUCdCjQiIiJ47733Sr4fO3YsrVq14t9//2Xs2LG1ODKlqiR1aMrURU/z1q0fsXL2upLjjVs35IqnLmTYBQNYNWddUGvwHzxjCkMm9ue2d67h0fHPU+h0lbmRLx1k+Fuy5C508+EDX2ILtTHx7rOZePfZx/QafRl1+VA+eeRrDB/BhqZrjLt+lN/dI4Lx3cvTee+uz8r8DBdP/5eFPy3jmhcu5fw7x/k8t/fpPfj5jd99Pq9pgrY9WxMR431Z2rALBvLj1N98BnhSSoac3z/o1+KPbtEZeE5fBp7Tt0r6UxRFUZRiNbW97YmuTgUaR5NSkpaW5rOMutPpLFNBMTs7uErGSu1q0akZz/35CIf3pJC84zDh0WG06d6y5FPoU0Z2Zf53i4Pqa/53iygsKCQvO99nYCKEoEmbhqTsS8OR530XJYDPH/+OM689rdryI+IaxXLj1Ct57cYPyuWqaLpGyy5JlQ5yDLfBPz8v4/PHv2XXf/s8B2Xp5z03/u/d/RknDezote5IZkoW6xZsQNM1n4GCaUouuO8cn+MYf/Pp/Pb+LJz5heX60CwaDZrFM+zCARV8dYqiKIqiHI/qVI7G0V577TUiIiLo16+f1+enTJlSpppibW3dpVROYvMGdBvahbY9WpVZ6jLsooFEJ0T5zeUoJiUsn7na75anUkr2bj7gN8gAT42LVXPWB/8CKmHc9aN5/Kd7aNujVcmxsKhQzr31DF6e/wRhkRVfVrR0xkouSLqWJye+fCTI8EHTNX55s/yMxaHdKVzf8x6+ef4XHwnWnv+fPOViBp3rewahYYsGPD/rEaITIj3naaLk3zYxKZ4X/nqU0PCQYF+aoiiKotQOSTVvb1vbL7Bm1MkZDbfbzUMPPcR3333HH3/84XMpyf33388dd9xR8n12drYKNk4AoeEhTPnjQe497UlyMnIDtncXuoMKSoKRl5lXJf340//s3vQ/uzfpBzNwFhQS3yQOm93q95zczDxW/70ed6GbuMaxrP57PRsXbyE/p4ANS7YE/QfLNEzWzSu/xe4LV7xJWnKGzxwSKWHw+f244N7xAa/RoXdbxkwewVfP/FgyLk3XOLgzhQ/u/YJ7P78l4OtVFEVRFOX4V2uBRsuWLUu+7tq1K9OmTQM85dTHjx9PfHw8y5YtIz4+3mcfdrvdZ6l25fjWrmdrPt32Os9d+jpLf1sZsH2gpO+YxCgyDwdeWte4TaOgx3is4hqVr35+NFehiw/u+x/T356Jy+mukuvq1rJB2Z5N+0uKCPoz//vFJO88RONWDf22m/bWTE+QASW1OKTh+f8FPy4lLOoD7vzg+soMXVEURVFqRiWK6lW4/3qg1pZO7dq1q+RRHGS43W5Gjx7NsGHDmDZtmt8gQznxRcZGMOme8QHbhUTYiWsc63dWI/NwNtEJkWia992INE2Q1LEpHftUvr5DVZNS8tz/vc5PU2dUWZAB0Of0nmW+37piR1DnCSGY980iv20Mt8H/nv7B5/PSlMz85G9SD6QHdU1FURRFUY5fdSpH4++//yY/P5+nnnqqtoei1BEnDexIq5Obo1m8v1WFJjjr+jE8O/OhgMunslJz0Cx6uXaarqFZdO54/7o6tS3qxiVbmPfdYq8Vuo/F2TeNKfO9xcdWtUcTmiAn3f9Stq0rd5BxMNNvG2lKlgUxS6UoiqIotaY6a2gUP+qBOhVobN26lT179tCyZcsyj0cffbS2h6bUEiEEj/5wFzEJUWWK6RXPTHQb2oXLHp9IYvMEn9vXlpyja5xx9Ui6D+tS5njXIZ15dcGTnDSgY9W/gEpy5Dt5/54vqrzfs24YTVKHspXMuw/rUlLszh9pSKISIvnwgS+Z2ORqxtgmcVGL6/nfUz+QW5Tb4swPXGxQaAJHvv/EfEVRFEVRjn91Khn8hhtu4IYbbqjtYSh1TNO2jXlv7UvMeP8vZn02l+z0XJq2bcSZ145i2IUDsFgtpB3wnchcTNMEQhM89+cjpB5IJz05g7hGMSQ0rRtL9Aodhcz5aiE/vvobezbuK9mStqr0GduDG6ZeUe54dEIUp181gl/fmeX3fItN57uXp5OTlluSE5OyN5XPHvuWPz/9m1f/eZqkjk3Kbd17NGlKWp7U/NhejKIoiqJUI1VHo2rUqUBDUXyJTojiwvvP4cL7vddwiEqI9Fv/ATw1IOKbxAGQ0CSOhKKv64Jlf6ziifNewlkNn/Tbw2xc9vgkzr3tDHRd99rm+pcvZ//WZFb95Xt737jGsaTuSyv3MzZNk0O7U3jthvd59Pu7GHhOXxb9ssxroKTpGonNE8rNKimKoiiKcuJRgYZyQgiPCmPguX1Y+OMyv1WpR1w8qIZH5l/q/jSeuuBV/vtnU5X2GxETzimjunL+HWfRIYgEd1uIjef+fIS/v/mHD+77Hyl7Usu1ObQrxef5htvkn5+XkXognRtevZyNS7eSnpxxVHV2DYvVwgNf3nbM1c8VRVEUpVqpXaeqhAo0lBPGZY9fwPLfV+MsKF+VGmDS3WfToFntLpPKzylgwQ9L2LFmFxmHMln483JcDleV9K1bdK5/5XI6ndqOtj1aVfhmXgjB8AsGMmzSAJ6/7A1mfzG/QudLU7J91U76nnEKby1/lq+m/MQfH82hINeBbtUZcn4/LnrgXFp0VrVuFEVRFKU+UIGGcsJo3rEpryx4kpeuervMlq1hUaFceP+5TLrn7Fobm2EYPHPRqyz4fmmV7yIF0Ork5tz+3nV06tvumPtaO39DhYOMYsU7WMU2jOGGV6/g2hcvJS8rn9DIEKw2VaRPURRFOU6oGY0qoQIN5YTSpltL3lr+HNvX7GLvpv2ERobSfVgX7KG1W9jx7uGPs25B+Yrcx2LiXWfRqV97mndqRvOOTQOfEKTf3p2FbtEqnIweEm6nc/8OZY7pFp2o+MgqG5uiKIqiKMcPFWgoJ6Q23VrSplvLWrt+bmYeq+asp7CgEMPtrvIgQ7doLPltBQnN4uk9pnuV9r27EjteCSEYf9PphIaHVOlYFEVRFKVWqBmNKqECDeW44yp08ecnc5n+zp8c2HaQ8OgwRlw8iPE3n17rW9UaboMP7/8fP73+O+7CqqvmXUIA0pN8vWfTft6+/RPmfLmA52c/QmhEqM/TpJRsXr6NmZ/MZee6PYRG2BkyaQCn/d/gcjtRhUeHIURwfwN1i47hNhgysR+XP3nBMb44RVEURVFOJCrQUI4rzgInD4x9hrXzNyAQSCkpyHXw3UvT+e292bw093Fad21R4+PauHQLP02dwYrZa8lOzany/q12C4bbLJvkLkEi2bJiBx89+BU3Tr3S67mFjkKevvBVFv2yvMzxf2eu4a1bP+Khb+6gz5geJceHXTDQ7wyM0AQtuyQR2zCGxOYJjLlyOJ37ta9TVdUVRVEU5ZiYeD7cq87+6wG1x6RyXPn88e9Yv2Cj5ya71EfupmGSn1PAo+c8j2nW3G9v6oF0zms4mVv6PcjfX/9T5UFG5/7tuemNybicbp/b9pqGye8fzqEgt8Dr81Ovf59F05Z7fa4gx8FDZ05h7fwNJcdGXjKIhs0boHmpFq7pGhEx4Uz54yGe+/Nh7vzgerr076CCDEVRFEVRylGBhnLcKHQUMv2dPzF9VJ02DZODOw+z4s811T4WKSXzv1vMhUnXkpWSXW3XceY52btxv9eb/jLt8p3s3Xyg3PGUfWnM+nwe+FkGJU3J+/d+UfJ9aEQoL/79WEmCuW7R0a2e5VUNmsXz4pzHiG8cW4lXoyiKoihKfaKWTinHjf3bDpKf7f1T+2K6RWfjkq30LrUUqKpJKXnj5g+Z9tbMartGsZ3r97J7wz6kj+CqNN1Svur3shkrgzp309KtHNx1mEYtEwFo1DKR99a8xOq/17Pqr3VIU9JlQEd6n97dZ3VxRVEURTlRCCkR1ZiwXZ191yUq0FCOG5oeeAJOSun1hvtYFTpdzP9uMX/9bz67N+wjZW9alV/DG9MwkYiAwUJsw2hadilfCM9ZUFiSQB5IVkp2SaABnp2kegw/mR7DT67osBVFURRFUVSgoRw/mrVvTHzTONL2p/tsYxomp4zqWqXXzUzJ4u4Rj7Nr/V6EFvimv0IEJLVvwv5tB33mYMj/b+/O46Ks9j+Af54ZlkGQEURAARkE9eaSV8WQMMktk66mubS4VebeFeleNcqiTK/KLbfMtAJ/KhamXfc9l7qFqViYmpJ7GGCAyqYsM3N+f3BFpwHZntng8345+vJ5znOe75zXcZwv5znn6Mrup1AqKi0z/J9PV5hgtXrYv1pJBgA09XGvXkEiIqL6jsvbyoJzNMhmKJVKjPjnoMrP2ynQLrQN/vJI3XfHFkLg9Pfn8HXCt5jVfy6u/nKt7LicSQYACMC3bQtIiqonU/u1bQEAKJ93/b8/+47uiaFRT1V4TafH26N5K68q6w5+ohM8WjDRICIiIvlwRINsypBpEUhLTceOlfvKd6++O8rg07o5Yr76Z53qLy0pxbo5m7B56U4UFRbLFHUF/vc405PjeqN5Ky8c3fnjA4srlAr0eCYEaed+vzcZ/n9/HEj4Lxq7u2Di+2OM5k9IkoQ3E6MQ1WM2SivZ18PByQHjY0fX9R0RERHVH3oBSCYcdZD7B5dWiokG2RRJkhC5Yjz6je6JXZ9+jbTUdLi4uaDPCz3QY2h3ODja16reiz9fwbxnF1e4clNdqZs1xiMDuuDk4TP447dsAICXfzMMe20gBk3pj+zfb+D/ZidWer3CToFWHVti/dyvKjwvhMDmpbsgSRImL3rR6Hzb4EB88vMHWDR+pdH+GG26BSJq1USL7D1CRERE9ZskRP15SCwvLw9qtRq5ublwdXW1dDhkAwpzC/FZ9HrsWLlf1nqV9ko8Hz0EHXs8hE6Pt4fSTgm9Xo/s329AkiQ0beEGheLek4tx0euRuHCLUT2SVPabJEmVzs8oL6uQ8EXaqgcuPVtaUopT/z2L0mItWgR6wa+tT23fIhERUa1Y8/e1u7H1bRUJO6Wjye6j1RXj60tLrbIN5MQRDWqQDm9MwuLxK6tcLremJAmIGN8Xr344Dnb2hv+8FAoFPP08Krzu5X+9AOcmzlg/d5PBI1tClP0mqjGjWwiB/371Awa/OqDSMvYO9ujSR97J8kREREQVYaJBDcq18xn4R68Y3Ei/KVudCqUCer0eEgBNBz+0f/Qv1VqK936HNyThqyXb6zQvRKFQIP9GQa2vJyIiortMvOpUdZeEtHFMNKjeKykqwZblu/B/b3+J0qJSWeo0XOZW3P2FK2euIfbF5Ujel4JZa/9u8HjUnwkhcDHlCpZN/RRnfzhf55j0On21VpgiIiIiMgcmGlSvfTpzLb58f7ts9UmSBGe1E5r5eeDqL2nQ6wT0uns/lbibfBz8/Dt07vMwnnypV4X1bFm+C+vmbEJedr5ssTVydUKPZ0Jkq4+IiKjB4j4asuA+GlQv/bAzGU86PidrkgEAU5e9jM031iB8xKMP/IyQFBK2LNtpdPz7rccwQPUcPpq2WtYkAwAiV4yHqpHpJq4RERER1QRHNKheWTR+BfbEH4bci6kp7ZX4+4fj8NSEfgCA8z9eeuA9hF7g0s9XodfroVAocCHlMmIGx5YvbyunFkHemLzoRXT/W1fZ6yYiImqQ9AImnUfBfTSIrJ9Op8PN67n4fN4mbP9Y3iVq7+o5IhQzV0+Fo9O90QJ7BzsoJAX0ovIlZxV2SkiShK/XfYOFY5fLEoukkNCkmSte+3QSBAC/Ni3g07o5JKnqncWJiIiIzImJBtmkotvF+GLBf5A4f7PBHAm5SQoJWWk5sP/TRoCPDOiCwxuSKr1OoZTg17YFPpm5Dl8t2iFbPI6NHPDe9mi0DQ6UrU4iIiL6E6Eve5my/gaAczTI5ny/5RgGuozC53P/Y9IkAyh7BOrskV/x04FTBsfDR4TCw8e90mVs9TqBq2fSsOmD7fI8xiUBT77UC5+dWswkg4iIiGwCRzTIZhQXFWNMq6m4kZlr1vsq7ZQ4vCEJXft1Kj/moHLAgn1vYVa/OcipZE8OOfILe5U9/jbxCYx6ayhc3RvXvUIiIiKqGledkgUTDbJ6v19Ix9+7v4H8G4UWub9er8ftfOMdxD1besDLv1mliUZdePg2RdSqCXhkQBfZ6yYiIiIyByYaZLWSv07B7KcWQFeqs2gckiTBJ8i7/O9Xf0nD3jWH8dWiHdDr5H3GctTbw9FzaAgCOvrLWi8RERGRuTHRIKtz8eQV/D0kGqUlWkuHAqBsRGPAK31w9Zc0xL70EX49flH2eyjtFYg7vQg+rX1kr5uIiIhqiMvbyoKJBlmN//7nKP41cgm0xdaRYEhS2SOUw6L+hj3xB/Hl+9tkj83ewQ5j5jyL52YOlrVeIiIiIktjokEWd+jL7/Gv55ZYOgwjjd1dUHDrNjbJuDytk4sK9o52CPxrAEbMfBrB900wJyIiIivByeCyYKJBFnPym9OY0XcOhImXqK2pqcteRlz0euTlFMhWp0KpgF/bFliaNA/Oro1kq5eIiIjIWjHRILMTQuCjyHhsXb7H0qFU6KNp8bLWZ+dghz4v9MCE98cwySAiIrIFAiYe0TBd1daEiQaZ3ZYPd5skyWj7SCBSj8k/Ubu2wkeEYtDUJ6Fp78c9MIiIiKjBYaJBZqUt1WLdnC9lrdPvLz64kXETF368LGu9tdXE0xXz985GUKcAS4dCREREtcE5GrJgokFmdSYpVfaN99LO/S5rfbVl52CHsXOexbMznoYkSZYOh4iIiMiimGiQWRUVFFk6BNlJCgm9n++BV5ePg4va2dLhEBERUV3p9QDk3ZTXuP76j4kGmZXfX+rPhnR/7d0RQ6OeQrvQNpyDQURERPQnTDTIrFoEeuOvvTog5fDpaq244N5cjRuZuVa1OoMkASNmDsYr80daOhQiIiIyBc7RkIXC0gFQwxP58Xg0buICPGAaQ1Nfd+zVbsDKH9+Hg8rBKuY82Nkr8dTEvtian8Akg4iIiKgKTDTI7HzbtMBHyQvQb3Q4lHb3uqCLmzNGzh6K/fqNSPxtFRQKBdy8muCd/8yAnYMSCuW9sgql+RKPoM4BmLN1FnYXJ2L6xxPh1MjRbPcmIiIiC7g7omHKVwMgCVF/3mleXh7UajVyc3Ph6upq6XCoGopuFyMvOw8ubi5o1Nip0nKZV/7AjpX78MOOE9BqdWgf2hbJe1Nw849cCL1purDSToFPTy+GX5sWJqmfiIioIbLm72t3Y+vr8TLsFA4mu49WX4Kvs+Otsg3kxDkaZFGqRo5QtWxWZTlvjSdeWTAKrywYBQBIOXwaR3f9aJIkQ1JIGDl7GMa+M0L2uomIiMgG6AVMOkHURD8ktTZMNMjmrHt3I9a+K++mfwAQNrgbJr4/Bs1becteNxEREVFDw0SDbMrFlCuyJhmSJOGpiX0xds5zaOJRf4cuiYiIqPqE0EMI0+11Ycq6rQkTDbIpH06Lk60uL00zLPp2Djx9PWSrk4iIiIjKMNEgm3Lu6Pk61+HkokLM5n+ia59OMkRERERE9Y4Qpp1HUX/WYnogJhpkU/S62g819ngmBJEfv4ImzZrIFxARERERVYiJBtkUn6DmuPZreo2ueSi0DebvfhPOro1MFBURERER/Rk37COb8uzMp6td9pGIzthV9DmWfT+PSQYRERFVHzfsk4VVJRpCCDz//PMICgqCj48PevfujbNnz1o6LLIi/caGo9uAzpUXkIDeI3tge2EC5u14A/YO9uYLjoiIiIjKWV2iMX78eFy4cAHXrl1Dnz59MGrUKEuHRVZEqVTiva2zMGnRWDR2dyk/7qCyx6Ap/bGnJBHR6yKhcnK0YJRERERk0/R6078aAEkI6x27OXXqFPr164fMzMxqlbfmLe1JfkIIFObehtJeCSdnlaXDISIiomqw5u9rd2Pr03gk7CQHk91HK0pwIH+9VbaBnKx2MnhWVhZiY2MRGRlZaZni4mIUFxeX/z0vL88coZGVkCQJLk2cLR0GERER1TdCAODytnVlVY9OAcD69evh5eUFT09P2NnZPTDRmD9/PtRqdfnLz8/PjJESEREREVFlrC7RGDlyJK5fv46cnBx4eXkhLCwMJSUlFZaNjo5Gbm5u+SstLc3M0RIRERFRfSP0epO/GgKLJRoajab8NWjQIKPz7u7uWLBgAfLy8vDtt99WWIejoyNcXV0NXkREREREZHkWm6Nx5cqVapVzdHSEk5OTaYMhIiIiIrqLczRkYVWPTn3zzTc4cuQIAECv12Pp0qVQKpUIDg62cGRERERERFQTVrXqlL29PSZPnozMzEy4uLggNDQUe/bsgaMj90QgIiIiIjPRC0DiiEZdWVWi8eijjyIlJcXSYRARERERUR1ZVaJBRERERGRxQgAw4cpQDWREw6rmaBARERERUf3AEQ0iIiIiovsIvYAw4RwNwRENIiIiIiKi2uGIBhERERHR/YQepp2jwZ3BiYiIiIiIaoWJBhERERGRlbtz5w4mTJgAf39/+Pr6YubMmRXO9fjpp5/QvXt3+Pv7o127dti/f78Foi3DRIOIiIiI6D5CL0z+qql//OMf0Ov1uHjxIs6cOYNDhw5h+fLlBmXy8/MxcOBAzJ07F1evXsXHH3+M4cOHIzMzU66mqREmGkREREREVqygoABr1qxBbGws7OzsoFarER0djfj4eINyX3zxBbp164a+ffsCAMLDw9GzZ09s2LDBEmFzMjgRERERkQErmwx+4sQJBAQEwN3dvfxYSEgITp8+DZ1OB6VSCQA4cuQIwsLCDK4NCQlBSkpKnUOujXqVaNx9Ti0vL8/CkRARERFRRe5+T7PmvSS0KAVMGJ4WpQCMv7M6OjrC0dHRqHxGRga8vLwMjnl6ekKr1SI3N7c8AcnIyEDv3r2Nyh09elTO8KutXiUa+fn5AAA/Pz8LR0JERERED5Kfnw+1Wm3pMAw4ODjA29sb32XuMvm9XFxcjL6zxsTE4J133jEqq9VqjRIznU4HAJAkqcpy95cxp3qVaLRo0QJpaWlo3LixxRq0tvLy8uDn54e0tDS4urpaOhybx/aUH9tUXmxP+bFN5cX2lB/btIwQAvn5+WjRooWlQzGiUqlw+fJllJSUmPxeQgij76sVjWYAgLu7O7Kzsw2OZWVlQaVSGSRrlZXz9vaWKeqaqVeJhkKhgK+vr6XDqBNXV9cG/eEjN7an/Nim8mJ7yo9tKi+2p/zYprC6kYz7qVQqqFQqS4dhoEuXLkhNTcXNmzfh5uYGAEhKSkJISAgUintrO3Xt2hVJSUl47bXXyo8lJSXh2WefNXvMAFedIiIiIiKyat7e3njyySfxxhtvQKvVIjs7G/PmzcP06dMNyo0cORIHDhzAwYMHAQC7du3C2bNnMXz4cAtEzUSDiIiIiMjqxcXFIT09Hc2bN0dwcDAmTJiAwYMHIyEhAZGRkQAAX19fJCYmYsqUKfD09MTcuXOxfft2ODs7WyTmevXolC1zdHRETExMpc/mUc2wPeXHNpUX21N+bFN5sT3lxzaluvDw8MDWrVuNjo8aNQqjRo0q/3v//v1x7tw5c4ZWKUlY89piRERERERkk/joFBERERERyY6JBhERERERyY6JBhERERERyY6JhgUIIbBixQp06tQJ/v7+6NKlS/kyZH+WnZ0NSZLg7+8PjUYDjUaDqKgoM0dsve7cuYMJEybA398fvr6+mDlzptGOmADw008/oXv37vD390e7du2wf/9+C0Rr/Q4ePIiwsDAEBQUhMDAQH374YYXlOnToAC8vr/I+GRoaauZIbcOrr74KtVpd3k4ajQZXr141Ksf+WT27d+82aEuNRgMvLy80btzYqKyLiwt8fHzKy1lqaUdrJYTA2rVrjf7t1qQvLlmyBEFBQfDx8cGQIUOQk5Nj6rCtVkXtWVpaijlz5qBjx47w8/PDY489hpSUlAqvT05OhlKpNOjbH3zwgZmiJzIhQWaXn58vxo8fL27cuCGEEGLnzp2iSZMm4vr160Zls7KyhCRJQqfTmTtMmzB58mQxbtw4UVpaKm7duiWCg4PFsmXLDMrk5eUJHx8fsX//fiGEEIcPHxZqtVpkZGRYImSrNm3aNHHu3DkhhBAXL14UPj4+Yvfu3Ubl2rdvLw4ePGju8GzO1KlTxdtvv/3AMuyfdTNx4kTx5ptvGh13dnYWly5dskBE1m/37t2iQ4cOIjAwULRt27b8eE364oYNG0Tnzp1FTk6O0Gq1YtKkSeKZZ54x23uwJpW15+nTp8Vbb70lCgoKhBBCrFy5Uvj6+oqSkhKjOo4fPy5atmxptpiJzIUjGhbg4uKCTz75pHxnx4iICAQEBCA5ObnC8o0bNzbY9ZHKFBQUYM2aNYiNjYWdnR3UajWio6MRHx9vUO6LL75At27d0LdvXwBAeHg4evbsiQ0bNlgibKu2dOlStG3bFgDQqlUrjBgxotLRtiZNmpgxMttVVTuxf9bepUuXsHnzZsyYMaPC8+yjFSssLMTChQvx2WefGRyvSV9csmQJYmJi4O7uDqVSiffeew/btm3DjRs3zPIerEll7dm+fXvMmTOnfP+CiRMnorCwEOfPn6+wHvZXqo/47dUKCCGQk5MDtVpd4Xl++FTsxIkTCAgIgLu7e/mxkJAQnD59GjqdrvzYkSNHEBYWZnBtSEhIpUPYdE9WVhb7ZR1V1U7sn7W3YMECTJ06tcI+qlAoKu27Dd3QoUMRERFhdLy6fVGr1SI5OdmgrIeHBzQaDU6dOmWSmK1ZZe35Z7dv38bt27f5mUoNChMNK7Bs2TK4uLhU+px7ZmYmNBoN2rVrh6ioKOTm5po5QuuUkZEBLy8vg2Oenp7QarUGbVRZuYb8PHF1HDt2DDt27MALL7xgdE6SJDz++OPlox6//vqrBSK0DdHR0WjZsiV69eqFffv2GZ1n/6ydrKwsbNiwAZMmTarwvCRJCAwMRJs2bTBu3Dikp6ebOULbU92+mJ2dDZ1OBw8PjyrL0j1vvvkmHn/8cfj4+FR4Pjk5Gf7+/nj44Yfx7rvvori42MwREsmPiYYFabVavP7661i2bBm2bNlS4eNRHh4eKCoqwpUrV3Do0CFcu3YNL730kgWitT5ardZo4vfdkQxJkqosd38ZMpSYmIhBgwZhzZo1CAgIMDp/8uRJXL16FWfOnEHnzp3Rt29fFBQUWCBS67Zs2TJkZmbi8uXLmDFjBkaMGIETJ04YlGH/rJ1169ZhyJAh8PT0rPD8zZs3cfnyZRw/fhyNGjXCwIEDK1wogu6pbl/UarUAwH5bTYWFhRg7diy++eYbrFu3rsIyXbt2RWFhIa5evYqtW7fi4MGDiI6ONnOkRPJjomFi968gMWjQoPLjWVlZCA8Pxy+//IJjx46hdevWldZx94Pby8sLy5cvx/bt2/mTDgDu7u7Izs42OJaVlQWVSmUwNF1ZOW9vb7PEaUt0Oh2mTJmCd999F3v37jXos/e7mxQ7OTkhOjoazs7OOHr0qDlDtQl320mpVCIiIgLPP/88tmzZYlCG/bN2Vq9ejZEjR1Z6/m7bq9VqLF26FKmpqbh06ZK5wrNJ1e2Lbm5uEELg5s2bVZZt6C5evIhu3brB3t4e3333HZo1a1ZhufsTtICAAMTGxmLjxo3mCpPIZJhomNiVK1fKX9u2bQNQ9tOg/v37o1evXti2bRuaNm1a7fq0Wi2USiWUSqWpQrYZXbp0QWpqqsF/dklJSQgJCTEYHeratSuSkpIMrk1KSuKSrBWYPn06Ll26hOTkZHTq1Kna12m1Wjg4OJgwsvqhonZi/6y5lJQUpKeno1evXtUqr9frodfr2UerUN2+6OzsjLZt2xqUzcjIwPXr12v0uVHf3bp1C71790ZUVBQ+++wzNGrUqNrX8jOV6g3LLXjVcO3bt89gCbwHOXnypLh27ZoQQohbt26JIUOGiDFjxpgyPJsyaNAgMWnSJFFaWiqysrJEx44dxebNmw3KpKWliSZNmogDBw4IIcqWE/b39y9fcpDK3LlzRyiVSpGenv7ActevXxcnTpwQQgih1WrFvHnzRJs2bcSdO3fMEaZN2bNnT/nS1Hv37hVubm7izJkzBmXYP2tu/vz5YvDgwZWev3DhgkhNTRVCCFFUVCSmTJkievbsaa7wbMahQ4cM/i+qSV9ctGiRCA4OFjdv3hTFxcVi7NixYvr06WaL3Rr9uT0/+eQT8cQTT1Tr2h9++EHk5OQIIYTIyMgQYWFhVS6NTWQLOKJhAefPn8dvv/1mtPFUTEwMAGDhwoWIjY0FAPz2228IDQ2Fr68vunbtiqCgIKxYscKS4VuVuLg4pKeno3nz5ggODsaECRMwePBgJCQkIDIyEgDg6+uLxMRETJkyBZ6enpg7dy62b99evuQglbl06RL0ej1CQ0MN+mX//v1x4MABjBgxAgBQVFSEMWPGoHnz5ggKCkJKSgr27t0LlUpl4XdgfRYvXgxvb29oNBrMnTsXmzdvRrt27dg/6+jo0aPo0qWLwbH72/TGjRuIiIiAj48PHnroIZSUlGDTpk2WCNWmVNUXhw8fXr7cdWRkJMLDw9GmTRtoNBo4OTlhwYIFlgzf6pw/fx5Hjhwx+r/+008/BQBMmzYN69evBwD8/PPP6NChA1q2bInw8HBERETgrbfesmT4RLKQhODsOCIiIiIikhdHNIiIiIiISHZMNIiIiIiISHZMNIiIiIiISHZMNIiIiIiISHZMNIiIiIiISHZMNIiIiIiISHZMNIiIiIiISHZMNIiIiIiISHZMNIiITOzFF1+Em5sbNBoN/Pz80Lt3bxw7dqz8fG5uLt544w20a9cOAQEB8PLyQvfu3XH79m2DehYvXgxHR0fk5ORUeB+tVotFixZh8ODBpnw7RERE1cJEg4jIDGbNmoUrV64gLS0NkydPRkREBLKysvDHH38gNDQUKpUKR44cweXLl5GZmYl///vfUCqVBnXEx8ejffv2SEhIMKo/ISEBrVu3xooVK1BUVGSut0VERFQpJhpERGY2fPhwBAYGIikpCePHj8fo0aPx9ttvQ61WAwAkScJjjz0GR0fH8muOHTuG0tJSzJs3D3FxcUZ1lpSUICEhAbNnzzbb+yAiInoQJhpERBZQUFCAW7du4dChQ4iKiqqyfFxcHMaOHYsnnngCOTk5OH78uMH5l19+GWFhYaYKl4iIqMbsLB0AEVFDUlhYiCVLlsDBwQEqlQoPP/wwVCrVA6+5c+cONm7ciFOnTkGpVGLMmDGIi4tDt27dzBQ1ERFRzXFEg4jIDBYuXAiNRoOQkJDykQy9Xg+dTlfltZs2bUK3bt3g4+MDoGxyeWJiIu7cuWPqsImIiGqNIxpERGYwa9YsvP766wbHAgMDkZqaCp1OZzTx+35xcXFISkoyGPkoKSnBpk2bMHr0aJPFTEREVBcc0SAispDg4GA0bdoUq1atqrTMxYsXcfLkSRQUFKCoqKj8tWrVqgonhRMREVkLJhpERBaiUCiwevVqxMTEYPXq1SgpKQFQth/G9u3bUVRUhPj4eAwcOBAODg4G1w4bNgxHjx7FhQsXLBE6ERFRlZhoEBFZUI8ePXDw4EHs3LkTrVq1gkajQVBQED7//HNIkoS1a9di2LBhRte5ublhwIABiI+Pt0DUREREVZOEEMLSQRARERERUf3CEQ0iIiIiIpIdEw0iIiIiIpIdEw0iIiIiIpIdEw0iIiIiIpIdEw0iIiIiIpIdEw0iIiIiIpIdEw0iIiIiIpIdEw0iIiIiIpIdEw0iIiIiIpIdEw0iIiIiIpIdEw0iIiIiIpLd/wNf6C4/+MrwYwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 4일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table id=\"T_56ea6\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_56ea6_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_56ea6_level0_col1\" class=\"col_heading level0 col1\" >평균이용시간</th>\n",
       "      <th id=\"T_56ea6_level0_col2\" class=\"col_heading level0 col2\" >평균이용거리</th>\n",
       "      <th id=\"T_56ea6_level0_col3\" class=\"col_heading level0 col3\" >주말대여비율</th>\n",
       "      <th id=\"T_56ea6_level0_col4\" class=\"col_heading level0 col4\" >새벽대여비율</th>\n",
       "      <th id=\"T_56ea6_level0_col5\" class=\"col_heading level0 col5\" >오전대여비율</th>\n",
       "      <th id=\"T_56ea6_level0_col6\" class=\"col_heading level0 col6\" >점심대여비율</th>\n",
       "      <th id=\"T_56ea6_level0_col7\" class=\"col_heading level0 col7\" >오후대여비율</th>\n",
       "      <th id=\"T_56ea6_level0_col8\" class=\"col_heading level0 col8\" >저녁대여비율</th>\n",
       "      <th id=\"T_56ea6_level0_col9\" class=\"col_heading level0 col9\" >야간대여비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
       "      <th class=\"blank col9\" >&nbsp;</th>\n",
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       "  <tbody>\n",
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       "      <th id=\"T_56ea6_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_56ea6_row0_col0\" class=\"data row0 col0\" >10.882042</td>\n",
       "      <td id=\"T_56ea6_row0_col1\" class=\"data row0 col1\" >65.326193</td>\n",
       "      <td id=\"T_56ea6_row0_col2\" class=\"data row0 col2\" >5604.094655</td>\n",
       "      <td id=\"T_56ea6_row0_col3\" class=\"data row0 col3\" >0.378952</td>\n",
       "      <td id=\"T_56ea6_row0_col4\" class=\"data row0 col4\" >0.012685</td>\n",
       "      <td id=\"T_56ea6_row0_col5\" class=\"data row0 col5\" >0.012044</td>\n",
       "      <td id=\"T_56ea6_row0_col6\" class=\"data row0 col6\" >0.119944</td>\n",
       "      <td id=\"T_56ea6_row0_col7\" class=\"data row0 col7\" >0.691378</td>\n",
       "      <td id=\"T_56ea6_row0_col8\" class=\"data row0 col8\" >0.127002</td>\n",
       "      <td id=\"T_56ea6_row0_col9\" class=\"data row0 col9\" >0.020602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_56ea6_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_56ea6_row1_col0\" class=\"data row1 col0\" >11.334426</td>\n",
       "      <td id=\"T_56ea6_row1_col1\" class=\"data row1 col1\" >61.208032</td>\n",
       "      <td id=\"T_56ea6_row1_col2\" class=\"data row1 col2\" >5272.998312</td>\n",
       "      <td id=\"T_56ea6_row1_col3\" class=\"data row1 col3\" >0.358206</td>\n",
       "      <td id=\"T_56ea6_row1_col4\" class=\"data row1 col4\" >0.024420</td>\n",
       "      <td id=\"T_56ea6_row1_col5\" class=\"data row1 col5\" >0.015835</td>\n",
       "      <td id=\"T_56ea6_row1_col6\" class=\"data row1 col6\" >0.314665</td>\n",
       "      <td id=\"T_56ea6_row1_col7\" class=\"data row1 col7\" >0.137034</td>\n",
       "      <td id=\"T_56ea6_row1_col8\" class=\"data row1 col8\" >0.354404</td>\n",
       "      <td id=\"T_56ea6_row1_col9\" class=\"data row1 col9\" >0.106522</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_56ea6_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
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       "      <td id=\"T_56ea6_row2_col1\" class=\"data row2 col1\" >65.905469</td>\n",
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       "      <td id=\"T_56ea6_row2_col3\" class=\"data row2 col3\" >0.353421</td>\n",
       "      <td id=\"T_56ea6_row2_col4\" class=\"data row2 col4\" >0.029655</td>\n",
       "      <td id=\"T_56ea6_row2_col5\" class=\"data row2 col5\" >0.254077</td>\n",
       "      <td id=\"T_56ea6_row2_col6\" class=\"data row2 col6\" >0.220918</td>\n",
       "      <td id=\"T_56ea6_row2_col7\" class=\"data row2 col7\" >0.255773</td>\n",
       "      <td id=\"T_56ea6_row2_col8\" class=\"data row2 col8\" >0.166268</td>\n",
       "      <td id=\"T_56ea6_row2_col9\" class=\"data row2 col9\" >0.048092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_56ea6_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_56ea6_row3_col0\" class=\"data row3 col0\" >3.797297</td>\n",
       "      <td id=\"T_56ea6_row3_col1\" class=\"data row3 col1\" >53.915573</td>\n",
       "      <td id=\"T_56ea6_row3_col2\" class=\"data row3 col2\" >5330.246846</td>\n",
       "      <td id=\"T_56ea6_row3_col3\" class=\"data row3 col3\" >0.363334</td>\n",
       "      <td id=\"T_56ea6_row3_col4\" class=\"data row3 col4\" >0.651066</td>\n",
       "      <td id=\"T_56ea6_row3_col5\" class=\"data row3 col5\" >0.013765</td>\n",
       "      <td id=\"T_56ea6_row3_col6\" class=\"data row3 col6\" >0.060601</td>\n",
       "      <td id=\"T_56ea6_row3_col7\" class=\"data row3 col7\" >0.110871</td>\n",
       "      <td id=\"T_56ea6_row3_col8\" class=\"data row3 col8\" >0.094365</td>\n",
       "      <td id=\"T_56ea6_row3_col9\" class=\"data row3 col9\" >0.040825</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x2747576bfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 2일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   1\n",
      "1     ST-1002   1\n",
      "2     ST-1005   0\n",
      "3     ST-1006   0\n",
      "4     ST-1010   1\n",
      "...       ...  ..\n",
      "1838   ST-991   0\n",
      "1839   ST-992   1\n",
      "1840   ST-993   0\n",
      "1841   ST-994   1\n",
      "1842   ST-996   0\n",
      "\n",
      "[1843 rows x 2 columns]\n",
      "n_clusters = 3일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   2\n",
      "1     ST-1002   2\n",
      "2     ST-1005   0\n",
      "3     ST-1006   0\n",
      "4     ST-1010   1\n",
      "...       ...  ..\n",
      "1838   ST-991   0\n",
      "1839   ST-992   1\n",
      "1840   ST-993   0\n",
      "1841   ST-994   1\n",
      "1842   ST-996   0\n",
      "\n",
      "[1843 rows x 2 columns]\n",
      "n_clusters = 4일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   2\n",
      "1     ST-1002   2\n",
      "2     ST-1005   0\n",
      "3     ST-1006   0\n",
      "4     ST-1010   1\n",
      "...       ...  ..\n",
      "1838   ST-991   0\n",
      "1839   ST-992   1\n",
      "1840   ST-993   0\n",
      "1841   ST-994   1\n",
      "1842   ST-996   0\n",
      "\n",
      "[1843 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "# 변수 초기화\n",
    "cluster_results = {}\n",
    "\n",
    "# n_clusters 값을 2, 3, 4로 설정하여 K-means 군집분석 및 시각화\n",
    "for n_clusters in [2, 3, 4]:\n",
    "    # K-means 군집분석\n",
    "    kmeans = KMeans(n_clusters=n_clusters, random_state=42)\n",
    "    grouped['군집'] = kmeans.fit_predict(scaled_features)\n",
    "\n",
    "    # PCA 적용\n",
    "    pca = PCA(n_components=2)\n",
    "    pca_features = pca.fit_transform(scaled_features)\n",
    "\n",
    "    # PCA 결과를 데이터프레임에 추가\n",
    "    grouped['PCA1'] = pca_features[:, 0]\n",
    "    grouped['PCA2'] = pca_features[:, 1]\n",
    "\n",
    "    # 군집 시각화\n",
    "    plt.figure(figsize=(10, 7))\n",
    "    plt.scatter(grouped['PCA1'], grouped['PCA2'], c=grouped['군집'], cmap='viridis')\n",
    "    plt.xlabel('PCA1')\n",
    "    plt.ylabel('PCA2')\n",
    "    plt.title(f'대여소 군집 결과 (PCA, n_clusters={n_clusters})')\n",
    "    plt.colorbar(label='군집')\n",
    "    plt.show()\n",
    "    \n",
    "    # 각 군집의 평균 값 계산 (대여대여소ID 제외)\n",
    "    grouped_means = grouped.drop(columns=['대여대여소ID', 'PCA1', 'PCA2']).groupby('군집').mean()\n",
    "\n",
    "    # # 컬럼 별로 가장 높은 값을 가진 군집의 셀에 파란색 배경 추가\n",
    "    # def highlight_max(s):\n",
    "    #     is_max = s == s.max()\n",
    "    #     return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "    # styled_means = grouped_means.style.apply(highlight_max)\n",
    "    \n",
    "    # 컬럼 별로 가장 높은 값을 가진 군집의 셀에 연한 초록색 배경 추가\n",
    "    def highlight_max(s):\n",
    "        is_max = s == s.max()\n",
    "        return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "    # 컬럼 별로 가장 낮은 값을 가진 군집의 셀에 연한 노랑색 배경 추가\n",
    "    def highlight_min(s):\n",
    "        is_min = s == s.min()\n",
    "        return ['background-color: #fffff0' if v else '' for v in is_min]\n",
    "\n",
    "    styled_means = grouped_means.style.apply(highlight_max).apply(highlight_min)\n",
    "\n",
    "    \n",
    "    # 결과 출력\n",
    "    print(f\"n_clusters = {n_clusters}일 때 각 군집의 평균 값:\")\n",
    "    display(styled_means)\n",
    "    \n",
    "    # 각 대여소가 속한 군집 저장\n",
    "    cluster_results[f'cluster_{n_clusters}'] = grouped[['대여대여소ID', '군집']].copy()\n",
    "\n",
    "# 결과 데이터프레임 확인\n",
    "df_out_2 = cluster_results['cluster_2']\n",
    "df_out_3 = cluster_results['cluster_3']\n",
    "df_out_4 = cluster_results['cluster_4']\n",
    "\n",
    "print(\"n_clusters = 2일 때 각 대여소가 속한 군집:\")\n",
    "print(df_out_2)\n",
    "\n",
    "print(\"n_clusters = 3일 때 각 대여소가 속한 군집:\")\n",
    "print(df_out_3)\n",
    "\n",
    "print(\"n_clusters = 4일 때 각 대여소가 속한 군집:\")\n",
    "print(df_out_4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\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>대여소_ID</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-999</td>\n",
       "      <td>37.5334</td>\n",
       "      <td>126.8765</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   대여소_ID       위도        경도    구\n",
       "0  ST-999  37.5334  126.8765  양천구"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ll_join = pd.read_csv('./서울시 따릉이대여소 마스터 정보(전처리).csv')\n",
    "ll_join.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>대여소ID</th>\n",
       "      <th>군집</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-10</td>\n",
       "      <td>1</td>\n",
       "      <td>37.55275</td>\n",
       "      <td>126.91862</td>\n",
       "      <td>마포구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ST-1002</td>\n",
       "      <td>1</td>\n",
       "      <td>37.52990</td>\n",
       "      <td>126.87654</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ST-1005</td>\n",
       "      <td>0</td>\n",
       "      <td>37.51395</td>\n",
       "      <td>126.85606</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ST-1006</td>\n",
       "      <td>0</td>\n",
       "      <td>37.53638</td>\n",
       "      <td>126.87151</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ST-1010</td>\n",
       "      <td>1</td>\n",
       "      <td>37.53620</td>\n",
       "      <td>126.82780</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     대여소ID  군집        위도         경도    구\n",
       "0    ST-10   1  37.55275  126.91862  마포구\n",
       "1  ST-1002   1  37.52990  126.87654  양천구\n",
       "2  ST-1005   0  37.51395  126.85606  양천구\n",
       "3  ST-1006   0  37.53638  126.87151  양천구\n",
       "4  ST-1010   1  37.53620  126.82780  양천구"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out_k_2 = pd.merge(df_out_2, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')\n",
    "out_k_2 = out_k_2.drop(columns=['대여소_ID'])\n",
    "out_k_2.columns = ['대여소ID', '군집', '위도', '경도', '구']\n",
    "out_k_2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "out_k_2.to_csv('./(군집_외국인_k=2) 서울시 따릉이 대여소 별 군집결과_마스터 조인.csv', index=False)"
   ]
  }
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