{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "hide_input": false
   },
   "outputs": [],
   "source": [
    "from preamble import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 모델 평가와 성능 향상"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "사이킷런 0.22 버전에서 `LogisticRegression` 클래스의 `solver` 매개변수 기본값이 `liblinear`에서 `lbfgs`로 변경될 예정입니다. 사이킷런 0.20 버전에서 `solver` 매개변수를 지정하지 않는 경우 이에 대한 경고 메세지가 출력됩니다.\n",
    "\n",
    "사이킷런 0.20 버전에서 `LogisticRegression`의 `multi_class` 매개변수 옵션에 `auto`가 추가되었습니다. `auto`로 설정하면 이진 분류이거나 `solver`가 `liblinear`일 경우에는 `ovr`을 선택하고 그 외에는 `multinomial`을 선택합니다. 사이킷런 0.22 버전부터는 `multi_class` 매개변수의 기본값이 `ovr`에서 `auto`로 변경됩니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "테스트 세트 점수: 0.88\n"
     ]
    }
   ],
   "source": [
    "from sklearn.datasets import make_blobs\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# 인위적인 데이터셋을 만듭니다\n",
    "X, y = make_blobs(random_state=0)\n",
    "# 데이터와 타깃 레이블을 훈련 세트와 테스트 세트로 나눕니다\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n",
    "# 모델 객체를 만들고 훈련 세트로 학습시킵니다\n",
    "logreg = LogisticRegression().fit(X_train, y_train)\n",
    "# 모델을 테스트 세트로 평가합니다\n",
    "print(\"테스트 세트 점수: {:.2f}\".format(logreg.score(X_test, y_test)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 교차 검증(Cross Validation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "hide_input": false
   },
   "outputs": [
    {
     "data": {
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t2UmemuTYLuu4KsmFSS7e9r1/lOSzW2uP6r3/yXJXOa1R3iDrqEVHLTpq0VHLKB2bm5tTL2EhRjkeOmrRUYuOWnTUMkrHbtbtF/5HGVzQUYuOWnTUoqOWUTpGOb/SUYuOWnTUoqMWHbXoqEVHLTpq0VGLDoDxPOlJT8qFF1641Nc4derUjv/B1ePHj+eyyy5b6msv0m4dLE9r7aLceojqb6ZaC3szuxLkr+XWA3wfTPILSf40yQVJHpbkEXPfvzzJ9VneBb84oMpDfL+QrSG+luRhrbULeu/vP9eTeu+9tfbCJN862/TM1tqbe+8/ffNjWmvfkK0hvpsvW/mzq7qEJUvzLbllgO+mJP8jyS8lefn8JWhba5ck+YpsXUb03rPNH5nkl1trn9J7f9/KVrxCo7xB1lGLjlp01KKjlpE6NjY2pl7GoY10PHTUoaMWHbXoqGWUjt2s2y/8jzK4oKMWHbXoqEVHLaN0jHJ+paMWHbXoqEVHLTpq0VGLjlp01KKjFh0AY7rwwgtz0UUXnfuBB3TllVfuOPi2bp/v7taxJk5n6yJD5/LOZS/kAD5l2/0/XeFrPzfJDy1wf0flKoLfk+Sz5u7/nyRf0Xt/2/yDWmufl+QlueVKi9/cWvul3vuvL3FtL0zyw/t8zl7+tzOsskN8vfc/bq29NVuXHr1tks9P8qt7fPqzkvw/SW6T5Lwk/6m19swkr0/ygCSfkK3hwGTrKm3PWeDS183fJnnIkvb9liXt92z+e5Lv7b2/cadv9t5PJ/mJ2aDnS5N8zuxb90nyL5P8wEpWuUKjvEHWUYuOWnTUoqOW0TvWzejHQ8c0dNSioxYdtYzSsZt1/IHQCIMLOmrRUYuOWnTUMkrHKOdXOmrRUYuOWnTUoqMWHbXoqEVHLTpq0QHAQYzy+e5uHWtks/e+MfUiDuhztt3/yxW+9nXzF2gq7oK9PKj3fsMyF9Fau1+S+ZOqtyT5vN77u3dYyytba1+Y5Pdyy6zYc1tr9++9f3hJS3xn7/21S9r3kMoO8c28MskTZre/IHsc4uu9v7219p1JrsjW1fZakvvl1sN7N1957zsK/kXwiCSvOcTz75rkzXt5YO/9A0ledbbHzC6/efckd8rWUOR7klzde7/2EGtctPcm+abe+wv28uDe+3tba/80W/+czptt/toMNsQ3yhtkHbXoqEVHLTpqGb1j3Yx+PHRMQ0ctOmrRUcsoHbsZ5QdCOqahoxYdteioRUcto5xf6ahFRy06atFRi45adNSioxYdteioRQcABzHK57u7dRw/fnydr8y3Th677f43t9Z+uvfed3z0EbXs4bx9OJGti5vd7Jt3GuC7We/91a21f5vk5pO0j0vyRUl+eWkrZF+OTfjae/kf+W/N3f6Mfe2893+T5D9ma2ivz73ezX+2JM/tvf+7/ex3Rd7Xe7/2oF/ZGrI7lNbaw1prz2utvSHJ+7I1Yf2aJP87yV8keVdr7W2ttf/eWvvK1tp5Z9ndTs5vrd19h6+7HXDJn7TXAb6b9d7fmuTVc5vu11q77QFfv5xR3iDrqEVHLTpq0VHL6B3rZvTjoWMaOmrRUYuOWkbp2M3x48eH+IHQKD/Y0jENHbXoqEVHLaN0jHJ+paMWHbXoqEVHLTpq0VGLjlp01KKjFh21bG5uTr0EgD0Z5fPds3VcdtllE6zoaGmtPTBnXonvsiT/fILlcA6z2Zavm9v0J733l+3hqf8myYfm7j9htweyelMN8X0gyQdnX2cb5vvt2Z8tyafu90V679+S5BuydbW1Nvf1uiSP770/eb/7HF1r7Z6ttVck+d1sTe3eP7v/e3KvJF+d5OeT/GlrbT9nAJ+Y5G93+Pqtsz1pN4e4KuBb5263JAcdIixllDfIOmrRUYuOWnTUMnrHuhn9eOiYho5adNSio5ZROs5mnX6QchR+sKVj9XTUoqMWHbWM0jHK+ZWOWnTUoqMWHbXoqEVHLTpq0VGLjlp01HLFFVdkY2Nj6mUAnNMon++O0rHmdpufeU5r7d4rXQl78ZDcer7lRXt5Uu/9b5L8ztymRx/gol0sySRDfL33u/feL5h9vf8sj3tLkmtnd+/QWvv4A7zWT/fe75fkY5M8OMm9e++f2nv/7wdY+tBaa/fI1pXpHjm3+V1J/luSZ2RrAvfyJP8iyb/P1tX5bvZJSV7ZWvu81ax2Ye647f6ulxZdFyO9QdZRh45adNSio5bRO9btw+PRj4eOaeioRUctOmoZpWMUo/xASEctOmrRUYuOWkbpGOX8SkctOmrRUYuOWnTUoqMWHbXoqEVHLTpqGeU/rAyMb5TPd0fpWGezq/DNX9XtL5NcM7t9lyQ/a9CrnO3/VeUz/0e0u1fM3b4gyScffjkswlRX4tuPP539eTrJ+QfdSe/9rb33V/fe/3oxy1qq81pr5x/0K8lB//J8bpKPmrv/rCT37L1/be/9Ob335/fef7b3/uO99xNJPj5bf5HfPIh5uyTPn62hvNba9is8vq73fv1U61mE0d8g65iGjlp01KKjlqPQceLEiQlWdDBH4XjoWD0dteioRUcto3SMYpQfCOmoRUctOmrRUcsoHaOcX+moRUctOmrRUYuOWnTUoqMWHbXoqEVHLQb4gHUxyue7o3Sss9babZP8TJLbzG1+apJ/OXf/c5P8myUv5Zmttb7Ar7sseb1Te9Dc7Z7ktft47p9su/8Zh18Oi7AOw1avydYg37/qva/9VdL26FWrfsHW2p2SPHZu06/03r/jbM/pvfckL5hdwe9Zs833ytZf4K88x0v+eW59xb+bfWhvK16Ir0oyf9nXn1nhay/c6G+QdUxDRy06atFRy1HpOH369ASr2r+jcjzWhY5adNSioxYdLMMoPxDSUYuOWnTUoqOWUTpGOb/SUYuOWnTUoqMWHbXoqEVHLTpq0VGLjloM8AHrYpTPd0fpGMCPJvm0ufsv7b3/UpK01h6XW+ZIvq219qbe+79b9QLZ0T3mbv917/2GfTz3z7fd/6gdHzWx1tq3J7nvDt+6/arXsirrMMT39N77boNdfaUrGdslufWVGU/t47nbH7uX/4F/eMqrIrbWPj/JT85tenOS5y1o35dm65/nyoz+BlnHNHTUoqMWHbXoqEVHLTpq0VGLjlp0sAyj/EBIRy06atFRi45aRukY5fxKRy06atFRi45adNSioxYdteioRUctOmoxwAesi1E+3x2lYxe338NV4N7be7+xtfa8JJ+47XsXL2dZZ2qtPTvJk+Y2/V2Sfz53/+uT/J8kHzu7/29bazf13p+7hOV8IMl+BtHOZZJ5otbaU5I8+CwP2X68D+rOc7ffuc/nvuss+1qkL22tffw+Hv/S3vuPz93/yiSfteA1lVZ+iO8sA3xJ0mKQb1Henq2/EG+eWP3i1toP995v3MNzH7vt/psWurIFaa19ZJKHJfm6JF+WW4YWr0ryZb336xb0UieSfO+C9nVOo79B1jENHbXoqEVHLTpq0VGLjlp01KKjFh0swyg/ENJRi45adNSio5ZROkY5v9JRi45adNSioxYdteioRUctOmrRUYuOWnbr2NjYyMbGxuoXBLCLUT7fHaXjLJ45+zqbz0nyu9kaUPqMpa9om9babZNckeRb5zbfkORxvferbt7Qe7+2tfZlSX4nW4NeLcmPt9buluT7e++LnNf5t73371jg/qby2Un+0QpeZ37w7n37fO57t92/y+GWsqt7z7726i1LWsfaKD/Edxa/nVsG+D4w5UIOq/f+g0l+cOI13NBae0GSb5ht+qwkL2mtfWvv/W92ek5r7YJs/Z/Pk+c2v7b3/gfLXe3etdZ+IskXJvmIJBdt+3ZP8gtJ/sVujdWN/gZZxzR01KKjFh216KhFRy06atFRi45adLAMo/xASEctOmrRUYuOWkbpGOX8SkctOmrRUYuOWnTUoqMWHbXoqEVHLTpqOVvH5ZdfbogPKGOUz3dH6VhnrbVPSPLC3Hp48MNJHt97/93tj++9/+lskO/Xc8tFoTaSPLC19oTe+7uXvGR2dtPc7WO7Pmpn2x+/l4t7TeEF2Rp23e6CbF1cazhrO8TXez8+9RoG9PRsXdbzk2f3vyLJY1trp5K8Icm12fof7x2T3DfJQ5LcYe7578zWVe4q+egk99xh+5uSPLn3/j9XvJ6FOQpvkHWsno5adNSioxYdteioRUctOmrRUYsOlmGUHwjpqEVHLTpq0VHLKB2bm5s7/vLcup1fjXKeqKMWHbXoqEVHLTpq0VGLjlp01KKjlqPScfr06QlWBXCmUT7fHaVjD27M1lDc2dw8gPVN2Zq/mPeSJBcvelGttTsmeVq25kLmL4D0/iRf1Xt/6W7P7b3/Vmvti5L8cm6ZEfmKJJ/VWntS7/1/LHq9a+zFSV57lu//8yT3WsDrzA9Pbr+g1bncYdv9ZQ1iviLJz+zj8W+cv9N7//GdHtRauziG+Bjd7FKoD83WZVOfkOS82deDZ19n84okJ3rvb1ruKhfm45O8tLX2O0meseCrB25m6/9YD+Jsf5n/vaPyBnld6KhFRy06atFRi45adNSioxYdteioZZSOUYzyAyEdteioRUctOmoZpSOJAb5CdNSioxYdteioRUctOmrRUYuOWnTUogNgtUb5fHeUjj36wd77xl4e2Hv/39u3tdY+sMjFtNbunK3Bse9Mcsm2b781WwN8p861n977/2qtPSLJ/0hyj9nmj07yi62130zyPb33Kxe28DXVe3/x2b7fWntkFjPEd+3c7e3H9Vy2P35ZQ3xv7L3/1yXte0iG+FaotXanJHeaeh1zbui9Xz2/off+niTf2Fr7gSRfneTzknxqko/KrS+p+c4kr0tyZZIX9d7/aDVL3p/e+5e01o4luXO2/g/kQUn+SZJHJWlJPifJ77XWntJ7f+6CXvOqJFcd5LmttXM+ZpQ3ljpq0VGLjlp01KKjFh216KhFRy06atFRy+bm5tRLWIhRfiCkoxYdteioRUcto3TsZt3Or0Y5T9RRi45adNSioxYdteioRUctOmrRUYsOgNUa5fPdUTrWTWvtY7M1uPf47Hyltpck+abe+7v2us/e+x+21j4jyYuSPHzuW5+f5PNba7+b5KeSvLj3fv2BF89evHXu9ke11u7Qe3/fHp97/23337agNXFIhvhW66lJvnfqRcx5WZLH7PSN3vvbkjx79pW2NV12UbauzPfe3vtNOz3vHJ6f5OTs9oGG3A5ittZ3zb5el+S/tNY+J8kLszUhfl6SH2+tvaP3/nOrWtdBjPLGUkctOmrRUYuOWnTUoqMWHbXoqEVHLTpqueKKK3a80s26GeUHQjpq0VGLjlp01DJKx27W8fxqlPNEHXXoqEVHLTpq0VGLjlp01KKjFh216ABYrVE+3x2lY01dm62LGm0f4Pu/SZ7ce/+Vg+y09/53syvyfVuSH962/89Ocvckv5Jkv0N857XWbn+QNZ3FBw8427IO/jDJ5XP3Pz3J7+7xuf9gh31RwMqH+Fpr917Cbq/tvb9nNmh2oMtOzobW2EXvvSfZ69Tubvt4/mJWc3i9999prT06yauTXDjb/OOttV/qvX9owqXtapQ3ljpq0VGLjlp01KKjFh216KhFRy06atFRy24d62aUHwjpqEVHLTpq0VHLKB27GeX8Ssc0dNSioxYdteioRUctOmrRUYuOWnTUMkoHML5RPt8dpWNd9d7f1Vr74iR/kOTiJH+V5FlJfuKwMxGz+ZF/11p7cZLvTvLEJLdN8s4kX9x7v+YAu3367GuRvjTJry54n1W8etv9x2TvQ3yPnrv9niR/sZAVcWhTXInvLUn6gvf5Q0m+J8ldD7j/HlclPHJ6769rrT03ybfPNt09yRcn+R+TLWoXo7yx1FGLjlp01KKjFh216KhFRy06atFRi45aDPDVoqMWHbXoqEVHLaN07GaU8ysd09BRi45adNSioxYdteioRUctOmrRUcsoHcD4Rvl8d5SOddd7/8vZIN89kvxy7/3GBe//HUme1Fr7viTfmOR3eu9vXORrsKtTSd6erWObJI9vrX3vuY5xa+1+ST5zbtMvz4YyKeDYhK/dFvS1qH0vXe99o/feDvOV5Du37fYRh9jfY8623tbaydZaX9LXa5f3T3pf/tu2+589ySrOYpQ3ljpq0VGLjlp01KKjFh216KhFRy06atFRiwG+WnTUoqMWHbXoqGWUjt1sbGwMcX41ynmijmnoqEVHLTpq0VGLjlp01KKjFh216ABYrVE+3x2lYxS991f33n9x0QN8217jqt77D/Xef3tZr8Gt9d5vSvJf5jZ9bJKv2cNTvzO3npH66UWui8OZ6upzex2am5/2PNvA3m7PO9fr9H2shTH9SZIPZuvSrsnWX2xljPLGUkctOmrRUYuOWnTUoqMWHbXoqEVHLTpqMcBXi45adNSioxYdtYzScTYnTpyYegl7Nvp5oo5p6KhFRy06atFRi45adNSioxYdtegAWK1RPt8dpWOVWmu3T3Ln3vvfTb2WVeq9vy8Dz+u01o4l+fgkn5Hkwt77Ty3hZf59kicnuWh2/9+11n6n9/62Xdb02CT/bG7Ta5L8ryWs61Baay3JvZN8apIHzb6e0nt/06QLW4EphviescfHfVySb57dfk+SHzjLY39/l+3fm+T6Xb535yTftce1HFU3zr4W5ViK/SXce++ttWuSfNRs052mXM+8Ud5Y6qhFRy06atFRi45adNSioxYdteioRUctu3VsbGxkY2Nj9Qs6oFF+IKSjFh216KhFRy2jdIxi9PNEHdPQUYuOWnTUoqMWHbXoqEVHLTpq0QGwWqN8vjtKx7K01u6U5D7ZGk76pGwNKH16kgckuSLJd0y2OPaltfbg2c3bJ7lg9nVpto7tfZLcL1vH9cLZ434zycKH+Hrvf91a+/4kz5ptumuS322tfVXv/Q/m1nssW8N7m/NPT3Ki9z5/cbVF+7jW2uN22H5ektvNvi5MckmSj8zWP8P7Zmv48fbbnnMk/vex8iG+3vsVe3lca+3huWWI7/q9Pu/mp2frX7jn9d7fucv+7xFDfGfVe//8Re6vtfarSb54kftckIvmbr97slXM2dzc3PEX6NbtjeUob5B11KKjFh216KhFRy06atFRi45adNRyFDouv/zytRniG+UHQjpq0VGLjlp01DJKxyiOwnmijtXTUYuOWnTUoqMWHbXoqEVHLTpq0QGwWqN8vjtKx4J8a2vta7J1kaObh7wuzC0DXay/3S40NoUfTfLwJF80u3+vJK9qrf1ekj/O1r9/D8vWYOG8jd77sjseM/tij6a4Eh/btNa+K8mXz+5e33v/3AmXc6S01u6VW199761TrWWeAb46dNSioxYdteioRUctOmrRUYuOWnTUclQ6Tp8+PcGq9m+UHwjpqEVHLTpq0VHLKB2jOCrnietCRy06atFRi45adNSioxYdteioRUcto3QA4xvl891ROhbobrOvvepJrlnSWpjWO5K8KsmLlvUCvfcPt9b+UZJfSPKFc9962OxrJz/Se//+Za1pQa7K1hDiq2ZffzHtclbDEF8NH5PkM2a3r5twHWuptfYvk2z23j9wgKd/7bb7r1zAkhZu3d5YjvIGWUctOmrRUYuOWnTUoqMWHbXoqEVHLTpqGeUHQjpq0VGLjlp01DJKxyhGOb/SUYuOWnTUoqMWHbXoqEVHLTpq0VGLDoDVGuXz3VE6VuiaJG9J8oYkr8vWkNIf9N7fOeWiOKd3Jnn7tm0fSvL+JNcneXeSv5095m3ZOr5/2ntfyX85ufd+Q2vti5N8c5LvT3LxLg99Q5Jv673/5hKXc65935Tkg0k+MPvzPUlOZ2to7++S/GWSN/be373ENZZliI9dtdZOZuuym9U9OcnXtNb+Se/9L/f6pNbavZM8c27TO3Luv1BWbt3eWI7yBllHLTpq0VGLjlp01KKjFh216KhFRy06ahnlB0I6atFRi45adNQySscoRjm/0lGLjlp01KKjFh216KhFRy06atFRiw6A1bn++utz6tSpnDx58ozvHT9+PA984ANz3XXrcd2fVXZcf/31C9vXEvxVki/dYfuHsnURp+uzNQT2twe8MNG+tNZuv+zX2IcP9d5vnHoRh9V7f2qSp069jrPpvfck/7619pNJHp3kM5PcM1uDcm9L8hu991MrWMcjl/0aIzPExyg+M8kft9Z+IMm/673fcLYHt9buk+SlSe4yt/lHzvW8VVu3N5ajvEHWUYuOWnTUoqMWHbXoqEVHLTpq0VGLjlpGGVzQUYuOWnTUoqOWUTpGMcr5lY5adNSioxYdtYzSsbm5mY2NjTO2r1vHKMdDRy06atFRi45aRukAxve85z1v1++dPHlyx6G4dTNKx1713q9L8qtTr2PO+6dewJwnJHl+a+0tSe4z8Vpu9n29942pF7EsvfcPZ2sW5qVTr4X9W4chvj71Aor59STXzt1/44pe94Ykb13g/vZ8xbw9+ODszzskeVaSp7fWXpStf1a/O3+Zzdnw3tcleXpuPcD30iTPXeCaDm3d3liO8gZZRy06atFRi45adNSioxYdteioRUctOmoZZXBBRy06atFRi45aRukYxSjnVzpq0VGLjlp01DJKRxIDfIXoqEVHLTpq0VHLKB0AABxtkwzxtdY+OcmnJ3lzkj/uvZ9tEritZFFrovf+miSvmeCl/7j3/uAJXncvvjTJi5I8cHb/kiTfOvtKa+39Sa7O1pDfR+zw/Jcm+Se995uWv9S92djYWKs3lqO8QdZRi45adNSioxYdteioRUctOmrRUYuOWkYZXNBRi45adNSio5ZROk6dOjX1EhZilPMrHbXoqEVHLTpqGaVjN+vWMcrx0FGLjlp01KKjllE6AABgqivxPSjJf57dvqm19upsXV70v/be/2q2/feT3Gt2+8YVr4810nv/89baZyX5hiTfluT+2x5yQW75d2ne1Ul+OMmPVRrgS5ITJ05MvYQ9G+UNso5adNSioxYdteioRUctOmrRUYuOWnTUMsrggo5adNSioxYdtYzUcfLkyamXcWijnF/pqEVHLTpq0VHLKB27WbeOUY6Hjlp01KKjFh21jNIBAAt2x6kXMOeG2Z+fluTYlAuZc8O5HwLTmGqI78O55Qp75yV58OzrB1prP5fke3rvb0zy9onWN6XWWts+hLYQvfc/W8Z+K+i9fyDJZmvt32fr36WHJ/nsJB+f5G5J7pLkPUlOJ/njJL+W5Od77++dZMGDGOUNso5adNSioxYdteioRUctOmrRUYuOWnTUMtLggo46dNSioxYdtYzesW5GOb/SUYuOWnTUoqOWUTp2s24doxwPHbXoqEVHLTpqGaUDGN41SS6dehEDu2bqBVTUe3/f1GvYrvf+nqnXAOtgqiG+m6+s17dtP5bkq5J8ZWvtZ5N8e+/9qP3Fe2GSNyxp3+3cD9nVZ7XWPrywlWx5Ue/9axe5w957z9ZVHH9/kfvlTKO8QdZRi45adNSioxYdteioRUctOmrRUYuOWkYfXNAxDR216KhFRy2jd6ybUc6vdNSioxYdteioZZSO3axbxyjHQ0ctOmrRUYuOWkbpAMbXe78pWxeZAYBzmupylTfO3X5Pkg/k1gNm5yf5Z0le01r77BWui7M7bwlfrKFR3iDrqEVHLTpq0VGLjlp01KKjFh216KhFRy2jDy7omIaOWnTUoqOW0TvWzSjnVzpq0VGLjlp01DJKx242NjbWqmOU46GjFh216KhFRy2jdAAAwHZTDfHNX9HtZJK7JvmiJC/IrQf87pHkla21b1/d0oCzGeUNso5adNSioxYdteioRUctOmrRUYuOWnTUMvrggo5p6KhFRy06ahm9Y92Mcn6loxYdteioRUcto3SczYkTJ6Zewp6Ncjx01KKjFh216KhllA4AANjJ+RO97k1zt2/Te78hya8n+fXW2ncn+YEkX5ukZ2uNP9Jau7D3vrHyla5A7/2JSZ449Tq2670fn3oN1DLKG2QdteioRUctOmr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      "text/plain": [
       "<Figure size 3600x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mglearn.plots.plot_cross_validation()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### scikit-learn의 교차 검증"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "사이킷런 0.22 버전에서 `cross_val_score` 함수의 `cv` 매개변수 기본값이 3에서 5로 바뀔 예정입니다. 0.20 버전에서 `cv` 매개변수를 지정하지 않는 경우 이에 관한 경고 메세지가 출력됩니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차 검증 점수: [0.967 1.    0.933 0.967 1.   ]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "iris = load_iris()\n",
    "logreg = LogisticRegression(max_iter=1000)\n",
    "\n",
    "scores = cross_val_score(logreg, iris.data, iris.target)\n",
    "print(\"교차 검증 점수:\", scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차 검증 점수: [1.    0.933 1.    1.    0.933 0.933 0.933 1.    1.    1.   ]\n"
     ]
    }
   ],
   "source": [
    "scores = cross_val_score(logreg, iris.data, iris.target, cv=10)\n",
    "print(\"교차 검증 점수:\", scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차 검증 평균 점수: 0.97\n"
     ]
    }
   ],
   "source": [
    "print(\"교차 검증 평균 점수: {:.2f}\".format(scores.mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'fit_time': array([0.015, 0.026, 0.016, 0.017, 0.016]),\n",
       " 'score_time': array([0., 0., 0., 0., 0.]),\n",
       " 'test_score': array([0.967, 1.   , 0.933, 0.967, 1.   ]),\n",
       " 'train_score': array([0.967, 0.967, 0.983, 0.983, 0.975])}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_validate\n",
    "res = cross_validate(logreg, iris.data, iris.target,\n",
    "                     return_train_score=True)\n",
    "display(res)"
   ]
  },
  {
   "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>fit_time</th>\n",
       "      <th>score_time</th>\n",
       "      <th>test_score</th>\n",
       "      <th>train_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.01</td>\n",
       "      <td>2.28e-04</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.03</td>\n",
       "      <td>2.29e-04</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.02</td>\n",
       "      <td>2.15e-04</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.02</td>\n",
       "      <td>1.89e-04</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.02</td>\n",
       "      <td>2.00e-04</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.97</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fit_time  score_time  test_score  train_score\n",
       "0      0.01    2.28e-04        0.97         0.97\n",
       "1      0.03    2.29e-04        1.00         0.97\n",
       "2      0.02    2.15e-04        0.93         0.98\n",
       "3      0.02    1.89e-04        0.97         0.98\n",
       "4      0.02    2.00e-04        1.00         0.97"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "평균 시간과 점수:\n",
      " fit_time       1.78e-02\n",
      "score_time     2.12e-04\n",
      "test_score     9.73e-01\n",
      "train_score    9.75e-01\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "res_df = pd.DataFrame(res)\n",
    "display(res_df)\n",
    "print(\"평균 시간과 점수:\\n\", res_df.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 교차 검증의 장점"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 계층별(Stratified) k-겹 교차 검증과 그외 전략들"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iris 레이블:\n",
      " [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.datasets import load_iris\n",
    "iris = load_iris()\n",
    "print(\"Iris 레이블:\\n\", iris.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "hide_input": false
   },
   "outputs": [
    {
     "data": {
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s2y0WHn8ws8GpHRljjKr65yT33nR4cZc1puvBSc5ZOPaI7ey2M8Z4W1X9WJJf3HT4DlV13hhjmTvbHVjzHYHuu3D4p071/PkQ5E8ledymww/OBIf1MvuzwC0Xjv3WGGO/f2/e6tfqdyR56BLf4zu2OPZ3Z3jNm3Pir4NVets+vc8qferC479fyyo+5LfGGA9a1smq6gFJfmdZ52vqmguPt7v79Scnuc9yl5JXLvl8a1NVZyf5roXDTxtjvHwd6zmT+Xrvm9maP+kUT7sys7+g4vX7tS4AAAAAANbPsB4AAAAAh0JVnZfkKfnQDkDHvTnJvcYYr0vyuqq6R5Jn5MTdlz4zyUur6keTPGaM8f59WPJHLzx+zT68J6zK9Rcev2s7A1an8M6Fx9fa5Xk4eO6/8Pi5Y4x/2cHrfyPJD+fEX4/3zdYDUIfRJ+fE3/suS/LsM7zmD5P8Qma7PCXJbavqI9cwxLYyVXWnJN+7cPjdmf1a2vy8+yf5ldOcanF30d14VpK3JLnJpmMPqarXJ/nJPXxfTfK/u34tDsq8MWf4dTDGeE2WOzA4WfMdQj9+4fDfrmMt7E5VnZsTd58cSd66puUkycvW+N7L9vCcOBg9svC9toOqun2Sr0/ygMx2Iz2dI0kek+R7qurnk/zKGGOdv14AAAAAANgHR878FAAAAAA4uKrqRlX1S0lekJMH9V6b5G5jjJccPzDG+Ockd07yTwvPvUaSH0vy71V1QVUt46b70/nYhceT2TWDQ+nShcfXqaqztnzmmd1g4fF7d3keDpCqumFO3rXmD3dyjjHG/yT584XD99zLupbgKVU1lvWR5Nv3sJbPWXj8t2OM953uBWOMtyT554XDd9vDGlqZD1Y9OclVFj71XWOM/1o4dpUk557mY89/geb8Lwv4zi0+9egkz6+q+1TVjn72V1VHqurzq+r/JXlsZrsKb/YdY4wP7G7Fp33fs6pqcafMw+BLcuKvhcuSPH89S2GXrr3w+O1jjA8u6dwjs53Yrkzygcz+jPP2zP5ykddmNjy76CVbHDtwqupTkvzIwuEnjDH+cf75j6mqO5zuI8mHr3B9n1hVP1BV/5TZ7tAPz9aDeseSPCInf61umNng4eur6k+q6kuqavH3FgAAAAAAJsLOegAAAABMUlXdIMn/SfLIJNfZ4inHktx3q50Nxhivq6pPT/ITSR6WE29cv3mSxyV5VFX9ZpJfG2P8+3JXnyT5lIXHL17Bexwa84GLH1zx2yzuHseHLO6ydVaST0vy9zs5yXzA7w4Lh1+9h3VxcNxxi2PP2sV5npnZTjjH3b6qrj7GuHx3y5qU2y883u7vOy/K7L/n4+6c5HeXsaB1mn+/+d0kH7Hwqb8cY5xuB72VGmM8sapuk5N/T/uMJE9P8raq+svMvi7/ltlOfJcluTzJ1TMbHLxJkltntpviZ+fUv39tjDGevNc1z38P/qr5Gu+U5MMy3xW1qj6Y5B2Z/aUEFyV55hjj2F7fs7GvXHh87ExDsbRz3YXHb9nuC8cYD0ryoN2+cVU9IslPbzr0viR/s9vzdVFV10vye0muuunwW5J896bHP5vkPvu4po/MbPj8rkk+Nyfu+LdoJHlakkePMV44f/2vZDZc/R058Vr0Kkm+eP7xjqp6Vmbfu581xnj7kjMAAAAAAFgTw3oAAAAATMZ8N5m7Zjak9xVJttr97ookP5nkUafbBWO+e83Dq+qPk/xKktsuPOXGmQ0CPrKq/iHJnyZ5TpIX7fWm66q6XWY30m/2qr2ck1w7e9txir15fma7w5y76djXZofDekm+MCcPlWxU1fef4XWr2L3pvlW17Rv0T+ONY4w/W8J5pm5xWO/tY4z/2MV5/nHh8VUyG1h64W4WNTG3WXj8im2+7qULjz96CWtZq/mfJ34ryb23+PRZVXWVLXabe3OS553mtB+Xk39v35UxxqOq6mVJfjGz3Zo2u0GS+84/dusdSb51jPHEPZzj+ADOjyf5usx2KN7K2UluNP+4a5Lvnrc9aozx1L28fzfzocXPWji852FI9t3NFh4v488C2/W5C4+fO8Y40DsMV9V1M7uG+rhNh0eSB48xFndmXtUabpfkEzIbWr99ZgPot9jGSy9N8gdJfnmMccLvhWOM9yT5oar6uSTfkuShOXnnv+sl+er5xxVV9a+ZDS2/ILPB8P38tQUAAAAAwBIZ1gMAAADgQKuqq2Q2nPdZSe6Rk3e72OxFSb5hjLE4rHFKY4znV9UnJ7kgyfdmNqS36A7zjx9J8v6qutsYY6dDSJvdY4tj5yf521O9oKq+MCcOQp3KzXe5Jti1Mcb/VNXTktxv0+H/U1WPH2P8y3bOUVXXzmzQdtHVsvVg7qptLOk8z0tiWO/MFgemX7nL8/x7kg9kNqS3+dz7Max3aZLv2of32ezdO3juxyw8fvM2X/eGhccfuYP3bKeqKsmvJrn/KZ5yjyS/W1X33zz0P8Z4Vk6z22NVPSGzobWlGGM8qaqemeSPcvIA2F78RZKvHmO8Yy8nqaq7JHlqkpvu4uW3S/KUqvr9JA+a/wUKO3GtqrrrKT535Rjjol2saRm+KSd+77k8yR+vaS2b3bOq/mSJ55v6nzUXB672ZaCqqm6Sk68RnrYf770q853Qn5UTd2dNkh8eYzxjH5fyQ5n9RS/b8b4kz0jy20n+fIvB7ROMMd6Z5NFV9ZjMhqi/PSfvEp3Mdp3+lPnHgzP7iwQM6wEAAAAAHFCG9QAAAAA40MYYH6iqOyf50tM87b+S/GCS3x5jXLmL93h/kp+tqscn+eYk35rkI07x9D/Y46BesvWw3oOr6sfHGOMUr/mFHPABCSbvUUm+PB8aVLhqkj+rqs8bY7z8dC+c7870hzl55y/WqKo+NrPdDhdtZzeanbrewuPX7OYkY4wPVtXrk3zUpsPX3eWadvre70zymP14r52aD6gt7lp5yTZf/qaFx7esqkcsHDsQP4+qqqsn+Y3Mdjk6na9KcnZVPWCM8T+rX9nWxhjvqqpX58RhvXdl9rX7yJz+3/uVSd6Y2U58m3e9e8kSBvU+NckzM9vVdvE9/27+8dbMhtWuk9n39rvn5CGor05y9ar68tP8+Wcrt8tsR9etvC/J1XdwrqWoqmskedjC4aeMMd6132vZwi2ymu/bU7WWYb3Mhj3P2vT48swGYg+k+UDvk3LycOcTMxueW/RHOfOOr3dJ8um7WM63JfmczL4fbeXVme3+95wkf7Wb/27nQ32/m9mw9+0yGwj/6pz455HjNsYYu/1LCQAAAAAAaOBA/HAUAAAAAM7goZnd5L14o/E/JvnZJE86064H2zHGeE+Sx1TVY5N8UWY3Wd4nH7rp+42Z7Zawa1V11Ww9rPdRSb4gB3wHjTO4Y1VtbHF8q90Ml+ETxhgvWdG5D4NfqqpfOs3n7zHGOHb8wRjjVVX16MwGZ4/7iCR/X1U/meToGOPtm09QVVfLbBeSH8nJA7IvSLLd3ZEuyInDKIdeVf1sZru2nMl1T/O5T0ny00tYznYs3kC/kx3jFr1n4fF193CuqTgnSS0cW/z3dCqLQwvXyP79ulia+a5Vf5rkTguf+mCSByT57CTfsOn4lyX5f1X1xWOMN+7PKrfln8cY51fV2UluluRamX19r5bk/Ukuy+y/nzfM/8KDf8jJu1rt2vx9n5CTB/WemOT7xxivOcXrzkryJUkemxP/PPelSR6U5DeXtcY1eXBO/vPML65jIezZ4rDe61b9hlV1bpKHLBz+vTHGdoeqF31iVX3DaT7/vDHGv+3y3Kc1/x7xiMz+bLd4r8IfZbab5knDuWOM39jGuTeyi2G9McabquqRSX45s11wX5zkXzLblf15p/q+tVtjjJcl+b4k31dVd0ryuZkNXd85yb+m6WA/AAAAAADbZ1gPAAAAgANvjPHfVfX1SZ6R2YDeczLb4e5Muy/s9v2uSPLHSf64qq6Z5DOTnJ/kOfOdk/biS3Py7kbHfX+mPax33vyD6dpI8tGZDboed83MbtjeqKp/TPLazAZKbprZ0My5W5znhUk+Z4zx3u28aVU9KHsb1ntdth6iXfTXC49/JMlzz/Cad+5mQUvwyZkNOR8Ui8N62x0k28rioN+pdtI5TM7Z4tj7t/na9y1zIetQVXdP8js5eej//UkeMMZ4SlU9JbPvV/fb9Pk7JLm4qr5ijPGC/Vnt9owxPpjZ99P99iVJPmHh2A+OMX7kdC+a/9nqD6vqbzLbFe/Wm1+fAzysNx+0+u6Fw89fwk7MrMfisN6r9+E9H56Thz1/dg/nu/f841S+PsnSh/Wq6nMyW/fttvj0ryf5pvn3gnX41SRP2+/h6zHG8d1Gf7iqzklyzhr/HQAAAAAAsCSG9QAAAACYhDHGX1XVtZaxg94O3/c9Sf58/rEM33yaz92xqu49xnjmFp/7vsx2zzmT/5PZbliw78YYYz4498bMdlXZvJPXWUnuOP84neckue92B/WWYYxxWZJjZ3pe1eLGZHnZ5t0FWaqT/mXvwJGFxyft4LNbVXW7JPda1vn2wW+MMd6VD+0Qu9l2fz/d7lBfO1V19SQ/nuRhOfnX1DuTfNkY46+TZIxxZVV9bWa/fr5q0/M+PMnzq+rHk/zIfv85pKEvW3j84iQ/ut0XjzHeUlXfnhP/XHXLqvqUMcY/b/M0b83sL1XYyjq+Pj+akwdBf2gN60iSjDE+bifPr6rfzYlD9v8yxvjkpS5qhea79H7hpkMfHGP8yRbPu1ZmO5wdd/kY4+lbnPJjFh6vdFivqm6d5HsXDv/ZGOPFq3zfZaqqOyf5vznx63DcFUm+b4zxk/u7qhPNd/Nb6y6p8z9vXrbONQAAAAAAsByG9QAAAACYjIN+g3xVfWxmO/Rt9mdJvmjT4wur6i8XW8cYT9zme3x2DOuxHK9LcslpPr+4e1mS/93t6bur6i+SPDrb303xHUm+a4zx6ztaJdt1WU7xNdvClfP//X/Z+sb7Rye5/TIWtck7Fx5fcw/nWnztf+/hXIvumOSxSzzfqv1JkncluXyLz11lm+e46hbHvirJ/yyc6492tLIVq6p7J/mZJFsNLr0yyZeOMV6++eAY44NVdb/MBjoetulTZyX5gST3qaoHjzFetJJFHwy3WXj8p/MhmJ14dmbfkzbv+HibJNsd1vvPMcbp/vKDfVNVd0jyrQuH/3qM8VfrWM8hdb0kT9n0+L3Z+veQmy087y1JPmzzE2o2lb/51/hI8h/LWebJ5u/3azlxd+APZPYXHrRWVWdldg3ziCR3OcXT3pDka48PRQMAAAAAwFQY1gMAAACAPh628PgdSb46yV8m+fT5sdsm+fYkj9m/Ze2bJyf56S2Of3SSP9jntXBmjx5j/PJuXzwfVLhjVX1Wki/NbDeyW2U29HLc25P8fZI/TfK7850sWY1fGmPs6Ob/McYbs8UuNFW1iiGCxYG6a+/hXIu7kL5zD+eaiq128tlqCG8rV1t4fGWSp24e0JrvYNfCfHjqp5Lc4xRPeWqS/2+McaqB45HkO6rqP5NcmBN/1vapSf6xqp6Q5PvHGG9a2sIPjnMXHr9zpycYY1xRVe/OicN6exnQXYuqumpmg1abf1+7IrM/x3EwfWROHJx7wxhjq2HnZfmmJHdfOPYLY4x/2+N5/yKzYe1TecFuTjofLrxLZtcvX5nkxqd46kjyhCQPH2O8czfvtRdVdeMkv7Hf77sHjzXgCwAAAABwsBjWAwAAAIAGqur2Sb5x4fCvjjEuq6pHZraD1XE/VFVPG2O8cv9WuC8uGWP8w+LBqlrlTdCs2fzm479Kkqo6kuQGmQ1ovGuM8Y51ro1W3r7w+Fa7Ocl8eObmC4ffuZtzTcxlmQ1P1KZj2x2OWhycfNcudlJbqfkOT1+Y5FuSfE5O7Dzu3Um+fYzxm9s55xjj56vqn5L8fk78NXUkyf+X2a/Z79rLug+oN+XE3Qo/YacnmA/SLA75nDQYfAA8NsknLxz7hTHGi9ewFpZjcSfOV6/qjarqjkl+dotP/eMSTv+ivfyFC6fx0CQ/f4bnPDPJ944x/mUF779d5yS5zxrff6eeuu4FAAAAAACwM0fWvQAAAAAA2Kmq2qiqcVA+tpn1szlx55V3Z7573hjj+Umeselz5yR5YlVdZRn/PqGLMcaVY4xLxhivXfKg3u2S3HTTx5OWeG72x0sXHn/sLs9z65z4vXarc+/aGOMJY4w6QB+vma97ZLab62Y32mb2TRcetxqyraqbJfnPJH+c2Q6eWw3q/XGS2213UO+4McbfZDaM9WcLn3pGku/Z8WKTVNX5O/wzxjctnOJuVfWe7X4k+ZSF13/nDv+cc/7C65+/8PgrqmpxQPZMvj0nfp0+kOSFOzzHWlXV/5fkgoXDr0ryf9ewHJbntguPX7WKN6mqm2b2fWlx59IkeVxV3XIV77sEj0ty7BSfuyjJ+WOMz1/zoB4AAAAAAKycYT0AAAAAWLOq+pIkn7Vw+GfHGJduevzIJO/f9PjTMtuxhd178T4Ma1565mWwamOMt44x3rzp43/WuZ6auXZVfXRV3aWqvqSqvrWqHlNVP7jOtTV28cLja1fV4g5H23HHhcfvT/Kvu1vS5PzbwuMP2+brbrbw+D+WsJalGWO8IcmFp/j0PyW51xjjy8YYr9/l+d82xvjiJPdN8uYkL0pyvzHGFbs53xIcSXLuDj6W/bPCJyb54KbH5yZ5RlV9xHZeXFX/JycPOj7tIO20WlX3TvIrC4ffl+QB6/79hz1b3Cly6bskVtU5mQ3qffgpnnLdJE+u2U6xrYwxrkxy/yTH//x7aZKfS/LJY4zPGGM8b22LAwAAAACAfXT2uhcAAAAAAIdZVd0iya8uHH5dkp/cfGCM8dKq+v4kP7Xp8EOq6qVjjF9a8TJhZarqNkkevs9v+1tjjBec6pNV9UVJbrXNc1Vm/1/7Vv9/+3dU1YOSXHvh41o59YDM85L88Dbf+zBZHNZLknsnecUOz3PvhccvHmO8b3dLmpxXJbnTpsfbHYb8+IXHL1nOcpZnjPFz852qHjk/9MLMfp/90/mugst4jydX1bOTXH2M8Z5lnPMgGmO8qqp+Pid+X//EJC+tqscneWqSf9o8tDb/s9DdM9sl8K4Lp/yfJN+12lUvT1V9TpI/zMm/JzxkjLHV97FVrOGWme0muSqftIOdo7fj68cYT1ji+VbpMxYeL3XYez6o9/Sc+L04Sd6e5PqbHp+X5PFV9aD5gFwbY4w3VtVXZrbep40xPrCPb/8POXFQ9rVbPWm+q+xWu6wCAAAAAMBSGNYDAAAA4CB6VZJnLPmc91l4/PKseHeg+Y4YT01yo4VPfdsY471bvOQxST4vyT03Hfv5qnrzGOOPV7RMWLUPz2xAYz+9MMkph/WS/J+c/D1hNxZ3cWOXxhhvr6oXJPn0TYe/KjvYYbSqrpPZ99DNnrmE5U3F4pDd4g5Sp/LJZzhPC2OM76mqNya5aIzxDyt6j3ee5tP/neQtmx6faqe4t2S2O91B8ZYtjn1Pklsn+cJNx66Z5GHzj1TVezLbbe7aSa5yinO/P8mXjzFa7dZ4KlX1xUn+IMnVFz712DHGr69hSSxRVd0oyW02HRpZ4rBeVV0jyZ8lucfCp146P/bkJOdvOv61Sd5fVd+4rKHjZRljHFvT+z49s2FHAAAAAABYK8N6AAAAABw4Y4zfS/J7yzznFjuE/MYY4zHLfI8t/HxOHub57THGn2715DHGqKoHZnZj8PHdNc5O8qSq+qoxxp+sbKUH33uTPGkHzz83yRcsHPv77Hynmnft8PlrU1VXT3LbzAZ0PjnJpyX5tzHGN6xzXYfQB9e9gMZ+PScO6925qu4yxrhom6//psx2NdzsCctY2HZU1f2S/P5+vd8mtx5jvHobz3tOTtzV9TOq6mqn23mwqm6S5FMWDv/1Lta4L8YYP7/G9/72JN++jee9PMkDVr+i1RljfKCqviLJD2a2m+FWP4+85vzjVF6Z5EFjjBeuYIlLV1UPTfJzOXnX1N9N8p37vyJW4C4Lj199hgHdbauq6yX5o5w4jJfMdob73DHGJfPfQ/4ps7/k4LgHJ/lgVX1Lt4E9AAAAAAA4zAzrAQAAAMAaVNWP5eTdxP4tyUNO97oxxhuq6muT/Gk+9P/vXSXJk+c7a/zW0he7RGca/FiVMcYlSe633edX1S1z8rDeL40xnrDEZS3TNavqw07xuaslucb84+qZDSvdLMktktx8/r+3TvJROXnI4E0rWe3hMzLbVevt84+3zf/30iRvTPKGJK9L8u/zf2Zrf5DkZzLbieu4x1bVZ4wxTjvkWFU3y2y3r82eP8b49yWv8SB7UZI3Jzn+veScJPdK8rTTvObLc+L3jZf4d0qSjDHen+T7q+p3k3xrZgOI1z79q5LMhpGOJnniGOPyFS5xKea7oR1N8qAtPv37Sb5+DUNUl2X5O1Cv0n+tewHb9BkLjy9exkmr6jaZ7QZ364VPXZrZoN4bkmSM8Zb5EOxfZfZnuuO+KclNquoBp9iZu42q+qEkd9/Ht3zlGGOluzdX1ZHM/pKPc+b/m8z+G3xvksvGGFes8v0BAAAAAOjJsB4AAAAA7LOqenROHhq5JMkXjDHec6bXjzH+vKoelOR3ktT88FWSPKGqPjrJozrsrlFVN0jy8fnQTm2fkuQ22d7N+uzMd+aA7twzxjiWD/06Xomqek2Sj9zBSx6b5KlneM5IcmWSK5J8IMn7k1ye2Q3a71n86PDf5CpVVa26cYzx3qr60SQ/tenwHZM8JsnDTrO2czPbjfV6m0+X5PtWsMwDa7576x/kxH+X35VTDOtV1VWSfPfC4SevZnWrVVWPy86+RyzD34wxfmIVJ66q6yf5mMwGs48PkZyT2feq40Mk78hsQPi1qxwmGWO8IslDqurbMvvzwB2T3DTJdTMbIP/v+VpemeSiMcZbV7WWZauqT0ny20luv8Wnfy3JN48xrtzfVSXzf4eLf+EAe/f4zHa/O27Pw/VV9VlJnpITf386fu57jzFeufngGOMF84G9P8nsz/7HfUmS51fVFx4f7mvq47O/w3qn271zx6rqhkk+J8ndMrum+ZjM/tKLxb/s4rhRVa/P7C9k+bckz0/y7PlfIgIAAAAAwIQZ1gMAAACAfTLfeeExSb5j4VPvSXKfMcartnuuMcYTq+o6SR638KkfSHJeVT1ojPGWPS341K5bVY/IbMBq865t18xsMOAj5h9bDeXt+6567NoVOTi73SzVGOOv1r2GrqrqWpndoP5xOXEY95uzPzs5PTbJ187f97hvr6obJ/nOMcYJu0FW1Scm+c0kn7pwnt8eYzx/pSs92SuSXLji97hmTt61dScek+SCJFedP75bVT10jPGLWzz3F3PigNt/z48dRHfP7NfzflrarnFV9QlJPjezIZLzcvLgz+l8oKpeleS5SZ6T5C/HGP+zrLUdNx8IfNH840Crqqsn+d75x1UWPn1lku8dY/zUSS/kQNvJn9PPpKquluRHkzw8Jw96vSSzQb3Xn2Idf15VD0zyxIXXfkqSf6yq+/tzzPJUVWU2/Ppdme2ueKrBvC1fntkw3y2S3DOz359HVf1tZn/xwNOn/pc5AAAAAAAcVob1AAAAAJiUqrp7ZoMcx/33GGPtO45V1XUz29np3guf+kCSLx9jXLzTc44xjs4HZxZ35vm8JH9dVZ+wot1ybpDkp1dwXtbnHZnt+PHyJC9O8k9J/mGM8e61ror9dIf5EO7Zme12dfXMhnCvleTDMxvE/fAk1z/F61e6O+JxY4wPVtXXJHnewlq+OsmXVdVzkrwqs/XfPslnbnGal2Q2ILGvxhgvyooHlarq5tnDsN4Y4w1V9StJvnXT4Z+tqtsk+fUkb8psUPO7k9xn4eU/NcZ4x27fm52ZD5B8WWa/lu+yh1NdJbNBxY/P7Ov+tvmvgZ9f4dD/gVVVX5zkZ5LcaotPvz3J140xnr6/q+IgqapPSvK72XpHxmNJvmSM8d+nO8cY4w+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      "text/plain": [
       "<Figure size 3600x1500 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mglearn.plots.plot_stratified_cross_validation()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 교차 검증 상세 옵션"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import KFold\n",
    "kfold = KFold(n_splits=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차 검증 점수:\n",
      " [1.    1.    0.867 0.933 0.833]\n"
     ]
    }
   ],
   "source": [
    "print(\"교차 검증 점수:\\n\",\n",
    "      cross_val_score(logreg, iris.data, iris.target, cv=kfold))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차 검증 점수:\n",
      " [0. 0. 0.]\n"
     ]
    }
   ],
   "source": [
    "kfold = KFold(n_splits=3)\n",
    "print(\"교차 검증 점수:\\n\",\n",
    "      cross_val_score(logreg, iris.data, iris.target, cv=kfold))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차 검증 점수:\n",
      " [0.98 0.96 0.96]\n"
     ]
    }
   ],
   "source": [
    "kfold = KFold(n_splits=3, shuffle=True, random_state=0)\n",
    "print(\"교차 검증 점수:\\n\",\n",
    "    cross_val_score(logreg, iris.data, iris.target, cv=kfold))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### LOOCV(Leave-One-Out cross-validation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차 검증 분할 횟수:  150\n",
      "평균 정확도: 0.97\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import LeaveOneOut\n",
    "loo = LeaveOneOut()\n",
    "scores = cross_val_score(logreg, iris.data, iris.target, cv=loo)\n",
    "print(\"교차 검증 분할 횟수: \", len(scores))\n",
    "print(\"평균 정확도: {:.2f}\".format(scores.mean()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 임의 분할 교차 검증"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "hide_input": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/pdf": 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      "image/png": 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Jp7r7bxpcT+GifwhBjmKQIy3kSEuUHAAAtLIox3NypCVKjkqaLUeU9UEO5CHK+iBHWgbKMWvWrKZpNI/S7EiOtJAjLeRIS5QcAAAAANBMaDTHC9x9iZm9XtIcScdIGlF+7FN+DOR6SbPd/cF8q6ybXSVdbWZ/kPSplO7CnqdW+BCCHI1HjrSQIy1RcgAA0MqiHM/JkZYoOSppthxR1gc5kIco64McaRksR2dnZwFVVS9KsyM50kKOtJAjLVFyAAAAAECzodG8gcxsoqSJRdeRsdrdF2dHuPsySceZ2TmSjpK0v6S9JG0jqS0z6bOS7pZ0i6TL3f1vjSm5Ou5+iJm1SZqk0t3NXy3paElvlWSS3iTp/8zsY+7+rTq9bYekn9U47111qmEjrfIhRLMgR1rIkRZyAACAVEQ5npMjLVFyVNJsOaKsD3IgD1HWBznSEiVHlGZHcqQlSo758+dr3rx5G41vthxR1gc5AAAAAADDRaN5Y31C0ueLLiLjWkkH9feCuz8i6Svlh8zMJI1X6Q7ny929u4b3mytpXvn50zXMX5Nyrc+VH3dL+pGZvUnSTyRNUynTN83sKXe/og7v97RqzFf6a66/KBfvyZEWcqSFHGmJkgMAgFYW5XhOjrREyVFJe3t7U+WIsj7IgTxEWR/kSEuUHFGaHcmRlig5JNFknhByAAAAAADqoWkazc1stKQdy4Pu7g8UWE7LcXeXtGKYy5hbn2qGz93/YGYHSrpN0rjy6G+a2ZXuvq7A0uouysV7cqSFHGkhR1qi5AAAoJVFOZ6TIy1Rcgxk9uzZRZcwZFHWBzmQhyjrgxxpiZIjSrMjOdISJUclzZYjyvogBwAAAACgXtqKLqAKe0m6t/y4q+BaEIC73y3pW5lRW0t6e0Hl5CLKxXtypIUcaSFHWqLkAACglUU5npMjLVFyRBFlfZADeYiyPsiRlig5ojQ7kiMtUXJU0mw5oqwPcgAAAAAA6qmZGs0lyTKPpuPu7e5uw3lI+kyfxe43jOUdNFC9ZjbPzDynRypfFvifPsNvLKSKHES5eE+OtJAjLeRIS5QcAAC0sijHc3KkJUqOKKKsD3IgD1HWBznSEiVHlGZHcqQlSo5Kmi1HlPVBDgAAAABAvTVbozlQb/+QtDYzvFNRhdRTlIv35EgLOdJCjrREyQEAQCuLcjwnR1qi5IgiyvogB/IQZX2QIy1RckRpdiRHWqLkqKTZckRZH+QAAAAAAOSBRnMMpKvOD29s+YNzd5f0TGbUxKJqqZcoF+/JkZYoOTo6OkLkiLI+yAEAAFIR5XhOjrREyRFFlPVBDuQhyvogR1qi5IjS7EiOtETJUcnMmTObKkeU9UEOAAAAAEBeRhZdANLl7gfUc3lmdpWkt9dzmXUyPvN8aWFV1EGUi/fkSEuUHJLU3t6+0bhmyxFlfZADAACkIsrxnBxpiZIjiijrgxxp6ejoKLqEuoiyPsiRlig5ojQ7kiMtUXIMZO+99y66hCGLsj7IAQAAAADIE43mCTCz/5B0RHlwlbv/W4HltBQz216972K+sKhahivKxXtypCVKjkqaLUeU9UEOAACQiijHc3KkJUqOKKKsD3KkZc6cOf1+mb3ZRFof5EhHlBxRmh3JkZYoOaKIsj7IAQAAAADIW8Mbzc3s4hpn3TLzvG0Yy6nku+7+5zovc6h2lDSj/HxlQTU0LTP7uKQOd19Tw+zv6zN8Yx1KargoF+/JkZYoOSppthxR1gc5AABAKqIcz8mRlig5ooiyPsiRlko5mk309UGOYkTJEaXZkRxpiZIjiijrgxwAACAh6zLPXZK5uxVVDABEktmfemb02kbWUMQdzT+o3oGr0TOfSfp/dalmgxskFdVoniQzmydp36LrGIJTJb3HzI5294eGOpOZ7SDp05lRT0n6Xb2Ly1uUi/fkSEuUHJU0W44o64McAAAgFR0dHf3eibbZjudRzkvIgTxEWR/kSAtN5mkhR1qi5IjS7EiOtETJEUWU9UEOAACQmFU9T9y9y8xGrl+/fsTo0aPXF1kUAESwfv36EVJp/1oe5ZKeb2QNbY18s0Tx7akYXiPpDjM73cw2GWxiM3uRpN9I2iwz+svuvjqn+nIR5eI9OdISJUclzZYjyvogBwAASAlN5ukgB/IQZX2QIy00maeFHGmJkiNKsyM50hIlRxRR1gc50jJ//vyiSwAAoHAzZszolvSsJLn7WklatWrVuEKLAoAgevanPftXSc+V97sNU8QdzVep9jua52nd4JMk4RpJSzLD9zfofVdLWljH5Q35zuND0LMBTZB0nqTTzOxylf6u/ujuS3smLDeYv1/SaerdZH61pG/VsabcRbl4T460RMlRSXt7e1PliLI+yAEAAFLXbMfzKOcl5EAeoqwPcqSFJvO0kCMtUXJEaXYkR1qi5IgiyvogR1puueUWzZs3r+gyAABIxZ8lHdzd3b2ira1t3IoVKyZMnjz5uaKLAoBmt2LFigmS1N3dvaI86tZG19DwRnN3n9Do94zE3f8u6e8FvPUd7r5PAe87FIdKulzS9PLwFEknlR8ys+clLVapEX3zfua/WtLR7t7Qb3kMR5SL9+RIS5QcA5k9e3bRJQxZlPVBDgAAkLpmO55HOS8hB/IQZX2QIy2VcrS3t/f7Cxmpir4+yFGMKDkiNTuSIx1RckQRZX2QIy2VcgAA0ML+IOngrq6u5SNHjtxq1apV49esWTNqzJgxzXLzVwBIzpo1a0atWrVqvCR1dXUtL4/+Y6PraGv0GwL15u7/lPRaSR+VdF8/k4yVtL02bjJfLOkTkg5z9+UbzZWoKBfvyZGWKDmiiLI+yAEAAFLXbMfzKOcl5EAeoqwPcqRloBx8mb3xyJGWKDmiNzuSoxhRckQRZX2QIy00mQMA0K9bJXW7+1p3f97dbeHChTusW7duRNGFAUAzWrdu3YiFCxfu4O5W3q+uldQt6U+NrqXhdzRvFDPbTdLW7n5z0bVUyczspXks2N37a8IOwd3XSOows29L2kfSvpLeKGlXSVtK2kzSMkmdku6Q9FtJP2+mBnMpzsV7cqQlSo4ooqwPcgAAgNQ12/E8ynkJOZCHKOuDHGkZLEdnZ2cBVVWvVdZHsyBHWubPn6958+ZtND5KsyM5ihElRxRR1gc50kKTOQAA/ZsxY8ay22+//WZJM9esWfPYmDFjdly3bt3oBx98cNdNN9106aRJk5aNHj16XVtbW3fRtQJAqrq7u9vWrl07aunSpROXL18+qbu7u83d161Zs+bR8iQ3zZgxo+E9ryEbzc1srKQrJO1iZu9w92uLrqkK4yTdm9OybRjzvtbM1tetkpLL3f199Vygu7tK39ho+Lc28hbl4j050hIlRxRR1gc5AABA6trb25vqeB7lvIQcyEOU9UGOtJAjLeRIS5QckmgyTwg5kIco64McaaHJHACAQbVL+r6kF69du/aR0aNHb9/d3T166dKlmy9dunTzgmsDgKbj7mvXrl37qKQuSQ9I+kIRdbQV8aYNcJGkl0kaK+lKM/v3guuJYkQODwxBlIv35EhLlBxRRFkf5EhLR0dH0SUAAJCk2bNnF13CkEU5LyEH8hBlfZAjLeRICznSEiVHJVGaHclRjCg5ooiyPsiRlko5Zs6c2fhiAABI1IwZM1ZIOlXSIndfu2bNmgVr165d2NXVtdTd10nygksEgNS5u6/r6upasnbt2oVr1qxZ4O5rJT0l6ZTyfrbhwt3R3Mw+LumDKh2YTKWMURvq0QKiXLwnR1qi5IgiyvogR1rmzJmj9vb2ossAAADDEOm8hByotyjrgxxpIUdayJGWKDkqidLsSI5iRMkRRZT1QY60DJRj+vTp/f5KBgAArWrGjBlP33777SdJ+qSk13Z3d6/q7u5eVXRdANCkXNKfJc2ZMWNGZ1FFhGo0N7PDJH1FG5rMXdIX3P1nhRY2CHc/VtKxRdfRl7vPLLqGVhfl4j050hIlRxRR1gc50lIpBwAAaB7Rz0vIgeGIsj7IkRZypIUcaYmSo5JIzY7kaLwoOaKIsj7IkZbBcqxcubKAqgAASNuMGTP+Jemk22+/faqkt5Uf2ytYryIA5GS9pEcl/UbS1TNmzHi64HrS2nmb2ZslXSrpHkl3S7pB0nXuPui3mszsQEmXqdRgLpWazC9293NyKhfIzeLFi9XR0dHvnWjb29s1a9YsdXYW9gWVqpAjLSnmWLx4ccj3GooU10ctyJGWSjnylNq2BeStUf/m2bbQalr5vLCv6Ocl5GisaNtWs6+PHuRISy05Uty2Wnl9pIgctWvk9jVz5kxNnz69aZoE58+f3+9dc8lRjGbLsWpVY24i2aj36avZ1kcl5EjLUHI08t986tczgHri3zsQw4wZMxZJukTSJbfffrtJGitpTLFVAUDS1kh6fsaMGV50IVnmnk49ZrafpN+p1CTeY42k6yVd5O4bf1VYL9zJ/HKVDkQ9dzO/QtJRnlJAYBBmxr9XoGQrdx/Wp1RmNkVS4d/oAhI0rO2LbQuoiG0LyAfnhUA+2LaAfLBtAfnh/1xAPti2gHxwXgjkY9jbFgAAAKrXVsSbmtmbzGxW+fHKzEvrs5OVH5tIOkTSb83sXjN7X59lfVqlpvJsk/kvJb2XJnMAAAAAAAAAAAAAAAAAAAAAqF4hjeaSZqv8sxiS3pUZ3zXAPCbpJZL+y8xuNbODzexqSV+SNFIbmswvkfQud19feVEAAAAAAAAAAAAAAAAAAAAAgEqKajSXSk3hfWWbw++VdLKk6yWtK4/raSZ/jaSrJB2UWY5L+py7f9jdu3OpGAAAAAAAAAAAAAAAAAAAAABawMiiC+gje0fzNe5+kaSLzGwbSadJOl7SeG1oOO/RKem97v67hlUK5GOrogsAEvFMnZbBNgVsbLjbF9sW0D+2LSAfnBcC+WDbAvLBtgXkh/9zAflg2wLywXkhkI96bFsAAACoUmqN5lmje564+5OSPmlmX5L0NUnvV6nZXCo1nI/WhrueA03L3Tu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      "text/plain": [
       "<Figure size 3000x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mglearn.plots.plot_shuffle_split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차 검증 점수:\n",
      " [1.    0.947 0.973 0.947 0.933 0.987 0.96  0.96  0.947 0.96 ]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import ShuffleSplit\n",
    "shuffle_split = ShuffleSplit(test_size=.5, train_size=.5, n_splits=10)\n",
    "scores = cross_val_score(logreg, iris.data, iris.target, cv=shuffle_split)\n",
    "print(\"교차 검증 점수:\\n\", scores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 그룹별 교차 검증"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차 검증 점수:\n",
      " [0.75  0.6   0.667]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import GroupKFold\n",
    "# 인위적 데이터셋 생성\n",
    "X, y = make_blobs(n_samples=12, random_state=0)\n",
    "# 처음 세 개의 샘플은 같은 그룹에 속하고\n",
    "# 다음은 네 개의 샘플이 같습니다.\n",
    "groups = [0, 0, 0, 1, 1, 1, 1, 2, 2, 3, 3, 3]\n",
    "scores = cross_val_score(logreg, X, y, groups=groups, cv=GroupKFold(n_splits=3))\n",
    "print(\"교차 검증 점수:\\n\", scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "hide_input": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/pdf": 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hdGVEZWNvZGUgL0xlbmd0aCAxODgKL1N1YnR5cGUgL0Zvcm0gL1R5cGUgL1hPYmplY3QgPj4Kc3RyZWFtCnicTZDBDsMwCEPv+Qp+oBIGUpLvqTTt0P3/dSbr1J54krGJ03LussFNPi2hPzwX5tAi6jdd8rt1pGQqXbvaonPRBp3Ekh/oOUhuT4rul3rTL+fd9hBoVnhIKsoxn7TTfzZ0PAijVIxxkUUsMj4bI8TDBNPkaM4dU5Wg17TucyKoFCHqNRFM9MEdutwluA+b5WYDWBfvzDeIOxWMUrSTQiwnp4mxF/iRRzNegtZVrGLIXPP4N63Sry+m5EssCmVuZHN0cmVhbQplbmRvYmoKMjIgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAyMjEgPj4Kc3RyZWFtCnicNZC5bQUxDERzVcEGFtDwklTPGoYT9596SPkHwgwoHo+MbTLFUx5fErZlWcgXhh5t+ztsoZ0bI1PFl0tayjsCKbFml/m/2v2hU+ZWBmZ0jTs/3CAPg8b0mlhjSt+hcZ1iyWNHsKlaNQjSMWCTj+3ObbXJGrJUgJCkpDUTO6AW0jwlF4imCHM1cPW4K4D5tZTirvtZ+x0/fYLMOgF2toOZRHirWbPRKSnBASAWyHOqHIc3Yb86BLot5R3GHBrbXr9O0s52W13uha9X74ByNdLYrxA+UAX4/QfKslKtCmVuZHN0cmVhbQplbmRvYmoKMjMgMCBvYmoKPDwgL0JCb3ggWyAtNDUgLTI4NyAxMDAwIDgzOCBdIC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMTkxCi9TdWJ0eXBlIC9Gb3JtIC9UeXBlIC9YT2JqZWN0ID4+CnN0cmVhbQp4nE3QOw7EIAwE0J5TcIFI+Is5T6RViuz92x1DVqHiSQZ7TDGVak71W1IuXO/iwzb1aFAP2kSNnuoriYCyyyu1Mau+Kaet6tJVAj0OIkUIpof3JEne4BGbDslO882r9eQqzFqZHZ16m7gTxgZI103uM1C86Joj1NsmtbxP1jdlCEQRfySYnRJ8jCCMIpa0Uc+iWFcIKytOTDZ8jIihkmLPzIbbbFw10EVxMtfsfRbxXAHVsXb673Ziz88PZRRUyQplbmRzdHJlYW0KZW5kb2JqCjI0IDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMTM2ID4+CnN0cmVhbQp4nE2OOwpDMQwEe51iLxCwZH3s8ziEFC/3b7N+wZBKIwl2NkZHg5rh0QM9CkV+quxThONzU2riEvWJtAGtQLpBJ/dsWGLWkTVgnsjJmb+gJSfyumlLLrHSP9qJm9ohL/oazBwxHdYUMZRZSkMk/RHsVtDOjuzEj/FC993aB077JW95fQEwZisiCmVuZHN0cmVhbQplbmRvYmoKMjUgMCBvYmoKPDwgL0JCb3ggWyAtNDUgLTI4NyAxMDAwIDgzOCBdIC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMTQ0Ci9TdWJ0eXBlIC9Gb3JtIC9UeXBlIC9YT2JqZWN0ID4+CnN0cmVhbQp4nFXPOw4DIQxF0Z5VsIGR8BfYUERB9t/GNkpwuqN5owsUEKlden2XTi20Q8JiQoYk1umrYFYDk1euFFzKfxryXX86p63CY1aQaXfg1kI7hIr+J1wQqWGMrDN64+o0lp2C9QEYlnbC9M9II6v5dVQ4K9bOLSky+xY9r/YIIosjdccOPMzRkaQYV3l9AC41R1QKZW5kc3RyZWFtCmVuZG9iagoyNiAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDI3MiA+PgpzdHJlYW0KeJwtUTtuxTAM23MKXuAB1t8+T4qiQ3v/tZSSISBjypRExzYsROBjgVBFEb/kOoKowt9FPfJgs6hkYAvuiyQj8XvJ2sjaECOehBQ9RFmiK1BaUPdx1X0G78tShrkkazc8HLlb8aP0VYQIcj0Y5lSG9bcKTqdYC87BnjvudNlE9utTX9kKJzT6ui9YGlWFeY/vy2HsbNuhx6gqNIuKBE+jF2viJDG3XvIZ7c1riB2ibhYvITOhs/UX42ph04Vb15q5+s+VeIhu7zSeVJmbV04uflYrysBbVT6DnAdtdms2tUyMb2B8sTR5+2R3tUImc28lO12N85ywe0ZBuHm6ztZUmJ1o0C3wPv99/Vzf/5VTZpQKZW5kc3RyZWFtCmVuZG9iagoyNyAwIG9iago8PCAvQkJveCBbIC00NSAtMjg3IDEwMDAgODM4IF0gL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAxMjcKL1N1YnR5cGUgL0Zvcm0gL1R5cGUgL1hPYmplY3QgPj4Kc3RyZWFtCnicTc/BDcAgCIXhu1O4QJOCILhQ48Hufy1gjd6+hLw/Ialiplrzm6RoaIQAb1NlPCR6/9ctJjR5ZWtWehLWfAGQxUF/jiBUNqHwoas0b/pma0564pZR2UIGIc8D0SFWn5TGh+aVRA95ZKyah2MC/n9kYAULr8zWvPb0fJHyPKwKZW5kc3RyZWFtCmVuZG9iagoyOCAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDUxNCA+PgpzdHJlYW0KeJw1lE2y3DAIhPc+BReYKvEjJJ3HqVQWk/tv84FeFh7aQkAD7ZnbZcg88omQ6SbLU37pY3v10d/HwkAueriEU+eWj7m8jyp3juyQXRkIfh+sjpDvBVtyiKpKGqb8GQCXXP2+lEunUo0liwhqTVxrCbXfx7jjKhZHbIrtNu/jZAR4ubb4HDx1nFtI4HvKxMA36ziot8oTclzCrRlxHnAjPiilsa7N054QW5WJhzCj5bIQomSh70VnFmI4P4i2CtmB0SEG+jGqbfcAJTxhoCG+RhPCsxNO5eWEPkOx5IGFgeglaHWOfa1fD2grd5lsZeNW3hHMaprRWEpmMp5rYT7jnhgxtRwWnFHZFE4JAy2PTjnsYNcY+JncIsXkYc31xrHdY2Xp45pqBJAs4PscwEIng7QQK5Xkab0wsjVYeSR2M+xAARWrBC/aNYawrEhifRTtKMQK8krToFG2RLAaeWwsi6Lm6pHGqLyM1Q51vMeaTT1YbyK6Gmsimzhws8o2W6t0Bp+54tpoRRdSFK73/iR7rM7GWyDX2CUivCt/lhpZC91duQQR7r2kEiOMyd/yKLmssjWdi5QBhmWLOjh3r6pIbYzmshHm6A/VkG5ZXc2yUH3CxCo1Js/pEFRXbHgJGifYrviRAGxdPiUg9vPpORSXj5fc7/f//3/gff48v/8BytHG+gplbmRzdHJlYW0KZW5kb2JqCjI5IDAgb2JqCjw8IC9CQm94IFsgLTQ1IC0yODcgMTAwMCA4MzggXSAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDEyMQovU3VidHlwZSAvRm9ybSAvVHlwZSAvWE9iamVjdCA+PgpzdHJlYW0KeJxNzksOwyAMBNA9p+AClTD+kQtFXZD7b8vgRnj35NHYLiZW9eL6lC66Nbdk6BLSo0i/hXRNiVYHco+OJ5nZv3MUqbMmYcssMq4kbrg3BiV1RkoJkUlrSbHj/Q6fmkr90Dr0bHpHzn5AgvdcWtIuzNPFovsHc645jAplbmRzdHJlYW0KZW5kb2JqCjMwIDAgb2JqCjw8IC9CQm94IFsgLTQ1IC0yODcgMTAwMCA4MzggXSAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDEyNAovU3VidHlwZSAvRm9ybSAvVHlwZSAvWE9iamVjdCA+PgpzdHJlYW0KeJxNzrsNgzEIBOCeKbzALxkDhiwUuXD2b8Mjit194nQnYPJsYtw+MFhSO8XWXZEeVboAxa/dvBNSrY5emqK/zlGlSnIpVvZ/L7YFe2P0aR4Y2ImRwguE4jC7VWEsHCUW6LT2INbPVNxJpNCg16WHKR6MzlFVFry/85E7swplbmRzdHJlYW0KZW5kb2JqCjMxIDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMTA4ID4+CnN0cmVhbQp4nE2NQQ6AMAgE733FfsCkQAH7H2M86P+vQhtjL2Sym1l0F1QwYROFWocz46ASCYnjSeCI7iIqo7xLU1uIqwel+lOqs/0pH8SK00Kz5Q+uIs2hXeJvHK4W4YAp6ELaaZDBWrqfmSvnCyGlKVwKZW5kc3RyZWFtCmVuZG9iagozMiAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDM3NCA+PgpzdHJlYW0KeJxNksltK0EMRO8TBRMYoLn0Fo8Mwwc5/6tf9fh/GJDEUnMrFtlXWrM+7a6yntumL/vwayxb074vb81GN8+w2uZjGDGvy/e24JPdoixmyryu0HNZRsqb1S0Xzzmm1QQP69uqhc3Oc9FqN6ts5m1haRCqXrXMO56e5tQ+dh8PKIJYygW4cpzueAIqmxdvlvpSWTzoPkEQTVEosXNLqosur50KGqtrnMfi8TjIESFRx4dyNKJnnWxvGnDYUmGXo40j3vuqvf6ggW7vy+d/NERyHtT/oVUgCCBNRWNEho8QkUQ6yUnzOlLHsYzlfpDGUm4uctoRSeSRq4rB4VeDKFaAZy3it3W4ZrAN9TzCdhas2jqBqF/b1vEgw/EEZ0BuPOvCw++kOUprWXSIdbaXNqDU7YZirrD7IcxWb8YRcV1bsBdZhmR3N1kO2Tu1eyLOJbgPUJPK99CZujaKper7WF45VcQlSBkjdFMoy7/niF/X1/X5A5WPipMKZW5kc3RyZWFtCmVuZG9iagozMyAwIG9iago8PCAvQkJveCBbIC00NSAtMjg3IDEwMDAgODM4IF0gL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAyMjUKL1N1YnR5cGUgL0Zvcm0gL1R5cGUgL1hPYmplY3QgPj4Kc3RyZWFtCnicTVBBbgNBCLvvK/yBSGAGmHnPSlUO6f+v9eymbU5YssE2R6/Cw4P4Ptrthq8L9rSNxP+jN/08kolu01ZtaW9BXfu2BDf9AYeFUMz6RD1/2T9033keNVCh248B97y84drxmGAHvInoxnnQdEnx6Au5UtPRjM3s4NxuG9V0UHyNPQNlt8aRpa3ZSOr2JMaimDDHoFy4EDkRVQgzMbsBh3Qj4cukd7iwGBoW3/WcQ4vKry7BUjC7DGWSdZUIRWfKorYhQzoboJ7GNFXUVIjz8KHy0rkuuHbu55x609cP/JVUOAplbmRzdHJlYW0KZW5kb2JqCjM0IDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggNTc5ID4+CnN0cmVhbQp4nDWTS24kMQxD930KXaAB6+PfeXowmEVy/+08qpJFQS7bkiiSnidt2Ex7V9qssJ3L/vir7rEV175fta+tGlZT8VrltjWXfV7l09YKy+vEZcmn+Hlljl7FJWdui+1d4/MK2qxIC+dkDHNuTE4/L6ePAPgqm+OaA6qeE3Yr0xxoebmR03KqmoNFqy/uJP2LLPDs01V0V3Wn1Vjm51j5sRhlFUdYgqmSHapUgZKpiq6cKId547KjCclTZLJZz87RDT4HZSmnyqnGR+dyPph9EMwhTLDsoC2mCyI3OKFznOq5Y/oTXQw2E3uhDMipPIPZYIUTRyQACxpq7IJdtWdw4LB+uyQhhlrkYiXiIE0aS5J3Aw5G7h3IeafaFbm/hDvaCO8xErbGOM4mCkNuiwijU3iQma7wFhwR8oEpPZhZpLsx/cPfASWUOdJPCPaYNq/uOzKuZIcbi34RxNsyLfJDdU+7UzIrMtt9/FoA3SkhdFM5EkE5dZZtCJ2DG2O3GNiXu1/PSv0xxIKrX8t/Xv/aTkG/7145UnohBAPJlp7q0X/Udoa78lfZaVOqjhwuH2MuKrfzmxqTtWgqGUL0ZfR/1tFpLvGlbdyKoiVsz4BHahb4fMho4o5Ys9WQ/sizZMp6rE6MVrNXqROn0+2cOH1ClRywpM7wreeRPZsejKyeV5iwwZaFdz8AxjjsYHXxn2P92Dx4wFrpGelGSKvOkaVVJVA9G5/ydz9OqvEMfYkcsYubdrNbtyu50MqdP4pInb//AZdw4CQKZW5kc3RyZWFtCmVuZG9iagozNSAwIG9iago8PCAvQkJveCBbIC00NSAtMjg3IDEwMDAgODM4IF0gL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAyMDgKL1N1YnR5cGUgL0Zvcm0gL1R5cGUgL1hPYmplY3QgPj4Kc3RyZWFtCnicPZBLbkUhDEPnrCJLgPxZz5WqDnj7n/Zw1XaACNixnYyuJaXyGbeYcob+X3yf8Yuf8T28Q3Ia3FCTMJWoKQ6amuKq8oxsFeOnvMXMpWHamiCVJeqBUqGhvNLBJiq9xeJygg7bJd4tHvqeWA7iilMstPNlGPksrqNmoIL2dFGclzU+DdJQaD5jGRVxV9EYmC/C1aVobPEbZ7u4EYe4TrRnGGYxryGjOjeRggUQBX4qfYyVTay5pez2+O63OiPmxRhixzvm3+oe1vj1A8icRfAKZW5kc3RyZWFtCmVuZG9iagozNiAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDc0ID4+CnN0cmVhbQp4nDO1MFYwUDAxVNA1NlUwNTJRMDe0UEgx5DIyhgjlchmaGIFZOVwmJiYKZiYWIJYhggHSkMMF0wphmYHVw8zI4crgSgMAFooULgplbmRzdHJlYW0KZW5kb2JqCjM3IDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggNjczID4+CnN0cmVhbQp4nD1UW24cMQz7n1PoAgGsp+3zbFH0I7n/b0lpWiAba2csiSKpzeOyxLd8RUhGyvaUX/rYVbGUn8fVGTge2xFPhCmfx3dKmPh1SZNYV4qPw0L2lvASvAnUU1U+Txe1K5FHNNecO/oNolvCG6a7cwzpeIP/lmwTYnua2OEbdvVF2ECja1Dp4RuAcyshavclHIPn57Ha8ySqb1jfYo6t6ip6TlfV7W8fzd2dlZjQQ8HTYFNwQbQKbETfZ8/TESbkDU7MnOGAVQCcRUERuzRlbAsKiQKENiw+Jk42AWzQ/8rxef60MrGM0oAQRo57sTA4UqJbeQUiDHxANdW7+A4gIHXhbuCjyC2Qytx9X7rjgu5QSY05RwhGWV0hW/crea3lVilWBH1loBxU1PjjmFQAAfAXcj3gkLKWCDkFqoG0QC7n4YmR95onOTfM/c0xza6i93ZVPfn20a3dWWuQKGw02Eg30eqLXv/Po++EvMGJNePlQMkIPpSSLFGb4c2WNZOmp5mlDYZrYzbYH4vOPDz/acXF+oGcpyNDzpfT/Fe+7DQaLJ/SLLwrSgfSSLjg4BDj9N9oBGgruK4KFnlUyw089AL2A04CdjusfFkBFf02/cqtQT207CjlGw5nGTSnWXD/jiM+T3EjITdm44rjt6HpZgB+sLOJFtColJOiQnHlgZfrjGe1m2lOcLkQJZvqYK223lYUkd3Wmj85ZGqPc3wiAuQNh0KTQ/53+/d21aj79olzu3MubyCJ9R9kCW9kb9gZ5DxnFDqfs8FbHDXuemcPbA/JCB9yHNW9xtW3KfzGTniTGsea5Fz7ZT3dWgb+mFIVniNTR04X3pYxMV3Lmnpa5d5llNRxQNSiI8KjDUJTjWUci0ITORakTfXajJb7/ReP8RU7CmVuZHN0cmVhbQplbmRvYmoKMzggMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCA1NjIgPj4Kc3RyZWFtCnicLZNJrhsxDET3PgUvYECcJPV5fhBkkdx/m1e0FzbZ4lws9k1bVo+9K63z2sltv/x1y95e9k9KH/srudvusb3tSdthPy/3sF7mmVZu3m3Zej7H4rFYy2JbREv8vGJ/vp8wAjIoe3lO/jffx40a+ZDIlbwcrXAixg8VkqwfCxFB3eoiG5beljSAhRdpf/E5lNhEXUuiaio/k5eo21bLLcibFwsN0MmhweaFXxTDJJ6pmFQMTccjuSZOkqGYeF6WXtQp3zOX04FG9sACIr762wEFM9wOOOAzsx+eqVrraBdFUYkjNFGa8kzWzAz6fQXCATWeaWgLe9+YSmWBabMmZ0OHkg7cx5U/Ak17YU/acgC1pFYQoyULOKyryHZWfqHe12lF6y+6ClavwdsXndANWRuvDn5rzxz40YvYVLJqBdPzaPLLAJImBuBCXfe6nyU/Aow4ce1OA0OTGrvlhqiaJZnjnSyQvGJuxBkp8vlogv3Nyr5E/nn9mWHqitTSVLKqphlxq1teReI+8MaRj1gCsMO6nNEZAOsGsOQsdo9FkAN3eiPPACspytfnpfRCu8Cxe3iz0FizA+EGchfAa3iDXwsGcjeM9NoDsBgF5PJVt8RL1l3fpVfLIvJgKS1xLFRLkPR+QE8gOp3P8XL5KcY+WgoQCl/PL6dTfO47jNW1fJib3KQ0XYY8Uvfmn9upyZJ0rqy1au5I90beozs+Yy3R43vH/vliwmpt47Mf7er3fx7O2r0KZW5kc3RyZWFtCmVuZG9iagozOSAwIG9iago8PCAvQkJveCBbIC00NSAtMjg3IDEwMDAgODM4IF0gL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCA0MDkKL1N1YnR5cGUgL0Zvcm0gL1R5cGUgL1hPYmplY3QgPj4Kc3RyZWFtCnicTZJLDtxACET3PgUXiGSg6c95RoqySO6/TT16ImUzbruheFXMM0/Z2q/9edb2Pv3u0w/P0JHr/473/tdTETZeVxenHMvKp+X7Wr3Doo59nnHCwreNVeZ72KhhXoubTPM4Utjm77GUqsQ/T5abZme8tiSzN4/PE1X9HoNbP/NW+7ztPq6cC+UOcIEwcmcTLP8i6acZ8yJne9DnbDjdlt5VXSP0Wd21JamOKXfIzwEPA6fKAJhyCdF6J6RCXKJv4ljXQoDUnnTCIhV4vj2kgAqpoArKnUNyTCZJSMj2opE2rL0H0L/7+Gg3I+u7mz6lNpBSXaqIUleirFQqszdQUzRywARxKrapOYm30C5K7pOeTPyXpbtNucAbT7me434hF1WE5tyeeFer+PFW9XW+c3yunszCIHH1XzaXd2h9eNP3s71xyqlaVSQLZ+ZhsagEfwephhJiTihl3Rymb4PElTls7E1s/G1qGvQul/jhKadyyAnHVJDB7SEVVEgJVXK7c0iSySQLCVlfNtKHlm1A/28/7OrnX3UOptIKZW5kc3RyZWFtCmVuZG9iago0MCAwIG9iago8PCAvQkJveCBbIC00NSAtMjg3IDEwMDAgODM4IF0gL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCA0MjgKL1N1YnR5cGUgL0Zvcm0gL1R5cGUgL1hPYmplY3QgPj4Kc3RyZWFtCnicTZJLjgMxCET3fQouEMnmZ/s8kUZZZO6/nSpIK7OIGhkoHkWuPaY85nT5vXR+wneFMzejs/9FDzuIqucbdcvrWnvI1AGlPFHRuyK+vyv7jTr7usIkxkYLA58SR2KprCkJ6ee1TVKPnCMZji68r8D7dJWakgvFgD0pSw0ZVZdlIRp4gaKeUd/nZcwgsoiqsB2fHscGVHEsRVXPe45vrclOAoDEvMkCnUQNvpKcX6zCzBFHNyvco3p8LqpBxTayULX0mmPuzGAy+UhiUCGbYidQg1a3V1bXqX34xabYsF6YQQU96B66QhW6xD761nMIgMGwlRzrBoPtRWoNbp9NXvA5Pgdi5DuhucEN58Hl3tNUXJdMuOG8BdjtsH8ebgI6brXwNe6dxT5whw3+UffQo/XFvqxFZOZVYXH3GGuhQm+oyhk9x8th/HQWifMCxeaWRes+ip7f3q0i481TIrR6eE9klP/DVszRM1KZ4eREPUkS+mTjvwMZ0CZ8IH1m1j7Zm7KWLzGqgh50D12hCl2iKn3rOXSSk+ksSeh1s9F90tZdQH/fh7f6+QMFrLaOCmVuZHN0cmVhbQplbmRvYmoKNDEgMCBvYmoKPDwgL0JCb3ggWyAtNDUgLTI4NyAxMDAwIDgzOCBdIC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggNjI5Ci9TdWJ0eXBlIC9Gb3JtIC9UeXBlIC9YT2JqZWN0ID4+CnN0cmVhbQp4nE2TQY4rMQhE930KX6AlGwy2zxPpaxaZ+2/nFZ1If9ExMbgoCrgiRouV7feKgxWzpUcLz5bbWlhvr2vZbtFnW8TNY23bbHO7PLu3OaK9rxX4iF4+OFdbPdoE6XXlOm1ObxneZlhLvDP1Ojuxy8lP7CZrgHYWnjD+9cMnDkSJS6FNS26jeZIPZO9CPXjMycM3xBKGY8BypFh6AbyvYYSc3obgSG7OOQRrVSxwfDGBX4hRJOeA4IYCQmWH4EYiKEES8Jy8U3HERgaiFcnDDQJNs5LR4zlf16DEfLhgLSR5U9L5WmSVFVCvM1adkuqJTrjVSRtWKNcqT5Tg8qy+25oScQ08E0SdNHR10FwNTTRY1J+5W65ZVeTc8qBGwjrUjkPbP+Pxun6ujQpOht+yDPGp4j/Dq4Zv1JsXC1VcD2SoyGw3ci4Eu6ubonNzu3h+iwhp71MU6ek9utjo0VhQ2hgmLjHl1JwylfeYdCU+BuIzM2U66lWUj/N9aQxsodncD75R7ZNynCwSGiCRGvmlOZ58bUyVoV/3uvZGl0dyZw7SaKN6Ykzc2AsGyFMDOuuEObiy0p8IFfy8Wb4KRVLt56gkPywQtRgqypiIxOhTmhTKU1KxkjSTklnhBGP0UTNDDQgbW8vAXKsmi1qv3YYW9eDxWfx0atqtLF9PhDOlzxtHJ6E48yZU2988Bh8SGyCaC2avaBl8oGnUBWkdbrWm3PUm767gW3mt+oc2YN10Sui3q2PKd2sj1SfmSozuWnhxvNk5cb6Z5JqB3LV/j6U6FaHKnzfSQijSRqhS68kj+ZRZaopJDaCoSW6tSRftTy/Uln9/2uT5dAplbmRzdHJlYW0KZW5kb2JqCjQyIDAgb2JqCjw8IC9CQm94IFsgLTQ1IC0yODcgMTAwMCA4MzggXSAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDI5MgovU3VidHlwZSAvRm9ybSAvVHlwZSAvWE9iamVjdCA+PgpzdHJlYW0KeJxNUbttRDEM698UWiCA9bfmCRCkuOzfhvTL5a4wTJgSScnXniWeJj9Xux/0OOhDnbCi32Hv9ce/UNgGos4L3Trfl3pINdWJOsiH5hsi+/ivY4/vFPdET6iLDRwixLIkesQs5fNKDVEwmSpaIQlP9SZjSKkU59NCqExQDOcoNZT46Gn2UsjtY2ZVYGxKTDfMUNvAq9A7YDQ31NCnS2qkoOd8xmPQrEWthJZsxb50M6c2kmvjwApZLWC1KWiYxdHiqxGEE0NysceTE+MFPsFddEsa3RxR0hQ9hnud0LyhZnOQzs0ohr6ZXAc8DhhmNbUnYhWQzT63x83AaddB4XrfSJvDFQUmSvxeFLaPHIHRIzkRa/mjgRU5qp7/+Ik//foFSGB0CgplbmRzdHJlYW0KZW5kb2JqCjQzIDAgb2JqCjw8IC9CQm94IFsgLTQ1IC0yODcgMTAwMCA4MzggXSAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDE1NgovU3VidHlwZSAvRm9ybSAvVHlwZSAvWE9iamVjdCA+PgpzdHJlYW0KeJxNz0sKAzEIBuC9p/AChfg25xkos0jvv60OKc0i+IHJbwQTRUnHD7TUCRf4tEORoxRJh14kvNsHO2fBL3HBDRyKs8ODu66uMRrq85CLlMjykGpPU41D4rG7f1G9X8AZW6LySGb1ap4aVU28wIYipaKZIU1BH4Zc54IW1b/r991jQhuMRFSzHem5IzlxVqw8q+zNrlry/QXxkD5/CmVuZHN0cmVhbQplbmRvYmoKNDQgMCBvYmoKPDwgL0JCb3ggWyAtNDUgLTI4NyAxMDAwIDgzOCBdIC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMTk2Ci9TdWJ0eXBlIC9Gb3JtIC9UeXBlIC9YT2JqZWN0ID4+CnN0cmVhbQp4nE2QuQ0DMQwEc1XBBgxoSephPQcYDuz+Uy9lGadIAw3/MqLLA6byKQP44XvhmDWJ/qatX6UZA0ZlVkdf9F70QA1i6gNtOslhB3lr2970q/MqfUqMrD1l1JQWflBfQ6D1g9yymfWTrI9tb8LIDK31T/vP6uTbxJoLpslVPGMCqx5iivcQ5Qw0JJjlIs0ESmfMUi4FFSAYY8FssB7nAK9pTsMeNBgkF438UdGMYK+rqFdhI4Xn+mAFPte+Rt7l+QWvY1IuCmVuZHN0cmVhbQplbmRvYmoKNDUgMCBvYmoKPDwgL0JCb3ggWyAtNDUgLTI4NyAxMDAwIDgzOCBdIC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggOTAKL1N1YnR5cGUgL0Zvcm0gL1R5cGUgL1hPYmplY3QgPj4Kc3RyZWFtCnicTc6xDcAwCATAnim8QCSDMSQLRSnw/m38iiNTcdKDHmLjItLKIMi5liBvkmTNpkQ9qX8pW5JqXemWXB2pWtZsC/p7gx46Hc3zBeBg3O7pmGsDy/cL/ykifgplbmRzdHJlYW0KZW5kb2JqCjQ2IDAgb2JqCjw8IC9CQm94IFsgLTQ1IC0yODcgMTAwMCA4MzggXSAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDExNQovU3VidHlwZSAvRm9ybSAvVHlwZSAvWE9iamVjdCA+PgpzdHJlYW0KeJxNz0sWwyAIBdA5q2AJAvJxQz0d2P1PC0k0jryHJ4JAYmgc+IOSN8IJruNQpRPWvQlfIG7IRtWTEulZ5e5bDXVoStiWhDKVlFrbGk9qqku9P6+4n6ppE3rEIedEOL1oNX0fV1lGvLh71/b1k88fvuIxlwplbmRzdHJlYW0KZW5kb2JqCjQ3IDAgb2JqCjw8IC9CQm94IFsgLTQ1IC0yODcgMTAwMCA4MzggXSAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDQ1NAovU3VidHlwZSAvRm9ybSAvVHlwZSAvWE9iamVjdCA+PgpzdHJlYW0KeJxNU0mO5DAMu/sV+kAD1ublPQUM6pD+/3VIOdWpkwnLokgqabpk9CW/jWCaXC1H/0YoXu1+dbV301CZutlBtBK3EfGNUL3+3rHH1hLvhh7LXsh04kzRtcXV5dV0qLh1UUfFcaLXw1jpqGTIQmFsDBLHrFcDDpRGSuAtD1+8BsgUVuECr2PxGt3ZQ0iWsEP6xBjQY2BiEAVkWkmi81ejyBxTKDqnCm3wfDW3Uchz1wsne/WEZrFQC1kjxz0nZtRkyqGS2POWln2U1lQt6XWWl0JUyhdQzp5jnp1eHqPC4ZwTFzsZIJUwUGo7EVMtQ6f6WsK9ltdnRSOwIucCgByKnB63g2OUN4cKMBvmIZs68RoVokDwRgesQu/w6tHyFh29qxdbLPb4wi25BzLZUJbIv5dOdyCqZib95K61EXDWDZzyhVnePdYPi+4oVl2fOcrpmKzwRCWKFI42rdzwTXBfUF9n+SkEhzqsHJPtZGA9KhXzXSl9cmOGi44Gf6aJHRBdhWzzbxrgfNCEolN9UOLnuYrlQYfl3WYu+VHjP6QYX/AquEdR+gN07Lv2IIvPlC/EouHD+QM/2MF1Zj3ojHq3f/8B0ujJ2wplbmRzdHJlYW0KZW5kb2JqCjQ4IDAgb2JqCjw8IC9CQm94IFsgLTQ1IC0yODcgMTAwMCA4MzggXSAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDQ4NQovU3VidHlwZSAvRm9ybSAvVHlwZSAvWE9iamVjdCA+PgpzdHJlYW0KeJxVVEluxDAMu/sV+kABa/PyngGKOaT/v5aUE3R6CExEEkVRTprFlKlbflqhbXK14faJEL3ak3e1d9spoxtKCAbfzfUPddbuB7zb1C7hExWFQDN7SHSXsUN8LXm1sYCmgWaJ55YRQzwqYoj4kNxT3KbkcJyKSNoWVzCBwVUlotf5ag75RJ5aGa7zrrHlxWKZxWrudx+r/C26jxJdjzadR61iRKqvE/MgQpSIMAOYNYEHEbDE3kLWVKs+ac4+6JweQiUZXtoyNlVDbVIX1CeUcB6er8YJiTgxM+jBqaErZKFLZKVvpw+dZGc6SyX0+mgr96G2tgH1z35e2NUw4oFdFQrUQ1+g16DDOcjcE/VQsEfx5DKJmVSDnrE4BWpxFRJOxyqd8C82HjqFu8HZeGK2ft44GJjhaXeNY1qy1G7Bapj19KF37GzTS4mNeWuzoaXWyj87p1eECIyVYXZqtCJk6bs2wj2zj2/6UXdo4+FNW7O0eXlItb4wQ+dtObviiXnmecOJmUEPTg1dIQtdIit9O33KSX4PdLbfXpe2ch9qaxtQ8eyHu0rszROrCuPVxbdGoHMC6Qcw3ImrrfWJTpAMf6go8LlC3pfqArHidhS8Ciok4l/g+wN9BVHV/KFT8m7fv9le0+UKZW5kc3RyZWFtCmVuZG9iago0OSAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDc5ID4+CnN0cmVhbQp4nE3NQQqAMAxE0X1OMRcQGpNpPJCIi3j/rbZY7e7BwHzSUbARixE0RayKXWXw6qpekaJhk1zLI2pMMhvrr3ac8hY62m9+hZRTjhvIsBnzCmVuZHN0cmVhbQplbmRvYmoKNTAgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAzNzYgPj4Kc3RyZWFtCnicTZLNrRsxDITvWwUbMCD+a+tx8JCD0/81H7VGEMAGuaI4nBmqdcmScHlFSOWS9iW/9Co3yV7y56pVkvfmq6T0lowl5SHvKxctcUtU0toS5ie+L992Mv+C+rrpKSrWnJiJTWWpmA5yUtGbiaBpq6SW6CD2nkoYDKl4it/5xJg5k9ndogFSGj0Ook8FTtouuvnD2Ba31IaBq+wQKyhyG2UMhTKS5tctNlJqwvuK3Od7MxJeeOFzO+es4Zt4I1n4dhwhMdR8cKD+yxwPPtdx4l9mOsna8gK3JoBnRBvNsckcbpCb1YTqiRDNJxvmLxiP7pceb2GHB4WCMatGH06sFCxiIwpeYeyuszwxutm87Z7gMVsgCRrAHOX9SH5fG5F4qzp6x1GQjj+6FUywjFeBScaAXjPXcbsR6Rg9jyrgOJEZ35PkXhuIbK91pif7bsYXOyxmFpyqhsBkicefJ6upORGRoSdyB305b9HzqXzf8Pv6ff38BezAiu8KZW5kc3RyZWFtCmVuZG9iago1MSAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDk1ID4+CnN0cmVhbQp4nEXOQQ6AMAgEwDuv2A+YFCig/zHGQ/3/VdvSeGLCbggujoLdsKnBxRDCOJn0G5UVD/VlDxsZR0pcoBZDnOJQiNfU7O32ox+e2S/1Y8hS9YhMvaze+qTRTdcLagEhrQplbmRzdHJlYW0KZW5kb2JqCjUyIDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMzU0ID4+CnN0cmVhbQp4nEWSuW3FQAxEc1XBBgQsrz3q+Ybh4Lv/1I+UDQcCR7xnuLm3DLEjd4Skhqy15EOvsCk2TL4fRNa7keuQMBN3rKZ4DnldMZb4GuIHu+sLCapfV3lD8SQexrhPCd8V0S0Ri9nYNLE1274uswcpU8OxszoHEeXPM0WptXMeSzYRkE5yXfFi88jqwKYZDNnZXGzOMsw4WsAVH9s5cNVS6RKwnEdo4NtlZbnhRUHR1HGaeA2CuNUoalhCi8CvbK/ri5jSvxUcBRBwDMGHwjfrlnS3tRR0ub0oad/BcrZlTX2Q7spgOjLe1lJY0oV+Q2XJLip4ZwrypJYjWE1LAshpnDqy7ixjli0BcnBBSgfZGD+4Ed4hPWfTLfW85w3QRNw6PN3rKHGqQM9gYnbX/NU4W2Rnt0LO2ZJVHE3zeRYsEnXewYfYwREiZiu6G70b1Wt8X3/v8kG3Z0f/kT7yfl2fPygGhYYKZW5kc3RyZWFtCmVuZG9iago1MyAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDU0ID4+CnN0cmVhbQp4nDMyMVEwUDA3VdA1NlUwNDNUMDc3V0gx5IIxc8EskGQOF1QVmAGSy4GryuHK4EoDABepDogKZW5kc3RyZWFtCmVuZG9iago1NCAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDI5OCA+PgpzdHJlYW0KeJw1UTluxDAM7P0KfsCAecp6zwZBmvy/zczYqUTxmIPsteyyLDurrCusI+3Lj7hvpX6PqKcY19iZY77wj7DP4Wg/l7kjmbbbciOL8rT1ZqK2eTCJik+SJy7RhXoZrM259GWNShN4ENzL1lghvW+rEp9vqwFhARl1X5xxVOLa1t4WNTJA9XzBkJeinFFHAu2ZKVSIUj1CrfXPU3uLWP3o6JhXWMO/lKKPwvXKiSJY61xy2rFe600LLdKh7utZU2FD2FplcoeF6rPUnK01Z8az9vcQn+NHRwneJMsZ5O0G3oJ7iKclXqNgySFi6Y2XzSEcrejgKjhSl/iIwSwgq1t8fLHULEW+Sx2uOR0ib6F4tFD5PjyMyMwOKuGMpAmEyyoKf43Q0/cfOM53LAplbmRzdHJlYW0KZW5kb2JqCjU1IDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMzMyID4+CnN0cmVhbQp4nD2RS27EQAhE930KLmAJKOjPeRxFWTj336bAmixG1BgaikfuLSor5fKtktMlHfJlw6ZJmsovVUgg5Bm2U4IlrkdiQxxT4hy5h9dDS/ET3QB4G90jdLeK+damslsaMxkuoeihwOro6ZXpGXyXS2wyBiM6w7ozu+FM9uKkGl9mjDNYfy0JZ/Aqx6GiSXCZK0Lg2pGGd7TyBCuWuG++ycqoy2UutgmA47nm4ufiQfG0aFjP+GBrVbCef2zP+BmWR3w2Qipbp/Klei1OoDNbKma7BqwtpvzHi9Bc2WCOfoz7TrImLQaiw27iR6AErmULNNw2MVuEWlWHH9m1VJGxusLyNlLxZV0KHBG5iYkRfKmdId1AfWU/OgCRVuTsM1v5KubaEKMP4aAiyjIdvEhtgVMOai0suuAP+S6OvmmhAK/duLj5B9tNhN9/Nz59HAplbmRzdHJlYW0KZW5kb2JqCjU2IDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMjAxID4+CnN0cmVhbQp4nD1QMW4DMQzb/Qp+oIAlSrbvPVcEHdL/r6GUtBMJU7JI8hATO/HFBPdGOvFtgysRNPwOZrEFxkLEBFnouAe9WIAWQk1Ma7yH69divmrC4HHpD5ZCR3jCbSOM8Kn960ixy8DjsCNcAdvUzdoxeaEbbOknzTZub8Xa+HN8EjRJmyK2/J+tziJ2JmJNXRXKo7tcXFf5SmpavnS9KqA2CytlvF+UO927h/RZSorZkdvdu12ftSJWnT3fTD1RaSr3X6/3+BmPF9zLRzcKZW5kc3RyZWFtCmVuZG9iago1NyAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDIxNiA+PgpzdHJlYW0KeJxNUUtuRCEM23MKXwCJfIHzUI26aO+/rcObkbpAtkKIHRNbMZCB7hMhm2fgSxorsiZ+i1Tpp0nIPyYrPkw3JAfWgsyFFJwmO2EG1YQO6BwFpynFSEwIzgatptMsFE6eVA/YcswaYnuDFlyoMZId42qd5qVIZTenZF7U4XVD9nj8rPKwbuXWqfZmnOB2yXoT9go9rUSfsCDo9cYVum3o9huRctNCLqNPaLIL6ZGmu93tvV6XWyJzrNHBOkdQfRlig7YZ2GnJ1GTWB0jcf6jUT/turz8XoUwpCmVuZHN0cmVhbQplbmRvYmoKMTUgMCBvYmoKPDwgL0Jhc2VGb250IC9OYW51bUJhcnVuR290aGljIC9DaGFyUHJvY3MgMTYgMCBSCi9FbmNvZGluZyA8PAovRGlmZmVyZW5jZXMgWyAzMiAvY2lkMSA0OCAvY2lkMTcgL2NpZDE4IC9jaWQxOSAvY2lkMjAgL2NpZDIxIC9jaWQyMiAvY2lkMjMgL2NpZDI0Ci9jaWQyNSAvY2lkMjYgNzAgL2NpZDM5IC9jaWQ0MCA3NSAvY2lkNDQgMTAwIC9jaWQ2OSAxMDggL2NpZDc3IDExMSAvY2lkODAKL2NpZDgxIDExNCAvY2lkODMgMTE3IC9jaWQ4NiBdCi9UeXBlIC9FbmNvZGluZyA+PgovRmlyc3RDaGFyIDAgL0ZvbnRCQm94IFsgLTQ1IC0yODcgMTAwMCA4MzggXSAvRm9udERlc2NyaXB0b3IgMTQgMCBSCi9Gb250TWF0cml4IFsgMC4wMDEgMCAwIDAuMDAxIDAgMCBdIC9MYXN0Q2hhciAyNTUgL05hbWUgL05hbnVtQmFydW5Hb3RoaWMKL1N1YnR5cGUgL1R5cGUzIC9UeXBlIC9Gb250IC9XaWR0aHMgMTMgMCBSID4+CmVuZG9iagoxNCAwIG9iago8PCAvQXNjZW50IDg1MCAvQ2FwSGVpZ2h0IDAgL0Rlc2NlbnQgLTI5OSAvRmxhZ3MgMzIKL0ZvbnRCQm94IFsgLTQ1IC0yODcgMTAwMCA4MzggXSAvRm9udE5hbWUgL05hbnVtQmFydW5Hb3RoaWMgL0l0YWxpY0FuZ2xlIDAKL01heFdpZHRoIDEwNTIgL1N0ZW1WIDAgL1R5cGUgL0ZvbnREZXNjcmlwdG9yIC9YSGVpZ2h0IDAgPj4KZW5kb2JqCjEzIDAgb2JqClsgODkyIDIyNCA4OTIgMjI0IDIyNCAyMjQgMjI0IDIyNCAyMjQgODkyIDg5MiAyMjQgMjI0IDg5MiAyMjQgMjI0IDIyNCAyMjQKMjI0IDIyNCAyMjQgMjI0IDIyNCAyMjQgMjI0IDIyNCAyMjQgMjI0IDIyNCAyMjQgMjI0IDIyNCAyMjQgNDQ2IDI5NyA1ODMgNTgzCjg5MiA4OTIgMjk3IDQ0NiA0NDYgNDQ2IDU4MyAyOTcgNTgzIDI5NyA0NDYgNTgzIDU4MyA1ODMgNTgzIDU4MyA1ODMgNTgzIDU4Mwo1ODMgNTgzIDI5NyAyOTcgNDQ2IDU4MyA0NDYgNjY5IDEwNTIgNjQ0IDYyNyA2MzkgNzIxIDU5NiA1NTQgNzEwIDcxOCAyNDcKNDEwIDYyNiA1MjkgODg0IDcxMCA3NTIgNTg2IDc1MiA2MTAgNTkyIDYyMSA2OTYgNjM1IDk2MSA2MTcgNjExIDU5NCA0NDYgOTYxCjQ0NiA0MzQgNDQ2IDI5NyA1NjAgNTg4IDQ5MCA1ODggNTU5IDM0MCA1ODggNTkyIDI0NCAzMDEgNTMwIDI0NCA4OTIgNTkyIDU3Nwo1ODggNTg4IDM4MyA0NzUgMzU3IDU5MiA1MzAgNzg4IDUyOCA1MzAgNDczIDQ0NiA0NDYgNDQ2IDY2OSAyMjQgODkyIDIyNCAyMjQKMjI0IDIyNCA4OTIgODkyIDg5MiAyMjQgODkyIDIyNCA4OTIgODkyIDIyNCAyMjQgMjI0IDIyNCAzMDMgMzAzIDQ0NiA0NDYgODkyCjg5MiA4OTIgODkyIDg5MiAyMjQgODkyIDg5MiAyMjQgMjI0IDIyNCAyOTcgODkyIDg5MiA4OTIgODkyIDg5MiAyMjQgNDQ2IDg5Mgo4OTIgODkyIDg5MiA4OTIgODkyIDg5MiAyMjQgNDQ2IDg5MiA0NDYgNDQ2IDg5MiAyMjQgODkyIDQ0NiA0NDYgNDQ2IDg5MiA4OTIKODkyIDg5MiA4OTIgODkyIDIyNCAyMjQgMjI0IDIyNCAyMjQgMjI0IDg5MiAyMjQgMjI0IDIyNCAyMjQgMjI0IDIyNCAyMjQgMjI0CjIyNCA4OTIgMjI0IDIyNCAyMjQgMjI0IDIyNCAyMjQgODkyIDg5MiAyMjQgMjI0IDIyNCAyMjQgMjI0IDg5MiA4OTIgMjI0IDIyNAoyMjQgMjI0IDIyNCAyMjQgODkyIDIyNCAyMjQgMjI0IDIyNCAyMjQgMjI0IDIyNCAyMjQgMjI0IDg5MiAyMjQgMjI0IDIyNCAyMjQKMjI0IDIyNCA4OTIgODkyIDIyNCAyMjQgMjI0IDIyNCAyMjQgODkyIDIyNCBdCmVuZG9iagoxNiAwIG9iago8PCAvY2lkMSAxNyAwIFIgL2NpZDE3IDIyIDAgUiAvY2lkMTggMjQgMCBSIC9jaWQxOSAyNiAwIFIgL2NpZDIwIDI4IDAgUgovY2lkMjEgMzEgMCBSIC9jaWQyMiAzMiAwIFIgL2NpZDIzIDM0IDAgUiAvY2lkMjQgMzYgMCBSIC9jaWQyNSAzNyAwIFIKL2NpZDI2IDM4IDAgUiAvY2lkMzkgNDkgMCBSIC9jaWQ0MCA1MCAwIFIgL2NpZDQ0IDUxIDAgUiAvY2lkNjkgNTIgMCBSCi9jaWQ3NyA1MyAwIFIgL2NpZDgwIDU0IDAgUiAvY2lkODEgNTUgMCBSIC9jaWQ4MyA1NiAwIFIgL2NpZDg2IDU3IDAgUiA+PgplbmRvYmoKMyAwIG9iago8PCAvRjEgMTUgMCBSID4+CmVuZG9iago0IDAgb2JqCjw8IC9BMSA8PCAvQ0EgMCAvVHlwZSAvRXh0R1N0YXRlIC9jYSAxID4+Ci9BMiA8PCAvQ0EgMSAvVHlwZSAvRXh0R1N0YXRlIC9jYSAxID4+Ci9BMyA8PCAvQ0EgMC44IC9UeXBlIC9FeHRHU3RhdGUgL2NhIDAuOCA+PiA+PgplbmRvYmoKNTggMCBvYmoKPDwgL0JCb3ggWyAwIDAgNzIgNzIgXSAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDE1MgovTWF0cml4IFsgMSAwIDAgMSAwIDEzNi44MDQzNzUgXSAvUGFpbnRUeXBlIDEgL1BhdHRlcm5UeXBlIDEKL1Jlc291cmNlcyA8PCAvUHJvY3NldHMgWyAvUERGIC9UZXh0IC9JbWFnZUIgL0ltYWdlQyAvSW1hZ2VJIF0gPj4KL1RpbGluZ1R5cGUgMSAvVHlwZSAvUGF0dGVybiAvWFN0ZXAgNzIgL1lTdGVwIDcyID4+CnN0cmVhbQp4nCWPMQ7DMAwDd72CHxDgOIrirF265w9tl3jJ0u+XVCHCgCnrRDc01vm0Bar7U/e9S/cLb/pfM18T1DQeSxu46DRQ06LT6XJ6gKIzcKSMZYCatgWOVgbfdhrZMEJGQtBM7GJq87T/7ssSriY7KRoHvYY5maIR7YUnexONy70CcHuIx3xeGRUwxGR8r3/oE6uw9rAfJbMxHAplbmRzdHJlYW0KZW5kb2JqCjU5IDAgb2JqCjw8IC9CQm94IFsgMCAwIDcyIDcyIF0gL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAxNjIKL01hdHJpeCBbIDEgMCAwIDEgMCAxMzYuODA0Mzc1IF0gL1BhaW50VHlwZSAxIC9QYXR0ZXJuVHlwZSAxCi9SZXNvdXJjZXMgPDwgL1Byb2NzZXRzIFsgL1BERiAvVGV4dCAvSW1hZ2VCIC9JbWFnZUMgL0ltYWdlSSBdID4+Ci9UaWxpbmdUeXBlIDEgL1R5cGUgL1BhdHRlcm4gL1hTdGVwIDcyIC9ZU3RlcCA3MiA+PgpzdHJlYW0KeJx1jzEOwzAMA3e9gh9wITuK4qxdsvcPbZd4ydLvl3TnwoQBU9aJcjjP4zC/rV739K3Hgv+P6z0btiZdT7ys4mNWlgQ1jFf1jpOOgxoWjU6T0wIUnY49ZdQOatga2H0a/NtopKOHjISgmdjE1ORhv9mnJYqKrKRobCyzmZ0pGtFl4sleRePwMgNweojHfGVmVMAQk/HL3ENLLMLa3b5HkDfECmVuZHN0cmVhbQplbmRvYmoKNSAwIG9iago8PCAvSDEgNTggMCBSIC9IMiA1OSAwIFIgPj4KZW5kb2JqCjYgMCBvYmoKPDwgPj4KZW5kb2JqCjcgMCBvYmoKPDwgL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMTEyOCAxOCAwIFIgL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMTE5OCAxOSAwIFIKL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMTIzNCAyMCAwIFIgL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMTU2MCAyMSAwIFIKL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMTc3OCAyMyAwIFIgL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMTgxOSAyNSAwIFIKL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMTk5MiAyNyAwIFIgL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMjA1MCAyOSAwIFIKL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMjA3MyAzMCAwIFIgL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMjI0MSAzMyAwIFIKL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMjMzMyAzNSAwIFIgL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMjYzMyAzOSAwIFIKL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMjYzNSA0MCAwIFIgL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMjc2OCA0MSAwIFIKL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMjg2NCA0MiAwIFIgL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMzEwNCA0MyAwIFIKL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMzExNCA0NCAwIFIgL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMzE2NyA0NSAwIFIKL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMzI0MCA0NiAwIFIgL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMzI5NyA0NyAwIFIKL0YxLU5hbnVtQmFydW5Hb3RoaWMtY2lkMzM3OSA0OCAwIFIgPj4KZW5kb2JqCjIgMCBvYmoKPDwgL0NvdW50IDEgL0tpZHMgWyAxMSAwIFIgXSAvVHlwZSAvUGFnZXMgPj4KZW5kb2JqCjYwIDAgb2JqCjw8IC9DcmVhdGlvbkRhdGUgKEQ6MjAyMTEwMDQyMDI2MDIrMDknMDAnKQovQ3JlYXRvciAoTWF0cGxvdGxpYiB2My40LjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcpCi9Qcm9kdWNlciAoTWF0cGxvdGxpYiBwZGYgYmFja2VuZCB2My40LjMpID4+CmVuZG9iagp4cmVmCjAgNjEKMDAwMDAwMDAwMCA2NTUzNSBmIAowMDAwMDAwMDE2IDAwMDAwIG4gCjAwMDAwMjE0MjcgMDAwMDAgbiAKMDAwMDAxOTU2MCAwMDAwMCBuIAowMDAwMDE5NTkyIDAwMDAwIG4gCjAwMDAwMjA1ODYgMDAwMDAgbiAKMDAwMDAyMDYyOSAwMDAwMCBuIAowMDAwMDIwNjUwIDAwMDAwIG4gCjAwMDAwMDAwNjUgMDAwMDAgbiAKMDAwMDAwMDQwMiAwMDAwMCBuIAowMDAwMDAyNjU2IDAwMDAwIG4gCjAwMDAwMDAyMDggMDAwMDAgbiAKMDAwMDAwMjYzNSAwMDAwMCBuIAowMDAwMDE4MjE0IDAwMDAwIG4gCjAwMDAwMTgwMTEgMDAwMDAgbiAKMDAwMDAxNzUzOCAwMDAwMCBuIAowMDAwMDE5MjU5IDAwMDAwIG4gCjAwMDAwMDI2NzYgMDAwMDAgbiAKMDAwMDAwMjc2NiAwMDAwMCBuIAowMDAwMDAzMTMzIDAwMDAwIG4gCjAwMDAwMDM0MzIgMDAwMDAgbiAKMDAwMDAwMzY5OCAwMDAwMCBuIAowMDAwMDA0MDE3IDAwMDAwIG4gCjAwMDAwMDQzMTEgMDAwMDAgbiAKMDAwMDAwNDYzMyAwMDAwMCBuIAowMDAwMDA0ODQyIDAwMDAwIG4gCjAwMDAwMDUxMTcgMDAwMDAgbiAKMDAwMDAwNTQ2MiAwMDAwMCBuIAowMDAwMDA1NzIwIDAwMDAwIG4gCjAwMDAwMDYzMDcgMDAwMDAgbiAKMDAwMDAwNjU1OSAwMDAwMCBuIAowMDAwMDA2ODE0IDAwMDAwIG4gCjAwMDAwMDY5OTUgMDAwMDAgbiAKMDAwMDAwNzQ0MiAwMDAwMCBuIAowMDAwMDA3Nzk4IDAwMDAwIG4gCjAwMDAwMDg0NTAgMDAwMDAgbiAKMDAwMDAwODc4OSAwMDAwMCBuIAowMDAwMDA4OTM1IDAwMDAwIG4gCjAwMDAwMDk2ODEgMDAwMDAgbiAKMDAwMDAxMDMxNiAwMDAwMCBuIAowMDAwMDEwODU2IDAwMDAwIG4gCjAwMDAwMTE0MTUgMDAwMDAgbiAKMDAwMDA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      "text/plain": [
       "<Figure size 3000x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mglearn.plots.plot_group_kfold()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 그리드 서치(Grid Search)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 간단한 그리드 서치"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "훈련 세트의 크기: 112   테스트 세트의 크기: 38\n",
      "최고 점수: 0.97\n",
      "최적 파라미터: {'C': 100, 'gamma': 0.001}\n"
     ]
    }
   ],
   "source": [
    "# 간단한 그리드 서치 구현\n",
    "from sklearn.svm import SVC\n",
    "X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target,\n",
    "                                                    random_state=0)\n",
    "print(\"훈련 세트의 크기: {}   테스트 세트의 크기: {}\".format(\n",
    "      X_train.shape[0], X_test.shape[0]))\n",
    "\n",
    "best_score = 0\n",
    "\n",
    "for gamma in [0.001, 0.01, 0.1, 1, 10, 100]:\n",
    "    for C in [0.001, 0.01, 0.1, 1, 10, 100]:\n",
    "        # 매개변수의 각 조합에 대해 SVC를 훈련시킵니다\n",
    "        svm = SVC(gamma=gamma, C=C)\n",
    "        svm.fit(X_train, y_train)\n",
    "        # 테스트 세트로 SVC를 평가합니다\n",
    "        score = svm.score(X_test, y_test)\n",
    "        # 점수가 더 높으면 매개변수와 함께 기록합니다\n",
    "        if score > best_score:\n",
    "            best_score = score\n",
    "            best_parameters = {'C': C, 'gamma': gamma}\n",
    "            \n",
    "print(\"최고 점수: {:.2f}\".format(best_score))\n",
    "print(\"최적 파라미터:\", best_parameters)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 매개변수 과대적합과 검증 세트"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "hide_input": false
   },
   "outputs": [
    {
     "data": {
      "application/pdf": 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      "text/plain": [
       "<Figure size 4500x300 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mglearn.plots.plot_threefold_split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "훈련 세트의 크기: 84   검증 세트의 크기: 28   테스트 세트의 크기: 38\n",
      "\n",
      "검증 세트에서 최고 점수: 0.96\n",
      "최적 파라미터:  {'C': 10, 'gamma': 0.001}\n",
      "최적 파라미터에서 테스트 세트 점수: 0.92\n"
     ]
    }
   ],
   "source": [
    "from sklearn.svm import SVC\n",
    "# 데이터를 훈련+검증 세트 그리고 테스트 세트로 분할\n",
    "X_trainval, X_test, y_trainval, y_test = train_test_split(\n",
    "    iris.data, iris.target, random_state=0)\n",
    "# 훈련+검증 세트를 훈련 세트와 검증 세트로 분할\n",
    "X_train, X_valid, y_train, y_valid = train_test_split(\n",
    "    X_trainval, y_trainval, random_state=1)\n",
    "print(\"훈련 세트의 크기: {}   검증 세트의 크기: {}   테스트 세트의 크기:\"\n",
    "      \" {}\\n\".format(X_train.shape[0], X_valid.shape[0], X_test.shape[0]))\n",
    "\n",
    "best_score = 0\n",
    "\n",
    "for gamma in [0.001, 0.01, 0.1, 1, 10, 100]:\n",
    "    for C in [0.001, 0.01, 0.1, 1, 10, 100]:\n",
    "        # 매개변수의 각 조합에 대해 SVC를 훈련시킵니다\n",
    "        svm = SVC(gamma=gamma, C=C)\n",
    "        svm.fit(X_train, y_train)\n",
    "        # 검증 세트로 SVC를 평가합니다\n",
    "        score = svm.score(X_valid, y_valid)\n",
    "        # 점수가 더 높으면 매개변수와 함께 기록합니다\n",
    "        if score > best_score:\n",
    "            best_score = score\n",
    "            best_parameters = {'C': C, 'gamma': gamma}\n",
    "\n",
    "# 훈련 세트와 검증 세트를 합쳐 모델을 다시 만든 후\n",
    "# 테스트 세트를 사용해 평가합니다\n",
    "svm = SVC(**best_parameters)\n",
    "svm.fit(X_trainval, y_trainval)\n",
    "test_score = svm.score(X_test, y_test)\n",
    "print(\"검증 세트에서 최고 점수: {:.2f}\".format(best_score))\n",
    "print(\"최적 파라미터: \", best_parameters)\n",
    "print(\"최적 파라미터에서 테스트 세트 점수: {:.2f}\".format(test_score))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 교차 검증을 사용한 그리드 서치"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(C=10, gamma=0.1)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for gamma in [0.001, 0.01, 0.1, 1, 10, 100]:\n",
    "    for C in [0.001, 0.01, 0.1, 1, 10, 100]:\n",
    "        # 매개변수의 각 조합에 대해 SVC를 훈련시킵니다\n",
    "        svm = SVC(gamma=gamma, C=C)\n",
    "        # 교차 검증을 적용합니다\n",
    "        scores = cross_val_score(svm, X_trainval, y_trainval, cv=5)\n",
    "        # 교차 검증 정확도의 평균을 계산합니다\n",
    "        score = np.mean(scores)\n",
    "        # 점수가 더 높으면 매개변수와 함께 기록합니다\n",
    "        if score > best_score:\n",
    "            best_score = score\n",
    "            best_parameters = {'C': C, 'gamma': gamma}\n",
    "# 훈련 세트와 검증 세트를 합쳐 모델을 다시 만듭니다\n",
    "svm = SVC(**best_parameters)\n",
    "svm.fit(X_trainval, y_trainval)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "사이킷런 0.22 버전부터는 `GridSearchCV`와 `RandomizedSearchCV`의 `iid` 매개변수 기본값이 `True`에서 `False`로 바뀝니다. 0.24 버전에서는 이 매개변수가 아예 삭제될 예정입니다. `iid` 매개변수가 `True`이면 독립 동일 분포라고 가정하고 테스트 세트의 샘플 수로 폴드의 점수를 가중 평균합니다. `False`로 지정하면 단순한 폴드 점수의 평균입니다. `False`일 때 기본 교차 검증과 동작 방식이 같습니다. 사이킷런 0.20 버전에서 `iid` 매개변수가 기본값일 때 가중 평균과 단순 평균의 차이가 10^-4 이상이면 경고 메세지가 발생합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "hide_input": false
   },
   "outputs": [
    {
     "data": {
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XD6q/xaS19tgk78/uFSkfWlWfGm5U9DIXH33m4+OjtfbsJH/bPd2e5NSq+sYQQ6KH+cN4aK29LMkfpzNO/5XO79E1A+zvcenMVZLkpiTHVNVCrv47ttyDGH3m4uPBfHw8tNbum06y1kHdoqdW1blDDIke5g/jobX2sSQPTWec/ndV/fmA+1uWTuLyid0+71tVXxlknwAAMGqWDTsAYDxU1XeT/I90bia3JK9srS3k1uXs38e6/7Ykf9xau8P+Lp6v1tqZ6SQsJMkNSf51kP0tIh/o/tuSvLC19oj9XdwHr08nYSFJfihhYeaq6uwkH+yeHpLkjUMMhym6N9sfn85qRUlnFb3XDC8i9sX8YfR1H4r67ST/r1t0VHY/2MZoeE/P8TNaa88YVEfdJJZzszth4TsSFmbsbT3Hv5zkba21gWzx3lq7TTrzlMkt7M/3wOHMVdU/J3lF97QleX1r7aD9VGGBmYuPPvPx8VFVf5/dv0MTSQa+yAWz8raeY/OH0fWWJFu7x3dI8qnW2s8MoqPW2kOT/GP3tJJ8yAOHM+cexOgzFx8P5uPjoar+NcnvZ/ffvL9ura0eblT0MH8YD5N/61qSl7TW7jPg/v44nYSFJPmJhAUAAJYiSQvAjFXVv2T3Q1Ork5w9vGiY4q1JbkznZtStk3yutfbAQXTUWntmkr/unlaS86pq+yD6WoTem86KKpXO6jf/1Fp7ZXdHhL5prR3RWjs3yX/vFlU6/40wO7+V5Mfd4zMWIMmEWaiqjUl+PZ0b/y2dB3nvNtyomI75w+irqm1JnpjOXKIleXxr7bThRkWPjyT5t+7x5EMd7+g+eNY3rbU7Jvlikof0FL+hn30sZlV1YZL3pTNGSfLUJN9urf16vx7Caa2taK39dpL/yJ5byb+2H+0vMa9McmH3+PZJnjnEWJieufiIMx8fK89LMrk68r1aa08dZjDsZv4wHqrqqiSvyu5xumeSb7bW/q61tq4ffbTW1rXW3p7ko+k8IJx0/r6+sh/tLyXuQYwFc/HxYD4+BqrqjUk+3T09Jp15HyPA/GFsvCPJT9L5HPWwJJ9srT2935201iZaa69O8uJuUSV5Z7/7AQCAcdAGuNswsAi11o5LckmSlUk2prON+KbhRkWSdFfdfUM6Nzomt1f+RDqreXy4+0DiXNtenuQxSZ6b5H7ZfZNtQ5K7VdWVc498aWmt3S+dLXsnsnucrktnVeP3J7lgLiugdD/Mvk+SJ6XzIffh2T1O302yzsoqs9dae2KSd6czTl+rql8ackhM0Vr7wyQvT2eMPlBVTxhuREzH/GE8tNaenc4uC5XkM1X14CGHRFdr7S5JvpzOQzeT84cdST6Z5LwkX66qi+bQ7knpzO2elM5W6JMLG7R0dtJ6QFXtnPc3sES01takM04/kz3n5Ncl+XD3axckubSqbpxBe6uS3C7JL6QzTo9JZzeUyXZbktdX1bP7/K0sCd3V876azs/yiiS399/7aDEXHw/m4+OhtfbgdO4RVZLvVdVdhxwSXeYP46G7I9l7kjwhe45TklyWnnFKcnmSHyW5JcnmqtrSvW+3qvs6Np0Vdm+X3eN08mRXPe3+dlVNrprMLLgHMfrMxceD+fh4aK3dOcl/prOb0jVJTqiqrfuvxUIwfxgPrbVfS/KBydN0d59N8g9J3l9V6+fR9nHp3Hf9vXQSiCc/t70yyd2r6oa5tg0AAONK0gIwa621/5HOihBJ8vdVdfF+LmcBtdb+Isnzs/fNry3prNA77c2v7tf3d/PrF5IcPNlN99+tSX6tqj45yO9pMWqtPS7Ju5KsmCzK7rHakeTbmf043SOdD+J622vdNs6oqksH+T0tZq21b6bz8006yR//tp/LWWCttYPT+X05Np3fnztU1eXDjYrpmD+Mvm6S4g/SWemwktylqr4/3KiY1N394kNJjszec72kk0z6w8xu/nBMbxc97X4zya9W1XUD+nYWrdbaMUn+Jcmp2f3zTPYcqyTZlAOP05FTm+9pqyU5J8nvlRs7c9Zae2M6/6+TJP+jqr41zHjYm7n46DMfHx+ttU9m99+8B3ZX+WcEmD+Mh9basiSvSfKC3uLuv/P5eU4do5uTPKOq3j2PNpc89yBGn7n4eDAfHw+ttZcmmVy9/yVV9Z1hxsNu5g/jobX23CR/PXna/XdyfH6U5GuZ2+frt+1pc3KsNqRz3/UbA/uGAABghElaAFhkWmtnprPF+8HZ/weds2q2p42WzrbAT6qqL8yjzSWttfZzSd6W5O7ZPTat55LZjtfUMUqSjyf5raq6eo5hkqS1tjKdm41JcqMP9kdPa+2e6dwETpIvVdW1QwwHxlp39afJB9kvqqqbhxkPe2qtHZ/kjUke3i3qfd9PT9mMmptSpyXZ2W3/hVV1yzxCXdK6CUDPS2fL9yO6xdPN9zLlaznANZPlVyR5QVWdN79IYfSZi48H83GYP/OH8dFa+4Ukr0rywJ7i/Y3VvkytszOdXVjPrqofzidGgH4xH4f+MH8Yfa21R6ST4Ls2e/+c5/K3b2rdluQ/kjyxqr471zgBAGDcSVoAWIRaaycm+cMkT8nuG8q9f/BncgNsuutvTPKGJH86ky3p2b/uCitPSvKcJL845cuzeYOe+tDh55L8RVV9Yn4RAgCjqLvrwnOTPDLJIVO+PJM5xNS54MYk5yX5K6vx9U9r7dAkT0vyG0num2RiH5fOZJ6+Lcnnk7wjyXuralufwgQARoj5w/hord05yROTPDjJvdNZZXe2tqWzcu9Hk7y7qi7rX4QAwKgxfxhtrbXVSX4/ybOSHNfzpZl+xr6v6y5J8pdJzqmqHfONEwAAxpmkBYBFrLW2Jslj0rn5dd8kJ82hmcuTfDGdm18ftOLyYLTWbpvd43SPJKckOXQGVW9OcnGSb6UzTh+vqisHFScAMDpaawcnuV/2nD+ckGTNfqptTGel3Yuye/7wxaraMthol7bW2iHpbAvfO05Hp7OS8sp0HkjcnmRrOtvEX5M9x+mr5uEAsLSYP4yP1tpBSX42sx+n71TV1iGEDAAMmfnD6GqttSSnZ8/PbY+YRRM3Zvd9149W1Zf7HSMAAIwrSQsAS0g3ieGOmfnNr4ur6vqhBMvkeO13nIwPADBVa2159jF/sMIuAAAAAMDMtdaOygw/X6+qnw4pTAAAGHmSFgAAAAAAAAAAAAAAgIFYNuwAAAAAAAAAAAAAAACAxWli2AEAAAAALBWttSOSnJjkqOzeTv6g7N5O/oYk1yZZX1XXDyVIkiSttcNygHGqqg3Dig8AGA2tteVJfibJKZnhPC/JRUm+W1U7Fj7ipau1tjrJHTPzcbq4qjYOI9alzlwcAAAAYPFpVTXsGACAJK21OyS5b5J7ZPYfcn4ryflVddlCx73UGKfx0Fo7MXMco6q6fOEjBmCxaq2dluSh2T1/OHIW1a9Pd/6Q5GNV9bX+R0iStNZOSPLg7B6nOyY5fAZVN6Vnnpfkk1X140HFudSZiwMwKlprJyf5jXTmefdJsmIOzWxN8pUkH0tyblVd0b8ISXYlKTw6u+fjt5tDMz9Mdz6e5MNVtblf8dFhLg7AKGqtrUpnnjfXexAXVNWWhY4bAABGmaQFABii1tpxSX4vyROTnDzdJQdoYuob+feSvD3JG6vqhnkHSBLjNC5aa7+Szhg9JMkJ82hqfTofRL+jqr7Sj9gYvNbarZLcIcl/WZkcGLbW2sFJnpPk2el8oLnrS3NorncecVGSP0/yD+WGTl+01p6Q5Kwkp2XP8ZnNWPWOxc4kn07y2qr67PwjxFwcgFHSWrtXklelc+9h8j2o971oJnO06a7fkeQ9Sf53VV05zzCXvNbabZK8NMlvJjlksnjKZfsbq31duyHJ3yV5TVXdPN84lzpzcQBGTTdR4cnp3IO4f6ZPTJ3ufWq6ecWWJJ9L5x7E++2wBQAAkhYAYChaa4ck+ZMkZ6azEsd0H1bO5MOZ6a6tJBuTvLiqXjfPUJc04zQeWmuPTvKnSX52sqjny7OZ7E5X71+TPLeqvjnnABm41tpLkvxhkol0Vjb6k6p65XCjApaq1tqDkrwlyfHZ/d4ym3nDVFPrVpILkjzWKqJz11q7W5K3Jfm5yaLMf5ymjvc/JfmtqrppjmEuaebiTGqtPTLJnZP8oKo+POx4gKWrtfbKJGcnWZb5zx0m9bZR6TwU/9iq+sI82lzSWmtPT/LXSQ7NnvOz+Y5Tb1s/TPLIqvruPNpcsszFSZLW2q2T/EE687zvJ/kL/48LDEtrraWTSPey7N4ldep7S6aUT1XTXDNZ9sN0Pmv66PwiBQCA8SZpAQAWWGvtDkk+muRO2fcHMjcmuSLJVUluSbK5+1qRZFWSg5Mcm+Sk7L55luz9Qec5Sc6sqp2D+F4WM+M0+lprK5O8OZ1Vb5LdP8/pbhhvz77HaLqVcnrb2Zrkt6vq3X0Lnr5prd0/ydSHOSrJGVX1xSGEBCxhrbVnJfnbdB5kS/Z8P/lJOskGl2bm84fbJfnFdBIgprb3wyQPrqqLB/X9LFbdhMdz0/l5T50/7Ejyncx+nO6ezoP16WmvkvxbkodX1dUD/rYWFXNxkqS1tizJx5P8ak/xZ5M8xHgBC6219s4kT8rec4f1Sb6S5KuZ/fzhl5LcN8ltu21Ntrslya97qG32WmuvTvKi7D1OW5N8M3Mfp3VJVnbbmmz3hiQPraoLBvpNLTLm4iS7dkz99yTH9RRfmeSedlAFFlpr7cgkH0hnZ4X9JTzelORH2f970xFT6kxNrHtpVb26v98BAACMD0kLALCAWmvHpfOw2nHZ80bVd5Ocl+6HnLO5Md9aW53Oh2f3S+fh7Ttmzw9nXl9Vz+nX97AUGKfR11o7KMknkzwge37AuSOd3RH2eGCgqq7ZT1uHZ88Pou/XfS3LnmP0u1X11sF8R8xVa+35Sf4iez+A+MKq+uuhBQYsOa21RyX5l+z5vvTddFYQPa+qfjiPtm+X5KlJnpHkhJ72/z3Jfapq29wjX1paa6cm+Vw6HypP/hyvT/KedOZ5X5vLaqyttYPTSTB5apInJjmk+6VKcn5V/fL8o18azMWZ1Fr79STvm1JcSX6jqt4/hJCAJaq19uJ0dv+ZfO/Yns7OWm+tqq/1of37Jnleksf19HFtkrt62HrmujssnJM97w98Mslbk3yoqrbMo+2VSZ6QzgrM98nucfphkntU1aa5R750mIszqbX22+ksRjP1Yd5nVNVbhhYYsOR0Px/6UpK7Zs97etcn+XB6Pmuqqhtm0N7q7PlZ02OSHJ4970H8YVW9qr/fCQAAjAdJCwCwgFprn0zyoOy+OfXlJM+vqq/2sY9HJvn7dB5om7wB9pCq+nS/+ljsjNPoa639TZLnZs/V7f4syT/2Yxvx1tpJ3fafm2R5t4+bktyrqi6Zb/v0T2vt4Uk+kr2TFh5VVR8bWmDAktJ9SOaSJGvT+Ru0McmLqupNfe5nVZI/T/Kc7P6790dV9Sf97Gexaq1NpLNy6+QD69uT/GWSV1TV5j72c0w6DzI+sltUSc6qqtf1q4/FzFycSa21/5nkr7L3PO8FVfU3QwoLWGK6yXSXZPcujd9O8qSq+vYA+npckndm94r+b6mqZ/S7n8Wou2r7pUkO6xZdleTpVfV/B9DX89OZk08+aP3XVfXCfvez2JiL06u7S+HfZ+953rOr6g1DCwxYclpr70pnN63JexCXJnlxkn+uqq19aP+QJL+d5FVJVnf72Jbk1Kq6cL7tAwDAuJG0AAALpLX2gHRWkpp8831tVZ09oL6OSPL5dLbGbumsKHXGIPpabIzT6Gut3THJ97L7w+HPp/PAQN9XH2yt/WKSjya5VbfovKp6Yr/7YX5aa/+Y5Gk9Re+oqv8+rHiApae19owkb0hn/rApyYP7+YD1NP29NskLuqfrq+p2g+prMWmtPTmdBwEnH5J6QlV9aID9TX7wnSTfq6q7DKqvxcJcnF6ttZ9PZ9eNyXl/S7IzyS94uANYKK21lyX543Tem/4rnQfM9rmbYx/6e2KSd3dPNyS5dT8emFvspuzCeHWS+w1y0YnW2vPSeeA+SX6a5DZVtXNQ/S0G5uL0aq2dkOQ/kqzJ7geFNyS5e1VdMczYoB+6iyINTVWtH2b/46K19nNJvpHd9yDOTfI7/Uym6+nrdunc75j8b+PjVfXIfdcAAIDFSdICwCLQWjt9mP1X1fnD7H9ctNbOSfL0dG5+faCqnjDg/m6b5PvprAS3M8ltq+rKQfa5GBin0ddae3WS/5XOGH0znQ+ibxlgf7+c5DPd01vSeWBg06D6Y25aa/dMckqSi6rqW8OOB/qltfbWIXZfVfX0IfY/NlprH03ysHTem15cVX824P6Wp7Py2wndPn+pqr42yD4Xg9baPyV5bDo/sz+rqhcPuL+Dk6xPclS3z3tV1X8Mss9xZy7OVK21p6ezmvWt0tld7UVV9eahBgV90lr7ryF2X1V18hD7HxuttS8lOS2d96anVtW5C9Dn15P8fLfPB1fVZw5QZclrrX0myS9nAVdqb619L8mdun2eUVVfHHSf48xcnKm69/Jenu79vHR23fi3oQYFfdJa25ndD8IvtKqqiSH1PVZaa/9fkrPSGavPJ3nQIJMQW2v3SHJhkmXp7LZwXFVdO6j+AABgFPmfFYDF4fMZ4s2veD+ZqdN6jl856M6q6rLuh0FPSmelovsk8QDOgRmn0ffAnuOXDjJhIUmq6nOttc8nOSPJqiT3S/KJQfbJ7HUTFSQrsBj9jwxnnte6/UpamJl79hy/cdCdVdWO1tp7krywW3RKEkkLB7au5/hvB91ZVd3SWjs3yXO6RXdJZzVR9s1cnD1U1VuSvKW1dvQgVzaHIblddq8uvdCsZjVzP9P9d2eS9y9Qnx9KJ2kh2b0aL/t3157jty9Qn+cleUn3+HZJJC3sn7k4e+jey3vssOOAARrGHI/ZeUDP8R8Oetekqvr37sInj0rns/VTk3xkkH0CAMCoWTbsAADoqzakFzNz2+6/t1TVvy9Qn9/oOT5+gfocd8Zp9J3S/Xd7kk8uUJ+f7jk+YYH6BOhl3jXajknn4b+fVtUNC9TnJT3Ht1mgPsfdrbv/Xl9VP1qgPr/Xc3zcAvU5zszFmZaEBRa5iiSCUbYmnfH5cVVtW6A+exPojl2gPsfdkdk9TjcvUJ+X9Rybjx+YuTiw1FTM80bd7bv/bq2qf12gPnv7cQ8CAIAlx8rYwKy11pals6Ln47pFH0jyl1W1Y5ZtvKDbRkvyz0n+YjZtMK3JG18eaBtNK9IZow0L2OeNPceHLmC/48w4jb7V6YzR1YNe+abHj3uOj1qgPmEoWmstyZ27p9+vqll/sNZt407pzEnm1AZ7Mc8bbTuSHJTOjjwLZWXP8UI9QAeDZi4OA9Rau22Sh3VPP15Vl+3v+n20cVK3jZbkE1X1w/5FuGRN7nD1xXRW82e03JzksCRHL2CfvfcdFvI9cZxtTXJIksMXsM/evm5awH4B9tJa+2/p+dy2qt43hzaekJ7PbavqvX0McanZmM7nGJPzvL/Onv/vyWg4JJ3xWcgk+Wt7jo9YwH4BAGAkSFoA5uLPkjy/e9yS3CedlUX/YJ5tHD3LNtjtqnRWc5q8+fWSbhmj5bp0Vke7dWvt4Kq6ZQH6vG3P8Y/3eRW9jNPo25TOSofHttaWLVDiwtqe4+sWoL8lqfug+5p0HsQ9KJ3dNLYmuWEBE1SWtNbayekkk961W/Tt1trjquriWbbxgSR36xZ9p7X22Nm0wR7eneTJ3eNK8uiqsm346LkyyclJDmutnVxVlxyoQh/cred4oVYqHXc/SXJSklu11tZW1ULMu+7cc2ycDsxcHAaktfaQJP+U5OBu0ebW2uOr6hML2QZ7ODPJ32d3cuqnqupPhhgP07s0yT2SrGitnVpVX16APk/tOXaPd2bWJ/mZJIe01u6xQDs2/XzPsXnegZmLw4C01l6U5NU9RU9ord2uqv58nm3cdjZtsIdfTfKJ7H4o/cSq+m/DC4d92JDObk1rW2sHLdCuWr27K/x0AfoDAICR0ix4CcxWa+0n6SQp9K72enVVrd13rf63wW6ttTsk+Uw6N/2T5AtJHmhV49HSWvtMkl9O57/7Z1XVmxagz28n+dlun79SVV8YdJ/jzjiNvtbaBUnunc7P6xEL8YBMa+1TSR7Y7fNRVfWxQfe5mLXWVia5b/d1jySnJDkxnYSFfa0if2M6DyFclORbSc5P8v8W6IOEJaPnb2Cvz1XVAxeyDXbrJvO8PclTukXXJLl7Vf1keFExVWvtXUmelM77xJuq6lkD7m9NOn8TD+v2eZeq+v4g+1wMWmv/lOSx6fzMXlNVLxlwfyuTXJ5Ogn4lWVdV3xxkn+POXHzxaa0dkc4876h0HtjZKzk1nZUm11fV9UMJcolorf1nkrtMKf52Vd19IdtgT621Zyf52+7p9iSnVtU3hhgSU7TW/k+S56TzPvG5JA8a5D3X1tpd0vl/3uXp7OZ1fFVdPaj+FovW2puT/HY64/RPg34wtLV2fJKL03lfqyS3r6r1g+xz3JmLLx6tteXpJAlN3s874Dwvnft537Xb+mC01tYnOWFK8ZVVdeJCtsH/z959x8lW1Okf/zxkBATJkgVJIskVlKCAAQwoCILiGlZUVGBdUUQFMaGCyMpPXRdEMQCCiiCKCCpJXSWqqKAICEiUfMnx8vz+qNP0mZ7uudPT3dMTnvfrNa853bemTs2c26erq+r7rZEkbUWZu12weurNtk8aYpOihaT/A7akvE+8aTJ2F5F0ESWZo4FX2P7loM8ZERERETGVJGghIrom6UZgpZanb+ly8KvnOmIkSesDF1AWLgHsZ/vLQ2xStJD0QeAL1cPbgK1sXzvA8+0N/E/18B5gBdtPDOp8M0Wu09Qn6TDgAMqg7mXA1oPMwitpa8oCeSgTbsvbzlbOEyBpM+A/gZ0o22M/9U9dVFP/AHMv8H3gSNtX9d7CkHQfsFj9KeB+20tOZh0xkqQFKQukGpNoA1+EE92R9BrgxzTvUQNbbF0FspwBvKI631+zWHR8JP07cHz18HFgF9tnDPB83wT+o3p4ne21BnWumSJ98elP0paU+1MjOHXpLn78HprBqT+zfUn/Wzh7SZpDc8wISh/tPttLTWYdMZqko4B3Vw//aPvfhtmeGEnS84BLafbzTgDeZfuxAZzrmZR74FrV+c5P8Pf4SNoWOJfmdRrYonhJTwPOp5lQ4xLbLxzEuWaS9MWnt2pXzTdQ+nmbAQtNoJrHgAuBnwEn2b6pfy2c3apEccvWn2JiyeZ6qiNGk/Ru4Kjq4e3As20/MMQmRY2kg4FPUd7Pr6UEEN85wPPtAvywevggsJztRwZ1voiIiIiIqWi+YTcgIqalr1IGq+pf/zuEOqLG9t8og/CNv+chkpYd84disn2TkincwArAeZIGMvFYDYQeWT00cHIW34xbrtPUdyzwZHW8CfDjQd3vJG0InFI9NPCLBCx0T9KKkk6lTEz+O2WhUzeBCm2rpWRx2wu4XNLhkvL5pnetmdrd5rnJqCNqqh1F3kh5fxKwa7UoNKaOnwJ/rI4FHCXp+GrhWd9IejbwG2CH2tNH9/McM9z3KZPQpmQ6PEXSIVUW1r6RtJSkk4C3VU+Z0seMeUtffBqStKikD0m6nnKPOgjYlpJ1t3XsZ6yvpauf+zhwoaQrJe1ZBWtF785nZB/c1XOTXUeMth8lYzvAJpLePMzGxEi2/wD8gOb//TcDV0h6fRVc3DNJC0naE/gLsGbtn77Q4Ueihe3zKdmsG+8pH5H0K0nP7+d5JL2EEmBXDy5K4qDxSV98GpK0iaQzKOM6h1ACUxem+VobVzXV18LAi4HDgGslHVftWhK9O4Hm9Wh8/+4Q6ogWtr8GnF09XI7S74up41hKQBWUPtgvJa03iBNJegXwneqhgZ8kYCEiIiIiZqPstBAREyLpTcDO1cPTbJ84gTr2oGwHDPBj2xn86gNJJ1IWtZmSeXr/ITcpaiTtRVlYZsrAr4GzKANjp1eLEida9/yU1+X7gK1pDizfCzzX9s0Tb/nskus09Un6MrAvzQx6c4BDgeNs396H+lcA9gE+RMkcJkqgxFa2L+q1/tlE0ubA6ZRMXY3XU31S817gn8BNwC3Aw8Aj1ddCwCLAosDywGrA6pQFcA311+mZwO62HxrcbzSzSXoBzesFcCfwmm7+31fX/Ke1Ou4Cdsxrp3eS9gG+Qvn/fo7t7YfcpKiR9BzKzmeL07wvzQV+DpwMXGD76gnUuxqlz7AHJatlI0BLwG+BbWw/2eHHo0W1g9I5wAI0r9PdwEmUbHcXT2TSuFq0uBnlOr0ZeDrN97u/Af+WyejxSV98epH0csq1WZnm37PRR59IsEHrzxq4GHid7X9NtJ3x1Gec44FGINA5wFu7+btWdRwHvIxyjc4B3pJr0ztJ21PudQautL3BkJsUNZKWpPTz1mPk+9PdlM9PF1DuVdeNJ9GBpEWANYDNKe9HO9MM9GrUf5Ttffr8q8xo1eLnSyiBj3VXUPp5F1D6evd2UeeilD7e1pQx9w0YeZ1Os71L762fHdIXn14kHQJ8hPIZtHG9oLdEJPU6TOmHv872r3qoc9aTtABlZ+Kdq6dOA77QzWenqo4PUZu3BQ7v5fNXFJLWBS4H5qeMta4yiB2bYmJadlsQJYjhG8C3bP++D/X/G/BflGROVOd4FNjU9pW91h8RERERMd0kaCEiYoaRtBLwD0rWmvuBlbPV6NQi6QjgA4yc5IQySPVHqklO4EbgVpoLeB+lZKFapPpaHliV5iTn5pSFvdCcOHgM2Mn2zwf5O81EuU5Tm6SFKBmKtmbkNZoL/B+1BQPAjbbvGaOuxRh5jbYGtmHkBKqAj9n+3GB+o5mpykp0IWWyuPF3nAv8grKA98KJDMxXmca3pgz0v6TxdHWOU23v1nvrZy9JT6f8fQF+282Cjn7WEaNVi22vAp5F+f/+HNvZxWIKqXbA+AklW3hrHwLKgozr6a7/sFz9FLV6LwNeZvvuAf06M5akXSgZIxdqPEXzOs2lLGzrtp+3EeUzWL0+VXVsa/u6Qf5OM0364tODpPdSgukawVT14NTbaF6n8QanrgG8gBIA0Vrf9cD2thvZ6GOCqs8/2H5wmHXEaJJ+TrlPAby0yvAfU4Sk5SiLQLdg5P2pdZLtAeb93rR0a/W1ugR8HXiPM4HXNUnrAD+jZEvudJ3uZfx9iNa+eKMuUQKNXmf70UH8LjNV+uLTg6QTKEEgrQlIbqCM9V1E9/28F1J2ali9qqtR76PA622fMeBfK2JoJH2M5i49B9n+6zDbE03Vzn7fA3Zj9BjEP2mZa6L23mT70SpwrtMYxNbAWo1T1erd03Zj14WIiIiIiFklQQsRETOQpP8ANq4efjWT+lOPpL0pW7wvytgTnV1VW6tDwL+APZKlaOJynaa2Ktvdt2kOJsPoxaENj9N5knORdtXTvEZPAgfbPrSPzZ8VJF1CmYxp/C2/B+xv+5Y+nmNDyv+DTaunDLzJ9vf7dY6IqaQKUG0snLk6O4tMPVWG168Br6qeat1hpvHcuKpr+ZnG+9LXKPfTh3to6qwmaVPK+8eGtM8Y2m1/r7WPB2UHoLf3Yxeo2Sh98alN0msoi3fr/ea/UV5XJ9u+voe616BkSd4LWKVW/5+BzZLtNSKGpQoi3g84EFiqenqszOOt71mdyjSevwn4oO2Te2vp7CZpceAwyvvIAnS+RvPqU7TrGwp4EPg0cEQCSyYmffGpTdKBwGdo/j2foOys9U3bl/Sh/q0o99Jdaue4C9gg1ysihkHSfJS+wwfrT1ff+zkG8RCwl+0Te6gzIiIiImJaS9BCRETEkEhaFfg4JVN4Y9F0/Y15PNsstyt/H3A08LnxbEkfY8t1mvokvZ4ykbZO9VQvW5W3/uzFwPttXzjxFs5OknakZBtv/E33tX3UgM61ACXDYWPXhT/Yfv4gzhURMV7VrgvvA3YEntbyz+MZjGl9H7ufskvNF5ORrz+qSek9gH0p2d3ruhkwa11gdR5lEdtZvbUw0hefmqrg4X8AK1L+vvcDB9g+ps/nWQQ4nPIabVzHT9j+TD/PExHRrWq3kbcAb6BkDV+gQ9HxvGc9DpwPHA98P4FZ/SNpNWBvYHdKxuNWY/X32l2vqynX6Sjbd/XcwFkuffGpqbaTd2MnjCsoQb5XDOBcuwAn0Nwl41jbe/X7PBER4yVpc+CzwEtrT09kvqn1Z54Efgh8pJcA/4iIiIiImSBBCxEREUMmaUlgZ2B7ykTnahOo5kbgN8AZwI+Tdbn/cp2mPkk7AG+kXKNn9lDVLZRrdLzt/+tH22ajahv5N1EG6L9u+z0DPt/SlO2aF6vOuW52GoqIqaBa3Ls1pf+wEbA2JXP4kmP82P2UTLtXA3+i9B9+Y/vRwbZ29pK0Os1+XuM6LTaOH30IuIbmdTrT9s2Daudslb741CJpL0rQh4EHgO1tXzTA832BZsbLG2yvMahzRUR0S9LTgM0Z2c9blrITw8KUgIYngMeAe4E7GdnPuyjvSYMnaW1G98e7uU6/yRjD4KQvPnVIOhj4FKWfdy2whe07B3i+NwKNjOP3AivYfmxQ54uIGA9J69Kca3o+Zefubj0OXEIZgzjR9j/718KIiIiIiOkrQQsRERFTTLUg59mMf/LsGtv3DKWxs1iu09QmaQ0mOBFt+7rJb/HMI+lqYC3KJOc6tv8xCef8OvCO6pxvsP3DQZ8zImKiJM1Ph/emZNidGqr+3ph9iPTvhiN98eGSdAbwSkqf60Dbnx/w+eYHrqNcbwMvtH3JIM8ZERERw5W++HBI+j9gS0qf6822T5qEc14KPK865/a2zxn0OSMixkvSgsD6dD/X9NcEYUVEREREjNZpy9qIiIgYEtv3Ar+vvmKKynWa2qotdq8fcjNmu5Wr7/dPRsBC5S+145Um6ZwRERNiey5w17DbEZ1V/b17h92OGC198aHbuHb8tUGfzPZcSd8D9q+eWpuSsTIiIiJmqPTFh2a96vuTwGQlA/kJJWgBJrajWkTEwFSJRf5cfUVERERERI/mG3YDIiIiIiJiRpqfkiHtkUk856O144Um8bwRERERs8lylH7eHbbnTNI560Gwz5ykc0ZERETMNktS+nn/msQdAG+uHS8/SeeMiIiIiIiIiCHITgsR0VeSFgL2AF4JbEqZyH46oAlWadu5V0VEREw/d1B2O1hO0lKTtKBtzdrxrZNwvllJ0tMoGZYb/bwJB8PbPq5f7YqIiIhJMxdYEFhkEs+5cO14shbQzSqSFge2ZuR43kT7ebb9jn61LSKi3yQtASwDLEV5j1kQeAJ4DJgD3FVl+o+YbR4ClgCWncRzLlM7zutuACRtw+h52176eWv1q20RERERERExu2QhcET0jaTNgR8AqzaeGmJzIiIGRtKqwEbA2pR73piTnMANwNXAn2zfOPktjhiKP1OCFgD2Ag4f5MkkzQe8sfbUPzqVjYmR9ErgAMpitn7t2peghYiYMiStCWzFBPt5wK9t/3Oy2x0xBDcDawFLSFrL9mT0u55bO05wah9JWhA4BHgPZZFiz1VSMjQnaCEipgRJqwDb0+znPZuyYHdeP/cAtX4e8HPb/xpgUyOmgusor5OFJG1h+4JJOOcWteNbJuF8s4akZwEnAZu1/tMEqjPNfl5ERERERETEhMjO58qI6J2ktYDf0xzsbwxeUXsMnQfCWm9GjXK2PX9fGhkR0QNJL6EsiN4BWKWHqm4AfgYcb/vCfrQtYiqS9G7gqOrh/cDLbF8ywPMdAhxUPfyX7ZXGKh/dkXQY8KHGw9o/derz0aZs68+knxcRQydpJcpC3TdSFmGPKjKPKlrve1dSArK+Nkm7DEVMOknfpeyyaeAY2+8d8PmWpHyOWqI653Ns/32Q55wtJC0AnA28iNpYXL3IGD8+1lhf+nkRMXSSdgP+E9iSkfeqbhbr1u+JT1LumV+wfW7vLYyYeiR9GdiX8n//PODlHuBiAknPoQQGzU/ZzWtl27cP6nyziaTlgMuAFWkGG0x03nbEz6WfFxEREREREROVoIWI6AtJPwBeT3PQ6z7gV8A1lIHG/at/+yfwqdqPLgM8D3gNzcnnJ4CjgbsBbNfLR0RMKkmvBT4HrN94qvbP3XSk2v3cb4H32b5swg2MgZP0DGBN4Frb9wy7PdOFpKdRdjtYnvL/fw7wIdvH9vk8C1Aywx5AcwLuv20f0M/zzGaSdge+Vz1sneBsPEeb59uVqZfLJGdEDE31PvUZYG/KDgrdLN6oa1fWlIC9A23/b49NjQGStCOwLnCV7dOH3Z7pQtJrgB/T/P//XtvHDOhcAs4AXlGd76+2NxzEuWYjSR8DPs3oe9k9wMOUndMa97Q/1n50GcqONAvXfnYuZRcOAGw/a2ANj4gYg6TnAt8GNm08RXf9u1b1z8GNek4B3m77wQk2MwZI0gqUxAvrAn8HjsguGeMj6XnApTT/r58AvMv2YwM41zMpu5isVZ3vfNsv7fd5ZitJ3wD2pHkPexK4gjJv+ziwe/VvtwJfr/1oY952C5r3zyeAH1J2HcT22yfll4iIiIiIiIgZJ0ELEdEzSUsBdwDzVU99B9jX9kO1Mg8AT6ND5mNJSwOHAe+kGdywje0bB9v6iIj2JC0MfAN4U+Mp2i/WhTJo/zDwSPW1ELAIsGh13Kpez2PAnrZP7Fvjo28kHQR8HFiAcp0/Y/uQ4bZq+pC0E3Bq4yHVQjPgW8APbd/QQ90rUTL8vocSVNJ4Td0MbJjs1v0j6S/ABpTrN5eSQfwMyiSngT9X36+wvVHt55amTHLuCbyhevoJ4EDKRCe2/zk5v0VERJOkNSn3sXXovIjtPuAm4BY69/OWB1YDlq79XL0uUxZ/7G37yUH8LjExkuYDzgReVnv6XGCHXKt5qwIJLgU2ofl//UTgANu39vE8z6YsOq0vmHqf7a/26xyzmaT5KX3n5aqnbqb0086wfU/1mfhByt/+H7bXafn5xSmflz8BPJNyff7H9n9N0q8QETFKlXzkJEp/rXUsby5lTOI6xt/PWwPYkBLkSq0+U4K5XpWs8FNLlXzkz5TAu4abgY2TjGR8JH2P5oJ2gGuBjwI/tv14H+pfCHgzcDjwDJqvqVfbPqvX+gMkLUaZt124euoXwLsbY7FVf/4hyn3vZturtaljXeBLwPaU63Mp5fPSnIH/AhERERERETFjJWghInomaXvgLMqg1d+BDVq3i5V0GbARJZPH0zplZZH0X8CRVV2/s/2iATY9IqItSQsCPwe2YeQE51zK7ggXAhdRTXLavnOMup5Oc5LzhcDW1dd8jJzofJftbw7mN4qJkPQiyq5BdQa2tf2bITRpWpL0Psp7O4zOTHgrcAnltXRj9bixYOBRyqKARaqv5YFVKa+lzYHVa3U2Xkv3Ai+z/fuB/UKzTLVY8CrK3/hJygTyL1rK3AqsANxve8kO9WwFnEzZkv5JYA/bJw+y7RER7VRBbxfTzB7eeG/6G+U+dSFwUTcLmqqFu41+3puAZzOyn3eU7X379TtE7yS9HvhBy9MG3mD7h0No0rQj6TnABcDiNP+vz6V8jjoZuMD21ROodzXKa2kPyu4KjQQZonwW2yaBJf3Rkkn5fkrg740tZa6l9L8ftb1oh3qWBk6jXDcDh9k+aHAtj4hoT9IWwHmURbiNvtg9lJ0DTwYumcjOCJIWBV5AWWT9RkpyJqpz/Nr2dr23PvpF0p6URDStO2Ts1e/dP2cqSUtS+nnrMfJzzd3A6dW/XQxcZ/u+cdS3CM3xvK2BnSnZ/OtjekfZ3qfPv8qsJWlbSlC2KWOu69l+pKXM5cBzKH34RW0/0aGuLwLvr+r6qe2dBtbwiIiIiIiImPEWGHYDImJGWKt2fFprwELlKkrQgiiLDNtOXNv+kqT1gb2ALSXtZfuYfjc4ImIevgBsS3Nh9b3A54HvdLuVeDVxc3n19VN4aiHO+6qv+Sn3xi9J+pXtf/TjF4i+2Kz63pp9+flAghbGyfaXJf2Dkml6RUb+PVcCXjuBauuTzo3Jzb8Ab7T9t95aHC2eXzs+szVgoXI1JWhhcUlL2767tYDt30raDvgdJYveUZLOt33HQFodEdHZtxgZsHAB8AHbF020QtsPAGdXX5+UtCPwVWCV6hzvlXSa7bN7bXz0zSrV99Z+3iptykYbtv8q6ZXAT2juNrIA8KrqC0n3AtfTXXBqI+s/jFzIdhmwUwIW+mqj2vGpHXY7vYpyXRaS9Mx2O2nYvlvSqyj30w2AD0k62fZlA2hzRERbkhag7ADdCFh4Avhv4NOtC3W7Zfth4HzgfEkfBY4FdqS8P71Y0t62/7eXc0RfLVw7rgcuLNimbLRh+15J21CCEreg+XdcBnhb9QU8tcv6vPp59Z3pYOS4nihjhgny7q91a8endLgPXk0JWpiP0he/rl1Ftj8gaQ1KsMmOkna1fUp/mxsRERERERGzxXzzLhIRMU/1jLrXdihTD1JYYx71fZiyQBgyUBkRk6zKKr4vzQVM51EyEX2+24CFTmzfYHt/4EWUjG+mZGn7bD/qj765ssPzf5/UVswAts8A1gEOpkxkqkNRjfHVqfy1wN7A8xKwMBAr1I47BetcVTtevUMZbP+dZt/uGcCnemtaRER3qoU3L6fZzzvc9la9BCy0Y/unwMaUgLrGQpyP9fMc0bNfU3b+qXP1fIyT7d9R/q//jJH9tUb/bSlgE8rCzndRgrYPoPQJP0LJ2PoeYBdKwPDyjO77GTgK2KpdYGT0ZJna8R87lBnXeF4VvLUn5XrND3yyx7ZFRHRrd5q7XT0B7Gb7wF4DFlrZvsP2a4GTqqdE5jCmmtMp80v1/sR9VMlkYnyqJBMvpvTd7m1TpNFnW4Iy5rcxZSeFF1F2odsEWJ/mjgrtxvdupux09u4OydBi4paqHV/VoUw387b7UAJTAPafWJMiIiIiIiIistNCRPTH47XjttuH0sXgV5XF5UfAfwAbSFrPdqeFoxHThqQXD/P8trMAZ3zeQQnsNCWb545VRrW+s32RpN2Ac6qnXiNp8WrBRwyZ7Z9JOh54S+3pE2z/bFhtms6q/9eflfQ5yqTn9sBWlAyvS42jisbE5n3AnygL6M+wfUH/Wxs1i9WOb+9QprWf12nRG7ZPkvQxysT1GyS9r9P28xHTiaRvDvH0tv2OIZ5/Onlz7fhU2x8Z1Ilsz5G0EyXYcSFga0kr2755UOeM8bP9B0nvBg6nBNLNAQ6w/YehNmwaqv5P7yhpS0pQwo6UgOxutS5iewA4Gfii7b/21sroYKHacbvFiDC6n9ex7237Ekm/ouxauIOkJW13qjdi2pDUKUnPZLDtteZdLIBda8f/bfsnAz7fOynjGssA60ra0PZfBnzOGAfbN0nalhJAtzblvezTtm8aYrOmJdtzgSMkHUUZH30DZSxvPOsLOiUgeYKyc8nxwPdtP96hXPSmHgTSKXirHsywxpiV2bdKOp0SILa5pNVs39BbEyOGr9oVfWjyOoqIiIiI2ShBCxHRD/fUjpfvUKY++PXscdT5R0rQApQMLQlaiJngfEYOFk8mk/f98Xpp7fhjgwpYaLB9nqTzKQs7FgG2Bs4a5Dlj/Gy/TdIXqSY5bf9p2G2a7qrMab+qvgCQtAywCrAsJYBhYco96wngMcoiqjuBm6pMbzF57q8dL9qhTDeZ2QBOowQtLEWZ7P7VWIUjpon/YDj9PFXnTdDC+GxZOz5k0Cez/U9JpwB7UK7VZpRsojEF2D4WOFbSsrbvHHZ7prtq14XfSVqU8pmmEZy6NqWft+QYP34/cBOlT9EITv2N7UcH2uiYUzvudH3GvZit8gvKZ9uFKP8PzphAuyKmmjVo7pw02ZJ5fPz+rXb8lUGfzPbDkk6iucvCcyi7bMUUUI3fvW7Y7ZgpbD8IHA0cLelplB0V6v28eY7n0eznXWT7oUn+FWaj+g5ly3YoUx/PW3McdV5ICVqA8tk2i61jJriezNtGREREREyqdIIjoh/qA1OdAhLqk5zbjaPOepbxlbtuUcTUNoxJzhi/tavvTwA/n6Rznk1Z2AFloiemkGqiM8EKA2T7LuCuYbcj2qpPco4nOHWjcdRZz1S6JglaiJml0c/LArOpafXq+8O2/zxJ5/w9JWgB8tl2SkrAQn9VQd+/rL6eIml+OixmS4bdoanvorVShzL1xWwvGEed/6odr9p1iyKmtkb/LuN6U9MK1fd7bN86SeesJ1rqdB+NmFGqgIPzq6+Yum6pHa/RoUy9nzeeXcLn1I7Tz4uZJH27iIiIiIhJlKCFiOiHS2vHL29XwPadkm6iLMbdVNIKtm8bo841asfz997EiCklk5xT2+KUa3S77Scn6Zz1hR3LTNI5IyLG44ra8eYdylxDWXg4PyN3q+lkwdrxCh1LRUeSBKxbPfx7tYPJROpYh9IfmVAd0Vb6eVPbQpRrdO8knvO+2vFik3jeiCnF9lwSpDrVXFY73qZDmeuAByn3r20kzTePz8lL1Y6f0VPrZilJqwOvrB6eafufE6hjtaoOAWfZvr5/LZzVGjtc/QaYrPGiiIiIiajP276sXQHbt0i6A1gOeIGkp9u+r13ZSj04a6E+tHHWkbQ7sEv18FTbP5hAHbtVdQj4ke3v97GJs1V9TDTjeRERERERA5aghYjome05ki4HngusJmkr279tU/S3wBuA+YDDgbeNUW19697bO5aKtiTNB+xPbfAL+O9qkUA3dXyQ2uAXcEQ3dcQotwDPpDnJeRAjM97E1PAAsCSw/DgWZPTLirXjuzuWioiYfJcDjwCLUBaqLWz70XoB249UfcFNgJUlvcT2uWPUuWnt+OF+N3imk7QWpV+2QfXUFZJ2sX1Nl3WcSum/A/xV0uu6qSNGORF4U3Vs4LW2fzrE9kR7d1N2jVlB0qJVRvhBW712/K+OpSIiJpntf0i6G1gaeH67BCO2n5T0e0r23acD7wK+Nka19Sy9kxkgNiNI2gE4BVi0euoRSbvaPmsy64hR9ga+SnNB2y9tf2aI7Yn2bgNWA54haUXbk9HvWrd2PFm7O0REzJPt2yVdS9nhdB1JG3XYbfAC4LWUBCOfBD4wRrU71o4TjNwlSQcAh9ae2k3SGrYP77GO1bupI0a5n5LIrDFveyQjk09ERERERESfKckUI6IfJB0EHEL5QH+G7de2KbMzZXEUVbk9bX+nTbkP0xx0MfA8238aRLtnKklfoDm42Bho+aLtD01mHTGSpDWBcygTaAC/Al6azMZTi6SLgedT/s+/ejIm9iX9kpKd3MBrbP9s0OecbaqM4ksCC1MmYZ4AHgPmTOKOGhHTkqTTgVdT7lH72D66TZnDKQGTBv4GbGr78TbllqVsP79kVXZX26cNrvUzj6RzgO1anj7P9nh2uehbHTFS9T5zHPDv1VN3AhvOY3e5mGS1//sG3mv7mEk45xXA+tU5X2L7V4M+52whaSlgVcpOZUvRpp9HWUxzg+17htLIiClO0jeAPSn3qM/bPrBNmQ8AR1QP7wY2tn1zm3KbAhdREiUZ2N72OYNq+0xUBQI/p+XpK2xvOJl1xGiS9gG+Uj18AtjC9u+H2KRoIekUSiIkA4fZPmjA51sYuBFYtjrnv9m+bJDnnA0kzQ+sB6zNOPt5lDGGvyXZUsRIkg4FPky5R51o+y1tyvw7cHz18Angle36b5LeTBnzoKpvC9sXD6ThM5SkG4BVWp6+2faqk1lHjCRpM+AsmjvGnWJ79+G1KCIiIiJi5kvQQkT0RbXt+DXA/NVTr7D9y5YyCwBXAM+muQj+bEqm2BspAwK7ADs3fgS43vaaA27+jCPpNsqWro2bvIDbba/Y+af6X0eMJml9SvaaJaqn9rP95SE2KVpIOgw4gPJ//zJg60Fm4ZW0NfDr6uFjwPLz2IY5xlBNGm9VfW1Ec5JzSTpv7XsfzUnOP1Gux+/aLbiOmI0k7QF8l3JfvB5Y3/ZjLWWeC/yZWvZR4J22b6qVWR44GXhR9dSTwKq2k5GyC5LuAxarPwXcb3vJyawjRpO0IHAesCXltZCJzilG0geBL1QPbwO2sn3tAM+3N/A/1cN7gBVsPzGo8810krYEXkGzn7d0Fz9+D81+3s9sX9L/FkZMP5K2oyRXMCXL6Hqt2cklrQBcR1kwKuAmymfmn9h+qNqp89XA0ZRdBEXZTWsF2w9M1u8yE0iaQ3O8CMrf8j7bS01mHdGepKOAd1cP/2j734bZnhipZeHt48Auts8Y4Pm+CfxH9fA622sN6lwzXbUT4Bso/bzNgIUmUM1jwIXAz4CT6mMREbOVpPUoc7JQxuBe2BpwJ2lRyph4Y4fwx4FvAacxct52X0pgqoDbgZUTKNSdas512fpTTGzetqc6YjRJW1E+Ey1YPfVm2ycNsUkRERERETPafMNuQETMDLZvAL5NGSARcHQ12FUv8wSwD2VwzFW5l1G21/4JJUvHzrU6DPz3pPwCM89jNBcNUh13u/i2H3VEC9t/o0xoNf6fH1JlnY6p41jKfQpgE+DHg7pGkjYETqkeGvhFAhYmRtJmko6jTJr8krKd9S6UBW3PoPR71eFrSWBDSka+TwLnArdJOkrSOpP6i0RMTacCjWy6awAfay1g+3LgBzSDg14OXCvpQkknVzvKXAds3fgR4NwELEzI31seu81zk1FHtKiC3d5ICYYTsGu1yDqmjm9Sro+BFYDzJA1khxFJ7waOrB4aODkBC92TtKikD0m6HvgNcBCwLSXrbqe+Xbuvpauf+zhwoaQrJe1Z7ZISMWvZPg+4lPI6eTrNTPL1MrdRdlpojNWtQglovVfSHcCDlIVtz6yV+V4CFibkfEYG27t6brLriPb2oyTtAdikyjodU8f3gWsp/+cXBE6RdEiV3KJvJC0l6STgbdVTpvQxo0uSNpF0BuWz6CGUwNRGgNx4+2iNsgsDLwYOo4xFHCdp5f63OmL6sH0lZe5BlIRz36h2M6mXeZiyc2qjD7cg8C7gDEpykl8D76+eb5T5nwQsTMgJNO9tje/fHUId0cL2b4H/ovmecqSkxYfbqoiIiIiImSs7LURE30h6BmVxKJSBqwtbs/BW5d4BHEVzV4bWibTGc6fb3mlAzZ3RJH0E+FzL0wfZPnQy64jOJJ1IWdRm4Ejb+w+5SVEj6cuU7EGNe9Ic4FDgONu396H+FShBXB+iZA8TJVBiK9sX9Vr/bCJpReB/gcb7ReM9xS2Px6P1ZwzMBf4f8BHbT7b7oYjZQNKewMHVw0eBLW3f3VJmOeAiYPXGU9X3+murEbj6BCXD2x8G2e6ZSNILgNNpZla7E3hNN+8fkjYHflqr4y5gx7wH9YekfSiLPg2cY3v7ITcpaiTtRckG3rgfGTiLErh6ei87LVULQHYG3kcJ0mrcB+8Fnmv75g4/Gm1IejnluqxMb328hnZ9vYuB17Vmlo+YTarMou+sHhrYv00/b37K4rXtad4/WzWev5Nyz+v5s/NsU40VHA80AurOAd7azT2qquM4SqIYVXW8Jfe5/pC0PaXfYOBK2xsMuUlRU+1meg7NbOAG7gZOAn4IXGz7kQnUuyBlB4A9gDdTgrwa98G/Af82kXpnM0mHAB+hmWSklz5eQ+vYw72Uft6veqgzYlqTtCrwkuqhgR/Zvr9NuU9SArzbvRbrz10MvCg7FHdP0gKU3cp2rp46DfhCN3/Lqo4PUZIvAfwYODzXoz8k/YLShzbwSduHDLlJEREREREzUoIWImIoJG1B2UXhhW3++VHgi8Ankoly4iS9idrgl+0TJ1DHHtQGv2wnY0efSFoJ+AclC9T9lO10k4VwipC0EHA2ZbFZfUHbXOD/gAsoA/TXATfavmeMuhYDVqVkJ9+8qnMbRk6gCviY7dZAoRhDtei2sXC3/rdsuBf4J3ATcAvwMPBI9bUQsAiwKLA8sBplofUytZ+vX/szgd1tPzS43yhi+pP0LMrODBszcsemp4pQAhbenn7FxEl6Os1dK35r+95h1BHtVQs7rwKeRXkdPMd2drKYQiQdAXyAke/1UD6L/pFaPw+4lWYf4lFKhslFqq/lGdnP25zSt4Bmn+QxYCfbPx/k7zTTSHovJfinsUtsvZ93G81rNN5+3hrACygBEK31XQ9sb7uRPTsi2qg+Jx8JvJuRr01ovp6uo9zzLp/k5s0o1TgCth8cZh3RnqSfU97zAV6aQOypRdIulKzTCzWeonmvmgtcQff9vI0oY7j1+lTVsa3t6wb5O800kk6gBIC0juXdAFxISYbQbT/vhZSdGhpJFBr1Pgq83vYZA/61IqY9SbsBh9N8HbU6CXhPu6CHiJlA0rrA5ZSki3cCq7RLzhgREREREb1J0EJEDJWktYEtgRWAxymLBc7OoFfMBpL+g7KoE+CrWSQztUhaFPg2sBujM3W1epzOk5yLtKue5uTZk8DB2cWkO5LWo0xkPp3m33Iu8AvgZMpuP1dOoN5nUxbx/jvNLFSN63Wq7d16b33EzFZloXw78DZKNsoFqn+6j5Kh97O2/zqk5kVMiipAdbnq4dUJept6JO0NfIGy4Km+WKqXgbJ6HQL+BeyR7K7dkfQaStbJep/5b5S++cm2r++h7jUoGZL3Alap1f9nYLNkqIyYt2oxz1sZPZ73U8ruhI8Or3URESBpU0q/YUPGzho+7iprP9c4PpMSjJ9dZbog6UDgM4zchfFY4Ju2L+lD/VsB+wG71M5xF7BBrlXEvFWZ/LdjdD/vDNtXDbFpEZNC0seAf6seHpQx7IiIiIiI/kvQQkRERMQYJL2eMpm2TvVUL9uVt/7sxcD7bV848RbOTpIuoQweNyYgvwfsb/uWPp5jQ8ok96bVUwbeZPv7/TpHxExXZZxfBnh8rF1pIiKGQdKqwMcpwYqNQNP6QNl4+nvtyt8HHA18zvZ9vbZzNqkCh/8BrEj5294PHGD7mD6fZxFKFtF9aV7DT9j+TD/PExEREcMhaT5KNv99Kbst1XUzMdoa7HAecITts3pr4exT23m4sQvGFZQA3ysGcK5dgBNo7pBxrO29+n2eiIiIiIiIiIjoToIWIiIiIsZB0g7AG4HtgWf2UNUtlEzjx9v+v360bbaRtCPwE5qTzPvaPmpA51oAOIvmrgt/sP38QZwrIiIihkPSksDOlH7eVsBqE6jmRuA3lH7ej7O7xsRI2osS8GHgAWB72xcN8HxfAD5YPbzB9hqDOldEREQMh6TVafbzNgLWBhYbx48+BFwD/InSzzvT9s2DaudMJ+lg4FOUft61wBa27xzg+d4InFg9vBdYwfZjgzpfRERERERERETMW4IWIiIiIrokaQ2ak5yrAMsCS1Gydy1A2dr8McqE2J3ATcDVwJ9sXzf5LZ5ZJJ0AvIkyyfl12+8Z8PmWBv5JmdA2sK7tawZ5zoiIiBieKojh2Yy/n3dNdpPpD0lnAK+k9LkOtP35AZ9vfuA6yrU28ELblwzynBERETF8VX9vzH5e+nf9Jen/gC0pfa432z5pEs55KfC86pzb2z5n0OeMiIiIiIiIiIjOFhh2AyJiZpK0KSVz0VrASpSFnosA83VZlW2/tM/Ni4joie3rgeuH3IzZ7AW14y8M+mS275b0PeAd1VObUDLtRcx6khZl4v08bN/Q90ZFRPTI9r3A76uvmFwb146/NuiT2Z5b9fP2r55aG0jQQsxqkhan9/E8bB/X56ZFRPRN1d+7d9jtmGXWq74/Cfxwks75E0rQAkxsN7WIGaNKzLMl/Zm3fce8i0VERERERESMlqCFiOgrSe8GDqRkKey5OkoGnIiIiLqVq+/32/7HJJ3zL7XjlSbpnDOOJAHrVg//7gls+1bVsQ6lnzChOmLiJL0UeC0lOHVNYMkeqjP5TBoRESMtR3l/uMP2nEk6Z70/+cxJOmfElCJpGeD9lH7ec/tUbYIWIiKibklKP+9fth+fpHPeXDtefpLOGTGlSNoB+BiwBWU8tafqKK/jBC1ERERERETEhGSBSET0haQFgBOBXWkOejUWEfY6CBYREVE3P+U95pFJPOejteOFJvG8M4aktYAfARtUT10haRfb4961oqrjVJoLqf4q6XXd1BETI2lN4ARG7nSSPt4UJelplGzlywFPZwLZkRuSJTkiJtlcYEFKxs/JsnDteLIW0M04klYHXlk9PNP2PydQx2pVHQLOqna4iwGTtBMlwGBxRvfvJhIgnCQkA1LtgrE1sCm99/OSJTkiJttDwBLAspN4zmVqx9lZY4Ik7Q7sUj081fYPJlDHblUdAn5k+/t9bGJ0IOkIYL/Gw+p7vZ/Wzdhe+ncDJGkbymehfvXz1upX2yIiIiIiIvopQQsR0S8fBV5fHZsy0CXgAeAG4H4md3FpdCBpIWAPRg9+TXThoW3n/SQiJtMdlN0OlpO01CRl4V2zdnzrJJxvJjqGkVlbnwt8DXhpl3VsWHu8wQTqiC5JehbwO0qfobEILQELU5CkVwIHUBazTThQoUWCFiJiMt0MrAUsIWmtSdpVq94/ST9vAqrsracAi1ZPPSJpV9tnTWYd0T1J21L+7o1+Q2s/L32+KUDSgsAhwHsoC357rpJkSY6IyXcdsBGwkKQtbF8wCefconZ8yyScb8aRdABwaO2p3SStYfvwHutYvZs6onuS3gN8oHrYGqjwEJm3nRKqcdeTgM1a/2kC1TX68gkwiYiIiIiIKUt2PrNERG8kLQzcCTyteuoB4AjgZNtXDq1hMYqkzYEfAKs2nupDtbY9fx/qiYgYF0k/A15BGXz/6KAnuCTNR5lYXbU651a2LxzkOWciSfcBi9WfAu63veRk1hHda3nNCXgSuBS4BPgnPUxy2v5On5o560k6DPhQ42Htn1oXH7YOArTrDz41yZl+XkRMJknfpQTZGzjG9nsHfL4lKYkWlqjO+Rzbfx/kOWciSZcDz2l5+grbG7YrP6g6onuSrgDWp/ne/w9KEEM/+nld77YRo1W7254NvIjuMySPtQtu+nkRMakkfRnYl3JvOg94uQc4SS3pOcCfKDu2zgVWtn37oM43U0m6AVil5embba/arvyg6ojuSJof+BewdPXUk5SkFCcDl9i+a1htiyZJywGXASvSPlHMWH25+r+3lkk/LyIiIiIipqxkxo6IftiO5gLCB4AtbP91iO2JNiStBfyCsqsCjF6w1s3g11jlIqILkp5ByeJ/re17ht2eaeLHlAXUAg6SdJ7tSwZ4vk/RDPa6LQELE/Z34Hm1x66em+w6oguSVgZ2oNkPOBPYO4vQphZJu1N2WID2fbZ6P6/bic6ImCBJOwLrAlfZPn3Y7ZkmvkcJWgDYS9IfbR8ziBNJEiWjZSNg4a8JWJiwVRj9PtLtIrR+1BFdkLQxzYAFgI/b/swQmxTtfQR4MeU61Xe3vQd4mLILoSkBJn+s/dwywNrAwjSv8VzKjjYR0QNJK1ACxteljEkcYftfw23VtPBtStAClDmlb0t6l+3H+n0iSc+kjB/OT7kH/joBCxNWfx+B8h604BDqiO68iNIXAHgc2MH2+cNrTnRwKPBMmq8PA5cD11Cu2+7Vc7cAX6/93DKUMfItaI77PQ78EOj7PTUiIiIiIqKf5pt3kYiIeXpW9d3A8QlYmLIOpQQsNAa/7gdOB46k7IzRWJx2PfD22tf+wImUgJRGmSeAr1AW8n568E2PmJkkHUTJeHQx8C9JBw+5SdPF8cBtlPvZEsDPJb2j3yeRtICkQ4EDq6cMnNDv88wi+wJ30Vxkcxfwn13WsU9LHXdPoI7ozotpvv9fCeycgIUpqfH+YcpitG8CuwIbAxvRvIaX256v8QUsC2xPWSTc8ARlAc6zKEF1EdElSfNJ+jllodThwGmSflnt3hRj+ynNRbcCjpJ0fLXwrG8kPRv4DSUwr+Hofp5jljmf0RlBzx9CHdGdTWvH5yZgYeqpsiQ3spJDCTh4K7CM7WWAtSiZkwFut71d7WsjYDngPZRxB1EW7/7E9rNsP4uI6FqVfORSYD/gVdX3i6vnYwy2/0DZBbrxfv9m4ApJr5fUlwXskhaStCfwF0Z+nv1CP+qfpU6gec0a3787hDqiO+tU3w2clICFqUfSYsCbaPbzfg6saXtj27tSgvkfrf7tSdufqn29z/bWlJ3qfkF5XS0APBvYz/bbJ/WXiYiIiIiI6IIGuPNmRMwSkj4KfJYysPIe21+fx4/EJJO0FHAHzWC17wD72n6oVuYB4GnAv2yv1KaOpYHDgHdSrvU/gW1s3zjY1kfMTJJeBPyq5WkD29r+zRCaNK1I2gk4tfGQKjsu8C3gh7Zv6KHulSiTAu+hTHA2JtNuBja0PWeidc92kp4ObF09/K3te4dRR4yfpP2A/6a8xj6RxWxTT7Xw9irKNXoSeLXtX7SUuRVYAbjf9pId6tkKOJmyJf2TwB62Tx5k2yNmKkmvpyzIqjPwBts/HEKTphVJzwEuABan2c+bS1nEcTJwge2rJ1DvapQ+xB6UXbsan48F/Jby+fbJDj8eY6gyTh8PvLR66hzgrd1kna7qOA54GeWanAO8JZmrB0fSAZRxHgMftP3/htuiaCXpeZTF0Y2dFDZsHYeTdC2wBvCo7UU71LM0cBrlHmjgMNsHDa7lETNXtSD+GzR3PqE63sv2sUNr2DQhaUlKP289mn9DU5JSnF7928XAdbbvG0d9i1DugZtT7nE7UzKQN+oVcJTtffr8q8wakhag7Oy4c/XUacAXbD/eZR0fAl5XPfVj4PBu6ojutMzb7mv7qCE3KVpI2hY4l3KNbgTWs/1IS5nLKYEJc4FFbT/Roa4vAu+v6vqp7Z0G1vCIiIiIiIgeLTDsBkTEjHB37XiRobUixrI5za2Q/w68w6Oj1q6hZOJdXtJCrdsy274b2EvSFZTdGVan7MDwokE3PmKG2qz63ngtNiY6n0/J+hpjsP3jajH1kTQnITegZE77QrVA9xLgOsqg/63Aw8AjlAxFC1LesxYBlgdWpTnJuXp1msYEJ8C9lAzzcwb8q81o1YTzz4ZdR3Slnu3w5qG1Isby/Nrxma0BC5WrKUELi0tauurXjWD7t5K2A34HPIOS3fx823cMpNURM9sq1ffWft4qbcpGC9t/lfRK4CfA0tXTC1CyGb8KQNK9lF0Cu+nnLVc7TX0h22XATglYmDjbtwHbV9lCsf3gBOvYoZc6omv1hYL3D60VMZaNasendkgcchXlHreQpGfavrW1gO27Jb2Kshh4A+BDkk62fdkA2hwx0y1cO64HLvRlp4CZzva9krahLHzfgubfcBngbdUX8FSSpXn185ZmpHogiYCvU3asiQmqFkl/rvrqpY5Dq6+YHPWgn2SwnJrWrR2f0hqwULmaErQwH+Vz7XXtKrL9AUlrUIKLdpS0q+1T+tvciIiIiIiI/kjQQkT0w0W14y2BrwyrIdHRWrXj09oELECZ5NyIMpi/OmUwbBTbX5K0PrAXsKWkvWwf0+8GR8wCV3Z4/u+T2oppzPaXJf2DMgG5IiMXBq4EvHYC1dYnNxsTnH8B3mj7b721OGJa+mfteNROTDElrFA77hT0dhXNHUpWZ2TQ8VNs/13SvsB3KYELnwL27lM7I2aTX1N2LFHtOVfPxzjY/p2kjYGvUQUqVBp/06WATYCNx1ll67VofD8a2N/2wxNubDylH4EGCVaYVPXPpOsMrRUxlmVqx3/sUOZqYPvqeA3KAt9RbD9QZYi/kJLY5JM0s2ZHxPidTlm8vSTNPsV9wE+H1qJpxvYdkl4M7AccSOnX1TX6bUtUXzB60bUYrV7mZsouQtk9MGarP9SOn9+xVAzTUrXjqzqUqc/TrkGHoIXKPsAOlKCu/YEELURERERExJQ037yLRESMrcrK9RfKQPHOkp493BZFG0vWjq/tUKZ18GssH6ZkHYdkKoqYENs/A46n3DsbE20nVM/HONk+g7LA5mDK4ox2k5bQ/Du3++pU/lrKYt3nJWAhZrHzgMbW47sMsyHR0WK149s7lBl3P8/2ScDfKPfBN0hKsoOILtn+A/BuYA7ltTQHeE/1fIyT7Ztt70gJuvoBJcvuRLT29x4AvglsZHufBCzELHY+zbGdPSQlS/jUs1Dt+N4OZbrp510C/IpyX9xB0pJjlY+I0WzfBGwL/JjyuenHwEuq52OcbM+1fQQlc/jelHvTXDqP09V1KvME8EvgrcBaCViIWe5CygJ3AbtLWnHI7YnR6oFW7XZZgJHBDGuMWVnZbet0yjXfXNJqPbUuIiIiIiJiQLL4ICL65QDgTMpk2vckvcT2ffP4mZg8j9eOn+hQpptJznsl/Qj4D2ADSevZ7pQ1PiI6sP02SV8E1gautv2nYbdpOrL9APBZSZ8DXkzJMrkVZfeYpcZRRWOy8z7gT5RM5WfYvqD/rY2YXmzfLun7wL8Dm0h6i+3jh92uGOH+2vGiHcp0E5wKcBqwPuUeuhVlAUlEdMH2scCxkpa1feew2zOd2f4d8DtJi1ICGBr9vLWBVRgZpN/qfuAmyn2w0c/7je1HB9roiGnA9sOSvgR8HFgZOJSSlTWmjjm14073unEvZqv8grLgeiHKPfWMCbQrYlarxu9eN+x2zATVDktHA0dLehqwOSP7ectSPpcuTJnTfgJ4jBLIdScj+3kX2X5okn+FiCnJtiUdDJxASXbxHUk72n58Hj8ak6e+C+qyHcrUx/PWHEedFwK7V8ebATdMoF0REREREREDlaCFiOgL2z+XdAgl0/WmwK8kvSmZqaeMe2rHy3coU5/kHM9uGX+kBC0AbAwkaCFiAqqJzgQr9IFtUxbWPrW4VtIyjHOS0/Ydk9zkiOniAODllD7EUZJusX3OkNsUTfVJzvH08zYaR531nbnWJEELEROWgIX+qXZE+GX19RRJ89Ohn5dFORHz9Dng1cC/AftJesD2J4fbpKip76K1Uocy9cVsLxhHnf+qHa/adYsiIgakCjg4v/qKiB7ZPlHSS4G3Ay8DflolI+m0S2dMrltqx2t0KFPv5714HHXOqR2nnxcREREREVNSghYiom9sf0LS/ZQJz42BP0g6HjjG9qXDbd2sV8+m0Skgob6Ybbtx1PlA7XjlrlsUETEJbN8F3DXsdkRMZ7ZvlbQTZVetpYAzJX0eOKzKihjDdUXtePMOZa6hLOKdH3jpOOpcsHa8wgTbNetJErBu9fDvVXDdROpYh7Ir0ITqiJjpbM8l/b2ICbH9mKRXAmcBzwMOlrQd8NFql5MYrstqx9t0KHMd8CAli/I2kuaz/eQYdS5VO35GT62bxSStDryyenim7X9OoI7VqjoEnGX7+v61MCIiAoB3Ag8De1MSklwh6UjgGwleGLr6vPnL2hWwfYukO4DlgBdIerrt+8aosx7kulAf2hgREREREdF3ynx3RPSbpE2AYyk7LjRuMvcC/6RkeejmxmPb41lYFWOQtBQlC6+BG2w/q0O5GygZyecCq9i+bYw6P0XZWcPAR2x/od/tnukkzQfsD+xSPXUq8N/Voptu6vhgVYeAHwFHdFNHRMRUIelplMDH5YCnA/NNtC7bx/WrXVFIWhv4LvB8yvv/HOAk4GzKYqk5dNfPw3a2Ke+RpAWA+4BFKAvWlrX9aJtyfwA2oVyjl9s+d4w6vwa8qyr7AdtfGkDTZzRJa1H6ZRtUT10B7GL7mi7rOBV4bvXUX4HXdVNHRETEeEhaCDgU2JdmoqO/0Vs/L/3xPpB0J7A0JQB11XZjdZLOp2TfNbC37a+NUd+pwM5V2f+0/b8DaPaMJmkH4BRg0eqpR4BdbZ81mXVERESMl6QdgSOBtSh9AAOXM7F+nm2/o99tnI0kXUPZ4dTAprb/3KbMacBrqzJfsv2BMer7HfDCquxeto8dRLtnOkm7U5u3tf2DCdSxG7V5W9vf72MTIyIiIiKmtQQtRERfSXo5cACwLWWhoWr/3O0NR5TBr/n707rZTdKfKQueDLzY9m/blDkJeENV5gTbbxtnfXva/s5AGj6DSfoC0BhgFOVv+UXbH5rMOqJ3VRbkJYGFKdmpnwAeA+bMI8NhRABVdtcDgK3pIVChLv2HwZD0LOD7lMAF6L5/V2fb2f2vDySdDryacj32sX10mzKHU4IlTVmEuKntx9uUW5ay/fySVdldbZ82uNbPTJLOYfTuZed1E5Ddjzpi4qrA71WBZShZqUf18yjZ/W+wfc9QGhkxTUhanNLP25Teg1OzSGoAqiDIN1KSImxc+6cJ9/XSH+8PSd8A9qRci8/bPrBNmQ8AR1QP7wY2tn1zm3KbAhdRAlMMbG/7nEG1faaSdDnwnJanr7C94WTWEd2TND+wHrA24+znUT4b/S0JYiLak7QNZdeYfvXz1upX26KQtD5lDmlXylhP5m2nCEmHAh+mXIcTbb+lTZl/B46vHj4BvLJd/03Sm4FG0LCBLWxfPJCGz2CSDqAEc9d91Pbhk1lHRERERMRMlqCFiOiLasHuUZSMrG2LTLDqDH71iaSDgEMog1Vn2H5tmzI7U7K5whjBCJI+THPAxcDzbP9pEO2eySTdRhnIb7wZC7jd9oqTWUeMn6SFga2qr41oTnK2DvbX3UdzkvNPwK+B37VbKBoxG0k6DGgEWrVOmo01idbuNdf4mfQf+kzScpSMbG9g9ORz+nlDJmkPyi4YBq4H1rf9WEuZ5wJ/pvla+iXwTts31cosD5wMvKh66klKRt9bB/oLzECS7gMWqz8F3G97ycmsI8ZP0pbAK2j285bu4sfvodnP+5ntS/rfwojpR9KClHGI9wBL9KNK0n/oO0kvBr4NrN6vKsl16htJ2wHnUPpw9wPr2f5XS5kVKJmSF6b8/W+iBIX/xPZD1S6drwaOBlasyjwMrGD7gcn6XWYKSXMYeU8TcJ/tpSazjhifaveyN1D6eZsBC02gmseAC4GfASfVP0NFzFZVUouTKK+rEf80geoynjcgkj4CfIrmTlpti42zulynPpO0HmVnTihjcC+0/fuWMotS5paeSfn7Pw58CzgNuJESfLcLzR3TBNwOrJyAu+5JugFYpeXpm22vOpl1RERERETMZAlaiIi+kPQp4ODqYX2R4QOUxbr3U7a57prt1uyiMQGSVgOuARqDia+w/cuWMgtQBsieTTNr/9nAjxg5+LVz40eA622vOeDmz0iSbgRWann6li4Hv3quI+ZN0mbAfwI7AYvX/6mLauqdrnspmcqPtH1V7y2MmJ6qrZa/Vz1sDVJoPEeb59uVqZfL5FkfSVod+BUlSKvRP5hooEJdrlOfVEF119DsE3zW9sfblPsesDvN181c4A80+3lbAovQvM7n2N5+oI2foSRdAjyv5enf2958MuuIsVWT//sC+1DucU/90wSqq78fXQ0cDnzLGXiLWaoaXzibEgj3VB+tXmSMHx+rD5j+Qx9V2ZHPoizi7Uf/riHXqY8kXUxzp7NTbO/WpsyngY9RW1BIWfw2hzKOUb/GBr6dXUsmRtJpwGsZeU873fbOk1lHjE3SJsBngR1o/t/vNrt4u/JzKeMYH223o0nEbFAltriMZiBcp8QjnfoWnfqE6T/0kaR9gK9UD1uv0UP0Nm/7rN5aFw2SfgC8vnr4J+D5rcEGkt4InMjIft6oqqrvBj5h+zODafHMViWKW7b+FBNLNtdTHRERERERM1mCFiKiZ5KWAG4FFq2eeoCyJfnJtq8cWsNiFEnHAO+sHl4HPNf2wy1lXgacScmiPJ7Br/fZ/upgWjyzVVluPtfy9EG2W7cNHWgd0ZmkFYH/pQQrwOjFNhMJWqjXMRf4f8BHbD858ZZGTE+S/gJsQPP1cBxwBmXxtWlmhb/C9ka1n1uaspB3T0rGRCjbYx8I/BDA9j8n57eY+ST9AngZzYmxJ4FLgUuAf9LbJOeoHZ1iYiTtSTOI+FFgS9t3t5RZDriIZibldu9rjev8BCXD2x8G2e6ZStILgNNpTlLeCbzG9kVd1LE58NNaHXcBO3ZTR3Qm6eXAscDK9NbHa2jX17sYeF1rRuyI2UDSx4BPM/q1cQ8lw/tKNDPH/7H2o8tQdrRbmJELRJ9aGJpFUv0j6UpgHZrv//8ATqE//bz0x/tE0lY0x/MM7N+mnzc/5bPU9nQOMm48fydlTPD2gTV6Bqt2tjgeeGn11DnAW7t5v6/qOI7yOUtVHW9Jn6E/JB0CfITR49u9BGe1fma6l9LP+1UPdUZMS5K+QRmTq48TXUEZz3ucZrKEW4Gv1350Gcp43hY0X0tPUMbyHgOw/fZJ+SVmuCq5xS2UBBVQrtFxlN01L7F915CaFi0krQq8pHpo4Ee2729T7pPAx2n/nlZ/7mLgRdnpe2Ik/TewHyP700fa/uBk1hERERERMZMlaCEieibpVZTFNFACFrawfcUYPxJDIukZQGPRp4ELbT/Wptw7gKNo7srQafDrdNs7ERMm6U00d644zfaJE6hjD+B11cMf2/5un5o3q1ULBRuLDdtljLqXsojjJsoEwMOUxRyPUDIYLkIJ5loeWI2yQHSZ2s/Xs+KcCexu+6HB/UYRU4ukZwNX0cwA+mrbv2gpcyuwAnC/7SU71LMVZcJtxaqePWyfPMi2zyYt1wng58B7swht+pL0LOBUYGM6B6c+Abw9fYreSHo6sHX18Le27x1GHTGapPdSMk7OVz1V7+fdRpnkv47x9/PWAF5ACYBore96YHvb1wzq94mYaqrF0zcDy1VP3UwJLj3D9j3VIqoHqRbJ216n5ecXB94EfAJ4JuU19T+2/2uSfoVZodpR8CKa/YFP2j5kiE2KHklaCDgSeDcj3+Og+b50HbCT7csnuXkzjqTFAGw/OMw6YiRJJwB7MHos7wbgQsp9r9t+3guBrWgGfzfqfRR4ve0zBvxrRUwZ1X3rDkqAKcAvgHfbvqH6d1Gy+C8E3Gx7tTZ1rAt8iWag3aXADrbnDPwXmCWq5GS/oBkY8grb5w23VdErSbtRdnVcvUORk4D3tAt6iPGpdgw8gNq8LfCFboJAqjo+RG3eFjg8gSQREREREUWCFiKiZ5L+izIhZuBo2/sMuUnRB5K2AP6bMinT6lHgi5QtRp+Y1IZFTAJJ61EmMp9OcyJyLmWg/2RKwE/XO8lUi3+3Bv6dZvacxiTqqbZ36731EdNDy7bWZ9h+bZsyv6a8Zgws15pNtFZuXeB3wDOAu4H1bd8xqLbPJpLeAnyHcg2uBDbJBMv0J2lB4O3A24DNgAWqf7qPkqH3s7b/OqTmRQyUpNdQJp3rC9n+Bnybslvg9T3UvQbwZmAvYJVa/X8GNsv9M2YLSc+jLD5r7KSwoe0bW8pcS1kI+qjtRUdVwlO7a51Gsz94mO2DBtfy2UXSXsDRlL/tubZfPuQmRZ9Un4/eCmxJCQJ/nBJE91PgONuPDq91EYMj6UDgM4zcPe5Y4Ju2L+lD/VtRMifvUjvHXcAG2bkkZgtJ2wLnUl4DNwLr2X6kpczlwHMo4+mLdppDkvRF4P1VXT9Ngqz+kfSflMAQA8fb/o/htij6pVoQvx2j+3ln2L5qiE2LiIiIiIgYlwXmXSQiYp4Wqx1fNqxGRH/ZvgDYUtLajB78OjuZOmKGO56RAQvfA/a3fUsvlVYZdq8Bvi1pQ8riuE2rc+wi6Q22v9/LOSKmkRVqx7/pUOYqmhnGV6cEJIxi+++S9gW+Swlc+BSwd5/aOdutWDs+KQtuZ4bqOh4DHFNlw14GeNz2PcNtWcRgSVoU+BrNgIX7gQNsH9OP+quAh89IOoKS/XDf6jwbAh+mLKKLmA02qh2f2hqwULmKErSwkKRn2r61tYDtu6vdPS8ANgA+JOlk25cNoM2zUX0nwGQJn0Fs/x1IgE/MKpJWAg6mubvI5ZSdGPu2I7Tt3wK/lbQLcAIl0/zSlD7eXv06T8QUt27t+JTWgIXK1ZSghfmAVSm7m4xi+wNV4PfOwI6SdrV9Sn+bO2stUTu+cGitiL6rgoB+WX1FRERERERMO/PNu0hExDzdWTteZGitiIGwfbXt79g+3PaRtn+UgIWYySTtCPwbzUnOfWy/qdeAhVa2/wK8gJKZCsriuQ/18xwRU1w96LFTRsKra8drjFWZ7ZMombIFvKHKOhW9q39mvHlorYiBsT3X9u0JWIhZ4i2UYCwDDwA79Ctgoc72I7bfR9m5TtXXO/t9nogprL4Y/o8dyoyrn2f7AWBPyut2fuCTPbYtmuqLDDPOExHT3TsoQQQA1wIv6WfAQp3tUynvTY1+3m6SFhrEuSKmoKVqx52yuo97PA/YB3i4Ot5/Yk2KNubUjjWsRkRERERERES0StBCRPTDBbXjrTuWioiYHt5YO/667aMGdaIqK87uwIPVU5tKevagzhcxxdQXRi3aoUw3k5wAp1XflwK26rpF0c61teOVhtaKiIj+2Kl2/DnbFw34fB8BbqqOV5W02YDPFzFV1Bdu3tuhTDfBqZcAv6IsuNpB0pI9tS4a/lo7Xm9orYiI6I8dascft31nx5J9YPt7wB+qh08HXjTI80VMIa4dt9tlAUYGM6wxZmVlt63TKf28zSWt1lProuHS2nE+h0ZERERERMSUkeyjEdEz23+RdDnwXGAnSevY7pRhJSJiqntB7fgLgz6Z7bslfY+SEQ5gE+CaQZ83Ygq4u3a8fIcy9f7ERuOos77Afk3K4rbozXnAE5TMxrsCnx1uc6Jbkhal7GyyCBNIXGD7hr43KmJ4Nq4df23QJ7M9t+rnNTKGrg1cMujzRkwBc2rHnQIMxr2YrfILYFtKQMTWwBkTaFeMdD5wH7AEsIekg2w/NtwmxXhIWhxYixJU3Es/77g+Ny1imBrBV08CP5ykc/4EeF51nIXWMVvUx/OW7VCmHpy65jjqvJCS2AfKAvuMQ/TI9sWSrqf0s3eTdKDtfw23VTEvkpYGtqT3fp5tv2PexSIiIiIiIiZfghYiol8+SsmGsiBwkqSX2O6UTS+mAEmbUrJQ92Pw66V9bl7EMK1cfb/f9j8m6Zx/qR0nk3nMFlfUjjfvUOYamgvmx/Nes2DteIUJtitqbN8p6YeUXWg2lvQ2298ZdruiM0kvBV5L6eetSefFouNhMm4QM8tylP/Xd9ieM0nnrPcnnzlJ54wYtttrx50+39QXs72gQ5m6+iKrVbtuUYxi+1FJXwEOotyfDgM+MNxWRSeSlgHeT+nnPbdP1SZoIWaSJSn9vH/ZfnySznlz7bhTMoaImeaW2vEaHcrU+3kvHkedc2rH6ef1zyeBbwNPA46X9KpJvD9GFyTtAHwM2IKy60hP1VHeDxO0EBERERERU1IWH0REX9g+Q9J/Ax+kZAk/X9Ietq8cbsuilaR3AwcCq/SjOkZuBxwxE8xP+X/daXvrQXi0drzQJJ53xpAkYN3q4d9td31vqupYh3Jvm1Ad0ZXLKa+zRYBtJC1su/5awPYj1W5OmwArV0GR545R56a144f73eBZ7EPADsAzgP+VdLPts4fcpmghaU3gBEYu/Ox1ojMGSNLTKJn/lwOezgQyJDckU/K4zaUEuC0yiedcuHacBSITIGl14JXVwzNt/3MCdaxW1SHgLNvX96+F0cZlteNtOpS5DniQkkBhG0nz2X5yjDqXqh0/o6fWRd1ngZ0oi+D/S9J9tj853CZFK0k7UQIMFmd0/24in1sznjdA1U4YW1M+n/baz0um5PF7iLJzTKfM74OwTO04CZwmQNLuwC7Vw1Nt/2ACdexW1SHgR7a/38cmxmiX1o5f1q6A7Vsk3UG5B75A0tNt3zdGnfUg14yN94nt4yS9EngD8BLgp5LebPuOITctaiQdAezXeFh9r/fTuhnbS/8uIiIiIiKmvAQtRETf2P6QpKuBIymLb/4o6VvA123/cbitC0kLACcCuzJ64CsL2qYYSQsBe1AW1tQnOSd6rWw77/vjcwdlomQ5SUtNUhbe+jbZt07C+WYUSWsBPwI2qJ66QtIutq/pso5TaWas/Kuk13VTR3TH9hOSzgFeTcn49Xbg6DZFz6YELQB8WdKm7bKCSVqW5lbyAF0vaIz2bN9cLZT6EWVRxs8kHQocZjvBIVOApGcBv6P0FxqL0NK/m6KqRQMHUBazTThQoUWCFsbnZspOc0tIWmuSdtWqZ8NOP69LVcbJU4BFq6cekbSr7bMms47oju1/SLobWBp4vqQVbN/WUuZJSb+nZN99OvAu4GtjVFvP0puFoX1SBQlvD/yA8r50sKRtgA/bvni4rQsASdtS7mGNPkNrPy99vilC0oLAIcB7KIvne66SZEruxnXARsBCkrawfcEknHOL2vEtHUtFW5IOAA6tPbWbpDVsH95jHat3U0d0x/btkq6ljGevI2kj239uU/QCyu5AC1Iy/o+1m9OOteO7+tXWAODNlPvjAZQgkyuqRfLH2s7fesgkvYfma6M1UOEh4H4mN7lWzEP1Wal13raX4NS1+tW2iIiIiIjpQkkgGxH9IKk+KPlMmlmGGjeZOcAN1fdubjy2/dJe2xcg6WDgU9XD+gTnA5RrM+HBL9vb9dzAeIqkzSkLBhpbIfdjAtq25+9DPTOepJ8Br6C8Tj466EkuSfNRJg5Wrc65le0LB3nOmaZa+N56Hzqvm/ePftQR3ZO0B/Bdyv/964H1bT/WUua5wJ9p9h9+CbzT9k21MssDJwMvqp56EljVdhaH9oGk51WHKwNfpezWZOBuSkDkuZTrN4cuM3rZvqFf7ZzNWt67RHkNXApcQgng6aWf950+NTMASYdRdi+BkX281gWIra+ldv3Bxs+knzdOkr5LCQw2cIzt9w74fEtSPmstUZ3zObb/PshzzjTVjkvPaXn6CtsbTmYd0T1J3wD2pPzf/7ztA9uU+QBwRPXwbmBj2ze3KbcpcBElAY+B7W2fM6i2zybVNYDyt92XZj8Pys5ovfTzElDXB5KuANan+b7/D0oQQz/6eQn07pMqWczZlM+k3WZJHiupTPp54yTpy5T7mIHzgJcPcgdNSc8B/kTZsXUusLLt2wd1vplI0g2M3g36Zturtis/qDqie1Uiiw9TXm8n2n5LmzL/DhxfPXwCeGW7/pukN9MMwjewRQIn+0PST2oPn0dzRwtXX39hYv287ALUB5LmB/5FCfSGMpZ3HGWM+5IElUwtVcKYk4DNWv9pAtVlPC8iIiIiZrUELUREX0h6kvaDWmMtvJlnteQDe19IWhi4k5LJGkqgwhHAybavHFrDYpQq2/vvKdk5oPMCtk4DYZ0WuOW1NE6S3g0cVT28H3iZ7UsGeL5DgIOqh/+yvdJY5WM0SfcBi9WfAu63veRk1hHdq96frqE5afZZ2x9vU+57lF0UGve4ucAfgBuBpYAtgUVoZqI8x/b2A238LNKhn9duIU63sgtQH0hambIouuEsYO8sQpt6JO0OfK962G43jPHsgtZu8Vv6eeMk6TXAj2n+Hd9r+5gBnUvAGTQDiv6aRfLdkzSHkdmqBdxne6nJrCO6J2k74BzK///7gfVs/6ulzAqUAO6FKdflJkoW2J/YfqgK8H41ZTeuFasyDwMr2H5gsn6XmWwe/Tza/Nu45b2pd5I2Bv5I8zp8wvZnhtik6EDSx4BPM7o/dw/lvrUSzfthfUfiZYC1KffB+ufdpwK4bD9rYA2fQapg+0tp/h1PAN7VmhihT+d6JvBryg5eBs5P0ovuSboNWLb+FHC77RUns47onqT1gCuqh08CL7T9+5YyiwJXU5KcCXgc+BZwGs3xvF0owUYLVGVupwQAzR34LzELZN52aqt20zq3evg4sIPt84fVnuhM0nLAZTQ/k/Yybzvi5/JaioiIiIjZaKJblUVEdKKWr7H+bV5f0T/bURbjCniQkq3mkAQsTEmHUgIWGoNY9wOnA0dSAk0ar43rgbfXvvanZLt+oFbmCeArlB02Pj34ps8YxwO3Ua7BEsDPJfU9c5CkBaqsVI2Mo6ZMqEb3WjMWu81zk1FHdMn2o8AnKAuubwB2l7R0m6L/SbnvNSwAbE6Z3HwJsGjt3+YCHxlEe2PUZEx9QmaiX9G7F9P8W14J7JyAhSnr4Oq7KfeqbwK7AhsDG9G8jpfbnq/xRVmEsz3NgAco/bwPAc8C1pyEts8UP6W5UFDAUZKOrxae9Y2kZwO/AXaoPX10P88xi5zP6Pef84dQR3TJ9nmUxaOifMb9Spsyt9H8nGtKpuTvAvdKuoMyfnEazcVuBr6XgIWBMyP7et1KH69/Nq0dn5uAhampypTcyPAPJeDgrcAytpehLGx/svq3221vV/vaCFgOeA8l27Iomft/YvtZCVgYP9t/oOxc27gHvRm4QtLrJS3Yj3NIWkjSnpTs5PU++Bf6Uf8sdALN69X4/t0h1BFdquaVTqF5z/pGdS+sl3mYMmfR6MMtCLyLEtj9Z0rgz/ur5xtl/icBCwPRLmHCRMb1or/Wqb4bOCkBC1PaoZTPpA2NnUp+xMi+xy2U+djG1/8Av6v+rVHmccqODd+huctMRERERMSskp0WIqIvJJ1Pb5l2O7K93SDqnU0kvRf4KuUaHW17nyE3KdqQtBRwB82gwu8A+9p+qFbmAcqOGW0z8leLfQ8D3km53v8EtrF942BbP7NI2gk4tfGQKjsuJRvUD23f0Olnx1H3SsAelAnpNWkOVt4MbGh7zkTrnq0kvYAS3NPIrHYn8BrbF3VRx+aUhYyNOu4CduymjhisagvmUymLeztlCXsCeLvtTFD3UZWZbRCSTaoPJO0H/DfldZHsu1NUtYj9Ksp1ehJ4te1ftJS5FViBMXb6kbQVcDIlu9uTwB62Tx5k22caSc8BLgAWp9nPmwv8nPK3vcD21ROodzVga0o/7xU0+/QCfkvpkw/qfjpjVZn4jwca2YvPAd7amrF/HHUcB7yMcj3OAd7STR0xMdU9653VQwP72767pcz8lMVr29N+Fxpqz98JPNf27QNr9CyTft7UJukAyhiPgQ/a/n/DbVG005Lh/37K2M6NLWWuBdYAHrW96KhKeGpM7zRKf8LAYbYPalc22pO0JKWftx7N9w4Dd1PGjS4ALgaus33fOOpbhHLdNqdcl50pu2PUsywflbH2iZG0AGWHpZ2rp04DvmD78S7r+BDwuuqpHwOHd1NHTIykVSmJRKC8Hn5k+/425T4JfJz2mcjrz10MvCjXrn8kXc/g5m0TVNcjSR8FPku5RvvaPmoePxJDIGkxyrztwtVTvwDe3ZgjrHbZfAhYCLjZ9mpt6lgX+BLNz7yXUnbWmDPwXyAiIiIiYgpK0EJExCzQMvj1HttfH3KTog1J2wNn0czwvoFb3qglXUbJxPsk8LROW5xL+i/K7gwGfmf7RQNs+owk6X2UvyE0J1Ma1+NW4BLgOsp21rcCDwOPAI9SMkQtUn0tD6xKc5Jz9VqdjQnOe4GXtW6jHeMn6emUCWSA39q+dxh1xGBV2RHfDrwN2Iyy4wLAfZTFbp+1/dchNW/GkvS2QdVt+zuDqnu2aFnM9k7b3xpyk6INSW+k7Ipl4Azbr21T5tc0F6kt17qwt1ZuXUqmtmdQFmCtb/uOQbV9JpK0JfATYGlGLmhruJeyw083/bzl6qeo1XsZpZ/X9nrG+FQLBbD94DDriMGQtBDls9e7aQb8tC5suw7Yyfblk9y8GU3S6vMuNTHZ+al3LcGpe9k+dshNijYk/QdlBy0D37G9Z5syZ9FcqLaK7Vs71LU4ZWH9BpSg/M1tXzaYls9MkpajLH7fgpHBcK2ToQ8w735e606Q9boEfJ0y1p6J1ogxSNoNOJzmuHirkyivpVFBDxEzlaR9KLvRGdjHdnZnnIIkbQucS7lONwLr2X6kpczlwHMoCTEWtf1Eh7q+SNlhxsBPbe80sIZHRERERExhC8y7SEREzAD1BTKLDK0VMS9r1Y5P6zDhdRUlaEGUQf62WWBtf0nS+sBewJaS9rJ9TL8bPJPZ/rKkf1AmIFdk5KKZlYBRiw3HoT652Zjg/AvwRtt/663Fs1uVIe9nw64jBqvKtnYMcEyVlXcZ4HHb9wy3ZTNbAgumvPqCwFG7MMWUsULt+DcdylxFM3hudUb24Z9i+++S9gW+Swlc+BSwd5/aOSvY/p2kjYGvAa+q/VOjr7YUsAlld5/xaJct1MDRlMzyD0+4sQH0J9AgwQpTVxWMv4+kLwNvBbak3DcfpwQQ/RQ4zvajQ2vkDJXAginvytrxOkNrRczLMrXjP3YoczUlaAFKsGPboAXbD0jaE7gQmB/4JM0s9DEOtu+Q9GJgP+BASr+urtFvW6L6gtEBDZ12/Wm4mbL7SXY8ixgH2ydL+hGwHaP7eWfYvmqIzYsYlj/Ujp8/tFbEvKxbOz6lNWChcjUlaGE+SmKL69pVZPsDktag9O12lLSr7VP629yIiIiIiKlvvnkXiYiIGeCi2vGWQ2tFzMuSteNrO5SpBymsMY/6PkzJEguw7wTbNKvZPoOyMOBgyoRyu0lLquc7fXUqfy1lgeHzErAQ0T3bc23fnoCFCM6jZGEF2GWYDYkxLVY7vr1DmXH382yfBPyN0qd4g6QkpeiS7Ztt70gJFPkBJcvuRLT29x6gZFveyPY+CViIGD/bf7d9kO3tbD/H9sa2d7L99QQsxCx1Ps1xnT2qnedi6lmodtxpx8Zu+nmXAL+i9DF2kLTkWOVjtGq84AjKwsG9KX/PuXQep6vrVOYJ4JeU4Lq1ErAQ0R3bT9j+pe1P2d7b9n/ZPjIBCzGLXUhZ3C5gd0krDrk90d5SteNO96tu5m33oTn+tP/EmhQRERERMb1lUjsiYhawfZmkvwAbAjtLerbta4bdrhjl8dpx2+1D6W6S894qg9F/ABtIWs/2lWP9TIxm+wHgs5I+B7yYkhlvK8qOF0uNo4rGZOd9wJ8o2ZXPsH1B/1sbERGzje3bJX0f+HdgE0lvsX38sNsVo9xfO160Q5luJjkBTgPWp/RHtqIsxoou2f4d8DtJi1ICGBr9vLWBVRgZWNzqfuAmyrVr9PN+k8XVERHRD7YflvQl4OPAysChZHHTVDSndtyp31Bf5LbGOOr8BbAtJSBia+CMCbRr1qt2WToaOFrS04DNGdnPW5bSl16YMl/6BPAYJfjkTkb28y6y/dAk/woRETFD2bakg4ETKIkuviNpx2qn4Zg66jsttdtlAbro59m+VdLpwO7A5pJWs31Db02MiIiIiJheErQQETF7HACcSZns+p6kl9i+b8htipHq2cKX71CmPvj17HHU+UdK0ALAxkCCFibItimLAZ9aEChpGcY5yWn7jklucsS0Vi0eXQxYhAnsEJfB/phlDgBeTuk/HCXpFtvnDLlNMdLdtePx9PM2Gked9Z251iRBCz2pdkT4ZfX1FEnz06Gfl8UEERExCT4HvBr4N2A/SQ/Y/uRwmxQt6rtordShTD049QXjqPNfteNVu25RjFIFHJxffUVERAyd7RMlvRR4O/Ay4KdVMpJOO3TG5KuP5y3boUy9n7fmOOq8kBK0ALAZkHmMiIiIiJhVErQQEQMhaWlgS2AtymTNRBcd2vY7+ty8Wcn2zyUdAhwMbAr8StKbbP9tyE2LpvrAVKeAhPpitu3GUecDteOVu25RjMn2XcBdw25HxExQTdC8lpLhek3Gzmw9LyafdWIWqbJ07UQJUF0KOFPS54HDquyiMXxX1I4371DmGsqC+PmBl46jzgVrxytMsF0xD7bnkv5eRF9IWpzex4mwfVyfmxYtJC1J79fp1/1u12xk+zFJrwTOAp4HHCxpO+Cj1W5BMXyX1Y636VDmOuBBymtqG0nz2X5yjDqXqh0/o6fWRUQMWOYDpwdJAjagP/3xT/e3dbPaO4GHgb0pCUmukHQk8I0EL0wJt9SO1+hQph608OJx1Dmndpzg1IiIiIiYdVSSBkdE9IekHYCPAVsA6rU6yiDl/D03LJ4iaX9KlrYFgEeB44FjbF861IYFkpaiZO0wcIPtZ3UodwMlu/9cYBXbt41R56cogSoGPmL7C/1ud0RELyStSdkGu55tstc+RPoPAyLp2cBrKMElrZOc3V43205wSR9JWhv4LvB8ynv/HOAk4GzKQqk5jNzWfJ6ya0l/SFoAuI/yWnkQWNb2o23K/QHYhHKdXm773DHq/BrwrqrsB2x/aQBNj4joSbU73fspwanP7Ued6ef1X/U+9TaaQcS9LpJOP6/PJC0EHArsSzNA+2/01s9LAFCfSLoTWJoSgLpqu7E6SedTFrIZ2Nv218ao71Rg56rsf9r+3wE0OyKiJ5kPnB4krQ8cCLyKkUFxE5br1H+SdgSOpIy3uvq6nIn18xIA1CeSlqfsgGXgKtvrdyh3G7AcZWfO5W3fN0adBwKfqer8qO3D+97wiIiIiIgpLEELEdE3ko4A9ms8rL7XbzLdDFqaDFIOjKRNgGMpOy40rtG9wD+Z2ODXeDLBxjhI+jNlIYeBF9v+bZsyJwFvqMqcYPtt46xvT9vfGUjDI6Y4SU8DNqYMHD+dCWSQasjCjv6R9CzgAsp1Ec33/16l/9BnVda8rwK7MfIa9XK9cp0GoHpdfZ8SuABdLl5rkQWHfSTpdODVlGuyj+2j25Q5HNi/KvM3YFPbj7cptywlk9uSVdldbZ82uNZHTE1V5v6tKZ9te+3nZWFHn1W7AB0HLM7oPsNE3p8yTjQAkjYHfkAzy2dP/TtynQaiCix5I/BBymfbhgn39XKN+kfSN4A9Kdfj87YPbFPmA8AR1cO7gY1t39ym3KbARZTgFAPb2z5nUG2PmKokbQO8kv7189bqV9si84HThaR9KQvh52PkNZlo/yHXaQCqwJIPALtSxnl6uVa5Rn0m6RrKztCmjNP9uU2Z0ygB4Aa+ZPsDY9T3O+CFVdm9bB87iHZHRERERExVCVqIiL6Q9B6gkfGpdcHhQ8D9wCMTqbtTtvmYGEkvBw4AtqX3gcoMfvWZpIOAQyjX4gzbr21TZmfg1Ophx2AESR+mZOFrlHue7T8Not0RU5WkV1LueVvTQ6BCXe55/SPpZ8AraPYdngQuBS6hBNL10n9IkFafSFoO+A2wNs3gEsiOGFNKdZ2OpAQ2tt7vJnqtco36SNIelJ0wDFwPrG/7sZYyzwX+TPN19kvgnbZvqpVZHjgZeFH11JOUjL63DvQXiJhCJC1I+dz0HmCJflRJ7nl9JWlbSgb4xntSglOnIEkbA7+juWtWrtMUJOnFwLeB1ftVJblGfSVpO+AcymvofmA92/9qKbMCJVvywpRrcBNlvOInth+SNB8lwPVoYMWqzMPACrYfmKzfJWLYqkD8k4DNWv9pAtVlMfwAZD5wepD0ekpgKvSvjwd5PfWVpI8An6K5k1bbYuOsLve8AZB0KPBhyt/3RNtvaVPm34Hjq4dPAK9sF3Qq6c2UwH6q+rawffFAGh4RERERMUUlaCEieiZpfsrWiEtXTz1J+cB9MnCJ7buG1bZokiTgKOBdnYpMsOoMfvWRpNWAa4DG3/QVtn/ZUmYB4Arg2TQXFZwN/Ai4kbLF7y6UbeSpylxve80BNz9iSpF0GPChxsPaP7VO0rR2iNvdDzPg32eSVgZuqD11FrC37X8OqUnRgaQTgDcx8rVzGyXApNfgkk/1o42znaTVgV9RMiRnweEUJWlhSj9vpeqpz9r+eJty3wN2p/n+NBf4A81+3paMXFx6ju3tB9r4iCmk+jx0NiVwp9usrmMF3uWe10eSrgDWp/me9A/gFPoTnJr+Yp+0ZPkUcB+lX96P6/SrPjVzVqsyjZ8FLET/FhtC7nl9J+limrudnWJ7tzZlPg18jNoYA2UsfQ5lV5r6dTbw7ewCFLNJFYx/Gc3AnU5jeJ3uh536hLnn9UnmA6cPSTcAq9B8HZ1HdZ2o+nm2Hx1eC0PSPsBXqocJAJqiJK1HmZOFcs97oe3ft5RZlLIj6jMp1/Fx4FvAaYyct92XEqAi4HZgZdtzB/5LRERERERMIQlaiIieVdnzzq0ePg7sYPv8YbUn2pP0KeDg6mF98OsByqLRXga/tuu5gfEUSccA76weXgc81/bDLWVeBpxJc7eMdm/o9UnO99n+6mBaHDH1SNod+F71sN3i3fFkim830ZlJzj5pyTh+JbCJ7ceH26poJWkZymR0I0vyZcD7bf9maI2KUST9AngZ2bVkypO0J80++aPAlrbvbimzHHARzWzKrYuy64t3nqBMlv5hkO2OmEokfQz4NKP7c/dQMlKvRDPT9R9rP7oMZdeghWs/Oxe4uVEgCzv6o8re/0eaf+dP2P7MEJsUbUh6NnAVzet0LLCf7QeH16poJelKYB0SADTlSdqK5niegf3b9PPmB84AtqdzoHHj+TspY4K3D6zREVOMpG8AezLys+0VlODvx2kGd98KfL32o8sAzwO2oPl56Qngh8BjALbfPim/xAyX+cDpQdILKbtpNfp5b7N9whCbFC2qxBa3UBazQwKApjRJPwBeXz38E/D81mADSW8ETmRkcOqoqqrvJp+TIyIiImKWGmubuYiI8Vqn+m7gpAxQTj2SlgA+SHOA5AHgCOBk21cOrWHRyYcpC3mhXLNRWTZsn11tw3wUzV0ZWrNONQbGfpqAhZiF6kFacykD/mdQJjkN/Ln6frntjRo/JGlpyiTnnsAbqqefAA6kTHRG/6xYOz4pAQtT1naU9xlTskJta/v+4TYp6qoFh42ABSiZeN+bRWhTk+1vAt+cR5k7JL0UOBXYmNGTnPWAhbcnYCFmk2qx5740Xxc3U/ppZ9i+p1r48SBV1sLWAHtJi1N2D/oEJQPi/MBPbP/XJP0Ks8WmteNzsxBjytqidnyp7b2G1pJoS9JmNAMWoCxsOmSITYox2P4t8Nt5lJkr6bXAkcC7aR+cKkoSk50SsBCziaTFaO7yCPBz4N22b6j+XcBOlB1Jnmy3c6OkdYEvUQKDFqDsVLyD7TkD/wVmj8wHTg8b1I5/lICFKelFwDNoBlm9wvZ5w21SjOGDlPklKNfsaZTg4afY/l61K8PHaZ80qz5vewnw+UE2OCIiIiJiqppv3kUiIuZpmdrxRUNrRYzlRZQBFFEWcGxp+5AELExNtu+x/avq69e2H+tQ7lhgG8rrrjUzmyhZpA4Fdh1ogyOmmGoB7waUAeAngR1tv9P2j2z/xfblwG2U18nq9Z+1fbfts22/CXhxVW5BygDy5lkE3FcL1o5v7lgqhm2l2vHxCViYkuoLDq+kLG7KvWqas30dsDnwHuBCSgBeYxHb/cBJlB1qvtuxkoiZaWNg+er4fmAr2yfYvgfA9qOUnQQFrNr6w7YfsH0MsCHwf1W5fSV9djIaP4ssXzs+o2OpGLYVascJ0J6aWgOAErAwA9h+zPY+lHGLQ4FfAX8HLgdOpwQzPKcau4iYTTYDFqmObwRe1whYgLL1KWW3GQHPlDQqMZ/tv9t+BfD/qnLPB7J7YH9lPnB6WK52nIXwU9P6teOTErAwtdm+0fZ3qq/jOo2R2/4kJRlWY1yirjGudxLw8iRxioiIiIjZKjstREQ/3Fc7brfVYQzf2tV3UxYcXjHMxkT/2L4A2FLS2sCWlEUHjwPXA2dncWnMUs+vHZ9p+xdtylxNeb0sLmlp23e3FrD9W0nbUbbSfgZwlKTzbd8xkFbPPvVF1St1LBXD9rTa8bVDa0WMJbuWzFDVtTwGOKbKLr8M8HhjcXbELLVR7fhU2ze2KXMVsAawkKRn2r61tYDtuyW9CriAsmj0Q5JOtn3ZANo8G9Xfi/KZdHq4c9gNiLbqC0MTADTD2P47cNCw2xExhaxbOz7F9iNtylwNPIeSlG9Vyq4ko9j+gKQ1gJ2BHSXtavuU/jZ31sp84PTwcO24bVKsGLolascXDq0V0Xe2T5b0I8oOxq3ztmfYvmqIzYuIiIiIGLoELUREP/yhdvz8jqVimBarHV82rEbE4Ni+mjJpExEjM4b+pkOZq4Ctq+PVgVFBC1AWEUjaF/guJXDhU8DefWrnbHceZevr+YFdgGQ4nppuqh0vO7RWxFjqOyhm15IZyvZc4PZhtyNiCqgv4P1jhzJXA9tXx2sAo4IWoOy6IGlPygKR+YFPUha2Re/quzquM7RWxLxcUzteY1iNiDHVF+wmACgiZrqlasedFnTWx7/XoEPQQmUfYAfK7g37Awla6I/MB04Pf64dbzi0VsRY5tSOWzPyxzRn+wngl9VXRERERETUzDfvIhER83QhZXBYwO6SVpxH+Zh89Yx5i3QsFRExM9QDtTot8Gyd5OzI9knA3yjvc29ot/18dM/27cD3KX/XTSS9ZchNivZ+TTNz3quH2ZDoqL4DRnYtiYiZbqHa8b0dynTTz7sE+BWlP7KDpCV7al00nE/z+uwhacEhtiU6O4/movg3DLMh0dFfa8frDa0VERGTo561v90uCzAymGGNMSsru22dTunnbS5ptZ5aFw2ZD5wefkMZFxelP77EPMrH5Lu0drzZ0FoRERERERExyRK0EBE9s23g4OrhYsB3MiE95VxQO966Y6mIiJmhnoFy0Q5lxr2YrXJa9X0pYKuuWxSdHEBzAu0oSS8dcnuihe0bgJ9RrtGLJO0w5CbFaI1dSwB2HWZDYuIkLSppWUmrSFqt269htz9iEs2pHXcKMBj3YrbKL6rvC5HPy31h+2HgS5T+w8rAocNtUbRj+17gG5TrtLak/YfcpBjtfOC+6ngPSQuNUTamGEmLS9pY0islvV7SmyW9tduvYf8eEZOovgtqp50e6+N5a46jzgtrx1kU3AeZD5weqizvn6seLg0cNcTmRBu2Lwaup/TFd0sAUEREREREzBbJEhsRfWH7xGqh4duBlwE/lfSWKotyDJntv0i6HHgusJOkdWx32mI5phBJm1IWSK9FyZ68GGW3jG4DD207i4FjtqhPci7foUz9HrjROOqsZzJfk5KRN3pk+1ZJOwFnUgJCzpT0eeAw2w8OtXFR90FgG8p70PGSXmr7L0NuU1Rs3ynph8AbgY0lvc32d4bdrhhb9dnptZR+3pp0Xnw9HibjOzF71McYOu0uU1/M9oJx1Pmv2vGqXbcoOvkcZZemfwP2k/SA7U8Ot0nRxsHAqyjvRYdKutP2t4fbpGiw/aikrwAHAc8EDgM+MNxWxVgkLQO8n9LPe26fqj2uT/VETHW31I7X6FCm3s978TjqnFM7Tj+vTzIfOG18BXhF9bWHpMeAvW132skkJt8ngW8DT6OMub7K9uNDbVHMk6SlgS3pz7ztO/rcvIiIiIiIKU8lIUJERO8kiTIItnf11F3AkcA3Mlg5fJJeTdkO2cBlwEuqrHoxBUl6N3AgsEo/qqMMfs3fh7pmper+tm718O+eQAeqqmMdyvWYUB0xPpI2Af5Aud+daXvHNmUWoWSsnB+42faYWaolvQf436rOg2wf1u92z2aS1ga+Czyf8jeeA5wEnE3Zcn5O9fy4VTsERJ9I2hE4GViY8tr5oO1jh9uqaJC0MvBn4BnAw8BOts8ebquiHUlrAicwciG1eqw2/bweSFodeGX18Ezb/5xAHatVdQg4y/b1/Wth1Elai7JYzcBFtrdsU2Y+4F7KwoF7gWVsPzlGne8HvljV+THb2RWgTyQtC5wFPI/y9/0/4KO2fzfUhsUIkp5N6XevRrlOJ1I+86Q/PQVUn10vpiyAN3BIAoCmpiog/zhgcUb37yYyBpTxvB5J2h3YpXp4qu0fTKCO3ao6BPzI9vf72MSokbQ8JZjUwFW21+9Q7jZgOeAxYHnb97UrV5U9EPhMVedHbR/e94bPUpkPnB6qfsTJlGBiA9cAnwK+b3vuMNsWhaSTgDdQrs/ZwJtt3zHcVkU71Q7EHwO2oPexvPTzIiIiImLWStBCRPRdtajtSEqGAVdflzOxRYfJMtBHkr5AyZZsysK2PWxfOdxWRZ2kBSgLBHalOejVeM30MgiWwa8JqhZG/QjYoHrqCmAX29d0WcepNLPs/RV4XTd1xPhVr6P7KNltHgSWtf1om3J/ADahvMZebvvcMer8GvCuquwHbH9pAE2f1SQ9C/g+JXABJraoo8G2k3W8zyRtRXmPWpVyfa4GvkEVXJJgyOGStDXl/WoZ4AngUMquJQ8PtWHxlOo+dwFlgY0or6NeJzkh/bwJqyacTwEWrZ56BNjV9lmTWUd0R9KdwNKUe92qtm9rU+Z8SvZdU7KJfm2M+k4Fdq7K/qft/x1As2ctSQtR3pP2pbkrzN/oLTg1Wcf7rAow+RrwOsr1mAv8gt6u06/728rZS9KKwA+ArSnX4dfAh21fPNSGxVMkbUt5vTQy7KafN2SSDqC8/9R1tWi9H3VEdyRdQ9n9x8Cmtv/cpsxplN1MDHzJdscdaCT9DnhhVXavJF/ov8wHTg+S9qUEKzyDck3uo+wkPNF+3qf73MRZS9L8wCHAAZS+w13AEcCxtu8aZtuiSdIRwH6Nh9X3+uumm35fo5+Yfl5EREREzEoJWoiIvpK0PmWb8l2BJRn5Ib3bG04+sA+ApL0og8iLAo8C3wK+bvuPQ21YACDpYMrgMYyc4HwAuAG4n7IQqmu2t+u5gbOQpHOA1r/debZfOpl1RHcknU4zg9Q+to9uU+ZwYP+qzN8ok6Gjtl+uFvBcTXlfM2Uh4mmDa/3sImk5yvvSGxi9hfJEF3mk/zAg1fU6gwSXTCmSnlcdrgx8lbJTk4G7KYEm5wLXk11LhkrSz4BX0OzjPQlcClwC/JPe+nnf6VMzZxVJlwPPaXn6CtsbTmYd0R1J3wD2pLyWPm/7wDZlPkBZ6AHlXrix7ZvblNsUuIiymN7A9rbPGVTbZ6MqoPiNlAQKG9f+acJ9iPTzBqMKgPwi6edNKdX9DMp9al+a/Twoi0J76eclAKhPJF0BrE+zn/cPSlBjP/p5Xe8CFSDpBkbvYHuz7VUns47ojqRDgQ9T7fxj+y1tyvw7cHz18Angle36b5LeTNn9hKq+LRLs1V+ZD5weJC1N2RHjbZTgkob0x4dM0k9qD58HrFQdNwKA/sLE+nkJAOqj2i7cMDow9SF66+c9q7fWRURERERMPwlaiIi+kfQRymLrsSYlx7v4MFkG+kxSPSvRMylZeKE50DWHsih+Dt0PfmXhdR9IWhi4E3ha9dQDlIU2J2dHjOGRdB+wWP0p4H7bS05mHdEdSXsA36Xcz64H1rf9WEuZ51J2nWnc834JvNP2TbUyy1O20H5R9dSTlIy+tw70F5glJK1Oyeq1Ksk6PqVV71EHUxZKLVH/px6qzXXqE0lPMrr/1i7rV7ey4LBPJK1M6Ws3nEXJ/p5FaEMkaQ6j72n32V5qMuuI7kjaDjiHcn+7H1jP9r9ayqxAyRq6MOWa3ETJXPkT2w9Jmo8S4Ho0sGJV5mFgBdsPTNbvMtNJejHwbWD1flVJ+g99J2ld4Fhgi05Fuqgu43l9No9+Hm3+bdxyjfpD0sbAH2lei0/Y/swQmxSApNuAZetPAbfbXnEy64juSFqPssstlDG4F9r+fUuZRSnJRZ5JuSaPUxIznQbcCCwF7EJzlycBtwMr25478F9ilsh84PRQjZEfxcjPrD1VSa5T33To50ECgKaMaieMf1F2e4Ty3nQcZc7okuyGERERERHRvSw+iIi+kLQP8LnqYV+zDETfPJeRg1uN48a1egZlQL8bjQWm0R/b0VzY/gAl+9Nfh9ieKP5OyXLT4Oq5ya4junMqcDMlO9EawMeAj9cL2L5c0g+A3SnX5OXAtZL+QHOSc0tgkcaPAOcmYKGvvg6sRvO9xJRMlD1no4z+qTKynU3Jjlx/7+9HgEn0V/36THSL8hiMF9O8PlcCO7fb3Scm3fnAaxn5ujl/CHVEF2yfJ+lSSjb4pwNfAXZrKXObpCMofUBTsiR/F3iyCjRZHFiIkQFe30vAQv9I2oYSoFX/O8cUI2kjyj2rkR251yDiXOvJ0etYXMbz+mvT2vG5CViYMk4A9mPkfe27Q6gjumD7SkmnAK8H5ge+Ien59WAD2w9L2p+yq6CBBYF3VV919X7e/yRgoX8yHzg9SHo95T6W/tnU19o3GytgdSzp3/Xfi2gmAXwc2MH2+cNrTkRERETE9JeghYjoWZV599M0B0OSZWBqG2twK4OXw9XYBtTA8QlYmDL2BU6nmVntTuA/u6xjH+CntTrumkAd0QXbj0r6BCUzPMDukv6f7btbiv4nsDnN7K8LVI83qx7XJwzmAh8ZXKtnF0nPBl5G8+97FvDeZB2fkv4X2KT2WMBtwKUkuGQqUcv3mFrq2VhPSsDClPFuyi5njZ3jzgHeM4E6FqW8p2mCdUT39gPeWR1b0tJt+nmfovTrtqe5mGp+mgsOqD1/F/DRgbZ49vkaZaeLRl/vH8ApJDh1qvkGJVi7cZ3up/TLc52mlvTvprbla8dnDK0V0erDlPf3navHpwFfmEAddwKvqx7/GDi8D22LsX2Q5mvJlP76/fUCtr9X7crwcdonVjDNft4lwOcH2eDZJPOB00OVHf7/MTIo9Tyq60TVz7P96LDaGEDZkTOBBlPbOtV3U8bzzh9iWyIiIiIiZoQELUREP7yIkqXfwBPAK2yfN9wmRRu/JoNfU91StePLhtSGaGH7ompx9dbVU7+1fW+XdVzcax3RPdvfBL45jzJ3SHopZWeGjRl9n2xM6jwBvN32HwbR1llqi9rxlcBOWcQ79UhamZLhsPHa+BPwX7Z/M7xWRRtvH3YDYp4WrB3fPLRWxAi2bwO2l7RY9fjBCdaxQy91RPds/xb47TzKzJX0WuBISnBJPdsu1WMB11H6IbcPqLmzjqTNKIs7Gn/rT9g+ZIhNijYkbUjZsaRxnY4F3p/72JTzrHkXiSGrf469v2OpmFS2n6Bkgv/cvMrOo45Dq6+YJLZvBL4zjnKflHQFJZBk9ZZ/bvT7TgLek/Gmvsp84PSwJWUH4kY/7222jx9ie6IN22sMuw0xT/WkBxcNrRURERERETNIghYioh/Wrx2flAHKqcn2tsNuQ8xTPTPoIkNrRYxi+z7gZ8OuIwbD9nWSNqcs+n0bZZeFRj/5Pkp2t89m95O+S9bx6WFrYD7KJOeNwDa2sxBnirE9zwUdMXT1XWRWGloroq1+LNDNIt+pyfZjwD6Svgy8lbJ4ZwXKAtPrKbuhHZcMo323ae343AQsTFnPrx1favtdQ2tJdJSd6KaFK2vH63QsFRF9Z/tkST8CtmN0P+8M21cNsXkzVeYDp4cNa8enJWAhYsLuqx0nMWBERERERB8kaCEi+mGJ2vGFQ2tFxPRXz9KxJfCVYTUkYrapFswfAxxTbZ+9DPC47XuG27IZbb7acbKOT12r1I6PT8BCxISdR8lCOT+wC/DZ4TYnYnax/XfgoGG3YxapZ6M8Y2itiHlZvnb8w6G1ImL6Ox+4F3g6sIekjyUoP2LyVDti/LL6isHLfOD0sFTt+NxhNSJiBqjvvP38jqUiIiIiImLc5pt3kYiIeZpTO1anQhExNtuXAX+hvI52lvTs4bYoYnayPdf27QlYGLhra8fJOj51LVg7vrZjqYgYk+3bge9T+nmbSHrLkJsUETFIj9SOE/A4dc2tHd85tFZETHO2Hwa+ROnnrQwcOtwWRUQM1JzaceYDp64HascJpIuYuAuB6yj3u90lrTiP8hERERERMQ8JWoiIfri0drzZ0FoRMTMcUH1fCPiepKcPszEREQPUyDoOsOswGxJjurF2vNzQWhExMxwA3E6Z6DxK0kuH3J6IiEH5a+14vaG1Iublqtrxs4bWioiZ4XPA7yn9vP0kfXK4zYmIGJjMB04Pf6odbzi0VkRMc7YNHFw9XAz4jqQFx/iRiIiIiIiYB5V+dkREbyRdC6wBPAisbftfw21RxPQl6VOUQTADfwbeZPtvw21VxMwhaVHKAPMiTCCI1/YNfW/ULCXpROCNlPvdnra/M+QmRQtJqwD/rB7+1vaLh9meiOlO0guAM4GlKIFbnwcOs/3gMNsVMd1JWhxYi7J7Uy/9vOP63LRZSdLCwG3AEsCtwJq2Hxtuq6KVpCUo12lh4B/Aus5kwbQhaUl6v+f9ut/tms0kLQucBTyP8hn3/4CP2v7dUBsWMY1JWhrYkt77ebb9jj43b9bKfODUJ2l+4GZgeeBuSn/8vuG2KuZFkoAN6M9n20/3t3Wzm6RjgbdT+nhnA2+pdlWNiIiIiIguJWghIvpC0luBb1M+rJ8LvMp2thydwjLgP7VJ2p+SpW0B4FHgeOAY25eO+YMRMUqVyfq1wFbAmsCSPVRn2wv0pWGBpJUpwVnPAB4GdrJ99nBbFa0knQG8ktLP29H2mUNuUoxB0rOB11Duea39PHVZXe55AyBpbeC7wPMpr6s5wEmUSc/rqsddDdYkoC5mI0nLAO+n9POe2486bc/fj3oCJB0CHES5n33J9geG3KRoQ9JXgfdSrtNHbR8+5CZFB5IWAN5G87PtM3qsMv28AZC0EHAosC9lTA/gb/TWz0tAXcw6knYAPgZsQfefY0dVR7nnpZ/XJ5kPnB4k7Qf8N+U6fd/2m4bcpOhA0vrAgcCrKEkuepZ7Xn9VASVfAfaunroLOBL4RoIXIiIiIiK6k6CFiOgbSScBb6CZZeDNtu8YbquiVQb8pw9JmwDHApvSnNC8l5Lxeg7dTXLa9kv72b5okvQ0YGNgOeDpTCDzTUMmo/tH0prACcAL6k/3WG3ueX0maWvgR8AylKzjh1Kyjj881IbFUyQ9B7iUkoX3buCltv883FZFqyog9avAboy81/Vy38s9b0AkPQv4PiVwAbpcvNYiiw4HpMrevzWlP95rPy/B3n0kaSfgOGBxRt/nJvJ6ymfbPpO0CHAxJaDEwCG2PznURsUokpaiBBGvAswF3mX728NsU4wmaXPgB8Cqjad6qM7knjcwVXDJG4EPUsaJGibc18t1GgxJ21CC8/vVz1urX22b7SQdAezXeFh9r7+GurkH5p43IJkPnPokzUe5NttSrtNxwHttPzLMdsVIkvalLH6fj5H3t4n2HXLPGyBJO1Ku11qUa2TgciYWnJpxooiIiIiYlRK0EBF9U203eghwAGVQ5C7gCOBY23cNs21RZMB/+pD0cspraVt6H6zMdRoQSa+kXKet6SFQoS7XqT+qxaAXUCaeRfOe1au8lvpI0vOqw5Upi61XoVyru4ETKdnaridZx4dO0uspu/4sDNwH7Gf7W8NtVTRIWg74DbA2zXseJFBryqmu1ZGUxR2tfYeJXq9cpz6TtCDls+17gCX6USW5Tn0jaVvK4pvGayj9vClK0oqUhdZbU67Tr4EP2754qA2LESStB/yY0o8wJfD7INs3DbVhAYCkjYHf0dw1K/e8KUrSiymZx1fvV5XkOvVdNV50ErBZ6z9NoLr/z959h0lalOsf/95kJIPktIAkEREk56ASFZUgoIDhABL8iQTPETgSFfAoKmYFJahIRgQDItGAJAFBkBwls0tOu3v//qhq+p3eDjPTb+/bM/18rmuvqZ6prq6Zd7u7uqqep2J+vGSSPgt8P99sfL17BXgRGNWGa9vLdNe7UBTrgWNDDsT/MSmgzsA9wJeB82xPrbJv4a351nPyzbLGeBDvSz2RT8Q4CNiBdJp3rNuGEEIIIYQwChG0EEIohaSLCzfXABbL5VqWgX8yuk2HkWWgJDHhPzbkI0Z/AOzVqsoom47Jr5JJOgE4tHaz8KPG51fja16zaxiLnCWT9FtgK+p/26mkTPE3kE4r6eY17/SSujnwJE2l9XMkso73iZzBH1Km0NOpB5fcBZxCDi6x/Xw1PQySfg7sxtD3oCdJr3vdvuYdXUYfA0haGrialCU5Nh32qZwh+XJgI0Ye6N0uYCiuU0kk3QGsTP05dB9wPuWM8x4qqZsDT9JBuTgTcAD18QOkTJTdBKfG6XQlkfTRXJyLtPGwdp0mA7+nu+t0TVn9HGSS/gqsS/017wXStSnjNe/qkro58HLW/t8Ds1DehkOI8UOpcgDxLcAiNB+Pdwr+bjUmjOtUgrwJ/gmgNgcxlZQZ/lzghtgI3z9iPXBskHRy4eaHSeM8SNdkEimg+EFGN847ptv+BZD0MPXxt4Arya955HGe7der62GokfQ/wNGkz7ctqw2zuVgPDCGEEEIIAy2CFkIIpWix6RAiy0BfiAn/sUPS0cD/5pvFhbOXgIfpbjF6s647GACQtDPwq3yz2YbD4WS4brbQGa95JZC0OOn5UvN7YL/YhNZ/CuOHYmb4IVVG2XQ8l0oUwSX9TdICpHFeLeP4LcCBtq+trFOhKUmXAe8jAur6mqQjgGOYdjw3EXiVtCHHpOv1j8JdFyBlKZ+1cN8pwGO1ChHs3b2ccfwf1P/GR9o+rsIuhRY6jB9o8rNhi3FeeWKc198kvQO4m/q1OJV04tnL1fUqNCPpLmAFIqCur0k6Bfg0Q8fjdwD3Am8CO+efPQ78pHDXBUgbs9ejPn8xGTgPeAPA9qemyy8xjuXTtK7IN98EtrR9VVX9Ca3FeuDYMIzrFOPxCklal3SaVu067Gn75xV2KbQgaX/gO/lmJAUMIYQQQgihS7FwEEIoW+Omw+FkGG8mIqrKtRFpcQViwr9vSZoLOJj6//+XSEcqn2v7rso6FpopBpZMIQUBXUpa5DRwW/56u+131+6Us5WvQVog/Vj+9mTgMNJCZyjHxtTfj+4CPmz7zWq7FNpQw9fQv4rjvOEEZ4XpYzNgRtI1eQTY1PaL1XYpNMqbDmsBC5AC6vaNTWj9JQd7H0D9Oj1GGqddanuipFmBl0mvfU81BgVLmpN06smRwKKk5+bFtj8/nX6FQbB6oXxFBCyMOd3O9bQKdA3dazbOK/5suMo6RSgk6xXKN9reu7KehJYkrUU9YAFSQN2xFXYpNCFpDuqn0wH8AdjH9sP55wK2J52WMbXZiXOSVgS+DXyAtL76DtI8+6Se/wKDYYX81cBZsX4xJsR64NjUzd87xuPlWaVQvjACFvpTngcqJraIpIAhhBBCCCF0KYIWQghleZiYqOpnMeE/NmwEvC2XXwLWt31Hhf0JTeRNh6uQnk9Tge1sX9ZQ50lgYWDp4vdtPwdcDlwu6Xukic1FgBOBh22f2/vfYCAsUiifFQELfS0yEY4dEVzSvxYrlM+MgIW+Vdx0eBewfbw/9aXVgIWon6Swge1Haj+0/bqkh4EJwJKNd7b9EvBjSecBFwEbAgdIesn24b3v/kBYqFC+tLJehOGKccPYUOY4L655uRYulCPRQf9qDKiLgIX+tBYwG/Vg74/Yfisrsm1Lug94J7CopJlsTy42YPvfwFaSTgIOBNYETicFO4TuLVAo/72yXoThiPXAsSPGZv1rwUL5ysp6ETrZCJiP+ilLW9mO6xVCCCGEEEIXImghhFAK2xOq7kNoKyb8x4bl81eTNh1GwEJ/WrNQ/l1jwEJ2D2lzwZyS5s/BCkPY/oukzUhHAM8H/EDSVbaf7kmvB8vMhfJjlfUidGT79Kr7EIZlmgyToa+8rVC+v7JehE4ioG5seHehfEExYKHgblLQwiySFrX9eGMF289J2gb4GynY9VBJ59q+pQd9HjTF504EafW3ZaruQBiWzTpXCX3imao7EFoqzrtGQF3/WrFQPr8YsFBwDyloYQZSgOoDzRqyfZCkCcCHge0k7WD7/HK7O5BeKJRjQ3wfi/XAscH2DFX3IbT1aqH8RmW9CJ2sXCifFQELIYQQQgghdC+CFkIIYTDEhP/YMEehfEtVnQgdFTMdXtuizt2kzLqQTluYJmgBUoY2SQcAvyAFLhwN7FdSPwfZQ4XyYi1rhRCGxXYELfS3Rwvlt1fWi9BJcbNABNT1r+Kmw3+0qHMP8IFcngBME7QA6dQFSZ8GrgNmBI4ibWwL3bmrUF6hZa1QOdsPda4Vqmb76qr7ENq6t1CeUFUnQkfFze8RUNe/5i2U725R555CeQItghay/YEtSac3HAJE0EL3bi6U12xZK4QQxofbCuVVK+tF6GSuQvm6ynoRQgghhBDCOBIR9iGEMBhiwn9sKGbNm62yXoROisElT7Wo07jI2ZLts4A7SUc1f0xSBJV270rSUb0AH62yIyGEMB1cQz0oddsqOxLaKp6CEQF1/WuWQvn5FnVGMs67AbiaNM7bUtI8XfUuAFxF/drsKmnmNnVDCGGsu5L6hviPVdmR0Na/CuWVKutF6KSYyKfZKQswNJhhQtvG0mlbvyGN89aWtFRXvQuQNoM+QPqb7ixpkQ71QwhhLLuWtL4k0mfbuTrUD9WYVCirqk6EEEIIIYQwnkTQQgghDIaY8B8b/lYob9iyVqhaMWve7C3qDHszW3ZR/jovsMGIexSGsP0UcDbpNe89knavuEshhNAzth8Gfkt6zdtI0pYVdyk0Vwyo26HKjoS2JhXKrQIMhr2ZLbssf52FGON3zfarwLdJr3mLA8dX26MQQugd288Dp5Be85aXdEjFXQrNXUX9lNtdJc3Spm6oTvEU1FYn1BXn85YdRpvFjMtrjbhHYQjbBv4335wDOD0CVEMI45XtycBX8835gR9U2J3Q2o2FcrzXhxBCCCGEUIIIWggh9IykRSW9W9KGkjYe7b+qf4/xICb8xwbb/wRuJy1Gby9phYq7FJorLnIu1KJOcTPbu4fRZjH78nAWRUNnX6SeqegHkraouD8hhNBLBwMv5fKZkuJY+T5j+xngPNL70mqS9qy4S6G54ilarU7EKG5mW2cYbT5RKC854h6FZr4K3ER6Pn1B0lHVdieEEHrqf0lzBgKOl/TJarsTGtl+HfgO6RotCpxQbY9CC/8plCe0qFMc5w1nXWJSoRzjvBLY/iXwM9Lz6X3AJZJazb+GEEZB0tySlpC01Gj/Vf07jCPfAX5P/bSFn0qKU9j7iO3rgQdJ12inSAoYQgghhBBC95T2sYYQQjnyBqmDgK1ovZl3JGx7phLaCYCkU4FPkY7DvhzYPWckD31C0rako8UN3AJsnjPrhT4h6T3AzaRr9Dvb2zWpMxspy96MwGO2207kS/os8P3c5uG2Y4G7BJLWAX5HOsFiMnAicILtl6vsV2hO0juAD5JOG1mOtFl0DmA2Rn70cowfekTSnKRM4asDCwJzM/pgeNv+TFl9G3SStgPOBWYlvQcdbPvUansViiQtDtwGzAe8Cmxv+/JqexWKJC1H2qxm4O+2129SZwbgedJ71PPAArantmnzQOCk3OYRtuNkgBJIejtpc8capL/tn4Ev2f5rpR0LHUmah6HjvBGPI2xfU3a/AkjaBNia8sZ5y5XVt0GXPytdDixFes37JWnu4OFKOxbekueBrgfeRbpGx9o+qtJOhSHyxvcnSNfnbtsrt6j3JOk18A1gIdsvNKuX6x4GHJfb/JLtr5Xe8QEkSaSNvPvlbz0LfBM4JdYy+lO+Zqsw7XzeaMZ5x5Tbu5Bf//YljfNWI50C2I2Ydy1RHkOcC2xLej+5FzgaONv2lCr7FhJJewCnka7PFcA2tt+stFMhhBBCCCGMYRG0EEIojaR9gW8BMzHyzYWt2PaMJbU18GLCf2yQ9H+kjMkmbWzb1fZd1fYq1EiaibQZdDbgZeDtOateY72bgfeQruP7bV/Rps0fAXvlugfZ/nYPuj6QJC0P/AJYk/T3nQScRdrw8UC+PaIBcWwMKZek+YHvATsxdPzQzVgixg8lyyc0HQt8FpirjCaJ61Q6SRuQNrEtSXptuwc4hfyaF4GQ1ZO0IXAhsAApoO54UkDdq5V2LLxF0jPA/KTrs6TtJ5vUuYqUfdfAfrZ/1Ka9C4AP57qfs/39HnR7IEmahfQcOoA0DwFwJ92N884osYuBtz4/7Ql8iBScOl+XTcYmqZJJWob0GWmtxh+NojkT47yeyMFaPwI+Qvo7TwEuo7vXvAgAKlHOvHsOKcjbwDXAf+cMvaEPSLqXdMKpgdVt39akzkWk9ywD37Z9UJv2/gqsm+vuHUHj5cqB+d8kbYR3/nc7o3vNi6QJPSBpZeAwYBtS0piuxfihXJI+BJxOCkaFctZuY5zXA5IOIAUrzEd6fXsBuJrRj/MiAKhEks4CPkY9KeAnbD9dba9CCCGEEEIYmyJoIYRQCklbkBbKRH2Bsqj2YtNuQqz4glSrF5NfPRAT/v1P0t6kazQ78DrpWOyf2P5HpR0LAEj6DfXMN/vb/mGTOl8DDsl17iQthk6TfSVvPLgHmCfX3cH2Rb3r/eDJm3DOJgUuwAgn+BvEJqkSSVoQuBZYnvoYArpfQIvxQ4nyZsPLgY0ojNGKVdrcvd01jevUA/l5dSnxmtd3JK2Ri4uTgrWWIF2f50jBJleQjpyfRATUVUbSKcCnSdfgRNuHNalzEPD1fPM5YDXbjzWptzrwd9KGegMfsP2nXvV90OT3p11IAd+rFX406te9eF8ql6S1SRt4l6x9q4vmYjN8D+Rxwy3AIjSf0+s0Pm81Jozr1AM5+PEkYpzXd/LYANJ7/gHUx3mQ5ly7GedFQF1JJB0P/Df5xBLbuzep83HgzHxzMrB1s/GbpE8AtWtjYL0IUClP3gx/ELADac602XvTsJsj3pdKlzdYf5N0mkI31+etJonrVKo8B/FX6icrdDPOK9aL61SynNRnP1Kwd/G0svhs2yckzUhK6PNF0nPhWdK80Km2n62ybyGEEEIIIYw1EbQQQihFQ1YhkRZiLiUdY2ng4vz1LlLWlZoFgDWATwLr5zqTgaNIk2nYvno6/AoDIyb8+5ukYoavRUnPEahfm0nAw4wuuGSLbvsXEkm7krL3m7TovLLtNxrqvIt0UkbtOv0R+C/bjxbqLEQ6+nej/K2ppIy+j/f0FxgQeQPON0kZcBqPIx/thql4zSuRpJ8DuzF00exJ4EbgIeBF4LXRtG376DL6GEDSEcAxTLuYORF4FVgs/+xFoBhctwApIGXWwn2nAG9t7LW9TM86PmAkzQr8L2mTVPE0jDi1pE9ImkqbRf8umo5NhyWStBnwJ+qvayvZfqKhzsKkgO9ZSdfwUdLC9cW2X5E0AynA9YfUNwK/Cixs+6Xp9buMZ5I2Bk4Dli6rSeI1r1SSViPN68xG6wQXoxHXqUQNgVoifSa9gzSf9yawc/7Z48BPCnetzeetR/36TgbOA94AsP2p6fJLDABJKwKnkv7eTauMoLkIAOqBDuM8mvxs2OI6lUfSSqTXOEivd+vavqmhzuyk5CKLkq7hm6RkMhcBj5CyyX+U+klPAp4CFrc9pee/xACQ9D+kbOPtPuMM93UvXvN6QNKOpMBUKG+MB3GdSiXp98AHqF+j+4DfUl+3PTl/vY90CnRNbZy3GzCB+jjvxFwX26dPj99hEOS1ph9Qzsm2EK95pZN0ceHmGqS5cKgnBfwnowtOjaSAIYQQQghhIEXQQgiha5KWJG0srL2g7GX7pw11ngHmBybZnr9FO7uRjjl/Gymz/NYRsFCumPDvfy0WOSGCS/pK3hh6L/XJya/Y/nKTer+ivskD0mbdm6kvcq7P0E08f7L9gZ52fkBIWpp0fPKSxCapviRpAeAJ6gEltwAH2r62sk6FaeQsUo8BC+ZvPQYcBlxqe2J+PXyZvPhpe4WG+89JWuQ8krTpw8B3bX9+Ov0KAyFnZLuclGk8Ti3pU4VxXvEaDakyyqbjOpVM0vXUs1ifb3unJnWOAY5g6DWdSlqknpOUzbIYlHJaLEaXQ9ImwO8Z+jcuQzyXStQkucULpOt2A90Hp8ZcUQkkzQE8TQrAgnSC6j6103skCXiF9Fx7zPZSTdpYEfg29Q1xNwJb2p7U819gQEh6N3AV9cQj8dm2D7WZz+uqWeI6lU7SOcCO+eatwJqNwQaSdiGdhDacsbuBI20f15seDxZJ+wPfyTcbX+9eobvxQyRNKImkh6mfKCPgSlJinrfGebZfr66HISdLKiZGOs72kQ11JgFzA8/YXqhJGzMDh5LWFGcgJS/Z3PZtjXXD6OQAoLMp93MtxPihVLFuG0IIIYQQQrkiaCGE0DVJO5AmJA1c1Sybe8Ni9by2X2zR1vqkDVezkbLJr2L75V71fZDEhP/Y0LCZrUwx+VUySZ8mZbSGFGi1vu3nGuosCPydegbYxmzKxQ0Hk0kZ3m7uZb8HhaTLgPcxNGPojZSzSSoySZWgkJXNpECeVVuND0J18pyV0FsAAQAASURBVFHyN1LPOL6q7Uca6txPyrz2uu3ZW7QzPykz5Ya5rRNsH967ng+WQpBcUZxa0mfyOK8XYpxXMkkbAP+Vbxo4pMk4b0bS6YLFzJWNat9/BniX7ad61ukBIukuYAWGZgw9n3LGeQ+V1M2BJukdwN3UP/ecCnwh5nf6i6RNSSel1sbjK9l+raHO7cA7SQH4s9ue3KKtk4ADc1uX2N6+Zx0fMIVAuggA6mMxzhs7cgKmzfNNAxc2m4uQdBTwZZoHhBe/dz2wke03e9LhAZKTIvyHlOgF0lzeGeTN8LafrahroUDSuqTTtGrPgz1t/7zCLoUmJH0Q+DXpOt1ke+0mdW4A3pvrzGn71RZtfZQ0hyvgX8DqrcaEYfjynMJD1E+wjQCgPjWMJCRvVR1mk5EUMIQQQgghDLR2mbZDCGG4FiuU/9Sizj2koAVIm9r+2ayS7b9K+m9SlrYlSZkrv1RONwdXnvA/hvpkSkz4969rKD8zW+iBfKLMTzvUeVrSFsAFpOzXjde2GLDwqQhYKEfeJFULWIC0oWPf2ITWd4rjhzMjYKFvvbtQvqAxYCG7mzS+m0XSorYfb6xg+zlJ2wB/A1YBDpV0ru1betDngSJpcVKm0Npr3q3A5+PUkr70qao7EIbH9l+Av3SoM0XSh4BvAvvQPDhVwAPA9hGwUA5Ja1EPWICU2fjYCrsUmluvUL7R9t6V9SS0s2KhfH5jwEJ2DyloYQbSPN0DzRqyfZCkCcCHge0k7WD7/HK7O3gkrUo9YAFSANCBEQDUlyKhyxiRP9N2TEZh+yhJdwBfo56MpKY27jsL+GwELJRmI2A+0mveZGAr21dW26XQxCqF8oURsNC3iidk/bZFnXtIQQuQ5vXubFbJ9gWSvkpar30ncDBwYjndHGjrUw9YgBQAdGaF/QmtPUys24YQQgghhFCaCFoIIZRhrkJ5mk1q2T2F8gRaBC1k3wMOIi0G7EEELZQhJvzHCNubVt2HUC7bD0ham7RRcU9gLepjsBdIGXq/YvtfFXVxPCpukrqLtFEwFpD7z9sK5fsr60XoZIFC+R8t6txDyjQOaZzXdDxo+6V8Ss11wIzAUaSNbaE7G5I2EtayJG8SQUD9KU7qGX9svwHsL+lk0mfX9YGFgTeBB4FLgDMiM2KpVi+Ur4iAhb61cKF8XmW9CJ3MWyjf3aJO43xe06CFbH9gS9LpqYeQTkAJ3VmzUL7R9l6V9SS0FUkSxifb50q6ENiMacd5l9pu9doZRmflQvmsWL/oWwsWynGN+tfchfLDLeoUX8Mm0CJoIfsqsDewELAXEbRQhlUL5YsiYKF/2Z5QdR9CCCGEEEIYTyJoIYRQhmJ2r1bHGDZOfrVke6qk80mBC4tIWs/237rr4sCLCf8QKpQ3zP8Y+HE+9ncB4E3bE6vt2bi1SKF8VgQs9K1HC+W3V9aL0MkshfLzLeo0bmZrOW6zfYOkq4FNgS0lzWO7VbtheJYolOPUkhAqYPvfwOFV92NAFIPpLq2sF2Eknqm6A6GlYrbQZqcswMjm8x6X9BtgZ2BtSUvZbrVJLgzPQoVyBACFUAHbk4E/5n+ht4rJsa6rrBehk1cL5Tcq60XopNXYrqhxPq8l269JOg/YD1hG0uq2WyU3CcMzb6F8RVWdCCGEEEIIIYTpbYaqOxBCGBeKm24XalGnOPn1zmG0WVwUXX7EPQqNYsI/hD5he4rtpyJgoaeKY9zHKutF6OQa6hultq2yI6GtSYXyPC3qDHszW3ZZ/joL6ZSA0J2ZC+U4tSSEMN4VN99EkFb/urdQnlBVJ0JHzxXKrYKIi/N5yw6jzeKc01oj7lFoNKVQjgCgEMJ4N6lQVlWdCB3dViiv2rJWqNpI121XHEabdxTKK7esFYbrpUI5ki6FEEIIIYQQBkYELYQQyvDvQnn1FnXupr4xcYthtFnM9rboaDoVhphUKMeEfwhhvCtu2l2ssl6EtnLW1d+S3pc2krRlxV0KzT1VKLd6PhUXOdcZRptPFMpLjrhHodEjhfKClfUihBCmj38VyitV1ovQyZXUA0w+VmVHQlv/KZQntKhTHOdtPIw2JxXKMc7rXjE4eJnKehFCCNPHjYVyBL71r2tJc0UCdpU0V4f6oRr3FcqtEskVxxmbD6PN1wvlxUfco9Do1kI5AoBCCCGEEEIIA2OmqjsQQhgXbgEmk15TNpc0g+2pxQq2X5Z0Fyn7xnLDODp0lUI5jpjtXuOE/w+q6kgI452k2YE5gNkYRYBo3sgdunMl6X1pRmAH4CvVdie0cTCwCek5c6akLWz/s+I+haFuKZQ3aVHnAeBl0nXcpNlYsMG8hfJ8XfUuAFxNPeB3O+BrFfYlhHFJ0pzAcqTgrW7GeWeU3LVBdBXwAuk0wV0lHW475gz6jO3nJZ0CHAAsL+kQ21+vul9hGsW5ovc1q2D7P5KeJgVGriNpbtsvtGmzGOQ6Swl9HHS1AKBZgV0kHWnbHe4T+oikeeh+/HBN2f0KiaT5gfXpfpxn258puXsDx/b1kh4kBdLtJOkw20+0v1eY3mxPlvRV4FvA/KS1pk9U2qnQzM3AVFJwyfubVbA9SdL9pNO0VpG0rO12J3iuUCi3m/cLw/NnUgDQQtQ/27YbZ4cQQgghhBDCuKCY4w4hlEHSFcCmpA1Tn7B9VpM63wX2y3Wus71Bi7bmAO4FFs51d7V9To+6PjDy5OME0qbC5WPCf2yIxbP+J2kL4EPABqQJ/nm6aM62I6i0BJJ+CexCeh/5tO3TK+5SaEHSdsC5pI04LwAH2z612l6FIknPkBaiJwNL2n6ySZ2rSNl3Dexn+0dt2rsA+HCu+znb3+9BtweKpEuBrUl/0+1s/67iLoUOJL0D+CBp/NA4zhvpyWgxfugBSQsAB5LGee8qo03bM5bRzqCTdCxwOOk179u2D6q4S6GJvFH3JtJnpCnAXrZPq7RTYRqS7iVdIwOr276tSZ2LSK+FHZ9zkv4KrJvr7h3j+u5J+h6wL+lv+iXbEaDaxyTNBOxJfZ6o2yDtGOf1QD7p8QhgPbo/lVik6xTjvBJI2gM4jfSadwWwje03K+1UmIYkAZcCW5Gu1emkuaDX2t4xTFeSrgPWJl2jD9r+bZM6PwU+mev8zvZ2LdqaCfg36eQnA3vY/kWPuj4wJH0B+Abpb3q27d0q7lIYhvwauArlJLc4ptzehRBCCCGE0P8iaCGEUApJewE/Ik2s3A68pzHzl6R1gb9SzwR7GvD/bL9cqDMr8Avgo/lbBpaz/WAv+z8IYsJ/bInFs/4naVng58A6xW932Wxcp5JIWhy4jbRB4FVge9uXV9ur0IqkDYBfAkuS3qfuAU4BLgcesP18hd0beDlT8qdJ1+ZE24c1qXMQUMug/Bywmu3HmtRbHfg76YQuAx+w/ade9X1QSHonKVvyrKS//xbNNh2G6uWA1O8BOzF03NDNGCLGDyWTtD1wBjAn016b0UykxXi8RJJmA64nBZMYONb2UZV2KjSVA7QuB5YiXatfAofH6XL9Q9LxwH+Tr4/t3ZvU+ThwZr45Gdi62fhN0idIr53k9tazfX1POj5AJM1L+my7BBEA1NckrQ2cQ/pcC12O74jxQ09I+jrwhdrN/LU4vhvJdYvr1AOSzgI+Rvr7Xk5KkvV0tb0KjfKY/FxgW9K1uhc4mrTxekqVfQuJpAOBk0jX5y+2N25S533AZdRfB48Bjmmyvnsy6RQ1ct1VbN/Vo64PDEkzkF7nNiX9Xc8A9o0AoP4kaWXgMGAbhp4kPGoxfgghhBBCCIMoghZCCKWQNBfwAPXsUV+wfXKTepeRjpyvvfhMJE3IPEL6gL81sCh5sh+4wfa6Pe38AIkJ/7EhFs/6n6RlgL8BC1J/veo2YAHiOpVK0obAhcACpM01xwMn2H610o6FpiQtSMrStmb+VjcfVCIbZYkkbQb8iXRNXgRWajyxSdLCpLHgrKTXw0eBLwIX234lL8JtC/wQWCTXeRVY2PZL0+t3Gc8k7UjaUFg7teQLtn9Wba9CUX6duxZYnvr4ASLosa9I2pT0WamWIS/GeX1I0iKkjaEbkq7RNcB/xwbp/iPp7aQkFx8hXasppI1Rl5PGDpMY4bjP9jXl9nJwSVoJuCPfnAqsa/umhjqzk4KKa/N1bwI/Ay6iPp/3UdJGtplynaeAxWPTYjnydfo1aQxhUgKFw20/WmnHwlskrUZK1lM7NSvGD31I0meB2kl/jdfoFdLn3VFtFLW9THe9CzWSZgSOJc0pCHiWlCThVNvPVtm3MC1JB5CCFeYjPa9eAK5m9OO8yDpekjwH8QAwe/7W7rZ/2aTeDcAa1N+//g1cTH2c9xFg9cJd7rRdymmEASTNCfyY+qnR9wBfBs6zPbXKvoW6/Fr3TdJcUXH8MNo1jFi3DSGEEEIIAyuCFkIIpZH0JeAr+eaLwDK2n2uosywpu+78tW8x7WZsF75uGZmxyxMT/v0vFs/GBkm/pX78tUibO24EbgAeorvrdHpJ3RxoktbIxcVJGa2XIF2v50gZXq8AHmR0i2eRGbZE+ZSl/yVtcpqr+KMumo0J/5JJup56QMn5tndqUucY0ilBxbHcVNLzbE5gFoYG451m+zO97flgyNn7AVYDTqf+mncX6dSSK4AH49SSakn6ObAbQ8d4T5LGEN2OH44uo48BJN0BrEz9Ot0HnE8547yHSurmQMun+0DaHH0A9dc8SCc/djPOO6NzrTBSOZj4JCI4tS9JOgfYMd+8FVizMdhA0i6kz1HFcd40TeWvBo60fVxvejxYJNVOo52LNKdXe82bDPye7l7zIgCoJJL+CqxL/TnyAun6lDF+uLqkbg60PC/+BPV1iamkjNbnkhInxdx4H5B0ceHmGsBiuez875+M7jXPMf9QvjwXsR+wJ7Bc4UejHuvFfF65JJ0IHJpvPg2s0Dg3lOfRr6UeeAetk2gZ+LjtX/Wmx4Mln2BR82HSOA/S33kSKTj/QSIAqFI5Ucw5+WZZgakQaxghhBBCCGFARdBCCGG6k7QmKfP14rRf5DzM9gnTrWPjXEz4979YPBsbJC0OFDet/x7YLzah9RdJU5n2tazZostIxSapEuXFzctJG60j63gfk7QB8F/5poFDmgSnzkg6LeMDtF7AqX3/GeBdtp/qWacHSLzm9T9JC5DGebXs/bcAB9q+trJOhWnkLMn/oP68iU23fajDax5NfjZsMX4ol6QVgVOB9VpVGUFzcYpgj0haEtg83zRwoe0Xm9Q7ipT1tdmYvfi964GNbL/Zkw4PmBjn9T9J7wDupn49TiWdevZydb0KjfJpWlfkm2+SkiVdVVV/QnMtXvOgu7FejB96QNKuwA8YmoCkqyaJ61S6nCxmkXzTrZLxSNoaOAuYm6HjusbghR/a3q9H3R04w3jNi8+2fUDSw9QDhwVcSV63JQen2n69uh6GEEIIIYQwtsSkdAhhurN9o6R3k7J77EF98zykD/x/A462fVkV/RvHtmPoBFdx4lGkDaPvHmGbtUnLCFoox0bAArkci2f9a2Pq//fvAj4cmzH6WnFxpVWGqFCd7wPvKdwWJWUdD+Wy/RfgLx3qTJH0IdJR2fsw7QJbbczxALB9BCz0RLPXvHi96w+bATOSrssjwKbNNoSGyq1eKF8RAQtjSrdZWVpljg+jlOd9rgLmYeipmqNusoRuhSZsP0I6qalTvaPyaTRfA5Zu+HHt+pwFfDY+I/dEq8+2tZ8NV5nZYUNSDMy60fbelfUktLNC/mrgrJhz7XuNY7PRvu7F+K4HctbxnxPvJ30vb6TumGzJ9u/yiQvHATsAM+cf1a7xf0jrtj/pSUdDo25eu+KzbYkkrcvQ0x33sP3zCrsUQgghhBDCmBdBCyGEStieCBwGHCZpaWBh0ibthxqz9obSxYR//4rFs7FhkUL5rNiM0dfU8DX0kXxqyY7U309uBT4fWcfHNttvAPvn4833ANanPs57ELgEOCOyT/VEvOb1t2Kg9pkRsNC3FiqUL62sF2E44rWu/50CzEt9rPci6ZS6t7JREsGpY47tcyVdSArGaxznXWr77gq7N56VOc6L18/yLVwon1dZL0InCxTKf6+sF6GTh4l1h76WT9n8FkODUiPr+Dhg+35gN0lvA9aiMM6z/Y9KOze+xdisv61SKF8YAQshhBBCCCF0L4IWQgiVs/0Qw8j0EboWE/79LxbPxoaZC+XHKutF6ORTVXcgdLQhMAP1rOObxCbe8cP2v4HDq+7HADm66g6Ejt5WKN9fWS9CJ8Vg1HhP6l/LVN2B0J6kVYE1qc9BnAocaPvl6noVymJ7MvDH/C/03mZVdyCMyDNVdyC09EKhHHPkfcr2hKr7EDpanxSUX3se7Wn7zAr7E0pm+xXg6qr7MQhsz1B1H0JHCxbKV1bWixBCCCGEEMaRCFoIIYQBERP+Y0Isno0NxSCrxVrWCpWyfXrVfQgdLVEoR9bxELpgO4IW+t+jhfLbK+tF6OSuQnmFlrVCpXLig9Df1iyUb7S9V2U9CWGMsx2bBvvfvYXyhKo6ETq6uVBes2WtEEInqxbKF0XAQghhnHu1UH6jsl6EEEIIIYQwjkT0dgghhNA/YvFsbLgSmJzLH62yIyGMccVTSyLreAhhvLuGelDqtlV2JLR1FfB8Lu8qaeY2dUMIrS1UKJ9XWS9CCGH6uBJ4LZc/VmVHQlvXAQ8AAnaWtEjF/QlhrJq3UL6iqk6EEMJ0cluhvGrLWiGEEEIIIYRhi5MWQgilkLRxyU1OBV4GXgQm2n625PZD6Ee1xbNlSItnR9h+ouI+hQa2n5J0NvBx4D2Sdo+MUiGMyiOF8oIta4UQwjhg+2FJvyUFLGwkaUvbf6i6X2Eo269K+jbwZWBx4HjgkGp7FcKYNKVQfqayXoQQwnRg+3lJpwAHAMtLOsT216vuVxjKtiX9L/BzYA7gdEnb2X6z4q6FMNa8VCjH86ePSVqq5CbfWre1PblT5RDGiWuBp0iB+btKOjxOjA4hhBBCCKE7st25VgghdCBpKvXMob3wLHArKXPVGbYf7eFjhVAZSbuRFs8MXA7E4lkfkrQo8A/SROUrwPa2/1Rtr0IYWyQtATyUb/7FdtkBkKEkkn5acpNDglOBO4FbbT9W8uOE0FckrQDcSNok9Sywhe1/Vtur0EjSLMBfgPeSxuTH2j6q0k6FMMZI+hBwEek59BXbX662R6EVSWWfeNZ0nAdcHXN5YTyTNA9wE7AsKXBrL9unVdqp0JSkU4FPUZ973d32U9X2KoSxQ9ImpHU6A9+3/bmKuxRa6PG67SvUx3lXAhfYfq39XcJwSZobmBuYYbRt2H64vB4NNkn/D/gW6fl0lu1PVNujEEIIIYQQxrYIWgghlKIw+aUePowLX88BPhcnMHQnb7xekO4nv64prVMhFs/GCEnrAL8jHYk9GTgROMH2y1X2K4SxRNKlwNak17vtbP+u4i6FJqZDcGrNfcBpwKm2n5wOjzcuSZoT2BBYne7Hebb9mbL6FkDSdsC5wKzAC8DBtk+ttlehkaS3A78H1iC9/v0Z+JLtv1basdBW3jC6GCkwaDZG8doXn23LIWku4EnSa919wIqOSei+1KP5vGbX2sAVwNdtX1biYw2UvFF0a8ob5y1XVt8CSHoHaR5vKdL/+V8Ch8emwf4iScB3gP3yt54FvgmcEvOv/Sdfr1WA5eh+nHdMub0bTJJmBB4jJfN5DljW9gvV9io0Mx3WbYtjvheB7wNH2X6jR483bklaCNiXNM5bDZilyyZte6auOxaAt96LLgW2Iv2/Px3YLwJ1QgghhBBCGJ0IWgghlCJPftU0vrAMZ0KseJ929WsTbCYdx7iV7VuH1ckAgKRVgYNIkysLldBkTH6VLBbPxg5JywO/ANYkvS5NAs4iLVI/kG+PaLAVi9nlyxsHPghswLSLnCNdtInXvBJJeicp6/ispIXOLWzfVm2vQqOGoIXic6bdmG84Y7tWbT4PfN72mSPs6kCTNDNwLPBZYK4ymiS95s1YQluhQNIGpE1sS5L+z98DnEIeP9h+vsLuhSyfuHA8cABQe++/k+7GeWeU2MWBJ2kmYE/gQ6Rx3nxdNhnjvBJJ+h5p441JQT9fq7hLoYmGzWzNXtM6zdENp25j+6cB+8cmn+GTtAxprmGtxh+Norm3rkeM88qXAx9/BHyE9LeeAlxGd+OHCKjrgRxM/E3SPJHzv9sZ3XWKYO+SSVoZOAzYhpQwpmvxmlceSV8AvkF6npxte7eKuxSaqGjd9k5gW9sPtakfCvIpdaeTglGhnCCTGOeVTNJspCQk25L+r98LHE16DZxSZd9CCCGEEEIYayJoIYRQCkl75uK6wD7UJ6meBS4CrgWeAF4v3G1uYAlSJtjtgbfl+z1I2lT/PDAnMA+wcm57U1IWnVr7jwHr2n6sR7/auCJpX9IRljNRXnaVmPzqkVg8Gxvy5oGzSYEL0F028tgoVSJJ8wPfA3Zi6GteN69/8ZpXMkk7AmdSzzr+Bds/q7ZXoajNImftuTQFeJppx3nzFurU7jeJdJ1FGufNBczc0H5toTM2OA5T3rh7ObAR0/7NofPicqs68ZrXI5IWJGVpi/FDn8rPq12Ag0mZDmtGfa3i+VQeSWuTTmBcsvatLpqLDbw9IGle4DbSvM8UYC/bp1XZpzAtSVeRngOzkubdiuOCl4EbaD2f9x7SOK52nweBa6iP82rzeYvlnxfHeRfY3qn832j8yWOGW4BFqP/9mgULdwoUbqwTr3k9ImlD4CRinNe38ob4g4AdSK9V7YLzOzZHPJ9KJekA0pz4DHR3bd5qkrhGpZI0A2kOYlPSdTkD2DcCEvuLpCNzcTngE9THEG+Sxmyd1m3XpT72eJAU1D+ZoeO8dXL7Rf8CNoiEDJ1JWgP4K/WTFboZ5xXrxWtej+T3qKNJSRNMmue+mtEHp8YpQCGEEEIIYeBE0EIIoTSSPgGcStoQP4WU6fUbtl8Zxn3nA74GfIZ6No7NG7PKS1oMOBH4OPUP/r+0vXtZv8d4JWkLUmavZguc0Hnyq1inWC8mv3ogFs/6X9448E3gY0x7JPloN03FdSpJvj7XAsszNKtntwFbcY1KlANLIG0GPZ20KGbgLlLW8SuAB2ORq3p58+5JpIzjkBY0f0Y6beZvtqc2uc8cwPqk8d2OpOffJGAP25cW6r2DtBD6cWBL6uOUqcAHbf+uN7/V+CHpCOAYpn2tmwi8StosaOBF4B+Fuy5Aep2ctXDfKaTAYABsL9Ozjg8gSbMC/0t6LhVPxIiAuj4iaWNSJvCly2qSuE6lkbQaaWNH7dSsZp9vRyOuUckkrQT8mvReY+DnwOG2H620Y2EISUsB51HfYH0naSPORbbfaHO/twF7AF8mbag3cKLtwxrqLUHaKHcIaXNP7Xl7sO1vlfrLjEOSTgE+zdAx8h2k7K5vAjvnnz0O/KRw1wWANYD1qP/NJ5Ou9RsAtj81XX6JASFpRdLc+HqtqoyguQio6xFJ/0N6jWsXDDLcaxXXqWQ5scU5+WZZYzyIa1Q6SXMCPyYFetdOEPwycF6zOaJQDUnvIz2namtMPwOOHM54PK9RfQt4P+kaXwNsZ/vlhnrrktZtN8rfMvB9258r6dcYtyT9HvgA9de7+4DfksZ5Bk7OX+8D9irctTbO2w2YQH2cd2Kui+3Tp8fvMEjyWsZ+pBMfi8E6kdwihBBCCCGEEYighRBCKfJC9M2kTQOvkTaY/WkU7RxKmlQxcKXt97WodyRQyxIyGVjR9gOj6fugkPRX6lnzRNoIein1ya+LqW8U3aZw19rk1ydJGw9rk19HkTaKYPvq6fArDIxYPOt/kpYmZU9Zktgo1Zck/Zw0aV+8Nk8CNwIPkTbujir7l+2jy+hjeCuDf8uMUF00HdkoSybpfODD+eatwM627x3B/TcinUqzCGkcsX2zYIQcZPkLYEHS/4Vbba/eXe/HN0kzkoIMFszfegw4DLjU9sS8Sf5l8uKn7RUa7j8n6fXySGBR0nPvu7Y/P51+hYGRFzcvJwVqRUBdn5K0CfB7UqbDsjZJQVyn0jT5bPsC6ZrdQPfjvPhsWxJJH83FuUhJLWrBqZNJ1+sKUsbWSYw8G+U1ZfVz0OVxwo3AO/O3TiNlSm4ZrNCkjQVIwSm1OaMjbB/fpN5CwG+AtfK3ngQm2H69sW5IchDw06QAU0jJSPax/XD+uYBXSO9Zj9leqkkbKwLfpr4h7kZgS9uTev4LDBBJ7wauor4pNOaJ+pCk/YHv5JuN1+gVuhtDRLB3CSQ9TH3MIOBK4FwK47x436iepJMLNz9MumaQrtsk0ub2B4ms45WStDjp5LP5SEGPnxnNRvZ8vQ8gXctzbe/Sot5PSIlLIL2WLmP7ydH0fRDksfHjhW8dZ/vIhjqTSKdfPGN7oSZtzAwcSlpPnIGUvGRz27f1qt+DStKuwA8YmoCkqyaJcV4IIYQQQhhQEbQQQiiFpIuB7UiTVp+z/f0u2voD9cwdH2gV/CDpBuC9ud5Btr892scc7yQtSZrUr73o72X7pw11ngHmBybZnp8mJO0G/Ah4GynD8taxqaNcsXg2Nki6DHgfQzMd3kg5G6UiA06X8qaZJ6ifgHELcKDtayvrVGiqELRQ3Lz71o+7aDom/Esk6VOkjKEGbgc2Hs3pF5JWBa4DZidtvnqH7Reb1FsL+DMwMx3Gg4HaUfI3Uj9JYVXbjzTUuZ+Uee1127O3aGd+4CJgw9zWCbYP713PB4+kX5GyIRdFQF2fkXQXsAJDMx2eTznjvIdK6ubAyqfz3E193HAq8IXGbJ+hehGcOjZI+grwJdI1udD2jqNsZx7SOHFxUhb/FZu95uUT8e4ibZ4zsJvts0fZ/XFP0qakAB8DjwAr2X6toc7tpKCTKcDstie3aOsk4MDc1iW2t+9ZxweQpOtJp5VEQF2fykFa/wHmzd+aCpxB3hBv+9mKuhaynK39r9THCXva/nmFXQottBjnQQljvZjPK09DUp9jupk3kHQdsHZuaz3b1zepMyPpNKja5+n9bP9otI853kn6ICnw18BNttduUqe4Dj6n7VdbtPVR0okaAv4FrN5qTBhGLp8CdDblJraAWMMIIYQQQggDKhZ4Qghdy5tDtyJNmjxIyjTQjf8jBS0AfBRotUnt26SFBYAN8u3QXHGy66rGgIXsblK2ynkkzdVsE6HtX0p6kJQhdjbgdEmrxAaRcuTFs2OoT+rH4lkfyhulagELkBah941NaH1lM2BG6hs7Nm32mhb6hhq+hv5zSP5q4FOjCVgAsP1PSd8G/gd4O/Ax4JQm9W7IC6ufyt/anNbjwQDvLpQvaAxYyO4mBS3MImlR2483VrD9nKRtgL8BqwCHSjrX9i096PPAyRkOd6Q+frgV+HwE1PWXHDRV22ABcKTtYyvsUpjWeoXyjbb3rqwnYbiKwandBKmWlbU8ZHljWS0b7ivA/qNty/bzkr4KfI8UeLoL6STVxnpPS/oO8OX8rQ1JG4BCcysWyuc3Bixk95CCFmYgnQbZ9CRa2wdJmkDKiL2dpB1sn19udwdTDs6uBSxACqg7MOZL+85G1AOmJgNb2b6y2i6FBqsUyhdGwMKY1E1garOEJmGU8qmaHyH9TZ8EpjkFa4SOBy7M5Z2AaYIWbE+R9E3qa8QbkJKgheaKJ2T9tkWde0hBC5Dm9e5sVsn2BXksfgRpXHgwTcbiYeTyZ6ZvMfQkrTgFKIQQQgghhC5E0EIIoQwbkF5PTNoo1e3E4tXAm7nNDdvUu6JQXqVlrQCwWKHcatPfPaSgBUiTX/9sVsn2XyX9NylIZEnSJNiXyunmwIvFs7GhuFHqLmB7229W1ZnQVPE178wIWOhrkRm8z+UNOCuT3puutn1zl02eTgpaAPggTYIWsjOpBy2s16JOSBYolP/Ros49wAdyeQJDj59/i+2XJH2adCLGjMBRpI1toXsbkjYT1gLqNon3p760eqF8RQQs9KWFC+XzKutFGK4yg1MjYKF8GwALUc+8/2SX7Z0PfDeXt6H1RqlfUw9amCajbBhi3kL57hZ17imUJ9AiaCHbH9iSlIjkENI1C91bs1C+0fZelfUktLNyoXxWzLn2pQUL5bg+/S/GZv1tI9JJpyYFPr7RZXuXkU51moGUXKSVPxbK7+nyMce7uQvlh1vUKY7/JtAiaCH7KrA3aXy/FxG0UJb1SetNxVOAzqywPyGEEEIIIYx5EbQQQijD4oXyPS1rDZPtNyU9TZoEWKRNvf9IehmYA5i/28cd5+YqlJtuUmPaRc6mQQvZ94CDgKWBPYighbLE4tnYUHxdOisCFvrS2wrl+yvrReiom2PJw3RTDAz9Y8taw2T735JeIo3f3tmm6t9JJw6JoZnHwrRmKZRbnYLROM77W6vG8kkXVwObAltKmme0p2uEIZYolCOgrn8Vg4AurawXYbieqboDoa3Nqu5A6GiZQvnv3TZm+ylJE0lzdBPaVL2VerKShdvUC0MzTjc7ZQGm3czWujH7cUm/AXYG1pa0lO1Wm+TC8C1UKEdAXf8qzo9fV1kvQjuvFsrdbrAOPWR7hqr7EDoqzkH8q9vGbL8q6RnS2G2xNvXul/QqKUBygVb1AtB6bFfUOJ/Xku3XJJ0H7AcsI2l1262Sm4ThW7VQvigCFkIIIYQQQuheBC2EEMowT6E8Y0lt1l6f5mlbCyaSNr3NW9LjjlfF48hbXaORLHJOlXQ+KXBhEUnr2W65+S0MWyyejQ3FRZnHKutFaOfRQvntlfUihPGhuBDZbfbdmueAOWmzSS0vhk4ibXqbr6THHa8mFcqtxs7DHudll5GCFmYhnRAQm7e7N3OhHAF1/au4aSACS/rTvYXyhKo6ETqzfXXVfQgdFQPyywpQfJk0fluwVYU8pzSRtNE7xnntPVcot/psW9zMtuww2ryOFLQAsBatM/uG4ZtSKEdAXf+aVChHhvj+dFuhvGrLWiGE4SgGDExpWWtkpuavncZvE0nzifOW9Ljj1cRCeaEWdYrjvBWH0eYdhfLKtD6RNQzfvIXyFVV1IoQQQgghhPEkMiGEEMrwdKG8UreNSaotbhp4tkP1soIkxruRTn61y3xcU9z8tvyIexSamVQox+JZ/ypuNGyZVShU6hrqGSm3rbIjIYwDxeyuZZ1sVWun03tdbcPwXG1rhacK5VbvS8Vx3jrDaPOJQnnJEfcoNPNIodxyI2eoXDEDZdefbUNPXEk9uORjVXYkhHGgmOBi8Za1hknSDNTnnDpljq1l056928cd5/5TKE9oUac4ztt4GG1OKpRjnFeO4hzpMi1rhardWCivVVkvQjvXkj7fCthVUswFhDB6xcDH5bptTNIcpHGeGTqWaKYW3BDrt+3dVyi3WpMtjjE2H0abrxfKXY/vAwAvFcpx6noIIYQQQggliKCFEEIZahm5BOwkadYu2/s49U1sLbOY58XQWraQyILZ3r8L5dVb1Lmb+sbELYbRZnET46Kj6VSYRiyejQ1XApNzeYcqOxKas/0w8FvSe8lGkrasuEshjGXF0xU26rYxSe8mnbJgOp/cUNug8HrbWuGWQnmTFnUeIG1MFLBJHke3M2+hHBmQy3E19fHzdlV2JLR1FfBCLu8qaZYK+xKasP08cArp9Wx5SYdU3KUQxrJikOI2JbS3OTAr6f3uiQ51a0Gsr5TwuONZcZ7ofc0q2P4PKaGMgHUkzd2hzWKQa7zPlaMYULeLpEhE0odsXw88SH0NY5H29wjTm+3JwFfzzfmBH1TYnRDGuuLa6o4lvDftQD0I4fEOdWunQ73ctla4mXqAx/ubVbA9iZRES8AqkjqdqrVCoTy1Za0wErcWynEKUAghhBBCCCWIoIUQQhmuJS0yGlgYOGm0DUmaABxNfUPPn9pUX5W0uGaGZh4L07qFtMlawObNNqrZfhm4K9dZTlKr4IaaVQrlN0rq50CLxbOxwfYzwHmk67SapD0r7lJo7mDqWXDOlBQTyn1O0pyStpL0JUknSTpF0k9H+e/Uqn+fceT2/FXAVpJW7rK9gwvlu1tVyhkV5yON857v8jHHNdv3kTLoCVhT0sJN6kwFbso35wb26tBsMUtv/P1LYPtR4Pek67SBpK0r7lJowvbrwHdI12lR4IRqexRa+F/qGzeOl/TJarsTwph1XaG8jqQPjbahvBHu2MK3bm5Td1FScOpwTlgdaLafov56t0IOAG7mb/nrzMBRHZotBk/G378Etl8EfkaeUwUOrbZHoY2j8te3keaKZq6wL6G571D/3LRrnuOZreI+hWGSNLekJSQtNdp/Vf8O48g11NftJgCHj7YhSfMDX2lou1XdFYHZSOO8TsENAy2vyd5Ier1bSFKrIOLi3/vkVu1JmgnYqfCtTkHEYXj+zNBTgDoFCIcQQgghhBA6iKCFEELXbL8GXEj6wC7gs5J+JmnekbQjaR1SBtJ5qJ+0cE6buxQzZ98xkscaNHnzzZ/zzXmBj7WoemWh/N1W7eWjYItttDwRI4zYUflrLJ71t0OBiaTXqu9LaprxMFTH9t3AbqTFmbcD10r6TLW9Cs1ImlnSCcCjwKXAccDngU8Be47i3yfzv1AC27eRAupMChY9Z7RBdZL2BnYvfOs3baqvS308eO9oHm/AXJS/zkh6/jRzcf4q4CuSmh4TnwNXi5vZ/t2sXhiVQ6ln4T2jzcbDUK2vkAK2BHxe0lHVdic0yqctbEU69XFG4FRJZ8Ymp/4laRNJJ0j6g6SbJd0r6f5R/ruv6t9nvMgBdbWgRgGnS9p8pO3kxBinAesUvn1Rm7sUT++KcUZn5xbKrTbD1+oIOEBS0xNUJX2CNM6u+Wf33QvZ4aTPtLWx9ier7U5oxvYZwNnkxD7AJZIWrLZXoci2gY+S5odEmue5VdJukmZse+cw3UlaSNKRkq6T9Cppvvwh0mmPo/l3/3T/JcapHFD3B+rrtkfnazWi55GkpYErgOIc0vlt7lJcJ/nXSB5rQP2qUP6fFnV+WShvna9js5MzTgKWKdy+qUmdMEK2pwAn5pvzAT+ssDshhBBCCCGMC0rzPyGE0J286elOYA7SBJiBSaRFy18DN+WsEY33mwvYkDT5vCP1YCoD59jetc1j3gmsmOvubTuyKrchaS/gR6S/1+3Ae9zwJiBpXeCv1E+6OA34f8VrJ2lW4BekxQNy3eVsP9jL/g8SSWeRgkIMXA58wvbT1fYqNJK0ISlgawHSSSbHAyfYfrXSjoUhJG1AmthfkvScugc4hfTceiBvegsVyRmgLidtXKotthTfm9odXe42dWw7FrNLIulA0sKXSX/vx4EvAWc2jiVa3H9e0ibgz9a+RRonLm+7aXZXST8G/is/5sm2v9DVLzHOSdqMdEKZgReBlWw/0VBnYdImgFlJ1+BR4IvAxbZfyRsOtyUtvi2S67wKLGz7JUIpJO0InEm6Di8AX7D9s2p7FRrl4KxzSJ9VTcps+N/5ZLTQJyS9nfQZ9yOk6zQFuIw8ziO914xo4tN2y6yhYeQkLQOcBazV+KNRNFcbh8Q4r0Q5o+sl1P++U0jvU9/Kwavt7itSQpETSKeh1twDvMv25Bb3u5gUIGngGNtHd/t7jGeSVqKerGUqsK7tmxrqzE76uy9Kuo5vkjL/XwQ8Qkpg8lHgAGCmXOcpYPG8ESuUIF+rXwPLk/5//xw4PAcIhT6RN+weS/osJNKJI18HTm31+TRUQ9IBpFO5a6cwvkBKejXacd4xJXdxoOUTmk4nneYIoxvfNYpxXonyaam3UH/vN3Af6USTX9t+uMN99ySNHWYv3P9y21u2ud8NwHtz3c/bbpkcLUAOnHuA9DcG2N32L5vUuwFYg/p1+DcpOUltnPcRYPXCXe60/a7e9Xyw5DnTy4FNSX//M4B9c1LHEEIIIYQQwghF0EIIoTSSPkLKCjFT7VsMnTh+nDSZ/DLpeND5gMWoT2bW6ouUUWX9fAx6q8c6P9efDCwRm7rbywEiD5D+7pA2SE1zlKiky0jZUGrXbiJpMqY2+bU19UVQAzfYXrexnTB6sXjW/yStkYuLA98DliA9H54jbZC/gpSZfBIjX0BruVgQRidP/l8KrJm/1c0A2LZn6lwtDIekI4BjmDYAYSJps/Ri1Ddh/6Nw1wVIG0FmLdx3CoWTf2wXM0uFLuT3pRuA91DYMEh6f7qElLnr30w7znsnKSBlu/y9YmDKgba/0+Lx5iaNO+bKdbey/cfyf7PxRdL11F/nzre9U5M6xwBHMPQ6TiVduzlJp2kUr9NptuOUmpJImj8XVyNt7qiNH+4iBdRdATwYAXXVknRQLs5E2qBRu06Qgr+7GeedUUonw1tyIPFJxDiv7+Qx+C3UA+Fq7z017QJQiz9vrBOb2Uom6XTSaVjF8QGkTMntxnnrAwsz9PpMAba2fXmLx1qO9L5XS1qypu1/NKsb6iSdQ0r2AnAr6e82paHOLqT5iMbrOKRa/mrgSNvH9abHg0dSLbnLXKQ5vdr4YTLwe7obP0RAXUly0FTNGqQ5B0jXxKTTRx5k5NfJ8bmpXPmz036kTdPLFX406rFejB/Kk+fG/0qaQ4DuxnnFejHOK5mk/UlBCsVrVPv7P0fzcd7KQG3+ojiOfwZYz3bTk88kbUp6v6u9pi5j+5Eyf5/xSNKJ1E/TehpYoXFeKD/nrmXa+dW3qhTKBj5uu3iKQ+iSpDmBHwO7UE+O9WXgPNtTq+xbCCGEEEIIY00ELYQQSiVpW+CnwIJ0npgsKta9C9imXeZ+Sf8EVsk3z7G9y6g6PGAkfYmU6RjSBtBlbD/XUGdZ4O9MOylJw+3a1y1bLUaHkYvFs7FB0lTaLK500XRslCpRPhnmf0kbDucq/qiLZmPxrCR5I/xjpDEDuXwYcKntifn6vUy6XvfZXqHh/nMCuwFHkoLpDHzX9uen068wUPLGwytJG9SaLXS2vTtDx3qn2N67zWMdCxyebz4OLBUZYDvLJ8v8V75p4JAm47wZSUFcH2DaTQUU7ltbjH5XqyDiMHIxfhgbOlwnmvxs2GIMUR5JKwKnAuu1qjKC5iKDfw9IOgX4NPW/71RStvh7SVngd84/exz4SeGuC5A+C69HfQwxGTgPeAPA9qemyy8xIHLm0DOBXZl2Lq/da16xTu1afcb2aW0e6xf5cQButb16q7qhTtKSwOb5poELbb/YpN5RpM1TzeZki9+7HtjI9ps96fAAinHe2NDiOkF3Y70YQ5RM0q7ADxg6l9dVk8Q1KpWk3zN0XuE+4LekcZ6Bk6ln9d+rcNfaOG83YAL1cd6JuS62T58ev8MgkbQ38C3ShvdWASZD7tLwM5E202/VLthU0l+ofz77ne1tu+j2wMhz4Ivkm26V1ErS1qRT7OZm6LVpXL/9oe39etTdgSSpmADww6TgVEh/+0mk0zkfJE4BCiGEEEIIYVgiaCGEUDpJ85GO7d0dmKfwo04LAs+SMn6cYPuNDo+xEDBzvjnJ9suj73FoJGlN4EJSFvl21+0w2ydMt44NgFg8GxsK16lT9sKRiutUkpyR7XJSNuvGDdPdiGtUkpwh6kbqJyms2ph9S9L9pEXM123PPk0jvHWtLwI2zG2dYPvwZnVDdyTNC3wD+CTDf14V67xBCp48zm0+iOZMsrWToc63/cPR9zo0kjQL8E1gH+pZjhuv5QPA9rZvn87dG9c6jB8ioK5PtBmPd9UscZ1KI+ndwFWk+YZmGfxHK65RSSTNQdrYNGv+1mXAPrUNOJIEvELKzvuY7aWatLEi8G3qG+JuJCVNmNTzX2BASdod+D9gofytZu9Vrd6/7gH2tn11h8c4hPr/i2sjg3z5JO0EfA1YukWVs4DPNgt6CKM3jHkiiIC6yg3zOsHwr1Vcp5JJ2hE4m3LGdkVxjUqS1+YeL3zrONtHNtSZRNpY/YzthWggaWZSZvmjSfMSE4HNbd/Wq34Punza1TeBbZh2LqjpXfLXycDPgUM7nQIuaW3q67YP2P7P6HscmslJ544DdqD+t675D3C07Z9Mc8fQlWGs20ZyixBCCCGEEEYgghZCCD2Ts0NsSzoufg3SpsN5SBly3iBlHHiEtPB8NXBxp2CFMP3k4JNDgT2oZ/uHNPlyHWny67Iq+jaexeLZ2JCvUy/EdSqJpF+RsrcWPUl6z3mItEn+tdG0bfvo7noXACR9knQ6k4HTbX+6SZ1i5rYlbD/eWCfXmxP4G+kUpsnA2rZv6U3PQw442QfYCZh3GHeZBPwCONn2Pb3rWRiJvBl0D9JYfWFS1usHgUuAM2y/Xl3vxqcYP4wNcZ36n6TrgTWpf9Z5Afg9cAPdj/PabrgOwyNpU+AK0jV6BFjJ9msNdW4nneA0BZjd9uQWbZ0EHJjbusT29j3reEDSbMBHSKchrE/9FM5mXgD+DPwM+HWraximP0kzAZsx7TjvUtt3V9i1cSvGD2ODpAcpPzgVANvL9KLdQZJPBnyItBZRG+ddCZxLYZwXn1WrJemDwK9J1+gm22s3qXMD8N5cZ07br7Zo66PAOaRr/S9g9RhP9JakxYBdqK/bLs20a021OfSrgTNtPzldOxk6kvQ2YC0K47x2p2CE7kRyixBCCCGEEMoVQQshhBA6krQ09cmvh2w/V3GXxq1YPBsbJO3Zq7bjCOzuSVqctJBZW3C5Ffi87Wur61VoJOlgUiZXAwfa/k6TOt8B9s91NrT9tzbtrUUKqgP4je0Pl97pMETeULAynYNTb41F5xBA0pGda41OBNSVJ3/26QnbD/Wq7UEhaVXS2K72memnpHFEnL7YRyTtA/yAdJ2+ZfvgJnUuBLbPdd5h+4E27V0AfDjX3dn2+b3od5iWpKVoPc67u93pWSEMEkmb9KrtCKgLg0LSRqRN0rX3lk/aPrPCLoUmJO1POjHdwLG2j2pS55ekjfEG3mX7zjbtHQMckeseZvvEXvQ7tCZpLgrjvJjDC2GoCE4NIYQQQgihXDNV3YEQQgj9L2+uiQ0204HtCVX3IXQWgQV9b0PSMde1zK6b2H6x2i6FJmYplJ9vUaeYlX8C6TSFpmzfIOlqYFNgS0nz2G7VbiiB7SnA7flfCKGDCCwYGyKwoO+tWSjfaHuvynoS2pm3UG6V1b1xnNcyaIEUxLolMBtwCBBBC9OJ7YeBh6vuRwj9LgILQijFqoXyRRGw0LfmLpRbjRGK478JQMugBeCrwN7AQsBeQAQtTGd53jzmzkNowfYMVfchhBBCCCGE8SQG2CGEEEIIYbxZolA+MwIW+takQnmeFnUaFzk7uSx/nYUUvBJCCCGE8WWhQvm8ynoROilm33+tRZ1hj/NsPw78hnSS2to5+38IIYQQxpd5C+UrqupE6KjV2K6oMTi1JduvUR/XLyNp9VH2K4QQQgghhBBCCGNAnLQQQgghhBDGm5kL5fsr60Xo5KlCebEWdYqLnOsMo80nCuUlR9yjEEIIIfS7KYXyM5X1InTyXKH89hZ1iuO8ZYfR5nXAzrm8FpH9P4QQQhhvXiqU36ysF6GTiYXyQi3qFMd5Kw6jzTsK5ZWBf4y0UyGMRT0Ixp4KvAy8aHtyyW2HEEIIIYQQQikiaCGEEAaEpI1LbvKtyS9gou1nS24/hBBG65FCecHKehE6uaVQ3qRFnQdI7zVzAJtImsH21DZtzlsoz9dV70IYQyT9tOQmh4zzgDuBW20/VvLjhBDCSBWz8y9TWS9CJ/8plCe0qFPczDac+YpJhXIEp4aBIansQPym4zzgatuPlvxYIYQwErcWyqtW1ovQyX2F8jtb1CmO2TcfRpuvF8qLj7hHIYxdDzL0lLrSSHqF+jjvSuCCfLJJCCGEEEIIIVRKdk8+B4UQQugzkqbSo8mv7Fnqk19nxEJneSQtStp4PTcww2jbsX1NaZ0KoY9JWgJ4KN/8i+2yg7ZCSSQ9A8wPTAaWtP1kkzpXkTayGdjP9o/atHcB8OFc93O2v9+DbofQd6bDOK/mPuA04NRmz9cwfJLmBDYEVqf7cZ5tf6asvoXmJM1DOhloDmA2RnG9YjzePUlzAU8Cs5Jek1Z0TG72HUkLkU7AMnC37ZVb1HuS9Br4BrCQ7RfatHkYcFxu80u2v1Z6x0PoQ4VxnkpsttnrpoErgK/bvqzExxo4kjYBtqa8cd5yZfUtDCVJwCrAcnQ/zjum3N4NHkkzAo+Rsvc/ByzbbmwQqiFpDuB50vvSU7YXbVHvXtJpWgaWt90yCE/SCcAXc90v2v5G6R0PoQ/1aJxXVBzzvQh8HzjK9hs9eryBImluul+3jRMEQwghhBDCwImghRBCGBDTYfIL6hNgBs4hbRiNExhGQdKqwEHAVrQ+ZnkkbDtOWOoBSe8APghswLSLnCN9vsV1KomkS0mbBAxsZ/t3FXcpNCHpFODTpOt0ou3DmtQ5CPh6vvkcsFqzbO+SVgf+TjpNzsAHbP+pV30PoZ80BC0U33saP/C3+lmr96tWbT4PfN72mSPs6sCTNDNwLPBZYK4ymiSNH2Ysoa1QIGkmYE/gQ6RxXrcn+MQ4rySSvgfsS2xe72sNG9VWt31bkzoXkZ5jBr5t+6A27f0VWDfX3dv2qb3odwj9pmE+r9liTrt5h3ZjwcZ6xfZPA/aPbLwjI2kZ4CxgrcYfjaK5t65JjPPKJ2ll4DBgG4ae2DhqcZ3KIekLwDdIz4Gzbe9WcZdCE5KuA9YmXacP2v5tkzo/BT6Z6/zO9nYt2poJ+DfpFDUDe9j+RY+6HkJfyeO8muGO24qGM7dXq1cb690JbGv7oTb1QxM5OH9f0rrTasAsXTYZ80QhhBBCCGEgRdBCCCEMiIomv54CtrJ9a5v6oYGkfYFvkTbelhVkEoucJZM0P/A9YCeGXqdurllcp5JIeidwIykL73PAFs02SoVqSdoM+BPpPeNFYCXbTzTUWRh4gHQtBTxKyr52se1XJM0AbAv8EFgk13kVWNj2S9PrdwmhSm3GebX3pCnA08DrhZ/NTdqgU6tTu98k4IX8/TlJG+tnbmi/NtaLzcIjkDdjXA5sxLR/d+g8xm5VJ8YPJZO0NikIe8nat7poLjYdlkzSvMBtwBKk17e9bJ9WZZ/CtCQdD/w36TnwS9u7N6nzcaAWADcZ2LpZ0KmkTwBn5JsG1rN9fU86HkKfySfPmfR5qBa4A+m95WXgBtLJJo3jvCWA95DGcbX7PAhcQ32cNw+wMin5Agwd511ge6fyf6PxSdKCwC3UP5M2Jo5pN5Yr/ryxTowfSibpAOCbpKzI7QK+h90kcZ1Kk+d4Lgc2JV2TM4B9I4iqv0g6EDiJdI2annIr6X3AZdSfW8cAxzSekibpZOCAfNPAKrbv6lHXQ+grko7MxeWAT1AfP7xJGrNdS+tx3oaksWFt3PEgcDzpc1VxnLdObr/oX8AGtp8v+3caryR9CDid9PeHctZuY/wQQgghhBAGUgQthBDCgJC0Zy6uC+xDffLrWeAiOk9+bQ+8jfrk10GkLLvFya91SQsKMxTafwxYt1lW7DAtSVuQJvObLXBC50XOYp1ivZj8KlFejL4WWJ6h2Qi7naiM61QiSTuSNkHNStqA+wXbP6u2V6GRpOuBNfPN85ttjJF0DHAEQzfRTCVtrp6TlNWouAH4NNuf6W3PQ+gveUP8SdQX+18Hfgb8Avib7alN7jMHsD7wGWBH0vNoEimz4aWFeu8gjfM+DmxJ/bk4lZRVMU6zGQZJR5A2ajSOGyaSgq0Wox7E9Y/CXRcgjTlmLdx3CmmcDYDtZXrW8QEjaTXgr9RPzSrrtLoY55VI0krAr0nPDQM/Bw63/WilHQtvydfojnxzKmle4KaGOrMD9wCLUt+c8zPSHMUjpOC6j5Le22pB/U8Bi9ue0vNfIoQ+IWkp4Dzqn5vuBI4GLrL9Rpv7vQ3YA/gyaTN90xPuJC1B2ih3COlkodr738G2v1XqLzNONZwiWBsn3wHcS3pt2zn/7HHgJ4W7LgCsAaxH/e8+mXS93wCw/anp8ksMgDxPdE6+WeaJxDHOK5GkOYEfA7uQrtM9pNex85p9rg3TX54bfwCYPX9rd9u/bFLvBtJrXO317d/AxdTHeR8BVi/c5U7b7+pdz0PoPznA5xzSOqtIn4eOHM5n23xy0LeA95OeY9eQTp1+uaHeusCJpCQa5Lrft/25kn6NcU3SGqR5otrJCt0EpxbrxfghhBBCCCEMpAhaCCGEAZKzE55KWuyfAhwLfMP2K8O473zA10ib2mpHiG5u+6mGeouRJr8+Tn0ipmlWxTAtSX+lnjlPwBXApaRFTpMm9Q3cRTrCvKa2yPlJ0ubD2iLnUaTJNGxfPR1+hYEg6efAbgydnHySlNn/IdJmw1FlALN9dBl9HHT5JAxIx/SeTgrAqj13TiE9tx6MbELVk7QB8F/5poFDbD/XUGdG0mvhB2i9saD2/WeAdzW+P4Uw3kk6H/hwvnkrsLPte0dw/42As0kb2iYD2zcLRsgBlr8AFiQ95261vXpjvTBUfh17jPR3I5cPAy61PVHSrKRsyQLus71Cw/3nJI09jiRt7jXwXdufn06/wsBoMh5/Afg9KZN1t+O8GI+XQNJHc3Eu0mfa2jhvMulaXUEKtJ/ECLMm276mrH4GkHQOKSgO0nvTmo3BBpJ2AX7J0ODUaZrKX03awHNcb3ocQv/JY4QbgXfmb51GyjreMlihSRsLkAK9avNFR9g+vkm9hYDfAGvlbz0JTLD9emPdUJcDgZ8mBZhCSkayj+2H888FvELa6PaY7aWatLEi8G3qn3lvBLa0Pannv8AAkfQw9XGDgCuBcymM8+L/e7Vy1v2aD5OuF6RrNom0IfdBRjfOO6bb/oU6SScCh+abTwMrNM6z5o2+11IPCIc2J8sAH7f9q970OIT+I2lx0imC85ECHj9j+/RRtFM7scTAubZ3aVHvJ6Q1XkjzGsvYfnI0fR8kkn7P0HWJ+4DfUl+3PTl/vQ/Yq3DX2rrtbsAE6vMWJ+a6jOZ6hxBCCCGEMNZF0EIIIQyInOXwZtIE8WukrLh/GkU7h5ImVAxcaft9LeodSdpUBWkSZkXbD4ym74NC0pKkBbLam/Netn/aUOcZYH5gku35aULSbsCPSCdjvA5sHRukypMX+58gnSgCcAtwoO1rK+tUmIakqbTJYNNF07Y9Uxf3D6MkaRbgm6TTgmrPv8YsRg+QNlrfPp27F0KlJH2KFJhq4HZg49EEZUlaFbiOlC3xaeAdtl9sUm8t4M/AzPkxPzCaceUgyZs1bqR+ksKqth9pqHM/aRHzdduzT9MIbwXlXUQ6Cc3ACbYP713PB0s+VeRu6u8vp5JOanq59b3C9BbjvLEjf8bdPN80cGGL95WjSBmUm2WoLH7vemAj22/2pMMh9CFJXwG+RP05tGOHu7RqZx7SOHFxUgb/FW0/1KTegqRg//nyY+5m++xRdn8gSNqUFDBnUvbwlWy/1lDndlLgyRRgdtuTW7R1EnBgbusS29v3rOMDJmeZ/iv195U9bf+8wi6FJlqM86CEsV5ksy5XDqpbJN90LVCrSb2tgbNIp3oXx3WNwQs/tL1fj7obQl9qSI51TDcJrSRdB6yd21rP9vVN6sxIOglqhVxvP9s/Gu1jDoIc1Pt44VvH2T6yoc4k0mvcM7YXatLGzKQgr6NJ6xoTSUkBb+tVv0MIIYQQQuhnM3SuEkIIYZz4GilgoZbFelQby2z/H/BH0kTyZjnbbrN6RwM35ZszAh8azeMNmLUL5asaAxayu/PXeSTN1ayRfBTzlqSAhdmA03PWt1COzUj/pyEtRm8aAQt9rXHDUy0bTjf/QgVsv2F7f2AV4HjgatKx8reTsoHuA7wzAhbCgDokfzXwqdGeImP7n6QMrwBvBz7Wot4NQHGDz+bN6oUh3l0oX9AYsJDVxnmzSFq0WSP5JJptSIvMAg6V9J4yOzrg1iuUb7S9dwQs9LVm47ziz0YytotxXg/YfsT26fnfGc0CFnK9o0jvOQ8z7XWoXZuzgPdHwEIYJHljWS0b7ivA/qNtK48Pv5pvzgw0zcBr+2ngO4VvbTjaxxwgKxbK5zcGLGT35K8zAEu2asj2QaQAVQHbSdqhrE4GVimUL4yAhTGncaw3EjHG6wHbr9t+KP9rGrCQ6/2OlGn8V6TkVo3j78dJp9NEwEIYKPlEzY+QXtueJM13d6N4/52aVcin3n2z8K0NunzMQbAO9detmxoDFrLaOG8BSdMkIbH9pu2vkj7zmhQc/AtJkTQhhBBCCCEMpAhaCCGEAZAzw29Fmgx5EPhBl03+X6H80Tb1vl0ox+RXZ4sVyq2CSu4plCe0asj2X4H/zjeXBI7oqmehqHidzmy18Sb0hcZFsNiMNg7Y/rftw21vZvudtlezvb3tn9h+ver+hTC95dMRViaN8662fXOXTRaPJf9gm3pnFsrrtawVahYolP/Ros5wx3kvAZ8mXfMZgaO67FuoW7hQPq+yXoThaDXOG814L8aHfcD2ucDypAD8o4EfkjZOH0zKWv7x+OwVBtAGwELUs+4/2WV751Pf9LtNm3q/LpTXblkr1MxbKN/dos6wxnnZ/sCruXxIu4phRBYslK+srBdhOLpNNhLzgH3G9v22dyNt1N2MFDi3A/Be20vY/kmlHQyhGhuRTjqFFPT4RpftXUY60QnaJxf5Y6H8ni4fcxAsVSj/tkWd4c7nXUAKIhbpBK6Du+1cCCGEEEIIY1FE74YQwmDYgPSab1Jm11Efo5xdDbyZ22yXce2KQnmVlrVCTfHkhMdb1Gmc/Ppnm/a+BxwELA3sAXypm86Ft7ytUL6/sl6ETkZ9lHIIIYwxxTHWH1vWGibb/5b0EjAHaQGtlb8DU0kLbUu1qReSWQrlVidhNI7z/taqMds3SLoa2BTYUtI8oz1hI7T0TNUdCC1tVnUHQm/Ynkx6L+v6/SyEcWKZQvnv3TZm+ylJE4H5ab9x/lbq834Lt6kXkuI8a7NTFmBoMMOEto3Zj0v6DbAzsLakpdplMQ/D9mqh3O3G0NAjtiPZ3jhm+xXS2lIIAZYolP/VbWO2X5X0DGnstlibevdLepV0SvsCreqFt8xdKLcajzWO8+5s095Xgb1Jgcl7ASd207kQQgghhBDGoghaCCH0HUlbkzJKLQtMBK4DTrPdbnN2aG/xQvmelrWGyfabkp4mTXwt0qbefyS9TNr0Nn+3jzsAXi6UZ2xRZySLnFMlnU8KXFhE0nq2W25+C8P2aKH89sp6EdqyHUELIfQpSQuSNmBNtN31uCQMWYjsNvtuzXPAnLTZpJYXQyeRxnjzlfS449mkQnmeFnWGPc7LLiMFLcxCCiS+dBT9CkPdWyhPqKoToT3bsdEphD4kaVbSKU1vzefFXF7XinNuZQUnvkwavy3YqkKeT5pI2kwV47zOniuUW80TFT/3LDuMNq8jBS0ArEXrTXJh+G4rlFetrBchhDAGSXoX8FmGrtv+yvbTlXZsbCsGDExpWWtkpuavncZvE0nzifOW9LjjWauA1KJhn6hl+zVJ5wH7ActIWt12qxNZQwghhBBCGJciY0UIoa9I2h+4BNgaWAlYFzgQuEXSTyXNWWH3xrLixqhWm+FHqhb41mrTVc3E/HXekh53PJtYKC/Uok5x8qtd9uOa4ua35Ufco9DMNdSz6G1bZUdCCGEskTS3pLOBJ0gZ5O+S9LSk/5MUmb1Gr5jZtawg0Vo76lDvxfx1rra1AsBThXKrjHfFcd46w2jziUJ5yRH3KDRzJfUF6Y9V2ZEQQhhLJK0K3AWcDRwP/JA0l3eDpE0q7dzYVkxusXjLWsMkaQbq802dNmDVstLP3u3jDoD/FMoTWtQpjvM2HkabkwrlGOeV41rSmFzArpLiM0wIIQyDpB2Bm4F9gS2BXYBvAQ9K+rKkstYcB00x6HG5bhuTNAdpnGeGjiOaqQU3xLXrbKTrtisOo807CuWVR9yjEEIIIYQQxrg4aSGE0G++RH1zVG0DVu32nsBqkja3XVZ2sUFRzHayUreNSaplZDPwbIfqMek1fP8ulFdvUedu6s+NLYbRZnEj46Kj6VQYyvbDkn5LCljYSNKWtv9Qdb9CGIsk/bTkJqeSNva8SFpQuBO41fZjJT9OGJ2fADs1fG8B0olAu0vazfYV079bY17xdIWNgG9005ikd5NOWTCdT26obfR5vZvHHBC3FMqtNm8+QHoNmwPYRNIMtqe2qAtDg4IjC3IJbD8v6RTgAGB5SYfY/nrV/QohhDHgR8DSTb7/XuAKSUfaPm4692k8KAYobgN0+zfcHJiVNM57okPdWhDrK10+5iC4sVB+X7MK+TTap0nzqetImtv2C23aLAa5zlJCHwee7cmSvkraaDs/8APgE5V2KoQxStJSJTf51nye7ckltx26dwLN95TMDhwJrCdpe9tvTN9ujXnF+eodJf2Pbbes3dkOpPVYA493qFs7GerltrUCwH2FcqtEcsXkcZsPo83iPGrXgckhhBBCCCGMNRG0EELoN3MxNFhhMvAO0ubsrwDvAX5OOm4+DF/tCHEBO0n6ou1uNpd9PLdlhk6sDZEzuNUyJ7/Yql54yy2k//MzAZs326hm+2VJd5Gybyw3jKNDVymUY9K4PAeTNhzOAZwpaQvb/6y4TyGMRZ9kaHBVT0i6DzgNONV2p03YoXe2Zeg4z8BVwJqkTFW/lfR+29dW070x6/b8VcBWkla2fWcX7R1cKN/dqlLOTDof6TpGQHEHtu+T9Bxpg9SakhZufD2yPVXSTaTsu3MDe5E2gbZSzNIb16A8/0vaGLoscLykZ2yfVm2XQhh7JN1fcpNNg1OBq20/WvJjhZF7D9OO844mbdrZGDha0iTb362me2PWdYXyOpI+ZPvi0TQkScCxhW/d3KbuotTnaDslKxl4tp/Kr3nLAitIerft25pU/RvwIWBm4ChS8HYr2xXKcQ3K8x1gq/xvV0lvAPvZ7nTySKiYpLlJn5FmGG0bth/uXCsM04P0aD5P0ivUx3lXAhfEc7RyCzN0nDeVNMbbgvRe9gFSINhnKund2HUNac1uZtJJTYczygDVnGjuKw1tt6q7IjAbwwtuCGnMPJX0f//9zSrYnlQYC64iaVnb7T4Pr1Aot0tWEkIIIYQQwrik7gK2QwihXDl7+VbUJ8Cus71B/tkiwF9Jmdt2tH1hNb0ceyTNBjxD/Uj3H9ref5RtTSBN0syTv/U1219qUXc14B+k6/lP2+8ZzWMOEklXAJuS/mafsH1WkzrfBfbLdd56jjSpNwdwL/VJ5V1tn9Ojrg8cSdsB55KyFL4AHGz71Gp7FZqRNCewIekEkwXpbpHTtmMBpiSSpjLtyUow7cJnq5+J5lq1+TzwedtnjrCroQSSHqGeMVTAC7bnzZsPvk06Ves/wMq2I9hxBPLC2NKkv+sdwPttd8qe26ydvYEf5psGDrD9gxZ13w/8Ide71vamo+j6QMkZ/D9N+pudaPuwJnUOAmqZ/Z8DVmt2Woyk1YG/k4JdDXzA9p961fdBI+kdwOXAUqS/7y+Bw2OjU/+RtAmwNeWN85Yrq2+DrjDOazVeG41mE9kGrgC+bvuyEh8rjICkfwErFr71uO0l8s/2BE4B3gTe1WEDT2gg6QZgDdJz6Xlgh5GeTpaTivwM2D1/y8DHbJ/Xov7OwK9yvT/Y3maU3R8Yko4H/ps8brC9e5M6Hwdqn0UnA1s3G79J+gRwRr5pYD3b1/ek4wMoz5OfSz2o/l5SkNXZtqdU2bdQJ2khYF/SOG81uj9xxLYjkV9JejTOKyqO+V4Evg8cFZn8qyHpWmD9wrdut71a/tkqpIQk8wOb2756+vdw7JL0a+pJ+gwcAxw3kvcjSUsDvwbeXWhnM9tNAxck7U8K4jNwvu2dR9n9gSHpOmBt0t/sg7Z/26TOT6knaPqd7e0a6+R6MwH/BpbJdfew/YsedT2EEEIIIYS+FEELIYS+ImkZ0uTKu4D7gQ/Z/lfh5+uSAhe+YfvQano5Nkk6k3RCAqSJkDOAL9ieNII21gHOAZagnjlvzVaZ/iV9kXR0rIFf2f54s3qhTlIto65JmZPf03gkbOF5UPv+acD/s/1yoc6swC+Aj+ZvGVjO9oO97P+gkbQBaRPbkqS/8T2kzRiXAw/YjqzHFZI0MymT5GdJWSK7bpK0yDljCW0F3lrkrGkWjDAFeJqhRybPDcxbqFO73yRSAJGAOUnXfOaG9mvvXV+y/bWuf4EwIpK+AhQDHX9QDKIsjFWOsX3UdO7emCbpQOAk6v/PHyf9rc8cztHykuYlZWT7bO1bpOfU8rabZnaV9GPgv/Jjnmz7C139EgNA0mbAn0h/sxeBlRqDSyQtDDxACooU8CjwReBi26/kTYfbkoJLFsl1XgUWtv3S9PpdBoGkt5PG5R8hXbMpwGXkcR7pOTKiSbVWmwbCyOW5g7OAtRp/NIrm3hojxDivPA2b2Zo9V9pdq3YBrI31iu2fBuwf2XinP0m7kE5GrQUN7Wv7R4WfHwJ8jXTy2V4VdHHMkrQNcAn1/+9TSBvfv9Uim3/xvgK2JM3NrVr40T2kAJLJLe53MSnTv0lj86O7/T3GO0krkYKHIWXMXdf2TQ11Zif97RclXcs3ScEkFwGPkD7nfhQ4gBSYKuApYPHYTF8+SQeQghVqp8e9AFzN6Md5x5TcxYEl6UPA6aT5HyhnY3yM80rUZj4Phne9hpOQpFavNta7E9jW9kPD6mQojaQ1gEtJybEmkdZt/1z4eW2scortvSvp5BglaWXSCey1930D95GCCn7dLnFCvu+epHHD7IX7X257yzb3uwF4b677+TgJrbOGede/2N64SZ33keaMaq9vx5DG0Y3ruyeTrhm57iq27+pR10MIIYQQQuhLEbQQQuhLkuazPbHFz5azfd/07tNYJ2lx0sTuHNQnryaRFvV/DdxU3PReuN9cpAzlewI7Ul+ANnCO7V3bPOadpEx7BvaOLPSd5b/3A6QFM0iBJSc3qXcZ8D7qE2ATSRuoaoucW1NfBDVwg+11e9r5ASVpQdKk/Zr5W90MriLrV0lyxprLgY2YdnM7dF4Qa1UnFjlLlq/VSdQn618nbdz4BfA329MckZxPklmfdOz4jtQ3WO9h+9JCvXcA65I2wm9JfbFzKikr0u9681uFZvJm6wOBTYAbgRNsv1n4+fykDTv/Z/s3VfRxrJI0I3AD8B6GLuo/S1o4vomUxWsS8DLpGPj5gHeSXie3y98rvl4eaPs7LR5vbtKYY65cdyvbfyz/Nxt/JF1Pfcxwvu2dmtQ5BjiCoddyKun6zUnKMlq8VqfFKUC9IWlD0ntUjPP6SB5/30I9cKcxy2u7sVzx5411YpxXIklXkf7Ws5LGY8Xr8jLpfesJpg1OXYL0fjZz4T4PAtdQD06dB1iZ+glOxdfLC5q9tobek/ReYGPS/NI1DT+bCfgy8BPbj1TRv7FM0umkUxIaA3Ueov04b33SBsPia90UUob/y1s81nLAXdTn/1omKwlDSTqH9PkU4FbS325KQ51dSMkvhhPUZeBI28f1pseDK3/23I803108ZWnUY70YQ5Qjb47+K/WTFboZ5xXrxTivRJKOzMXlgE9Qv05vksZs19J6nLchaWxYew18EDiedAJNcZy3DkOfnwD/AjaIREHTXw68Wwm4z/YLTX6++UhPggpJw8kHjesYz9F8nLcy6XQLGPqZ+BnSCU1N19AlbUo6pc753zIxNu8sz0E8QAoOAdjd9i+b1CuekGbStbuY+rrtR0inRNbcaftdvet5CCGEEEII/SmCFkIIYYBI+gjpePfaZpnGxbHHmXbyazHqE2XFya/7gfVtP9Xmsc7P9ScDS9h+usRfZ9yS9CVStmNIWXiXsf1cQ51lgb8z7cQkDbdrX7dstSAdRiefZvG/pI3WxSz+3WT/igW0kkg6gpTNpnExcyIpI/Vi1DNdFzdgLAAsT9pcVbvvFOCxWgXby/Ss4wNI0vnAh/PNW4Gdbd87gvtvBJxN2rg4Gdi+WTCCpC1IgRALkv4/3Gp79cZ6IYxVeQHtStIGtWYLnW3vztDXy7bZ8SQdCxyebz4OLBXZX4cnn9L0X/mmgUOajPNmJAVEfoBpN+lQuG9tQfpdrcbkYXQkrQicCqzXqsoImoss/iWTdArwaYYGI94B3EvaKLVz/tnjwE8Kd12AtIFgPeqve5OB84A3AGx/arr8EgNC0lKkv28t8OdOUlbri2y/0eZ+bwP2IG1yX4R0rU60fVhDvSVIG+UOIc1f1K7rwba/VeovE0KFcvDvmcCuTPsZt91Yr1in9vz4jO3T2jzWL/LjQHxmGhFJSwKb55sGLrT9YpN6R5Fe35ptvi5+73pgo2Kgd+iepF2BH1DOiZwQ47xSSfo9Qz8H3Qf8ljTOM3Ay9UzkxZN7auO83YAJ1Md5J+a62D59evwOgyJnFT+HFGQgUgKSI20/Ooz7rgx8C3g/6VpdA2zXmFQrnzh9IinZArnu921/rqRfI4S+IGlv0nNiNloHaw25S8PPRDqteKt2waaS/kJ9nuN3trftotsDRdKJwKH55tPACo0BVDnw7lqmTQzzVpVC2cDHbf+qNz0OIYQQQgihf0XQQgghDBhJ2wI/JW3a7JSZqKhY9y5gG9sPtnmcfwKr5Jvn2N5lVB0OLUlaE7gQWJz2E5eH2T5hunVsAOSMbJcDqzHtRs9uxCJnCfJmz8dIr3Pk8mHApbYn5oCTl8mLn7ZXaLj/nKRFziNJJ5YY+K7tz0+nX2FgSPoUaVOogduBjUeTLU3SqsB1pGxHTwPvaLE5ZC3gz9Qz937A9p9G/xuE0F8kzQt8A/gkw39/KtZ5gxQ4eVzj8eUNj3MO9VOhzrf9w9H3OjQjaRbgm8A+DD3pDOrX8wFSoNbt07l745qkdwNXUd980ypwZKRinFeCfNrS06QAU4DLgH1sP5x/LuAVUnbex2wv1aSNFYFvU98QdyMpyHtSz3+BAZLH3DeSgukgnfK4b7tghSZtLEA6GXJ90rU6wvbxTeotBPwGWCt/60lggu3XG+uGMJZJ2h34P2Ch/K1mGcVbZRm/h3QK6tUdHuMQ6q+x1zaemhHKIWkn4GvA0i2qnAV8ttnn2jB6knYkJT0oY2xXFOO8EuT388cL3zrO9pENdSaRMvY/Y3shGkiambSp9GjS56iJwOa2b+tVvwdRPtX7NtK8wFRSQNyIg0IknUxKCGTg3FZrSJJ+QjptFeA1UpKnJ0fT9xD6VT7t6pvANkw7D9T0LvnrZODnwKG2n+3wGGuT5sUBHrD9n9H3eLDkz7eL5JuuzUE0qbc1aRw3N0Pn8RqDF35oe78edTeEEEIIIYS+FkELIYQwgCTNR5q43520Gaem3cZ3gGdJx5Se0GmjQV5kqE1+TWrMkhPKka/loaQslIsVfmTSBt6jbV9WRd/GM0m/ImVwLXqStCnnIVL2/tdG07bto7vrXcgZbW6kfpLCqo3HHEu6n5R57XXbs0/TCG8Fp1xEOrbcpNe+w5vVDaMj6Q7ScdZTgbVt39xFW18F/od0rfaxfUqLeqcCnyKuaRjH8uvgPsBOpOPHO5lEOonkZNv39K5nYaTy5uo9SBt2FyZlkX8QuAQ4Izbklk/S9aSs8LVghReA3wM30P04r+1G0dCZpE2BK0jX5xFgJduvNdS5nbRRfgowu+3JLdo6CTgwt3WJ7e171vEBJOkrwJeoZxvfcZTtzEMKbl2cFFy3ou2HmtRbkJRgYb78mLvZPnuU3Q+hb0maDfgI6TSE9amfwNnMC6Sg7Z8Bv271ehiqIWkmYDOmHeddavvuCrs2LuUEFw9RP3lTpJPqzqUwzovxdXUkfZAUrGjgJttrN6lzA/DeXGdO26+2aOujpFMABPwLWD1eA8sj6eekhC8GjulmPlvSdcDaua31bF/fpM6MpJPVVsj19rP9o9E+Zgj9TNJiwC6k8cEapADHxmC72lrU1cCZEcTTXyQtCxwH7EB9nbzmP6R1259Mc8cQQgghhBAGRAQthBDCAMuZIbalPvk1gRTEMBdpM8Ak0kaQ2uTXxSPJihimL0lLU1/kfMj2cxV3aVzKmaQeoj5RfCvwedvXVterUCTpk6QTZQycbvvTTeoUj5tfwvbjjXVyvTmBv5FOjplM2lh/S296Pljy6Qi3kq7BVba36LK9FYE76bDxsGGz49W2N+/mcUPoZ3lhf2U6j/NujQ0cIUzz3gRpPHFgBGD3D0n7AD8gXaNv2T64SZ0Lge1znXfYfqBNexcAH851d7Z9fi/6PWgKJ58tRDrh7B3dbKSRtC/wPdJ1Osz2iS3qHQV8Odf7vu3PjfYxQxgrJC1F63He3e1OzwphkEjaiDS/XXtOfNL2mRV2KTSQtD8pYZKBY20f1aTOL0mbeQ28y/adbdo7BjiCDuOHMDJ5rvRJYDbqp1uNes1I0vak06QNnGT70Bb1ip8DfmF7j9E+5iCSNBewACmxxaykjdSTqY8bnh3N6bdh+sjX761xXszhjQ2S3kY6DfCt4FTb/6i2VyGEEEIIIVRvpqo7EEIIoTo5c9QF+V8Y43K2yWkyTobSbUg6nreW3XUT2y9W26XQYIFCudUk8D2koAVIGzyaBi3YfknSp0knl8wIHEXa2Ba6t0qh/MduG7P9b0kvAXOQsiu38nfSyQ4Clur2cUPoZ7ankLJT3151X0IYI9YslG+0vVdlPQmtzFsot8pCXTwxZgLQMmgB2B/YkrTp6hAgghbKsQEpYKEWTNpt5s/zge/m8jZAq02HvyYFLUDK2BvayBlANwDeDSwPLEmHzWzAw6Tn2K3ANc1OvQjTl+2HSdclhNDeqoXyRRGw0JfmLpRbva4Vx38TSMkrWvkqsDdpTLIXrccPYWQ2AmYnjfPOLyHJ1WWkE9JmANolFinOHb6ny8cc1yQtQZr3ro3z3sHQ51er+71EYZwH/MH2Ez3sahimvP4Ua1BjjO1XSAGTIYQQQgghhIIIWgghhBBCGJklCuUzI2ChL81SKLfKENW4me1vrRqzfYOkq4FNgS0lzROZp0qxWKFc1hHWzwFzkrIXNWX7VUmTgPmB+Up63BBCCOPDQoXyeZX1IrRTzBj+Wos6jZvZWjdmPy7pN8DOwNqSlsobgEN3limU/95tY7afkjSRNH6b0KbqraQMljPRZjw4yCQtBnyWlKV6uWZVGm7Pkv/NSfos/O6G9u4CzgB+ZHtS2f0NIYQSzVsoX1FVJ0JbrcZ2RY3zeS3Zfk3SecB+wDKSVo8M16Uozo3/q9vG8jzdM6Sx22Jt6t0v6VVSsPECreoNMkk7AZ8jnaxeHNM1ju9amQtYPf/7JDBV0uXA/9mO180QQgghhBBCCKWYoeoOhBBCCCGMMTMXyvdX1ovQzqRCeZ4WdYa9mS27LH+dhXTaRuhecdPh/CW1WWun02JcLdhorpIeN4QQwvgwpVB+prJehHaeK5Tf3qJOcTPbssNo87pCea0R9yg0s0ihXFaw78v564KtKtieCkwkjQUjOLVA0tsknUT6DHs4KeOuGN2GtlpdASuTMlk/KGm/krobQgi98FKh/GZlvQjtTCyUF2pRpzjOW3EYbd5RKK884h6FZooBA1Na1hqZqflrp/FbbZw3b0mPOy5IepekG4FfkU5XKO7/GMn4rlhfpFOHPwD8UdI5kubourMhhBBCCCGEEAZenLQQQggh9BFJG5fc5FTS5o4XgYm2ny25/UH0SKHccsNMqNRThXKrDF3FRc51htFm8SjsJUfco9BM8XSFjYBvdNOYpHeTMsCazic31IIVXu/mMUMIYSQk/bTkJoeM84A7gVttP1by4wySYlDjMi1rhSr9p1Ce0KJOcZw3nM9XkwrlGOeV4+VCefFuG5M0A/XNi52yML+av87e7eOOF5KWBS4FViBtQHP+V9yU9gLwKOk59irp7/waKWh7NtLfcyFgKYYGHNcCkecGvpPH5PvlAJIQBoakspNaNB3nAVfbfrTkxxoUtxbKq1bWi9DOfYXyO1vUKY7XNx9Gm8V5n67HJAEYGkTc7NSmEckb4RcijSkmdaheG1/M2O3jjheSPgScRRqv1cZ55PIU0mkYDzD8cd4E0mtkMXGTgB2AZSVtY7s49x7CuCdpqZKbfGucZ3tyyW2HEEIIIYTQ9yJoIYQQQugvVzE0+3ipJD1LWqS7EjgjFjpH5Wrq12g74GsV9iU0d0uhvEmLOg+QJobnADaRNEOHjTXzFsqRtbUct+evAraStLLtO7to7+BC+e5WlSTNRbqGprzMvyGEMByfpIfjvBpJ9wGnAafa7hTEFYa6krR5Y1ZgF0lH2u75NQsjcmOh/L5mFWz/R9LTpADjdSTNbfuFNm0Wg1xnKaGPYWjA7zbAcV22tznpeemGtpupbah/pcvHHBckLQZcQ/p/XtzEdidwLumkkb/bnti8haZtzgmsSzqBbjfSqQ21IIi9gMnAASX9CiGMFRMYGgxUhuIYZJva9yRdAXzd9mVN7hNa+zMpycVCwK6SDu8wPgjT382kjZwC3t+sgu1JOUhoWWAVScvabhc0tEKhHAF15SgGye8o6X+6/My0AykIwcDjHerWTlp7uW2tASFpPeAc0meY2jWYRDpx4VzgBtsj/ltJmp2U5OcTwC7A20jPy9WBs4HNuu17CGPMg/RoPk/SK9SDU68ELrDdKVA/hBBCCCGEMW2GzlVCCCGEUAH16N/bSRs+jgUelPRLScUjnUMHOdDj96S/5waStq64S6GB7ftIWb8ErClp4SZ1pgI35ZtzkzbXtFPM0hsb3Utg+zbqE/6zAOdIWmQ0bUnaG9i98K3ftKm+LvWNJPeO5vFCCKEExfHZcH/WanzX+PN3kMZ6d0ranTBstl8Efkb6Oy4HHFptj0KjnNXzftI1WiFndW/mb/nrzMBRHZrdrlCOk+nKcV2hvE7OADsqkkR6Tau5uU3dRUknapm4ljU/ox6wINJzYz3bq9g+yvbvRxKwAGD7JduX5/uvAHyIlL239hj7SmoaVBTCgHCTfyOpX9NszDcDsAXwO0mnSpqtxH6Pa7anACfmm/MBP6ywO6GJvLn6RtL/94UkbdOi6jWF8smt2pM0E7BT4VudAh/D8FwDvJHLE4DDR9uQpPmBrzS03aruiqRTAYYT3DDu5f/fp1MPWJgMnAAsbnt/21eNJmABwPar+f7/RTqB8JLawwIbS9qv+98ghDGpF2u2cwDvBT4NnAk8IemrkiKhQgghhBBCGLciaCGEEELoP7WFyJEscNYMp35xofNjwO2SVhtFPwfZoaQsvABntNksFapzUf46I/D5FnUuzl8FfEVS02PiJa3O0M1s/y6jgwFIi8u1o8tXAW6StEfenNaRpHklfQ/4AfXXvedJWcZaKS5Y/2PkXQ4hhK7UFiWLY7ba96YCTwIPFf5NKtyPwn0m5p8/nMvNjpOfFzhN0hfL/zXGtcNJm29r44NPVtud0MS5hXKrwJJaHQEHSNqiWSVJnyAFNNb8s/vuhRzoXQsQFnC6pM1H2o6kGUgnx6xT+PZFbe6yUaE88GN2SZuQMlXXxslfs72B7b+X+Ti2LwFWIz1/au9rR5T5GCGMAdfkf9cxbVDpK6STVX9F2mBa+3chcANpHFe8zwP552cAFwB/Av7TpN1Pkja3heH7NulaCPiYpJ9F4Eff+VWh/D8t6vyyUN5a0pEt5pFOIm24rrmpSZ0wQjnQ+w/UP8cena/BjCNpR9LSwBVAcT72/DZ3KQZE/mskjzVO7Uz9tKvJwE62Dys7Q7vtp21/CDgrf0vEiVphMPVy3bYYoDo38N/Azfl1MoQQQgghhHFHccp9CKGTfNxuVWx7uQofP4TpStKeubgusA/1Bf9nSZszriVlhXq9cLe5gSWADYHtScf1mpTB/CDSBt45gXmAlXPbm5KCFmrtPwasa7t4vHNoQ9KOpMXhWYEXgC/Y/lm1vQo1kjYjLewbeBFYyfYTDXUWJm0GmJX0PHgU+CJwse1X8iapbUnZ9xbJdV4FFrb90vT6XcazvKB5A/Ae6q9Htcy4l5AWlP9N2rT7Mimj2nzAO0mb0rbL3ysuGhxo+zstHm9u4BHqGXi3sv3H8n+zsUPSxp1r9Y7tlln0QhiPcjbEk6gv8r9OyoL9C+Bv+SSgxvvMAawPfAbYkfSaNwnYw/alhXrvII3zPg5sSf11dSrwQdu/681vNf5IWgn4NbA86e/4c+DwvBE7VCxfnzvyzamkzzE3NdSZHbgHWJT0PHiT9Fy7iDQWmBf4KOm5OFOu8xQpM+mUnv8SAyBnR76E+mvRFNLnp2/lE7fa3Vek17ETgFULP7oHeJftZoFaSLqYND40cIzto7v9PcYyST8hvXcYuMD2Th3u0u3jLU0au89Cem4uHXMMYZBIWgo4D1gzf+tO4GjgIttvtLnf24A9gC+T5h4MnGj7sIZ6SwCfAA4hfS6ufX4+2Pa3Sv1lxjFJcwI/BnYh/f3uIf3tz2s2Fg/Tl6QFSXN1s+dv7W77l03q3QCsQf158G9ScpLaOO8jwOqFu9xp+1296/lgkbQycAv1cbSB+4DvAL+2/XCH++5JGofPXrj/5ba3bHO/G0jZyA183vZ3S/llxihJ55P+nzd9z+jB481OSpqwQH7M99iOgO8wECQdmYvLkcZitc+4b5KCVjut29ZOfq6t2x5PCjYqrtuuk9sv+hewge04+TuEEEIIIYwrEbQQQuhI0lTqH8CnN9seUYaWEMa6nO3zVNKk/xTgWOAbtl8Zxn3nA75GfWPCncDmtp9qqLcY6Uj0j1PP7vFL27uX9XuMZ/noakjZJE8nTT4auAs4hZQl6sGYTKyWpOupbxY4v9kmHUnHkLKAFjfMTyVtBp2TtOGmuCH+NNuf6W3PB0tekL6SFIhQHG8M54NK7ZrVyqfY3rvNYx1L/dj6x4GlBn1jYmGcVwXbnqmixw6hEnljwYfzzVuBnW3fO4L7bwScTdrQNhnYvlkwQs4q/wtgQdLr4622V2+sF6Yl6aO5OBdpHF4b500Gfk8e55HGCiN6/YxArfJIOocUxAPpubRm43u6pF1ImXiL47xpmspfDRxp+7je9HgwSTod2J1pr8FDtA9OXR9YmKHzUFOArW1f3uKxliN9HqudLLym7YE+VUvSHaQNMAZW7xQsUtJj/gLYNT/mDrYv6vVjhtAPJM0K3Eh6DYN0Ssy+7YIVmrSxAClocn3Sc+gI28c3qbcQ8BtgrfytJ4EJtl9vrBuGknRy4eaHSeM8SH/vSaSNhw8yunHeMd32LySSTqR+mtbTwAqNc6yS1iBtEm1MZPFWlULZwMdtF09xCF2StD8pSKHZXN5zNB/nrQzU5tVVuO8zwHq272vxWJuSPofVMpUvY/uRMn+fsUbSg8BSpL/HErYfnw6PeTIp2MTAbrbP7vVjhtAvJL2PdLrzPKTXrZ+R5hA6JrfIwVrfon4K3jXAdrZfbqi3LmndtnaCoIHv2/5cSb9GCCGEEEIIfSGCFkIIHTXZzDY9gxciaCEMlJw19GbSRP5rpKy4fxpFO4eSJrcMXGn7fS3qHQnUsoRMBla0/cBo+j5IWmzyHclG61ZiA2+JJG0A/Fe+aeAQ28811JkRuBT4AK0D9IoLaO9qDAIK3ZM0L/AN4JNMG4jQSrHOG8BXgOPc5gNO3uA4X755vu0fjr7X40MEp4Yw/Uj6FCkw1cDtwMajCXCUtCpwHSkr5dPAO2y/2KTeWsCfgZnzY35gNOPKQRPjvLFB0pLA5vmmgQtbPA+OImVPbja2KH7vemAj22/2pMMDKp9cdib1TewwvOdTsU5tbPgZ26e1eazaZnmIQC0AJL1EOonxFdtzTqfHPAj4Ouma/T/b35sejxtC1SR9BfgS9fekHTvcpVU785DGiYuTPueuaPuhJvUWJAVqzUdsHh22NkH7XY/14rNteXIQ0CL5pltl7Ze0NXAWKZt1cZzRuJb1Q9v79ai7A03S3qSNuLMx7dzScJ5rIn2m3apdsKmkvwDr5Zu/s71tF90eFyS9Sjo9+Dnbb59Oj7kf8F3q8+zfnB6PG0LVJC0O3EYad00lfTY9fRTtFAN/zrW9S4t6tRPzIK0TL2P7ydH0PYQQQgghhH4UQQshhI4aNrOZtPFluh2VbHuz6fVYIVRN0sXAdqTn2udsf7+Ltv5APXNHy01qDUcrH2T726N9zEHR5HVxyI+7aDo28FZA0izAN4F9qGdmbdxU9QApm/Xt07l7AyVnytsH2AmYdxh3mUTKJH6y7Xt617PxK4JTQ5h+ChmvpwJr2765i7a+CvwP6fm7j+1TWtQ7FfhUrneC7cOb1Qt1HcZ5b1UbQZNvtRWvedWQtBPpNLqlW1Q5C/hss6CHUA5JuwP/ByyUv9XsM1Srz1X3AHvbvrrDYxxC2rgFcG2cbAKS3gBmBJ6wvfh0esz/An5Mup5fsv216fG4IVQpJ0N4jPQa9zIpoHTUG8sk7Qt8j/Q8Osz2iS3qHUU9MC+y8A5Dj04ajHFehSQtCxwH7EAK1i76D3C07Z9M944NkHza1TeBbZh2XrXpXfLXycDPgUNtP9vhMdamfn0fsP2f0fd4fIighRCmH0k/B3Yj/d8/xvbRXbR1HbB2bms929c3qTMjcAewQq63n+0fjfYxQwghhBBC6DcRtBBC6EjSZ0kLJTVH2j6uqv6EMF7lY+AfJ20qeJC0yDnqN+p8XOllpEmtH9rev0W9TwBn5Hrn2955tI85KPIiZy/EImeFJK0I7AGsDywMvEl6Ll4CnGH79ep6N1jyxPzKwBrABNKxy3ORMk1OAh4BbiRl0Z1cTS/HB0mPAotS3yx4BGlhf7oYTVaqEMaifDrCraTn2VW2t+iyvRWBO3N7l9jevkW9TYErcr2rbW/erF6oi3He+CRpJmAzph3nXWr77gq7NjAkzQZ8hHQawvrA/G2qv0BKmPEz4Ncx3hsdSU+QNlFPBeay/ep0eMxjgcNJ7zufsn1Grx8zhKpJ2hi4ivT//hzbu7a/R8f2FiLNDwL82fYmLeqtDtyUH/dG2+t087iDIMZ545ektwFrURjntcvcH8onaTFgF9I4bw1SwHBjsPeTpPm8q4EzI3P46El6EFiK9B6wuO0npsNjfhv4XH7Mj9v+Va8fM4SqSZqT9No1W/46wfYbXbS3PXAh6Xl0ku1DW9TbB/hBrvcL23uM9jFDCCGEEELoN3EsfQihI9s/zJsHv5O/9WVJv7N9U5X9CmEc2oD03mzggm4CFrKrSYs0MwEbtql3RaG8SpePOShGnUkl9C/b/yZtsAkVsz0FuD3/C721MfAn0kInpBN6tijhPSiEMFRxjPXHbhuz/W9JLwFzAO9sU/XvpM2qov48D+3FSX/jUN70/kdKeP6F0bH9GulUi7MAJC1F6+DUu2MsUoo7SEELAnYnnYDQax8tlB+aDo8XQj9YplD+e7eN2X5K0kRScNeENlVvpT7vt3C3jzsIbM/QuVYYi2y/QpoLDxXJpx+clP8BIGkuCuO8CEQt1U3UP+N/jh7PaUualRR8XHNXLx8vhD6yETA79aRvow5YyC4DppBOpmmXWKQ4d/GeLh8zhBBCCCGEvhJBCyGEYbH9PUnvAvYhvXb8GHhvtb0KYdxZvFC+p9vGbL8p6WlgMWCRNvX+I+ll0qa3dtkuQ9bN8a8hhNBPbN8vaRvgb6SF5E1Ii50nV9qxUClJC5I2X0203fWYJABpPFZTVjbJ54A5abNJzfarkiaRxnjzlfS445rt2OwUwnRg+2Hg4ar7Mc79lhSIJeBoSZfbvr9XDyZpP9JpaZACUP7Sq8cKo5M3HH4QWBaYCFxn+5/V9mpcKM65PV9Smy+Txm8Ltqpge2oObliIGOeFEPqQ7ReBF6vuxzh1AekUMwGHSPqr7Ut7+Hg/AN6eyw/avqWHjxVGIa/hf5bCOA/4le2nK+3Y2LdEofyvbhvL83TPkObyFmtT735Jr5JOeFig28cNIYQQQgihn0RWkRDCSHwBuDeX3yPpE1V2JlRH0taSLpH0L0l/kfQNSatW3a9xYJ5CuawjxWsBivO0rZUmMQHmLelxQwghjBG27wQ+SVroFHCspLe3vVMYlyTNLels4AlSIMtdkp6W9H+SYoGsO8WM4WUFidbaUYd6tU0ic5X0uCGEEMaGnwIvkN6DFgaulLRFLx5I0j7AN/NNA+dGNuX+kuft7gLOBo4HfgjcIukGSZtU2rmx7+VCefGWtYZJ0gykQASA1zpUfzV/nb3bxw0hhDCmnA3cTxp3zQycL+nYHKBYGknzSjoL2DN/y6QxZugjknYEbgb2BbYEdgG+BTwo6cuSylpvHETF+dApJbU5NX/tFHQ6kTTnN29JjxtCCCGEEEJfiKCFEMKw2X4NOKDwrS9V1ZdQHUn7A5cAWwMrAesCB5IWOn8qac4KuzfWFTOerNRtY5JqGdkMPNuhekxahhDCALN9EfCrfHNO4H+q602o0E+AnagHsIi0OHcQcIekdseWh/aKpyts1G1jkt5Neq6azic31IIVXu/2cUMIIYwdticCXyS9nxtYErhM0qWSPipp5m7alzSjpB0kXQ18n7RhDlKgxLHdtB164kfA0gwd54l0ku4Vko6osG9j3ROF8jYltLc5MCvpeftEh7q1INZXSnjcEConaamS/y0haT5JM3V+9BDGjhwc+klgMun9YhbgMOBRSSdL2ljSbKNpW9LMktaX9B3gAWBn6skS7gK+0W3/Q+lOICUwaxznzQ4cCVwiaZbqujemPVcoL9dtY5LmIAWnmnQ6XTu14IZYvw0hhBBCCOOKbHeuFUIIBZL+AKydb25h++Yq+xOmL0mPUj+ysvYmov/P3n2HS1aV6d//3uQmdZMRyYKKCIIoKjCgMGYMIPgj6IiDEdRRxDA6rwHEMCA6KCJiQgRUBEFFRUAFdBQQAZHgELWRKDQ0SZruvt8/1i5r9+HkynXuz3Wd6+y9a9d6Vp06VfXUXqm2fwWwq+12LYc+Y0h6IXBOtXsHsIntaXcuk/RO4H8oz8tltrcf47ylKI2bywF/t732aOdFDBJJ7Z7xaTFl9sQHKDPcXAtcaftvbY4T0TOS1gNupHSQeQB4ou0He1ur6CZJD9KcpbXRwfFXwLMoHd8XAC+0fVFPKjjAqkEGV1S7C4Btq1VOplveicDrKc/RObZH7SAnaRWajaC3215/tPMiBomkm9pc5Kh5HnCB7VvbHCui6yQdRRmAaJqf71AGs10OXELpkDYXuJ0yc/s/qtuXBVaoftamDHzYmHJdcHuWzBugfMa9ynbj2kb0CUkPU/J8aP4ffJzSQX7nav8/bH+xNzUcXJLWB/5K87W1h+0fTrMsAf8LPKcq71Tbo652LOkJwN+q826x3XJHuplK0qrAqrQw0Zvtv7avRjOXpMUsuUpdOz1MM8/7JXBGNVFXxMCStCdwMqVtB5bM9RYBVzP1PG9rHp8zqCrj+bZv7uRjiqmT9ACwYmOX8h13V2A3yveAFYFv2j6wNzUcXJJeDvyIKt8CNnMLHawk/Rvwzaq8P9redpxzH6a8PufZzgq4ERERETE0MmghIiKmRNL9lFldoVz8WghsRrn4dQSwDvAT26/oTQ0HVzXzzd9pNvp/2fbB0yxrY8pysLOrQ/9te9TVUSQ9g9JRwcBVtreZTsyZqlpdZCdgW8rKFq00cjoXjtujw42cdTdSLjJ/zfZEM11H9D1JBwDPqHaPtX1DD6sTXSZpLs3BqQLm255TdeL5H+ANwG3AFrYf6FE1B1bV0boxw/HVlAEgE82eO1o5bwG+XO0aeIft48Y4tzEo1sBFtp8/jarPWJJ2oaww1648L50J26CW52mic6dgtLzRwC+Ao2z/vI2xIrpO0kHAkZTrDfXXTyvfmepliDL5wr62L2ihzOgQSdcAT6kd+udgRklvAL4KPAY83Xa7B4cNPUmXAs+kvBbuB15j+xdTLGMp4BuUgalQXlv/z/b3xzj/tZTV8sYdxBqPJ2lt4O2UPO8ZNDv7TpdtZyb/NuhQnldX/9x7gLJS0MdsL+hQvIiOk7Qt5fr0Vjx+ojGYer43MscD+CnwRtt3TbOa0UGSLgJ2qB36k+1nVLdtSZmQZHXKhHPJ1aegmgzkbpqryn3U9iemWdbqlIFzT6S8vr5o+z/GOPcplIF2Bq61/fTpxIyIiIiI6EcZtBAREVMi6SfAS2he6Pyd7R2r29alzAa2EbCX7R/0ppaDS9JJwP7VroFvAe+xfd8UyngO8D1gfZoz4TzL9uVjnP9+yvKxBr5je//RzoslSVoWOBx4G2X26ZaLpDRyZqnXNhgxaGG8RpqxbhurcXSsMu+nzEp50hSrGhHRNyQdAdQHOR5XH0BZy1MOs/2xLldv4El6N3A0zYb/2yl/75MmM0ubpDmUQcJvaxyirKKwue17xrjPV4A3VTGPsf2elh7EDCFpE+BU4Nkjb5pGcf+c2Tx5XnuM6Mw22mtnvOdpvFxw5Hn18r8JHJzZeGOQSdoA+Ajls3yF6vBkvgPVjXb+fMpguk/ant9qPaMzJO0DfJvm4Lu32z6+dvuhwH9TBuS/uQdVHGiSXgb8mObnxyLgJODztv84wX0FvJhybW6r2k3XUwaRLBzjfj8Edq9iHmb7460+jplA0iuBEymDUaE9neOT57VJlec1TDZvq5vs51o917sWeLntv0yqkhF9qBr4ti/wDspqPXVT6Qwy8pr3LymDuH/WWg2jkyQ9EzibMqncfcArbf+6dnsjT/mq7bf0pJIDTNJZQGOiPgOHAZ+wvWgKZWwEnEVZyaRRzgtsXzjG+QcDX6jOO932a6dZ/YiIiIiIvpNBCxERMSVVB56zgKcDN1Eufl1Tu/25lIELn7X9vt7UcnBJeiKloWQlmg0n91E6yZwFXGb7oVHutwpltv83AHvRbIQ28D3b+44T81rKbHsG3mL7a216OENL0jLAecC/MPoMlZPpKDXaOWnkbJNxGjkbf/dFlBlyHq3dtiowh8c/p/dROuKIstLMKjRn1mmc13i9/qft/275AURE9EDVyP1uYBfg98CnbT9Wu3114EzgSNs/6kUdB5mkpYFLgW1Y8rPjHkrj8WXAnymfOw9ROpSuBjyNknPsXh2rf0692/YXxoi3KjCX8rll4CW2z23/IxsuktYCrgDWpfkcjTbIcaIBjiPPSZ7XJpJ+Rfk7Lw88lyWfk4cor7M7eHyetz7l9bds7T63ABfSzPNmA1vQXHWm/lo9w/be7X9EEd0laTbwauBFwI7AhtMoZi5wEaVz1Fm2H25bBaNjJG0H7Ey5tnThiNuWoQxqOcH23F7Ub9BJOpGySsLIgW9/Yfw8bwdKJ8N63rAIeKnt88aI9STgOprX/8acrCSaqk6d/0tzZYVW8rz6ecnz2kTSR6vNJwGvo/kcPUbJ2S5i7DxvJ0pu2Hj93QJ8irJSdD3Pe05Vft01wI6272/3Y4rotqpzdCPP2xrYnNLeNJGHgRsoM8FfBPzU9t86Vc9oL0mzgKcCN442kFjSrlNdBSoKSVtQrhMtQ/Mz5kbKoIKzbP91gvu+gTKgaFbt/ufZfvE497sU2K469z9sf7EtDyYiIiIiog9k0EJEREyLpNVszxvjtifZvrHbdRoWkvagLO/eWFZ85Ayit/P4Rs71aDaU1TtX3QTsMNayvVWs06vzFwLr2767jQ9nKEn6L8psKiMbM+cBj1CeD1OWGa83Gq9BaSRYvnbfRcA/L/7b3qRjFZ9hqk4XR1MuCENp0PwGcDLwW9uLR7nPSpQOAwdSBgA1ZrH+N9tn187bjNIQuj9lRsTGa24x8ArbP+3Mo4qIiEFWdYj/JaWDWr2T1GQuztRzQjHBDHmSDgc+XO3eDmw4lVngZipJXwX+nSU/26+mdN54DHhtddvtwAm1u64BPBN4Hs3naiHwfWABgO03duVBzACSNqT8bZ9VHboW+Dhwpu0F49xvReDfKB1z16U8T5+x/aER561P6Sh3KOX7VuM5fa/tz7f1wUT0WDWIYTNKh881KQO5l6dck1hIeQ+7H/g7cCtww1jXgyJmsmoA8EmUma5HXi8aL9ern9P4vDnQ9jfHiXVyFQfgStvbTrPaM4qkn1E68jb+1jcCP6HkeQaOodkRsb7iSCPP2w/YmGae95nqXGyf2I3HMBNI+lfKKsKzKc/TN4CP2r51EvfdAvg88ELK83QhsPvISYCqiZc+QxkcTnXul2y/s00PI6KvVPneuHle8ruIsY1Y+WBkfncvow9O3QJYvVFE7b5/B543Vju6pOcDv6jON7BJBhVHRERExDDJoIWIiIg+JOnlwNeBtZh4lq+6+rnXAS+zfcs4ca4Ctqx2v2d7n2lVeAapZkn+G+W5odr+EHC27XmSlqdcmBRlVpsnj7j/ypRGzo8CT6A8Z1+0/R9deggzhqTTKTOIQpkh6rW2b5jC/f8F+C6lQ9tC4FWjDUaQtBtlIMRalOc9HQYiImJMkuYAnwUO4PEDEcZSP2cBcARlKfoxL+pI+h6lkRTKUvJfnn6tZ4Zq8OLdlE4cAD8H3tqYNU+SKLNPLgf8zfbjZieX9BTgf2h2iPs98GLb93X8AcwQVb79e8rgHyir0r19vMEKo5SxBmUlux0oz9N/2f7UKOetDfwIeHZ16E5gY9uPjjw3IiICQNLrgSOBtatDo83OP9aM/ddTVkG9YIIYh9LMVy4auXJGPF71mX577dAnbH90xDn3UWbt/7vttRlB0rLA+ygDJZeiTF6yq+0/dqreM021CvEfKd9jFlMG8Ex5QIikYyiTmBg4baxr3pJOoExcAvAPSsfQO6dT94iIGG6S3kIZGLcCY6/WtMRdRtwmyjWnl4y3Qpak31AmxICy4snLW6h2RERERETfyaCFiIiIPiVpNUoj2OspM0s1jHfxC+Aeyowfn56o407VYLdstXvfyFmn4vGqpeR/T3Mlha1GznIi6SbKzGuP2p41RjmrA2dSli435fn68GjnxtRJeiPwNcrf9k/AztNZ4l3SVsDvKEv33g1sZvuBUc57NvBryuvJwItsnz/9RxAREcOuyineCuxNme1wIvdRBskdY/v6ztVs5hoxm91c4Km2/zHinD9ROssvAmbZXjhGWUcD767K+rHtV3Ws4jOMpCOA/6T8bX9ge69pljObkic+kTIY6Cm2/zLKeWtRBoSvVsXcz/Z3p1n9iIiYASStAOxBWQ1hB5qz7I5mPuV6wjeAs8bKLaI1kl5BGbBo4DLb249yzqXAdtU5K9t+ZIyy9qSsBCDgGmDbPG/tIenblMleDBxm++MtlPU7YPuqrOfZvmSUc5amrKr25Oq8g2wfP92YEREx3CQ9Cfgc8DLKAEaY3IpaC4FvA++zfc8EMban2W57s+3bpl/jiIiIiIj+k0ELERERfa6aSfTllEbOZ1I6w88GVqF0rrmP0qnq98AFwA+nMstoTI2kAyirYBg40fa/j3JOfbn59W3fPvKc6ryVgd9SVrtYCGxv+4rO1HxmkXQ1ZfndxZS/6x9aKOuTwAcpz+dbbX91jPO+BryRDEKJiIgpqDrKbMHEed6V6QzVWZLeChxH+Sz/vO33jnLOD4BXVedsZvvmcco7g7LqkykrPp3eiXrPJLVVz9amrG62WSuz4Up6O3As5Tn6kO3PjHHex4CPVOd9yfY7pxszIiJmHkkbMnae93/jrZ4V7SHpYMokLwYOt/2xUc45BdinOufptq8dp7zDgP9ighwiJq+6TnonZQbrxupW077GLelVwA8oz9HRtt83xnn17wAn2/636caMiJguSasAa1AmtVie0ml9Ic2c4Z7pTMoUnSFpPUrO0Gi33YjHr6B6J81225Oykk9ERERERLFMrysQERER47P9KHBG9RO9t0Zte6wlXK+nDFqA0ig96qAF2w9K+nfKTP5LAx+jdGyLFlSrI2xBaWy8oJUBC5UTKYMWAF4BjDpoATiJMmgBmsv3RkREjMv2Isps73/qdV1iiRUv/m+Mc+qrXGwMjDloATgYeDGl49WhQAYttG5HyoCFxgoWrTb6nw58sdp+GTBWh8OzKIMWoMzYGxHRcZI2pbzvbQ1sDmzABJ3ZgL9SPquuBC4cbQWZ6D7bf6U8N9E7q9a2x3ou6vnfxsCYgxaATwJvoeQlb2bsHCIm718oK50aOL0Nk/L8nLI62lLAruOcd25te5sWY0b0heQQ/U3S+pT2o8ZztBlLfk6Ndb8HqT1HwDm27+hgVWMM1eoHR1c/wD8HnvxzcGomHomIiIiIGF0GLURERERMzXK17bFmthnZme23YxVm+1JJFwDPB14saXZmzGnZlrXtc8c8a5Js/7lqEFgJeNo4p15MWdlBwIatxo2pk7QWsAkwz/b1E50fERExQn2W43+Mcc7IzmxjF2bfLulHwGuB7SVtWHVajOnbpLZ9cauF2b5L0jxgdcZ/Pq8EHqNcS12n1bgREWOpZm19G2Xm1ieNdsqI/eWqn5WB9Skd3+rlXQd8Czje9n3trm/EABkrt6sbeT1vTLb/Ien7wEHAJpK2tT3W5CYxOevXtq9ptTDbj0j6OyV3W2+c826S9AhloPEaY50X0e+SQ/Q/SXsD76TMzl9/PkY+N2NZBdi2+jkAWCzpPOBI279oY1VjGmw/ADzQ63pERERERPS7pXpdgYiIOklPl/R9SVdVv7fqdZ0iIka4r7Y9e4xzJt2ZrfLz6vdywE5Tr1KMUG+IbNeSu/dSGg/G7KRm+xHK/4eA1doUNyZB0qqSvgvcQRkkdJ2kuyUdKSkNzhERMVn31rbXHOOceme2TSdR5u9q28+eco1ipHVr2+0a6PtQ9XutsU6wvRiYR/K8npC0vKS9JL1f0ptzrSiGkaQVJR0N3AR8mDLjrpheh7bGuaKsQvhJ4BZJB7WpuhGDaF5te+0xzqnneU+ZRJlX17a3mHKNYqT69ZtFbSpzcfV7ovytkefNaVPcmKSqTfCLkn4i6WRJ76wmJYlJSg7R/6r/898D36GsrlDvozOV56Z+viird78IOFfS9ySt1HJlIyIiIiIiOiwrLURE35D0RMpylrMpF1u2BHaVtJXtv/W0chERTXfVtseapaveyPmcSZRZX8J3gynXKEaqz5K8epvKbJQzUSPCA9W5q7QpbkzOCcDeI46tARwCvF7SfpltKiIiJuG22vbGY5xTz/N2nkSZ99W2k+e17qHa9hNbLUzSUjQ7Lk40A/Mj1e9ZrcaNyasGKPyQESuZSfoDcKjtC3pSsYg2krQpcDbwZMp3Tlc/9U5p84FbKZ9Vj1Des/5BmfxgBcp709qU10r9e3Dj+/GqwBckbQ0cVA3GiphJbqxtj7WKZn0Skl0nUeajte2W85JYYgDxaLPET0nVeXdtyvvgfROc3nhPXLrVuDF5kvYCTmHJv/s+wKclfQY4wna7BrAMpeQQ/U/SK4FTKX/rxnNEtb2IsrLMzUz+OdoY2ApYth4GeA2wqaSX2a63YUVERERERPSVDFqIiH7ySspMNvWLarOBVwBf7l21IiKWcEVte5cxzrmZ0qFqJWAXSUtNcDF/Tm07M7e2rr66wr8An22lsKpBZmXKZ9NEKzc0Bis8Ou5Z0W4vZ8kGHwO/Ap5FadD5iaQX2r6oN9WLiIgB8fva9r+OdoLt2yTdTZmV/zmSVrU9f5wy64Ncl2tDHWe6+mDflwGfaLG8XYHlKbnDHROc2+jA83CLMWNqjgc2GuX4dsAvJH3Udqv/BxE9I2k9yiQu67Hkd5prgdMoK/ZcbHve6CWMWubKwHMpKznuR5lxuXGt9c3AQuAdbXoIEYPiD5SO6QJeONoJtu+TdBNlNa0tJW1q+6ZxynxybTudeFtXn7hqL0kftO0xz57Yayid4Q3cPsG5jVXWHhr3rGi3TzN6X4VZwEeB50l6le0F3a3WYEgO0f8kPQ/4HuVaQOM5uo+y4sJpwKW2p/y+I2kWZbKs11EG+qxIeY62Bb4LvKDVukdERERERHTKUhOfEhHRNWNdeHysq7WIiBiH7RspM38JeJakdUY5ZzFwWbW7KuWC/njqs/Te3456znB/qn4LeImkLVos77217f8b6yRJq1AGnZg8j902svHtAdu7UWa0PpHSMHRq9RxFRESMqpqN8CZKDvHkauDiaH5b/V4W+NgExe5e276npQoGlI43Dc+pZq2cFkkCDq8d+sM45z6BMjjV5Hnstm1oTm5B9ftjlA5aAj4uKR2nYpB9g2ZnQ1E+Y55ne0vbH7P9s6l0NgSw/aDt86r7P5kyUcyttRhvlzTq4LyIYVV1Cv095TWwtqSXjXHqhbXtY8YqT9IyLLni40SDH2NiF9JsI9oY+PB0C5K0OnDEiLLHOvcplJnMJzO4IdprHZbM8xYDz6fk6A8DLwKO60nNBkNyiD5WfU40rkubMuDj08ATbR9s+1fTGbAAYPuR6v5vAjYBftwIC+ws6aDWH0FERERERERnZNBCRPSTH1AuCovm0qV3VMcjIvrJmdXvpYH/GOOcH1a/BRwhadRl4iVty5Kd2f7cjgrOZLb/CNxCaQxYDviepHWnU5aktwCvrx360TinP5fm59cN04kX0/YtlswfTgawPd/2G6v99VhyAEpERMRoTqttv2+CcwS8Q9Juo50k6XWU/KDhqtarN7PZvpXm4GABJ0radarlSFoK+CZldsqGM8e5y7/UtpOvd9cttW0Dt9s+zPbzgTdSOrf9t6RNe1C3iJZI2oUy43ujs+Z/297R9sXtjGP7x8AzKJ9DjU6H/9XOGBED4ju17Q+Occ4pte2XSvpoNdBxpKMpHUUbLhvlnJgC2w8A59C8vvPx6u+/9FTKkbQR8Augfi329HHuUu+Afc1UYkXLrqhtG7ja9oW2P0r5HnUvcED1eRk1ySEGwmtprlSxENjb9ods/6OdQWzfbfuVwKnVIZHVMCIiIiIioo+ptZU1IyLaq1rO9H3A5sD1wFG2/zb+vSIiukvSC4DzKRecHwCeavuOEeesA9wMLE+5UHwr8H7gh7YfrjpKvRz4MrBudc4jwDq2H+zWYxlWkt5NaUBuNKbcDvwncNJklpaXNIcyI9vbGocoSzdvbnvU2XUlfQV4UxXzGNvvaelBxKRVr6d3A7tQZk78tO3HarevTumIeKTt8QaeRPQdSTtPfFbn2B5zRsqIYSTpqcDV1e5i4Lm2LxtxzizK99UnUHKExyizXJ4JzAXmAHtSOgosU51zF2VGxUUdfxBDrpoZ+cc087xFwEnA56vBq+PdV8CLKTNcblW76Xrg6bYXjnG/H1IGGhs4zPbHW30cMTmS9gG+TXPynbfbPr52+6HAfwNfsz3RCnczSnKI/ifpBOBAynvLGbb3nuAurcbbiDLwajnKZ9xGue4aM4mktSjX6mZVh15v+5RRzrsUeCYlzzDldfNDmnneHsC2tbtca/vpnav5zFGtlnoFzRzawI3AF4CzbP91gvu+gZKDz6rd/zzbLx7nfpcC21Xn/oftL7blwcSEJD0TOJuy4sJ9wCtt/7p2eyPv/6rtt/Skkn0qOUT/k3Q65fPCwGdsf6jD8WYBfwXWqGJuYzsTJ0RERERERN/JoIWIiCEg6aYehrftJ/UwfkRPSLoEeFa1e/poDQOSDqPMPNToUGXKRf37gJUpF/kbs7UZ+KbtAztb85mhmoXtUmAblvz730Np7LqM0tByH/AQZRn41YCnUWbS3b06Vn9+3m37C2PEW5XSeL1Kde5LbJ/b/kcWETONpMU0Z87rNttepkexI3pG0veAvardK4FnjRxsUHWkPoUl84zHFVX9NvBR25/oTI1nHkknUlbDGvn3/wvj53k7UDpF1WdMXgS81PZ5Y8R6EnAdzU7zz7J9eRsfTkxA0nbAzsBlIzvCS1oG+Ahwgu25vahfv0oO0f8kXQ1sQXmetp1o4FWbYp4M7FvFfI3tMzsdM6KfSPoMzdW07gaebPv+Eec8E7iIx18X+ucptW0D+9uur+IQLZB0MGWQQiPPg+bf/15Gz/O2AFZvFFG779+B59m+cYxYz6esyuDqZ5PkE91VdbR+KnCj7fmj3L6r7V90v2b9LTlE/5N0C7Ah5e+1vu3buxDzGMrALQP72f5up2NGRERERERMVQYtREQMgVpD9GhLVXeabU9pieaIYSBpR8qs+lBef4favnfEOUtTZot6EWO/RuuNaE+3fVfHKj3DVDPo/ZLSQW20hs5x7147T0wwo5ekw4EPV7u3AxtmJuWIaIfkeRHdJ2kDYNdq18APbD8wynkfo3SWrucM1O7XOHYJ8C/1VYCiNdUqSyfR7DQDk8v16uc08r0DbX9znFiNzjkAV9redqxzI/pJcoj+J+lBYEXgYdsrdynmIcBRlP+Nd9k+thtxI/qFpOUpK55Cea8adeZ+SS8FTgVWZclcY+TghS/bPqhD1Z2xJL0F+DxlUMLIz7KJBgs39u+mTCoy5mBTSb8Bnlft/tT2y1uodkTXJIfof5IeoazCfa/tNbsU8yDgizTbqz7XjbgRERERERFTkdmOIiKGy2idZSKiA2z/BvjNBOcskvRK4HPAWxm9AU2UpelflQEL7WX7bkk7AZ8FDmgcrn6P9z7ZmF1NwALgCGCimZGfApxfbZ+eAQsR0QHJ8yK6pJpd9cRJnPexaobL/wY2GnFz47V6KvC2DFhoL9uLgf0l/Qw4Eli7cdOIU0d2LmzkeAKuB95i+4IJwl0OXFNtX9RKvSN6JDlE/1qO8vzcP9GJbVSfxXqlLsaN6Au2H6WszDTReT+tVlz4BPAaYNnqpsZ76W3Ax22f0JGKznC2vyLpfMo11Zcx8eDUeo63EPg28D7b90wQ6j00n9ubW6p0RHclh4iIiIiIiIiBlEELERHDpdEh4yJgcY/rEhGA7QXAwdXSvP8G7ACsAzwG3AL8GPhW1WgabWb7PuBAScdSBo7sDcyZ4G6iLDN/MnCM7esnEee1LVU0ok9UM1cfCuxZHToD+OxUBuJUZby3KkPAD4CjMphn2m4DnkAzz/twdSwi+oDt0yT9AHgBj8/zzrb9fz2s3tCzfZKk04A9KKsh7ACsPuK0ekft+cCvgW8AZ9leOIkYR7WpuhHdlhyi/91LGXS1jqRZth/pQsz6ILs7uhAvYmDZvgnYT9KKwLOp5Xnjzd4f7WH7RuCVktYD9qHkec+kvI+NHIh3J/B74ALgJNt3TjLGJe2rcURXJYfof3cCGwKrSVrXdjf+Zk+pbd/ehXgRERERERFTJnu8FdMjIiZH0gbA1sDmwAbAGpROoctTZqpZSJmt+j7gHuCvlFkNr6xmsYwWSHobUF+K9aO2J5oVPCJixpG0NLAFpZFzY2A2sArNz6i5lEbOKyfTiS1i2Eg6EjiksUvp4Ha07fd1s4xokrQpZSWXDatDFwC7OV/mIyJGJWlDxs7z/i/vnzFTJIfof9Us4i+g5Mtvt/2VLsS8mvKd2MCuk1htJiKi70hahVqel2t4vVM9F+O2B9ru5moAM0JyiP4n6XTK4HoDn7b94Q7HW57ynXfNKuZ2tq/oZMyIiIiIiIjpyKCFiJg2SbtSZrh5MbB+C0X9FfgJZQac37WjbjORpIOBL1S7C4Hn2b6sh1WKiIiIASPpTmAtSuMWlEEHd9let5tlxJIkbQH8ltIpA+A9to/pYZWiD0haC9gEmDeZVYEiIrql6iy/I9Oc3AK40PZful3vYZQcor9Jei9wZLV7J7BjNbN7p+IdBHyx2p0HrJOOvv2n6nT4CmBTyvP0O9tX9bZWEREgaX3gRTTzvM2AVSdx1wep5XnAOV2adX5oJYfof5L2B06qdh8D9rR9dgfjfR04oNq92faTOhUrIiIiIiKiFRm0EBFTJumVwCcpM2rAkkvxTuVNZbT7/QZ4V2Z/mB5JxwFvrXYvt71dL+sTvSXppcDB1Bo5gW+moTMiIsYiaS6w3ojDt9neoJtlxONJejVwRrX7APAk23/vXY2iVyStCpwA7FU7fC/wTcrsfff0ol4RMbNJWg94G2Vyi9E6yGiUY3UjryddB3wLON72fS1XcAZLDtG/JK0G3EwZVCLK7Lj/bvv8DsR6K3AMZdCQgRNsv63dcaI1krYCfkhzhZSGPwCHZlbriOgFSXsD7wR2YMmcbqL8rq6e6y0GzgOOtP2L1ms48ySH6H+SlqF8p9mE8hwtoAw0+YTtR9sYZw5wHPBamivefsT2Ee2KEe0j6emU7831dtvv2L67pxWLiIiIiOiiDFqIiEmrZnn6KrBf4xDl4sdoFyYXAo8A/6h+lgNWAGZV2yPVy1lAubh2StsqP0NIWgH4I2WGGwNvsP3t3tYqeqFaeaMxe2LjtdpwImVw0INdr1hERPQ1SR+kDE6t+7DtT3WzjBidpFMonUENfM72oT2uUvSApO8Ce49yk4G7gf3S8SMiukXSisAngIMoHZlGm6BiMh3aRjvXlE72H7L9pRarOqMlh+hfkt4CfJnmtVEDPwO+BvzI9mMtlL008GrgXcBONF9f9wNPt/236dc8OkHS/wLPHeNmAx+1/YkuVmmoSBo5GKRVi4GHgAcy43gMo6pz7TeBbRuHmFp+N1K9HbBRzunAG20/NM1qzljJIfqfpJ2A84FlaD5H9wKnAt8HLrH9j2mUuyzwbGBf4HWUFU8az9G1wHbTKTc6S9JewCnA0iNu+gfwGeAI24u6XrGIiIiIiC7LoIWImJTqAsg5wC4sOVhhEWV1hN8BF1Nm9rh1vBnbqplBNwQ2pjTC7FT9LMWSF9febPvrnXlEw0vSiygXJg1cZ3vLHlcpekDSrTRnuR7ZkGDgCmBX2/d3uWpDoVpqt53+2chJmV3lWuDKXPyPiF6QtB+lYRLgzOkMJJW0L7BHtXuW7ZPbVL0ZrZrF+kZgecpnxhMzCHHmkfQgZTA4NL87/Qp4FmWWxQXAC21f1JMKDjhJN7W5yFHzPOAC27e2OVZEV0naFDgbeDJjd2KbD9wK3MbYk1usTblOtHrtfvWyTFlh5iDbizvxWIZdcoj+Juko4BCWvC4K8ChwOXAJ5ZrrXOB2mq+lRymDhVaoftYGNqBcc92++qnnDFDyhFfZPqeTjymmR9LDlNcpNP8XPg7sCuxc7f+H7S/2poaDTdJiprZS9FQ8TDPP+yVwRjqMxiCrVlw/lfL5MnICs0XANVTtgUwuz9sY2IryuQVLfuZdDrzM9l0dflhDJzlE/5O0J3AyzQn96s/TIuBqpv4cbc3j84XGihvPt31zJx9TTI+kGygrLIzGwM8pr7EF3atVRERERET3ZdBCREyKpM9TZtRoXPi4jzLq/0Tbd7Sh/A2r8t9FmWFAlI4d29i+sdXyZxpJ51AuKgLsZvsPvaxPdJ+k+4GVG7uU1U82A3YDjgDWAX5i+xW9qeFg63AjZ92NlNmsvmb7zi7Ei4iIPifpAOAZ1e6xtm/oYXWiByTNpTk4VcB823OqweH/A7yB0mlkC9sP9KiaA6uW501n5tCxjJY3GvgFcJTtn7cxVkRXVJ3gL6G8H9VfM9cCp1FNbmF73hTKXJnm5Bb70VxFstER5zjb72jXY5hpkkP0N0kHAUdSOgiONhP1tIqtlSHgDmBf2xe0UGZ0kKRrgKfUDt1ue/3qtjdQVkF+jDLLdbsHWg69DuV5dfXX6wPAl4CPpfNhDBpJz6MMvlmO5mtmHvAdSp536XRWRpA0C3gOZWb4fYAVq5sMXGj7Ba3XfuZJDtH/JG1LaefZirFXmJtSkbX7NbZ/Slm1JIN/+pSkB2i+74kyycWulHbbQ6rbvmn7wN7UMCIiIiKiOzJoISImJGkz4DqaFz5+Rbk41fYLH5KeQ5mlb7Xq0Gm292l3nIhhJ+knwEtoXuz8ne0dq9vWBf4X2AjYy/YPelPLwTVi0MJ4F5fHum2sxtGxyryfMpPeSVOsakRERAwZSUcA/1k7dJztg2u3nwTsDxxm+2Ndrt7AG9GZbbSLZuN1chsvFxx5Xr38bwIHZzbeGCTVZAkvpPn//FvgENsXtzHG7sCxwPo0XzMvtn1eu2JE9BNJGwAfoXyOr1Adnsy1hLrRzp8PfBn4pO35rdYzOkfSPsC3KSsSA7zd9vG12w8F/psyucWbe1DFgVbleQ2TzdvqJvt6rOd61wIvt/2XSVUyosckLUNZRaExeHQh8FnK98u2fV+RtBbwNWD36pCBd9r+UrtizCTJIfqfpKWAfYF3UAbv1E2lw87ItqNfUiZD+FlrNYxOk3QRsEPt0J9sP6O6bUtK/4vVgV0zQCgiIiIihlkGLUTEhCR9CvgA5eLHFcBOth/pYLwXAOdXu48A62TJ+oipkbQJcBbwdOAm4JW2r6nd/lzKwIXP2n5fb2o5uMZp5KwvkX03ZQnfhlWBObVzGve7j3LxX5TVMVahuUx247xGQ+d/2v7vlh9ARBdI2rmX8W1f2Mv4ERGdUjV0vxvYBfg98Gnbj9VuXx04EzjS9o96UcdBJulXlLxrecqM7/VBpQ8Bl1JmmRyZ560PbEPJ4xr3uQW4kGaeNxvYguZKGfU87wzbe7f/EUW0n6RdKJ1jGv/rR9r+YIdizaF03tiK8nq50PbzOxErol9Img28GngRsCOw4TSKmQtcRJkc5izbD7etgtFRkrYDdgYuG/m9tupM/BHgBNtze1G/QSbpo9XmkygzvTdysccoOdtFjJ3n7UTJDRu52y3Apygduut53nOq8uuuAXa0fX+7H1NEu0najzJ4qjFgYW/bP+xgvJMpHbkBrrP9tE7FmgmSQwwGSRvRfI62BjYHVprEXR8GbgCupDxHP7X9t07VM9pL0jMpr6t1KO2Cr7T969rtLwN+DHzV9lt6UsmIiIiIiC7IoIWImJCkS4BnUS5S7m77p12I+Qvg+VXMl2eGiIjpkbSa7Xlj3PYk2zd2u07DomooPpoyMw6UBs1vACcDv7W9eJT7rESZSeVAYC9KQ+d9wL/ZPrt23maUhtD9gRfTbERdDLyiG+/DEa0asSJJt9n2Mj2KHRERA07ShsD3Kd+DocyQ+3HgTNsLxrnfisC/UToTrkv5HPyM7Q+NOG99Ske5QymrDDY6v73X9ufb+mAiOkDSCZTvNF0ZcFN16vkzsBzlO9FG6ZwTM0nVAXEzSsfpNSkTIiwPLEPpULqAskLj34FbgRvGuhYUMdNJ+lfge5RBBqJcy/uo7Vsncd8tgM/TXGnoQkp7yUMjznsu8BngX6pDBr5k+51tehgRHSPpdGAPxvgu04F4s4C/AmtUMbexfVUnY84kySEGR/Vcjfsc5bkZfNV73lOBG0dbvUTSrrZ/0f2aRURERER0TwYtRMSEJM2jXMR/DJg1WkfcDsT8EPAJykXKt9r+aqdjRkRMRdWA8+pq90rgtbZvmML9/wX4LqVD20LgVaMNRpC0G2UgxFqUxtQrbW/bWu0jOq82aGEyy4+3m20v3YO4A0vSDpRGzIarbV/WprIPozSONhxt+0/tKDsiot0kLU9ZwaIxw+c3gbePN1hhlDLWoKx6tgPls/C/bH9qlPPWBn4EPLs6dCewse1HR54b0U8kXU2ZTdrAtrb/2IWYjVl4DbzG9pmdjhkREcNF0hOBP1IGjS4GDrR94jTKOYYyiYmB02zvM8Z5jUF+AP8ANrF953TqHtEtkm6hzM5vYH3bt3chZv01tZ/t73Y6ZkRERERERET0xlK9rkBEDISVKRcL7+rGgIXKHbXtNboUMyJiUiS9kTLjFMCfgBdMZcACgO2LKKsoPEKZNeebklYZ5bzzgVdQBjYAbF0NZIgYFKZ3Ky7EJEhai7I09Teqn2Np72CTiygrx7yh+vlKG8uOiGi3jwBbVts/sH3gVAYsANi+B3g58DfK++lHq5niR553F7A70JgtcW2ag2Ij+lnj//mRbgxYqNQHUz6xSzEjImK4fIYyYMHA4dMZsABg+13AJZQ8b29J249x6tuA/6u2lyd5XgyGdarf87oxYKFyXW17vS7FjIiIiIiIiIgeWKbXFYiIgfAgZaWFtSUt1aWBC+vWtu/tQryIiKk4tPpt4I22759OIbavkvQ/wAcpS//+P+BxK8vYvlTSt4E3Vod2Bc6fTsyILroNeAKlEd/Ah6tj0X8Oo+R6UFbW2tv279tVuO1zJR0IfKs69BxJb5huB5GIiE6RtDTN2XAfBg6eblm275f0ScpAsGWBfSgd5Uaed7ekL1AGSwDsRFmNK6KfLUfJ76b1PWia5te2V+pi3IiIGAKSVqZMQGLK6laPWwVrij4F/KDa3psyiGEJthdJ+hxwXHVoR+D4FuNGREREREREREQMrAxaiIjJuB54FuU940XAz7oQ8wW17b91IV5ExKRI2grYgtLIeYHtP7RY5ImUQQtQVlR43KCFykk0By08r8WYEd2wM2VwzYbV/guB3Wxn1YU+ImkWZRWExvNyjO2253q2vy3plcBe1aGDKe9/ERH9ZEfKagcGfmz7zhbLOx34YrX9MkYZtFA5i+aghbFm6o3oJ/dSXivrSJpl+5EuxKyvVnLHmGdFRHSZpE0pOcTWwObABpSVg+dQZtdflrJ65gLgPuAe4K+Ua+5XAhfa/ku36z0D/Qswi5LnnT7VlbRG8XNgEWVF+13HOe/c2vY2LcaM6IY7KdfyVpO0ru1u5F1PqW13a3WHiJ5K/jCYqtXSx32epjvJWURERETETJFBCxExGb+gDFoAOELSBZ1skJa0E7BbtfsY8OtOxYqImIYta9vnjnnWJNn+s6QHKbOFPm2cUy8GFlNmrd9wnPMi+oLtmyS9DPgtsAqwC/BO4JieVixGegWwcrV9F2XVhU55L/BySkeR7SRtafvqDsaLiJiqTWrbF7damO27JM0DVgc2HufUKynffZcB1mk1bkQXXE0ZtCDg9cBXuhBzz9p2OudERE9JWg94G2UlpSeNdsqI/eWqn5WB9SkdFOvlXUdZme542/e1u74BlL97wzWtFmb7EUl/p+Ru641z3k2SHgFWoHRyjOh3l9G89vxOysqpHSNpeWDf2qHrOhkvopeSPwwWSetTJnNsDC7ZDFh1Evd7kNrgEuCcLg0Ai4iIiIgYCEv1ugIRMRC+RukoC2U2oLMkrdmJQNUM5qdXuwZ+bnt+J2JFRExTvSGy1dl3G+6lXJAes5NaNVjsvuq81doUNyZJ0lqStpe0ea/rMkhsXwscQPm/FXB4p3KImLYdq98GTrX9QKcC2Z4LnFE79K+dihURMU3r1rbbNTPeQ9XvtcY6wfZiYB7J87pO0vKS9pL0fklvrq5JxMR+Uv0W8PFqltCOkXQQZbU7KN+JftPJeBERY5G0oqSjgZsoHXk3o/l995+nTaXI6mcL4JPALdV7XrRffcDAojaV2WgzmSh/a+R5c9oUNyZB0tMlfVHSTySdLOmdksbMyeOfGtdtBBwq6eUdjncc0LhWeIvtKzocL6Lrkj8MFkl7S7oQuAU4gdK+8UxgNs2//Xg/qwDbVvf7OjBX0k8ljbcyU0RERETEjJFBCxExIdvXA1+iecFkN+DPkg6VtHY7YkhaR9JhwCU0L1AaOKId5Uf7VBf7vy/pqup3OnXETOPa9uptKrNRzkQXphudiVdpU9yYgKRVJX0XuIOyYsB1ku6WdKSkzJA3CbbPBL5T7a4MfLB3tYlR1GfoOqsL8U6vbT9rzLMiInrjodr2E1stTNJSlNnoAf4xwemN1QxntRo3Jqf6Lnsd8F3gU8CXgSskXSppl55Wrv99HZhP+W60DvBLSbuNf5fpkfRW4HPVroHTbC/sRKyIiPFUA7QuA/6DMusxLHmNSJTrNtcA5wE/Ak4DTqJ81pwF/By4gmYndkaUsyrwBUlfrvKIaJ97a9ujzW49JZJWouR5pgyoG09jcMPSrcaNyZG0F/AH4O3Aiymzmn+e0rH3I5LyXIztu5SO1QaWBU6XdHi1IkLbSJoj6VTgDdUhU3LMiKGS/GFwVO3fv6e0ZezIkn2ppjKopH6+KJ//LwLOlfS9KoeIiIiIiJixZHvisyJixpO0HOViyU6UiyCqfi8Cfk3pyHkJcDMw1/a8ccpaCdgA2BjYvipzF2CZWrkC/sv2JzvziGI6JD0RuIrmbBJQGmW2sv23XtUropsk7Qd8m/Je9SPbr26xvK0pF5wN3Gx7s3HO/TtlgMNDtjNwoQuqAQt7j3KTgbuB/Wz/oru1GjzV0tc3AstTGmGeaPvB3tYqACTdAmxI+Z9euVrVpZPx5lA6ixi4yvY2nYwXETEVVeem71Heoy62vUOL5f0rpXOBgT/bfto4595PGZg63/acVuLG5Ej6X+C5Y9xs4KO2P9HFKg0USW+hDPSoXyP6GWW1zh/ZfqyFspcGXg28i3LNqHH94X7g6bn+EBHdVn2nvYSy+mbjfQ/gWkrHwt9Rcocxr4mPUubKlM+hnYD9KLMu199Tj7P9jnY9hpmumi3+R5S/7S3AZm6hgVTSvwHfrMr7o+1txzn3YWAFYJ7tTIDRBZJuAMZaCcqUHP1Vthd0r1aDQ9JOwPks2WZ3L3Aq8H3gEtsTDcoerdxlgWcD+wKvo3S0rr+fbjedciP6VfKHwSHplZT3uBVYsq8ClL4Q11D6QNwK3EaZeOIf1c9y1f1mUQY0bkjpA7EVZfAXLPkcXQ68zPZdHX5YERERERF9KYMWImLSJM2iXIjfm+bsDWLJGSEaHqP5hf1RypfyFWo/jyue5hf2xcD/Z/tTbax+tIGktwPH8vjn/2DbX+5ZxSK6qDbIAGABsK3ta1so70Tg9ZTX0jm2XzbGeavQnLntdtvrTzdmTJ6kB2nOeNx4z/sVZYb4VSj/Ay+0fVFPKjhAJB0APKPaPdb2DT2sTlQk3QvMAR6wPbtLMR+i5IO32d6gGzEjIiZD0vrAX2l+39nD9g+nWZaA/wWeU5V3qu3XjXHuE4C/VefdYrvl2X9jYlUHwsaMsY087+PArsDO1f5/2P5ib2rY/yQdBRzCkh0woFwHupza5BbA7Yx9nWhtlpzcYnuWzMGh5N2vsn1OJx9TRMRoJJ0DvJDm+91vgUNsX9zGGLtTrruuT/M99cW2z2tXjJmsuq52N83Og9MenChpdeBKyspcBr5o+z/GOPcplM6pBq61/fTpxIypkfQAsGJjl9LmtCtlFfFDqtu+afvA3tSw/0naEziZ5szw9VxvEXA1U8/ztubx+beqMp5v++ZOPqaIbkv+MBgkPQ/4JeX9rvFczaOsuHAacKnth8YuYcxyZ1GuCb2OsuJP43PJwIW2X9B67SMiIiIiBk8GLUTElFWzT34CeHJ1qN6BfapG3vcS4N22fzf9GkanSDoQOIHHD1p4i+2v9axiEV0m6SZgI8pr4GpKp/U7plFOY3ZSKK+ld9g+boxzXwicU513ke3nT6PqMUWS5lJmQoLyfM+3PUfSqsD/UJYwvw3YwvYDPapmxLRJWkBZonqu7Y27FPMWyoxTWTUmIvqOpEuBZ1I+9+8HXjPVVZUkLQV8gzIwFUr+9v9sf3+M819LaQwfdxBrtJeka4Cn1A79c2CwpDcAX6VMyPB02zf1oIoDQdJBwJGUQQb12ShbuehcL0PAHcC+ti9oocyIiGmRtAulI1vjfe1I2x/sUKw5lIkStqK8/12Y6z/tI+ks4BXVroHDgE/YXjSFMjYCzqJ0vm6U8wLbF45x/sHAF6rzTrf92mlWP6ZA0kVAfdW0P9l+RnXblpTX2erArskvxiZpW8pEZlsxejvgVPO9kTkewE+BN2bG8Rg2yR8Gg6RlKKsoNFasWAh8FjisnSu/SFqLsirh7tUhA++0/aV2xYiIiIiIGBQZtBAR0ybpxZSZAV4EPKGFom4DzgZOsv3rdtQtOqOaReoqlny+bwe2sn1vb2oV0X2S3g0cTbOB5XbgPynvYxMmV9VF5COAtzUOUVZR2Nz2PWPc5yvAm6qYx9h+T0sPIiZF0hGU57bhONsH124/CdifchH7Y12uXkTLqlUPZgEP2l61SzHvAVYDFtpebqLzIwaBpJ17GX+sTlIxdZJeBvyYZp63CDgJ+LztP05wXwEvBj5N6SzQcD2l4/vCMe73Q0rDtSk5xcdbfRwxMUn7AN8GlqoOvd328bXbDwX+G/ia7Tf3oIoDQ9IGwEcoeXFjdc3696LJTHIx2vnzKYO8P2l7fqv1jOg3yR8Gg6QTgAMp71Nn2N67w/E2Av5Mme13MbCR7b91MuZMIWkLyuqpy9CcjOdGyqCCs2z/dYL7vgF4B+U7dOP+59l+8Tj3uxTYjqzg1FWSnklpc1qHcs31lfW2p1rO/1Xbb+lJJQdENSB7X8r//nNG3DyVTgYjBzv8EjjK9s9aq+HMlByi/yV/GAyS9qNcF2gMWNh7uituTjLeyZT3VIDrbD+tU7EiIiIiIvpVBi1ERFtI2pgyu9DmlCUo1wTmUJZ6XYbyRX8BZabKvwO3UjpuXJklXweLpPWA91Ge6+spF5Zz4WsSqtn5e8W2n9TD+ENF0tLApcA2NDu0GbiH0uB1GeUC8X3AQ5SOO6sBTwP+hdIpbQWWnF3q3ba/MEa8VSnLZK9SnfsS2+e2/5HFSFXD3LuBXYDfA5+2/Vjt9tWBMykzJf2oF3WMaIWkWymriRiYbfvBDsdbmpITCrjf9mqdjBfRLZIW09qs4q2w7WV6FHsoSTqRskpCPc8D+Avj53k7UDpG1TvkLAJeavu8MWI9CbiOZsf5Z9m+vI0PJ8YhaTtgZ+CykR1vqhkXPwKcYHtuL+o3aCTNBl5NmdxiR8rKSlM1F7iI0tHwLNsPt62CEX0m+cNgkHQ1sAXludp2okGMbYrZ6NBmyqpPZ3Y65kwxYuWDkasD3cvoed4WlFn5oZkbitLO8TzbN44R6/nAL6rzDWySnKJ7JM0CngrcONrgR0m7TnVFtZmu6hTdyPMa7YErTeKuDwM3AFdS8ryfpk2pNckh+l/yh8Eg6XRgD8rf7DO2P9TheLOAvwJrVDG3sX1VJ2NGRERERPSbDFqIiIjoktqF5MnMMtlutr10D+IOrWo5119SOqiN1tA57t1r54kJZvWSdDjw4Wr3dmDDqSxdHxExFkkXAjtR3pNeZfvHHY63FaWR2pTZpLbsZLyIbkmeN1yqQYsn0Wzsh8nlevVzGvnegba/OU6s+ix7V9redprVjug71SCGzZj85BY32J7Xk8pG9EDyh8Eg6UFgReBh2yt3KeYhwFGU/4932T62G3FnCklvAT5PGZQw8jU4Wq43Mg8UcDdlUpExB5tK+g3wvGr3p7Zf3kK1I/pSle+Nm+clv2u/5BD9L/nDYJB0C2WwvYH1bd/ehZjHUFavMbCf7e92OmZERERERD/JKPiIiIjuG9nxKQaQ7bsl7QR8Fjigcbj6Pd5z25hdTZTGmyOAT0wQ7inA+dX26RmwEBFtdCll0AKUVWA6OmgBeGlt+5oOx4roheR5Q8D2YmB/ST8DjgTWbtw04lSNONbI8URZle4tti+YINzlNN8PL2ql3hH9xvb9lNVJLut1XSL6XPKH/rYc5Tm6v4sx67PCT2YW85gC21+RdD7wOeBlTDw4tZ7jLQS+DbzP9j0ThHoPsGy1ndWmYyhV+V433x9jSckh+lfyh8GwTvV7XjcGLFSuq22v16WYERERERF9I4MWIiIiuq/RuekiYHGP6xItsH0fcKCkY4G3AntTZpUajyjLzJ8MHGP7+knEeW1LFY2IGNt5lI4UonTQ/ZjtOzoYb5/adjrnTkM1A/yhwJ7VoTOAz05lQFtVxnurMgT8ADgqg+JachvwBJp53oerYzHAbJ8k6TRgD8pqCDsAq484rd45ZD7wa+AbwFm2F04ixlFtqm5ExLiSQ/Sl5A+D4V7KAMZ1JM2y/UgXYm5U2+7k97MZy/aNwCslrUf5nroD8EzK335k5987gd8DFwAn2b5zkjEuaV+NIyKWkByi/yV/iIiIiIiIGEUGLURERHTPQcCxNGe/Odf2RDPsxwCw/QfgrZIOAragNHJuDMwGVqGsqHAfMJfSyHnlZDqxRUR0wbnA3cCalCXLPwG8qROBJO0LbFPtmtLJLabuM8Ah1baAZwNrAe9rsYw1p1hGLGlnyqpIG1b7LwR2sz3WbK0xIGz/Azi1+kHShoyd5/1fnvOI6GPJIfpP8ofBcDWl06GA1wNf6ULMPWvbf+lCvBnL9m3A0dUPAJJWoZbn5Rpeb1TPwxqUCWKWp6xasZBm/n1PNct/xEyUHKL/JX8YDHdSXkerSVq3w5P5NDyltt2t1R0iIiIiIvqG8t01ImJmkLQBsDWwObABE1zwB/4KXE/pXD23+zUeTpIOBr5Q7S4Enmf7sh5WKSIiZjhJ76bZQcPAQbaPb3OMDYHfUmaBM2UG8j3Hv1eMRtKdlA6GjS/zAu6yvW43y4jHk7QF5f98lerQe2wf08MqRQwdSZsCOzLN77bAhbbTeSNmpOQQ/Sn5Q/+T9F7gyGr3TmBH2zd1MN5BwBer3XnAOuk0H8NO0vrAi2jmeZsBq07irg9Sy/OAc7rU4XTGSj7eP5JD9LfkD4NB0umU1TUNfNr2hzscb3nKpBdrVjG3s31FJ2NGRERERPSbDFqIiBhiknalLG/9YmD9For6K/ATyvLXv2tH3WYySccBb612L7e9XS/rExERM5uk5SiNx+tTOp4tpAxc+Gqbyl8XuIDS6UCUhustbd/YjvJnGklzgfVGHL7N9gbdLCNGJ+nVwBnV7gPAk2z/vXc1ihh8ktYD3kb5bvuk0U6ZoIiRFz+vA74FHG/7vpYrGDEgkkP0r+QP/U3SasDNlE6honQ0+3fb53cg1luBYyidfg2cYPtt7Y4T0S8k7Q28E9iBJXO6ifK7unqutxg4DzjS9i9ar2FA8vF+lhyifyV/GAyS9gdOqnYfA/a0fXYH430dOKDavdn2aO+pERERERFDbaleVyAiItpP0isl/Qk4FziQMtuNmNrFfmr32YhyUfo3ki6UtE0bqzsTvQe4odreRtLrelmZiIiY2WwvAN5Madw3sAxwvKRTJa3VStmS9gWuojlgwcDnM2ChJcfSzNEaP1/qQRkxCttnAt+pdlcGPti72kQMNkkrSjoauAn4MM3Pkul2aGvcdwvgk8At1WyUETNFcog+lfyhv9meB7yf5veZDYCfSzpb0p6Slm2lfElLS3qNpAsor6dGefOBw1spO6JfSXq6pN9T3vt2ZMn26um0YTR+L01ZseFcSd+TtFLLlZ3Bko/3v+QQ/Sv5w8D4LuU9zpS/4emSDq9WRGgbSXMknQq8oTpk4OvtjBERERERMSiy0kJExBCpLqJ8FdivcYhy4WO0C8cLgUeAf1Q/ywErALOq7ZHq5SygzAhyStsqP8NIehHwM8rf9TrbW/a4ShERMcNJejulI1rjM9/Ao8CJlNnvrphkOatRZt97E7BNrSyAHwF7OF9EWyJpP+DV1e6Z08nJqgEle1S7Z9k+uU3Vm/GqWShvBJanzHT4RNsP9rZWEYNF0qbA2cCTWfJzpP7ddj5wK3AbY3+3XRvYEFi9dr96WQZOoKwwtLgTjyWinySH6F/JH/qfpKOAQ1jy+xKU70yXA5dQZlSeC9xO87PpUUonuBWqn7UpHRc3BravfmY1wlS/FwCvsn1OJx9TRC9IeiVwKuX1MLL9YhFwDeW1NNk8b2NgK5odduuv0cuBl9m+q8MPa+gkHx8cySH6W/KH/idpJ+B8ykQ+jefoXspn1feBS2z/YxrlLgs8G9gXeB2wKs3n6lpgu+mUGxEREREx6DJoISJiSFQXP84BdmHJi/2LgN8AvwMuprrgP94SsZJWpXnB/7nATtXPUix5Ye3NtjMTxDRJOodyYRFgN9t/6GV9IiIiJH0AOIIlZypsfGmcB1wIXA/cQ2m8WZrS4DIb2BTYDngSS86818gdLgBeYvvRjj+QiB6TdADwjGr3WNs3jHN6RNRUnW4uAdZjyU5s1wKnUX23rWaunGyZK9P8brsfZZbY+nfb42y/o12PISJiOpI/9L9qRvAjKZ0E659RrTS0jfzedAewr+0LWigzoi9Jeh7wS0qn9sb//DzKTPGnAZfafmga5c4CnkPpFLoPsGJ1k4ELbb+g9drPHMnHB09yiP6W/KH/SdoTOJnmpH71a+KLgKuZ+uCSrSmDierlqSrj+bZv7uRjioiIiIjoVxm0EBExJCR9HngXzYse9wGfAU60fUcbyt+wKv9dlA6KAh4CtrF9Y6vlR0RERH+QtCtwCqWRZeRMehN9gazPuFcfQHkEcLjtRW2sakREDKFqcPcLaX6O/BY4xPbFbYyxO2V1ofVpdh54se3z2hUjIiKGk6QNgI8A+1M6p8GS35NGW/F2pNHOnw98Gfik7fmt1jOi30hahrKKQqOz+kLgs8Bh7ZxpWtJawNeA3atDBt5p+0vtijHsko9HtF/yh/4naVvgm5TVe0ZbXWaqHatGDiwB+CnwxqwAFBEREREzWQYtREQMAUmbAdfRvOjxK8qMGm2/6CHpOZRlgVerDp1me592x4mIiIjekbQG8F7gIMpKCjB+Q9rIL5aNBuefUDogXNqJekZExHCRtAtl9t3G58qRtj/YoVhzKN+dt6J8bl1o+/mdiBUREcNH0mzg1cCLgB0pq9ZO1VzgIsq11rNsP9y2Ckb0GUn7Ad+mOWBhb9s/7GC8k4F9q93rbD+tU7GGSfLxiM5K/tDfJC1F+ex4B2UFn7qpdKwaOdjhl8BRtn/WWg0jIiIiIgZfBi1ERAwBSZ8CPkC58HEFsJPtRzoY7wXA+dXuI8A6th/sVLyIiDpJO/cyvu0Lexk/opuqhrQ3AXsA2wPLTHCXhZRc5FfAV7IcfURETIWkE4ADKd9tz7C9d4fjbQT8GVgOWAxsZPtvnYw5DJKPR0Q8XvXdaTPKrOFrAnOA5SnfoRYCC4D7gb8DtwI32J7Xk8pG9ICk0ynXFgx8xvaHOhxvFvBXYI0q5ja2r+pkzGGQfDyiu5I/9K/q/akxuGRrYHNgpUnc9WHgBuBKyuCSn+Z9LSIiIiKiKYMWIiKGgKRLgGdRLiTvbvunXYj5C+D5VcyXZ3aIiOgWSYuZ+lK87WLbE3XajhhKVYP/1sAmwLrAipTGs3nAvcAdwOWZ3aszJO1AacRsuNr2ZW0q+zBK42jD0bb/1I6yIyKmQtLVwBaUXG9b23/sQszGLLwGXmP7zE7HHHTJxwdLcoiIiOgHkm6hzChuYH3bt3ch5jGU2bIN7Gf7u52OOeiSj0dEjK0aZDLu4JIMKomIiIiIGF8aeCIihsPm1e+FwDldinkeZdACLNlAHRHRLZr4lIhol2oVp4urn+giSWtRlnxftTr0MPCCNoa4CPgxzWsETwV2aGP5ERGTtVH1+5FudJCqXEbpJAXwxC7FHBbJx/tccoiIiOgj61S/53VjwELlutr2el2KOeiSj0dEjMH2/ZTBCRERERERMU1L9boCETF4JC0l6f2Sflf9vF/S0tMo432SfluV8YGplhFLWJkyC81dthd3KeYdte01uhQzIqLO9G6G15ii5A8RLTkMmE3pHLoQ2Nv279tVuO1zgQOr8gU8R9Ib2lV+RMQULEfJ77rZCWB+bXulLsYdBsnH+19yiIiIiJiK5OMRERERERER0TFZaSEipuMzwCHVtoBnA2sB72uxjDWnWEY0PUhphF5b0lJdGriwbm373i7Ei4houA14AuXzw8CHq2PR35I/REyDpFnA/jQ7hR5j+2ftjmP725JeCexVHToYOLHdcSIiJnAvsDawjqRZ1So/nbZRbfuOMc+KuuTjAyA5RERE9Jk7gQ2B1SSta7sbeddTatvdWt1h0CUfj4iIiIiIiIiOkZ3JsCJiaiTdSelk2HgDEWWG/3XHvlf7y4gmSZcAz6L8PV/eiUboUWKeC+xWxXyF7Z90OmZEBICkTYHzKQ2dABcAuzmJbV9L/hAxPZJeC3yn2r0L2Nz2Ax2KtQFwHTCL8jrb2vbVnYgVETEaSecDL6C8B73d9le6EPNqYIsq5q62L+h0zEGXfHwwJIeIiIh+Iul0YA/K58SnbX+4w/GWB+ZSJrswsJ3tKzoZcxgkH4+IaKq+++4IbA1sDmwArAHMAZYHlqWsaLcAuA+4B/grcD1wJXCh7b90u94REREREf1sqV5XICIG0gKanQWpth/rQRnR9Iva9hHVbHodI2knyoAFKM/brzsZL2LYSVpL0vaSNu91XQaB7ZuAlwGNDje7AO/sXY1ikpI/REzPjtVvA6d2qrMhgO25wBm1Q//aqVgRM4Gk5SXtJen9kt4saate12kANAbDC/h41UGgYyQdROkgBaWDwW86GW9YJB8fGMkhIiI6RNLTJX1R0k8knSzpnZLW6nW9+lzjc0LAoZJe3uF4x1EGLADckgELk5Z8PCJmNEnrSTpM0v9RBh98k7L68yuAbSiD91elDFpYClgOWBlYH3gGsDvwnup+N0m6WtIHJM3p6gOJiIiIiOhTGbQQEdNxLOWCZf3nSz0oI5q+BiyutrcBzpK05tinT1/V0eb0atfAz23P70SsmL6q4ez7kq6qfqeDVB+StKqk71KWvf4tcJ2kuyUdKWmNHlevr9m+FjiA5mfI4Z1634u2Sf4QMT1b17bP6kK802vbz+pCvIihVOXf1wHfBT4FfBm4QtKlknbpaeX629eB+ZTvmusAv5S02/h3mR5JbwU+V+0aOM32wk7EGkbJxwdCcoiIiA6QtBfwB+DtwIuBfYDPA7dI+oikpXtYvX72XeAmSt61LHC6pMOrFRHaRtIcSacCb6gOmZJjxuQkH4+IGUnSipKOpnxWfRjYjOb33X+eNpUiq58tgE9S8oSD2lTdiIiIiIiBpazaHRHTIWk/4NXV7pm2T5lGGftSlgMGOMv2yW2q3owk6RjgHTRnoL6P0jnmW7bvakP56wAHA++jzBohykCJHW1f3Gr50T6SnghcBcymeQHtPmAr23/rVb3i8aoBC3uPcpOBu4H9bP9ilNujIukUSuOwgc/ZPrTHVYpxJH+ImDpJt1Bm8DKwsu1HOhxvDnBvFe8q29t0Ml7EsJL0v8Bzx7jZwEdtf6KLVRoYkt5CGeRhyvcZAz+jDNb/ke1pr7JUdSJ8NfAuYCea35fuB56e70tTl3y8fyWHiIjoDEk3AGPNPm/g58CrbC/oXq0GQ7WC8/nAMjTzvHuBU4HvA5fY/sc0yl0WeDawL/A6ygzYjTzvWmC76ZQ7UyUfj4iZplpV5mzgyTTf92DJQQrzgVuB24BHgH9UP8sBKwCzgLUp38FWr92vXpaBE4CDbC8mIiIiImIGyqCFiIghIWk54DzKhd76xeRFwK8ps7hfAtwMzLU9b5yyVgI2ADYGtq/K3IUlGxME/JftT3bmEcV0SXo7ZTbykRfCDrb95Z5VLB5H0oOUC5nQfJ5+RZmVchVgAfBC2xf1pIIDQNJ6wI2UpXgfAJ5o+8He1ioion0k3QvMAR6wPbtLMR+iNLbdZnuDbsSMGDaSHqbkJ9DM8z4O7ArsXO3/h+0v9qaG/U3SUcAhLPndFuBR4HJq322B22l2GHiUMnPvCtXP2iz53XZ7lsy/oeTcr7J9Ticf07BKPt6/kkNERHSGpAeAFRu7lIl9dgV2o+QvKwLftH1gb2rY3yTtCZxM6eQJS+Z6i4CrmXqetzWPz71VlfF82zd38jENo+TjETFTVN9pLwHWo/meB2XQ22nA74CLx2tXH6XMlSkTWewE7EdZtaH+fnqc7Xe06zFERERERAySDFqIiBgikmYB36TM3D6yw/pIjzH2heQVRiue5gWVxcD/Z/tTbax+tImkAykzdYz8H3iL7a/1rGLxOJLmUi6EQnme5tueI2lV4H8oy5jfBmxh+4EeVbPvSToAeEa1e6ztG3pYnYiItpK0AFiaMuh04y7FvIUyK9hDtlfpRsyIYSPpGuAptUO3216/uu0NwFcp38mebvumHlSx70k6CDiS0qmp3nGglYuZ9TIE3AHsa/uCFsqc8ZKP96fkEBERnSHpImCH2qE/2X5GdduWlAlJVgd2TY4xOknbUtoxtmL02aynmu+NzPEAfgq8sR2rUM9UyccjYiaQdA7wQprvS78FDrF9cRtj7E6ZbG59mm22L7Z9XrtiREREREQMigxaiIgYQpL2Aj5BWcYSRr/wP1kj73sJ8G7bv5t+DaOTJK0OXAU8oXb4dmAr2/f2plYxGklHAP9ZO3Sc7YNrt58E7A8cZvtjXa5eRET0gWrG4lnAg7ZX7VLMe4DVgIW2l5vo/Ih4PEn7AN8GlqoOvd328bXbDwX+G/ia7Tf3oIoDQdIGwEcoOXFjcH39YuZkvuOOdv584MvAJ23Pb7WeEf0oOUREe0jauZfxbV/Yy/jxeJKeCZwNrAPcB7zS9q9rt78M+DHwVdtv6UklB4CkpYB9gXcAzxlx81Qar0cOdvglcJTtn7VWw4Dk4xHTlfxhMEjahfK50XifOtL2BzsUaw5lYONWlPfCC20/vxOxIiIiIiL6WQYtREQMMUkvBvYBXsSSHdin6jZKQ8xJ9QaY6F/VcqbvAzYHrqc01Pytt7WKkarGuXcDuwC/Bz5t+7Ha7asDZ1IulP6oF3WMiIjeknQrzeXJZ9t+sMPxlgYWUBrP7re9WifjRQwzSdsBOwOXjewwIGkZSuefE2zP7UX9Bomk2cCrKd9td6TM5D5Vc4GLKN9tz7L9cNsqGNGHkkNEtIekxbQ2q3grbHuZHsWOcVQrHj8VuHG0DteSdrX9i+7XbDBJ2ohmnrc15Zr2SpO468PADcCVlDzvp7kG3hnJxyOmJvnDYJB0AnAg5bk6w/beHY63EfBnYDlgMbBRPrciIiIiYqbJoIWImDRJOwCb1Q5dbfuyNpV9GGVJxIajbf+pHWVHIWljmhf81wfWBOYAywPLAAspjcv3A38HbqV0dr/S9s3dr3FERAyD5A8RrZF0IbATpfHsVbZ/3OF4W1E6fBi4zvaWnYwXETEdVaepzZj8d9sbbM/rSWUjeiQ5RER71DodTmcF21bZ9tI9iBvRc1W+N26el/yud5KPR4wv+cNgkHQ1sAXludrW9h+7EPNkykpDBl5j+8xOx4yIiIiI6CcZYR0RkyJpLcrsJ43l5B8GXtDGEBdRlkxuvC89FdihjeXPeLZvAW7pcTUiImIGSf4Q0RaXUjocAuxO+Z/vpJfWtq/pcKyIiGmxfT9wWfUTEaNLDhHRXo0ZwHrR+TBixqnyvft7XY8YXfLxiElL/tDfNqp+P9KNAQuVyyiDFgCe2KWYERERERF9I4MWImKyDgNmV9uPAXvb/n27Crd9rqQDgW9Vh54j6Q22T2xXjIiIiOi65A8RrTsPeA+lcXN/SR+zfUcH4+1T276og3GGmqSlgEOBPatDZwCftb1oimW8typDwA+Ao6ZSRkREzGjJIQZM8oe+dRvwBMrf08CHq2MRERF9ITlEX0r+MBiWozw/3RwkN7+2vVIX40ZERERE9IUMWoiICUmaBexPczaIY2z/rN1xbH9b0iuBvapDBwPpdBgRETGAkj9EtM25wN3AmsCKwCeAN3UikKR9gW2qXVMaqGN6PgMcUm0LeDawFvC+FstYc4plRETEzJUcYvAkf+hPOwPnAxtW+y8EdrPtse8S/U7SKsAawBxgeWBZYCGwALgPuKeaST4iYhAkh+g/yR8Gw73A2sA6kmbZfqQLMTeqbXdyUHlERERERF9SvhdFxEQkvRb4TrV7F7C57Qc6FGsD4DpgFqWRc2vbV3ciVkQ/ql4DWwObAxswQeMZ8FfgeuBK23O7X+OIiNElf4hoH0nvBo6udg0cZPv4NsfYEPgtZRY4A2fZ3nP8e8VYJN1J6SDQuOgi4C7b63azjJgaSZsCOzLNfBy40PZful3viIixJIcYLMkf+pekLSj/56tUh95j+5geVimmQNL6wIto5nmbAatO4q4PUsvzgHM6vGLNjJZcPGL6kkP0p+QP/U/S+cALKP/3b7f9lS7EvBrYooq5q+0LOh0zIiIiIqKfZKWFiJiMHavfBk7tVIdDANtzJZ1BmZkZ4F+BdDqMoSZpV2Af4MXA+i2U81fgJ8BJtn/XpupFRExX8oeI9vkS8B5KniDgC5IW2f5qOwqXtC5lNuZGQ/RjZCa9Vi2g2dBPtf1YD8qICUhaD3gbJR9/0minjNhfrvpZmfKa3HpEedcB3wKOt31fu+sbETFFySEGS/KHPmX7WkkHAGdUhw6XdIrtv/ewWjEBSXsD7wR2YMmcbmR+N5ZVgG2rnwOAxZLOA460/Ys2VnXGSi4e0TbJIfpQ8oeB8BPKoAUBH5d0nu2bOhVM0kGUAQtQBuD9plOxIiIiIiL61VK9rkBEDIT6hd+zuhDv9Nr2s7oQL6InJL1S0p8oDfwHUmaPEpNvOPtnUdXPRpRGnt9IulDSNm2sbkTEVCV/iGgT2wuANwOLKY3GywDHSzpV0lqtlC1pX+Aqymyjqsr/vO0bW6v1jHcszRyt8fOlHpQRY5C0oqSjgZuAD9N8DUynQ1vjXFEanz8J3FI1RkdE9ExyiIGT/KGP2T6T5mqCKwMf7F1tYjySni7p95Tna0eWbAudznXXxu+lKSs2nCvpe5JWarmyM1Ry8Yi2Sw7Rp5I/9L2vA/Mp32XWAX4pabdOBJL0VuBz1a6B02wv7ESsiIiIiIh+JtsTnxURM5qkW4ANKV+gV7b9SIfjzQHureJdZXubTsaL6DZJywNfBfZrHKL8v4/WELMQeAT4R/WzHLACMKvaHqlezgLg322f0rbKR0RMUvKHiPaT9HZKI3Lj897Ao8CJlJkkr5hkOatRZrJ8E7BNrSyAHwF7OBcLWiZpP+DV1e6Z08nJqg6he1S7Z9k+uU3Vm9EkbQqcDTyZJf//6/n4fOBW4DbGzsfXpnzWrV67X70sAycAB9le3InHEhExGckhBkfyh/5WzQp/I7A88ADwRNsP9rZWUSfplcCplHxt5DXXRcA1wM1MPs/bGNgKWLYqo/4+ejnwMtt3dfhhDZXk4hGdkRyifyV/6G+S3gJ8mSU/438GfA34ke1przgiaWnK6/JdwE40P+vuB55u+2/Tr3lERERExGDKoIWImJCke4E5wAO2Z3cp5kOUi8+32d6gGzEjukHSssA5wC4s2XC2iLIM6O+Ai6kaz8ZbJlbSqjQbz55LueC1E2X2sPrFtTfb/npnHlFExOiSP0R0hqQPAEew5IyfjS/284ALgeuBeygDeZYGVgVmA5sC2wFPYslZLBt5wwXAS2w/2vEHEtEjVWeBS4D1WLIT27XAaVT5uO15UyhzZZr5+H6UmWLr+fhxtt/RrscQETEdySEi2kPSAcAzqt1jbd/Qw+pEjaTnAb+kdGxvvD/No8xwfRpwqe2HplHuLOA5wOsoA7dWrG4ycKHtF7Re+5khuXhEzFTJH/qbpKOAQ1jy8wPKQO/LKZ9dNwNzgdtpDqh7lDKwcYXqZ21gA0q77fbVz6xGmOr3AuBVts/p5GOKiIiIiOhXGbQQEROStIDSUDnX9sZdinkLpTP2Q7ZX6UbMiG6Q9HnKjBqNC1/3AZ8BTrR9RxvK37Aq/12U162Ah4BtbN/YavkREZOV/CGicyTtCpxCaQgbOSvlRF/y67NX1gdPHgEcbntRG6sa0XcknQO8kOb//2+BQ2xf3MYYu1NmNF+fZmP3i22f164YERHTkRwiIoaVpGUoqyg0OqwvBD4LHGb7H22MsxZl5uXdq0MG3mn7S+2KMcySi0dERL+SdBBwJGWQQX1gXSsdqkYO9r4D2Nf2BS2UGREREREx0DJoISImVM1aPAt40PaqXYp5D7AasND2ct2IGdFpkjYDrqN5kepXlItTbV9CXNJzKMtsr1YdOs32Pu2OExExluQPEZ0laQ3gvcBBlFmQYclGNI24y8gv/43OGz+hdOS5tBP1jOgnknahzL7beD0cafuDHYo1h5Lvb0V5vV1o+/mdiBURMRXJISJiGEnaD/g2zQELe9v+YQfjnQzsW+1eZ/tpnYo1LJKLR0REv5O0AfARYH/Kygkw/nel0Yx2/nzgy8Anbc9vtZ4REREREYMsgxYiYkKSbqW5XO9s2w92ON7SlKURBdxve7UJ7hIxECR9CvgA5bV0BbCT7Uc6GO8FwPnV7iPAOp1+/Q4DSTv3Mr7tC3sZP6Jdkj9EdIek2cCbgD0oS44vM8FdFlLykF8BX8ly9DGTSDoBOJDy2XSG7b07HG8j4M/AcsBiYCPbf+tkzEGXXDyie5JDRMQwkXQ65f3MwGdsf6jD8WYBfwXWqGJuY/uqTsYcdMnFB0Py8YiIf35XejXwImBHyurOUzUXuIgywdxZth9uWwUjIiIiIgZYBi1ExIQkXQjsRLmY/CrbP+5wvK2AK6t419nespPxIrpF0iXAsyj/27vb/mkXYv4CeH4V8+W2f9bpmINO0mJaW+61FbY9UUeRiIGQ/CGi+6qOM1sDmwDrAitSOhjOA+6lLEF+eRrJOkfSDsBmtUNX276sTWUfBqxfO3S07T+1o+yZQtLVwBaUz4ptbf+xCzEbs/AaeI3tMzsdc5AlF4/ojeQQvZX8IaJ1km6hdCg0sL7t27sQ8xjgHVXM/Wx/t9MxB1ly8cGQfHywJIeI6I5qEMNmlNfEmsAcYHnKwO+FlMmU7gf+DtwK3GB7Xk8qGxERERHR5/LFPyIm41JKp0OA3YGOdjoEXlrbvqbDsSK6afPq90LgnC7FPI8yaAGWvMAcE5vMMq8RMbbkDxFdVq3gdHH1E10maS3K7GmrVoceBl7QxhAXUd5LG9dyngrs0MbyZ4KNqt+PdKOTVOUySkcpgCd2KeYwSC4e0UXJIXon+UNE26xT/Z7XjQELletq2+t1KeYgSy4+WJKP97nkEBHdY/t+ymdKWwYFRURERETMZEv1ugIRMRDOq34L2F/Suh2Ot09t+6IOx4roppUpsxTdZXtxl2LeUdteo0sxh4Xp3axSEcMg+UNEzDSHAbMp73sLgb1t/75dhds+FziwKl/AcyS9oV3lzxDLUfK7+7sYc35te6Uuxh10ycUjYqZI/hARM0Vy8cGSfLz/JYeIiIiIiIiIgZOVFiJiMs4F7qYsd7gi8AngTZ0IJGlfYJtq18APOhFn2ElaCjgU2LM6dAbwWduLpljGe6syRHkujppKGfE4D1IuIq8taakuDVyodxK+twvxhsFtwBMo//cGPlwdiz6V97y+lfwhImYMSbOA/Wl26jjG9s/aHcf2tyW9EtirOnQwcGK74wyxe4G1gXUkzapmFu+0jWrbd4x5VjQkFx9Ayccjpif5Q0Rb3QlsCKwmaV3b3ci7nlLb7tbqDoMsufhgSD4+AJJDRERERERExKDKoIWImJDthZI+BRxdHXqjpEttH9/OOJI2BI5qhAV+aHtuO2PMIJ8BDqm2BTwbWAt4X4tlrDnFMmJJ1wPPonz+vgho+0XkUdSXA/5bF+INg52B8ykNnQAvBHaznZml+lfe8/pQ8oeImGFeQVlVC+AuyoyHnfJe4OXALGA7SVvavrqD8YbJ1ZSOUgJeD3ylCzH3rG3/pQvxBl1y8cGUfDxiepI/RLTPZTTzh3dSOlp3jKTlgX1rh67rZLwhkVx8MCQfHwzJISIiIiIiImIgLdXrCkTEwPgSMJfSGVDAFyS1bbZkSetSZmRuzAr/GGmYbsW/UZ4naD5nr+9BGbGkX9S2j6hmw+kYSTsBu1W7jwG/7mS8YWH7JuBlwAPVoV0ojZ3Rv/Ke17+SP0TETLFj9dvAqbYfGO/kVlQDs86oHfrXTsUaQj+pfgv4uKRNOxlM0kHAFtXufcBvOhlvGCQXH1jJxyOmJ/lDRPs0/r8FHCrp5R2OdxxlcB3ALbav6HC8YZBcfAAkHx8YySEiIiIiIiJiIGXQQkRMiu0FwJuBxZSLYMsAx0s6VdJarZQtaV/gKmAzmkvOft72ja3VekZbQHNZWKrtx3pQRizpa5TXEMA2wFmS1hz79OmTtBVwerVr4Oe253ci1jCyfS1wAOU9ScDhnXquoi3yntenkj9ExAyydW37rC7EO722/awuxBsWXwfmUz4z1gF+KWm38e8yPZLeCnyu2jVwmu2FnYg1bJKLD6Tk4xHTk/whon2+C9xE+fxYFjhd0uHVightI2mOpFOBN1SHTMkxY2LJxQdE8vGBkBwiIiIiIiIiBlIGLUTEpNn+OfAumh0DBbwW+Iuk4yRtM9myJK0m6e2SLgO+DazRCAP8CPjPdtZ9BjqW5gXlxs+XelBG1Ni+nvI3bMweuRvwZ0mHSlq7HTEkrSPpMOASmrN9GTiiHeXPJLbPBL5T7a4MfLB3tYkJ5D2vjyV/iIgZYpPa9sVdiPer2vZWXYg3FGzPA95P8zNpA+Dnks6WtKekZVspX9LSkl4j6QJKHtEobz5weCtlzzTJxQdO8vGI6Un+ENEmVYf0A4CFlDxvOeBDwK2SjpG0s6QVplO2pGUl7SDpC8DNlGsajeu71wGfbbX+M0Fy8cGSfLzvJYeIiIiIiIiIgSTbE58VEVEj6QOUDtCNC/ONi8wA84ALgeuBe4B7gaWBVYHZwKbAdsCTaDZCQ7MT4wXAS2w/2vEHMuQk7Qe8uto90/Yp0yhjX2CPavcs2ye3qXozlqTlgPOAnWj+3xtYBPwa+C1lwMHNwNyqMWesslaiNO5sDGxflbkLZSbzeufg/7L9yc48ouEmaT3gRmB5ypLYT7T9YG9rFaPJe17/S/4QEcNM0r3AHOAB27O7FPMhYAXgNtsbdCPmsJB0FHAIS+bjAI8Cl1PLx4HbgUeAf1S3L0v5u68ArM2S+fj2wKxGmOr3AuBVts/p5GMaRsnFB0vy8YipS/4Q0X6S9gROpgxagCVzvUXA1Uw9z9uako/Uy1NVxvNt39zJxzRskosPjuTj/Ss5RERERERERAyqDFqIiGmRtCtwCuXCcOONpN6BcNy717YbF6YXUToyHm57URurGtF3JM0CvgnszZKvn9FeO48xdsPMaLOD1RvOFgP/n+1PtbH6M46kA4BnVLvH2r6hh9WJGGjJHyJiWElaQBlsNdf2xl2KeQuwIfCQ7VW6EXOYSDoIOJLSsanxuQITfx6NW2ytDAF3APvavqCFMme05OIRMcySP0R0hqRtKddet+Lx1x5g6vneyBwP4KfAG23fNc1qzmjJxQdH8vH+lBwiIiIiIiIiBlUGLUTEtElaA3gvcBBlJmRY8qKyRtxl5BtOo3P1T4DDbF/aiXpG9CtJewGfAJ5cHRqtEW2yRt73EuDdtn83/RpGRLRf8oeIGEbVjIOzgAdtrzrR+W2KeQ+wGrDQ9nITnR+PJ2kD4CPA/jQHBI/3mTSa0c6fD3wZ+KTt+a3WMyIihlPyh4jOkbQUsC/wDuA5I26eSsPoyMEOvwSOsv2z1moYycUjpi85RERERERERAyqDFqIiJZJmg28CdiDsgTvMhPcZSFwBfAr4CuZmSVmOkkvBvYBXgQ8oYWibgPOBk6y/et21C0iolOSP0TEMJF0K7AepdPMbNsPdjje0sACSsec+22v1sl4w676THo1JR/fkTJ75FTNBS6i5ONn2X64bRWMiIihlPwhojskbUQzz9sa2BxYaRJ3fRi4AbiSkuf91PbfOlXPmSq5eMTUJYeIaA9JO/cyvu0Lexk/IiIiIqIXMmghItpK0izKhf9NgHWBFSmdDOcB91KW5L08F40jRidpY5qNZ+sDawJzgOUpHXoXUi4O3w/8HbgVuB640vbN3a9xRETrkj9ExKCTdCGwE6XDwKts/7jD8baidJ4ycJ3tLTsZb6apOk5txuTz8Rtsz+tJZSMiYmAlf4jonSrfGzfPS37XG8nFIyaWHCKiPSQtZmorMLWTbU80kVNERERExNBJEhwRbWX7EeDi6ie6TNIOlAv6DVfbvqxNZR9GaShoONr2n9pRdjTZvgW4pcfViBgIec8bHskfImIIXErpMACwO9DRDgPAS2vb13Q41oxj+37gsuonIsaQfDyiZckfInqkyvfu73U94vGSi0dMSnKIiPZSrysQERERETFTZNBCRMSQkLQWZfnjVatDDwMvaGOIiygXPhufHU8Fdmhj+RERk5b3vIiI6DPnAe+hNHLuL+ljtu/oYLx9atsXdTBORMSoko9HtEXyhwEkaSngUGDP6tAZwGdtL5piGe+tyhDwA+CoqZQREREzWnKIAZP8oe81VlvI4IWIiIiIiA6T3avVziIiop0kHQe8tdp9jLIk7M/aHON1wLeqXQP/bvvEdsaIiJiMvOdFREQ/kbQM8DdgzerQN2y/qUOx9gVOrnYXA5vYntuJWBERY0k+HtG65A+DSdKRwCGNXcr709G239fNMiIiYuZKDjF4kj/0J0m3Ak+g+ff8L+C2bsXP99uIiIiImIkyaCEiYghImgXcCaxUHerYRSpJ3wP2oly8ucz29p2IExExlrznRUREP5L0buDoatfAQbaPb3OMDYHfUhpUDZxle8/x7xUR0V7JxyPaJ/nD4JF0J7AWS87Ie5ftdbtZRkyNpE2BHYGtgc2BDYA1gDnA8sCywEJgAXAfcA/wV+B64ErgQtt/6Xa9IyLGkhxisCR/6E9VfnA+sGF16AJgN6cTVUREREREx2TQQkTEEJD0WuA71e5dwOa2H+hQrA2A64BZlAtjW9u+uhOxIiJGk/e8iIjoR5KWo3RqWp/ScLyQ0mngq20qf11K4+lmVfkLgC1t39iO8iMiJiv5eET7JH8YPJLmAuuNOHyb7Q26WUZMTNJ6wNuAfYAnjXbKBEWMbEC9jrIC0PG272u5ghERLUgOMViSP/QvSVtQBuesUh16j+1jeliliIiIiIihtlSvKxAREW2xY/XbwKmd6iwAUC37ekbt0L92KlZExBjynhcREX3H9gLgzcBiymfUMsDxkk6VtFYrZUvaF7iKZmcBA59PZ4GI6JHk4xFtkvxhIB1L+XvWf77UgzJiDJJWlHQ0cBPwYZqvgfoghYkGLCxRZPWzBfBJ4BZJB7WpuhER05IcYuAkf+hTtq8FDqD5Nz1c0po9rVRERERExBDLSgsREUNA0i+BXSgXDnez/asOx3s1pdOAgVNsv76T8SIi6vKeFxER/UzS2ykNyabZuP8ocCJlVtYrJlnOapRZYd8EbFMrC+BHwB5Zrj4ieiH5eET7JX8YLJL2A15d7Z5p+5RplLEvsEe1e5btk9tUvRlN0qbA2cCTWfL/vz5IYT5wK3Ab8Ajwj+pnOWAFyuo+awMbAqvX7lcvy8AJlFnNF3fisURETEZyiMGR/KG/STqF8how8Dnbh/a4ShERERERQymDFiIihoCkWyiNKAZWtv1Ih+PNAe6t4l1le5tOxouIqMt7XkRE9DtJHwCOoNk5qt7YPw+4ELgeuIfyGbM0sCowG9gU2A54EkvOCNvogHAB8BLbj3b8gUREjCL5eERnJH+IaI2k9YBLgPVo/u8DXAucBvwOuNj2vCmUuTLwXGAnYD/KrOP1jsHH2X5Hux5DRMR0JIeIaF2VR9wILA88ADzR9oO9rVVERERExPDJoIWIiCEg6V5gDvCA7dldivkQZeap22xv0I2YERGQ97yIiBgMknYFTqHM0jpyhteJLsbUZ4JtdBRYROmEcLjtRW2sakTElCQfj+ic5A8R0yfpHOCFNP//fwscYvviNsbYnTKj+fo0OwW/2PZ57YoRETEdySEiWifpAOAZ1e6xtm/oYXUiIiIiIoZSBi1ERAwBSQsoM6PMtb1xl2LeQplZ8SHbq3QjZkQE5D0vIiIGh6Q1gPcCB1FmMYQlOwtoxF1GXqRpdIT6CXCY7Us7Uc+IiKlIPh7RWckfIqZO0i7AL2m+Ho60/cEOxZoD/ArYivJ6u9D28zsRKyJiKpJDRERERERERL/LoIWIiCFQzTg4C3jQ9qoTnd+mmPcAqwELbS/XjZgREZD3vIiIGDySZgNvAvYAtgeWmeAuC4ErKJ2hvpKZ3dpD0s69jG/7wl7Gj2iX5OMR3ZH8IWLyJJ0AHEjpbHuG7b07HG8j4M/AcsBiYCPbf+tkzEGXXDyie5JDRERERERERL/KoIWIiCEg6VZgPUqjzGzbD3Y43tLAAsqsK/fbXq2T8SIi6vKeFxERg0zSLGBrYBNgXWBFSgeBecC9wB3A5bYf7lklh5SkxTx+Jsluse2JOopEDITk4xHdl/yh9yTtAGxWO3S17cvaVPZhwPq1Q0fb/lM7yp4pJF0NbEH5bNrW9h+7EPNkYN8q5mtsn9npmIMsuXhEbySH6K3kDxEREREREUvKBZqIiOFwE6XDAMDzgR93ON7TaC4Te1uHY0VEjJT3vIiIGFi2HwEurn6iN9TrCkQMuOTjEV2W/KG3JK0FnA00Vpd5GHhBG0NcRHkvbbTZPRXYoY3lzwQbVb8f6caAhcpllEELAE/sUsxhkFw8oouSQ/RO8oeIiIiIiIjHW6rXFYiIiLa4tLa9exfivbS2fU0X4kVE1OU9LyIiIlphejfLa8QwSD4eETPNYcBsSmfrhcDetn/frsJtnwscWJUv4DmS3tCu8meI5Sj53f1djDm/tr1SF+MOuuTiETFTJH+IiIiIiIgYISstREQMh/OA91AuSu0v6WO27+hgvH1q2xd1MM5Qk7QUcCiwZ3XoDOCzthdNsYz3VmUI+AFw1FTKiPHleepLec+LiIiI6bgNeALNGds/TGZt72vJxftW8vGImDEkzQL2p9nJ+hjbP2t3HNvflvRKYK/q0MHAie2OM8TuBdYG1pE0q5pZvNM2qm138nNwWCQXH0DJxyOmJ/lDRERERETE6DJoISJiOJwL3A2sCawIfAJ4UycCSdoX2KbaNeUCc0zPZ4BDqm0BzwbWAt7XYhlrTrGMGF+ep/6T97yIiIiYjp2B84ENq/0XArvZzkyv/Su5eH9KPh4RM8krgJWr7bsosyZ3ynuBlwOzgO0kbWn76g7GGyZXUwYtCHg98JUuxNyztv2XLsQbdMnFB1Py8YjpSf4QERERERExiqV6XYGIiGid7YXAp2guAfpGSW9tdxxJGwJHNcICP7Q9t91xZpB/ozxfUP6ejUa1bpcR48vz1GfynhcRERHTYfsm4GXAA9WhXYB39q5GMQnJxftQ8vGImGF2rH4bONX2A+Od3IrqPe6M2qF/7VSsIfST6reAj0vatJPBJB0EbFHt3gf8ppPxhkFy8YGVfDxiepI/REREREREjCKDFiIihseXgLk0L/p+QVLbZjqUtC5lNsV1q0OPkZlwWrWA5tKwVNuP9aCMGF+ep/6U97yIiIiYMtvXAgfQ7Gx9uKQ1e1qpGE9y8f6VfDwiZoqta9tndSHe6bXtZ3Uh3rD4OjCf8rm0DvBLSbt1IlA1UO9z1a6B06oBfTGB5OIDKfl4xPQkf4iIiIiIiBhFBi1ERAwJ2wuANwOLKRd9lwGOl3SqpLVaKVvSvsBVwGaUxgQDn7d9Y2u1nvGOpdlA0/j5Ug/KiPHleepDec+LiIiI6bJ9JvCdandl4IO9q01MILl4n0o+HhEzyCa17Yu7EO9Xte2tuhBvKNieB7yf5ufGBsDPJZ0taU9Jy7ZSvqSlJb1G0gWUPKJR3nzg8FbKnmmSiw+c5OMR05P8ISIiIiIiYhSyPfFZERExMCS9nXIRuDHboYFHgROB421fMclyVgP2Ad4EbFMrC+BHwB7Oh0jLJO0HvLraPdP2KdMoY19gj2r3LNsnt6l6Ucnz1L/ynhcRERHTIWk94EZgeeAB4Im2H+xtrWI0ycX7W/LxiBh2ku4F5gAP2J7dpZgPASsAt9neoBsxh4Wko4BDWPJzCcpn0+XAJcDNlNWCbgceAf5R3b4s5e++ArA2ZeDDxsD21c+sRpjq9wLgVbbP6eRjGkbJxQdL8vGIqUv+EBERERERMboMWoiIGEKSPgAcQbMBpd5AMw+4ELgeuAe4F1gaWBWYDWwKbAc8ieasN9Bs6LkAeIntRzv+QCIiJiHveRERETEdkg4AnlHtHmv7hh5WJ2JgJR+PiGEmaQHlfWuu7Y27FPMWYEPgIdurdCPmMJF0EHAkZZBB4/MEmp9N0yq2VoaAO4B9bV/QQpkzWnLxiBhmyR8iIiIiIiJGl0ELERFDStKuwCmUWaEab/aTbaBRbbvRELOI0gnhcNuL2ljViIiW5T0vIiIiIqJ3ko9HxLCqZi2eBTxoe9UuxbwHWA1YaHu5bsQcNpI2AD4C7E+ZdRqW/DzS4+70eKOdPx/4MvBJ2/NbrWdERAyn5A8RERERERGjy6CFiIghJmkN4L3AQZRZDGH8xpmRHwqN2RF/Ahxm+9JO1DMioh3ynhcRERER0TvJxyNiGEm6FViP8v402/aDHY63NLCA8p54v+3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      "text/plain": [
       "<Figure size 3000x900 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mglearn.plots.plot_cross_val_selection()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "hide_input": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/pdf": 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\n",
      "image/png": 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+/Hg98MAD+v777yVJ//d//2d3K1uSvvrqq3JXjQoJCVF0dLSio6MVGRlZGrbYq2vXrnr66ac1ZMiQCldrbdiwoTZu3KioqKga/x2sWrVK+/btc+i5y4qMjNT1119f68cDgDdxy84aX/+6zsSJEx3ep/Poo4+W/nPz5s3Vv39/NW7cWMOGDavTLPfff78yMzNr/fi77rqLsAYAAMBirVu3rnXbu02bNk6dJSQkRKNGjary/qioKLvO8+qrr9ZpB2Xz5s0JawD4DbdfDcqZ9u3bZ9cysyuvvNKlS8mq+yqWu9XUNgIAAACssGDBAhUWFtb68Y42ggDAm3l1WPP7779rxIgRNR73/vvvs0EeAAAAsFBwcLBTdlcCgD8wJN3Ut2/faQsXLoyxehh4rn79+qV/8cUX95im+ZnVswAAAFghNDTUTE9PV2hoqNWjoIzc3FzFxMQoNzeX6g0AnxFg9QAAAAAAAAD4H8Ia2MU0TatHAAAAACrgfSoAXxQgKScrK4v/h0O1MjMziyTlWD0HAACAVQIDA5WdnW31GDhFdna2AgMDrR4DAJwqQNK+33//ne93olp//PFHgKS9Vs8BAABglbCwsIKdO3daPQZO8ccffygsLKzA6jkAwJkCJCUeOXIkb8eOHVbPAg+VnJysI0eO5EraYvUsAAAAVsnOzv7h448/tnoMnGLevHnKyspab/UcAOBMAWaxWSNHjswpKiqyeh54mKKiIv3zn//MMU1zlskXggEAgB/Lycl59b333lNKSorVo+CklJQUvf/++8rNzR1r9SwA4EwBkpSZmfn88uXLf77ttttyaNigRHJysm677bac5cuX/5yZmTnS6nkAAACsZJrml5mZmbM6d+6s5cuXKz8/3+qR/FZ+fr6WL1+uzp07KzMzc5ZpmoutngkAnMkoKUsYhhEeGRk5xjCMwQ0aNAhp2bJlUWRkZIBhsM7Gn5imqczMzKI//vgj4MiRI3mmac7MzMwcaZom2/QAAAAkBQYGvhoXFzciLy8vvF27dmZcXJwCArjIqjsUFRUpLS1NmzdvNkJCQrLT0tLeKiwsfNrquQDA2YxTv9liFKczbSWdKSnMiqFguRwVLxPewlefAAAAKmcYxoWSrpHUQBKfcLqHKemIpOWmabJPEYDPqhDWoHKGYTQ3TXO31XMAAADANxmGcaWkqZJuM03zR6vncQbDMDpK+kjSMNM0v7N6HgDwFvQ17feVYRgtrB4CAAAAvsUwjCjDMP6j4qBmmK8ENZJ08ne5V9IHhmFMMQwjyuqZAMAbENbYb72k7lYPAQAAAN9xsk2TqOKv97Q1TXOFxSM53cnfqZ2KvyqWaBhGD4tHAgCPx9eg7GQYxj2SrjBN826rZwEAAIB3O9kweU1SLxW3aXwupKlMma96LZX0tGmaGRaPBAAeiWaN/WyiWQMAAIA68oc2TVVo2QCAfWjW2OnkVbJSVNyuSbF2GgAAAHgbf23TVIWWDQBUjWaNnU5ewtom2jUAAABwkD+3aapCywYAqkazxgHsrQEAAIAjaNPYh5YNAJRHs8YxNtGsAQAAgB1o09iPlg0AlEezxgHsrQEAAEBNaNPUDS0bAKBZ4xD21gAAAKA6tGnqjpYNANCscRh7awAAAHAq2jSuQcsGgL+iWeM4m2jWAAAA4CTaNK5DywaAv6JZ4yD21gAAAECiTeNutGwA+BOaNQ5ibw0AAABo07gfLRsA/oRmTS2wtwYAAMA/0abxDLRsAPg6mjW1YxPNGgAAAL9Cm8Zz0LIB4Oto1tQCe2sAAAD8B20az0bLBoAvollTC+ytAQAA8A+0aTwfLRsAvohmTS2xtwYAAMB30abxTrRsAPgKmjW1ZxPNGgAAAJ9Dm8Z70bIB4Cto1tQSe2sAAAB8C20a30LLBoA3o1lTS+ytAQAA8B20aXwPLRsA3oxmTR2wtwYAAMC70abxD7RsAHgbmjV1YxPNGgAAAK9Em8Z/0LIB4G1o1tQBe2sAAAC8D20a/0bLBoA3oFlTB+ytAQAA8C60aUDLBoA3oFlTR+ytAQAA8HyGYURLelW0aVBGmZbNMklP0bIB4Clo1tSdTTRrAAAAPNbJv5BvFm0anKJMy0YqbtlcaeU8AFCCZk0dsbcGAADAM51s07wm6RrRpkENaNkA8CQ0a+qIvTUAAACep0ybpki0aWAHWjYAPAnNGidgbw0AAIBnoE0DZ6BlA8BqNGucwyaaNQAAAJaiTQNnoWUDwGo0a5yAvTUAAADWoU0DV6JlA8AKNGucgL01AAAA1qBNA1ejZQPACjRrnIS9NQAAAO5DmwZWoGUDwF1o1jiPTTRrAAAAXI42DaxCywaAu9CscRL21gAAALgWbRp4Elo2AFyJZo2TsLcGAADAdWjTwNPQsgHgSjRrnIi9NQAAAM5FmwbegJYNAGejWeNcNtGsAQAAcAraNPAWtGwAOBvNGidibw0AAEDd0aaBN6NlA8AZaNY4EXtrAAAA6oY2DbwdLRsAzkCzxsnYWwMAAOA42jTwRbRsANQWzRrns4lmDQAAgN1o08BX0bIBUFs0a5yMvTUAAAD2oU0Df0LLBoAjaNY4GXtrAAAAakabBv6Glg0AR9CscQH21gAAAFSONg1AywZAzWjWuIZNNGsAAADKoU0DFKNlA6AmNGtcgL01AAAA/0ObBqgaLRsAlaFZ4wLsrQEAAChGmwaoHi0bAJWhWeMi7K0BAAD+jDYN4DhaNgBK0KxxHZto1gAAAD9EmwaoHVo2AErQrHER9tYAAAB/Q5sGcB5aNoB/o1njIuytAQAA/oQ2DeBctGwA/0azxoXYWwMAAHwdbRrA9WjZAP6HZo1r2USzBgAA+CjaNIB70LIB/A/NGhdibw0AAPBFtGkA69CyAfwDzRoXYm8NAADwNbRpAGvRsgH8A80aF2NvDQAA8AW0aQDPQ8sG8F00a1zPJpo1AADAi9GmATwTLRvAd9GscTH21gAAAG9FmwbwHrRsAN9Cs8bF2FsDAAC8EW0awLvQsgF8C80aN2BvDQAA8Ba0aQDvR8sG8H40a9zDJpo1AADAw9GmAXwDLRvA+9GscQP21gAAAE9GmwbwXbRsAO9Es8YN2FsDAAA8FW0awLfRsgG8E80aN2FvDQAA8CS0aQD/Q8sG8B40a9zHJpo1AADAA9CmAfwTLRvAe9CscRP21gAAAKvRpgFQgpYN4Nlo1rgJe2sAAICVaNMAKIuWDeDZaNa4EXtrAACAu9GmAVATWjaA56FZ41420awBAABuQpsGgD1o2QCeh2aNG7G3BgAAuANtGgC1RcsG8Aw0a9yIvTUAAMDVaNMAqAtaNoBnoFnjZuytAQAArkCbBoCz0bIBrEOzxv1solkDAACciDYNAFegZQNYh2aNm7G3BgAAOAttGgDuQssGcC+aNW7G3hoAAOAMtGkAuBMtG8C9aNZYgL01AACgtmjTALAaLRvA9WjWWMMmmjUAAMBBtGkAeAJaNoDr0ayxAHtrAACAI2jTAPBUtGwA16BZYwH21gAAAHvRpgHgyWjZAK5Bs8Yi7K0BAADVoU0DwNuUadksV3HL5oTFIwFei2aNdWyiWQMAACpBmwaANyrTsjElbaZlA9QezRqLsLcGAACcijYNAF9BywaoG5o1FmFvDQAAKIs2DQBfQssGqBuaNRZibw0AAKBNA8DX0bIBHEezxlo20awBAMBv0aYB4A9o2QCOo1ljIfbWAADgn2jTAPBXtGwA+9CssRB7awAA8D+0aQD4M1o2gH1o1liMvTUAAPgH2jQAUB4tG6BqNGusZxPNGgAAfBptGgCoiJYNUDWaNRZjbw0AAL6LNg0A2IeWDVAezRqLsbcGAADfRJsGAOxHywYoj2aNB2BvDQAAvoM2DQDUDS0bgGaNp7CJZg0AAF6PNg0A1B0tG4BmjUdgbw0AAN6NNg0AuAYtG/grmjUegL01AAB4L9o0AOA6tGzgr2jWeAj21gAA4F1o0wCAe9GygT+hWeM5bKJZAwCAV6BNAwDuR8sG/oRmjYdgbw0AAJ6PNg0AeAZaNvB1NGs8BHtrAADwbLRpAMBz0LKBr6NZ40HYWwMAgOehTQMAno2WDXwRzRrPYhPNGgAAPAZtGgDwfLRs4Ito1ngQ9tYAAOAZaNMAgHeiZQNfQbPGg7C3BgAA69GmAQDvRcsGvoJmjYdhbw0AANagTQMAvoWWDbwZzRrPYxPNGgAA3Io2DQD4Hlo28GY0azwMe2sAAHAf2jQA4B9o2cDb0KzxMOytAQDAPWjTAID/oGUDb0OzxgOxtwYAANehTQMA/o2WDbwBzRrPZBPNGgAAnI42DQCAlg28Ac0aD8TeGgAAnIs2DQCgMrRs4Klo1ngg9tYAAOA8tGkAAFWhZQNPRbPGQ7G3BgCAuqFNAwBwBC0beBKaNZ7LJpo1AADUCm0aAICjaNnAk9Cs8VDsrQEAwHG0aQAAzkDLBlajWeOh2FsDAIBjaNMAAJyFlg2sRrPGg7G3BgCAmtGmAQC4Ei0bWIFmjWeziWYNAABVok0DAHA1WjawAs0aD8beGgAAKkebBgBgBVo2cBeaNR6MvTUAAFREmwYAYBVaNnAXmjUejr01AAAUo00DAPAktGzgSjRrPJ9NNGsAAH6ONg0AwNPQsoEr0azxcOytAQD4M9o0AABvQMsGzkazxsOxtwYA4K9o0wAAvAUtGzgbzRovwN4aAIA/oU0DAPBmtGzgDDRrvINNNGsAAH6ANg0AwNvRsoEz0KzxAuytAQD4Oto0AABfRMsGtUWzxguwtwYA4Mto0wAAfBUtG9QWzRovwd4aAICvoU0DAPAntGzgCJo13sMmmjUAAB9BmwYA4G9o2cARNGu8BHtrAAC+gDYNAAC0bFAzmjVegr01AABvR5sGAIBitGxQE5o1XoS9NQAAb0SbBgCAqtGyQWVo1ngXm2jWAAC8CG0aAACqR8sGlaFZ40XYWwMA8Ba0aQAAcBwtG5SgWeNFTu6t+U60awAAHow2DQAAtUPLBiVo1ngZwzDultSdvTUAAE9DmwYAAOehZePfaNZ4H5to1gAAPAxtGgAAnIuWjX+jWeOFDMNIUXG7JsXiUQAAfo42DQAArkfLxv/QrPFONtGuAQBYjDYNAADuQcvG/9Cs8ULsrQEAWIk2DQAA1qFl4x9o1ngnm2jWAAAsQJsGAABr0bLxDzRrvBR7awAA7kSbBgAAz0PLxnfRrPFeNtGuAQC4AW0aAAA8Ey0b30WzxkuxtwYA4Gq0aQAA8B60bHwLzRrvZRPNGgCAi9CmAQDAu9Cy8S00a7wYe2sAAM5GmwYAAO9Hy8b70azxbjbRrgEAOAltGgAAfAMtG+9Hs8aLsbcGAOAMtGkAAPBdtGy8E80a72YTzRoAQB3QpgEAwLfRsvFONGu8HHtrAAC1QZsGAAD/Q8vGe9Cs8X420a4BADiANg0AAP6Jlo33oFnj5dhbAwCwF20aAABQgpaNZ6NZ4/1solkDAJBkGEaVr+u0aQAAQFmOtGyqe48B1+BfuJcr2VVjGEYLaycBAFjJMIyeoaGhfxqGUe+U26MNw3hbxZ+cDTNN8yHTNDOsmRIAAHgS0zRPmKb5d0nDJE01DOPtk03cUoZh1Dv5HqOnNVP6J8Ia32AT7RoA8FuGYQTFxMRM7dixY6PY2Nj3ytxOmwYAANSoupZNbGzs+x07dmwUExMz1TCMIMuG9DOENb7BJsIaAPBbwcHB97Vv3/60r776KjA2NrZXQEDArbRpAACAIypr2QQEBAyIi4u75quvvgps167dacHBwfdaPae/YMGwDzj5FSibaZotLB4FAOBmhmHERUZG7v7xxx9jzjvvPK1fv149e/YsysrKmibpUUIaAADgqJNfhXojMjLy7m+//TagU6dOSkpKUqdOnY5nZmY2N03zuNUz+jqaNT6AvTUA4L+io6PHDBo0KOS8886TJHXu3Fn33XdfYWxsbCxBDQAAqA3TNE/ExsbG3nfffYWdOnWSJJ1//vm64447QqOjo8dYPJ5foFnjIwzDmK7ids10i0cBALiJYRhtoqOjN+7atSuifv36pbfn5OQoISEhc+/evQMLCwu/tHBEAADghQIDA69v2rTpR9u3b48MCwsrvf3o0aM666yzsk6cONHeNM3fLBzR59Gs8R02sbcGAPxKXFzcey+99FJ4/fr1ZZqmUlNTtXHjRi1dulTdu3ePDA0NnWEYRqjVcwIAAO9hGEZYaGjozCuuuCJy6dKl2rhxo1JTU2WapurXr6+XXnopPC4u7r2az4S6oFnjI9hbAwD+xTCMuyRN79atW96+fftyDhw4EGYYRl54ePiBgICAnVlZWduzsrKSJE03TbPA6nkBAIB3OHnFp7sjIiLOj4iIOLeoqKhldnZ2Y9M0Qxo3bpxzxhlnhK1ZsyZE0l2mac60el5fRVjjQwzDSJHUvWSHDQDAdxmG0UNSH0krJKVI2m2aZqalQwEAAJ9lGEakpOaSWkjqKWmRaZrfWTqUDyOs8SHsrQHgCwzDuFBSL0n1JRkWj+MvTElHJS0zTXOL1cMAAAD7GYYRLukSSfUkBVo8DhxTKOmYpA2maWaXvYOwxocYhnG3ips1d1s8CgA4LDAw8NW4uLgReXl54e3btzdjY2MVEMBqNXcoKirS8ePHtWnTJiMkJCQ7LS3trcLCwqetngsAAFTNMIyE+Pj4cTk5OT0TEhLyGjVqZISEhPBBlxfJy8szDx48aCYnJ4eEhYV9m5qa+qRpmskSYY1PYW8NAG8VEhIys169enfOnDlTPXr0UHBwsNUj+aX8/Hx99913Gjx4sI4dOzYrLy9vsNUzAQCAigzDOC8yMnL1yy+/HDd48GAjPj7e6pFQB6mpqZo5c6b5/PPPp2VmZnYzTfNXwhofw94aAN7GMIzr4+Livti4caNatGhh9TiQlJKSog4dOigtLe060zQXWz0PAAD4H8MwjKioqD+nTp165oABA2jS+JB58+aZw4YN25uRkdGcfrnvsYlLeAPwImFhYU/fd999BDUepEWLFrr33nsVGhr6jNWzAACACtrXq1cvlqDG99x6661GfHx8nKR2hDW+xybCGgBeJDw8vNOtt95q9Rg4xYABAxQREdHZ6jkAAEB5ISEhN95xxx3hVs8B5zMMQ4MGDQoPCQm5kbDG99hEWAPAi+Tk5AS1atWqxuNM01RGRkaVPwUFBW6YtvaKioo0d+5crVu3rk7nWbBggVasWFGnc/zwww+aO3dutf/OWrZsqZycnKA6PREAAHC6yMjIVm3atHHaa/SJEyc0d+5cbd261Vmn9Djr1q3T3LlzVVRUVOtzbNq0SXPnzlVmZmatz3Ho0CHNnTtXv/32W5XHnH322UGRkZGtCWt8TMmumpPLhgHA4xUWFio8vOYPh3bu3Kno6Ogqf+bOnVvp4zIzM7V9+/Yqf44fP17u+KysLDVp0kSPPfZYnX+3f/zjH7rrrrskSXl5eRo4cKAmTZpUp3Pee++9GjVqVJ3O8fbbb2vgwIHKycmp8pjw8HAVFhbW6XkAAIDzBQQERNjz3qk6Y8eOVa9evSRJ+/bt08CBAzV//nxnjOcRlixZol69eikxMVGSNGnSJA0cOFB5eXm1Pufs2bM1cOBAHT58uNbn+PXXXzVw4EAtX768ymPCw8MVEBAQwSdmvsmm4nbNdEunAAAnatSokT766KMq7+/SpUult69atUrXXnttlY+bNm2a7r777tI/FxUVad++fTp27Fi18/zyyy/6888/K9weGxurHj16SCr+FOfgwYPVnkeS9u7dq+eff16LFy9WTk6OOnXqpJdeekndunWr8bGStGzZsiqfJzAwUHfeeadd5ynLMPgaPAAA3ujrr7/Wvn37KtzeqlUr/d///Z+k4pZIdYFBdQYOHKi5c+fq4MGDatiwYY3HZ2dna8aMGXaff9iwYQoKqjqqOHLkiFavXl3pfT169FBsbKz+/PNPLV++XM88U/36vcLCQr355pt65513tHv3bjVv3lz33nuvHn300WpnKPH7779XOYskXXHFFTrrrLNqPE9ZJe/BCGt8k02ENQB8wF9//aWePXs6/Ljx48eXflp02WWX6aeffqpwzOrVq/WPf/yj9M979+6VVNysscebb75Z6RuPdu3aadOmTXbPunfvXnXu3FknTpzQ0KFDFRsbqxkzZqhHjx764osvqg2aSowdO1YrV66s9L7Q0NBahTUAAMA7TZgwodIg5o477igNa+riyJEjCggIUGxsrF3HHz9+XA8++KDd5x80aJCioqKqvH/r1q268cYbK71v48aNat++vd3PNXToUM2YMUN9+/bVPffcozVr1ujJJ5/Upk2bNHv27Bofv3r1at1zzz1V3v/RRx85HNaUIKzxTTZJL1o8AwDUWVxcnMaPH+/w48q+SMfExOiSSy6pcEzZJkpBQYGaNm1aqxmTkpJUr1690j8HBwc79PjHHntMBw8e1Nq1a9WxY0dJ0ogRI9ShQwcNGzZMu3btUkhISI3nqV+/vo4cOeLY8AAAwGeZpun0cxYVFWnDhg2Kj493+D3PQw89pMmTJzttln/9618VQqAGDRrY/fglS5ZoxowZGjFihN58883S20eMGKHJkydr4MCB6tOnj13n+vLLL3XdddfZ/dz2IKzxQaZpphiGIcMwWpTssAEAbxQaGlrakFmxYoX++9//asOGDdq7d6+ys7MVEhKihg0b6sILL9Stt96qO+64QwEB5dex5eXlVfqVprS0tNJ/DgoK0qpVq0qPd6TNc/rppzv0xqCsQ4cO6bPPPlO/fv1KgxpJqlevnh577DE9+uijWrp0qfr161er8wMAADjTF198Ufoe6tVXX9Vzzz1n2SzR0dFq1KhRrR//9ttvKzg4WC+++GK521988UW98847mjp1qt1hjSuwYNh32cRVoQD4iJkzZ6pnz57au3evXnjhBX333XfasmWL1q1bpzfffFOnnXaaBg8erEceeaTCY9euXavGjRtX+Dn1q0HdunVTt27ddNlll7nr19LatWtVWFioK6+8ssJ93bt3l6TSEAkAAMBK2dnZeu6551SvXj3deuutGjVqlNavX2/346dMmaKTpYIqf6666ioX/gblrVq1Su3atSvXkJaK28oXXHCB5e/BaNb4LpvYWwPAR3z33XeSpJEjR1Z4EW/fvr0uu+wyzZ07VzabrcpzPPTQQ7rtttsq3N6mTRsVFhbq/PPPl1S3yvCGDRvKvWn566+/qj1+z549kqQzzjijwn1NmjSR9L9dOjXJzc2t9LvV5513ni666CKNGDFCW7ZskSRt377drnMCAADvdeqVMm+44QYNHz5cOTk5DoUskpSfn69BgwZp27ZtmjNnjm644QZdcskluvbaa7VixQp16NChxnPccccdGjlyZLXHREZGOjRXiczMTE2bNq30z9Ut/ZWKL1d+/PjxSt+DScXvwzZt2qScnByFhYXV+Pw2m61ca1uSwsLC1L9/fy1evFjjxo2TpArHVIewxnfZxN4aAD7ikUceKb0EY+fOndWyZUuFh4crLy9P+/bt09q1a1VUVFTtG4AWLVpUeXUl0zQ1aNAgScVfgxo9enSt5ly2bJn++c9/lrutefPmVR6fn58vSZVeujwiIqJ0HntkZGRUukj48ccf10UXXaS4uLjSr2vZ86YDAAB4t4EDB5b784EDB3T8+HFlZ2eXvgexx86dO3XXXXdpzZo1Gjt2rG6//XZJxe97unfvriuuuEJvvPGGhgwZUu154uLidM455zj+i9ghNTVVI0aMsPv46t6DSeXfh9nzvmnChAkVbqtfv7769++vsLCw0vdgjnwoyNegfFTJrhrDMFpYOwkA1F379u21c+dOTZs2Te3bt1d6erpSUlJ0+PBhNW3aVK+88or++OMPDRgwwOFzHzhwQCtXrlSzZs00cuRIPfXUU7Wec+TIkTJNs/SnU6dO1R4fHx8vqfIGzv79+yWpQjW3KvXr11d2dnaFn7Fjx0qSRo8erfnz52v+/PmlX7ECAAC+69T3BI0aNdInn3yiRYsW2XVVqMTERN1///0699xztWXLFk2fPl1PP/106f3NmjXTypUrdd5552no0KHq2bOnlixZ4pLFxjVp0qRJufdgb7/9drXHx8TEKDAwsMoW9P79+xUUFKTo6Gi7nv+zzz6r8O+75PLpPXv2LH0P9tJLL9n9O9Gs8W02ST0kTavhOADweFFRUbrzzjtrfRnqiRMnavbs2SosLFReXp4yMzN1+PDh0uZKx44dNXjwYGeOXKN27dpJkn755Rfddddd5e7buHFjuWPsQWMGAACUqOv7gkmTJmnWrFm67bbbNGbMGDVr1qzCMU2bNtXq1as1btw4TZgwQXfeead++OEHtW7dusKx27dv1/Tp02t83iuvvLLS53KmoKAgnXfeedqyZYvy8/PLXdkqLy9PSUlJatu2rQzDsOt8wcHBTn8fRljj22wq3ltDWAPA63Tv3l0rV66s0znWrVunpk2b6vHHH5ckGYahwMBAhYaGKjY2VqeddpqaNWumhISEOl1NoLY6dOigVq1a6aOPPtLYsWPLVXGnTZumgIAA9e3b1+1zAQAAvPvuuxo9enSVe11KBAUF6dlnn9Ujjzyi/fv3VxrUSNK3336rb7/9tsbnXbBggcvDGknq37+/XnjhBS1cuFD9+/cvvX3hwoVKTU3VP/7xD5fPUB3CGt9mE3trAHipmTNnKisrq8r7Bw8erF9++UVbt26t8pgWLVooLCxM48ePd8WIkqQZM2YoJCREGRkZ2r9/v3bs2KHNmzfr999/r/GxhmHo3//+twYMGKCBAwfqrbfeUkxMjF5//XUtWbJE999/f7U7b8oqKCgoXRZYVFRUujgvNTVVv/32m5KSktSuXbvSr0UBAADf9s033yg/P18ZGRnat2+fduzYocTERM2ZM8euxwcFBdUY1JQVERFRaVDTqFEjl3w1av369frPf/6j7OxsHT58WLt27dLWrVvt3l3z8MMP691339Xw4cNVr149XXbZZVqzZo2GDx+uRo0aafjw4XbPkpycXLqXJjs7W8ePH9fx48e1Z88eJSUlKSkpSYmJiQ79foQ1Psw0zZSTl0BrUbLDBgC8RdlPVH744QfFxcUpISGh9LaSxW+OLKr7+OOP9fHHH+u1115Ty5YtnTLnE088oZCQEMXHx6tJkyZKSEjQ008/XeXCulPdeuut2rt3r5555hktXLiw3O2TJk2ye47jx4+rS5cuFW4PCgpSQkKCLrzwwhp36AAAAN/xt7/9rfSfw8PDdfbZZ+viiy9WTEyMhVM5z6effqrPP/9cUVFRaty4sVq2bKm+ffuqR48epVcSrU5cXJyWLl2qG2+8UT179iy9vUWLFvrss89Kdwva44knnqj09jPOOEMXXnihrrnmGrvPVYKwxvfZxCW8AXi5rl27qlevXlq0aFHpbc2aNXP4igK//vqrPv30Uz3zzDNVhjVRUVF2ffozffp0u753bY/HHntMAwYM0Lfffqvc3Fxdeumlat++vd2PnzZtmjIzM0v/HBwcrKioKEVHRys6Otru71sDAADvN3XqVGVkZMgwDAUHBysuLs7uCxZI0tGjR/Xll1/WaYZu3brp999/d+hS1ac6/fTTdeWVV1a4vXv37jW+V7MnrJGktm3b6tdff9U333yjP//8U82aNdNVV12l0NBQux5fcgnzEgEBAYqIiFB0dLRiYmLK7cJxFGGN77OJsAaAD5o5c6bVIzjVmWeeWesFx2eddZaTpwEAAN6qSZMmdXr8rl27dM8999TpHNOmTdP48eOVlJRU63NcccUVlYY1zhYaGqo+ffrU6rFxcXGKi4tz7kAnEdb4PpvYWwPAB6SkpGjy5Ml2HfvQQw9V2yb5+OOPS/e71OU8AAAAvuaSSy5Rfn5+nc4RGBio22+/XUVFRbU+R0BAQJ1m8HaENT6OvTUAfEVSUpLdC+MeeOABBQVV/RI3btw4p5wHAADAFznj/U9ISIgTJvFfhiu2MsOzGIYxXZLNNM3pFo8CABWEhoaa6enpdn83GO6Rm5urmJgY5ebmUi0CAMCDNGjQYMGUKVNuGDBggNWjwAXmzZunhx566HP/7hX5D5uK99YAAAAAAAAPR1jjH2wirAEAOIDmLQAAgPuVvAcjrPEDJbtqDMNoYe0kAFBRYGCgsrOzrR4Dp8jOzlZgYKDVYwAAgFMUFRVl8d7Jd2VnZ6uoqCiLsMZ/2ES7BoAHCgsLK9i5c6fVY+AUf/zxh8LCwgqsngMAAJSXmZm5c8eOHbxG+6jffvutIDMz83fCGv9hE2ENAA+UnZ39w8cff2z1GDjFvHnzlJWVVfP1zQEAgFvl5eUtmDNnDtUaH2SapmbPnp2dl5e3gLDGf9hEWAPAA+Xk5Lz63nvvKSUlxepRcFJKSoref/995ebmjrV6FgAAUMGmY8eOHZ83bx4L5nzMxx9/bKampqZJ2kxY4yfYWwPAU5mm+WVmZuaszp07a/ny5crPz7d6JL+Vn5+v5cuXq3PnzsrMzJxlmuZiq2cCAADlmaZpZmRkXDN06NC0SZMmmampqVaPhDpKTU3VpEmTzKFDh6ZlZGT0Mk3TNLjag/8wDGO6JJtpmtMtHgUAKggMDHw1Li5uRF5eXni7du3MuLg4BQTwmYI7FBUVKS0tTZs3bzZCQkKy09LS3iosLHza6rkAAEDVDMNIiI+Pfy0nJ+eqhISEvEaNGhkhISGG1XPBfnl5eebBgwfN5OTkkLCwsG9SU1OfMk0zWZIIa/yIYRh3S+pumubdFo8CAFUyDONCSddIaiCJNxzuYUo6Imm5aZpbrB4GAADYzzCMcEkXS6oviUs5epdCSUcl/WyaZrk9RIQ1fuTkV6Bspmm2sHgUAHAbwzCulDRV0m2maf7oAfM0kRRumuZvVs8CAADg6QzDiJQk0zQzrZ7FneiX+xH21gDwJ4ZhRBmG8R8VBzXDPCGoOek8SR8ahkFrCAAAoGbDT/74FcIa/2MTV4UC4ONOtmkSVfz1nramaa6weKSyvlbx17t6Wz0IAACAFwg++eNXCGv8j02ENQB8VCVtmodM08yweq6yzOLvH78o6UXaNQAAAKgMYY3/sYmwBoAP8vA2zakWi3YNAAAAqkBY42fYWwPA13hDm+ZUtGsAAABQHcIa/2QT7RoAPsDL2jSnol0DAACAShHW+CebCGsAeDFvbNOcinYNAAAAqkJY459sIqwB4KW8vE1zKto1AAAAqICwxg+xtwaAN/KFNs2paNcAAACgMoQ1/ssm2jUAvISPtWlORbsGAAAA5RDW+C+bCGsAeDhfbNOcinYNAAAATkVY479sIqwB4MF8vE1zKto1AAAAKEVY46fYWwPAU/lDm+ZUtGsAAABQFmGNf7OJdg0AD+JnbZpT0a4BAACAJMIaf2cTYQ0AD+CPbZpT0a4BAABACcIa/2YTYQ0Ai/l5m+ZUtGsAAABAWOPP2FsDwEq0aSqiXQMAAACJsAa0awBYgDZNtWjXAAAA+DnCGthEWAPATWjT1Ix2DQAAAAhrYBNhDQA3oE3jENo1AAAAfoywxs+xtwaAq9GmcRztGgAAAP9GWAOJdg0AF6FNUye0awAAAPwUYQ0kwhoATkabpu5o1wAAAPgvwhpIhDUAnIg2jVPRrgEAAPBDhDVgbw0Ap6BN43y0awAAAPwTYQ1K2ES7BkAt0aZxKdo1AAAAfoawBiVsIqwB4CDDMKJp07gW7RoAAAD/Q1iDEjYR1gBwwMk2zWbRpnEH2jUAAAB+hLAGkthbA8B+J9s0b4s2jdvQrgEAAPAvhDUoyybaNQCqUaZNUyTaNO5GuwYAAMBPENagLJsIawBUgjaN9WjXAAAA+A/CGpRlE2ENgFPQpvEotGsAAAD8AGENSrG3BkBZtGk8D+0aAAAA/0BYg1PZRLsG8Hu0aTwa7RoAAAAfR1iDU9lEWAP4Ldo0no92DQAAgO8jrMGpbCKsAfwSbRqvQrsGAADAhxHWoBz21gD+hzaN96FdAwAA4NsIa1AZm2jXAH6BNo1Xo10DAADgowhrUBmbCGsAn0abxvvRrgEAAPBdhDWojE2ENYDPok3jU2jXAAAA+CDCGlTA3hrAN9Gm8T20awAAAHwTYQ2qYhPtGsBn0KbxabRrAAAAfAxhDapiE2EN4PVo0/g+2jUAAAC+h7AGVbGJsAbwarRp/ArtGgAAAB9CWINKsbcG8F60afwP7RoAAADfQliD6thEuwbwKrRp/BrtGgAAAB9BWIPq2ERYA3gF2jSgXQMAAOA7CGtQHZsIawCPR5sGZdCuAQAA8AGENagSe2sAz0abBqeiXQMAAOAbCGtQE5to1wAehzYNqkG7BgAAwMsR1qAmNhHWAB6DNg1qQrsGAADA+xHWoCY2EdYAHoE2DRxAuwYAAMCLEdagWuytAaxHmwaOol0DAADg3QhrYA+baNcAlqBNgzqgXQMAAOClCGtgD5sIawC3ok2DuqJdAwAA4L0Ia2APmwhrALehTQMnol0DAADghQhrUCP21gDuQZsGzka7BgAAwDsR1sBeNtGuAVyGNg1ciHYNAACAlyGsgb1sIqwBnI42DVyNdg0AAID3IayBvWwirAGcijYN3Ih2DQAAgBchrIFd2FsDOA9tGrgb7RoAAADvQlgDR9hEuwaoE9o0sBDtGgAAAC9BWANH2ERYA9QKbRpYjXYNAACA9yCsgSNsIqwBHEabBh6Edg0AAIAXIKyB3dhbAziGNg08De0aAAAA70BYA0fZRLsGqBFtGngw2jUAAAAejrAGjrKJsAaoEm0aeDraNQAAAJ6PsAaOsomwBqgUbRp4Edo1AAAAHoywBg5hbw1QEW0aeBvaNQAAAJ6NsAa1YRPtGkASbRp4Ndo1AAAAHoqwBrVhE2EN/BxtGng72jUAAACei7AGtWETYQ38GG0a+BDaNQAAAB6IsAYOY28N/BVtGvga2jUAAACeibAGtWUT7Rr4Edo08GG0awAAADwMYQ1qyybCGvgB2jTwdbRrAAAAPA9hDWrLJsIa+DjaNPAjtGsAAAA8CGENaoW9NfBltGngb2jXAAAAeBbCGtSFTbRr4GNo08CP0a4BAADwEIQ1qAubCGvgI2jTwN/RrgEAAPAchDWoC5sIa+ADaNMApWjXAAAAeADCGtQae2vg7WjTAOXRrgEAAPAMhDWoK5to18AL0aYBqkS7BgAAwGKENagrmwhr4EVo0wDVo10DAABgPcIa1JVNhDXwErRpALvRrgEAALAQYQ3qhL018Aa0aQDH0K4BAACwFmENnMEm2jXwULRpgFqjXQMAAGARwho4g02ENfAwtGmAuqFdAwAAYB3CGjiDTYQ18CC0aQCnoV0DAABgAcIa1Bl7a+ApaNMAzkW7BgAAwBqENXAWm2jXwEK0aQCXoV0DAADgZoQ1cBabCGtgAdo0gGvRrgEAAHA/who4i02ENXAz2jSA29CuAQAAcCPCGjgFe2vgTrRpAPeiXQMAAOBehDVwJpto18DFaNMAlqFdAwAA4CaENXAmmwhr4CK0aQBr0a4BAABwH8IaOJNNhDVwAdo0gMegXQMAAOAGhDVwGvbWwNlo0wCehXYNAACAexDWwNlsol0DJ6BNA3gs2jUAAAAuRlgDZ7OJsAZ1QJsG8Gy0awAAAFyPsAbOZhNhDWqJNg3gNWjXAAAAuBBhDZyKvTWoDdo0gHehXQMAAOBahDVwBZto18BOtGkAr0W7BgAAwEUIa+AKNhHWoAa0aQDvRrsGAADAdQhr4Ao2EdagGrRpAJ9BuwYAAMAFCGvgdOytQVVo0wC+hXYNAACAaxDWwFVsol2DMmjTAD6Ldg0AAICTEdbAVWwirIFo0wC+jnYNAACA8xHWwFVsIqzxe7RpAL9BuwYAAMCJCGvgEuyt8W+0aQD/QrsGAADAuQhr4Eo20a7xO7RpAL9FuwYAAMBJCGvgSjYR1vgN2jSAf6NdAwAA4DyENXAlmwhr/AJtGgAn0a4BAABwAsIauAx7a3wfbRoAZdGuAQAAcA7CGriaTbRrfBJtGgBVoF0DAABQR4Q1cDWbCGt8Cm0aANWhXQMAAFB3hDVwNZsIa3wGbRoAdqJdAwAAUAeENXAp9tb4Bto0ABxBuwYAAKBuCGvgDjbRrvFatGkA1BLtGgAAgFoirIE72ERY43Vo0wCoC9o1AAAAtUdYA3ewibDGq9CmAeAktGsAAABqgbAGLsfeGu9BmwaAM9GuAQAAqB3CGriLTbRrPBptGgAuQrsGAADAQYQ1cBebCGs8Em0aAK5EuwYAAMBxhDVwF5sIazwObRoAbkK7BgAAwAGENXAL9tZ4Fto0ANyJdg0AAIBjCGvgTjbRrrEcbRoAFqFdAwAAYCfCGriTTYQ1lqFNA8BKtGsAAADsR1gDd7KJsMYStGkAeAjaNQAAAHYgrIHbsLfG/WjTAPAktGsAAADsQ1gDd7OJdo1b0KYB4KFo1wAAANSAsAbuZhNhjUvRpgHgyWjXAAAA1IywBu5mE2GNy9CmAeAlaNcAAABUg7AGbsXeGtegTQPAm9CuAQAAqB5hDaxgE+0ap6FNA8BL0a4BAACoAmENrGATYU2d0aYB4M1o1wAAAFSNsAZWsImwpk5o0wDwEbRrAAAAKkFYA7djb03t0aYB4Eto1wAAAFSOsAZWsYl2jUNo0wDwUbRrAAAATkFYA6vYRFhjF9o0AHwZ7RoAAICKCGtgFZsIa2pEmwaAn6BdAwAAUAZhDSzB3prq0aYB4E9o1wAAAJRHWAMr2US7pgLaNAD8FO0aAACAkwhrYCWbCGtK0aYB4M9o1wAAAPwPYQ2sZBNhjSTaNABwEu0aAAAAEdbAQuytoU0DAGXRrgEAAChGWAOr2eSn7RraNABQKdo1AADA7xHWwGo2+VlYQ5sGAKpGuwYAAICwBtazyY/CGto0AGAX2jUAAMCvEdbAUv6yt4Y2DQDYj3YNAADwd4Q18AQ2+XC7hjYNANQK7RoAAOC3CGvgCWzywbCGNg0A1B7tGgAA4M8Ia+AJbPKxsIY2DQA4Be0aAADglwhrYDlf2ltDmwYAnId2DQAA8FeENfAUNpVp1xiG0cIwjHqWTVMLtGkAwCVo1wAAAL9DWANPsVXSsHr16n0SHR19OCAg4I/AwMAHrR7KHrRpAMB1aNcAAAB/RFgDyxiGcWNJOFO/fv1RN91002UTJkzon5iY2OCyyy5LLyws/MXqGSXJMIwq/3dCmwYA3IJ2DQAA8CtBVg8A/xUTE/PU+eef33HmzJkBLVq0UMkHpkVFRdq4cWOopPXWTigZhtEzNDR0hmEYbU3TPFbm9mhJr0m6RsVtGkIaAHAR0zRNwzBeVHG7ZsnJtg0AAIDPolkDy6Snp/fdtGnToXXr1pllm+3JyckKCgo6ZppmqoXjyTCMoJiYmKkdO3ZsFBsb+16Z22nTAID70a4BAAB+g7AGljFN83BGRkaP++67L2PNmjWlt69bt04BAQGrLRxNkhQcHHxf+/btT/vqq68CY2NjewUEBNzKbhoAsAa7awAAgD8hrIGlTNPcnp2d3fe6667L3LlzpyTp+++/z0pLS/vWyrkMw4gLCQl55e23344MCwvTvHnzIsPDwz+SFCzaNABgFdo1AADALxDWwHKFhYW2rKysET169Mg8duyYbDZbkWma66ycKTo6esygQYNCzjvvPElS586ddd999xXGxsbG0qYBAGvQrgEAAP7CYEcfPEV0dPSrrVu3fmzbtm1mbm5uuGmahVbMYRhGm+jo6I27du2KqF+/funtOTk5SkhIyNy7d+/AwsLCL62YDQD83cmQ5idJL5imudjqeQAAgGsZhjFSkkzTHGP1LO5EswYeIyMj45nff/89MSQk5KhVQY0kxcXFvffSSy+F169fX6ZpKjU1VRs3btTSpUvVvXv3yJNXhwq1aj4A8Ge0awAAgD+gWQOPYhhGiKQmpmn+YdHz3yVperdu3fL27duXc+DAgTDDMPLCw8MPBAQE7MzKytqelZWVJGm6aZoFVswIAP6Odg0AAP7DX5s1hDVAGYZh9JDUR9IKSSmSdpummWnpUACACgzDuE7SC5I6mryZAQDAZ/lrWBNk9QDwDCc/pTxPUjNJ4RaPY7W1ksIknSPpnGpa9tmS/pT0K39RAAC3W6zir0P1PvnPAAAAPoOwxs8ZhhEcGRn5UnR09JCYmJiIhISEwsjISIM9ANUzTdPMzMw0k5OTA9PT0zOjoqKmZWZmvmCaZr7VswGAPzBN0zQM40UV765ZQmgOAAB8CWGNHzMMIzgmJuaLrl27Xj5u3LiI888/3+qRvFJSUlL0k08++ciaNWs6GIbRl8AGANyGdg0AAPBJXA3Kj4WGhj7VuXPnyxcuXEhQUwfnn3++Fi5cGNG5c+fLQ0JCnrR6HgDwF1wZCgAA+CrCGj8WHh4+bMyYMRHBwcFWj+L1goODNXr06IiIiIhhVs8CAH5msSRDxe0aAAAAn0BY46cMw2geGBh42iWXXGL1KD7j0ksvVUBAwOmGYTS3ehYA8Be0awAAgC8irPFfZzZv3jzfk97Xzp07V2vWrLF6jFozDEPNmzfPl3Sm1bMAgJ+hXQMAAHwKC4b9V1h4uHuu0L1+/foKtzVt2lRnnlk+0xg4cKBuvvlmde3atcZzpqenq6ioqMLtRUVFKioqUlRUlMLCwiRJq1at0ogRIzRq1Cj17du33PG//vqrduzYUe1zFRUVqbCwUJdffrkaNmxY7bERERFS8WW/AQBuwpWhAACAryGsQZVyc3P19ttv2318x44dddlll1W4vUuXLhVuGz16tEaOHFnr2Vq2bKmjR49Wef/ixYvVu3fxB6zHjx/X5s2bdezYsQrHzZw5U6+++mqV5zEMQ6ZpKioqSlu2bKn1vAAAl+PKUAAAwGcQ1qBK2dnZ+sc//mH38WPGjKk0rFm1alWF25o3r9tal/fff1+5ubmlfw4MDFRoaKhGjRqlX375RR06dLDrPKNGjSoXGhmGocDAQAUFBWn79u26/vrrdeDAAc2bN08tWrSo08wAANehXQMAAHwJYQ2qFBcXp/z8/BqP27Ztm9q2bavo6OhytycmJmr//v0VjjdNUxs3btTevXsrbd3Y48Ybb6xwW3p6ugYNGqT/+7//U+PGje06T0hIiEJCQsrdlpOTo3Hjxmn06NGKj4/XypUr1alTp1rNCQBwK9o1AADAJxDWoFpBQTX/J1Ly9aL69euXu/21117TnDlzqnzcAw88UOuwpjKvvvqqTpw4oeeee65Wj9+7d6+mT5+uKVOm6ODBg5Kktm3b6tChQyoqKlJAAPu4AcCT0a4BAAC+gr99os4OHz4sSWrUqFG529944w3t2rVLKSkp2r17t/bs2aODBw+W7ojp3r2702ZYuHChXn31VQ0cOFDXXHONmjRpIsMwZBiGrr/++kofc+DAAS1cuFDPP/+8unTpombNmunFF19Ut27dtGnTJi1atEgZGRnq27evWrdurccee0xLlixRRkaG0+YGADgdV4YCAABej2YN6qwkrDn1q0cNGjRQgwYNKhz/8ccfKz4+Xtddd12F+7KyspSSkiJJCg8Pr/HqS6ZpauLEiXrmmWfUuXNnvf/++5KK9+eUhCpJSUl65513Kjz29ttvl81mU0hIiC677DKNGzdOt99+e+nv0a5dO/Xu3VtLly7V+++/rylTpmjixIlatGiR+vTpU8O/FQCAFWjXAAAAX0BYgxoVFRVpxYoVat68uc4++2xlZWVp7dq1SkhIUNOmTbV//34ZhqGzzjqrxnPNmDFDP//8s0aPHq3IyMgK9y9durT0PD179tQ333xT5UxLlizRv/71L23cuFH9+/fXjBkzSi6drbvvvrv02EWLFlUa1syaNUsHDx7UBRdcUHqZ71MZhqHevXurd+/eysjI0KZNm9StW7caf08AgKXYXQMAALwaYQ1qlJeXp7/97W96/PHHNX78eP3555/629/+pokTJ+rRRx/Vtm3b1LhxY4WHh1d7nu3bt+vhhx9WUFCQ7r///kqP6dKli5566ilJ0umnn17pMW+88YYmTZqklJQUNWvWTLNmzdKgQYPs/n3279+vL774ovTPGzZssPuxkrR161Y1a9as9NLgAADPQrsGAAB4O8Ia1NnWrVt1/vnnV3vMzp071bt3b2VlZamgoEBDhw7VZ599VmGB8RlnnKEbbrih2nNdcsklat26tV566SXddtttFa7mdKrw8HCdeeaZpU2eHTt26MEHH6z5F6vGNddcQ1gDAJ5tsaQXJPWRtMjiWQAAABxCWIM6OXLkiJKTk6sNWNauXat+/fopPT1dn332mTZt2qR//etfuuWWWzRr1ixFRUU59JzdunXT119/Lal4X05ubm61xyckJGj9+vWqV6+epOLFxnzICgC+7ZR2zWLaNQAAwJsQ1qBOQkNDtWrVKrVu3brCfXl5eXrjjTf0wgsvKDo6WsuXL1f37t11/fXX6/jx45owYYIuvfRSffLJJ7rgggtq9fw33nij1qxZY9ex06ZNK7fLpkRubq5mzZqlhQsXasuWLTp06JDy8vJKGzkXX3yx7rjjDpo0AOB9lojdNQAAwAsR1qBOoqOjK124+8MPP2jQoEH6/fff1atXL73//vtq0qRJ6f3jx49Xy5Yt9eijj2r+/Pm1DmtKZvjvf/9b5f0///yzxo4dW+l9R44cUc+ePbVt2zbdc889uueee9SiRQuFhYUpIyND27dv17x589SnTx/dfvvtmjVrlgICuOI9AHgDdtcAAABvRViDCn744Qdt27at9M/5+fmSpG3btmn27Nk6cOCAJOnHH3/U9OnTKz3HzTffrE6dOumVV15R//79Kz3m73//u3r16qWWLVvWad6QkJAqn0NSlVd6kqRx48YpMTFRM2bM0ODBgyvc37FjRw0ePFj33HOPpk+frjvvvFO9evWq07wAALeiXQMAALwOYQ0qmDVrlqZMmVLh9iVLlmjJkiWlf/7oo4/00UcfVXqOu+++W7Nnz67xueoa1NTV0aNHJUkNGjSo9riS+48cOeLymQAAzkO7BgAAeCPCGlQwefJkTZ482eox7JaTk6N33nmnyvu3bNlS5X3333+/Zs+erXvuuUfPPfecrr76arVo0UKhoaHKyMhQcnKyPvnkE02aNEnNmzdX3759XfErAABci3YNAADwKoQ18HqZmZm1vhT3pZdeqlWrVum5557T448/rsLCwgrHRERE6Pbbb9crr7yimJiYuo4LAHAz2jUAAMDbENbAY9TmvfPq1avr/LyXXnqpvv76a6WlpSkpKUkHDx5UXl6eIiIi1KRJE11wwQUKDQ2t8/MAACxFuwYAAHgNwhrgpLi4OHXt2tXqMQAALkC7BgAAeBOuQQwAAPxFyZb83pZOAQAAUAPCGv+Vk52dbfUMPicrK0uScqyeAwBQ0ck2zYsqbtcYFo8DAABQJcIa/7Vv9+7dwbTAncc0Te3evTtY0j6rZwEAVIl2DQAA8HiENX7KNM3dhYWFhzds2GD1KD7jp59+UlFR0SHTNHdbPQsAoHK0awAAgDcgrPFj2dnZU0eOHJmVn59v9SheLz8/X//85z+zsrKyplo9CwCgRrRrAACARyOs8WO5ubmvrV+//vt+/fplJSUlWT2OVzJNU1u3blW/fv2y1q9f/31eXt44q2cCAFSPdg0AAPB0BjtL/JthGMEREREvBgYGDomJiYls06ZNYVRUlMGb1+qZpmlmZGSYO3bsCExPT88sLCz8b1ZW1oumaVJTAgAvcPJ17kdJL5qmudjqeQAAQOUMwxgpSaZpjrF6FncirIGk0jet50lqKinC4nG8RZakPZJ+NfkfEgB4HcMw+qi4YdOR/x8HAMAz+WtYE2T1APAMJ9+kJp388SiGYURKkmmamVbPAgDwKUtUHNb0lkS7BgAAeAx21sAbDD/5AwCA07C7BgAAeCrCGniD4JM/AAA4G1eGAgAAHoewBgAA+C3aNQAAwBMR1gAAAH9HuwYAAHgUwhoAAODXaNcAAABPQ1gDAABAuwYAAHgQwhoAAOD3aNcAAABPQlgDAABQjHYNAADwCIQ1AAAAol0DAAA8B2ENAADA/9CuAQAAliOsAQAAOIl2DQAA8ASENQAAAOXRrgEAAJYirAEAACiDdg0AALAaYQ0AAEBFtGsAAIBlCGsAAABOQbsGAABYibAGAACgcrRrAACAJQhrAAAAKkG7BgAAWIWwBgAAoGq0awAAgNsR1gAAAFSBdg0AALACYQ0AAED1aNcAAAC3IqwBAACoBu0aAADgboQ1AAAANaNdAwAA3IawBgAAoAa0awAAgDsR1gAAANiHdg0AAHALwhoAAAA70K4BAADuQlgDAABgP9o1AADA5QhrAAAA7ES7BgAAuANhDQAAgGNo1wAAAJcirAEAAHAA7RoAAOBqhDUAAACOo10DAABchrAGAADAQbRrAACAKxHWAAAA1A7tGgAA4BKENQAAALVAuwYAALgKYQ0AAEDt0a4BAABOR1gDAABQS7RrAACAKxDWAAAA1A3tGgAA4FSENQAAAHVAuwYAADgbYQ0AAEDd0a4BAABOQ1gDAABQR7RrAACAMxHWAAAAOAftGgAA4BSENQAAAE5AuwYAADgLYQ0AAIDz0K4BAAB1RlgDAADgJLRrAACAMxDWAAAAOBftGgAAUCeENQAAAE5EuwYAANQVYQ0AAIDz0a4BAAC1RlgDAADgZLRrAABAXRDWAAAAuAbtGgAAUCuENQAAAC5AuwYAANQWYQ0AAIDr0K4BAAAOI6wBAABwEdo1AACgNghrAAAAXIt2DQAAcAhhDQAAgAvRrgEAAI4irAEAAHA92jUAAMBuhDUAAAAuRrsGAAA4grAGAADAPWjXAAAAuxDWAAAAuAHtGgAAYC/CGgAAAPehXQMAAGpEWAMAAOAmtGsAAIA9CGsAAADci3YNAACoFmENAACAG9GuAQAANSGsAQAAcD/aNQAAoEqENQAAAG5GuwYAAFSHsAYAAMAatGsAAEClCGsAAAAsQLsGAABUhbAGAADAOrRrAABABYQ1AAAAFqFdAwAAKkNYAwAAYC3aNQAAoBzCGgAAAAvRrgEAAKcirAEAALAe7RoAAFCKsAYAAMBitGsAAEBZhDUAAACegXYNAACQRFgDAADgEWjXAACAEoQ1AAAAnoN2DQAAIKwBAADwFLRrAACARFgDAADgaWjXAADg5whrAAAAPAjtGgAAQFgDAADgeWjXAADgxwhrAAAAPAztGgAA/BthDQAAgGeiXQMAgJ8irAEAAPBAtGsAAPBfhDUAAACei3YNAAB+iLAGAADAQ9GuAQDAPxHWAAAAeDbaNQAA+BnCGgAAAA9GuwYAAP9DWAMAAOD5aNcAAOBHCGsAAAA8HO0aAAD8C2ENAACAd6BdAwCAnyCsAQAA8AK0awAA8B+ENQAAAN6Ddg0AAH6AsAYAAMBL0K4BAMA/ENYAAAB4F9o1AAD4OMIaAAAAL0K7BgAA30dYAwAA4H1o1wAA4MMIawAAALwM7RoAAHwbYQ0AAIB3ol0DAICPIqwBAADwQrRrAADwXYQ1AAAA3ot2DQAAPoiwBgAAwEvRrgEAwDcR1gAAAHg32jUAAPgYwhoAAAAvRrsGAADfQ1gDAADg/WjXAADgQwhrAAAAvBztGgAAfAthDQAAgG+gXQMAgI8grAEAAPABtGsAAPAdhDUAAAC+g3YNAAA+gLAGAADAR9CuAQDANxDWAAAA+BbaNQAAeDnCGgAAAB9CuwYAAO9HWAMAAOB7aNcAAODFCGsAAAB8DO0aAAC8G2ENAACAb6JdAwCAlyKsAQAA8EG0awAA8F6ENQAAAL6Ldg0AAF6IsAYAAMBH0a4BAMA7EdYAAAD4Nto1AAB4GcIaAAAAH0a7BgAA70NYAwAA4Pto1wAA4EUIawAAAHwc7RoAALwLYQ0AAIB/oF0DAICXIKwBAADwA7RrAADwHoQ1AAAA/oN2DQAAXoCwBgAAwE/QrgEAwDsQ1gAAAPgX2jUAAHg4whoAAAA/QrsGAADPR1gDAADgf2jXAADgwQhrAAAA/AztGgAAPBthDQAAgH+iXQMAgIcirAEAAPBDtGsAAPBchDUAAAD+i3YNAAAeiLAGAADAT9GuAQDAMxHWAAAA+DfaNQAAeBjCGgAAAD9GuwYAAM9DWAMAAADaNQAAeBDCGgAAAD9HuwYAAM9CWAMAAACJdg0AAB6DsAYAAAC0awAA8CCENQAAAChBuwYAAA9AWAMAAABJtGsAAPAUhDUAAAAoi3YNAAAWI6wBAABAKdo1AABYj7AGAAAAp6JdAwCAhQhrAAAAUA7tGgAArEVYAwAAgMrQrgEAwCKENQAAAKiAdg0AANYhrAEAAEBVaNcAAGABwhoAAABUinYNAADWIKwBAABAdWjXAADgZoQ1AAAAqBLtGgAA3I+wBgAAADWhXQMAgBsR1gAAAKBatGsAAHAvwhoAAADYg3YNAABuQlgDAACAGtGuAQDAfQhrAAAAYK8K7RqjWFOL5gEAwCcZxR+SAJ7DMIyE+Pj4fwcEBARIUkFBQYIkBQUFJUtSUVFRUWpq6nOmaSZbOScAAP7IMIw+Km7YdJTUOzY2dkJmZmaz/Pz8CGsnAwD4gpN/HxxT5u+D50hSUFDQdkkqLCwsSktLe940zR1WzulqhDXwOIZhnBUUFPTbf/7zn8CYmJhy96Wnp+vBBx8sLCwsPNs0zV0WjQgAgN86+RWo5JiYmPAzzjgj9tVXX42++eabC/Lz84Otng0A4P0Mw2gZFBT025QpUwKio6PL3Zeenq7hw4cXFhQUtDFN8w+LRnSLIKsHAE5lmuau+Pj4j//6669b7r333nL/jY4ePbogKirq47S0NIIaAADc6GRI0zs2NnZCo0aNmowfPz68T58+4oM/AIAzmab5R1xc3MeHDx++5b777gsse9+YMWMKoqKiPklNTfXpoEaiWQMPZRhGy5iYmC179uyJKGnXpKenq0mTJtknTpw4n1YNAADuFRMTY4uPj+84ZcqU8D59+qhkx3BRUZFCQ0Np1gAAnKbk74N79+6NKGnXpKenq2nTplnp6ekX+nqrRmLBMDyUaZp/BAQELHzzzTcLSm6bNGlSQUBAwAKCGgAA3C87O3vK0aNHC//66y8+6QMAuJRpmn8YhvHFm2++WVhy25tvvlkQEBCw0B+CGolmDTxY2XaNJFo1AABYzDCM1tHR0Ut69+7dZOrUqeFRUVE0awAALlG2XWOapl+1aiR21sCDmab5R3x8/MJJkyYNME1TtGoAALCWaZq/G4bRdunSpf85//zzb128eHHkeeedZ/VYAAAfdHJ3zReTJk269eTfB/2mVSPRrIGHMwyjZXR09HZJOnHiRAJhDQAAniEoKGhAWFjY1Ndffz3qoYceKszPz+dDQACAU53y98FzCGsADxIdHb3BMAylp6dfYvUsAADgf05+LWplVlZW44KCAnYhAgCcLiYm5mdJSk9Pv9jqWdyJsAYezzCMEEkyTTPP6lkAAEB5hmGESXrSNM3RVs8CAPA9J19nZJpmjtWzuBNhDQAAAAAAgAfhu8U+wDCMcEmXSKonKdDiceCYQknHJG0wTTPb6mEAAO5nGEa8pPaS4iQZlg6DujIlpUnaZJpmqsWzAIDdDMMwJJ0nqZmkcIvH8RbZkv6U9KvpghYMzRovZhhGQnx8/LicnJyeCQkJeY0aNTJCQkJ4k+dF8vLyzIMHD5rJyckhYWFh36ampj5pmmay1XMBAFzPMIzu9evXH5OdnX1x27Ztc+rXr28EBgbyOu7FCgsLzaNHj5qJiYlh4eHhPx89enSkaZo2q+cCgKoYhhEcGRn5UkBAwJCYmJiIhISEwsjISONkeIMqmKZpZmZmmsnJyYHp6emZRUVF0zIzM18wTTPfWc9BWOOlDMM4LzIycvXLL78cN3jwYCM+Pt7qkVAHqampmjlzpvn888+nZWZmdjNN81erZwIAuI5hGNfGxsZ+MnXq1Mg+ffooPJwPMX1Jdna2Fi9erGHDhmUeP378FtM0l1o9EwCcyjCM4JiYmC+6du16+bhx4yLOP/98q0fySklJSXryySez1qxZ8316enpfZwU2hDVeyDAMIyoq6s+pU6eeOWDAABJPHzJv3jxz2LBhezMyMpq7okoHALCeYRjx4eHhe9esWRPRoUMHq8eBC23cuFFdu3bNys7ObsLXogB4mrCwsOevuOKK5xYtWhQRHBxs9TheLT8/X9ddd12WzWZ7OTc399/OOCeXWPRO7evVqxdLUON7br31ViM+Pj5OUjurZwEAuMwN1157bRFBje/r0KGDevXqVSSpn9WzAMCpwsPDh40ZM4agxgmCg4M1evToiIiIiGHOOidhjRcKCQm58Y477qAv7YMMw9CgQYPCQ0JCbrR6FgCAa9SvX3/Q7bffHmX1HHCPO+64I6p+/fqDrJ4DAMoyDKN5YGDgaZdcconVo/iMSy+9VAEBAacbhtHcGecjrPFCkZGRrdq0aePUK3ktWLBAK1ascOYpnWbu3Llas2ZNnc6xbt06zZ07V0VFRU6aynXOPvvsoMjIyNZWzwEAcA3TNJu2atXKqef05NdxT1VQUOCW9wUtW7aUaZrNXP5EAOCYM5s3b57vzD3Cvvxa9OWXX+qrr76q9hjDMNS8efN8SWc64zm5dLcXCggIiLB3EeHnn39e4baLLrpIzZqVf89w77336oILLtCVV15ZeltSUpLy8yvuRiosLFRBQYFatWqlBg0aSJIyMjIUHR2tu+66S9OnT7f/l6nEuHHj9O2332rZsmWSpIEDB+rmm29W165d7T7HzJkz9eGHH2rGjBlq2LChJk2apHnz5umGG25QWFiYJGnz5s06cOCAevXqVe6x2dnZWrlypVq1aqWzzz679PYnnnhCEyZM0K5du9SiRYsaZ1i6dKnWrFmjYcOG2XV8ifDwcAUEBETY/QAAgFcxTTPUHa/jkvTLL7/ozz//rPY5CgsLVVhYqKuvvlpxcXF2zeVqx48f1/3336/+/furf//+WrBggZ599lnNnDlTHTt2rPaxYWFhys3NLXdbbGys0tLSSv9cm/cta9as0UMPPaShQ4dqxIgRdv8u4eHhMk0z1O4HAIB7hHnra1FqaqoKCwurPSYwMFAlF+FZsWKFhgwZovHjx6t///7VPq4qI0aMUIMGDXT11VdXe1xERIQkhdXqSU5BWOPjbryx4rdppk2bprvvvrvGx/bs2VN//fVXlfevWLFCPXr0cGiebdu2KTm58itTd+vWTQ0aNNDmzZu1fPnyKs+Rnp6u77//vsLtBQUFioqK0lVXXaUdO3Zo+fLlys7OrvI8r7zyiubNm6dT9/j+9ddfuvbaa/X8889rzJgxdv5mFX3wwQf69NNPNXDgQIcex1XyAAAl6vI6LklvvvmmZsyYUeX9hmHINE01btxYSUlJds+1cOFCHT582K5jL7roIl100UXlbmvQoIGOHj1a4di3335bDzzwgLKzszVv3jydc8456t+/v44fP67k5GRlZWXV+HyJiYkVGjOBgYF2zVqdzz77TJs3b9YZZ5zh0ON4XQfg7TzttahDhw7avXt3tce0atVKv//+uyQpKytLu3fvVkZGRun9hw4d0tq1ayt9bEFBgQoKCtSzZ0+ddtppNc7jKoQ1Pm7Xrl0Vbitpw9RkyZIlysvLk2EYMgxDwcHBCggIUI8ePZSbm1vjJ1uVmTNnjl5++eVK7/vuu+/UvXv3Gs/xxx9/6Prrr6/0viuvvFJXXXWVw3M52/79+7VkyRLFxcXp3HPPtXocAICXqsvruCS9++67mjx5cumfS17TAwMDtWHDBg0YMEC5ublavHhx6SeQ9hg9erR+/vlnu4594YUXKoQ1knTOOefo+eefL3dbp06d7J6hrLVr1+q///2v3fM48rtK0urVq/XWW29JKr7C08033+zwjADgrTzttei///1vjeF9YGCgNm3aVOX8v/zyS6UhVFnJycmENXC+tWvXaseOHZXeV1hYqLi4uBrfaFT2xuqjjz5Samqqhg4dqsjIyFrPl5SUVFqbmzdvnoYNs39p9oUXXqjU1P9d/TIwMFBFRUWKj49Xo0aNHJ5l+/bt5f68b98+SdK3336rnJyc0ttXrlxp1/ny8vI0ePBgZWdnKzs7W88//7xeeeUVh+cCAPgvZ7yOS1JoaKhCQ8t/A+fgwYMaNWqU3n33XV100UX69NNPK1TZ7dGwYUOlpKRUef8vv/xS7VeYGzZsqEGD/rd3Ny0tTQUFBTpy5IiOHTvm0CypqanaunWrXceWfW23x6xZs/Tggw+qRYsWGjhwoF5++WX9/PPPmjhxos455xyHzgUA3sRTX4uuvPJK7dixQwkJCfr3v/+tZ599VpI0adIkPfroo0pMTJRhGLrwwgurPceBAwckFYdHAQEBCgwMVHBwsO68804tWbLEoVUWrkBY46P++9//6oMPPih3W8l/gPn5+Ro0aJDDnwodPHhQjz32mGJiYvTCCy/o+PHj6tmzpyQ5vKAvIiJCUVHFF8I49X+4NQkMDKzwPcZt27bJNE21bdvWoXNJqrL5snv37nI7e0pCnOocOnRIt99+u7799lu9/PLL2r9/v8aOHavExES99957OvNMp+yaAgD4OGe/jpumWdo+mTNnjkJDQ2UYhjIzM/XFF19o8ODBiomJcXjOkj1wlQkJCXHoXN26dXPoq1hl9enTR3369JFU/Lv+8MMPSkpKUl5enpo0aaIrrrii3O9XtgpfmezsbC1atEgTJ07UunXr1LdvX33wwQdq0KCBunfvrvvvv18XXHCBevXqpcGDB6t79+46/fTTazU7AHgqT34tKvl6a0FBQeltJX93CwoKUqtWrfTbb79JklatWqUhQ4aUe3xISEilH/SbpqmffvpJnTp1cvh1zNm4GpSPeu+995Sfn1/6U1BQoJycHHXv3l3BwcF68sknHTrf8ePH1bdvXx08eFCdO3dWkyZNFBgYqPbt26t9+/a1CkmcafXq1ZKkLl26OPzYn376qdzPF198IUkaMmSINmzYUPpz1113VXmOEydO6PXXX9e5556r1atXa/LkyXruuec0efJkvfXWW7LZbDr77LP1wAMPlNbxAAC+wTCMAMMwrjIMw2kfgjnjdfz777/XuHHjNGDAAJ1xxhnq1q2bvv/+e40aNUp79uzRpk2b1KZNGz3yyCNq3Lix+vTpo9dff1179uxx1q/hkNWrV+vw4cM6fPhwrUObbdu2qW3bturSpYuefPJJjR07Vv369dOZZ56p999/v8LxM2bMKK3jv/HGG5KKd9rFx8fr1ltvVWBgoBYtWqSFCxeWVv579OihLVu2aMqUKUpJSSn997t58+Za/+4A4AyGYbQ0DCPBWefz5NeioKDil9yyi4ZLwprg4GBlZ2eX/j2uqnZQZVavXq39+/fruuuus/sxrkJY46MCAgIUFBRU+pOamqp+/frp66+/1ltvveVQuPLrr7+qW7du2rBhg/r376+vv/5agwcPVnBwsKZOnaqpU6eW+w6is7zzzjt655137Dp23rx5atCgQYW69dKlSzV//nzt3bu3ysdecskl5X5K6nJ//fWXNm3aVPpz6NChCo89ceKEBg4cqDPPPFOPP/642rdvrx9//FEPPfRQ6THDhw9XYmKibrrpJk2dOlUdOnRQy5Yty32VCwDg1VpI+io6Onp3UFDQnc4IbZzxOv7pp59q1KhROnDggO677z798MMP+u2339S8eXM99dRTOu200/T555/rt99+01NPPaV9+/ZpzJgxCghw79vD3NxcHT58WCkpKVqxYoUWLVqkevXqOXwe0zR10003aefOnVqyZImOHTum3bt3a/fu3Tr33HN1//3366effir3mEsvvVQTJ07UxIkTdcUVV0gqvprJ+PHjlZycrFWrVpU2dsoKDQ3V/fffr61bt+r333/X8uXL1a5du9r9CwAAJ4mOjn46MDBwW3x8/ALDMOr8PU1Pfi2qqVmzZ88eDRw4UAMHDtTYsWPt/p3Hjx+v4ODgSpcn5+fna+/evdq7d68OHjxo9zlri69B+TjTNPXZZ59p+PDhOnjwoIKCgko3YZd8DakqRUVFeu+99/TYY4/JNE3NnDlTgwYN0owZMzR06FAlJSVp2rRpLntz8uCDD9p1XGJiolasWKEnnniiwtUe/v73v9f6+UuCqOpER0eradOmuv322zV48GBddtlllR7XqlUrzZ49W6+88oo+//xzRUREOLzcEADguc4888wT8+bNO+Ppp5+ekpiYODYoKOiZwsLCj0zTLKj50VWry+v4hAkTNHHixApveFetWqV3331Xjz76qBo2bKiWLVvqhRde0AsvvKC8vDy31b5XrlxZ7kpJhmHo9NNP10033aRevXo5fL5du3Zp+/btGjZsmK699trS25s2baqXX35ZV199tZYuXapLL7209L7zzjtPjz76qKTiq4XMnz9fktSoUSMlJiYqMTHR7uefP3++YmJiarysKwC4SkBAgPHaa68Zpmn2HTNmzNXx8fFfpaWlPWua5vaaH101T3wtqq5ZExQUpAsuuKD0qr+LFi2q8gI1ZX399df64osvNHz4cDVs2LDC/YmJiWratKmk8lebchXCGh918OBBffHFF3rjjTe0bds2XX/99aVBwb///W9NnTpVw4YN04gRI9S4ceNyj83Ly9OHH36o119/XVu2bNGFF16o2bNnlyand911lxo3bqyhQ4fq4osv1pIlS6oMKeqi5H9c1V3y0jRNPf744woPD9cjjzxS4f5ffvlFTZs21X333acFCxZUeo6S2nOJkqWG9913n0aMGFF6+4QJEzR9+vQKj3/ttddq+lVKNW3atNw5AQC+o2vXrlq9enX0mjVrousa2tTldfzw4cPauXNnlef+66+/JEmbN29WWlpapcc0bNhQZ511VrUzZmdnV/uhRnWXVf3222+Vn5+vgIAAhYWFKTY2Vqeddlrpm/OjR4/q4osvLr1MdoMGDXTxxRcrOjq6ynPGx8crMDCwdGFkWSV756q7qsehQ4d0yy23VHm/PRISEipcuAAA3CkiIkIPPPBAwIMPPhjx9ttv1ym08cTXogMHDmjx4sU6ceKEpOIr9JW8Fm3YsEFScTvm+PHjSkxM1NChQ+1aXHzgwAENGTJEDRs21IsvvljpMS1bttSrr74qSTWGVM5AWOODpk+friFDhsg0TV1xxRWaNGmSWrdurePHj+u5557T3XffrfHjx+uzzz6rNOAICgrSsmXLlJ2drbffflv33ntvhcbK1Vdfra1bt2ru3Lm6+uqra1zU5yoTJ07UN998o7Fjx1a6vDc+Pl4NGjSoNJmNi4tTw4YNK63FlaS7F1xwQelt9evXL3dMXb5TX6J9+/YVliWXZRjGHZKqf7cMALBavKTSbfllQ5unnnpqamJi4pSgoKCnCwoK3rbnZHV9HV+8eLHuueeeGp/ntttuq/K++++/v8avIqenp+vee++t+ReqREkr98SJE9q3b59OnDhR+sa7xOzZsyUVX7WxdevWmj17drVvuOPj4/XQQw/pzTff1IMPPqgBAwYoKipK69at0wsvvKCzzjpLt99+e5WPb9asmQ4fPlyr36dEySe9VTEM4ypJnev0JABQhcjIyA4l/xwREaHHH3884MEHH4z4z3/+02/MmDF9YmJikk+cONHNNM3jNZ3LU1+LkpOTy732LF++XMuXL5dUvPS+Xr16WrBggc444wy1bdtWHTt2rPErS4cPH1bv3r114MABff311xX+3lciPj5e/fv3r/F3chbCGh909913KzQ0VJ06dVLLli0lSTfccIMWLlyo7OxsnXnmmaXfz65MQECA5syZo4CAgGpbLbGxsbr//vslFf+fwbp169x6HfoPP/xQTz75pP72t7/p8ccfd/jxjuzEqczKlSvr/Ancd999p+7du9fpHAAAz1XSEnVEXV/Hb7jhBl1yySV1mrumnTEln16WyMnJUXh4uK655hotW7bM7udZvHixBg4caPfxNb1uTpw4URdccIE++OADzZo1q/RqUIMGDdLIkSMVGxtb5WMDAgJKlwivXr1aw4YN00svvaQBAwZU+Zh33nlHb7zxhj7//HMu4w3Ap3jqa1H37t0dfm397rvv1KpVq0qvNFWyW3T37t2aPXu2evToUet5nY2wxkc58sanMmWbNHPmzKnwaVdVEhIS1KpVqxqPmz9/fukbonXr1jk0m2maeuWVVzRy5EhddNFF+vjjj2v8JMsVrr322tLLwVVmyJAhWrVqVbXH1HQpb9M059R6QACAWxiG0VLSMJ1s16xZs0ZPPfVUxpYtW9KzsrJq9TWouryOx8XFVdnaPHHihI4ePaqCggJFR0fr9NNPr/aDGVe76qqrtGrVqhqPW7hwocaPH1/jcQEBAbr33ntrbPyEh4fr66+/Lv2a1akyMjKUnJxc48UAjhw5ouTkZOXk5NQ4mySZpvmNpG/sOhgAHBQXF9dM0iVS8R6ut99+u2jMmDE5kr46fvy4w1+D8pbXotWrV+uDDz7QDz/8oD179ig7O1uhoaFq1KiR2rdvr9tuu007duwotzcnKytLEyZM0JgxYxQTE6Mvv/yyVvvSXImwxseYplluyVKJoqIiSdKePXuUl5en9PR0HTlyRHv37q1003VZzz//fLXfOy/rrrvusiuNdPTS4WXdeOONWrhwoXr16qWPP/642u+v2+uyyy5TRkZGtYsEr7zySgUFBZV+KhcZGanWrVtXeXxERIQkVXsMAMB3OCOkccXr+LZt2zRx4kQtW7aswqVQw8PD1aVLF919990aNGiQ24Ob6OhotWjRosbjqqqkV6ZBgwY6evSoXcfeddddle6jK/Hjjz9Wu5eAy3UD8DQnQ4jSkKY2u2q86bVo5MiRevnll3XGGWfopptu0tlnn62oqChlZ2dr586dWrZsmW699Vb17t1bn3/+uYKDgyVJgwYN0oIFC9S3b19NmTJFTZo0sfs53YWwxsesXLmy2rCkTZs2koq/U12/fn01bty42u9vS1JKSkqNz5uRkWFXaDJmzBiNGTOmxuNqOkePHj308MMPO+1NZXp6eo17d3r37q3evXs75fkAAL5l37590ddee+3+2oY0JZz9Or506VL169dP55xzjv7973/rsssu05lnnqmgoCClpaUpKSlJH374oQYPHqyFCxeWXg2pMklJSRUufV2i5Aoc+/btqzb86N+/f7nwY9WqVfrb3/5W5fG1MXny5BqbLrm5uXrggQdqPNe0adM0bdo0Z40GAC5VVFRkPvXUU0XR0dFf1OUqUJ78WlTWb7/9ppdfflmXXnqpvv3220r/PjphwgQ98cQTev311zV79uzSPTrTpk3TiBEjPOprT6cirPExHTp0KFcnNgxDgYGBCgkJUWRkpKKiohQTE+OUNopVLrjggnKLfwEAsFiKpL+dOHFiZV0v1e3s1/ExY8YoPz9fixYtqrCct379+rr88st1+eWX69ChQ/r0009LrwJZmaVLl9bYjN26dWu1CyW7d+9eaVPl6aef1nXXXVfj71PVbGVVt6yyREZGht1hTXWfFo8dO1bPPvtsjecBAHc4ceLEq5ImpKam7qjLeTz5taisQ4cOSVK1Vws0DEPdunXT66+/rv3795feHhsb69FBjURY43NiY2PVrVs3q8fwSidOnNDkyZNrPO7SSy9Vp06d3DARAMAbmKZZJOlbZ5zL2a/jJfsCtmzZUuWVlLKysrRz504FBARUunyxxBNPPKEnnnjCabOVdfDgQbsueV1QUODWxfzfffddtS2dH374wW2zAEBNTNP8wxnn8eTXorI6duyoc889V++9956ioqJ0xx13qHXr1oqMjFRubq727Nmjr776Si+++KIiIyPrfHEYdyOsAU46duyYRowYUeNxzz//PGENAMArjBs3Tps3b9YNN9yga6+9Vt26dVOjRo0UFBSk9PR0JSUl6bPPPtOBAwc0ZswYNW/e3JI5Z8yYoRkzZtR43B133OHWsGbmzJmaOXOm254PAHyRq16LgoOD9d133+mRRx7RG2+8UeUi+q5du+qNN94o/fqWtzBqc0lJWKtBgwYLpkyZckN1l5KE95o3b54eeuihz48cOXKj1bMAAJyvXr16u9etW9csISHBLc934sQJTZs2TYsWLVJSUlLpFTiioqJ01llnqVu3bho6dKjat2/vlnn8TXJysrp06fLnsWPHrEnCAKAShmFc2bVr109Xr14d547nc/VrUXp6ujZu3FjualCnn3662rVrp8aNGzv3l6lGt27d0tasWXOzaZor6noumjUAAAA+LDo6Wg8//LAefvhhq0cBAPgpV78WxcTE6IorrnDJua0SUPMhANyJthsAAL6D13UAQG0Q1nihoqKirOzsbKvHgItkZ2erqKgoy+o5AACuYRhGLq/j/iM7O1uGYeRaPQcAnCKH1yLny8rKkqSqN9M7gLDGC2VmZu7csWNHnS4NCs/122+/FWRmZv5u9RwAANcwDGPPzp07rR4DbvLHH3/IMIw/rZ4DAE6xb/fu3cG0/5zHNE3t3r07WNI+Z5yPsMYL5eXlLZgzZw4xqA8yTVOzZ8/OzsvLW2D1LAAA1zh69OjsDz/8MMPqOeAec+bMyTh69Ohsq+cAgLJM09xdWFh4eMOGDVaP4jN++uknFRUVHTJNc7czzkdY4502HTt27Pi8efOIQX3Mxx9/bKampqZJ2mz1LAAAl/l82bJlxsaNG62eAy62ceNGLVu2LEDSQqtnAYBTZWdnTx05cmRWfn6+1aN4vfz8fP3zn//MysrKmuqscxLWeCHTNM2MjIxrhg4dmjZp0iQzNTXV6pFQR6mpqZo0aZI5dOjQtIyMjF4mfUQA8FmmaaZmZWXd0qNHj8z58+eLnQG+Jzs7W/Pnz1ePHj0ys7Oz+5umyZs1AB4nNzf3tfXr13/fr1+/rKSkJKvH8UqmaWrr1q3q169f1vr167/Py8sb56xzG/yd0HsZhpEQHx//Wk5OzlUJCQl5jRo1MkJCQgyr54L98vLyzIMHD5rJyckhYWFh36Smpj5lmmay1XMBAFzPMIzu9evXH52dnX3JhRdemFO/fn0jKCiI13EvVlBQYB49etTcsmVLWHh4+IajR4/+0zRNm9VzAUBVDMMIjoiIeDEwMHBITExMZJs2bQqjoqIMwzB4ParGyQKFuWPHjsD09PTMwsLC/2ZlZb1omqbTakqENT7AMIxwSRdLqi8p0OJx4JhCSUcl/WyaJh+tAoAfMgwjXlJ7SbGi9eztiiQdl7SJNg0Ab3IynDlPUlNJERaP4y2yJO2R9Ksrvhnx/23Vo8L680uAAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 700x210 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mglearn.plots.plot_grid_search_overview()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "매개변수 그리드:\n",
      " {'C': [0.001, 0.01, 0.1, 1, 10, 100], 'gamma': [0.001, 0.01, 0.1, 1, 10, 100]}\n"
     ]
    }
   ],
   "source": [
    "param_grid = {'C': [0.001, 0.01, 0.1, 1, 10, 100],\n",
    "              'gamma': [0.001, 0.01, 0.1, 1, 10, 100]}\n",
    "print(\"매개변수 그리드:\\n\", param_grid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.svm import SVC\n",
    "grid_search = GridSearchCV(SVC(), param_grid, cv=5, return_train_score=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target,\n",
    "                                                    random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=5, estimator=SVC(),\n",
       "             param_grid={'C': [0.001, 0.01, 0.1, 1, 10, 100],\n",
       "                         'gamma': [0.001, 0.01, 0.1, 1, 10, 100]},\n",
       "             return_train_score=True)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_search.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "테스트 세트 점수: 0.97\n"
     ]
    }
   ],
   "source": [
    "print(\"테스트 세트 점수: {:.2f}\".format(grid_search.score(X_test, y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "최적 매개변수: {'C': 10, 'gamma': 0.1}\n",
      "최고 교차 검증 점수: 0.97\n"
     ]
    }
   ],
   "source": [
    "print(\"최적 매개변수:\", grid_search.best_params_)\n",
    "print(\"최고 교차 검증 점수: {:.2f}\".format(grid_search.best_score_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "최고 성능 모델:\n",
      " SVC(C=10, gamma=0.1)\n"
     ]
    }
   ],
   "source": [
    "print(\"최고 성능 모델:\\n\", grid_search.best_estimator_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 교차 검증 결과 분석"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mean_fit_time</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>std_fit_time</th>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>param_C</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>param_gamma</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>params</th>\n",
       "      <td>{'C': 0.001, 'gamma': 0.001}</td>\n",
       "      <td>{'C': 0.001, 'gamma': 0.01}</td>\n",
       "      <td>{'C': 0.001, 'gamma': 0.1}</td>\n",
       "      <td>{'C': 0.001, 'gamma': 1}</td>\n",
       "      <td>{'C': 0.001, 'gamma': 10}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split0_test_score</th>\n",
       "      <td>0.35</td>\n",
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       "      <td>0.35</td>\n",
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       "    <tr>\n",
       "      <th>split1_test_score</th>\n",
       "      <td>0.35</td>\n",
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       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split2_test_score</th>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split3_test_score</th>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split4_test_score</th>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean_test_score</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std_test_score</th>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rank_test_score</th>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split0_train_score</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split1_train_score</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split2_train_score</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split3_train_score</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split4_train_score</th>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean_train_score</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
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       "    <tr>\n",
       "      <th>std_train_score</th>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
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      ],
      "text/plain": [
       "                                               0                            1  \\\n",
       "mean_fit_time                                0.0                          0.0   \n",
       "std_fit_time                                 0.0                          0.0   \n",
       "mean_score_time                              0.0                          0.0   \n",
       "std_score_time                               0.0                          0.0   \n",
       "param_C                                      0.0                          0.0   \n",
       "param_gamma                                  0.0                         0.01   \n",
       "params              {'C': 0.001, 'gamma': 0.001}  {'C': 0.001, 'gamma': 0.01}   \n",
       "split0_test_score                           0.35                         0.35   \n",
       "split1_test_score                           0.35                         0.35   \n",
       "split2_test_score                           0.36                         0.36   \n",
       "split3_test_score                           0.36                         0.36   \n",
       "split4_test_score                           0.41                         0.41   \n",
       "mean_test_score                             0.37                         0.37   \n",
       "std_test_score                              0.02                         0.02   \n",
       "rank_test_score                               22                           22   \n",
       "split0_train_score                          0.37                         0.37   \n",
       "split1_train_score                          0.37                         0.37   \n",
       "split2_train_score                          0.37                         0.37   \n",
       "split3_train_score                          0.37                         0.37   \n",
       "split4_train_score                          0.36                         0.36   \n",
       "mean_train_score                            0.37                         0.37   \n",
       "std_train_score                             0.01                         0.01   \n",
       "\n",
       "                                             2                         3  \\\n",
       "mean_fit_time                              0.0                       0.0   \n",
       "std_fit_time                               0.0                       0.0   \n",
       "mean_score_time                            0.0                       0.0   \n",
       "std_score_time                             0.0                       0.0   \n",
       "param_C                                    0.0                       0.0   \n",
       "param_gamma                                0.1                         1   \n",
       "params              {'C': 0.001, 'gamma': 0.1}  {'C': 0.001, 'gamma': 1}   \n",
       "split0_test_score                         0.35                      0.35   \n",
       "split1_test_score                         0.35                      0.35   \n",
       "split2_test_score                         0.36                      0.36   \n",
       "split3_test_score                         0.36                      0.36   \n",
       "split4_test_score                         0.41                      0.41   \n",
       "mean_test_score                           0.37                      0.37   \n",
       "std_test_score                            0.02                      0.02   \n",
       "rank_test_score                             22                        22   \n",
       "split0_train_score                        0.37                      0.37   \n",
       "split1_train_score                        0.37                      0.37   \n",
       "split2_train_score                        0.37                      0.37   \n",
       "split3_train_score                        0.37                      0.37   \n",
       "split4_train_score                        0.36                      0.36   \n",
       "mean_train_score                          0.37                      0.37   \n",
       "std_train_score                           0.01                      0.01   \n",
       "\n",
       "                                            4  \n",
       "mean_fit_time                             0.0  \n",
       "std_fit_time                              0.0  \n",
       "mean_score_time                           0.0  \n",
       "std_score_time                            0.0  \n",
       "param_C                                   0.0  \n",
       "param_gamma                                10  \n",
       "params              {'C': 0.001, 'gamma': 10}  \n",
       "split0_test_score                        0.35  \n",
       "split1_test_score                        0.35  \n",
       "split2_test_score                        0.36  \n",
       "split3_test_score                        0.36  \n",
       "split4_test_score                        0.41  \n",
       "mean_test_score                          0.37  \n",
       "std_test_score                           0.02  \n",
       "rank_test_score                            22  \n",
       "split0_train_score                       0.37  \n",
       "split1_train_score                       0.37  \n",
       "split2_train_score                       0.37  \n",
       "split3_train_score                       0.37  \n",
       "split4_train_score                       0.36  \n",
       "mean_train_score                         0.37  \n",
       "std_train_score                          0.01  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "pd.set_option('display.max_columns', None)\n",
    "# DataFrame으로 변환합니다\n",
    "results = pd.DataFrame(grid_search.cv_results_)\n",
    "# 처음 다섯 개 행을 출력합니다\n",
    "display(np.transpose(results.head()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scores = np.array(results.mean_test_score).reshape(6, 6)\n",
    "\n",
    "# 교차 검증 평균 점수 히트맵 그래프\n",
    "mglearn.tools.heatmap(scores, xlabel='gamma', xticklabels=param_grid['gamma'],\n",
    "                      ylabel='C', yticklabels=param_grid['C'], cmap=\"viridis\")\n",
    "plt.show() # 책에는 없음"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/pdf": 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22t/S+tiePQLVraAx21R796fwu4TSyNzS4mZL9RJCjAOwHMAIh3+qAlDssC4bwKdCiOuC2J8nAcwDkGizWgIoAFDnsPnJAFYKIfrAR63jpEUA7vCzq5owaEQPRMcqY4xfv93odVvHbUceE9oxRkyc/Z1pav2cvOQoLiEaJ04bbl3+4dM/UVcb/kUVmK1nasyWuXqmxlwBZusNNWbLXD1TY64As/WGWrMlItICdV9J0gghxCQAGwBcE6LnTwKwEsCRNqv3Avg3gKEAoqSUXaWUWQBSAJwPYKfNtgMBvNpJ3e1UvztcHBg70vvbb/bMi0BWhnJ7Esd9+Sq/sNluuV/vSBdbOhcTY0DXbKU/K13cDnTRV9XWx2NGRGPEEO+PWU30mK0eMFftYrbaxWy1SY+56uUcKlxxTBXehibbVyPZWL7P67aH6spwuKFK2VeIKlDP6jHO+ji/rgw/F/7lclstHK839Pha78w/7ilGSamlYuuFZydg0sQ4n547HOkxWz28jzNXbeYK6DNbf+0/pPRPCCAtJXwvj4zsal+ceO2hfK/bHqioRLFNde6RueFfcXvnYaVidq/UVMRFel+pPT4yEr1SU5V92VTf1gohRC6AL2C5g0+b+QD6SSkTpZSZANIA/AtA24ufAPCCEGJyEPpzHYBbbVYVAbgOQIKUsguAOFjuPLTIZpscAF8JIbwqid5aZXsWgL8AnBGIfqvZQIcKj3+v836MUXiwDKXFyhhj4PDQjjF69FO+ELtnewEa6psCst/JZ42yTmhqaWnB5++6/rJtOGG2nqkxW+bqmRpzBZitN9SYLXP1TI25AszWG2rNlsiRkNr8IW0L308mdUIIsRjAYgBtlQbMAO4D8GsndiMCQNun6IcB/BOWD/zullJukFJaP9GWUlZKKd8DcBQA2zIfZwohhnVWhzvLhr8arI+TEg3o19v7D4wB4KjhyoWSDX83uNnSs9Jy+1t3JiX6/ucbZ1P1a9fe9idyZrPEF4uVD/UvPsf7Cj1qo7ds9YK5ahez1S5mq016y1VP51DhiGOq8NcnIdv6uKqpDntrStxs3d7m8gNO99VZusamYlxGf+vywn0r0ALXn5ip/Xi9pbfXeme+XlKD9z6xXMBJTzXiqbnaqOart2z18j7OXLWZK6C/bP3V3Czxwy+11uUjB0QiKip8L4/0z0i3Pq6sr8fu0jKf2m8oKHC6r3D11Zat1sexkRG4fNRIr9teOXokYiKU3/sv/97qZmvVehlAqs3ydVLKq6WU1vGElLJUSvkILNWt2+7/LgC8JoQI2DfLhBB5AJ60WXUAwAQp5UtSyprWvkgp5Top5VkAHrfZth+Ah7x4jmgAawG8B0v1cMBSxXs2LF+Q1Z2e/ZVxQXVlHQ7u8W2MsW3jfpt9dQlYv3x1zJQjkZWj3GxqyWdrA7JfIQROv2CsdfnPZTt8/j8KFWbrnlqzZa7uqTVXgNl6otZsmat7as0VYLaeqDlbIiItCN9PJvVjjM3j9QDGSSkfgP3tszvLYgADpZTPSCnd3vtCSlkG4B8Oq6cHq2OhsmO3cnGgRzcThPDtjus9uykfGJeWtaC0zOxma/eiIu2fu7bO91+RfQeVqjL7Dza3+/d1mxqslcIA4MRjYq2Pt2xvxJy5xRhx0l4k992J2B470HPUbkw65wCef7UcxSXt9xfO9JatXjBX7WK22sVstUlvuerpHCpMcUwV5vLilMlC+XW+TToCLFWo2yRHxiIxIiYg/fLWud3HwigsH5/Um5vw6f7VbrdX+/F6S2+v9Y6qqltw3e1F1uUn56YjPc3opoV66C1bvbyPM1dt5groL1t/vbOwCgVFyrGdeapXRX9DpkdKsvXxgYpK1xu6sL9caZMSE4Ok6Cg3W4fe4m07sHyfMini+nFjMPPIQR7bzTxyEK45erR1edmeffh++043LdRHCDEewKk2q96TUr7kansp5XIAt9us6grghgB26R4AtieoV9hOIHfiTgC2Zfuua60g7k40LHcuavMzgOFSyld86qmG5HRPsz4uPOj7GKPggNImMTkW8UmdP8YYdnRv3PzAmdblQ3sP44sFganoePQJA5Cdq3y34fN3fw/IfjsDs3VPrdkyV/fUmivAbD1Ra7bM1T215gowW0/UnC0RkRaYQt0BAgBsBfAIgLellKGYXFAP4A4AT0gpfSm0vxhAFZTb8411s60qHchXLg7k5vhWrcbSxv5PbP+hZqSm+Hch17Gdbd+8sW1nIyqrlF8v24tXbWyr6qSlGNC3VyTq6lpw2wMlmPdWBVocfjv3HWzGvoPNWPJrHe574jDmzknFTVelQA30lq2jsooWXHNbIfKLzDhcakZ1TQuamiSSk4xISzVi+OAojB0VjROPiUVEhG8X/EKJuWozV4DZMlvXmG140luuejqHCmMcU4WxzOhE6+PC+gqf2zu2yYpOQmVTXYf75Y1YYyRO76pUfPwufz0qmmrdtFD38fpCb6/1ju58qAT7D1me56RjY3HRzEQPLdRDb9nq5X2cuWozV0B/2fqjrNyMux5WqobFxQpcfVFSQPYdLNkJysTygqpqn9sXVFfZLXdJSEBFfccqqtsa0iUbj06dhMy4OCRGRyEuMhJSSlTUN6C4pgbr8wuwav8BbCgo9HqfN372JV47ewaGdMmGyWDAI1MnYUr/vnhzzTqs3H8A9c2W36dokwmju+Xi0pHDcWyvHtb26w7l46bPvwzYMYaRG20emwHc5kWbVwDcDGBA6/L1QojHfRyrtCOESAZwoc2qb6WU37lrI6WUQohboEzejgBwDYC7vXjK1QAelFJ+7kd3NSU9S3nNKinwfYxRUmjfJiM7CdUVwR9jJKfFY+CI7jjh9GE4+oSBMBotX4gtK6nC/Te8hYa6wNxZYfpF46yPD+09jNW/bAvIfjsDs3VPrdkyV/fUmivAbD1Ra7bM1T215gowW0/UnC0RkRZw4nbonQRgTUc/MOsIKWU17G9X5207sxBiO4ARrasyA9qxEGtulqioVC4UdMn0/YJFlyz7Noc7ULFmUP9Iu+U16337oP3bpTV2yzW17eezbN6iFAXs3ycSNbUtmDLrIH5fVW9dHxkpkJluRGVVi92FlIrKFvzz3hL8ta0RLz6WCYMhfCeX6TFbR5VVLZj/jrNqPZaT/K++t+wzK8OIqy5Mwh03pCA2Nrxv0sBctZkrwGwBZusOsw0/esxVL+dQYYxjqjBmFAYk2FSMLqmvcrO1cyUN9q+TSRGxLrYMvNNyRyI+Itq6/MEe99VM1H683tLja72tX5fXYd5blgs3sTECLz+hnT9dPWarh/dx5qrNXAF9ZuuP6/+vyK7a9m3XpyArI3wvjRiFQGK0cv5RVFPjZmvniqrt2yTHBLYyXN/0NPRNT3P576cc0Q8AsK24BK+uWoNFm/7yuM+yunrMWvAhbp4wFpeMGI7oCBOO69UTx/XqiSazGYdrLRMk0mJjEGFUfm/rm5rx5p9r8exvf6DRHJjJ/uFCCBEL4HSbVYullAc9tWudLP0GgMdaV3UDMB7Abx3s0hmwVMNu87o3jaSUy4UQf0OZSD4L7iduVwIYJaVc408ntcZgNCA+UfkbLi32fYxRWmTfJjE5eGOMm+6fgVHH9EN8Ygxi4uyr/be0tOD37zfjpX9/4ddxONOjbxaGjultXf5iwR8I4ccDPmG27qk1W+bqnlpzBZitJ2rNlrm6p9ZcAWbriZqzJXJKtv5oidaOh9oJ71kfOiClXB3KCQYBUG/zOLzvL+mj8gr7CwMx0b7/uTi2cdynLzLTTejdQ6ma89m31aiv925/ZrO0XlRu09DY/tduu82tVVOSjbj29iLrBa2zTovHz5/monZPb+xd0xNl23pjx4oeuP2GFETYFPOZ/04lnviv77eZ6Ux6zNZfhcVmPPR0KYaesA+r19V7bhBCzNV7asoVYLa+YLbMNhzoMVe9nEOFK46pwlu8KdpuuaHFt8qbANBgtm9jOzE62M7prhRBX1u6B9uq8t1ur/bj9ZYeX+vb1Ne3YPacQrS96sy9LQ0983yvcBuu9JitHt7Hmas2cwX0ma2v5r1VgQ8+VSpWDz4iEnfckOqmReglRttfpK9v8v18wrFNYlSUiy2Dq19GOh4/ZTLePvcspMREe9y+0WzGEz//huPmvYaPNmyyro8wGpGdEI/shHi7SdsfbdiEia+8hid+/k1zk7ZbTQBgOzvkIx/aOm47pePdwSSbxw0AfKmEbduf3kKIPq42lFK2cNK2Ij7BYYxR73uFxYYG+zZxicEbY6RmJiKjS3K7CUcH95Zg7rVv4d//WBCwCUcAMP3i8dbHdTUN+G7R6oDtO9iYrXtqzZa5uqfWXAFm64las2Wu7qk1V4DZeqLmbImItIITt6mjutk8LnG5lQo5XhiIjva9uo5jm45ebDj/zATr49KyFjz2gncXj/7zchm27HA4qXRSrbO8XPlwe8v2Rry7sAoGA/Dq05n4cH4XTBgTAyGUY+qZF4FH7krHko9zERerrL/vicPYtrMR4UqP2QJASpIRF56dgMfvTcfXC3Kw/sc8HFjXE7V7eqNmd2/kb+yJXz7LxbMPZeDEY2NgEzV27W3CpHMPhvVkQeaqzVwBZsts3WO24UePuerlHIqCRrNjKgCINNhXs2xo8eMDcoc2EQbfq4n6Y3xGf3SPS7cuf7jXfbVtQN3H6ws9vta3efA/pdi607L9iCOj8I+rk33vbBjTY7Z6eB9nrtrMFdBntr5Yva4e/7y32LocGyPw7kvZiIwM3yrqABBptH/vd/xSlzcc20SaOn4+sbesHO+uXY97v1uCWQs+xMmvvoHRz7+M/k88gyFPv4BjXpqPSz5YiGd/+wNbiort2o7tnoe3zj0bydGeJ2+fckQ/vHnOmZg5ZLDHbWcOGYxXzpyOE3r38vu4wtx4h2XPJ6StpJS7ARS62VdH+7NWSulLWf3lbvZFbkRE2o8xmhp9f01oarBvExHR+Xcd6No9HQ/MuxSPv301+g/p5rmBFxKSY3H8acOsy0s+X4vaat/u9hBKzNY1NWfLXF1Tc64As3VHzdkyV9fUnCvAbN1Re7ZERFrBidvkNyHEINhPMlgVqr4EQ3Oz/UWKKD8+0I+Osm/T1NSxCx+zL05CfJyyz4eeLsU7H1e6aQG8+m4F/vXwYQDA8MHKt/MSE9r/+VdWKxVwdu6xXCj5v5tScdmsJLfPMX50DJ5+MMO63NQEPDu/3G2bUNJjtgAwdFAU3nw+G7dem4LJx8dh8BFR6JJlQlSUAdHRBmSmmzB+dAxuuCIZ332QixXfdMOQgcotbisqW3DBdQVeV0rqbMxVm7kCzJbZusdsw48ec9XLORQFntbHVABgFPZ/M00tvldCbHSYeGQSnTOR+VybatuF9RX4sXCzxzZqPl5f6PG1HgDWbWrAky9ZJiAajcC8JzNhNIb35D9f6TFbPbyPM1dt5groM1tvHS4145yr8tHQoBzPy09kYvARoak87Qujwf64/akk3dBs38Zk6PiloM/+2oL7vl+KBes2YPWBg9hdWobSujqYpURtUxPyq6qxbO8+PP/7cpz2xju48bMvUV6nfOl4QGYG7jlxosv9x0VG4OUZ0/DctFNxRKbl73BPWRke+OFHTHr1DQz+z/MY+swLOP2Nd/CfX5ehuLoGADCkSzZeOWs6Hps6CREBOM4wM8TmcQWAbT62X+liXz4TQiQDyHOxb2+scFjuUH/0xGhyGGP4Memo0aFapCkieH8rc699E6cM/Bdmjrkfs09/Gk/d+RFW/7oNLS2W9+YjR/XEU+/Oxunnj/WwJ8+mzjwKUdHKnR6+eNfr7zaEBWbrmpqzZa6uqTlXgNm6o+Zsmatras4VYLbuqD1bIgo9IYRBCDFNCLFACLFDCFEnhGgUQhwUQnwthJgthIj1vCe/n3+uEEJ28OekYPXPW5r7FIs61W0OywsDtWMhRKYQYpAvPwB6B+r5AcBk6vhFi0aHCjWmDn4Br0uWCU/OVS4etbQAl9xYiJlX5mPxjzUoKmlGY6PEoYJmLPqqGlNmHcTsOUVoaQFmzYjH2KOUiiZJTi58VNfY9zcrw4i7/pHiVd8uPy8RfXoqJ3cLFlXBbA7PO9brMVt/jBwajZ8/zcXIIcoFrR27m/DiGxVuWoUOc/WO2nIFmK23mG3bPjvUJWYbAHrMVS/nUBQUmh5TAYBZ2n/JxCR8f210rDjtuM9g6BGXgTHpyt3bF+5b4dXzqvV4faXH13qzWeKqWwrR3HqN5+arkjFiiOeqoWqjx2z18D7OXLWZK6DPbL3R0iJx4fUF2HtAuTA/57oUXHBWov8H1onMLfbv/f5MRo402rdx3Gdn+Gbrdpz77geoalAqt00fNACDs7PabWsQAi9MPw0n9VVOR19ZsRqTX30Tb/25DrtKy1Df3Iyaxib8XVSMF/9YiRPmv47PNv9t3f6sIwfhockhv+YWaH1tHu+RUvr6R77b5nGqECK1A33p47C82+lWLkgpSwHYfoujr6ttw0k4jKvMzfZ/v0Y/KuibHKpDOu4z0KSUqK6sx74dRfjhsz9xz9X/w+0Xz0dJgeWzLKPJiOvumYYJkzxX1nfFYDTgtPOOti7/+ft27NtZ1OG+dyZm65zas2Wuzqk9V4DZuqL2bJmrc2rPFWC2rmghWyIKLSHEQFgKUX0G4DxYxsDRACIA5ACYCuBlADuFENNC1U814MRt8osQYhyAi2xWrZZS/hLAp7gOwCYffz4L4PMjMsJ+ub7B9wsfjm0CcRvOqy5Mwr232n++uuirapxy/iF0OXI3YrrvQLfhuzHzynx8/3MtAODs0+Px+tNZKK9QTiR7dnc4QLQ/5kvOTURUlHcvE0IInDMt3rpcWdWC9ZvD83YqeszWX4kJRrzxXBZsrw8tWFgVsP0HEnP1nppyBZitL5gtsw0HesxVL+dQFFh6GFMBQJO0r/YYafB9NphjG8d9BsO5PcbB0DrpusHchE/2e1cMXa3H6ys9vtY/9VIZ/txoeX3umWfC/beldbi/4UiP2erhfZy5ajNXQJ/ZemPO3BJ891OtdXnKCbF45C71vG43me0nA0T5MZs+0uhwPmHu/InbALCztBSP/fSr3bppA/q32+6CYUNwTM8e1uUXfl+Ox3/+FWY385Trmppx61fftpu8fXzvnh3vePjItXm834/2BxyWO3Jv9VyH5Y72JzD3eQ++kI+rmpscxhhRfrwmOLRx3Gdn2LxmD+666nXU1zZa11179+ntqmF6a8KkQcjokmxd/vwd9VWKZLbOqT1b5uqc2nMFmK0ras+WuTqn9lwBZuuKFrIlckVIbf2Eo9Zrm8sBjHD4pyoAxQ7rsgF8KoS4LsjdqgKw04+fWmc760ycuE0+E0IkAHgD9r8/c0LTm+BJSrT/xp0/Fz7q6u3bJCcG5hbX981Jw8evdUHPPPcnl9HRAvfNScX787IRFWXA3v3KrVwG949st31sjP1LwqSJvt21YMxI+2pjm7Y0utgytPSYbUcM7B+FieNirMtrNzWgtCz8Jo8wV9+oJVeA2fqK2TLbUNNjrno5h6LA0cuYCgCqm+rtliONvk/AinJoU91U16E+eRJvisYpOcOsy9/nb0R5Y41XbdV4vP7Q22v99l2NuP+pUuvyi49lIjZWmx+p6S1bQB/v48xVm7kC+szWk6deKsOz88uty4P6R+K9l7NhMHR8Qnpnsa1QDQCRRt8ziXaoDFfZELovH3y6+W9UNyp/Q2O759n9u0EIzD56tHX576JiPPub95MH7vt+KQ7XKNfarh87pgO9DR9CCBOAJJtV+X7s5pDDcke+wZDusNzR/qjn2xQhVlPtMMbwa9KRwxijKjRjjH07ivDFAuXvOzUjEaOPO8KvfU27cJz1cf7+Uqz8aUuH+9fZmK1zas+WuTqn9lwBZuuK2rNlrs6pPVeA2bqihWyJKDSEELkAvgCQYLN6PoB+UspEKWUmLGP9fwGobmsG4AUhxOQgdm2RlLKPHz+/B7FPXungjQ9Jp16B/W3sXpFS/hyqzgRLZKRAQrwBVdWWaiRFJc0eWrRX7NAmLSVwF3ZnnBKPU0+Kw/e/1OLrH2qwfVcjikrMEALIy43AxLExOP+sBGRlWP7MzWaJtZuUD+gHHdH+wkdaqv1FgBFHRvnUp2459ieu4TiZDNBnth01YUwMlv6mDEQOFTYjNSUwF/IChbn6Tg25AszWH8w2MJitf/SYq17OoSigdDGmAoBmaUZ1cz3iTZYJcKmRcT7vIzUy3m65vCm4X4I/o9soxJqUv+MP93o/cUiNx+sPPb3WSykxe04R6lsnNl5wVgImTfQ9V7XQU7bW/ungfZy5ajNXQJ/ZuvPeJ1W448ES63JOthFfvZuDxITwGjN50tTSguqGBsRHWX5v02J9++KBszbldaH7Ilh9czM2FxRiTJ6lwHJWvP25zlG5XZGdoKx7c81a+PIVhOrGRnywYSOua52wPSynC7omJuJgZWWH+x5iyQ7L/oTo2MZxn75wbNvR/jjuj1xobjKjtroesfGWMUZSaryHFu0lp9mfv1aVh26M8eOX6zDzyuOsy4NGdMcfS/7yaR99B3XFoBE9rMtfvbcc0k2F/nDFbNvTQrbMtT0t5AowW2e0kC1zbU8LuQLM1hmtZEtEIfMyANtb7F0npXzJdgMpZSmAR4QQPwJYDCARlsnbrwkh+kspvauSpBOcuE0+EULcCGCWzaq/ANwShKd6EcBHPrbpjQDfgi63iwl/b7dUAzlwyPcLH/sO2rfJ6+rf7T1diYwUOPWkOJx6kueLxus3N6C2znLSJQRw7NEx7bbp1lV5SUiIN7Sr2uNJXKx95Rp/qvx0Fr1l21FZGfa/C9U1obm9qifM1TdqyRVgtr5itoHDbP2jt1z1dA5FHae3MRUAFNVXIr71A/Ks6CQPW7eXHWPfprCuPBDdcsoAgbPzjrYubyjbi78rD/q0DzUdb0fo5bX+h19q8fMfljlGaSkG/Of+jID2MxzpJds2enkfZ67azBXQX7auLP2tFpf/oxBt15wT4g344u2u6Bbg4+ksBVXV6NM6cbtLYoKHrdvLcWhzqLIqIP3yV7FNRey4SPtMhuV0sVv+fe8+n/f/+9591onbADA0J1sLE7cdv3FS73Qr9xzb+PYtFvdtO9qfjvSlM4XFuKqkoAJ5fSxjjIxs38cYGV2S7ZaL8isC0S2/7N5agKbGZkREWt6rs3JTPbRob/rF462P62sbsXjhqoD1r7MxW3tayZa52tNKrgCzdaSVbJmrPa3kCjBbR1rKlog6lxBiPIBTbVa95zhp25aUcrkQ4nZYJnsDQFcANwB4LHi9VB9O3CavCSHGAnjKZlUVgLOD8W0IKWURgCJf2ggR+Ntd9ukVYb3wsWe/7xc+9tjc2jMl2dCu2k9neu8T5cP5kUOikJvT/qJFj1xlXW1dC6SUPv2/VlTaTx4LtwqgtvSWbUfVO9w2Nz2Ex+sOc/WNWnIFmK2vmG1oMFuF3nLV0zkUdYwex1QAsL+mBL3iMwEAXWJSfG5v26aisRYVTcGrGHls1gB0jVU+9P7Ah2rbbdR0vB2hl9f6mlrlvfdwWQuyBu/y6zl+/qMOxi7b7dbde2sq7puT5tf+gkkv2bbRy/s4c9VmroD+snVm/eYGnHV5PhobLa/ZJhPw4fxsDBuslnmh7e0pK0efdMt7RG5ios/tu9q0Ka+rR3m9P3NsAyfapFyKKnOo/p0Vbz+pv7ja91PjQoc22fG+V9MLQ47X7xqcbuWeY/Ad+aAi0P1RxbcqwmVcdXDvYeT1yQIAZHX1fYxh26aqvDak1SIBoLK8FmmZltep2HjfXquT0+Jx7JQjrctLv1iL6srQvsZ1BLNVaClb5qrQUq4As7WlpWyZq0JLuQLM1pbWsiVqR7b+aEl4Hc+NNo/NAG7zos0rAG4GMKB1+XohxOOSpf6tAnffQ9I0IUQmLFUF2j5MawFwgZTy79D1KviGDlROdooPm+0uZHhj5Vrls0vbfXW2piaJBYuUCx/Tpzj/4Hr0CKWPZjOwc49vx9t2kahNTnb4XtTSW7YdtcPmd8FoBHKywvN7P8zVN2rJFWC2vmK2nY/Z2tNbrno6hyL/6XVMBQDbqwqsj1Oj4tElJtmn9oOSuzndVzDM6j7O+ri4vhJLCjb5vA81HW9H6O21Xk/0lq1e3seZqzZzBfSXraO9+5tw6gUHUVmlTLZ/+YlMTJroucJ3OPu7uNj6OC0u1m4itjeG5WRbH2+x2VeodE9Jtj52rP4dYbT/+4qN9H0+b2yEfRvHfaqU4zcx/JnoHOlhn74IdH860hfd2b013/o4OS0emTnJPrU/Yogyxthls69QiY5RfhVqq3ybMHTqrDHWSpMA8MW7vn/ZNpwwW4WWsmWuCi3lCjBbW1rKlrkqtJQrwGxtaS1bIuo8QohYAKfbrFospfR4q9rWCdpv2KzqBmC88631iRO3ySMhRAyAT2ApW9/mLinlFyHqUqeZMCbabvm3Fd5XOtu9rwkH85XPHo/x4daegfbs/HIUFJkBALExApef7/yD/nFHxcCm+AmW/OpbZbe220cDgMEAjBsVumP2RG/ZdoSUEt8sUarWHD0iGrGx4fn2wVy9p6ZcAWbrC2YbGszWnt5y1dM5FPlHz2MqAFhbusdueVhKD6/b5sSkICtauY3l2tLdAepVe30SsjEyrZd1edH+lTDLFjctnFPL8XaUXl7rIyIEkhINfv3YzhkzGtHu36OjglPlvqP0km0bvbyPM1dt5groL1tbpWVmnHL+QeQXmq3r7puTistm+X4L7HCzer/99a9RuTlet81NSkR2QoJ1edV+j9fSgio3KRF905U7TPyxd7/dvx+uta9a1y893efn6J9h38ZxnyrV6LAc7XQr9xzbOO7TF4HuT0f6ojub1uyxWx40sofXbbO6piA9W3ld3LR6j+uNO0F6dhLiEpRfhcJD5V63NUUYccq5o63L61fsxJ7thYHsXqdjthZay5a5WmgtV4DZttFatszVQmu5Asy2jRazJaJONQFArM3yRz60ddx2Sse7ox3hOdODwoYQwgjgPQDjbFa/LaV8NERd6lTHjIlBQrzyZ/L+p1Vutra3YKH9tlNPDE2Vl737m/DQ06XW5esuS0Z2pvPqnHGxBkw+XunnK29XwNs7FFRUmrHwy2rr8sghUWF9G1m9ZdsR7y6ssrvV7vSp4VuBjrl6T025AszWF8y28zHb9vSWq57Ooch3eh9TAcC6sj2oblYqgEzqMsTrtlNyhtktLyveGqhutWNbbbuxpRmL9q30az9qOd6O0str/aknxaF0a2+/fiaMViZAThgd0+7f77gxtdOO1Rd6ybaNXt7Hmas2cwX0l22buroWTL/kELbsUCqMXzorEffemuamlXqsOnAQ1Q1KNfTTBvT3uu20gUfYLf+0K7RfBLtu7Gi75e937LRb3lpcYrc8fdAA+OoMhzZ/F4W+yngAVDgs+zNR2vHbGOX+dQVA4PtT7n9X9GfT6j2orVbGGBNPHep12+NPH2a3vOqXjo8xzrhkPCIi/HtvPP40+/6sX7HT+YZOHDt1CFIzlC/2fP7O7371IZwwWwutZctcLbSWK8Bs22gtW+ZqobVcAWbbRovZElGncqyS7XXJfinlbgC23xRhxW0bnLhNnvwXwHSb5aUArgxRXzpddLQBZ5+uTIpa/GMttu30XAiirq4Fr7yjfI7Zt1cExoxw/jnmmvX1eGZeGT76ogpms3cXkLxVctiMqecdRFW1pUpceqoRt1+f4rbNDZcr3xpct6kBL7/p+Hmsc/c8dhgVlUo1uusvT/a9w51Ib9m++m4FSg6bXf67K7v2NuGWe5ULHempRsy+OHyrFjFX76gtV4DZeovZMttwobdcAf2cQ5FfdD2mAiyToJfkb7Iuj83oh7xYz5OqogwmnNntKOvy3poSbK444HTbIxJzcF6P8TgxezAM8L2KcVJELCbnKB/cL8nfiNLGajctXOuM4w0Henyt1ws9ZquH93Hmqs1cAX1mazZLnH9tAX5fpVyAP/m4WMx7IjOgfQulRrMZ32zdbl0+tmcP9EhJ9tguymTEeUOVL43tLi3D+vwCp9sOysrEZaOGY2r/vjAI1+dPEQYDLhoxDCaD75eTTu7bG2cfOdi6/MuuPdhUYF/Z7dfde9HYrHxJ+ewjB2F4Thevn+PUI/phXPc863J+ZRU2Fxb53NdwI6VsBGD77Qp/fsEd2xz2v0cocVjuaH860hfdaWpsxq+LN1qXR07oh649PFenj4wy4ZRzlC9PHNhTgq0b9jvdts/AHJxxyXhMmDwYBoP7MdUZF43H42/PRnaub+fPGV2SMPPK46zLpcWVWPeH95OOpl+ofNm28FAZli/926fnD0fM1kJr2TJXC63lCjDbNlrLlrlaaC1XgNm20WK2RNSpbKsTVQDY5mN72ypJ3lc60gFO3CaXhBD3AJhts2oTgDNbPzDUjX/OTkbbZ9ItLcDl/yj0eIHizn+X4MAh5cPmW691fuL12oIKHH3Kftw6twSzri7A1PMPoqXF/b4X/1jjVYWg1evqcdwZ+7F1p6XqjMkEfDA/G2mp7r/Bd/JxsZgwWrlI8897i/Hxl+4r9Tz7Shn++7pyoWdA30icNyPBTYvwoKdsX/xfOfqP34Nn5pVZL4R5smZ9PU486wAOlynbP3xXGuLjwvutg7m6p9ZcAWbrCbNltuFGT7kC+jqHIu9xTKVYsOc3mKXldcwoDLhvyNkeJ1jf0H8KsmKSrcvv7PrF6XbTckfijXHX4ZYBp+LR4efjuaMuhfBx8vaMbkch2hhhXf5gr9cFA5wK5vGGE7291uuJ3rLVy/s4c9VmroD+sr3xX8X4fHGNdXnY4Ch89GoXmEy+f3krnL2+6k+YW1rPJwwGPH7KZLcTrAHg9uOOQZdE5Xf21ZWrnW4388hBWHTRebjrhIl4fvppeH3mDJdnKtEREbjvpOPx1WUX4eS+vT32oc0Zgwbg6dNOsW5f19SEx37+td121Y2NeGfteuuyyWDAK2dNx9F5uR6f45Qj+uHxUybbrZu3YpVX/VMJ22/xdfOjfZ7D8r4A9QXoeH860hddWvTGbzCbW18TjAbc8vDZHicHXX7rVGR0SbYuL3zd+Rhj0lmj8MyH12P2nafhrmcuwIPzL4Pw8Ld+xNBu+O+nN+PsK45FRKTnO89l5iTjgXmXIiFJKbz+wSs/o6mx2U0rxYBheeh3pPK68NV7yz2+H6kFs9VmtsxVm7kCzFar2TJXbeYKMFstZ0tkS0ht/oSJvjaP90hvb2uosL0VXKoQIjxvRRoC4T3bg0JGCHEZgAdsVh0EMFVK6V1pGg0Z1D8KV1+kVOj5Y3U9Tr/oEMor2lfLbG6WuP2BYrzwmvLfdNSwKFx+XmK7baWUuOPBErTYzNla8ksdvvy+pt22ts67pgBDJu7Ds6+UYdvORruLIPX1LVj6Wy0uvakA40/fb3er0GcezMDEcbEej1cIgTdfyEZiguXloakJOPeqAlx2cwHWblSq2EgpsWxlHc649BBuuU8pthEXK/Dh/GxVXCjRW7blFS24dW4Jcoftwuw5hfjoiyoczLc/oTebLbleeUshxp66H/sOKv9+7aVJuOL88K3u2oa5ajNXgNkyWwtmq55s9Zarns6hyDscU9nbVV2ET/YpX6ofktIdT4+6GPGm9pU9jcKAm/pPwaweSiWQzeX78fmBNU73fVP/qTAK5eONMel9cUxmf6/7ZhQGnN39aLvn6mil62AebzjR22u9nugtW728jzNXbeYK6Cvbh58pxby3lL7ndTXhy3dykBCvvUsd2w8fxvvrlepwI7rmYP5Z05EQFdVuW6MQuGPiMbhk5HDruvX5Bfho42an+75j4rEw2lTQntCjO07o08ttf3qnpeKlGdPw0+zLccsx4zChRx7iIyPttok2mXBin154+9yz8OSpUxAdYZmI0CIl7vj6O2wtdizabPHcsuXYcVgpwJwSE4M3zzkL/zltKkZ364oIm77GRJhwfO+eeP3sGXhu2qmIMimTHVbs24/31m1wexwqs93mcQ8/2tu2KZNSdqTK9Q43+/ZICJEAwPbi7HZX25Jz+3YU4ZsPlTHGwOHdMfelSxCX0H6MYTAacMWcqZh+kTLG2LphP75b6PzLHFfOmQqjUfk7GzGuL0ZPPMJlX5qaLO8vsXFRuGLOVLy19A5ce9fpOOq4/oiNt3+NysxJxqzZE/HCopvQo2+2df2Kn7bgi3e9/8Ls9IuVO2rX1zXi24+dH4saMVttZstctZkrwGy1mi1z1WauALPVcrZEOtRbCDHIx59A3J7O9pv1zm8/4F4gvgjuzlFCiP8JIb4VQqwQQmwWQmwSQvwqhPhQCDFHCDHa8246n/B9Ejx1BiHETwDa7nWxV0rZoxOf+xQAnwFo+8SzEsAxUsqw/sRTCDEIlgp2AIANP+VhUP/2H2L7o7a2BcdMP4B1mxqs6xLiDThnWjwGHxGJyEiBXXub8MFn1XaVavK6mrDsy27IyW7/TbnikmZkH7m73frH7knHnOtc3xoltf9Ou9u1xkQLpKUaUV8vUVLa/mJMYoIBrz2dhTNPjW/3b+78uKwWZ1+Rj/IK+2qgsTECaSlGFJaY0dho//qRlmLAx6/l4NixMVALvWQ788p8LPrK+a3eIyMFUpMNMBoFig+3z1UI4O5/puK+OakevyEaLpirNnMFmC3AbJmturLVS662wuUcavPWBgyZaFfAbLCU0vmsDY3imMp3jmOqQS9diZjuGQHbf5QhAq+NnY3+iTnWddXN9fghfyN2VhWisaUZubGpmNRliF3l6fy6Mlz+x8soaWhfJTU5Mg7fn3hXu/XPbvkG7+xuX9HRmZO7DMHDw2ZZl+9d/yG+ObTO+wNzIRjH2xErhn8c0P210eNrvbdOOPMAfv6jDgBw3NgYLF3kuXJoONFjtuHyPh5MzFWhpVwB/WTb66jd2HtA6X9qigEpSf7dMeHMU+Px6N2eb5PtjX5vXRuQ/TiKNpnw4QXnYmCWcp2tuqEBX23Zhm0lh9FoNiMvOQmnHdHfrtL2wYpKzHz3fRRVt59knxoTg5U3XtNu/aM//YJXV7b/4liUyYjvr7wUOYntJ/cDQG1jEyrq6xFhNCAlJsZuQjgAVDU04LavvsUPO3a5PdYuCQn438wZ6JOe1u7fGs1mlNbWwiAMSI2NgcnQfqL+qv0HcdXCT1HdGJib2zQWFGD/04/brur0MZUQ4gEA99is6iml3OND+wMAurYu/iSlPL6D/dkH5QLrz1LKiT60PRnAdzarLpVSvulHH/YA6O5PHzqL47hqfM8rkBAVmHFVVHQEnnr3GvQeqIwxaqvr8fM3G7B3eyGaGpvRpVsajjtliF2VyMJDZbhl1ksoLW4/xkhKicP7v9/dbv2rT3yNha87H1N17ZGO//vPeeg9IMfpv9fXNaKyrBYxsZFISG7/hZwVP23BY7e+h7pa7/5e07MS8b/vb4cpwvJ6/+3Hq/DsPYu8aqsWzFab2TJXbeYKMFutZstctZkrwGxDmW1VQzGW7X7NdpXurlVRcDiOu44453bEpGa7aaE+daUF2PLh4543dO9+KeVcfxsLIUwAmmxWzZdSXu3jPi4A8I7NqhOllEv97VPrPucCuM/HZpsBPCmlfKMjzx1Inu+7QLoihDgKwIdQfjeaAJwd7hMMgi021oDF73fFjMsO4fdVloo8VdUteG1Bpcs2g4+IxIfzuzi96AEA6WlGJCcZ2l006tsrwun2beLjDHYXPurqpd3FFlvHj4/BS49nom+vSKf/7s7x42Px2+fdcO7V+di8VTnxq62TqK1r/3zTp8Thqfsz0DPPff/DjV6y/XB+Nt74oBKPPFuGnXua7P6tsVGioKj9RTMAGHdUNB68M0111eeYqzZzBZgtwGxtMdvwp5dc7dvq4xyKXOOYyrWGliZcv/J1PDXyIgxNscy1iDdF44xuR7lss6OqAHeuXeByEnN5Yw0qm+qQGGE/sW5fjfNqjs7M6j7W+vhwQxW+z9/oZmvvBeN4w5EeX+v1Qo/Z6uF9nLlqM1dAn9kCQGlZC0rLWjxv6ERhsXe3lg6l+uZmXPLhQrw8YzpG5lou7sdHReHcoUe6bLO1uAQ3fPal00nbAFBaV4eK+nokRdtXmNtTWuZ0+4ZmMya/9iauPXo0zhs2BCkx9uddsZERiI1s/zthbmnBl1u24plf/8D+Cs83ncmvqsL0t97FTePH4oJhQxBvU1k80mhEdkKC03YlNTV4ddUavL7qT7Ror1CR44yPCQD2eNNQCNETyqRtAHB+f3ff+3N+6+PRQogIKWWTuwY2JjgsB6I/utNQ34R/XfEa7v3vRRg0ogcAIDY+GlNnui4etntbAf5987tOJxwBQEVZDaoq6pCQZP+3fXCP6zHVwT0l+Oe5L2LS2Udh2gVjkdfbvohbdEwkomPav65XlFbj/Vd+wmdv/Q5fCoudet7R1glHAPD5O7973VYtmK2F1rJlrhZayxVgtm20li1ztdBargCzbaPFbIko6JIdluv82IdjG8d9dpZBAP4nhLgYwDlSSu8vJAYJK26HqVBUhxNC9AHwOwDbr/77VfUgFIJZcbtNc7PEy29WYN5bFfhrm/NvsXXLMeHy8xNxxw0piIpyf4vO+e9U4Nrbi9D2Z3j8+Bh892FXGAyuq2jW1Lbgk6+rseTXWmz8qxF7DzahqroFQggkJRjQr1cEjh4VjbNPT8Do4e1v7+Irs1li0dfVWPRVNdZubMChgmY0NkmkpxrRLceEE4+JxVmnxWP4kR1/rlDSU7a/r6rDt0trsf6vBmzd0Yiy8hZUVrfAaAAy0ozIzTFh4rgYnHJSHMaOUk9lKWeYqzZzBZgts2W2aqOnXNuE+hyKFbc5pvJHsCtutzEKA87KG4Ozuo1Gr4Qsp9sU1JXjswOr8eaun9HU4vxLLW3OyB2F/xt8BgzC8tqx6vBOXL/ydUh4/rxjQGJXvDX+euvyqzuWYt72H3w4Gs8Cfbz+ClbF7TZ6fK33RO0Vt9voMdtQv493BuaqzVwB7WfrWHG7Iy4+JwH/ezYw1ZiCVXG7jVEInD98KM4fNgR9nVSkBoBDlZX4aMNmzFuxCo1m9+cT5w4ZjAcnnwRD692c/ti7Dxd/sNDj2VOEwYDjevXEmLxc9M9IR15yEhKiohAbEYH65maU1tZhb1k5ftuzFz/s2Il95Z4nbDsTHxmJKf37YlRuVwzOykRabCwSo6MgJVDRUI/i6hqszy/Aiv0H8MP2nR6P1x9hUnE7GkARgLZZ619LKU/1su3dAB60WXW0lHJFB/tzPoB3bVadI6X8yIt2AsA2AH1aV22RUg7wsw97oOOK220MRgNOmzUGp8wag+59nI8xig6VY/HC1fho/k9oanL/NzJl5lG4ce4ZMLRWs1+3fCf+dflrXk8MOmJYHo4c1RODRvZATl4qEpNjEZcQg9qaBlSUVmPX1gKs/mUrln23yesKkW0iIk14+6c7kZQSBwDYuHo3br/oFZ/2oSbMVpvZMldt5gowW61my1y1mSvAbEORLStuU7C0q7g9U6MVtz8KecXtrgAO2Kx6XEp5h4/7OAXAVzarzpdSvudvn1r3eSGA8QA2wPJ7UASgFEAZgGgAKQCOADAOwFkAHCsgbABwgpTycEf60VGcuB2mOjrJQAgxEsCxsPzxLJJSuj2jEEJkwjLBoLfN6nullA+6aBJ2OmPitq2/tzViw98NKChsRlMzkJ1pRN9ekRg9PApCuL5w4Wj1unr8urwOXXNMOPOUeJhM3rel4GC22sRctYvZahez1Sbm2jk4cZtjKn901sRtWz3iMtA3IRvp0QkwCiMON1RhX00JNlcc8NzYxoDErhie2gNF9ZX4sXAzzNK/ypvBFqjj9UewJ27b4mu9djFbbWKu2sVsO0+wJ27b6p2aiv6Z6ciMi4PJaEBxdQ32lJVjfX6BT/sZnJ2F0bldUVBVjcXbtsPMa0V2wmHiNgAIIV4DcHnrYguAAVLKbR7axMAyUbrtW2PbpZT9XGzr9bhHCBEH4BCAxNZVv0kpj/HiGE4D8IXNqruklA97audiX3vAidt2uvXKQM/+2UjNSITRZEBpcRUO7T2MrRv2+7SfvoO6YvConigprMCy7zejxRyeYyo9YbbaxFy1i9lqE3PVLmbbOThxm4JFpxO3pwPY6eNuiqWURf72QQjRHfZ3/npQSnmvj/s4AcASm1WXSCnf8rdP/hBCzAQwD5YJ3W3elVJe2Jn9cMSJ22GqI5MMhBBXAHgFQFu5lB8ATJbS+ZXr1g/bfgIwymb1a1LKK33rdWh19sRtIiIiIqJwxYnbHFP5IxQTt6nzdObEbSIiIr3pzInb1DnCaOL2IFgqQbWNTf4AcIyHCdbPAbjRZtXVUsr5TrbzadzT2uYxALfbrLpOSvmSm+2TW/vfrXVVFYAeUspSV23c4cRtIiIiIiL14MRtChadTtwOxZ3AHCtuPyql/D8f9zEFwDc2qy6QUi4IRP987McAAMuhfBkdAI6SUq7u7L60cX8fRFKd1lvOPQH7bE8CcJqL7U0APob9BINvAVwTrD4SERERERGFK46piIiIiIgoXLRelJ1ns2osgC9bJ0TbEUKYhBBPwH7S9ioArzvZ1qdxj42HAdiWd39OCHG9cFLGv7Uy109QJm0Dlmrbfk3aJiIiIiIiIqJO1eiwHO3HPhzbOO6zU0gp/4b9F9EB4PxQ9KWNKZRPTkGRDvuy7m36u9g+F8AUh3VHAtjiy+0ybdwupVzkT0MiIiIiIqIwwDEVERERERGFkzmwTNge1ro8BcA+IcQHsFQYawDQG8AsWMYnbfYBOMNFdW5fxz0AACllhRDiPACLAUTCcp3xBQDXCyEWAdgLS/WqkQDOat2mzatSyufd7Z+IiIiIiIjIZ7L1R0vC43gqHJb9mbgd47Bc7l9XAuJtAE8CiG9dPjGEfeHEbQ0qgeUXPNlh/TYf9tG1A8+f6HkTIiIiIiKisMUxFRERERERhQ0pZa0Q4mQAnwEY17o6AcCVbpptAnC2lPKQi3/3e9wjpfxJCHEGgPehjF8GALjLTbOXYV8JnIiIiIiIiIjCmJSyUQhRBctnEACQ6cduHNsc7liv/Nf6+coaAMe1rurI9dwOM3jehNRESilhKetu+72LHwF8EZoeERERERERqQfHVEREREREFG6klCWwXFi8CcBfbjbdD2AugFFSyq1u9tehcY+U8hsAgwHMh+tqWRLAbwCmSCmvlVI2e7NvIiIiIiIiIgobB2wed/OjfZ7D8r4O9CUQCmwex7vcqhOw4naYklJO7EDb+UKItQCOheWPZ5GUssXFtnsA+HX/biIiIiIionDFMRUREREREWlJ68Tn5wE8L4QYAGAIgC4AIgDkA9gOYGXrpGxv9uf1uMdF+/0ArhZC3ABgPIDuALIB1AA4CGBV6zYBI6XsEcj9EREREREREZFb22G5yxYA9PCjvW2bMillyCput4qxeVwSsl6AE7c1S0q5GsDqUPeDiIiIiIhIjTimIiIiIiKicCWl/BvA3wHYT4fHPVLKRliqdRMRERERERGRtqwHMK31cYYQokdrUStvjXHYV6j1sXkc0urfnLhNRERERERERERERERERERERERERESqIqTlR0vC6Hh+dVieAGCPNw2FED0BdLVZ9UuA+uSX1v4MtFm1NFR9AQBDKJ+ciIiIiIiIiIiIiIiIiIiIiIiIiIiIwsqvAKpsls/zoe0FDstfd7w7HXKXw/KnoehEG07cJiIiIiIiIiIiIiIiIiIiIiIiIiIiIgCAlLIewEc2q6YIIfp5aieEiAEw22bVdinlChfbjhRC/FMIMVMIYXSzz0ghxI1CiAhv+2/TdgaAy21WLZZSrvZ1P4HEidtERERERERERERERERERERERERERERk6z8AWlofGwC84W6CdavHAOTaLD/hbCMhxBUAVrY+x4cAvhVCuJrTHAvgOQAbhRAzvOhD23NcDGABANG6qg7A7d60DSZO3CYiIiIiIiIiIiIiIiIiIiIiIiIiIvWRGvsJI1LKzQDm2awaC+BLIUSy47ZCCJMQ4gkAN9qsXgXgdSfbClgmdNvOYT4JwGkeutQfwCIAu4UQ/xZCTBJCJDnsO1YIMU0IsRTAmwCi2w4HwKVSyg0eniPoTKHuABEREREREREREREREREREREREREREYWdObBM2B7WujwFwD4hxAcANgFoANAbwCzYV9reB+AMKaXZyT7TAaQ4Wd/fRR8aAOwH0K11uRuAf7X+QAhRC6AUQGTrvh2LWlcCuFhK+ZmL/XcqTtwmIiIiIiIiIiIiIiIiIiIiIiIiIiIiO1LKWiHEyQA+AzCudXUCgCvdNNsE4Gwp5SEX/14CoBxAssP6bS76UCeEGADLRO1rAKQ6bBLb+uOoBcD7AO6RUu5y099O5TirnIiIiIiIiIiIiIiIiIiIiIiIiIiIiAhSyhIAxwG4CcBfbjbdD2AugFFSyq1u9icB3A5A2qz+EcAXbtrUSCnvAtAFwAwAzwBYCmAvLJPAm2GprL0TwGIAtwLoJ6W8IJwmbQOsuE1EREREREREREREREREREREREREREQuSCmbATwP4PnW6tdDYJlEHQEgH8B2ACtbJ2V7s7/5Qoi1AI4FcADAIillixftGgF82vqjSpy4TUREREREREREREREREREREREREREqiKkhPBunrBqqOF4pJR/A/g7APtZDWB1x3ukLoZQd4CIiIiIiIiIiIiIiIiIiIiIiIiIiIhI6zhxm4iIiIiIiIiIiIiIiIiIiIiIiIiIiCjIOHGbiIiIiIiIiIiIiIiIiIiIiIiIiIiIKMhMoe4AERERERERERERERERERERERERERGRT2Trj5Zo7XioHVbcJiIiIiIiIiIiIiIiIiIiIiIiIiIiIgoyTtwmIiIiIiIiIiIiIiIiIiIiIiIiIiIiCjJO3CYiIiIiIiIiIiIiIiIiIiIiIiIiIiIKMk7cJiIiIiIiIiIiIiIiIiIiIiIiIiIiIgoyU6g7QERERERERERERERERERERERERERE5AshLT9aorXjofZYcZuIiIiIiIiIiIiIiIiIiIiIiIiIiIgoyDhxm4iIiIiIiIiIiIiIiIiIiIiIiIiIiCjIOHGbiIiIiIiIiIiIiIiIiIiIiIiIiIiIKMhMoe4AERERERERERERERERERERERERERGRT2Trj5Zo7XioHVbcJiIiIiIiIiIiIiIiIiIiIiIiIiIiIgoyTtwmIiIiIiIiIiIiIiIiIiIiIiIiIiIiCjJO3CYiIiIiIiIiIiIiIiIiIiIiIiIiIiIKMlOoO0BEREREREREREREREREREREREREROQLIS0/WqK146H2WHGbiIiIiIiIiIiIiIiIiIiIiIiIiIiIKMg4cZuIiIiIiIiIiIiIiIiIiIiIiIiIiIgoyDhxm4iIiIiIiIiIiIiIiIiIiIiIiIiIiCjIOHGbiIiIiIiIiIiIiIiIiIiIiIiIiIiIKMhMoe4AERERERERERERERERERERERERERGRz2SoO0DkG1bcJiIiIiIiIiIiIiIiIiIiIiIiIiIiIgoyTtwmIiIiIiIiIiIiIiIiIiIiIiIiIiIiCjJO3CYiIiIiIiIiIiIiIiIiIiIiIiIiIiIKMlOoO0BEREREREREREREREREREREREREROQTCQgZ6k4EmNaOh9phxW0iIiIiIiIiIiIiIiIiIiIiIiIiIiKiIOPEbSIiIiIiIiIiIiIiIiIiIiIiIiIiIqIgM4W6A0RERERERERERERERGqVsCfUPaBAqysNdQ+IiIiIiIiIiEirWHGbiIiIiIiIiIiIiIiIiIiIiIiIiIiIKMhYcZuIiIiIiIiIiIiIiIiIiIiIiIiIiNRFtv5oidaOh9phxW0iIiIiIiIiIiIiIiIiIiIiIiIiIiKiIOPEbSIiIiIiIiIiIiIiIiIiIiIiIiIiIqIg48RtIiIiIiIiIiIiIiIiIiIiIiIiIiIioiAzhboDREREREREREREREREREREREREREREvhDS8qMlWjseao8Vt4mIiIiIiIiIiIiIiIiIiIiIiIiIiIiCjBO3iYiIiIiIiIiIiIiIiIiIiIiIiIiIiIKME7eJiIiIiIiIiIiIiIiIiIiIiIiIiIiIgswU6g4QERERERERERERERERERERERERERH5RErLj5Zo7XioHVbcJiIiIiIiIiIiIiIiIiIiIiIiIiIiIgoyTtwmIiIiIiIiIiIiIiIiIiIiIiIiIiIiCjJO3CYiIiIiIiIiIiIiIiIiIiIiIiIiIiIKMk7cJiIiIiIiIiIiIiIiIiIiIiIiIiIiIgoyU6g7QERERERERERERERERERERERERERE5AsBQMhQ9yKwRKg7QEHHittEREREREREREREREREREREREREREREQcaJ20RERERERERERERERERERERERERERERBxonbREREREREREREREREREREREREREREREFmCnUHiIiIiIiIiIiIiIiIiIiIiIiIiIiIfCJbf7REa8dD7bDiNhEREREREREREREREREREREREREREVGQceI2ERERERERERERERERERERERERERERUZBx4jYRERERERERERERERERERERERERERFRkHHiNhEREREREREREREREREREREREREREVGQmULdASIiIiIiIiIiIiIiIiIiIiIiIiIiIl+IFsuPlmjteKg9VtwmIiIiIiIiIiIiIiIiIiIiIiIiIiIiCjJO3CYiIiIiIiIiIiIiIiIiIiIiIiIiIiIKMk7cJiIiIiIiIiIiIiIiIiIiIiIiIiIiIgoyU6g7QERERERERERERERERERERERERERE5BPZ+qMlWjseaocVt4mIiIiIiIiIiIiIiIiIiIiIiIiIiIiCjBO3iYiIiIiIiIiIiIiIiIiIiIiIiIiIiIKME7eJiIiIiIiIiIiIiIiIiIiIiIiIiIiIgowTt4mIiIiIiIiIiIiIiIiIiIiIiIiIiIiCzBTqDhAREREREREREREREREREREREREREflCSMuPlmjteKg9VtwmIiIiIiIiIiIiIiIiIiIiIiIiIiIiCjJO3CYiIiIiIiIiIiIiIiIiIiIiIiIiIiIKMk7cJiIiIiIiIiIiIiIiIiIiIiIiIiIiIgoyU6g7QERERERERERERERERERERERERERE5BsJSBnqTgSY1o6HHLHiNhEREREREREREREREREREREREREREVGQceI2ERERERERERERERERERERERERERERUZCZQt0BIrVpaZH48vsafPBZFVatbcDBgmaYzRIZaUYMGRiFaZPjcdHZCYiN7ZzvRWze2oCFX1bj+59rsfdAM4oPmxFhArIzTRg6KApnTI3DzNMTEBkpvNrfT7/X4sSzDnaoT/+6OQUP3pneoX2EArP1TI3ZMlfP1JgrwGy9wWwDg9kGhtZzdWfP/ia8/0kVfvq9Dn9ta0RpmRnNZon4OAN65EZg8IBIHD8hFmdMiUNSojEAR0cU/gQEjsnsj5O7DMWgpFxkRCfCKATKGmuwvbIAPxf9ja8PrkVDS1NAn/e+I8/CabkjA7a/V7YvwfwdSzxuF6rj7Wx6fq231dwscfTU/Vi7qcG67rixMVi6KDegz9OZ9Jytlt/HtZ6rXs+7Ae1na6uyyowffqnDkl9rsfLPeuze34Sq6hZERQokJRrQv3ckRgyJwoxT4jF2VEwQjq7zCAEcO7gXJo/qj0Hds5GZHA+jQaCsug7bDhTjpw078dWKv1Hf1ByU55996tG45tSxHdrHNc8uxIqt+7za1mQw4OSR/XDi8D4Y2C0LqYmxAIDSylr8tb8QS9buwPdrtqG5paVDfSJSKyEERk88AsedMgT9j+yGtKxEGAwCFWU12L21AH8s+QtLP1+LhvrgjzHSsxIxYkI/DB/bB72O6IL07CRERZlQV9uIqoo67N1egL/X7cOv325E/v5St/s66YwRuPWRmQHr24aVu3DHJfMDtr/OwGy9o7Zsmat31JYrwGy9pbZsmat31JYrwGy9pcZsiYjURkgpQ90HooAQQgwCsKltecNPeRjUPyqgz/HX1gZccmMh/tzY4Ha77EwjXno8E9Mmxwf0+W0dKmjGbQ8U44NPq+Hpz7hX9wi8+1I2Rg+P9rhfvV7UYrbeUVu2zNU7assVYLbeYrYdw2wDRw+5OlNZZcacuSV444NKmM2et4+JFsjf2AsJ8R2fQLN5awOGTLSbEDFYSrm5wzsmTXMcUw166UrEdM8I+PP0jM/E/UNmYkBSV7fbldRX4pHNn+KXoi0Be+5QTNwO5fHaWjH846Dst41eX+udefS5Utz1yGG7dWqeuK3XbEP5Pt4Z9JCrHs+7AX1k27bv/7xchlffrURVtXcTd4cPjsLzj2QEZQL3yAeuDfg+bfXKTsWDl07BwLwst9sVV9Tg3wt+wM8bdwW8D505cXtY7xzcf9Fk5GUmu91uX1EZ7n1rMdbvyu9Qv5ypKy3A1g8et13FMRV5xXFcNb7nFUiICuy4Kq93JuY8dg76DnI/xigtrsRz932KFT/+HdDnb9N7YA7OufI4jD95EIwm777A9tvijZj36FcoKahw+u96n3TEbL2npmyZq/fUlCvAbH2hpmyZq/fUlCvAbH0RqGyrGoqxbPdrtqs4rqKAcBx3DT/pVsQmZoewR4FXW1mAtT88ZbuKfz8aw4rbRF76fVUdTjn/ULsLAQnxBkRHCRQfVq7iFRSZceZl+Xj+4Qxce2lywPuyblMDpl18CAfz7aunREQAWRkmVFS22PVz194mnHDmAbzxfBbOPi3B6+cxmYDuuRE+9y8tRV0Vppit99SULXP1nppyBZitL5it/5ht4OgxVwDYsr0RZ152CFt32ldlMBiArAwjTEaB0nIzamqVGSx19RJmM79YS9o2JDkPzx51KeJN9pOyqpvr0WhuRmqUMnksPToRT4y4EE/89QU+3rciIM9/uLEa+2sOe97QjeyYJEQYvPs4JdTH21n0+lrvzLadjXjwafcVcNREr9lq/X1cj7nq4bwb0E+2H3xWhdlzipxO2DaZgMx0I1pagOLDZrsvXqzd1ICJMw7g9WeycMFZiR07wE40tFcXvHD9DMTH2Bcpqa5rQGOzGakJsdZ1GUlx+M/saXj0w6X46JcNQetTdV0DSqvqfG5X3+S5at0Jw/rg0ctPQYTDBIaKmnoAQFKccl6Vl5mCV24+G3e89hV+2hD4yepE4WjAsDw8NP8yxMbbjzFqq+vR2NCM5DRljJGakYh7X7gQLz70Bb56b3lA+3HFnKmYcekEGI3tv7TWUN+E8tJqREdHICnV/gtCEyYfiYEjeuCuK1/Hnm0F7drW1jTg0N6OjdmSUuMQlxC4L2Z2FmbrmRqzZa6eqTFXgNl6Q43ZMlfP1JgrwGy9odZsiYjUihO3ibxw4FATpl9if9HjygsSMee6FPTtFQkAKC0z45W3K/DIc6WorpGQErjxX8Xo1T0Ck4+PC1hfDhU0Y8qsg3YXWk48NgZ33piKieNiYDBYbim6bWcjXnm7As+/Vo7mZssFxAuvK0DPbhEYOdS7k62u2SZs+6NHwPoejpitNjFX7WK22sVstUmvua74sx6Tzz1od9zHHh2Dm65KxsnHxSI+TvlAbsfuRnz3Uy1eW1CJdZvcV0UkUrvM6EQ8NfJiu0nMn+xbibd3/4r9tZYPlRMjYnBmt9G4tPdExJmiYBAG3DbwdByoLcXyku0d7sMLWxfjha2L/W6fFZ2ET4+bY10ub6xxuW04HG9n0OtrvTNSSlx9ayHq6y2Tdwf0jcTf2xs7dlAhpNdstf4+rtdctX7eDegr23c+tq+yffTIaMw8PR5TT4xD314R1v3X1LZg6W+1eOKFMixbZZn029wMXP6PQgzsF4nhR4b/BenM5Hg8c810u0nbC3/biLe+X419xeUAgMTYKJx9zBBcPnk04qIjYTAI3HnOCThQXIE//t4blH4tXbcD9739XcD32z83Aw9fNtU6abvJbMY7P/yJ935ai+IKy3lXRlIczps4HBeeNAIRRiMiI0x45PJTcfET72H7wZKA94konKRnJWLuS5fYTTj65sOV+Pj1X6wTdeKTYnDKOaNx7uzjERsXBYPBgOvuPh35+w7jz2WBG2OcOmuMdcKR2dyCP5b8heVL/8Kfy7ajrKTaul1SShzGnTQQ515zPLJyUgAAqRkJmPvixbhm2jOor7U/X/79+834/fuOFZGb//Ut1klHlWWux2zhhNl6R23ZMlfvqC1XgNl6S23ZMlfvqC1XgNl6S43ZEhGpmTru3UkUYtfeUYTSMuViwAuPZmDek1nWix4AkJpixJ03pWLxB12RmGD505ISuOrWItTUene7Tm9ccmOB3UWPf92cgsXvd8UJE2KtFyUAoF/vSDw5NwM/Lsq13qa3qQm46PoC1NcHrj9qx2y1iblqF7PVLmarTXrMtbC4GTOvzLdOJImMFHjmwQz8+EkuZpwSbzfZCwD69IzEdZclY833eVj4ehfExXKIRtp156AzkBypVIR8dPNneHjzp9ZJzABQ2VSHN3b9jBtWvY7qJssEK4Mw4O4jz0S00fdKqYF2TvexMBksE4nqmhuxOH+9y221cLze0ONrvSsvv1WBX1dYcjxtUhyOGh7loUV402O2engf12OueqHHbI8aFoXFH3TFsi+74R+zU9C/T6Td/uNiDTh9Ujx++bwbbr4q2bq+uRm4/QF1TPC967wTkRwfY11++L0leGjBD9ZJ2wBQWduA1xevwrXPLURVneVLJAaDwH0XnozoSPXU7jEIgQcunoyoCEufm5rNuO2VL/HcZ79ZJ20DQHFFDZ777DfcPv9LNDVbfs+iI024/6JJEMLprok044a5M5CYrIwxXrj/Uzx33yd21RWrK+rw4fyfcdcVr6GmqnWMYTDgnw+dhaiYwI8xfvpqPWaf9jT+ffO7WPLZWrsJRwBQUVaDbz5ahWtPfwYbV++2rs/qmoIZl0wIeH+OOrY/cntmWJe//Xh1wJ8jGJitZ2rMlrl6psZcAWbrDTVmy1w9U2OuALP1hlqzJSJSs/C/mkAUYstW1uHrH2qty7NmxOPaS5Jdbn/0yBg8ene6dflgfjP++3p5QPry47JaLP1NuQXlzGnxePDOdAg3n0iPOyoG77yYZV3eurMJ7y6qCkh/1I7ZahNz1S5mq13MVpv0mKuUErOuLrDeDt5kAj57swtuvDLZq36eMTUeERGcaUDaNCQ5D8dkHmFd/vbQeizct8Ll9pvK9+O5rd9al7Oik3BO97FB7aMnUYYITM8dZV3+9tA6VDbVOd1WC8frDT2+1rty4FAT/u8hy8UeoxF48I40v/YTLvSYrR7ex/WYq17oLVuDQeDWa5Px2xfdcNKxsS63s/XEfek4oo9ysf2n3+twqKDZq7ahMrRXDo49spd1+ZtVW/DRrxtcbr9xTwGe/eRX63JWSgJmHTcsmF0MqMmj+qNfrjJR4K0f1uDnjbtcbv/Thl14e8ka6/KAvCycPKJfUPtIFEoDh3fHmInKGOPHL9fhq/ddjzG2rN+P1578xrqcnp2EaRcEboxRV9uAx2/7AI/NeR8H93j+MkxdbSOevONDmJuVL/Ycf9rQgPWnzbQLx1kfH9hdjDW/bQv4cwQas/WO2rJlrt5RW64As/WW2rJlrt5RW64As/WWGrMlIlI7TtwOQ0KIa4QQ0uZnTwj6kCqEuFUIsVQIUSiEaBJC1Agh/hJCvCqEmNjZfQqVF2wuWhiNwOP3ZLjeuNXVFyViQF+lms2L/6uAlLLDfXn+Vfu+PHlfuuuNbZx2cjxOn6zc7jRQF2LUjtlqE3PVLmarXcxWm/SY66KvqvHLcmWSyrMPZWDSxMDdcp68xzFV+Dm3u/LBb3OLGc9t+cbN1haf7F+JXdVF1uWZeUcHpW/eOqXrcCTZVND+YO8fLrfVwvF6Q4+v9a5ce0eRtUrzP65OxpCB6q62rcds9fA+rsdc9UJv2b75XBYevzcDJpP3X5YwGgXOmBpvXW5pATZvbfC6fSicN3GY9XGzuQVPL/rFY5uFv23Ernylatw5xwX+gn6wzLI53vLqOsz/ZrnHNq98vRwVNfXKPsJgoroQwiCEmCaEWCCE2CGEqBNCNAohDgohvhZCzBZCePeNg8D0J6jjEiFEhBDiAiHEIiHEXiFEfevP3tZ1FwghAlKiUAhxWuv/pXWsF4j9qsW0C5UJQ+ZmM157wvMY45sPV2LfjkLr8mnnBW7S0dWnPo0fv1znU5uiQ+XYuvGAdblrj3SYIowB61NuzwyMGN/HuvzFu67HbOGE2XqmxmyZq2dqzBVgtt5QY7bM1TM15gowW2+oNVsiO1KjP6RpnLgdZoQQ1wN4McR9uBrAbgBPAjgeQCYAE4BYAAMAXAHgRyHEd0KIriHraCeorW3Bl98pt2GcNDEWXbt4vr2kEAKXnJtgXd5/qBnLVta7aeGZ2Szx4zLlAuKJx8QiN8f7zzuvvSTJ+nj95kbs2N3Yof6oHbPVJuaqXcxWu5itNukx15YWifufLLUuHzMmGte4qXJIwcMxVfiJMkTYVZ9eXrIdxQ2VXrX98oBSRTE7JhlDU7oHvH/emmVTAXvN4V3YWV3odDutHK8nenytd2XBokprpdueeSbMnaPuatt6zFYP7+N6zFUv9JhtcpJ/F6jzcu37UlLa4td+OkN0hMmu2vYff+9BcUWNmxaKz5f/ZX3cJTURw3rnBLx/gdYlNRFDenaxLi9esxUNTWY3LSwamsxYvGardXlorxxkpyS4aRFcQoiBAFYB+AzAeQB6A4gGEAEgB8BUAC8D2CmEmNYJ/QnquEQIMQHA3wDeATADQB6AqNafvNZ17wD4SwgxztV+vHyuGQA+huX/UneioiMwZuIA6/KaZdtxuMi7Mcb3n/5pfZyZk4xBIwIzxqip8u89o+hQufWxwWBAQnLgvscw/aJxMBgsl75rq+vx/SdrPLQIPWbrHbVly1y9o7ZcAWbrLbVly1y9o7ZcAWbrLTVmS0SkBZy4HSaEEDFCiJcAvAAgZPdVFUI8CWAegESb1RJAAQDHe0CfDGClEKIPNOq3lXWorVO+wnL26d5/6Ou47eIfvftg3ZVNWxpRWaVcTDhubIxP7Y89OgaRkcqv1rJVHbsQo3bMVpuYq3YxW+1ittqkx1y//bEWm7cqE0v+84DnKocUWBxTha9hqd0RY1Iqei4p2OR1W8dtx6b3C1i/fDE6rTd6JWRZl91V29bC8XpDj6/1zpQcNuOf9yi3NX3xsUzExqr74zY9ZquH93E95qoXzNZ71TX2E7WTE8P39XpYnxzERCnzU7//c7vXbb//0/6W1uMG9ghUt4Jm7AD7SRD+Hq/BINrtq7O0TkxeDmCEwz9VASh2WJcN4FMhxHVB7E9QxyVCiDMBLIVlcrqtstYfW31gmSA+3dv92zyPUQhxH4CFsEwI16VBI3ogOlYZY/z67Uav2zpuO/KY0I4xYuLsY6z1c/KSo7iEaJw4bbh1+YdP/0Rdbfh/uYvZeqbGbJmrZ2rMFWC23lBjtszVMzXmCjBbb6g1WyIiLQjfTyZ1RAgxCcAGANeEuB/XAbjVZlURgOsAJEgpuwCIAzAcwCKbbXIAfCWEiIcG/e5wcWDsyGiv2/bMi0BWhlL9xXFfvsovbLZb7tc70sWWzsXEGNA1W+nPyj/1fVGL2WoTc9UuZqtdzFab9Jjroq+qrY/HjIjGiCHeHzN1HMdU4W1osv3kmY3l+7xue6iuDIcbqpR9hagC9aweSoHA/Loy/Fz4l8tttXC83tDja70z/7inGCWlloqgF56dgEkT43x67nCkx2z18D6ux1z1gtl6b/3mButjIYBRQ8N3DuiwXvbFjzfsyve67aHDlSixqc6thorbtn1sNrdg854Cr9tu3luIZrMyKX9oCI5XCJEL4AsAtt+GmA+gn5QyUUqZCSANwL8AtL3pCAAvCCEmB6E/QR2XCCGGA1gApfp1M4DHAHSVUqZKKVMB5Laua3thiATwvhBiiA/HcRSAFQDmIoRfzg0HAx0qPP69zvsxRuHBMpQWK2OMgcNDO8bo0U/5Quye7QVoqG8KyH4nnzXKOqGppaUFn7/r+su24YTZeqbGbJmrZ2rMFWC23lBjtszVMzXmCjBbb6g1WyIiLeDE7RATQiwGsBiWigMAYAZwH4BfO7kfebDcLq/NAQATpJQvSSlrAEBarJNSngXgcZtt+wF4qPN623k2/KV8mJ+UaEC/3r7dhe+o4cqFkg1/N7jZ0rPScvtbQyb5UREmzqbq1669gTmRUytmq03MVbuYrXYxW23SW65ms8QXi5WJERefE7pbc+sRx1Thr09CtvVxVVMd9taUuNm6vc3lB5zuq7N0jU3FuIz+1uWF+1agBdLl9mo/Xm/p7bXema+X1OC9TywXcNJTjXhqrjaqNOstW728j+stVz1htt7Zs7/J7ksak4+PRUa6KWD7D7S+XdOtj6tq67G3yLGAsXub9yoTn/vmpLvZMjzYHu+u/MOob2p2s7W9uoYm7Co47HRfnehlAKk2y9dJKa+WUlpLh0spS6WUj8BS3brt/uwCwGtCiIB98yvY4xIhhBHAG1CqXzcBOEtKeaeU8lDbdlLKg1LKOwGc3boNAEQDeEMI4fHFQQgxD8BKACNtVr8E4H1PbbWoZ39lXFBdWYeDe3wbY2zbuN9mX10C1i9fHTPlSGTlpFiXl3y2NiD7FULg9AvGWpf/XLbD5/+jUGG27qk1W+bqnlpzBZitJ2rNlrm6p9ZcAWbriZqzJWpHAkJjP24uQ5FGcOJ26I2xebwewDgp5QMAWlxsHyz3ALC9d+UVth8qOnEnANuvWl3XWlVCU3bsVi4O9OhmghC+FXXo2U25UFJa1oLSMrObrd2LirR/7to6339F9h1UPvDef9D7D7+1iNlqE3PVLmarXcxWm/SW67pNDdZqqwBw4jGx1sdbtjdiztxijDhpL5L77kRsjx3oOWo3Jp1zAM+/Wo7iEv3+ngQQx1RhLi9OmTyTX+fbpCPAUoW6TXJkLBIjYtxsHXjndh8LY+vcknpzEz7dv9rt9mo/Xm/p7bXeUVV1C667vci6/OTcdKSnGd20UA+9ZauX93G95aonzNaz3fuaMP3iQ6irt1zxiowUeOSu8J7MnJeZbH186HCl6w1dOGjTJjk+Bomx4VtdHADyMpKtjw8ervC5/aES5Xi72eyrMwghxgM41WbVe1LKl1xtL6VcDuB2m1VdAdwQwC4Fe1wyC4Bt1ewnpZSfu9pYSvkZgKdsVg0HMNPN/tvYjvN2A5gqpbwOQMe+YaJSOd3TrI8LD/o+xig4oLRJTI5FfFLnjzGGHd0bNz9wpnX50N7D+GJBYCo6Hn3CAGTnKt+d+Pzd3wOy387AbN1Ta7bM1T215gowW0/Umi1zdU+tuQLM1hM1Z0tEpAXhW1JCX7YCeATA21LKzp5cACFEMoALbVZ9K6X8zl0bKaUUQtwC5QO9CFhuS353UDoZIgfylYsDuTm+VauxtLH/E9t/qBmpKf5dyHVsZ9s3b2zb2YjKKuXXy/aipCtlFS245rZC5BeZcbjUjOqaFjQ1SSQnGZGWasTwwVEYOyoaJx4Ti4gIdd2pkNlqM1vmqs1cAWbLbF1jtuFJb7naViZMSzGgb69I1NW14LYHSjDvrQq0OJzh7zvYjH0Hm7Hk1zrc98RhzJ2TipuuSgF1CMdUYSwzOtH6uLDe94k4jm2yopNQ2VTX4X55I9YYidO7KkX+vstfj4qmWrdt1Hy8vtDba72jOx8qwf5Dluc56dhYXDQz0UML9dBbtnp5H9dbro60et4NMFtXqqpbsGpdPT77thpvvF+J6hrLpG2TCfjfs1kYMjC8JzJnJcdbHxeUV7vZ0rnCsiq75eyUBFTWBm6+66Du2Zh70SSkJ8YhMTYKsVGRkJCorG1ASUUNNu0twJ/bD2Dz3kKP+4qPiUJsdKTLvnujsFxpkxAThfjoSFTXN/q8Hz/daPPYDOA2L9q8AuBmAANal68XQjwupexQPa1OGpfYHm8pgAe96NoDAGYDaHvDvBHAB160OwBL9fCXpZS6nLDdJj0ryfq4pMD3MUZJoX2bjOwkVFcEf4yRnBaPgSO644TTh+HoEwbCaLR8IbaspAr33/AWGuoCc2eF6ReNsz4+tPcwVv+yLSD77QzM1j21Zstc3VNrrgCz9USt2TJX99SaK8BsPVFztkREWsCJ26F3EoA1Hf1AroPOgOUWdW1e96aRlHK5EOJvKB8uzoKGJhk0N0tUVCoXCrpk+n7BokuWfZvDHahYM6h/pN3ymvW+fU757dIau+WaWs/zWSqrWjD/HWcVXSwngl99b9lnVoYRV12YhDtuSEFsbPgX8me22syWuWozV4DZAszWHWYbfvSY6+YtyoSA/n0iUVPbgimzDuL3VfXW9ZGRApnpRlRWtdhNRqmobME/7y3BX9sa8eJjmTAY1DVRKExwTBXGjMKABJuK0SX1vk/EKWmwf51Mioh1sWXgnZY7EvERSrQf7HFfzUTtx+stPb7W2/p1eR3mvWW5cBMbI/DyE5k+PV8402O2engf12OujrR43g0wW0evLajAv58uRWV1C8rK27cdOSQKzz2cgaNHhufdLNoYDQIJscr5R0lFjZutnSt2aJMUF9hj7p2Tht45aS7/fdLIfgCAHYdK8NYPa/DF8r9cbpsSH2237Nh3bzg73s6YuC2EiAVwus2qxVLKg57atU6WfgPAY62rugEYD+C3DnbpDARxXCKE6AH7StjvSyk9zlyRUtYJId4HcG3rqnFCiDwp5T43zS4DsFFKqe/bKgAwGA2IT1T+hkuLfR9jlBbZt0lMDt4Y46b7Z2DUMf0QnxiDmDj7L8m0tLTg9+8346V/f+HXcTjTo28Who7pbV3+YsEfCO3HA95jtu6pNVvm6p5acwWYrSdqzZa5uqfWXAFm64masyUi0orw//RZ46SUq0M8wQAAJtk8bgDg8rZ2Tnxk87i3EKJPYLoUeuUV9h/ux0T7/ufi2MZxn77ITDehdw+las5n31ajvt67/ZnN0npRuU1DY+B+7QqLzXjo6VIMPWEfVq+r99wgxJit99SULXP1nppyBZitL5gtsw0Hesx1u83t6VOSjbj29iLrZK+zTovHz5/monZPb+xd0xNl23pjx4oeuP2GFETYFESc/04lnviv77fqI46pwl28yX4iTkOL7/MuGsz2bWwnRgfbOd3HWh+vLd2DbVX5brdX+/F6S4+v9W3q61swe04h2l515t6Whp55vle4DVd6zFYP7+N6zNVfajrvBpito/KKFuw90Nxu0nZiggFPzU3HH193C/tJ24ClYrSthiY/zicc2iTEhqbCeJ+cdDxw8WTMu/ksJMdFO90mIcbh/Mmf420M2fFOAGA7e+MjVxs64bjtlI53J+jjkkkOy/4er3CyLztSyrWctG0Rn+DwN1Lve4XFhgb7NnGJwXstTM1MREaX5HYTjg7uLcHca9/Cv/+xIGATjgBg+sXjrY/rahrw3aLVAdt3sDFb99SaLXN1T625AszWE7Vmy1zdU2uuALP1RM3ZEhFpBSduE2Cp5NBmrY+3nFvuZl+q5nhhIDra96pJjm06eiHp/DMTrI9Ly1rw2AveXRT8z8tl2LLD4aTSRdWglCQjLjw7AY/fm46vF+Rg/Y95OLCuJ2r39EbN7t7I39gTv3yWi2cfysCJx8ZA2Bzirr1NmHTuwbC/sMVstZktc9VmrgCzZbbuMdvwo8dcy8uVqoRbtjfi3YVVMBiAV5/OxIfzu2DCmBgImyB75kXgkbvSseTjXMTFKuvve+Iwtu3stNt5U2BxTOVCpMH+Rl8NLX58QO7QJsLgezVRf4zP6I/ucenW5Q/3uq+2Daj7eH2hx9f6Ng/+pxRbd1q2H3FkFP5xdbLvnQ1jesxWD+/jeswV0P55N6DfbH1VWdWCW+eW4Ijxe/HOx84qr4eXCJP9e78/E5kbHdpEmjp+PrG/uBwf/bIeD7+3BJc/9SHOmPsGTrj9ZYy64RmM++cLmHLXfFzz3EK89OUf2Haw2K7t6P55mHfz2UhyMnnb8Xgbm3yv+t7QHPjj9ZLjubvnE8ZWUsrdAArd7Kuj/QnGuMR2nRnASh/2v6q1jbv9kxMRkfZjjKZG318Tmhrs20REdP4Nmbt2T8cD8y7F429fjf5DugVknwnJsTj+tGHW5SWfr0VttW93ewglZuuamrNlrq6pOVeA2bqj5myZq2tqzhVgtu6oPVsip6TU5g9pWue/q1BYEUIkA8izWeXLB20AsMJheUiHOhRGmpvtXwCjIv248BFl36apqWMvqrMvTsLT88pQXWPZz0NPl6J3jwhceHaiyzavvluBfz18GAAwfHAU1m6ynHAlJji/8DF0UBTefD7b5f6iow3ITDdh/OgY3HBFMtasr8eVtxRiw1+Wi5MVlS244LoCrF+ah2g/qvx0BmbrnNqzZa7OqT1XgNm6wmwtmG34ZavHXCurlYp+O/dYJpv8302puGxWktt+jR8dg6cfzMDVtxYBAJqagGfnl+O/j2b6cHQUahxTuWcU9n8zTS2+T8RpdKhAbRKdMxHnXJtq24X1FfixcLPHNmo+Xl/o8bUeANZtasCTL1kmIBqNwLwnM2E0+n7s4UyP2erhfVyPuQLaP+8G9JutK7dem4JbrklGdY1ESakZazc24OslNfjg0yrU1kns2tuES24sxOIfa/G/Z7NgMoXna7jJ6HA+0ezHRGaHyc+O+/TH1yu34OuVW5z+W11DE+oamlBYVo0VW/bhla+X46ThfXH3+SdZJ2v3y83AbTMn4u43vnXom30OjX4cr+Nk70Acr5dsz90rAGzzsf1KAKc72ZfPOmlcYrtus5Sy1tudSymrhRB/ATjSzf7JCaPJ4TXBj0lHjQ7VIk0RwfsbmXvtmxBCIC4hCqmZieg3KBfHnToUI8b3gcFgwJGjeuKpd2dj3iNf4YsFXn/XwampM49CVLRyp4cv3u3Y/jobs3VNzdkyV9fUnCvAbN1Rc7bM1TU15wowW3fUni0RkVaE5yfO1Jkcb3e325fGUspSALZlSvp2uEcAhBCZQohBvvwA6B2I527j+MG9PxctGh0q1Jg6+FWJLlkmPDk3w7rc0gJccmMhZl6Zj8U/1qCopBmNjRKHCpqx6KtqTJl1ELPnFKGlBZg1Ix5jj1IqmiT5eOHDlZFDo/Hzp7kYOUS5ZcuO3U148Y0KN61Ci9l6R23ZMlfvqC1XgNl6i9m27bNDXWK2AaDHXNsmpbTJyjDirn+keNW3y89LRJ+eygdkCxZVwWzmN6hVhmMqN8yyxW7ZJHx/bXSsOO24z2DoEZeBMelKtAv3rfDqedV6vL7S42u92Sxx1S2FaCvoefNVyRgxpH3VULXTY7Z6eB/XY67+UNt5N8BsnRFCICHegJ55ETjz1Hi8+p8sbP6lOyaMVva7YFEV/nlvsZu9hFaz2eF8wo9JyBEOkxQc99kZfli7HZc99QGq6pTKbaeOHoCBeVl22zU7vG76d7wO508tnXa8tufue6T0uRyW7dghVQiR2oG+dMa4xHadT/t30saxv2EpHMZV5mb732ejHxXlTQ7VIR33GWhSSlRX1mPfjiL88NmfuOfq/+H2i+ejpMDynmo0GXHdPdMwYdJgv5/DYDTgtPOOti7/+ft27NtZ1OG+dyZm65zas2Wuzqk9V4DZuqL2bJmrc2rPFWC2rmghWyIireDEbcp1WN7vxz4O2DwOzL05gOsAbPLx57MAPTcAIDLCfrm+wfcLH45tIv2oeuPoqguTcO+t9p/fLvqqGqecfwhdjtyNmO470G34bsy8Mh/f/2wpeHH26fF4/ekslFcoJ5I9uzscYAckJhjxxnNZMNi8oixYWBWw/Qcas/WemrJlrt5TU64As/UFs2W24UCPuToe8yXnJiIqyruhlhAC50yLty5XVrVg/Wbekk5lOKZyo0naVz+MNPg+G8yxjeM+g+HcHuNgaJ103WBuwif7V3nVTq3H6ys9vtY/9VIZ/txoeX3umWfC/beldbi/4UiP2erhfVyPufpLTefdALP1Vl5uBL5a0BWD+kda1730RgU2/BV+f69A+0nWkX7Mpo90mGAQionbALC7oBTPfvKr3bqpR/W3W24yO5w/+XH78UiHSRhNQZ5QYcN2LNDRcQDQsbFAUMclrRW94wK4/0QhhPvbW4SHkI+rmh0qykdG+fE34tDGcZ+dYfOaPbjrqtdRX9toXXft3ae3q4bprQmTBiGjS7J1+fN31Fcpktk6p/Zsmatzas8VYLauqD1b5uqc2nMFmK0rWsiWiEgrOHGb0h2W8/3YxyGbx5q5cpmUaP9hrz8XPurq7dskJwbmFtf3zUnDx691Qc889yeX0dEC981JxfvzshEVZcDe/cqtXAbbXKgIhIH9ozBxXIx1ee2mBpSWhd8EA4DZ+kot2TJX36glV4DZ+orZMttQ02OusTH2w6pJE2N96teYkfYVWzdtaXSxJYUpjqncqG6qt1uONPo+ASvKoU11U12H+uRJvCkap+QMsy5/n78R5Y01XrVV4/H6Q2+v9dt3NeL+p0qtyy8+lonYWG1+pKa3bAF9vI/rMdeOUMt5N8BsfREfZ8Bj9yinbVIC/3uv0k2L0LGtUA0AURG+ZxLtMPm5qjZ0k9S/WvE3auqV18bR/fPs/r3a8Xj9qIQXHelwvHX1LrYMHCGECYDtxOOOjgOAjo0Fgj0uCfT+nT0HOVFT7TDG8GvSkcMYoyo0Y4x9O4rwxQJlclBqRiJGH3eEX/uaduE46+P8/aVY+dOWDvevszFb59SeLXN1Tu25AszWFbVny1ydU3uuALN1RQvZEjkjpDZ/SNs6eOND0oBkh2V/zjRs2zjuT7UiIy231ayqtlTnKCpp9nkfxQ5t0lICd2F3xinxOPWkOHz/Sy2+/qEG23c1oqjEDCEsVWQmjo3B+WclICvD8mduNkus3aR8CD7oiMBe1AKACWNisPQ35dfhUGEzUlMCc7EnkJit79SQLXP1nRpyBZitP5htYDBb/+gx17RU+wxGHBnlU5+65dh/+BeuE4PIpWSHZY6pbDRLM6qb6xFvskxsTI2M89CivdTIeLvl8qbagPTNlTO6jUKsSfk7/nCv91VH1Hi8/tDTa72UErPnFKG+dWLjBWclYNJE33NVCz1la+2fDt7H9ZhrR6nhvBtgtr6afHwsUlMMKC2z/H8tWxl+X44CLNWxq+saEB9jeT1KTfDtCyUAkOLQprwmdMda39SMv/cVYlQ/SwHnjGSHc51q+775dbzxDsdbHfyJ2wj8OMDZPn3h2DbQ45JA79/ZPsmJ5iYzaqvrERtvGWMkpcZ7aNFecpr9+WtVeejGGD9+uQ4zrzzOujxoRHf8seQvn/bRd1BXDBrRw7r81XvLIaX6ZjUw2/a0kC1zbU8LuQLM1hktZMtc29NCrgCzdUYr2RIRaQUnbpPj1Sh/PtG0bePb1S3XXgTwkY9teiPAt6DL7WLC39st1UAOHPL9wse+g/Zt8roG7tatgOXizKknxeHUkzxfNF6/uQG1dZaTLiGAY4+O8dDCd1kZ9hewqmtCcwtObzBb36glW+bqG7XkCjBbXzHbwGG2/tFbrt26KsOqhHhDu8qHnsTF2t+O3p9KiRRSHFN5UFRfifjWD8izon2/G3p2jH2bwrryQHTLKQMEzs472rq8oWwv/q486NM+1HS8HaGX1/offqnFz39Y5hilpRjwn/szAtrPcKSXbNvo5X1cb7l2lFrOuwFm6wuDQWDEkdH44RfLxfbdNtW9w01RebV14nZWSoLP7bs4tCkoqwpIv/x1uFKZ4BDrULWusrYBdQ1NiGld79fxpiptauob21UtD5JAjwOc7dMXwR6XhNvxdpawGFeVFFQgr49ljJGR7fsYI6NLst1yUX5FILrll91bC9DU2IyI1kr5WbmpPu9j+sXjrY/raxuxeOGqgPWvszFbe1rJlrna00quALN1pJVsmas9reQKMFtHWsqWiEgLOHGbHH8H/PlE0/bDtoB8si+lLAJQ5EsbIYTnjXzUp1eE9cLHnv2+X/jYY/Phf0qyoV0Vp8703ifKh/Mjh0QhNyewF2EAWCuQtUkP4fF6wmx9o5Zsmatv1JIrwGx9xWxDg9kq9JZrj1xlXW1dC6SUPp2bVlTaTwQKx2qO5BbHVB7srylBr/hMAECXmBSf29u2qWisRUVT8CpGHps1AF1jlQ+9P/Ch2nYbNR1vR+jltb6mVnnvPVzWgqzBu/x6jp//qIOxy3a7dffemor75qT5tb9g0ku2bfTyPq63XDtKLefdALP1VXqaUlG8sip8J+TvKypHry6W94ictESf29u2qaipR0VNp1SgdikqQjlldqywDQD7i8vRL9fy5Sh/jreLTZt9RWV+9NAvgR4HAB0bCwR7XBJux9spwmVcdXDvYeT1yQIAZHX1fYxh26aqvDak1SIBoLK8FmmZlr/b2Hjf5u8np8Xj2ClHWpeXfrEW1ZWhfY3rCGar0FK2zFWhpVwBZmtLS9kyV4WWcgWYrS2tZUtEpAWBu+8hqZXjp/n+fFBme89K368OhLGhA5WTneLDZrsLGd5YuVb57NJ2X52tqUliwSLlwsf0Kb7fBsYbO/Yo/z9GI5CTFb7fDWG2vlFLtszVN2rJFWC2vmK2nY/Z2tNbrqNHKH00m4Gde3w73raJNm1yssN3YhA5xTGVB9urCqyPU6Pi0SUm2af2g5K7Od1XMMzqPs76uLi+EksKNvm8DzUdb0fo7bVeT/SWrV7ex/WWa0ep5bwbYLa+sv1CTlJC+F4e2Xaw2Po4NSEWXVJ9m8w8uEe2032FSreMZOtjZ9W/bfvYt2s6Ikzev5ZGR5jQNyfdZl8l/nXSd4EeBzjbpy+CPS4Jt+PVld1b862Pk9PikZmT7FP7I4YoY4xdNvsKlegY5Vehtsq3CUOnzhpjrTQJAF+86/uXbcMJs1VoKVvmqtBSrgCztaWlbJmrQku5AszWltayJSLSgvD9ZJI6S6PDcrQf+7Bt47g/VZswxv6/47cV3lc6272vCQfzlc8djwnCbVu99ez8chQUmQEAsTECl5/ve9UST6SU+GZJjXX56BHRiI0N35cYZus9NWXLXL2nplwBZusLZhsazNae3nIdd1QMTDZzeZb86lt13J//ULY3GIBxo0J3zOQXjqk8WFu6x255WEoPr9vmxKQgK1q5jeXa0t0B6lV7fRKyMTKtl3V50f6VMEvfK3Gq5Xg7Si+v9RERAkmJBr9+jDZzzoxGtPv36KjgVLnvKL1k20Yv7+N6y7Uj1HTeDTBbX/21VTnV6p4bvsV+/9xx0G55eJ8cr9vmpCUiKyVB2df2g262Dr6ctET0zlHuMLFy6/5229geb1SECYO6Z3m9/8E9s+0mev+5/YCfPfVZoMcBzvbpi2CPS8LteHVl05o9dsuDRvbwum1W1xSkZytjjE2r97jeuBOkZychLkH5VSg8VO51W1OEEaecO9q6vH7FTuzZXhjI7nU6ZmuhtWyZq4XWcgWYbRutZctcLbSWK8Bs22gxWyKnpMZ+SPPC9xNn6iwVDsv+fNhm+4l+uf9dCT/HjIlBQrzyZ/L+p+2rgbiyYKH9tlNPjAtYv3yxd38THnq61Lp83WXJyM4MfJWgdxdW2d2OdfrU8K5Sxmy9p6Zsmav31JQrwGx9wWw7H7NtT2+5xsUaMPl4pZ+vvF0BKb0bUVdUmrHwy2rr8sghUUhNCc9KneQSx1QerCvbg+pmpQLIpC5DvG47JWeY3fKy4q2B6lY7ttW2G1uasWjfSr/2o5bj7Si9vNafelIcSrf29utnwmjlT3vC6Jh2/37Hjamddqy+0Eu2bfTyPq63XDtCTefdgP6yfefjShw45A9GXAsAAHjhSURBVFtV8TbL19TZVdU/fkJ4ftECANbuOIjqOqUa+pRR/b1ue8pRR9gt/7Y5tF8Eu3LKaLvln9bvbLfNss170NKivPb6e7zmlhb88fdeP3rpl0CPA4COjQWCPS4Jt+PVlU2r96C2WhljTDx1qNdtjz99mN3yql86PsY445LxiIjw75zn+NPs+7N+RfvXBFeOnToEqRnKF3s+f+d3v/oQTpithdayZa4WWssVYLZttJYtc7XQWq4As22jxWyJiLSAE7fJ8b6BmX7sw7bN4Q70JexERxtw9unKxZnFP9Zi207PRSDq6lrwyjvK55h9e0VgzAjnn2OuWV+PZ+aV4aMvqmA2B/YrMyWHzZh63kFUVVuqxKWnGnH79Skut3/13QqUHDb7/Dy79jbhlnuV21mmpxox++IkNy1Cj9l6R23ZMlfvqC1XgNl6i9ky23Cht1wB4IbLlTzWbWrAy286XtN27p7HDqOiUqnoe/3lyb53mEKNYyoPGluasSR/k3V5bEY/5MWmuWlhEWUw4cxuR1mX99aUYHOF8wqKRyTm4Lwe43Fi9mAY4HsV46SIWEzOUT64X5K/EaWN1W5auNYZxxsO9Pharxd6zFYP7+N6y1Uv592A/rJd8mstxkzdjyW/1vr0PE1NErfeZ3/adt6MBBdbh15jsxk/rN1uXR43sAfyMpM9touKMOKsY5Qvje0tLMOmPQVOtx3QLRMXnDAcJw3vC4Nwff5kMhowa+IwmAy+X046fmhvTB872Lq8bPMe/LWvfWW3ovJqrNqmVOI+ZfQAJMZGedx/SnwMpoxSJm6v3LofxRU1bloEjpSyEYDttx86Og4AOjYWCPa4JND7d/Yc5EJTYzN+XbzRujxyQj907ZHusV1klAmnnKN8eeLAnhJs3dC+6j0A9BmYgzMuGY8JkwfDYHA/pjrjovF4/O3ZyM717fw5o0sSZl55nHW5tLgS6/7wftLR9AuVL9sWHirD8qV/+/T84YjZWmgtW+ZqobVcAWbbRmvZMlcLreUKMNs2WsyWiEgLOHGbHK8Cd/NjH3k2j/d1oC9h6Z+zk9H2mXRLC3D5Pwo9XqC4898lOHBIqcxz67XOT7xeW1CBo0/Zj1vnlmDW1QWYev5Bu8oiziz+scaryk+r19XjuDP2Y+tOSxUZkwn4YH420lJdf4Pvxf+Vo//4PXhmXpn1Yokna9bX48SzDuBwmbL9w3elIT4u/F9emK17as2Wubqn1lwBZusJs2W24UZPuQLAycfFYsJoZaLLP+8txsdfuq92+OwrZfjv68pkmQF9I8N68gi5xDGVFxbs+Q1maXkdMwoD7htytscJ1jf0n4KsmGTr8ju7fnG63bTckXhj3HW4ZcCpeHT4+XjuqEshfJy8PaPbUYg2RliXP9j7h0/tHQXzeMOJ3l7r9URv2erlfVxPuerpvBvQV7YAUFBkxuRzD+KqWwtRUNTsdlvAMkn9wusLsHyNUmntjKlxGH6kPwWDO8/bS/6EuaX1fMJgwAMXT3Y7wRoAbj7jGGSnKK9Fb/6w2ul2Z4wbhLfvOA9zzp6IJ646Df+9YQZc7To6MgJ3nHM8Prz7Ihw/tLfHPrQ5bcwAPHzZKdbJC3WNTXj2019dbv/2D2usjxNiovCv8070+Bz3XXgyYqKUc7g3v3d+vEFkOxbo6DgA6NhYIKjjEillKQDbb0x0dP/VUsoyP/ahW4ve+A1mc+trgtGAWx4+2+PkoMtvnYqMLsnW5YWvOx9jTDprFJ758HrMvvM03PXMBXhw/mUQHv7WjxjaDf/99GacfcWxiIj0fAeMzJxkPDDvUiQkKYXXP3jlZzQ1en4dB4ABw/LQ78hc6/JX7y33+H6kFsxWm9kyV23mCjBbrWbLXLWZK8BstZwtEZHahf+nzhRsOxyWe/jSWAiRAMD23r7bXW2rVoP6R+Hqi5TKOn+srsfpFx1CeUX7qj3NzRK3P1CMF15TLtwdNSwKl5+X2G5bKSXueLAELTbXjpb8Uocvv3dfEeS8awowZOI+PPtKGbbtbLS7CFJf34Klv9Xi0psKMP70/diyQ7n15zMPZmDiuFiPx1te0YJb55Ygd9guzJ5TiI++qMLBfPuTPrNZYtnKOlx5SyHGnrof+w4q/37tpUm44vzwrkTUhtlqM1vmqs1cAWbLbC2YrXqy1VuuQgi8+UI2EhMsQ6ymJuDcqwpw2c0FWLtRmSAipSXbMy49hFtsKv7FxQp8OD8bJpPvlYIp5Dim8sKu6iJ8sm+ldXlISnc8PepixJvaT5gyCgNu6j8Fs3oolUA2l+/H5wfWtNsWAG7qPxVGoXy8MSa9L47J7O9134zCgLO7H233XB2tdB3M4w0nenut1xO9ZauX93G95aqX825AX9lGRojWvgGvL6hEr9F7cP61+Xj7o0ocKmi2e67yCjPe/LASw0/ah4+/UO6kkdfVhJcf96dYcOfalX8YC39TqsMN7ZWD566bjviY9pWojQaBf8w4BucdP9y6btOeAnz2+2an+/7HjGNhtKmgffSA7jh2cC+3/emZnYr/zJ6GLx+8HNdPG4ejB+QhPjrSbpvoCBOOO7IX5t18Fh68ZAqiWycitLRI3PfWd9h+0LFos2LZX3vw26bd1uXJI/tj7kWTEGlqP5E/OsKEf186BccN6W1dt2TtdqzY0unfgbQ9d+/hR3vbNmVSyo5UoO6McYntc/i0fydtNDnuCaZ9O4rwzYfKGGPg8O6Y+9IliEtoP8YwGA24Ys5UTL9IGWNs3bAf3y10/uWGK+dMhdGovCaMGNcXoyce4XRbAGhqsry/xMZF4Yo5U/HW0jtw7V2n46jj+iM23v41KjMnGbNmT8QLi25Cj77Z1vUrftqCL971/guz0y8eb31cX9eIbz/u9C9qBA2z1Wa2zFWbuQLMVqvZMldt5gowWy1nS2RLSG3+kLYJbypfUOcTQvwEoO1eF3ullD2C+Fz7oFRH+FlKOdGHticD+M5m1aVSyjcD2D2vCSEGAbDej3rDT3kY1N/z7RS9UVvbgmOmH8C6TQ3WdQnxBpwzLR6Dj4hEZKTArr1N+OCzartKNXldTVj2ZTfkZLf/plxxSTOyj9zdbv1j96RjznWub42S2n+n3W14Y6IF0lKNqK+XKCltfzEmMcGA157Owpmnxrf7N0czr8zHoq+c3w48MlIgNdkAo1Gg+LAZjY32rx1CAHf/MxX3zUn1+C3CcMJstZktc9VmrgCzBZgts1VXtnrJ1daPy2px9hX5KK+wr+wYGyOQlmJEYUn7bNNSDPj4tRwcOzYGgbJ5awOGTLSbtDBYSul81oZGcUzlO8cx1aCXrkRM94yA7T/KEIHXxs5G/8Qc67rq5nr8kL8RO6sK0djSjNzYVEzqMsSu8nR+XRku/+NllDS0r36bHBmH70+8q936Z7d8g3d2u67oaOvkLkPw8LBZ1uV713+Ibw6t8/7AXAjG8XbEiuEfB3R/bfT4Wu+tE848gJ//qAMAHDc2BksX5XpoEV70mG24vI8Hk15y1dt5N6CfbCurzLh6ThE++tx5viYTkJluhNkMFB822006B4C+vSLw6Rs5OKJvpNP2/hr5wLUB3V+b6AgT/jfnXBzRTZloXl3XgO/WbMOO/MNoajYjNz0Jk0f1t6u0nX+4Epc8+T6KK9pPsk+Jj8HSx69pt/7pRb/grR/af3EsKsKIT+67FF1S20/uB4C6hiZU1NYjwmhAcnyM3YRwAKiqa8C9b36Lnzbs8ni8qQmxeOeO8+yeq6yqFt+u3oo9hZbizD2zUzB51BFIiVded7fsL8IV//kQtQ1N7fbpr7rSAmz94HHbVe3GVEKIBwDcY7Oqp5Ryj7fPIYQ4AKBr6+JPUsrj/exu2/6COi4RQrwF4KLWxQYASVLKBnhBCBELoBxAW4n0N6SUl3nbP5v9vAHgkrZlKWXYvVA7jqvG97wCCVGBGVdFRUfgqXevQe+ByhijtroeP3+zAXu3F6KpsRlduqXhuFOG2FWJLDxUhltmvYTS4vZjjKSUOLz/+93t1r/6xNdY+LrzMVXXHun4v/+ch94Dcpz+e31dIyrLahETG4mE5PZfyFnx0xY8dut7qKtt9HTIAID0rET87/vbYYqwfJHj249X4dl7FnnVVi2YrTazZa7azBVgtlrNlrlqM1eA2YYy26qGYizb/ZrtKt1dq6LgcBx3jTzuFsQlZLtpoT41VQVY8/N/bFfx70djPN93gfTgVwDntz4eLYSIkFJ6+wnnBIfl8L+Xsx9iYw1Y/H5XzLjsEH5fZam0VFXdgtcWVLpsM/iISHw4v4vTix4AkJ5mRHKSod3FwL69Ipxu3yY+zmB34aOuXtpdbLF1/PgYvPR4Jvr28u5CxIfzs/HGB5V45Nky7Nxj/yvQ2ChRUNT+wgoAjDsqGg/emabKCmXMVpvZMldt5gowW4DZ2mK24U8vudq3jcVvn3fDuVfnY/NW5cOz2jqJ2rr2zzd9Shyeuj8DPfPc95/CHsdUXmhoacL1K1/HUyMvwtCU7gCAeFM0zuh2lMs2O6oKcOfaBS4nMZc31qCyqQ6JEfYTJvfVuK7m6GhW97HWx4cbqvB9/kY3W3svGMcbjvT4Wq8XesxWD+/jeslVb+fdgH6yTUww4v15XXDh2dV49pVyLP2tzu7fm5uBQwXt842MFLji/EQ8dGcakpPaV3AOV/VNzbj2uYV4+prpGNbbcnE//v/bu+942a6yfvyfJ7lJSA+B0JKQUBUIHWkBBUUEQUGKEgEFEZAuPwERRSnfr4B8VRREehVRUBCQJtKkF+mhBSQkBEJ6SG93/f7Yc7z7zD1tzpk5M2fO+/16ndedve7ea56ZtffMXmuevfa+++R+d7rpstuccMoZeeor/33JpO0kOfv8i/KTCy/OQfstnmHupNPOXnL9Sy67Ivd7zuvziHvcNg+4081yyAGLz7v23Wev7LvP7vvEFTt35v2f/1Ze+q5P5ZQzz93t/5dy1nkX5lEv+pf8zWPvk+te4ypJkisfuN+imcSHfeGEH+Rpr373WJO2RzCckXGnJCeuZcO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      "text/plain": [
       "<Figure size 3900x1500 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 3, figsize=(13, 5))\n",
    "\n",
    "param_grid_linear = {'C': np.linspace(1, 2, 6),\n",
    "                     'gamma':  np.linspace(1, 2, 6)}\n",
    "\n",
    "param_grid_one_log = {'C': np.linspace(1, 2, 6),\n",
    "                     'gamma':  np.logspace(-3, 2, 6)}\n",
    "\n",
    "param_grid_range = {'C': np.logspace(-3, 2, 6),\n",
    "                     'gamma':  np.logspace(-7, -2, 6)}\n",
    "\n",
    "for param_grid, ax in zip([param_grid_linear, param_grid_one_log,\n",
    "                           param_grid_range], axes):\n",
    "    grid_search = GridSearchCV(SVC(), param_grid, cv=5)\n",
    "    grid_search.fit(X_train, y_train)\n",
    "    scores = grid_search.cv_results_['mean_test_score'].reshape(6, 6)\n",
    "\n",
    "    # 교차 검증 평균 점수의 히트맵 그래프\n",
    "    scores_image = mglearn.tools.heatmap(\n",
    "        scores, xlabel='gamma', ylabel='C', xticklabels=param_grid['gamma'],\n",
    "        yticklabels=param_grid['C'], cmap=\"viridis\", ax=ax, vmin=0.3, vmax=0.9)\n",
    "    \n",
    "plt.colorbar(scores_image, ax=axes.tolist())\n",
    "plt.show() # 책에는 없음"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 비대칭 매개변수 그리드 탐색"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "그리드 목록:\n",
      " [{'kernel': ['rbf'], 'C': [0.001, 0.01, 0.1, 1, 10, 100], 'gamma': [0.001, 0.01, 0.1, 1, 10, 100]}, {'kernel': ['linear'], 'C': [0.001, 0.01, 0.1, 1, 10, 100]}]\n"
     ]
    }
   ],
   "source": [
    "param_grid = [{'kernel': ['rbf'],\n",
    "               'C': [0.001, 0.01, 0.1, 1, 10, 100],\n",
    "               'gamma': [0.001, 0.01, 0.1, 1, 10, 100]},\n",
    "              {'kernel': ['linear'],\n",
    "               'C': [0.001, 0.01, 0.1, 1, 10, 100]}]\n",
    "print(\"그리드 목록:\\n\", param_grid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "최적 파라미터: {'C': 10, 'gamma': 0.1, 'kernel': 'rbf'}\n",
      "최고 교차 검증 점수: 0.97\n"
     ]
    }
   ],
   "source": [
    "grid_search = GridSearchCV(SVC(), param_grid, cv=5, return_train_score=True)\n",
    "grid_search.fit(X_train, y_train)\n",
    "print(\"최적 파라미터:\", grid_search.best_params_)\n",
    "print(\"최고 교차 검증 점수: {:.2f}\".format(grid_search.best_score_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mean_fit_time</th>\n",
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       "    <tr>\n",
       "      <th>std_fit_time</th>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>mean_score_time</th>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>std_score_time</th>\n",
       "      <td>0.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>param_C</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>param_gamma</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>param_kernel</th>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>rbf</td>\n",
       "      <td>linear</td>\n",
       "      <td>linear</td>\n",
       "      <td>linear</td>\n",
       "      <td>linear</td>\n",
       "      <td>linear</td>\n",
       "      <td>linear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>params</th>\n",
       "      <td>{'C': 0.001, 'gamma': 0.001, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.001, 'gamma': 0.01, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.001, 'gamma': 0.1, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.001, 'gamma': 1, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.001, 'gamma': 10, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.001, 'gamma': 100, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.01, 'gamma': 0.001, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.01, 'gamma': 0.01, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.01, 'gamma': 0.1, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.01, 'gamma': 1, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.01, 'gamma': 10, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.01, 'gamma': 100, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.1, 'gamma': 0.001, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.1, 'gamma': 0.01, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.1, 'gamma': 0.1, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.1, 'gamma': 1, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.1, 'gamma': 10, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.1, 'gamma': 100, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 1, 'gamma': 0.001, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 1, 'gamma': 0.01, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 1, 'gamma': 0.1, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 1, 'gamma': 1, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 1, 'gamma': 10, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 1, 'gamma': 100, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 10, 'gamma': 0.001, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 10, 'gamma': 0.01, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 10, 'gamma': 0.1, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 10, 'gamma': 1, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 10, 'gamma': 10, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 10, 'gamma': 100, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 100, 'gamma': 0.001, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 100, 'gamma': 0.01, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 100, 'gamma': 0.1, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 100, 'gamma': 1, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 100, 'gamma': 10, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 100, 'gamma': 100, 'kernel': 'rbf'}</td>\n",
       "      <td>{'C': 0.001, 'kernel': 'linear'}</td>\n",
       "      <td>{'C': 0.01, 'kernel': 'linear'}</td>\n",
       "      <td>{'C': 0.1, 'kernel': 'linear'}</td>\n",
       "      <td>{'C': 1, 'kernel': 'linear'}</td>\n",
       "      <td>{'C': 10, 'kernel': 'linear'}</td>\n",
       "      <td>{'C': 100, 'kernel': 'linear'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split0_test_score</th>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.91</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.91</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.91</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.52</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.87</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split1_test_score</th>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.96</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split2_test_score</th>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.91</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.68</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.55</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.59</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.59</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.77</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split3_test_score</th>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.59</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.59</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split4_test_score</th>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.73</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.73</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean_test_score</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.84</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std_test_score</th>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rank_test_score</th>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>22</td>\n",
       "      <td>20</td>\n",
       "      <td>8</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>22</td>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>17</td>\n",
       "      <td>26</td>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>24</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>24</td>\n",
       "      <td>27</td>\n",
       "      <td>21</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split0_train_score</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split1_train_score</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.97</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split2_train_score</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.84</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split3_train_score</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.89</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split4_train_score</th>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean_train_score</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std_train_score</th>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                               0   \\\n",
       "mean_fit_time                                                 0.0   \n",
       "std_fit_time                                                  0.0   \n",
       "mean_score_time                                               0.0   \n",
       "std_score_time                                                0.0   \n",
       "param_C                                                       0.0   \n",
       "param_gamma                                                   0.0   \n",
       "param_kernel                                                  rbf   \n",
       "params              {'C': 0.001, 'gamma': 0.001, 'kernel': 'rbf'}   \n",
       "split0_test_score                                            0.35   \n",
       "split1_test_score                                            0.35   \n",
       "split2_test_score                                            0.36   \n",
       "split3_test_score                                            0.36   \n",
       "split4_test_score                                            0.41   \n",
       "mean_test_score                                              0.37   \n",
       "std_test_score                                               0.02   \n",
       "rank_test_score                                                27   \n",
       "split0_train_score                                           0.37   \n",
       "split1_train_score                                           0.37   \n",
       "split2_train_score                                           0.37   \n",
       "split3_train_score                                           0.37   \n",
       "split4_train_score                                           0.36   \n",
       "mean_train_score                                             0.37   \n",
       "std_train_score                                              0.01   \n",
       "\n",
       "                                                              1   \\\n",
       "mean_fit_time                                                0.0   \n",
       "std_fit_time                                                 0.0   \n",
       "mean_score_time                                              0.0   \n",
       "std_score_time                                               0.0   \n",
       "param_C                                                      0.0   \n",
       "param_gamma                                                 0.01   \n",
       "param_kernel                                                 rbf   \n",
       "params              {'C': 0.001, 'gamma': 0.01, 'kernel': 'rbf'}   \n",
       "split0_test_score                                           0.35   \n",
       "split1_test_score                                           0.35   \n",
       "split2_test_score                                           0.36   \n",
       "split3_test_score                                           0.36   \n",
       "split4_test_score                                           0.41   \n",
       "mean_test_score                                             0.37   \n",
       "std_test_score                                              0.02   \n",
       "rank_test_score                                               27   \n",
       "split0_train_score                                          0.37   \n",
       "split1_train_score                                          0.37   \n",
       "split2_train_score                                          0.37   \n",
       "split3_train_score                                          0.37   \n",
       "split4_train_score                                          0.36   \n",
       "mean_train_score                                            0.37   \n",
       "std_train_score                                             0.01   \n",
       "\n",
       "                                                             2   \\\n",
       "mean_fit_time                                               0.0   \n",
       "std_fit_time                                                0.0   \n",
       "mean_score_time                                             0.0   \n",
       "std_score_time                                              0.0   \n",
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       "param_gamma                                                 0.1   \n",
       "param_kernel                                                rbf   \n",
       "params              {'C': 0.001, 'gamma': 0.1, 'kernel': 'rbf'}   \n",
       "split0_test_score                                          0.35   \n",
       "split1_test_score                                          0.35   \n",
       "split2_test_score                                          0.36   \n",
       "split3_test_score                                          0.36   \n",
       "split4_test_score                                          0.41   \n",
       "mean_test_score                                            0.37   \n",
       "std_test_score                                             0.02   \n",
       "rank_test_score                                              27   \n",
       "split0_train_score                                         0.37   \n",
       "split1_train_score                                         0.37   \n",
       "split2_train_score                                         0.37   \n",
       "split3_train_score                                         0.37   \n",
       "split4_train_score                                         0.36   \n",
       "mean_train_score                                           0.37   \n",
       "std_train_score                                            0.01   \n",
       "\n",
       "                                                           3   \\\n",
       "mean_fit_time                                             0.0   \n",
       "std_fit_time                                              0.0   \n",
       "mean_score_time                                           0.0   \n",
       "std_score_time                                            0.0   \n",
       "param_C                                                   0.0   \n",
       "param_gamma                                                 1   \n",
       "param_kernel                                              rbf   \n",
       "params              {'C': 0.001, 'gamma': 1, 'kernel': 'rbf'}   \n",
       "split0_test_score                                        0.35   \n",
       "split1_test_score                                        0.35   \n",
       "split2_test_score                                        0.36   \n",
       "split3_test_score                                        0.36   \n",
       "split4_test_score                                        0.41   \n",
       "mean_test_score                                          0.37   \n",
       "std_test_score                                           0.02   \n",
       "rank_test_score                                            27   \n",
       "split0_train_score                                       0.37   \n",
       "split1_train_score                                       0.37   \n",
       "split2_train_score                                       0.37   \n",
       "split3_train_score                                       0.37   \n",
       "split4_train_score                                       0.36   \n",
       "mean_train_score                                         0.37   \n",
       "std_train_score                                          0.01   \n",
       "\n",
       "                                                            4   \\\n",
       "mean_fit_time                                              0.0   \n",
       "std_fit_time                                               0.0   \n",
       "mean_score_time                                            0.0   \n",
       "std_score_time                                             0.0   \n",
       "param_C                                                    0.0   \n",
       "param_gamma                                                 10   \n",
       "param_kernel                                               rbf   \n",
       "params              {'C': 0.001, 'gamma': 10, 'kernel': 'rbf'}   \n",
       "split0_test_score                                         0.35   \n",
       "split1_test_score                                         0.35   \n",
       "split2_test_score                                         0.36   \n",
       "split3_test_score                                         0.36   \n",
       "split4_test_score                                         0.41   \n",
       "mean_test_score                                           0.37   \n",
       "std_test_score                                            0.02   \n",
       "rank_test_score                                             27   \n",
       "split0_train_score                                        0.37   \n",
       "split1_train_score                                        0.37   \n",
       "split2_train_score                                        0.37   \n",
       "split3_train_score                                        0.37   \n",
       "split4_train_score                                        0.36   \n",
       "mean_train_score                                          0.37   \n",
       "std_train_score                                           0.01   \n",
       "\n",
       "                                                             5   \\\n",
       "mean_fit_time                                               0.0   \n",
       "std_fit_time                                                0.0   \n",
       "mean_score_time                                             0.0   \n",
       "std_score_time                                              0.0   \n",
       "param_C                                                     0.0   \n",
       "param_gamma                                                 100   \n",
       "param_kernel                                                rbf   \n",
       "params              {'C': 0.001, 'gamma': 100, 'kernel': 'rbf'}   \n",
       "split0_test_score                                          0.35   \n",
       "split1_test_score                                          0.35   \n",
       "split2_test_score                                          0.36   \n",
       "split3_test_score                                          0.36   \n",
       "split4_test_score                                          0.41   \n",
       "mean_test_score                                            0.37   \n",
       "std_test_score                                             0.02   \n",
       "rank_test_score                                              27   \n",
       "split0_train_score                                         0.37   \n",
       "split1_train_score                                         0.37   \n",
       "split2_train_score                                         0.37   \n",
       "split3_train_score                                         0.37   \n",
       "split4_train_score                                         0.36   \n",
       "mean_train_score                                           0.37   \n",
       "std_train_score                                            0.01   \n",
       "\n",
       "                                                              6   \\\n",
       "mean_fit_time                                                0.0   \n",
       "std_fit_time                                                 0.0   \n",
       "mean_score_time                                              0.0   \n",
       "std_score_time                                               0.0   \n",
       "param_C                                                     0.01   \n",
       "param_gamma                                                  0.0   \n",
       "param_kernel                                                 rbf   \n",
       "params              {'C': 0.01, 'gamma': 0.001, 'kernel': 'rbf'}   \n",
       "split0_test_score                                           0.35   \n",
       "split1_test_score                                           0.35   \n",
       "split2_test_score                                           0.36   \n",
       "split3_test_score                                           0.36   \n",
       "split4_test_score                                           0.41   \n",
       "mean_test_score                                             0.37   \n",
       "std_test_score                                              0.02   \n",
       "rank_test_score                                               27   \n",
       "split0_train_score                                          0.37   \n",
       "split1_train_score                                          0.37   \n",
       "split2_train_score                                          0.37   \n",
       "split3_train_score                                          0.37   \n",
       "split4_train_score                                          0.36   \n",
       "mean_train_score                                            0.37   \n",
       "std_train_score                                             0.01   \n",
       "\n",
       "                                                             7   \\\n",
       "mean_fit_time                                               0.0   \n",
       "std_fit_time                                                0.0   \n",
       "mean_score_time                                             0.0   \n",
       "std_score_time                                              0.0   \n",
       "param_C                                                    0.01   \n",
       "param_gamma                                                0.01   \n",
       "param_kernel                                                rbf   \n",
       "params              {'C': 0.01, 'gamma': 0.01, 'kernel': 'rbf'}   \n",
       "split0_test_score                                          0.35   \n",
       "split1_test_score                                          0.35   \n",
       "split2_test_score                                          0.36   \n",
       "split3_test_score                                          0.36   \n",
       "split4_test_score                                          0.41   \n",
       "mean_test_score                                            0.37   \n",
       "std_test_score                                             0.02   \n",
       "rank_test_score                                              27   \n",
       "split0_train_score                                         0.37   \n",
       "split1_train_score                                         0.37   \n",
       "split2_train_score                                         0.37   \n",
       "split3_train_score                                         0.37   \n",
       "split4_train_score                                         0.36   \n",
       "mean_train_score                                           0.37   \n",
       "std_train_score                                            0.01   \n",
       "\n",
       "                                                            8   \\\n",
       "mean_fit_time                                              0.0   \n",
       "std_fit_time                                               0.0   \n",
       "mean_score_time                                            0.0   \n",
       "std_score_time                                             0.0   \n",
       "param_C                                                   0.01   \n",
       "param_gamma                                                0.1   \n",
       "param_kernel                                               rbf   \n",
       "params              {'C': 0.01, 'gamma': 0.1, 'kernel': 'rbf'}   \n",
       "split0_test_score                                         0.35   \n",
       "split1_test_score                                         0.35   \n",
       "split2_test_score                                         0.36   \n",
       "split3_test_score                                         0.36   \n",
       "split4_test_score                                         0.41   \n",
       "mean_test_score                                           0.37   \n",
       "std_test_score                                            0.02   \n",
       "rank_test_score                                             27   \n",
       "split0_train_score                                        0.37   \n",
       "split1_train_score                                        0.37   \n",
       "split2_train_score                                        0.37   \n",
       "split3_train_score                                        0.37   \n",
       "split4_train_score                                        0.36   \n",
       "mean_train_score                                          0.37   \n",
       "std_train_score                                           0.01   \n",
       "\n",
       "                                                          9   \\\n",
       "mean_fit_time                                            0.0   \n",
       "std_fit_time                                             0.0   \n",
       "mean_score_time                                          0.0   \n",
       "std_score_time                                           0.0   \n",
       "param_C                                                 0.01   \n",
       "param_gamma                                                1   \n",
       "param_kernel                                             rbf   \n",
       "params              {'C': 0.01, 'gamma': 1, 'kernel': 'rbf'}   \n",
       "split0_test_score                                       0.35   \n",
       "split1_test_score                                       0.35   \n",
       "split2_test_score                                       0.36   \n",
       "split3_test_score                                       0.36   \n",
       "split4_test_score                                       0.41   \n",
       "mean_test_score                                         0.37   \n",
       "std_test_score                                          0.02   \n",
       "rank_test_score                                           27   \n",
       "split0_train_score                                      0.37   \n",
       "split1_train_score                                      0.37   \n",
       "split2_train_score                                      0.37   \n",
       "split3_train_score                                      0.37   \n",
       "split4_train_score                                      0.36   \n",
       "mean_train_score                                        0.37   \n",
       "std_train_score                                         0.01   \n",
       "\n",
       "                                                           10  \\\n",
       "mean_fit_time                                             0.0   \n",
       "std_fit_time                                              0.0   \n",
       "mean_score_time                                           0.0   \n",
       "std_score_time                                            0.0   \n",
       "param_C                                                  0.01   \n",
       "param_gamma                                                10   \n",
       "param_kernel                                              rbf   \n",
       "params              {'C': 0.01, 'gamma': 10, 'kernel': 'rbf'}   \n",
       "split0_test_score                                        0.35   \n",
       "split1_test_score                                        0.35   \n",
       "split2_test_score                                        0.36   \n",
       "split3_test_score                                        0.36   \n",
       "split4_test_score                                        0.41   \n",
       "mean_test_score                                          0.37   \n",
       "std_test_score                                           0.02   \n",
       "rank_test_score                                            27   \n",
       "split0_train_score                                       0.37   \n",
       "split1_train_score                                       0.37   \n",
       "split2_train_score                                       0.37   \n",
       "split3_train_score                                       0.37   \n",
       "split4_train_score                                       0.36   \n",
       "mean_train_score                                         0.37   \n",
       "std_train_score                                          0.01   \n",
       "\n",
       "                                                            11  \\\n",
       "mean_fit_time                                              0.0   \n",
       "std_fit_time                                               0.0   \n",
       "mean_score_time                                            0.0   \n",
       "std_score_time                                             0.0   \n",
       "param_C                                                   0.01   \n",
       "param_gamma                                                100   \n",
       "param_kernel                                               rbf   \n",
       "params              {'C': 0.01, 'gamma': 100, 'kernel': 'rbf'}   \n",
       "split0_test_score                                         0.35   \n",
       "split1_test_score                                         0.35   \n",
       "split2_test_score                                         0.36   \n",
       "split3_test_score                                         0.36   \n",
       "split4_test_score                                         0.41   \n",
       "mean_test_score                                           0.37   \n",
       "std_test_score                                            0.02   \n",
       "rank_test_score                                             27   \n",
       "split0_train_score                                        0.37   \n",
       "split1_train_score                                        0.37   \n",
       "split2_train_score                                        0.37   \n",
       "split3_train_score                                        0.37   \n",
       "split4_train_score                                        0.36   \n",
       "mean_train_score                                          0.37   \n",
       "std_train_score                                           0.01   \n",
       "\n",
       "                                                             12  \\\n",
       "mean_fit_time                                               0.0   \n",
       "std_fit_time                                                0.0   \n",
       "mean_score_time                                             0.0   \n",
       "std_score_time                                              0.0   \n",
       "param_C                                                     0.1   \n",
       "param_gamma                                                 0.0   \n",
       "param_kernel                                                rbf   \n",
       "params              {'C': 0.1, 'gamma': 0.001, 'kernel': 'rbf'}   \n",
       "split0_test_score                                          0.35   \n",
       "split1_test_score                                          0.35   \n",
       "split2_test_score                                          0.36   \n",
       "split3_test_score                                          0.36   \n",
       "split4_test_score                                          0.41   \n",
       "mean_test_score                                            0.37   \n",
       "std_test_score                                             0.02   \n",
       "rank_test_score                                              27   \n",
       "split0_train_score                                         0.37   \n",
       "split1_train_score                                         0.37   \n",
       "split2_train_score                                         0.37   \n",
       "split3_train_score                                         0.37   \n",
       "split4_train_score                                         0.36   \n",
       "mean_train_score                                           0.37   \n",
       "std_train_score                                            0.01   \n",
       "\n",
       "                                                            13  \\\n",
       "mean_fit_time                                              0.0   \n",
       "std_fit_time                                               0.0   \n",
       "mean_score_time                                            0.0   \n",
       "std_score_time                                             0.0   \n",
       "param_C                                                    0.1   \n",
       "param_gamma                                               0.01   \n",
       "param_kernel                                               rbf   \n",
       "params              {'C': 0.1, 'gamma': 0.01, 'kernel': 'rbf'}   \n",
       "split0_test_score                                          0.7   \n",
       "split1_test_score                                          0.7   \n",
       "split2_test_score                                         0.68   \n",
       "split3_test_score                                         0.68   \n",
       "split4_test_score                                         0.73   \n",
       "mean_test_score                                            0.7   \n",
       "std_test_score                                            0.02   \n",
       "rank_test_score                                             22   \n",
       "split0_train_score                                         0.7   \n",
       "split1_train_score                                         0.7   \n",
       "split2_train_score                                         0.7   \n",
       "split3_train_score                                         0.7   \n",
       "split4_train_score                                        0.69   \n",
       "mean_train_score                                           0.7   \n",
       "std_train_score                                            0.0   \n",
       "\n",
       "                                                           14  \\\n",
       "mean_fit_time                                             0.0   \n",
       "std_fit_time                                              0.0   \n",
       "mean_score_time                                           0.0   \n",
       "std_score_time                                            0.0   \n",
       "param_C                                                   0.1   \n",
       "param_gamma                                               0.1   \n",
       "param_kernel                                              rbf   \n",
       "params              {'C': 0.1, 'gamma': 0.1, 'kernel': 'rbf'}   \n",
       "split0_test_score                                        0.91   \n",
       "split1_test_score                                        0.91   \n",
       "split2_test_score                                        0.91   \n",
       "split3_test_score                                        0.86   \n",
       "split4_test_score                                        0.91   \n",
       "mean_test_score                                           0.9   \n",
       "std_test_score                                           0.02   \n",
       "rank_test_score                                            20   \n",
       "split0_train_score                                        0.9   \n",
       "split1_train_score                                       0.93   \n",
       "split2_train_score                                       0.88   \n",
       "split3_train_score                                       0.89   \n",
       "split4_train_score                                       0.93   \n",
       "mean_train_score                                         0.91   \n",
       "std_train_score                                          0.02   \n",
       "\n",
       "                                                         15  \\\n",
       "mean_fit_time                                           0.0   \n",
       "std_fit_time                                            0.0   \n",
       "mean_score_time                                         0.0   \n",
       "std_score_time                                          0.0   \n",
       "param_C                                                 0.1   \n",
       "param_gamma                                               1   \n",
       "param_kernel                                            rbf   \n",
       "params              {'C': 0.1, 'gamma': 1, 'kernel': 'rbf'}   \n",
       "split0_test_score                                       1.0   \n",
       "split1_test_score                                      0.91   \n",
       "split2_test_score                                       1.0   \n",
       "split3_test_score                                      0.91   \n",
       "split4_test_score                                      0.95   \n",
       "mean_test_score                                        0.96   \n",
       "std_test_score                                         0.04   \n",
       "rank_test_score                                           8   \n",
       "split0_train_score                                     0.94   \n",
       "split1_train_score                                     0.98   \n",
       "split2_train_score                                     0.94   \n",
       "split3_train_score                                     0.97   \n",
       "split4_train_score                                     0.96   \n",
       "mean_train_score                                       0.96   \n",
       "std_train_score                                        0.01   \n",
       "\n",
       "                                                          16  \\\n",
       "mean_fit_time                                            0.0   \n",
       "std_fit_time                                             0.0   \n",
       "mean_score_time                                          0.0   \n",
       "std_score_time                                           0.0   \n",
       "param_C                                                  0.1   \n",
       "param_gamma                                               10   \n",
       "param_kernel                                             rbf   \n",
       "params              {'C': 0.1, 'gamma': 10, 'kernel': 'rbf'}   \n",
       "split0_test_score                                       0.35   \n",
       "split1_test_score                                       0.35   \n",
       "split2_test_score                                       0.36   \n",
       "split3_test_score                                       0.36   \n",
       "split4_test_score                                       0.41   \n",
       "mean_test_score                                         0.37   \n",
       "std_test_score                                          0.02   \n",
       "rank_test_score                                           27   \n",
       "split0_train_score                                      0.38   \n",
       "split1_train_score                                      0.39   \n",
       "split2_train_score                                      0.37   \n",
       "split3_train_score                                       0.4   \n",
       "split4_train_score                                      0.36   \n",
       "mean_train_score                                        0.38   \n",
       "std_train_score                                         0.02   \n",
       "\n",
       "                                                           17  \\\n",
       "mean_fit_time                                             0.0   \n",
       "std_fit_time                                              0.0   \n",
       "mean_score_time                                           0.0   \n",
       "std_score_time                                            0.0   \n",
       "param_C                                                   0.1   \n",
       "param_gamma                                               100   \n",
       "param_kernel                                              rbf   \n",
       "params              {'C': 0.1, 'gamma': 100, 'kernel': 'rbf'}   \n",
       "split0_test_score                                        0.35   \n",
       "split1_test_score                                        0.35   \n",
       "split2_test_score                                        0.36   \n",
       "split3_test_score                                        0.36   \n",
       "split4_test_score                                        0.41   \n",
       "mean_test_score                                          0.37   \n",
       "std_test_score                                           0.02   \n",
       "rank_test_score                                            27   \n",
       "split0_train_score                                       0.37   \n",
       "split1_train_score                                       0.37   \n",
       "split2_train_score                                       0.37   \n",
       "split3_train_score                                       0.37   \n",
       "split4_train_score                                       0.36   \n",
       "mean_train_score                                         0.37   \n",
       "std_train_score                                          0.01   \n",
       "\n",
       "                                                           18  \\\n",
       "mean_fit_time                                             0.0   \n",
       "std_fit_time                                              0.0   \n",
       "mean_score_time                                           0.0   \n",
       "std_score_time                                            0.0   \n",
       "param_C                                                     1   \n",
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       "param_kernel                                              rbf   \n",
       "params              {'C': 1, 'gamma': 0.001, 'kernel': 'rbf'}   \n",
       "split0_test_score                                         0.7   \n",
       "split1_test_score                                         0.7   \n",
       "split2_test_score                                        0.68   \n",
       "split3_test_score                                        0.68   \n",
       "split4_test_score                                        0.73   \n",
       "mean_test_score                                           0.7   \n",
       "std_test_score                                           0.02   \n",
       "rank_test_score                                            22   \n",
       "split0_train_score                                        0.7   \n",
       "split1_train_score                                        0.7   \n",
       "split2_train_score                                        0.7   \n",
       "split3_train_score                                        0.7   \n",
       "split4_train_score                                       0.69   \n",
       "mean_train_score                                          0.7   \n",
       "std_train_score                                           0.0   \n",
       "\n",
       "                                                          19  \\\n",
       "mean_fit_time                                            0.0   \n",
       "std_fit_time                                             0.0   \n",
       "mean_score_time                                          0.0   \n",
       "std_score_time                                           0.0   \n",
       "param_C                                                    1   \n",
       "param_gamma                                             0.01   \n",
       "param_kernel                                             rbf   \n",
       "params              {'C': 1, 'gamma': 0.01, 'kernel': 'rbf'}   \n",
       "split0_test_score                                       0.91   \n",
       "split1_test_score                                       0.91   \n",
       "split2_test_score                                        1.0   \n",
       "split3_test_score                                       0.91   \n",
       "split4_test_score                                       0.95   \n",
       "mean_test_score                                         0.94   \n",
       "std_test_score                                          0.04   \n",
       "rank_test_score                                           15   \n",
       "split0_train_score                                      0.94   \n",
       "split1_train_score                                      0.93   \n",
       "split2_train_score                                      0.92   \n",
       "split3_train_score                                      0.94   \n",
       "split4_train_score                                      0.93   \n",
       "mean_train_score                                        0.94   \n",
       "std_train_score                                         0.01   \n",
       "\n",
       "                                                         20  \\\n",
       "mean_fit_time                                           0.0   \n",
       "std_fit_time                                            0.0   \n",
       "mean_score_time                                         0.0   \n",
       "std_score_time                                          0.0   \n",
       "param_C                                                   1   \n",
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       "param_kernel                                            rbf   \n",
       "params              {'C': 1, 'gamma': 0.1, 'kernel': 'rbf'}   \n",
       "split0_test_score                                       1.0   \n",
       "split1_test_score                                      0.96   \n",
       "split2_test_score                                       1.0   \n",
       "split3_test_score                                      0.91   \n",
       "split4_test_score                                      0.95   \n",
       "mean_test_score                                        0.96   \n",
       "std_test_score                                         0.03   \n",
       "rank_test_score                                           5   \n",
       "split0_train_score                                     0.98   \n",
       "split1_train_score                                     0.97   \n",
       "split2_train_score                                     0.97   \n",
       "split3_train_score                                     0.98   \n",
       "split4_train_score                                     0.98   \n",
       "mean_train_score                                       0.97   \n",
       "std_train_score                                        0.01   \n",
       "\n",
       "                                                       21  \\\n",
       "mean_fit_time                                         0.0   \n",
       "std_fit_time                                          0.0   \n",
       "mean_score_time                                       0.0   \n",
       "std_score_time                                        0.0   \n",
       "param_C                                                 1   \n",
       "param_gamma                                             1   \n",
       "param_kernel                                          rbf   \n",
       "params              {'C': 1, 'gamma': 1, 'kernel': 'rbf'}   \n",
       "split0_test_score                                    0.96   \n",
       "split1_test_score                                    0.91   \n",
       "split2_test_score                                     1.0   \n",
       "split3_test_score                                    0.91   \n",
       "split4_test_score                                    0.95   \n",
       "mean_test_score                                      0.95   \n",
       "std_test_score                                       0.03   \n",
       "rank_test_score                                        12   \n",
       "split0_train_score                                   0.98   \n",
       "split1_train_score                                    1.0   \n",
       "split2_train_score                                   0.98   \n",
       "split3_train_score                                    1.0   \n",
       "split4_train_score                                   0.98   \n",
       "mean_train_score                                     0.99   \n",
       "std_train_score                                      0.01   \n",
       "\n",
       "                                                        22  \\\n",
       "mean_fit_time                                          0.0   \n",
       "std_fit_time                                           0.0   \n",
       "mean_score_time                                        0.0   \n",
       "std_score_time                                         0.0   \n",
       "param_C                                                  1   \n",
       "param_gamma                                             10   \n",
       "param_kernel                                           rbf   \n",
       "params              {'C': 1, 'gamma': 10, 'kernel': 'rbf'}   \n",
       "split0_test_score                                     0.91   \n",
       "split1_test_score                                     0.96   \n",
       "split2_test_score                                      1.0   \n",
       "split3_test_score                                     0.82   \n",
       "split4_test_score                                     0.95   \n",
       "mean_test_score                                       0.93   \n",
       "std_test_score                                        0.06   \n",
       "rank_test_score                                         17   \n",
       "split0_train_score                                     1.0   \n",
       "split1_train_score                                     1.0   \n",
       "split2_train_score                                     1.0   \n",
       "split3_train_score                                     1.0   \n",
       "split4_train_score                                     1.0   \n",
       "mean_train_score                                       1.0   \n",
       "std_train_score                                        0.0   \n",
       "\n",
       "                                                         23  \\\n",
       "mean_fit_time                                           0.0   \n",
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       "mean_score_time                                         0.0   \n",
       "std_score_time                                          0.0   \n",
       "param_C                                                   1   \n",
       "param_gamma                                             100   \n",
       "param_kernel                                            rbf   \n",
       "params              {'C': 1, 'gamma': 100, 'kernel': 'rbf'}   \n",
       "split0_test_score                                      0.39   \n",
       "split1_test_score                                      0.43   \n",
       "split2_test_score                                      0.55   \n",
       "split3_test_score                                       0.5   \n",
       "split4_test_score                                      0.64   \n",
       "mean_test_score                                         0.5   \n",
       "std_test_score                                         0.09   \n",
       "rank_test_score                                          26   \n",
       "split0_train_score                                      1.0   \n",
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       "split2_train_score                                      1.0   \n",
       "split3_train_score                                      1.0   \n",
       "split4_train_score                                      1.0   \n",
       "mean_train_score                                        1.0   \n",
       "std_train_score                                         0.0   \n",
       "\n",
       "                                                            24  \\\n",
       "mean_fit_time                                              0.0   \n",
       "std_fit_time                                               0.0   \n",
       "mean_score_time                                            0.0   \n",
       "std_score_time                                             0.0   \n",
       "param_C                                                     10   \n",
       "param_gamma                                                0.0   \n",
       "param_kernel                                               rbf   \n",
       "params              {'C': 10, 'gamma': 0.001, 'kernel': 'rbf'}   \n",
       "split0_test_score                                         0.91   \n",
       "split1_test_score                                         0.91   \n",
       "split2_test_score                                          1.0   \n",
       "split3_test_score                                         0.91   \n",
       "split4_test_score                                         0.95   \n",
       "mean_test_score                                           0.94   \n",
       "std_test_score                                            0.04   \n",
       "rank_test_score                                             15   \n",
       "split0_train_score                                        0.94   \n",
       "split1_train_score                                        0.93   \n",
       "split2_train_score                                        0.92   \n",
       "split3_train_score                                        0.93   \n",
       "split4_train_score                                        0.93   \n",
       "mean_train_score                                          0.93   \n",
       "std_train_score                                           0.01   \n",
       "\n",
       "                                                           25  \\\n",
       "mean_fit_time                                             0.0   \n",
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       "std_score_time                                            0.0   \n",
       "param_C                                                    10   \n",
       "param_gamma                                              0.01   \n",
       "param_kernel                                              rbf   \n",
       "params              {'C': 10, 'gamma': 0.01, 'kernel': 'rbf'}   \n",
       "split0_test_score                                         1.0   \n",
       "split1_test_score                                        0.96   \n",
       "split2_test_score                                         1.0   \n",
       "split3_test_score                                        0.91   \n",
       "split4_test_score                                        0.95   \n",
       "mean_test_score                                          0.96   \n",
       "std_test_score                                           0.03   \n",
       "rank_test_score                                             5   \n",
       "split0_train_score                                       0.98   \n",
       "split1_train_score                                       0.98   \n",
       "split2_train_score                                       0.97   \n",
       "split3_train_score                                       0.99   \n",
       "split4_train_score                                       0.98   \n",
       "mean_train_score                                         0.98   \n",
       "std_train_score                                          0.01   \n",
       "\n",
       "                                                          26  \\\n",
       "mean_fit_time                                            0.0   \n",
       "std_fit_time                                             0.0   \n",
       "mean_score_time                                          0.0   \n",
       "std_score_time                                           0.0   \n",
       "param_C                                                   10   \n",
       "param_gamma                                              0.1   \n",
       "param_kernel                                             rbf   \n",
       "params              {'C': 10, 'gamma': 0.1, 'kernel': 'rbf'}   \n",
       "split0_test_score                                        1.0   \n",
       "split1_test_score                                       0.96   \n",
       "split2_test_score                                        1.0   \n",
       "split3_test_score                                       0.95   \n",
       "split4_test_score                                       0.95   \n",
       "mean_test_score                                         0.97   \n",
       "std_test_score                                          0.02   \n",
       "rank_test_score                                            1   \n",
       "split0_train_score                                      0.99   \n",
       "split1_train_score                                      0.99   \n",
       "split2_train_score                                      0.98   \n",
       "split3_train_score                                      0.99   \n",
       "split4_train_score                                       1.0   \n",
       "mean_train_score                                        0.99   \n",
       "std_train_score                                         0.01   \n",
       "\n",
       "                                                        27  \\\n",
       "mean_fit_time                                          0.0   \n",
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       "std_score_time                                         0.0   \n",
       "param_C                                                 10   \n",
       "param_gamma                                              1   \n",
       "param_kernel                                           rbf   \n",
       "params              {'C': 10, 'gamma': 1, 'kernel': 'rbf'}   \n",
       "split0_test_score                                     0.96   \n",
       "split1_test_score                                     0.96   \n",
       "split2_test_score                                      1.0   \n",
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       "split4_test_score                                     0.95   \n",
       "mean_test_score                                       0.95   \n",
       "std_test_score                                        0.04   \n",
       "rank_test_score                                         13   \n",
       "split0_train_score                                    0.99   \n",
       "split1_train_score                                    0.99   \n",
       "split2_train_score                                    0.98   \n",
       "split3_train_score                                     1.0   \n",
       "split4_train_score                                    0.99   \n",
       "mean_train_score                                      0.99   \n",
       "std_train_score                                       0.01   \n",
       "\n",
       "                                                         28  \\\n",
       "mean_fit_time                                           0.0   \n",
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       "std_score_time                                          0.0   \n",
       "param_C                                                  10   \n",
       "param_gamma                                              10   \n",
       "param_kernel                                            rbf   \n",
       "params              {'C': 10, 'gamma': 10, 'kernel': 'rbf'}   \n",
       "split0_test_score                                      0.87   \n",
       "split1_test_score                                      0.91   \n",
       "split2_test_score                                       1.0   \n",
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       "split4_test_score                                      0.95   \n",
       "mean_test_score                                        0.91   \n",
       "std_test_score                                         0.06   \n",
       "rank_test_score                                          18   \n",
       "split0_train_score                                      1.0   \n",
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       "split2_train_score                                      1.0   \n",
       "split3_train_score                                      1.0   \n",
       "split4_train_score                                      1.0   \n",
       "mean_train_score                                        1.0   \n",
       "std_train_score                                         0.0   \n",
       "\n",
       "                                                          29  \\\n",
       "mean_fit_time                                            0.0   \n",
       "std_fit_time                                             0.0   \n",
       "mean_score_time                                          0.0   \n",
       "std_score_time                                           0.0   \n",
       "param_C                                                   10   \n",
       "param_gamma                                              100   \n",
       "param_kernel                                             rbf   \n",
       "params              {'C': 10, 'gamma': 100, 'kernel': 'rbf'}   \n",
       "split0_test_score                                       0.52   \n",
       "split1_test_score                                       0.52   \n",
       "split2_test_score                                       0.59   \n",
       "split3_test_score                                       0.59   \n",
       "split4_test_score                                       0.68   \n",
       "mean_test_score                                         0.58   \n",
       "std_test_score                                          0.06   \n",
       "rank_test_score                                           24   \n",
       "split0_train_score                                       1.0   \n",
       "split1_train_score                                       1.0   \n",
       "split2_train_score                                       1.0   \n",
       "split3_train_score                                       1.0   \n",
       "split4_train_score                                       1.0   \n",
       "mean_train_score                                         1.0   \n",
       "std_train_score                                          0.0   \n",
       "\n",
       "                                                             30  \\\n",
       "mean_fit_time                                               0.0   \n",
       "std_fit_time                                                0.0   \n",
       "mean_score_time                                             0.0   \n",
       "std_score_time                                              0.0   \n",
       "param_C                                                     100   \n",
       "param_gamma                                                 0.0   \n",
       "param_kernel                                                rbf   \n",
       "params              {'C': 100, 'gamma': 0.001, 'kernel': 'rbf'}   \n",
       "split0_test_score                                           1.0   \n",
       "split1_test_score                                          0.96   \n",
       "split2_test_score                                           1.0   \n",
       "split3_test_score                                          0.91   \n",
       "split4_test_score                                          0.95   \n",
       "mean_test_score                                            0.96   \n",
       "std_test_score                                             0.03   \n",
       "rank_test_score                                               5   \n",
       "split0_train_score                                         0.98   \n",
       "split1_train_score                                         0.98   \n",
       "split2_train_score                                         0.97   \n",
       "split3_train_score                                         0.99   \n",
       "split4_train_score                                         0.98   \n",
       "mean_train_score                                           0.98   \n",
       "std_train_score                                            0.01   \n",
       "\n",
       "                                                            31  \\\n",
       "mean_fit_time                                              0.0   \n",
       "std_fit_time                                               0.0   \n",
       "mean_score_time                                            0.0   \n",
       "std_score_time                                             0.0   \n",
       "param_C                                                    100   \n",
       "param_gamma                                               0.01   \n",
       "param_kernel                                               rbf   \n",
       "params              {'C': 100, 'gamma': 0.01, 'kernel': 'rbf'}   \n",
       "split0_test_score                                          1.0   \n",
       "split1_test_score                                         0.91   \n",
       "split2_test_score                                          1.0   \n",
       "split3_test_score                                         0.95   \n",
       "split4_test_score                                         0.95   \n",
       "mean_test_score                                           0.96   \n",
       "std_test_score                                            0.03   \n",
       "rank_test_score                                              4   \n",
       "split0_train_score                                        0.99   \n",
       "split1_train_score                                        0.99   \n",
       "split2_train_score                                        0.98   \n",
       "split3_train_score                                        0.99   \n",
       "split4_train_score                                        0.99   \n",
       "mean_train_score                                          0.99   \n",
       "std_train_score                                            0.0   \n",
       "\n",
       "                                                           32  \\\n",
       "mean_fit_time                                             0.0   \n",
       "std_fit_time                                              0.0   \n",
       "mean_score_time                                           0.0   \n",
       "std_score_time                                            0.0   \n",
       "param_C                                                   100   \n",
       "param_gamma                                               0.1   \n",
       "param_kernel                                              rbf   \n",
       "params              {'C': 100, 'gamma': 0.1, 'kernel': 'rbf'}   \n",
       "split0_test_score                                         1.0   \n",
       "split1_test_score                                        0.96   \n",
       "split2_test_score                                         1.0   \n",
       "split3_test_score                                        0.86   \n",
       "split4_test_score                                        0.95   \n",
       "mean_test_score                                          0.95   \n",
       "std_test_score                                           0.05   \n",
       "rank_test_score                                            11   \n",
       "split0_train_score                                       0.99   \n",
       "split1_train_score                                       0.99   \n",
       "split2_train_score                                       0.98   \n",
       "split3_train_score                                        1.0   \n",
       "split4_train_score                                        1.0   \n",
       "mean_train_score                                         0.99   \n",
       "std_train_score                                          0.01   \n",
       "\n",
       "                                                         33  \\\n",
       "mean_fit_time                                           0.0   \n",
       "std_fit_time                                            0.0   \n",
       "mean_score_time                                         0.0   \n",
       "std_score_time                                          0.0   \n",
       "param_C                                                 100   \n",
       "param_gamma                                               1   \n",
       "param_kernel                                            rbf   \n",
       "params              {'C': 100, 'gamma': 1, 'kernel': 'rbf'}   \n",
       "split0_test_score                                      0.96   \n",
       "split1_test_score                                      0.96   \n",
       "split2_test_score                                       1.0   \n",
       "split3_test_score                                      0.86   \n",
       "split4_test_score                                      0.95   \n",
       "mean_test_score                                        0.95   \n",
       "std_test_score                                         0.04   \n",
       "rank_test_score                                          13   \n",
       "split0_train_score                                      1.0   \n",
       "split1_train_score                                      1.0   \n",
       "split2_train_score                                      1.0   \n",
       "split3_train_score                                      1.0   \n",
       "split4_train_score                                      1.0   \n",
       "mean_train_score                                        1.0   \n",
       "std_train_score                                         0.0   \n",
       "\n",
       "                                                          34  \\\n",
       "mean_fit_time                                            0.0   \n",
       "std_fit_time                                             0.0   \n",
       "mean_score_time                                          0.0   \n",
       "std_score_time                                           0.0   \n",
       "param_C                                                  100   \n",
       "param_gamma                                               10   \n",
       "param_kernel                                             rbf   \n",
       "params              {'C': 100, 'gamma': 10, 'kernel': 'rbf'}   \n",
       "split0_test_score                                       0.87   \n",
       "split1_test_score                                       0.91   \n",
       "split2_test_score                                        1.0   \n",
       "split3_test_score                                       0.82   \n",
       "split4_test_score                                       0.95   \n",
       "mean_test_score                                         0.91   \n",
       "std_test_score                                          0.06   \n",
       "rank_test_score                                           18   \n",
       "split0_train_score                                       1.0   \n",
       "split1_train_score                                       1.0   \n",
       "split2_train_score                                       1.0   \n",
       "split3_train_score                                       1.0   \n",
       "split4_train_score                                       1.0   \n",
       "mean_train_score                                         1.0   \n",
       "std_train_score                                          0.0   \n",
       "\n",
       "                                                           35  \\\n",
       "mean_fit_time                                             0.0   \n",
       "std_fit_time                                              0.0   \n",
       "mean_score_time                                           0.0   \n",
       "std_score_time                                            0.0   \n",
       "param_C                                                   100   \n",
       "param_gamma                                               100   \n",
       "param_kernel                                              rbf   \n",
       "params              {'C': 100, 'gamma': 100, 'kernel': 'rbf'}   \n",
       "split0_test_score                                        0.52   \n",
       "split1_test_score                                        0.52   \n",
       "split2_test_score                                        0.59   \n",
       "split3_test_score                                        0.59   \n",
       "split4_test_score                                        0.68   \n",
       "mean_test_score                                          0.58   \n",
       "std_test_score                                           0.06   \n",
       "rank_test_score                                            24   \n",
       "split0_train_score                                        1.0   \n",
       "split1_train_score                                        1.0   \n",
       "split2_train_score                                        1.0   \n",
       "split3_train_score                                        1.0   \n",
       "split4_train_score                                        1.0   \n",
       "mean_train_score                                          1.0   \n",
       "std_train_score                                           0.0   \n",
       "\n",
       "                                                  36  \\\n",
       "mean_fit_time                                    0.0   \n",
       "std_fit_time                                     0.0   \n",
       "mean_score_time                                  0.0   \n",
       "std_score_time                                   0.0   \n",
       "param_C                                          0.0   \n",
       "param_gamma                                      NaN   \n",
       "param_kernel                                  linear   \n",
       "params              {'C': 0.001, 'kernel': 'linear'}   \n",
       "split0_test_score                               0.35   \n",
       "split1_test_score                               0.35   \n",
       "split2_test_score                               0.36   \n",
       "split3_test_score                               0.36   \n",
       "split4_test_score                               0.41   \n",
       "mean_test_score                                 0.37   \n",
       "std_test_score                                  0.02   \n",
       "rank_test_score                                   27   \n",
       "split0_train_score                              0.37   \n",
       "split1_train_score                              0.37   \n",
       "split2_train_score                              0.37   \n",
       "split3_train_score                              0.37   \n",
       "split4_train_score                              0.36   \n",
       "mean_train_score                                0.37   \n",
       "std_train_score                                 0.01   \n",
       "\n",
       "                                                 37  \\\n",
       "mean_fit_time                                   0.0   \n",
       "std_fit_time                                    0.0   \n",
       "mean_score_time                                 0.0   \n",
       "std_score_time                                  0.0   \n",
       "param_C                                        0.01   \n",
       "param_gamma                                     NaN   \n",
       "param_kernel                                 linear   \n",
       "params              {'C': 0.01, 'kernel': 'linear'}   \n",
       "split0_test_score                              0.87   \n",
       "split1_test_score                              0.87   \n",
       "split2_test_score                              0.77   \n",
       "split3_test_score                              0.77   \n",
       "split4_test_score                              0.91   \n",
       "mean_test_score                                0.84   \n",
       "std_test_score                                 0.06   \n",
       "rank_test_score                                  21   \n",
       "split0_train_score                             0.85   \n",
       "split1_train_score                             0.91   \n",
       "split2_train_score                             0.84   \n",
       "split3_train_score                             0.77   \n",
       "split4_train_score                             0.88   \n",
       "mean_train_score                               0.85   \n",
       "std_train_score                                0.05   \n",
       "\n",
       "                                                38  \\\n",
       "mean_fit_time                                  0.0   \n",
       "std_fit_time                                   0.0   \n",
       "mean_score_time                                0.0   \n",
       "std_score_time                                 0.0   \n",
       "param_C                                        0.1   \n",
       "param_gamma                                    NaN   \n",
       "param_kernel                                linear   \n",
       "params              {'C': 0.1, 'kernel': 'linear'}   \n",
       "split0_test_score                              1.0   \n",
       "split1_test_score                             0.91   \n",
       "split2_test_score                              1.0   \n",
       "split3_test_score                             0.91   \n",
       "split4_test_score                             0.95   \n",
       "mean_test_score                               0.96   \n",
       "std_test_score                                0.04   \n",
       "rank_test_score                                  8   \n",
       "split0_train_score                            0.97   \n",
       "split1_train_score                            0.97   \n",
       "split2_train_score                            0.94   \n",
       "split3_train_score                            0.97   \n",
       "split4_train_score                            0.97   \n",
       "mean_train_score                              0.96   \n",
       "std_train_score                               0.01   \n",
       "\n",
       "                                              39  \\\n",
       "mean_fit_time                                0.0   \n",
       "std_fit_time                                 0.0   \n",
       "mean_score_time                              0.0   \n",
       "std_score_time                               0.0   \n",
       "param_C                                        1   \n",
       "param_gamma                                  NaN   \n",
       "param_kernel                              linear   \n",
       "params              {'C': 1, 'kernel': 'linear'}   \n",
       "split0_test_score                            1.0   \n",
       "split1_test_score                           0.96   \n",
       "split2_test_score                            1.0   \n",
       "split3_test_score                           0.95   \n",
       "split4_test_score                           0.95   \n",
       "mean_test_score                             0.97   \n",
       "std_test_score                              0.02   \n",
       "rank_test_score                                1   \n",
       "split0_train_score                          0.99   \n",
       "split1_train_score                          0.98   \n",
       "split2_train_score                          0.98   \n",
       "split3_train_score                          0.99   \n",
       "split4_train_score                          0.99   \n",
       "mean_train_score                            0.98   \n",
       "std_train_score                             0.01   \n",
       "\n",
       "                                               40  \\\n",
       "mean_fit_time                                 0.0   \n",
       "std_fit_time                                  0.0   \n",
       "mean_score_time                               0.0   \n",
       "std_score_time                                0.0   \n",
       "param_C                                        10   \n",
       "param_gamma                                   NaN   \n",
       "param_kernel                               linear   \n",
       "params              {'C': 10, 'kernel': 'linear'}   \n",
       "split0_test_score                             1.0   \n",
       "split1_test_score                             1.0   \n",
       "split2_test_score                             1.0   \n",
       "split3_test_score                            0.91   \n",
       "split4_test_score                            0.95   \n",
       "mean_test_score                              0.97   \n",
       "std_test_score                               0.04   \n",
       "rank_test_score                                 3   \n",
       "split0_train_score                           0.99   \n",
       "split1_train_score                           0.99   \n",
       "split2_train_score                           0.98   \n",
       "split3_train_score                           0.99   \n",
       "split4_train_score                            1.0   \n",
       "mean_train_score                             0.99   \n",
       "std_train_score                              0.01   \n",
       "\n",
       "                                                41  \n",
       "mean_fit_time                                  0.0  \n",
       "std_fit_time                                   0.0  \n",
       "mean_score_time                                0.0  \n",
       "std_score_time                                 0.0  \n",
       "param_C                                        100  \n",
       "param_gamma                                    NaN  \n",
       "param_kernel                                linear  \n",
       "params              {'C': 100, 'kernel': 'linear'}  \n",
       "split0_test_score                             0.96  \n",
       "split1_test_score                             0.96  \n",
       "split2_test_score                              1.0  \n",
       "split3_test_score                             0.91  \n",
       "split4_test_score                             0.95  \n",
       "mean_test_score                               0.96  \n",
       "std_test_score                                0.03  \n",
       "rank_test_score                                  8  \n",
       "split0_train_score                            0.98  \n",
       "split1_train_score                            0.99  \n",
       "split2_train_score                            0.99  \n",
       "split3_train_score                             1.0  \n",
       "split4_train_score                             1.0  \n",
       "mean_train_score                              0.99  \n",
       "std_train_score                               0.01  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results = pd.DataFrame(grid_search.cv_results_)\n",
    "# 좀 더 나은 출력을 위해 결과를 전치시킵니다\n",
    "display(results.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 그리드 서치에 다양한 교차 검증 적용"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 중첩 교차 검증"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차 검증 점수:  [0.967 1.    0.967 0.967 1.   ]\n",
      "교차 검증 평균 점수:  0.9800000000000001\n"
     ]
    }
   ],
   "source": [
    "param_grid = {'C': [0.001, 0.01, 0.1, 1, 10, 100],\n",
    "              'gamma': [0.001, 0.01, 0.1, 1, 10, 100]}\n",
    "scores = cross_val_score(GridSearchCV(SVC(), param_grid, cv=5),\n",
    "                         iris.data, iris.target, cv=5)\n",
    "print(\"교차 검증 점수: \", scores)\n",
    "print(\"교차 검증 평균 점수: \", scores.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "def nested_cv(X, y, inner_cv, outer_cv, Classifier, parameter_grid):\n",
    "    outer_scores = []\n",
    "    # outer_cv의 분할을 순회하는 for 루프\n",
    "    # (split 메소드는 훈련과 테스트 세트에 해당하는 인덱스를 리턴합니다)\n",
    "    for training_samples, test_samples in outer_cv.split(X, y):\n",
    "        # 최적의 매개변수를 찾습니다\n",
    "        best_parms = {}\n",
    "        best_score = -np.inf\n",
    "        # 매개변수 그리드를 순회합니다\n",
    "        for parameters in parameter_grid:\n",
    "            # 안쪽 교차 검증의 점수를 기록합니다\n",
    "            cv_scores = []\n",
    "            # inner_cv의 분할을 순회하는 for 루프\n",
    "            for inner_train, inner_test in inner_cv.split(\n",
    "                    X[training_samples], y[training_samples]):\n",
    "                # 훈련 데이터와 주어진 매개변수로 분류기를 만듭니다\n",
    "                clf = Classifier(**parameters)\n",
    "                clf.fit(X[inner_train], y[inner_train])\n",
    "                # 검증 세트로 평가합니다\n",
    "                score = clf.score(X[inner_test], y[inner_test])\n",
    "                cv_scores.append(score)\n",
    "            # 안쪽 교차 검증의 평균 점수를 계산합니다\n",
    "            mean_score = np.mean(cv_scores)\n",
    "            if mean_score > best_score:\n",
    "                # 점수가 더 높은면 매개변수와 함께 기록합니다\n",
    "                best_score = mean_score\n",
    "                best_params = parameters\n",
    "        # 바깥쪽 훈련 데이터 전체를 사용해 분류기를 만듭니다\n",
    "        clf = Classifier(**best_params)\n",
    "        clf.fit(X[training_samples], y[training_samples])\n",
    "        # 테스트 세트를 사용해 평가합니다\n",
    "        outer_scores.append(clf.score(X[test_samples], y[test_samples]))\n",
    "    return np.array(outer_scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "hide_input": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차 검증 점수: [0.967 1.    0.967 0.967 1.   ]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import ParameterGrid, StratifiedKFold\n",
    "scores = nested_cv(iris.data, iris.target, StratifiedKFold(5),\n",
    "                   StratifiedKFold(5), SVC, ParameterGrid(param_grid))\n",
    "print(\"교차 검증 점수:\", scores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "#### 교차 검증과 그리드 서치 병렬화"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 평가 지표 및 측정\n",
    "#### 최종 목표를 기억하라"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 이진 분류의 평가 지표\n",
    "##### 에러의 종류\n",
    "##### 불균형 데이터셋"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.datasets import load_digits\n",
    "\n",
    "digits = load_digits()\n",
    "y = digits.target == 9\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    digits.data, y, random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "예측된 레이블의 고유값: [False]\n",
      "테스트 점수: 0.90\n"
     ]
    }
   ],
   "source": [
    "from sklearn.dummy import DummyClassifier\n",
    "dummy_majority = DummyClassifier(strategy='most_frequent').fit(X_train, y_train)\n",
    "pred_most_frequent = dummy_majority.predict(X_test)\n",
    "print(\"예측된 레이블의 고유값:\", np.unique(pred_most_frequent))\n",
    "print(\"테스트 점수: {:.2f}\".format(dummy_majority.score(X_test, y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "테스트 점수: 0.92\n"
     ]
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "tree = DecisionTreeClassifier(max_depth=2).fit(X_train, y_train)\n",
    "pred_tree = tree.predict(X_test)\n",
    "print(\"테스트 점수: {:.2f}\".format(tree.score(X_test, y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dummy 점수: 0.83\n",
      "logreg 점수: 0.98\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "dummy = DummyClassifier(strategy='stratified').fit(X_train, y_train)\n",
    "pred_dummy = dummy.predict(X_test)\n",
    "print(\"dummy 점수: {:.2f}\".format(dummy.score(X_test, y_test)))\n",
    "\n",
    "logreg = LogisticRegression(C=0.1, max_iter=1000).fit(X_train, y_train)\n",
    "pred_logreg = logreg.predict(X_test)\n",
    "print(\"logreg 점수: {:.2f}\".format(logreg.score(X_test, y_test)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 오차 행렬(Confusion matrices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "오차 행렬:\n",
      " [[402   1]\n",
      " [  6  41]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "\n",
    "confusion = confusion_matrix(y_test, pred_logreg)\n",
    "print(\"오차 행렬:\\n\", confusion)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/pdf": 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      "text/plain": [
       "<Figure size 2400x2400 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mglearn.plots.plot_confusion_matrix_illustration()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/pdf": 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Odvi/kryz1npjD8Z7PMmJpZSvJlm6F2N0SdMHUM8axX1WaTj2r0m+N4p7jdUimX+Xhf1MOt9yBwC6aODpsUsGXhOKee6QzHMnFvNcIIkCDwDgn2qtZyU5q+UY46LWul8p5dEkuyY5IMkXaq21x2P+JclfejnGGDX9krxWKWVqrfWJEdznBd0KBADAyJjnNjLPBZiA7IEHADBJ1VpnJlmt1vr5Xn+oMUFc1XBsepI15vUGpZRF0tk/BgCAlpjnDnJVwzHzXIA+p8ADAJjEaq0PtJ2hX9Ra/5bkxoZTLxvBbV4Vc2wAgBGptV5aay0NrxvHcE/z3AHmuQATkyU0AQDoR7uls6/F7MZjH4gfJXn3HMfekOQL8/j+LRqO/STJvw/zng8mefU83n9EBj70Kr24NwAweZVSlk+ycTr7nz03yapJlkuyVJIZ6TzdNSvJo0nuTnJnkj8nuS7JlUl+Vmu9c9yD9wfz3C4wzwUmAwUeAABjVkpZIMlq6Syrs0KSZdP5YGJ6Or9Yz0rycJK78n8f4NxQa32o6X611u+NQ+wmF2TwBxtvLKUsXmu9f7g3Diwr9NaGU5+rtZ4/zPs2H3lMAIDxVUpZMck7k2yT5IWZe3kyY+C1eDoF34tmO1dLKb9Mcn6SL9Vab+t64C4xzzXPBWiLAg8AgBErpUxP8tp0vrX7snQ2tJ8+wts8WUq5LskVSX6Q5Hu11nu6GnTkLk5yezofzjxl8XS+PXzsXN67ezof6MzuoSQXdS0dAMA4K6WskuSwJDsmWaBbt02y0cDr6FLK2UmOqLXe3KX7j5p5biPzXIAWWLcYAGAESiknl1Jqn72uGseff41SyqeS3JbkP5Lsmc7SSSP9UCPpzEWfn2TnJF9Oclsp5RullFd2Ke6I1VpnJflMw6kDSinPG+p9pZQXJDm44dTptdZ/dCsfAMB4KqXsmeT36Ty51a3ybk4LJNklye9KKR/q0RhzZZ7bzDwXoD0KPAAA5qqUslQp5bQk16bzLd2lejDM9HSW5rmslPL9UspzezDGvPhEOksgzW7xJN8ppaw158WllA2SfDfJYnOceiTJx3uSEACgh0op00opX05ycpKF5+EtdyS5PJ3i62tJzhr4638k+a90SrG5WSTJJ0sp55RSxm3VMPNc81yAfmUJTQAAhlVKeVGSbyRZeRyH3TTJr0opu9Vazx7HcVNrva+Usk86HzzNbvUkV5dSLkpyVTpz6Y3SWV6p6Ytxh9Vab+lhVACAXjkzyfbDnL8jybfS2Vftl7XWv8/thqWUpdPZB++tSbZMsvwQl74jyRNJdhpB3lExz/0n81yAPqTAAwBgSKWUVyT5XjrfiB7Kk0l+keTSdJZY+n06+2s8kOTBgfOLDryWSfK8gdfLkrwyQy9LtHCSL5ZSlqy1njLWn2Ukaq1fLKW8Pp0PkGa3QJKtB17DuSQT4FvJpZRXJ/lxyzGa7F1rPbntEAAwGZVS3ptkhyFO/z3JMUlOq7U+MpL71lrvTvL9JN8fWCpzt3SWZpxzb7UkeWcp5ce11rNGMsZImOea57bEPBeYZwo8AICxuzedDyPGwwZJBi1v0wullGcmuTBDf6hxY5KTknxlHr51fc/A65Z0vtX71BiLJnlLkn3T+dmafKKU8vta6w/mNXuX7JJkySSbjfB9P0+yVa31ia4nAgDooVLKIkmOHeL0FUm2rrXeOtZxaq2PJjm5lHJ+km+m82TenI4vpZxXa314rOPNyTzXPBdgIlDgAQCM3U211m3HY6BSyskZpwIvnT0ylm44/liSw5KcMNZf3mutDyQ5N8m5pZTtk3w6nQ8TZjclyedKKWvVWh8by3gjzPZoKWXLJEcm2S/J1Lm9JcmpSfYZ+FAKAGCi2T6dJ8nmdG2S19da/9HNwWqtfxl4GuzKJGvMcXr5JG/P4OUeu8E81zwXoO81rWEMAMAkV0pZPck2DaceS7J5rfXYbn/zttZ6bpIXp7M005xWTTIuJensaq2P11oPTLJuks+ls9/LnG5NckaSdWutu/tQAwCYwN48xPF3dbu8e0qt9b4kuw5x+i3dHs88t8M8F6D/eQIPAIAmb01SGo4fUWu9uFeD1lr/UEp5d5KLGk5vk+RLvRp7OLXWa9P5YGnXgSWXlk/yeJI7a623tZGpS+5M8o2WM7wlnT1XAID2NS31eFWt9ee9HLTW+qNSyg1JVp+HPGNlnjsb89yeMs8FxkSBBwBAkw0bjj2e5N97PXCt9dullOszeBmlF/Z67HkxsO/LmPd+6Qe11mvS/A30cVNKuTfJEm1mAAD+afmGY78Zp7F/m8EF3jN6MI557hDMc7vLPBcYK0toAgDQZNmGYzcNLHE0Hv634VjTB0oAAPTWeH1+2PSgQdOTcmNlngvAhKDAAwCgySMNx8bz26NNY80ax/EBACajpiUTe7GM5dOUUkqS9RpONe3LNlbmuQBMCAo8AACa3NBwbNlSykt6PXApZZkkTeP8qddjAwBMcr9qOLZuKeUVPR530yTPbjj+6x6MZZ4LwISgwAMAoMkPhzj+8VLKjB6PfUKSRRqOX9rjcQEAJruLhjj++VLK4r0YsJSyZJLThjj97R4MaZ4LwISgwAMAoMn3k9zScHzjJF8b+KClq0opC5RSTkry7iEu+UK3xwQA4Gm+muTOhuNrJvlhKWXlbg42cL9LkqzWcPquJOd2c7wB5rkATAhNm8MCADAyq5dSLhmnsdYaj0FqrbNKKQcl+VLD6bck+d9SyqFJvlJrfXQsYw3sebJ5kiOSrD/EZefWWq8ayzgAAAyv1vpwKWX/NBdK/5rkqlLKx5J8qtb6wGjHKaUsmmT3JPslWXqIyw6otT402jGGYp4LwEShwAMAGLtFk7y27RDdVms9p5TyuiQ7NZxeOcmZSY4vpVyY5OIkl9dab5+Xe5dSlk7yonT2O9kiyerDXP6HJHuMIDoAAKNUaz2zlLJJkh0bTi+d5NgkB5ZS/iPJt5L8Msmfa61PDnXPgSJr1SQbpTP32yzJcEtynlNrPWN0P8HcmecCMBEo8AAAGM5705kzvmOI88sned/AK6WU+5P8MckdSR5K8mCSms5eHwsnWSbJGgN/nRfXJnlDrfXuUeYHAGDk3p1kapLthzi/eJJtB15J8nAp5YYk9yV5IMnDSRZK54tui6dTYi08j2Ofm+Rdo4s9Iua5APQ1BR4AAEOqtT5WStkxnW9WH5vOBzHDWTzJC7s0/JeS7FFrva9L9wMAYB7UWh9P8o5Syi+SHJO5l28LJVl3jMM+lOSgWusnx3ifeWKeC0C/m9J2AAAA+lvt+GSS56azH8qY9gKZBz9M8vJa6zt9qAEA0J6BOeDaSc5K8niPhnk8nSUrnz9e5d1TzHMB6Gel1tp2BgAAJpBSyvLpLDW0TZIXp7O80lj9PskFSb5ca/1dF+43XyqlrJrkzw2nNqm1Xjq+abqjlHJvkiXmOLx3rfXk8U8DAAyllLJSkp2TvC3J+l245a+SfD3JF2utf+vC/cbMPLc95rkAgynwAAAYtVLKkklekmTDJM9LsmqSFdLZ+2ORJNMHLn0snb1Q7k5yZ5Ibk1yf5NdJfl5rvXUcY09YA3+/92049flaa9MHHn2vlPLf6SxJNbvjaq3ntJEHAJi7gTJv43SWlFwrybPT2TNuqSQz0tm25/EkjyS5J519425Kcl06xd1Pa623jX/yeWeeO77McwEGU+ABAAAAAABAH7EHHgAAAAAAAPQRBR4AAAAAAAD0EQUeAAAAAAAA9BEFHgAAAAAAAPQRBR4AAAAAAAD0EQUeAAAAAAAA9BEFHgAAAAAAAPQRBR4AAAAAAAD0EQUeAAAAAAAA9BEFHgAAAAAAAPQRBR4AAAAAAAD0EQUeAAAAAAAA9BEFHgAAAAAAAPQRBR4AAAAAAAD0EQUeAAAAAAAA9BEFHgAAAAAAAPQRBR4AAAAAAAD0EQUeAAAAAAAA9BEFHgAAAAAAAPQRBR4AAAAAAAD0EQUeAAAAAAAA9BEFHgAAAAAAAPQRBR4AAAAAAAD0EQUeAAAAAAAA9BEFHgAAAAAAAPQRBR4AAAAAAAD0EQUeAAAAAAAA9BEFHgAAAAAAAPQRBR4AAAAAAAD0EQUeAAAAAAAA9BEFHgAAAAAAAPQRBR4AAAAAAAD0EQUeAAAAAAAA9BEFHgAAAAAAAPQRBR4AAAAAAAD0EQUeAAAAAAAA9BEFHgAAAAAAAPSR/w+ZiymAyfPpjgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mglearn.plots.plot_binary_confusion_matrix()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "빈도 기반 더미 모델:\n",
      "[[403   0]\n",
      " [ 47   0]]\n",
      "\n",
      "무작위 더미 모델:\n",
      "[[359  44]\n",
      " [ 40   7]]\n",
      "\n",
      "결정 트리:\n",
      "[[390  13]\n",
      " [ 24  23]]\n",
      "\n",
      "로지스틱 회귀\n",
      "[[402   1]\n",
      " [  6  41]]\n"
     ]
    }
   ],
   "source": [
    "print(\"빈도 기반 더미 모델:\")\n",
    "print(confusion_matrix(y_test, pred_most_frequent))\n",
    "print(\"\\n무작위 더미 모델:\")\n",
    "print(confusion_matrix(y_test, pred_dummy))\n",
    "print(\"\\n결정 트리:\")\n",
    "print(confusion_matrix(y_test, pred_tree))\n",
    "print(\"\\n로지스틱 회귀\")\n",
    "print(confusion_matrix(y_test, pred_logreg))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### 정확도와의 관계\n",
    "\\begin{equation}\n",
    "\\text{Accuracy} = \\frac{\\text{TP} + \\text{TN}}{\\text{TP} + \\text{TN} + \\text{FP} + \\text{FN}}\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### 정밀도, 재현율, f-점수\n",
    "\\begin{equation}\n",
    "\\text{정밀도} = \\frac{\\text{TP}}{\\text{TP} + \\text{FP}}\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "hide_input": false
   },
   "source": [
    "\\begin{equation}\n",
    "\\text{재현율} = \\frac{\\text{TP}}{\\text{TP} + \\text{FN}}\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\\begin{equation}\n",
    "\\text{F} = 2 \\cdot \\frac{\\text{정밀도} \\cdot \\text{재현율}}{\\text{정밀도} + \\text{재현율}}\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "빈도 기반 더미 모델의 f1 score: 0.00\n",
      "무작위 더미 모델의 f1 score: 0.14\n",
      "트리 모델의 f1 score: 0.55\n",
      "로지스틱 회귀 모델의 f1 score: 0.92\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import f1_score\n",
    "print(\"빈도 기반 더미 모델의 f1 score: {:.2f}\".format(\n",
    "    f1_score(y_test, pred_most_frequent)))\n",
    "print(\"무작위 더미 모델의 f1 score: {:.2f}\".format(f1_score(y_test, pred_dummy)))\n",
    "print(\"트리 모델의 f1 score: {:.2f}\".format(f1_score(y_test, pred_tree)))\n",
    "print(\"로지스틱 회귀 모델의 f1 score: {:.2f}\".format(\n",
    "    f1_score(y_test, pred_logreg)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "        9 아님       0.90      1.00      0.94       403\n",
      "           9       0.00      0.00      0.00        47\n",
      "\n",
      "    accuracy                           0.90       450\n",
      "   macro avg       0.45      0.50      0.47       450\n",
      "weighted avg       0.80      0.90      0.85       450\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "# 0 나눗셈 경고를 피하기 위해 zero_division 매개변수를 0으로 지정합니다.\n",
    "print(classification_report(y_test, pred_most_frequent,\n",
    "                            target_names=[\"9 아님\", \"9\"], zero_division=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "        9 아님       0.90      0.89      0.90       403\n",
      "           9       0.14      0.15      0.14        47\n",
      "\n",
      "    accuracy                           0.81       450\n",
      "   macro avg       0.52      0.52      0.52       450\n",
      "weighted avg       0.82      0.81      0.82       450\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, pred_dummy,\n",
    "                            target_names=[\"9 아님\", \"9\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "        9 아님       0.99      1.00      0.99       403\n",
      "           9       0.98      0.87      0.92        47\n",
      "\n",
      "    accuracy                           0.98       450\n",
      "   macro avg       0.98      0.93      0.96       450\n",
      "weighted avg       0.98      0.98      0.98       450\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, pred_logreg,\n",
    "                            target_names=[\"9 아님\", \"9\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 불확실성 고려"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "X, y = make_blobs(n_samples=(400, 50), cluster_std=[7.0, 2], random_state=22)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n",
    "svc = SVC(gamma=.05).fit(X_train, y_train)                                     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 4500x2400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mglearn.plots.plot_decision_threshold()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.97      0.89      0.93       104\n",
      "           1       0.35      0.67      0.46         9\n",
      "\n",
      "    accuracy                           0.88       113\n",
      "   macro avg       0.66      0.78      0.70       113\n",
      "weighted avg       0.92      0.88      0.89       113\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, svc.predict(X_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred_lower_threshold = svc.decision_function(X_test) > -.8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.82      0.90       104\n",
      "           1       0.32      1.00      0.49         9\n",
      "\n",
      "    accuracy                           0.83       113\n",
      "   macro avg       0.66      0.91      0.69       113\n",
      "weighted avg       0.95      0.83      0.87       113\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, y_pred_lower_threshold))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 정밀도-재현율 곡선과 ROC 곡선"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import precision_recall_curve\n",
    "precision, recall, thresholds = precision_recall_curve(\n",
    "    y_test, svc.decision_function(X_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/pdf": 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\n",
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\n",
      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 부드러운 곡선을 위해 데이터 포인트 수를 늘립니다\n",
    "X, y = make_blobs(n_samples=(4000, 500), cluster_std=[7.0, 2], random_state=22)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n",
    "\n",
    "svc = SVC(gamma=.05).fit(X_train, y_train)\n",
    "\n",
    "precision, recall, thresholds = precision_recall_curve(\n",
    "    y_test, svc.decision_function(X_test))\n",
    "# 0에 가까운 임계값을 찾습니다\n",
    "close_zero = np.argmin(np.abs(thresholds))\n",
    "plt.plot(precision[close_zero], recall[close_zero], 'o', markersize=10,\n",
    "         label=\"임계값 0\", fillstyle=\"none\", c='k', mew=2)\n",
    "\n",
    "plt.plot(precision, recall, label=\"정밀도-재현율 곡선\")\n",
    "plt.xlabel(\"정밀도\")\n",
    "plt.ylabel(\"재현율\")\n",
    "plt.legend(loc=\"best\")\n",
    "plt.show() # 책에는 없음"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/pdf": 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      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "rf = RandomForestClassifier(n_estimators=100, random_state=0, max_features=2)\n",
    "rf.fit(X_train, y_train)\n",
    "\n",
    "# RandomForestClassifier는 decision_function 대신 predict_proba를 제공합니다.\n",
    "precision_rf, recall_rf, thresholds_rf = precision_recall_curve(\n",
    "    y_test, rf.predict_proba(X_test)[:, 1])\n",
    "\n",
    "plt.plot(precision, recall, label=\"svc\")\n",
    "\n",
    "plt.plot(precision[close_zero], recall[close_zero], 'o', markersize=10,\n",
    "         label=\"svc: 임계값 0\", fillstyle=\"none\", c='k', mew=2)\n",
    "\n",
    "plt.plot(precision_rf, recall_rf, label=\"rf\")\n",
    "\n",
    "close_default_rf = np.argmin(np.abs(thresholds_rf - 0.5))\n",
    "plt.plot(precision_rf[close_default_rf], recall_rf[close_default_rf], '^', c='k',\n",
    "         markersize=10, label=\"rf: 임계값 0.5\", fillstyle=\"none\", mew=2)\n",
    "plt.xlabel(\"정밀도\")\n",
    "plt.ylabel(\"재현율\")\n",
    "plt.legend(loc=\"best\")\n",
    "plt.show() # 책에는 없음"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "랜덤 포레스트의 f1_score: 0.610\n",
      "svc의 f1_score: 0.656\n"
     ]
    }
   ],
   "source": [
    "print(\"랜덤 포레스트의 f1_score: {:.3f}\".format(\n",
    "    f1_score(y_test, rf.predict(X_test))))\n",
    "print(\"svc의 f1_score: {:.3f}\".format(f1_score(y_test, svc.predict(X_test))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "랜덤 포레스트의 평균 정밀도: 0.660\n",
      "svc의 평균 정밀도: 0.666\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import average_precision_score\n",
    "ap_rf = average_precision_score(y_test, rf.predict_proba(X_test)[:, 1])\n",
    "ap_svc = average_precision_score(y_test, svc.decision_function(X_test))\n",
    "print(\"랜덤 포레스트의 평균 정밀도: {:.3f}\".format(ap_rf))\n",
    "print(\"svc의 평균 정밀도: {:.3f}\".format(ap_svc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### ROC 와 AUC\n",
    "\\begin{equation}\n",
    "\\text{FPR} = \\frac{\\text{FP}}{\\text{FP} + \\text{TN}}\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/pdf": 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\n",
      "image/png": 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      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import roc_curve\n",
    "fpr, tpr, thresholds = roc_curve(y_test, svc.decision_function(X_test))\n",
    "\n",
    "plt.plot(fpr, tpr, label=\"ROC 곡선\")\n",
    "plt.xlabel(\"FPR\")\n",
    "plt.ylabel(\"TPR (재현율)\")\n",
    "# 0 근처의 임계값을 찾습니다\n",
    "close_zero = np.argmin(np.abs(thresholds))\n",
    "plt.plot(fpr[close_zero], tpr[close_zero], 'o', markersize=10,\n",
    "         label=\"임계값 0\", fillstyle=\"none\", c='k', mew=2)\n",
    "plt.legend(loc=4)\n",
    "plt.show() # 책에는 없음"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/pdf": 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\n",
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import roc_curve\n",
    "fpr_rf, tpr_rf, thresholds_rf = roc_curve(y_test, rf.predict_proba(X_test)[:, 1])\n",
    "\n",
    "plt.plot(fpr, tpr, label=\"SVC의 ROC 곡선\")\n",
    "plt.plot(fpr_rf, tpr_rf, label=\"RF의 ROC 곡선\")\n",
    "\n",
    "plt.xlabel(\"FPR\")\n",
    "plt.ylabel(\"TPR (재현율)\")\n",
    "plt.plot(fpr[close_zero], tpr[close_zero], 'o', markersize=10,\n",
    "         label=\"SVC 임계값 0\", fillstyle=\"none\", c='k', mew=2)\n",
    "close_default_rf = np.argmin(np.abs(thresholds_rf - 0.5))\n",
    "plt.plot(fpr_rf[close_default_rf], tpr_rf[close_default_rf], '^', markersize=10,\n",
    "         label=\"RF 임계값 0.5\", fillstyle=\"none\", c='k', mew=2)\n",
    "\n",
    "plt.legend(loc=4)\n",
    "plt.show() # 책에는 없음"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "랜덤 포레스트의 AUC: 0.937\n",
      "SVC의 AUC: 0.916\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import roc_auc_score\n",
    "rf_auc = roc_auc_score(y_test, rf.predict_proba(X_test)[:, 1])\n",
    "svc_auc = roc_auc_score(y_test, svc.decision_function(X_test))\n",
    "print(\"랜덤 포레스트의 AUC: {:.3f}\".format(rf_auc))\n",
    "print(\"SVC의 AUC: {:.3f}\".format(svc_auc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gamma = 1.00  정확도 = 0.90  AUC = 0.50\n",
      "gamma = 0.10  정확도 = 0.90  AUC = 0.96\n",
      "gamma = 0.01  정확도 = 0.90  AUC = 1.00\n"
     ]
    },
    {
     "data": {
      "application/pdf": 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\n",
      "image/png": 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      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "y = digits.target == 9\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    digits.data, y, random_state=0)\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "for gamma in [1, 0.1, 0.01]:\n",
    "    svc = SVC(gamma=gamma).fit(X_train, y_train)\n",
    "    accuracy = svc.score(X_test, y_test)\n",
    "    auc = roc_auc_score(y_test, svc.decision_function(X_test))\n",
    "    fpr, tpr, _ = roc_curve(y_test , svc.decision_function(X_test))\n",
    "    print(\"gamma = {:.2f}  정확도 = {:.2f}  AUC = {:.2f}\".format(\n",
    "        gamma, accuracy, auc))\n",
    "    plt.plot(fpr, tpr, label=\"gamma={:.2f}\".format(gamma))\n",
    "plt.xlabel(\"FPR\")\n",
    "plt.ylabel(\"TPR\")\n",
    "plt.xlim(-0.01, 1)\n",
    "plt.ylim(0, 1.02)\n",
    "plt.legend(loc=\"best\")\n",
    "plt.show() # 책에는 없음"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 다중 분류의 평가 지표"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "정확도: 0.953\n",
      "오차 행렬:\n",
      " [[37  0  0  0  0  0  0  0  0  0]\n",
      " [ 0 40  0  0  0  0  0  0  2  1]\n",
      " [ 0  0 41  3  0  0  0  0  0  0]\n",
      " [ 0  0  0 44  0  0  0  0  1  0]\n",
      " [ 0  0  0  0 37  0  0  1  0  0]\n",
      " [ 0  0  0  0  0 46  0  0  0  2]\n",
      " [ 0  1  0  0  0  0 51  0  0  0]\n",
      " [ 0  0  0  1  1  0  0 46  0  0]\n",
      " [ 0  3  1  0  0  0  1  0 43  0]\n",
      " [ 0  0  0  0  0  1  0  0  2 44]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    digits.data, digits.target, random_state=0)\n",
    "lr = LogisticRegression(max_iter=5000).fit(X_train, y_train)\n",
    "pred = lr.predict(X_test)\n",
    "print(\"정확도: {:.3f}\".format(accuracy_score(y_test, pred)))\n",
    "print(\"오차 행렬:\\n\", confusion_matrix(y_test, pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "hide_input": false
   },
   "outputs": [
    {
     "data": {
      "application/pdf": 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\n",
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scores_image = mglearn.tools.heatmap(\n",
    "    confusion_matrix(y_test, pred), xlabel='예측 레이블',\n",
    "    ylabel='진짜 레이블', xticklabels=digits.target_names,\n",
    "    yticklabels=digits.target_names, cmap=plt.cm.gray_r, fmt=\"%d\")    \n",
    "plt.title(\"오차 행렬\")\n",
    "plt.gca().invert_yaxis()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00        37\n",
      "           1       0.91      0.93      0.92        43\n",
      "           2       0.98      0.93      0.95        44\n",
      "           3       0.92      0.98      0.95        45\n",
      "           4       0.97      0.97      0.97        38\n",
      "           5       0.98      0.96      0.97        48\n",
      "           6       0.98      0.98      0.98        52\n",
      "           7       0.98      0.96      0.97        48\n",
      "           8       0.90      0.90      0.90        48\n",
      "           9       0.94      0.94      0.94        47\n",
      "\n",
      "    accuracy                           0.95       450\n",
      "   macro avg       0.95      0.95      0.95       450\n",
      "weighted avg       0.95      0.95      0.95       450\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "micro 평균 f1 점수: 0.953\n",
      "macro 평균 f1 점수: 0.954\n"
     ]
    }
   ],
   "source": [
    "print(\"micro 평균 f1 점수: {:.3f}\".format(f1_score(y_test, pred, average=\"micro\")))\n",
    "print(\"macro 평균 f1 점수: {:.3f}\".format(f1_score(y_test, pred, average=\"macro\")))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 회귀 평가 지표"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 모델 선택에서 평가 지표 사용하기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "사이킷런 0.20 버전에서 `SVC` 클래스의 `gamma` 매개변수 옵션에 `auto`외에 `scale`이 추가되었습니다. `auto`는 `1/n_features`, 즉 특성 개수의 역수입니다. `scale`은 `1/(n_features * X.std())`로 스케일 조정이 되지 않은 특성에서 더 좋은 결과를 만듭니다. 사이킷런 0.22 버전부터는 `gamma` 매개변수의 기본값이 `auto`에서 `scale`로 변경됩니다. 서포트 벡터 머신을 사용하기 전에 특성을 표준화 전처리하면 `scale`과 `auto`는 차이가 없습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "기본 평가 지표: [0.975 0.992 1.    0.994 0.981]\n",
      "정확도 지표: [0.975 0.992 1.    0.994 0.981]\n",
      "평균 정밀도 지표: [0.976 0.989 1.    0.999 0.95 ]\n"
     ]
    }
   ],
   "source": [
    "# 분류의 기본 평가 지표는 정확도 입니다\n",
    "print(\"기본 평가 지표:\",\n",
    "      cross_val_score(SVC(), digits.data, digits.target == 9, cv=5))\n",
    "# scoring=\"accuracy\"의 결과와 같습니다.\n",
    "explicit_accuracy =  cross_val_score(SVC(), digits.data, digits.target == 9,\n",
    "                                     scoring=\"accuracy\", cv=5)\n",
    "print(\"정확도 지표:\", explicit_accuracy)\n",
    "ap =  cross_val_score(SVC(), digits.data, digits.target == 9,\n",
    "                           scoring=\"average_precision\", cv=5)\n",
    "print(\"평균 정밀도 지표:\", ap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "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>fit_time</th>\n",
       "      <th>score_time</th>\n",
       "      <th>test_accuracy</th>\n",
       "      <th>train_accuracy</th>\n",
       "      <th>test_average_precision</th>\n",
       "      <th>train_average_precision</th>\n",
       "      <th>test_recall_macro</th>\n",
       "      <th>train_recall_macro</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.89</td>\n",
       "      <td>0.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.95</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fit_time  score_time  test_accuracy  train_accuracy  \\\n",
       "0      0.01        0.02           0.97            0.99   \n",
       "1      0.01        0.02           0.99            1.00   \n",
       "2      0.01        0.02           1.00            1.00   \n",
       "3      0.01        0.02           0.99            1.00   \n",
       "4      0.01        0.02           0.98            1.00   \n",
       "\n",
       "   test_average_precision  train_average_precision  test_recall_macro  \\\n",
       "0                    0.98                     0.99               0.89   \n",
       "1                    0.99                     1.00               0.96   \n",
       "2                    1.00                     1.00               1.00   \n",
       "3                    1.00                     1.00               0.97   \n",
       "4                    0.95                     1.00               0.90   \n",
       "\n",
       "   train_recall_macro  \n",
       "0                0.97  \n",
       "1                0.98  \n",
       "2                0.98  \n",
       "3                0.98  \n",
       "4                0.99  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res = cross_validate(SVC(), digits.data, digits.target == 9,\n",
    "                     scoring=[\"accuracy\", \"average_precision\", \"recall_macro\"],\n",
    "                     return_train_score=True, cv=5)\n",
    "display(pd.DataFrame(res))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "사이킷런 0.22 버전에서 `GridSearchCV` 클래스의 `cv` 매개변수 기본값이 3에서 5로 박뀌었습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "정확도 지표를 사용한 그리드 서치\n",
      "최적의 파라미터: {'gamma': 0.0001}\n",
      "최상의 교차 검증 점수 (정확도)): 0.976\n",
      "테스트 세트 평균 정밀도: 0.966\n",
      "테스트 세트 정확도: 0.973\n"
     ]
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    digits.data, digits.target == 9, random_state=0)\n",
    "\n",
    "# 일부러 적절하지 않은 그리드를 만듭니다\n",
    "param_grid = {'gamma': [0.0001, 0.01, 0.1, 1, 10]}\n",
    "# 기본 정확도 측정 지표를 사용합니다\n",
    "grid = GridSearchCV(SVC(), param_grid=param_grid)\n",
    "grid.fit(X_train, y_train)\n",
    "print(\"정확도 지표를 사용한 그리드 서치\")\n",
    "print(\"최적의 파라미터:\", grid.best_params_)\n",
    "print(\"최상의 교차 검증 점수 (정확도)): {:.3f}\".format(grid.best_score_))\n",
    "print(\"테스트 세트 평균 정밀도: {:.3f}\".format(\n",
    "      average_precision_score(y_test, grid.decision_function(X_test))))\n",
    "print(\"테스트 세트 정확도: {:.3f}\".format(\n",
    "      # grid.score 점수와 동일합니다\n",
    "      accuracy_score(y_test, grid.predict(X_test))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "평균 정밀도 지표를 사용한 그리드 서치\n",
      "최적의 파라미터: {'gamma': 0.01}\n",
      "최상의 교차 검증 점수 (평균 정밀도): 0.988\n",
      "테스트 세트 평균 정밀도: 0.996\n",
      "테스트 세트 정확도: 0.896\n"
     ]
    }
   ],
   "source": [
    "# 평균 정밀도 지표 사용\n",
    "grid = GridSearchCV(SVC(), param_grid=param_grid, scoring=\"average_precision\")\n",
    "grid.fit(X_train, y_train)\n",
    "print(\"평균 정밀도 지표를 사용한 그리드 서치\")\n",
    "print(\"최적의 파라미터:\", grid.best_params_)\n",
    "print(\"최상의 교차 검증 점수 (평균 정밀도): {:.3f}\".format(grid.best_score_))\n",
    "print(\"테스트 세트 평균 정밀도: {:.3f}\".format(\n",
    "      # grid.score 점수와 동일합니다\n",
    "      average_precision_score(y_test, grid.decision_function(X_test))))\n",
    "print(\"테스트 세트 정확도: {:.3f}\".format(\n",
    "      accuracy_score(y_test, grid.predict(X_test))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 요약 및 정리"
   ]
  }
 ],
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