Epoch Elites - MLDL Final Project NOTEBOOK.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4c24d9ae",
   "metadata": {},
   "source": [
    "# FINAL PROJECT "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92406146",
   "metadata": {},
   "source": [
    "## GROUP: EPOCH ELITES :)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1736857",
   "metadata": {},
   "source": [
    "Members:\n",
    "    \n",
    "    - Sharmi Das\n",
    "    - Sajib (RYHAN) Suny\n",
    "    - Shalini Ivaturi\n",
    "    - Siddhartha Chowdhury"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9d3a798",
   "metadata": {},
   "source": [
    "# DATASET"
   ]
  },
  {
   "attachments": {
    "Screenshot%202023-12-15%20001005.png": {
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WG+baSw/RKXFfSPMabt2o5yfO0JkPTVLnn4yTzwyd7/lIZz45W/dPXaVpdXg9K9vT587eKPOwnjqxEanisecfX7fWtN759vHcZe75NnmF3lm+TatKqpxwtagtMApry9o1euSVqTrmdxXn088mrtC07fH2k6TBI4bogbq07Ow1SI+dUHtoHSwp1KLla/V8+fmVp+/yQ+ZdW4k/S0d3q2M3zHvatOWaHKengC4H99S1Xrmuxg47QLFuWZy3bLUe8sq7ir0P8SL73rfXnUc+0pBfu+dJ3z9Pcc6TKZuDVV+nKsz1cEg/3dnIFovNeg/RNV2qtpp0jqvKObNJi/LKar0mBVp21u8aGQ43teNprE5DB1S9RjjXnh80Yar7WNzfdbVd7+vzWmfohssPqz3IDoe0eWNexTXQ/I77eF2hCqqdcJk92+pQrwwAAAAAALC7+UpLS+uUzqVc+5JXapgB4djd8O1WkYi9RaFKCtJ05oBvddc5c1VSWOZ82B1I8Wv8tD6KJG3XWQPXKyXdPC2hiEJlZjBjm2G6kaYZ/JLf51PAjH1JpsZW+p05To/E9hPHiBnbdcyqzoo2BPWbZWzIaxf12Z06oZKZabsQtsuFzX7MerZVbsiUbYtXy1nMrJMUsGGxKZhxsNint79qp2Bha5139CKFy0Iyh6q0jCT97s0BemtOH6VnFisYsvu0GzLr7UHz/bux+V5Nhh+vHy4/ME4IVqhXnhyvC7/0Jne3Ycdp3ZU5au9NVlEU1Lb05PL7+4WKt+u9L5bqv9Ny9Vqube3UXMMP76QrTuimjE8m6ZJp7nKO7EP0yR8G6Ni4L0FE29ev1l9fm6u75m/36qrK6dJDt1x8mH5W070bw+b5e8Y8f5X3Xc4cw6PmGGKtvGO1rr7pYz3pTcZzww1j9GC/Wtq0rFuqw38/o+ZuOE86UVsv7LDzvRKDG/R/176vu73JynLOOEXfnN0uflgUDmrx/IX65UsL9H6sFtXtu+nhK4fo591Saw/XchfJd88cb6Ka7EM19Y+H6uiYT0OZFnw6TSPH5db6ZQL39RyogUte07ETvMpYmsS54zl/pCKnxP4Ef/3cL9ThsXh3Io6jkdt74I7LdHOs5EvmvVpk3qvlja7D+mH5Sj36xbd65dMNslF/TpcOGjmkj27I2aK+zs07K9jge9plOepUw5cOnPf/J1/rpte+d7YXS58Bh+je8/rprPbJ2ljD4znnynP06rCs2OeleV3enzhNV72zLs451U633DBc9/WLHRrnLZqlgQ8truF8zNBvbzlLf+wVv9tR+1jfeGemfhnnGPocMVRPjzlIR9Sh1dzs98dpyKvexC409prz9PRhsVrd5+kvP5mkW7ypoRefqWkjWsZ47oJ6/+WXdOqH3mSteuvtB4dq5E4XqAI9/88JujR6itVwztd43ams0jaC2zfq2fcW6i8frI57HroydMFlJ+ipY1vGuYZGzGszwbw2Nbfcjf+8VlOyQxPem63fvBX7uOw5898LemlYTTdvDm7UH/7vPd1ZQw8ZTe14avwbog6vb90eT0Sbvv9WNzw1U8/FaNJt72n9ymU91b+G3xl1ea1rfCwOe11dqpuejn0c9n7Xt485XHccVodeBbat0hW3fBK/NwwAAAAAALDfK310jFdqmBo+9dl3OS1DK31ma78470vya87abN054VT9v6fO0IPv9tPXuS1UVhZQSnpAqZkBpaX6lJxsV/Q54azNsINFYZUUhlWUH1JxQZlKistUGixTWahM4UiZ/L6Q/P6QAmbwmXLE1AXLzDKlZSouMssX2fXCzlBa7G4z2uI11ewrPc2MM/xKNccQMseycGULPfxeb+cY/++1U/Xlmmz5k8zx2IfkBbe2Zax9iIihfUYNLRGLlbunQtjaVAphC9Ys1cV3vqEzXvzGC2Gt7Zr65Te66v5qIaxx7aV9agzS1iyaq1G/+yRukGatyv1O15ttX/rpVhV4dTvxZ+jcU4ZqqDdZ1df6YEWcNlF1uk9sdx3bqZYQ1jqgtS6spbXNxT1a7BzCGqG1m+J8ENtdfz++phC2UO9PmKK+j8UJYa313+v6+97Wz6btiP/81cWgtuof52kozv1WP6pDCGu5r2ctIazRNM6dvU2lENaeG699qPb3T9UfvRDWWpW7Tv9+zZwz1UJYKUd3n35gjSFs+fu/hhDWWjz/a537uzc1csIafR+vmVrXQfrtkDghrIr00YSpOjVuCGtt0AMPTdUjq2K/t7P79Kz5fqfDhuramkLYret0+yNv6NwajmHxjJk68u4ZenZDmVez95j53kpNj/naJOvYQYfWuZV4zqiuOiHGBSq0ZrV2OsUSIVSsaZM/16E3v6erag1hrUK9Mm6y7l8a7zXy6eBudewZoRah/A36w8MTdW6c0NOy58xR935Z8zmT3Ebnndram2i4pnY8jWOu+XNnaNB9ccJPY/GM6Rr50iqtMX/HxubTwF4HeeV4WuuBEzrWEMLaLx19rqH3xz8O5a3TfY9N1EjzS7lRv3MBAAAAAAASYL8MYp37pFYKKp3JSERpaaXKyCrQym3Jenb6AF097kyd99Rpuvf1wXp1RmctW5us4pIkpSQnKTUjoNQsv5LT/UpN9SvdDKlJPiXbVqves+q0iLUtW81gg9Joy1qZ/dlWsckBKcWsk2bWTUtzu0V2Q1dTNvuw+/re7HP8zC66b+IQXfD0abrqf2fq6WmDlLslSelZhUpNK3OO3cbD7g+XfUzY2enNUrxSDDsKtcQrNlWhrat0wyMz9Epd72Pbdah+dnDcJE0Fud/okocW6VNvumbuh+k3zI93v1cp0OlA3TDQm6jmme+3xemesg73ie3fXgOqpaehrYU732Ox1vvEttZxHWPva0lunBDzjJ46PVZy64ho0dSpOvW9Dd50TQr15FMf1BBG1EHL1JghsrV46eKaWwLXVxM6d/ZOZZr9YV3PDVfOqH66sG38i3dB7iKN/EM93v/meX//nSk66snYrWHHnt5Ng+ME++vnz9eVdTr2DbrxzVXK9aaq8LfQccPih0e/HV5D2BLepief+EgPLPWma5K3TGP/tlCfNoGON+ol7yu9sDj2Qad171xziF2utW4b1EY7d8gc0vQ5CxN7TbA2r9a9j0zSUS/W/EWAnRXq7g9Wxz5PjLS2LXWxV24we8489r7urOs588y3mh33nPGpf//eOt2bapCmdjyNVLxqiS55rPbbN6yaOlN/iXNeW4E2LXWVV47JPM5zu8T+eoiVt2henXp+sD599WPdMLewhq6xAQAAAAAAdr39Moh1RD/rtuOIDS5NIexXKGzGKRGlZxZKqflavz1D4+f30j2ThuvKcRfq0v+epbHjjtd9bx2q1z7vpM++aaOFq1to5eZ0bS9MVqjUJ3/Ep6SAX0n2nrPJASWnBJTiDbYu2cwLmB2Hg35nnVVm3UVrWujzRW01flpH/entQzX2f8eafY0y+7pAfzT7fnVeL63ZmqFIWr7SsgrlT5PKQgGFzfHaY4+2hq0cMGNn7dLif7hn+4Ku7V5te1S4UOMnfKIn6xzCSKeP6KT+8d7lwTw99tycOgZpUYV68oVvawg8MnX0kNjtuFbN2hw36K7tPrFDB7ZW9bu/5n6/WTs/FbXdJzZHA2PeH3abPpsa+4aNv+3XOkbI4Qpt/F53jKt70OaEEa98q9m74ERrnlnDzY8boCmdO3ujgu8X65pX63NuxAvUPAXr9NvH6vuc16SPLukTpxvS4Eb9+4V63C973jd6d51XrsKnvt27xGnZeYhO7hrvehzR8hnz9LO6BFhReV/r5k/yVOxN7i0e/WxdnBC7pc48qQ7vh4F9dWanGOF90Qa9+mYt3b82xJSvdMeiBm533lrNiXez8Mx0Na5NbAPOmaVz9KsZ8b4gZLRtrbPrFIbH0tSOp7EKNP7NWXX+4s1DMzbs/EWpqGYZ6u0VYzl9aLudft+XM9emR56tqbvz6szvnZcW6SOaxQIAAAAAgD1o/w1iKysPZd3mqraFaVnIr7B5egJJISVlFiq9WYHKAoVaV+DXglVt9Mrsg3XvByfoV6+cqh/9b6QufNq2nh2lS549Uz/+36n6xfMj9MsXj9NNLw3XrS/b4RjdZMY3vni8rnthhH487hRn2fPNOheY4UfPnqEbXjlF97x/ol6a3U9fr2pn9hUw+yxWemaBUrIKFUgOKRzxm2Nzux42P93jNqNI+WPwxtjnFC9fpptquofmTuyHtlleeWe5c7/WLSu8ifrI+1r/XRS/ZWOXbjmxW+2sWKVZG71yNWkHttMNXnlnGbqwS3OvHFWk+fNWaUmMD/Xbt28bv4vbk1qrT6yr3sbNmhjzuagpLApp+vR5et2bqrMVczRuaQOT2FA47of03fsdpKtq6Za57prYubPXKdDEd+bVrzWibe0WK1BzhPT55Gl6qB5fwqjVSZ10RJwcdtvS3JrvRbmTzfpkbexwLtCulc7zylWc0UGHx+ttPLhJ/5tY96glauary/Vp/NOraYobYpv3Q48uOscrx3PtMR0U61bFectW6yGv3HQs13dbvWJ1yUlxW/vXSQPPmU8nrdG8uN3oZqnvwV6xvpra8TTWurX16+Z6Wp6+jftrLk1dDveKO6n5d8/6BUvreW0y8hbrsYUksQAAAAAAYM8hiK3E6+DX5TNTPht4+hQOu+FnyOdXJCmklLRSpWUWKjVrh5KyCuVLLTbrlmlbcUArtqTr6x9aakZuO32x/AB9sqyjJn9rhw76ZGlHTTV10828r9e3MMumaatZJ2zbYaYWKCmzwGxzu9IyzLbTS8y+wmarUlnY3pPWPZZot8rufW7t8TqJLPZ5IX258Kt6tAKx4rX+tAr0+az6f0gc9cy8TfFbu7RurmO8YlVr9eKyfK9cTXozHRb3PrE9dHjHaid50VZ9Om255myIEUvWcJ/Y03Oaxfywf/3q9XrHK1dxeEv1iBsW5enDzxvWMuyh3BpaPdVk6fa4XXuqxYF66FfDdU38G+vVQ1M7d/YyG3/QuHremzNWq+9y29bqiQS3bhzbq2Wc4Cuk+Uvr1+ms9cLmOG1R0zPUJ0YrvosPzIrb+rc4d53+06DQebFmr/e+oLTX2Kz/LN4a+3rQuoOuHuGVY8k+VBf3idV9eIHe/aypd7SfWMUr1tY/oLPycjXrB6+8k4AObNfRK9dPUzuexlqz9od6dnO9WSvihe7mj9akuJ2T1PS7p0jT5sXuZr02ry/eovr0TwAAAAAAAJBIBLGGc99We59VO5RXeCGnU3b5ImGZ/22jNCccdcJZM4S95qj+QEj+5DIFUoMKpJeYwY5LlZQRNEOpV2fGaWYwy/iTzfKBsJOn2pauIS/wdYJXMzj3fi3fvVtwAliH2yrWOU4zrljOqjKBukpJUiuv2OSEt+jzt71yXQ1vqW7x3uE7tmhKPYOiKmpq7eLPVJ9hXrmadxZviRPCZWnIwDj3kjypnQZUC0OLV29wWnvFvO9s3PvExmtpU6I5i+N8uNu5mTp5xZ1s2qq3GxQWGeuLFKdxcM0WrNDHG+K/vzPbddU/7xyj7286Ur8aUL0VcT00wXNnb7Jm5drYwX4NTu1QQyuw5av0jFdOjAwNbBOnOazy9c1Cr5gQKWrXwStWMqhN/PtCL1+7pp5fOqmwZOve1jmxNPO9lZoe8z2RqhOGHhqna2cp5+gOMe/xG1qzun6tFxOuuYYf0kmXnHyY/n75cZry69O08P4LteWRS3RzrOa7CbB83VqvVF+bNc1cj+PJyqjl/uVxNLXjaaz1m+vbBcJabWjId0eGtVCXeL97nC9geeX6WpRvjggAAAAAAGDP2E+D2IgbaHqhphOj2tavdrBFv3lazDxnttPq1I7sPO9+rOVjW29bzjoLOsvbwd63VRG7DWcJJ7yN2Drn6bbzbF2gfHmzAfu/ty1v2872ncryshm5vLE7MhswBS8L9lSZQCXPbKyh38r01Pih2562vUBfe8U6a5+hdl5xJ3nb9aRXbJgd+iFuT38pah2vi9xpP+irOC9B9w6xW/rs3HIvpNmLv3NKse87G+8+sR3Vt41XrKwoTx9M8crVjG0bL6ySNmzYXM8WQomwVnd+vD7GvXEr8Sera++e+uu1o1T0t7M1+fK+Oqu+rWSb4rmz14ho9Yb6hhZddWjb+F1gf7uyYa3A4muvnXr7LtdCP/3NZYo8Xs/hlHgvXJo67nT+dVePuLc0LtayFbHv17zPyvtKLyyOffPktO6ddVvM+4LGu6dwSNPnLNxt16acLh300zOO1PibRmrZX92wNfL4WfrsuhF67oKDdf3wHB3fvY36ZaeoZequ+pMzqNXrG37OTI7Xmtto17IhX2hpasezF2mfrrZecSebtuk1r1hvefG79QcAAAAAANjV9tMg1g03o8mmE2I6qag3bcvls91w1GmdGl3HBq/OMnYBM9j1KoWodh37n62z65X/Z8t2Ve8/N1x1KtxtOPu3+7Jlb/vOCnZpu4y3rF3XXdT94dSVjww3FEYMRWWK/xFnhg4a7hWbmm0FesEr1tXFreN1/Gk319huTlcoN8b9WV0BZcbNLxfrne9jN4eMfZ/YjjrhwGobC2/TtGiXwHHuOxvzPrHDW6tPjNZj0da1sbRKTfJKO8svTGxXsXW16sNpum1uYR0+VPYpLauZRgwfrIlOK9mhurJL3VpTNc1zZ29RrLVx+16OJ0mpcbvqLNKKuP1RN1RzdWzmFXe5WN2QpigzxSvupExb43Zpuu969LN1sbsd97fQccNi9BYwsK/OjHVP4eBmvZvgbqx3lqFTTjhSk++5UN/dcaL+dXZPje6drR7NdmXYWpMyFTTiFqCrwon+g6mpHc/eY2hmsvktEFtxcUmDW8oDAAAAAADsSftpEOsGouVs2Wf+t6FolClGl4mGsE5A6wzOwhUL2M9CnRDV3W55IGvqouWKodJ8Z392bEd2RTM223COw853N+YOVnQds1031I3I72zDDmaW/WFnO9twqlDdxiLFb6eSpp5d43SPuxdK8cc/CYpKSr3S7vfQ0i2xw/BY94ntmqMh1ZvH/LBZL5c3CV2ryatjNLE9oJVGe8Wo03u1jNHKs6J1bSydMuPdIFbasmNPdXRYqCcfe1cXf7pF28NeVW2cVrK99d/bR+mba/orbuNFT1M9d/ZdzdUpbjBaqg0LvGLC+JW0R3/7Z6h13MB9VzzevcC8b/TWGvd3eVU+9T+0r87xpqKuPaaDYvXym7c4V3d75V2i/UF67q5RmnRRT41om6L4V0ig/vo1i/sNDW3Nb0S6DQAAAAAAsAftt0GsO6r40NMW7b1Zne6BbYWXaro5qPnhLOuGEzbodEJZU++MLbOeV+XURevL5zvc+oohOt8WKvZRXu9ty86ObtccoVNvf9gQ1h5ztEtlOzjz7CrOhGUnvGJFYf/15VZ9F+/+lEbvHt13bkmJxJq2SQtjBog73yc2Z0hr9fbKUctXrKrS7eYzS7dqpwaW/hYafJJXdmTolANj3IOzcuvavUqhXhn3tvo/PE8T1gfr3uWiP1l9DhuoSb89Rff02zP3GgQQy2b9ac6m2F9Sad1BV4/wylb2obq4T6o3UVmB3v1s587aE6ZXP733q6G6pH38VouxhIJBbd2xQ3OXb9IysjQAAAAAAADsZ/bbromdUNJJN90pO7RJCaq0MF22MVjAb0NLf6VQ1A1p3bHXotUGo2bshqVend1WdL7931vOHSrWrTw4XRHbVU3ZPayKejuOhryWHdlb2AZMdWlRulqnhpzV7OrRnNVOW846zra9Ge5S+7m1+maTV4wh0OEAjY15Pz4kTF6upq+LnpNV9c7J8Uqusd1aVPvAv0jzF1driTpni5btFOwm6+AelV/IHhoU6z6pVVrX7n1WLVqgc3/3po54ZommbCxVDd8xqCKQ1U6/ueZ4PdDLqwDKhVVQWKqtCRx21PXE3M+t+nydZsd8rlJ19IA+XlkaempnHRmjKWpozWo9NM+bSLh2+tdlh+mUlvH/jrCB66p1m/TOl4v18MQZOvOR99X3J+OUdO1LanXTRA26/129XsPv3z3l9BpaYRaX7v6Tt6kdDwAAAAAAABpnPw5ivQ8TzciGmmUlYf14xFxdduyXCuY3V1lRqgL+kPx+t4WsDVsjYVNy001n2s5wWqmWh6Wmzv5vl600uElpxTLVh4r7xNplo+uHnXq3bANZc5wBtyvikDm20vwsXXzUPP3sxC/NsZvj9HbhPiy7sei03bZTabj1+7fNmrgi3yvH4G+pi0dVb4O5d1q0I34Xsu2zW3qlhuqodnEbVBZrTY33yNysZ77b7pWrCrRvXek+sX10zIHV2l1t26SJ07xyVF6uZv3glSvp1PGAitbNce4PW711bXXBGu7V1751U0nsCzX785k64Y6X1eOeafrz3DytMtezWqVm68Yrjtqpy1Or6Z47+6qgCuLmK+nqMcwrJsx2rdnhFXeyVY/d8LJaJXAYMdHbdLmwyuKeomnqcrhX3N/kfaUXFpd4E1W16NVFdzpdirfW2IOqf0HFCmn6nIU1Xs8aY+j5QzS2Q/RviapCxds14Y2P1f/al9T59+9q5JOz9Mu3l+rtrzdosbdMU9YpI/69wPdEd7hN7XiaipZZmV6pAbommyspAAAAAADAnrGfBrFeSGmDT5uzmLLPlNOTwrr1jG/0xP+bqMGd1ytcnKnSgjRnmSRfWElmvvwRL5C1q7tPXzRQdTifU3rlaADq7MddxtaUdyTszPfCVmcx2wrWneUdlJICZjD7ltlnaX6ac0wDc37QY5e8odtHfaXM5JB8YXe7zjp2s876iOedKeu0yCvHkn3wQfrXPtBScOaWktjdXFotMnWxV2yY1uoaN48r09atXjGOmfM2a7lXriK9hY6KhjAnddIR1T453bbmBz3jlSvECdcr3Sc29v1h8zV1Zs33eV2yNe4zqNbN497Us3adMhWrgW5jrcr9Trc9Nkmdr3tdQ55ZqEm1dFscaNtFN4/aORVtyudOouTUcB/c3a9Am+P2kJ2ubjmJ7ka6TCVxT4xdEfxWt11r4wbBqTqg+n2h66F/9t4dtzz62TrleuUqkrN10tHmPOjaUyM6xTh3g3n6cJd1s95aPz4kW+avoZ2V5OnBR97QuW+t3oOhq0+B+vSVXEVrDWkX85E51myM+ZuqFk3tePYez2yMcc93T1pWRsNvHXFgutp4RQAAAAAAgN1tPw1ibfhpRk4a60w6xVAootKisAZ02ap/XfaZHr3oDY0esFzNkqWywmYqsaFsSZLTKjWQZAZ/yOnC2G2NWhHKOi1kne3bmmjsaif8ztjpitiUfba1rVnWDrblrd8fNtszQyDsbFOlSc4+y4qaKStJGnXoCv1jzBt64v99osHdtzrHGg67x2436YTBZuzs39mrZfdfUYaxYpmmrIk+JzH4W+iqOC0F9yq5+YobM7ZsqeMa06BzWLYOitHC1FG0Q3MXeOV4FqzX/J1u7Gpl6OCD3PvEju3VUi2cUlRI85fG/qj/ncVbtFNDyvL7xGbohI4xWtJs26LJtRxnTS1D09pla6xXrq8bDmxEiFsntpXsXJ3xuzc1csI6rYnb+jCgwX16eOVKmuK5U1QWNxxuSCvdU9s2pcBuuRbnxb8m9enaU1U77W6sFVq2Jd7+dkXwW902bYibGQZ0UOfuXrm++ujQnb9xsXeZ943eivn7KaAjD+2jY4e3Uz+vprK8xSt0567qZj27m47o4JWryZ3/tW5Z6k3UKkNJu+SvzjR17tjAcza7i4Yc4JV3UqjlK71ivTS149mL1HCd1wGtdaHTKrz+Yn8ZCwAAAAAAYPfYb1vEVhaNLe0QMD/LSiIKloU0pEe+/u/smXrtx2/rT6Pf0+n9v1eP7BL5wykq3ZGu0oJMlRSlKViaZHtalD8SUZI/okC0Jat5dpMDYTNEvHHYme+2cg2ZfYXNOmbvIZ/Kgn4FS9JVkp/lbNcfSlX3lsU61ezznrPf1as/ekt3njNDhx+0Q6XBMrOs2Y8XsTof2ZofVfLX8tDVRr8VZVib9YtP16qmz6wDbbvpHzf007He9F4pbthptdBpJzU82jnn4Oy4LTqLV2/QQ145vuWauDx2yxf3PrEddcKB1YKy8DZ9Wb1b4qhpP+irnTYXvU9sDx3eMfoeqBC7dW1VM9cXKv5TmK1TBnrleumtk7vESyITrVDvv/ORLpm8Je6H22ltW+7cwrUpnjt5JYrbWLberXQ76piO8Vud7QkTVsXurttK695ZtyW4J+zP1sfv4jTxwW91m7V4S/x7Xbbv3LFhX4QZ0UFD9vr+RzfrT3M2xXy/Bjp20N97V/16iqtA7362xCvvAv2yzDsmlqCWrFjlleuis/rtomaJDT1nc45uq4Pj/SUczNdXX3rlempqx7PXWLgtdm8Zlr+FhtlW4fXWWmd3zfLKAAAAAAAAu99+GsS691yN8noIVnKqT/4kv81UpXBEJcVhlRaH1CyjVCMO3ai7z52pZ654S89eNlF3nfWZrj5qrkb0ylW77AI1S5JSI+lScaZCRc0UNINtzVqYn26GDG9IN3XpChZmKVTSXCrNUko4Tc2TpTYtinRsz1xdddQc3TXqMz1z6et69sq3da/Z58kDNqpFs1LnWGwrWO9w5U/2KznZTEVDWMsZ25a25qddyD646LyKAqZ8pf/m1tRpq0+d+h2m5/fqMHa5PloZ+36DVpcBffXbhrQuye6jaw6Od6+2kGYv/s4r1+yZpVtjhpzOfWK75mhIte5JQ+s26uW46flKfbVh5y8aOPeJjdkCM6gZC+rQkeacLVoWtzVppk47vk+9P2wfen4PndCIW901xKcvr9SX8XIvn18pXrFCEzx31hXH//JEfVvpDuyu4xrR/e2uELe7bsveu/qc+p9rNYnZityT1r277m7Qlwzq7rXVO+J3m926g645qb6BS2s9cFR7NbDBXJOy6s0VmhwrJ09upYExWkuG1qzWQ/O8iV2hfUac1oRlKqjHLUtzTuq0y4Lyhn1ZIUd3H9kmdpfLRnHu+lq/rBNPUzuevcaKjVoS90tAAR055JB6/02Wc9JAXRCnRTcAAAAAAMDusJ8GsV7XxJX4An4t/L6lNm5LUkpmwA1lzbNjlysLhlVSFFZxUZkCgZB6dizSGYPW6GcnL9JfL5ymt370gV696i09O3aCHr9kvP5+/njdN+o93X7qVN184nTdeOIM3XDCDN1kyr8xdfee9b7+fu54PXHxeLPOeL1y1dtmG+/rwQu+0M9PWWS2vVq9OhU5+yox+ywpDCtojsGyx5Sc6ldKVpLydiTp6+9buZXmOCs/Jlt2wlk7VHussDbrlpeXa1HckM2yYewgTbr7ON3er7FddTbXpRedqtlXNbTLzYaJe79BK7Wdbry8vuFOhq4a008nxsvSCtbrhTfreJ/CDzdofqxwML2ZDjuqhao/U0u+W66ZXnlnhXo5N0aLwjYtdGGP5ju3wAxu0WcfeuWa5OVq+rr4b6DsPv309+H1ODd6DdJjx8W51+IuVaQabncbU5M7d1Zs0+q4tw+sTyvddnpwVI66eFNNxoIleqeGLtOz+w3UhPMT2LnmtFWaFi/w8GfpwlFDdumXUFbN2qhv4l5/U3XiKUN1VT1S1WPPP0LXdGnwjTmbmCWatDz+FyGqCmn6nIU1XBt3pTR1rPPNrnN094hdGJT7W+qKiwfW6x6ix154qC5sG+8LaiHN/maZ6tPet4qmdjx7jZq/BBTo0E1/q891MLun/n7KvvEFDQAAAAAAsPeiRawRipgnItWvl2YN0Pn/OlePvHuIFuRmKsmXotTMgFLS/UpJ8ptpKVgmFRVHVFQQcgLSkpKwwipV8/QSdWlXrP5dC3Vk3wKdNHCDzj9ypS49doUuP3a5xprhMlM+b9hKnWzm2WUONst2blukZhkliviCKik12zPbLC4MOfsoDUkBv08pyX6lppljyAiY6RQtzE3To+8frPP+NVrjZgxyjj0UfUze5/iVH58TxmJnS2fomg/zVFuDnsx2Obr3+lH65rrDdGWXegay7Q/Ury4/Wd8/PErjTmirjrurR9qoed/olRpa/mb3G6xp1x6kPt50zTJ0yoXH66HDMhQ77oho0eyFetSbqt13mhLz2JJ0cLesamFlvmbN2+yVY4vZojA5VUfGuFdfaO2mOrYsit9NqMOfodFjjtcDvbzpmmT31Pir+2pwqjfdAGN/eoamX9ilngGoMbC9BsS7LW1hsRZ5xSqa3LmzUos2ecUYuhx2qB6s9XXI0FVXHaWf5TTFwM6ca5+vr6HL9CQNPuk4fXJOh3q8/uZ5P32Evoj5BZDlenZRftxWqWk5vRvcI0BOlz567q4Tda83HdOKhXptefzzK9AyRw9dM6hO+88ZfpyePylbu7mh+S5V4xchKgvm6cPP6/jll4baWhKni3afBvQbVIew0bzvrhmqS+OGjImR2c2cd1fWrUtg55w5oVX8L8XU50tFcTS149lbPLpgUy3XweEaX5cvQGV30IPXDNHolvwRDAAAAAAA9qz9NIitxOe2Ho2EI0pKL9SO0oCemdZPP31htC556lT9/d0+mr6krTbtSFHA71dqZpLSswJKz/ArJcWnpIC7gaDtyrg0oqIiG9JWGnaE3CHfDmEV5kdUbOsL3aHUrBMK2Ra69t6xPqWm+pSW7ld6ZkBpGUlOEJuXn6KZS9vokfd669KnTtFPnhutpz7vr20lASWlFchnWxVFm8M6Iz50qqtPX/1YN8wtjBtGlPMnq88hB+u/d5yj/PtHadJVQ3TfyV11xiGddEbP5lL7dm75kK761blD9Nz1p2nh/Rep9K7j9dfhB6hr2p56TTbrlrdztTxuyzOfOg0Yqhl31dLqt303PfzrkXqrhrAjtHWl/jxugzdVF4X6z/JtMZ77NA3MqdZ/5bYtmrzAK8cT876mzTWse/X0O6JvlufWuWVR3G5Co1KzdfP1Z2v86fEDsj5HDNX03x7R+A+E/Wk64qTh+vbPp+rho7PrFsi1P0gTL+kStwVo7qq1cVrTNbVzp1DPfx+3z0qn29brrjlNDx9h3o+xZHfQ7dedqn8eXj3kbzpWfThP//6+zJuKwZ+qY0eO0MxfH6nramyln6HBRx+mt+8y16rRndQtzhdAXp+4WB/FPbcregT43YA4z2k1OV166OGbztGC24fokvapqvl7J4W6c2ZNwbOU2aVfLT0S2J4GTtOcy3LUaV/7a2beN3qrhhbSUXmLV+jOmp7ERFiWrzVesbq0LgfVHDba990Np+lfcb+EkUhJ6jXscE29rr9OidsEsi7nTEizP/+qHl8qiqepHc9eYspCvVJDTxTOF6AuO0PTL+oW94tA9nfuF78ZoRu6JHk1AAAAAAAAe46v1CaBdZBy7UteqWEGhOvazd4uFInIH5Bz79YzB36ru86e63T9a6ORlPQk3TVhiN74qrtSmxUrHJRCZUkKBVOctDotq1j922xV59Zb1bF1nga0+UEHtAypRUZE6akR+fxhyQ6W3WBNz2rl+XYc8SsS8qkw6Nf2fGnD9iTN39RO6za1Vu6mlvp6cysV56cpbBYOJJeaISR/UkjF29N12sGrdPf501VWWKaw2W5qRpJ+/+YAvTmnj9IzixU02/X57E4aGQA10nx/I5oB7nLt9MDtI3Rjt+Rd/kHx+rlfqMNjce4EOew4rbsyZ+dudK3cRfLdM8ebqL9jLzxD751UQ2sbR1gFeTv09dot+nKD1wY0q7mO6dZafVunKq2moCOcr2f/9brG1vc+hV2P0MLf9FI/bzKevK9nqvUjS7yp+G64YYwe7Fdbs+Nt+ve9b+pnK7zJOhg6+jRNOb1NrS3ugoU7tGD5Zn3mPX8ZrVrpqG5t1LtloNK5FdGa3K1K7tIq9n0Xa3itx15znp4+rCKktvubteQHvbNwleZsKtJXi/KcgLlPz07q0TFb5xyco5H9W6mjvZd0LOGtevT+t/SLGp6LJnXudB2qr3/dW/1r2p45li0bt2r69xu01FxPbbDfq2drHdmpmVpVeoMXlJQpMzX2h/Q1vk89D9xxmW6OmW4XacJTr+ncad5kffUapFnX96tDy+mI+b2Qr2/WbNXsNQVy28qZx9q1lfqbx5qTWvEk1fR46nZum31t3a4p367T/NxNmro+2qd4snr3aqPBB7bTEV1bqGtW5fM8T3/5ySTd4k3F1lr33n6ybu9WW1hS/TVNUk6ntjqie/Oq53a40DwXfg3OiX22zn5/nIa86k3sQtXfpxXq8pxUyBl1qr4d1baG916Bnv/nBF1a1+vu+SMViZcI1vg7JkfP3XecLmntTe4kou2bN+itmav19tLtbuvZVrGuP2XmfZdk3nfeZBW1Pzfxn9cYQqX6LvcHTVlRoJU7StSmWaq5HrfWiN6t1SOjxguIQuuW6oTfz9Cn3nQ8Te14Gvs3RE2PpyHvnUZdI4cdo9Vju9T6BYtQsEhLVm3RvBXbZTtMaNMu1rVIKjbLrMxppYO86Sq2rdIVt3yy799/FwAAAAAANFjpo2O8UsMQxFYLYifO76bkrBKFy3zy+SOyDV5tN79lZQGFSgMKh/2KmDXSkvzKDJQpI73UaUnbOrNQXbMK1Cq9QFmppcpIiSglKaQkf9gJciNmG7bRaplZvzQYUGGpX/mlSdpa1Ewr8tO1qSBdwcJMFZekKb/Mr+IyG52Gzb7DCqTa7YTM8Ughs6Fw2HZZbB9Hik7vv1L3nDdDpeZx2BfSDWIH6s05vQli66WdbrlhuO7rt2tb7eypINbtGnIXtUoKF+qNFz7U2Z/EuEdrrTrqmXtO0OVtvcmYgnr/5Zd0al3u6Tr6NJWd3qbmx7hxuUbe8YXe8Sbrpp0euOME3ZyA1jWhrav0szekP15e/9e6Xh/81yqiRZ9+oINrbYnatM6dhDwHJZt03wy/bj82dii1R4NYI2f4MZp6aRd1TtATXvPj2VWvbx1DxzoHz7WJaM3cGbpTA/REAsOkhoh/jtYviJV66+0Hh2pknJQ8tGaJhv1hZt3vD9vgIFYaevGZmjaiZaPOkQKzjxfVTz+O+b5pXBA7b+kG9erVrvHdU5eY43jYHMdSb7oGTe149qkgNpHXJec5XK8Rt5jrjFdVBUEsAAAAAACoRWOD2Fq+a75/ce+r6gaW0bINTm2YaVu7JqUHlZJRrLSsIiklX/m+Uv1Q6NfKjc00e3lHTZjfW/+ZNkQPTzla9793tO56+xj97s3j9ds3j9P/vWGH4526+98/Wg9/fJRZdqhem9dbs5Z3MttooQ1FAeWrREouUFpmgbOvlMygEwiXRXzOcTg9EHvRuc/8F+2ReM/GrPuCDXrgoXc1ctIP+qHWfor3RoV68rGpuv3rAkXbsiVEqEATGhzCWmv14jKniVt8wS36rC4hrDV3i2prN7t+9fp6hrDWBt3y2CxN2Oq94RqqJE8PPvGJntzj51hEaxbN1TV16kq6aZ07z7w0v3GvQ7hQE176VL+Je+PfPW/V1M80/LnlWrpbvr/kvr53m53tkdNy6RyNfmmV1sTtArtuCnK/0SWPLUvsObrHLdETC+P1HR3RvIUL6x7CNtLMF77UkzV1F1uLUPEmPfbyHG3xphMt9P3Uut1moCYlO/TsSx/XLfSsRVM7nr2Pe116MLeGrtrrwrne76/PIQAAAAAAaCoIYiux92m1fD4bcNpo021NakNZOysStvV+hUJmMGPbFXAkEFZyaplS00uUnFGk1KwCpWTlK6VZvlKbFyq1WYE7NkNac7ds59llnGUzzTy7bmrQ2Zb90M7ZdiTg7CvshK/uMdjjsh++uhN2HK1DYhTq/dc/UPs/fK5Hlhcn/gP9UKlWbdmT6c8GPfDIezpzwhqtbHTiEtH29av0G7O9cxscwrreWbxF671yLKG1m+reUmXFKs3a6JVjKtK0eTW3dIwrb5nOvX+Gnt3QsA+GQ/kbdO9jTeAD4XBQ8z+dqmEPLaq9q8tyTejcsa/DE1/r0/wGhELhEn369lSdO9XtyLcpWzX1Cx308BxNWB/cDQHpBt35wNu6+NMt2t7IQNRlX+Mtqu22zlGrpn6iYeMaGjxHtGnpAp372Jx6nM97j9en/6CYV6zgJr01eXeexxv0s3Fz9X4DvgRhr313P/LuLr72eV8YWdSw8NO9Pn+gsQm7NjS149kbbdAt90zWHxr6JZGSHXr+hQ9rv95vL9BkrwgAAAAAALArEMRWEg01nUDWF3HGTiBrBiecNf+5TU9t58S2zp0MhXwKhf1m8KmszLag9avMDKVB24rVlgPOYMu2zs5z6s2ydh1nXTNt9+Bs0+7S7tvZk62zFXZPtqbS2I6QeOu/1/X3v6oeD83Uf5bs0OZgY55oe+/MbXpn6myd/YeXdfiLa736PaVQ778zRV3+8LF+/2We1tb7sdl7Rebp+QmT1f93n+i+RQn4kHjaD/qqyCvHsCQ317nvad2s1eTVNWysaKs+bUSXsTYEHPvbSbps8sa6t5wOB7V47jyNvPt93dHI52vR0nWak1fWsC8J2HsULlmiH933pgaOq89zGtWEzp2lX+m4P39Rry9MBLdv1ENPvK3j3qxLK+AmYukinfu7NzVywgrN2Rqqdxhh7yE8ZfI0nflSXb58UKhXxr2t/g/P0/Mri1TckEA2HNLmjT/okWfeMa/xtHp19ekEz/fU70swoeLtmmDOp0EPzNP7eV7lvmbBEr2zZuf3Wt7iFbpzdz9mcz6eev9UPVTn1yisH5Yv1sXm2nfnbvkCSkXPFnW+Ppnr4sIEXZ931tSOZ2/kfklk5IRVWlxc19859rxbosvumahLo1/26Zqs2J0uG+FwA34fAgAAAAAA1B33iI3eIzYtoD9OHKLX5/VQclaxIrYlqql3AlinRaobgEbLZlSJs6SzHcud5Ya17hxXtOxGrNWXNyov7Ijuy4a+7kwnJDbjQCCi0oJUnXZwbvk9Yu3n5mncI3YXaK7hh3fSGYd20PE5LdWnRZKSU1OUWe3GZaFgUDuCEe3Ytl3frd+q6cvW6+2vV2hqTc0997jmOuvkHhrT9wAN7NhcHTOT1DK10vczwiFtLw5p27YtmvXder33Ra7+vaxxLWD3GdnZunJYP11weDsNa5WqZuYaEj0lgiWl2rJ9mz7/eqWe/vgbvZHgcyCnS2ddMLizTjqouQ5qm6XWKdVeN3PtKC4OqriwSIvXbtHH36zUq7NXanZCg5umce7kdOmhX4zsrjO7tNKBzZLVPDl6rQuroLBYuas2663pX+sfn+ft9R+29xnQV2OHdtCp3bLVzTzWyuec+3jLVFCQr0WrN+rNGd/plTmNeMztD9Svju+hUT1bql+bNDVPS1Za5VMsVKatJWHze8juL89c79Ym7Byzr+kVJ3fRRT3bxHhNS7V+/UZNmv2d/vnBai325mD3ivu+s+eFue58Y86HFz5ZqEcSGCbW6x6m9vo84hBdPait+jZPqXRt8s6hTXmaMTdXf5v2XYPP2aZ2PPs++zunt64Y3FFHt09XK/P3brI3x/7OLSgo0rRlK/TKB9/pqdxq590uvQc/AAAAAADY1zX2HrH7aRCbqjMHLNVdZ89RSXHI6eU3JSNJf5wwRK/P766UZsUKBf3y2c/JbPDphbFOmOlMO1urYKv8ttIGtc7i3thdz047i1Wriy5rfnrzbZTqznCWi86xPyJ2umI9J4jNT9OpB6/UvedNU9A8Drt2anqSfv/WAL05pw9BLAAA2CfUK/jcDZra8aAGZ5yiorPbKc2brGzbollq+RBf6QAAAAAAAPE1Noit3L5lP+KGnF4K6vT66wSt/rATWroBqdv61U0+7cgLNM2kt1oFO21m2cXthLtaReDqLmDXd/fjzqtY1j0Yy13G5/M7VXY5dxlbGV3PmWPWMcv6TZ05ZvPT2Y6zGbuK+wMAAADYr53eLiNmCGtt3kYvHwAAAAAAYNfaT4PYaEBqg1En43RCzrKSNKclbMDvhrHRBWz4acPQaJ0bhrqi23E24kShFYGpO64IRd0uhivmucvbn+7+bJUd22kz5ZSdTNWptMuEzdhdKJAUdo41WJLqrFc1e7UrAgAAAPuz1jq7a5ZXri6oZav29L37AQAAAADAvm6/DWKdMNUMNsS0T0I4GNYFQ+aqe9sCFW3Lkt8XUZINZN0VDFsyy0cTT2+G3YydcMZOImpVrOV2C+yqXK5Yxj0GuwG7jWjZrfeO0xkHzLRfSYGIObawCrdmqkt2sS4+fK7CZWHnqKJ7r9g2AAAAsJ8a2FendfDK1YV36CtuDwsAAAAAAHax/TKILW+lalNPL/wMlYXVv0u+nr7yTV06dIFSQikqLkhXIORTUlJEfn/ILGcWdJJSO3Y2YH84nJKzLXe+MzbT0Za07uDWVVnGjJ3c1RRtyOuW7Tx3HVvrNxOBpJDMITjHlBxK15ghi/XMla/rsO7bnSDW3qLWW9zYT/N1AAAAwNFaD5yRoy7e1E5+2KyX87wyAAAAAADALrJfJnY25HRDUJeXfSpYElFWWlg3nTFfz10xURcPXqjmaT4V78hSsDBD4TKfecLKnJaytvti22LVaSFrw1Zn7IanthWrG6i6rV2d5bzBWazyMtFQ2FnebM28InbbAVMd8LldEQeL01WSn6WsFJ/GDFqoZ8dO1G1nzlXzjLBKS8LOi2hXdziF8ikAAABgv3Ps+Ufomi4Bb6q6iBYsXqaZ3hQAAAAAAMCusp+2iLWD88MJRu1gM1LbqjQUiqikOKycdiW6ZdTXeuFHE3TvWR/rmN7L1TLVLFuSpaKCdAULzUTQ7zyByUk2mA0rELDjkBukmmnbvbEULt+H/dDH77PzzbLeMoFA2Olu2G7Db+8BW+o3204x+0hTpDhLLZIjGt7rO919xsd64coJus0cU7cDClVSFHKOtfzjJWf7UVUmAAAAgL3EQL1/1wj96ehs5Xg19dNcl15+piadkq1Mr2YnBev1n/c2exMAAAAAAAC7zn4ZxFpOi1g72CzWZrKmzm+ejZAZB8xEsDSsksKQWqWHdNqg1Xroghl67aq39ciFEzX2mNk6vtc69cwuUcD8V2KD2fwsMzRTaUGWWS9dJcVpZkhVWWmKyoqTnCFYkuzVm8EsU1qQqWBBMwV32HXS5PclqXvLEh3Xa73GDp+rf1z4hl798dv6+4UzNHLIarXOCjnHFCyNOC1mQ+Y4/aZgG9U6mS8AAACwV/Mru30n3Tr2dH3755Eaf1Ffndclw5tXk+YafuxQffHnM/TM8JbxQ1jz1/68aV/rIbolBgAAAAAAu4GvtLS0ThFeyrUveaWGGRAu8Up7UCQif0Aqzk/VqMOW6q6z56qk0HY1bOdJhcEkNcsyBbNcyDwtZWZsG836nR/2Pq1mSPYC3JBPZcVhbTDbWrsjU5t2pCnPDJsLkrW5KFObi9O12YawoSTZhq5OWuoPKykpqNbJZWqdXqw26fnKzihVm6xSZTcvUvvmhWqfVazkNLOsbepqjyNohjJ7TM7/zmaSzLEk2eMw4/wdPqWa7dmHUGb2k5qZpN+/OUBvzumj9MxiBc1xOl0i7+FWsvP9tjkxAABA/Y295jw9fVi6N1XV7PfHacir3sRu0tSOZ98ySLMe76fB3pQrouLiIi1fu0NL1m7RqlKv2sho1Ur92zdTvzbpam7/Pq5FQe4ijbxnjj71pgEAAAAAAGpS+ugYr9Qw+28QO/BbN4gtDslvnoGk9IAemnik1ueHNfaYJepzwFb50/xSWcj+r1A44rQ6DdvbtppN2dazSWZbAds01fZpbJNQy860Q9h+EOQzu/Q+ELJ1pujeJzY6uLPK17HBa5kZzDq222E7327Wbt5n9pOUZCbMTiPFYS35oYWe/byXWqak6+ZzP1fYPA4bHKdl2CB2oN6c05sgFgAA7BMIYvcnsYLYxAhtXaWf3f+JnqQ1LAAAAAAAqKPGBrHR+HC/Yhu0Oj+8roltg1XbVXFeuEyTvu6rK/93ui4fd7L++VFvfb0qVWWhFKWm+pWS4VeaGdL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96h/oOl28ML80Aqf/iGkFZqzzdB6h4uj69evw9vZGyZIl4eXlhYceesi0OOP+uiP2fDL2KoWlV9tgBLvQz29X9iaM7RmOj5PkBpzIcDNbyBRqWdgTMxhBwUOkB8SfyDIWHqI85Fw/j2MJczGsTyBCZ+yxmtbQGx06KtMl4gh2b7f8ZbPdSNyp3IeTdwA7d8ur1gzbdwu/IqqHzl2tBmGz9mBGaCDCJsZhyzHzSTfycnD9xC7ETQxHz1EJDqddNKQuxuCgYAyZuwopJzSOdUsc1h1W3rKStSdG9bdZSiEly8u5jvPHEjB3WB8Ehs7AHo/O/5iGheF9MDIuRe44E+Tl3ML/pDUzw8XNiOoViD7Sw9tPmAt7keEmsk6kYNWyTTinvGUmpJEZoQgMm4i4Xeq/M6ePIcFBGBV/0SptqegUf84x4OSKt81p2tgYFz+5qexvn3DMT3X89PqUOb0Q2GeY8Du7cey8dXo5gZRVHyMsaCQSdNhxT26rMNIWhqPPyDikiIOw4htCnN2ySlyGk/EYK6QtY/wWTFtiHA9E16C3seKkzVRiISthFHqGy2nO+HNiPjuRNBev9zOGQxaSJvRG8MhY7FLnZ2GbJ3bFYWJ4OGJSndueJQP2HpAHYSGc+rTr7GLhXLMDWhuLsrQjSFFWtYn5TAjrIXORUCCPCHnz4zChbJkPe4djOLkCb0tlVIJlGjLFgfgbMTico7xvR87hGIT3EfJQwjHz4JAQLjfPH0OCsC9BI7Xzq3/fXvBXauKzy95A+IxkXHQlCgrNuXIwa88MhAaGYWLcLqG+M560ymlLKsOHBCNoVLydfdahPHSR/6C/o4UUtulYvWS/g9/PRvyKJPkO2Hp9EdZMetMhXcshsdwX4kROj5ZhfSJlFT4OE9oV81N1Dycjd+p7zxDKryghvMW0tEWdzwR262SB4SRWvB2EYKW8MLdHhDyadQK74iYiLDAUMXYyuzkvbCkYP1L52ROjPF3hSNxplxbO+bWRCOo6UAiDH6R2nWUUiGkkFiODB7hYjxQhIf7jx6rSjqosU6eBgV2D8PaKk07lMUPqfFOZbyxDxXR4PmUlxocaw8CA1MWvIijs4wL11CWp/OyPMTbTTArmGNugu4V9VrXNxL831nO26hZXuF/eF5GsBIwSyqaRscJ+mcJBLmPFeAvvOcp+GatD/neG6+cNdpxfi8igrhgotBd/0PjN88e2IHZkMAbE2KgbspKkfSpwPiEw3MyS6pZlm6z3SEy3qjLFOu0J7ZotcetwT6uDnMOIHRyErgOVPO3kPha3cwf9z5VzcDhGo20spZUEoR0RhJHuHlwRlKfucTW9erqMvXftYf0Vr2Mp8nNgd8thkb16yHiu+OpiONHdYv+3HNZpxaR8N1xE/KieCBfCVB0fcpta57akR8ss/frVPE7HtlL2prFCnvwYSdIAk0j4jWyrkNVxe672w3icHmWJibv1vafTqrC/sULZI51HiufSzvc1uNV32qw7ApRJ965uXIPt8qoN2di0OUUOh9IdEWQ9COvpPEIPrPtrIPbwLziurNZv2kL7KhGX3cHO6UJGuPskwmeuwba9e5GcuASR7UyX0AmykDDqZUTGHcU1Ic95VaiPoIhoLFq3DuvEZfk8jAtvi+rSjhmQsTISEVaFqHfHDmguhXoeDtgaYd2/HXtN8yHext7t+5V1S7t3ylMo4tF26Ky+asSQipiISKzMELfshQr1gxARvUjex3XLMW9cONpWL4Fr2yYj6odb8t9oMWzHpGELcFQ8WO/qCLA61ikR/dD8MR+UUL6uJjaIX46Mk//WqwLqB0UgepHyt6Z9kGPQkLESkRExdgdM9HRuyWQsOlkRnd5bgsTkvdi7bQ1m9n4CJZXPRWKH9Bv930fCOa0wFJZF0RgR3gUNqlpf7qKkkZUZQrwLf9c4BOPmLTcfd2QQ6lcQEkDeNWyb8ipm7tc4aL3iz0lZCWMwaNZeKU2L8dw2fBzmLTcfZ0RQfVS4m4Ev/7kAx+Q/sensyXPycdfvgvARqvSyaDJCGlcQPhHcSMbkcatUU4XWxaBY5XvrRuBvyrvV+sxR3pOXWKurg1zbljNU+zOnD4zjgpb7EwvNi5XOLcHkRSdRsdN7WJKYjL17t2HNzN54QpW4pM7bsClIktKWN6q3DVelkXVYFB2BoPry/udd24tZg8Y47hDKWIiIyTuARiHC9uXfWT5vHEIalpM/F8NhzAocXvwOxm26BFTphEjjNsU47lRFDq+8TMT9cya0kqV9GThxSlmt2AhNrW/Od1pDPPm4snr7BI7bmar3+PwIIZ+dRJkC+SMEjcU8JjBkfIlhY7Qb3nI8zMJerfJNSEPhbatLdYwhIw5D3llhv/GetRLvDInDyTKNETJuHpZLv7MI0RGdUEXeFSEKJmPcKo2UWHMQPpnYHnJMifXGSPTpOQQxW88IzVV7nsVE4/6q0unfRijvKcvEZ5UPrDhTDsrl+EqIRZFXBfWxiekrUkmneUJZNAWvztQa6HS9PKw7KNZ0DCPMhQLmKO9JS2zB2Sos+AYjVJ6fGJfjYxFvryA4vRzfHhALQS+0eKm/01eB61cOHcd8sdw/WcayvhTbFSGNISdpIX18OczOwI0b3KjvPeW0WH4lKOFtkZbEcnMEwrs0QKX/U76sJtSp88PDMGvvNSG1CmVugLo9sgiTje02QwbihryDFRrBa0iNQYSSFwq0aYxtvxJCOp4cBderZVfytPvt0sK4nnlS2o539eboFzHF3FYQthMZIJeZcj0yW5qtRXfPTjSFw5w+phDCCOPxSstEISRVlPifkiSmHXHf2yJcVZaZ2jliHhPKor2zBjnOYzd+wrhhX+L0wwF269I9SZMwbEEqbpRriJDJSj0l5emGSpl/A8mTx2imOaF0wUmxnSCmty7hGKFqgy6abK7nCtYtrtUN7pf3trlVnt/5DbMHRWHbrUdU5ZJlXZ93bRuiZ23X3icd8r8zXD9vcOB6Jk4q5XLzfhGYYlGHBih5Ow+Zcf/E7AKZ7jQWvzNO3ichHTUOUbXvxTbKiHB0aVAJ1sWmYbuYbuUyxbt6gMVxLJ83BRH9muMxn0LUBqp8a4p/63xrq7GiJSsJE/oNQexRMU418rSpzipj0aYRuVpn69ImsVIU58pZK9/BkDihbayuI9Vlk1TmjINWc9QpepSnOqcH19OrJ8tYHfoHioIrdWpxOxZPnAO7VQ6LhDAbM0iphwrmG/HcP0D4kRupC/DPBQ56W9ys03Qv311yBykzX8WUbbfwiGr/LeJNoy3pUjlcFG1AO/TsV9PkbPlZ2HJWz7bSnZ2Y/nES7j4ZjplrtmHv3mQkLomERbe6nttzqR/Gtf5Ht7ldlpi5W98XeVq1IF4I0w9DYuWyp8D2xOOfEoF+zR9DGauGm/t9p80Q1reevHp7OzZul1c1nV+JNVJ/EFD5hZfQUVpTeDqP0INNnJpYvfzvf//Lz8nJyb99+3b+zZs3869du5b/559/WnznXi2/zQnOb968ubQMW6v9ncIuR6ODlN9skd/imeD86EM3Nb8nLpfXDstvq2y/w+Cv8n+/qf293Avb86OCWyi/G5g/ZZ/688v5X70q/0bzoOj8o+q/U5ZdUV2kz4ODlePV/N6u/Kgu8u8ETtln8Zn6mIKn/5x/XfWZabl5On/lsA7K98QlKD/6qOV3Ln/1qvJZl/z3t9sKl5tCOrF67/La/GFtld/tMDj/q99t/e2F/O1RwfktlH2wPo7c3KP50UHK79gIK/MibFP5naDoowU/F+JOPhYhnlt0ENLPhYLfMS43D+VPN263Ref84StP59/U+p7Gcvn74fkdpO10yB/81e/af3d9e/77gcrv952Xn271uV7x59RiEVfD8lee1o6r6z9Pzw9uYdyWsAxbq/m976cOz1/+63XNz8T4/upVY754Of+zTK3vOIhH1eL+tpxYjkbnBzncH/M+t2jRIr+DEDYXNL8nLqo03SI4P2q7rXR4M//3rwYraUn43cHL8i8X+I55u+KivV11OIhpX/it4Oj8QwXKrpv5iWOM6alt/phE688dLap9cZhX7S/fDzfub8E0bVFeC2FtO38cyo82lcEdhOOxTtdH8+con7cIjsrffkH9mXG5mX968atK+dQ2/92N1r9hGf7a4Zqbf/PQdFMa0srvxuXC9in5fZ4x/564PPP80Px5SU6UP6p0arduLEw5ePn7/OEd5N+0Xd9dz9/+fqDym33z56Vbfq5HeSgua4cpnztIW+b0MSx/rfH9fVPyA6X3muf3nZde4G/k5Wb+xnfbyn/b9t38jcZjNYWX7XB1rxxSlwdinATnT/9Z+7duHoo2l8EdxuQnasaHg8V0PDrW904s5nhxXE/Zjmtzm6f5K4ttl7FCu9U6nR0V2o5SPrZT5t48vTj/VSV827670eo3LMttm3F0emX+MCXPaB9DIRYn87Q+7VLnl6NfjM+Ptlkm3RTar8byQKseUZWZNtoQpsWJ49fM7xqLRZsqarvNtHPz96/yBxvjr8Xg/GWXrb+jSgfCYqsuNYeBXOeKbau1GnVM+mcvm9q/L3+WWeDz3Nzv86cOX57/63Xr95XlwlemNNv85c/yM7W+42zdoEN57+ziXHluGdY226cXVua/aWzDthDCWWO/3c//TixunDfYK5el5egX+eOjk/JP28jbN3dFmeq4tmMSLT8XPuuifPbKYtv1vXi+b36tOk/t8n7+dltlikZZ6/BYhMUU/3byrf28fSF/5ZtKfd38mfw+0TbagTYWPc4dCp2Gtco73c6VhUXVVpHKuehDGunvZv6h6cZwtdcesr/oV57KizPpwf7iRnr1YBmrb/+AVlg5SG+q+tfW+ayzdapebXv7i/PHIy5Ffg7sTjksLJeXDTbl4Q7DVtr4Hcu8Li5aacq9Os2d/OLE4qAOMKcxcbF1Hqou47XOv+XFuXJY/zLL7qJnv5pO9am4OFXv6nqu1CL/GRv9IsbF/e1ZlgHu9cM4Lh+dXoqyTScuetX3OvcBO1ourHzTdL76TJ/o/J9t1bsFFnW6sp1WxGO223ea+Vn+y8pn9tr56fP6ytvSOM/xdB7hUrwXcYxUHCsVz6HEsVNxDFUcS9X6rtaiXCNyfzDcKcopHPLwf52GYWhD6TIUDYew4JNkedrCct0w6ZNQqB7/ZMmvNcZPDcOj0ovLWL88SboCS+aLzu2UyeLP7kVygTu+DiFx+1Xh/8poNaCT/Bta30tLxl7xa6iIjoGqORQNCViwVJ6/2avZSMSObKr9TBnvqgie8QEC5ZuFNJ27cElZKwM/P1sH6w1vq48OLfgEyXJAodukTxBqO6DQevxUhMkBhcvrlyOpiC+aFOM5r84AvBtk+3KT7Pi5WCEFoReajfwG0cHOPg9LSCOzt+GGsFau2yR8Elpb++98WuOfbyhTVKdvRHyG9K5Mx/hzRtrihUpcVUbvmTMQbONZLj5NR2LO68qVRHZ0GxVt51kEfujbp61yhdZx/OLmnDee3Jaz8vLqYMC7QcLWtWWv+jfk6PWC/5tzML61rW96o3boTIxqL0dw3oFvsfy0tKrNqwWGTdbarhAOYQFQfkXYv0cRNnU4ChZz3ujY5zmhNBHdxtGDxmmGPa9OLeMV2fbkAU3s5Y+GGD7ndcgp9gZ+XL1ZVQbL8bAkU/gNL3+8OWc8tKPBG1VfeRt9K4vrt5G0Pkl6V1s9vD5HK1zFXXkDA4xFdLpQltu4KtGv9RisSFyK94x3lQkM53YJx/giuvQai9XHHU9x4jzH5eChBbOxTS7M7NR3Pmj9zzdM0/9utCjMdCgP9dAsDMaLINNXL7W4stokOx4rkuRpKB7tNwgFHgVih27lkJSkYzGyqfZveTccbi6Db/yI1Zv1rSxdre895wIuSW0eQUU/m2WsuIMWu5i9Cv9ekikEr/0y17vqK3hbzuy4nbQe6txuSFhgKreb2YujqsGY8UGgUt56gl7tUuf5/z0Kw20+A80bLUOeV7ZxG8eO6J2ZXSDGv7FN5f8m5oxvbTPteNcOxcxR7eX4yzuAb+1WupXR9wPturTlwL5K3SPWuaXRftRkaBW1NUN6oomynnb4gLKm1g2jou08596vL/q0lUsXHP/FrWkE3S/vi1JpBH5go33qF4zXusstF+T9ghTrQNAh/zvD9fMGJ/j/HVHD28PWoxa9W4bgeeU86vaxI7CIFaFcNxebNktN6RlHZufEP5OVEcpaWwdiXdZ6yqFYLNgj19eVe8cgbriNdqANxeXcocjOleu9jjnDG2rEjTcavjEA5uZociFnCxIUWXnqDnfSq6fK2GLSHtZFMTwWT5wDu1MOIw2Lv1JmsRPr2BnBNn7HMq9rcrtOKz7le+nADzBD8zzUD8GvdTfFx/5dbhTEHi6z9O5X8xi920p5/4dOw4Zq9otIdG+bud8P4zFulSVW3KjvPZtWDyF2wR75fLVyb8TEDYeNU+kCdOs7rRaCPvIJDG7v3IQdmu2o0/ghMV1a82rxEvqrp0fzdB6hB57SuiTxRL9jUIDtRkfaVuwUn/AsqDfgH+joKNP4DzIV+rd3JkI9CXG15wOVB8inYedWq2LRuJ2KHRHYrz1aSa2Qgt87n7wXUplUuhU6qp43bdi8Gbukll5pBIT1tdnYkHgHIKijXFhpqVu/rpJAzuKndYcdTJNplIat5oDCPxwHFAaZAwqJNmZr1pN/9552pp08j5VrlMZy5b54O9RuCFoypZGKeK5PR7sNWN8mjZSpjDLxe6q0ItEz/hxLw4af5Map+EzEgS3tx1XNnt2VdOs6byFNycedh7tF/GgMT27LxL87etpMXAZs32F85kAAXg93NPmpL4LCjSci6di62c48vc8E2Xxmtvffmpvjzb8XXrYViS2b4yll9WyGcRJ4z7tw0ZnpgJzIHzX7o49StOT9kqLqQFHFQ5OeCLEbDc3QuIG8lnf8mJBjbGjWx7KxZsEXTzcxnlVfwgV7D4fzqY++09dhy/ezEaFMjSwynEuSnvPx6mLXpxS1Zr8cNJfjFZ/rY7++822CRsrYeaa6MNOhPNRHTbz2pjI4dnk9lmv0YJ5e/i3kWYlb4O+D3C3lLDldDgllQlhf+/VNzf59lJOqPPxSYMTBPa7V955UH3WN2ejAD1jt5EMqDdt3IEXO7OhpP7OjmTmz45gpsxuwefMuU7ntKI68A4LgVrVcGDq2S3XjL8STsnrnjl6llevM8S/UGa+HO5xy3DcoHN2Vcb30rZuFFqEN1bqhpxKWBdRsgabKb4jPF+obZKNy9n0apqpBqHMLf/mTN+rXVQrfvLtwvZmjQ3lflCp2R4idq2Na/q2pUnZdxaUL0oqJ+/nfGW6cN+jCX0gHyuqdO5ZtBOEDc7G52sln+9YV/kzpHjj7E9YdLl61wfZv10NKrUJ9/cY7Le22LVzhmXOHojtXbtbHzqMV1GWOkFnsNUe1FFl56paiTK86lbHFpj2sg+J4LMXiHNhOOZzxI7YZu1scttX88XIv2+ch7tdpxaV8r4juIXb6XVXxcdW6Yi8Ez5ZZnu9X04vubSWtZ2uq6L49vfphigU7ZYkV1+t7D6fV7d9ivdxwQ4s33oGDzano2Xfqi+Bg5UI7oR21SWsk9tBSrJbGYYXyIjRY+AszT+cRevApNfH9obyv8swAgf4dPI/h8SeUVQ2GY7/LA59Ck7J1B0eFgEhV6Fs/67Bae7RSPjqy2/KZRqe37pS2U7FLd7QU/nVsJffoWX4vWziBk3N16XaBaCOtyY7/9odcWKEp2nZwnLkfqWq7w8C7aziC5Qs6cPbbIejWbyy+3pcJu8+QNhzD70q5Xq11B4cNHpHv001Md1CcsPdQSF2URp36ykmVpgM4rBSYFTsGmq4kcoY5jVzF2qGt0KqVnSU8TvkucOqE+VonPePPocLGVbVHUEVZdSgnC+eObsPatUsR8+FojB7yMrp3fw6dBpqPWzee3JYDpevUV046tRzHb3/IsYumbeFE9FqciJz643dlraBq9Z6wfTLj66s8i05Q5RE7++cOIW0YO55v3Sj8VfYq2TflOx3EMrmOzcdy+KP53xwFoC+aGnuMrwoNb3lNoIqHQ7MQqJU/VUtUsvxVnM/ECWXVWrVGTS0aa9b8TS1q53hXbY+IufKAbLjxmWW4gdQFgzDAjec7mjkoB1Vlw9W1QzXDxbyEI85cmJmu3NSjPNSLd0B/vCDVZbeRtCLeMn0a9mOJ3OoW2vihNjtzHHK3HPJvDsdJuqlpEMSdjgktLtX3HuWPvw9oppxA7cHHfXpiyIwNOJplvxPJXKcewqxAjbSnXsyZHZmmzF7YcvsRuFMtF4au7dLCMmTjUvo+bFq7FrHThfQ+fCCCu3dHQPsoGEOxOChsm0qodNHcXOnCZq1b+3HUV1YLEurcMsqqX1UhRbgvJ+scjm5bi7VLY/Dh6NEY8nJ3dH+uEwaaCl836FDeF6knGwuxZ0edWjbbNe7nf2e4ft5QOAZkX0rHvk1COoidjtGjh2NgsJAOAtqb2ynW/P+OAc3kFsTtPR9Lz5+fseEo7Beb3ugaHgy5OjiLb4d0Q7+xX2NfZrYObQ93peHgUaWN2CQA3Vytr0X38tyhyM6Vq6FRU7utUXMHrwuKrDx1iz7ptSjL2OLUHnZXcTwWz54Du1AOp/6OTGmlIpq2cJzbqz1iu7fF/TqtuJTvT6Kx3YpddfGlGzxaZhVlv1oR072t9NjjsNOtrvv29O6H8QwXyhILbtT3Hk6raQePynfDogkCCtVw07fv1LtrMAKkoZXbSIq3nC1PdGhjknyhX+l26Ga1MU/nEXrw3VcDsdXq14HxRoPfjuo9X1AVPGKndZZx4pSy9ggedeaMSWAu9G8g+7qyKvFHj2fl1kXegZ2quxLOY/NWsUO4NFopt7m2aSdP62L5vRQckU76vdCiYweLxmdGpnJyVrqC7elGnOXdEqP/+xGCpKdO5yHnVBLmDgtBYJceGBi1Gse0emgzTsAUUs4HlOkOihuWAVUE/FDVXq9Y2nFTx1LV6jWUNeeY00jhqC8q0DX+HFHFVfmK+vQcGy4mI2ZID7Tv1B29Bo/C1KlzEPfDVmxNOYGsrOvIUepSPXhyW87ys5u4MmCM3opC2nIues0nIrdv2h7e9CpRQlm7V2qgelVl9WoGjrs8EpsqNLiU1YrVUcNmIJUTz60dKlFCq4ozx0Oh2LkavqjCXxyQHb4oAfEfdUMV6VDykBk3DgtsXV3nNAfloKpsKBTVlZt6lIf6aYYwZX5i66lqsuNjES+1uivjhf52rs62QbdyqJyv3ZNIWQloJmk9uFLfe5hf6CdYGNEYFcQwMFxBysqJGNy9Czr1i0Ts1jOad/Ga6tRCUd8JZS4vSlfwK3T6KEr6tkudlHMcq8f2Q6eOgUJ+GYYJU6cidpWQ3ncfw/msLNy898nEgin+7dYnluqbK13bFxWVLOmBtGDAxeQYDOnRHp2698LgUVMxdU4cfti6FSknspB1PUfpFHCTDuV9kXIjrN3P/05w47zBOTk4vnos+nXqiMAX+mPYBCEdxK7C1q27cey8kA7sZjo/hH6yEBHKBV2GKylYOXEwunfphH6Rsdh6RntE1rvlaPz3oyDI1UEOTiXNxbCQQHTpMRBRq4/dwwt0hLBWOg9LP/KoE3VmQcXi3KHIzpW9hHavsloEiqw8dZPr6dUzZWzxag+7pzgei2fOgV0vh9OOm2oIuFtF6FGnFY/yvSRKulqxF4JHy6wi6FfzFN3bSg4uetB7e/e+H6ww3GnTqblR33s4rR43N9zwaKEabjr3nXoHIES55T1vVzziLT7ej/U/Sh1CqCzEi/XNqp7OI/TgK6ouvaLRvAmMt8Vf3ZsMt/uiXeKD0oV5GI0N/u1bybfN396L7fult4DzPyBRPKjSHdG9o/yWd8cOaC7Gkvp7+7djr3hZiVdzdLA1v0mFynhYWXWHd9WuiFqXiDUzI9D2MR85wRiu4FjCxxjYNQiDY21PYeijR0DdQ36VlduDCq0BXv9qHdatc26JHaRxuZJO8ecs14/VzJAagwHBIxGXckU4tfWCT/k6aN75eYSPGI/xU+ZhuXCsGz8PN02T5g5Pbqso+JQ23i7zoKiGpo2Mt8QeQdImF7tbTu/AHqWd49X0b1DNul4kfJ+bopkntZeJeFb5O8/yRtWuUxA3UrkbEGexasl2ac0TGrz+lUZY2FhiB5k6Cs10KA91ULP/S6ZnGy771DjDxGks//aA3NFWry/CCnkr0/1eDllzp773DB80jViEhM1L8F5QA1SSmj/ioPEuxI7ug8BeUdhsa+5N3+cwxSqt2VsmamT2CpU9WSsXhj7tUoeyEjAyKAwfJ52SBiu8y1ZDgzad0S9CSO/jo7FICLf1iRPQXvl6seJTGvdXrWtAaswABI+MQ8oVIU17+aB8nebo/Hw4RowfjynzlgvpdCM+D9e3dHG/vC+mdMj/ztCjLW0pCwkjgxD2cRJOyZkO1Rq0Qed+EUKeG4/oRcL+rk/EBHuZzqcpIhYlYPOS9xDUoJLckSV2vu+Kxeg+gegVtVljymKx3RGFdYlrMDOiLR7zkVsfhivHkPDxQHQNGozYezxlsSvlcXGss+/Lc+ViV566kl7vRRlbPNrD+niQjsURHcphif2bPgrFrTqt+JfvuvNwmaV/W8BDPNRWMvH09u45vcoS/Xg0rbrRv61X32nLF56TZwTIS8FmVX+lIWklNl4V1+qhr70Oob9cmqWiIte89wvfzmhnHIk9uxZLttvocCsC5mmRT+IPJx8dYb4CTmh4VVdWjVp2Rxdp3OIq9ibLQ8rZW3dKg8sW0w37dkNAE3HlKg7skX8vLXmv8EqgMS1TSePtMuczTVdo23P3rtQF7YAPanSOwNxV27Bl4yJMDlHuSMm7hqOxQ/DGYtXtReXNU8CcdD6gTPtaxSKgqsPO7CxFw5X9V5jTyFXcyquO6tWdW6r4mgfTiyb+bPAuiZLKqlNTBhnu2Hk+zml8OSkOmeLulGuByKVbsO3Hb7Bw5iQMD+uN3t2eQT3hWP106W/w5Lb05Iuyyi3959N/VwaCHDFf/V+xih4THBYdU8MGeTjw7XIhlgrv0NLVUCaJRcALAdKaO8xX4JVV3Tlhjofs7Bw8rMqL9hc/oSS8d/z69sQzyvrtoweL9kIkVTl49VaeRljYWKr4yp28Aj3KQ135BiNCmXv3xo9fy1dBqp4F0n6gneesaLoX5ZDqbqCyrtwL5IxC1PdOqq5zRe7t2wB9o5Zgw5ZErJwXiQDpsn6hijqXgPf7T4K6aehrzuzIeVg7zWkt5ngraboL+XymU7Uy3KmWC0P3dqldBiTNmI7kG8KqVy30nv09tiTFY0nMTIyNENJ7705oLIRbFV9jq0KLagp7DzHF//l0/O7kKYOp3qgohJG85nmnv8SkuEzpIpFyLSKxdMs2/PjNQsycNBxhvXuj2zP1hHSqU52kQ3lfXLmf/53gxnmDI4akGZguZzrU6j0b329JQvySGMwcGyHkud7o1FjYXyEe7OU6mTd8G/RF1JIN2JK4EvMiA+S7oYR8fS7hffSfZPmYHBOfGugcMRertm3BxkWTEaLcWZt37Shih7wBF6oDN7nSjjYqRucOup4re06xL08Lk149WMYWu/awGx6kY3GWfuVwBo67efKma51W7Mp3/Xm0zNK1X82zPNJWUvH09ooL/coSN3k4rbqSD2VF0HfaLAzyJGl5SNm8Sbnr3YAdm3ZK0yd7tXhJ83nDf9U0S0VH6V66X1RDSFh7ZXriG9g06z9ILdxZmMuqNW2kPPj5PPbscKZlko2DR4ylQF3UL9Bnan7+69m9ycKvZmNT0hHhlfV0w77orIw+Zx7cK3zrPJL3yr/r366zanBB9kQ9Y8nxC1KMd9DalI3DvxbuNnsfv8boMWYREuInoL3UFs9D2rIlMG2qWlMYb4w7v2eHU4Mx2QePKM8QqYi6FgHlC1N7P+ui6hmPGlJ/g3FGU7dUq486xgLfyf03Mk+dfR77d7syfUHRx5+FusKxKiXA2SMHhV9z4PBR/KasFpARj43yCBrqDZiAV+rbqHUuXESWsuoyT25LV83RxHghyeFd0HpGfAH7U4SUIKv9uFuPyS96QsPmZX8lQaV/gUkrChn6pxdj5mp5ShBUfgH97T7A3pmT2f1IMQaefxMh9I2ewOOPKauH96qmfC/mVI3mIqcuB/fvFkq0wtOjPNSXN1oO7Au57X0AGxKysf3b9fKzQIT09lpQIQc29S6HMo47HlxXlQf+Tcwpuqg4rO+d5GuuyHHRfkVunprcGd6+qPXMK5i+LhGfD6glN2hvbMKS1eba7AlzZsdelzL7EzBXyymOjz37MNyplgtD/3apPUlYnyQ/4ad0wDCMbl9VexDu/AVcUlYL8jU/O/XSBbvlivk5dO5pbq50scu5Stdcb9R+3DQLj6dlxG9ULkqqhwETXoHt4kWHVo4O5X1x5X7+d4Ib5w2OJK1Pkp+rVToAw0a3R1XtTIcLtjNdAd6+tfDMK9OxLvFzDKglt9lubFoCVbGpwQd+jXtgjPiohAnt5UHEvDQsW1LY2sBd6vabk+1oo+J07qDrubLn3D/lqeP06skytvi1h133IB2Ls9wth/0b1Fc6XM/iyEGHvS1CU9+YaQoqmjqtuJTv+vNomaVnv5qHeaStpOLp7RUXRdGmc4mH06o6vp3Lh0ZF0XdaE88HGh9XtQEJ4sEbNiNeOsf1QvOu3QqMr4j+qmmWio6SBe8fvkHv4jVjZ//ZZRj2zgqcLEx+dlXLjlDGTZG+egn2O9pm2mIsOySvVn7uBc0pNtsEtpMbs2k7sTVrO3ak5Akx0hZdu1qWytXat5KnSTqyG9uztmKn1FtbD527FpzfpK7wXfmen6vYuDLJ7pUjhtTPTftYWN5VgxH+nHIWefWSapDUPMAsBBSWOA4oLDYHFF6wCqhHjLdP3N6PXTb31YD9azYJ1ZYe2iCwXWH2X6VNIIx/mvbNIsdpRIOn4k/WFm2lea8Fh9ZYPDexoCzEf7lR2CsbVFdKVa9h674yA5IStssNEHd4clu6Ml9UgdtJWLra0cl9NhLilDD3aoEehR0o8riaCH8/VJnSLQ+HZkdg6h4nOzCykjDhzc+QJt1JVg6dRg6F/Vliz+KHlfvt5o+s+C+VKUasL1qphq6d5QYYbv+IJYUdML5XTp/BOWXVS2hAF+0kX6pyMO0bLHKlMNOhPNRdzf54SZ6fWCjyRuDL7XIJUa9vmIP0pkHvcujsD1hpN5DUZbA/2nX2XHlgu7530iNVlAHD29hvuyKHYf8abHKpIvdB0zdegjR5iODSBWNOEXJ7187y4Luw7R+XrHChg70u2reSa2Vc3YiVSXZrZaR+vgxuVcuFUQTtUtvumO709bPznJ7T3220c0GBapaT43uQbPPMPwurv9unrLvHt3M7pSPtNpKWrnYY/9kJcUq94YUWPYI0T8Y9wXDHVLrAdvGShASlDHOPDuV9MeV+/neGG+cNDtwxZzrbz7c7/R02unKXlU9TvPGSqdSEqti0wxtVg8Nhrg4KXRu4Sd1+c6YdrVKszh30PVf2lPuvPLWdXj1axhbH9rCrHqRjcZLb5XDbZ0zt00NrHMwYlRWPL40nrxqKtk671+W7/jxbZunYr+ZhnmkrmXl6e8VFkbbpCsWzaVUd387kQ7Oi6Ts1P67qEH5MyEZ2fDx2iVFTOgChwdp/81dNs1R0lBx4P6mJQZ9MVO7OAG4cmIXQ3qOw+rj9ZxkYso9h9dhILHS5YOuIf7zmLwfY5bUYbW8AOGsPpo5fKl+5Wro1hkZod/F6d+ioFAJHsO/jn6QCwKt5BxR47Kt/e7QSG0V5B7Bz7j7h24JH26Gz1omD6XZ7oZhI/BfGxF/UHqzISsKkUSvs3nGQtnAsZiTb+HuhoDuReV1etZj2Uwipf7wGeaz8MtaOfgcrbAcU9kwdj6VyQKH10IgCneFN27ZUrry8jPWfx2sWejmH/4Np8cqddG7zRsAw9f6/gcW2brs2XET8/KXmKYS9OyCku9JhK6aRMfEaz10yEh/UPgrRm5SXRjrGn2O+CA4NUMI3HV+MmA3tR4IYkLp4BObssXMyqrpb78B27QHkrIQx+Fei8ye0Nq/QKoJteUq18DfRTb7U1MFApQEnV4xGdLJ8DI+GRsJGu6BY8W74NqaF15LLybxMrI18GYNjku3kAwMuJsfg1X5jsemS2ALyQq3weZhmPee6hsvxEzEpSTv8DCdXYNycPUJTSVCuG94Mt7xopWZIHzSTd1KKh9l2noVjuJiMmKivimgq4DQsjByLr/edsf/szZzDmD3iC9O0zW27drQ5EPKL41vpneCNDiHdlYtCxHJwDOJtRyJyjq/GKOvCTI/y0NrZI3DiYnI7VGVe+hEcEROI0FB/SWsOGkd0L4cuI37iJGgnabE8GGcqg8t1exNWSdptrtb3TmnaFi2VjrvL6z9HvHZFjv9MixdCwZZN+Ojtr2GzqZd+0tS5Vc63vLImqBmCPnJmR96h2YiYbec5t0KdnhwTha+sMnuzMOVOaqFESfyX7byQlTQJo1a4VytrsZ2n9W+X2maeovnszq2aHYni8xdHfKHccqbJF+1bKQ0coT371eepGulNqBPiJ+OzQ0pnhVPszCBSLRxvypWuHP9T99g8eRbrjdHRyXK98WgoIu9hpetd0lS6YLvm4H8WEsb8C4Vp5thORzqU965wuzx3gg753zE3zhscMD2u5OxObNXOdIgxtQ00bPoIb3993OYxp580lZowF5tCu2TsDCTbSgPZJ2CuDjyfR2q+NkzVjg7HBBvtQLFdcThmIRKVV0Vy7uBGGtbzXNljimV56lp69WgZWxTt4SJlp069747FfW6Xw75B6NNeaQSnf4ERtuoh4XcWj5gDe90t7tdpxbt8d4m9ctijZZaO/Wqe5pG2koqnt1cITt0h6iK3yxLdeDit1nwNw1T5MHxCks18mHM4BgtNDbci6jv17YauykD0oR/jkbAjRfh1cYK0/rA5IV8xTrN0f1JKg/uMXxBmLH4XLeT8jLxL2/BxWBd0emEghk+Pxdq1a5VlKWI+HI6BL3RCx8CB+DjppO0M44Sagz7BRGUEWBoADgpDVOw2HD13DufEJX0f1sREoteL72Ct/BAatB87GcF+0p8U5N0RbaRL5PJwYN8BqQBoEqB1O7zxytnbwsnCPrmgaNfZxnQZNfHah+GQZ5u6geQpfRASGYMNR5V9PHcUG6R9HItNl5ug9wvy/Wuacn7DypHBCAqLQuymfUg3HufRbYgdG45/HxD3xAu1Qgeio/wXspqD8MlEZWqTGwcwKzQIYVGx2Gbah3TsWxODyF4v4p21yvNZ2o/FZI2A8u4QAmN7//aeKej36gys2Zcu/44Y3jMGo+eQZbjStj2ekr/mPov9T8WCQYHoJ4ShabtCGG6LjUJYUDCmbPpTdTLvjZajxyNIeqCe8KfJU9Cn5xDMWKMKOymNjMHAHoEI+3gbzhgvyDXRMf6c4B0wBmOVNJ2XuQxDegpp+mvz/qbv+xpRYUEYtCAV/9e7N1pL39RQ9zl0UnblduI49B71NfalK/sspZdeeDEqGeVbt4b98YMWaGpM2Ic+w9sxW+V9Oboa89cqXVe6beseEPL8h/OU+BUHKt95Eb0s0tY5HN0WK4V56KwDQgoQclitcEx7u6HNgbfixRsNh8dhYXhdeX/F50rGjURw4AsYOHw6Yi3K5iF4OaALXhwZh1TxQIWypEq3aYgd7syxPopaNS9j01gh/MaqyhalTAgKnYUD0m8KZfCodwte3OIXig+HKdsR4mHZkG7op/4dJR6mD+mHwOCRiEux1ehzX87JJMwd1ged2gcgeOBwfBizVFWHCfswfCB6BL6BZVKdIpeVE62v8PN/Go2Vc/yr8RMxavVR6RjSt8bgq13y+4Xl3XI0xgfJzwsSCjNM6dMTQ2asMec1pRwfM7AHAsM+xrYChZke5aGshblQwGdvx2CrtA9HsXr+Wqc7tI28A/rjBaVOEZUOCHXtIge9y6FHa6Hm5U0Y+2IvjFW1K9L3rcGMwebyQEgAGPWu7YF4l7la3ztD3XF3ew+m9HtVlQ7EdDQDg4W0sexKW7S3WZHfwZ975yIssBcihTxi2Z4Q/n7UankQt1wnDAxRh7gfQj8choZyZkfmsiHo1m8sYrfJecR0jNOHoF9gMEbGpRQ8ORROID80XmAi5YUQYR82mNt+RzcgJlKI77GbcLlJb7hZLcuczNO6t0ttaotn2yo7lB6LgUJbzNQuMZa7g+Jw6ZnWdtti5otggLPLBgn5RlXuSmlNONGdsguV2jvON/5PN1Y6Ea4ifuIorJZ+Jx1bY76COYi80fHDeQiXK11krn0HL/aKRIy6HBK3GxVmrje8aiF82ttKmrk36j7XSZld4jYSx/XGKFW7TKybxgrt56jk8mjd2kEoOZmO3C/vnadnee6YDvnfGS6fN9jX9tm2po6y2IFCubnBuN9KuRc0CHGXnkFrW5nuzp/YOzcMgWKaX2pVLgh5dpTyOIhynQZCXWzm/LYSI4Plc7dNVu3TseH/hlwd1ELowELXBu6zaEdfktqBPQYK9ZYpTuW0GtkrEG/EpeJ/8l/pWmfrkoZ1PFf2nOJZnrqSXj1bxurXHi5Kztap98Ox6Mntchi+CJo41vSID7Ee6im0tb82pVXhd74W64dBWJAKdOtms7dF4H6dVqzL90Jwrhz2bJmlW7+ax3morWTi6e054kT/ow7cL0v049m0apkPL20aixd7DLQ4XxX7O8Rz6cA34pBqargJiqTvVDUQfeRbLPtDLPTqoW+YvcvciluapfvdQ7m5ufnKuiQ/P9+05OXl4c6dOzAYDChfXnWHQXGRcxyrP3wXs5LOOXVS6+XTHMO/WYgwVZs6LaY3wuPEy0zbI2rvbATJb9tmOIn4cW9h6rZLQha0w7suQv79Kca0tn/ClL0iAoGzjBPZNcO7ibEI1egUNiSNw3NjE+WrtFARvRdswng7UxNlJU1A+LhNkG4y0yLsX/iC/6LHlv7K8T8q/L8Ww42VkMAcNrbIAydxUwKEosmaASfjx+Gtqdts74PEG3VD/o1Px7TW+A2ZIXU+wt/4Ehk2ItmrVm/MjW2O5d2jkCy8fjQ8DmvVByJKGIlWwgm21nFqc3L/a72GFSvfspwmNCsJUa9NQMI5B6lSiIM3Fq/AEI190SP+nCZegfnGMKHxL3Xza/BChU7j8fW0kpjWXg5jCP/vnW2ZW8S7YQYMioMyXlRAufYTsHzICQx5NU66K6d91F5Y/YQke9Mo9JqwTR50UFHHq17bcigtBr2F7UohrJWuJAkY2cpO2tOQtScGI8YZByBtEcK91Uh8PjsUtTVbEs5u1/w9rXgzc/Z7zhDvdF2A96KW4ug1uwWAxMvnMXQe9W9MCa5tp9FkVV5v7IqfXp6MbbZ+36sCOo3/GtOCbTzLUNjH1MVvYvhnR2F/F4V4CJiM1dOtL5IpRLzbLH/SENM7HHaLWRNvVA+KQuz7XTWfKZI2PwQDv5Q769Qs0n6hy8EsJEW9hgkJjupYoRx/YzFWaBdmbpeHQqGAUb0mYFvBQgFxa4ebLkpytj7PXvUPdJ0uXvzkIBxM4WUVjgr3yyFV/At5bmPXn/Dy5G0206NXhU4Y//U0BGs/VMYxO/HvXn3vBKGemR/+Br60XZGj99xYNF/eHfIuWsatOr/ZVK4hhs77HIM0ek8MqYvx5vDPHJZHXhUCMHn1dBS8KV/ICxPCMW6T7bafd91wLPhvD2zpr8RpgWMoHKfytEjndqlNWUIc9BPiwEa95VVrABbGPYnFneyXi1kJo+ym83It3sXiyAuIdFh/p2F+yEB8WSADauT/rD2IGTEOcfYrXSH+W2Hk57MRqlnpWuZX23Wk6nt204C97wn1U8wADIorGP+ycmg/YTmGnBiCV+UdslnmOZ2O9CjvneFUee5sWAtU7TRbacX9/O8MF88b7NbLWcLH/YQy0Wamw4CFcXhycSftclNVh9lSruFQzPt8kKrTWRX2tnhVQbdpcZgSYFWWONHGSBjZSt5Xe2nWibrcqXa0VydM2R2NbspL3c4ddEvDOp0rOxHuRqbwt1s2OaBLeSpzJj3Y52p6vQdlrJvtYfv5wlF6c+acpTB1qg5te7v0OB6Rqu1oty6x9z03y2GFWA+9MWyB7TLLeN5acpqwC+IP2e7vc71Oc6N8d4aDssjZ8zTH8S9w8txQomOZ5ZBO/WrOlOvOlp/Ofs+9tpITcWbFve05WwYInAhLZ/ofnWJ3WzqUJXrW93qlVWc5lQ+90GnKbkQbG24KffpO1bZjQud3scl4s2+zd5EYG6pxQ5wlT+cRKr6uX78Ob29vlCxZEl5eXnjooYdMizPky9nuVz710Xf6OiSumYdx4V3QoJofyqoznZcPyvtVQ4M2/RA5bw22bLMchHWJd20ER6/HlqWTEd6lAaqV9zEHondZ+NVpjn6R87AmcYVTnV3mZxcI/NvB1mPfzNMYC0q3QkcHz4fxC5iCtfELERkk7KMpULzgU14Ij6D3sFTYv+FNfZT3tfkPmYd5kf3QvI46XJXf6BKOyUs2Y63NTllv1A6OxvotSzFZipvy8DEHFMr61UHzfpGYtyYRK+wMwoq8G76FuDVax1IHbSNmI37ZeLjar2ibvP9rNy9R9r+s8I5CTFfVGqBL+GQsjbMahBX5BSBqXSKWTg5HW4uwE361rB+qNeiC8HEL8f0W2ycmesSf07wbYtB/E5T9VcWTlJ7bImJ2PBKig208UN7Mu+FwLIufjYi2dVDe/CMoK4RV0HtLkTBb+I0Sytt2+HabhuWzI4R9MYe5d9k6aNTAfDGIXtu6V/xaD8d/N36PhQ7yV8J/nGlIFEfeqNp+OBZt3oKl0RHo17wO/NRlpXScfqjTvB8iopdgc+IqTHcwCFuAXxCiv4sT8mdb1CmQRyKxMD4B0TYHYUXeaDhoERKM+Uy9f1LdIZZREYheugWbCwzC6qUuBsWI9dfzaNOgGvz81OWkuBvl4SeVNeOksnJdlPYgrMj/rTjEvReEBlWMxyGERZUGaODW3Xl+CIgS6lixvhPymp9lYWbat4Xfb7HdKa9DeShOITNtuZzfTX8vbL9OowZw5RIx3+BQBJQWQqjF3zHI1jadoHc55BcUje/i5LA2J2m5vgmKXIj4hGjXB2EdcK++d4JQz7wVt0Yo84Q0qqpPxTRep20EZscvw3i7FXlXYR8ctLsS/qs5CCvybjgIixLile2r85m6LFqKLZttDcIIeWHKWsQvjESQkFcLxI8Q34krhkOvalnkdJ7WuV1qk1Dmzk5YivdstsVGOnX86nSumW8+Feo9p/KNv5Cm4qT9qWL8HSE+qjRogALFnl9rDP/vRnwvxJ9UH5kTuZQGpXJoslAXJfzHvQ443YizSyxDvNQWsmyXVWsQhPeWJmC2UL85E0zO1w06lPfO0Lk8d4b7+d8Zbpw32OSHoNlC+1yMPxvl5kh7ma7rZCwR6t4uQpllzmticMvHLJ4bJ/xXPQgr8seQefMQ2a856vhpH8OSzWtd66TXkdSOTlij1FvqODWfYy6Mn2YahBXpVmfrlob1O1f2qGJVnrqaXu9BGatHe7hIFaZOLe7Hoic3y2GFWA/9V2hDSeetqnaad1mxnS3+jvV5axmUs9Uv6HKddn+U704pTDnsyTJLp361e8EzbSUzT2/PHmf6H92nT1miG0+nVSkfJmDNPDkfarZLF8ZjmtUgrEj/vtOOeMk0RZrzz4QuTmmW7m/39x2xRET0l+H8lbRE9wNeGUlEREREREDG/BCEfpkprPljaHwcBrl7EwkRERHp6q99RywRERERERERERHRfSkbew+Kg7CCio3QlIOwREREDxwOxBIRERERERERERF5mCH1cyw7JK+XbtURDp5ERkRERPchDsQSERERERERERER6WXTRxgck4yLBuW1BsPJFXhn2DKITyuBlz9e+0dH6X0iIiJ6sHAgloiIiIiIiIiIiEgvd/7E0biReLFLDwyMisWmfek4d+6ctBzdthQxkf0QGDoLB26IX/ZCrbD3EV5T+ksiIiJ6wHAgloiIiIiIiIiIiEgvJUvIna6GKziWEIsJw/qjV69e0jJ41BzE7TqFnDzhc68KaPXuCiwb3hDe4veJiIjogcOBWCIiIiIiIiIiIiK9dIvGlqXRiOjXHHX8ysNH1QPr5VMefnWao19ENJZu2Yz/hNbmICwREdED7KHc3Nx8ZV2Sn59vWvLy8nDnzh0YDAaUL19e+QYRERERERERERERERER0YPt+vXr8Pb2RsmSJeHl5YWHHnrItDiDd8QSEREREREREREREREREemMA7FERERERERERERERERERDrjQCwRERERERERERERERERkc44EEtEREREREREREREREREpDMOxBIRERERERERERERERER6YwDsUREREREREREREREREREOuNALBERERERERERERERERGRzjgQS0RERERERERERERERESkMw7EEhERERERERERERERERHpjAOxREREREREREREREREREQ640AsEREREREREREREREREZHOOBBLRERERERERERERERERKQzDsQSEREREREREREREREREemMA7FERERERERERERERERERDrjQCwRERERERERERERERERkc44EEtEREREREREREREREREpLO/1EBsWkxvtGrVSlhGIkF5j4ioUHKOY3XUQLzQqY1cnrTphIGLM5QPyTEDLibHIvLlALSXyuNWaB/wIRKVT4nIgxJGKu2i3ohJU957oKQhprdczrTqHSO8IiIiIiIiIiIi8izeEUtFzrB9Ap4VO0GfHYmELOVNGJA6P1QaiGnf6yNsz1beJo/KShiFrm1aoU3XwfiKPdSOZSVgZFAYPk44hks5efJ7eTm4nm2Q18kBId/HDEDwyFjsOnFTeKW8e/M6/qesExHRA0qsQ58VB8afxUhzg5CIiIiIiIiI6IHGgVgqWlkJGPPhJtxAObQfNRFBfsr72IyFX2ZIAzGGc+uwerv8LnlSGr5auA3X8oC8a0exagNHYu07jcXvTEbyDWHVqwJaRczD8nXrsHxmOJqb0jXZY9g+CcPiMiEOYXvXDcLkReuwbt0ivNepBkrKXyEiogeVXxBmzBuAR4VWYfLkd7D4tPI+EREREREREdEDjAOxVISyED9xujRwVa7Te5hsHoUVdMWQ1+rCW1jzrt4LfTvK75In+ePvQzqhglAKeFVojH49/JX3SVPaaqxLk++CfTRsHv4T8QzqVa+Oep2HI+rvDDvHDNi8+keI49go3R7vfx6FHo2ro3r1xugbPQrdpO/8NeWc2Yevpw9Bv1fmc+pUItJRDs7s+xrTh/TDK/OLR+ni3fBtfNC7MpCXhs/eWwyOxRIRERERERHRg44DsVRkDNtnYc6e20Iqa4Y33+8GX+V9mTcavrUCyXv3Innd++ho+SF5iF9QNDbv3ovdmxeBY4n2GY79jrPSWjV07srAKrzj+O0PZTrnpgHoyjxv8lP0MMxdlYJTN+8o7xAR6eEnRA+bi1Upp1B8ihdvtHznHbQvLY7FfolZCXw2BRERERERERE92DgQS0XkNOI+k+9+qxz8D/Tl1K10n8s4cUpZ80KJEsoqFUIGMs8rqyVLSnfDExHRX5BvEN4Nryes3EbyJwtwSH6XiIiIiIiIiOiBxIFYKhqHluIbaRrXeug7sCUHXYiIiIhIUrP/S2ghnoVcXo/lSQb5TSIiIiIiIiKiBxAHYqlIbP92PS6LK836oH9N6S0iIiIiIsA3GKEBpYWV20iK3wwOxRIRERERERHRg+qh3NzcfGVdkp+fb1ry8vJw584dGAwGlC9fXvlGMZJzBvtWxSF23U/4/UwWbiq9ON5l/VDjiWfR759vIbSB+UGEaTG9ER4nPuWxPaL2zkaQ/LYFQ/YxJC5ehtU7dlv9ZjU8/kxPvDnqNbSvauf+TsNFpHyzGPPXbcaxzOvIkR6J6AWf8lVRp8VzGDx8OLpoDEzmHN+AhQuX4sd9f+C8eaPwq/EEnu33T7wV2sDqGatm0t9+sgjrD59BlvS3yvY6hOKfb72M5kWwv/btx9RuQ7H2KtDs3UTEhmrvuf34SENM73DIH0dh7+wgYVdT8M38f2PpT2m4JO6oED7Vnnoew98fiedqm48x5/hqfDz5S2z947wcf14+qOL/LMKE9PBy86rad+cmjESrqGRh5VFhn9ZiuL85XOMPZuK6FDDeKFvtcTzT802Meq097AWrzICLKd9g/r9XYMeJi+bf8KuBpi8MxjtDeqC+j/xNSwWPXTymD8d/IvzOTeFXvfHE0M/Qd88bmH5A/M1meDcxFjaCWXEIM56PwEpxdLxeBFYvj4AUrRrHbYspjR46hctZ4n6IzMczdFAgGvjaCBTTdsRD2gvhkGxyJp8WTbrVkBaD3uFxyrNhbXhUiKu1w2EOuhyc2bcKcV9tRPKvJ3Dxeg7k3fNB+VoN0LX/GET2rQ/NqEcCRraKghQjwnbXDq+Li8kLMGHqShy+JPyO8BtdP9qGjwK1vutvSrNrfj4hpX0vn/Ko1XYQPnjvFTQxTQ8upMvkL/HR3BU4aAw7IS/V+VsfDH5nCHpoJ0qXJYxsBSXqbdJOEzk4vmEhFi79EYdOXVbKNoFULjbFC4OHYlCgUC7azIeFCUsVKW3Nx79X7MCJi+bwkbf5Dob0sBV3MmfLcnM6t6NA2tKHsSxdscOcPqU6rvNrmPheX6FcMoedsQyyVPiwzTmzD6vivsLG5F/N4Srl2Vpo0LU/xkSK25W+qkna58XzsW7zMWSq81TVOmjx3GAMH95FLtMsmNPQPmN9ILDVRtCVqYz6Cennrynlv5wnq9bpgNB3ItDvmRp20pKL6ddY/sSuw0+/G9sEAo00KNGs+6zqUOFvqz3eGaH26lCF6/HsTL0Xh68H1ZW/bpRzHBsWLsTSH/fhj/NyvSSVe08HK+VZpvl3dcxPp2P7o29surBWEb0XbML4lvL71szfs1fHmttMpbvNwtYpHZX3ZYUPU1VY2mGsNwqQwvQTLFp/GGeUut6UbgvTjqp7EckLJmDqysNSm83Lpys+2vYR1EnWIPxNR+Fv8ryE+n67UN87bFcREREREREREXne9evX4e3tjZIlS8LLywsPPfSQaXHGfXpHrAEXN0ehV2AfDJu7CiknzAOmIsPNLJxIWYVlm84p7zjn/NpIBHUdiIlxP2j85nkc2xKLkcEDEJOq+kDFkLoYg4OCMUTaJ2NnmSgPOdfFv4/DusPKWyZZSIrqhcCwiYjbcszccS8y3ETWiRSsWrYJ2keShT0zQuW/3XXC3OFq3F7CXAwJDsKo+ItSR5o11/bXCWnJ2HtVXPFHu876dHIbUucjvM8QzE04Jg/CSm/exPmUlRgfaowTA1IXv4qgsI+RcMzc6Y68HFw6loC5Q/pjTEKW8qY9Bpxc8TZ6hsvhauxAF9+/ef4YtsSORHDQKNj9KcNJrHg7CMFD5kr7YvEbWSewK24iwgJDEXM4R3nftuxNY4V9+RhJUme0SPiN7FLo1rW5koEP4buVxodv2nBoI5KkW5SFWOneU2PAwg7hWOLHqtKoaRBWZD6egV2D8PaKk6rPikaRpVtdpGBOr0D0GTYXq3YLYWUcMBIJ6fC6mJ8/DkPQyAQh9zqWtjAcfUbGIUUceBHfEH7j1v+kjwrIShhlSrPGtJ+Xcx0nkubi9X4jlfQqlDcTeiN4ZCx2qcNOyEsndsVhYni4zfLNkwwn4zFWCMewiXHYIuQfc9kmkMrFXYibOBBdg97GipPO7a8zYWk4uQJvS2krAcfOW4aPvM0wBIbGQDvbulOWe4pctgUFy2WpOn1KdVzCxwgLehWLU+8o7zrHUdimzBHCpc8wzF212zJchW/nXD+BlFXido1p1JpYrg+W93lVCk5Y5ymxTI5bh4JVaxKiVGnIMjpcayM4K2tPjKqMylKV/3KePC/WR8P6CGlpBvY4UxAInEq/FzdLxyyVPynqNoHAqTQohPV8sU1hVYcKfyvt85A+CJ+farOMdy+eLWnXe5ZbztozA6GBYUKbbYuwPXO9JJV7UnnWE6OcqvMLr2bndnhUWruKvclp0lpB57F5qzgIKzorfM9GPW1qM5VGu8A20ltGeoapM8xhugsnVHW9Kd0OCUbQqHhctJUITNKwMLwPRsalmNpseTm3YF19eXdsgybiSt4B7NwtvUVERERERERE9MC5DwdixU7ZN9D//QScEzuCvCqgflAEohetw7p18rIoegTCuzRAVXu3LWm4nnkS1/IA7+rN0S9iCuYtV35z+TxEBlSX7wDIy0TcP2fjkPQXKobtmDRsAY7KP4CAiGgsUvZH/PspEf3Q/DEflFC+bnR68TsYl3BOOCovVGgcgnHzlhc4jkr/p3zZQhYSRr2MyJUZGn+7HPMig1C/ghC9edewbcqrmLnfqtfMxf11RvbBI/IdhBUboWk16S333PgJ44Z9idMPByDSeIyLohHRqYqcgKU4mYk9SZMwbEEqbpRriJDJi0zHMi6kIcrJP4TkyWOwwkGH5Y0fx2HQrL249UhbhI+bh+VKuCyKjkBAdfl2jbxr2zA5IgaaY1aGVMwPD8OsvdeQJ6Sa6gHq9LkIk8PbQvoZQwbihrxjf3/u7MT0j5Nw98lwzFyzDXv3JiNxSSTa+Ymz+oVCmtVPkJb4A+wNxZqmivZqgT4hhYgU5VimJIlpVEwqlmEixUNQfYhJTUxre2cNcnKw20VFmG411R2EWOX35/Qxhls19JmjbFNcYgfBfI/WWZwUCyaxXOoSjhHRSjoUlkWTQ9BYCighjSVPxrhV2dK6TeeWYPKik6jY6T0sSUwW4n4b1szsjSdKKp+rZSxExOQdQKMQ4W/k7S2fNw4hDeWUL2wQk8eswGGxvNl0CajSyW5esi4u3PHsRCWc1o3A35T38LcRynvyMvFZ5X2BdNFF2BQkSQW8kH/ahluVixEIql9B2t+8a3sxa9AYx4MQToSlvN1Z2KuVthZNRnhbuQ4wZMRhyDsrCgykF7Ysrzso1vT5CGPAVOuDOcp70mKRttyXlTBGKtvEQxSPsW34OHM9J6YDsZ67kYoF/1yAY/KfOOZE2J49qYRL/S4IH2EZriGN5biU0ui4VbDOFYbtYrl+VKmbAxChylPL501BRL/meMynQM2Kxe+MQ4KSFxuHqI5TKIOjR4SjS4NK0Kxa3SReEPFyZJxcRhVonwh187hwtFXqEUPGSkTaqkfUnEq/i/FG//flY5bCOsgirMT4HRHeBQ3sNIyy1v8T//jyJMqo068xXUjfMCBjyUeIOy29KMCdeLZgp94zMqTGICJyJTKkw7UKZ7HeF+vZEkL7Z3IUfrgl/42u/DujXWV59aywf5r1b/ZW7FSN0abt3Kp53OeT98ptJqF+7thBDmkj18K0LgbFKt9TlbvV+sxR3pOXWKu7i+W0K4epV4XGCFHV9cvnRSrlbh6ubZuCV2fuF/bLtnNLJmPRyYro9N4SJArHt3fbGszs/QQKVF++rfB0LXHlNo4dyZDeIiIiIiIiIiJ60Nx3UxMbUmfjpVeXSZ1WXhU6YfzX0xDseI5YiaMpT9O+isKGem9haHutadcM2D81GEPXisNZpdFt1laoZ4/LXhGBwFni8GxFvPDJenzYWmufDEJYesPb9JF5Ojo8FYmNi1+Bqp/RTAh/g/BH6l/M3jQKvSZsww2UQ4t3F+OT0NoF9zlnDyb1eQfrraejFbi2v87ZP7WbEE7SvMRIjA21OaWy01MTC7xqhWPxsuFoaLEv6jjxgpdXHvLKCL+1Svgtq4A8vTgcIQvSpDuJ/IfGI26Q1WCkaUo9+XfKtJ2A5TOCNaYfzhK+2g9RyTeEdS/ht1YKv2V5f2na/BAM/DITeV610HtuLMa3Lhirhotf463guTgk7FDpwOn4cVqAKv5Ux+7lBe+aYfi8wLHLtk/ojHc33RbW6iFi9XJEaN3qakjCuOfGIlH4WoFtaUxLqWaOIy/U6j0XseNba6ZR8U7CdwbNwgEpWFpg7OZP0U8d8abt2JqG1sxeuijKdOuIeb/sTTG5CdGjbqD3FBvTb2atQMTzs6R4FxIP4uMGwTIlmqcjFac4KNN2IlYJgaVZLqi+KyrXPkrju1lYEfE8ZkkblNM2amrnpe0TugtpSYzAguWbPhxNdytSp33b+Ufc35Mr3sGgWQeEMlBMcmOx+dN+VmVNYcIyDfNDBuLLzDxhs70xN3Y8Cm7WgItfv4XguYeEcqQ0Aqf/iGkBxkB0vSwXmaZvLqKpiCXZq/CPrtMhzWZerj0mLJ+hWXdm7ZmKiMi1EIJC5mBqYsdhK+SK6FG40XsK+mpnClUa9cfQ+DiYi+ds4bNA4TNhteIL+GT9h9DO8lbhun8qug1dCzk6NmLxK9p7JrZtxClFdJMthMuLQriIRXK5Fnh38ScIVU2bb5aFPVMjELlWqCeEV5VDYvHDmGbyRyaFCGNDKma/9CqWSfmmAjqN/xrTgu1PIWyiKpuFP0atAQsRN7Kp1ZTJBqTOfgmvShuwPaWt6/Escr7esy4nBiyMw8imBbdpuBiPMf2nQKquRTrnL1Nbx8a0usb6yqtWLVTLzMRZze+Z07hWOeZemIrM6cjmVMSi7E0Y1WsCtglhVa7Fu1j8SSgKJt0c7JnUB++slxqVBdscFu2oMmg7cZVQ19sqFcxM5Z/NeoGIiIiIiIiI6N76i01NnI34uSuUOweaYeQ30U4PwjrD/+9RGK45CCvyRsuQ55Wp6ApeuX/uwiVlrQz8/Gztk/Xg0AVcEnuKRRX9bHZii39k+YuHsGC2OAgLlOs2SXsQVuTTGv98o4UcyekbEa/aZdf21zkXlIMq/cijNgdhC6cy+n6g1SErxMnAvqgnrechL6802o+aXGAQVlQzpKc8/Z0g7fABZU2L8Dt+vTFTcxBW5IegGR8gULoTNQ9p61bDYlLC7FX49xKxc90L/m/OsTGIJOx51Vfwdl/5dprbSeuRJK1pyPs/dBo21EZnNNDxpReE0BGlI/EH7duUDDs2Yac4MCB884X+6gFfB8RjWSp3vHv5v4k5NgZhRd61QzFzVHvIwXIA3y63ccuUm4oy3eqjG0ZF23nWpV9f9GmrFLvHfyk4napKXl4dDHjX9uCWBa8WGDZZ67t+6BsWIMeLlEceRdhU7bzUsc9zqCit38bRg7am2ixa2av+DTnJ2c8/4v7WDp2JUe2VIzvwLewlOUdhKW53iTjy6OWPN+doDcKKvFH1lbchZ9vbSFqvzrWuluWek7b4K3kQFuXQbZL2IKzIr/V4TA2TazpnOJNOu42KtjGQJBLSaJ+2SmPkOH6xyBTnhPpEWS0jhKvNLG8VrsIfmaPD9p7pOggrOLTgE3kQVgpjW4OwIj+0Hj8VxmC+vH45kuzcXugw/cbPxQol3zQb+Q2inR2EtVbvdcwpMAgr8kbDNwbAOFR89shBzTs7XY9nKw7qPUPCAlM50WxkrOYgrMi7ajBmfBColH/6a9mxlanOKzitbjY2JR0R/vdC85deQl3xwLW+Z9iO3eLXBE0CuhVoM+kWpg4cWjBbGoQVGpWYpDkIK/JB63++gRbSBtOxUd2otCDUNXUG4F0nBmFF9esqGeHSBbszexARERERERER3a/k/pv7xfmVWCP3JKNy37cR6lwfj37865umibxzx7LXtG79ukpgnsVP6w7D8ZM/RcLvGfu7D/yA1Y4fuiVL24qd0jyzFfFcn452O1x9mzRS7rjLxO+p0orEtf11RgZOnJLX/Ko+Iq+4q1o39LS+WcioZgs0lUePgNId0TfIxtCv79NoYgzrjOOWg6dW6vUdiJb2AtU7ACHdlY2ePYKDqh5pw/YdSJGSaBP0DLH/JNZmjRvIK3nHcczWDgnHFGS6605Ds954Xjmu9MQfUHAsKhvxK5IgjQ3U64swW+GowXwspRHwerjD58r6BoXDGCzpWzcXSYdq0aVbT/FG/brKLUt5d2H3SZz+3dHTUaAbPROEYBtJ3/tvzc13gPn3wsu2bgdr2RxPKatnhTzieQZs35ECOckF4PVwhykOQeHdlcHjdGzdbCfF2Q1L1Xab9IT9bNsM5mx7TFWOuFiWe0wGftwmX1SBegPwj472CjghuF7u5fxdg4VJpzZ4C/lazhV5uGuRKeoK+UVpppz9CesOO5njhd8zR8dqJ55nqYc0bJUrZqfCWAg4DBqgFMi3dyLR3vMx7Ybxeaxcc0BOv5X74m03GkbN+vS3Xc6bppAVXLrg0rOObcezFbv1ngGbN+8ylRNhfe0fr3dAEDoW1Uhsx+7Kb9/G3u37pbdMDNuxQ6pAmyAgKAhtpCvBNL63e6dygYRrz9R3OkztMqfdis/1gd2k69sEjZQqLFPdqLRSmGfRe5dUJiy+kY3r8hoRERERERER0QPl/hqIPXBY6fiuiI6BhRhRKixDNi6l78OmtWsRO300Rg8fiODu3RHQXp7eTYt313AEG58X9u0QdOs3Fl/vy0S23Q5gf/x9QDM5Em7vwcd9emLIjA04mmW/s9lw7Hf5rmBcxdqhrdCqlZ0lPE75LnDqhPnuBdf21xkG3HG5M9CG2o+jvrJakC/KlVFW/arC/aHfimjawnH3YdPGTyprl3BB1SN9/Lc/5A5iHMKsQI34UC+m6SDPI/OEsmrtscfxhLKqzR99X5DvCUb6eqy2HtDN3oTN8mgq6gU+73THqMh8LE3R1uq5ddpaorlxJO/UH/hdWdVT0aVb/eVkncPRbWuxdmkMPhw9GkNe7o7uz3XCQGk+TcdK16lvNW2xbdXqPWH7ggxfIY8oq6jyiNO/6XnH8dsfcopD07ZwLsmZB49P/WE7xdkPS9V2D81CoFZeVS3mbJsJc7Z1rSz3nFT8nimvVWzawnE5UO0RVFFWHSlMOhUyBc4d3Ya1a5ci5kOhbh3yMrp3fw6dBprrKUve6BoerNz1fxbfDumGfmO/xr7MbKGmscP/7xjQTG7e3N7zMfr0HIIZG46iSKPDcAy/KwdRrXUHp8pa36ebmGbZOHHc9oUE9sP4AA4r5X7FjoGmu1YLrxoaNbU3EFgXdR5TVh0pdDxbsVvvFbaceARVi+yivTZoJ98eiqt7ky0u8DLs2C4PsDZ7DkFCGdy5nXxpg/X39m/fq1wo1Rld7WUkd8PUHlXavbp2qGa5Z16UKaFFp05A+57Y0qhT3/mapq7TCYuIiIiIiIiI6P50Xw3Eph03dvlURfUayqqeco5j9dh+6NQxEC/0H4YJU6cidtVWbN19DOezsnDTXs+vd0uM/u9HCKou9grmIedUEuYOC0Fglx4YGLUax2yMFPmFfoKFEY1RQYwJwxWkrJyIwd27oFO/SMRuPaN5x1+G8ZbTQrK4i9fF/b0nSpa0e9evvsqgnBM3pZju4LCSkenKfaB27mRxYuCsZv8+Suf7WfywVnyYoll2wga5M9irBV7qX5hhWNWxVKyOGk5GgGmKwds3NaeudFuxT7cGXEyOwZAe7dGpey8MHjUVU+fE4YetW5FyIgtZ13OUwW3HCnNHuVeJEsra/SwD5iRXw8k8b74T9fZN2ynOfliat1soVnc0u1KWe0zacdOASVWdK09n0qnhYjJihvRA+07d0WvwKEydOgdxPwh1a8oJZGVdR46dTOHdcjT++1EQ5Cyfg1NJczEsJBBdegxE1OpjNi7C8EPoJwsR0biC1MgxXEnByomD0b1LJ/SLjMXWM0UQGxknYKyZH3nUybJWNcvGjWzb9wLaDWPd4tYL7hYj7sSzBbv1njm/lq7g58G2gRZvdO2qTA18di+SVeXI7sSd0gCrf7vO0nTD1dq3kgfdLb53Hod/lSfRflT4nlaq0S1M7VGl3UK5c8fGBRF+0GtCFCIiIiIiIiKiB8F9NRBr5ofKyl1xuslKwMigMHycdErq2PIuWw0N2nRGv4jxGD8+GovWrcP6xAlor3xdi3fVrohal4g1MyPQ9jEfOXANV3As4WMM7BqEwbFaU6n6oGnEIiRsXoL3ghqgktSrKA4w7ULs6D4I7BWFzTbnVWyA179ah3XCvjmzxA4ydvnKXNtfcorvc5iiEQe2lonPKn/nCt8g9FDuyrmctBHmodjTWL5GflU6INTm1LUO+ZSG8abj4qD4plsDUmMGIHhkHFKuCHnWywfl6zRH5+fDMWL8eEyZt1yI6434PNw4aSrZ4lP63qQ43+emFMibtpeJsMy27pTlnlPlEefvVNODITUGA4JHIi7lipBDvOBTvg6ad34e4SOEunXKPCwXwnLj5+GmqYQL8kbVrlFYl7gGMyPa4jEfuawzXDmGhI8HomvQYMRqTVns0xQRixKwecl7CGpQSR6wEwdyd8VidJ9A9IraXGRTFvuUtvVMz6Llp3vDyHnux3PhVaj8sLJ273h3bKM8fz4NO7caLwbZjo3bpWFYBD6v5Df/zmgnRY/qe9lbsVO6PbYy2nUuOBn4vQjTBq9/pVHW2VhiB5kuJHDHedODoImIiIiIiIiIHkxyj+Z9oryvcYLNk/hD10cYGpA0YzqSbwirXrXQe/b32JIUjyUxMzE2ojd69+6ExtWro4qv9l2QlnxQo3ME5q7ahi0bF2FyiHKHVN41HI0dgjcWF3yKp8jbtwH6Ri3Bhi2JWDkvEgHS7T/Cnp1LwPv9J2G7qsPYHA5XcSuvOqoL++bMUsVX694R1/bXNn/x8XySrIsX5JUHkPnu7HLwLa+sCnzLKg+jy85GzsPa8aC1+LnVb++L4NAASFu+nISNxpHY0z8gMV1cqYwX+gcU+s4h07GcT8fvTg5YHM9Q5iysWMVymuhHqijP8tSL3ulWB6e/xKS4TOmO13ItIrF0yzb8+M1CzJw0HGG9e6PbM/WEuPYT9py0+cKc5H4XSmVnHIc5ybl6C5Z5u9nZOXhYI39qL9pxWZiy/F7IOG49f3lROo0vJ8UhU84UiFy6Bdt+/AYLZ07C8DChbu32DOoJYelU+edTA50j5mLVti3YuGgyQpS7XfOuHUXskDegneW94dugL6KWbMCWxJWYFxkg31krpK5zCe+j/6TtTqYzJ5Q3TwF+0tkGiupu1iqPVFfWCsmV7epOx3h2qCRKKC3X85nG0LPnLu7qcdeoLb5BeE6ZD/rIbiU97d+OveI4rMV0w80Q2FGuBY/s2yX9b9i+G0fElYodUfBpGx4MU1UaunorT6Oss7FU8S10u0LL9Wyx8S3w6OwnRERERERERESeo3Rn3R+q1a8jDzbhPPbs0HOgJQnrk6SndKF0wDCMbl9VuzPo/AUU5rp9H7/G6DFmERLiJ6C91MuVh7RlS7Bf+tQGb1/UeuYVTF+XiM8H1JIj6MYmLFltnnZTHQ77d7syp6Y2l/ZXg3EA7/a1LP06uT3mPDKOO9rrbBw8Yhz9aYSmqhvMnnjc+Kyzw9i7W1n1AO8O3dBOCvbL+HG9HGNpq9dDHocNQHcXHhzYvInxDp3D2LXDmZjcj5RflNXaj8Pi/h7fcqa7ai9dsJdmDThmfFidk/RKt+7KiN8ohzfqYcCEV1DfRgf5hYtZyhpZag5zktsF55JcCsxJruAdZc55AuZsuxe6ZVsnynKP8W+A+kptf/bIQcfThqvC1S0Z8dgoZwrUGzABr9jOFHA+V/jAr3EPjFmUgPgJ7eUBpLw0LFtiP8d7+9bCM69Mx7rEzzGglhwYNzYtgW7RUa0pGilXm5zfswPOtFCyDx5Rnu9ZEXXruzhlQbX6qKNcSODsdnVXJPFsyxOoZ5zD95cUx+V89mH8ql8zSYP5+a95B3ZK5cehxO0QJxy2nm64ZcdWUtst7/DP0n7v3nlAunCndKuOaCl+Qc2TYapOQ/t3C60gzzphnGv6sTq63GFLRERERERERFTc3FcDsWgTqAw2Aemrl2C/bqN8d0x3TPjZeTbh6e82wpV7ibyrBiP8OaWH9uolOHefqA+avvGSMuWdOHh1TlkTqMIh7ZtFOoaDzLX9NTMNRp78A/fq/hzX5WHXmtV2OzYNqZ9jmXLXqXUHarWunVFPWruNH5es0KHT2UneAej/gjwt5dUtG7Efh7D2B7mLv17fMOUZsoXj27mdMph6G0lL7YeJKDshDhulx915oUWPIOm5eCbVH0EVZfX4nmTbA0FZq/HdPmW9kNxNt+4y3DE+MbQ6ath6RKQhCQnSlJVUkHlAA7eTsHS1wxSHhLiN0oCH+AzkHkGuzr1dDV07y7kWt3/EkhV651o7ZbnHtMUzxh04tAbL7Y7WZSH+SyVc3WW4Y3qObnXbmQJJCdul52kWjjeqBofDnOWdzPE+TfHGS6bYgH7R0RIdW5kaKFjisGJOw2JjRVL5ObxQYCTOWW0QaG4YObHdIlCk8WytLtq3UqZgvroRK5PsHa8BqZ8vU03XXzRM9f7tvdi+Pw1bd14WXjyKZ3tYXRzSph2kpwhc3YvktP3YLt02WxrtAttIH1vwaJiq0lDaN1jk0TSUgeMn5AZ4tVochiUiIiIiIiKiB9P9NRDrHYBhr/nLO315LUa/sRipNvqLDBfjMX+pM9PWicxT3Z3duVXzjhLxWV0jvlBuT9CQtnAsZiRfhPbuZONE5nV5tXRZ1QDVJnz09tc4buuBluknTftSTj3/rXcHhHRXOiLFcBgTb+dZdzk4vnoUojcpLxWu7a9zqjVtJE9De34/dLxh12PyDn2GEYtTtcMmaw9mfrBCvovJyx+v/aOj9LZJzRD0aSYnprxDsxEx287zSg0XkRwTha90mim0WfcASKni6hZsXLEVUl+wVwu81N9WJ64D1cLxZjd5wkLpWKbusTkYazi5AqOjk+UO4UdDEWn9QFrf9miljHXlHfgKn2tlXCE84id/hkN2ppF0Nd0aEkaiTatWaNUqHIuLKE16lzROXX4A2zUHB7KQMOZfSHS/1/weSENMbzH8WqHzhO3Ke/qrFv4m5CSXh0OzIzB1j80Uh5MrRiM6WQ7MR0MjXX8GsqBmSB/I2Vbe7mytZ44qDBeTERP1ldVFOS6W5dbOHsFBW1cppMWgt5SGO6PwUeCLoD7tlZkU0vHFiNnQPkQDUhePwJw9OiVS75JC7So7sD1JM99mJYzBv2xmijQsHDsDybYquOwTMGd5VQLY9BHe/vq4zbI3/aQpNiymlnc3nXf8x2vwlxsoWDv6Haw4aWO/hbJgz9TxWCpVJKXRemiESxfLyLwRMEy93Tew2HbDCPHzl5qmQ9aN2/FcOM3C+poueEr81xjE20gfWUmTMGqF/RkWdKkbanZGO+lBrVdx4JsvsE3cZOV2KPDYV++OaCNdA3AWe5d+hwPi1Q5CHd2xg8blf0UQprbvhvdGh5DucvtBSkO2w1SUc3w1Rlk3Kl1lSMXvUnb0gv9TDaW3TITP5r/SCW3adMIr8220yYiIiIiIiIiI7gPK8OP9o+agTzBRnn8UN1IXYFBgP0TGrMG+9HM4d05Yjm5DbFQYgoKnYNOfznbbtMWzbY13lMRi4KszsOGo8nvp+7BmxmAEDYrDpWda4yn5WwXl/IaVI4MRFBaF2E37kC7+rXF/xobj3wfE0SUv1AodCPPQ3R38uXcuwgJ7CcewFNuM2zyXjn1rZmDwqNUQx9JQrhMGhqjmv4U3Wo4ejyDpoZhCOCRPQZ+eQzBjjWq74n7HjMHAHoEI+3gbzhhvrTByaX+d1LIj5BuDjmNPsl7zPnpKRdSqBaQuGISgwTOwZl+6EidHsS12LHq9+A7WSg9tE8Im7H2EFxjj9EPoh8PQUOpXzUPmsiHo1m8sYrcdVX5HCePpQ9AvMBgj41Ic3mnqtGZh6Cv1Tl/F3mU/SYPFpQNC3Rig8kbHD+chXJrGUziWte/gxV6RiFGnM2N+C52FA8ozlsOnva0cv1pNhPRpphQ4Z7FsUG+Mit2Go8rvHN0Wi7EhfTBlVyW0b61O61ZcTLeHU34RjkBg8cw+fdV9rhOkvnhxcGCccHxfm/dPOr5eLyIquTxa2zu+4ir7IOTZuG3cvaUX7474cF445CSXibXvvIhekTGqfCiHZVRYEEJnHYCc5MIx7e2GQmp1g18oPhym/Iaw3WVDuqHf2FhVmSxvd/qQfggMHom4FOtc62pZLmvR1DhicwifvR2DrVJ9dhSr5681DZqZprEt3Q6uRIFv0ESMVerOvMxlGNIzDFGqNJq+72spXActSAW6dUNr6ZtuqvscOsmZArcTx6H3qK8t6+qxvfBiVDLKt24NW7ki57eVGBkchLCoWGyySgdjw/8NOcvXQuhAVY6/8yf2zg1DoFheLTWXM8b6fNRqKTaE6BgIi+hwN53XHIRPJirTJd84gFmh8n5bpocYRAplwTtrledJtx+LycF+4l+4zmK7qVgwKBD9LPKNWH9FISwoGFM2/an/gJYO8VwoNV/Dh+G15PrkRjKm9AkR8t0Gczwf3YCYSGGbYzfhcpPeeEHZNy361A3+aN9KvjX70r590kUXFTsGagyum+/6P5WUhEzhf6/mHdBRq/DSLUxbwFy8fIa3Y7bKef7oasxfax6S9245GuOD5Ocuy2HaE0NmqNrWStodM7AHAsM+xrYCjUoX7d4p52E0wTNtpXfMkr7Akt9zkJeXg9+XfIEk5W0iIiIiIiIiovuNPC5yX/FD0IzFmNCpirTzeTmnsCtuGob174VevYRl8CjEJhzHtTygZElnu+Z9ETRxrPJ8SbEfcyUmDlZ+r/8wTFt5FNk1B+CTmc/Ld3ralIdrxxMQO2EY+ot/a9yfpHMwCHtbpds0xL5lfYuEwHBOOIY5GGXcZq/+GDZtJY6KB1GuIYbOm4Zu1oNp3h0R9c00BFWXj9FwJQUrp6m2K+533BYcu2IQvlsXDetLX7Pi4v461AbtpPn38pCyeZONOzCKqzLo9K95eK1uCVw7uhLThvVX4mQwRsUm4ZzUg+2NuuELETfcxuBPzb/j88+HorE0UJ6HnFNJiB01WPkdJYxXpeBUTh68KjyJBtXlP3NfTfTsLsfX2bPiaEJFdA8JcG+AyrshhsfORXhDOXMYzu1CnDqdqfKbV4VWeHfFMgwvOAor8QudgYmdlI7evEvYFjsKg5XfGTwqFknn/g8tRs7CkCccFUuFTbfncfhXeaJV62f26cp/KKYZBwfE45tr3j/j8bWfsBBvOTy+YijliHwHqK27t3Tk3XA4YueGQ05yBpzbFafKh3JYJhy/JqQCL1Ro9S5WLBuuMfBfeDX//jk+H9oYcrbNwamkWFWZLG93Vcop5OQJ232yATSzrStluaBayEB0MtU/cRgt1WeD8fGmTNOgWcoR+R5crxYd4VoUiHXnPAxV8nLeteNIUKXR/sPmCuGaDd9OE7D8w3amu/EqVnlEWXOFP4ZOUwbWhRi7tG2uZV0t5Nn/az8BC996Qs43tuRdw/GEWEywSgdJYoHsVQXdpsVCu2oVyqs55nLGWJ/L0TEU86Z1s5zxQYd07hc0A4sndEIVKR3J+22ZHuKwS6pIhHok5BOsmh0kxIz7LLcrpF+LfCPWXwk4LjeM3KsTNOkUz07zRsPhsZjWTW4HyvluojmeB09E3K5zECpqLPwkxE746lc3tOzeRWof3r5xQwiBiujSXXuuaeM0xrdvy3eyNgmwSoMmeoVpNYQM7CQP0uMGUuNGy3l+8MfYlGksXUTe6Bj1DaYFVZfTh+EKUlaq2tZK2t1y7IpQJglpV7tRWWjbNypTKzd7Di7PLk9EREREREREVMzp0yfmad61ERy9FpuXTEZ4lwaoVtbcrejlUx7VGnRB+OSliHurEM+b8gvC7ISleC9I/Xte8ClfB20jZiN+2Ug09VHe1uA/ZB7mRfZD8zp+MO+O+PfV0KBLOCYv2Yy1UwKsOgS7Cu8rx1DexxwZ3mXhV6c5+kXOw5qE/2KQrVEGvwBErUvE0snhaGuxXfEn/ORwGLcQ329ZgSFWndSu7a+zvNE1OECaBjMvZTM23W83xZZoiLfi1mBhZBAaVDHHiximddoKYbM0ESuGN4Wd5ADvhoOwKCFe/o1q5eFjilwxjIXfad4PEdFLsWXzdM2BGVdVC+kjP4NO5NZzB1X8WmP4fzfi+4WR6Ne8Dvw089sSbE74D0Jr20irEj8ERX+HOCm9qsJESO/VGgThvaUJ+DS0Nkoob2txKd0a9uKANLqi8cw+XYmDA8sQPzvC5vHNDq5q9/iKq9SfD0ud5V5tu6KrvSjWiV/r4fjvxu+F/GM/rhP+Ewq7Sa5QhPgbtAgJ8QsRKdYD6jLZywfl/eqgeb8IRC/dgs3TrQdP3CzLfbth2vLZiGhbx3yswt/WadQA8sy5qfj5sBQDaNu1qzxQ4grvhhj03wSlzrBOo10QMTseCdHBqKraQJly7hVQ4sD6snj52MqbN4iy1Rog6L2lSJgtbM9mpvDHkHnzENmvOer4lTUftxgfwt93CZ+MJZvXYkqAVU3VVXhfOMYuDaqptikeplz2Rs5bg4T/DiowgK9POvdG7eBorN+yFJPDu1iV/8JxS+koEvPWCPXImNYu1rFa5O2u3bxE2a52eC2NewtF8SRO9+LZFX4ImLIW8UK9FCTEsynfKMcqbjNxxXC77TZd6wbTTCCC0q3Q0Vbda5rGWOSPdp1t5y+9wtS32zQsl+olc5rwLlsHjRpYT5MuhGnUOiQuFcoyYZvqul4qy6Q0NA4Lv9+CFdaNSleYnpmu8Vx5UcDrGPiEUJ4KcfrEwNcRoLxNRERERERERHS/eSg3NzdfWZfk5+eblry8PNy5cwcGgwHly9t5rh1RAYcw4/kIrLwMPBoeh7XDi3IATAcJI9EqKllYeRThcWtR3HeXCmH/VHQbuhZXK4cg9ocxbjyL8a8qGysiAjHrkBdajN2MT/vpeOUAOSd7BSICZ+GQVwuM3fwpijwKMuYjJPRLaepU/6HxiBuky4SyxRzT+V8O64Z76vTicIQsSENeuW6YtXGK9hTNRERERERERETFwPXr1+Ht7Y2SJUvCy8sLDz30kGlxhvlWESJdNcPQd9pLd8WeXbUACffbXbH0wMjYcwDi5JPaz+wjx3Zh3xHx/yYI0PP2bXLern2QoyBA1zvobcnee1AahBWnN2/U9K8wCCtiOv+rYd1wDxm249Ov0qQp5v3//g8OwhIRERERERHRA40DsVRkfIPexWv+QhK7nYzo6dtNzzok8hwDjqSKQ0ql0crmXJFkV+ovSMsT/vdvBzuzaFIRSv1FHLAQo6CzjedJ6siQis+XHZLX7U2x+qBhOv+LYd1w7xiQ+p9Z2HRDWH00FO+HF9mT24mIiIiIiIiIigUOxFIRqolBH78JcSz2xqapmLmfQ7Hkabux97DwX+mO6N5RfocK5/zu/Tgv/O8f+GcLXt0AAKVgSURBVDz+KvdGFi/nsXu/FAMIfN6dGNiEjwbHIPminXLYcBIr3hmGZWfFF17wf+0f+KtkG6bzvxrWDfeKIXUBPlghFDJetRA+7e0Cz2omIiIiIiIiInrQ8BmxVOSyEkaiX1QybpRrj6hVsxHkp3xQnPAZsUT0QEvAyFZRSIY3KjXoin7hLyCwSU1p+nhc/h1JP63CqpV7cCpHvC1UHCMJx+JlwzlIQkT6MaRi9kuvYtnZcmgftQqzi2WDkIiIiIiIiIjIkrvPiOVALJGIA7FE9EDbhFFtJmCbPM5qhxcqtBqJz2eHojYHYYmIiIiIiIiIiOgvzt2BWE5NTERE9MDrhugtSxEd0Q/N6/ihvI+q+vfyQXm/OmjeLwLRS7dg8384CEtERERERERERESkB94RS0RERERERERERERERERkhXfEEhEREREREREREREREREVMxyIJSIiIiIiIiIiIiIiIiLSGQdiiYiIiIiIiIiIiIiIiIh0xoFYIiIiIiIiIiIiIiIiIiKdcSCWiIiIiIiIiIiIiIiIiEhnHIglIiIiIiIiIiIiIiIiItIZB2KJiIiIiIiIiIiIiIiIiHTGgVgiIiIiIiIiIiIiIiIiIp1xIJaIiIiIiIiIiIiIiIiISGcciCUiIiIiIiIiIiIiIiIi0hkHYomIiIiIiIiIiIiIiIiIdMaBWCIiIiIiIiIiIiIiIiIinXEgloiIiIiIiIiIiIiIiIhIZxyIJSIiIiIiIiIiIiIiIiLSGQdiiYiIiIiIiIiIiIiIiIh0xoFYIiIiIiIiIiIiIiIiIiKdcSCWiIiIiIiIiIiIiIiIiEhnHIglIiIiIiIiIiIiIiIiItIZB2KJiIiIiIiIiIiIiIiIiHTGgVgiIiIiIiIiIiIiIiIiIp1xIJaIiIiIiIiIiIiIiIiISGcciCUiIiIiIiIiIiIiIiIi0hkHYomIiIiIiIiIiIiIiIiIdMaBWCIiIiIiIiIiIiIiIiIinXEgloiIiIiIiIiIiIiIiIhIZxyIJSIiIiIiIiIiIiIiIiLSGQdiiYiIiIiIiIiIiIiIiIh0xoFYIiIiIiIiIiIiIiIiIiKdcSCWiIiIiIiIiIiIiIiIiEhnHIglIiIiIiIiIiIiIiIiItIZB2KJiIiIiIiIiIiIiIiIiHTGgVgiIiIiIiIiIiIiIiIiIp1xIJaIiIiIiIiIiIiIiIiISGcciCUiIiIiIiIiIiIiIiIi0hkHYomIiIiIiIiIiIiIiIiIdMaBWCIiIiIiIiIiIiIiIiIinXEgloiIiIiIiIiIiIiIiIhIZxyIJSIiIiIiIiIiIiIiIiLSGQdiiYiIiIiIiIiIiIiIiIh0xoFYIiIiIiIiIiIiIiIiIiKdcSCWiIiIiIiIiIiIiIiIiEhnHIglIiIiIiIiIiIiIiIiItIZB2KJiIiIiIiIiIiIiIiIiHTGgVgiIiIiIiIiIiIiIiIiIp1xIJaIiIiIiIiIiIiIiIiISGcciCUiIiIiIiIiIiIiIiIi0hkHYomIiIiIiIiIiIiIiIiIdMaBWCIiIiIiIiIiIiIiIiIinXEgloiIiIiIiIiIiIiIiIhIZxyIJSIiIiIiIiIiIiIiIiLS2UO5ubn5yrokPz/ftOTl5eHOnTswGAwoX7688g2iv5Lf0HtYChKUV0AZjBrbE1NrKS/pr+v6Ocz5Pg07r5dAs3bNMLqpL0opH91TxXW/iIg8pqjq7rtI23cAH++/hRvlq+DDkEZ4igUsERER0V8A24GOLP3PCryWqrwQBL0SirXtlBd/WZcwfuJPiL6svBQwXIiI7k/Xr1+Ht7c3SpYsCS8vLzz00EOmxRn34UBswUpMk1cJVCpTAo9UqYTOTz6KPs88hvbVfDgg8ReUe+sCNiWm49Ojl5CSlYvLN+8KTWiFKZ1UwQutamPw3x5FfeG1GQdiScPdDAwcuxfLbyuv4Y3gV4OwspWP8voeKa77RUQPsLu4eiIT83emIz71Oo5fz8X1O8pHghKlSqGysDz5ZFWEdWiAv/t74uKQoqm709f/gKcSrpvaECWq1seeD1uiqfKaVC6noNXE35CivJSUqo5vozuhl7qZRURERPph/Vtk2A50TI+B2MMrv8Pfkm4pr9xRXPruOBBLRPSgcHcg9sGdmjjvLq7cyEVqxnl8uuEAuv9rHSq9twGvb/kTelTpVPzlXjmBjz75DpVGb0HfDZnYdPo2LqoHYUWmdHIG0St2otGi48oHRHac+RN7TIOdIgPi955U1u+h4rpfRPRAunX6V/T/YDWqztyLqOQ/ceCK5SCs6G5uLi7euIHt+9MxNO4Yjinv3492Z5g730R3L57F8kzlBVlITz5r2Qksyj2PxXssWmFERESkI9a/RYftQCIiInLHX+oZsbnZ1/DVt4mo+sFWfHmODdEH112kJSai9od7MOnYLeQq7xLppqw3KiirRtUr+Spr91Bx3S8ieuBc3LkFj08/gtVX8pR3HnwVfaxuJfHyQZ2HlXVSuYTPf85W1tXysXH3b8hSXhEREZGeWP8WJbYDiYiIyB0PxEBs9ceqoXcT66USGpYrqTn9Xe6V8xgy9QeMz/DsYOyt7HP4ftM+hE6Lx8Of/aa8+9eTe+sKkvYcxPDo9aj20X4cVt7Xx038+NUPaLb6T1zW6hsWpyIuVwoN6xrTSClUKuXc7eNUxO7m4Hjq75i6dDOajfkBHxbnq0srN0Fc/2qoL6UdL1Rr8BQ2hz4qf6Y7Ay6lZ2Duyq1o88Eq9N+pvK3Fo/tFRH9VuRn78OyyCwXq2RKlfNDiSaF+bVkPM0P98Q+xPVa33ANTzwa93Aqj6v2f1LYsUao8hv6jHYaUkT8r/gpRl7jr9z/wtY1HiNzNOINvOTUNERGR/lj/Fql71g68n/pJdOD3WBWrvl3V8tj/Kd9SlCqLZ7W+Jy1V0Lys8j0iIqJi4IF4Rqzd+fVzb2HvzgMYmnAWR25aHCpQugq+nPgswjxwaAWec9CwOXLfflJ58Rey8yeU+vqS8kJQuR5+nvyMTs/VuIv9K39Ah6SbltMP4yFUrv4o/hXWAmH1ykCrrSwOkv+0JQ1jLtTAr2/UV94V8RmxnsFw1sbniRBRcZOF6VM344Mz6jaVNzr36oR13R7WrGPF+vnqid/w7sY7iHyzqQeepcU6xZJn65JdS9ehc3KO8qo0Wte6iz2Z5vlJOvTthZ8C+exyIiIiPbH+fRDdX21aPZ4Ra1eR9icWFfbpEBE9KPiMWEdKlUGrLh2wf9pzmPO4t/Km4vYlDFvCKVoeFLkpO9HDehDWywf9X30eJyd0wBs2BmFFZXyr48Wena0GYYmIiMjC5ZNYZTEIC9QN6IjNNgdhRSVQsU4jfOGRQVi6t07jq0PGTmCBV3kM7VhBSAFmO/YcwyllnYiIiPTA+peIiIioOPvrPCO2RCW8FdkOo6pajlDfTD2GqN+VF3QfO4vRK87imvJK4lUWkZFBWNLKV3OKaiIiIiqkmwbLuhZl0K9VFWWd/upy96dj2Q3lhaBsk1oIaV0D3dVnHGfOYslFZZ2IiIjcxvqXiIiIqHj76wzEikpUw9RBdVFXeSnLwcrdp5V1ul9lJf2ChdeVF5KH0LxHe8ysb3UXNBEREenoDq7ymWMkuYsf9l/ETeWVeCf08y1ro1SJ+nj5SfWFkNlYtZvz0RAREemD9S8RERFRcffgPyO2gBzMj16HERnKS5FfXeya0gotlZdqubcuYFNiOj49egkpWbm4fPOuMvXtQyhT1gcNHq+OES80R/+aBQf8CjwX1q4q+HLeswhTXhm5s31LBpxIPY6F207i2z9u4LTF73ijil8lvNSxAUZ3eAR+0vtaxGe8/YEZG9Mtf6NkSVStXB592zTAP7s8hjrWt59aP8fBLleeeaERp+VrY+u0NmirvHSd7Wdy5F45g/nrjmDe0WyczMmTPi3lUxqNG9fFrF6N0L6SeiIgLUqc7DqN9b/dwJmcXFy/o3xkCtNGGBtYAzVs/pTt/bv4y0G88e0f2HxJiKeS/4c33+iNT5ooX5OI8ZmJ+TvTEZ96HSduGHDFWBx4lUCliuXQuVk9TAz2x1NO31IsHtMx/Ht9JlZfvK2dXrs3Qd86PihVYN/tqxvwLH4L0brrysV0aeJKGBauHLp16RSWbU1H7KErOHY1F7fk5IISpUqhcrnSaN+sDsYGNUALaV7Pgr9tl8Xzpl0rH8VyZnXCMcwR9u/4da10aDsMC3dsRHTfu3UUz47+BTuUl6KyTzbDb8MboKryulCs2wgOnqHv3DP37TxPK/cqvttwCB/t+xNHr9yB+OQ0sbyqWbUKhvVrhrf87cyi4cJzqdTlq7mM9EL5cmXQrFktTOjaAAFVnL1oTFXfpd/EuRvy/otK+ZTC49WrYdALDTGkYUXhiN2pS1x0Vwj3EUK4K/UASlXHt9Gd0Etow+QKYVdBCDu5TSBwqp1mu07LPXcMQ788hhWn/4dcoc3SKbgbfuyqca4ixHfSllRM2X0ehy4b6zetNol9+rXHiYiIdKZ7/WvkXh+Sse6cfVBdBwvEc0wfHzzZ7FG8/9zTeNZeA/JuDlKOpGLRj2c1+he8Ubuquu1TCKr2wS9Z2v0g44IeR/Myqo6YQrUD3elrKS79JGpyP8+/1mZg/cUc5VjEOCiLTq2ewDTlOIrlM2LFuN79O77aexGbLuXgqlb7Obix/XMAhWtp2vk+mvT1P+CphOtKGhc9BP+ATjgQUs1y39T54twtXFT6I+VzjJKoUaUaQoMaYnyjisr7RESkBz4jttB80LOhVUdN1lXssR4vvXUa0z/5DpVGb0HfDZnYdPo2LpoafaJ83Lp5GwcOp2PgtLV4emkmdJ3lRcft5145jtc/WAv//xxG9OFrOFngd3Jx8vR5RG/KtP3MkNyz+GhmPKrPPFjwN+7cwcULV/Dpup3wH52AyF/M12J6xK3jWKkehBU0bvukDoOwtl3cvx1PfrgDY34WwsLU6BGCKUeIk59/RcCkjfgwwxzK1jJ27kDLMWvkONl/Bak3VI04kSlMd6D+uETMP2f7t7RcFBqoT81PwwZxAFF8487/cCpb+kiSdSwFwR+sRtWZexGV/CcOXMk1nxiI8u7iypVrWJN0EE87GacXf9mHztIx/YpPM27YTq+LjuCY8q7bijBdOgpDp9zNxsrF36Fq1E4MTTovhbNxoFJ0NzcXF6Vw/h0r/1Te9KS7V/DlZ3I5M1DZP+10uBMjflbeMyrux0ZERaNMffR/3OoxD78dRrO5R/CLsVejmMrNSEH78RvRb6NYZpk7YcTy6uTpMxgz9wfUnnsUaYWrcm0wYHf8RtQeay5fzWVkHq7fuIHtyb+ie5RzbUhx4LG/VG8r9Z2qE0mUm5OL1IxMjPnPAaxV3vO0rG2Z2KiqB8o2rInnlf7LUtbTI16/gOUuPhokN2MfWkw9hK/EQVjxDaHNcura/6TPzO7izN4dQv2/Ed3XZWL7BXX9pmqTCG0Iu3F+r88HiIiIHCiK+te9PiRzG0isOy3rYIF4jim1g9IQc1x5rwChHj+8D53HxaNVbJqN/gVj22cjqn6wFV861WdyEz+u3Ijq75rbB7b6QUITrihvFk5R9LUUmp79JNczMf7j76R+nq+EdpD5WMQ4uIEN4nGM34Dpdvq/7o2rWLo4QY7rFemIE9OQrfazw3MAPdK0fWL7NniD5SBsjaf/hp+sBmFvHT9omS9U/ZHyOYZ8TFE/XVDeIyKi4uIvOBALPPZ4BVheL/Y/nLYeKPjzHBYdu2VRSduWh1+Sd+PF9TpO86LX9q//hpen7sdXV9SVcyEJvxEyYQcmnchVNQpsuJONBZ8mYbwnG2GZ1/GbsiorjcAmtu/rdZfh5D48++VZnLEXpEI4TJu3Ewk2gmHXgTM4clPVGLfj7s0/MWKW7d8qIPso+i+7ZPUMP0unjp7CBmfThBSn2zDdZs/iXexfvwFPzU/HLiePSRdFmS6dCEPHbmLpgs0I+9nZfOxh19MxcOKPGHLYlf0r5sdGREXIB0NCHoe/RQsyH5fTfsXTo79DcHwGhGK5+Ll0GAFzfsO+28prTeJx/IL2C35zczBNLCO/R8DGq7jssKqV23DPrjxvszyVLv6aegir3WnLFbkcfHswS1UfK9MiKq9QYHpEFx8Ncvc0RixMR5rdoBDaJWs24sn/nsEJdSeZJgdxfq/PB4iIiOwqgvrXrT4koQ5eudHJNpAtSj3+mfP9C7lXzmPI1B/sn+/fPY/pH29EUJI7++aYvn0tLtCzn0QIs/GzdyP6lEF5w4bb1/DBvJ3YUIThWngX8M3P2U7GtdIeXJyh0ebTI007IOa5eZbt2woNm2HPG/UsZhwSB2tbzU3zbL8bERHp5i85EIsy3iinrMpu4VebbVEv1KlbC1ERnXB8Si/cmBeKGzODsCO8Np4prXxFko+UH49gnar90iCoC45P6iEt37W1+DJQv5HpM3lpg97KR5Zc377YYFi3/AgSVJ2OJcpWxNDwTjgzOxS5wm/lxvTCiUmdsLpHDbSooJp2xUhqeB1CvKqiL1WpGua/2xNXxb+fF4KLH7TCqMdUU7Hl3UT0wj3YatyXv7UxH2evysqbCr9a+M4iHLpgTA3lMyflXroNy4mPy+FpywcB6+g2/vON2EB6CJXr1MZMMV7E8OtVG23LWt2GfvssojZYPLi2gBJlfdEnoCk2ju+hxElfnBnfDjMa+winUCrCb01wsmNv38Y/sMPZBmLJMujY3h+r3+2BEzND5Pic0glL2ldABeUrkrzr+HhtumZH5MWdW9Ej4ZrVoKWSbkNbYYcQrylvt8DMgCqoU1L5WFIPsaZ4b4QA5V1ZaUS8qU4XPZAUVEn5TKBHurSjUGFoQ+7+/RiWqjph8SqFtu2fxo6P+8p5TwrrHtgR4Y+/1/RRTaVUCWNGGo+7DSKsrikI6GUZLsdfrad8UghS+P2M5VctG/ByemyEuLcDhd8W0nWosG/VS1mmRYHrx0ZED4RaLfHTgEdQ2boVeecWNmzcC/9316Dl4l+L0R2y/0PssmPYd0esK6pgVK8WUr17/N1WGnUTcC31F4xKcaKy0CR21iTh9aOqzi+hru37krntdWNmV6wKUNez+UhL2oMRxwpuU+xwKXjxl9AGqV7N4jg+FdpxTSzaIR6oS9QuH8Pnf6jqlFJVEdpcXXuUQEjbaiirvBJdOpDh9LR7Rtf3pWKx/aaV3C75MdvcZhHrqIBW+FVq5whxMLsndrz0CGqo0u+11EPon2jvjhB32uNERERFRPf6180+pIuHEZF009wGEuvPpo2w8QO57hT//urHYv9AU4xqUBa+Vm0wUYF6XFCiVFn0MJ2nBmLjQH/8o24Zy+laxfP9edvxrebTwcSL5HbiA+sBRaU/5FOpX0f83UbCfln9rqtc7mspLv0kOfh24U5EX7TsM5Db0nI/j0Vb+vZZLLe8Q6KYUNrNoe2QMkkJB6EtmPJ2IwRXtOzDu3YwFTOtB8V1SNN2KXFmkeeq1sOGoU9aPfYlCzO/thysFeN2xttdcTFG3g/xuI6Pb4cFQpzU97HuxSEionvtrzkQW6s8Giqr9pSpVhvx/+qLtFFtMb55ddTyk58hVaqML1q1bYOkYXVhMd6XexGrjijrAvF7tR6uIC3VfawG6bxLmT6TlzIFBivc3T5wDhv/ULemSmHQ4O6Y27Y6qhhbliV88OjD1fFizw7Y/W6LAs9WSN9wELNVDa8KDZsj/V+d8UY94/6WQMVqdTH1ve6YU1d1jNdPY8q2HHm9VBnzcZazSnJeJVHdIhx8UbGQ7YVjF6xa2n7l4OZTzuzIx928h+DfuQP+GN0GkWK8iOHXrQ22TmiKrlYt9pQ/zmoOXgpnEniuVyAuzwjCipCGCKhRQYkTb1Sp8RhGDH0OC560DIijR0/anjra5Ba2/iGEu9LpmCadLAmN7eH+6OSrfEVSAk+1b42Mf/dEYtjTeLFeBTwqPf9EiE+/6ugf1hUbOlumyJupZ/Cjsm5y6zcM+dbyztESZR/GnAlKuu1UF62EeG3U8AlEhjyLtJmBmPGUj3CUIuFYTfFeSjilUHsIFSqq04Vx/2S6pEubnA1D+3b9elk43TOr0uoZbA3zRytf40mPGNYV0Kr50/hiXFdMMD0XWX5fPu4yqGCVZUqXswyXWqbfc97hNfusTqi8hPTQFiel9NgELzd8WPhtIV13EvZtQjCOv1kbf1OlbdePjYgeFFXbdcEfkf4FL0IS5eXiyM9HpDtk+2/5UyhV77W7uHYbqPH0M0Jd8SymdntCqndr1asr1U1HP2yGIItKyIBvf/oNLt3XePEIhm5VddaUroIv/9UTy7uY216lylRCz5Ae+KWvn1BaGuVgcYL1Ni8harHV3Z8lfTH0rRdwbkJni+MYLLTj9k97HvHtKyr1adHXJWrpyWeRoqyL1NMiGpVqLrynbiflXkDc/gK9fnbt+OOKELZiB1gT7FUGVq9GPY3BVZUDvJuBUatV7RKvshj1z2BsDamL+sZ2hNAubdWlC34b9hiqy+8I8rHjxyPYpbxSc789TkREVDT0r3/d60PKOnIJR5V1Sd2G2PNmEwRUMz+PvYyv2D/QEFPfeRFftVLeNLqbjhFW/QsVHvNH0vQXEW86T30YAa2fRsyonkh/6zHLWVpuX8CEBMvL9EVZO/dYXkgsDs75P4WjSn/IYKlfR/zdJsJ+9cTFcY3Q07rx5DR3+1qKST/J7ykYddQyzPw7d8RFqS0t9/MY29Jp/3oG/a0GNYuDkmUfxoxxfeR2c6fH0MjY7yq0BRs1bIKVY6378LKxbp/lFX9up2m75AsELPpmhHOHL0Y+g5ZW+Ri3ziDxnLIu8ROOrTNGNKxk7kMV+15rPIbXhTj59Y36yptERFRcuNqyuL/dMsDBxfRAjRbY80Eb9KhkXfuZlarbFJEWPS93cfqyo0EeJ+myfQNuuHU3ylnM3aF6RoFXJXw02PqqLKOyeOu56qorLfOx45eT2oOQRc3rIWWgr4hUfwLxLz9aYOAc5RtgwjM+ygvFn9maz0MNGRKMhG4PF/wNk7J4rdujllNoX7uFdGXVPm8EDegmdTrWkVqGQmP7yafxzybSh5IGfbrjYFgd1LCZvEqg5Yt10UF5Jcm9jRNWvenpP/6BBHUki43GCYF4q7qNHy71MEaENnHqQgjbPJEuHYehIzf/V7jOZY8RTm4/TlZHpHBCFdARe8Jq2QjDEqjRtA0m/E15KSi2x0ZEHlWm/tPYKg7+BVQseHes6M4trP42EVX/tRs/Omx4FbHKdbHOanovo1KVGuCbAeq6Qigq/ziNZS6MIO/68SRSTAOnD6HzC+0QVl55aaVq4BN4SdX5czfjPH5QFa+5+1Ox4LLyQiQOKo7ojrlPqfdUpYQveoS1QB/lpedkYdlh9UPUraZFNCpRG6EN1e2Du/hhf2HbinKddfTNRmiudDyWqeKPsZ3kGVeyth3Ht6o7Cqq3bYGpdbXbJKUaNMZb6llYrl/Cd5nKutG9Ph8gIiKyqSjqX/f6kG7kuHeemLXlOFZa9C88iv+OfhptChyUrOpT7bDUalAzY9/v2Kqsy7Iw/6dLFhcSi9O+HopsDH8b1XuZmk0Q3dVqNjcn6dXXUnj69pMkbD0N9bhfiRr+2v1govL1sORNqwvT7rn6WDotECNq2ukdLN8AY1pYJq4zVyxPWtxN07Yps+hYzDQmtPWHddY+d7h9BzeUVSIiuj/9NQdi/7yNM8qqrDSeMF8SLytRomADtgAfVLQadzuTpW4Iu0GX7VfGUxYjeblY/NUWfH4ix7lOr2MnsFLVBinxZC28ZnvkEHjMF08oq6K756/hntwQkJ0DF5465rQObRvC1gR+bRtVsujIxeVsy6vnFKWE+HXIegrtGzlW6VZbibr+WNjORietwtntW7b/rJ+lfB3fHrVM7407PW2zw1k3HkiXzoShI02qW/79pb37EbLlAq7e6zHMI2fwg7oAKFUNH/Wp5kR5Y1Zsj42IPE8c/AvpjpOTOmBG07Ioo9GyzD1/EkGTf8LSezYY+xA6BzQpMOuHWqmW9TDAotK9jt1pyqrTTuOrQ6oBOK+HMaiTVUPNglU7Le8GDqoGAn88eNGi07Bsk0aIsjGoeE/9/hsWqnvqCkyLaCR2EFe1aCfdPCLU6YWpO8rXxDybdVYOlu0X75g1KoNXOjyqrGspjyZV1ft5C4dOWu3MvT4fICIisqVI6l/3+pAeq1HOsj8kIw0vrszACac6oIR6/KDl3CCNOzVGkIOmT9Mgq0HNG1fwk7rj5PJJrLO4k9AXI162NUDpPn36Wlygaz/JeSSdUCeQEujTvYnNfjBJrScxuJCPGStaQhvOiajwK205l/Cla5aPqnAvTduWtXc7elhMeSzeDBBg8wJCVK6ABhaN0ix8GLMP312ymm6biIiKrb/mQOz5m7C84N0HdR9RVjUZcOnPc/h+WyoWfbcLL3+aiDYfrEHNd7/Fa6nKV4qUq9svjyHPPWLx/Im7Vy/grZnrUOm9DQhdmYaUW5qtb0nWmRsWz169m5qCcsNWoJStZeJvFtPiIOsGPPGIiAaPWLUudbma0JYyaPOEnU7VSj6FbtDn3srGr6m/Y9G2Ixi/aCtejl6PmmPXoOLMdGQo3ymMZ1s3LNw+5N5CZnqGsP1UTF0qbD9mA54Qtv9wZIqDZ7edwy6LkWE/vPGc1UPoioAn0mWhw1DDYwFPIFg9j1BeDuK/3YKq/1yLNp/tw3JnL4jQ2eHjVy2nFW5RD72cOEFRK67HRkT3TqlKNTDizRdxdVYglrTXuEP29iW8PnsfCjkTrU5K45nH7Q2IiqqjlUXn0V1cL2xb4tZVHFNfqp53Ca8N16iXTMsP+MCiHr2N300dhZewI1MdWKUwoFO9Ql004ym79l2wuGNCa1pEowLTI+b9icUOHxlgVuvpeuhss876E0ctZiO8hejpWuFuXnoftEyQxy9cUda03OvzASIiIrOiqX/d60NC8wYYXlU9Ra0B+5L2wv/dlWgUvQtzUq/aeWTFVWRcVVYlpRHYxIn+hTLV0dHi5P0mDp1UVkW/XbHsD6hbC28V1SisNZf7WgpP136Su1fxq8WYuB+6aQ7yq5XHY0V9Ub7L7uJq1p9I2iO04Tbtw+BPtyJwstCGG7MSrZMcNPjdStM23PgNg765oJqC2wtPPdcO39i9GaAuRnUqC3UsXDuVjn5Ra1AxajOGbzrl9uAwEREVrb/kQOzW37JUVx0J/CqitcaVYrdOpyFy1jpUfGc1any4DX1XHMY/NmRi7ZE/ceBKLi7mqB/apT89tu/XqiM2BBXsEM3NvoY1SQfRavRq+H9yEBuuFGxMn8r6n7JWvJWqUtpyCl9cx45UOycHxcHdbCRv2opm736LcqMT0Pw/B/CPFb8iev95rM24gYs3cnHLpeRVBs1qO2ogiwz4ZdduPDd+JUqP/A71Z+0Vtn8YUcnC9n+7hpPC9q/fUb5qS+Z1WPQ7liqNOvauuNRJ0adLZ8PQgTL1sXTYkwWfn3jnfzhwOB0DxZPZD37CR4ezPTpoefS85WlCjUounC0V02MjomKg1MPoHybeIduywLOi7l7MwNANLj151QNKoJS7reICM6644wp+VU9LDB/UtmzsFBNWdwELbh7aZ7vjb/g+yykHxanwDqZbPRvXtsY1qylrWm7ibBHM2XavzweIiIgKKrr6150+JKAKJo38G/5eyeqP8+7ieEYmxvxnIyqPScDrW/7UGLy6ht8tdsjRDRNGlfGknVmED5+1vMOxbMWyKNrLx3Xoa3GBrv0kZ7JxXFmVlCoFi0lE7hO5V85gzmfr8XDkSlSdkIjuS4Q23Lp0xB05j+0XhDbczbuWfcOa3EnT2jZ+dwgJqkdp+LV8BnucmKWsaZ8ALP9bGavv5ePWpSv4dN1O+L+7Bi0X/4pf2AlDRFQsudvldP+5m4m4o5a1UpUnH0VLZV12F/vXb0DtaQexID1He0CsZElULVcK5S1nsdCJntsvgZYvdMcfE1vhwwbWFbYoDyeOpSH4w3iEbLc/aFJCbHwJ2yzMor5prsg8URnPWKTku1iz9TenO/U87no6Bk78AQHrziNVs/PuIZQpK4Rf2RIWV7vp5u55TP/4OzwddxLbrmk3PEv5iPFXsnB33pT9Pzh1nqSzYpsuBaXqNsfWKd2wqnsV1NHIq7lXLmHSZz+g9oJjOHOPrh2oUt7eVZe23Q/HRkT3TqlK9bFkbDMEWRS4+Ug5dBKnlFcPPK8SqKRRB9lbKtmseEvhkYrKanGSkoFlbg5+3v3jJBZaDDrrxQvlNcLY3vJIaXWD8l6fDxAREdlQpPWvm31I5evhi6ie2PtSDTSxvnBXcPdmNr76NhFV/7UPu+0OGJVAmf9TVnVUuXwR9gYUVV+LC3TtJ7lHfT3uuLh/O578cAfGHL6hPfCttNMrlSqYRgvQLU3Laj1cxqKvL+vgUURlONNpUha9BgXh9Ogm+Hv1UgX7C/NyceTnI3h6dALGH+eUxURExc1fbiD24pZjiLNosPogpE1NZV2We2wP+iZcM08TIVTQ9RvUw4K3A3F8Uk9cnReK3Ln9cHp6H8SoH6qgk6LYfpkqdfH+Oz1xZWZXbOxVAy0qWA3yCRV2/PIteF9V+Vs/KwH+TaRtOr90QB/lT4tUidoIqmt1180ff2CqUw0ZT7uJ+Qt/xvKr+cproSHuWwF/79EKOyb1wImZIcid9zKuzhDC7+3aqKV8Rz93sXXpHnxwytwoK1GqLHoENMXG8T1w/OO+wvZDcWOWGH+N8ZzyHU0lvOCtrEqysnHEA0F+36RLo1IV0TP4WaT9uxd+fbsR/l7Tx+oZivm4fPQQnl113iN3j3qXsMwrv52zmMexcIrZsRFRMVP+SYxsZtXNdO4qdiurxct5HDyvrEpKoHxhZ3ko620xlR/wMD7RrIdsL4v+pvypsP2SFuXpTfxi+VyNYuAu1u29YDHdvWuuY0WyHpfPlUJ5i+RWGsOGa4ezrWXbC+Zbau71+QAREZE2z9S/rvQhmZTwQfMuHbB/Rh+cefdpjGpQrsBFS7nn0/H8p8dwUXldsB53tu1zGb9ZDChbtuGsz38zz18tonNTHftaXFCk/SROPXbsLnKLyyQh14+i/5dncca0P16oVrMGoiI6CW24IFyMEdpwn4TgvHDcm9o7OTDvUprW1rBrAL5oqOpNy7uJ6HlbsVT1jF/bSqBinUb4YkIfXP64E5YEVEFDH6uu/TvZwu9tw5dO/R4REXnKX2ogNjdjH55dazktcdmGDRBl1Xny446zqmdtPIQOvZ/Hr+88g9cbPixduVTUs68W5fZLlamEgG4dsHtqHxx/sx6esWhz3MJ/NpifSmr9UPq757JwWFkvXnzwWudqlg/QF45l7uLd+LG4NTwu/44vM8yDsCj/GNZ/1ANf9KyLVg9XwKNliuQeWJVMfHFANYWRlx9mTXoR8SENEVCjAmr5Wgyt2lejElpYnChlYVNK0Y/E3j/p0orQcK/fsAm+GNcLFye1xqjHLMM6Y/sxrFPWi1KbWr7Kmiwz7RzSlXWXFZNjI6Lip0CnUF4e7F6fffG63TI967Yrc7ndwVVHc4VdPIdEi77IsnjqMWXVWZUroIG6XszLxkGXB0+r4pnqyqrkNhKPFLO5Pu4ex2KLK7AewtNtm+LTUMfLiLqW7Z2jh0+4XxehMp6ymL75Fg6ddL1dcq/PB4iIiDR5uP4tTB9SQd6oUs8fU995AX/ODMT8xj4Wg7k3fzuOeabnOljX4062fW5dwM4/lXWJZRuuYd0Kln1FGRfxQ5F0W+jY1+ICXftJapVHQ2VVdg07jimrNmXiJ3tJwYNObT+FHapB4ept2uL4uA4Y37y60IbzRUW3ut0Kk6ZtKYuwgU9Zzhx0+xJen70P+wuRNsv4Vkf/kGdxaFZvHHzpEdRQ9/Dn/onoxCKZcoaIiFz0lxmIvXX8IALmpSNNfYVWqYcxe+CTVs+HuIQdmeqarzTaPGE5xGd2Fnv0exiYwlPbL4EaTZ9BUq+Hldcyi8aaf2X8TZ1CLp/Fp8eKpMXqtlItm+C9GlZThFw+jZ7Tt2Ol5rNL7pHfriBFWZXUqIzONhqBWX9cFZqyOsv8E3vUl3/6+aGDrUeE/p6Fg8qqturo8Jg6zO9izfcHCtVwdMl9lC5tKVWpDqaOboSuymuJWx32znvM30+IOZVzGfjnTvevpza6l8dGRB5w5ghGJV5x8k6CLHx3zGoEtGoFPK2sSir5WD7n/XIWdtgaNL2bjs8OuHIPQy6+3ZFhZ5/vYuvGTBxVXkkqP4zn7TxvTJt1vXgLX2897eJdF+XRqY6Psi47uu2gk1fKe0bWtkxsVLervfzwet+GGNzJ8TIloKplp+i50/jc7XrCOszysXFnqsO7ErTd6/MBIiIibfeu/nWiD8meUg/jjaGt8bZFB9xNHDqprAr1+PP+lpc5Hd2Viq0OTvXTfzyBrerwqF4NL6nbcNb9B7nn8f6aIpixSde+Fhfo2k9SHW1rKKuSXCzblm43zC4m/o5vdQ9U12zPsGwwP/14TRtTQedgd6bqYa2F5TBN21H+SXwzrB78VXF292I6eiz4zYW2qzee6tIFKzta3t2bdsbiCgUiIrrH1NX0A+nWpVOY89l3qDo7DfvU9atXKQS/1Aav2WoYmdzBpWytxosBu785gIVOdog1eMTquvlTl7FVWbXPne0fxz/mHincg9p9vM0D02XqYdCT6lHCHHz++U+Yf85eY+4urv52EJ2XWDza36x6Ocvpdu11uBaKH8a+4Y/mVin67tWzCPswHp2XpiHllu39vpV9DstX/oRGn9vY76JyM1ezkZV75RgGrb9icfd2kfifsH2tjeSexeilmao7QbT44LVnq1tMwyg1HO2ludw/MWfFEaQqL80q4AmLxust7P5ddTWpWlGkyyLw7ZJEzDldmOdylESFAn28leBveZ6LfX+cVtZc9MSTeMviogUDEpYl4a3Dtp4RfRdnDu/GlJ+VlwJ9jo2I7kt3c/Dd6h9RNWor5qReFUprG+5mY8NXyZhiVZFUf6K65RX2T1RCc2VVloXp32Rq/O5NLF2QgpUudvBcO3gQL9t4Fv7FnVsRsltd5zyE5q3ro6nyynk+eKnNwxYdnOd278ULDgauc2+dxkczd+Jb5bVR2+dqW7ZrpCvld2KDrQvMxDBfegBrlJdmRVCXCHXvtwctZ5kpUbcGXnLyNtFSzWvieYsesVv4esdZZd11bTs8irrKuuhuxq949qtM+x1auVexbPFPmGK3I1qf8wEiIiL3FHX9614f0uH4rYi0eV6pxXIa4abd6qKDuu1z/RRC5h5Fmo2mz8VfdiJ4c7bySvQQOrdviHrKK0kZ8VEZ6rtR85GWtBMvbPrTZjv21ukjGLXZzbsJ3eprMbpX/STl8VJjy5m0bh5KsdmWvnV8b4HZB4uTyze0Ljy/izPbd+L9P1Qz1mlwN03bU6ruM/hpQBWLPrVrqYfQ+vP0gm3XzAPov/QEzhQikMv6aA8/ExHRvfFADMQe3LYVL39qtcRswBPvfouKUTsx5vAty0rTywf9X+uGle20RgYqoXFV9SBFLv67cCPe2HUOmVk5uJp9Db+mpiJy5vcI2Co025wMwVL/Z/U8jRun0X/mbixPv4bM9AxMXbBH6YDTc/t3cT7tVzw9+jsEr0xF0plbpobmLeF39u7ajYB1lldIVa9TFeZZXHwQFlzX4got3L6CEVPj0XLxQXyT+icy/xT2X1rO4ftN+xActQbVY9Kw67qN1kGpEsKvqmVhzDSxM1f4rTOn8MXSHfi3q3dEVG2O7//xmOX+ivJysSv5IFqNXoWKY9bgiWmJ5jQydg0ejlyBiu9tw8CkSzieU8RNx5q+Fh2EyExFs7kHhbi5hku3cnBWDMfvtqLxpENI+N9DlmlGDzXKo6E6fIR02HtqspQOzwrbv/Tnn0jathudJ+zAXCFpONp+qeYtMFf9bAvBtT/kNBe49CAWpQjpVkgfv6b+jqlLN8N/dCLG/JKjMS2lN8pYzdSzI34z+m86hV+VfXp9o/FZpkWQLouA4fqfQtpeC/9P9uELYZ8uGQuh3FtCnk8T8vCv2Ky8JSnvh04F7r4qgbLe6vIAuLR3n3RhwV7h+PamHETI8sIOLvth5ACr8Mu7ic8/+wG1p2zF+E2/S+nRGHahU+JR/7OT+FlViOpzbER0/8rHrUvnMeY/G1ExchWaRQt1qljmb0sVynphPXo9Hv5nAoJ337TskPHyw9gXH1VeKErUQa/HLcu5c/t243GhjSSWL5liHbDnIPp/kIDXUgtzAYg1AxKWC+Wc8Ltzlbppb8oRjP/kO9T7+pL5OaCi8jUxs4dFr5fT/No1wXCLdpwBW1f/KJSvOzB1j1inGesn4/a/R9WxyZh0QqNurNoECzqXtaiL7148heAPhfrus32Ya/w9oR05d+VWtBz3A4KTr6Lgdf1FUJdcPobPLTquHkKHp+tZzTJjR4naCG1o2co4dyQTu5R1l9VqgimNrTpbd+9CvQ9+Euq3DOl4jeEvtU0Wb0Ct0Rvx6s83rTpji+Z8gIiIyC1FXv+62YeUex0LpPNKod0jtLfOGi+Gv5uDs2dOYc6CPfiPerZhrwro4K+si8o3xpxnLds+1/74Bc1GfS/szxF8L/afSW0XpQ03/5TFrHcl6jbC1wGWPU5iOyjoZatpYMX22bpEVP1gM4Z/l6r8rtzmHB79HapO+xXfXVPfZusEnftaZPeun6Tec48jyGIcT2lLK3Frakt99j0enZshxIM3KljekHnPNK5mORK657tNCPpODLNbuHorW+6D/SwBTy6/hBtelm3kAtxN0w5UbdcZGwLUaT4fZw7+jGdXWt+1fRcHk/eg/rgEvP6d0KYV2qPy53dxNUtIC5u2IGS7+izgIfztcYu50IiI6B57KDc31+Lyn/z8fNOSl5eHO3fuwGAwoHx5h7eOesgljJ/4E6JdvDitRMVHsODtjnituu1mT27KdtSIPWvZKaehRNV6eNsvHXNVT62vG/AsfguxmGRPdjcdYaP22bmTowq+nPcswoQ1/bb/G3oPS0GC8sqREhVrY8PkNgWmyr248yc8Zd1J6UjD5sh9+0nlhVoWPpqyCZNsXv5XBqPG9sRUi9tmC0echrrrp1Z3QDurwH5bh6GD/cvchyenp8P8aAxzvMqyMH3qZnxwxv5Vd2KDOyjgEaQmnbbzW6JC7p/QSEv4fB16H3TUmf0Q/APqoHZShmpAzcZv3z2PD6dux7TzTp6oVK6Hnyc/U+BOo/T4BDTYqL6a1ZJ13tIvXRY2DEUFy6GgV0Kxtp3yQrD0PyvwWsFbf7V5lcbQYS9gboOC5VLu/m14ZNE52Jw82OKYHO+X0cWdW9Bs2QVc/v/27gM+ijL/4/iXhOSogYD0IiAGUJqgCCJgpBqloyBGTlS4UxTkpAh/ROQQpXgIHnpHPOS4HILS1SgghioiUkUpIk2aIAQSSi6B8J/ZnU12k93NJmwCCZ/36zWvPDO72UzLzm+e3zzP4+Nhc/4cf20bgDwow3XOR7aH4NpoduOMD8El7f5Gt7/7a+YtAwqX0ZC6FzR5k1PKzMfv9Yi6BbRsZ7r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    }
   },
   "cell_type": "markdown",
   "id": "bf8d8004",
   "metadata": {},
   "source": [
    "![Screenshot%202023-12-15%20001005.png](attachment:Screenshot%202023-12-15%20001005.png)\n",
    "\n",
    "\n",
    "### Source: https://archive.ics.uci.edu/dataset/400/crowdsourced+mapping\n",
    "\n",
    "class: The land cover class (impervious, farm, forest, grass, orchard, water) [note: this is the target variable to classify].\n",
    "\n",
    "max_ndvi: the maximum NDVI (normalized difference vegetation index) value derived from the time-series of satellite images.\n",
    "\n",
    "20150720_N - 20140101_N : NDVI values extracted from satellite images acquired between January 2014 and July 2015, in reverse chronological order (dates given in the format yyyymmdd).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07b00b43",
   "metadata": {},
   "source": [
    "## Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "6e47a782",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import accuracy_score\n",
    "import matplotlib as plt\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "from sklearn.ensemble import BaggingClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.cluster import KMeans\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "617c4f79",
   "metadata": {},
   "source": [
    "## Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "3c6fa175",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the dataset\n",
    "df = pd.read_csv('Crowd.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "373e54fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data Overview:\n",
      "---------------\n",
      "Number of rows: 10545\n",
      "Number of columns: 29\n",
      "\n",
      "Data Types:\n",
      "---------------\n",
      "class          object\n",
      "max_ndvi      float64\n",
      "20150720_N    float64\n",
      "20150602_N    float64\n",
      "20150517_N    float64\n",
      "20150501_N    float64\n",
      "20150415_N    float64\n",
      "20150330_N    float64\n",
      "20150314_N    float64\n",
      "20150226_N    float64\n",
      "20150210_N    float64\n",
      "20150125_N    float64\n",
      "20150109_N    float64\n",
      "20141117_N    float64\n",
      "20141101_N    float64\n",
      "20141016_N    float64\n",
      "20140930_N    float64\n",
      "20140813_N    float64\n",
      "20140626_N    float64\n",
      "20140610_N    float64\n",
      "20140525_N    float64\n",
      "20140509_N    float64\n",
      "20140423_N    float64\n",
      "20140407_N    float64\n",
      "20140322_N    float64\n",
      "20140218_N    float64\n",
      "20140202_N    float64\n",
      "20140117_N    float64\n",
      "20140101_N    float64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "# Display basic information about the dataset\n",
    "print(\"Data Overview:\")\n",
    "print(\"---------------\")\n",
    "print(f\"Number of rows: {df.shape[0]}\")\n",
    "print(f\"Number of columns: {df.shape[1]}\")\n",
    "print(\"\\nData Types:\")\n",
    "print(\"---------------\")\n",
    "print(df.dtypes)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a9456f2",
   "metadata": {},
   "source": [
    "## EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "e954163a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Summary Statistics:\n",
      "---------------\n",
      "           max_ndvi    20150720_N    20150602_N    20150517_N    20150501_N  \\\n",
      "count  10545.000000  10545.000000  10545.000000  10545.000000  10545.000000   \n",
      "mean    7282.721268   5713.832981   4777.434284   4352.914883   5077.372030   \n",
      "std     1603.782784   2283.945491   2735.244614   2870.619613   2512.162084   \n",
      "min      563.444000   -433.735000  -1781.790000  -2939.740000  -3536.540000   \n",
      "25%     7285.310000   4027.570000   2060.600000   1446.940000   2984.370000   \n",
      "50%     7886.260000   6737.730000   5270.020000   4394.340000   5584.070000   \n",
      "75%     8121.780000   7589.020000   7484.110000   7317.950000   7440.210000   \n",
      "max     8650.500000   8377.720000   8566.420000   8650.500000   8516.100000   \n",
      "\n",
      "         20150415_N    20150330_N    20150314_N    20150226_N    20150210_N  \\\n",
      "count  10545.000000  10545.000000  10545.000000  10545.000000  10545.000000   \n",
      "mean    2871.423540   4898.348680   3338.303406   4902.600296   4249.307925   \n",
      "std     2675.074079   2578.318759   2421.309390   2691.397266   2777.809493   \n",
      "min    -1815.630000  -5992.080000  -1677.600000  -2624.640000  -3403.050000   \n",
      "25%      526.911000   2456.310000   1017.710000   2321.550000   1379.210000   \n",
      "50%     1584.970000   5638.400000   2872.980000   5672.730000   4278.880000   \n",
      "75%     5460.080000   7245.040000   5516.610000   7395.610000   7144.480000   \n",
      "max     8267.120000   8499.330000   8001.700000   8452.380000   8422.060000   \n",
      "\n",
      "       ...    20140610_N    20140525_N    20140509_N    20140423_N  \\\n",
      "count  ...  10545.000000  10545.000000  10545.000000  10545.000000   \n",
      "mean   ...   4787.492858   3640.367446   3027.313647   3022.054677   \n",
      "std    ...   2745.333581   2298.281052   2054.223951   2176.307289   \n",
      "min    ...  -3765.860000  -1043.160000  -4869.010000  -1505.780000   \n",
      "25%    ...   2003.930000   1392.390000   1405.020000   1010.180000   \n",
      "50%    ...   5266.930000   3596.680000   2671.400000   2619.180000   \n",
      "75%    ...   7549.430000   5817.750000   4174.010000   4837.610000   \n",
      "max    ...   8489.970000   7981.820000   8445.410000   7919.070000   \n",
      "\n",
      "         20140407_N    20140322_N    20140218_N    20140202_N    20140117_N  \\\n",
      "count  10545.000000  10545.000000  10545.000000  10545.000000  10545.000000   \n",
      "mean    2041.609136   2691.604363   2058.300423   6109.309315   2563.511596   \n",
      "std     2020.499263   2408.279935   2212.018257   1944.613487   2336.052498   \n",
      "min    -1445.370000  -4354.630000   -232.292000  -6807.550000  -2139.860000   \n",
      "25%      429.881000    766.451000    494.858000   5646.670000    689.922000   \n",
      "50%     1245.900000   1511.180000    931.713000   6862.060000   1506.570000   \n",
      "75%     3016.520000   4508.510000   2950.880000   7378.020000   4208.730000   \n",
      "max     8206.780000   8235.400000   8247.630000   8410.330000   8418.230000   \n",
      "\n",
      "         20140101_N  \n",
      "count  10545.000000  \n",
      "mean    2558.926018  \n",
      "std     2413.851082  \n",
      "min    -4145.250000  \n",
      "25%      685.680000  \n",
      "50%     1458.870000  \n",
      "75%     4112.550000  \n",
      "max     8502.020000  \n",
      "\n",
      "[8 rows x 28 columns]\n"
     ]
    }
   ],
   "source": [
    "print(\"\\nSummary Statistics:\")\n",
    "print(\"---------------\")\n",
    "print(df.describe())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "61594205",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Missing Values:\n",
      "---------------\n",
      "class         0\n",
      "max_ndvi      0\n",
      "20150720_N    0\n",
      "20150602_N    0\n",
      "20150517_N    0\n",
      "20150501_N    0\n",
      "20150415_N    0\n",
      "20150330_N    0\n",
      "20150314_N    0\n",
      "20150226_N    0\n",
      "20150210_N    0\n",
      "20150125_N    0\n",
      "20150109_N    0\n",
      "20141117_N    0\n",
      "20141101_N    0\n",
      "20141016_N    0\n",
      "20140930_N    0\n",
      "20140813_N    0\n",
      "20140626_N    0\n",
      "20140610_N    0\n",
      "20140525_N    0\n",
      "20140509_N    0\n",
      "20140423_N    0\n",
      "20140407_N    0\n",
      "20140322_N    0\n",
      "20140218_N    0\n",
      "20140202_N    0\n",
      "20140117_N    0\n",
      "20140101_N    0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(\"\\nMissing Values:\")\n",
    "print(\"---------------\")\n",
    "print(df.isnull().sum())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "aa9e2b3d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Sample Data:\n",
      "---------------\n",
      "   class  max_ndvi  20150720_N  20150602_N  20150517_N  20150501_N  \\\n",
      "0  water   997.904    637.5950     658.668   -1882.030    -1924.36   \n",
      "1  water   914.198    634.2400     593.705   -1625.790    -1672.32   \n",
      "2  water  3800.810   1671.3400    1206.880     449.735     1071.21   \n",
      "3  water   952.178     58.0174   -1599.160     210.714    -1052.63   \n",
      "4  water  1232.120     72.5180   -1220.880     380.436    -1256.93   \n",
      "\n",
      "   20150415_N  20150330_N  20150314_N  20150226_N  ...  20140610_N  \\\n",
      "0     997.904   -1739.990     630.087   -1628.240  ...    -921.193   \n",
      "1     914.198    -692.386     707.626   -1670.590  ...    -954.719   \n",
      "2     546.371    1077.840     214.564     849.599  ...    1562.210   \n",
      "3     578.807   -1564.630    -858.390     729.790  ...   -1025.880   \n",
      "4     515.805   -1413.180    -802.942     683.254  ...   -1813.950   \n",
      "\n",
      "   20140525_N  20140509_N  20140423_N  20140407_N  20140322_N  20140218_N  \\\n",
      "0   -1043.160   -1942.490     267.138     366.608     452.238     211.328   \n",
      "1    -933.934    -625.385     120.059     364.858     476.972     220.878   \n",
      "2    1566.160    2208.440    1056.600     385.203     300.560     293.730   \n",
      "3     368.622   -1786.950   -1227.800     304.621     291.336     369.214   \n",
      "4     155.624   -1189.710    -924.073     432.150     282.833     298.320   \n",
      "\n",
      "   20140202_N  20140117_N  20140101_N  \n",
      "0    -2203.02   -1180.190     433.906  \n",
      "1    -2250.00   -1360.560     524.075  \n",
      "2     2762.57     150.931    3800.810  \n",
      "3    -2202.12     600.359   -1343.550  \n",
      "4    -2197.36     626.379    -826.727  \n",
      "\n",
      "[5 rows x 29 columns]\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Display a few rows of the dataset\n",
    "print(\"\\nSample Data:\")\n",
    "print(\"---------------\")\n",
    "print(df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "4f1f1bf0",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot boxplot\n",
    "plt.figure(figsize=(12, 8))\n",
    "sns.boxplot(x='class', y='max_ndvi', data=df)\n",
    "plt.title('Boxplot of max_ndvi for Different Classes')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "4fb145ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Ev0bDhg3ZtWuXwbzQ0FDq1q2LmZmZUWJKxboA165dQ6FQcPLkyeedFSGEEEIIIYT4z3n48CEnT57U18muXr3KyZMniYrSjQkQEhJC37599ekHDRrE9evXGTVqFOfPn2f58uUsW7aMMWPGGC2P0hX8H6bu5kXY1w7EwsOFY68O5s62Pfmmd2xSj4C547AJ8Ed9+y5XPltK1JK1BmncurSh0pThWFX0IuVKFBcm/Q/U8Pbr3nRq646tjSmRF5OYt/gSV6PyH6DJxlrJO318adrQGVsbM6LvpLJw2V8ciXigT+PsaM57/SrQpJESMyWoM0ChAHNTuBULO49lci8x7xhVPBUEBZjgaAsmJvAgCY78mcWZa4aDB9XxU9Cwqgm2lnA/Ucvk6Qs5un896tREXLyqE/TKJBzd/POMc/6P9Vw6vpUHdy4BULbcC9RrNxKX8tX1aY7tWsDx3V8arqgwQak0w9WrOk265B8j8o/1XIjYyoOY7BgvvjQSV6/quac/vJQz+z9n8swldGjXFEtzuHlfy09/ZHIvPu/Bk6p6KWhaTYmjnQKlAmKTtBw+l8Wpv7IHQmkSaEKAtwnO9gq06PbZp/MW8vvu9aQmJ1K+YnU69v0IV8+8y3Pn5iX2bFrArWvniL9/m5d7jSOo3Zs50h3ZvZpDPy8nIe4eoz6YQPdXu2JtZcaNu1q2HM7gblzeZXnBx4TmNU1xslOgNNHl8+BpDScu5z6oSz1/aFwVJkxbwC/bs49/484FH/+LEYbHv367kbg8cWyOhS4g4qnjP2LkWHr1eQsrlYLrd7LY9JuaO/mUp1oFJS1rm+Fsb4KJCdxPyOLASQ0RF7NHQjJRQJt6ZtSuZIqdlZbPv1jIjz+u42FSIu4+NWjVcxLOHnmX5f7tSxz66QvuRJ0j8cEtmncLoW6LfgZpsjI1/L5jAefDt/Mw8T5WNs7YOZYj7t5V1KmJuHlVp9mrk3ByzzvO2bD1/Bn+xPns+QIN24/EzfuJfbb7a66c3kXc3b8wM1NhaVOGtOQE1GnJeFaoTvs+k3Apl3eMu7cusXfzF0RfO0d87G3avR5CwzaG59hvP33N+Yhd3I/5CzMzC7z9a1DGyZ2z4btISU7Ey686XfpNxC2fcxng9NFQfv3xC2Lv3sDJpTzteoygWr1W+uUzhrci7v7tHOuZmVug1Wrx8qtO17cm4ubpV2CcnT8uIPbODZxcy/NSj+EGcaYPa51rHBMTJRWq1KLb2xNwL59/jJN/7OLndQu5f+cGzq7laf/aMGrUb5lr2l2bl/LT2s/xqliN+NgY/T4zZlnMzC3RarMoX7E6nd+cmO99BuBMeCi7NmQfmzbdRxBYNzuOOjWZ0I1fcO7YbhLjY7G0cSBTk06GOgVX70fncj7X/7mw9fx57Klz+eWRuD51Lv91Rncum5pZ4OJVExt7N66e3VWi95knHdn5NQe3zcPdpzqJcdGoU4xzD0hKuIepmQptVhZZWRrcvGvQolv+1/+Zw+s5H76F2GhdWVzKv0BQh1EG1z/AqYM/ELF3GcmJ9yjj4sekTxYQVLscFmZw+wGEHs/ifj7fAWpUUFDNW4Gzve7/mDg4cCaL6OyvGbzX3oQy1tndW7VaLQsXLmT1mnUkJibi4VuDl3pNomw+95p7ty5xYNsXRF8/R0LsLVr3DOHFVv3yTP/Hr4v5/af/YfroXHb3rkGLHpNwzmef3Y++xOEdX3D3hu64BHcNoXZzwxjpaQ/5fcfnXD61m9SHsbh5VcG1nD8XTx8gNTkRzwrV6dD3I1zzKcudW5fYu2kBtx/dN196fRyN2hreN69dCOfQz8u5ff0cSfH38Kk7mQF9X6ZlAxtsrEy4dD2dZZtiuXkn75HtmtWzYchrzjnm9/7wOhka3edg5xb21K9mRTkXM0xM4H+fL2TTxvWkPEzE278aPfoX4n52ZBc7nrifdXjd8H52MHQdh0LX8eDebbK04OTmh0PZ8kRd/IO0R9dMm9cnUTafa+be7Usc3P4FMdd1x6Zl9xDqteyXI11S3B32b/6UxeMOkpaWho+PD9OnTycwMDDfMvydmJg+n67gRXXs2DGaN88eJe7x89lvvvkmK1euJDo6Wl/JBvD19eXnn39m5MiRfPnll3h4ePDFF1/w6quvGi2P0mL9D5N4+gLnhk8rVFpLH0/qbV/Cg0MRHKrXmcuzF/PC/ybg1iV76PkyDWpSa/X/uPXDVg7WeYVbP2yl9pr5jHzXj56dPZn39WUGjDpObFw6/5tWHct8Rtg2NVXwv4+r4+ZiwUezIuk16ChzFl7kfmz20Pm21qYsmlMLTaaWNfszOXoxC3Mz3YfistBMktO09G6uxDyfn3xS0+FQZBYrdmWy5JdMTv2VRacXTajgln1jCPBS0La2CYfOZfHdPlj09VLC966kVY+P6PL+j1jalOXnpW+Trn6YZ5zov45SsWZ7Oryzis6D12Jdxp2fl/YnOeGOQToHV3/emHiQ2i0GYWZuRfPun/Dq8B+xsi3L9m/eJj0t7xi3rxzFv2Z7Xnl3FV2HrsXWwZ2fvunPw6diANy9cYa/Tmzg/REhdH6pATv+0PD1Dg0PU7W82do0/32mht/OZPLNzxl8uT2DE5ez6BykxM8je5/5uJnwx59ZLPlZw8E/taz7fikHf1nJK29OZPDU9djYO7NiTn/Uqcl5xslIT8OhbHna9hiFjX3OD1eA00d+5ucfZtGs07vM+HI3vXt2YdKkccz9/hZJqVoGvGSOeT49dFLVsO+khq+2pTN/YzoRFzLp1swMf8+ctzNPZwXVvWH+gm/4efNKgjp/RNdhumOzoxDHxq9mezq+u4rOQ9ZiU8adHXkc/z4fHaTVgFBmLzlCv7feYvPBdOZvSCUpRcu7nSxQ5VOelDQtuyMy+GJTKp+tSyX8Tw09W5hTuXz2tda8thmNXjBj88F0Rkz+hu++XcHkSZOY8r8NWNs5s37BW/mWJSM9lTLOnjTtPBpru7K5pvkj9BtOHVxLyx6TeGPcDtx9a3HrylG8qzSh58gfsbIry9bF+e+zW5ePUql2e7oMWUW34brzeevi/jyMz95nt66EU71xL7oPX0f1Bh2JuxuFVqvlrXHfYWNflm/nvo06NZ+yqHXnWKvuo7Gxz70s1y+EU79lLwZOXEffMcu5F32Nw7vX0KHXBwz/eD229s58M3MAafmcy9cuneSHBaOp07gTo2Zupk7jTny/YBRRl0/p0wz7eD0ffXmAj748wKSv9lM/WPdh3bxTf4Z/sg47e2eWzCggzsWTfP/FGOo07sTomZuo07gT330xmuuXT+vTDP9kHZO+2s+kr/bTuss7mJlbANDzncnY2jvz1fR38o1x9eJJVs3/gHpNOvLhnA3Ua9KRlfPHcO3S6Rxpr18+y+E9G7At48yta3/Spd8Eo5VlwoID1G2m22fNOvRn6FTdsVk6e0C+95nrl06yZuFoagV1Yvj0zdQK6sTqhYbHZuOyj7h09jA9Bs2mRpM3SH34AE16Kh0GLMbathDn8hXdudx58Cq6DXt0Ln9teC7fvhJOtaBedBu+jlfeXU7CvaucC1tDgw5jS/w+A7rPgNO/r8Pazpk7N87Tqsck3vjQOPeAWs36kqVJJyszg1pN+2Bt68ymr/KPcfPyH1Su3Z5Xh35Lz5G6fbZp0dsG++zC8Z85sHkm9du8R+8PtvDue0NpXKMM2w7GsnJ3FslpWl5rZpLv55l3WYiM0rJ6fxbf7skiMUXLa01NsLHMTrNydxZfbMvki22Z/BgGH378DStWrKBLv0m8PWEDNvbO/PC/t1AXYp+16Jr3veax21dPc2zPMhQKE8r716f3GN1x2bgw/32mSU/F3tmTxp3yPi6hqycS9edhXuo7h6GfbMVcZUXEbxto0eV9Bk3WfTav+rSAz+ZH983W3fP+bE5Xp+LmVZn2b0wEoEeHqrRvZsfyzQ8ImR9NfFImE991xUKVfyUsJTWLgVNuGEyPK9UAARUt+PVwEhO+iGba3CWsW7OSSZM+4sPZa7Ar48zCTwq+n62Y/wH1mnbkw083UK9pR5b/z/B+VsbRlU69RvDBzLX0C9mImbkFkeE/8WKbgbw5Tnf8132e//HXPDr+wV3yPjZpyQl89+nrmCjN+Oabb9ixYwfjxo3Dzs4u330knk1wcDBarTbHtHLlSgBWrlzJ/v37DdZp1qwZx48fR61Wc/XqVQYNGmTUPErF+pGsrCxmz56Nn58fKpUKLy8vpk+fniNdZmYm/fv3x9fXF0tLSypXrsznn39ukGb//v3Ur18fa2trypQpQ1BQENevXwfg1KlTNG/eHFtbW+zs7KhTpw7Hjh0rdD4vTp5PzJZdBScEvN95jbSoaCJHz+Dhn39xY/kGbqzcRIVRb+vT+L7/Jvd3H+bKnCUkX/iLK3OWcH/vETq0duPb9VH8Fnafq1EpTP/fn6hUSto0c8kzXvtWbtjZmBEy/Rxnzidy556a05GJXL6WfYPs3a08d++rmfn5BW4/gOq+Jhw8m0XEZS33EmDrkSzMTCHQO+8b9/W7Wi7c1HI/EeIewtGLWu7Eg1fZ7HUaVDbhxF9aTv6lJTZJy9YN39L3rUF069wGR7dKNO85C01GGpdP/JRnnBavz+WFhr1w9qhKGZcKNH31Y7TaLG5dNnypvImJEksbZ/4M30idVu9RpV5XnNwq0eK1WWjS07iUT4xWveYS2KgXzuWq4uBSgWbdHsW4ZBgjQ53M7tVjqPvyZF7r8Qrrth7ifJSWu/FaNh3KxMwUqlfI+3K+dkfL+Sgt9xMgLgmOnM/iTpwWL5fsdb7breHklSzuxWuJT9ayZvUqBg0aRJPgNrh6VqLbO7PISE/jVFje5fGsUI2XXv+A6g3aY2qW+ysuft+5ijrNulIvuDstX3ThwFkTfv8jksN7fmD9/gzMTKFmxbx/wPkrOotz13T5fJCk5fdzmcQ80OLjalh+c1Po2cKM0JNa1q/9ls6vDaJCtaeO/8m8y9Ky11xeaKQ7/g4uFWjaLe/jb2VbFgtrZ1rUtWfPcQ1n/tLlac0eNeamCmr55/0t8crtLM5ezeRunJbYR63v0bFZ+Lpnl8fH1YSz1zREXtMQFvot9dsOomqdNtQMrMRLfWejSU8jMjzvsrj7VCe464dUrdsepWnux+X21ZP4VW9JxWrB2DqU4+alP3B08yMrU4OTeyVa99Id/4vH847Tts9cqjfuRdlyVXF0rUCLnrp9duOJ8/mVd5dStX5XHN38OBv+C03av0PKwzg0GWq6DJhFhjqN00fyjlGuQjXa9hxLtRfbY2qa+y8WfUYvpVbjrriU88e1fGVSkxNBq8Xe0Q238v68Nmgm6elpnDicd5xDv3yLf2BDWrzyDi4eFWjxyjv4vdCAgzu/06exsXPErkxZ7MqUxdbemRNhO7Cysad1l/dwL+/Pa+/NeBRnR55xDu78Dv9qDWn5ykBcylWg5SsD8X/hRQ7+8m2OOLb2zvyxbxOePlVxdi3Pi8GdeWPIdDLUaUQcyjvGgZ+/p3L1BrTuMgDXchVo3WUAlQJf5MDP3xukU6el8N3CcfQcOImUpATKVwykWv3WRimLXZmy2Ng7cyrsZ6ys7WnZ+T3cyvvT492ZZKSncTKf+8zvv36LX2BDmnfSHZvmnd7BL6ABv/+qOzYZ6WmcDd/Fy6+NwbdyHS5EbOfFdsMoU9aHW5f/oFUv3b05v3O5zRtzqRakO5cdXCvQvIfuXL75xLnc6dG57OTmj5NHZdSpiYAWa3u3Er/PZKiT2btmDK17fUxqcgLu3tWoVKsNZT1K/h5QIbAZ58O38mK7ofgGBPMw4S5t3phNRkYaf0bkHeOlvp9Ro0lvXDyr4uhakVavfQJZWURdzC7L8f0reKHBqwQ27I6jW0Ve7diCld+uZ/P6FdxPhJ+OajFT6n4cz8u2P7Qcv6Llbryux9ovx7QoFODjkr1OqhqS03RTarqW3375lrcGDMK9ShtcylWi01uzdefJH3mXx8O3Oq26f8gL9fPeZwDpacls/mYMCoUCW0cPypT1xtmjEm3fmI0mI40/j+Udw827Os06f0iVOrnHyEhP49KpUJq88gGefvVwdPHi7q1L2NiXJf7+LVw9K/HqwILvm54VqtHutUefzXmUpVL1prR6dQQv1NU1vnRuV4XNu+M5eiaFGzEZfLnmHipzExrXyv+Vj1ogISnTYHrSjG/ucCD8ITdi0gnd+h1tuwykw8ttqVK5kv5+diyf+9m+Hbr7WZsuA3ArV4E2XQZQOfBF9u3Ivp9VqxvMC7Wb4uLhg4OLD7Exul4l5hZWlC1XifZv6o5/5NH8r5kWr35IQL28j/+R0G+wc3Sj/ZszqV69Op6enjRs2BAvL69899HfjcLM5LlM/0b/zlI9g5CQEGbPns1HH31EZGQkq1evzvHuM9BVwD09PVm/fj2RkZFMmjSJ8ePHs379egA0Gg2dO3emWbNmnD59mrCwMN555x39sO69e/fG09OT8PBwIiIiGDdunNEeoC/ToCb3dv9uMO9e6EHs6wSiMNV90XdoUJP7uw8ZpEmIOINKpeToiTj9vAyNlpNn4wmskvevcI1fdOLsn4mMHuTHtm8b8u3CuvTp7oXJE2dZUH0n/rycxMcfBjC6qxJbSwVmT9Q5MrN0FWfPsoXvluLjqsDJDq7f0/0iamIC7o7wV4zu/6QHN0lNukf5ykF4OOrWUZqa416hHneunyh0HE1GKlmZGlRW9gbzE+5f57uPg0hJusetS0dIjL2hj+FRoR4xRYmRnnuM3zZPw7tqMFWrNcTZyYETZ/7SL8vMgmsxWsoXYZ9VcFPgbKfrqpybuHs3SYq/T+PGjUl/1CPZ1Mwcn8r1iLpU+PI8TaNJ5/a1c/gFBmGtAjsrBZduZuHq05DY26fIzIKr0Vl4uxb+1lTRw4Sy9gquxhiW5ZUgMy5EZXHuwk0exN6jWu3s96Y/0/F/fGwsczv+TfgzdCB21iacOp/dzTUzC67czsTHrfDl8S9nQtkyJvx1O/vLyNXoLPzLKbHQ3iY58R41ajfGrQzciNUdl/L+9bj917MfFwDPinW4fuEID+5cJTH2JilJ90hOuIdPQFNAt8/K+dUj+moR91mWBounzmeAxNibPEy4h7uPrrucpbU9pmbmeFeux43LxSvLk+Lu3eRhYiwAVja6fJiamVOhSl2uXzqZ53rXL5+kUvUgg3mVqwdx7WLuebsbfZUMdRo1G76sv9+bmplTsWrdPNcBXetr5WqNcsbJJW8P7t4kMf4+0Tcv8WLzLigUCl2MgDpcvXgqR/rHrl48ReXqhjGq1GjE1YuGMX5cNp2AWk1wditPZmYGDs7Z7/gs6bIA3Iu+SkZ6KjWe2me+hTg2/oGGx8a/WhDXH92bsjIzycrKxNTMnAf3dOeyV+UglGYqbl+N0J3LFesRfa349+bHEh/cJPWh7jx7fL6X5H3m0JZpeFUJxqGsF1mZGdg5Gh6bkrwHXL8QRkriPewcPbn9VwQ+Ac0wNTXHs2LRr//MJ67/TE06d2+cw7tyYwBsLcHGUsGV6Ezu3jipS5MFUffAM/dG1VyZKXWPy6Sl5/7ITWLsTeIe3KOcf2P9PFMzc7wr1ePmleLfa35ZPY3y/nVIS0kwuNeZmpnj6VeP20XYZ0/TZmnQZmViaqYbOTnu3k0eJtzH2rYM1y8e18fxqVKPqBK8b3p6euLkYMmpi9kv59ZkQuSVNCr7WOS7roW5gi8neLLoI08+7O+CT7ncK6XpKTEkxt+nWm3dPSMjE8zMzPELqMPVC3nfz65dPEWVQtzPHou7d53kxHtkZWko51sLyL5mbhXzmrl0ai9uXoFsXjKMhg0b0rlzZ319QPw3yTPWQFJSEp9//jkLFy7kzTd1z5xUrFiRxo0bc+3aNYO0ZmZmBi8z9/X15fDhw6xfv54ePXqQmJhIQkICHTp0oGLFigBUrVpVnz4qKooPPviAKlWqAODvn/9zZMWhcnVGfee+wbz0u7GYmJlh7uyAOuYeKjdn1HdiDdJoNbov9A/i0w3mx8Wn4+qS9w3Vw82S2tUt2LX/Dh9MPYOnhyWjBvmjVCpYufa6Pk3nlyxZt+UmiScyeaWBKQ2rmBCXlMXpR89IJ6eBff4/iKIygxGvKFEqQauFn49lcfVRRdpKBSYmCpLTdP+nJN0DwNzKCesnRvW3tHHiYVzOZ/3ycvSXeVjbu1LOL/uG7lK+BsE9Z6FJT2X/+nGkqx+yaeHrvDZmOxbWDljaFi3GkZ91MTz9s2NcOrmD+7cieXXYBmwsdV8+4xMeUuaJ9ZLTtAbPk+VGZQZjupthqoQsLfx0JJMr0bl/EUlK0J03CpUjiUnZ823snYjP5fnIwkpJiicrKxMbe2csHv2elJSqRWXlhDr5vv5/B9uCyzK+t0pXlizY+ruGy7eyK9bVK5hQzlnBwi0ZpD86/vZlnCA1exuWNk48jC98Wf54fPyfODYuXjVo/tos7J19UGXpupTtXTuMgLaLMLcsoytPihbHAspjYQ6T3rTC1ER3bDb9ls7Fm9nl2XsiAwsVvNowiY0LoFszJ85GwV+Pelha2TqT+ODZjwtA/TYDUacmsWzaSyge/eYa2KgHlWp30KexsnEiqQjn8+Gf5mFj70r5So1yLHt8XYbv/QEv/zq4elYCin+OPS0pQRenfMVA3Mpn329t7Z1zfdZXv178fWztDF/HYWvnpL82nnb6j18BqB/c1WC+jZ1TgXFs7A3j2Ng7kRSfM87j2OrUFF5s9soTZXEi7l50/mV5KoatvROJT8Q4/vsv3LwayegZa7l59TyAvsu5McoCcOboTgB9d3B93uyciYvNO87DPMrzeP+oLK3x8qvJni2LafJojIfbf0VwJ+o0ZZy9AbC0Ldq5HLYj73MZIPnReVbWsxqObpX080viPnP50WdAl/c3kPwgEgBTc0uD9UryHvDjF28B8MuqkTTqMIoqdTpkxyjCPju0/TNs7F3xqqwrS2pyHNqsTKweXVdWjz6P1ZlmpCZlnyPJaVrsrRXo2j4LFlxdwcNUuJqz97wuDrpjE69xwuyJ7wDWds4k5HOeFca5ozuIiYqk7WsTOX14E0qlYUNJcY+LuYUN7r61OLLzKxzdKpCZoivknZuXcHLz0aezsXMivphleVLZsrquz0+3NickZeLsmHfV4fadDL5ae5+o6HQsLUx4uYkdHw9144PPbhNzX2OQVqPWPRRfq7IrcQ+zePjoO5utvRMP7ud9P0uMv49dGcPr365MzvvM7aiLfDbhDdLTdY8jvtxnBs4e2c9uW9sV/5qJv3+DE7+toX6rt5j10SBOnz7NJ598grm5OZ07dy7WtsU/k1SsgfPnz6NWq2nZMveBXJ62ePFili5dyvXr10lNTSU9PZ2aNWsC4OjoSL9+/Wjbti2tW7emVatW9OjRA3d33a/Lo0aNYsCAAXz33Xe0atWK7t276yvgT1Or1ajVaoN5GdoszBRF6GigfeqD6fEL0Z+Y79CwFtUWZT+3ffXzVY/SPLUthSLfzzkTBcQnpDPny4tkZcGFKw9xdlTxeldPVq69TutmLpibKcjSQreO5fjxd93Gzl7TUsffhNPXsm/gBX2cqjNgyc5MzE3B101Bm1omxD/M4vpdLRdP/EStqVPJ0GjRaqHd21/rss9TlRvtE/ujACf3L+XKyR10ePdbTM1UXDqxnYObJuuXt3trMQAtX5/D5i97c+HYFmo0e+tRQQoX48S+pVw+uYNXBn2r/3XaxyGed8a0QBmia9H5frdGn/WnFbTP0jNg0fYMzE0VVHBX0K6ekrgkLdfuaLl29icifsk+Bz75TLfPTl4Hsyd/5NBq9S1LRVXeCWrXcaHn8eOYmVtw+NKTGdfqj4VCkfO0za0sX2xKx9wU/MqZ0L6BKQ+StPwVncX9KzuY8+UnTM/UHf+XHx//XPNdtOPf8YljU8UThrZvqk/zzU+6X/a1Wi03z/9EhdpvZJengO2r0+GzdamozBT4e5rQKcic2MQsDuz9iTN7p2OigD1LFHQbuACAPy4paNsAUtRwKQZ0+69QRclV5NFt7Px+ApmaDJSmZgR3m8yetRM4e3gtDi4VqFq/C4+iFPqaidizlIsndtB1iG6fXYjYzr712ddMx4G6a+be7SsMmLhOP1+rzetYFc7psO1sX5UdxzegIQBd+k02SKfVagsuy1PLtWSf/8d/387GZVP0y1w8KgBgV+bpZ/EKvmZyLH+0D44f+okNT8ToP3YRAP6B9bF3dDFIX1BZcsbIzteBn39g06pZmJlbMH5AE94dpxuQL+cWn70sQI7ylPXQffbZPrXPtGhz3q9zBnqqOLq8nfh9O5tXTEGr1aLJSOfqn+EARB7dSKVaHbh3KzI7X4W8aI7vXcrF4zvoMiT7+r8QsZ39P2afU56VdOdZk65TctnCs99nzhz6lsPbZqA0s2DV1IZ0G/z48+xpz34PiDy6jdA1k8nK1JCpyaDhS4MJ++UrgrtO4MjOL7GxdyGgfhdAW+gQx/Z8w4XjO+g2NLssVb0tOH78OKbmFpgoYEeELm1WluG1qCh8nZoXKysIKK/gh/1ZZD76LfLKqe2EbZuiT/Pp/5YAkJah4Mlqr7YY++zMkW38/N1HZKSnYWpmked1obvPPFsMgPPh27h38zyZmnSWTGyK4tH3v6p1WnM/OrvnmlarpTiBvJyhToXs9bc96tWY61fIfI7NpSg1l6Kyv7deuHaP2SM9eKmxHfMWbuDmmexHJ33rfwzoei2cjsqudGsLdW3mvP4fn0PhB39i7ZJp+vlte03m1x8ms3v9dNy8XsiuXBf0RaMQtFot7t6BNOs8ioAACAgI4PLly6xZs+YfVbH+pwxe9k8gFWvA0tKy4ESPrF+/npEjR/LZZ5/RsGFDbG1t+fTTT/njjz/0aVasWMGwYcPYuXMn69atY+LEiezatYsGDRowZcoUevXqxY4dO/jll1+YPHkya9eupUuXLjlizZw506B1HOB1hSO9lYXrI6W+cx+Vm+EXFvOyjmRlZJAeG69LE3OftFsxHKzbWZ/Gq393ABwdzImNy261drA3y9GK/aT7celkarRkPdEj9/rNFJwdVZiaKjh0NJb7D9I5HZnAku+u0vyVOgAkq7VUtMq+qK0tdK3WBYl7NObEnXgtznZaggIUXL+rxbViczZtqsnOCF0rtpmprsKuTrlPsjr7y2hqciyWNgW/IP7UgWWc3Pc17Qcux8m9MgDeAc0NRgfP1Oj2S7o6GSf3SsTf17XQpz6MxdK24Bgn9y/j+N6v6fjOcpw8KuvnH/7jBF9Om4nCRPfMsbmZOW+320bSzd9Yv/sbun0YgYmJEmsLBQ9T8/+Q0KJ7Hg20xMRpKWuvGyn82h0N5fyb4+ShK09wDRMquOo+5O7du4+HdfY+e5j4ABu7gsuTm+g4+DUhgwXjX6V9nwlUedTN1tZKgTrlASor3XZtLHStDwWVJTZRV97oB5m4lFEQXFPJX9FZvNioBR+9V5fMLN3yjPR0tn8Nblb3ad7Rhc+369ZPfRiLVSGOzakDyzix92s6PHH8Aa7E6EajfSz50f73qliT2/ezR6W0sVSQlFLwsdGVR8vt2CxcHUxoWduMC9ea4eAWyJAuFoSd03DsvG7HnL1yn3IeLtTw0VWsU5JisbYtQt/Jp/hVb4GFpR3Vm7zGC/U7kZKi+2JUqVYHju1Zoq9Ypz6MxaoQ18zxfcs4tvtrOr+3HOdH57PvC81xHZN9zfzxyxcAdOg7BXtHN/385MRYrJ/xHAOoXLM55Sro4uzf+iVXzukehzExMfzi8DAxNker55NsyzjnaJ1+8vwPqN0Cr4q6OAkP7rB4uq6VLynhPnYOZQ3XKShO/NNxYrGxdyKgTnNG+VXTz4+9e0sXu2YTg/RJhShL4lMxkhIf6Nexti8DgCZDdx9bOG0AAH/s30T4b1uZ9e0JTEyUxSoLYFCe+Ad3WfzJo30Wf8/gB4kn18mNTa5xdMcmoHYLyvtln2dpDxNZOKUnrV6bQcTeb7Bz9AQKf29+fC6/8sS5DI/O50cjdx8N/ZIbF3Xn2dMVrOLeZyysdc8vPf6MWfu5rgX+9OENnDmymVFfnMHERFmse4Bf9Ra4+9RgzWe9qN7kNarUbkfYL1/hUbEutYLfJHzX1wTU70JKUixWhYgRsXcZR3d9zauDV1C2XBX9/FtxlnTp2ongrhPxrtoY5aM2AkszjcFnsZVKQbK64EpP/coKGlVVsOZAFvcSsud7VWlBWU/dsbGxhIpeuu8AyYn3sS2T/XmWkhiLtd2z7bNKNVuQnvaQX36YikaTznef6Y5L9LWTRF8/xcnffmD4/86Q+rB49+aK1Vrg5lMD0HWtN9PGsXx2P9LTknFwLqdPl5yU/7VZkNsP4MHD7H0eF6f7cCtjpyT+iVZrOxtljlbs/Gi1cOWGGjdnU+zcGlDJIfvcfqW5FbPD4ODJGMp6OujnF3RvtsvtfpaQfT+rVrc5Pv7Z94Bb93XlcnDx5ti+b2nXW1fpTk569uP/mI19WZzcDRvHKlSowK+//lqs7Yp/LnnGGl13bEtLS/bsyf/VVQAHDx6kUaNGDB48mFq1auHn58eVK1dypKtVqxYhISEcPnyYwMBAVq9erV9WqVIlRo4cSWhoKF27dmXFihW5xgoJCSEhIcFg6mHiWOhyxR85iXNLw25rZVs3JiHiLFqNruIUd+Qkjo3rkXIlSj/ZVquCWp1JvZrZNzpTUwU1A8tw9s+834FxJjKRcu6WBg0J5T0suR+rRqPRkpqaycmz8Tg7qrgVnca9RF233/JlFSQ8Gt/MxAS8XRTcvFf0XxKVj744K82sMbf1pl4NH2ydvHFw9cPStiw3Lx7m9qPXcWRq0on+KxxX71r5bvPUgWUc37OIl97+hrKe2V9wzVU22Dt76ycHVz+sbMsS9edvxN29grVdWTI16dz+Kxy3AmKc2L+MiD2LaD/gG1zKVzNY5uxVjwbdF/Liq5/z4qufU6HZTO7HxtG+a3/a9P8RExMlShPwcVNwo6j7TAHKR2OEmamssXX04rWXfGnewJeb6RWxsXfm8rnD+uQaTTrXLoTj5Z9/efKiyYI0jRkaE1vCf99NYiokpmjxK2fC3WtHcPKogdIEfN1N8nz2O7+ymD46/jceWLIp3I2tEe5sjXAn7KYfjk5l2fLLYb7br6vEFvb4n9yvO/4v9/+Gsk8dmwwNxCdnT3fitCQkZ1Gjqgcqa92HtdIEKnoouRZT9PIolQpMza2xLuNFBV8fHMt6YeNYAWu7slw7/zuPf6DP1KRz41I4HhWe7biArrthZpYGazsnHFy8cXTTnc8JD26AVpf3TE06ty6H4+6bf5zje5cRHrqIV979BlevJ64ZCxvKlPXG3tmLk7+t4uaVo1jZOnDvdvb9U6NJ5/qFcMr7PXtZVJY2OLp4cSR0FVfPH+Htcd9jW8aZi2eyB1DSaNL5689jePvXzHM73n41uXTmsMG8i6d/x6eSLm8WltY4u3nj7ObNlfNHsbF3xNbemYtnDK+ZK+eP6dfJNY5/TYO8AVw4cxgf/5oGMZzdvLl64TgKhQKNJvsHTo0mgyuREfhWqpFnDN9KNbhw+qkYpw/jW0lX/sDawXz46SbGztnA2Dkb+GD2j5goTfHwqcrImRsxMVEWuyw59lnkUWzsHHX3mbOGx+ZqIY7N5bOGx+bS2d/x9q+FytIaZ1dv/VSuQiBWtmX569xeov48hG9gC925fCUcd5+Cz+VjuxbR6Z1vcH3q+je3sMHe2YtTv63i1qUjdB3yPVa2Zbl5KTtfJXGf8a4aTPdR2+g+cgvdR27hzfFbMDExxaV81Ud/K4t9DzC3sMHBxVt/D3By98PKrixRF35HYaJEq9WSqUnn5pWCr/9je5byx69f0WXQUoPrHyBLYU6a1pYTf+wmMUX34/jDVC0V3E1wKV8T0H0H8CoLN3N/ekDvxcoKgqoqWPdblsEPnKD7PLNz8sbOyZum9Xzw9PLDxr4sf0VmjzmTqUnn+sVwPCs+2z5TWdgQ2KAT70zZzjuTtzJw0hYsrR2wKeNK1bod6fPhFrRZmdy8HI5HAfssP+YWNjiU9cahrDdly1XBp0p9rO2cuH7hGFVq63pZajTpXPszHK9i3Dc1WfAwLXu6fPkysXGpVK+U/TiIUqkb0fvCtUK0fDzB28Oc+KRMlKZWqKzLobIux3tvVOOVtoHYOzhzKuLJ6z+Dy5ER+FbO+37mU6kGF566z/z5xP3MwtKasm5e+snZ3Q9ru7KkPozX/3j4+JopV4zPTQDPirV5cOeqwbxr165Rrly5PNb4e1KYKZ7L9G8kLdaAhYUFH374IWPHjsXc3JygoCDu3bvHuXPncnQP9/Pz49tvv+XXX3/F19eX7777jvDwcHx9fQHdy8qXLFlCp06d8PDw4MKFC1y8eJG+ffuSmprKBx98QLdu3fD19eXmzZuEh4fn+T41lUqFSqUymOdUM0D/t5WvJ3Y1qpD+IIG0G9FU/mQUFuVcOfXWhwBcX7IW78G9qfrpOG4sW0+ZBrUo/9arnHhjtH4b1xZ+S4O931NhzEDubN+Da8eWOLdsyOZfY+jT3Yubt1O4cTuVvj28UKszCT1wV7/uxJGVuRebztff6m4qW365TbcOHgwf6MfGn27h6WFJn+5ebPjpln6ddVtvsXhOTfp09yLDRjdQ2QteCv64kEVZe2gcYEKGBs5ez64kvtLAhKRU2HtK9wU/KEDB7QcQl6RFaQJ+Hgqq+yr4OTy78nLkQhadG5hw+4GC2CQFr7zal+9Wfs3NFG/M7bw5se9rTM0s8KuV/fzovnUfYm3nQv2XdPvn5P6lHAv9nBavz8XWsZz+mVAzcyvMVLr+0Ud+mo1XQHNsynjgW6014aELMDExxdWrBnvXhWBqboH/EzH2rPkQa3sXGrysi3Fi31KO/vo5rXrNxc6hHCmJj2KodDHMLWxweuJ5PYUqgx83b6TP612wOaokNhGaVtPts9NPvJO6a2MliSmw+7jul+UmgSbcjtWNoq00gUqeJtSsaML2I9m/PHd4UUm1Cias2auhrIuSpi/3Ze/WJZR188bR1Zv925ZgZm5BjYbZ5fnx6w+xc3ClbQ/duwQ1mnTu3tJVlDI1GSTG3eX29fOoLKxwctU92xjU7k02fD2Ocr6BKFOa0rq+PQ3rV8GjVi9eamxGhgZOXsnOV49gMxKStfwarvsxKLiGkpv3tTxI1JWlspcJtf2VbDmkW56egcF7o7VmCrr26Mvqb7+msVr3Q8iJvY+Of83ssuxdqzs2Lz5x/MN//ZyWvfI+/mE/zca7anNsHDyIi7nF6rU36f/WG1iWTyIpXUHL2uaka7ScuJTdze31luYkJGv5+YjuXaAtaptx824m9xO1mJpAFW8ldSuZsvG37MpT5DUNreqYEf9Qi7pNX37/+Ws6B/sQc9ObX779GlNzCwLqZZdlx8qx2JZxpWnn0Y+ORTr3ox8dl8x0Hsbf4c6N85irrHBw0R2XitWac2TnYuwcPLB1rkj5Sg25ELGdCtVaEht9kWO7v8bM3MLgmevQHz7Ext6FRh10cSL2LOXIL5/Tto9unyU/cT6bP9pnBzZO40LET3To/yX3rh/mt+2LsbJ1wNWzMmG/rsBMZUH1BtkxNn3zIbZlXGjdfbT+HHtcGc/MzCAx7g7RUbqyPD7Hdnw3jTNHfuL1YV+isrKhXrNX2bP1axyc3XHz9GfP1iWYm1tQq1F2nDWLxmHv4MLLr+nO5cbt+rDo477s276UF+q04FzEXi6dO8KQSdmjgoNuQMvwA5up17QzltZ27Nn6jb7yuFcfp312nK9CsHd04eXXRgLQpN0bfDXtTfZuW0pgnRacjdjLpbNHGDI5Z5xjB7dQoWod9mxdjouHL2XdvNi15RvMVBbUaZwd4/uF47F3dKFjrxEANHvpDb6Y0o/dW5dRrW5zzhzbx4UzfzB8qu6xHwtLazy8DMf7KOPoxp2bl7kfo+t9U9JlCf9tM3WadsHS2o5925fg5KarCO/brrvP1HziPrNuse7YtOupOzZBbfrw9fS+7P9pKQG1WxB5fC+Xzx1h0MTsOBdPH0KLlrJuvngHNOVY6FfYOZXHxasau9fo7s1Pnsu7Vuvu/4/P5eN7dedymzfyP5cvHv+J9m9/ibmFDZXrvcrxPYuxKeOBo5tfidxnzC1sDJ7ZtrNRYOvgRmz0ZeLu6o7NHztL/h5Qtd4rHNn5JSYKE/xqtiX0hxDMzCz0z1sD/Pr9WKztXWncURfj2J5vCNvxOe36foZdHvusdvBb/Pr9WFy9AnH3qcWm7dd5840eOPqlkZIFjaoqyMjUvU7rsQ71FSSlwoEzunkvVlbQNFDBtiNZJKToerkBpGt0P3g+qbqPgqt3FdRvqbtvOrr44Ojqze8/6+5ngS9ml2frsrHYOrjSomv2PtPfazTpJMXdISbqPOYWVji6eKOysMGlXPaxqdPybX7/aT5pKboGiJ3fh2BqZkGVutkxfvl2LDZlXGnSKTtGbMwTMRLucPfmecxUVjiU1R2Xa+cPotVqcXTxJfb6NRQKEzKzNFha2XHn5kUO/LQkx31zwxLdZ3Ob7tmfzfduPXnfvEv0dV1ZHt831WnJPLiT3dtqw/Zj9O7WgBu3YrmfaEWXlvao07M4dCL7TS9DXnfmQYKGNT/HA9CtjT2XrquJvqd59Iy1LT7lzFm2KXssn/5dHWlc24Y5y+/Qov0b7Ny0FPdy3ji5erFzk+5+VveJ+9m3C8dTxtGFTo/uZ8Evv8Hnk/uxa8syqtVrzplw3f1s5LRV+nW2rf6cgFqNcXBy496ddJzcKhB18Q9eeLEj925dJGyn7vgH1M/eZ9tX6K6Z4C45r5mszHSScrlm6rV8k+/mvM7hXxbTosJLnD59mvXr1zNtWuFeiyv+faRi/chHH32EqakpkyZN4vbt27i7u+f6rrNBgwZx8uRJevbsiUKh4PXXX2fw4MH88ssvAFhZWfHnn3+yatUqYmNjcXd3Z+jQobz77rtoNBpiY2Pp27cvd+7cwdnZma5du+bo7p2fJse26v8OmDsegBvfbuJ0/xBU7mWxLJ89UmjqtZuEd3yHgM9C8H6vN+rbdzk3cjoxm0P1aeLCTnCi9ygqTx1B5anDSLlygxO9RvK/tO4kJGYw6j1/bG3MiLyYyMhJp0lNza7wuJa1IOuJRtK799WMnHSGYQMqsnJBXe7Hqvlx+y1+2Jh9o/7zUhLjZ5zj3b6+eJdXEv8QLt3W8oK3CXX94VYs/LA/Uz8SNehGjtY+8SyMmVLBS3UV2FnqRqm8nwhbwrIMPogjo7RYmmfR9AXduy3v1xlATGwau9ZPIz01AZfy1Xl5wDLMVTb6dR7G3zboxhd5ZDVZmRns/n64wTGo3WoIdVu/r1sn4Q57V48mLSUeC6sy2Dt5k5YSxy8rB+PiVZ0OA5dhbpF3jHNhuhih3xnGqNt6CPXavE9uflj3E/aOHnRs1xQLFdy6p+XbXRqDfWZvbbjPzM0UdGigxM5KN/Lm/QQtGw9mcvZadmW8fhVd8/Xb7XRPoXWo9Q4LndL57ttpJD9MxLNCdd4auxSVZfZD1wmx0fpnvgCS4u7x5UfZgzcd+mU5h35Zjm+VegwYr3vlTvUGL5PyMJ59W79i68qp3P9gIh9/MhtrSzNu3NOy7Jd00jOyy1LGWmHwKJS5mYLOQUrsrRVkaOBegpZ1+zIMflh4Ws/eA4hLSOOXzdNQPzr+7Qt5bHY9dWzqtBpC3UfHJjnhDnseHX8zizJccauGp18TerV1w1KlIOpOFku2p6F+sjw2Jmi12Xk1N4WuTVWUsdGV5258Fqv3qDl5Ofta23wwnXb1zena1Jw32w7kcyc106ZOJSkpAXefGnR/f7lBWZLiolE8MRz/w4S7fDuzs/7/8N3LCd+9nPL+9XltpK4y0qrHRA5t/5zd66aSnBSLlW1Z3CvUJubaSdbN64ard3VeGfTUPosz3Gdnftfts19WGu6z+m2H8GK79x+lWQPApi/76pdvXT4BE6Up5f1q0mf0MlSW2TESYg1jJMXfZfHk7EdnDu9czuGdy/GpXI+3xunKEr5PF2PF7OwYABuXTUGjScerYnUGjluKxRPncvxT57JPpVr0HjqXnT9+wa8/foGTqxdvvP8ZXn6GLSmXzoYRHxtN/eCuOLt5k5GuZtOKj0lNTtTFCfnGIE5cbDSKJ7ql+1SqRe/3P2Xn+gX8+uMCnFy96PP+XLyf6M6sj3M/msHjv+b44V/YsOwTUpIT8farxnvjv843hm/lmrw5fA471i3g53ULcXYtT7/hnxp0l3yavZMbNnYORi1L3aaP91kaW1dOIzUlkfIVqtP/qfvM08fGu1ItXh8yl9ANX7Brwxc4unrRa4jhsUlLTWLn+vkkPIjB3MKesp4BJMVFs/Hz13D1qs4r7y576prJ/VzeucrwXK7XJvtcPntYd55t/srwPDu4aTKZGnWJ3WeeZuvgjpWtI7vXTiUtxTj3gIeJ9zEzsyArU8OFiJ9w865Bl/cMYyTGRcMTx+XUoTVkZmawY8Uwg/y+2G4oDV/SlaVy7ZdJS47jyK9fkZJwlzKu/pQtt4BXmpTDwhxux8LaA1n5fgeo7afAVKmga5DhaxkPnsvi0LnsdL6uus/CfZHQsN1AMjLU7Fw9ldTkBMpVqEGvkctRPVGehAdPfZ7F32Xpx9n77Ejoco6ELserUn36fmD4YxFAvVYDOXVwDTcu/cEPn76Km08NXh2Sy3FRGB6X72dnx4jYs5yIPcvx9KtPj+G6GOrUJA5tn8fD+Bgsre0JqNMalYU1O36YTlpyIp4Vq/PmmJyfzSZPfTZ/NTn7s/n3ncv5/dF9s3+I7rP59tVzLJ/9pj7NvOkDSE8YysBefbGzs+NylJrpS+6Q9kQ3fecypgafz9YWJrzTzZkydkpSUrO4ejudyV/GcOVG9g/FbYN0b5eZOsQdrXYQ5cpoWLdiOvHxCXj7VWPIhKfuZ/ejDa6ZCpVr0m/EHH5au4Ad6xbi7Faet0YY3s+SEmL5buF4EuPuYW5pi7NHJV6o34mTB9dz5Ndv8PCtQc9hhsc/MZfjv2J69rE5ums5R3fprpneo3XHxt2nOl0HLeTAlnl06PAlnp6ejB8/nk6dOvFPIs9YlxyFVlsCT++LUrPDrHLBiUrAzHZLjB6jba+gghOVACvLvN+JXJKUJgWnKa4HcRkFJyoB1auUzm9ux07n/cx+SXFxURWcqATcupVSKnGqVi5gyPwSkFaI5xtLgnOZUgmDlXkRu+I/A4WidPaZmdL4ZQHIyDT+DU2TWTpf5m7eK52n3p5uLTUGO5vS2WcZpfNRQ3xi4Z/XfVaebqXzHSClaD2kn4mDbelc/xs2RBWcqAQM6Oth9Bi3HuT9DvKS9FbzUgljFHt98v6R1ZhaXDv9XOIakzxjLYQQQgghhBBCFIN0BRdCCCGEEEKI/6B/60Biz4O0WAshhBBCCCGEEMUgLdZCCCGEEEII8R8kg5eVHGmxFkIIIYQQQgghikFarP9hSmO0boCQne8YPUZwp+5GjwGgdKpYKnHQGn+0Tq3yjtFjAMTbv1wqcTp4HDF6jETfukaPAWCn3l8qcTItKxg9hjI52ugxAO47NyuVOGaZaqPHSDWzNXoMANMs44+kD5CmNP7o8xrMjB4DoInVjVKJY3PnktFjpJT1NXoMAI2pZanEMc00/lDaqSp7o8cAsEyLN3qMTNPSecvFC5fHlUocB4v5Ro/xQrnSao2tVkpxxN+ZVKyFEEIIIYQQ4j9IoZSu4CVFuoILIYQQQgghhBDFIC3WQgghhBBCCPEfZCIt1iVGWqxLSL9+/ejcuXOh00+ZMoWaNWsaLT9CCCGEEEIIIUqHVKyfkzFjxrBnz57nnQ0hhBBCCCHEf5TCRPFcpn8j6Qr+nNjY2GBjY/O8syGEEEIIIYQQopiee4t1cHAw77//PiNGjMDBwQFXV1eWLFlCcnIyb731Fra2tlSsWJFffvkFgMzMTPr374+vry+WlpZUrlyZzz//XL+9tLQ0XnjhBd55J/t1UVevXsXe3p5vvvmmwPysXLmSMmXK8Ouvv1K1alVsbGxo164d0dHZr5/JzMxk1KhRlClTBicnJ8aOHYtWq9Uv//rrrylXrhxZWYavX+rUqRNvvvkmIF3BhRBCCCGEEOLf4rlXrAFWrVqFs7MzR48e5f333+e9996je/fuNGrUiOPHj9O2bVv69OlDSkoKWVlZeHp6sn79eiIjI5k0aRLjx49n/fr1AFhYWPDDDz+watUqtmzZQmZmJn369KF58+YMHDiwUPlJSUlh7ty5fPfdd/z2229ERUUxZswY/fLPPvuM5cuXs2zZMg4dOsSDBw/YvHmzfnn37t25f/8++/bt08+Li4vj119/pXfv3iW014QQQgghhBDi2SmUJs9l+jf6W5SqRo0aTJw4EX9/f0JCQrC0tMTZ2ZmBAwfi7+/PpEmTiI2N5fTp05iZmTF16lTq1auHr68vvXv3pl+/fvqKNUDNmjX55JNPGDhwICNHjuTKlSssXbq00PnJyMhg8eLF1K1bl9q1azN06FCD56Hnz59PSEgIr776KlWrVmXx4sXY29vrlzs6OtKuXTtWr16tn/fjjz/i6OhIy5Yti7m3hBBCCCGEEEL8nfwtKtbVq1fX/61UKnFycqJatWr6ea6urgDcvXsXQF/pLVu2LDY2NnzzzTdERUUZbHP06NFUrlyZBQsWsGLFCpydnQudHysrKypWrKj/393dXR87ISGB6OhoGjZsqF9uampK3bp1DbbRu3dvNm7ciFqtBuCHH37gtddeQ6lUFjofarWaxMREgykrM73Q6wshhBBCCCFEXkyUiucy/Rv9LSrWZmZmBv8rFAqDeQqFbudnZWWxfv16Ro4cydtvv01oaCgnT57krbfeIj3dsMJ59+5dLly4gFKp5NKlS8XOz5PPUBdGx44dycrKYseOHdy4cYODBw/yxhtvFGkbM2fOxN7e3mC6efmHIm1DCCGEEEIIIYRx/S0q1kVx8OBBGjVqxODBg6lVqxZ+fn5cuXIlR7q3336bwMBAvv32W8aOHUtkZGSJxLe3t8fd3Z0jR47o52k0GiIiIgzSWVpa0rVrV3744QfWrFlDpUqVqFOnTpFihYSEkJCQYDB5+skz2kIIIYQQQgjxd/KPe92Wn58f3377Lb/++iu+vr589913hIeH4+vrq0/z5ZdfEhYWxunTpylfvjy//PILvXv35o8//sDc3LzYeRg+fDizZs3C39+fqlWrMm/ePOLj43Ok6927Nx07duTcuXNFbq0GUKlUqFQqg3kmyuLnXwghhBBCCCH+re+Ufh7+cS3WgwYNomvXrvTs2ZMXX3yR2NhYBg8erF/+559/8sEHH/DVV19Rvnx5QFfRjo+P56OPPiqRPIwePZq+ffvSr18/GjZsiK2tLV26dMmRrkWLFjg6OnLhwgV69epVIrGFEEIIIYQQQvy9KLRFfXhYPFeNOx4olTghO98pOFExBX/V3egxAJTeFQtOVBK0WQWnKW6Ie3eMHgMgvu7LpRLH4cqRghMVU6Jv3YITlQC7s/tLJU6mZwWjx1DejzZ6DID7VZqVShyzTLXRY6Sa2Ro9BoBpVukMYJmmtDZ6DA1mBScqAc6pN0oljs2doo3n8ixSyvoWnKgEaEwtSyWOaWaa0WOkquwLTlQCLNPijR4j01RVcKIScDdkXKnEcZgz3+gxtIrSaY0tV6lawYn+psIbN3gucesdMv53wNL2j2uxFkIIIYQQQggh/k7+cxXrl156CRsbm1ynGTNmPO/sCSGEEEIIIUSpUCgVz2X6N/rHDV5WXEuXLiU1NTXXZY6OjqWcGyGEEEIIIYQQ/3T/uYp1uXLlnncWhBBCCCGEEEL8i/znKtZCCCGEEEIIIUBh8p97MthopGL9D9O2V1CpxAnuZPwRu/cP/tHoMQCqRW4plTgOCdeNHsMso3RGBH5g6loqcTSVmho9xg1NeaPHAKhSJfdHTEraA2tPo8coY+du9BgAGhPzUokTb+Js9BhJGVZGjwFgYVo69wCNxvhfDyyUxh+tHeChhVOpxNGUszB6DOuk0hmxP8nKpVTiKLTGH30+QVE6j/mVsVQaPUZMlofRYwBUe/OVUolz1dT416YJxn9jixCPScVaCCGEEEIIIf6DFCb/zoHEngdp+xdCCCGEEEIIIYpBKtZCCCGEEEIIIUQxSFdwIYQQQgghhPgPMvmXvlP6eShSi/XMmTOpV68etra2uLi40LlzZy5cuGCQRqvVMmXKFDw8PLC0tCQ4OJhz584ZpFmyZAnBwcHY2dmhUCiIj4/PEcvHxweFQmEwjRs3ziBNVFQUHTt2xNraGmdnZ4YNG0Z6evbALlOmTMmxDYVCgbV19mAZmzZtonXr1pQtWxY7OzsaNmzIr7/+miM/GzduJCAgAJVKRUBAAJs3by70fuvXrx8KhYJZs2YZzN+yZQsKhZzMQgghhBBCCPFPVqSK9YEDBxgyZAhHjhxh165daDQa2rRpQ3Jysj7NnDlzmDdvHgsXLiQ8PBw3Nzdat25NUlKSPk1KSgrt2rVj/Pjx+cabNm0a0dHR+mnixIn6ZZmZmbRv357k5GQOHTrE2rVr2bhxI6NHj9anGTNmjMH60dHRBAQE0L179ojXv/32G61bt+bnn38mIiKC5s2b07FjR06cOKFPExYWRs+ePenTpw+nTp2iT58+9OjRgz/++KPQ+87CwoLZs2cTFxdX6HWEEEIIIYQQwlgUJornMv0bFakr+M6dOw3+X7FiBS4uLkRERNC0aVO0Wi3z589nwoQJdO3aFYBVq1bh6urK6tWreffddwEYMWIEAPv37883nq2tLW5ubrkuCw0NJTIykhs3buDhoXv9wGeffUa/fv2YPn06dnZ22NjYYGNjo1/n1KlTREZGsnjxYv28+fPnG2x3xowZbN26le3bt1OrVi19mtatWxMSEgJASEgIBw4cYP78+axZsybfMjzWqlUrLl++zMyZM5kzZ06h1hFCCCGEEEII8fdXrMHLEhISAHB01L0j8OrVq8TExNCmTRt9GpVKRbNmzTh8+HCRtz979mycnJyoWbMm06dPN+jmHRYWRmBgoL5SDdC2bVvUajURERG5bm/p0qVUqlSJJk2a5BkzKyuLpKQkfZkex3qyTI9jFaVMSqWSGTNmsGDBAm7evFno9YQQQgghhBDCGBQmJs9l+jd65lJptVpGjRpF48aNCQwMBCAmJgYAV1dXg7Surq76ZYU1fPhw1q5dy759+xg6dCjz589n8ODB+uUxMTE54jg4OGBubp5rLLVazQ8//ED//v3zjfvZZ5+RnJxMjx498o31LGXq0qULNWvWZPLkyUVaTwghhBBCCCHE39czjwo+dOhQTp8+zaFDh3Ise3pALq1WW+RBukaOHKn/u3r16jg4ONCtWzd9K3ZucfKLtWnTJpKSkujbt2+eMdesWcOUKVPYunUrLi4uJV4m0LXCt2jRwuBZ8Lyo1WrUarXBPE2GElMzVZHjCiGEEEIIIYQwjmdqsX7//ffZtm0b+/btw9PTUz//8fPQT7fk3r17N0eLb1E1aNAAgMuXL+tjPR0nLi6OjIyMXGMtXbqUDh065PnM9rp16+jfvz/r16+nVatWBstyi/WsZWratClt27YtcOA20I3Cbm9vbzD9tnV2kWMKIYQQQgghxNNk8LKSU6SKtVarZejQoWzatIm9e/fi6+trsNzX1xc3Nzd27dqln5eens6BAwdo1KhRsTL6eJRud3d3ABo2bMjZs2eJjo7WpwkNDUWlUlGnTh2Dda9evcq+ffvy7Aa+Zs0a+vXrx+rVq2nfvn2O5Q0bNjQo0+NYz1qmWbNmsX379gKf0Q4JCSEhIcFgavrKh88UUwghhBBCCCGEcRSpK/iQIUNYvXo1W7duxdbWVt+Ka29vj6WlJQqFghEjRjBjxgz8/f3x9/dnxowZWFlZ0atXL/12YmJiiImJ0bc+nzlzBltbW7y8vHB0dCQsLIwjR47QvHlz7O3tCQ8PZ+TIkXTq1AkvLy8A2rRpQ0BAAH369OHTTz/lwYMHjBkzhoEDB2JnZ2eQ7+XLl+Pu7s5LL72Uo0xr1qyhb9++fP755zRo0EBfJktLS+zt7QHd895NmzZl9uzZvPLKK2zdupXdu3fn2g2+MKpVq0bv3r1ZsGBBvulUKhUqlWG3b1MzzTPFFEIIIYQQQognmSj/na3Hz0ORWqwXLVpEQkICwcHBuLu766d169bp04wdO5YRI0YwePBg6taty61btwgNDcXW1lafZvHixdSqVYuBAwcCuu7RtWrVYtu2bYCuQrlu3TqCg4MJCAhg0qRJDBw40ODVVkqlkh07dmBhYUFQUBA9evSgc+fOzJ071yDPWVlZrFy5kn79+qFUKnOU6euvv0aj0TBkyBCDMg0fPlyfplGjRqxdu5YVK1ZQvXp1Vq5cybp163jxxReLsvsMfPzxx2i12mdeXwghhBBCCCHE34NCK7W7f5SP15ROi/Woh1OMHmP/4B+NHgOgWuSWUonjkHDd6DHMYq4aPQbAlSqdSyWOnTbO6DFuaMobPQZAlYyTpRLngbVnwYmKqUxq0d548KweWjiVThzsCk5UTEkZVkaPAWBhml5wohKgyXrmsU0LzUKpLjhRCbAloVTiWGiSjR7DOim64EQl4IFDxVKJo9BmGT1GgsKx4EQloIw21ugxYrI8Ck5UAqqdW1Uqca7W6Gb0GCYY/xwDqFyxdL5rGMO5V1o8l7gvbN37XOIak/E/OYUQQgghhBBC/O38WwcSex7+nW/nLkVRUVHY2NjkOUVFRT3vLAohhBBCCCGEMCJpsS4mDw8PTp48me9yIYQQQgghhPi7UZhIO2tJkYp1MZmamuLn5/e8syGEEEIIIYQQ4jmRirUQQgghhBBC/AfJM9YlR9r+hRBCCCGEEEKIYpAW638YK8uc7+I2BqWT8V+1UVqvwToT0LlU4tQ8t8HoMTRlfI0eA6Di6fWlEkdbxvivQTHzKJ1X+phq0koljuefvxo/iKKUfnP1qlYqYdxu/278IKnGf9USgNa+dF5RprEy/ivK1ia2N3oMgA6epfOKKvuYP40e40K5VkaPAWChKJ37ZlyG8c+zaokHjB4D4IGj8R8LrHbV+N8zALJcjf9aRwDfK6FGjxHvVdPoMXT+ua/bEiVHKtZCCCGEEEII8R8kXcFLjnQFF0IIIYQQQgghikFarIUQQgghhBDiP0harEuOtFgLIYQQQgghhBDFUKSK9cyZM6lXrx62tra4uLjQuXNnLly4YJBGq9UyZcoUPDw8sLS0JDg4mHPnzhmkWbJkCcHBwdjZ2aFQKIiPj88Ry8fHB4VCYTCNGzfOIE1UVBQdO3bE2toaZ2dnhg0bRnp6eo78zJ07l0qVKqFSqShfvjwzZswwSHPgwAHq1KmDhYUFFSpUYPHixQbLv/nmG5o0aYKDgwMODg60atWKo0ePFnq/9evXD4VCwaxZswzmb9myBYVCfiUSQgghhBBCiH+yIlWsDxw4wJAhQzhy5Ai7du1Co9HQpk0bkpOzR0OdM2cO8+bNY+HChYSHh+Pm5kbr1q1JSkrSp0lJSaFdu3aMHz8+33jTpk0jOjpaP02cOFG/LDMzk/bt25OcnMyhQ4dYu3YtGzduZPTo0QbbGD58OEuXLmXu3Ln8+eefbN++nfr16+uXX716lZdffpkmTZpw4sQJxo8fz7Bhw9i4caM+zf79+3n99dfZt28fYWFheHl50aZNG27dulXofWdhYcHs2bOJi4sr9DpCCCGEEEIIYSwKE5PnMj2Lr776Cl9fXywsLKhTpw4HDx7MN/0PP/xAjRo1sLKywt3dnbfeeovY2Nhnil0YRXrGeufOnQb/r1ixAhcXFyIiImjatClarZb58+czYcIEunbtCsCqVatwdXVl9erVvPvuuwCMGDEC0FVY82Nra4ubm1uuy0JDQ4mMjOTGjRt4eHgA8Nlnn9GvXz+mT5+OnZ0d58+fZ9GiRZw9e5bKlSvnup3Fixfj5eXF/PnzAahatSrHjh1j7ty5vPrqq4DuoDzpm2++YcOGDezZs4e+ffvmW4bHWrVqxeXLl5k5cyZz5swp1DpCCCGEEEII8V+3bt06RowYwVdffUVQUBBff/01L730EpGRkXh5eeVIf+jQIfr27cv//vc/OnbsyK1btxg0aBADBgxg8+bNRsljsZ6xTkhIAMDRUfcu2qtXrxITE0ObNm30aVQqFc2aNePw4cNF3v7s2bNxcnKiZs2aTJ8+3aCbd1hYGIGBgfpKNUDbtm1Rq9VEREQAsH37dipUqMBPP/2Er68vPj4+DBgwgAcPHhhs58n8Pt7OsWPHyMjIyDVfKSkpZGRk6MtdGEqlkhkzZrBgwQJu3rxZ6PWEEEIIIYQQwhhMlIrnMhXVvHnz6N+/PwMGDKBq1arMnz+f8uXLs2jRolzTHzlyBB8fH4YNG4avry+NGzfm3Xff5dixY8XdZXl65oq1Vqtl1KhRNG7cmMDAQABiYmIAcHV1NUjr6uqqX1ZYw4cPZ+3atezbt4+hQ4cyf/58Bg8erF8eExOTI46DgwPm5ub6WH/99RfXr1/nxx9/5Ntvv2XlypVERETQrVu3fLfj6uqKRqPh/v37ueZt3LhxlCtXjlatWhWpTF26dKFmzZpMnjy5UOnVajWJiYkGkyZDXaSYQgghhBBCCPF3kls9R63OvZ6Tnp5OREREjsbQNm3a5Nl426hRI27evMnPP/+MVqvlzp07bNiwgfbt25d4WR575or10KFDOX36NGvWrMmx7OkBubRabZEH6Ro5ciTNmjWjevXqDBgwgMWLF7Ns2TKDfvG5bfPJWFlZWajVar799luaNGlCcHAwy5YtY9++fQaDruWW37y2P2fOHNasWcOmTZuwsLAoUplA1wq/atUqIiMjC0w7c+ZM7O3tDaY9G2cWOaYQQgghhBBCPE1honguU271nJkzc6/n3L9/n8zMzCI13jZq1IgffviBnj17Ym5ujpubG2XKlGHBggUlvg8fe6aK9fvvv8+2bdvYt28fnp6e+vmPn4d+uoB3797NsSOKqkGDBgBcvnxZH+vpOHFxcWRkZOhjubu7Y2pqSqVKlfRpqlatCuhGFM9rO3fv3sXU1BQnJyeD+XPnzmXGjBmEhoZSvXr1ZypH06ZNadu2bYEDtwGEhISQkJBgMLV8NeSZ4gohhBBCCCHE30Fu9ZyQkPzrOUVpvI2MjGTYsGFMmjSJiIgIdu7cydWrVxk0aFCJleFpRapYa7Vahg4dyqZNm9i7dy++vr4Gy319fXFzc2PXrl36eenp6Rw4cIBGjRoVK6MnTpwAdJVlgIYNG3L27Fmio6P1aUJDQ1GpVNSpUweAoKAgNBoNV65c0ae5ePEiAN7e3vrtPJnfx9upW7cuZmZm+nmffvopH3/8MTt37qRu3brFKsusWbPYvn17gc+dq1Qq7OzsDCZTM1WxYgshhBBCCCHE85RbPUelyr2e4+zsjFKpLFLj7cyZMwkKCuKDDz6gevXqtG3blq+++orly5cb1B9LUpFGBR8yZAirV69m69at2Nra6gtnb2+PpaUlCoWCESNGMGPGDPz9/fH392fGjBlYWVnRq1cv/XZiYmKIiYnRtz6fOXMGW1tbvLy8cHR0JCwsjCNHjtC8eXPs7e0JDw9n5MiRdOrUST/qW5s2bQgICKBPnz58+umnPHjwgDFjxjBw4EDs7OwA3UjctWvX5u2332b+/PlkZWUxZMgQWrdurW/FHjRoEAsXLmTUqFEMHDiQsLAwli1bZtDFfc6cOXz00UesXr0aHx8ffbltbGywsbEp8k6vVq0avXv3NmpXBCGEEEIIIYTIz7O++qo0mZubU6dOHXbt2kWXLl3083ft2sUrr7yS6zopKSmYmhpWdZVKJZD92G9JK9KeXLRoEQkJCQQHB+Pu7q6f1q1bp08zduxYRowYweDBg6lbty63bt0iNDQUW1tbfZrFixdTq1YtBg4cCOi6R9eqVYtt27YBul8w1q1bR3BwMAEBAUyaNImBAwcaVHaVSiU7duzAwsKCoKAgevToQefOnZk7d2524UxM2L59O87OzjRt2pT27dtTtWpV1q5dq0/j6+vLzz//zP79+6lZsyYff/wxX3zxhf5VW6B7Z1p6ejrdunUzKPeTsYrq448/NtpBFUIIIYQQQoh/i1GjRrF06VKWL1/O+fPnGTlyJFFRUfqu3SEhIQavQe7YsSObNm1i0aJF/PXXX/z+++8MGzaM+vXrG7xVqiQVqcW6MBVBhULBlClTmDJlSp5pClpeu3Ztjhw5UmAsLy8vfvrpp3zTeHh4sHHjxnzTNGvWjOPHj+e5/Nq1awXmJT8rV67MMc/b25u0tLRibVcIIYQQQgghnpXCpOivvnoeevbsSWxsLNOmTSM6OprAwEB+/vln/eO90dHR+jG0APr160dSUhILFy5k9OjRlClThhYtWjB79myj5bFIFWshhBBCCCGEEKK0DR482OD1y0/KrSHz/fff5/333zdyrrL9/TvV/81FRUXpn7XObXrylxMhhBBCCCGEEP8+0mJdTB4eHpw8eTLf5UIIIYQQQgjxd/NP6Qr+TyAV62IyNTXFz8/veWdDCCGEEEIIIcRzIhVrIYQQQgghhPgP+ie8buufQirW/zDK0jr3tVlGD+GQcN3oMQBqnttQKnFOvtDN6DFa7pxg9BgA56v1LpU4jopYo8eI1rgZPQZAJdOHpRLnRuXc39dYkswV6UaPAZBVSsN8xFc0/jmQlGVbcKISkKYxL5U45kqN0WME2iYaPQbATYVPqcRJKO9s9BhltHFGjwEQk+FaKnE8TW8aPcYlx4ZGjwHgmnXb6DEu+3UwegwA37uHSyXOOR/jf55ZmpTOG3hK55uG+LuTnyiEEEIIIYQQQohikBZrIYQQQgghhPgPksHLSo60WAshhBBCCCGEEMUgLdZCCCGEEEII8R8kg5eVnCLtyZkzZ1KvXj1sbW1xcXGhc+fOXLhwwSCNVqtlypQpeHh4YGlpSXBwMOfOnTNIs2TJEoKDg7Gzs0OhUBAfH58jlo+PDwqFwmAaN26cQZqoqCg6duyItbU1zs7ODBs2jPT07EF3rl27lmMbCoWCnTt36tNER0fTq1cvKleujImJCSNGjMiRl+Dg4Fy30759+0Ltt379+qFQKJg1a5bB/C1btqBQSPcLIYQQQgghhPgnK1LF+sCBAwwZMoQjR46wa9cuNBoNbdq0ITk5WZ9mzpw5zJs3j4ULFxIeHo6bmxutW7cmKSlJnyYlJYV27doxfvz4fONNmzaN6Oho/TRx4kT9sszMTNq3b09ycjKHDh1i7dq1bNy4kdGjR+fYzu7duw2206JFC/0ytVpN2bJlmTBhAjVq1Mg1H5s2bTJY/+zZsyiVSrp3717ofWdhYcHs2bOJiyudET2FEEIIIYQQIl8KxfOZ/oWK1BX8yZZegBUrVuDi4kJERARNmzZFq9Uyf/58JkyYQNeuXQFYtWoVrq6urF69mnfffRdA3yq8f//+fOPZ2tri5pb7APahoaFERkZy48YNPDw8APjss8/o168f06dPx87OTp/Wyckpz+34+Pjw+eefA7B8+fJc0zg6Ohr8v3btWqysrIpUsW7VqhWXL19m5syZzJkzp9DrCSGEEEIIIYT4eytWp/qEhAQgu+J59epVYmJiaNOmjT6NSqWiWbNmHD5c9HfizZ49GycnJ2rWrMn06dMNunmHhYURGBior1QDtG3bFrVaTUREhMF2OnXqhIuLC0FBQWzYUPx3Gi9btozXXnsNa2vrQq+jVCqZMWMGCxYs4OZN47+3UQghhBBCCCFE6Xjmwcu0Wi2jRo2icePGBAYGAhATEwOAq6urQVpXV1euX79epO0PHz6c2rVr4+DgwNGjRwkJCeHq1assXbpUH+vpOA4ODpibm+vzYWNjw7x58wgKCsLExIRt27bRs2dPVq1axRtvvPFM5T569Chnz55l2bJlRV63S5cu1KxZk8mTJxdqfbVajVqtNpinyTDH1ExV5NhCCCGEEEII8SR53VbJeeaK9dChQzl9+jSHDh3KsezpAbm0Wm2RB+kaOXKk/u/q1avj4OBAt27d9K3YucV5Opazs7PBdurWrUtcXBxz5sx55or1smXLCAwMpH79+s+0/uzZs2nRokWuz4I/bebMmUydOtVgXtvXJtHu9SnPFFsIIYQQQgghRMl7pq7g77//Ptu2bWPfvn14enrq5z9+jvlxi/Fjd+/ezdG6XFQNGjQA4PLly/pYT8eJi4sjIyMj31gNGjTg0qVLz5SHlJQU1q5dy4ABA55pfYCmTZvStm3bAgduAwgJCSEhIcFgatUt5JljCyGEEEIIIcRjChOT5zL9GxWpVFqtlqFDh7Jp0yb27t2Lr6+vwXJfX1/c3NzYtWuXfl56ejoHDhygUaNGxcroiRMnAHB3dwegYcOGnD17lujoaH2a0NBQVCoVderUyXc7j7dRVOvXr0etVj9za/djs2bNYvv27QU+d65SqbCzszOYpBu4EEIIIYQQQvy9FKkr+JAhQ1i9ejVbt27F1tZW32Jsb2+PpaUlCoWCESNGMGPGDPz9/fH392fGjBlYWVnRq1cv/XZiYmKIiYnRtz6fOXMGW1tbvLy8cHR0JCwsjCNHjtC8eXPs7e0JDw9n5MiRdOrUCS8vLwDatGlDQEAAffr04dNPP+XBgweMGTOGgQMH6kcEX7VqFWZmZtSqVQsTExO2b9/OF198wezZsw3KdfLkSQAePnzIvXv3OHnyJObm5gQEBBikW7ZsGZ07d9Z3RX9W1apVo3fv3ixYsKBY2xFCCCGEEEII8fwVqWK9aNEiAIKDgw3mr1ixgn79+gEwduxYUlNTGTx4MHFxcbz44ouEhoZia2urT7948WKDZ4ebNm1qsB2VSsW6deuYOnUqarUab29vBg4cyNixY/XrKJVKduzYweDBgwkKCsLS0pJevXoxd+5cg7x98sknXL9+HaVSSaVKlVi+fHmOFudatWrp/46IiGD16tV4e3tz7do1/fyLFy9y6NAhQkNDi7LL8vTxxx+zfv36EtmWEEIIIYQQQhSVDF5WchRarVb7vDMhCm/+ttI5XINUub/TuyRlOJUzegyARLvSiXPyhW5Gj9Fy5wSjxwA47/VyqcRxVMQaPUa0Jvd32Je0SumnSyVOtJWf0WOYK9ILTlQCsor3xsdCU6IxeoykLNuCE5WANI15qcQxVxp/n6VnPvP4qUViapJVKnFsTR8aPYaFNsXoMQBiNMUbF6ewyilvGT3GfVyMHgPANeu20WM8UJZOWXzvFv0Vuc/iT+dgo8ewNEkzegyAAD+PghP9TUWP7lVwIiNw/2z1c4lrTKXzqSaEEEIIIYQQ4m/l3zqQ2PMge7KYoqKisLGxyXOKiop63lkUQgghhBBCCGFE0mJdTB4eHvrBz/JaLoQQQgghhBB/N/KMdcmRinUxmZqa4udn/GcehRBCCCGEEEL8PUlXcCGEEEIIIYQQohikxfof5kFcRqnE0SrvGD2GWUbpjDysKeNbKnFKY8TuPe2mGz0GgM/51qUSxyxTbfQYmVlKo8cAMMnKLJU4pcEiK7lU4tzTls7Iw9ZK44+knJhuZfQYAJbK0vkMeJhhYfQYzqoEo8cASNKUzrGx0zwwegxlVukcf3OlU6nEMdEa/76ZojH+uQxgnXbX6DHu25bOWy6Ud2+WShyVi/G/ByZqrI0e459OuoKXHGmxFkIIIYQQQgghikFarIUQQgghhBDiv0het1ViZE8KIYQQQgghhBDFIBVrIYQQQgghhBCiGIpUsZ45cyb16tXD1tYWFxcXOnfuzIULFwzSaLVapkyZgoeHB5aWlgQHB3Pu3DmDNEuWLCE4OBg7OzsUCgXx8fE5Yvn4+KBQKAymcePGGaSJioqiY8eOWFtb4+zszLBhw0hPzx4I4dq1azm2oVAo2Llzp8F2Dhw4QJ06dbCwsKBChQosXrzYYPm5c+d49dVX9XmaP39+UXYb/fr1Q6FQMGvWLIP5W7ZsQaGQAQOEEEIIIYQQpS+3ulJpTP9GRapYHzhwgCFDhnDkyBF27dqFRqOhTZs2JCdnjyA7Z84c5s2bx8KFCwkPD8fNzY3WrVuTlJSkT5OSkkK7du0YP358vvGmTZtGdHS0fpo4caJ+WWZmJu3btyc5OZlDhw6xdu1aNm7cyOjRo3NsZ/fu3QbbadGihX7Z1atXefnll2nSpAknTpxg/PjxDBs2jI0bNxrkt0KFCsyaNQs3t2cbkdHCwoLZs2cTFxf3TOsLIYQQQgghhPh7KtLgZU+39K5YsQIXFxciIiJo2rQpWq2W+fPnM2HCBLp27QrAqlWrcHV1ZfXq1bz77rsAjBgxAoD9+/fnG8/W1jbPimxoaCiRkZHcuHEDDw8PAD777DP69evH9OnTsbOz06d1cnLKczuLFy/Gy8tL3wpdtWpVjh07xty5c3n11VcBqFevHvXq1QPI0WpeWK1ateLy5cvMnDmTOXPmPNM2hBBCCCGEEKKkKGTwshJTrD2ZkKB7B6WjoyOga/2NiYmhTZs2+jQqlYpmzZpx+PDhIm9/9uzZODk5UbNmTaZPn27QzTssLIzAwEB9pRqgbdu2qNVqIiIiDLbTqVMnXFxcCAoKYsOGDQbLwsLCDPL7eDvHjh0jI6Pk3hepVCqZMWMGCxYs4ObN0nk/oBBCCCGEEEII43vm121ptVpGjRpF48aNCQwMBCAmJgYAV1dXg7Surq5cv369SNsfPnw4tWvXxsHBgaNHjxISEsLVq1dZunSpPtbTcRwcHDA3N9fnw8bGhnnz5hEUFISJiQnbtm2jZ8+erFq1ijfeeCPP7bi6uqLRaLh//z7u7u5Fynd+unTpQs2aNZk8eTLLli0rse0KIYQQQgghRFEpTP6dzzs/D89csR46dCinT5/m0KFDOZY9/UC6Vqst8kPqI0eO1P9dvXp1HBwc6Natm74VO7c4T8dydnY22E7dunWJi4tjzpw5+op1XvnNa/vFNXv2bFq0aJHrs+BPU6vVqNVqg3maDAWmZqoSz5cQQgghhBBCiGfzTF3B33//fbZt28a+ffvw9PTUz3/8HPPjFuPH7t69m6NVuKgaNGgAwOXLl/Wxno4TFxdHRkZGvrEaNGjApUuXDPKcW35NTU31FfiS1LRpU9q2bVvgwG2gG4Xd3t7eYPr9J3k+WwghhBBCCCH+TopUsdZqtQwdOpRNmzaxd+9efH19DZb7+vri5ubGrl279PPS09M5cOAAjRo1KlZGT5w4AaDvmt2wYUPOnj1LdHS0Pk1oaCgqlYo6derku50nu3c3bNjQIL+Pt1O3bl3MzMyKlee8zJo1i+3btxf43HlISAgJCQkGU1CHsUbJkxBCCCGEEOI/xsTk+Uz/QkXqCj5kyBBWr17N1q1bsbW11bf02tvbY2lpiUKhYMSIEcyYMQN/f3/8/f2ZMWMGVlZW9OrVS7+dmJgYYmJi9K3PZ86cwdbWFi8vLxwdHQkLC+PIkSM0b94ce3t7wsPDGTlyJJ06dcLLywuANm3aEBAQQJ8+ffj000958OABY8aMYeDAgfoRwVetWoWZmRm1atXCxMSE7du388UXXzB79mx9XgYNGsTChQsZNWoUAwcOJCwsjGXLlrFmzRp9mvT0dCIjI/V/37p1i5MnT2JjY4Ofn1+Rd3q1atXo3bs3CxYsyDedSqVCpTLs9m1qlp5HaiGEEEIIIYQQz0ORKtaLFi0CIDg42GD+ihUr6NevHwBjx44lNTWVwYMHExcXx4svvkhoaCi2trb69IsXL2bq1Kn6/5s2bWqwHZVKxbp165g6dSpqtRpvb28GDhzI2LHZrbVKpZIdO3YwePBggoKCsLS0pFevXsydO9cgb5988gnXr19HqVRSqVIlli9fbvB8ta+vLz///DMjR47kyy+/xMPDgy+++EL/qi2A27dvU6tWLf3/c+fOZe7cuTRr1qzAV4bl5eOPP2b9+vXPtK4QQgghhBBCFJcMXlZyFNrHI3WJf4RJq0qnxTpEObfgRMWkKONg9BgAd6q0KJU4rtf/MHqMPe2mGz0GgM/5/aUSxyHzntFjXM2sYPQYAC+kHyuVOLdsKhs9hp02zugxAO5pizf2RmFZK1OMHiMmreTH5MiNpbLkXgOZn9RM4zwK9SRnVYLRYwAkaaxKJY6XomhvP3kWyqzSOf63lD6lEseV20aPcU3jW3CiEhCYdsToMa7bVjd6DIBK59aWSpzLgT2MHuOhxtLoMQAaVLEvlTjG8OCTd59LXMeJXz+XuMb07+zgLoQQQgghhBBClJJnft2W0ImKiiIgICDP5ZGRkfrnwoUQQgghhBDi70KhkHbWkiIV62Ly8PDg5MmT+S4XQgghhBBCCPHvJRXrYjI1NX2mkcGFEEIIIYQQ4rmSwctKjLT9CyGEEEIIIYQQxSAt1v8w1auUziGLt3/Z6DEemJbOiMAVT5fOa83OV+tt9Bg+51sbPQbAtarBpRLH58BMo8dQOZU3egwAraJ0fvGteG6j8YPY2Bk/BqD0rFkqcRzCfjJ6DG/b0tlnpSXd09/oMTbcaWv0GACeTqXzNg2H2FNGj7Hf4TWjxwCwt0grlTj77gcaPUYn691GjwHwwM7b6DEqnV5j9BgAD15oXipx/I5/b/QY1+v0NHoMnX/uqOAKE2lnLSmyJ4UQQgghhBBCiGKQirUQQgghhBBCCFEM0hVcCCGEEEIIIf6DFDJ4WYmRFmshhBBCCCGEEKIYilSxnjlzJvXq1cPW1hYXFxc6d+7MhQsXDNJotVqmTJmCh4cHlpaWBAcHc+7cOYM0S5YsITg4GDs7OxQKBfHx8Tli+fj4oFAoDKZx48YZpImKiqJjx45YW1vj7OzMsGHDSE/PfZCSy5cvY2trS5kyZQzmR0dH06tXLypXroyJiQkjRozIse7KlStz5EWhUJCWVrjBPfr164dCoWDWrFkG87ds2YKilAY8EkIIIYQQQggDCpPnM/0LFalUBw4cYMiQIRw5coRdu3ah0Who06YNycnJ+jRz5sxh3rx5LFy4kPDwcNzc3GjdujVJSUn6NCkpKbRr147x48fnG2/atGlER0frp4kTJ+qXZWZm0r59e5KTkzl06BBr165l48aNjB49Osd2MjIyeP3112nSpEmOZWq1mrJlyzJhwgRq1KiRZ17s7OwM8hIdHY2FhUW++X+ShYUFs2fPJi4urtDrCCGEEEIIIYT4+yvSM9Y7d+40+H/FihW4uLgQERFB06ZN0Wq1zJ8/nwkTJtC1a1cAVq1ahaurK6tXr+bdd98F0LcK79+/P994tra2uLm55bosNDSUyMhIbty4gYeHBwCfffYZ/fr1Y/r06djZZb/6ZOLEiVSpUoWWLVty+PBhg+34+Pjw+eefA7B8+fI886JQKPLMS2G0atWKy5cvM3PmTObMmfPM2xFCCCGEEEII8fdSrHb4hIQEABwdHQG4evUqMTExtGnTRp9GpVLRrFmzHBXawpg9ezZOTk7UrFmT6dOnG3TzDgsLIzAwUF+pBmjbti1qtZqIiAj9vL179/Ljjz/y5ZdfFjn+kx4+fIi3tzeenp506NCBEydOFGl9pVLJjBkzWLBgATdv3ixWXoQQQgghhBCiuBQmiucy/Rs9c8Vaq9UyatQoGjduTGBgIAAxMTEAuLq6GqR1dXXVLyus4cOHs3btWvbt28fQoUOZP38+gwcP1i+PiYnJEcfBwQFzc3N9rNjYWPr168fKlSsNWrCLqkqVKqxcuZJt27axZs0aLCwsCAoK4tKlS0XaTpcuXahZsyaTJ09+5rwIIYQQQgghhPh7eebXbQ0dOpTTp09z6NChHMueHpBLq9UWeZCukSNH6v+uXr06Dg4OdOvWTd+KnVucp2MNHDiQXr160bRp0yLFflqDBg1o0KCB/v+goCBq167NggUL+OKLL4q0rdmzZ9OiRYtcnwV/mlqtRq1WG8zLSDfDzFxVpJhCCCGEEEIIkYPJv3Mgsefhmfbk+++/z7Zt29i3bx+enp76+Y+fQX66dfru3bs5WpeL6nHF9vLly/pYT8eJi4sjIyNDH2vv3r3MnTsXU1NTTE1N6d+/PwkJCZiamub7PHVBTExMqFevXpFbrAGaNm1K27ZtCxy4DXSjsNvb2xtMm1fNKnA9IYQQQgghhBClp0gVa61Wy9ChQ9m0aRN79+7F19fXYLmvry9ubm7s2rVLPy89PZ0DBw7QqFGjYmX08TPN7u7uADRs2JCzZ88SHR2tTxMaGopKpaJOnTqA7jnskydP6qdp06Zha2vLyZMn6dKlyzPnRavVcvLkSX1eimrWrFls3769wOfOQ0JCSEhIMJi6vDku33WEEEIIIYQQojBye6VwaUz/RkXqCj5kyBBWr17N1q1bsbW11bcY29vbY2lpiUKhYMSIEcyYMQN/f3/8/f2ZMWMGVlZW9OrVS7+dmJgYYmJi9K3PZ86cwdbWFi8vLxwdHQkLC+PIkSM0b94ce3t7wsPDGTlyJJ06dcLLywuANm3aEBAQQJ8+ffj000958OABY8aMYeDAgfrnqatWrWqQ/2PHjmFiYqJ/JvyxkydPAroByu7du8fJkycxNzcnICAAgKlTp9KgQQP8/f1JTEzkiy++4OTJk888IFq1atXo3bs3CxYsyDedSqVCpTLs9m1mnvVMMYUQQgghhBBCGEeRKtaLFi0CIDg42GD+ihUr6NevHwBjx44lNTWVwYMHExcXx4svvkhoaCi2trb69IsXL2bq1Kn6/x8/A/14OyqVinXr1jF16lTUajXe3t4MHDiQsWPH6tdRKpXs2LGDwYMHExQUhKWlJb169WLu3LlF2gEAtWrV0v8dERHB6tWr8fb25tq1awDEx8fzzjvvEBMTg729PbVq1eK3336jfv36RY712Mcff8z69eufeX0hhBBCCCGEEH8PCq1Wq33emRCFt+GP0mmxDrI/bfQYD0yL99x9YVU8XTo/YJyv1tvoMcwVGUaPAXCtanCpxAk+MNPoMc47NTd6DICKaca/ZgAsr50xfhCbZ3+LQlE88KxZKnEcwn8yegyFbenss9KS7ulv9BgbEtoaPQaAp1N6wYlKQJPYdUaPsd/hNaPHALC3SCuVOH/dtzF6jE7Wu40eA+CBnbfRY7id/sXoMQAevFA6n5uOp0KNHuN6nZ5GjwFQuWL5UoljDEkLPngucW3f//S5xDUmGQZOCCGEEEIIIYQoBqlYF1NUVBQ2NjZ5TlFRUc87i0IIIYQQQgiRg8JE8VymZ/HVV1/h6+uLhYUFderU4eDBg/mmV6vVTJgwAW9vb1QqFRUrVizWm6EK8szvsRY6Hh4e+sHP8louhBBCCCGEEOLZrFu3jhEjRvDVV18RFBTE119/zUsvvURkZKR+cOun9ejRgzt37rBs2TL8/Py4e/cuGo3GaHmUinUxmZqa4ufn97yzIYQQQgghhBD/SvPmzaN///4MGDAAgPnz5/Prr7+yaNEiZs7MOWbPzp07OXDgAH/99ReOjo4A+Pj4GDWP0hVcCCGEEEIIIf6LFCbPZVKr1SQmJhpMarU61yymp6cTERFBmzZtDOa3adOGw4cP57rOtm3bqFu3LnPmzKFcuXJUqlSJMWPGkJqaWuK78DGpWAshhBBCCCGEKDUzZ87E3t7eYMqt5Rng/v37ZGZm4upq+EYhV1dXYmJicl3nr7/+4tChQ5w9e5bNmzczf/58NmzYwJAhQ0q8LI9JV/B/mGOnS+e1IR08jhg9hqZSU6PHANCWcSyVOI6KWKPHMMvM/Ze8kuZTCq/BAtjfLMToMeqeXm30GAAaM8vSieOa+3NEJck06YHRYwCYZySXSpyk2m0KTlRMCkrnVYilJdXM1ugxqtnEGz0GgMqkdD43U5QVjR6jrNlDo8cAMDUx3jOIT6rhnmL0GOp0e6PHAMg0Mf5X6rQKNYweA8Dx5slSiZNauZ7RY5hROtf/P9ozDiRWXCEhIYwaNcpgnkqlyncdhcIwr1qtNse8x7KyslAoFPzwww/Y2+vuA/PmzaNbt258+eWXWFqW/Pc2qVgLIYQQQgghhCg1KpWqwIr0Y87OziiVyhyt03fv3s3Riv2Yu7s75cqV01eqAapWrYpWq+XmzZv4+/s/e+bzIF3BhRBCCCGEEOI/SKEweS5TUZibm1OnTh127dplMH/Xrl00atQo13WCgoK4ffs2Dx9m9/S5ePEiJiYmeHp6Fn1HFYJUrIUQQgghhBBC/G2NGjWKpUuXsnz5cs6fP8/IkSOJiopi0KBBgK5red++ffXpe/XqhZOTE2+99RaRkZH89ttvfPDBB7z99ttG6QYO0hVcCCGEEEIIIcTfWM+ePYmNjWXatGlER0cTGBjIzz//jLe3NwDR0dFERUXp09vY2LBr1y7ef/996tati5OTEz169OCTTz4xWh6L1GI9c+ZM6tWrh62tLS4uLnTu3JkLFy4YpNFqtUyZMgUPDw8sLS0JDg7m3LlzBmmWLFlCcHAwdnZ2KBQK4uPjc8Ty8fFBoVAYTOPGjTNIExUVRceOHbG2tsbZ2Zlhw4aRnp49SMGFCxdo3rw5rq6uWFhYUKFCBSZOnEhGRoY+zaFDhwgKCsLJyQlLS0uqVKnC//73vxz52bhxIwEBAahUKgICAti8eXOh91u/fv1QKBTMmjXLYP6WLVvyfOBeCCGEEEIIIYzKRPF8pmcwePBgrl27hlqtJiIigqZNswdCXrlyJfv37zdIX6VKFXbt2kVKSgo3btzgs88+M1prNRSxYn3gwAGGDBnCkSNH2LVrFxqNhjZt2pCcnD2y65w5c5g3bx4LFy4kPDwcNzc3WrduTVJSkj5NSkoK7dq1Y/z48fnGe/yLxONp4sSJ+mWZmZm0b9+e5ORkDh06xNq1a9m4cSOjR4/WpzEzM6Nv376EhoZy4cIF5s+fzzfffMPkyZP1aaytrRk6dCi//fYb58+fZ+LEiUycOJElS5bo04SFhdGzZ0/69OnDqVOn6NOnDz169OCPP/4o9L6zsLBg9uzZxMXFFXodIYQQQgghhBB/f0XqCr5z506D/1esWIGLi4v+FwOtVsv8+fOZMGECXbt2BWDVqlW4urqyevVq3n33XQBGjBgBkONXhafZ2tri5uaW67LQ0FAiIyO5ceMGHh4eAHz22Wf069eP6dOnY2dnR4UKFahQoYJ+HW9vb/bv38/Bgwf182rVqkWtWrX0//v4+LBp0yYOHjzIO++8A8D8+fNp3bo1ISG6VwOFhIRw4MAB5s+fz5o1awrabQC0atWKy5cvM3PmTObMmVOodYQQQgghhBDCWBQmMuRWSSnWnkxISADA0VH3nuCrV68SExNDmzbZ7wxVqVQ0a9aMw4cPF3n7s2fPxsnJiZo1azJ9+nSDbt5hYWEEBgbqK9UAbdu21XcNyM3ly5fZuXMnzZo1yzPmiRMnOHz4sEGasLAwgzI9jlWUMimVSmbMmMGCBQu4efNmodcTQgghhBBCCPH39syDl2m1WkaNGkXjxo0JDAwE0L9b7On3ibm6unL9+vUibX/48OHUrl0bBwcHjh49SkhICFevXmXp0qX6WE/HcXBwwNzcPMc7zho1asTx48dRq9W88847TJs2LUc8T09P7t27h0ajYcqUKQwYMEC/LLdYrq6uOeIUpEuXLtSsWZPJkyezbNmyAtOr1WrUarXBPE2GFlOzwr3zTQghhBBCCCGE8T1zi/XQoUM5ffp0rl2hnx6QS6vVFnmQrpEjR9KsWTOqV6/OgAEDWLx4McuWLSM2NjbPOHnFWrduHcePH2f16tXs2LGDuXPn5ljv4MGDHDt2jMWLF+faxbskygS6VvhVq1YRGRlZYNqZM2dib29vMB355dMixxRCCCGEEEKIHBSK5zP9Cz1Ti/X777/Ptm3b+O233wxesP34eeiYmBjc3d318+/evZujxbeoGjRoAOi6czs5OeHm5pZj8LC4uDgyMjJyxCpfvjwAAQEBZGZm8s477zB69GiUSqU+ja+vLwDVqlXjzp07TJkyhddff11frqdbp5+1TE2bNqVt27aMHz+efv365Zs2JCSEUaNGGcyb9r22yDGFEEIIIYQQQhhPkVqstVotQ4cOZdOmTezdu1dfGX3M19cXNzc3du3apZ+Xnp7OgQMHaNSoUbEyeuLECQB9hb1hw4acPXuW6OhofZrQ0FBUKhV16tTJtwwZGRlotXlXULVarUEX7IYNGxqU6XGsZy3TrFmz2L59e4HPaKtUKuzs7Awm6QYuhBBCCCGEKBEmJs9n+hcqUov1kCFDWL16NVu3bsXW1lbfimtvb8//2bv3sKrqvP//z81pA7IhT4BkKCmVDBampmghlWB33pZWv5obx2KmmBzxgNblHeo9aY0gpt4kNppNqdMMHiYt9U4NZlTKURpjJE8zFpNJFjsrERV1c9q/P/y6py0obGBtPLwe17Wuy73We63XWksEP3zW+nz8/PwwmUykpaWRkZFBZGQkkZGRZGRk4O/vT1JSkuM4VqsVq9VKSUkJAPv27cNisRAeHk6HDh3YtWsXhYWF3HvvvQQFBbF7924mT57MQw89RHh4OACJiYlERUUxZswYXnnlFY4fP87zzz9PSkoKgYGBAPzxj3/E29ub3r17YzabKSoqIj09nSeeeAIvr/OX/tprrxEeHs5tt90GnJ/Xet68eUyYMMFxvpMmTSIuLo6srCwefvhh1q9fz5///Gd27NjRrJveu3dvRo8eTU5OTrP2FxERERERkSuHSw3rxYsXAxAfH++0ftmyZY7HmqdOncrZs2cZN24c5eXlDBgwgLy8PCwWi6N+yZIlzJo1y/H5wuTeF45jNptZvXo1s2bNwmaz0a1bN1JSUpg6dapjH09PT95//33GjRvH4MGD8fPzIykpyen9aS8vL7Kysvjss8+w2+1069aN1NRUJk+e7Kipq6tzDIzm5eVFjx49mDNnjmNqMDg/+NmqVauYMWMG//M//0OPHj1YvXo1AwYMcOX2OXn55ZdZs2ZNs/cXERERERGRK4PJfrlnouWK88Ib59ySMzNsueEZ390SZ3gGQKevGp5+rbUdC7/L8AzvWlvjRa0g6IcSt+RsH5JueEa/vbmGZwB42GvdkuN30rXZCJrD69RxwzMATne51S05dR7ehmeYqDM8w53OelsaL2qhb+u6NF7UCsweVY0XtYIbbcZ/3zzs3cvwDAAvjxq35HiajP93E1rl2qw0zXXSt5PhGR1PlhqeAeD7g3tyznbqZnhGeUDXxotawc09erglxwhnVtSfLckd/J/6dZvkGunafMBdRERERERExE2aPY+1nFdaWkpUVNQltx88eNDxXriIiIiIiMiVwnSNDiTWFtSwbqGwsDCKi4svu11ERERERESuXWpYt5CXlxc9e/Zs69MQERERERFxjUk91q1Fd1JERERERESkBdRjfZUJDja7JedkRD/DM76qucnwDADvMPeMpF1WE2p4Rm2dp+EZAOaO7vm7cceI3Z/cnmR4BsBP/rHRLTlnOgUZntEuwD2jgv/g557RWs/U+Rme0dlu/GjtAGc8A92SY7afNTzjqwr3XMv9XlvdkvOvgD7Gh7hpHpeqWh+35NzgXWF4hmete0aFP2YzflRws/8ZwzMAzvh1cEtOuWdnwzMsdScMzxC5QA1rERERERGR65GHqa3P4JqhR8FFREREREREWkA91iIiIiIiItchkwYvazW6kyIiIiIiIiIt4FLDOjMzk/79+2OxWAgODmbkyJEcOnTIqcZutzNz5kzCwsLw8/MjPj6eAwcOONUsXbqU+Ph4AgMDMZlMnDhxol5W9+7dMZlMTssLL7zgVFNaWsqIESNo164dnTp1YuLEiVRV/XuQikOHDnHvvfcSEhKCr68vN998MzNmzKC6utpRU1ZWRlJSErfeeiseHh6kpaVd9h6sWrUKk8nEyJEjm3bTgOTkZEwmE3PmzHFa/95772Ey6b0GERERERGRq5lLDeuCggJSU1MpLCwkPz+fmpoaEhMTqaysdNTMnTuXBQsWsGjRInbv3k1oaCgJCQmcOnXKUXPmzBkeeOABpk2bdtm8l156ibKyMscyY8YMx7ba2lqGDx9OZWUlO3bsYNWqVaxdu5bnnnvOUePt7c2TTz5JXl4ehw4dIjs7mzfeeIMXX3zRUWOz2ejcuTPTp0/njjvuuOz5HDlyhOeff5577rmnyffsAl9fX7KysigvL3d5XxERERERkVbnYWqb5Rrk0jvWW7Zscfq8bNkygoODKSoqIi4uDrvdTnZ2NtOnT+eRRx4BYMWKFYSEhJCbm8uzzz4L4OgV3r59+2XzLBYLoaENT2GUl5fHwYMH+eqrrwgLCwNg/vz5JCcnM3v2bAIDA7n55pu5+eabHft069aN7du389FHHznWde/enVdffRWAt95665LnUltby+jRo5k1axYfffRRg73slzN06FBKSkrIzMxk7ty5Lu0rIiIiIiIiV64WvWNdUXF+/sEOHc7Pd3f48GGsViuJiYmOGrPZzJAhQ9i5c6fLx8/KyqJjx47ExMQwe/Zsp8e8d+3aRXR0tKNRDTBs2DBsNhtFRUUNHq+kpIQtW7YwZMgQl8/lpZdeonPnzjz99NMu7wvg6elJRkYGOTk5HD16tFnHEBERERERaTUmj7ZZrkHNHhXcbrczZcoU7r77bqKjowGwWq0AhISEONWGhIRw5MgRl44/adIk7rzzTtq3b8/f/vY30tPTOXz4ML/73e8cWRfntG/fHh8fH8d5XDBo0CD+/ve/Y7PZ+OUvf8lLL73k0rn89a9/5c0336S4uNil/S42atQoYmJiePHFF3nzzTcbrbfZbNhsNqd1NdU+eHmbW3QeIiIiIiIi0nqa/euC8ePHs3fvXlauXFlv28UDctntdpcH6Zo8eTJDhgzh9ttv55lnnmHJkiW8+eab/PDDD5fMuVTW6tWr+fvf/05ubi7vv/8+8+bNa/J5nDp1ip/97Ge88cYbdOrUyaVraEhWVhYrVqzg4MGDjdZmZmYSFBTktPzlncwWn4OIiIiIiAgmU9ss16Bm9VhPmDCBDRs28OGHH9K1a1fH+gvvQ1utVrp06eJYf+zYsXq9y64aOHAgcP5x7o4dOxIaGsrHH3/sVFNeXk51dXW9rJtuugmAqKgoamtr+eUvf8lzzz2Hp6dno7n/+te/+PLLLxkxYoRjXV1dHQBeXl4cOnSIHj16NPk64uLiGDZsGNOmTSM5Ofmytenp6UyZMsVp3ZI8nyZniYiIiIiIiPFc6rG22+2MHz+edevWsXXrViIiIpy2R0REEBoaSn5+vmNdVVUVBQUFDBo0qEUnumfPHgBHgz02Npb9+/dTVlbmqMnLy8NsNtO3b9/LXkN1dTV2u71Jubfddhv79u2juLjYsTz00EPce++9FBcXOxrtrpgzZw4bN25s9L1zs9lMYGCg06LHwEVERERERK4sLvVYp6amkpuby/r167FYLI53mYOCgvDz88NkMpGWlkZGRgaRkZFERkaSkZGBv78/SUlJjuNYrVasVislJSUA7Nu3D4vFQnh4OB06dGDXrl0UFhZy7733EhQUxO7du5k8eTIPPfQQ4eHhACQmJhIVFcWYMWN45ZVXOH78OM8//zwpKSkEBgYC8Mc//hFvb2969+6N2WymqKiI9PR0nnjiCby8/n3pF96dPn36NN999x3FxcX4+PgQFRWFr6+v4x3yC2644QaAeuubqnfv3owePZqcnJxm7S8iIiIiItJiHtfmQGJtwaWG9eLFiwGIj493Wr9s2TLHY81Tp07l7NmzjBs3jvLycgYMGEBeXh4Wi8VRv2TJEmbNmuX4HBcX53Qcs9nM6tWrmTVrFjabjW7dupGSksLUqVMd+3h6evL+++8zbtw4Bg8ejJ+fH0lJSU7vT3t5eZGVlcVnn32G3W6nW7dupKamMnnyZKfz79Onj+PPRUVF5Obm0q1bN7788ktXbo9LXn75ZdasWWPY8UVERERERMQ9TPamPhMtV4QF693z1/WzyIanLGtNJaZbDc8AuNlU4pacL7m58aIWqq1rfFyA1mD2rHZLzk11Xxie8cntSY0XtYKf/GOjW3JMGP89oN2544ZnAPzg17XxolZwps7P8IzOdmvjRa3gjGegW3LM9rOGZxQdjzQ8A+B+r61uyflXQJ/Gi1qozu6eniV35dzgXWF4RqczpYZnABzyut3wjJs83XMtHvY6t+SUe3Y2PMNiP2F4BkB4ZC+35Bjh3LpX2yTX95FJbZJrJPX9i4iIiIiIiLSAGtYtVFpaSkBAwCWX0lL3/HZRRERERERE2kazptuSfwsLC3MMfnap7SIiIiIiIlccj2tzTum2oIZ1C3l5edGzZ8+2Pg0RERERERFpI2pYi4iIiIiIXI9MejO4tahhfZX5+uszbskJtG03POO224wfdRbAq+acW3Ju8TpteIZHXa3hGQB2k3seC6rxNn60ZneN1n2g1wi35AzZMa/xohaq8m9veAaAJzVuyYmo3G94xjnfIMMzAMwe7vm+6WE3/nuNO0a4B/g6MMotOT1O7jE845sg94w8XGt3zwwUp2vbGZ7h59vB8AyAm2s+NzzDXuem0dpLCt2S49M9xvCMSjf9/YuAGtYiIiIiIiLXJzd1plwP1PcvIiIiIiIi0gJqWIuIiIiIiIi0gB4FFxERERERuR55qJ+1tbh0JzMzM+nfvz8Wi4Xg4GBGjhzJoUOHnGrsdjszZ84kLCwMPz8/4uPjOXDggFPN0qVLiY+PJzAwEJPJxIkTJ+plde/eHZPJ5LS88MILTjWlpaWMGDGCdu3a0alTJyZOnEhVVZVj+/bt23n44Yfp0qUL7dq1IyYmhj/+8Y9Ox1i3bh0JCQl07tyZwMBAYmNj+eCDD+qdz4kTJ0hNTaVLly74+vrSq1cvNm3a1KT7lpycjMlkYs6cOU7r33vvPUx6r0FEREREROSq5lLDuqCggNTUVAoLC8nPz6empobExEQqKysdNXPnzmXBggUsWrSI3bt3ExoaSkJCAqdOnXLUnDlzhgceeIBp06ZdNu+ll16irKzMscyYMcOxrba2luHDh1NZWcmOHTtYtWoVa9eu5bnnnnPU7Ny5k9tvv521a9eyd+9efvGLX/Dkk0+yceO/Rwn+8MMPSUhIYNOmTRQVFXHvvfcyYsQI9uz59+ieVVVVJCQk8OWXX/LOO+9w6NAh3njjDW688cYm3ztfX1+ysrIoLy9v8j4iIiIiIiKGMZnaZrkGufQo+JYtW5w+L1u2jODgYIqKioiLi8Nut5Odnc306dN55JFHAFixYgUhISHk5uby7LPPApCWlgac71G+HIvFQmhoaIPb8vLyOHjwIF999RVhYWEAzJ8/n+TkZGbPnk1gYGC9hvvEiRP54IMPePfddxkx4vzUONnZ2U41GRkZrF+/no0bN9KnTx8A3nrrLY4fP87OnTvx9vYGoFu3bpc994sNHTqUkpISMjMzmTt3rkv7ioiIiIiIyJWrRQ/VV1RUANChw/k54g4fPozVaiUxMdFRYzabGTJkCDt37nT5+FlZWXTs2JGYmBhmz57t9Jj3rl27iI6OdjSqAYYNG4bNZqOoqOiy53zhfBtSV1fHqVOnnGo2bNhAbGwsqamphISEEB0dTUZGBrW1TZ/n09PTk4yMDHJycjh69GiT9xMREREREZErW7MHL7Pb7UyZMoW7776b6OhoAKxWKwAhISFOtSEhIRw5csSl40+aNIk777yT9u3b87e//Y309HQOHz7M7373O0fWxTnt27fHx8fHcR4Xe+edd9i9ezevv/76JXPnz59PZWUljz/+uGPdF198wdatWxk9ejSbNm3i888/JzU1lZqaGn796183+ZpGjRpFTEwML774Im+++WaT9xMREREREWl1Jg1e1lqa3bAeP348e/fuZceOHfW2XTwgl91ud3mQrsmTJzv+fPvtt9O+fXsee+wxRy92QzmXy9q+fTvJycm88cYb/OQnP2kwc+XKlcycOZP169cTHBzsWF9XV0dwcDBLly7F09OTvn378s033/DKK6+41LCG873w9913n9O74Jdis9mw2WxO62qqa/DyNruUKSIiIiIiIsZp1q8oJkyYwIYNG9i2bRtdu3Z1rL/wPvTFPcbHjh2r17vsqoEDBwJQUlLiyLo4p7y8nOrq6npZBQUFjBgxggULFvDkk082ePzVq1fz9NNPs2bNGoYOHeq0rUuXLtxyyy14eno61vXq1Qur1er0eHpTxMXFMWzYsEYHboPzo7AHBQU5LX/Lm+dSnoiIiIiISIM8PNpmuQa5dFV2u53x48ezbt06tm7dSkREhNP2iIgIQkNDyc/Pd6yrqqqioKCAQYMGtehEL4zS3aVLFwBiY2PZv38/ZWVljpq8vDzMZjN9+/Z1rNu+fTvDhw9nzpw5/PKXv2zw2CtXriQ5OZnc3FyGDx9eb/vgwYMpKSmhrq7Ose6zzz6jS5cu+Pj4uHwtc+bMYePGjY2+d56enk5FRYXTclfi8y7niYiIiIiIiHFcehQ8NTWV3Nxc1q9fj8VicfQYBwUF4efnh8lkIi0tjYyMDCIjI4mMjCQjIwN/f3+SkpIcx7FarVitVkfv8759+7BYLISHh9OhQwd27dpFYWEh9957L0FBQezevZvJkyfz0EMPER4eDkBiYiJRUVGMGTOGV155hePHj/P888+TkpJCYGAg8O9G9aRJk3j00Ucd5+vj4+MYnGzlypU8+eSTvPrqqwwcONBR4+fnR1BQEAC/+tWvyMnJYdKkSUyYMIHPP/+cjIwMJk6c2Kyb3rt3b0aPHk1OTs5l68xmM2az82PfXt6Vl6gWERERERFxwTU69VVbcKnHevHixVRUVBAfH0+XLl0cy+rVqx01U6dOJS0tjXHjxtGvXz++/vpr8vLysFgsjpolS5bQp08fUlJSgPOPR/fp04cNGzYA5xuUq1evJj4+nqioKH7961+TkpLCypUrHcfw9PTk/fffx9fXl8GDB/P4448zcuRI5s3796PSy5cv58yZM2RmZjqd74WpwABef/11ampqSE1NdaqZNGmSo+amm24iLy+P3bt3c/vttzNx4kQmTZrECy+84Mrtc/Lyyy9jt9ubvb+IiIiIiIhcGUx2te6uKs/91j091rM7LTY848xtAwzPAPCqOeeWnBovX8MzPOqaPsVbS9jd9NvLGm8/wzMqfW4wPAPgQK8RbskZssP4cRaq/NsbngFw3P9Gt+R0OuXarBTNcc43yPAMAJuXv1tyPOzGf6/5pPxWwzMAbu3wrVtybjx50PCMb4J6GZ4BUGv3bLyoFVTVeRue0dnknr9/n5qzhmfY3TR68w0lhW7JOd09xvCMSt9LT7Hbmrr1dM/3MyOc+6BtZiryHfZ0m+QaqdmjgouIiIiIiMhVTNNttRrdyRYqLS0lICDgkktpaWlbn6KIiIiIiIgYSD3WLRQWFkZxcfFlt4uIiIiIiFxxNHhZq1HDuoW8vLzo2bNnW5+GiIiIiIiItBE9Ci4iIiIiIiLSAuqxvsr0urWdW3Jq/W42PON4u66GZwB0/ecHbsn56taH3ZLjDj0OrHVLTk1IuOEZZzq5Z7Rmd4zWDVBw9/OGZ9z/B/eM1Hmmz4NuyfGpsBqe4XvssOEZAFTb3BJTFRpheIatxj0jXHuY6tySYz68z/CMY7cNMjwDwOxZ7Zacb05aGi9qoUjcM8L14fb9Dc+45eAawzMA6toHuyXHd8cGwzO+SxhveMZVz0P9rK1Fd1JERERERESkBdRjLSIiIiIich2ya/CyVqMeaxEREREREZEWUI+1iIiIiIjI9cikftbW4tKdzMzMpH///lgsFoKDgxk5ciSHDh1yqrHb7cycOZOwsDD8/PyIj4/nwIEDTjVLly4lPj6ewMBATCYTJ06cqJfVvXt3TCaT0/LCCy841ZSWljJixAjatWtHp06dmDhxIlVVVY7t27dv5+GHH6ZLly60a9eOmJgY/vjHPzodo6ysjKSkJG699VY8PDxIS0tr8NrXrl1LVFQUZrOZqKgo3n333Sbft+TkZEwmE3PmzHFa/95772HS4xciIiIiIiJXNZca1gUFBaSmplJYWEh+fj41NTUkJiZSWVnpqJk7dy4LFixg0aJF7N69m9DQUBISEjh16pSj5syZMzzwwANMmzbtsnkvvfQSZWVljmXGjBmObbW1tQwfPpzKykp27NjBqlWrWLt2Lc8995yjZufOndx+++2sXbuWvXv38otf/IInn3ySjRs3OmpsNhudO3dm+vTp3HHHHQ2ex65du3jiiScYM2YMn376KWPGjOHxxx/n448/bvK98/X1JSsri/Ly8ibvIyIiIiIiIvDb3/6WiIgIfH196du3Lx999FGT9vvrX/+Kl5cXMTExhp6fS4+Cb9myxenzsmXLCA4OpqioiLi4OOx2O9nZ2UyfPp1HHnkEgBUrVhASEkJubi7PPvssgKNXePv27ZfNs1gshIaGNrgtLy+PgwcP8tVXXxEWFgbA/PnzSU5OZvbs2QQGBtZruE+cOJEPPviAd999lxEjRgDne8ZfffVVAN56660Gs7Kzs0lISCA9PR2A9PR0CgoKyM7OZuXKlZe9hguGDh1KSUkJmZmZzJ07t0n7iIiIiIiIGOYqeRR89erVpKWl8dvf/pbBgwfz+uuv8x//8R8cPHiQ8PBLT99aUVHBk08+yf3338+3335r6Dm26E5WVFQA0KFDBwAOHz6M1WolMTHRUWM2mxkyZAg7d+50+fhZWVl07NiRmJgYZs+e7fSY965du4iOjnY0qgGGDRuGzWajqKjosud84XybateuXU7XdCHLlWvy9PQkIyODnJwcjh496lK+iIiIiIjI9WrBggU8/fTTPPPMM/Tq1Yvs7GxuuukmFi9efNn9nn32WZKSkoiNjTX8HJvdsLbb7UyZMoW7776b6OhoAKxWKwAhISFOtSEhIY5tTTVp0iRWrVrFtm3bGD9+PNnZ2YwbN86x3Wq11stp3749Pj4+l8x655132L17Nz//+c9dOpeGsppzTaNGjSImJoYXX3zRpf1ERERERERam91kapPFZrNx8uRJp8VmszV4jlVVVRQVFdXr6ExMTLxsR+eyZcv417/+5ba2V7NHBR8/fjx79+5lx44d9bZdPCCX3W53eZCuyZMnO/58++230759ex577DFHL3ZDOZfL2r59O8nJybzxxhv85Cc/celcGspqzjXB+V74++67z+ld8Eux2Wz1vsCqq8x4+5hdzhUREREREbkSZGZmMmvWLKd1L774IjNnzqxX+/3331NbW+tSR+fnn3/OCy+8wEcffYSXl3smwmpWj/WECRPYsGED27Zto2vXro71F96HvvgCjx07Vu9GuGrgwIEAlJSUOLIuzikvL6e6urpeVkFBASNGjGDBggU8+eSTLmc3lNXca4qLi2PYsGGNDtwG57/ggoKCnJbNKzNdzhQREREREblSpKenU1FR4bRcGM/qUpra0VlbW0tSUhKzZs3illtuadXzvhyXGtZ2u53x48ezbt06tm7dSkREhNP2iIgIQkNDyc/Pd6yrqqqioKCAQYMGtehE9+zZA0CXLl0AiI2NZf/+/ZSVlTlq8vLyMJvN9O3b17Fu+/btDB8+nDlz5vDLX/6yWdmxsbFO13Qhq7nXNGfOHDZu3NjoO9oNfcH9x39d/gtORERERESkSUwebbKYzWYCAwOdFrO54adyO3XqhKenZ5M7Ok+dOsUnn3zC+PHj8fLywsvLi5deeolPP/0ULy8vtm7dasitdKlfPDU1ldzcXNavX4/FYnFcXFBQEH5+fphMJtLS0sjIyCAyMpLIyEgyMjLw9/cnKSnJcRyr1YrVanX0Pu/btw+LxUJ4eDgdOnRg165dFBYWcu+99xIUFMTu3buZPHkyDz30kGPUt8TERKKiohgzZgyvvPIKx48f5/nnnyclJYXAwEDg343qSZMm8eijjzrO18fHx2kAs+LiYgBOnz7Nd999R3FxMT4+PkRFRQHn3/eOi4sjKyuLhx9+mPXr1/PnP/+5wcfgm6J3796MHj2anJycy9aZzeZ6X2DePs2KFBERERERuer4+PjQt29f8vPzGTVqlGN9fn4+Dz/8cL36wMBA9u3b57Tut7/9LVu3buWdd96p1zncWlxqWF8YdS0+Pt5p/bJly0hOTgZg6tSpnD17lnHjxlFeXs6AAQPIy8vDYrE46pcsWeL0TH1cXJzTccxmM6tXr2bWrFnYbDa6detGSkoKU6dOdezj6enJ+++/z7hx4xg8eDB+fn4kJSUxb948R83y5cs5c+YMmZmZZGb++xHqIUOGOE311adPH8efi4qKyM3NpVu3bnz55ZcADBo0iFWrVjFjxgz+53/+hx49erB69WoGDBjgyu1z8vLLL7NmzZpm7y8iIiIiItIizRgzqi1MmTKFMWPG0K9fP2JjY1m6dCmlpaWMHTsWOP+k79dff83vf/97PDw8HINrXxAcHIyvr2+99a3JpYa13W5vtMZkMjFz5swGXzy/oLHtd955J4WFhY1mhYeH83//93+X3L58+XKWL1/e6HGacl2PPfYYjz32WKN1lzqPi3Xr1o1z584163giIiIiIiLXiyeeeIIffviBl156ibKyMqKjo9m0aRPdunUDoKysjNLS0jY9R/cMkSYiIiIiIiJXFo9mz77sduPGjXOafvnHGutMbaxjtzVcPXfyClVaWkpAQMAll7b+zYmIiIiIiIgYSz3WLRQWFuYY/OxS20VEREREROTapYZ1C3l5edGzZ8+2Pg0RERERERGX2K+SwcuuBnoUXERERERERKQF1GMtIiIiIiJyPTKpn7W1qGF9lTlna3xqsNbgWVlmeMYNgV0MzwDc9g3Dx1RleIZvXaXhGQAEBLolxuvUccMz2gUYnwFQ5d/eLTn3/+FpwzP+8rM3Dc8AuH9TsFtyToX1MjzDt/J7wzMAaswBbsmp8/Q2PCM26DPDMwBq3fRfnbpOxv9M8/cy/ucMwJkaH7fkBAecNTyj1uZneAZAmO1fhmfUtXfP90yP743/PyCAR/cehmd0/aHY8AwAetzonhy5oulXFCIiIiIiIiItoB5rERERERGR65Bdj4K3Gt1JERERERERkRZQj7WIiIiIiMj1SNNttRqXeqwzMzPp378/FouF4OBgRo4cyaFDh5xq7HY7M2fOJCwsDD8/P+Lj4zlw4IBTzdKlS4mPjycwMBCTycSJEyfqZXXv3h2TyeS0vPDCC041paWljBgxgnbt2tGpUycmTpxIVdW/B/Y4d+4cycnJ9O7dGy8vL0aOHFkvZ926dSQkJNC5c2cCAwOJjY3lgw8+cKpZvnx5vXMxmUycO3euSfctOTkZk8nEnDlznNa/9957mPTFLCIiIiIiclVzqWFdUFBAamoqhYWF5OfnU1NTQ2JiIpWV/x6peO7cuSxYsIBFixaxe/duQkNDSUhI4NSpU46aM2fO8MADDzBt2rTL5r300kuUlZU5lhkzZji21dbWMnz4cCorK9mxYwerVq1i7dq1PPfcc041fn5+TJw4kaFDhzaY8eGHH5KQkMCmTZsoKiri3nvvZcSIEezZs8epLjAw0OlcysrK8PX1bfK98/X1JSsri/Ly8ibvIyIiIiIiIlc+lx4F37Jli9PnZcuWERwcTFFREXFxcdjtdrKzs5k+fTqPPPIIACtWrCAkJITc3FyeffZZANLS0gDYvn37ZfMsFguhoaENbsvLy+PgwYN89dVXhIWFATB//nySk5OZPXs2gYGBtGvXjsWLFwPw17/+tcGe8ezsbKfPGRkZrF+/no0bN9KnTx/HepPJdMlzaYqhQ4dSUlJCZmYmc+fObfZxREREREREWoMGL2s9LbqTFRUVAHTo0AGAw4cPY7VaSUxMdNSYzWaGDBnCzp07XT5+VlYWHTt2JCYmhtmzZzs95r1r1y6io6MdjWqAYcOGYbPZKCoqau4lUVdXx6lTpxzXdMHp06fp1q0bXbt25T//8z/r9Wg3xtPTk4yMDHJycjh69Gizz09ERERERESuLM0evMxutzNlyhTuvvtuoqOjAbBarQCEhIQ41YaEhHDkyBGXjj9p0iTuvPNO2rdvz9/+9jfS09M5fPgwv/vd7xxZF+e0b98eHx8fx3k0x/z586msrOTxxx93rLvttttYvnw5vXv35uTJk7z66qsMHjyYTz/9lMjIyCYfe9SoUcTExPDiiy/y5ptvNlpvs9mw2WxO66qrffD2Njf9gkRERERERBqi8Z5aTbMb1uPHj2fv3r3s2LGj3raLB+Sy2+0uD9I1efJkx59vv/122rdvz2OPPeboxW4op7lZF6xcuZKZM2eyfv16goODHesHDhzIwIEDHZ8HDx7MnXfeSU5ODgsXLnQpIysri/vuu8/pXfBLyczMZNasWU7r/iPp1zw4eqZLmSIiIiIiImKcZj0KPmHCBDZs2MC2bdvo2rWrY/2Fd5Av7jE+duxYvd5lV11o2JaUlDiyLs4pLy+nurq6WVmrV6/m6aefZs2aNZcc6OwCDw8P+vfvz+eff+5yTlxcHMOGDWt04DaA9PR0KioqnJaEx9NdzhQREREREanH5NE2yzXIpauy2+2MHz+edevWsXXrViIiIpy2R0REEBoaSn5+vmNdVVUVBQUFDBo0qEUneuGd5i5dugAQGxvL/v37KSsrc9Tk5eVhNpvp27evS8deuXIlycnJ5ObmMnz48Ebr7XY7xcXFjnNx1Zw5c9i4cWOj752bzWYCAwOdFj0GLiIiIiIicmVx6VHw1NRUcnNzWb9+PRaLxdFjHBQUhJ+fHyaTibS0NDIyMoiMjCQyMpKMjAz8/f1JSkpyHMdqtWK1Wh29z/v27cNisRAeHk6HDh3YtWsXhYWF3HvvvQQFBbF7924mT57MQw89RHh4OACJiYlERUUxZswYXnnlFY4fP87zzz9PSkoKgYGBjqyDBw9SVVXF8ePHOXXqFMXFxQDExMQA5xvVTz75JK+++ioDBw50XJOfnx9BQUEAzJo1i4EDBxIZGcnJkydZuHAhxcXFvPbaa8245dC7d29Gjx5NTk5Os/YXERERERGRK4dLDesLU1fFx8c7rV+2bBnJyckATJ06lbNnzzJu3DjKy8sZMGAAeXl5WCwWR/2SJUuc3h2Oi4tzOo7ZbGb16tXMmjULm81Gt27dSElJYerUqY59PD09ef/99xk3bhyDBw/Gz8+PpKQk5s2b53RuDz74oNPAaRem0LLb7QC8/vrr1NTUkJqaSmpqqqPuqaeeYvny5QCcOHGCX/7yl1itVoKCgujTpw8ffvghd911lyu3z8nLL7/MmjVrmr2/iIiIiIhIS9g1eFmrMdkvtDDlqrBok3v+up6p+a3hGadvvtPwDICA0n1uyfnq1mGGZ/jWVRqeAdC59BO35FBXZ3jE6S63Gp4B4GGvdUuO/0HXpy501V9+1visBa3h/k3uGTPiVFgvwzN8K783PAOgxhzglpw6T2/DM077djQ8A6DW1OxxWl0SenS34RkHQh8wPAPgTI2PW3I8Tcb/nyba9rHhGQA13n6GZ/gf/8rwDACP78saL2oN/u0Mj6ju0LzXNl1luavxV0mvVCeLPmiT3MC+xv+/2d3c89NGRERERERErizX6EBibUF3soVKS0sJCAi45FJaWtrWpygiIiIiIiIGUo91C4WFhTkGRLvUdhEREREREbl2qWHdQl5eXvTs2bOtT0NERERERMQldjR4WWvRo+AiIiIiIiIiLaAe66tMpxvck/N9pyGGZ9R4uGfUUcJ7uyWmzg2/p/rOHmJ4BoBn1xi35PhUGz/K+Q9+XQ3PAPCkxi05Z/o8aHjG/ZuCDc8A+MuDmW7J6fXPTYZnnPOxNF7UCj49dYtbcnoGWA3P8DZVGZ4BUFnrnpHUrV37G55RedZseAZArd09PVju+K75Q1B3N6SA5dxxwzO+7+Km/8+Exbglx6/6lOEZ/qe/NTzjamfX4GWtRndSREREREREpAXUYy0iIiIiInI9Uo91q9GdFBEREREREWkBNaxFREREREREWsClhnVmZib9+/fHYrEQHBzMyJEjOXTokFON3W5n5syZhIWF4efnR3x8PAcOHHCqWbp0KfHx8QQGBmIymThx4kS9rO7du2MymZyWF154wammtLSUESNG0K5dOzp16sTEiROpqvr3YCjnzp0jOTmZ3r174+XlxciRIxu8roKCAvr27Yuvry8333wzS5YscdpeXV3NSy+9RI8ePfD19eWOO+5gy5YtTb5vycnJmEwm5syZ47T+vffew2TSEPciIiIiIuJ+dpOpTZZrkUsN64KCAlJTUyksLCQ/P5+amhoSExOprPz3yL5z585lwYIFLFq0iN27dxMaGkpCQgKnTv175L8zZ87wwAMPMG3atMvmvfTSS5SVlTmWGTNmOLbV1tYyfPhwKisr2bFjB6tWrWLt2rU899xzTjV+fn5MnDiRoUOHNphx+PBhHnzwQe655x727NnDtGnTmDhxImvXrnXUzJgxg9dff52cnBwOHjzI2LFjGTVqFHv27GnyvfP19SUrK4vy8vIm7yMiIiIiIiJXPpcGL7u4l3bZsmUEBwdTVFREXFwcdrud7Oxspk+fziOPPALAihUrCAkJITc3l2effRaAtLQ0ALZv337ZPIvFQmhoaIPb8vLyOHjwIF999RVhYWEAzJ8/n+TkZGbPnk1gYCDt2rVj8eLFAPz1r39tsGd8yZIlhIeHk52dDUCvXr345JNPmDdvHo8++igAb7/9NtOnT+fBB89Pc/OrX/2KDz74gPnz5/OHP/zh8jft/xk6dCglJSVkZmYyd+7cJu0jIiIiIiJiFE231XpadCcrKioA6NChA3C+99dqtZKYmOioMZvNDBkyhJ07d7p8/KysLDp27EhMTAyzZ892esx7165dREdHOxrVAMOGDcNms1FUVNTkjF27djmd74XjfPLJJ1RXVwNgs9nw9fV1qvHz82PHjh1NzvH09CQjI4OcnByOHj3a5P1ERERERETkytbshrXdbmfKlCncfffdREdHA2C1WgEICQlxqg0JCXFsa6pJkyaxatUqtm3bxvjx48nOzmbcuHGO7VartV5O+/bt8fHxcSmroeOEhIRQU1PD999/D5xvaC9YsIDPP/+curo68vPzWb9+PWVlZS5d06hRo4iJieHFF19sUr3NZuPkyZNOS3WVzaVMERERERERMVazG9bjx49n7969rFy5st62iwfkstvtLg/SNXnyZIYMGcLtt9/OM888w5IlS3jzzTf54YcfLpnT3KyGzvfH61999VUiIyO57bbb8PHxYfz48fz85z/H09PTpRw43wu/YsUKDh482GhtZmYmQUFBTsv6tzNdzhQREREREanHZGqb5RrUrIb1hAkT2LBhA9u2baNr166O9Rfeh764x/jYsWP1eoVdNXDgQABKSkocWRfnlJeXU11d7VJWQ8c5duwYXl5edOzYEYDOnTvz3nvvUVlZyZEjR/jnP/9JQEAAERERLl9HXFwcw4YNa3TgNoD09HQqKiqclofHpLucKSIiIiIiIsZxqWFtt9sZP34869atY+vWrfUalhEREYSGhpKfn+9YV1VVRUFBAYMGDWrRiV4YgbtLly4AxMbGsn//fqfHsfPy8jCbzfTt27fJx42NjXU63wvH6devH97e3k7rfX19ufHGG6mpqWHt2rU8/PDDzbqWOXPmsHHjxkbfOzebzQQGBjot3j7mZmWKiIiIiIj8mN3k0SbLtcilUcFTU1PJzc1l/fr1WCwWR09vUFAQfn5+mEwm0tLSyMjIIDIyksjISDIyMvD39ycpKclxHKvVitVqdfQ+79u3D4vFQnh4OB06dGDXrl0UFhZy7733EhQUxO7du5k8eTIPPfQQ4eHhACQmJhIVFcWYMWN45ZVXOH78OM8//zwpKSkEBgY6sg4ePEhVVRXHjx/n1KlTFBcXAxATEwPA2LFjWbRoEVOmTCElJYVdu3bx5ptvOj3i/vHHH/P1118TExPD119/zcyZM6mrq2Pq1Kmu33Ggd+/ejB49mpycnGbtLyIiIiIiIlcOlxrWF6auio+Pd1q/bNkykpOTAZg6dSpnz55l3LhxlJeXM2DAAPLy8rBYLI76JUuWMGvWLMfnuLg4p+OYzWZWr17NrFmzsNlsdOvWjZSUFKeGrKenJ++//z7jxo1j8ODB+Pn5kZSUxLx585zO7cEHH+TIkSOOz3369AH+/R51REQEmzZtYvLkybz22muEhYWxcOFCx1RbAOfOnWPGjBl88cUXBAQE8OCDD/L2229zww03uHL7nLz88susWbOm2fuLiIiIiIi0hJ1r833ntmCyX2hhylVh1U73/HXd3emA4Rk1Hj6GZwAEnPuh8aJW8INf18aLWqiy1t/wDIBQ+9duyfGprjQ8wx1/LwCe1Lglx7fW+HvW6cgnhmcA/OVB9wzG2OufmwzP8K5zz4wNn566xS05PYNcm8mjObxNVY0XtYLK2gC35AR4nDI8o/RsWONFraDWfu38R7t7u2/ckmM5d9zwjHPe7QzPAKgzuT44b3P4VRv/b8b/9LeGZwBY+j/olhwjfL9/V5vkdoqObZNcI12bD7iLiIiIiIiIuIlLj4JLfaWlpURFRV1y+8GDBx3vhYuIiIiIiFwprtWBxNqCGtYtFBYW5hgQ7VLbRURERERE5NqlhnULeXl50bNnz7Y+DREREREREdeYrp0xFdqa+v5FREREREREWkA91lcZf586t+R41xo/wu0Jj06GZwCEfvNXt+Sc6BFqeEY7zzOGZwC03/V/bsk5dWei4Rln6vwMzwCIqNzvlhyfCuNHaz4V1svwDHDPaN0A/7jN+NFa78/9peEZAEP9P3RLDj/4Gh4x88ufGp4BkBR/0i05Icf2GZ5xJMA9r5d5ebjn/xo/VBr/dRbipu/NX3QcaHjGLYffNzwD4LuIAW7JCSotNjxjb7fHDM8AuMstKXKlU8NaRERERETkOmTXA8ytRndSREREREREpAXUYy0iIiIiInIdsmvwslajHmsRERERERGRFnCpYZ2ZmUn//v2xWCwEBwczcuRIDh065FRjt9uZOXMmYWFh+Pn5ER8fz4EDB5xqli5dSnx8PIGBgZhMJk6cOHHJTJvNRkxMDCaTqd580ZMmTaJv376YzWZiYmLq7Xvu3DmSk5Pp3bs3Xl5ejBw5sl5NWVkZSUlJ3HrrrXh4eJCWllavJj4+HpPJVG8ZPnz4Jc/7x5KTkzGZTMyZM8dp/XvvvYdJvyUSEREREZE2YDd5tMlyLXLpqgoKCkhNTaWwsJD8/HxqampITEyksrLSUTN37lwWLFjAokWL2L17N6GhoSQkJHDq1ClHzZkzZ3jggQeYNm1ao5lTp04lLKzhUTDtdju/+MUveOKJJxrcXltbi5+fHxMnTmTo0KEN1thsNjp37sz06dO54447GqxZt24dZWVljmX//v14enry//1//1+j53+Br68vWVlZlJeXN3kfERERERERufK59I71li1bnD4vW7aM4OBgioqKiIuLw263k52dzfTp03nkkUcAWLFiBSEhIeTm5vLss88COHqFt2/fftm8zZs3k5eXx9q1a9m8eXO97QsXLgTgu+++Y+/evfW2t2vXjsWLFwPw17/+tcGe8e7du/Pqq68C8NZbbzV4Hh06dHD6vGrVKvz9/V1qWA8dOpSSkhIyMzOZO3duk/cTERERERGRK1uL+uErKiqAfzc8Dx8+jNVqJTHx33PTms1mhgwZws6dO1069rfffktKSgpvv/02/v7+LTnNVvfmm2/y05/+lHbt2jV5H09PTzIyMsjJyeHo0aMGnp2IiIiIiEjj7JjaZLkWNbthbbfbmTJlCnfffTfR0dEAWK1WAEJCQpxqQ0JCHNuaeuzk5GTGjh1Lv379mnuKhvjb3/7G/v37eeaZZ1zed9SoUcTExPDiiy8acGYiIiIiIiLSFpo93db48ePZu3cvO3bsqLft4gG57Ha7S4N05eTkcPLkSdLT05t7eoZ58803iY6O5q677mrW/llZWdx3330899xzjdbabDZsNpvTuuoqL7x9zM3KFhERERERueBaHUisLTTrTk6YMIENGzawbds2unbt6lgfGhoKUK93+tixY/V6sS9n69atFBYWYjab8fLyomfPngD069ePp556qjmn3CrOnDnDqlWrmtVbfUFcXBzDhg1r0sBtmZmZBAUFOS3vLJ/T6H4iIiIiIiLiPi71WNvtdiZMmMC7777L9u3biYiIcNoeERFBaGgo+fn59OnTB4CqqioKCgrIyspqcs7ChQv5zW9+4/j8zTffMGzYMFavXs2AAQNcOeVWtWbNGmw2Gz/72c9adJw5c+YQExPDLbfcctm69PR0pkyZ4rQuf3+zHzIQERERERERA7jUSktNTSU3N5f169djsVgcPdNBQUH4+flhMplIS0sjIyODyMhIIiMjycjIwN/fn6SkJMdxrFYrVquVkpISAPbt24fFYiE8PJwOHToQHh7ulBsQEABAjx49nHrIS0pKOH36NFarlbNnzzrmuY6KisLHxweAgwcPUlVVxfHjxzl16pSj5sfzXl9Yd/r0ab777juKi4vx8fEhKirK6TzefPNNRo4cSceOHV25bfX07t2b0aNHk5OTc9k6s9mM2ez82Le3T22LskVERERERADsLryuK5fnUsP6wtRV8fHxTuuXLVtGcnIycH7e6bNnzzJu3DjKy8sZMGAAeXl5WCwWR/2SJUuYNWuW43NcXFy94zTFM888Q0FBgePzhV7yw4cP0717dwAefPBBjhw5Uq/GbrfXWwdQVFREbm4u3bp148svv3Ss/+yzz9ixYwd5eXlNPr/Lefnll1mzZk2rHEtERERERETajsuPgjfGZDIxc+ZMZs6cecmaxrZfrHv37g1mNzYPNuDUOL6UplzXLbfc0qS6hixfvrzeum7dunHu3LlmHU9ERERERKSlrtWpr9qChoETERERERGRK9pvf/tbIiIi8PX1pW/fvnz00UeXrF23bh0JCQl07tyZwMBAYmNj+eCDDww9PzWsW6i0tJSAgIBLLqWlpW19iiIiIiIiIvXYTR5tsrhq9erVpKWlMX36dPbs2cM999zDf/zHf1yyrfXhhx+SkJDApk2bKCoq4t5772XEiBHs2bOnpbfskjTEdAuFhYU5Bj+71HYRERERERFpngULFvD00087pj3Ozs7mgw8+YPHixWRmZtarz87OdvqckZHB+vXr2bhxo9P4Wq1JDesW+vE82yIiIiIiInJ5NpsNm83mtK6hGZHg/PTNRUVFvPDCC07rExMT2blzZ5Py6urqOHXqFB06dGj+STdCj4KLiIiIiIhch+yY2mTJzMwkKCjIaWmo5xng+++/p7a2lpCQEKf1ISEhjumfGzN//nwqKyt5/PHHW3zPLkU91lcZk6l5I5O76qy3pfGiFjpV7W94BgBnK90Sc6rO+Ht2sso996ybJdAtOSbqDM/obG/aN9yWOucb5JYc32OHjc+o/N7wDIBzPsb/mwG4P/eXhmf8JWmp4RkA96+d6JYcqoyftcJs9jQ8AyCk5iu35NR5ehue4eHhnv8D+HjUuCXH29P4nwEebpqB5btzxv/cvOX0ScMzAM55tHNLDrW1hkcEebvnnoF7/g9wLUlPT2fKlClO6xrqrf4x00Vzbtvt9nrrGrJy5UpmzpzJ+vXrCQ4Odv1km0gNaxERERERketQcwYSaw2Xeuy7IZ06dcLT07Ne7/SxY8fq9WJfbPXq1Tz99NP86U9/YujQoc0+36bQo+AiIiIiIiJyRfLx8aFv377k5+c7rc/Pz2fQoEGX3G/lypUkJyeTm5vL8OHDjT5N9ViLiIiIiIjIlWvKlCmMGTOGfv36ERsby9KlSyktLWXs2LHA+UfLv/76a37/+98D5xvVTz75JK+++ioDBw509Hb7+fkRFGTMo/tqWIuIiIiIiFyH7DT+jvKV4IknnuCHH37gpZdeoqysjOjoaDZt2kS3bt0AKCsrc5rT+vXXX6empobU1FRSU1Md65966imWL19uyDm69Ch4ZmYm/fv3x2KxEBwczMiRIzl06JBTjd1uZ+bMmYSFheHn50d8fDwHDhxwqlm6dCnx8fEEBgZiMpk4ceLEJTNtNhsxMTGYTKZ680VPmjSJvn37YjabiYmJqbfvuXPnSE5Opnfv3nh5eTFy5MgGMwoKCujbty++vr7cfPPNLFmyxGn7gQMHePTRR+nevTsmk6nevGiNSU5OxmQyMWfOHKf17733XpNeuBcREREREbmejRs3ji+//BKbzUZRURFxcXGObcuXL2f79u2Oz9u3b8dut9dbjGpUg4sN64KCAlJTUyksLCQ/P5+amhoSExOprPz3qMtz585lwYIFLFq0iN27dxMaGkpCQgKnTp1y1Jw5c4YHHniAadOmNZo5depUwsLCGtxmt9v5xS9+wRNPPNHg9traWvz8/Jg4ceIlX1Y/fPgwDz74IPfccw979uxh2rRpTJw4kbVr1zqd780338ycOXMIDQ1t9Jwb4uvrS1ZWFuXl5c3aX0REREREpDXZTR5tslyLXHoUfMuWLU6fly1bRnBwsOM3Bna7nezsbKZPn84jjzwCwIoVKwgJCSE3N5dnn30WgLS0NACn3yo0ZPPmzeTl5bF27Vo2b95cb/vChQsB+O6779i7d2+97e3atWPx4sUA/PWvf22wZ3zJkiWEh4c7eqF79erFJ598wrx583j00UcB6N+/P/379weoNzF5Uw0dOpSSkhIyMzOZO3dus44hIiIiIiIiV54W/bqgoqICgA4dOgDne3+tViuJiYmOGrPZzJAhQ9i5c6dLx/72229JSUnh7bffxt/fuLl7d+3a5XS+AMOGDeOTTz6hurq61XI8PT3JyMggJyeHo0ePttpxRUREREREmsOOqU2Wa1GzG9Z2u50pU6Zw9913Ex0dDeAYbe3i+cRCQkLqzTvW2LGTk5MZO3Ys/fr1a+4pNonVam3wfGtqavj+++9bNWvUqFHExMTw4osvtupxRUREREREpO00e1Tw8ePHs3fvXnbs2FFv28UDctntdpcG6crJyeHkyZOkp6c39/Rc0tD5NrS+NWRlZXHffffx3HPPNVprs9mw2WxO66qrPPH2adpk6iIiIiIiImK8ZvVYT5gwgQ0bNrBt2za6du3qWH9hYK+Le6ePHTtWr1f4crZu3UphYSFmsxkvLy969uwJQL9+/Xjqqaeac8qXFBoa2uD5enl50bFjx1bNAoiLi2PYsGFNGrgtMzOToKAgp+VPy7Ja/ZxEREREROT6YzeZ2mS5FrnUY22325kwYQLvvvsu27dvJyIiwml7REQEoaGh5Ofn06dPHwCqqqooKCggK6vpDcKFCxfym9/8xvH5m2++YdiwYaxevZoBAwa4csqNio2NZePGjU7r8vLy6NevH97e3q2adcGcOXOIiYnhlltuuWxdeno6U6ZMcVr35wOehpyTiIiIiIiINI9LDevU1FRyc3NZv349FovF0dMbFBSEn58fJpOJtLQ0MjIyiIyMJDIykoyMDPz9/UlKSnIcx2q1YrVaKSkpAWDfvn1YLBbCw8Pp0KED4eHhTrkBAQEA9OjRw6mHvKSkhNOnT2O1Wjl79qxjnuuoqCh8fHwAOHjwIFVVVRw/fpxTp045ai7Mez127FgWLVrElClTSElJYdeuXbz55pusXLnSkVNVVcXBgwcdf/76668pLi4mICDA0Zvuit69ezN69GhycnIuW2c2mzGbnR/79vapcTlPRERERETkYnb7tdl73BZcalhfmLoqPj7eaf2yZctITk4Gzs87ffbsWcaNG0d5eTkDBgwgLy8Pi8XiqF+yZAmzZs1yfL4wufePj9MUzzzzDAUFBY7PF3rJDx8+TPfu3QF48MEHOXLkSL2aC+9RR0REsGnTJiZPnsxrr71GWFgYCxcudEy1Bed7zC/sBzBv3jzmzZvHkCFDGp0y7FJefvll1qxZ06x9RURERERE5Mrh8qPgjTGZTMycOZOZM2desqax7Rfr3r17g9lNadR++eWXjdYMGTKEv//97y7nN9Xy5cvrrevWrRvnzp1r9jFFRERERETkytDsUcFFRERERETk6mVv/uzLchHdyRYqLS0lICDgkktpaWlbn6KIiIiIiIgYSD3WLRQWFuYYEO1S20VERERERK40djR4WWtRw7qFfjzPtoiIiIiIiFx/9Ci4iIiIiIiISAuox1pEREREROQ6pEfBW48a1lcZb886t+R41VUZnuHrZXwGgD2oo1tyztX4GJ7h51lteMa15oxnoFtyzB5n3ZJDtc3wiBpzgOEZAJ+eusUtOUP9PzQ84/61Ew3PAPjLowvdknP/qrGGZ1i/OWV4BsBZb4tbcvxN3xqe4a6fAR4m9/xf49RZT+ND7O65lpNnvQ3PsLfvZHgGQEB1uVtyqDb+/4GHyt0z1tGtbkmRK50a1iIiIiIiItch9Vi3Hr1jLSIiIiIiItIC6rEWERERERG5DqnHuvWox1pERERERESkBVxqWGdmZtK/f38sFgvBwcGMHDmSQ4cOOdXY7XZmzpxJWFgYfn5+xMfHc+DAAaeapUuXEh8fT2BgICaTiRMnTlwy02azERMTg8lkori42GnbpEmT6Nu3L2azmZiYmAb337dvH0OGDMHPz48bb7yRl156Cbvd7theVlZGUlISt956Kx4eHqSlpTV4nBMnTpCamkqXLl3w9fWlV69ebNq06ZLn/WPJycmYTCbmzJnjtP69997DZNJviURERERERK5mLjWsCwoKSE1NpbCwkPz8fGpqakhMTKSystJRM3fuXBYsWMCiRYvYvXs3oaGhJCQkcOrUv0f/PHPmDA888ADTpk1rNHPq1KmEhTU8op/dbucXv/gFTzzxRIPbT548SUJCAmFhYezevZucnBzmzZvHggULHDU2m43OnTszffp07rjjjgaPU1VVRUJCAl9++SXvvPMOhw4d4o033uDGG29s9Pwv8PX1JSsri/JyN420KCIiIiIichl2u6lNlmuRS+9Yb9myxenzsmXLCA4OpqioiLi4OOx2O9nZ2UyfPp1HHnkEgBUrVhASEkJubi7PPvssgKNXePv27ZfN27x5M3l5eaxdu5bNmzfX275w4flpR7777jv27t1bb/sf//hHzp07x/LlyzGbzURHR/PZZ5+xYMECpkyZgslkonv37rz66qsAvPXWWw2ex1tvvcXx48fZuXMn3t7np1Po1q3bZc/9YkOHDqWkpITMzEzmzp3r0r4iIiIiIiJy5WrRO9YVFRUAdOjQAYDDhw9jtVpJTEx01JjNZoYMGcLOnTtdOva3335LSkoKb7/9Nv7+/s06v127djFkyBDMZrNj3bBhw/jmm2/48ssvm3ycDRs2EBsbS2pqKiEhIURHR5ORkUFtbW2Tj+Hp6UlGRgY5OTkcPXrUlcsQERERERFpdXZMbbJci5rdsLbb7UyZMoW7776b6OhoAKxWKwAhISFOtSEhIY5tTT12cnIyY8eOpV+/fs09RaxWa4Pn8uNzbYovvviCd955h9raWjZt2sSMGTOYP38+s2fPdul8Ro0aRUxMDC+++GKT6m02GydPnnRaqqpsLmWKiIiIiIiIsZrdsB4/fjx79+5l5cqV9bZdPCCX3W53aZCunJwcTp48SXp6enNP77Ln0tD6y6mrqyM4OJilS5fSt29ffvrTnzJ9+nQWL17s8vlkZWWxYsUKDh482GhtZmYmQUFBTsuat/QYuYiIiIiIyJWkWQ3rCRMmsGHDBrZt20bXrl0d60NDQ4H6vcHHjh2r13N8OVu3bqWwsBCz2YyXlxc9e/YEoF+/fjz11FNNPk5oaGiD5wL1e9Uvp0uXLtxyyy14eno61vXq1Qur1UpVVVWTjwMQFxfHsGHDmjRwW3p6OhUVFU7L47+Y6lKeiIiIiIhIQ/QoeOtxqWFtt9sZP34869atY+vWrURERDhtj4iIIDQ0lPz8fMe6qqoqCgoKGDRoUJNzFi5cyKeffkpxcTHFxcWOaa1Wr17t0uPXsbGxfPjhh06N37y8PMLCwujevXuTjzN48GBKSkqoq6tzrPvss8/o0qULPj4+TT7OBXPmzGHjxo2NvnduNpsJDAx0Wnx8zJfdR0RERERERNzLpVHBU1NTyc3NZf369VgsFkdvcFBQEH5+fphMJtLS0sjIyCAyMpLIyEgyMjLw9/cnKSnJcRyr1YrVaqWkpAQ4P9e0xWIhPDycDh06EB4e7pQbEBAAQI8ePZx6yEtKSjh9+jRWq5WzZ8865rmOiorCx8eHpKQkZs2aRXJyMtOmTePzzz8nIyODX//6106Pgl/Y7/Tp03z33XcUFxfj4+NDVFQUAL/61a/Iyclh0qRJTJgwwXGciRMnunL7HHr37s3o0aPJyclp1v4iIiIiIiItda32HrcFlxrWF94pjo+Pd1q/bNkykpOTgfPzTp89e5Zx48ZRXl7OgAEDyMvLw2KxOOqXLFnCrFmzHJ/j4uLqHacpnnnmGQoKChyf+/TpA5wfnbx79+4EBQWRn59Pamoq/fr1o3379kyZMoUpU6Y4HefCfgBFRUXk5ubSrVs3x8jhN910E3l5eUyePJnbb7+dG2+8kUmTJvHf//3fTT7Xi7388susWbOm2fuLiIiIiIjIlcGlhvWFgb8ux2QyMXPmTGbOnHnJmsa2X6x79+4NZjc2Dzac7x3+8MMPL1vTlOuKjY2lsLCw0bqGLF++vN66bt26ce7cuWYdT0REREREpKXsdvVYt5YWzWMtIiIiIiIicr1Tw7qFSktLCQgIuORSWlra1qcoIiIiIiIiBnLpUXCpLywszDH42aW2i4iIiIiIXGnqNHhZq1HDuoV+PM+2iIiIiIiIXH/UsBYREREREbkOabqt1qOG9VWmutY9r8Wf82xneEZNjXu+/Gr8A92S4+NZY3jG6WpfwzMAqrpGuiXnrLel8aIWMtvPGp4B4GGvdUtOVWiE4Rl1nt6GZwD0DLC6JYcf3PDvpso9szzcv2qsW3L+8tMlhmcEvPpLwzMAPO3Gf28GqPX2NzzDw1RneAZAVZ17fj6HBNkMz/D46qThGQDVPm5onJjc83/Ak94d3ZIT1KmL4Rk1dWo0ivto8DIRERERERGRFlCPtYiIiIiIyHVI81i3HvVYi4iIiIiIiLSAeqxFRERERESuQxq8rPW41GOdmZlJ//79sVgsBAcHM3LkSA4dOuRUY7fbmTlzJmFhYfj5+REfH8+BAwecapYuXUp8fDyBgYGYTCZOnDhxyUybzUZMTAwmk6nefNGlpaWMGDGCdu3a0alTJyZOnEhVVZVTzZo1a4iJicHf359u3brxyiuvOG3fsWMHgwcPpmPHjvj5+XHbbbfxv//7v/XOY+3atURFRWE2m4mKiuLdd99twh07Lzk5GZPJxJw5c5zWv/fee5hM+mIWERERERG5mrnUsC4oKCA1NZXCwkLy8/OpqakhMTGRyspKR83cuXNZsGABixYtYvfu3YSGhpKQkMCpU6ccNWfOnOGBBx5g2rRpjWZOnTqVsLCweutra2sZPnw4lZWV7Nixg1WrVrF27Vqee+45R83mzZsZPXo0Y8eOZf/+/fz2t791nNsF7dq1Y/z48Xz44Yf84x//YMaMGcyYMYOlS5c6anbt2sUTTzzBmDFj+PTTTxkzZgyPP/44H3/8cZPvna+vL1lZWZSXlzd5HxEREREREaPY7aY2Wa5FLj0KvmXLFqfPy5YtIzg4mKKiIuLi4rDb7WRnZzN9+nQeeeQRAFasWEFISAi5ubk8++yzAKSlpQGwffv2y+Zt3ryZvLw81q5dy+bNm5225eXlcfDgQb766itHw3v+/PkkJycze/ZsAgMDefvttxk5ciRjx56fnuTmm2/mv//7v8nKyiI1NRWTyUSfPn3o06eP47jdu3dn3bp1fPTRR/zyl+enAsnOziYhIYH09HQA0tPTKSgoIDs7m5UrVzbp3g0dOpSSkhIyMzOZO3duk/YRERERERGRK1+LBi+rqKgAoEOHDgAcPnwYq9VKYmKio8ZsNjNkyBB27tzp0rG//fZbUlJSePvtt/H3rz835K5du4iOjnbqzR42bBg2m42ioiLg/GPkvr7O85f6+flx9OhRjhw50mDunj172LlzJ0OGDHHK+vE1Xchy5Zo8PT3JyMggJyeHo0ePNnk/ERERERERubI1u2Ftt9uZMmUKd999N9HR0QBYrVYAQkJCnGpDQkIc25p67OTkZMaOHUu/fv0arLFarfVy2rdvj4+PjyNr2LBhrFu3jr/85S/U1dXx2WefkZ2dDUBZWZnTvl27dsVsNtOvXz9SU1N55plnLpvl6jUBjBo1ipiYGF588cUm1dtsNk6ePOm0VFfZXMoUERERERFpiB1TmyzXomY3rMePH8/evXsbfBT64gG57Ha7S4N05eTkcPLkScej15fS0DF/nJWSksL48eP5z//8T3x8fBg4cCA//elPgfM9yD/20Ucf8cknn7BkyZIGH/Fu6TVdkJWVxYoVKzh48GCjtZmZmQQFBTktf1qW5XKmiIiIiIiIGKdZDesJEyawYcMGtm3bRteuXR3rQ0NDAer15B47dqxej+/lbN26lcLCQsxmM15eXvTs2ROAfv368dRTTzmyLs4pLy+nurrakWUymcjKyuL06dMcOXIEq9XKXXfdBZx/l/rHIiIi6N27NykpKUyePJmZM2c6XVdLr+mCuLg4hg0b1qSB29LT06moqHBa/r+f/7fLmSIiIiIiIhfT4GWtx6WGtd1uZ/z48axbt46tW7cSERHhtD0iIoLQ0FDy8/Md66qqqigoKGDQoEFNzlm4cCGffvopxcXFFBcXs2nTJgBWr17N7NmzAYiNjWX//v1Oj3Tn5eVhNpvp27ev0/E8PT258cYb8fHxYeXKlcTGxhIcHHzZ67TZ/v3IdWxsrNM1Xchy5Zp+bM6cOWzcuLHRd7TNZjOBgYFOi7ePuVmZIiIiIiIiYgyXRgVPTU0lNzeX9evXY7FYHL24QUFB+Pn5YTKZSEtLIyMjg8jISCIjI8nIyMDf35+kpCTHcaxWK1arlZKSEgD27duHxWIhPDycDh06EB4e7pQbEBAAQI8ePRw95ImJiURFRTFmzBheeeUVjh8/zvPPP09KSgqBgYEAfP/997zzzjvEx8dz7tw5li1bxp/+9CcKCgocx37ttdcIDw/ntttuA87Paz1v3jwmTJjgqJk0aRJxcXFkZWXx8MMPs379ev785z+zY8cOV26fQ+/evRk9ejQ5OTnN2l9ERERERESuHC41rBcvXgxAfHy80/ply5aRnJwMnJ93+uzZs4wbN47y8nIGDBhAXl4eFovFUb9kyRJmzZrl+BwXF1fvOI3x9PTk/fffZ9y4cQwePBg/Pz+SkpKYN2+eU92KFSt4/vnnsdvtxMbGsn37dsfj4AB1dXWkp6dz+PBhvLy86NGjB3PmzHFMDQYwaNAgVq1axYwZM/if//kfevTowerVqxkwYECTzrUhL7/8MmvWrGn2/iIiIiIiIi1R19YncA0x2e12e1ufhDTdxqIat+T0uuErwzPKa9obngFwW8Vf3ZLz2Q2xhmecrvZtvKgV9Dn3kVtyTgSGN17UQnZTi2YVbDIPe61bcoJOGv9vs9psabyoFXznZ/zfP0D3L/5sfEjVOeMzAM6ddUvMX366xPCMra/+3fAMgLSEhqfXbG2WymOGZ5T43WF4BkBVnUv9Ls12tsbb8IzBX/3e8AyADe2fabyohUbYVhueAVB6091uybnJ+jfDM7Z4jzI8A+CRu9zzfw0jFP6zok1yB94W1Ca5RnLPd04RERERERG5olyrA4m1hav31ytXiNLSUgICAi65lJaWtvUpioiIiIiIiIHUY91CYWFhFBcXX3a7iIiIiIjIlcaOeqxbixrWLfTjebZFRERERETk+qNHwUVERERERERaQKOCX2Xe/Zt7Rh7u1bHM8Ixqu/GjgQIUfhnilpzoG08anhHoXWl4BsDHpV3cktP7xhOGZ3xVEWh4BoAJ93wrtdUY//vQ2ODPDM8AqPFwz/eAN/5i/Cs5ZrOn4RkA1m9OuSUnINBseMZ9k+40PAOgbMsht+QEBxn/87mjv3tGhS8/554ZKLoHfm94xvJ89/wMSLv/C8MzVh/8ieEZAAk/+c4tOX8rDTY84+HQjw3PAOj8k+ZPwdvW/nrwdJvkDo4KaJNcI6nHWkRERERERKQF9I61iIiIiIjIdUiDl7Ue9ViLiIiIiIiItIAa1iIiIiIiIiIt4FLDOjMzk/79+2OxWAgODmbkyJEcOuQ8KIjdbmfmzJmEhYXh5+dHfHw8Bw4ccKpZunQp8fHxBAYGYjKZOHHixCUzbTYbMTExmEymevNFl5aWMmLECNq1a0enTp2YOHEiVVVVTjUffPABAwcOxGKx0LlzZx599FEOHz7s2F5WVkZSUhK33norHh4epKWl1TuHdevW0a9fP2644QbatWtHTEwMb7/9dtNuGpCcnIzJZGLOnDlO69977z1MJj1+ISIiIiIi7ldnb5ulOX77298SERGBr68vffv25aOPPrpsfUFBAX379sXX15ebb76ZJUuWNC+4iVxqWBcUFJCamkphYSH5+fnU1NSQmJhIZeW/RyqeO3cuCxYsYNGiRezevZvQ0FASEhI4derfI5meOXOGBx54gGnTpjWaOXXqVMLC6o/oWltby/Dhw6msrGTHjh2sWrWKtWvX8txzzzlqvvjiCx5++GHuu+8+iouL+eCDD/j+++955JFHHDU2m43OnTszffp07rjjjgbPoUOHDkyfPp1du3axd+9efv7zn/Pzn/+cDz74oEn3DcDX15esrCzKy8ubvI+IiIiIiMj1bvXq1aSlpTF9+nT27NnDPffcw3/8x39QWlraYP3hw4d58MEHueeee9izZw/Tpk1j4sSJrF271rBzdGnwsi1btjh9XrZsGcHBwRQVFREXF4fdbic7O5vp06c7Gq8rVqwgJCSE3Nxcnn32WQBHr/D27dsvm7d582by8vJYu3YtmzdvdtqWl5fHwYMH+eqrrxwN7/nz55OcnMzs2bMJDAzk73//O7W1tfzmN7/Bw+P87xCef/55Hn74Yaqrq/H29qZ79+68+uqrALz11lsNnkd8fLzT50mTJrFixQp27NjBsGHDLn/T/p+hQ4dSUlJCZmYmc+fObdI+IiIiIiIiRrlaBi9bsGABTz/9NM888wwA2dnZfPDBByxevJjMzMx69UuWLCE8PJzs7GwAevXqxSeffMK8efN49NFHDTnHFr1jXVFRAZzv0YXzvxmwWq0kJiY6asxmM0OGDGHnzp0uHfvbb78lJSWFt99+G39//3rbd+3aRXR0tFNv9rBhw7DZbBQVFQHQr18/PD09WbZsGbW1tVRUVPD222+TmJiIt3fz5k+12+385S9/4dChQ8TFxTV5P09PTzIyMsjJyeHo0aPNyhYREREREbmeVFVVUVRU5NTGBEhMTLxkG3PXrl316ocNG8Ynn3xCdXW1IefZ7Ia13W5nypQp3H333URHRwNgtVoBCAkJcaoNCQlxbGvqsZOTkxk7diz9+vVrsMZqtdbLad++PT4+Po6s7t27k5eXx7Rp0zCbzdxwww0cPXqUVatWNflcLqioqCAgIAAfHx+GDx9OTk4OCQkJLh1j1KhRxMTE8OKLL7qcLyIiIiIi0prsdlObLDabjZMnTzotNputwXP8/vvvqa2tdamN2VBbMSQkhJqaGr7//vvWuXkXaXbDevz48ezdu5eVK1fW23bxgFx2u92lQbpycnI4efIk6enpl61r6Jg/zrJarTzzzDM89dRT7N69m4KCAnx8fHjsscew2117a95isVBcXMzu3buZPXs2U6ZMafRR9oZkZWWxYsUKDh482GhtQ19w1VUNf8GJiIiIiIhcDTIzMwkKCnJaGnqk+8dcbWM2VN/Q+tbSrIb1hAkT2LBhA9u2baNr166O9aGhoQD1fnNw7Nixer8xuJytW7dSWFiI2WzGy8uLnj17Aucf7X7qqaccWRfnlJeXU11d7ch67bXXCAwMZO7cufTp04e4uDj+8Ic/8Je//IWPP/7YpWv28PCgZ8+exMTE8Nxzz/HYY481+pffkLi4OIYNG9akgdsa+oJbu2JOo/uJiIiIiIhcqdLT06moqHBaLtWp2qlTJzw9PV1qYzbUVjx27BheXl507NixdS7iIi41rO12O+PHj2fdunVs3bqViIgIp+0RERGEhoaSn5/vWFdVVUVBQQGDBg1qcs7ChQv59NNPKS4upri4mE2bNgHnR4ObPXs2ALGxsezfv5+ysjLHfnl5eZjNZvr27QucH33c09PT6dgXPtfV1blw5fXZ7fZLPq7QmDlz5rBx48ZG3ztv6Avu0adeaFamiIiIiIjIj9ntbbOYzWYCAwOdFrPZ3OA5+vj40LdvX6c2JkB+fv4l25ixsbH16vPy8ujXr1+zx9pqjEujgqemppKbm8v69euxWCyO3wIEBQXh5+eHyWQiLS2NjIwMIiMjiYyMJCMjA39/f5KSkhzHsVqtWK1WSkpKANi3bx8Wi4Xw8HA6dOhAeHi4U25AQAAAPXr0cPSQJyYmEhUVxZgxY3jllVc4fvw4zz//PCkpKQQGBgIwfPhw/vd//5eXXnqJ//qv/+LUqVNMmzaNbt260adPH8fxL8yPffr0ab777juKi4vx8fEhKioKON9z3K9fP3r06EFVVRWbNm3i97//PYsXL3bl9jn07t2b0aNHk5OTc9k6s9lc7wvM26e2WZkiIiIiIiJXoylTpjBmzBj69etHbGwsS5cupbS0lLFjxwLnOyS//vprfv/73wMwduxYFi1axJQpU0hJSWHXrl28+eabDb7G3FpcalhfaEhePP3UsmXLSE5OBs7PO3327FnGjRtHeXk5AwYMIC8vD4vF4qhfsmQJs2bNcny+MLr2j4/TGE9PT95//33GjRvH4MGD8fPzIykpiXnz5jlq7rvvPnJzc5k7dy5z587F39+f2NhYtmzZgp+fn6Pux43soqIicnNz6datG19++SUAlZWVjBs3jqNHj+Ln58dtt93GH/7wB5544okmnWtDXn75ZdasWdPs/UVERERERFqi7iqZbuuJJ57ghx9+4KWXXqKsrIzo6Gg2bdpEt27dACgrK3Oa0zoiIoJNmzYxefJkXnvtNcLCwli4cKFhU20BmOyujuIlberdv7mnx7pXx7LGi1qo2m7MYxgXK/yy6e/3t0T0jScNzwj0rjQ8A+Dj0i5uyel94wnDM76qCDQ8A8CEe76V2mpaNEtik8QGf2Z4BkCNh3u+B7zxl7DGi1rIbPZsvKgVWL855ZacgMCGH8drTfdNutPwDICyLYfckhMcZPzP547+Zw3PACg/5+uWnO6BxozM+2PL893zMyDt/i8Mz1h98CeGZwAk/OQ7t+T8rTTY8IyHQ10bU6m5Ov9kgFtyjPCXfefaJPf+3u75PuNOxv8PTUREREREROQa5tKj4FJfaWmp413shhw8eLDeO+MiIiIiIiJtzW6/Oh4FvxqoYd1CYWFhjsHPLrVdRERERERErl1qWLfQj+fZFhERERERuVpotK3Wo3esRURERERERFpAo4JfZXLed89f1391KzQ847RvR8MzAMw1Z9ySc9TU3fCMWje9B3PS5td4USsI9T9heEa3U3sNzwD4OvDSYy20Jg9TneEZPtgMzwA4XWdpvOgqEVLzlVtyznq755552msMz/ig1D3/Zro8cKtbcm46+JHhGe0xfhRtgBoPH7fkeNcaPxpxQOUxwzMAdnsMNjzjBl/3jAof4mH8zDAAR2u6Gp7RxedbwzMAInpcvU+v5n1a1Sa5iXe45/uMO6nHWkRERERERKQF1LAWERERERERaQENXiYiIiIiInIdqtNLwa1GPdYiIiIiIiIiLeBSwzozM5P+/ftjsVgIDg5m5MiRHDp0yKnGbrczc+ZMwsLC8PPzIz4+ngMHDjjVLF26lPj4eAIDAzGZTJw4ceKSmTabjZiYGEwmU735oktLSxkxYgTt2rWjU6dOTJw4kaoq5xfw7XY78+bN45ZbbsFsNnPTTTeRkZHh2L5u3ToSEhLo3LkzgYGBxMbG8sEHH9Q7jxMnTpCamkqXLl3w9fWlV69ebNq0qUn3LTk5GZPJxJw5c5zWv/fee5hMmpRdRERERETcz243tclyLXKpYV1QUEBqaiqFhYXk5+dTU1NDYmIilZWVjpq5c+eyYMECFi1axO7duwkNDSUhIYFTp045as6cOcMDDzzAtGnTGs2cOnUqYWFh9dbX1tYyfPhwKisr2bFjB6tWrWLt2rU899xzTnWTJk3id7/7HfPmzeOf//wnGzdu5K677nJs//DDD0lISGDTpk0UFRVx7733MmLECPbs2eOoqaqqIiEhgS+//JJ33nmHQ4cO8cYbb3DjjTc2+d75+vqSlZVFeXl5k/cRERERERGRK59L71hv2bLF6fOyZcsIDg6mqKiIuLg47HY72dnZTJ8+nUceeQSAFStWEBISQm5uLs8++ywAaWlpAGzfvv2yeZs3byYvL4+1a9eyefNmp215eXkcPHiQr776ytHwnj9/PsnJycyePZvAwED+8Y9/sHjxYvbv38+ttzY83UZ2drbT54yMDNavX8/GjRvp06cPAG+99RbHjx9n586deHt7A9CtW7fL36yLDB06lJKSEjIzM5k7d65L+4qIiIiIiMiVq0XvWFdUVADQoUMHAA4fPozVaiUxMdFRYzabGTJkCDt37nTp2N9++y0pKSm8/fbb+Pv719u+a9cuoqOjnXqzhw0bhs1mo6ioCICNGzdy880383//939ERETQvXt3nnnmGY4fP37J3Lq6Ok6dOuW4JoANGzYQGxtLamoqISEhREdHk5GRQW1tbZOvx9PTk4yMDHJycjh69GiT9xMRERERETGC3d42y7Wo2Q1ru93OlClTuPvuu4mOjgbAarUCEBIS4lQbEhLi2NbUYycnJzN27Fj69evXYI3Vaq2X0759e3x8fBxZX3zxBUeOHOFPf/oTv//971m+fDlFRUU89thjl8yeP38+lZWVPP744451X3zxBe+88w61tbVs2rSJGTNmMH/+fGbPnt3kawIYNWoUMTExvPjiiy7tJyIiIiIiIleuZk+3NX78ePbu3cuOHTvqbbt4QC673e7SIF05OTmcPHmS9PT0y9Y1dMwfZ9XV1WGz2fj973/PLbfcAsCbb75J3759OXToUL3Hw1euXMnMmTNZv349wcHBjvV1dXUEBwezdOlSPD096du3L9988w2vvPIKv/71r5t8XQBZWVncd9999d4Fb4jNZsNmszmtq672wdvb7FKmiIiIiIjIxeq4NgcSawvN6rGeMGECGzZsYNu2bXTt2tWxPjQ0FKBe7/SxY8fq9S5fztatWyksLMRsNuPl5UXPnj0B6NevH0899ZQj6+Kc8vJyqqurHVldunTBy8vL0agG6NWrF3B+RPEfW716NU8//TRr1qxh6NChTtu6dOnCLbfcgqenp9NxrFZrvVHIGxMXF8ewYcOaNHBbZmYmQUFBTkv+mkyX8kRERERERMRYLjWs7XY748ePZ926dWzdupWIiAin7REREYSGhpKfn+9YV1VVRUFBAYMGDWpyzsKFC/n0008pLi6muLjYMa3V6tWrHY9fx8bGsn//fsrKyhz75eXlYTab6du3LwCDBw+mpqaGf/3rX46azz77DHAefGzlypUkJyeTm5vL8OHD653P4MGDKSkpoa6uzuk4Xbp0wcfHp8nXdcGcOXPYuHFjo++dp6enU1FR4bQkPH75XnwRERERERFxL5ceBU9NTSU3N5f169djsVgcPcZBQUH4+flhMplIS0sjIyODyMhIIiMjycjIwN/fn6SkJMdxrFYrVquVkpISAPbt24fFYiE8PJwOHToQHh7ulBsQEABAjx49HD3kiYmJREVFMWbMGF555RWOHz/O888/T0pKCoGBgcD5kbjvvPNOfvGLX5CdnU1dXR2pqakkJCQ4erFXrlzJk08+yauvvsrAgQMd1+Tn50dQUBAAv/rVr8jJyWHSpElMmDCBzz//nIyMDCZOnOja3f5/evfuzejRo8nJyblsndlsxmx2fuzb2/safdtfRERERETc6lodSKwtuNRjvXjxYioqKoiPj6dLly6OZfXq1Y6aqVOnkpaWxrhx4+jXrx9ff/01eXl5WCwWR82SJUvo06cPKSkpwPnHo/v06cOGDRuafC6enp68//77+Pr6MnjwYB5//HFGjhzJvHnz/n1xHh5s3LiRTp06ERcXx/Dhw+nVqxerVq1y1Lz++uvU1NSQmprqdE2TJk1y1Nx0003k5eWxe/dubr/9diZOnMikSZN44YUXXLl9Tl5++WXs+koWERERERG56pnsat1dVXLed89f1391KzQ847RvR8MzAMw1Z9ySc9TU3fCMWrt7Bpg4afNzS06o/wnDM7qd2mt4BsDXgVFuyfEw1TVe1EI+2BovagWn6yyNF10lQmq+ckvOWW/33DNPe43hGR+UuuffTJcHbm28qBXcdPAjwzPa873hGQA1Hq6/5tYc3rXnDM8IqDxmeAbAbo/Bhmfc4HvW8AyAEI+yxotawdGaro0XtVAXn28NzwCI6NHTLTlG2PBJ06cPbk0P9fNsvOgq06J5rEVERERERESud82ebkvOKy0tJSrq0r91P3jwYL13xkVERERERNpanZ5dbjVqWLdQWFgYxcXFl90uIiIiIiIi1y41rFvox/Nsi4iIiIiIyPVHDWsREREREZHrkIaxbj1qWF9lqo0fqBWAgG8/Nzyj5kZfwzMAgqz/dEtOxU2dDM8IrDlueAZA+x8+dUvOGc8ehmf8K6CP4RkAPU7ucUuO+fA+wzPqOnUxPAPA2rW/W3JCjrnhnnl6G54B4G9yzwi3td7+hmcEB107o3UDfBV1j+EZnv/YbngGgA9VbskpOXuT4Rl3ep80PAPgBm/jR+zuVf6h4RkAHtXumRmiE/sNzzgYPNTwDIAIt6TIlU4NaxERERERkeuQHfdM5Xo90HRbIiIiIiIiIi2ghrWIiIiIiIhIC+hRcBERERERkeuQ5rFuPeqxFhEREREREWkBlxrWmZmZ9O/fH4vFQnBwMCNHjuTQoUNONXa7nZkzZxIWFoafnx/x8fEcOHDAqWbp0qXEx8cTGBiIyWTixIkTl8y02WzExMRgMpkoLi522lZaWsqIESNo164dnTp1YuLEiVRVOY9kabfbmTdvHrfccgtms5mbbrqJjIwMx/aysjKSkpK49dZb8fDwIC0trcHzWLt2LVFRUZjNZqKionj33Xcbv2H/T3JyMiaTiTlz5jitf++99zCZNGCAiIiIiIi4n93eNsu1yKWGdUFBAampqRQWFpKfn09NTQ2JiYlUVlY6aubOncuCBQtYtGgRu3fvJjQ0lISEBE6dOuWoOXPmDA888ADTpk1rNHPq1KmEhYXVW19bW8vw4cOprKxkx44drFq1irVr1/Lcc8851U2aNInf/e53zJs3j3/+859s3LiRu+66y7HdZrPRuXNnpk+fzh133NHgOezatYsnnniCMWPG8OmnnzJmzBgef/xxPv7440bP/wJfX1+ysrIoLy9v8j4iIiIiIiJy5XPpHestW7Y4fV62bBnBwcEUFRURFxeH3W4nOzub6dOn88gjjwCwYsUKQkJCyM3N5dlnnwVw9Apv3779snmbN28mLy+PtWvXsnnzZqdteXl5HDx4kK+++srR8J4/fz7JycnMnj2bwMBA/vGPf7B48WL279/Prbc2PF9m9+7defXVVwF46623GqzJzs4mISGB9PR0ANLT0ykoKCA7O5uVK1de9houGDp0KCUlJWRmZjJ37twm7SMiIiIiImKUa7X3uC206B3riooKADp06ADA4cOHsVqtJCYmOmrMZjNDhgxh586dLh3722+/JSUlhbfffht/f/9623ft2kV0dLRTb/awYcOw2WwUFRUBsHHjRm6++Wb+7//+j4iICLp3784zzzzD8ePHXTqXXbt2OV3ThSxXrsnT05OMjAxycnI4evSoS/kiIiIiIiJy5Wp2w9putzNlyhTuvvtuoqOjAbBarQCEhIQ41YaEhDi2NfXYycnJjB07ln79+jVYY7Va6+W0b98eHx8fR9YXX3zBkSNH+NOf/sTvf/97li9fTlFREY899liTz+VSWa5eE8CoUaOIiYnhxRdfbFK9zWbj5MmTTktNtc2lTBERERERETFWsxvW48ePZ+/evQ0+Cn3xgFx2u92lQbpycnI4efKk49HrS2nomD/Oqqurw2az8fvf/5577rmH+Ph43nzzTbZt21Zv0LXGtPSaLsjKymLFihUcPHiw0drMzEyCgoKclr+8k+lypoiIiIiIyMXq7KY2Wa5FzWpYT5gwgQ0bNrBt2za6du3qWB8aGgpQryf32LFj9Xp8L2fr1q0UFhZiNpvx8vKiZ8+eAPTr14+nnnrKkXVxTnl5OdXV1Y6sLl264OXlxS233OKo6dWrF3B+RPGmaijL1Wu6IC4ujmHDhjVp4Lb09HQqKiqclvsfu/wvG0RERERERMS9XGpY2+12xo8fz7p169i6dSsRERFO2yMiIggNDSU/P9+xrqqqioKCAgYNGtTknIULF/Lpp59SXFxMcXExmzZtAmD16tXMnj0bgNjYWPbv309ZWZljv7y8PMxmM3379gVg8ODB1NTU8K9//ctR89lnnwHQrVu3Jp9PbGys0zVdyHLlmn5szpw5bNy4sdF3tM1mM4GBgU6Ll7e5WZkiIiIiIiI/pum2Wo9Lo4KnpqaSm5vL+vXrsVgsjl7coKAg/Pz8MJlMpKWlkZGRQWRkJJGRkWRkZODv709SUpLjOFarFavVSklJCQD79u3DYrEQHh5Ohw4dCA8Pd8oNCAgAoEePHo4e8sTERKKiohgzZgyvvPIKx48f5/nnnyclJYXAwEDg/Ejcd955J7/4xS/Izs6mrq6O1NRUEhISnHqxL8yPffr0ab777juKi4vx8fEhKioKOD9lV1xcHFlZWTz88MOsX7+eP//5z+zYscOV2+fQu3dvRo8eTU5OTrP2FxERERERkSuHSz3WixcvpqKigvj4eLp06eJYVq9e7aiZOnUqaWlpjBs3jn79+vH111+Tl5eHxWJx1CxZsoQ+ffqQkpICnH88uk+fPmzYsKHJ5+Lp6cn777+Pr68vgwcP5vHHH2fkyJHMmzfv3xfn4cHGjRvp1KkTcXFxDB8+nF69erFq1SqnY/Xp04c+ffpQVFREbm4uffr04cEHH3RsHzRoEKtWrWLZsmXcfvvtLF++nNWrVzNgwABXbp+Tl19+Gfu1+usaERERERGR64jJrtbdVWXBevf8dY0LeNvwjBM39jY8AyDI+k+35By56R7DMwJrXJsqrrnaf/2pW3LOBPcwPOOIT8Nz2Le2Hqf3uCXHfHif4Rl1nboYngFg7drfLTkhx9xwzzy9Dc8AoBmDZjZHrXf9aS5b24c1xn/PBOge9INbcr6KMv56uv9ju+EZAD6mKrfkfHk61PCMOz2LDM8A+MI7yvCMXuUfGp4B4HENzUBzMHioW3L63dreLTlGyN3RNk3BpLuvvQHMWjSPtYiIiIiIiMj1zqV3rKW+0tJSx7vYDTl48GC9d8ZFRERERETaWp2eXW41ali3UFhYmGPws0ttFxERERERkWuXGtYt9ON5tkVERERERK4Wdvu1965zW9E71iIiIiIiIiItoB7rq0xggHt+q3Smc4ThGe1OlRmeAXDoRveMCHmDvdzwDM+6asMzALa3/6lbcjp7nzY+xE3vDn0T1MstOcduG2R4hr+Xe0YErjxrdkvOkQDjX8nx8HDPF5qfp3u+B3iY6gzP6Fh71vAMgPZ875YcTzeM2P1lr3jDMwDC/+Ge0acj2x0xPOOLWuNH6wb39Pp9ZP4PwzMA7mj/D7fkFFca/3OzXY17vmeKgBrWIiIiIiIi1yVNvNx69Ci4iIiIiIiISAuox1pEREREROQ6pOm2Wo96rEVERERERERawKWGdWZmJv3798disRAcHMzIkSM5dOiQU43dbmfmzJmEhYXh5+dHfHw8Bw4ccKpZunQp8fHxBAYGYjKZOHHixCUzbTYbMTExmEymevNFl5aWMmLECNq1a0enTp2YOHEiVVX/HnTnyy+/xGQy1Vu2bNniqFm3bh0JCQl07tyZwMBAYmNj+eCDD5xyli9f3uBxzp0716T7lpycjMlkYs6cOU7r33vvPUwmDXEvIiIiIiJyNXOpYV1QUEBqaiqFhYXk5+dTU1NDYmIilZWVjpq5c+eyYMECFi1axO7duwkNDSUhIYFTp045as6cOcMDDzzAtGnTGs2cOnUqYWH1R3Stra1l+PDhVFZWsmPHDlatWsXatWt57rnn6tX++c9/pqyszLHcd999jm0ffvghCQkJbNq0iaKiIu69915GjBjBnj17nI4RGBjodIyysjJ8fX2bdN8AfH19ycrKorzc+JGjRUREREREGmO3t81yLXLpHesf9/QCLFu2jODgYIqKioiLi8Nut5Odnc306dN55JFHAFixYgUhISHk5uby7LPPApCWlgbA9u3bL5u3efNm8vLyWLt2LZs3b3balpeXx8GDB/nqq68cDe/58+eTnJzM7NmzCQwMdNR27NiR0NDQBjOys7OdPmdkZLB+/Xo2btxInz59HOtNJtMlj9EUQ4cOpaSkhMzMTObOndvs44iIiIiIiMiVpUXvWFdUVADQoUMHAA4fPozVaiUxMdFRYzabGTJkCDt37nTp2N9++y0pKSm8/fbb+Pv719u+a9cuoqOjnXqzhw0bhs1mo6ioyKn2oYceIjg4mMGDB/POO+9cNreuro5Tp045rumC06dP061bN7p27cp//ud/1uvRboynpycZGRnk5ORw9OhRl/YVERERERFpbeqxbj3Nbljb7XamTJnC3XffTXR0NABWqxWAkJAQp9qQkBDHtqYeOzk5mbFjx9KvX78Ga6xWa72c9u3b4+Pj48gKCAhgwYIFvPPOO2zatIn777+fJ554gj/84Q+XzJ4/fz6VlZU8/vjjjnW33XYby5cvZ8OGDaxcuRJfX18GDx7M559/3uRrAhg1ahQxMTG8+OKLTaq32WycPHnSaamusrmUKSIiIiIiIsZq9nRb48ePZ+/evezYsaPetosH5LLb7S4N0pWTk8PJkydJT0+/bF1Dx/xxVqdOnZg8ebJjW79+/SgvL2fu3Ln87Gc/q7fvypUrmTlzJuvXryc4ONixfuDAgQwcONDxefDgwdx5553k5OSwcOHCJl8XQFZWFvfdd1+D74JfLDMzk1mzZjmtGzHmRR56aqZLmSIiIiIiIhfTdFutp1k91hMmTGDDhg1s27aNrl27OtZfeAf54t7pY8eO1etdvpytW7dSWFiI2WzGy8uLnj17Aucbxk899ZQj6+Kc8vJyqqurL5s1cODABnuaV69ezdNPP82aNWsYOnToZc/Pw8OD/v37u9xjDRAXF8ewYcOaNHBbeno6FRUVTst//Nflf9kgIiIiIiIi7uVSw9putzN+/HjWrVvH1q1biYiIcNoeERFBaGgo+fn5jnVVVVUUFBQwaNCgJucsXLiQTz/9lOLiYoqLi9m0aRNwvvE7e/ZsAGJjY9m/fz9lZWWO/fLy8jCbzfTt2/eSx96zZw9dunRxWrdy5UqSk5PJzc1l+PDhjZ6f3W6nuLi43nGaas6cOWzcuLHR987NZjOBgYFOi7ePuVmZIiIiIiIiYgyXHgVPTU0lNzeX9evXY7FYHD3GQUFB+Pn5YTKZSEtLIyMjg8jISCIjI8nIyMDf35+kpCTHcaxWK1arlZKSEgD27duHxWIhPDycDh06EB4e7pQbEBAAQI8ePRw95ImJiURFRTFmzBheeeUVjh8/zvPPP09KSopjRPAVK1bg7e1Nnz598PDwYOPGjSxcuJCsrCzHsVeuXMmTTz7Jq6++ysCBAx3X5OfnR1BQEACzZs1i4MCBREZGcvLkSRYuXEhxcTGvvfaaK7fPoXfv3owePZqcnJxm7S8iIiIiItJS1+pAYm3BpYb14sWLAYiPj3dav2zZMpKTk4Hz806fPXuWcePGUV5ezoABA8jLy8NisTjqlyxZ4vTucFxcXL3jNMbT05P333+fcePGMXjwYPz8/EhKSmLevHlOdb/5zW84cuQInp6e3HLLLbz11ltO71e//vrr1NTUkJqaSmpqqmP9U089xfLlywE4ceIEv/zlL7FarQQFBdGnTx8+/PBD7rrrriada0Nefvll1qxZ0+z9RURERERE5Mpgstv1e4qrye/+4p6cRzp/ZHiGt+2U4RkA/7qhv1tybjCVG57hV+2ee/b3c7e7Jaez/2m35LhDO68zbsk5dq694Rn+XlWGZwBUVrvn1RZ3/JTz8HDPj1I/z2q35HiY6gzPsNV6G54BEO5d6packybj/21+2Sve8AyA8H986JYcCxWGZ3xXG9x4USuw25s+SG9z/XC2/vSzRrjD/x9uySmu7GV4Rjuze75nDvmJe/5ujPB6XtvkPpvYeM3VpkXzWIuIiIiIiIhcKcrLyxkzZgxBQUEEBQUxZswYTpw4ccn66upq/vu//5vevXvTrl07wsLCePLJJ/nmm29cylXDuoVKS0sJCAi45FJa6p7flIuIiIiIiFzvkpKSKC4uZsuWLWzZsoXi4mLGjBlzyfozZ87w97//nf/5n//h73//O+vWreOzzz7joYcecim32fNYy3lhYWEUFxdfdruIiIiIiMiV5lp7Kfgf//gHW7ZsobCwkAEDBgDwxhtvEBsby6FDh7j11lvr7RMUFOQ0qxVATk4Od911F6WlpfUG1r4UNaxb6MfzbIuIiIiIiMjl2Ww2bDab0zqz2YzZ3LLxV3bt2kVQUJCjUQ0wcOBAgoKC2LlzZ4MN64ZUVFRgMpm44YYbmpytR8FFRERERESuQ3Z72yyZmZmOd6AvLJmZmS2+HqvVSnBw/UELg4ODHdMqN+bcuXO88MILJCUlOaZxbgr1WF9lqt0zuCE1Xn6GZ5zyd89Inb4mW+NFrcBaHWJ4ho9nR8MzAIJ8z7klx8ujxvCMqlofwzMAau2ebskxu2FU6DM17rpnxo+iC+DlYfwI1z5u+FoG94zWDVBVZ/x/D8rP+RqeARBmds/Xsw/Gj6bvrtG6S3vFuSUnZH+hW3LcwXo6wPAMd3wvA6jydM+/TXeM2G3xPmt4xnlX76jgbSU9PZ0pU6Y4rbtcb/XMmTOdpmtuyO7duwEwmer//8Jutze4/mLV1dX89Kc/pa6ujt/+9reN1v+YGtYiIiIiIiLXobo2esfa1ce+x48fz09/+tPL1nTv3p29e/fy7bff1tv23XffERJy+U6w6upqHn/8cQ4fPszWrVtd6q0GNaxFRERERETkCtapUyc6derUaF1sbCwVFRX87W9/46677gLg448/pqKigkGDBl1yvwuN6s8//5xt27bRsaPrT4nqHWsRERERERG56vXq1YsHHniAlJQUCgsLKSwsJCUlhf/8z/90Grjstttu49133wWgpqaGxx57jE8++YQ//vGP1NbWYrVasVqtVFU1/TUf9ViLiIiIiIhch+xtNt+WceOs/PGPf2TixIkkJiYC8NBDD7Fo0SKnmkOHDlFRUQHA0aNH2bBhAwAxMTFOddu2bSM+Pr5JuS71WGdmZtK/f38sFgvBwcGMHDmSQ4cOOdXY7XZmzpxJWFgYfn5+xMfHc+DAAaeapUuXEh8fT2BgICaTiRMnTlwy02azERMTg8lkqjdfdGlpKSNGjKBdu3Z06tSJiRMnOv1W4csvv8RkMtVbtmzZ4nScgoIC+vbti6+vLzfffDNLlixx2l5dXc1LL71Ejx498PX15Y477qh3jMtJTk7GZDIxZ84cp/Xvvfdek16iFxERERERkcZ16NCBP/zhD5w8eZKTJ0/yhz/8od60WXa7neTkZOD8u9l2u73BpamNanCxYV1QUEBqaiqFhYXk5+dTU1NDYmIilZWVjpq5c+eyYMECFi1axO7duwkNDSUhIYFTp045as6cOcMDDzzAtGnTGs2cOnUqYWFh9dbX1tYyfPhwKisr2bFjB6tWrWLt2rU899xz9Wr//Oc/U1ZW5ljuu+8+x7bDhw/z4IMPcs8997Bnzx6mTZvGxIkTWbt2raNmxowZvP766+Tk5HDw4EHGjh3LqFGj2LNnT5Pvna+vL1lZWZSXlzd5HxEREREREaO01XRb1yKXHgW/uJd22bJlBAcHU1RURFxcHHa7nezsbKZPn84jjzwCwIoVKwgJCSE3N5dnn30WgLS0NAC2b99+2bzNmzeTl5fH2rVr2bx5s9O2vLw8Dh48yFdffeVoeM+fP5/k5GRmz57tNIpbx44dCQ0NbTBjyZIlhIeHk52dDZx/Lv+TTz5h3rx5PProowC8/fbbTJ8+nQcffBCAX/3qV3zwwQfMnz+fP/zhD43ctfOGDh1KSUkJmZmZzJ07oDSEbAAAdXJJREFUt0n7iIiIiIiIyJWvRYOXXXguvUOHDsD53l+r1ep4nh3OD6U+ZMgQdu7c6dKxv/32W1JSUnj77bfx968/N9yuXbuIjo526s0eNmwYNpuNoqIip9qHHnqI4OBgBg8ezDvvvFPvOD8+3wvH+eSTT6j+f5NG22w2fH2d5/Tz8/Njx44dTb4eT09PMjIyyMnJ4ejRo03eT0RERERERK5szW5Y2+12pkyZwt133010dDQAVqsVoN4cYSEhIY5tTT12cnIyY8eOpV+/fg3WWK3Wejnt27fHx8fHkRUQEMCCBQt455132LRpE/fffz9PPPGEUy9zQ8cJCQmhpqaG77//Hjjf0F6wYAGff/45dXV15Ofns379esrKypp8TQCjRo0iJiaGF1980aX9REREREREWltdXdss16Jmjwo+fvx49u7d22Cv7cUDctntdpcG6crJyeHkyZOkp6dftq6hY/44q1OnTkyePNmxrV+/fpSXlzN37lx+9rOfXfZ8f7z+1VdfJSUlhdtuuw2TyUSPHj34+c9/zrJly5p8TRdkZWVx3333Nfgu+MVsNhs2m81pXXWVGW+fpk+mLiIiIiIiIsZqVo/1hAkT2LBhA9u2baNr166O9RfeY764d/rYsWP1eoUvZ+vWrRQWFmI2m/Hy8qJnz57A+YbxU0895ci6OKe8vJzq6urLZg0cOJDPP//c6ZwbOl8vLy/HxOCdO3fmvffeo7KykiNHjvDPf/6TgIAAIiIimnxNF8TFxTFs2LAmDdyWmZlJUFCQ0/LBmkyXM0VERERERC6mwctaj0sNa7vdzvjx41m3bh1bt26t17CMiIggNDSU/Px8x7qqqioKCgoYNGhQk3MWLlzIp59+SnFxMcXFxWzatAmA1atXM3v2bABiY2PZv3+/0+PYeXl5mM1m+vbte8lj79mzhy5dujg+x8bGOp3vheP069cPb29vp/W+vr7ceOON1NTUsHbtWh5++OEmX9OPzZkzh40bNzb63nl6ejoVFRVOy7DHL9+LLyIiIiIiIu7l0qPgqamp5Obmsn79eiwWi6OnNygoCD8/P0wmE2lpaWRkZBAZGUlkZCQZGRn4+/uTlJTkOI7VasVqtVJSUgLAvn37sFgshIeH06FDB8LDw51yAwICAOjRo4ejhzwxMZGoqCjGjBnDK6+8wvHjx3n++edJSUlxjAi+YsUKvL296dOnDx4eHmzcuJGFCxeSlZXlOPbYsWNZtGgRU6ZMISUlhV27dvHmm2+ycuVKR83HH3/M119/TUxMDF9//TUzZ86krq6OqVOnunL7HHr37s3o0aPJycm5bJ3ZbMZsdn7s29unWZEiIiIiIiJO6q7R3uO24FLDevHixQD1JspetmyZY4LtqVOncvbsWcaNG0d5eTkDBgwgLy8Pi8XiqF+yZAmzZs1yfI6Li6t3nMZ4enry/vvvM27cOAYPHoyfnx9JSUnMmzfPqe43v/kNR44cwdPTk1tuuYW33nrL6f3qiIgINm3axOTJk3nttdcICwtj4cKFjqm2AM6dO8eMGTP44osvCAgI4MEHH+Ttt9+uN9G4K15++WXWrFnT7P1FRERERETkymCy26/Vp9yvTYu3NF7TGh4N/8TwjLM+lsaLWiPH1M4tOSeqjb8eH48awzMAztW659EIf69zhmdUue1azrol53SNn+EZtlrvxotaQU1di2Z8bDIvD+OHH3XXv01vj1q35FTVNXts0yY7ftb4r2WAnwR96ZacGoz/d3PO7tt4USso7RXnlpyQ/YWGZ9hp+uC5LVF2yvj/A7jjexlAVOBht+QcsXVtvKiFLN7u+dl85y0d3ZJjhAXr26YpOOVh9/zbdCfjf3KKiIiIiIjIFUddrK3HPd0F17DS0lICAgIuuZSWlrb1KYqIiIiIiIiB1GPdQmFhYRQXF192u4iIiIiIyJXG3majl+lRcLnIj+fZFhERERERkeuPHgUXERERERERaQH1WF9lTpx0z4iwXrXGj9ZssrtntO7y6kC35HT1Omp4hofdPX//276PdkvOHV3OGJ5xg3eF4RkAp2vd8/X8zUnjR54NDnDPKKruGUcbfqg0fiRlb0/3jNZ76qynW3JCgmyGZ3QP/N7wDABvN/w8Ayg5e5PhGZHtjhieAe4ZrRvg2+iBhmf4/v1TwzMAbm3/jeEZ1nPuGXnabnJPv9vX5cbPDNCtg3u+N1/NNI9161GPtYiIiIiIiEgLqMdaRERERETkOqTptlqPeqxFREREREREWkANaxEREREREZEWcKlhnZmZSf/+/bFYLAQHBzNy5EgOHTrkVGO325k5cyZhYWH4+fkRHx/PgQMHnGqWLl1KfHw8gYGBmP7/9u48PqZ7/x/4a7JNJqtYkghCLEWIRkUJStqSaFOtpVXiIkrwtVXpdYsqpbLYGqKVtldVtSFa+7U0LhJViSXEXkSjsY20FUGQ9fP7w8/cjuyZmU/i5PV8PObxMOd85vOa9+TM8nHO+RyVCrdv3y4xMycnB97e3lCpVEWuF52eno4+ffrA1tYWdevWxaRJk5Cbm1tsP6mpqbC3t0etWrX0lm/cuBG9evVCvXr14ODgAF9fX/z0009F2vj4+KBWrVqwtbWFt7c31qxZU/qL9TfBwcFQqVQIDw/XW75582aoVMq7hhsREREREVV/hYWiSm5KVKGBdUJCAsaPH4+kpCTs3r0b+fn58Pf3R3Z2tq7NggULsGTJEixfvhxHjhyBq6srevXqhbt37+ra3L9/H71798aMGTPKzJw2bRrc3NyKLC8oKEBgYCCys7Nx4MABrFu3Dhs2bMDUqVOLtM3Ly8PgwYPxwgsvFFm3f/9+9OrVCzt27EBycjJefPFF9OnTB8ePH9e1qV27NmbOnInExEScPHkSI0aMwIgRI4oMwEtjbW2NiIgIZGZmlvsxREREREREVP1VaPKyXbt26d1ftWoVnJ2dkZycjO7du0MIgcjISMycORP9+/cHAKxevRouLi6IiYnBmDFjAACTJ08GAMTHx5eat3PnTsTFxWHDhg3YuXOn3rq4uDicPXsWV65c0Q28Fy9ejODgYMyfPx8ODv+7xNKHH36IVq1a4eWXX8bBgwf1+omMjNS7Hxoaii1btmDbtm1o3749AMDPz0+vzbvvvovVq1fjwIEDCAgIKLWGx3r27InU1FSEhYVhwYIF5XoMERERERGRqXDyMuMx6BzrrKxH14etXbs2ACAtLQ1arRb+/v66Nmq1Gj169CgyoC3LzZs3ERISgjVr1sDGxqbI+sTERLRt21Zvb3ZAQABycnKQnJysW7Z371788MMP+Oyzz8qVW1hYiLt37+pqepIQAnv27MH58+fRvXv3ctdjbm6O0NBQREVF4epV01/vmIiIiIiIiOSo9MBaCIEpU6agW7duaNu2LQBAq9UCAFxcXPTauri46NaVt+/g4GCMHTsWPj4+xbbRarVFcpycnGBlZaXL+uuvvxAcHIxvvvlGbw92aRYvXozs7GwMHDhQb3lWVhbs7OxgZWWFwMBAREVFoVevXuWuCQD69esHb29vzJ49u0KPIyIiIiIiMjYhquamRJW+jvWECRNw8uRJHDhwoMi6JyfkEkJUaJKuqKgo3LlzB9OnTy+1XXF9/j0rJCQEQUFB5d6zvHbtWsyZMwdbtmyBs7Oz3jp7e3ukpKTg3r172LNnD6ZMmYKmTZsWOUy8LBEREXjppZeKPRf8STk5OcjJydFblp9nAQtLdYUyiYiIiIiIyHQqtcd64sSJ2Lp1K/bt24eGDRvqlru6ugJAkb3TGRkZRfYul2bv3r1ISkqCWq2GhYUFmjdvDgDw8fHB8OHDdVlP5mRmZiIvL0+XtXfvXixatAgWFhawsLDAyJEjkZWVBQsLC3z99dd6j42NjcXIkSOxfv169OzZs8hzMjMzQ/PmzeHt7Y2pU6fizTffRFhYWLlreqx79+4ICAgo18RtYWFhcHR01LvFbw4v83FEREREREQkT4X2WAshMHHiRGzatAnx8fHw8PDQW+/h4QFXV1fs3r1bN/FXbm4uEhISEBERUe6cZcuW4ZNPPtHdv379OgICAhAbG4tOnToBAHx9fTF//nzcuHED9evXB/BoQjO1Wo0OHToAeHQedkFBga6fLVu2ICIiAgcPHkSDBg10y9euXYt33nkHa9euRWBgYLlfiyf3JpdXeHg4vL298cwzz5Tabvr06ZgyZYresqXbKn2QARERERERkU6hUo/LrgIVGqWNHz8eMTEx2LJlC+zt7XV7jB0dHaHRaKBSqTB58mSEhoaiRYsWaNGiBUJDQ2FjY4OgoCBdP1qtFlqtFqmpqQCAU6dOwd7eHu7u7qhduzbc3d31cu3s7AAAzZo10+0h9/f3h6enJ4YOHYqFCxfi1q1beP/99xESEqI7n7p169Z6/Rw9ehRmZma6c8KBR4PqYcOGYenSpejcubOuJo1GA0dHRwCP9hz7+PigWbNmyM3NxY4dO/Dtt99ixYoVFXn5dLy8vDBkyBBERUWV2k6tVkOt1j/s28KyoITWREREREREVBUqdCj4ihUrkJWVBT8/P9SvX193i42N1bWZNm0aJk+ejHHjxsHHxwfXrl1DXFwc7O3tdW2io6PRvn17hISEAHh0eHT79u2xdevWcj8Xc3NzbN++HdbW1ujatSsGDhyIvn37YtGiRRUpCV988QXy8/Mxfvx4vZreffddXZvs7GyMGzcObdq0QZcuXfDjjz/iu+++w6hRoyqU9Xfz5s2D4P8QERERERFRFRGFVXNTIpXg6O6pErZezh7rMa0TTZ5xz7qOyTMA4Fp+g7IbGUFDC9NfRs1MyPn777vZtuxGRvBs/QyTZ6hVlTtlo6LuFdhKybl828nkGc52D0yeAQA5BeZScrIeWJk8w9Jczq+Euw/kvGYujqZ/37hobps8AwBqFf4pJefcgxYmz2hh+7vJMwDgz4J6UnJutu1s8gzrYydMngEADW3+MHmG9qGc303u1tel5CTeaGbyjMa1s02eAQBdPe2k5JjC3O/zqyT3oyHKO73VoOtYExEREREREdV0yvuvAsnS09Ph6elZ4vqzZ88WOWeciIiIiIioqvHgZePhwNpAbm5uSElJKXU9ERERERERKRcH1gb6+3W2iYiIiIiInhaFCp1IrCrwHGsiIiIiIiIiA3CP9VOmoaucGWEfqB1NnpGlqm3yDADwupMgJedibV+TZ9zPtzZ5BgC8bvtfKTk5uabfzswLck2eAQAaaznbcwskmTyjIEdj8gwA+MuxiZQcl+zTJs8we/jQ5BkApF2jxOzKHZNnfPj7P0yeAQAfdj4rJec5S9O/Zr8VlDyny9NIxozdD5971uQZAHDx0BmTZ7ycFVt2IyPIaOQjJec1TZzJM86bdzJ5xtOO51gbD/dYExERERERERmAA2siIiIiIiIiA/BQcCIiIiIiohqokEeCGw33WBMREREREREZgHusiYiIiIiIaiDBXdZGU6E91mFhYejYsSPs7e3h7OyMvn374vz583pthBCYM2cO3NzcoNFo4OfnhzNn9GdK/PLLL+Hn5wcHBweoVCrcvn27xMycnBx4e3tDpVIhJSVFb116ejr69OkDW1tb1K1bF5MmTUJubvEzAKempsLe3h61atUqsi4hIQEdOnSAtbU1mjZtiujoaL31fn5+UKlURW6BgYElv1h/ExwcDJVKhfDwcL3lmzdvhkqlKlcfREREREREVD1VaGCdkJCA8ePHIykpCbt370Z+fj78/f2RnZ2ta7NgwQIsWbIEy5cvx5EjR+Dq6opevXrh7t27ujb3799H7969MWPGjDIzp02bBjc3tyLLCwoKEBgYiOzsbBw4cADr1q3Dhg0bMHXq1CJt8/LyMHjwYLzwwgtF1qWlpeHVV1/FCy+8gOPHj2PGjBmYNGkSNmzYoGuzceNG3LhxQ3c7ffo0zM3N8dZbb5X5/B+ztrZGREQEMjMzy/0YIiIiIiIiqv4qdCj4rl279O6vWrUKzs7OSE5ORvfu3SGEQGRkJGbOnIn+/fsDAFavXg0XFxfExMRgzJgxAIDJkycDAOLj40vN27lzJ+Li4rBhwwbs3LlTb11cXBzOnj2LK1eu6AbeixcvRnBwMObPnw8HBwdd2w8//BCtWrXCyy+/jIMHD+r1Ex0dDXd3d0RGRgIAWrdujaNHj2LRokUYMGAAAKB2bf3r065btw42NjYVGlj37NkTqampCAsLw4IFC8r9OCIiIiIiIlPgZayNx6DJy7KysgD8b+CZlpYGrVYLf39/XRu1Wo0ePXoUGdCW5ebNmwgJCcGaNWtgY2NTZH1iYiLatm2rtzc7ICAAOTk5SE5O1i3bu3cvfvjhB3z22WfF5iQmJuo938f9HD16FHl5ecU+ZuXKlRg0aBBsbW3LXY+5uTlCQ0MRFRWFq1evlvtxREREREREVL1VemAthMCUKVPQrVs3tG3bFgCg1WoBAC4uLnptXVxcdOvK23dwcDDGjh0LHx+fYttotdoiOU5OTrCystJl/fXXXwgODsY333yjtwe7rH5cXFyQn5+PP//8s0j7w4cP4/Tp0xg1alS563msX79+8Pb2xuzZs8vVPicnB3fu3NG75eXmVDiXiIiIiIjoSYWFokpuSlTpgfWECRNw8uRJrF27tsi6JyfkEkJUaJKuqKgo3LlzB9OnTy+1XXF9/j0rJCQEQUFB6N69e4X6Ef//mIji+l+5ciXatm2L559/vtQ+SxIREYHVq1fj7NmzZbYNCwuDo6Oj3m3b92GVyiUiIiIiIiLTqNTAeuLEidi6dSv27duHhg0b6pa7uroCQJG90xkZGUX2Cpdm7969SEpKglqthoWFBZo3bw4A8PHxwfDhw3VZT+ZkZmYiLy9Pl7V3714sWrQIFhYWsLCwwMiRI5GVlQULCwt8/fXXJfaTkZEBCwsL1KlTR2/5/fv3sW7dukrtrX6se/fuCAgIKNfEbdOnT0dWVpberc+Q0v+zgYiIiIiIqDyEEFVyU6IKTV4mhMDEiROxadMmxMfHw8PDQ2+9h4cHXF1dsXv3brRv3x4AkJubi4SEBERERJQ7Z9myZfjkk090969fv46AgADExsaiU6dOAABfX1/Mnz8fN27cQP369QE8mtBMrVajQ4cOAB6dP11QUKDrZ8uWLYiIiMDBgwfRoEEDXT/btm3Ty4+Li4OPjw8sLS31lq9fvx45OTn4xz/+Ue5aihMeHg5vb28888wzpbZTq9VQq9V6yyytDIomIiIiIiIiI6vQwHr8+PGIiYnBli1bYG9vr9vT6+joCI1GA5VKhcmTJyM0NBQtWrRAixYtEBoaChsbGwQFBen60Wq10Gq1SE1NBQCcOnUK9vb2cHd3R+3ateHu7q6Xa2dnBwBo1qyZbg+5v78/PD09MXToUCxcuBC3bt3C+++/j5CQEN351K1bt9br5+jRozAzM9OdEw4AY8eOxfLlyzFlyhSEhIQgMTERK1euLPYQ95UrV6Jv375F9mRXlJeXF4YMGYKoqCiD+iEiIiIiIqKqV6FDwVesWIGsrCz4+fmhfv36ultsbKyuzbRp0zB58mSMGzcOPj4+uHbtGuLi4mBvb69rEx0djfbt2yMkJATAo8Oj27dvj61bt5b7uZibm2P79u2wtrZG165dMXDgQPTt2xeLFi2qSEnw8PDAjh07EB8fD29vb8ybNw/Lli3TXWrrsQsXLuDAgQMYOXJkhfovybx58xR7GAQREREREVV/orBqbkqkEhzdPVXW7JeT85LrKZNn3DJzNnkGAHj8dVhKzsXavibPuJ9nbfIMAPB6mCglJ8fa0eQZ5gW5Js8AgGzr2mU3MoJamWkmzyiw1Jg8AwD+cmwiJccl47TJM8xyH5o8A4C0XyNm2XdMnvHh74adVlXunM5JUnIKLE3/+fybpafJM2S6k2v61+zhc8+aPAMAxKEzJs94OSu27EZGkNGo+CvyGJtT1mWTZ5y362TyDADo2LKWlBxTmBb9oEpyF4yV81tDpgodCk5ERERERETKUMh9rEZT6ctt0SPp6emws7Mr8Zaenl7VT5GIiIiIiIhMiHusDeTm5oaUlJRS1xMREREREZFycWBtoL9fZ5uIiIiIiOhpwem2jIeHghMREREREREZgHusnzL3JU08q3l42+QZtTTmJs8AgFu15RxR4FJ43eQZtg8zTJ4BALccGkvJKTAz/UdQRk5dk2cAQNP8i1Jy0pw6mjzDLeeSyTMAwP7hLSk5v9XpbPKMPx46mDwDAO48sJSSk2elMnnG5OZnTZ4BAEcedJWSU8vS9DPrCmH6vwsAaO/ZSclp6WT6782LEmbrBgBVpzYmzzh9+pDJMwCgSe4FKTmp9qaffdwNV0ye8UgtSTnGV1jIPdbGwj3WRERERERERAbgHmsiIiIiIqIaiKdYGw/3WBMREREREREZgANrIiIiIiIiIgNUaGAdFhaGjh07wt7eHs7Ozujbty/Onz+v10YIgTlz5sDNzQ0ajQZ+fn44c0Z/4ogvv/wSfn5+cHBwgEqlwu3bt0vMzMnJgbe3N1QqVZHrRaenp6NPnz6wtbVF3bp1MWnSJOTm5urWnz9/Hi+++CJcXFxgbW2Npk2b4sMPP0ReXp6uzcaNG9GrVy/Uq1cPDg4O8PX1xU8//aSX89VXX+GFF16Ak5MTnJyc0LNnTxw+fLjcr1twcDBUKhXCw8P1lm/evBkqlZyJSIiIiIiIiP5OFIoquZlSZmYmhg4dCkdHRzg6OmLo0KGljjefNGbMGKhUKkRGRlYot0ID64SEBIwfPx5JSUnYvXs38vPz4e/vj+zsbF2bBQsWYMmSJVi+fDmOHDkCV1dX9OrVC3fv3tW1uX//Pnr37o0ZM2aUmTlt2jS4ubkVWV5QUIDAwEBkZ2fjwIEDWLduHTZs2ICpU6fq2lhaWmLYsGGIi4vD+fPnERkZia+++gqzZ8/Wtdm/fz969eqFHTt2IDk5GS+++CL69OmD48eP69rEx8dj8ODB2LdvHxITE+Hu7g5/f39cu3at3K+dtbU1IiIikJmZWe7HEBERERERUfkFBQUhJSUFu3btwq5du5CSkoKhQ4eW67GbN2/GoUOHih1/lqVCk5ft2rVL7/6qVavg7OyM5ORkdO/eHUIIREZGYubMmejfvz8AYPXq1XBxcUFMTAzGjBkDAJg8eTKARwPW0uzcuRNxcXHYsGEDdu7cqbcuLi4OZ8+exZUrV3SFL168GMHBwZg/fz4cHBzQtGlTNG3aVPeYxo0bIz4+Hj///LNu2ZP/ExEaGootW7Zg27ZtaN++PQDg+++/12vz1Vdf4ccff8SePXswbNiwUmt4rGfPnkhNTUVYWBgWLFhQrscQERERERGZSqHCZi87d+4cdu3ahaSkJHTq1AnAo7Gbr68vzp8/j5YtW5b42GvXrmHChAn46aefEBgYWOFsg86xzsrKAgDUrl0bAJCWlgatVgt/f39dG7VajR49euDgwYMV6vvmzZsICQnBmjVrYGNjU2R9YmIi2rZtq/e/CQEBAcjJyUFycnKxfaampmLXrl3o0aNHibmFhYW4e/eurqbi3L9/H3l5eaW2eZK5uTlCQ0MRFRWFq1evlvtxRERERERESpKTk4M7d+7o3XJycgzuNzExEY6OjrpBNQB07twZjo6OpY5HCwsLMXToUPzzn/9EmzaVuy59pQfWQghMmTIF3bp1Q9u2bQEAWq0WAODi4qLX1sXFRbeuvH0HBwdj7Nix8PEp/uLxWq22SI6TkxOsrKyKZHXp0gXW1tZo0aIFXnjhBcydO7fE7MWLFyM7OxsDBw4ssc0HH3yABg0aoGfPnuWuCQD69esHb29vvUPRS1PcBpeXa/gGR0REREREVFXCwsJ050A/voWFhRncr1arhbOzc5Hlzs7OpY5HIyIiYGFhgUmTJlU6u9ID6wkTJuDkyZNYu3ZtkXVPTsglhKjQJF1RUVG4c+cOpk+fXmq74vosLis2NhbHjh1DTEwMtm/fjkWLFhXb39q1azFnzhzExsYW+wcBHp1DvnbtWmzcuBHW1tblrOh/IiIisHr1apw9e7bMtsVtcLtiDd/giIiIiIiIqmrysunTpyMrK0vvVtrYb86cOVCpVKXejh49CqD8Y8THkpOTsXTpUnzzzTcGTSxdoXOsH5s4cSK2bt2K/fv3o2HDhrrlrq6uAB79T0H9+vV1yzMyMorsXS7N3r17kZSUBLVarbfcx8cHQ4YMwerVq+Hq6opDhw7prc/MzEReXl6RrEaNGgEAPD09UVBQgNGjR2Pq1KkwNzfXtYmNjcXIkSPxww8/lLgnetGiRQgNDcV///tftGvXrtz1/F337t0REBCAGTNmIDg4uNS206dPx5QpU/SWfbtfXUJrIiIiIiKi6k+tVhcZ65VmwoQJGDRoUKltmjRpgpMnT+LmzZtF1v3xxx8ljkd//vlnZGRkwN3dXbesoKAAU6dORWRkJC5fvlyu51ihgbUQAhMnTsSmTZsQHx8PDw8PvfUeHh5wdXXF7t27dRN/5ebmIiEhAREREeXOWbZsGT755BPd/evXryMgIACxsbG64+V9fX0xf/583LhxQzeIj4uLg1qtRocOHUqtIS8vD+JvJ+qvXbsW77zzDtauXVviieoLFy7EJ598gp9++qnEw9PLKzw8HN7e3njmmWdKbVfcBmdpZVA0ERERERERAJj80lfGUrduXdStW7fMdr6+vsjKysLhw4fx/PPPAwAOHTqErKwsdOnSpdjHDB06tMiO1YCAAAwdOhQjRowo93Os0MB6/PjxiImJwZYtW2Bvb687Tt3R0REajQYqlQqTJ09GaGgoWrRogRYtWiA0NBQ2NjYICgrS9aPVaqHVapGamgoAOHXqFOzt7eHu7o7atWvr/W8BANjZ2QEAmjVrpttD7u/vD09PTwwdOhQLFy7ErVu38P777yMkJAQODg4AHs3mbWlpCS8vL6jVaiQnJ2P69Ol4++23YWHxqPS1a9di2LBhWLp0KTp37qyrSaPRwNHREcCjw79nzZqFmJgYNGnSRNfGzs5O99wqwsvLC0OGDEFUVFSFH0tERERERERFtW7dGr1790ZISAi++OILAMDo0aPx2muv6c0I3qpVK4SFhaFfv36oU6cO6tSpo9ePpaUlXF1dS51F/EkVOsd6xYoVyMrKgp+fH+rXr6+7xcbG6tpMmzYNkydPxrhx4+Dj44Nr164hLi4O9vb2ujbR0dFo3749QkJCADw6PLp9+/bYunVruZ+Lubk5tm/fDmtra3Tt2hUDBw5E37599c6ftrCwQEREBJ5//nm0a9cOc+bMwfjx4/Hvf/9b1+aLL75Afn4+xo8fr1fTu+++q2vz+eefIzc3F2+++aZem5LO1S6PefPm6e01JyIiIiIikqlQVM3NlL7//nt4eXnB398f/v7+aNeuHdasWaPX5vz587orXBmLSnB091T5Ik5OzluuP5fdyEDZmjplNzICgcpPQlARFoV5Js+wzc4weQYAZDq4l93ICArMKjXNQ4Vk5JR92JAxNMVFKTk3LRqZPMMt55LJMwCg0MxSSo7W0vTb8x8PHUyeAQB3Hsh5zfIKTP+52aVO2ZN4GsO5By2k5NSyfmDyDCHkfJ9p71X8aLzKaOl03eQZF7Pql93ICFSdKnd5nopwPn2o7EZG0KTggpScKxbNTJ7hAtNvYwDQ4BkvKTmm8H8Lb1dJ7op/1qqSXFMy6DrWRERERERERDWd6XcXKVx6ejo8PT1LXH/27Nki54wTERERERFVtadl8rKnAQfWBnJzc0NKSkqp64mIiIiIiEi5OLA2kIWFBZo3b17VT4OIiIiIiKhCON2W8fAcayIiIiIiIiIDcI/1U8bJvlBKToGF2uQZ2kI5h8l7pf0oJSe1+Wsmz/jT3tXkGQDwzMm1UnIeNn3W5Blqm/smzwAAUSjn/ymfObve5BmFTs4mzwCAP+vLmUX1mbTtps+4d8fkGQAgnOTMcg+V6bfnz88OMnkGAHRvbdzLqZSkdeZ+k2f8rH7F5BkAYGEm57eG9qHprw7yclZs2Y2M4LSEGbsz2nYyeQYAND2+SkqO5+nvTJ5xqs1wk2cAQAMpKVTdcWBNRERERERUAxVy8jKj4aHgRERERERERAbgHmsiIiIiIqIaiJOXGQ/3WBMREREREREZoEID67CwMHTs2BH29vZwdnZG3759cf78eb02QgjMmTMHbm5u0Gg08PPzw5kzZ/TafPnll/Dz84ODgwNUKhVu375dYmZOTg68vb2hUqmKXC86PT0dffr0ga2tLerWrYtJkyYhNzdXtz4+Ph5vvPEG6tevD1tbW3h7e+P777/X6+PGjRsICgpCy5YtYWZmhsmTJxf7PCIjI9GyZUtoNBo0atQI7733Hh4+fFj2iwYgODgYKpUK4eHhess3b94MlUpVrj6IiIiIiIiMSRSKKrkpUYUG1gkJCRg/fjySkpKwe/du5Ofnw9/fH9nZ2bo2CxYswJIlS7B8+XIcOXIErq6u6NWrF+7evatrc//+ffTu3RszZswoM3PatGlwcys6e3RBQQECAwORnZ2NAwcOYN26ddiwYQOmTp2qa3Pw4EG0a9cOGzZswMmTJ/HOO+9g2LBh2LZtm65NTk4O6tWrh5kzZ+LZZ4ufofj777/HBx98gNmzZ+PcuXNYuXIlYmNjMX369HK9bgBgbW2NiIgIZGZmlvsxREREREREVP1V6BzrXbt26d1ftWoVnJ2dkZycjO7du0MIgcjISMycORP9+/cHAKxevRouLi6IiYnBmDFjAEC3Vzg+Pr7UvJ07dyIuLg4bNmzAzp079dbFxcXh7NmzuHLlim7gvXjxYgQHB2P+/PlwcHAoMnCfNGkSfvrpJ2zatAl9+vQBADRp0gRLly4FAHz99dfFPo/ExER07doVQUFBuscMHjwYhw8fLvX5/13Pnj2RmpqKsLAwLFiwoNyPIyIiIiIiourNoHOss7IeXRuydu3aAIC0tDRotVr4+/vr2qjVavTo0QMHDx6sUN83b95ESEgI1qxZAxsbmyLrExMT0bZtW7292QEBAcjJyUFycnKpz/nx8y2vbt26ITk5WTeQ/u2337Bjxw4EBgaWuw9zc3OEhoYiKioKV69erVA+ERERERGRsfFQcOOp9MBaCIEpU6agW7duaNu2LQBAq9UCAFxcXPTauri46NaVt+/g4GCMHTsWPj4+xbbRarVFcpycnGBlZVVi1o8//ogjR45gxIgR5X4uADBo0CDMmzcP3bp1g6WlJZo1a4YXX3wRH3zwQYX66devH7y9vTF79uwKPY6IiIiIiIiqr0pfbmvChAk4efIkDhw4UGTdkxNyCSEqNElXVFQU7ty5U+Y5zMX1WVJWfHw8goOD8dVXX6FNmzblfi6PHzt//nx8/vnn6NSpE1JTU/Huu++ifv36mDVrVoX6ioiIwEsvvaR3LnhJcnJykJOTo7csL9cSllbqCmUSERERERE9qZCX2zKaSu2xnjhxIrZu3Yp9+/ahYcOGuuWurq4AUGSPcUZGRpG9y6XZu3cvkpKSoFarYWFhgebNmwMAfHx8MHz4cF3WkzmZmZnIy8srkpWQkIA+ffpgyZIlGDZsWPkL/f9mzZqFoUOHYtSoUfDy8kK/fv0QGhqKsLAwFBYWVqiv7t27IyAgoFwTt4WFhcHR0VHvtvnb8DIfR0RERERERPJUaGAthMCECROwceNG7N27Fx4eHnrrPTw84Orqit27d+uW5ebmIiEhAV26dCl3zrJly3DixAmkpKQgJSUFO3bsAADExsZi/vz5AABfX1+cPn0aN27c0D0uLi4OarUaHTp00C2Lj49HYGAgwsPDMXr06IqUq3P//n2Ymem/VObm5hBCVOqi6uHh4di2bVuZ551Pnz4dWVlZere+wyp2+DkRERERERGZVoUOBR8/fjxiYmKwZcsW2Nvb6/YYOzo6QqPRQKVSYfLkyQgNDUWLFi3QokULhIaGwsbGRjejNvBoj7ZWq0VqaioA4NSpU7C3t4e7uztq164Nd3d3vVw7OzsAQLNmzXR7yP39/eHp6YmhQ4di4cKFuHXrFt5//32EhITAwcEBwP8G1e+++y4GDBige75WVlZ6E5g9vj72vXv38McffyAlJQVWVlbw9PQEAN3e7vbt2+sOBZ81axZef/11mJubV+QlBAB4eXlhyJAhiIqKKrWdWq2GWq1/2LelVcX2kBMRERERERVHqROJVYUKDaxXrFgBAPDz89NbvmrVKgQHBwN4dN3pBw8eYNy4ccjMzESnTp0QFxcHe3t7Xfvo6Gh8/PHHuvvdu3cv0k9ZzM3NsX37dowbNw5du3aFRqNBUFAQFi1apGvzzTff4P79+wgLC0NYWJhueY8ePfQu9dW+fXvdv5OTkxETE4PGjRvj8uXLAIAPP/wQKpUKH374Ia5du4Z69eqhT58+ur3nlTFv3jysX7++0o8nIiIiIiKi6kElKnMsM1WZ9Yly9li/6HjU5BmXzZ8xeQYAeKX9KCUntflrJs8oFAZdIa/cnjm1VkrOw6bPmjzjnk1dk2cAgEVhnpScWud/MXlGoZOzyTMA4M/6XlJynNOSTB9y747pMwAIJznbM1Sm/6z5/PYgk2cAQPfWWVJyWmfuN3nGz+pXTJ4BALJ+GdqqTf+5+XzGJpNnAMBpt/JfgrWyMtp2MnkGAHQ+vkpKju2FIybPONVmuMkzAKBjy1pSckxh2KwbZTcygW/n1a+SXFOS8yudiIiIiIiISKE4sDZQeno67OzsSrylp6dX9VMkIiIiIiIiE6r0dazpETc3N93kZyWtJyIiIiIiqm4KOXmZ0XBgbaC/X2ebiIiIiIiIah4OrImIiIiIiGogXm7LeDiwfsr8+KOcc7bbpH5g8gyv4W+YPAMACl0aSsnxyDho8gzzjKsmzwCAW21elJJT+2qKyTPua2qX3cgIaqVKmHkacmbsNvtTzgyhhW7eUnL+8DD9TLoPzWxNngEAdnmZUnLuWNYxeUavBn+YPAMAauEvKTlmeTkmz3jW6ZzJMwAg19xaSo6QMPt8RiMfk2cAQJPcCybPaCpptu6k9iOk5HQ88b3JM1zMZM14XUtSDlVnHFgTERERERHVQLzysvFwVnAiIiIiIiIiA3BgTURERERERGQAHgpORERERERUA4nCwqp+CopRoT3WYWFh6NixI+zt7eHs7Iy+ffvi/Pnzem2EEJgzZw7c3Nyg0Wjg5+eHM2fO6LX58ssv4efnBwcHB6hUKty+fbvEzJycHHh7e0OlUhW5XnR6ejr69OkDW1tb1K1bF5MmTUJubq5ufXx8PN544w3Ur18ftra28Pb2xvffF50oISEhAR06dIC1tTWaNm2K6OhovfVfffUVXnjhBTg5OcHJyQk9e/bE4cOHy/mqAcHBwVCpVAgPD9dbvnnzZqhUqnL3Q0RERERERNVPhQbWCQkJGD9+PJKSkrB7927k5+fD398f2dnZujYLFizAkiVLsHz5chw5cgSurq7o1asX7t69q2tz//599O7dGzNmzCgzc9q0aXBzcyuyvKCgAIGBgcjOzsaBAwewbt06bNiwAVOnTtW1OXjwINq1a4cNGzbg5MmTeOeddzBs2DBs27ZN1yYtLQ2vvvoqXnjhBRw/fhwzZszApEmTsGHDBl2b+Ph4DB48GPv27UNiYiLc3d3h7++Pa9eulfu1s7a2RkREBDIz5czoSkREREREVJrCQlElNyWq0KHgu3bt0ru/atUqODs7Izk5Gd27d4cQApGRkZg5cyb69+8PAFi9ejVcXFwQExODMWPGAAAmT54M4NGAtTQ7d+5EXFwcNmzYgJ07d+qti4uLw9mzZ3HlyhXdwHvx4sUIDg7G/Pnz4eDgUGTgPmnSJPz000/YtGkT+vTpAwCIjo6Gu7s7IiMjAQCtW7fG0aNHsWjRIgwYMAAAiuzl/uqrr/Djjz9iz549GDZsWDleOaBnz55ITU1FWFgYFixYUK7HEBERERERUfVn0ORlWVlZAIDatR9dJzYtLQ1arRb+/v66Nmq1Gj169MDBgxW7xu/NmzcREhKCNWvWwMbGpsj6xMREtG3bVm9vdkBAAHJycpCcnFzqc378fB/38/fn+7ifo0ePIi8vr9g+7t+/j7y8PL1+ymJubo7Q0FBERUXh6lU51yImIiIiIiIi06v0wFoIgSlTpqBbt25o27YtAECr1QIAXFxc9Nq6uLjo1pW37+DgYIwdOxY+Pj7FttFqtUVynJycYGVlVWLWjz/+iCNHjmDEiP9d+L64flxcXJCfn48///yz2H4++OADNGjQAD179ix3TQDQr18/eHt7Y/bs2RV6HBERERERkbEJIarkpkSVnhV8woQJOHnyJA4cOFBk3ZMTcgkhKjRJV1RUFO7cuYPp06eX2q64PkvKio+PR3BwML766iu0adOmzOdbUv8LFizA2rVrER8fD2tr6zJreVJERAReeuklvXPBS5KTk4OcnBy9ZQX5OTC3UFc4l4iIiIiIiEyjUnusJ06ciK1bt2Lfvn1o2LChbrmrqysAFNljnJGRUWSvcGn27t2LpKQkqNVqWFhYoHnz5gAAHx8fDB8+XJf1ZE5mZiby8vKKZCUkJKBPnz5YsmRJkXOii+snIyMDFhYWqFOnjt7yRYsWITQ0FHFxcWjXrl256/m77t27IyAgoFwTt4WFhcHR0VHv9uvhFZXKJSIiIiIi+jtRKKrkpkQVGlgLITBhwgRs3LgRe/fuhYeHh956Dw8PuLq6Yvfu3bplubm5SEhIQJcuXcqds2zZMpw4cQIpKSlISUnBjh07AACxsbGYP38+AMDX1xenT5/GjRs3dI+Li4uDWq1Ghw4ddMvi4+MRGBiI8PBwjB49ukiWr6+v3vN93I+Pjw8sLS11yxYuXIh58+Zh165dJR6eXl7h4eHYtm1bmeedT58+HVlZWXq3Vs//n0HZREREREREZFwVOhR8/PjxiImJwZYtW2Bvb6/b0+vo6AiNRgOVSoXJkycjNDQULVq0QIsWLRAaGgobGxsEBQXp+tFqtdBqtUhNTQUAnDp1Cvb29nB3d0ft2rXh7u6ul2tnZwcAaNasmW4Pub+/Pzw9PTF06FAsXLgQt27dwvvvv4+QkBA4ODgA+N+g+t1338WAAQN0z9fKyko38djYsWOxfPlyTJkyBSEhIUhMTMTKlSuxdu1aXf6CBQswa9YsxMTEoEmTJrp+7OzsdM+tIry8vDBkyBBERUWV2k6tVkOt1j/s29ziVoXziIiIiIiInqTUvcdVoUJ7rFesWIGsrCz4+fmhfv36ultsbKyuzbRp0zB58mSMGzcOPj4+uHbtGuLi4mBvb69rEx0djfbt2yMkJATAo8Oj27dvj61bt5b7uZibm2P79u2wtrZG165dMXDgQPTt2xeLFi3Stfnmm29w//59hIWF6T3fx5cCAx7tZd+xYwfi4+Ph7e2NefPmYdmyZbpLbQHA559/jtzcXLz55pt6/fw9q6LmzZun2BP3iYiIiIiIahKV4OjuqTJw6mUpObNT3zF5RrPhb5g8AwAKXRqW3cgIRAUm6Kss8ww5l2q71dpPSk7tqykmz7jV0NvkGQBQ++IvUnIKHeqU3chAZn/eKLuREWjbvSIlx1zkmzzjoZmtyTMAwC4vU0rOHUvTb2c5hXIm4qyFv6Tk1NWeNnnGbeeWJs8AgFzzik/OWhlCZdBVX8vFTBSYPAMAbHKzTJ5hVmj6zzIASGo/ouxGRtDxxPcmz3hoKeez2b1Fayk5pvDmu79VSe6PS5tWSa4pVXpWcCIiIiIiInp6FYrCqn4KimH6/ypUuPT0dN251sXd0tPTq/opEhERERERkQlxj7WB3NzckJKSUup6IiIiIiKi6oaTlxkPB9YG+vt1tomIiIiIiKjm4aHgRERERERERAbgHuunzKhhcg4td7KONHlGmoXpZ50FAI9LcVJyzjQx/Sznaudck2cAQPNj30nJedCyo8kzMs3rmTwDAKyaeEvJsT5Q/ssSVpZZk2YmzwAATd5dKTmO6SmmDymQM/Mw8uR8BjjWrW/yjJiHA8puZASebhopOXVh+lnBU7LlzDxsq86TknMt0/R/m9c0cn4DpNr7mDzD87Sc72YZs3UDwJFnh5g8w+2snCt2uEtJMQ0eCm483GNNREREREREZADusSYiIiIiIqqBhOAea2PhHmsiIiIiIiIiA3CPNRERERERUQ1UWFhY1U9BMSq0xzosLAwdO3aEvb09nJ2d0bdvX5w/f16vjRACc+bMgZubGzQaDfz8/HDmzBm9Nl9++SX8/Pzg4OAAlUqF27dvl5iZk5MDb29vqFSqIteLTk9PR58+fWBra4u6deti0qRJyM3938QuDx8+RHBwMLy8vGBhYYG+ffsW6f/GjRsICgpCy5YtYWZmhsmTJxdp4+fnB5VKVeQWGBhY5msGAMHBwVCpVAgPD9dbvnnzZqhUqnL1QURERERERNVThQbWCQkJGD9+PJKSkrB7927k5+fD398f2dnZujYLFizAkiVLsHz5chw5cgSurq7o1asX7t793+yv9+/fR+/evTFjxowyM6dNmwY3t6IzYRcUFCAwMBDZ2dk4cOAA1q1bhw0bNmDq1Kl6bTQaDSZNmoSePXsW239OTg7q1auHmTNn4tlnny22zcaNG3Hjxg3d7fTp0zA3N8dbb71V5vN/zNraGhEREcjMzCz3Y4iIiIiIiKj6q9Ch4Lt27dK7v2rVKjg7OyM5ORndu3eHEAKRkZGYOXMm+vfvDwBYvXo1XFxcEBMTgzFjxgCAbq9wfHx8qXk7d+5EXFwcNmzYgJ07d+qti4uLw9mzZ3HlyhXdwHvx4sUIDg7G/Pnz4eDgAFtbW6xYsQIA8MsvvxS7Z7xJkyZYunQpAODrr78u9nnUrl1b7/66detgY2NToYF1z549kZqairCwMCxYsKDcjyMiIiIiIjIFXm7LeAyavCwrKwvA/waeaWlp0Gq18Pf317VRq9Xo0aMHDh48WKG+b968iZCQEKxZswY2NjZF1icmJqJt27Z6e7MDAgKQk5OD5OTkypRTbitXrsSgQYNga2tb7seYm5sjNDQUUVFRuHr1qgmfHREREREREclU6YG1EAJTpkxBt27d0LZtWwCAVqsFALi4uOi1dXFx0a0rb9/BwcEYO3YsfHx8im2j1WqL5Dg5OcHKyqpCWRV1+PBhnD59GqNGjarwY/v16wdvb2/Mnj3bBM+MiIiIiIio/IQorJKbElV6VvAJEybg5MmTOHDgQJF1T07IJYSo0CRdUVFRuHPnDqZPn15qu+L6rGhWRa1cuRJt27bF888/X6nHR0RE4KWXXtI7F7wkOTk5yMnJ0VuWm6uClZW6UtlERERERERkfJXaYz1x4kRs3boV+/btQ8OGDXXLXV1dAaDIHuOMjIwie5dLs3fvXiQlJUGtVsPCwgLNmzcHAPj4+GD48OG6rCdzMjMzkZeXV6Gsirh//z7WrVtXqb3Vj3Xv3h0BAQHlmrgtLCwMjo6OerfYlTw/m4iIiIiIqDqp0MBaCIEJEyZg48aN2Lt3Lzw8PPTWe3h4wNXVFbt379Yty83NRUJCArp06VLunGXLluHEiRNISUlBSkoKduzYAQCIjY3F/PnzAQC+vr44ffo0bty4oXtcXFwc1Go1OnToUJGyym39+vXIycnBP/7xD4P6CQ8Px7Zt28o873z69OnIysrSu709cppB2URERERERMCjycuq4qZEFToUfPz48YiJicGWLVtgb2+v22Ps6OgIjUYDlUqFyZMnIzQ0FC1atECLFi0QGhoKGxsbBAUF6frRarXQarVITU0FAJw6dQr29vZwd3dH7dq14e7urpdrZ2cHAGjWrJluD7m/vz88PT0xdOhQLFy4ELdu3cL777+PkJAQODg46B579uxZ5Obm4tatW7h7967uWtje3t66No+X3bt3D3/88QdSUlJgZWUFT09PveexcuVK9O3bF3Xq1KnIy1aEl5cXhgwZgqioqFLbqdVqqNX6h31bWeWW0JqIiIiIiIiqQoUG1o8vXeXn56e3fNWqVQgODgbw6LrTDx48wLhx45CZmYlOnTohLi4O9vb2uvbR0dH4+OOPdfe7d+9epJ+ymJubY/v27Rg3bhy6du0KjUaDoKAgLFq0SK/dq6++it9//113v3379gAe7X1/chkAJCcnIyYmBo0bN8bly5d1yy9cuIADBw4gLi6uXM+vLPPmzcP69euN0hcREREREVFFKXXvcVWo0MD674PRkqhUKsyZMwdz5swpsU1Z65/UpEmTYrPd3d3xn//8p9TH/n1wXJLy1PXMM8+Uq11xvvnmmyLLGjdujIcPH1aqPyIiIiIiIqo+DLqONRERERERET2dCkVhldxMKTMzE0OHDtVN/jx06FDcvn27zMedO3cOr7/+OhwdHWFvb4/OnTsjPT293LkcWBsoPT0ddnZ2Jd4q8scgIiIiIiKiygsKCkJKSgp27dqFXbt2ISUlBUOHDi31MZcuXUK3bt3QqlUrxMfH48SJE5g1axasra3LnVvp61jTI25ubrrJz0paT0RERERERKZ17tw57Nq1C0lJSejUqRMA4KuvvoKvry/Onz+Pli1bFvu4mTNn4tVXX8WCBf+7tHHTpk0rlM2BtYH+fp1tIiIiIiKip0VVTV6Wk5ODnJwcvWXFXRGpohITE+Ho6KgbVANA586d4ejoiIMHDxY7sC4sLMT27dsxbdo0BAQE4Pjx4/Dw8MD06dPRt2/fcmfzUHAiIiIiIiKSJiwsTHcO9ONbWFiYwf1qtVo4OzsXWe7s7Ky7VPSTMjIycO/ePYSHh6N3796Ii4tDv3790L9/fyQkJJQ7m3usiYiIiIiIaiBRaNqJxEoyffp0TJkyRW9ZaXur58yZo3e55uIcOXIEwKOrVD1JCFHscuDRHmsAeOONN/Dee+8BALy9vXHw4EFER0ejR48epeY+xoH1U+baLSspOW0aFL/hGZMZ5LyRb7t7S8nRmJn+8ml38m1NngEAv3d4W0qOJXJNnmFfeNvkGQCQbV1bSs4fvSaYPKPhXykmzwAAm3s3peScbPymyTMcLe+YPAMAzmfKmbcjv9D03wFv1Dpk8gwAuGdVR0rOWeeeJs+wzc8zeQYA2Fs+kJLTuLbpfwecN+9UdiMjcMMVk2ecajPc5BkA4GJ2Q0qO29lfTJ5x3bOryTMAoH3eeSk5SlLRw74nTJiAQYMGldqmSZMmOHnyJG7eLPr74o8//oCLi0uxj6tbty4sLCzg6empt7x169Y4cOBAuZ8jB9ZERERERERUbdWtWxd169Yts52vry+ysrJw+PBhPP/88wCAQ4cOISsrC126dCn2MVZWVujYsSPOn9f/D5ILFy6gcePG5X6OHFgTERERERHVQFU1eZmptG7dGr1790ZISAi++OILAMDo0aPx2muv6U1c1qpVK4SFhaFfv34AgH/+8594++230b17d7z44ovYtWsXtm3bhvj4+HJnc/IyIiIiIiIiUoTvv/8eXl5e8Pf3h7+/P9q1a4c1a9botTl//jyysrJ09/v164fo6GgsWLAAXl5e+Pe//40NGzagW7du5c7lHmsiIiIiIqIaSIiqmbzMlGrXro3vvvuu1DZCFN1T/8477+Cdd96pdG6F9liHhYWhY8eOsLe3h7OzM/r27VvkWHQhBObMmQM3NzdoNBr4+fnhzJkzem2+/PJL+Pn5wcHBASqVCrdv3y4xMycnB97e3lCpVEhJSdFbl56ejj59+sDW1hZ169bFpEmTkJv7v8mQHj58iODgYHh5ecHCwqLE65AlJCSgQ4cOsLa2RtOmTREdHa23/syZMxgwYACaNGkClUqFyMjIMl+rvwsODoZKpUJ4eLje8s2bN5c4Ox0RERERERE9HSo0sE5ISMD48eORlJSE3bt3Iz8/H/7+/sjOzta1WbBgAZYsWYLly5fjyJEjcHV1Ra9evXD37l1dm/v376N3796YMWNGmZnTpk2Dm1vRWVALCgoQGBiI7OxsHDhwAOvWrcOGDRswdepUvTYajQaTJk1Cz57Fz9aZlpaGV199FS+88AKOHz+OGTNmYNKkSdiwYYPe823atCnCw8Ph6upartfqSdbW1oiIiEBmZmalHk9ERERERGRMhYWiSm5KVKFDwXft2qV3f9WqVXB2dkZycjK6d+8OIQQiIyMxc+ZM9O/fHwCwevVquLi4ICYmBmPGjAEATJ48GQDKPBl8586diIuLw4YNG7Bz5069dXFxcTh79iyuXLmiG3gvXrwYwcHBmD9/PhwcHGBra4sVK1YAAH755Zdi94xHR0fD3d1dtxe6devWOHr0KBYtWoQBAwYAADp27IiOHTsCAD744IPyvVhP6NmzJ1JTUxEWFoYFCxZUqg8iIiIiIiKqfgyavOzxCd+1az+6fmtaWhq0Wi38/f11bdRqNXr06IGDBw9WqO+bN28iJCQEa9asgY2NTZH1iYmJaNu2rd7e7ICAAOTk5CA5ObncOYmJiXrP93E/R48eRV6e8a4XaW5ujtDQUERFReHq1atG65eIiIiIiIiqVqUH1kIITJkyBd26dUPbtm0BAFqtFgCKXHzbxcVFt668fQcHB2Ps2LHw8fEpto1Wqy2S4+TkBCsrqwplFdePi4sL8vPz8eeff5a7n/Lo168fvL29MXv27HK1z8nJwZ07d/Ruebk5Rn1ORERERERUM4nCwiq5KVGlB9YTJkzAyZMnsXbt2iLrnpyQSwhRoUm6oqKicOfOHUyfPr3UdsX1WdGs4vp5PEucKSYWi4iIwOrVq3H27Nky24aFhcHR0VHvtj0mzOjPiYiIiIiIiCqvUgPriRMnYuvWrdi3bx8aNmyoW/54Yq8n9xhnZGQU2Stcmr179yIpKQlqtRoWFhZo3rw5AMDHxwfDhw/XZT2Zk5mZiby8vAplFddPRkYGLCwsUKdOnXL3U17du3dHQEBAuSZumz59OrKysvRugUGl/2cDERERERFReYhCUSU3JarQwFoIgQkTJmDjxo3Yu3cvPDw89NZ7eHjA1dUVu3fv1i3Lzc1FQkICunTpUu6cZcuW4cSJE0hJSUFKSgp27NgBAIiNjcX8+fMBAL6+vjh9+jRu3Lihe1xcXBzUajU6dOhQ7ixfX1+95/u4Hx8fH1haWpa7n4oIDw/Htm3byjzvXK1Ww8HBQe9maaU2yXMiIiIiIiKiyqnQrODjx49HTEwMtmzZAnt7e92eXkdHR2g0GqhUKkyePBmhoaFo0aIFWrRogdDQUNjY2CAoKEjXj1arhVarRWpqKgDg1KlTsLe3h7u7O2rXrg13d3e9XDs7OwBAs2bNdHvI/f394enpiaFDh2LhwoW4desW3n//fYSEhMDBwUH32LNnzyI3Nxe3bt3C3bt3ddfC9vb2BgCMHTsWy5cvx5QpUxASEoLExESsXLlS7xD33Nxc3aHbubm5uHbtGlJSUmBnZ6fbm14RXl5eGDJkCKKioir8WCIiIiIiIqpeKjSwfnzpKj8/P73lq1atQnBwMIBH151+8OABxo0bh8zMTHTq1AlxcXGwt7fXtY+OjsbHH3+su9+9e/ci/ZTF3Nwc27dvx7hx49C1a1doNBoEBQVh0aJFeu1effVV/P7777r77du3B/C/86g9PDywY8cOvPfee/jss8/g5uaGZcuW6S61BQDXr1/XPQ4AFi1ahEWLFqFHjx5lXjKsJPPmzcP69esr9VgiIiIiIiJDCaHMicSqgko8HmHSU2HVPjk5/g1OmTzjnnktk2cAgGOecWd3L8kti/Kf219Zd/JtTZ4BAE6Wd6TkWCLX5BkWhabPAAChMujqheV2X2Vn8oyGf6WYPAMAYIIJIotzzr6ryTMcJb1nzme6ld3ICPILTf+3ecH2iMkzAOCetfHnSynOX/mmz8nOl3M6mL3lAyk5DyTUY2Web/IMAHBTXTF5xnXRyOQZAOBidqPsRkbwF+qZPOO6p+k//wEgMO+8lBxT6N7vQJXk7t/UrUpyTalCe6yJiIiIiIhIGZQ6kVhVkLOLRcHS09NhZ2dX4i09Pb2qnyIRERERERGZEPdYG8jNzU03IVpJ64mIiIiIiKobUchzrI2FA2sD/f0620RERERERFTz8FBwIiIiIiIiIkMIUrSHDx+K2bNni4cPHz71OUqqRVaOkmqRlcNaanaOkmqRlaOkWmTlKKkWWTlKqkVWjpJqkZUjqxZSJl5uS+Hu3LkDR0dHZGVlwcHB4anOUVItsnKUVIusHNZSs3OUVIusHCXVIitHSbXIylFSLbJylFSLrBxZtZAy8VBwIiIiIiIiIgNwYE1ERERERERkAA6siYiIiIiIiAzAgbXCqdVqzJ49G2q1+qnPUVItsnKUVIusHNZSs3OUVIusHCXVIitHSbXIylFSLbJylFSLrBxZtZAycfIyIiIiIiIiIgNwjzURERERERGRATiwJiIiIiIiIjIAB9ZEREREREREBuDAmoiIiIiIiMgAHFgTERERERERGYADawU6duwYTp06pbu/ZcsW9O3bFzNmzEBubm4VPjMiIiIiIiLl4eW2FKhjx4744IMPMGDAAPz2229o06YN+vXrhyNHjiAwMBCRkZFV/RTLZGZmBpVKVWoblUqF/Px85kjMUFoOa6nZOUqqRVaOkmqRlaOkWmTlKKkWWTlKqkVWjqxaqOawqOonQMZ34cIFeHt7AwB++OEHdO/eHTExMfjll18waNAggwbWzz33HPbs2QMnJye0b9++1A+kY8eOVTpn06ZNJa47ePAgoqKiYIz/E1JSjpJqkZXDWmp2jpJqkZWjpFpk5SipFlk5SqpFVo6SapGVI6sWqkEEKY69vb24cOGCEEKInj17isjISCGEEL///ruwtrY2qO85c+aI7OxsIYQQs2fPFnPmzCnxZmznzp0Tffv2Febm5mLYsGHi999/N3qG0nKUVIusHNZSs3OUVIusHCXVIitHSbXIylFSLbJylFSLrBxZtZAycWCtQC+++KIYNmyY+Pbbb4WlpaW4ePGiEEKI+Ph40bhx46p9cpVw7do1MWrUKGFpaSlee+01cerUKeZUgwyl5bCWmp2jpFpk5SipFlk5SqpFVo6SapGVo6RaZOXIqoWUjQNrBTpx4oRo27atcHBw0NtzPGHCBDF48GCj5QQHB4v//ve/orCw0Gh9/t3t27fFtGnThEajEb6+vmL//v3MqQYZSsthLTU7R0m1yMpRUi2ycpRUi6wcJdUiK0dJtcjKkVUL1QwcWNcgDx48ELm5uUbrr0+fPkKtVgs3NzcxZcoUcfz4caP1HRERIWrXri08PT3F5s2bjdavknOUVIusHNZSs3OUVIusHCXVIitHSbXIylFSLbJylFSLrBxZtVDNwVnBFejKlStQqVRo2LAhAODw4cOIiYmBp6cnRo8ebdSs27dvY/369YiJicHPP/+Mli1b4h//+AeCgoLQpEmTSvdrZmYGjUaDnj17wtzcvMR2GzdurHSG0nKUVIusHNZSs3OUVIusHCXVIitHSbXIylFSLbJylFSLrBxZtVDNwVnBFSgoKAijR4/G0KFDodVq0atXL7Rp0wbfffcdtFotPvroI6Nl1apVC6NHj8bo0aNx9epVrF27Fl9//TU++ugjgy5PMGzYsDIvgWAMSspRUi2yclhLzc5RUi2ycpRUi6wcJdUiK0dJtcjKUVItsnJk1UI1B/dYK5CTkxOSkpLQsmVLLFu2DLGxsfjll18QFxeHsWPH4rfffjN6Zl5eHrZv347vvvsO27dvR+3atXHt2jWj55Tk6tWrcHNzg5mZGXOqUYbSclhLzc5RUi2ycpRUi6wcJdUiK0dJtcjKUVItsnJk1UJPL24ZCpSXlwe1Wg0A+O9//4vXX38dANCqVSvcuHHDqFn79u1DSEgIXFxcMHz4cNjb22Pbtm24cuWKUXPK4unpicuXLzOnmmUoLYe11OwcJdUiK0dJtcjKUVItsnKUVIusHCXVIitHVi309OKh4ArUpk0bREdHIzAwELt378a8efMAANevX0edOnWMltOwYUP89ddfCAgIwBdffIE+ffrA2traaP1XhKwDL5SUo6RaZOWwlpqdo6RaZOUoqRZZOUqqRVaOkmqRlaOkWmTl8CBfKgsH1goUERGBfv36YeHChRg+fDieffZZAMDWrVvx/PPPGy3no48+wltvvQUnJyej9UlERERERPS04cBagfz8/PDnn3/izp07eoPe0aNHw8bGxmg5xp5hnIiIiIiI6GnEgbVCmZubF9mTbMjlrx7r379/udvy8gRERERERFQTcGCtUD/++CPWr1+P9PR05Obm6q07duxYpft1dHTU/VsIgU2bNsHR0RE+Pj4AgOTkZNy+fbtCA3BjkHW5BCXlKKkWWTmspWbnKKkWWTlKqkVWjpJqkZWjpFpk5SipFlk5vDQXlYWzgivQsmXLMGLECDg7O+P48eN4/vnnUadOHfz222945ZVXDOp71apVupuLiwsGDhyItLQ0bNy4ERs3bsRvv/2GQYMGoW7dukaqpnyUNDmGrBwl1SIrh7XU7Bwl1SIrR0m1yMpRUi2ycpRUi6wcJdUiK4eTl1FZeB1rBWrVqhVmz56NwYMHw97eHidOnEDTpk3x0Ucf4datW1i+fLlRcurVq4cDBw6gZcuWesvPnz+PLl264K+//jJKTnlcuXIFbm5uMDc3Z041ynhac9LS0tCoUSNYWOgf1GPsWvLz84tkmCKnOE/j36Wqc57WWridVRxfs6crR0m1mCJHCFFkb+vTWktV5siqhZ5e3GOtQOnp6ejSpQsAQKPR4O7duwCAoUOHYu3atUbLyc/Px7lz54osP3fuHAoLCw3u/8iRIxgyZAg8PDyg0WhgY2MDDw8PDBkyBEePHtVr26hRo0p/0N24cQPfffcdduzYUeSw+ezsbMydO9fgnD59+mDNmjV48OBBudobUk9JLl26hJdeesngjCdfo0uXLmHy5MkIDAzEqFGjkJycrLfekFpkbQNPatmyJS5evFhkeWUzdu3ahVOnTgEACgsL8cknn6BBgwZQq9Vo2LAhwsPD9f4nvLI5Ml4vmX//EydOYNiwYWjatCk0Gg3s7Ozg5eWFWbNm4c6dOwbnVIf3JWC896aStjMA2L17N2bPno29e/cCAPbv349XXnkFL730ElatWmWUHCW9Zkp6bwJy/v4yPwNM/VsjJycHU6dORY8ePbBw4UIAwCeffAI7OzvY2dkhKChI729TnWsBqsfns7E+m6kGEaQ4Hh4eIjk5WQghhI+Pj4iOjhZCCPHTTz8JJycno+W89957wsnJSSxcuFD8/PPP4ueffxYLFy4UderUEe+9955BfW/atElYWlqK3r17i08//VTExMSI77//Xnz66afilVdeEVZWVmLz5s0G13D48GFRq1Yt4eDgIDQajWjRooU4ffq0br1WqxVmZmYG56hUKmFhYSEcHR3F2LFjxdGjRw3us6JSUlKMUouZmZm4efOmEEKI48ePCxsbG+Ht7S1CQkJEx44dhZWVlTh06JDBOTK2gX79+hV7MzMzEz179tTdN5Snp6f45ZdfhBBChIaGijp16oglS5aInTt3isjISOHi4iLCw8MNypD1npH199+1a5fQaDSib9++YvDgwcLGxkZMmDBB/Otf/xLNmzcXzZo1Ezdu3DAoozq8L4Uw3ntTSdvZmjVrhIWFhXjuueeEnZ2dWLVqlahVq5YYNWqUGDlypLCyshI//PCDwTlKes2U9N6U9feX9Rkg47fGe++9J9zc3MTUqVNF69atxfjx44W7u7v47rvvRExMjGjevLmYOHGioaXwdxNRKTiwVqCRI0eKOXPmCCGEWLFihdBoNKJnz56iVq1a4p133jFaTkFBgYiIiBBubm5CpVIJlUol3NzcREREhMjPzzeo7zZt2oiwsLAS14eHhwtPT0+DMoQQomfPnuKdd94RBQUF4s6dO2LcuHGiTp064tixY0II435BnDlzRnz66afCy8tLmJmZiXbt2omoqChx69Ytg/sXQoilS5eWeps2bZrRann84+21114Tb775pigsLNStHzFihOjdu7fBOTK2AZVKJXr06CGCg4P1bmZmZqJv3766+4aytrYW6enpQggh2rZtK2JjY/XW/+c//xHNmzc3KEPWe0bW39/b21usWLFCdz8uLk60atVKCCFEbm6uePnllw3+28h4Xwoh772ppO3M29tbLF26VAghxH//+1+h0WjEkiVLdOsXL14sunbtanCOkl4zJb03Zf39ZX0GyPit0ahRI7F7924hhBCXLl0SZmZmev9hExcXJxo3bmxQhhD83URUGg6sFaigoEDk5eXp7sfGxoqJEyeKpUuXipycHJNkZmVliaysLKP1p1arxfnz50tc/+uvvwq1Wm1wjpOTU5GciIgI4eTkJA4fPmzUL4jHP3iEEOLQoUNi9OjRwtHRUWg0GjF48GCxZ88egzPc3NxEkyZNir25ubkZvZaGDRuKAwcO6K1PSUkRLi4uBufI2AbWrl0rGjZsKL7++mu95RYWFuLMmTMG9f139evXF4mJiUIIIVxcXHQ/QB67cOGC0Gg0BmXIes/I+vtbW1uLtLQ03f3CwkJhaWkprl+/LoQQYv/+/aJevXoGZch4Xz7OkfHeVNJ2ZmtrK3777TfdfUtLS3HixAm9nDp16hico6TXTEnvTVl/f1mfATJ+a2g0GvH777/r7ltaWurtSU5LSxM2NjYGZQjB301EpeE51gpkZmamN+nKwIEDsWzZMkyaNAlWVlYmyXRwcICDg4PR+mvWrBk2b95c4votW7agadOmRsl6+PCh3v1p06ZhxowZ8Pf3x8GDB42S8aTnn38eX3zxBW7cuIHPP/8cV65cQa9evQzqs3Hjxvj000+RlpZW7G379u1Gee4qlUo3CYq5uXmRv7uDgwOysrIMzpGxDQwaNAgHDhzA119/jQEDBiAzM9Og/krSr18/zJ8/HwUFBXjjjTfw+eef6523uXz5cnh7exuUIes9I+vv36BBA5w/f153/9KlSygsLESdOnUAAA0bNsS9e/cMzvk7U7wvAXnvTSVtZ5aWlnrnbqrVatjZ2enuW1lZlfvcy9Io6TVT0ntT1t//Sab6DABM/1vD3d0diYmJAB6d069SqXD48GHd+kOHDqFBgwYG5wD83URUEl7HWiFOnjxZ7rbt2rUzSubNmzfx/vvvY8+ePcjIyChyGYKCgoJK9z137lwMGjQICQkJ8Pf3h4uLC1QqFbRaLXbv3o24uDisW7fO0BLQtm1bHDx4sMhr8v7770MIgcGDBxucURqNRoPg4GAEBwcXO1lWRXTo0AHJyckYOHBgsetVKpVRLhUhhMAzzzwDlUqFe/fu4dSpU/Dy8tKtv3jxIlxdXQ3OkbUNNG7cGAkJCfj444/x7LPP4quvvjL6tSpDQ0PRs2dPtGrVCr6+vvjhhx+we/duPPPMM0hNTcVff/2FuLg4gzJkvV6y/v7Dhg3DqFGjMHPmTKjVaixZsgSvv/667j8HU1JS4OHhYXBOcYz5vgTkvTeVtJ01b94cv/76q+6qE9euXYO9vb1u/aVLl9CwYUODc5T0minpvSnr718SY38GyPitMXbsWAQHB+Pf//43kpOTsXjxYsyYMQO//vorzMzMsGLFCkydOtXgHP5uIioZB9YK4e3tXa4PAJVKZdCA9++Cg4ORnp6OWbNmoX79+kYdjAwYMAD79+/H0qVLsWTJEmi1WgCAq6srfH19kZCQAF9fX4Nzhg0bhoSEBIwdO7bIun/+858QQmDFihUG5/To0aPMowVatGhhUMbcuXNx//79Etd7enoiLS3NoAwARWZjbdasmd79pKQk9OvXz+AcWdsA8Ogoj48//hj+/v4YOnSo0d4jjzk6OuLgwYNYuXIltm3bhiZNmqCwsBC5ubkYPHgw/u///s/gH4myXi9Zf/8ZM2YgOzsb8+bNQ05ODgICArB06VLd+gYNGhj83pTxvgTkvTeVtJ3NmDEDTk5OuvtP7n09evRoiT+GK0JJr5mS3puy/v6yPgNk/NaYPHky6tWrh6SkJIwaNQpvv/022rZti48++gj379/He++9h5kzZxqUAfB3E1FpeB1rhfj999/L3bZx48ZGybS3t8fPP/9s8GFyRNXJvXv3cOnSJbRu3dpkp04QERERkbJwj7VC/H2wHBYWBhcXF7zzzjt6bb7++mv88ccf+Ne//mWUzEaNGinqEJmCggL8+eefUKlUqFOnzlN9rUIl1SKbnZ0dnn322ap+GvQ3StqelVQLkZK2ZyXVIouSXjMl1UJVh5OXKdAXX3yBVq1aFVnepk0bREdHGy0nMjISH3zwAS5fvmy0Pv/uxIkT+OSTT/D555/jzz//1Ft3586dIv9xUFmbNm1C165dYWNjAzc3N9SvXx82Njbo2rVrqRPOGNO5c+eMMnmNkmoBgH//+98YPny47hDH2NhYtG7dGk2bNsXs2bONklEaY9Yia3suydNYS1Vvz8Z8zaq6FsB49VT1+xJ4OrfnkjyNtcjYnpVUC6Cs7UxJn2fVoRZSELmTkJMMarVa7zIVj126dMkol/R4rFatWsLKykqYmZkJOzs74eTkpHczxE8//SSsrKxEmzZthLu7u6hbt67Yu3evbr2xLucQHR0trKysxNixY8WmTZvEwYMHxS+//CI2bdokxo4dK9Rqtfjyyy8NzilLSkqKwfUoqRYhhPj000+Fra2t6N+/v6hfv7745JNPRJ06dcQnn3wi5s6dKxwdHcUXX3xhhGdcMmPVImt7Ls3TVkt12J6N9ZpVh1qEME491eF9KcTTtz2X5mmrRcb2rKRahFDWdqakz7PqUgspB8+xVqAWLVpg9uzZ+Mc//qG3fM2aNZg9ezZ+++03o+SsXr261PXDhw+vdN9dunTBiy++iPnz50MIgUWLFmHu3Ln44Ycf0Lt3b9y8eRNubm4GTzLVvHlzTJ8+HSNHjix2/ddff4358+fj0qVLBuVMmTKl1PV//PEHYmJiDKpHSbUAQOvWrTFr1iwEBQXh+PHjeP755xEdHa2rb9WqVfjss89w9OjRSmfIqkXG9qykWgA527Os10xJ700Z70tAWduzkmoB5GzPSqoFUNZ2pqTPM1m1UM3BgbUCRUREYOHChVi4cCFeeuklAMCePXswbdo0TJ06FdOnT5f6fMLDwzF27FjUqlWr3I9xdHTEsWPH9GY1Xbt2LUJCQrB27Vo8//zzRvlS1Wg0SElJ0V3S40m//vor2rdvb/D1Ms3NzeHt7V3itb7v3buHY8eOGVSPkmoBABsbG/z6669wd3cHAFhbWyM5ORlt2rQBAKSmpqJjx44GXXtaVi0ytmcl1QLI2Z5lvWZKem/KeF8CytqelVQLIGd7VlItgLK2MyV9nsmqhWqQKtpTTiZUWFgopk2bJqytrYWZmZkwMzMTNjY24uOPP66S52Nvby8uXbpUocfUq1dPHD16tMjydevWCRsbG7FixQqjHNLUoUMHMWXKlBLXT5kyRXTo0MHgnJYtW4o1a9aUuP748eMG16OkWoQQok6dOuLs2bO6+w0bNhSXL1/W3b948aKws7MzKENWLTK2ZyXVIoSc7VnWa6ak96aM96UQytqelVSLEHK2ZyXVIoSytjMlfZ7JqoVqDs4KrkAqlQoRERGYNWsWzp07B41GgxYtWkCtVlfJ8xGVOCjC29sb+/btQ4cOHfSWv/322ygsLDToMPO/W7x4MQIDA7Fr1y74+/vDxcUFKpUKWq0Wu3fvxu+//44dO3YYnNOhQwckJycXOTz/sfJcg7wsSqoFAFq1aoWTJ0+idevWAIArV67orf/111/RpEkTgzJk1SJje1ZSLYCc7VnWa6ak96aM9yWgrO1ZSbUAcrZnJdUCKGs7U9LnmaxaqObgoeBkcvb29jhx4kSFZm/ctGkT9u/fj08//bTY9WvXrsWXX36Jffv2Gfz8Ll++jBUrViApKQlarRYA4OrqCl9fX4wdO9YoPxK1Wi1ycnKMdg3xkiipll9++QW2trYlXif9888/R2FhISZMmFDpDFm1yNielVTLY6benmW9ZoBy3psy3peAsrZnJdXymKm3ZyXVAihrOwOU83kGyKmFag4OrMnkKjOwJiIiIiIielrwOtZET7h48SL27NmD1NTUqn4qT5VvvvkGWVlZJs8RQqCwsPCpzyAypd9//x2HDh3C4cOH8fvvv5skIz09HYcOHcLRo0eLXJfXWJ6cmOjw4cNISkpCTk6OSfIAOd8B/J6pHFnfM0r6PiMieTiwpmrJ3t4eI0eOxMGDB02aEx4ejr179wIAMjMz8fLLL6Nly5bo1asXWrZsiVdeeQW3b982OCcuLg75+fm6+zExMfD29oatrS2aN2+OZcuWPRUZpRk9ejSuX79utP7y8/Px4YcfokePHpg9ezYAYOHChbCzs4NGo8Hw4cORm5tb7TMe2759O0aNGoVp06bh119/1VuXmZmpm8G/umeU5cSJEzA3N1dEztNYy6effopGjRqhadOm8PX1RefOndG0aVM0atQIkZGRRsn4/PPP0bhxY3h4eKBLly7o1KkTXFxc0K1bNyQnJxsl4/Lly+jQoQPUajUCAwNx584d9OrVC507d0aXLl3g6emJCxcuGJzz5HdAz549jf4dICMDkPcdUJXfNcb+npGVI+u7RtZ3wN9zzp07Z7Kc0ijpO4AURPZsaVTzvPLKK+L69esVeoxKpRJt2rQRKpVKtGrVSixatEjcvHnT6M/N3d1dnDhxQgghxKhRo0T79u3FsWPHxIMHD0RKSoro3LmzGDlypME5ZmZmuuf/448/CnNzczFx4kTx/fffi6lTpwq1Wi1iYmKqfYYQQjg5ORV7U6lUwtHRUXffUB9++KFwcXERU6ZMEZ6enmLs2LGiUaNG4rvvvhPffvutaNiwoYiIiKj2GUII8f333wtzc3MRGBgounXrJqytrcV3332nW6/Vag2e3VRGRnmkpKQIlUqliJynrZa5c+cKBwcHER4eLo4fPy6uX78url27Jo4fPy7Cw8OFo6OjmDdvnkEZCxcuFPXr1xeRkZEiOjpatG7dWsydO1fs3LlTDB06VNjY2IgjR44YXMuAAQNEjx49xLZt28TAgQNF165dhZ+fn7h69aq4fv26CAgIEH379jU4R8Z3gJK+Z2TlyPqeUdL3mazvgJr0XSPrO4CUg+dYU6WtXLkSI0eOLLI8Pz8fs2bNQlhYWKX7NjMzg1arxY0bN/Dvf/8bMTExuHfvHl577TWMGjUKvXv3hkqlMuTpA3h0Ddbz58/r9r6sXr0a3bt3161PTk5Gnz59DP6f68f1ODs7o1u3bnj55Zfx8ccf69YvWrQI69evx+HDh6t1BvDoaIIePXrgrbfe0i0TQmDUqFGYO3cuGjRoAAAGz3LarFkzLF26FK+99hpSU1PRsmVLxMTE4O233wYA/PDDD5g7dy5OnTpVrTMA4LnnnsOIESMwceJEAMCPP/6IESNGIDIyEiNHjsTNmzcNvoapjAwA6N+/f6nrs7KyEB8f/1TkKKkWAGjUqBGioqLQt2/fYtdv2rQJEyZMwLVr1yqd4eHhgc8//xyvvPIKAODChQvo0qULtFotLCws8O677+LcuXOIi4urdAYAODs7Iy4uDt7e3sjKyoKTkxP279+Pbt26AQCOHTuGV199VTfZUGXJ+A5Q0veMrBxZ3zNK+j6T9R2gpO8aWZ/NVHPwUHCqtKlTp2LAgAG4deuWbtmvv/6K559/HuvXrzdKxrPPPouoqCjcuHFDd87Ta6+9Bnd3d3z00UcG99+4cWOcPn0awKNLN1hY6F+BztzcHNnZ2Qbn/N3Fixfxxhtv6C17/fXXjXJYo4yM48ePIyMjA3v37sWAAQMwfPhwBAcHQ6VSoW/fvhg+fLhRLh1y/fp1PPvsswCA5s2bw8rKSncfAHx8fAw+d1RGBvBo8PHaa6/p7r/55pvYtm0b3nvvPURHRxvcv6wMANi2bRsePnwIR0fHYm92dnZPTY6SagGAv/76Cy1btixx/TPPPIPMzEyDMjIyMnSX2gKAFi1aICsrC3/88QcA4J133kFiYqJBGQB0rxfwaPBjbm4Oe3t73XoHBwfcv3/f4BwZ3wFK/Z4xZY6s7xklfZ/J+g5Q0neNrM9mqkGqdH85PdV+++030bVrV+Hm5ibi4uLE8uXLhUajEUOHDhV37twxqO+/H2r2pLS0NPHhhx+KRo0aGZQhxKPDGlu3bi0uXrwoFi9eLHx9fUVqaqoQ4lF9fn5+4s033zQ4R6VSiX379okTJ06Ixo0bFzlU8ty5c8LOzq7aZzyWl5cnpk2bJpo1ayYOHDgghBDCwsJCnDlzxij9CyGEi4uLOHnypO5+ly5dxNWrV3X3z507JxwcHKp9hhBC1K9fXyQmJhZZHh8fL+zs7MTMmTMNPnRORoYQQnh5eYl///vfJa4/fvz4U5OjpFqEEKJHjx5iyJAhIi8vr8i6vLw8ERQUJHr06GFQhre3t/jyyy919/fs2SNsbGxEYWGhEEKIX3/9Vdjb2xuUIYQQnTt3Fh9++KEQQoivv/5auLi4iA8++EC3fu7cuaJDhw4G58j4DlDS94zMHBnfM7JyZHzXyPoOUNJ3jazPZqo5OLAmgxQUFIhJkyYJMzMzYWlpKdauXWuUflUqVZnnVD/+IWeoiRMnCktLS9GqVSthbW0tzMzMhJWVlTAzMxM+Pj7ixo0bBmeoVCphZmYmVCqVUKlUIjIyUm99TEyM8PT0rPYZT9qzZ49wd3cX06dPF5aWlkb9IfLiiy+Kb775psT169evN/iHtYwMIYR44403xEcffVTsun379glbW1uDv7xlZAghRHBwsBg3blyJ68+ePSuaNGnyVOQoqRYhhDh58qRwdXUVTk5Oom/fvmLMmDFi7Nixom/fvqJ27dqifv364vTp0wZlxMbGCktLSzFw4EAxbNgwYWdnpzfgjY6OFr6+voaWInbt2iWsra2FlZWV0Gg0Yv/+/eKZZ54RHTt2FJ07dxbm5uYiNjbW4Bwh5HwHKOV7RmbOY6b8npGVI+O7RtZ3gJK+a2R9NlPNwXOsySBbt27FqFGj0LJlS5w/fx5eXl5Ys2YN3NzcDOr3448/xj//+U/Y2NgY6ZmW7ty5c/jPf/6D3377DYWFhahfvz66du2Knj17GuVc7icP8bKzs0OdOnV097/99lsAwLBhw6p1RnH++usvhISEYN++fUhKSir1UNSKuHDhAiwtLeHh4VHs+piYGFhYWGDgwIHVOgMAEhIScPDgQUyfPr3Y9fHx8Vi9ejVWrVpVrTMAICcnBwUFBSZ/b8rIUVItj929exffffcdkpKSdOcfu7q6wtfXF0FBQXBwcDA4Y+fOnfjuu++Qk5ODgIAAhISE6Nb99ddfAKD32VNZaWlpOHbsGHx8fNC4cWPcvHkTn332Ge7fv4/AwEC8+OKLBmc8ZurvABkZsr4DquK7xlTfM7JyZHzXyPoOUNJ3jczPZqoZOLCmShszZgxWr16NTz75BFOnTsXNmzfxzjvv4NChQ1ixYoXBgxEiIiIiIqKnAQfWVGlt27bF999/rzcBBwB89tln+Ne//oV79+4ZnHHv3j0kJydDq9VCpVLBxcUFHTp0MPqEEkrKqapaXF1d8dxzz/E1q+IcJdUiM6c4+fn5uH79Otzd3RWRk5eXhxs3bhglR2l/f743q2dOVX3P8PusZuVU5fcMKUxVHodOT7eHDx+WuO7XX381qO/c3FwxadIkodFohEqlEmq1WlhZWQmVSiU0Go149913RW5urkEZQjyatEQpOUqqRQg524Cs7UxJtShtOytNSkqKtOuxPi05Svv787O5euYoqRYhlPUdoKTvmurwPUPKwoE1VUuTJk0SDRo0EOvWrROZmZm65ZmZmWLdunWiUaNG4t1332WO5Ayl5bAW5pTmaRrwyspR2t+f783qmaOkWmTlKKkWWTnV4XuGlIUDazLIDz/8IN566y3RqVMn0b59e72bIerWrSv27NlT4vr//ve/om7dugZlKC1HSbXIymEtNTvnyc+sJ2+tWrUyyoBXSTlK+vvLylFSLbJylFSLrBwl1SIrR1YtVHNYVPWh6PT0WrZsGWbOnInhw4djy5YtGDFiBC5duoQjR45g/PjxBvX94MED1K1bt8T1derUwYMHDwzKUFqOkmqRlcNaanbO2bNnMWjQoBJn6r1x4wYuXLhgUIbScpT095eVo6RaZOUoqRZZOUqqRVaOrFqoBqnqkT09vVq2bCliYmKEEELY2dmJS5cuCSGEmDVrlhg/frxBfb/22mvi5ZdfFlqttsg6rVYrevXqJfr06WNQhtJylFSLrBzWUrNzOnToID7//PMS1x8/ftwoe5KVlKOkv7+sHCXVIitHSbXIylFSLbJyZNVCNQcH1lRpGo1GXL58WQghRL169URKSooQQogLFy6I2rVrG9R3enq6aNu2rbCwsBDe3t4iICBA9O7dW3h7ewsLCwvRrl07ceXKFYNrUFKOkmqRlcNaanbOu+++W+r5c6mpqcLPz8+gDKXlKOnvLytHSbXIylFSLbJylFSLrBxZtVDNwcttUaU1bdoUP/74I5577jl07NgRo0aNwpgxYxAXF4dBgwbh1q1bBvVfWFiIn376CUlJSdBqtQAAV1dX+Pr6wt/fH2ZmZsYoQ1E5SqpFVg5rYQ5VjNL+/nxvVs8cJdUiK0dJtcjK4fcMGRMH1lRpo0aNQqNGjTB79mxER0djypQp6Nq1K44ePYr+/ftj5cqVVf0UiYiIiIiITI7/DUOV9uWXX2LmzJkAgLFjx2L16tVo3bo1Pv74Y0RHRxs9LzMzE0eOHMHVq1eN3rdSc5RUi6wc1sKcESNG4Pr16ybNUFqOkmqRlaOkWmTlKKkWWTlKqkVWjqxaSHm4x5oM8vDhQ5w8eRIZGRkoLCzULVepVOjTp0+l+50xYwY+/PBD2NjYIC8vD+PHj8fKlSshhIBKpcIbb7yBmJgYWFtbG/T8lZSjpFpk5bCWmp1z8uTJYpf7+Phg/fr1aNq0KQCgXbt2lc5QWo6SapGVo6RaZOUoqRZZOUqqRVaOrFqoBpF+Vjcpxs6dO0XdunWFSqUqcjN05lkzMzNx8+ZNIYQQ8+fPF/Xq1RMbNmwQ165dE9u2bRMNGjQQc+fONbgGJeUoqRZZOaylZuc8/qwq6TPMGJ9lSstRUi2ycpRUi6wcJdUiK0dJtcjKkVUL1RwcWFOlNWvWTIwbN67YyxQYSqVS6X5Ue3t7i5UrV+qtj42NFa1bt2aO5Ayl5bCWmp3z7LPPisDAQHHu3Dlx+fJlcfnyZZGWliYsLCzE7t27dcsMpaQcJdUiK0dJtcjKUVItsnKUVIusHFm1UM3BgTVVmr29vUhNTTVJ3yqVSmRkZAghhKhTp444deqU3vq0tDRhY2PDHMkZSsthLTU7JycnR7z77rvC09NTHDt2TLfcwsJCnDlzxqC+lZqjpFpk5SipFlk5SqpFVo6SapGVI6sWqjksqvpQdHp6vfnmm4iPj0ezZs1M0v9XX30FOzs7qNVqZGZm6q3LysqCWq1mThVkKC2HtdTcHCsrK0RGRmLnzp14/fXXMW7cOPzrX/8yqE+l5yipFlk5SqpFVo6SapGVo6RaZOXIqoVqDg6sqdKWL1+Ot956Cz///DO8vLxgaWmpt37SpEmV7tvd3R1fffUVgEcffMeOHcMLL7ygW79v3z60bNmy0v0rMUdJtcjKYS3MAYBXXnkFR48exYgRI7Bjxw6j9Kn0HCXVIitHSbXIylFSLbJylFSLrBxZtZDycWBNlRYTE4OffvoJGo0G8fHxUKlUunUqlcqggfXly5dLXd+5c2f06NGj0v0rMUdJtcjKYS3MeczFxQU7duzAsmXLULduXTg4OBitb6XmKKkWWTlKqkVWjpJqkZWjpFpk5ciqhZSNl9uiSnN1dcWkSZPwwQcfwMyMl0QnIiIiIqKaiaMhqrTc3Fy8/fbbVTKozszMxLfffsucapahtBzWUrNzlFSLrBwl1SIrR0m1yMpRUi2ycpRUi6wcWbWQglT17Gn09Jo8ebKYP39+lWSnpKRIubagknKUVIusHNZSs3OUVIusHCXVIitHSbXIylFSLbJylFSLrBxZtZBy8BxrqrSCggIsWLAAP/30E9q1a1dk8rIlS5ZUuu87d+6Uuv7u3buV7lupOUqqRVYOa6nZOUqqRVaOkmqRlaOkWmTlKKkWWTlKqkVWjqxaqObgOdZUaS+++GKJ61QqFfbu3Vvpvs3MzPQmQ3uSEAIqlQoFBQWVzlBajpJqkZXDWmp2jpJqkZWjpFpk5SipFlk5SqpFVo6SapGVI6sWqjm4x5oqbd++fSbr297eHjNnzkSnTp2KXX/x4kWMGTOGOZIzlJbDWmp2jpJqkZWjpFpk5SipFlk5SqpFVo6SapGVI6sWqjk4sKZq6bnnngOAEi+nU6tWLRjjYAsl5SipFlk5rKVm5yipFlk5SqpFVo6SapGVo6RaZOUoqRZZObJqoZqDs4JTtRQUFARra+sS17u6umL27NnMkZyhtBzWUrNzlFSLrBwl1SIrR0m1yMpRUi2ycpRUi6wcWbVQzcFzrImIiIiIiIgMwD3WRERERERERAbgOdZUbWVnZyMmJgYHDx6EVquFSqWCi4sLunbtisGDB8PW1pY5VZChtBzWUrNzlFSLrBwl1SIrR0m1yMpRUi2ycpRUi6wcWbVQzcBDwalaOnv2LHr16oX79++jR48ecHFxgRACGRkZSEhIgK2tLeLi4uDp6ckcBdYiK4e11OwcJdUiK0dJtcjKUVItsnKUVIusHCXVIitHVi1UgwiiasjPz08MGjRI5OTkFFmXk5MjBg8eLPz8/JgjOUNpOaylZucoqRZZOUqqRVaOkmqRlaOkWmTlKKkWWTmyaqGagwNrqpY0Go04c+ZMietPnTolNBoNcyRnKC2HtdTsHCXVIitHSbXIylFSLbJylFSLrBwl1SIrR1YtVHNw8jKqlpycnHDx4sUS16empsLJyYk5kjOUlsNaanaOkmqRlaOkWmTlKKkWWTlKqkVWjpJqkZUjqxaqQap6ZE9UnNmzZwtHR0excOFCkZKSIm7cuCG0Wq1ISUkRCxcuFE5OTuLjjz9mjkJrkZXDWmp2jpJqkZWjpFpk5SipFlk5SqpFVo6SapGVI6sWqjk4sKZqKzw8XNSvX1+oVCphZmYmzMzMhEqlEvXr1xcRERHMqaIMpeWwlpqdo6RaZOUoqRZZOUqqRVaOkmqRlaOkWmTlyKqFagbOCk7VXlpaGrRaLQDA1dUVHh4ezKkGGUrLYS01O0dJtcjKUVItsnKUVIusHCXVIitHSbXIypFVCykbB9ZEREREREREBuDkZVRtPXjwAAcOHMDZs2eLrHv48CG+/fZb5lRBhtJyWEvNzlFSLbJylFSLrBwl1SIrR0m1yMpRUi2ycmTVQjVE1R6JTlS88+fPi8aNG+vOeenRo4e4fv26br1WqxVmZmbMkZyhtBzWUrNzlFSLrBwl1SIrR0m1yMpRUi2ycpRUi6wcWbVQzcE91lQt/etf/4KXlxcyMjJw/vx5ODg4oGvXrkhPT2dOFWYoLYe11OwcJdUiK0dJtcjKUVItsnKUVIusHCXVIitHVi1Ug1T1yJ6oOM7OzuLkyZN6y8aNGyfc3d3FpUuXjPa/iErKUVItsnJYS83OUVItsnKUVIusHCXVIitHSbXIylFSLbJyZNVCNYdFVQ/siYrz4MEDWFjob56fffYZzMzM0KNHD8TExDCnCjKUlsNaanaOkmqRlaOkWmTlKKkWWTlKqkVWjpJqkZUjqxaqQap6ZE9UnI4dO4pvv/222HXjx48XtWrVMsr/IiopR0m1yMphLTU7R0m1yMpRUi2ycpRUi6wcJdUiK0dJtcjKkVUL1RwcWFO1FBoaKl555ZUS1//f//2fUKlUzJGcobQc1lKzc5RUi6wcJdUiK0dJtcjKUVItsnKUVIusHFm1UM3B61gTERERERERGYCzghMREREREREZgANrIiIiIiIiIgNwYE1ERERERERkAA6siYiIiIiIiAzAgTURERERERGRATiwJiIiIiIiIjIAB9ZEREREREREBuDAmoiIiIiIiMgA/w/yGUv3gwDYGgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "# Create a copy of the DataFrame\n",
    "df_encoded = df.copy()\n",
    "\n",
    "# Instantiate LabelEncoder\n",
    "label_encoder = LabelEncoder()\n",
    "\n",
    "# Encode the 'class' column\n",
    "df_encoded['class'] = label_encoder.fit_transform(df['class'])\n",
    "\n",
    "# Plot correlation heatmap\n",
    "plt.figure(figsize=(12, 8))\n",
    "sns.heatmap(df_encoded.corr(), annot=True, cmap='coolwarm', fmt='.2f')\n",
    "plt.title('Correlation Heatmap')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "7984b670",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot class distribution\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.countplot(x='class', data=df)\n",
    "plt.title('Class Distribution')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efb615ca",
   "metadata": {},
   "source": [
    "# UNSUPERVISED LEARNING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "0d775016",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: scikit-learn in ./anaconda3/lib/python3.11/site-packages (1.3.2)\n",
      "Requirement already satisfied: numpy<2.0,>=1.17.3 in ./anaconda3/lib/python3.11/site-packages (from scikit-learn) (1.26.2)\n",
      "Requirement already satisfied: scipy>=1.5.0 in ./anaconda3/lib/python3.11/site-packages (from scikit-learn) (1.11.3)\n",
      "Requirement already satisfied: joblib>=1.1.1 in ./anaconda3/lib/python3.11/site-packages (from scikit-learn) (1.2.0)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in ./anaconda3/lib/python3.11/site-packages (from scikit-learn) (3.2.0)\n",
      "Requirement already satisfied: threadpoolctl in ./anaconda3/lib/python3.11/site-packages (3.2.0)\n",
      "Requirement already satisfied: numpy in ./anaconda3/lib/python3.11/site-packages (1.26.2)\n"
     ]
    }
   ],
   "source": [
    "!pip install --upgrade scikit-learn\n",
    "!pip install --upgrade threadpoolctl\n",
    "!pip install --upgrade numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "0be7a543",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/20/g3kpbwhd1sd3gwq9d2zdcf5r0000gn/T/ipykernel_70078/337148442.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  X['class'] = pd.Categorical(X['class'])\n",
      "/var/folders/20/g3kpbwhd1sd3gwq9d2zdcf5r0000gn/T/ipykernel_70078/337148442.py:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  X['class'] = X['class'].cat.codes\n",
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/sklearn/cluster/_kmeans.py:1416: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  super()._check_params_vs_input(X, default_n_init=10)\n",
      "/var/folders/20/g3kpbwhd1sd3gwq9d2zdcf5r0000gn/T/ipykernel_70078/337148442.py:10: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  X['cluster'] = kmeans.fit_predict(X[['class', 'max_ndvi']])\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Selecting relevant columns for clustering\n",
    "X = df[['class', 'max_ndvi']]\n",
    "\n",
    "# Convert categorical variable 'class' to numerical values using label encoding\n",
    "X['class'] = pd.Categorical(X['class'])\n",
    "X['class'] = X['class'].cat.codes\n",
    "\n",
    "# Apply K-Means clustering\n",
    "kmeans = KMeans(n_clusters=2, random_state=42)\n",
    "X['cluster'] = kmeans.fit_predict(X[['class', 'max_ndvi']])\n",
    "\n",
    "# Visualize the clusters\n",
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "# Scatter plot for class vs max_ndvi with color-coded clusters\n",
    "scatter = plt.scatter(X['class'], X['max_ndvi'], c=X['cluster'], cmap='viridis', alpha=0.7, edgecolors='k')\n",
    "\n",
    "# Add labels and legend\n",
    "plt.title('K-Means Clustering')\n",
    "plt.xlabel('Class (Encoded)')\n",
    "plt.ylabel('Max NDVI')\n",
    "plt.legend(*scatter.legend_elements(), title='Clusters')\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "55951c97",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Silhouette Score: 0.8535518902080583\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import silhouette_score\n",
    "silhouette_avg = silhouette_score(X[['class', 'max_ndvi']], X['cluster'])\n",
    "print(f\"Silhouette Score: {silhouette_avg}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a05566b0",
   "metadata": {},
   "source": [
    "# SUPERVISED LEARNING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "4102cd48",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Separate features (X) and target variable (y)\n",
    "X = df.drop(['class'], axis=1)  # Assuming 'class' is the target variable\n",
    "y = df['class']\n",
    "# Split the dataset into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "e7e546cc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9378852536747273\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Assuming you have X and y as your features and target variable\n",
    "# X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# Create a base classifier (you can replace this with any classifier of your choice)\n",
    "base_classifier = DecisionTreeClassifier(random_state=42)\n",
    "\n",
    "# Create a BaggingClassifier\n",
    "bagging_clf = BaggingClassifier(base_classifier, n_estimators=50, random_state=42)\n",
    "\n",
    "# Fit the BaggingClassifier on the training data\n",
    "bagging_clf.fit(X_train, y_train)\n",
    "\n",
    "# Make predictions on the test data\n",
    "y_pred = bagging_clf.predict(X_test)\n",
    "\n",
    "# Evaluate the performance\n",
    "b_accuracy = accuracy_score(y_test, y_pred)\n",
    "print(f'Accuracy: {b_accuracy}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "b5f51ee0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Separate features (X) and target variable (y)\n",
    "X = df.drop(['class'], axis=1)  # Assuming 'class' is the target variable\n",
    "y = df['class']\n",
    "# Split the dataset into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "\n",
    "# Create a Random Forest classifier\n",
    "clf = RandomForestClassifier(n_estimators=100, random_state=42)  # You can adjust the number of estimators\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "5da1cacf",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "from imblearn.over_sampling import RandomOverSampler\n",
    "# Standardize the features using StandardScaler\n",
    "scaler = StandardScaler()\n",
    "X_train_scaled = scaler.fit_transform(X_train)\n",
    "X_test_scaled = scaler.transform(X_test)\n",
    "\n",
    "# Oversample the minority class to address class imbalance\n",
    "oversampler = RandomOverSampler(sampling_strategy='minority')\n",
    "X_train_resampled, y_train_resampled = oversampler.fit_resample(X_train_scaled, y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "c0c98977",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {color: black;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestClassifier(random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestClassifier</label><div class=\"sk-toggleable__content\"><pre>RandomForestClassifier(random_state=42)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "RandomForestClassifier(random_state=42)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Train the classifier\n",
    "clf.fit(X_train, y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "c98a679c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9416785206258891\n"
     ]
    }
   ],
   "source": [
    "# Make predictions on the test set\n",
    "y_pred = clf.predict(X_test)\n",
    "\n",
    "# Evaluate the accuracy of the model\n",
    "r_accuracy = accuracy_score(y_test, y_pred)\n",
    "print(f'Accuracy: {r_accuracy}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "a52afef1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9416785206258891\n",
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "        farm       0.87      0.85      0.86       268\n",
      "      forest       0.96      0.99      0.97      1506\n",
      "       grass       0.90      0.74      0.81        85\n",
      "  impervious       0.90      0.84      0.87       202\n",
      "     orchard       1.00      0.18      0.31        11\n",
      "       water       1.00      0.81      0.90        37\n",
      "\n",
      "    accuracy                           0.94      2109\n",
      "   macro avg       0.94      0.74      0.79      2109\n",
      "weighted avg       0.94      0.94      0.94      2109\n",
      "\n",
      "Confusion Matrix:\n",
      "[[ 228   33    0    7    0    0]\n",
      " [   7 1493    2    4    0    0]\n",
      " [   4   13   63    5    0    0]\n",
      " [  18   10    4  170    0    0]\n",
      " [   2    7    0    0    2    0]\n",
      " [   2    2    1    2    0   30]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix\n",
    "\n",
    "# Assuming y_test and y_pred are your target values\n",
    "# Evaluate accuracy\n",
    "r_accuracy = accuracy_score(y_test, y_pred)\n",
    "print(f'Accuracy: {r_accuracy}')\n",
    "\n",
    "# Display classification report\n",
    "print('Classification Report:')\n",
    "print(classification_report(y_test, y_pred))\n",
    "\n",
    "# Display confusion matrix\n",
    "print('Confusion Matrix:')\n",
    "print(confusion_matrix(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "4d510f41",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/xgboost/core.py:160: UserWarning: [13:02:24] WARNING: /Users/runner/work/xgboost/xgboost/src/learner.cc:742: \n",
      "Parameters: { \"use_label_encoder\" } are not used.\n",
      "\n",
      "  warnings.warn(smsg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy on Test Dataset: 0.9634898055950688\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "import xgboost as xgb\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "\n",
    "# Encode the target variable using LabelEncoder\n",
    "label_encoder = LabelEncoder()\n",
    "y_train_encoded = label_encoder.fit_transform(y_train)\n",
    "\n",
    "# Convert the dataset into DMatrix format (optimized for XGBoost)\n",
    "dtrain = xgb.DMatrix(X_train, label=y_train_encoded)\n",
    "dtest = xgb.DMatrix(X_test, label=label_encoder.transform(y_test))\n",
    "\n",
    "# Define hyperparameters\n",
    "params = {\n",
    "    'objective': 'multi:softmax',  # For multiclass classification\n",
    "    'num_class': len(label_encoder.classes_),  # Number of classes\n",
    "    'eval_metric': 'merror',  # Classification error metric\n",
    "    'use_label_encoder': False  # To avoid XGBoost's native label encoding\n",
    "}\n",
    "\n",
    "# Train the XGBoost model\n",
    "num_rounds = 100\n",
    "xgb_model = xgb.train(params, dtrain, num_rounds)\n",
    "\n",
    "# Make predictions on the test set\n",
    "y_pred = xgb_model.predict(dtest)\n",
    "\n",
    "# Convert numeric predictions back to original labels\n",
    "y_pred_original = label_encoder.inverse_transform(y_pred.astype(int))\n",
    "\n",
    "# Evaluate the model\n",
    "x_accuracy = accuracy_score(y_test, y_pred_original)\n",
    "print(f'Accuracy on Test Dataset: {x_accuracy}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "42932a7a",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Assuming you have the accuracy values for each model\n",
    "model_names = ['K-means','Bagging', 'Random Forest', 'XGBoost']\n",
    "accuracy_values = [silhouette_avg,b_accuracy, r_accuracy, x_accuracy]\n",
    "\n",
    "# Create a color palette for better visualization\n",
    "colors = ['skyblue', 'lightgreen', 'lightcoral']\n",
    "\n",
    "# Create a bar plot with annotations\n",
    "plt.figure(figsize=(10, 6))\n",
    "bars = plt.bar(model_names, accuracy_values, color=colors)\n",
    "\n",
    "# Add data values on top of the bars\n",
    "for bar, value in zip(bars, accuracy_values):\n",
    "    plt.text(bar.get_x() + bar.get_width() / 2 - 0.15, bar.get_height() + 0.01, f'{value:.3f}', ha='center', va='bottom', fontsize=10)\n",
    "\n",
    "# Enhance chart aesthetics\n",
    "plt.ylim(0, 1)  # Set the y-axis limit based on your accuracy range (0 to 1)\n",
    "plt.title('Model Accuracy Comparison')\n",
    "plt.xlabel('Models')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.grid(axis='y', linestyle='--', alpha=0.7)\n",
    "plt.xticks(rotation=45, ha='right')\n",
    "\n",
    "# Add legend\n",
    "plt.legend(['Accuracy'], loc='upper right')\n",
    "\n",
    "# Show the plot\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "833fd389",
   "metadata": {},
   "source": [
    "# FEATURE REDUCTION BASED ON IMPORTANCE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "4b84be5e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "28\n",
      "29\n"
     ]
    }
   ],
   "source": [
    "print(len(rf_feature_importance))\n",
    "print(len(feature_names))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "49219055",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
       "        17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]),\n",
       " [Text(0, 0, 'max_ndvi'),\n",
       "  Text(1, 0, '20150720_N'),\n",
       "  Text(2, 0, '20150602_N'),\n",
       "  Text(3, 0, '20150517_N'),\n",
       "  Text(4, 0, '20150501_N'),\n",
       "  Text(5, 0, '20150415_N'),\n",
       "  Text(6, 0, '20150330_N'),\n",
       "  Text(7, 0, '20150314_N'),\n",
       "  Text(8, 0, '20150226_N'),\n",
       "  Text(9, 0, '20150210_N'),\n",
       "  Text(10, 0, '20150125_N'),\n",
       "  Text(11, 0, '20150109_N'),\n",
       "  Text(12, 0, '20141117_N'),\n",
       "  Text(13, 0, '20141101_N'),\n",
       "  Text(14, 0, '20141016_N'),\n",
       "  Text(15, 0, '20140930_N'),\n",
       "  Text(16, 0, '20140813_N'),\n",
       "  Text(17, 0, '20140626_N'),\n",
       "  Text(18, 0, '20140610_N'),\n",
       "  Text(19, 0, '20140525_N'),\n",
       "  Text(20, 0, '20140509_N'),\n",
       "  Text(21, 0, '20140423_N'),\n",
       "  Text(22, 0, '20140407_N'),\n",
       "  Text(23, 0, '20140322_N'),\n",
       "  Text(24, 0, '20140218_N'),\n",
       "  Text(25, 0, '20140202_N'),\n",
       "  Text(26, 0, '20140117_N'),\n",
       "  Text(27, 0, '20140101_N')])"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Assuming the first column contains the target variable (feature to be removed)\n",
    "target_variable = df.columns[0]\n",
    "\n",
    "# Drop the first column\n",
    "df_without_first_feature = df.drop(columns=[target_variable])\n",
    "\n",
    "# Get feature importance from Random Forest\n",
    "rf_feature_importance = clf.feature_importances_\n",
    "\n",
    "# Plot Random Forest feature importance\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.bar(range(len(rf_feature_importance)), rf_feature_importance, tick_label=df_without_first_feature.columns)\n",
    "plt.title('Random Forest Feature Importance')\n",
    "plt.xticks(rotation=45)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "9705a969",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lowest Feature Importance: 0.0132268091292374 for Feature: 20150109_N\n"
     ]
    }
   ],
   "source": [
    "# Find the index of the feature with the lowest importance\n",
    "lowest_importance_index = rf_feature_importance.argmin()\n",
    "\n",
    "# Print the lowest feature importance and corresponding feature name\n",
    "lowest_importance = rf_feature_importance[lowest_importance_index]\n",
    "lowest_feature_name = df_without_first_feature.columns[lowest_importance_index]\n",
    "print(f\"Lowest Feature Importance: {lowest_importance} for Feature: {lowest_feature_name}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "d5fafd4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot XGBoost feature importance\n",
    "xgb.plot_importance(xgb_model)  # Use XGBoost's plot_importance function\n",
    "plt.title('XGBoost Feature Importance')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "f4823109",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lowest Feature Importance (XGBoost): 246.0 for Feature: 20150720_N\n"
     ]
    }
   ],
   "source": [
    "# Get XGBoost feature importance using get_fscore()\n",
    "xgb_feature_importance = xgb_model.get_fscore()\n",
    "\n",
    "# Convert feature importance dictionary to a Pandas DataFrame\n",
    "xgb_feature_importance_df = pd.DataFrame(list(xgb_feature_importance.items()), columns=['Feature', 'Importance'])\n",
    "\n",
    "# Find the row with the lowest importance\n",
    "lowest_importance_row_xgb = xgb_feature_importance_df['Importance'].idxmin()\n",
    "\n",
    "# Print the lowest feature importance and corresponding feature name for XGBoost\n",
    "lowest_importance_xgb = xgb_feature_importance_df.loc[lowest_importance_row_xgb, 'Importance']\n",
    "lowest_feature_name_xgb = xgb_feature_importance_df.loc[lowest_importance_row_xgb, 'Feature']\n",
    "print(f\"Lowest Feature Importance (XGBoost): {lowest_importance_xgb} for Feature: {lowest_feature_name_xgb}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2339db93",
   "metadata": {},
   "source": [
    "Let's try to train the models with dropping these features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "1ac8b72c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original Model Cross-Validation Accuracy: 0.9172 (+/- 0.0493)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.metrics import accuracy_score, precision_score, recall_score\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "# Assuming '20150109_N' is the least important feature\n",
    "feature_to_remove = '20150109_N'\n",
    "\n",
    "# Remove the least important feature from the DataFrame\n",
    "df_removed_feature = df.drop(columns=[feature_to_remove])\n",
    "\n",
    "# Modified dataset (without the least important feature)\n",
    "X_removed_feature = df_removed_feature.drop(columns=[target_variable])\n",
    "y_removed_feature = df_removed_feature[target_variable]\n",
    "\n",
    "\n",
    "original_scores = cross_val_score(clf, X, y, cv=5, scoring='accuracy')\n",
    "print(\"Original Model Cross-Validation Accuracy: {:.4f} (+/- {:.4f})\".format(original_scores.mean(), original_scores.std() * 2))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "d0aafc1d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model without Least Important Feature Cross-Validation Accuracy: 0.9167 (+/- 0.0469)\n"
     ]
    }
   ],
   "source": [
    "# Train and evaluate the model on the modified dataset\n",
    "model_removed_feature = RandomForestClassifier(n_estimators=100, random_state=42)\n",
    "removed_feature_scores = cross_val_score(model_removed_feature, X_removed_feature, y_removed_feature, cv=5, scoring='accuracy')\n",
    "print(\"Model without Least Important Feature Cross-Validation Accuracy: {:.4f} (+/- {:.4f})\".format(removed_feature_scores.mean(), removed_feature_scores.std() * 2))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "a63862d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Original Model Metrics:\n",
      "Accuracy: 0.9172\n",
      "Precision: 0.9107\n",
      "Recall: 0.9172\n",
      "\n",
      "Model without Least Important Feature Metrics:\n",
      "Accuracy: 0.9167\n",
      "Precision: 0.9102\n",
      "Recall: 0.9167\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/sklearn/metrics/_classification.py:1471: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/sklearn/metrics/_classification.py:1471: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n"
     ]
    }
   ],
   "source": [
    "# Modify the metrics as per your specific requirements\n",
    "original_predictions = cross_val_predict(clf, X, y, cv=5)\n",
    "removed_feature_predictions = cross_val_predict(model_removed_feature, X_removed_feature, y_removed_feature, cv=5)\n",
    "\n",
    "print(\"\\nOriginal Model Metrics:\")\n",
    "print(\"Accuracy: {:.4f}\".format(accuracy_score(y, original_predictions)))\n",
    "print(\"Precision: {:.4f}\".format(precision_score(y, original_predictions, average='weighted')))\n",
    "print(\"Recall: {:.4f}\".format(recall_score(y, original_predictions, average='weighted')))\n",
    "\n",
    "print(\"\\nModel without Least Important Feature Metrics:\")\n",
    "print(\"Accuracy: {:.4f}\".format(accuracy_score(y_removed_feature, removed_feature_predictions)))\n",
    "print(\"Precision: {:.4f}\".format(precision_score(y_removed_feature, removed_feature_predictions, average='weighted')))\n",
    "print(\"Recall: {:.4f}\".format(recall_score(y_removed_feature, removed_feature_predictions, average='weighted')))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "dfaf242f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/sklearn/metrics/_classification.py:1471: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/sklearn/metrics/_classification.py:1471: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/Users/sharmidas/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a DataFrame for visualization\n",
    "metrics_df = pd.DataFrame({\n",
    "    'Metric': ['Accuracy', 'Precision', 'Recall'],\n",
    "    'Original Model': [\n",
    "        accuracy_score(y, original_predictions),\n",
    "        precision_score(y, original_predictions, average='weighted'),\n",
    "        recall_score(y, original_predictions, average='weighted')\n",
    "    ],\n",
    "    'Model without Least Important Feature': [\n",
    "        accuracy_score(y_removed_feature, removed_feature_predictions),\n",
    "        precision_score(y_removed_feature, removed_feature_predictions, average='weighted'),\n",
    "        recall_score(y_removed_feature, removed_feature_predictions, average='weighted')\n",
    "    ]\n",
    "})\n",
    "\n",
    "# Melt the DataFrame for easier plotting\n",
    "metrics_melted = pd.melt(metrics_df, id_vars='Metric', var_name='Model', value_name='Score')\n",
    "\n",
    "# Plot using Seaborn\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.barplot(x='Score', y='Metric', hue='Model', data=metrics_melted, palette='viridis')\n",
    "plt.title('Model Performance Comparison')\n",
    "plt.xlabel('Score')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "35101d29",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}