final_pipeline.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "392b0f06",
   "metadata": {},
   "source": [
    "# Instructions for Running the Jupyter Notebook\n",
    "The main Jupyter/Google Colab notebook for this problem statement is 'final_pipeline.ipynb' and\n",
    "it is divided into 6 sections. In the first section, the relevant libraries are installed and the models\n",
    "are loaded. The dependencies were selected with consideration to the Google Colab\n",
    "environment. It is important to upload the models directly in the '/content/' location and ensure\n",
    "that the correct paths to the models are provided in the third cell. To initialise the different\n",
    "variables and functions, all cells should be run once in the beginning. The last two sections\n",
    "contain the inference function and digitization functions, which are to be called by passing the\n",
    "location of the image as the parameter."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3c8af9f",
   "metadata": {},
   "source": [
    "# Abstract\n",
    "Medical vitals extraction from an image is a crucial yet time-consuming process. With the\n",
    "growing popularity and efficacy of Artificial Intelligence (AI), a large section of the community\n",
    "has started working on automating different healthcare activities, such as medical entity\n",
    "extraction and X-ray processing. In this work, we propose and build a transfer learning-based\n",
    "object segmentation incorporating a vital extraction model, which takes a monitor as input and\n",
    "outputs different medical vitals like oxygen and heart rate. The model first identifies the monitor\n",
    "segment, marks the region of interest for vitals, and finally recognizes the marked boxes with\n",
    "their respective vital labels. Our proposed model is a pipelined approach that helps to locate\n",
    "errors effectively and scale up easily. With the proposed model, we found that our model\n",
    "identifies different vitals with reliable confidences ranging from 0.9 to 0.97. We also did a\n",
    "thorough human evaluation, showing that our model can handle different uncertainties like\n",
    "monitor angle, shape, and background colour."
   ]
  },
  {
   "attachments": {
    "image-2.png": {
     "image/png": "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"
    },
    "image.png": {
     "image/png": "iVBORw0KGgoAAAANSUhEUgAAB4AAAAQ4CAYAAADo08FDAAQpLklEQVR4nOzdB2BddfUH8NPd0tICZZa99x4KCMhQ9hJREGSILJWNDNl7yVJQNoJsBGSDKDL+7K3svcvoLt0j/5xfSUyhlDZJk/b286nPvNz33n2/l9K85H7vOad9Ta0AAAAAAAAAYJrXvrUXAAAAAAAAAEDzEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAAABQEQJgAAAAAAAAgIoQAAMAAAAAAABUhAAYAAAAAAAAoCIEwAAAAAAAAAAVIQAGAAAAAAAAqAgBMAAAAAAAAEBFCIABAAAAAAAAKkIADAAAAAAAAFARAmAAAAAAAACAihAAAwAAAAAAAFSEABgAAAAAAACgIgTAAAAAAAAAABUhAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAAAAACpCAAwAAAAAzaimtRcA1GvT2gsAgFYgAAYAAACAZvTgR629AqDOmnNFdGjb2qsAgJYlAAYAAAAAAACoCAEwAAAAAAAAQEUIgAEAAAAAAAAqQgAMAAAAAAAAUBECYAAAAAAAAICKEAADAAAAAAAAVIQAGAAAAAAAAKAiBMAAAAAAAAAAFSEABgAAAAAAAKgIATAAAAAAAABARQiAAQAAAKYio8dG3PjaqHjg/dHx3Kdj67fP3LlNuczdrU2sMle7WHXOdrHIzG1bcaUAAMDUSAAMAAAAMBXI4Pfy/46Ki18YOcHb+w+vKZe3B0Q8/OGYsm3Orm1iwwXbxyYLd4gFe7RpwdUCAABTKwEwAAAAQCuqqb3c/fboOPb/Rkz2Yz8ZUhNXvDiqXL7bq13st0rHWHgmVcEAADA9EwADAAAAtJIBIyK2vnlIDBnV9H09/vGYePy2YbHpwu3joNU6RbcOTd8nAAAw7REAAwAAALSCnO+7573Dmn2/d76Vs4PHxCnrdI4le6oGpuX0fv+dePHpR8r1ZVZZM+aab8Ep9lwvP/t4fPTum+X6Whv/KDp3mWGKPdekGjygf7zx0nPR77NPYokVVo15Fly02fadr/eLgQNi5bV/EO3atWu2/X5VS/4dAgBTjgAYAAAAoIW9NWBs7HNf84e/dT7+oiZ2vnNYHPu9TrHJQg7/MM5TD9wbx/3qp+X67oedElvutHez7j+Dw5P3/Xm5/rs//HWKhod3XntJ3HXtpeX6DU99v9UD4NuvviguOOHgGPrF4PL5Aaf8udkC4HtvvCJOPWCXcn3LnX8V+590frPsd0Ja8u8QAJhy/AYAAAAA0MIOfWB4jBw75Z8n5wqPrn2eLRZxCIiI0aNHxZBBA8v1USMnf+Y0E9bnk4/j3CN+HWNGjy6ft23XLtq1a75/cx+89Vr99ffffHW82z77+IN45N5by/Uf/GjH6NZjpmZ7XgBg2uWnfwAAAIAWdNELI+P9QTUt9nwnPjou6BMCw5SR7Znrwt+td/1N/Oa4c6Nt2+Zrv77NL/ePTz56r4T3ux1y4ni3/eeJh+MPR+1Trq+81gYCYACg8JM/AAAAQAsZPDLi6pdGtfjzZgg8Q4eIDeZ3KAia27Ahg+uvL7nid5o1/E0zzzp7HPnHqyd42+e9P2jW5wIAqsFP/QAAAAAt5O9vjIpho1vnuX/34IjouWHbWHGO5g2nqL43X3o+7rru0njr5Rdi2JAvouccvWKVdX4Ym27/y4nO3s12xTdedFa89cp/omPnzrHYMivFljv9KuZecJEJ3n/0qFHx0F03lctnH70fnWfoGosss2JsvuOeMe9Ci03yerMqNtf70btvRrt27Wofu3hsucuvY5Gllp/kffR+/524/aoL47X/PB3Dvhgcc863YKy3xXax5oZbRps2bervd9UfT47nHrm//vN//O3KUhG8xAqrxYY/3ulr+x01cmSZFTy2ZmzMNtc88bNfHzbe7WPGjIk/H39Q7cfRMfOsc8RO+x8VH77zRtx06bnl9jV/uGWssvYP4uXnnoj7bvprvPT0o/WP/eu5J9ZXAO9z/B/GC6Ib+3f41a/J3y45J959/aWyjznnXSDW3+pntWvaYpIeDwC0HAEwAAAAQAu55fWWr/5taN9/Dos7ftw1enRq1WUwDbnuz2fExaccFmPH/m9o9RsvPheP/+vOuPWKP8XZN/w7es4x19ce98zD/4yzDt0zhg8bWr/thccejFv/+uc47OwrYt3NfzLe/fv3+SyO/uXW8WKDQDM99+i/4+9/OS/2PfG82Oxnu3/rei857Yi4+o8nj7fthccfijuvvSSOPO+aWG/L7b51H/fdfFWcecgeMWL4sPptrzz/ZPz7tuvjO+ttEkf/6bqYoduMZfu//n5NvPvaS/X3e/qh+8plg60HTDAA7tCxY7z96n/j+cceKLOCN/rJrjHLbHP87/U+cn992LvtHgeWj30++aj2a3B+uZ6hcQbA77/xSv22Ov+85X9Vwr859pyILwPgxv4dNpT3PXr3H5UAu/5r8twT5Wuyxc/3igNO+fNEHw8AtCwBMAAAAEALeG9QTXw4uOVm/07IiDERv75vWFy1WZdWXQfThgxjLzzpkHJ95tnmiM132CO69Zg5Hrzjxnjpmcfig7dei/OO3T+O+fP1X3vsvTdeUQLO766/acw659zxcu39M/gcOXx4nLL/TjHfIkvEwksuV+5bU1MTJ+2zQ334u9q6G8Uqa/8wBvXvW6pwB/brE2cftlfMs+CiscLq3//G9WaF6jXnnVKuL7bsSrHd3ofEqFEj46o/nFTW+vtDdo/vbbhVqUb+Jlk9fOoBu8TYMWNKBe3qP9g8Zpltznji/rvis48/KB/PPHSPOOr8a8v9l//uOtGuXftSWZsWWXqF8noXXWbFb3yOH/54pxIA53NktfNWO/+q/rYHbr9hvPt9k9l7zVu+tu+98XJ53Sm/Nlk1ndp8Gf425e+woXOP/E0Jf7vP3DN+edjJ0WPmWeOuay+JJ/59d9z21wtigx/tGMuuuuZE9wEAtBwBMAAAAEALeKr3mNZeQvF6v7Hx0AdjYu1527X2UpjKPfqP26Jr9x6l5fHpV99b30I52zjvut5S8fF7b8ej991W2hZnq+WGstL1zOv+Fcuu9r3yeVafZmvjbCE8asSIEsrWhY4ZhmbFcNp619/Evif8sX4/G227S+z2g+VKNW62OJ5YAJxhZobJaZ3Nto11t/hpub7o0ivGkw/cU64PHtg/enb+5mrXS08/ogSz6fhLbqlvbzxk8KDYd+vvlRD7/luvix1+87tYaMllY/+Tzo97bvhLnHbgruV+P9nzoPjBj3ac6Nd1nU1/HH848jelOvqBO26oD4DHjB4dD99zS7m+cO3XemItq1f63vrlct4x+9dXDGcVbgbrDTXl77BOhvaffPBuub7ECquWELluDXdec3G53r59h4m+ZgCgZQmAAQAAAFrAa/2mjgA4HfHQ8Lh/+67RwThgJmKP351aLhlM5hza/z75f2U2bZqt17wlPMxwcPCAfjFTz9nGe+xmO+xRH/6mrKbd84jTS+DZ55OP4/F/3lF/22MNrveaf+F48M6/jbev2eeer4S7/3nioRIkN5xt29BCSy5XqntzTZeedkQ8+3//Ki2bV/v+RvHTvQ7+1tf7xaCBpQI4Lbnid8abbdt1xu6x435HxvF7jwuVH/3n7SUAboxsH/29jbYuLZv/W/t8/T77JGaZfc6y3qx6ThOr/p0cTfk7rJNf06zWzlnOT/77nthtg+Vq179VrLLOhvHj3Q/4xuB4avLxxx/HP/7xj9hll11aeykA0CIEwAAAAAAt4O0BY7/9TpNgls5tYsiomtLOubHysec8PTJ+u1rHZlkT1ZTVtFl1+7dLzo7BA/p/4/3qKmYbWmzZlb+2rX2HDrHwUiuUADirXwf17xfdZ54lPv/4g/r7nH/sAd/4PKNHjSpBZY9ZZp3g7bPO2St+f+0/44yDdyuBcVYV5+VPxx0YveZfKLb71aH11asT8nnvD+uvz7vw4l+7vWF1bZ8G922MDHgzAM5AOwPvrHz+9x3j2j9n6+wNtt6hSfuv05S/w4ZOu+qe0ro7v55ZBZ2XK885Ibr1mCk22W632O23J060tXZrGjZsWKyxxhrx3nvvxZlnnhm33357LLDAAq29LACYogTAAAAAAC2gz9DGz//t1iFi52U7xlaLdogenSLG1O4q2zif/viI6Du8cfu98dVRsfeKHcu+YUIyOLz890eX6wssvnSsvck2MUPXGcvnt1z+x/j0o/e/8bED+n4+we2D+vUpH7MlcZeu3cr1Tl1mqL99vxPPq59jOyFdZ+wx0TXnHNorHnilzL599uF/xrOP/CtefOqRUul61qF7lvWvv9X237Dv7vXXM2j+2tq/rM5NM3Tr/rXbJ8fKa21QAusMw7MqevMd94xH7vl7uW3VdTaMWWabo0n7r9OUv8OGes4xV/z+2vvi/bdei6ceuCeee/Tf8cxD98UXAwfEDReeGUO/GBwHnXZhs6y5ufXv37+Ev+nFF1+MVVZZJW6++eZYe+21W3llADDlCIABAAAAWsCgkY0Lahfs0Sb++IMuMfsMbeq3tau9uu587WL+7p1jpzuGxchGFhdngHz8Wp0a92Aq794b/1I+ZsvlP9z0cMw408zl84H9+9aHit/k7usvi21226/MAq7z2gtPx2v/faZcn3+xpepvW7jBrNuZZ5ujzMitk+2JH/vXuBbRPefoVaqIv8nLzz5eP6t29R9sXsLgnQ88poSVB/5kvbL96Yf+8Y0BcO5/5llnj/59Pov/PPlwDOzXZ7xq4wfvuLH++qLLrjTR1/9t8muaVb7X/fmMElD/429XxqAvQ+cNt915kvfTrv3/Du+OHDnia7c35e+wTobnrz7/ZLmerbHz7zUv+fXZae3Fy7rz6zq16tWrV9x5553xk5/8JIYMGRJ9+/aNddZZJ84777z49a9/3drLA4ApQgAMAAAA0AKGjJr8x3RpH3HOBuPC36z6veX1UfHuwJr40WLtY6GZ2pbL+gu0j7vfHt2oNd3zzug49Ludoqsq4OlOhncfvfPmBG/rtcDCpUI358ambFP85svPx4prrFsqPk/Zb6cYMXzYRPf//puvxgHbfj923PeImHXOuUs4e+npR9a3Gt5ix73q75tB6GVnHBXDhw6Jc373q2jXrn2pgh00oG9pCV03E/jA0y6MZVZZ4xufM+fbXnDib8v1LXfaO351zNnRsVOn8ap5J1a5m7Nsc3ZxVs0OGTQwDv35xrHH4afGzLPOEf+69dq4/apxFa75etb84ZYTff2T4oc/3rkEwPn1/dMJB5VtXbv3iDV/sMW3PPJ/ZptrnvrrGeiut8V20alzlzKjNzXl77BOfv1O+PW40Hyplb4bJ152awnKs+q3bp5w1yZWRE9pm2yySTz99NOx8cYbx7vvvlu2/eY3v4lnnnkmLrroomjf3mFyAKrFOxsAAABAC+jcPmL4ZOa0Gy/UPubqOq7y9+THRsTtb47bwb/fHx23bTNDqQSev3vbJq3r6pdHxh7LmwU8vbnqDyeVy4Tc9drg0p452wXfePHZZVtW0Gbol8FxholZCfrKc0984/4zmHzpmcfi8J03+9pt2f54y51/Vf957vfg0y+Ok/fdsbSOPuqXW3/tMd9Zb5PYdPtfTvQ1bbHT3nHntZeU+b+3XvnnuPdvV0a37j1Km+XUoVOn2GT73Sa6j5/vd1Q898j9pYV0ViwftN0G492e4eqR511TguWmWnDxpWPRZVaMN158rgTOad3NfzpZs3TX2vhHcelpR5SZyo/+47ZyyRbad7/+Rbm9KX+HdRZffpUS0ufM4gzyf7LqPCUU7/f5J/UB85a7TP2VtEsssUQ8++yzpRL4n//8Z9l2+eWXx2uvvRa33HJLzD777K28QgBoPgJgAAAAgBbQrUObGD568tpALzVru/rr9737v/T486E1MXRUxIwdI94Z2Mj+z1+65+3RAmAm6JeHnVKqPO/92xUxetSo0hp5hm4zxi4HHRe95lsojtxtq298bFaJ3nH1RaUVdD425WNz1u1uh5xUWhI3lG2Zs/3zRScfWoLXOlkRu9XOv46dDzjma4/5qi4zdI1zb3qoVAHnXN2sKM5Lyvm3+57wx1h4yeUmuo9sS33m9feXato7rrmoVMumrIhecc314lfHnPWt+5gc2e45A+A6P/zxTpP1+Dnmni/O+duDZb2vvvBUCXcbasrfYUOHnf2XmGehxeLmy/5QZiF/3vvDsj0D5Z32Pzo232GPyVp3a5l55pnj3nvvjd/+9rdx1llnlW2PPvporLjiinHHHXeUjwBQBQJgAAAAgBYwa5c20WfY5AXAQ0eNu//Y2g+zdG4TH38x7vPtluxQwt/+w2uiQ9uI783TLp7qPSZGjJn8dX04uCZe7js2lurZtEpipn6rb7BZ/PvDSf9vMKtcDz7j4tjrqN/HR++8EW3ato15F168BK3pq/v6wY92LJc6B556Qezxu9Piw7dfL9W38yywaHTq0uUbn2+lNdeLC+58Kvp+2js++/iDUgk738JLjDdHuM5vz7ikXL4qA8nDz7kiDjjlz+V5s81xzvadc575J+t173nEabHrwcfHx++9VULkOeddIGbqOdsE77/RT3Ypl8aom6c7MSus/v2J/r1lhe6pf71rgrc19e+wTs4a3vmAo0tL7/y6Dh7YP2bsMXPZ17cF81ObXO+ZZ54ZK620UvziF7+IkSNHxscffxxrrLFGXHnllbHtttu29hIBoMkEwAAAAAAtYK5ubeLVft9+v4Ye+2hMLD1ruzj9iREl/M1ZvQes2im2WGTcIZ2ZO7eJo9cc14r2kyE1cfD9w+P1/pNfEfzEx2MEwHyjbKOcIWNjH7vECqtO1mN6zjFXuTRF5y4zxCJLr9CkfWR4usBiSzVpH1OLpvwdNpRzkudfdMlmWFHr22GHHWKxxRaLrbbaqgTAw4cPL+2hDz300Dj55JOnuWAbABoSAAMAAAC0gEVmbhf/fn/ySnQf+3hM7WVY/eejx0asNte4ttB9h9fEy33Gxjwzto0Fe7SJObu2id+v1zl+fMvQGDmZGXBWD++6bIfJexDANG7VVVeN5557LjbbbLN46qmnyrbTTjst/vvf/8a1114b3bt3b+UVAkDjCIABAAAAWsCiMze9mixbPJ/xxIiYfYY2ceubo0sgnI5fq1NstGD7EgKvt0D7Mtd3crzUpxG9owEqYPbZZ4//+7//K+2gr7766rLtrrvuipVXXjnuvvvuWGSRRVp5hQAw+QTAAAAAAC1gxTnaNct+Hv7w62HtJS+MLAFwWmSmyQ+ah42O6D2kJubq2qbJ66uqXXbZJa644opYYIEFymWmmWaKFVZYodz2/e9/v3xcfvnly3Zg2tKxY8e46qqrYrXVVouDDjooRo8eHW+++WYJgW+66abYYIMNWnuJADBZBMAAAAAALaBHp4ilZm1b2jY3t3YNctvBI2satY8PBo2Nubo2T0hdRRn+pnfffbdc0t///vfx7pPhb7aTjQ4LtOzigGax7777lhM5tt566+jfv38MGjQoNtxwwzjllFPikEMOae3lAcAkEwADAAAAtJD15msfL/cZ2ejHd2oXscuyHeO9QWPr2zx3bh+x/6qd6u/z0AeT1/65zmdDGxccTy/WWWedePDBByd6nwEDBowLhxddoEXWBDS//Lf+7LPPxsYbbxyvvvpqjB07Ng499NB4+umn48orr4zOnTu39hIB4FsJgAEAAABayI+X6BDnPdu4ALhrh4irN58henVrExnVbrhg++gztCa+N0+76NllXAnwVS+NincGNi7IbWzl8PTinHPOiRVXXHGi9+nRo0dpC/38kBZaFDBFZJv3p556Knbccce49dZby7Ybb7yxtIW+4447olevXq28QgCYOAEwAAAAQAuZoX2UWb33vDP5VbpDRkX87bVRse/KHSPj3jXn/l+75rE1EZf9Z1Rc/ELjq4vHNH9n6krJYPfnP/95/PWvf/3G+2y11VbjZgALgGGa161bt9Lm/dhjj43jjz8+ampqSov3PBHklltuiTXWWKO1lwgA30gADAAAANCCDvlup0YFwCkrfN8aMDZ2WKpDLDxT2xIKP/3JmLjulZHxbiMrf+u0bfPt92kuI0aMiE6dOn37HacSAwcOjCOOOGKi4W/KoAiolvx3naHvz372sxg6dGh89tlnpU30RRddFLvuumtrLw8AJkgADAAAANCCunWI2G7JDnHdK6Ma9fjHPhpTLs2te6cpnwBnBV22UT399NPjggsuiFVWWaVsHzZsWHTp0mWKP39jXHzxxXHYYYdFv379Jnq/DISybSxQPVtuuWU88cQTsfnmm5c536NHj45f/OIXZVZwtodv167dt+8EAFqQABgAAACghe23SsdGB8BTSo8WCID79+8fRx99dKkAPuaYY+Lmm2+OK664Iv70pz/FTTfdFAsvvPAUX8OkeuSRR2KPPfaIl19+ebztCy64YLRv3z7eeOON8bbvsssuLbg6oKUts8wyJfDdeuut48EHHyzbzjvvvPjvf/9bWkLPPPPMrbxCAPgfATAAAABAC2vXJuIPG3SOff85vLWXUm/BHm2n+HPMMssssc0228Q111xTgtXVV1+9hMLpzDPPLEFwa8v2rgcddFBcddVV423v2rVraQN98MEHl3B43XXXrb9t/vnnFwDDdCBD3n/9619x4IEHxh/+8IeyLcPglVZaKW6//fYSEgPA1EAADAAAANAKvturXSzYo02808TZvc1hhvYR88zYMkOAN9100xIApwx/27RpEz/5yU/ikEMOaZHn/ybZ0vXss8+OE044IQYPHjzebdttt12cddZZMddcc5XPv//978fOO+9cqpeT8BemH9nu+dxzz40VVlgh9tprrxg5cmRpC/2d73ynfG/LdtEA0NoEwAAAAACt5OKNZ4gNrhvS2suI787dMvMr77nnnjjggAPG25aB8Kmnntoiz/9NsqJv7733/lpb56WXXjouvPDCWHPNNb/2mJz7OWDAgJhpppli//33b6GVAlOLXXfdtVT8brbZZqVzwNChQ0t76KOOOiqOO+641l4eANM5ATAAAABAK+neMeLAVTvGWU+NbNV1rDNvyxwiyrCkpqamtIIeM2ZMDBw4MO68884ya3fZZZdtkTU09N5778V+++0Xt95663jbs81rVgJnKNy27YRbY2fw+/e//70FVglMrVZdddV47rnnSgicH/P72/HHHx8vvPBCaSPfrVu31l4iANMpATAAAABAK9puyQ7x4Adj4plPxrTK83dsG7HOfFPmENErr7xSZv1moPq9730v5plnnvjzn/8cK6+8cqkGPvTQQ0tgcvTRR8fNN99c2kG3hOHDh8dJJ50Uv//978v1Ohn2/vKXv4xTTjmlhNQA36ZXr17x6KOPlu8dV199ddmWJ5VkOHz33XfHAgss0LoLBGC6JAAGAAAAaGXnrN85tr9taHw4uOXnAW+0UPsyA7g5ZfB7xBFHlIq4Ohn+Xn755bHuuuuWz7fddtu49tpr4/nnny+XG264IX7605+W2zIUnlJh8I033hgHH3xwvP/+++Ntz/md2e55+eWXb/JzLNKjybsAmkm7FjivpHPnzqXid8UVVywntmSHg1dffTVWWmmluOWWW2KdddaZ8osAgAYEwAAAAACtrFO7iPN+0CX2uGdYfDa0ZUPgXyzXsVn399hjj5XZmCNGjCgVtd27dy+zcrMarkeP/yWjGfBmq9Qtt9yyBL5ZdZttoPv06ROnnXZauS0rhZtLhjFZoffII4+Mt33OOecsz7fTTjs123PNo+srTJcOOuigchLJNttsE4MGDYr+/fvH+uuvH2eeeWZpNw8ALUUADAAAADAV6NWtTfxl0y6xz33D460BY1vkOXdZtkN53uYyatSoOOCAA0r4m/N+//SnP5XK37fffjsWXnjhr90/A9+f/exnpW1qzgPedNNN62/LttB33HFHkyuBBw8eHEcddVScf/75MXr06PrtHTp0KIHMscceG127dm3ScwDU2WCDDeKZZ56JzTffvJx4ktXA+++/fzz11FNx2WWXRceOzXvSDQBMiAAYAAAAYCoxa5c2ccnGXeKQB4bHU72n7EzgJXu2jV+t2LxBRM77/fTTT8v13/zmNzHvvPPGsGHD4oMPPohrrrmm3D7TTDOV25Zeeulyv8MPP7y0is7b6mRYnG1UmxL+ZlVxtpzO/X/22Wfj3ZbtWC+++OJYdNFFG71/gG+yyCKLlMA329rfddddZVue6PL666+XE1tmn332Vl4hAFUnAAYAAACYinTtEHH+DzrHpf8ZFRc+P3KKPEfPLm3i7PU7N/t+cw5mnay6veCCC8o84KwIbujxxx+P++67L2adddZSfZvzfzMgzqA2Z2huuOGG0a5du0avI6vv9txzz/KxoQUXXDDOOuus2GqrrRq9b4BJ0a1btxL25vfCk046qWzLUDi/x+X2/AgAU4oAGAAAAGAqtNtyHWL52dvGiY+OiI+/aL65wPN1bxOXbjxD9OjU+H28//778d///re0Nl1sscViiSWWKNsXX3zxWG211eLJJ5+Mzz//vFxSz549Y/XVVy+VwC+88EKZCXzLLbfE7rvvXm7PELjuelPk/OBDDjkk/vKXv5QK4DpdunSJww47rFQVd+rUhBcOMBmyi8GJJ55Y5gLvsssuMXTo0Pj4449jjTXWiEsuuSR22GGH1l4iABUlAAYAAACYSq0yZ7v4+49miJtfHx1/fm5EDBzx7Y+ZmD1X6Bi7Ltsh2jays3K2dz7yyCPjn//853jbs5ItK2sXWGCBEmpkq9MMOeaee+74zne+U8KPDEIyoF111VXLY3I2b3PJIPqPf/xjmeebs4Qb2mabbeKcc84ps4gBWsO2224bSy65ZGyyySblRJjhw4fHjjvuWNrfn3766dG2bdvWXiIAFSMABgAAAJjK/Wix9rHpwu3j7rdHx1UvjYz3B01eRfCKc7SNk9fuXFo/N9aHH34YW2+9dQlxvypDjC233DJuu+22mH/++WOvvfaqvy2D3rpZvldddVX99rXXXrvRa2nowQcfLM/36quvjrc9q5KzBXXO+wVobcsss0z5XrnFFlvEo48+WradeeaZpSvCTTfdFN27d2/lFQJQJQJgAAAAgGlAp3YRWy3avlye/mRMPPbRmHim9uPLfcdO8P6zdG4Ta8/bLnZcumNp+9xUBx54YAl/s1LtoIMOKoFv3759S/XaI488EoMGDYr999+/tHZOWeV2wgknlKBjzTXXjHfeeSfeeOONcltWvq2yyipNWk8G0gcccED87W9/G297jx49SiXwPvvs06Q5wgDNLdvh50kr++67b/z5z38u27Kjwsorrxy33357fTt9AGgqATAAAADANCZbQ+elzmdDa6Lf8JoYMnJcZfDMXdrEQj2ar6Xoa6+9Fk899VS5vscee8SvfvWrcj1bPF922WWx1VZbxSuvvBLPP/98PPHEE6Xt8xlnnBH33Xdfud8//vGP8jHn72ZInPtorBEjRsRpp50Wp556agwbNqx+e1YZ54zNDKRnnXXWRu377bffjosuuqi0uj7//PNjhhlmaPQ6ASakffv28ac//am0w8/vhaNHj44333yzfH799deXNtEA0FQCYAAAAIBp3OwztCmXKSXD3TpfbancsWPHUh28++67l88ff/zxEgDn3N31118/Hn744Rg5cmRpf/qjH/2o0eFs+vvf/16eK6uJG8oZw5deemmpopsUl19+eZnBuffee9dvy3Ued9xx8etf/zrmmmsu4S8wRe26666x+OKLl5bQ2U3hiy++iM033zxOPPHEOPzww1t7eQBM4wTAAAAAABRDhgyJAQMGxOyzzx4dOnSo3143wzdllex3v/vd8R6XgW+d/v37l4/ZKjrbROelqbJ1dAbM2Tq1odlmmy1OOeWU+MUvfjHeGr9Nzh/OMDrX1qtXr7LtvPPOK8FL3WvLSuP8GuTrAJgS1lhjjfoZ6vlx7Nix8bvf/a5c/8tf/uJEFAAaTQAMAAAAMJ3LGZQZgL7wwgvl86zq3WijjeKwww4r1bDLLrts/X2z0vbHP/5xuU+dt956q/76PPPM02zrykA65/mee+65MWrUqPrt2UI1K3VzxvCMM8442ftdeOGF46c//WkJfLMVa1pyySXL9ccee6xUA7/66qvRrVu3Ui289NJLN9trAmho3nnnLbPSd9ppp7jxxhvLtvyYnRfuuuuucjsATC4BMAAAAMB0LGfpXnjhheNty5bNt912WwlCr7322tKmNCvVMqTICuDf/va3ZdZuzvTt06dPHHPMMeVxWS3bXPMr//rXv8YhhxwSn3zyyXjb11xzzbjkkktiiSWWaNL+99tvv1hvvfXikUceKfvMqrucv5mh85FHHhkrrLBCXHzxxfGHP/zha18fgObUuXPnuOGGG8p88/xelJXAL774Yqy44orle3F+/wWAySEABgAAAKiYDHD//e9/lzai7dq1iw022KAECV+VM3Xrws1FFlkkdt555xLiZhCR1cDZzjnn5N5zzz1x/PHHl1mVQ4cOLYHEAw88EHPPPXe8+eab9dW5BxxwQH1L5cbK591zzz3jiSeeGG97VsGdeeaZse222zZ637n2vOQc4q5du5agJcPru+++u1Q0//znPx/v/qNHj47u3bs3+vkAJsehhx5aOi5sv/32MWjQoDIbOOeuX3TRRWVmMABMKgEwAAAAQIXccccdpar3o48+qt+WrY0znN13333Hu2+2fU4Z5N5888317ZSzxXOGoU8++WS88847ccstt5SWydn+OVsv9+vXr4QTeUkZMh944IElLG6s3Ofhhx9eqnuz+q1OVsYdfPDBccQRR5TrjVFTUxPnnHNOeY0Zjv/sZz8rFcA5d/Oaa64pbZ732GOPct+bbropPv3009J+Naudcw4nQEvJLgrPPPNMbLzxxuUEmzwRJeec5/fjP/7xj6UFPgB8G+8WAAAAABXw+uuvl2rWxx9/fIK3n3322aUSeKmlliqfZ+BaN7s3K3sbztLNatiTTz653D/de++9JQD+7ne/G/fff38JhJ9//vlS+bvYYouVwDhD5MbIsPfPf/5zHHXUUaXiuKFcV7Zgnn/++Ru17zq5/3ytOev4888/j7XXXjvWXXfdWG655eK4444rr22rrbaK2WefvVQwv/vuu7HZZpuV15/hNkBLyo4MGQJvs8025ftWuuCCC+I///lP6cDQs2fPVl4hAFM7ATAAAADANGzw4MFx7rnnlkrVMWPGlG0ZZu61114lzMy2yVdccUXZntXBdQFwzrptuI+vWnjhhcslg9OG1cQ9evSIXXbZpVnWnvN3s93zSy+9NN72RRddtIS266+//mTt79lnny1hSc4OvvXWW0s4veSSS8btt98el112WZlZfOONN5ZtGZZnRXDOEv7JT34Su+++e8wwwwwlcF599dWb5fUBNFa2n8+Tb7IzQs5cTzmHPdv553zyDTfcsJVXCMDUTAAMAAAAMI3KCtxsF/rhhx+WzzPYPOGEE2LllVeuv8+RRx5ZKsayurYuIE4ZDmdL5eHDh8edd95ZQtOGVcDZNnnYsGHl+iyzzNKs6+7du3ccdNBBce211463PZ8/K4GzXfWktDkdMWJE7LTTTnHssceW155zgq+++upSBb3QQgvFmmuuWe6XAXDu7/e//30JtLOCeeutty6zjrP6N+du5jzkueaaK2abbbZmfa0AjZUz2U877bQS+uZc4PTBBx+U7/snnXRSHHbYYa28QgCmVgJgAAAAgGlUhw4dSovQrABO2Sq5Yfib2rRpU9/GOGdK1sltWSl83XXXlXD4d7/7XZmTW3ff66+/Pj7++ONyfb311muW9WZgnSFsBhcNK5DTjjvuWKqVsw3zpMrXv9Zaa9WHthnsdu3atcz5zeepk+HvY489Vqrn/va3v5VQZbXVViuzkvN1XnnllaWNNcDUaLvttovFF1+8tKbP78vZOj8rg5966qkyxzy7GwBAQwJgAAAAgGnY3nvvHTfddFOpAr7nnnvi4YcfLqFoypAgZ/n26dOnBKt/+tOfYqaZZoof/ehHZZ7vPvvsE3fffXcMHDiwtId+88034zvf+U68//778e9//7vsI6tqM3xoqn/961+xxx57xNtvvz3e9qWXXjouvfTS8ryTK4Pc3/zmN/HEE0/EZ599VsKRbE+9+eabl/bO+TrrvPPOO6Wlaj5m6NCh8dprr5XAOL9G3bp1a/LrA5iSsgr4ueeeK90L8mSWlN/n8nt5djmYZ555WnmFAExNBMAAAAAA04Cs+srWn9m2OWfbdunSpWzPyq+jjz66hKsp2yFnqJtzdXP7iy++WLZnQHrfffeV6zkHN1uH5vzd888/v4TIOQf41VdfLZc6WVGcsyYbtoaeXBn47rvvvqXNdEM9e/aME088saw7Q9nG+PTTT2OOOeYo4W5W8mYYkhXPxx13XHnOH/7wh/XhbobCl1xySZn3O2DAgPjtb38bCyywQKNfF0BLyxN5Hnzwwdhyyy3jrrvuKtuef/75WGGFFcpJPBkGA0ASAAMAAABMpXJmb4aaGVy+/vrr9dszBM6WxRliZlXrD37wg1hnnXVKMJCBa1a+ZgCccn7v7rvvXoKB3Hb88ceXFsk5V3KDDTYoc3IznL3oootK9XC2g85KsgxMsy1zY6tjs8o2A95s65zPVydbTGfwnJXJPXr0aPTXJquaMwTJeb85xzfnCWewnQFvvtasKM6W1jkD+Y033qivcv7Pf/5Tqo6bEmoDtJZsaZ/fy7IFdH4fT3379o211147/vCHP8Ree+3VyisEYGogAAYAAACYCmXFb7Y3zpafXzV8+PC46qqrSkXwX/7yl7ItK3833HDDErZm0JtVtTvssEMcfPDBJSROWSU2aNCgOP3006OmpqZUBC+88MKlzfMJJ5zQbGvPucL5vB999NF42zOUzXbPGcA21ayzzlrmCPfr16+E3Fn1m0H3RhttVF5vBr/ZErp3794l9M0geoYZZlAhB0zzstNBzjDPme877bRTeU/IGevZzSHbQ1922WUlKAZg+uVdAAAAAGAqk6HlNttsE5988kn5PMPO/LxXr14lzMzWn7/85S/jV7/6Vf1jsp1xbss5v2m99dYr1b5ftdRSS9VfHzFiRLOuO4PnrO595JFHxtue6z7jjDPiZz/7WaP3nW1OZ5tttph77rnrt2Ur7KyMzlA3w+111103zj777DjmmGNKa+i///3vZS1HHXVUzDnnnI1+boCp0bbbbhuLLLJI6YaQJwSlv/71r6XrQVYJZ6t9AKZPAmAAAACAqcwBBxxQH/5me+Os7s22z3VOOumkMvs3ZZXts88+W1o2Z8XwLbfcUgLkf/7zn/HEE0+Uqts62VI6K4frrL766s2y3myvfMQRR8QFF1xQnqNOx44dy2vJWcRZfdsU2Z76iiuuiD/+8Y/1615iiSXKzOK6qt5DDz20tMPOr1nelmFxtoQGqKoVV1yxdIrYYostSvVvytb4dXOBl19++VZeIQCtQQAMAAAAMBXJitUMbtPGG29c2nx+VYa/2er5wgsvLBW/Y8eOjWWXXbZUAWcQm0FwykrYDACyFei7775bZkZmMJA23XTTWG211Zq01mwjffHFF5fnzJm8Da2//vplrvBCCy3UpOeos88++5TW0Vn1nNd/8YtflJD3lVdeqb9PVrsdcsgh8eabb5bbAKYH+b0vZ8Dvsccecfnll5dtH374YTkB6Jprrilz4QGYvgiAAQAAAFpRVuvONddc9Z/fc8899dezenZC7r///jLz9v3336/flp/ngf8Mdq+99toSJL/22mslhM1ZuZdcckkJjVO2DT3xxBObtO4MqbPd8wsvvDDe9pwpfM4555T5u80t21rffPPN5XlffPHF2GqrrUqb54a22267Zn9egKldnuiTs3/zxJ599923zATONv85PiBPjDnllFPKbHgApg8CYAAAAIBW8PLLL5fWyGuttVbst99+9dvfeuut8jHbJy+66KLjPSYP5md1b7Z3TvPMM0/Z9vnnn8cDDzwQ9913X2mBnC2js3p49OjRZfZunazGzargtddeu9Hr/uyzz+K3v/1tmTOZFcB1unbtGr/73e/ioIMOqm9PPbn69etXKpqffPLJEiQfeeSRX5thueCCC5Y21wcffHCpPM720wCMs9dee8Vyyy1XWkL37du3bDv99NPj6aefLt87u3fv3sorBKAlCIABAAAAWli2S86Zvdm6ed111x3vtrpQNau3smI3g+A6GazmY/JjHuTfe++9S8B76aWXlttPOOGEEu4ussgiseuuu5b2zCnn72bb5N122y06dOjQqDVnmJyVvccff3wMHjx4vNty5u7ZZ589XiXz5Mp95n522GGH+PnPf14ql3/5y1/G3/72t2jXrt14982w+c9//nOpap5vvvka/ZwAVbTGGmuUucBbbrll+Ziyc8RKK60U9957bznBBoBqEwADtLIxNWOjJmrG29auTdtoU/sHAKpibM24S0Nt24y7AEyPxowZU4LclG07G8pAM+f0ZhD81FNPxZprrjne7RnA5mPnnXfe8nmGvXU++OCDuOCCC0pFcbYAvfXWW0s70KyUnXPOORu93pwtufvuu8cbb7wx3vacs5sh7FfX2BjZyjmroXfZZZfy+SqrrBJ33nlnmee7+OKLT/AxGRAD8HX5HvHoo4/GTjvtFDfeeGPZlh0mMgS+4YYbYsMNN2zlFQIwJQmAAVrYw589Ew/VXp7t90p8MqzPRO+74ixLxkq1l417fS/m6jJbC60QAJru9X5j48EPxsQzn4yJZz8dM9H7LjZz21hpznaxcu1lnXnbTfS+AFXRps3/zoD5akVuhqB5cD795S9/+Vq4Ovfcc4/3+YABA8b7PCtjc+ZjtofOSq+ZZpqp0et87733Yv/99//anN3cZwbRv/rVr75WnftN+8lq5q+2tG4o2z9nZXPOLc4W1vk6s9X1rLPO2uj1A0zPOnfuXN5PTj311HIiUJ48NGjQoNhkk03KHPjDDz+8tZcIwBQiAAZoAb2HfR6XvXVLPPTpM/HF6KGT/Ljn+r1SLpe+eXMsOuN88ZMFNopNeq01BVcKAI03eGTEnW+NimtfHhW9h9R8+wO+9Hr/seVy3SujYq6ubWKzRTrEdkt2iBk7fvtjgfGNHp2VpbWXsV9+/PJ6zdj/3adN24hOHXO+bO2lcZ2AmQwZzmaIuemmm0aXLl3qtzcMgL9aAfzDH/4wZptttjLXNx+bbTvXW2+9Ce4/K4lvu+22cj1bSt9+++2lcvj5558vAXBjw9/hw4fHKaecUuZG5vU6bdu2LW2kM0yYZZZZJnl/jz32WFx//fVx8803l9eelcnXXHNNzDzzzHHcccfFHHPMEauuumppaZ0VazkbeeWVVy6PzZnCP/7xj2P11Vdv1GsBmN4ddthhZS7w9ttvXwLgDIJzZnvOBb7qqqvGe38CoBoEwABT0ODRQ+OyN2+OG967t8n7emPw+3HSfy8qYfARy+xRKoMBYGpxx1uj46wnR8QXo5q2nwyOL35hZFz78sjYfqmOsfvy0in4JqNGRwwdGjF8xJeX4Tk7dvL3k0Fwpy8vXbtGdOnc/GudHuXB9euuu67M580QOAPTPfbYo8y2zQPtEwuAc+bvb3/72zjkkEPK5wcccEBcffXVscwyy4x3v6yozYquV155pczEzcB2scUWK0Hw/PPP3+i158zdDF3ff//98bZnIJuzhpdffvnJ3mfO9r322mtLJVpWDGdr56w8y8A6Q99sT5ozK5dccsnyGurC36wGznbYGQgD0HhZ9fvMM8/ExhtvXFrrpzwpJ0++ueeee8pJQwBUhwAYYArJNs8Z2E5Oxe+kyLbR+zx1cqw1+8pxxLJ7xIztZ2jW/QPA5Pj4i5o4/pER39rmeXJlkJxB8B1vjooz1u0ci83Stln3D9OqDHkHD6n9N/JFxIiRzbPPkSPHXQbXXu/TL6J9u4gZu427zOBHzUYbNmxYfPLJJ6VCN/Xt27cEtBdeeGEJgrMiuM5XW0CnbbfdtszdzaA0q7WyAjbn3WZ1cLb0fPbZZ+Piiy+Ot99+u9w/b8sQ+De/+U2j1/zqq6/GXnvtVZ63oZwdnAF2zpFsGFx/m/wa1FWV5eOyZXSuM4Ps/Dpk0J0VadmuOgPu3P8555xTPm622WalCjpDirPOOit69OjR6NcFwDg5Mz5D4KwEvuuuu8q2l156KVZYYYW444474rvf/W4rrxCA5iIABpgCzn31qmap+p2YnCW8y6NHxKkr7h+Lztj4s/sBoLFyvu9v/z28yVW/E5MVwTveMSyOXrNTbLawX1+YPo2q/TfWb0DEoEHj2jlPaaPHRPQfOO7Stm1E9xkjZplpXKUwky7D2AMPPLAEnlk1e/nll8fgwYPLnNsMU88///z6+361ArjOaaedFkOGDIkHHnggRowYUR7T8HF1fvSjH8W+++7b6LXmurLC9rzzzovR2Uf8SxlM77PPPiW4zdczOfJ1brnllmV28E033VT2m/OC119//XjkkUdK+JuypXTuvy70zbA5Q4lsA50yjOjoPz6AZtO9e/cS9mYXhnyfSXmS0tprr11Owsnv1QBM+xxBAWhmJ714Udz10cMt8lxZDfybJ0+O81b7nRAYgBaVLZ+z8rel5HN9MbKmzAaG6cUXQyL6D4gY0rwNZSbL2LERAwaOu2RF8Gw9BcGTKw+0ZwvnnJt72WWXlSA4K3ozdK2T1VgbbbTR12YwZuia4XFWy15yySUlVG1o3nnnLa2aM2htjJwV/Je//KXMhvzss8/Gu22dddYpFcaLLrpoo/ad84EXWmihMrt4hx12KEFyyrbW6667bqlgXmmllcq2ZZddtrQkzSAiLxmIZxABwJSRXRnyZKRst58n4OSs91GjRsWvf/3r0nY/36++6eQkAKYNvosDNKOWDH/rZItpITAALamlw986Zz01Mrp1bKMSmMobNDji8z7jZvxOTQZ/Me5SguBZIzo6H2OyZBC8//771wfBeckgOGX745y/mK2hd9xxx5ihQe/trJDNGbm/+MUvSmj6zjvvlO05Kzdbdk5OS+aGXnjhhbKWDJ8bWmCBBUrL5a233rqRr3Scf/zjH/Vry5nEdeF2BsMHH3xwnHzyyWXWcJ2ceZzV0g3bRgMwZeW4gWwLnScSffDBB2XbX//613jjjTfitttuK634AZg2OXIC0EwuffPmFg9/69SFwH9b52wzgQGYol7vNzbOerLlw986GTx369Amvj9fu1ZbA0wp2eq596cRQ4e19komri4I7jFjRB4Xbu+f42SZccYZY7/99ivXs9Vmna/OCP75z38+XhDcqVOnWH311culKfr06VMqfjOAzgrgOhm6HnrooeWSM4ab6gc/+EGZV5yVy8ccc0zccMMN9bdlRfB1110XN998c2lfnWaeeebSKhqAlrXiiivGc889F1tssUV9+/2sAl5++eXj7rvvLh8BmPYIgAGawbP9XonL3rqlVdeQIfDhz50T5636u1ZdBwDVNXhkTPGZv5Pi+EeGx2KzzBC9ujWu6g2mNpnB9ekX0bfft993ajJwcO33hSHj2kLPPFNrr2baUzdrN1tsZovobLc8YMCA+hnBF110Uey+++6lNWfDILixxowZU2b8Zhg7cODA8W7LEPbcc8+NeeaZp9H7f/vtt0uIPNdcc5XP66p/d9lll7j++uvj1ltvrW9VXTf3N+dMbrrppiXcBqD19OzZMx588MFyAlKOKki9e/eO73znO3HNNdfUn6wDwLRDAAzQDLL189TguX6vxPXv3RM/nX+j1l4KABV08Qsjo/eQmm+/4xSWAXRWAl+wYdMr1KC1DR8R8VHvcdW/06KcEfzp5xEDB0X0mktb6MmRgWydDEJ33nnnuOKKK8YLgnMe7gMPPFC2NyUkfeSRR0p75VdffXW87TnfN58v5/1OiqwQy7m+PXr0+NptWc2c83632mqr8bZnwH3ccceVkDvn+mb4fO2118bhhx9eWl8LfwGmDvn9OrtDrLbaarHvvvuWmcAjRoyIbbbZprTpz5OT8gQeAKYNAmCAJsrWz58M69Pay6h32Zu3xCZzr60VNADN6uMvauK6V6aehOrZT8fEA++P0QqaaVpW/H7et7VX0TwyyH7nvYg5ZouY6evZIBNQVwE8NlP0Wl27dh0vCM4WyVn9mxW0eVC+MT788MM48MAD48Ybbxxve84jzkrgPMA/KfsePHhwmUPcsWPHOOqooyYYAOdM4tdff32Cj19jjTVis802i+9///vldZ5xxhlle86dBGDqstdee8Vyyy1XWkLneIKU37dzZvwtt9xS3kMAmPoJgAGaYPDooXHDe/e29jLGk62gb3j3nthtEe15AGg+Wf3bVG3bRMzapU3M0CHi86E1MaSJefLZT42I78/nhCemPaNGR3zcO2LY8NZeSfPKVtaffFb78+iQiF5zZpvf1l7R1K2uArguAK5TFwTnpbGyYisP1udM4aFDh9Zvz7bMGTDnbbPOOusk7y+rhDPgPeKII8rn77//fgmp999//zLTOC2++OKlsvebZHD8i1/8ImabbbYSJAMw9coTd7LrQ7buz4/p/vvvj5VWWinuvPPO8j0fgKmbABigCe766KESuDbVgt3mju0W2DjWnn3lGDDqi9j+4d82aX8ZSguAAWguWf1751ujG/34jm0jfrl8x9hy0fYxc+dxMyHH1kQ8/cmYOPPJEfHOwMa1lc521KqAmdbk3NxPPxvXOrmqMgB+692IeXpFdNGp/RvVVQA3t5y1m1W/OZO3oeWXXz4uvfTSWHnllSdpPxkc180e7ty5c7zxxhvRv3//Eh5vsMEGMWzYsNh8883jwgsvLEHAEkss8Y0VwHXmnnvuxr0oAFrcvPPOG48++mjpRlHXSeKtt94q7yM33XRTbLjhhq28QgAmRgAM0AR3f/Rwkx4/3wxzxn5L/jy+O+ty9dtG14yZyCMmTYbSd370UGw699pN3hcA3PFW40t127WJOHv9zrHqXOOHtFkNvFrttks3mSF2umNofDi4cSHwgx+MFgAzTcjAt/enEYO/aO2VtIwsbn3vg4ieM0fMNumFptOVhjOAswq4qXMVM6DNNs3/+te/xtueFbcnn3xy7LbbbqUCeFI89thjseuuu8bzzz9fwt8dd9wx1lprrdIONNtGr7vuumXe79/+9rfYfvvt4/jjjy8tngcNGhTDhw8vjwFg2pffz2+44YYy/ze7QOT71ZAhQ2LjjTeOE044ob4zBABTHwEwQCP1HvZ5vDH4/SbtY5mZFx0v/G1OD3/2jAAYgGbx0PuNPzlpk4Xb14e/z306Ni54fkQMHRWx3ZIdYtPa27p1iNhrhY5x5MMjGrX/rEw+Zs1OjV4ftIShwyI+6j0uFJ3e9O0f8cXQiHnmiujQobVXM3WpqwD+8Y9/PMnB7ITkgfjjjjsuzjnnnBg16n8n7LRr1660kc4D9BOa2TsxWd119dVX1we5WeWbAXDOf9x0003r15trX2qppcq8yBdeeCEWWmihUh229NJLN/r1ADD1Oeyww8pc4DzpJ0/2qampiSOPPDIef/zxEhB36dKltZcIwFcIgAEa6aHPnmnyPj4f3r+0a36h/2tx2DK/jBnbN98cw+f6vdps+wJg+vXFqIjX+ze+V+0G84/7lWP46IhDHhgWA7/MeU98dER8p1e7MhN4tV55n8YFwOnlPmNjqVkNG2Xq9NnnEf0GtPYqWteI2n/eb78XMefsET26t/Zqph7ZMvmWW26JFVZYodH7uOqqq+KQQw6J3r17j7d9zTXXjEsuuaQ8R2PkjN4MgX/3u9+VquKDDz64hL4ZKJ933nnlOetkAHz77beXecDPPvtsaQMtAAaonk022aScCJTVv2+++WbZdscdd8Sqq64a99xzT8wzzzytvEIAGhIAAzTSG4Pea/I+nur7YrmkQ5b+RZP311C2gR406ovo3qFbs+4XgOlL32GNa81cp0/t45/qPSbeG1RTH/6mMbW7/aB2WwbAXZr4W8mLfcYIgJnqjBwZ8WHvcR+JqKkZ1wI75wPPNUdEE7sdV8Iuu+zS6Me+9NJLpaXzE088Md72nNf4+9//Pn7yk580cXXjzDHHHKWC+KKLLiqfZ7VXHvjfdtttY8EFF6y/X1YYX3bZZXH44YeXVtQAVNMiiyxSQuCsBL7rrrvKtnxPypOZ8qSm7BYBwNRBAAzQSL2H9WntJXyrYWNGCIABaJJ+TQyAT3h0wpW9ORt4/h7jWoh+NLjxFcbp86FNWyM0t379Iz6b+n9UbBU5A3nY8HEtoY2JnXz9+vUr8xYzkM05jHU6depUqnSzYneGGRrXVShnEl9//fXxj3/8o7R5zpA3WztvsMEG8eCDD8Y666wTvXr1it133720nP7LX/4y3uOzQnj99dcvVWAAVFf37t1L5W+e9HPaaaeVbX379i2z4c8+++z4zW9+08orBCAJgAEa6fn+U3+L5UGjhsQcnXu29jIA4Gs2Xqh9zNJ5XAD8z/dGN2lfAmCmFqPHjJv1O2xYa69k6pajb9/9IGLWWWovflSdJBn2XnDBBXHUUUeVELihzTffPP74xz/G/PPP3+j9Z/ibFcnzzTdf7LnnnvVtPDNYPvroo0vgm8FutobeY4894m9/+1vcd9998YMf/GC8/bz44osx55xzNnodAEwb8qSfU089tYwL2GmnnWL48OFltv0+++wTTz75ZBlDkO8ZALQeATAAAPCNeg9pWnXuhMzRtU3st0qncn3AiIjrXh7V7M8BLS0rW7PF8djm/ydTWX36jWsJPU+viPaOTnyjbPOc7Z6zxWZDCy20UKkEzqrbpsqD9aNGjYqTTjqpflsezO/cuXMJea+++urS4jkrgvOA/sknn1wO9DeUFV99+vSJCy+8sMnrAWDakN0isi30lltuGR988EHZ9te//jVefvnluPvuu2O22WZr5RUCTL/8igUAALSYbh0izl6vc/QYl//GCY8Mjy/kv0zDxtZEfPJpxKDBrb2SadPwERFvvzduLvCMJpeMp3fv3qWt8zXXXDPe9m7dupVZvAceeGB06NChUfseOXJkmd346aeflsrfrB7O2b3nnntufPjhh/Hvf/87vvjii9h6663jlFNOiWOOOaZc32qrrUqF7xprrPG1fWb76WwRDcD0ZcUVV4znnnsutthii3j00UfLtpwTvPzyy5cQOD8C0PIEwAAAwDfq2K759tW9Y8QfftAlFpm5bfn8rKdGxsMfjmm+J4AWlrNss+Xz6KZ1MZ/uZdV0fh17zBgxxxwRbdu09opaV1binnXWWXHiiSeWELahHXbYodw2++yzN3r/77//fmnjnAfk55prrhIiZ3B7xRVXxD//+c8S7uZcx7Zt28bGG28cr7zySiy55JJlPe3affObgvAXYPrVs2fPMi8+318uv/zysi1PZPrOd75T3l9++tOftvIKAaY/AmCARuravksMGT11D3jr0Na3eQCapmfnts2yn2z7/IcNusSCPcYlO394ZmRc94rSX6Zdn/eJ6Nu/tVdRLQMHRwwZNq4ldOdOrb2a1vGvf/2rHDx/++23x9u+9NJLx6WXXloOpDfVCSecUNo1b7bZZuNtX2aZZcqlzsCBA8ts4Kw4Tl+9PwA01L59+zIuYLXVVot99923nNA0YsSI2G677eKpp56K008/vZxcBEDLkAwANNKiM84fz/d/tbWXMVEztp+htZcAwDSuOSqAl+rZNs5cr3P07NImxtREnPb4iPj7G81XMjl/DweSaDkjR42rVh0xorVXUk1ZTf3u+xGz9YzoOUtrr6blvPfeeyWUveOOO8bbPssss5TK2z333LPZDprnfnI2Y1ZrPfzww2XGcLZ1zmA45/tmhXH37t3j5ptvjl/96lcx77zzNsvzAjB9yHnxyy23XGkJ3bdv37LtzDPPLG2ib7rppphppplad4EA0wkBMEAjLdp96g+Au7Tv3NpLAGAaN0uXpvViXX/+dnHs9zpHpy+D5L/8d1S8M3BsLD/7+EHG+4Nqov/wmkY9x+wzTOf9Ymkx/QdGfPZ5RE3j/lNlMnzeN+KLIRFz94po34yt6Kc2Q4cOjZNOOqkcGB/R4KyCDGmzEjhvyxC4sR555JE477zzok+fPnHEEUfE97///Tj22GNLqJwhcFZp5fYrr7yyVGYdddRRMeuss5ZWz9dee23MPffczfEyAZjO5DiBDHy33HLL8jHdf//9scIKK8S9994biy++eCuvEKD6BMAAjbTSLEvGje/d29rL+EZzdO4ZM7QTAAPQNHN1bVq4evBqnerD37Tbch3K5auOf2RE3PFW46qCl5q1wukQU4UxYyI+/iRiyNDWXsn0JWcsv/1uRK85I7p1be3VNL/rr78+Dj744Pjwww/H255tnrPdc7Z9nlR777137LbbbrHKKqvUb7vvvvtKsJzB7pAhQ2L33XcvB99z7u/5558/3uNzLvCdd94ZXbt2LVW/ANBU2UHi0UcfjZ122iluvPHGsi07Xqy88sqlEnjDDTds5RUCVJsAGKCRVpxlydZewkStNJWvD4Bpx9rztouHPhjTuAdP4eLcObu2qZ8rDFNChr4f944YM7a1VzJ9Glv7df/w44iZukfMMXvtt5QK/HN/9dVX45e//GWpzm2oV69eJazdYYcdJnufWdl7zDHHxG233Vaqd9MZZ5wRZ599dgmSMwxuU/vFO/nkk+Occ84ptz///PO1X9+x8corr8Sf/vSnr4XCANBUnTt3jhtuuCFOPfXU0nEi33fypKSNN944jjvuuNJ5AoApQwAM0Eg5X3et2VeKhz97tln2t8n9ezfLfur8dIGNmnV/AEy/vj9f+0YHwBvfMGVLJnNtMCVkm+dPP4sYMKi1V0LKv4chwyLm6RXRqWNrr6ZxBg4cGEceeWT8+c9/jjFj/vc9Nefu7r///nH00UeXCtzG+MlPflJaNl999dWl0ir94Q9/iCWWWCL+9a9/lbm+OV/4pz/9aTz55JOl9fOLL74Yt956ayyzzDKlGnmeeeZpltcJAF912GGHlbnA22+/fQwaNKj256ya8r6X70kZEHfp0qW1lwhQOY6WADTBWrOv3GwBcHPK9s+Lzjh/ay8DgIpYZ9720bXDiBgyqrVX8nXbLfn1dtLQVMNHRHzUO2LUVPjf/PQs/z7eeS9i9lkjZpm5tVcz6fIg9yWXXBK/+93vyizehtZff/246KKLYqGFFmrSc2R17/HHHx8777xzbLbZZmVucIa/b7/9dqn6zYPrPXv2jA022CAOPfTQ0nZzn332iR133LFJzwsAk2qTTTaJZ555plT/vvnmm2Vbnpy06qqrljEE88/vOBZAcxIAAzTBpnOvHZe+eXN8Orxvay9lPLst8qPWXgIAFTJjx4jtl+oQl7wwdaVhmy7cPnp1q0A/WKYqffrVXqauH+34is/6RAweEjHPXBHtpvIR4HmgO2fzvvDCC+Ntz8A32zNvscUWjd73Rx99VCp+P//881IBnAfQN9poo9JGOlttpoceeiiWXXbZEv6mvG8GvyNHjowZZpih8S8MABphkUUWKe+NWQl81113lW0vvfRSrLDCCmWMwVprrdXKKwSoDgEwQBPtv+TP4/DnzmntZdRbZMb5SjANAM1p+yU7xrUvj5qqqoC3V/1LM8rq0qz6zepfpn7DhkW8/W5Er7kiuk6FOeZnn30WhxxySFx55ZWlArhOhq5ZCXzwwQdHp06dGr3/PHiebaOzgjcrpkZ9Wa6ez7neeuuVA+vLL798uZ4zf7MF9GuvvRZLLrlk/OhHThYFoPV07969VP4efvjhcdppp5VtAwYMKO9Z+X6VJyoB0HQCYIAmWnv2lWOFmZeI5/u/2tpLKfZbQhs3AJpfVgEftFqnOP6RqSMd++XyHWKxWdq29jKoiIGDIj75bNzcX6YdY8ZGfPBRxEw9IuacvbVXM87o0aPL7N3jjjuuzDhsKKt0zzzzzGaZtXvsscfGGWecEd/97nfH2z7zzDPHgQceWOYq/v3vf4/55puvVAnfd999seuuu37t/gDQGnJ0QXarWHnllcvs+uHDh5f30H333TeeeuqpMjqhY8eOrb1MgGmaAHgqNqb2z+i6S83oCXw+Nmoa/Bk73vWxzbaONl/+aVt/reHnbaNd7aV9m/a1/zG1G3f58nq78nn7cj+oulNXOiC2eXD/GDJ6WKuuY9v5N4yVZlmyVdcAQHVttnD7eOD90fHQB2NadR2Lzty2VCRDU2WA2PuTiC+GtPZKaIoBAyOGDhvXEro1jxU/+OCDsfvuu8cbb7wx3vacxZsHstdcc81me66s5s12mROyww47xE033RR77bVXjBkzpjz30ksv3WzPDQDNZdttty1tobfccsv44IMPyra//vWv8fLLL8fdd98ds802WyuvEGDaJQBuBaNidO2l9v9rMswdPV6oO+76uI9Ti/+FyhO904Svx7gAuf2XYXDDgPh/19tHxy8jY5hWzdh+hjh1xQNin6dObrU1ZOvn/VX/AjCFHbNm59jr3mHxRv/mO+FwcnTtEHHGup1LRTI0xdChER99EjFm6vnViyYYOTLi7fci5pgtYuaZWva5P/zww1KxdMstt4y3faaZZiqVwL/+9a+jXTMPK15ggQXiiSeeiHXWWad+23PPPVfC3vPPPz8uu+yyuP322+N73/tesz4vADS3FVdcsbyHbbHFFvHoo4+WbTnqIEcZ5HtZVgkDMPkEwFNAVuKOqP0zsmZUjBwX9Zbro768Pr3J8Hhc6D26bkPDG+tlpXCHL/90bNP+y4+1l9qPncIRPqZ+WXn7u2V2j5NfvLjFnzvD3/NWO6LFnxeA6U8GrxnA7nD70BafB5zh74Ubdole3XSYofGyzfNnfSL6D2jtlTAlfPp5xOAvIubuFdFuCneJz3aV2b7y9NNPj2HD/tcJKNta/uIXvyi3zTrrrFPkuXfZZZc46aSTYpVVVomuXbuWbRkIzznnnOX6LLPMEjvvvPMUeW4AaG49e/YsnTT22GOPuPzyy8u23r17xxprrBFXXnll/PSnP23lFQJMewTATZStlofFiBheU3up/TisZngJfZl844LzkeVSHwx/+TGriDtHp+jSplPtx87lo1CYqdGmc69dPrZkCFwX/mYVMgC0hAxgM4g97pERLVYJXBf+mvtLU4yo/VXjw48jRvmVrdKyHfTb70bMPWfEDFPoR+Sbb765zNp97733xtueVUqXXnppqVpqrP79+8dZZ50VDz/8cMw+++xxwAEHxOqrrz7efbbffvt4/PHHY+utty4HxbPt9AsvvBBXXXVVo58XAFpT+/btSweL1VZbrXTWGFX7A9vIkSNju+22Kyc5/f73v4+2bf0uADCpBMCT4X9h7/DyMcPe6bGitzVkFfGwGF6+5hED64PhLtEpOjcIhTMkhtaWIfBcXWaLw547e4rPBN641/divyV/LvwFoMVlEHvBhl3i4H8Pi+c+nbIhcM78PWbNTsJfmqRv/4jP+7T2Kmgp2dr7/Y/GtYOeoxnHB2bQmnN+s0qpoTnmmKNU/GbVbVYAT9oax8TVV18dHTp0KIFuGjRoUPz4xz8ul2uuuSaeffbZMss32zo3bOecz3HuuefGv/71r/jPf/5TDpZnu+lOnfxODMC0Ld/3lltuudISum/fvmXb2WefXU50yhn3OWIBgG8nAP4G/wscVfZOzcYF8SNqrw0qofC4SuGO0blN5xIOd2nTWaUwrSLbQd+0zjlx0n8vjIc/e7bZ99+1fZc4ctk9Y+3ZzUEBoPVkO+isyr3ohZFx7cujpkhL6O2W7BC7L9/RzF8abfToiI961/7uMLy1V0JryFbfOe85W0J37ND4/QwePDiOOeaY+OMf/1j739T/TgTPaqV99tmnhK8zzjjjJO/v6aefLvtbaKGF4ogj/jfKJQ9sZxXx3nvvXT7v1atXCYoPP/zweOCBB8abJZwh8AYbbFAuAFAl2fo55wJvueWW5WO6//77Y4UVVoh77703Fl988VZeIcDUTwD8pYx3h5XK3nFVpqUNMdOcccH9uFC4/7gNZbZwXYVwlxIMd44O/tOnBWRV7qkrHhDP9nslzn31qnhz8PvNsl9VvwBMbfZYvmNstnCHuPiFkXHnW83TIWfFOdrGQauq+qVpBg2O+OSziLEt06mcqVS2/n7nvXGVwDP1mLzH1tTUxBVXXBGHHXZYfPrpp+Pdts4668TFF18ciy666CTvr0+fPnHKKaeUFtKHHnpoqXJqKNs/fzVIzgqorHx65plnSqUvAEwP5p133nj00Udjp512ihtvvLFsy9ELeaLUddddF5tttlkrrxBg6jbdpmAZ8Q6uGRJDaobG0HAqeJXlbOGhMSyG1gyrbx3drvZP1+gS3drMUHvpWvsPod3EdwJNkNXAV6xxUgmCb3jvnkZVBM/RuWdpLf2TBTYS/AIwVcq5wNmmOat1r3tlVNz+5uRXBOec3+/P1z42W7h9rDynn89ovAx8e38aMfiL1l4JU4uamnEnA+R/E3PPFTEpIwSz1eRuu+1WgteG5p9//jjzzDNjm222maw1ZMXSscceW/Z54oknxuWXX16uZwvoOt/5znfi4IMPLuFwx47jWh9kpW8eBB84cOBkPR8ATOs6d+4cN9xwQxmzkB0zxtb+kDdkyJByclS+px599NGtvUSAqdZ0EwDn/N4vYmh8UZOXITE6xrT2kmhFY2r/DKr9L2JQzRclFM5G0TO26VrC4C7mCDOFZBCcl8Gjh8Zz/V6JNwa9V0Lh3sM+j0+H9x3vvivMvETM1WXWWLT7/OUxi844fyutGgAmTwbBB67asVxe7zc2HvhgdPk4eGTN12YF52zfbh2jhL0rz9FO6EuzGDos4uNPxrV+hq8aMjTirXfHhcAzdJnwfbJKN1suX3bZZeVAc508CJ3BbFYD5/XJteSSS8att94as88+e6kszmqmDIH32GOP+vusueaaJWA+4YQTyiX997//jddee031LwDTrXzvzbnA22+/fQwaNKi8j+YohaeeeqoExF26fMObOsB0rNIB8OjaP4Nqhoyr9I2hrb0cpmJZET68ZkR8XtMv2kXbEgSXQDi6lhbS0Jyygjdn9+Zlt9ZeDABMQdm+ebFZDO+l5XzWJ6Jf/9ZeBVO7MWMi3v8wYpaZI2afteH2MfGnP/2pVBMNGDBgvMdsvfXWpQ1zhrONNd9889Vfz6renBv885//PLbaaqsSCtc599xzY5dddinVTT179oy33norzjvvvOjRYzL7VwNAhWyyySalK8fGG28cb775Ztl2xx13xKqrrhp33nlnk96jAaqocgFwXWvnwTVflLm+MLnGxNgYWDO4XNrU/sma4BlLINxNq2gAAJgKjaz91e+j3uNmvcKkypMFsiJ4nrkisgtzVt8+8cQT491nkUUWiQsuuCDWX3/9Zn/+5ZdfvhzMPvnkk+Occ86p3z7HHHOUA9pPP/10qUDOWYd17aABYHqW78sZAmcl8F133VW2vfTSS7HCCivEbbfdFmuttVYrrxBg6lGJAHhYjIiBNYNKO1+tnWlONbV/6lqH9675PLpE5+jRplt0bzOjMBgAAKYC/QeMq/zNGa8wuUaMiHj7vYgP3ntqvPB3hhlmKC2YDzzwwCn6/Iccckist956pYVlVjDVadeuXZkHDACMr3v37uVEqRzXcNppp5Vt2bkj309///vfx3777dfKKwSYOkyzAfCoGF0qNAfUDIqRtZ9BSxgWw2NYzfD4pKZPqQyeqU33UhmsTTQAALSs0WMiPu49buYvNEWePDDPfKvGRZfcFQfuv1386EdbxRlnnDFeW+YpZZZZZikhc84xvP3220vwCwBMXI5SOPXUU0uXjJ122imGDx8eo0ePjv333z8ee+yxuPLKK3XPAKZ701QAPDZqYtCXoe/QGN7ay2E6NySGxZCaYdGm5rPo3qZbCYMzFAYAAKasL4ZEfPxJ7e+IY1t7JVTJWmtvHE892zfmn7d9dOnccs+7ww47xC233BL/+c9/YsUVV2y5JwaAady2225b2kJvueWW8cEHH5Rt119/fZkRfPfdd8dss83WyisEaD3TRACcYe+A0uJ5cAmBYWqSbaLrZgZ3qP0nlUHwzLWX9tPGPy8AAJhmjK39dfDTzyIGDmrtlVBd7eO9DyJmnaX20rNlnjGrfm+66aZo27ZtyzwhAFRInjz13HPPxRZbbBGPPvpo2ZZzgpdffvnSXSOrhAGmR1NtQjWm9k//mkFaPDNNydbkn9f0K5duMUMJg7M6GAAAaJrhwyM+7B0xenRrr4TpQZ9+4yrN5+4V0aEFjpwIfwGg8Xr27BkPPvhg7LHHHnH55ZeXbb1794411lijtIP+6U9/2sorBGh5U10AnMFv35oB0a/2otqXadkXMTS+qBkaHWs6xGxtZokebWZs7SUBwDSptX8ibNPKzw9EfN43om+/1l4F05vhIyLefjei15wRMzqvFwCmau3bt4/LLrssVltttdh3331j1KhRMXLkyNhuu+3i8ccfj9///vel6wbTqkk5MuC3d2hoqgmABb9UVVawf1TzafSp6V+CYBXBMG164KPWXgHQWr47Z0RnxwmgVYwaNa7qd8SI1l4J06uamoiPav8b7D5jxJxzRLR1XBEApmp77bVXLLfccqUldN++fcu2c845p7SFvu2222KmmWZq3QVWVU12cR017mPN6NrLmNrPv/yYn0fdxwltG9tKi24f0abDBC4Zm33l8/wYDgwwbWn1AHhM7T/uDMYy+K0R/FJhI2JkfFjzSakInrXNzKU9NAAAMGEDBkZ8+vm4AA5a26DBEUOHRcwzV0Tnzq29GgBgYrL1c84F3nLLLcvH9PDDD8cKK6wQ9957byy++OKtvMJpwdjaH8SH134YWfux9lIf7jYMeb+8HtPqjJbRX76OYZP+kDYdGwTDHb/5EsZ70PpaLQAeXSp+M/gdKPhlupIVwR/XfBafl4pgQTAAADQ0ZmzEx70jhgxt7ZXA+HL+9LsfRMzas/YyS2uvBgCYmHnnnTceffTR2GmnneLGG28s2957771YeeWV47rrrovNNtuslVfY2mp/6B47bFy4W4Le4eM+1owYd32aDXWnsJq6QPzbtPt6KNy27nqn2utdolQZwxTU4gHw6No/WfHbv2aQ4Jfp2qivBME92nQ3pQAAgOlahr4ffxIxZkxrrwS+WZ++tf+tDomYe66cN9jaqwEAvknnzp3jhhtuiFNPPTWOOOKIGDt2bO17+JDSHvroo4+OY489trWXOAXVBbwjGgS8dddzvoqAd8oaM66yeKLVxe3HBcF5aTPDl9drP7bJdjOSApquxX5Vyag32zx/VtNX8AsN1AXBeWJEr7ZzxAyhn9jUbOjQofHJJ59E9+7do2fPntGmzZR9M+7fv3/069cvZptttvKcADC9yZZtgwYNiu9973vRrt20N3Ppo48+iuHDh3sv/xbZ5jnbPWfbZ5gWDBse8fZ7Eb3mjOjWtbVXAwBMzGGHHVbmAm+//fbld4ua2h8+jzvuuDIXOKuBu3atwJt5acc8JGLs0NpLg4+tNl+Xbze69q9n8LjLV7Xp0iAQ/vJj2xlbfolM01okAB4eI+KjsZ+WGajAhGVr6HfHfhgzt+kec7SZNdqaE9AsXnzxxdhhhx3KD3bzzTdf3HbbbdG27fhf2zzz74c//GEMHjw4unTpEvfcc0/MPPPM9bdnAPvXv/61tIvJg7h1OnXqVB73i1/8oswQaSiD4u9+97vl+rrrrhvnnnvuJK/5jTfeiL/85S9x++23lzXVycD5Rz/6Uey8884x99xzT86XYYIuueSS+MMf/vCNt2ernDvvvLPJzwNA4+UBipdeeilmnHHGeOSRR1p7OS3upptuioMPPrhc33HHHeOEE06Y4s+ZPxfke3eGtrPPPnvcd99933jC16hRo8p98yBSvk//85//LCH1mDFjyvvspZdeGp9//nn9/VdcccU4/PDDY9VVV53ir2NaMnxExEe98+vZ2iuByTN2bMSHH0f06B4x5+wRU/jcUACgCTbZZJMS+G688cbx5ptvlm133HFHaQmdc4Hnn3/+Vl7hZMiq0rFfRIz5YtzHEvSq6K2U/Dsek5d+DTa2rf1ft9pL1y8/dhsXDKsW5htM0QB4bNSUit+s/AUmTbZHH1wzJOZqO3vMGBU4+6yVLbPMMuUHuX//+9/lAHqGu/kDX0NXX311fPzxx+X6z372s/HC36w62nvvvePTTz/92r5HjBhRQtr8YXG//faLfffdt/4AcQbOdeHtsGETa/Uxvjzr8JhjjomRI79+wkzfvn3j4osvLvc566yzYoMNNpjk/U7Iq6++Ol7A/FVffPFFk/YPQNPl9+KJfa+ugrvvvjs+++yzWHDBBWPttdce77a33nprgtenpDz7PwPau+66q3zt8yDRKqusMsH7PvTQQ/Unh22zzTb1FcqHHnpoCa+/Kn+uyFD/yiuvjDXWWGPKvYhpSN9+EZ/3be1VQNMMHBQxdNi4ltCdO7X2agCAb7LIIouUn+/zZ/L8eT+99tprpbAji0bWWmutrz3m+eefLx+/WvzRYr4W9ubxOvNSpk/Z1nvQuEtD9WHwjBHtuo+rGIaYggHwsBgeH479JEY58wQm2+jaN/EPxvaO7m26Ra82s6sGbqKsHMoAOJ1//vnjBcAZtGaFTurWrVvsueee9be98847pdooq3lTVu1stdVWpTI2D8hnJdbNN99cqn/OOeecaN++ffz6179u9DrzB82sCqqz6aablqqiWWaZpRwYzwPkDz74YDkYneu89tprY7XVVmv087399tv1r2ujjTb62u09evRo9L4BYFKdfvrp8e6778Zmm232tQA4u2xkwJrvfXWVwC0hO27UHRC69dZbvzEAztsaPiY99dRT9eHvPPPME0cddVT52eFf//pXnHnmmaU6OGeQ5fv+9GxU7a+JH/ce10YXqiAr2N99P2K2WSN6zvzt9wcAWkeOZclijjwGd9ppp5VtAwYMKMfgfv/738f+++9ff9/s0LfrrruW63ls8fvf//4UXl3tD8ljBo5rCTxmsLCXSVN/YsAnX27oMC4Izkvb7uPCYVXC06UpEgBn1W/OMwWaZlDNFzG0ZljM3XbO6BrO3GmspZZaqoS+eSD35ZdfLj+w5Q91Kds617Vm/OUvfzle9W/+wFcX/ub1rPJtaPPNNy8BcV4GDhwYZ599dqy33nqx5JJLTvYacw1HHHFEud6xY8dS6fvVg+A//elP429/+1v89re/jbFjx5Y1PfDAA+X+jZEBd93rqPthFgBaWu/evb/xtllnnXWyxig0l3XWWae0dM7uG/nzQ3bnyBO9GsoOH9nyOWUlwbLLLluuZ9Bb54wzzqgfCZE/Hzz66KPx2GOPla4kGQRPizONm0NWS376WcTYmtZeCTS/z/tEfDFkXDVw++nznzgATPWyg1+elJldA3faaacy/iV/Pj/ggAPi8ccfLx178mf3hsfL/v73vzd/AFwzPGLMlxWdGfzWTHoXQfhmo2r/e+o77lInq4PbfhkKt5updoMfVKcHzRoAj6r98+HYT0v1L9A8shr4vbEfxSxtZoo52vSMNs7WaZSDDjqotH/O4PS8884rAXD+YHfhhReW27PaNauM6jz77LPxn//8p1zPIPar4W+dbDF97LHHlh8Qc3/ZTvrEE0+c7PVlEF3XcjmD3a+Gv3V+/OMfx9NPPx3XX399OWD+j3/8IxZffPEyozitvvrqZZZJQxn0Xn755eV6trTMwDfPbMxLygPW+YNutoTOH4AXWGAB1b8AU7GsOs22ZTmf9je/+U383//9X+kK8f7775fv3z/4wQ9ihx12+FpgmeqqU7Odco4yyDlX2XFiQp0gUlbm5r5ffPHF8j4111xzlfvmYzp06FB/vxdeeKG+6jXfc/v06VM6bOR7S6dOnWLppZeOn//85+U9pk6eOJX3y3WkfI6jjz66XM8Adv311x/vPSxf11dbsuXXId9Dc4ZXvocttthi5YSp5ZZbrklfs/y4xRZblOfu169fOfjz1ffmDH/rxjxk++c6ef173/teuf7VyuHRo8d1R8quI9Nj+JvzUj/+ZFw4BlWW3xrefndcCNx1htZeDQDwTbbddttyMmf+7P/hhx+WbXnMLX+Pyd+FGsqufE2Ws3rHDvxf6Fvz9RFwMEVkVXleRo8bYRRtan9Ibddj3KVt7aVNh4k/nmlSswXAg+KL+Hjsp2XuL9D8cpb2kJqhMV/bXtFhyo7vrqSFFlqotGbMCtoMd/Nsvk8++SQ++OCDcvtee+0VM844Y/3969o+pp133nmi+85A9fjjj4/+/fuXkLkxAXDd87Vt27ZUFE9Mrid/GE35fFl1nAfds1o5X9dXA+B8zXUBcd3B67r2zylD5DwonyFwyoPe2er6uOOOixlmcMQKYGqTYeQNN9xQgsv8Pn3CCSeMd3uOKMj71J3klPIEqKxiveqqq8a773//+9/S/iwD1z//+c/Rpcv/Oo7kcxx55JFl1EGdPDnq3nvvLWfEX3TRRaVCN+X7St17Ta7piiuuqH9fSU888UQ5SSpbqmWr55TvXXXzc1MeYKk7yJJt2TIA/vTTT+v3m+FzXQBcU1NT3qfyeRrKk6Suueaa+NWvflU6ZjTla7b11lvXh88ZIH81AK5r/5zB85Zbblm/fdFFFy2XhjLozq99BvCpYWA8vcimKh99EjFGBzumE3nCwwe13+Jm6hExx2z5vaK1VwQATEiORnvuuefKz/T5O0HKE1y/KmcBZzHFTDPNNBl7z5bO/Ws/9Bv30bhMphY1tb+gjc7Llx252nQaVxlcLrOECuFqaJYU6ZOaPiWcAqasETEy3h77fszddo7oFl1beznTnKyszYO1eSD7j3/8YzkYm/Lg9VdD3rpgOK2wwgoT3W9W8GQl8MMPP1xaRda1jZ4cdc+38MILjxdET8gSSyxRqqmyYiorl/JAdlZj5TziN954o1waHniuC5dzlnBdq5qGAXC2m04ZPmdAkNVJGRrnvrM6KrcDMPXJ8QMnn3xyaS2c399zXvwtt9xSvpfnyT3ZijhD1HT++efXh7/5PpMhbNeuXUv4mydE5dnsGYrm/lIGtocddlgJWnM8QlbVzjbbbKVyNkcp5AGSfffdt4StX5Uhar53ZLeNOeecs5x49dprr5X3rawOzve6XPMaa6xRAt6HHnqoPC6rc7NSOOV9JuZPf/pTffibr+eHP/xh6cSRJ0Zl8Jy3zz333PGzn/2s0V+z7JCR76f5vpqhdz4u33/r9lO37uy+keH0hOQ+99xzz/rP8+uSJ6Tl13Z68unnEf0HtPYqoHUMGBgxpPbXg3l6RXRq3OQWAGAKy2ODeVLo3nvvHRdccME33i9HsWXRxESVYC0D337jqnxhWlAzova/20/HXbIDaakO7jnu0sYPsdOqJgXAY2v/fDD2kxgSkx92AI0zpvbf3ftje8ecbWYtbaGZdHkgeLvttiuVRHVn9KVf//rX41U8pQxy62QV0rdp2DI5W0U2nCX8bTKQHjRo0CQ/V1Ya5cHuPJCez5XyYHIGwOnOO+8sYXfKGYN11VR5JmNda8uGAfBKK60UJ510UmklndsPPfTQ0ibzySefLPNNct8A07OpeU5pzpfNKtW6dswZWuZogpRBbYaZ2bo5q3tTth7O0He++eYrn2elbJ5ElEFoVshm1Wy+h5111lkl/M3753tB3f1zXEKGl9mJImfZZkVrjhdoKNeS1b512zNczfeZyy67LEaOHFnC6BzHcPrpp5f3v+WXX77cb7XVVisnaH2bfD0Z8KZ838wTnfI9vu71ZGeOfI8855xzSku3hq2qJ/VrViffA0877bQYMmRI3H///fVdNu6+++76yujJeZ/MADkv+diOHav/S/SIkREf9Y7av/fWXgm0rvx28e77EbPPGjHzTK29GgDgm8wxxxwTvX3CAbAqX6qmpva/5QHjLvHWuHbR7WcZVxnc9tuPXTP1aHQAPLr2z3tjPy4ViUDLy8r7kbX/DjMIZtLts88+ZVZgXVvKrNj5anVQahjg5oHmb2vvMnjw4Ak+dlLkAeg8wJ7PUzcHeGLygHzd89U9V131Uc4FzgP7dQFwhsF1Gh6gXnDBBcvrzjA5q7Hq9pMVVxkSZIvNPHie+xIAA0y9srq0YcCZ4WddmFk3wyqD2rpZtdtvv319mJvy+3+GmXXdK7IqON9j8iSglBWwOZs3L3WyUrdO7vurAXA+R8NtWfWaoXG+p2TQnFW2TZHPWbfefC+rC3/r1vvjH/+4BNCff/55aVm98sorj/f4Sfma1cmTpzKozvfe7CJSFwDXtX/OE8i+aX5yylA7g/XsOpIBcnbYyLXlzOLrrruu8V+EaUDf/hGf92ntVcDUo/bbSKmGz2rgXnPm98bWXhEA0FCe+JpjZiamfg5wzvId82Xgq8qXqsuq9lF5yd+X2/+vTXT7PJ5sdvDUrFEB8KgYHe+O/bB8BFpPtl4fXTM65mk7Z2svZZqR7SvzYHFWIaWc/TuhCpx55523/noePP7q3L+G8qBwVtqmrATOg+dZKTQ58vleeeWVeOutt8pB7YnN3s2DxhnOprqD3nlwPc9AzPA295GtNrOity4AXmyxxUqb6jpZEZWXCcmvUd0B/7rqYQCmTgsssMB4n2e7/7qW/nXvFXlyUJ1FFlnka/vIx+SlznvvvVd/PVs9Z6eMb1I3TqGhrKj9qgxcl1pqqRIA50lYkz87638avp6FFlroa7c3bB/d8L51JuVrVidPrsqTrLJzSJ7tn+F4hunZIjttuOGG5X3/m+RrrAvDMzzO1nLZUi4fn0F27rtqRtX+ivhx7Zd92PBvvy9Mj76o/TXh7Xdrf46fK08iae3VAAApj3/tuuuu33q/Mgf40ydjphkzFxk75RcGU52seO8z7jKqU0T72Wsvc0S06dzaC2MCJjsAHhmj4r2xH1Um/P2892fx+P2PxaLLLBZLLL/kZD8+DxTdee3tMctsPWPNH35vCqxwnFeffzneeOmNWH39NWLWOWebYs/z79vvjxHDh8dG224yxZ6jNXz60SfxynMvx1obr1PmtVbJoPgiPhz7iRB4MjSsFGp4vaE8oJvtIVNW6kwsAM65gHUHwHMGYWPk82UAnPN3s63mxH7ozPXUafh822yzTX2Lzwx+s81mzvFNX63izefK9pMZNE8oDKirFOvc2Zs3wNSsrrX/hOQJSim7TNTJ4PXbNByLsOaaa050xlXDmfN1Go5RaKh///711yd2otO3+bbX03Bbjkz4qkn5mjWU76EZAGc4nDN9c/5v3f0m1CXjyCOPLO+xefLVbrvtNt5tORe5bqbY66+/XrkAeOCg2p+7P5u626bD1GD0mIj3PozoOUvEbD1bezUAQP4OMSm/K6Xnn3sivr/2ilN2QTAtyLnBoz4Yd8nW0CUMzuyqWvnLtGyyAuAMf98Z+2GMqf0zpf3x6LPj6vP+GhfedVks/90VJnifZ//v6fjVFnvEDr/5eexz/AGNep7XXng1Dtvp4Njzd79qVAA8auSo8vgV11x5igbAd11/Z1x6+kVxyb1/maIB8JmHnhZ9Pvm8cgHwXpv+Ml7/72tx6FlHxE777dLay2l2QuDmly0b86D2G2+8UQ72Zhg8oVA2Z+YeffTR9Z9PqJ30pMh2lRne5sHlM844I5ZbbrmvtaxMGTZfeeWV5XpWLNW1okxZ8ZSPy4rlugA4ZVXT1ltvPd5+cs1PP/10mUP40EMPjdfOM8PhuhnBefAagGlbww4QOS939913LyMA6hx//PGle0TKdsdzzjln6WiRQWeGufke0vAEuv/+97/xwQcflOs5UuCrctRCvmc27LCR7035uJTvr3W3NdzvyEkcFLv00kvXX8/3xXw9dcaMGVO2pXz/W2KJJSZpnxOT77VHHXVUOTnqtttuK1+XlO+dGZB/1f/93/+VKuqePXuWdtgNw+533nmn/nrDIHtaN2ZsRO9PxlU2ApOub7+IbBw0d6+IDo0e0AUANNUKK6wQt9xyS5xzzjn/2/j/7J0HfBTVE8d/d5deSEIPCR2kS5cuTQSkS1VEmqKCNEUBUcofQREQERCR3nsHUamC9C4d6b2XQHpy99+Zvb3cJXchhIRLYL58lrtse7Nv9/btvt+bGVO0MkWxMHz4yBme1aRhVRF/BcEeFAo9iqZzgEtmZcou+YLTAEl+xYgxh31+HuIvEREeiUcPHyE2xrGncUxMLK9D6wpCYuQplBfnTpxFzny5bOZHR0Xh7q178M/kDw/P9O3pSCLwZeN15NQHOtuUFwLqGB87dix7PVGHNHWOU54P6gQPDg7mEM/bt2/HnDlzLHkIKacgPTDGh5Y7CqWcLVs29rQiT2TqXCavIepgbtOmDVq1asWeQiT0UshMytG4evVqi9fRqFGjbLy0CPJEok52EnDnzZvH86pWrWoj8BKNGzdmAZgE5/fffx8DBgxgsff48eMsDmtlkB2CIAhC+obu7zSwifL6Hj58mPPEd+3alUMXU1uhRbwoUqQIt0tE69at8dtvv+HkyZPo06cPT5QigMIgU+54ylmfI0cO/js+JCZT+/Hpp5+ymExhpKnNosg5RNu2bS3rkg0ZMmRASEgIt6szZszgNouEW3vhnQlKcVCuXDlux/bv34/evXujU6dOLP7+8ssvnAaBoCgZ2vE8CyTgUqQOyglG4q52HPSMoLeTxJMEY/LyJfH8k08+wZdffsl2HDhwgAd5ESR8V6tW7ZltSwvQY9DVGyS+O9sS5xAWForTp/7F9euXlTqIQfbAnChevBw8PBLG9r169SImTRyG1yrUQMNGyRs0mBo8uH9XuTfsRuUqdWzyYxOhjx8pz4cHcP/+HVSsVFv5vfqzh/uO7etR4tXyynNq6g1OPnf2JC5e/E95vq6EgIyZU60cZxMRqYaEprzAvi/OuBBBEARBSHfQ833TxrWBGOXhNuY2JMSzICQH5XcTc0uddF6Aa3bVMzh52WiFZyRJtW5U/l00XkPMcxJ/BSGlGbNwHCKVN2t3D3eb+TvWb2cvclr+Zot6TrIu5XiEUNw23UMWXcYnryw8EeoInzx5Mrp3784d0yQA02QPElGpc9we1KFNQq49pkyZgtq1a/N36hCncqhzmEJBU6e8JuJaQ1673377rd19krBLy2h7ylNIUGjo+FDHPHmB7dq1izvKyf74fPDBB6hYsaJduwVBEIT0xejRo3kQE6UsIC9WmqwhIZa8fzVIVKX2i3Lck/BJkzXUFtE+44tFBOW5JdE3fvhjgjxm27VrZzOvSZMmmD17Ng+uGjJkCM/r378/unTpkujx0KAnElnt2UeDtag9TCmoLCpDE3+1efagAWEUPYQGY1GUDZri89lnnyUYnJXeoLFiN28DDx462xLnQMLozz8PxPKl05VnLttK8Pb2xbvvdUO3Twcpv5W4QaZ3797E4kWTOQx5WhKAe/ZogT27t6DrpwPRvccQy/x//92Djz58iwViYumKAyhatDR++3U4xo8bjHLlX8fsufafjVOCVStnY5JS1vSZG1GxUq1UKyctQL+nq9cBvwxA9qw0GNXZFgmCIAjCy0SMKlZF31Aa5TBnGyMILw70eyKP4KjzgCET4BoI6P2cbdVLxRMFYPIBI6/CSCQtJJsgpFXii7/EnZt3nGBJ6kICsKvy0/bXSYiFlIBy/5JQSkIwhYIhgdYa8t6hMJeOBN6nhTyFyEuLhOENGzawkKtB+XgbNmzIoS4dhWYOCAhArVq1uOOZoPCS9vISU4c9eXyRl/OCBQts8pyQN3K3bt04bKUgCILwYkCC6Jo1a1gUpRDJ5MGnQXloBw0axJ61GtTmUChnEoWXLFnCHr8apUuX5mgR9qJeEOQhTOGeFy1aZGnHSGCmNAk0WCq+1yxFvyDvYmpnKbR0TCIRgDRy5crFxzN06FA+nliz+ykJ040aNeLIFv7+/kmtnidCwjV58d68eZP/Llq0qE19WUPl0rF///33bGNERIRlWc6cOXlgWcuWLVPMNmdAHoskVlldRi8V165dwkcf1MeZM8dRrlw1NH27A3LnKYioqEic+e8YZs4Yg8mTvsehgzsxZdpflpDnWoQVnS6h57gzyZkrP/bu+Vv5XRWwmT9h3GAWf/t9NQaly1RGvnxqSPXgnPk4Wg4dc2oSV18vjxpKebTDwpU6DqT7mbOtEQRBEIQXHKPyjhNzXbx9BSHVUZ7rY++ok85DFYJdKFqXeAWnNk+s4TumewhF+POwJUXYvGojtq//Bz2G9saDO/cxc8w0nDh0HAYXF5SrVh7te3eEf6aAJO1r54btWDV7Bc6dOgeDQY9XShRGm0/eTTRX8MYV67F67kpcv3QNfpn8UbZqObT8sA0yZrHvkXnt4lUs+m0Bjuz9F49DHiModxAavNMItZvWSfIx/7v7EJZOW4KzJ9RcBPmLFECrLm1QrGxxu+vfuHIDiybNx797DuPRgxAE5QlGo/eaomajpI+q1uq5+/964di+I3wMdCxZArOgfuuGaPhuY17vpFL3s3+eiTPH/oOXrzeq1KmKtt3fh6dXwpBod2/dxeLJCzi388N7DxGYKwfqNK/L+Yit88MRM36cirDHYeg6sDt2b96FxUr5l85ehF9GP9Rs/AYfP42s11i3aC32b9uHzl98yPslexb8Og8nD5/g5UunL8aev3fz9zeb18NrNSpYto2KjMKaeauwadUG3L52CwHKuaxYqxLe7tQSGfwzOLSL9j3/l7m4cv4ypv41M8l1mxJcN92Ch84dHpBeA3tQmEiakgoJooMHD+YQzdTxS+GYSVil0JfWef2soY5u6zx/TwPl/qWJQk9fu3YN9+/fZ28qCqNpz9MqPpMmTUpSOdS537dvX+6ov3TpEovAlK+QOqfthbQUBEEQnj8U+j8+I0aM4MkRWj7f+JCAOW7cOBZz6b5PaQBy587NqQbsQWkGSBju168fr6+FfX5SWGUSYYcNG8bbkRcsiV+UK5jaHXvQchJFaYoPRaJw1J5SuzhhwgSOeEH2sSClHA+1wfFJbp1pULtIUTOSCrWnFNGDBHeyn9JBkMhNbWx65849ZbrrbCucBw02+Lx3GxZ/+/YbjQ6dPrNZXrnyG2jZ6kN06vAGi6qTJ32Hbt0H8bK0Kmh+O2wK+n/1k/LbsY0/fP7cKfj5BaB9h14285s0bYc6b76tPAcn/K2lJEaT2hGb1uortaGBFecvAVkzAxmT1nUhCIIgCEKSMZnD015XBWBBEJ4vpgjVIzjqIuCSBXANUkNFC6lCogIwef2SAJyeOLjzAOb/MgdFyxTDd72+hU8GH+QumBvnT51nYXHt/NWYv3MJMmXNlOh+Bn/8DYuRvn6+eLVCSRZnl05dhOUzluKnReNQs3Ft2w2Ul/mBH36FpdMWI2f+XMgenB1njp7G9j+3Ye742ZiwchJKlH/VZhMSUb9s9zkiwyNQRLHXLyAD9m3dgz+XrEPdFvXxw9wfbURMe4wb9BMmDfsFnt5eKFa2GIxGEx/jMsWOPiP7oX2vjjbr/6PY83mbHqrYnCcYOXLnwOHdh7jMd7u1c1CK43o2xsZi4aT5yFUgNzJly4zdm3Zhy5rNOH7gGIqXL4H+7b/kc1CgWAHOwbtn8y78tfQPzPp7vk3O3T1bduOz1t1x/8595CuSH1kCs3JdrF/2J4vVPy/9BX4Z/S3rk73XLl5DBqXORnw2HHleyQv/zAE4vOsQh3X+54+tGL/iV4uIReWSSN20/dssAJMIvmbuShZ3if1b9+LwzoP8vUCxghYB+Prl6/i06Uc4eegE25S/aAFcOHUO29b9zcL2+OW/okjpojZ2XTl3GQWKFsQX732GGOXtnc7N84a6lq4ZbyKvPid0eLk6TFITGohAHd80PQ+oQzxPnjw8pSZ0n3GUZ1EQBEF48aBBTOTBmlRI0C1Y8Ok9/Xx9fVGyZMmn3i455RQrVizVy0kOVHeUz/hFgJysyes3LP2MDU4VKOQzefY2e7tDAvFXw9PTC999PwP16xbC3Dnj8Um3b/i9xGR8sqBJHvC0blIG45EYHX+gbGL7TezdMr74S0REhivXcMKBu0Rqi7+ERTB/SQcm3roDhIapuYGTeJoFQRAEQXAEiU6U25fCPOPJEYcEQUhtKFfwTXXSZ1C9gg2ZlfmiZaQkDt8ATcq/K8YbMD1Pa1KQYd2H4KMBXfFhv4/5BZvC3A3q8jVWzlqGyd9NRL8xXzvc9veFa1j8LV/9NYxfMYkFTOLA9v3o9EY7DP7kG1StVw2u5lBexL+7D+P0kVO8vuZJSznClk1fgqFdB6FXi25YfnitxWP00tlLLBBmzZEV45ZNZGGRoDy1I/t8h/kT56JgiUL45OtuDu0kr9Zfv53AYvS3U76zeDbfvn4LvVv34P0ULV2Mj4MgD10Sf2NjYm1y3tKL9ao5KzD4o695mZdP0gVLEn8H/zqUvZy143q/+juY9dN0uLm74Y2mdTB8xg8cfpnE1i/a9saG5X9hgXJ8HT5T88KRyNpTqR8Skyf9Pg1V61bj+bT+TwNGsxf31x/053qyhjy8f/nfeExcPVk5H6/zPPIi7lK/I/5eu5kFdkee1FTGrnsHMGXEJIz5ahSGT/8hQQ5g6lAhUZrE389HfIn2vTtZOljWLliNrzr0Rfe3P8HyQ2t4oIAGeS8P+vhrtO/VAY3bNUP2nIFJrs+UJIIHcNyXfMCCIAiCIAjCMxGrvJtfuPzyhny2ZsVyNbJP124DE10vT95XMGvOFkREhCv1FsW5gB15ANM6M6b/yPu+dPEMLy9QsBjee687Wrb+0GZdeq+dMW00Fi6chOvXLsHLywdlylZBz17fomixMjbr3rlzEz//9A02bVyJu3dvIXPmbKhZqzG69/wfsmTJbllv44aV2LN7M9q2645cufJj69/r8M+2P/D40UMWX7//7jMeVPp69bdQqXJt/PffMSxZNBnVXq+PqtXq2pR5+9Z1LFk8BYcO7ULo4xDkCMqNBg3fQfUaDezWE4XNXrN6nlLm77h9+zoCAjKjevUGHFYbadRj+nlCAvC5i0BwDsDTfhAFQRAEQRASJVZ5gLqiTFchYZ4FIY1iDAEilUmv/E5d8wAGf2db9MLgUAC+ZbqXrvP+ln29PLr0/8TyN4VN/XJUP6yes4K9YBPj+qXrqFi7srJ+f4v4S5SpUpbDEVOI52P7j6FUpdKWZSQW9v1xgE0YZRq13aJzK1y7cBWThv+C5dOXsIhIzPl5JsKVt7lR836yiL8ECaX9x36D3Vt28Tof9O3iMOTr5O9+RebsWTBy7hibkMrkqUr7rZO3OmaMmWoRgMljlTx/B/w80EbspBfqJu2a4cbl6/j5mzGJ1k18ajV5wyL+Erny58J73d9nUdVDsWnIb8MsuXdJEO49vA8LwHQONAGYjjPk/kP8b/Jwi/irrU/n4Oi+I9i0cgOHVLYOv02j2Dv1+cAi/hLk2d31m+7o0byrUsbWpwqlHR/y8iVhv1HbJko5th0vDdo0wrnjZ/DrsF+wYuYytOvR3rKMroWWH7TCZ99/meyyUwry4PfVeUsoaEEQBEEQBCFZkAZ36YqIvwSJlQcObGdxNjhn3ieuX/616jZ/2/NoJUG3c8c6OLB/O0qWrIAG3b5BaOgj/L52AQZ+0wU3b13Fp90HW9YfNrQ7Fi6YhNcq1EDz5p1Y5F25Yhbef68GFi3Zg3z5VY9zflfq8AbOnjmOho3eRd58hXH61BEsXTIVR/7dg/mLdsLDQ32H3Ld3K2bNHIs33nybBeBTJw9j6dJpLEwTi5TyaHBzxoxZWAC+cvkcr+/nl9FGAN65YyN692yJhw/vcx2RmLtt2x9YvWou6r/VGj+MmmPjhXzr5jV8/FFDnDh+EF7ePsifrwiH1iZBmsovWlR9337ZIxqR9/3Fy6oncAbfJ68vCIIgCAJhVMM8RykPspAHWUFIF1BY9sijgF556HXLp34Kz4RdAdio/Ltvevi8bUlRajdJKPyRhyx53N66djPRbSlPLE0P7z/E/m17cePqDUSbQwWHPg7lzzs3bttsQ2F+SSi0R6uP3mEBeNsfWy0CMOUXJm/gh/ce8Pf4UHhmCpl86cxFzukbnzs37+DUvydZ3D2044DdckkcPrL7sOXv7X9tg4urK5p2aG7fzi5tnloAfv2tGgnmFSz+Cn+WqVrWRkAnchfMA1c3V5tzQEIt2UW5j+3R5P1mfB4orHP8/MskQCcov0Qh/rx1/dZTHUt8tIECFDbarl3tm7MAvO2Pv20EYILyA6cFqIuJvICDddmfuK4gCIIgCEJyofQIderUsXwXXhwo7HNkpLOtSBvcuHGFRdzg4CeLv/YwIaFHK3nLkvjbuMl7GDFytmX+xx8PQKMGxTB50vfsCewfkInF4mVLpyN3noKYPnOjJUx07TpN0blDHSyYPxFffT2W5x08sB3/nT6K5i07c45fjbFjCuDXicNYmK1Tp5lduz78qB9PVStlg5ubOzb9fcn2OOx45l6/fhm9erRgj+Tfpv6BV19VByGTiPzD959j/ryJyJ+/iCUfMgnKn/VqzeJv2/c+Re/Pv7OEoT54YAcvO35sP/+dlHDYLwPXblDqFsDLflRuQRAEQRAYkznU82Xla/p1bhOElxrjI+VF4jBgyAi45ZEcwc+AXQH4tuk+i8DOxGBQX/K0l0t7aDmUDC4JE+IE5Q6yu42Pny/u3U48rzGFHh715QjO+RsRHmF3HWOsbf0E5gxkj1V7UD5g8oK9eeWGZR6FaX708BE+qNshUVsePXhkd/4ds7i59+89PDmCxFaNW1dvInO2TPBykJM2IHNGFqUTq/P4BAYnDG+shUPObmcZdRJ4+/pYcu9a2+XhIKaVdi5vXk0o3JNQnrB8teMgOurZRndpInUOO2Xw/Nxq5+YtO3Y5K+yzPUJMjxGhi4IH7F+fgiAIgiAIz0qFChV4El4s7t0HzONfBQXyzCW8vZM3Et2SA9jKozVbtiD28G3WvKPNuiT4Nmj0LmZOH4PDh3ejeo23+D3NZDJyaGYKl0zbEpUq1cbSFQdYfNWgqETE1Svn2XOZhFzigw/7os6bbyNLlrj3FXt28XylPHvhl43m9WG1jHIdh4Q8wPiJKy3iL0FexgO+GYd9+7Zh9qyxLCyTLbt2bsT+/f+gStU38fXAcTb7L12mMsaOX4rWLSqYi3m5PYCtuXINyJuLIpw52xJBEARBSIMYHwCRZ5WHmHBnWyIIQkoQew8IVyaXbKoQDHkIfloSCMAxiMU90wMnmGJLxqyZ+PPB3QcO19GWZcqWOcEye6JwUhnTfyTmjp+F6g1qovuQXshVIBfczeLk+EFjMfn7XxNsQ6GVHUFiJ01evt6Wed4ZfFiMnrNtYaK2ZMpqP3+rt9mztn6rBugzsp/D7a3flWmb0ETspE6CsMdh8PRO+pDixOrZJYnngOolMbu0urXOs5uU8p8Vbx/1fIU9sm9b6CO1N8zHjl0urg6jqzuFm8Y7yK0XbxxBEARBEAQhaURFAbfuONuKtEXmTNn48969209Y0z7aQFtrj9ZatRvztHfP3xz2+fata5wzmF7kTp44xOs8evSAP93c3NDu/Z6YPm006tUpyPl8q1d/C9Wq17eES9YoV/51Dim9a+cm1K6RG3XqNud1K1SslSBXsD27CKPJaPtCqa2PhOvv2L4eXl7eHDOcxF4Sk0m45UlZL2/eQuyRfO7sSRQuUhLbtv7B27V555ME+ydIRCY7jx87YNeGlxXS3lkEzu1sSwRBEAQhDUGCLwm/JAALgvDiEXNTmZSXU9ecykQah0QISioJVKpHpseWFzpnUqCYGkZ439Y9DvO47tu2lz8LFiuYomWvX/4XDAYDRs79kb1VrTm4Y7/dbchb9L+jpy3hj63Z/tc//FJd+NXClnmvlCiE7X9uU16adciaI1uCbS6fuwST0QRXNwdexTkDWRA9deQkexjHh3I+Ufho6xDMhUsVwZbVm3Bk778oUf7VBNvs3rSTt3veFFLq5e+1mxPk+LXYtXkXf9pb9swk0pnwyqtqKOm9W/cqdVc0oV1KfaWaXSlMKMJ4cIcLUk8wFwRBEARBEF4crt548jovGxkzZeVctf+dPsJesE8bmthe6OTbt67j065N8e+/e+DjkwHZswfDzd2DvXLv3k2Y0ubLfqPwaskKnMt344YVWPf7QrajarV6GDJ0Em9PUK7dGbM3Y/68X1hYXjBvIubP/YU9clu2+hB9vvzB4hVszy5tvl5n5xi19WF9HNcQFhbKuYgT4+FDNRrXzZtX+ZPCWTsid+6CLABLCGhbIs2DM7ImHAcvCIIgCC8Z0UDUJTXXryAILzixyk/+gvJ7v6Z6AxuyOtugdEECAfihybEn5vOk0huVWdhcPHkh3mxRH6Ur245SPrjjAJZNW4wcuYNQsXblFC2bXjDphZ68Ya0F4M2rNmLf1r0Otxv66WD8tm6aTSjj+3fuYdSX3/PLtHVe2GYdmmPr71sw8ovv8cOcH21etinfbfuabTmn8HczR9oty9XVFY3ea4p5E2Zj4aT5aP3ROzbLp4yYhHEDf8LQKd/h7Y4teF7zji1ZAB7e83+Y+tdMePnEeSRTvuMf+nyXxBpKWZor9UIC8IjPh+O336faiN7HDxzjUNwkktdsXCvFy9YE8muXriZY1vDdxhaP7zpv17UR2kMehHC+ZLpWWnzQKsXtSg1CTI+QUefvbDMEQRAEQRCENE7II8n7aw8aJFyzZiOsXTMfe3ZvQcVKjt9PSDydOGEoomOi8UnXb9h7117o5O+G92bx96OPv0LXTwfxehpjRn+F3yZ9l0AArVe/JU/h4WE4eHAHli6eyiJv927NsHhp3Psqib0dO33OE3ktkzfwjGmjMXvWz8r7pBu+6DvSYmt8u8wL7IZfticYU/jpzFl0mL9gBw8oV8NVm+LWN/+dPTCnur453294uOMY46GhIWo5EA/g+FB49gy+yjl2d7YlgiAIguAkSASKuggWhQRBeHmg3N6RpwH9dcC9oOQHfgI2AnC08i8MaSNGPr1cfzdzFD6s1xHvV38HDd5phFcrlOSX0iO7D2PNvFUc/nfErFEpPiK4fusGLKB+9FZnvN+rA/wC/LH/n30cFrpa/erYtu7vBNuQ5++5E2fQsnxTtPywDYuFF/+7gAUT5+LGlRvo1OcDlKxYyrL+m83r4a3WDfH7gjXsPUzicAa/DDi671/MGjsTmbNnQff/9UrUzp7ffoYd6//B0G6DcHjXIdRoWJPnk5i6YuYylK/+Ghq1bWxZv1aTN1hUXj13JZqXbcKiMQnol85eYjspbHFw3px4eO9BSlRjkiEP78bvNcWqOSvQplILtitjlkxKXRzBnHGzuKPk+5kjHXpDPwvlX3+NOy5++d845fydhX/mALTo3Aq5CuRGlsCs+OrngRjUZQBavdYM7Xq0R/4iBdg7e+742bh64Qp6DO2dLjyAiYciAAvCc4HuWXdvXkPY40fKPSWr0oZkcrZJaRbqCN63db3SFuVHUJ78zjYn3bFn8x84tHMLQu7fxUcDfoCvf4CzTUoxdm9ah4M7NuGdrn3hl1FcnATheXPnrrMtSLu0efcTFlu/G96LxVbNizY+GzaswLifB6FY8bLo2Wsoz7MXOvngge38d3zxl9rILVvWmP9SBdAtm9dg967NaNTkPQ757OnphcqV3+CJwkUfPbIPoaGP4e3tg1kzx+LG9cvKfgeyZ3HGjFnwVoPWKP9adbxeJRC7d2+2KYtLiSf20jNNUgXg/AWKsn0urq4WL2Rr7ty5yV7NZDNRqJAakWr3zk02OYM1IiLCcWD/drt2CSo3bwO5E1a1IAiCILzYGB8DUf8pn44HkQmC8BJgfASEHwBclQdi11yQsND2sRGAH5nS1o3ztRoVMG/7IvzQZzgLviRcEvSCXK76a+g7+qtUEd8+HdwDD+89xPIZSzGgk5pfl8ItfzGyH7IHB9oVgCmM8ci5YzDkk28w4rNhlvnZgrJhwLhBeLfrewm2GTFnNPIXK4DZY2fiqw5fWuZXrfc6+o/5msXZxCDv1Xk7FmNE72H4fcFqrJy1jOfTS/c7n7RFr+F9Eoimw2f8gLyF8yllzmDvY4JeqKs3rInBE4cqx9sX/+5+kLSKSkGGTR+BfEXyY9ZP05U6HGiZT57ffX8cYDdkdUqQv2gBjJr/E34bPpGvL8rVXKl2ZRaACfJODsgUgDEDRuGnAaMt2+XMl5O9s0m4Ti+EI1LCQAtCKnLgn41YPHkM9v79J2KtwunnzF8ITdp3RdP3u8LgkrbygzubLWsW43+ftGaBb/nhW9LB+xQs/HUUfv32C64zX78AdOzzP2eblKKM7tsFt69fgY9ybO91/8rZ5qSB5CiC8PwICweiop1tRdqlXLlqaPvep5gzexw6tX8DI0bNQVCQbUJW8g7+un8n/t6j59C4BXZCJ1NY6Rs3ruDkyUM2QuikX4fj9Kkj6vrm9pE+Z0z/Ef/+uxvTZ260iM8Uejnk0QP2+NXm3VT2SbmCaRvN05egUM1Ehgxxg4Y0YdpeCGidncHW9jyGmzZrj82bVmPkiC8w6sd5Nvs6dnQ/WresgDfqNMNPPy/mefXqt8KY0f0xdcoPnJ84T7xQ0LSfx49VD2AJAW2f8HASysnT29mWCIIgCMLzIFZ5SL0g4Z4FQbAl+opyX7gNuOUHDBmdbU2aw6YnOgwRzrLDIcXKFsfMzfPw4O59XL2ghukNzhsMv4z+dtf/7LsveHLEyn9/t/mbxNZjsf/ZzCPRdPCvQ/HZ91+wF6+rqwtyv5IXnl6evNx6fXcPd5u/52xbiJtXb+DG5RuKjX7ImT8XezPbg15kPx7QDZ2/+BCXzlxCeFg4C4v2js3RcfkF+LGoO2DcQN6H3qBn8VKz1V6ZH33VlT2SL5+7jMcPHyFHnmBkzqZ61/y2brrd7ZJqD1GmarkEdWrN9lt77Nr1Yb+P0eHzzrh89pJqV+4g9oS2x/wdSxzuPyBzxgTlD5o4lCd71Gv5Fk+OIM9pmsjj986NOwjIkpHPkz2hIjG70gLhym/cF95PXlEQXkIuXLiAPHnyPPV21Ak6dcQAzB3/Hdw8PFCjUSvkL/IqXFzdcO3iWWxcMQ/jB/bEjr9WYfj01XD3tH9/TioP7t7mMgMyp71cFyTYeXr7wieDX5LWzxaUi+ssZ75XRPx9StbOmwwPTy9M33QM2XPmcbY5KU6zjp9i54Y1qPJmE5v5Z44fxvmTR1CzUWse8PbcEAVYeIl4nDYyAqVp+n01htstCqVc9438eK1CTeTNWwiRURE4c/ooDh/eze+AX309Fq9Xr2/ZTgsBbd3mtXu/B/r37cBi8lsN2iAgIDP279vGYaFJaJ47Z7xl/eo1GqBuvRb4848laFCvCGrVbqy8u7pjy6bVuHP7Bj7o0pdTBRFdPv4KGzeuxLSpozhMdNly1RAW+hi//76A373ad+gdd0B2hGl1dtJDQL9Ztznqv9WKvaPv3LmB1m0+gp9fRhw9ug/TpoyEbwZ/9OodN1A6S5bsXI+DvvkIbVpWwHtKPRQrVhYhD+9j5crZ2Lf3b5QsWYHrMkFoasECBe/Kkf2JqwmCIAhC+ib2NhB1TnkIkVGKgiDYwRQJRB4H9H7msNAyQlLDRgAON6U9AVjDP1MAT8+TDP4ZkuV5mi0oO09JhQRn8kR9FihXcZHSRZ+qzHyF0164TeqwSIt2EUF5gnlKz4SawuGrEwFYEOLTq1cvjB07FjVq1MDy5cvh7++f5G0XTRrN4m/RMhXxv8nLkClboM3yD/oOx1cdGrKH8G/D+6L70J+fydYv3n2TO16n/HXomfaT0jwOeYhW5XOieeee+HTIT0nahups9bEHqRLi/0WHxPZswblfSPGXoNDPNMVnzdzfsHLmL6hUuyF8/Pyfv2GCkM4ZPHgwAgIC0LNnT4frPEpbQaHSJJq4S16s8+ZO4DDOe3ZvRmxsLIc/Jm9YElgLFylps10GvwD2IA4OzmuZR+vqdHrMnP4jViyfAb3egKLFymDqjPUssB46tFN5LolLJzF6zAJUe30m5s/7BUsWT2FROXeeghj67WQ0b9nZsp6fUhaFqCYv4HW/L+T9e3p6o0jR0ujabSBeq1DDsq6jENDkGZxUAZgYOXoe8uUvgtkzx+Lz3u9Y5pcr/zq+GTgeefK+YrN+q9Zd2BP5px+/woRxQyzz8+YrhKnT1yv1uoMFYBkk5pjH8nsVBEEQXmhMZq/fq842RBCE9IDxIRB+GHAvpLy0+TvbmjRBvBzAMY7WEwThBSCCRsNI/4kgJGDGjBn8uWXLFuTNm5dFYBKDn8SNKxcxbdQ3yBIYjB/m/glv3wwJ1qF5Q35bitYVcmH13El4/7NBz5QX+N7tGwjInC3Z26cWZFdycHO3nzsxPRIdFcWfzypoR4aHw0XZh6MIIkSsMdZuWM6kQoJBZEQ4PL0SDgqijv3HDx/AO4NfksJu0voR4WF295XYNuGhj+Hp7fNUHfv3b998qjKe1i6CzqMMShBeRH766ScMGaKKbNTuUVsXP/IFOahGi2NFkilTtgpPBIm/RGL3bgrxPHve1gTzmzRtx5M9YXXJsn0269L+m7foxBPhyEuX8PX1Q4+e/+MpsfW+GTQBA74ZB5d4qSr27Htgd33y9CWP3/jHSn9/2n0wPuzSD+fOnURo6CMWu+3lBNaoV78lezVfvPAfbt26xiGx8+cvwraWKl0Z77TtCi8vH4fbv+zQb5bCtjsIACYIgiAI6RdTmPJyfFrN+SsIgpBklBfayKOASxDglgcvuxgiyQgF4SUiFrHONkEQ0iTUKd6xY0f+/uDBA9SsWZO9pAYNGpToduuXzkZURATa9x5kV/zV8M+UBf1/moWbVy4i/PEjFoC3/7UK+7b+hWYduyNX/kIJtpn101A8uHsLPYaO47/nTfievT4pBDTlGB779ac839PLB12++j5Jx7l70zqsXz4H1y6chbuHJwqVLIdGbT9CUF7bKBTk1Xz98nl0/9/PCQTA8LBQTPzf58jzSjG83ak7i5W/DvvCIswd2rnFYlvBYqXx1jud4QgSGaeO/Br5i5ZEw3c/5HnnTx3DqtkTUa9lB3h4eWPhpFEc8peOs0y1N9Dig14c+vj29atY/NtoHN27nT2UipSugFYf9UH24NwJyrn43wlln7/i9L/7EBUViRy58+ONZm1R5c3GCdal41sxYzz2b9uA0EcPEZgrH+coJkxGI4f2tvZwjomOxiLFjt/nT+WQ30Rw3oKc95nObVLzFoY+CsGcn4dhg3J+7ty4xvmiCxQrxR7Vdd5+z7Le/F9G4C/luouJisLVC2fQsXZxnv9e9wGo3fQdR7vH/7q2QZhSxpejp2HcoJ7Y/ucKFjozZ8/BdpK3LQmyv33XD38tmWURZymkedeBP9oN673377/YnqP7tiM6MhIZ/DPi9bea433l95AlMMiyHl0jHzcsjxoNWqLx+5/w9bP196UsQNM29Vp3ROcvh9kMBpg+ehCvQ4Mn6PehHTf9hohPm1a2CODfTllhcw0n1S5LvSi/ye9nrVXO+wQsnjIGjx7cw6qj95J03gQhPUHtm8ahQ4dQunRpTJ8+HU2bNrXMD0+7AaHSPIkJv0klOZ6uSd0msfWorbLXXjk6JtpXfLHYGnd3DxQpUipJdmn7I+/g+B7CFB3K1TVpaSVeZsJFABYEQRBeNCjPL4V8llw8giAkF4ocQB7B7oVf6pDQlrc2k9xQBeGFhwTgyZMnY/HixYiOjuaOHupwsf60Ny+9LEsLNjjTdg+Pl7cxe1Y6dOjAXlDUCf7w4UOeRwIwdZBT57ijkNA716/m+q9ar+kTy6jRsKXN38f372TBqWrdpnYF4C1rFuHK+f8sAvCujWtx7uQRGGNjWaBav2wOzycx+UkCMAl9w3u8p+xzMbx8fPFKibIIexzCQu/yGePx+Yjf8Gbzdpb1/167BMcP7MKng3+iXmGbfUVFRmD1nEkoX6MuC8DR0VFsi9Hs+XTpzAncuHKBv5OwlpgAHB72mOugSt0mFgH4xuXzPI8EyL8Ve0mEzFWgMB/7wR2bOZdyz2ET8GXbumxLoVfLsii+fPp4bFg+F+NX7OD1NX5fMA2j+3bh81S8XGV4u3tg96bfsWX1IrzbrR8+7P+dZV2yl4TF8yePsviaNSgX14MmOtI8TQzW6vWLd+vg8K6tvG8SamNjY3j/4wf1wr+7t2HwpMVP7Jy/e/M6ejSvxsJ8qUo1lLroglDl/JCNw3u0w5E9/+Cz73/ldf0CMiMoTwFc+u8EXF3d+Dvh/YS8yyQWXzl3Gp+3qc0iN4m+NJCAclRP/q4/i8N7t/6Fi6eP83Fkzh6E3ZvXYZ1SfzRv3IrtNuLA/F9+ULbrB1+/ALzVpjMyZsmOU4f3Yu38Kdj2x3L8uHAT8hUpwesajbG4cOoYTgbnwfqmc9i7lnL8krfctnXL+DqkwQ0Df1lg2f+dG1d5m6iIcJvjfnDnFl8b2XPmteQAdrHy1n0au7R6ofP767dfYOGvozi3dr7CccsF4UWGBOFmzZpxGoQxY8bwvCjx/hWEdEdklLMtEARBEIQUJOqsKgALgiA8KxRBgEJCexRW8wO/hIgHsCC8RMTCiH79+uHePfFsepkhoTitiddpZRl5AS9btgyXLl3iulqxYgX27t2LNWvWAFlKJajLm9cusdBkLQo+LVq4xyfx87Jt/Fk7twvyFir+VDmAJw37ksXfmo1bo88Pk1kEJv47ehDfdG6KHz7vhOB8r6Bo6QpPbRt5hq45/oBFyh5vV0Pjdp8kOQdwYvy5eCaLx72HT2Shj0S/AZ2a4OD2TUo5VZErf2F8N3Mte7ASCyaO5OOkadj0VTzv+qXz+OmrT5AxSzb8uGgzcuZTPYvIw7Z3yxrsJUqewHkLq1605MlL4m/Pb8ejaYduPI9E0u96t8fG5fM4n3OFWvUtNs75+VsWfzt/+S3e6zHAMr/D50Pw89efYuWsiXwc9Vp1SPRYf+jTicVfqjfy+NXoqOynf4eGLLi/WuF1xdZ3uU5oejO/BwvU305dkaT6pOubBG7ymp38x0H4+gfw/JZdPkOHGkU4jzXV8/iVO1lUJ97r+TW+eKcOC+97t/xpOfaj+3Zgyvf9kTN/IYxR6jVj1uyWcrb/uRIDP3wbQz5phembjqmisVkAp0EMNFjimwkLLN6+5D3f+Y0S2LxqIdebNhhCFy9Ej3bcn7d5g/Npfz1uboIcwE9tl7leQu7fxbqF0zmMe/nqbyapPgXhRYKiYFAKBAoJ7euXx9nmCILwlERGOtsCQRAEQUgJjEqjdkp5Cb/rbEMEQXihiAYijprzAie//za9IgKwILxkUGjbpUuXOtsMwYlEREh8x6fh6tWraNKkCWbuuJhgGXniUv7f5PAkr9D4AlhSt4vPw3t3OKQyeU/2GzPTJsxuweKl0XfMDHzWqhbmjf/OIiYmVoYju/CUdml7S7gbdR4Juz2Hjrd4eZIn8Af9hqNbo4ocdrv3dxMt4i9BQuayaT9z6GbyLKWwlZfPnkKJ16qxAKuJv9q+3+nWDyP7dMauTWstAvDhnX/DzcODwxRrUCjmlh/0ZgH44I5NFhGUcuiumTcZuQsWsRF/CRIXKWzy7wunYa2yTmIC8OVzp7Fn8x+KnVVtxF/tmL8YORXtqhXEsqljWQCOX09PS4fPhljEXyJbUC5UqdeUj69O83YW8ZePXalDqgsSgCmcsnbsFCKbjp+EcmuRlSBv7jfefo/DSFuLxlwvyv56KOfU+hqk0On1W3fCjB8Hs1d8fG/4+IMQEjvu5NpFZXTp/32i4u+VK1fQ5u1GHBVAENIr7onkXNdCQu/Zd175y/+52SQIwrMTI1l+BEEQhHQPCTTHJN+vIAiphAmIPAm45VVzA79EiAAsCC8RBuixZMkS7Nu3DyEhIdxRTh3f1p/25j3vZTQRJOKkRfueZLszbBBRN3XJkMF+fl9f/4ycx/ZZcORly0KXnWWO5juCxDsKVVyrSRsb4U2jdOWayJojJ/Zs+YNtsRbY7NmmLXckzCXVo9kae9uUqlSTxVhryPOZoHDHRctUtFlGYiWJsfu2rmePTgrl+1rNejzR8Z88tBe3rl1iL1gqj8RhgryBNUigJI9fmvRWYYUpzLVaRtxj061rl3Hv1g0EZMqKqT98HXcc5mOh717evjh/+liix04hpolKbzSyuzwoT34OaX3qyH62y2CdczEZdV2k9GsJ5gXmzMufhUuWd7iMwmxb20z5mUtXqWW3jIq1G7DQeuLQbhuhlcTm+Dl4iRzKMcYvwxGJXWfJtYuoUOutRMvdsGGDiL9CuifyCW6CFBL61KmTKFCwYqLrCYKQtogVAVgQBEFIz5jCgIjjyqf0awmCkMpEnQeMyj3HraCzLXluWHoRHXr0CILwwuBi/smXK1fOyZYIzoKE4rQmXqcl4f3MmTOYO3eujaBeuHBhrF69Ghfs1CcJpyQsPrx/l3PxPhWa0OpIxEvE0/FpRFbKpUpkD87jcJ1swblZ0Ax5cI+PIzGR7Ymep09hm919mefZ86z29PJmkdaR17WXjyrUx0THJcOjMMyzxw7lPLv2oPy0GhVq1ufwwlNGfMUeoSS2Pg55iJljhvBy8iLVIO9v4sbVi9i0aoHlOUo7JvrM4J8Rrm6OPe4IEquJxMKI07KL/51QbHmQ7HDjml0BmbMlWObm7vHEZdb1RDbTsTm6FjQbyfvcuuxMWQPtrm+vjCddZ/auzae1y7oc/0xZEi2P2s1s2bLh5s2bia4nCOmZkiVLokyZUgh55GxLBEEQBEEQhJcCUzgQfgTsASwIgvA8iKF+HRPg9soTV30RsPEA1kMHI57em0R4Nnas/wfBeXMiV4HczjZFeMFx07k62wTByXjE86gU4hg8eDCmTp1qM2/QoEE8n7hwNeE2r9WszwIw5Rd9q02nRPf/7+5tLMZSSGLygtRykMbE2H/ReXD3VvIE2HhoomhYqOMe/bBHIbxfb/O6OrNtsWRbPK/h+4pdzFOE5n0ido7TxtM1/jJD0gKY0Hn56auunBOWwl9TyGsfvwC2lUJFf9m2rs36TTt8ig3L52LRpNFYt3AaC5Y3Ll9ARHgYOnw22MbrWBMMK9VuiAHj5iTJHnuQBzFx/45jYZHEawqFTR7nGskduJdoeO8knkN/xWa6lrVQ2/G5ZxbbM2axDcOcnDDhCX4Diewj2XbhycdevHhx3LhxIwkWC0LahdqzIUOG2F3Wvn17zgWs03uIACwI6QzzY5sgCIIgpC9Y/P0XIv4KgvDciTH3bbIn8IvtGGvTg+qq/ItElKN1hVRg/bI/0avlp8gQ4Iftt/ZYBAFBSA08kLgnmiC8rHTo0AEzZ860/O3n54cVK1agRo0aiW735tvtMHfccPYwrdm4NXuo2iM89DG+6tgI4Y8fYcFuNZewt68ff96+fiXB+vdu37SIfgnQ6WA0GZN4ZED+Iq/y5+Fdf6PFB70SlnXrBocpzlOomKU8a9so/LA1Z44dsluOJqA9jW2pzdZ1y/iz26AxKPd6HZtlR/f+k2D9HetX4dzJI6j0RkM+bjoHFBr49QYtULR0BZt1M2cPQvacebB/23pERUYmCK9N4Yw3r1qIvIVLoFSl6g5tLF6+CtfdP38sR9tP+ydYTvV99cIZlKlaO8EzQnLCbacEr1aohnULp2Pv33+iop3QyVvWLubPUpVqpHjZBr0q7NobOOFMuwQhvULtHQm/1A4SklFCENIfdsY8CYIgCELaxhiqPHgehYi/giA4DRKBTbGAO/V7vrgisI0A7KXzQKRJBODnSWCuHPDw9EDugnlE/BVSHU+dCMCCYA8SezWqV6/Of/v7+z9xu6C8BfBejwGY+eMQDOjQCIMnLUGGgIw265A4+O2n7yI05CHebPG+JXwxeaMSG1fMQ+N2H1vWJ1Fv8nf9HJbp4+uHuzevISY62r5AHI9CJcuhQLFS2PHXKuzd8ifK14jzeiVPyXGDesKofDZu94llPtm2a+Na9obt9MVQy/zwsFDMGmPfe0wTjW9eufhEmzTseV2mZEoKrV0NexxiM/+GYuOy6eNs5h3Zux1Du73D9ftOt35cBx6eXg73TbY379wTEwb3xo/9PsIXI6dYvJbp3Izu2wX//LECoxdsSNRGEpGr1X8bW39fihk/DmZPYw0S57/v1Z7LavPJlwnKfxpSsl6bdeyOv5bOxtgB3ZB74SblWSavZdmKmb+w53XxcpVR4rWqyS/bwfH5Z1Y9pk8c3I0qbzZ+JruSbZsgvCBQyOcZM2agVKlSlnl2UsULqcwtpU2fNfMn1KrdBGXKVnG2OQm4cP407ty9iXLlqjnbFMEB8rsVBEEQ0hUs/lLY5xhnWyIIwstO7F0g8uQLLQLbCMA+Om/cN4U4WldIBYqXK4Gdd/fD1U1C8wqpi1755wVPZ5shCGmSXr16sQcUfWohn5NKux5fs6fomrm/4d0q+fBG03eRv2hJzv165fx/+HPxTA5LS0Js9//9bNmuVOWayFe4BIeG7tfuLdRq+g5iY2I4n+zF08fxSokyOHvi3wTllaxUA1tWL0LvljVQpExFBOctaCMg26PvmBno0awqBnRqzELvqxVex+OH97F2/hQcP7CLvVyt9/FWm85YPHkMezdT3lla/+6t61g5YwKClPIunT2VwPs0ON8ryJw9BwvHg7q0QI7c+VCm6hsoX/3NJ9Zhanmy1mzUGn8smoGxX3+K28o5yKnYeFmxfdFvo5X2twrbqpG3UHHUbvIO1i+bw3VFZAjIhCzZg5CrYBFeZp0DmCAB+Nj+nXyOj+7djtdq1uNj2bN5Ha5dPIfWH/dhz90n8dmISbhy7jQPJCCR8tXXquGRcn7IIzns8SMW4e3Vo7M8gEkcp2v5Z6VeO71RApXrNOLwyyeUa+nEoT0IylMAX0+YnyJlxT9GOqdU3wM/fBt5ChaFu6cXxq3YziGfn6ddgpAeyZMnj+W7FvI5/mAnGnvh4Q5ERD5f215mpk8bjRnTf8SO7euxbOVBZ5tjQ1hYKJo3K8OfM2ZtQoWKNZ1tkmAHDxGABUEQhHRDLBB1GiL+CoKQZiAROPoq4BrsbEtSBRsB2Bue7AlhkjzAzxU3dzdnmyC8BGi/b0EQEkKi79MKvxrk9fn5iEkcYnjJ5DFYOWuizXISRcmrkzw43T3jBmGQd+rwmWvwXc922L15HU9EsbKV8OOiTZj6w9e48N/xBOX1/HY83NzcsWfLHzi6bweHEH6SAFygaEn8sno3xg3sgWXTfsbSqWN5fgb/jHi/1zfKNNAmCgV5pQ6fsRoj+3TG8unjedIbDCxu9xr+C9pWLcB/29SD8vfwGWvw67dfcFjkrb+HwMXVLVEB2K4H8BM8W6m+HeUHJptUu9R9kCDbc9gETBnxFSb+73PLOm+17oTOfYeheZlA5bjV4/DJ4Ae/jJm5Hpp/0IvF33u3rnP45Z0b1nA45y5fjcA7XeM8ccnWgb8swGs16vEAgL+WzOL95y5YFB/2/x41GrZM9Fg0/JSyJqzehcW//cgDAH5fMBUeXt6cL7rlh73tisivVnydxc2k8sqrZeFG15+d+g3MmZfL0LxrrfH09uFldEzWNHn/Ex7AQGL6wR2bEfroIbIH5+HrqWWXz7k+NahOSlaqzuvbIyBzNi6DttegvM20jZePr826FWrVx5jFm1nYv3XtMozG2GTb9aR6EYQXDQrzTIIvTYmlOPDxFgH4eVK3Xgvs37cNb7folGDZ+r+WIUvWHChVqqKdLVMfet7Inj0nbty8gixZAp1ig/BkvGSMryAIgpBeiDyhegALgiCkJaIvAHrlRdgQ4GxLUhybHlTyEPTVeSPE9NhZ9rx0hD56jDFfjUbB4q+g9Ufv8LyzJ85g/i9z0aRdU/j4+WLG6Kk4+e9JePl4ofIbVfBej/bwVN7y7ty8g1ljpuHAjgMcvvPV10qife9OHFY6PudOnsWiSfNxdP9RREVEIjhvTjR8tzFqNXnDrl2/L1yDdQvX4uaVG8gSmAWBOXPYdI52/LwzgvLEjYr4d/chLJ22hG0n8hcpgFZd2qBY2eIpWV3CM+Cn833ySoIgJJvqDVrwFPoohMMgh4c9RqasgSymOiJbUC78tORv3Lx6ifPtZs6Ww7L+oIkL7W7jnykL+o+d9dT25XmlKIcjpty0Ny5fYIGRPCJd3ewPQipduSbmbj+Li/+dQFjoIwTlzs8CKbHs4A2725AH5pNCHluTMWt2bL5iO+iMRNv486z566zjBJX26qxp+65o8M4HuHjmBKIjI5EjT34WXImNF+NGHR8/uBtLpvyEVh99jk++GWWzj9vXr+Kjt8pyrmfy6rUWy0kErt+6I0/PAoWbbtfza56SwojZ655q/yTcO+KNt9vyZA+6Hh2dUwqlbB1O2RF0jf20eIvD5ZS7N34Zrbp8xpM9KIdvYnl8k2oXkVi9CMKLSNOmTZ+4jo8PcOde6tsiqJQqXQmLlu5JMJ/SNPTq0RING7d1mgDs4uKCVWuPct51d3cPp9ggJA49kogALAiCIKQLSGCJfeBsKwRBEOxDoaA9SwG6F+vhOoELTSadvwjAz5Hw0HDM/2UOqjeoaRGAr1+8xvNCQx5j/fK/4OnlgXxF8uO/I6ewZ/MubFq1AYMmDkWXeh0R+igURUoXRcj9EMz+eSZWzVmJOdsWIF/h/JYyVsxahkEfDuDvJSuVZlF52x9b8eeSdej8ZRd89t0XNjZ93bkfls9YykJyoZKFcevqTWxZs5mX5cgdhIDMAWy3xrhBP2HSsF/g6e2FYmWLwWg0Ye381Vg2bTH6jOyH9r2erVNceHZcYEAGnY+zzRCElwJv3wzKPdu+p6MjSAim6XlAAjJNSYHETRKO0zskQJIXdGKcPryPPwuXei3BsiyBQZxHmXIohz0KUdpR/9QwUxAEIU1A4WQ9PZT3FMfjbdI0MTExCA19BE9Pb7gp9/97927jv9NH4e7hiSJFStkImZGREbws1hiLV14poWzjOPc7cf7cKdy4cQX+AZmQP39R3n9SIDGXBg89Tf72O3duKO9VRuh1+ievnMwyCC5D77gMivBhiBf1Q0g7+MorniAIgpAeiL0DRF9xthWCIAiJEAtEHFdFYLw47z8JBGBPeHCe0DCE21tfeI6smrMCTdu/jcG/DuXO67DQMHza9GPs3rQTbau0Qs78ubBw9zKLx++0UZMxuu8PyjQCE1b+xvOuXbyKIR9/g4AsGTFtwyyLMHzr2k20r9kWU3/4DQ3eaYRCrxbm+Xu27Gbxt17Lt/D97FFwdVVzEy+evACDlf3UbVEffX7oa7Fx3aK1+PXbCajZuDa+nfId/DOpbvK3r99C79Y9MLLPdyhauhjKV0/YoS48PzLr1PMSHh6O/fv3210nICAAxYoVe+p9T506FQsXLkRUVBS++eYbnD9/nr0FKMxgcrh69SoGDRqEKVOmJFh24MABLFmyBMOHD0/WvlOD+PbS57McvyO++OILvP/++yhR4umExdQg/jmvXfvJOU5Ti9Sqb+HlI0dutX1ct3AaqtZtauMZfe7EEc7xm7tgERF/hSRx9OhRREdHJ5hPIkvJkokPRrDHnj178OOPP+L27dto3bo17+OPP/7g9ie5dOrUifcZPwdsYuzduxcbNmxA//79k11uShK/Xrp06eI0W3bv3v3M5yQtkVF5dLx63dlWJI9Dh3ai3buvo1//H3Hz5lXMmf2z5ffo5xeAgYN/wVsN2mDunPEYN3YgHj68z8s8PDzxYZd++KTbNwlE1C2b1+CHEX1YANbIlCkrr9++Y2+bdRct/A3z5k7AuAnLcfbMcUwYPwQnTxziZWXKVkXvz7+z8ejdu3crhg/tgTbvfoLWbT7ieU0avarYHMXfN29ejbeblmGbSirbDRw0wbJtREQ4pk8dhZUrZ+PK5XPKM5ErChcphXbv90CDhu84tOvu3Vt87AcPbMevv63FaxVqOKxPylFMonf/r8ZY5n03rBeKFC2NevVbYfbMsdi5cyNiY2NQtGgZtGvfEzly5GJhec3qedi0cSVClDrOk68Q2rT5GK8USvgsS+v+sW4RNqxfzmV5e/uidOnKXCcZMyYctHZCqc+F83/FuXMnWbTPlauAKuwrdUT1VLFiLVSpapuCYt++bTh8aBcePw5BUI7cqP1GUwSYI5ukZzJldLYFgiAIgvAkYoCos842QhAE4cmYwpX71XnArYCzLUkx7CbRy6rPiAvGq8/bFiEeWQKz4psJQyyd0F7eXug59DO8u6klIsIjMFBZZh3umcI/zx03Czs37OAR4DRS+9zJcyhTtRyavN/Mxis4a45s+KDvRxj44VfY+vsWiwC8b6safqxt9/ct4i/R4oPWGPnF99izZZeNjZO/+xWZs2fByLljOCy1te2j5v2EOnmrY8aYqSIAOxHy/g3QqTkPQ0JCWLgj7ty5g2PHjqF69er8d6FChZ5aAD5+/Dh+++03/PnnnxbPgLCwMBbkkktERAROnjxpd9mjR49w7ty5ZO87NYhvb7Zs2Z7p+B1x5swZhIY6P0+KvXPuTOLX96JFi/g6Ts5gBuHlpnyNujyRl2+birlR7vU3OUfyjSsXsGvjWuV6d8Fn309ytplCOoEGyjx8+BAmkwlbtmzB66+/zvdMDw8P/PLL04WdJmHkww8/5AEvxYsXx927d1nw9PJK3FPxSezbt8+uSJ0Y9+/fd9hGP2/s1YszIU9Q63Ny8OBBPk9vvuk4D3pahrwK6dE+LB2OCabfHTFlyg8IfRyCrp8OYmHyxImDmDhhKPp+0Y7FwPlzf0H9t1qjzptvK8/I9/HbpO8w7udB8PH1w/vte1r2t2L5THzVryMyZc6GL/uNQqHCJXH92iXMmvkTvv/uM1y5ch4DvvnZsv6d2zdw6uS/mDdnAmbPGovqNRqgYqXaLAZv3rQa7d+rgXkLtqNY8bK8/qOQB8rv6jDu3rlp2UdwcF7lufchC86eHl6cf9dkMsLHJ4NlHRKu27erwWUVL1EOHTv3QXhYKOcN7vPZu9i3dysGDZmYwK51axdi/LjBPC9HUG72lE4MEnFPHD9oIwDPmT2OQ1fPnvUze1AXfKU47t+7jT27t2DFipmYO+8fjPj+M2z9ex2yZw9m7+tduzZhyaLJGD1mAde5RmjoY3T9uBFvmzlLdhQoUBSXL53FP9v+xMIFkzBn/jbkzJnPsv4f6xbji8/fVd5V3VDi1ddY0F0wfyJ7fpNwnFk5T1SmJgBfv34ZvXu2YvGXoHsxvSt/O7Q7+vb/Ee+8+8kTrqi0C+XrdnN98nqCIAiC4FQizygPaE/33iEIguA0Ym4oLw2ZXph8wHZVCvIAFi9g5/NajQrw8LTNtVSwxCv86ZPBh4Vda+hlNm/h/LixYTse3nuIjFkyomrdajxFR0XhyN5/cf3SNYQ9VkWki/9d4M87N25b9qE3qOG/oqNsG2bqZIuNiYXBJU7woRzEp/49yeLuoR0H7B4DicNHdh9OxtELKQV5/+qgejGQWDZu3Dj+vmvXLgwcONDyd3xI2Hz8+DEyZcrkMJQcCbI5cuSw8R5q1KiR3XXJW5TWp/3Fhzph7t27h4wZkz6EnbyZSWy2tz/q+KOOYG9vb3h6Ji9uf3LtTc7x0zIS52lZq1at+Jxkz57doW0k3mfIkMFu2EHq/KIOevLoflYh3t75t3fOHUEd335+fhY7Hzx4wOIHTUktzxo6p76+vjbHHb++165dy7bZE4CTUkZkZCTc3d2feGzCiwddE8Onr8afi2diy9rFOLh9EyLCQ+EXkBl1W7RHq4/7IFf+Qs42U0gnjBmjCiV0Ty5YsCDf1+m+HR9aTu0Z3dscQevQvatUqVI8OC84OJin0qVLJ1iX2j9a19H+6B5O7WJS2oek2Ga9X7q3Ww8e1CB76L4dv82iZ0taZq9erKFjov2THdb3bnv14ghqZ0nspucCrWwaVGXv2ByVZw21J7TMur2g82F9Tug5y5EA/DR160wCswHnLlKdONuSp8RsMAme02duRMVKtfjv16vXV663APxvcFcWf99t2w3fDBpv2axylTp4q24hzJg22iIAk6fskEGfKM9VmbF46V4WFjUaNnoX77etzmLom/VaoHz5183Fq+WTQEzetdVer2fZhtYdNrQHfp04DOMmLLNZX2cVhnnCxJU4feoIewKTXcO+m5bgMIcM+pgF3a6fDkT3HkMs83t/NhxdP2mMBfN/Rdly1dhO63LG/TwQH3Tpx97LXl6Ji7/advF/CzTvwP7tKFCwGNb9eQpBwXl4/pjRX7GQ3rplBfZg/nn8UovYu2PHBnz84VsY+E0X5Vy8ZQnFPf7nQSz+kvfzV1//bLlXTJs6CiNHfIHh3/bExEmreR6F7B4y+BNkzpwdCxbvUt5tgnj+yROH0fadKgjOmRcrVsW9e5KH9Ied6uLy5XP4/IsRaN68E3wz+LOgPezbHnwt0LmtV7/lE+shLZI1/TswC4IgCC86sbfV8M+CIAjpiaj/AM8ycCCfpiscHkE2fSacN0psfmeSPWdggnnkBUxCr71lhI+fmgQoKjLKMm/Br/M4TDOFZbZHbKzR8r1q3dcxbuBPyvrjUbhkYfhl9Gexi+aR13HNRnGhXu+Y97f37z08OcJVhiU7DVfln+b9m1SoU/Prr7/Gpk2bWLyjTsr//e9/qFmzps16a9aswYgRI3Dz5k1LCOCVK1diwoQJ3CHaq1cvFtOoM3TIkCE8nzqL6PqdNWuWpaOW9kPLqROUrrWkhPKlcinMInXQ0n4mTpyIwED1N7Ft2zYMGDCAw2ySqEpeVxQymrxyLly4gDZt2nCnrAYdG4ml3bt3TxF7ybanOX76Tt5gJEqSQNq4cWOH4u/p06cxdOhQPkckAvfo0QOdO3e2LCfP3MmTJ/N5o3117NgR3bp143JbtmyJFi1a8PGT3VTO559/jlq1aiX5/Ds65z4+ccnHaDntn8J1U8c8rUuecDNmzMCJEydw69YtfPrpp+y1lZTrjfZH55I8qeiYb9y4gQ8++ICPPX59N2nSBP/99x9OnTrF85s3b46uXbsmqQyaR9cOXSPff/89mjZt+sTrUHjxcHF1RYN3P+BJEFITah8GDx6MdevWcftEoiy1VRUqVLBZ7/Lly9zOkGBZp04dbkOGDRvG96zp06fz/ZV45513+B5P3rDaACkSnbX9URSJnj178j2YxNJPPnHs8Ub7Jlvo/q4Jpj/88AMqVqyYYF26r/fp04ePh+759evXt4RA/vfff9G3b18Wm6ktIPu+/PJLPhY69h07drCoRG3Ur7/+igIFEoZYomOkNpLEZSqD2rT27ds7rBdrG0n0pWcAanOoDaLBUWRfgwYNOH0B7Y8GDM2bN88ixDoqj/jnn384ikrmzJnx999/80CwatWq4eeff+bjoOXaOaEBdjQgieqS1n3llVf4WeVJ510bOEBe49SW0b6d6UFMen72rMD1m09eNy2hCZ0ULlkTfzXq12/Foh9Bwqk15GX6askKLGw+uH+X8/yS9yuJiJ/2GGIj/hIkYPb6bDg6dXgDSxdPjROAoZZPwqu1+Eu0eecTjPnxKw69HN/e+CIrXd/25hPk1frnH0s4p/Gn3QfbLPP28cXw72fgzdr5MHPGmDgB2GwXia89ew1NsE9HmBQ77AnAxP+G/mYRf4luii2LF01Wfm930PmDL2w8fStXfgN167XkOj10cCcqVFSfwx48uItKyrIv+422GSjSqXMfDvO8/Z+/+PdMy0gUp3Pz8ScDLOIvUbhISaWu63OdaOeOoO3Pnj2BocOmoEXLuGfmEq+Wx6TJv6NRg2IYM7q/YleLp86d7GwC/CnygLOtEARBEIREMEUpLz4S+lkQhHQI37/OKC99hZ1tyTPjUACmXMCZdAG4a7r/PO0RrEjMO8OQRM++TSs3YGi3QchbKB+GTx+BIqWLwtdf9bTYtXEnPnqrk836xcuVwDuftMX8iXNRK1c1BOUNxt2bd/Hg7n1UrlMFHT+Pe3H2zqCKPvVbNUCfkf0c2pDO3qVfKIL12Szev0nlp59+4k7SnTt3srBGISIpT+DGjRuRJUtcDq6GDRsiX758LJzSMkdQRzTlQiTxjYS8r776ikVP+qQOYeocnjNnDgul1HmsdbQ6gvL9kXi5efNm7hgjsZc6UydNmsQCIXX0khBKnanUWUR/U35AEgCTQkrbm9j+yKOVbKNl5E1MAuv69esd7mvBggVcNq1LnfkkUlaqVAlFixblDmba7+rVq1lApk5+6myn0N5vvPEGvv32W84hTJ3fK1asYG/w+OIvkdj5T+o5X758ucUO6nRv27Yt75c6silHNHW+k4hLHW1Jud6oc37p0qVc9pUrV7izn8Tt+J5TJFbQ+aDyrDvMk1IG2bx48WLkzJnT0uEqCIKQWtD9kO7TNCCJxEYagPLRRx/xvZwGqmjQPYnuVXSfX7ZsmSXyBK1Hg1s06DuJkxQGn+6NdN+k9kVL+0DiL93DSfilQTrUJtIgKnuQUEmDaUjQJIGScttS+2NPAKbBWCR2UptLHraUVqJdu3Z8v6byqQ2mez61hST4EiQM0z6pvaN2gNp1e17AVCfTpk3jeztFnqD7Pw1mIjGV2j579WINCVTUbtNEeYvJ45cE22vXrnF7S/VOg6hIqKXBUU8qj+rtr7/+wsiRI1nkpmOiNpXOobZcOyc0yIgGppEHMNVPUs87PbdQezd37lzkzp37idfR88AvA6X3AB7av1zSJJo4SaGE40PCoJubO4dSphy+8dFExUePH/K6//13lP8u/1p1u2WVLVeVP0+fPpKgfMr3Gx96v8sRmEt5HorLJawJswlEViT0DNagcMb0vEJ5bO0Jl0FBuZVnwFdx9Mg+9polsVqzq2atxnaPxRFkh97KBm0/lE+5dJnKNuuSSJs3XyHc338HtWo3SbAvyk9MAjDl+dX4bsQM/rxz5yaOHz/AobDp2KhMCulMnsQPH9xFlqxxA6BjYmMS7DsmRo1gZV1fFA6bvJwbN2mXYH2y//XX62Ppkmm4cP40251eoMEZWcT7VxAEQUjrRFN7n7DNFgRBSBdQ9AKT8jKse7b0W84mURUxmy4THptCEYmoxFYT0jAblv/Fn31Hf4XKdWw7IQ7tTBi2+eyJM1ivbJOvSH682bwerp6/Am9fb1SoVQlvNHvT5uWfvJB9/Xxx6shJZA9O6LFIXg+XzlzkcNXC84cGcNBAjqeFOkJJMNPCGpYrVw5lypThzlPyMEoOXbp0sVw71ElMHcbE1q1bef9ayETyJKXOaRJ0HUHC5bvvqp4MtE/y8CSBkzqKqAP11VdftXjSUCcULafO1aQKwCltb2L7I1GSPH+1juvChQtj7NixDvdD4qa2LnlK1a1bl4Vw6gCnzmw6P5r3cNasWbmeSIil+qF9k3Dev39/7N27F0uWLLFbRkqcfxJfNTtIgCYPa7KVyJs3ryVsJ4kUSSmP7CcxgSDPado3deDTvpNCUsogb2CyTRAE4XlA92by9tRC4pMwSfdpasfoXp0c6J6vDYwhsVZL8UBCJg2+0SIvkLcsee2SqGsPEiBHjRplSaFA7VZ8z2SN3r178+f169e5jaSBTTTRPTtXrlz4/fff+bjy589viRyhDVIiL1gSjF977TW7+6Y6ImGWxFiC7v+tW7fm+SS4JhUaMESQNzPZRNEitHon20ggTmp5JOpq54fqh545Ll26lGR7knLeqT2isOFpiUClSY+MpoEGzrYkacQJlPZTi9BvwN8/YUoOdZnt6zHl1CUc5cmlPLQk6oaFPU5QvrWHqjVu7h62g800D2DY97K1N5iTPGyJgIxZEizT8A/IbFmXvJe1/dkTvhND3U4X72/6PeSyu76PjzqIhfILxyeDrz9/amItcfvWdQ7HvGH9ch5I4dgGVUCmPMHLl05Hs2YdkC+/OiJ/185NnG+YvL5J2NWg/MxhyjksVcKDhXLbSa+Up3ZK37lzI90IwKT351RuU3oZZC0IgiCkZUyRSoN/3dlWCIIgPBtRFwD3hAOL0xNPdCPNqQ/EOeNlGCEeUekRnfnN8PGjxzbzr128irnjZ9vMexzyGB1rt8Pdm3fQa9jnqNW4NoeAdgSFEGz0XlPMmzAbCyfNR+uPbMWhKSMmcejooVO+w9sdW6TMAQlJwgseyKqz37H1JMhbJX4IYvqb5icXLTwzQUKo1rlDncQkVFqjdbwmZV8ECcLkMUOePY5sJ89gR9jz9kxJexPbH3WIk8cPiZPFixdn79569eo52o3dY6cQlAQde3zvLDp26pDXII9g8lai9Rx5FqXE+afwmBrUwWbtOa7N0zryklJe/OO2rsOkkJQyEsu5LAiCkNKQABr/vqN5jCYX63slDYCiwTYEtYE02Mg6sgz97SjfOQmiSWnbCPLipTD6FEqZRGLrtoUGHFF0DvICpraKBGiK/kDHTfPJ25YGZxUpUoRD75O3szVUR/GFZzrGY8eOJck2gtoLa+/g+G2SdXuUlPLit0fW9ZwUknLe45eRVsgVBFy4TKG1nW3JkzGazKGT7XjO8nKzd6mjZYRepy7PmlX9LVy7egEFCxZLsP7VKxf4GshhJYZq15Reb7BbRvycuo5CQJsSCQGtCdgP7jt+xiVRk7bNmDFrkuxyhCN7Sfx2sIXD5fa8nbt3a4bDh3dz3uVWbT5SfqOBfH6onK4fNcK+fdss69P758BBE9Dj0+Zo3LA48uYrzCLu+XOnlOfPbPh2+FSb8mg7yvHb58sfeH9su9l+/hvqvNy509agi8TIGSShnwVBEIR0QNR5aM8EgiAI6ZbYe8pLYojyEpUwall64YkCsBtcEazPjkvGa8/DHiGFofDMK2Yuw7DuQ3Dr6k3kLpgHF06fx4wfp6FkxVLYtu5vy7rk6fte9/fx2/CJ+LqzGtLZy8cb2YKyKdvlRrX6NdC8c0t+8dbo+e1n2LH+Hw4zfXjXIdRoqOZy+nvtZi63fPXX0Kht8jxZhOThqvysaeBGcgeFU8codf4GBcV5LVDeVfJySS6OOtnIM5Q6Q60hL6LEIFusIVupE5u8ccl2LcSk9frU0a3ZEV/wpe215alhb2L7o04p8oiicJi030aNGuHtt9+2u669ssh2EpEJ7bxZQ8duLcaOHj2a8x5SjkgKv2nPoyslzn/8jkpHx5/U8hLbPikkpQzyBhIEQXhe0L2ZRD/r+xLdp8gjNrk4uleSOEsCLA2c0e51lCee8tHaQ7tnWovANMhKywesQaIJ5fSl9AMlSpTgeX/++adlOXnIUn52msgLmUJBU+oB8g4mr1+ayCYSfymsMoVHtkarI2vstdlPi6N6Skp5z9oeJeW8p9X2iA49by6l/VQegx6GONuaJ+BAUI1bbHKYo0YTN7XllMN3xvQfsWTxVFSv0SDB+ksWT+HPGrUaJb38eAK0IwFY+1sTtK0hT1davmnTqgS5jIkLF/7Dmf+OKc86r8Xl1bUIwE93HTsSgB3tx7Jcl3B5/GOlXMYk/hYpWhr9B/xksy6Frj558rC6vrks8uadPetnDuvctl133Lxxhe8jzVt0Vp6hOyIgo21c5ODgvLx/yj3s7Z2+o1LRuG4Sf83BGQRBEAQh7UIhU2MdD1ITBEFIV5AXsEfydRFnk6REsj7wQmZdAO5IPuB0R9V6r+Pr8YMxdsBo/NDnO55HHUvNOrZAj6G98XpgnMcgvYjnLpAH0dExqNGoFl6rXgE3rtzA9cvXcGjHQWxZsxnb/vgbE1ZMsmxD4Z3n7ViMEb2H4fcFq7Fy1jKe7+LqyrmEew3vA1cZovzcoBBxJP4akPzOw7feeovz/02YMIE7jA4cOMDTDz/8kIKWqlStWpXDJx86dAilSpXiDmbK35sYJILOnz+fQ/dSJ9Kvv/7KHcp0/VIHKuXdoxDH5cuXZ89gOhYSVgnymA0JCeGOaArtSHl0KcchhVBOLXsTg/IlUohOytFIHkFeXl4OOwsJyqdL4ZVJiD579ix7XmkhPem8UZ7B5s2b83FSBzPVkxb6mkJFU9jkDh06sBczHQeFjY7f0fw8z39qlEfhT7VBAnT+aZ/P+5gEQRCeBN2XyAuWRE8aWEftFnmavv766yleVp48ebhdmD17NrcB1HYmlm6A8stT20TtK90zKUcvta3UZpCtYZQQFqqnJLWDtG+C2sZz585ZIjT069ePPX4pZQGJypTnl0RnOlZqk7744gtug8g+CqNsr46oXIpeQcIpDZSiXO3Dhg1L8TpKjfJoYNrRo2r+WOv26Hmd99SAHlECldPt7aU8j9206IlpjsQESG25YxHUVqCsWKk2ypatyuGJx475Gp90G8jnkq7/ZUumYeqUH5AzZz683byjZQ/GRDx31RLsC6rxRWk/s5fvqROHE3gt58iRi/P/kl3jxw3Gp90HW5Y9fHgf/fu25/126PR5ku1yiAMB2JGInlg58T2stWOKjAhPIDRPnDAUjx+H2Ozr895tsHfP32jzzsdo36H3E8NZ16nbnD2IZ88ai48/GWCz7P69O3i/XQ0ULlwSI0fPTXQ/zsZdeZ0OzqHm/hUEQRCENE+MiL+CILxAkAcwKIVN+nwYT5IATFA42WjE4KHpUWra89KROXsWHIv9z2Yeibbx51nzb9RJh8t+WjQ+wTwSYlt0bomzJ84iOjIKOfPngn8mNTeSdTmREZEY/PHXKFyqCMYtm2jTyRClbPdJow+xZfUmHN13BMXLlbAs8wvww/AZP2DAuIG4dOYS9AY9chXIDU8vGZ78vCFvfQ/YD+mYVMhTh8I2kncoCY0RERGcry5+6OOUgDxghg4dyrltycOGrrnOnTuzUOcIyt96+vRp7iwNDw/nkJHUSU1Qhy11WlNOQupYffjwISpXrozPP1c7v8hTmI6PvJBIAKbO6FatWqWqvYlBnegkVHfv3p3DB5JHFgnBkydPtnj2WkOd0i1btuTvJPDScVHuQIJyBrZt25Y7l+m8kbcXdfTXqVOHO56HDBnCYTrJ5oYNG7LHFgnE7733nk0Zz/P8p0Z5lK+Rwo3S8ZF32fDhw5/7MQmCIDwJaqf69u3LbRSlAiBhlNov63DFKQnd87p164bp06dz+0jtjpYvOD50D6VoETToiewh22h7omTJkjyIitoayq9O91eKXEFevSSKkUcwHdu8efNQunRpbpc0r1dKcUDhnikkNR1rlSpVuB2mtpAG6cSHBnedOHGCUxeQHdSuUZubWmJpSpdXt25dHiRGn+QNvWLFiud+3lOLDL6qF+LVa0CEfUdyp+LIozZuudHhsvjiJT03/fjTQnTr2gS/ThymPDtNRJ7cBZVjv4g7t28gd+4CGD9xJXx84kKCaWGOE/eQjSvfkWAaFJQbJUqUx5Eje1G7Rm72Zm3SrD1atOzMy4cMnYQL509hwrgh+HvLWuU5pyYePXrIovC9e7fRqXMf1KvfMsl2OSK5HsD2QnDHF48pT3LpMpVx8MAO9OrREk2avs9l/fHHYvzx+yLLMq38Fi0/wPFjB7Bg/q88eXv78j6Cc+ZVnqmro2XrLjY5gFu3+Yi9tMf/PAjR0VFo884nnBv62NF9+HZod5w/dxL9+v/4VPXxvPH3A7LLI6sgCIKQnoi5+eR1BEEQ0hMxtwGXpKXKSmskWQAmgnTZEGuKxWOEpZY9QipBXriFSxZJdJ3LZy8h5EEIipctnuCF3s3dDZXeqIJdG3fg5pUbNgKwhrevD4qUTt9JsdMz9Pv0hfeTVzRDeWD/+uuvBPOpk5Jy0pJXz6NHj1gkc9TBQ56zGzdutJlHHZsaJLieP3/eZjl542oeuQSJmo0bN7bk1yVvIPLutQd5+GphEqkTlYRN6xDHBHXUUt5b6mymcJXkgWPNxx9/zAIueQJrXkspae/THD91nDdr1swS9lkLp7lo0SIWLK1Zvnw5f5KoS15J1FkcP38jHVunTp3YNhKotZB/9LllyxabdakMezzp/Ns759ZYHz9B15lmu8apU6eSXF78/RHW5cdfXq1aNfZWI/Ffy/OYnDIEQRBSAsq7G78dIOi+RF6gNJCJ7k10z07MK+/48eM2f1u3h0T8+ywNciLvUg0SbqltpPaBhEdqF5o0aWK3LFpGA4ZosMzjx49t2llqe2g/dI8le7t27YqOHTuyiKuFSibRlETmvHnz8qAcEnwpwgVNBO2PBunQ/umeTH87OnYSrbt06YL79+/zAB7XeO5v8evFGmojKVqGNfHrqU+fPkkuL36dE6NGjXK4nNqav//+m4VkTeB90nlPT+2Rq/IWmScXcOeuMt1ztjW25MyVH590+4YFQXu07/gZsmTObndZ1ap1OWcsCYsaWbPlwNz52/HnH4tZaL116xp7BVeq/AYaNX6PwxFbQ0ItLc+QISD+7pn8+Ysq28Q9n1J5ZcpWQWBgzgTrTp72J2bOGIN/D+/G40cPOd+tRsaMWbBg8W5MmzoSv69dwOu5u3uieIlyeL99L9SqbZuG50l2OSK+ABzfS9re+g6X21k2eswCfPl5W/z151KeCMq9PP6XFfjnnz9VAdgsmOfLpw58zJuvEFq2+hC3bl7DjRuXcezofmz9ex0WLfwNS1ccgK+vH6/n7u6BqdP+wuefvYNfxv+PJw1aZ/j3M1Cl6ptPVR/PC4PyqJojUPW4FwRBEIR0g/Gh0t6nwRGCgiAIzwINbHkZBGCCwsteNl4XEfgFJHvOQLi6uWLL2s34sP8nyB4c1zES+ugxfl+whjsyi9kRfwXnQuKvn86+J09yIfE0fr6/1II6mwMDA59qG/IacgSJe/HFXWuoA9bzGRJoJcdeR/uhzmvyyKXv1DFPndXkNeUIEpwTKzulbHue5z+ly6NOf3vevc/7mARBEJ7Es7ZHTwO1jdrAmKTg4eHBU3xIFLUWheMfQ3yRNv5ArSft3155zzNiQ0qWR3Vu7/if53lPbTJnAnyUpvXKdeWdOObJ6z8PyCu3R8//OVze54sRDpe1aPUBWuCDBPPp+apR47Y8PYlWrbvw5Igff1pg83elyrV5sgd5syZ2LJTXtnuPITzFDxP9tHY5YtXaozZ/u7m549jJWIfrT5y0miPb2Mu527xlZ9St39LGY5qE79nztuLqlQu4evUCLyv4Sgn+LVaoWEs5/qGWfX03vBdCQu5jyfL9yv0s7l2VROeRI77A9GmjsXTxVHTo9JllWZasgZg1ZwvnAj50cCfCQh8hKDgv53S29hZOS5DomyM7Pfc72xJBEARBeEpibjnbgnQBPSv9tXEvsmT2R/myiTtspQRnzl7B0ePnUfP10srzT8JnNOHpuXT5plKn53DvXggaN6BBlinf3/g8r5Nde47xdUK83aQ6vLye/K7+UmEMVfOb69Lf6MynFoC1HKMiAr94UD7frgO7Y+zXP6JhkTc5FHVgzkA8vPcQW9dtwf0799F7eB8bYVhwPqkh/grPBwrLTCGKa9eube4o8+bci448oAVBEARBENIapOPny63mBX702NnWvLw8bWjnpGKwo0ImVhZ53bo7yEijLrPfmRQUnIcna0h41yLaEEeP7GNPZmvxlyCPYhKWSQC+fj1hTnGiZMkKPKVlyDE6WxY17LMgCIIgpEtiQ5xtwXOjZv0eOHjYNoWju7srsmfNiOCgrGjcoApavV0LAQEJ+2w/7PYDZsxZx98Xzf4fWr5dM9XsPP3fZZR4rT2ioqJRtEgeHNs3O9XKehmgQZdde/2IydNXW1K5nDgwx64AvGXrQTRt8xV/b9msBiZPcBzx6cChU6j1Vi/+3qRBVcycPOC5XidTZqzB1Jlr+HuN10uLAGyP2AeAy0sgABOaCHzNdEtyAr9gdOn/CYd3Xjp1MY7tP4Ldm3bCO4MPSlYshTYft0W1+vZDqQnOIViXHRl0MnIrvUL5fikUpCAIgiAIQnqG9MCgQOBhCHDzFmA0Odsi4UWExN/jxw9g/75/ULZcVZtly5dO589X07jI6wgSzYMDKQqBsy0RBEEQhOQSC5jCnW3Ec+PRozA8fJhw9OOtW/fx79Gz+P3Pnfjy64mY+ks/tGhWw2adU/9dtnw/efriM9uydMUWXL9xF68UzIk3a79ms+zCpess/hJnz11jBxSK8CkkjyXLt2DS1JWWv11dXRwOjqxW5VV4ebrzuVm4dBN+HtULnp72R0rOW7TBcj01bVSNPxO7Tshjd9+Bk/D29kTHdm890zEJSYQGuKTDMNDJ/rWTCEyeh55wxw3TnZS0SXAyletU5UlIu7jAwIMwPCGjcQRBEARBEIS0gV8GgNI9X7kGREr6NyGF6dn7W3T9uDHat6vBOZhfeaUEoqOjsHv3Zpw+dYTz+dat19LZZj41mTOq4dQFQRAEIV1jfDkjhZKg9/Oonvw9IiIKN27e47C9e/efQEhIKFq+9w3mThuId1vXsWzz0w/dMXjYdA7t263L289sQ/9Bk/DfmSto3aJ2AgH4jZrl8GXvd7Hv4Cl06dhIxN9n5J+d/1q+P8krlyLp0HkfPXYBDxhYs26H3fUpncnCJZv4e8aMGdCgXiX+nth1Mm3WWvZCzpY1owjAzwtj+nSEfeZffEadP9x0brhivAEjjClhkyAIieAFDwTrA1kEFgRBEARBEIS0hKvyhpk3F3D7LnD3nrOtEV4kSOBdvHQvZs0ai317t+LA/n/g6uqGXLkKoP+An/Bu227pqlOTTCWv3ySkQxcEQRCEtM9LKgC7ubnigw6NbOZ9O+hDLF+1Fe92HMKicLfPfmQhNmvWAF7+Wrmi+H35yBSz4crV2w6XkXfqiG8/SbGyXnZIyNWoVKHYE9d//526LAAT8xdvsCsAb/3nsHIO1fzZbVrU5muKSOw6uXxF8m0/d0w0wplCXemcbclTkSJvRz7wQn59Llw13kQYXp5QD4LwvMmkC0A2nQwPFwRBEARBENI2WZRHVh9v4Op1ICbG2dYILwqvFCqBb4dNcbYZzwx5y2fLCujTV/+RIAiCIDjGFO1sC9IUzRq/jv592mHQt1Px4MFjLFy6Ed0/acHLKDz073/u4u99erZBntyBNtv+s+NfzJy7DidPX2IBOX++ILR6uybebmKbmpH2ffPWfYSHq6F3KI/sp5+N4e/16lRAw/qV+bs2r2jhPOjapZnNPijs8PTZv2P9pn24dfs+smfLiPpvVkT7tvU4vLA18xaux47dRxGYPRMGfPk+Nijb/DZ9Fc6dv8a5jil37ccfNLE7IO/Qv/9h6sy1OHzkDB4/DkeOwEzsrfxBh4Y2+WbJc3rm3D/4+/DBXfhzwm/LsHHLfowa3g3bdx7BiVNqOOTen7biurGGvGn7fj0RYUqdUPhlEr91usQfuHbsOsJ1QPuldYsVyct2lStT2LJOaGg4+n7zK3btPW6Z983/pnAdtW1dB5UqFLe771dLFEBJZaLjpnNO9e3nZ5vOkYRhjfffrWf5bu86mTP/T7bhwOHTPP/R4zDL+c2fNwd6d29ts+/Vv2/n8NNnzl6B0WhCPmUdykfcvGmNROvEmm3bD/O5O3PuCgwGPQoVzIVuH73Nx/XyQQ6w6cspL8WGx7oqu8qjD8It013cMd1Pqd0KggC6rRgQrM8Gb6S/ROOCIAiCkN6RdKaCkDw8PYB8uYHrN6lzwtnWCILzoRRxObKrgyMEQRAE4cVCRvzFp2O7+izSEqt/32ERgPfsO4EJk5bx9/favGkRgI1GI7p//hN++W25zX4o1+vCJRtZmF0yd6hFMCWh9OKlG5b1KAw0TYS/n49FANbKqvvGazYC8MHDp9G09Ve4dPmmTXkUqvinCYuwcuF3KFI4j2X+pr8PYOrMNRym2FuxoXffcTbbkSBM6yybP8xm/sif5qHfN5P4+OLKBtb+sRO/TF6OzevGIjB7Zp5/6vQli70kYn/efzxOm3PhknBM3rHacnd3V4z+7lObsv7auEcpbz5//7Bjo0TFXxKLe34xFuMmLrWZTwL8b9NWoX+f9zDMLEKTyK6VqzFjzjr+LPVqAYcCMNHunbosAEdGRmHZqq02IZujo2OwZMUW/k45nCuUL2pZZu862bB5Pw8O0AgLi7CsU6VSCYsATPtt034wlq3828YWEtjpWqLBBAtnDX5i9JwBg3/D8JGzbeaRx/KUGWswb/pAtGn5RqLbv3ikv96hFI+PlFWXCb46bw4JHS03fkF4ZnzgjSB9VhaBBUEQBEF4/pjS3zO+IKQZSPAKCgQehgA3bsnvSXh58fIEcii/BRd5rRMEQRBeRMQDOAE5g7OxWHrvXgguXr7xxPVJaNPEX/ISbd28Fnx9vTg/LIUIXvfXLhZdJ437gtepXaMsrl67jT837OG/cwRmRumSBfl74VdyJVrW7dsP0LB5X1y7fof/JgGTtt215xgOHDrNQnKT1v1xYPtU+PjYOiTR8Xwx4Bf2ACVR+vqNu5iz4C/ExsZy6GsSkDXxmbxrvxwwkb9TvtounRohwN8Xi5dvwc7dR1nw7fXlOCycNSSBje27DOOyrCFvWyqbPGlnzfuDvYTd3d0syydMihPPe3VrlWgdfDdqjkX8pfpu2rAaYo2xWLZyKwurdD5y5cyGjzo3YeGZcvMePnLWEq65ds2y8FDKpnUSo22bOuw9TPUzf9EGGwGYBOu7dx/ydxKKnwSJzXfuVsK2Hf9yjmk69jcUOwjyXNYYNXa+Rfwt9WpBFpAjIqMwaepKDh9NyyZPX4NPPmzqsKzzF65xHRFlSr3CuaSjomIwbOQsPm8ffvoDmjaqBg8P9yfa/eKQ/l5mUyVBjic8kF+fGzdMt/HAFPLkDQRBSIAeOmTTZUGALoOzTREEQRAEQRCEZ4JC3pIAduU6EBnpbGsE4flBjidZMwMB/s62RBAEQRBSEVOssy1Ik5AnLomYd8winyMot+z3o+fy9wwZvFl4pXC9RP/P38OrFTqwWDtt1loWPTNl8sPUif3w4MEjBASpgmK1KiWxYObgJNk17tclFvH3sx6tLZ605KX7QdcRHBKZRGD61DyXranxemn8vmwkXF1VealcmULsvUys/SNOAF61djuLq/Q89Oeq0ZawweSJXLRsOw4fvWrtPyyOGgy2o+So3np92gpdOjZCUI4s8PHx5JzGHd6rj7ETFuPOnYcsOGteqOQNrYVMJm/nokXyJFrf341SPVspfPXBHdOQO1d2c31fQLlqH7DX7+Bh09Hp/QZ8TtYs/QEdugy3eODOmPQVgoOyPrGus2fLhDq1yuGP9bvZQ/rmzXvIli0jL5u/eCN/kqcyibRPguqDplIVO7JXMV1fZFd8yLua6j1b1gDs2DQRnp6qSEuDCgq++g5/X7bq70QF4FP/XWYvaYJyF7duUZu/00ABOhbivnL9BWZ/iQTg9JcCOHUEYILEqxy6rPDX+eK68TYiEZVaRQnCC4ef8ruhXL8uqfcTFQRBEARBEITniqsrkDcXcPsOcFeyBgkvAeSQEpQDcHN1tiWCIAiCkNqIAGyPhyGh/JkxIHEHn01/7+c8s0SXjo0t4i9BYu/hXdPx2LychNBnhUJSEyS6/u/rzpb5JLB+/7+PWfjV1rMnAH/Z612L+Eu0aVHbIgBfuBjn7fz90I95iomJYUGZwivHxKjXSs7grCwAU57je/ceIUsWf5symjSsijEjuicou+uHzfDzL0tYnPxt+mqLAPzrlJUsJBMkkiYG1TeFlCaovjXxlyDhmETmiZNX4MbNuxw2uXLFEonu70mQdy+JpmTfomWbuE7Jy3jlmm28vFqVVxPkgn4W/tnwC3/SNXXy9EUWvCkHMEHCMHlQawMAHPFq8fzw8HDj8zNg8GTOw/zWmxU5NHefXu+kmK3pC/EAToAXPJFfn4s9gW+a7ipNgTQGguAIT7gjuz4Le9ELgiAIgiAIwotIlszUcQVcuQbEyuuh8IKSKUC91gVBEATh5UCcWOJD4qEWwpjEzsS4cvW25XuRwrkTLM+c2Z+nlOLKNTWMcVCOzPD2thWUs2YNYK/Y+/cfWdaLT4H8QQnsIzGZBE4KNaxBIu23I2ZizPhFvD9HUOjl+LxRs5zddSlXLoVfppzDW7YexJmzVzgM89RZa3g51R95ACeGdX0XshMuu/Arue2um1yaNX6dw3mTEEtevyQAr/59u0WEfv/des9chjXkGd69z09YtHQzoqLsh2ePjTXana9BIcU3rPkJnbt+zyGfqb5p+qzfeB6g0PeztujSqXGK2p3mSSSndFrlud2Z/XUZkEHngzum+7hregBTOlTLBSG1cIMrsuozIQN8nG2KIAiCIAiCIKQ6nh5A/jzAtRvA41BnWyMIKYeLi5r32lPG9AqCIAgvEzq9sy1Ic8yZ/5clhC55TiZGBl9vy/f4eW9TAyqPQijfu5+wrOjoGISEhCWwyxpr79/4aMdMkPg7cOhU/l6saF40b1IdvuacwuN+XYpLl2863A+FN3YEeQGTGEllTZ6+GiWK5eO8xgTl/tU9Qah7Un3fvRcXspvCPz8rFIK5RdMa7FlNuY8vXLyO+Ys3WJa1bFbzmcuwpnnbb7Bpy37+Th67VSu/Cnc3V0THxLA3r/U5SowqlUrgxIE52LHrKDZs3sdewNt3HmHP7Y+6j+Rz+U6rN1LU9rSNCMCJolf+ZdVlQkadP26b7uG+KfHY94LwomNQ/mXRZVR+E37ONkUQBEEQBEEQnit6PRCcA3gQAty8RZ1FzrZIEJ6NDL5A9qzqtS0IgiAILxfiAWzNxs37MOS76fzdy8vjiSJZmVKvWL4vXr4Zn/dsYyNi9vryZ5w8dZG/T/u1P3tnEi4ucXlzIyOTnoKT8riSiEceqOs37kWd2uUtyyivrhZK2dqu5DBjjpovl0JLb/trAnsWE3fvPsTAb6cme7+NG1Rhr+rLV25hxtx1yGMO4Uzhsinc8pOg49dYvnor17cGHfvy1WpoZvJqplDIKQF5+WqhtSlc9bq/1Dy6FOr6aUVm7bxHRiU855ev3LSIv6VLvoJ1K0ZZlv3+584ki7+79hxjoZpo9FYVFoMHfdURm/8+gFpv9eT5f23c85IJwOnvId8pd2YXGBCoy4JMOn/2CKbw0ILwMmFQbhaZdQEIUH4D+nQ4ckQQBEEQBEEQUgr/DABFnqOQ0E/RbyUIaQYSfAOzAb4S0ClFCY0G7oabcD/CBF93IJOHHn7uzrZKEARBsIv+5Qx9Qd6yC8yenJFR0bhx8x42bt7PnpJGoxpid/R33RCUI0ui+yHv2NerlsTWfw5jz74TeK/zUPT//D3O9ztp6iqMnbCY1ytZooBF/CV8fLzg7++DBw8ec5njJi5BYPbMLFpSqGRHfNy5KZau+Ju/t/vgW/z4/acs9m7fdQRfDFDzx5L4+VHnJsmvHAUt3y/VxaF//0PN6mU4PPH7Hw5DeHhksvdLtlH44W/+NwW3bt3nifhImUcetU+ieLF87BVLOYnJo7XdB0PZc5js/W7UbBw5epbXa9qoqk19PwvVq5XiXMMXL93AqLELLCJ7UgTr+AQHZcH+g6f4vPf9eiLKlSnMdpJIq9U5QWHIKdcvLTtx8oIlT3NSoLrRroVPPmzK+Zjd3d1svMZTwjs6fZH+dBynDs2hsLc5dFlZCCOP4Icmx3HgBeFFgLzgaeBDJuWaF+FXEARBEARBEFRcXYG8uYFbd4B7951tjSAkHU9PICi7GvpZeDZ2X4/FPmU6cdeI0/di8cBOv7C3cq8olNGAYpn1aF7IFTl85L1aEAQhTaB7OUfohIVF4J0OQ+wuI7Hspx+64+MPmiZpXzN/G4CKNT7GzVv3MG/hep6soRyy037tl2C7tq3fxIRJyzi/bI8+Y3neyGFd0afXOw7LeqNWOfTp+Q5GjZ3P5bXt9L8E63z3vy4sOD8LzZtWx5hxi/g7eY1SfmEKPU2CcIXyRbF77/Fk7/vDDo0w9PuZlhy3FJa620dvJ3l7qu9KtT5m8ZjCddNkTZ7cgZj4U59k2xcf8uhu27oOho+cbRF/s2XN+MR8xfZ4r01drFzzD3//Ycw8/mxQrxLWLP0BefPkYDH/wKHTuH7jLnIXbsGe1xQim7zRSfw+euzcE8sg0XfKzDWc/3fi5BWYNe9P+GXwZkGZoOu78/sNntr29E36e+5ME68oJAQH6bJxKFwRgoUXEfJ6J+E3QOfHIrAgCIIgCIIgCAnJmhnw8QauXqfwa862RhASh67XjAHOtiJ9c+qeETOPRGPblRhEJuE3T17BB27G8jT7WDRez2nA8OoecJPXbEEQBOfyknoAW0MCZPZsGREclJXFOPLszJUzW5K3J8HxwI6p+KzfeA7DrAmbRK0aZTH2hx4s3sWHPIyp3Nnz/8T5C9fZKzkpjBzeFYUL5cKwH2bxdhpFCufG0G8+QPOmNZJsuyO+G/IRC9Mz5/7BdpHYSkL2kAGdkC9vDjRt/VWy951NOWbySu3W+0f+u1XzWk/lrUvlH9g+Fb37juP61jxnPTzc0KZFbaVeP0XGjBmSbZ89KAw0CcAa77Z+g72Zn5YWzWpgwczB7El88vRFDuVtzbL5w9Dho+HYsvUgHxeJv3QtTv+1P1av25EkAdjb2xNb/xzPXsCLlm1CaGg4TwR5rI8b1QuvPuMAgXSFPn2m8EwTArCGJgRTnmBVCA6BpIES0jMuyj811HMG6NLhCBFBEARBECDPo4LwnPHyBPLnUUXg0DBnWyMICXFzA4ID1U8heZy+b8TEA1HYfvXZRnpsvRyLqnNCsbCJF/L6yTu3IAiC09C9XALwvn+mJHvbwQM68WQPEjBJ2CPR9Oz5q4iIiEKBfEHInNnf4f7IE/Prvu15socpdJvDbTu3b4hO7zdgAfjW7fsIzJ6JwxTbY8ovfXlyREzIFru2TZ7QF6OGd8N/Z69Ar9ehUMFcLC7as+29d+rylFR27D5q+d7701ZJ3k6DQnMvmv0/PHz4GOcuXGMvXapvCq1tjxm/fcVTcin0Sq5Ez4c1iV0nROsWtXmyB53Dzet+Zm/dS5dvwlc5HhL7SWymwQQknFvj6NySx/bMyQMwceznOH3mMoftpmvU0TXyQmNIn6M+05QArOGqmEWhobPpMuG+KUSZHiIaSRu5IghpAW94IUCfARkgSaAEQRAEIb0jArAgPH8op2rOIODBQ+DmbeV3KD9EIY2Q0R/ImngaPyERHkYCEw5EYsV/KdvH03plGL6q5I6mBdNkN5cgCMJLgPLwZvAHYh8425AXAvKSLfVqwedSFome5A1LU2rh5+fDeWpTkstXbmLhko38vVqVkihbulCy90X2lS75SkqZlmYgsTYlchhT6OjndT2mWUQATnkMyj/ynqQpFOG4b3yIEDx2tlmCYBe6Xv10vhzq2TVt/7QEQRAEQRAEIV3g70cdDsDVa0BklLOtEV5mKDpfUKDqoS4kjyO3jfh8U7jd3L4pwfCdkbgRasTHpcQ1WxAEwSkYMokALDw3fpqw2BK2uVe3lk62Rnih0SnPlnpvZ1uRLNKNSuUNT3jrPRGr/HtgeqRMIYiE9AAIzscHXvAXb19BeOGp+JJEN3nWwHm6FI68l5qB/HQO/0jhfaciySonBYxLawEW05o9giCkLG6uQN7cwK3bwL0HzrZGeBnxVV71ArOpnulC8iCPXxJoU5tp/0YjLBr4rLyIwIIgCM8dEoBx1tlWCC8BFLJ58vTV/D1vnkA0aVjVyRYJLzTp1PuXSDcCsAZ5WZKHJU1hiMBD0yM8Mj1GDJ4tb4wgPA0ecEcGnQ/8db6c51cQhBcfD4OzLRAEQRCElxsKu+vjo+YGjpXXPyEVWLTwN4wfNxitWnfBp90Hs+CbLSvg5+tsy9I3Y/dHYe6x6OdW3oIT0agUZEClHPIALwiC8FwhLzlDZuVB7Y6zLRFecPbuP4la1cvw99bNa3NuW0FINVwCnW1BsknXypUXPOCl80CgLgvCEYEQ02NlCkU0nt+LhfDy4AVPFn19dd4S4lkQBEEQBEEQnACF382XB7h2HQgNc7Y1wovGtCkjcfvWdUwYNwT/HtqB5SuWwM83g7PNSteM2BWJpadTNt9vUhi9JxJLmno993IFQRBeelyDRAAWUp03apXjSRBSHcptrk+/kV9fGBXLEx7w1Hkgmy4zohDNXsEkBpMwLAjJQQ8dvOEFX7Poa4DE+xIEQRAEQRAEZ2NQHstzBgH3H6phoU0mZ1skvCi0bdcdw7/tyd+3bVuPCq+Vwdq1a1GoUCEnW5Y+mXk02iniL3EpxMRhp5sWfGG6vQRBENIHel91Mj5ytiWCIAjPjkuQsy14Jl7IJ2E3uCKTLoAnyhlMQvBjmhAGE6R3QHCMCwwWwZdy+wqCIAiCIAiCkDYJ8AO8lUf2K9eAqChnWyO8CHTq3ANZMunxxRe9ERMTg7Nnz6Js2bJYunQp6tat62zz0hUHbxox4YBzf5iLT0aLACwIguAMXHMBkcecbYUgCMKzofNM1/l/iRf+SZhyBgfoMvBE4i/5BJMY/IhDRTtnJKqQtiDvcRZ8dV6c21cQBEEQBEEQhPSBmyuQLzdw8zZw/4GzrRHSMwH+QNbMQK9en6Js2ZJo1qwZ7t69i9DQUNSvXx//+9//8PXXXzvbzHTB/QgTPvoz3Nlm4L/7RrYlwEPnbFMEQRBeLkgw0fsBxofOtkQQBCH5uOV0tgXPzAsvAFujU/6RVycJfdl1WThXcKgpAmEIR5gpnENHCy8+npw72pPzR3srf+kltLMgCIIgCIIgpGuyZQF8vYGrN4DYWGdbI6QnDAYgKDvgZRUAqlq1ajh06BDq1auHY8eOwWQy4ZtvvsHu3buxaNEieHp6Os/gNI7RBDRcknYSdO+6Fov6+V6qri9BEIS0gVtuIOJfZ1shCIKQPGgQiyGrs614Zl7qp2BX5Z+/TpngS+owh4sOQwSLwTSFI9LZJgrPCIm7XlaCL4m/NBBAEARBEARBEIQXCxLw8uUBrl4DwpzvfCikA3y8gcDsal7p+AQHB2Pv3r1o1aoV1qxZw/Pos3z58pwXOHfu3M/Z2vTBF5sjEG10thVxiAAsCILgJPQZAJesQMwtZ1siCILwlOgA9wLONiJFkKdgKyhctC+8ORwwnWMKGU2CcLhJnSIRJV7CaRgSdt3hBg+dOzyVbyT60t+CIAiCIAiCILwckJCXK1gNB33rjvJOZ3K2RUJaRKe872fPCvhlSHw98vRdvXo1vv32WwwcOJA9gckjuFSpUli1ahV7CgtxrL8Qg21X0pYL/o3QNKRGC4IgvGy45QNiHygPZM7NCS8IgvBUuAap+X9fAEQATgQSFClEsDedbLPTKInCEYhCpCmSPyOUT/oXC3mpeJ6Q97YH3OCuc+dPEn3dlHmCIAiCIAiCIAiUz9XbC7hyHYiSPkfBCg93IChQead8itdHyv1Lnr/NmzfnnMAPHjxArVq18OOPP6J79+6pZ2w64m6ECQO2pr0oaiFpzyRBEISXCBfALT8QecLZhgiCICQNnZvyopD+c/9qiAD8lJAoTH6lnjp3bQYTg1gWgiNMqpdwlCmacwyLx3DyofDNbsolSmKvm86VvXndlR+gh/JNwjgLgiAIgiAIgpAYbsq7e77cwM3bqkewIGTOpEwZk7dt3bp1sX//fjRo0ABnz55FTEwMevTowWGip0yZolxvL3f0qUHb0qbS+ihKwgAIgiA4FYPS+BoyA7F3nG2JIAjCk3ErCIoV/KIgAnAK4aJcFC7wgrfOS51hpU/GKP+ilCnaIgqr36P4rxjnGJwG0CuV5Mr/XFjg1YRe/lv5nwRgQRAEQRAEQRCEZyFbFjXX67XrQKwEbnopIW9f8vr1cH+2/RQqVAgHDhxAs2bNsGnTJp43e/ZsHD9+HOvWrUOWLFlSwNr0x8l7Ruy5nvKhnw06oHQ2A6oEGXD4diy2XHr6Mh6LACwIguB83F8BwsMAU5izLREEQXCMax7lATTA2VakKCIAPwdczP+g84ibaSUQxyr/Yvh/86cp8b/TKuSV68KZlA3qp86Q6N8i8AqCIAiCIAiC8DygcND58gBXrwNh4c62Rnie+PupgwB0KRREKkOGDFi/fj369u2LUaNG8TzyDC5ZsiTnCy5btmzKFJSOmHo45eKsZ/LQoVKQAVWDXVAhhwHe5lDd78JVKScavz1lWb7uEj1MEATB+egBj8JA+CHlu4zGEwQhDUKRClyDnW1FiiMCcBrAYP5nIf77Sby/jcq/+AKx+o+WUJZi9dNo0v5O3ohX8tAlkVanUz+1vw08GeCiM1hsd5VLSRAEQRAEQRCENIxBeeXKpbzT33sA3LrtbGuE1MagB3IEquJ/SqPX6zFy5EiUK1cO7du3R2RkJK5fv47KlStj1qxZaN26dcoX+hRcvXoVI0aMwNChQ+Hn55eqZZ1/aMLfl59toHrRzHpUDXJB5WADimTS2034RPM6lHDFxosxOPsg6eJBDh8RgAVBENIEFDXTrQAQddrZlgiCINii91YjFbyAiGqXDlFz45L3rHkorKP3GXnPEQRBEARBEARBsCGjP+DjBVy+BkRHO9saITUg0TdHdlX0T01I6C1cuDDq16/PAnBUVBTatGmD3bt3s3cwCcXPm/DwcHTp0oXDUv/777+YPHkyChYsmGrlbbyQvLRWFNa5dh4XVFY+M3rYdl48iAT+uRLDYaW7lHRDsK+6fOSeyKcSf4ls3hJ5TBAEIc3gkhUUCxNRZ51tiSAIgorODXAvCryg0WpFABYEQRAEQRAEQRBeKtyU9/x8uYGbt4EHD51tjZBSUJhnCvfsn7pOrzZQ6OfDhw+jcePG2LVrF88bM2YMz1u6dCn8/f2fnzEKX375JYu/xMWLFzlfMdlTp06dVClvx9WnF4Cr5zTgh5oeNmPWL4WYsPVyDE+Hbxk5jtm31dwt4u+K/2Kw/PTTlxXoLSPjBUEQ0hQugYApFoi+4GxLBEF46TEA7sWUlwh3ZxuSaogALAiCIAiCIAiCILx0kFiYPSvg6wNcuw7ESkq6dI27OxAUCLi5Pv+ys2TJgm3btqFTp06YPXs2z9u0aRNKlSqFP//8E4UKFXoudkyYMAFr1qzh7xkzZoSvry+LwOQR/Nlnn6F79+4pWt7jaODonaf/4bxXzM0i/obHAL02huPgTWO8dVzxZl61y+rIbSN+2B2ZLBuLZU5lN3BBEATh6eE8m0oDEH3F2ZYIgvDSorw0eBRXwz+/wIgALAiCIAiCIAiCILy0ULjgfHmAK9cpfK6zrRGSQ6aMQJZMzrXBxcWF8/9WrFgRPXv2RExMDIuvZcuWxYIFC9CwYcNULX/jxo0YPXq0xZZffvmFw1OT6Evi9I8//ogTJ05waGovr5RJjLz9SvLCP3ffEI6BVdzxRm4XeLoAQ6t54MvNETh+VxWBXws0oFsZN/5+J9yEL7dEICaZAzQq5BABWBAEIU3imgcsTYgnsCAIzxvy+CXxV+fpbEtSHRGABUEQBEEQBEEQhJcayhWbOxi4dx+4dcfZ1ghJxcUFCA4EPDycbUkcXbt2RYkSJTj08t27dxEaGsrhoQcPHoyBAwemSplnz55Fr169YDKZ+G8qq0KFCvx9+vTpGD58OKZNm4Z169bhwoULnBc4KCjomcs9dDM2WdtFxABf/R2JU8WN+KS0G7J66TCpnie+3xWJg8o+h73uAYMOiDYCfbdE4G64KVnlVA02wF30X0EQhLQLeQLrDJITWBCE5weLv6++0GGfrREBWBAEQRAEQRAEQRAUMgYA3t7AlWtAdLSzrRESwy8DkC0roE+DKV6rVauGQ4cOoV69ejh27BgLs4MGDcLevXuxaNEieHqmnLdBSEgIPvjgAzx+/Jj/rlu3Ltq2bWtZbjAY8M0336BYsWL46quv2AuYBGASiZ+VK4+SJ8xqzDwajdP3jPj2dQ/4ugGDqrjjQaRybs39cSN3R3L45+RSLVi6vARBENI8lBOYEBFYEITUhjx+2fP35RB/CXkaFgRBEARBEARBEAQz7m5AvtzAzdvAg4fOtkaIj14P5MgO+KTxdF3BwcEs+L733ntYtmwZz6P8vOXLl8fatWuRO3fuZy4jNjaWQzyTV6/Ghg0bMHPmTLRv395m3bfffhv58uXDxIkTWQhOCa6HPnvi7J3XYtF+bRhG1fRAPn89/M39cSv/i8GK/5IXYlqjZm7p8hIEQUgXkAis8wAiTyp/JC+6hCAIQqIYApQXvcL0xdmWPFfkaVgQBEEQBEEQBEEQrNDpgOxZVZHx2g3A+Ow6l5ACeHkCOQIBl3TSb0OevkuXLuUQzOSFa1QuJPIILlWqFFatWsWews/C999/j61bt/L3HDlycOjpP//8k717ydP3f//7H9zc3CzrU7mTJk16pjKtuRTybB7AGuRJTPvK5x83j3L3Fsqox6l7yfvxtSjkahGTBUEQhHQAiTOeJYGIo4ApytnWCILwIuGaU5meffBlekQEYEEQBEEQBEEQBEGwAwnA+fIAV68D4eHOtublhQT5rJmBAH9nW5I8yOO2bNmyaN68OecEfvDgAWrWrInRo0ejZ8+eydrnihUrMGXKFP7u4eHBYZ2LFCmC8ePH48cff8TChQtx+vRpFnyzZMmSkofDhKZgiPQPSrqiRi5V1X8UBXi7Atm9dZzDN7kC8PvFXVPOQEEQBOH5oPNSGrVSQORxwPjY2dYIgpDucQHcC6kDTF5SRAAWBEEQBEEQBEEQBAeQt2nuYODufeD2HWdb8/JBIbmDAgErR9Z0CeXm3b9/Pxo0aICzZ89y+OZevXph586dmDVrlo2n7pP4999/0a9fP8vfo0aNQtGiRfk7hYQuXLgwevfujYMHD6JRo0ZYvHgxcubMmaLH452C+mqgt54/o41Ar43h8HXToW5eF0z9N3kqc8P8LiwgC4IgCOkQndIeepQEoi4AMVedbY0gCOkVHlBS7KXK92uPFBeAo6OjcPnyBcvfJuUfTCbodHro9TrlL3oIj1Hm6ZR5LsoiozqcV1lNpz7zK2sof+tMPI8CCtG2vIp54Cftx2j+Q0cLeK8G5X+j8qnnfer0el5mNMZCr9OxHSayg/5RQTres7I8htejyWRUttbreT22XfmksgCd+Vi08tRlvA2VZV4OvWKTSd23nss28f5oS6NRPQ7VVh3bZ+KZ2o5Nln1SfcHm07qGrZY9CbOt6vYmy3HY7NCyjnm5znr9uK2eJrCTycHubc22tkU71rh6td2RLm5fujhrtPNE55z/1pkSHKZ5t7ydzmobbXudXm9lh7WN2o6syjP/F/caaVuf1nVkOQaea+c4LHWisyrPTkVp59/qJMTtTRc3Wxc3T10nzhqaZznueO/AvEz7ocXVjOV3a4K1sXHrBwRkho+3LwRBsCUsLAyPHj1W70fmdoDQae2cydy+WWGycz9Xf9vaPc78G9Zu0eb7dcL7s6M7tePOL1O8pba3AlP8OQ62flLnmrofagPj31/V+yEdX6x2s9Y+bO555rVhc2u1FKsztx2A1c3Q6oBs7s5xzarlph53z41/KkxWMzXbre+ZlucF8zyTyWR53tD2bzJZrac8M5isttX2r14n6nax9GxgMtk8i5gsf8ffn5Vd8do3wsjlJXK9JWhX4l9Purhj0cWtpDbHOnMZJm6H1fNjOVNx7ZC5vk3qxWtpu7T6Sfhk4uiKpHWN5i20Z7GEW8SdX5OlwY3fImttJT2rGQwGvFqyGNzdX+4XAkEQkkamAMDbS/UGjk5B70fBMRkDVM/fF4VChQrhwIEDaNasGTZt2sTzyFP3zJkzWLduXZI8dWNiYljkjYyM5L9btWrForI1derUYQ/hDz/8kHMRU3jo1IBE4JTwBB66I5I9fcNjTDhyW+3r2XE1+TkgO72azkcLCIIgvPQo72xueVWvvchTyt/y4CUIwlPgojz7uuVRvuiftOYLT4oLwCEhDzFr9kSLqKozd3S7uLjgyNFTPNK1UeP6MMYYsWb1H3irQV3Oi6PTGxBrjEVkBLB27WpUqlSBX2yOHT2hLPfAm3Vrw8Q3+1jcv/cIGzZshl7vgnr13sThw4fx4H4omr3dCKtWruJOvwKvFMDJkye57y84Zw6UK1daKcMEN1cPrF71B6pWrYo//1yPpm/XYztdXZWLwegGk2KDweDKZVNnYGxsNMIiwrBi+VplPYOyn7I4dPAQXFxdUbZsGeTLH6zs00dZPwL37z9WXt4WKy9zjXH58mU+Vh8fP+V46yJWOV6yxYgo5RhjMGHcVHTs9B6/lPn4eCu2N4W3rwdio2O4Q1LtzI1V9mviurN0tCr2qaKhlVBqRptvLVjrzcInjMr+WDinjlyj1ba2graG0SrJlSaKG606jW1tUDukaQSzweACrQtZFbyNvC+dWQjhOjDCLK4buDOczqNaXty6VO/qvmhvblBWVZZFK+fJjc8NrefqakCMUqYOage0wcWg1JUB0dHRZuFdx2XFREWr16JJFeFpkAKVzWXqKMyUntdn20wxXK4x1sTnmzrP9QZVtDAY9OZr2qB2devUQQxkN61DuCnXhYuLBw8siIwO55dyY6xSni6WO61NloELenMduFjmaR34cYMMjLye0WglepjPjdrZToMIzL8vNxcbkUA7f5bBDZpYbvVdbxa/rc81nSMX5Vio/tWVdFzf2n71ZjGgRvX6KFq0FARBsOXChUvYu/+Acr+NRawuRmmxjKreazLAYHSFzmgwq2cmixgYN85DZ76fKfcUnclm0IqVlsX3Wh4xRb9hU9xwjzgxlbZXBxyp4pt6/zPy7d9kvt8ZoMlh/NvW6WwGOWkDPoymaG7HtcEqNCZKZ24TVNv0fB/U6+LuJzRwitYxsp20gdI26NX7XWysyTyeRL2H6Q0GNiNWufeqJqsDvEzGOPGZy6HbFN2XaSCZ0cj3Kk1spfqIjlLtpPnUTmr3QVoWExNrrmsTf+c6ofViYxAVE2lZl9ah+21stLKesg9arm1PnyzOKvN4H6plSnui/K3M4/2Zy1PLUu+rdP+MNZep3X9pHSOroXrLsdJ+tXOotnGx/Aygif9qmeogNd7eGDeAybJPrnu1PeN2QqmrWGUf0WaFQnuWoHXpU1sP5oFxJITqrfZJdmiD4/gaMbdzPDBOp54LOi6qAzedOz878eA+5dFSD7VN1RtoHeUYqT1X9h8Trbbf6sVoFn/NZfEgPqVtdqU22Hzc9EymLOX2V6/sR69cJ1x3Jnp+0POzlVZvVF8GvvbUa4RtpTYU2uA69bcVS9cilGNVfgPuyjOht7c3lq2ciWzZUj40piAILyYe7kC+3MCNW8DDEGdb8+KiNFvs9evp4WxLUp4MGTJg/fr16N+/P3744QeeR57BJUuWxOrVqzlUdGJQmz527Fh89NFHuHXrFpYvX87bkBBsTYECBbBy5UpuU6mdJ6if4o8//kBISAgKFizIQjH1xyT7WNx0CI1ObMBg0ll0MmU69ymcdLDvkwYoCoIgCOkCg7/yMFAGiDoFxD5wtjWCIKR1KIKA+yuA3t/ZlqQZUiUEtF5vq6xTZ9+tW/ew/Z89eL16FaxeuREVK5bDrZsPQR6zMcZo6M0dyQvnL1DWqYZVq9bgnTbvoM6bdbB580YYTWbh06iHl5cXGjdpgvV/rcfJkyfw8EE4cuYKwj/bduONN+vi4P4jCAuLQI0a1ZRyQ5T5f6N8uXLQIZY7oG/cuItpU+chMiIa167ewxXlJSjGGI68uQohNPSRMoWhVKmSZiERLAg2bNAUf/+9HZGRMaheo7qyzS0cPPAvXimUD5MnT0HLlk0x/ufpaNn6LcyYMQdZswSiStXXsGH9Zu4EP3jwEDw8PBEcHITff1+Pu3ce4uKFKwgIyAJXF1ecOnUW5coVh1HzVuGOYurIjTF3vtvWrbUAq3XE23qdqh2gJrMntEkT/kzx8+eYZQcHQqG1KGy9XPtbE3ZJUNVbRAFN1DBaxEVV/I0TqLUXUO7AjTUL0iZVtFW3dWPRgjpo9TpX8zYu3BHt5ubOVlOnrrurQe3IJpE2Vn2x9fJURWjVM1jZjoUOtWOZ7NQ6vlnMIDvMx8GiheaGDr3Fk8mknD8anEAd1zxPr4PFk5w1ZFWgNZjF0pAHYWaRwROuBjdExz5Wrt8oZR1NvI+rP1sPYdjUt7UgbM/znAUFl7jzpnX+O7pOrH+f1p5ltvsGi+ouSr2QSECT3krsIRGJ962TF2pBsEescq+LjIpWfih0D4jmtotw0Sn3LRI3Y9TfLmu3MFkiRahOlqrKy+KnLm4+obPyetRrgrF2b9CpcqrmhWo039N5MJEOfI+l+eqdECx+sWDJ0TLUNjrGaiCI5fdOraYpmrdikTU61jwQBhYRksXbGKj3SOX+R+2mdt9RxUplXlQkD+BhHddIYp+R55MN0WZxlYVbbqKMvA9NtKQj5oE+VHdK+eER4WbR26RuzwJstOp9q7TxJBiqYi5YCORjMw8aUl1Q1YFpRhZ7Y1WR0nwuVOHcRRUXoQ76oXaB6w9qZyuhtWdaG8FtB8BtE4VujIqKUI4rCq6uVnERzfao51cTXal90vGJoVs6RyxR1vFQ2rVovk70an1FGZX2hb7TWXbltlXPUVWMLNBrdU3tH+2T6o6+a+0vfddEYuv2wmhlB5WrNz8v6Lkti7UIxsYYsxe6Xo2qQgOnqO00mQcDuNHgOhKzaWCTYmOMSWdepq5PurFBad8NsS7K846bWi+a97UJ3N7QOUZspPm4XKBFyIhVrpuoyFC4ulP7r1xbseQhrYOL3l15tlL272IenKVX21LSmWlwWFRUFKzdli0DFmigF9mjlOOid2PRWjx/BUFIDnT7DswG+PoA126oA1yFlCODL5A9q9pGv6hQuztixAhUqFAB7777Lg8cvn79OipXrszhoFu3bp3o9qVKlWKx+OOPP+Ywz3379sXx48fx9ddfW55ZCBKbNQ4dOsQicbSV+3pAQACGDRuG+vXrJ+s4Ajx1uB6aMgJwSpDHT4cuJcX7VxAE4YWC+oXdiyvvjHeAyP9AzmGCIAgJMGRW7hUFIFlvbUn52tCZ+1hh7pzWqyIXeWi6uLghNPQxoqLCkStPIDy9vLgne9++vYiIiIanh7fydwxCw0K4NzQiMhTLVyzB++3b4vz5s7h48RJ3QpYrVx7bd2xF+ddKc+fi9Wu38ejRfcTG6HHqvyNKMxCOipWrKC9Rj5WXqBtwdfWAQSk7OjoUBr0LPNw90aFneyxasAxrVq3D22+3wPwFc5DBOwh//fUXSpYsgWvKy1f+ArkQGxsFN3cDdvyzC4WK5Ebx4gVx9/4N7kj19PTiTspPPumq2PxQ2X8kQkLuWzpxyYuSO0+VlSpVqsTH/9df67mDmcKE3r+vbBNFnqw6uJi9XfUWAVitP+pMVjtp4wI0qp62BhuRz9rjM+5TZxXC2mTxFtU6izVvW+uIw9ZeofYEX/MpVjuxLR6ncSEoeTvFNgN5dEfHspDLIgB5MpMbr87aZsrn5MKdt+TZ6+bqzi+reu7ENnAnPX+Hq+pdZvaIUzuVTea+fF1cZ7xJ9TjTsVeV2rFMHf9q57fRPIhAH3eB0nowd5CbvZCjle3d3dzNHrDq9UvCsZtio5eHK3eAa33Kqoe1JqAaEaW8tIc8fMjiBszeuWQ3eQRHs3eX5nltLbJrDy1xgqp1qE+dOU6mqttbuQDCPN98rgx6zQMqbt/W583eeYwrB1zXWth1gyZGmWARESzXi1mI1+te4N4YQXgGjCxqGhFL6QWg3rv53oJIFrDo/qN68ALaIA8WRnmgidlzlMTO2BiLNyvBnqX0N+0vlgRbzTPfyCKoKurFWjz2tXks1sbEmiM46NhjkssnO6DayV6qvH8jC3GaWMietuZ7lNEsrLLVJnOEB2XfUeR5ax64o4qttL7REuWAA8mbBx9ZD1ri+4o6Dki9n5hshVUefMKDewyAFlCY7u/k4aqsT4Kz1hZZ7qlKuRzBwNxm6k1qSghXjg7hwjbFDThSt6V7vMGgpoOgAUnUDrFQr+yDtlGjX+hZtNS2Y0FYp9qtttXq/dHNTRVlaXLl9jba0pZzvZnbLRq4w56p5nPI93qTKhjHxERym+jiEsN1T4eiOt6S97TOfE2Y7/6mOA9ubWCTJvJyvWrPCNAiiMRF/7A8M0Bn8STWRGHtHNHxu7gq93sXPQu31AKTYK9T5hsUWz08vLgOY2LJw1dp85XlMTTwSjmx5M9rMj//qW7jLizY0qAuF6WNdSHhV5lcaehCrAkZ/QPg423A40ePlOciGhRgfgZSnr8iox/j8eMH9CNR1nVhD2OKDAI+X27wyeCh2KrD49AQuHm6IGPmAH7euHf/vvKcdZ8HR2jPLOQRbdSp16feZFCOy50H5xleZIVBEIRUxUd5fc2XB7h6DQiPcLY16R+6HWvC+svC22+/jd27d6Nhw4a4cuUKD2Jq06YN5wUePXq0ZeC0PbJmzYoFCxZgwIABWLJkCWbOnInTp09jwoQJLOzGh0TjL774At9//z38/f3x4MEDbiu7du3KIjAJ0U9L2WwGHL+TdkZAjH0j+d7MgiAIQhqHxB3PDEDUf8qL+X1nWyMIQprBoAq/BonsZo9U8wC2yZGrfPr5+yKDnxcePQpFseIFce/eHUREhuHOnTuoVKkyNAGMwkPeu3sf+fIVwPFjp1C5UjXs3X0IlauUR4ECeXid/fuP4cH9MFy8cBUeHu78okiDWPPnz42tW3eiZo3q2PHPfoQrb+GZM2dl70sS2rgzlzu8I6A3RCM6NhxZs2XC2XNnlH2Y4OZmUF6wyLskij1KdWbvlrP/XcWJE2fh65sRW7fsZc8eX58AREaF8fH99tuvaNnybZQpWwy3bt5HoUIFERYWaQ5xDO5g3LFjJ7y8PPF69deUF61Q5SVvj/I32R5r9pSNsQi5mreO6o2qdTBrgp3O4uVj3/sXNp2/mhCszof5u7YunRv7l4CjMNN6c8hRttWyLtibi72lXAwcQpM6ejNkyMIeUeRNpdaFyXw9gP92d/fkc0LCQpRyAo2xau5DnV7dBwvYRrNHMYvqakc7CRTUUa6KHNFwdTNfb1C9tUnIjFXOEYnneuXvyMgI5Tpx42ONioqBu3LNkMCsCgzullDTWmisGPJgc3VjUYAFZBdX5Vox8qe1wG6W01WhWrHt7u27qte4eR0D16Ha4a3mqI6F1lkfh7Uwaw4LrdNyVrP/sXkVc7hWqzCiqsBvYLE6JibaLAAYWNhx5PVrTwi27Jf+Uaht8qTma0fN6aj1i/O5N6rXqHWOYUEQ4jh3/jxWrlnLEQlM5lyupNiZNI9LEqHMofyN5lDG6iAPo5pLVRNIOWyx0raZvVe1kLYsQNK6UEMma2KqdXhhTUCF+Z7Gg1XoNw21AzE2Vm1fDC7qwBqjVTuitT+qF63Zq9KqzVHvU3EDjsh+tWPSZBGBtUExcfdWHUdDUAVNGsCkhRGO5bD93CZY2gezOGr2iNbDHK7YoDMPeInle66LKW5ADd/7XQw8pIe9Ys2hmLV96Q1ki9rW0r3UlQcaQWnDw9WwwXSvN0bzfc/dzTwQRrnfU51xGGTl09WgMw84iuX641DL5nNoMsWYwyNHscjr6q4K72Q/C4vmtlcTW7mtJCWYrhFuP3Qs7tIxxMaoHsrk5RprcuFwx2Fh0Uo9eSpluSE6itolvSoGm+LCXWto7Ri1RTzfAMu5NMWtZL7nq3ZxuwGd5ZqMO9c61VvXCI5U4uLqDnZMNrjC4OrBg+v4IlTqM1xpz4107ShtJ03kfxtD4adpMBXVu169eMkD3qQ8E3gox+YRbYKXUY8MLh6oUKYMXimaHXfu3sO+3UdYAC5QIC9KlCqo1EUkNmz4E+dOX4CbzpcFYlelPigXfcaMGfF6zTLwyeCG31f/hWzBWVBFec7yzeCNc2cuYfnyNexNxdeoSQ3tbdKraRRMSvnubp7KM4QbdDKoSRCEZ0C5fSN3TuVd4B6gvA4IyYSiEAdlV0M/v2xQ6GfyziUReNeuXTyPQjxTruBVq1axWOsIeucdOXIkihQpwiIuCceNGzfG5MmTUbhwYV6HwkTTQHd6rqlduzbq1auHnDlz8vxevXrxNgMHDkS5cuXwyiuvPJXtFXMYMPtY2sjL2KucGwK9JVKVIAjCCw2Hdy2mvE8rD11R55X3PBmBJwgvNTQwxC2fem8Q7JLir1c6q3DC/LdOzUfn5mZC6zbNcPf2YwTmyIwbN2+iRcumLLxSJzEJiNRPWrNWVdy8cRPZsgVyXhqaMmf1gd5gYnOp37l4sSIIDgrkvHvZs2VF8RKFEB4ei8yZfeHt5cl5dosWK8Chg+/cu4sOHduC87TqXTj/a9NmjbiDtXGTt+Dv54erV6+jxKv5lRerjAjO9R48PLy501PtrAfy5M2OZs3rsTDm7x/AHjCPH4Wg/GtNOKxlly4fKuU/QovW9XHl0h0E5cyMyPBoXLl6FR07tYZJF4Gq1aqwF1Z0DImRHviy72fInMUfeW7m5I7tPHlyIyY6wkr81TyGYPZc0byn9Dbhfu2HBzaZwxojLswi1D5f6mjWQjSrmCwdn/Y8Q23ma/9bvVOpoqNqIx2H2jHuotRrJvh4Z1bzAerU88ZCsS6aO99dSFSNjkZktHK2IiI4z7PBzQWPH4co14qnUg9uHAbL3V3tmI2IiGSxnwWTcOq09eBOdNoHeVZrggedN/508WBbqY6o45q8yMgzzcPdg+ufvHRdDDqzh5TmdQazAKLn/IXsAebhwuEu6by5WATgOC9bztXJHs7RiAhXzp/ela81LTemmtsR0JlzDet0tp3rcV7UaihOSxWbhXsWRGBgm9RFmkgEs0ALDouthq/WcgXbhvJO7JzanFfz79dgFoE5XDaFAo2NtfyWtZCqOsiLtSDYI+TRI1y9fpNDFpNnI1j81PNvV73XxImnlt8lh6NXf88s3PLQDzWIPedvj1WFK/OGLBSqXrcxLAzrzNEKWO9T7r+01E25X5HGaD2gSI2soDN7/BrNoXN1lvzunPPXHBZYC5dvLlT10DUPtAEPaoHl/qczewID6v2TBqTQ/ZI2orLofhpjUiNXuLBXaJSyC2XSkw0x6n1aF2tJUcCiOB0n7Vuv5ZLVs4hI9yfy9mRlk54vdFpYfy3stcmSV5i246gSVnltTVbCMXgAkLpPelB0V9oHqr+I8CjVJldqO7zjQhkbtLZSb/b+NYddjtcWkw0k0FPZ5KHK4ZU5nDTMoZqVNhAuZlEy1py3V/V6cnFR2yQS5406re1wx6mTl3Dp0l2lhr2VanJV7ssGHmjF7Yx6cHH53C3PAXT5GS1e5nENvzk6i8lklZ4hrk0zmAdssQcwt53mwOEGd9UDmUR0pQ02uSh/K21ejKs7Yv394ZM1Ewy+voq5SvvrqlxnShnR5OWsXA8xuhgOz6yLioW30u77RCpl3gpDZuVYyuTNj8b1ysM30IWjogRlC8L5s1fxes1yyBGcgbND+Hq5Y96sxXhwJwImgyuyZsmBbFkDUbRoAZQqW5gjsOTKmQvlqryKAgVyc8oG/zJ+uHb5BlatXsvtJB03eQa7uKu/qygaBGYOfiEIgpASZMoIeHtDeQ5QBycLSSer8tqYMaHD6ktFpkyZsG3bNnTq1AmzZ8/mefQ3ee2uXbsWxYoVS3R72q5QoULo1q0bexJv2bKFBeAjR46gbdu2eKQ8oxLU3lMY6G+++YY9iCdOnMhhqOndm8odOnToU9ldPtCxh/LzpFqwAe8WdX3yioIgCMKLgSET4Kk8fEVfVabLkLDQgvCSofdWhV+9n7MtSfOkuACs9TFySFmYLJ6fLH4hGlmyenM+wMyZA6DmtjXYhCUkQS9zlszsheubwZO9hjnopTkELnUgergYkMM7s7njkjpO3eDlpebKyxGcSbXDHObXz18N46xlPiRbfH09uTPX399L+YxErtzZVc8lUywyKXapHpTa0ei4IztnzhwW7ybqrM2UyUdZX/XyDY8IUUNhRkYja7YM7HHq6uaKfPnystcndapT2GuCOoI9PV2QIyiAjz1P3pzcIU3LDRaPXRWtM1YV28weoIjr0LfUuSVcsFXe17hIxTYhhTUvH82b2Po443v7xhcMLZ3LZtch69DC7PVqUj2i3Ny84e+Xlb1rCRY0zB3frjoXFmxJDNdzDt9YuCg/WBq5TOfe19dfFXFjTPBw9+bwk9Ex0ew9TduHh0WY8xip55vEek1k0EJ0Unm0P/LqiqZwmhSuUrlGKPyqKga4cG5lfbz6jvOUVsUEk9U8F1fNAy5uHnvrKmtRB3no48eqty/U3M18zZpiOMQ074/82Lg3X892WQu01h69plg176MW/pl1EPLe1Vl13Ju/qV5jsezJpjNvA4tfdlzuQ8s1YTWwwOZvs4cx5880ew9zTmWzoECCiCpq68whU/Xi/ysIjmCxkpweTSzjst4J1UuTc6hyBl4dh0U26bScqubfOt+79WpoZuUe5arcB12V9VxpIIarHlE6kznPbbSyF+WeFkuZV6NZ5KOQu3Bz4TINyi5djKoAxwNUjEbz/SSG0w1QtAu6H6lZ0mkd6ixzsXj9U5hc0h3NjqFqWH2jAVoeYjWKA1jMNjv5clhqdbCXmypK68wbg9os1dPZ3eANdxcTPD0ewcf/MTy8o3mAjnKLh6dLDHsD6w2uHLmB7jMuyr6gVz2OXcjrlIRTV/LIjTHb4a7cnzzM93RlVZdo9hoiAZOFcIM6AIjbA55H9WtOTUDCMUXgMERYBqKFhkZyCgBfb29uM/QGN6U8T1UM5wFD6jnV6Tz5+PTmQTFxg7G0wUSx7IlMA5movabjdyOvYCqPH7uorfJQQxlzFRmhRuQwmgcIqJ8mEspZbPfG1k37sWzRP8qZ8Fbu+57K+dNzpIxYIyz5k7U8xxbBF+B9qF7Cam5pdQCPep55SAK3LbFqqG5+RtLxezO3DdFGysphDqGsJ61aua44g7SynyhEeChtdUZ/mDJmQf4aFRBcqQBuu6ijvWjfYTTYQNnU06QmXCARmATXrEr9e96JwPm/TiDgsU55VsoNXx8XXLtwB77+3sibN6tyTUTC29sF58/cVJ4F3JA1czYEZg9GYDYTMmbMgds3QpExUyYUK50LXr4uuH8vTLledPDx88SNq7dw9PAJlK9QGvnz51SeOygqCbhtVgerqXXgplPDk+uManQOQRCElMBDef1Rbmu4cQt4GOJsa9I+1NQHBVJaIGdbkjagd1XK/0t5gHv06MHvxxcvXkT58uWxaNEi9hBOjCpVqrDH8Pz58zk3MEFCryb+0ns0PZssXLgQ+/fvx5QpUxAcHAx3d3cWgC9cuJAsu9/K54Lfz8Uka9uUgPL+jqzp4bTyBUEQBGehvHC6BitTNiDqAhBz09kGCYKQ6rgoLxHKC5dLoLMNSTekToAlk1ko447NuByjqhip5RON5c5vNQRynPhIHbbW4SxN5rytqohmCaLIITRdSJiydLqqQhnlTdRCIKpiYDSLWeTRqO7LLHCZO2wt+WHNoZfVoI0xZtsNFq8p8h7VPJ00D0+9uWNa2xd1LrJd5rhVaghKE3vxqJ3lVrkP2SPJaLVf2zytcfWmfrcVfG3FWRYB9Zp3rxbUUWcTpjfO09Rk87fmGaXmbbQVJG08kS3HaxYqrf5Wj8dFLVupgwy+meBq8DHXpVX9UBhJN1fOQUnbkGAbHW2El6eXmpcRRs4zCPMAAgMJCSY1CCi4g98AikZJZak2xnD9qx3smheY2SNLC+do0rMHMs2LjbX1mta8bKnzXG/uxNeuAxJA9OY8y5oI6uKqt4jglMOZvY8pV6TpEedPUo9RzfFIArdahotZDNbK1ERaTbC3Ou90feoR56VlFovNsTMtaN5acSFaYf6x6ay+msyDD+LCb9t6wZnMtmj7Ng/CoOuVc5Ga7ddbeQCac5lae5ULgmALiY2UH57C1+s1qY3ukxR5wTx4Qqfe1VQPTbqfc/hno+VnRaKcUW+Cu9J4uBnV32EMRWA3qINvjFHR4KFBlBLAqOaCjdGrAjDdy1zJ61i590Wac/GS+EntYCyHtFeFUW3wB+fZ1buyh6Tm0ap69hrV+5F5uSos6iz3VtVrVvVo1kLwx4mh5nubUb3vqM67ergo+/Jwi0TpMvlRuXouuLjRfZM6C0mojVL3R3VmcGWhWg27bzCXo2fPWrCAq3lDU+26mj+hLqO9mb2CYfEMNlieIUy8rZtZoKbvkUo1RHLEkPshD5W2ywBfb0+zl7MHZRVWi4J5YA9o8BINQjJvT+eV96lOJqhtmY7XjTafbbIr1iy5khW0Tw/EPYKZLB7iMG9BqDnqdZxGgcIgs/czH4tyzDFmD2wXVbCl/MgunMtY3YPRPGiOhV/zICS6pnipeeAdh7rWm/O8m+srVksHYGn7jeYQ4gauSwOdB65HtR1ycfWAydsHoZk9ccVNh6sGdbAB7SNCWTdM2drLXHcxiqHKlYZHyt+BroqNvm7K7wTwCXBBTKQRZ09cQ+5XcsDHxwMZM2bm4/jv5CVkyhSA/K8EIWvmYATnyIE8BYKx8Y99KKDMy5jFhwc4REZH8SAIg3LtxCrPBu6eHtC7G9TTpOcRfjxIgQezmUOgWzynTWknb6EgCC8GdB+kPLaUH/j6TcAotxm7BPgD2SRNl11IvCXPXxJ87969i/DwcA7rTGGaBw8enOi2uXLlQt++fS1/Hz58mD8pbcLmzZuV51RPjB8/Hj///DOaNGmCN998k6OuEblz506WvZ+UdnOaAJzPT4+ZDT1heW0VBEEQXkKUd2S3gsoLag4g6ozy8PXI2QYJgpAauGRXfut5kFqS5otKKtaWHlqoS0sKPGjildEsEMflEtSWcbhIqxzCmtilhS7mDmvqUEac96bmKat9txYt+dPoSMiMW1+dp1PFa70m0um5U1jdxmARYwnrUM3WYip1WnNnqjnco+YtFSfiJsyrGxdUWKsH27n2wvla70MVrq3CPJr3atKOz6p+tU/2CouNtYjRCUJPmxLaqYm/2rFYr6OGx3Rh4dDX19ecY9LInrOqUAkWHkhk4E5jFzf2eI4xd3CrxwA136BCVIwqpJNo6+oSt5zEFc7lbC5bzU9oUgUAs9eqKgib8+myF5iLWr6qWJhzbmr1oTPnX1aPn72Vzd54FNaZxWDF/vCICDwOfcTrcE5I5dogryTKF0wjqnmeiXIeGs3Xm3YOVe9c9rxCDOe5jDvbJptzy35YJNAYVPFer9OuSVjEfGvP3VhzaGZrYdd6gIPdMuKVB8t5jLvOtG2tvb7jrh2Yvb8hCIIdKGx9Bt8McFN+R55u7txWWXLbkrgKapNizL89I4tRqoOlOSKDSf21k2joTqKpWcCLplzxepZHYSCvT516X3WPBZfB4rCbge+pJG25KnNjLWGczV675oEyfI8isVanCnq0nO7ZWthmdbAUzTaylyl55Op1LjaDj8g7WG/2YCbBTWfSWQZ9qU2FFpJZx/c9Ei5d9TFK/UQibz4vFCrioxzDLZIJLXdEVWQ1sdcqzPI5zHIqzOKr+WhgjjfC2xnN91qzbzVgWUtv+c5tr0VaJTcjc2QDLos8qml00SNw76GOInaQVOlu/jS3e1y+6jGrKosxUJ8VYszzzCGyoQnCgNXTj3mp9ne4Kl4nmE/+tQbzvqLVZaYoREeHK20onS+DGmWC2jNdLA8WiLUI8TrzgCMjLPd+nXZPV2rHpLZHPCiI8iRbwj/rLCK+Xhc3IE1rT/UUxpkiWpD4bDLXKdnBIjqFo1Zqz0NNGeCiPDNF66KU61YP9UlNqV3FfnfFLjdlOzeTAS5K2+oWY8SDu7fxMEy5tlxzIVKx58HDxwiKVuynfMjKfui3ER4aCQSogxyiI0y4fjEEjx9cgreXNwoWzYHrN2/Ay9sDkdQWR4YjQvnMmTMrsgRmZNspVUhUTJRyKat282A1/g0Yzb8LnSWEtyAIQkrj6wN4eqghocMlPZ0FasLI69fL09mWpG0qVqxoyQtMIi61y0OGDGHP3QULFsCb4o0ngQIFCuDMmTPcLlIqJHp/7t27N4oXL86fixcv5vXoHbtdu3b8/f79+ywWR0VFcXjovHnzJlpGNm8d2hd3xcyjzzf2ednsBox9w0N57n6uxQqCIAhpFQoJ61FSeUW/peYHhuTkEIQXAkMA4JpH/Y0LT00q5ADWxCJNjDQLijD3q/6fvfcAtOwqy4aftdtpt5epmZpMMimkAikEQklEmkj5xAJYwF74BFQQf9EPEMunoCKK9bOLCAiKiNJDegjpbWaS6fX2e0/bbf3rfd+19jn3zkwSMENC2O/k5N57zi5rrb32Wvus532exwGTnKIpoJ7nOdCxBz46wM/50jHTc1laZ7/fnioWkAWcUpbVoRlMy61Hao8t6fECt3dcmqjmMom3ovUitNv1wFV13H4rgbV+MNVjdo2wglwhe+Ac+dFZoFL1PGhdGxTE0GXM4OP/dgu4y68CLHCoinO6/XLLNuNlbAJnlfhGOuABfUCikz3mhX8L1jpIuXe9rA+wabtGvW6+MM6wLGe1WoMf1BBFoWUKa/blY6A8EEZuUR4LZpJ3JLeBaTNiBKW5SIfmqSxYMzTQ9ezPGN2gw+VJmdnm8zXn333xaGTWLy1gU3KBPbd4VFoJaI9kx1PehphQ5HfLfY9IVUnK8s5xnhABC6HVQ6XF96QTo5nEaLdadiFZQHC36E7t0buGGRyTHX0sr5XXsZ/1vcxjVzlGfI/93Z8k4fpAHx6C3hF62zkwtwB4iyQBt1O2DER22/aYxitfZZRRxspIk8yMDx0zHkVQYYXnLWKkVmo1ZlwoVqTIAGuTQP6+NA5DCPgMSQo7M0OkhW1JTNCE5YvNOBibeS3hnBeeQQdUZL7YZOjmqRmrzH5Vs42Xy3hJwC0nJWWSUGLL6IXKJqbkPEdx4pNOBXpkX1qnoGDGYVI5SMxcFYl8bkzJLm6M4rHa4/mDgds+f13PJWMRS5WOlcVmuwQVv4MoWDKfTZn3p0AMXAFBCWxlKNsmvDhQ1CO33L6RR0BTj2c3GnNTiCOxb8FjYbv2mLe9+VbYtw4UDgqwWIBYArljUZggn10+XmDPlTNLWHFZ6ZzuS6RmAFYVrF45vvB5O8UY7DHgHFretwDGBHyDj0nnc+eScpAfMSmRaL0ox9Mhut0l2N4hCVa2/TNz3TkBjqfNrJcs5EnNioQn234yn4tMsyiuyNwrSiJeMVe4RDFo+7ymJDGAWcm2fyjqW0rYu6eZftKcX0BzcQaDA3VE9QpLeA9mAfYf3ostg5MY9YTt3jDPZCNmn70LLaikwnXq6gRTM1Nmbt5o6lQ1dUksY9cmAJrfO60YcwuLWJiL8bRLtmB4tIaFxdzcW6E5Xw3jE5O4796HuXy1WgWjIwNI4kSeCahBtJLkQXONCRjmBAjyykbveauMMsoo4/EOEobatAFmjDOv6Se6NE98EChO7GivBOw4/vRP/5T9eEdGRk74Ockz33TTTfj+7/9+fOxjH+P3/v3f/x2XXHIJPvOZzzwmxu4v/uIv4sd+7Mdw7NgxvOENb8Db3/52DAwM4J577mHZZxdve9vb2EP47rvvxmtf+1rMz88Xn73mNa/BO9/5Tn6WPVn86IUR/nt3ioNL35xJ9fvODvHzzyi1w8soo4wyyjhBBKvMaxyI95iv3wef6NKUUUYZ32gw8LvRfHkYfKJL8i0dp4wBrC3bpmDiuEU8Apis7LK3jAEs2zmZQSfFK9K9WR/jUFvJXo/BvuUyxE5qWBYvfUHh0PNH7bE+nURiD9zV9ve0AIxl9dZKMAqE3bf/SpC0B9gtZwbnfQSglV+GrEyjPdVKpi+fnVg6WVYAyxQrGcy96PsmXUgOW/hA98rD/OZcM2DaX3ZX5tSeT8qUF6AjL5halrOTIHZ1CIIK6tUhbjs6dhholqpqtZb6wERfPG6L42o4Rq6rp/PxpWzjjvlCStsRODJQr3NWMh2fvRz9kL+wOrCdtg/MvuQZTOc1VWPwN+6mfZLcufUAVgw0EwhNC89x3OXj+V5Y9C1mEFM/8hUm10wQ+mv+82RB2hwrUSmaS00GC2hBnJjAjlUb+JZdbYH9NE8kkUD1PJdPxDaiRXwql2NBa9GGtV0lgIM/XLu5/uD6kuuXXp+0dC8R4fg+0w8kC7ue9suO6w/FGZR7D+VieRllnCQIUIvN2EQS0DEDZB4n+kTkbVuR8SGlf2lfJmqW8thTSPXDSvOyPUEm3sFa5rNKFuKKS56JRqWKu2/4GrDQRdWvY+OZp2Pn4d042p1FXlVMr8mUBXdpqtdwKR/C1uXhxLyTigJAQOOqKWueaJ6q2PrA/D4wMMKKFq3mEs/rNTPW0zjabLbMeBshjTsIaiQxTSzilOdd+unOl1s2qqIkGCTwEaPCQ1xieb2eMEnJYNZ8xh7HllkrcsqeZcTSeE2exwN9XF5atGzzGMyexl5ktgpto/bN27bekhDl/OF8QUm1MHsZqOVnCAIk6/I3q4ukzBJO8lnz3oL5vW3K27bzupQ9NGXyzUtp2q/C4G8O2j5jRnYFI7bcAeJs0ezbReQJm5jqlvJ4atpVDVrwuWKfoVIuZ87zYCJWD7DjOcHeuZtPbY2V5TyzP3zeG+sp+YptHpzVgQWB+xL0/D7Lg2J+UrCewSL5zBA6JTSQQgZ9pu1zXu5hxLRDtxOjfXgKA2bOrJq+EQZy9Eaq0D54FGeuWYOmmRvHTP+pmT4SJikqqkbSGaY2PqoV837N9K2lJTRbC1jtD6FaDVBvVPh5gO6ZyG9gaGCIwV0ivW/ctB70C/W/p519HhYW57Fvz2FW6Khu34hD5ryenQOlHVPxA3agr9dvdVBGGWWUcepiYgzm+wyw/xAlvD7RpfnmB81hJPc8PPREl+TJFTT/vuIVr8AHP/hBnH322Sfchvx5P/rRj+I3f/M38Y53vIPn5gceeIAloun95z//+Y94jmuuuQa/+7u/y/t+5StfwUte8pLjtqEyEDhM8e53v7sAfwnwpe/W5Bn88MMP42//9m9ZketEQbmC//RddfzAv7Wwb/HUfln8tSsr7DtcRhlllFFGGScP850/2mpeW8zD1zEg2W++CLae6EKVUUYZjyVK4PdxjVPz1OxZQUNlfQ61LBxmuWUbamGcMDvHyV7CAUw9YIqCZW5Z4lfJWq2yi3XK+fGiAH8FMBOmSl7QZ2k7WfjkP7V4nzrg0IHT7jNXDjmWrY9bC7WMLeeB2O+ruxIs670nC41eIe8plZQFZyuva8G7fn9eOZ8qpH4diNl/7P5Q/bKNcCCxY5tacNBjN0r4xILxxJtW2QXfHjitebGfgfZMAExXxjCoMcPI8yqosNdkwFLOIilpQXEG3T0kBLD6fnF9syw25+kUDO3C89I1CStepujGTQY+kqTLwAct+tJrYSG3fSpCoz7A4AS1S5LGfHw6F8mXeoEnIC8lD4Qe6hUBI0i2MotjxFmHpUjTPMbifItPTkzfbnNJvA39wJw7Q1SrY3zVKkyuXssAdAURA8yxjtHptES2VYOBX4p+MDa3EtC+6Xdplpj92+a4Igkq101Y4f1McuajEfMs6meA91i4PVlPab8sletU9GGXRWA7q7RtDvF61Cg8fldED4h318UXzFnpZYxhSUJw4ACbKh53rDLKKAOcJBJ3ujCjEbIg5fGMEklo3PUyAnQTARVJ5cCuAMutKzOBz8oEwm8lYFhz9pQFbRONF151Da644BnwmhprDjfw4K134NynXYDJzesxvXsKHZVgKW0hDTXL7vfHSpl/HvqVJNXQ7JCn5v7OPFz1nKvM+BXhtlvvxGXPutyMlxm+9MUvIjLj/vbtZ2F8fBz7D+zDxk0b8aUvXYfZ5lEriW/na2oHLUxhBhaVzLvkU0ss0ih05fK5nppba9581sJiOo1KQPt3ebE4MJ8lDB6bN70BVPSE2bbOjNxUT5lydsy43kbbjOP1yoQ5T5Vh127aRkTzAnv5arNtzGCzp1abI5FHfWqBZfHrZRloryOWAczO9e1oSixdkhY+ZI49a841Z9q1g3pYNVtE7BGcg9i5g6ak4wSRo51OmTIfRJUsECyQLfO9j2521IzdTRLoFmdccx3apn0r3oj5fJSPA1M/qm/fE4VVszDl1/Lsk2XaPlsxrVZ4z56AvTSkuwQ79wxC9epXgugP5//b30/4OQyiopHT3GXmep7T7SMFAdIFW91cz7gawRttYNPIOejoBC0qjB+ha45TXbsKzYU2HqhoJJTsZfpzzTwjzHbbWOtV0ZxNMbglxBXPuhhjEyO486s7MD01jbPP24ynP+M8VAeqeHjnPp43L7lkM7PrD+2Z4+sW1IE1G0fRaac4uncOZ563DiPjFW7u2Zl57HzgYUar3fxFzZWbc7PUtefZ57M+n5IyyiijjFMY1SqwdTNw+Aiw8G1kTUcy2OvWAmGJ1x0XBLpu374dP/ADP8DevuTze7Ighu5FF13EjGHy7J2bm2P/3t/5nd9hKedHile+8pUs5fxv//ZvvO9dd93FYDDFBRdcgPe+973FtjMzM8X7H//4x/H5z38eP/MzP4Obb74ZH/rQh/CzP/uzJz1P1Vzjf3p5HW/8dBv3TT/+5tdnjXn45csrOHu8/C5aRhlllFHGYw1lGcHmlc0KEJzPP/puZZRRxjc/SuD3lMSp+RqmewKOFtKU95ctsClmXlIGqQOYKAgUcwDscexUC0rx+34POJZTujOJ9KUDNlXfiU/oD6yXS/8dD6yebJ/lsroOADweZBOmlWYQu+8cuh8w7tVlJYhML8eKfaTogdF8AttO9EneY50W5/btJbEMaVroFgR2GeuUlUEZG/aQZjl7BlUH6oW0NTNlPQFb07SL3tXO2KeQgH5apGagNuky8821WW6lnUWGVOrms/SmfJkj4CKIQtQbDXsdlS2Pskw5MFPL9wf4mjuZZwI+ZYE6EPCBqMAMhgODo0OFnLHvGLLcPhmOHDqIvbv3YGZ2Dlma4dLLr8D6jWuRMru5avpqhphYvpD6EDuptdREWKky4Ez1WFpcZHZ0SJLXoO07pl1iUwZiTptz5Z7UV2c2waHnHW0vopWfVgUg5O6l/r6lrdcmLYbLur31i+xLAmCwCD0v3xMx1NF3XMeid/3RMcF68s92P0jfLaOMMk4c2o4RNI5kZszIVI7MF/AzT63HuPVUVZYlyzLMdm++5819R6xQZcazgGmfHjyz60C1ge0bz8BN/3EdxpYGcO7ac7HmzFGMD01ix633wZvL0BiuIFFmzM064J2UJP54fOt6KCT8kVvQT3G5qAyZGecmx9dh+xlPM1+MQqwfPxOr14+aY+VozrcxNDSAxcUFBKqKibE1OG39JjSqd2N26RgDhVFQsXNwyrLXNO7ROJWbsS/yyApA5h6XMKStT27K3FjzHGDmmma3xSzeTrqAIVNfksCvmvE8QZeBYI0Gg6NJtoT5eD/qlUQURbSZM+gnnZNZux0L7SpmH7fN8arBELNqNYOvubBo7TjJQDTNbeSly/LN9HgUFI8tUVAzzUWAPiU6EYDss6Qzz5/s1kzMY88yd8nvuMaiz6wQgdgKTweoRw14SO05FJK8a8pHQHXFHk/OK3LQNnlNSyIYzcWS7OMAS/FnDgmEzkUtg2WdGbSlruSxz6LWXjFuy9ypl80noq7h2MR62RzBc4z2uU6uf3MZyFDY0+xLrOsRpish5s3cN8fS5BHa5lp0PeJng58dvFod8zpBxZxm0PSfqXgaM2aOXDJtc+jgHLrbV2Pthgkc2j+Pu25/iOt7eP8C1m8aR6vZxV1f24PQ9K/TNg1hbjbGTTfsxIMPBqg1FK58wQWYOjKPe267D1UCl89Zb+bfGJ//r+ux6/6HzTUNbb0DTmag1vGUsMO5XenZ5HEfCcooo4wyThw0Ba5bI1LIh44AJ8jLeUrF5DgwPvZEl+LJHdPT0zzvErhKwCwBvcuVnnrxwhe+ELfddhv/3LVrF89jb37zm1km+m/+5m9Oys6lWL9+PX7iJ34CS0tLuPzyy/m9yclJPi+9R/tSOV784hfj93//9/HQQw8xGPyCF7yAJaj/8i//Ep/85CcfEQCmCM38/1cvruG3b+riYw8+PnT3iZrCT14U4WVnlFkEZZRRRhll/A+CwCV65QtAvNf8nHuiS1RGGWXwGhOpr65n4kcZj3+ckidopS2rllfcnGwtrN9gL1uT5Px8ZpsKgCVfdE7AorW/s/VcH5h5vIeqYzVpXjjnxVBaJ+37AiXHXLmPLbc6Hhxz+xR1s2DaieR0KRxA7VjJDPxp97llQme9L0KuPXrl6nnu2rMv+wLY82LtL1dPxrG/crxgq/t9Zy1ATLKi7to4xnTuGNgahZcjhHUd+REaUY1lkmk3keaWcqdZXEiIykJ/j6VKDGGSnczYV1d8lQmsJKBSvpyK1DMvx9IiLC3NkxRqZv0Jg4D388x5HXjth8qCplZGnFlGPrPmfAv0gkHzqvhqsrxjD2Dl/eDZ5AQWKGWPzk2nn4Utp29Htxuj3elg1eQqBgeiwLPgjMiCc4KCBVPI71iRbLS9DsQQDv2APQX9gMDYHJVqiKmpA2i25rndi8V1z17vvK8v4QR9ekVf632cW8C37/0VC/fSl5z8eq+f9cfKxX7HHHfyoQWgDAtGM1j/FF+pKqOM/0mY+yRLU+got6CTfZ+k7mmc85wlAUnlB5wc5NQQKGR7YScqq3jBaSBaVAJIKndheg7tnVPYlK3F5gsvwKGv3ImlvVOo6Ag+qTTkvhkDAyIMFwflxBEt47vV9JXxg8qTiXQ8+aEPDQxioFYnqBK628GenUewbsMa1KMBBi/bqo3OUhdHD82hEU6judg29Yh4BZvLmveStxjcZpQ7gnjZinx/wBQgkVYWbiwV1JzTbDdUzRGpFF5QAyx/NmCANYG4GEcskeypBPVg1GzbNeMtzfNmezVkprMqg6kDQYOPTxBwJ1sgh3rzPgHAlEU4wDLPCrJIalvFzBn0f/IipgYKIb7E4N+rdBI0TTXa0MWjk51XGQSmY1VJK8OUq27P0+Z6ZiwpPcZAccTHFGiY5uiK12XWssfS1LQdaWPWbBLdPLcbt1Em/SmHuAr7niRzkaAK+xArsXQAK1n4nHwglGAZs+V5yIezopfnFF08U/CzEz83ZfaZQ+Y6pa2SSUYs6oxll3kCRGD7sI/UzHepYtdic5Wo1TM+bZdrT0UQNnOoQkQ091E/NM8GS80mDjVT3Lpo+sHCIoK6jwce3IWHdu3G8PAw/vPfbsLadWswdWwGDz+0F/VagM/85xfRaQXYt/cYPyPU6iE6bDfRxOLCEm760tdwz233Yn5xFvc9eA86pg9rT+Z6mtc0S0Fn4n1sno9C36ljlBBwGWWU8c0NAoCJGbv/IMxY9USX5vEPcrRZv9bMjJVH3/bbOe69916WZv6zP/szlnQmf156/fZv//ZJ9zn99NMZBCYmMPkAU5BE886dO5nhu3bt2kc8J/n/kszzr/7qrzL4u3r1avzCL/wCZmdn8b73vQ9vfOMb8ZGPfAQHDx7EL/3SL+HP//zPC6/hVqsnnUkA8datW094DnpUeNtlFVy1McCbPtv5epuliHUDCj94XoRXnFkCv2WUUUYZZTyO4Znv3dXzzHfjJSDZC2QzT3SJyijj2zDMF4ZwDRCsA1T46JuX8Q3HKXqSdtxfC8Y6kBT9cslAo1EvwFIBneSz4wBPuzaXF8deLpHbzxLu/8mgIEk9A8dtu/zvfjZkrxY9b2Cv+Hmic/WD2hSONdn/Kkred/yVrEwHMsrfvUXJfqlqXbCnem0tbeSvqIdikFHrxF6LvIets5xoT/JZFccBLxILidhnvyFi5eYpMD+/hHpjgL8wUpsSu5XAW8feFUAWDErywjSDpAFf80o1KuQn2TPX+v3ScQggpWVzAlED246elUCVRAIBDLifKAv4aidtaplz2usDHOQi9vyZhT0nLCb5zPUH8vwVVW7yNJS+OlCAF14fyAxeFKf3iOE7ODCMeGhYpKA1Cra5znI4WVVKbqC6xt0M4xPrkR1RIDyD3idWcJbHDIzkqtc/HAiB4h45PsFBrlMPnO31HTkCHHhU1H85+7fnTS3su9yC0iKHCeknSvfnYQgIoKzkKBwTuIwyyjhRMADKCRMCvmnLFM15DMsg+SSKfVPFZ1b8xgnE02bMznyZ6QIdMctSeeySiyDVGKzWEUU+2ogRjVQQjlaQEiN3IEKnorGkU3SqmnOqqkrYqPDE7kDb5CQad1lxgxNqfAbrmPFPpQnMOBV62L/vACpeAyND41izahRZK8V5Z52J+YVFVCtV+BUfB49Mm58hamYeX5wX0FHELcRPV+x1BQEn1izymIFaPzLjbUjbJJYFW7Es2i6PiQ1m6ZJn8igJN1sOr+gZeCSfzz7ABDZXTRk3Q2Y+Hogpnccyfmu8rRvIKr45jxIZ6ZyBWWHXssw0PJsMRGNc1/wcZFlnCl/3krUUA7SBZSD3kq5yrexZPMuN9fgfAblyLs3sYM3npPIR+FxlmNRjgJzPBDHM8Pl9zefVcFLUuQ5Ycpl+95RpLy+y8uCmDn1JZmILQDXLoG0/ogQtLhclYXnuWULOq2Nbcuorns1WIEWPXMjjITF/U/M3XVOS4/ak76bm/USbeZlezSbU/DzmDi2gmmiMmgeGpnmlpiBVcy8Q49cn8FlrFsyuU19PUszduQv+/CLazQXsnZpB+/BBU1uzb7sltgzdDubn5vDAvQ+wpQTVr1nxMDV/wBTFtAdJOSc5Wksh5nYcsolj5vO5w0iyGN2kjU7cNt8hTH9Pu1zfXCVcf+obdA+4Z9Ig6FmKlFFGGWV8M4O+zmzeCJhhEFPTT3RpHr8YHQZWTaIcWx8lCHD98R//cbzlLW/BZZddxu8RAOskmB8phoaG8OlPfxq//Mu/zN7AFF/96ldZtpnev+SSSx5x/5e//OXsHTw4KPJ6BETTi9i9/+///T9mAL/mNa/B5z73Ofz93/89Xv/61/M6AAHPLn7u536O5at/4zd+46TM48vX+bj+tQ187MEE/7YzxQMzj5xITBLSJO/89DUBrljv49yJUuq5jDLKKKOMUxjENqycY74ct4HkEJAeAaxSWRlllHGKQtWBcJ35MrQaZTL+NycedwDYSckSc7PfQ1Q5H8O+b4LChFUFiOqA1pWMWytWaRdpNfwTfJvsB8H6z5FbOej+7bTOj9v3eDBtuXRu/+f9wNrKv119+8FfzzFT+45fSCHz4mOwDFxeBhyzb53U3AGTLOEM8e0rgEJqXt+3ba56DB7lwYG8DBzzCr0Atcp6AhPISmCtpdkycEmykp5vt9UexsbM+4FvAWgf1fqoBbq5JFZOUXGZtAX06Ry0VJ7LR1bdVDP7xmOWkWe+SDbM9sIO4jbov55aPAi5rSw4mmu7eM1AMETetO8aiDqybMNl5Xo5ijeK6+PY0J5lyFIZfU9ZEFRkMbkf22sXsQy31JX+DsMaL9i3uh1mFVEHJYCU9onNe3TN4m6LweDBoSqOHJ7D2NCoOb60bTfJeEFa+ZkF9nN7vZYnDyzve/19UtjbcotpZhzDMthF1lr1Mc9RSDr3h1L9CzO9NmJGYv+2WgCC/uSLMsoo48Sh7DyXs9+tY/f6DM6R1Kx4r1vJ+8xjP3G63XjM9sQ7l8dwx94nhQPzS7vVxplnnYm1Z5wGrxpiw4XboEONO6/7Cs56zqUYjTagteMgYsqJCSy47PUSVPK+ZCWXZEUJP8qXMV0RWFet4OChA+gsfQU68THUGDLjfoTFxSbGxkcwOzdH5uYMFh4+chQHD+9Hq7Novd5twhdEit8xjJllqkg+P2HA1VQaYk3sZnSNULt5XtpKW7hXsQRzzskqNOoEDBRbZnEhl9wbm2Rk9wD7vkutUcxAji2ULI89qmDvCmBNagzdTgdDlZTtCuyMY5m6bswTr13Vd045lrL/9wpBaTBQbZO47GeyTcAAs2LRa1UcRSSoYd+zgDQD2SGD3nGX5tbQNE8oCVBUxpwUM0Aq2dx2GXk40zXIFCt3cIIP9TNffOGTLOG+R7YSWSJs9JDnjlx87TNtPYSFKcuM31BqoK1CiID8Uk5KaFqamUJi+uaRj5l5z5SL2MCx2S7JnN2Cz/dClgmw3SCXg+Yiqkst1OMut0SSmv2bC8hUzM8ddJ/EeQftpVlTvhCVUDJBW92cfapJXpzep2eSmI5L5SbVCk+S07QSXjklWNHkTsfsxh1R/BBZGJswJq2fZuUX/DLKKOOJjYkxUhaCmYNhxsQnujTfeNDjBclbU13KeOSgRKSf/umfZl/eH/qhH1r22djYY9PMprmMvHuf8YxnsERzt9vFsWPHcMUVVzBr93Wve90j7u/AX4rx8XH+ScegePrTn85gMAHBxBYmGWjyEaYXxdGjR3HPPffwi54zf+/3fu+k56FHje/ZHvKL4t7pHIeXNKbbORZjU9+awmRdYcOgh41D5SJgGWWUUUYZT0ComvkKv9W8NpsviMfM65Cwg8soo4zHL1jmeS3gDT/RJfm2i8cdABbmqS/yu7TA6cvCJIN52rNg13KJ2pUM2v5jOSllWqjz2SuYAGDxbSPglBYYnX8w/w1lgUwrb4wTAVZZcfweqNUrz/ES0I51KzKaSvUxIVeweHvMTdleVIh7YIAfyKI8LYQyMAzxNtZWkpkWc0dHJhEGJLksMsm8oM3Kjjmf2/dFS4vBTRuejrF3zx5s2rSN2UEkUSnAg6wO9wPWBEQw+6wP5MvhkE9hL3Eb95GjCyCRAGktbNdj08d4uT6oRMjT1LJmvYKR62lhmWkLzBatYoHJ0eFBlr0ktpLv+8X15ivhPCKtV6Gy8qXs2GgBdjgAMw+h/JQBDvLZDYl5axoy9JQwbH1i0xGbCQwj0Csk4Dj00ckSRLkkJ2jyEU5NbyUwJEv5mrOMaiIsauUHy3x8fZKOzFr0DR6pqT8xojsdYkYnBWOJ+mSWeWguLaJWqTPYzmAMt0aCalWOJ0z5HvO7vx0YFsmUTRKQ/mOvCvcnJ+O5LBHBszK0mc/s695N5eQ+HSPc+v26e8R6PtO9KtvmNv3CyYgLCFAm6JRRxiME3ftm7CBZeAan7JiXZeIIy16u5KMOx5D1RJ6Xx01RrQg8gScJlMttMs+R6Sns3rsPw6tXQdd9XHvbDeb4bXR2fhWDW81D1KEQXS9m8I5YtTTPuLHb+byy56mbD2zCEKlFcKIHjYlJBwePHWRP3UNTh+3YrbFvysGgNrGJQLXFBQbbVJDa5BPNYxbXLBeFAWJXBiSfz6zTjOdD3yc2LTFyGxYYpbm7VkC7qg9Gzez/raO5/cxBp17xkrKJp69m9q9vU58c0JfbnyHQ9z7PS5qeWcxR0kXTnmb+9EJ7GaVOMpe6ZwrN86vYKwi4K+/7XCMeM7UVtrZJUjLcyrYy1RNI7luw3I3JVuLDgcYM6vo858zNLKE5G7L3MgPIOfklkyxzxcxtHs+h7GmsEx6fA0oGI19nOk8gMDvN65Flg4vlApiRTR7E2jw/0ETp8/xv9vWl3pk5XsoJCT73WQaGcykzJSZEecTAedgBqnsOICElF5qzooDbk5KzPPO5x/kAOTPg86xrzmPmXXPcCjODTRlUipTmU9N3cwcyU9v7cn/kecAJU5Q8pfyQgew0ie19E/AzZk7PEQTsmr5I8s48H/p2/spR2D/kzIZPRGGE/ZwlGbFMayqjjDKe6CA56NO3wHy/Aqa/BVUIR4j1OwGc5Gt9GSuCWLPku/ue97znf3wsAmXJA/ilL30p9u/fz99JibF7yy23MKP4ZH7C/UGM4GuvvRY333wzbrzxRmYk03sEANP3249//OP4yZ/8yWJ7Yga7IBbw1xPnjHvmRb89ernKKKOMMsoo45sbnrAS6UUAMAHBBAiXVnhllPGNhdew99QqnDIh4jIeNR5/BjAvlqZ2gVkWNoWBIw/4PfC3F/1M4ZVxHJtXyWLmyXx43SJej1eDZdsuB2mXs3yLY9htHCtXzpkXC779ZVlZ1t7xe5/nDIRqYWMVu3gCJhNImcmibxRWMTw2iVp1yGwXWilRjxfzHRtJ2tR60qpeexGwsHbtZnPYCFnu5Hyp7MKAVQX8Kj6uQvYNesRP5bYXSVJmAqsTs6NJBnmhvQg/rDCTiOoSBHnBcBLA3OubHjWzuLjWBOib4w02hk09I2bnEJupnz3da9d+NrYrXx8A7FqStCphF68D8hHumjJG4h1JYG0q54yV6xseEkv7JUYugcy0UJ5ZoEVYxB4Dp51Ol8+Z5inLYa5Zs4p9MufnZ5Gkco3b7TZnS9OXbXoxZpNncFLnwsbVfO1ynZjPUvuZKUcXCCOR/s7z5d7QwoIWENgB5I657Jju7tVrE1W0m2M4nUhO2u1X3HvKgjtWvnw58C+MYE5mcGzCvHz4KaOMk4VTdWCpe6smwPeMFlsCYm/y/UzKur71bKVximBbQuUIQKaPrYQyTR5RVMXe/QfxiX/7D6QdjQe7DyBZnEfVjON7yf+3+TCWwi5yM56kygKlgqQVtgQU/eMBjeXkwU4gNZVBdKDNPoHMTcRRTSGgIs+7uR1htHBafW0Zy562iTE9ywQeOXJJnmImbE7JK6GArvmoaZuIGa0EPlKZMkrEoSbKRTUi1xYPtaodTr3D4yQaN58Lg5rGW04Eyz2rFEHjbJcBP5171mvdAbHtApCXl3xGzNKpqSkMDaZ8DkqgYe6xORd500OLVQFfy8z5zctoy+WxCTXga50x+EnzcsbsV1FWoKmek324T9A8LglVzgrAzfkMtuYEziac/NNuasxPB/DVgCmLuSbmuKnZJk19ThTL8o4UJqSsgYyP79P8bo7XoYQAKllGLO+c24KVLcyVzX0BtqmPclKYFsCZ+kBCEt3Uh4npa+Y838qVQ7tELtMv0jaqphOkXVPOeImZ0yx13hUQm6F8mp6tDDQlZRHbV3kkO57zcwG1E8G3XkhzUMLJVfz8BMvPzkX6m8He3LRBbvuikgQ6utY8f9LVIqa5l1tWN5HVNfejxFw/2j/NpAMzq5zb3Fwbsmso15/LKKOMJ1FMjsPMRcChw98a3sDk8bt6lQDYZTy2IDD1k5/8JL/Icqk//uu//osll+n54RWveAVe9apXPaZjkvTz7bffziAwAbgUf/iHf8jv0XlGRkYecX8Ckck/+Etf+hKDx9/1Xd+FHTt2FJ9nK9QyPv/5zxe/f8d3fMdjKmMZZZRRRhllfEsFyUNH2+SVzZnXUSAlz45SQaqMMh45QgF86UUAcBlPeJwS6F3Wqx19dDlQuhK0de8dz7rtB/96oCuzfHMBUx0IuwygLI7jFec+0bFO5KHa7/PbL+/sWQDWbn1ceU9Udl2wjdw21q8WPV9kt4gu7eSjXh9GvTZqih3JIjexevxQFirtuQW49Y87rxeFUBXymM0RRuEJWM8WsLOsWY9RTq8PfF/Bfla2ZH2AubKawT3Jbt+8Imb4MjroAEkti7PKeRVb1pDPy7IZBgcGUa3WmCHGC9F9YOPytlwJsPe264+M/BBpkdi8Hyem3cMKKpoEP4UdTuyj1NNITRkqxBDiCvsiDZmTLGbGbGACQQgwTjoJVCBtTGzeKKpwWZIkw9TUNC/uJ2nH/B0zO7jZbPJPYgGfqH8z7iOoskh2kv8vAc95iDhLeCG+Ul0u1ez6oesj2kqjCvArbdMPAPfOqYr7QsB5JcCS7xjeCjgBg72Q3HZ+xgUrLbOS7j5LZ7qyeSv6fBlllNELHiOVS+JQfO94bvz0rOw+MxI1jzvk46oCq4ahnU95f1KNEun4boy9h/bDV6TLmyIaBDpm3CG5hoS8Uys+Kxmwv6ky86W9j11y1XGJT1q8YIs5Kbd+sL6AxzSmEUjIUw77oct+lARDErw8hjBoK/OIz8Cp+A37gUhaSx6Yc+r1sbTYwrWf24FV95ux2F805ewwwKo7wlJNWVEhZ5aqb87BCTWZzLspMT8zkebnBBaNZaxmLw14vM149szZXJHzasxY6+WS8JQQ4CxW8lY9oecfT/UK/AXr5w5maQvIKNc1z5UdH21bWDsBaVMzX5g5Qfzs6XzWV1YzVG7mDPGR52tqwW2a2/kpzLd1zGVuDkj22cwzqZaELZ1XkCambXUkoDaD7JS8RAC++WnamuSTtUfgdcrgdaRCBoKpvqQsEpp5MiC2bKxZYplOpgjBt6xf9oqmBDA/EEsEbTnSnKiW8nNXnCYWCCamOoGoMb9PiQKZss8m1D+sLUJIrHYLlJPUMylskBc0dMqcb5cM5WTDtWiWM0id26Qpl1iQpplcB69rVSvcM5svvoMZzcvErs/lGcf52mfsds9gtChf0P0miiWZZanzPfnNGBjKKKOMMh5jVCLxBp6dEzZw+iRcZ6QyTk4AA+WaztcdBNB+4AMfwNq1a5e9/6EPfQh/8Rd/wb6+k5OTvM19992HX/mVX3lMxyUZZ2LxkjfvH//xH/N79PeFF16IT33qUzj33HNPui/Nx3/yJ3+CN73pTQxCf/SjH1123O/93u8t/qaE5+uuu45/P/PMM7F58+bHWvUyyiijjDLKeNLH7t27sWfPHv79qquukjf9EXlFtOAwK6zgjMDgUkuqjDIkPLlHCPQlqecynlTx+EtA84KhRyQUiYLR6cDYvGCIrowTgWcrj16Af7rHdOzfR1umq4Bbxy9498BDz7KAYBcZ1TLQbaXPLyzoZk++rCzHM4Ft+SwhUykLhdMqLJafR1hhAWrVBsaI/VsZQKdDYGXOgACUA/xs6y4Dnh0by9bH/D+Kgp58sGXruH2l+I656dmy+MxyKmrmQHS94r3eReIf1VoN7W4MWuPnenmW8V1IM+e8kC3F1XAQdq1eN3WtmP6RwpJwl8WJwPrjP+vJZHIdssSCKV1EoY8sUUhJZpWVQX1mV9Hic82PkJhjdHnx2eOFYpaDNPtELPtMOIopcxhYMCAprhEDAaZTt9st7sM5S6uikH3mlrXtLsRd10dkG4WeR6YDdPhlSkKgAZ2wQispcKx59PoH3EK39epckcSgLNvPNQ+BDUr1+jCBT1rZDpPLgj+z6lR+3KK35e1xXd05uG0LOXXYupYPOWWUcaJgFQXL6iUpXl87JQjNiRSCGXrCAiWGIsntKmHRkr8ueaYSAEYZc8LM15atb+X76T+fQKwcsXnltUDk3lnNWYuSAE+vVt55hWpF/9zDY4odTzIC2FLFrFWnBOFZkDWNU5HzNecn2XlSbaB5gwDZ3IzlgQoEUEtF2YABT9rH1CmqBOzdzuxSVUGShti9K8a+PQvodGcRRcIiDpktTI8kLtFJ2NIJ+6UT4E0g5RAGhwYwvzDP+7D3uSdgOdW9kgcMHOeBNmN5KjYGxLpGFV5eYYCSwHaXiFXMJdoysc081u16Mg8w8zVn0JRAWNikKWbtEojppIoJXqTJwxy3NlRnBYqFxdiUpQZR3OBeYdow48QuSe7S3E50TgLZU5XZZAEPgQ4R6sD6NldY8llnIqmsbTHkgYJkoOUZIY+I19yGjtro5ov8pdRjdjQ4uYnlL+j3ridtbOue+bmpa46OKbNHNgpWetoUyJTDzJLmZ5RViAPO/Y3AVOXJs0ZGTF2iNCsBtiuE7SbChA5ZgtomMuXSCzPzsNBWlBiQs1h2mify1JIL0M6JCLrntqwsAA3L0KYyE8s3iWM+Ls1rJLNO7U9tTgcg1wwHsHNSmJXYZlaxwMxiwSE1kGekPnuDMsooo4wnW4yOyGthUYBg89XrCQ/6ujIxDgwOPNEl+daN3/qt3zruvTvuuIMBX2IHn3HGGfwe+fA+//nPZ0buxo0bH9OxKVn+gx/8IC6//HL8yI/8CD9n0CI2+QT/8z//MzOETxbVapVB6P/4j//Ahz/8YRw4cABnn3023vzmN2NioreQd/3117MCFsULX/jC445z22234ROf+ATvNzw8/JjKXUYZZZRRRhlPhpibm8NFF13EP/uDkqlITYOSnuhFNgkXXniFgMDplPlJ/h2lUmIZ32ZBa3X+mHmNC/iL47G+Mp4ccQoYwLKw5uSNnWytsuCj5znwiv9/AvC0B271y+BmzEKU4vaUj33HvbFArmLgsQcOWjByxXnkuMfL4p5MJref/ftI2/YIyE5iWRxUC63IvrIWK5QWiJ2YnDRfqAeY+UQLqwK6Cdgn5FFtj+sXgLQcpgeKKstOlk88ZmEJs8U2mOqVIS+27bWJq5drqWXM3xXtFPgKw4N1Lq8XBcwCVrDOjKp3jVVxsUQOMqxEwhbze3KhvWty/CLs8vdsGxRgvJLF8SBFN6uYY1bNJomALLTQTNKdvAJu3p5pYu/du7DmnG1mbGqYDhUzC6qLFMN5gHv/3ycw/cAeXPzj/wvp5gkERap9bn2IYUHVlNlqIu8qzLOV8uIMnjOTNuP9EtJ5NtUkUD9jb11hWLFUZZazl3PSzcQnM0DBFGdpTl+utzDc+ph7OB4A7geOXZsqy6jzLKPZ6nq7C1z8vkxGXdnt4BIkPAtiWHCrNPcqo4yTBoGmQRAKRkf3j/WBJUY+38ssSe/JCBYo9gsfGR/Bho0bcO999yM3Y5dOFdKOX7Dt5ZYT310CeGkb8hJOzVzB4J25v1WqxbtbCxO3l6NxYm97Z9NAAK6vKti06XSMDo9hcGCMmbgz07MYHh7E7NIShseGUa/XcPjoIdxx1+3soUpqDqSesHXLFmxevwE3XHeLGdYjPOfZz+Xj33nXHVhamjPjT4fn7/GJcXznC69BFIpn/NBAFTdcfx0efOAuM59kZizO7RhHi5c+wiDCqjXrMDI8wdLRC/MdtFsa55633Zy3g737duPe++8yc4rPXq8MaObSLghMG1cVNm/bgvvue9C0pULkNeClxEgN2JbBsUfp4hATNLBWBB2YupnrMjo8iqxpztkm1msgKk+5s0gYgCCbBNKa6+EliM112Hj6dlRNva7/wg0YwqDIOzt5aGaF+5KgQ6Vl0Bjo5C1sO3c7jhw7iumj06iaNkxSKRdNX75XNZtV+BwaMTLaz87xJLesKqZuIyEuvuJyNL1p7D72ILZs2cx1m5mdwYaJTZg5MItbvnAbH6/q1U3/0vIM4GsMrxnB8Pph3LPrbqRmLiW7A9XxEDQDVJtV1FFjOWkWWfY0s4Rzmz2nWSA6k3k/U9bJT9jB3PczeR7jp51cmMeiKpEy+MseyYD4BZvy+qpncVA8d7lMPdHg5uM5uW/fl+dM9vSFnZt47rUJTry5Fo9rvg8zeVZRcnQCkVndopzTyiijjCd5kCQ0vZotmLFdfn6zo1EXn98S+D018Q//8A8M2Drwl4LkodetW4e9e/c+ZgDYxete9zps27aNAd/p6WkGbEnWmdjEv/7rv/4ICffAi1/8Yn6dLD772c8Wv/fLP+/atQu//du/zQxiCpKT/rM/+zMuRxlllFFGGWV8KwSxf1eCvxRkqdAf73//+/GFL3yBgWFhO+YCApdgcBlP9SBJZwZ9zcsbfKJLU8ZjjFPkviyeptqyPwUE1IWUrGMCC9tnORu4t1Ctis+Y+cTMR7eNA9v699NWKjljOUNa8FNw0s3LgUzHDnb7O5bq8vNLOMlbiT6gj7btK3fPf7UX2oK/OUlW+svPJ+ewXrteaL7Uj5tzedwuJB+pLbOIpD5T83vIEtI1pHlXZDGJeaNjEGLIfnq5SC1q5dodKDIvtDBY3eK61ivY1iz9qYv3C+DX+ggLgqrFz8+Cr1S3algR3z2mdPsCOKMHHPdaDOJtSGyyzPrc5gJCS/sqbiNY8JFlMpUwi5djwr02lveZV4R2qvGJa+/AwORGqHwJEyN1bFw9hLEoYIDaV7Oozs5grK0wfet9GN62gRfxQ/OlejFpITttFQY3rcElz7kcB/MYlSS3HpQ5etc0h2MKOXatu+79jHGR/+4HVonhFcOxfglFoH6fpgnXL7BAMi1Ad+MMNU5yyC0g4Rfn6d03DgT3bNF04YnpvKq5vyrrmUkysKEweBV6XGx33V0dhB0Im0DRSyLg+ubKsrMsP/gESQFllFGGhJMTZvY9MRWth7fcw5Axn+YoLfdrqhPUhutYv3U9vnbv7ahGVVzxrCvRMt8bxkeHcd8992L62DHx0aX7m4iwKmPlgMHRIYysHseevXv53g0JPFUy77HDaubK0/MhFhayZ7nB4p1bq4W48opnYf2a08yYVGW279J8E5VqgP2HZrFq3QSq9RC7dg9j7559WGrPo520eUQcn5zE1i1b8bVb70a1OoQzzzibz7nxtE249as34O5772CGc22ggi1nnG6OH2HXg/sxNnYaBuqHoNOjZjzsII1Sy+ZN4WUeyyBfcvpFeNaVl6PbUugsZdj/0DSmpqdw9nlnY7FVMW2wl9Wl2XbAy9EmZm5IzN8uKyqs2X4m7j90GIvHFlElT2Mzn0ZxJAAhxPtd5pmAfX2p3HGQI/FTnHHBOXjowYcwv/cwKjTPWt9m9vPVoYykpl4qJM/lHF0adxtVhOND6BBLOrEJWzYpjVjTsGxgOq8mc1zzapvrP7xmDIeXjqHjJfAjmojJs5bg1KopV4XlqxlG9WMBr5VVhvAVA93hcIhN2zfgq7v3IBuJEa738fCBPdh+8TloTS9hzptFHHVMmULTPBHXhdizRKoeWT+Oq17xbKw+ugZJpWvmHtMfuzXc9OmbMHfPPGqqygxiAVhDeV6wnszEwmaWuKl6ixPXLECOPi0LO3ewL3GmOCHCV5IQRvCxNtcltc8uftLla+krmeN4zsp7yU8sk01exr5IRnfbXa4HzXGwTF9pY2tBwZ7P9EYG8QWml28tEeR5y5W1jDLKKONbIQiEpRd9HVhqAs2m/DwVEtGUO1qrmfM1gKEBoMyVObVBi83Pec5zlr1HgCpJQJ933nnf0DEvu+yywheYGMY0d7/rXe/CzTffzBLPjcY3pt9NC94UBE5T2Q4fPswL4R/5yEcK9SoKAn7pOZPeI1YxsZvvvPNOLC4ussT1pZdeih/4gR9gplUZZZRRRhllPBmCAF2SfaYkpkcKmreXWyB4AgQzGKwtGDxtZaKfhF4eZZTxmEOZfj1sQV/Tv1X0RBeojG8gHncAWNsFPfQtgheAleWIrgRL+xmLug84c+xDkY/uZypaRrESxqmTyGRgLleFJCT70fVwrGWyzj1auitH/2cozlWUB2rZe+oE34KdJHPBVrE/eozVXis5Cq+nlGV5eoWsbqNRQ279Xqfmc8wsJFg9UcGhA20Mj0eIkyWM1atoRFSOivjY5VlB7szt4iwtIjuWMJe3jzWs8+XMz+wEyUkiP2oZ1LadCyi8rzpyzLS45v3X1DXM8XLZfdc/twvKrs1WZEotuw7Fbr1rFSPC4JotOLwYoBoN4uiBFg5MdzBrvlx6mcJ3XjSO8MhOxHNHicuEI1/6KppTZjKOKlh76XnwtqxDVQXYeWg/hs/aYhl0HrPJXO2l7/hWGtmzvoz9LHJVlI2BUsv6o+vCbCXPeUeKRCuDQwTwpnlxbUiiq9nsoN4I2VtZvkDnRQIF90/nrc2+ypB7zUrLMpjOHoxO4tIlNDig2l0XXbDV82XXhXw3RWq66Ee5Ek9FSMKDZ7frscnLKKOMZUH3GTM3A7kfieVPvry5Zf6yfLIZ4XWAIA844Yf0j0c2DMEbM+NOJ8fG9VtxuDmP1aOrsRN7EKm2GUe6yFXCfqyZl2NRL2Hrmadj+7nbsevoDpkLM5rzfJ4TiCkaUEKJuWfbdO6BEKvXjuPg/r08LkY6kqQhUIJJhLnZJhrVNsaGQmSxKWHqcx1GBkfRnk/QbadYu34tnv/iF+Cz134Gi4fnec6JTB0qQQ3Pe+7zcfjgLOZn5zA0Mszgc8FGNmVOdAddv4PYz6CGPBw8dgwHDx9hRilp92pPvHXJEqFrGjANNbpVjYPzMzi8ewZeN8CBfVPsw14dDLBn3wHTDn0SvpSkpCgpKUBLxWb/HPN+F4uBKbuX88MOewx7knxEA2WqZXwlQLT4SkZJO+b9dphgPmihFcbw8xARAY809oda5ltN7VPja5L65hyBKXOUYCmdM+egRK1MPH1zC7bnTqo/l1X0nPyIU7QrMZYqTTS9Jo+rHnkoZ4E8A/Dcl5j2o2QhiOcvMb3NAzeBmARuJqY+ETHJfXPNKiLhPdOewt0P347VqyYwumoMg/N106w5Qj+En4aSpBSYNqBniIbCfDiP0c2jONo9jKH6ECbSSTTWDuDYfdNcbtL7zKjcuahWIMk5vY5UNjye06ioFZ7nWDHDN+XQqchtK7DMdJiaPVJJ7qLnB/IJpp98j9AzTEqgd8JzG0lbU78htjY/q2XKAsvEUG6bfh3ypcpNOWKSHU9Mvcx7xOImOWxqL8riIr/igBPKPJkrKemQwG/rNZxnZBehUA3C/oeLMsooo4wnfdCQRUxcx8btdoF2B+h05UV/n0BY6REjDAVcrlUF+I3Cx7/cZZw8vvM7vxN/93d/h2uuuYa97Ym1+zM/8zP40R/9UZac/EbjtNNOw0033YTv//7vx8c+9jF+7zOf+QwuueQS/rlp06av63gESB88eJB/J4CZ5Kz/6q/+yvS5brENAdlvectbcP7552P//v141atedRxzit6nFwHRr3zlK/F//s//+YYB6TLKKKOMMsp4PIOSmh4tOYkkoE8+PysriWteDAbPmdeUAMJIH9/CllHGqQgiAvijFvQdRint/K0fp4gBvCJ62sjHsQf7ZYYFnKLFXH8FGOsAQScPqArASlsGj3jC+T3KCfpYqFpANgd6Wl3AnjRywSzVxX4nBYKtNHV/LPcWRuFdp61s53K2ZP+3cVWUWwBvkSjsdlu8qBlFg/jvz9+HnftjbNo6irlWHa14D3RnHq944YVYP5IgUB3TCsQw9SzX2UUu4DOzc+37xNRR9j1XmiJL9wQ3s6Pw2AVbqmNaMNjsJrrHhnUt6N5zUsZ9LQkH/PazWfvtZPtZ2sJq9Yp9gJVsW0kY8HWManYMG0bN4KTbqI9U0KhG2Li5ipr2MV5PkW6cxIanPw1pqw2VpqjQYnzgoxN6IBW1fKiOVRvXIRmpITWnDPsStIrycyM4X2UpNEtA571+4zx0HUBK7OYsTwsWIDPPtANZNXuAskwzLVb7FWY7dbqe+QJMsp85s+HE31JaN8+EqevalmTRSVK2399T2q/vMjrQF7qozErWu7u3GODlzTyEDIrovmtsJTR7t3MZZZSxIiQBBDxe0P3qaRkFKaGCsDN2GCfp2owAqkjE8SvmvYa5r8zLSwMkHdovYKCKATgzHpEfrRcSsCZSx4mfobGqAV3XSIKumS+qyDqKvcxJGpgAO8/cr4QJL6VdDE8O47Sz12P/zENmmDTHSHwGW/2ggk4c486778KBfcdEfjrO2fd3aLABP4xwbHqWmcqrt41h8vQxdKMOUj9GaMq356HdmJteMGOQwtxMC/v2H0CtWjXjWAvdeBEVMxbHZhw7eOwgHtj3ANpxgluvv8MUykdrasmMYYySMtBJbUbM1zxQ6JqRueO3cf3XbsTdN9yLKKlDU5lNgx6cegitzhICaje/Nyyr3Mor01gdmXHVfNZFwuCfIoUN0+ZUD1FBoKtFo6LvFO/tGC74rNcwY2vDtEWQmTnDY3lt+ozGRAbi2Ss3EKY1Ua8j8rmlduuaLdJChYGfNGwBe6r7msFo6gfVsRqqk3V07+1Irloi9WCAkiWthQFLQCUnHYGkxKWeVM6EHRVCcz1zLM4uol6tY/3welx92dUYaYyh4lUwPDAiCQcqYAY2PR50k9jMdTlmjszivpvvw/CGYcy0ZnHDwzdiWA1jevc0BsIhBGmIlOucCvPY7OOZNgnomYNMljOZXwIlcwwnTmkx6PA5k4iryU8ons9az9yH6U1KUODnM/NZpMQXmxQyRMpbweXwkS1GYuZGp6RCn+Z5Lz0tNjdWoDNmXOdBLuIqcMmCPgPG3TSTfmAOQn2bErH8gDJXhdlcqlqUUUYZ38pRqcirP8iitZtQgil6Xz8V58HweBoEy38v44mNV7ziFXjooYcYAL7gggtw7bXXsmTzz/3cz51we/LzfclLXvKYQFOSkiagleSZ3/72t/PzxQMPPMAsJ3qffIYfa5D/rwsHKLsgQJiAX/IupiAZze/5nu/BsWPHim2IMUwy17Oz5pnjhhsQm2dQOs6OHTvw93//9xgcLKUEyyijjDLKeGLjzDPPxBVXXLFszlsZP/RDP/QYj6YskGZe0Tb5wp/N2tec+Tx5HEpcRhn/0/Asy9eCvgQAl/GUilPzdc9TBeOWQtiyPWB1ObDrGMLuPa8ApJihkya8+On7Tj7Zbm+Zjyw1rVUBKPLfK0BGWoQnOV3P+s66hcHet2HHKO7t1w9E9v/sP25xfCsTXfjIOTptLkDgSjC5/6d914JsOTNpqM7aXJo4SfHQ4XkcbWZY663Dzj334uztG3HPvj3MXs39Li+MCvPWs0ADhB3qQD8Ca0+wsFnIWK8Ar/sjFzQXBePULZg7meOC2Z33jmkBcmGvLm8zuMNZ4B62rPy5pZ1mfUAmH9sxV5HbRAJ3Lei8IilFi9qXnbMRGW1OfpjmmKEmxlwMjyQjE7P90Ahmm21z6hQxgQ0kxZzS+Uy7HWlBbRjHQpAjMpXOlGYG8PIGg3g2Ksd+lWMIG9xKaKMPEC98g810br7YKssA7vUlZSFZnxlQtPgiPr8BslhYwqRqSX3KScnSMXyHIGSagYHU/E5+o3KfqELe2clwOtbxiaL/fnTs8/7kB2KSCdjbA+DlYpVeFmWUcbKgezUo/OrNvKAJ6PIK2WUGvLRXjHk8CpibvdVtIU0SBoB3PvgAknmFmdlDWGrOQfmZgGm+9Z3VKTMsw3oVSZaKnysx+pW2rFY7KvshjZLo5i0MjE6iMkhyxW2EQRVZIokeNI4kSYydu3fiYexleWr2vOUBTcZ9kvg1W2FPO8SzN16BdraIzDfnDys4OjONo7MzzCL2VAi0PPM9xozLvmagkMrsBQpx2sVCZxFzCws4NHUQUaeCql9h9i35zjIxlpOU2G2WGcwxuphaOoqlfAE1M5bVgrqAgWa88wKxKdB23CsSvxzSSklVbr5wtFMemi0wyCih7p+m+H32YI40KvUKavWa/M1ev5kA+WQvwSzvTPyGPes9TGzYoIJuN2WmLus3FPO9KJowZ9ezqgxEAjZjfFirotZooEvH89gdQQBpAkQJiM51UQeeCygxJ82ZZs5S4u0cyVwXu+/cjSE1jH1HjuGB2V2mXyTY0dyDVaOr0JzqIIwrfHCqCyUOsQVxx0PrYBv3Td2LYDBC18ybi0tNdEx/qLQj1LMBs11g+nTb9L+OfRwwxwg8Zm4ndJ08Jp2bmrWknIy/mh5EbNtcOmJE6hn0gOJrC4LLc0eayZddem7jKSv2eQ70iD1sOkRKoLNPP+1cTz7BaYU/U7yPz8xtnsOoH9Hx09T0Xh8h2VJogfgJ9KW5M+VkKukOWZry3EsM5lD1J8+VUUYZZTw1gli89CrjWycIPCUg+K677sJP//RP46yzzjrhdiS1/Lu/+7sM7BLYun79+sd0/F/8xV/k7ekcC+Z5jOQrycOXWLx07kcLknom4HhlEEuK9n/Ws55VvEeew2984xsL8HfLli34vd/7PfFKtDE1NYV3vOMd7BlMdX7zm9/MnsFllFFGGWWU8UQFJSO99a1v5TnvZEHqGd/93d/9jZ2A1kyCVfKiMN/BkS2Y780L8pP+LqOMb0Z4QwL6egT8DqFk+T6143EHgJmVUmQZK5yYVeEYiVZW2O/JMRf+cbrnSdoDXMW3TTawcryeYnlNZYEx3XdO3q8PeOwBi1IGOcdyEHOZf20fu9V95t4vztFXb1qYVrr/HP2Liu44Xu8zJSAAA9N2UTLNFSpRwABfs9VCuzOLdWsnUfcW8OY3Xg3VaWHv/btx+033YdN3noe424QfKst8ssDcMs9i56Un73mWfeRkgV298nw5SFjUUXSM5WopByjmSHSvfdwrF41h3r8Hdsq+IomsCu9FLisvbIscp+xKsqO5ZSt71oO31x+k3JYRbBf06ZyBSpGlvesYEDRLgEVuAXCS185iLnPVD9COu8wyy+IYtI4e0XJ1o4qzTt8mZ8sto4w7s8LxK8MO3M5F5rLozxAJT+WSEMTjmYBdAn8ow5n8gGu1Bn9GcstJmmGxvYTB4SGRLqf7wRNvxTi1PsR2oR8WbPacp2ggrHEvbqMxUGcJaSHwHg/4niipwcmxF4A03Q+cJJHxeT1iZzHQLIkVXMC8nwVdRhllHB/C+s+tdLp4nWseA8irVFlslYE0ur1pjgsk2QlKxsJbbrkZdTVg1Ro0oiBkr3dilub8yoRWab47LMaLAtASKsnUVWFI0s/EbJaY/VIvRmMsRBa2kPkdhEFkbmUC5QI5PyeXmP0o+ciMPcrPRR2CEnICMIDbydqojQyhvipExzPHCc22aYSw4vP5talzYrYPKxHTjTIzjhFjmeqUmDGamLgkdd3OWww01ms16CSHwKipMGy1gL8JJbd4KXRIIHAbLb2EMAzMWCqfU3lI5trZTRCQ55Jw+Lkj8GUsg/jLiuOsZ+cMuUYy10OukEuGYVDW1LluxtuKMuWOuf487ylxk9VFfpo4LbuHHgIiiYXd6rR5Hs89UXyQBxnwsw270dKxyAbA7JN6lMBj3ifJZJ5PcgY16fmGd81kztPWq5llxQnY9KQ+fmIKHCdIpjLc+ZU7TRvPQ0UpWqprJad97EkPIdABhtQYojCStkq0sIFzc/1jUsQwl6xp5pm8jjoGmAHuZz68RCSdfdPeFX5cFOWNLCHQ2yYmUeKWEtYv9xklst/MXNdip0CexwS+ppmoSLjkM6A3N8mzgSi1EGPXo/bOE9MOiqWcZXqXz+W2cHOsxwB0Rm1o/qyZe6USWI/tXPN96Icix67SWC4e3Yf0vMFy1eYooVfKWpRRRhlllPGkiK1bt/LrZEFevu985ztZNnnv3r14z3vegz/8wz9kP93HEsT2ve2225g9TGAuPV/QQvctt9yCv/7rv2ZQeWUcOnQIf/zHf4wPf/jD/H3WBbF5CbR93vOed9w+H/jAB9jDmOL0009nxvLY2NiybSYmJvi4xHL+1Kc+hc9+9rPsuUjei2WUUUYZZZTxzYy7774bP/mTP4mvfOUrj7rt//7f//vxO7GqAQFl7K22b6TLAeF8CSttEsso4+sPWpQaLAHfb+M4ZYJPxeIeL1Tak9GiHP9h9XU9twCIAgBU6PkA06JrTx5ZWJ89CWjd975dRCQv3TwvFvKUZXV4QVAwTgv/Ycfi1AJ4OUSLZaSB4wAzz/NwHAC8jNHsyiFVEzZoXrzX8zeWBeHcAtx0fmXBTm2ZvDqXv4PQw8+87iqkXgSP2DfpYbNtih/7oUsRmTacndrLwFxKC8N5yPXJIaxNXqymeuWysMm+fRCQtsdcTgUs1E5+Gryoqu31kcVYU05ecM0EuNWOeWthXMuAZhasPYb4DwujldlquS4Y4VzPTLxt2acy0UhzWRQmz8gspYVucNmJ5cXbmO3pdypLkmRIaRteRBcGUUzynKaeSZKinXdNO5kJs5siJXA2Mz+7MbPAyTuQ9DIFHDZlTlKWzyT67RWXPBPnnH0OYjPZ+o4Z1uvM8tMtPDsfR9tX2XtaCffMgTq8oJ1JW1Mb0eL/wvwcy3Tddefd2Gq+CFNd4zjBXXffiWc/+0oGBPh0JPusrJSs7d+pZZ9xGUhyM064/1HuRKs1j0210+D5lglXENt794b72c9cp8X7zDKEPWXlTfOY+6rrr8yysmBJnmUnkOUuo4wy+sMlFtENxYkUec+X3Y2NIBBPUEH+LKoGbGVAo2po5qvKAIGjGT/nByz3bsYtBmdzljz2rU2CH/loJ11h/ubkj5qh6kec/GKRSU4wYn/VqkI3a7J0c9xNEAEFoMmAtRlj6Hg0VnZ1l8FNTjiBjNst3UTFjDFttYiOv8g+xEzyTIU1S4MRgdQE9RLwS/NINxP5+8zPeHtm9Zpjk8Z+khGjNGQFYToXMYh5yPIJoDNjDkkq+6kZk812AQHqsdnWt97kNgEpl/mTbRlo/mQViUzkrwORUSbQkduLVTJ8zmFxKiLOq50TaTxJyDIzCgZGBjA01DDTSJvhaW3nZ9qW2jhU1rohVzzPcOJP4CGKaub88wRRM3CpLaOZ5k0qh7BWabIgvc0cMckQm3rXKg3UBgYwl8/wfKhyeTYh9i+N6wQK03ROc2GWkRh0KAo95l+dPjN9IPIGMBCaa5/EDLpSsYhi7NFjntJ2rs6KuoReaJ4bfHO+rplOuuaS+KiRH3UqSVmJqXdm2l2TYjQxminfzmzvmzakclV96zVNMuPUV3TNMtFzniuoXei6EmOa+mcuBO2eoYPN4xLlCknI0xVfUquoO5kNQl0p5lB5VDHXN4w5WUDlAujzsx31B0qYov6XpWyh4fE1CkVGm+6jgFpN7oc2bezL9dG+9Qcuo4wyyiijjCd5EGOWFqff/e53MwBM8exnPxvr1q37uo5DgOxXv/pV9uYlH2AKAnfvv/9+fPrTn8batWv5PWIIE9OYwNt+4JekMX/+53+efYtPFMT+/Zu/+Rv+PQxDfPCDHzwO/HVBz1/vete7GPwlH+F/+qd/KgHgMsooo4wyvmkxPz/PahR/9Ed/dNxnb3vb23DdddexLUN/PHb5528kAuu7OsYJ/xx5sw8QXjRffjun8PxlPDWCmBwNK+s8LOBvCfh+W8cpdfwpGKR9zIoCPFW938W/1F8GUDm/VMZzrVSmsBAtiMrHdwCsBVfzFX67ywDbfrCY/7+C8dH7vd/j1/3ujtsDctG3fx94nOuC/XrC9rBKlAULmkFvZX/3LAjoIzDtQQvPft7B7OF9vCifiSOrKcQhYWZmYI9IWjDOmf2pGVxNLKuKlnEJFE1oX/M5fRYTIJpaFm/S5gXcNNVIzXYEppLPJC0wk7xloltmP49fhMoSKzXp0vYdBgx4O1pUZqYqLdB3BRzMzT4ZgYoBA9HCdNa8ME3S1gQ8UzWI8Ua+kcSKTXPzWVblxWQhnsXcjgQYcPsoWbgl9hMtXBM4HZgvlDoK4Gch2sQErkQs5VgNq6hmwqJFFqGT0uJ4B3kyCvJbqNZ45ZzBhcC0eVQJETUGoQloIZDFdo3jrmMP57d9qp9NK/3BMZ4tFY37Cy1IU9kXFhZRrzeYBUjAQ7PVhB8EmJqeZvZutRrZfkC3pUi9Oja0Q3YFrFW29+TspUj9gOVTiRGoxWORgVosZ7S7+hQSzyvqx3wxm3CRZS5Boc8TW7nEi5L+W0YZJwu6X2ixy3nSu4QKp25BIWxTSSoi1YOwGgqIirxI1tEqsclC4iksfFMBPwW8EtAxbnUgfrM5g6PsE26RNrpXaVzIGWD1ePwnZmxoxk3V1tYDnvUr5Fw0xygra68siEzF9ilxxoz3VTP+R13kYcbSvPyxx5RPBv1EzcMZqOec45XbeYv95yOFhMZ6TxjGNC94nDrjCRhn87dknjPzWxSydDQxfiUBJ7dgOreiVbcQxQWee0iemaSAKWHJjOcpqSwQAKxDBgxFelsVwCMsyO3C4+nLHCMyY7QvLGNm/1KbMps1YHYrJ1vRPEXzKckUE8jpiZQ3gbp0IAKbU97IqoLY5xenF0FgbO4LUE3XnmYOljTOtPhEaxnn6Xq653TPt+xgyg2w7GD6R8xtn9F48x3RE3lnnduEMkrw8kR1w/UjkkNm2WVtX7QPZwCJNzGD/9SnTPlyX55NdBbBzhLgnAQ+EvWXWFRM0kiuN83hKpVy+wyfs1IGu1VYiw+XIMHXjY2PZZqjthSJbJJlDiV5ItXimW3aPVPkW2z6Q0ZAtXkG0NJO0gcsU5ueaXKZewkADknJgrqwqQOB1nQV4jSX+5GTB6ifBcufHcsoo4wyyijjSRZJkuCnfuqn8OpXv7oAfylIUvnIkSMsnUzbvOhFL2K55UcLSkomsPdXfuVX8Bu/8Rv8HrGLyX/4k5/8JPv5kh8vMYId+EvM5De96U142cte9ojz5s0334ylpSX+ncpLgPEjxejoKMtI33jjjQxMl1FGGWWUUcapDlq3+fM//3P88i//MidY9ccLXvAC/Omf/inPe1/84heXKV384A/+IEZGRr65hSUgj17BWvsGrXUvChhML/qd3ivj2zCIHFA//lVkD5RRhsQpAYBP5nnb7ydK7E3l9wSU+2WeaZGzGycIaLHOMohXQk7CTuTfYG3p4CSPV27XX5YekKv6AOHlPrj9Es8ro38f+84Kad0eW1gYsD2GsN3TIsCKF795AdwXaWvxABY2LAFvtDBZqQ1g8+mj+Od/+gjuvPNO65WYCPsptQv+zHoy75s2IyAxVTmyOOE2JiYUARG8SMwMGo8XhrWOwV57ni/lYAZoysyhABWEIUl00oJ2zv60JJkchAHMfyz5SS/PEw9Ikr30VcSym76vUYkaZrsK2U+K7KYXISLPQS8x2wbmOBkCbxCeSs0+suJ/cP8CHrgvNl8whQGdUh2ZJZzyYrdbpCe4omLK4gVVqLCBbHg1Kk/bDjU6hAVaiE9jrJnPcWE8hOe/4Ew8dP8hbDlzNf7hL/8JIwOb8LJXPwvN7qz5QjuM3/3t95vyR9zHJkbGBefwHXN7OWu2v//0WLRFz7IsprzoC7lNRmCWLQEQpq+Pjo2Y62naNgq5XtVahL17D7APk8uVKFbC4X4XyWUCCwq2VFEegU6cL7b0Ledz3evzWPF7r/w9efVen/f67lOvx2ZEj5FPQE8ZZZRx8ijsBmwSiHtJYgndP6R4kMBjSWgPjaEGj79xEoME4pHLvEAvkuOVYUGYoKzsQBzQMDRjbcj+vTTXVLwK81wJACPPYZadZt9yGr9JQrpixnQadyMG5wIGAhnCY4lfVmGwfvZcB0/GMWbPmnOT17imMT3yEDVCtKc6Uk6eW3Qx/zEsmKXFeCXDk8dKHDS3i++r7qksaNmGkln4c5b91YjM3EKDESkl+NbGgCX9PZEidkk2zo/eWtUXjwAkq09/EvNWJKLluSO3zxQi6yzHcKAzy/lTO5MBu00CIlzeYzauz7LZLP2sRF5aC6rJrGBK7KnUquy9y5N34rHlAoOTjOH2PTNYwJKegSgJiBOfaJ7wRC6ZmMUMBLukNzqN7xXJUNxemWUtm+uCXNpUMztYlDtEEju3IiDSF31tlUyUPI9knqhsUEaUPI/lPV9eKpsWj1w6KvVTxaIi5AGcIc47nBAQqw6zx7O8ywAyK1TQ/Ed1pnrEGc8p5DtMYLgkIuVw8yYzdIt5xmNFE2q+NIgZYE4p6SAwNSHpdEoIy8z7nRgVkslKFKG5CAjg5/6QibEIP/toVv8gL2JixSvTjwhYr5D8eUpseGmbCvk9K2fNUUYZZZRRRhlPznjf+96HgYGB42Qnb7jhBvzET/wEA63kBUy+u8RYuuaaax71mDT3koT0JZdcgte+9rXM3CXPXmIV/+Vf/iVe97rXMUB87rnn8rMmfWd1ammPFE76meKFL3zhY6pftVrln8TEKqOMMsooo4xTGZRs9IY3vIETn/qDFDLe//7346UvfWnx3nOf+1xOfvr93/99/vtxlX/+hoNYwqPycqFb5uvwkkhGM2PYvEpQ+CkU5F1VA0uGE8BLEs4l0FvG1xGnXALaxTLmLLNA8sIv16ozw/nAMaxlF4N7bBG9YoGuJ6fsfgrBth+MPb4cbt9+4mbv3PkJt+9/70TgsHZsIve+7tUZRZn6gDi6ceHqYyV1i4Vry+TKLQDJspo+l5eybyu1CL6q8EIxrKxoQou/pux1FbKEYqvTQkTr2JVIGEMkK+qHCMIK+xIGvBirUQka7BEZVTSzsogFFJCvoCnLZZfX8D2vHWAWGoEHHqoiZUySpbSNZSizqKKiZdXInKWLdncB1cqI2ScCaUcqRXAGyVMsMQuN6iy2ugMoKLVK45abHsaH5/eaL55VJKlidmqa0OJ0woCwdoxh0CIuLcKbulL5x0/HwBtfhfnRuqlXjDDPMHT/NJ6xP8ZAVMFVV16CqblZvPJF3ws1EGPtpgk0W8Mge6PAyl0qJgQr9mWUVWTnSXziRIB+IFXnlqnFqGnvc2ZCWV9lkRcNMT45wZ+dse30oq+Pjo0t63cC2shCuDObZKDAs30GPQlnbSVmHdOXPQ/hWMM9oJj6Yc+TWaTPeRNmXmkGvkVFM2dwRY7dYwvnViaaj0WAVBoX6QxllFHGiuDkH5G4J8YoLZhpqwzBQCJJIttcJVIHUBWFodFBNOOmJHoQV5MUHcJcknZ43BTAkVifBMCRogNCzQoQYNZvwj9JOjhgoM+eAwmSbm7ZoBGq1WGzTWj2Z5FiyGgugKST7xXFDWFcCrvSs6x/ScjyCl90C3DnwhIWpqWMZQT2Un3Z9gHkH5wyO9YPQrEsMOMIgZEBgYIs16uQWpCZGJ8EFobkjZvkLO8fqZDfI693T+in1gtWW6BZWzapSGoT+Dc0PMqJVOKr6/H4SF7q2gHxVvoe1seXGbm5jIUVM1cyCGvamQBu3wLA2iVqQRQuCIT3wi4zYhvmGg6ODKDVbTFIr1O5yMzMTfJeEg+1n2cVHtgzXtjAmZnv2MbZzq8s/MCf+0W/4DGf54vAsm3BSQRZojhJi+rbTbuStOU8kJVIiVM7+vTIZ+cA7Zn6Eqvb1DMw8zS7EJv5XpjCOTOYIx1yvROvi8zLePImv+aO+bsVtNGpttEOW+ioNoPAiubTjnkqiCtoZDVEccQ+w4HpcwQkyxzjWQuKXPqsrxgoZ2Zy5jNInPkxOlGGbtRCq9JGPJghrmTwUg+NpRqXI0tM/6GkpEDsCzwlc7nKe89c9MzkBZqTHqpmDl43sQpjAwOYPhgiNo1XHxnGbKcD3039ZZRRRhlllPEkDZKbrNVqy5TKyJuXwN/Vq1ezNDR56tKiNb1IRjmKosd0bGIUkwcwSTrv37+fE8pf//rX46abbuIFbwJ+v57oV9GiMj1a0HPBvffey78TG7iMMsooo4wyTkUcPXoUv/ALv4C//du/XUYCI1UMkoF+61vfyt/xV8av/dqvYfPmzay6Qa8nZag6EBAguKr3nqZ1IgsG5y37aqMEhp/EoSoC7DLQW+v9rh7bM10ZZZwsTqkENIXzz+0HoDy7iOwAtn6Ijf1weeE4KIAxz0pA2yMuY1e5vYVl02MV9bMaHUNyJctXztcv/7hcD32ld+qJ31suscvArKcsJm2BOgioLUX1BOBzZeLz+rzoutzYXY6dmwE7DGq8kEmvMPIwNjCEsbERkMVhqsVvjxfpM7NttY4rN16K+R2HMBUs4mA+DR3Z82lhDzX8KqpRwzSVL6CsrzC9cMQC2Rkq5tRjw0uo1Um8sYNMz5l6kRbjAHwzqSTmb6UJiK6aw8Wm3Svm99Wm/qEpaxdRQHLRC0jwoKncIny9ynw+at47yj9pcV6rJnsGBiAJixB5ksBH1ewfIcu6vMDOxGjts18mgSgEduSuDynxbk78AEOzc1gw561mKTaaclVn5tBNauwH2Vlqo1Gv447du/HMF5yDelTHsYPH4A976HRaqFSrJI6KqFa1wIdLVuj1AcdiW672vBwYdj6G/QxhxwbvZ9UVLFp+TxVMYff38v2Xn1MA5dwCxH392Mp59rx8te1XvXP2yqkLhm/Bl7eH85QqFuZX3hfU/vQSSdmSLVVGGY8UDEZxLonIMROYSYAczQ0kTUzMSj8MkAYJe5rqSHPiDt+DzMgMGAjVEK9xWKlfT0xykWQpDw50yPrQgLA3Y7n/ieFK801A8voq5y8wURphJBpHLR/BcLQKzXQRgFOqUAwYkvYDgZXERGWPcF+AXwKtuTJWcppyQ5I4t1LABKiCx07anuciO15mKmeZfhrvkbQwPDaMynAdbTO+E+hJYLVIU4ecgENsTAJOqS6EKdOLxuckzQpZa5YqVhb8tUlUns2v4mNSHQKSjY6tDHEKLyOAMWDAVuZrm9yiHfNXWMS5kyOmY0WBKb9l4eby/JF6Oc+zFQLuacyla8tWDCkzeDmvKwQzYfk5QCjUPLxyIpYdNDMl2V5eTh68gZkvI068kuQfprlaP2jFaCazjZV4CosbgE3yyT1usyxLWFFC2fnEYzljzUkIlAWgAic7rWxCmmVsS6Ox5z31x8w+qTDLmgBmUpOAnJt8qLVpz9jM951qjGajjWhjBRPrViNabeZ/tpPpINQhkqkEU3uPYWb3NBb2xZjwJlFbCkF4OHn0hpnM47HK+PpXNHkp+/w5Mda5H5l7Q42Ycq2t4uzLtiLcGGLeW0BNNbAx2YSb/+tmTN86jfFwkvclD1+S/faV3GMkDR3mkhRFrUsWFsOVGs4amkSlnWBVMARVraDJ0uwEhFew/Em0jDLKKKOMMp5csWrVquPeI+lKYtgS2/f7vu/78Du/8zu8ME3fNQ8cOPCYpKBdEMv39ttvZ7DXeR2SHyIpkH384x/H+Pj4Yz7Wxo0bi993m+/gdOxHCvIhpkV5iosvvvgxn6eMMsooo4wyHktQYhMlNP36r/86FhcXl31G8yf53a9du/Yke4Mln58czN+vMxRJuI2Y78gjKz7IBAgmL+HcvHTb/ozlhVL18dSFZ0HeivxU1T5mb+OJLlwZT+E4ZRLQ/YzfHojWA7c8XrjMCuasA8+I5eNAMpF5dkuXahnoJCCWXa2F/K4sg7YfpD0RkHYyeecTgcEOSO7fZmW9HOjs9dXT62MUew5MdLKPdtFZeKfiDSn7+Nwu/eV3TFD26O0moFydOFuAJuAykEVvlhlWJAnqYduqLRjdX8fVky/Ev9z9KcyvrqGdklmw4sXgih/ivDMuwNXPfSnmZufw0MM7keQan/78vyJq+Azo5ma8jxiM7DADt92dQ7XSha+65m+NVB9E4DfMuYfNvubLmja/+yNm34g0JYVTxmvLgz3wHQkzyrSpgdIDyFVLFvF96gOJKX+Tq8rgRRQiMMdJ0rYFH8GL32AZz0wW35nBlMKrh4jXrEY6IMDFw+Z4Q+a4N3zlDnS3r8Kue6exausgs4f/5g8+izO3j6HeqGHHvrtQCcfR6kwhjGrMtM4tJOpkRHsSpiKNiRMsEPcnGTChSWd9gK7HwAg9bDhZ8P79XL918rCuv/Qz5d3Eq2zfWN4X+87PyQIiDctseU8d13f7+7hjLPN2zrfaW14/AkpEylXKR0kZzv/3ZD7XZZTx7R7aeddr8fKVezFjkFBTQgsxX60ULsncxqF50CZJ3ZSUEnJWVqAHdfKspXE9ZzQ1R6jl3s7JP5dYk6H5vWJegyFy8kJv+0gSGmEz1EnyuZ1j1cYNOOPcs7Br/x5sW302/CDCsy94Ma7/4rXodFsCTHpyj7PcuzlH4GsGcll+mOajRJibxBYl+WcWfdaBJJrQuBVqZqqyGoEnDF1JQAmI3IsuKytkqA1HiM0z7aL5ckFsUwKvcx7LPfikOkzH8FwLpJIM5InCBSthEIPXqiL05nttZ9UMkv8VCHhM1gURyUfHpnqKmakkZs3CGjphT1v28nV+ulRnloLwZQ6qhkg8YdxWLPM5pqYy42E1IT/knJUp+IB0bU15aT7OVMrtqrgDhAwusiRyZhPTIGMnsbhZlpsVNCB9w9OcHEDXnEnOBEwq8X/mhABilFMtCOzPWNfDjMkVZm17xABOxT6AAFyap0MdwSMJb5JMZqTcE0/iIojVHHCilDJtwjLUdCY/4vNQP07JAzj0+NnE1BDxkOmnq1OsecZajD1tHEvVFqb9GbTUkrnWLVTNv0ZW588nFkaw+8aHcPCLe7AJW005qkxZrrU9dLUc27xpvneaemUVc/yKafe2uSTm/hiqQ69XqF1mni2eVcGe6m40MQ9fB8x0bj/YRHxHG35H+o8OxNNepSLxzVYWMZHkffikIGKu21A1QP3oAgaml8z7KdpRgo75Wamae2ywJ+BSRhlllFFGGd8q8eCDD+IHfuAHGAAmn8Kf/dmfxXnnncdM4U2bNvFaS6vVYi/fxxIE8n7hC19gqUsCfykIDCZQ+T//8z8fFch1Qf7B5B3c7Xbxd3/3d3jxi1980vWX2dlZZla5+F//638Vv5Mn8L/+678yO5j8jQlYvvrqq/Hyl7/8MbObyyijjDLK+PaOL33pS/jRH/1R7NixY9n7NKf9xV/8BS699NInqGRPZNDiBqlyDkgi+wmD1pdz67Mla1vye1aoihXyp2X0hSUDsHKp2H3Ke779vVx4KOOJiVPEABafWfSBtjxOsNesLtiUBdAJYRBREOAo0skWcOv3rFN6OThqQWYRAMwLsPHEQBv/xb87gLkI5eSkrc/gCUBf99O9vxxYW+4lzJ9ZJjCzqTwBvAvZZyUNIuAbAb9hIbnpWQlLZeUcffK2Y7lD0mrO7akqyIiNFdKiOPn/+QgCs08YYXB0hPc92DqGeE0NOqDF3BaDEakfmFeGHQ/vwOLMxxhAbcc5Fprz7F3oqQQpyVqaAT2qewy2+hjCUHWA24VkIrRXRQ0TvHBNA5rvnSFL8HmVGUlZXLGAR2Qu4WnItbvCpj7ZKnRZ+ZIWqMe5D7QYTqhi4RixjMYRBsRsq5hrlHJ7EUCcWB/LjBfRA17o1ooWtWtI9zyMfe/7F8xWFKpdAl7aSI4dQbpvCg/cnYK+GnoPmGNXI9T8Kq67LWdAodtdRK5iLluSJggjYZbxcGwZb4oBEYjOpksusBKgxWSnRMpTZJphZZtp/5SvnxV2Bim23n///ezNtDC/gLHxUQaGqS9SxvPoyAjGx8axe/deVKt1hKGwnom9V6s1zJdcnxfhMzaD1My+43vIEwY3gQfsc+lU0Wkx3NPLQGV59d2XWu5Di63beglrWecCTlNCBjMSiRGoRJK0n9FcRhllLA8aDYgtmnly/zMrkRicJOtrQUaS1eUpzowLQSVk/964EzNAR9LR2hM/eE7pMOM6rEwwjYsxcTUrZqwNzdGDEG2dMuiVZGYMNOOz79UZ4EzS2IzSg1g7vgXnPu0SjK9fjdm5eaRjhFlWWCpa68QcP2EQEdYFl7zcSS6YYV9S42DWrcyr5J9KhWJ2KEnbW89wYnY6PQ4hvuYMQmZFggx5u9UY1CZAlOSFfZZjDsDkWWIek6VBas4XhYj8yJyryuNQp9URGeXMN+3aJ2GsrJqGHch4fDPjrhndzaapOQ4Bnl2WOiYWbMaey8S6lcQrKoskzzDayteH5msCdT0z7sVphjg2Y7Cpa6aJERyI/DZZ2dJ4m6viucZcRDMH10ydPTO3ZHwMwjdz9sTNhb0L661MLW+OmXoJOn7bNMywadIEMWfamr7AYLTVccjFdgGudemEGXpTT0pzsJkvCeimedKcNDXzOJ0psMoinEKkeqL94sfrQ/x+c5nzOGHLZ3A5sglb1CdoKiTgm5IUskHz3tocq56+DsPnjeJgdADH9BHEqmtavIM58zJXDiEnFWQYnxzGpmvOwXx+Fx688QAmFycxuiS+vSz/bbaWZ5yc2yMkL2RT97hqrtmEQmdtgtXbJnCgshf7sIc9sgPzrNTCItposiw1JU6QHHamEzjSteJkhIzdgBkIprnN9KtuHmMxaZrz5Dy3E/hrOhonxyVIvmnjQxlllFFGGWU8XkHevV/+8pdZupl8Cz/84Q/j7W9/O/7v//2//F3tX/7lX/De976XgV0CWa+44opHPSY9I3zgAx/gBfEf+ZEf4e+rJAv9jGc8g8Fckot+tBgaGmJgmnyECcT9rd/6LfYlXhkzMzP44R/+YRw5coT/JuD4ec97Hv/9zne+k5nB/UHfpf/rv/4Lf/AHf8BsrWc+85mPsaXKKKOMMsr4dos9e/Ywa5cSifqD5sR3v/vd+LEf+7FyXfMRw5fXMsnWJ6osZZRRxv80Tg0DGD0mLKz4oOcvZ/CuZAk7BuRx0sz6+H34bS0L4szigV52nP7t+3/2SzU7Rqa8bDmsJu7JJgGRc7b4bd/CtiviCTNbCxapO78n7CUIq5MYUKpn91pI8wog7LwXNTNYiYFJYpkZYl4srwQ1pInZLgpQpUXQJMFtd34Nd6YRKrFGMlwx23V5oTwlKUuPnQsx0zqGmeaMaYeEj+GxH3OCtKNQaQRQfor77jBt5NOCdIq420Xa9ZghREAmgYJpnPECf5IS24YWvmPzmUac5EipbWjxO9YsL6pCjaXuEiJdZXaxn5n9SUaUPAN1aH730EmIYTSIOBtCS08jCeZ4QRhxxIvxvloy9egi9AaZaZSm5tp3F1FRe6FuP4LAHK9GvsAwddIxYmJTEcMnS3jhPUgiJLQgTkw5Zn/lSFqJACA+SXdr8QD2hO3LQKkqLmwP3FXyvs57ntTLWbvuM2UvqoWAswzzcwvotGMcO3YMGzZswPz8PM7YtgX33Xcfzn/a+ajX6rjjjjswNjaJNWtWcz+kL8ZbtmxFtRqiUonYR9P1PW3BdWbosmekA3lzKxPau1+WJSf0Slq85HMn1Z7bYtt7l+VH88L3t3xIKqOMRw6+V9heVrn0oGVzjc5FvYFvNcLttG/Gho5gmXbosDlDPHbw4eg+DwXUI4AwZzN3hZbZj8bdWjSI5132HchUA3fcejsW5jOEqo5AVdAyY12t1WXZ6Yce3o04TsxnkSSO+HI/W0twllwOrH+95/xy7fwVkkcv+Rub8Z98zWkOI59jAqxdLiPX0+tTviAmsBnjSc5ZJIcJsPPlJ7FyLVBMlGCWm6ZkE/qUgGeSB6bjk7+5y560MvYEUBJe6xXAqk1iocnHKTHoXBQRuGCa4VDflpHlkalNbSIMPaNQrosfeYi8iCW4CXSmMhHImvoRXzf2GFa5NXbQbCGgc5/bg8pZjxro6A7kycSOpV5vvCbok96OvbZ5dRE1Qm5bYrBGNEd5ltOsU+4jGWPzIv3P155AU6tKQdeCyqf4Uc6di1Q6Ep7PSPiDT2fNjdluQts5SYt6iLL5TczIhkhH87WknQmM9sy8PxgjW5Ni4MJhhGdX8UC0C0fMv0x1zB5k2ZAwcztm7rZiL+E2ZpBVm9h25WbctXgPFu6ZxZCZh3PTd8wEb+oQcoJfhc5D4Hrgm/Yw121Eo73KPC+cV0F7zSL2qT2YNcfSxGw3/1J0zO5teDXTD+Kc60kS2OR7rbQkJGScPEEJAKb8Zpuq6bfNbhOLHgHUYLb9kmnTJKqbaxWbZ5SSAlxGGWWUUca3Xvz4j/84g7TkZ/jc5z4X69atY/DWxatf/Wp+7dq1i7d93/veh6c97WmP6dive93rsG3bNnzXd30Xf3dtt9t41atexR6J73rXu07K6HXx5je/Gddddx0eeOABfOhDH8Jdd92Fn/qpn8L555+PpaUlZhoTkOvAX5K4JlCXpKu/93u/l0FnF+QjvGbNGuzbt4+/P9NnBDBTfcjvuIwyyiijjDJcdDod/MZv/AbbItDvLijBieZC+mx4ePgJLGEZZZRRxjc/Hn8AuPgyoAsZ3R6StpzB66RymeuSoXifF0OdPDTv5q8Aj0VWU8ECqVgOcq38QqJ1geQVsr4rCm1fJ5Yv4OM6sM/6rPZ8UnuSz/0esG4/mmSUZfwKydjt41mg3GdJQzm79TWE8wvslSdJUoRhxBKIdFySx4zzDJWRGhprBjGYTmJpZpa/UKWNLoK6j2R+if3xFPnp0bJskmNocBgve8Ur0WzHaNQr+OyNX8L0zH6cs/18rF+9DXfdcwuqgwGuecHz8G//+knMTR9Eprp43gu+A0G3Dj+Jce1XPo9aw0NcX0JttIHO4RxeOsQSm1T++rpBLB5aMG1S5ypklRhnPnMLHrjxASAleecIWZhg8LRhHNs9hUpe4/bIVIykGuDpL3869uf3Ynx0And94gEER2uYOGME1e0a02b7I18iOdQRpGRgH5s6oo2aEolPWi1PvIwX6cnHkBbnSY4zzcy2prsHxJYy1ySIFLJOWoAcHvsMC1uPQXdPWRBerpfmDurkG3oymifqb7KA7/ydZX8CrNesXc0SXOeedw6mp6bRajXR7XZw6aXPZE+JuBvj6muuxpFDx7BoruOIeSiha95sLmF4ZK1If6IHPEsChcfSpQyI0GI3sZqo1p5flK+/H/e/J37Ay8vfS8rQhWy6tgCGsjRn9qcslT7KKOPEYW6OgMA1Aidzkewln1XSTKDxJs1THm8omYPGB98yg9tLHb6HM/J1N/dYmIuUbZbaJA8C1hLzfhQxw5FAWkpcSVptM6YqjDfGzPgcYsaM+76OUIsGcGxqCp//4ucRV1K84KXPx0JrEXfd/zUoYkESRMagorBqZV5LC7BZco+YLspJR524I2Mlg8SJGXMjmxzjs1KFZ5NnfBorSN3XlJiShEguOiaQkhDGQKFWb5ijzYmsMJ2LKZrCcKVxi/10icFM7Fszzw2YOWuptSRzZiZexDSeEsTnGLw+2ykokdxniDVAJajwUF0ha4KuFq9bGt8CkUnIlRgxOM9jBkR9gVJrvqkPZSkxAzjkfRl+JWY3HNtYAFce4SmpjOpi3iLFjDk9bT7PkHmplccG159AT5axJrUMKmngscID/a0pmSvzuO403lINW9miKXMNUVBlRqsy/YIUNAJPJLeJ5a0DnxOZYq+Fbr6AJO+a9u4iItl+c6gwrzLYz09LDJj7RaIQK68oXSQaCEbt8RxGUG5MwK65Zv6oaYGNVUyeuxa7agewD0ewaK5hZPZomOMNYwBjZtfElJL4wDH/I65uivXjgzjv0o24b99eJO2MzH+5T9Bl0OTPTNeTAHXTJ6MBc80mU3Q3djGwbQSHogOYwjF0zByfQxjnHTTR1kuczKD9lJPotJUABymmOCsH9gU2++SJ+amw2ElMqU3dKjXTd005PZIj72Iu6WKsuqbMZi6jjDLKKONbLkjqmVi5xPS94YYb8KIXvYjfJ5/Dz372s3j605+ON7zhDcwO/u7v/m58+tOffswAMAUxcik5mY5LPyne85734NZbb8VHP/pRNBon96qjz/72b/+WGb733HMPrr/+en6dKAjc/cd//EfU63W87GUvK8Df0047jcHmq666ip/5iI38kY98hN8jQJpAZlLXuuiiix5zncooo4wyynjqBs2Hb3nLW7B3795l7z/rWc/iZKTHamVQRhlllPFUi1PCAGYQieSCLaPVgaWFr68FnNz7yrKNWM6ZmcBOl1b1sQ0VLzALQCWStNru41sPXbe/ix6w5UBZ+ZvKIWV0EKssCK/0GZZjWBZPATILCNjv1QtLHnYLiIUPsCuLFjCNIWtlGcCWwSmgmpJFZd7U43r2ADY5aJLECIhxlQmLhzYmRlUwFKC+sYIt5t/DrRitxSXzbTBHZfMglu6aQs2LoAeByfWjOHr3MXTj1Hz5upWc+rAUL2Lz5Wdg/2f34Oj0Ig4e/Co6yRyiusa1d9+E2UVTqrCBpk7xwOx+HLh7HhWYMtSGEPvmCo94WGwQphua44UMrHY6S2isa2BhahojOkCamGNUfcxHTbRVgqpusJRmVutCj2ZIHuqYNqkJI44XyEneNEcURCxDHVbJtzhAq9lBGNYx145Z8liha64jsXt8ZmrlPrswMmuYWD8+LwPHljGVQ2cB8lbKEp1BTfNiPDO+GGAx7VUh6dRI5JyV8Lpy2wGofzKfNndMM2X7aXZigBWO/Vtcfv5s48b1qJprRpnLa9ZOoN6IOPNMfI4z86W3xhlqW87YbOoW8jXeRBKsIfkIx0Uf7k+e8DwBNTzLGmOWoMWoXdEcu/64cjrGeSEPrYvt+pMp3LkIIFH2Hni0rO8yyvh2DWJnkoyuT0zKnJJ1fESsn06sWXM/izYwEgLYslik/M3nKfmbE8Dn8+Ri9quI2oK1WiEP4ETHLIVP999wfQBhxcwd3S6i1EPNnEdRUkuS8vH9wIzRwRKOtqbRbJvx178AR5sHsJgdRTWqgkpJLFjfclV5wMsdI9RaJFivVm3O45kxtFKvWJldxUB1xtCbeB5rpvxKokzm/I+VzFUkmRzUQmaYEnAXBCF0KmMrT+csUewXJFYaXmjOo2mXzjmrFhARW1kn7LHbSWg+CHju9xTJWdPL1N+X5KnAjJ8kG11vNFjlwk8Dfo8A9vl8lsx6UQ3NrGXG/NTMiTUzLscEcIemNUyz1IlpnZs5V2cM/pJ6RpI3EecJg+jVRh11akOaE7yEua8s0w+xDqDnH5EpTpgV61dCTvAhALjq1bis2sxfNO9MTq5Cy5zbz4Xx7PHzQIKu18XYpjEsLrY5sYs6QRJ3MVBpIDXbJImZ+yLTb8gaQi2hPqTNvDKJJSxi/eZ1OHL4IDasWYsHr3uI1ThYqZqeHTIInE2y28xCJxZt3ktky9jxGUzQNdfea5jrNhxgcMMQ8oaPacwyMExgbN30ofV6AtWEkgBIkTzAnDeHw6bOGdc8wZSewvpVG6BGzKw9TezdCipmLg9z3z5Zmf4aZsirCdSwaZdVGYa3DUGPZOZc02amT2xaXMBb0z3Q7nYwYP6xDDndLyyLLZLckghg5ix6nxLQzPzuxTEnZBxuL5p+GGDYXKuOqfOcuf/a1Jaq93xYRhlllFFGGd9KQesar3nNa/hF8d///d/4+Mc/jve///3YuXMnA8DEriUAlxa/v95Yu3YtbrrpJvzgD/4gS0xTkDQzyU9/6lOfYnD5ZDE5OYmPfexjDEiTHHQ/E4uCnj3I8/cXf/EXWZKTpDod+HvWWWcxKDw6OlpsT2po3/d938dewFQe8gX+//6//w///u///nXXq4wyyiijjKdOkEXAG9/4Rlae6A9KJCImMClLlFFGGWV8O8cpAYBFhhHoV4rtl252oBl9YWEQ2G4joJOApNp6kTqpZndcZq1YdmzBAtbLmZgrf4rssmMVWxCXGZ4O/u3J4LpFwN7xekzcAtjVynrb9t5zx3Egt3uJf7HUyVNecbx+prBHLGFavFaqVz53Ti3GdsR4YmZpSiwkCGieC+CX6gzXXvsF+LkwV3WQYEm1kfsaZB3sDeToDiyiS6yhuIP7D9+NIFZoVhbgB+SR2MThmd3iVUlnjio42N5vtm+x72tL+5gPFrCEaXM9hpAHdB2IqWUB7VQW3YnZRoycYMRD4ndNe6e8IMzcnWqFpUkzqrfvIY5MWYdrpnwBImJIkTy1riHsenjgX3chC5s4li0iikehiSl2qIMjHzuEajdCZMqXZTGCJEBsZSrbSRMV054xyWZS0/ghS11GxI7yra9m5jNDiWU+vQjVSpWlR5tJ25QzFJlnZcH+vJ+9bvua7oGmDGq4RfMVACuz6bh/eQKAmCDmrzDbcwwMDPDvY2OjcMkJjnlbqVQYDGF5T7qeBLTnWdHPREI2L/oXe2AGFszOXbk0L86zJzDyZf1tJQu4d9/Z45EnpwVv7KcFkLwSFC6jjDKOD8eghwwBZizKzXiY8hiXkgZ+CJZlpns58WOWoNehxujoCO9DCSu5uZ+7Pnmyp2aM1ALcUVJJmMOL6F6PMTxqxmIzXrWaSzxOVyNKYCFT4RRp0EFa6SKptdDxm2YMn0c20EZTTSMJF8l91cwpBEYHXD4aM9hj1pf7OtUpz62UUJOoBIkXM6N1ZPUQ2qrF4KW2qsPEtIxVyoxW38wNSdZFEPnM7mTw1TVH1WPZfxqjE5JoDkQxIiEZ/lyAc59k/2nMUTkfo2vG+Q7ZE5i5iwDRRHew4az12HbmNhybPoI777iL5xmWS04kqWvJ/MvrZsyv5uiQXHBkjm+Oo/I22mkHI9tGccE55+PBe3fgoR0PoV6roa1bpnx0fvL4bfOcQSxaOmfNlHspWULXtPuGMzZg6/qLcO+D9+PwnsOIco+Zsh3T3qib+Yd8fQmkj3IG+BNzDbdu34rLLr8c9+98ANdd+xV04kVyyuX5maYav66wuNTmdlZm7m6rJoKGj/MuOQdnn38m9u45gM997ktYM7GGAd0d9+9Aq2XKGzYIakfXlC0w+1Um6jjnGdtxy4O3YHjzMCZMPTetOQ177z6EhUOLDJjrRNjVkEvCgLy2auX8rOX5kmBH86W5Br6puz8Uoj2So7F6BFOYYY9lcyRUUcNp2Rp0di9gz46DiKpVjJ42jolNa7EU0nVImcU8bfrGkDlOdc0QurtNPzJzf94VKWswUGsuvmmv3LSfWmv6+pYQQ1sH8LDaZY7RsqLZovZCHsNeTokL5nhhnW4u5KkkLFAfJk9jEVzxpPwQFj0l1nV1xn14b2sRQ2a+1+TzbJ4TssgUNqqW+G8ZZZRRRhlPidi9ezfLQV944YX8evnLX87s39e+9rW43DyPUBAjl4BWYggT8Ori6NGjDBavDPp++k//9E+8PXn50poKSTtffPHFDDY///nPP2l5IvN8ShLVP/ETP4EvfvGLePDBBxm4JTuk5zznOfyTgo73iU98gn8nD+G/+Iu/WAb+9gcxuV7ykpfgk5/8JNeF7JTOPvvsb7jNyiijjDLK+NaMxcVFTgT6oz/6I1aJcEHz1lvf+lb88i//MqtLlFFGGWV8u8ep8QDmBTcndUzZmh4zTERakvVkZeGPSRc+s4cEOKW9dQH+0s7as8xcAp48J6cMkfmzEpUitdsDV/kougd6+Wz312MHC3alC7nqAsxSVubW1cMTCV8G1tziYC7SjyJ3ucI2Ti8HyAqvRwL3uC4ewjDkLz0UBJ4mWuRAM0Z1c2H3FocjJkvOfolJN4OXyQK3RywhAmHN/sFwyFLIPm2X5cLbCqrQcYdZPBVmEwXmrQFTpjlmSClaaPYbzCz1h9ogUzzy0M3MMRR56YU1Zn0FgWLpRGKiUX0qFWLMZiC81yOcYWjY1GWB/StT6yOZUpfyM0TdiqlfldyK4TVyXuwWPJV+Jsx0SlSXF27Jq4+OQeKR2h+Hbpv941CYp5m0C9GyPKIk5V10SQY0CtCuzWFhdJHBcT0L1JciJKYNwixgT2Oi/HRrGosTiyzAGu0PUcsayJMYKgYGTJusrVcx41VQiXwGMJhFRj6CvgDB0gdgPSilPzMwC68AbZcnC5CkqRZAhaVdtWlHX5IddCYgixaWcT9jfLk3L5hBJn1MFuQ1XPKEAM3cl+n8acxgL7+thH3GUqXMDkav3zLDHTaBQq4V95c+Vr7cHz3gl/8mWelHAZDLKKOMXhCrksbIPPLYPLdD46ofoz5Qwfptm3Bwdj868x1U/AqStGvGnhCZSlEfHEAYmXEzD3i8nM5nzJjs8bxBygtV4urS7RcQybcNXRlEJ0vNuRRL6Ho1M6YGKZJqYsa9Dha7c2b/DuKgg8HVg8gHMyzqebNNbOV/gXbWZinf0IyvgSdeuwSYEXvWY1n+BHFmRua8w2Bq1dShGS8xQ7USNpi928xaWKzN4+KLLsS6davx5Vu+gIX5eUyMrkJrYQmdJXO+rMPAd8ecj1i05C9LX9BSU5/R1WNmPokxP93mSZc5xR6pNIDnm45pI6rfbDqPxuoqtj/rXMwsTWF4+xjygwrHjsxgpDKCemMAKTFu/QQLwQJalSZSM2/OmHYciIbQNcfZctZWnP6M09HstDBxziTuOXgvPHOdxkfH0G63mCldHwvRqZvjhEuIGxlmF+fhhQlWb9+GTRduxqEjD2PTZRsR17sIumbf1RNYUGa/dUNY8rtYMG0+my8xq/S0Ladh7Tlr8aUHv4itm7Zg++Xb0PBqGKuPoNntYk7PoRO2zPYzWPTmUTfz1cDIBLaddTrGNo/iE7d8Atu3Pg1nPXM7Nm3aiIqZJ8c2jCLrBGhE41icSnHdF69F7omXPUlse7UAHTPHtc017uQJs8xJVpultXNhAlPjypMVeB7hVqfxPRcpcGKhs+BFaN6LzFYjAbIBZXrKHEuHUwLBCAYQzXs4dOcMho4OY6BuninS0Mz3HibXrmbpZlMK4veiG2aojwyY9pmVMhLT2g+4TOQfrWupubaDWNzYxMhZw2gNNHHUHCFnE4cAwq02c7v5F+iKeb5RnHhG94pOJWFQ5kZR38itQoxAwx4/a7Itg3kvNs84bdrf3DeNkUFoCwaXCHAZZZRRRhlPhXjlK1+J17/+9SyDuXXrVvze7/0eM3FpITyOY/5JDCny4qVFc/JCvPrqq7Fnzx7el6SdN2/efMJj074E+r7iFa/AwsICv6655hr85m/+JoO8jxSUDE3yzicLYgq7ICYwSTs/UpCUNQHAFMT8KgHgMsooo4xvn6D1SFKWePvb384+9f1B3vXkMb9p06YnqHRllFFGGU++ePwB4IJJKJ55DN4RsycMGBTjRTlt6cF9rEnn+es7kNa+yJiVwTLPeuwyqNzP9nU0Y/ezH5iygJYSWUDtvOHcZg4I1rq3GIoeq1e5svarAxbsxz56swP+PCv1rHoAmR94DPiSlyuB3/TFS3yBrWSv/X35kWBZw0rASJJ+1F1kAQHKJEmZI1cBnyuo51hMm8y+zUnCOMuRRRphLWRfSAIgnn/xc6HNl67PqU8i8yGOiSTtWCE/4Ro8WpDNQihT1jyJMLB6FPPzh5D7VZA9o4cmpMbk1TsAn7x3SZq41kGzk6DhNViCkVhqmd8y5fSRBqYsppxBEjIgnLN3IQGzIjuae+ZvUxgCOAgwJZlG/pzAW9NWxGIzBWLGXEBtlGr4XGGNRpjj2OppVF81iqX1hLAvoTEVYP5vZrH2wdOw0F2CF8OUwbTV831Er/RRma5i5l3zqDQj9pRGJ8NkUMGV2RAOqwjDqYfQC5mzREaO3iMAnM6/ud/rudf98yKRAUL+lhfhtez9mBfdqU+V/DiAlVhaPShW/u/ZZAhdaI5re29YH0cnp07MbG8FoJwL+x3sRykyrSv9qqX8x9fb1XXZNuVaeRllnDgoaSgKGPgl1m9Q8dBVCS696lJcbl43330Drv/MV8xc0MZS3sREOMb+p8RiJU9XmjMWFuZQ31TFc6+6BkeOHsN1X74W880OJ3hkZuxMQjN+VUaRmBk8JWYxvcy42PFjDE0M4aXPeglmpg/gM9d9CocOH8a2bVuxkMwLE5kSVMwQ0DbnioZCXHbFM7G4sITde3dDp8QMTjDXnOMxPQxCSZ6pBxgfGQMJGrfiltm3ZcazCrqdHNVaDZe/8DKsWjWBpe4crnzRlWbu8TE5OImp2Wns27PfzC8ZBk255pZmEGdttLIWknaK07efj4uffjFuv+kmpMfmef7PtQDApITQ7LYwuzQLv1bBulXrMLltEgc7R/DFm7+Aq597NZ519ZWYPjqDTWObMRwN8zw5iykc7O4BBoDF7gKWwiWGAS++4CxccN4FuO7+G7Bv/35cfcXVuPKaK7F6eBVGhoYRJx20Wx2gmuNoOo1jnWMY2zCO+dYxTIxN4IJnXoDbd9+OW776JTz/qhfg+de8AJmZ/x4+tAcbJ1YhWlVDCx2MnzaJpJlgw8g6nH3+2bhrz1244Y7r0dZNPOeiKzE3PY377rkHA8NjWLdlHZSvmQV84aXn44zRM7F6fC0OLx7Cjfdfj4f278LqidPwzAsuxXV3XY+77/gaJocnMTqwyszVVWChYq5Zzn7QOtE4euAoIlRwdP+UuYazOLTzIBYXm4jMnMqJdvQcxXLJumAAuycjxk5ZM9nMf6HIKFNf9kwfI9UPYjMT+5fSvOgZZALDaE014Zm5d3hhBMPtCryqec6ZzTGytoFBVLFk9qBtA1bRMH1XZeZ4Acs2SzKgL97Ig+b5cCBFtC5AuDbCHvUwOxBrK/7MvsUQZQufbChiD2k3ZyUPzzxbUuJamiecQKcKdQ5RTyFcmBU6lFg+sJKKmV8jAn5Nu6jI9HH/lORCllFGGWWUUcY3PYjRS2xdAoD/+Z//mRnB//Ef/8FrM+94xztw6NAhfOlLX2JFKmIB/9AP/RAze3/0R38UP/MzP3NS8NcFsX1vu+02ZuASa5fmWJJwvvHGG/EP//APzLr6RoKOSUEyz69+9asfdXuql4uVylQ7duwwz77bvqFylFFGGWWU8eSOr371q2xv4LzpXdC4/8d//Md4wQte8ASVrIwyyijjyRuP/6qX9fq1qKv9SYzIVFgnlimp0QOUHJPSySX3QCmR3mXcrAB/BfsiTqTKlfgROtlmOIbxcp9Skhrk89nzyMbCzhScLhew1YKyPfawHFUWEm1ZlYWKle7zeZVthC2c2/e1lfzNmPUrJ/L4Sw29T6xVPwiRpAmXi6UnU9dsxZKsPadGN+7yO772EKZWxZGBuACt+SWEpj46j1jCN6/EmO908Yxzr8KDdz2EZlvzInZqto18ApBFZliZAxHDVquQJRbjvA3fq8KvmrZpVkxZK8z2IWlNP6wiq7SZJYskZy9DKojv1bgXMd5IPoOmlGEcYCCvYanio2HahEDeKKgxU5kkTIllFlSVqbu5iqbecaXLLOdaUEfSSkDora4uQWUalazOvpS+5yO3bdKaWMDw90/irtMfMJs2kXop9m06irWv3oC59x3DSD5i2sLHzNYFZN+V4e6BO7AmXovR2pCpV2LqrNExZZifn8Xheo4jeYLBasB9qh/Wl350PNLZk4BezvYGM9dlmywTlXHp7nmPKb7yeGrFcdHz7hX5aOlvBXvYvuNuL5ZL96ycp7bAdSFTbfeztPncZifkQktfxmDm+yTP0UussPdOISGtOZnAdXlVIsBllHHi0JRf0kUSLsAMRsgHYjz9ygtQP0fhX2/8G1x60TMwdngA1VoDZ55xJqY704gbZsxOF9CNujiWHMbkmavw3Jc+G0tLc9j8tLXQA09Hu9Nm4DWLYoyNjaGxto654KAZkafQ9hYwG7Zx2vphDK8aM8c8jGiVjytf/UxsPDaJickxHFrYBzWQIWt0MaunsPaMDbjsOZeZ+SLFRLga51z5NPZsTTsZOgsdGUcCD5kZH4n5WxusmvO00W1mmDh9FeJWii2rT8MFZ12IOOvgi9d9FvMLi3je5c9F1k1x5213YuO6tdhy2lqgplAbH8TeqX0YHqugev4Ezj3taRj0h/G1O2/FgYOH0DDzoW/mJwLLSRI7M5PK4PAwrnj+ZRgaGULNq5hzxrju5usRzns4eMc+nH/O+ZiP53DXfV9DnHTNOJVj0Jxn+3nbcbhzBGsG1uElL3qJOc8gBsMGbrj5WhzYcZSToB66bRfO3X4uDu87hK/suRa1aoSoWsHAqgGMbRjDRFrHxVe8AM2LllAx89mO++/Fgdt2YEO6Efuu3YfWWBMtM/8cnD2IgckGLnjm+VhozeOiM85BtuksJGbeve3ur2HXfQ9hTboOR2+YwrW7rsPswoxppxkz/x7Evp2HsHrjakysHsP5516MPfv34jOf/wyOHDqKtJ1iUq3BwRsP47O3fR7Hjh3FkB5BOpfhaDaNLA6Rp8QMN/N31zwH7Ovi3n0PoOubq6hSVk1ZMP8qySACM1/zcwfNF2SHYeZeAo2JhSsGzlbZhBK+KOuLtER4gqE5OsaQmacbSuZ3B8QS0Dx/dBGN5igG2qsRqgonu1FSUg5a/CWvYwJ/6fknYouKKIhMH68xIF3rxMwObpEVw5i5dqvmML51DaYrSziMeZDDdM2mS3UYBvb5zMrUuUKvLDL1IduNBBVTXz/JEJv6kO+2x0oYGdc5IdZvoAsf7YAfFOkhipIZ2qiF5omoWiltDcooo4wyynjKBLFtf/iHfxi33norvva1r6FWq/GCOfkDf+5zn2Pwl4K8EZ/5zGfyQvp5553H+zyWIN9fOt6rXvUq9gOmIAbvpZdeik9/+tPsG/z1BrGJKYj5S+V/tHje856Hf/3Xf0Wz2eSyuyDp6Pe+9734lV/5FQa3yyijjDLKeGrE1NQUq0389V//9TLiCs0Zv/qrv8rqEUFQJvaWUUYZZZwoHvfRsYBEdSYStpaJ6LOHofVW9T32dWPLUuvpWwBOSvxttf1d53kP+PUsOKZz67PaK37BYCnA4342Y49pTECWMC+tXCDyAni2Oy0DwVYC04IJ6z4ZaYgPsZKFyn7mMIHXBIZnDPYGyFlyN2Bgj+Qv5xYWMTs3jw2bzrbAca8BrWAvM6HiJIZHnnbUhn4XS2GE4bEMc+39qHmbMdiYxLHoiGmvLpqtNgajOiICdfMMzYF53DD9eYJ8kVViLEZd6G6OamC+WDUS+GGCpXwRlW1DzHxNF7rIBzJ0p3NUBjXC1DdVqWBed7DUWMDTr3w6brnuejT8UfhDCkuzsxg4YxUmNqzHQ/fuYBnpZnUJR6IDuPiFV2Fq1y5UyDcySOBtCnH+Zedg7/59qA1E2N88hKGzqth40Xo0F1Nk8xrtQwG8SJv3NmPpaBM7/3snqnmd5RppQTeLMoSnheiskwVu/WWN1aOrEVxors+GHPOjTQxma+CNLGHw6mE8MHGPafeYgVHyH+7SPikxhSLMmC+MXzT1rzeGsCUMECiRKtd98Hu/tPNydrnr58vfE/lzm7ygfMsCFjllklxezhY+MctYkhcC29c9BjX6PbT7t2OmuPVHZHlyxwwu+nFPNprum1zLer9iWWm9DABeeXz2grT3ju6T1CyjjDJOHsSSHFzjYfvFF+PcZ5yLcNiHqincdvst2PnAAzhz/Xl46fO+G0vdJg5M78em9ZsYOGsM1DE8PoSJxgSueOazsH/3Adx661cxMTyBM7acgeHKCLNgZ+NppElqtluFJIxx7lnnYFNtGzYMb8emDZtx8OBh/PfnP4euGde3n78V45OrcfbkNty7/x7UxqoYXTuKujeAi8+9CDt378B99zzAfujDZhwkEHWgPoiJ0Um0zVzSNXNPp91kX9+BsUHURqpYtXYVvvOKF6PT6iJeirFn117svH8XOs0uKnkVt37hDs6Aycw4O7NrmhOsgpEI67dtwID5cnblec9Gt9vFgV2HsGPHQ2hNdcx8VTHjrxL/co+kfYG0pbF4ZAljqyZw33134+CegwjbFcSdGGN63Bx7Dl9++FrEacxS0cwazlMcDo7i8J4pnivqjTq2btqKQweP4K6Dx9CcbmEgHWG/4ekds7j24es4SYaO0fLaDI7WDs9j/sgiOt02jgxOYXZ2BogV2jMx6p2GmUuryDsZpudm2CpgwBuCPpJh13UPMet25v4ZtE39lhZjZM0U9aSBkJKzzHA6/1ATXhBhLFhtHkHI2z7Dw4d24+DgQexo7MK8eR5IWxki044DKmLVCN3y2ad+0BtmWwaW5c9C86OCTAcMylY8EkhugcZnthwg1myqEGmaR3yeI3I7t7GKOLWxZ2cOy8T1fckqomsQ+r5cB+WzJDhZPHTFvIEtG3KbpkZCH+QPHVQzfpZIgxR+VBH/Y9DsQ+CvubZmDjddi+vlU1vkpPYiPtLUN5LRBGPbxhGuCjGHw1yPkP/5LDgtuXGpfUdEoUmxIwwr/L5KMpucJ6ovy5RYtK21TZSieThjZRlhA2d5JrLXJQBcRhlllFHGUyyI2fvnf/7nnIz+5S9/mVm7/Z6/FMSkpecyAk2/nmg0Ggz20qL7e97zHp5ziY11wQUXsDTzZZdd9nUdb2Jigv2BHRD8aEEMLwKAP/jBD+KMM87g96699lqWtKZnnl//9V/Hvffei3e/+93sQ1xGGWWUUca3ZtDa+R/+4R/i137t15bNEfT97XWvex1+53d+54T+9WWUUUYZZfTilKTHeH5vAc6iWKKBq3LhWGqRdxSgSzxvHf4K9Ni3HnsGB4V/aU831zeH01b21h6fQVhvGUanLftRZKLddn3lshLUzttVPuuBv1Q2+jKTW4lo1sSEZQhrJ1VtGc26B2Zrh0aTk2uSif8rMUK9AK1WFzPT85ibXSLjYwSVkMuu+/SAlQWiGXSGx4uVcZLAGzJ/1VKMXOJj6zPXodUewfimUey8+yFsvHI9ao0hLM4ew+jpI9i1Yw97Ep5z+jYkE7PYt283xi+dwMDwEFTmsURlMKbQqubYeuXpCLwQ2htE2M0wsXrUnD5FbWwcB+7dCRUmmFg/gclV47h/x/0445zzEMdNRKuqGB4cR2cuwaF9h7B28zrEWYLBoTouesGFeOjue7Fu1Wq04xgV03YTG1fhy/91A9asHkNrpo1NZ2zCYquJW//7ToyOrUHHvOfNm/KFbfZx6M51MJDXkfuK2zZUEWUSIKtn6AYt1Jc8BA8OYXTzanQVLQObMgUBGhUfs1t9JBd1sYh5VE29ojRCaI4VhDX2AM5TjWbkIybmdlBBJawgzVLul75dRO4lJvQzwsF9ThWvfkDXXjct/UlBvLBZwtLzJW9BCUtXZNJV0Y9cv5I7oOdPLcciADlcBtbSe1kuPtAK0k8pY4JZ6LrXTx34m2vLTDfvsVyo+b0HSNvkhoLxLmzg/vLkK0BifQIwvIwyyqDbMMXzX3w5rn7+C/HwzB48sGcndj60E4tzZnxqDeHLn7oVp21ZjSPzh7B/aj+u/o7nY6m9hDO3nIUL/tdFZmzKcc/d9+Gem+5HJa5h3swVtz18u8jxVhQSrwtS0kcaouu3sXl8EzaeMYnB6ip87e47zNhuxpg4RJjU8NAN+3j76fNn0fIXMbl2DC+7+ruRmfHvaw/cjod27kajPQgVKzQXOmaM0pj3ljC/d8mMTcrmOMlkPDM/Z8bLBHvuPYBqpcJSvAT6khxvNTNja15lH2FFnqxpZsdA0evoTpv95g+Y33LsHz/E8+LSzBLCzIzLGQGE9CgiwCOphURZiLid4vbr7oQOc8S6C9+cJ8pqZhyvmrprVIKIx6kKJbZQQhdN/yS9YB4psn0ZK0PMeYu47Z7b4WemtDrAsB5HoGuScEVnjHMeL+tW5INg1OxYjsWpDgPKRzErc7ypU0MPwTdt7pPBsyceyiSZnTFXNUGyEKOmGmjPdvmZombOE2QBvCTgfQhIJcUPv0JWCxmLGZMH7gC5IsykSMyrrgd4W2pDAmllSBbrhDwhoDPn66JN+2jTFklitvHp7E009QLa/gI7HPipqasaRhB7cH6/UmF5yvCd2oT5Ms3PM56yzzmwCiUkvEHJUlL3tilvVROrNzLbRAy6khz44Ljpn/VpxMEi23wkDXM9GnUsoGM+l2c1EoOOuhHi2QSNdABBEjCMyyh/3bzGzDPQaRFGzprEvnC3mbMXGeCtYZhchs1f5vkHXQa4GfzNTX0y8qoO7GOSeFYHYWjmcJ8TnbzAevoWCVHgdvOs8oXvywUnsLuQ0yh97csoo4wyyngKxoYNG/gnAaz33HPPss/+8z//k2WcCbA9mXSzWFmFJ/yMvke+613vYubv93zP96Ddlu/wz372s9mbkRbmH2tcccUVuP766zE7O8tg9XOe85xH3YeAX/I4piAPY5Kwzvssxj7ykY9g586d+NCHPsQ+yGWUUUYZZXxrBVkWkEUBSfv3ByUbkeLDJZdc8gSVrIwyyijjWytOAQCs2e9VZKAp+hbZIAtw2jJ61XGMQobMeCGOvACV86Szx3VglZAhvQLcsgK2coZ+FodykrXHe5Yq97n1My2kn/v2ZeFpu787FwOBdH4HKhfEYS2+rRbYszq8shBp9iUf2/m5JTNx7cbg0Cg8P2QJ5ES3LeDbAx01LDuZ3vN8+FmOlFisaYJ1q9dgaXYJd332PlSrDRx+eBEDowM4tnMaeWsWMRIc3r2A0cl1ODS9iAe/tgd+fQHj50wykNDc1YXOpMLEXvJCj5nJtaQKj2SdTfmn79jDjCoVN1FVddNJ6jj85WMMTNTM7/O75rhd5m/vWIa3qWceYW7nErdf82tdBhcH9DDm9zR5gX3J/CMwe3W6BpjRLI987P4ZBkXX6HXIj9RR0Q20uxVMPmMAi+kx+EdSXsAm3JcUG5Mo5dMRI6qS1hDVQ6RnJMjXdzGnOpg8Noig20AwnCG4aghTIw9jsz4dR9UCqlkFkdcw9cmRhHVTzpj9/6gdYrrOgdcnJ07gaCp9S1sJcLhrmjMDy4GmwjhSvb7jOSBVCYBCjCwGNfr8r11ftl7Z3Hv7vqyyrDN95voaLZajx+jlo5NPMe9nSuCTX3TOEtlaO6ZwBnf3aNtPe3WR8BlUzgqWMt23Dvh17HcHAnteL0mhZEqVUcbJg5I9rr32Rtx9704cnT7KChBDA8MYrA6ZMa4CPQXsnT4AVQVGMYEj90xjZmEGD9+2F0ONYVZ8IKZqrTnENgcew2GeSM4nmv1Y42aM+760iyWh7wt3wlcVnHfmM6HbNQwEI6h1hs1eg2Zs7yDzExy6+xha3hIO7DiE5tEYi50l7Dt0AIPJMIbzMZ4DyJfVSQPzmGbOxxJKNA7QuTMwAJy1zC8tGT9I6p80dsNMFgb93CZ05QL+sqKCGeR9GjYzGaO6BzN+j4BBL/MgcKBnhs6U/Wl9HfI4TwlYJF2cdhJEQYUB3CCJTBnNvECJYx0wCEj+spmS8dUzcxuVk8DfWthggJXHMvNeZLbNE7DXfMBewzTmunEzY+9lZZO5aAxOiXfqa5HWpxLmHgOz9LuZDM1/GX8WeqYEZpLKCCClcTTO+JgpJYSZ7SueudCZSPKHvtkuoXk/5VpH5v/c5qY+kVexPvGK24WfnTwakwNOhKM6ZJQIRnU3bZQT2EkWDuZHMBDgzDO3wR/N8PCRhzAajmP6/lnkHZ/94DmJyCmpZOKH6/LMPCsLrZ01gGkHVhyheY4A4K6ZDxfNtWmnGI3GsIgFU7vE/GxjYtUIgjMqOHTwEMYHR1DdNAxvPMA05vg5r4oKNmItOocX4c8Aw/4Yqrpq5sSc+38+5iGZSFHfOoh4VOOgPsRgb930jgFT7wHzW+aZ+wHzfE5qM+5HiXmmoutJiXVaAFzqvyx1zZYewhnuV7Sg68btYOobRiHcnE7qLEEQluIWZZRRRhllPKWD5JoJECUG1ctf/nLcfPPN+P3f/30Gakl2uT/iOMaf/MmfsJ/i+9//fnzqU596RFnNl770pbjlllvwnd/5newrTGyt17/+9bjhhhvwB3/wB49JkvM1r3kNezeSpPPb3vY2fPjDHy7A60eLpaUlBggcM4w8hNesWYMPfOADLIH9ile8Av/4j//4mI9XRhlllFHGExs0l7zpTW9ie4H+oGQeUqz4kR/5kXJdsowyyijj64hvgkC+srLH8ruATdoKCCbMXiwYvpDFc2HT9kDjfuCLoh+UWhkOSOPP3EHVcn9T2c8yPOGYvK54hQZzAT47R14uRW5ZkQ74tZKK/exlWVi2rGFaPPYCHDs6g4OHjqJaH8TiYhPzC0sIIh/1wSqD5Qz25T3ZaTkvix4jThMk5rzjtXEce3gGawdHsWbVOqi2h85CinhvjqoagcoCDJPH8EKOWmcIw8kgVqerobsVdO5IUFfjaBCTyJdlb2LR0GIzLUATg8pz52ZGkOkctPgtxCr4KXnneVaSW9iu7MlnFZKVle7kOifUDqHIfWvxLda5AP+ebRMGFFwdPQIpIH7ApgzBcAOro9Nw/+33oVINmDUV0oK8KWNE7KjDOfxdQHreAILvyHBYdzGkB6BvXTBttAGL2xYRXUhMNFOfgx4aG4k15qOiA4S1SBhQUQQdE5M8Y1ko33ozK8sKOv5hgq6p62891uxxgKhjDMP5RUt/U6xAqSxjSS3rx+68PclxAlF63r39+/TY7IpB9Fz15MiVk3S210feFfY9ARzOp7i4MZQDnXvH0FbeXKnl5eyBwSVLqowyHikir465fRpLB6YRhSEGqoMYi0YYzFKpFuAqGETaMfeUn2LxgTYIkyOJ/3ks8h1W9wdRywdtzomoWNC9zF7ocYqIZIgTD4PeCLNeEzMuV1sNJM3AnLOKSrOOyFdIQ8X+6jT+VVXVnDPFoduOskzvpF5nxkSzbRLJPJZbj4WsL/GKFAhyAslkjvKZeqxZfYDl6bWy81yPYapZY17Gdpr7eEzJPK4HgXPay4tRiGT86X06J/sNZ5oBOpmkNDNVCSR18zpNvyxcrJjYas6VyfNC32RPZcq7OQsFS36S4uPoXLbJdMqJM2689Ti/hsDvnJmhBEhTkhTNZrlpW0ngEflkenTI+ZwZ16WXKEOEVp/lhFmU34zLlTDgOtGHNN8SQMmjND8TKJkfrYQ/HZ+ATToBg9sEUNN5uGEU+zBTog+TstnDNzXbhNJMvjlnHVi9ZRWGNtfgTylsHtmKz+/7ApKlrmm/wFpMuOcuO6bbNlWetEua5wVYbGcwnkOztunTsznSQ4tYMzSKWXUMc+iiiRiNgRyrL96M5roWqrUaqhMDmAoXzWcdEn7GGoyhPudj/9f2Y2ihhrquMQieow09aJ5txjTS1QEG19SwX+83vd88F5m+PaZHMDdzFIO1QYSNmilJixnndEySFqdEiJBsLvzQ9B/OLmDrEJbM9ixIb9sVbKEQclKhZtULD7G5h8IwYjluqq/PvsflAkIZZZRRRhlP3ajX6/iXf/kX/Nu//Rt7Af/pn/4p3vGOd5xQqpm+G8/Pz+Onfuqn8L73ve8xAbjnnnsubr/9dgZbSYqZggBdAmD//d///Tjp6ZVBDGWSbX7rW9+KQ4cOMaj85je/Gddccw1LVBNL+WUvexm2bt26bD96pqHtHDvswgsvZElqqsM555yDn//5n8eBAweYjUx+xSdjOpdRRhlllPHER6fTwW/91m/xi1QlXNA89NM//dOsOvFYfOLLKKOMMspYHqcAAFYWwOpjK/IiqQO0HGKYyWIxszW8PjDMK/Zxsru8uOp56AHBPWDq0bJ+3HH6pZ0pnNwhLyTrnvqfWwx1IdK6etkx7CcFWFacyy4OS1kti9MPsLDQwux8C4cPz2B4eAT7zZeQqZlpRBUfmzdvRBj4zJhlFo71kLVnYKbSUpIQHAideWj4A6iGVfbEJSZYFES80E2LnASQEmOJCtJK2nhw9z3wo9y8gEFvEGmmkZARYSALwbmsnDMT2M8EpCe2LrNsiVlELn58OI9BAFp9ZmDRskEVeQsqLewxT4AAIUpbUMDWhZlFeR+wvkJq0ctq5twR0naKwXwQR288jHbaxHB9HEmeQIUin0wsKGKBLZk/KlGVfRXr/iLmFAlTRiyBnY8kGHpmHXsq++Dd42GtfxoOqf2I0gBDlRrSNEQjIgVRAjMUMt/JQrr+4cq4vO/0/vYYhFAn8c1ltVTIds5XkBIgPPKCzlI5j/YhHtm9vn58v/UKEHZ5e/X1fS/jPlewc1W/n6/brsdQF9axvR4WROmBv8KG6wd+e2XpeWG75AxVLpaXUcYJw8vNGJNNohaIekM9CTAQN1BTocBS5j5KzDjEnuMZZ8ig7jXMOCqe7ywxT0xTcxxJlFEMJBO4mMW5+fIT8cStOWuGT4hukmIoHcZiK0N9sC4+tUksY3vgse9qlAdF0pPfjUjj1w4QOY/xcNL0FrSUfxbMJfA2UXauIZZtbkUufNnG7JLlIqHvBXaOtWoe2jk15AIqCqZJ4C5tZe0X+JFB2ecB2O0ckCxwXkYqB6RM4Um5PC3zFSO4lCBEbaUzlk4WOWhJxBIxDc2nL6qseuOmxYgFnCb5Yzt3cQ0oWck+cmhmGucMPJMaRi9RSxLD3FjMag+2LxDYzPOmOX/GzzEunUxz0pVMl8opFUOaKWerAALK2duYKkPJWOzzm3HdeE+bqJWqGEkWY6Y5AxUPYXBomHQnhIHsqaIsnNxEZZIj2rlIy5xNrF+bvKZtBhA77Zo+mDRjeFM52g/NIlpVwbqxNYjRMf+amFYLqA2Z/jYwSDbJmFfz5t02PV1gBEMYatfx4Ffvg96dYCQZ4/mbkpaSmukr4xrtiS4GtowiHuxiGkf5nCMYg99UaO1vorGlgRZRvSVVEKG1EPHNHErPHz4nGCQ8x+pY83MUyZBHQcgAd5pKbWVa96zUtTCgKekrIilz83Plc18ZZZRRRhllPBWDQFFiAt92221YXFzED//wD59wO2LUkuwmsXKJRUsM4Wc84xn8GTGGCewl2eeVQSDvF77wBQZdya+R4sYbb2RQluSmab9HCirb3Nwc+/YSm5fYyvRyQecm1vJzn/vc4j2SgCZAm4I8IEnu2Xn+vuhFL2L5amIHk0T03/3d3+ENb3jDY26vMsooo4wyvnlBbF9K6KHxuj+uuuoqVqXYvn37E1SyMsooo4xv/ThlDGBhUcIuVupiIdKBTgISBgUo5VnAyzENe4BtP6DVA8KWyeH2MRWXgWoWvOtn//Z7qBbAlmVx5szUsWBvro87a/++yHtMSfdZP8gsC8IiPTl1bAazs4vMOLnn3nsYJF61agQXXHAOhoZGmWXEwGLuADxVMIs9WtTsxtSiqNYrUFmMSqUGrxJB+bz6b/5FDBRX7SI6WM44ECdbYm4R+4VaO1BICZjM8l5b5wLgpogtOKjtmrnUJ6NF5FwW28kdN7fSoFasm+tHkpQ6dwvNtg2gLEta5CVZElw7eWsn3y2AIi2S809PEgNo4b6uBxlkCPyAgRFGDcw5ml4H+uwAR09fQKeTIP1KgqEz1+LopoPwL6hgrnMM0aY6s+TyIxn8zT66qo2sNoZsXQxvX5VzD5jN5gtTmbLJiL3sWdaVOu620EUfkmvU8wMW2ejlTPQ87weHRZoSti0cL1epYMU+0i4MEBT97FGSHNw9QIywLLOyzy7JwiU19IPC/btqubauz9p+K7dP7xh9vd/eM7kFOPLjjllGGWWAmYYVGu9SgZ6IQerUFkjlQPsydrJsrfWtJ1niNBPf3CAMJEGJ9gt9yyC1XvSeU4rwxCbBnCFJunjeZc/D6sktuH7/17DlvNMwNj6IW2+7gY/pw+vNWc6T3Pr78mxjzkPMV1Yf5kwbXSR60Iji+1Ypo1AxkLHe80TuWQi/ipOS2NdVy3jJwyCP836RaaUsM5i3KWwVbPKUEgZsYsZ9X4mNBI+7fWzknGchOS4zcn3HVrXqITaryzFDaawisDRntWQ5TmB97Hg8y1Qx2jngW1pF5mRP+zy2FkCyeV/a3bcPB3Z8daxZuw0xmUmFOGc7CwhzmBKl0FMmIaFo+tzTNBfI3CBEXV2wi4VlLcAyJQDQfEjtz8dVPjPCKzS/J2YOXdSYfmgWew7txZqBeeQthYbfEMDbJQnRsUlKWrSfbY8VQBj2GSjLxadeWWa1ogS1OfOEcCjBw/c8hPBpAxgaHkKiOuwD3KVEMW+Rr3MOYS1XSZg77uKu++8AHkqxJd/M/saUyNAlEHY4RDxhni/W+Rg8bRgHvf1oYQ4DGMRYNo5dD+3EMKmYRMM4Rs8mfN2JDe4z2E0JCST/HQYRM+d1d4nn8VpYZXCe5vdKrYZuJ0baTeS+tAlZdE+QZLiixCwrBU77PkouYRlllFFGGWU8ZeLiiy/m14mCnhfe8pa34Pzzz8dv/uZv8kI8STkTAPzFL36RF+E/8YlPnPTY9PxGss+0/Rvf+EaWkyYpT/qbANhXvvKVj1g2AmhpkZ/YyStBAAKFP/7xj7M/MM3hn/70pxmgdkGgM4HA/XH11VdjbGwMMzMz7C1cAsBllFFGGU+uIAUHStShxKP+2LRpE373d3+Xk4PKKKOMMsr4n8UpAYC1ZbooR689SfQDWw4QXMbWZTlCXYBt/ThW/2JdP8B1YjalesTPlwG7J4ie/+nKMluw1ALJ5HcTsJQwb8nA6I4du7B/3zHECbB7N/n/VrBhw2l4yUuuxvzCLPI06gOu3UKzKhiWxFhqd7u8PBySV10UokoAMLHJbBsza5iABUtlJinGuNNFGFV4oVqzVLMwXYM0QebLwrP2xPePmEW0tJ5nJAdtXW3ZQ08Lk0pZprAnoD20Y4o6gNKz4HGvXQhIDcNAgGzVW2hW2i2A9+SmyfswSYh57MmCuDlP5EXo5AsMjJAoJ7GhqGSpHyM8q46DwQGM7wBOu3kd0IngbRrE3Ko5+Js0WgMx2rqFVc9bj1k9bX7vYnH1ErZ9zyYc/ON51L01vDjt5yITSl9U+1muRY5CcZ17YKdjNivV81FUUMf3QdvevLjupLH7+k8/sOva0Pnz9li/fQCtOv4cAhKI3Chv6znPTe61y1jBsq9XAL3LytIvoKrUivtMFfKrcpwS+C2jjEcK8udWUZul71nONxCvdTOAs9843WypF0P5nsjoZwLMkkoAJ9YIhorcz20qkL2nzbgYWIsEZn+GQJJ1eP+du3bioQcPYXp6CdfeeB2yoIOmmkdkzuu7sSJQFulMEetYWL+Zx567LO3PAK4wYR1ZtwBflZSRQEw3v/XP7Sp3bGQBOxlo5gQjmTMy0yaZmVM8OMDVKRLk4sJr1TRIMprAO5aC9kS+V1BqzYoNSpuxnkBGVqRIZc6wcsUEiIqfr+xGDFF2CFZSHxqzuelSKTon5mhdeLU7Ji9tT+Asw7w0dgtezczSNE9ZLIHOqx2I7dRL4Ji5is/NID3VyaqIeLkFzWkTam/PPsdkympmyPznGpKY1NLmHp9P5hkB1kmxg8oWmHmyG8dAy8Ou23aba76AxPSb+bSLRtxAiBoS1eVyChhtjkXS1LYPMRNW+fZZy+M6KqEJczECV38zR1MiVtzuIG11UR2ummMH7JOsuLVMXxR4m/+umE/DRLF/cKAGTN+qgx43+TkjNG08aLYa8TCxaS2ySs5sYmWOMKJHMD9l6nAswejQBELygxbhbBL0NseNhEFujhbS/RKLHJjKTb9IJJnPt8kRBJbHVCrfs77Jmq9NZJ6LEqvAQWA6SX+rE9iJlFFGGWWUUca3YxCISpLJH/3oR/lvWoCnF61jEDBMss5r16591OOQ5DJJMBML99ixYyzlSYv4b3/721mi+ZFU3J71rGfhs5/9LLOJCXwmVjB5+r7whS/EBRdcwNvcd999XJ7+IMCaGMDkEeni6NGjLGdNQWB0GWWUUUYZT44gJYp3vvOdPO/QWrqLWq2GX/qlX+JXtVp9AktYRhlllPHUiVMCAFsIUUDBXC9j8TppWwHPHGJofzDA5AkLUTBFu78szuV2Q68AzlRv4di+55iayq3aWsaqMDBPAg5bwExKiB4TFsvBX1dG2c+94fZSUgbnhWj+jrs5L34vmImt3c7QaNTMl5cxXHXVFfxFhCSJEt7e54XdYhlaS92YtOUr9sClzSI/ROj57F9brVXlc1h2j5KF6CioIonNWaMat6UwmmmBNmSJzooKLYNIFrJJFlp8FIn1E5kXay3zNgQ4Z1ki14lXq/mCykI7M5yJOWzOmdPivq235zwhPQtGZraxcuYZMRBBC8sqQIKUj9vNY5bKRko0qQSBOUead/k956+YssewOWct4ktVyU0ZTL0XScq5FqJljpWnGgMBOUaOoGn+zWAWXWIMm7IkXoqpfI6ZTwl7S1KdqiwuGrIHsN8HbjpAonctXR/kquWWIZdbv96iD/RAcWi5B/ICIO/JJp+sH/L1zHN7kLwAa7XCsj7Y64eqkCjVuveelD8rPnfS1e4YeeH92PMTLipnO7XWjiUO6w0N20eFqV5KQJdRxolDMDwZzXNKBAmJyRuY8UoJAMhepZqBLAJ94TklCr+4Vz3L7Odj5DIWM14ntGE7ORIAWIdXUZienzPbLZix0Mw3nRazeH2eR8lnWABSp27BiUCO3UnsXvK/JaawTc7hORgots2ZAQuIQgH43LmduyXJBDzekByz4LUyDyoHEpu5xuaoSGIMsY3zzCb7WHgvF4UHC9HaRJScJX3lONavlxQieMoMOGFJWxSVVRf6FBD4mJ6Mv2xbwKCm9WK34ywD6/32DkqSqLS2DF+wtSwkmca2F7/fSwZzyT/ueYNAUuWJ067vubncJni5cRS5Zd86GwotYDlVy3dMXcXzJ18z00dSArtpetQJUbaZ4Yxczkd1jEyZq1kNEWUFZD5No8JANvOeVM0rroHnnlE82Dk6Z1/d2M95PvZzDyH1AdM3Ol7XvDpIBs3B1gTYuH0j4kmFQ2rKzLhVbuvIzOQV7jEhFs27XfPqIEalXsd5T7sAR9OjWLzlGAaDVebYpv2q5hqOmOeZ0wYRrBrEfrUfbTODNzCGRreKgzt3Y6wzhsrAANeNYNyGuVkCEPg/ZMpdQRYQAJyjTnLSpj6xuT9CU616V5lnEd+8pxGnLPXBzG4nliHezRn3eWa4m2ciYoSzQkkZZZRRRhllfJsHgap/9Vd/xZ69/V65zWYTP/ZjP8Zs2oDXB7LHNHdecskluOOOO9i796tf/Sq/9973vpclqP/5n/8ZQ0NDJ92XzkP+v/RaGcTmpfI4f8jv+q7vwk033cR+w3QuAoKf+9znMnD8pje9yaq5oJCxLqOMMsoo44kL+h7213/913jb296GI0eOLPuMEoXe//7347TTTnuCSldGGWWU8dSMU8QAFqanLF/blTf0g7HK4q3CTPQL5iMsdceBsn3Am2zR+z8vklrmitOyRG+x1TEmtWXoKDjvvZXRW8R1TKN+79eVEtIuChDNgpvynmb5YmLu8CJ7EKLTibFu7Tp0ugmOHjtovsQ8F2naNV+aKrI4zcfwmRlD9aGFX1qgzQriFQHJMfwoMMfzzJexCOFAnT3vxNNPGFKhV+F2S80xw4qPNE5kEdy3ksV5yoBtkodI84T/ThPxzPOJnUXAqClX6IsUaSWsMDCbkPS0HyJLzedJisgzX/rMu7wAS9+lGMywkpKWrc1ABvG0lDlnaMpnNqa1eZaEzmXhtUttEAioHNi+kgWpKU8btSAyZcuY/sztonIrlWquQ2quSUveS9YBB84+gvEL1+CQnsbqoxPIv2L2uC/FpD+JrJoiuGocB8b2YGBHBfP/kmBNey2ClABs0w4esd8IXK9ZD0C53iKn3N9X+lm44isp/QIF4N/fPSSxwS++GJNUpVd47qLoL8W90s+Qtsxq5YB0iHXmiaSgc+08Lknq1CuY98zByoSNDsva67F9XRkFZO5JjquingIqO9avvWcLFjH6WMZllFHGcaEVMzMlBUTxPMDyxDYRiaEyFQrbM+/tw2Op74DHjG9WAv1oTKaEkpwTdQQkFHUBc0xPvFs9X1tPd3Pf+1ZNgP3K42JwIr/UArR0SUteb2xzkstwgKGdunkUdokpvDEsSzcr5kFmL1uA1wG7PDMy0JvbeU2yupz0s0jlu1nZs/LSzgLCEVQlGckleGV5VoyFPMqKBINVqehLS5EcJFGgdooHgD2/BdvRU1GwH8lWLP2sxC/Wzf2k8GHnBd8lXKEHgMOO0bp4FnGqCiKHDQv08zOCksQyZYFXHqeVXHPPtYa5hhnPqznvqjNh2WYMpmtJzDKTahgplqmGSlhynDYKIJLSmv2Dc0vUVhb89grGNWxCAbORzfuk2JEwyB5wkldmnhPaeRtJxRxn0sPk9gkMbhjGfWoXmmjRUwCGMIAxhIj4Oa5mWjXGUcyYz9qYV00EjQbOffr5eODQLVjctQgvqiEcN31/PMf/z95/AFpyXGXi+FfV4aaXJ49G0kijLNuSZcs2zuAFk1nCktZLsk1efkSzJpu0mAy7C5jgBZs1BhYbDPwNeDHY2EK2LFvBymE00uSZl9+7oVP965xT1d3vzTiBZBlcZ/T03ru3b3d1dXVVv/Od7/tmD+zEcrqGNaxyP+3EXmwcHaI6VmFnbze6lX3OYd9sUuoomQNMZ0fFX6wLEhNQDQF8HWDfobVWy/MOjTMVyTNGq5SL70NiNsfk0a01F+KxcssneJuHCBEiRIgQ/97i7rvvZtCWPH99eEloep659NJL8cd//Md4zWtew8n7ubm5j7lPYgvfdNNN+Lqv+zr+LMXf/u3fsgQ1fT906NAn1EZiiX3Hd3wHy0pTvOAFL2Af4OXlZXz91389nwN5G5MfMUlG57lYQZAM9EfyPA4RIkSIEJ+coKIgkuL3RUE+SPqfLAbI7zdEiBAhQjz+8cQAwPBMXDgG0FbWrJGcbQMotcGt1rcatHIJSr0lRaeaz3qmEXzCWDxRKcmq9XYAucXe2SZ369+rE8wt0Kv9u99neztmSjFfp2T5Ry8JneUlPnz3h7Fr9wKe/oxr7B8h45pVTGwU7wUr3rLsuOgAOCXsUrvHzeEIirz+ulNIphL0dnVgho7RUyoM7OudeGD/yFlFZ4diiee4ZPNllousPOhO++0WMJQ83gQnkFmUkSUQFTrzMbJhAc2AbYmRGWHPZXtx8sHj6KlpYcpUGhvRCPuv2o0zd5xBpLrImS0auWshSVbqoWpKYe/BvXjkw8eROqasIr9D24bp+SlsnNqwx6JEtTCcLn76AZw9uo5qcd31qwNi2WgYnHSPM4XhvWPse8oePDY4guRLuziLk9gd7QDuyDF/6gCiI/LZfJc9lxsUevPTmHpsCvMndzDjh/LkUU7Qsr0WcVpfXwpf0dyWIGkzZ41nlG1LF2+XdvbgBd8HWjsGrkd7to7D80uYN69XxrTGayPpXBdH1LKhDXPXA9kfKc7Haj/fz16avT43x0IjACJEiBDnBs2lEcnsVuKjmsQJf/H6oFGzQXmOJL9VLWsAFwK5ezxhn1qZLyIqwGFwUDOAp7R8F1n/Zh3zXrGyL7lf0yQV32AjUvSCygoQ6QulKPzPjYKGnIsRw2GWG26v19we0WwWpjDNV60ik2au9EoFTf9IW5QwSKqCj6FVi0kLmbuEgRzVc6nsXtegsy+wkQIV1ExXUWgQMNS05s76+rj5t6rVRdy8Whd6mYZx7J8fdGtfW1jRW+fw+pmDgVTvlewUTMpqSx/KNhrNfO6KbSDJTfcQJMVQpFURKSmEojHgfOzFXkA8fMu6mM1bA4i/rdLN2oFtSxddMwJ7SQmjLErHWmYXY0zsP/Ttc8GODiZ7c0QX9HBYPYYl+6+w7/fQxVSW4uyJUxgvb2B2Zjc6+3ZhZ3cXVtRJ3sNps4y53i7MXmOfF86eQFdnMHapjvfacTlrsIxFHufT9l9cJXj0/tOYy3ZgkE7B5FQc5orJuNk589hT26wO2UtEJSt7kDx1bJ9DCHzPqDiiKvmcDHwhlYxK5YoE5B6QNbly150A96BpESJEiBAhPt2DJJbf+MY34nu+53vw2te+FmmassfuiRMn2Ht3enqatyN2Fvky/tRP/dTHtV/az5vf/GY861nPwqte9Sp+znvooYcYBCYmMB33442f/MmfxM0338w/kzQ1SYfSM+HOnTu3ANKLi4v1zyQf/frXvx7z8/Mf93FChAgRIsTjF2fPnmXGL83F7Zwjzds/8RM/ge/8zu8MqkwhQoQI8QTG4w8AKziJx6olLuvBLycXuS35TFEzbVxSltN2lWnYG60kqRzHONYsnM+svNxO+NI+qeqTPeKEVlmD0Y6qKvlQJQ1vZKObfbV/Fm/bRh64DRDT6/WCRfvTCqPxGEmSYmHHHL7ki1+KopzU+9C65OZwUr4G8IRNXBqfspQk9mSSo5t2ENl9dec72H3tAo7dfBKxEdnkHVO7MTU7i8WVJft+ardT2FydoMwp+ZtIG4m5azL09sSoRgWKJUryFryPkiUxc1x87QHcd+sD6FZdbkOBHJitMK42MBXPYFJm7Mlbdg1G6QZLmkZ0vSIl0pceTFCSZK/sdsneFNVdYKBa+sX2Qa/E7BU7sHZ60w0YuS7ldI5xPETHXR/pRsNtoWsd0SUb22t5N5C8w+CKz7wcq/EKOsUIa++y+3zfPAYbKTKBI6A2x5hfnEJvahqLJxfRHfUwUTkzgAtVoowy5OR76BhYvmhgK3jRjIPGO9dJQDOAj/NuIwALHGMsdiCF8lcVwgN0HHnlr3/7NvLM3EZu2bSAXqU8sCKsMykecIzuqAFzfJsaFruToUXDYm/fg82YN83nPRO5KgSACBEixEcMWgfoHqOCpZiAOGbeascchYCLkPtU1gwP2kY1WEjvEYvfs2G9T7l227Dsv9BzXTFVw+KVkDkKqrnf+Rg0N0aqBktlyWvmia0FU36brUUqvHeRG6h1AwjIraoWm9avlVXVANtebtlJD6v6835+29oWYSS35jm/ttfFMQ7NNA5Uds8NfobdAqy25nO/1rcB53YBT1vloe2X3hRu+f5uCsLan29/p2grkjSFRhWD4Mycbq0hDePYkcIdyA6WBxdlCWY6cycqu8bbtZyAW5ZvNrzy0T6rvPEYpr5Gq2jNt6ku2FLiacwFC0KRZvWOiiQ+pmybZir0DkxhvTfCSSxiiDHzp3dVMzhxz6MY3buO2XwG0U5gOF7H3GW7UaWbWLHbjdUYR81x7NrfRb63QlYUKBcqzO/vYyk+jXUsM9icYoAHTz3ETJ1+NIt1s85+T5OIjCJEBpy+Z+Q6bNu12R9hsb9ij5uwL3BSiaIKya2jqLhYonLruUiS+7XZsfDtPUlqKvJsCC5wqKsPQ4QIESJEiE/TmJqawv/9v/+XfXcJtCUP3j/8wz/E2972thr8paD1czwef8L7/97v/V5cf/31LPFJ8sy07n/+538+fvZnf5a9Hj9WUIEcefpSDAYD/M7v/A5mZ2f5d8r5kLQ0xWWXXcYMM2IJX3LJJfjCL/zCLZLWIUKECBHikxOUY6VCIgJ5ad73QX+nfdM3fRPbAlABT4gQIUKEeGLj8QeAjQeSKrEqrCVyJWHdllOuk6VbPi5OseyBZySJafxGTf62hsfqz7kfad/0x4FPIDfHahLlzIRFiwVciz82TKXzgb/t8OBYmyXEHoiQxCr9vLE5xMr6Cvbs2YnRaIgkFZleTtK32ltLR2rjla/rfiGv2slkYhfOjGULM4ywND7rksaGJZ6PnngM1elH7e8Fcl0hKwuMxpnIQRKwSeeuSxTl2P5h18F4NIIqu0Bq38tL9vGt7LGrfo6sGqFrUhgCjscGqsOmgexXScaRJCupWVaxYh9IOpUqM7WnobRKAIa0n2Cihw7IFX9HkuqMehqTaMTy1iylqUpmr3X6HdlDWV8oOIwDJfkV220Lex6d8RQm/7SOyd1rSDv2PDcTLKztRDpKGDQh6KWK7fhbBk78n1O8u06eYl2RHGqGRE0wtO2esh0QFzJeqH3syWz/eGwS/Vuv+TlD/RxGb4tl5mQ+y7JqgQx+nLYG8pbPN+OtagPK29rhX/IynpqlRQs3DuV8/LjcDkwbs3Xsbj0fD0i39s/RFG94kIdB8xAhQpwTyjFmqXgl8gAqWqoWSjlg1c8PVQ20ypxRMqjXBgaZ6ekATgGCZZ+VL2RSnmnaUqlwhU1Nu7RbV1usYdUUiLTBUr820n7aagiVQz+9gofI5Ve8psrxRTHAg9VlazFrAOaKmakyD5n6fZrHqD/odZpfZB6TIimZy+gwXhnDFX85MJTWElGpbgDkNhjbBrblvCPe1gPnEtr1x3aLB8/U9kBuM++3atjqY/l+0udZQ3w7RJ1Bt+ZpX1DkWM0o3fIna4dxYDotjkzKljIpfj+qGcdyuf1aS0HPDEXVtKFd9FOvMdR3Rkmhki8kMgXKuEQ1sL/OVOjPz+CEPoMJg7Al9mIe5dIEk7s2sffMPsxMpu0aq7Ga2HbsqrBn1zyGOGOfVjKsYQk7ejsQ79bYWB9hYccM9CywjLN2fyNmH4/MGHOdOey7cQ9m1TxS1YWaAdY6a3abDCIRDqxiE90dXVzxWU/FJaOLoY9EuOc9hzHI7GeiDkuCG/gx7PtDWOHKV/wBcMPE3SIe6P/o632IECFChAjx6RD0DEayysTW+v7v/3687nWvw549e+r377vvPgZeibn7L4nP+qzPwm233casX9oXPZsQK+z9738/3vSmN31UoJba9pu/+Zv49V//dVxzzTW4/PLL6/fuuOOOGpR+7nOfi6/+6q/+F7UvRIgQIUI8PvHe974Xr3jFK3DvvfdueZ2sBn7v934P11133ZPUshAhQoT49IvHHcWRpHTpkt1N0rUSwlCdwBb5xcbLz/OAPCDb+ABWLFPYZkGyxCPEF7YGXx2rmFm/RS4JePeel5Fsg8heFlFeM3UbfT7Xs0GBJkF+3vPdwhR1XrV233mZY219Axub63jqtVeyvx75IZbETnHSzsaxRD0NueFeuiS02/doJLLRw9EQ08RUyQSQJfCUWLnk6UtsF3LGGyQDjFaGKPPYHqsQdha8j2wOk1BquULX/gGVs48gOBtKAqMkHW2YPWS3JW/lIuZzYXnn0klm8ulJAl6A2YITr4WTChbWkfBW40hhONnkjtUsEW1bojrsUUwsJe0YR7kphblEwG3uZTmLWj1cGErSH327bTFRiLIZTG0OkBN5l/rd9knu2kqcoaiA/eqghwRxWaFzQQf5nhx79l2EKhoiOWiPf1rh/r981P4xuYPZaEVeCADwEa+vl18GvOQ44EEUn8Rv7gT6WYoRvMyoAzzYX9Jsw3UdO7ipZJC9OMa89+f09w0XR7h9CjgBB9AWW5h8tTx55YEZf6xzz0/uAbkmpsWCFvZeI7ta90GIECHOCVoDkjhlr1bdYogy6KhljiwqX6ThGbp6S3GUgJ7tQhEn9wwPHitXaNMAlW1LA14PiWEcx04SWdi/W8umZN9SLNWAwG2wtF1Mwu2CW5/qc2qAZIr2XMI2xq6iiWWKlZe9Njyf14A4fJvb0s6+cAy1HHRTC6Nazxa+aGWbzHOL9evnMF8QU5amBszbrNumWEZvmT+3z5G0unmVBd+29rZaNZ7F9We2FeRoZwvglRzE37kBlP01piIrxteN9DNfT344UMgmom7CTxOkQBKTz7RdH/PMHj+RNbMsXHHWuf3i28hex/Y8SmYKC6BcUX92bB/0KiQ7ejB9MPN3wn68CQboY+Oxs+ieSLEw3IWpfAoq2sR4yu5neYKFXX2kvKoTv3cMpDm6CwlWJ+vYMZhBEWV2f0O7vzE/t5Sqhz0Le6EXWOyan+/IZ5jkpkd2K3FtTrkNR9PT2HvJTnrCwPTCNEa3r6G7lPJ9RxLWVSQ2DaR+4osVNLHejSjTcDGCdlfSFRgEubEQIUKECBFiaxAji0Detkfv6uoqvvmbvxk/8AM/gCuvvJLZXL/xG7+BD33oQwzGkoTn/v37P+a+SbqZ/B8JpP2rv/orfu0tb3kLnv3sZ/PvBw4c+IifpWeZ/+//+//Oed3LQlOQtHSIECFChHhygtQXSPHhT//0T7e8TnL8ZC/wX/7Lf9nyt3uIECFChHji4wmh8fmpvKolBp2koXGJVmLxaM840s7jVDwNhfjSkl50rFyD1r74VceU2YJEiZwuV456YhHlSp2MblUnazXEX9Zt4D/t9RBd+MSxT4x7FpD3iT1XIjLmJCMB4ONsgon9IrLszl1ztg0FJ+CjSIBgBkoRuUR25WQdHTsLPmEfcQp1PNokRNb+R+LGXWCjxKSYICWANs9RRRnDsWWVIe3OIrfHJZljrWI866nXYXp6H/7hlndjMtpA0ku5fRk2EFcpJrqA8MoymK5tpaJ2ppwMJjlm1Y1Y3jmPcqQ6BfnxVkmOkW1jWpEPnz0uecLSJSaAw76fUCKaWL2dHsrNEVRSceI4KRQzv4quQUEUXNaKdj6F5AM4t2Dbfxa53mRwmNjClWNGeYA452ti+6uc2GNSPyUo8jHiOGWPRWIyK2Y82eNEBtq+VtrtN2w70tM5Tq8dx1q+ic6RCtnYnvfI9n/XfjYiiekEJTGlVXPt2wxaYV5pTk7ziCz9aPdjxhctSMJe6wbEMM7PU/ALD6B6YLk1/rbdQ74aQMBfL9HsP1fWODSBPKU5F4yg8F7ASnkgYSvgwXdIi3pey52bqi6Q8Nv7woiPxY4OEeLTNxrGL60JMXsApzzf0XJT2vk/jqN6DRHcU/FrDWDZthXQDWjr72+4AyDyECiaAg9XrEOfq/x85D/u5XC1247Lg84BPLfH9kKYBpSlQp+omS9aqga+2IQBVSkNc3ORK7iqKudhjObzLaC2ZhLXeLSssY1Ms8yx8rOugWjPavZt9cdSW9b2NpPXFxp5eLst1VzW12FL37RYwu3iMO8RrFos6S1rSH19dV3MxuuEaUlb8/bueYjWPtpW+/m6kmvqLAX4M/45xIPPNK7oOaRy64MxaF/Rtmw1t4E+GtHaKeOA/HPpRR3bsRkbDGYGMGkF0QoxDNimeYqlU5vo5h0BcIlBnFNlAzVZu+cz8YbmhzpSDkkU8jijGjD3nCGjJUOOdfs8Qmvk2D5ZyNWUdbbgcq7CPf9V/MrYbluZCauj7MYujJIR5iMpMuOytEieAeh5QHPxoDzhaAdsG2Ld19dc+qNddBAiRIgQIUKEkGiDv/S8813f9V14znOeg5e97GU4c+YM/tN/+k/8+8/8zM/gzjvv5KT+G97wBlxwwQUfc98k4fyXf/mX+PEf/3H2Eqb1+Pbbb2eJaAKBab+fSLzvfe+rfyZ2WYgQIUKE+OQGKVf+/M//PH7u534Ow+Gwfp2UFqlwh2Sgae4PESJEiBCf/HhCAOCqcgRJYtlQ4tT5+rL0svEArmc8OhYuJ6sVxNtXsrjGUTXqdLqpWolhSqBqAQNV5aQtnRcfH6Oqsd06EYpWgtf5Ltbyz+ojs4h88rj2zTsPSCzJ3AqeJzXazFBkGRbmZ9BJIlSGhZYZAC5d8lYAcp941NJxdRMbX+ONyQaDsBsrI8xe1cHZbBUqSzCuMgxMB6XdlmQZE92FiRWDw5cduB4E7S6eXMXymQnyzZJZvgw8lBq66iAzQ8RFgkh3kJMnMXXYJEdeju1160Pbfk07JSq7X2LQgHwB7Wc7nRhpGSNTlMi1Z1B20CWDXtvGIhGmaso58RLjpICy21Kyljz80lIhjft81lmcM/smHpMnr8F0f5q9C6mvEndlfE6emE1+5IB8i+05x5G2fVygix7yfMIewSa3WyT29ZISweK1XNnt40Sx9/D68gr27d2J9bVFDHYtIL82h9oQQL5kYFmzzeL2ijS5zv5amRpE2VqIsBUIZnCnBb66IVwXHRjHRPJJaM8AawMKW7wvVetzSsRWKy5kEMnxus1m6/jkEVnLWhduvHq5Vj/WXYGGYxXLiFQ1KHMO+IMQIUKcLxh0YtDTAWpR5JiIAg6yhL7mu1e211HDsmWlA8/q9euNqb23WVLaM1krXmARa8fChcyPVPBE6gsMePlCJxcydzQeuNxWd3w+pvbrrTB1a/TYSeSSRDMFMU9JLl+CXiv46AzCuWIVmIjnTMNLQ8n79QCtnyt9kUwNirbAYQ8A14UplWduumahcsLAihm54hdcuveA9olvZfc6BQ4jn2sYsdrNdQ24jbqPtnoje5uLNtDcnqOpgCqq2bxK5n7fBng9E/dk4xa5ulDObcPy2to/o7hnHghLl86bmbvuYYvWZ6/aQOAvnwqxW6lfqE+2jdEt7GiS3lYlc3WNiXho0lJHn+UiLGYi5/Zdud7E0I3tMXQhqi6TxD4z2M91abzF9oU44WcPd8WlrSBljtw+M2T2mSJ1r0Q8XgoWgh7xOCpdQYM8LRR8TAMpAFM8hgr70Jrb54Uhg8VZNEEZEzU6tW1MbTti++yQ817ovpFCCMd+53VN7h/ylKD7kvwN6X7Z7n0dIkSIECFChNgaBOyur6+z/DMFefbSs0qWZczoveKKK5gh/Pu///v44R/+4Y97v695zWtw44034iu/8isxGo2wuLiIF77whSzz/K3f+q0f1z5IsYYYxRS7du36qAziECFChAjx+Mef//mfM+v38OHDW15/yUtewtL9bcn+ECFChAjxyY8nBACWFPJWoFSysj7h6RKmHvisN/Hyv+cCrECbIemBLgGxPHOWmTHKsYIc2rYVyGuSyp+I5MR2NlFbLvAc+UdOaEfIJgXKIsf+vbtZctJLDVICfWsCOnJ94BFCf34uDWq/DYsJxvYPm7H9A2u9GqJXxlA6w85r9+Kx2x5FlcfoqATL5Qp29LoYmzE24gx5V+H2R98HbY9TRond1whX7rwUS9kypgYa6YLG6skllFUEZUdCkUywZDZx8Q2XYHljBeOztv/iCGtmGde88CDuueODmFa7oQaZfb2L9Z2beOqLr8Ht774Tg2wW2p5n2TGIOwIqpxfFWDyzinKHxoFnXYLNlTUU4wr5bGH/wFuFurLEpddfhNP3n0SR9pHtrGy/DdHhAgDbIALNKzT9Y4Tlw0znDnlT5ojtdhUzlgRoUFEsDFtVIq7sWLCvl/btzkKC/r4ppN0Bpi9aQLVud7mri6kkxfg9a0jLBGVcMCk5IXnN844E3QJnGxbsdsZc20+w2s4krt+R623awC3MR9ynvAaYFngsBHZfSLHlrvEtaX12exv9sbbfB1vZbI3E+rnemiFChDg3CDjrJImdviqRCia5+8TOS5F2cxN47WJQigpoqCiolEIORbLNKnbroxZ2pmnu6Ep7KwVt59v2euEsDLSuJZod/5/BQLp9RQGjWYvESqEUtiqtRezrrRi85HtcOyUAAsvqtdq01rpGUjovvY8xakazAOHGWTq4diop8qo9h40HCOlcc1EEceBvnMicTvYDXJxEQCVyx+g0whKtZH6N3MxKxVUMLmppVymYel0Epk3lFBiMa460h8DTigHlxluZr4+f/xyVugaxPWtXO6Zti/nM51ZyJzNgK9trKQZqPfLo2ru4ZDsH6SLlsXZhz7LEf1mDv9TnpOwBHSMr6epmiJKS13hBx8u6KI5YwwW3vb0eVS1A34VTH4npnyHpaLu2GoHXqaAsShQzdsF9n/GzFQG5RYeA15KL02L7+SwtYB8lkNhnjQkzdz10DeYNm9yASr9Se2+M2ZgitcdK7VEr+0Vb2n3a1V9zSxSfry+TIPg5dkzexG6T2n89dFFuFuDFuhKbCyoMU6XnHjcFEHLdvM92xFYJsb0n49S2ZTzCJ/A4GCJEiBAhQnxaxtd+7dfii7/4i7l46rHHHsMtt9yCm266CW9+85tZyvl//a//xWAwgcCfaHzhF34h7+8LvuALcOTIES4y/LZv+zbe/+tf/3ouPPxoQc9H1AbaNsg/hwgRIsQnLx544AGer//+7/9+y+uXXnopfuVXfoXXjRAhQoQI8eTH4w4A12lQl1Hz7FmRRhTubYNxNuBpLUFZG/FWkqBFGzzbClgp7cAq0/5db8G0PNDsvQq9hO72HOj5wrMd2+dD0fYH9u/JV8LHJmCyzEvkWYnZuRmuSiUZUKUk8chShpx81w0zE1uBb3+8xB6+2swRxSVG8SoOPeVqnNk8gYU9C4hmCly170qMNsdIyw4myNDd3cf0wVnM7dqBUVnh0IWXMnuWkp7FJEe6s4/9Tz+AWTWL4XgdOy+ZR9KJMenaY8z38dSXXImNsxvYceEMdl7ag55VeM6XXIHjp4/h6Z/1QmysL0MNSvbtvfyCA7j7ngdw1bOehnx5A0mSojA5J8+zzQxE6rn4wouAfREOHzmM2arPgG1/Rw/pgV0w0zFue9fd2LdjJ1+Pwx88ingYI4oK2G6CpPUdYOHGg7C8I2Ys5d2SE9qUjO7kCapUYVyto1910J0QoBDDlDl0FWH90U2cPnbKHj/BmYfPICEZ6sj2y2aCp+65UdjZpWbAICcpzKpC7TPp2ePqXClPuPGkHODQploJo+8jA7rtAdiMz63s363M362MNsYSCNy31zlNo5q5WwMb7kZry5efj9ksiEQl6XrjwJqqzSd0gJIDgXXg/4YI8RGD75xKFhhKWClKWiURg7sV308Vz0ke4K0cm1NUJMDSuzXoSyzPhoCLin8XBn5i5zdWGSCQkV6ne51AW3vvln4u8OxJyD0sYLO7j6NI1mNSBSD7AiUFStSGyhVwNQUsDRmY1i5hnrpzJWA7imuvWponGcRmIJTWT13XNnl5ayiRcwZkTudtabpUTkYftI6WDgh18zDN+VVmzzvhQiDxEdbumUGeLOh16tmolH0RIElfxHKOyEud2Mh+LbHHpGMIIC7nWLByiGZmtUIj10wPL1p5+Wrqv1iARGbXGmGVOhUQ6gICFxPyoy8Lvl78zMEXxK0H9MV9o2pA2PeN8uogtB8GhmOeu4tSLgDLUucT+17fsVfBz1KaqgMY/Szsce13bddEQwxxRtEhoLzma9xosLg1x4DXZhpTZBtc6VgUMaj37XuJSZDS+3RdSG8krhDv6mOYDlFlFYPO+XQB3VOYmepiGSsYQ2Se7Wpvt7Fr89IEc8MZLhabMT37bmqfQ0gaLLPXhQDegowp+J9tOYZqHYt2T6vY5HbS6z307dcA89kULq0uwebiGjobXejCjvKClEdoXMT1syWNQ163af2jQjE39gxfOylU7PRSZjxvWbxDhAgRIkSIEFuCgN+FhQX+eWlpCfv27cP09DRe+cpX4pprrsHXfd3XYXl5Gb/927/9L9r/tddei9tuu43Bgn/6p3/i1974xjcyuECS0Dt27PiIn6XnpB/90R/F1VdfvUV2NESIECFCPDGxubnJks6/9mu/1lIGE3n/H/qhH8L3fd/3iTVjiBAhQoT4lIgnhAHcBq4YAI68b2rFjEXj5J1j1fjqbQW7BHTyspc+Ks/orf1VG+9SpUT+kY/fknU2Xme3BnwbtuUWSehtwNg5/q+ufd4LsA0CenANDABnKPIJv0aJ2iSJmI1DSUgChhNiY5WVa4wDx8kHkTz7ygpbgEK7SRblmIwy21cpYtPFP//5rbjshkvx2GOn0BmR2OESkEzs58hbWOHo7baNA4PFxTMYPgYsjk7B2H2ouIDJNR665TiiuMJScQZR3mOGkNY5Sznr9LhtT4w0S7Gm1pEWGqOZB9nvj1jHD91yP7KuRmJyBinG5TL6kwGO3/8Yy0JWWjOThxhBSqf2Mq1iwhntElPjKfu9iw09QnXvKrJ0aNufYg4zWD+Ws4zp6fwE0moKuTmNDiWihYMF7//skEmUqcHFzzsIdant66l19M0sFu9ewuz+Bag5hcljG7j/z+6z+9iJOEqQ2WNe/hmXIB+UmJmdwiNHHsI1L7gKo7TCY28/gmi9QqUKpBHJaY/Rt+c/4p5pkvV8tarG45IlvZ08azOe3MitmqKAagtbzm/pxpXx4+D8ca686FYQmIGCwrDncxp3pZe4w6r2Xtz380hcKvFH9CAwSX5Xpv25BhzWjlHYsNxDhAhxviDAME27IpWuI8fajJiiy/oQpFIQOQWAqtoiVcws00r2weBv1fife8Yse8N77XgH5FVyc3JBSOVZw8atocbPJaq1dvHBZIatYmHXlk66mV5n3eaS/VKFQev4xI6pLG11a7JxEtQeXKX/dMWfjbT4yYr0fLs4y6t6yLMAAddNwYyToXfMVMbvHBO5nhPJ87wiv/lEwGICPiNnP0F7qNfmljSCaaSX5VGgJYWthXksKiL1FnzsdpNFdcHtn4q5GKRVdbvJr5bbac97UnqwO5I1cdscLDYZstO6OM2/xs82Zb2t9L+T+o9FJrkwwsaNULVAZNT9Bs+ENsJs9tLhWrsiH1UbcUjhALv8wjGXSx6bVBQ13BiiW/Wh7VqqGQImcHaM3Rftw0N7HsIZLGImttvPGfT2DFDNKpy1zyU5FVXZ7QeYRcc+J+SnbEtXUyzeuYrODnrmICURAdwLYkHbp4eI2zJB1imR7upiR38Xi0DnGIPchvfYJ4aN0yMcfeQxlOu2fx5QmN7ciV4xDTXWtV+0cWurlzOv7TsgY4me42gsU7JiZna6KfYKESJEiBAhQnzMIMCX1tB3vetdeNGLXoTnPe95LP38nve85xz/XdrubW97G778y7/8Y+53bm4O//AP/8DAAYEKFDfffHPtC3zdddd91M9/xVd8xb/8pEKECBEixMcM+puKinPIBuDkyZNb3iMlhl/+5V/mAqEQIUKECPGpFY87ACx5RUk+1qxDTkBLclUSlZKlZWc6B8rWTGHdMIaNY63UPoAqErCU3qtMnaQ1qqHzNoBcK6qSQWDvqeiB38ZfsKqZPl5it05Ca0nQRlFSS1xSG9nj7xxfwDG3ZZiVyArBncmbj5LglWMNV3XSXlg3kph0MoVKeDnGQ56GbWwxLjJObEZZivnVKejbFWbjed6mS/srBpKwNRGSooNqrcJCb8HufIjNfBaqzICJ9Mug0JycJ8AZzo+2lpfMvC9yKfu1w6O/2mcpT0r0x/al7ogSzF3u754D442zziXJZQbJvS0z+kjIt5l8eLXdq8nRyVP+TCfvyuHpuJRMLw061RyI+tuJZm0LJigzhSSOxD+SmEvMlquYiXXi/tPAUGHcHyO1Y2F4dIS1s6eZtTQ+WaKj99ur3EFBPpTo4aGbzzCzN05XWUzyn++6XxLjE40Dlw7sPhPnU5liQuBMEfNJeClWkfusWLq1KipmrzEQEOnGe1FJir8kyhTJT5OTcelklB0zrpF43spe96GchybLVzrwQmRbq23bSdGDssfKxiSd2pVkt0Ort/hNOvD4HCZxzYhXdXEEJcarsrCnubUYQVjqDf+tkTwNESLE1hCmZRUZRCQza7+IbSsSxIa9T8ndlOs1HCtf+XuRcV82IRcxdqdEIKxi8diVJUrYxKpVvETzEG0DZer1hGWendwF/U6MVzmmbnx6iYFbOsFdx3Il1QgOAuZkqRIw134uL3LH4HVrWWWYnSlQogeMSyeYIH1BChfCTnbApxFf4FLLvOL9irm4i0HNuAaH67XaCItTQ7zY6bWcQFi7MOUqs2vuhKWGyQ4hcaB53bdKCnh47ooaWftmPgZqyXvlio6Mv5ryv+bRQCHLxzzXx1Eqcyb7HkvRkMO8+VoKINv4z9bzvZLnAzg2NUthO1C/cj6/nn1LG5aV83ynIh1aHSu7PuqU2a6JdtLigPO8lTWL1mx6/iioEMGtU42FgbfbcOxnLdeD5b6JYU2vEQPbPjdUG6V99kgQ91LeMz23rWANC/NzuODGA3jkzqMYIsfCRbswf+k0TnXOMgOYPH+pJGwn9mC8uInylH0+2ZjCmaVlu06fRhXbM1GF61tX5BSVSKcTVAslptQMBhdO2fascHsJ6p8xfSzdfwYb921gfW2EhcVdmLLPDQkpgNjnC+WuMfcFPXP5okIP0rtzptc8ACze3GE9CxEiRIgQIT7eSJIEv/d7v4dv+ZZvwZ/92Z/xs9BrX/taTv5vD5Jxpm0/HgCYgvb1q7/6q/iMz/gMZhWTrPTRo0fx7Gc/G29605vwZV/2ZY/36YQIESJEiI8jbr/9drz85S+vPdd9kILD6173Oi4GChEiRIgQn5rx+DOAPRCmtUgVElAaScLWc2m0EyA0NfvRNCyl2ie42b4BgRu2sJfl9aDp+Ri7/mfP+vlIIcBveZ7XVQ2oCZgtr5dVWTMit+5VwGv6QyXLxuh2ky1t8b6D2jF+lZOAPu9xIXKalDDP84L7MGKwWEBCz1wWwDpiGVFKbo7zHHFscMdDN0OrLmJWQywFVLDHLDmxHXvCkm1MKUAny4aWTbKUk+8571uS9/4SKscwgpP7bF1696tRTZ67Ys3QmvMqspx1u/0HjfhNom+/9VFMhjWjLB8Vto8q5CTlHHds3xM4qzA5Yl9/jM6FoWJ0zA4UBEInKToT8jweOb9DhZTAXPvVc8nvwog7YaQF7I7NnP0hBbG3BVCxbfQJaT9Ga7lncHKeANk2e70dGqgBl1oqtdUn57ve50hEt4a/B3+3b1e522BldQU7dkyzjyT5j24lFDbsen8azc7PZb57sEi7tlfb2lXvJ+TLQ4Q4b9BcrdMEsZ2P4zSGInl2YrhyUUjEUr3EwhQAV9bDWv6ZGMMsiUyevM6zlEArlvSViYTWH5ovPaE2JmnnStaVemLXjtnpblTtCqCUKt2cIGsKr8MlFSaV4pfKzM+SpZJZH8DuN/PKB9qpIDgmpfFKB3QGNC9r8qy3L0bO+zWiZwCSQNauoMQDuHJeBDay1DStUbGd44uCRTxI4lnVEvS6VoAQVjTIGl7eieS9cTkGugYHr7wYJ0+cRb4+QUpqHL59Wp4BHE7qVA5Eglopz65V8t3wMinAoZ8jCawmsDgSgD6vcuzcM4det4cTR08iEv3gpp8jxV60ZSXIeUTrZeURXwE7GWwlH1pmh2tIPYByEtslA72uKkDWbgdSit19hYsuOYDZud2489a7ZR3QIj9N23BxkpHzkj7XTra7RGMD0KwlBBAT95fAYgHoFXcCsX/NSCM7k6Fcy+35drm/aOuRfTZ4TB3FvoN7cWjXZVxjNzU1i9VoFadxCpv2n72imMMA0+U0jj78GDrrfXRGU8yYjgrDYC0Tzd1YobGj0xyJXauzbg41SfnZw2tx0Ogkx+D+UoLJ6T5mh3Por88iLXu2r+n5QDyRTSnPOswAr58DpeBBt9Rb5LkUbn0OC1qIECFChAjxiQT5O/71X/813vve9zIgXK+r2+Jv/uZv8NKXvvQT3v9XfdVX4bLLLsPnfd7n4cyZM5hMJgwiv+pVr8J//+///bw5lBAhQoQI8fgHyf7/t//237iYpykoBtsC/NRP/RS+9Vu/NczJIUKECPEpHo+/B7DynqMlJxSVS/ZKztUlVT0IZYxLzqqa2cs6jmiSyx6QMrX/agvY9QAZjFO93cpY9MxG4xOv8AAsPObcSEKqyLFxPVBWbmEfKbdPz1Rpn28jEW0YdCRWCSVcOwQAa++Z6gE3YWoZeDlG3QB0ptlXA6Aq9u5l9pVrp2xT1dQkRdKJlJglj8MoYRZX0lWS7K+cDCXDkhFLV9bMKvpOzCuUwqnaci6OwuTJ15wwFhZW3damExzYIELfvvENkC/anMIeLeu+cFQrHickX12NN7Fz5yay/AT6/b7tuxxraxoz8ztw4uQKijJCGpXO39Jw4t04aUxK/JK/L+EkVdcO7CJFRcxjVfC22kgKmQsSYu2AD5Eo7Xb32OswEuaViRkgF6i8PbD9eGy95Fh7zXjwMHdz7syEY2xeeepsXSThx7lpBmI9ptpjfcsx3Xv+wYv6nf4g3twcoT9IaqaZ2dr6LdKvvrmNTLvf1gluGyly4BHgj9c+zzYYHiJEiC3BDFN7KxKgSUUZBEbGcQdVQeoIupaC9t6r9X1JoF1hBIhz8sXMdtV+HigZWOzO9ZFVBSbDMYvmCnGXmJuO3ejvTa824cAvUuFgr+HKcyQhoC+B0Xae7PZTZraOhhMyIrZtjRoGLf0rt84Jfh7gGhfjGLyJsW3L+O2Y9kEVSEXlXRhk/aft2Y9Yzq3UFUaTDVz11CvtfBzjvjvvQy8eALWVkChQGO/YoJTzBVYCMtNclRo8/XlPx8033YJjDxxFx+5HZ9KHpSfUMiCILSxQdyL8f2/vUCuCMBPZSwfLvEg4bmaPN7t/jgHRBx95mM9R1RRhYV1zexkvjhzAD5njIyl2ok6dmu5jY30Dyo4LAr2NA6BpTWJPZ8MGDUDrGYrA8qijsPPAAvZeeAFuu+N2tvc1vL4oLiBoLr+b3+GAZPes0bbb8D/TteJCMC2AN+PPI7vLVTt+pxKsn1nB7I4BBnHXrrQTlmSmf8fVCXSnetxTq+z7S/9GxN9Gii72mj149L5HsPLACvaXF3IxVlza4xXafikudGB2thbGe17Yz06RD7HidbiQK8Ni0sTupkIuPVLoTXro2680J15wYV/O7H1jny4KOxZKGR9eUpwKEQuI73HplFgiO27iWMY39fd2u5EQIUKECBEixMcO8gX+zM/8zI/4Pj1/vuMd72DmbjvW19fZP5iCwN277roLL37xi8/5PMlJE+Psi77oi2rG2c///M/jAx/4AN761rdiZmbm8TuZECFChAixJehvp9/8zd/Ej/3Yj7HHuw/6e4oUIH76p3+69oYPESJEiBCf2vGESEALcOgZqsQqbQ7TBsw4XWragNdW5m77M5zAjBop2yZ5We8JDfTmP+elHZvXVIN+8TcCtrRpHQdN8txLPnvmLjzbM9KeRuTkKyO3r4pBUvL7y7MCC3NT8JLO3DrvW+wPb5wE6Pn8WV0P0fEIUCYZUU5aamH/ip+iS4I7qeJOkjKruqoz5ZJ4114D0zGlxQNQtyR9Y9m2TozL/lUNkSsHYlNEcDh67RfLEsX15dqKZnrGqWmg9vr8vexmmRskcWofMBbxHz57H+Z2xOjoKRRmgre97TCe84Jn4k//7yNIkhlM8gKpMk7qccLS0+R/nNLYIGlSYvbQAaKJyKUy65iSv3YcFoYrlPNC2HTkH0l/mNJ3uRWc5DhLOPszqOCLEuALAeqxcj72bgMCtxPslR9DHym2gcDtN87HEBZgRsYnATLj0QT9fkekW/1+WveKB4wpJ+6lW5sD+2IJDxALQ9Gfh0hSbzn4RzmRECE+zcPeHpvlCDPzUzh0xSV47OgR5CjY8z5i2XaRb+aiCuPtDyKMRkNcfeVV2Lt7r90mxskzi3jk8CMQ7qNBqUoMixGuu/7pWBut48MfvJuZpTSjxqYu36iLn6BVa21xM5crWmGJX2Khss5DyQzgK664FKfOnsTyQ2ftnNlBXNo1xyRiYWA8KNqsx34eEFDZkJo0snKMpJ/gwosvxPGjx1GMMvY8rvxazfuJGKgjwLhKiA2bYZgPMX/hHLKJbU1SMEM2JrC8aJ4ZlJO99mxd48BrmvDHZiQgYM+ua7TPQtQsTGnqdZznNcZJ1Rb1hu0qCdxvinar7fUSpjItpIZZ0hW0XYvzbo60lyCz6wz5D5NktVYiW10ycKsQ2/Val1rsENz5M9dWF7aPIlx5w+X44AduRbaWSRkXsZZ9t/KlUlIMULhnCy3reRWVmKgx1s2a/T5CQkxzRwevnB1w5YrIVKvgqK3KwqBvLM9lvLZXzq++Et9nAkQJlC42bD8uaeSPDjGzbwYHd1xkz+BhjCA2FlTQtYZ1SElbya927E8E/u7DbnTPJnj4A49hfnke0+MeklyKIGhssdK1KwYglRPqr6KKheFt1+ouEh75U+jZlV6zBzCyBKMhSVJ3oEZ2X7athS6R2+tPDwM0XrkYoeWt7e8HHvPud/K7pqicl/RH1ucIESJEiBAhQvxL45ZbbsHs7Kx9xryCf19cXGSpaGIN/+Vf/iUDB+973/vw67/+6+cFgCnIS5JkpEkO+o//+I/5tXe+85244YYb8Ld/+7c4dOjQJ+t0QoQIEeLTJmiefsUrXoF77713y+skx09MYJJ9DhEiRIgQ/3bi8WcAO94MO8V531IlCcWyaqRsKRpWoiTfKDnZfr/5WdVShmj5oTZJW9UCuoq6JR8ptoDQTpvXs3H9+8bJcwrCphvw1yVaedtKJDbZd08Jo4k8FpnNapvYHwxaeXfDSXKtfd68ZGYys6CUSC4KAOllrT2ALQBwv9fjhK2wV5RQgeyXcG5tW8mHUFWOaeTkPrXzHlSGk9MCxFaORdycJ0HBUZSKZLIDAzWEkeO98SrnWVwDhWilTJWHdVtsNqVqb1x4BhR3bgTvhcsv2WMmrMWcI0ln8OCDq7jUdHHixIrddIKV1Tm85S3/BPLxJQZapCuRFI3Ec1I5kJvYYirW7CsorYnk3Om68vFj8W6m800iJw9p9xeRbLScl6m0FAuowo2gxifRJ44ZyPVs3i3FCuYcUuxWxnCzTQ29mub1dvGC97/2IPn2wob6mOS9qYQLRx7GFUnLRlWd8BeZ6rantgN+4MCRyhcE+HusAYxLT002cPcdaqDEX/MQIUKcJ+ztMkGG+X0LeMoNT8GJxaPIxxN7zyQsB6x9YYibR4T9K0VDsZ3XEvvV7U2hl05EaYFAslgx0DWpxtB2WdEdO3F17UqbE8NWAOJaFYDuU62cKoasb1Vr7ZElT2bwws67VVxinI/QnY6Rnx3bqTRjGWpaSsnX3RdG1eoUvu2+cAqkGFDwvD4pJuj1ujh09SU4cfo4ykkh/r6FYYYyFQ15gUApPqpEbj8yGKoNbBZDTGLyrB+jY9sfsxqDXxMr6Vzl1UKUeOLaOU91NDbLITayDRSqYE2LhPx5TSTKFUqKr7asYY7l68mfvtDLP2vwJ0rfp+B9kJdzQuuHvQbpQhdlx9jeqtDR4lvMzwll5NZcV+BmyCtYmLhGF8jVCFGSIp2z203bazAuEBWZAKK1T7ADzJUD8o2TzebzteOkZ5+nlL12dn+KwXQj48oV+wjwXwlru+4vNzx144EsEuOi0JG7Qh/mLBOYavugyOzYODNGlVRYTM9g57P24dLpS3FSnbBjfMiAdsU9kNtrVSJRKfqYwg6zC1gs8eBND2Dm5Ax2b+zGdNa3Y5mem3T9jMTt8Wuxk8yO7TWLihjz9jmAmLsz6NgjJJi1/3rFLCa2qwamg8TYPjRUnDDhIj6SMtdFl/nChclkHYR7Jm097yn3fETR7Xa5KOwcC4YQIUKECBEixL863v72t+NzP/dzOcfzh3/4h/i1X/s1fPEXfzG/Tuzd+++/H1/4hV+IL/iCL/io+yGm8Zvf/GY85znPwfd///fz/h566CEGgf/kT/7kXyQxHSJEiBAhzo0TJ07ge77ne+qCGx8XXHABfuEXfgFf8zVf8yS1LESIECFC/GviCWAAU5LTy+dGgp1CpIxZDlEJG5SBKW1qcBgtFuy5fmwNcCU79szXLUQkl5xWjunTALv13rQH4RqgVV4XKeHKA3CUzG2xluEAXmbybmGGyvcmker8FCuRX+50KCFcQFLevr2lSz4SSE56jrED2iiBHnECV85Dzqsi0JNkCpMEZZLZTXq2fT2WbuZkPjOcUpS6ZIZwVXrvQs9c1RDpz9L1TcwguU+ga9sGIsBU2nvVOrBRGeI0eRjcsakK8fd1AHVNprYfLU3ESXwCAog5BZZejgTw0CmycsKjjdvrpaXdNSv00P7Uheqk+NDta7j1g/ZcUsXSnXTeKhKJTQE4SO46R1F5r8NKPI0VeU2PWf5RRR2YTLEXY079rTX7DpJUZElAMEmbYoRIz9h+zNBJe3xdIme1SddBOYfOSuAHAcRLSat7qevKtL2MPahQyfii/iDfy2KCJJmy7Sh4nNd4rhvX8DLPFVDXSyiR9RZwHpLIJiADIkHKo64ScNdQW+35rm9uoj/dZTBd8vum3o4KB9pFFwwqkfekbhjKbfY7v9aQv91rAiIRECGM9yCZGSLE+YIKaciTtNQ5xmaTGa2G5G4Lw4UV2ghYqpyMfu39at9L047H/7iYSCuRsi2cBDIBZaWdW3Mztq/ZLzuXkY07L43EiFUyN5lKfF89Y5d+pnlZyQQmVgaQ9bqwbSW0tTeXMrOU2MBwxSG+8IMBSS1etnUhiJsj2CucJwyS2s0xu3MaSA2G5Yg9a8u8cL7xNIcWfNxYk0dyzAxe9nil54TEYFwMCb6zy6KdawvnxcsKCiWvPQRK8lqtnAeyY7ZGScTHmuQj12bUzwJwhTBSwEP9GG8F/FyH1+oHTjKbnxLcQ4asqiSfQDLcORcaEfhK/2jtqXxxEGPUWp4faL10RVUszcx2AIa9ao3tnyq1a85AIz+dox8NhC3swWpnt1AWBe9LSZWAXF97HTqk9kDvu2tuHAOcfqAxRmxaEWGpK6+kAE35Ui03VskX14HgsVMU4TWN1pdScX8TM9mczVna+SgexeyV8ziwYz/G3TEmdv3cNGOWhO5igl7VR3c4wPhkhsfuOIr4SIxdoz2YnswgzWLHfG/WDm479Q+BsratsR3PSZEgWxujt9bBYNmunXa8j+3XlJlFtGjvhdXIbtfl8SPPR5EdbvYZiO8FzY89yoHhxvWbXAUZAxFdH3ruqaRIsdPt1IVuIUKECBEiRIjHJ2jN/bu/+zu8/OUvZwlnYgL/0R/9Ea688kp+n6Sdv/Ebv5GZwAQs0Pb33Xcfrrrqqo+4z+/+7u9mWWgCkVdWVrC2tobP//zPZxnSV7/61Z+sUwsRIkSIf3dBtnK/+Iu/iJ/92Z/FcDisX+90Ovje7/1e/MiP/Ajb9IUIESJEiH+b8bgDwD5qIBENCFuzPj0jxckSi5RwdY5x/HamsBe5PF9sZ3DUCWr/M+dTjWM7bmUBc7LXsY+9T9759l37CmMrY7huL1SdVKSNCHhjVmbNPvHAp/fhJTXpBJ7b1E5BNsxkhUlWYKAS7FrYjTgTCWcmJilKZpKvnUaiBwzQal3Y3w17KXKfRgI+1569DFTHDYOLGFliANwCAZ0HZS2d3WJLn8POJqyT+LYCMMcQFq0AloY9GqtqjCSOuF2NRGmz68RMM4+IGM06noLqjBl01yrlJHjlfH5Zvpi9hBMkKZ2ePd9yGkav2fMsgLKPWAvLuUopGR+jy4zhkf1gYts4YLnQosiQxn1kxRgpeSZHuh6vykmXVw6BVzVTGTVrCO73jxYCklTnjJktMuPbxte2PdT/b/N/29tqAsYLzdf6wgMXMnCitaS6ubiiBXz4z7ZZ7tulpduS1R4obl0mAX5rk+fAmAoR4nxBIB4tAWU0wjhaQZZuQI07iKqUi2JYhYHldp1yhRFvWvrj6tTpU1hdWUOn28PS8iqKKmMJf1qdCpYiNki79m6cDO3dbr8MgV9dLjqiYpdc5VK8Q1K4ZcRyw1ywo0S6n7FnZ9EgnNSI15K8l2FNL2O1XBSQcmKPUUR2f6Wbz8UXvJ6Qahaxnw0cUKoKdGYijOMxsmSCJIuRFiSFbNtA0sxxIT6sNCfa+ZlAPJL3ta1EN+2yH25EnrgVyftSMysGdsmjmA4fkbd7VImKARzIWQhrNWLWc86sV7uR/Tly7S0hMLOfz0qnnCEAb+XnRSfTzIxYo1lymwqt2AuZin/4/HPb3jW7/uy2+y8YEKallEBFlqVWQnGuuLZNM0hMSwwrKdD1tvsiz+AyrrgwILNrE03ZMbnmVlr8cF3b2Ms9djLJdB4kxU3rqM4Rdzu1KgcVQiXkalCIAggVPpEsNTFrSR665LEmBQa1ugiaNYDXPFMKZ5jUH8ANsmOv4Db1zcAON9vfJ0sM18dYPHIcyYEO4j0JersH6NjrRgUJcbGJ9dMbOP3waVRHgbmVWcyMZ9Eb96GzyK63Bq46SYrXqtIJrNB6I/Lcsd1udCbDZKPCQzedgLrHYDPaZEZ9WT0GrERYOL0H3ZJYwfbzMRWZ2bbktv22T4vOiC04yCqjcP7PXnI9jhUXqJG3Mt2HIiNu7yf7MLFlbQ8RIkSIECFC/Ktjc3OTlTZe//rX44d+6Ie2sHzPnj2Lb/u2b2OgYdeuXfiGb/gGHDx4kCWj/+Iv/qK2qThfvOAFL8Btt93GrF8CjCmPQ/snX2BiGfd6vU/G6YUIESLEv5ugQhxi/ZKyQjtIoYGUGy699NInqWUhQoQIEeLxiidAAtozGD23CS5ZCwEZATQclKjF4P3ogJJxbBZmIXlJ28o0rNU2VmnEdVe3wEr5uHj0toFb+r0NgjVJ0a2MkLZvsSRddfvNuo2NzLVmuSI4UUXfCmOa9jf7cSwl5U/UsX+NyHoS+ymNU6yvbGKuN0BZJNAxJZ4LzE7txo3P+A8o8hgfvvcDOLV8GFGimH0UR+LMp0km0TXec4M9IGwcs+t8gPY510CLLGYtD133kbCVSIaY5KmLfMisZHo7p6R9LN6XpqqwzU3WgY2Rk2PmLDcn8ytO5hfcfmEwM97L3piUytelQSeK7Dkex4GDEaZngUcOH8Xq6pTd1wBRGSPRm9ixa4hDV8xicXnN/pF4CqY4IDbGRiMhX+U4YglIwCfet4LdW2WcGxB3u1e1MY0Eaxso94A3M8j9jkwb0m1+9Iy7LbeC/1159+hmW+akaWp/B4PBDNY3V4TRpbfub4vcudtpzd7eMs49S90IYATPpKvq+7mWYA+SmSFCnDdYQr0kFqtGXuUs4Z+ajrB5lRQJObMDZvoTY5NAK7IMOHr8ON97Uqwkawgtc6TQwOxPur/JCpVYu5D1piBWbSmFLwRaUsRaQMm8zCCWAIq9z+k72Q4QsCp2ALIO0RpALOPRZGR/jtzc5+aZ1vrsQUS9BTBz7Fi7HhGbOOkkvOazjy8pXbTmSF+QROdLxTwgj1snd5yKFr9j/QowqEqZf1jxoJJ20vuFm5diKnSyv3fsMZm5y+oL4rNMnczqHNqvpaJgIMVPsuYRFEzKGR6M59cr9wygfVGQEuVp23QdK76uM9MzLNld8rotBV9aLr6sD6UHmKUgiq6htsfJuV+IoRuhE3cY1K+fCSB9QeegHHuZVtqCWMBGlDtkPamQdjoYjSdyHVidoWQZZLq2RLDNqBgMGt62oL1uEQAd8Rgt3fUz9Xa0ePAYlavN7SqynE4ccdVDWoI9jofLG9i8ewNFJ+NiK2JF24uPeNJBb9THTDaDfjaNaJLYczTsW8yjxEtY+EIoI4UDxOTVMUuE8O+6jDA+NUS+lLN/dpnTE12CtErRVQMGxQ0XPRi+B+gZgYB/Ko7j0obKsYpjUQ6hZyAqQugYXT+L0uvj8Zj7V29ZB0OECBEiRIgQ/9qYmprC2972NgZzCQj2Qc/F3/7t344v//IvZ3loihtvvJGZZz/3cz/3UcFfHxdffDFuvfVWfPVXfzX+6q/+il97y1vewvv5m7/5Gxw4cOCJOakQIUKE+HcUDz/8ML75m78Zf//3f7/ldQJ8f/u3fxsveclLnqSWhQgRIkSIxzueEAawaskyC2wkYFINcDkYUsBfBxQrrzfbAGvnSkFLstPxhlEnEKsWK7IG3nxu0cnZalXLCBNo1vYWbidHz+tPbJRHtl3bWuziLaRY7WR8hUlKf8Cw2rTz4/PalMolbVGfv5OJrHuswddISjSvJnZfGsRhpcRtHJec1I5UD8O1DPfe/WGMRkNsTlZ5O2JqJVFX9uk0q0kC2edetW761vsF+u5vYOFtTF058RoAb18alq0kNk9Uoiy67M9bGs1cN5ixPQlibcWodMb+fz48j5Q8BCPd4+2m+hu48KISZ84ASysEfscMFpCkMiXQC05Sl+jYk9k3V+Dzv3IfLj5oj4kR1jdn8cd/8ggePdzFTGeMZz9/gM940W4knQmKsoN77o7wp3901H7+UuQZnUDMjGECJRiTdeNIWOIiSSmveePmBhBgDPScooVqW5+55DaBF3o769dfC13LhNZy0K3/80/+njFbX5dxZcdFJ2XAY2pqGuNsw7Ytk1sDzRj2UqlyXNViPG0tftheAMGgjZNcF+lYJSP1YxQLhAjx6RoMLNr5kIDC8XiIiqWcI7QFFeheJIywgLMEiBQm5QSdXlfWKVbNME3xFIyTli5ZFn+SZQwys886zVEEAGspCCEA0UvER8xwrZjhSaxImUKIWkvvi+1AyaCyyEMTgKtbRTp8/ythUfoiIV/s0sx1bkUmeWrIecPJVReV+NMmfByxWRC42K+5DUibpAmDkk6BuN63P44UKBkGOyliV1RDYs2RnQM1ecDXLFcHoNJSy4VFMTOKyRO4dGu2MajnRFVr3jcFWF4kg/YZia4wg+1xL8bU9AxOnzrDYDkVJXkLCFovPCOamLjcD1S5VIoaBwPTSsBklnAuSvdcQvYSFc+vDIBrkaKmayrS275dAqInaQdrG0NRxzCmBs3LSsqE+HcaFgTy1nO/qRnADfhLPwvFmNQ6+PdKCnzIi5rA6YK2LSJ00UFSdewxcwzser2AaTKJZkYt91Mpnsu0DXtTV6LuQoVVuSawngdYrY5BwDuNu7Is6vaxTDYVfI0qdHUHHdVh8Da2+9aVjO08HrMdQ2aPG6dS7FaWmR0PJR8jo/FPrOw04bZLmYW97hNDZ8DqJPTkS89nlIT2RREhQoQIESJEiMc3CATeHj/5kz/JrxPbjIIAiN/93d/Fr/zKr+ANb3gDRqMRM4I/VgwGA2atveY1r+Eveo646667cP311zMoTH7BIUKECBHi3CCFBpqLf/VXfxVZltWvT09P40d/9EdZbt+TZEKECBEixL+PeMIkoBuGpCRtxZPNJXE9esjMDd6aGZneQ9WDVtvBKElebpef3crEbANePpjhCjk2szSNJNhrdg+EOaO1PkcCWuSrXSKZ9tVifvqUMUkIC1BGCdOxYy9FwvpkRhY7xsIYDzqr+mc+XtWck7BvjKNeAkUuspuJTtDRHWE8aUqYElAwRn96hFNn12wbOvRpBnrjmI6V2891JImtCnesCD6hrp1kJSc+2de18cQTedBzGTFb+hTiYiydVOGSg3OY5Gs4cSKHiRKM8wKJyvDUa2dw8tgqVteMJModblg5WW6KlGQqqyHybIyDV83hGc+ew623rmFpZUMYWY6RRiAwsZopu9uNNvDs50/hokMaRbHJ7KDZGYWv+NJr8PrfehgX7prBMz9jFnHvDIpJD3GS4WnXzeChh8a45X2bSDqzXJigYi0eua5NNW/XyYF64BOueMFjsJVp4F+zbSw1TN9zwdztMstmy3hyY8CNmLZEs3GVD6oFiDCQFCtmCdIDmrH9OCIAuF2AoQRgoffbDGA/Bmo2vW9L1WbEGwFqlB+j2gEr1XnHR4gQIeReZUamWzRIRpdtdYntyeClYVlefxcJsFvBewF7WWhTCuhL6xeBbJmd71kV3/4jYJmYi/QVk7S0k7P1nrB0z+cEEOvSsVIr/l7y+ipFNOx7Tq0hSVzHuK2UsElZylgJIFdWjZrG9rWRgoFWJfLFNJ/qJMKkyFDaeSKN5HNUw8P26g7cJuCavG0rFhwuGQgkYDMniV76VwmITYxdBoMJnHRsUQaQ3Xc6H5I7HsxN89MMMZ6pqQzUEjNayedl3laOHSrFWM3cB8B5BQvzWTfzrSz6/Dvts4oNyw5r+5UTc9SzhE3jii51Q6q+nrTWR8r5ptOziO2Xmbk5BnGpuCmy62WVVfWx5IdKmOGVEVsDGjsoeDwIWK8xHE34nPgZgtmvDsB1xWbs/67luhhsLfBpnpEc0l2/74rA6DnE7jO2bYti2z6iXOeKn0NMRjLWXQZdfQGbMLQjLgaLtCifcP/E7MSAnJ5HWh73vrzBjyEpzNMitU3qHPafjoQpTvcPSZrTv0JNUMYlduzZidNry1iebKA/28Xc9ACbqyso8wzJbA9Vh1ji4kG9dHYZu6Z3IslSVMMSmyubmDIzEAWWSIB2c245V4gQIUKECBHi8Y0/+ZM/wXve8x5mBtO6v7Gxweyz7/qu78J//I//kf1877///k9onz/+4z/OvsDEBiZQY3FxES984QsZ2CCmcYgQIUKEaIKk8n/wB38Qx48fr1+jv89e9rKXsRLD7t27n8TWhQgRIkSIJyqeUA9gz/SowVnjJCShHSNRErBV1Qa71BZQzMeW15TLBfukoU9Ocy62lcYzDbDW9niTNkU149Ingrezjn17OCrn1KvQJI09wlcK04okMMnnlrivcRIzwKidcC/vye/Ks6ogILGAi1vb7RPUBSXK0bH70wy4UpI8SgekAYrLL9uB6ekcR4/lOLtCSeiu3fkQhy6Zxqkz69gYUvI/xsJMgrnZGA8fWUOp+8xmKtQa05AS1eUEPLWdErcKObN0K2e3XDKQoZzMIlg6NI5TFAWBBDH/nibA/GyCzZHG2Ti3be6hl0aYm4rt9wK7dqRYX5vY3fXsISVRTPLV7E1JY6EY4elPuxCH79/AffecxAP3rwN6wb6fcLJdOcCVCVWU1I405maAiy6356sy3HTzAzjzgMHnfMlBzMyXuOCCIS67bCd6M2OcPVPh7f/3g7jhGdfgKTd2cMU1fdxxe8zghzExoigWxhrQStg34K8vSgC8cLlnSDcMqmYbxwgnhhEDKQJSiPWz+BDKOKzOKVJo3zNe6rkBfz/C/QVKYKfodgY83irm6iYs0UnAflVlwjiDT/jr1nGa/fCY9PLV2oFPxgG+xCCvfIsqB5To5r4IESLElqDZIc/HXFhCBTvMHvU+rk7Cl0m7Xoa/rJiFycxbLYx7ZmiKzAATdqtIWMUE/pGf+nA8dt71AtrR5wW0JTKxK+6huYd8Zemwmim5HnZzTFUH8BLQB2FMxp0UIzNBQZ6wTqq4clA1beeBOop6vqpEBpnWiIqKQxLl/HNlDiMv1sQtpRWaNsraVzpGtGJwtYADgL0gP8sDV7UIB+/BzVXGAZV03jPz0+yrS7618IoW2q0vDIhzi2ugj4E/3fjeCwtX2LY8FyrHrHbPBMxMtu2jgptSycUsi1zOoRQJY1NqJwMt8tsUJbNLE7tuaZHrJl9dOxz6gx5fawJJE+Kn2nFCaztJKRt3jny1XB/GER1X2hoRk9s2IZvk8LBznhf83MGsY4itA4PqRkByH9ufc4xQnO11a1jExmPQRsZm7SMvA4m/Supm07HPEU4vxK452mT8TEHFCmVeceEQeR7rnNja9tnCiEQzH7sUqWsqcpC2yPhOipSL2IxyTGEtrPLSjkltnx0q+3xBYiE3vugZ+PDhe3Bi+TSSXoznPe8z8I9/93dYObOJZz7vWsxdPI+NbIO4x3jwgQdx4c4DqJYVsjMl7rr5HkypGekf209dYt2fozYTIkSIECFChHi844ILLsDv/M7vMMuM4vu+7/vwtKc9Dd/4jd/Iv1NR81Oe8hTcfffdOHPmDEs69/v9j7lf8qkkSWjyBT5y5AgrfHzHd3wHbr75ZvYg/nhkpUOECBHi33OQQsLLX/5yvO9979vy+nXXXYfXve51ePazn/0ktSxEiBAhQnwy4omRgHZesQ0LUdXArWp9+eSldlnT7Tm484GylQPnmF1FyXLHamUgmVmNngncSAwLc9EdS7UAY0qIfxQl28b/UNVAc2UaGFCp5gicao6UA501g4oewKVIkqiWXfRt9Il02iUlgFvETmEtV5R4zlkakxr6ghdeh0ceeJAgWiSdCAs7ZnDvXUdw6dWXY3njCIpJhulBF1O9BOmBKdx1T4YsX8Pey3cjiSv0e8DGhDK3FQ7uTjGz0MVd924gjqYY3CYpRkrCxmyaSCwj8REkBCJyzCiCKVgyNKZzLRiU7Q00Tp5aZRbx1EyGldWJfb1v/7hLcfjBwzhw4YUozQqiaMDgpCYWUS0rrDA1lWJzYx0by/YB5Ln7kHb24Zb3neFEd1lLhrrENstga3S7id3/lP1tFffdZve0fDFOHQUumS+xc3eB/tSUvdYdHHnwBNZOXoaH761w9XWp/UzftiOz+5mx15JkpRPue9/zcs1pTJXN9XcsdYUWU9cXNzSDRRhFcgPUjHcfZgt713N8UY+fNmvXj73tEtznePm6sUaAEJ0DgQS9Xh+jYc4MOjoPkh+tmczw957ryxb7dzuD3o9pYeY3vsKeBR3S5SFCnD/4/rH3SzdNxZu3qIT+WgkAysUjlQN2K+HFwvvOVuKxyiBnfZuzji6Dh1NTA8z155GNJ3IfllIIpZweA7sTsJywYo9aAlBJGpnmdlEM0Ox7TvMRA7aVsJJJnaGTdJDaeXWkM16jGDP2TNxIfRSPeFkXmcmspd0EqiEyDCQTGMrqGMoxi6WUCllBjrh2zdECitL25G3McyUpctD8TPN9HKNQwgqm81BcDMXlUAJUEyjeSzExGe8vjbtQZFvrQHeRsdbc3wz8Eke2EpYtt97Pfd4agZcm5drKfG5+SKFipMrVvxCsPx6NuDiGgFMBbI1jtgLCinVgO6t6KCmesT+TPy/tW/rfwC8UMk23Z1bT+q7cdykeSOIERSFex3R9OuRnX4kEttGukKkyLLsN3bB/vfKDH6db/OprdjWcrHTEr1FPE/hdeflt2q+Sa1hp5+qgCOQvubCtpPGeaPEgroTJzteBmNRRw0KO3P4FiNecrOXnM7pCjiVeUWNiOl6BKrLrmn2OGZoJViYrmJrv4plXPwUPHn4A3dkIuw/uxup4FVls1/+FHhdAGTuOXnTFczFcGWN8vMC9Rx+AfSxgP2ApXjBOrSWsaSFChAgRIsQTHc973vPqn9/97ncz25c8e7fHe9/7XgZ0f+RHfgQ/9VM/hRe/+MUfc99XXnklbrvtNvYWfuc738mvvfGNb8QDDzzAjONdu3Y9bucRIkSIEP9WYmlpCT/8wz/Mnr6e9EFBc+LP/MzP4BWveEUohg0RIkSIT4N4YsohG1QM29OZXsLZ1IiXEjB3m5TzeXfbBqc4UdtIGssBjGPatiEqcYATwKvZv2dEqm0sYIq2Xx5vq8TPkJKZ2oHBkup1Es9KkrvC6io56UoMTKOrLZ6JdO70OrG2IleJqjywWplzEuzMPMpLFCZDlPZw03v/GZ/13Kfh7vuOYXpqD4aTEuvjGONsHd1Oisye594LBjh6bBn7DkxhbnaCSR5hYzhCNgJmZmaQLRE7tMIFO/diUq6CyK/EXlqYMtgcj2z7Z5GTDyTJQhO421E4cMEuPPzwKZSqaz9buKS1+AqbYoxBZ8CgY25ff+rTDuH973sQhT1up9PFaGzbVUSYW+hhbYN8BmMRFiZZUU4tF/a9PjZGJXSHfBWXMDVNDOEYldIs9eklOFmSmPtbJCaJcUVC1FMzBTZHK+jPHLSbjDDoJrYvx/a9BPMLA+j0DOZ2LTBImiapHTarzF4Cs5ljZrkpNGB/e4xUXj9U+RHcGr+tga3QSDjz55STifYgq8/f19c2ctsW54zr7Sz084HBEo6V7XwsGRjv9JjFPRpvuPfboLFvX+kA58b3sJE+lwR8GxzwLDkBUray6UOECLE9BAxludy8Yg9gAoG9AgYxJIVkqh0D0tQCEAw2lqX7yalHuGmHgOFut8NAJUkle2In+cjGBJY6/19mCtsJ6MCBC7C2uIahnf8P7L+A56Ll1SWM85F3GKjnBSpYIungcZ4JSK2ccYEDqNt2DLUyQUtGmIE7ktOnuZSKg8RZgNtaB883Rd1HPAeJFAaD0gTk0ndw4VTB6xJKB1hX4oXMag3ejwFimWDYF1dx/5QVyWLnSNyzgHHgtchsG1asICCX0WBplCg1KFPLb/sOV66KTbN6A7jgTL4ruWak/OEukAdvjSsQYjXpLaoRmh9XtF1vyA+egPi8zKWkiV4rmuI2r3DSWgXQSEMbDPoD7JzdhfHwLrduOdayvx5ONpzmdJKP5iKqqjpnXauLf8iCmsaOewYR6XHD3rr0Oo89YuTqhh2ckG2DEeY6WHa85DWdx00poDgVH3lrD5GV9j3uflZwoH5THJVBQGApNHIdUWqI87z92fbbYGYW3aiLmKyJV+2zzeoGTj12AhcdOIjN9RzDxRwn7j2NDaxgamcX66dXsXR8BXPFTmyc3ES/nOJnuaq2IDm/ykaIECFChAgR4omL4XCIhYWFLexcWpsnkwle+cpX8texY8dY2vlP//RPsXfv3no7AnSJ7dvpdLbsc25uDu94xzvw/d///ewpTEEsYGK4vf3tb+fvIUKECPHpEDSf/tZv/RZ7+hII7IPmXJLHJw/g2dnZJ7GFIUKECBHikxlPCAC8nSHopZSFAEPJv6oFcp3fD3WL7+82cLYtoesToD48a7NO5FICVzkWj29ZLWXo2tViKrf344+h5cCSs6xEPlO7xLWXDCYJxbjOcPoEqJdPrBjQpBSmWKlGGE1y3gdL9ZaKE6FxnNRsIJ+cz7Ock7lJt4N+eRCPPbaEa67ci6Wza1hbrRCnHZw6sY75+S7OnlD2DyGFzbHC4cObuPTQPEbjITbXU5xe3MCll81jaXER01N9nB7mGK4bHNy7C2fPrODKK3fj5MkVHDmWA8SKpeTuJMKeg33s3qWxvJhiZbNyrC7DMs6RNjh0aCeKagXLaznKqouV5SF2757CqVNynSv0sLZWYv/+ndh4aINlncWCUQkrrMoxP9fF/Q9uIO5HOH0qxYnjq7aLpqUXuC9NDUJGzB429o/DDJubGXpTE3zO512NtZUSey4EkojY0h3bPxkD7Zcc2ocv+qoB9uzbYfub2GK57XPNMs3kV5jYByAZU37Uij9zG4wXuXK9ZYy2WbJNYttxyjydyBc5sKxyAxC3oz3OZMhuBZfPKUbYco9ELKlJbDDDRQciI2occOvLL7b7acu43AZiu/vBmDbTGTU7q10t2CKNhQgRYlt4v1iRDq5EydkBdMxqJBC4KLgwyTh5dbqdvEIESdyLj6/IGYtnLmo7Bd5/IQCpdlLKuZ0PszJHOkj42FO9Hp733Ofg7PFlloffuWsvlldWcde9d+Hk6eMCw3JRkyTaZpIpKV4SbV9mp8b+nleoAcP2PNSeU2K7pmVGVlkCNKktLOLsil88kC1fYgMRaWLDluzhywxWV6BjXOGKfM6t20Rk5Xm7dHLESgpf3D/qB/I8LlhSucMHIv9YahedF20fE8jsTBkYeK7X2mZmbltMoH7NbeVUH2ICulklo2KJZe37xX22rIR6nHARU4W6A+C8hQlIjaSPqf/5uwOf/XFrHBq+79yZ0vFtXyWdBD17jZM0xb6FfSjWNrG+tOzWVumvisdUU0jgz0+K7+S6CthqGDj3DzQsCR45e4r6kcmxmMnigvo14kcBb8vMxVqmjHmsxlrK4wgg9pLPLJFtqhoUl3EmQc8+9BxEXyQAzkVG1K+080KxD7FCimpSct9tbE7wz+99PybZit13YZ93NnH2qP056SIr7DpYkBpLiVGyjiIdccFFlMUYjOfRWZ/ClJnmcxNVl0aRJYDAIUKECBEixCcvCMC95ZZb8JKXvAR/93d/x36UX/u1X4vxeMyy0ARQkLfvjh078OCDD9YA8J/92Z+xv+8LXvCCcwBgClrff/mXf5nlTL/u674OWZbhxIkT/Pub3vQmfNmXfdkn+1RDhAgR4pMaJPNMcs8k+9wOUmH43d/9XVx11VVPUstChAgRIsSTFU8IALzdIZQTgChYtlGSmuI3J5nVrUCb/36O3O15ghgnFQNt1ZbtmsSpz6Y2woyGM6xRDWIJg7IteWtqsUWG0Iz8IeE9CQn0ZDlJBvQqB7Q5ZrPyZ+6kpR0ATCAjJaZjToxXzJTVccpAcMEMq7j2beS9Vk5ykvKfJAFNPrWRAAErwwiHOj1cdfVOfOBDDyHp7LZ/KBU4dGgGK4uP2Bb1kdM5mAEmI409u3fg1qMn7HYDZhxNTZcY9DWWlpaxuTHGRU/dgVSPcPT4SeyY2Q1THIaK9pJ1MKKsRLcT4wPvvxuHrrgaaw8fs20YMNtKJxGzbUuMsXPXPB45vmg/N41HHjmOyy7Zh8Wl4/YcdiHq9LG2Tu1bQBqv2PPpuMueQJcR4jRCmiQYjSvoVHq9M5jCaKId21S5hLbzwzQxa3sORx3c8+EVPH/XLOZ3jrBjF8HvxGFLsDkeYPGxEZ5yQ4rpeWD/wWl7DTTLsBLYrvU0M4uVSfj1RCvHnvLjcKtUpoybOoXuXhDmdgs6aCXWReBafIHdNT2HwVvVoPa5x8BHfG37fUFtTGz/UUI9SWLkeeTAWueD2fIqbu/j/IxiSHu0J5s5/2yScGUmmIBZbdnQECFCbI2imNi50M6zC30M7b+JGqNT9ZDlGWiCmGgBVxOjmC0phS3iu64ig7HKGTiMqUCFPFTtV8FsTKL5F3YuGdu5k4DOCGWeoxgV2D2/H/Pze3D89CkU4zU7R9t5cmJw8MBF2GXXAJLlt3tDNiodmFwweMZSz0rc6iNiI08qROTZykoXtq3O81dDipS8PziB2MquSYU9T1WWSMkM1rZvQvNK2rXnarcrVO2PS6AiqT9oO38TwzSiI9CaFk2Q6xx7L9yFomtXkzIDYZEsX2xfz5MMud2GgXBWhICAkIxxFijte1Vq10jyHSb2cl6ydHRSJbbPO3w86AkKZY/DggcCLsokRyCurNfkNcvANxksMLpJG+cMcuqS2NvCAiY2saEvWiDt+pFGdj20xzL2+Dl74DpmN0lw20by5wnkLewTkKJrT+drt4vtceyJagI4GUSGWzuUg7wFoBQvYtLJsP3IPsmKPZYzu590mp4nxhjlY3udJnYlLu2zgohjc9EZg7bGPm+UTnHE+QELXZmvIzF76Qkmco+C4q/s+LYEnhdlDfZHXOhm95hoZJg4xrIDzL2ktjsH4xRPKg/0Klmd7e7Ew9hBwcyvpqFDT4dUEKBlrSTWPPclWw6LokZOYyiL0c07GG0M7dghtniMQTVlH0XkfHRc8bMSnX9qn7EY/KYCLjsO6Loo2w9jbZ/FlPjZp+TR3UvsNZkgQMAhQoQIESLEJy/oGYKYacTWJe9fAm0JnKXf3//+97NcKX3fv38/nvOc5/Bn7rjjDpaEJiB3fn7+o+7/q77qq3DZZZfhi77oixgApoJHkoem/b/2ta/9KNYmIUKECPFvM2iuI2/1P/qjP9ry+kUXXYRf+qVfwld8xVc8SS0LESJEiBBPdjxhAPB2gEhYlI0HKksDYqsH6fn8SNuf97QY3paSoUxQ2i5HyVszOMe5SC2MTpKfdJBZDdwpl2D0DB/JwTrGMVrgWyVsIwYkXVLV44DeU5iP79jA9B75ssZRzElPYtcQe4ms8fKSpBM1Hn3kMUwPBrj2qgh5XtbtaBie3BiMswli+0cRgXxpxyDtTuOe+09i5wKBtHMsK2ns/86e3sRTn7Yfjx5bRa87y169J8/kWN/MEMV9u78+1pY3cMnBAxgN17F4okKqp+z2K7h47xwO37WB+ekIBw7M4sSSYqA1IY1FAu3VDv4+M9XB2jBij8GSE7xdPPpYhiNHNqGSWU62KtOBKSPs31dgQj6VzP5ROHXqrP18F8ur7npVIqtNrGcCoqnzCttBBAYPxwJmMuCgnUemEbltFWf2dY28GOD2Dy7Zc41x0WXGHmuMpDPE7v2zGOc5ls7M4W/+8jhufP5Ou43B2eV7ccXlV9hj0DVLGXCJKIGfiPSoB+79WNsqxdymg3n/3oYmVl83LUwv5V9TXt61Yfe2PYRVKxG//V7xDHbP/qrvLdX4UDODicZtJL7MwqLS9nwHfC4ERFE/FpQ496O/xShuvgvozbBD5HU+UQPAZS0fKn3kGcQhQoQ4N9jLNFbozfYxGY1YxYHmeF3IfVUaVkiW+RIQpiUEZGUmsMkZgGNOpl17YpJOtv9lBLra+Y6U7ydVLpMMgYN5gSuuuAr791+C6SOP4dYPvJ8hvfFwaL8yLC4u23Vggs3RGCtLKxARC8Nt5NU41lKQZcNkJc+LJElM7GX2aqU1gMUftPNtrWQOYgCb9YFrj2PaTUIAIbWPwMOykZX3ZF6eD8ligPanYz7H6f60Pd/cfiSzbUnsg0nKwCoLbTD4GHNbBRiP+fOE4cW0LiJBN+qwdHZMwLJ2qguR2BtQxPacokoYrSqqmBnLIKeRhVfzHF25c5PnBwIXI7IqqAQizavSnSOB9SUmBNQzoGzXSntcYRqDAWg6VSruouWLIVmW8FZ8Xqnuoq8HfGxa06igSlWeWQ1RuShkjWS1ikpAepawtu3uRQN0dA9RYdtnj7WysowqK+xaFrM6CT3plG6JorUhclLcXsWhLlryNGOvBqHkvONY1gT2E4YrhnMsdnoO4rWLwPuiFKhYx7xvXdcFyTqolfMkpgIHAu+jqFaDqRUyXNA4EjaxXIPYKa5UqhTFEfYPppo6rk6A7hCgXvD4yUcZOvb626vKRQMJAcAsu27QTTvUoXbsDxGldi3UJT+TlKoj25G8tP5o/tYhQoQIESJEiCcySNGEgp45Dxw4wD8/61nP4mcL8vQlCVMqoj979iy+9Vu/Fa95zWtwzTXXfFz7Jgbx7bffjs/7vM9jT2GKX/zFX8QHP/hBvPWtb2V7rBAhQoT4tx6UfyCA96d/+qexublZv97tdvGqV70Kr371q/nnECFChAjx6RtPkAS0qckUxJjx4CpLO2pVg0nKg2Uu+dYGfj3rRLuEowfYtGlAMOUwu8a/9Dz78HLNHOItx6Acb+SBL/nFuH1vkX/WLVYvlAOUG7+9LdK8opnrPFmZsyP7JNYJyxdG2BhN8Nijx3D/PXfhuZ9xI3vzMUeUE+1yHAbKIaAzgag6TRFHHSS6wwnhTmcHVjPbhmSAyJ4fkZyWVsfQHYPhmMCCLpOYsixFNS5Q6YoTuFmusWy3m57uoUgIQOhidX2MD6+egYrncddDp/GMp12M08vHUFQJ5manMM6HSPtzePjIaTznmdfj1tvvRkaS1SQ/TD6A1Oq4z6AwJ8f1HI6fXsFnvvA5eMc/3oFITdn2GZw6vYoL9i9gcXHd9kePmUfatquTKgwnIzsQZ+Fy4Eg7WnwEyZeQ5cJj9oDkQ1TOtzmaMPBx5+2ncdO7gSn7mS/46t0sTb22UkB1Yqyv5/jbt51EMU5ww7P2ILl6YF9bQ2KPb6pYgIYkcoC+A2+VGyfQzbVtjSfvRyyAf+PR6TnkEhUn0smT0hc7sFe031uNEPs8eJMI9wl05SRBy+3j2gicAjdeJFkf22ubu76z19x0MBpvyn7sdSJJTgIPtstXCwtZw7PwhczVZjX71xvAt8WzR4gQIc4TisDa3JFMlXj10pJRiPRwwv7wJRdmaCWyxMxONLLGRA5xK2NiTYoyBDE3JzSJ23ltpAqMuKhDfH87nQTZpMCxYydk/Yk1s0L//l3/iDIT+4GS1TI0M3GN0+4lRjCxaLMqQ9xNGGRj/3oC62jfJnJyveQvTmCvgLG1PG8ZcSENnx/vm3yP7VzcT7C4ug5T5rItxLO9gusT91neOfkX23NICexlALVioFmZ1HZBykVXeTZi73cCqslfmIuunFyx7Qp0CFRVKQOgg2QaakjM4hLEibXLAStfdKjop0jZK7lUGatzwDhg2v1finsMe+ZK0Vfrkupmne/ECQONQ6zbfZUyH5PsMO1bSr5qBQ8GNCupNGPAu4zRMV1MJTO8ZU4gckqqIDmD5QycE+BN87ZKhJvLHsiGmbNkm9BLB+gRgDyy83+ZMNBN10E7PWaWGHfMbS9wTesn7UMAXH9O2kkzN2uDf96pHDDM6idVVfcTrSe0/5gY0E6CG04tgovuHMAv4LryKwj3kUihC9DrnwHlOSt2BXmK19SEivVce6gfqJ8IPI7sWp2bCab2JDj01CtxavWEHWtTuPtDdzFTOS8y+wyk8PRnPwtry8u4/cO3Y/9FF+Cqp1yFD99/N/ZfuB9Hjj/KRWf7Fi4GVhTO3r8sz5A0Hrfo1oQIESJEiBAhPpnxQz/0QwzwPvroo/zs8fu///t43eteh4MHD7KS2nd+53fiC77gC/AlX/Iln9B+d+3ahZtuugmveMUr8MY3vpFfe+c734kbbrgBf/3Xf40rr7zyiTidECFChPikxMMPP4zP/uzP5u/t+NIv/VL2Qr/44oufpJaFCBEiRIhPpXj8AWAPbkG12LXKJRDbQJfxaddtvqZbAdz2z94n1e9HeyYJzgWB2yzHssxFwtYzOzVqP8X6i5Ldqqqloreyj1EzKAW0Exaw3794yUlimhlR5C9LyfRSWMGTSYECKZZXNvDokUdx8tgxPOMZ1+GyKw45Dpgk/+HA6LZXLLHHup0efxGDic4jijvMCK4oSW1Ebro0dv/rE/tJ8gWMUFYTJHHKYAB5SYrI5xTOLI9w+syQQVgCbaucANyU2WZRtQMnTpzF/EKF5cUC8zvnsbi6xPs2qoM7776X/4g6dWqRwYSCmEnUl6qqWaJVHGNzHOOv/+Yu2w09youLfGaZcNWZxorIOKuM/7gjf7/NjaHtAnsMexwS2iTAgZLCiAtO0vO+I5dop74pKszNGXzZV16FXfsN3vInt3GCf2FnxNVvk80INz5nN57+7GkcObyEm9/zCA4cvMgeYw1nT5Mk95xIWnJfxvX18z6MwFZJ8cZnuoJHfAkmYKlnFX0EP10Bsetih/Z4hmMBu9PZLnPu0uXwnNtz7wFHtXLyrfSdzpvAXGZjufe3AtN+rEet4xnHPmyYzGgdlYsXag/gEv4uMA6oChEixLlBwG7UsfNtojFaGjPoql0xkeG5umCpYWZ+EuBZkV9sArnvIie/brfLxWNWxI4L+1nD+60ior4qeE/Yyk1Luf05N6Wdg4ktWWFMUtERkXMLthxQDABWfE/TekCHI9niiZ2L5/fM2+0zltlNI5JnjkR1gT6tc5ZEZkZtwQfieQSkyKDEG5bfs+2b3zGLwUwHx86sEeLNfrXI7HoU5xirDQZju0mXAVraT0mMTF0wiN2xO4kKJw5MxU8qZ7C2t0CgIxX82L7SXbvbiay3xEKlbUgKmgqEyP3Xvp/ZRhZ2nxO9iYn9nOlVGI01+mYKXdOxc77mOZNWROMKY7gOhguLnMQ1yQ6TBLSbb8nLtojssZIcqmc3Te3pxZWwllmy256PfW2sSJJ5kwH7XrePHskoZyRZbdc3u9aRBHQRZ4h6MfeZPYDtBrvPVKSwk6kIV199Ne697z6srq3b1XyACSmH0zNHakdNas+tk7OM9CgbMSPWmKguptNxhCLLGTClKBmANjXLtbEtECuLiMYRU8J9kY/iJKt/XqoVTkoBmRlYtv9I0tqvmzTeYx03j3dK+UcZXh/rtbWSwijtJKDpOMx4TsQKg96j+8BURb3WMRAduUKosuKxGjlp8KHZ5CK7a5/1FGaB79y9E8NiA3N7dmLzWIWlRzLsuiBF9+odeMo1z8L0zBQWsv3c7vL4GBuHR8juH6GbpiyzHla0ECFChAgR4smLPXv24E//9E9x55134g/+4A/w9V//9XjRi17E75HsMyld/bf/9t/49/e+970MDl966aX4r//1v7JP8EcLkph+wxvegGc+85ksj0rPIA899BAzhMlTmPyIQ4QIEeLfUhDTl+ZGAnnJ69zH5Zdfjt/5nd+p588QIUKECBGC4glgAKsaaEULJGV2iN7KGjQO0tsOuJ2zxxr0YhFIB2zVdM1zt2s1xcgbjnViXPO2bVdJghL1MZpt2j6tWySmpdnwvr+cEDeSFDW1w51GnhdQSRdLi2s4fvwE7r3nw/jCz/kP2LdvJyeXCSSmP2jIw7VhxVQOQ1cYT3IkaQdJnCBVJANt92x/JvZOHLn2ELuHWDemy2xjQ4lrSrJy20pmAzP/uiTG6LRILSry4xtzgp6YYJHKWOpydWWE62+8Arct34mZuX04fsYB1DrFMB9Db4y4zcxoItYRqU6SxLX9bBQZlPkEnaSPPEtstyb2oznLUkJ1MBzl2Lc3wYlTQ2aGEyjS7RJjN7OftedU9GHyDft5uiQZS0yS7yWxWzvplD0OsYGG9nzIU3Jsz2HM7OfP/cLL0aG+6W7i7rsXMd7oYjxa5AT7JZd3sWf/FRhMz6BUQzz80Ckktn0lNuzlInnspGY9tcfsRxiIkixnmcqyznebenORfBZWrWJGXD1uWkPf1zA0+XJXSOAQ4bbfsGrt3++HrwjdTyRhaX+JtWIWXRTF3NUEAqednvgvVrn9I9cVKdQgsGq3BK2WuPbDAQWekS4sRC99rXXroyFChNgSxKStkhITM8a4GrECAgGUSEnONsdYD2GnOzuvFTzvRUUicsFG1CMIrCPWI03v5B/LaxbJ8Wu7RsQVxvmmnSMjbCJj0DZJe8gJjKTjocA4GrNEbmXnN2FkEgiX2fneFaxokfMl8CzTYwYt05nUtnXMgGmiyHc358/nBHB2JgxasywvFb0QG5M9cBXPn7Su0BoytvPr9NSABCiYqUnnXdi1YRJNMFHriOYr7FqYx/LSMobr67wfAoBH0QYwS8BzIizRyLa9k2MzG6KzoPHcz30RTp19DO9/zy3oFtMsOU3FUDQFFVQkNLDn3s3suShRXSAvWTVBlhTYc2g3nnnjM3DksSO4/Z9vRydPkRRdYePaxx9dufWWdJLtKRUEztu+IYlnulYRr7OM1CKLM0zSMS4+cAGWs2VR+rD9nsVj7q/cvmdmDK596jWYG8zhAx/8AI6dOoPp6QEzmjPbtNxex8puN5xZx0DPoNPtIh/avu4Y9PZ0cP1znoZ9B/fizMwJHHn/gxjY8+1O9Xj8TOxaGs8kKHcVOJUfx7I5y8UAJIld+WcAaqlyfr5KGLSV1942XnVZ1pGy8utT/YbzrZdtuHiuqpyCimrULpTjFVeO4exWCjjGMXv4unUsckBy5farHLvYH0fppjBK5J8NF9Fpx8ZmFjJccZ+SAqdur4/eYBaD0QJfH2UH3OlTyzhy9AQzgK/qTWHHwl48/7kvwfHFY/aZZoiTa6cwv3MOnekEk/EQ6aRkL8CCGOhU8BAWtBAhQoQIEeJJD5J6fvrTn44zZ87g7W9/O79GAC0xdt/2tre5nEnJbOBf+IVfwOnTp9nr981vfjN27tz5Mff/Xd/1Xbz/L/7iL8bKygoDKCQPTSDKD//wDz/RpxciRIgQj0v8n//zf1ja+fjx4/Vrs7Oz+Imf+AmeH2kuDREiRIgQIdrxhKwMDPaqNj7rPXIbgFW2kw00U2HOZd56hgnHdp9UNBhU5RiYW1ibWtXSvd73V3YjHqYNM7nVlhYzUg53fj/iNgNS1S0xLOMMdt9l90YUlBhP+lhaWcfJEydx4uij+JLP/2zs2bXASVOSIqQEKXnfElBLTJ52EECa5RkG3R465ANMksWx/VySIiUZUZYaLZhhmxrn2ciU3ERkh43zOUTCTWS/YFYllvZGUeq2ARITI+euWsB99x7HlVfuZe+8sogY5LVbMNtoY0hssq5jmFauLzWzqlRFSXxi7Ob8WZboJLRB2+1KjWMn1/G0a/faP9aOI6qmkBdDdHoJslMpb375NeR9mOP0iTVcdGgnDj/0GK6++gKk3S7ed8tpe75dqDJm+enROMcjD61j595ZDKZivgJnl3K86x/GyMqDOProGBtrU5ieNehNKUyyCu/752WMh+SbbPtQJ8yO5uQ+Sxy3r2/ZeBW2wufG/bU3rf/74cFAqZGEeNmS4YRjkW+Re952rVX9akuq2VS1/Kh4U7fbKfeTZ2ZREAhMrGoqGBhzpl4YVyJHamrp8roN25j2zevaSZGbet98rQ2acwoRIsQ5QfxeZmtGOSb2XxkXKMwEG0WBlfEKnvGCG3D55VfgH9/zjzh9/CzLPxPDkiT+aT5SzOgvENvXSQaY7rtJOcQmVpFjxD8T97TQGdsDlJlda7oVdu3fDdVPcMfRD+DM8Awik4l/rp3A6auoxKRX5PUdwGf/TZIJirRg4DVPc4zHI/bBJRnpQ1cfwtXXXc5M1zvvuAOPPvwIUju3zM7MY319HRn5wBJIaufmdbOEKfIct+vFyNiWEtu1XEJsxrjw0F5c++wr0Bv0cPbsGfzze29GV5GyRYqMPN2nM7uW2T5ThW3PCEO7NqQLKa550fU4Uj6Mzt4E+Y4c5eY65qfnkW3m3C/MJO7bOW0a2FCb2NSbMHZeL+1Etf/QfjzlGdfggY37sHBwHskxhaUTi7igfyH6cQ8rS8ssyx05ZnZuF8eubR8tCVScRfLCtE7MdGaR2vMrIntl+zkuOXgxji8fxWQ0sb2SYdjZQGdXin37dmP3Rbswu2sWk+EEn/nSF+KxRw9j//xeBt8fePRRHF86iandMygGOY6dOIqRvZY013a6HRy89nLEcxH+f7f+Na697Bo8u3cjZpI57Jnei81shNV8DYOFaUxNzeHo0mPcR5qXV8fU9YAuZHaWpagps5MVTdUe7mzH4Yt9VFU/YtEaYrzShalYPlw0T4yYVwOO+V3VQK4cT56rmFUtuK/48joPemKwi1ILw8RsvyBLUiGFBUpkoqkwQBnfWleQRBeoMJzMyNYVHvzwo1gZLfH+knIFmytDTCYje6+V2Dw15OcjWt/XV8/g9qPr2BivIx2k0Ak9C1CxW4zusI8pM81y5wH/DREiRIgQIT514nM+53NY0pSYuuT5+6Y3vQnz8/P8Hj//2a/rr7+eQV8Ci3/v934PP/iDP/hx7fsFL3gBewuTnPRdd93Fz0Q/8iM/gptvvhl/8id/UnsShwgRIsSnWpCn+Xd8x3ewCkI7vumbvgmvfe1rP65CmBAhQoQI8ekZT4wHMCUkec/CKJTsWsXgmHJJQH53C7hanX9fQkdsvOZ4Ow3vmEtByezG885HI5nrs3vkhciyvbqV7XOSzp6VSbRRSotXLEkolajmPAAzs1uiyB03crKJmrFVOkd+XaU4u7KO02cWcf899+KzX/w8LAzsHxXEzGLJT83gr9YJ8qIUQWzvz+eYmnmWYTCYQt/+MUIeg72OPfNkgESBE/ok5UwZ0rwgxljFkqJVVjELyJCkp5E2VaYUyUs6O5LuJA9cCLhAMppxYduTlJwQHhfA2lqK9dFxdDozyFn+154jaJ89lIRWqJwBZfJUrIwDz6vIsYNyRGJCLO/Rp20/5vZjS0srOHT5AOPhGHFHYzBDwHnGYHSR234pMuycm8bMTIkL9u/E3DRJnw5tu+y1i8gTcsxewaacw/vfcxr5BLjq+nmu4n3H3x7FZHIdS2wuL2q87c/ux4tecrntowJ33PYIHn10Bml3D0tnRzrlsRknHb6O28fj+YD/+jU0vrn+dT9GKqfHqp0Xox8rnhXeji3+0a3vfhwLq0sS4NzGyrjCCi1jzzGWSQqVAF8qpCg5ma4Z8BF2leKEPt03NEalSEDVkultANh/54Q9F2XompW1va0hQoQ4fxBztDPfRZkUmKgRJtGIwSpUGpdcdzEuf/al2Byu44Jr9uHI4hFcdtkVmO7P4uHDh7G8tsRzZWe6w9LBmZ3gxtkEPbu/gxddgt7uAZbGK9isRtiE/bLv75jeh31X7Efc62J69zye+oKn4cjhOzA/SPneX1xexPrmOrp2Tuh3++iwhYCAb91+H3laYmbXDFaKJZTdEsvLy5hKKjz1+qfi2c+7EUdPPcbA9Gd/wUtwx4dux/7d+zC/MI+Ti6fx4IMPY3Z2Hnt278HyaBGbsV3vxmvIUoWRnYcxneDpN1yFZ13/TNx17E68+0Pvxkte+BJ8zue9FFPpFAOfq8UKytkMm3psP2/PKlnDoUOX4ClPfQpMF3jr3/8dXvKcl+KKy65BnEZ4+uVPt2uL2EpMqjFWsxWM7Fo3zOxn+5t2PoxxzaGn4elPuwF3PXY33v3Bf8JLX/zZ+KznvwSj1REO7LgQVV5hYtcgWl9pjWcWKHns9jSyYsIgN3nv0rqsJhrj9dyugxn0lMKuHbuwWWzg0MWXAaOHcdkll+Hyyw/RYoiN4QZu+eAHsHh6ES+68YX2WBdgaXHRTtoJbnzajcgduznXm9hIjuLAlRfgwoWLcMGOA1D2XN9+01/bZ4azONC7CJ/1lM/GgycfwH1H7rXHugK7pvbg1NoZDLrzGOhppBN7HUt7jRG51UU1gCwDuJVTPtHuOUeexXTrecqYhhncttngYh8qwKvkZzo3wmD5eYGeweo1qnJS5Ha9U85SIKqhW7khlGMNU0EbrVcMSoO31ywNLaAxtavU4iVsqEiB65tEnpoh40KKCEdnRzh75gzLitNx04KkvzvoRl2+97LTQ17n6Jg9WhNXx+jb5yG1Is9BKTHtk5793sdAzQgrXrWNN0KECBEiRIgQT3YoZ59C9lOPPPIILrroIqytreHAgQMs+/wDP/ADeP3rX4+XvexlnAf4RII8MW+55RZ85Vd+Jf7qr/6KX6PvN954I/7mb/6GjxEiRIgQnyqxtLSEV7/61fjd3/3dmpxBQdL5P/dzP4dv+IZvePIaFyJEiBAh/k3E4w4AM4k0EjYJ+5NSYo8B0UJkiSnRWIrkIgGFtc8bHPBmPINY10Cc+M7Znyth83qp3UassAG0GnBZCwMG4pPLvnMu2Vlt913VFQPDHgRmL19ivRCbVXQOuY0CFDIdhT0KKyddTZ57jPslJJlo3ysVpmamMZyMsba6hFPHjuC5n/F07Nu/k+WalfcMJvZOrNhPT6mu21/EoB0lMJOkwnicY2FhD7N+YkqMmgI9OsVuFxEBmZVhmc5El8IkMxp5x4iPHrE4K8mf1j61se3LSnPylXuHfCVpGNhrllSpvBYlOLlc2POcd16LMV+DJO4zq1Xg0qQFbLpOjdx1NMJINTHrQ9fXisbDseMTzO9I+VoS8+vY8RV7vGmUE/Lisedhj5VEGY6vFQxXHz9tMM4NCjJd5PNIOGmc05gyc3jPzRn++dbTwnDWVzHbmS7tJOpgstzFW9+6zBLYUXyh/RqAuUiJMLzI0FKjkcGkvuPks5GCBB6jPinukuv0HhUykB+ll41u2MICmFJxQkyA9njIoAKNFe2ky88HuLoGcBJaOFMSnLznPhS5TR7TYPtPPg4Nx9hJNtO4I8nnKFLMFK/s8TtpH5PROjOavfciXQO6D2lMcB1E5Zj5NUvMiI8wFzagrW/NY7NSTNHyop8hQoTYFiQB/OXXfAUGsx0kAzvZdA3mZ+Zx5cVX4sqnXY533v33OH78FF7ynM/Gf/qar0CadJkB/JQbr8H6+gZ79y7M7OAinWpcYWO0id58B+UgR9HLsTnZwMyeBehsiEuuuhTPue4FGE0q3Hn4bhTHDA5dvh+XXfGZyPNlrA/HuHpwNRf/lFS04+YgkmamQo+1lSHQidGf6TMQR6wIrEfYN3XAtj3C/7vzHbjvznuR2nn3+Z/xfBy85CAeO/ooPnjfB3H5ZVfixS94EZZHyzizdhKDvT1cuPdiLGWruPjg5Zjv78JCd5YMBnDX4Q/j/bfdihW77S2334prLr0aDzz8EAPeF9j2Xjx3AJkqccm1l+KpV3Vw5b5DWLLvved9N6NcsuvGPUt4/nOfhxV9Eu+97WakOkWv08PK+gouOngh1ifr6PRSvOBznosu+rigdxB33X8fbr3tg+hmfdx589146iVPxUxnGu9++J9w4vhxXHbgUnTsPDnJJuhSgZXth7PrZ7G+uoqFuXksrSwhn9gLM9TI1ksu6ImmFC677lKMoxEuu+AyXHngSmyUG/jQ/R/CI0cOY7Rs17DN1C6nHbznr6kyu0RR5Bjb9W1u4X70Zgfo2fVv54Wz9hlhgCuffyVWV9aRDye47f13YPWxdfTMNB74p0ewdNs6To9O8Ji454MPw3Q1RnmGnbN7cdW+a9FZ6SGeJCw3rr31hvGFS40SC0kqm1ruuSlWovBFa0VlWoor3vdY87rCoK4WD2rjLQK0k3lWprYm4GOoVsEQPUtFmiWcqe8qLq0zkBUSvF4p9r920tFlbp8ZetIWOhct25H0syJva+2QZHtP9JPEPpspe+/E/LyVVAmD+caOobKjUSSiQGLIrsJE/OwWFfZ8SHZdxejlsxhEVFg3zf7FBBwHVYsQIUKECBHiUyvoWYTknbnQ+x3vwHve8x72u3z5y1+Od7/73fze13zN13xMD+DzBTF9//Iv/5Lln3/8x3+cn1+IEUzM4re+9a3yTBwiRIgQT2LQ3+u/+Zu/iR/7sR/jIm0fif1biCTtSSFhMBg8iS0MESJEiBD/VuJxB4DFm1cgrMpJ4YrkZNQwDmu53GqrzDM8+7Jhl5yPlblFIhfbgDSgBQZHzDpRrYTn+Rid3ne1zXL0IK2XztWmDTB7aUJKWpa1JG7EidYSab+HmfkdOH1qEUcfPYzp6Q4OXXLAgeCaF3L5jHanorjPPFOnHaMiw4zdXxqRb6ESQDBOCOZkIHqwsAPVCOxlN8o2MT0zwNIy+d8WmOTktRvz8ZpKsaqWgJTvDmCv2cyamcVRmtSSkOLl5ySddSMh2Y7twCb3VQ1qOvY292cPZ5ciZkQx0GrsuRBATKxU8srUxATuIso5RYyIQFjyObTvcYKXQeeIWTsFJXYJlLbXJk7oWPZcqa0Eqqux7dKObe+M/bzdf0yAujC9YlVgulPhqU+fxaMnRnabid0vMYJLkUatGrlw+UEJi6l1zqbF7m2fs+9jSZD7Pt82ts7D/K29pt2Yax3onH72yfnIyXoTUziOnCczWVlSUhwpM9vGxrSKKXQ91gXMRp3w92Ob5Tfp+lamPnSbLVwfPwDAIUKcN2j521xctvfJAJftuxyXftFldm1IsHJqGe9817vw6PGjKCcKH/j7D+KySy7Hg488iNXVFVyw7wCmZ6extrmGyZiKenriT2/nkXE5wtAMWWJ4YdcCnv+UFwJXVcxOPbu+jI1FhU4+hSP3PIDDt96DpDtBVqwwK3bQ72NmMMXz0Wg0RFEWNSA4HE7Qn57BviN7oFOFi/cdxHq+icOHH8TRo8dwZukMpvIZEnzAB/7uVp5nSKmBAOSlBxdx1/Tt7A2/Wti1xn7+hhtuwGY1tPPrFAadPu659y6cPHYC2VKF1PSwQyc4e+cy3vPhf7b7yXkNW35kCcc+dBTdizt4+jXXY7I0wt/9v7/H0pllFHZt22V2Yum+0/ins/+AYbSKpbPLDAoSqFfYeezM4SVE3Zh9j6644iAeO3EUtz52N0bLBfrZLAaYBzaADz92P6/b5E9MahqPnDrKayoUnG9txSxXmtvG2hUV0RpjYkyhx3NisZLjyE1HsZGs4eTUafTTKYyzMVZW16BzhRnMIc1T6MKpSrjiMgI+C9sHG0vrWD9a4dRdJxHtVDg8dxTLp1ZRbNgtMmBB2+uQ2xZkMdbObqKT9tCPppGvkNy1Rp9UQ84YPPTQo/bhILazfJcLpVA6WwstPvX8o1H1GkxyyP4ZQLcsA9o2HDKrK5n3aa1gn3lZJ2hdJeWQSVygjHJoKnYrMrgaP7tuV8iiiX0u6djz7yC2473MKt5NMhVjWA7tNlxdZ9ctjdw+Kw3inn12KTEeZuhqu1YXkWMpg72xad0tCBSmz8VSuGU6Brv2ztsxt4mzq4tYyzbQ7dprYx+Lrrrqapw8e5LB/YUdCzhw8ABOr51if+uH7XNYV3Wxa2ovkqyDjSObyKrMSVVHiE0n+ACHCBEiRIgQn4JBDGD/9Uu/9Eu47777cOWVV+IzP/MzmcVLAPC/Jn70R38Uz3rWs/DlX/7l7Am8uLiIz/qsz2Kgmbw0Q4QIEeLJCJJ5fsUrXoF77713y+sveclLGBS+/PLLn6SWhQgRIkSIf4vxBEhAE+AqTFkGyZQHkjzzhLOq55GUdSxLJx1oWpLONaDoQFlhaDr2qdoKRTVApGEmLyc/oc8LAG8PY5x/nvP4bX9GwFldJwkrNtOFa4NioJJTqFphYX4XVtc3sbq6itj+fuMNT+ekLCWsBTdsADlTNQdnAo2TaTTsumdfzgp0kg6QJtiYZOjPTENNd5CVBuPlIXv/9lLys1UYl5oZxVTRWpQTx+Apa6lq35dlmddgbw3C+/4l0JzYw9JKuYaujZ7n6vfHICG9rkwNiPLZaV3vu2HUliIBqStEZWSHAPlixqi4T4hR3XEM8DGimHi6GTNhiRmdVjGzWIlNRG33hFtmZHtPWgLHbdsTAjBVIgA+gaFRxYBwHHXtMYjVaz9QlJid7eKiQ32s5xMBais37tiL2Y8XP1YcQ9b59LJHMLZKI2+9BUSq2eG5brx4CfPtBQutogYP/hp/OOVebpymvfC0sNkZ/UVZFMjzHFk2QadLLO7KMdZjYW+XuQONG/BYu0IEvy9fdFFfaLpnnLxnXaTg3z5PAUCIECEkHnrgQfzFX7wF6XQPVz71alx80UHcde89WD+1ijRLMIMddjpUGK5McPvDd/JNTQU+J5dP4YQ6yfUmPKeV67VML819BISdOHECj+pH8fCOR5AVGxhvZphLD+CaCz/D7ncBsxszOLO0AvTtPW4STEUDmPUKK9UqM//Zrxcd+IlmBn3kwxJHF4+jiHI8FB+280mJ2H6WPHrniwUkZYdZkqaoeN2LY/GMLUeF/SrR1QPb3nn78wT3/uP9UKl42hMblbxWU5WiU3TtvN/h+ZUVCIjyDLcGZRWylRwrZ0/inff8A8k78L6TcoApdBFXdj63a9vmo2t2nTPYFe8SxYSS/JbtDLUIVupYPraCWx76ICty0LH6po+oSMT6AaJEwQVJZcUFTbI2OSUM99xBq7hx3nJULFRWMkdqV0TD615ukHRSFPbcRyQLHaWYy3dBFcb2hT1eKWolyrabJDjoX6RKJPb69aIeyqxEOSlRjDOsHt1AghQprd123SGwOaJ5vRQGbFna54xCgeBJQ6Cyfa9koDSxfUggOA2QnNm1EbNvS16LCdClgUQexxUVNrEiStkUsSk5p7r4jVRHKu83b6+SK9jyCw7bCHQVrrjuEAZ7OpjoDbsVeTxniAddoKPt2r6JXdFuVBsaFwwO4Kb3/DNOLJ7ADS9+Oub3zHJhwOL6ou0H20d5hP3Te/HQ7Q/hwzfdjcSeN72ueG2lMS/nai+U+A7TmLIPO3rG4IrnXsbXaH1zA8dOHMee/Xtx6uxpXPfipyG6J8ZDiw/i0CWX4urnX4UdozlkvQx7qp0YrU8Qb3SRnyix+OhpO5ZEpp1Yy1FFBwkAcIgQIUKECPGpGnNzc/if//N/MiByzTXX4P3vfz9+4zd+43HZ90tf+lLceuut/P3IkSNsm0Qy03QMklxN0/RxOU6IECFCfKw4evQovu/7vo89ydtx6NAhLkz5oi/6oiepZSFChAgR4t9yPGEewB6Y9QlHxh+VAE/isdvy7PUAsXzbIleoVMO2ZIC0zQLWyuXs1BampAfmSHawTu8KlubeQ+u4LZjPJd7ZJ5X86Kqy9gv2IJw7gICj7kOVg61LJBhMT/O262sbOHHiMTz/2c+UxLvdlKSe6VSiWBLPkQPdVP1/By47EJD6aFLkKCKN1TLD/AV7UGiD4eJZJAsLGFx2IRZPLGEw2eSkNpIKa5srcr46Fj4PM6/LFuPX+77KNSAQkHBArYSvyn6zOnWgrhHwV7XYQmIWKD+7BLIg5+eyrBnwZjnowskrG5aZJvnpXMmYiExiP1AgI6bVOEJs/8CamJwHZhnFKCpyKjYs2TzJJ/bzU/Z4BTO1lAe2dZesmwWcrwTFV5Rk1iI9qY1Ia0eK2MXk+zuFtaHB4SMplpYSzM2724AZyXoLuCk/euTWFSM48HfLWEIb2BWJ8pJkJVV7R2rbtg2jVooOXOHDFj9HtXUMtr8a92oBClwxAkk4x3HprkHCsuokz218hYNncbvmELhEmX6+JyvlJMNdwUDlmPd8vEhAlMogAMAhQpw/iOk6WN+BcljhkY3HcOKOM3buiTATzaFTpIgLmRcHxGC1ky8DjsSWpIIWLfNpBVGwIFCQggCqPC/Yu7ZAzl62Uceup8MIU3MDdDdidOx82ctSDAhszchyuE/IKE/TMkVrZidLUUfF8zffxrTmFSXycsKAIas9FIpZywRmEvVSPMFdkU8mqgMRqTY4iWHyX63sfFeoiZ0nSt4/gYqJ7qDI7DpqUvZ5pzOjOYbWQgqeVew+Uiqi2tQo1guWsI/J2bYiUDC1bYh5uy7PuwTAgoFsWrv8A4yORWGkLDYRRx2UuT02rS1cbCRrNTNJFetKMNArgG4pTFf3jED9Q1YK1Hbj5PH5mYXWFWYHR9x/nVHXrkuyBlFfsa0FL8H0uyucibzzu2apY36uYdxb8bXoJj103XzKtroQ0JaVPpzVQMVy+xI0j5OaCkkYp0kHRKA29rmAQHnmL1PfkK0Bz+eVe+7RrOjACiWR/E7nzOuGrtxa7grZ+Fmt+VnAYbj1FMwG3ntgJy58ygW4++RtOLZ8FAt7Z5F3x1A9u05nGuvDZRw9dgyXXHsAyZEKyysnkM+son/RHHI7DpYfPo7rLr4eo+UxHnz4Hjx4+EF7DnZd1wN6fLHPOobXu6rIaNSz53NpO5YkmhO+5hniDmzf9bE+XsHCnhlcevmFGGarfPF27Z7DFTdcjkmcwfQNg8dxV7HU8/ScfTZbi/CofS7Lswmm+307hm1/0oXUQQI6RIgQIUKE+FQPUpp5+9vfjptuugmvetWrGBB5vIJYxbfddhszgd/5znfya2984xtx99138zGJgRwiRIgQT1RMJhP8/M//PHv6DofD+vWpqSn88A//MIPCJP0cIkSIECFC/EviiQGAjQBgnLE0ngXavOdxsI/Eyj2fNPM5eFNLnpl/dZ/zstE1E1iJn2sDzYk3niTWPdIq71aqOZZyQDRJKFMCl/1nnfOpsGnF064tUT0uKsRJiuOnTmH57Fns3jWHXl8YmR5QI1leQeS8pHVL7trLYbfOdTIcYW1lGb3eAlaGBTNk+t0uVLaCzdV1BoInaRdmeQ1dLQltz0r23q7S/+zC22K2ukSwEmDWIc78XlU5UJez1ZrbVYOdxieNHUPZAaHiHduApw1AypxhJ8VNkp3cCuhqABNXyAmcnj+A+cGFWH3gCNJKo1Ol9hMFJlrYQCStTSn6ju7Z/Yy5TZzjJulGHTELiv2OI8W/M2gZE5CR2C9j+5xeJ3aVeB+TZPTyRoFbbh6h0+1jfk7AC/Ff1gx412PQdddWiedzx237vD1gW0ttG88cbvrEj7NzWcTn/3lLwUSLmVyxX6IDbJndXTL714mA2ofEFBm/VvK2Sgujl4obahY436bS10Sro6pnf35ybV07tQAlOoC/IUJ8xIiLBFPjBUS9CF100GEA076ex/Y9jRSJnffIPgD8M80XXGxEc3Ipd25pCnev0tojbFWGHGmOt//69P7EYGNziJmpWfTyHuLMfn6zRFoSaFqhYKBPvNcpRHGiqpUztFsvuejFzpcxz9NiB6BKe5+XEfvDU0ESrQRlKaA0uHgpkUol/tlun4lkcELv5wUva7z+2K+46vA+adaoKi3M08qXuXiVD4V+OS1FWMoBtPQvt32TV0iihGV+86rg5ZP7023DGDYB1XRuUYf2hsTQPmKWcDZcDMY6xtyukhjBNMUp1EAwBVtGsLJFJSxlqoxiUNjN3yJJIWAve81LxxBrloF8+0VKHIKWGiaw8nMDWUOUwrilc4vh7BWcRDKB71p51Qy/9nJncd9KyELE14z2ZY8Z2+vG7r/M7KZiqIyLdLjoyRVrGff85RUgZFdazsNUDSNY/quVICKnSCGFSXQ8w+v92voG7n7wHuTd0j7rkCrJiCXEV8fr2N/dzeoeu/bvwyifYH2yCd2J0OsOMNoYYTgZYtCfxtETx1Ct2f3TtZ3Y66g7zPalMaCUPJJSARqvY5WA7KaKmAE9Wh/h3jseQhInuOueDyNJ7TicxDh1bBEfVvewCkY36+DUoyfwUHwfTq2fQDprnyZ0jnJo2zxMsfTQmn2WGNhL5J7tmBlePiFzQYgQIUKECBHi8Q0CQz7ncz7nCdk3sYzJa5jAZZKbpiBm8HXXXccgMH3/l8Q/Hns8WxkiRIh/TTxvH+zfrE92K7bGn//5n+N7v/d7cfjw4S2v/+f//J/xC7/wC9i3b9+T1LIQIUKECPHvJZ4QAJjCOGleSShWjpFrmJ3IwJWTUGYZXzi2jZe63ULRbZKV/tXKSTQrTnA7GcNtx2+kjZWTNWzYyKg/0cgteyYrgV+ciKXUKrdVO/ajZxlzGpslJwlgBAQsLlXBzNUi0xgPC4xH67jxmc9EZKSFZQ0WGwHiCGxkAK9guUNhWMnrmtm6BNApDDeHuO/+O3D29GksdGexY24W45l5dLodTGU9TDbGUHt3wSzMoFjLmEUT69zJTjqJZJJ3pJ6Kq1r+kpL7uT0/2iQmaU9MUJXanpdiphD1N0lMSrLbEX8pa15p9vKLCTiwP+eMVtjjteS6KdjnWDEXDDTMyF+XrXVL8vRNYApi+WqMFhawY98Cjt7xIJ6xcRHmlwYM1upkhAd3HsVmuom0SqAnM/Z8Mqx3SpTxqm13avuc/BlLRHHcJLmp/8gHMaZEe0HKlPb6S1vousb2e67Fc7BMUnucyuGpjivuwF7qEWZkKQ/s8qiCCGNHApKycnS1BcCVIgTBAKpSCQOX0QbH9nby0LUnc0uGtO47Zpg3wE1b/rxmA6MBfatWn0dM5wYzuPr9PlayCQubwrHAI1dgQAy8iOWhqf1VXfAwKSYOKJJ7j4shIu2KE4wDb6q6bSFChNgWJM1bpEiKmKWPiRlJqwzNd5FxlgWuCIjXmrJ0BRbMsRcQ0M0hdT2QEX94mpNi8j8v7HyRa8xEPVyw62KkqsPFHrt378KjJ9ZBPGGtunZvuRM3lvBzBXurGwGYZS0lm9VY5PCJ/Wu8dL/MC2RlwMVL1L6ighelpynIF5EwnEuTPJu1GrekOpCXAG43X/Ec7eYYL9/PzwY0zysnzcwHhnQAyU2zNLBir3jlCmdIQUNqlyphOoNIran7WCRN4H0ZBkilQyHyym7JbxdcScGUqCFoL49gmnlOpl7NfVsD18wgVlJEFRl+DqDvPL8Xsm+6qgxg01xrNAP9XG/FCwFd75wLk6S9iseGyDQbbgcV70SRHC9nVjJds5jPo6rseOA1Rkwj+Hy5TZFbZ2SsiV2Dt+bwaiNauhfSR77Ix7jnD+4WAsXpNKiIyI7nxx48hfHhTfQXUjuyDMYYIU+GqDrA2fxRdKl4q4yxesddOH1khCRfwP3/fMLuwz4TVYz2YunUUXTKLrr2KxrNCNNd9eVZsVTwqhemFhfRPDbMRPE9dOzONR4vfb2PvakffJ9tU1Zi5eEHue0JPXPZfT905Diz5TM9QhUViElmelSga+aAZGA7J7Z9Nw0qw5C+CREiRIgQIUJ8ugc9g/3iL/4ibrzxRnz91389s/LIguXZz342/uAP/gBf9VVf9WQ3MUSIEP9O4oEHHsArX/lKvOtd79ryOhWbvO51r+N5J0SIECFChHg84gkDgIX96JPYjZ8uAZ5tQLZmNroEaNWStVUuQUnJR/50iznLco9g9cqWhLJso2rJXCPJUOPBN5EIbpjB3Ar3YyMTzfvg75V7oQUa16wZ5RKrZClrHFQdY2N1HRvrq9izayeDbdxOAyeJLWlaSZg3ks/C0pHj1Ixax+bcHC3j3g8/iK7u4cDCXhy4cB927rgIgx3z6M3MYGowh2hcQC8MMLN7N7JMY7S5yaxZ3iVTt3JuC0liapIbjUpUHQIpSFq0wpjYsiYRSc/Ks5yp3TH7B4KT1uQ3WzCQG9n2EghsWKc5I+SAJS65y7R2MtIetFfMHpL+r5iZVakcZdKB3rUXA/vZpfsewl61A+lI44LJvN1wgmEhMqAmNRglE/RNhrTsINFDIOkzg5uSukk+Z7fPtvjbipS3SGnSNYq0yHZWipjDMVRceS63I4CbGmswzj/XJ/5rNjsaBrX3Umy/5kMABXfdS1eEECkBi50Up28rHEm+bDHha/a2Y1g3o6QpjODx4YACQXMNA7mj8QSdXp+Bei6sIMnthEDeyI6LjAEcOhdhyTfs48p5Xsq4k5EubD/nDeyPW7lOUu1WhQgRYkvQ7a4LFAzkpnbOEg9zOHnd3BQsa0tTM8vkkyoBr1PCsBWpYlrfMpCfOc2zGuIRT4VTPJ0SI7PUeNrTbsBVV1yB2z50H2bsenDds6/E5vtXcfTEGnufA17a1q2bgp6ywzrvJpI5kUWnuQjEqRfwkkcSxDS/yLYiSyw+sZ4pyvLSiopyZDqidtJ8x3LHSoBXLpKpaA2SAhLDoLR2JTcCdsb2M6XxKhxVoxRC/RBTXzGFVli1kDKckp4WSgdGG+WKdoTVSUAx9T97Dbup0u0O3vO89vQ1TXGW+KMrZu0yENwqbOJ1X0lRT2Gvr1cCkbMoBfh1yif0aQLljbzdPHP4GjL3rENSFlSs5PuitGssfYSfHcib1oHUspbYNTxOkWfEiE0YWKYDkMc7sX+jOOE+JoC6lM50a7dhVnBZKQaSZW1ulCeKsvKC0e7CG6E7c5dIXxgqbisKnH5gHZn92VSbSOk5Rtm1hSSaSTXckDa4bUeuWca7G+9Ex/bz8RMjeXaia1KUSCPycI4xzCukyQwXFIwZoLcH5GIJVxSg3Lnb55TMDuOECpGIBz+JapUWpaXAMLXjy7OVbUfYUZCyVDh9OIrteNPCjtZFx461ATKSzk7oGWHAhRLlNouGECFChAgRIsSndxDQe9VVV+HzPu/zGAAmIPirv/qr2ReYGHmNMleIECFCfGKxvr6On/iJn8D/+B//Azn5+rggqfmf+ZmfYa/z7SqZIUKECBEixL8mHn8A2DQAk8sgOpC3AWjRArnkI420rqlhL8fsdUCyyDibGhz2wDGBpB74E0iuQmw8E7MFrBnPaGwzOj2o5sHfJsEd+dd9uxzw60N5VjIxjUpKzEcYDTOMR2Nm63Yv2CmMHxW1SESKf+bPVnDSzKZ+z5+XOwCfWzYZISY2zmgNywTiYYSV06cwWNiJnfsuxGBqjiUYpzdnMDxlj7trD3qzM9CJZqZvGkW2P2yvFgXyzTGy0QQJSUca50Vs990lb1wCcu1rse2zgjKu9nOJPa8ijogbDKNT26YUY5PZS1gxgzTNDCICimN7DQruBD7fimlh4AS0FuNmd64KRRIx8wa7dkL1UowePoKFtMI4Uzh6wQlkg3VsTNN5VlibPmV7pYdOZI89tYm1cowysdcmTpGMEnRL20cpNTpxiXtXEOCKAlhWM4JjxEq3xtQG0f50EqWQ5D2ESVt7R7eYX4IawL3mmFplUbOmtgcDys53UjtAXCjxcrz6GtOuKwEVKnfNm/sAtfxy1LpXthyHWd5yj1AT6Q9TONZ75cZrEsfISf46Emlr7gP7WlX5+6y5P6rKOFYxkGUFe4zEsZMl9f6fXAPRsI5DhAixLehmTEoGYMk3lRUjeC0wjK9VglfyfVeQZyvxOSNBNhmQrFrS+ZB1qVAeQJR7nv1c7c+33Xkr7vjwbchLqbZ6351O0p8AYiMqAjIXiPKDtM+te07UovBgoBEmq5B3/VpleE6R1+yrsTCYa89xVssg5qvitSSJYrExdmoWBNgWpnSSxO7wSiZpFbliGoFCWc7Yg3jK+8vDg8KuTQYORDYNCOgqaaRdVS1pDG/n4E7ag8BwBUmeF610M7/y80RdmNXytZdOq+f8guWhK1ZaUKyIAFdo5ryVXaGNdDLqfRjWFjGuIEkx4G6ERl2DslRgpcSIXa5brPm8KpYDp85NuKinzFPktO6Wsp+45Go5uzY7FnUJJxct7SudPYZmuWiZzyPvnVwZv2jC1z+1i5HIeoKKw7r2enYISqUhnjvgnQD/JOLnBjpVWjMUgc2VrpcNVgMhxZYkYgdmPnwkBQF5lHORQGEKpFSgxeuhcKz52vDxuqI+wc1MXDGeETa6bUanHs8VhlQaEHXYN5tGp07pGaXgIqkC9Dxjnx8UlZfZ8UqGwvzQ0CReQoQIESJEiBAhKIiFd/vttzMITFLQFL/8y7/MXsF/9md/xpLRIUKECPHxBv3d9fu///t49atfjVOnTtWvU37u27/92/GTP/mTmJ2dfRJbGCJEiBAh/r3GE8QA9mwKD9561qITWzYuOVyDsW4jyVjXjMtanrDF0GlH2xdVmDylAG4uwauVr8x0/BojnrYCytW8ylpq0GWHHfNY+yyoA3+r5sx040msXCKaEvCbmyOu5jpz6gT27Z3hhDElipnV5ZikzGhxAKHW3rPYJWR1m/0syewys8d24Go3SVmocGO0gsnJTSyfOo7BwgLm9+7HzI5dmO/vBFbGGPdidGf6zC5L0g4zYMGgthZWbamRTPWgd85gPMkxOruMKdOxm0hymxhOxJBZHWjs3LsLfdtfa2tjTLIxlCFp0wrT01PIoxgrDz6K2QIo9ESuW82uJi/J2F6LUmQs3fUjL7/eVZdhY3kROP4YdiQahZliqeZ+1UPUnULRP2b3nTEITczkPCqYDaW6EYPXlFjuF/OYHs9jefY0JnqT+5JBEe2Yq8R8Iv9mYlFFwoSaW53HIE+wOLWMvDsWIEC1pR+3FgfUrzoGV+US98aVIrTQhS1jWXlvypI8KT2b3LtVNneHyCz7611tGd7tJrQLJdqe0zX7zDS+w8wzJ1Zh4YsfNIP1eV5gNN5EmqbMwmeJbh3zGNEsFW6vQ57x6/QAGkVb+8W4m4SS6AH6DRHiowQXbhTiQU6/EzlU4Cye+wkAJBlnZ6LOksAEmCknDYxKFAyUnfsKJnLae7OWu5BiJb7d7dxKQDOVtCSJY+UzqTRyBS8GIpqrHYMX8MVOHpisHNjL/xzAZhxQyPMds461A41ln9zAWOwLlPLqCSQRLaoNitUOHGOXJaBp/UnAmKl2PsLKK3GYulhFOcDRy90zIM2f9jL7woT1rYADmZuVXNQmqIdpniqdyoZ2ks6xEUCdAEcBEOE60jQ4rSv24b17oQNXvOMl9xmUJOCWfJIrUZrggrFSQGxi9ZL/csnqEwJGs6WCV2xwxWMxrY9eBaXSNbgNt3aA7QrsSCJ/ei02GVzdZOft3K7haTqNfjJgRjVBmzGB/mQpQRVwpWE1Zbp0MROFSy4cUK5vyWOaT5+UNPyziStQovNmH2Gt4ZnjZLdRQ+ZGShNYAIT+0bOLPVgnFwlxYpWTZDcvb7R/u/4ksTDbHe9cxnopjGClUvsZUiGJ3RrpC/KM2wcBxTEXNvGvdM21ceunHw1NcVZClgt2vUvLLldbFBldlZL9o8kYwpG0nS2E/QyxuXXeVImFCBEiRIgQIUK4IEbeTTfdxIy8N77xjfzaO9/5Tlx//fX427/9W1x55ZX1tisrK/jSL/1SPPLII/jf//t/48UvfvGT1OoQIUJ8qgUVkXzLt3xLXUzi40UvehF+67d+ixUHQoQIESJEiCcqHn8AmJOmlWPLoEmmMgDsQF3PntXC5JFEuEtCG5cARbNtvWufnN7ugwo0yUrjScam9mdtpG7NFglcaRd/um68b5uwHhu/vIaFLFLPJMEbeSaP3XacFciLAkvLi1jbXBHWjktwG5amdPLOpUgrmqqRoGRvRZZhrFx+2CU67bb5ZAxBBJQDooFO1AGlXqtqjOUzx7G6uIjZ6Tksze9Ef2E3ZhcWMLUxg/5gGlU3Q9JJEaUpS0Ty/u2+suEQ48c2EM8MMHVgJ6rVESbZRBhQOkJ3agG7ex2snjmFcn0TnTJCp/JSkgWy5VVk/T72HjqExSNHkUzERY8TxboUxhudtWd+ESPJ7ndq/35sLJ5FYvfZVQmqmPpDAG5ilW1WQyT5LPJonWWnE9O3vZ0jzu3nC2HU5UkO05nYVzeIDMX+ip4BLIrFBjrxMqWKXyfeUUlym+RzrJ13L18eX4jgwe/IMbsFvGjeQ83+Kh0DVhhp50kam6bQQTsAQSSXhUEWucFH15sT2TUAori/vPyzH+OCVVStMSzjNuLfFTP4xkUOPclQ5PZ7LNsVeVkzzWVfEXI7Tol1R0CB1q6IosVWU4557gsrylL4agSowPlwMwTUYjGHCBGiHfYuIYvwmAX/EeuY2Y9CstRc7OEVdqkoh+a5+j51NTRCxPcyy3b2Uq21igsx5DDaA3eVAG+87la5U1yAA3ad9yvgoV633kqwkH3tf9vIO2unxuFBQw/W8paRrIF+TiBAlFnMlayZJCvNKhbGyUJzYZawepX0gJ1b7LweR9xunv+cn3ANhNf1NdqpNSjph0a8oAFFXbcrV2hTuflRM0CsGSsnxrQ8GpgaSPcTmvEHdN+4JKdq5kHli8gg8tEM6Csp4tKsdu1tIAzLKGv3/MEzN137qmoKgWrEmpFyx3g2bj0SYJOfYXhBNTzHE5tcgO3cfpE3sJ3L8xGvxVoROziza17Eayi/r+SLfYkZ5af1MZHrXU1gl0ye20mKmZtiZL2W86N+dR73EJZtzJUFtk9yXwZV1edQ6Upq9/zY1YrbRedBPvN0HiWN8YjYzySdTZ6+kRQGOI9iGY/Cj/brrZfS1h6EdustFUTwmsXPmeAx5J/D6PkgVRP2m46jkvs2VvJslXIxGBVHZHbIxGBbZWb+Fm6shwgRIkSIECFCnBtUQP2GN7wBz3rWs/A93/M9bItx5MgRPOMZz2Am8Etf+lLe7hu+4Rvwj//4j/zzr/7qrwYAOESIEDh79ixe9apXMfO3nTs8ePAgfumXfglf9mVf9iS2LkSIECFCfLrEEyABzTlNYVYYYd2K/y0YAGYPQn6fspviodp47HpQV37yoJsHvSjaDEjPSqTwoFUbMPYSjn5b7dk+kAS6gqdStSR5mZ2EGvjjfXuZ3sq11zF12TuVWhhHyNZLDIcj5KMREqF3coKxZA8+XSd4KTmqOEEqiXbl2EHM0IUXw3Qym3mBLHf+fKpJzFPjjZMEjZUwptc3lrC2uYT07FHMzu/Cjl37MJheQH8wY7/PotsfoEhS9Lo9ZuEonWBA7VneRLU2xnpq0B30oeMuqtEE64vLmC4NpjlZnjB7yTiGjLJ/BJG1ZGczw+rDh7H74MVYfPQY9HjCEqckRZmTLDNJENs+yqnvVIzevv1YWT6LdJyBeEtMLFMJ93Oh7XH1KqK8g6s3L8Lqxgo2ywJJX2Ojs4Yr9GUwoyHumjkG060wHNhjTdN5VOw5GRHiEvft7xO+pPZoMGwCSGyhkq9x1t/EYq9EocYM0Mg48szaZswoB2wYp9XqMWztZJK1Z/vCM3OBho2r6+KBNInQob6ykeeZHM8NdAZ/3Fii7RmIjUXaUjnwoh7D8F7Kmj1CSGLTF1lULA0qfpt5kTPYQ6ASs8ac7GbS6WJlYw3HTi5hyo6DCRUVqBK9TsrgiWZ2XsWJeg90RJ5QaMTPs3IFCgVLrkfsGxkiRIhzg0BH8hUlZqMhiVvt5mtSfSDw0M6FeTFxShJOCtjJ1ivnAUx3vPHrkCmdDK9xnqdubeQ11K1tUeRWK+WKbWQN4TmBoDbH6JciFAcKE4Dp1lDjmb1uF77KRMDiXNZFMLlV1j5ab93aLatq6eYqQQJLI/K+1F72sTVFPdfSYdhvnt6wn/NS/MTybMBYtNZsoR+TxLB2+v7aSSb7bXxRTGHqE5D2OUy3IhDSK4O468BSzkXhmKBONtk0PujS9/yjHNs9X1RF6Y4r/ZyrUti7WtaLygHNkTu4L+zRzndYAGjNzxW0XnD7jCv8MSKzzesOgZj8iNLlfkI84eem4WaO1C5gaWfTfn7Nvk9tK6UQgD9L15YYviP7fWT7JLZDqG/b3Xdg+brd2zrLMSdqxu4jcdevEhY2yf4zg7dyTO2KC/NEqcSfe1T3eWIcizt1zHVXpMDjh3yBYzl/ugeKMpexZReYOI15LJZF6QoMqG1FXdTnn+XkWldOzSJnewj6uXKALvVr4djofE/RJYtpTzmPUzmcZrsF3/8xF41FSPUcUlaj0airCkKECBEiRIgQIc4T3/md38my0MTyXVxcxObmJstDv+Y1r+Fc1F/8xV/U277rXe96ElsaIkSIJzvo70zy+CWv37W1tfr1fr+PH/zBH+SvTqfzJLYwRIgQIUJ8OsUTIgFNzI/SCCAmScLKebk50EzDsRnRyAZD8n/e05eCEriV8y2tGbheorD2s/MS0bJPWmj9602SmPfAe/RMTEk4ns+HGPXvbQ9Av60HYSkRGtv9Z0WOSVlhkmVYWVlCTB53zniWP1oyb4dBSe399QhMq3xyX5KnteyhqeB5L5R0LssRGG1VTh6xKoUZ5NByxfvIGaSlHi4mE5w9fRJrq2uYmpnDwo6dmJ5bwNT0vP19FtlkiE5vCkQ6piQsM5wqjdlJhXIyYpAvsf0zzenr0qlga2aqcoK51CylyMlwe53pkWXpxHHM7N2F9aPH0CklIU6+wyWDGzFLceqZaQYje5OCE8acYPeymzF5/CmUcYR00sH8msIc9oIEVNe7q3hA5UgX7cOSPR/TOQvNzB4BsbU9h4SBzgqdyvZRGZMhIEpVCkObx4ljriYTZNTxhe1dew4Fja2o27r+jpnLrFhVS0zWUs2OWc7jwns0yuCox41nldE73V6XgY440vbngYwH48Yrs8EFxKW207itxxoz0J1HYxQ5SruMp8jLhnpGmxEJTmFc5wwQE6BL45Q8fMuqA10QWNDBjL3+pX1/c3NoP1fYbYXNZqqJeGfado7t+KE2jzY3uE3EKB6NJsyyon0Q0JTZazh6fvaJTgshQnxahL+PeY70dgFGXifwUJScG9UJ/n9d4eRZu5CyD63rOcevQcbLECtVF6Go9lqGmqsqCgz1587fTs/69+tm+z2gkZ3n3yoH8ioH6tVFVo2tgnYeuH7OlAIwU8v7CrgqE2XVWru3r8F+DRd7hxZ7WZ1b3GUM6u/MWIbask2tgsDPDs3armp1jzb4J+0UiWYuF9vSL165g4IYt+zbG+n6+UOK0VR9jnDzPlqqEr4fZb9yjlWrz+V8KmamGld4plhgO0E3IlB9giQaYnomw2BQYXn1jJ2XJzz3J1HHrvtzGI2HyMo1zM/vxOLpVQw3yQKgj11757Bjz0V48MFHcOrksj3PKQe+esq1s8vwax23k16v3DbeTkO5/xr5bqmdKhl45T5xvVl5UJ37MnLrpOFtaQ1nBW0CcYVzXN8bfq2VfpdnI26pESCavZEdcN++en459x7CXHfgnhn5iwoQlPhtMVAd5J9DhAgRIkSIEB9HvOAFL2AP4M/93M/FXXfdxc8gP/ZjP3bOdiQHTduRVHSIECE+vYIKQF75ylfigQce2PL6V37lVzLr98CBA09Sy0KECBEixKdrPO4AMCf7KpG2bZi1hv3/OCjxpiWxynKSzJYCs5zgfBDbCWf+tDGOFVI5cHUrAFzrOALn/axP/tYJ2XOSwx6JbEBZmK1J5nrfTiLaM4iIyTsaFxiORuh1UyRVH/M7dmB6dt6BfU4G0nh5Svs9cj7FLvlrlPCVRAMS9bkULAFNjNMEuooR6470HQHCkM0rxxlmp0SWyIxZHjEbrWJxcxWri2cwM79g27QXU/M7BAieGiHpDjDopEhTu33SQW5KBhvTSFKw5AGc6MgxwDTLTLK0Jx8vQV7mhDmja69DUlYYDTfRuWAfzPGzDNwS0MwesyQ7OT2NeMc0RoePMfOXCULK8cfs9e8UFbJYs7cf+Q+XcYpuHqM3UFguclSdAdRsjEe7p+2+KttG3chC2sEz2LB9PpnGWOWYThKcxipG3Rzw3pGEs5L38OoA3TUCqDPkU2v2mOtOHrVJ7HtPRmGCNxLQcOwsSS5Xjf+gA2zqBDdXNcSc77/77g8LCzq159hJ0O1MsYQUfXXSrjDC7LmQd2a/1xEWnD0u9Zsfb97rd5JPXMK7xGQyEl9pVHXb/T1BgARzixk4Keqxnto+nZ2dxZlTp/ial6W9lmmH5bPp4wxa2EZ34gGybIJoKsXIjumyHNr2ybiP4j7ipIvxeNOeb9sjOESIEO3YCjxKkY9mpqG8z+uHg28Fq/L3usjLEyvWg7zYtqbRfS6FIahBQ3+sSqQtajiT/cDdnCZgmi+O2lr45F+TfTTWCdw23QDPrROsQWC4YhkPjHK5SmudlvY5INizgP1a6MFkUkIoUa/D7XP1bNt237Z/377mKzSgdns//l3uDyOqHtSPDL5WVX2tPFjur4dqAYxbPdhRn7Ofq+uCNH8qrUIyef7wdgICpm+1qdB1e+DWNmb+MuZKNhEJPyZRwVMnKrB3V4LnvvBK7L0gxn33fhinT5/keX1meoAbbrgWq+tnMBwuYt/+g3jgnpN45//7EOJoFvv27MBTnn4Jjj56v+2DoT1myvN57QGMqi5KExawiDPL2ganhlK685Rr6rYAl+1Fcj1ZOaKlXiFKJpW8B+UKCVxxE/dVyeuhqsUlpDiAtucCJ14vueNkrYy8VHTZYopLm5qx4M7JWRx4FjcVNNG2URy5Z7TA/g0RIkSIECFCfHxB4M0tt9yCl73sZXjLW97yEbcjOegAAIcI8ekTJA3/3d/93fjzP//zLa9fe+21eN3rXofnPe95T07DQoQIESLEp308ARLQkmyOdAOy1slmB3RWohHtEoiOr2RcIpWSzS6hijYrQ0nWtGLmia4lLZvQKIqKWZHb2TpN06oaBN7COnLJVt6S2Mttpoj7vE+EchrTMZ1y8tszJMtbYnNjHZcdvAiHH3oYV1/zVE5wMtOoqmomkxxXfHFLiDR2BSezCZHOrk/XvjTOc5Y8hGc/szxi7oBl6c+atQqRAUVRso8e9T+rfFZjrC0ex3i4hvnJPpT5ENl4Br3BNMpBD71uF51uH52kw7LDyijHVtYt5nSbDaZF/pNB/IpZwOS3F61tIu32sDLdgV4v0Y97mFS2X+IIg9k+Nh85hj5Jg0KOAQdYRPZcJknKLORB1cVUoXDxBQs4dvwkJoMUs5OdOLiuGITciMfMulZIeeCWkE7oVAnmx1MYqwwmLe17pbCideEYVyUnl43po0uftq8tOxaTboEEbSb5tkEtYKvzdGyukarlSv3nBSgW9hQBrgX58pYZJiP6Wq6vF4MFVPyQGGaaEROJxgWxdulnGt8EDFOiOmKQuMPXJE3sOM8VM6eUAwfoetC1oPFYFpVrh4wnec9w4QSx06oWZ1k7cDliFrj3x7b9R/6Qk5Jl3Knfy1KAJeoDGmIzs1Nb780QIULUoRlgSpqCktIxF51Hr0JTSOQZvj5YrjaCWxvOz4ql+aEuTtLa+ZY3TFwPruqaPVzV6w/5wyovU9AqmvLAWMNMdvMgqzg0a6VvT/v425m27fnTryPMeNV+n27/mimarrDFiFWCVmiv23VBTquNFF5m/5y+9yob2wq82ooK4rVsHHiuWu019XGYWeo+0wab2797cJqCwGYPIkvxTclrD7Unch7H3srCrzGVKutzrOWlnZoDA6m0RrF5sWKvetI1Jq9lO8mzv22/YzAzPcbS0kPYuWuCG575FIyGGcrMYLj5gF0rSpzZfATD9QqdDlkSjOxe7doZVbx+ZGQFwNfQCPhqlFNXMVwAxetD5c6dVSmK+hpLF7iChbqflAOPxd7AKJGUrlVN2LagrK+PsI5bJRC6AdF9v7THqO83jRYrXPlrKNev8mNH6XrseOltfxmlPQ5YV+66bL3E/3/2/gPAsuyqDobXTS9Xruquznm6J89IGglFBJKQQIhoWTZgI2NMMIYfTPjgQ+RkghECY8CAwB9gbIJtEAILlMVIM9Jo8vRMT890rpyrXrzxP3vvc+69r7tHKMwgI84alerVezece+5559zea6+1LSwsLCwsLCw+Ier1On77t38bH/zgB7nG5/VABDCRQRYWFp/b6Pf7+Omf/mn8/M//PL82mJycxE/8xE/gW77lW675N6WFhYWFhcXfJ54TC+hhZKVYszekVnScq9UxnigrXeTkMAdsXVEYMQmbmZp/wwqmPOCbpdcqgpyybWOmyUtjqwkdnBSTRScdVv3K/g4HMz1tCekyCSqRXKbF1D6kjJ2ZnsLWxiZiCmZ75hw6mDu04Mu1wlhRGyVMVhJ7qX2jMNIW0AmTnk6mfojCdHrS7swck2q2iq2wOb7UbpXzELEbdUMsXZpDf6eP8em9aI1liMMYcS1GVFevW+rItRoCImMzPqUodxwdIDZEvTpkTW0zGESs5o6dGJ6fwg8ThCvr2HP8EObmFrG81UZzbBT7jxzCxYdPYwKk7BWy240LS9OM1EzqvzRWvd+oYbsV4u6thxEdriH0+6j068h8H2tBhM6EOo8ranKukkn1f9VhNkY3kDbUtXQHiEb66CchXbWMmVRIzjiNsFVbVm11mRkdUCBaX48ZP0NjysmuGkdlu9GstF15nDl8TzN1fYHnM8E7PbMb/V6Pa3FCj2FWfZXGGQX8mehX6PVCxHF/SHFG/U91IIn4IfXwyMgI1w5JWe2bMclLILvmQThANSa1bkUTRWrMqL+rpPatiGU2Ec6ROmdN/WYuhO6tJiloRBGZ4VHdRl2u0dTxpuPJb+NBbmFhcT1kJTLRcQvyytOkF317PFb7O6WyB8OuGcPkZClhCXraycsRFGti2RJZ9sGQglXI4oK4dF13SAVL9cULRapRBMdXKY2vJablTydfv8pEsJB1jhZuFg2LjarTNaUIhu2Vy6UcyqpkR5Pnpv3mPOXyEeZay31nkKtFca3LR/lvc7whe+FM6gaXj1tWGxsrYUNYptrqOSuRxaYN5Xulufb83K5pLz/PaFVzpvvJE4K50+1iY30Zu/ZU0e/3sLW5qNZ0YGx0Gr1ujEy1qabWC7XM46EHT6t9aE1S23YzzF1eVf1e5+Omict1m3PlOKt8NTHtOULOU1ID15ku3/eCfM10UgOPYq38NclvRbJAKdGACOLUKLOH77M8K5XKb+RJgvqYHjRJX04GLBIFUr0u8/EyqUXtwiQT6FIWPD6EoOd7YQMyFhYWFhYWFp8ivuIrvuIZyV+CrQNsYfG5jz/6oz/C93zP9+Dy5cv5e/Tvk2/6pm/CT/7kTzIJbGFhYWFh8dnGc0MAO9mweiYTy0DHLVlOcsxOK6SYbXS1G2BuXonchtkEUQFTBXDIglfOo4OjmQkIl5VETkkxJIRgVgqwO0aVpRUnhQLFBGRFIcIWwBRk5PCmB8f3EPUGXHe31WggCgdsfZlGEWd+ifqnYvwetTrL0zXpovycRUDbE0WnI9umYSjqSwokJxPq+PvUe2SiHLINc+wIYU0dxzVvE9UHQYXKDotClhSuqj2RK+QyEQ4rAxcba2tojRFhDYyOu2i0fNQHPlp1H41mhclrUi2RMjRxtGrJ3Av1oj8gu+i6KH38lInIoJKxZfXKU4sYnZxAtTkFL0xx6eFzGMkaiD0hqEkZRMFmJyuperIqkkYNfaePbKyClVG6jWSjXIU/4bGSl8ZKos7pJRUhK5yY+87TauJN9bfbUO2N1PbpqCZ3EyaYszRQ9yRhQjx0Yr57SKtsOQ2/mquRcz43KwZWPoayYuxmeRhcW3ub2oh6PBOJIjV1PfiVClrqhxW7RjGsVUc8lrJS4HnILrQgBsz7URRiYmIccRxyvUc6T16XUSOORWFlSA6Hx1ssSkFSGHsBwqSv7q1OZuBAvCi10tSQQs6Qes3zfb5OsU5NmcTyr1HgW1hYCHI2D8YO2CAntRyjRC0IL54amDAjYivNE5XMflcnPZlzGfKQ/8oJ2lQSkVCQom5OrhqrYj5armS9HrHLvJ7rXkNglkEEmx94sqJqMrSwXC4pjE3btVLZYxI4gX+V5X2Z6CWU25ef8ypLaLO/qe9riMcyDFFYfvt615TptckQyMP2z6a/s6G2GgLTzN2FLbSbr/HlY5m+F5JZzsM2/Jo4J6U2E5QQq3BW4JKrhVr32TlCzcnVegWjo9NoNgaoVEYxMt7C5vo2lpYGmJo6zFb++w7sR7eXolJbQz/cUfN+Ax9/4Byyh57Wts911ZaASzyIw4ooZnm+hxm7ab7CGBtrY5Mtz0uetowuBo2onV297ujnKRibbehkN0P8ejDrLV2zKXVQHjvmeU76FvqZUPqX1tqcOKfSCE6RSefyM5ecT46T8rMcP8+lqU7CcPEMQ9vCwsLCwsLC4rogZe/fRfCaOsCYuePvpU0WFhZ/f3jiiSfwjd/4jbj77ruH3iebZ7J7JttnCwsLCwuL/1vwHCmAk1x1ZOySOcipCTYOHqaFwoPVF1RjNlegeLomoq4ZqG2S3VJ94DwUrIOvBUHnlj99xgC6uASWjpUH64s6hUZlJIJQV9eR0wSgK+RaGMbY2dnGvl0TSOIQ9Vodrl9DFHYQ+EFua80EsLYSTrPCDjpLTacU9pimgmA0CJF46vrIejHpYjztYGQrQcOtIkp2MKi6WK9LYB2JWApHWR8+1eyNHYRV9XcaoaKuiZSzRJqmrjp/5KG93kfU2UTY34XR6XEmRRMuwpiwEphURk61Al2pl6+X7CDZtdOTYeNp1VDq+BywranXgeqswdqmBJFV37SIqvYcUU/r2G9e6hiiLIqob6ivfFKzEimrrtcj2+Kq1GnMPMRJzCrnOA3Zhtt3dc1ktW+ojuOr60IUIyHLZNXnsSGNY7FKTrhusroOdRy6jwnday+BrwlWGTdZMUbLYwcl5ZqGU7IaFbWUJvP1fiVzcx5HjrnH+uieK+N8SEJ8DaQxHgpbzMnJcczNXVLtpz6t5ePZtDWKIlZWkUqNA/MpOEBOZAaNTSZ7WZmW5EkTovx1hRiXkam/n3rsQ6zPU1YCa+W+VQBbWFwfhv+FSTpCoXSFfOeT1HzzaQ2IxSLazI9aTZnnJAFDhKYhxQwtV7aALmZWnVyj1zPTLi8n0+iNoi7u1YSqITH1CSXhQxPImalRWzqwzH+m9VqZbJK9tKJVVrXUyJL1dXlMFga+WkNIaZwOl3AYJl+L9pn3DPla/H3tWj/sOnLVrcrbUb7+4WOUf5vEnKtJ8yF1tiF+i7OYbszfL4jn4VITJgfOOFPQc4eMhwSpJzXe2bsi9nD+4hIa93XQaO5gbLyOw0dH8JEPn8HS/Db279vC5ta2GhsZGhOjWNlU66wzrtaNETUI1HhzZJ1wXLXGOxW17kZ6TfCLe5Rfj06WI6I2lVYawjsnavl+67FJzaWFldaQ2NSEluQ846whyQJu6dp1HWnX9GuRGJdlRuntcjKXq1PwzPdE7kWaJxvy8yfXlE5zJTWnPZjxnDl5QpbYkBffGwsLCwsLCwuLTwa/+7u/+0ltx3WA33jHc9oWCwuLvz9sbW3hLW95C37t134t/7cQ4cCBA2wB/aY3vemz2DoLCwsLC4vr4zkhgK8O1haKXBMANYpXHZjNhpWQRDJpcQnE5rgU2E6Hiadr7Z4L1VDZ6lHOW7KHzgO2haKHA4MwhJkEJolIowB7QgHGzNSSc0lei4HaLo4zdLttjIzvZVVza2QM/gDoZAkTqsba83rtLL/jGMVy6V1S8ED9z00i1Cs97O2dxxv9Osba6vT9EE+2GvjITBVjYYTROMRGJcBT43VW3ByJItQ66oHEreCJMQdJUGHi2UsdJlfpNKSW3Vxfh+PuQsVpw8U4Ov642qUFJ6hSC+A7gaiSyFJZc+tFqFpoTsfPRNXrJGRUjWpKauAIaTUTW21Ws2lS1NEBXrO/6st6VkM0FSC8eRzRVgjvyRXUyZaUxNPTIwjjBN5KH24UIwtCdSptpUzBYT9j90oQSe6r7Yig9B0EiRDaDsgWOUJGylhuiShkPXVdWRarezZeugfXQgLV+VDNx3RuqWoC2Fqumwf2deD6evf6mnNcpW4rq8uMemnYAhVsD15HDSYYTwkA9H4YRigIHjkGWTdHanwEgY9ms45ep61J4OL7UFipOnnw3XUK63K6/wHXhfRz8sbCwuJa0LeDvjZEbrICX39djGKSt8ntmxMhd2GSjUxykivvOOZ4htzUJzGv3WHXADNV8TeZ1ZdGGZvqNcYQejrxqqT6dDWBashm41jA06s5eT4hlkjMzBDNw9bRTomUNiUfTONkTi2ssRNtQW0UoSb5ysyDZcK1rC4uJ5GZeq/Sr2m+r1yP2d88TwzDEN6F2jTN1a7FM4ImgM16nskaZvorb1eW5ZbC5XnbJAs5Wg1tnlHyz/T7nNRGhHuW6jWF07PU9qH6u86DK4wdtnN+9PQCfHcTjZEKPn7/ZXTafSRxgPW1Jb1vjL63pp5hJtSfk2rfOtKkzwlVrLx19P3n164mUuV5x/RTrnCmvvP0MFBrfJKrwtXnZB2e6ee8kn2zg8L2mUsJuPqJILeHlss0/WzU1zx+9POBIYINYSylLUTZy04b6iWVJSA1L635Uuc6lYCMJqpZ/a7HOZWBEKcOcTpx9NOIhYWFhYWFhcUnize/+c1429ve9ndud/jw4ee+MRYWFs856N8Pv/mbv4kf/MEfHLJ+J/EMWUD/wA/8AJdps7CwsLCw+L8Rzz4B7JQUI85wLbey4sPRwcay8sUEExOuDehpC0anCOaawKw5FatAxUYy8P1cOTJE6ubtMIScDlCXrXfTLFcmG+VyuQ4hwbvK8pZ46H4/YoK40ayiWg2YFN49O4vR0Rk88cTDElTl9hYKIjmPHM8pKaGMotSIxuizwSBEnEVwKz76fgA/9hCQglWdigr7zbldkCXky7c9zHYcnB31sDAC9JwEN0UVHN6KsFIDFsZSrJN6iK4zV2pRcDRCtxPCdeiYKWbJMrnigvhcv+VxLdms6iFV/VwhBbGX6GsR1YxjgvSsIM00GSEErO8Xttu+G8i94PvgMelB9yMVlgIRB2lTtCpEVGeInJRVw3TdlbEmIrLCXt3icxCFG6n/yMKYDkC1fYNUahE7FGAOI1YUkxUy12qMEvQi1YckEI4GyDwJSgeqTaQ6Z7Wa6fMSTVuovoq/c0VwmhX1KrVq2AxKQzLkRA7tlxSEAPePe70amtnwOR0hXlxN5NLnpKImhZaxWBUS1yh15V5EUR+Gyqbx5/tyr9VdUOPVKPqEkBe7zSKwTmSE3LNEaj9z/4jqlzsuc8SQ1EbLLSyeEZmabFwipNSXz/WC/LuV6SSR8kwj+VBmhZA1xsk8qY/qxrpUAtnZx2xnT1k4Hs2nas5zmdCSo5lap1IyQeznjeY2/7ryn2lOssH8pDJ/xKX1kUnOvEa9MzQ3Xp8tS5GW9ie3ADqmx8SiYasz5u2MDTQTgETgoVCEFmk45TlS1nHfNXO1bqNRymr7/swtCMSyHfM1iV4w8/rVyVmajKVkIm1tnCty9XOMp/uD11K4Oemu6Urpb36+kOcTU9GCZl4mTKGTohxxEGFNtCGMTZ/APH+o89A2Tij7ZVX1Tl2tw1L3Nk4a6t1ptV1LreNgdbDH5LnahVThqdgde+yG4UkJDqfHxhOeU2HHkJjaRGOLiVohgzkJwBDfpu4wPRuQ10bq8vh0tDcIXLUWZaHUtOekKp1EkIkC2HMlAUxI5EiSi1DlMhP07CJW0ZI8xudIpTSBahnXnua1ip+9XB7znGjgSl1quhXSbQlfS6qeBbgPHVnHPNctntscrUynNY6PX+Fjuuq7xAmIntUAW1hYWFhYWHzy+KVf+iX+IZDNM9k9X43x8XHccccdeP/c32/bLCwsnl3ce++9+OZv/mY89NBDQ+9/5Vd+Jd761rfi0KFDn6WWWVhYWFhYfHJ49gngLCsCzLnlH3+QK48IhrxidYhrlLdEDBYkMRFtKZOxrJeBYyxqddw6M0FiHQg2iiZTW9bYT+szorBlLFQ3xj5TWiikGgUD41jORZ8bu8PyNdKnRDwPBj3M7prUFroSuI3jAQcukyQrtdWQfKZ2nQ4uuxK81zorAMYWmAjgAcZGG6i1mqivJejUfbxrkKGpDtiZ9HF5uoaem+H9oxG8aoJ+k+oAD7A38fGIO8CH9khoeoeCwqmLiq4jmGQ1CZImYqXca28DK3TRCWajGE7QRjbWQVavImi0ENWa6FYDeL4jxIIr6lBiJ4zdJynNXE9UuSbq7aTSt3x/U6OYJdtIcP3dDFKMz6N+34kwuG+e7Z5HvIpsF6UIn16AS+MkpQA0WTmnHJxOwwxRo4psegw7nTaC1QGxn3DimBXDgyTGTrWJaLyJsNdG9cpluERKuHJDam7IjWaCZmj4luxDnWKsyLjTNatL9Q7dkh66GNuFVI/6ORn6rKRAK5HL+Z96XA+xrNkwAc3HdcU+fNh6lBTAoQS/iVgn4lsTT6SKIkKj2WxiZ7uCbruDMOoKkeQG3C5DKhuL01ytyH2R5so31/3EimYLi3/MSFPzPSlKFpj62kbBKqSaoYLNfCLzv0myYbU9zR4maygrSFKxtnVRXpYMjJI0VROtx8pMejfjNYfJrtJamKGwUIZOJBEVsFdSpbpF+11zPYUi92pVrll/ad2W1c4tkrb0/9M5KNGrjOESDWVHBDP/SUKMIbpdT8hAIla5fi4Rg3x919YIdrVCuLCMNsk2bqFw1Wrqop/zk+ccdq6u1h1WvDZ0colILCeSERl5lSq4SCpLh1TQ5X4SZjLRpSIomUjP966QxlRuIl8XnAriVJckoHvmpFpRrO+1Y+S2+vkKkoDg6mctOj+1idYN2pHaSyUUeEz5uh/0uDZJT7R2iHNKwmpjGpOeq2sXu0VCnsvPHo4QyDqZzyklBOTKc6g13DXPCkZwrp+PslQ/61Gd34QbL9vKmp6lhUCdU810EkRqEg31s6aQ2l5pzDlDz6YWFhYWFhYWFp8KiOS1+PSxvbGOh+75AI7ffAf2HDzynJ7r7nf9GbqdHTSaI3jpa7/8OTvP3PmncP7Mo7jjJV+A1ujYp32c0/ffg/bWJp7/itdcI0ixeO6xvLyM7/7u78bv//7vD71/6tQp/Pqv/zo+//M//7PUMgsLCwsLi08Nz4kFdKqVHzrurElQUwtVHlwyFHUHud6ogzxImxPAea3cwqLR07UUDdlKgUHf81nJwna3WjFMChFSShn7x6stmMv1GkzA2fWMNbXL9oBG4YMhkk3q3qWZkGZRMsD42IyoPNXZz517GkeOHpfgZtl2Oq83nGrFpqPVS44mzXUg0/xSf5MF9K7ZA7jz1Eksru/gztOr+LzVdfSdHi5Vm5gfxAjrwD63hmOhj0fRQwM13BlW4ao+uBtdXBhzEBPJrc4bqDaEFdUnA1LK+BwI9el61DnjzW3spAluW4lxK9oYG1M/lToqzTFc2jWNs7N19Jo+arEE3YkM9l0fFXgS7KX6vFrxSpQu338iHHSQnCwiieiuRAkMvxnRNmyv7fM+9Uw0vlRjmBS7XDaaAvtZggEi1YUJa1nTmGwtK0iPzcK9eTeSpy4jvrIMbxCiF/aRhDG23TGELziF4K4j2H7yKcR/8BTG1XVz7UDdVs8PYOr/DanRM62au4qIKAZM6eVVctghC/Jc7T5M3ubK4FzyXT5sQSjnNKsOTrta0SQlOIVccUuqNtqOVGCksM4yj+0tyRozSUK+vkqlyn83GnVsbWzA6RERVWHiw/crOiGC5OUJkwas9HK8Evnk6LrBRkFnYWFxNeg7QmuS84zffyGdCvtZR+qSp7peLpcf8EkDyWug6+rkIGOBzPJgs1YZtb973bmKSUleX4TENApRQqJVpq43zCIbFwOZRwxRWhC9hrwcXquHr88QmfJ+UcfVOII4bC8/rCp2S84IZXI5t1BmtSzy9cOogbMSGe2abbMsf88ES8rPF+VzEMrtdVyvpHnOhODMdG3b/NqGr7ts12+ON2RVXaptTM8PZVvroftVbj/TuJ65ULmHdD3a0jjOMlYiZ2Y8BS6T6iEpgVkh7epnF+TPQUMdjlgSCDJd3xcFWW4U2a4rY4brwxs7a0rD4rw7OqZ6hMxkHfXcrhCsmqwttOOSDJglPj8jSXJAwkly+qT6O0DPKR3dNtpWEszkHkndYnlESjS5LElkTIqzulcOJyrtLL8P5tnRJBVyG/XtEicWq/61sLCwsLCwsPh08Xtv+0n8j9/4BX797T/2Nrz2jV//jNv+6dt/Gb/zCz/Mr7/lLT+PL/ln/xrf+qV3Yf7iOVRrdfzu+x/H7P7nTk35n3/iuzF/4WnsPXzsExLAvW4Hb3zBvmverzdamNq9B/sOH8cXvOFN+LxXvR5+EAxtc/nck/jXr76VXewO33ATfue9j31abX3XH/9X/IfvejO//vKv/7f4zp/61U/rOBafOigh9hd/8Rfxkz/5k2i32/n7Y2Nj+NEf/VF8+7d/uyXkLSwsLCz+QeE5IICNRaJWGrmmtp4JbBbqJ2RJvr1hlMqBbLYshKhoXQp45zXjJIjnOVolpW2NRU0sQT+PlZ1O3qQMWR7QlcB2UeuQt/c9rXBx86As2ViCnQxdHVQEW0enqShXKajrqb+b1YZ6SAjheC7W1zewe7arg4qZPl8mloiOtonUQVej4jIKMAmoppo4djDohxgfa2L24AHM7HIQTi7jPY+fQ/vKHNb8FJv1jGvZPuqHmGtG2Kr6aFeBrttFNfPU51Wkrih2fU1q+qG6N766zkj1gWpv5LDcU71W73e3MZdGaLl9TNcT9MisMUiwHVUR9lK1rY/AVSeo+EwwjqltD6k2joUJBjUfK0EFS02yrUw52JtqspCPT/dMdXFD9d34wEOk2rPYcBET0UB2xBTIdqvcZ57aMHIjttSmSDPVr3UQc13hgToX0gDru8bhHJ1Gl5RAvTYqvS1k7Rg99TuKK1jdtx/xiVnMJSkqcQ+19U301YOcH1FR5RRBVkFrtMkWq9dYGudDUo9JbTGalixJzdi5HsimmRVUnqeJ5eucw5zqKhKBVeG8faHacrQdNNtC5xaXaT5WCx6ZtotZOV5r1FnlNBj0c5V9v9dX/0Dx0eu3VT92iHJXjaRxIOST75LxZqwtRF0kYaqTLhweH462hc7lXxYWFtfAEWlvvpaVSUf+nN0XEp0kgzwhSL5SlHjhM6kl64x6h4i9LJJ10HFzK2F2YigpW4dt5Av7ZqlEkPI6RAkgskkmZDBykSvMd9oQlcYdg+dumpmdDNcS2Ve5Juh2pFpNWlw/MKzClWOYeezqWr9DjhsQYpyaR7VwHU1aG/v9MilaJo7LZLIhbM0/1MslHnKlsyFfk3QowaU4znXudGmduPp4hf308HHyfr3OZ+YY9LxEDiImAc3lRByPH5loXufjx1KKwuUkn5R/uO9xVeIBrSVs4a+P7xpC2TzniEq7XPs5X/sMGQxdz9olJW+sk4CEgE1ij5+LPCfWNaczVvLKdTlM+rLTBJ+DCGDVcLKlZm+MjO2gaRs4lJRW0T3r0wiV+5slMOUzwEppevbzJTmJyHlPiG55rks1YY8h55byPeF1U18bP/dlRsttYWFhYWFhYWHxqeIVX/LVePvP/xC//pv/+fufkAD+6z/5/9DZ3uJSOS/9oi9HOOhj8cpF/mzQ72F57tIQAfzBv/xTrC0tYP/RG3DX53/Rc3shZahnRmrn1aD3VhfncOah+/DeP/vvOHDsJH701/8YR2+8Nd9m8fIFJn8JcxefVs/KMV/vp4rLT5/JX1966omhz5bnL7OamfCar/o6tMbGP+XjW1wf73nPe/BN3/RNOHfuXP4e/bvhG77hG/AzP/MzmJ6e/iy2zsLCwsLC4tPDc6IAJps/Jj5FlwFT71eQivI1cwpiViswCvWLUZIKODBMktDEELlGVSLHgwlYOpCgsA6sS5Az5eClsV8WbYhRfepAqNaplgPhUltVH9ctSLbUEevFOE0QxiECrnUb61p0IeI4ApWuo8ulWHNE5HcmNpwchPddbY/olNowXPtQOhHoDwYIqk3UxsfQQAuTE1OIRqfwaLOJ5fUlrueXJTEWRgIsjNVQCYW4O9egoGnMgV5WVqvr81Xnhep1kAbwEo8VuWzHGFJAPYJH4prMw4VggIv+FlqJiz1eFUG9hlq8gaQTwU2qqv0DuHGAoFJB362i53qoaq9GOibV/1WHl6qzzGTSNavzqXN5qs/6SYgd9V67Sqphn0mFulMD2VcmFPulmr6JwzUF6WGZIt5kVU31fEPVH/3UQ+eIeuh64RFs1VUfkYF0GKO6vQ2nq4476GHHH8fOXUexOFHBqhozY50+Wls7cFRfYdBlG2w3djGIRvMAcTnoLeMJpftRsgNlcqMI2A8p1Az54TpcT5MrFhvfUD5Omh9GfmfF2EVBqfIujgSq5X0zvoVASXi8SV1ECsanMHWxHSYB2u0uxsYn+TtCZAPV+g0jdZ8qNR6jtC9lNYaq/11SrhO5S0F0P+Baz/SSFWtOxj/8rUodLWLP4NhYuYXFM4IJTRQq0LKSNVch6uXLZccKIfuqlTp6nVDNxglqat4ndwVKVkniSHKCuC6qEIixtuY1atLh8xfEsFHFpkx+luceTfRqa2FH2+DmNc1zhWuqVZ0FiWbI03ICVW4NrLczRGtBKLr6R00zvluaP918X7PtkKoWyMnklG2E9fFQEN6unhuN7vPqxBxRGg87gZQztoeSzoaI7OH5vXguMO0bdogo90uZYC73g3ld/sy8voZ8pXWU3sv00xQdkxOldKkIvolSHAOu3o/7Xvoyya3GdUYTq2m1hFpawuPKdySpTey/iwEij2hSz1nsyKWDufyDI/1Bx3N9cWbxEiJ6I64LzDV95aGA3VH4YtjBmay6JTnQCKQd/ZxGzyluWskTruRD2T4IxB2EEpUyNxC1vDp2nKRM/NKzB5xYri8rK4evJn91EoBJGIR20rAEsIWFhYWFhYXFp4VDJ27EDbc9H08+/HE88OH3YX15EZO7Zq/ZjpSxtA3hha98HSamd/Hr7/uF38a7/uT/wy0veAlue9HLh/b5zZ/5AVw5fxZf8GVv+vslgEsga+qv+Ppv49ed9jZW5i/jb9/1v5noJZL22778xfjNdz2A/UdO8DbPf/mr8c++9ftw5uH78Iav/aZPi/wlfPU3ficW5y4y6fyvv+8nhz57+N4P4Zd/6Nvz81kC+DMHEb7f8R3fgXe+851D77/oRS/Cb/zGb+D222//LLXMwsLCwsLiM8dzQwCzsiPVAUWpd8sksDO8Vf6qpNTxPGqSDvxq0thFYUHLf7uFWqU4GtNtvK8EooUUo+B1QgFM6OC3SHbyOrZZlugAsBxFfpdsHl2xwpQ2CLHscJ28BP2wj1q9wiSc1n2hGkhNPAkspvkxSQEswfWMSWQTmC0HfnNCMBOiOlbnuLSwhMX5RZw8cgP2ug1Mje/G7E0Oli84uHL5IquCqqkoPzMvk65LtLUvBWSJlCWSgNRfQQVZ4oJEL5FHNz9CJSOtToDESVCJ1fbqnINwC2F/gH7URd3ZhbF+CmcwQCPwEdZrqFbraNTqWKuF6DbqCGo+k4ZukCKIq6hQgJjq65JqW/WHk+kgr3p7NqnAS2K0iWRU1+rHquV+jLhWwejRWXQ219Be2oLPit8BkjBCpPqZsigHgxBbjVGkdxzG5Zq6B2mMrqv6MuxhfG0Dzk6CTuRi/rY96Ny2F3NEgjsV+JsdOGvbiPsdpGEbUdxHkAWshr1aaVbEgc3YKpPz5u9PDCJYmRRxTeBdk7lXKeieCdk1r8RC09GW4qzkC0QdKF8RN1fmEtnR7Xa1yky+MyGp02FU9T6azQbXCvadgO1l3cyTCtYBuFawkFT62JmbqwelSZmo0SwsLK4LXvcAKSNwFQll6v+Sfb4pZxCHKY4dOYkjh0/i/NOXQXkqR4+c0ORogqcvPonLc+fUnCrJGKzH9D22xzfJITkZWlLZFupb77oEJ80RCcpKWDNbFcks5rNyglaZuOR64I53jYK1vKaViVxTq9fMqcYZhN6n9lxdu9coh/WB4ao+dcukqjmSUSq7uk69o68kM8RskrfheoS56TMmB/X8l/Om+XbmOaHYj9pt9rua0DVtNCR5uW/K13k1iZwTyGTB7Bi3FHGFyJwiUc0onz0v4wSCoT4xzzmOELipToCTZuhsNrZL4buA8qqTJw8YJXGmy3Ck4thCbXK4EfRcFHPSl6PW4lqFkolIojxQn4X8/JOmRLbW1CMJkbWUOCelPagvWYFu6vayyjdDQGOVGuWq9alCSWwDeEEMeqxK1bmiSP2/eq6hMsVppp4l3Kr68flZ0YyXBKVxWxqDeTIGwCS5GW+W+rWwsLCwsLCw+MzwRf/kXzK5Sy5H7/uLP8JXf8N3XLPNe//3Hw5tb0CK4WdSDa8sXHn2G/spYvf+Q3j913zj0Hvf+sP/EW//ubfgD/7Tz6Df7eBnv+vN+JX/fTd/Rs+X3/yDP/sZn5cI8rf8yh9c97OVhcuf8fEtBBQ7+/Ef/3G89a1v5RiZwZ49e/BzP/dz+Lqv+7rPYussLCwsLCyeHTwnBLBRO7JVIClHKPCoo5amJiyH+RxD7l5Lig0pYrTVIqlmpd5fquv/FqpZR5O2bAMJE8ROJQhfSHsZonyi3VImeIVcNuolE4T1YIhgo+iiYyRaRUzXQzV6J6dG1fFTsS9UV9PrDZgw5hZlbn5uOl2aNyGFPvxQj2mjSq1Qzpj47O+s4eknH8VkpYGZo4eRjkyjPzWCG+sB2p0drG1uYaQ/wIFejLVqBT3PwWwvQiPtoONXsTJSwVQ/RiN2uXbwVhPoq/f3b6QI61UM1EP6bKeHKI2wOFKFEzs4OADieAed9hba/S6csXF48QRifwRuWEWt1kMvaiKIauo8pFarcT83ohjtSoLRJACoLGBVbROr/iPbUd9h4neTXIcrJDty+f1UEwCB6uf25Xmkgz4T2j31IEYkNPXBoNdFf9BlW6B1CvD6KebVtn117zrqwSzbWMfelU2k7QzztRlkLz6F5SBFdZBiUAV6gwGSjW00kr5qQ1/du1Cd3kWtUuFanZ8YRZ1NM4SGLJuvJkooKM82rTH/dvWYlx1LiQyOkOJXj3lz/GGiZbjeb0GumL/TXMdOgfBev8OW5L4fcJ3jMOqr+ynfFwret5qjmryQ2pysFDfWp16QJyJwAgMrsEhpWNKoO44NmltYPAOM8p5Qthcuvt/Q9WSZTuMki1Z9DPXKCE7dcLv6rIpwEKt/jO6A6axYLHxpLkkQaaITQog6xbxT/jGQdpjzFokcxhY50SSy5wkp6+TuB0XyiZ6uhhSqheMBSscDH99xhlWX+VymeUe90OmklEKNSi4PhLIdc3mRzIk87cRg+tqQveVWm7aUz19W5przlz8387LkiRV/68yxoccUcfzIhtqb3/8h1TCuOXc54e3q/hwm6nVtW+0SkifmwCiNRbWdpWK9rM1PuH9cR9qos69KxwUn5QlR7OT3wvScaU/hjGHaL4pgfohhO2f1bOWp9SLrIfASVGoxRlohxifrmJxpqnWkyi4pnXYfK8ur2NjoI4ta6jSjSGMihdWDQCpjn8l5JxICmEp7uCEqjQEarZ46VoDpXaNojTS4PaF6xlhdX8X83CZWV4gQbqlrnVC/A7gZJQcEkjh4HYK9uCZXO2N4+bgfYvYtLCwsLCwsLCw+Jbzqy/85fu3Hv5sd3IjovR4B/J4/EwKY1Kovec2X5e//6W+/jVW+FLv4th99K7/3O//xR7CxssTxH8LZR+7H297y7/g1qYdf/Oovzfcnl7i/+h9vx0ff/3+wunAFlWoNR07dyvWFT91x13NyvfRc+Y3f/9M4ff89rHp+9L4P49zjj+RW0Kath07chK/4+n87tC9d6//6nf+Es4/ez8/kpByuNZr553sOHME//ebv5u2obwhkl/2CV7wGpx+4F3/zp7+Hx9T5DKgGs1EAf/uP/3L+zNtt7+B/vv2XuY3rK4uYnt2H5730VfjSr/k36tm99pz0yz80/MEf/AG+7/u+D/Pz8/l7lUoF3/Vd34Uf+qEfQrPZ/AR7W1hYWFhY/MPBc0IAk6KQ1BpMKPkULPSkJrAnQc085JuZoKRXCjyXAnFakXQt2ySKyjQTS8NygJ3qxzIB64jVpmA4KI60CBaLWqZkOYgiSMj7pEkeQDWHo5B5rK4nimJUSJqSt8pFvd5QP3UMwjaTZlSrjnVbjlYf0TVphbBxY3TKgfE8hJ2qYwzU/1exuraNuUtzuLU+hrGZWXQnGpgK9uD4zs2oPPAIZucu480nJ/BHZ+YQYhRfsa+Lg1Me3n1mGQ8vj+GLJ10cn1zDam8Uf3apgvZEHV9Tm8R7V1Ywofb4kiMOFta38b+2JjGaZHjD7j68oI3Tl8fw5+r6V7pdOP0+Ritt1Ebr6Ffr8GsN9aDaQqr6IA6q2J262J/4WBivYo/TxKCWojfqYF/sY+DHiPwMe1QntCPSDLnwVR9suWLzPXCkpjLdtzRM0N8mwnKAvnrgjwc99Lo76A/a6uE+RLuj/hHwrvdi8cF5TH/tV2DeixBsbCNQfTTo+dh6xUn4N8/Cb/fgXV5F9aaDqh97aMSZELKsnvPhq3FSq1aHrED1YMiD3jkBwbaSBVFxvYSFofFPYyQxCqrSYB4ewtfiKkvovEliFFsciwP9fvFNKphpkBKYCIFOt4PxsQnu04q6P4N+h78PYu3soqYe+sNeQjy8mgUK1ZjUnhQ1Fh+L7pZj6m0XdtkWFhbPAMeQdeq7lq8P8p0x9V/NhJ9ql4xud6D2qaFRr2F7O1IfVdCstdShIsRRymuoWB2nXA+Y5wlXEoyurmHrmnq4+sw8FznGhnlYhSqWyYU9s9T8NXXojbOGvoLrJLzwNlmmlbwyFZUdOgpC2tFtdFHULi/spjlRzC3q/5ZVzLnbBx/cKebOrLCjN3Nhkopt/bBK2b2GwL7mlmmFKAw/7JhrSOUtQ6Dql3zftDW16YPCNno4WehqArL82qiDr04i0pcn6452K3FUH8Vk1ZzK9cp9pm0S6VNKLNNkbpZKG2kcUL1k4cg1qZwJOS7JSJ5ubzLUP7QG5G3lZ5+Qr50SppxUjUV1Tl89OzQaDsYnfBw+Mo0jN1QxOdNCvUnnTNhdJRwk2NgY4OzZS3jgwTVsbQfw3CYnNaSUJZbqOtjqWKQebtYzjLRS7DvcwvEb92H33goaLXItkZIHdMx+VMPy0m7cd99FPPHYlnoGqar2qCeZsKK+DzW1VkU8lkz/lvuVx5NXVlG7plssLCwsLCwsLCw+TYxPzTAx+5F3/wUTjvMXz2HvoaP5508+cn9e0/aVr38jKtVq/tmH/s//wkMf+QAC9Z4hgN/1x/8VS7o2MIHIUPohtEbHcwJ4ZWEO3/PPX31NjVwiZN/5334T3/yDP8dk6nOF173pXzEBTPjwu9+RE8D/+3d/lX/f9crXDhHA99/9Xvzgm9+Afq9btPVjdw8d88Y7X8RtplrD5jgze/YzAXzp7OP5ewbv/l+FSvjf/egvcSIk1VX+9q94iTpGQWxS3WKqG/yuP/mv+KU/+QDqjX+85OZDDz2Eb/7mb8a999479P6XfumX4m1vexuOHj36DHtaWFhYWFj8w8RzQgBzTdHEY2s+QuYkTCA5qQ4i80Z0cmOROVxXNA/awVgaGiWOI2SYJ8Fvj4KhOpDOwVpHAtYUBU21zEpqDzt50HlIrZMreIYDuMaWUs7tsQ6HCGyP3xf9cpoMQMV+K7UqKy89DuYn2LdvN2p19UC7kbDlMhHFLsS6lwKP0IoTEwxnftkxEUit1qFGJRkrYL00QholWF1dx9bYGqYqDVQn92K8VsHB/Ycw9vQFvOpEhN2NJzHSG0VzMsI+N0Znfg0v3dfAzn2buOV4hEG3AzetIvYdTPVdzNSXMLO2iVfd0sTK+adxYN847riyitqoj32jK9juqnumrseL93F74vVFLLlrqG414DdqqDZbGKuNIproYsypY18vxaw6fn3bwY2TVZzdbmKk7+FUK8JC14cXNDAehGqbAJshEFU8nFHX36s2Vb+p+1VJ0BppYn7xMtIeqX4H6HR3VB+0WQHc67TR7e2gMxhg5/FH0awcwIoTq34PMCDCeCdFZ9dxjH/NK7HecLDz+3dj1803oUP3V/VjUqvDCyPEahCSe3KizukHAY1AHjfMecDNx0uWFaSFUdmWo8Tm/bwOJkflpT6041LCg+o731iJFkreYXUYS6rkkyHlF9XJdvPvAPHPHo1DR42njOlzUU85rLPPxz/VoqbdlpeXsXvPPoy0RtU1Zlz/kwjffjRgC3Cqn3jixI24dPkKdnY68InghVhW82WTsoxUXuo66NxU15osxaFrJTpMstiIuYXF9cCkbJIVFrpGRZvX9dbkLzlQpGoG8wNcuniOXQ9m9+7CuQvnEQ4iqYeqJquYXAvcnkwVXsa2v6LyNAlVGQJPO11ASMzMqE39RCde+bKWOZJMkhJJhljqtJMhRmrUtw7Px8K1ekyogkockFW8Y4hZvkr+3Ng/G4cCPifPlw5b/NJyR3MhJaWkSDTpLNefk7ea5DVEdRlDtdW5FIO2Ws6JPU2CQ2qZ8/zkOnktYNrWdwzRnaKYdjNOFuNjkB2Hei9KZTZlVS23NuVa7Cmkr8koXwS1LpgO9bRylZO6PHb8oK6m5x0mY11vSAVtFM6AqHSN1bY0QoZFphW8hCSJVP/RnJvR44CQtmQ1zc4k5IHcR9KnlpBNcl/t3GHVrePW1DFqav1p6BLPpeLPQD4WU60klzFZ2EDHJccUYyWdOuKUQs9cgXpdQR9jzRBTs13c+rxp3HjHbnjVHXW+rlwv20OH6r0YzbEq9u0/jKmZBt7xFw8hiXere+Wrtd3lkh9uFqpVPEJVjfXZqR0cPt7CHS87hta4evbJtpgcznK/DLWuBgMcPFrH7OwNqNY/ho/fc1qtc8fVeXer+1TnBDu+Ayny+6WrWPPYpw8S+g7RtXmOPNvZsgYWFhYWFhYWFp8RyNaZCGDCe//8v+Prvv3/zT97759d3/75mfC8l72KCdCPvf9d/Pf07F4cv/lOfn3w+Kl8u5/7nm/Iyd+XvvbLWeG6ePk83vH7v8Ek62/81Pfhrle+DkdO3vyZX+B1cPymO/LXZcL6eqB/R/389/xrbhfZSn/Nt30/6s0Wq3SfePBjcj1/8C6cuOXOZzzGrr0H8Hmvej0unj2NhUvn+b07XvzKXEHs6CTT3/2PP8LkLz3Lf/13/QjXMX7o3g/ij//LL7JV95/+1i/h677jBz+TS/8Hi3f8+Z/jq7/yy4feO3LkCH71V38VX/zFX/xZapWFhYWFhcVzi+fIAhpcd5fAQVCnXDfVuer3tSiTYbl1JLQoyVhO0n9OyqpOaMUKKTvL+xv9ZLn+G+97lYLJwHWv/lwUxoW+SKx4KVBNwWgK3HtMkulrDRx01noc6M1cE3CEPkZhZyl1kf0hFSgHsPOAvthdU53hWO3bTyLE/RD3dZawkY7ikLMLE34d7v59uP3WY9h370eR7niqPzw87lfRfaKP1+2rINj0MVZXbYkHeOLRDGeqDlb37cLh9gYGUYjEGWCi5ePDy02kow72BG00gxoun93Bw1cm8fj4KNoTVa4hHLgBQqTod9tA2Een00EYbKHZ76Dm1LAnSjHv1eCFY+j1gEFjAgFa2O730FWvZmbU65UeJqc9DHptNLwW3MhFz+0CkY9udwtLVOey30VvZ4fbRxbU/R4pe9UxyI6aSOB+hG4vxc7IlNTSVH0WcEC3Afclt2Dn+Aj680vYPL+C8Ze1MFB9nEzMIp6ZQmO+w2oo38k4IcGv+Rzmd0zfO0YVNTwuRA1Wsu683piFse7WyjGkxfg1d7hkl3qt3efweUscR74/t9MQzY6Tj5lMK8fpvGEUqXHTQxQmUm+T6hyS4pkEdknM1kojrTFsrG+gol6LYEzIHWPHrruBOB9pRObk/5hIOWPBL4gLCwuLIRi1LdeiRUkRqgla4dIKy2XfV+uX+t4uLl7E2uY84iySOuKR+m5Haq4K1JwVCJGar0WZWZckYyjTtshOptcdmsdcXXKBiVtJYpK2ybzhuVKagOzqzTqbJsbu2OF6s4XFsiFUXU2QSpKVY9qRJ7VwD6jjpFwz1rhr5DXQIWphIudonSwUvkX/ldW/5R9D0bG62TXWyFL315DSJX/pvP+N8wF/4kpNW2qL56o5MiYi3NOktwffq6i2R3xsI8DNyWOIqwhfMzG9TKKHTMhLLXaxbOa7TMrhWKuF03ToOpjs1nXV83IApv8cSVpjdS/N3amUkhBVs8+uIlTv11fPPhXPR3Mkw623HcbC4uM4duIIr8vj4wfwkXvPYG09VMepw6h+zX0sbLCLxCZOeDJtRFYkEOj/y1Ph0kidN8VIPVVruodjJ6dw7KYZuJUNdYyB2qLCiUrSD7E8L2VUk76KUzfuxcZmB+9/33l1nBH1nlp/iHzN+hhpOBhp+th/sIFb7jqK1mikjrcGSlJIi5Eu95/uV9pBpV7BK15xGzbWPoZzT66ojeqqb9T52eFDxkiWFsl1uaLc48Ghntd8Jv+z0tpsYWFhYWFhYWHx6YFsncmKuL21yYSvIYDpGex9f/4/+DWpgm994cv+zmN93y/8Nh/nDTdP8N+3vvDl+OH//N+HttnZ3MATD34UzdExfN4Xfgne8p/+W/4ZWS//wvf9G37uvftd//s5I4CN9TJha331E2575dyTWLx8gV9/50//Z24z4fkvfw2++s5Zfr2zuc5q6mcCEeP0859+5Dtze+jv+plfGyLFCYYUHxmbwJu+9XtRqzeYID9w7CS6O9vYc/DIp3Sdn0u4+28/lL9uNBr40R/9UXzv937vZ7FFFhYWFhYWzz2eGwLYoUB1mhOqFOj0fWPhp2nUDFp9IkHZfFfnqmBybjvpwM1ESSvOka4E8rJC6ZPp2r1DZKpT1N/jzzJTP88dbnJOwpXbgRJva7Z3JBCvjletBKwKcjlE6SKKY7RGW6wslSB/oVuRmLQjNe9YKVThgDPX1ssFN04ebKXrpQA5tzthP0dsDwbokQ1ybwsjM6NA6ONKfRRzm028YLKPMPWw2qhgZsrD7K4pPPzEFewe3Ydmo4+7XtTExHobG9vbOFR3Ma8eLteCcURJguNq3/1NFxeCHqbU/qO7RrD3cB07p3dwIZlE0qBYtwPSy6Z0bykYHofoR6FqX4jIraJar2G+t4MVT53brWC5t4F+cxz7vCqaql2eansYhuiFfWSDPtJ6gF475QA8WTr2wh0kSReDzg4Ggx42N9fY+rnb2cbWxiaTwVQPOFHtSPw6klbG9TmoLenOJmLPRfX4LJacEMnsJE5+z9eg0yASM0XrtS/F7oqL3o/9GlpZHV4aqz510Kg3mRDOoC2PjUIs08qhXCluCJC0sC7NkxOSfJzpSL6u1Zui8JbMzEf6OJm+1cP2qgUKQkRszeU8JFKS4H0mYx8SwC9yJFyxW48HTPAePnJQjcUqBlFXyHLfV5/5GKixVK3U+T1KYCBbT1dbnvr0HaGEiSRD7MrxTJ1kFgd7RsE//P2xsLAQSI1R4/Igc4D5njI0Wel7gahr0wjVKq1NPmI1LwX+KH//vWofQ/MH2UfreUNKADvarcIRMlHOJHNQIEQk1FycadcNRyclCZVJB/J0MkkxV7n5WqzLKvCJygStA8O9loo55A4bZaJTiNxU9wPYIYO31scq2ycDw4kwV9dZ53nQ83Ly0lhcMzmYCcnLLgyesbIWFbRJXMlMf7GKl8jpAbt4pFmfbYg9Sl5yW4jVveA8M83cF7OyJpu5Ljo9OPVZgesggsy7NfV+Q20hJR9IHW0UvuU+MesHq7c9t1gUStdvbKGpEZlaO2WqFcU0EZtEqxLBHlQ8NFohDh5uoNYaxclT0+h01Do/vhdPPnlZrQEDLkGR6NoVOfFr7rBJ6jEOF7pmPWvEy6Q/XZUam2xg4vTVWh+zOnff0RZuuG0faur5Qsa3qTed8o/Dziiu7hNPrdcZXnjXKSwv9fH4oztqrRllMr5Wc9FqpZiahDreQYxOEYG8rvYP+bo9U5aDxy4dNxaCV/0eG23ipS99PtbXHsXGaldtNJBnRp2SVfSvI/fJ0TbsfK2uJEnkpUIsLCwsLCwsLCw+XZCtM9k7/8V/+02cf+LRvCbuw/d+CMvzl3mbV3/V1z1r5xsZn8A7Htvg10S+Pv7AR3XN4CwXhhBWl+af4QifOTrbW/nr0fHJT7htucQKJeUblNv6bJXaIhvpxx+4F9ub6/i6lx3Hy7/4q3DX578Wr/7Kr/1Hbf1MeMsP/wgeevABHDhwAD/7sz+LXbt2fbabZGFhYWFh8Zzj2SeAOcYcM2HlMrFEigt6wCkUsNAqJO3PN6ROKcPoLTNHLPyMyoePlElAkwisKIo4mEmEYC62dYuah2LV6+VKKGh15vVqGRYXUbzk4LUhZ+kYEAVwvVaVQDyptTIJLE5N7UFVtUMUR6mu2zisGqVr8Vk5nOrg+lUksAYRwG6sHhTDGKG6sGgwwHZ7B+mmg8EYMNMaweKxm5F93ivgnnsv3MoWRtoOtroj+NsnL+HFJ6lOXhfv+mgVnWgTr3vhHkycWcf0DVWcSXysTI7inktbeNnxUXT6C+qETZw/28IF1axbjrTx/JEMD/dDbNdrrECKyAbYH8BLHCRM8mfodbex1aH2JdjKXKwPEgyiBH2/htWKi2RyEju9DPWsh8r6Aqq9vej2NlHvd7Gttl+qu+rvquq/jnoo3kG/20W3vYntrQ3sqB/63e8OOHDrsuLbR0aWndWKut6A7yUR4UTIN2ouRtS5B0Ed2+q5tg8JSkdOhHCELDEDOKpPE/VDqq1arV6iYLUiL1dtG4LXze9drqBiNZhJOigPWE1guKKUFcLlqnFtSA5zvJISeGiz63wXOLSuCWBWsjlS35MD+Vmp5qN6f2enzeMqiVP+rtH4FFWZtvJUY5XqVXc6fVaaVXUdHueqk/J3guxSfSFOuGQw9Y2VTFlYPAOuJfXMWiSvZRWLIzXnhW31vVRzRUD1yJvwspr6jsu8kWYRW+SyglXbzZusJK6XDpqDZW1MeK5zpb48kcKuWNuSutXRC6an5ww6fqbVqkT+0nzB4mLImlm0WxalNDXXZFS3Tl5rlk3oec11de1fWadNXWBDrl1vrTX1kA0xeT1njrIFNM1TokjNcvLSEJbltdvY6xsC3tGkH5PBRAonMWpq6Th67AB27RnFpYuXcf78AgJP9T1ZRrgBK0SJGM3Vp7z+iDUCrQiNSoQjR/bi4OG9uHT+Ck4/dlEd3+d6Ekx8M1laEOHmuoy6uVwD2CSpmc/zes4w1v+x2i5iG236EbtintARBK5aCsn+m5LFqI50wrbRHPySvLRCfZ0Yx4gyuW6obelX4yaR33GjAieSHKrfKilGWglGJwY4dMMBjExSO3vsxgImw6VMh8tFMcya6ujXXTQbDdx5x2FcvvAY+tttVPwRjDQ9NJoDHDwyiZl9DTjettq+o34GmshVaz3qEDJ4ANG1C1Gvnjqwf/80jh6fwAObW2ptmlTPH+RQ4cHU4nZQ7ms9ziGOL9zXXGP52Qm2WVhYWFhYWFj8YwbZOxMBTCAVMBHAQ/bPX/UvntXzEdH8Sz/4b5lkfiakJeL12caFJx/LX8/sPfAJtyWVLtXyXVm4gl/+oW/Hv/zOH2Yy9k9+65f4cxKR3PaiVzwr7frWH/oFJOrfPH/5h7+FtaUFrhtMP0Glghe/+g1ca3nX39Hez1W0Wi28+93v/mw3w8LCwsLC4u8Vzz4BTLXuBgNQ9NHzKlqxlOqQeCYqESfTqpbhoFtZOVQOAruaLDZkLiuIXSGhoiTl4K6ptVcS3Jqj6mCrywSdqI6ursU6rD6SyyjeT3XQMDNKz8ThB8nGSKNQ9eh6w/SgRYFFJsy0AkiIY76SPNBoFJxFsFWCkGW7Q7GABgbquJU4Qz1MkLY76Aw6GE+24IxMqzZUUN+/C/3tKfSSLr66GSMbbKrzqvPHIfZPVbCECtLtGsIQqKVtNLIJLDoBvKCC1raPD/xtG8+7aQ+i7g5au33EywHcpIko29J1iyuIiKQgBVeibbBJeasDqlTZMOzG8NUJlrNFPO0leLo6hu7SZVzaXsWS18KlzgZu9Pr4yNoqxt0KVq5cwYWJEewELrpRA3G8iW5/hese97Y3EfY6CKOQiYZGrZLbp6YUhqbaktUqUlfUsTTeqljF+u+9Hf0PTyCNPfRnjmDiTa9Ce2YU7l++G+E7PoIJCrzTNThiY1ytVljdmqSOHpt0D7Wdd6HdzsdLrh533NJ4ka3zgZe5OqmhqAHK+5u60tD1g/Ue3vXI33y8GJIYOUmQxoUCrqwey+2pMxo3Ibrtvro2l2tHUm1MzsnQ94u+j7VGFZ3LXdXviVYfCiFDpIKTkzaGiCL1vVay5d8xGzC3sLg+DEnq5kSfkxOmUnM+iTqYmmzgZS//IjXnbeHBBx7CxsY2Mqorm9J6FnAdVVbW0tyTiMKVySoX7ByRpj2uBe65gVa6iqqUSVVh7yB1zcm1IRQaTNu9O6QMJkcHIhZ1QohREtNxRG0bqZfi5OHoGrBpaqyr6WApl3pwtS10ThrreaZYw1Otpi3WXemT4TW4TIqWlbP5Z5rMdczcrLczTxfcZp1w5WqZcpYWCmSTaFZRTz1Tky3cdvtJ1bc97N03pfZ1cf78BgK1VmVupslxl8l3VkVz8kvGvvhUQmByvIJTJ/ejUnExfssxXL44j15P9aVXFf1rNnx95joM6S2Q/uJEnasCU7nq2Y9Z1UpqWFqvRkcnsbS4wc8GRA932z4ef3gVc4trmL+yjoFag8fH1rG2SrbLdXZySD1ZK1K9ZJg1JTP3R+ThyJcUyXjjEgCurrvhZh4CNR6JAK43I+zZV8OuvXW17Q6oRm+CiJW5blZBvx9j0A9Rr3moUKKWm+gxQc+FA+zbN4GDB5p48rENVNUzSF2t762RFAdOjMGvUdrWDpO/0js+wkEFG2tb5EWB0fGGWrsqfBzaJlXn9qtdHD8xg0cfXUTS76jzVVlNz32byhMVJQCaNZ7V2ZysIPWkPT22bEqThYWFhYWFhcVnBrJ3Jpvn+YvnuA7wm7/7x/CBd/4Jf3bLC16CfUeOP2vn2t5Yx79/0xdic22FydPXfPW/wIGjN/Az3uWnz+Cdf/hbz9q5ngl//ae/l782ls7PBPp3wL//2d/AD/zL13P7furbvzb/jJ5Jv/WH/iOmdu95VtpF/fGdP/WrePO//1Hc+96/xAMffh8+9oF3YX15ER/8yz/lGsJvf8+j17giWlhYWFhYWHxu4jkhgMmq16sEYrOnVUOOJwSs1A+UwGpeE88R20BSGCaZkz+I5ESwUw6mplKrlJ13yWoT2n5QtnW1YpPpWreosyiB1rhEyuljsgjZ5Tp7ojYu1FaOVj85VM/QS7n+nuNXuK2kwGrUKxwkd10fXuaw1WJnu43uTg+Dbg+jzQltMZyx6pQDjJ4mlOn4RD7GWpXCMVemB6V/VBvCaCD9F0Xwkz6ev+LDqfXgH4gRxSFiqllYr2NkehzB1Em4TSKH1/BFN4UI0inc/9Q8UncaLz5BNZL7uLJaR1CpI1b9sF1x4cd93HS8j2hXEzUnwFIc4K7JPr7AW8Xukd34n+fq6BwNEHhqn8oAXpyJGoz6gYgI9bsW1dFvZOrYGSayCKHXw+9TbUc/hENq5KSFygiRwz4+tLONsWAEX7i5jguDNlb8XdgZuOgNauj3lhCmq+pSVT9RrVp13YEnhCNxDkTSppnHJLxLrKYXoUMxXfVhL+zBSfsYP/s0Zi546PfVPwj2qra9PsX2VAjv9EVMXVhEoO5jnITqOBRUr6Jer7GySqRSVKs6YCUTj1Eec4YUdsW+lD6Dm6vaHK28LVRnMn5IlZ5EWpmLNE9OcLTc3fy+WnVkXJUzkxSgxycPG7fGjqGJto/mgH3miUIrFZU8DRVWjavzddtLqg0eBvEOGo2quucpB/R1VUwOeLe7bXhqPJOCHR4p9jO2M0/Ub7Iz5/dohojJfroKqkGZkgJb3NwtLCyuA7ErdjFMdpYTnGL1eYgXPO9ONddtqzVgB5/3ebfjwx95ANvbofouRzq5hhwORHnr8pqQaieERE3BIfbvm0Sgvp8LC+tMvNG3OzEKR5a9OmxvbCyPA/W9Dnw1Pw4iSdzJ1Z5Zfh4nJyVTsXvneU9sopOEElkCJoo9TxJd6IS8VnIdXaFiM0cfjdWVhsyVUhBFYpWbr7Nlktxwo2UyOO9XGEJSp5+47rAC2Kzzej+eG10947HSOGN1LKlkW6M17Oxs4gPv+yvcctttOHnDCVw4f7eaXwf8LMAELu9rFKQy7/o8zaaYGB/B+toK7vvo3fii134JpmdGcenyDit0ydLNqKbLSmczFrg2u6OTgkrjpkji0YQ490cPlUqqnjVcvOTFL8Dk5H48/tg53P3hj6o2VtR4AR68f47twddX+6z6vhjPq3l7XB2/Km3Q9tEeleHISgS7Ppc8l3h5goBJQDM/ougWZXGl6qDeBHbtHUelRvsSYRuzGt1JA8yrsfjI/U+hszXArpkJnDh5AHsPTYFqJYuemuzOE+zZ28D5M6uoN6bVT4bp3S1M7G6qbRYBXTuYbLW3NhN87N4HMX9hDSP1cRw4OIPjN89icnpKjTMihdtM4k9N1zA+4WN1vocgEA1ySol6OhGjsCjXBLh5nkxlXCArvEAsLCwsLCwsLCw+fRAR+19/8cewcOk8fu9tP5HXxiV18KeCsjVyFA6u+fye976TyV/CV7753+Hf/sgv5p/9xk9936fT9E8Jf/iffw73vOed/Pr4zXfg5O0v+ITbcy3kP5M6xkRUj01OIxz0cfD4jXjD130zbnvRyz/pc5f7Jryqb3qdNj7y7r/g17MHj+C1b/x6/qF45Pd+7WvxwN3vxcWzj7Mt9+z+Q5/0OS0sLCwsLCz+4eI5qQEcRzGcwOM6dV7gi3JyyOY5za0ZhRA2sl132H63hHIgGDBBPHkt6g5taajfS1m5k2lLymGb3aFj50Hj9CrVJn8o6icO+YqCxHV8VrrQieh1Ye4sdY4X5hfR6fZB7sRTk2PoDrr8aa1Wg+95SHS5xWFlkPldrgkoNYC9LEFMVpoJ1QqpIu4Bm3EHjV6ENErQao6iN30I8zM7iF8E/PUj9yOeW4OjHgQfdfei7Y9hYX0LE4M2PjwYRXsvEQAu5nZPYuCk+KPlNm7CAE9sOXjk8B2YW1/Ana09uHfbxQOzu9Ct1OHECTLPgUcBfLLSVNdfd2tIiKjw+9hS7f6bXWTNPIb1WsAKXSay2zu40NtE0O6g6k2xeqyZrSDqpFhIOli+GCKMMoQpBYg7apeIu8DTtSk1VQqjlHKMpXYyQLCzjPrH70M83UI2dwWZ6hg3peQDh2sGVpJFNM+cxlS7hXRuUX0Ws1KJSFxP175ly3CtTBOn41jfEy8fHkxaUDTflUQBHqtOagZlbqNZjCtN8tCIcbxrlOXm9fXru1xfjc7JASzh9YvvgZMyMW0GPPULa8jUe3Gs+jHxMOgP4Pia2HHEapUSEmq1Bp+r0agjSVwet0blR8RLnBSWrKJMMwo9IXtIQWWD5RYW1wdxl57r57XtxXVCiFZ6PVBrwp6ZMYw263j/+9+NbncHn//KL8Sxo8dx/wNnWPHp+VL/Ncs0gcXK3ki9jtX+HUxMNfGyF9/GKst77nkQ588vcUIKE7FaNUz/UY32NOlhtOHiNa9+qVqXPHzo7nuwvNbj+YnWTrLLTbU9MCUlsa+9k2jyN5U6uaodQaWBlNYCY3Wf2ywLYSyksfZOyCShxXOFuJb12M3Jx/JcV1gjF04HZTK0sO7V/VtWBsMx/sXaGtqRmrZ0PFfmtSxJ82QyuTcRdu+ewbxaF3r9DBfOz6u/j2Lvvr24dGWZ1aM5Qe1I0hHfT1K40pSr1pKZXXuxvbOEXhhhbWMdk5MTuHhpE9R9ia4lT4lhV1s+m/HA3DmyoeeaXEGt1xCunkv9mYWqfbtRrwZ471//H/UMUUfFq6ifpiQsedTvDdWugNcuVnc7kvQDX/qC3jd221Lb2ZWayY4m4x2pBcx9CGiNtZM7TbiBakvFQaXqq/Ujw+joGBPpghQBqtjYifGRj5zGwtMh6phEtOlg0F5U249heral+kU9Lzhk5Z1gcqrKyl3H67BDRWu8pZ4VE95GECCJm3j00dN44ONzaLi7kXbGOBkpSeZw54v2ct1jIpRT9DEy0lD3ZAwrVwaQ7EBtiW5Y7KKX+ftECmDjHPPM67GFhYWFhYWFhcWnitd8lRDAhN//lZ/m3wHVB/7Sf/opHafebKE1No721ibu/9v34H++/VdYIXv0xtuYQCVC0+DC2dMI+31UajV8+G/egT99+y8/a9ezujiH92rittvZwcr8Zdz9rj/D048/LNdWqeD/eevv/p3H+bWf+B5WDNNz5xu/6d/jrle+DjOz+4bI3E8WZCVt8Du/8MP4wi/7Z6jW6njZ675CtaeKt/6/38r9NjoxhV/4w7/BiVvuZJe4frfD+1AbqH8tLCwsLCws/nHgWSeATUCzXq+zioaCin5ue5hwbT29ZW6yyxaXjtHaODqYTJ8IAWsIQILrFgQpSraahlB1dcQvQ7mWIfS+175XHNoQ0gUx6zhGEVWojjjAjKKOqpg2m+N78AMfvnqIi5IuK27qbp1JNA5ya5WSq4OPplah7jghDDJRcxryjYKjZP/sqON+vNVHo1XHaNRHHGasSvW9FOHkHszvj+BudNHbPoHfX5tEs+EiDFxyE8WlqInR5nHsuAmqmYOnUlLzpGwL/KHxG3B3qI43niLOPKyMHcJ9nRDpiIftBsmdEnW1EZxMiAGfCEHVTiqV6KVj8Ccz9Gc28WAl0mozUSFliac+ryDzfBzs78ILp16pHjp9fOzBD+C+eBVRoLYZ9OG7AZIoUn0l9WVZbctqcCEJ0lyxJDWV2Q5bXVNl6RI2fugX0Ot3MV73hOzPAqRuzHUTm6vnsfUTb0W/VcUuUhOTApsU4JpcIIvueqMuNXzdgrgtjwMZoy5/bqpBZkKzFkHjUgA/M+pc6Fq9wbVfr+vWuv6ECQoQ+85EAvfGKnQoaO2aMSr1gUlFTbWOSSVe4zrJLl87qfZSbYlJTW21RtDe6ct4zGtkp/n3hH4TORxFRglY1LW8KqpuYWGhQTMCrQEB1Rx3izWFPyMSLskwPTmNjfUtdLbJ5r6GuYvruOHGW/CAcw6u78kcquYz45RB6xolZrhE6GUDHDl0AnOXzqhv4QAnju7DwtyS+jyRNcaVmYDmDJfnqwh3PV/UxhtbOzh8YAaLi08gqJEbhMPnE8Wqx6Qw1RMG17FNOfFkZLTKAYOw31PzREO7EqR54hYTv6X5QzsMs0sGkcU8k6epTjCReYOTaq6a87SHgpaconD+MPb5Wq3K6ugs90nIlayO+c8xzyGkfCYine1C9JobojXawPjEGE6ffhSVYAQ76h5sbXWxZ/8+nL8yh2pA67vqh8y4cUiiGrQStl6rojEyiTPnnoAX1LCwtKzux42oVK/o+yZOHqme103d9nKiEBPDQJ4kIFcCcQbJpJ57RPb8tQovI0cPHcMTp5/EuacuIvAm1HPBiHoGqKiFcENtu8wJP45ab11nRN3GhiSsOWodpx/ObtIEuFe4qxhiOnNKSmAgr9zraqKY20bJB2rsBWrxrdYC1NXaQUlb+olNna2Ci5dWcfFcD9XwsFrTp5gW3l7ewqWn1zA5rdrsN6Rf1Lgam2igOabWFydW49DB6EQLhRKd/T+w3c1w7tw6nGSGjzeIxxFVHCzPLbDSd9/xUbXeb/DaTFbcs7un8Bjm5RpcXbKDn9XkiowtuNRo1uu7m2veP+3vu4WFhYWFhYWFRYF9h4+x3fOj9304r7/74ld9KUbGJz7lY736K7+Wa9d22zv4lR/+Dn7vW97y83jTt3wPXvjK16HWaDKp+bH3vwtffuuUejYP1L+vtnD45M1YvHwhJzw/E5x56D78xLf98+t+RkTsD/3n/47jN93+dx5nZGyCyV4irn/x+7+F36PnU6odfNPzPg9f8fXf9kmrgF/+xV+F3/7ZH0S/18WH//rP+Yf64q+ebLP987f84M/jF77v32B7Yw3f/MXPZ+KcCGHanvCFX/7P1PP41CfZAxYWFhYWFhb/0PEcKICFmDW2kKxe1MHHNBOLWWgLXJi6a7l9o8cB50IFrI/oGJKsOEsGs7/DtrYFIadVRDD7l0hWPAMB52gOrVzLVRsgUgDbMYFCx1yfBKW5Pm5SPn6KhILebirqK60qJhKNrIElIOyyJac3REYXik++zswQBeqBuVJBEAGNQYova1exqvY9px4ayS6mH/fR4E1qGB2vY9fMLFbmFrDRX0V/MEBW9VEhJU3FwaYzYEXSIE452B97HpMUcdZFv+ajmvqs+qJ7sVXXarO4AjIb7ZPCiBREvsv1BCN1DCfs40V3vgwXD6/B+/wFxL0tSGy5l5OWLodxR3BjeBzf+tKvQjwI8fF33IjL51fwVx/6n1jdeYLbE6ZkWU3qtlCcvTn4rIPnjgn+U9sSuGQFDTVGnBi71T2I6j4CdY+6ZB1NY40Vvj48/tyFx/czglcTNXoUEnOt9gk8VGoB18xM02HFUJYhD+KbhII0r4tb1HVGKaBv1GvGWjItWZxfT71uSF9Wg5eO9YzfKg7ee8Vxc3W02VEs1OnmUh1qR/XpQPV3vVWFqfGZJBETNVRLMgx9NJtNtNt9vm5WQzlyvQnbmrtqbGjVsFvYqBMR4mYOrv0WWVhYEDyql+70xEmASMS0qr4vgeQ+ZQPUKhmmp0exvrGJoDKhvmMOVtY7uHNkBNNTE1hTrz1Xzb2krCUyl5NuwHbtSdJFo1bHnt0zOP3YRxDHXRw5eiPGxhpYXYs16cXe+GqNitWc21XbjmPX7il84D1/iYnJcbX9DTz/pXEoyuLEzVW3KTKt8FdzsTr2TScO4PY7j2NtYwPv/+A9bG+cJERQB7Lyqnk24bmRFM8p21tz2QJyx0iNu0dSrOmmk1yTjGL+1HMm72usirXal7WyaYlyFhRpYdDrs8MKUzlebnaviWdwn1DN44npKex02uj2KPGoqfowxdZ2D7v37FL3g5b0HpcDkDZ4WvGccfKLp9aXSdWHibrOne0+k7Gri23ccKyGmekxzM1tshqX7KMTfW5fJ94Ya2ymph15hjHri7FmpucJTyck0fpMZhPjE6Pw1f06d/EyKtVJ1Cu7QIKHQI2jQ8enMXtgBitLG2pcTaoxMYd+r8cKYF6O1Il818kTnwgs/FUfBlzOQshm/VTG73uOLnmA4bWLrt/X1+N5gfbkoM89vv9r610MeoF65hhVY2REPaOQE0eM9bUOup0YtbGK3iNBreqp61DHDyNJkvAq+XHMeOl1+9jeoDIYu1WjVZ/HDRIAq49l3crScbVvTa1HIX8/JqZa6jiSGOc5QktnVLYAksDE6mj68Xy2JqfERM91NAlsVzQLCwsLCwsLi2cLZPdMBHD5708HVBd3cmYWf/Onv4eFy+cRR1H+GZGaP/2772Cic/7C00Ju9qTW8Ft+9Q/xlm/4cjz12IOf6aUMoVZvYFKdd++hY3jl69+IV77hn6I5MvpJ7fu6f/qv8Ff/4+1sjU11kmv1JhavXMDSlYv88/53/BF+8u1/hpe85g1/57F27zuIX/qTD7D694mHPpbbbBu8/mu+EQ3Vrt/5+R/C5XNPqn+vSJIkqYRf96Z/hW99yy986hdvYWFhYWFh8Q8WzzoBTEFHNgmOYlbDMkmbplrdYowFJfDJPBp9RgHAlMi3tFTLT3A1eVYg0zaLotSFVg7nKt9cPZzmpJ1YcZbIPXfoaHq/gpQ1gk7emgLWrlH3OBzsls0yFCRuwmoqDLSqisgydumV8LUQxxTkTZgAdkyH5VroAhQwTuIENc9XD2o19Ko+Hgli9MgmMeyi12sj6veRqM9ShKhWaxibGcPErkksba+DrRGzUEiERN0Ht4o4Gah7UmWSvZp5bJUcVZuoph5iJ+T7ljIJUCMqHo46l6deE6lIQWIit2tpAI9I2HqA+8/fD2+6iaCr3qeatwHRHBV0qXxsVZ23nyGoplyfN4573GcfuOcdatCNIIra6vpEZWSIchelOn0Q4t0Q/azAUtv5VJRW9UugFT6B1mBXfKK6PSZ+SXlNJAaqqu/DAapkbxP28/NAq3q9oCBUizFVELfIRwTYCpUi+KI0S/PxW5C/kGQBvR/bnkOSC7J0WOFbjLnit6OTJnJiuDzunSL5IIqMBatrql3qTUzyg/wMBgOsra5gjJRVXJ86yb8HPLbUGCQi2Ffjq7DCdJlsokSBLOsPtYXuHUpqd6sAtrC4PvbOTqJO9ra0Hvkj4NrZsc8W9WncxmjTxciYj/MX1TwdjHFSymq7g9WdZRw7uR/b9z4hxLEjytOYJxiPv5f9XopTN52Aq469tdFHu9fF0soq9h3ai43tK6wCpXrpcKjOr5rvKxFuuvkGXJlfxFY7Qhjv4NiJBk6cPInHnzgH3yF1L2WIZLwueEw6qtdqvtyr5vYX3XYIFy+exuz+fZiZ8NU5diBEXQ1Uo1gUuj6fM1H7E8kt87grtcWZvE2QaSd5xzVOGBiad4mw9UoK0IznolTW6CzLnxmSPCms9IyQZiaDC6acAtv80pKbyVzte7I+E5k8PTOOnfYOYvXMUfGb6hwxlpbWcdMtN2D/3ilcJBtotY6lEOLeyXQNX1+UsAf3zWBnZ00tKWoOdceRqbUv6scYG63h8hUqd9BS98yHWGPrtmorbGm7+pOYfSfRltKOlJTQ6lzO0KI60UxMxmqsjKqxsYTNbge12jF1nDG1bReNegdHD83i1C0zWFxaRrM5jfm5K7i0vabm9mnVf5LYQ88tbPecytoneXHiKmHWLs9zdD/r/i7ltTEprP4jE+wKa4vpw5jX0wRmLVLPEBGRw3UuVUCpCCnzuT6XGYhj2q4CqhlM97JRr2Ki1cDGSozAkaODV3NyrKB6wVTygBKZ1PqUNVUf1ZBx3WnKhGip5sfcBjdTzzOo831vtNRxyFkkSXQWFz3R+HzvaWxzAh6vd1VW0fu67rGs50XZBwsLCwsLCwsLi88MVNOWfj4Z/NIfv/8ZP6tUq/gX/7+38M/1cOdLvgB/8LdPMclJalcii/ccPMKf/ea7Hrhme9r2kwHZI7/vyqfvEHO9fX/lh7+dyd8jp27Br73jo6jW6/z++Scexf/zL74YKwtX8Ie/+h9yAviOF7/yE7aBag7/h9/7y2f8/Ave8E/5Z/HKRawtzTP5e+Doyfy8FhYWFhYWFv948JzUAOY6oRTwBLj+HgUXuQYgBR+5Pl/GNdikNqmDUqwxt4nMCTAd3M2uQ8652oCwqNvrahIOKOuDpM5hQV6J9WFx1iGiK1dtFm0ypLK0QayKXW3TTMFDqvnnOb4EvTksmnIQnVQoCQr7ST4W1VvMpPUSEM8gdR6NFaFWo1A92ziBX3FRq9aRtWo4rR6AvVqA8e6AFcBJp4OBes+tVOBWPTTGmpiYGsf4cgMb4aqokFPd8mSgzp0hJlIgJcfITIpVJqT4MRbVDgdefVf+TiCB9EriaBUNWTNShD/joH+axAgfWMXW6T5CdyCqaAoEU3DbjVFNK9h0d/DR5AF8z++/BVGSYOXiAsJ4gEAdNwiqTBw0gobqiFiroUSRVL7fFLgnVasQtJEOpst1ucySuPAzUYr5TF4mUqa3T6q5QJIRqL1xzAogqmNJVp3NRksICa1QN3SqSQIolMCiZo4hLEZ5DBLp4bkBH5P4DqmrmOXJCJKI4Et7tdS3TC4TMetq208z1ug7k5nzaNtKIZ9TJhVEDSykOKvomD9IRTXN9Tb7fK9W1zbVQ7669tQrVPRaXeZ5fv5dE2Wem6uMwyTKra1N3xTfnU96GrCw+EeJ2dlZ3PX823D/Q6fVtyoEEVoek1dApL7vo+MT6tsdsO0wsjp/qeIoxcMPPYqXv/QleLx+DpHaLSZSNU7lu0rJOlEffuDgyLEDmJ87q+aagNXFT545h5tuvQ2+f0WtGaSYlKSOMHbRUP/Ar1SqeOiBB5j42tnp4cLFy7jh1M04d+4y20aL277PRDWtbcxDqjXh2PGTWF/fwoMPnMZLRiZxYP9hrD18XohKmje0ShdqTq7wtBLz+iHEp9gog02oXV3eXtcmdsRJwMzxJsGFnhjSJCSjfybkXN/htTtNhBRmtSmRpo5bSrTJOMEqtzDWU5Ws99oOmghtev5Qr6uqLyYmxjB/5ayQftwmF2vrG7h06QpuVP2yuLzNiTaeIzbWtC76nrSZ6sYfPHQAH/7YR9iSu6LmZ1qn19e3ceTIETxx5rzaR82fTlUUspR4o9cLtzSPSs6am8+nuTW2UT0TKUv129X6QnV3t7fbspa7DiuuaTwMBgnW1trodWd5HGVJBWHksnrZpecR4krlZoLVz6WcHTo++5SYddQxiXSQ8guU8JZoxwet1ia6N3OFrGeVtk7SgtYCs+aaXDrUOCBxMRHrLrmKpOLKwfdXk8eUPABWjIc8bhxPrMqldEdVjumI6jhSzy6U2FWvqGO4VPO3p/pmVHUf9W1SlGegdZ/a57i5q4yj1dVyr42Nd6YdXFw9ZhxrAW1hYWFhYWFh8Q8YVBP4/3YYRfSJm+8cImGJED51xwuZAF5ZnHvWzzu7/xD/WFhYWFhYWPzjxbNfA1j9RFGEOrS6UwcYc/vHTGyWs8yQYSgRakaxK8cylo5GEWreM39l2mKSgpKigHTFltm0pRTTK5O8RgU5rMos7J8zY9WMEgloLIBh6rFmYFEkgjyomWWG5NUOwXwceY+Ct65hlXUwmNueplrJ7OX9xO3LRBmdpETIxehFfSSuwyqc/vqWOm0Vju+jHQ643gephTrtDgfbK5UmnKCrbQ+FBKZjxhCSNWKi0EXGNRHBqhhALKdTHhI6aOppy0St6iYigtRcCZPg1O/qOjIflV4NFVIFq/OlqQ44U1Be7R+R9Ev9b25lXgfr6R5VxTmbVbik8MlYmeygwTVRiICkwDARoUTeMnmeScCaYr1GFUxWlWRhaoTcdG+SXFYbc4A9jolJGWDAlo+B1INUO1TqYlmKTI8DXTuTbIUoyC+WzxTsDrhNEowOOAgeRUYB7HCAPVafB1T3WZ0n0wMv44QHp1DUAlxnlwiBOE64L+UaxOKVTVTZ4lkIXdo2J6Oh6xk6pe9AJv2d5LU0CyUw30d1Hxbm53FrcjNiNX7I8pXbql6TtShZuVYqAb/HtaxdnXiRSH1NaCLCKIOFLJbf0Mp3CwuLa7G0uITnPf92rK2tYWFpQ32RQlZjkiKWloOZ2Vm0O6H6PtU4UYNI3SSpYnFxlW2h9+3fg3NPz6mvWY3nMBcyB6deionRJlsCP/jAqvqKVlGpVrC4so3jat46eGgWZ5+aU/Nrk4+bRhlGd42yJXAY0VpQheu7mJtfw6mbKhgbG8PaxnY+f/g056RUC36A0bEWpqen8dhDH8Ug8tQ+G7j51tvw5FMr6PVIZRlrUpMmZkq46aCm5lRKiImSOE9mykwNVkdoOt7WkfUhyZ0wHCmloObqipoWRyYa7Aayur6u5jEiCtW6kFZ53nGNSwgKxwRCvpaXlnRaE33OykmYpCaSslGrMqm+TUpmTlKjtvhMXD762BN4xcvvwvTkOBYWt8QOmhKhYrFlplOMjY3wGrK6ts4kZpQ4CLwa5haWcOjoXkzNTGFtZaDuQcprp3EokebpRDL97MPPL1q8XK4RnbF9t8PnJDK11WxgfmkTlaAhamF1PBK5RrGLxaUO3vPu+9Dtd1GrjWBrS61ftRFZt1Nx7WDil23+JRHPWG+Lq4aQoPl7+hGFLbS14wn/58gzCZHC9PwD44SC4rltZqqFVoOGe5vfr1BpiXqE2X0TaDRJO9wxT3hM1HIJBleSBtJ0ACJ+TRIWaYJbzSZmZkaw0O6i4nbUmhWjrsZYfQSYmGnxWGC1OHuZeFybuV6vYNBTo86j8S/Pn452gsmfMVkR7uVJebny2cLCwsLCwsLCwuI5wuy+Q9hYWcL7/uKPuEbxXa98HceE7vvgX+Mj734Hb0P21RYWFhYWFhYWzzaefQtoiOkjwdS8FWLTKxG7JiBqXhcWyKLgdYvXmpAsc7VGlcnElWN0wG6u0B22p3VykrlQlJZJZ8BYSAOFna98YIhlQyZLu5jUM3FPY/GIJFfYOKb2IZN7Wv0DrT4xylZXApMUaCW7XiLkpN6qkGyjo01867/9NwgHRuWiVSyp2GCSraGUIM7Q6XeZoCUNzdSe3RibmgLFaOn4FKw2ZGamyU4iDU3Al377nhCURHQSqWgIctpNgtTaKtKVfek9OUamCXKJ3/M1sbUk2HKReiumoDGpY1kpnbH1Jd0tuk1hTJakMbLE43qVUTSGJEl1kDiW81BtXyKvY2kvkQYUkE9Lip04lf5xskyT9qJcIkmubJ/w31ECJoF5PHpVVGoNsVPW6nA6l0kMcLTCW5S8DhPfZAXqpB6rmajWJTS5zsQqKXk9psllTOh2SJBZxhERxXR/RX2r1dlUs5jr88Z6bEst4iSVOtFijU39K2abwveW7CozUe9KWyXAH2uf1H6/w3WXUfUkAYGC+jweZJxVKzUedyQypmuM1TX55juRFTbkHPB3HX2fM1izTAuLZ8bc3CIGnUXcfsdt6N97HzY2e/xdJtKOsoYmpib5H/+UPJRlkkgS+HV2Rjh79jxO3XAC8/OL6A1oLiBLZ1crZiOMq313Ottod6jWegMuJZ6oeevChXmcOHEEV+bm1XrSVTNCnVeEqckJnncoOcnzq+r0AbZ3+tjaamPXrmlsbG2iUqV5Q88RvELFGBsfV+cfYGVtR51jFBcvr+D25zdx7MgxPPH4RXY7yGgOpJk67uPATBPPu+sObLU3ce/HHlJzkAdJjpK5MNVrsMtkaybzniNuBzqlh50ojh45gDtecLPqqz4+8MEPYnm1o87f4DVCFJ3xUPLW1QRwXsrBEQKVFiMXoi4lW+VGtc7JNTEvkB4izrfxOCkpCkNsb3dx6NAhLK88qOa+AZPXDrt7pEw4+oGLbr+NQUh22XV1TJa6qnvSwU5X9cOBA1hbOg2vQqlCHjudlBPPdCNNPpkmw93CxYTX3oSJdVFTR6jVqtjc6PA9ovXLY8ttl22m5+a31e49Xp/Y8oJI1NTXVtkm6c7R64Y8j3G/6GcVqbtMEJWvuHg4+bpn1jJahFL9vEFrsTi6UKEI444SqX6bwcVDl7F4YQX1Zopmy8fMHjVmTu1V/RFy8pSkkkmJjGq9pq5jm8dnr9tWn7VMygBfOzl03HzrIXQ2n0AWrWGkOYrWeAMHTsxicnpUXVaf712mSeyRxgiazTr6HXUdnibeS3lKxhqcFcJs+1wkNw0/M1pYWFhYWFhYWFg8u/jG7/9p/MCbvxRhv4//8tPfzz9lTM/uVdv8zGepdRYWFhYWFhafy3hOLKAdrRyEIdJSsenzWHFqmFOC1jiaX1lh38eUZaqJ2+TauqxG8WvIYnPeHCVfaVNX1rx2S0HZq9vianJa7J2N4lET1sYuk9pC9ptc2DBmy00KuqZOUhyN49quaDc5Cm5C0xkTuaTCTNJMk5sRKkHAgVkiE41y6M7n36J2k+OmZPHLFtoeW1J6nrZqdNLciFF6Rqy1M90vbn7dJgBsSHZnqF/YXbI4iChAqd4ux4o14co+nalWzLBOSCy9KcBv1LSs3TEUrowBajf1K2l9/MTYGev+diUYywS362lCJJMAuVPYjCbGUjnTxPTQgNO/yTo5FdVSIoy11N+FXAPXuCWVchKzMipOIyFc5fZgZ2sblVpVq3gLy3AikS9eOs920zO7prG6uohdu3ZhfnEBu2ZmdX1d6deFuYuYnp7h/ZaWluAHojSqVqsY9EPU2ZK1xtfi+x42t3awvb2NPXv26MC/KJSEMEpYmUZsy/LyEkZHG7yN3BuxHjXj1lhiE+IY6nwBmnUfq0srGBk9wKpjcZMu6mFT3ehGo4kwjGRcurouZKrvsf4ee9q+le6P+e4MZWRYWFiU4OMDH/goXv/61+Lmm27EPffcp74uIX89iRKtVTz0+gNIKgUlowhZWquOci3aY0di7DuwG2fPXuG1hdT5jq+2U/PW+GQLG5vr6rtP00KFlb6VyhgWFjdx/ISHG288jtOPPsFWyoGa0Kenx7G+vqm+r2q9ctS8o45DyuCnz13AsWP7cenKRYSxgzh0xLaZ1rAsQqtVw3a7jd5AzQtBEzs7HTz04COY3TWLin+Z59VIzZE0h9ZrPm6/7Uasr81jz/49mN09gctXttW56uIIwWt6mq/hxh2DXRRcXZNWvRuo14cO7sXZ049gcnoE+2en2Vo5RcRkNq2LSZLpecjJ5yeTzFSGOITEan6ewLHD+/Hwgx9V81wPE+OzvP72e9T/kgBEayWvcHGGp85ewF133aq2a2FlpYPAr4pdM62QtAZ7GfqDHrjSsep/qmsbUZt8Ukkv4OiRQzjbfBoDSvbxqjJfX9UyfqYgJbSZS9Pce0QcKvLEoT5GWjWe2zttdT/VfaASEkTSkvNFRs8JXoOTBKjmsyTs0Jrn6XU1ERI3dXV/6CSuRFTYcl3aPjvNtDjWyZPaXF1+gB1PfEoQkoS2uK/uSE+1czzICVha7SfGm3jRi2/CmZGLGHRjTM/UcfSGvWiN09nb/GySMmXs87hN6FhU6leNu3434b50sCl9TUf1Qhw/uY+fdRaurKJRa2DvgX3YtX9KvdfT1s9caFi6NtMJU/QMlelnOXLV4JISTu7owv3nancLXW7kemPIwsLCwsLCwsLC4tnC8172Kvzue0/jL/7gv+D+u9+D1cU5TkCdnt2HF77ydXjTt34vxiamPtvNtLCwsLCwsPgcxLNOAKeZWEKW7ZRzy8MS4cr2j56xcJRaeJkOsjIBZWrsMik1rNx1r1LVmCCwBCzdUmuyoXaY/ct/Dys/RJmbmZqrJXI4JzxNEBFGeVmoh31NaGZsWZwwYSi0b5pbSTMJro/n69qwFd/DxvoqpqcnEUYDJggH6mEwcaHJY107UbeGAptkQyy2hh48qmtLRKEjBHqWK0ILRSzXGTZNLcmcnfwemb4pVNBc708rn1khnOk6zrSNY5TT0sWOG2qC2eNAc0YKYMfP7Rw5kAwKaadCUg8psIVgzrQ9tpMWVo1Euju+ECVsq8w3SNro6U3iRMhL/sNL4cntk4CwZ8juRPeVfO5Tv2cB9zcF1bvdDiuxmyMtrTST/qChTAqlH//xH8PX/vM34Y/++AH0+3382I/9GH7pbW/FD3z/D2N7Z4MD8oFXwfvf+x686tWvxsOPPsJkLylonz57FiduOIHHzzyBu+56EW695XY+Np3vz//8z/DqV78G9913H+684w51PiJfxtBut1Fr1FEJqnji8cfV+X8cv/7rv8rHY2V5Gud1I5GZcZ4Jwa1e1upV1Ko+OjtdhKoPAyZNfLhEElCtZEpA8KvqekeAnbYo8dI4t2zn/0+NAlxsSbkctx4rwwy8hYWFgeur+Ttq4N6PPYJXvuKFmJkex9rqtvrupJgca6mfOh7Z6YjS3021CjMQpWwSY2l5lYnQJ888qdaLBs9lNH8FFQ9TU+N4/LHH1devor6PrtSndRsIaZ556jJe9KKbcPHC09ha38HoyChazRrOPrVOqTdqnnRZCVypjODy5TkcPboXe/buwtmnL6r5ocZkGa1fNBWMjjWws91Wc29dvV/nefWpp87j4P4Dak4Cep0uz+th3MPhY0cxMt7CBz/ybmR+gsNH9mNu8TFxYcjEPpm1wibTprACEYvmLGX3iZm9U/BqLh5/4jT27dmFU6duwsL8BlY3qaZuiDh1c9tes+4bFCUkJNnH5cQe+olw6sbDWF48jcWFFXUv6lhfW2cFMM3ZqevpdUFdYlbBxtqWuleruPGGY2q7h9Q5EiaSHa6n62BsfFStzX31E7ELByVkSapYgIXFFZw8cRTNZhXd9YFae2oml0rbVWs3amg3Bsf4WDiyYDk6CUcef/gZiRKOOjs9teZoNTik1n3MtecdtgEnZTAcSdMi62NHnVfWZGrbQGyQtdOKcLqedrVI877LdK1fznOLpEyA9KS0ichmWjdi1bh+N8b2RheTs5Pqnm7ztfPa43axZ984ds/uQqT6JwhI6avWFGzz+OZjwdMuKB6PxzjxEYY+2luRWn4qasmmpLNYJ7WlqFRjnLz5II6dOqjeqap7UOEawBlC3bc0BgK+jjgWZxJf17dnkTdR1K70jzDebk7+0lhyzTOHTWiysLCwsLCwsLB4jrHn4BH8mx+wKl8LCwsLCwuLv188JxbQREgiJzwpuBbktefkPV1vNNXKDK24zRypPyrBXSH7pB6d5ps0SVm2U8y0IpRtamHUvhJMldheplXHRkWcs6DgYOBVwb+CONV2z2mWqzJZ16rVIixwhlcEcImpTQ3harZLdL1gJ/+Rff2cXKRtarUa2js7WF1ZRmNkFEkcctAyZNvhoj6yHEMC6axq4belr7m1ju4XrXIpCGBHc6mizDV22bnS2RFy2yivDaFNal9HB4/FRlqI35wgdMRKku9T6mpFtFZBOxkrfolE9ByxChUSO81V4I45FtVO9jSJzQppn0VAnmkf2y1rJXBua8mVEnV/uPqsouaNc9VyYfudZFpmZZStakxKLV4H/X4X6+vrGBkdhR8EvK0h0WmnSsVnG85zFy/g8178YvzR//gj/Nmf/TniQYRz557C9s4W39Pjx44z6TsyNoJz58/hjf/kn2BmahqXLlxgtS+RO512GxcunmMbTzr2qDrn4cOHsG/vPrzvPe/G3Xd/SO33JvzW238Le/fMYmJiEm9+85uxb98+VorLd4DsXD1E0QB5kgPXBJYx56vv1/bWFrZWdtQ4aOJYdBxx2kejUddJEkZzBz4+jbX11TXRI5YTJfKaifp7gdL3zjLAFhbXh5pbmqP70O7sYG5+GXe98IV44GP3YXFxCYf2zaDf3US7Tda9dV4zxOrd5zkJXozl5TWcPHUQJ44fwPkLO7xWRmrdoLq8ZPW7sbGl9hlBSHMZ59ZU1GzVYrK01x3g6JH9eHDjIRw5cgPCqI9ut6vOVUMckXo04LkoyrqYm5vD3gO71DkuQfKHyJJ5wCrX5kgdly7Nq8mdNMtkE19Br99hq969e2Zw9sx5PlazEaj5az9On3kSvTDEyvoqbrx5H2p1tX034Wvi1YUSn1xN2WmbYXaw4PVRkmymdk9gcXmB5/mlhRUcORjj4N6Dam4+o/olJI2wOqcvpSUwPFflyUSQhwUmf51E7buAuctncfLkfvX+MqtSP3LvOZ1U5epEM5ePKc8tLhYX5nHHnTejqa6h34+I0ed7FAQupqencPnyk7LmcoKTEKWkayVSmBKJjh45iFXVZiF6CzMJo7rl5wb9LMN21DphTspZZGLJzwlYLs/PS8vbap2qq/XbE9KW1mWarF0nT5QT9TbTnZJQwCU3TPkHr+SU4vCzlXECMc9F+dB1dE14XiPpGU3245Vdve73YnSDEKuLK9h3bBxutcJ2zZL+lvIa7qr2VevUL2RJTe4SLvePPFMJqZyqNT+MHCaAo5DWnx5W1PjdtZ/GeKS3TVlZTIQvvECcRnilj0rqXyGf6YfGkFRmcIvr4nVRnjtd34GpZe8yoV9cp+V/LSwsLCwsLCwsLCwsLCwsLCw+F/HsK4CTFCuLa2hNTMGpZojiiOvWFfVttZMwq3alziupYQiOIR6hSVsHuYUiBevoZdny0dE1UrMS+WsIPwlqZjn5SQFRp1S91NR4Le9nzlPU/dX1hFnEK5+zZofrAYoilVQ8MGpTYT517Vtdl7ZUe9jULsxyG2Zt9ahej49PYWt7A4tX5pAkkbSX1byxbrsmyiH9yPbAOV3ri4qWVa7ukDpKSGCtmkKcX7sQt0bxa+wRrwoGu0Y5bBh4rdLWmidRMRly3M3bJ3aZ0EFyUd0YO0nTJ4bMzu+DVuLwPRiy9Xa13WdxLmMfalTYcLPCWlSTlNTXXinoLUHxTPddltuRdzod1e/bmJnejZGxca0s1or03DabbCUdvPGfvFHdpwn8xV+8E695zWvwoQ99CNOTY5Lk4PlqvwyB+i3tBdczXtvYYIvnwK/AdwP1uYeJiXEmgPuDPnq9PmrVBv72Q+/G/fffj7HREaxvrGF6agrHjh3Hxz/+cYyMjPI11OsNdNodvmaqGZxlxQhw9DiV70fCNtxuzUcvaqt2BfCqUjM7DPsyjlX/UFtjri+t2l0JkKj2mDGQGetPvul6nCAtKectLCyuB1JeJqDvexVPnHkKs7OTuPP5d+Keu+/Gnj0zWF6cy79norr0WN0Krk9aVXPSNs6du4RbbrsJ6+uPoN1R83YaYqQ5jl6/z8pGmk9cluQ7bKlL5GV/0MbHP/YgXvCCk9i3bzeOHtmHhx59EuGA1pOm+v4HrBgmJ4egUsXC/BIOH92Hvfv34sr5tmpvqrbtY2ykzkrNTqcLItloHiMCN4kdnL9wHjefOoW5S1fU+ULUKg34foaFpUX4lToWFtZw8y0+JtUcd6WzoS6pAipvzpbFupZ8aqoJyP+x7TE5FkxMjuKpJ59Q+1RZzbm6to3jJ27A6TNn0Y96qs2+JABxrVqTlAStftXlDjJdrgFC7FH9+Y9+9B689oteihe/5CXqmhcwv7ACrzLKiUNkB01sKtONWYxAzcsrq+vodDu4447bcd99p6Xdau6rN2rwfB+XLs2pa24KyZqvMeoeRhnOPvUUbr/5FoyOXsJGP9FlDaBVz45eD6FJbJMQ5pi0Jh4Dnlon6BmjUatifGICZ568IgpxrkUs9Xn5ijNJBMvLJTBBSpD1UdY8N1fESkHcTCyhTXHczBla88UFpXBbYQeWVJLbaBkYDFIMQhfzV9awd3ESew+1tCJX1MicSEZrSlY4lMjiLi4i8nTksQI4Ch22rO51ErUWuXjysYsYn74BlXoN8qSliXF9XZleg9RKpde9gK9frstFGGWabJf1iqygM65rbZ4dpO8lqdAZuk6jHrewsLCwsLCwsLCwsLCwsLCwsPhcwrNOABOZFLN6pWSjq4lP/pzqs3It3UK9U7Zyzo+jI8WZictlotowql2ul8oW0Tqop4lG0apoMtkoFznuqS0Sc/Wrrk+c81kSWE2QaFWIW7SZlS0OklwpKwpj8WfWClaIzbAEuaXOLHLCrLBhZjVMqkmCGKyGphqyFJycnNiNsZEJZEzuSfCTbJidrKKtptVx2frQyS2lTR96nq/Jcke3wdS1y4qgMfVbFudkNvLrKYLyJhAq+5r2S1DdkKhFf+U3C2ZPQ8BmEnnV96og2tPM1SRllgeJ09QQ97q2LZBfg+OYw2f6fqX6Psst4GOV1ahmLHkOYiqUaZSxdI1pKCODj+MwaVKp1bBnz15MTc4g1ucpk6B07l6vi10zu9g2leyZDxw8jEE/wqFDh9FotNQpRAU2UOfrDUKcP3cRr3nNa/GRD9/DTXrVq1+Dxx8/zerg48dPYGx0nI8/NjaGGXXcP/mTP8H+/fuZ8G3Ua+p8IQ4cOIhbb70Nm5vbOHv2KfX3YTz6yGnccOIE1010uI5iKIpmGHFzxqpmTriIU7aqJrtTsvSUGpGuJr51HwUeeu0+2jtbaixKDUlOytCEB5BotVaKwHVy9TTK/W1hYTEMV60zlRh+tcJ2wR/84D34wi94KV79xV+C7k4HDzzwuJq7mkiyOnyf6CxKHkp4HiNb5SwewZnHV9gZYM/eEVw6dx7JoIsDu45iZytS+6n1wFfnyAJ1KqonK04AjWoDc1eW1bzUxe23P0+tswOsLu3AT+tqTlXb+4lOCAKTrDvdAS7PbeLGm27C2vKH1TnW4bkhxpoHkPQqSENt4RvT2lxDUJ/GymqbV9hDR2fx+GOPYHykqVrcxSDpq/l0HL2NFJ3VFHumR7G8dJ67I4tn6P/U55GaY3VyDZOnDpOFadLD7slJNCuB6h81p7kTiNWS+tTlVRw4fgwnbzqCJx55TPVZH1EWMAksFKjLfSf2ymKNzyUKeD0jV4mKOlET61ttfPS+C2ruPIbTZ9qI3DFUnIaQqmyfDLEO9n0M1FzXC13c/8jTePlLX4Z9CwtYnJ/n5wxaI3qDGJ2+i0plVB1bzfvugC05qExFrTaB1dUd9NU937d/GsuPXIRfG1H3KJD28HJL9ekjvn9Oqm2/ySuDnjfo2iKHrb7dpI3p8Rb3z+b2ltqvpZ5JKohCXf4h0wQnrZZUt9kRVxH2wVDjL1Z9JUu5x31fJLUVKUNMyjqZfpaQ54M4kecnV9fO5funtvHVa0/9Gap+22irpyQnwOMPrmBkpIHWBF0bKbQb6ndbXU9HJ2PV1Bmq6rooYa4vzwbqb659nfmSuEZW0KGHfjvA4uUMF59awpFTs3A8skgPeRVynKraIxD3EPSl/zCixlNNtW1bbUHna2GgxukgIQK9yj9JnOpHNZ9Jb5eePahEhBvnyYiy3hs1sYWFhYWFhYWFhYWFhYWFhYWFxecWnnUC2PMDHL/pJLOJREJxoM0tyF9CQfQKOVqG4xRq3MxoRkpqXSGoCoLOyfdDrqYR8tMQmm5+PmPljFx5U9QSzlUgWvmZOgVp7ZZIZqM0ZbvDnNjWbXONykbIs/I1i/Ui6zK5Zi04AC42yqTIouAzHZn6jywnjcrX852r2tHigDErnfJrHybR8/4x94RJZhMEzrRaSNdrzgpVTLkvygq1MrgmbG4b6eod08JCMRP7Ra5nmFtkG7VxlpO9pt1mxyENUuncRoXtQEhjc8/K2zmlYxvItnSfI9XfA9nOc7C6vsVW2BPjE2hW6+iHIaIk1Zqigvw1KnN6r9UawU/91H9AqLalur1f/dVvxFZ7B1/xVV+NTq+viXEhuv/Fv/xXHGS+cuUK3vCGN0hQPY5x6sYb+Wj0mi2pdaD9Na9+Df9Nx77tlltYsUZqObqkKIq4DiZt+93//nvQaPg4f/48k0Zy/dCK6KQYY44QIEEQcJA9ikJ0utsY8WtI6Zylaxuo45MimOsGpwkrz8VGXOutXEkc4P2GbNfzIW9hYXENHARUOzeLUK2OIexv4+4PP4Rbb70V8/Pz6AzUsutVhTjUSyBZAbNGMnWYfKOar5cuzmP/nv1YnifFcKzmrBYunX4KNTVvhVR7NpN67452HKAFpdYYw9NPz2F8Ygyrq5tsm+z5VCfWlzWH2yfq0UpQx/zledx46jAO7NmNy5cuI8r62LNnEm01Z0jbKmJ1TOupmneisKfmoMtcI3dtbR2Hjxxjm2s1DaJCds9uhnMXLuP2Ow5jZX0Zcws78INYk9yB1K11jCNEyutCouafvftm0e501HUP1FpVo5Ohq16fPv04XvTCO5FGKc6cuchzHdW5pbWTnRdg1ogi2Qypsat3eC2t1kZw6coKFhZW2N4/qJJ6N1DzmknckvWY1nxK9CKidWN1G2srq5jdPY2lxYvqfnoYaVWxsb7Kcyz9R+u2UZyS0jVRaw0da3FxFdPTu9TcegbVSp3P5WrS2tSkTXMyVreVnkcy80yS8pw/OjbGDhFxIjVxWY1L22RSR5efP/TyXHY/Mc8A5ffy1+4wEczzemnxHXpWMqNZv6ZlgBTTUZxB3SpcvLCNauM8bn3eAYxMtNSHfZinI1FVV9gyenH5EnbvmkKjXtdJeKJcJtI9UWM4in013qg/PTz20JI6ThUHjk4hqA3Y7lmeDkQRTEvd0vI612betWufKLi1vTTXV1brK1k9F88driQapEKYs/04/XbEEcNxXe3y8ezOABYWFhYWFhYWFhYWFhYWFhYWFv834FkngClWF8UxE5r0Q4SX2DMWCosycVoOvJnaumV2ydTNy4y9sSYXDXlqSOAs8bS9ojNEuuakHrTtorEsdortitrEXkkRnJWOw6aKoiSFVvjqmsZaWGP2yCntlFXOCTJdc1cIaaqh10U/jEvK4FQHXTNWDZv6uETceYHHAVJHH9nN5HypNkPM0sI0OzXnlsgypG5vgnAQqvsxYBI4M4pZ/VtU0dpKWiuUciW2vihDwkpXaLJbWzebOn0oBVALO0ljNVki2VmOI32d6WND30dCYOoZyonzNlDQmiyT2fI7igviOENBasvJh2ymsyjJLTIXlufxkY89iI2NHbZQbdYauOOWW3DH7bdipFHl2o2GXM6tunVfEBFLxIRJMqC/qXlE2hora7G7dDAIB3yNZJtKQXyTaCD76HqKROxrJa55n/al10QEgGs9Jvz9ofqdtC2V/w0q8j2I46I+dRInokTPnPy9iYkJ1TayXqdakXV0dnbQaNSQ+S4TNIYgQCL3pxL4WNvcYtvo8r2kaxCiRduKl2h6WwPYwuL64HUoM3VXXVQbU5xo8rH7zzAx5vnjPM+7IsUVEtcRGou/b2qua3gjeOrsZUyOjWPf/n1q3lpWG8To9Trw3YY6fo1JVSZAU23qQHOt38ROt48Pf4SsiyMmgMmhgGrnolxKQH23K5U6+t0tnH7gMRw/fhArixe5fvj0TBMPPvwkyUDV/hX1q8IuFTQfeH4dFy8tY2J8Gi952auxsbqCcxeeVG1oqvZUUan6uHx5Ebv2jOLEqVOYX/yIOi/Z1tfZgUCUllL2gOc6ss33yf1iDOtb87xO8ttspZ/g3MXLXIP91IkTmF/YxMZ2yAQpWxdrlxFO9oEmNXUBXTp2qpNhiAQmhexAramuT/Ouz0RvxnbR6n7oJJo0CflavZQkwRkW5xdx882H1fXUuaZ6qxVgcWkZgUcJOI7JF9NLUabmaLEyXl/bVPfsAGamJ9T9oueWBGJ7LISxJNYgX79yLpatm+V4vlr7yUZ7fX2V1cWs9s2cfN3wA5/7gclvp/zMU5C4xgUkc1Imnc17fB63SKozxh/lhKrhRCvwuVP1t89OI1RKIEN7O8WjD6xjayPFDTfvwfTeGLVaXR2qotaoFDtbbVy8eAHt7ipmJndLH7CDiYdev422GsuZ20SoxrKX1tDfpvHtYWfnEubnd7D30Lgaiy217lHjBthpr2N1ZRmXLyzj+A23YteugO3PSVFMtYq3Nrb5cYS+f4l+3qKkO0r44kssXZe81smCWekhzsLCwsLCwsLCwsLCwsLCwsLC4nMIzz4BrMGEVhiymilOIlR8b1j5iZIC5ioFT17j15E6fhR4LsSiErwkq8IUUj+Yaply1BiF3XC5rh3ZHps6cFkReeUap9coXK9jR01K5tQRKhdeUV8vTUUpkznSXhZYwrQ5kaCpJpd96oc4wtzcPE7dfGt+PdLOVOoJgwjzAXr9Lja2V9EabWBibIotEF0OxKtz+322TaTtkzBjJZK+4CHlKtVVpNqzFOScmhjT/eYhimL4rs9WwfIe2EKSalaWg8LGplt+3FJQWddFhiadKXhKAXjd/44meKnPU11fkGruhoOYg/JMRJINeCp9zRS5SILIEJJvTWzsqtNkSMXdbDZRrVZz5bKxtaSavam2Ks7vO9kjU/3DoIIrcyt4z/vuhlttoTIyCbr0TN2Pjz/yGLwgwE0nb1DtamJnZztPXKDrL9tAS53qlElfscZ28nrRop4lW0nZj4L3rDRyXZTVWGZcmiB+qm1HY06Y8Fj9y3WLnSKAX+zj5ypjIkzMfeAak5qUzxKpzVypVLTaPMH45BTuuecjeN2XvB61mpOT7nTOSrWivgM11Lo1dDptrn8pCRfmO6C/L5mQwfI74ZqfFhYW1wclTNCSRDb0NE/FNLdVGpzokjpUd9vl+dLjudfXatCCmGWVJ72fVvHU05fw8pfdrubt/Vjf2NSW7x7bBfOc5IrfBLtWJKQ8JuV/lW2AiW1k1Wisk6V0Qg4nUxGJqfb1vRounbuMo4f3YdeuCXT726rtMbbbW2qbJpK4InVUDYGok4AeeOhxrK5vY2dzA90ekdA1xGTTS+pcN8DpM+fw8lc8H9Mzk1iYX+d5luYaLuVAyWB6TRT5M9T8W8HSCpVNcKVttJao377XwCOPPYnJiRkcOHgIG488zoQ59FzosupYUlOYxCU3Cp77fHZ84P6n/qVkF9U3xk9CiGjOPpKEKJrLU7IklkQlV633c5cXcOjgBI4e2Y/HTm9xoszm5pZqU1Ud09Ft1G4i0jm8Vm5v99V6l+L48UN45OEn+Vi8eerAeDW4uqY9C3L1fE9X4WTact+T8bO+sQEp0yAEsKNdN8zTDY8xFM9WpsRG2WWlnOxGMM8J+XuOViXnrhflJD0Bt5vXWd0GV93vmMospHj80U08dXYJ47NtjLRGOAktGgzUWtlBVd3ykzcdRKM+oVrSVftHcNV1tNttbG7tqOcZ9XyT1Vn1TeUuKLlpc62Njc0lPPTwBYxO1FGr0vNOR322o55dMoyNjmJ8dA9/DyjRguzEqS3LC2vw2Qrby8eZwz+SGEBjmPqFxh1VbXD1uKFrH66DbGFhYWFhYWFhYWFhYWFhYWFh8bmB54QAZjtEIm09sTmmgCErMjBsRyiELYUWkyG7YQo+ep5Wl6ZyPA72pVrZGkuQlkPS6vM40YpNqr3oZKVgnicB65QNm3PlR5bXux0OdBpb3qtfE2FHJKkobVyjx0VMdQ2Z8PWR8jWILjJOSWUbIDJq1EzOubq6ij17Z9Q7YksM2iYS+2euQ5il2A57+Njpe3Gxf0U1O8QX3/yFODhzE7LKANFIB974+xCghe2Lz0PFqyJL61xXlxRLnpcwiZpQVcbuNitjnrjSxsoDq6xCIjNFNwsx2gA+/6UvghsN8PSFRbXNnGqPxwpjqp1HfThad/DiF9yCULX7/IUFzC+vs2UjGTsGZCXqOaj6Ke66/STSWoZGt40rZ/5K3Zsu31ciG0hN1on62Hvq1ahP7kccRrjn/iewMxgwqdCoUiBd9Zvqx1tvPIap3ZNsx/zU2TPo7PS5XiKpt2pBDbN7JtU5hUypkOrHlUC5BK6JWBEynoLPRNaTOvrC5fN4+NHT2NjuqQ8bQuTTfSJVkDp/pTaCM09dxKmTJ1m1TrbJTPzm9Y0zreIT8jdNhahh0nWozjKNkaCkIk9z23MzvgwRrKldDvaTHSopxQNPCH0hZ029Zqm37DFXEqt+ojbr7wtdY5JqZXg6ZPcJrdTOyEJc3fOVlctIInUf2ltoNmtII1Gl01c/JVkx3adKnUn3uNNVY9Hle8tEExP7DmKk2k47Y5W2qQ1pYWFxLcRVoc/kLvOmtGbQMuQ6OWHLSI17AVeu5flV3BAcrnMbVFvY3Gnj3KVljI/V1Fx1Sa0pntSTzcRVQuZAX+YDV+rqcr1zWiO9jOuv8uZxls9J0LXoY15nK2qKbeKppy/i8NFDav7tYH1ri+dZUsO6aQWUHiQlY7Vyl9btRM2vF5d4rSAS2XHrQqbStaj5ZLu9ybbLN950M9bW/pbtkclaOYWZ38BzHq39Y6NNtFo1bG1vQ+rNU6dV1DljJnWDWhPnLs7jebffjoWFBaxu7MianDpcn9bUe/DyxBno+QqaCBTi0tPEMZcsMOULtNMHz8hU95bnV7XGuWquTPs4f+4Kbr7tGNQSgXa7j24nVHPkiCR3Qd87T7tRIODjUXIV1W4/cvgAHj9N6uhYlNj0zOIGMn8ykW/spwHo2ZyugfvUd9h2OolSVi8zqZ2adUkUy3KNaZ5sVFg+a6cP+oyvXSeFZdkQ0VmU0ciktEMp8W04Sc8R9wdyj3ASfs5w1b3xnYTHQsVvqPvrYmPJx+aCamfscl9MTo2hWg/RqE+qfdSzStaDKR1Bzz1p4vKYcOj5RR3Tc6XOsOuqMeeOqGeSGtYW6SmGiPkKRluzaE2kqFX7qm9qkG9SKiRwRjV/fU5+IFUwldKgZwBoy21KoJLrEtLc0clZZm1OM5vUZGFhYWFhYWFhYWFhYWFhYWHxuYfngAB2OPjH9seJ2OyxD2NmDJIF5fp0Qvh6+d8ShHSGtoUmusoBzIKkK4KZRgXKlpA62OgWuxQK1xLxW1ZaXq2UIQKQArpcd5dlI9A1UyX8a0hAsYZOWeXK1842wBE8rVRdWVnmdpI6k66Vg46JsQ+GqIeSGHMbc+iMJHCnJxCnCe5bOI19e4+o7TPUxpbhj30AgTOGy4/MYO/UTYgHqaibXKqWRwHkAI46DvwKHj67hKdXPOwaPcTE5lq/DzcANjbWWa08iFM8drmPLm6A31T3YRCiHVbUrj6Wl87iLi/D9naIJy+uYO/hU1he3UBzYlz1ZxXnr2xjZ+Up3HariyDOsL78cbTWPo6RagNuvIJO0ESzv43O5mV067vQvHkXLi7sqDbsRaraNjZeV301UP3RwMLCHB49u4LJ6XGsrmzjT955H1q1XZhS2+y01TFCIjd28NVf9hrsn51BQtbGWpUrJIIEuFkRlonV90ang/d+8F5EqYvMrbCotlGvodvpcXCdaknXWi1st7s4c/YibrrhKCpegDiKuB9ZjcX+oZ4eiUWCglGsX11f0QTQ09ze+9qgsi4ZWbhpl+sx5se8ei9tvqzVyKYNbNGcGgKh+M4E1QrCbj8fozQO+wNdq9gT6XkSx5xwwIoo30e/30PSVn1TU+OT61EL/05jMFeXZ1qdeJU9uoWFRQGxIpafhNS/rhDAnq5HKrVYXVk/ErAFsaPXKar/TWsH17rnY9Xw2BMX1faJ2Ac7dbVDhd0GOL0pM+sfpDQCNcCRerNcC5fVnbJ0OTx/JPm23Fai16otLK11cOSGEYyOjOO+jz/A1s9xLMeTZKxEq5SlbipdEJerd7QTBqQub5JpO3rVziuXV3HTjadw4sQxnHlyTm0vNsmUsOSY8gOqPdOT0+j32mpd2lLHr7DDRcolF1xOAPLdGtY2dth++a4XPA8f+dj92NrpcZKLGFA4fDmcMOOIItRBYXcscHV9X73m0/uuuG/w/+hGmMQWci9R815ANZIXNjE5tYmDh07hnnsf4OtKMl+7NDh6LTBlDhxRdKu35q7M4+TNh7CHaitfXOUkGyKsxbXCFXtqbqVJNDPOJDJHk+11rV5FFCVMkHIdZnhawZ3pJDZHUgec4jnE0QkE+dqkD+161zpRlGu6m34qP5PlY5muULXB4/IBoboffTUmeqjWKJlqgGrd53V8dVmNWfX84KoxG7hU0iFG4G9jdHxCj03jTuJhc6OLNK6gwgrdAbwgRb2Rqv0idbIErbFRdDqJOmZX/dlSoytA1W2pq+2i3txWP6o/nZ46WASqsdzpxNjYHCCojKgzBDq5wlQkdkqJWPKc6eo1zSy2VgBsYWFhYWFhYWFhYWFhYWFhYfG5iOeAAC5UibrgnbznOEVQVteoNQSsa6xn83qxxk4YMEHWq8lfU4DPKdWqA0qkHEwtXJQCnYXloQkIXm39V95WFCLaolrEW8gNkA3px1snbLk8iPt0NUgoeE8EHXtvVhANQq6Jt3v3Lj5vkqZ5ELfoNbVnpYmdToTx1i5MVH00/RauLJ/F3Mp5zJCFojcOp/PlcJMaJkb2YGttABOY9yhozvxkCDdLsLCZ4fxcqO5wA81GD4GbYWG7oy5gHF4/4QBpmATY6kVojbloUW2+WorNThu9uI56RHUfAwzCEFMTM+qwEUZrPvo7q6rPG+h2MlY5E5FYUT3S31jAeLWKsD6LdKuNielT2LpyN+LOumqPalsyQNjdweFDx7G2rfop62Hv3jGsrw+wvtXH7HgLbuhgZ73DtqN79+7CG77oRXjf++7FRx+dR1Cbwrvf/RD+5dd8kbriGEElEKWXHi+u4+bBXrpv99x7L6KYiJBAyA7V54MwZgtsqptL/d/lfRxcuLKAo4cOoNKosDVyUKvqoprmzhSJAjI2zXvF+CmPm+wq+8x8xJqAvOPkx3DL2QkYHhP5OCekRm2c5VaWVJczV7PrdmmBmNjQEhlN49Z3sba6igMHDpmvjSQjqO8dJQFQu+q1GpbUNlWyS/cD7lefVG5UZ5N+eyl8831JLQFsYfGMYJlhBSK9zbj8AM1PotAFq3I5NcN1Jb0kle8427x7YMWtuNvTd1rNrl6VFb7Ehzpcq93Xcwypb8UVwHX13GTs+vXamZjPiRx1S5knkJquRMalTg2hmhs/dv9Z1cYY7TbVJa+KewbbFyf5mkwW1sY6N2ErafEjTuJUyrYz0UcK3ho21bx+30cfxq23HsPK6jY2NkUVLdbPHiszyYRgZLSJzc11rlfvBnWuTc5kM5N1rtQ6Vk1+5NHH0KrfgmPHjuD+hx7TNZQdcQnRbg1cE9ks89DW14D0k34e4JKw1H9auUtuEhmM1b8mldU9GcT0IsCDD1/E42cW0en14XoNJqa5N3RSjH7a4Fq9dMCKG7Bd99LSHKYmx3Hl8gp8StAiJXia6TIRWgHtSAKPqWVPRDSR9LV6hY6I9k6X2+KmJtkIeaKb/BanBgD580w5uQ76bpvPryaAJalJSgdcXa7AgJ0t1PmqTopaJUajHuPwkUnM7h9V63CEkbE6WiMT+MAHHsOTjyyg7k2zIwYR/rWGrz6rkS5anpn42ctX65F6FokDLutADhi79zZw9OQ0KrUBPLVeTUztwfJyB+9650cQtckJo6n6Xh2zkqKhxktQpWsL1XiMVNsb2FZjdrsdq+1a6uICsQDn75a5LlGFExFuEgadUpIhhl5bWFhYWFhYWFhYWFhYWFhYWFh8buA5sYDOVUaAVlEWxK8JOpbtnqn+qd46tzgsq1jkOFcrf6GD6kW9VA7qeW6uzEWmrWtNjWE5kBy9RNyVg6JO0XCuT8t2lTAmnfIfBRETjjqLZWcay3mcxGNC1AQcjeJncXERhw4d5EA8BfmJmHMzvY1rrt3VtVcTDLIQ47U6B6lrbgW7Z45iNG0A8Q7mLk5j99gBrqM3PjbFtXbJ9jCLu9K3nihQLz98BmEnxiDoY3MnVK97qm1E7AmZTbV0O/xeD71oC34QQBhk0m+TqqYP9klWbVjfXMdUbQTLm23UWw22EU7jNgJngAoF1uM+ol6MJOqovS8hzlbR3rii+mMLfafKFqUDdb2bYYp2ewGxo84Q9rCymqIbEhnSU/etjsTzsNXrsh1kd7CFhx9/CPNrCxzkJbvS1e0+1tbamBzzsb2zw0Fmsq2m8HtCNSW1OqobhVheWCKzamHtiVIJY3T6AwwGA465++o+tOMEdXVd7Z02QnXfKOBPt4QIe7JCFrWVHnP6/w0BbBIWyvWrze9UB/nlbxdFCB5DKl6TnJBbceaCJEMwF3WoeWykogZDSfFl1M+ZUZCRoozqEacZKwRTUqGr8baxvsZK38xLmQQnRHHI9aDp/oyMjuIp1adUrzsIKqj4FQ64c31MeHkn8PfVFRLLwsLiWpDNr+vUmFTztEqT1yqttPR4DpZJwIOsYQ4TnuAatkwauzIZUGX0iJ00Aq1UFUWxWB3oRBMnlrr0+Zop8w/NjIkjdWo9T+zx8wwRPc+Q7TEVDvCrI2p+7NGSptaCEWkZ1VZNJaFLp2rpOYDWQJ/nOZMCxYlSTsYKYN+jurxqrolSPHn2HPbvncCe2RmsrJ1V19HkNQ5ymTzPjoy2sL4yz2shGQ5w66mWMNkN+1XEUaYTVxw8/MjDeOHnvQyTE2NYWNqAFwixy30MfX2GGEUxn8qanIiZMXPu8rlxDPG0dTYATRQ7rCwlxTNd//aOmhcrLe4J0eyWyVYpWSGOFKkoktV+81cuY3bPUbXWSmkBSghIU5PoVvZDkTYWSuIEtVoL7U4HfbVm+X5LHEtcneKkE3wcpKVnl5KTCZz8usqfFfdqmAiWxLz0KgeUIkmPnCZoBaiq19PjDczubeGulx/H6ARt21Fb0rrfw+yhEE8/tajWHk+tq+MI6ilmD0yi1qQ+7Ko+T3gt6Q5irK9to6auq1VvoKk+v+WWvdh/ckKdf1Geq7CFKXX4yZkIq+rZpll30Bxx1TkD7D+gnn888ukYcF/R/Vpd30Qce6gF6vkk0c9Yjq+f4XSf+Z7uO0+e1/TyamyuLSwsLCwsLCwsLCwsLCwsLCwsPtfw7BPAHICVOrm5LSIFYD2HVUKEqwOQUsfO5SCpIYb5UNkwcVwEND2tmIEoobRyhfcPHG2NWFJmuk5htVuSB5UVIGVCOFdqAjq4LPszEUYBU1eCznzOLEXYH6BS9ZlMy1gG1Wf7wcCv4tL5C9g9O6P2izjoSKrgNKsPt0Wf33cqmJrehccvfwwXNy/ACXzs8ceoWisHNSO1//KlNUzdcACdToRgJNHKpT4rNflmJj4H/E8dnUXcvoBukiFeW4AXZRjNAjj9Hk7ddApRfwv1iofpaob5C09gK87UMRK2t6T9b7z5Bg6oN2oeNlfmcOGppxHF2sSRAsKqbXfcfFzsvmsZ/JHDeOCBe5CGG8iCPqrxZdVhVUTVm3Dn2AmugVjzIjxw+kEkpHRTfbXkUZ1k1R/dDDOtfap3Y4y1aoh2tnHudA9nHn2ULUGRBOqTGFm1hp2dPg4d3IeRrMVjy2XFlNQ79DhYnaCSRmzbnaEqY8KTmo/xoI9+d4df+34Az69wn6dxQ4hziLU0zFjSVqd5kkBOzprfzrXBdMfUmBYSANexSzY6PGTlfdLSftd+rdyc3NGJCFwfmK5XdOmG6IjjiNsehgM+JpG8VI+5u9PR7XDZJpVU1KbtFBifnpph4iaKZD+HVIM0oNiqVrUtrqj7mnAfY3joWlhYlMACYPOdpGQh+m6T+pAZJ9dU/JWED11v23XNWgMEVKM8SbiGKZG9ji6JkDnGwl3XbdXqXhHBGkcBaYOQnQ48rgNr7J+1swaE1OPzudTOlBNLfK+uieWcKhRlLYzLhpw75dq8xnlA1veU7ahdsYJO5L2AEk6SKi5eXMSxE2rObvjodkN2xSBim+yxae7J1HbLO+tMREudYnV8Z8BnTsiGmi2hab6rYbu9jcXlDdx0481oNC5hYXEZ4SBl0t3U5U1kEmdCVih3R+rCO0Le5i4OqU6xScWpxNMqXJ4X2cnaZSUpk6lqLU8dLydWuegDq0oD/eyRippbrW0RXZdq89zlZRw5fAK7dzVw5dKWOseY9I+XIEKXr8vjVTbiNczJqGZ0lcnW8dFR9Do7CFVfVisVkS3zQ0jMxC/4/ia6Nq8r9yXVxzFW0WSk7cl1GILTMXpl49CS21hL4lKeXKetkk29ZrpXkTo+bZMkdP831c9A7batxnefa/nunx3F3j0VdDc2UW95mNjVwt6D0/zsJyMq5P4k++eNNVqTR7kWMPVGL+yo9jSlfjUTxT11f6s4emwCvZ3zqNcDtMZ8HDwyg/HJhjraDiQlQPV3WMHK4pZqs3quIjcZSK1qx6G7neSJAJTQxH1B5LCXMdEMpHktYAsLCwsLCwsLCwsLCwsLCwsLi881PPsEsCPKRSZmWTgoEUWysDSBNgm2abJN2y0yaUtqG12XVB9ME8hynIIso8CettfMFbRi3+hoYjXNbafVNuyMqRVVtE+W5SLLqwm8/FhAbvMIvT+Rt1IfNUBCgVay7kwTVKsVJmtZeROLunLv3gPY3OpgfGISQRBoxSb4GimYO6CarOo3WRk7dEyXVEsDnNx1FA+fP40VdwA/jHHXrXeqc/gcZA3iOu647QsQD2KMtsDq3/xSVGfGRFY6ISt59+6dwYH9u8QSU6ugnVRU00SNxlEfvpfgiz7/Nu5LsaUGk/dklxn4LqIsQqvq4au+5BVCqKZCasZhhHq9itHROsJ4gCxOMXboebj5K09xHeMsTrjfqD0jE+OoNRtsa3rq8CzGag2t/ipI/YnJGdVPI6AqxocP7sE3fN2XsTUpWYSyYlr9VKkmYq2C1lgNSaSVr3JrmAQmUOCdlMCkXp0Z342VzW2uf0nX3FfX0mtvIuwNWDmcuuraWgErg8dGRhEwWeIg1IRolmTkRMoEiUiodKDcJCJkYhXqm1g6tYhIBCJ80lDdz5TtVFl9xIPLg6kx6Wh1GrUrLam4oMcckwKZJjE078IEsLYYzZVg1GZP7p3YXSZcO7Q3CBFGAx5jcZKw/fag16dyiWq3kPuT7FZpHPiOqOdGVB9U6kSG03lSde+IaBhwDU6qY50EsR4jZCcbaGWzhYXF9cCWy75xCdDJI+UEkaxI9Mh4FpAVR9O4eb1gwFB32jaa1jXmK12xvze2AXo+JYKO1aGy+Ko5X5N8EFKv7HBB65CYJsu8I810hWiGqVdbUvjqtdXMSalOlimMLMzaL+V16SiNegsrKxs4dHgvbr3lZnzso48y4UkTM00h9UYNnprbt9pdNUXWxPaZHRQSURHztXq6rxL4lQbOnH0alVod+/bvx5W5BTlvps+t1wWnZIOdr+qOk6/5/Lyh527HdYtttBrUMQSosPh6X0/XYdZJMOaZBKleA7RzCc2rbgX93jbW1zZw8OBeXLm4pLZtcn1nk5RGltyuSY5jBwtH1k8nRk2tuyvr8/mlcYISJTlRVg7VtU9S7h/PKH+J7KTP2FlE7P8dsl3mOstZfo3G0UTa7THxzffLzXK1LyUfeF7h+sB9w7kLGdeEj6IIYT9i8pVUzUT+qr0wM1PHi158I849OafW1DqOHN+r1n/aeUttG3I/uajg0qWLGPQDVJ0W20HTKtjrduU+0/pLCQBqjPheiptuOqDWfgf9ToR9+/Zg995prkMsqnQaFw1sb8dYW+2p7adUE+uqv3ztppGyU4W40FBPCxlM/U42064n6+dVuXgWFhYWFhYWFs8qxquf7RZYWFgY2LxPCwsLC4t/jHgOFMBiQ2tqm4r9nnk9bJebupkmAynomDExZUhao7A1dtGOo6PKcgAJZLqiiioTc4W9rmPK6wG6vl+W20IWte44EHxV7btcbZxqErmkoDF2ghz4NrX3KDrKiiFRI9dqdVbtrCwtYv/+PRKC1kFGqrtIdWYHYY/JNiKV6/UasiRCnQKSQR1f9LyX49LKZeya3oXZ1jjiXqS2G7C6OBrEHIiW6xMSUq4w1YpSj/sqHES6T4pt6HNPq6Aco+BySMkUlUh3sUwcROq3K6raoOLAD3wmEJhgGGlwkLjd32EVKt0D1AI06xOitFbbsK13JragsTo+3flas4WjR0b0ffAKAt6R4CyrxgIXR47u08HdcpBd7mdqbJjFTxWmDrPmIjhQTmPvhS+8A+9813tZhR3HIbo7O+h0OhLkjmPup2raRFVd9onjx/h4rJ5VP0SeUnd46utRrdX0WNTjiu6/Hopch1GPR00Bc3+zrXKtgVqlxv1lxpTmdLl/hOTQRElW1KpOkxgJKcM8Lz8sXXuUhahUPBljTumG6vHMiQ6kTItCRL2OGk8JMiqwGSc8jntpD4vLy9hzYAqxGnPUT5SkEbNluYORkRFMTE5gfXGFGQdReqVws5iTHahPnIGQ8Q6KpAsLC4urUXZ20LV9eQ4rlIZJKnOYkIliSZvlbgNC+kkdXLN+CllIiVTGPtjY2Zp69mIJXyQ18XrmaRt7R5dH0PW7HTU/+/ozbpdmgDM91+aqyNSsrcjXZEevp652HShmYNELc25WIu2nmr9kzXvh/Bxe+rIX4tKFRa6PS4kqkZqfpib2I+r3MeiEao0ZVXONkLTUAZKslPK8BtcQ3xW2sH/wgceYxEtihxN6KDlJ1kUh38sYSvKCk7t/SB6attA3/ZVKXXln6PmlZBzC6mBZ18rgRDR9LLYXJhLSa2JpZQOnTh6BX6EkrFD1dFUdK1ArS4sVqpQkxFw1u6Akat0kIjhBpeah1+/x+kzJROSewtbbpEhW29K65hMhm/SF6EyFmGeqn45LRHMq9YQDFg+nrBAW5whP31axSY75eSvS4ywbHj8mCYES1NS+YZSodmXY3goxs2dGbUNrqboGJvUHOHhkF/buO6CuxVfXQhlH26qvOnrcBNjpAueeXlbr1Kg6Hjl0BOpZpY/2dhsxlWeo6PFFCQ9OD41WCzffdlK119OlQgb8rEBuLCnVx8YILl1+SrVHPaN4Y+zmwSPRlXshBK+sy67n6SRDqVnt6ec+uURb0sDCwsLCwsLiucEd05/tFlhYWFhYWFhYWPxjxnOgAEZRa67Q1QyRXCYYm+jAtWvUKUnMKsqyJV9u7exKzTuj3mFFK3RdwzJKfzo6MM3bckBZE89ZmpO8Jnhebhfvm8uzMiZeM11TlTXFmVgDc0VBPi5YkZO6oj6amZnGY488hhPHD+c9UFaYENHY67WZAHYHdKyY1VQ+Ba9rLmZqLew9cisGUYy4G6Lf7XCAlgLgrF7NJHhJNYb5CjUhbVgBCWAbwtsttkmFJJRL8zkwmnGbqWZsICoirUHNUOH3WUmTE/LIg+fcR+rCwzBjLpbCsZEmEygAHg6gBWFmNJA6m7fioLqrazHyXXKFOCB1E9fIdBMJLIu2CsbSW4gRTwu7smvutyiZHLZc3TUzgpe++Pm4+8Mfw9rKCrbbO6zeJuKBgr9+pYpqpYWxsVHsnhlX92LAfTYY9KTUJVkgaxWUEKwu22Ayz0AbsoLMEDGixHPIllMLzxIKlLe7kPqQMsahxzrXA/VdfWzkiQ5iKa7OE2VcGzPNCmtnIkLiZDiBwgwsJ3M0+S/2nOFgwL9JqW3KfpJSjOtQIsu/i2bci6qrzyrg9YVVTfDK9062TXnMenGojhlw4oEhmywsLIZB3+WAHCFKiUZcd9TRdcVZxe/nxKKpzyrJIzoBKk113ViZG43q1GGXAZmXjD1vuTyCOb85ZmZUx4YcdoXAlDVUJ1l5pVrjjtjoX7Mu5vOsJqNdIQtTVjMneu3QBDBLViH2vDRveHUsLW3j/LkruPPO2/HA/fdic3MdUdrD5PgJtLe2WRnKiVSalMx0/XNarxJdF1n6wmUikNoUhkSYVmU9dmRe1d4feZ8UriH6b1f6PzVOIGYd0v3lacI9f4LRa1SaSqmB4Tq5BbRRiJYUU5IX2FJ7a6sPP6jhpptuwMOPPKX6oqI2UetQ7OdraRT25X5Qwk7FQb0VqH2qWFnZBJVAIKtoSUIjkjiGVyECtK/aGIJKS5ClP1dAzoT4pTy6VL1mJ24iokHPC9QzIZPOVAt+0E8QRmqvoKX7zSQxGdL0qmchHi8uBuqU/V6G1aVNHDq2Gx65m6jjppzAFbCNtU+uJoBW3NI9bbDbBOIGHn3sKSwvRAjcKbXtiLqHrlqvHGxt9rG+soXpfWP87OGyClg9F6ljUimJTEzVQfbgrhNyW4A6NjYGePLJeSaCVc+xGjnTBDitn2ZsZzqhwNELtKst2Yukv0/ji25hYWFhYWFhYWFhYWFhYWFhYfF/OZ59AhgSgL5ajWRQBKodbasLUdM4RYz5egFWJivTbKhGsNm2HKi++vPyOTMT1L5Ou649X2ELTSpJDtaSaopq7XpuHqTPdE1ACpqzZXJzHE8//TQGEdnvRmznKCpmL1cWpWmIXncHWeKL0oXqAqvu2tnewsye3ajX6kzI9QcDLM0to9fvoFavolKtIBxQAFRqFuYqJkBT0w4H0IUpyErWl0afVaifxCqSRFOpqG9TV1sl6mNRLWDX2BOXLIozCcrnNWthzpNKfUpIzWQmHSGqNiJejQIarlMo0jSRILUoPQ4WszqJyV9XtzllEsOFq9lSo4DN8mNkxgZTH4/Hgeqj2ZkRvPJld+D97/0A0shDRPeI1K+ksE0CKqeIW08dR9jfQKTuU6Ou+j3sqb4PWc3F9QLVwSvVOo+BlALSaWL8TbU9qE5igLajJgI6TtDvEwM+kDGSRvl9EPJcqoAKcZxqMtaFr4PTbM7pC1EhVpVsFIrBIGTlEwvVWDFWSrDQRDmR1GEc5cporhKdOmj4PtcTNeem71yURlp1nHK/t1ojeT3u/H7rMW6+C0yEJ6IctrCwuBY8H3hiYc9KWdfTBLAst5zYwuSTITaLhCmZ4sR2nssNlNYpJn711Jdm1yZglL+3rG6ktYsSWRydZGNyhHRdYWM6nZh10HW1nbOXr6csT83XQhQuBrzMGNJQrz2OzG6puRpHbKopnSiOUzz40Gnc9YJbcOzYITz04BJqVQetRg2Xrqyh4jfUMQM1R3nszkDTLJPAbsbrSJLF+Rphzhe4kpSUsvuBx9crjgvDzxvXPhs4mvCV7oR2KXGMUtTVdZv13+XjmIS1VK973IdiA8HkcUrrHautA9X3DnbafTxx5jxuveU4Ls/NY2O9rfYngrPO5Kyr1dQkbiVyN036qNVaar8Q3a66xqCp2uezopZqL/sBuWQMsGumptatLU4kaKttw26MejXAvr1TbL186cplPPXUJTWGmrwW7ts3rZ4rgOXlK7jxphuwudnDAw+d5T7wvRaXmWDCtJSAYCDjj/q3xvcxUsvZ6kobW+vbmNxNg2Gg+oVcPup6/Yo0GZ0waUtKXbJmvjy3g4fuW1DXPK02GlXPR1Xu41Ctxb2ei4XLW+p4e+ByclQfUvhAkgFcV56VJIGJ1p6GWmNd3P/wY+paEtVn40yq03pKFuhp/r1ztdpZxoVjEuRMEqFRe1sC2MLCwsLCwsLCwsLCwsLCwsLicxDPCQE8HDyUIKqpISiBVCF/nVQCzrqcb65mKsPRQWVRLfEROcjoMTkHicA6hc202Yd/c2MyISaz7JoYX1llfDVJXdhFOznJm9tnukKspaxwUf+fipK4VmtiY2MT/TBiy+RY/edzvVSH1alkoejoPgjDUKrSkcoyEfVXlMToPb2DoFblAHhnewdST1DIy7g/YCUoX0vmaBIR2nxY14HNfzQhmttXZhKv1wRjppWjRilGhZINp6Bp1fyeac2anCfnLBJWftHvhO+Nj9ySmBVHUl+Pgtdcm5BsG71MgrnQShxNW3s58anHjNwUvq+Zk+h3JfAvQfzC+risctZemrId3TMiMuIO7nrejbj7ww9gZaOjBrzHJOrM+Bhe/KKbMDHqYGN9jhW3STTCZ2lvb8Eny0y+TwO0xiZZeY0kRBQlrIA1SmuU7CMdSP1eqi3YGmlx+9I40QR/ysSpKMmE9CHVONdnpv4jG/RMK26ZqEk1cS+1P6netMO1mSvcr57qyyg2/e3C0BlMUBMJQYIrOhYf20W3vYPz585jz8Fdkgih+zJBogkfoNlqaYVzMfZjUj0nou5D1tfnkKQFCwuL68GoDWVdEgvokkrXkfUv1YpeToLRtXpZseikXBqAVYquqPGLNUrXIqeZhtY1tR8pOg3KiUsm4UmcB3xx0jCKWGgiGJkpdp87ZBgFsSR/ZExq8vuG/KQ6sWmijw12onBlR3P1vE7w9emyAa5f43rkj55+Ep//sjuxZ3YvLl26hEqlin4/hBdU1RonxLSTlWyr5YDITS4coV0dGJUz2J5YVNVmO4eJv3J/lMlxIotNW4fJd73GZXJ95oGhuA8l54VUEtey0pokatdEEpqofURYu1VcuriEo0f249TJ47j3nvvV2jgA1cQNo1jdI5cJY7DbQsQk8OhYU60zGfoDFw013wsBLNR6pZpg9646Xv+lL8Hm5jnEkaOO+QSWLu+g1fBx+NAEZnZ5aI7txuX5s6y+Hm1W8IIX3KDOtY1GfR0nT06h13Vw6fIFrG0MVHurqp2BWjMLsvsaO3Gynlb92g89db8ybKz1cOXCIiZm9vM6S8lODnpM/koygNTxpV7xnUksrm7jb+9+DJsbLVSD3Wqta/DTU1Wtq+1el5Osrlzo/f/Z+7MfSbIszRP77iIiutjmbr6Ee+yZkZXZlVVd083uxswDiXkgQPCB8yeQIIev/HP4SPCJzxwQfCBIcAACZDe7Jqu7KiuzMnKLyIzVV3PbdBGRu/Cec66oqkdmNUjQC4PyOp+HhpmKynI3MzXoT77v4J0PXuLB42V539lyJHbm2sF0Tlf2l5rGVPd36Dv89G8/xy9+/rSs/0eljTMGuY5q1LMFmm7AmKpqy9+OEkvteE1SKseub7u/LVUqlUqlUqlUKpVKpVKpVKq3S/8gAHgSRTrzB7pkXKoRfGLcNPUD2/ohbf3wmT+wrjV/8y7+FhxnK/APXAfP8Ae49MF1ZHcj1TacPmwnsYvxACqmGiGN+gHvYf3f14BzBV8Uuci1btlJIl8Z1GVxuXKt4iSQlNyqcUzo2q5cs8G333yL87uP8OzFcwzjgLaZahFPH1yjstmMMW7R9yP6bSiPAYZgIRc6TAKXrXzAnEaJQ6Y6yduR3C4dYsjofFuBYuQPtLvZHMvlUsBdFOBIH4LSV+lz4thtggsx5ur4ldqCzspc0bnYrcwOHlcdT9Onoxatm3EUZuB6guCatVxv1lR3DuhD7KY8bxhL0rC3roEhSEHXo3PTwmM4LPPtcODQcuI4S6k6fOul5UN2gaUylYYddmOI8pwcQint3LkCEeTD3/nM47/8H/1LPH1+jWfPL3B8dBc//vGPcHn9BC9fPEPbNgxVh2GFs9Nz/iB+CAGeIE3ocTOsMTs5EbcS11am+pme+2m9gG4GEqm6n8t0kHOX47rZv9YIDE7iJJ+cRxQTTfPA0JbnUcCqOJ1qpGmWdZMZLDAnqA52Xw6RMROwkxhIpNJu4ULTuk7sXKbakZ4vXuawzaAfKboBg3/esjiHaf2w6W46cnInZqmZOA4DrxXqRFQHsEr1R0XuWwGQpt78VOsAQ8Am/zo1ttbbrTc5GQG9QE0D8A3/vuQIZGHDO6icUN8/q+v2sHY9vfeJ29hw6QLznZubDvcF9rcK7X7RGnn/TPX9gl6c6qjS77dAvzi+cyeV3KTViCPYyHvvlGwgMdSZHc/eLbDpb/CrX3+Bf/ajf4H33v9B+f1tyza5iYjBbI1/5trykBtgOIkiyW8lSR6ozk5+P0+cyBHL7+zI71l259I9fJ/fvddXl/B0YxnD2pokITcsZX4fcfw3Bl3x8Dxu9z66ex+fbr0xeO06uUYQJ4pvTg2++OJb/NmffYTTsxY3N1f8N4lvvUReZ1+uV8bN96UPNzi7U/6OePoCs8WMo8Tpdy7XIub3tYbHeixj9uLZC/Tl9/L17TUD637b4/nzJ3j43gf44stfoy/vZ213jNvVDZ4/+wbHy4SLF9/g8uIxjk4eczx3yK7+zVNHe7pp4GC9cGkCBAbs1nag0sQ5tvj5376AL3+LfPyDc3QLuuHpFqg3isn4+NJOg99++RT//i8/xZOvO8y6j8rfPeXvFhrLsmT6Mm8u2tJGz38H/fVPfos/+5cf4d5D+juGUjSSrAn+uaH3vA6vLg3+5m9/hV//+qL8ffVhGbs7Zc5m8HZW00D2fZC/FaTmsXMyxwSI6W+raa0c/BSoVCqVSqVSqVQqlUqlUqlUb5XePACu8bQMdylO0NZoXI4tdtWxGXefuUn8XhK3UA2Q3H1gXWExA9edk4M+ZE0Qg8p3XFWTzP6D8XywD32we/gx3/RB8fT93mUlNVhjGstXw0CYgCpF9JosUBW11iydmj7IpbjOzz77HO+++x4oQbhrOq7xy86VJDCX0Kd84OzENevIdelxdERRiAt2hPZ9wPXNLS4vV+i3G64DTLRuHEasbtcIpd9HRyfSAe6PRDHT+b73vR+Uc0e0nS/n2YqTKYjLmGKNyc26Xq3w5Mk37LoK4yjwktxNZoupNi996EzDMtLrlE1ZthPgTlGq8hpnMPmpuTby5BTNApTJfkr1Gbn+LX1A78UF7bqGProXAFxjobm2cz6YhwrdxQF3+MG6AFGqE0xri44nsN1187KfuMwFfDgcn5yUPjTTMuD96GJdef29h+cc0fzLn/2kzOkWTWkTrbzAC9BhuZhhPp8h9JFdzNQu51tc3rxCN2vKdVsBoq4RuIFGEG/TMtThbiWqwTty1DdpV7+Y+be4qwhe0zoiUCx1Lxu+0YE+3A+BnE+R10NM+xqctgIVHn2G52WvcayMNjGU7cscT+459m4zxJHo2Ocvn/M6oillkF7HbBgCOw+Pj48FkNBQ0P+c/GzSnBIs4BrLxKk2UhNYpVL9oaZas/wz7jz/XiXnoTVuBx/593Z14k8xtPzbM6Z6q5D83ubfa/agQmsWh74EYVhJuPhO+sV0fcu/R2N9b5NoZ2bGGbvYfG5PdbbuMjLq71wCbtbUcg703lfvDEmcLHBQToFuhoqmvi/IjSiukd/zqL9L+KYXT+cL+PLL51jOlnj4zkP84pe/KL9b5DW6ISVNsdIVytYsitovSFZyhbLUH7qBJtba69z+VDtXO3IIgvl7vB7bz+/2pS+hlpegmPxk9u9vplqQpzGczstjYuuNSVO8MCos5/d2GduULIPJr796hk++9xB/+qef4L/7yU95TTAvL+9nNrX8HjabR3Rzj7PzBr/67EU5eSztIlftQhIbzIxLGQxrj1/89Pf41a8+w4//sz8t49CW98EGi8URPvroe6B6zN9+8zUePf6gjPGP8btf/RRtO8PJaYPV6gavXl2UY07L3wBjOeey7N/s+jXV/z28oY7XiYm1zr3nGGiXlnj5NOIn/6+vyt8Tt/j+Dx/h/N453xhFf9+FcYsXz1+Uv4me4lefvih/j9xDax6UuTqWtVfTJ8gV3pVj1tvyN1Ppx1e/G3F99Xt89P27+PB790ufuvo+ZnBb3oO//fbrcs7npQ+0rt8p17pXpnwpNyDwzQuDvF9acWjvHN51SeQK+CWFxNTyHP/pciAqlUqlUqlUKpVKpVKpVCrVP1b9gziA9zAV1cXEPh7sygZWZ260iV2WucYNZi8fpk4fSBMYM9MHwWaCgXtnI2qUY7bTB9iHH2JndjZKe6Yg3ek1s9tn/+Fufi32MCYBq7e3Pbp2wY5Qcr/wB/JsxUkc08wf7JfH1eoW8/kcd++e487dB/j6y68xDmseYnIwEcM29ZJTdVZxc0WB4AxWPeaNx/LkPt774B2ph0sftNdo5v/m//h/QtPO8T/7r/6n6Ps1u235A344rg+7Xo2lbUdoGocNfRifIztWxyQuWQKOYdiiLdfpU89g4d/863/OsdXffvsNLi8veRx+9KM/Z/D9v//f/Td8ncWiwX/9v/6f8wfLjRPnWq71m6eSuP+X/+v/vRy/5lE+OT3iD/yvLl8xdJ7PFzwHf/4XP8YH778rzlUIW8wMOkZeAwQ8JPaYIGSLaao5ijQKRAh5xfNH8H0cE549e4l+u+WxPJoveT7/1b/617DHnqEmAZVxDAhxQCxjxO7iMi6rMl+3NytcXF6Xc1l+nvLI5/FeIlt922A2mzEEmRHgLWNCfVmUx7xsXywWmM3PMO88WoLbrilrJWO9vRDXFMMcJxGf5AL0AhYIDPjqPhqn6NfpBwNTnULwGkGNm6Y1wm2jNRFvy9qKCGFTxpfiMenHOHCt6GfPn2C7WvNabNtWxjdkrl99dX3FpwtJ4r4J2AxjX93JETWZHZgchlwHM9YoWbEGh5GODfqBuUr194nAr+8YJjIGpZ9943dpGPTcZwG0h+5DAZzgm1/EhSru4TQV7929VzX8e1cKEeA1FzABOOT9jSLeyfUjp2LIjTS72H+6Kcfkmt4gotfo95/EvNebsUwtuQBUYJzrTUNTKHJ9rzVyswtH1mezcxCzi9g4ufnHH5WnLX72y2/w8/IAOzLn/HuObpGaKLOtX/n+E/qbIMrvQFcTHuL0e9NUuEzXoOSJXXXePQSeIvqnMhMcdZ3lhqUd5KT0D2smezYnSKQaMb1LC5n+hjA42Bc1kjtPSdoS6R0z33gzlQugkvA/+9nn+Df/+Y/xPz67xxBVftc7BtnzWVfeSyTZ5PPffY2LV1e1/q/djSENRggOz1+sy/ve03LeFn/1V7/HdhvQmhk244iL6x6zO3fwzuM/RT9YnJ2ccM3hZOa4uIpYnn4C172Pf/+Tz3G7smhmraQ6WLv/+6eOX6wpEjRentJA+IaCzI5cCmZOYYF4NeDV31zj17+5wd17ErFM7w90c9nLl1flbxL6u+9ROced8j5b5pnSQFBLJdjJx041scs56Ua7dcJqvcbz58/w6acvMS9/e0ztGvoeNytKoSh/47RUr35Ot3XJWuGyHOVBN4p5cY3TDVLy4+H5B4vWB0exW4mDZsd5LS2xXy8qlUqlUqlUKpVKpVKpVCrV26N/EADMQHeq35emWof7D0ynKOapdh/LHtTa3TmAU/1U3O5dSvngg9p8EDdoXo+3lBjGyG4c1Np202d8U6TxFH04fcDIdXSnWOposdmM+Pyzr3F+7wwDuV78DZ49veAYyhB6PPtmjbM7J9hu11guTrm9v/rVL/Hw0TVePnuJ5WxW+t7wB7wvX77gSOjjxRG7U49PFuW4LQNSclMeHy/K4w6acn3aHsMgDlgvoJAjMJ30ezveYt1fc71Acimz03fMUsfPd+y+WhzNsN1sYIgUDJT3OyKkHmPYYqRjKDIYI65vn5fzUs1i+fA5x7EcH7A87vC/+F/9VwwIqR3NbOS4a47ezql+KG4FapY5HuO6tIv6k3CzWlVTlHwYT+NDvIDg4fwosgM35/2EkKuIQC3oA3wGp6HGh9abCRhEmPoB/qxGJQuAJ+dU30fcXN/g6dMn/MF74x1ab9h5PFD9QHKylX1jPXcu402Oqe3G4/T4FH3p49npGX8g/dU3z3FxccFAdLE8wkW+LudqkMaxjHmP1WrN83f37h2cHB/j5PS4nMujm3luz0//9lN88+TbGi/pBCZDYs1pbZG7+uz4iD9UPz5e4t6Duzg6Wgr8xlTTuTqpGcKIo81AgMtqsy7rciM/E0b6eH5+j0fydnWFYZuxWQFjP+D0bI71mlzsM567+cxK7ekyDl0zZ/BONxnEIDClbWb4wZ/8EF989jmMSwwFTPQVQgvM4Nhr7svkGlOpVIdi9y8lEEBiey3H1U+/vy3fZOFz/bkuvydCFJe9xB3LDSpy45TU6JUSs/JOJ783a11gJqv1LXxXs3e6AQv83mknt2wyFVza3fveLtoYODgul9/TYZc6YKZI/eqWJLzLpA0TlJbrUOrDdC5X4+tTNntgysCQ3MH0u2QO07T1vdsIOCXgOEHY2p9p7FJ0DKDpxiN25+YkiSKQ0g6u/hnD7yFwO6hrapz19D4jsfh76BtrXDaPU3VNx6muMIHpCn7JqTqBcDmvkVSHmiiyc2BXUMtlHBjwU3qGlHWwpsOXX18h/Nuf452HJ+X9NiL0gf8+IXdtIGha5mi1Dvjqqxdl+5JBOd9ANtUWppt5CEwnKvHQlKk/xuWrHrPmGJs8YD2s8f/8y58i/ruR+0rvdX/rfsfXePXf/oSbty3vC5/+9ufl+HLm7n7Z0nDJh7A3y1Yw7gTl8xohh7esm1j/Bkg8T7Py/tqVjUcYrsrfEtdX/D5D/aVEFGcflL9f6P16jjE3Avgr8KUL8lwnmddINzZRa/KSb3Ao7464vNri4kr+/iBY2zTl76N2Wdo+3zHxqWZ2op8X+iODEkJclBsFTZK/EelGwuzrzQWB/y6Z3p/NDgDrDU0qlUqlUqlUKpVKpVKpVKq3T/8wAHiKoTTTB68J1uXqkSHV1zLqh3/YxUVOMtU1Obl+d/vvPpieXDl7hw7JVicLX7/S4cOIzL3EQbxHwewnmj5n5w+ZKVJ3uVwgjOJMDePANVbbxkqdx+4INhos2jlsqpHRbYPnL56ga+kD7zVW1xnbmDBrj7keMIFd+gDy6bcXHCd8c7PGr3/9S9y5e8b1Z8m5yTV8wyhwOMuYkRP1e3/yp7hzegf/4W/+Dg/u3+O4Z+8iNv014pDw6NGHmJXjCVDeXG/Rztl2KvUI6cPXXmIrQ4oYxsD1Zj/77EuMocftamTH6pdffoWr1UbqLmJT+iwfBhPcZAibUGsFy5gTKGVXVpnEy1fX/AF/DFJHmEQRnRQ/6cr+X371NZ48+VzcWq7Wei7HNqarNX/zQeRzOlhDE/xHjTOWMQlD5JjSbRzZnXR0elKuYzBfLHByvGSXWkuRmcNQ+lh6U+OwKV5ZYk0zGvr8GtTvLzBUCLs8m3MENIF+ctGOZc7IQTvzC3bsXl1dYyz9evL8Oc+LyWPpR8ZY5uDFyxuBKRxLnaWkccIuarJrE+6ctTheznF6eoTNZs2AXKLO9/GbAlPkQ21x+FbHeLSYdaWftoVEdlI05lpqjuYF7t75EN97/wR9mVOCz8fHZ+hmS5ycdGXq51JTtIwXfK0Xaj1GM/C5CCx8/PH3sb7ZonEt10pcLJe4c3Jafg6O2TVFbmJaRI8evff/768JleqtlBEKKq75GnM/5dlz3CzHMBuOPKafO19dueLyT+LYzJO7F/X3Xa6uWMtAi8Eh5Hfm9DvjsJzBYZpF3iVhCJDNKe+ey3vx9Ls67iKTvxsrTZpcwQyfDxIAvvvuyqC4/j6bjtv9Ttu9TztxC+eKf+3BWeq5GWgnKbMw1TveXXMXvYxdv/cxz3kHrQ/rIu9LPOBgvPLBZQ+g+MG+r5WROKidzC3nebP8jP4mYADKZRGoARGYxqvau7/5+iW+/vKbcm2KP3Zyc5wVuMx/IWWPrjniWr8MXpn1y01w9JC675lv/MnoS79miFlqJ5vyPkrOW5iZuJylpDG7cmPkRVf2jxyp3LZetqGtfYq78ZJ5yrtx5XlHfU4x3XxzggxdrNCfa9bnc24bwXm66Y3XVe74pi2JaE4ca03rLxu8lghja8JFjtSvRkpAUOkILOoMlPamhmsqy60P002BEq0u8dRGEDPdMMDlINJubeYyL+wx35WViDI/SK+tAZVKpVKpVCqVSqVSqVQqlept0hsHwCcnZ/iv/5f/mz/4TO2PMdgJ4L627Y+5MaYPgOvr+/p8++MPP2D+7gfY9RSs/J3nh9/xa3lyLIGjg1P6Ix/+chNrnGatvep8I2cwciY7OaB3tQP3H1JP21E/PJYPrqf9zM5VNPU4Y/qQtdYVLDsuFnNcX10hxoG35ySwkOrHcnRlBceoUdzTB//Th/hSy1b2y7uoy+kz9f0H3/+pz0Z3btVcnVxpVxlYPtl9DSLQ//durGmWzXSd1/bbx3Xu5mcyhSPv9uG1cODMIlEE6uNHj3Yu71wdWeIiTvV7GQcC3lPM6Wq1qTWM88F4T2Oyj0w1hyvHmIN28if5/AE9geOphZOV+fBGhtmsq9mmeO1cf98gc/3HCtQZCBuBNq5CZXJvc41krivs5MN7Zw/OW8cilX1bh8ldOPV3cg7yTQ7DiP/yf/g/YcDgat3SPPmtDub05OT4j7dXpfonLo7MrYBq+j23i1+G/DRasePy7wtvxA27i1Em+GvK7yeXd/CXotjpdzvdsEE/xxKAEevvFAGZKe1r3VIygqQmyM+ubJP3moS0e4+USOj9zTYTMD2EgZP+2Psqan8Ot07HTNfb7XdwDVJC2v0+yTWSWVzLdX9rat+mq8i7IUdUf6dkAw7e+6ebvg6h+NQevgHoMPr5OzedHcLzHRBOr7/H1J0P6v9WIMw3FYF/BxP4lfmZ3ss9p3mkSKUJllw7gV3iVmrmZsQ6FA50f44pa0LAcr8b4SmaWW7EqrCb2ktwlSvR098T3e69nG9pcwJHqyG87Bv45gKb659+ppaoqCuTxmeKAD8cF7pRi0ttWFed1LyquOayre9RObtapz5x8gu7velPTNMwwDUUHF3dt9MbjrNTeQ+JKk/keqbTmsBrnt+rqB+ZoLCXG8NsqDcE1GQK63Yudr5JgspicJkJCh2X/RN6fq/kuWG3t2MIXN6tud0qlUqlUqlUKpVKpVKpVCrV26g3DoDJffrRB99/06dV/RE9vP/wv+8mqFQqlepQlHAQDd+EQXBLoJRltz7XhM3iCCX3pHcNzk7uYrMesF33HJMsN10khsAMdJlPRRwdzcv+LV6+vODLUPqBmZzG9NxOUHQPTiVafq/DpIHpZqBdSYSDFI1D9yd36Tsg+LDcQt3xNbj7B0PC6QVxd9MTQ/DD+OpD1609qANsJrBqdrHQfPwfgdQT4J2iqw8B8QS1Sc45HMLo15y/B8klf+As/iNjYKcJr9HUXLu5TFjm+rOBY4+5tjqzYSv1jqksBt04JsiWIXCudZ857N+X59FUIDq5tC1ClqhqutGHgbGtUeCmundhOdaak0ww3QjnBNxON1Cxs9fzWPrWSlVjvktK4O8+Pvs7MJzd2rtIFY73nm7QytWZnmpJjt18GgHGkxN+uudpOje/PMFbSOpKRqw3OUm75V47cTiDnb6x1g6WdcBO351rvd5oUV5vyvcN3RxlE7o2YnlSzukF5N+sAzahL98HBsrqAFapVCqVSqVSqVQqlUqlUr2t+geJgFapVCqV6p+ipF5pJyZHKWAqzsOdkVTim0OMWBzN8eDhQ9zebDEOI8btyAkBBLOu1itcXl5gCmJoyzlPTk4x6xbYbHq8un7KAFhgrjiBDxMUJufvIeDctbHGNFPsuzmIkZ709yVqTND4EJRODuI9JM275ATe7sRfar1/zXKbD79OYLrC3lRTKWrYhrSJI4jTrg2H7ThM6fguiD6Mo572OYyCPjzPfqymOrGvw/H6RGA1u3z3mRAEH8eYJH6ZgGmsBmcjdY6p77a6VilGOZsgDu9a+zhLBQKuOWycwFwSpzqwU5jWTEZbxkEioMVlzHVt2Sdb+2gEJNP5CfimvE/UoJsSpH0CqNmRCwH00xjFuIf+tkaXZ4NdGgrPc0y70gZU75jd2m5K86hwnvrF5HusoHsPn3eW5IMUF3Y228D9ovGZQL6h2tlG3MAynrY6viUBAxXE19PB1H3pZ3DeWtx/uMSP/+IxTENuX4/ffv4Mf/uLi9fOOcWkq1QqlUqlUqlUKpVKpVKpVG+TFACrVCqVSvWGlKzF1njiYhVmSkAv1enmrwwBI5E+uG6Goewwm3eYz1tsmgFH8xmXjh2zwe3tbTl+5Mjftm0Yys0Xc4m7vXW1dm6uJYbNLtJ++soXqZoAJ0G7ydnJtcMPHJCH0b/fBcbTsYcwdYqP58DrA4D6WlJ0jWXm2PnarsNo5ulaZiJ4u/aC4bmAzTzZRGv8sgRpH7p0vwt9p3Z/N/b5u6LI4+mYyTHNDtTvOJ2nsbGTG7mMg+cxjwyMOfrbe4knZud2xzHGfJQVtyvXvyWnK6+FzC5UcJmCCme5vUlilB3Vh6ZjLK+HVJ3AEumcGSRbU9srhQIq0LQQLkv9DXyzAbmKPcFXHLhxuc1S8CBj73g+BMA7oM4w3O4q71Jb6RwNjV2aSiRwq7nmcJ4KO9R8cELgNP+W27+fo8MSHnScUPB9GQ4xgUutXnGmO+ziwBluJzROoqenGG5T6/xSGk3b0s8L0M7H0uhNeWGBpgul/YFBscDiP6jIoFKpVCqVSqVSqVQqlUqlUr0VUgCsUqlUKtUbElUovSAnqHfwXcMgjyJ2meKFiK51WBBK8x7bYcC3334Lk53AtBi5rnvjO1xfX0HqyTM95AjlYdiy+3cYRgGxr3PUP3DsEsic3LKHrtf9/nvmOtV//S74PIxYJv2BC/g77snD+rsE6PjaqO7QnSM2H4BgswPEeerDFDk81aeHxD/7yZFatju378th7eLX4poPYp2nfb8biz0da9lZ618bK9IUmT1FJHO/UDGkMbuatqYCWgLBBBSpVrPsInCU4o3puMSD7tByaLPA3RqKLTHH/FdZdemmqS6yRdN4cd3W2GJGvsZzPV+p91z2mlKakesNAQJUpUx0OSJJ/LXEjEvd4DS5kCFgmW4KOHRSs/OXx97t1oqtDmPLgDmxIzomcXtTm2SdyNIQ17PMYqznnW4i2MVuT7Hfu5hoiUyXWOjMtYIZ8hqJCLcH9YNpXCWdWmpmRx6ztsxXgxCklnDGtjy/5X3Ww0pis13cua/x+pJQqVQqlUqlUqlUKpVKpVKp3gopAFapVCqV6k2pcbj/0UOcnh2haYDsMsfkEqBb3fR4+eIS17cbdARnxwCMAxqKZGYYlnG5umCnYxgA56UOriv7vrq+rnVmJRaYXLB746IAw12dWykcjJTDH0QgE+Bkp2qtW7tz8bJDdIKfYt1khzCz68iAMKXXa+Xmg6hmTHHIxlSYKEC0GnkZBpq6M53H7py8NRU4iVNXqPQUn2xrRK/A0JxyhdYH9X+nNuz6aWo/DpKGK1A+hOOHQPwQ8n438prH0zl2lO5g8eTCRXU7E3RGzVrGVAt3qjdM1w3yOoHM+iKnHPN4WnbYpiy1oqfppOs4TP2T6zDctFkctbQr7c8Da/mRq703R7o4nddLXVwQPHZ8IwIDa55Wy3CUR8dGAehUZxj7mwgoijqUtnN93yQ1hHl2qb411S7mjWBwzWuOahWPiSOqedwJ8mcnTm6Gs1FWahKozyDXeZkxro3tdzcUhCiY3TtZ68LZy/iX7d7JjQO7SPVaH5p+bjiC3bUw9LNDP3uW5q0t+zS7WtRUi5tuumDX9N9Tt1qlUqlUKpVKpVKpVCqVSqX6xy4FwCqVSqVSvSGdnJ9gvjZ48s0Fhs0KOY1wjcPy5BSLsxO8+/1HWF31uHhyjWEMmLdOas6yvVMcj2Ma4LoGieq7VuDJEI2gFUGwLLHD5sACzIy0umDl+d65OwG9ycW6f90wNNtHP7uD/eXcBO7o2ryNwGGaHL9mX4fV7MHnxNMY/RqBmxzhWx2mUgvX1EhnU8Fr2EVHmyTgj6/CdXYrYN6RZrk29Z8AKwPsqf3ZVJOxwyEer0cIsDR7gH3oZv6uDiOQp/HZw++9Q1qaVnFwuW5IAkX95I5m47MXQMl7yxxHAsO1hm4urycutJvZ4Usw3DIkJkjaIGZyCks96Z0nmkEvHVKu2Rg+H42d4FTPAD6a6ixOEj2ep/rKWdoBmns6N60ruiYB4iT1jRO7Y8t6qLWFq+eY4X1ksGzFpY29y5eXqa3wHxNEz3xOOpeD1C5ms+7kUk81gpvaZSF3C9j6nJ3FZVso7felLU5WfL09gZ3Du7rTdavNqbZ/i2BDOXRZ1teDcr3T0r/Sx/iynLst+865JjAB5b8nHVylUqlUKpVKpVKpVCqVSqX6Ry0FwCqVSqVSvSFdXtziVz/7DHNv0VqgdeVtNmSsL29xcXGNkzunePD+Q8yOFnj59XNsbrYMydps4KKFo68E2qY6qBAXa2IAeggicVi+t0YQm31UM8VQO/cawDyMQ56ijr8LjCfSOkUI72KZs8RRZysRvWK+zfX778DWGuMsjZb9d05eji42HA+9j5g2Usd41456nLX7bTm9Vjt4+v4w3pkctUk6850+7duFQ/fywYPHjpyt+fWxeT0y+/Wx2sHH6Xjql6luVkKdKe7amvcVbzHBcnJdx3BQa3cHVKc2GoGzrkOMBLsdc1sCqRRhTP2lGQp0U4At64aAaZBobYK/AxK7uMk5nGwF9nSBmHZNobZGLhecxDCbsHMb82scIZ3I5Msu31TjrcWN7ap7vJzXSdsnN3WukJfHlG8+qPOTzC5uO9foaHbw0sFNdaqHVMdAxjjmGludJVZc5snJObPUF+b1GqXedqYbKVYBm3XAOK5xefm70i66Q2LE85ebcv1TPl6Is9sBfZVKpVKpVCqVSqVSqVQqleptkgJglUqlUqnekFI/4MRauJjhKYlXirzClydUR3X76hq/vl3jwXv38e73HuLZNxdYX9wiDAkLQr/kAs0JET0fx3CtRg7zP3KOmuqSnWKXIU5L1kSGKys9dLHyuax9DQKTJtevAEhx9e7drRITLFG9juOMp8jpGCf37ASNbX0+hfOaCnAPwqq/U5N3gtbkAp46I3HT6WBfbuVrztvDNu/6wwPxn4Z5U8L1NA4yBnXj5F4+OPcONAM7x2vOU58nlzVqnLWZWl8dzPZgXNJ30oYdj6c1ucZlmwrbBapTreDeNBJdnB1O7t5Dv84YNiO7ecnNakws1w3ivBUDOVry7JpyXm8kLpquG6UWcM3o3oFg+n+mKPGyb7SRwXAOMt++deVpYhc2XYMSnp2fHLOmjkFdX5CIZ1ojDGTtfm4P6/1SveCmdXx9cqO7Sv3ttC5ojp3Uu6bRoLhsMhc35bwEn/ncdA7bcldCWTP0s0H9nW4yELArUdEZHW5uIq4uN5B62uXh7mJ5p2GYDD7O/cENDCqVSqVSqVQqlUqlUqlUKtXbIAXAKpVKpVK9IdkY0YWxRv4aeO8AqsmaqZ6p4TddE0c8/+wbbO+s8M7jcyzmM1w8vcblzRYL26BhiBerT7T8PyYcIsdcWaOZnhBEc4zMKpMUR+3kFP4uMP1jzthD4HkYHy0XtjvAPEFecX7WGrvGH7hizR+A5HSYDV11WIN3+vr693a3Hz+3BwnQB8ftHKe1rjDXvv0jfcm7Wrr76+wh8/5aU7+ner/7Y/fjuHfrTn3Y98lMDa0R1VLyV2KZ92Zig1jrJBMfNbXubqx1dikGeShf1u0Ruu4IP/jkQ8zbOT796ZdIWzmvTXINOmlTnd6ElJvKMvmLzRXg1kaaWke5XMuV9lB93mzZq8zR07x/U53fXKw48Zql42SuI6S+8n7M2H1rp8hnalt1OE8u9cn7XM7hm8kJPrWpOqfrjQ6RxsxK7Wn25nLh31R7k2vcuJGbEBguG1lX1PY69ol8z+UYbyZ3r4drWky1oMHQPMpr2e3aqlKpVCqVSqVSqVQqlUqlUr1tUgCsUqlUKtUbkokB4+01w6bGt0iB3mYtbJs4tpew1JExmBHke3mFz65ucPfRQ7z/ySM8e3qFyxc3HAe9TJZBnacH5e9WiCoO4F2V3IrXDHaEeLft/4u2HsQOH8ZHH0YtS0neXN23AucgTYH3e9AnMHUCxRNklTZ6+zq9PYyerkSQaxFPra8v7F4WdyjtF78Tv7zvBw9RstVNHP+gn9zX19qGXQzxbr86jvnguEPou3NMM2icIqxr3du8b2ueGs5DJxHHKeYKz2sV21QPyAf7Ulx4adNYrjMaD3N8F5/8+PuIY8C//cnP4YdMlWvRltfnDMU9RzSnYLg2c0NZziHAtHT+sg7DQKfjMU1W5ocub4NEjac+sG24sVJTOtJNB56MwEFq9ZbtVsgpXLkWjZ9r5CaDNIF5yNwK7M5iNCYHPI1JEkBN7l1eDbbO667ruQJky3A5c41quvlBgL+d3OW01pzdHUNrjGOkHbmUI68dU+tCWxek/jPXp66At960QNeJaSwnEfe1nD7+wc0JKpVKpVKpVCqVSqVSqVQq1dsgBcAqlUqlUr0hhaHH+vYS1jQYfQvvG46ZdaOFaz0a7+AqvqXnSA4vvvwW280W7370GGU3vHpxyXVW26mWbk4MEjksl6N0GXfJa2ZiqHkX88wioJv3jtrvAtND8HvoACYdfp1A7uQoFnesRE47BmxpBwDpmxDiziE8gbpDOj2dk+DrVGuXxLVld65R3vOg5i5B1ix93kFueeGwjrCxr/f3D/pF7XECuunak3t4AruoADeEwNun1w/HhGEvmWWN57q31N+c9vWNU+0DXYdjiKsjWwCx5bUgcdWRHeJ0MHtty7axPB8pmrhbYH58gn/+L/8Ul5dX+OlffYouAmd+jnY14mSwmI0Ee8uBZY2ZckxjPVwoKyNFjM0I1wTMjmYY8qosseroJadu2ZfWX9r06GzH4Nj1ZYy8RTAJYxxLQ4fSOop9TgL/4dg5S9HjDFsrkOea0DkK+KYoatQocmLCtDZqZLetdYgxrQdb61UbmTNbXdO+XMM5V926vFutgT3dIJCrs9pU6G55/XEd6mltYyivJb4+jXWqkdd8/4SVmwicO9m72ykiG3G3PlUqlUqlUqlUKpVKpVKpVKq3RQqAVSqVSqV6QxqHHpvNLZybwY0BTVu+uoYje10OSNnX2qcWuQ9omxmDqNsnL/D7fsD54wdYzO/j+e9fYhhGHDnBxdXIuXP3shN4V/8WDLsm+LuvjTsd84c6rMV7GA19uE0A7N79unOvct1XVOBqOOF6V/V3R3ClXfsY5j+ss7oHvPm1tk9fvxu1vIO/34mPnl4zUw3eyc1s2J/6nWjnuDvHOI6yDQeA2Nrdead+CyyWvk9tmOD1YRumYwgopnKduGuYg2saCCA2HAnNI2sllhoT6Hcthmxxcvccn/zoY1w8/wa/+NtfYxYtjvMcR9sGx9s5HqVzzNbMaeGbDkNZRw2B5RjhfUKYBdygx8XlDV6d3MDMMztlCc4SzHVlDdpUztktYMs5ttdr2DndoEBku+c6vDC9RD4z+BUIy/Nu6zqBwNdpPGIF6js4yyHXqO5miXy2B/HYmGoeMy2eXOyZaw3TgpI6whJPPbm/60zza4bXf8SuBvW0JoB6g4Xj6PIJVCcbIfWVYwX+aVe7eartrFKpVCqVSqVSqVQqlUqlUr1NUgCsUqlUKtUb0jj2uLm5RtOMMK5FGwJDOnKENtFhKA+QC9haNASG45oBcess+osrPB0GPProMd775B1cPLnE5nLFwDBxXWCBlLnWUSVVtCnf70BsrXG7g6IVsNWc4j30lfNMcdKH8NbWuq4pi8NX3J5mV682oQI5ivg1+8joyak5mWrlOolhHD83eXftCRILaMVrUbymukMZ3qZa6vgAgO+6mad9+eQS83zgIs7SyV3UcPpOfeBdvDTEIZtrHw7rCB9GQOca2Wwq7M51Evbu5VoDd4rL5j4YPmcMcrxnZ7FEFbNJm+OTLcZynfOHj3Dv/Xfxm999ieef/x0WZQ115d9xdjgZWyxuO5ykU/gXwGnbASuLVxfXeP+9M3RlXV1fX+HydoP2/gKxnPz2+BKJnLVGHL7k/3XJcXx06CPascEin5X112IwY1m/l+wmBo9XYJDLbuBaX3kH5Y3djZvZOXrtrv+mjufOQT7Nab1hYYrapmNs3cDu6bJOskn1tf0NCNMq5rmZ1oCRfaZr8H5ZTlx+umpN7BpLTedOucaAT2sjSn3qP3JzgkqlUqlUKpVKpVKpVCqVSvWPXQqAVSqVSqV6Q9puNri4eIKmmfHDd3N438G1M3SzGRhNNZ4hYNdRbdiypYnwbcvuybi+wWcvf4mTT+7j8Q/exbOnDZ59+wppO4IMmkfWY8auVcJyiSkvga4cM3b4jUEYuTJr3VRid7TBJo7V3UFZdoQaydoVryz3YYJqhPgixQDbDEdgbkzlOolxXsPQEkJljUDfnKe6v3s3LzPRSm/FB5x3sdUc4ZxivVZiYyhhZcOuzIhEpWzpOOaoBIIrXKXY5CTu0MobJf6axsFKfdqdsbR835SNPgnwHbjUcAXDB07fHeDlxtlav7a2UQ7hcaFn7HatcJPrDVupUSv1jzO3A0lc3twH1BrJVtAwuWob7qjDaFtsXIut83j04fv4/vcf4W/++md49tXXOO/asl8LygW3pR3BDdgQlHUjA84lnbBcYDskLMu1F97hdmWwPJ3jOt+WJtwg+9KvKXa5xngP5PKdD9iOm3LMAjPTYfQB27gtazAhuczuWKobnMvDRctgltZBMlQrWICpoz8hae55/EId1+knwVW4O0WGR559guJm5wqXeOgJKjsG76nOiTiz+bVy3UBjTv+CLe2PyE1daTTv1ekbSx9HJ65qZ0eB/jwliePQxUlM9aLZmi7rMdc5V6lUKpVKpVKpVCqVSqVSqd4yKQBWqVQqleoNab1e4eWzp+hmC3603RztfAE/zLk+MEU1d12Hpmm4Rqx1XtArwcgxcO1Sl4GLz75GuNzg/qN3cPr998p5N1hfr8tjhe04wBmCkOKIdUmcvOQqplKviaOA6e3dVPer4RqzDMnI8cs81nH9U8vOS2p52oFQlpHtnvYj6MsOXQGsBHqjIVgrTk1XU5on+Dc5NnfGY7vfTvG8BFdTjXbe1SaeopipHwQVK5xm6JoqsDZ58payk3iqt8tO4dKWFOs56ftal5e2BKrVa2u9YbEa17bmXexzfVa9qpNzeB8fPWlyTcc8uVLlHFP8cYy5gmDDrlPsurevhczNcA2X8I1NC9PO8fFH7+Hs7h385N//Da5fPMXZvIWPAbQ6TNk3jUBPkHVmMfoR7iThtqydoR8xPkj4ZryFG9bId4Hr2Qov7AW2JyOyTwLKOa45MfCkPhKIZUBaJrYf16U9HYynWOxBau9awaKJo5J9dVcn7i+7okubCArzcNbIbV47efL7ytgRICfXrhWr985RPb0+wV+aS2/3taLrEhQnOt0QAEjN5J3DW5zEHDmd5R4DBtb1GD5uIveQ13lW8n6N11n6/+GnW6VSqVQqlUqlUqlUKpVKpfrHIwXAKpVKpVK9IYVhi5vLCwztBttuxTWAu/kCi+Ux0mzBgNekJVJoMZR9m7aD9y1S7JCNhfMejXc4Chn95hm+eH6F5f17mJ0ucXZ+jHuP7nB0rSNoFgPWqy1HCxPNcrXO6jgmbDdbmDFx9C+hvM12QNmRfJnsXuWHEQgsJVltdeZKndsomBVtclwvNldXbWKYnCtbrnVXo51YL6YoXnEVpx3OE7i6j+O1dV+JEi7jRuflsrISh0xfbWmft+I0DlRTl5ycBANj4vPbmmpNAJZr9dK4UL1kdvMGhp0EBcfyIABM6kZx99opXtqIEzgJMWawjJQO6g//oaQ+LSpbFBDJEDPtXa3U1glwugp+GcNmcQFvyzwP5ZXkPL7/g4/QdA1+/h9+iv7mCqe+Q1f64qmObiRMPGMX70AT1UW8LP9OjhpssYE5bRjgvko37JDletJ+jevlGtvlphwXah/lwdCU2sSklO452MItGqzjbWlz2ac1PGbk0qW1Ss7sWu63fPFlbGU9ZboDQKaPx8O9Vjva7dbRvh6z3cVmo0aZTyCWXnccIb2/IUAgsdQKRq0lzePtp0hyuTlgQrnU5uQSA17HHuy9o32fCZ7rOtw/V6lUKpVKpVKpVCqVSqVSqd5WKQBWqVQqlepNiUDk2GOIkWFw7xsMmxXG7RrdbIm2aRHLdtd2cM6j7Wbs8PQMghuOgi7fcGStaxo46/Hqm6fYfJNhOo+j0yVm84YvdXJyhuPTEzR+Z2xlXtYQRKaYaQKIWdy+m9sNQt/z89X1FjdXN4hxZJDsra2O3RrTbMTlmy05hp2AWQJ7NmMKcqZNjakR02mCoNUFvCslfFAjdqpBnAREWo6NFvFZGSBa/poI+toGsewTKda5HDOmKHWHy+shh12N4ulyFFtMdXWJD3pJZS7XSAy4DY2DrVHTY3WT0rlzrFCyumFdrZ1cBtOXuQkh1G7sXaIcNW2afYx2bQHXv639ZYjMEdviMKXzx9r1zJHGFtsy1+iW+JMffYzlYom/+aufA/2AO2U9NCmUeeGe800B5DbOprTHRfgji5vhBlhQTeEbDPRX3Ixwfel72YfgeJplbBc91u2mjIc4vqUerzSXauwSxG+M43jlbAIfRxHMw0jjlOG85bVHIDVRveLSjia3pV10A4OTaOsypqMJAoFNPoC+dlfr19QI6GohF3hO+9UY8EMITHnoh05p3j7ViaY1Wm96MHWtMMSOmds71RW2U3HhODmFbb22zHs2U/74vp62SqVSqVQqlUqlUqlUKpVK9TZKAbBKpVKpVG9MGYZjdhNSGBDGEak8hu0W3WyNk+NjxDSimc05/jnGAU3TIaeA3LblK8X2eiRPkcIZuaf6si2Oy/MUEsbnVxIdbA0u3SWDMWcr/TISfduV83TzuTgqU8K863B6Muc3fPI/3r13zvB4dXuNm1cvxcbJXDcJwCMHa41Y7pnTWnREmSM5UiPDaZ8lTpdA6LgDpAJ7c6XRrnHlEIkgts6RjZfhI7U5VehLsFfioJPU3i3P+5QRKU65vE4g3c86Ohs7n8HNdNW9C4He1Qq82YYyFhkLAuvRoeHo6oCWKB+DTYputrXma3X+Vjey9Y6hYuIax7k6WaszGnu3M0U9753BDhKtXMOEK3AksIwae2xqZWZbnbPk5CW3c1PWweMPPyxj1OInf/kfEVdbnmPuKdVFzpHHTQLCLQNbAtQEl/uyRnxb+lfmNfmEwW1guvIVWyovXNZPGWo/IDUjWaulNrOZDMumAu86ZxSPTdHSZc5DuW4z9+LO5WYnqeOLhqGvHRq4sTyi5zHvyzVMV/prw2vM/xD+8jqgeG86j8378axjQvtRTLTMbeZtMsYCbTla2sp40w0A7E4uHXSxQZs8fFlTtvRhLD8VsYwArV2OJK9rOgnx5vOwy7t6z6X27/4mBJVKpVKpVCqVSqVSqVQqleptkwJglUqlUqneoKYauFMkbhgHpL5Hv1mhX9/CzeZYHB9x/PN8vmSQ58cZmlC+Ni2cb7BtPTtBjW0ZAHvbMEjz7PB1yFRDmJy0FWdKXVYrzloCuTe3GI1EMIfbNTavrhnuEktr25adqQRLCYTZfFgLtcb4WoP798+BkwWu1yvcXK4QyBlbdpuZiiVjjTm2ubopq4OT+aqcQ2oMV0eok1qsBI45DrlsI5A9ljYMZYxon3be4vT0CN2yg+lKv2flWqX/40gwM2Cq8jvFK/M4Z4LNHtfbDa5e3eDqyRU2qxGLMk6z7OBCjy437BQdnTmIGTbVHSqOZxoLrplca9ROcdYCDlH3yzh4Wt2usi/BbqpJSxHImQGjrect13QePXHocu67Dx/g3e+9h+vLG/z0P34KV/p2Sv0cS/9C4HZS3VzCvymKuxZlLaBe25bx935WTlauRXHYvqwxNyAaqv0scd00Fz5j55ZNtY1piu1mB3MU0EtwfqpPXOOtTS23y/NI64oAcO8wj0fwsYxlWQgxXCOVvyINOdARqvsXOyAO1HrLfGqpy2wJ4O4A9D7u2VQL+aEjmMcwS7w5r28jUeM2l5+NsUHTl5+VPpefj9LHZkQqayB3pR1mRM01L/vmveO31mSe3ONmcqgfOLxVKpVKpVKpVCqVSqVSqVSqt0UKgFUqlUqlekNiIGiN1EnNUyyyQEVyl27Wa8TtGrerK679e3RywjWCm26GtptjNpuX71sY36BrRzR+hmwHwDU7UGYbD1Me1nu46lwlSIfBsJOT3LbkouT02wp2CZ2lLA5MQzHVITIUZEdmNhwNTRsYiRGYTcDN9S2a1uLs/Aj3Hp5jdbvBy2eXePXqGl3586GjyGrqW5I6syZjB9aySbvardM48GvsxATHIAdncBtGBONw/t59vPfePbSzroxNj/W6x/XVNYbnAav1gLEf2Fmd68kYZjuBrrRtPp/j9J1TfPy99zA+fhe/+/XXuCptHct+C0+OYEg9W6Qd8ItJXKZTnyXNOVfwKE9zpb3mACJOUcfT9tdfk3q2STyuHI8toNshNg3uf/AYjz9+jC9/8xme/v5LtOW4WZkrX8bBlzFzXuAko3s7k1rIpZ9NnT9yvc6wwNKe8n6tobjxniFzZG6dpc4zhTdncc8ygEZ1Aucap0yQWWh8mY8K/bNl6muqm5kgbYxlv1h6Eslt2+LYnMAEhxndRFDOdT1cMoCmOOhdbeQa9Ty5gJ2f1sBEztM+GhrCZx2tX2rva5nMtR3W7G8soPrCg0cTOyzTERampYlEbwbkcVV+BFZlnC3DfDOtP9RI81wd3wST7f4mDZVKpVKpVCqVSqVSqVQqleptlAJglUqlUqnekAg2jVHqz9oa/8s1Zcu7LYGwVGvgpjhiPQzox55dv+QGbro5g8yufF12C4zNBl0zL693HBVMNYHJ5du3Hm6waMkh6xupwcqxygbWTwDYwifDrmFyFOcap8sBx1zH1rOT1tHBUWinq4VZCRjSnpvNFhdfbhC/cWiXHe7eP8F733+E1focr15e4+p6A0N1a0PivjHwnOriGkGr4uCsMchca9jxa9sUEcr+9x4/xIP37mJogCcXr/Dy909we3HDsc02BLRln3k5YDHFS091hukqo7g7CRr2V7d4enuFb373DR59+D6+/+Pv49n5K3z9my8Qh4ilIUd1xOTtTWkPglGdxNO5OI3aiIs1VwfpBIKpTm4sc0iAXeKL94B4eiQ+j/Q1M2y0iGUBPHj/XSzu38Vf/eI3GL75BmcEdmncSz8bI1HUlZoyqMzZ8fxSdDYh3DLT5VGu2/syNjP4WM5PQBRdGZvEDusQCMSKQ5vcw9mGGg3upD30f1PXZ66QlmKxK1ylDdTH0rOyLMo5vWP3bwOKXG7R2Rn625HHwLZlXZR+jVSBuBzrKvSl4wTa1rrP1bctNwCY3Q8K7Z9q1DaD2ihx3nvX9VSfeQLsieepIQd0KiNRFk0bZtzRebtEGm352dvAdjL+UqdZ3Ol0Y8Q0vNi1CDt39xTqrVKpVCqVSqVSqVQqlUqlUr0tUgCsUqlUKtWbUpbKoowUq+ORY4G5oqvAX1ejm11DYDEiEwgeRoT1FnG9wTibIXQbdLM5tu0cvu1gXAPfzRgCN0N5tA3GcWDY61sCwZ5rCkt9XnGeEhjL3nDtVEnkNewarjiNYacJVuKAjamBvVInlfBlw3AxMzQebjb49mqFl8tXOLt3ig/ev4tVTLh4eoX+2S1iDPClLeys5Bq2XOWXgXXI9BDn6ZgjbOexODvFo/unsDODpy9f4fLFK9xe3WBR+nnuyOGZ2SFtyJFaI4Wn2r2pjiuBvVTdutTW4zLymzHhyaef4+biBo8/eozjv/gTfPWb32NztUF0CXOK1Y6R5ygTMHUSVOyjRUPFlSnM2OQd+GWDdE00FmezuKmpnjDDdKG23Dea21id0I0h6OswlisNZczf/eg9nN09xq9++VuEV69wv+nQEfGk2GgaswpKqR4uA1snNWtpc+LayARLy3zaiLFdY9M1sJHqLw9IHLW9gE/UBrpiYpA6Ent3mWfT5RbUa3JmJyP1ll0SF25qCLZnSKldGtNQ+lFrNxPMpWGnetTzhFW6Ae6UddFlrMOajzVc7xhyMwFD2uqmrkCX1iS5jAnkkjM515LV4hSeIpjFjQxzMNZsITcV/PNqKtu93ODgKU67x4rrSxvMKdp7iOIwr27uauiWSxHwDwG2uqT3cdP2wJmsUqlUKpVKpVKpVCqVSqVSvT1SAKxSqVQq1ZsSgaUktWC5XuwEE62t0cXieGS8tYtGzuwMTmHAGBJiP2DVrrBYHDEEJvdvS9HQGOBjh5jo0SCV7b5pGJIRLCTjJtWAtbXObmC3r5A4dt8yn4sC6Ur7PLlJpzq3vJfEKU81gemrhThFCWh2Zb9x3ePlV89w9fISi7vHOD8/QnvvDl5d3uKmPFabbTl9qFHCpT3kfiXwN5+hWzg8PF9gvpihL7s8ffESN1dXiEPAvFzjvmvgSvM8HRuTxFJDHKUkZ6urM9V46erYlbjfco0KMclNfXVxhV9d3eDdD97Fj/7Zx/j8N0/w6tlLhohzqjVM8cYEOhl+C2D13NvM44lc52+KRHZO3KLk/p1cpJM7mMcus9uXx9aKi7ov24bW4d1PPsTx8QKf/vw3yLc3eEB1nMco9Wmn2stGauZylLcRBzLdKMD/nGfY7HgQyjnNBtfkn46RSwO75gh2dOzANmZLJ2fQbmwDm+iGAILFLUP93CaOjG7Ka7PUItJ6K9fxMdOpEUzEWAYx1qhsGhNTxinYct4u4ZpqNRN9LceEhmC+La+NPCY7F7Wx+1q+Fe56OyF8cVuzw5lmQ+zr4hY3aTeeOKjTm6fzSuVpBuGBIp9LX2K5Nh29DrcY/QjT1LhrpJ0D2VYnOv1cTtHPE/Sd3OQqlUqlUqlUKpVKpVKpVCrV2yYFwCqVSqVSvSFNcbYMwLgMr2FXJ4HEXINnOQZa/IkMy+h1AlFct5fdiRFhO+J66NnVy9HQS4HBVCeYvsamRS5fU2wQxlH2awKiHxHDKLVXSzvEGWy5VjDtM0Xech1UiqQ2+yjkXGnY9JXclJbdxJnBJjlVKR54Vs632QRcfPEUL9wLLO6c4r337+Pjj+9xbPRqtebXhz7i/O4CpumwOOoYPl9e3OCL336DzeUt2nLe49IugpGR7KLlP3LE2slBWttJ31O93qnt0kjsnMC7yGCCzbGMcohYlHYSEP78Z7/B9t3H+OD9DxCGAdcXFwwd6UHwmCKYuV5vGXNyvRJcnOrkZp63Oj5RrhNom8m72rI0l9aK5xtJ5jQQKC/96pPBhx9/gLO7J/jL//dfw44DluUoD4HIuTpu2bC6c4t7eU7ubQKYUYAluWsFgJZ5aErfslyTopDbOEPqa5w3NWPeMiCl6O9l9GUc6o0GbcYwbNGapvS7Q7ue8fFmQ4MQOC56bOlmgdJHKzcviPt25FrCdNOA8eX65WSB1oMvY93Qeib3d1Md0zVke4LbVgBwNmVNx5GhbkOx5Vl85hJPLWs1ROzmU8bF1VhtsfHSOszUpnLdEAPczJW5Tgy7Q2kj1U+OJrKb2pg9aI4QFzl72w1qDLVR+KtSqVQqlUqlUqlUKpVKpXqrpQBYpVKpVKo3qAkaslu1xtmiAj9jpDYqvUb1YwUYG67bSsrVzUoRynGMCEOPFMbyfY+182i7GRbLI4597mZLNOVr08zYCex8i7bp6vce3jYI5Rj+nra5yE5WAsIMF1NAMrHWs62OzQngUT9ilO1TMi8RNHIql+2Lco65n6PPI24vX+HXN9c4Ws5xdHzEx85mHdczvrrZYLO5wXq9RuhHpC3VuwVOqS+lDQ05bEPCcFgnlk5Q2jTVcJ3qB0/jOrUxTu1DhbMUL+0dfNlOjtbWWBwdneD6+QUuF3P88J99iF/9xmL9/BXXrvVjQluODTQONB8215jpfT1fGjueF1QHskwSjyFfl53KUsuW6ioTAB3Kcdsy3nfvnXNs91/95U+Ryjwet6XP4whP7lzC3LWmsVzLsatW1g04opmniGsSG4avNPaxHEugl9yy3pb5zmW+r4D50PF4BuuwKePsF0v0o8XiusxTGetgB/T9bdnu4NoO8cbiZDjGPLQM4pNL2LgtbuIaaB2iy+UYmotElmy+eSGU8W/ICV3dtZQ4nWyskeciimPOBzc3SN+kP6acl0tCk7uZoHmu48z3F5jX5lKOz6/9PMlrmaO70UT0VO/XyljQDQQjQWYC2TwX5uAGAYij2AiQthNU3lX+nVqvUqlUKpVKpVKpVCqVSqVSvT1SAKxSqVQq1RtWrhG3XGM1iZPy0GkrUdC2gk32ku5e44TjFNE4AY5k7IzDFokcruXruF0xWJwvt5jPlwhND9+07PiMZXvTdGjbFtl1SN4hRs8O3kRu4EhuS8/ALxPErPB3ci3L9fcAW5yUU5yvQGBmkeRkjomjlBc2c3hyuFrh1dUGgfvrGKZS31y5dlP2m9G5yI0MTjLmB0f+mowm1Y5WFjd5fcXZK1HPBKq5Rm6Vq5B4+p6OZ/hHbaxAOSSB1U+//hpjHPCDH32IX4eIzcU1lmW8bAgShE2c21Z0GSvErC7SvIvrzpUmGjb72hp7zI7SRKiUoLBHX/ab372L+w8f4PPPfs81no9K+xqKBicrMdUhto3g7jrOJOqj1Mc1DEptjaKu3JLrNNO/mGQMZsbBbzLuxwX+5PwR92ewEZ8+e4JVKPNR+r1YtXjv3bu4TTf44noNOyvXHcs4DS1+9Pgx7tsZ3BYYSoe+XL3E7arsc+zKGmlKl4L0z3Tsoo38vWOHttTaJVt0sx8HVHibq4OXF3R1aNexs3YP13c6HIMDGCvJ6ZNbV+5CMHV1UO1lisVOLkqUd/1HceV8o4I9gOm8mmq9ZiNzN50pqw1YpVKpVCqVSqVSqVQqlUr1lkoBsEqlUqlUb0jEk3J1FlLMMIOvCqBeg30VTk1AM+XJZruvebqvfSq1VCdX40gQOIzYbDboujmWyyO07QzdbMaOYe8bjF1XvoobmOBwioG/JzDrXQvfNsjJspuX6wdTDC+5gysI5ojo6ng1tRYuOWBTFLCanUBA+iNimZisCbRloOsYsuVKLqmub1NrsaLW7GUQV4FrKptnqM7j8n2g6+W8h6v1+uzerHWAJTb7dXhHzlSKkDY7N3FiJzVdl67/7Ksn8LM5Pvjoffzq5lOshgHLMkeeLKU5SB1mjuCGREwTCK/UcV+3FjsXMLtZeRIDIkH1cq5ANYiPj/GDH36Crz/7AqtXlzgm8F7my5PDN4krnGOnLXYmVILpDK95/MXt7HgOaJ1YiaTmAc4MqvnrUOZ0dPjg7D7m1w7jesT5x0e4G4/hNz36MeLx8gSP2gW+ul3DJ88R1zz85d92lcoYJDQ3GbN7Lbt7aY30COw0pphnTzSVaggTsHZTyrWR2r0U0cx9iAzcd87dAwew1OClf57rM+cp+npyPtvJ2UtjUG86OICzErFtdpHOqFdIksktY5nSdEVx09cawPwzyOO3/7njSHRr6s0XBqmOqUqlUqlUKpVKpVKpVCqVSvW2SQGwSqVSqVRvUnnv8k2YnIgJ1bi5A31TFDR9ZRCcpQYs2U1z9gKF8x5s5QpFLUcAG4QwYD32GPoN2rbDbL7EfL5A07SI4xyu3fL2Jnbl2iN8aOF9C7SpnKO0zHu+ztQe0mGNYIo/JscuGzoJr9J1bd7xslrlFS4L2GVHr93Xs90ZLcU+yyCZXrNZopZzBXgCgXOt6wsGj3wqrvsq9W+JHuZaX3ka28OaxRzXzHDVljaLuzrXeSA42dH5HPD08y+x+NEnePjRI3zx69+joXmgoY9sG+ZoYIox5qZPjmiO5RZYzrNhGzAapzq9pgZXty22AehOTvD9H32Ey6dP8fyrr9j5Oyu7euvYJZ2pDrOg8KkIsDh8na383/EgCvCsUNVNUBjioKbXkuG58K3UM3757AbjzYA7Hx2V63msrre448j9u0BL7DyAIW7yBN5LCxrg25eXePnS4iw1eHByB9fbFeyi9GxWmlDO643nGskxc9Xicp1DF2+tfUxQm/Bunno1RUDXyHD+Sg5utwP6HH3tMkNaAs2m1uWl/aZxZyCcTHUAT0CfloHbR0rzDRaJ61TLXpZvAKA1LDcZVAexkZsDaFs2k1e53lTAN14oAFapVCqVSqVSqVQqlUqlUr19UgCsUqlUKtUbkt1FPQv0Jcx1WFdXQF7cxeAyGCYH4wRNM0FGh5ir33GKRM6Tw3JyoEZ4KzViY+jRl+P7vsdms8Z8tsBs1sPPWo6C5kc35wcB4ECO1TDAuha2PCf4SDVZCUJPzl96hBBgvNQMpmhda9POtSn1X6UxNlUgSX2l+GczxfUK1A3VOWpLvzmeOTMn5sjjHU+msbBmSg8W2FfH0NOYGap/m1+rA3wYqc1jX8eGzhFR4TsEDFO7GkMR2Bkvnj7Buz/6CKtxxM3vn6IpfW8YuAauJ7tLJzZiV7W51vutru1cPaZUtpkjmUu7B0PO3yWD5ZdXV/jdL36N4zLuC4KjIXLf2ZVKcJnrPQsIl3VSx9E6hqk0jhTTXc7MEJTkvURqH6RkIzXA6BO+ffkCs7HFydmC3dRjcqXPHu8+OIMdy/rays0FNL7BOYTGoDvyHOpsjwwenN/B2m7Q+wHmuJygIxszrUI6D7j/ucY4W0frGewkptRtMGA38LERtzrT3Ndr99I/HnteNFlgLPXNyM9GMmlf+9rsx9raac2T2zpzG3i9pIP5KefkJOpco53zUKPXU41hFxc6PQ/kGp/Gjl+v4Fj5r0qlUqlUKpVKpVKpVCqV6i2UAmCVSqVSqd6QxI0aYSrZZJyX4y6SlhyeU0Tx5LZl9yrV462OU4HCo7hdKzCTyFombvXh5HhyDVPkcuQ8YvRxgzgEbNdrtPOO46ApGno+H+D8Bg05gtsZmm4GX75aioi2jgEwRUCTA5kevjws1QeOpR3eieu0OlI5jjhLXd7JZWsqLKXXKr2tYcDVxVzjrQ1FRzPEywzzSDQKuwhsCNythVplTA/KxdqDyGB2hVZgmGustKn0+DAemtvNkco0Vg0uX93gm98/w7sfPMZvy/fr6w2OOKTYl2sFHm8+fmpDmmrzOn7NpSAubLIMuxYj7eY7fPC9j7FJEV/97mvcbcvZyjE+Uy1nsGM1VgjLY5j2/eUvkqJd4WndJ9td/PQER6eKzI6AKgH8Mre9TZgvLM7vH2N7m7G5GXByPMPxWYuvfv8tHnx8LmA0Bm5zbij+u2EI2s0slnfKfi+fYruMCMuM2NANCmlX65d5vt0XPTbVqk2OYIb9vPQcR0yboew2ZIksp477jBFlDIbyeu8QfIBbWoQWUkOYgDjHnVcP71RnmZf5FAtuxBldrjXSdSNB/QYut0jbJOM01WimbQgIply1XIuuQbCa3L65zCNBbTNFWO/cykqAVSqVSqVSqVQqlUqlUqlUb58UAKtUKpVK9SZlp7q/eSrri1gBLcNSdtumnUuR6pJybVxyTFZA6NnhWhNqIVnIYUyvOV+N8WVzYjCc2WGaGTjHcYscynfjiNi25fuINEa4pkU7m6MZA9pQHjnApgbROTQUDW26WmcYCLG0i0ydHO2bkCimmq5JNYQJPmap7Mr1gyukzFOB1yzw0kzwMslY2AqPpRRwrnG84L5xBHOCOFx38Ffcm4zPaZ8D9y/B6n0d4FwdrnW8aJ9Uo7LJXc1xyZbb1ZbtJ6Wvl09eId47x4c/+AC//cXvEMoY+TFVyE0DMBlZzVRNWPoPimDe8KRG02CTPEbb4L33Hpd2eXz2d7/Asuy9SOMubjjQDDK7N1LpOEtU9QR3pzrPPF7yP6l7HAUSO3aQJ47Qdlyz2PK8NaHjWG8ah/MHCyw6h6dfrsrcZpy/u8BqHLCiISzbm1XGfCR7cFkPQzlubDAfDB4sT7HZ9LjKW6xmESs/lLGSmr6CmyV+mwbDVthOY01roPaGx8fS2tkYLNYd7toj2GAwrMsYzDNWdoNu43DuT0p7NrhYX2LII0dNx0Q+ZFkXjRnrGa3UkE6mwnxeRDyGVDfahgZmXR4rB7v2ZTx8jUhPiENZEzT5sx72aESYDQhlnU/KshRrMeLELmgFwCqVSqVSqVQqlUqlUqlUqrdRCoBVKpVKpXpjMkjRMyzj2rHY1zCt1WLL/z3DJ0sQzVQnrVTCldeT4Whn9vk6R2nPe+fr5Hakc1EtVyMOY8uAzlVgVmuc5gFDP2LTr7g+cNvNMIahfD+CcnPJ7Wpjh/KCnJOoWyvnIcclOScp8jcnW7760o7I0cTSdovMGcDSanIMcy+y1HOlEGaOfZ7ir3Ot+TsBbUztJBHQ3dt8JcL3dSjHzleqo3tQA5jAt8Rng93KudI9gcSTmdbuxtUwtA08/q7s+8Wvf4f3PnofD+6f4/mX33JNZK7QGzmvuqJfUyOp8w7gxzJvqYzPWNqcynXffe8dnN1d4rNff45Z6fTMW3bE1s7UyG7soq1rh3Zt2ve11qc9NKXWWsaMYunGgPKcPOTUt4bq+q4DHp7cwd2jBb797UvcrgKaI4/5HVoLDT5ePsS883jn9AFWFwYvbhPa2JZjDealn+QUfnZzWfoU2bHLjt/qwLa1FrHYrafcZVQHeN7XXi6PjtZyeX52dIQPz+5juAz49ukFxhiwmC1wupzjwdkJVm6BzeUWYxq5Xq8gZvkZMGbkGwOE0h783HAx4cRf3GgxtzN2Q7d+hrP7d9Df9hi2fbnWiMXpDM2xx8XmOa7jrbjvDVcb5vXhvN0PtUqlUqlUKpVKpVKpVCqVSvUWSwGwSqVSqVRvSFLzlDN/d6AzcV1c7KNtJ3cqOxDBDk6q8do4z9BYfKYSCc1gDBLznKu7VuDuyHHKu6hiAolGIOUEFZl/Umxw+X7Y3pbrDBhDz19D+eq7Gbr5EmkcYKxnuNt1ixoDXdrTdHA+I0T6vmEnKzmFc3WDetNIS4kX7vngDg7K9zwq2IFNVHhtzGsR2FMN2On4Pz62rz+frjPFUKPWCJ6gM8PaMrZmd93ELmGLiJl12Gy2uPj6KT7+kw+x3fZ4+uwlTnzpIzWL0olp3Gk8K4ikeGKascGQ69dhW6517/E55qdz/Oxnv0AzjDiiWsDkRK2QfNfmjD3T/E6HdvP1XejNc2dlbMnJyzWTc63LW/6AGzLmZW4ePTiDWVGTAxbnHqs04un1DaxPmLkO3VjauoqwK49TKu7bztCvt5gTqC/9Jdcv52M3AktJ7DTnCGorjui8b+tundf6vMLGR95+c3uDL65KGzfl9ZBxZ3mEm02PTdjg87IGRz9i8Ft289pdpWdZ8RFpB/EPmbipNX35JoKy1mkN2+DYZbwON+w0pp+TWMZ/PfQwPc1Rz/HTmesLh+quzvVGitcX0hQjrlKpVCqVSqVSqVQqlUqlUr1NUgCsUqlUKtUbU+b6qRMcm5y9EvMrTl9iaVTzl+OJeS+JMhaHLMHgliOiDTtcQ639u68jLHWBy/bsKliW6+YUamqyY9iVGAILiAwxlEdECAM7edllWV20SHLN7CJvI/BLrmCKpub4ZKrVmpzU6i3XCENmWDzViCVASeCVoDHHWR+ORpaI6l2NVhbB3ym+2TCUo3PYqT6uyXjdFbuv+RtCwuuyta8VQnO07+Q0FpBJDuppnAJlO9MYlx2WpV3ryyt89fsn+OGffYzbn2XcPHuBkzJ+tsyPZbZO8dRjhdbSkNE0CE2L9z98jPuP7uKnf/PLMiY9luXlOe1JkdsUy01tqOeZmOOEHiUyew/D92B1H/1Njt+c5GYCLnE8uZEpNrye92SxwPFJh25p8f2HjzGUQfj0d9/im+1zxNyjczN8/+h9PFtdYjWOeHR+BrNs8PvbG/iTFkMXcL1eA8cWox2534S+TZa601J/V9q1h/p7SCz3JCRsQS7zrqzSAdt+ixYNTuYLPH73DL/57AnHQIduwGApFjqV5VTWog3IVla1XCvtYsMTr+fMN0+gxjRTDLnxuZx/ja6ZIZadr1cDmnmLe3fu4dm369KK27Kcy/5tWY8dmYzrTQbVQc/3BpjX19bfd8OBSqVSqVQqlUqlUqlUKpVK9Y9ZCoBVKpVKpXpD4mhiV8FvrjV03T4+eFffNcQK+wimmp3LUbixxNXmGHh/gpC2OoGFAUq93ByMgOTKr0zdIcdcgdrkzqSIZifMtxwz5rFcf4VhE9D2EcujJcycbLwGIQWOf2bfayIY7KTebsi7OGpDNWJtYkjNoLRsb9tGYFvpl3O2tsdUSGi4nu0UGTzZYamN4tbNOwBae7Jzxb62Oddo5+9ageu4RwaFqBHGFXCXvtB2W+E7n6PCeEKDbRn7i6fPkbzDxx+8j6/LMesXl2gYSpc+kw+4QtBEQcIEJbsZ3nn3Ie7ePcXPf/pLbK6ucVyOdwT0QxCga6u/lWO5BWbiwOVrD2o87+bP7vstbfTgFlD8Nsdp+1o/GaCU6tFHrM0Wn716Bh9k+6bs+HJ2CxyXufENbsYNfpueYLxT2nbs8czcIA4Gw9m27DfgarjBuukRO4/gEy0BcZ9naXtiWB/gDkyyk8N65+AuXQxuQE+x0eV7N3PoNz1W8RbXr8rDXiMsA4b5gOwI/iYEE8o6DLyW+SYCimfmSOh6U0Ntg4yRZRdvTFFqADdlf0PnGGCXFtuhrOXtBptuA3RljJska4Ed2xIRzvWU+caA6Y4JI+ng+Q/XkkqlUqlUKpVKpVKpVCqVSvU2SAGwSqVSqVRvTEaA1a6MqWW37Q5oArXOr3iDUeOPc3XCEqyKSeDoFB3NNVdRXZiR6pi2cLzN7GJxJ1q2g6PVTczPCR5nL9AzUSxyRhoiRrvFtg8YtyNmixHdbI6mm2McI5p2htFFBsAU/+xdYndv8mAgSfG61C9X+sfgNxP4LV9ceR4iQ2GCzukg+pm0h8AiiWw2EomNCYbmfe3caVQPwXENZd7nKosYlNbtjhy4FVBSfeTKwsu1GobyPObkBC77dWWKLr55wvv8yfc+wBelv0++fsb1dn2tics+1BTRLlt8+PEHDEd/+bPfYLhd4dQ1cMMo7tLSBop/pmOsqRCZ2kJAMmFaFK/1a+f+PQDfDHwZVpML3HENW3ZK8wM8p+HY4sV2jethjaZszOWaY1PaOSvz0sr8040Gt/kS9k6HpkzbdXjFbNUsgRXFNpPr9tiUY8o16S9CqsUcp8q89rXx3c/Dd7/PCGRUprrJZkR0mW8CiGVtXY3XcCcWoQsYmmF3A8MYApKR/XanMeIUTzHvIDD/vJR+8Zota58AMGPd8pUcxL6TtdiHHnmRuf3J1Bhpdsrb6pzO1UEvfTITfVepVCqVSqVSqVQqlUqlUqneUikAVqlUKpXqTYkie9NMavFCgC5FLrMjNAuUMhzpXN3CFXIRXAwhs6NWapIaBpeosNiaPUi1WUAnAU6Oec5mHzEsGbeYUDMfIhm7XM+VoSLElcuQNQLrmw36bcRsHtB0I3zXoZtLLPSsbZBbclXSvgaUMm0ptrch4Jrhm3INgm7RMABuGnH1TrVzba51iqvLd3IsE/g1tQ6yREJPEdBgZ7HUfj2Aj1lqKaeJ4UH4ncQTc8/3DujqHJ7gKrtwaRtdExJpnchlbQgPZszg4Mt+62+f4Wnpy/s/+AAnd8/w7dfPsLpZM+Du5jM8enQP9x+dYbPq8du/+x3MZsAdqpMcQpm3hp2+yYqTl5pI45BM5LhsapdzAq8pjpszq6vsrgatvO7qc5kpOodhV3YZVAHABIlLm2MZ+2FGQN8hEBAufQq+vNZCYshDmcNQ2uUthnL41o1IY0Bb1h+5zqmmMwFwW44bfUAs8+q8uKd3I29MbZ/AdJk3swfXvP5KK2lBkNuablyg81AhZZsYigdynJPrl3rE9w04tjBTG6i2tUmojmeJOZf1b+u6SBXc0r4tbJjqAUvGd6ow2HVycwTNaartzhNwr45qrl1d5uLQQP7Hai+rVCqVSqVSqVQqlUqlUqlUb4MUAKtUKpVK9YZEMG7cNDs3KsfWkguUn+daE7etJXil7i/XPI1RYG12vA8BSnLQCkRO7O5MFWSNQSJzUZ2tk+j1VKOFOXrZJky22sC2TydAlL5PqDWCwbHG/TCWxxpNm9DMEvw6oW0Dhq4tXyParmxvqE0evimvEVf0GS25lb1l7k3lfzmmGHLNnMgJTABxgrW5QrksQJPdy6WdFQQzBJ5ioWt93ENxy83eTV09vTtXdZpAM+r45FpTF9O+NGQ0LjxAHAJtcyXKZQy60vYX317g2brHxx/ex5/9xfeQptrF1uF2E/Hpb57j8tsn6MoLRwQq+4CGrl76SZWCQ5a2OL6klbaW87Nju+Y9e9dKLDTkJgFr9/V1eTXYuj3RWvA8VjSO8AIxA7W4jHv0pe1lHlJIcIkLSyM1Mu889rTJdGUfh8GFsjZiaWfmOGVnPI87wW2Ku468XshlS5e3NSVZvvK8TKP8WoR3HfMyjy629bVa39lwhnTpmwDZRDccJImyNhRJTv0KhvvBcdPk8rVb/nkAO+in+TQVCINrXlv6+QojjxGNSYyRI6o5FpsGvzEMhfnGg7ivuMzx2twlt4tSn8zYfyxSXKVSqVQqlUqlUqlUKpVKpfrHLgXAKpVKpVK9IZl8jG58H4iWoRSBOECcvrE6KxPFEBMUNELXaB9DwM47hEQJvFLrlKJ4fY2DJlNsdl6ieQNBQKZymINAWuI43aG6NClwOI0QUMhAldyeGSMBY6rZmzMaclK6sp3bmDl2l1y8oXcY+47dv3k2g511yG2DNLQYy/5N15YHgbzyvPQxZA9fzumI/rZtOXfDMLGh5+T2jbY6Vquz1QnspP1T5dMEBznWl+v4ihuUx5IBI/aOXrEFI4VaU7eC5TiBYinqWmstg7/nGG3ZysfwvpTGzMBZxov2FwBvMCtjvLoY8ZuLr9HMGk4llkYA/XpELmN9XvpOjuFEMcbl+4FqI1ObKng3FTxSHDYdF6prlkEvjzd4vlHjsCc39gStKT6bHbp0c0DsyjR37LKNZRaj6RlaN+TkHsXB6yrEJLAdquu1Kdva8nXb1BrGyaGJUmOaLleWB8+9oShlOoZil8lBS2NR6yfLmIIjqGN1bAuLzZAyy3sYDOPFuZ2l/nSmGPDStmkbX6K6wKdIZpNljfN8xwpsK/xO9UYBoI4L5IYFWtRBKDss3TxALnh2H0ut7Dwmnq5E9ZNzvQ7bjnv4JktdbMuVjWvE9UFxY5VKpVKpVCqVSqVSqVQqleotkgJglUqlUqnekCjCmSJ3c43OJThKYMoaAV3suqXMW0qKpsqwBH8t0z9QijDBvMwxv5lhI9U05RqyVmqbstuznMc72SdRnDB9dcyc2YlqEsHWLN9DatE6qgdbaxEzsDVUVTYxaDSU3Ux/DdSY5RwHDGEAU+TUI6dZ2Y+AmWfoNwyBnaQuO4Q4omk8ZuXfkGstYIq45hq71XFM9YC9Z1doShKHHcnFWSOhGdJaqYGMyfGcpI7uFNGba1VakWH3J4NhWyEx10v+rmd4t7scacWBiz0f3kVF53otFyMWBFc91bCNgtRrfHRLTtfSDzNBTVsjpn11lda2yznd7tpc57b6kMWFaip8rK5fPiDzvPH+PCfl+kbWhY3iZJa4cMeO4zZbvj61kCFwaT8BXRoXnmOO+q4dNbnWExZHMq2LUI6cgsIpgznLbtKv6lQGamQ2jQu50e3UPyv1niHrRTqROXa6Ws55Te/q7Brs6lvnKZyc3MxRYsKF0O/rXZNo/fKhtf4v70JzTOuOHeJZIp2pP/Sc17jl8TAMly2vVVrzztN68eVrnDpZx8UcLA6VSqVSqVQqlUqlUqlUKpXq7ZICYJVKpVKp3pDseAuzfY7q1WUYReCNHKaWE4stgg1YY8TQOMRWauIy+A3iEg4EvxrD0cxcM7aciVgwhxVHidAlxyWBujFmjoqm+OGeag1zvK4Fsa4xR4ZwDdV5RX3DJ5dvORmbKGnjKEV0U60TTPuHIbBbtQ8GwzZjO+swjEdoZzPM0gK+adn52nadOF7RYLTkhvXlecNO5ZQHdgi3TcM1cA21haOFM4M6rn9MoNi46s6tNYCprexSrUCxMkSBwuwPriBTnKEct2wlGpnjtI1UPs7VCWx2GdkCFH11BQs8TgKf6/VoGzmuuzJGMYivWOAs+PnkFx0JM06nneBlde2mXT3ZKNfgRVE7kQSukhOaGXmtk8wBy5JKjQmgxtK3sRxHTmo2yDLajAzvyfHN4LlzZS0ldm9zNHYWoA+zd7W6CkenMUF9mV3gDOOBKUd8GmMe9yQwVyLDM9dNlvhyx/OUKuiWmr100sggmc+Vc40xr+fgcxsB9DIM1Xcr48FgP8mNEVPdZ55zmu9U476zzAGvI2NrDezqBK/nOZxnYzyPK7WDjktp5LXKw/Fd4qslgFUqlUqlUqlUKpVKpVKpVG+hFACrVCqVSvWGdBw3+GTznArroskWNkrksJ3ib8u22zbjZuHKo8VtYxmIEXRrrePav8xiyRHrBWb1VNO0ERcwAeCOQarUBPY2o3UOQ7lISw0o5/DJMggcXUAo5+VIYcJeBArZJZnBKcXOVBBnuP6rdeJkTS5LXDHF67KTc8AwbksrunLZI1DwNAzB3zm62QzkQ80En13L7TcEgo3AYFgBfzEFdpHSeRPEueuESFdo63Yu0sk5aqojWPhk5jaKs1QcuOR2petN7lHpiqlu03Rwjgo4KbqYHK5GAGXmqOEJIss2pOqghTi0UR2vyZP7OvIYwU41jQ9rDAc+j6+uYL7uZPmlM9EkOxlrhtIVHIuj9oBAVlhLD08OV3JeWwHMdLNA70a+kYBqLyczltcICoMjnJ2QXY445psPLMSpy4DbyNcJylLt3wn8VvjNY0nrhWLJCejWaGkpySzzYiienEF87Yut80VXdHnn3qbr1oLPr7l7eb3VKHQG43LngdQMzmM969SmWOH/BHnjbn9xURvZh08ztc/WtZAYOtNqY+hr5aurY//3eMVVKpVKpVKpVCqVSqVSqVSqt0YKgFUqlUqlekO6nwb8F6tLhBhwZ36CYb1Gkx1iCLzteHGKJ87hVzcrPG9nlPfMYLcZIhYE+caBIRo5eKlebmw8VuWdelP2G7hyKfuA+R/FFXdDwCwDS4JsDTlvyyvJMWjuu4i1zRiEgAlsLNsJ81Jc9MTnOGo5RXjfsGuTXaZG4Co7OYkW59KI3KK3BOm25bUZg2HvyA9LLt8ZxqG03XSg6rPOdVI/lur6EpAm2muk7abSWnI42wrtcq3Jmnc1ZXf0lKGoAFvOx+ZNudbP5e93UcqokL1CwwP37+RETd9xBe9ApbE1AhsMmvMEKflaEh3MUJciiA8CqfmwLG21E1hkoB0O3Mt5lzZcDwD7uU1NIT6Igp76QL10HCNd+u6plm8Z1YdzdMcLvFhtYNoWhOJvn77COAa+CcDVmwwINNtUa996j4HmkSKz6ZES/+HnRwLG4Mhuct5S3PguvtpVYJ0TpohkwzHQlkFryiPPW63Qi3p7w26cOZK8gm3uXxLXbiWvO3f2FMe9kwkyRwSg+aWIGOMBSK/nptdDlshwIxCfX6/rGGaCw1Od6NqOfDDW0+sqlUqlUqlUKpVKpVKpVCrVWyoFwCqVSqVSvSG90zUw4wZX/TUeO4vbcIU75rQ8vwIhOrdOaNpTPO+3WPUGG4pvvu1xZwTOxgQTeoZ58+TQm4yr8i7dLDzsskXyBqP4TGFNhBt7nA4JD8p57XrLkC4xOmwwjCNulx5u6XDtGoyNg29daVvgCOXGGTKNVm421c8da3RvroAv1Zhiy+g5lmMD51iX/ShSt7RhS4HIFAlNz71HR27gFLg2sAsNZrM5XLLwmfCk37mAWQTrrEQ6E2AWGDrVAZ6ifHcYtn6tDtCdmxW1dvC0T7XmIu3mxOy2Q9y0mBKZ8w4SGghgjgRDqWZsNlP5XIScdtcnWG9G2Z+Bbb2uwNv8B+VkDUcO2x2ETDntXLiv1catEHlXfhfgGHFqFdV3HpuM+x+eYjzzuFfGjKKsz6nvJuDV58+wbI/YdS51piHuWsLQvsxlN8NIULcp62eQeOsQIzxFc4fKVk2udZsnF3adil2Ucx2vOpa5upQndy65yqXOdZ0jjqQ+PD6JFXk3XngNsssNB6FOoYyPrbWRJ2Ccpzk1AtBzFgBs3TTaEttNLm5qiHMH18sCfZ3Z7by7roJglUqlUqlUKpVKpVKpVCrV2ygFwCqVSqVSvSHNvcf98zNcf/UccViDwpkbS/BrAEyLFEZcXl8iLloMJmEMCcfZ4ofNEe7c3KDdJMwtsDQeN+Xr887i1+MW2TcIxiEZcVvmmNAOCe93R/gkN3CXI+J6jaOzu1wzeOsaPCvX++1mjbg0uCCAW+OKTZoikcX9GwkcWnF3Vm/kznxLscLOiueVnbil/aHGKzPH5QjmwKjSt92u5iy/REiZYqVLO2KUasYEP8kNzNfj+q8ihoRpcsHKxf9eOHfoIq0SqJv38dEQF6kAxP1OpmY319BiqR1rdlZdjs6O9HqSYrXULHJME1NMZjKRTrA276KIua0p1XZj1zbePrV1um4Z01CjqwliCtyEQPc81ePlcOzddVNZQ5kgbhmwF5cvcH56ik05xcsyv8Zb9OOAGdVTlrK5QONkbb17B7O7x8gLj142w/YjPv/r38GTc3iyPR+0W5juHmZPbZqin80B5d59m2u95lptmJ/XoWXIPUHjfDivE+SX66VdPd9U25ERQpB4anIepyQ3CxyMLzmEOa58Gm9y1FfjMl2XXiMQzCZhI054lUqlUqlUKpVKpVKpVCqV6p+CFACrVCqVSvWGtO5HrLzH2M1hjk+xvQq4BUU5HyM6j2QtLvKI21mDVeMYAvtscN+2eDA4nIYGPg5oMOKkLd83Hi9TQB+A22jQlG301m3TCAwBR97ieDXgvBy3aMv1bkdsDRDbFsbM8CRscRnKhobq/FqpXxsyR/5yfV4Gv7lGS5MEBktcMj+FsNAIW/5iiGNCpWkYy/HeE0D2CONYjnP8NRsLL+QPA8VC54y28ezydVl8rSROX67wjg2nRoAdg8NaSzel9EfH2dRo4klpgsGVKP5R93Ce0oTzznXLdYFrPWWGsJA6zURSOWjb1v7v/KdmSqGWZ7XN3FYcXDNLTWWGlwTYnUQgmwqRLe+87zdJnNFS35bmJJZ5TpznzBWSpYRwOddJed4micweyvOZJ6DuyarMfTFU27nMxZgJ1ht88+IKZ49OYOct1mUttXS91pd5CwygpaRyjbGmNjPozRwDPUVys0k7HUDt3ZAKdOcxpDZR9HOF4jv4zvWF9wB4B2tTjXOusDgkqQEs22Tc+HvIfgJ7edUwGJ7Whq1rmLrlbSMgmWC+txVAy/y0FLkOuzeTq/NXpVKpVCqVSqVSqVQqlUr1FksBsEqlUqlUb0jPtgN+8ewaoz3GGhYbzDE3GUPbMZjdWIPfHs3xzYnDxYxgmsd2CHgybBEagyvTMaBFHrG8c4JQ9g23A+ASjItAM6LHiIbA2Nzh+bhGu43Yth6db/BqWGHsLFBe+9yNuGhbjl6ejQTQCCqC69gSEPPs1s1cwZXhnbHVgev2tWvJeUr1bFFNncTc4oiYImJ5simnWDuD03JcN3q0lClMZ5ycr+Q8LvuOwcOWtpQmsgvXhHId79ldy7VqIZWNOSY5mdcgrp3ga81k3jl/zQGMzBRgLfDRZXHwWjO5QjODbgarOQrYNuIIJdZJwcGmQm9CvSYPZaylzrIUBs7VMQyJMfa+xj8b7Dm02UVRW2mmnJMc237vrM1ThLWT722q1YSzAFZyeBPaTeUkXHqZor6bABvKuL4q43414GFZE9uXEvn9TnuEdbpkAGu9pamtVl6DpvEYXq5K+wO6bo7Lm5e4Xq3RWYfZENHIYO9ipwWUphrynCTYOctzmZPanzy5aYmT1/ku//fU/qHnmwIoKjxaweaG3c6R4XWOMviRnOe0lMoEUJtd2W7jtqylMo/ZYtaX9Tw4jjxfWap+TcdTPWtxLPN5ak3fQK9RV8q/UMaLnNROBphvYCCHO80n94mhe43u3lNslUqlUqlUKpVKpVKpVCqV6q2TAmCVSqVSqd6QLkzC3/gRY4ow65fovIFPI7tlQ9eibz1uTzpsFuQKJlhp0duA322v8JLgm+mBmdR/bfItxr7HMxsxeIdM9XMDcOTLW3c5p5+1uFgnbNuE3w1rpJARXGaomNcjLhZzhHI9ol1Uf5iAbeV44r7NuWwTuOuqQ5Vr46ZUnbgSkcx1c9mNGyXpt8Ydj8OAkd2xpY9uRDtL1U0ayj4RDQG3JNHFsBI9Tc7jUPrRlD6k8n0KEuFrfQNLjk8CdwQzk+N6snZPXqXtxlRPKqpT2Fbw6mpEsABfi+rmpd3MYW1du4+HhsQxSwRxrT1cnavkNBXYmfe1ZKd98j6i+lD7eOhapjYLlJzqDbMLuMw3uVdjmVN2p9YxZ/iaqru4OmgdObXLgLoY0MSIF795ioHqL5MT24Syriya8ljYdl+zuFqM2WVMkHUo81Iac/PkJYbtFnOCo1bWiNvV151itzO7fydH7hQFLvV+zQ50J1oXDHDL62VNxxy5tnPqg3xNss4iu5RpTVQnLz1Pcr1IwJ7WX4xci9qVuXdlzrfl+7X1ZVvD62qwZX37Mij9Br7s24eRiG45T6xx0rWvXm5mCEmqYKfSuhSs7EMwn6Khp1rNB705jLpWqVQqlUqlUqlUKpVKpVKp3iYpAFapVCqV6g1pbBxenXSYYFpDcI+Al3XYNL48HILPGIy4ccmlmmcO29GRURPJd4jOwJsGY0y833C0QGwaxGAwH4F5ECuuKeeh2sA3dzr0tB+B3WwxjwZ2TMgtuU8NQtlOjsxca9CS85fAWAwBI8G70jYCngT+6Gs6iPolusbuUo74BZNjgcHiGnYxwm9DOX/CTXl9lUaY2KHLcxzFgJlp4f0Mnohz2c+05MZ0MM1UCziU1+h5ea30JVOd47Kd6hVnK07YJIVzy9hYdnfWxu1ryVYo7TObm0vfTI1znpzIVty01HwmgrUWLUcSC9xk6ElzxuZZt3NDT7V+GdWaKZZ6P9+v1Sk+jBQ2Qq/trm6wHCSwslJtdqNamFoJeZofem65HjHFMZfvy7zbXMalzGnnyjwMVJjYStS2Jde1ZQetq27kPF1TUri5LwSCZ00j1+GI58SOWq5zTKjViF02MuRP3Px9XeNUx4u6aLk2cSgXG1pX1jvddFDaQYC79JEB8xDFpVtrARP05/VSHbk01jGIk5vOHzjuuoxrmGM1a3HtPa7Lrm1ny/qn+POEWRmHoxDJ41sBsLTJyoDx2OTqJJdxpDrLgfeRWGi5qYHWGt+lcDB/KpVKpVKpVCqVSqVSqVQq1dsoBcAqlUqlUr0hHY0G710Erre66XvMqO6os7gexVnZh4B81LJ7ciS4ZoENx+MOeGc2hw0jtustw1s2o3ovdXIJpiaP5rrHY3+EeQaG1QZh5vAMa4RlixW5IMu1thSsbANH8BrnEUyFv+xojezM9AwgybnbMFRNaYpWnty+UodV6gEbdq4SJBTgadjlS9G6KY5o4hZm1mEsbfdkTx17tIHg94BFafPMzdC0Hbt1l4slnHdorEPXtIw/26ZBoJhkgtxlv01peyrni17ihiNBYIKEMe/qudoaQUxyZZtjV3Ri2Iva11TanNju7Lj/ievKEvA2AkaTRFxzEjKq05Xdt3lXjxe1XjAjRWurW3cqNfy6E3hylyZ2VieB1abiXb6AxFJbAtzkDc6Tl1mAdU4CgK0RJ7JjgC3tbHhXxyeiNhIVT/X89BrtK1Za4LA4ckNtpjhsSDFjruubxZWbY+11dYEfWmEnVzQ7wCGglpy/5EJPbYOxa3D+yQOYswZrAr9l9+3TC7z49Auc+tL2WDkrxY6PUcZkcphTFDQ7eMVlPtAcl/NGd4RNWR/Nu2flOhk9uYPLiVy/wc0vf88u6IbOEVH7ILWZuQYw3U6RxBJM6yHzzQul3eWYFO3OtT3dODDNGdcaTkljoFUqlUqlUqlUKpVKpVKpVG+dFACrVCqVSvWG9DAY/Bc3QJdmuFhvsTyeYesSrroOq9kcP3/5La7mLbsaTWsQQKAr4Nw2+GfL+5g9vUR/OWKzBPJyjq9vbvDSRrTnZzhdzPDyy6d49OAU7+aGY57JDPocDk9zwu9tj/WpQe8zYpsF+JK/UwymNdLX1kTlzKDMOLGLGpNr/LNAYMuu4Ck6WaAhDqCZOIYFhAaK5R2p1GwPl3osG3IANzgvL35oPY7sCNsnjOOIO+cUgRyxnJV9HLmFE2Zti9GXR2lzOu3wTdhiU867nXuMjWFwyPCUeDlHM0/OVIGu4lrNUv81S/1XR+CX2pymurUCTqkGLAFIU8EsgUKCsQSZCcoTP3UHsJdGrSUIz3WSJSo7HThkU20H71//ce3fXOsHszMW7Oi1SeotU+FhgreR+kHuXDqPwQ62u1oTmCKQM7uIHTDNmat1m6XxfB3BxbnWOM61fnKW7ucotZwZjYvTmceuOp7pKuxIpvGjer5Jtu/WgbEVNtMUl743DYauRfP4LpYfneOmrfAaVAM4YPWbMp+j4RsADFnaQ0AaZX7I1U2O81iuQ2OBQOPusXEOQ1n/+eQY/uN38PBfPELoLHoaPpNwMgT8x2ff4vrqAifUNjo+Sk1gGg5afyHXSG0CyTy2dudaJsdwNWDXqPNc51ZuemAYrEZglUqlUqlUKpVKpVKpVCrVWyYFwCqVSqVSvSG1KePYJPhtD29aJKqTW/41roOLLXyWOqgEKj25VNmNCFCZ3O52xIPrhFlosTUzBNNhs3oBd9JisVjg6uYKXQMMYYXUA6fDyLjw/tER7sSI7XqDV/OIFzYitA4hiLOXgCjXReWarGBHsdT2rZAzCyy2NUJ3ioAWwJskDtmKa1LA6B4w0gljhXqUQUxgzuURrh9xbD3O/RzHOfK5V9sN7s3nuLy8xPHJKRa+hQ0JDUUYH93BFbalbQ3mCOjJEVzGjOoFj1agdVNhtMQIH8RUT211AtRNaRhFQTfki6WYatqahAZGI0CUxp9q8kaIO5rIbzpw69IYGIbI4jJlRzEBTfyh65dEtW8JRNfiu+zipZrGFIvsK/z1BCypnWWsKOZ6pPYwcc7SDppNW52rkOhudhzXqGi+njMM6xlW07jVKOmdg7V+5arIRoCveIwrNM9RbgSoAJm5Pj8XUM3wOFUAXMeY0PFITl2G9A22RzOcv3OMy9aUOUOZtYSOBypgmwNCLOtlHMvcSpw0ua7jGBhob+v4+1iuM5S1XPqwnneIi1OsTlucvneEZ3OHV0bOSzWq3y/fX6LHSVn0s2Q4upzGdoqCFhdvWXeNq5He3B2Jf65R3rmOa5ogPPbrZxfhrVKpVCqVSqVSqVQqlUqlUr1FUgCsUqlUKtUb0rpr8PTuHQwUPUvBu97iNhm8SCNu8hYXC48bih1uOoaB5GIkl+XoMy5twGLhMJqyTwqI5bgNwb/FDNfjFlexh5073LZlX99gmyJ8BAPOG3aV1kBhOifHAXt4W2OIOUq41qGtLlFTa87iAKJGhsS2un7lQenKU91fcf9OkdCQOrPiVRVwGUZ2HA9jROwWuNncoHMNO2u3mzViGZehH7C+XWG+pHq2kaOwfdmXwKjNJ6WtSVyyZQy4LjIEQhOsjKWvdir8unNtkpM2CsQmsF763pW2LsvYuWFEm8fyxw4HGWPkbGLHMJxr2XqHnsA1GuoS78VR0SExjJ36TQDbGFcjoKu7F9X5W8cJNRY61e8JAhPcbnLErIxAW/an6tDkgE7WY1v229JJKoiOqDHSlUfS8VQfl1zLrjqMMdUwrvWZE8Ninr3qZLUVJXMlYY7/Jhpqar3dVB2+sBJ5nZh2h4pE087tncgpHAWa5+wRHDl/57idl3X74AT5fIZXEEhLtzhQjeKhzN8Qy/wnx07iEAgGS/Q5wVqa+9ER1KU4b1fWqce6XGDj5xiaBTaPjjF/uMTTcs1VOXdfHdXHZZ9V6cesHEcR6nEk53iEHSP3ay+at8D9JBc1AXKKrDZlfA3Vj+Y47KTAV6VSqVQqlUqlUqlUKpVK9U9CCoBVKpVKpXpDennc4t+eOaxu17AxwIXITstt43A5DtgcHWE9p1qqieFtQwDXWFz7Ef9u9TXeP1oAtsd2jAhbh3h3iVsTsF5foelm6IzH57c3+GKI8OW8jFbHLQaqOXyyxLZtYLxDm8vmJLHAuTp6uaot10sVaBgncIm9Q9RyXWAmvrUOMMQBXOvbkqZ6qgJGxWnKYLE8p4jftQ1c4/dl3paLlLbFGZpc+tI0eF72uybgyUDOcPzz3DfYuMjuUFe+3oYeQy77JM81XE2W6GZ2LlP0bzI7gL0DwcQ0h8xtmSWLo7LbcYqYDQmL0q4ZwWGuxTzCNwYhE2A05WFxGzN6jg+2CA5yrcltDLure8zgl14jpy/29WMnFynDcTe5qxuOfXahjGkfynxQu4BFueawGct+M4bNgWBo2e4bu+sHHU9xzb7yXpsrFM4S2cwPm3kYos0V4lceTrWHa4Q01/y1UmuY5yrVE/KpCKVLxLJh8Cvgn8H4FBFtBCSPpYHkxB6onvTxAotHx7huqNZ0ZmydMJb/l9fDiHEsc9c77nMYQlmDkeOZW4rdjmOZV9q7rJnyGuWXx25e1sIcQ3eM+fsPcDlrcAFyBmeJgC7fX5X/345lHsuan/dbBsDk7KabHGx1/JIDnZm4GH15HTSlvamsw0A3GJSfC441d07qPx/Ed6tUKpVKpVKpVCqVSqVSqVRvoxQAq1QqlUr1pvTwDtK//CGG5y+wubhE3G4ZVhJsGzzVOgV6O0ymWzSO6qtabOAwzo7xqzDCzzvY7NkRmhqPLUHHst/gLEYHrknrykNSjQ2/Rm7JwdH3BEHF5Rg47lb22VFC7BggpEYtOB6XI3LJ6pslXpgAG9XnJVcoATyiZnmqlUq2XIo3pga4CVwydeNrEPS7Lc9/11/jRWnBi9KepWsYLN+OtzBzh7TosLbkBO1xRhHAri9jYxkYX+WEPo7oB0KTpZ98DSK0FNvsy3ms1L+lurTVDcswuAJsgrVpTAzHCf62mwFtpHEjB++A0pTS1xbbMpZrrm0r0HMgp7STseAhStIvgcHkME67Or0MfbnuLmqN3X08tTi7I6IRkEnzMyaLlhzH1DbfcPxzT7tVVmswJTlzJjNfGhU6E5h1fE0C8zInxmIHjE2NekZtA9cChsB4Rv3k6E2xAu2MmobM4Bc1SjlRrHQOyOV5pMLSWaoGU43iwS+xbucYzxY4/uAMOG6w2lU8tuTJJv80hqHMWRlrAsBxPXCtXmrrSGB4K2uxN2t2F4fQlu0ew6zDVdtg+cFdpDsLXFBN7LLfulx/U7625I5PA263Gyz6LebrLWIYpZ4yW9bFBcz9Kw+OKucJEwdwU8a6m8/gyJnO4D7VGweyOoFVKpVKpVKpVCqVSqVSqVRvtRQAq1QqlUr1huS6DrN7ZwwRbdPg4uoSt2HLtWkJriHVWqvZsG8yTdCRQBo5RudzBKJ7iTEfYDwqzyqbDLY2Ypx7hltkYCTgRWRtJBBGUcYML2NlvZbdrAIrJd6YXarADmQSRSUPp9TClT4QuKPassRjLQc8S31c3osioalvKfIrNpX/W3GKGspQrkQzlIOvy/Z12XTbRhx1HmYcMA9X6FyLri/naVq4WQsbr0t/MppmBvS3iE3Hzl8GiCEzNCVRjLOxI5L3EuvLccmJ+0ARyeTujBWyEtTN5fxsZnWeYTFFELdEfznr2VYQzlnN4hy1ucZhZ+63uElrnDLtU4H7BO8lctnVWGxbYSxk7JJhOD3SZm+x6qk/BDYJ6hsMZUWM5BYuryUncdrOmFqbV1qQs+V2UKa2ZRc2tclxwehEzt06lxSvLcNgGNKTs5vmKhKwTsyMWTTPU2Qyw1D6PkSew2AoojlhWmxlNhDKPOW2w6o7RnpwhLMfnWI4bXFTxmnk2xMobtqV71vMOD68rLwyX8xZ6QaELGvElQ0xU7R52T+I2zhEh5WZYbU8xubxXZz9szt42gLX3HLL8HfFFa4J5g8Yhg2GOPDPUKBzUFw4OdSp5jRkAOi8XBuY60A7ZtspZFkX5HB22AH7XMG51gBWqVQqlUqlUqlUKpVKpVK9rVIArFKpVCrVG9IRLD6meqbzjOsjoBsjnmzK9+OAYAXDuurKZE5GWLZGCxOAy2x0JWgr7lxHADJO9V2ZBfJRfGw15HLdWwLFScAly9Q3+BobzA5Trk/LVV/ZQUlx0DYLuBQoLQeyc7ihSGhTzynXIFBIkI0cyHTtkaAbHZYkHNpVx2yi9tqI7AgEA6+wwbWL8NZj1rryIDdugjMB8/LEe6mV2zWOj6HGZAQ+DwNWikMuX6mticFwgvWO45Y5Aphhdtk1CLQdQ8ZY+kp1ZMtFERZU37ecJwQGrOQipvrIm9L+LbmqyzaKOCanLkNfdonWYazR1wQRZXwsqj+3qjqQGQCnCo3FxUuw1ZXvm1Qe5Mq1AvyH6jqW4RY4yTzWivXXGokF5/jp7NjRbKThAuvZUZ55nUhytJF2MdUsY0B1eHNA9RXvWip1g2tt5ySuWY5BLs9Hqq3LbmByAhuMZYi2Za6G4xb2nSXufXIX62PPccz9tP5qFeGh/H8OcC1njoGmYR7Fccu9DIkdxj3Vf44UXd1hcAsMR2e4vbPA/JN7uD1u8KL0amBfssEtpAbwkq41Upx0uUqICGMF1fSzkupNAvyDEaV+MwRskxk9jeLI7ntX1lcDZ53MWFb3r0qlUqlUKpVKpVKpVCqV6u2XAmCVSqVSqd6Q7vgOf3H2ANfmBld+zs5IgrZhfYPbQL5PqWlLMJMZFMG8JDDQeIncDQQQifexezOxg5Ojjameawpssk2ciuzZNUrOS0GABP+kHQxFTa4RwFKr1pNz1kg8cKwxwFz3l45NhiHwBCX5NV+uGS1DQZcF0nL925i5nQRVY7lO0zQw5CQl43Es16nO1ZjEeRyGiCFtymkdNuV6XTn5rPRx5meIwxamL+3vOrTO1pq34Ghfong0Jq48WkdOaCeOZdovyHbvGwbBOTkkcoZaicZ25Vovxx63BNwJwmbaV9rP0cEpcfQ2nWtb+kDgMdKcVDBrauS0PLHVgS0u6gOmil3xXZ4A+SYxZ5SI7CYAs2DQMXAt3WrEicvttOLQ5lrM5QhmtgyUZfIZVHJdW8PO31jO75cd+jSiJ+hfvlqZXvbi0tibJCTfZHEySx3nWrc4SRS0rW5oej2U5/0YkIYgjuhI49tgO29wc7rA8Q8ewb17gqedxQ1X+2U0jxpWzc5xAsCL0oJ1Of9qGLDtyyvrNa8tuuEA41j6SGuAagI79GaGfrHAluphPz6Fe7TEF+Uc1zz2HEzNDmCpLkyHl/6uthg2A/pNLG2mtkZ+xHHgmyTE0UxQeBTXdnWj0/ogKL0wS54tGg/n1PmrUqlUKpVKpVKpVCqVSqV6+6UAWKVSqVSqN6SZcbhnW7R+hrM7c2zGEStvsOk8+qtLhL6HGdPOTZqyRBATfWMumaNAM28rrJXYWk6FNgIKQwVlxsQakpsZ3hFgZUexwa4OrMBBcETyVB+WX8tSI9bTMVEgMDt5yVVbrj3VrrXWSdxwFCcwW2P5Wrac02CMgR8MkY3dOWVDBtcCJnjZEMgegegpsrfHMJTzdaXtTeB45plv0Jf2EDd0LsA1LV+XYpepLQyijUcwvsZcO45ctsEh+MgAmOE2xR7bxGWJU/bs+GybMj7ecJy1Y2etF0dvdfVS/DJB7MDjNtUzTjw+zIBtheFC6yVy+zACGjUmmtO05XgaL4o/blLmesDz0q9ltOJgpXEra+SaQL+tXmI71TCWuGlnZO57gv/khuYU6DJH8w7n7x3DZ1pnGaGsp/75Da8ARyCfbxZIdT1krlucU3W8EowNgd3JfANAiHyDgMzfyK97ItexzJ13Zc2WefngHN1HZ/i6XPu2vECu5bTzG1uua71lAJywnADwOGC9HeH6AdQ7cuvGkZy6PUIaMeQTrFyH7ekRrpYznH5yHxcLj+flPFvGyeB5IBhPIkxN7uRx3SNuA9cZDoHc4SO7fnMYuCY1RUITBI7UF4p7TpYhcNt26NIMzaLdRT7Lg2CwAmCVSqVSqVQqlUqlUqlUKtXbKwXAKpVKpVK9IRnvuEatnc3gnMXyzhnuLBrcLFqsCeheX4nLMYz8ekxjjWDO8Iaiji3X+h0rlGUw6GtpXar5SrCTr5S53qnNVAPVMXwkCEwuUQLFBM4IeBIkIydx4xqGfHQOOj+7kpNE+CYCnU5q3KLWSHViIGUHMUFP5p5JQDPRMzpXa6SecSY4XGvnkmGYY4UJ0HLtYcPu1MSADuzUJVjH7s3Qoy9jFWZz2CFzvLNpZtyvZD3HPBNJpraSYzbaVgCwc2ia+ucLgzzDDleKkpYgYImqNhy1DB4zKXdMbXY7sy7jdQbkZlf7V1oMjkjmWGthogzKqf0UP80GXSMgtGLhCm+zAFfqrzM1Blrq8HYU5RzKeWisG4t1eXGYxmgCyk7ANDu26dEY3kaQOLiMMPa4HubAvBUgXM4TqF4zuaOTtIvnh+a5RjuTK5pXC4HflNj5S2PFQJgim+OAMZVzlIkrpyrXQJmThC3NY2vQl68X5di1CTwOTRbA70vbt+U5gWFCvaflcVNOQDc8DKNFU05E64JioWNpQxxGNnVvyzrczI9xvVwC33sAvHuMl5Ycv1KH2tXax3UWGDgTrB5XawybHps1RVVTJPSW3b5p3PDaIvDNwLkMMs9NOYcrPynkBKcz0Q0C/L2ZajibHcBXqVQqlUqlUqlUKpVKpVKp3kYpAFapVCqV6g2pbxwulh2SdwgMbE/R9B7zJuPcZoazq5gxEKhzFdLmAJcsmrI/uUYbrmlrGKyRS5fr0yIxdGvoMDq2H9CZ+hZOuc9GQOnYOozO8rXZgRoNbLleGyJDSnarljbGComjwxR6XGsKlzaHhJYgn6lAt7pbyZlM4JZeL90pj7J3kKK1ydtyXakPS+3w9KBeJHGfWi/tIBCYS5sI2lE7c2lLb0ccxRFtM2MIHN3ILmCYjoEqtdX4zI5NGicT6HgP39C4eXYDpySAlr4nJ7Qtz+m1xrRwttnXSxartNRYhjhFaRSNLduojixBdUf78cCw55UcuxSp7Ex1AFO8szHseJ6UTa2tC8n8pr5S3WJy8AYbOWLaNp7HiaKNhTlX8Gymes4VSHKRZiNtNFK/mW4MaMrcns4bXKzXZQ7LechpW28eYO83OVq5Lm5k0Euxy+MweXYTQhgRxpG/NrQ+hwEh9oxwcxnPPDpaVhi7FhsCuHTzAC01Q65zx3A2lfl7fnmBx/ceYCjjfEvO33KGu6UNF9s1brYb3G6Abt2zs3wsbaI2sBMYHTbdDKvZEW4eHuPhjx/gaibR0nS7QwML8XGjhkwLnB/L2h02W9zeruBvR4a8EuUduM/URoLCvHZtrcG8o+oSQ05ucIoqz7VOskqlUqlUKpVKpVKpVCqVSvW2SwGwSqVSqVRvSH1jcXG0gO0CUoiIc4d2dDhqgE0OON5sOU756uoK/Tiw09NTfd0MdMmgK1/bPmPObkmDW5MZwJE7srUWc9p/zOhGoCHoRc5f6zGW/QYbOErZto5hZTcGdMaV/Qx8OV9jnLhzU43WLecfyrUp7jlwXWBxYLblxVlpyyzbcs6E0RrkRvYhV2lbjlmUfboxlfMahHLcJgSsvNS4tQxgy2vDiE78ydxnnyiq2CAN1NaIbWnUph2oWjB6P5SLjkhxgHGzsn9T9qfvPRNvn1o0xO04Gluis0cCmaGB9QSDHSIT4HK9XJ6Xfxx2nKmNkWErQdtkmvJ9kLhnduBagbZlG0ytm8wANjNEzOQadQSYR7gyzk2NhGZ3dgW2OydpjegmRmyjQOfsSt9a4LKMFUVaE3AfyrgHclWTE7uWGWZnNjmqKUbbVi6cgtQrJgwaM9d/fvn5c6yHdZkPC1fWV0tQuow9w/1IEduRXcGRakWT05dKNlP94RwEDAcBxBTPLTCY1uCmHOMZqvfJYQg9tmXN+rJPA6kxzAA6JPz2iydY32zw7t2H3I/SEtyWce5LRwj+kgN4synju+nFAVz6SM0bEtVa9tjYFuvjBWZ/Uo5/MMeTcuxQQ7mb0th5mbfByPoMvNVKHWN2+BqJPDcC8sn5bac5oHaSu5nAOUd1y00Upo4tjKxLlUqlUqlUKpVKpVKpVCqV6p+KFACrVCqVSvWGlBqP8aSDHRsBcmGE3RrMkHE8DtjcrNFvenaSZoqrpdhbgn45oS37L8aA+XqLkyFhTfVrG4KUM5Qj0FlipBntZsBxGNAMW6TUw/kG6JZY2Ra3bStu1daiHQwWZb/lELAghzHVViWMayXqd+ssVuWkbtZiO/PiMk7lGn3AclOOGcp+bUA/79CbI3abtuVcR6UNs20o7diiI1jnDG4IlHYN194dmsQ1aRchYln6vKRrj+QqdqWfEltMdXI3rcFll7HKEdt2xDYEGN+imUV4s0QKZhfTHMg9TO1rG3H58sOIo5lqxI40Vh6uPAhcUj1YjkYOieeBaiATHE7svpVjCZKTM5SOD0QVnWf3MDmtW54XytSWGrwEFin9mPKc2XNKY1x9qpnqKxuhtvRHVVsfI0dyl73KGA+NxG2H0m+CwDbVyG5nqgk4v1ZTmK7Rln0b6+V6kGjwVMa9o4hsjv/Opa2G3bXUTnJVE9SNFPdMIJjoL12jvB6iOHo5whrkyh3ZJTyW9RHTgDRSFHlbjm3KPGzLsS0bZSMBf0L0Zc3+/G9/jadfvcA7jx4hlhe35bUNzWM536rM981qXfbboh/Kdceec8tD6edYBnCTCf42GI9PYd67j6NPzvGsjMOqxm7PjcPN0+c4OTlHLuutgTh36dVNFGg9RWPz/PPNDCNDc7J+MzSX1GuJSacIcXJi2/oo7fU1Ahoa/axSqVQqlUqlUqlUKpVKpfonIAXAKpVKpVK9IfkU0JoegwM7ZwdDbtwF5gQxxwHDnS1HGefU4/rlGpvtFjE06FKDxXqN97YX+DcPz/DYN/j0xQV+2QdczjpcphmbVE/L/nc3Kzy2PT48t1jOI25uXuDr5xEX+R28On4Hz7PFKid0fYP7ty/xwc1LHPUjQ8/erTGiL+08Q2zv4OsWeHl2jpe+RW8sFkg4X63xcTD4qDvDJn6J32w6fO3vA9s13l1tcH57jVkc8M6dBo25xZNXV6V9J7g+ehffpDkuZuTQ7HF8c4UHN2vc7ddw5VjvltgSNvUZsyT1fr9YdviiOUbMCwzrMjY+Io9U7zaimy/hm67WQc4YXRmAsTzIGVrGxzdeauhmcSaTg5ngLUUEjxRT7clWLe5ZoomO9inzQ47ptvR1GQNm4y2cd1iX69wujspuDWbB4iyOZc4ixnLpzdxhaLk6bTmunLu0tR1i2W/Ldt9t07Bb25Tzd3lES25huk4ZQ2s7hNLWNUd0G47P7ral72V77y2PxRR1TC5tRsFUG5pczsaXvrfsSKa60gOBe0NVjptyDSK7I7teTco7aIwaXU1c1DIXHjiGmupLhzHzTQcCm5OAX1NrQFPMdhw5jpxg9pg26BBxpxy3vnqF/+6//Xd49h+f4L3H38Pxww6bcqmnpS1U0Xoof0o+L9ff0o0GfcRA69wM5frlmluHbS79p7aX8d3cOcedP3sfN/fKOgHNZcQR+YzLmtv89VMs/tUd5DnNAgHshG3pz2rs2c1sy/lpPtpEoN1ygWauTEwAnlzxkBrQdHOAr0Cex7WcY9Z2fKOFq55hXjMqlUqlUqlUKpVKpVKpVCrVWywFwCqVSqVSvSHN+oyHt4adjdvWY+UMNi4hmxmiOcFILs1mBjPr2KV4+/wCuO3R3d7idH2B7x8Df/rODCdzi2+HCPt0i7RlbIp5GrFYP8WfPzzBjx8d4e5RQOM8hmGGh+db/N03t9huvsR5+7DsO4Nd3eL7dy3+9Z88xFm5rm0NQrdGMD2aeIbb9Sn+H7/4Bv32BpttwzVqj0KP0+0tfvzOY3xvscSnXzVo1xQJvSqPW5wMz/GDhx3eu/8AZ8uEtvThejPDr79e49NX3+J0oKDoBSgwerkd8eHpMf4VOT7zFYPWSFHPNqEJHV699DDf9hivPb48BRJFUscR/SYhDj3W6zUWyyNY11ARV3b3xqbhKF8CrONouK6rJbcn1SGOTRmLAW3Z1hA4ru5ScsWSCzSU89DWWQ7wgWK2E06oXnI/ljlBabWDNwNOxljaGzAv87e2DoOzUmOZAKOxOB62WJTxJFhO5ttbqrHcGr5WF8px5diZI9dxy6DxZrNheGx86W+MWJQ5u+mH0l46Quoxk2uVrcZGah1THeWUHbt4czIMQKkeMzm7hw1FIlP941hr/orjN5fjYnUBU2QyRScHgrwUBZ32NYA5JjqM7BiOJmBIPdAnvsGgL6ccSv/Gm0vg8QM8L+vzb/76J7j5/Qt80L0LtxnRVGhMzt9Relb6OWC7LltuN1iXfTgCmts5w7aM/XA6Rzq/g+6juzj5+AhfO1ohqcxHGbOyZj7/t38D//KWXep0vsDuanAEdRzL2h1zec3wKwK8E0dil16VuSVnMJmyDc8zA3MT4YzcIED9b8gd7h0fZ4w4gRm9KwdWqVQqlUqlUqlUKpVKpVK9pVIArFKpVCrVG1LbB9y5ZbsprLcY2/JwFq1nmyVSSFjDYd33mHWn8G6AC1vMNld4L13gz85P8KB9jmipcOpz+NhiFi0y1UftL/Hndw3+9TsW5/OXyGGFtLU4WZxg+e4M3SLh+qfPsNjMsDUNsL7Cw/MR795pscxbRAyIXY9kAtpIdYQtlmWfI+9wO4wc8Xzcb3G6ucU76HE6vEC+uMJpcw+b1QbL9BJ/cjLgL94/xqxdw6QbuHSN+dJh9sEMm+0V+tL3+fIxhtLPoxDw/dMOD+9v0Zjn5fwD0PSI5S8PP5xg6I/gM4Ht83KuyA5lqp9L7lXDscURW6SyzXPtXzSegS85PJ33HPHc+4bjnS3XCiYQ3HAMd2pLX31bHrI/A+CmxUDQOGQsxoSH5flJO8Ples31kG0/YoYyf3HA/cUcR7NjfDv0WFGt5bhEbugaBktyQZdrnR8vsCZH8rYv/SWSmNg1fLezOJt1sMlz1PblMOCqH9ixSpHO590cL8IGF+XFTVkXFPMday3bxLWAwVHVIUpcMQFuqgG9PJvj3uNTfPW7b3H1/BYLig4PEuUcy1hz1HOo8Ld8P44j1/6lbVwTOFBd6pEhMcHhRNHXecSYy5qg2ObSh1C+Roq3LvPyy//z/w23Zf8uDHg0NGjnK2zsBiGJa3kgeA0wVCX4PJZxiesthm3pal+We2iR7LzMxwLx7n2Mjx/i0f/gA9zcaXDNZ4hYZIvtZ99g+5ef4c7HH3OdZXD95sCR2ZS6HfsN6MeBoqgNOa2pNnJZLzIq4n6mtcPt5njoWli5xkiH0k+uS81wWWo28wP7yG2VSqVSqVQqlUqlUqlUKpXqbZMCYJVKpVKp3pBiyggE38gdajJyY2C8haear+RMnM2x7LcIsxbz+RKmuwHCFqe4wr94v8X3H0U09ltkcimOK3R5AR98+X5AF3q8u+xw3iZ2BX/11QU2K+DD73kszlo8PAXeWUQ8u1mhicfl0eN+l8sb/QWyG/n6Nhvk6JGCwzhKDVvjyV+cYWN5bKlmb8Q89UibDTtxbRpwlNY4t2v86MECR1jj5mqDly9eYuZ73H1whOPZDB+fL/Dico3rm1uM2WE23ODh8gi+eYUUr+ACZRNTLHG5XsgYcmQYbW0Pb2cYIBHOBPM2IbBD2pCjtfSb3MFxtAhtW/Z3aJqWIbChXGSK/KXvTYOmnSGX8UrDiLbrkMv+VMyW9rXE5QeHdtvjbIh4tHSIt9cw6xUWyzl7Tuelbw9mwH2qBzzcol0NaNwcC1POEyiJOuMkbsoczHFU5i2W8ZqNYMhMUPW4cTgp7fdlfky0ZS4b+K6cq8z5uuzrSxvn3RJnpS1riv+2HUbjuS4wxzebCiSFVHJfCXqSA5he9q3l2OO+zElH7lty8RIAnh4EeMvYcf3pcgw5gAkE87YUGA7HcahwOLILOJXxDYH2TfUrrYUEfzuWPkauqzuWtRFyj74fKlal4eAKzRzHTPWIYx8YIpvUlDVTGpub0s4W/fwU/d1zLH/0IeafnOG5I/QbuU7y7GbE7//938FflXkx89Jli1S92zQY/EcqxZeT/ZngsCUHsMRtO6rPXH7GBorBJqcvxWBTvWdveQyp1jT1l753u1rAcl5AAHBWC7BKpVKpVCqVSqVSqVQqleotlQJglUqlUqnekG4Q8GVco585JBcQuxZcrnQkd6uD9XPcna/QzBsMrUc2ASdHGX/x/mN87+wabfMMyDdI4QiUzNvkOWzqGGydnNzF/LjFEAdcvprjV7+jkrgR8+WI95YL+Dbg7tEMry4Dg8GjxuD+6QIUSL1dB1xcmNKmGdZjuW6e4bb3uJ4vcdV02DQN11Elh/L9O3fRzjpcX12itwnZRthwg8cPWtxZOMRxjd/+7gW++vqm/BGR8cmwwEcfz/Do/ASLTz/HgJ7ClNGmWzT2JfywQbgCNlcN188dfWmTP8GrZwNDw2CuMM4tIjlsK0glwEd+zcQQL0osMEUjk6XWGAzew/uWIW/T0viIe5YcxEiEJJuyr+FUZedK38jZWo5vwwzLDdUlHnC/zM3zVQ8zjOUcDcwm4myeyvw0mOUeA20fy/hGh3k53vQWc+dw76jFwpcWhYFjmCnW2QYHU9rdtY6KPePV7SXMmHC8OEa7WJZxSGU72WIzhnL9ubeYjSP6UHpZthF8za6ck5zMNQaawKWMBdgBnkPGuB3LXG7ZMU2Ak6A6fR2HgaExj1WNeB7Hsv7KIqLXY3X+gqOhI8NgOiaPPdf+Hcvr21C2leEL1UFM0cuGb2gw2JbHOItcyzd7qaRL6NRRXWQC9wRfCdqTW7sMOlXbDaZFmJ8g3X8IfPAOHvzLd7FdWmwg3tzT7LD69W+w+fmXOPMfofEdQhnfkQPEBdPSNfJQ2lLOtyobmvIzlE2Cp3UZe14fxHTZ5e0sVwFufMNjhVoHmGTY/VtxLzmWYdT5q1KpVCqVSqVSqVQqlUqlequlAFilUqlUqjekK0R8jjVaN4c3I1qQk7UVFkUgsiNENYMbl9guVpifLfDPH/0AH+Sv0QwXGFOAaWdIvQUxPaqCSo7I1Dpce4dPr3tcvewRb2ZYmYflpBfYBGKG5RpjAxtnHBlM/szOZ3SN5fjbb7/d4je/CtjEARs7x9o2WPuAl4s5LhgAO8ziCBcGzN0x1wN+vlphXY5fpQH9doN7J3dKv0as+oTn17mc5y47Pr987nD/kUPbBJwfO/SXfWm1wcO7pzieixPzqycR3366xmgyrq3FrcvYOo9nsw5PZ8DIzl/H7unAzE7cpVTbll3KNbA3R6n/GkMqxwQM/QDnt1zfleCp7xvMaPzaDqEMYGra0q4Orpw7kXt0W/q3XeEOxQuvLnF7u8Xadeg3a5zZDsfluPXlJWz5amZzjFuKrW6R1ht0Djg/WcIR4L/dYF6u02/LXESL6FIZG4O2zPM4lDEaM9wQy7UjGgK5BB3JrRp63G5ucffkGPPy/CaMMBwP7hhwIweukUwkOyfaNlanasTLb1/g4uULDOtrNBT5PAjkpeuFMncMgGn8+Lk4g0PcSu1frvkrtYAJBhP8pWhkAsDlAHZfb8sxfdlnpMLGhFLJ/Vu+p7rAqzLeeUmR3CjrqhEwC4H0VBN4lsU1TE5bAvEhG4xlvZvzexge3sfRj9+HezTDU5pTirMmRL/a4MuffFra0ACzBrEx6MsY9gcOYIrG3pZzheMzbHLpxzYxMG9z4hsqCO4bAucUCw7HoNfyTQTE2uV7cgeLQ9y89rOqAFilUqlUKpVKpVKpVCqVSvU2SwGwSqVSqVRvSD0irsyIGbtGHdqxg3cN16g1rUE0Dt4v0RIwO+1xsrrCo6OAo9sX+OrXr5BdwMN37yLGASlZdrAGO2JsE56YAVevVjhZZ9wZFjixCzR4AV9esylhfQPcXCQY25RWjOga8k327FS9fjkib3x5058D8yXibI6+W+K2cRibsn8a4cOaY43v+lPMYPHy+gY3aQkO/Q0Bc2/K1tIum7Gl+q/NGcPC63GLoVx/4ba4f2bx6mKNZFo8PDop2zZYl+NfbTI25HZtFri0S1zPF7jpWrxYtnh51JT9GwbABHfJ8spwsTz3znB92ZAFAksssmGgmqLstx02aCjqufS3r7Cz6bdoy5inpiuPnmvvUhi26cufPetLHN09xnZ7yXHZl6f3MZBbN3lcP3+FcPEtZh+8xw7i1bpHf7zEOG44onnIAzbPLzAj6HlvjrFPHI9M9ZX9vOV5XZNLt8x9R7HJgUCp24HImMueZaPJ5K4dMA5lfhuLQG3N4lIFQe9sGNimUdzQkaB3WRthVWaDoPAg7lc6VxilDjDHHYcokc8UB12eb/t1rQscpe4vRz5Hnu++78ux5TwE+AkmRw4CZ/cvAdQwRobAfen3mBo4incubWwJVqOmVLM3N6GhA0pnnJUXMkU5tx3Gk7LWHt3D0Q8f4EVZ/9fVh9slg2c//w3WX1/BnNzB9qTM/7Jcx4JhdGSwbLjG8Og6xDtnZZxK616W/pV11Jd+N+xDlhq/BIClPnDiWshUSJnWD8c+U+3lssapBjBHQJv/5I+wSqVSqVQqlUqlUqlUKpVK9VZIAbBKpVKpVG9IIWYGaYtsuEapGyOsS/Desos3GUKFLWI3R57N0C2W8G6Dm2fX+P0vr3D/8R3g/jHS+JwdoymPGM0GvS/fHzXAgkCYg3k14s4i4Pv3H+LRQ4q7HbC6HNGvUjmvh7ER79w/wawjP+WIpXf43vvvwc4f4NPLF7jI1xjJFenvwJfzdeU6y9zjnc7iQWlnXq8F+FmqudsJnA0DkAbEsh9cRrYW2Tn4LpW/JgKcW2PRDGgS1ffdYO4X5Y+MBvl6gLvs8eHpMbtCV0OPdbTweQab5qWvc6CL5byBwSEBOqpPW22mwusI/JbXKA6Z3bRJqriSibPxLVWhRUiRI6ApzpiAtfUd+kDxzJHd1yZZxHUZjdUr5GNb2ghsymxcU5SwneHZ1SXC7S0eNi268u92KHM1jliHHlvbYAgbxDLGRzdrzOYz0J9Q9I+crxjKHHcG1JIVRRZLUV+B+JGJKMPUSk05ghlUk7fSSAa/pXPsUqV9KYKZwCYdSzHPiaKyB6osDTNuy2Ms40XQtnylOGeCukMo1wt8HYLHBILJGRy5jjJ9LY+RQLC4gcm9vC3nCmYUkErO4dL2NCSO1A4VBJuGqw3TFJe5tZgZj7X0jttTViYszV1PdY+TRC+XiWiWS6wWczz40bvwD2Z4Uvemkdn2A64u12jf+QCuOYZZLDB/fFbWuanTTi5kAc32/j34996Df9WXdbnC+vKG20A1nQno0s0VBHppjfCaSNXZW0Gv4xrRjpv12guyrKBGYJVKpVKpVCqVSqVSqVQq1dsoBcAqlUqlUr0hZYZiAcmUr9aiTxkNwSlvGM7BRnTOcmzuaHv0jcMvbx2ef+ux9ffxcDaDJ7qJhqOFLblWMUPyFoMv541bLNoRfv4SP3j3DH9+7xyz9ALfPvkGP/9mxE3zDsbcoMkrzI86dsUam/H+D1s4ImZ+hWXvcfQ18PmLF+gI1PXn2KLDfGswdwFH5OK9vMbLAdgezbElF24jTtBk55jNAk67EfmmhwtHuAMCcgbGpXLNk3Kdi3L9V2hnFqkr50SPH/65R7NYlrYsce8i4ZefX+Cz9Rqjfw8b25VxSNhSLdxyjuSI4hJUFLcmRSMLGBb3aOZavwT+hN5ZGmtyxUYqIRx5W3KutBccAc0u0LKtYwdoj8W8HJNHDENgx/Bt2paxb7Aq475edHDO43G5pu1HpE3E5sjhhuoNE0Qs1501R1yDOFI9XESGvlR32JUNiQh1acJiW84z75HbiOBHaR9FKpOr1QYEnkOHdpWx6C3HXlPEcTQUpUzLxDEsHgkCl44lqs7L0JigdORrEBseCeiSE5rGiNyvY2QAnigamkB4HrnuLzuD+6HsO3IE9DD0DHxjGNCPA/UAsRdAHMhNbMSRTK5ngur0Os9LA7jyoMGmar2RYWrZQLWag0BtS1WBy3HNYo68sLjzbofbNnNtX8HG5Ziuw7v/+V9g9p8lOFpXZW7CccNrTeTLT5HhesF3fvg9PHrwAO+HjPV//A/46f/2/wB7neApursMkyttackVTnHaRHOZpdsyHoSDHVNecogb2sdEBsF8A4FN1VX+38/vCpVKpVKpVCqVSqVSqVQqleofUgqAVSqVSqV6Q6IIY4qkHVMqjwhPtVqz1HR1FIsbI0NdmBZuvsCtX+FyfYu4fIj23iWGWU8sERg7cSaW49h9S8cS5Mu+nL+nhFs0syXGwWHuZhwzHcKaa7Y6Qw7OHnN7ChMMu3TtrEMi0Gdf4e7S48fvLrG5fIF+e4X/T3v31mxLlt0HfWTmuu3LOadOVXVVdbekliwkbDA2hIngAfsBeIBPwNfilc9gggdHEMHNhgcTOLCwkLFkWxJqdbe6q6urq85tX9ZaeWXOmbn2qXY4eKFCEBm/n2Jrn9p7rcyZM/NIJ+K/xhi3zbMSkjWn9J7b9H0zxdfv3sbDkOe4bkrItrvZx7scDlZN7K+a+Oh5ur6vfxGb+j5ePt/Hft+mNZ5jGuto0vW+uLqNj26vYjo9RDPu49ntvrQ6nnKV8cdXaW0vo/3zu3jVvY6r7S66IV90Du/mMs1qmS97qQDOe5j3oylh7rzXZT7wlPdkbgWcQ+HcArga55m7Qw6Uq7Tm87lUMt9sdhHHt3E47Mqs3ofuFENujVyPZTZytd3GYzr2u7y/fZfLVGN4eIzugz7OOVRO7znnGb85xK2qEvT3Y7rucVsqeoe+iaGboutype6hBP51P8XNkGc65xbJUdoU52C7ys9EDlpztW3d5Y8MlBA8R71NOlGdjpnbXp/TGtNNTLdnTNeUK3yH8nzlCuHS1nlp+ZwrfPN5+3zuvi97U57Dfp4BXGb5tqc4HXNL6LbMR+5yCJzfn16b15NfkwPUErbnObo5Hs3Zdg6N63m+b2zT+nOF+KU8u0TD6bV97hk9zMlq3v9x3qc23db8IYBczb4rO9aUGcBdeq7rF1fRvpjT1zHmds/vW0uXux95DHZ9vU9fuzimn27ffhL9dTr/fT5Pbu+8Tc97Vb7qZij3Pj/LU38p963KvOjNdjPv/VPA/M2yXyXAAAAAAKyPABgAviW5erLMZE1fufpznKZo2y72+9wGehPjZoqqb6K+qiNedDGmP3fDrrQ2juo+ppt30W2PEcdzem8VcySYWy83EV2udt1FPe1KmPrHvzjH13c/j7/1g3189v3P4t+J2/hnfzKU8Pnq5oO4nm5iOnXxttvGT37yLs7Hu/j+9/bx3e/exourJn79w338/C9Osd8cIxec3m7q+PXvfCequaNxxOGmVLr2+21a23X85PV9/JuffhDP02J/+3efxQ8+HnOJcGw/eR6bw+cRUxvdeSoB4/X2Jm7iw4jHJs5tE1+/eR1tc4wXH0R8cB3x8oNDfPdlFX/68zfxsvogjumfIyXEy9uQO0rn+a35+tP+bZq6zHgdSnvfsexzaZWcv6efN00zt4XODZXT2nJQmefd5vm2eV5uTstP4zFO1TamuzdRPbuONl3Sm69fxWPaz7vdPvpndTx2bRzS/Ts9PsR5l871cIz+/hTd8w/icZv+uTSk16XjXz208WFzFVO3Szc8/T7d3zZX6ab7U6W9HtPPHvsc4t5Hk5P6XTrfu3Ssh7SWTRObqYnqKh0uHb87jmVdx3Tlp34qQWs91mVG8HnYRted0rW1UTdzO/AyF3gYlzm/ebZvV1pF5z0vQXC6hiF/5Z8N6RjnY6n2ze9rz+c4ndI5077kauBcSV0q1qccSo8ldI9lX/OHDXK1bJ3WmsP3XNGef59fWzX1Epku/awjSiA9tn3UQ1Wqk8d0nJzBtnnGdNOU1+xirpDPbaD7pRL4uBwp3/nh6ailLvcpAM6veygV3FU8yzOx0zH77VjOk6PoJn8yIM83TmvNR6mXqt4y8ze3KU/3bL/fzdXB5QRLOFyWXy1nAwAAAIB1EQADwLekBHRdF+3pHO0mt13elBC1bfex3W7T1yaupqZUa3bXh/SG5xFDFX17jN3pRWxvmzL9dLo7zDN2N1WpAN3lIHSqY9vVcZj2cX9u40/evItXj4/x8c0xbl/exvd/7Tvx5s1j/Phnj3HdvIivfjnEm8c6fvzVOb58vU1rq+Ld2MWzj5p4fjXGdz68idsfvSqzbfOc2Zv+HB/dfCe6tJa7Yxdx8zJOV4d43G3TdVTx5UMfP/56it+or2J/GOP2eR9pMem1r2OKh3J953Oe1Xsb524XP/78mF63i59+9S5+9nqIdjrF977Txr/3ux/Fdf86bqo2nudw73gfze5QZvm24xBNk8tOo3xtmya9byqhZ532sezJEuSVua+L0gK5HuZq6xIBTlGVmcBNNOlH0znP5T1Fdf9QKmm7PIv5/k2cql2ctocy4zfdrTJPN+7vYnN7HcPdfYxvHqJ/9iq6zbYErk0zxfnhFNN2jOphF1M6XnuqYtxPkQ6f/rtL9/Ehmse7ONRt3EyH2Dw8RHU8xXjqStvoemoj9tty/HNbx3G7i2NVl+vMlcC5dfE0pOej30afvo9jG1Xdp+vu59A3XWGu7s0V3dNlxm9+npYK4LkieP5ZrvrNP8/zfnMQnD+YkJ/RIVf9LkFpbo18GYQ7B69VyYGrHPZWeX5uWkeziyrdi2qb9nNX5yLf0s56fk9V/jvPK96MS4Vznnmdq23T85ufnVIpPM1h7DzfdyofbZjVyzzh6SmMHZdwuZofg/Jf+Xt7PpX71+e25Ol4m2oTmzIneZgD5Kb8JUz3fVs+JDBNc5vnXdrjcoX/2mJfATAAAAAA6yMABoBvSQ4iz4+n2G120W336fs2uraNNn3t9/uom03sSzvdMaar3OZ3H1Of/vz4LDZ3h9jetFH3OejcxZjD4xhLdebVMMa2zW2ap7hKr+/ybNar5+mEQ3zVfh2P/TleHNrY7rqo4hzH40P88K6LdneMd/EsusNHJQD+ov0yfvG4K8HsdlNHPbRxPfaldfNV38VmGOLheIo35zaGj57Hw24Xj4dtHLa7eHjs4l/+6E1a7z4+evk8brpjtF+/iS/fvI0f/O4u6tt9tF1ae7OLX57G+PwvviyzV19Ph7i/+vWY4hRT+zZ+Z9rFoenixfOrePFqjDd9U9pjT7k9dgl/l/AvB3jVXI2avw9lHm41V3XmQDxXVOfKz6UqOIeLuXXxNEwxpH3Jr53bRFfzHNyxiqHtS7XzuEuvyzOIh2N0u+u4T3tztbuK4/kcY9q7Kt3D+pTWe3ws4e3weB/9eI5hW8f4cC7B/JDnOt/dRT9so502adfH0iL7pjvH/esv0n2OeLH7NKa3r6J9eIg8urdN+72pthEPN9G+fZfO28R9uuaH9D2P0G2HLmfxaQu2ZZ+7NreA7tK+jKUCuLSazu2t+9z+Oc/xnVs852esXyqAz+dT+fM5P3e5zXWez1uqZKe5tXYzt8yOMq44PV+5zXjVLL+fW2lHbjs+1SWMzy3Ec6V1pGe3yiF8NbdrnuZa27ldc75neeZunp2co9pqKFN8r9P1fpLe+jZX+1ZzpLstq5hbSFfLEXJFcLfEvpeMNr8qV/juI+fIVXyUvncPx6jOXXpRM4fXOfMts37z+ppyrbktdv57V64j/Sa3f95st/MHBupLsLy8GQAAAABWSgAMAN+WcSozZ4e2iz5/7fvY9svc1jwTeLeN7TTmwsgywzTPvq0P25iud7G/PcTu+hT1MVcBb2LIrYnHTUw50OrOse+PcZuO/3L7LF6nn1XNoRz3OIzRb+pSKdw0uQVul44/Rduk/xe/v46h38W4+Sj6qo7jeI53bW7PextVPaS1TNGkY+7Tmj55/jxuNk18eTrFudrEXdXEOQfZdRW7Ka1hfxXTwzl+/KPH+MmP7+PQn2J7vI9PXu7jev9JdMchXr15SGdP66qndIxI5+ri8eo2ToebdL1Xca7reOz3EbuhtDWOqYumOpRALgd0OdTtS61nVSpQS0/oaQ7scqCXw95cvXqRQ95LKDzkd5ZZwVMJLHNla55xm5XoM13/sNlGm/brKl3XR4fr2L25iybfpzjGKe3D4/Ecjw/HePf4GNMxfT8+xJuHt3G/z2H5oezF6aFL+5LbG1dxfHiMt32drncT5/NDPB/28emmj8+u5tC57o7x5d27+MXdY4x5/86neJYD4HTt/fEUj+mc73ZN+r5Nz0z6WW7pXALRXZkPPPTnKMOD6/z8pOdqaEtVa9enNeegt52rfi8tn/v2XGb7Dksr8i63wJ6mJQwtG5aejaYE5KVF8pT7KOfvczia2yQP4/y6srcxV/pW6Vmqd7uI7abMPx6W4HaOf+dwPt+b/GGF9Iq0x2k/X38R40/PcfjZz6N5Vsd9/b6ad24KXZXztGkduU30cZ/2sMpBcGnmnY8at+not+n6nndD/JX05z/9+VexT/vybHso87XLzN9pro6ey5Yvz8RyDel+bXKAnWuM02s3S8vn6dJjOn+bBMEAAAAArI8AGAC+JWVOaq5YHUsZ51wZWUylajOHcXks7FTN82tzC9up2sXU7GN/dRPV/pjes41+t41zs4lh2kbdVfG8aeJv/sb34ru7Ka7T0f7gT34Up/NNmed63eyiycfJVbGRQ902Pn12G7effhx341384Y9/mpbyMtphW4LhF7urEvp27VBaVOcgbFNX8enHH8Zus4m7x2MM+1085AB5amI79LE5vonr/hwvN2PUbRX3Qw5qn0c9NnF9tY9muI1uaOP88Cqd4ypevriOmw9v43ie4odf3cUmz8SNbWlhve3zPNbckviYN6FUlubvzXZbGgGPS1Y5lardKK1988+aUpX6vv1zmWG7fJUQuCr9f0tlZ2k0PJUXxjDmQLWP4zjEw2YXr+/fxPnUx2GsY3caYnPu06vTepo6HocuHtKxXo+5TXQfr7djfDUc49VpE1dVF/tNHW/T69+cm/iw3cbrdA1f9lWcun1s0nvj1Ztonh/i+W5TwufXd+/ih+/u46txrnx90ffxrNvF8auv4u27uzjf3Mb9+THu8v7U6Rnpcnvj3A76XIL/3P55HE7pOUhf+c9jV9pC53B3ypW9y+zfHPiOpe1zbvHcR9m4XKNbLWF4fuaGuQp4KlN1Y6n2rUtb7dw2uezhVM1VuGUecz3/LD17+d4MMbdmzlnxWF2OMIe5/emcU+B0j/K9OEe+k+3dObq3n8f/9F/8JNqPruNxX89rSs9ak57UaWhivLqN4cPvRHz8nfjsP/1b8fy7n8SbpRp4n77fns/xw7/3X8f0R38ef9qmZ/ZHP4vvVYd4lqulp6FMFC63PefApeo7Pcub5in8zc9Gnk+cK5nnSuc5dI5vhL65zbU5wAAAAACsjQAYAL4t0xyqlSh4Gsvs2rkqNcr3Mf9h08TQ52Aqd63dlra64+4m9jcvYrM7xTQcom+amLa5+e0uquMQ+6GPX7/axb/xImJ4fB2/GF/Hm8dzdFMdn96+iKvcnrcbo3/3ENu+j+dNHb/2cRW/vL+PF8NX0XbbOEw3cXPVxgf1PjZdGw9v79Na9nMIO+U5qdtSxfl4Pse0e1lmF+/SPxN23Sluh4f4zQ+28Tc++zB3941//pO/iMfHNqrtLnbXL0uIfXy4j7od4vl2jN/65CY++vQm3ry6j+Mv09cxt2W+jkM1xXWbuxoPcf/2bZz6m+g3ad3TEP1Qx1CVNLqEdHXdpJ/NFarV8j9N2pfS8rla5tVOcwVn2ddqTtZLEFxfpsrOYWZu2dzm9tbpmMe0Z+2pj33ar13ut5zn86afD9sm3qZr/3qY4kd3b2LK1dLXTdwdqjjuphLEXqXlvE3v+fKxiu3Ylmrprw7X8TCd0l6NMTy8i7GtIm1VDOn4r47pNWMV3dWzOBy7uDp18Wz7LO7f3MXrd6/iPq3tvqniMT0TTX5OcqV4usbTlJ6LsS6Bb9c/puto0zXOX3lOcd/1ZcZxCX37rnwf0vc59R5LtXmp/C1beQnJ62jS3lZ5Fu+l/XIuVK7mDyqUFsnVHNCOJQCef5+D7CG3oL7s5VLJO6vKPyT70zGtvYs6V+OOXfnapxd+lt7/+MUXcfxyKB9cyBW429zYeWjinK7x8dkHMf16RPtmiv2//xA3353irgTA8z9Qr89ttP/0X0bzhz8thdAfpev4uE3PZDpXW6XzVOXjASXoLi2dywcCqhKKb3LkvovS8jrPMa6q91XLl7UDAAAAwFoJgAHgW3J96uOjd10cDnnA6lyNmtvt5qrM3K62yoFwmUWa/t/vkKsSx6i2bVSbPq6udrGrX5Q5vs3tFM32l7EZqvTSOh6PXXz+9Zfx2y+u42r3Nr773U08/uxdfLzbxQ8+flFm975+d4qfvr6PvrmNd1NuBP1lPH9+jt/5zZv4yc9+GVW8i1///gfx/DpXz3bx1ZvH6KoXZY2H/RC7mzHu4pReNcU5vX/o0tr36fzp+6Gf4uWhig8/yDOKH+Pj69fx8+M5Xn72PD745BynbogvfvkYbW5dnC799dvX8eFnVVw/T2t8cYpffHlXQrjf+OxFPEvX2Z2aePt4Fcf6Oo7biHZXR5/7Yud2vU31vsK0ynNg67K31dxVOTfzLb8rufU0z7WtqjGaaq76zYFlXW1K0LmLKMHsrqmj2U9xqqs4Hq/TuZv4ZDjETV/H8zZd+1Ufb9P7+0MTP7p/jJ+9uiv73j27SXt/l+5Z2ov036+32+i3+zj2ffz54xDpRsf5sIs+3cdzNaTraOL1+RjN23MJ18fNIS1gF4epiauHx6jv79M6tvF4d4pTqWLtoqv7cvzcxbh0xc6Vz0OXrnUoM3/7c66UPpcW0P1wKh8kaHPL5baL4Ty3e84bk3+eP3yQK1/L9xzzVkMJgHMVbF3PbbTLPg6XivQ5MB9zJfA073nJ0udGyZE/pTDlZ7Qqn1vIo4Gjr3JFddaUSt/8D8l3edZwbl+dM/gyu7ePTf4wRPpBbjP+ItcTl9bR6ZzpGjZTuun1Pt6kc7fnq3gcn8fzsSn3qy5fVbnv27TO/AGIj4ZNfDKm/86VynkGcn4u0nG3JfQfyyzjzRL+PqnGEoBv0n3bbpulWrzU4i8ziJeXVfVfzv9xAAAAAIC/RAJgAPiWfBTb+M7dFP3+FMPVoQRoZT5qrtAc5hm1MQ2x2eyjnjZRDW0MOQvbjbG7PsS+3kbT1dFvH2L34sN5Jm5/inf9Nn56auPnpyp+4yriN377ZXz6axG7cYhd08XjuYkffXWMX1a7dO7beHjs4sVjG598eBU/+M1P47vfO0aO1fa7q5imJn751Rg/f2ji4fA82u4uXl5tSjB79/WbONf7aHfXZV7vXT3E9XYb576OL9/dxfHFEC/2D/G7PzjEdz+5iv3VVRw2p/jidRWf30fcPftO9OM8R/ajcxfPN3389m99HB+9PEVdd/HhiyqaqoufvWrjx2+reHj5Iq0hr3kb065ZWvEu1bx5Rm1u9TyURLJk5vWYW2zP/3Qp4W/ez2Zu7ZtbIm+apaXx1JT3VeM8E3jMVaubKo7p9febJn76tourtBfb7XVsm6oE8W2uhN1V0X9wiD4OpeVxDjTH0zGa3F44re94uIpTDhVzdfYut0Ye0znStZ2OZd05mk6XEvv0HOTpvWnBcZi6tBenuH28L7OW796+jp++fhOvd3U8pPv/eL6Ph3Rfq7aMcY5zev2xT8fq0g+ijdPxVbpzx3Tsc/rqS8VulwPdMY8GHuZ2xzG3yC77UNobV6X9dZ7xm/ew2dYl9B2HoYS4c0w7LtXf09OM3GqpXq+WoL2ExuXlczvqfNIcMA9Lm+Y88zefamjPOXkvE4Fzg+l+PMcmH6/fpNvT5DLjcqy+GWKq5lnD6cFLe5/2/TzlTDg2U2k6XfZwWALa3O46Vyfn1uS7Lrc4T9eXrqXPD9g5fXXDsutpzTmszvc7Vzo3cxA+LS3Bt7vm6e/oNDeyLn9+et4AAAAAYGUEwADwLdkNVTTdEGMp7xxjbPtoDlVpUdzmsDZXKlbNMqt0U0a1Tv0upsNtCcba3F+5HaK/+SD2n30/xtd9nKe7yJnnX5x/Gf/8y8e4/t5tfHQ4xbN9FzHs4uFcxZ9/9Rh//Oocdzcv4xQv0jHrePHLOnY3t/HB4Rg3110JFM/tKV4/1PFnXwzx8+lZvN7WcZj2cdi/jPq4j7sv02u6fTzeHuLt7T6OuybqdPLT9U18OXTxZVvFtspzf6/Te5qYujoeXm/ix794E3+Rru7++bM4D328bh/j5as+/urzF3G96eL6k31pSzyk/Xn9WMVPHqZ4c3gWX+WZvLtdLoZeGjbP1Z+l1XAsIW89V3VOS5h7mfk7dyh+X72Zq17nKbPpnU167SYXxuZK6F2pWs2hY31+jHdNFb84TPHpJ8+jO9fx6vF1DIdDaRudWw9P23mGbG41PYfAVbl303mIYz/EaXwX29023dddVJttWvs8v7jJs4xzWJlWtc/55pjrZKu4qTaxSfvWHE/xWy8+jS/ePcaPHh/i82YXv3g7xldpP7r8mnTPxn6M49TFKW1IbmFcpxW05zaaup/bHeevHMrmsDQ/Q9t5FnJe69zieFFaaOdwd57xnCuAy86WvHOu9M0haWkY/TQPd7q8dQlV5zC4yRW95f4MkSc/72IO3pvcHjrmude7x3NUD+eY2qGEzMtQ3sivyLN5S8Scz5v3ZJorj6t6KB8KOFRt+v0xNvVY2qbPZ51bV/ftOV1bn/a4Kv9ibfoc9A9lZnGe9Zt/Vy159zevoTwb1fzBgPy6cm/KXOC8b2NcRnN/c8sAAAAAYE0EwADwLcmBU67OzLNrx64rbaDHfihVjLnlbp5DW42bEpJt6m1scwi83cd08yJyDPbl8SGqbhNvmusYvvPdmA59jPvbeHy1jfFtH//H11/EcXiIv/bRFB/tpuj7On761Sn+9FUXP69exvnZx9Ftn0XXTTHevYrjF238lZdjfLyPaB/P8fXDOX78Jr328Ta+fvYyXm2reF5X8WZzFT87TvGL8RBv94d4s7+K+6ttdJsx6naKu6vr+On9KX7/63PcP5vi020dm7aN7n6Kz3/ZxP913sXPX6TjPX8R/TTF8/ttbL58F5vueXz6LGK3T9c+NvHuVMVP37Tx56dtfH71PF7f3qbz7KOv5om94zQHkjmoG8ts31yFulnm/b4Pf6sl8XsKh6dL9epUWvzmOtRc0TrlgbVN2rt6Dtu7zTZe78f4YZ/bKT/Gu+0UXx22ccrzj3OlapPuXz3Pas6VxFU9z0euLiHpkI6RWw53bQlgpz6/tortLkr1cR1NDHnGcG53XGY/d7lMN+3VVCqUf3R+jOHNm/iz4Ryv0jXcdUPar90yLzq/J7dtHstah34sYWUzpr1O15Aj2H5cfpcLfHOr7DwHuKSZ09wKOqIEv3lXyqzk9Lv8QYM5GJ3D8vz+0kq7bN0U36yAzaHrJUieW27nQLeNJn1V/TGu21N8lg7QpV++KS9q4jfS2X5895iucYhdniWcK6nz+sZcIRxl3fl1U5krPJTWzFOeFTyl48Y5tpHe29/FR0MX+xy2p3fcp6+P03G398eo0rGbtovpnPY9va8ugfc8A/mpknn5u1fV7+dFX64uz43OIXD+Sb20Fq++UQNsFjAAAAAAayQABoBvydfjOb4YjrHbXc0DXYcuroc+tl0fm9yutxtj2uaWxOMcSDVN1LscAF6XcPjrHHLFPo5XL+P44irO9Ske2z7uTunP/fNSQfn45l382avXcRhPEel9ff087nefxvH2RbTX13He1NGn8x2b2/j6/j7+5N1DvBzuox6HeIxtfN1cxf0HH8Tp+nl06fyneB3/6PUv4/d/foyr/XU5zpvDVfS5wrI+x7Ad4yFXyI4fxMPD1/Gju/t4mdZxna5nOEe8qz+Itx+8jFcv0veb29K+N8++/eEYcf/qFC/e3MXtdR2ncxUPfRMP9XXc397Eu+fP4u5qF6dt9TS7tUR5ufp3nNsS1/Uyu7XM+Z1DvnFc2g7nMH2pdM3v7pcZt7luNoePuSVwLg8tLYtz++EcHF4f4rTbxudNFV/2D+na+xieXcUpF8puN3P4moPgvJ5pDk2nrivn2TXbpdV0s1TXpv1J15Pn2db9Pp3zKk+tTT9P1zSm19XHGKuHqPc53D3Hu/4cP//pn8W+neLxw5s4bus455nFbRtDO6R3puM1dQl305tjzNW0eZDutDQqzjN1c4i7XHOeKz2MyzTepvmV53CejRxl//JM5LxhOQTNofJQqoWbcrzcUvrp4PG+EngOgacSTFdTH+P5Ie4+/0mcq3N8+b98EOP3bst78/zgu2kTr/73fxrXj+fYDXVpFT3VQwlZN6XUvc51wOV4m2q+ntKGOof74zG6V5/H8f5VPPzBZ3G9n+I6PQ9jaZ0dcfqjP4kX9318Vu/ipu6iq/JaujIjOd/XTbpn/TClr648PaXddbl/TxtRPhhQ183l0p6u7327bC2gAQAAAFgfATAAfEveNmM83G7jdKhjrPq43tRxyNWg/Vjmu1bdWNr8Tk21hFNjNHUV59yi9nAdU+4c3U/xMFXx2L2NvhuivtpFdXOIU3udXltHt7+JN/2L0gZ3Xx2i2d3EebuL066OYVeXVr05dDvd3MRDu4u3D7fxrP80dnUTw36b1hhxt8vxXBPbcRvTB7fxOG7Sua+i3lyl915Ht9uVCst66spM11Na33D1rISn70638UXbxj73bb6u4/FmE/0uv+cqzjG3JM6B8fCd78R9e4xte1tm1da7TVTX++j3h3jcNfG4r6It/wrpY65dnds+l/rMaa7tLCHlpV1vnsNbfaPlcw5+q/eVnmMOh0syHLFL17apNqUVdF+la2jOMTRTOl9a6zTG9nYTda64Tf8Mmpo6+lz1W53nVsnTvJZcJrtJ113uVw6kN0tV7dJ+uS7tkXexGQ5pG17EbfNhus7cAPpQAuC6aeP+9FWc7t7EkO5HySWfNSVQ7tL9z0FsrgqvyzWN0ZWZxpvyXDTTNk/7LRXQQw43SwjdLwF1lHm6Odyeq3vnwLfMS16+l/bV41xVXS9hZw7M33d7HstelkrhGJc5wvOc3rwHlznC+QMKTZWf5SGuu2Ocf/Sj+Cf/5Q/juGtjLOfblCroXfcuvpueh93Qx3ns5nbeuVNznyupm3Rtw1MF7lwVnBtL9+k6z9Hfv4ptOse//Lt/L/7Z//j347hPT8RmKhXFN/dtfO9+iKtzm57HdNzNUN6Ztyzf7RKK55nM6QfDPO53fjaW+dH58cjheG53nY1lb5c24dP8rL1vgQ0AAAAA6yEABoBvSdU0MebK2SW5HJeQr9rHU1vjnFqVStdpiCZXITZVqbbth010u32017fRdrnlbq4cbuPmahPVs5t4GLo4PVRxynNn43mMw1jmzW63mzIjuK3nyuImt/2tmjg2UxzrQ3r9TZzSAnJlZM4Xz00Xj9M5qqFJa9xGX21iqHfpvdcxVVdzVWsOGae2BIV9rkxN/91tmzjvrqI+5OC4jrrflND1uMtzWtM6mlwdO1c2d7mSdZ+ONW3TeZ6n11bR5BA857O7Oh7T2obNFHVuGZw3Y1OXFsGxjI+tytTYOpYccq7YHJe5trEEsb+y8dVS9ZqH1W6i3hxKAH+uH6P6IOK0P6U9OKVrr0uIWipm833o2/L2cpocynbz+qtlhG0OP6dhbq9cKktzZFhv0v7sYpuubZ+WcdXvY7/Zx3c/+F4051wFvIvTNM+6/frrJr76Ordy7qNNP2+rxxgPXYm8cxCa5xrnttP1bhvntkt/nGJbN9G2ad/7c6lwrfP42npeVG5vPV5i8ksWPsU32jZXT/OA52vs571cKnrz9kxL2+jS3nrZ21KAPSwVv0tH5FJ5PQ7lQwq5bXS6bfFh+t3zYxfD47msYxrn+cpTeqZepHu8Hab5WcwHyHuWn53Ile71HM4OU5kFnM9dQv/xHIf09+M6rfXqviuVvN1+U2ZCN+le3PZTfJCj9vS6qp7Kc5lvQ1V6hc9hff7AQ93Mz880zoF3DoC3221sNrnN+vy9hNxLx+d8T8u+Ne/bRQMAAADAmgiAAeBbsuumqNsxtv1UBrU23RDVrjSdLSHqUCo3qznRK0FdrgDOY2pzOLwplcJTv4/x5ja23Tlujo8xXR2iPh1jPGzjdVfHqSRgVUzp90P6n7bpY2qmmItHc9CWk8FtbMYmLWGM836KbpdbBfcl6mqijs2wi6nKQWU9T4YtoWsd/ZhntW5L1ey2yRWW+/SrbSmznOpcpdqVULGvtzENOTjMYd1Qgtu6mUo1Zsn5cjiYrrGfmuhypequjl0ZSdvHedPHQzWV2b6HHDYPdZnj+tTmuQS/Q6l23myb0ho7H/US/j5V/eZwfZkJnMPOaphKSFvlUDIO8RinOF9t4q/9h78b/UeP6Zxv8mDaaHNkWM+xX24VXboR5/Pn6ysVuU0Jm+eTTHPOmOfZ1s1cMZrXMtbpHm/jRbyMF8PH8YOb34m//df+TjyL69LHus1pZzvFH//TH8V/9/f+Qdy9exe7tGdj2o9mN8Wpuy+zdXOVcg49+yrdx6ov1am5Tfh4zrOBc4hdL/OB2/TIdFE18+zaPt2HKier4xxmX2YjX+YA55/lILiuhnlPp2FuwjxeZidH2ePcHjpXADe5Aj2qZc7yPD/5krGXuuwc2A99eVZu0v1uxja9t0/X08aQ5yePpzi0VfpHZXo+8xPW1Mu9qKJPfx/yLOn8YYfN8nyW2DVdQA5ym/GcnvX0u9zuO7e0bnflWvZLK+/cTrrdzW2/t9NS9d3M1c6lqjo/h8tQ42rp3D0toXd+Zra77fx8RCzP0ByQP9X9qgAGAAAAYIUEwADwLflwauKj8xj9aYzutiSHMU5DmdXa51nA6b+bUlmZw8slEM6thEsVZRNDDraaKraHXTS7XdTNXOlZl7G0uZ1uVaojp6mLzSaHe1MJNcd6DlTnWHOTzpmOOaav7SaGTRt9fSoVpPVUp5/vYptD3vTKU9XHIb2vyZWb45yeTZsprW0ogXJ6cwmV69JeeSzryK2D+3GIaPpSaVlCvc3STDivc5znz+Y+yc1Ul7BySOfpSqnvstZ8XUt757IPJWgdYm5KXM3VwMts2m+2eZ7bCNelajaWqy1f6X/tSwjcxKa+iv/4P/rP4nU8xH/7f/73sf3+s2i/08e4SdeZQ9TcRHicZwM31WaecVuuJ8p659bIc2vgucVwnZtll6rVHE6PZXZtE4dhH4d+H8+7m/i1jz+L3/mb34vrcQlRc9VuV8VuN8ZXX/zNON+d4+27+/jx5z+KY/cYp+MpraGNajdX5ubno4SXuTp3mD8wkOVZzuPYxXY7X2iJKkuGOZYUt+zFNO/5ONeVLxWw8/rHHLIuLa3nSt/pVybezllqM1cOD2OpL760wK4vVcV1VY6Ty4Q35dzdXL0eS/vovk3PVVp/evbTQxnVpTJ3LFHrHNBf2jGXCu0oe3iZvVuV5yU/m/PzWQ1dqbzOLcvzZxmO6Xy5arwco5tKO+cc0ue/C/kG1emcufI8t5kuoXCuMK6WoDiPIM5rqr9RIT3FEhZXT+3FRcAAAAAArI0AGAC+JS+GiF87RnzZt/Gq3sW5bmNbdRFDG93Dfez2m9jmWb31FP12FznNy6FjbtlcItY6t9qtcvFwHPa7ON7cRnNuS/XsYaziNge7x4c4tznsakqlbaTz5OAwJ8Oli3KeeZu+6u0S3OZss5QHX8K8dO5NP8+QHXJdcK7u3ZZgcRjOpS1vfl36beQuwtH35dryOXJ1cJ6wW3oCl7bL76f3VtWmVI/mKPLS4jcH1DmMK1XBOaCu5umvV8PSYjhX3e7GpWqzKu/pc8CYq0XzWtO56zK/tZqrm+u51W+Z1TuXsS6VrVMJcpu0cc+uruJv/fW/EV+0r+Mf/PHfj4e4i3fb1/F296q0yM5LzqFzDle325xo5/LlpUI67XHXpuPkecWbaZkPm4PJprwvR8F55nIOMff9XAX9vHqZVteXCuhpCcpzYJorhje3Vfzt/+Tfjc20jz//s6/is8+/Hx9/+kH8w3/0P8cf/tHvze2d+yF2OahN/zHkEL7JgeamLKsq7Z2bss9l/vHYx5Rbis8p8Hy+aQ5+c3voS6Xr0Hfzvc/3pJqD8rlF8hzylvdXc8vsUn89zOF7qSIu1c7VEuJOc6vmHKTO/ZZLFfOYX11C/Gn+h2R1Wz5QkOcY57be+cme0jN+ruZq231V8uNSzVst4et2mu9rqS7Pz0jevzzPd1uX5+889KWSNwe4m2GuLh6imz81kOcSzxddnqPSnnvMz346fq4+zqF2bkOe5zine9xsmhJ+D+V5rctx5/B8fo4BAAAAYG0EwADwLXmsxnjXDHHOeVSuqu2GGM5tdFVbAqumO6evbQmohnoskWfOn+pqnuyag6rdflfmnebAtWvb6NtzCejO6fv5fIq+b0vFaNeNJdDLIWpd10+VsiVKXdolD3O545JzLdW1pfJ2KgFg/vWmaaJfZhOXoGxpiZu/180ShI6l8fHcBrlaQrvlPdVSPpl/nAPDUjG7tCC+hJO5V28JlS+llrkauRymeWpbXCpBc4A9DPP5yhqXoDivpczgnTv2VsvM3/m8czvfKe17m/bs3fA67f99vG2/irZ+SD8/pb3PM2vTvuX1pPX16b48nh/iZnOd1jrNc27zvUjr6YYuxn6M3W43z8SNudb4fE73Lv2zqdp1JUDM849jO0afw/3qVMLHvlmqqMe5DXFOjX/6+U/jZvdBfPid2/j4u/9WbPdN/PyXvxV/9C9+rxx7ngudc+j0rAxNaZPdl0rifOwpttt5FnJp6Vwv93Gc96Tch+WeX6p8Iy5tsTdLcFy9v/dzbrw8E9M3uh+/r4FtSnvlqlSu52uYW33PFcHVMl/3m3t/CVCry71a5kDX+dMDl07aJRgf5qC+mauALyFstbw5n7eE53nP8/XHN9p7L9eVn61vrqNUJqdj9rmCOtd2L8FvSZur6akCuK7fH29a9vupdBwAAAAAVkgADADfkjdTHz/LYeC4jX4Y5lnA3RjDLlebXpfK3hxwzvNIqxLo5TBqyGFvnqk6jKVSsRRGNvMM3Pw9h6fb7Sb996ZU8JawK89+reffzRWb4xLo5QCsLiFxKRBeqkJL5rX8frxU6i5hXlP/K6Heoqx1ms9V2ubWS5Pmeq6iLCFi18+B8zd+n01LC+VY2vHmUHEqgXC1nHcsa6nLOORh2Y+6fOXzTu/Tybm179LGdxzHp/mu42VQbX7NZt63N/dfx3/13/zd+LL9Ou33Y+Qi37qfW29XJZzelILfto3Y7evSyrjMHc7rmprYtOm+1dv0fZPHHZfAcduk+3me5wNvd00JiOt0b8d+KBW5l6A6z1wu9za3Q07LuX+8i9/7/f8tdtUhfus3/0q8eXcfv/z6q/jFl5/nxDv6ZbZwDqZzW+2ptC+eK6nnALebrzWHssP8AYHcwnroc1h8CTSXDxHUl1B8WvarlFmXudL10mr8UjH7/hbPe3aZI3zZ8nHsn8L8ar4BT0FzqRq+BKmXVsrj+PTepq5/NWidD/j0TJcx2Ol/bTbbuZXzeKkAzx9G2JTq7mpZU30JuMvahvT7Jfgd5+c3PzfjOC2V0tXc7jm9rz21Zb5xblmer71aWmJ/84MDl+cKAAAAANZIAAwA35K7Zoq7232ZhdsMY2z6KartVEKttmujysHaNMwB2zA3462WebaXOcE53OpzQJurF3fb2O52sdtvY3/Yx+FqH7vHbbRtG0P/fj7u+4mqlxA3/7GZQ9bpMs92KnN5SyCW2+nmNsr1WMLWbRkyuwS+TxWj8+Eu/30Jzy5B8iXgu7RlLuuY5um1c/XvZS2X6uSlCjWWttA5+B7GJej71fD5qYJ4nKubn0LNb4TT81qW8LrsXxObPBf30MS/+Od/GMdtG/vvp307beP5400JREvr4nT9XboX9cMUz+vbp4AwlmrXzf05NucmtoftXCU9TiUQPjycyl5eTdfltdu0vx+ML2J/PkRz3kQzNqWhcqlUXe7EV19/Ff/kD/5xnB7P8b/+40Op4N6me5rv+5h7POcAc5ndmyuOh76eq7I3uTf0Jvr8oYB0D7dzIjrPlB7nub6bzVJhO857nK+j3NM55Z1bdkc8hbhDbql8CTwv93JaKm6ruWp2/vVSaVsvHxu4FMw+PRNjWWO5H3Pc/VQNnpXK32/I92eeHz1XJZejjnPb6WaznGecn+EyvziH0aU6+P0c4k2u2h7GpXp9nGcjl0rjag6qY26FXaq089zr/OwM83Vtd/v5eSpNqv/1ga86YAAAAADWRgAMAN+SbreJh8PccnafQ61+KpW9ddeVWbr73O44z2FNf+6bdinJneaq1By65VBvyP/POQegm3SMXQl9z+d97NrTEgJfRdt283zWfq7yHZc5vc1mnrM7PbUErpdcbm75G0tr6FKQuVTxXoLd92HrNypul9bDxfK6S1VmqfYd57m3l1itBG25erWeqzfnELhMCF6OEUvYd2lTPS1toqunCtZLSJlD0BwSlvNUcyXrJYR8CjKXayth4bgvVbI5rK33u9ik7+3dOX74D/803javo9/2ZfZv3vMcfOZ5sG+bVzF3Uq7nFtN5rnI3xmbflHByqudQfNfsYuymMgP43fYu+qErl3K3fYhXD2+jv51i98VurjSthjJbuG+H+IPf+4N4OL0r4e4Yp6h3Q7q9fQl3N9s5mC8hZ7Ups37zhwHSmdN6cvg7zzx+2u9L1XMObJv5d/nPc1vuy++XUL6Zf5crlJ/eH7GE5XPr5aFU0c4B6mXGcD7W5R7k4/VLyFraLi8Vv8PyPGyWkD7f3VJjvlQCx7BUaF8+SLA8diWun97fwzIBOJ835sC3tP6e6uVRW6rJp3j6QMGlErq8L6+/G0r1cHNJ2/MxxqHse773uVo6t5W+Sn9fqiWqvhz76Rn/xocaAAAAAGBNBMAA8C1pq4hzHbGr6tLSN3+14xSbUjI7pl92MdSnGHMQ12xKTeJQD7F5qpad/1cOr/b1rsymPVxfxePjQ6n4zNWj1zeHaLs+52zx1Jh3mKth53my4xyIjZcQbqnQXAK+3Bq3BGplCO8S9F0C5KV68xLcPf053s/iLe2Zc3XydlMqiuf89n3AW+a6lsQvHXs5z1LrvISRc+vo+S1LGLgExpcg+nK+Syhd5grXv9rC9/LnS9VyDlGjnq+xSYs65DbDQxMPP75P+5zek3tBD+P7yuGlLXBeQz/OrZubJVAetmO0U7dUx0ZZfw5mc2BZqrSrtF95znP1Oh7ac3zx5qv4/f/hD8qc29PwGGVccbqMXbrHh/1VmeubK1JLgDv0Jai8VLpWy/UP09wiOc92rpZZv5vy/rq0iB6Hdg568z4NpRR2nrs8vW+DXQLh8uaxLGCXnpdhnNtpl6ripeq6H7uynrn9cxXzlk/zOksRcbXMpr7c+3FpoXypDJ5/dgl0L8Hx5QMEl/t3uU/lPc0ynziquIwOzm3Sc5/tOpY5zpeK86Y0ml6C2+ryaD3Nhp6WCuS54nlZ33I9+b2X6vP9fh+Hw34O2pv66fj/6voAAAAAYG0EwADwLcmR0jDOwWUOWh+7NoZdE1XfxK7tI0658reLdtPOrY9jV6p/Y7O0RY55PmqZi7q0Pa5LFeMh2tMhTqdjeV9Tgra5/W4uk2xyC+dpDlunqZ5/338jUIsobXjbtIYyP7hqllbUcwvmkvdO8TR7t4SFsYR3MVdjzpWfVamqzMF2dWnnnP47t5DOIfIlSC4ZYn59DnHzn9MaS8VoNQd4OaTLwWQ+fq4WHodvBnvj07nfh3PTUwXsJWTMa80L3y4zZ7sl0OtzCXV5y1QqqZ9Vz+Kmui2ZaGlHnMuEY1iqUmOuQJ3KrqStnIPrHJDm0HeqlmrkahP1NAeS+Wd93ZXgvh5zUH8VzbPd3LJ6M8Q+3dO+bed1XkL0fDv6eb112tsyOzmtNO9lvu/j0k57WGbyzvegKWFz257neb55X8c5MJ6rrqclhJ3bVJcq6bQnQ9WX+5nvYX5/bv2c39N/Y1+jhLWxPKeXAHkJTqf3c3ZLKH8pAF+i2Mv3y+zoeQbwUO7d0/zfb/ydyPd9Spt/mUldnoi839P8jFRLW+66el+pnH/X56r5yzNY2oyn680fAlhaT+drfv+c1HMr9RLK59tbPc2q3u32T9dXqtFLe+zxV9taAwAAAMDKCIAB4FtSKlVzwJcDqlxJOo3RDnPr51I5mgO5tolu05V2z7vS6jZX4M4tnaOulkrZPI92mYGbQ9ImvXa/i6vrq+jaLvpuKkHv42NdjjsnjVNsN9ulqHYsYWsOHavlHPXcqPcpnCvB29THZrstlabvA9y5JfWlBW8Oi/P7q0toVsosl+AyV7IuFcY5PMzrfB/kLlWkOZQulaqXCcBTCRUvrYuHMtP2Mme47GIJEvMahqZfguYoLZovAeElPM7HLuFnXc0tm5s5DG3KXNmqtOBuYju3RR5LxFvCyNIrery0Hc6B+CYdf1N+lo9Zl9bWUV6bK3U3U25HnSu5m1J5XeWAcezn0L6fSriZs+NuTPdm6qKMNJ6W1trz5OFc3lumA5cItxrK9Zc7tczgzWFwDoa3eYZtP1fI5vXmGbb5QwDz8dqy5rnAeA4yZ0v1dzV/gCDfl1xdW5VZu0tFeHNp7b1UZy8tm0s1cgluY07ul7ryMqc35oD2EprOFeLzXYwloC/tt9OzPAxztfT0jcrhfO6yx2NufT28b8M81cs55+d9jEuL6Pn3lw8SPLW9zuF6vuJ6LH8vynvzMS5hc7VUr+dLS+fa7jZldnZ5ljfNUh2fq7jfVyjP26b9MwAAAADrJAAGgG/J+dzG67d3ZXZtTk93+20Jo443N/FwfRVvb+/jcL2P/dWhVCYeDofYp69N3UTXd6WSNqejufozB5H37+7j8d1D3KVj9m0Xp+NDvH1zH8dTG8fzOU7d3Mo3h3N9CcaGpcp1nNcQ1TILdamI/Ma83zk4HqJL79vvqxI6jlNTwsh+zMHmXCG6ycFqrk0d5zB3rjLOSd8lxJurg6tqu1SMziFvqTC9zKvNVcNdP7cRXqow62Z+fV1aZNdP84bnWcBzRXJdjtmUADQHgM0yz7ZZqj9LG+ClfXP6YTnPUA1PM2Nzxei0tJ/OB+yG3Pq5LqHvXNFcl/AwV/sO01K122xKuF7eOcwh5lT3c/vh3EV5u0m3dpf+AbUtx8yzhKOa2xhv6/SCbq48zfteAsYhz9xNZ9rMla1jCcirEjjP1zg+tVDe1PNrN+mZqTZVmYl7fX2djnxO+5rXup8/GNCPpVp4rJaW2aVF8zAHwOU5PM4tvtvyMYSn1twlSM8tuYe5Ojvv56Z+38I5h8pjqe6ul1bKY9mvstebpfK3XMt2fuDrS0vu6mmucF3NM4jLq5slEU4v2aQNaJa5wUtWvbSznqvd5+epeqpQvlTAX9o8zyn+HDyXCuK6fpo7nN+XK5ynvp+re3NVfTOVDwQcbtLftfT3LYfu+e/iXDn89FGGpRL4L+H/OAAAAADAXyIBMAB8S3IlZLPbxtTN5ZRDntXaDfHw+BBd18axPcX2XRM5G6ybKnb7Zm7pXCorc+XrtlTtDtNcgXk+tXNwmn7Wp+MM6avrupi7H+8j58Wbq/znIdr+XILeEtiO6XU56JqacswcA45DVaqTS9VnDounXVlzDsAeTg9xfLx/CnOXTsTLhNr384kvbZnz2sq6S6vouX3xZe5qCX3LgecAMZZAcHoK3pZwt1T5zkF3swTHufLzaQ5wCYmbEornAHhYQt1LuNssbannKt5LReo8V3YaL+2w3weNl4utL9cwDy9+f/OWGbf5PsztlMenauK5TfNcjR1LlfP8lnT+dG9K3HlpVRxLtDjMrbxzoNpUzfvTjMtE5GGugM3XVo/VU5A9V2yfS4VxXvDdMe9vW95XLxXiQz8u7beXiusYlv2sy5qa3Vy121Zdqbwtc4Fjabmdq5jr4Vdbbk9z2+jSAbuankLjuSN0/ZSSTpcNHef7NLfPHi+9xi8PTbmeeYvm56Qcq1qahtfzDOhcHZ8rv0tL6Kd7Ms+zrur3M6Uv1buxtMnOH44of626ZSZ0zJ8WmJ+pZY/79N+PQ2yHXfzxn/xh3D2+ScdczvO+BD4uC/7NX/vPY7fd/r/4mw8AAAAA//8iAAaAb8nf/jv/Qfzbf/2vvq8yXFrtllbHQz+HfXn6a9uWObM5JO6WGay5OnFTb5fKyV1c+uFWS3g4feN/lUrVPgesfTSbqlSvnk+nqOp5FuxFDooPh6v0mv0cRi9zXuslYJvG+fvp9Bhte/xL2SP4yzQH3f/PjZ53O+EvAAAAAOsiAAaAb8mLF8/KFwAAAAAA/H9FAAwAAAAAAACwEgJgAAAAAAAAgJUQAAMAAAAAAACshAAYAAAAAAAAYCUEwAAAAAAAAAArIQAGAAAAAAAAWAkBMAAAAAAAAMBKCIABAAAAAAAAVkIADAAAAAAAALASAmAAAAAAAACAlRAAAwAAAAAAAKyEABgAAAAAAABgJQTAAAAAAAAAACshAAYAAAAAAABYCQEwAAAAAAAAwEoIgAEAAAAAAABWQgAMAAAAAAAAsBICYAAAAAAAAICVEAADAAAAAAAArIQAGAAAAAAAAGAlBMAAAAAAAAAAKyEABgAAAAAAAFgJATAAAAAAAADASgiAAQAAAAAAAFZCAAwAAAAAAACwEgJgAAAAAAAAgJUQAAMAAAAAAACshAAYAAAAAAAAYCUEwAAAAAAAAAArIQAGAAAAAAAAWAkBMAAAAAAAAMBKCIABAAAAAAAAVkIADAAAAAAAALASAmAAAAAAAACAlRAAAwAAAAAAAKyEABgAAAAAAABgJQTAAAAAAAAAACshAAYAAAAAAABYCQEwAAAAAAAAwEoIgAEAAAAAAABWQgAMAAAAAAAAsBICYAAAAAAAAICVEAADAAAAAAAArIQAGAAAAAAAAGAlBMAAAAAAAAAAKyEABgAAAAAAAFgJATAAAAAAAADASgiAAQAAAAAAAFZCAAwAAAAAAACwEgJgAAAAAAAAgJUQAAMAAAAAAACshAAYAAAAAAAAYCUEwAAAAAAAAAArIQAGAAAAAAAAWAkBMAAAAAAAAMBKCIABAAAAAAAAVkIADAAAAAAAALASAmAAAAAAAACAlRAAAwAAAAAAAKyEABgAAAAAAABgJQTAAAAAAAAAACshAAYAAAAAAABYCQEwAAAAAAAAwEoIgAEAAAAAAABWQgAMAAAAAAAAsBICYAAAAAAAAICVEAADAAAAAAAArIQAGAAAAAAAAGAlBMAAAAAAAAAAKyEABgAAAAAAAFgJATAAAAAAAADASgiAAQAAAAAAAFZCAAwAAAAAAACwEgJgAAAAAAAAgJUQAAMAAAAAAACshAAYAAAAAAAAYCUEwAAAAAAAAAArIQAGAAAAAAAAWAkBMAAAAAAAAMBKCIABAAAAAAAAVkIADAAAAAAAALASAmAAAAAAAACAlRAAAwAAAAAAAKyEABgAAAAAAABgJQTAAAAAAAAAACshAAYAAAAAAABYCQEwAAAAAAAAwEoIgAEAAAAAAABWQgAMAAAAAAAAsBICYAAAAAAAAICVEAADAAAAAAAArIQAGAAAAAAAAGAlBMAAAAAAAAAAKyEABgAAAAAAAFgJATAAAAAAAADASgiAAQAAAAAAAFZCAAwAAAAAAACwEgJgAAAAAAAAgJUQAAMAAAAAAACshAAYAAAAAAAAYCUEwAAAAAAAAAArIQAGAAAAAAAAWAkBMAAAAAAAAMBKCIABAAAAAAAAVkIADAAAAAAAALASAmAAAAAAAACAlRAAAwAAAAAAAKyEABgAAAAAAABgJQTAAAAAAAAAACshAAYAAAAAAABYCQEwAAAAAAAAwEoIgAEAAAAAAABWQgAMAAAAAAAAsBICYAAAAAAAAICVEAADAAAAAAAArIQAGAAAAAAAAGAlBMAAAAAAAAAAKyEABgAAAAAAAFgJATAAAAAAAADASgiAAQAAAAAAAFZCAAwAAAAAAACwEgJgAAAAAAAAgJUQAAMAAAAAAACshAAYAAAAAAAAYCUEwAAAAAAAAAArIQAGAAAAAAAAWAkBMAAAAAAAAMBKCIABAAAAAAAAVkIADAAAAAAAALASAmAAAAAAAACAlRAAAwAAAAAAAKyEABgAAAAAAABgJQTAAAAAAAAAACshAAYAAAAAAABYCQEwAAAAAAAAwEoIgAEAAAAAAABWQgAMAAAAAAAAsBICYAAAAAAAAICVEAADAAAAAAAArIQAGAAAAAAAAGAlBMAAAAAAAAAAKyEABgAAAAAAAFgJATAAAAAAAADASgiAAQAAAAAAAFZCAAwAAAAAAACwEgJgAAAAAAAAgJUQAAMAAAAAAACshAAYAAAAAAAAYCUEwAAAAAAAAAArIQAGAAAAAAAAWAkBMAAAAAAAAMBKCIABAAAAAAAAVkIADAAAAAAAALASAmAAAAAAAACAlRAAAwAAAAAAAKyEABgAAAAAAABgJQTAAAAAAAAAACshAAYAAAAAAABYCQEwAAAAAAAAwEoIgAEAAAAAAABWQgAMAAAAAAAAsBICYAAAAAAAAICVEAADAAAAAAAArIQAGAAAAAAAAGAlBMAAAAAAAAAAKyEABgAAAAAAAFgJATAAAAAAAADASgiAAQAAAAAAAFZCAAwAAAAAAACwEgJgAAAAAAAAgJUQAAMAAAAAAACshAAYAAAAAAAAYCUEwAAAAAAAAAArIQAGAAAAAAAAWAkBMAAAAAAAAMBKCIABAAAAAAAAVkIADAAAAAAAALASAmAAAAAAAACAlRAAAwAAAAAAAKyEABgAAAAAAABgJQTAAAAAAAAAACshAAYAAAAAAABYCQEwAAAAAAAAwEoIgAEAAAAAAABWQgAMAAAAAAAAsBICYAAAAAAAAICVEAADAAAAAAAArIQAGAAAAAAAAGAlBMAAAAAAAAAAKyEABgAAAAAAAFgJATAAAAAAAADASgiAAQAAAAAAAFZCAAwAAAAAAACwEgJgAAAAAAAAgJUQAAMAAAAAAACshAAYAAAAAAAAYCUEwAAAAAAAAAArIQAGAAAAAAAAWAkBMAAAAAAAAMBKCIABAAAAAAAAVkIADAAAAAAAALASAmAAAAAAAACAlRAAAwAAAAAAAKyEABgAAAAAAABgJQTAAAAAAAAAACshAAYAAAAAAABYCQEwAAAAAAAAwEoIgAEAAAAAAABWQgAMAAAAAAAAsBICYAAAAAAAAICVEAADAAAAAAAArIQAGAAAAAAAAGAlBMAAAAAAAAAAKyEABgAAAAAAAFgJATAAAAAAAADASgiAAQAAAAAAAFZCAAwAAAAAAACwEgJgAAAAAAAAgJUQAAMAAAAAAACshAAYAAAAAAAAYCUEwAAAAAAAAAArIQAGAAAAAAAAWAkBMAAAAAAAAMBKCIABAAAAAAAAVkIADAAAAAAAALASAmAAAAAAAACAlRAAAwAAAAAAAKyEABgAAAAAAABgJQTAAAAAAAAAACshAAYAAAAAAABYCQEwAAAAAAAAwEoIgAEAAAAAAABWQgAMAAAAAAAAsBICYAAAAAAAAICVEAADAAAAAAAArIQAGAAAAAAAAGAlBMAAAAAAAAAAKyEABgAAAAAAAFgJATAAAAAAAADASgiAAQAAAAAAAFbi/wZ3l77W0gi6NQAAAABJRU5ErkJggg=="
    }
   },
   "cell_type": "markdown",
   "id": "128238bd",
   "metadata": {},
   "source": [
    "# Architecture:\n",
    "![image.png](attachment:image.png)\n",
    "![image-2.png](attachment:image-2.png)\n",
    "\n",
    "## Brief Description\n",
    "The model emulates the process of human vision in reading vitals. Like how a human would first\n",
    "locate the monitor, then determine its type, identify digits based on position, size and colour, the\n",
    "model follows the same process to accurately classify and report the readings. It starts by\n",
    "detecting the monitor screen, classifying it based on the cropped image, and then using the\n",
    "location of the digits to label the data which is then passed on to the OCR for reading and\n",
    "reporting the results.\n",
    "\n",
    "## Monitor Segmenter\n",
    "To identify the monitor from an image, we used YOLOv5 (You Only Look Once) which is a state\n",
    "of the art model for quick object detection. The model will give us the x-center, y-center, height,\n",
    "and width of the monitor it has detected, then we select the one with the maximum confidence\n",
    "score and crop out the monitor and pass it to later stages.\n",
    "\n",
    "## Monitor Classifier\n",
    "Once we found the bounding box of the monitor, we classified the monitor into four classes by\n",
    "using K-means clustering. For this we used a deep learning model, Inception V3 which is based\n",
    "on CNNs. This is documented as the image_feature function in the final pipeline which gives us\n",
    "the label of the monitor as output. Using unsupervised learning through Inception V3 introduced\n",
    "some novelty in our pipeline.\n",
    "\n",
    "## Digit Segmenter\n",
    "To detect digits in monitor images, we utilised the YOLOv5 object detection system. This system\n",
    "is designed for real-time object detection and is known for its speed and accuracy. The YOLOv5\n",
    "model (loaded as digit_segmenter in the Colab notebook) was used to obtain the x-center,\n",
    "y-center, height, and width of the detected digits. To prevent false positives, only the top 6 digits\n",
    "were selected based on their confidence scores and were then cropped for further processing.\n",
    "\n",
    "## Vital Classification\n",
    "The digit's location and size information obtained from the previous step is fed into an XGBoost\n",
    "classifier to predict its vital type. XGBoost, a flexible and powerful ML model, uses decision\n",
    "trees as its base learner and improves predictions through gradient boosting. This results in\n",
    "accurate vital type classification based on digit position and size. The final dictionary object is\n",
    "then easily populated with the key-value pairs obtained from OCR.\n",
    "\n",
    "## OCR\n",
    "To detect text from images of various vitals, an OCR system is used. We used EasyOCR, which\n",
    "employs deep learning algorithms for accurate and efficient text recognition. The final result is\n",
    "returned in the form of a dictionary object.\n",
    "\n",
    "## Heart Rate Digitization\n",
    "We trained a separate YOLOv5 model on the whole Classification Dataset to give HR graph\n",
    "coordinates. We cropped the obtained image of the graph and used the Contour Detection\n",
    "method to extract the coordinates of the graph using OpenCV library. Contour detection can be\n",
    "explained simply as a curve joining all the continuous points (along with the boundary), having\n",
    "the same colour or intensity. We did not use edge detection since it has some limitations. One of\n",
    "the major limitations being, it cannot detect the whole graph if there is some noise present in\n",
    "between the curve, of which we saw multiple examples. We plotted the obtained coordinates\n",
    "using Matplotlib."
   ]
  },
  {
   "attachments": {
    "image-2.png": {
     "image/png": "iVBORw0KGgoAAAANSUhEUgAACAAAAAYACAYAAADimKhtAAHlWUlEQVR4nOzdB2Bb1bkH8M8je+8NGayEDWEHyt6UsimjLaUt8B60UEbZFChdjAJlFCizlFE2BcosexP2SCAhkJC997AdP5/Ls0mI7TjBiWzn9yuqZenq6lxZcmR9//OdwtIyAQBUKf1DmZfrQQAAADXkHTwAALDqKsz1AACoZT7rqnUeTgAAqE+8gwcAAFZdAgAADY3PugAAAAAAAFZJAgAAAACsANoSAQAAAKxsAgAAAACsAIr/AAAAACubAAAAAAAAAAAANAACAAAAAAAAAEA9Yck5qI4AAAAAAAAAAFBPKP5DdQQAAAAAAAAAAKABEAAAAAAAAAAAgAZAAAAAAAAAAAAAGgABAAAAAAAAAABoAAQAAAAAAAAAAKABEAAAAAAAAAAAgAZAAAAAAAAAAAAAGgABAAAAAAAAAABoAAQAgFVGadkpL9eDAAAAAAAAgBVEAABYZSj+AwAAAAAA0JAJAAAAAAAAAACsdHoXU/sEAAAAAGg4fHYCAABAveEPWGqfAAAAAAANh89OAAAAgFWYAAAAAAAAAAAANAACAAAAAAAAAADQAAgAAAAAAAAAAEADIAAAAAAAAAAAAA2AAAAAAAAAAAAANAACAAAAUO+Vlp3ycj0IAAAAACDHBAAAAKDeU/wHAAAAAAQAAAAAAAAAAKBBEAAAAAAAAAAAgAZAAAAAAAAAAAAAGgABAAAAoMEqKSmJYcOGxciRI2Pu3LnRvHnz6NSpU/Tv3z8aN26c6+Ets6FDh8a///3v+Oyzz2LOnDlRWloa3/ve9+LnP/95roeWef311+Ovf/1rdv7000+P9dZbL8cj4rsaMmRI/OlPf8qeayeddFJsuOGGuR4SAAAAUA0BAAAAoEFJRf+vvvoq/va3v8V1110XU6dOXWKbRo0axb777hunnHJKVqRu0aJFDkZac+mYbrnlljj22GOjuLh4seuaNm1aZwIAX375Zfzzn//Mzv/4xz+u9wGAFLLYcsst44MPPqi47Morr4wTTjhhqbd96623YrPNNlvssgkTJmQBlNq2YMGCmDhxYna+Xbt2WdCltqQx33XXXbFw4cI4+OCDBQAAAACgjhMAAAAAGozp06fHJZdcEn//+99j3Lhx2WWFhYXRo0ePaNu2bcyfPz/Gjx+fhQLuvffeeOCBB2LnnXeO66+/PlZbbbUcj75qqZh82mmnZcX/tddeO/bYY49o3bp15OXlxSabbJLr4a1SHn/88Tj66KOrLbKn2fKpA8LK8vbbb8dWW22VnU/P/TQ+AAAAYNUkAAAAADQIaYbyr371q7j11luz75s0aZLNmE+z/Hv27FmxXSqiP/fcc1lb8+effz5efPHFbPZ0XQ4APPvsszFlypTo0qVL3H///TFgwIBcD6lSKWxRXhgvKCjI8WhqVzq21IkhLXOQZsX37t27ym0//vjjeOaZZ7KARuo2kWbo11f5+fnZzzS9vhrazxQAAAAaIgEAAACg3ksF1t/97ncVxf+NNtooWwJgiy22WGLbVMhNs/633XbbrEh76aWXZoXauuzTTz/NvqYgQ+fOnXM8mqrtv//+2akhGjhwYAwdOjQmT54c//rXv7KODJVJs/8ffPDB7Py6666bPbcWXUKgvhk0aFB2zAAAAED9IAAAAADUe6kF+tVXX52db9GiRfz73/9ebNZ/ZVKHgD333DO22WabaNy48coY5nJLSxskaZxpRjkrXwpebLrpptnzLC0zcfLJJ1c6I37OnDnx9NNPZ+d33XXXrHsDAAAAwMoiAAAAANR7aUZ2apGfCrJ//OMfl1r8X1SbNm2qvG7GjBlZl4C33norRowYEbNnz45WrVrFWmutFVtvvXVst912VYYH0qzv//73v9n5Y445Jhvbq6++mi0/kGaSz5o1Kysqp5nle++9d/To0WOJ+7755puz88OGDcu+jh07Nuts0LRp0+z7FHY48MADo23btvHGG29k+0/BhrQGfFVBgXQMDzzwQDare5NNNsk6IVS2TVoa4bXXXsvuO40lzWRPx56WSkjHn7or9O/ff7HbffbZZ/HYY49l5/fbb78ql1VIRfL0OKQxp/3PnDkzWrZsGX379s32u9NOO0WzZs0qvW3aPt1Hmml/6KGHRseOHWPw4MHZY/3RRx9lY23fvn12bHvttVe2z9ry61//OusykZaMSI9heuy/LT1P0vMldZrYfffds+OsTmqtnx63d999N1s64Isvvohp06ZlrffbtWsX66+/fvYzSseTLlvU3Llz4/rrr48vv/yy4rIUPkjPrUWln8P3v//97DmYHvsbbrghuzx1yvje974XH374YfY8T8/Z9LxIz51rr702OnToEKNHj846GqTHOz1PF1364M0334xXXnklO5/CEalbQGXSshvpZ5Yem/Q8OuCAA5Z4vgMAAAC1QwAAAACo9+65557sa/fu3bP2/rUhBQpSETut+T5//vzFrktFzFSgTjO8b7rppqxQ+22pMHriiSdm54888si45ppr4uKLL86K3amYWi4V+a+66qqscNulS5eKy6dOnVpx+3KpOHz66adXfN+tW7fYfvvtswDAU089FWeffXYWaDjiiCOqDACkbgIpJJGK5SeddNISAYA0tqOOOioeeeSRrMBcmVTcTsX18lb35d55552KMQ8YMKDSAEAqQB9yyCFZwXnevHmLPRbpcU3hhi233DL++c9/Zsf3be+//3427lQ4TyGM+++/Pzvu9Hgtuq/bbrst/vKXv8QTTzwRa665ZqXHsaxS0XqXXXbJiv933nln7Lvvvks8zqlDQCrAp+diCogszV133RXHH398FrpIS1l8Wyr6p3DE//zP/8T555+/WOAk3c+3nyNpf+m0qPSaSN0uUgBg0duccMIJ2XMqfZ+CE+kxLZeeqykAMHz48DjllFOy61KYYtEAQApanHHGGdnzJIVDUiBg7bXXXuIY3nvvvew5lV5T6TVz7LHHLvVxafjSc7VuLz0CAABA/SQAAAAA1GupkP3VV19l51PRNZ2+qzRTORVMhwwZkhWlUyE3FdpTwTPNiE6zzdOM7Yceeih++tOfZsXmVACtymWXXZad0izprbbaKiuMp4J1mh2eWsSnGdgpbPCf//ynoiNB8+bN4wc/+EF2PoUQ0uz/dP/p9uVF5xQ8SF0Aaksq8qbibApUpONOyyOk++vVq1f2fZqZ/umnn2YdDNL3y2r8+PHZcaZOBcnmm2+ezfZPwYcJEyZkj0cqIqfHJIUE7rvvvujUqVOV+0uF7uuuuy4LG6SxpgJ1KnC/9NJLWeE//RzTrPUXXnhhsXDFd5F+JikckcIO6XnXp0+fxY4vPReSc845J+vGsDSp8J8ey/Q4r7HGGtkxpEBHujw91i+//HL2eKfnT3reHHfccRW3TftP40mF9XSMycYbbxyrr776Yvex4YYbLtE9IEkz/lP3jFToP+igg7KODiUlJVnBvrzLRHX69esXTz75ZPYznTRpUvzqV7+Ku+++e7GuGp9//nkcdthh2RjTa/P3v/99nV9yY+VQ/AcAAGDFEAAAAADqtdRuvVyaoV1dIb4m0mz/8847Lyv+J2eddVY2A3rRomYq9P7sZz/LCsEpBHDhhRfGn//85yr3mWbcp1nWaaZ6Ku6WSwXTdHnqApACBalwnWbWJ6m1fSqmJgcffHB2P2km+y233BKtW7fOLk+F4zQbv7akVvLl3RR++MMfZrPZ03EvWuxPBeLURSB1MlgW6XbpcSgv/v/4xz/Oitop1FAuhSJOPvnk7PFISxCkmf6poF5Z8Tq54oorsu4K6bFfNCiQiud/+MMf4qKLLsoK0KlInbarDanrQCqYp8cqHcuiAYBUTE8dDrp27Ro/+clParS/FIBISy2kgEL5z7Vc6mgwatSorKNDejx+85vfZMsOlB9r2j49R1JApLzbQApwfPu+0+NX2fMkhQZS2/477rgjG3PqEJCkn1VVj/m3pdunrhRpbKmrQ+pSkH6uSeoqkLobpCBDuv/03E1LGQAAAAArjgAAAABQr6WZ8eVSYXZ5ZqYvasyYMVk7/iS1Tk/F/W9LxdpUmE5rqI8cOTJrQ5/aqaeZ8pVZZ511sv18e137VMA99dRTs5byaXZ96gRQHgBIx1E+U7r8mFJRNs3+X1EzqNMs7qKioux8Wqd90bBCuVQkTkX7RQv3Nd13Wgc+SUXgVOT/9s8qdTRISyUMHjw4a/WfOi2kIEaa4V+Zzp07x6WXXrrEWFJXhGOOOSZuvfXWbJZ+mq1fWwGANOu9fOmBa6+9Ng499NDs55IK/+XHl7oO1GQGfZJm/FclPT5p1v8//vGPWGuttbLQRbrfdGzl0nNh0WUI0s+nps+PNMbUqSAFZxZVHgSoqdSVIIUJHn744WzZhdRx4PDDD88en7Q0RRpfup+0fAIAAACwYgkAAAAA9Vpq+V6upkXX6qRi8bhx47IZy6m4W5VUrE6zrc8888xs+88++6zKAECaIf3t4v+i+0m3SwGANNs7l1Igobz4e9NNN2WF7NoKG6QZ82k9+VTUTh0NqgpqpJ9h6gKQZrFPnDix2gBAKjxXFURIx5LWq08BgPIlImpDGnf6eaZCfOoAkDpQpKUMUnAknU9t+XfffffvdB9z587NntdpJn6S9tmtW7fsMUxLJCwaAPguUieBNIP/u0rLVaTZ/en58sorr2SdLoYNG5Z1AiguLs66HKSADAAAALDiCQAAAAD1WmqVXy61HP+uUgEztV5Pheg0c786W2yxRVYgTy3nUyeAqlRXZE23TwXUZFnb6te28tntjz/+eDz66KPZTP1f/OIXsc0222TdFdJjnWbXL0+XhdSmPhW00/FWVdAvl65PBfy01MAnn3xS5XZprFVJAY7yx3XRkEht2GyzzbKffTqmG264IQYOHBj33Xdf1uUgzaZPj9eySEtKpJny//znP7MQQdpPddvWljTu2gjNJCnIkpZi2G+//bLAxe9+97vs8rRsRVpioLJuEgAAAEDtEwAAAADqtZ49e1acTzPxU5F5WVuYLyrtI0kF5FTUrE7Lli2zIvOCBQuqLdq2atWq2v2UF9QXLly4jKOtXemYU2v+k046Ke6999746KOP4le/+lXWvSAVtlOngq222ip+9rOfRZ8+fZZp3+VLNZQvIVCdFDJIpxQAmDx5cpXbpZBAVdJjWr6OfflM+tr04x//OJuN/+KLL8bnn38eV111VXb5gQceGF27dq3xflLBP4UsPvjgg2y2/NKk7gC1JS1lUZvScyM9d1JXjCT9nNPjkpZqAAAAAFYOAQAAAKBe22677bKicirypuL9lClTstbmy2vRYnF5AbkmUteAqizPjPlcScXrNGP7+OOPz2a3pzb3aXmCNKs7tXV/9tlns9bu1113XfzoRz+q8X7LH9dFC/PVKX/MqntccynN8k+F7REjRsQf//jH7PFJrfpPO+20Gu8jPa4pYJGWnUghi9Qq/6c//Wlsuumm2c8hhUvKH4fUFaG6bgjLIwU+atPUqVPjnnvuqfg+dV6orjMGAAAAUPsEAAAAgHotFWE32mijGDx4cLZGepqN/V0CAOWzt9Ns7FSgrc6cOXMqZmQvbVb7ilbTgnnqMlBUVLTUfaUCdzqVL2+Qiv/PP/983HrrrVm3gzTTO7XC79+/f43GV/64piBAKhRXJz2m6bFNcv24VmWttdaK9dZbL55++um47bbbsst233336N69e4338emnn8a7776bBVhScOC8886rMixSXSeEuuIPf/hD1skgLSuQumekrg+/+c1vonfv3rHzzjvnengAAACwShAAAAAA6r00azrNok4F+9tvvz0rTNd09n55wby88Lr55ptnX+fPnx/Dhw+PLbfcssrbpmJn2i7N3l5ttdW+41F8N2kMSSqeV9dKPs3KTl0Saiq14k9F/nTaZ599YpNNNonDDz8828c111wTf/3rX2u0n/S4psc4hQ8+++yzarf94osvsp9lKoynQntdlIrcRx11VBYASMeUxnrwwQcv0z5SqCIFHdq2bRu77bZblcX/tN2ECROq3M+it8tFx4R0nw899FDWGSKd32+//eLCCy/MlgRIz5O0ZETqHLGsy0YAAAAAy04AAAAAqPf22GOP6NevX1ZYvv7662PjjTfO1mhPRdmleeSRR2LDDTesKOAPHDgwOnbsmM1yv//++7Nid2VSIT21wU9SF4K+ffvW3gEthx49emRfUzH6v//9b+y///6Vbvfoo49+p9nkgwYNqjg/ZsyYGt8uPT6rr756VtxPj+svf/nLSgveafxXXHFFVkju0KFDrL322ss91hXtBz/4QdbCP425ZcuWiz02NVEe1EjHuujSE4tKAZNzzjmn2v2Uhz+SXHQKePnll7MQTjqO9NpLQYCePXvGjTfemF2eOkicccYZ8c9//rNGr0kAAABg+QkAAAAA9V6aWZyK8WkN9QULFsT//u//ZkXZn//855V2AkiFyunTp8dZZ50Vt9xyS7zwwgsVAYBevXplM5f//e9/Z4Xqv/3tb3HMMccsVqxO+z722GPjo48+yr7ffvvtswBCLqWZ+eVScT21o09ryJdLx/zSSy9lrearmiX+8ccfZ8e2/vrrZ8dbWYH+xRdfrDifWuDXVApJpMep/PFOreH/9Kc/LXYfaXmC9DNJ1ycpmLHBBhvU+D5WtvT4Xn755ct9+zXWWCMKCwtjxowZ2Qz5tOTCt2fz33nnnfHAAw9Uu59UbC+Xtk0/46q6CdS2NMZTTjklW9Yh/YzvvffeivHsu+++ceSRR2ZdIu6+++5sKYA//vGPK2VcAAAAsKoSAAAAABqEHXbYIZtxfPrpp2ft0o877rhsvfodd9wxayPfqlWrLByQrkvrrqdZ8mk2empxv2ixNLV2P//887MlBb766qssTJAK57vuumu2j9QZIIUDHn/88Wz7rbfeOi655JJcHXaFVEz+xS9+kXVAGD16dOy1115x2GGHRadOnbJuBW+88Ua2PEIKKqTwQ2Ut5dOa9IceemhW2N92222zxy3dvnHjxtlt0uOW9pGkGf3HH398jceXZn6fffbZ8frrr8cnn3wSF198cdbaPo2zffv2Wcv/J554Ih588MFs+zSGG264ocZLOdRH6We20UYbxVtvvRW///3vY9SoUdnj3qZNm+znk8IWqaCeHotx48ZlP9fKpMfvgAMOiPvuuy97fNNyAuuuu272cyu/n7RcQQob1KbZs2dn4Zh0n0l63aQif7n0s0vHlV5n6TWTggBbbLFFtkQAAAAAsGIIAAAAAA1Gavuf1ppPs45TAf/VV1/NTqnwmYr8abZymmWeTkmTJk2yGcnfnsme2pin4muaRT906NCsdXmawZz2kW5b3q59yy23zC5PSwbUBVdeeWUMHz48nnnmmXjuueeyY0hF2HTcqd18Kjbfdttt8cMf/rDKNeXTtoMHD85O6bapcF9+3OUt69Oa9TfddFMWDlgWKXzw/PPPx5577pkVvdNs9Ycffji7n0Uf1/79+2fdF9KSAQ1ZmjGffmY777xzzJkzJws83HzzzdnjkR6LdErPzfQY7bLLLlUGAJIUfkmBivfeey+eeuqp7FQu7f9HP/pRrQYA0vMkdd244447su9POOGESjtupKURrr766mx5jiFDhmRLJqQwTQreAAAAALVPAAAAAGgwUvExzXxORf80wz8VQVNBPK2LnlrbpxnRaXZ1avOfZu7vvffe0a5du0r3lWYyp5n/acZ7muE8duzYbD32tN56un1abuCggw5abP31RQ0YMCBbJiBJQYOqpI4DaUZ0Ks6n8EJl0ozurl27ZksdlM/qrky6n7vuuisrzr/yyisxceLE7DFJAYXUISEFI9L3Bx98cHY86TFYVAo8PP3009lxp+UAUkhg5syZWSE6tbtPY0hjPPzww7Pi9belAn/5MS/aln5RKTSQAgqptX26n1TUnjt3bjb27t27x3bbbZd1LmjdunWlt0+PQZp1ngrQlY2hXCp2p6BB+jmmQMHySPtIP+PUmj8tRbA869cfeOCBFT/Xyp4rabmJ999/P1tqIhXv0+OdHot0bOnnk8IaXbp0iUMOOST7ma299tqV3k96XqdlBNJjm5amKH/OJ+uss07F2NMYyn9G6biWplu3bvGzn/0se7zLl8lIUjeNNNb0s0gdCFJ3h6oen/R6ufTSS7MuAMk999wTP/nJT5Z63wAAAMCyEwAAAAAanFRA3WOPPbKCdirap2JlmmGeit+NGjXKiu41WSM9Fc5PPPHE7PZpP6kQnoqc6fZpP9VJrdzTaWlSYT2t2V6d8oJtTaQxp/3NmzcvG3M6zhQaSGMud+6551Z627RN+bjTbP90+/Q1FX/TcafHtboAwqabbpqdliYV91Ph+Kc//Wk2zvLHdWn7T1J3hmuuuWap95H2k2alfxdpH+ecc8532scZZ5yx1G1ScOJPf/pTFoRIRfv0WKT7XjQ4UtXPbFEpzJICB+lUlbSMxbXXXluzwZdZc801s9b935bGdt5559V4PymMkU4AAADAiiUAAAAANFip+J2K2osWv5dHKsYurTBd13zX406z32t7zfhvSyGKpQUpVhUpnKItPgAAAPBdCQAAsGopLTstfcInAAAAAABAvSMAAMCqRfEfAAAAAABooAQAAAAAAAAAAKABEAAAAAAAAAAAgAZAAAAAAAAAAAAAGgABAAAAAAAAAABoAAQAAAAAAAAAAKAByEkAoLTslJeLOwYAAAAAAACABionAQDFfwAAAAAAAACoXZYAAAAAAAAAAIAGQAAAAAAAAAAAABqAOh0AKA3LBcDKcvbd78W/B3+V62FAzr33571yPQQAgDpj8IjpuR4C5FxeXl7ZKdejgNwqLc31CKBu2KR361wPgf/39KufxNHn3JbrYdQZg+85Kzq2a5nrYQB1RJ0OAPjbClaemXOLYuKM+bkeBgAAUIcUlaj4QF5eaRYCgFWZAABQ1ywoKo4Jk2fmehh1xsKFflED36jTAQAAAAAAAAAAoGYEAAAAAAAAAACgARAAAAAAAAAAAIAGQAAAAAAAAACAeiQv1wMAqLMEAAAAAAAAAKhf8vJzPQKAOkkAAAAAAAAAAAAaAAEAAADqgdLQ3g8AAAAAoHoCAAAA1AOK/wAAAAAASyMAAAAAAAAAQP2SZ7JABQ8FsAgBAAAAAAAAAABoAAQAAAAAAAAAAKABEABoQEpDlxcAAAAAAACAVVWlAQCF5PrJzwwAAAAAgIYlffJdmutBAEC9UWkAQCEZAAAAAADIPcV/AFgWlgAg9HwAAAAAGjKffABAA5NX9i97Xn6uRwFQJwkAEP4EBgAAABoyn3wAAACrCgEAAAAAAAAAAGgABAAAAAAAABoy62AAAKwyBAAAAAAAABoyxX8AgFWGAAAAAAAAAAD1S550E0BlBAAAAAAAAAAAoAEQAAAAAAAAAACABkAAAAAAAAAAAAAaAAEAAAAAAAAAAGgABAAAAAAAAAAAoAEQAAAAAAAAVmF5ZafSXA8CgGVS9rs7Lz/XgwCokwQAAAAAAIBVmOI/1F0COgCwrAQAAAAAAACAOkjxHwCWlQAAAAAAAAAAADQAAgAAAAAAAAAA0AAIAAAAAAAAAFC/5OXlegQAdZIAAAAAAAAAAPWH2v+3eECAbwgAAAAAAAAAAEADIAAAAAAAAAAAAA2AAAAAAAAAAAAANAACAAAAAAAAANQjeWX/5ed6EAB1kgAAAAAAAAAAADQAAgAAAAAAAAAA0AAIAAAAAAAAAABAAyAAAAAAAAAAAAANgAAAAAAAAAAAADQAAgAAAAAAAADUL3l5uR4BQJ0kAAAAAAAAAADUf6VlJ9kQVnECAAAAAAAAAED9p/gPAgAAAADUV6Z2AAAAACxKAAAAAIB6SvEfAAAAYFECAAAAAAAAANQjeWX/5ed6EAB1kgAAkENatgIAAAAAAEBtEQAAckjxHwAAAAAAAGqLAACsYNOmTYtTTjmlVvf5hz/8ITp16lSr+wQAAAAAAADqNwEAWMFmz54dN998c5SWltbaPs8880wBAAAAAAAAAGAxAgCwgjVr1iwOPvjgWt1ny5Yta3V/AAAAAABQb6TVZfMsMQtQGQEAWMHat28fd955Z66HAQAAK13qgeUjOQAAAICVRwAAAACAFULxHwAAAGDlEgAAAAAAAAAAgAZAAADqgIULF8YXX3wRQ4cOjYkTJ8a8efNiu+22i3XWWadim5kzZ8aCBQuiWbNm0bx58xyOFgAAAAAAlsKaYAA5IQAAOVZaWhqnnHJK3HXXXTFjxoyYP39+lJSUxN///vfFAgCXXHJJ3HTTTbH//vvHZZddFgUFBTkcNQAAAAAAVGOFFv/Ldp6XvyLvAKDeEgCAHBo7dmwceeSR8eyzz0Z+fn507949pk2bls32/7Ztttkm/vznP8czzzwTU6dOjY4dO+ZgxAAAAAAAAEBdJQAAOfTXv/41nn/++ejUqVNceumlsfXWW8fxxx8f//nPf5bYNgUAWrVqFZ999lm2TIAAAAAAAAAAALAoAQDIkblz58Z1112Xnb/88svj0EMPzc43a9as0u1btGiRBQQefvjhGDx4cPTv33+ljRUAAAAAAACo++pxAKA0VvACMrBCvfzyy1kr/0022SQOOuigGt1m3XXXzQIAw4cPX8GjAwAAAAAAAOqbehwAUPynfhsxYkT2deONN46CgoIa3SZ1AUjmzJmzwsYFAAAAAAAA1E/1OAAA9VvTpk2zr/Pnz6/xbYYOHZp97dSp0woZEwAAAAAA1At5JopCTmjSXucJAECO9O/fv+z9SV689tprUVxcHIWF1b8cZ8yYEY8//njk5+dnXQMAAAAAAABgpVL8r/MEACBHUhG/T58+MXz48LjzzjvjyCOPrHb766+/PqZOnRq9evWKdddddyWNEgAAAAAAAKgvBAAgRwoKCuKEE06IU045JU499dTo3r17bLPNNlFaWppdv3DhwigqKoq5c+fGFVdcERdccEGUlJTE7rvvbgkAAAAAAAAAYAkCAJBDhx12WDz//PPx0EMPxd577x0DBw6MESNGZNfddttt8eijj8Y777wTI0eOzC7bcsst48wzz8zCAwAAAAAAAACLEgCAHEoz+e+9996sA8CVV14ZL7/8cuTl5WWnl156KdsmnU9SQODuu++OZs2a5XLIAAAAAACQW+lj87z8XI+i7rAmO7AIAQDIsfz8/Pjzn/8chx56aDzxxBMxZMiQmDp1atbuv2XLltGvX7/43ve+FzvvvHM0btw418MFAAAAAAAA6igBAKgDUkv/zTbbLDsVFRVlxf8khQMaNWpU0QUAAAAAAAAAoCoCAFDHpIJ/OgEAAAAAAAAsCwEAqEOKi4tj2LBhMXr06Fi4cGF06tQp+vfvH02aNMn10AAAAAAAAIA6TgAAciy1+3/ppZfi1ltvjYcffjimTp262PUtW7aMnXbaKY466qjYddddhQEAAAAAAFjF5f3/ia95LIBvCABADs2bNy9OP/30+Mc//hHTpk3LListLV1sm5kzZ8ZDDz0UTz/9dOy8885x2223ZaEAAAAAAABYZeUpegNURgAAcuiGG26Ia6+9Nmv337dv39h+++2zIn+vXr0iPz8/xo8fHy+88EI89dRTMXTo0HjwwQfjlFNOiSuvvDIaN26c6+EDAAAAAAAAdYgAAOTIggUL4k9/+lMUFxfHXnvtFZdddlmsscYaS2y37777xoQJE+IPf/hDXHXVVXHPPffEaaedlgUGAAAAAAAAAMoJAECOPPPMMzFmzJho1apV3HjjjdGpU6cqt+3cuXP89re/jfvuuy+++uqrePLJJ+PYY49diaMFAAAAAAAA6joBAMiRVMhPdt1112qL/+XatGkT+++/f9b+v/y2AAAAAAAAAOUEACBHunbtmn1NHQBqKoUAFr0tAAAAAACscvLKTvl5uR4FQJ0kAAA5ss0220S7du3i+eefj7lz50azZs2q3X7BggXxn//8J1q0aBGDBg1aSaMEAAAAAAAA6gsBAMiR9u3bxy9+8Yu4+OKL44ILLogLL7wwCgsrf0mWlpbG3XffHe+++27ssccesdZaa63k0QIAAAAAAAB1nQAArGALFy6MmTNnVnrdT3/60xg1alRcffXV2dcf/OAHsf7660eHDh0iLy8vpk+fHp988kk8+eST8c9//jO+973vxTnnnBNNmzZdyUcBAAAAAAAA1HUCALCCjRs3Lpuxnwr6lSkpKYn58+fHHXfcEffcc08UFBREfn5+dl2a+V9cXBxFRUXZ7V966aXYYYcd4oMPPojevXuvxKMAAAAAAAAA6joBAFjBUhF/zpw51W6TivvplAr96VTZ9UkKCqRT6ioAAAAAAACrpryy//JzPQiAOmnlBgBKI/udDKuSNm3axKWXXlqr+0xLBAAAAAAAAAAsauUGABT/WQW1bNkyTjrppFwPAwAAAAAAAGjgLAEAUAvat2gcP99pjdhyzY6xoGRhPP/xhPj7f4fFguKaLddw2vcHxG4bdqv0usffHROXPPJJlJZWffvN1+gQf/jhRtn5C+//IJ77aMKyHsIy0tIFAACW5uN334xnHrs/pk6eGO07dY4ddt8vBmw4sGKZt+qk5eQmjP0qPvlgcAx5/+0YPXJE2WUL4zcXXR2t2rRdYvt7b/tbvPvGi9Xu84hjTo511t9keQ8HlsvsWTPjmUfuiw/feT1b0rB/2XNw74N+FE2aNavR7YuLFsSnH38QQ8peC59++F7MmDE1Ntpsmzjwx8dGfn5B1bcrLo7XX3gqBr/6fEwaNzZat2sfa6yzXmy1/a7RpXuv2jo8qLERnw2JJx++K8Z9NTLatu8QW++4Z2y65XaRX1D187hc+jdh8sTxMfSDt8v+XXg7vhw2JBaW/Ztw6oVXlu2rY7W3nTppQjz1yD0xfMiHUVL2uujQpVtsUna/W2y7c20dGgBQxwgAAHxHG6zWLq77xebRoWWT+Hz8zGiZXxin7N0/frBZz/jF9a/HFxNnL3Uf3ds1i/492sQbwycvcd28oupDBK2bNYpT9xkQa3RtFY0K8qNN2fcrnuI/AABUpahoQfznvn/Gw3fdFO06do6WrdvEiKEfx3tvvBT7H3FM7PaDH0Z+fvVr1n4+9KP489knxPx5c6NJs+ZRXFSUFUJLSoor3b5x48bRtFmLJS5fWFISw4d+GI0aNY4OnbrWyvFBTU0cNyau/uNZMfLzz6J7r95ZofOJh+6K55/8d/z6t5dG7zXWXuo+7rntb/HYvbdnr5nGTZrGvLlzolfvftWG5CeNHxs3XfmH+Pj9t6Jr917RvEXLLIjz9CP3ZiGE/Y/4eS0eJVQv/d5+/omH447r/xIt27SNdu07xldffh7X/PHM2HXfQ+OQnx5fbZglmTR+TPzprBOyYFiTps2y53HRgvlRXFxU5W3Sda89/1TZ/V4WBYWNon3Zv0d5eflZeGDEpx8JAABAAyYAAPAdnb3/utGjffM47obX45VPJ5X90ZYXB22xWpxzwHpx/G5rxSm3v1PjfR125ctLXFZcsrDaDzb22qR7rNuzTTz4xqg4aKvVl+cQAACAWvTeGy/HA/+8PtbdePM48thTsxn7M6dPi9uu+VPc94+/RY/V+sQGA7eudh8tWrWOnfY6IFbru1Z07tYzbr/u0mz2ZlX2OOCILFjwbR+9+2ZcceGpsd6mW0anrt2/87HBsrjzxitjxGefxNEnnhUbbT4oCvILYvBrL8SNl1+Uda345Vl/yIr61Vm97DVw8FH/G/3WXjdGfTE87rzhimq3nz9vXvz1D2fGhDFfxQln/D76lt2uWfMWsWD+/JgxfWo0btykNg8RluqLz4bEfWXP9y49esUvfn1e2e/iHjFn1sy4++ar4ql//yt6r7FObLX9btXuIxX9t9lpz+jYuWt069k77r/9uvjw7dervc0n7w+O2/92afYa+uEvToxOnbtlHWjmzZsbM6ZNqc1DhNypQVclgFWRAADkWGrh9cUXX8Tbb78dL7/8cowdOzZmz65+xvj1118fXbuauVEXbLFmxxi0Tue4/cUR8eg7Yyouv+6Zz+L7A3vE/lusFhfe/2FMn1N1IntRc+ZXPpunKj07NI8zf7Be3PDMsChaWLPlBgAAgBUntVd+/cWns9mZu//gsOjSvWd2eZqBvPfBP4lhF5ySzYAesNHmUVhY9ccyXXusFgcfdXzF902aVN8uPc3wj281A0tjeOW//4mCgoIYtNOey39QsBxS0fPNl/4bm271vdhul30qLt92573KnpePx0fvvBETx4/NAjHV2XqH3SvOp44Y1dZ6Skvj6Ufuye77sJ//MjbdevuKq5o2ax6t27Zb3sOB5fbWK8/FzBnTyp6TJ8bq/b7uepH+TTjkpyfEkA/ejntuuSZ7rlYXTmndtn3sd9jPKr5PoZbqpN//9//j+uz3//+c/rto065DxXXNW7bKugEAAA2XAADk0Pz58+OKK67ICvpffvlllJSULLFNSuaWfmv695w5c1bWEFmKA7boFSULS+O+10ctdnn6kd3x0pfx5yM2jn026RG3v/RFrd9388YFccFBG8TkWfPjrle+jAO2tIYhAADkWmr/P3L4p1lBfs0BGyx2Xbeeq0fbdh2ytujTpkzKZnKuSJMmjI3PP/04a/2fOgnAyvTuWy9nn2lsuNni3S7SZbvvd2h89O4b8eZLz0aPw6oPACyLuXPnxPtvvRrNW7aM9TbZMrts9swZkZefnxVcIRc+fu/NKCxsFBtvud1il7dq3SZ69u4Xwz75IMaMHJF1Aqgtnw/9MD7/7OPYc//Ds+J/WkZm9qwZWXeZNBYAoGETAIAcuvfee+O3v/1tlspde+21s1n9//3vf6N169ax6667xpgxY7LuAJMmTcpCAFtvvXV07949Wrb0R2tdMbBP+5g5tygmzpi3xHXvfDklUnRjszU61DgA8PgZO8Sa3VrHrHlF8eKQiXHNE0Pjs3Gzoqhkydn9267TOes+cOrtb8fYaXO/45EAAAC1IXUAmDxpXPRYvW/WsnlRrVq3jWYtWmaF+dkzp6/wAMCXw4bGtKmTYqPNBq3w+4JvGzViWDRq3Dg6dOqyxHVrr7tRFgT47JP3avU+U1v1SePHZh0zpkwcH9f86ewY+fln2XX91lkvm4G9xtrrRn5B9eutQ21Jn+eNGfVF1g3m2yGUNOO/XfuOX/+7UfZ8rc0AwHtvvRqlC0uj39rrxcN33RyP3fePmDN7VtY5YJsd94zvH3pUtC27bwCgYRIAgBz685//nHUBOOWUU+Kcc86Jjz76KCvyd+vWLf71r39lfySkJQGeffbZOPvssj9aR47MvnburE1XXdC4MD/atGicte1fUEmBfubcssuLSqJH++ZL3deC4oXx6qcT48NR0+PZj8Znrf13Wq9r7LFR9/jTQx/FDf8dFos2gmhbdr9n7rdePPrO6Pj326Nr87AAAIDvYM6cWVG0YEGlBfeCwsKsAJSuX7Bg/gofy1uvPJsVlrbdZe/Iz1fwZOVJHQ5nz5pZ9pxvtEQQJklBmEaNm8SUSRNq9X7T62r27JlRunBhXH/ZBVnQ4Hu7fj+77IUn/h1/OvP4+Mn/nhaDdt4rCyDAijZ37uxs6Yq27Tstcd3XnSlaxcLShTG37N+O2jT2qy/Lfu/nxf23Xx8zp0+NnfY+MNqVjeGTDwbHM4/eG199OTxO/d2VXy8fAwA0OAIAkCNDhgyJDz74IFq1ahUXXnhhNG685Bvu9MdomvF/+OGHR9u2beOAAw6Ic889NwYOHBht2rTJwahZVKOC/Mgv+xnNX7hwiWUaknRZWh6gRZOl/6r97T3vx5wFiy8BsXGf9vHAydvFKfsMiHtfHxlTZi3ILk/3ef6BG0TzpgXx18eHxsKFS943AACQG/Pmft2dq3ElRc8kFT0XlpRkpxU7jjnx9qvPR7sOnWKjzQet0PuCb1u48OvnePr7tarZ9o0aNap4vdTa/ZbdZwq9pOf/VjvsFj/5399UXLfOehvHJeeeFE8+/K/YeItto2Vrn6uw4s2f93XHyEaVfO6XFJa9DtKMj+Ki4lq937mzZ2UdR8eMGhFn/ulvsda6G2WX77zPQXHTlb+P5x5/MJ548M7Y+6Af1+r9AgB1gwAA5MjgwYOzrzvuuOMSxf9UOE5v0vPz8ysuS0sCbLrppvHOO+/E0KFDY/PNN1+m+3vttdey5QWq8s7npWW/Efov0z5XdWnW/sKyn1Xh/wcBvi0FONJ1M+cVLXVf3y7+J++MmBLn3fN+/OGHG8VR2/eLSx/5JLt80DqdYveNu8U1T3waX06c/d0PBAAAqDXNmn/dAWz+3DmVXr9g/rysIFpQsGI/knnq3//KZkP/YJ+DzXRmpSvIT8/xguyzjZLiysMuRUULon3zpXfMWxZpRnW636ZNm8Xmg3Za7LpUAO25et/46svPY+aM6QIArBRNm339HE+/+yuTXgeRPj9KQYBa1KTZ1yG09TbZsqL4X27fHx4db7z4dDzz6H2x14E/8m8E9Vhe+sWf60EA1EkCAJAjU6ZMyb726NGj4rL0R2phYWHWKm/evHnRfJE/hFMyfpdddolXX301K+YvawDgpZdeirPOOqvK65v23jza7SYAsCyKShbGlJnzs3b9jQqXfLPZpnmjbJmAUZMr/+CvJv791ldZAGDj3u0rLjt8UO+I0oiRZfvdZ5Nvnj8Denz94cXAvh3K3v7mxYtDJ8bkmSu+rSgAAPCN5s1bRuMmTWLiuDFLXFdcXJStUZ66AKRtVpRUaHruPw9Gi5atY5OtvrfC7geqkkIuLVu1KXvOF8f8eUv+TTx75oyy5+n8SpfK+C5SO/MmzZpnr4Fvr2+ePnNZvd/a8fmnH8eMaVOiW8/VavW+oTLNyp6PKQQwdfKSy12kgMzsmTOzCUAtWrSs1fvt0Onr19ZqfddcckzNW0Sbdh1iwrjR2fIE5SEFAKDhEACAHOnU6eu1v2aWvdEv16RJk7I3/C2y4v/EiRNj9dVXX+w2c/+/Nd748eOX+f4GDRoUF110UZXXP/55aQxb5r3y+rDJ0b9Hm+jRrnl8Pn7x9do279ch+/rap5OWe//tWn79oeDs+d+0gktdBVo1axRX/3SzSm9z9I5rlJ0i9r/0BQEAAABYyQoKC6Nj524xZtQXMWf2rGi+SFFnxrSpMWfO7GjRqvUKnX08fOhHMWvm9OizZv9szWfIhdXXWDtef/HpSsMwH733ZvZ17XU3rtX7TIXNtu06xPgxX0XRggVLXD971oxstnOTKpbogBWh5+r9YsSwT2LmjGnRqnXbistTUGXq5InZZKAOXbrV6n2ute6GWYv/uXOW7BxZWrow6xCTOtEUFtZu5wEAoG4QAIAc2WCDDbKvw4Z9U3Zv3bp1dOzYMcaOHRsff/zxYgGA+fPnx7333pud79ChwzLf35ZbbpmdqjL+lrdi2Gsjl3m/q7p7yh6zn+7QLw7ZerV4ccg3ae7UPe3I7frE3AUl2Sz+5XXMTmtkX5//+JvQxy9vfqvSjgM/37FfnLRX/zj5H4PjP++OjVk1WHoAAACoXYWNGmezjFMAYOiH72RrjZdLl02bMinWWX+TaLsCC/NDPng7WwN9vU22iKa13GIdamqjzQfF3TddFW+//mK27ni5tOzho/fcnrU832zbnarZw7JL4ZpUbB35+acxdvSXZa/FtSquS4XQoR+9G63bto9W2v+zEq278eYxbMgH8eZL/40d99y/4vKZ06fFqBGfRas27aLHan1q9T433nzbst//LeKDwa9mr7lF2/xPGDs6pkyaEP032LTWlx4AAOoGAQDIkf79+0f37t3jvffeixkzZmTF/65du8bGG28cw4cPjwsuuCDbLoUAZs+eHbfddluMHDkyWrZsGTvvvHOOR0+5976cGk+8Nyb2HdgrBg+fEk+8PzYKC/LiiG37xBpdW8VNzw6PecULK7a/7uebxz6b9oyfXPNqPFm2bbLBam1js34dYvCIKTF26twoLimN9i0bx96b9ogjtusTQ0bPiAfeHFWxj6wbQCUT++cWfb2u4pyy66fNXnKmAwAAsOKlNuNb77B7NvP50Xtvizbt2metmCeOHxv3335d5Oflxd4H/Shr+ZwM+eCd+MPpx8YGA7eOk8//S8V+ShcuLLvNmKxFdFK+fnQq3KTifrp9u46ds5bni0qFnsGvPp8VdTYf5G9Hcqfn6n1ju133iZeefjQevuvm2Gr7XaOgsFG8+twT8cWwT2LTrbePdu2/meBw+/V/iSceuDOO/tVZsf3u+1ZcnmbyT5o4LjufZkuXPcVj7pw5MW70yGypgbTsRnqdJanIucu+B8fg156PR+6+NesG0K3n6jF/3rx4+pF7s4LrNjvskYUAYGUZWPZcf+7xB+PxB+6Izt16Rq/e/bLn8j23XBMLFsyLn//63Gw2fjJqxLA4/9c/je69esdvfn9VtpRLkn63p6J90YKvPxBK/w4kqcNGcdHXE0DadegcTZo2zc6nfwP2OvDIePCff4/brr0kdv3+wWX7ahWjvxwRt1z9x6xbxqE/PWFlPxQAwEoiAAA5kv4o3W233eKWW26Jf//733H44YdnSwCcccYZ8fDDD8frr78eBx98cLYkQFozb/r06VFSUhJ77bVXrLXWWku/A1aai+7/MCv2n3fQBvHLPdfJZv+3b9E43h0xNa5+4tOl3r5zm6bx27Lbphn7qWPAwtKIJoX50aZsHxNnzItTb387uxwAAKgf1tt4i/jx/5wWt//t0rjk3BOjceOm2TrLJSVF8aPjTo211t1oqfuYP39eXH7BKTFzxvTs+zmzvl4+7srfnRZ5ab3oVq3j+NN/Hz1791vsdp99/H589cXw2HSr7aJztx61fmywLA7+yf9koZX7br8+nnz4X1lwZVbZc7p9xy5xyFHHR6PGTZa6jzST/09nfl2oLC5aUPY6Ko4P33k9hv/mw7JL8mKbHfeIw37+q4rtV++7Vvzvb34X1/zp7Ljstydns6AXlpSU3e+06Lf2unHIT9P9Nq7i3qD29eqzZhx53Clx/SW/jb9edHo0a948C3WlIMsPDv9Z1i1jaVKR/7ZrL47hQz7Mvp87++tlKP/6+zMqAmX/U/a8H7DhwIrb7LL3QfHFZ0Pi2cfuizdfejpr9586YaRQzeHH/Dp6r7HOCjhaWIlSY4tFulsA8A0BAMihVOxPIYC+fftWXLbRRhvFk08+Geecc058+OGHMWXKlGwGSa9evWLQoEFxySWXRNP/T/NSNwwbPyv2/tNzceAWq8X6q7XNZvC/9fnkuO/1UVFUsnCxbd8eMbXsD7O8GD99XsVlr3w6KY669tXYcPV20a1t02jWpDBmzC2Ktz+fEv8ePDrmFdWs+D+8bByPvjM6xkydt/SNAQCAFSbNSt5+9x9Ez95rxBsvPBUzpk/LZihvNminrAC5aCvmVm3axsBtdsiWDVhsH/n50Xft9WLunFmV3kezZi2iSbMl1zH/6othsenW34u9Djiydg8KlkObdh3i17+9NF57/skYNuTDrKNF3zX7x/d22zcaN1m8+L9anzVjs7LXQqeui6+F3rRZ81h73Q2rvI+uPXot9n16fa2/6ZZx9iXXx6vPPZl10kidMlJhdIvtdq6YaQ0rS/p9vnnZ7/8evfrEK88+HpMmjCv73d8mNtpsUAzYaLPF/k1o3qJlbLrV97LZ/KlgXy4vPy9WK/s3pbDs35eqpGDYopq3bBUnnPXHGPzKs/Hxe4Nj9qwZZa+vHtnrTPEfABo273ghh9ZYY43s9G3bbrttPPjggzF27NiYO3du9odAu3btomfPnmVv/r1s66Lpc4rixmeHL3W7657+rOy0+GWpZf/TH4zLTt/Ff94Zk50AAIC6YY111stO1UnrPp9w5h+XuLxxk6bxsxPPXub73HGvA7IT1BWp1fgOe+yXnaqz3S57Z6dv69y1R/zy7D8t8/32WK1vHPijY5f5drCi9Fi9bxz0k/+pdpsOnbvGcadduMTlKQxwwHI8n1P4IIXP0gkAWHWoJEId1bZt2+wEAAAAAAAAUBMCAAAAAAAAAADQAAgAwApWWloaRUVFtbrPRo0aLbY+GAAAAAAAAIAAAKxgU6dOjaOPPrrW9pcK/9dee2106dKl1vYJAAAAAAD1R17Zf/m5HgRAnSQAACvY3Llz4+GHH846AdSWSy65pNb2BQAAAAAAADQMAgCwgrVs2TJ++ctf1uo+27RpU6v7AwAAAAAAAOo/AQBYwVKx/i9/+UuuhwEAAAAAAAA0cAIA0AC8//77MWXKlBgwYEB07tw518MBAAAAAIAVKy8v1yOoQzwWwDcEAKABOPPMM+PJJ5+M22+/PQ4++OBcDwcAAACAOq40lIsAABoiAQBoABYuXBjFxcVRWlqa66EAAAAAUA8o/gMANEwCAAAAAAAAAADQAAgAAAAAAAAAAEAD0CADANavAgAAqJ6/mwAAAAAangYZAPAhFgAAQPX83QQAANRbeWV/0eTl53oUAHVSgwwAAAAAAAAAAMCqRgAAAAAAAAAAABoAAQAAAAAAAAAAaAAEAAAAWDalYfFwAAAAAIA6SAAAAIBlo/gPAAAA5FqeDygqeCiARQgAAAAAAKxoOugAAACwEggAQAORJ+0IAABQd/mTDQAAgJVAAABy5IEHHoijjz462rZtG5999lkUFBQs975OPvnkOPTQQ2OLLbaoxRECAAAAAAAA9YkAAOTIhAkTYtq0abHHHnt8p+J/stNOO9XSqAAAAAAAAID6SgAAcqRnz57Z1yZNmuR4JAAAAAAAAEBDIAAAOTJo0KBo3759vPrqqzF//nxBAAAAAAAAqJG8sv/ycz0IgDpJAABypE2bNnHMMcfEn/70p7jmmmvipJNOyvWQAAAAAAAAgHpMAABy6NBDD40333wzzj///Jg8eXLsueee0b1792jWrFnk51edXkydAwoKClbiSAEAAAAAAIC6TgAAcuiggw6KOXPmxMyZM+P3v/99XHvttVlngEaNGkVeXl6lt0mXP/nkk9GrV6+VPFoAAAAAAACgLhMAgBz69NNPs6+pqJ9O06ZNi6lTp1a5fdqmtLQ0ioqKVtYQAQAAAAAAgHpCAABy6NJLL12u23Xo0KGWRwIAAAAAAPVEaqBbRRddgFWdAADk0EknnZTrIQAAAAAAAAANhAAAAAAAAAAAADQAAgAAAAAAAAAA0AAIAEAd8Nlnn8Vzzz0Xw4cPj1mzZsXChQur3f6CCy6Ijh07rqTRAQAAAAAAAPWBAADk0Jw5c+Lss8+OK664Ivu+tLS0Rrc75ZRTBAAAAAAAAFhF5ZX9l5/rQQDUSQIAkEO//e1v4+qrr87Od+rUKQYMGBDt2rWLgoKCam/XokWLlTE8AAAAAAAAoB4RAIAcSa3+L7/88igpKYnvf//7cfPNN0fr1q0jLy9vqbetyTYAAAAAAADAqkUAAHLkiSeeiOLi4lh99dXjlltuiTZt2uR6SAAAAAAAAEA9JgAAOTJhwoTs64477qj4DwAAAAAAAHxnAgCQI+uss072dd68eTkeCQAAAAAA1DeWygWojAAA5Mg222wTPXr0iGeffTaKioqiUaNGuR4SAAAAAADUD3kCAACVEQCAHGncuHGcfvrpceqpp8aFF14YZ5xxRjRr1izXwwIAAAAAAADqKQEAyKGjjjoq5s+fH+eff358/PHHcfzxx8emm24arVq1yvXQAAAAAAAAgHpGAABWsNGjR8dqq6221O3uv//+eOCBB2q0z88++yz69u37XYcGAAAAAAAANCACALASlJaW1up2AAAAAAAAAN8mAAArWNu2bePqq6+u1X127NixVvcHAAAAAAD1Sl5erkdQh3gsgG8IAMAK1qJFizjuuONyPQwAAAAAAACggRMAAAAAAAAAAIAGQAAAAAAAAAAAABoAAQAAAAAAAAAAaAAEAAAAAAAAAKg/8vLS/+V6FHVHaa4HANQlAgAAAAAAAADUL3kCABU8FMAiBAAAAAAAAAAAoAEQAAAAAAAAAACABkAAAAAAAAAAAAAaAAEAAAAAAAAA6pc8C9/n0vz58+ODDz6IMWPGRMuWLWPAgAHRtWvXWr+fzz//PD766KOYN29etGvXLvr37x/du3cv+/H7+UNVBAAAAAAAAACApZo1a1Y89thj8be//S1Gjx5dcXmTJk1ijz32iOOOOy569+79ne5jwYIF8eSTT8b1118fQ4cOXey6VPhP+//jH/8YG2200Xe6H2ioBAAAAAAAAACApbruuuvipptuiuLi4ujZs2esu+66MXny5Bg8eHA8+OCD8cknn8Tll18effv2Xa79p+L/ueeeG48//njMnTs3WrdunRX627Rpk91P6jowYsSIGDt2rAAAVEEAAAAAAAAAAKjW22+/XVH8P+igg+Lss8+Opk2bZte9+OKL8Zvf/CabsX/ttdfGxRdfvMz7LykpiWuuuSYeeOCBbL8HH3xwnHzyydG2bduKbWbPnh2PPvpodOrUqbYOCxocAQAAAAAAAACgSvPmzcsK/Kn4369fvzjttNMqiv/JNttsEz/+8Y/jsssuiyeeeCJ+9KMfxfrrr79M9/Hll1/GPffcE/n5+XHkkUdmxf/U8n9RLVq0yIIBQNUEAACAVU9p2SlvqVsBAAAAAGVS6/2RI0dm548//visNf+iUtH+sMMOy2bwp7DAHXfcEX/4wx+W6T5uv/32mDRpUjbjP+3r28V/oGYEAACAVY+/HQAAAADqsbyy//JzPYhVyvvvv599TYX/rbfeutJtWrVqlXUCeOaZZ+LVV1+NWbNmRcuWLWu0/2nTpsVDDz2Und9+++2je/futTNwWAUJAAAAAAAAAACVWrhwYXz11VfZ+R49ekSTJk2q3HbgwIFZAGDOnDkxceLEGgcAUoeBFBhI9t577ygtLY358+fHggULsvtPHQYaN26c3bfOAFA9AQAAAAAAAACopyZPmRz5xU2X+XZNmzatUYG+pKQkK+Yn7dq1y4rxVenVq1f2taioKCZPnhx9+vSp0ViGDBmSfU3F/Q022CDuvfferCPAZ599FrNnz866C6R97bzzznHIIYdEixYtarRfWBUJAAAAAAAAAEA9tc8+34+C4tnLfLvDDz88zj333KVul2bjz507NzufCu/VBQDat2+ffU2z9stvUxPlAYNU6L/zzjvjL3/5S/Z9+Wz/qVOnxpQpU2Lw4MHxxhtvxLXXXqsTAFRBAAAAAAAAAACoVHk7/qSwsLDawnvqKlB+m9QFoKZmzpyZfU2z/a+44opYe+2144QTTojNN988mjVrlnUCuO2227KuAM8++2xcdtllceKJJ0ZBQcF3ODJomAQAAAAAAAAAqD9S/dns75WqfNZ/KuynU1XSzP9yyzJDv3zbtNxAChGcfvrpsfXWW1dcv+6668ZFF12UdQF44YUX4j//+U8cfPDBFUsOAN8QAAAAVmHpjxV/LAIAAABQfz300IPRsVWTZb5d8+bNa7RdKs43btw4O7+0Wf1z5sxZ4jbLOpbevXvHZptttsQ2qfvAAQccEK+++mqMHz8+Ro8eLQAAlRAAAABWYYr/AAAAANRvnTp2is5tm62w/afZ/61atcrOp1b9i87y/7YJEyZkX1Nr/hYtWtT4Ptq3b19xfquttopGjRpVul2PHj2iZcuWMXXq1BgzZkyN9w+rEgEAAAAAAAAAoFKpmN+5c+fs/OTJk6O4uDiaNKm848Dnn3+efU0F/I4dO9b4Pvr27VtxvnXr1lVul7oKpPEks2fPrvH+YVUiAAAAAAAAAABUKrXz79OnT3Z+1KhRMW/evCpn97/++uvZ1zZt2lSEBmpi/fXXrzifQgZVmT9/fhZASKoLCsCqTAAAAAAAAAAAqNLGG2+cLQWwYMGCuOeee+LYY49dYpsvvvgi3nnnnez8nnvumc3Wr6nU2n+jjTaKd999N1599dWs0F9Zl4GRI0fGrFmzomnTptGrV6/lPyBowAQAAAAAAAAAqEfyslnprDz9+vWLbbbZJl588cW48cYbY7fddqvoCpAUFRXFddddFwsXLsxm/x9xxBFL7ON3v/tdjBgxItZdd9343//93yUK/ClUcPzxx2ddBl544YXYZZddFrs+hQ/+8Y9/ZB0A0n0LAEDlBAAAAAAAAACAKhUWFsZFF10UP/jBD2LKlClx5plnxjnnnBMdOnTIiv+PPfZYPPLII1FQUJAV/zt27LjEPt577714//33o7S0NAsKfNtmm20WW265Zbz00ktZWKBZs2ZZ8CDtc9KkSfHnP/856xCQxnLggQdGp06dVsahQ70jAAAAAAAAAABUq0uXLnHWWWfF2WefHW+//Xb86Ec/ygr9c+fOjfHjx2eF/T322COOPPLI5dp/y5Yts2DBqaeeGh999FH84he/iG7dumWdAiZOnBgzZszIQgGpU8Dhhx9ey0cHDUelAYDSSM1TAAAAAAAAAL629957xzrrrJPN0B86dGhMnjw58vPzs3b8KRBQXfE/hQVSQb99+/ZVLuGQZvzfddddcfnll8fDDz8cM2fOzAr/adb/gAED4pRTTomtt97aEhBQjUoDAF4yAAAAAAAAwLetscYa8fe//z2b9Z8K9I0bN87a8bdq1ara21177bU12n/a32mnnZZ1AEit/xcsWBBt2rSJrl27ZssBANWzBAAAAAAAAAD1ihngi8jBQ5Fm5Pfo0WOF3kfbtm2zE7BsBAAAAAAAAAAAoAEQAAAAAAAAAACABkAAAAAAAAAAAAAaAAEAAAAAAAAAqEtKy055uR4EUB8JAAAAAAAAAFB/5EXDL4439OMDVhgBAAAAAAAAAABoAAQAAAAAAAAAAKABEAAAAAAAAAAAgAZAAAAAAAAAAAAAGgABAAAAAAAAAOqNvHTKy8v1MADqJAEAAAAAAAAAAGgABAAAAAAAAAAAoAEQAAAyrZo1ik6tm+R6GJBzU+cU5XoIANQBTRvlR6OC/FwPA3KuUYG2qhB5eaHDMKu64pLSKFlYmuthAABQAwIAQOZ3h2yYnWBVt9NfX831ECDnSkp8sAc/2WK12KJ3u1wPA3Ju0z5tcj0EyLmiknTy/ohV2yfjZsbEGfNzPQwAVhHpnZf8JSw/AQAAAAAAAACgTlD8h+9GAAAAAAAAAIB6Jc8aPQCVEgAgRzRwAQAAAAAAAKhNAgDkiOI/AAAAAAAAQG0SAAAAAAAAAACABkAAAAAAAAAAAAAaAAEAAAAAAAAA6pG8yMuz1PA3PBbANwQAAAAAAAAAAKABEAAAAACg1qR5J6W5HgQAAADAKkoAAAAAgFqj+A8AAACQOwIAAAAAAAAAANAACAAAAAAAAABQb+TlpVNerocBUCcJAAAAAAAAAABAAyAAAAAAAAAAAAANgAAAAAAAAAAAADQAAgAAAAAAAAAA0AAIAAAAAAAAAABAAyAAAAAAAAAAQP2Sl+sBANRNAgAAAAAAAAAA0AAIAAAAAAAAAABAAyAAAAAAAAAAsFKUht71AKxIAgAAAAAAAAArheI/ACuWAAAAAAAAAAD1Sl6eMAVAZQQAAAAAAAAAAKABEAAAAAAAAAAAgAZAAAAAAAAAAAAAGgABAAAAAAAAAABoAAQAAAAAAAAAqD/yyv7Ly8v1KADqJAEAAAAAAAAA6hHF/0V5NIBFCQAAAAAAAAAAQAMgAAAAAAAAAAAADYAAAAAAAAAAAAA0AAIAAAAAAAAAANAACAAAAAAAAABQr+Tl5eV6CAB1UkUAoLTs5FclAAAAAAAAANRPFQEAxX8AAAAAAAAAqL8sAQAAAAAAAAAADYAAQH1gfQYAAAAAAAAAlkIAoD5Q/AcAAAAAAMiksklenuIJQGUEAGAFO+CAA2rtjUhpaWnsuuuuccwxx9TK/gAAAAAAAICGQwAAVrAHHnggCwCk4n1t6Ny5c63sBwAAAAAAAGhYBABgBdtnn31qtRXRBhtsUGv7AgAAAAAAABqOBh0ASPOtrQBDrj300EO5HgIAAAAAAACwCmjQAQDFfwAAAAAAgAYmLxSBFuWxABbRoAMAAAAAAAAAALCqEACAOqC4uDjeeuuteP7552P8+PHRtm3bOPfcc3M9LAAAAAAAAKAeEQCAHJo+fXr84x//iKuvvjo+/fTT7LLS0tJYe+21FwsADB06NPbZZ59YuHBhvPTSS9G1a9dcDRkA4DsoDX0JAQAAAGDFEQCAHLrgggviqquuyjoAJK1atYoZM2Yssd1aa60VvXr1iueeey4ee+yx+OlPf7qyhwoAUAsU/wEAAABgRRIAgBx58MEH44orroimTZvGySefHCeccEKMHDkytt566yW2zcvLi+233z4LALzxxhvxk5/8JPLz83MwagAAAAAAAKCuEgCAHCgqKoqzzz47a+l/zjnnZAGAwsLCLABQlXXWWSfbZtSoUTFv3rxo3rz5ShwxAAAAAADUFXnZxLnlYnU6oIETAIAc+PLLL2PcuHHRrVu3OPjgg7PC/tJ06NAhm/U/ffr0LEAAAAAAAAAsI8V/oIETAIAcmDFjRpSUlETHjh1rPJO/oKAgSzSmrgEAAAAAAAAA3yYAADnQpEmTrJi/YMGCLAhQExMnTsy2bdGiRRYGAAAAAAAAAFiUAADkQNeuXaNx48YxevTomDRpUnTv3n2pt3n55ZejuLg4evToEU2bNl0JowQAAAAAAADqEwEAyIEOHTrEtttuG/fdd1/8+c9/jhtvvDHrClCZ1PJ/yJAhccstt2TfDxo0KAoLvXQBAAAAAFh1pS67ACxJFRFy5OKLL46XXnop7rzzzqz4f+KJJy6xzfDhw+Puu++OK664IqZPnx7rrbdeHHjggSt/sAAAAAAAAECdJwAAOdK7d++ssH/00UfHzTffnM3wT8sClJaWxhdffBFdunTJlgdI36ckY7du3eKpp56Ktm3b5nroAAAAAAAAQB0kAAA5tP/++0ezZs3isssui1deeSXmz5+fXZ6+Tpw4MTvftGnT2GWXXeKss86Kzp0753K4AAAAAAAAQB0mAAA5VFhYGPvss0/sueee8fHHH8c999wTgwcPzmb+d+zYMTbbbLM48sgjo0+fPpGfn5/r4QIAAAAAAAB1mAAA1AEFBQWx/vrrZycAAAAAAACA5SEAAAAAAAAAQL2Rl055ebkeBkCdJAAAiymNr986rFxFRUXx+eefx5dffhlTp06NBQsWRNOmTaNDhw7Rr1+/WH311Vf6mAAAAAAAAID6RQAAFrPyi/9Dhw6Nk046Kd57772YMWNGzJ8/P0pKSrJlAZo3bx6tW7eObbfdNi655JLo1q3bSh8fAAAAAAAAUD8IAEAO3X777fHLX/4ypk+fnn3fpEmTbNZ/o0aNsiDAtGnTslDAnXfeGW+//Xbceuutsfnmm+d41AAAAAAAAEBdJAAAOfLKK69UFP/bt28fxx9/fOy5557RokWLKCwszJYFSAGAFBK47rrr4tNPP4199903nnvuuVh77bVzPXwAAAAAAMiNvMhFQ1+AekEAAHIgFfdPOOGErMC/1lprxf333x8DBgyodNttttkmjjjiiDj44INj7Nixcf3118fFF18c+fn5K3nUAAAAAAAAQF0mAAA58OWXX2anNNs/FfSrKv6XSyGA1CHgnHPOiQ8//DDmzp2b3RaAVUsKtpfmehAAAAAAANRZAgCQAzNmzIiSkpLo1atXrLnmmjW6zWabbRaNGjWKmTNnRnFx8QoeIQB1keI/AAAAAADVEQCAHGjTpk0UFBQs121bt24dhYVeugB8B1oJAAAAAAA0SKqIkAN9+vTJTp988kmMGzcuunXrttTbvP/++1FUVBQbbLBBNG/efCWMEoAGS/EfAAAAqFPShxV5uR4EQIOwnAEAv4jhu8jPz4+rrroq9tlnnzj22GPj5ptvjgEDBlS5/UsvvRTXXHNN9OjRI37+859HXp7XHwAAAAAADcWyf+btc3KAyi1nAMAvVaip4uLiSi/fdNNNs8L/4YcfHoMGDYpTTz01fvGLX2Qt/suNHz8+Lrroorj++utj7bXXjmeffTa6d+++soYOAAAAAAAA1COWAIAVLBXuq5Pa+s+bNy/OPvvsOO+886JDhw7RtGnTmDVrVkyZMqViuwkTJsT2228fP/zhD+N3v/vdih42AAAAAAAAUM8IAMAKNmLEiBpvm7oFpFn/lUlhgHSaPHlybQ0NAAAAAAAAaEAEAFaK0rBswqrrsssuq9W1iNZff/1a2xcAAAAAAADQcAgArBSK/6uyE088MddDAAAAAACABiSvVifeATQkAgAAAAAAAAAA0AAIAAAAAAAAAABAAyAAAHXEwoULY+7cuVFUVBSlpaVVbtekSZNo3rz5ShwZAAAAAAAAUB8IAECOTZkyJW666aZ49tlnY+rUqUsNABxwwAFxxhlnrMQRAgAAAAAAAPWBAADk0JNPPhk//vGPY8KECdUW/Re12WabreBRAQAAAAAAAPWRAADkyCeffBJHHXVUVvzfeuutY999943TTz89CwJcddVVMW3atPjggw/i8ccfz86nwn8KC6y33nq5HjoAAMCqK2W383I9CACAVVteXjp5U/YNjwXwDQEAyIFU5D/ttNNi7Nixscsuu8Rjjz0WBQUFWQAgOe644yq2HTFiRBx++OHx1ltvxV577ZWFBQAAAMgRn60CAABQhwkAQA6kWf9vvvlmtGzZMi666KKs+F+VPn36ZEsF7LfffnHBBRfExhtvHPvss89KHC0AAAAAAABQHwgAQA6kAMCCBQuie/fu2alcfn5+lJSUZNc1bty44vIUFEhdAJ577rm47777Ys8996w2NAAAAAAAAACselZaAMASefCNVOBfuHBhNG3adLFCfvPmzWPmzJkxadKkxYIBSe/evaOwsDC++uqrmDt3bhYKAAAAAACAVVFenqoTQGVWWgDAr2H4RrNmzbLZ/kVFRVkQoFwq+g8dOjTef//9JQIAadtk9uzZUVxcvFLHCwAAAAAAANR9lgCAHOjWrVs2+3/KlCnZbP5y2267bQwZMiRuvPHG2HHHHRdbBuDZZ5/NOge0adMmGjVqlIthA1SrW5smccTAnrHZ6m2jVdPCmDmvOF7/clrc+dboGDN93jLvr2PLxvGHfdaJvh1bxIjJc+Jnd7y32PVtmzWKX+/YN1Zr3yzalZ1v1qgg5iwoiS+nzI1nhk6Mp4ZOirlFJbV1eFAjjQryYoe1Osa+G3SNPh2aR35eZM/Jxz+eEI99NCHmFy9c+k6+Je3vrN3XjMKynd3y2qjsVJ1d1ukUZ+62ZqSJEH997vO4791xy3s4sNwmTRgfD9x5S7z56gsxZfKkaNmyVay74aax/w9/Ev3W7r/U28+eNTP+8+C/YshH78eoLz+PCWPHRGlpaVx/16PRuWu3Sm9z9603xLChH5VtPyImjhsThWXvmX9zwSWxyeZb1/bhAVBDaTLD4/95NO79110x7LPPskkQffv1jX2+v1/st/+B0aRp0xrt59OhQ+LmG2+IwW+9GVOnTomOnTrFVlsPih//5Kexeu8+i2370ovPx1NPPB6fDx8en48YHnNmz45NNh0YN95y+4o4RKiRaZMmxH8fvCM+euvlmDl1cjRt0TL6rbtR7PSDw6Nnv7WXevsvhn4Yb/z3sRg1fEhMHj8mFsyfFy1at4nV1ugf2+y2X6yz8RZL3ObJe26JUcOGxPivvogpE8dFYWGj+Mlpv4t1NlpyWwCgYREAgBxo165dbLDBBvHUU0/FqFGjom/fvtnlhx12WNx6663xyCOPxPnnnx+nnnpqlJSUxDXXXBOXX3559qHnhhtumC0VAFCXtGveKK44YL1o3bRRPPD+2Hj3q+mxxert4vsbdI3+XVrG/9z9fiwoKV2mfe62Tqfo1LJxlde3bFIYncuuf/bTSVmBdeb84ujXsUUcuFG3OP57faJJo/y4552x3/XQYJkMXK1tnLxTv5hd9nz86/Ofl30tiR9t0StO2L5PNCt7Tt751phYlldCt9ZNsqDLguKFUdi4YKnbNy7Mjx8O7B7T5xZF2+YCg+RGKt5ffP5vYtiQj2K7XfaMQTvsEh+993bcf8ctMWzox3HFTf+Kps2aVbuPWTNnxNOPPRTjx46Ort17RoeOnWPSxPHV3uaxB+6O6dOmROeuPaJlq9Yxb97carcHYMV7+eUX46ILfxstW7SM004/M1q0bBk3/O2auPhPv495c+fGj3/6s6W2b54zZ3acd/aZMXToJ3HIDw+P731vh3jyif/Evx96IL4YMSL+cuVV0aZN24rtX3rxhXi47LrmzVvEeuuvH2+8/toKPkqo3tzZs+LWS8/NivebbrdrbLT1DjH84/fivw/8M74aPjROveyWaNy0+vdGKTjw+jOPxICB28R2ex8cbdp3jCHvvB7PPXxXDPvwnTj+wquiR581F7vNS/+5P2ZNnxrtO3eL5i1aZaEBAGDVIAAAOXLsscfGK6+8Ev/617/K/nj9XnbZxhtvHPvvv3/cfffd8cc//jE7lUvF//XWWy+7nbWNgLok/Uraa93O0aFF4/jHG6PitjdGx8Ky31mvfzEtps4piiM37xmHbtqj7PKvarzPtbu0iP036hbXvTwyTtmpX6XbjJ42N469+4PFLhs8cno8M3RS/O3Q9eOQTXrE/e+Ni5KFyxY8gOXVonFB/HL7PjFjblEcf8+HMX7G/Ozy4ZPmxFUHrx97rtclHvloQtn1NV/K58CNu8eCkoXxxIcT47CBPardNnUb+PnWq0VhQX7c+vqo+NUOfb/T8cDyGvzaS/H5p0Ni2512j+NOOjMaN2kSm24xKHr06h3XXnZR3PDXP8fxp55b7XvaNu3ax4lnXRidu3aPdu07xp9/+5uY9Hz1AYBTzvtj2X2sHu07dorfn3lSvPf267V9aAAsg1kpEPaHi7JOhjffdkd07/71e5m11l4nfnLkD+OB+++NHxxwULRt27ba/dz5z9uz4v8vTzw5fnzU0dm/HwM33yIKCgvjgfvuiZdeeD722mffiu33L9tnOvXu0yeKFhTFoK0GrsjDhKX6ePArMXrEp7HJtrvEgb84ORo1bhL9N9kqOnXvFfded2ncf9MVcchxv6n2vdHaG20em+2wR3TuvlrFZWttMDDWWG/juPXS8+Ifl58fp112a+QXfBMa/tGvf1t2H6tlYYEb/3B6fPbB4BV5mABAHSIAADmy1157xQcffLBYm//WrVvHtddeG2ussUZcccUVMXPmzIrrfvjDH8Yll1ySLR8AUJc0ys+PTXq1zc4/NWRSVvwv98LwybH3+l1iqz7t44H3xmWz9Jcmzew/cfu+MXLq3Hhh2OQqAwBVlfUnz14Qo6fNi/W7t46mhfkxe4FlAFg5NuvdLrq1aRp3vDm6ovifpOfjQ++Pix9v2Ss2KHtevjR8So32lzpa7LFu5/jto0OjS+smS91+i7L7/8GGXeOvz41YrqUGoLa8/vJzUVS0IL5/0OFZ8b/cZltvF4/cd0e8/uJ/47Cjjo0OnbpUuY+mTZvFOutuuEz3u/7GCjwAdcnLL70YY8aMjqOO/nlF8T9ZbbXV46CDD40brrs23hn8Vuyw085V7iP9e3LLzX+P7j16xpE/PqqiQFpYWBi/PPHXWReAu++6Y7EAQAoYVNx+QdEKODJYNh+98VIUFxXF9/Y6KCv+l1tv4KB48dF748PXX4jdDzk62nboVOU+1lh340ovTyGArj1Xj1HDh8bM6VOzYn/FbdbbpPYOAgCoVwQAIEcaNWoUq6+++hKXp2T8BRdcECeffHIMGzYsWy8vLRHQuXPnHIwSYOkKC/JitXbNYsrsBTFm+uItBSfOWhAz5hVHu+aF2TIBNQkA7LRWh+jRplmc8+iQZSrep88CU3hgQJeWsVbnlvHllDmK/6xUG3RvlXWc+HTCrCWue/azSfGTLXtlRfqaBADaNWsUF31/nXjzy2nx9qjpWRCgOs0bF8Qhm3aPYRNnx9NDJ8W2/dov93HAd/Xpxx9Gq9Ztok+/tRa7PLViTu38R4/8MsZ8NbLaAAAA9d/bgwdHQUFh9B+w7hLX7brbHnH9366Jl156vtoAwPBhw2PWzJmx2WZblO1r8eWQWrVqHWutvXZ89OEHMXv27GjRokWtHwPUhi+HfRLNW7WJ7n3WWOzyJs2aR4cu3WPimFExaeyoagMAVUn5+6IFC7JwzLdfI7BK0CgXoFICAFBHpSDApptumuthACxV44K8aNOsMCtSfntW/twFJTFrXnF0btk4a4++NO2bN4ojNu8Z9747Jt4fPaNG99+vY/M4acd+2d98TRvll91Xk2z2899e/HLZDwaWUwqgpNn/qV1/Cr1826gp86K4pDT6lj1flya18t9vo67RpVWTOP+xoVFcg2Us9l6vS/Tu0DyOu/P9mCP4Qg6l2W2TJ46PNddZN/Ly8xe7rrBRo2jTtn2UlJTEtCmTczRCAFaGtIzhmNFfRZMmjaNNm7ZLXN+7T99sFv9nn35a7X7Gjhmdfe3cpfLQWI8ePeOD99+Pr0aNjLXX6f+dxw21rbi4KKZPnhCrrdm/7G+GJd8btWzTLhaWvTeaOW3qcu1/xJD3sgBB77XXixat29bCiAGAhqDBBQDSx6NCXwCw8qRZ9/l5eZUWPdO/y3OLSqIwPz9bl7w6qV3/b3ZZI6bOLop/fzi+yhb/lUn/9qcCbLqfdH/XvvhFvDN6+jIdB3wXBWVPwMZlz/HUAaCoZMn2+2lpjPnFJdG66dLffndv2yz2WrdL/OONUfHJuCW7CXzbmp1axNFb94o73xoTYxdZegByYfbsWbFw4cJo0bJVpdc3ado0KwrNn++5CtCQFRcXx/wF87MOAIsufVguzVRu0qRpzJhe/Xv22XNmZ1+bNW1W6fXNmn8963/WrKW/Z4JcmPf/742aNm9Z6fWNm3z93mjBgmV/bzRp3Oi4/fILs04CBx/3m4olMgAAGlwAwNscAKifBvVrHxv2aBOX/Xd4TJtT87U6R0yeG6c88HHFEgBbrN42jt+uT3Rv0zT++dboFThiqH1NCvPjjF3XiDEz5sU/3vhqqdun1v9HbdUrppS9Zh79cPxKGCHUlL/MAKiJpcR+y69e6j8ryxIfhpWv+uL8sj9/582dE/f//S8xZ+b02PPwY6JLj9WWf3AAQIPT4AIAUNdsscUWtbq//fbbL04//fRlvt0111wT559/fpXX77HHHnHLLbd8h5EBq6pZ84uzdQdbN1nybUX6iKNZo4IoWbgwiiuZFV2uID8vDt20RwydMCteGTElWjRZfLmA/Ky4n/bzdUeBRaWZ1eWXpdbnqXvAOl1aZuutv1y2ry8mz/3uBwlLUVL69cz/1AmgUSXdLlKXjCaFBTFzftXPx/R6Sa381y57/l7y9PAsDFD+skrnk7TkRnotzC/++v427Nk6Bq7eNi59Znj2Omj5/6+dJo3+f/uy26XL5hUtrNFSAvBdtWjRMvLz82PO7JmVXj9/3rzsA/DGTZqs5JEBsDKl9v5p5n9a9qWoaMES16eW56kbTKvWbardT/MWX8/wnzev8vdQc+fOyb62aFn57GrItaZl743SskhzZ1fepWLB/HnZ0gCVdcqoyrw5s+Nf1/45PvtgcGy2416x/T6HfN0SDwDg/wkAwAr25ptv1ur+Ntlkk+W6XWo3llrwVSX9UQ6wPBaUlMa0uUXZ2ubpI4dFS4zNGhdks/LnFC2M2dWsS96+eaPo06F5fDVtbly0z5Jrd3Zt3TS7fMSk2XH5cyOWOqaPxs6M3Qd0joGrtRUAYKVIIZix0+fFZqu3rbTNf892TaOwIC8+nzSnyn3k5+fFut1bZYGX/TbqGnuv17niuvbNv/5AcOd1OsUGPVrHg++Pi6eHTIote7fLQgf7rNe17PTN2rhty15TyffX7xrb9G2fdRN4/YtptXS0ULW0lm2HTp1j9KiRUVr2/jN94F2uuKgopk+bmrV9btuufQ5HCcCKlsJePXr0jNdefaXsd/+Sbf6/+GJEtjb6mmutVe1+unXrnn2dMH5CpdeP/uqrLHjWq5fZz9RNhYWNom37TjFx7KiyvxkWZsX+cuk1MHv6tMgve2/Usk3N3hvNnzsnHrjpinj/tedimz32j+//6H+z28OqKc/SFwBVEACAFezEE0+s1f1ttdVWy3W7448/PjsB1LY0qzgV7tfv3jq6tWkaY6bPq7iuU8vGWTF06tyimFpNW/9UPJ04a0E2Q7pLqyU/vEgdArq0apIFDWqivPhZYsYzK9EHY2fGfht1izU6t4jnPpu82HXbr9EhC8e88cXUavcxc15xTJ5dVFHwL9f0/2f0p0BN+oCjReOv38bPnl+Stf/v0nrx2dRN/79jQKuy119hQX7Z7X0oyMqzxjrrxqvPPxNffj4seq/xTWEnzdIcP+araNS4cXTvqVAD0NBttPEm8a+77oghQz6OnXfdbbHrnnryiew9zTaDtqt2H/3W6BfNmzePTz8dmnUNWLTQOXv2rPh06JDoP2BA1oEG6qpea6wT77/2fIz98vPo3nuNistTMX/yhDFR2KhxdOrWc6n7SYGBJ++5Jd56/onov8mWsdfhx0ZBoY/3WYWp/QNUyTsEWMEuu+yyXA+BVVoqN3k3zIqV2pC/PWp6FgDYee2Ocfubo7O2/EmaedyueaN4/JMJMXP+111IurdpGgds1C2+mDwna9efTJq9IA69eXCl+3/mhK1i1NS58bM73lvs8jU7tYjPy/bx7SJ/r3bNYo8BnbNxDR655GwjWFHe+GJaTJg5P3ZZu1M8/P64svNft7vt1qZJ/GDDrlmHgPdGf9MWfds12sfGPdvEM0MnZV0r0nP5L//9PDt92z7rd4mTd+oX/3p7TNzy2qiKy69/+cvs9G279e8UZ+y2Ztz86si4791xK+BooWpbbLN9vPnKC/HwvXfEsb8+Ixo3/jqgMvi1l2LUl5/HNtvvEh06fd2xYsqkifHQv27POgLsud8h0aRp01wOHYBaNGjQdtGla9d49JGH48CDDo2u3bpll3/11aj41913RI+ePWPTTTer2P6/Tz8Zb775Ruyx516xwYYbZ5elf0N+9JOj47prr4o7/3l7HHbkj7LgQOpweNWVl2dfDzr4sJwcH9TUepsNio/eeiVeePSeOODnJ2dhyOTjwa/G+K++iI223jHadOiUXTZ9yqR4/t93Rau27WPQ7gdEo/9fNiktFfD4XTfGC4/cE5tuu2sc8ItfW1IJAKiSAADUc3PmzIlRo0ZFk7I3/b179871cKhzFP9Z8VKt/5EPx8d+G3aNwwb2zNYof3vUjNiqb7vYf8NuWXeAf771VcX2HVs0jh9s0DVe/2JqRQBgeRw7aPVsNvQTn0yI4f/fVj0VU/ffqFs0a5Qfd741OkZO1f6flWfW/OK48rkRcd6ea8W1h24Q1774RdllJXH0VqtFu+aN46ZXR8aMRbpYbNC9dfZ8Tc/fFACAhmLgVtvG6n3WiOeeejTyC/Jjux13jw/feyv+ddvfo2PnLnHsr8+saNU5c8a0ePzhe6Lnan1il733qwgApFmeb732UkyZPDH7fsKY0dnXF57+T7Rs3frr+9ly22x/5d4b/EaMHT3y6+3Hj4mS4pIsdDBh3Jjssu/tvGc0a9585TwIAESrst/Xp/3mrDj9tF/HkYcdFCeefFq0atUyrrnqrzF1ypQ49LAjok3bthXbv/324LjrjttjrbXXrggAJEf86Cfx9FNPxKWX/DHGjR8b2++4Yzz+6KPx4AP3xYB114vv7bDDYvebAgavvfJydn7BgvnZ10kTJ8a9/7orO9+zV6/YfIutsqUDYGUYMHCb6Fb2XifN3E/LI208aOcY9uE78fS9t0bbjp3jgF+cXPHeaPbM6fHyEw9Fl56rxxY77VMRAHj9v4/GC4/8K9p17hqbbr9bFhz4tq69ekfjJs0qvv/0/bdi0tiv30NNmTguW/7zk8GvxpTxXweEN91ul2jSzHsjAGiIBACgnnvttddil112iY033jjeeuutXA8HWEWlFuQn3PNhHLl5z9h9QJc4cOPuMXN+STw1ZGLc/uZXsaC49lvxvzR8Sgzq1z4O2aRH1uY8rYM+Y35RDB0/M14YNiWeHjqp1u8TliYFWy7/7+exz/pdsxn7+WXPy9TBIoUBUlcAi1KwKmjZqnX85oKL495/3hRvv/5yPPfEo9G8RYvYYtD2ccBhR0XTGnzQXFxSHA/e/Y/4+P23F7v89r9fVXH+3D9ftVgA4OlHH4gX//vEYts/ev9dFec33mwbAQCAlWzQdt+L0886J+6/919x0QXnxcKFpdnkhRNPPjUOPuSHNVq7uUXZvyHn/+4PcdMN18V/Hn0k7vznP6JDh46x+x57xVFH/zzatm232PaffPxRXHThbxe7bOTILysu22XX3WLgZlsIALDSNG/ZKn5y6kXx9P3/iCFvvxZvPfd4NG3eMtbbfNvYaf8joknTZkvdx6jPhpS9fhbG5HFj4rrzT6p0mxP/eH2stmb/iu9ff+aReOelZxbb5sXH7qs4v84mWwgAAEADJQAADURpqZICkFtfTZsXf3pqeBTkp94TeVFa9r+ShVGxHEC5D8bOiD2ueX2Jy6uSti2tpGz64Pvj4uEPx0d+9plhXtbvIm2XVgT49rIAsLIUlZTGox9NiMc/mZgV/9PzMj3Xiyt5Tv7tpS/jhpdHVnrdtz364YR44uOJUVLD181TQybFs59OrvH2UNs6d+0ex/36zGwWfvY+tez1UFD2D0R+fsFi263WZ424/eHnsgJQYaNGFZenls8XXHpttf9WFH5rzdtfnXlhnHD6+VVu32iR/QOwcjRu3Dj22/+g+P6++2fFyyQV3r/9Ozw58denxi9/9etK1zQfMGDd+POll0dJSXH270peXn7ZvysFlRbxd9p513j9rfeWuLxc6k5T2f3DitS+c9c46JiTsy5HX3+Gl1f2XFzyOdxttb5x0a2PZu+dCgu/ee9yyP/+Jg4+7tRq76OgcPH3OoedcHb88Pgza7w9ANBweLcLANSaVKhZWJLOVV2wSZ91LChZWON9VrVtuodU6C+p+A7qjq+fm9U/L2uyTbn02lpQUvPn+bJuDytCKs4UNqp+dmUq/Jevg/tthctYsFfMAaibspBXDX5HZ9tUs10qlObnV/5vxre3szY6dVEWXClc+nujwkZLPs8LCspeGwWV3KAalYVpoKGpSSeZVYWHAliUdwEAAAAAAAAA0AAIAAAAAAAAAABAAyAAAAAAAAAAAAANgAAAAAAAAAAAADQAAgAAAAAAAADUG3nplJeX62EA1EkCAAAAAAAAAADQAAgAAAAAQB2U5jOV5noQAAAAQL0iAAAAAAB1kOI/AAAAsKwEAAAAAAAAAACgARAAgHouPz8/GjVqlJ0AAAAAAGCVkJfrAQDUTQIAUM8NGDAgbrvttmjbtu0y3S61E/X+CAAAAAAAABqOagMACoSwcixcuDCKioritddei48++iimT58eHTt2jE022SQ22GCDKCwsjLy8yl+NnTt3joMPPniZ79NrGwAAAAAAABqWagMACoSwYqWi/1NPPRU33nhjPP300zFr1qwltunatWvsscceceyxx8amm25aZRAAAADIsfRWvTTXgwAAAABWZZYAgBy64YYb4rTTTos5c+ZUuc24cePipptuioceeigee+yx2GyzzVbiCAEAgBqrJ8V/OQUAAABouAQAWOXlaqmLJ598Mk455ZSYP39+DBgwIGvjv8MOO8Rqq60WzZo1i5kzZ8awYcOy7e68884YP3587LzzzvHCCy/EhhtumIMRAwAADYHiPwCsSiz0SwPlaQ1QJQEAVnm5eJ+wYMGCOOmkk7Li/8YbbxyPPPJIdOnSZbH2/p07d45+/fplRf8TTjghdtxxx/jiiy/i73//e1xxxRWRn5+fg5EDAAAAAPWHKikNVZ7lcgGqIADAqqMOhV1HjBiRtfZv0aJFXHfdddG1a9cqty0oKIjevXtnIYBTTz01Pvnkk2zJgJYtW67EEQMAALCy1KE/XwEAAKhnBABYddShT09SAX/hwoXRq1ev6N69e41us8EGG0SjRo1i7ty5UVJSsoJHCAAAQK7UoT9fAQAAqGcEACAH2rdvH4WFhVkhv7S0ZitwFhcXZ1/btm2bBQEAAAAAAAAAFiUAADnQo0ePbEb/q6++GsOGDatRF4A333wzioqKYpNNNolmzZqthFECAAAAAAAA9YkAAORAmv1/zTXXxA477BBHH310PPDAA9G/f/8oKChYYtt58+bFu+++G1dddVX06dMnjjvuuMjL0xASAAAAYJWSmkj6SAiggs/JASonAAA5kp+fH+eee26cd955sccee8Ruu+0WO++8c/Tt2zeaN28eM2bMiE8++SSefPLJePzxx7PLzz///Jg+fXp2+rYUIAAAAACggVLnAgCgBgQAIEd23HHHGDNmTMX3N910U9x8881LbFdaWpp9ff/992O//fardF8p6VhcXLxiBgqwAqXPr0pzPQgAAAAAAGggBAAgh8qL+1V9X9PrAOorv9kAAAAAAKD2CABAjtx///0xf/78XA8DAAAAAAAAaCAEACBHNttss1wPAQAAAAAA6qW0NC4ASxIAAAAAAAAAoN5Q+geomgAA1DHFxcWxYMGCaNq0aeTn5+d6OAAAAAAAAEA9IQAAdcDEiRPj2muvjUcffTRGjhwZCxcujIKCgujfv38cdNBBccwxx2hnBAAAAAAAAFRLAAByaNy4cXHFFVfE1VdfHbNnz47S0tIlrn/uuefi7LPPjnPPPTeOO+64aNSoUY5GCwA1k/41E1sDAAAAAFj5BAAgh4466qh4+umnsxn/yQYbbBDrrrtutGrVKiZPnhzvvPNOfP755zF16tT4zW9+E++//378/e9/z/GoAaB6iv8AAAAAALkhAAA58tvf/jaeeOKJaNy4cRx22GFx5plnxtprr73YNikY8PLLL8cFF1wQzz//fNx8882x2267ZcsCAAAAAADAKikvLJsLUAUBAMiBSZMmxY033pidP+WUU7IW/02bNl1iu/z8/Nh2223jgQceiCOOOCIefvjhuP/++2PffffNggMAAKssa00AAAAAwBIEACAHxo4dG7Nnz46uXbvG0UcfXWnxf1EtW7aMQw45JB577LEYPXp0zJs3TwAAAFi1Kf4DAAAAwBIEACAHylsTdezYMZo3b16j23Tv3j0KCgq0NQIAAAAAAAAqJQAAOdC5c+do1qxZzJgxI5vNXxOTJ0+OhQsXRpcuXaJJkyYreIQAAAAAAABAfSMAADmQAgCHHXZYXH755XHPPffEKaecUu32paWl8eCDD0ZxcXHsvffeAgAAAAAAAKzaNMsFqFTtBgBKwy9cqKGLL744Bg8eHGeccUbW1v/oo4+Oli1bRmHhNy/LoqKimD59epx33nlx9913xyGHHBI/+tGPcjhqAAAAAAAAoK6q3QCA4j8s4YILLqjyuv79+8c777yThQBuv/322HDDDaNr167RtGnTmDVrVowePTrefPPN+Pzzz6Nv377Rr1+/ePTRR2OvvfZaiUcAAAAAAAAA1AeWAIAV7Le//W2116fZ/8l7772XnSq7Pp1GjBgRF110URxzzDECAOSGLi8AAAAAAAB1mgAArGBpVn9t6tGjR63uD2pM8R8AAAAAAKBOEwCAFez111+v1f3l5+fX6v4AAAAAAKB+yavorgvA4gQAYAVr3LhxrocAAAAAAAAArAIEAAAAAAAAAACgARAAgBwZNmxYfPjhh9GmTZvYYYcdFrtu7ty5cfXVV8cNN9wQo0aNig4dOsQRRxwRp556arRv3z5HIwYAAAAAAADqMgEAyJGzzz47HnjggTjttNOWCAD87W9/y64vKiqK0tLSGD16dFxyySXx+uuvx5NPPhmFhV66AAAAAAAAwOJUESEHZs+eHS+++GLk5+fH/vvvv9h1EyZMiHPPPTcr/m+77bZxwAEHxIgRI+KWW26J559/Pu66666sGwAAAAAAAADAogQAIAfGjh0b8+fPj27dukXHjh0Xu+7BBx/MAgL9+/ePhx56KFsiIEmz/i+99NJ45pln4tBDD9UFAAAAAADgOyktO+XlehAsh7y8dPKzA6iMCiLkwMyZM6OkpCRatmwZjRs3rrh84cKF2Sz/ZJ999qko/ieDBg2KK6+8MkaOHBnz5s3LbgsAAAAAwPJSQAag4REAgBxIhf7S0tLsfPnXZPr06fH5559HkyZNYuDAgYvdpl27dtmSAXPmzIni4uKVOl4AAAAAAACg7hMAgBxIs/cLCgpiypQpWUG/3Lhx4+LLL7/Mru/Tp89it1mwYEEWFki309oIAAAAAAAA+DYBAMiBnj17Zu39R40aFXfddVeceeaZ2eV33HFHjB8/PtZcc83stKixY8dmywa0bt06GjVqlIthAwAAAAAAAHWYAADkQIsWLeLoo4+Oc889N84555y4//77s8vfeeed7OsPf/jDrNC/qI8//jhr/d+jR49o2rTpSh8zAAAAAADUFRrlAlROAABy5JRTTokPP/ww7rvvvnj77bezy/Lz82O33XaLk08+ebFtU+v/p556Kmv9v+mmm2bbAQAAAAAAACxKAABypEmTJnH77bfHIYccki0DMG/evNhnn33iiCOOyK5b1ODBg2PSpEmx2mqrxS677JKjEQMAAAAAAAB1mQAA5FBBQUH84Ac/yE7VGThwYIwYMWLlDAoAAAAAAAColwQAAAAAAAAAAKpTWnbKy/UgYOkEAAAAAAAAAKhX8vJUYit4LFYODzP1hAAAAAAAAAAAADQAAgAAAAAAAABAjcycOTPeeuuteOedd2LixInRrFmzWGuttWLzzTePvn37Lvd+P/nkkxg5cuRSt0v31adPn+W+H2joBAAAAAAAAACApRoxYkScccYZWbF+3rx5FZfn5+dH586d47jjjotDDjlkuZZouPfee+P2229f6nannHJK/PznP1/m/cOqQgAAAAAAAAAAqNb8+fPjwgsvzGb+t2nTJvbYY49Yf/31Y/LkyfHkk0/G8OHD4+KLL44uXbrEDjvssNz306hRoxg4cGCV1/fo0WO59w2rAgEAAAAAAAAA6pXlmGDOd3TLLbfEK6+8kp0/99xzswBAQUFB9v0BBxwQv/rVr+KDDz6IK6+8Mrbffvvl6gKQtGrVKrsvYPkIAAAAAAAAAABVSrP8U2G/tLQ0dtppp9h7770Xuz7Nyv+f//mfbAmAjz/+OB599NEltgFWDgEAAAAAAAAAoEqDBw+O4uLibFZ/KvRXZtCgQdGrV68YNWpU3H333bHXXnstdxcAYPkJAAAAAAAAAABV+uSTT7KvXbp0id69e1e6TePGjWPrrbfOiv/Dhw/PugZ07NhxJY4SSAQAAAAAAIDllGb1leZ6EADAClRSUhLjxo3LzqcAQGFh1eXFAQMGZF8XLFgQkyZNWq4AQLrtXXfdFaNHj86WHGjTpk2st956MXDgwGjUqNHyHQSsQgQAAAAAAIDlpPgPALn2yccfR5um+ct8uw4dOkSPHj2Wut3ChQtjypQp2fm2bdtGfn7V99WzZ8/sa1ouYOrUqcs8pmTWrFlx3nnnLXF56jxw6aWXxrrrrmtpAaiGAAAAAAAAAAD1Rir+KgB/42c/+1nE/JnLfLvDDz88zj333KVul2bhz58/PzvfpEmTah/7li1bVtwmzeRfVqnDwAYbbJAFCdK+Zs6cGZ999lm8+eab8cUXX8QxxxwTv/vd72KHHXZY5n3DqkIAAAAAAAAAAKhUKuYXFRVl51P7/+oCACkgkKSuAeW3qamDDjooTjrppGjevHlFyCPdd9rXc889FyeffHK2rEDaJn2fuhEASxIAAAAAAAAAgHpqt912iyax7LPt119//RptlwrxjRo1ys6n1v6pKF+V8k4Bi96mptZZZ51K77ugoCB22mmnOPvss+Occ86JuXPnxk033RS//vWvl2n/sKoQAAAAAAAAAIB66qyzzooOLRsv8+3y8/NrtF0qwpfP7E9t/asLAMyePbti340bL/uYqrP//vvHrbfeGp9++mm89dZbMW/evGjatGmt3gc0BAIAAAAAAAAAUE8VFBZmrflXlFTMb9euXXZ++vTpWUv+qnz11VfZ1zSeNm3a1Po4UpeAFABIQYM5c+YIAEAlBAAAAAAAAACoV6pZhn6Vs6IfitSCv2vXrtn5cePGZcsAVOWTTz7Jvqb2/506dVohY0lSF4LqOhHAqkwAAAAAAAAAAKhSmnmfjB8/PpvlX/79ooqKiuKVV17Jzvfu3Ts6duxY6+P48ssvs6/NmjUz+x+qIAAAAAAAAAAAVGnTTTfN2vqn2f/XXHNNXHnllUtsk4r/I0eOzM4ffPDBkVfLbRrefvvt+OCDD/6PvbsArLrq/zj+ueve2AaMbgQkDaQkBOzEQMLCQOwWsQt9LBRELOCvmCgqj4qESAg+KiXSnYMxYM06/jsHmcCCAXe729375fP737tf3XP5L373dz7ne+zzZs2aKSAgwKnnB9wFAQAAAAAAAAAAAAAAxTLl/G+77TaNGzdOM2bM0MyZM9WnTx95eHjY7aYygAkGmLL8pnP+sssuK3SOq6++Wn///be6du2qsWPH2lH8h6xatcpOG1C3bt1CHfvmnGb7Qw89ZKsMmOMGDhzo9IAB4C4IAAAAAAAAAAAAAAAokQkALFmyRH/88YeeeeYZO+K/devWiouLs6GA1atXKzAwUPfcc09BMKC0FixYoAkTJqh58+Zq1aqVnUIgODhY8fHxWr58uRYtWqSYmBj5+vrqkUcesfsAKBoBAAAAAAAAAAAAAAAlMiPvn3rqKT3wwAPasmWLPv/884JtZjR+WFiYbr/9dlsZ4ETOnZmZaTv6//zzz0LbzfQDNWrUsOfv37//Sb0PwN0RAAAAAAAAAAAAAEClYSq/e3hQ/t0VmjZtqkmTJmnhwoX666+/tG/fPtt5b9Z37txZLVq0KPbYO+64w47oNx35ptz/4S6++GI1adJE27dv17Zt2+x509LSbEUBs3/Lli3Vrl07O0UAgJIRAAAAAAAAAAAAAABQKqGhobrwwgvtcjx69epV7Lbw8HB17drVLgBODgEAAAAAAAAAAAAAAADcAAEAAAAAAAAAAAAAAADcAAEAAAAAAAAAAAAAAADcAAEAAAAAAAAAAAAAVCoOh6tbAAAVEwEAAAAAAAAAAAAAAADcAAEAAAAAAAAAAAAAAADcAAEAAAAAAAAAAAAAAADcAAEAAAAAAAAAAAAAAADcAAEAAAAOE+DLn0YgNT3b1U0AXC4nL0+Z2bmubgYAoELIy/8PqNo8HJKX+T8AUIE4HPxeAoCi0MsBAMBhalULcHUTAJeLjjvg6iYALpeelav41CxXNwMAUAGYzv/cPCIAqNq8PTwU4MWtZAAAgMqAqzYAAAAAAAAAAAAAANwAAQBUXSa8T4UgAAAAAAAAAAAAAG6CAACqLjr/AQAAAAAAAAAAALgRAgAAAAAAAAAAAACoVBwM8gOAIhEAAAAAAAAAAAAAQKVB5z8AFI8AAAAAAAAAAAAAAAAAboAAAAAAAAAAAAAAAAAAboAAAAAAAAAAAAAAAAAAboAAAAAAAAAAAAAAAAAAboAAAAAAAADAPTjylzxXNwIAAABA2XPI4XC4uhEAUCERAAAAAAAAuAc6/wEAAAAAQBVHAAAAAAAAAAAAAAAAADdAAAAAAAAAAAAAAAAAADdAAAAAAAAAAAAAAAAAADdAAAAAAAAAAAAAAACVisPhcHUTAKBCIgAAAAAAAAAAAAAAAIAbIAAAAAAAAAAAAAAAAIAbIAAAAAAAAAAAAAAAAIAbIAAAAAAAAAAAAAAAAIAbIAAAAAAAAAAAAACASsXhcHULAKBiIgAAAAAAAAAAAAAAAMBJyctfXJ9OIgAAAAAAAAAAAAAAAMBJcX3nv0EAAAAAAAAAAAAAAADcRsUYiQ7XIAAAAAAAAAAAAAAAAG6Dzv+qjAAAAAAAAAAAAAAAKg0HfZtH4t8DwGEIAAAAAAAAAAAAAKBScZACAIAiEQAAAAAAAAAAAAAAAMANEAAAAAAAAAAAAAAAAMANEAAAAAAAAAAAAAAAAMANEAAAAAAAAAAAAAAAAMANEAAAAAAAAAAAAABApeJwuLoFAFAxEQAAAAAAAAAAAAAAAMANEAAAAAAAAAAAAAAAAMANEAAAAAAAAAAAAAAAAMANEAAAAAAAAAAAAAAAAMANEAAAAAAAAAAAAAAAKimHqxsAoEIhAAAAAAAATpUnbr8AAAAAQNlyOPjcBQBFIQAAAAAAAE7FTSgAAAAAAAC4BgEAoIw1b97cqee79tpr9dxzzzn1nAAAAAAAAAAAAAAqPwIAQBnbuHGjU8+3d+9ep54PAFAFmcHJea5uBAAAAAAAAADA2QgAAGXs6aefdur5Tj/9dKeeDwBQBdH5DwAAAAAAKjGH4+ACACiMAABQxpwdAAAARm8DAAAAAAAAAICiEAAAAKCyofMfAAAAAAAAAAAUgQAAAAAAAAAAAAAAAABugAAAUAFER0dr2rRpWrlypRISElS9enW99tprBduTk5MVHx8vT09P1alTx4UtBQAAAAAAAAAAAFBREQAAXCg1NVWjRo3Siy++qIyMDOXlHazrfcoppxwRADABgXbt2ik3N1fbt29XrVq1XNVkAAAAAAAAAAAAABUUAQDARUxn/3333aePPvpIOTk5atq0qcLCwrRo0aJC+5pAQM+ePfXzzz/rhx9+0K233uqCFgMAAAAAAAAAUBE45HA4XN0IAKiQCAAALvLFF1/oww8/lLe3t1555RXdc889WrJkibp06VJoX3Mhc84559gAwB9//KGbb75ZHh4eLmg1AAAAAAAAAAAAgIqKAADgAunp6XrhhRdsJ74p///AAw8c85gmTZrIy8tLu3btsscHBASUQ0sBAAAAAAAAAAAAVBYEAAAX2L59u2JiYlSnTh1dffXVpTomMjLSBgaSkpKUlZVVxi0EAAAAAAAAAAAAUNkQAABc4MCBA8rNzVVoaKj8/PxKdcyh+YzMcQAAAAAAAAAAAABwNAIAgAv4+PjYDn0zkj8nJ6dUx+zZs8d2/gcGBsrT07OMWwgAAAAAAAAAQMX1z5g5AMBRCAAALhAVFSV/f39FR0dr165dql279jGPmT9/vg0M1K9fv9RVAwAAkPkwnOfqRgAAAAAAAAAAygMBAMAFIiIi1Lt3b33yySd66qmn9OOPPxaU+C/KggULNGnSJLtPz5495eXFjy4AoJTo/AcAAAAAAACAKoNeRMBFXnnlFc2ZM0czZszQ4MGDde+992rv3r12m5kWIDY2Vrt379b06dP15JNP2nXt27fXlVde6eKWAwAAAAAAAAAAAKiICAAALmKmARgzZoxuuukmffnll5o1a5YCAwOVl5enHTt22AoB+/fvt6GA3NxctWzZUlOmTFFAQICrmw4AAAAAAAAAAACgAiIAALjQ5ZdfrvDwcD3yyCNau3at7fA3Zf4zMzO1atUq+7xatWpq3bq1xo0bp4YNG7q6yQAAAAAAAIBbMRNzMnsaAABwFwQAABfr3r27Zs6cqZUrV2rNmjXasGGDkpOTFRISoqZNm6pNmza29L+Pj4+rmwoAAAD8w9wid7i6EQAAAE5B5z9Q+TgcsgPoAACFEQAAKgDT2d+lSxe7AAAAABUfN9oAAABQhZGHBY4bPzZA+SEAAAAAAAAAAABuhW4WoEzx4wUcN35sgPJDAACoADIzM5WSkqLt27dr7dq1SkpKUkREhC3/X6NGDQUHB8vT09PVzQQAAAAAAEClQDcLAABAVUUAAHChnJwc/fzzz/rwww+1YMEC7dmz54jtHh4eatiwoXr06KG7775b7du3d01DAQAAAAAAAAAAAFR4BAAAF/roo4905513KiMjQw6Hw3b4m0ez5OXl2WXLli3avHmzpk6dqvnz56tVq1aubjYAAAAAAAAAAC7loNgJABSJAADgIrNnz9Z9991nO/+bN2+uAQMGqHPnzqpdu7b8/f3tlADbtm3T3Llz9fHHHysuLk7du3e3X7du3drVzQcAAAAAAAAAAABQwRAAAFwgOztbd911lw4cOKBTTjlFv/76qyIiIuzI/8O1a9dOF198sR588EGdddZZ2rVrl95//3299dZbhfYFAAAAAAAAAAAAULURAABcwJT0j42NVWBgoCZOnKjIyMhi9zXTAtSpU8dWCxg+fLjWrFljgwNBQUHl2GIAAAAAAAAAAAAAFR0BAMAFTHn/3Nxc1atXTw0aNCjVMR06dJC3t7dSU1OVk5NTxi0EAAAAAAAAAAAAUNkQAABcIDw8XF5eXjYEkJeXV6pjDnX6h4WF2SAAAAAAAAAAAABVFdPkAkDRCAAALlC3bl21atVKixYt0vbt21W7du1jHrN06VJlZWWpffv28vf3L4dWAgAAAAAAAAAAAKhMCAAALmBG/48ePVoXXHCBbr31Vn3++edq2bKlPD09C+2bmZmpxYsXa+zYsWrUqJHdn2QjAAAAAAAAAAAAgKMRAADKWGxsbJHra9WqpVGjRum+++7ThRdeqPPPP1+XXnqpTjnlFAUGBiohIUErVqzQlClTNGvWLLv+tddeU0RERDm/AwAAAAAAAAAVgxkYVLopRQEAQNVEAAAoY1FRUcccsZ+Xl6fx48fbpbjtZrqAHj166LbbbtO4cePKoqkAAAAAAAAAKjQ6/wEAQMkIAADlwHTgn+w+pTkHAAAAAAAAAABVATPlAkDRCAAAZezrr7926vkaNWrk1PMBAAAAAAAAAFCp0PkPAMUiAACUsX79+rm6CQAAAAAAAAAAAACqAAIAAAAAAAAAAAAAAAC4AQIAAAAAAAAAAAAAAAC4AQIAAAAAAAAAAAAAAAC4AQIAgAvl5eVpxYoVmjlzppYtW6bdu3crNTXVri9u/379+mn48OHl3FIAAAAAAAAAACoGh/nP4XB1MyoQ/i0A/IsAAOBCU6ZM0R133KG4uDjl5uYW2m4uYI4OA5x++unl1bzyY94i1ycAAAAAAAAAAADASSEAALjIypUrbef//v371bdvX3Xq1EnPP/+83fbSSy8pMTFRW7Zs0Z9//mkfmzdvrsGDB+vMM890ccvLAJ3/AAAAAAAAAAAAwEkjAAC4yL333qt9+/Zp4MCBevfddxUUFKQXXnjBjvh/5JFH7D7Z2dl2WoD77rtP06ZN04YNGzRixAgXtxwAAAAAAAAAAABARUQAAHAB06lvKgCYTv/hw4fbx6J4eXmpXr16+vrrr3XhhRdq0qRJuuiii3T11VeXc4sBAAAAAAAAAACcifmBgbJAAABwgb179yorK0u1a9dWeHh4wXoPDw/l5OQoMzNTPj4+BesdDocGDBig2bNn6/vvv9fll18ub29vVzQdAAAAAAAAAACXc9Bv/K9K+29RaRsOVGgEAAAXMJ3/ubm58vPzs6P8DzGVABITExUbG6u6desecUz9+vXl6emp6OhopaenEwAAAAAAAAAAAAAAcAQCAIALBAYG2s58M9I/Ozu7YL3p5F+xYoUWL15cKACQlpamvLw8+2jCAwAAAAAAAAAAAABwOAIAgAtERUXZ0f/79++3HfqHdOnSxQYAJk6cqAsuuEC+vr52ven4nzNnjq0cEBISckTVAAAAAAAAAAAAAAAw6EUEXCAsLExnnHGGpk2bpk2bNqlJkyZ2ff/+/TVp0iTNmjVL9913ny699FI72n/mzJn6+OOP7T5nnXWWAgICXNl8AChWg2r+6lAnWMG+XkrOyNay6CRtj09XXimO9ff2UKNwf9UL9Ve1AC/5enkoLStXW+LStGJ3stKzj6x+YuZ5G3Rabfl6ehQ6V3Zenqav3as9yZlOemdA6Znv5S6NwtW8eqA8PBzatO+AftmwX5nZJ1bBJ8DHU7d2ri/v/O/137bE5S/xR2z39nSoXpi/mkYGqnFkgILyf/52JKTpy6W7nPF2gBMWs3ObliyYrf17YxQUEqpTT+ukZqd2yP+5KPx7u5D83+NJCXHavnm9tm9apz3R220o9ppb7rPnKu6Y6G2btfzPX7Vvzy75+vmrSYs2Oq3rOaV7TQBAmUhNzb8WmjVLq1ausPc4TmnZUhddfGn+72m/4zrP38uXacH8edq3d6+iatXSOX3OVdNmzQvtl5SUpL+WLtbqlSsVG7tHPr6+atSocf7+fVW9Rk1nvS3guO3OvzZa/OvP2r9vj4KCQ9XmtM5q1rp9qa5TzHVQ8j/XRtvyr41idppro1xde6u5Ngor9rhd27forz9+1d6YaHMWVY+qo/aduqt2vUbOe2MAAKDCIQAAuMjQoUM1b948ffXVVzr33HPtuo4dO+qiiy7SlClT9P7779vFMBf55sNAw4YNdffdd8ther0AoALxyP+11LFeqK47o7ZycqWs3FzbWdm7WYQmLY7Woh1JxwwBtKoZpBvOrGN/55lz5OX/55l/4nOahdsQwegF25SSkVOwv/lNeEbdEPs6aVk5R5wrKzdP8zfFOf+NAscQ6uelR3o3Uds6ITqQ//1quvzPbVFdV7WrpRE/rFVsyvGFUszPwD3dG6lb43AbetmVmF4oADDkrPq6tE1N0/dpf/Z88n8mVuxOIgAAlzG/x//+c4E+fO0pe93q4+unrKxM/fzdF7p08G06r9/gY17P7ovdrTefuld7d++0U2eZ7+/c3BxdNnhokQEA85p/zJ2uz8a9ap+bzn/TyTRv2hTN/XGKbh/xcvHBAQBAmYmPj9OIRx7UkkV/Kjg4RI78a5up303RRxM+0LsffqRatWsf8xzm9/nnn3ysUa/9RwGBgbZaYnp6uj58b5yefPYFXXTJZQUdqLt2RWvoTdfbjn//gAB5e3vb4w+kpOjjieP1xuixOqVlq7J+28ARzLXJ8vxro/dffbLg2ig7/9po1tTPdUX+tU1pro32518bvf7k3fnXRtFHXBtdcd3QYgMAixf+ov976wVlZ2fJz98MJnIoPS1V//18vG6853F16nme898sUM64Tw4ARSMAALhI3759NWPGjIIy/4a/v7/Gjh2rDh062GDAunXr8i/Ss1W3bl1dcskluv/++xUZGenCVgNA0U6pEWg777fFp+mr5Xu070Cmqgf56Op2URp8eh3tS83W5v2pJZ5jR0K6Jv4ZrbjUTNvRbzrxg3091aFOiM4/JVK3nVVPby/crsycI0dR/707SZ8s2V3ofOlZJzbaGjgZg86ooza1Q/T5kl2au3G/svK/X3s1i9B1Z9bVTZ3qadScLYW+h0tyZv0wdW5UTatiktW6VnCR++xMTNNPa2K1Pf/nLz41S8P7NHXW2wFOSPS2Tfps3CsKDY9Q/1sfUL3GzRW/L1bfTRqnH7+YoHqNmtlqACXx9vHVqR3Okn+33oqq20ALZkzVhtXLi91/09oV+uK91xVePUrX3HyvajdsoqyMdP0+d4Z9zZ+++khX33yPs98qAOAY3h07RksWL9ItQ4fpgosukbe3j3768b8a9/ZojX7zNT37wkvy8fEt8Rzr1q7R+PfftaP9hz/+lOo1aKCNGzZo5HNP653Rb+rUU9uocdOD1z95+Z8hWrdtq46duqhlq1MVWb26MtIztGTRH3rrjdd0zx1DNWHSZ6pTt155vH3Ait66SZ+88x+FhUdqwND8a6NG5tpoj775eJztjK+bf23U+ljXRvk/O607dFLA2cGKqtNA82fmXxut+qvY/RPj9+vTca/K4eGhm+59Uk1atrEh+vUr/9LHY1/W1xPfVodO3W1oEgAAuB8CAICLmBS6Ked/tIiICD366KN2AYDKwMPhUKcGYXak8vS1+7Tpn47+xPRsfbdij+7sVl8XtYzQ2wtSS6wCYEZGHz06Oin/HIlpcWpbK1i1Q30VEeCt3ckZR+yTnZunA5lHVgAAXKFumJ8uOrWmlu1M1GdLogvWT162W50bhatzw2qaGLBTsUd9DxfH/Gxd3b6WVu5O1oJNccUGAH5cFVvw3N/b8+TeBOAEf/0+Twlx+zTg9ofU5owudp254X3dXSM08v4b9dm7r+r5cZPl4Vn892totQh7/CHL//i1xNecMWWSMjLS1f/W+9Wy/ZkF6y8ZcLNWLf1dv86cqn433iFPTz4CA0B52bpls6ZM/kJnde6i24bdVbD+xptv0y8/z9K8X2Zr/759qlW7TonneeuNV3XgQIpGvzNVNWoeLOEfERGph4c/rvvuul3ffD1ZDw0fYdfXqVtXL706qtA5zPot+e2Z9H8TNH/eXA0YdJ0T3ylQsqX/m2uvjQYNe1htTv/32uj6/Guj5++/QZ+Oe00vvvtlyddG+fub4w/564/5Jb7m6mV/KjkxXn0vu1Zn9Ti3YH3nc2pp45q/NW/6t1q3Yqnantn1JN8dAACoiLj7AQAAToqZf7xBNX9l5+Zq3d4DR2yLSc5UQlq2qgf5KszfW/FpWcd9fq/88/t4edjwQE7esSYSAFynY4Mw+336+9b4Qtum/LVbj/Vtqq6Nqunbv2OOeS4zOmfwGbVVLcBbj/53jc6oF+b09gJlxdxwNh3tp3c954j1pgS/GeG2dcNq7dqxRXUbOqdaRXZWlvZEb7flb8Miqhfa3vr0ztqybqUWzZ+lTr0ucMprAgCObf7cObY0c4+eR/49MOuuv+kWPfbw/Zo9a6YG33BTsefYt2+vli1ZrFat2xR0/h/SpVu3/HVRmjVruh58ZLgd6VwSEzQwr50Qz1RhKF+r/jp4bXTGUddGwaFhthrA1o1rnHptZPj6HxzZf7D0/5H8AwP/2cbofwAA3BUBAAAAcFLMKGUzMj8mKUNpR5XdT8rIzl+Xo/D87UG+nscVAPDycKhuqJ+uaFNDtUJ8tTomRXsPFJ4/vXF4gJ47r6mCfb0Uk5KheZvi9Pu2xJN+X8DxahIRaEv+70ku/H26fOfB78k2tYJLFQAwo/2v6VBHHy/aoX0phc8HVGRmCoCImrUVHFrtiPVmvlvTQZ+zJtvOY+usm9xm2k+Hic3YkFjhoFhe3sG/TSaYQAAAAMrP2rWr5ePjY0ffH61jp4PlzpcuWVxiAGDr5s3KyclRgwYNC23z8PBU06bN9NvCX7VnT4yiatUusT3RO3fYudgjIwuHxYCyZK6NIou5NqqWf220ae3f+ddGMU4NALQ5vbN9vYWzp+nCq2+w0ysZB1KS9evM7xVRI0rNTu3gtNcDAAAVCwEAoIwlJyc79Xxm6gA/Pz+nnhMAToafl4d885e9KYU793Ny85SamaOawb7y8Sx5RM4hHeoE67ZO9eyUAoYJFfy6OV7frdyjowsAmNL/8WnZSkrPskGEqBBf3XhmHXVtWE0fLY7WvgPHX3EAOBHm+y/E30vZOXk29HK05Pzv1YzsXNUILnmOW8M7/2flyna1FJ2Yrhlr9pY4dQZQ0aSnpSo99YAaNG1RaJuHh4cCg4KVm5er1JQUp72mp5e3GjRroUXzf9amNStUq16jgm2pB5K1eMFs+zx29w6nvSYAoGSm0z4xIUFe3t7yDyg8Ajk0NEy+vn7aHb2zxPPExe0/uH9YWJHbwyMi7OPevXtLDADs3LFdM6dPU1hYNZ3do1cp3wVw8g5dGzVs2rLQNnNtFGCujXLNtZGT7x/6+OrWh57VD19O1DN3D1aLdmfY9etXLlOd+o1sKMBUxAAqNb6Fj8A/B4DDEQAAyljz5s2dekF93XXX6T//+Y/TzgcAJ8vf++DvONO5WZTMnFyZvvxjVOQssGFfqkbN32qnFmhYzV89m0Yo2MdTGVlHdoPm5n/56twtNiCQnf+FaYUJI1zVLkqdG4bpklNraOKf0UW/COBkJt/imf/3PjcvzwZfimKqA/h7Fz+v5yE9moSrTe1g3fPNKiWmZzu7qUCZMje5DdOpUxQvbx87Uj87y7mVLS6+9mYt/W2uJn/4pp0SwIz0T05K0Ffj39Kendvs9XjaAeeFDgAAJTMBgJzsbNvB6eVZ9O1HUx3gQGpqiefJyEi3j2YwRFF8fQ+GK9PSij9PYmKC7rhtiOL279frb41VVK1apXkLgFMc69rI+9C1Ubbzw+s1atW1P4N7du2wi5V/TRTUKkyRUXWc/npAeTP3gQiyAEDRCAAAZWzPnj1OPV9SUtIJHbdhwwatWLGi2O21a9dWp39K8AHA8cjIPtjZ6eNVdA+/Gc1sRu4X0ydaSEpGjtbvPXiTZFXMAS3ZmaS7uzXQgz0baOzCHUrO+LdDNCHtyM7RlMwcfbpkl5pE+OvMeqGa/FeMrRIAlLVc+z2eZ28+HKpecTQvDw+lZ5fc6dmgmr+Gdm2gmWv3KjohvSyaCpQp338qVWVlFv29bm9u5/+ceBXTkXOiatSup5sffEY/fjFBk8e/qc/fe82Whq7TsIluuPcJfTxmpAKDQpz6mgCA4nnmX/d4eHoqLzdXOblFX49nZWXJ37/kCoc+/5Qtz84uOhRpzmEU17lqggGvjHxBu6Kjdf1Nt6hTl66lfQuAUxz63szKyihy+6FrI08v596m3xsTrTefvt9OhXT78JFqfdpZMt2lK5f8T19NGKOxLz6iB58fY6dnAgAA7ocAAFDGxo8f79TznXLKKSd03Pfff6/hw4cXu/3SSy/V119/faLNAlCFpWXn2pHN4QGFLyvMiOgAb0+7PauYCgHHsiclU+v2HtBZ9cPUOMJfy3eVXBoxKzdPa2MPqEcTX9UN9bPHAmXNjPo34RUvD4etRHG0AO+DU2XsP1B8AMBMI3BZmyh5eTps+f/T64UWbKsf7m8fa4f62vUmHBCTXPRNRMCV/PwD7Xy2CfH7Cm0zN6DTUlPyv9c95B8Q6PTXbt+ph5q0bKvEuP1KzH/9oJAwRdSopZ1b1is3J0e1GzRx+msCAIpmOjODQ0Jsx31aWlqh7QcOpNjR/TVqljwa/1Dp/+RiBkPEx8fbx4h/pgI4nAkHPDniUf06d46uunaAbr39Dnk5uZMVOBa/gH+ujf6ZzuJw9troQNlcG33/xQQbArhjxEtqf1b3gvVndOud36Ygvfn0vfrv5+N1/V3F3ysEAACVF1e9QBm76aabXN0Eq2XLlhowYECx20877bRybA0Ad2I6PuNSs1Q71E8+ng5l5vw71D/Q11P+3h5Kzco94ZH4pnpAaubBjlVzrtLw+KcEnBmRDZSXrXGp6tY4XBGBPoW2tYwKNgN7tGZP8SXIzfYAH4/8nyMPDevWsMh9ejWLtMuE37dryvIYZzUdcBpTBSOqbkPt2r7Jznfrd9jN7MyMDNs5b0aEVousWSavHRIWbpd6alawfvGCX+y207ow5zMAlKemTZvpl1kzFRtT+Jrlr2VL86/z89S2bbsSz9GgQSP7O3znjh2FtpnO0y1bNikoOES1ah9ZztyEC9587RXN+2W2Lr70cj362JOUiYZLmO+7WvnXRtH510Zp+ddG/kddG5nQpAnMhDv52mjHlg3512EBiqxZu9C2Bk2ay8fXV5vXrXTqawIAgIqDAABQycXkf5CeMWOGwsPDdckllxS73wUXXGAXAHC27Nw87UjIUM1gXzWJDNCaPf+OuK8Z5KMQPy9tiUs74bnMvT0ddtSzeZ20rGNXEfD2cOjUqCC7/85ESqij/CzZkajrzqyrM+qHacbavUdsMyP7zffkb1viiz0+N3+7mcLix1WxhbZ1bFhN/dpG6ed1e/OXfYz+R4XWou3p2r5prZb/+avO6nl+wfoDyUmK3rZJgcGhqlWvYbm0JWbnVv05b4ai8l/PtAsAUH66dOuu9955WwsX/KrLr7y6YL3p+P/8k4/l5eWtc/qcW+I5akZFqUWrVlq9eqXi4+JULTy8YNvyv5Zp186duuCiS+Tp6XnE+d9+c5SmfjtFZ/fopfseeoTOf7iUuQbZZq+NFqhTz/MK1qckJyp66yY7TZGzr41Cw8K1a/tme/11tH17disrM0vVKP8PAIDbIgAAVHKrV6/WkCFD1L59+xIDAABQVkwFgKU7E3Va3WD1aRah2ORMO9o/wMdT57eIlLenh37ZEGc7P41mkQF6uFcjrdydrNELthecp22tYMWnZSkhLVuZObkyt+j8vT3VrnaQmlcP1P7UTO04bE70Lg3DtD0+XYnpWbbqgNnfhA2uaFNT1fy9NX9zXKkCA4CzbNh7QH9si9dZDcLUo2mElu5ItFUozqwfpvZ1QrQ8Okl7kv7tuL+1c31d3jZKb83boplr98r8hOyIT1Ph8W1S3bCDUwDsyf/5WrH7yGkwTEjGTLVh+P3z6OVwKNTv4KW+mRYj9QQrcAAnon3nHlr48/ea+e1nqtuomS3Db6oBfDfpXaUkJei6O4fbUriGCQS8/NAtiqrbQPc9P9reALfyf3ZS84/J+WfO5+x/5ng2N7EPHesfGGg7jw7ZsGqZImvWyV8fZOecjtsXqy8/eMOW/+9z2bW28gAAoPyc2rqNzu7RU/Pm/qLp035Q567dbEf9r/PmatEfv+vMszqrTt26Bfu/8erL+mzSR3rimed1eb+r7DoPDw/dc99Duu+u2/Xog/fp2RdfVlhYmGJjY/XyC88pIP9vQf+BgwvOYcr+j//gXX3x2SR1zD//Cy+/kn8OT6Wn//s5wrTB2/vfvx9AWeuQf220IP/aaMa3n6heo6b22shUA/jWXBslJ+r6ux4ruL7ZuXWjRuZfG5lAwIPPj1FAUPDBk9hro5RjXBsFFVwbdep1vlb/tUjf5L/GkHufUEi1CPuZOT7/+uijt0fmXxd5qPv5V5TvPwRQBsh3AUDRCAAAAICTtnx3sqat3ms7/O/t3kDJ6dkK9fdWNX8vfb8qVitjko95jjPrhapNrSDtT81SWlaOHPn/Bft6qkawj3YlZmjSkl12qoFDOjcI09Xt/Oyc6unZuXZUT3iAt8LzX9d0kP64Zm8JrwaUjQ9+267wPj66r2cjbd2faoMvDaoFKCEtS5MW77Tfq852alSwhnSqZ58fGt3WMCJAz190in3+184kfbRopw3rAOWhYdOWuvjam/XNR2M19vmHFV69ppITExS7e4d6XNDviKoAxTFzRn89YYx2bF5nv94Xs8s+Tnzz2YIb29fe9qCatGxTcMxHo0fK08NDwWHhys3N0f7YGBs8uPz629Wxe8kjTAEAZeOBhx/T3r179dzTT6hZs+b5v8O9tHnTRjuS//Y775afv/8xz9Hh9DN0zYBBmvR/E3TnbUMUWaOG9sTs1u5du/LPcY+aNT+lYN9d0Tv19Ref2ef79sXqgXvuLHS+Ll3P1vU33ey8NwkcQ6NmrXTpgFv09f+9rTH510bVImsoJf/aaE/+tVGvC69U51JeG00eP1rbN6+3Xx+6Nho/6ll5/nNtNOj2h9SkxcFrozO79dGWDWs0d9oUvTriTkVG1bYBgL0x0UpKiFPPC/upfcduZfOGAQCAyxEAAAAAJy0rJ0//Xb1XG/en6pxmEQrz89aupAx9vnSXVsceMIMVCpjR+mYUc3zakVMCfLtij7bEpdrR/qYj39NDtsz5zPX7tWhHojKO6jj94q/dal87RI0j/AtGOm/al6rPtidoxe7i51kHytLu/O/7x39cq8taR+m0uiHy8nBo2uo9+mLZLqUfVZEiMS1L0YnppRqdfyAz2+6bnFF4Kg0Ph6Ng5L8R/c/UF4fWeXt5nMxbAo6bmcf2nEuuUeMWrTXr28+0J3q7Hel2yYCbdVrXXnYk5iGmM79G7XoKrx5lR3keLiszQxlpafZ5cGg1u+RkZdvFMJ38h7vyxju19Lc5it21ww4Fantmt/x2XK1a9RqV8TsGABSnXv36euf98fr800n6feFCZeX/Du93VX/dMnSY/AMCjti3WrVw1W/QUEGHRjz/w4QG7n3gYXXocLq++/ZrRe/cqRYtT9UzL7ykDqedccS+DoeHatSsqZDQMPtasXv2FGpTUlKi898oUAJzbdTbXBudcqpmHH5tNPAWndGl1xFViry886+NatVVRP61keOIa6O8g9dG6f9cG4VVs4sJBmT/UxXAVD06/DX733yv2pzWSb/9Mk27d2yz5zil9Wnq3PsCtWp/1lHnBwAA7oQAAAAAcJrVew7YpSTb4tP05PQNhdbHpWXpl41xdimN6MSM/IVR/qh4DmTk6LMl0XYpyeS/dtulNOZvirNLUcwUHLd98fdxtxMoaw2btdKtj7xQ4j4169TXk299XGi9ufl984PPHNfrdejc0y4AgIolJCRUQ4fdZZeS3HTLbXYpTvde59ilJPUbNNBnX313Is0Eylyj5qfq9kdfLHGfqDoN9MyYTwqt9/L20a0PPXdcr2fCla1P72wXAABQtRAAAIAqwAy+ZkosAAAAAAAAACeGO4wAUFkQAACAKoBLcwAAAAAAAAAnruLdYXQ4Kl6bAKAiIAAAAAAAAACqAEatAQAAuA+u6wCgOAQAAAAAAABAFcBNYgAAAACA+yMAAAAAAAAAAAAAAACAGyAAAAAAAAAAAAAAAACAGyAAAAAAAAAAAAAAUAwzkVCeqxsBAEApEQAAAAAAAAAAAAAoBp3/FY/DcXABABRGAAAAAAAAAAAAAAAAADdAAACo5Nq3b6/p06crODjY1U0BAAAAAAAAAAAA4EIEAIAKIDs7W0uXLtXChQu1detWHThwQKGhoWrWrJnOOeccNW/evNhjw8PD1bdv33JsLQAAAAAAAAAAAICKiAAA4EIZGRn63//+p0ceecQGAPLyDs4mZR4d/0xg5OHhoXPPPVcvvvii2rVrV7AeAAAAAAAAAAAAgPOZHrvK2iNHAABwoVdffVWvvPKKHfFvOv29vLxUs2ZNBQYGKjExUXv27FFOTo4t8b98+XK9/vrr6t+/v6ubDQA4EeZqMc/VjQAAAAAAAHAPDJYDUJYq828YAgCAi/z00096+umn7fPGjRvr/vvv1/XXX6+goKCCffbu3as333xT7733nnbv3q2BAwfqlFNOUfv27V3UagDACaPzHwAAAAAAAABQxggAAC5gRvw/9NBD9nmfPn1sB3/Dhg0L7Ve9enVb+t+M+h88eLBWrlyp999/X2PGjJGnp2c5txoAAAAAAAAAAABARUYAAHCB7du3KyYmxpb6Hz16dJGd/4dr27athg0bprvvvltr165VamqqgoODy6exAAAAAAAAAAAAACoFAgCAC2RkZCg3N1f16tVTSEhIqY4xpf+9vb2VmZlpjwUAAAAAAAAAAACAwxEAAFwgLCxMXl5etiM/L690k0JnZ2fbRxMYMEEAAAAAAAAAAACqKofD1S0AgIqJAADgAmbkf8eOHTVnzhz99ddfql279jGP+fXXX5WVlaUuXbrI39+/HFoJAAAAAAAAAAAAoDIhAAC4gKenpyZOnKi2bdvqxhtv1IwZM9ShQ4di9581a5ZGjx6tBg0a6O6775aDaCMAAAAAAAAAAACAoxAAAFxk27ZtevDBB/Xiiy+qd+/eGjBggHr06KGIiAj5+PgoPT1dMTEx+vHHH/XVV1+pUaNGeumll7Ry5coiz9e1a9dyfgcAAAAAAAAAAAAAKhICAICL3HDDDbaDPzU1VTk5ORo3bpw++OADW97fw8PDrjPbcnNz7Yj/Xbt2aejQocWeLy4urhxbDwAAAAAAAAAAAKCiIQAAuEhWVpYyMzPtaP/DmY5/sxh+fn5HbMvIyCh0HqYDAAAAAAAAAABUNdwZB4CiEQAAXGTKlCk2BAAAAAAAAAAAAErPjItjcBwAFI0AAOAibdu2dXUTAAAAAAAAAAAAALgRAgAAAAAAAAAAAAAAALgBAgBABZKamqqMjAzl5OTIy8tLfn5+dgEAAAAAAAAAAACAYyEAAFQA8+bN05QpU7Rx40YlJCQoMzPTdvxHRETYqQKuvfZanXrqqa5uJgAAAAAAAAAAAIAKjAAA4EL79u3Tvffeqy+++EJ5eXl2ncPhsI+Hvv7hhx80cuRIPffcc3rooYfk6+vrsvYCAAAAAAAAAFAR/HMrHQBwFAIAgIuYcv+DBw/W7NmzbWd/nTp11LlzZ9WtW1f+/v5KSUnR5s2b9dtvv9mqACYAsHXrVr399tuEAAAAAAAAAAAAAAAUQgAAcJFHH31UM2fOlIeHh4YNG6ZXXnlFgYGBhfbbs2ePnQJg/vz5mjBhgg0JDBkyxAUtBgAAAAAAAAAAJ89UAKaEAYCyQQAAcIG9e/fqm2++sZ3/jz32mJ555hl5enoWuW/NmjU1a9YsXXPNNfruu+80Y8YMWznAx8ennFsNAAAAAAAAAABOHp3/AMoOAQDABXbt2mWnAKhdu7ZuvvnmYjv/D/Hy8tLAgQP1448/2mPT0tIIAAAAAAAux6gdAAAAAABQsRAAAFzAdPg7HA6FhobKz8+vVMdERkbaigGHjgUAAADgalyXAwAAAACAioUAAOACZuS/GcGfmJiojIyMUh2zb98+5ebmKioqqtShAQAAAAAAAAAA3BED5QCgaAQAABcIDw/XbbfdppdeekmfffaZHn74YVvmvziZmZn6+uuvbQDg8ssvp/w/AAAAAAAAAAAAgEIIAAAu8thjj2n9+vV64YUXFBMTo+eff14hISGF9tu2bZvuvPNOzZ49WyNGjFC/fv1c0FoAAAAAAAAAAAAAFR0BAKCMvf7668Vua9GihebOnasxY8bYSgB9+vRR8+bNFRgYqISEBK1cudJuT0lJ0emnn66goCDNmzdPffv2Lcd3AAAAAAAAAAAAAKAyIAAAlDFT3t/MRZSXl1fkdrPNLHFxcZo8eXLBfofPX2SeL126VEuWLNHQoUMJAAAAAAAAAAAAqixz9/ywW+hVHv8WAA5HAAAoY2aUvzNFRUU59XwAAAAAAAAAAFQ29HkDQNEIAABlzJTsdyZ/f3+nng8AAAAAAAAAAACAeyAAAJSx6tWru7oJAAAAAAAAAAAAAKoAAgAAAAAAAAAAAAAAALgBAgBAGUtOTnbq+by9veXn5+fUcwIAAAAAAAAAAACo/AgAAGWsTZs2cjgcTjlXXl6eBg0apBdffNEp5wMAAAAAAAAAoNJxOJx23x0A3A0BAKCMbd++vVT7HbpYMZ38Ja2Li4tzYusAAAAAAAAAAAAAuAsCAEAZ++KLL4rdtnr1ao0ePVpZWVnq1auXzjzzTNWpU0f+/v5KSUnR1q1btWDBArs0a9ZM9957rzp27FiOrQcAlMjktPKOuRcAAAAAAAAAAOWCAABQxq655poi16empurJJ59Uenq6vv32W/Xs2VO+vr6F9ktLS9NXX32loUOHasKECRoyZEhZNxkAUFp0/gMAAAAAAAAAKhACAIAL5Obm6uabb9a2bds0ceJEnXfeecXua6oBXH/99Vq2bJnGjBmjsWPH6v7772d+IwAAAAAAAAAAAABHIAAAuMCuXbv0yy+/qF69ejr77LNLdUyfPn00btw4zZ8/X8OGDbPBAAAAAAAAAAAATowpbVg5B5qZVjNGDgCKRgAAcIG4uDhlZmbKz89PXl6l+zEMDAy0o/7379+vrKwsAgAAAAAAAAAAgJNADzoAuCMCAIALeHp62s58UwkgOTlZUVFRxzxm06ZNys7OtoEByv8DAAAAAAAAAAAAOBoBAMAFTOn/atWqaevWrXr66ac1ZswYRUREFLt/dHS0JkyYoJycHDVq1IjR/wAAAAAAAAAAAAAKIQAAuEBISIieeOIJ3Xzzzfryyy+1e/du3XnnnbrooouO6NxPSEjQZ599pnHjxmn16tV25P/1119f6mkDAAAAAKB4lXfOVwAAAAAAUDR6ESsUbr5UJTfddJOWLFmiDz/8UPPmzdP8+fPl7e2t+vXrKzg4WHFxcdq+fbvdNy8vz4YGnn32WfXs2dO1DQcAAADgJvj8CQAAAACAuyEAUKFw86WqGTlypE477TS9+uqrWr9+vTIzM7Vx40Y70t90+hseHh7q2LGjRowYYSsEAAAAAAAAAABQ1TnoUwGAIhEAAFzIjOofMmSIBg8ebKsATJ8+XevWrVNycrLCw8PVpk0bXXHFFerQoYOrmwoAAAAAAAAAAACggiMAAFQAPj4+6tu3r10AAAAAAAAAAAAA4EQQAAAAAAAAAAAAAAAAwA0QAAAAAAAAAAAAAECl4nC4ugUAUDERAAAAAAAAAEA5y8tfuGsPAABOHFcSAFA0AgAAAAAAAAAoZ9yyBwAAAICyQAAAAAAAAAAAAAAAAAA3QAAAAAAAAAAAAAAAQKkkJSXpt99+019//aV9+/bJ399fTZs2VefOndW8eXOnv96aNWu0bt06+zwkJERdunSRn5+f018HcBcEAAAAAAAAAAAAAAAc0+bNm/Xggw9q48aNyszMLFjv4eGhatWq6Y477tCgQYPkcDhnyqeEhATdfffd2rFjh/3aBA1at25NAAAoAQEAAAAAAAAAAAAAVBqmb9lZHcwovfT0dD377LNavXq1wsPD1bdvX9sZv3//fs2cOVNr167VqFGjFBUVpT59+jjlNb/88ktFR0fLy8tL2dnZTjkn4O4IAAAAAAAAAAAAAAAo0fjx4/XHH3/Y508//bTOPfdcO/LfuOKKK3TPPfdo+fLlGj16tHr37n3SIQ0TLPj444/l6elpy/7PmzfvpN8DUBUQAAAAAAAAAAAAAABQrH379umdd95RXl6e7fg///zzj9huRv2b8v+333671q1bp//+97+67LLLTvj1TLWBe++9V/Hx8RoxYoSdAoAAAFA6BAAAAAAAAACAvPyFSsIAAABFWrx4sS3Bb0b8m47+onTt2lX16tXT9u3bNXnyZF166aUnVAXAhAymTp2qRYsWqXPnzrrqqqvs1AIASocAAAAAAAAAAEDnPwAAQLHWrl1rH2vWrGk7+Yvi7e1tS/WbAMDmzZtt1YDq1asf92slJCRo0qRJtvT/DTfcID8/v5NqO1DVEAAAAAAAAAAAAABApXKS08vjOOTk5CgmJsY+NwEAL6/iuxdbtmxpH7Oysk4oAGBG/7/xxhvauHGjnUKgW7duJ95wVACU2XIFAgAAAAAAAAAAAABAJWU66HNyPI77OFOe35T0P5bc3FzFx8fb52FhYSUeU7duXftopgswI/mP15w5c+z0AXXq1NGLL75YYtgAlQGd/67ATw0AAAAAAAAAAABQSb300kvyzE4/7uM6d+6syy+//Jj7mVH5GRkZ9rmPj48NDhQnKCio4JjMzMzjak9SUpI++OAD2+l/yy230PkPnCB+cgAAAAAAAAAAAIBK6qefflL2gcTjPi4wMLDUAQBT0t8wnfIlBQB8fX3to6kacOiY0po6daqWLl2qhg0bql+/fsd1LIB/EQAAAAAAAAAAAAAAUCTT4e/t7W2fm9L+JhBQnEOVAsw0AYeOKY0VK1bojTfeUEhIiN588035+fmdXKOBKowAAAAAAAAAAAAAAFBJvf/++wo8gR6/yMjIUu1nAgCHRvabsv4lBQBSUlIKjjHTBZRGamqqRo0aZR+HDRumli1bluo4AEUjAAAAAAAAAAAAAIBKw5H/n0cJZeirmlNPPVVh/qUfbX+8zGj+atWq2ecJCQm2vH9xdu7caR/NVAFhYWGlOn90dLRWrlwpf39/5eTk6Msvvyy0z/r16+1jUlKS/vvf/yo4ONhOFXDWWWcd57sB3B8BAAAAAAAAAAAAAABF8vT0VFRUlH2+Z88eOw1AcVavXm0fTfn/0lYYMIEC0/GflpZmqxmUJDY2Vq+++qp9ftlllxEAAIpAAAAAAAAAAAAAAABAsQ6V5TcBgO3bt6tVq1aF9snKytJvv/1mnzdp0qTUAQAzmv/cc89Venp6sfusWbNGW7ZsUVBQkDp27Cg/Pz+1a9fuBN4J4P4IAAAAAAAAAAAAAAAo1umnn27L+pvR/2PHjrXL0RYsWKAdO3bY59dcc40cpZymoXbt2nrppZdK3MdsNwEAU4ng2WefVY0aNY7/TQBVBAEAAAAAAACAEuXJzDQLAAAAVFVmNP+dd96p0aNH6+eff9a0adN03nnn2ekBjF27dumdd96xz1u0aKGLL7640Dmuvvpq/f333+ratasNEPj7+5frewCqCgIAAAAAQJHo7AEAHMLfAxhcGwAAUJGUcnA5nGjIkCH6888/9b///c+Owjcj/tu0aaP9+/dr5syZ2rBhgy3Rf88998jDw8PVzQWqLAIAAAAAQJG4kwAAAA7HtQEAABUGf5Zdws/PT0899ZQeffRRrVu3TlOmTLGLYTr8TZWAoUOH6pxzznFxS4GqjQAAAAAAAAAAAAAAgGNq3Lixxo8fr0WLFmnZsmWKjY1VQECAmjdvro4dO6pp06bFHnv//fcrISHBBgV8fHyO63Uvv/xytWvXTsHBwQoNDT3ZtwG4NQIAAAAAAAAAAAAAAEolJCREvXv3tsvx6NKlywm/ZsuWLe0C4NgIAAAAAAAAAAAAAAAVgpnfIM/VjQBQiREAAAAAAAAAAAAAQKXicDhc3YQydHzvzXGc+wNwbwQAAAAAAAAAAAAAAABwAwQAAAAAAAAAAAAAAABwAwQAAAAAAAAAAAAAAABwAwQAAAA4zAXNI1zdBMDl6oXVdXUTAJd7473v9fzCFa5uBuByMfP+4+omAC7n4+mQtwfz6qJqC/TxVHpWrqubAQAAgFIgAAAAwGF8PD1c3QTA5QJ9uEQEsjIzlZh0wNXNAABUEA76/1HFmZ8BfgwAAAAqB+7uAgAAAAAAAAAAoNIwoSQCegBQNAIAAAAAAAAAAAAAAAC4AQIAAAAAAAAAAAAAAAC4AQIAAAAAAAAAAAAAAAC4AQIAAAAAAAAAAAAAAAC4AQIAAAAAAAAAAAAAqFQ8HA5XNwEAKiQCAAAAAAAAAAAAAAAAuAECAAAAAAAAAAAAAAAAuAECAAAAAAAAAAAAAAAAuAECAAAAAAAAAAAAAAAAuAECAAAAAAAAAAAAAAAAuAECAAAAAAAAAAAAAKhUHK5uAABUUAQAAAAAAOB4mTtNea5uBAAAAAAAAHAkAgAAAAAAcLzo/AcAAAAAAEAFRAAAAAAAAAAAAAAAAAA3QAAAAAAAAAAAAAAAAAA3QAAAAAAAAAAAAAAAlYbD4bAL/sE/BYDDEAAAAAAAAAAAAAAAAMANEAAAAAAAAAAAAAAAAMANEAAAAAAAAAAAAAAAAMANEAAAAAAAAAAAAAAAAMANEAAAAAAAAAAAAABApeLhcHULAKBiIgAAAAAAAAAAAAAAAIAbIAAAAAAAAAAAAAAAAIAbIAAAAAAAAAAAAAAAAIAbIAAAAAAAAAAAAAAAAIAb8FJe/v91uLoZAAAAgHswl9Z5rm4EAAAAAABuzHz2djjo3AKAonjR+Q8AAAA4D53/AAAAAAAAAFyFKQAAAAAAAAAAAAAAAHADBAAAAAAAAAAAAAAAAHADBAAAAAAAAAAAAAAAAHADBAAAAAAAAAAAAAAAAHADBAAAAAAAAAAAAABQeTjy/+dwdSMAoGIiAAAAAAAAAAAAAAAAgBsgAACUsfj4eN11111OPeeoUaNUo0YNp54TAAAAAAAAAAAAQOVGAAAoY6mpqfriiy+Ul5fntHM+//zzBAAAAAAAAAAAAAAAHIEAAFDGAgICNGjQIKeeMzg42KnnAwAAAAAAAAAAAFD5EQAAyli1atX08ccfu7oZAAAAAAAAAAA4hal363BxGxwOV7cAAComAgAAAAAAAAAAAAAoNbreAaDiIgAAAAAAAAAAAAAAAIAbIAAAt9W8eXOnnu/5559X//79nXrOQ3Jzc7Vp0yatWrVKsbGxSktLU58+fXTqqacW7JOUlKTMzEz5+/srMDCwTNoBAAAAAAAAAAAAoPIiAAC3tXHjxmPuc/gcQXl5eYXWH74uMTHRia37l3mN++67T1988YVSUlJsJ78JBHz44YdHBABeeeUVffDBB7rqqqv01ltvycuLH18AAAAAAAAAAAAA/6IHEW7rvffeK3K96XBfsWKF3W5G0p955plq06aN6tWrJx8fH9vRv3btWi1evFjr1q3TGWecoYEDB6p79+5Ob2N0dLQGDx6s+fPny8PDw7YhLi7OjvY/Ws+ePfX6669r7ty5SkhIUGRkpNPbAwAAAAAAAABARWeG8Hk4jrlblcE/BYDDEQCA27r11luLXL9r1y7bkW46+82o+27duhUqqZ+Tk6O9e/dq1KhRevvtt7VkyRLdcccdTm/j6NGjtWDBAtWoUUNjxoxR586ddfvtt+vHH38stG+XLl0UEhJiKxuYaQIIAAAAAAAAAAAAAAA4HAEAVCmmtP6QIUO0fft2TZs2Tb169SpyP09PT0VFRemJJ57Q8uXL9c0336h///668MILndaW1NRUW+bfTDdgggCmtL/h6+tb5P4BAQE2BDB16lQbSGjVqpXT2gIAAAAAAAAAAACg8iMAgCpl06ZNmj17ttq1a1ds5//hgoODbaf/zJkzbZl+ZwYAFi5cqPj4eDvFQL9+/Up1zKmnnmoDAJs3b3ZaOwAAAAAAAAAAAAC4BwIAqFLMyH9T3r9atWqlPuZQqf0dO3Y4tS1bt261jyaMYCoOlIa/v799NNUDAAAAAAAAAAAAAOBwBABQpXh5HfyWX79+famPWbFihX308PBwalv8/PzsY3p6eqmPWbdunX2sUaOGU9sCAAAAAAAAAEBlYqbXBQAURgAAVUqLFi3k4+OjnTt36oknntDjjz9eMKq+KGvXrrUl982FRKtWrZzaFnM+c97ff/9dWVlZ8vb2LnH/hIQEzZgxwwYRTjvtNKe2BQAAAAAAAACASoO+fwAoFgEAVCk1a9bUgw8+qJdfftkuZkqA2267TR07drTBgEP27NmjKVOm6L333rOj7sPDw3XBBRc4tS0dOnRQkyZNtGnTJn3yySe66aabStz/3XffVXx8vOrXr+/0MAIAACfHfOrOc3UjAAAAAAAAAKDKIwCAKseM+l+8eLFmz55tO94//fRTBQYGqmHDhrYagOn837Fjh903Ly/PrnvppZfUvn17p7bDjOS/++679cADD+ixxx5TrVq1dPbZZys3N9duz8nJsdMDHDhwQKNHj9bIkSPtugsvvFCRkZFObQsAACeHzn8AAAAAAAAAqAgIAKDKCQgI0Pjx4+2I+okTJ2r37t1KSUnRypUrbUl+0+lvmA560yH/0EMP6eKLLy6TtgwYMEC//vqrrTZw+eWX26oApiqBYdpmph/4+++/7ZQFRteuXW1YwNPTs0zaAwAAAAAAAAAAAKDyIgCAKqlu3bp64YUXNGLECH333Xf66aeftH79eqWmpqpGjRrq3LmzBg8erBYtWpRpO8xI/smTJ2v48OF688039eeff9r1Jojw+++/Fzw3YYTLLrtMn3/++RFTFQAAAAAAAAAAAADAIQQAUKWZagADBw60iyuZ8v7XXHONfv75Z61du1ZxcXG23H9QUJCaNm1qKxH07NmTzn8AAAAAAAAAAPI5XN0AAKigCAAAFYAZ4X/aaafZxXT85+bm2vVm9L8p928eAQAAAAAAAAAAAKAkBABQpe3evVsrV660j6b8vxlt36dPn4LtZl1aWpq8vLwUGhpaLm0yHf5mAQAAAAAAAAAAAIDjQQAAVVJeXp7eeOMNjRkzxpbbT09PV3Z2tq699tojAgCzZs3SXXfdpXr16tnngYGBZdou04YNGzZo586dtgpA9erV1apVK/n5+ZXp6wIAAAAAAAAAAACo/AgAoMrJyMjQ/fffr/fee8+W1o+KilJQUJBiYmIK7duhQwfb+b5mzRotXbpUZ599ttPbYzr958yZo0mTJunHH39UQkLCEdtN6KBnz5664YYbdNFFFxEGAAAAAAAAAAAAAFAkAgCocr7++mtNnDjRdv4/99xz6t+/v7766iuNGDGi0L61atVS27ZtNXXqVK1evdrpAQBTeeCBBx7Q559/rqSkJLvOVCc4XEpKig0G/PLLL+rRo4e++OILBQcHO7UdAAAAAAAAAABUFo78/zwcDlc3AwAqJAIAFZzpCuZPmPNkZmbqkUceUVZWlp5//nk99thjdn1YWFiR+3t7e6tdu3b69ttvtW7dOqe3591339X48eNtuf/mzZvrnHPOUa9evVS3bl15eHgoNjZWCxYs0MyZM20A4aefftKDDz6ot99+Wz4+Pk5oAd9hAAAAAAAAAAAAgLsgAFDB0TXrXKaU/+7du9W4cWM99NBDpTqmYcOG9rGoKQJOhpmK4JVXXrFTAFx66aUaNWpUwWsd7uKLL7Zt/c9//qM333zTVisYPny4fQ8nj+8wAAAAAAAAAAAAwF0QAECVcqgTv1GjRnZ0f2n4+vraR9Nh70yzZ8+27QkNDdUHH3ygyMjIYvc125588kk7fcG2bds0Y8YMDRs2zKntAQAAAAAAAAAAAFC5EQBAlXKobL6ZAqC0du7caR9NR70zHTpv3759S+z8PyQkJESXX3653nrrLUVHRzu1LQAAAAAAAAAAAAAqPwIAqFLq1asnh8OhDRs22BDAsaoAZGZmauHChfYY55Tc/1edOnXsY2BgYKmPCQ4Oto+1atVyalsAAAAAAAAA4MTlielGAQCoGAgAoEoxnfgdOnTQsmXL9MILL+iZZ56xnfvF+fnnnzV//nwFBATozDPPdGpbunbtqoiICM2dO1epqan2NUpiwgjTpk1TUFCQzj77bKe2BQAAAAAAAABOHJ3/KH8l3NoHgCqNAACqFA8PD40dO1bdu3fXiy++qBo1auimm25STk6O3Z6Xl2crA2RkZOirr77S7bffbr9u27atPcaZwsLCNHToUL388ss2iGACCYemKDiaad+nn36qv//+WxdffLGaNWvm1LYAAAAAAAAcwjheAAAAoPIiAIAq57TTTtP999+vV155RQ888IAmTpxYEABYtGiRBg0apJUrV9ppAsz6Fi1a6LPPPpO/v/8JvV5ubq6SkpKK3HbjjTdq586dGjdunLZt26bLLrtM7du3V2RkpA0rJCQk2LZMnz7dBhJ69+6tJ554Qr6+vif8/gEAAAAAAEpC5z8AAABQeREAQJXj7e2tl156SU2aNNHdd9+tpUuX2mkAzLJlyxZt3rzZPjfVAE455RR9//33dt8TtXv3bjVo0KDYqQbM65jFdPBPmTLFrju0r1lvmBCBMWvWLDstwfr169WoUaMTbhMAAAAAAAAAAAAA90MAAFWS6WC/9dZb1bNnT/33v//VqlWrtHfvXmVmZiogIED16tVT165ddemll57wyP/DHerAL6k9Ziluv0OBgEPbDwUDAAAAAAAAAACoaqhWAwDFIwCAKq1Zs2Z68MEHban/7Oxs27FuOttNlQBTgt8ZwsLCNHr0aKec6xAzRQAAAAAAAAAAAFVVcVV3AaCqIwAApzLj0iv6n9xff/3VXhh069atYJ2np6ddirJu3TrFxsbasEBUVNRxv15gYKDuuuuuE24vAAAAAADHrTJ8QAcAAAAAOB0BADhVZbi3YMr6m9H9+/fvL9X+b7zxhiZPnqxRo0bpxhtvLNvGAQAAAADgDJXhAzoAAAAAwOkIAKDKSUxMPK7y/mlpafaYzMzMMmwVAAAAAAAAAAAAAJwcAgDAMeTk5NgpA44nNAAAAAAAAAAAAAAA5Y0AAFCClJQUxcTEyMvLSwEBAWXyGnl5edq4caMWL16s33//Xbt371ZqaqpdX5zx48crKiqqTNoDAAAAAAAAAECF5sj/H1MeAUCRCADAra1atUqzZs0qtN50rr/55pslHnvgwAEtXbpUf/75p/z9/VWvXj2nty8jI0OvvfaaPvzwQ+3YsUO5ubmF9jHVB44OA5iAAAAAAAAAAAAAAAAcjgAA3JrpvH/ggQdsJ/rRHnzwwWMebzrezbHdunVThw4dnN6+L7/8Ui+88IJ9jfbt26t69eqaMWOGQkNDdfHFF9tqAFu2bNGuXbtsOKBr165q2LChgoODnd4WAAAAAAAAAAAAAJUbAQC4NT8/P0VGRh6xbt++ffYxIiKi2ONMh7w51oz6P/fcczVkyBAFBQU5vX2vvvqqMjMz9eijj+rxxx/XypUrNXPmTFvef9KkSTaAYKYg+PXXXzV8+HAbBjCPJigAAAAAAAAAAAAAAIcjAAC3NmDAALsczsPDwy6xsbEuatVBa9assVMUmNH+zzzzjHx8fArtY4IItWrV0jXXXGNH/ffr109PP/20OnbsqLCwsPJvNAAAAAAAAAAAAIAKiwAAqpxBgwYVOSVAeVuyZIl97NWrV6HOfzPy35T8N0GFQ/r27aszzjhDixcv1tq1a9WpU6dybS8AAAAAAAAAABVFRbjPDwAVEQEAVDmmtH5FEB8fbx/NCP9DPD095e3trZycHKWnpysgIKBgm5eXl3r37q2FCxfqjz/+IAAAAAAAAAAAAKiSHP8s+Af/GAAOQwAAVY7pWN+zZ49NB9avX7/EfTMzM7V7927b+W466g8fkX+yqlevbh9TUlIK1vn6+tpO/7S0NDtFQcOGDY84JjU11T66evoCAAAAAAAAAAAAABUPAQBUOa+++qpeeuklnXfeefr2229L3Hf79u3q06ePHZE/Y8YMtWrVymntaNeunX3csGFDwbrQ0FAbDIiOjtbq1auPCABkZGToq6++ss8jIyOd1g4AAAAAAAAAAAAA7oEAAKoU04n+zjvv2A79kSNHHnP/OnXqqG3btpo+fbr+/PNPpwYAWrRoYc+/fPlyJSYm2s7/mjVrqkOHDtq4caOeffZZZWdnq1GjRjpw4IA++ugj7dy5U8HBwTaUAAAAAAAAAAAAAACHIwCAKsV0rJvy/82aNVPLli2Pub+/v786duyoH374QStWrHBqW8wUBOeff74mTJig//73v7ruuuvsFABPPPGEpk6dqkWLFmnAgAHy8/OzgQUzVUBubq4uvvhiNW/e3KltAQAAAAAAAAAAAFD5EQBAlWJG0Bv16tUr9TFmBL5hyvI722OPPaYLL7zwiFL/rVu31uzZs/XMM8/or7/+UkJCgjw9PW07evXqpRdffNEGBQAAAAAAAAAAqKocDle3oOLgnwLA4QgAoEoyI+mPd18zCt/ZGjdubJejdenSRV9//bViY2OVnp4uDw8PhYSEqFatWjYMAAAV1YYVS7Rw+ndKjNursMga6tz3UjVrc7qtenIsOdnZ2rxmuVYt/k3RW9YrKzNDEVF1dFq3PmrZoZM8ivj9t3/PLm1cuUybVi3T7u2b5RcQqIF3P65q1aPK4u0BpXIgJVk/ffeVli/53V4/tG5/hvoNuEF+/gGlOj47K1NrV/6tFX8t1poVfykpMV6nndVVg26+s8jrgMyMDG1Yu0orli3WquVLlJyYoMbNW+qe4c84+Z0Bx6dDy3q6Y0BPNWtQQ3v2JenzHxfp+3l/5/9clP5a3GhSr7puuqKLzmzTUF75PwObdsRq5m+rNXX2cmVlH3mN3qltI93Yr4taNq6lxOQ0zViwSuO+nJd/TZ/nzLcGAABw3LZsWKPp332p3Tu3KSw8Ut16X6AzOvco8rPu0fLy8rR/7x6tXbHUXvNv3bhOebk5Gv7iGIVFRBZ5zPMP364DyYmF1js8PNRv0K06s2vPk31LAACggiIAgCqlevXq9nHLli32hvyxOtPNxfXatWvt84iIiDJv3+FMh79ZAKAyyM7K0pypn2vW1x8pLKK6AkNCtWPjWq1e/JvOv/Zm9bikvw0zleSbD0fp95+/V0h4pELCIuxNkK1rV2r5b3PUsdeFuuymu+Xr51+wf15urt54+BalHUiWr3+AsjLSFRAUYtsCuMqe3dF67bnHtHXjetVt0EieXl76Ycrnmj1tqkaMHKUmzY89BdGn48fp2y8+sj8z5ns+LfWA6jdsUuz+H733ln785gt7XROY/zNgAgMBQcHOfFvAcfH28tQNl3XWKw/1076EA9q9N1GtmtbWpFeG6O1P5+iJt6YqpxSBXM/8n4FrLzxD/3mwn7KycxW9Jz7/uDyd1baRrjrvdP22dJN27T14U9vDw6H7ruutJ26/UPHJadoZE6/q4UF69q5LNOiSjhr08ARtid5X1m8dAACgEBN2nzN9qj55b5SCQ8NULf8z885tmzRm5Aidd/m1GnjL3fnXMiXfo9y7Z5deGn5X/ueNnfYzgvk8nJmZoezs4j//Rm/fbO9/1m1w5OAjD4dDXl50CwAA4M74S48qpVWrVgoODtaOHTs0YcIE3XrrrSXuv2/fPs2aNcvegG/Tpk05tRIAKp/VS37TjC/Hq3m7M9XvlvsVFBKqA0mJ+vqDN/TT5x8qql5DtTytc4nnMB3/1941Qg2at8o/PszeAElJitePn76vP2b/oOCwcF0w4JZ/D3A41OXcy1S7YVNF1qqjCS+PUE4JNz+A8vB/497UpnVrdNcjT+n0Tt1sp/yi3+bp7Vee06fj39Gjz74qXz+/Es/RqGlzXX/bPWresrW2bdmoCe+8UeL+TU9ppcG33p3/2FIBgUF6ZNj1znxLwHFr37Kenr7rYm3cvle3PDVJW6P3KSw4QM/ffanuGNBDf63doS9/WnzM81x1/ml6a8S1mrlglZ5790dbRcAEAEIC/VSrRqjiElML9j23Sys9OewiLV+3U0Of/kS79yXK28tLF/doo3FPD9Qjt5ynYc9+WpZvGwAAoEhm5P9XH72rqDr1NezhZ1Q9qrZSU5L1+YSxmjl1cv71fwt1Pef8Es9hOv3P7nuRqtespdr5n6/N+f5e8vsxX9sEkO9/6tVC6728fU74/QAAgIqPAACqFD8/P91999166aWXdOedd6pGjRo6//zz5evre8R+ZuR/TEyMXnjhBS1ZskTh4eHq3LnkjqvimHNlOXk0qre3d6nKaQNAecjJydZfv/1ip0zpfvE1ioyqY9f7BQSpd7/B2rpupeb98JWatz3TjoYuznnX3FRonSnpf/41Q2yZ/2ULZ9vz+fge7Dw1vwcvGjy0YF9zbgIAcKVN69fof/Nn66yuPXXO+ZcUrO957sWaO3Oa/l7yp/bERJc4mt/o3ueCgufp6WlyHGMmv17nXVzwPC01tYQ9gfJxaa+2igwL0qOvf6O/1+2065JS0vX4W1PV/czmeu7uSzX1l+VKzyj+d3b1akF64Po+2p+QoifGTNXmHf+O3k9KSdPOPfEFX5vLYjPVgPm78OToqVq3dU/Bto+m/k/XnH+6rjnvdD3y+hQl57cDAACgPC36ba6SkxI0eOj9atCkuV1ngrsDbr5La5Yv1pcT39GZ3XrJx8e32HOEhoWr36B/A/F+AaWbXswE6w+vpAcAAKoGAgCocu677z5Nnz5dy5Yt05AhQ2zH/jnnnKNmzZrZgIAZ9b9o0SL98ssvWrFihT3mnnvuUbt27U7o9eLi4nTdddc5rf3mxub48eMVFcX81gAqhpysLEVv3mBHEDRucWS1lBq16yukWoTiYncrMX6fwqsf/+8ub19fe3PDlE3MyswoCAAAFc2SPxbav9Ond+p6xHqz7pKrB2r5kj/0+/zZxwwAAJVdr44tlJGZrR/m/n3E+vikA1q1YZc6tW+slo2jtGzNjmLP0axBDbtMnr5EW3bul5eXp8KC/fPPkaqcnCOnD/Dx9lLDOvl/axIPKHZ/cqFzzV20Xud0amGDAOO/XuicNwkAAFBKq5Ytyr+W8dbpnbsfsd5UzqvXqKnWr/5b0du2qFGzFi5qIVBJ5X/WZpAcABSNAACqnMjISL399tvq37+/du3apWnTpumnn34qcl9/f38NHTpUTz755Am/Xnp6ug0cOFMqo/sAVCDZ2dmK379HUfUbyeeokQWBIaG2EkBc7C6lJiedUAAgKT5OKQnxiqxdz1YEACqqbZs2yNvHRxE1Cn+ft2rTwd6YWLNyhQtaBpQf831+SuOa2rRjrx31f7i0jKx/SvN7qF5UtRIDAO1b1JO/n48Wrdyqp+64SPcO7p3/tbdS0zL03uRf9drEmQVTAJhpAbKyc/LP62mDAkcLDTr4t6nnmacQAAAAAOXKVAaN3rFVUbXr2lH/hzMj/sPCI21Vvf1795RJAGDzhjW65/pLlRi/X+ERNXRWjz4695KrVS2iOh2nAACchLz8pSL/JSUAgCqpU6dOWrBggT799FN9/fXXWrlypTIzMwu2V69eXb1799agQYNsdYCTERQUpIceeuhkm1zAXJyHhYU57XwAcLLSU1OUnf87tFr1moW2eXp6yT8wyG43o/ePV1b+cdO/HK/MjHT1vmKwPR9QEeXk5OhASrId2eNXRIlNc7PPx9dX+/fGuKB1QPkJCvBVkL+vYvYlFtqWm5unhORUeXh4KCSo5FK0jepF2sdbrz47f18/vf5/s+wI/87tG+uuQb3UtUMT9X/wg/zXSVJ2do4WLtukm/t1Ud8uLbVq466C89QID9Y1F5xhnzeoHeHEdwoAAHBsaakHlJGeprCI6oW2mWsi8znBTKeXlv+52tkCg0JUp34j1apbX6aLYtvmdZo25VP9NmeGbrv/CbXu0NHprwmgPJmuxzxXNwKosipy57/BXXRUWfXq1dPw4cPtYkbUb9++3T7WrFlTderUcdrrhIaG6pVXXnHa+QCgojE3Mwxfn6JL85sR0eaGRm5uznGdNzcnR99Pekcb/l6sM3qer/Zdep10W4GyYr6/TQjABPU8PQuPQDZMOCA9La2cWwaUr0B/H/uYnpFV5PbMzGxTqdOO1i9JcMDBvykNaoer3z3v6n9/bbZfvz95vpJG9NfNV3bTdZd20qsTZtr1L777o/r1bq8X773MhhAm/fd3RVYL0isPXqnwkAD7dyg4oPh5dQEAAMrCoc/L3j5FX4d4e3ubMgHKzir62ulkjBz7iXz9/v2cnpd/PfTTd1/o0/ff1NeT3icAAFR6dP4DKB4BACBfQECAWrSovPNsLVu2TPv371fr1q0VFVV0ee3ff/9dP//8c7HnOOWUU3T11VeXVRMBuDE//wD7eOjGxtEyMzLk4ekpD4+SO3uO9uu0r/XnL9PUuFU7XXDtLSfdTqAseeZ/f5uO/7y8XFvCsyhZWZnyZxoLuLmU1IPVXkz5/qL4+nqbe9zKzCr65+SQ1LSD1blWb9ytJau2Faw35f6nzFqmG6/oojNaN5Cvj5cyMrO1Z3+yrQjw6C3n68Eb++rxoRfaaQF++X2trn9soiaPuk374pOd9C4BAABK59A0dqaqXVEys7JsiNjLu+hrp5NxeOe/4fDw0HmX9deihXO0YfXfit0drRq1nDcICgAAVBwEAAA38Pjjj2vGjBn67LPP1L9//yL3MVMePPnkk8We4/LLLycAAOCE+AUEyduUNo/dXWhbTna20g4ky9vbRz6+RVcIKMrvs3/Q1P97WzVq19Mtj70iX/+SS0UDrmZCLsEhocrOyv+eL2KUf0pykg3DVK9ZywWtA8qPCQAkHUhXnRphhbZ5eDhULfjgaPzE5JKrYezal2AfN2yPVWbWkRVktu+KU15uniLDguTl6aFDE8yYaQAuvXOsfLw9VTv/9ffGpehAWoYu6H6qPD08tHzdTie8QwAAgNLz9w/I/8wcoLh9ewptM9dEqfmfExz/TAVQHkxouUPHrlq38i9t2biOAAAqNVN+28PVjQCACooAAOAm8vJKLvlz9tlna+TIkcVub968ubObBKCK8PTyUnj1Wtqzc5udt9A/4N8bF8mJ8Uo/cED+QcEKDA4t1fmWzJ+p/04cozqNmum6B56h8x+VRqNmp2jBnJl2JM3R/l76p308tW37cm4VUP5Wb9yl009toIiwQO1POFCwPsDPx3bMm5H523bHlXiOlet3KTsnV6FBhf8G2OoCDocd+Z9bxCWwCQxsjd5f8PXACzsqJzdXX05fcuJvCgAA4ATVa9BUmzesVnJSgoJDwgrWm6oAcfv32qnCyjMonJKUaB/9+KwNAIDbIgAAtxUREWEfzzrrLE2bNq3Q+uP1xhtv6IYbbnBK21zB/DuYBQCczdysqNu4ufbs3KpNq/5S6zO7FWyLjd6mpPh9atKqnULCI495rnXLF2nyODPiP0A3PTJS4TWKntYEqIjO7NxdH783Wn8unKcLr/i3Io8J6X37xcfy8vZW5559XNhCoHzM/n2tOrVrrCv6dNCHXy8oWB8eGqi2p9SxI/PXbCpcNeZwm3bs1e69iWrVpJY9Li7x3yBB+xZ1bTWB7bvjlJlZ8lQC7VvU0xV9O+ivtTu1eOW2EvcFAAAoC61P66gNa/7WH/Nnq8/FVxasT0pM0PbNGxQcWk11GjQul7ZkZmZo/s/T8j/He6lF6w7l8poAAKD8EQCA24qPj7ePycnJRa4/XhkZGcfeCQCqIFP6/PTu52rZwtn65btPFRwWrmrVoxQfu1s/ff6hnc/wnH7XycPjYGE2ExIY+9TdatGhk2574tWC86xZ+rsmjXpWQaFhGnDX47ZMYmpKUsF2h8NDfv4BtjziIQn7Y21ZdSM3J9uWUDRTERwaEBpZs7ZtH1Ae6jVsrD4XXqZfpv+grz4Zr+69z7ed/vN/nq5N61brrG69FB5evWD/8WNf1/dffao7HnpS5158RcH6rMxMxe452Dm6f29s/vdznlJTU7Vrxzb7/RwYGKSw8H8DjWn528zIISMj/WBZdfNzEb3jYGenKTtaLSLS/iwC5eH7OX/r5iu76Z7B52jzzn1auSFatauH6bm7L5G/r7dueXKSHd1vnNq0tuZ//JDWbd2ji24fo/ikVLt+S/T+/PMs1y1Xna0HbuyrCd8s1IHUDDVvWEN3Deyl7OwcTZ6+xI7sP2TwJWdp9cbd2hkbL6/8n5XWzWrr6Tsuzr+Oz9ZrE2Yes2IWAABAWTizS0/Nmfatpn3zmWrWrqv6jZra6/cvJ4xVZma6bn/4aVua39i+ZaOeuvcm1anfSCNefluBQSF2vbmOidsXa6sGGOlpB6+ZYmOilZWVaZ+HR9aQr9/BUf2//PRt/ueAwPzPKE1swMB8ptgbs0vTpnxqK/V173tx/r6ln6YPAABULgQA4Lb+85//2Mc6deoUuf54MXoegDsw3X9l0f3RvN0Zuuq2h/TNh6P0/gsPycfH196YyMnOVr9bH1Djlm2PeY7fZk5VempK/jFZ+nT084U6K4NCwnTjwy8ovMbB0ojmBsh3E0Zr85q/7depyYl23Sejni3o9H/4jf+zgQSgvAy+9S7F7Nqpzye+qx+/+UIeDg8lJyUqskaUrh96j3x8fY95DtNx//SDt9vn2VlZ9udo+ZLf9cR9K+y6HudepCF3PFCw/8q/FuvtV561zw/1b27dtE4j7h5in5/RpbvueOBxO10HUB5WbIjW/S9P1vgXrtfnr96ilNR0+fv6KCjQVy++N00zFqw65jlMB/9TY75XVGSo7h3cS9ddepZdFxToJy8PDw15/GPNW7T+iGMeH3qBQoMDlJaeaf+GhOTva4IGtzz1sX6Y+3dZvV0AAIAS1W/cTDfc+bDGvfK03nz+URtsNyPxTSf+lYNuVYeO3Y55DvO5YOLbr2jj2oOfCdIOHKyO9OYLwwvC9nePGKlT8z+bG+tWLtf/5s6Uf0CgvHy87Y2AjPzP6GkHUnRq+zPU/6Y7yujdAgCAioC7gHBbDz/88HGtB4CqoKzGPnp4eKpTn4tVq35j/fXbLzpg5jYMC1fbTj1Uv1mrIzrzzQj/dp17qU6jZkeco0GzlnY6geL4BwbJy9vniHW1Gza1lQGK41nC+YCyEFYtQo+PfFML5szU+tUrlJOTq6antLSVAXx8jxxh06hJc3Xp2UdRtY4MK/oHBOjU9qcX+xp16jY44uuQ/J+pkvav37Axo/9RrnJz8/Td7L+0dkuMrr3gDNWrFa79CQc0/deVmrtovXIPG4mflJKmqXOWa1dsgjKzco44z4G0DA154iNd2L21enY8RUH+vtoRE6evZy7Vyg27Cr3ubU9/YverW7OaDYRt2LbH7rttV1yZv2cAAIDimA76s87ubUf1/zZnuvbFxig4JEztO3aznfGHX6sH5H/uPbNrLzua//DPxw4Phxrmf37w9i7+M25QcEjB82tuvF1tTj9L2zdvVFJinHJzchQWHqnWHTqqzWln8fkAAAA3RwAAAAA4TYPmrexSkpp1G+qGh54rtL7Pldcf12uZGxbnXn3jcR0DlAczyqbvRVfYpSTnnH+JXY5Ws1YdPfLMK6V+vVNObatHTi39/kB5Wbs5Rs+M/aHEfXbExGvI4x8Vuz0jM1vf/vyXXY7l1yUb7QIAAFAR1W3QWNfcWPLIe1M57M5HC39eNmGAq64fWurXiqgepW7nXJD/oeO4mwlUKoRZAKBoBAAAAAAAAAAAAAAAAHADBAAAAAAAAAAAAAAAABWGmUCQOh8nhgAA3NYdd5RcUut4DRw4UN26dXPqOQEAAAAAAAAAAAAcic7/E0cAAG7r3XffLfW+Rc0VlJeXd8TX7du3JwAAAAAAAAAAAAAAoMIiAAC31blz5yI79o3U1FStWrVKubm5CgoKUnBwsEJDQ+Xn56f4+HilpKQoMTFRWVlZqlu3rl1q1qxZzu8AAAAAAAAAAAAczdz592B4MAAUiQAA3NbChQuLXJ+WlqZhw4bp77//to+DBw9Wy5YtFRISYrebUMDOnTv1v//9T6+99pri4uLsdAKXXXZZeTb/uBUXdgAAAAAAAAAAAABQNRAAQJUzcuRITZo0ScOHD9eLL75YaLuHh4fq169vF1Pyv2/fvrr33nvVqlUrOw1ARfTII49o0KBB6tSpk6ubAgAAAAAAAAAAAMBFCACgStm7d6/eeustNWjQQM8999wx969du7b69eunl19+WT///HOZBgAyMjK0fPlybdy40U5DkJeXZ6cmaNy4sU4//XQFBAQUe2zPnj3LrF0AAAAAAAAAAAAAKgcCAKhS1q1bp5SUFHXu3Fmenp7H3N+U1W/Tpo2dFmDVqlVl1q6ZM2fq9ttvt1MPmI5/sxx6fbP4+/vr9ddf15AhQ2yFAgAAAAAAAAAAAAA4GgEAVClpaWn2MTY2ttTH7Nq164hjnWn//v166qmn9MEHHyg7O9uu8/PzU0hIiO34N2GFAwcOKDk5WcOGDdOPP/6oUaNGqWHDhk5vC9yLiZA4XN0IAAAAAAAAACgj3P8EgKIRAECVUrduXfu4cuVKzZ8/X927dy9xf9PxPm3aNPvcTAdQWqXtfB03bpzef/99W2GgWbNmeuKJJ9S7d28bAjBMKOCPP/7Qs88+q6VLl2rq1Kl228SJEwv2AYrCxS8AAAAAAAAAt+UwFXRd3QgAqJgIAKBKadGihXr06KF58+bp8ssvtx3wF154oYKDg4/YLycnRxs3btTYsWNtUCAgIEB9+vQp9euU5rojKSlJb731ln2twYMH2+fVqlUrtN8ll1yiiy++WE8//bRefvllWwXAtK1169albg8AAAAAAAAAAAAA90cAAFWKKas/fvx4GwIwpf1vvvlmWxWgS5cuNhzg6+urffv26c8//7RVAmJiYpSXl6fLLrvMjsx3JhNCMFMAREZG2qDB0SGEo9v92GOPafLkyVq/fr3mzp1LAAAAAAAAAAAAAADAEQgAoMpp3LixJkyYoEcffVSrVq2yHeobNmw4Yh/T6W863cPCwjRgwAC9+eab8vJy7o/L7t277WPfvn1L7Pw/xN/f3wYRXn31VRtMAAAAAAAAAAAAAIDDEQBAlWQ63du2bas5c+bos88+0//+9z87Gt8wHf+tWrXSRRddpGuvvdY+d3bnv1G/fn376OHhUepjDu1bp04dp7cHAAAAAAAAAIDKwEzDa+7lAwAKIwCAKqtmzZq2g98sRmpqqtLT0+2o/+PplD9RPXv2VPXq1fXLL78oMTFRoaGhJe5v2vfDDz/YagHOno6g8snTwUs8AAAAAAAAlDtuzQAAAFRYBACAfwQEBNilvPj5+enhhx/W448/rgcffFCjRo0qcSqAt956S+vWrdPgwYPVoEGDcmtnxcQnTLfDjQMAAAAAACoPPsMDAABUWAQAUKXl5OQoOTnZjq7Pzs62AYDIyMhye/1+/fpp8eLFmjhxolatWqXhw4fbqQl8fHzsdtOmTZs26fXXX9f06dPVqVMnPfLII4qLiyt0Lm9v73JtO+BU3DgAAAAAAAAAAAA4aQQAUGWZDvd3331XS5cuVWxsrNLS0nTppZfqnXfeKdhn3rx5mjx5sp0uwIzU9/T0dGobzj//fOXl5dm5iv744w9deeWVdgqCkJAQu+7AgQPav3+/DSqYaQliYmJ02WWXFTqPOcepp56qb7/91qntAwAAAAAAAAAAAFB5EABAlWM6y7/66isNHDhQubm5tmPddLabTvaEhIQj9jUd/19++aXdx4zWb926tVPbsmXLFvtozm8WIykpyS6HggFm8fI6+KO6ffv2Ys9lggMAAAAAAAAAAAAAqi4CAKhyli9frvvvv992sHfv3l1XXXWVli1bZsvwH61u3bpq166dFixYoBUrVjg9ADBu3Djbwe8MERERTjkPAAAAAAAAAAAVnQfTihbgnwLA4QgAoMq54447bCn9Tp06aebMmfLx8bFTARQVAAgKCrIBgDlz5mjNmjVOb8stt9zi9HMCAAAAAAAAAAAAqJoIAKBK2bZtm/744w9Vq1ZN3333ne38P5YWLVrYx5LK7wMAAAAAAAAAAACAqxEAQJWyadMmW/rflPKvXr16qY4xYQEjKSmpLJsGAAAAAAAAAAAAACeFAACqlKysLPvo7e1d6mPi4+Pto7+/f5m06WgZGRkF7SxOQECAPDw8yqU9AAAAAAAAAAAAACoHAgCoUg6N+o+Oji7V/qZawNKlS+3z2rVrl1m7tm7dqjFjxmjWrFlKTExUbm5uifsvXLhQ9evXL7P2AAAAAAAAAABQkTkcrm4BAFRMBABQpZx66qmKjIzUhg0bNHfuXPXs2bPE/Tdu3Kg5c+bYigGnnXaa09uTnJys0aNHa+TIkUpPT7eBg9LIzs52elsAAAAAAAAAAAAAVG4EAFCl+Pr66qmnntK9996rAQMG6KefflL79u2L3NeMyr/uuuu0adMm1axZU926dXN6ez7++GM999xztpz/wIEDVatWLb3++uv29Z544gnFxMRo2rRptgqBCSEMGzZMbdq0KahkAAAAAAAAAAAAAACHEABAlXPTTTfp22+/tRUALrjgAg0ZMkSxsbF22549ezRlyhT98ssv+vzzz5WQkKCgoCC9+OKLqlevnlPbkZOTo7feesuO5n/hhRf0yCOPaPHixTYAEBoaqjvuuMPu9+yzz9oQwEMPPaT33ntPX331lW0TAAAAAAAAAAAAAByOAACqnMDAQH3wwQcaOnSoZs+erZdfftmudzgcmjdvng0GHCrFHxISotdee0033HCD09vx999/2+oCZtS/qUjg6elZ5H6mXRdddJFt94UXXqhnnnlGXbp0UXh4uNPbBAAAAAAAAAAAAKDyIgCAKqlx48aaOXOmPvzwQzuqft++fUpLS7Oj8r28vBQcHKx27drZMvzFTRFwslasWGGDBqYzPyAg4IhtZr1py+GhgJ49e+qss87SggULtH79enXq1KlM2gUAAAAAAAAAQEXmcLi6BRUN/yAA/kUAAFWK6VhPT0+3z/39/XXrrbfq+uuv186dO5WYmGjL8fv6+qp69eqqWbNmsaPynSElJcU+RkZGFqwz4QNvb2/bDhNIOLrUvwkBmCoFv/32GwEAAAAAAAAAAEAV5ZAHKQAAKBIBAFQppvO8d+/eioiIUExMjDw8PGyHf5MmTcq9LYc6/g8FAQzTFlPq34QUYmNjCwUAkpKS7KPZBgAAAAAAAAAAAACHIwCAKiUzM9NWAWjdurXt/HelM844Qw6HQ6tXry5YV61aNUVFRWnLli1asmSJnargENPp/+2339rnjRo1Kvf2AgAAAAAAAAAAAKjYCACgSjGd60ZOTo6LWyLbuV+/fn399ddfSkhIUFhYmG1fu3bttHbtWt1///0KDw/X6aefbqcDuPPOO7V9+3ZbFaBv376ubj4AAAAAAAAAAACACoYAAKqUFi1a6JRTTtGqVau0f/9+OxWAK1100UV65513NHnyZN12223y9PTUE088oT///NNWATj33HPl7++vjIwM5ebm2uoFN910k+rUqePSdgMAAAAAAAAAAACoeAgAoErx8fHR//3f/6lHjx668sorNWvWLHl7e7usPWPGjNHo0aPtVACHtGrVSgsXLtRVV11lH1NTU+16EwQYMWKEXQ7fHwAAAAAAAACAqsTcIXftJL8AUHERAECV4+fnp2HDhtnO9/POO0/XXnutrQpQrVo1OwK/OLVr17b7OJPpyC+qM79mzZqaN2+eNm7cqJiYGHl5eal58+aKjIx06usDAAAAAAAAAAAAcB8EAFDldO/e3ZbSN8vcuXP166+/ytfXt8TOf+PNN9+05ffLi4eHh+30NwsAAAAAAAAAAAAAHAsBAFQ5ycnJBaPuzWNubq7S0tJKPMaEBbKyssqjeUDVk6eDNbsAAAAAAAAAAABwUggAoMqZM2fOCR1XliPxf//9d3322WdatmyZ4uLilJOTU+L+s2bNUr169cqsPUC5ovMfAAAAAAAAAADAKQgAoMrp0aOHq5tQYPPmzXrooYc0depU+7WpNFAaVCMAAAAAAAAAAFRlDgYWAUCRCACgSsjMzLQj///88087wr5GjRrq1q2bOnfuLC8v1/0Y3H///frxxx/t84iICHXs2NG2zdPTs8TjgoODy6N5AAAAAAAAAAAAACoRAgBwe3PnztXdd9+t1atXF9rWtWtXjR07Vm3atCn3dq1du1bff/+97ew3QYCnn35aQUFB5d4OAAAAAAAAAAAAAO6BAADc2oIFC9S/f3/t27fPfn14iX2Hw6GFCxfqwgsv1LRp08o9BGBe2+jQoYNeeOEF+fr6luvrAwAAAAAAAAAAAHAvBADgttLT0/XEE0/Yzv+AgAD17t1b1113nerUqaNNmzZpwoQJ+v333xUdHW2rAJjlWKX3ncnxzwRFJgBA5z8AAAAAAAAAAACAk0UAAG5r8+bNtqPfdK6PHDlSd955pzw8POy2Tp066dprr9WIESP0+uuv688//1RSUpKqVatWbu07++yzbXu2bdtWbq8JAAAAAAAAAIA7ODTIDgBwJAIAcFt79uxRXFycGjVqpKuvvrqg8/8QM9r/5ptv1ttvv2074dPS0so1ANCsWTP16dNHv/zyizZs2GC/BgAAAAAAAAAAJXP8s+Af/GMAOAwBALgtMwVARkaGwsLCVL169SL3MeEALy8vpaSkKCcnp5xbKL344ovq37+/rr/+er3xxhvq3LlzubcBAAAAAAAAAAAAgHsgAAC3ZTr0c3Nz5e3tbUf7F+XQtqysLLtveTv99NP1+++/69JLL1W3bt3Upk0b+3isSgQPPPBAuVYrAAAAAAAAAAAAAFDxEQAAXMhMUWCmIIiJibFfr1ixwi7HctNNNxEAAAAAAAAAAAAAAHCEChwAyBOTlsDdjRw5UqNGjbLP8/LyXNwaAAAAAAAAAAAAAJVZBQ4A0PmPk+dwOLRy5UpddNFFxe5z4MAB+2hG1fv7+xe731133aULLrjAaW2Ljo7Wu+++a59fccUVuuOOO9S+fXuFhYXJw8PDaa8DAAAAAAAAAIBbcZj7/65uBABUTBU4AAA4R3x8vKZPn17iPiYoMG/evGK3m9H5l112mVPb9fPPPys1NVUNGzbUpEmTSgwfAAAAAAAAAAAAAMCxEACA24qMjFSfPn2cdr66des67VxGTk6OfezZsyed/wAAAAAAAAAAAABOGgEAuK0zzzxT33zzjdPO5+vr67RzGW3atLGPh6YgAAAAAAAAAAAAAICTQQBAebKTxcDteHp6KjAw0NXNKJYJKJx22ml2KoA9e/aoZs2arm4SAACVnLmmy3N1IwAAAAAAAADAZQgA0PkPF3ruuec0aNAg3X777Ro/frzCw8Nd3SQAACoxOv8BAAAAAKgqPOjeAYAiEQAAXMh0+D/44IM2CNCpUyfdcsst6tChg4KDg0s8zuzj7CkJAAAAAAAAAAAAAFRuBAAAF+rSpYt9dDgc2rRpk4YPH37MY8y+GzZsUOPGjcu6eQAAAAAAAAAAAAAqEQIAgAtFRESc0HGenp5ObgkAAAAAAAAAAACAyo4AAOBCM2fOPKHjatWq5eSWAAAAAAAAAAAAAKjsCAAALtShQwdXNwEAAMC5HPlLnqsbAQAAAABwZw5XN6CC4d8DwOEIAAAAAABwHjr/AQAAAADlwMNBtzcAFIUAAAAAAAAAAAAAAAAAboAAAAAAAAAAAAAAAAAAboAAAAAAAAAAAAAAAAAAboAAAAAAAAAAAAAAAIBSy87OVmxsrJKTk+Xj46Pq1asrKCjIKedOTU1VXFycUlJSlJeXJ19fX9WoUcNp5wfcHQEAAAAAAAAAAAAAVB6O/P85XN2Iqmvz5s168cUXtW7dOmVlZcnDw0OhoaG67rrrNGjQoBM+79dff62ffvrJnj8zM9OGDEwAwNPTUwEBAerVq5eGDRumiIgIJ74bwP0QAAAAAAAAAAAAAABwTNOmTdOIESOUlpZmR+RHRkba51u2bNFzzz2npUuX6sknn1RYWNhxn3vcuHHauXOnvLy8FB4ermrVqsnhcNgqA9HR0Zo0aZLmz5+vkSNH6owzznD+mwPcBAEAAAAAAEA5yJMdpgMAAAAAqJRMyf8XXnjBdvh36NBBTzzxhA0AmCoAP/74o8aOHWtH8Ddq1Eh33XXXcZ+/YcOGuuqqq3T22WcrJCTElv430tPTbcf/66+/rm3btumBBx7QN998Y18bQGEEAAAAAAAA5YDOfwAAAACorHJycuzI/v3799vO+Zdeesl29B8yZMgQbd26Vd9++60dqT9w4EA7iv94jB8/vthtZnoBUxng2Wef1Z49e2wA4Lbbbjvh9wO4MwIAAAAAAAAAKBlFPAAAAKq0TZs22VH4hunsP7zz3/Dx8dHQoUM1depUJSQk6JNPPtE999zj1DZcffXVGj16tOLi4rRixQqnnhtwJwQAAAAAAAAAUDI6/wEAQAViLk08uD4pV0uXLlVubq7t6Dcd8UUxoQAzNcCSJUvslADDhg2Tt7e309pgKgAEBgbaAIBpC4CiEQAAAAAAAAAAAAAAUKS8vDxb3t+oW7eu/P39i923Y8eONgCQmJhoS/Wb/Z1l+/btiomJsc/btWvntPMC7oYAAAAAAAAAAAAAAIAi5eTk2M58IzIy0o7EL07jxo3tY2Zmpvbt23fSAQATPsjOzrbneuihh5SVlaVatWqpf//+J3VewJ0RAAAAAAAAAAAAAAAqqX379uqAl8dxH2dG8gcHBx9zP1NuPzk52T4PCgqSh0fxr1WzZs2CYw4cOHDcbTLS0tI0evRoZWRk2PCBqSawcuVK7dy5U126dNHDDz+s0NDQEzp36eWJebBQWREAAAAAAAAAAAAAACqpSy+9TOnJCcd93KBBg/TUU08dcz8zCt+M6Dd8fHxK3DcgIMA+mgDAoWOOl+n4nzx5slJSUo5Y36dPH40YMcJWACh7dP6j8iIAAAAAAAAAAAAAgErFQQdtuTId+obD4bBLcQ6vDnDomOPl5+enO+64wwYITMn/2NhYLV68WLNnz7aPQ4YM0a233lpiJQKgKivbAADVMQAAAAAAAAAAAIAyU9ZdcabD/9DI/+zsbFsRoDjp6emFjjleJgBw8803F3xtXs9MJ3Dffffp119/1ahRoxQZGakrr7zyhM4PuLuyDQDQ+Q8AAAAAqITMx9nib2kBAAAAQMXx3++/l7/X8XfK+fv7l2o/05l/qLR/ampqiSP74+Li7KMZnW868p3BvH5QUJDGjBmja665RuvXr9dXX32l8847z64HcCSmAAAAAAAA4Ch0/gMAAACoLCIiIhTo41lm5/f09LQj7o34+PgSAwA7duywj97e3rZdzmQCC3369LEBADMtwP79+wkAAEUgAAAAAAAAAAAAAACgSGY0f7169ezz6OhoZWRkFFs9YMmSJfbRVAyoUaOG09sSHBxsH3NycuwCoDACAAAAACfKDA9lyiMAAAAAAAC4uTZt2tjHxMRE/e9//9MFF1xQaJ/k5GQtXLjQPj/rrLPKZHT+zp077aOZXsBZUwwA7oYAAAAAwImi8x8AAAAAAKDcmVsyHtyXKVcmAFC3bl3bAf/222+ra9euCgkJKdhupgX4/PPPlZaWJh8fHw0cOLDQORYvXqykpCSFh4fb85mpBQ4xx5kOfYej+P/HmukFZs2aZZ+bigTOnmIAcBcEAAAAAAAAAAAAAAAUy5T8f/nll3XDDTdo48aNevXVV/X4448XjML/7bff9H//93/2+bnnnqu2bdsWOsd//vMf/f333zY8MHbs2COmEfj++++1atUqXX/99WrSpEmhY01lgZEjRyo2NtaGBIYMGSJfX9+yebNAJUcAAAAAAAAAAAAAAECJzjzzTN10002aOHGiJk+ebKcCaN26tfbv369FixYpLy9PTZs21bBhw0ocyV+U+Ph4ffHFF/ryyy/t6P5mzZopLCzMTiuwfv16bd261e5nqg7cc8896tKlSxm8Q8A9EAAAAAAAAAAAAAAAcEy333676tSpow8++MCW5DeLYUbjn3feebbzv1GjRsd93tNOO03du3fX0qVLtX37drsczlQL6NGjhwYMGKAzzjjDKe8FcFcEAAAAAAAAAAAAAAAcU3BwsAYOHKj/Z+8+AKSo7j+A/67SewfpNsAG2FFUbLFFEzWWWKLGRI0mmqjRFBP9GzUaExVLLLEkamKLRo2KFXvBig1pivTe4eDa/2YQIt5xgN7d3h2fD5nM3szs27fn3u7OvO9777vf/W68//77MXny5GjatGn069cvOnXqVOl977vvvjXuS0YXSJbly5enUwxMmDAh5s+fH40bN46OHTumIw0kt4G1EwAAAAAAAACgzkgGl89evxHmqWINGzZc1WhflfLz86Nv377pAnw9AgBAaklhcRQWl2a6GpBx+bnZma4CZFz2es7RBvVRi2aNokOb5pmuBmTc9NkLM10FyLic3NzIyXMJjQ3bsqKSTFcBAIB15OwFSN355pR46dO5ma4GZNxfD9sy01WAjHNxDyKu//WRkZ97VKarARnXaIdzMl0FyLhuW24WG2+3VaarARl1SL+OsWVH4UgAgLpAAAAAAAAAAAAA6gEBAAAAAAAAAACoBwQAAAAAAAAAqDuyssr+l5XpWgDUSgIAAAAAAAAAAFAPCAAAAAAAAAAAQD0gAEDNKS1bjMgDAAAAG57kekBppisBAABQ/wkAUHM0/gMAAMCGSeM/AABAjRAAAAAAAAAAoE7R5/B//C6ALxMAAAAAAAAAoE7J0uoNUCEBAAAAAAAA2JAkU7NoPAWAekkAAAAAAAAANiQa/wGg3hIAAAAAAAAAAIB6QAAAAAAAAAAAAOoBAQAAAAAAAADqjGQWiyxTWQBUSAAAAAAAAAAAAOoBAQAAAAAAAAAAqAcEAAAAAAAAAACgHhAAAAAAAAAAAIB6QAAAAAAAAACAOiUr0xUAqKUEAAAAAAAAAKg7ssr+lyUCsIpfBfAlAgAAAAAAAAAAUA8IAAAAAAAAAABAPSAAAAAAAAAAAAD1gAAAAAAAAAAAdUYy5X2Wee8BKiQAAAAAAAAAQJ2i/R+gYgIAUE0mTpwYv/rVr6q0zBtvvDEaN25cpWUCAAAAAAAA9YMAAFSTefPmxd133x2lpaVVVubQoUMFAAAAAAAAAIAKCQBANWnZsmUcffTRVVZeVlZW5OfnV1l5AAAAAAAAQP0iAADVpGvXrvGPf/wj09UAAAAAAAAANhACAADAN5RVtlTddCcAAAAAsDZZWZmuAUDtJAAAAHxDGv8BAAAAAKA2EACADCopKYkxY8bExx9/HDNnzoyCgoLYf//9o3fv3un+0tLSWLBgQRQWFkaTJk2iUaNGGa4xAAAAAAAAUFsJAECGJI3/p5xySjz44IOxaNGitJE/2da1a9dVAYDk5wsuuCD+9a9/xUknnRQXX3xxZGdnZ7jmAAAAAAAAQG0kAAAZ8Nlnn8WRRx4ZI0aMiJycnLTRf8aMGbF48eLVjkv2DRkyJIYOHRpPPPFE/OY3v4nGjRtnqNYAAAAAAABAbSYAABnwpz/9Kd58883o0qVLXHfdddG/f/846qij4uWXXy537F577RUNGjSIjz76KObPny8AAAAAAADABi2rbMlO/x+ArxIAgBqW9PK/66670qH8r7/++jjwwAPT7fn5+RUe36RJk9hll13imWeeiddffz0OOeSQGqwtAAAAAAAAUFcIAEANe/7559Oe/DvuuGPst99+63SfLbfcMg0AjBkzppprBwAAAAAAANRVAgBQw8aNG5eut91228jJyVmn+6wc9n/JkiXVVi8AAAAAAACgbhMAgBrWqFGjdL106dJ1vs/HH3+crjt06FAtdQIAAAAAAADqPgEAqGHJcP5ZWVnx4osvRlFRUeTmVv5nOGfOnHj88ccjOzs7tttuuxqqJQAAAAAAAFDXCABADUuG/u/evXuMGTMmHnjggTjiiCPWeGxxcXFcddVVsWzZsth4441j8803r8GaAgAAAABALZRV9r+sTFcCoHYSAIAalpOTEyeddFL87ne/i7PPPjs6d+4cAwYMiJKSknR/0uhfUFAQixYtiiuuuCL+/Oc/R2lpaRx22GHRuHHjDNceAAAAAAAAqK0EACADkgDAK6+8Ek888UTss88+aQAgGREgce2118att94a7733XkyZMiXdtvvuu8cZZ5yRTh0AsDalkYagAQAAAACADYwAAGRAx44d47///W/aqH/jjTfGa6+9lm5PGviff/75Vbezs7PTKQLuuuuuTFYXqGM0/gMAAAAAwIZJAAAy6Kqrropjjz02nn322Rg1alTMnTs3nQqgWbNmsckmm8Ruu+0Wu+66a6arCQAAAAAAANQBAgCQQTk5ObH99tunS3Fxcdr4X1pamvb8T/YZ8h8AAAAAAFaXXDnPdvl8Fb8K4MsEAKCWSBr8kwUAAAAAAADg6xAAgFqgsLAwPvnkk5gyZUo6AkDHjh2jT58+kZ+fn+mqAQAAAAAAAHWEAABkSFFRUTz99NNxxx13xLBhw2L+/Pmr7W/WrFnsueeecfzxx8d+++0XeXl5GaopAAAAAAAAUBcIAEAGLFmyJH7yk5/Egw8+GAsXLky3JT3/v2zBggXx0EMPxVNPPZUGAe68885o0qRJJqoLAAAAAAAA1AECAJABV155Zdqgn5WVlQ71P2TIkNhjjz2ic+fO6bZp06bFCy+8kI4Q8PHHH8d//vOf+O1vfxtXXHFF5OTkZLr6AAAAAACQQVmRnZWV6UoA1EoCAFDDli1bFtdee22UlJTEkUceGZdddll07dq13HHf/va30yDARRddFDfeeGP8/e9/j1/96lfRtm3bDNQaAAAAAAAAqO0EAKCGPfHEEzFz5sxo2bJlXHPNNdGmTZs1HtuxY8e45JJL4p577ok5c+bE448/Hscee2wN1hYAAAAAAACoKwQAoIZNmDAhXR9wwAGVNv6vlAQFDjvssLj55ptj4sSJ1V09AAAAAAAAoI4SAIAatnK4/6ZNm67zfZo1a5auu3TpUi11AgAAAICaUhrJ7N0AAFQHAQCoYbvttlvaq/+pp56KpUuXRqNGjSo9ftmyZfHII4+kIYDkvgAAAABQl2n8B6pCljcTgAoJAEANa926dRx77LFx3XXXxRVXXBHnn39+5OXlVXhscXFx3HTTTTFmzJg45phjYqONNqrh2gIAAAAAQO2i7R9gzQQAoJokjfcLFy6scN8pp5wS06dPjyuvvDJt3D/ooINiq622ijZt2qT7582bF++//3489thj8cADD8SBBx4YZ599duTk5NTkUwAAAAAAAADqEAEAqCYff/xxDBgwYI37S0tLo6SkJO6666745z//GdnZ2avtT/YlS1ZWVjz++OMxbNiwNDSQTB8AZIAJCgEAAAAAgFpuHQMAWj1gfSUN/EVFRZUekzTuJ8vKxv6K9ieS0QSSBcggH4MAAAAAAEAtt44BAK0esL46d+4cV199dZWW2ahRoyotDwAAAAAAgDpKH24qYAoAqCZt2rSJM844I9PVAAAAAACA+iUrIjtLqydo/KciAgAAAAAAAAAAUA8IAAAAAAAAAABAPSAAAAAAAAAAAAD1gAAAZEhpaWmMHj06RowYEa+//npMmzYtli5dmm5fk3vvvTeaNGlSg7UEAAAAAAAA6goBAMiAgoKCuPjii+Mf//hHTJ48OUpKSsodk5WVVS4MUFhYWFNVBAAAAACAWisrK9M1AKidBAAgA2699da4/PLLIy8vL7bZZpto3rx5DB8+PNq3bx9DhgyJqVOnxqeffpqOCpAYPHhwdOnSJfLz8zNccwAAAAAAyCxt/wBrJgAAGXDNNddEcXFx/Pa3v41zzjknnnvuuXj++eejV69ecffdd6c9/6dMmRLPPvts/PrXv47x48fHb37zm2jcuHGmqw4AAAAAAADUUgIAUMM++OCDGD16dLRs2TLOO++8dBSAr0qG/096/B977LHRqFGjOOKII+LCCy+Mxx57LBo0aJCBWlO/JFNLyMgCAAAAAADUNwIAUMNef/31dL3PPvusavzP+mKyoqTnf0lJSWRnZ686/uCDD44tt9wyXn311XQkgD59+tR8palnNP4DAAAAAADURwIAUMPmzJmTrjfaaKNV23JzcyMnJyeKiopi+fLl0bBhw1X7kpBAEhYYOXJkvPLKKwIAAAAAAABs8LLXfgjABkkAAGpY+/bt0/XChQtXbUuG+U8a/ZNtSUCgc+fOq91nyZIl6XratGk1V1EAAAAAAACgThEAgBo2cODAdD1q1KhV29q0aROtWrVKG/jHjRu3WgCgoKAg/vnPf6a327VrV7OVBQAAAAAAAOoMAQCoYf369YuOHTvGW2+9FQsWLIjmzZtH9+7d0+3Dhg2LX/3qV3HeeedFt27d0v233HJLzJ07N1q0aBHf+ta3Ml19AAAAAAAAoJYSAIAalpWVFbvvvnvcc8898eSTT8Zhhx2WTgHwhz/8IZ577rl4+eWX44gjjkinBCgqKopFixal90u2denSJcO1BwAAAAAAAGorAQDIgAsuuCBt+N9kk01Wbevfv388+uijcfHFF8f777+f9v7Pzc2NXr16xZAhQ9KAQE5OTjXUprRsyaqGcgEAAAAAAICaJAAAGbD55puny1clDf0DBw6MWbNmRUFBQWRnZ6dD/3fq1Cm9XT00/gMAAAAAULcko+0CUJ4AANQiyReWli1bpgsAAAAAAADA+hAAAAAAAAAAAIB6QAAAqklpaWkUFhZWaZn5+flVWh4AAAAAAABQfwgAQDWZMGFC/OQnP6my8pLpAe65555o0qRJlZUJAAAAAAAA1B8CAFBNFi5cGE888UQ6EkBVqeoRBQAAAAAAoK7J+mJhBb8L4MsEAKCatGvXLn7xi19UWXnJCAANGjSosvIAAAAAAACA+kUAAKpJx44d4/LLL890NQAAAAAAAIANhAAA1GEjRoyIBQsWRP/+/aN169aZrg4AAAAAAABVIJlg2vQOfB0CAFCHnXHGGWkI4Iknnoi9994709Uh/vdhXPoN77+2Mtb2of91Hx+qQmnp/16ByfQlNVFGVTwmVLWVr8v0FVkDfwtfPnZdjgegZqx4O07+rzRKv8EX9S+Xk/hqWevyefPVzwqoSd/0fPnrlLWu59hQY8reh1e+Fr/29/V1LGNt7/nOFwBqP+/UfF0CAFDHuYCTeQ1zs2Nwr9axS69W0bl5gygu+28ycV5BPDtmdrzx+fwoKln7f6PDt+4YfTs2jbZN8qNxXnZ6IjdncWF8OG1RPDV6VkxZsGzVsZu0axy/2K1nNM7PWWN5L4ybE7e8Pqkqnh6ss0kTP4+bb/prvPLSi7Fgwfxo0aJlDNpl1zjxhz+Ort26rVMZxcXF8c+7/hGP/OfBmFhWXnZ2dmy+ed/43lFHxz777rfascn733VDr4pRH38U48eNi2nTpkbLlq3itr/fHd179KiGZwhrV1hYGE898Vg8eP89MW7smCgpKY4evXrHAQcdEt/+zqHRoEHDdSpnzOhP4h+33RJvvzUi5s2dE23atosddhoUxxx3QnTr0XPVccnfzL3/vDOef/bpmDxpYvq3V1JSEm3atI3+224XRxx1bGzet191PV0AKtGzS5s474Q9Y5+dNotWzRvHnPmLY9irn8Tltz8bn06evc7l9Cor55TDB8VeO24aPTq3LnufL42psxbE8BFj45dXPxJLCpanx910wZFxzAEDKy1r71NuiJfeGf+Nnhesj9ycrNitd5vYr2/76NG6UWSV/Zs4b2k8/cnMeHLUrFheXLLeZQ7u3Tp+MaR35GZnxV1vTo6735q82v5tu7aIXcqO6daqUXRt2Sg9d35/yoI475FRVfW0YL3NmTk9/vvAP+Ld11+KeXNmReOmzWLzLfrHAYcfFz023nyt91+yeGE88+gDMXbUyJj8+Wcxa/qU9Jz4ytseirbtO5U7/r7br49H77uj0jLPuuDK2GaHXb72c4LaQOMoQMUEAAC+oV17tY6jBnSKqQsK4ubXJkZebnZ8d8sOceL2G6WN/0kIYG16t20ck+YVxPCxs2P24qJo2iA7dunZKvbctE30bNMo/u+pcVH8RZAgCRdc/tz4yP5KUju77MeDt+gQ/To2jbGzllTLc4U1mT17Vhx/7NGxcMH8OOroY2Lb7XeMl14YHvfd+68YOfK9uPue+9ep4XPoVX+OO/9xe2y62WZx4cWXxaJFC+OGa6+J35x/buTl58cee+y56tjkYse99/yz7DEXRK9evSO/QYPqfIqwTl5/5aX44x9+H02bNo2fn3t+NGnaLG696Yb4yxWXxpKlS+K4H/xwrT1tli5ZEv/3u1/F6FEfx/eOPCZ22W33eObJJ+K/jzwUEz4dH5dfdW0asEkkAYCPPnw/2rZrH3vu863o0rVbLF+2LA0EJEGE4c88HX/7x7+iV++Na+DZA7BS+9ZN47lbfhKtmjWK6+55KZ5/a1zsN6hP/OjQnWL7LbrFoOOvjoLlRWstp2mjBnHfn34QfXp2iLseeyt+e91j6XlAUsZuAzeOBvm5qwIAl932VPztoVfLldGsccN46C8nxfQ5C+PV9z6r6qcKlRrYpUWcvmuPWLS8OP768oRYUrY+emCX+PGg7tEwNyceeG/qevXM79i8Qfxk155RWFQSuWsIxW/brWXsvVm7WFpYHJ/MWBTblNUBMilpvL/20vPjs7GjYuc99ovtd90rRn3wdvz3vr/Hp2NGxR+uvysaNGxUaRmLFy6MF556OGZOmxLtO20Urdq0jzmzpq/x+D32/05ss/2gctuXLSuIP11wZnqestW2O33j5wYZVfadyEgWABUTAAD4Bprm58RB/drFrMXL4/LnPo15S1dcxPt8bkH8eq9ecUDfdjHi8/lrvaDxx2fGlzsmCQ4kIYKkd8MWHZvGe1MWptsLCkti/Oyl5cpo3jA3WjfOS/ePmrG4Cp4drJukIf7f998bc2bPipN/fFqcctrpac/9XQfvFm3btYsbb7gubr3l5nR7ZSdmn4z6OB64/57YdLPN49obborWrduk2/v22yLOOO1Hcc2f/xTbbN0/WrVunW5Pyrp66PXRo2fvaNWqVRz4rb1iyRLhFzInCaxcefkl0aJly7jptruiY6fO6fZNNt0sTv7B0fHogw/Ewd85LB2pojL3/PPOGPPJqDj9Z2fH948/IX2tD9h2+8jNzY2H/n1fvPzi87H/gQenx+bn58dFl1xR7m9r9yF7Re+NN4nrh/4lHn7o/vjZz3/pwghADUneb0/6zo7RoXWz+MMtT8Ulf3sq7bU/7JVRaSP8r0/aO35x3B7pvso0bpgfd15yTFrO4efcHv998aNV+x554cMvHut/x4+bODtdvuqnRw8u+26WFXc8/EYUl6x/b2v4upqUnS//eJfuMb+gKM75z0cxc9GKsMqns5fEnw7pG/v2aRfDPpkZCwvWHoZJJC/3Q7bsGMuLitMR9w7bpnyv58Swj2fGEx/PiMnzCyIvJzvuO6HykTGgur37xssxYfzo2Gn3b8XxP0nC7Q3SxvdOG3WP24deFv/465Vx0s9+Xen39eZl5xA/PvvCtLd/i1Zt4rpLf1VpACA5rqKRAV4dPixKyz4Ltt5uUGTnrHlkSQCgbhMAAPgGduzeMlo2yovb3pi0qvE/8fncpfHKZ/NiyMZtolebxjFuduWNkhUFBJIO/yOnLEwDAF1aNFwVAFiTLi0aRKfmDeL9qYti+qJllR4LVWn58uXx+msrepsdeNC308b/lYbsuU86CsCLLwyP7x97XDRvvubeN2+//WYsXrw49hiyV7Rq1XrV9o033iS22mqbeOXlF+Pjjz+KnQetGKIwuTjSf8C21fSsYP299spLMXXK5Dj2hB+uavxPbNS1W3z3sCPj1ptviHffeSt232OvNZZRWLg87rzjb9Gpc5c46tjjV10ETBr/Tz3jrHjk4QfjgbK/qZUBgMSaLhR279krvd+cWbPToI4AAEDNSHrlD9luk/T2P594O238X+k/z70fJ393p9h/l77pyADzFpYP9q60/ZbdYtcBveLh4R/EsFcrHrp8bTPCJSGCI781IOYvKojHX/54/Z8MfAMDuraIDs0axH3vTFnV+J+YumBZPPbRjDhqYJfo16FpvDZh3jqV17Ps3HqvzdrGJU+OTUcCWJNP5/zv/DtP+ya1wDuvvRBFhYWxz8FHpI3/K22z/S7RuWuPePvV5+O7x/woWrdtv8YykhECNt58y29Uj+Kionjn9Rcjp+wcYcsBO3yjsgCA2k0AAOAb2KZLsygsLokxM8s38L8zeUHsuUmb9Ji1BQC+Kj8nO9o2zYt9Nm+bTiMweubae/Tvs1nbdD7F/340Y60XAqEqFRUVxqfjx0frNm2ja7fuq+3r0LFjtGzRMubMnh2zZ82qNAAw5pNP0kbKLbfaerWGypycnNhiy63imaefjImfT4gYZI5Caqf33n4rfb1uvnnfcvuS4fn/dtP18epLL1QaAPh03LhYtHBhDNx2+7SsL2varFlssunm8fGH78eSxYujcZMmFZaRhAhmzpwZLwx/tux2YfTo1Xu1YA4A1Ss/Nyc27d4+ps9eGOMnrd4jf9L0+TFn/pJ0ioCkZ39lAYDt+naLRg3yY/ibY2OzsvL69uoYLZo2jKmzFsT7Y6bG59PmrrUu/Xp3jO4dW8XYz2fG2ImzvvFzg/WxRcdm6VR2Y2aVP599cdycdCqA7bq3XKcAQMtGufGbfTeJtybOj5FTFkTH5u2qocZQPcaN/rDsu3yL6NZrk9W2N2rUJNp16hLTJn8e06dMrDQAUBUWzJ8bn475KBo3bhqb9N26Wh8LAMgsAQCAryk7K6Jzi4axeHlxLC8uP5TmjIXL04sd3VpVPo/bl/1i957RvEFO5JQV3qxhbjq6wPCxs2P8WgIE7Zrmx9adm8fEeUvXKSwAVamgYFnMmzc3tt9hx3I9jJs0aRJNmzWPqdOmxqJFiyotZ9q0aem6c+fO5fZt1LVrup46dUoV1RqqVhJemTJlcjRo0CCdAuCruvfomfbGHzdmdKXlrHyNt2vfocL9Xbp0iQ/ffy8mTfo8Nt2sz6rtSUP/DddeFe+8NSKKi4pj4cIFMWP6tHTqgO8efuTXf2IArLeGDfKibcsm8eyI0ennw5ctXLIsbfTfqH2LaNZ0zT2YE5t2b5cO8b/lJp3jtz/aNzq1a152DpIVhWXv8xOnzYtf/PmheOLlikcGWGmX/r2iVfNGcfO/R8fcBaZKouYkr90OzRuk58qLCorL7Z80ryANu3dv3XitZSXn3gdt0SHal/3NXPbU2PR+UFckgfm5s2ZEr037lf1drB7Kzc3Li+YtWkVxcXHMn1t+CpeqNm7UBzFr+tTYYfA+0aZdx2p/PAAgcwQAAL6m3OystKE+ufhQXEGX+6TxP1maNlj3MQeTC4QrS0rKf27M7PjPBzNibdc3dureMq3LmxPnr/VYqGpJQ2NJSUm0qGBe8yQQkIQAkqEGkwsflVm6ZMVF6caNy/dqXrkt6fUMtVFR2Wt82bJl6TyaeXn55fYnvfkbNGgYCxbMr7ScJUtWvMYbNmxY4f5GX/wtLFpYPlCTlS5ZkXySJFNz7LzL4DjrnPOjZQWBBACqT8umDSO77Lv57PnlG9yT7/uLliyL3NycdKSASstptiJI/INvbx93PfZWXH77M7FgcUEcue+A+N0p+8YNvz48vnXajfHJZzMqvH8SFjhs763TEcvufOxNo4RRo3LKXn/JyHZJVr6wpHxgvqTsBbm8qCQNwK9Np+YNY5/N28U/354s8E6ds2TxovR8uXHTphXuzy/73p98NhQur96pHJPHePqRe9Nz9P0P/b7pwagXsr5YAChPAADga6v6r5jXvfx5WmpeTlZ0bNYwTtqxS3Rq3jX+8vxnUVBU/qJJolFedmzZqVkUFBbHx9NdDAGo1aqp8SUvLy9+dNpP095DyRQAs2bOjJuuHxo/P+OU+M3vL44tttqmeh4YgPLWcpqwrh8FKxtn3vzw8/jNtf9NRw9I3Paf16Nnl9bxs6N3i7133GyNAYDttugWW2/aOZ58ZVSM/dzw/9RWlf/B5Odmx8/36BVT5y+Le98xGhj1z8q/gOrOaE36bGx88uF70XuzftG15yZrvwMAUKcJAMAG4vrrr48LL7xwjftb990ptjv5ohqsUd1XVFKS9vBPRwKoIDmd/cUIAYuXlR/ucE2WfdHIX1AUsXDZ4hj64oT4w/6bxpH9O8XtIyZXeJ9k+P8uLRrEnCWFMWHumucQherSrFnz9AL1/Hnl56FNehkkvfZzcnMjNzev0nIaNV4x/OeSpeV7y63sFb2mOc8h05Lh/fPz86Pkiwb4r0oa5pctK4hmzVtUWs7K0S4KCgoq3L/0i7+FphX0IEqmH/iilGjRomUcd+IP4/Qfnxi3/+2m+MPlf05HIACg+s1bWJD2bm7dvPzQ5sl3pmaNG0RRUdnnxRoCvistXrri8+TNjyauavxPFBWXxLBXRsVZx+yeNvBXJOn9/9Ojdk1blG7+96vf4NnA15OMkpeMPpGTnYxul11uf/IaTRr3Fy4rWmMZyVn2fn3ax8btmsTQ5z+NBmXHN/jiSmZy33Sdk5WOuresaMXjQW3TuEnTyC77G0hGAqjIsrLv/clnQ35+5dPCfBPJefkrzz1Rti6J7XYZovc/AGwABABgA5EMN5YMT7wmxSXr3kjNCslQ+1MWLIvN2zdJhzb8qg5N89MAwOdzK27EWRczFxXGgoKi2KFbizUGALbq1CyaNsiNxz6eucZRAqA6NWzYIFq1ah1jRq+Y5/bLFxOSxv+FixZEk8ZNKmyw/LIOHVbMeT51ypTo1q37avsmT5qYrjt26lTFtYeqkbzuO3feKF5/9eWYP39euf2fT/gs/RzuvUnlvW1WvsZnzqi4N+eUKZPTC4hdunZda526bNQ18vPy07+fxWV/iwIAADWjYFlhzJq7OLbcuFP6+VD6pbH3mzZukA7tnzToJ8P5V2bS9HnpetGS8sNCz1+04r6NGlQcsOzWqVXs0r9XjJ88O0aOmfo1nwl8fcnLftrCZdF/oxbRrIJh/ru0aJiG6T+bUz78u1ISqu/ToUmUreKgLTrEvn3ardrXqvGK1/7um7SNfmXnxP/9cEYMH1v9c6jD+kqC8K3atI9pkyemDfBZWf+7flRUWBgLy84dkmnEmrdsXW11WLxwQXw88u1o0rR5bNp362p7HACg9hAAgA3E6aefni5rctOrE+OlT8v33qVy701ZmDbA927bKCbNX/0C3jZdmqVDuL03ZcHXLj+5IJL0cli+hob9pNfEHhu3Sfc/M8bFDjIjuaDRvUePeOftt2LSxInRtVu3VfumT58W8+fNj9Zt2pQtbSstZ5NNN00vkr8/8r3YYcedVm1Pek5/8P7IaNiwUXTt2r2SEqg5ScjDRMJftVX//nH/vXfHJ6M+jj33/tZq+559alj6+t5p0K6VltGz18bRuHHjGDvmk3Q0geRi4EqLFy+KMZ+Mis379I0mTSoP1CSSAE4SAEwCA1lmRgSoMcuLimPM5zNj0DY906H6x0/63/f0jdq3SEcGmDZ7QcyYU3Fv0JU+Gj8t7e3fqV2LckGC7p1apeuZcysuY4ctu0erssd5bsSYssdaWAXPCtbfR9MWxYH9OkTvdk3i5a9cb9i1d6v02+RbE+dXWsbCguKYvbgwWjRaPeySTIWXaJJf9l2paYNonF8+lA+1Rc9N+8SbLz8XEz8dF916/S8QXLB0ccyYNjny8vOjY5e1B3y/rhnTJsXUSZ9Fh7LHMPw/AGwYBACgjjNsV2a99tnc+Ha/dnFAn/bx7uSFMb9gxSgLXVs2jJ17torP5y6NsbP+16Nht96to3urRvHc2Nkxcd6KwEDLRrmRjFT41aEPk6EMD9+mYzTKy4nhY+dU+PhJ+CCZAiC5mLK0UO9/MiMZ9jxpsE8CAP999D/xo1N+kjY4Jp595umYPXtWfPuQ70bz5s3TbRM/nxB3/eOO6NV74/jekUevKmfAwO2iSZMm8dyzT8d3D/tetG69ogfEuLFjY+TI99IRAvr06VvzT5AKaPyvSNK436Fjxxj22KNx6OFHlt1e0Zs/6YH/wH3/jM5dNor+A7ZbdfxzzzwZb414PfbZ78DYauv+6bbk7+n7x58Yt/z1urjn7n/Ekcccn37WJ6MH/HXoVen6u2Vlr5RMFbB40aJo07Z8wOapYY+l02d07dYj/dsCoGYsX14Uw0eMSQMAR31rQFx669NRUrLis/Pbu28R7Vo3jdsffj3mLlhxntB7o7ZxxlG7pg3+Nz3wv+H6X37305gzf0kMHtArurRvHpOmr2gobdqoQRy138BYVlgUL7/3aYV12HfnzSMvNyceeGZkFBsWnQx58/N5MXPRshiySZt4/KMZZbdXTGvRsXmDOKBfh5i2oCA+mPq/gMqgsnPorbo0j+FjZsfH0xelU+5d99JnES+VL3v/vu3jJ7v2iAdHTou736p4tDyoLQbsODjeff2lePI//4rjf/LLtME/8e6Il2PKxE9jh8F7p6MEJObOnhmP//uuaNGqdex90PcivwpG8Rrx8nNRsHRJDNnvu5GbV/nUfFDXuDT+JX4XwJcIAEAdduGFF8asWbNiiy22yHRVNlgLlxXHfz+aGUf27xTnDukZD4ycHg1ystOG+7zs7HisbN+Xm8m26Ng0dujeMt6funBVACAJBJw2qFu8NH5uun3J8pJo2zQ/9t6sTfRu0zimzC+I+96bVu6xky+4u2/cOr0o8vrn82rmCdcKyW/UN9raJGmcPPSwI+Luu/4Rt95yUyxbvjx22GGneGH4c/HPu/+RDud/0sk/WhVYSoY2v+dfd8egXXZdLQCQ9GpOggL/uvvOOOO0H8XJPz41Fi1cGEOv/nPMnj07Lrv8z+lIAquUlsYLLwyPGdOnpz8mQ5wvL3vsYY//d9VxBxx0cDRq1Kjmfhls0Jo1ax5nnfOr+O15v4gTjzkizjjrnGjarFncdMPQmDtnThx26tHRomXLVce/9+47cf89/4xNNuuzKgCQOOqY4+PZp56Mq/98eUwve33vtseQeOqJx+Lhhx6IPn37xS677bHq2JkzpsfpPz4hBm6/Y+w8aHB07NAxHXnj0YcfjFdffnFFoOC4EyK/QfXNKQrA6krKvqPc8uBrcdoRu8S5PxgSDfJz47kRY+OAXfum28Z9PjOuuOO5Vcd3atc8fnzYzvHEK6NWCwB8NmVOXPjXx+OaXx4aT95wavz+r0+kgYCTv7tTHDi4X7w9amIMK7vPV+XlZscBu/SNWfMWx2MvfVwjzxkqsnh5cdz48ufxy716x5WH9I1bX5sYSwqL4phtu0aLhnnx8AfTYmHB/4LwfTs2S0cMGDdrSRoA+Lo6NmsQ/TdaET5eOV1f68b5sd8XUwhMW7As3p2yIEplWqkh22y/a2zUo1e8/NzjkVX2mtxp8D7x8ftvxcP/ui1at+0Qx516zqrz5UUL5sdzjz8Ynbv2iN2/9Z1VAYBkdLAkMDB/zopRZZKRAxKvPjes7JyjRXp76+12jtbtOqz22MVFRfHCsIejUZOmseteB9bUUwYAMkwAAOqwfffdN9NVoMzwcXPSoZUH9WyZNuQnF/wmzVsWD70/PUasZTjDxIxFy2PklIWxRaemaY+HZMj/wuLSsu3L4qlPZqVD+xeVlL8y0a5JfjrSwOwlhWWPV/n8ofWLxv/aqG27dvH3u+6Jm/56XTz80L/jrr/fEc1bNE8b4E/+0anp8P3r4qxfnBtt27aL/z76cJx3zi8iJyc7Ntl0s/jZWWfHXvus/p6X/FUkIwm88fprq22/4fqhq27vtvseAgDUqEG7Do6zz/9t/OeB++KPf7gwHYI/mSIjCQN89/Aj1mnknsaNm8RvL7ok7rj1pnjqif/Gff+6M51CY59vHRDHnnBStGzZatWxSehg5112i5HvvRMvPf9cGppJGvvbt+8Q3/7OofGdw46IPn0FBQFqWjLs/uCThsavTtw7jj9ou/jpUYNj3sKlcfdjb8Vltz4dS5cVrlM5t/7njTTwe8LBO8S15x8W+bk5MWn6vLj2nhfjz38fHgsXLyt3nx8fNiiaN20Yv73+Mb3/ybg3J86L61+aEPv1aR9nDO6RfheaNG9p3PLa5+moANXRBp9MOXD64J6rbetSdu68cttL4+fEyKkLo1gCgBrSpGmzOOPXf4xH7r09Ro54NV5+5vFo3KRJDNxptzjw8OOjYaPGay2jqLgoHRlg9Ifvrrb9/r/fsOr22f93dbkAwOsvPl12jjA/9jrwsMjJ1RQAABsKn/pQB0yaNCmd77FLly6rhtWm9igoLInHR82MYZ/MiuysFY2SyXWEkgouJvz1lYlx46sTV7vQMHXBsrj+lc8jmaH5i/+tKiP5776mSxLJ8InnPvpJeru4goAA1LTu3XvE//3hj2mDZ/LaTS7uJe9ZX33f6j9w23jj7ffL/l7KN4Tm5ubGD078YRz3gxPTcpJDsrKyI+dL86CvlJR/3V9vWW0+3K/Kc4GDGpaXlx8Hf+ewOPDb3yl7bZakb+hZ2RW/hs848+z4yU9/XuG+ZESMP/zxz6v9PSXHfTVA0LJVqzj3VxesOm7FsfHF31/54wGoOWM/nxU/vOhfkfOl70LFZe/XJV/57p4M9d9il/PKbV/pjkdGxJ2PvbXqu1PyXp98/1/Td6C/3vdy3PTAK1FUpPGfzEvC7U+WnS8//cX5ciJ56VbU+P631ybGba9PrPBc+que+HhmWm5FfzavfDonDr55xBrvm9zFOTQ1rW37TvGDnyTv9cUrvrMn/yo4X96oR++44d6nv/j+/7/z2fz8BnHepddVev775eNX2nG3fWL7XfdMzw0AgA2Hq+JQzZIL8q+99lrceOON8fLLL6eN+Ulv1D59+sT+++8fxxxzTPTo0aPSMnr27JmWkwyB3fJLQwdTuyQXKdZ2DSG9yFHBMekFkKh435q4aEFtVFGD/1clFzLyKpl3cGVDZ0WNol+Vq4GfWmrF67fy1/DaXufr8veUWPk3A0DtkzTqJ409lUkac5YXVn5M0pO/8iP+pyjp9b+uB0MNWZfz5XU5Zl2OTc6vi/Tupxb6aqP+mo7Jza34fHlt963Iup5TAAD1i6vmUM2Sxv9DDjkkZs2alX6JTy7uFBYWxuuvvx5vvPFGDB06NG6++eb49re/XWk5lSV8AQAAAABgQ2LUuy/zuwD+RwAAqtHnn38ehx56aNpzv02bNrHPPvvEZpttFnPmzImRI0fGiBEjYubMmXH88cfH//3f/8Upp5yiNysAAAAAAADwtWhphGqU9OyfMWNGdOzYMYYNG5Y2/ifDXie9+RcuXBjPP/98nHzyyWkI4Nxzz41x48bFH//4x8jPz8901QEAAAAAAIA6RgAAqsnSpUvj7bffTochOuuss2KLLbZYtS/Z1rx58zjooIPilVdeSUMAL774Ylx//fVpQOCCCy6Ipk2bZrD2AAAAAAAAQF0jAADVJAkAJEP/N27cOAYOHLjG43r16hX/+te/4vTTT4/77rsvrrrqqnQkgGT0gNatW9dgjQEAAAAAAIC6TAAAqklxcXEsX748srOzo2HDhpUe265du7jrrrvSUQGS9UMPPZROA3DttddGmzZtaqjGAAAAAAAAQF0mAADVJBnKP+n9X1hYGHPmzFnr8bm5uWnv/w4dOsQll1wS9957b0yZMiVuvfXWGqgtAAAAAADUDVllS3amKwFQSwkAQDVJGv+TxvyCgoL45JNP4oADDljrfZo0aRIXX3xxtGzZMi688MJ48cUX4/jjj6+B2gIAAAAAAAB1nQAAVJNkCP+tttoqHnzwwXjsscfi5z//+Trf92c/+1k6HcAZZ5wRr7zySmRlZVVjTQEAAAAAAID6QAAAqtHee+8dF110UQwfPjzeeuutGDhw4DrdL5k+4Ec/+lH06NEjjjzyyJg/f3411xQAAAAAAACo6wQAoBptt912cdppp8WSJUvimWeeiQEDBqxXb/699tor/vGPf8S1116b/pwEAwAAAAAAAAAqIgAA1ShpsB86dOjXvn92dnYccMAB6QIAAAAAAJTJClPnAqyBAAAAAAAAAAAA1AMCAAAAAAAAAABQDwgAQAbNnz8/XnjhhRgxYkR8/PHHMXfu3CgtLY2WLVvG5ptvHttuu20MHjw42rRpk+mqAgAAAAAAALWcAABkyIQJE+LII4+MkSNHxtKlS8vNV5QEARo0aBBbbLFF3HvvvdGzZ88M1RQAAAAAAACoCwQAIAPefffdOPDAA2Pq1KmRnZ0dm222WfTo0SOaN2+e7l+0aFEaEPjkk0/irbfeim222SaeeOKJ2GmnnTJccwAAAAAAAKC2EgCADLjsssvSxv/WrVvHn/70p9hzzz3TYf6THv/JSADLli2LOXPmxGuvvRZnnHFGeuzFF18c//73v9NjAAAAAABgQ5a19kMANkgCAFDD5s+fH4888kja83/o0KFxxBFHlBv+v2HDhtG5c+f47ne/mzb4H3zwwfHss8/GjBkzomvXrhmqOQAAAAAAAFCbCQBADUsa8pcuXRo77rhjHH744eUa/7/qW9/6Vuyyyy7xwgsvpPc9/vjja6imAAAAAAAAQF0iAAA1bMKECel64MCBkZOTs9bjk2OSsEASAJg4cWJ1Vw8AAAAAAACoowQAoIa1bNkyXa9PY/7K0ECLFi2qo0oAAAAAAFBnJOPqrm10XYANlQAA1LCdd945srOz47HHHovx48dHr169Kj0+CQo88MAD6X122GGHGqolwNokJ1ilma4EAAAAAADwJQIAUMM23XTTdPj/N998M0488cS45pprYquttqrw2LFjx8aZZ54ZRUVFseWWW8YWW2xRw7UFWBON/wAAAAAAUNsIAEAG/PSnP42TTz45XnzxxRgwYEAceOCBccQRR0Tv3r3TYYs+++yz+Pe//x333XdflJaWpr3/k+MbN26c6aoDAAAAAAAAtZQAAGTA4YcfHnPmzIlLL700pk2bFo888ki6JI39iZVzFyU/t2vXLn7xi1+kAQAAAAAAAACANREAgAzIz8+PM844I77zne/Er3/96/jnP/+ZDvO/UtLwn5ubG4ccckhcdtll0atXrwzWFgCgGiX5x6xMVwIAAAAA6gcBAMigjTbaKO644464/vrrY9y4cTFv3ry08b9FixbpdADNmjXLdBUBAKqXxn8AAAC+huxMV6AWcWoNfJkAANQCTZo0ia222irT1QAAAAAAAADqMAEAqCUKCgpiyZIl6QgAjRs3jkaNGmW6SgAAAAAAAEAdIgAAGVRYWBiPP/54Og3ARx99FMuWLUu35+Xlxeabbx7HHHNMHHzwwZGfn5/hmgIAAAAAAAC1nQAAZEBJSUm8/vrrcf7558dLL72U9vpPli8bO3ZsPProo7HtttvG5ZdfHrvuumtkZ5vVCAAAAAAAAKiYAABkwNNPPx3HHXdczJgxI/25Q4cOsdtuu8VGG20UWVlZMXXq1HjxxRdj4sSJMWLEiDjkkEPi5ptvjsMOOyzDNQcAAACoYlllS+lajwKAVbKSf1lZma4GQK0kAAA1LOnpf9FFF8XMmTOja9euccEFF6RhgGTY/y8rKiqK+++/P92fjAZw6aWXxv777x+NGzfOUM0BAAAAqoHGfwAAqDICAFDD3n333XT4/ySd+Le//S2GDBlS4dD+ubm5ccQRR6QhgcGDB8fIkSPT0QCSkQIAAAAAAAAAvkoAAGrYG2+8EcXFxWlD/l577VXpsUlIYNCgQbH33nvHk08+KQAAAAAAAEA1SIZjMaQ+QH0gAAA1LOnZn9hiiy3W+T79+/dPAwAr7wsAAAAAAFVH4z9AfaE1EWrYtttuGzk5OTFu3LgoLS1Ne/lXJjnmk08+SacJGDBgQA3VEgAAAAAAAKhrBACghm299dax8847x7PPPhsvvvhiDB48uNLj33zzzXjsscdim222ie22266GagkAZFoSESzNdCUAAACgljJmAUDFBAAgAy666KI45JBD4rjjjov77rsvHeI/GRVg5WgASa//4uLiGD9+fBx77LHpzxdccEE0atQowzUHAGqKxn8AAAAAYH0JAEAGDB8+PHbfffd49NFHY9ddd43tt98+ttxyy2jdunUaApg3b158+OGH8fLLL6dBgH333TfeeeeddPmqXr16pSEBAACA1SVRIv2iAAAAYEMiAAAZcOGFF6brpLG/pKQkbeh/6aWXVjtm5WgAiWQKgGSpyJ577ikAAAAAVEDjPwAAAGxoBAAgA5Ie/1Vl8803r7KyAAAAAAAAgLpLAAAy4KmnnqqysnJycqqsLAAAAAAAqAuyDHgFUCEBAMiAZs2aZboKAAAAAAAAQD0jAAAAAAAAAAAA9YAAAGRIaWlpZFUwRlGyfdSoUTFu3LhYsmRJbLTRRtG/f/9o1KhRBmoJAAB8c6Vli/FJAQAAgOonAAAZcO6558abb74ZP/zhD+Poo49etT1p/L/lllvi4osvjilTpkRxcXE0b948tt1227j77rujffv2Gaw1AADw9Wj8BwAAAGqGAADUsKKiorj11ltj3rx5cd111622b+zYsXHJJZfEpEmTomXLlmnj/4wZM+LZZ59NQwF/+ctfIicnJ0M1BwAAAACAzEsittmCtgAVEgCAGvbBBx/EnDlzYrPNNkuXL3v00Ufj888/jy5dusRtt90WPXv2jIcffjh+/vOfx/3335+GAJJQAAAAAAAAAMBXCQBADXv33XfT9Y477hjZ2dmr7fvXv/6Vrk877bTYc88909s//elP4+qrr44JEybEiBEjVm0HAAAAAAAA+DIBAKhhs2bNStetW7debfvMmTPTcEAyxP/xxx+/ansSEjjwwAPT6QLee+89AQAAAAAAAACgQgIAUMMaNmyYrufPn7/a9uHDh0dhYWFsvfXW0alTp9X2tWnTJl3PmzevRuoIAAAAAAAA1D0CAFDD+vTpk66ff/75WL58eeTn50dxcXE8+OCD6fZddtml3H0mTpyYrlcGAQAAAAAAYIOVVfa/rExXAqB2EgCAGrb77rtH8+bNY/z48TF06NA466yz4o033oinnnoqcnNzY6+99ip3nxdeeCFd9+3bt6arCwAAAAB8Q6WRtlcCAFQ7AQCoYTk5OXHCCSekjf/nn39+/OUvf4nZs2fHsmXLYquttoptt912teNHjx4d48aNi6ZNm0b//v0zVGsAAAAA4OvS+A8A1BQBAMiACy64IEaNGhXDhg2LKVOmpNvatm0bt912W3Tp0mW1Yx955JF03a9fv2jSpEmN1xUAAAAAAACoGwQAIANatWoVjz/+eLz55ptpD/9kSoBddtklWrZsudpxJSUlsdlmm8UVV1wRffr0iQYNGmSmwgAAAAAAAECtJwAAGZQM9//VIf+/LDs7Ow488MB0AQAAAAAAAKiMAAAAAAAAAAB1SlbZPwDKEwAAAAAAAAAAgHpAAAAAAAAAAAAA6gEBAAAAAAAAAACoBwQAAAAAAAAAAKAeEAAAAAAAAACgzshKlqxM1wKgdhIAAAAAAAAAAIB6QAAAAAAAAAAAAOoBAQAAAAAAAAAAqAcEAAAAAACgjkqmPy7NdCUAAIBaQwAAAAAAAOoojf8AbJiyIjuNwZHwmwC+TAAAAAAAAAAAAOoBAQAAAAAAAABgnRUUFMQ777wTn3/+eTRv3jy22mqr6NKlS5WUvWDBgnj33Xdj0qRJkZOTE127do0BAwZEw4YNq6R8qO8EAAAAAAAAAIC1mj9/ftx3333x97//PaZPn75qe35+fuyxxx5x6qmnxuabbx5ZWes3McH48ePjkUceiRdeeCE++uijKCkpWW1/y5Yt48ADD4xjjjkmevTosd7lw4ZEAAAAAAAAAABYq6FDh8Zdd92VNtAnDfHbbLNNzJgxI1599dUYNmxYjBo1Kq699trYdNNN16vcZ555Jq6//vr0dnZ2dvTr1y8to7S0NN54442YMmVK3HnnnfHmm2+mx1XVaANQHwkAAAAAAAAAAJV6+eWX4+67704b/4877rg4++yzo0GDBum+119/Pc4555yYMGFCXHfddXHVVVetdy/9zTbbLPbdd9847LDDokOHDqu2JyGAW265JQ0fJAGDP/7xj2n5SVAAKE8AAAAAAAAAgDojaVY2AnzNWrp0aZx//vlRXFycDvF/5plnrmr8T2y33XZx4oknxqWXXpr25n/nnXdiwIAB61x+Mrz/wQcfHO3atSsXHEh+Pv7442Ps2LHx0EMPxdNPPx3jxo2LTTbZpMqeH9QnAgDUf6Wx4tsAAEBt5LsKAAAAUMu99957MX369LQx/vTTT48mTZqstj/pjZ/03E966S9atCgdKaB///7rPApAp06dKr1Ekp+fH0cccUQaAEhCCCNHjhQAgDUQAKD+c0EdAKjNfFcBAIDaRUgXoJz3338/Xbdo0SK23377Co9p2rRpDBo0KIYNGxYjRoxIgwDNmjVb58dY21vvl8tKRiQAKiYAAAAAAAAAK2n8B1hNSUlJTJo0Kb3duXPntDf+miS9/pMAQNJAP2PGjPUKAKxN0ut/pY4dO1ZZuVDfCAAAAAAAAABAHZU0tOdmr//9GjduHM2bN1/rccmQ+7NmzUpvt2rVKh3uf026du2argsLC2POnDnRu3fv9a9YBRYuXBh33nlnejup8w477FAl5UJ9JAAAAAAAAACwgatTs1+UVXQdp5bfIBzyne/Ewnlz1vt+3//+9+OCCy5Y63GlpaWrhtxPQgOVBQCSgEAiGTWgoKBgveu0JsmoAqNHjy77754VJ554YpWOLAD1jQAAAAAAAACwwalTDd41wO+CNUkCAMuXL09v5+bmpo3wa9KwYcNy9/mmPvjggxg6dGgUFRXFFltsEYcffniVlAv1lQAAAAAAAACwwdHgTX2Rm5uTNsyvr8p68q/p2KRhP1nWJJku4OuUvyaff/55nHDCCbFgwYLIyclJRyxo27btNy4X6jMBAAAAAAAAAKijHnrwocj9Gm3tjRo1Wqfjkh7/DRo0SG+vrVf/kiVL0nXS+J+fn7/+lfqSuXPnxq9//eu08T9p9P/DH/4QW2+99TcqEzYEAgAAAAAAAABQR7Vu3Tryv04CYB0ljflNmzZNby9atChKSkrWeOz06dPTddJbf+V9vo7kcb7//e/H+PHj05/POuus2G233b52ebAhEQAAAAAAAAAAKpQ05nfs2DG9PXPmzCgqKlo1IsBXjRs3Ll3n5eV97aH6k1EEfvvb36ZlNWnSJH72s5/FoYcemo5EAKydAAAAAAAAAAB1SlZoDK4pScN7z54909uTJk2KpUuXpg3zFXn99dfTdYsWLaJDhw7r/VjFxcVx/vnnx1NPPZX+fOKJJ8axxx6r8R/WgwAAQLUpjfAlFAAAAACAOm7AgAHpVACFhYVx1113pb3yv2rMmDExcuTI9Pa3v/3tyM1dv2bIZcuWxZ///Od44okn0hEEvve978WPfvSj9HGBdScAAFBtNP4DAAAAAFD39erVK4YMGRJPP/103H777bH//vvHJptssmr/8uXL44YbboiSkpJo1apVHHPMMeXKOOecc9KQwDbbbBPnnXdeNGzYcLX9f/vb3+Luu+9Oe/snjf/JSABJEABYPwIAQKp90wbRu03jTFcDMi5HmBQi25BqIMe3zox4VN9tt1WvTFcBMq5Bxza+H7HBy87OKjtf9ncAsCFLeuH//ve/jw8++CCmTZuWNs7/4he/iI4dO6Y99x977LF02P6k1/8JJ5yQTgHwVZ999ll8/PHH0bp16ygtLV1t30MPPRRXX311ertNmzax/fbbxxtvvLHG+nTp0iV69OhRpc8R6gsBACA1qEer2Kpj80xXAzKuQa4LGlBckukaQOZp6FlXfk/13Z/OPzrTVYCMe2PivHhu3KxMVwMyqmFeTjRqkJPpagCskpyJOG2ree3atYvf/va3aU/+999/P0477bS0oT8JAMyZMyc95pBDDomjj17/84i33npr1e3Zs2fHmWeeWenxScjgl7/85Xo/DmwIBAAAAAAAAACoU7T/Z8Zee+0VDz74YPzlL3+JUaNGpY3/jRs3jo022iiOOOKIOOyww9Z43969e6c9/3v27JkO8/9lSY/+Lbfccp3rkYw8AFRMAAAAAAAAAABYJ8nQ+3/+85/TXv+LFy+OvLy8aNWqVRoEqMxll122xn2nnHJKugDfnAAAAAAAAAAAsM5ycnLSKQGSBahdBAAAAAAAAAAAoB4QAAAAAAAAAACAekAAAAAAAAAAgDolq+wfAOUJAAAAAAAAAABAPSAAAAAAAAAAAAD1gAAAAAAAAAAAANQDAgAAAAAAAEDVS6ZoL810JQBgwyIAAAAAAAAAVD2N/1SjrKxM1wCgdhIAAAAAAAAAAIB6QAAAAAAAAAAAAOoBAQAAAAAAAAAAqAcEAAAAAKA2SObINY8pAAAA8A0IAAAAAEBtoPEfAAAA+IYEAAAAAAAAAKgzsr74B0B5AgAAAAAAAAAAUA8IAAAAAAAAAABAPSAAAAAAAAAAAAD1gAAAAAAAAAAAANQDAgAAAAAAAADUHVkR2VmZrkQt4ncBfIkAAAAAAAAAAFSiNLSzA3WDAAAAAAAAAABUQuM/UFcIAAAAAAD1gl5ZAAAAbOgEAAAAAIB6QeM/AAAAGzoBAAAAAAAAAOqMrHQR/1zJbwL4MgEAAAAAAAAAAKgHBAAAAAAAAAAAoB4QAAAAAAAAAACAekAAAAAAAAAAAADqAQEAAAAAAAAA6pSsrEzXAKB2EgAAAAAAAAAAgHpAAAAAAAAAAAAA6oEvAgClZYuxUgAAAAAAAACgrvoiAKDxHwAAAAAAAADqMlMAAAAAAAAAAEA9IAAAAAAAAABAnWJsa4CKCQAAAAAAAAAAQD0gAAAAAAAAAAAA9YAAAAAAAAAAAADUAwIAAAAAAAAAAFAPCAAAAAAAAABQZ2QlS1ZWpqtRi/hdAP8jAAAAAAAAAECdoskboGICAAAAAAAAAABQDwgAAAAAAAAAAEA9IAAAAAAAAAAAAPWAAAAAAAAAAAAA1AMCAAAAAAAAANQpWZmuAEAtJQAAAAAAAAAAAPWAAAAAAAAAAAAA1AMCAAAAAPVBaRgDEwAAAGADJwAAAABQH2j8BwAAANjgCQBANZs1a1YcffTRVVrmHXfcEZ06darSMgEAAAAAoM4QggaokAAAVLNly5bF008/XSVlZWVlRWlpaSxdurRKygMAAAAAAADqDwEAqGZNmjSJE088sUrLbNasWZWWBwAAAAAAANR9AgBQzVq2bBm33HJLpqsBAAAAAAAA1HMCAF9HaZhbBgAAAAAAAIBaRQDg69D4DwAAAAAAkDFZGmsAKiQAALXE2LFj49VXX43PPvssFi5cGIcddlhsv/32q/YvX748iouLIy8vL3Jz/ekCAAAAAAAAq9OKCBmWNPb/5je/iZtvvjmWLVuWbistLY3NN998tQDAueeeG0OHDo1jjjkm/va3vwkBAAAAAAAAAKvRgggZ9Omnn8YPfvCDePHFFyMrKyu6desW8+fPj3nz5pU79tvf/nbceOONMWLEiJg7d260a9eu5isMAAAAAAAA1FoCAJBB11xzTbz00ktpY/5tt90W+++/fzr0/7///e9yx+6yyy7RrFmzGD16dMycOVMAAAAAAAAAAFiNAABkyKJFi+KOO+6I7OzsuOWWW9LG/8rk5+fH4MGD03BAMgpA3759a6imAAAAAABQe2RlZboGALWXAABkyPPPP58O9b/DDjvEgQceuE73SRr9kwBAMnUAAAAAAABsqIQAAComAAAZMnny5HS95ZZbln1RWbdvKnl5eel62bJl1VYvAAAAAAAAoG4SAIAMadKkSbpeunTpOt9n9OjR6bpdu3bVUicAAAAAAACg7hIAgAxZ2fP/lVdeiYKCgmjYsGGlx8+cOTOeeuqpyM7Ojm233baGagkAAAAAAADUFQIAkCFbbLFFbLLJJjFmzJi444474sc//nGlx994440xe/bs6NGjR2y22WY1VEsAAAAAAACgrhAAgAxJevL/7Gc/i7POOit+//vfp1MC7L777lFYWJjuLy4ujrlz58bEiRPj3nvvjT/96U/ptu985zvRtm3bDNceAAAAAAAyJyvTFQCopQQAIIO+//3vx/Dhw+O+++6Lk08+OXr27BnTp09P91155ZVx0003xaRJk1ZtGzRoUJx33nmRk5OTyWoDAAAAAAAAtZAAAGRQ8+bN41//+ldsvPHG8fe//z2dDqCkpCSysrJi9OjR6THJSAGtW7eOAw88MJ0GoEGDBhmuNQAAAAAAAFAbCQBAhiWN/RdeeGEcc8wx8e6778abb74ZU6dOTacCSBr+t9lmmxg4cGBstdVWGv8BAAAAAACANRIAgFogNzc3+vTpky5HHXVUpqsDAAAAAAAA1EECAAAAAAAAANQtWZmuAEDtJAAAtcTy5cujoKAgZs6cGVOmTIni4uJo3759dOnSJR36P1mS6QIAAAAAAAAAKiIAABlWWloaDzzwQPzzn/+M119/PaZNmxYlJSXpvqTBv02bNtG/f/849NBD44QTToi8vLwM1xgAAAAAAACojQQAIIMKCwvjpJNOirvuuisNAiQN/sl6peT27Nmz46mnnoqnn346br/99nj22WejYcOGGaw1AAAAAAAAUBsJAEAGXXnllXHPPfdEdnZ2DBw4MPbff//YZpttom3btmkYYN68efHhhx+mAYDhw4enIwScdtppcf311wsBAAAAAAAAAKsRAIAMKSoqiiuuuCJdf+c734mbbropWrVqlTb8f9l+++0Xp59+elxyySVx6aWXxr333hu/+c1volevXhmqOQAAAABrlQzymLXWowD4WrLSfwCUJwAAGfLkk0/G3Llzo127dnHddddF69at13hs0tv/F7/4RTpawJgxY2LYsGFx6qmn1mBtAQAAAKpD0nhTutaj6iTtUgAAZIAAAGTIhAkT0vWQIUOiQ4cOaz2+RYsWcfDBB8ef/vSnmDhxYnVXDwAAAKAG1NPGfwAAyBABAMiQnj17puu8vLx1vs/KY7t161YtdQIAAAAAAADqLgEAyJDBgwenw/4/88wzsWzZsmjQoEGlxxcWFsbDDz8cTZs2jd13371mKgkAAAAAAADUGQIAkCGNGzeOM844Iy655JI477zz4ve//306zH9Fksb/G264IT755JP43ve+F927d6/h2gIAAAAAAAC1nQAAZNCZZ54ZRUVFcdVVV8V7770XRx99dAwZMiS6dOkS2dnZMXPmzHjppZfizjvvTNfHHXdcXHTRRdGoUaNMVx0AAAAAADIiK1myMl0LgNpJAACq2eTJk6Nbt25rPW748OHx/PPPV7ivtLS07MtMVtx2223pMnbs2OjZs2dVVxUAAAAAAACowwQAoAYkDfjf9Lgv71vX8qg5ixYujOefeTzGjh4VuTm5sXm/LWO3vb4Vubl561XO2yNejbffeDUWzJ8XnTfqFrvtuW906tK1wmOTY14a/lT6mGUvitioW4+y478Vbdq1r4qnBMDXtGTJ4nj6qSfjg/dHRklxcWzet28ceNAh0bBhw/Uq571334kXnh8eM2dOj06dOsdee+8bm2y6Wbnjli9fHuPHjY2PP/owPv74o/QzqUfPXvGjU06rqqcEwNc0fvRHMeLlZ2PBvHnRolXr2Hbn3aPnJn3SgPfaJOd9c2bNiM/GjorPxoyKGdMmp9uO/8m50aRps0rvO3PalPRxp02emP7cpl2H6LPVwNi039ZV8rxgfTTMy46dureKjds1juzsrBg/a0kMHzs7Cou/3rWNxmXlnbhjt7Jz76x47dO58dqEeeWOSf7EerdtHDuWPW6zhrmxsKAoXv1sbvrYrqiQKZM//zReeu7JmDVjWjRr3jIGbL9z9N16YDoK6Nok7//z5s6OT8d8EuPHfFxW1oSybSVx4unnRPMWLcsdX1x2HjLqg3dj3OiP08dbsmhh5DdsFD033ix23m3Pss+R5tXwDAGA2kIAAKpZixYt4sorr6zSMtu0aVOl5fHNTJn0efz+lz+LqZM/j8ZNmqYnZY8/fH889p/747eX/CVatmq91jIKCwvjtr9eHQ/de2c0btwkcvPzo2DJkrj79hvjt3/4c2y3066rHT954oT47dk/iZnTp5U9ZpP0AmLB0qVl978rLrnqxjQMAEDNmzt3Tpx3zs/jzRFvRLNmzSMrOyv+858H4/a/3RI33XpHdO7cZa1llJSUxN13/j2uvOKy9D2+YYOGUVCwNG656a9xwYUXx0HfPmS1i4R/ufLy+Nfdd6afBXllnx/Lly2LAQO3FQAAyKDkvfyV5x6PW6+5NA0F5+WVvT8vXxZP/ueeOOlnv44dd9t7rSGAcZ98GH/81ell3/OXRE5ubpSWlZmUe/TJPyvbW3EAIAmevf36i3HLXy6OoqLCyG/QIN1eVHa+8dIzj8UVt9xf1U8VKtW8YW6ctXvP2KJTs1i8vDjJrseQTdrGd7bsGL97YnTMXLR8vcrLKftudeouPWKnHq3SRv4p8wrKBQCS7bv2ah2nDOoeJWUPmAQN8nKyYr8+7ePaFz8rO35u6FdBTUquE7356gvxl//7Vfre36BhwyhcvjwefeDuOOrEU+OQI45f62fCjGlT4qJzTotpUyZFTk5O+houKSmO7//w9IgKAgBzZs2MC88+Lf0cyC37DEnOH5JQwNOPPhj/+tv1cd4lV8Umm/erpmcMAGSaAABUs6ZNm8ZZZ52V6WpQjW694aqYPPGz+OFPfhE77zYkiouK4r8P3Zc25t93161x8ulnr7WMN155IR7/z/2x9cDt48RTz4w2bdvFJx99EH++5IK4ceifot9W/dNwQWJ22UncpRecGwsXzCsr+xexw6Dd0pO5Tz7+IG657sr43blnxKVX3RTtO3aq7qcOwFdcf+018dabI+LkH58W+x94UOTn5cdj/30krht6VVz95z/FRX+4LBp80RizJp+M+jhuvvGG2HjTTeNXv/lddOvWPcaOGRMXX/S7uPaav0S/flvGxptssur4nj17xaGHfy96994k2pZ9fpx79pnV/CwBWJsP3x2RNsL33LRvHP3Dn0XbDp3SHvx333RV3Db00mjbvmNs0nerSsto1LhJbDto97Lv9RtFxy7d4r/3/yMmjPuk0vuMeOW5uPFPF8ZmW2wTBx5+XHTaqHvZ1hW9RmdNm1qFzxDWzZEDOke/js3i3nemxovj5kRRSWkM7t06jhrYOY7dtksMfXFCFBaXrHN523ZtEdt3bxkfT18YfTtWHITZslOzOHVQ9xg/e0nc8cakmLl4ebRvmh8/2KFrnDG4Ryx4sjA+nLaoqp4irNWE8WPixr9cEq3Kvqv/8Ixzo0fvTWPWzOlx1y3Xxn1/vzn9uf92O1daRn5+g9hm+52jadNm0blrj3jqv/+Oj0e+s8bjk5FiTv/l78s+B7pG8xatys5BGsbiRQvj3Tdfjduv/3O6/OGav1X1UwUAagkBAIBvYMwnH8fLzz+TDtX/nSOOWbX9hz/5ebz+ygtpEOD4H52RnqhV5t47b43CosL45e8uWzViwE677hGnnPnL+NP//Toevv+fceTxJ694zFEfxuefjY/tdtolDvjO99Lkd2LndkNi0uefxe03Do3XX34+Djr0yGp61gBU5NNPx8f99/4rdthp5zjltNNXbT/hpJPjmaefiuHPPROzZs2MLl02qrScv1x5RSxevCiuu/7haN+hQ7qtTZu28cvzfxNnnPajeOD+e9LbK33vyKNX3V68eHEVPysA1lfSw/LlZx5L10kj/MqG/lZt2sVhx58aV110Tjx8z+1x1u/+VOmwz1269Ywf/+L3q34ePuw/lT5u0hP0kXvuiOys7Dj1nAujecv/jUTWum2H6LVJ32/2xGA9dWnRMPbdvF28O3lB3Pfu/wIo/x45LXbo3jJtyG85ImmgX7cAQNL7/5AtO8aHUxemvf4rCgAkx3yrz4pp8R54b2qMnrniu9HcJYXxYNnj/mL3XrH3Zu1i1PTFUWwYAGrI6y8+F3Nnz4ofnXl+9N9+RUN/q7Lv96f+4jdx7inHxC1X/zGuuePfq67vVCQ5/uSf/nLVz2+8PLzSx0xGEhu8136rbWvZuk3ZZ0uPGPHy8/H+OyNi6dIl0ahR46//xKAWWPukShsOvwvgywQAAL6BZx5/OLKys2OfAw5ZbXsydNuBhxweN15zRbz43FOx574HrrGM6dOmxNhPPoptdxhUbrqAnQcPiRYtW8XjDz8QRxz3w7Tc2TNnRGHh8th4s77lTg433rRPOgfch++/IwAAUMNeeP659H16992HrLY92Xb8CSfGL88+K555algc94OT1lhGEhB4+60R0bfflqsa/1faedCg6NChYzxdVsY5v/zVOs0VCkDNKyr7rv7Z2FHp0P99thqw2r4uXXtEy9ZtY/qUiTFvzqxo3bZ9lT3u2FEfxsRPx8R3jvlR2vifTAGwrKAgnWIsy2cGGbBttxaRNLGP+HxeuX0PvT8tzh7SO3bs2Soe+WDGWstKGjW+t02naNkoN658blwM6NqywuOSKQc6t2iYTjcwbvaS1faNmbE4CopKomurRtGkQU4sKCha/ycFX8N7b70eOTm5sdPgPVfb3rxFy7T3f3JNaNKE8dG91yZrKKHqJNeTFsyfl35G5fhsAIB6SwAA4Bt4/723o0njJtG+Y/k5nft+cbFv5NtvVhoAGPPxh+lcnr0361NuX3JC1qFTlxj98Qcxb+6caNW6zap54ZI5QL+q5IttkyZ89nWezjeUXNqRNQU2XKM+/ijy8/Ojy0ble/jvsOOKnj5vv/VmpQGAT8ePT3uM9ujRo9y+7OycdOj/l196MaZPnxadOnWusroDUHWSKcFmTp8anbp2j8ZNVu+hnDTMJ70y58yaEYsWzKvSAMArzz2Rng/ssse34tF774iHy5ZkjulmLVrGt4/4QezxrUMiJ9dlIGpOz9aN0+H9ZyxcXm7fyCkL03UyPcC6BAD6dmwah27dKe56a1LMWly4xuMa5+WkIYE5i5fH/KWrN/DPXVoYC5cVRevGedEgV8MnNWfip2PTazvNW7ZabXuDho3KPgfaRfGHhTFj2tRqDQAkn02TJ02Ie2+/MZ2SYJvtdor8Bg2r7fEAgMxy5ge1wIgRI+Kll16Kjz76KGbPnh3Lli2L0kqGorv11lujY8eONVhDKlJUWBgL5s2Jho0bR15eXrn9zZs3T7dPnzqp0nKSed8Srdu0LbcvOysrmjZrnt5OEtpJAKB9p85lJ4kN4/333oolSxanPXoSSYPRO2++mt6eP3/uN3puX4/Gf2DDlbwHz5s3L3LL3vdXvi9/WYsWLdJ5N6dMnlxpOXPmzEnXzcuOr0ibLz4rZs6YIQAAUEstWbwoli8rqDAknH5ONG0e0yZPLDvvK6jSx10x6kBu3HH9FTFh/OgYuNNu6VRkn475KO7865VpA9Rxp52d9kKF6pacyzZvlBtFxaVRUFRcbn/SQ39ZUUm0a5q/1rLyc7LjkK06xuT5BfHM6NmVHpubkxWNcnPWGBKYtWh5tO3QJHKznb9SM5Jh9pNrN703Kz8NSzKiV3LNJwlvLVm8sFoef/yYUXHOj7+/6uf8Bg1ilyH7xmHHrDmUDADUfc76IIOKioriggsuiOuvvz4WLVq0qvd2YmUv78RXwwBLlqw+jB2ZUVhUGCVl/23ycvPKTtrKXzzIyspOL64lJ3qVWbp0abrOz68geV1W7MpwwfJly9L15v22is4bdYv333krbhr6pzjmxFOiYcNG8cQjD8bjD/877SG68lgAakYSAEh61STzLq+pd2UyOsDaPhNWNgYlx1ZYRoMG6XrlZwcAtU/S2JNouIZ5lRuUvZeXlBRHSXH5RtFvYuH8eek55rsjXo7zL7s+Ntuif3qeUlD2mXH1/50bw594KPpus13ssOueay8MvqGc7LIlKysdJ664pOIODoXFpdEob81znq+0S+9W0bdjszjnoY/WOmx/EjzIKXvdL6sgdJBIwgi52dmrXXOB6lTwxff/pCNHRfLKvvcn1/2SEVuqQ6cu3eL3V/41PV+ZPOHTeOzBe2LalImRnbP2vz0AoO4SAIAMuuOOO+Kqq65Ke2nst99+0ahRo3jggQeiZcuWcfTRR6c9CceNGxfvvPNO+kV9xx13jG233TbtRbi+Ro8eHe+///4a9zds0T76bL3dN3k6G5zcnNz0okFy4a6kghEbkhO44pLiaNiw4gt/KzX4Ysi1ZB628oWsCIok8r5oDGratFn8+v/+FH+9+vJ48dlhMeyRf6fb27brEEcce1Lcdetf13hiCUD1yMnJSZfS0pI1NugUFhamga3K5OeteK8vKqz44vbKz4oGDRt8g9oCUJ1WfhdfUw//5cuXp6HdZKlKDRut+IwZsOPg6Lv1tqu2N2rcJA447NgY/eF78fIzjwkAUCOSNv/kPDlpZs9eQ2N70ls/GQWgMt1aNYwTtu8az3wyK6YsWHvQPT0PL1uSUQMqkp+bHUVllats1EWoSg2++P6/fA0N/Mnoksm1pdwKRpasCo0aN44t+6+43rfNtjvGTrvtGRede3pcedF5cfFVt0TjJk2r5XEBgMwSAIAM+uMf/5gO93/++efH2WefHSNHjkwDAO3bt4+hQ4emJ6RJCCCZGuCYY46JUaNGxTnnnBNt2rRZ78d69NFH47zzzlvj/j33PSCuu/Wf3+TpbHDy8vLTodrmzJqZnrB91eLFi9Lt7TpUPl1D67YrhnOeN3dOuX3Ja2DJohXDwDX7YiqARJeu3eNX/3dF2WPPipkzpkZubl6079gpfbzbb7ym7DXS7ps8NQDWU9L436x58ygsKlrV8/PLFi9alDYEdSh7r65MEgJMLFgwv8L9c+esmOKlTQXTxgBQOzRu0iw9V5g9Y1q5fcloMcn3+yTcm9egasNcbTt0is/Hj1mt8X+lFq3bRKMmTWP2zGlpmCwvb+3DrsM3kfT6X7SsOO2N3zC3fGN8o7zsaFC2ffbiNfd6ToIDB/brkAYFpswviP5d/ndO3LXliqBNx+YN0u1TFhTE9IXLo7DscZNQQevGFTemtmmcn44CsKZRCaCqJSGsJAQwd/bMcvtKS0rS84Ss7Oxo3LhmGuJbt20fh37/pLjqD7+KF55+PL518OE18rhQLbLCjKQAayAAABnywQcfxNixY6Nt27Zp43+jRuV7BCYJ4FatWsWgQYPixhtvjEMOOSQuvvji2HXXXVc1EKyrPn36xFFHHbXG/Rv32Xp9nwJlXzA377tlPPXYf2LunFlpo/yXjfn4g7QBv++W21RaTO9NNk//W382bnS5fUXFRTFj+rRo3qJltPpKY0+jRo3LHrNbuqw0/KnH0nWvTTb7mk8KgK9r4403jaefHBbTp5Vv8HnnnbfTz4Sttq7887Z7j57pZ8KkSRPL7UtGF/j003HRrFmz6Ny5/LzSANQOyQhvrdt1iEkTxqXhr5UjfiUWLpgXS5csTkMCTZs2r6SU9ddnq23j7VdfqHAY6aSRKVnSkQeyKu4ZDVXt87lLY6ceraJ1k/KN8Zu3b5q22XwyY9Ea758MHJBMEZD05j95524VHrPbxm3S5e8jJsV/3p8eBYUlMX9pYbRsnB9NG+SkIYSVmjXIjZaNcmNu2f5lxZWPPABVJflun1wvmvjZuPT9PwkErLRs+bL0elIywmSb9h1qrE4tW6/oWDT5809r7DEBgJolAAAZ8u6776brwYMHl2v8TxoIStKLM/+7MDNkyJB0CoCXX345HRFg5513Xq/HS6YYSJY1mbmwMBYWVO0clBuCPfbZP4Y9+mA89+RjscXWA1dtT/4bPlG2PZnDedc99qq0jOREsGuPXvHOiNdi4YIFaQ/Sld57642YM3tmfPeIY1d7PVRkWUFBvPDsk5GXlxcDtl+/1wcA39wuuw6OG667Jl566YX47mHfW7U9+Uy4+86/p6O1DNlrn0rL6NCxY/Tp2y8++vDDmDtnTrRq3XrVvvfefScmT5oUBxz47XTEAQBqp6R3fffem8b0KRNjzEfvxRb9d1i1b+qkz2P+3NnRe7N+0bKKR3PZefd94t7bros3Xx0eB37vuNX2TZ86ORYvXhhbd985cnJdCqJmvD1pfhw5oHMM2KhFPDN69mr7DuzXPh2K/7XP5q3x/iVl++95Z0o8/vGMcvu269Yyvr1Fh3h29Kx4buzstPd/YmFBUUxbsCz6dmwWPVo3jg+mLlx1n43bNk6nAJg8ryCWLHf9g5qTDME/fsyoGPHKCzF4r/9dm1u4YH58Pn5sNG3eIjbq3rPG6vP2ay+m6y41+JgAQM1y1gcZMn/+iqF9k+H+V0ou5ieNt0Xp8MFLo0mT/6WCk14kSc//4cOHxxtvvLHeAQCqx9YDto8tth4QTzzyYGy74y6x5TbbRklJcTw77L8x+uMPYq/9vh3NW7Radfwlvz0nXnzuyfjdZVfHjrvsnm5LGva/e+Sxce0Vf4jrrvxD/PD0n5f9t28aU6dMiqsuuzBatmod3zv2h6s97ocj34kWLVuV7WuTvm4WLVwQzwx7NEa8+mJsPXD72G6nXWry1wBAmb79tojddh8SLwx/Lv776MMxaJfB6Xv0i8+XfXa//mpsv8NOsdFGXVcdf+Xll8ad/7gjLvj9/8V3Dl0x9GbymXDmz8+JM37y4zj7rJ/G/11yWfo5MGP69PjDxRel3w2OOOr7qz1uMp/ooi+mi1m6ZMX0A8l3iTlzVlxoT8JoTZs2q4lfAQBlkgb27XfZM0a8/Fw88eA/o0PnrtG0WYtYXPad/dH77kiH4N/n4CPSYFhi1PvvxB/O/XFsvd3OcfZFV60qJwmQLVo4P0q/GKq8uGjFtGPJKAJJT/6s7Kx0JIGVobBmZecd2+68e7w6fFg8899/xw6D9yzblxuzZ06PB/7+17LPgwax97e/F1BTxs1aEiM+nxfbdW8Zu/ZqHe9OXhDFZa/rbbu2iK26NI/3yn6eseh/I1acsP1GceAWHeL6lz5LAwPJK3/SvIIKy96o5YqOFDPL7v/RtP+NIrC8uCQNBGxdVv4B/dqnYYDFy4uiaYPc2L/s55ysrHh+3JwoLDYFADVnh133iGeeeDj+c8/fo3uvTdIpHJcsXhR33Xxt+p5+6i9+u2q0mAnjx8T5P/lBGgi44Irr06knE+kUkclUk198FiSfJYkkRJD/xZQyTco+E3LzVny2DB/2aHQsO/do36FzNGrcOB1So6DsXOG9t16LR+6/O1q3bReD99y/pn8VAEANEQCADGn7xbzvixcvXrWtYcOG6YX9goKCmDFjRvTsuXoSd8kXF/WTfdQeJ512Vlz6u3PjTxf/Jrr37B3FxcUx4dOxZSd1G8f3jjlxncrYZfe9Y+TbI+L5p5+Iz8pO9pq1aBlTJ09ML/idfvZvVhsVIPHAP2+P0R9/WHbS2DkNh8ydM7vs+Emxyx57x6ln/jK9uAdAzfvFuefFzJnT46Lf/TY22XTT9D16/Lix0bp16zj19DMqnPLnq/oPGBhHHvX9uOO2v8WpPzop2rVvn04rMGXK5Dj1Jz+NTTdbfZqXd95+M67685/S28kIQomxY0bHT045Ob29w447xRk/OyttBAKgZgzYcdc4+MgT4tH7/h5X/OZn0bxlq5g3Z1bMmTUzvvP9k9PG/rVZvqwgrrv017F40YL052mTV0wPc/0fLyj7fMlJG/9/cPovo9NGK6YiS4aZPuTok2Lip2PiX7dcHS889XDZcfnpSARJWUf98GfRa9O+1fekoQK3vz4pWjfOj9N27R4T5iyN4pLS6NqqUcxbWhT/entqLCuq+qH435gwL+5/d2p8Z+uO8btvbRLzCgqjZcO8aNs0v+wxp8RbE+dX+WNCZZJRX7533I/izpuujst+c1a0bd8h5s+bV/a+/nnse/Dhseteax6xc6Wk4f+OG/4S48d+kv48Y+rkdD300gsi54tG/5N/+svYrN9W6e333xkRN199WbTr2DmaNm8eWWX/kiBacq2peYsWcfLPziv7HGlS8YNBHZKVTigDwFe5CggZ0r9///QCzahRo1Zta1H2BTwZEWDixInpFAFfDgAsWLAgHnjggfR2586da7y+rNnmZSdXV998d9ooP/KdtyIvNzeOOPaHcehRx5VriG/Ttl1s1K1HNGrUeLXtSY//c357SQzcflA8++SjMWf2rNhm4A5x6JHHRc+NNy33mEf94Mcx/MnHYvSoj2LxooVp2OCEU34WOwzazbDQABnUtWu3uOGmW+Puu/4Rr73ychQVFcehhx8ZJ//41GjcePX3/lat20SPHj2jabPVe+cnoYFkFIABAwbGg/++PyZNmhR9+vaNCy++NAYM3LbcYybBs4KlS1f9nJSZWLktGSGgVCc3gBqVV3YecOixP45N+24dTz58b8ydPTO6dOsVx592bmwxYIf0XHClpOdm0ojfuk371cpIensmDffJVF+JVm3apetkJIBkSUYQKC1ZvfG0c9ce8Yfr74rHHrgr3n3j5bLPgsWx1bY7xT4HfS96bLJ5NT9rKG/awmVx4ROj44C+7dNe+TnZWTFs1My4/90psaxo9S8o8wuKYsr8dRuePzkmOXbhsqJy+5KpBe57b2qMmbk4vtWnfbRukpcee/Orn8f7Uxf6XkSNS77fH/DdI8s+E7aMR+69M6ZMmhAdOnWOI47/Uew0eM/I/tJ1nGQamU4bdYt2HTqVmwoy+V6/rGDFd/wWrVqnS1FxUbokSr70mXD8qWdFv60HpFNLzpxW9vdW9nnSqm272ONb3469DjgkGjXW+A8A9ZkAAGTIxhtvHF27do33338/Zs+eHW3atIkOHTrEgAEDYvTo0XHBBRekowNstdVWMW/evPjrX/+aBgOSkMCQIUMyXX2+Ihme+aTTfr7W4378s3Pjx5XsH7LvAemyNpts1jddAKh9mjdvEaecenq6VObEH/4oXdZk8O5D0mVtdh60azz4yOPrXU8Aqt+WA3dMl8okvfIvv/m+ctsbNmocF/z5b+v9mMn0AAcefly6QG2weHlx3Pvu1HSpzL9HTkuXdfHS+DnpsiZJI/87kxekC9QWm2zeL35+waWVHtO5a/e48uZ/ltueBAPO/PXF6/xYzVu0jCH7HZwuAMCGRwAAMiRJ8R5wwAFx++23x7Bhw+Loo49O5+j9zW9+E48++mh89NFHcfzxx5e73yGHHJKGBwAAAAAAAAC+TAAAMujcc8+Ngw46KLp167ZqW58+feKpp56Kyy+/PJ5++ul06P9keMjevXvHkUceGWeccUYaFAAAAAAAAAD4MgEAyKDu3buny1dtv/32cf/996dzPs6dOzdt8G/atGkGaggAAAAAAADUFQIAUIslPf9bt26d6WoAAAAAAECtkZUsWZmuBUDtJAAAAAAAAAAAAPWAAAAAAAAAAAAA1AMCAFDNpk+fHoMGDarSMp977rno2rVrlZYJAAAAAAAA1G0CAFDNioqKYvz48VVaZmFhYZWWBwAAAAAAANR9AgBQzZo3bx6///3vq7TMVq1aVWl5AAAAAABQl2RlugIAtZQAAFSzZs2axQUXXJDpagAAAAAAAAD1nAAA1ac0RPBqyDvvvBOzZs2KLbfcMjp27Jjp6gAAAAAAAAAZIABA9dH4X2N+/etfx7Bhw+Luu++OI444ItPVAQAAAAAAADJAAADqidLS0kxXAQAAAAAAAMggAQAAAAAAAAAAqAcEAAAAAAAAAKhbTEMMUCEBAAAAAAAAAACoBwQAAAAAAAAAAKAeEAAAAAAAAAAAgHpAAAAAAAAAAAAA6gEBAAAAAAAAAOqUrLJ/AJQnAAAAAAAAAAAA9YAAAAAAAAAAAADUAwIAAAAAAAAAAFAPCAAAAAAAAAAAQD0gAAAZ8sgjj8TZZ58dHTt2jOeeey6ys7O/dllnnXVWHH744bH99ttXYQ0BAAAAAKAWyir7X1amKwFQOwkAQIZMnTo1xowZEzvssMM3avxP7L333lVUKwAAAAAAAKCuEgCADOnZs2e6zhJTBAAAAAAAAKqAAABkyE477RTt27ePF198MZYtWxYNGjTIdJUAAAAAAACAOkwAADKkadOmceqpp8bFF18cV155ZZxzzjmRl5eX6WoBAAAAAAAAdZQAAGTQ0UcfHZ999llcfvnlMW7cuDj44IOjX79+0bJly8jOzl7j/Vq0aFHpfgAAAAAAqK+yvlgAKO+LAEBpeKuEmrfZZptFVtaKv73bbrstbr/99nW639ixY6Nnz57VWDMAAAAA1pvLrAAAZNgXAQDfSiFTSktL0xBAsiS31/U+AADUPdoEAKCe80EPAECGmQIAMujGG2/8Wvdr165dFdcEAICaoE0AAAAAgOokAAAZMn369Nhoo40iOzs79tlnn1VTAQAAAAAAAAB8HQIAkCGPPvpo/PSnP41BgwbFvvvum+nqAAAAAAAAAHWcAABkSF5eXixdujS6deuW6aoAAAAAAEDdYlDd//G7AL5EAAAyZOutt07Xs2fPznBNAAAAAAAAgPpAAAAyJAkA9O/fP55++un4/PPPjQQAAAAAAAAAfCMCAJBBF1xwQRx33HFx8sknxx133BEdO3bMdJUAAAAAAACAOkoAADKoc+fOccYZZ8Rll12WjgaQhAF22WWXaN++fWRnZ6/xfltttVU0aNCgBmsKAAAAAAAA1HYCAJBBO+ywQ7rOysqKGTNmxBVXXJEulUmOHTNmTPTq1asmqggAAAAAALVMVvoPqKNKI/wJVx8BAMig1q1br/d9kgBATk5ONdQGAAAAAAAAqpnG/2q1XgEAYQyoWk8++eTXul/Hjh2ruCYAAAAAAABAXbdeAQCN/1C1BgwYkOkqAAAAUIN0rgAAAKA6mQIAAAAAoIZo/AcAAKA6CQAAAAAAAABQp2RJVgJUSAAAAAAAAAAAAOoBAQAAAAAAAAAAqAcEAAAAAAAAAACgHhAAAAAAAAAAAIB6QAAAAAAAAAAAAOoBAQAAAAAAAADqjKwvFgDKEwAAAAAAAAAAgHpAAAAAADZYSX+J0kxXAgAAAACoIgIAAACwwdL4DwAAAAD1iQAAAAAAAAAAANQDAgAAAAAAAADULVmZrgBA7SQAAAAAAAAAAAD1gAAAAAAAAAAAANQDAgAAAAAAAAAAUA8IAAAAAAAAAABAPSAAAAAAAAAAAAD1gAAAAAAAAAAAdUpW2T8AyhMAAAAAAAAAAIB6QAAAAAAAAAAAAOoBAQAAAAAAAAAAqAcEAAAAAAAAAACgHhAAAKpFadmSlelKAAAAAABQ/2SV/c8FaIAKCQAA1cJ3LwAAAAAAAKhZAgAAAAAAAAAAUA8IAAAAAAAAAABAPSAAAAAAAAAAAAD1gAAAAAAAQLXIKltKM10JAIB6J+uLhRX8LoAvEwAAAAAAqBYa/wEAAKhZAgAAAAAAAADUPUneUvd3gNUIAAAAAAAAAFD3aPwHKEcAAAAAAAAAAFgn8+bNi+effz7ee++9mD17djRs2DB69+4dgwYNin79+n2jsktLS9MyJ02alC4LFy5Mt2+88cax3XbbVUX1od4TAAAAqDHGpQMAAACoEi6xZMTYsWPjjDPOiIkTJ0ZhYeGq7VlZWXHzzTfHqaeeGieccEL68/p69tln44YbbogpU6ZEQUFBuhQVFaX7jjzySAEAWEcVBABcmAYAqB6+YwEAAABQNy1dujR+//vfx/jx46Ndu3ax//77R58+fWLu3Lnx5JNPxsiRI+Paa6+Nzp07x7e+9a31Lv/dd99Ny0gkAYIWLVqkIwAUFxdX9VOBeq2CAIAL0wAAAAAAAMD/3HjjjfHmm2+mty+88MLYY489Ijs7O/35oIMOip/+9Kfx9ttvx9ChQ2Pfffdd71EA8vPzY+DAgWlP/2233TYNEpx00kkxderUKn8uUJ+ZAgAAAAAAAABYoxkzZqRD/JeWlqY9//fcc8/V9icjAvzkJz+JH/7wh+k0AQ8++GB897vfXa/HOP3009NlpZKSksjJyamS+sOGRAAAAAAAAADqu6QjbmmmKwHUVW+99VYUFRWlPf5PPfXUCo/Zcccdo3v37vHZZ5/FvffeG4cccsiqEQKAmiMAAAAAAAAA9Z3Gf+AbGDVqVLru2LFjOjR/RXJzc2PnnXdOAwATJkyI2bNnpyMDADVrHQMAyTeD9ZunAwAAAAAAAKpDlnarGlNcXBzTpk1Lb3fo0CFt6F+TzTffPF0XFhbGzJkzBQAgA9YxAOBNlA2MzAsAAAAAAFAHvPba61FSXLje9+vUqVNsvPHGaz2upKQk5s2bl95u0aJFpcP6b7TRRuk6mS5g/vz5610n4JszBQBUROM/AAAAAABQB/z85z+PeXNnr/f9vv/978cFF1yw1uNKS0tj2bJl6e38/PzIylpzI0qTJk1W3Wf58uXrXSfgmxMAAAAAAAAAACqUNOYnQ/onkuH/KwsANGjQIF0nowasvA9QswQAAAAAAAAAoI46/HuHx7KlS9b7fgMHDlyn45IG/7y8vPR2MrR/EghYk4KCgnSdTBOw8j5AzRIAAAAAAAAAoE6ppBP6BufMM8+M3Ozq+4UkAYCVPfuTYf0rCwAsXrx41X2S6QKAmicAAAAAAAAAAHVUdWchkt78rVu3Tm/PmzcvHd5/TSZOnJiuk6kCWrVqVc01AyoiAACk2jTNi9ZNvCUAENEoX4QelhWVRkHRmns0wIZiQPfmma4CZFyfzk3j8P6dM10NyKimDXOiQa7zBIANVU5OTnTs2DG9PW3atHQagDX56KOP0nXS+79t27Y1Uj9gdVr7gFQ6OpAxkwCI6k+NQ11RyYiGsMHIzfGpAA0jJ3KyszNdDcio/NysyPVnALBB69OnT7qePn16fPrpp7HllluWOyaZHuDll19Ob2+88cbRpk2bGq0jsIIAAAAAAAAAALBG2267bTqsf9L7/9prr40bb7yx3DEvvPBCTJ48Ob19xBFHRJZOh5ARAgAAAAAAAADAGrVu3TrOPPPMuPLKK2P48OHx0EMPxUEHHZROD5CYOHFiXH/99entfv36xX777VeujMMPPzxGjhwZgwYNiuuuuy4aNWpUo88BNhQCAAAAAAAAANQp+pbXvOOPPz5ee+21eOmll+IPf/hD2uN/m222iVmzZsWTTz4ZEyZMiKZNm8bPfvazyP4aUyjNmDEjzjvvvCgoKEh/Li0tTbclnnnmmRgzZsyqYzfddNP41a9+Ffn5+VXz5KAeEQAAAAAAAAAAKpU0tv/2t79Nl/fffz/++9//pksiafDv1KlTnHLKKTF48OCvVf6yZcvinXfeiSVLlpTbN3PmzHRZKQkHlJSUfL0nAvWcAAAAAAAAAACwVj169Igbbrgh3nvvvXj77bdj+vTp0bhx49h8881j4MCB0b179zXe9/zzz48FCxak0wlU1HO/Xbt2cc0110RxcfFa69GiRQu9/2ENBAAA1qQ0jCMFAAAAAABfkgzzP2jQoHRZHwMGDKh0f8OGDWPXXXf9JlUDQgAAqo/G47rPfz8AAAAAgNonK1y/BVgDAQCoLr58AAAAAAAAADVIAAAAAAAAAAAA6gEBAAAAAAAAAACoBwQAAAAAAAAAAKAeEAAAAAAAAACoF0rLlqxMVwKADBIAAAAAAAAAqBc2jMb/rC/+AVCeAAAAAFDl9DkBAAAAgJonAAAAAFQ5jf8AAAAAUPMEAAAAAAAAAACgHhAAAAAAAAAAAIB6QAAAAAAAAACAOiXL3HMAFRIAAAAAAAAAAIB6QAAAAAAAAAAAAOoBAQAAAAAAAAAAqAcEAAAAAAAAAACgHhAAAAAAAAAAAIB6QAAAAAAAAACAOiUr0xUAqKUEAKAGDB06NB588MEqLfPZZ5+t0vIAAAAAAACAuk0AAGrA2LFj4/nnn6+SskpLSyMrS7YRAAAAAAAAWJ0AANSAgQMHxpFHHrnG/ZMnT46XXnopSkpKomHDhtG/f//o2LFjFBQUxEcffRQTJkxIj2vQoEEcfPDBkZOTU1NVBwAAAAAAAOoIAQCoAccdd1y6fFXS4H///ffHWWedlYYEzjzzzDjooIOiadOmqx03evTouPHGG+OGG26IwsLCuP7662uq6gAAAAAAAEAdIQAAGfT+++/Hz3/+82jZsmXceeedsckmm1R43KabbhqXXXZZ9OzZMw0LdOrUKa699toari0AAAAAANQSZsoFqJAAAGTQCy+8ENOmTYujjz56jY3/K+Xl5cXpp58e11xzTfztb3+L3/3ud9GuXbsaqikAAAAAAABQ2wkAQAZ98MEHUVpaGv369Vvn+2y88cYxbty49L577LFHNdYOAAAAAAAAqEsEACCDlixZkq6nTJmyzveZMWPGavcFAAAAAAAASAgAQAb17t07XT/yyCNx8sknR9u2bSs9/tFHH433338/vZ2MBAAAAAAAAACwkgAAZNDgwYOjadOm8frrr8eZZ54ZF110UXTu3DkaNmy46piSkpKYN29ePPfcc3H88cdHUVFRer/NNtssgzUHAAAAAIDMyEqXrExXA6BWEgCADNp5553jBz/4QQwdOjTuvvvueOGFF2LrrbeOXr16RatWrWL58uXp9ABjxoyJkSNHxtKlS6Nnz55x3XXXZbrqAAAAAAAAQC0jAAAZlPT0v/rqq6NJkyZxww03xOTJk2PSpEnpvqysFenF0tLSdJ2XlxfdunWLv//979G3b9+M1RkAAAAAAAConQQAoBZIhv4/6KCD4qmnnopXX301xo0bFwsXLkwb/du3bx9bbLFFDBkyJA444IBo06ZNpqsLAAAAAAAA1EICAFAL5Obmxk477ZQuAAAAAAAAAF+HAAAAAAAAAAB1yhez6ALwFQIAAAAAAAAA1B0a/wHWSAAAaomZM2fG2LFjY/bs2bFs2bIoLS1d47FZWVlx6KGH1mDtAAAAAAAAgNpOAABqgUsvvTSuu+66WPj/7d0HmFTV2cDxdylLLyIgKiqggmDBBsaoGHssiRpjN7YYW+yJmlixl1g/Syyx18SSWBIVjYoVNbFGxY4dFUVsFCmf/2MuGYaZ2VnY3dny//nss7g7M3tn7rmnve8598svY/r06TFz5swan2MCgCRJkiRJkiRJkqRcJgBIFTRp0qTYe++94y9/+Uta8d+uXbvo2bNntG/fPq3ylyRJkiRJkiRJkqRymQAgVdADDzwQf/vb31Kwf5tttonDDz88evToEW3aeGlKkiRJkiRJkiRJqh2jjFIFPfLIIzF16tTYcMMN4+KLL46uXbtW+pAkSZIkSZIkSWr03ENXkgozAUCVMStsnb/zwQcfpNX/m222mcF/SZIkSZIkSZIkSfPFBABVhsH/hO3+0blz5wofiSRJkiRJkiRJkqSmzgQAqYJWXXXVaN26dTz//POVPhRJkiRJkiRJkiRJTZwJAFIFrb322rHkkkvGqFGj4s0334wBAwZU+pAkSZKkFsL7kkmSJEmSpObHBACpgvr37x+XXXZZ7LXXXrHbbrvFEUccEeuss05UV1dX+tAkSZKkZs7gvyRJktSUVdmll6SCTACQKoiV/8cff3z69yOPPBKbbLJJdO/ePe0E0K5du6LPq/quZ/Pwww831GFKkiRJkiRJktRoGPuXpOJMAJAq6JNPPonHH388Zs2aNftnEydOjH//+98ln1dlaqMkSZIkSZIkSZKkPCYASBW00EILxbrrrlvpw5AkSZIkSZIkSZLUDJgAIFXQ+uuvn74kSZLU+LDn0qwaHyVJkiRJkiQ1HiYASJIkSVIBBv8lSZIkqTHzVrmSVIgJAJIkSZIkSZIkSZIkNQMmAEiSJEmSJEmSJEmS1AyYACBV0PPPPx+33nrrPD135MiRdXswkiRJkiRJkiRJkpo0EwCkCnrhhRfihBNOiFmzaneH2aqqKhMAJElShdBv8T6LkiRJkiRJUmNkAoBUQb17944111yz5GOmTp0an3zySbz77rspUWDo0KHRuXPnBjpCSZKkfAb/JUmSJElqTBypS8plAoBUQeuuu26stdZaJR9DAsCnn34aN998cxxzzDGxwgorxJlnntlARyhJkiRJkiRJUuNTZdT7f/wsJOUwAUCqoNatW6evUtq3bx/dunWLww47LKZNmxbHH398/PCHP4w99tijgY5SkiRJkiRJkiRJUlNgAoDUhJAEcMUVV8Tvf//72HrrrVNigCRJkiRJkiRJkiTBBACpCamuro6BAwfGqFGj4vnnn6/x9gGSJEmSJEmSJEmSWg4TAKQmZsqUKen7pEmTKnwkkiRJkiTVh1nhjWwlSZIkad6YACA1IR988EE88cQT6d+9evWq8NFIkiRJklQfDP5LkqSatcweg4mSkmpmAoBUQdOmTYtvvvmm5GNmzJgREyZMiEceeSTOOOOMtAPAUkstFUOHDm2go5QkSZIkSZIkSZVn8F9SzUwAkCropptuil133bXGx82aNSt9oUOHDnH55ZdH+/bt6/noJEmSJEmSJEmSJDUlJgBIFcYK/3J07949hg0bFnvvvXesvvrq9XxUkiRJkiRJkiRJkpoaEwCkClp77bXjtttuK/mY6urq6NWrV/Tv3z+t/nflvyRJkiRJkiRJ0nxi42XvqqBmyAQAqYL69u2bviRJkiSp/jm7JUmSJEmzOTxSM2UCgCRJkiRJLYKzW5IkSWo+quzeSlJBJgBIjcy3334bkyZNiqlTp0br1q2jc+fO6UuSJEmSJEmSJEmSSjEBQGokPvnkk7jooovivvvui88++ywlArRq1Srat28fSy65ZOyxxx6xwQYbpJ9JkiRJkiRJkiRJUj4TAKQKmzFjRvzlL3+Jgw46KCZMmBCzZs2a6zHPPvts3HrrrfGTn/wkzjrrrBgwYEAFjlSSJEmSJEmSJElSY2YCgFRhZ599dowcOTImT54cbdq0iWHDhsUPfvCDWHDBBWPatGnxxhtvxKhRo+Ljjz+O22+/PT766KO488470+8lSZIkSZIkSZIkKWMCgFRBL730UlrRP3Xq1Bg6dGhceOGFKfifj10BjjvuuDjzzDPjiSeeSN9PPvnkChyxJEmSJEmSJEmVVZW+qip9GI2In4Wk/zEBQKqgRx99NK3sHzx4cNx8881Ft/avqqqKo446KhZZZJHYZ5994vzzz4/DDjssunfv3rAHLEmSJEmSJEmSWhhuXWySgdRUmAAgVdAzzzyTVvdvvvnmRYP/GW4PsOeee8a5554bY8eOjRdeeCHWWmutBjrSJsI+iCRJkiRJkiRJdcyJd6kpMQFAqqBJkyal70sttVTZz1l88cVTAsDnn39eT0fVhNkHURHmhkiSJEmSJEmSpJbABACpgjp37py+f/TRR2U/59NPP53juZJqZvBfkiRJkiRJkiQ1FvW5cNEEAKmCll122aiqqorbbrstfvnLX0bPnj1LPv7OO++MZ599Nqqrq9NzJUmSJEmSJElqcarCVT+SmrT6rMJMAJAqaLXVVovu3bvHk08+GXvvvXdce+210b59+4KPveuuu2L77bePGTNmxM9//vPo3bt3Ax+tJElqsrwXiiRJkiRJktQimAAgVdAqq6wSu+22W5x99tnx17/+NZZeeunYdNNNY8iQIdGpU6cU7B8/fnyMGTMmRo8eHZMnT46BAwfGySefXOlDlyRJTYnBf0mSJEmSJKlFMAFAqqA2bdrESSedFJ07d45TTjklPvjgg7jkkkvSbQFatWoVs2bNipkzZ6b/B6v+r7nmmlhiiSUqfOSSJEmSJEmSJEmSGhsTAKQKq66ujqOOOirWWGONuO6662Ls2LHxySefxJQpU6J169bRpUuXWHTRRWOdddaJffbZJ7p161bpQ5YkSZIkSZIkSZLUCJkAIDUCBPrXX3/9FOSfNGlSfPPNNzF9+vS08r9du3YpCaBjx46zdwKQJEmSGruxL70YN1x3Tbw97q1YsGev2GSzn8aP1l0v9X3L9fXXX8UN114TTz7xeMSsWbHSqsNi2+12jB4LLjjXY1/+7u/d/89748Xnn4uvvvoqevXqHetv9OP48Sab2Y+WpAr68ssv4i83Xh9jHn8s3epw1WHDY9fdf5XmOWrjkYdHx+1/+2u8//570a9f/9hmux1i6IorzfW4qVOmxH/+80L866knvvt6Mj7//PMYMmTZOO7EU+rqLUmSGgl7+ZJUmAkAUgWxop9V/7vvvnucffbZaTK0R48e6UuSJElqikhk/dstN8XZZ5wWC3zXr+3de6F468034ojDDoltd9gpDjzk0LKSAMaNeysOP+TA+PCDD6Jf//7p9ljXXXVFPPzgA3HGOefFIov2nf3Ys/9wWlx/7VUpMaDXd3+vXXV1jHv7rRh59BHx15tviuNOOjUWXmSR+nzbkqQC3nvv3fjdoYfEa6++EgOWXCrdCpHksNv+emucc96FMXjIsjW+Bu3KHy/4v7j8T5dE38UWi549e8Wzzzwdd9/199j/wENix1/sEm3btp39+LPP+kP8+YbrUlvTtWu3mDjxs+++d63PtylJkiQ1KiYASBXEyqSvv/46VlhhBVclSZIkqVkY+/KLcdEF58ViS/RLqy0X7btYfPnFF3H+uWfFTTden4I9G2/6k5KvwY5YZ//h1Pjg/ffikMN+H+uuv0FKAHjh2WfjiMN/E4cdcmBccc0N0ba6Oj2+qlVV7H/wb2ONNdeKBRfsmX7+xReT4vJLLoq/3XpzXHvVFXHo749siLcvScpx9pmnf9cuvBTHHndirDli7RSUH/3AA3HcsUfGheefG3846/+iffv2JV/j2WefjuuvvTpWXHnlOP7EU6NHjwVj/PgP4/DfHhxXXHZprPaD1edIJFhuueWj94GHxJBll4tOnTrFzjtuW99vU5IkSWpUTACQKmjRRRdN36dOnVrhI5EkSZLqxgP/vC8+/3xiHHzo4TFomcHpZ507d479D/5N2o75gnPPiXXX2yDalQj4jHvrzXj+uWdj4KDBselmP43qdu3Sz3+41oj40Xrrx1133pFuC7DGWmunnx/0m8Pmeg2CPvvsf2Dc/rdbY8zjj9bDO5UklZJuzXLfvbHOuuvHTzbfcvbPN/vp5nHnnbfFE2MeT4le7AxQDMlf5551RrDJ85lnnTf7FjBLfvecI446Nn61+87x5xuvi5HHn5zz+lvM/vfXX31V5+9LkiRJauxMAJAqaLXVVot27drFI488Er/61a/SVniSJElSU/bkmMejbdvqWHud9eb4ebdu3WPppQfGc88+E2+++UbJbZ9fefml+OrLL9PK/yz4D1aODl1x5bj773em18kSAIphlWj7Dh0MAElSBTz80Oi02+Gaa42Y4+f8bKdf7JLai/vuHRV7lkgAYKX/Sy/+J1ZaeZXZwf/MSiuvnBZWkHh29LEnlHV7GUmSJKklMNooVdA666wTq666atx7773xwAMPpP83CUCSJElNFSs1Wb2/2OKLp1X/uUh87dmrd7qX80fjPyyZAPDqq2PTa7F9c75FFlk0BY/Gf/hBeq1S/ec333g9Bf/79R8w729KkjRPXnvt1ZTEtVCfhef63Uorr5rq8uefe6bka7w9blzMnDkz+i62+Fy/q6pqFf0GLBkPj34wPvyuTejbd7E6O3ZJkiSpKTPSKFVQq1at4qijjorjjz8+dtppp9h8881j/fXXj6WXXjo6duyYBsPFDBw4sAGPVJIkSarZ119/HZMnT46evXrN9Tv6vl26dEmBnK9qWJH/6YQJ6Xuh1+nStWvqJ3/11dfptYrhNlvXXHVF+rvsJCBJajgzZsyIL7/4Itq2aRsdOnSY6/ckibVr1z7Gjx9f8nU+nzgxfe/6Xd1fyAIL9EjfaTdMAJCklqfE9LkktWgmAEgVdMcdd8TOO++c/s0Kpz/96U9x2WWX1fg8JjxZ7SRJkiQ1JpMnf5O+V1e3K/j7Nm2rU7/322+/Lfk6U6ZM+f512s39OtmK/+nfvQavVQg/f3j0A3HXnbfHYkssEVtutXXZ70GSNP9IAOCrqlVV0a3527ZtG1P+224UM3Xa1O8f26Ztwd9XV1en71m7IUmSJMkEAKni8icti01izq8xY8bEfffdV/T3gwYNiq23dmJUkiRJ865Tx07p+9Spkwv+/ttp01Iya3XbwoGcTLZadGqBgM70/yYPtK1uW3DHLHYFuOcff49TThwZSy09ME4+/azo2rVbrd6HJGn+EPRv06Z1zPquTp4xo/AChmnftQkd/9tuFNO+XfvvH/vttIK/Z7cXFNplQJIkSWqpTACQKmiDDTaIBx54oEH+1iOPPBJHH3100d9vscUWJgBIkiRpvnTs1Cl9ffzRx3P9jsD8F19MSlvydy6ylXOmZ6/e6fvHH30Uiy/Rb47ffTFpUkqa7dy5S8FVpS88/1ycfsqJ0a59+zj2hJO/e/4S8/6GJEnzhPq5W/fuaceXb76Ze5U/dfnUqVNi4UUWLfk6C/RYYPbjC/ns00/T96zdkCRJkmQCgFRRvXv3Tl8NYcSIEXHqqacW/f3SSy/dIMchSZKk5m2ppQbGSy++EJ9P/Cy6//fezJgyZXJ8/PFH0aZN21hk4dIBn8GDl02r+1947tlYdfhqc/zu3ffeSQkAi/btO0cCAD8b89ijcdwxR0S3bt3i2BNPiaUHDqrbNydJKtsyywyJUXffFe+/995cv3tizOPp+8qrrFryNfoPWDIljo0bN26u35FY9sbrr8aCPXtGnz596uSYJUmSpObABACphRg+fHj6kiRJkurTaquvHs8/90zcd++o+Pk2283++eeffx6vvfJKLLDAAjFgySVLvsbSgwZF127d4r77RsUOv9glreYH95N+5t//TsH+oSutPMdzxr78Uhx3zJEx/dvpcdyZp8XQFVeq+zcnSSrbiLV/FOeefUaMfvD+2Hb7HWf/nDr8qisvi7Ztq2P9DTYq+Rq9evWOlVZeNZ579un45OOPo1fOIorHH3skxo8fH9tst0NKEpAktSxV//1PkjQ3EwAkSZIkSXXmR+uuH7fefFNcd82V0XexxWLppQfFJ598HOefe1ZMmTolRp54SrRu8/1Q9PXXXo1dd9ou+vUbEBdeell07dot/XyJfv1i2PAfxMOjH4hrr74yNv3JT1PA6OGHRscjDz0Yq63+w1h5lWGz/+YrY1+Oo39/WEz+5us4+NDfRb/+/efaLpqEAklSwxmw5FKxxZY/jztu/2v86ZKL4sebbBrVbdvGXf+4M15+6cVYd70NomevXrMff8bpp3zXdlwVxxx3Qmz5s//dovCgQ34b++71y9j/13vFEUcfG337LhZvvvFGnHbyiWn1/8+33m6Ov/vN11+ndif9+7+3H5g6ZUq8Pe6t9O+OHTulv8tOM5IkSVJzZAKAJEmSJKnOsO3+4UccHUcfcVgcfsiB0aFjx5g6dWpM/uab+NU+v441R6xd42u0b98hDvvuNT54/7249KIL4883XPfdT2eloP6QZZePU/9wdrRt23b24y+68LwY99abKbHg4u/+fcmF58/1mv+478E6fJeSpHLsd+BB8d5776R6+obrromqVlWpLu+z8MJx4CG/jXbt2tX4GkOWXS5232OvtJvAr/f+VXT4ro0gsD958jdx5DHHxZJLLTXH45966om0IwxIHsMrr4yN3XbeIf177R+tm57Xpo3TopIkSWqe7OlKFXTnnXfG73//+1o9h8Fx165dY+mll4411lgjfvCDH8RS3w123e5OkiRJjQH90nXX3yD69b8p7v7HnTH+ww+je/fuscZaa8ew1X4wx4rLzp27xDrrrR+9ey0Ubdu0neN1evToERdfflXc9fc748UXng9iOIOHDIkNN94kunzXH8617LLLRbvq6gZ5f5Kk8i24YM8457wL456774r/vPBczJgxM4YMWTY233KraP/f27tkBg1aJjbY8Mex6KJ95/g57cquu+8RQ4euGA8+eH+6FcDCiywSG260cQxaZvBcf3OBBXrEqsNWK3pMJAy4+l+SJEnNmQkAUgVNmjQpXnzxxdn/nw1Aswz13J/l//zBBx+Myy67LPr16xfHH3987LDDDg1wxJIkSVJ52Pp53/0PKvkYVoCecPLpRX/foUPH+NnPt0lfpeyx177zcoiSpAbQqVPn+NlWW6evUn6y+Zbpq5iVVlk1fdVkhaErxulnnlPbw5QkSZKaDRMApApaaaWV4oQTToh77rknHnvssRTMHzx4cAwZMiS6deuWtrR75ZVXYuzYsfHaa6/FEkssEVtssUVKCnjuuefS11tvvRW77757WiH14x//uNJvSZIkSZIkSZKk+ueGLpJUkAkAUgUNGjQovv7663jhhRdiv/32i/333z8F+XPvQ8eq//Hjx8eVV14Zxx13XHz66adx3nnnRevWrVNiwJ577hlPPvlkHHXUUTF8+PCUCCBJkiRJkiRJkiSp5TEBQKqgxx9/PC666KIYOnRojBw5Mt0bNR+r/RdeeOH43e9+l1b8X3XVVfGzn/0sNtlkk1hhhRXi/PPPj4022ijefvvteP3111MSgCRJkiRJkiRJkqSWxwQAqYJGjx4dX3zxRdq6v1DwPxeJANwu4C9/+Uucc845KQEASy21VCy55JJpF4GPP/64AY5akiRJkiRJkiRJUmNkAoBUQazYZ4v/RRddtKzHDxgwIH1/+umnZ/+sa9eu0a1bt5g2bVpMnjy5Xo5TkiRJkiRJkiRJUuNnAoDUCLz00ktlPW7MmDFFf9eqVato3bp1XR2SJEmSJEmSJEmNVlWlD0CSGikTAKQKGjRoUPp+5513xj777BOLL7540cdOmTIlDjjggPTvYcOGzf75V199lb7at28fnTt3rt8DliRJkiRJkiRJktRomQAgVdB6660XZ555ZtoBYJdddkkB/nXWWSe6d+8++zHffPNNPPXUU3HeeefF888/Hx07doxDDjlk9u8//PDDeP/996NLly7Rp0+fCrwLSZIkSZIkSZIkSY2BCQBSBa266qpx4IEHxjHHHBOjR4+ORx55JNq0aRNLLbVULLjggvHll1/G66+/HpMnT44ZM2bErFmzYptttom111579mvwnPfeey+WX3759DxJkiRJkiRJkiRJLZMJAFIFVVVVxVFHHZVW7rPC/z//+U9MnTo1XnzxxfQ7Av7Z47g9wM477xy/+c1vorq6evZrbLLJJunxbP/P7gCSJEmSJEmSJEmSWiYTAKRG4Je//GVa2f/EE0/ETTfdFM8++2xMnDgxBfWXWWaZFOTfeOON064AJAPkWnjhhdOXJEmSJEmSJEmSpJbNBACpESCo37Vr19hggw3SlyRJkiRJkiRJKqKKefVKH4QkNU4mAEgVNH369GjVqlX6qo2HHnooRowYUU9HJUmSJEmSJEmSJKkpMgFAqqB77rknpk2bFltuuWXZz7n//vtju+22i48//rgej0ySJEmSJEmSJNUFNiuYVemDkNRimAAgVdDnn38eBx54YLRt2zY222yzGh//7LPPxu677x6ffvppAxydpEaNEYPbnEmSJEmSJEmNnsF/SQ3JBACpgjp06BBffvllSgJYZJFFYuWVVy762DFjxsSmm24akyZNilVWWaUBj1JSo2TwX5IkSZIkSZIk5TEBQKqgddddN37605/GLbfcErvsskvccccd0a9fv7ke98Ybb8Ruu+0WEydOjDXXXDOuvfbahj9YSZIkSZIkSZIaiSpXyEhSQSYASBXUvXv3uP7662OjjTaKhx56KLbZZpu4/fbbo0+fPun3s2bNihdffDFGjBiRbhcwYMCAuPLKK2PxxRev8JFLkiRJkiRJklQZhv4lqTgTAKQKa9u2bVx22WWx9dZbxzPPPBP77bdfSgqorq6OcePGxc4775y2/R8+fHj6OUkAkiRJkiRJUkvAfbMN9EmSJJXPBACpEejfv3/cdNNNsfrqq8df//rX2HXXXeO4446LH/3oR/Hhhx/GggsuGJdffrnBf0mSJEmSpHpDmHlWpQ9CeQz+S5Ik1Y4JAFIjQRLAzTffHDvuuGPceuut8eCDD8b48eNjhRVWSCv/hwwZUulDlCRJkiRJasYM/kuSJKnpMwFAakTWXHPNOPvss2PbbbdNwf9u3bqllf8G/yVJkiRJkiRJkiTVxAQAqQE89dRTMXbs2LIfv95668U///nP2GGHHeLFF19MX7mqqqpip512quvDlCRJkiRJkiSpSajyHiGSVJAJAFIDYAv/Cy64oOzHz5o1K2bOnBmXXnpp+irEBABJkiRJkiRJkiRJuUwAkBpAly5dYqGFFqr0YUiSJEmSJEmSJElqxkwAkBrAoYceGvvtt1+lD0OSJEmSJEmSJElSM2YCgNQA2AGAL0mSJEmSJEmSJEmqLyYASJIkSZIkSZIkSZLUDJgAIFXQzJkzY8KECTF9+vTo2bNnVFdXl3z8+PHj03N69OgR7du3b6CjlCRJkiRJkiRJktQUmAAgVdAbb7wRe+yxR8yaNSsuv/zyWGqppUo+/qyzzop//OMfseeee8YBBxzQQEcpSZIkSZIkSZIkqSkwAUCqoGeeeSbGjBkTa6yxRvTp06fGx++8885x9tlnxxlnnBH77rtvtGnjJSxJkiRJkiRJkiTpe0YPpQp6/vnn0/b/w4YNi86dO9f4+OWWWy4GDBgQr7/+evpaZpllGuAoJUmSJEmSJEmSJDUFJgBIFfT222+n74MGDSr7Of3790/B/7feessEAEmSJEmSJElSi1RVVekjaDz8KCTlMgFAqqBZs2bN83O//fbbOjwSSZIkSZLqG2Ngp6clSZIkqT6ZACBVUI8ePdL3V155pazHkzAwbty4OZ4rSZIkSVLTYPBfkiRJkuqbCQBSBQ0dOjRatWoV9913X3z00Uex0EILlXz8zTffnLb/79ixYyy33HINdJSSJEmSJEmSJEmSmgITAKQKGjZsWCy44ILxzDPPxLHHHhsXXXRR0ceOGTMmdtlll7QLwI477hjdu3dvuAOVJEmSJEmSJEmS1OiZACBV0LLLLht77LFHnHrqqXHppZfGc889F1tttVUMHjw4unTpEtOnT48PP/wwnnjiifjLX/4SU6dOjYEDB8aRRx5Z6UOXJEmSJEmSJEmS1MiYACBVUOvWrWPkyJHx9ddfx/nnnx9PPvlkPPXUU1FdXZ1uDcBqf5IAvv3226iqqor27dvHxRdfHH379q30oUuSJEmSJEmSVDFV3/0nSZqbCQBShbVp0yZOOeWUGDp0aNx4443xn//8J8aPH5+C/+jUqVMMGjQoRowYEYceemgsscQSFT5iSZIkSZIkSZIkSY2RCQBSI8DK/l133TW23nrr+Pzzz9OOABMnTkw/79q1a3Tu3DkWWGCBlCwgSZKkpoP1KLMqfRCSJEmSJElqMYwmSo0Iq/35kiRJUvNg8F+SpPlEY+oOz5IkSVLZTACQJEmSJEmS1DgZ/JckSZJqxQQAqRGZNWtWTJs2LaZOnZr+zVcx3bt3b7gDkySpBXPRmSRJkiRJjUtV1fdfkqS5mQAgNQIE/e++++647bbbYty4cSkBYObMmUUTAKq+69k89thjDXyUkiS1TM4nSJIkSZIkSWoqTACQKmzChAmx9957x9/+9rcaV/1nqkxtlCRJDchdECRJkiRJkqSmwQQAqYI+//zz2HnnndPq/4UXXjh22mmn9O8XXnghtt9++1hhhRXi7bffjnvuuSfeeuutaNeuXey///7Rt2/fSh+6JKlZMsyrwiwVkiRJkiRJUtNgAoBUQWPGjImHHnoo+vTpE3fddVcK+L/xxhspAWC99daL3XffffZjjz322DjttNPS1v/sFiBJUt0zzCtJkiRJkiRJTZkJAFIF/etf/4rJkyfHFltsEUOGDCn52COPPDKqq6vjmGOOiZNOOinOPvvsBjpKSZIkSZIkSZIaF5cxSFJhJgBIFfTmm2+m76uvvnq0afP95VhV9X23Zfr06XM8luA/SQCXXnppnH/++WlHgO7duzfo8UqSJEn1z9uRSJIkSZIkzSsTAKQKYvU/unXrNvtnHTt2TN+/+OKLgs9ZZpll4t133023CVhrrbXq/yAlSZKkBmXwX5IkSZIkaV6ZACBVUJcuXdL3KVOmzP5Z79690/e33nqr4HOmTZuWvn/66af1fHSSJEmSJEmSJEmSmhITAJoQN8JsfpZeeun0/fXXX5/9s2HDhqXv9913X9oFoGvXrrN/9/LLL8fTTz+d/r3wwgs34JFKkiRJkiRJkiRJauxMAGhCDP43P0OGDIl27drFs88+m1b2V1dXx6abbpp2BiAp4Mc//nFcdNFFseyyy8aoUaNijz32iC+//DIWWmihWHnllSt9+JIkSZIkSZIkVYZBE0kqyAQAqYJIAFh88cXjww8/TF9LLLFEdOrUKQX999133xgzZkystNJKsx8/a9as6NGjR/p927ZtK3jkkiRJkiRJkiRJkhobEwCkCiLgf9ddd8WMGTOiT58+s3++9dZbp90ADjnkkHj33Xdn/7x///5x7rnnxsYbb1yJw5UkSZIkSZIkSZLUiJkAIFVQq1atUlA/X5s2bWKrrbaKLbfcMl599dUYP358LLzwwjFw4MCoqnJfI0mSJEmSJEmSJElzMwFAasRIEFhmmWXSlyRJkiRJkiRJkiSVYgKA1EhwG4APP/wwPv7443jnnXdi4sSJ0a5du7Tyf6GFFoq+fftG165dK32YkiRJkiRJkiRJkhopEwCkRoDA/wknnBCjR4+Ot99+O7755pvZv2MXgAUXXDCGDBkSe++9d2yzzTbeBkCSJEmSJEmS1IJVhbPkklSYCQBShb3xxhux8cYbx+uvv54C++3bt4+ePXtGmzZtYubMmTF16tT47LPPUnLAQw89FP/617/ipJNOiurq6kofuiRJkiRJkiRJkqRGxAQAqYLee++92HrrrVPwv0OHDrHrrrvGRhttFIsttlj6f24LwK0AXnnllbj00kvjqaeeigsvvDAGDx4cu+++e6UPX5IkSZIkSZIkSVIjYgKAVEEPPvhgvPDCC9GtW7e4/vrr004Ahay55popUWCzzTaLRx99NA455JDYaaed3AVAkiRJkiRJkiRJ0mwmAEgVNGbMmLTKn8D+euutV/KxXbt2jZtvvjmWX375mDBhQtoNYI011migI5UkSZIkSZIkSZLU2JkAIFXQp59+GlVVVbH22muXtZq/d+/eMXTo0PjnP/+ZkgAkSZIkSZIkSWppqviqqvRRSFLjZAKAVEF9+/ZN37/99tuynzN9+vT0fbHFFquXY5IkSZIkSZIkSZLUNJkAIFXQD3/4wzjvvPPi/vvvjz333DNat25d8vFfffVV2vqfxIEVV1yxYQ5SkiRJkiRJkiRJUpNgAoBUQWuttVba/p8EgMsvvzx23nnnaNeuXcHHvvbaaylJgFsFnH/++dGqVasGPlpJkiRJkiRJkiRJjZkJAFIF9ezZM/785z/HAQccEAcffHBcffXVsffee8c666wTvXv3jqlTp8bYsWPjpptuiuuvvz4++eSTuOaaa2KTTTap9KFLkiRJkiRJkiRJamRMAJAawEEHHZS2+q/Jo48+Go899ljB382aNSuqqqpi2223Td+nT59e14cpSZIkSZIkSZIkqQkzAUBqAATv+Sr3sfPyO0mSJEmSJEmSWoqqSh+AJDVSJgBIDWCnnXaKVVddtdKHIUmSJEmSJEmSJKkZMwFAagDDhg1LX5IkSZIkSZIkSZJUX0wAkCRJkiRJkiRJkiSpGTABQJIkSZIkSZIkSU1LVaUPoBHxs5CUwwQASZIkSZIkSZIkSZKaARMAJEmSJEmSJEmSJElqBkwAkCRJkiRJkiRJkiSpGTABQJIkSZIkSZIkSZKkZsAEAEmSJEmSJEmSJEmSmgETACRJkiRJkiRJktSkVH33nypj4sSJce+998bzzz8fn332WbRv3z769+8fI0aMiKFDh87360+ePDn++c9/xpNPPhmffvpptGnTJhZffPFYbbXVYvXVV4/WrVvXwbuQmi8TACRJkiRJkiRJkiTV6NVXX4199tknPvzww5gxY8bsn1dVVcVll10W++67b/zqV79K/z8vJkyYEHvuuWe88sorMX369Dl+d9VVV8U222wThx56aLRr126+3ofUnJkAIEmSJEmSJEmSJKmkb775Jo499th47733YqGFForNN988Bg0aFJ9//nncc8898e9//zv++Mc/xqKLLhqbbrpprV//66+/jmOOOSZefPHFWGCBBWLjjTeOlVdeOaZOnRr33XdfPPzww/HnP/85Fltssdhll13q4R1KzYMJAJIkSZIkSZIkSZJKuvDCC+OZZ55J/z7xxBNjzTXXjFatWqX/32STTWL//fePf/3rX3Heeeel4H32u3I9/vjjMXr06LTl/8EHH5xW+2c7CfD6hx9+eIwaNSrOOuus+NGPfhRLLLFE3b5BqZkwAUCaX7MivNWQpCbHukuSJEmSJElSmcaPHx+XX355zJo1K37605/GiBEj5vh9jx494te//nXsvvvu8dZbb8Utt9wSW2+9ddmvz+0EzjnnnLTt/1JLLZX+Ru5tBDp27BjHH398jBkzJr744ou48sor024B83qrAak5MwFAml+2LZKaIusuSZIkSZIkNVHEfI37Niy29ydIz6r+vfbaq+Bjhg8fHv37948333wzbrrppthqq63K3gXg1Vdfjddffz39e4cddogOHTrM9RhuC8DK/9tvvz2ee+65mDRpUnTv3n2e35PUXJkAIEmSJEmSJEmSJKkoAvRYeOGFo0+fPgUfw9b9q6++ekoAePfdd2PChAnRu3fvsl6fBAN2F2BF/3rrrVf0cSuttFJKAOC1+TIBQJqbCQCSJEmSJEmSJEmSCmLlP7cAAAF9Av3FLLPMMun7t99+W6sEAG4bgK5duxZNMAAJCG3bto0vv/wyfUmamwkAkiRJkiRJkiRJUhM1bdq0ebrjJ9vzlwrmZ2bOnBkTJ05M/+7WrVvJbf0XXXTR9H369Olpi/5yffTRR+l7r169Sj6uU6dOUV1dHd988036kjQ3EwAkSZIkSZIkSZKkJuroo46ap9Xwa6+9dmy33XY1Po6t+UkyAMF3tukvhgA9SBrInlMTdhjIHtu+ffuSj2X1f+vWrdMxTZ48uazXl1oaEwAkqRGgg0O2ItmWHTp0qPThSBXDdcDgoGPHjiUziaXmjAHs119/nQbT2aBZDY+pjBLzGWoAUyZPienTv4323/WNylmRIjVH9o0aB9oD24TKSX2jr/7bN+ps36hSvAQqb8qUKWk77Q72jaTZrJv+55FHHolPP/201s9jO/1y0B5TB4E6qFQCQLt27eZ6Tk3o8zJHDgL8pdAvzvrG1I2S5mZPQZIagZdeein222+/WHHFFePcc8+t9OFIFbPvvvvGuHHj4qqrroolllii0ocjVQQZ+1tssUV06dIlbrvttkofTovVrk1VtHM6qaL+cNJpcf/998dJJ50UI0aMqPThSBWxzz77xNtvvx1XX311LL744pU+nBarTSu+bBMqZdKkL2Lbn2+Z7gf8t7/9rdKHI1XMKaeckvpGJ598cqy11lqVPhyp4mia2xnhajAE/LPAPFv7E9wvJgvKE6SvKZifyb0VQU1JAyQKkDAAF9NJhVk9SlIjQLDnySefnJ0dKbVUL7zwQowdO9bsXbVoDKSfeuqpWGCBBSp9KFJFvf766/HEE0/Mvs+k1BLRN3rllVfsG6lFy/pGPXr0qPShSBX12muv2TeSVNS11147ewV9bXTr1q2sx5EAkG3NP3Xq1JIJAF999dXs53C7gHKwpX/22Jq29SdBgPfK65sAIBVmAoAkSZIkSZIkSZLURA0YMKBeX58V+lky3ueff14y2eDdd99N31nRX5vFDYssskj6/vHHH5d8HLdNJAmB22R560SpMBMAJEmSJEmSJEmSJBXECv0+ffqkf48fP75kAsCLL76YvrOiv1evXmX/jSyJgd1y33nnnaK3wCLBgB2CevbsmW6fKGluJgBIkiRJkiRJkiRJKmrIkCHpOyv033jjjRg6dOhcj2Fl/mOPPZb+PXDgwFrdwmf48OFpW39uL3DXXXfFXnvtVfBx3EoXvXv3rlWCgdSSmAAgSZIkSZIkSZIkqahVVlklbevP6vvzzjsv/vSnP831mNGjR8cHH3yQ/r3tttumgH65+vXrF8svv3w8//zzccMNN8SOO+4YnTt3nuMxH330UTz00EPp36uuuqo7AEhFmAAgSZLq3Kzvvsrv3kuSJEmSJElqzBZYYIH47W9/G6effno8/PDDcfPNN8cWW2yRkgIwbty4uPDCC9O/V1hhhdhoo43meo2tt946BfjXWGONuOCCC6JDhw6zf0eywEEHHRT77rtv2mXgqquuir333jvdfgD87LDDDotp06alY9l5550b4F1LTZMJAJIkqc4Z/JckSZIkSZKal5122ikef/zxtNL/5JNPjgcffDBWWmml+OSTT2LUqFFp9T+r8g888MBo1apVrV+fVf0kDtx2221xySWXpL81YsSIdGuBu+++O958881o165dHHPMMbHwwgvXwzuUmgcTACSpEVh66aXj8ssvT/ctklqyE088MSZNmmQHXi0a29uxjV51dXWlD0WqKFZ9bLrppmmbSamlom/0xRdfRJ8+fSp9KFLF2DeSvvfrX/86Nttss1h55ZUrfSiSGrt63Jqzbdu2cdRRR8WMGTPi6aefjnvvvTd9gZX6SyyxROy1115phf+8ILh/xBFHpNdnq/+nnnoqfYGEAubPWfm/wQYb1Nl7kpojEwAkqRHo1atXbL/99pU+DKniNt5440ofglRxTG5znzyppWPCaF4njaTmYpNNNqn0IUgVRyDAvpFk30hSLdTz1pyLL754nHfeefHiiy+mJIDx48dHp06dYvDgwbHiiivGoosuWvS5I0eOjK+++iq6deuW2vhCunfvHqeeemqMHTs2nnzyybSrAIkHAwcOTK/fr1+/edpdQGpJTACQJEmSJEmSJEmSVJaOHTvGsGHD0ldtLLvssmU9joD/8ssvn74k1Z4JAJIkSZIkSZIkSZIkNQMmAEiSJEmSVJ/q8R6ckiRJkiRJuUwAkCRJkiSpPhn8lyRJkiRJDcQEAEmSJEmSJEmSJEmSmgETACRJkiRJkiRJkiRJagZMAJDULJxyyilxxBFHpH/PmjWrwkczp2+//TZ22WWXuOGGG2LvvfeOCy64IFq1alVnr3/UUUfFSSedFEsuuWQ8++yz0blz5zp77XJ88803scUWW8S9994bxx57bIwcObJB/74Ku+WWW2KbbbZJ5eGNN96Inj17VvqQyrbWWmvFI488Eocffniceuqp9fLaI0aMiNGjR9fpa5dr0KBB8eqrr8Z5550X++23X0WOobmiHaA9WHHFFeOZZ56Z/fOxY8fG4MGD078ffPDBWHvttSt1iLVCe7bXXnvFpZdeGjvssENcddVV0aZN3XXfTz755DjyyCOjV69e8frrr0fXrl3r7LXLMX369Pj5z38et912Wxx44IFxzjnnNOjfV9P11ltvxcCBA1MZevLJJ2PYsGF19toTJkyITTbZJJ566qnUv8r6lw3pX//61+z3NHHixOjevXuDH4Pq3meffRYPP/xw6pdVVVWlMrzOOutEx44d6/xv8Xfo6+Djjz9O9Xx9vPa4ceNiiSWWqLPXLtfVV1+dxldobGM/lYdx6/Dhw9NY+f33349FFlmkzl77ww8/jA022CBefPHFuPDCC2Offfaps9cuF2PjDTfcMPWt3n77bevxMjB2vemmm2LdddeNf/7zn5U+nLIxZj399NNjmWWWiZdffrnSh9Picb396Ec/ivHjx8eNN94Ym2++eaUPSZKkijEBQJIkSZIkqY6988478Yc//CElHZKMRrAzF4mam222Wfz2t7+NVVZZpUJHKUmSJElqbkwAkCRJkiRJqmPsRnP++eenf7ODyw9+8IO0S03r1q3TjjQvvfRS/PnPf44HHnggxowZE/369avsAUuSJEmSmgUTACRJkiRJkuoY29OvttpqaWtrbnmy2GKLpe3/MW3atLSV/W9+85v46KOP0u/Z9rpbt24VPmpJkiRJUlNnAoAkSZIkSVId417W3Iu40P2/q6ur45e//GV8/vnnceihh6ZbBPzrX/+K9dZbr+EPVJIkSZLUrJgAIKnZmj59enzyySfx5ZdfRocOHWLhhRdOW2+Wa+rUqen533zzTXTq1CkWXXTRejza71cIMQHIFyuCmBTs2bNndOnSpdavNWXKlPj444/Te+DY+/TpE61atSr7OLLPbebMmdG1a9fo1atX2c9X/eHcTJo0KT777LNURtq2bZvuHbvggguWVbZ5PivMOLft2rWLhRZaKH2vjcmTJ6fywd/nb/fu3bsiZWPGjBkxceLE9HlwrXONU075Xltc49l7WmCBBdJ1V5vj4LlfffVVWtHH9cL58HqpX5z3CRMmpM+cz3teV0t++umnqRyxFTPXQ8eOHWv1fM7/+PHj4+uvv051La9Rm3amrmR1A++Fep/rms+F8lhbPJ/2g3ZkXtoPPtMvvvgifTa0X1yXfL6qO9xDnHNEuaMepn+TrSjO8PnzmKy+5zH0K0qhLs3qVZ7P9UAdX9t2AhwbdSOv2aNHj/RVCbwP6grKJOWzffv289T2gc+F8s3r8H4I6OZ/7qWOg/aXtoI6Yn7qrZauUF+IuoZzUm79S/1G+eQ7z6VMlHsu+ZtcW/QduKY4l6X66jXVw/zdTTfdNEaOHJmO55133inrOOoK/TrKNe+Huj7r95f7eeTiM2Ucw+dC21Gb64y/z7XKZ8DzqHvmpU+neZc79qV+4roohPqUMkNbtMgii6R2qD7RjlA2aM9AuaB81NSmFUK9QRlFbethjoM+H58P9c68jtNVO7SbWXkrt36izc3tj9KfoTzXtsxkfWvqJcodZaY+y3s2VufvcszUo5S1eZGN2flO+8jnlv+3uK74W+BaoEzPS90/v7LrkmPiMy6UMFcI7TGfVzZm4Rw75pAkaU4mAMyTWd99NXynSFL5/vOf/8QxxxyTvjMgYLDHlpunnHJKuvdmPu7Nec0118QKK6wQ55xzTjzxxBNx0kknxdtvv50GFgMHDoz77ruvXo6V4/vrX/+a7v/5+uuvp0lzJhiyCc1NNtkkvZdyJ8HYOpRjZwKRgTKTaLznP/zhD0UncjKvvvpqmoDkfqUMFhmE8Xd5/xzDqquuWhdvWfOACYyjjjoq3S+WCTDKCANcghkM6Lfccss45JBDij7/zTffTM//97//ncock+RcE0cccURsuOGGBZ9z1llnpXLJeT/jjDPS3z755JPjgw8+mB10X2ONNdLjGiqQwQTBX/7yl7jtttvS9ckkHBM7XOMcw7bbbhv77bdfmgSoCQkubL178cUXp8l83hOTLazWO+6442pMBHj44Yfj9NNPT9cNnykTJjx/+PDh6flLLLFEXb1t/Rf18dlnnx3XXnttug74zJkkovz/7ne/K/t1mBA7/vjj4/77708TiwQ9mHDad999Y+eddy4YRKKNoK0YMGBAXHbZZem+zVxTb7zxxuyg++DBg+PUU0+NIUOG1OXbLoq/e/vtt6frlJWjWfvB8dN+bLDBBqnuLvf6fOSRR1LZfeutt2a3H6usskoq59QXpXA9Hn300Wn1KtdlFmxdeuml48gjj4zVV1+9Lt5yi3P55ZenOgr0TbhHOGX3tddeS+efz5jtxTlHBPnBhO7BBx+cHp/V94MGDYozzzyzYNmk/rvhhhvizjvvjPfeey+1/9SrnH+ur1122SX22GOPov2Qn/70p2kC9sc//nEqAxzvlVdemSbfeR0my7PflTupO78+/PDDVL//4x//SMeW9WmywCTvZ6eddiorYMw1dd5556VzQX3B63BNbbXVVqneKRVQ4LH08ehbEjjifNB285mwyps6pDZJZy0dAQLK0QMPPDC7vsv6QvRxN9tss/jtb387RwAj68vQL6DOv+uuu9L18u6776Z6jufST2aMQDCzGMryTTfdFH/84x/j/fffT+0R5YfEwS222CIOO+yweUosAW0Q/X7qTo6pvtH/efrpp1O79vjjj89OpuBz4zrv379/Kps//OEPywoG8VnS1lA/8R44JwRoORc/+9nPSiaREXzi+rjjjjtSoI33z2dB33b33XePX/3qVxUJSDV3jAtvvvnm1PehnuS6oK+fjX3XWWeddE3svffeqQ6l3VlzzTXT9UQ/PKsLeZ2tt966Xo6RsSxtyT333DM7OSSrx+mT0GfjthnllA/qCt4PdQHHDoKiv/jFL+KAAw4oGTTkb9Lv5Nqn/0jby+PpZ1HncO03VNvW0lBHXXjhhakMZoF8+hOnnXZawbaX/sx1112X6hP6Abn9GepqdlyhTqkpSEx7fcIJJ8RDDz2U2pqsXuKcjxgxIu3Ysvjii5f9PihDl1xySepHYIcddkjj1dzjeOWVV1KfgvEFx837o1/HWJ33THmn3t5+++3joIMOmv08rlf62RzrT37yk/TvG2+8MdWrXDf8nnr43HPPnf0c5gVoS3m9rH/EZ0sfkbmg5Zdffq73QN3OXAPzRBwLfcNCOAccBzh/zCNlqOO55ugf0sYwz0XdQl2UJfhwnhiL8R5LXdscO58N82fZmGW55ZZLcxUmj0mS9D8mAMwTB6BSYzZq1Kg0qcvgPptUZUKbIA2T1Exy5Aey+f2TTz6Z/s3EBgMRBkEM5pkkYxBYXxgY7bnnnmkAyN/j7zKhyCCLiY/nn38+DYoIeJYKKjG4veiii9IkBJOcTOgw4OO9ESjgc2EwzHvPH0wxaGLC/sADD0zvl4lpBl9M2BHsZUBKYIgJcAasTsQ1rBdffDEN/DmXlBPKNQPbbIUnAWgmC4olAPB7Bunjxo1LE+ScV8o0g3/KPWWeCb58lD9+z+Q4j2FCILsusrJF2WDS8O9//3ustNJK9f1RpOAqk41MwnAcfA5cL0wa8P6YlCAwcNVVV9WY8MLEzoknnpjeE+WdiUXeU7YFLxP9hSZ3eO88j2NhQpFAECtSuHaYOH355ZfTtcZk4cYbb1xfH0WLw2TRPvvsk84LOGd89gQeKJtcJwQcakKwgUQRElp4POWb4AflZ6+99po9KZYfyGEikeuBiUAmowkgUk8TpMjOPZNQjz76aKrXmdSqb0zCM0lGvcBnQd3PtcFkHp/LCy+8EH/729/i1ltvjaFDhxZ9HY6fSXYm27geaD9oFwhy0X6QWEYbRJCs0EpzJjQ5N1mwN2s/mLDl+UxKUocw8Wr7UTucg6x/wrmkLmeils+Yc0QbzWdMW0CgmcRH6h3KAG0Fj6VeI6mD+pFkRiZIcx177LGp/8Bkc1avUqYItvI8JllJeKKfwN/N99xzz6X2Yqmllorf//73KUmHSXLKJNcIf582iscxMV9T3VwXmFimXGZJDFznlD3eE9c41ynlkn5NqYQx+pIEIanPuS64PqgDsv4ZSRa0N4WC+JwT+mQkImSr2rg+OG+0y5wr6hIm6ktdn/oedfxGG22UromsL8T5oB2mruEz5ZzSF8oNqmR9GT57AklZkmDWT+b1eC5tAglVhc4F/QPqRwI4nEvKFO0+5Zu2g2uE65NEmtxgR7l4DRI9sx0F6ht9wF133TVdl3wWXKu0HdThfB707R577LEUMKLOKVVv81oEg5599tl0bfM6BEmpOxiP0V8iIalQwI3Pncc89dRTs1dU8xlw3fGZcH3Rx6TuKad9V/n4fLku6MOQHEayRraTRra7FYHurH6nf0MSJOPobBzC76kP6wv9Cv4e9XdWj9Nfoc9GPc41y9iV/ji/K4Z6nzkA6luOnccybqDfRrtIOaOMFUqW5HrgOOjXg+dTl/DeadvoZ9Gu0raR8Ki6QZ1LMJxkLc4LX/RrKIuM0ygXfC255JJzPI+66JZbbkltP8/J7c8wF8T4jj4t57vQzkS0z9TltPtZgnC2wxzHRJ+Ltp+dIctNPKaNIhhPYJ56jgSEX//613PUiSRPbbfddqlM8hjqO46FepUxC9ce40uuWZLvc3FN0A/kd/TDOC6uadoorulsN4TsWOgrUq9nSQb8Lep46gQ+W9pR2rrNN998juQtXoff83dIeiuG4876rbSR+Z8F74kxFX0gxvT0x7iuOGe0g3wGPIY6h/dR6NrmeuMc0YbzPM4R74cywesx5pAkSd8zAUBSs0MAh0Akk67Ztv1MGvJzJjMIYLMKutCWfUyEMRghm5/JKiaysi1x6wsTb7vttluamGA1A/+fJQAwucGKGiYXGDRef/31RTOaGUiR8cygkGAYr8XkBJOSZKkzObr//vunyc38STQCakzaM/gjqMXxMChm0Mfr/t///V8KIDEBwsQkwWg1DCaa+fyZgOKcMslF8Cab9GYCi4laJisKYbKCMg8CGDyXCQcmZgmQUD6YKGD3C1Z6FcLkHxMmrIynnLAagbLF5DCvQRnheiHwXt/BPcouk/Drr79+WqnH9cLfZJKG4ySQxQQfZf5Pf/pT0ZWZTGAw6cekCpMwlGuuOSYOuH6YuGByhEmS3FU9nA+Cw0zkMBFCPcMECdcLvyPoymQ3kyfUOXxGffv2rdfPpCVgMonELOoqzjefLfUUwUgmi6ifCDqWEzihLmUCj0AQq9KpUynDXFt33313WlXE61CmC+EcE8ju169f2m2FlZJMvlFPUx6YnGQCkgnl+g50Ug+wkoaJOJJVmJTOTSCjLNPeHX744SlZoNhW1CRFkBDDan/aEV6LSTUm4LL2I5sAz98JgJ8ROOB64FiY2MxuG0MA9IILLkgBTj5Prl/aOs0bAh0EQFmtyGfMOWI1I+Xw3nvvTd8JiFDumDRnIpiySd3I+eM8UmdzPnInVKlLaQfWXnvttDo+uxUG7QuBOepVrj0maJmELraalyQB+kuUAa5P6k7qZibjWXnJpDvXDmWxtrfbqC3KKXU1917nes76TtQXHAd9KyaQV1555RQQLobgPQFOPnvKN20O74mfsxqU9obPnfonF20knynJAZR7joX6hmuQ85btykMggUAsCTa1WU3Y0vB5UjfRF2J3HSb3Kd9ZX4jzSnCEpI9i/RCCA+xwQjnn/DNGoI9E4IU6kjqTPjDnIn8nANoNdn6hnSdgTR1Pu8/zszJAn4LrjITb2mxBzDXKe8sScAutvKxrHB99Pso+f4+2NEsAoJ6gfF9xxRVp3MCuN6x4LYbPjOASZZ3kCfpd2Y4A7C5A2efzzPqiGYL/7FLD577MMsukc8MuOtRNtGGjR49OP6ON4drIXb2qukOdTfkl+Eh/mPqKOoqynYs2hSAq39m9hGuP81SfO5hwjXNsjG0po9TjXCf0WdixhnaFQCV1K/35YuiHUK4Zw7BjAK/Da/Bcyi19SMZBrCbORZ1B3U8ZpC9Pn4o5BuYQqJOoc3gO7ST1OK/TEAluLQFtI/1qdpfgHFDOSDah/aZeoP6g3mZsm9uf4Txxnmn7Kcu5/RnGsvRnWFhBsgb93vy6mvEbSfG089lqeJK6aPuzWywy5i5npznwOvR/6W8wlmGMQTuRu/sQ7Rrll7qQskX7RpnmMazgJ0hOv6+cWwHQ/pAgk9sP4+9y3YB2inqdsk2ZZ+xDm0q/jrExCXTMEZBczOdEn7M+0JYylqbtZp6Da5zzyHVJf4p+KueWemmttdaa47m0L4w7qKdoM/hMqSvANclYjM8rvw6TJKmlMgFAUrPDpC+B8txAEBNLTKoR2CermOAekxf5GKSxapPJ6oa6hzcTYvmTYhkGZgSX2N6XCUaCVEzEFcJEBI9ne9PcASITe2RGMwgkIMWECRnTGSa2mbzj+QxQmdjJfe8MepksZatbJjaYiGEisL4n7/U/nDcGyuwUUaisDBs2LE1IF8LgmGAnE9q5q9G5JpZddtn0XCYzmCggGaDQ9rUMxgmScP5zJzwoWxwXE+FM1DK5Uew46goD/mKYlCMoSzCUZARWejAxUAjvmceRJJA7cbTiiiumyRKSDAgKMNFE2c+wqoAJCwIMrPLOPx98rtwCgIkbJiF+85vfpEkMVz3PHyajCBryORJAJPCWi8A1v2MyuCYkhLHqlySC7LxQzxEMoV0giMnvOe+FAnJMVhHEo53hfGeYKGSykTaEdoZzTxClPtsSjjG3fOaiPWBlFJNqXJ8EHCnfhRBAY9KU8p2bNMM1zvVAOSeITEIMk2oZriN+R/tBPcDnlt9+sGUwP2NlLAEhEonq+37BzRX1GXVWbiIH54g2ghWIlH8mtZngzW2jKZus7CKISVIHk8y5q5QJ0BXDtcXkMJPwJMhwLeavuMswKUt5oI7MbUtoPwi4MJFO3UySQn3vkMHfKoadkHhPO+64Y3ocfaBiq0eZmCeww9bYuYECPnfKP/U7gUn6VbmBWxJvaCP4HAgc0//MRfvLOWBynUAHfTzaYRVG8IYEXeoSAhRsZ5yPtrfYlsQguE2QgGsl91xSVxLMJ+BBP4hynttP5lxmqwnpR3E+c+tJnk9whUAgfXCuUdqXcnBMtGcEncB1Ni87CNQWQUqCn4XQrtHv5zO69NJL00pZ2pFiSQ30dbJATYZbjrBjDH0hzhsJDpT1bGzG++a6oS6ijqFeyE/MJpmAPid9X3YooU01SabucS64FRhtdD7q+wyr3WnjaesbSqmkD653VngzLqBvwbVTrL/FOIhkRhJ0c5EUzfui/iWoTF2fm/xDMJWxD+0pZZzrIv/5tLkkxpMEQF9rm222mY93rAzBfhKs88dQ9GMZ25JARyCe9pOykKH/UQx1DfUM7QQLIig7ubsAEDCmfBNAZzzJfFBuPz9DP5bxb00YP5O8wFiAv0OySf7tMrJAOHUh/RDeE6+foS7li/EJ77UmJAyQrEiSc/71wN/iGiAZhmR+jid3XMB7ZSzE3ADHw+p7+vDlJjvUBsfCOeaayd+Zk4A+bTELHLg2cxMAaGsZBzJ/Rb+S98DxZugnc+64VklQKrUziCRJLYUJAJKanWyVej4GfUxas0UagcFCCQBMqjMR3lDB/3Iwschghkl7JiIKbdUOJpkJWhbKDuc+bAweCeAweZM7sclqKbLAmbhmgq7Ye2dAzN/nsyOQlL+FsOoPEx0oJ/O/EO6PXiiDn4lUzjnBDwb6THIX2gWAwTPBj/wJACZkmCwjc59VA1w7BH8qef1wvTCpwbaBvKdiCQBggr7QxACBBSa8mWhh69kswMpkBauAWEnBDgTFtj9kQpJEGq67LHGn1H2FVTMSMZiwoo6mvBZC8Ib6jM+7FMoHj81PyuD6ogxzvRD0o74sFmxgorjQpCD3zOW1CaxQXzKxXMmABcdIXU1SA59hsQQAVhnRdhbaMYOyzvO4DQzBoNwEACZmaT/4OwTIil37PIfdNfg8CBblTtapfATCCu3iQJtOUDPbxadQgh51OxPfTA5nW8GWi3qV1dIE+DmHxRIAwIriQolkTLgTQGFCl7LYELfIKIUgDYFk6gsmmovtgEPdTRAqP/jJtcLPaSOylaT0rzIkW5BYQztQ7FYwWeCI9oYgkwkAxTHpz+eJee0LUc/R7hcKZNNHoq4kiEc5ze0nZ1t/M7agDsyvJ7nu6H+TpEbyDQF9yns5gQf+Hv0wEDBnNWZjQdkkuMJKW1aJF1vpTf1QqD9EoheBWRJt6I+RCJAFUAn8cO2AtqfQrmygPeU6YyUw1wlJyKpblFMCajUhSEcb1JjQ3lDGKKOMT4ttwc8YmH5bPtpK6m0Sshhr0YcksAzqHFYS0/cnib7YLhjUGwQoWS1Nkr0JAHWD5FOSNvL76lk/h4RHFm4w3uKzLxc7A1CHM04k0J+bAEBdT1kCdXGhfn7ucZRCeaRNJ8DN36BdIdEmH3UrfXSwQ1Zu8D9D3UtQvJzbyrGLE+PyQv1xEnqyepd6mbo7H4nMXFfsYMTcE8kz9XVrC9oNEkTz0d8kqZ/+Iv2zXNltycBxFhpP8JokXtheSJL0PRMAJDU7hQZOYEKaQQ0DOyZrC2EFZP72xg2BDGW2peMezGyXyWAr956KrM4Ak2fFMFAudg92ArdseUhAi8Eck//ZPZ75e2CFIAG2UngdBqrcSkENhxVrBM1YVcYEFBMSnIti29vnY3K1WGCOgCUTE6xq5tooFAQhk57Js0LIvicJgIkCVpgSIGJlZX3iWJksYUUF1w2rAFiBnGHSLrvvdTEEAPJX8mSYPOF6yO7vnPu6JEnw2gR1uY6KBdL4TKlzmFBkwsUEgPnD9ubZfZeLBbFZNUlZrSkBgEmvYsEGyjkTT1wLnH+Cd/ko86yuKYbAD0Ei6nUmGOs7AYAAPEEnJq6pz0leoP3IVidl7Qd1SDFMgueuoMrF+2WSjgQA2iACyExGEozL7vHJZ89q6GJ4LJ85bQztm+ZNsQBEluhEm1Bs+3CuHc4l56/Qtqhs7cwqXHZyoZ7jXGXJZ5SlbPtYJsyLod4jiFkIiTdcX0zoUm/XN46Z98Rqbla2MonMsWfvCdm1QdtVLAGAwE6xW2fQp+ScEDTgPdEOUe/zd9jlACTQlCrzWf2QP8mtOVFHUTdzqy62B2ZlOfU9Py+3L8TjeF4h1E+cKwLy1KPUWSQMUF74myCRuNh96AmikgBJXUyfhP5HtiVxMdTVrJqnzWJFPklUhe5BXl94j5RNdrMhcEm7xzWTXevZdc+YKf8+zrkIchVLdqA+4r3xedAeZv0uEgLoGxFEY+xF37EY6g0SAAikqe5xDZVz2wmSZHK3LW8IlD/qU1ZrcxsaxrGMQxm/ZrJ6nPJULFDJWKdYGeU5XNvs+kUZYycPxkyU1ywYzK0qSo0psrkDrn/VDT7TYueTephgOGWCgDZlIDexizLCuIG2n3NC/7RQ289uXbn1NP0F0F8pdUuJmlC/kQhCu07/mATNYvNLlG/aAurCQotTMiRk0ccq1QcDQf1ifRZ2msmuHZLcis0N0E4yz8B8T6nran7wfgnUFzoGfpbthJM/tmBsRr3AY7hlSTHstMCtEyRJkgkAkpqhYitUGGgwccGEVu4gMBcTgA29tX12v2gGqsWOK8OAthgmNkrdh5GtNDMM5kgAIEiUDSRZucRXKXx2DLi8p1rDodyy6wPBBCajCDYQnM628Cc4wfZ8xVbE8fNiwXsQEKLcUA6KJXZQVkpdF7nZ+0xk12cCAAFHVm0yUZdN4BTDlsHFMJmR3RO62O+ROynNhEM2AUiwla9SuF4IBrFCRfOHFR9g5XGh1cUZVmJlSU3FlFp9TvAlmzhjYrAQEkRKrUDleqItoZ4k2FqfmDRkAoydJmqqlwnsFMP74X0VQ12T4VzwHgl2ZhNzTM5nq2SL4XqgPiNhQfOGeyAXkgU2mAAvltzC72i/qTfz607aF1baMVmdBf+KKVWvskK02Ko4+l9ZsLtUIKWukMzACrBSiZOZUnU0t2EqJWsr6E+RnNarV6+08i/DCjW+alKqf6fvE1D5HKnfqYMoa9RL2S4n9INI4ijVPnANlErGyxJpqEtp+zn3BMmzRD8C1cW2wUe2mpK+fE3nk520tt9++9TOcF2TNFYseaY+UH+TcMBXTe0U7yc34Jovf/vmXLltKok2GZKMQLtQ06rWLJmtpiRlzRvq5kI75+Uj4aah0a+gbcr6gKWUqsdrOnbqccYVXLcku7B7Bddohp2hymE9XneoN0olRNGXJwGA80VflKA9WB3Ozg0seKipP5PbL+axWR3FOHtekQBGwgjJI9SNV1xxRcnFJfSJKbskqNF/KIU2qaYEABKuivXDsjJNO1nqVjOMB3gM/b3c/kxd4hhLnd+sLc9N8EeW5E27mbt7Qz76DPy+1NhHkqSWwgQASc1Oqcm5mjAJ0pDblzOpxuppJqoJwLD1OCtpWOHKoCVb1cRAkuzxbPvTQnjfpbYbzQ0cMEkNJvSyoBF/v9xVVI3pFgktAVslc99ytujkHt2sRmM1VJawwQQ4W3HnJnlkGECXClZSbrJBdrEVXpSLUtdV7gC81Cqx+cUqNO7XyGdAQgIrrVlhwcolJop4nwRhmEQn6FMqQaCmyc5swjp3QpFJ6Oz/y71eyr2mVFq2awurmEup6fcode45r9n1UmwymcSRUlt/ZtcU10J9JktRfxP8v+2229Ixs1sB2/Oyko33mJU9Jq65p2ip64E6vVT7kfu5ZueC18uC+fz9UoG3/L+leVNO/6ambWnzEbCgXiUgl91igzJDcJVkAvpFBAhZuUvbU6oclZqMRZacUN9JUZRR+lN8p+9Dv4rVYCQQMeGclUEmwAkslXpPNd37NntPXI9ZkDR3lymuq/npl+p7lGu2R6Ztpy/02GOPzdUXoi/Av4tt28xrlEr8yw1GZEEDgkJZPV5TgnBWT1KeStX9lBOuMxIaKV8EiArtNlOfCHayJTrjEK71/fffP22NTZID75PPitu2cN3Q9yl1v+t5aVNzV3Vmf68mDb36vKXgsy/nthqlrp36QBIO5Y/rhaRDEoC4JzzBfNqqrB6n/BEUnZ96POvzM84uVI+XW0bn9fYkmltu3VFIbr2T1S2UGXa9o12nbaZPnNufoS2mbqeeY7yYO6/Cec8WYszPTiz0i7NEAgLoBORLodxyHJTnmspPOddgqdfI5n9IcCnVL+HvZNdXfQbQS40Hsustv+3J5hlyj7EQ2otyxyWSJDV3jqIkqYLYxozJSyaIuV9bsfu/ltpaOZNNOBZb/Ze7VXk2sM0dHHFfVI5BjROrB9jmkEkFJsBJCGACl5WbY8eOjc022yz9npVwucicL7VyK3eiutgEGa9RKvkkd/VYTZNs84MJHSbMuV7Y/n+rrbaa6zG8l1LHmqnpNhbZxF/u9cRkRBYA+M1vfjP7vr2qfwRWmNiraeVLTb9HqdWOuSsdi9WlTD6VCoZk1xQTU/U5Yc71wHbVBPq5ByqrnQsp55YtBLmYtCyWQJG7qi17DO8vaz922mmnGnfEUOPE9rislONcEjxlm+d8NbUjmZpWEmeTz8WurbpywQUXpDqciXd2Vyq2vXV2PKXUlKyQvUZuUlju+yNBhyRO1Q12GBo1alTayYr+M30hbtXDqk/+n62+2c6eRKh81NvZ6t5CcgMdWdJsbnJU7q25Csnan1IJuaxip7+dJf5yj2KSPBvaGWecka7r1VZbLe3gUujWBuX2p7juBwwYUPB3tKlZUC33usiShehXZdtkS7koo7Q7JG5RjxfajYX+VjkJZTU9Juvz59bjufUECXKldlNT3csC8sWCuLl926xuoS2gbaA+Y3eAQrdNyr1FVq7cRNb5CXpTTtlZhUQEdgHg1jDXXHNN0V22sr9LX6KmNqbYbefKlc3/cD3k3zYhF+OBbPeEYjtPlVLTjpbzI5tnyD3GQmi73LFSkqTvmQAgSRXENnEMMpnQ5N6jhTAY5J65NWEgRKJAse3jcu9LyGQKCGZmwRySEdS4MVDn3PHFKhgG70yccq8+tlQ+4YQT4s9//vMcz2EChVVy2daI+Sg3TN6SDFKs7PB7Js2LTQLk3s+5Pu91z3tlwppVH8W2jOVYy5kMJHjKeyq2oi+772fu/duZqOZz5LlsicgEhyv8G0Z2D2Bug8GETrHgCo+pCYkz7BxRCJPA2URwsS1j2X6y1OQW9TCrfpikKnVblvnFRCDlnb+x4YYbFnwMZbycrXN5P7yvYvVE7ueaBWqYsMzeH0lI2Rb/alrYUYW2hAnzYuWIslZq6/8MCSnFygGTsdltNUpth1sXstuAcM/cYsF/rp1ythTP3Qa6kKytIFiUrSLNvQ0Oq6hNAKhbBOWzvtAWW2yRyi91EFtC068m+HLdddfN9Twex21TigXySCYA7UvW9uf2jehn8RrFVh1yf3JQNxZbFX/UUUelgDuvcfbZZ6dbgFWi3uS6B7uQFQr+g6S7cgI5BN2GDx9e8HeMcbIkmdwAbna7BOqLl19+2QQAzSEb34AV3MVuxcI1V04ZJShcSjbOZpyTjQvy63ETABpW1h8vVj9R74C+dvYYEuTpa3DuSG4qhHqt0G4R1MkkMpFMVs6tg0phjHrllVfGuuuum3ZwJCGNsXKhPjbJCyRE0c8q1d9gvF5Of76UpZZaKn1nLE2bmXt7r1yMB7Kt97PbHIHPKNuJpdR198EHH8zXcZaSzTPwefFVLKGUuQCS8tyBSZIkEwAkqaIYgJK9zORfsQlA7u1czgocJtlYoVBoMMfE/S233JL+zSRdFvRnkpJ7prJynIE0k/el7o+txoVBLeeLbXH/+te/Fp2wOO+889KquEKT1px7VvcSvCi2bS5BGybGF1100bl+xwCb7WvB5Fihx9SV3HuHF7teCPyUs2MGk85M8hTadpeJiywQQHJFhs+b6+fhhx9O2w8TDCi26k11i0AedRiBBCaFqbfyEUR45513anytG264IY455piCq9057wSICAAVuqUGmBT705/+FL/73e8K/p57OYNrqj6DGtm93Eu1Hw899FBZgVuuLa6dlVdeea7fkYTGLQTA77OVm6xa4nYbJB1xTkisyL1e1DRk26lyPosF7ylH5ewkwWQ99WOhVXdcV1mQpViwsK5kq76KBWrpdx177LFlvRbvnUnkQrc34D3xe1D2s4QwVvrxGfC7a6+9Nu0Yw5bDqh+0zfR96QtRH3FeSH7M3wqZuvuRRx4pGMijD02fAJy7rOxwTtlZidclgEP/IDcwmOE6YpUn6Afl94Woh48++ui47LLL0nXGbTd23333iiVNZf2pYtvqM+7Ixg01ueSSS9JtGQolVLK7CH0ykmNyA0mcA5Ls2NWKHRs23XRTt/jXbFn/BsXqca5xdtAoB9c2Zb7QrkyMnSinWG+99WZfk4MHD059OJK82CFv5513rvH2Yao7BOrpMxRKAKCOZycYkBCflZGs7S/WL6buZTeJYsFrxoT04amzCOCTIDWvuKUK/SHqecrQz3/+87jqqqtmB+EzJNKSzEZwnzr3kEMOmWvXA477tNNOK2s+qBRu5cRr0xZSb5OEVuj64rjp+7OLUm4yNM/NdsYgIbsQjrVQAl5d4TaZHDP9uDPPPDPNcRTCMVBHmAAgSZIJAJJUUWzFxoQZE4pkfeevOGWAxhaIpe5rmGEwy0Bou+22m2tVMsGbbJXaAQccMMfvuD8eEygMmrlnLpOjhSY3M6x8ZvWeK58bTqmVuWCSBMVW8DO5escdd6RJklxMvB555JHp36yuKRT8A+Xw4IMPnn2/2gyDfAKhlAlQjurz/t5ZggJllcm6/GAjEzYEdsvdevCiiy5KKzPzV5OzbSTBZH6euzUvk0msNmQikOD/L37xizQBVey2B0xOkJRjUs38YyKNVR/UlUxaFUoAYLKunBW9PIbHsmV+7gQhE0XcE5lADpNxxRIAwOMINg0ZMmSOnzOxeP3116d/U3bqc0cMJuFY+cIKGCZJ8xN4uD5PPfXUORJnimFSkW3TuQ1Nft1OGc9WttJe5GLr/9///vfpmuQ2JNQR2Q4zhTDBycpa78vZeBDkACviSYDJXzFP32TkyJFl9UPAZCwB/vx6lcAnbQX1JUGW+kQZZNVdNtGfX6b5XZa4VhPqi7333jslDuVOJPO6v/71r1Ngl3qEbd1zMVm/1lprpeuTtpHrq1j7yDVKIl591hdNHf0QAhKFEjEyWf1Pv7pQMJkyTLtPUCc/KEAyJIFAzhFtey7qeoL3nKNddtkllavc5ALqWm7Dwm5LoJ+dX8cRaDn//PPTY/n9iSeeWNF+NMF4dna58cYbY7fddpvr8+Caz3YJqAnv++abb04B0lxcG7wObSvtU+4tqmi/CPpzXZAkQ/+UNqQY2n6Ct/OyHbWaHq6NbMt0rk36MvkBXXbS+Pvf/17W69H2HHbYYXMFC6lTqMcpo/xNElkyXBOMqwkKkwj9hz/8Id36q1g9zmvxVWzFumqHpCw+b3ZfyD331KEE6emrU89zXjPZThHsBMMYNz8Jl7EbdU6x23ixcp96iraA8THjt2Kr5P+XMMlrFU7kWmONNVJiGEn4JNnynVv35faTaa/Ylezuu+9OybT0Nxhb59bJzM0UC3TXBvM3lGfqa+p+6uz82+UwluZvMYZlXiC3X8LnzefBrY24Lqnj81fgs5iE20nVFxLvOU9c+xdffHG6xUL+fADHUBeflyRJzYUJAJJUQayAYbDKJByBFSbK+BkDSjKrmXjgOwGTmla2MjHGgJcJZwbDvC6TygRkmHxmsnrNNdec6/6+TFQwOOXvMzBmQo7AGMdBggLPY/UbAdFbb701Dbjvv/9+EwAaCANwBracO24TwXnNBtsM0glKsCqN81HoHuBMQvOc/fbbLyUSkDnPAJ6EECbUWLHJihbu352/Wi7D7yl/BDRJBKA8UrZYIcCEGOWVraNJIKlPbBnLpAkTeQcddFCanGGVHZP63MKCiSICkUws13QbAJ7HZMyOO+6YJvxIsGAigwkNrjs+d4LOfOUi8EwggGuKXQCYzGHykMl0JnEIUhBI43iYAGHV2+jRo+vxU2kZKHOcK4IsV199dZp44/+pv6ifSHKiDDMxlCWkFMOE3vHHH5/KMNcVAUmSaM4999xUX3ItHXrooUV3syAAwTW07bbbpuA3557ywm1WCOoQTGfSkWOtz9WdJIxRT7N7C9cD1zLBXCan+QwIOBGYKaf94NpnspXA7RFHHJFWKHEtUbfwnqj3V1111bkCNKxcYsUSk4gEOqkjqIeYQKXsM6lO0IwEBXYpYdUWOwWYANB4UIdlyTW0E5R9/p9zx2R0lthFu1PTbhKUGxJGCIZzfZKURrnk3DMZy3VLGaGfUp9ITCHJhz4Nu4ewAp/rmeAMySynnHJKqjt4P9l924uhTqHvw6Q8E830i7hWWF1GYIK6gM8sP9Cw0korpYSaP/7xj2mSmmPhuLhuKf9cX/TZuH65hrhfMO2rCqO/Q8Ie9TcJJJwX2nrqWAL/rNAnsML5IEhfqO4loMJnzgp/VuCT7Eo7QKCb/gPtN218/i0b6HuwYwSPoT3ffvvtY4899khliDLFTl20HyC4QtnPRcIJZY6+Cuefejr/dk25SD7LtsivL6xK5TOgH8f3rbbaKrWF1NeUd8oswaJytnKm3eAa4LqgnaB8kzhEG0jSF30jkuZyd92hTqG8M55gfEECAH0pAjt8rpw/+nFcNyRcEHAiCGYCQMtBv4IgP2NkbgNAHcmKZOpt+mqUL9octvfPdrIphnEQdTHljrJO3UGfhX4j1z/9Pq7R/Ns2Me6i3iZJhYR8gsoEa9nRhefwdxlbMR4gqEp/KT+BSPOGtpb+InUD7S/jNHYBoz6lf0t/Yuutt54j+ZX2gX4HfV7qE/rGPI+5DPqz1EPUR7QFhZIaaT8oJ6zWp+5jXMuKfJJ96dNyvvk5wWfG098vqijdz6d+ZLxJ/4Eky2wngNw6njJDAgB9AcY4jElIOCeRkudQ/miv6JuRnDCvYwuex9iZ46E/zt+lz0//hWuD16ato52kvj788MPn2jWD9o/+HNcPY2QS77O2lGPluqSd4/f1gfdAIjhzI5xnEvp4T1kyK+NvrkPaCtpn+rKSJLV0JgBIUgWxuoFBLBOGBGyYkMuCu0x8MTglwMpAs6YADq/FJPf++++fJiuY3CAQxeQ7g2QGwAyYCm1fyMQKASwGggzemLznOJjE4xiYqGZgx+swued9nhsW55BgA9n6TNBmyRdMRHBeCN5xX9n8Ff7gHDLRTLCS4A4TGAzymUBjQoSJkHPOOSed12II5lFGKF9k1fMcyhYTMZQJAitMftd3uWDij+QWyieTf0zCUc45Bt4PZZVVIQTws5V4xZBIQDCTiQ+C/nyufB68Dq9HYJjEmOyezhneI0FfJhayz4NAAMfBxBHHwDnJtqGs75WuLQVlnMQLJqWYHOOLiTImpvismeSh3mN1aBaIKYZEKx7DhBHnl9fm+dm1xARh7iqwfEzAcc2w2worJ3PLINcFdSx1bf5Ecl3j7zDRRoCTSWmOmfeTBU4IZjEJRoCxpvaDiVbeN9cWk+68J8oy1zhtA9ceE+WFVijz91ndTR1DYhH1DO0H9RTPzW0/sgQ3NR6cUwJxBPDYsj7b6YVzR5lmopx6leAIgbpSuOcudStJAwRDsqQoyiPnnwRDXqvQNsx1iSAuk9hMTD/wwAPpGuBYmAimTBO8IXjPBHtNCQDUKwSYuaZpSynX2XsCbSOT5Ploe9kFgLaC7+zEk+0YkwUfaMOz++y6TW3N6AsRCCHxMb8vxBf19wknnJACfIVQBkj+oq4kGEM9R5mgnFPeSSqgbaG+y0dfgXN+1llnpbaHYA3Bmdy+EOWf1aX555LAddYnoK4mkFkKdXF9JwDQ3ye4yvVBe8iOGHx+WdkmaMVx7rvvvjW+FgEzHkuwjbaE90+bynvmM2KcU6h/Sl1BAgAJG1wb7JBAW0L9QDtBn4zXyW514zXSstBHp23imqOsEvjN2hSuWYKW7G7G+KWmBADKMYF+Apckh1F30C+hfIF6Pn8XF1B+eQ71TdYGkHDK/zOW4vrnb1NWKaP1uQtaS0MduO6666b6kFs4cO75nKlvwUp0kjJyE0p5DkF5xguUF+re3P4s54c6mvmW7NznI7BMfUhyAX1ayk7Wp6W9yILK9Ilq817YHYwEJ3awo2xTpkkiAONHdqehvNEG8X6zW9KAtoV2j3KKYjvPlYNdnthhgHaSPh3jmGzswGfEeyMJizmHQrdz4nNnJzySMkgSJSGA48naQpIwaFO4RVh9od/K38jGHdn4B9QNjAVJYqNNYtwoSVJLZwKApGaBFQClto4EgysGdQxScu9DCbLHeT7Zw8VWQc8rBpusBGNAkr+1LoMtAoSsKGKCmNX+DG6Z/GIikkEZg0UmqPlZoS3aCahw7CQAMKDlbzAoYvUNr8Vnw/tmIrxYQIpJNYKp3BuO5zJJwkoeJln4PBj4MmHOqigy13O3e+O5DEwZgNfn/a5bKsoPE05MFBDUZnUWk6qUHSY1WNXC5Ck7O+ROPJHwQbCFyQQy8QlyEyxkBQSTu6zs4rms1uW8l8I5ZnCdDfpZmUDZouyxvSEB1fxA+fwgeMPKgyybP/ezYKcKjp0JHLbkZNKea4PVGQz0+c6EBNcPX8Vem/dCAJ/XYrKFFR1MevA+mHDid8W2GubzYGUJj2Pim5XfBCayew7zGnzmXJeFdkVgxS3XSv4tP1Qa5Z3gIfUNE1PUi1wH1Gt81iQ/8XP+nX/ueW7WRnDOSahh4pCAJ3Ud5zSrQ6njaroXMcfA5CLXFKvbmUjmb5Isk62mqQu8PyYOOXbakdzgOf9mco6VPKxM5Tiy9oOyRSCfrav5XZa8lS9rOymzrFql/WCynbaI+p8ADYEgEoyKbU/OdUlwh2uIxAhWlGb1FNcDnz1JQrR1TNblrgLlPXBcTM7m305B36O/UlP/JivftMPF6i3abVYzcm5y+wKU/Ww1NME3VoVRrzLZTtnL7l/PSjzKA9dPKUy881pciwTOmRQmCE4bxcQ8AcK6wPHRxlF2cssUKJMcd7bDEbuycA3wGTDhTrtH+0JdTDuWf9sjJvpJAiMQTFtB/4nrjwl8Pj8+Hz7DbNVysR2R+Hsk4bDrAZPRrIam/eUz4TlZO0cSKOcmF59Tdt7rul/aFFE/E5Qh4EfQIr8vRJ1HP4XPsVigmMfSr2ZXFPoQrBymzmRcQD+ZurtQ8B+cL+p7dq9g9SaB/KyOY8Up54ogeKHdTWgParqGc+WPUeYVdUH2d/PLKAlkJOmwExTtIIEb2r2s3HGNsBqUBC9+lh9wyn1t2gZei4Rlkm2y16KuIEhE+S8WGOW8ElBlxyR2CmHFf5YwRlvGcRJQou3gWs1FvVSbz1Vzor/C51dqVwXqWdruTz75pF5uUULfg/JBPZ5/2xjKEAk7XK/cmitL1uI5lAnKKOMY2hbG2Pm3SuNaZHzDY6hneTxjGHa4oM8O2gjKFom8xcoo9XS2Kpw2knojS9Lnb/D58VmSUJYfMM3qBj5H6/HysCU9dQD9D8aXtMHU/fRNaDs5/+w6RxJvfr1GmaG/Sh1K0ir9Utpr2gh2VqGvQ3+UuRXq70JlmvaD39Nek7zE7g7UaVn/mrqP88zK81yUMc419VIhvB/qWhLZeS3aEcpm1ieiHPE+CfJnCz/oZ9AXIdGQ/kR2m5v8+RyOOetLl7p9WfZY6nXmFKizs3kB6lw+N8oy/af824plaEdJIKNNoF/D7jycF64Txti8P/5GVjfnzw9wzminuZ6LfVbIxidc/4VwvXHsJGKMHTs2jVk4P3zOJOrzuTJOp6+Q3U5EkqSWygQASc0CWdp8lcLEAqvSCmEQlz+QqysMglhZx1cxTGSQ2c1giCAix8rAJZssYEVTMQzCcrcbZFBK1jVBrey1GFSWsyqBiU+CRWS3M5nC8zl+BnkMPAu9BpMfpY5P84+JDr6YEMlW7jMA59wy4C402c0gnKSBDANwJrwZCLNahQE45aI2E1IM2Jn8pmwx2Gegzd+v6xUvJMOUwsQMgZssEJP/ObCKrNzXZhU3kwhMBvKeKOv5waRimOwhYYaJkyyow+RTdr0UW+nMKg/NG8otq3EIbjMhx2dM2c6CE/w8/z7EYJKJwFEuJo14Da4pyjCTerXZmp5AIsFF6m0mnrK6tq5XKbKinq9imOxjVWzWfvAeaD+yiVEmSYsh8YuvDG0Hr8X1QD1Tm/aDz4/JeuqXrJ7is2Dim+uh0OfCz5isVXHUUXyVUqh85yPITbJTMfShmGylXmUiOP/c036UgzqQRBpWhVGOmJDm/NdlkhjorxA4LCa7nzPHQZvFe8qv35m8LoRjJREmF6tDmZjPVnvzGIIKNaGOIlGOLz6PbEVzllzJ9VGorWAivqZz2pLweRG04CvrC1Hv8tnxGdamL0JAM+vLUGdm95avaXeSLNmJgGWWJEt5pyxwDMWw2wBfDY3AWakyRJ1Nn4hySR+G90KZzso1ASV2Oyj3tUkA43OhjFO3E7wvp4/J508iK58Rx8LnyjWW35blI7jDl+YNCSs17UaR7f5TX0icLFWPUzZI7iRxJ1v5TT2em0hGYlYhlO/8dovt3Lk1SxbwLJTcUgh1A2Mg6g7KOHUQ44+sHs92rchHP9F6vHbYUSd3V52sb5L1J7LzX6q+JqmDxLqs7ef8ZLuTgISSmpBQQtIXbU1u4h6vk5+sgnLmkkiiLFangjaGxRb5t6EBiW8kniHbOSCT7QRYG/QJ2d2Cz5V+e6E+UjF8jpwXkowZe+T287LzUqzc8/mxC0dNypnbI2mZfm3u/Fluv5WEHUmSZAKAJDUaDN6KrTyqLQaorGqYVwwA52d7OdUPJjDmZ+tkBuVMiBVbIVoOJmTrqpzODwb5+at95ue1Ck3mlIPPlEmP3F0xVP9ygxTzg8mq+QlMMgnGCq9Kq+v2Y37eE4GwUsEwNV7z28bU12vNj7osj/PbN2Liu652QGjJ6qJszU8/OVv13xzQhyHgU27iY03m57X4XOv71jlqmuqqz4f56bNzvRBgLLVrgurevNT5ddX2N9QYL7sNWaEdyAjSk7xCoJ2Ez7raXn9+63/mBOpqLD6v+LzmZ85LkqSWwAQASZIkSZIkSZIa0D/+8Y90uz5uNcFtEEiGYgeDp556Kt26gtuOkSBw3HHHFd0VRZIkqRATACSpDGyJyz3OaoPtx7j/5byuLJaaKu7TyHaJtcX9/up6+3Sp0pjAy+7bWS5W5dB+NIYV1FJ9YLtZ2gq2C68NVuCXum+s1FywFX625XNtEDhi+32pvlGPv/vuu2n1cm2w81KlVw5LjQnb2LNlfbFt61ltn3/bLkmSpHKYACBJZeD+YgcffHCtnsM266NGjYqVV165no5Kapy4R/u83PNywoQJ83V7Aqkx4l6j3D+8Nti2lPbjhz/8YT0dlVRZ06ZNS9cFK95qg/uv33nnnfV0VFLjwT2fhw8fnu49XRusED366KPr6aik/yFJZccdd4xHH320Vs/jOddcc009HZXU9Ky99tpx4IEHxuOPPx5vvvlmSh5me3tuN7P66qvHVlttFRtvvHGd3QpDkiS1HCYASFIZWIVZ2/t9cj+1Qvdxk5qKc845J33VFvc4npf747LqWWqsDjvssPRVW+wCU9vrgTaHrT6lpuDtt9+ep+fNS1vBylGpNua1L1Np7IjE9VHbBIC6uO+1VC7Gu7WtxxvinupSUzJw4MAm2U5JkqTGz8iUJJVhzz33TF+SasaOGZK+94tf/CJ9SfoftrO9/vrrK30YUqO1/PLLp9tkSI0VCY7zsuOXJEmSpIZhAoAkSZIkSZIkSZIkSc2ACQCSJEmSpCZg1ndf3i5GkiRJkiSpFBMAJEmSJElNgMF/SZIkSQ3PVGRJTY0JAJIkSZIkSZIkSVIBBv8lNTUmAEiSJEmSJEmSJEmS1AyYACBJkiRJkiRJkiRJUjNgAoAkSZIkSZIkSZIkSc2ACQCSJEmSJEmSJEmSJDUDJgBIkiRJkiRJkiRJktQMmAAgSZIkSSrLF198Ea+++uo8P79nz57Rr1+/ujsgSZIkSZIkzcEEAEmSJElSWcaMGRMbbbTRPD9/t912i8svv7wOj0iSJEmSJEm5TACQJEmSJJWlY8eOseSSSxb83YQJE2LSpElRXV0diyyySLRu3Xqux/Tu3bu+D1GSJEmSJKlFMwFAkiRJklSWNddcM15//fWCvzvwwAPj//7v/2LQoEFx7733xkILLdTARydJkiRJkiQTACRJkiRJkiRJkiRJagZMAJAkSZIkNbjp06fHK6+8km4d0KdPn1h66aWjVatWdf53vv3227RrAX+H2xMstthi6RYFkiRJkiRJzZEJAJIkSZKkerXPPvvEJZdcEquvvno8/PDDccstt8Ree+0VEydOTL/fcMMN088I0q+33nrx1ltvxV133ZV+XshDDz0U66yzTvr3Rx99FD179pzrMSQYXHzxxXHkkUfGF198MfvnVVVVsckmm8QVV1xR8HmSJEmSJElNmQkAkiRJkqR6NWvWrJg5c2YKyp9yyilx4oknRqdOnWKVVVaJGTNmpH/nPo4v/l3T6xXz2muvxUEHHRR33313+v9+/frFQgstFJMnT45XX3017rzzzlhhhRXi0ksvTckAJAVIkiRJkiQ1ByYASJIkSZIaxDPPPBNPP/107LrrrnHaaadF27Zt089JAujQoUOd/A1W+++7775x3333xcILLxyXX3552nmgTZs2KXHgs88+i5122intRHDIIYekRABuCyBJkiRJktQcmAAgSZIkSWoQ06ZNi/XXXz/OOuus6Ny5c738jXvvvTfdIoDt/W+99db4wQ9+MMfv+btXXnllrLvuumk3AG49wG4BkiRJkiRJzYEJAJIkSZKkBsFW++eff369Bf9x4YUXpkSDjTfeOIYPH17wMQMGDIhtt902Tj/99Lj66qtNAJAkSZIkSc2GCQCSJEmSpAbRt2/fGDRoUL29/tdffx2PPvpo+neXLl3ijjvuKPrYqVOnpu/PPfdcTJ8+Pd0iQJIkSZIkqamrtxmOWd99VdXXi0uSJEmSmpw+ffrU6+u//fbbswP77ATwxz/+sehjZ82alb7PnDkzJk2aFAsuuGC9HpskSZIkSVJDqLcEAIP/kiRJkqRcbdu2rdfX//LLL2f/e7nllosePXrU+BzGrtyaQJIkSZIkqTlwj0NJkiRJUqNQbiB+ypQpBX/evXv32f8+7LDD4he/+EVdHJYkSZIkSVKTYQKAJEmSJKlRaNOmTbRu3Tr9+6uvvir6uFdeeaXgz/v37x+dO3dOzx01alTsuOOO0apVq3o5VkmSJEmSpMbIBABJkiRJUqPQtWvXaN++ffr3c889F1tttdVcj5k6dWpccsklBZ9fXV0dm2++eVx33XXxwAMPxGuvvRaDBg2q12OWJEmSJElqTEwAkCRJkiQ1Cl26dInBgwfHf/7zn7jiiivi4IMPjgUWWGD276dPnx6XXXZZvPzyy0Vf44ADDojbb7893n///Rg5cmRcfPHF6XXzby9AIsFHH30UX3/9dfqbkiRJkiRJzYEJAJIkSZKkRuO3v/1t3HnnnfHee+/Fj3/849hll12iX79+8cknn8To0aNTcH/LLbeMW265peDzhw4dmhIHjj/++Ljxxhvj1VdfjU033TRWWGGF6NChQ7o9ADsDPPPMMzFmzJj090wAUEs067uvqhofJUmSJElqakwAkCRJkiQ1GsOHD49TTz01Dj300HjyySfTV6Z169bxq1/9KrbddtuiCQDt2rWL4447LhZddNE45JBDUqD/6aefnutx7AjQpk2b2bcckFoag/+SJEmS1DyZACBJkiRJmm+s1me7/t69e0enTp3m+B0r8Pv06ROLLbZYWa+19957p1X/d911V4wbNy79bPHFF4911lknNt9887R1/7HHHpt+3rFjx4KvQaLAGmusEf/4xz/SLQXYQWDatGlpF4C+ffumVf+rr756rLTSSvP+piVJkiRJkhoZEwAkSZIkSfNt4403Tl+F/OQnP0lf5aquro6f/vSnsdlmm8XMmTPTz1q1apW+QHLAyJEjS74GK/yXXXbZ9MVrZK+T/1qSJEmSJEnNyX8TALzzmyRJkiSpcamrQL0Bf0mSJEmS1FL8NwHA4L8kSZIkSZIkSZKUuHZWUhPlLQAkSZIkSZIkSZKkXAb/JTVRJgBIkiRJkiRJkiRJktQMmAAgSZIkSZIkSZIkSVIzYAKAJEmSJEmSJEmSJEnNgAkAkiRJkiRJkiRJkiQ1AyYASJIkSZIkSZIkSZLUDJgAIEmSJEmSJEmSJElSM2ACgCRJkiRJkiRJkiRJzYAJAJIkSZIkSZIkSZIkNQMmAEiSJEmSJEmSJEmS1AyYACBJkiRJkiRJkiRJUjNgAoAkSZIkSZIkSZIkSc2ACQCSJEmSJEmSJEmSJDUDTToBYNZ3X1WVPghJkiRJkiRJkiRJkhqBJp0AYPBfkiRJkiRJkiRJkqTvNekEAEmSJEmSJEmSJEmS9D0TACRJkiRJkiRJkiRJagZMAJAkSZIkSZIkSZIkqRkwAUCSJEmSJEmSJEmSpGbABABJkiRJkiRJkiRJkpoBEwAkSZKkJmDWd19VlT4ISZIkSZIkSY2aCQCSJElSE2DwX5IkSZIkSVJNTACQJEmSJEmSJEmSJKkZMAFAkiRJkiRJkiRJkqRmwAQASZIkSZIkSZIkSZKaARMAJEmSJEmSJEmSJElqBkwAkCRJkiRJkiRJkiSpGTABQJIkSZIkSZIkSZKkZsAEAEmSJEmSJEmSJEmSmgETACRJkiRJkiRJkiRJagZMAJAkSZIkSZIkSZIkqRkwAUCSJEmSJEmSJEmSpGbg/wGWSAjEXL1Y4QAAAABJRU5ErkJggg=="
    },
    "image.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "e6f056e5",
   "metadata": {},
   "source": [
    "# Training and Other Details\n",
    "\n",
    "## Monitor Segmenter\n",
    "To train the model we trained the yolov5 model on the 1800 of the 2000 image samples\n",
    "provided and tested the model on the other 200 data. The training was done at 25 epoch with a\n",
    "batch size of 8.\n",
    "The following table summarises the efficacy of the model\n",
    "- Precision: 0.991\n",
    "- Recall: 1\n",
    "- mAP50: 0.995 \n",
    "- mAP50-95: 0.99\n",
    "\n",
    "## Monitor Classifier\n",
    "We first tried using Microsoft’s Resnet-18 Convolutional Architecture for Monitor Classification,\n",
    "but we realised we should be taking Monitor Layout as the key attribute/feature instead of\n",
    "Monitor Type for classifying and this would be done better on unsupervised learning than\n",
    "supervising it to only Monitor Types, so we switched to Inception V3. Using K-means clustering\n",
    "through Inception V3, we were able to get 100% test and train accuracy on the given 1000\n",
    "monitor classification images. We used this cluster data in our final pipeline.\n",
    "\n",
    "## Digit Segmenter\n",
    "The objective of the model was to make it machine agnostic, hence we trained it on all four\n",
    "classification datasets provided and treated all the vitals as the same class. To maximise digit\n",
    "detection, the model was trained with a batch size of 10 and for 30 epochs. However, a\n",
    "challenge arose when the model sometimes labelled the background as digits. To overcome\n",
    "this, only the top 6 scores with the highest confidence were considered for digit classification.\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "The following table tabulates the validation parameters-\n",
    "- metrics/recall: 0.99627\n",
    "- metrics/mAP_0.5: 0.9942 \n",
    "- metrics/mAP_0.5:0.95: 0.80342 \n",
    "- val/box_loss: 0.015804\n",
    "\n",
    "In our initial attempts we tried to get yolo to both segment and classify the labels. However the\n",
    "results were discouraging and hence we abandoned this approach.\n",
    "\n",
    "![image-2.png](attachment:image-2.png)\n",
    "\n",
    "## Vital Classification\n",
    "To accurately classify the digits in the monitors, an XGBoost model was specifically trained for\n",
    "each of the four monitor classes. The position and size of the digit's bounding box was used as\n",
    "input features for the model to make predictions on its class. The model was trained on a total of\n",
    "around 250x6 samples per class, with a grid search performed to optimise the hyperparameters\n",
    "of n_estimators and max_depth for improved accuracy. The final accuracy results for each class\n",
    "were reported on test data (80/20 split).\n",
    "\n",
    "- BPL-Ultima-PrimeD-A-classification: 100%\n",
    "- BPL-EliteView-EV10-B_Meditec-England-A: 98.69%\n",
    "- BPL-EliteView-EV100-C: 97.0%\n",
    "- Nihon-Kohden-lifescope: 99%\n",
    "\n",
    "## OCR\n",
    "EasyOCR was employed for text detection and addressed the common problem of detecting a\n",
    "mixture of alphanumeric characters faced by other OCRs. It provides a feature that allows you\n",
    "to specify certain characters for recognition and ignore others, leading to improved accuracy\n",
    "and reduced extraneous information. EasyOCR, Pyterreact, and Calamari OCR were tested,\n",
    "and EasyOCR showed better accuracy compared to the other two. Also before being passed to\n",
    "OCR, we are increasing the sharpness and using auto brightness to remove glare in the image.\n",
    "\n",
    "## Heart Rate Digitization\n",
    "We rotated the cropped image by an angle. This angle is the mean of lower and upper 40% of\n",
    "all angles, which are made by lines joining the mean line and the peaks or the troughs. By doing\n",
    "so we try to align all the peaks of the graph to get the same y-coordinate for all of the peaks.\n",
    "Since there was some noise in the cropped image, we took the largest continuous contour to\n",
    "get only the graph coordinates. Since Contour detects the border, it detects both the inner and\n",
    "outer borders of the curve. This gives us multiple y-coordinates for a single x-coordinate. We\n",
    "tried various methods to get a single y-coordinate for a given x-coordinate such as max, mean\n",
    "and min. We found mean works the best in such cases. Hence we finally plot the obtained pairs\n",
    "of (x,y) coordinates.\n",
    "\n",
    "# Conclusion\n",
    "In this study, we aimed to tackle the challenge of accurately recognizing and digitising heart rate\n",
    "and reading the vitals from various monitoring devices in low-resource settings. Our work makes\n",
    "a contribution in this direction by demonstrating use of open source models and data to achieve\n",
    "satisfactory performance on the trained dataset. As future work, efforts can be directed towards\n",
    "developing zero-shot or few-shot solutions to address this problem."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5mxIT9w2bIfy",
   "metadata": {
    "id": "5mxIT9w2bIfy"
   },
   "source": [
    "# Load the models and install relevant libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "xGKl3z2ZqFT1",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "xGKl3z2ZqFT1",
    "outputId": "7ef10755-1927-42e2-cd28-bcd8873ed4e2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: xgboost==1.7.3 in /home/sharchit/anaconda3/lib/python3.9/site-packages (1.7.3)\n",
      "Requirement already satisfied: numpy in /home/sharchit/anaconda3/lib/python3.9/site-packages (from xgboost==1.7.3) (1.21.5)\n",
      "Requirement already satisfied: scipy in /home/sharchit/anaconda3/lib/python3.9/site-packages (from xgboost==1.7.3) (1.9.1)\n",
      "Requirement already satisfied: easyocr in /home/sharchit/anaconda3/lib/python3.9/site-packages (1.6.2)\n",
      "Requirement already satisfied: ninja in /home/sharchit/anaconda3/lib/python3.9/site-packages (from easyocr) (1.11.1)\n",
      "Requirement already satisfied: torch in /home/sharchit/anaconda3/lib/python3.9/site-packages (from easyocr) (1.13.1)\n",
      "Requirement already satisfied: PyYAML in /home/sharchit/anaconda3/lib/python3.9/site-packages (from easyocr) (6.0)\n",
      "Requirement already satisfied: python-bidi in /home/sharchit/anaconda3/lib/python3.9/site-packages (from easyocr) (0.4.2)\n",
      "Requirement already satisfied: pyclipper in /home/sharchit/anaconda3/lib/python3.9/site-packages (from easyocr) (1.3.0.post4)\n",
      "Requirement already satisfied: scikit-image in /home/sharchit/anaconda3/lib/python3.9/site-packages (from easyocr) (0.19.2)\n",
      "Requirement already satisfied: torchvision>=0.5 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from easyocr) (0.14.1)\n",
      "Requirement already satisfied: Pillow in /home/sharchit/anaconda3/lib/python3.9/site-packages (from easyocr) (9.2.0)\n",
      "Requirement already satisfied: opencv-python-headless<=4.5.4.60 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from easyocr) (4.5.4.60)\n",
      "Requirement already satisfied: scipy in /home/sharchit/anaconda3/lib/python3.9/site-packages (from easyocr) (1.9.1)\n",
      "Requirement already satisfied: Shapely in /home/sharchit/anaconda3/lib/python3.9/site-packages (from easyocr) (2.0.1)\n",
      "Requirement already satisfied: numpy in /home/sharchit/anaconda3/lib/python3.9/site-packages (from easyocr) (1.21.5)\n",
      "Requirement already satisfied: typing-extensions in /home/sharchit/anaconda3/lib/python3.9/site-packages (from torchvision>=0.5->easyocr) (4.3.0)\n",
      "Requirement already satisfied: requests in /home/sharchit/anaconda3/lib/python3.9/site-packages (from torchvision>=0.5->easyocr) (2.28.1)\n",
      "Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from torch->easyocr) (11.7.99)\n",
      "Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from torch->easyocr) (11.10.3.66)\n",
      "Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from torch->easyocr) (11.7.99)\n",
      "Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from torch->easyocr) (8.5.0.96)\n",
      "Requirement already satisfied: wheel in /home/sharchit/anaconda3/lib/python3.9/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch->easyocr) (0.37.1)\n",
      "Requirement already satisfied: setuptools in /home/sharchit/anaconda3/lib/python3.9/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch->easyocr) (63.4.1)\n",
      "Requirement already satisfied: six in /home/sharchit/anaconda3/lib/python3.9/site-packages (from python-bidi->easyocr) (1.16.0)\n",
      "Requirement already satisfied: tifffile>=2019.7.26 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from scikit-image->easyocr) (2021.7.2)\n",
      "Requirement already satisfied: packaging>=20.0 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from scikit-image->easyocr) (21.3)\n",
      "Requirement already satisfied: imageio>=2.4.1 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from scikit-image->easyocr) (2.19.3)\n",
      "Requirement already satisfied: networkx>=2.2 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from scikit-image->easyocr) (2.8.4)\n",
      "Requirement already satisfied: PyWavelets>=1.1.1 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from scikit-image->easyocr) (1.3.0)\n",
      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from packaging>=20.0->scikit-image->easyocr) (3.0.9)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from requests->torchvision>=0.5->easyocr) (2022.9.14)\n",
      "Requirement already satisfied: charset-normalizer<3,>=2 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from requests->torchvision>=0.5->easyocr) (2.0.4)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from requests->torchvision>=0.5->easyocr) (1.26.11)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /home/sharchit/anaconda3/lib/python3.9/site-packages (from requests->torchvision>=0.5->easyocr) (3.3)\n"
     ]
    }
   ],
   "source": [
    "#Install relevant libraries\n",
    "!pip install xgboost==1.7.3\n",
    "!pip install easyocr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ead56da4",
   "metadata": {
    "id": "ead56da4"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-02-10 10:09:39.694482: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2023-02-10 10:09:39.815662: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
      "2023-02-10 10:09:40.327796: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory\n",
      "2023-02-10 10:09:40.327834: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory\n",
      "2023-02-10 10:09:40.327838: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n"
     ]
    }
   ],
   "source": [
    "#Import necessary libraries\n",
    "\n",
    "import torch\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from PIL import Image\n",
    "import pickle\n",
    "from tensorflow.keras.applications.inception_v3 import InceptionV3\n",
    "from tensorflow.keras.applications.inception_v3 import preprocess_input\n",
    "from tensorflow.keras.preprocessing import image\n",
    "from tensorflow.keras.preprocessing.image import img_to_array\n",
    "from sklearn.cluster import KMeans\n",
    "import pandas as pd\n",
    "from tqdm import tqdm\n",
    "import os\n",
    "import shutil\n",
    "import cv2\n",
    "from PIL import Image, ImageOps, ImageEnhance\n",
    "import easyocr\n",
    "import math\n",
    "#from google.colab.patches import cv2_imshow\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.signal as signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d5d03108",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "d5d03108",
    "outputId": "8301996e-ce92-4bb8-b8c0-0a0e34405dbd"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using cache found in /home/sharchit/.cache/torch/hub/ultralytics_yolov5_master\n",
      "YOLOv5 🚀 2023-2-2 Python-3.9.13 torch-1.13.1+cu117 CPU\n",
      "\n",
      "Fusing layers... \n",
      "Model summary: 157 layers, 7012822 parameters, 0 gradients, 15.8 GFLOPs\n",
      "Adding AutoShape... \n",
      "Using cache found in /home/sharchit/.cache/torch/hub/ultralytics_yolov5_master\n",
      "YOLOv5 🚀 2023-2-2 Python-3.9.13 torch-1.13.1+cu117 CPU\n",
      "\n",
      "Fusing layers... \n",
      "Model summary: 157 layers, 7012822 parameters, 0 gradients, 15.8 GFLOPs\n",
      "Adding AutoShape... \n",
      "Using cache found in /home/sharchit/.cache/torch/hub/ultralytics_yolov5_master\n",
      "YOLOv5 🚀 2023-2-2 Python-3.9.13 torch-1.13.1+cu117 CPU\n",
      "\n",
      "Fusing layers... \n",
      "Model summary: 157 layers, 7012822 parameters, 0 gradients, 15.8 GFLOPs\n",
      "Adding AutoShape... \n",
      "CUDA not available - defaulting to CPU. Note: This module is much faster with a GPU.\n",
      "2023-02-10 10:09:50.007476: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/sharchit/anaconda3/lib/python3.9/site-packages/cv2/../../lib64:\n",
      "2023-02-10 10:09:50.007496: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)\n",
      "2023-02-10 10:09:50.007520: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (sharchit-Ku): /proc/driver/nvidia/version does not exist\n",
      "2023-02-10 10:09:50.008120: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
     ]
    }
   ],
   "source": [
    "#Loading the models\n",
    "monitor_segmenter = torch.hub.load('ultralytics/yolov5', 'custom', 'monitor_segment.pt')\n",
    "kmeans_monitor_classifier = pickle.load(open(\"cluster_model\", 'rb'))\n",
    "digit_segmenter = torch.hub.load('ultralytics/yolov5', 'custom', 'digit-finder.pt')\n",
    "hr_locator = torch.hub.load('ultralytics/yolov5', 'custom', 'hr_locator.pt')\n",
    "\n",
    "xgb_NK_path = 'NK-A.pkl'\n",
    "xgb_BPL_Ultima_path = 'BPL-Ultima-PrimeD-A.pkl'\n",
    "xgb_BPL_EliteView_EV100 = 'BPL-EliteView-EV100-C.pkl'\n",
    "xgb_BPL_EliteView_EV10 = 'BPL-EliteView-EV10-B_Meditec-England-A.pkl'\n",
    "\n",
    "xgb_NK = pickle.load(open(xgb_NK_path, \"rb\"))\n",
    "xgb_EV100 = pickle.load(open(xgb_BPL_EliteView_EV100, \"rb\"))\n",
    "xgb_EV10 = pickle.load(open(xgb_BPL_EliteView_EV10, \"rb\"))\n",
    "xgb_Ultima = pickle.load(open(xgb_BPL_Ultima_path, \"rb\"))\n",
    "\n",
    "reader = easyocr.Reader(['en'])\n",
    "model = InceptionV3(weights='imagenet', include_top=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "398d5eeb",
   "metadata": {
    "id": "398d5eeb"
   },
   "source": [
    "# Monitor segmentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2f3d3545",
   "metadata": {
    "id": "2f3d3545"
   },
   "outputs": [],
   "source": [
    "# Function to extract monitor bounding box by using YOLOv5\n",
    "def getMonitorSegment(path: str):\n",
    "    img = Image.open(path)\n",
    "    predictions = monitor_segmenter(img)\n",
    "    df = predictions.pandas().xywh[0]\n",
    "    df = df[df.confidence==df.confidence.max()]\n",
    "    # print(df)\n",
    "    xcenter = df.iloc[0]['xcenter']\n",
    "    ycenter = df.iloc[0]['ycenter']\n",
    "    width = df.iloc[0]['width']\n",
    "    height = df.iloc[0]['height']\n",
    "    img = img.crop((xcenter - width / 2, ycenter - height / 2, xcenter + width / 2, ycenter + height/2))\n",
    "    img = img.resize((416, 416))\n",
    "    return img"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "809222ab",
   "metadata": {
    "id": "809222ab"
   },
   "source": [
    "# Inception v3 Model Classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "AxM1pHxJKk5K",
   "metadata": {
    "id": "AxM1pHxJKk5K"
   },
   "outputs": [],
   "source": [
    "# Function to Extract features from the images\n",
    "# run once\n",
    "def image_feature(imgarray):\n",
    "    features = [];\n",
    "    x = imgarray\n",
    "    x=np.expand_dims(x,axis=0)\n",
    "    x=preprocess_input(x)\n",
    "    feat=model.predict(x)\n",
    "    feat=feat.flatten()\n",
    "    features.append(feat)\n",
    "    return features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "Bl5wrzrGKtFu",
   "metadata": {
    "id": "Bl5wrzrGKtFu"
   },
   "outputs": [],
   "source": [
    "def getMonitorClass(img):\n",
    "    res = cv2.resize(img, dsize=(224, 224), interpolation=cv2.INTER_LINEAR)\n",
    "    img_features=image_feature(res)\n",
    "    result = kmeans_monitor_classifier.predict((np.array(img_features[0]).reshape(-1,len(img_features[0])).astype(float)))\n",
    "    return result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf584f57",
   "metadata": {
    "id": "bf584f57"
   },
   "source": [
    "# Get Digits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e785952d",
   "metadata": {
    "id": "e785952d"
   },
   "outputs": [],
   "source": [
    "def remove_glare(image):\n",
    "    image = ImageEnhance.Sharpness(image).enhance(10)\n",
    "    return ImageOps.autocontrast(image, cutoff=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2d3bf6f",
   "metadata": {
    "id": "d2d3bf6f"
   },
   "source": [
    "## Functions for each of the 4 monitor classes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "agl65YM-hKcU",
   "metadata": {
    "id": "agl65YM-hKcU"
   },
   "outputs": [],
   "source": [
    "padding = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "72f4edc3",
   "metadata": {
    "id": "72f4edc3"
   },
   "outputs": [],
   "source": [
    "def getDigit_NK(image):\n",
    "    #display(image)\n",
    "    predictions = digit_segmenter(image)\n",
    "    #predictions.show()\n",
    "    df = predictions.pandas().xywh[0].sort_values(by = ['confidence'], ascending = False).head(6)\n",
    "    digits = []\n",
    "    read_digits = {\n",
    "        'HR': None, \n",
    "        'SBP': None, \n",
    "        'DBP': None, \n",
    "        'MAP': None,\n",
    "        'SPO2': None,\n",
    "        'RR': None\n",
    "    }\n",
    "    \n",
    "    for i in range(df.shape[0]):\n",
    "        xcenter = df.iloc[i]['xcenter']\n",
    "        ycenter = df.iloc[i]['ycenter']        \n",
    "        width = df.iloc[i]['width']        \n",
    "        height = df.iloc[i]['height']\n",
    "        \n",
    "        vector = xgb_NK.predict(np.array([xcenter/416, ycenter/416, width/416, height/416]).reshape(1, 4))\n",
    "        label = np.argmax(vector)\n",
    "        \n",
    "        digit = image.crop((xcenter - width / 2 - padding, ycenter - height / 2 - padding, xcenter + width / 2 + padding, ycenter + height/2 + padding))\n",
    "        digit = remove_glare(digit)\n",
    "        digits.append(digit)\n",
    "        \n",
    "        # display(digit)\n",
    "        # print(label)\n",
    "        # print(readImage(digit))\n",
    "        va = int(readImage(digit))\n",
    "        leftout = []\n",
    "        if label == 0:\n",
    "          if read_digits['HR'] is None:\n",
    "            if (va >= 40 and va <= 220):\n",
    "              read_digits['HR'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 1:\n",
    "          if read_digits['SBP'] is None:\n",
    "              if va <= 300:\n",
    "                fin = readImage(digit)\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              elif va < 1000 :\n",
    "                fin = readImage(digit)[:2]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              elif va < 10000:\n",
    "                fin = readImage(digit)[:3]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              elif va < 100000:\n",
    "                fin = readImage(digit)[:2]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              else:\n",
    "                fin = readImage(digit)[:3]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 2:\n",
    "          if read_digits['DBP'] is None:\n",
    "            if va <= 150:\n",
    "              fin = readImage(digit)\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "            elif va < 2000:\n",
    "              fin = readImage(digit)[1:]\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "            elif va < 200000:\n",
    "              fin = readImage(digit)[-2:]\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "            else:\n",
    "              fin = readImage(digit)[-3:]\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 3:\n",
    "          if read_digits['MAP'] is None:\n",
    "            read_digits['MAP'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 4:\n",
    "          if read_digits['SPO2'] is None:\n",
    "            if(va >= 70 and va <= 100):\n",
    "                read_digits['SPO2'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        else:\n",
    "          if read_digits['RR'] is None:\n",
    "            if (va >= 5 and va <=60):\n",
    "              read_digits['RR'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        # print('\\n\\n')\n",
    "    del read_digits['MAP']\n",
    "    k = len(leftout)\n",
    "    for key in read_digits:\n",
    "      if read_digits[key] is None:\n",
    "        #print(k)\n",
    "        for i in range(k):\n",
    "          if key == 'HR':\n",
    "            if (int(leftout[i]) >= 40 and int(leftout[i]) <= 220):\n",
    "              read_digits['HR'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'SBP':\n",
    "            if (int(leftout[i]) >= 40 and int(leftout[i]) <= 240):\n",
    "              read_digits['SBP'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'DBP':\n",
    "            if (int(leftout[i]) >= 40 and int(leftout[i]) <= 140):\n",
    "              read_digits['DBP'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'RR':\n",
    "            if (int(leftout[i]) >= 5 and int(leftout[i]) <= 60):\n",
    "              read_digits['RR'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'SPO2':\n",
    "            if (int(leftout[i]) >= 70 and int(leftout[i]) <= 100):\n",
    "              read_digits['SPO2'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break     \n",
    "    keys_del = []\n",
    "    for key in read_digits:\n",
    "      if read_digits[key] is None:\n",
    "        keys_del.append(key)\n",
    "    for key in keys_del:\n",
    "      del read_digits[key]\n",
    "    return read_digits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "Wh0wBCmDeTlN",
   "metadata": {
    "id": "Wh0wBCmDeTlN"
   },
   "outputs": [],
   "source": [
    "def getDigit_BPL_EV100(image):\n",
    "    #display(image)\n",
    "    predictions = digit_segmenter(image)\n",
    "    #predictions.show()\n",
    "    df = predictions.pandas().xywh[0].sort_values(by = ['confidence'], ascending = False).head(6)\n",
    "    digits = []\n",
    "    read_digits = {\n",
    "        'HR': None, \n",
    "        'SBP': None, \n",
    "        'DBP': None, \n",
    "        'MAP': None,\n",
    "        'SPO2': None,\n",
    "        'RR': None\n",
    "    }\n",
    "    \n",
    "    for i in range(df.shape[0]):\n",
    "        xcenter = df.iloc[i]['xcenter']\n",
    "        ycenter = df.iloc[i]['ycenter']        \n",
    "        width = df.iloc[i]['width']        \n",
    "        height = df.iloc[i]['height']\n",
    "        \n",
    "        vector = xgb_EV100.predict(np.array([xcenter/416, ycenter/416, width/416, height/416]).reshape(1, 4))\n",
    "        label = np.argmax(vector)\n",
    "        \n",
    "        digit = image.crop((xcenter - width / 2 - padding, ycenter - height / 2 - padding, xcenter + width / 2 + padding, ycenter + height/2 + padding))\n",
    "        digit = remove_glare(digit)\n",
    "        digits.append(digit)\n",
    "        # display(digit)\n",
    "        # print(label)\n",
    "        # print(readImage(digit))\n",
    "        va = int(readImage(digit))\n",
    "        leftout = []\n",
    "        if label == 0:\n",
    "          if read_digits['HR'] is None:\n",
    "            if (va >= 40 and va <= 220):\n",
    "              read_digits['HR'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 1:\n",
    "          if read_digits['SBP'] is None:\n",
    "              if va <= 300:\n",
    "                fin = readImage(digit)\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              elif va < 1000 :\n",
    "                fin = readImage(digit)[:2]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              elif va < 10000:\n",
    "                fin = readImage(digit)[:3]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              elif va < 100000:\n",
    "                fin = readImage(digit)[:2]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              else:\n",
    "                fin = readImage(digit)[:3]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 2:\n",
    "          if read_digits['DBP'] is None:\n",
    "            if va <= 150:\n",
    "              fin = readImage(digit)\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "            elif va < 2000:\n",
    "              fin = readImage(digit)[1:]\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "            elif va < 200000:\n",
    "              fin = readImage(digit)[-2:]\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "            else:\n",
    "              fin = readImage(digit)[-3:]\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 3:\n",
    "          if read_digits['MAP'] is None:\n",
    "            read_digits['MAP'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 4:\n",
    "          if read_digits['SPO2'] is None:\n",
    "            if(va >= 70 and va <= 100):\n",
    "                read_digits['SPO2'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        else:\n",
    "          if read_digits['RR'] is None:\n",
    "            if (va >= 5 and va <=60):\n",
    "              read_digits['RR'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        # print('\\n\\n')\n",
    "    del read_digits['MAP']\n",
    "    k = len(leftout)\n",
    "    for key in read_digits:\n",
    "      if read_digits[key] is None:\n",
    "        #print(k)\n",
    "        for i in range(k):\n",
    "          if key == 'HR':\n",
    "            if (int(leftout[i]) >= 40 and int(leftout[i]) <= 220):\n",
    "              read_digits['HR'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'SBP':\n",
    "            if (int(leftout[i]) >= 40 and int(leftout[i]) <= 240):\n",
    "              read_digits['SBP'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'DBP':\n",
    "            if (int(leftout[i]) >= 40 and int(leftout[i]) <= 140):\n",
    "              read_digits['DBP'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'RR':\n",
    "            if (int(leftout[i]) >= 5 and int(leftout[i]) <= 60):\n",
    "              read_digits['RR'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'SPO2':\n",
    "            if (int(leftout[i]) >= 70 and int(leftout[i]) <= 100):\n",
    "              read_digits['SPO2'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break     \n",
    "    keys_del = []\n",
    "    for key in read_digits:\n",
    "      if read_digits[key] is None:\n",
    "        keys_del.append(key)\n",
    "    for key in keys_del:\n",
    "      del read_digits[key]\n",
    "    return read_digits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "Y-0WBNWZeUMn",
   "metadata": {
    "id": "Y-0WBNWZeUMn"
   },
   "outputs": [],
   "source": [
    "def getDigit_BPL_EV10(image):\n",
    "    predictions = digit_segmenter(image)\n",
    "    #predictions.show()\n",
    "    df = predictions.pandas().xywh[0].sort_values(by = ['confidence'], ascending = False).head(6)\n",
    "    digits = []\n",
    "    read_digits = {\n",
    "        'HR': None, \n",
    "        'SBP': None, \n",
    "        'DBP': None, \n",
    "        'MAP': None,\n",
    "        'SPO2': None,\n",
    "        'RR': None\n",
    "    }\n",
    "    \n",
    "    for i in range(df.shape[0]):\n",
    "        xcenter = df.iloc[i]['xcenter']\n",
    "        ycenter = df.iloc[i]['ycenter']        \n",
    "        width = df.iloc[i]['width']        \n",
    "        height = df.iloc[i]['height']\n",
    "        \n",
    "        vector = xgb_EV10.predict(np.array([xcenter/416, ycenter/416, width/416, height/416]).reshape(1, 4))\n",
    "        label = np.argmax(vector)\n",
    "        \n",
    "        digit = image.crop((xcenter - width / 2 - padding, ycenter - height / 2 - padding, xcenter + width / 2 + padding, ycenter + height/2 + padding))\n",
    "        digit = remove_glare(digit)\n",
    "        digits.append(digit)\n",
    "        \n",
    "        # display(digit)\n",
    "        # print(label)\n",
    "        # print(readImage(digit))\n",
    "        va = int(readImage(digit))\n",
    "        leftout = []\n",
    "        if label == 0:\n",
    "          if read_digits['HR'] is None:\n",
    "            if (va >= 40 and va <= 220):\n",
    "              read_digits['HR'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 1:\n",
    "          if read_digits['SBP'] is None:\n",
    "              if va <= 300:\n",
    "                fin = readImage(digit)\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              elif va < 1000 :\n",
    "                fin = readImage(digit)[:2]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              elif va < 10000:\n",
    "                fin = readImage(digit)[:3]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              elif va < 100000:\n",
    "                fin = readImage(digit)[:2]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              else:\n",
    "                fin = readImage(digit)[:3]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 2:\n",
    "          if read_digits['DBP'] is None:\n",
    "            if va <= 150:\n",
    "              fin = readImage(digit)\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "            elif va < 2000:\n",
    "              fin = readImage(digit)[1:]\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "            elif va < 200000:\n",
    "              fin = readImage(digit)[-2:]\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "            else:\n",
    "              fin = readImage(digit)[-3:]\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 3:\n",
    "          if read_digits['MAP'] is None:\n",
    "            read_digits['MAP'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 4:\n",
    "          if read_digits['SPO2'] is None:\n",
    "            if(va >= 70 and va <= 100):\n",
    "                read_digits['SPO2'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        else:\n",
    "          if read_digits['RR'] is None:\n",
    "            if (va >= 5 and va <=60):\n",
    "              read_digits['RR'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        # print('\\n\\n')\n",
    "    del read_digits['MAP']\n",
    "    k = len(leftout)\n",
    "    for key in read_digits:\n",
    "      if read_digits[key] is None:\n",
    "        #print(k)\n",
    "        for i in range(k):\n",
    "          if key == 'HR':\n",
    "            if (int(leftout[i]) >= 40 and int(leftout[i]) <= 220):\n",
    "              read_digits['HR'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'SBP':\n",
    "            if (int(leftout[i]) >= 40 and int(leftout[i]) <= 240):\n",
    "              read_digits['SBP'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'DBP':\n",
    "            if (int(leftout[i]) >= 40 and int(leftout[i]) <= 140):\n",
    "              read_digits['DBP'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'RR':\n",
    "            if (int(leftout[i]) >= 5 and int(leftout[i]) <= 60):\n",
    "              read_digits['RR'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'SPO2':\n",
    "            if (int(leftout[i]) >= 70 and int(leftout[i]) <= 100):\n",
    "              read_digits['SPO2'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break     \n",
    "    keys_del = []\n",
    "    for key in read_digits:\n",
    "      if read_digits[key] is None:\n",
    "        keys_del.append(key)\n",
    "    for key in keys_del:\n",
    "      del read_digits[key]\n",
    "    return read_digits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "OhjD1EIreUaC",
   "metadata": {
    "id": "OhjD1EIreUaC"
   },
   "outputs": [],
   "source": [
    "def getDigit_BPL_ultima(image):\n",
    "    predictions = digit_segmenter(image)\n",
    "    #predictions.show()\n",
    "    df = predictions.pandas().xywh[0].sort_values(by = ['confidence'], ascending = False).head(6)\n",
    "    digits = []\n",
    "    read_digits = {\n",
    "        'HR': None, \n",
    "        'SBP': None, \n",
    "        'DBP': None, \n",
    "        'MAP': None,\n",
    "        'SPO2': None,\n",
    "        'RR': None\n",
    "    }\n",
    "    \n",
    "    for i in range(df.shape[0]):\n",
    "        xcenter = df.iloc[i]['xcenter']\n",
    "        ycenter = df.iloc[i]['ycenter']        \n",
    "        width = df.iloc[i]['width']        \n",
    "        height = df.iloc[i]['height']\n",
    "        \n",
    "        vector = xgb_Ultima.predict(np.array([xcenter/416, ycenter/416, width/416, height/416]).reshape(1, 4))\n",
    "        label = np.argmax(vector)\n",
    "        \n",
    "        digit = image.crop((xcenter - width / 2 - padding, ycenter - height / 2 - padding, xcenter + width / 2 + padding, ycenter + height/2 + padding))\n",
    "        digit = remove_glare(digit)\n",
    "        digits.append(digit)\n",
    "        \n",
    "        #display(digit)\n",
    "        #print(label)\n",
    "        #print(readImage(digit))\n",
    "        va = int(readImage(digit))\n",
    "        leftout = []\n",
    "        if label == 0:\n",
    "          if read_digits['HR'] is None:\n",
    "            if (va >= 40 and va <= 220):\n",
    "              read_digits['HR'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 1:\n",
    "          if read_digits['SBP'] is None:\n",
    "              if va <= 300:\n",
    "                fin = readImage(digit)\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              elif va < 1000 :\n",
    "                fin = readImage(digit)[:2]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              elif va < 10000:\n",
    "                fin = readImage(digit)[:3]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              elif va < 100000:\n",
    "                fin = readImage(digit)[:2]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "              else:\n",
    "                fin = readImage(digit)[:3]\n",
    "                if (int(fin) >= 40 and int(fin) <= 240):\n",
    "                  read_digits['SBP'] = fin\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 2:\n",
    "          if read_digits['DBP'] is None:\n",
    "            if va <= 150:\n",
    "              fin = readImage(digit)\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "            elif va < 2000:\n",
    "              fin = readImage(digit)[1:]\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "            elif va < 200000:\n",
    "              fin = readImage(digit)[-2:]\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "            else:\n",
    "              fin = readImage(digit)[-3:]\n",
    "              if (int(fin) >= 40 and int(fin) <= 140):\n",
    "                read_digits['DBP'] = fin\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 3:\n",
    "          if read_digits['MAP'] is None:\n",
    "            read_digits['MAP'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        elif label == 4:\n",
    "          if read_digits['SPO2'] is None:\n",
    "            if(va >= 70 and va <= 100):\n",
    "                read_digits['SPO2'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        else:\n",
    "          if read_digits['RR'] is None:\n",
    "            if (va >= 5 and va <=60):\n",
    "              read_digits['RR'] = readImage(digit)\n",
    "          else:\n",
    "            leftout.append(readImage(digit))\n",
    "        # print('\\n\\n')\n",
    "    del read_digits['MAP']\n",
    "    k = len(leftout)\n",
    "    for key in read_digits:\n",
    "      if read_digits[key] is None:\n",
    "        #print(k)\n",
    "        for i in range(k):\n",
    "          if key == 'HR':\n",
    "            if (int(leftout[i]) >= 40 and int(leftout[i]) <= 220):\n",
    "              read_digits['HR'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'SBP':\n",
    "            if (int(leftout[i]) >= 40 and int(leftout[i]) <= 240):\n",
    "              read_digits['SBP'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'DBP':\n",
    "            if (int(leftout[i]) >= 40 and int(leftout[i]) <= 140):\n",
    "              read_digits['DBP'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'RR':\n",
    "            if (int(leftout[i]) >= 5 and int(leftout[i]) <= 60):\n",
    "              read_digits['RR'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break\n",
    "          elif key == 'SPO2':\n",
    "            if (int(leftout[i]) >= 70 and int(leftout[i]) <= 100):\n",
    "              read_digits['SPO2'] = leftout[i]\n",
    "              leftout.pop(i)\n",
    "              k -= 1\n",
    "              break     \n",
    "    keys_del = []\n",
    "    for key in read_digits:\n",
    "      if read_digits[key] is None:\n",
    "        keys_del.append(key)\n",
    "    for key in keys_del:\n",
    "      del read_digits[key]\n",
    "    return read_digits"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "408c2ab3",
   "metadata": {
    "id": "408c2ab3"
   },
   "source": [
    "# OCR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ef438ebb",
   "metadata": {
    "id": "ef438ebb"
   },
   "outputs": [],
   "source": [
    "def readImage(image):\n",
    "    result = reader.readtext(np.array(image), allowlist=\"0123456789()/\")\n",
    "    try:\n",
    "        accu = result[0][2]\n",
    "        ans = ''\n",
    "        for char in result[0][1]:\n",
    "            if char in '0123456789':\n",
    "                ans += char\n",
    "    except:\n",
    "        ans = 0\n",
    "    return ans"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "kKyZ0f9FeCv_",
   "metadata": {
    "id": "kKyZ0f9FeCv_"
   },
   "source": [
    "# HR Graph Digitization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "KzF3V8YHeBFd",
   "metadata": {
    "id": "KzF3V8YHeBFd"
   },
   "outputs": [],
   "source": [
    "def digitization(path):\n",
    "    img = getMonitorSegment(path)\n",
    "    predictions = hr_locator(img)\n",
    "    df = predictions.pandas().xywh[0]\n",
    "    df = df[df.confidence==df.confidence.max()]\n",
    "    try:\n",
    "        xcenter = df.iloc[0]['xcenter']\n",
    "        ycenter = df.iloc[0]['ycenter']\n",
    "        width = df.iloc[0]['width']\n",
    "        height = df.iloc[0]['height']\n",
    "    except:\n",
    "        return\n",
    "    \n",
    "    img = img.crop((xcenter - width / 2 - 40, ycenter - height / 2 - 40, xcenter + width / 2 + 40, ycenter + height/2 + 40))\n",
    "    # display(img)\n",
    "    img = cv2.cvtColor(np.array(img), cv2.COLOR_RGB2GRAY)\n",
    "\n",
    "    # img = cv2.imread(path, cv2.IMREAD_GRAYSCALE)  # Read input image as grayscale.\n",
    "\n",
    "    threshed = cv2.threshold(img, 0, 255, cv2.THRESH_OTSU)[1]  # threshold (binarize) the image\n",
    "\n",
    "    # Apply closing for connecting the lines\n",
    "    threshed = cv2.morphologyEx(threshed, cv2.MORPH_CLOSE, np.ones((1, 10)))\n",
    "\n",
    "    # Find contours\n",
    "    contours = cv2.findContours(threshed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)[-2]  # [-2] indexing takes return value before last (due to OpenCV compatibility issues).\n",
    "\n",
    "    img2 = cv2.cvtColor(threshed, cv2.COLOR_GRAY2BGR)  # BGR image - used for drawing\n",
    "\n",
    "    angles = []  # List of line angles.\n",
    "\n",
    "    # Iterate the contours and fit a line for each contour\n",
    "    # Remark: consider ignoring small contours\n",
    "    for c in contours:\n",
    "        vx, vy, cx, cy = cv2.fitLine(c, cv2.DIST_L2, 0, 0.01, 0.01) # Fit line\n",
    "        w = img.shape[1]\n",
    "        cv2.line(img2, (int(cx-vx*w), int(cy-vy*w)), (int(cx+vx*w), int(cy+vy*w)), (0, 255, 0))  # Draw the line for testing\n",
    "        ang = (180/np.pi)*math.atan2(vy, vx) # Compute the angle of the line.\n",
    "        angles.append(ang)\n",
    "\n",
    "    angles = np.array(angles)  # Convert angles to NumPy array.\n",
    "\n",
    "    # Remove outliers and \n",
    "    lo_val, up_val = np.percentile(angles, (40, 60))  # Get the value of lower and upper 40% of all angles (mean of only 10 angles)\n",
    "    mean_ang = np.mean(angles[np.where((angles >= lo_val) & (angles <= up_val))])\n",
    "\n",
    "    # print(f'mean_ang = {mean_ang}') \n",
    "\n",
    "    if(str(mean_ang) !=\"nan\"):\n",
    "        M = cv2.getRotationMatrix2D((img.shape[1]//2, img.shape[0]//2), mean_ang, 1)  # Get transformation matrix - for rotating by mean_ang\n",
    "\n",
    "        img = cv2.warpAffine(img, M, (img.shape[1], img.shape[0]), cv2.INTER_CUBIC) # Rotate the image\n",
    "\n",
    "    # Uncommment to Display results rotated image\n",
    "    # cv2_imshow( img)\n",
    "    # cv2.waitKey()\n",
    "    # cv2.destroyAllWindows()\n",
    "\n",
    "    # Apply thresholding to create a binary image\n",
    "    ret, thresh = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)\n",
    "    # Find contours in the binary image\n",
    "    contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n",
    "    # print(len(contours))\n",
    "    # Extract the largest contour (the graph)\n",
    "\n",
    "    graph_contour = max(contours, key=cv2.contourArea)\n",
    "\n",
    "    # Uncommment to Display results of contour in image\n",
    "    # cv2.drawContours(img, graph_contour, -1, (0, 255, 0), 2)\n",
    "    # cv2_imshow( img)\n",
    "    # cv2.waitKey(0)\n",
    "    # cv2.destroyAllWindows()\n",
    "\n",
    "    # Extract the coordinates of the graph points\n",
    "\n",
    "    graph_points = graph_contour.reshape(-1, 2)\n",
    "\n",
    "    #Uncomment to see the contour plot\n",
    "    # x = [point[0] for point in graph_points]\n",
    "    # y = [ point[1] for point in graph_points]\n",
    "    # fig, ax = plt.subplots()\n",
    "    # plt.gca().invert_yaxis()\n",
    "    # ax.plot(x, y)\n",
    "    # ax.scatter(x,y) \n",
    "    # plt.savefig(\"save.jpg\")\n",
    "    # plt.show()\n",
    "\n",
    "    points2 = graph_points\n",
    "\n",
    "    # print(graph_points)\n",
    "\n",
    "    x_coordinates = np.unique([x for x, y in points2])\n",
    "    y_coordinates = [np.mean ([y for x, y in points2 if x == x_coordinate]) for x_coordinate in x_coordinates]\n",
    "    y_coordinates = [y_coordinate for y_coordinate in y_coordinates]\n",
    "\n",
    "\n",
    "    # Show the plot\n",
    "    # plt.show()\n",
    "\n",
    "    plt.rcParams[\"figure.figsize\"] = [20, 3.50]\n",
    "    plt.rcParams[\"figure.autolayout\"] = True\n",
    "\n",
    "    fig, ax = plt.subplots()\n",
    "    plt.gca().invert_yaxis()\n",
    "    ax.plot(x_coordinates, y_coordinates)\n",
    "    ax.scatter(x_coordinates, y_coordinates)\n",
    "    ax.grid(color='black', linestyle='--', linewidth=0.5)\n",
    "\n",
    "    #To Adjust the graph\n",
    "    ax.set_xlim(0, 100)\n",
    "    ax.set_ylim(0, 100)\n",
    "    #set the aspect ratio to equal\n",
    "    ax.set_aspect('equal')\n",
    "    plt.gca().set_aspect('equal', adjustable='box')\n",
    "    # plt.savefig(\"digitized_graph.jpg\")\n",
    "    # graph = Image.open(\"/content/digitized_graph.jpg\")\n",
    "    # display(graph)\n",
    "    plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "QEFPmKLPmwsg",
   "metadata": {
    "id": "QEFPmKLPmwsg"
   },
   "source": [
    "# Inference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "xdyCm5E39kW2",
   "metadata": {
    "id": "xdyCm5E39kW2"
   },
   "outputs": [],
   "source": [
    "def inference(path):\n",
    "  monitor_segmented = getMonitorSegment(path)\n",
    "  classified_monitor = getMonitorClass(np.array(monitor_segmented))[0]\n",
    "  #print(classified_monitor)\n",
    "  if classified_monitor == 1:\n",
    "      ans = getDigit_BPL_ultima(monitor_segmented)\n",
    "  elif classified_monitor == 0:\n",
    "      ans = getDigit_BPL_EV10(monitor_segmented)\n",
    "  elif classified_monitor == 2:\n",
    "      ans = getDigit_BPL_EV100(monitor_segmented)\n",
    "  else:\n",
    "      ans = getDigit_NK(monitor_segmented)\n",
    "  return ans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "07d84747",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 1s 790ms/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'HR': '92', 'DBP': '82', 'SPO2': '98', 'RR': '26'}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inference('/home/sharchit/Documents/models2/prashant_icu_mon--1_2023_1_1_5_15_1.jpeg')"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "provenance": []
  },
  "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}